2022/10/07 07:33:06 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.7.13 (default, Mar 29 2022, 02:18:16) [GCC 7.5.0] CUDA available: True numpy_random_seed: 1992433072 GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/cache/share/cuda-11.1 NVCC: Cuda compilation tools, release 11.1, V11.1.74 GCC: gcc (GCC) 5.4.0 PyTorch: 1.10.0+cu111 PyTorch compiling details: PyTorch built with: - GCC 7.3 - 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 v2.2.3 (Git Hash 7336ca9f055cf1bfa13efb658fe15dc9b41f0740) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.1 - 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 8.0.5 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -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-sign-compare -Wno-unused-parameter -Wno-unused-variable -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 -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.10.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, TorchVision: 0.11.0+cu111 OpenCV: 4.5.5 MMEngine: 0.1.0 Runtime environment: cudnn_benchmark: False mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: None Distributed launcher: slurm Distributed training: True GPU number: 16 ------------------------------------------------------------ 2022/10/07 07:33:06 - mmengine - INFO - Config: preprocess_cfg = dict( mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], format_shape='NCTHW') 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=700, 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'), train_cfg=None, test_cfg=None) 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')) 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' train_pipeline = [ dict( type='DecordInit', io_backend='petrel', path_mapping=dict( {'data/kinetics700': 's3://openmmlab/datasets/action/Kinetics700'})), dict(type='SampleFrames', clip_len=4, frame_interval=16, 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='petrel', path_mapping=dict( {'data/kinetics700': 's3://openmmlab/datasets/action/Kinetics700'})), dict( type='SampleFrames', clip_len=4, frame_interval=16, 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='petrel', path_mapping=dict( {'data/kinetics700': 's3://openmmlab/datasets/action/Kinetics700'})), dict( type='SampleFrames', clip_len=4, frame_interval=16, 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=16, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='VideoDataset', ann_file='data/kinetics700/kinetics700_train_list_videos.txt', data_prefix=dict(video='data/kinetics700/videos_train'), pipeline=[ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/kinetics700': 's3://openmmlab/datasets/action/Kinetics700' })), dict( type='SampleFrames', clip_len=4, frame_interval=16, 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=16, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='VideoDataset', ann_file='data/kinetics700/kinetics700_val_list_videos.txt', data_prefix=dict(video='data/kinetics700/videos_val'), pipeline=[ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/kinetics700': 's3://openmmlab/datasets/action/Kinetics700' })), dict( type='SampleFrames', clip_len=4, frame_interval=16, 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=1, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='VideoDataset', ann_file='data/kinetics700/kinetics700_val_list_videos.txt', data_prefix=dict(video='data/kinetics700/videos_val'), pipeline=[ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/kinetics700': 's3://openmmlab/datasets/action/Kinetics700' })), dict( type='SampleFrames', clip_len=4, frame_interval=16, 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)) file_client_args = dict( io_backend='petrel', path_mapping=dict( {'data/kinetics700': 's3://openmmlab/datasets/action/Kinetics700'})) launcher = 'slurm' work_dir = './work_dirs/slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb' 2022/10/07 07:33:10 - mmengine - INFO - load model from: https://download.pytorch.org/models/resnet50-11ad3fa6.pth 2022/10/07 07:33:12 - mmengine - INFO - These parameters in the 2d checkpoint are not loaded: {'fc.bias', 'fc.weight'} 2022/10/07 07:33:12 - mmengine - INFO - Checkpoints will be saved to /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb by HardDiskBackend. 2022/10/07 07:34:12 - mmengine - INFO - Epoch(train) [1][20/2119] lr: 4.0000e-03 eta: 10 days, 22:01:29 time: 2.9679 data_time: 2.6650 memory: 5826 grad_norm: 1.0295 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.5472 loss: 6.5472 2022/10/07 07:34:18 - mmengine - INFO - Epoch(train) [1][40/2119] lr: 4.0000e-03 eta: 6 days, 0:45:59 time: 0.3118 data_time: 0.0257 memory: 5826 grad_norm: 0.9491 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.5542 loss: 6.5542 2022/10/07 07:34:24 - mmengine - INFO - Epoch(train) [1][60/2119] lr: 4.0000e-03 eta: 4 days, 10:28:47 time: 0.3390 data_time: 0.0233 memory: 5826 grad_norm: 0.9256 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.5340 loss: 6.5340 2022/10/07 07:34:31 - mmengine - INFO - Epoch(train) [1][80/2119] lr: 4.0000e-03 eta: 3 days, 15:01:20 time: 0.3248 data_time: 0.0267 memory: 5826 grad_norm: 0.9509 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.5318 loss: 6.5318 2022/10/07 07:34:38 - mmengine - INFO - Epoch(train) [1][100/2119] lr: 4.0000e-03 eta: 3 days, 3:33:28 time: 0.3367 data_time: 0.0261 memory: 5826 grad_norm: 1.0122 top1_acc: 0.0000 top5_acc: 0.0625 loss_cls: 6.5180 loss: 6.5180 2022/10/07 07:34:45 - mmengine - INFO - Epoch(train) [1][120/2119] lr: 4.0000e-03 eta: 2 days, 20:09:28 time: 0.3533 data_time: 0.0269 memory: 5826 grad_norm: 1.1724 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.5163 loss: 6.5163 2022/10/07 07:34:52 - mmengine - INFO - Epoch(train) [1][140/2119] lr: 4.0000e-03 eta: 2 days, 14:42:46 time: 0.3407 data_time: 0.0264 memory: 5826 grad_norm: 1.2851 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.4868 loss: 6.4868 2022/10/07 07:34:59 - mmengine - INFO - Epoch(train) [1][160/2119] lr: 4.0000e-03 eta: 2 days, 10:49:39 time: 0.3587 data_time: 0.0240 memory: 5826 grad_norm: 1.3462 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.4897 loss: 6.4897 2022/10/07 07:35:05 - mmengine - INFO - Epoch(train) [1][180/2119] lr: 4.0000e-03 eta: 2 days, 7:13:23 time: 0.2994 data_time: 0.0635 memory: 5826 grad_norm: 1.3925 top1_acc: 0.0000 top5_acc: 0.0625 loss_cls: 6.4517 loss: 6.4517 2022/10/07 07:35:11 - mmengine - INFO - Epoch(train) [1][200/2119] lr: 4.0000e-03 eta: 2 days, 4:39:38 time: 0.3358 data_time: 0.0269 memory: 5826 grad_norm: 1.4918 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 6.4250 loss: 6.4250 2022/10/07 07:35:19 - mmengine - INFO - Epoch(train) [1][220/2119] lr: 4.0000e-03 eta: 2 days, 3:00:33 time: 0.3914 data_time: 0.0235 memory: 5826 grad_norm: 1.5826 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 6.3961 loss: 6.3961 2022/10/07 07:35:26 - mmengine - INFO - Epoch(train) [1][240/2119] lr: 4.0000e-03 eta: 2 days, 1:04:45 time: 0.3160 data_time: 0.0205 memory: 5826 grad_norm: 1.7002 top1_acc: 0.0625 top5_acc: 0.0625 loss_cls: 6.3665 loss: 6.3665 2022/10/07 07:35:33 - mmengine - INFO - Epoch(train) [1][260/2119] lr: 4.0000e-03 eta: 1 day, 23:56:40 time: 0.3895 data_time: 0.0204 memory: 5826 grad_norm: 1.7998 top1_acc: 0.0625 top5_acc: 0.0625 loss_cls: 6.3268 loss: 6.3268 2022/10/07 07:35:47 - mmengine - INFO - Epoch(train) [1][280/2119] lr: 4.0000e-03 eta: 2 days, 0:42:50 time: 0.6661 data_time: 0.3059 memory: 5826 grad_norm: 1.8963 top1_acc: 0.0625 top5_acc: 0.1875 loss_cls: 6.2863 loss: 6.2863 2022/10/07 07:35:52 - mmengine - INFO - Epoch(train) [1][300/2119] lr: 4.0000e-03 eta: 1 day, 22:54:32 time: 0.2458 data_time: 0.0251 memory: 5826 grad_norm: 2.0092 top1_acc: 0.0625 top5_acc: 0.1250 loss_cls: 6.1942 loss: 6.1942 2022/10/07 07:35:58 - mmengine - INFO - Epoch(train) [1][320/2119] lr: 4.0000e-03 eta: 1 day, 21:50:25 time: 0.3385 data_time: 0.0469 memory: 5826 grad_norm: 2.1310 top1_acc: 0.0625 top5_acc: 0.1250 loss_cls: 6.0769 loss: 6.0769 2022/10/07 07:36:06 - mmengine - INFO - Epoch(train) [1][340/2119] lr: 4.0000e-03 eta: 1 day, 21:03:41 time: 0.3701 data_time: 0.0466 memory: 5826 grad_norm: 2.2491 top1_acc: 0.0625 top5_acc: 0.0625 loss_cls: 6.0261 loss: 6.0261 2022/10/07 07:36:13 - mmengine - INFO - Epoch(train) [1][360/2119] lr: 4.0000e-03 eta: 1 day, 20:13:01 time: 0.3392 data_time: 0.0151 memory: 5826 grad_norm: 2.3625 top1_acc: 0.0000 top5_acc: 0.0625 loss_cls: 5.8672 loss: 5.8672 2022/10/07 07:36:19 - mmengine - INFO - Epoch(train) [1][380/2119] lr: 4.0000e-03 eta: 1 day, 19:19:56 time: 0.3113 data_time: 0.0209 memory: 5826 grad_norm: 2.4620 top1_acc: 0.1875 top5_acc: 0.2500 loss_cls: 5.8704 loss: 5.8704 2022/10/07 07:36:27 - mmengine - INFO - Epoch(train) [1][400/2119] lr: 4.0000e-03 eta: 1 day, 18:58:16 time: 0.4101 data_time: 0.0157 memory: 5826 grad_norm: 2.5607 top1_acc: 0.0625 top5_acc: 0.1875 loss_cls: 5.8023 loss: 5.8023 2022/10/07 07:36:33 - mmengine - INFO - Epoch(train) [1][420/2119] lr: 4.0000e-03 eta: 1 day, 18:05:40 time: 0.2791 data_time: 0.0262 memory: 5826 grad_norm: 2.6462 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 5.6747 loss: 5.6747 2022/10/07 07:36:40 - mmengine - INFO - Epoch(train) [1][440/2119] lr: 4.0000e-03 eta: 1 day, 17:35:07 time: 0.3510 data_time: 0.0189 memory: 5826 grad_norm: 2.7344 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.6578 loss: 5.6578 2022/10/07 07:36:46 - mmengine - INFO - Epoch(train) [1][460/2119] lr: 4.0000e-03 eta: 1 day, 17:02:57 time: 0.3325 data_time: 0.0216 memory: 5826 grad_norm: 2.8136 top1_acc: 0.0625 top5_acc: 0.0625 loss_cls: 5.5931 loss: 5.5931 2022/10/07 07:36:54 - mmengine - INFO - Epoch(train) [1][480/2119] lr: 4.0000e-03 eta: 1 day, 16:43:20 time: 0.3773 data_time: 0.0234 memory: 5826 grad_norm: 2.8913 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 5.3699 loss: 5.3699 2022/10/07 07:37:00 - mmengine - INFO - Epoch(train) [1][500/2119] lr: 4.0000e-03 eta: 1 day, 16:15:25 time: 0.3307 data_time: 0.0242 memory: 5826 grad_norm: 2.9555 top1_acc: 0.0000 top5_acc: 0.0625 loss_cls: 5.4548 loss: 5.4548 2022/10/07 07:37:07 - mmengine - INFO - Epoch(train) [1][520/2119] lr: 4.0000e-03 eta: 1 day, 15:53:44 time: 0.3508 data_time: 0.0145 memory: 5826 grad_norm: 3.0423 top1_acc: 0.0625 top5_acc: 0.1875 loss_cls: 5.3930 loss: 5.3930 2022/10/07 07:37:13 - mmengine - INFO - Epoch(train) [1][540/2119] lr: 4.0000e-03 eta: 1 day, 15:24:09 time: 0.3024 data_time: 0.0240 memory: 5826 grad_norm: 3.0862 top1_acc: 0.0625 top5_acc: 0.1250 loss_cls: 5.2216 loss: 5.2216 2022/10/07 07:37:22 - mmengine - INFO - Epoch(train) [1][560/2119] lr: 4.0000e-03 eta: 1 day, 15:15:45 time: 0.4033 data_time: 0.0210 memory: 5826 grad_norm: 3.1512 top1_acc: 0.0000 top5_acc: 0.1875 loss_cls: 5.1812 loss: 5.1812 2022/10/07 07:37:28 - mmengine - INFO - Epoch(train) [1][580/2119] lr: 4.0000e-03 eta: 1 day, 14:52:29 time: 0.3187 data_time: 0.0217 memory: 5826 grad_norm: 3.1917 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 5.1856 loss: 5.1856 2022/10/07 07:37:34 - mmengine - INFO - Epoch(train) [1][600/2119] lr: 4.0000e-03 eta: 1 day, 14:26:19 time: 0.2935 data_time: 0.0235 memory: 5826 grad_norm: 3.2789 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 5.2139 loss: 5.2139 2022/10/07 07:37:40 - mmengine - INFO - Epoch(train) [1][620/2119] lr: 4.0000e-03 eta: 1 day, 14:08:31 time: 0.3326 data_time: 0.0201 memory: 5826 grad_norm: 3.2929 top1_acc: 0.0625 top5_acc: 0.2500 loss_cls: 4.9833 loss: 4.9833 2022/10/07 07:37:47 - mmengine - INFO - Epoch(train) [1][640/2119] lr: 4.0000e-03 eta: 1 day, 13:52:07 time: 0.3345 data_time: 0.0205 memory: 5826 grad_norm: 3.3436 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 4.9488 loss: 4.9488 2022/10/07 07:37:54 - mmengine - INFO - Epoch(train) [1][660/2119] lr: 4.0000e-03 eta: 1 day, 13:38:17 time: 0.3443 data_time: 0.0212 memory: 5826 grad_norm: 3.3829 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 4.9571 loss: 4.9571 2022/10/07 07:38:01 - mmengine - INFO - Epoch(train) [1][680/2119] lr: 4.0000e-03 eta: 1 day, 13:24:20 time: 0.3383 data_time: 0.0189 memory: 5826 grad_norm: 3.4055 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 4.8127 loss: 4.8127 2022/10/07 07:38:08 - mmengine - INFO - Epoch(train) [1][700/2119] lr: 4.0000e-03 eta: 1 day, 13:11:35 time: 0.3412 data_time: 0.0210 memory: 5826 grad_norm: 3.4863 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 4.6583 loss: 4.6583 2022/10/07 07:38:14 - mmengine - INFO - Epoch(train) [1][720/2119] lr: 4.0000e-03 eta: 1 day, 12:58:07 time: 0.3314 data_time: 0.0191 memory: 5826 grad_norm: 3.4869 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 4.7884 loss: 4.7884 2022/10/07 07:38:21 - mmengine - INFO - Epoch(train) [1][740/2119] lr: 4.0000e-03 eta: 1 day, 12:44:24 time: 0.3247 data_time: 0.0263 memory: 5826 grad_norm: 3.5523 top1_acc: 0.0000 top5_acc: 0.0625 loss_cls: 4.8004 loss: 4.8004 2022/10/07 07:38:27 - mmengine - INFO - Epoch(train) [1][760/2119] lr: 4.0000e-03 eta: 1 day, 12:29:10 time: 0.3085 data_time: 0.0210 memory: 5826 grad_norm: 3.5967 top1_acc: 0.0625 top5_acc: 0.2500 loss_cls: 4.7179 loss: 4.7179 2022/10/07 07:38:34 - mmengine - INFO - Epoch(train) [1][780/2119] lr: 4.0000e-03 eta: 1 day, 12:18:44 time: 0.3383 data_time: 0.0216 memory: 5826 grad_norm: 3.5720 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 4.7286 loss: 4.7286 2022/10/07 07:38:40 - mmengine - INFO - Epoch(train) [1][800/2119] lr: 4.0000e-03 eta: 1 day, 12:06:37 time: 0.3216 data_time: 0.0244 memory: 5826 grad_norm: 3.6145 top1_acc: 0.0625 top5_acc: 0.2500 loss_cls: 4.8643 loss: 4.8643 2022/10/07 07:38:47 - mmengine - INFO - Epoch(train) [1][820/2119] lr: 4.0000e-03 eta: 1 day, 11:57:07 time: 0.3375 data_time: 0.0212 memory: 5826 grad_norm: 3.6291 top1_acc: 0.0625 top5_acc: 0.1250 loss_cls: 4.6292 loss: 4.6292 2022/10/07 07:38:53 - mmengine - INFO - Epoch(train) [1][840/2119] lr: 4.0000e-03 eta: 1 day, 11:44:47 time: 0.3113 data_time: 0.0208 memory: 5826 grad_norm: 3.6478 top1_acc: 0.1875 top5_acc: 0.2500 loss_cls: 4.5595 loss: 4.5595 2022/10/07 07:39:01 - mmengine - INFO - Epoch(train) [1][860/2119] lr: 4.0000e-03 eta: 1 day, 11:40:46 time: 0.3744 data_time: 0.0225 memory: 5826 grad_norm: 3.6575 top1_acc: 0.0625 top5_acc: 0.3750 loss_cls: 4.4673 loss: 4.4673 2022/10/07 07:39:07 - mmengine - INFO - Epoch(train) [1][880/2119] lr: 4.0000e-03 eta: 1 day, 11:28:35 time: 0.3048 data_time: 0.0146 memory: 5826 grad_norm: 3.7066 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 4.5254 loss: 4.5254 2022/10/07 07:39:13 - mmengine - INFO - Epoch(train) [1][900/2119] lr: 4.0000e-03 eta: 1 day, 11:20:08 time: 0.3321 data_time: 0.0269 memory: 5826 grad_norm: 3.7246 top1_acc: 0.1250 top5_acc: 0.1875 loss_cls: 4.5828 loss: 4.5828 2022/10/07 07:39:20 - mmengine - INFO - Epoch(train) [1][920/2119] lr: 4.0000e-03 eta: 1 day, 11:12:08 time: 0.3329 data_time: 0.0183 memory: 5826 grad_norm: 3.7198 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 4.4870 loss: 4.4870 2022/10/07 07:39:27 - mmengine - INFO - Epoch(train) [1][940/2119] lr: 4.0000e-03 eta: 1 day, 11:08:46 time: 0.3711 data_time: 0.0212 memory: 5826 grad_norm: 3.7420 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.4104 loss: 4.4104 2022/10/07 07:39:34 - mmengine - INFO - Epoch(train) [1][960/2119] lr: 4.0000e-03 eta: 1 day, 11:01:09 time: 0.3312 data_time: 0.0243 memory: 5826 grad_norm: 3.7894 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 4.4021 loss: 4.4021 2022/10/07 07:39:40 - mmengine - INFO - Epoch(train) [1][980/2119] lr: 4.0000e-03 eta: 1 day, 10:52:39 time: 0.3202 data_time: 0.0219 memory: 5826 grad_norm: 3.7864 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 4.5085 loss: 4.5085 2022/10/07 07:39:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 07:39:46 - mmengine - INFO - Epoch(train) [1][1000/2119] lr: 4.0000e-03 eta: 1 day, 10:41:07 time: 0.2884 data_time: 0.0235 memory: 5826 grad_norm: 3.8221 top1_acc: 0.0625 top5_acc: 0.2500 loss_cls: 4.4868 loss: 4.4868 2022/10/07 07:39:54 - mmengine - INFO - Epoch(train) [1][1020/2119] lr: 4.0000e-03 eta: 1 day, 10:39:40 time: 0.3814 data_time: 0.0202 memory: 5826 grad_norm: 3.8353 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 4.4029 loss: 4.4029 2022/10/07 07:39:59 - mmengine - INFO - Epoch(train) [1][1040/2119] lr: 4.0000e-03 eta: 1 day, 10:26:48 time: 0.2683 data_time: 0.0193 memory: 5826 grad_norm: 3.8096 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 4.4248 loss: 4.4248 2022/10/07 07:40:06 - mmengine - INFO - Epoch(train) [1][1060/2119] lr: 4.0000e-03 eta: 1 day, 10:22:23 time: 0.3484 data_time: 0.0224 memory: 5826 grad_norm: 3.8315 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 4.2790 loss: 4.2790 2022/10/07 07:40:12 - mmengine - INFO - Epoch(train) [1][1080/2119] lr: 4.0000e-03 eta: 1 day, 10:13:59 time: 0.3060 data_time: 0.0210 memory: 5826 grad_norm: 3.8399 top1_acc: 0.0625 top5_acc: 0.5000 loss_cls: 4.4263 loss: 4.4263 2022/10/07 07:40:19 - mmengine - INFO - Epoch(train) [1][1100/2119] lr: 4.0000e-03 eta: 1 day, 10:07:50 time: 0.3264 data_time: 0.0221 memory: 5826 grad_norm: 3.8782 top1_acc: 0.1875 top5_acc: 0.1875 loss_cls: 4.3530 loss: 4.3530 2022/10/07 07:40:26 - mmengine - INFO - Epoch(train) [1][1120/2119] lr: 4.0000e-03 eta: 1 day, 10:06:12 time: 0.3719 data_time: 0.0246 memory: 5826 grad_norm: 3.8506 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 4.2568 loss: 4.2568 2022/10/07 07:40:32 - mmengine - INFO - Epoch(train) [1][1140/2119] lr: 4.0000e-03 eta: 1 day, 9:58:35 time: 0.3068 data_time: 0.0205 memory: 5826 grad_norm: 3.8633 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 4.3089 loss: 4.3089 2022/10/07 07:40:39 - mmengine - INFO - Epoch(train) [1][1160/2119] lr: 4.0000e-03 eta: 1 day, 9:53:51 time: 0.3356 data_time: 0.0204 memory: 5826 grad_norm: 3.8836 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 4.4678 loss: 4.4678 2022/10/07 07:40:46 - mmengine - INFO - Epoch(train) [1][1180/2119] lr: 4.0000e-03 eta: 1 day, 9:48:41 time: 0.3290 data_time: 0.0227 memory: 5826 grad_norm: 3.9237 top1_acc: 0.0000 top5_acc: 0.3125 loss_cls: 4.1997 loss: 4.1997 2022/10/07 07:40:53 - mmengine - INFO - Epoch(train) [1][1200/2119] lr: 4.0000e-03 eta: 1 day, 9:47:47 time: 0.3757 data_time: 0.0211 memory: 5826 grad_norm: 3.9358 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 4.2703 loss: 4.2703 2022/10/07 07:40:59 - mmengine - INFO - Epoch(train) [1][1220/2119] lr: 4.0000e-03 eta: 1 day, 9:40:44 time: 0.3042 data_time: 0.0198 memory: 5826 grad_norm: 3.9575 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 4.4301 loss: 4.4301 2022/10/07 07:41:05 - mmengine - INFO - Epoch(train) [1][1240/2119] lr: 4.0000e-03 eta: 1 day, 9:33:44 time: 0.3021 data_time: 0.0274 memory: 5826 grad_norm: 3.9545 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 4.1105 loss: 4.1105 2022/10/07 07:41:11 - mmengine - INFO - Epoch(train) [1][1260/2119] lr: 4.0000e-03 eta: 1 day, 9:26:36 time: 0.2981 data_time: 0.0219 memory: 5826 grad_norm: 3.9744 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 4.1810 loss: 4.1810 2022/10/07 07:41:19 - mmengine - INFO - Epoch(train) [1][1280/2119] lr: 4.0000e-03 eta: 1 day, 9:28:47 time: 0.4083 data_time: 0.0322 memory: 5826 grad_norm: 3.9495 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 4.1726 loss: 4.1726 2022/10/07 07:41:25 - mmengine - INFO - Epoch(train) [1][1300/2119] lr: 4.0000e-03 eta: 1 day, 9:21:17 time: 0.2898 data_time: 0.0267 memory: 5826 grad_norm: 3.9526 top1_acc: 0.0000 top5_acc: 0.3125 loss_cls: 4.2906 loss: 4.2906 2022/10/07 07:41:32 - mmengine - INFO - Epoch(train) [1][1320/2119] lr: 4.0000e-03 eta: 1 day, 9:19:35 time: 0.3596 data_time: 0.0214 memory: 5826 grad_norm: 3.9647 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 4.2061 loss: 4.2061 2022/10/07 07:41:39 - mmengine - INFO - Epoch(train) [1][1340/2119] lr: 4.0000e-03 eta: 1 day, 9:13:53 time: 0.3083 data_time: 0.0247 memory: 5826 grad_norm: 3.9436 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 4.0822 loss: 4.0822 2022/10/07 07:41:46 - mmengine - INFO - Epoch(train) [1][1360/2119] lr: 4.0000e-03 eta: 1 day, 9:11:44 time: 0.3518 data_time: 0.0267 memory: 5826 grad_norm: 4.0025 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 3.9312 loss: 3.9312 2022/10/07 07:41:52 - mmengine - INFO - Epoch(train) [1][1380/2119] lr: 4.0000e-03 eta: 1 day, 9:06:34 time: 0.3116 data_time: 0.0233 memory: 5826 grad_norm: 4.0085 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 4.0902 loss: 4.0902 2022/10/07 07:41:58 - mmengine - INFO - Epoch(train) [1][1400/2119] lr: 4.0000e-03 eta: 1 day, 8:59:42 time: 0.2871 data_time: 0.0272 memory: 5826 grad_norm: 3.9877 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 4.2780 loss: 4.2780 2022/10/07 07:42:04 - mmengine - INFO - Epoch(train) [1][1420/2119] lr: 4.0000e-03 eta: 1 day, 8:56:15 time: 0.3307 data_time: 0.0205 memory: 5826 grad_norm: 4.0234 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 4.2211 loss: 4.2211 2022/10/07 07:42:11 - mmengine - INFO - Epoch(train) [1][1440/2119] lr: 4.0000e-03 eta: 1 day, 8:52:45 time: 0.3286 data_time: 0.0241 memory: 5826 grad_norm: 4.0041 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 4.1240 loss: 4.1240 2022/10/07 07:42:17 - mmengine - INFO - Epoch(train) [1][1460/2119] lr: 4.0000e-03 eta: 1 day, 8:49:50 time: 0.3354 data_time: 0.0202 memory: 5826 grad_norm: 4.0233 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 4.2184 loss: 4.2184 2022/10/07 07:42:24 - mmengine - INFO - Epoch(train) [1][1480/2119] lr: 4.0000e-03 eta: 1 day, 8:47:44 time: 0.3460 data_time: 0.0178 memory: 5826 grad_norm: 3.9935 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 4.2205 loss: 4.2205 2022/10/07 07:42:31 - mmengine - INFO - Epoch(train) [1][1500/2119] lr: 4.0000e-03 eta: 1 day, 8:46:05 time: 0.3514 data_time: 0.0190 memory: 5826 grad_norm: 4.0038 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.0528 loss: 4.0528 2022/10/07 07:42:37 - mmengine - INFO - Epoch(train) [1][1520/2119] lr: 4.0000e-03 eta: 1 day, 8:41:05 time: 0.3025 data_time: 0.0246 memory: 5826 grad_norm: 4.0721 top1_acc: 0.1875 top5_acc: 0.2500 loss_cls: 4.0321 loss: 4.0321 2022/10/07 07:42:45 - mmengine - INFO - Epoch(train) [1][1540/2119] lr: 4.0000e-03 eta: 1 day, 8:41:00 time: 0.3727 data_time: 0.0220 memory: 5826 grad_norm: 4.0199 top1_acc: 0.1875 top5_acc: 0.2500 loss_cls: 4.0675 loss: 4.0675 2022/10/07 07:42:52 - mmengine - INFO - Epoch(train) [1][1560/2119] lr: 4.0000e-03 eta: 1 day, 8:40:18 time: 0.3634 data_time: 0.0198 memory: 5826 grad_norm: 4.1125 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 4.0684 loss: 4.0684 2022/10/07 07:42:59 - mmengine - INFO - Epoch(train) [1][1580/2119] lr: 4.0000e-03 eta: 1 day, 8:37:42 time: 0.3347 data_time: 0.0197 memory: 5826 grad_norm: 4.0506 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.9296 loss: 3.9296 2022/10/07 07:43:07 - mmengine - INFO - Epoch(train) [1][1600/2119] lr: 4.0000e-03 eta: 1 day, 8:38:41 time: 0.3882 data_time: 0.0196 memory: 5826 grad_norm: 4.0885 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 4.2610 loss: 4.2610 2022/10/07 07:43:12 - mmengine - INFO - Epoch(train) [1][1620/2119] lr: 4.0000e-03 eta: 1 day, 8:32:53 time: 0.2845 data_time: 0.0236 memory: 5826 grad_norm: 4.0945 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.9531 loss: 3.9531 2022/10/07 07:43:18 - mmengine - INFO - Epoch(train) [1][1640/2119] lr: 4.0000e-03 eta: 1 day, 8:28:36 time: 0.3057 data_time: 0.0207 memory: 5826 grad_norm: 4.0936 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 4.0189 loss: 4.0189 2022/10/07 07:43:25 - mmengine - INFO - Epoch(train) [1][1660/2119] lr: 4.0000e-03 eta: 1 day, 8:25:58 time: 0.3302 data_time: 0.0251 memory: 5826 grad_norm: 4.1108 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 4.2058 loss: 4.2058 2022/10/07 07:43:32 - mmengine - INFO - Epoch(train) [1][1680/2119] lr: 4.0000e-03 eta: 1 day, 8:23:51 time: 0.3376 data_time: 0.0219 memory: 5826 grad_norm: 4.1038 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.9755 loss: 3.9755 2022/10/07 07:43:39 - mmengine - INFO - Epoch(train) [1][1700/2119] lr: 4.0000e-03 eta: 1 day, 8:22:00 time: 0.3411 data_time: 0.0257 memory: 5826 grad_norm: 4.1525 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.9879 loss: 3.9879 2022/10/07 07:43:45 - mmengine - INFO - Epoch(train) [1][1720/2119] lr: 4.0000e-03 eta: 1 day, 8:17:25 time: 0.2957 data_time: 0.0208 memory: 5826 grad_norm: 4.1236 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 4.0513 loss: 4.0513 2022/10/07 07:43:52 - mmengine - INFO - Epoch(train) [1][1740/2119] lr: 4.0000e-03 eta: 1 day, 8:16:12 time: 0.3497 data_time: 0.0188 memory: 5826 grad_norm: 4.1453 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 3.9966 loss: 3.9966 2022/10/07 07:43:57 - mmengine - INFO - Epoch(train) [1][1760/2119] lr: 4.0000e-03 eta: 1 day, 8:11:46 time: 0.2955 data_time: 0.0233 memory: 5826 grad_norm: 4.1087 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.9488 loss: 3.9488 2022/10/07 07:44:04 - mmengine - INFO - Epoch(train) [1][1780/2119] lr: 4.0000e-03 eta: 1 day, 8:10:29 time: 0.3469 data_time: 0.0289 memory: 5826 grad_norm: 4.1681 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 3.9139 loss: 3.9139 2022/10/07 07:44:11 - mmengine - INFO - Epoch(train) [1][1800/2119] lr: 4.0000e-03 eta: 1 day, 8:07:51 time: 0.3236 data_time: 0.0204 memory: 5826 grad_norm: 4.1545 top1_acc: 0.0000 top5_acc: 0.4375 loss_cls: 3.9197 loss: 3.9197 2022/10/07 07:44:18 - mmengine - INFO - Epoch(train) [1][1820/2119] lr: 4.0000e-03 eta: 1 day, 8:06:13 time: 0.3399 data_time: 0.0216 memory: 5826 grad_norm: 4.1319 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 4.0824 loss: 4.0824 2022/10/07 07:44:25 - mmengine - INFO - Epoch(train) [1][1840/2119] lr: 4.0000e-03 eta: 1 day, 8:04:58 time: 0.3461 data_time: 0.0214 memory: 5826 grad_norm: 4.1335 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 4.0496 loss: 4.0496 2022/10/07 07:44:31 - mmengine - INFO - Epoch(train) [1][1860/2119] lr: 4.0000e-03 eta: 1 day, 8:03:24 time: 0.3400 data_time: 0.0180 memory: 5826 grad_norm: 4.1292 top1_acc: 0.0625 top5_acc: 0.2500 loss_cls: 3.9295 loss: 3.9295 2022/10/07 07:44:37 - mmengine - INFO - Epoch(train) [1][1880/2119] lr: 4.0000e-03 eta: 1 day, 7:59:38 time: 0.3000 data_time: 0.0244 memory: 5826 grad_norm: 4.1514 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.0299 loss: 4.0299 2022/10/07 07:44:44 - mmengine - INFO - Epoch(train) [1][1900/2119] lr: 4.0000e-03 eta: 1 day, 7:56:58 time: 0.3188 data_time: 0.0205 memory: 5826 grad_norm: 4.1449 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 4.0474 loss: 4.0474 2022/10/07 07:44:50 - mmengine - INFO - Epoch(train) [1][1920/2119] lr: 4.0000e-03 eta: 1 day, 7:54:34 time: 0.3225 data_time: 0.0227 memory: 5826 grad_norm: 4.1622 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 3.9474 loss: 3.9474 2022/10/07 07:44:57 - mmengine - INFO - Epoch(train) [1][1940/2119] lr: 4.0000e-03 eta: 1 day, 7:52:30 time: 0.3276 data_time: 0.0231 memory: 5826 grad_norm: 4.2034 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 3.7576 loss: 3.7576 2022/10/07 07:45:04 - mmengine - INFO - Epoch(train) [1][1960/2119] lr: 4.0000e-03 eta: 1 day, 7:51:06 time: 0.3395 data_time: 0.0219 memory: 5826 grad_norm: 4.2128 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.8606 loss: 3.8606 2022/10/07 07:45:11 - mmengine - INFO - Epoch(train) [1][1980/2119] lr: 4.0000e-03 eta: 1 day, 7:51:28 time: 0.3721 data_time: 0.0228 memory: 5826 grad_norm: 4.1520 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 3.8335 loss: 3.8335 2022/10/07 07:45:17 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 07:45:17 - mmengine - INFO - Epoch(train) [1][2000/2119] lr: 4.0000e-03 eta: 1 day, 7:47:53 time: 0.2973 data_time: 0.0198 memory: 5826 grad_norm: 4.1709 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.8027 loss: 3.8027 2022/10/07 07:45:24 - mmengine - INFO - Epoch(train) [1][2020/2119] lr: 4.0000e-03 eta: 1 day, 7:47:08 time: 0.3504 data_time: 0.0187 memory: 5826 grad_norm: 4.1659 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 3.9322 loss: 3.9322 2022/10/07 07:45:30 - mmengine - INFO - Epoch(train) [1][2040/2119] lr: 4.0000e-03 eta: 1 day, 7:44:01 time: 0.3042 data_time: 0.0224 memory: 5826 grad_norm: 4.1929 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 4.2104 loss: 4.2104 2022/10/07 07:45:37 - mmengine - INFO - Epoch(train) [1][2060/2119] lr: 4.0000e-03 eta: 1 day, 7:42:15 time: 0.3297 data_time: 0.0226 memory: 5826 grad_norm: 4.1732 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.9160 loss: 3.9160 2022/10/07 07:45:45 - mmengine - INFO - Epoch(train) [1][2080/2119] lr: 4.0000e-03 eta: 1 day, 7:45:29 time: 0.4275 data_time: 0.0220 memory: 5826 grad_norm: 4.1658 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.6412 loss: 3.6412 2022/10/07 07:45:52 - mmengine - INFO - Epoch(train) [1][2100/2119] lr: 4.0000e-03 eta: 1 day, 7:43:38 time: 0.3277 data_time: 0.0204 memory: 5826 grad_norm: 4.2203 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.7916 loss: 3.7916 2022/10/07 07:45:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 07:45:57 - mmengine - INFO - Epoch(train) [1][2119/2119] lr: 4.0000e-03 eta: 1 day, 7:43:38 time: 0.2601 data_time: 0.0220 memory: 5826 grad_norm: 4.2815 top1_acc: 0.1000 top5_acc: 0.3000 loss_cls: 3.9046 loss: 3.9046 2022/10/07 07:46:06 - mmengine - INFO - Epoch(train) [2][20/2119] lr: 8.0000e-03 eta: 1 day, 7:31:33 time: 0.4645 data_time: 0.1209 memory: 5826 grad_norm: 4.1868 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 3.7611 loss: 3.7611 2022/10/07 07:46:12 - mmengine - INFO - Epoch(train) [2][40/2119] lr: 8.0000e-03 eta: 1 day, 7:28:25 time: 0.2976 data_time: 0.0181 memory: 5826 grad_norm: 4.2710 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.7787 loss: 3.7787 2022/10/07 07:46:19 - mmengine - INFO - Epoch(train) [2][60/2119] lr: 8.0000e-03 eta: 1 day, 7:27:52 time: 0.3501 data_time: 0.0234 memory: 5826 grad_norm: 4.2131 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.9624 loss: 3.9624 2022/10/07 07:46:26 - mmengine - INFO - Epoch(train) [2][80/2119] lr: 8.0000e-03 eta: 1 day, 7:26:30 time: 0.3327 data_time: 0.0225 memory: 5826 grad_norm: 4.2626 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 3.6037 loss: 3.6037 2022/10/07 07:46:33 - mmengine - INFO - Epoch(train) [2][100/2119] lr: 8.0000e-03 eta: 1 day, 7:26:03 time: 0.3518 data_time: 0.0567 memory: 5826 grad_norm: 4.2723 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.8779 loss: 3.8779 2022/10/07 07:46:38 - mmengine - INFO - Epoch(train) [2][120/2119] lr: 8.0000e-03 eta: 1 day, 7:22:00 time: 0.2748 data_time: 0.0239 memory: 5826 grad_norm: 4.2654 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.8115 loss: 3.8115 2022/10/07 07:46:45 - mmengine - INFO - Epoch(train) [2][140/2119] lr: 8.0000e-03 eta: 1 day, 7:22:00 time: 0.3602 data_time: 0.0203 memory: 5826 grad_norm: 4.2388 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.8610 loss: 3.8610 2022/10/07 07:46:52 - mmengine - INFO - Epoch(train) [2][160/2119] lr: 8.0000e-03 eta: 1 day, 7:20:46 time: 0.3337 data_time: 0.0184 memory: 5826 grad_norm: 4.1793 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.6847 loss: 3.6847 2022/10/07 07:46:59 - mmengine - INFO - Epoch(train) [2][180/2119] lr: 8.0000e-03 eta: 1 day, 7:19:08 time: 0.3246 data_time: 0.0225 memory: 5826 grad_norm: 4.2072 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 4.0576 loss: 4.0576 2022/10/07 07:47:05 - mmengine - INFO - Epoch(train) [2][200/2119] lr: 8.0000e-03 eta: 1 day, 7:17:34 time: 0.3255 data_time: 0.0225 memory: 5826 grad_norm: 4.2365 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 3.8018 loss: 3.8018 2022/10/07 07:47:12 - mmengine - INFO - Epoch(train) [2][220/2119] lr: 8.0000e-03 eta: 1 day, 7:16:06 time: 0.3271 data_time: 0.0209 memory: 5826 grad_norm: 4.1813 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.7286 loss: 3.7286 2022/10/07 07:47:18 - mmengine - INFO - Epoch(train) [2][240/2119] lr: 8.0000e-03 eta: 1 day, 7:13:54 time: 0.3098 data_time: 0.0337 memory: 5826 grad_norm: 4.1862 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 3.6728 loss: 3.6728 2022/10/07 07:47:25 - mmengine - INFO - Epoch(train) [2][260/2119] lr: 8.0000e-03 eta: 1 day, 7:14:30 time: 0.3728 data_time: 0.0228 memory: 5826 grad_norm: 4.2144 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 3.5643 loss: 3.5643 2022/10/07 07:47:32 - mmengine - INFO - Epoch(train) [2][280/2119] lr: 8.0000e-03 eta: 1 day, 7:12:23 time: 0.3109 data_time: 0.0239 memory: 5826 grad_norm: 4.2109 top1_acc: 0.1250 top5_acc: 0.1875 loss_cls: 3.8448 loss: 3.8448 2022/10/07 07:47:38 - mmengine - INFO - Epoch(train) [2][300/2119] lr: 8.0000e-03 eta: 1 day, 7:10:52 time: 0.3241 data_time: 0.0173 memory: 5826 grad_norm: 4.2730 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.7964 loss: 3.7964 2022/10/07 07:47:46 - mmengine - INFO - Epoch(train) [2][320/2119] lr: 8.0000e-03 eta: 1 day, 7:11:50 time: 0.3808 data_time: 0.0213 memory: 5826 grad_norm: 4.2456 top1_acc: 0.1875 top5_acc: 0.2500 loss_cls: 3.8048 loss: 3.8048 2022/10/07 07:47:52 - mmengine - INFO - Epoch(train) [2][340/2119] lr: 8.0000e-03 eta: 1 day, 7:10:48 time: 0.3348 data_time: 0.0234 memory: 5826 grad_norm: 4.2031 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.8618 loss: 3.8618 2022/10/07 07:47:59 - mmengine - INFO - Epoch(train) [2][360/2119] lr: 8.0000e-03 eta: 1 day, 7:09:39 time: 0.3316 data_time: 0.0206 memory: 5826 grad_norm: 4.2527 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.7411 loss: 3.7411 2022/10/07 07:48:06 - mmengine - INFO - Epoch(train) [2][380/2119] lr: 8.0000e-03 eta: 1 day, 7:08:53 time: 0.3404 data_time: 0.0185 memory: 5826 grad_norm: 4.2159 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.5959 loss: 3.5959 2022/10/07 07:48:12 - mmengine - INFO - Epoch(train) [2][400/2119] lr: 8.0000e-03 eta: 1 day, 7:07:33 time: 0.3266 data_time: 0.0578 memory: 5826 grad_norm: 4.2287 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.6664 loss: 3.6664 2022/10/07 07:48:19 - mmengine - INFO - Epoch(train) [2][420/2119] lr: 8.0000e-03 eta: 1 day, 7:05:42 time: 0.3134 data_time: 0.0231 memory: 5826 grad_norm: 4.2846 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 3.5346 loss: 3.5346 2022/10/07 07:48:26 - mmengine - INFO - Epoch(train) [2][440/2119] lr: 8.0000e-03 eta: 1 day, 7:05:56 time: 0.3638 data_time: 0.0221 memory: 5826 grad_norm: 4.2423 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.8477 loss: 3.8477 2022/10/07 07:48:32 - mmengine - INFO - Epoch(train) [2][460/2119] lr: 8.0000e-03 eta: 1 day, 7:04:04 time: 0.3121 data_time: 0.0250 memory: 5826 grad_norm: 4.2312 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 3.5682 loss: 3.5682 2022/10/07 07:48:38 - mmengine - INFO - Epoch(train) [2][480/2119] lr: 8.0000e-03 eta: 1 day, 7:02:06 time: 0.3091 data_time: 0.0249 memory: 5826 grad_norm: 4.2822 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 3.9911 loss: 3.9911 2022/10/07 07:48:45 - mmengine - INFO - Epoch(train) [2][500/2119] lr: 8.0000e-03 eta: 1 day, 7:01:41 time: 0.3469 data_time: 0.0251 memory: 5826 grad_norm: 4.2644 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.5286 loss: 3.5286 2022/10/07 07:48:52 - mmengine - INFO - Epoch(train) [2][520/2119] lr: 8.0000e-03 eta: 1 day, 7:01:24 time: 0.3501 data_time: 0.0194 memory: 5826 grad_norm: 4.2288 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.5569 loss: 3.5569 2022/10/07 07:48:58 - mmengine - INFO - Epoch(train) [2][540/2119] lr: 8.0000e-03 eta: 1 day, 6:59:12 time: 0.3017 data_time: 0.0229 memory: 5826 grad_norm: 4.2768 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 3.6760 loss: 3.6760 2022/10/07 07:49:05 - mmengine - INFO - Epoch(train) [2][560/2119] lr: 8.0000e-03 eta: 1 day, 6:57:55 time: 0.3241 data_time: 0.0258 memory: 5826 grad_norm: 4.2779 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.6042 loss: 3.6042 2022/10/07 07:49:11 - mmengine - INFO - Epoch(train) [2][580/2119] lr: 8.0000e-03 eta: 1 day, 6:57:14 time: 0.3391 data_time: 0.0282 memory: 5826 grad_norm: 4.2897 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 3.7486 loss: 3.7486 2022/10/07 07:49:17 - mmengine - INFO - Epoch(train) [2][600/2119] lr: 8.0000e-03 eta: 1 day, 6:54:52 time: 0.2957 data_time: 0.0213 memory: 5826 grad_norm: 4.2450 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.5917 loss: 3.5917 2022/10/07 07:49:25 - mmengine - INFO - Epoch(train) [2][620/2119] lr: 8.0000e-03 eta: 1 day, 6:55:42 time: 0.3777 data_time: 0.0281 memory: 5826 grad_norm: 4.2528 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.7707 loss: 3.7707 2022/10/07 07:49:32 - mmengine - INFO - Epoch(train) [2][640/2119] lr: 8.0000e-03 eta: 1 day, 6:54:40 time: 0.3292 data_time: 0.0205 memory: 5826 grad_norm: 4.2841 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.6735 loss: 3.6735 2022/10/07 07:49:39 - mmengine - INFO - Epoch(train) [2][660/2119] lr: 8.0000e-03 eta: 1 day, 6:54:39 time: 0.3559 data_time: 0.0207 memory: 5826 grad_norm: 4.2668 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 3.6918 loss: 3.6918 2022/10/07 07:49:44 - mmengine - INFO - Epoch(train) [2][680/2119] lr: 8.0000e-03 eta: 1 day, 6:52:01 time: 0.2860 data_time: 0.0220 memory: 5826 grad_norm: 4.2964 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.5064 loss: 3.5064 2022/10/07 07:49:52 - mmengine - INFO - Epoch(train) [2][700/2119] lr: 8.0000e-03 eta: 1 day, 6:52:05 time: 0.3580 data_time: 0.0232 memory: 5826 grad_norm: 4.2457 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.5937 loss: 3.5937 2022/10/07 07:49:58 - mmengine - INFO - Epoch(train) [2][720/2119] lr: 8.0000e-03 eta: 1 day, 6:50:33 time: 0.3141 data_time: 0.0188 memory: 5826 grad_norm: 4.2958 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.8644 loss: 3.8644 2022/10/07 07:50:05 - mmengine - INFO - Epoch(train) [2][740/2119] lr: 8.0000e-03 eta: 1 day, 6:50:04 time: 0.3427 data_time: 0.0240 memory: 5826 grad_norm: 4.2900 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 3.6883 loss: 3.6883 2022/10/07 07:50:11 - mmengine - INFO - Epoch(train) [2][760/2119] lr: 8.0000e-03 eta: 1 day, 6:48:29 time: 0.3124 data_time: 0.0216 memory: 5826 grad_norm: 4.3074 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.5975 loss: 3.5975 2022/10/07 07:50:18 - mmengine - INFO - Epoch(train) [2][780/2119] lr: 8.0000e-03 eta: 1 day, 6:48:17 time: 0.3494 data_time: 0.0171 memory: 5826 grad_norm: 4.3986 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.6461 loss: 3.6461 2022/10/07 07:50:24 - mmengine - INFO - Epoch(train) [2][800/2119] lr: 8.0000e-03 eta: 1 day, 6:46:44 time: 0.3124 data_time: 0.0196 memory: 5826 grad_norm: 4.3599 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 3.4952 loss: 3.4952 2022/10/07 07:50:31 - mmengine - INFO - Epoch(train) [2][820/2119] lr: 8.0000e-03 eta: 1 day, 6:45:51 time: 0.3304 data_time: 0.0250 memory: 5826 grad_norm: 4.2793 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.5483 loss: 3.5483 2022/10/07 07:50:37 - mmengine - INFO - Epoch(train) [2][840/2119] lr: 8.0000e-03 eta: 1 day, 6:44:34 time: 0.3187 data_time: 0.0238 memory: 5826 grad_norm: 4.2672 top1_acc: 0.2500 top5_acc: 0.3125 loss_cls: 3.6236 loss: 3.6236 2022/10/07 07:50:44 - mmengine - INFO - Epoch(train) [2][860/2119] lr: 8.0000e-03 eta: 1 day, 6:44:48 time: 0.3618 data_time: 0.0159 memory: 5826 grad_norm: 4.2491 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.7560 loss: 3.7560 2022/10/07 07:50:51 - mmengine - INFO - Epoch(train) [2][880/2119] lr: 8.0000e-03 eta: 1 day, 6:44:15 time: 0.3388 data_time: 0.0186 memory: 5826 grad_norm: 4.3002 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.6121 loss: 3.6121 2022/10/07 07:50:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 07:50:58 - mmengine - INFO - Epoch(train) [2][900/2119] lr: 8.0000e-03 eta: 1 day, 6:43:56 time: 0.3461 data_time: 0.0180 memory: 5826 grad_norm: 4.2935 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.5792 loss: 3.5792 2022/10/07 07:51:04 - mmengine - INFO - Epoch(train) [2][920/2119] lr: 8.0000e-03 eta: 1 day, 6:42:08 time: 0.3026 data_time: 0.0199 memory: 5826 grad_norm: 4.3457 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.7375 loss: 3.7375 2022/10/07 07:51:10 - mmengine - INFO - Epoch(train) [2][940/2119] lr: 8.0000e-03 eta: 1 day, 6:40:06 time: 0.2951 data_time: 0.0213 memory: 5826 grad_norm: 4.3001 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.6413 loss: 3.6413 2022/10/07 07:51:17 - mmengine - INFO - Epoch(train) [2][960/2119] lr: 8.0000e-03 eta: 1 day, 6:39:19 time: 0.3314 data_time: 0.0214 memory: 5826 grad_norm: 4.2969 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.5021 loss: 3.5021 2022/10/07 07:51:24 - mmengine - INFO - Epoch(train) [2][980/2119] lr: 8.0000e-03 eta: 1 day, 6:39:34 time: 0.3614 data_time: 0.0218 memory: 5826 grad_norm: 4.3209 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.5032 loss: 3.5032 2022/10/07 07:51:30 - mmengine - INFO - Epoch(train) [2][1000/2119] lr: 8.0000e-03 eta: 1 day, 6:37:38 time: 0.2966 data_time: 0.0141 memory: 5826 grad_norm: 4.2813 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.5639 loss: 3.5639 2022/10/07 07:51:37 - mmengine - INFO - Epoch(train) [2][1020/2119] lr: 8.0000e-03 eta: 1 day, 6:37:07 time: 0.3382 data_time: 0.0235 memory: 5826 grad_norm: 4.3135 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.5831 loss: 3.5831 2022/10/07 07:51:43 - mmengine - INFO - Epoch(train) [2][1040/2119] lr: 8.0000e-03 eta: 1 day, 6:36:45 time: 0.3426 data_time: 0.0192 memory: 5826 grad_norm: 4.3505 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.4729 loss: 3.4729 2022/10/07 07:51:50 - mmengine - INFO - Epoch(train) [2][1060/2119] lr: 8.0000e-03 eta: 1 day, 6:35:29 time: 0.3158 data_time: 0.0204 memory: 5826 grad_norm: 4.3308 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 3.5919 loss: 3.5919 2022/10/07 07:51:57 - mmengine - INFO - Epoch(train) [2][1080/2119] lr: 8.0000e-03 eta: 1 day, 6:35:18 time: 0.3475 data_time: 0.0234 memory: 5826 grad_norm: 4.3277 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.3987 loss: 3.3987 2022/10/07 07:52:03 - mmengine - INFO - Epoch(train) [2][1100/2119] lr: 8.0000e-03 eta: 1 day, 6:34:32 time: 0.3301 data_time: 0.0240 memory: 5826 grad_norm: 4.3183 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.4488 loss: 3.4488 2022/10/07 07:52:10 - mmengine - INFO - Epoch(train) [2][1120/2119] lr: 8.0000e-03 eta: 1 day, 6:33:38 time: 0.3259 data_time: 0.0174 memory: 5826 grad_norm: 4.3090 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.4764 loss: 3.4764 2022/10/07 07:52:16 - mmengine - INFO - Epoch(train) [2][1140/2119] lr: 8.0000e-03 eta: 1 day, 6:32:39 time: 0.3224 data_time: 0.0199 memory: 5826 grad_norm: 4.3309 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.2608 loss: 3.2608 2022/10/07 07:52:23 - mmengine - INFO - Epoch(train) [2][1160/2119] lr: 8.0000e-03 eta: 1 day, 6:32:46 time: 0.3572 data_time: 0.0196 memory: 5826 grad_norm: 4.3511 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.4613 loss: 3.4613 2022/10/07 07:52:30 - mmengine - INFO - Epoch(train) [2][1180/2119] lr: 8.0000e-03 eta: 1 day, 6:31:42 time: 0.3194 data_time: 0.0218 memory: 5826 grad_norm: 4.3258 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.4495 loss: 3.4495 2022/10/07 07:52:36 - mmengine - INFO - Epoch(train) [2][1200/2119] lr: 8.0000e-03 eta: 1 day, 6:30:39 time: 0.3199 data_time: 0.0210 memory: 5826 grad_norm: 4.3378 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.6281 loss: 3.6281 2022/10/07 07:52:43 - mmengine - INFO - Epoch(train) [2][1220/2119] lr: 8.0000e-03 eta: 1 day, 6:29:38 time: 0.3208 data_time: 0.0211 memory: 5826 grad_norm: 4.3048 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 3.5105 loss: 3.5105 2022/10/07 07:52:49 - mmengine - INFO - Epoch(train) [2][1240/2119] lr: 8.0000e-03 eta: 1 day, 6:27:51 time: 0.2956 data_time: 0.0232 memory: 5826 grad_norm: 4.3437 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.5181 loss: 3.5181 2022/10/07 07:52:56 - mmengine - INFO - Epoch(train) [2][1260/2119] lr: 8.0000e-03 eta: 1 day, 6:27:58 time: 0.3559 data_time: 0.0206 memory: 5826 grad_norm: 4.3840 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.5892 loss: 3.5892 2022/10/07 07:53:01 - mmengine - INFO - Epoch(train) [2][1280/2119] lr: 8.0000e-03 eta: 1 day, 6:26:04 time: 0.2910 data_time: 0.0198 memory: 5826 grad_norm: 4.3510 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.3899 loss: 3.3899 2022/10/07 07:53:09 - mmengine - INFO - Epoch(train) [2][1300/2119] lr: 8.0000e-03 eta: 1 day, 6:26:22 time: 0.3620 data_time: 0.0233 memory: 5826 grad_norm: 4.3272 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 3.5145 loss: 3.5145 2022/10/07 07:53:16 - mmengine - INFO - Epoch(train) [2][1320/2119] lr: 8.0000e-03 eta: 1 day, 6:26:22 time: 0.3525 data_time: 0.0190 memory: 5826 grad_norm: 4.3467 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.4979 loss: 3.4979 2022/10/07 07:53:22 - mmengine - INFO - Epoch(train) [2][1340/2119] lr: 8.0000e-03 eta: 1 day, 6:25:01 time: 0.3077 data_time: 0.0215 memory: 5826 grad_norm: 4.3489 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.7032 loss: 3.7032 2022/10/07 07:53:28 - mmengine - INFO - Epoch(train) [2][1360/2119] lr: 8.0000e-03 eta: 1 day, 6:23:55 time: 0.3159 data_time: 0.0239 memory: 5826 grad_norm: 4.3148 top1_acc: 0.1875 top5_acc: 0.1875 loss_cls: 3.5453 loss: 3.5453 2022/10/07 07:53:35 - mmengine - INFO - Epoch(train) [2][1380/2119] lr: 8.0000e-03 eta: 1 day, 6:23:39 time: 0.3426 data_time: 0.0196 memory: 5826 grad_norm: 4.3129 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.4092 loss: 3.4092 2022/10/07 07:53:42 - mmengine - INFO - Epoch(train) [2][1400/2119] lr: 8.0000e-03 eta: 1 day, 6:23:00 time: 0.3302 data_time: 0.0233 memory: 5826 grad_norm: 4.2614 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 3.2891 loss: 3.2891 2022/10/07 07:53:48 - mmengine - INFO - Epoch(train) [2][1420/2119] lr: 8.0000e-03 eta: 1 day, 6:22:03 time: 0.3200 data_time: 0.0191 memory: 5826 grad_norm: 4.3016 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.2466 loss: 3.2466 2022/10/07 07:53:55 - mmengine - INFO - Epoch(train) [2][1440/2119] lr: 8.0000e-03 eta: 1 day, 6:21:15 time: 0.3248 data_time: 0.0180 memory: 5826 grad_norm: 4.3207 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 3.5701 loss: 3.5701 2022/10/07 07:54:01 - mmengine - INFO - Epoch(train) [2][1460/2119] lr: 8.0000e-03 eta: 1 day, 6:20:40 time: 0.3312 data_time: 0.0235 memory: 5826 grad_norm: 4.3722 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.4220 loss: 3.4220 2022/10/07 07:54:08 - mmengine - INFO - Epoch(train) [2][1480/2119] lr: 8.0000e-03 eta: 1 day, 6:20:09 time: 0.3340 data_time: 0.0202 memory: 5826 grad_norm: 4.2860 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.4511 loss: 3.4511 2022/10/07 07:54:14 - mmengine - INFO - Epoch(train) [2][1500/2119] lr: 8.0000e-03 eta: 1 day, 6:18:08 time: 0.2819 data_time: 0.0240 memory: 5826 grad_norm: 4.2756 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.7209 loss: 3.7209 2022/10/07 07:54:20 - mmengine - INFO - Epoch(train) [2][1520/2119] lr: 8.0000e-03 eta: 1 day, 6:17:46 time: 0.3387 data_time: 0.0208 memory: 5826 grad_norm: 4.3395 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.5037 loss: 3.5037 2022/10/07 07:54:27 - mmengine - INFO - Epoch(train) [2][1540/2119] lr: 8.0000e-03 eta: 1 day, 6:17:33 time: 0.3435 data_time: 0.0235 memory: 5826 grad_norm: 4.3369 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 3.5478 loss: 3.5478 2022/10/07 07:54:35 - mmengine - INFO - Epoch(train) [2][1560/2119] lr: 8.0000e-03 eta: 1 day, 6:18:28 time: 0.3835 data_time: 0.0187 memory: 5826 grad_norm: 4.3371 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.3997 loss: 3.3997 2022/10/07 07:54:41 - mmengine - INFO - Epoch(train) [2][1580/2119] lr: 8.0000e-03 eta: 1 day, 6:17:29 time: 0.3162 data_time: 0.0225 memory: 5826 grad_norm: 4.3400 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.6222 loss: 3.6222 2022/10/07 07:54:48 - mmengine - INFO - Epoch(train) [2][1600/2119] lr: 8.0000e-03 eta: 1 day, 6:17:24 time: 0.3482 data_time: 0.0169 memory: 5826 grad_norm: 4.2912 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.5432 loss: 3.5432 2022/10/07 07:54:55 - mmengine - INFO - Epoch(train) [2][1620/2119] lr: 8.0000e-03 eta: 1 day, 6:17:05 time: 0.3402 data_time: 0.0252 memory: 5826 grad_norm: 4.3314 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.2248 loss: 3.2248 2022/10/07 07:55:01 - mmengine - INFO - Epoch(train) [2][1640/2119] lr: 8.0000e-03 eta: 1 day, 6:16:17 time: 0.3226 data_time: 0.0241 memory: 5826 grad_norm: 4.3276 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.6117 loss: 3.6117 2022/10/07 07:55:07 - mmengine - INFO - Epoch(train) [2][1660/2119] lr: 8.0000e-03 eta: 1 day, 6:14:27 time: 0.2851 data_time: 0.0281 memory: 5826 grad_norm: 4.3596 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.3833 loss: 3.3833 2022/10/07 07:55:14 - mmengine - INFO - Epoch(train) [2][1680/2119] lr: 8.0000e-03 eta: 1 day, 6:14:01 time: 0.3345 data_time: 0.0198 memory: 5826 grad_norm: 4.3113 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.3153 loss: 3.3153 2022/10/07 07:55:21 - mmengine - INFO - Epoch(train) [2][1700/2119] lr: 8.0000e-03 eta: 1 day, 6:14:23 time: 0.3647 data_time: 0.0237 memory: 5826 grad_norm: 4.3497 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.4249 loss: 3.4249 2022/10/07 07:55:27 - mmengine - INFO - Epoch(train) [2][1720/2119] lr: 8.0000e-03 eta: 1 day, 6:13:10 time: 0.3063 data_time: 0.0196 memory: 5826 grad_norm: 4.3367 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.4901 loss: 3.4901 2022/10/07 07:55:34 - mmengine - INFO - Epoch(train) [2][1740/2119] lr: 8.0000e-03 eta: 1 day, 6:12:23 time: 0.3218 data_time: 0.0229 memory: 5826 grad_norm: 4.3369 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.4863 loss: 3.4863 2022/10/07 07:55:40 - mmengine - INFO - Epoch(train) [2][1760/2119] lr: 8.0000e-03 eta: 1 day, 6:11:43 time: 0.3258 data_time: 0.0197 memory: 5826 grad_norm: 4.3516 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.2535 loss: 3.2535 2022/10/07 07:55:47 - mmengine - INFO - Epoch(train) [2][1780/2119] lr: 8.0000e-03 eta: 1 day, 6:11:16 time: 0.3336 data_time: 0.0232 memory: 5826 grad_norm: 4.3512 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.4124 loss: 3.4124 2022/10/07 07:55:53 - mmengine - INFO - Epoch(train) [2][1800/2119] lr: 8.0000e-03 eta: 1 day, 6:09:59 time: 0.3023 data_time: 0.0230 memory: 5826 grad_norm: 4.3351 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.3048 loss: 3.3048 2022/10/07 07:56:00 - mmengine - INFO - Epoch(train) [2][1820/2119] lr: 8.0000e-03 eta: 1 day, 6:10:04 time: 0.3538 data_time: 0.0272 memory: 5826 grad_norm: 4.4170 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.3469 loss: 3.3469 2022/10/07 07:56:07 - mmengine - INFO - Epoch(train) [2][1840/2119] lr: 8.0000e-03 eta: 1 day, 6:09:42 time: 0.3362 data_time: 0.0204 memory: 5826 grad_norm: 4.3361 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.3307 loss: 3.3307 2022/10/07 07:56:13 - mmengine - INFO - Epoch(train) [2][1860/2119] lr: 8.0000e-03 eta: 1 day, 6:08:57 time: 0.3218 data_time: 0.0212 memory: 5826 grad_norm: 4.3883 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 3.3891 loss: 3.3891 2022/10/07 07:56:19 - mmengine - INFO - Epoch(train) [2][1880/2119] lr: 8.0000e-03 eta: 1 day, 6:07:46 time: 0.3052 data_time: 0.0230 memory: 5826 grad_norm: 4.3833 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.4973 loss: 3.4973 2022/10/07 07:56:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 07:56:27 - mmengine - INFO - Epoch(train) [2][1900/2119] lr: 8.0000e-03 eta: 1 day, 6:08:31 time: 0.3786 data_time: 0.0451 memory: 5826 grad_norm: 4.3823 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.3521 loss: 3.3521 2022/10/07 07:56:32 - mmengine - INFO - Epoch(train) [2][1920/2119] lr: 8.0000e-03 eta: 1 day, 6:06:50 time: 0.2852 data_time: 0.0209 memory: 5826 grad_norm: 4.3045 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.4188 loss: 3.4188 2022/10/07 07:56:39 - mmengine - INFO - Epoch(train) [2][1940/2119] lr: 8.0000e-03 eta: 1 day, 6:06:49 time: 0.3494 data_time: 0.0189 memory: 5826 grad_norm: 4.2970 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.2393 loss: 3.2393 2022/10/07 07:56:46 - mmengine - INFO - Epoch(train) [2][1960/2119] lr: 8.0000e-03 eta: 1 day, 6:06:48 time: 0.3491 data_time: 0.0212 memory: 5826 grad_norm: 4.3146 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.5026 loss: 3.5026 2022/10/07 07:56:54 - mmengine - INFO - Epoch(train) [2][1980/2119] lr: 8.0000e-03 eta: 1 day, 6:07:03 time: 0.3603 data_time: 0.0195 memory: 5826 grad_norm: 4.3288 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.5030 loss: 3.5030 2022/10/07 07:56:59 - mmengine - INFO - Epoch(train) [2][2000/2119] lr: 8.0000e-03 eta: 1 day, 6:05:17 time: 0.2805 data_time: 0.0198 memory: 5826 grad_norm: 4.3903 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.1326 loss: 3.1326 2022/10/07 07:57:07 - mmengine - INFO - Epoch(train) [2][2020/2119] lr: 8.0000e-03 eta: 1 day, 6:05:40 time: 0.3647 data_time: 0.0245 memory: 5826 grad_norm: 4.3423 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 3.4057 loss: 3.4057 2022/10/07 07:57:13 - mmengine - INFO - Epoch(train) [2][2040/2119] lr: 8.0000e-03 eta: 1 day, 6:04:48 time: 0.3160 data_time: 0.0211 memory: 5826 grad_norm: 4.3277 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 3.2233 loss: 3.2233 2022/10/07 07:57:20 - mmengine - INFO - Epoch(train) [2][2060/2119] lr: 8.0000e-03 eta: 1 day, 6:04:23 time: 0.3331 data_time: 0.0216 memory: 5826 grad_norm: 4.3239 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.2569 loss: 3.2569 2022/10/07 07:57:27 - mmengine - INFO - Epoch(train) [2][2080/2119] lr: 8.0000e-03 eta: 1 day, 6:05:04 time: 0.3767 data_time: 0.0194 memory: 5826 grad_norm: 4.3655 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.3722 loss: 3.3722 2022/10/07 07:57:33 - mmengine - INFO - Epoch(train) [2][2100/2119] lr: 8.0000e-03 eta: 1 day, 6:03:53 time: 0.3023 data_time: 0.0259 memory: 5826 grad_norm: 4.3199 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.3851 loss: 3.3851 2022/10/07 07:57:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 07:57:38 - mmengine - INFO - Epoch(train) [2][2119/2119] lr: 8.0000e-03 eta: 1 day, 6:03:53 time: 0.2596 data_time: 0.0172 memory: 5826 grad_norm: 4.4074 top1_acc: 0.6000 top5_acc: 0.7000 loss_cls: 3.4903 loss: 3.4903 2022/10/07 07:57:47 - mmengine - INFO - Epoch(train) [3][20/2119] lr: 1.2000e-02 eta: 1 day, 5:58:23 time: 0.4583 data_time: 0.1199 memory: 5826 grad_norm: 4.3462 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.1091 loss: 3.1091 2022/10/07 07:57:54 - mmengine - INFO - Epoch(train) [3][40/2119] lr: 1.2000e-02 eta: 1 day, 5:57:50 time: 0.3265 data_time: 0.0207 memory: 5826 grad_norm: 4.3851 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 3.5120 loss: 3.5120 2022/10/07 07:58:01 - mmengine - INFO - Epoch(train) [3][60/2119] lr: 1.2000e-02 eta: 1 day, 5:57:56 time: 0.3525 data_time: 0.0252 memory: 5826 grad_norm: 4.3698 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 3.3590 loss: 3.3590 2022/10/07 07:58:07 - mmengine - INFO - Epoch(train) [3][80/2119] lr: 1.2000e-02 eta: 1 day, 5:56:59 time: 0.3096 data_time: 0.0196 memory: 5826 grad_norm: 4.2780 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.3892 loss: 3.3892 2022/10/07 07:58:14 - mmengine - INFO - Epoch(train) [3][100/2119] lr: 1.2000e-02 eta: 1 day, 5:56:44 time: 0.3383 data_time: 0.0229 memory: 5826 grad_norm: 4.2724 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.5046 loss: 3.5046 2022/10/07 07:58:20 - mmengine - INFO - Epoch(train) [3][120/2119] lr: 1.2000e-02 eta: 1 day, 5:55:54 time: 0.3140 data_time: 0.0210 memory: 5826 grad_norm: 4.2696 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.2326 loss: 3.2326 2022/10/07 07:58:27 - mmengine - INFO - Epoch(train) [3][140/2119] lr: 1.2000e-02 eta: 1 day, 5:56:09 time: 0.3585 data_time: 0.0163 memory: 5826 grad_norm: 4.2721 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2418 loss: 3.2418 2022/10/07 07:58:34 - mmengine - INFO - Epoch(train) [3][160/2119] lr: 1.2000e-02 eta: 1 day, 5:55:25 time: 0.3181 data_time: 0.0216 memory: 5826 grad_norm: 4.1781 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.3723 loss: 3.3723 2022/10/07 07:58:41 - mmengine - INFO - Epoch(train) [3][180/2119] lr: 1.2000e-02 eta: 1 day, 5:55:34 time: 0.3547 data_time: 0.0214 memory: 5826 grad_norm: 4.2974 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.3100 loss: 3.3100 2022/10/07 07:58:47 - mmengine - INFO - Epoch(train) [3][200/2119] lr: 1.2000e-02 eta: 1 day, 5:55:07 time: 0.3298 data_time: 0.0233 memory: 5826 grad_norm: 4.2472 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.4023 loss: 3.4023 2022/10/07 07:58:54 - mmengine - INFO - Epoch(train) [3][220/2119] lr: 1.2000e-02 eta: 1 day, 5:55:06 time: 0.3475 data_time: 0.0247 memory: 5826 grad_norm: 4.2995 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.3537 loss: 3.3537 2022/10/07 07:59:00 - mmengine - INFO - Epoch(train) [3][240/2119] lr: 1.2000e-02 eta: 1 day, 5:54:05 time: 0.3049 data_time: 0.0197 memory: 5826 grad_norm: 4.3813 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.1898 loss: 3.1898 2022/10/07 07:59:07 - mmengine - INFO - Epoch(train) [3][260/2119] lr: 1.2000e-02 eta: 1 day, 5:53:42 time: 0.3325 data_time: 0.0185 memory: 5826 grad_norm: 4.2217 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.3545 loss: 3.3545 2022/10/07 07:59:13 - mmengine - INFO - Epoch(train) [3][280/2119] lr: 1.2000e-02 eta: 1 day, 5:52:32 time: 0.2977 data_time: 0.0247 memory: 5826 grad_norm: 4.2848 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.1526 loss: 3.1526 2022/10/07 07:59:20 - mmengine - INFO - Epoch(train) [3][300/2119] lr: 1.2000e-02 eta: 1 day, 5:52:22 time: 0.3413 data_time: 0.0199 memory: 5826 grad_norm: 4.2320 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.5485 loss: 3.5485 2022/10/07 07:59:27 - mmengine - INFO - Epoch(train) [3][320/2119] lr: 1.2000e-02 eta: 1 day, 5:52:18 time: 0.3449 data_time: 0.0192 memory: 5826 grad_norm: 4.1742 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.3732 loss: 3.3732 2022/10/07 07:59:34 - mmengine - INFO - Epoch(train) [3][340/2119] lr: 1.2000e-02 eta: 1 day, 5:52:42 time: 0.3661 data_time: 0.0219 memory: 5826 grad_norm: 4.2644 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 3.4549 loss: 3.4549 2022/10/07 07:59:40 - mmengine - INFO - Epoch(train) [3][360/2119] lr: 1.2000e-02 eta: 1 day, 5:51:21 time: 0.2886 data_time: 0.0243 memory: 5826 grad_norm: 4.2121 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.3187 loss: 3.3187 2022/10/07 07:59:46 - mmengine - INFO - Epoch(train) [3][380/2119] lr: 1.2000e-02 eta: 1 day, 5:50:46 time: 0.3223 data_time: 0.0206 memory: 5826 grad_norm: 4.3197 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.3245 loss: 3.3245 2022/10/07 07:59:52 - mmengine - INFO - Epoch(train) [3][400/2119] lr: 1.2000e-02 eta: 1 day, 5:49:14 time: 0.2803 data_time: 0.0197 memory: 5826 grad_norm: 4.3132 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.4634 loss: 3.4634 2022/10/07 07:59:59 - mmengine - INFO - Epoch(train) [3][420/2119] lr: 1.2000e-02 eta: 1 day, 5:49:09 time: 0.3443 data_time: 0.0270 memory: 5826 grad_norm: 4.2690 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.4823 loss: 3.4823 2022/10/07 08:00:06 - mmengine - INFO - Epoch(train) [3][440/2119] lr: 1.2000e-02 eta: 1 day, 5:49:14 time: 0.3512 data_time: 0.0220 memory: 5826 grad_norm: 4.2421 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.1905 loss: 3.1905 2022/10/07 08:00:12 - mmengine - INFO - Epoch(train) [3][460/2119] lr: 1.2000e-02 eta: 1 day, 5:48:39 time: 0.3221 data_time: 0.0244 memory: 5826 grad_norm: 4.2414 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.3933 loss: 3.3933 2022/10/07 08:00:19 - mmengine - INFO - Epoch(train) [3][480/2119] lr: 1.2000e-02 eta: 1 day, 5:48:12 time: 0.3272 data_time: 0.0219 memory: 5826 grad_norm: 4.3090 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.5205 loss: 3.5205 2022/10/07 08:00:25 - mmengine - INFO - Epoch(train) [3][500/2119] lr: 1.2000e-02 eta: 1 day, 5:47:38 time: 0.3217 data_time: 0.0224 memory: 5826 grad_norm: 4.2899 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.4529 loss: 3.4529 2022/10/07 08:00:32 - mmengine - INFO - Epoch(train) [3][520/2119] lr: 1.2000e-02 eta: 1 day, 5:46:55 time: 0.3153 data_time: 0.0182 memory: 5826 grad_norm: 4.2198 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.2582 loss: 3.2582 2022/10/07 08:00:39 - mmengine - INFO - Epoch(train) [3][540/2119] lr: 1.2000e-02 eta: 1 day, 5:47:22 time: 0.3686 data_time: 0.0228 memory: 5826 grad_norm: 4.2329 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.1402 loss: 3.1402 2022/10/07 08:00:45 - mmengine - INFO - Epoch(train) [3][560/2119] lr: 1.2000e-02 eta: 1 day, 5:46:55 time: 0.3268 data_time: 0.0214 memory: 5826 grad_norm: 4.2499 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.2264 loss: 3.2264 2022/10/07 08:00:53 - mmengine - INFO - Epoch(train) [3][580/2119] lr: 1.2000e-02 eta: 1 day, 5:47:12 time: 0.3609 data_time: 0.0232 memory: 5826 grad_norm: 4.1869 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.1816 loss: 3.1816 2022/10/07 08:00:59 - mmengine - INFO - Epoch(train) [3][600/2119] lr: 1.2000e-02 eta: 1 day, 5:46:38 time: 0.3213 data_time: 0.0275 memory: 5826 grad_norm: 4.2573 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.2822 loss: 3.2822 2022/10/07 08:01:06 - mmengine - INFO - Epoch(train) [3][620/2119] lr: 1.2000e-02 eta: 1 day, 5:46:27 time: 0.3392 data_time: 0.0299 memory: 5826 grad_norm: 4.2494 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 3.3288 loss: 3.3288 2022/10/07 08:01:12 - mmengine - INFO - Epoch(train) [3][640/2119] lr: 1.2000e-02 eta: 1 day, 5:45:52 time: 0.3209 data_time: 0.0220 memory: 5826 grad_norm: 4.2626 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 3.4662 loss: 3.4662 2022/10/07 08:01:19 - mmengine - INFO - Epoch(train) [3][660/2119] lr: 1.2000e-02 eta: 1 day, 5:45:42 time: 0.3401 data_time: 0.0189 memory: 5826 grad_norm: 4.2351 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.4067 loss: 3.4067 2022/10/07 08:01:26 - mmengine - INFO - Epoch(train) [3][680/2119] lr: 1.2000e-02 eta: 1 day, 5:45:42 time: 0.3473 data_time: 0.0219 memory: 5826 grad_norm: 4.2830 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.2645 loss: 3.2645 2022/10/07 08:01:32 - mmengine - INFO - Epoch(train) [3][700/2119] lr: 1.2000e-02 eta: 1 day, 5:44:36 time: 0.2957 data_time: 0.0248 memory: 5826 grad_norm: 4.2163 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.3699 loss: 3.3699 2022/10/07 08:01:39 - mmengine - INFO - Epoch(train) [3][720/2119] lr: 1.2000e-02 eta: 1 day, 5:44:24 time: 0.3381 data_time: 0.0340 memory: 5826 grad_norm: 4.2392 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.6630 loss: 3.6630 2022/10/07 08:01:45 - mmengine - INFO - Epoch(train) [3][740/2119] lr: 1.2000e-02 eta: 1 day, 5:44:11 time: 0.3373 data_time: 0.0213 memory: 5826 grad_norm: 4.2313 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.4149 loss: 3.4149 2022/10/07 08:01:52 - mmengine - INFO - Epoch(train) [3][760/2119] lr: 1.2000e-02 eta: 1 day, 5:43:16 time: 0.3040 data_time: 0.0213 memory: 5826 grad_norm: 4.2058 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.3952 loss: 3.3952 2022/10/07 08:01:53 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 08:01:59 - mmengine - INFO - Epoch(train) [3][780/2119] lr: 1.2000e-02 eta: 1 day, 5:43:23 time: 0.3528 data_time: 0.0216 memory: 5826 grad_norm: 4.1711 top1_acc: 0.2500 top5_acc: 0.3125 loss_cls: 3.4896 loss: 3.4896 2022/10/07 08:02:05 - mmengine - INFO - Epoch(train) [3][800/2119] lr: 1.2000e-02 eta: 1 day, 5:42:32 time: 0.3070 data_time: 0.0212 memory: 5826 grad_norm: 4.2085 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.2330 loss: 3.2330 2022/10/07 08:02:12 - mmengine - INFO - Epoch(train) [3][820/2119] lr: 1.2000e-02 eta: 1 day, 5:42:20 time: 0.3372 data_time: 0.0232 memory: 5826 grad_norm: 4.2430 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.2997 loss: 3.2997 2022/10/07 08:02:18 - mmengine - INFO - Epoch(train) [3][840/2119] lr: 1.2000e-02 eta: 1 day, 5:41:22 time: 0.3002 data_time: 0.0214 memory: 5826 grad_norm: 4.1848 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 3.3914 loss: 3.3914 2022/10/07 08:02:24 - mmengine - INFO - Epoch(train) [3][860/2119] lr: 1.2000e-02 eta: 1 day, 5:41:24 time: 0.3489 data_time: 0.0229 memory: 5826 grad_norm: 4.1715 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 3.2802 loss: 3.2802 2022/10/07 08:02:32 - mmengine - INFO - Epoch(train) [3][880/2119] lr: 1.2000e-02 eta: 1 day, 5:41:34 time: 0.3561 data_time: 0.0186 memory: 5826 grad_norm: 4.2542 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.3853 loss: 3.3853 2022/10/07 08:02:38 - mmengine - INFO - Epoch(train) [3][900/2119] lr: 1.2000e-02 eta: 1 day, 5:40:32 time: 0.2964 data_time: 0.0211 memory: 5826 grad_norm: 4.2653 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.2024 loss: 3.2024 2022/10/07 08:02:46 - mmengine - INFO - Epoch(train) [3][920/2119] lr: 1.2000e-02 eta: 1 day, 5:41:43 time: 0.4058 data_time: 0.0217 memory: 5826 grad_norm: 4.2040 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.3740 loss: 3.3740 2022/10/07 08:02:51 - mmengine - INFO - Epoch(train) [3][940/2119] lr: 1.2000e-02 eta: 1 day, 5:40:09 time: 0.2697 data_time: 0.0217 memory: 5826 grad_norm: 4.1797 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.3423 loss: 3.3423 2022/10/07 08:02:59 - mmengine - INFO - Epoch(train) [3][960/2119] lr: 1.2000e-02 eta: 1 day, 5:40:52 time: 0.3832 data_time: 0.0234 memory: 5826 grad_norm: 4.2507 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.3428 loss: 3.3428 2022/10/07 08:03:05 - mmengine - INFO - Epoch(train) [3][980/2119] lr: 1.2000e-02 eta: 1 day, 5:40:14 time: 0.3155 data_time: 0.0213 memory: 5826 grad_norm: 4.1719 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 3.1741 loss: 3.1741 2022/10/07 08:03:11 - mmengine - INFO - Epoch(train) [3][1000/2119] lr: 1.2000e-02 eta: 1 day, 5:39:30 time: 0.3107 data_time: 0.0226 memory: 5826 grad_norm: 4.2279 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.3367 loss: 3.3367 2022/10/07 08:03:18 - mmengine - INFO - Epoch(train) [3][1020/2119] lr: 1.2000e-02 eta: 1 day, 5:39:04 time: 0.3252 data_time: 0.0240 memory: 5826 grad_norm: 4.2237 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.5097 loss: 3.5097 2022/10/07 08:03:25 - mmengine - INFO - Epoch(train) [3][1040/2119] lr: 1.2000e-02 eta: 1 day, 5:39:00 time: 0.3442 data_time: 0.0217 memory: 5826 grad_norm: 4.1768 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.2666 loss: 3.2666 2022/10/07 08:03:30 - mmengine - INFO - Epoch(train) [3][1060/2119] lr: 1.2000e-02 eta: 1 day, 5:37:51 time: 0.2883 data_time: 0.0216 memory: 5826 grad_norm: 4.1967 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.2376 loss: 3.2376 2022/10/07 08:03:38 - mmengine - INFO - Epoch(train) [3][1080/2119] lr: 1.2000e-02 eta: 1 day, 5:38:19 time: 0.3711 data_time: 0.0270 memory: 5826 grad_norm: 4.2339 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 3.2544 loss: 3.2544 2022/10/07 08:03:44 - mmengine - INFO - Epoch(train) [3][1100/2119] lr: 1.2000e-02 eta: 1 day, 5:37:21 time: 0.2978 data_time: 0.0207 memory: 5826 grad_norm: 4.2004 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0550 loss: 3.0550 2022/10/07 08:03:50 - mmengine - INFO - Epoch(train) [3][1120/2119] lr: 1.2000e-02 eta: 1 day, 5:36:48 time: 0.3188 data_time: 0.0212 memory: 5826 grad_norm: 4.2582 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.1476 loss: 3.1476 2022/10/07 08:03:56 - mmengine - INFO - Epoch(train) [3][1140/2119] lr: 1.2000e-02 eta: 1 day, 5:36:09 time: 0.3136 data_time: 0.0244 memory: 5826 grad_norm: 4.1854 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.3247 loss: 3.3247 2022/10/07 08:04:04 - mmengine - INFO - Epoch(train) [3][1160/2119] lr: 1.2000e-02 eta: 1 day, 5:36:31 time: 0.3659 data_time: 0.0195 memory: 5826 grad_norm: 4.1357 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.4423 loss: 3.4423 2022/10/07 08:04:10 - mmengine - INFO - Epoch(train) [3][1180/2119] lr: 1.2000e-02 eta: 1 day, 5:35:50 time: 0.3109 data_time: 0.0214 memory: 5826 grad_norm: 4.1648 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0178 loss: 3.0178 2022/10/07 08:04:17 - mmengine - INFO - Epoch(train) [3][1200/2119] lr: 1.2000e-02 eta: 1 day, 5:35:56 time: 0.3529 data_time: 0.0184 memory: 5826 grad_norm: 4.2085 top1_acc: 0.0625 top5_acc: 0.4375 loss_cls: 3.3200 loss: 3.3200 2022/10/07 08:04:22 - mmengine - INFO - Epoch(train) [3][1220/2119] lr: 1.2000e-02 eta: 1 day, 5:34:26 time: 0.2685 data_time: 0.0262 memory: 5826 grad_norm: 4.2425 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 3.0964 loss: 3.0964 2022/10/07 08:04:30 - mmengine - INFO - Epoch(train) [3][1240/2119] lr: 1.2000e-02 eta: 1 day, 5:35:06 time: 0.3811 data_time: 0.0203 memory: 5826 grad_norm: 4.2411 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 3.1602 loss: 3.1602 2022/10/07 08:04:36 - mmengine - INFO - Epoch(train) [3][1260/2119] lr: 1.2000e-02 eta: 1 day, 5:34:07 time: 0.2956 data_time: 0.0274 memory: 5826 grad_norm: 4.2094 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.2068 loss: 3.2068 2022/10/07 08:04:42 - mmengine - INFO - Epoch(train) [3][1280/2119] lr: 1.2000e-02 eta: 1 day, 5:33:44 time: 0.3260 data_time: 0.0265 memory: 5826 grad_norm: 4.2006 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.3203 loss: 3.3203 2022/10/07 08:04:49 - mmengine - INFO - Epoch(train) [3][1300/2119] lr: 1.2000e-02 eta: 1 day, 5:33:19 time: 0.3248 data_time: 0.0249 memory: 5826 grad_norm: 4.2253 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.3414 loss: 3.3414 2022/10/07 08:04:56 - mmengine - INFO - Epoch(train) [3][1320/2119] lr: 1.2000e-02 eta: 1 day, 5:32:58 time: 0.3280 data_time: 0.0235 memory: 5826 grad_norm: 4.1440 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.2803 loss: 3.2803 2022/10/07 08:05:03 - mmengine - INFO - Epoch(train) [3][1340/2119] lr: 1.2000e-02 eta: 1 day, 5:33:13 time: 0.3604 data_time: 0.0238 memory: 5826 grad_norm: 4.1955 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.4454 loss: 3.4454 2022/10/07 08:05:09 - mmengine - INFO - Epoch(train) [3][1360/2119] lr: 1.2000e-02 eta: 1 day, 5:32:37 time: 0.3146 data_time: 0.0228 memory: 5826 grad_norm: 4.1346 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 3.2390 loss: 3.2390 2022/10/07 08:05:15 - mmengine - INFO - Epoch(train) [3][1380/2119] lr: 1.2000e-02 eta: 1 day, 5:31:55 time: 0.3088 data_time: 0.0233 memory: 5826 grad_norm: 4.1030 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.2313 loss: 3.2313 2022/10/07 08:05:23 - mmengine - INFO - Epoch(train) [3][1400/2119] lr: 1.2000e-02 eta: 1 day, 5:32:28 time: 0.3770 data_time: 0.0215 memory: 5826 grad_norm: 4.1954 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.2126 loss: 3.2126 2022/10/07 08:05:29 - mmengine - INFO - Epoch(train) [3][1420/2119] lr: 1.2000e-02 eta: 1 day, 5:31:31 time: 0.2944 data_time: 0.0255 memory: 5826 grad_norm: 4.1830 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1525 loss: 3.1525 2022/10/07 08:05:36 - mmengine - INFO - Epoch(train) [3][1440/2119] lr: 1.2000e-02 eta: 1 day, 5:31:32 time: 0.3476 data_time: 0.0254 memory: 5826 grad_norm: 4.1329 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.0397 loss: 3.0397 2022/10/07 08:05:42 - mmengine - INFO - Epoch(train) [3][1460/2119] lr: 1.2000e-02 eta: 1 day, 5:30:45 time: 0.3036 data_time: 0.0193 memory: 5826 grad_norm: 4.1901 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.2385 loss: 3.2385 2022/10/07 08:05:48 - mmengine - INFO - Epoch(train) [3][1480/2119] lr: 1.2000e-02 eta: 1 day, 5:30:39 time: 0.3415 data_time: 0.0192 memory: 5826 grad_norm: 4.1804 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.2567 loss: 3.2567 2022/10/07 08:05:55 - mmengine - INFO - Epoch(train) [3][1500/2119] lr: 1.2000e-02 eta: 1 day, 5:30:14 time: 0.3241 data_time: 0.0236 memory: 5826 grad_norm: 4.1226 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.1154 loss: 3.1154 2022/10/07 08:06:02 - mmengine - INFO - Epoch(train) [3][1520/2119] lr: 1.2000e-02 eta: 1 day, 5:30:23 time: 0.3548 data_time: 0.0281 memory: 5826 grad_norm: 4.1556 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.2387 loss: 3.2387 2022/10/07 08:06:08 - mmengine - INFO - Epoch(train) [3][1540/2119] lr: 1.2000e-02 eta: 1 day, 5:29:48 time: 0.3139 data_time: 0.0195 memory: 5826 grad_norm: 4.1965 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.3918 loss: 3.3918 2022/10/07 08:06:15 - mmengine - INFO - Epoch(train) [3][1560/2119] lr: 1.2000e-02 eta: 1 day, 5:29:40 time: 0.3391 data_time: 0.0191 memory: 5826 grad_norm: 4.2223 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0257 loss: 3.0257 2022/10/07 08:06:22 - mmengine - INFO - Epoch(train) [3][1580/2119] lr: 1.2000e-02 eta: 1 day, 5:29:45 time: 0.3511 data_time: 0.0281 memory: 5826 grad_norm: 4.1881 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.1995 loss: 3.1995 2022/10/07 08:06:28 - mmengine - INFO - Epoch(train) [3][1600/2119] lr: 1.2000e-02 eta: 1 day, 5:28:57 time: 0.3016 data_time: 0.0224 memory: 5826 grad_norm: 4.2040 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.1539 loss: 3.1539 2022/10/07 08:06:35 - mmengine - INFO - Epoch(train) [3][1620/2119] lr: 1.2000e-02 eta: 1 day, 5:29:18 time: 0.3662 data_time: 0.0254 memory: 5826 grad_norm: 4.1834 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.1064 loss: 3.1064 2022/10/07 08:06:42 - mmengine - INFO - Epoch(train) [3][1640/2119] lr: 1.2000e-02 eta: 1 day, 5:28:53 time: 0.3237 data_time: 0.0186 memory: 5826 grad_norm: 4.2365 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0610 loss: 3.0610 2022/10/07 08:06:49 - mmengine - INFO - Epoch(train) [3][1660/2119] lr: 1.2000e-02 eta: 1 day, 5:28:33 time: 0.3277 data_time: 0.0217 memory: 5826 grad_norm: 4.1724 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.3317 loss: 3.3317 2022/10/07 08:06:56 - mmengine - INFO - Epoch(train) [3][1680/2119] lr: 1.2000e-02 eta: 1 day, 5:28:42 time: 0.3548 data_time: 0.0246 memory: 5826 grad_norm: 4.1532 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1936 loss: 3.1936 2022/10/07 08:07:02 - mmengine - INFO - Epoch(train) [3][1700/2119] lr: 1.2000e-02 eta: 1 day, 5:28:04 time: 0.3112 data_time: 0.0237 memory: 5826 grad_norm: 4.1931 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.1699 loss: 3.1699 2022/10/07 08:07:08 - mmengine - INFO - Epoch(train) [3][1720/2119] lr: 1.2000e-02 eta: 1 day, 5:27:47 time: 0.3303 data_time: 0.0262 memory: 5826 grad_norm: 4.1312 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.3211 loss: 3.3211 2022/10/07 08:07:15 - mmengine - INFO - Epoch(train) [3][1740/2119] lr: 1.2000e-02 eta: 1 day, 5:27:16 time: 0.3168 data_time: 0.0241 memory: 5826 grad_norm: 4.1351 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0824 loss: 3.0824 2022/10/07 08:07:22 - mmengine - INFO - Epoch(train) [3][1760/2119] lr: 1.2000e-02 eta: 1 day, 5:27:14 time: 0.3439 data_time: 0.0270 memory: 5826 grad_norm: 4.1825 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.2231 loss: 3.2231 2022/10/07 08:07:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 08:07:28 - mmengine - INFO - Epoch(train) [3][1780/2119] lr: 1.2000e-02 eta: 1 day, 5:26:45 time: 0.3186 data_time: 0.0202 memory: 5826 grad_norm: 4.1548 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.4003 loss: 3.4003 2022/10/07 08:07:35 - mmengine - INFO - Epoch(train) [3][1800/2119] lr: 1.2000e-02 eta: 1 day, 5:27:09 time: 0.3701 data_time: 0.0211 memory: 5826 grad_norm: 4.1533 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.2516 loss: 3.2516 2022/10/07 08:07:42 - mmengine - INFO - Epoch(train) [3][1820/2119] lr: 1.2000e-02 eta: 1 day, 5:26:31 time: 0.3095 data_time: 0.0226 memory: 5826 grad_norm: 4.1928 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.2022 loss: 3.2022 2022/10/07 08:07:48 - mmengine - INFO - Epoch(train) [3][1840/2119] lr: 1.2000e-02 eta: 1 day, 5:26:27 time: 0.3431 data_time: 0.0215 memory: 5826 grad_norm: 4.1435 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.1848 loss: 3.1848 2022/10/07 08:07:56 - mmengine - INFO - Epoch(train) [3][1860/2119] lr: 1.2000e-02 eta: 1 day, 5:26:49 time: 0.3678 data_time: 0.0241 memory: 5826 grad_norm: 4.1568 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 3.1361 loss: 3.1361 2022/10/07 08:08:02 - mmengine - INFO - Epoch(train) [3][1880/2119] lr: 1.2000e-02 eta: 1 day, 5:26:24 time: 0.3221 data_time: 0.0214 memory: 5826 grad_norm: 4.1612 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0905 loss: 3.0905 2022/10/07 08:08:09 - mmengine - INFO - Epoch(train) [3][1900/2119] lr: 1.2000e-02 eta: 1 day, 5:25:55 time: 0.3181 data_time: 0.0229 memory: 5826 grad_norm: 4.1984 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1526 loss: 3.1526 2022/10/07 08:08:16 - mmengine - INFO - Epoch(train) [3][1920/2119] lr: 1.2000e-02 eta: 1 day, 5:25:52 time: 0.3443 data_time: 0.0254 memory: 5826 grad_norm: 4.2060 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 3.4342 loss: 3.4342 2022/10/07 08:08:21 - mmengine - INFO - Epoch(train) [3][1940/2119] lr: 1.2000e-02 eta: 1 day, 5:24:52 time: 0.2872 data_time: 0.0237 memory: 5826 grad_norm: 4.1622 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2209 loss: 3.2209 2022/10/07 08:08:29 - mmengine - INFO - Epoch(train) [3][1960/2119] lr: 1.2000e-02 eta: 1 day, 5:25:10 time: 0.3644 data_time: 0.0212 memory: 5826 grad_norm: 4.1857 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 3.2682 loss: 3.2682 2022/10/07 08:08:36 - mmengine - INFO - Epoch(train) [3][1980/2119] lr: 1.2000e-02 eta: 1 day, 5:25:17 time: 0.3531 data_time: 0.0234 memory: 5826 grad_norm: 4.2041 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1159 loss: 3.1159 2022/10/07 08:08:43 - mmengine - INFO - Epoch(train) [3][2000/2119] lr: 1.2000e-02 eta: 1 day, 5:25:22 time: 0.3522 data_time: 0.0228 memory: 5826 grad_norm: 4.2185 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.2753 loss: 3.2753 2022/10/07 08:08:49 - mmengine - INFO - Epoch(train) [3][2020/2119] lr: 1.2000e-02 eta: 1 day, 5:24:58 time: 0.3226 data_time: 0.0198 memory: 5826 grad_norm: 4.1807 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0843 loss: 3.0843 2022/10/07 08:08:55 - mmengine - INFO - Epoch(train) [3][2040/2119] lr: 1.2000e-02 eta: 1 day, 5:24:10 time: 0.2987 data_time: 0.0238 memory: 5826 grad_norm: 4.1698 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.2292 loss: 3.2292 2022/10/07 08:09:02 - mmengine - INFO - Epoch(train) [3][2060/2119] lr: 1.2000e-02 eta: 1 day, 5:24:19 time: 0.3549 data_time: 0.0171 memory: 5826 grad_norm: 4.1243 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.2373 loss: 3.2373 2022/10/07 08:09:10 - mmengine - INFO - Epoch(train) [3][2080/2119] lr: 1.2000e-02 eta: 1 day, 5:24:41 time: 0.3691 data_time: 0.0236 memory: 5826 grad_norm: 4.1700 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.2086 loss: 3.2086 2022/10/07 08:09:17 - mmengine - INFO - Epoch(train) [3][2100/2119] lr: 1.2000e-02 eta: 1 day, 5:24:46 time: 0.3526 data_time: 0.0239 memory: 5826 grad_norm: 4.1492 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.1276 loss: 3.1276 2022/10/07 08:09:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 08:09:24 - mmengine - INFO - Epoch(train) [3][2119/2119] lr: 1.2000e-02 eta: 1 day, 5:24:46 time: 0.3595 data_time: 0.0202 memory: 5826 grad_norm: 4.2081 top1_acc: 0.3000 top5_acc: 0.4000 loss_cls: 3.1128 loss: 3.1128 2022/10/07 08:09:33 - mmengine - INFO - Epoch(train) [4][20/2119] lr: 1.6000e-02 eta: 1 day, 5:21:20 time: 0.4648 data_time: 0.1285 memory: 5826 grad_norm: 4.1810 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 3.4196 loss: 3.4196 2022/10/07 08:09:40 - mmengine - INFO - Epoch(train) [4][40/2119] lr: 1.6000e-02 eta: 1 day, 5:21:05 time: 0.3315 data_time: 0.0254 memory: 5826 grad_norm: 4.1352 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.3480 loss: 3.3480 2022/10/07 08:09:46 - mmengine - INFO - Epoch(train) [4][60/2119] lr: 1.6000e-02 eta: 1 day, 5:21:06 time: 0.3468 data_time: 0.0322 memory: 5826 grad_norm: 4.1567 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0996 loss: 3.0996 2022/10/07 08:09:53 - mmengine - INFO - Epoch(train) [4][80/2119] lr: 1.6000e-02 eta: 1 day, 5:20:51 time: 0.3307 data_time: 0.0258 memory: 5826 grad_norm: 4.0988 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0465 loss: 3.0465 2022/10/07 08:10:00 - mmengine - INFO - Epoch(train) [4][100/2119] lr: 1.6000e-02 eta: 1 day, 5:21:05 time: 0.3611 data_time: 0.0261 memory: 5826 grad_norm: 4.0558 top1_acc: 0.0625 top5_acc: 0.4375 loss_cls: 3.1092 loss: 3.1092 2022/10/07 08:10:07 - mmengine - INFO - Epoch(train) [4][120/2119] lr: 1.6000e-02 eta: 1 day, 5:20:49 time: 0.3299 data_time: 0.0254 memory: 5826 grad_norm: 4.0870 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.3053 loss: 3.3053 2022/10/07 08:10:14 - mmengine - INFO - Epoch(train) [4][140/2119] lr: 1.6000e-02 eta: 1 day, 5:21:09 time: 0.3676 data_time: 0.0191 memory: 5826 grad_norm: 4.1118 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0231 loss: 3.0231 2022/10/07 08:10:20 - mmengine - INFO - Epoch(train) [4][160/2119] lr: 1.6000e-02 eta: 1 day, 5:20:13 time: 0.2871 data_time: 0.0222 memory: 5826 grad_norm: 4.0738 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.3258 loss: 3.3258 2022/10/07 08:10:27 - mmengine - INFO - Epoch(train) [4][180/2119] lr: 1.6000e-02 eta: 1 day, 5:19:53 time: 0.3252 data_time: 0.0245 memory: 5826 grad_norm: 4.0851 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1186 loss: 3.1186 2022/10/07 08:10:33 - mmengine - INFO - Epoch(train) [4][200/2119] lr: 1.6000e-02 eta: 1 day, 5:19:50 time: 0.3434 data_time: 0.0186 memory: 5826 grad_norm: 4.0041 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.2401 loss: 3.2401 2022/10/07 08:10:41 - mmengine - INFO - Epoch(train) [4][220/2119] lr: 1.6000e-02 eta: 1 day, 5:20:12 time: 0.3696 data_time: 0.0230 memory: 5826 grad_norm: 4.0344 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.1947 loss: 3.1947 2022/10/07 08:10:47 - mmengine - INFO - Epoch(train) [4][240/2119] lr: 1.6000e-02 eta: 1 day, 5:19:19 time: 0.2903 data_time: 0.0223 memory: 5826 grad_norm: 4.1375 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.1538 loss: 3.1538 2022/10/07 08:10:53 - mmengine - INFO - Epoch(train) [4][260/2119] lr: 1.6000e-02 eta: 1 day, 5:19:05 time: 0.3319 data_time: 0.0252 memory: 5826 grad_norm: 4.0636 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.3627 loss: 3.3627 2022/10/07 08:11:00 - mmengine - INFO - Epoch(train) [4][280/2119] lr: 1.6000e-02 eta: 1 day, 5:18:56 time: 0.3366 data_time: 0.0241 memory: 5826 grad_norm: 4.0121 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.2183 loss: 3.2183 2022/10/07 08:11:06 - mmengine - INFO - Epoch(train) [4][300/2119] lr: 1.6000e-02 eta: 1 day, 5:18:26 time: 0.3141 data_time: 0.0259 memory: 5826 grad_norm: 4.0451 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.1204 loss: 3.1204 2022/10/07 08:11:13 - mmengine - INFO - Epoch(train) [4][320/2119] lr: 1.6000e-02 eta: 1 day, 5:18:03 time: 0.3215 data_time: 0.0269 memory: 5826 grad_norm: 4.0344 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0723 loss: 3.0723 2022/10/07 08:11:20 - mmengine - INFO - Epoch(train) [4][340/2119] lr: 1.6000e-02 eta: 1 day, 5:18:05 time: 0.3485 data_time: 0.0245 memory: 5826 grad_norm: 4.1057 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.2345 loss: 3.2345 2022/10/07 08:11:26 - mmengine - INFO - Epoch(train) [4][360/2119] lr: 1.6000e-02 eta: 1 day, 5:17:30 time: 0.3090 data_time: 0.0180 memory: 5826 grad_norm: 4.0316 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 3.1226 loss: 3.1226 2022/10/07 08:11:32 - mmengine - INFO - Epoch(train) [4][380/2119] lr: 1.6000e-02 eta: 1 day, 5:16:49 time: 0.3018 data_time: 0.0249 memory: 5826 grad_norm: 4.0633 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.2287 loss: 3.2287 2022/10/07 08:11:39 - mmengine - INFO - Epoch(train) [4][400/2119] lr: 1.6000e-02 eta: 1 day, 5:16:52 time: 0.3493 data_time: 0.0207 memory: 5826 grad_norm: 4.0560 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1426 loss: 3.1426 2022/10/07 08:11:46 - mmengine - INFO - Epoch(train) [4][420/2119] lr: 1.6000e-02 eta: 1 day, 5:17:13 time: 0.3691 data_time: 0.0226 memory: 5826 grad_norm: 4.0048 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.3595 loss: 3.3595 2022/10/07 08:11:53 - mmengine - INFO - Epoch(train) [4][440/2119] lr: 1.6000e-02 eta: 1 day, 5:16:56 time: 0.3281 data_time: 0.0231 memory: 5826 grad_norm: 4.0157 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9474 loss: 2.9474 2022/10/07 08:12:00 - mmengine - INFO - Epoch(train) [4][460/2119] lr: 1.6000e-02 eta: 1 day, 5:17:17 time: 0.3689 data_time: 0.0236 memory: 5826 grad_norm: 4.0479 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9898 loss: 2.9898 2022/10/07 08:12:06 - mmengine - INFO - Epoch(train) [4][480/2119] lr: 1.6000e-02 eta: 1 day, 5:16:47 time: 0.3137 data_time: 0.0218 memory: 5826 grad_norm: 4.0930 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 3.1119 loss: 3.1119 2022/10/07 08:12:13 - mmengine - INFO - Epoch(train) [4][500/2119] lr: 1.6000e-02 eta: 1 day, 5:16:21 time: 0.3179 data_time: 0.0235 memory: 5826 grad_norm: 4.0489 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.2225 loss: 3.2225 2022/10/07 08:12:20 - mmengine - INFO - Epoch(train) [4][520/2119] lr: 1.6000e-02 eta: 1 day, 5:16:20 time: 0.3447 data_time: 0.0245 memory: 5826 grad_norm: 4.0584 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.2426 loss: 3.2426 2022/10/07 08:12:27 - mmengine - INFO - Epoch(train) [4][540/2119] lr: 1.6000e-02 eta: 1 day, 5:16:35 time: 0.3636 data_time: 0.0179 memory: 5826 grad_norm: 4.0020 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0869 loss: 3.0869 2022/10/07 08:12:33 - mmengine - INFO - Epoch(train) [4][560/2119] lr: 1.6000e-02 eta: 1 day, 5:16:11 time: 0.3195 data_time: 0.0315 memory: 5826 grad_norm: 3.9867 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.2626 loss: 3.2626 2022/10/07 08:12:40 - mmengine - INFO - Epoch(train) [4][580/2119] lr: 1.6000e-02 eta: 1 day, 5:16:02 time: 0.3359 data_time: 0.0222 memory: 5826 grad_norm: 4.0276 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.2733 loss: 3.2733 2022/10/07 08:12:46 - mmengine - INFO - Epoch(train) [4][600/2119] lr: 1.6000e-02 eta: 1 day, 5:15:25 time: 0.3054 data_time: 0.0230 memory: 5826 grad_norm: 4.0111 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9498 loss: 2.9498 2022/10/07 08:12:54 - mmengine - INFO - Epoch(train) [4][620/2119] lr: 1.6000e-02 eta: 1 day, 5:15:47 time: 0.3712 data_time: 0.0235 memory: 5826 grad_norm: 4.0073 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 3.2523 loss: 3.2523 2022/10/07 08:12:59 - mmengine - INFO - Epoch(train) [4][640/2119] lr: 1.6000e-02 eta: 1 day, 5:14:37 time: 0.2673 data_time: 0.0246 memory: 5826 grad_norm: 4.0019 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.1798 loss: 3.1798 2022/10/07 08:13:01 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 08:13:06 - mmengine - INFO - Epoch(train) [4][660/2119] lr: 1.6000e-02 eta: 1 day, 5:14:54 time: 0.3656 data_time: 0.0238 memory: 5826 grad_norm: 3.9492 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 3.1344 loss: 3.1344 2022/10/07 08:13:12 - mmengine - INFO - Epoch(train) [4][680/2119] lr: 1.6000e-02 eta: 1 day, 5:14:20 time: 0.3080 data_time: 0.0265 memory: 5826 grad_norm: 4.0643 top1_acc: 0.1875 top5_acc: 0.7500 loss_cls: 3.0536 loss: 3.0536 2022/10/07 08:13:19 - mmengine - INFO - Epoch(train) [4][700/2119] lr: 1.6000e-02 eta: 1 day, 5:14:20 time: 0.3468 data_time: 0.0331 memory: 5826 grad_norm: 4.0679 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1647 loss: 3.1647 2022/10/07 08:13:25 - mmengine - INFO - Epoch(train) [4][720/2119] lr: 1.6000e-02 eta: 1 day, 5:13:35 time: 0.2944 data_time: 0.0257 memory: 5826 grad_norm: 4.0184 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 3.1110 loss: 3.1110 2022/10/07 08:13:32 - mmengine - INFO - Epoch(train) [4][740/2119] lr: 1.6000e-02 eta: 1 day, 5:13:35 time: 0.3461 data_time: 0.0244 memory: 5826 grad_norm: 3.9978 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2724 loss: 3.2724 2022/10/07 08:13:39 - mmengine - INFO - Epoch(train) [4][760/2119] lr: 1.6000e-02 eta: 1 day, 5:13:13 time: 0.3220 data_time: 0.0212 memory: 5826 grad_norm: 4.0425 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.4982 loss: 3.4982 2022/10/07 08:13:46 - mmengine - INFO - Epoch(train) [4][780/2119] lr: 1.6000e-02 eta: 1 day, 5:13:20 time: 0.3542 data_time: 0.0204 memory: 5826 grad_norm: 4.0598 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9297 loss: 2.9297 2022/10/07 08:13:52 - mmengine - INFO - Epoch(train) [4][800/2119] lr: 1.6000e-02 eta: 1 day, 5:12:39 time: 0.2986 data_time: 0.0276 memory: 5826 grad_norm: 4.0082 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.2226 loss: 3.2226 2022/10/07 08:14:00 - mmengine - INFO - Epoch(train) [4][820/2119] lr: 1.6000e-02 eta: 1 day, 5:13:30 time: 0.4051 data_time: 0.0235 memory: 5826 grad_norm: 3.9825 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9936 loss: 2.9936 2022/10/07 08:14:06 - mmengine - INFO - Epoch(train) [4][840/2119] lr: 1.6000e-02 eta: 1 day, 5:12:42 time: 0.2910 data_time: 0.0242 memory: 5826 grad_norm: 4.0024 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.3415 loss: 3.3415 2022/10/07 08:14:13 - mmengine - INFO - Epoch(train) [4][860/2119] lr: 1.6000e-02 eta: 1 day, 5:12:45 time: 0.3502 data_time: 0.0260 memory: 5826 grad_norm: 4.0449 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1751 loss: 3.1751 2022/10/07 08:14:19 - mmengine - INFO - Epoch(train) [4][880/2119] lr: 1.6000e-02 eta: 1 day, 5:12:21 time: 0.3189 data_time: 0.0216 memory: 5826 grad_norm: 3.9654 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.2149 loss: 3.2149 2022/10/07 08:14:25 - mmengine - INFO - Epoch(train) [4][900/2119] lr: 1.6000e-02 eta: 1 day, 5:11:56 time: 0.3167 data_time: 0.0233 memory: 5826 grad_norm: 4.0342 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.4768 loss: 3.4768 2022/10/07 08:14:32 - mmengine - INFO - Epoch(train) [4][920/2119] lr: 1.6000e-02 eta: 1 day, 5:11:51 time: 0.3406 data_time: 0.0233 memory: 5826 grad_norm: 4.0045 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.2284 loss: 3.2284 2022/10/07 08:14:39 - mmengine - INFO - Epoch(train) [4][940/2119] lr: 1.6000e-02 eta: 1 day, 5:11:41 time: 0.3342 data_time: 0.0208 memory: 5826 grad_norm: 3.9725 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1659 loss: 3.1659 2022/10/07 08:14:45 - mmengine - INFO - Epoch(train) [4][960/2119] lr: 1.6000e-02 eta: 1 day, 5:11:23 time: 0.3260 data_time: 0.0261 memory: 5826 grad_norm: 3.9630 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1328 loss: 3.1328 2022/10/07 08:14:52 - mmengine - INFO - Epoch(train) [4][980/2119] lr: 1.6000e-02 eta: 1 day, 5:11:04 time: 0.3236 data_time: 0.0186 memory: 5826 grad_norm: 4.0516 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 3.1314 loss: 3.1314 2022/10/07 08:14:59 - mmengine - INFO - Epoch(train) [4][1000/2119] lr: 1.6000e-02 eta: 1 day, 5:11:07 time: 0.3503 data_time: 0.0214 memory: 5826 grad_norm: 3.9872 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9867 loss: 2.9867 2022/10/07 08:15:05 - mmengine - INFO - Epoch(train) [4][1020/2119] lr: 1.6000e-02 eta: 1 day, 5:10:31 time: 0.3029 data_time: 0.0247 memory: 5826 grad_norm: 4.0146 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.3540 loss: 3.3540 2022/10/07 08:15:12 - mmengine - INFO - Epoch(train) [4][1040/2119] lr: 1.6000e-02 eta: 1 day, 5:10:21 time: 0.3352 data_time: 0.0211 memory: 5826 grad_norm: 3.9880 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1341 loss: 3.1341 2022/10/07 08:15:19 - mmengine - INFO - Epoch(train) [4][1060/2119] lr: 1.6000e-02 eta: 1 day, 5:10:27 time: 0.3529 data_time: 0.0259 memory: 5826 grad_norm: 3.9632 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.1758 loss: 3.1758 2022/10/07 08:15:25 - mmengine - INFO - Epoch(train) [4][1080/2119] lr: 1.6000e-02 eta: 1 day, 5:10:13 time: 0.3302 data_time: 0.0719 memory: 5826 grad_norm: 4.0397 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.4337 loss: 3.4337 2022/10/07 08:15:32 - mmengine - INFO - Epoch(train) [4][1100/2119] lr: 1.6000e-02 eta: 1 day, 5:10:03 time: 0.3346 data_time: 0.0181 memory: 5826 grad_norm: 3.9922 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1109 loss: 3.1109 2022/10/07 08:15:39 - mmengine - INFO - Epoch(train) [4][1120/2119] lr: 1.6000e-02 eta: 1 day, 5:10:03 time: 0.3461 data_time: 0.0261 memory: 5826 grad_norm: 4.0624 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.3369 loss: 3.3369 2022/10/07 08:15:45 - mmengine - INFO - Epoch(train) [4][1140/2119] lr: 1.6000e-02 eta: 1 day, 5:09:48 time: 0.3282 data_time: 0.0241 memory: 5826 grad_norm: 3.9745 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.1413 loss: 3.1413 2022/10/07 08:15:52 - mmengine - INFO - Epoch(train) [4][1160/2119] lr: 1.6000e-02 eta: 1 day, 5:09:36 time: 0.3320 data_time: 0.0200 memory: 5826 grad_norm: 3.9397 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0015 loss: 3.0015 2022/10/07 08:16:00 - mmengine - INFO - Epoch(train) [4][1180/2119] lr: 1.6000e-02 eta: 1 day, 5:10:12 time: 0.3906 data_time: 0.0202 memory: 5826 grad_norm: 3.9967 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.3311 loss: 3.3311 2022/10/07 08:16:06 - mmengine - INFO - Epoch(train) [4][1200/2119] lr: 1.6000e-02 eta: 1 day, 5:09:56 time: 0.3266 data_time: 0.0251 memory: 5826 grad_norm: 3.8924 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 3.2491 loss: 3.2491 2022/10/07 08:16:13 - mmengine - INFO - Epoch(train) [4][1220/2119] lr: 1.6000e-02 eta: 1 day, 5:09:38 time: 0.3254 data_time: 0.0243 memory: 5826 grad_norm: 3.9689 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.0335 loss: 3.0335 2022/10/07 08:16:20 - mmengine - INFO - Epoch(train) [4][1240/2119] lr: 1.6000e-02 eta: 1 day, 5:09:25 time: 0.3304 data_time: 0.0240 memory: 5826 grad_norm: 3.9890 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0757 loss: 3.0757 2022/10/07 08:16:26 - mmengine - INFO - Epoch(train) [4][1260/2119] lr: 1.6000e-02 eta: 1 day, 5:09:16 time: 0.3356 data_time: 0.0263 memory: 5826 grad_norm: 3.9811 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.1784 loss: 3.1784 2022/10/07 08:16:34 - mmengine - INFO - Epoch(train) [4][1280/2119] lr: 1.6000e-02 eta: 1 day, 5:09:39 time: 0.3745 data_time: 0.0225 memory: 5826 grad_norm: 4.0315 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.2610 loss: 3.2610 2022/10/07 08:16:40 - mmengine - INFO - Epoch(train) [4][1300/2119] lr: 1.6000e-02 eta: 1 day, 5:09:12 time: 0.3134 data_time: 0.0196 memory: 5826 grad_norm: 3.9978 top1_acc: 0.0625 top5_acc: 0.3750 loss_cls: 3.2728 loss: 3.2728 2022/10/07 08:16:46 - mmengine - INFO - Epoch(train) [4][1320/2119] lr: 1.6000e-02 eta: 1 day, 5:08:46 time: 0.3155 data_time: 0.0211 memory: 5826 grad_norm: 3.9557 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.0904 loss: 3.0904 2022/10/07 08:16:53 - mmengine - INFO - Epoch(train) [4][1340/2119] lr: 1.6000e-02 eta: 1 day, 5:08:36 time: 0.3342 data_time: 0.0377 memory: 5826 grad_norm: 3.9510 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 3.0720 loss: 3.0720 2022/10/07 08:16:59 - mmengine - INFO - Epoch(train) [4][1360/2119] lr: 1.6000e-02 eta: 1 day, 5:08:11 time: 0.3145 data_time: 0.0209 memory: 5826 grad_norm: 4.0080 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0620 loss: 3.0620 2022/10/07 08:17:06 - mmengine - INFO - Epoch(train) [4][1380/2119] lr: 1.6000e-02 eta: 1 day, 5:08:01 time: 0.3350 data_time: 0.0272 memory: 5826 grad_norm: 3.9634 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.1428 loss: 3.1428 2022/10/07 08:17:14 - mmengine - INFO - Epoch(train) [4][1400/2119] lr: 1.6000e-02 eta: 1 day, 5:08:34 time: 0.3879 data_time: 0.0220 memory: 5826 grad_norm: 3.9207 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9248 loss: 2.9248 2022/10/07 08:17:20 - mmengine - INFO - Epoch(train) [4][1420/2119] lr: 1.6000e-02 eta: 1 day, 5:07:57 time: 0.3002 data_time: 0.0162 memory: 5826 grad_norm: 3.9650 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 3.1002 loss: 3.1002 2022/10/07 08:17:27 - mmengine - INFO - Epoch(train) [4][1440/2119] lr: 1.6000e-02 eta: 1 day, 5:08:11 time: 0.3648 data_time: 0.0216 memory: 5826 grad_norm: 3.9444 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.1189 loss: 3.1189 2022/10/07 08:17:33 - mmengine - INFO - Epoch(train) [4][1460/2119] lr: 1.6000e-02 eta: 1 day, 5:07:52 time: 0.3226 data_time: 0.0332 memory: 5826 grad_norm: 3.8994 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.0951 loss: 3.0951 2022/10/07 08:17:40 - mmengine - INFO - Epoch(train) [4][1480/2119] lr: 1.6000e-02 eta: 1 day, 5:07:51 time: 0.3458 data_time: 0.0188 memory: 5826 grad_norm: 3.9298 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1410 loss: 3.1410 2022/10/07 08:17:47 - mmengine - INFO - Epoch(train) [4][1500/2119] lr: 1.6000e-02 eta: 1 day, 5:07:24 time: 0.3121 data_time: 0.0246 memory: 5826 grad_norm: 3.9790 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.1483 loss: 3.1483 2022/10/07 08:17:54 - mmengine - INFO - Epoch(train) [4][1520/2119] lr: 1.6000e-02 eta: 1 day, 5:07:41 time: 0.3684 data_time: 0.0192 memory: 5826 grad_norm: 3.9311 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0535 loss: 3.0535 2022/10/07 08:18:00 - mmengine - INFO - Epoch(train) [4][1540/2119] lr: 1.6000e-02 eta: 1 day, 5:07:13 time: 0.3118 data_time: 0.0226 memory: 5826 grad_norm: 3.9924 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0384 loss: 3.0384 2022/10/07 08:18:07 - mmengine - INFO - Epoch(train) [4][1560/2119] lr: 1.6000e-02 eta: 1 day, 5:06:57 time: 0.3264 data_time: 0.0269 memory: 5826 grad_norm: 3.9428 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.3121 loss: 3.3121 2022/10/07 08:18:14 - mmengine - INFO - Epoch(train) [4][1580/2119] lr: 1.6000e-02 eta: 1 day, 5:06:54 time: 0.3429 data_time: 0.0212 memory: 5826 grad_norm: 3.9526 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.2390 loss: 3.2390 2022/10/07 08:18:20 - mmengine - INFO - Epoch(train) [4][1600/2119] lr: 1.6000e-02 eta: 1 day, 5:06:35 time: 0.3226 data_time: 0.0234 memory: 5826 grad_norm: 4.0076 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8991 loss: 2.8991 2022/10/07 08:18:27 - mmengine - INFO - Epoch(train) [4][1620/2119] lr: 1.6000e-02 eta: 1 day, 5:06:32 time: 0.3431 data_time: 0.0225 memory: 5826 grad_norm: 3.9213 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0628 loss: 3.0628 2022/10/07 08:18:34 - mmengine - INFO - Epoch(train) [4][1640/2119] lr: 1.6000e-02 eta: 1 day, 5:06:48 time: 0.3670 data_time: 0.0238 memory: 5826 grad_norm: 3.8531 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.2045 loss: 3.2045 2022/10/07 08:18:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 08:18:41 - mmengine - INFO - Epoch(train) [4][1660/2119] lr: 1.6000e-02 eta: 1 day, 5:06:20 time: 0.3109 data_time: 0.0212 memory: 5826 grad_norm: 3.8990 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.1322 loss: 3.1322 2022/10/07 08:18:47 - mmengine - INFO - Epoch(train) [4][1680/2119] lr: 1.6000e-02 eta: 1 day, 5:06:16 time: 0.3412 data_time: 0.0192 memory: 5826 grad_norm: 4.0011 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0755 loss: 3.0755 2022/10/07 08:18:54 - mmengine - INFO - Epoch(train) [4][1700/2119] lr: 1.6000e-02 eta: 1 day, 5:05:57 time: 0.3235 data_time: 0.0207 memory: 5826 grad_norm: 3.9563 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.1781 loss: 3.1781 2022/10/07 08:19:01 - mmengine - INFO - Epoch(train) [4][1720/2119] lr: 1.6000e-02 eta: 1 day, 5:06:17 time: 0.3721 data_time: 0.0245 memory: 5826 grad_norm: 3.8646 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 3.1259 loss: 3.1259 2022/10/07 08:19:07 - mmengine - INFO - Epoch(train) [4][1740/2119] lr: 1.6000e-02 eta: 1 day, 5:05:28 time: 0.2840 data_time: 0.0221 memory: 5826 grad_norm: 3.9206 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 3.0932 loss: 3.0932 2022/10/07 08:19:15 - mmengine - INFO - Epoch(train) [4][1760/2119] lr: 1.6000e-02 eta: 1 day, 5:06:12 time: 0.4038 data_time: 0.0226 memory: 5826 grad_norm: 4.0033 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.3350 loss: 3.3350 2022/10/07 08:19:21 - mmengine - INFO - Epoch(train) [4][1780/2119] lr: 1.6000e-02 eta: 1 day, 5:05:40 time: 0.3057 data_time: 0.0190 memory: 5826 grad_norm: 3.8983 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.8957 loss: 2.8957 2022/10/07 08:19:28 - mmengine - INFO - Epoch(train) [4][1800/2119] lr: 1.6000e-02 eta: 1 day, 5:05:53 time: 0.3638 data_time: 0.0219 memory: 5826 grad_norm: 3.9450 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.1867 loss: 3.1867 2022/10/07 08:19:34 - mmengine - INFO - Epoch(train) [4][1820/2119] lr: 1.6000e-02 eta: 1 day, 5:05:06 time: 0.2850 data_time: 0.0245 memory: 5826 grad_norm: 3.9279 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.1876 loss: 3.1876 2022/10/07 08:19:42 - mmengine - INFO - Epoch(train) [4][1840/2119] lr: 1.6000e-02 eta: 1 day, 5:05:30 time: 0.3792 data_time: 0.0203 memory: 5826 grad_norm: 3.9006 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.3617 loss: 3.3617 2022/10/07 08:19:48 - mmengine - INFO - Epoch(train) [4][1860/2119] lr: 1.6000e-02 eta: 1 day, 5:04:59 time: 0.3058 data_time: 0.0237 memory: 5826 grad_norm: 3.8937 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.2779 loss: 3.2779 2022/10/07 08:19:55 - mmengine - INFO - Epoch(train) [4][1880/2119] lr: 1.6000e-02 eta: 1 day, 5:05:17 time: 0.3706 data_time: 0.0234 memory: 5826 grad_norm: 3.9986 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.1552 loss: 3.1552 2022/10/07 08:20:01 - mmengine - INFO - Epoch(train) [4][1900/2119] lr: 1.6000e-02 eta: 1 day, 5:04:28 time: 0.2831 data_time: 0.0215 memory: 5826 grad_norm: 3.9354 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 3.1939 loss: 3.1939 2022/10/07 08:20:08 - mmengine - INFO - Epoch(train) [4][1920/2119] lr: 1.6000e-02 eta: 1 day, 5:04:32 time: 0.3516 data_time: 0.0226 memory: 5826 grad_norm: 3.8837 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.1991 loss: 3.1991 2022/10/07 08:20:15 - mmengine - INFO - Epoch(train) [4][1940/2119] lr: 1.6000e-02 eta: 1 day, 5:04:36 time: 0.3523 data_time: 0.0239 memory: 5826 grad_norm: 3.9387 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0567 loss: 3.0567 2022/10/07 08:20:21 - mmengine - INFO - Epoch(train) [4][1960/2119] lr: 1.6000e-02 eta: 1 day, 5:04:08 time: 0.3095 data_time: 0.0235 memory: 5826 grad_norm: 3.9229 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.9254 loss: 2.9254 2022/10/07 08:20:28 - mmengine - INFO - Epoch(train) [4][1980/2119] lr: 1.6000e-02 eta: 1 day, 5:03:56 time: 0.3314 data_time: 0.0246 memory: 5826 grad_norm: 3.9602 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0363 loss: 3.0363 2022/10/07 08:20:34 - mmengine - INFO - Epoch(train) [4][2000/2119] lr: 1.6000e-02 eta: 1 day, 5:03:30 time: 0.3117 data_time: 0.0292 memory: 5826 grad_norm: 3.9166 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9624 loss: 2.9624 2022/10/07 08:20:40 - mmengine - INFO - Epoch(train) [4][2020/2119] lr: 1.6000e-02 eta: 1 day, 5:02:38 time: 0.2777 data_time: 0.0206 memory: 5826 grad_norm: 3.8701 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0394 loss: 3.0394 2022/10/07 08:20:47 - mmengine - INFO - Epoch(train) [4][2040/2119] lr: 1.6000e-02 eta: 1 day, 5:03:07 time: 0.3865 data_time: 0.0198 memory: 5826 grad_norm: 3.8915 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 3.2922 loss: 3.2922 2022/10/07 08:20:54 - mmengine - INFO - Epoch(train) [4][2060/2119] lr: 1.6000e-02 eta: 1 day, 5:02:41 time: 0.3107 data_time: 0.0294 memory: 5826 grad_norm: 3.9646 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0388 loss: 3.0388 2022/10/07 08:21:00 - mmengine - INFO - Epoch(train) [4][2080/2119] lr: 1.6000e-02 eta: 1 day, 5:02:17 time: 0.3148 data_time: 0.0245 memory: 5826 grad_norm: 3.8772 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.1532 loss: 3.1532 2022/10/07 08:21:07 - mmengine - INFO - Epoch(train) [4][2100/2119] lr: 1.6000e-02 eta: 1 day, 5:02:15 time: 0.3449 data_time: 0.0206 memory: 5826 grad_norm: 3.9502 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8682 loss: 2.8682 2022/10/07 08:21:12 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 08:21:12 - mmengine - INFO - Epoch(train) [4][2119/2119] lr: 1.6000e-02 eta: 1 day, 5:02:15 time: 0.2764 data_time: 0.0172 memory: 5826 grad_norm: 3.9167 top1_acc: 0.2000 top5_acc: 0.5000 loss_cls: 3.2922 loss: 3.2922 2022/10/07 08:21:12 - mmengine - INFO - Saving checkpoint at 4 epochs 2022/10/07 08:21:30 - mmengine - INFO - Epoch(train) [5][20/2119] lr: 2.0000e-02 eta: 1 day, 4:58:54 time: 0.4001 data_time: 0.1667 memory: 5826 grad_norm: 3.9866 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9477 loss: 2.9477 2022/10/07 08:21:36 - mmengine - INFO - Epoch(train) [5][40/2119] lr: 2.0000e-02 eta: 1 day, 4:58:37 time: 0.3233 data_time: 0.1098 memory: 5826 grad_norm: 3.9031 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9600 loss: 2.9600 2022/10/07 08:21:42 - mmengine - INFO - Epoch(train) [5][60/2119] lr: 2.0000e-02 eta: 1 day, 4:58:03 time: 0.3002 data_time: 0.0573 memory: 5826 grad_norm: 3.9294 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2334 loss: 3.2334 2022/10/07 08:21:49 - mmengine - INFO - Epoch(train) [5][80/2119] lr: 2.0000e-02 eta: 1 day, 4:57:49 time: 0.3267 data_time: 0.0463 memory: 5826 grad_norm: 3.8651 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 3.0798 loss: 3.0798 2022/10/07 08:21:55 - mmengine - INFO - Epoch(train) [5][100/2119] lr: 2.0000e-02 eta: 1 day, 4:57:29 time: 0.3189 data_time: 0.0276 memory: 5826 grad_norm: 3.9091 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.1903 loss: 3.1903 2022/10/07 08:22:02 - mmengine - INFO - Epoch(train) [5][120/2119] lr: 2.0000e-02 eta: 1 day, 4:57:31 time: 0.3491 data_time: 0.0180 memory: 5826 grad_norm: 3.8868 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 3.0821 loss: 3.0821 2022/10/07 08:22:09 - mmengine - INFO - Epoch(train) [5][140/2119] lr: 2.0000e-02 eta: 1 day, 4:57:13 time: 0.3222 data_time: 0.0207 memory: 5826 grad_norm: 3.9345 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.2148 loss: 3.2148 2022/10/07 08:22:15 - mmengine - INFO - Epoch(train) [5][160/2119] lr: 2.0000e-02 eta: 1 day, 4:57:09 time: 0.3404 data_time: 0.0225 memory: 5826 grad_norm: 3.8663 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.8535 loss: 2.8535 2022/10/07 08:22:22 - mmengine - INFO - Epoch(train) [5][180/2119] lr: 2.0000e-02 eta: 1 day, 4:56:44 time: 0.3110 data_time: 0.0205 memory: 5826 grad_norm: 3.8873 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0878 loss: 3.0878 2022/10/07 08:22:28 - mmengine - INFO - Epoch(train) [5][200/2119] lr: 2.0000e-02 eta: 1 day, 4:56:30 time: 0.3275 data_time: 0.0338 memory: 5826 grad_norm: 3.8747 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 3.0976 loss: 3.0976 2022/10/07 08:22:35 - mmengine - INFO - Epoch(train) [5][220/2119] lr: 2.0000e-02 eta: 1 day, 4:56:24 time: 0.3385 data_time: 0.0224 memory: 5826 grad_norm: 3.8715 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.0940 loss: 3.0940 2022/10/07 08:22:42 - mmengine - INFO - Epoch(train) [5][240/2119] lr: 2.0000e-02 eta: 1 day, 4:56:25 time: 0.3471 data_time: 0.0189 memory: 5826 grad_norm: 3.8802 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.1556 loss: 3.1556 2022/10/07 08:22:48 - mmengine - INFO - Epoch(train) [5][260/2119] lr: 2.0000e-02 eta: 1 day, 4:55:59 time: 0.3105 data_time: 0.0254 memory: 5826 grad_norm: 3.8156 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.0313 loss: 3.0313 2022/10/07 08:22:55 - mmengine - INFO - Epoch(train) [5][280/2119] lr: 2.0000e-02 eta: 1 day, 4:56:10 time: 0.3618 data_time: 0.0181 memory: 5826 grad_norm: 3.8430 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.1570 loss: 3.1570 2022/10/07 08:23:02 - mmengine - INFO - Epoch(train) [5][300/2119] lr: 2.0000e-02 eta: 1 day, 4:55:42 time: 0.3069 data_time: 0.0250 memory: 5826 grad_norm: 3.8893 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.0088 loss: 3.0088 2022/10/07 08:23:09 - mmengine - INFO - Epoch(train) [5][320/2119] lr: 2.0000e-02 eta: 1 day, 4:55:44 time: 0.3487 data_time: 0.0251 memory: 5826 grad_norm: 3.9503 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0951 loss: 3.0951 2022/10/07 08:23:15 - mmengine - INFO - Epoch(train) [5][340/2119] lr: 2.0000e-02 eta: 1 day, 4:55:33 time: 0.3313 data_time: 0.0239 memory: 5826 grad_norm: 3.8834 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.1843 loss: 3.1843 2022/10/07 08:23:22 - mmengine - INFO - Epoch(train) [5][360/2119] lr: 2.0000e-02 eta: 1 day, 4:55:23 time: 0.3316 data_time: 0.0248 memory: 5826 grad_norm: 3.8536 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0665 loss: 3.0665 2022/10/07 08:23:28 - mmengine - INFO - Epoch(train) [5][380/2119] lr: 2.0000e-02 eta: 1 day, 4:54:59 time: 0.3124 data_time: 0.0224 memory: 5826 grad_norm: 3.9156 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9438 loss: 2.9438 2022/10/07 08:23:35 - mmengine - INFO - Epoch(train) [5][400/2119] lr: 2.0000e-02 eta: 1 day, 4:55:06 time: 0.3578 data_time: 0.0232 memory: 5826 grad_norm: 3.8448 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.2184 loss: 3.2184 2022/10/07 08:23:41 - mmengine - INFO - Epoch(train) [5][420/2119] lr: 2.0000e-02 eta: 1 day, 4:54:34 time: 0.3005 data_time: 0.0221 memory: 5826 grad_norm: 3.8383 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 3.1168 loss: 3.1168 2022/10/07 08:23:49 - mmengine - INFO - Epoch(train) [5][440/2119] lr: 2.0000e-02 eta: 1 day, 4:54:48 time: 0.3656 data_time: 0.0218 memory: 5826 grad_norm: 3.9077 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0775 loss: 3.0775 2022/10/07 08:23:55 - mmengine - INFO - Epoch(train) [5][460/2119] lr: 2.0000e-02 eta: 1 day, 4:54:15 time: 0.2993 data_time: 0.0189 memory: 5826 grad_norm: 3.8264 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2229 loss: 3.2229 2022/10/07 08:24:01 - mmengine - INFO - Epoch(train) [5][480/2119] lr: 2.0000e-02 eta: 1 day, 4:53:51 time: 0.3123 data_time: 0.0235 memory: 5826 grad_norm: 3.8439 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.3210 loss: 3.3210 2022/10/07 08:24:07 - mmengine - INFO - Epoch(train) [5][500/2119] lr: 2.0000e-02 eta: 1 day, 4:53:29 time: 0.3145 data_time: 0.0213 memory: 5826 grad_norm: 3.8259 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0091 loss: 3.0091 2022/10/07 08:24:14 - mmengine - INFO - Epoch(train) [5][520/2119] lr: 2.0000e-02 eta: 1 day, 4:53:31 time: 0.3488 data_time: 0.0237 memory: 5826 grad_norm: 3.8006 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 3.2387 loss: 3.2387 2022/10/07 08:24:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 08:24:20 - mmengine - INFO - Epoch(train) [5][540/2119] lr: 2.0000e-02 eta: 1 day, 4:53:09 time: 0.3143 data_time: 0.0242 memory: 5826 grad_norm: 3.7938 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.2251 loss: 3.2251 2022/10/07 08:24:28 - mmengine - INFO - Epoch(train) [5][560/2119] lr: 2.0000e-02 eta: 1 day, 4:53:32 time: 0.3807 data_time: 0.0245 memory: 5826 grad_norm: 3.8742 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 3.2245 loss: 3.2245 2022/10/07 08:24:34 - mmengine - INFO - Epoch(train) [5][580/2119] lr: 2.0000e-02 eta: 1 day, 4:53:08 time: 0.3121 data_time: 0.0227 memory: 5826 grad_norm: 3.8002 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.1282 loss: 3.1282 2022/10/07 08:24:41 - mmengine - INFO - Epoch(train) [5][600/2119] lr: 2.0000e-02 eta: 1 day, 4:52:57 time: 0.3306 data_time: 0.0234 memory: 5826 grad_norm: 3.7550 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0195 loss: 3.0195 2022/10/07 08:24:47 - mmengine - INFO - Epoch(train) [5][620/2119] lr: 2.0000e-02 eta: 1 day, 4:52:49 time: 0.3341 data_time: 0.0225 memory: 5826 grad_norm: 3.7855 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0092 loss: 3.0092 2022/10/07 08:24:56 - mmengine - INFO - Epoch(train) [5][640/2119] lr: 2.0000e-02 eta: 1 day, 4:53:56 time: 0.4452 data_time: 0.0221 memory: 5826 grad_norm: 3.8486 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.0724 loss: 3.0724 2022/10/07 08:25:03 - mmengine - INFO - Epoch(train) [5][660/2119] lr: 2.0000e-02 eta: 1 day, 4:53:34 time: 0.3145 data_time: 0.0240 memory: 5826 grad_norm: 3.8230 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0853 loss: 3.0853 2022/10/07 08:25:09 - mmengine - INFO - Epoch(train) [5][680/2119] lr: 2.0000e-02 eta: 1 day, 4:53:11 time: 0.3139 data_time: 0.0251 memory: 5826 grad_norm: 3.8192 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.1399 loss: 3.1399 2022/10/07 08:25:16 - mmengine - INFO - Epoch(train) [5][700/2119] lr: 2.0000e-02 eta: 1 day, 4:53:23 time: 0.3639 data_time: 0.0222 memory: 5826 grad_norm: 3.7943 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.2851 loss: 3.2851 2022/10/07 08:25:23 - mmengine - INFO - Epoch(train) [5][720/2119] lr: 2.0000e-02 eta: 1 day, 4:53:27 time: 0.3524 data_time: 0.0214 memory: 5826 grad_norm: 3.7427 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9571 loss: 2.9571 2022/10/07 08:25:29 - mmengine - INFO - Epoch(train) [5][740/2119] lr: 2.0000e-02 eta: 1 day, 4:52:58 time: 0.3037 data_time: 0.0255 memory: 5826 grad_norm: 3.8387 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.1872 loss: 3.1872 2022/10/07 08:25:36 - mmengine - INFO - Epoch(train) [5][760/2119] lr: 2.0000e-02 eta: 1 day, 4:52:48 time: 0.3330 data_time: 0.0197 memory: 5826 grad_norm: 3.7545 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0537 loss: 3.0537 2022/10/07 08:25:42 - mmengine - INFO - Epoch(train) [5][780/2119] lr: 2.0000e-02 eta: 1 day, 4:52:18 time: 0.3018 data_time: 0.0261 memory: 5826 grad_norm: 3.8275 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.1759 loss: 3.1759 2022/10/07 08:25:48 - mmengine - INFO - Epoch(train) [5][800/2119] lr: 2.0000e-02 eta: 1 day, 4:51:58 time: 0.3175 data_time: 0.0232 memory: 5826 grad_norm: 3.8410 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0506 loss: 3.0506 2022/10/07 08:25:55 - mmengine - INFO - Epoch(train) [5][820/2119] lr: 2.0000e-02 eta: 1 day, 4:51:55 time: 0.3411 data_time: 0.0274 memory: 5826 grad_norm: 3.7530 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 3.0026 loss: 3.0026 2022/10/07 08:26:02 - mmengine - INFO - Epoch(train) [5][840/2119] lr: 2.0000e-02 eta: 1 day, 4:52:02 time: 0.3574 data_time: 0.0180 memory: 5826 grad_norm: 3.7786 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0709 loss: 3.0709 2022/10/07 08:26:09 - mmengine - INFO - Epoch(train) [5][860/2119] lr: 2.0000e-02 eta: 1 day, 4:51:48 time: 0.3271 data_time: 0.0230 memory: 5826 grad_norm: 3.7274 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.2165 loss: 3.2165 2022/10/07 08:26:16 - mmengine - INFO - Epoch(train) [5][880/2119] lr: 2.0000e-02 eta: 1 day, 4:51:40 time: 0.3335 data_time: 0.0227 memory: 5826 grad_norm: 3.7663 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 3.0768 loss: 3.0768 2022/10/07 08:26:22 - mmengine - INFO - Epoch(train) [5][900/2119] lr: 2.0000e-02 eta: 1 day, 4:51:27 time: 0.3279 data_time: 0.0278 memory: 5826 grad_norm: 3.7998 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.1283 loss: 3.1283 2022/10/07 08:26:29 - mmengine - INFO - Epoch(train) [5][920/2119] lr: 2.0000e-02 eta: 1 day, 4:51:35 time: 0.3596 data_time: 0.0235 memory: 5826 grad_norm: 3.8098 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9861 loss: 2.9861 2022/10/07 08:26:36 - mmengine - INFO - Epoch(train) [5][940/2119] lr: 2.0000e-02 eta: 1 day, 4:51:22 time: 0.3268 data_time: 0.0222 memory: 5826 grad_norm: 3.7324 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 3.0837 loss: 3.0837 2022/10/07 08:26:43 - mmengine - INFO - Epoch(train) [5][960/2119] lr: 2.0000e-02 eta: 1 day, 4:51:15 time: 0.3364 data_time: 0.0247 memory: 5826 grad_norm: 3.7950 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7926 loss: 2.7926 2022/10/07 08:26:49 - mmengine - INFO - Epoch(train) [5][980/2119] lr: 2.0000e-02 eta: 1 day, 4:51:08 time: 0.3371 data_time: 0.0228 memory: 5826 grad_norm: 3.7507 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 3.2780 loss: 3.2780 2022/10/07 08:26:56 - mmengine - INFO - Epoch(train) [5][1000/2119] lr: 2.0000e-02 eta: 1 day, 4:51:10 time: 0.3496 data_time: 0.0215 memory: 5826 grad_norm: 3.7982 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0732 loss: 3.0732 2022/10/07 08:27:03 - mmengine - INFO - Epoch(train) [5][1020/2119] lr: 2.0000e-02 eta: 1 day, 4:50:54 time: 0.3227 data_time: 0.0190 memory: 5826 grad_norm: 3.8043 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.3307 loss: 3.3307 2022/10/07 08:27:09 - mmengine - INFO - Epoch(train) [5][1040/2119] lr: 2.0000e-02 eta: 1 day, 4:50:44 time: 0.3320 data_time: 0.0204 memory: 5826 grad_norm: 3.7437 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.2857 loss: 3.2857 2022/10/07 08:27:16 - mmengine - INFO - Epoch(train) [5][1060/2119] lr: 2.0000e-02 eta: 1 day, 4:50:36 time: 0.3351 data_time: 0.0201 memory: 5826 grad_norm: 3.7753 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1651 loss: 3.1651 2022/10/07 08:27:22 - mmengine - INFO - Epoch(train) [5][1080/2119] lr: 2.0000e-02 eta: 1 day, 4:49:57 time: 0.2862 data_time: 0.0290 memory: 5826 grad_norm: 3.7635 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0143 loss: 3.0143 2022/10/07 08:27:30 - mmengine - INFO - Epoch(train) [5][1100/2119] lr: 2.0000e-02 eta: 1 day, 4:50:44 time: 0.4207 data_time: 0.1525 memory: 5826 grad_norm: 3.7800 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.0760 loss: 3.0760 2022/10/07 08:27:37 - mmengine - INFO - Epoch(train) [5][1120/2119] lr: 2.0000e-02 eta: 1 day, 4:50:24 time: 0.3152 data_time: 0.0231 memory: 5826 grad_norm: 3.7344 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.1933 loss: 3.1933 2022/10/07 08:27:44 - mmengine - INFO - Epoch(train) [5][1140/2119] lr: 2.0000e-02 eta: 1 day, 4:50:27 time: 0.3518 data_time: 0.0219 memory: 5826 grad_norm: 3.7710 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9172 loss: 2.9172 2022/10/07 08:27:50 - mmengine - INFO - Epoch(train) [5][1160/2119] lr: 2.0000e-02 eta: 1 day, 4:50:13 time: 0.3262 data_time: 0.0263 memory: 5826 grad_norm: 3.8809 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8514 loss: 2.8514 2022/10/07 08:27:57 - mmengine - INFO - Epoch(train) [5][1180/2119] lr: 2.0000e-02 eta: 1 day, 4:50:05 time: 0.3342 data_time: 0.0221 memory: 5826 grad_norm: 3.8239 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.0564 loss: 3.0564 2022/10/07 08:28:03 - mmengine - INFO - Epoch(train) [5][1200/2119] lr: 2.0000e-02 eta: 1 day, 4:49:56 time: 0.3337 data_time: 0.0221 memory: 5826 grad_norm: 3.7336 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9452 loss: 2.9452 2022/10/07 08:28:10 - mmengine - INFO - Epoch(train) [5][1220/2119] lr: 2.0000e-02 eta: 1 day, 4:49:39 time: 0.3215 data_time: 0.0275 memory: 5826 grad_norm: 3.7645 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8816 loss: 2.8816 2022/10/07 08:28:16 - mmengine - INFO - Epoch(train) [5][1240/2119] lr: 2.0000e-02 eta: 1 day, 4:49:21 time: 0.3182 data_time: 0.0232 memory: 5826 grad_norm: 3.7567 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0302 loss: 3.0302 2022/10/07 08:28:22 - mmengine - INFO - Epoch(train) [5][1260/2119] lr: 2.0000e-02 eta: 1 day, 4:48:52 time: 0.3014 data_time: 0.0248 memory: 5826 grad_norm: 3.7274 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1164 loss: 3.1164 2022/10/07 08:28:29 - mmengine - INFO - Epoch(train) [5][1280/2119] lr: 2.0000e-02 eta: 1 day, 4:48:34 time: 0.3184 data_time: 0.0268 memory: 5826 grad_norm: 3.7898 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.2567 loss: 3.2567 2022/10/07 08:28:36 - mmengine - INFO - Epoch(train) [5][1300/2119] lr: 2.0000e-02 eta: 1 day, 4:48:32 time: 0.3441 data_time: 0.0220 memory: 5826 grad_norm: 3.6932 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.2383 loss: 3.2383 2022/10/07 08:28:42 - mmengine - INFO - Epoch(train) [5][1320/2119] lr: 2.0000e-02 eta: 1 day, 4:48:19 time: 0.3271 data_time: 0.0236 memory: 5826 grad_norm: 3.7599 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8461 loss: 2.8461 2022/10/07 08:28:49 - mmengine - INFO - Epoch(train) [5][1340/2119] lr: 2.0000e-02 eta: 1 day, 4:48:16 time: 0.3432 data_time: 0.0227 memory: 5826 grad_norm: 3.7315 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0593 loss: 3.0593 2022/10/07 08:28:56 - mmengine - INFO - Epoch(train) [5][1360/2119] lr: 2.0000e-02 eta: 1 day, 4:48:21 time: 0.3547 data_time: 0.0311 memory: 5826 grad_norm: 3.8238 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9328 loss: 2.9328 2022/10/07 08:29:02 - mmengine - INFO - Epoch(train) [5][1380/2119] lr: 2.0000e-02 eta: 1 day, 4:47:59 time: 0.3119 data_time: 0.0262 memory: 5826 grad_norm: 3.6529 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.9950 loss: 2.9950 2022/10/07 08:29:09 - mmengine - INFO - Epoch(train) [5][1400/2119] lr: 2.0000e-02 eta: 1 day, 4:47:42 time: 0.3212 data_time: 0.0204 memory: 5826 grad_norm: 3.7447 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9717 loss: 2.9717 2022/10/07 08:29:15 - mmengine - INFO - Epoch(train) [5][1420/2119] lr: 2.0000e-02 eta: 1 day, 4:47:16 time: 0.3058 data_time: 0.0230 memory: 5826 grad_norm: 3.7194 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.0475 loss: 3.0475 2022/10/07 08:29:22 - mmengine - INFO - Epoch(train) [5][1440/2119] lr: 2.0000e-02 eta: 1 day, 4:47:25 time: 0.3610 data_time: 0.0207 memory: 5826 grad_norm: 3.7314 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.2045 loss: 3.2045 2022/10/07 08:29:28 - mmengine - INFO - Epoch(train) [5][1460/2119] lr: 2.0000e-02 eta: 1 day, 4:46:58 time: 0.3037 data_time: 0.0269 memory: 5826 grad_norm: 3.7361 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9182 loss: 2.9182 2022/10/07 08:29:35 - mmengine - INFO - Epoch(train) [5][1480/2119] lr: 2.0000e-02 eta: 1 day, 4:47:01 time: 0.3526 data_time: 0.0257 memory: 5826 grad_norm: 3.7694 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.3229 loss: 3.3229 2022/10/07 08:29:41 - mmengine - INFO - Epoch(train) [5][1500/2119] lr: 2.0000e-02 eta: 1 day, 4:46:40 time: 0.3136 data_time: 0.0217 memory: 5826 grad_norm: 3.7319 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8783 loss: 2.8783 2022/10/07 08:29:49 - mmengine - INFO - Epoch(train) [5][1520/2119] lr: 2.0000e-02 eta: 1 day, 4:46:46 time: 0.3572 data_time: 0.0230 memory: 5826 grad_norm: 3.6929 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 3.0148 loss: 3.0148 2022/10/07 08:29:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 08:29:55 - mmengine - INFO - Epoch(train) [5][1540/2119] lr: 2.0000e-02 eta: 1 day, 4:46:25 time: 0.3127 data_time: 0.0279 memory: 5826 grad_norm: 3.7625 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.2746 loss: 3.2746 2022/10/07 08:30:03 - mmengine - INFO - Epoch(train) [5][1560/2119] lr: 2.0000e-02 eta: 1 day, 4:46:49 time: 0.3863 data_time: 0.0203 memory: 5826 grad_norm: 3.7125 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0451 loss: 3.0451 2022/10/07 08:30:10 - mmengine - INFO - Epoch(train) [5][1580/2119] lr: 2.0000e-02 eta: 1 day, 4:47:00 time: 0.3669 data_time: 0.0224 memory: 5826 grad_norm: 3.7682 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0199 loss: 3.0199 2022/10/07 08:30:17 - mmengine - INFO - Epoch(train) [5][1600/2119] lr: 2.0000e-02 eta: 1 day, 4:47:15 time: 0.3723 data_time: 0.0210 memory: 5826 grad_norm: 3.7201 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1049 loss: 3.1049 2022/10/07 08:30:24 - mmengine - INFO - Epoch(train) [5][1620/2119] lr: 2.0000e-02 eta: 1 day, 4:47:15 time: 0.3467 data_time: 0.0219 memory: 5826 grad_norm: 3.7556 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0198 loss: 3.0198 2022/10/07 08:30:30 - mmengine - INFO - Epoch(train) [5][1640/2119] lr: 2.0000e-02 eta: 1 day, 4:46:41 time: 0.2919 data_time: 0.0213 memory: 5826 grad_norm: 3.7274 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9565 loss: 2.9565 2022/10/07 08:30:37 - mmengine - INFO - Epoch(train) [5][1660/2119] lr: 2.0000e-02 eta: 1 day, 4:46:24 time: 0.3196 data_time: 0.0263 memory: 5826 grad_norm: 3.7017 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 3.0992 loss: 3.0992 2022/10/07 08:30:43 - mmengine - INFO - Epoch(train) [5][1680/2119] lr: 2.0000e-02 eta: 1 day, 4:46:10 time: 0.3258 data_time: 0.0182 memory: 5826 grad_norm: 3.7702 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 3.0114 loss: 3.0114 2022/10/07 08:30:49 - mmengine - INFO - Epoch(train) [5][1700/2119] lr: 2.0000e-02 eta: 1 day, 4:45:51 time: 0.3157 data_time: 0.0203 memory: 5826 grad_norm: 3.7323 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.2176 loss: 3.2176 2022/10/07 08:30:57 - mmengine - INFO - Epoch(train) [5][1720/2119] lr: 2.0000e-02 eta: 1 day, 4:46:03 time: 0.3676 data_time: 0.0205 memory: 5826 grad_norm: 3.6693 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.0519 loss: 3.0519 2022/10/07 08:31:03 - mmengine - INFO - Epoch(train) [5][1740/2119] lr: 2.0000e-02 eta: 1 day, 4:45:47 time: 0.3216 data_time: 0.0214 memory: 5826 grad_norm: 3.6688 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9486 loss: 2.9486 2022/10/07 08:31:10 - mmengine - INFO - Epoch(train) [5][1760/2119] lr: 2.0000e-02 eta: 1 day, 4:45:52 time: 0.3552 data_time: 0.0208 memory: 5826 grad_norm: 3.6503 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0478 loss: 3.0478 2022/10/07 08:31:17 - mmengine - INFO - Epoch(train) [5][1780/2119] lr: 2.0000e-02 eta: 1 day, 4:45:32 time: 0.3154 data_time: 0.0257 memory: 5826 grad_norm: 3.7316 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7312 loss: 2.7312 2022/10/07 08:31:24 - mmengine - INFO - Epoch(train) [5][1800/2119] lr: 2.0000e-02 eta: 1 day, 4:45:32 time: 0.3468 data_time: 0.0205 memory: 5826 grad_norm: 3.7275 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 3.1905 loss: 3.1905 2022/10/07 08:31:30 - mmengine - INFO - Epoch(train) [5][1820/2119] lr: 2.0000e-02 eta: 1 day, 4:45:15 time: 0.3203 data_time: 0.0177 memory: 5826 grad_norm: 3.6948 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 3.0867 loss: 3.0867 2022/10/07 08:31:38 - mmengine - INFO - Epoch(train) [5][1840/2119] lr: 2.0000e-02 eta: 1 day, 4:45:40 time: 0.3897 data_time: 0.0181 memory: 5826 grad_norm: 3.6509 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9867 loss: 2.9867 2022/10/07 08:31:45 - mmengine - INFO - Epoch(train) [5][1860/2119] lr: 2.0000e-02 eta: 1 day, 4:45:36 time: 0.3410 data_time: 0.0230 memory: 5826 grad_norm: 3.7636 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.0942 loss: 3.0942 2022/10/07 08:31:50 - mmengine - INFO - Epoch(train) [5][1880/2119] lr: 2.0000e-02 eta: 1 day, 4:44:46 time: 0.2642 data_time: 0.0235 memory: 5826 grad_norm: 3.7124 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.2810 loss: 3.2810 2022/10/07 08:31:57 - mmengine - INFO - Epoch(train) [5][1900/2119] lr: 2.0000e-02 eta: 1 day, 4:44:42 time: 0.3411 data_time: 0.0314 memory: 5826 grad_norm: 3.7509 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0768 loss: 3.0768 2022/10/07 08:32:03 - mmengine - INFO - Epoch(train) [5][1920/2119] lr: 2.0000e-02 eta: 1 day, 4:44:32 time: 0.3306 data_time: 0.0217 memory: 5826 grad_norm: 3.7496 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0264 loss: 3.0264 2022/10/07 08:32:10 - mmengine - INFO - Epoch(train) [5][1940/2119] lr: 2.0000e-02 eta: 1 day, 4:44:33 time: 0.3504 data_time: 0.0221 memory: 5826 grad_norm: 3.7439 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9040 loss: 2.9040 2022/10/07 08:32:17 - mmengine - INFO - Epoch(train) [5][1960/2119] lr: 2.0000e-02 eta: 1 day, 4:44:18 time: 0.3229 data_time: 0.0280 memory: 5826 grad_norm: 3.6751 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.9581 loss: 2.9581 2022/10/07 08:32:23 - mmengine - INFO - Epoch(train) [5][1980/2119] lr: 2.0000e-02 eta: 1 day, 4:44:03 time: 0.3223 data_time: 0.0260 memory: 5826 grad_norm: 3.7169 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0032 loss: 3.0032 2022/10/07 08:32:30 - mmengine - INFO - Epoch(train) [5][2000/2119] lr: 2.0000e-02 eta: 1 day, 4:43:56 time: 0.3356 data_time: 0.0212 memory: 5826 grad_norm: 3.7644 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9489 loss: 2.9489 2022/10/07 08:32:37 - mmengine - INFO - Epoch(train) [5][2020/2119] lr: 2.0000e-02 eta: 1 day, 4:44:14 time: 0.3785 data_time: 0.0299 memory: 5826 grad_norm: 3.6728 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9934 loss: 2.9934 2022/10/07 08:32:43 - mmengine - INFO - Epoch(train) [5][2040/2119] lr: 2.0000e-02 eta: 1 day, 4:43:39 time: 0.2889 data_time: 0.0184 memory: 5826 grad_norm: 3.7157 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.1618 loss: 3.1618 2022/10/07 08:32:50 - mmengine - INFO - Epoch(train) [5][2060/2119] lr: 2.0000e-02 eta: 1 day, 4:43:30 time: 0.3320 data_time: 0.0265 memory: 5826 grad_norm: 3.7045 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8548 loss: 2.8548 2022/10/07 08:32:57 - mmengine - INFO - Epoch(train) [5][2080/2119] lr: 2.0000e-02 eta: 1 day, 4:43:26 time: 0.3411 data_time: 0.0270 memory: 5826 grad_norm: 3.7064 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0112 loss: 3.0112 2022/10/07 08:33:04 - mmengine - INFO - Epoch(train) [5][2100/2119] lr: 2.0000e-02 eta: 1 day, 4:43:26 time: 0.3480 data_time: 0.0194 memory: 5826 grad_norm: 3.7411 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8585 loss: 2.8585 2022/10/07 08:33:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 08:33:09 - mmengine - INFO - Epoch(train) [5][2119/2119] lr: 2.0000e-02 eta: 1 day, 4:43:26 time: 0.2649 data_time: 0.0201 memory: 5826 grad_norm: 3.7353 top1_acc: 0.2000 top5_acc: 0.4000 loss_cls: 3.0436 loss: 3.0436 2022/10/07 08:34:05 - mmengine - INFO - Epoch(val) [5][20/137] eta: 0:05:29 time: 2.8177 data_time: 2.7471 memory: 1241 2022/10/07 08:34:11 - mmengine - INFO - Epoch(val) [5][40/137] eta: 0:00:30 time: 0.3146 data_time: 0.2476 memory: 1241 2022/10/07 08:34:18 - mmengine - INFO - Epoch(val) [5][60/137] eta: 0:00:24 time: 0.3189 data_time: 0.2526 memory: 1241 2022/10/07 08:34:22 - mmengine - INFO - Epoch(val) [5][80/137] eta: 0:00:13 time: 0.2358 data_time: 0.1713 memory: 1241 2022/10/07 08:34:30 - mmengine - INFO - Epoch(val) [5][100/137] eta: 0:00:14 time: 0.3907 data_time: 0.3232 memory: 1241 2022/10/07 08:34:35 - mmengine - INFO - Epoch(val) [5][120/137] eta: 0:00:04 time: 0.2452 data_time: 0.1784 memory: 1241 2022/10/07 08:34:46 - mmengine - INFO - Epoch(val) [5][137/137] acc/top1: 0.4052 acc/top5: 0.6515 acc/mean1: 0.4050 2022/10/07 08:34:50 - mmengine - INFO - The best checkpoint with 0.4052 acc/top1 at 5 epoch is saved to best_acc/top1_epoch_5.pth. 2022/10/07 08:34:57 - mmengine - INFO - Epoch(train) [6][20/2119] lr: 2.4000e-02 eta: 1 day, 4:40:28 time: 0.3720 data_time: 0.1773 memory: 5826 grad_norm: 3.6841 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9266 loss: 2.9266 2022/10/07 08:35:04 - mmengine - INFO - Epoch(train) [6][40/2119] lr: 2.4000e-02 eta: 1 day, 4:40:12 time: 0.3191 data_time: 0.0920 memory: 5826 grad_norm: 3.7157 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9575 loss: 2.9575 2022/10/07 08:35:10 - mmengine - INFO - Epoch(train) [6][60/2119] lr: 2.4000e-02 eta: 1 day, 4:39:51 time: 0.3116 data_time: 0.0785 memory: 5826 grad_norm: 3.6887 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.1212 loss: 3.1212 2022/10/07 08:35:16 - mmengine - INFO - Epoch(train) [6][80/2119] lr: 2.4000e-02 eta: 1 day, 4:39:38 time: 0.3259 data_time: 0.0688 memory: 5826 grad_norm: 3.6856 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9686 loss: 2.9686 2022/10/07 08:35:24 - mmengine - INFO - Epoch(train) [6][100/2119] lr: 2.4000e-02 eta: 1 day, 4:39:43 time: 0.3548 data_time: 0.0235 memory: 5826 grad_norm: 3.6960 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0435 loss: 3.0435 2022/10/07 08:35:31 - mmengine - INFO - Epoch(train) [6][120/2119] lr: 2.4000e-02 eta: 1 day, 4:39:45 time: 0.3517 data_time: 0.0178 memory: 5826 grad_norm: 3.6659 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.1153 loss: 3.1153 2022/10/07 08:35:37 - mmengine - INFO - Epoch(train) [6][140/2119] lr: 2.4000e-02 eta: 1 day, 4:39:23 time: 0.3100 data_time: 0.0263 memory: 5826 grad_norm: 3.6401 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.0984 loss: 3.0984 2022/10/07 08:35:44 - mmengine - INFO - Epoch(train) [6][160/2119] lr: 2.4000e-02 eta: 1 day, 4:39:27 time: 0.3544 data_time: 0.0193 memory: 5826 grad_norm: 3.6923 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9518 loss: 2.9518 2022/10/07 08:35:50 - mmengine - INFO - Epoch(train) [6][180/2119] lr: 2.4000e-02 eta: 1 day, 4:38:54 time: 0.2894 data_time: 0.0187 memory: 5826 grad_norm: 3.6334 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.4477 loss: 3.4477 2022/10/07 08:35:57 - mmengine - INFO - Epoch(train) [6][200/2119] lr: 2.4000e-02 eta: 1 day, 4:39:14 time: 0.3828 data_time: 0.0329 memory: 5826 grad_norm: 3.6839 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.2087 loss: 3.2087 2022/10/07 08:36:04 - mmengine - INFO - Epoch(train) [6][220/2119] lr: 2.4000e-02 eta: 1 day, 4:38:56 time: 0.3167 data_time: 0.0227 memory: 5826 grad_norm: 3.6330 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 3.1205 loss: 3.1205 2022/10/07 08:36:10 - mmengine - INFO - Epoch(train) [6][240/2119] lr: 2.4000e-02 eta: 1 day, 4:38:45 time: 0.3278 data_time: 0.0174 memory: 5826 grad_norm: 3.6844 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 3.0243 loss: 3.0243 2022/10/07 08:36:18 - mmengine - INFO - Epoch(train) [6][260/2119] lr: 2.4000e-02 eta: 1 day, 4:39:01 time: 0.3761 data_time: 0.0229 memory: 5826 grad_norm: 3.6600 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8659 loss: 2.8659 2022/10/07 08:36:24 - mmengine - INFO - Epoch(train) [6][280/2119] lr: 2.4000e-02 eta: 1 day, 4:38:44 time: 0.3174 data_time: 0.0289 memory: 5826 grad_norm: 3.6758 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0826 loss: 3.0826 2022/10/07 08:36:30 - mmengine - INFO - Epoch(train) [6][300/2119] lr: 2.4000e-02 eta: 1 day, 4:38:12 time: 0.2910 data_time: 0.0268 memory: 5826 grad_norm: 3.6194 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0858 loss: 3.0858 2022/10/07 08:36:37 - mmengine - INFO - Epoch(train) [6][320/2119] lr: 2.4000e-02 eta: 1 day, 4:38:19 time: 0.3614 data_time: 0.0269 memory: 5826 grad_norm: 3.6491 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9304 loss: 2.9304 2022/10/07 08:36:43 - mmengine - INFO - Epoch(train) [6][340/2119] lr: 2.4000e-02 eta: 1 day, 4:37:46 time: 0.2880 data_time: 0.0222 memory: 5826 grad_norm: 3.6729 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.0493 loss: 3.0493 2022/10/07 08:36:50 - mmengine - INFO - Epoch(train) [6][360/2119] lr: 2.4000e-02 eta: 1 day, 4:37:45 time: 0.3469 data_time: 0.0214 memory: 5826 grad_norm: 3.6525 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1587 loss: 3.1587 2022/10/07 08:36:57 - mmengine - INFO - Epoch(train) [6][380/2119] lr: 2.4000e-02 eta: 1 day, 4:37:41 time: 0.3397 data_time: 0.0214 memory: 5826 grad_norm: 3.7038 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 3.0433 loss: 3.0433 2022/10/07 08:37:03 - mmengine - INFO - Epoch(train) [6][400/2119] lr: 2.4000e-02 eta: 1 day, 4:37:22 time: 0.3136 data_time: 0.0231 memory: 5826 grad_norm: 3.5751 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 3.0036 loss: 3.0036 2022/10/07 08:37:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 08:37:09 - mmengine - INFO - Epoch(train) [6][420/2119] lr: 2.4000e-02 eta: 1 day, 4:37:09 time: 0.3245 data_time: 0.0230 memory: 5826 grad_norm: 3.5987 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9799 loss: 2.9799 2022/10/07 08:37:17 - mmengine - INFO - Epoch(train) [6][440/2119] lr: 2.4000e-02 eta: 1 day, 4:37:17 time: 0.3620 data_time: 0.0190 memory: 5826 grad_norm: 3.6481 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1800 loss: 3.1800 2022/10/07 08:37:23 - mmengine - INFO - Epoch(train) [6][460/2119] lr: 2.4000e-02 eta: 1 day, 4:36:52 time: 0.3034 data_time: 0.0188 memory: 5826 grad_norm: 3.6355 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.2466 loss: 3.2466 2022/10/07 08:37:30 - mmengine - INFO - Epoch(train) [6][480/2119] lr: 2.4000e-02 eta: 1 day, 4:36:55 time: 0.3535 data_time: 0.0226 memory: 5826 grad_norm: 3.6032 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6432 loss: 2.6432 2022/10/07 08:37:36 - mmengine - INFO - Epoch(train) [6][500/2119] lr: 2.4000e-02 eta: 1 day, 4:36:32 time: 0.3067 data_time: 0.0220 memory: 5826 grad_norm: 3.5459 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9495 loss: 2.9495 2022/10/07 08:37:43 - mmengine - INFO - Epoch(train) [6][520/2119] lr: 2.4000e-02 eta: 1 day, 4:36:45 time: 0.3707 data_time: 0.0211 memory: 5826 grad_norm: 3.6173 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9997 loss: 2.9997 2022/10/07 08:37:49 - mmengine - INFO - Epoch(train) [6][540/2119] lr: 2.4000e-02 eta: 1 day, 4:36:07 time: 0.2800 data_time: 0.0161 memory: 5826 grad_norm: 3.6093 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 3.0902 loss: 3.0902 2022/10/07 08:37:56 - mmengine - INFO - Epoch(train) [6][560/2119] lr: 2.4000e-02 eta: 1 day, 4:36:22 time: 0.3746 data_time: 0.0200 memory: 5826 grad_norm: 3.6091 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.0346 loss: 3.0346 2022/10/07 08:38:02 - mmengine - INFO - Epoch(train) [6][580/2119] lr: 2.4000e-02 eta: 1 day, 4:35:53 time: 0.2947 data_time: 0.0226 memory: 5826 grad_norm: 3.5734 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8063 loss: 2.8063 2022/10/07 08:38:09 - mmengine - INFO - Epoch(train) [6][600/2119] lr: 2.4000e-02 eta: 1 day, 4:35:48 time: 0.3400 data_time: 0.0258 memory: 5826 grad_norm: 3.6567 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0839 loss: 3.0839 2022/10/07 08:38:16 - mmengine - INFO - Epoch(train) [6][620/2119] lr: 2.4000e-02 eta: 1 day, 4:35:41 time: 0.3340 data_time: 0.0356 memory: 5826 grad_norm: 3.5947 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.3009 loss: 3.3009 2022/10/07 08:38:22 - mmengine - INFO - Epoch(train) [6][640/2119] lr: 2.4000e-02 eta: 1 day, 4:35:22 time: 0.3135 data_time: 0.0271 memory: 5826 grad_norm: 3.6628 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 3.1251 loss: 3.1251 2022/10/07 08:38:29 - mmengine - INFO - Epoch(train) [6][660/2119] lr: 2.4000e-02 eta: 1 day, 4:35:08 time: 0.3228 data_time: 0.0188 memory: 5826 grad_norm: 3.6366 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.1734 loss: 3.1734 2022/10/07 08:38:35 - mmengine - INFO - Epoch(train) [6][680/2119] lr: 2.4000e-02 eta: 1 day, 4:34:58 time: 0.3299 data_time: 0.0279 memory: 5826 grad_norm: 3.5680 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0557 loss: 3.0557 2022/10/07 08:38:42 - mmengine - INFO - Epoch(train) [6][700/2119] lr: 2.4000e-02 eta: 1 day, 4:34:55 time: 0.3414 data_time: 0.0238 memory: 5826 grad_norm: 3.6051 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0647 loss: 3.0647 2022/10/07 08:38:49 - mmengine - INFO - Epoch(train) [6][720/2119] lr: 2.4000e-02 eta: 1 day, 4:34:49 time: 0.3367 data_time: 0.0207 memory: 5826 grad_norm: 3.6475 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.1196 loss: 3.1196 2022/10/07 08:38:56 - mmengine - INFO - Epoch(train) [6][740/2119] lr: 2.4000e-02 eta: 1 day, 4:34:48 time: 0.3469 data_time: 0.0169 memory: 5826 grad_norm: 3.6265 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8272 loss: 2.8272 2022/10/07 08:39:02 - mmengine - INFO - Epoch(train) [6][760/2119] lr: 2.4000e-02 eta: 1 day, 4:34:39 time: 0.3321 data_time: 0.0254 memory: 5826 grad_norm: 3.6102 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 3.2435 loss: 3.2435 2022/10/07 08:39:09 - mmengine - INFO - Epoch(train) [6][780/2119] lr: 2.4000e-02 eta: 1 day, 4:34:33 time: 0.3360 data_time: 0.0210 memory: 5826 grad_norm: 3.5554 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6221 loss: 2.6221 2022/10/07 08:39:16 - mmengine - INFO - Epoch(train) [6][800/2119] lr: 2.4000e-02 eta: 1 day, 4:34:35 time: 0.3528 data_time: 0.0246 memory: 5826 grad_norm: 3.5399 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9213 loss: 2.9213 2022/10/07 08:39:23 - mmengine - INFO - Epoch(train) [6][820/2119] lr: 2.4000e-02 eta: 1 day, 4:34:30 time: 0.3383 data_time: 0.0237 memory: 5826 grad_norm: 3.5450 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9899 loss: 2.9899 2022/10/07 08:39:29 - mmengine - INFO - Epoch(train) [6][840/2119] lr: 2.4000e-02 eta: 1 day, 4:34:01 time: 0.2936 data_time: 0.0315 memory: 5826 grad_norm: 3.5980 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1469 loss: 3.1469 2022/10/07 08:39:34 - mmengine - INFO - Epoch(train) [6][860/2119] lr: 2.4000e-02 eta: 1 day, 4:33:22 time: 0.2759 data_time: 0.0279 memory: 5826 grad_norm: 3.6536 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 3.0120 loss: 3.0120 2022/10/07 08:39:41 - mmengine - INFO - Epoch(train) [6][880/2119] lr: 2.4000e-02 eta: 1 day, 4:33:23 time: 0.3496 data_time: 0.0263 memory: 5826 grad_norm: 3.5883 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9923 loss: 2.9923 2022/10/07 08:39:48 - mmengine - INFO - Epoch(train) [6][900/2119] lr: 2.4000e-02 eta: 1 day, 4:33:14 time: 0.3313 data_time: 0.0245 memory: 5826 grad_norm: 3.5378 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9947 loss: 2.9947 2022/10/07 08:39:55 - mmengine - INFO - Epoch(train) [6][920/2119] lr: 2.4000e-02 eta: 1 day, 4:33:28 time: 0.3751 data_time: 0.0216 memory: 5826 grad_norm: 3.6139 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1046 loss: 3.1046 2022/10/07 08:40:02 - mmengine - INFO - Epoch(train) [6][940/2119] lr: 2.4000e-02 eta: 1 day, 4:33:21 time: 0.3352 data_time: 0.0253 memory: 5826 grad_norm: 3.5284 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9298 loss: 2.9298 2022/10/07 08:40:08 - mmengine - INFO - Epoch(train) [6][960/2119] lr: 2.4000e-02 eta: 1 day, 4:33:07 time: 0.3217 data_time: 0.0255 memory: 5826 grad_norm: 3.6195 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9791 loss: 2.9791 2022/10/07 08:40:15 - mmengine - INFO - Epoch(train) [6][980/2119] lr: 2.4000e-02 eta: 1 day, 4:32:46 time: 0.3074 data_time: 0.0291 memory: 5826 grad_norm: 3.6605 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.1328 loss: 3.1328 2022/10/07 08:40:22 - mmengine - INFO - Epoch(train) [6][1000/2119] lr: 2.4000e-02 eta: 1 day, 4:32:58 time: 0.3716 data_time: 0.0229 memory: 5826 grad_norm: 3.6309 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7620 loss: 2.7620 2022/10/07 08:40:28 - mmengine - INFO - Epoch(train) [6][1020/2119] lr: 2.4000e-02 eta: 1 day, 4:32:41 time: 0.3170 data_time: 0.0230 memory: 5826 grad_norm: 3.5796 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8882 loss: 2.8882 2022/10/07 08:40:35 - mmengine - INFO - Epoch(train) [6][1040/2119] lr: 2.4000e-02 eta: 1 day, 4:32:27 time: 0.3207 data_time: 0.0207 memory: 5826 grad_norm: 3.6317 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9616 loss: 2.9616 2022/10/07 08:40:41 - mmengine - INFO - Epoch(train) [6][1060/2119] lr: 2.4000e-02 eta: 1 day, 4:32:18 time: 0.3319 data_time: 0.0257 memory: 5826 grad_norm: 3.5360 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0983 loss: 3.0983 2022/10/07 08:40:48 - mmengine - INFO - Epoch(train) [6][1080/2119] lr: 2.4000e-02 eta: 1 day, 4:32:14 time: 0.3394 data_time: 0.0255 memory: 5826 grad_norm: 3.6078 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9028 loss: 2.9028 2022/10/07 08:40:55 - mmengine - INFO - Epoch(train) [6][1100/2119] lr: 2.4000e-02 eta: 1 day, 4:32:03 time: 0.3280 data_time: 0.0190 memory: 5826 grad_norm: 3.4899 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9674 loss: 2.9674 2022/10/07 08:41:06 - mmengine - INFO - Epoch(train) [6][1120/2119] lr: 2.4000e-02 eta: 1 day, 4:33:58 time: 0.5681 data_time: 0.2498 memory: 5826 grad_norm: 3.5473 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8712 loss: 2.8712 2022/10/07 08:41:12 - mmengine - INFO - Epoch(train) [6][1140/2119] lr: 2.4000e-02 eta: 1 day, 4:33:29 time: 0.2932 data_time: 0.0279 memory: 5826 grad_norm: 3.5517 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.1890 loss: 3.1890 2022/10/07 08:41:19 - mmengine - INFO - Epoch(train) [6][1160/2119] lr: 2.4000e-02 eta: 1 day, 4:33:40 time: 0.3708 data_time: 0.0209 memory: 5826 grad_norm: 3.5826 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1335 loss: 3.1335 2022/10/07 08:41:26 - mmengine - INFO - Epoch(train) [6][1180/2119] lr: 2.4000e-02 eta: 1 day, 4:33:24 time: 0.3173 data_time: 0.0233 memory: 5826 grad_norm: 3.5600 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7462 loss: 2.7462 2022/10/07 08:41:33 - mmengine - INFO - Epoch(train) [6][1200/2119] lr: 2.4000e-02 eta: 1 day, 4:33:23 time: 0.3477 data_time: 0.0358 memory: 5826 grad_norm: 3.5152 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 3.1356 loss: 3.1356 2022/10/07 08:41:40 - mmengine - INFO - Epoch(train) [6][1220/2119] lr: 2.4000e-02 eta: 1 day, 4:33:20 time: 0.3428 data_time: 0.0236 memory: 5826 grad_norm: 3.5829 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8851 loss: 2.8851 2022/10/07 08:41:46 - mmengine - INFO - Epoch(train) [6][1240/2119] lr: 2.4000e-02 eta: 1 day, 4:33:10 time: 0.3300 data_time: 0.0232 memory: 5826 grad_norm: 3.6011 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 3.0052 loss: 3.0052 2022/10/07 08:41:52 - mmengine - INFO - Epoch(train) [6][1260/2119] lr: 2.4000e-02 eta: 1 day, 4:32:33 time: 0.2760 data_time: 0.0274 memory: 5826 grad_norm: 3.5975 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.0984 loss: 3.0984 2022/10/07 08:41:59 - mmengine - INFO - Epoch(train) [6][1280/2119] lr: 2.4000e-02 eta: 1 day, 4:32:34 time: 0.3505 data_time: 0.0218 memory: 5826 grad_norm: 3.6113 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.1463 loss: 3.1463 2022/10/07 08:42:06 - mmengine - INFO - Epoch(train) [6][1300/2119] lr: 2.4000e-02 eta: 1 day, 4:32:34 time: 0.3488 data_time: 0.0181 memory: 5826 grad_norm: 3.5418 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.1057 loss: 3.1057 2022/10/07 08:42:12 - mmengine - INFO - Epoch(train) [6][1320/2119] lr: 2.4000e-02 eta: 1 day, 4:32:15 time: 0.3130 data_time: 0.0195 memory: 5826 grad_norm: 3.5512 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0579 loss: 3.0579 2022/10/07 08:42:19 - mmengine - INFO - Epoch(train) [6][1340/2119] lr: 2.4000e-02 eta: 1 day, 4:32:17 time: 0.3530 data_time: 0.0220 memory: 5826 grad_norm: 3.5046 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0988 loss: 3.0988 2022/10/07 08:42:25 - mmengine - INFO - Epoch(train) [6][1360/2119] lr: 2.4000e-02 eta: 1 day, 4:32:01 time: 0.3175 data_time: 0.0223 memory: 5826 grad_norm: 3.5668 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.8782 loss: 2.8782 2022/10/07 08:42:33 - mmengine - INFO - Epoch(train) [6][1380/2119] lr: 2.4000e-02 eta: 1 day, 4:32:05 time: 0.3574 data_time: 0.0185 memory: 5826 grad_norm: 3.5215 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.1207 loss: 3.1207 2022/10/07 08:42:39 - mmengine - INFO - Epoch(train) [6][1400/2119] lr: 2.4000e-02 eta: 1 day, 4:31:48 time: 0.3150 data_time: 0.0285 memory: 5826 grad_norm: 3.5603 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9831 loss: 2.9831 2022/10/07 08:42:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 08:42:46 - mmengine - INFO - Epoch(train) [6][1420/2119] lr: 2.4000e-02 eta: 1 day, 4:31:44 time: 0.3411 data_time: 0.0240 memory: 5826 grad_norm: 3.5483 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0489 loss: 3.0489 2022/10/07 08:42:53 - mmengine - INFO - Epoch(train) [6][1440/2119] lr: 2.4000e-02 eta: 1 day, 4:31:48 time: 0.3560 data_time: 0.0158 memory: 5826 grad_norm: 3.5449 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9289 loss: 2.9289 2022/10/07 08:42:59 - mmengine - INFO - Epoch(train) [6][1460/2119] lr: 2.4000e-02 eta: 1 day, 4:31:29 time: 0.3116 data_time: 0.0258 memory: 5826 grad_norm: 3.6447 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9672 loss: 2.9672 2022/10/07 08:43:06 - mmengine - INFO - Epoch(train) [6][1480/2119] lr: 2.4000e-02 eta: 1 day, 4:31:22 time: 0.3351 data_time: 0.0139 memory: 5826 grad_norm: 3.5765 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9570 loss: 2.9570 2022/10/07 08:43:12 - mmengine - INFO - Epoch(train) [6][1500/2119] lr: 2.4000e-02 eta: 1 day, 4:31:14 time: 0.3334 data_time: 0.0188 memory: 5826 grad_norm: 3.5696 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.2671 loss: 3.2671 2022/10/07 08:43:19 - mmengine - INFO - Epoch(train) [6][1520/2119] lr: 2.4000e-02 eta: 1 day, 4:31:17 time: 0.3550 data_time: 0.0218 memory: 5826 grad_norm: 3.5633 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 3.2422 loss: 3.2422 2022/10/07 08:43:25 - mmengine - INFO - Epoch(train) [6][1540/2119] lr: 2.4000e-02 eta: 1 day, 4:30:45 time: 0.2867 data_time: 0.0273 memory: 5826 grad_norm: 3.5201 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.1332 loss: 3.1332 2022/10/07 08:43:32 - mmengine - INFO - Epoch(train) [6][1560/2119] lr: 2.4000e-02 eta: 1 day, 4:30:32 time: 0.3240 data_time: 0.0248 memory: 5826 grad_norm: 3.5548 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9989 loss: 2.9989 2022/10/07 08:43:39 - mmengine - INFO - Epoch(train) [6][1580/2119] lr: 2.4000e-02 eta: 1 day, 4:30:50 time: 0.3839 data_time: 0.1158 memory: 5826 grad_norm: 3.5429 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9783 loss: 2.9783 2022/10/07 08:43:45 - mmengine - INFO - Epoch(train) [6][1600/2119] lr: 2.4000e-02 eta: 1 day, 4:30:12 time: 0.2745 data_time: 0.0155 memory: 5826 grad_norm: 3.5912 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8980 loss: 2.8980 2022/10/07 08:43:51 - mmengine - INFO - Epoch(train) [6][1620/2119] lr: 2.4000e-02 eta: 1 day, 4:30:02 time: 0.3274 data_time: 0.0231 memory: 5826 grad_norm: 3.5557 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8016 loss: 2.8016 2022/10/07 08:43:59 - mmengine - INFO - Epoch(train) [6][1640/2119] lr: 2.4000e-02 eta: 1 day, 4:30:20 time: 0.3869 data_time: 0.0171 memory: 5826 grad_norm: 3.5376 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7536 loss: 2.7536 2022/10/07 08:44:06 - mmengine - INFO - Epoch(train) [6][1660/2119] lr: 2.4000e-02 eta: 1 day, 4:30:09 time: 0.3262 data_time: 0.0321 memory: 5826 grad_norm: 3.5527 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.9015 loss: 2.9015 2022/10/07 08:44:13 - mmengine - INFO - Epoch(train) [6][1680/2119] lr: 2.4000e-02 eta: 1 day, 4:30:07 time: 0.3456 data_time: 0.0215 memory: 5826 grad_norm: 3.5974 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.8327 loss: 2.8327 2022/10/07 08:44:19 - mmengine - INFO - Epoch(train) [6][1700/2119] lr: 2.4000e-02 eta: 1 day, 4:29:42 time: 0.2979 data_time: 0.0203 memory: 5826 grad_norm: 3.5844 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9726 loss: 2.9726 2022/10/07 08:44:26 - mmengine - INFO - Epoch(train) [6][1720/2119] lr: 2.4000e-02 eta: 1 day, 4:29:41 time: 0.3475 data_time: 0.0213 memory: 5826 grad_norm: 3.4801 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.9890 loss: 2.9890 2022/10/07 08:44:33 - mmengine - INFO - Epoch(train) [6][1740/2119] lr: 2.4000e-02 eta: 1 day, 4:29:44 time: 0.3552 data_time: 0.0258 memory: 5826 grad_norm: 3.5245 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.1794 loss: 3.1794 2022/10/07 08:44:40 - mmengine - INFO - Epoch(train) [6][1760/2119] lr: 2.4000e-02 eta: 1 day, 4:30:04 time: 0.3904 data_time: 0.0180 memory: 5826 grad_norm: 3.5190 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9792 loss: 2.9792 2022/10/07 08:44:47 - mmengine - INFO - Epoch(train) [6][1780/2119] lr: 2.4000e-02 eta: 1 day, 4:29:47 time: 0.3152 data_time: 0.0289 memory: 5826 grad_norm: 3.5305 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9167 loss: 2.9167 2022/10/07 08:44:53 - mmengine - INFO - Epoch(train) [6][1800/2119] lr: 2.4000e-02 eta: 1 day, 4:29:34 time: 0.3235 data_time: 0.0258 memory: 5826 grad_norm: 3.5270 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0634 loss: 3.0634 2022/10/07 08:45:00 - mmengine - INFO - Epoch(train) [6][1820/2119] lr: 2.4000e-02 eta: 1 day, 4:29:25 time: 0.3305 data_time: 0.0210 memory: 5826 grad_norm: 3.5612 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.0233 loss: 3.0233 2022/10/07 08:45:07 - mmengine - INFO - Epoch(train) [6][1840/2119] lr: 2.4000e-02 eta: 1 day, 4:29:30 time: 0.3592 data_time: 0.0238 memory: 5826 grad_norm: 3.5660 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.1915 loss: 3.1915 2022/10/07 08:45:13 - mmengine - INFO - Epoch(train) [6][1860/2119] lr: 2.4000e-02 eta: 1 day, 4:29:02 time: 0.2933 data_time: 0.0202 memory: 5826 grad_norm: 3.5480 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8599 loss: 2.8599 2022/10/07 08:45:20 - mmengine - INFO - Epoch(train) [6][1880/2119] lr: 2.4000e-02 eta: 1 day, 4:28:55 time: 0.3359 data_time: 0.0157 memory: 5826 grad_norm: 3.4972 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 3.0822 loss: 3.0822 2022/10/07 08:45:27 - mmengine - INFO - Epoch(train) [6][1900/2119] lr: 2.4000e-02 eta: 1 day, 4:29:13 time: 0.3854 data_time: 0.0211 memory: 5826 grad_norm: 3.4969 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8374 loss: 2.8374 2022/10/07 08:45:33 - mmengine - INFO - Epoch(train) [6][1920/2119] lr: 2.4000e-02 eta: 1 day, 4:28:46 time: 0.2952 data_time: 0.0212 memory: 5826 grad_norm: 3.6133 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 3.0599 loss: 3.0599 2022/10/07 08:45:44 - mmengine - INFO - Epoch(train) [6][1940/2119] lr: 2.4000e-02 eta: 1 day, 4:30:30 time: 0.5628 data_time: 0.3325 memory: 5826 grad_norm: 3.5693 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9779 loss: 2.9779 2022/10/07 08:45:50 - mmengine - INFO - Epoch(train) [6][1960/2119] lr: 2.4000e-02 eta: 1 day, 4:29:53 time: 0.2729 data_time: 0.0242 memory: 5826 grad_norm: 3.5400 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.3636 loss: 3.3636 2022/10/07 08:45:56 - mmengine - INFO - Epoch(train) [6][1980/2119] lr: 2.4000e-02 eta: 1 day, 4:29:41 time: 0.3249 data_time: 0.0223 memory: 5826 grad_norm: 3.4632 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0424 loss: 3.0424 2022/10/07 08:46:03 - mmengine - INFO - Epoch(train) [6][2000/2119] lr: 2.4000e-02 eta: 1 day, 4:29:37 time: 0.3414 data_time: 0.0250 memory: 5826 grad_norm: 3.4883 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 3.0974 loss: 3.0974 2022/10/07 08:46:10 - mmengine - INFO - Epoch(train) [6][2020/2119] lr: 2.4000e-02 eta: 1 day, 4:29:38 time: 0.3526 data_time: 0.0291 memory: 5826 grad_norm: 3.5357 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9147 loss: 2.9147 2022/10/07 08:46:17 - mmengine - INFO - Epoch(train) [6][2040/2119] lr: 2.4000e-02 eta: 1 day, 4:29:34 time: 0.3424 data_time: 0.0213 memory: 5826 grad_norm: 3.5291 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7334 loss: 2.7334 2022/10/07 08:46:24 - mmengine - INFO - Epoch(train) [6][2060/2119] lr: 2.4000e-02 eta: 1 day, 4:29:41 time: 0.3647 data_time: 0.0248 memory: 5826 grad_norm: 3.4754 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.1941 loss: 3.1941 2022/10/07 08:46:30 - mmengine - INFO - Epoch(train) [6][2080/2119] lr: 2.4000e-02 eta: 1 day, 4:29:18 time: 0.3008 data_time: 0.0224 memory: 5826 grad_norm: 3.5117 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9701 loss: 2.9701 2022/10/07 08:46:37 - mmengine - INFO - Epoch(train) [6][2100/2119] lr: 2.4000e-02 eta: 1 day, 4:29:14 time: 0.3430 data_time: 0.0221 memory: 5826 grad_norm: 3.5570 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7820 loss: 2.7820 2022/10/07 08:46:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 08:46:42 - mmengine - INFO - Epoch(train) [6][2119/2119] lr: 2.4000e-02 eta: 1 day, 4:29:14 time: 0.2894 data_time: 0.0226 memory: 5826 grad_norm: 3.5725 top1_acc: 0.3000 top5_acc: 0.5000 loss_cls: 3.1509 loss: 3.1509 2022/10/07 08:46:51 - mmengine - INFO - Epoch(train) [7][20/2119] lr: 2.8000e-02 eta: 1 day, 4:27:23 time: 0.4517 data_time: 0.1248 memory: 5826 grad_norm: 3.5274 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8328 loss: 2.8328 2022/10/07 08:46:58 - mmengine - INFO - Epoch(train) [7][40/2119] lr: 2.8000e-02 eta: 1 day, 4:27:14 time: 0.3296 data_time: 0.0213 memory: 5826 grad_norm: 3.5274 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.9917 loss: 2.9917 2022/10/07 08:47:05 - mmengine - INFO - Epoch(train) [7][60/2119] lr: 2.8000e-02 eta: 1 day, 4:27:21 time: 0.3644 data_time: 0.0177 memory: 5826 grad_norm: 3.5197 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9563 loss: 2.9563 2022/10/07 08:47:11 - mmengine - INFO - Epoch(train) [7][80/2119] lr: 2.8000e-02 eta: 1 day, 4:27:05 time: 0.3158 data_time: 0.0200 memory: 5826 grad_norm: 3.5648 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.3096 loss: 3.3096 2022/10/07 08:47:18 - mmengine - INFO - Epoch(train) [7][100/2119] lr: 2.8000e-02 eta: 1 day, 4:27:00 time: 0.3397 data_time: 0.0198 memory: 5826 grad_norm: 3.4620 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0160 loss: 3.0160 2022/10/07 08:47:24 - mmengine - INFO - Epoch(train) [7][120/2119] lr: 2.8000e-02 eta: 1 day, 4:26:41 time: 0.3105 data_time: 0.0211 memory: 5826 grad_norm: 3.4603 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8382 loss: 2.8382 2022/10/07 08:47:32 - mmengine - INFO - Epoch(train) [7][140/2119] lr: 2.8000e-02 eta: 1 day, 4:26:50 time: 0.3679 data_time: 0.0243 memory: 5826 grad_norm: 3.4556 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8990 loss: 2.8990 2022/10/07 08:47:38 - mmengine - INFO - Epoch(train) [7][160/2119] lr: 2.8000e-02 eta: 1 day, 4:26:38 time: 0.3262 data_time: 0.0228 memory: 5826 grad_norm: 3.4621 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7338 loss: 2.7338 2022/10/07 08:47:45 - mmengine - INFO - Epoch(train) [7][180/2119] lr: 2.8000e-02 eta: 1 day, 4:26:42 time: 0.3587 data_time: 0.0243 memory: 5826 grad_norm: 3.5213 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8583 loss: 2.8583 2022/10/07 08:47:52 - mmengine - INFO - Epoch(train) [7][200/2119] lr: 2.8000e-02 eta: 1 day, 4:26:35 time: 0.3350 data_time: 0.0203 memory: 5826 grad_norm: 3.5265 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.1368 loss: 3.1368 2022/10/07 08:47:59 - mmengine - INFO - Epoch(train) [7][220/2119] lr: 2.8000e-02 eta: 1 day, 4:26:24 time: 0.3255 data_time: 0.0192 memory: 5826 grad_norm: 3.5028 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.8515 loss: 2.8515 2022/10/07 08:48:05 - mmengine - INFO - Epoch(train) [7][240/2119] lr: 2.8000e-02 eta: 1 day, 4:26:01 time: 0.3027 data_time: 0.0274 memory: 5826 grad_norm: 3.5187 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9731 loss: 2.9731 2022/10/07 08:48:11 - mmengine - INFO - Epoch(train) [7][260/2119] lr: 2.8000e-02 eta: 1 day, 4:25:44 time: 0.3119 data_time: 0.0220 memory: 5826 grad_norm: 3.5207 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9360 loss: 2.9360 2022/10/07 08:48:18 - mmengine - INFO - Epoch(train) [7][280/2119] lr: 2.8000e-02 eta: 1 day, 4:25:48 time: 0.3589 data_time: 0.0335 memory: 5826 grad_norm: 3.4481 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9243 loss: 2.9243 2022/10/07 08:48:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 08:48:25 - mmengine - INFO - Epoch(train) [7][300/2119] lr: 2.8000e-02 eta: 1 day, 4:25:40 time: 0.3342 data_time: 0.0243 memory: 5826 grad_norm: 3.4952 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 3.0606 loss: 3.0606 2022/10/07 08:48:31 - mmengine - INFO - Epoch(train) [7][320/2119] lr: 2.8000e-02 eta: 1 day, 4:25:28 time: 0.3235 data_time: 0.0228 memory: 5826 grad_norm: 3.4235 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9938 loss: 2.9938 2022/10/07 08:48:39 - mmengine - INFO - Epoch(train) [7][340/2119] lr: 2.8000e-02 eta: 1 day, 4:25:32 time: 0.3600 data_time: 0.0240 memory: 5826 grad_norm: 3.5263 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1440 loss: 3.1440 2022/10/07 08:48:46 - mmengine - INFO - Epoch(train) [7][360/2119] lr: 2.8000e-02 eta: 1 day, 4:25:50 time: 0.3881 data_time: 0.0218 memory: 5826 grad_norm: 3.5122 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9491 loss: 2.9491 2022/10/07 08:48:52 - mmengine - INFO - Epoch(train) [7][380/2119] lr: 2.8000e-02 eta: 1 day, 4:25:12 time: 0.2687 data_time: 0.0231 memory: 5826 grad_norm: 3.4674 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8880 loss: 2.8880 2022/10/07 08:48:58 - mmengine - INFO - Epoch(train) [7][400/2119] lr: 2.8000e-02 eta: 1 day, 4:24:57 time: 0.3178 data_time: 0.0332 memory: 5826 grad_norm: 3.4717 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.1501 loss: 3.1501 2022/10/07 08:49:05 - mmengine - INFO - Epoch(train) [7][420/2119] lr: 2.8000e-02 eta: 1 day, 4:24:45 time: 0.3242 data_time: 0.0271 memory: 5826 grad_norm: 3.4308 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9468 loss: 2.9468 2022/10/07 08:49:12 - mmengine - INFO - Epoch(train) [7][440/2119] lr: 2.8000e-02 eta: 1 day, 4:24:51 time: 0.3630 data_time: 0.0258 memory: 5826 grad_norm: 3.5034 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8470 loss: 2.8470 2022/10/07 08:49:19 - mmengine - INFO - Epoch(train) [7][460/2119] lr: 2.8000e-02 eta: 1 day, 4:24:48 time: 0.3435 data_time: 0.0222 memory: 5826 grad_norm: 3.5003 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.9443 loss: 2.9443 2022/10/07 08:49:26 - mmengine - INFO - Epoch(train) [7][480/2119] lr: 2.8000e-02 eta: 1 day, 4:24:56 time: 0.3682 data_time: 0.0206 memory: 5826 grad_norm: 3.5512 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9686 loss: 2.9686 2022/10/07 08:49:32 - mmengine - INFO - Epoch(train) [7][500/2119] lr: 2.8000e-02 eta: 1 day, 4:24:23 time: 0.2793 data_time: 0.0190 memory: 5826 grad_norm: 3.4503 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 3.1174 loss: 3.1174 2022/10/07 08:49:39 - mmengine - INFO - Epoch(train) [7][520/2119] lr: 2.8000e-02 eta: 1 day, 4:24:33 time: 0.3702 data_time: 0.0335 memory: 5826 grad_norm: 3.3887 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8216 loss: 2.8216 2022/10/07 08:49:45 - mmengine - INFO - Epoch(train) [7][540/2119] lr: 2.8000e-02 eta: 1 day, 4:24:21 time: 0.3253 data_time: 0.0284 memory: 5826 grad_norm: 3.4558 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8320 loss: 2.8320 2022/10/07 08:49:52 - mmengine - INFO - Epoch(train) [7][560/2119] lr: 2.8000e-02 eta: 1 day, 4:24:14 time: 0.3345 data_time: 0.0183 memory: 5826 grad_norm: 3.4793 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9302 loss: 2.9302 2022/10/07 08:49:59 - mmengine - INFO - Epoch(train) [7][580/2119] lr: 2.8000e-02 eta: 1 day, 4:24:11 time: 0.3434 data_time: 0.0359 memory: 5826 grad_norm: 3.4357 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8299 loss: 2.8299 2022/10/07 08:50:06 - mmengine - INFO - Epoch(train) [7][600/2119] lr: 2.8000e-02 eta: 1 day, 4:24:14 time: 0.3586 data_time: 0.0196 memory: 5826 grad_norm: 3.4665 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9841 loss: 2.9841 2022/10/07 08:50:12 - mmengine - INFO - Epoch(train) [7][620/2119] lr: 2.8000e-02 eta: 1 day, 4:23:54 time: 0.3050 data_time: 0.0250 memory: 5826 grad_norm: 3.4831 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0476 loss: 3.0476 2022/10/07 08:50:19 - mmengine - INFO - Epoch(train) [7][640/2119] lr: 2.8000e-02 eta: 1 day, 4:23:51 time: 0.3438 data_time: 0.0199 memory: 5826 grad_norm: 3.4991 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0133 loss: 3.0133 2022/10/07 08:50:26 - mmengine - INFO - Epoch(train) [7][660/2119] lr: 2.8000e-02 eta: 1 day, 4:23:42 time: 0.3313 data_time: 0.0232 memory: 5826 grad_norm: 3.4409 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9832 loss: 2.9832 2022/10/07 08:50:33 - mmengine - INFO - Epoch(train) [7][680/2119] lr: 2.8000e-02 eta: 1 day, 4:23:45 time: 0.3580 data_time: 0.0180 memory: 5826 grad_norm: 3.5324 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9054 loss: 2.9054 2022/10/07 08:50:39 - mmengine - INFO - Epoch(train) [7][700/2119] lr: 2.8000e-02 eta: 1 day, 4:23:19 time: 0.2934 data_time: 0.0183 memory: 5826 grad_norm: 3.4365 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.2425 loss: 3.2425 2022/10/07 08:50:45 - mmengine - INFO - Epoch(train) [7][720/2119] lr: 2.8000e-02 eta: 1 day, 4:23:02 time: 0.3123 data_time: 0.0208 memory: 5826 grad_norm: 3.4255 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0917 loss: 3.0917 2022/10/07 08:50:53 - mmengine - INFO - Epoch(train) [7][740/2119] lr: 2.8000e-02 eta: 1 day, 4:23:13 time: 0.3748 data_time: 0.0209 memory: 5826 grad_norm: 3.3747 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 3.1023 loss: 3.1023 2022/10/07 08:50:58 - mmengine - INFO - Epoch(train) [7][760/2119] lr: 2.8000e-02 eta: 1 day, 4:22:44 time: 0.2854 data_time: 0.0217 memory: 5826 grad_norm: 3.4668 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0964 loss: 3.0964 2022/10/07 08:51:06 - mmengine - INFO - Epoch(train) [7][780/2119] lr: 2.8000e-02 eta: 1 day, 4:23:04 time: 0.3958 data_time: 0.0207 memory: 5826 grad_norm: 3.4735 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1323 loss: 3.1323 2022/10/07 08:51:13 - mmengine - INFO - Epoch(train) [7][800/2119] lr: 2.8000e-02 eta: 1 day, 4:22:50 time: 0.3206 data_time: 0.0229 memory: 5826 grad_norm: 3.3547 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8270 loss: 2.8270 2022/10/07 08:51:19 - mmengine - INFO - Epoch(train) [7][820/2119] lr: 2.8000e-02 eta: 1 day, 4:22:40 time: 0.3276 data_time: 0.0223 memory: 5826 grad_norm: 3.3895 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8867 loss: 2.8867 2022/10/07 08:51:25 - mmengine - INFO - Epoch(train) [7][840/2119] lr: 2.8000e-02 eta: 1 day, 4:22:19 time: 0.3043 data_time: 0.0201 memory: 5826 grad_norm: 3.4289 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 3.0207 loss: 3.0207 2022/10/07 08:51:35 - mmengine - INFO - Epoch(train) [7][860/2119] lr: 2.8000e-02 eta: 1 day, 4:23:31 time: 0.5099 data_time: 0.0298 memory: 5826 grad_norm: 3.4540 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1481 loss: 3.1481 2022/10/07 08:51:42 - mmengine - INFO - Epoch(train) [7][880/2119] lr: 2.8000e-02 eta: 1 day, 4:23:23 time: 0.3328 data_time: 0.0405 memory: 5826 grad_norm: 3.4528 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.2182 loss: 3.2182 2022/10/07 08:51:49 - mmengine - INFO - Epoch(train) [7][900/2119] lr: 2.8000e-02 eta: 1 day, 4:23:24 time: 0.3540 data_time: 0.0195 memory: 5826 grad_norm: 3.3934 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0180 loss: 3.0180 2022/10/07 08:51:55 - mmengine - INFO - Epoch(train) [7][920/2119] lr: 2.8000e-02 eta: 1 day, 4:23:03 time: 0.3034 data_time: 0.0205 memory: 5826 grad_norm: 3.3385 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7892 loss: 2.7892 2022/10/07 08:52:03 - mmengine - INFO - Epoch(train) [7][940/2119] lr: 2.8000e-02 eta: 1 day, 4:23:11 time: 0.3696 data_time: 0.0249 memory: 5826 grad_norm: 3.4180 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0765 loss: 3.0765 2022/10/07 08:52:10 - mmengine - INFO - Epoch(train) [7][960/2119] lr: 2.8000e-02 eta: 1 day, 4:23:13 time: 0.3555 data_time: 0.0240 memory: 5826 grad_norm: 3.3776 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8609 loss: 2.8609 2022/10/07 08:52:18 - mmengine - INFO - Epoch(train) [7][980/2119] lr: 2.8000e-02 eta: 1 day, 4:23:31 time: 0.3906 data_time: 0.0204 memory: 5826 grad_norm: 3.4439 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8731 loss: 2.8731 2022/10/07 08:52:24 - mmengine - INFO - Epoch(train) [7][1000/2119] lr: 2.8000e-02 eta: 1 day, 4:23:17 time: 0.3196 data_time: 0.0217 memory: 5826 grad_norm: 3.4171 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0515 loss: 3.0515 2022/10/07 08:52:31 - mmengine - INFO - Epoch(train) [7][1020/2119] lr: 2.8000e-02 eta: 1 day, 4:23:15 time: 0.3471 data_time: 0.0212 memory: 5826 grad_norm: 3.4388 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9939 loss: 2.9939 2022/10/07 08:52:37 - mmengine - INFO - Epoch(train) [7][1040/2119] lr: 2.8000e-02 eta: 1 day, 4:23:04 time: 0.3273 data_time: 0.0255 memory: 5826 grad_norm: 3.4175 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0013 loss: 3.0013 2022/10/07 08:52:45 - mmengine - INFO - Epoch(train) [7][1060/2119] lr: 2.8000e-02 eta: 1 day, 4:23:14 time: 0.3730 data_time: 0.0230 memory: 5826 grad_norm: 3.3912 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8782 loss: 2.8782 2022/10/07 08:52:51 - mmengine - INFO - Epoch(train) [7][1080/2119] lr: 2.8000e-02 eta: 1 day, 4:22:53 time: 0.3035 data_time: 0.0173 memory: 5826 grad_norm: 3.4148 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7942 loss: 2.7942 2022/10/07 08:52:58 - mmengine - INFO - Epoch(train) [7][1100/2119] lr: 2.8000e-02 eta: 1 day, 4:22:53 time: 0.3523 data_time: 0.0252 memory: 5826 grad_norm: 3.4358 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8254 loss: 2.8254 2022/10/07 08:53:05 - mmengine - INFO - Epoch(train) [7][1120/2119] lr: 2.8000e-02 eta: 1 day, 4:22:47 time: 0.3370 data_time: 0.0265 memory: 5826 grad_norm: 3.4442 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8497 loss: 2.8497 2022/10/07 08:53:12 - mmengine - INFO - Epoch(train) [7][1140/2119] lr: 2.8000e-02 eta: 1 day, 4:22:49 time: 0.3562 data_time: 0.0213 memory: 5826 grad_norm: 3.4141 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9204 loss: 2.9204 2022/10/07 08:53:18 - mmengine - INFO - Epoch(train) [7][1160/2119] lr: 2.8000e-02 eta: 1 day, 4:22:30 time: 0.3082 data_time: 0.0251 memory: 5826 grad_norm: 3.4386 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7371 loss: 2.7371 2022/10/07 08:53:25 - mmengine - INFO - Epoch(train) [7][1180/2119] lr: 2.8000e-02 eta: 1 day, 4:22:26 time: 0.3421 data_time: 0.0215 memory: 5826 grad_norm: 3.4320 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8657 loss: 2.8657 2022/10/07 08:53:31 - mmengine - INFO - Epoch(train) [7][1200/2119] lr: 2.8000e-02 eta: 1 day, 4:22:07 time: 0.3079 data_time: 0.0250 memory: 5826 grad_norm: 3.3712 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8650 loss: 2.8650 2022/10/07 08:53:39 - mmengine - INFO - Epoch(train) [7][1220/2119] lr: 2.8000e-02 eta: 1 day, 4:22:17 time: 0.3745 data_time: 0.0341 memory: 5826 grad_norm: 3.3960 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9467 loss: 2.9467 2022/10/07 08:53:44 - mmengine - INFO - Epoch(train) [7][1240/2119] lr: 2.8000e-02 eta: 1 day, 4:21:48 time: 0.2847 data_time: 0.0244 memory: 5826 grad_norm: 3.3692 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.3944 loss: 3.3944 2022/10/07 08:53:51 - mmengine - INFO - Epoch(train) [7][1260/2119] lr: 2.8000e-02 eta: 1 day, 4:21:44 time: 0.3421 data_time: 0.0189 memory: 5826 grad_norm: 3.3747 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 3.0910 loss: 3.0910 2022/10/07 08:53:58 - mmengine - INFO - Epoch(train) [7][1280/2119] lr: 2.8000e-02 eta: 1 day, 4:21:36 time: 0.3339 data_time: 0.0239 memory: 5826 grad_norm: 3.4130 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0902 loss: 3.0902 2022/10/07 08:54:00 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 08:54:04 - mmengine - INFO - Epoch(train) [7][1300/2119] lr: 2.8000e-02 eta: 1 day, 4:21:24 time: 0.3246 data_time: 0.0322 memory: 5826 grad_norm: 3.4066 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 3.0964 loss: 3.0964 2022/10/07 08:54:12 - mmengine - INFO - Epoch(train) [7][1320/2119] lr: 2.8000e-02 eta: 1 day, 4:21:50 time: 0.4100 data_time: 0.0198 memory: 5826 grad_norm: 3.3608 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9558 loss: 2.9558 2022/10/07 08:54:19 - mmengine - INFO - Epoch(train) [7][1340/2119] lr: 2.8000e-02 eta: 1 day, 4:21:38 time: 0.3252 data_time: 0.0195 memory: 5826 grad_norm: 3.4055 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9536 loss: 2.9536 2022/10/07 08:54:26 - mmengine - INFO - Epoch(train) [7][1360/2119] lr: 2.8000e-02 eta: 1 day, 4:21:30 time: 0.3329 data_time: 0.0202 memory: 5826 grad_norm: 3.4216 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9227 loss: 2.9227 2022/10/07 08:54:33 - mmengine - INFO - Epoch(train) [7][1380/2119] lr: 2.8000e-02 eta: 1 day, 4:21:30 time: 0.3509 data_time: 0.0216 memory: 5826 grad_norm: 3.4563 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9074 loss: 2.9074 2022/10/07 08:54:39 - mmengine - INFO - Epoch(train) [7][1400/2119] lr: 2.8000e-02 eta: 1 day, 4:21:19 time: 0.3257 data_time: 0.0267 memory: 5826 grad_norm: 3.4304 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.0672 loss: 3.0672 2022/10/07 08:54:46 - mmengine - INFO - Epoch(train) [7][1420/2119] lr: 2.8000e-02 eta: 1 day, 4:21:08 time: 0.3263 data_time: 0.0204 memory: 5826 grad_norm: 3.3981 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0036 loss: 3.0036 2022/10/07 08:54:53 - mmengine - INFO - Epoch(train) [7][1440/2119] lr: 2.8000e-02 eta: 1 day, 4:21:10 time: 0.3563 data_time: 0.0208 memory: 5826 grad_norm: 3.3409 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0915 loss: 3.0915 2022/10/07 08:54:59 - mmengine - INFO - Epoch(train) [7][1460/2119] lr: 2.8000e-02 eta: 1 day, 4:20:54 time: 0.3147 data_time: 0.0305 memory: 5826 grad_norm: 3.3739 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0787 loss: 3.0787 2022/10/07 08:55:06 - mmengine - INFO - Epoch(train) [7][1480/2119] lr: 2.8000e-02 eta: 1 day, 4:20:46 time: 0.3346 data_time: 0.0256 memory: 5826 grad_norm: 3.3502 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2478 loss: 3.2478 2022/10/07 08:55:13 - mmengine - INFO - Epoch(train) [7][1500/2119] lr: 2.8000e-02 eta: 1 day, 4:20:44 time: 0.3452 data_time: 0.0200 memory: 5826 grad_norm: 3.3753 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1359 loss: 3.1359 2022/10/07 08:55:19 - mmengine - INFO - Epoch(train) [7][1520/2119] lr: 2.8000e-02 eta: 1 day, 4:20:33 time: 0.3256 data_time: 0.0239 memory: 5826 grad_norm: 3.4172 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0972 loss: 3.0972 2022/10/07 08:55:26 - mmengine - INFO - Epoch(train) [7][1540/2119] lr: 2.8000e-02 eta: 1 day, 4:20:21 time: 0.3242 data_time: 0.0233 memory: 5826 grad_norm: 3.4399 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9109 loss: 2.9109 2022/10/07 08:55:32 - mmengine - INFO - Epoch(train) [7][1560/2119] lr: 2.8000e-02 eta: 1 day, 4:20:00 time: 0.3026 data_time: 0.0248 memory: 5826 grad_norm: 3.4013 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.9953 loss: 2.9953 2022/10/07 08:55:39 - mmengine - INFO - Epoch(train) [7][1580/2119] lr: 2.8000e-02 eta: 1 day, 4:20:11 time: 0.3774 data_time: 0.0244 memory: 5826 grad_norm: 3.4601 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0122 loss: 3.0122 2022/10/07 08:55:46 - mmengine - INFO - Epoch(train) [7][1600/2119] lr: 2.8000e-02 eta: 1 day, 4:20:04 time: 0.3366 data_time: 0.0265 memory: 5826 grad_norm: 3.4062 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0573 loss: 3.0573 2022/10/07 08:55:52 - mmengine - INFO - Epoch(train) [7][1620/2119] lr: 2.8000e-02 eta: 1 day, 4:19:41 time: 0.2964 data_time: 0.0271 memory: 5826 grad_norm: 3.3858 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.1417 loss: 3.1417 2022/10/07 08:56:00 - mmengine - INFO - Epoch(train) [7][1640/2119] lr: 2.8000e-02 eta: 1 day, 4:19:53 time: 0.3805 data_time: 0.0238 memory: 5826 grad_norm: 3.3462 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 3.0548 loss: 3.0548 2022/10/07 08:56:06 - mmengine - INFO - Epoch(train) [7][1660/2119] lr: 2.8000e-02 eta: 1 day, 4:19:35 time: 0.3108 data_time: 0.0222 memory: 5826 grad_norm: 3.4195 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.1615 loss: 3.1615 2022/10/07 08:56:13 - mmengine - INFO - Epoch(train) [7][1680/2119] lr: 2.8000e-02 eta: 1 day, 4:19:31 time: 0.3416 data_time: 0.0188 memory: 5826 grad_norm: 3.3910 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.2802 loss: 3.2802 2022/10/07 08:56:20 - mmengine - INFO - Epoch(train) [7][1700/2119] lr: 2.8000e-02 eta: 1 day, 4:19:31 time: 0.3528 data_time: 0.0210 memory: 5826 grad_norm: 3.3882 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8729 loss: 2.8729 2022/10/07 08:56:25 - mmengine - INFO - Epoch(train) [7][1720/2119] lr: 2.8000e-02 eta: 1 day, 4:18:55 time: 0.2652 data_time: 0.0226 memory: 5826 grad_norm: 3.3831 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9714 loss: 2.9714 2022/10/07 08:56:32 - mmengine - INFO - Epoch(train) [7][1740/2119] lr: 2.8000e-02 eta: 1 day, 4:18:54 time: 0.3509 data_time: 0.0234 memory: 5826 grad_norm: 3.4045 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0553 loss: 3.0553 2022/10/07 08:56:39 - mmengine - INFO - Epoch(train) [7][1760/2119] lr: 2.8000e-02 eta: 1 day, 4:18:58 time: 0.3597 data_time: 0.0267 memory: 5826 grad_norm: 3.3733 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9414 loss: 2.9414 2022/10/07 08:56:46 - mmengine - INFO - Epoch(train) [7][1780/2119] lr: 2.8000e-02 eta: 1 day, 4:18:42 time: 0.3146 data_time: 0.0218 memory: 5826 grad_norm: 3.3227 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0372 loss: 3.0372 2022/10/07 08:56:52 - mmengine - INFO - Epoch(train) [7][1800/2119] lr: 2.8000e-02 eta: 1 day, 4:18:25 time: 0.3111 data_time: 0.0261 memory: 5826 grad_norm: 3.3573 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8967 loss: 2.8967 2022/10/07 08:56:58 - mmengine - INFO - Epoch(train) [7][1820/2119] lr: 2.8000e-02 eta: 1 day, 4:18:16 time: 0.3306 data_time: 0.0204 memory: 5826 grad_norm: 3.3893 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0660 loss: 3.0660 2022/10/07 08:57:05 - mmengine - INFO - Epoch(train) [7][1840/2119] lr: 2.8000e-02 eta: 1 day, 4:18:14 time: 0.3466 data_time: 0.0206 memory: 5826 grad_norm: 3.4131 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.0520 loss: 3.0520 2022/10/07 08:57:12 - mmengine - INFO - Epoch(train) [7][1860/2119] lr: 2.8000e-02 eta: 1 day, 4:18:01 time: 0.3232 data_time: 0.0198 memory: 5826 grad_norm: 3.3629 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9347 loss: 2.9347 2022/10/07 08:57:19 - mmengine - INFO - Epoch(train) [7][1880/2119] lr: 2.8000e-02 eta: 1 day, 4:18:00 time: 0.3495 data_time: 0.0228 memory: 5826 grad_norm: 3.2974 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0786 loss: 3.0786 2022/10/07 08:57:26 - mmengine - INFO - Epoch(train) [7][1900/2119] lr: 2.8000e-02 eta: 1 day, 4:17:58 time: 0.3462 data_time: 0.0192 memory: 5826 grad_norm: 3.3729 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.1403 loss: 3.1403 2022/10/07 08:57:32 - mmengine - INFO - Epoch(train) [7][1920/2119] lr: 2.8000e-02 eta: 1 day, 4:17:50 time: 0.3320 data_time: 0.0256 memory: 5826 grad_norm: 3.3419 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7570 loss: 2.7570 2022/10/07 08:57:39 - mmengine - INFO - Epoch(train) [7][1940/2119] lr: 2.8000e-02 eta: 1 day, 4:17:36 time: 0.3191 data_time: 0.0198 memory: 5826 grad_norm: 3.3879 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.9517 loss: 2.9517 2022/10/07 08:57:46 - mmengine - INFO - Epoch(train) [7][1960/2119] lr: 2.8000e-02 eta: 1 day, 4:17:35 time: 0.3505 data_time: 0.0194 memory: 5826 grad_norm: 3.3465 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9355 loss: 2.9355 2022/10/07 08:57:52 - mmengine - INFO - Epoch(train) [7][1980/2119] lr: 2.8000e-02 eta: 1 day, 4:17:19 time: 0.3128 data_time: 0.0210 memory: 5826 grad_norm: 3.3753 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0392 loss: 3.0392 2022/10/07 08:57:59 - mmengine - INFO - Epoch(train) [7][2000/2119] lr: 2.8000e-02 eta: 1 day, 4:17:11 time: 0.3339 data_time: 0.0312 memory: 5826 grad_norm: 3.3517 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0821 loss: 3.0821 2022/10/07 08:58:05 - mmengine - INFO - Epoch(train) [7][2020/2119] lr: 2.8000e-02 eta: 1 day, 4:17:03 time: 0.3329 data_time: 0.0255 memory: 5826 grad_norm: 3.3870 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9604 loss: 2.9604 2022/10/07 08:58:12 - mmengine - INFO - Epoch(train) [7][2040/2119] lr: 2.8000e-02 eta: 1 day, 4:17:04 time: 0.3535 data_time: 0.0174 memory: 5826 grad_norm: 3.3326 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9021 loss: 2.9021 2022/10/07 08:58:19 - mmengine - INFO - Epoch(train) [7][2060/2119] lr: 2.8000e-02 eta: 1 day, 4:16:45 time: 0.3073 data_time: 0.0205 memory: 5826 grad_norm: 3.3282 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9322 loss: 2.9322 2022/10/07 08:58:26 - mmengine - INFO - Epoch(train) [7][2080/2119] lr: 2.8000e-02 eta: 1 day, 4:16:48 time: 0.3583 data_time: 0.0251 memory: 5826 grad_norm: 3.3738 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7683 loss: 2.7683 2022/10/07 08:58:32 - mmengine - INFO - Epoch(train) [7][2100/2119] lr: 2.8000e-02 eta: 1 day, 4:16:39 time: 0.3316 data_time: 0.0202 memory: 5826 grad_norm: 3.4001 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9875 loss: 2.9875 2022/10/07 08:58:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 08:58:38 - mmengine - INFO - Epoch(train) [7][2119/2119] lr: 2.8000e-02 eta: 1 day, 4:16:39 time: 0.3091 data_time: 0.0206 memory: 5826 grad_norm: 3.4266 top1_acc: 0.4000 top5_acc: 0.5000 loss_cls: 3.1156 loss: 3.1156 2022/10/07 08:58:48 - mmengine - INFO - Epoch(train) [8][20/2119] lr: 3.2000e-02 eta: 1 day, 4:15:20 time: 0.4916 data_time: 0.1547 memory: 5826 grad_norm: 3.3758 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6924 loss: 2.6924 2022/10/07 08:58:54 - mmengine - INFO - Epoch(train) [8][40/2119] lr: 3.2000e-02 eta: 1 day, 4:14:58 time: 0.2982 data_time: 0.0266 memory: 5826 grad_norm: 3.4143 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.2861 loss: 3.2861 2022/10/07 08:59:02 - mmengine - INFO - Epoch(train) [8][60/2119] lr: 3.2000e-02 eta: 1 day, 4:15:09 time: 0.3806 data_time: 0.0226 memory: 5826 grad_norm: 3.3538 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7896 loss: 2.7896 2022/10/07 08:59:08 - mmengine - INFO - Epoch(train) [8][80/2119] lr: 3.2000e-02 eta: 1 day, 4:15:01 time: 0.3333 data_time: 0.0220 memory: 5826 grad_norm: 3.3572 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.0177 loss: 3.0177 2022/10/07 08:59:15 - mmengine - INFO - Epoch(train) [8][100/2119] lr: 3.2000e-02 eta: 1 day, 4:14:50 time: 0.3245 data_time: 0.0302 memory: 5826 grad_norm: 3.3842 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6606 loss: 2.6606 2022/10/07 08:59:21 - mmengine - INFO - Epoch(train) [8][120/2119] lr: 3.2000e-02 eta: 1 day, 4:14:33 time: 0.3101 data_time: 0.0225 memory: 5826 grad_norm: 3.3511 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9875 loss: 2.9875 2022/10/07 08:59:28 - mmengine - INFO - Epoch(train) [8][140/2119] lr: 3.2000e-02 eta: 1 day, 4:14:27 time: 0.3375 data_time: 0.0211 memory: 5826 grad_norm: 3.2924 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9869 loss: 2.9869 2022/10/07 08:59:34 - mmengine - INFO - Epoch(train) [8][160/2119] lr: 3.2000e-02 eta: 1 day, 4:14:17 time: 0.3278 data_time: 0.0237 memory: 5826 grad_norm: 3.3333 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0212 loss: 3.0212 2022/10/07 08:59:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 08:59:42 - mmengine - INFO - Epoch(train) [8][180/2119] lr: 3.2000e-02 eta: 1 day, 4:14:29 time: 0.3816 data_time: 0.0672 memory: 5826 grad_norm: 3.3326 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.0095 loss: 3.0095 2022/10/07 08:59:48 - mmengine - INFO - Epoch(train) [8][200/2119] lr: 3.2000e-02 eta: 1 day, 4:14:08 time: 0.3000 data_time: 0.0280 memory: 5826 grad_norm: 3.3297 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9943 loss: 2.9943 2022/10/07 08:59:55 - mmengine - INFO - Epoch(train) [8][220/2119] lr: 3.2000e-02 eta: 1 day, 4:14:08 time: 0.3528 data_time: 0.0177 memory: 5826 grad_norm: 3.2874 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.8455 loss: 2.8455 2022/10/07 09:00:02 - mmengine - INFO - Epoch(train) [8][240/2119] lr: 3.2000e-02 eta: 1 day, 4:13:59 time: 0.3305 data_time: 0.0287 memory: 5826 grad_norm: 3.3946 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9985 loss: 2.9985 2022/10/07 09:00:09 - mmengine - INFO - Epoch(train) [8][260/2119] lr: 3.2000e-02 eta: 1 day, 4:13:59 time: 0.3514 data_time: 0.0237 memory: 5826 grad_norm: 3.3366 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8287 loss: 2.8287 2022/10/07 09:00:15 - mmengine - INFO - Epoch(train) [8][280/2119] lr: 3.2000e-02 eta: 1 day, 4:13:48 time: 0.3247 data_time: 0.0231 memory: 5826 grad_norm: 3.3788 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.1384 loss: 3.1384 2022/10/07 09:00:22 - mmengine - INFO - Epoch(train) [8][300/2119] lr: 3.2000e-02 eta: 1 day, 4:13:39 time: 0.3308 data_time: 0.0250 memory: 5826 grad_norm: 3.3445 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0000 loss: 3.0000 2022/10/07 09:00:29 - mmengine - INFO - Epoch(train) [8][320/2119] lr: 3.2000e-02 eta: 1 day, 4:13:47 time: 0.3715 data_time: 0.0211 memory: 5826 grad_norm: 3.2922 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8380 loss: 2.8380 2022/10/07 09:00:35 - mmengine - INFO - Epoch(train) [8][340/2119] lr: 3.2000e-02 eta: 1 day, 4:13:27 time: 0.3019 data_time: 0.0185 memory: 5826 grad_norm: 3.2954 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7640 loss: 2.7640 2022/10/07 09:00:42 - mmengine - INFO - Epoch(train) [8][360/2119] lr: 3.2000e-02 eta: 1 day, 4:13:27 time: 0.3536 data_time: 0.0251 memory: 5826 grad_norm: 3.3421 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0339 loss: 3.0339 2022/10/07 09:00:50 - mmengine - INFO - Epoch(train) [8][380/2119] lr: 3.2000e-02 eta: 1 day, 4:13:42 time: 0.3904 data_time: 0.0227 memory: 5826 grad_norm: 3.3308 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8749 loss: 2.8749 2022/10/07 09:00:57 - mmengine - INFO - Epoch(train) [8][400/2119] lr: 3.2000e-02 eta: 1 day, 4:13:28 time: 0.3171 data_time: 0.0231 memory: 5826 grad_norm: 3.2967 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0655 loss: 3.0655 2022/10/07 09:01:04 - mmengine - INFO - Epoch(train) [8][420/2119] lr: 3.2000e-02 eta: 1 day, 4:13:31 time: 0.3604 data_time: 0.0188 memory: 5826 grad_norm: 3.3713 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.0051 loss: 3.0051 2022/10/07 09:01:10 - mmengine - INFO - Epoch(train) [8][440/2119] lr: 3.2000e-02 eta: 1 day, 4:13:12 time: 0.3059 data_time: 0.0211 memory: 5826 grad_norm: 3.3298 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.1076 loss: 3.1076 2022/10/07 09:01:17 - mmengine - INFO - Epoch(train) [8][460/2119] lr: 3.2000e-02 eta: 1 day, 4:13:09 time: 0.3449 data_time: 0.0195 memory: 5826 grad_norm: 3.4081 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9193 loss: 2.9193 2022/10/07 09:01:23 - mmengine - INFO - Epoch(train) [8][480/2119] lr: 3.2000e-02 eta: 1 day, 4:12:56 time: 0.3200 data_time: 0.0254 memory: 5826 grad_norm: 3.2371 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8699 loss: 2.8699 2022/10/07 09:01:30 - mmengine - INFO - Epoch(train) [8][500/2119] lr: 3.2000e-02 eta: 1 day, 4:12:56 time: 0.3528 data_time: 0.0186 memory: 5826 grad_norm: 3.3148 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.1860 loss: 3.1860 2022/10/07 09:01:36 - mmengine - INFO - Epoch(train) [8][520/2119] lr: 3.2000e-02 eta: 1 day, 4:12:41 time: 0.3140 data_time: 0.0183 memory: 5826 grad_norm: 3.3254 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0182 loss: 3.0182 2022/10/07 09:01:43 - mmengine - INFO - Epoch(train) [8][540/2119] lr: 3.2000e-02 eta: 1 day, 4:12:36 time: 0.3404 data_time: 0.0187 memory: 5826 grad_norm: 3.2559 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0723 loss: 3.0723 2022/10/07 09:01:50 - mmengine - INFO - Epoch(train) [8][560/2119] lr: 3.2000e-02 eta: 1 day, 4:12:26 time: 0.3262 data_time: 0.0205 memory: 5826 grad_norm: 3.2996 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7603 loss: 2.7603 2022/10/07 09:01:56 - mmengine - INFO - Epoch(train) [8][580/2119] lr: 3.2000e-02 eta: 1 day, 4:12:18 time: 0.3339 data_time: 0.0146 memory: 5826 grad_norm: 3.3477 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0223 loss: 3.0223 2022/10/07 09:02:03 - mmengine - INFO - Epoch(train) [8][600/2119] lr: 3.2000e-02 eta: 1 day, 4:12:10 time: 0.3308 data_time: 0.0209 memory: 5826 grad_norm: 3.3406 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7228 loss: 2.7228 2022/10/07 09:02:11 - mmengine - INFO - Epoch(train) [8][620/2119] lr: 3.2000e-02 eta: 1 day, 4:12:22 time: 0.3850 data_time: 0.0226 memory: 5826 grad_norm: 3.2695 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0607 loss: 3.0607 2022/10/07 09:02:16 - mmengine - INFO - Epoch(train) [8][640/2119] lr: 3.2000e-02 eta: 1 day, 4:11:50 time: 0.2713 data_time: 0.0237 memory: 5826 grad_norm: 3.2624 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9106 loss: 2.9106 2022/10/07 09:02:25 - mmengine - INFO - Epoch(train) [8][660/2119] lr: 3.2000e-02 eta: 1 day, 4:12:14 time: 0.4133 data_time: 0.0195 memory: 5826 grad_norm: 3.3544 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.2287 loss: 3.2287 2022/10/07 09:02:31 - mmengine - INFO - Epoch(train) [8][680/2119] lr: 3.2000e-02 eta: 1 day, 4:12:02 time: 0.3228 data_time: 0.0245 memory: 5826 grad_norm: 3.2957 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8527 loss: 2.8527 2022/10/07 09:02:37 - mmengine - INFO - Epoch(train) [8][700/2119] lr: 3.2000e-02 eta: 1 day, 4:11:44 time: 0.3060 data_time: 0.0194 memory: 5826 grad_norm: 3.2531 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.1412 loss: 3.1412 2022/10/07 09:02:43 - mmengine - INFO - Epoch(train) [8][720/2119] lr: 3.2000e-02 eta: 1 day, 4:11:21 time: 0.2953 data_time: 0.0271 memory: 5826 grad_norm: 3.3450 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0393 loss: 3.0393 2022/10/07 09:02:51 - mmengine - INFO - Epoch(train) [8][740/2119] lr: 3.2000e-02 eta: 1 day, 4:11:35 time: 0.3891 data_time: 0.0239 memory: 5826 grad_norm: 3.2913 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.3283 loss: 3.3283 2022/10/07 09:02:57 - mmengine - INFO - Epoch(train) [8][760/2119] lr: 3.2000e-02 eta: 1 day, 4:11:28 time: 0.3334 data_time: 0.0159 memory: 5826 grad_norm: 3.1992 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0146 loss: 3.0146 2022/10/07 09:03:05 - mmengine - INFO - Epoch(train) [8][780/2119] lr: 3.2000e-02 eta: 1 day, 4:11:33 time: 0.3673 data_time: 0.0171 memory: 5826 grad_norm: 3.3216 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8074 loss: 2.8074 2022/10/07 09:03:11 - mmengine - INFO - Epoch(train) [8][800/2119] lr: 3.2000e-02 eta: 1 day, 4:11:11 time: 0.2967 data_time: 0.0200 memory: 5826 grad_norm: 3.3455 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8564 loss: 2.8564 2022/10/07 09:03:18 - mmengine - INFO - Epoch(train) [8][820/2119] lr: 3.2000e-02 eta: 1 day, 4:11:06 time: 0.3399 data_time: 0.0219 memory: 5826 grad_norm: 3.2855 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.1047 loss: 3.1047 2022/10/07 09:03:25 - mmengine - INFO - Epoch(train) [8][840/2119] lr: 3.2000e-02 eta: 1 day, 4:11:08 time: 0.3578 data_time: 0.0201 memory: 5826 grad_norm: 3.1988 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0567 loss: 3.0567 2022/10/07 09:03:31 - mmengine - INFO - Epoch(train) [8][860/2119] lr: 3.2000e-02 eta: 1 day, 4:11:02 time: 0.3368 data_time: 0.0194 memory: 5826 grad_norm: 3.2147 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 3.0168 loss: 3.0168 2022/10/07 09:03:38 - mmengine - INFO - Epoch(train) [8][880/2119] lr: 3.2000e-02 eta: 1 day, 4:10:51 time: 0.3255 data_time: 0.0271 memory: 5826 grad_norm: 3.2849 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0131 loss: 3.0131 2022/10/07 09:03:45 - mmengine - INFO - Epoch(train) [8][900/2119] lr: 3.2000e-02 eta: 1 day, 4:11:01 time: 0.3788 data_time: 0.0183 memory: 5826 grad_norm: 3.2415 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8520 loss: 2.8520 2022/10/07 09:03:52 - mmengine - INFO - Epoch(train) [8][920/2119] lr: 3.2000e-02 eta: 1 day, 4:10:45 time: 0.3117 data_time: 0.0273 memory: 5826 grad_norm: 3.2892 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7654 loss: 2.7654 2022/10/07 09:03:59 - mmengine - INFO - Epoch(train) [8][940/2119] lr: 3.2000e-02 eta: 1 day, 4:10:45 time: 0.3529 data_time: 0.0172 memory: 5826 grad_norm: 3.3115 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.1222 loss: 3.1222 2022/10/07 09:04:05 - mmengine - INFO - Epoch(train) [8][960/2119] lr: 3.2000e-02 eta: 1 day, 4:10:25 time: 0.3029 data_time: 0.0193 memory: 5826 grad_norm: 3.2914 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9472 loss: 2.9472 2022/10/07 09:04:12 - mmengine - INFO - Epoch(train) [8][980/2119] lr: 3.2000e-02 eta: 1 day, 4:10:36 time: 0.3820 data_time: 0.0202 memory: 5826 grad_norm: 3.2803 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9188 loss: 2.9188 2022/10/07 09:04:20 - mmengine - INFO - Epoch(train) [8][1000/2119] lr: 3.2000e-02 eta: 1 day, 4:10:40 time: 0.3639 data_time: 0.0256 memory: 5826 grad_norm: 3.2271 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.0116 loss: 3.0116 2022/10/07 09:04:26 - mmengine - INFO - Epoch(train) [8][1020/2119] lr: 3.2000e-02 eta: 1 day, 4:10:23 time: 0.3097 data_time: 0.0158 memory: 5826 grad_norm: 3.2405 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0249 loss: 3.0249 2022/10/07 09:04:32 - mmengine - INFO - Epoch(train) [8][1040/2119] lr: 3.2000e-02 eta: 1 day, 4:09:58 time: 0.2864 data_time: 0.0273 memory: 5826 grad_norm: 3.2653 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0314 loss: 3.0314 2022/10/07 09:04:39 - mmengine - INFO - Epoch(train) [8][1060/2119] lr: 3.2000e-02 eta: 1 day, 4:10:03 time: 0.3667 data_time: 0.0211 memory: 5826 grad_norm: 3.2658 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.8535 loss: 2.8535 2022/10/07 09:04:48 - mmengine - INFO - Epoch(train) [8][1080/2119] lr: 3.2000e-02 eta: 1 day, 4:10:32 time: 0.4301 data_time: 0.0206 memory: 5826 grad_norm: 3.2725 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.8619 loss: 2.8619 2022/10/07 09:04:53 - mmengine - INFO - Epoch(train) [8][1100/2119] lr: 3.2000e-02 eta: 1 day, 4:10:01 time: 0.2720 data_time: 0.0191 memory: 5826 grad_norm: 3.3541 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0176 loss: 3.0176 2022/10/07 09:05:00 - mmengine - INFO - Epoch(train) [8][1120/2119] lr: 3.2000e-02 eta: 1 day, 4:10:05 time: 0.3652 data_time: 0.0222 memory: 5826 grad_norm: 3.3006 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.1185 loss: 3.1185 2022/10/07 09:05:07 - mmengine - INFO - Epoch(train) [8][1140/2119] lr: 3.2000e-02 eta: 1 day, 4:09:56 time: 0.3277 data_time: 0.0220 memory: 5826 grad_norm: 3.2997 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 3.0594 loss: 3.0594 2022/10/07 09:05:14 - mmengine - INFO - Epoch(train) [8][1160/2119] lr: 3.2000e-02 eta: 1 day, 4:09:56 time: 0.3547 data_time: 0.0218 memory: 5826 grad_norm: 3.3128 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7941 loss: 2.7941 2022/10/07 09:05:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 09:05:21 - mmengine - INFO - Epoch(train) [8][1180/2119] lr: 3.2000e-02 eta: 1 day, 4:09:56 time: 0.3540 data_time: 0.0212 memory: 5826 grad_norm: 3.2710 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0178 loss: 3.0178 2022/10/07 09:05:28 - mmengine - INFO - Epoch(train) [8][1200/2119] lr: 3.2000e-02 eta: 1 day, 4:10:02 time: 0.3687 data_time: 0.0244 memory: 5826 grad_norm: 3.2423 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0658 loss: 3.0658 2022/10/07 09:05:35 - mmengine - INFO - Epoch(train) [8][1220/2119] lr: 3.2000e-02 eta: 1 day, 4:09:44 time: 0.3077 data_time: 0.0221 memory: 5826 grad_norm: 3.2960 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9718 loss: 2.9718 2022/10/07 09:05:42 - mmengine - INFO - Epoch(train) [8][1240/2119] lr: 3.2000e-02 eta: 1 day, 4:09:56 time: 0.3837 data_time: 0.0191 memory: 5826 grad_norm: 3.3368 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0692 loss: 3.0692 2022/10/07 09:05:48 - mmengine - INFO - Epoch(train) [8][1260/2119] lr: 3.2000e-02 eta: 1 day, 4:09:36 time: 0.3024 data_time: 0.0171 memory: 5826 grad_norm: 3.2846 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.1367 loss: 3.1367 2022/10/07 09:05:55 - mmengine - INFO - Epoch(train) [8][1280/2119] lr: 3.2000e-02 eta: 1 day, 4:09:29 time: 0.3348 data_time: 0.0192 memory: 5826 grad_norm: 3.3017 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.9076 loss: 2.9076 2022/10/07 09:06:02 - mmengine - INFO - Epoch(train) [8][1300/2119] lr: 3.2000e-02 eta: 1 day, 4:09:32 time: 0.3628 data_time: 0.0209 memory: 5826 grad_norm: 3.2454 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.0438 loss: 3.0438 2022/10/07 09:06:09 - mmengine - INFO - Epoch(train) [8][1320/2119] lr: 3.2000e-02 eta: 1 day, 4:09:22 time: 0.3248 data_time: 0.0191 memory: 5826 grad_norm: 3.2730 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0276 loss: 3.0276 2022/10/07 09:06:15 - mmengine - INFO - Epoch(train) [8][1340/2119] lr: 3.2000e-02 eta: 1 day, 4:09:11 time: 0.3269 data_time: 0.0208 memory: 5826 grad_norm: 3.2766 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0757 loss: 3.0757 2022/10/07 09:06:22 - mmengine - INFO - Epoch(train) [8][1360/2119] lr: 3.2000e-02 eta: 1 day, 4:09:11 time: 0.3528 data_time: 0.0202 memory: 5826 grad_norm: 3.2332 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6990 loss: 2.6990 2022/10/07 09:06:28 - mmengine - INFO - Epoch(train) [8][1380/2119] lr: 3.2000e-02 eta: 1 day, 4:08:50 time: 0.2974 data_time: 0.0244 memory: 5826 grad_norm: 3.1746 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8943 loss: 2.8943 2022/10/07 09:06:36 - mmengine - INFO - Epoch(train) [8][1400/2119] lr: 3.2000e-02 eta: 1 day, 4:08:54 time: 0.3639 data_time: 0.0218 memory: 5826 grad_norm: 3.2542 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9133 loss: 2.9133 2022/10/07 09:06:42 - mmengine - INFO - Epoch(train) [8][1420/2119] lr: 3.2000e-02 eta: 1 day, 4:08:42 time: 0.3230 data_time: 0.0199 memory: 5826 grad_norm: 3.2328 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8252 loss: 2.8252 2022/10/07 09:06:49 - mmengine - INFO - Epoch(train) [8][1440/2119] lr: 3.2000e-02 eta: 1 day, 4:08:36 time: 0.3364 data_time: 0.0220 memory: 5826 grad_norm: 3.2185 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.1884 loss: 3.1884 2022/10/07 09:06:55 - mmengine - INFO - Epoch(train) [8][1460/2119] lr: 3.2000e-02 eta: 1 day, 4:08:25 time: 0.3246 data_time: 0.0239 memory: 5826 grad_norm: 3.2678 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 3.1122 loss: 3.1122 2022/10/07 09:07:03 - mmengine - INFO - Epoch(train) [8][1480/2119] lr: 3.2000e-02 eta: 1 day, 4:08:34 time: 0.3800 data_time: 0.0210 memory: 5826 grad_norm: 3.2472 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8051 loss: 2.8051 2022/10/07 09:07:10 - mmengine - INFO - Epoch(train) [8][1500/2119] lr: 3.2000e-02 eta: 1 day, 4:08:30 time: 0.3419 data_time: 0.0204 memory: 5826 grad_norm: 3.2232 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.9766 loss: 2.9766 2022/10/07 09:07:16 - mmengine - INFO - Epoch(train) [8][1520/2119] lr: 3.2000e-02 eta: 1 day, 4:08:16 time: 0.3162 data_time: 0.0225 memory: 5826 grad_norm: 3.2750 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9378 loss: 2.9378 2022/10/07 09:07:23 - mmengine - INFO - Epoch(train) [8][1540/2119] lr: 3.2000e-02 eta: 1 day, 4:08:20 time: 0.3659 data_time: 0.0216 memory: 5826 grad_norm: 3.2531 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9810 loss: 2.9810 2022/10/07 09:07:30 - mmengine - INFO - Epoch(train) [8][1560/2119] lr: 3.2000e-02 eta: 1 day, 4:08:03 time: 0.3079 data_time: 0.0289 memory: 5826 grad_norm: 3.2810 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0022 loss: 3.0022 2022/10/07 09:07:37 - mmengine - INFO - Epoch(train) [8][1580/2119] lr: 3.2000e-02 eta: 1 day, 4:08:05 time: 0.3593 data_time: 0.0228 memory: 5826 grad_norm: 3.2781 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0889 loss: 3.0889 2022/10/07 09:07:43 - mmengine - INFO - Epoch(train) [8][1600/2119] lr: 3.2000e-02 eta: 1 day, 4:07:52 time: 0.3192 data_time: 0.0176 memory: 5826 grad_norm: 3.2043 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0387 loss: 3.0387 2022/10/07 09:07:50 - mmengine - INFO - Epoch(train) [8][1620/2119] lr: 3.2000e-02 eta: 1 day, 4:07:48 time: 0.3438 data_time: 0.0173 memory: 5826 grad_norm: 3.2458 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9850 loss: 2.9850 2022/10/07 09:07:56 - mmengine - INFO - Epoch(train) [8][1640/2119] lr: 3.2000e-02 eta: 1 day, 4:07:34 time: 0.3165 data_time: 0.0284 memory: 5826 grad_norm: 3.2077 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.0048 loss: 3.0048 2022/10/07 09:08:04 - mmengine - INFO - Epoch(train) [8][1660/2119] lr: 3.2000e-02 eta: 1 day, 4:07:43 time: 0.3788 data_time: 0.0259 memory: 5826 grad_norm: 3.1917 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8831 loss: 2.8831 2022/10/07 09:08:10 - mmengine - INFO - Epoch(train) [8][1680/2119] lr: 3.2000e-02 eta: 1 day, 4:07:27 time: 0.3096 data_time: 0.0178 memory: 5826 grad_norm: 3.2147 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7847 loss: 2.7847 2022/10/07 09:08:16 - mmengine - INFO - Epoch(train) [8][1700/2119] lr: 3.2000e-02 eta: 1 day, 4:07:14 time: 0.3186 data_time: 0.0165 memory: 5826 grad_norm: 3.2011 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.2333 loss: 3.2333 2022/10/07 09:08:23 - mmengine - INFO - Epoch(train) [8][1720/2119] lr: 3.2000e-02 eta: 1 day, 4:07:10 time: 0.3453 data_time: 0.0462 memory: 5826 grad_norm: 3.1857 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0268 loss: 3.0268 2022/10/07 09:08:30 - mmengine - INFO - Epoch(train) [8][1740/2119] lr: 3.2000e-02 eta: 1 day, 4:07:03 time: 0.3333 data_time: 0.0257 memory: 5826 grad_norm: 3.2976 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9898 loss: 2.9898 2022/10/07 09:08:36 - mmengine - INFO - Epoch(train) [8][1760/2119] lr: 3.2000e-02 eta: 1 day, 4:06:49 time: 0.3159 data_time: 0.0733 memory: 5826 grad_norm: 3.2298 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0113 loss: 3.0113 2022/10/07 09:08:44 - mmengine - INFO - Epoch(train) [8][1780/2119] lr: 3.2000e-02 eta: 1 day, 4:06:55 time: 0.3711 data_time: 0.0478 memory: 5826 grad_norm: 3.2524 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8590 loss: 2.8590 2022/10/07 09:08:51 - mmengine - INFO - Epoch(train) [8][1800/2119] lr: 3.2000e-02 eta: 1 day, 4:07:02 time: 0.3749 data_time: 0.0172 memory: 5826 grad_norm: 3.2592 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9744 loss: 2.9744 2022/10/07 09:08:57 - mmengine - INFO - Epoch(train) [8][1820/2119] lr: 3.2000e-02 eta: 1 day, 4:06:32 time: 0.2710 data_time: 0.0232 memory: 5826 grad_norm: 3.1921 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0107 loss: 3.0107 2022/10/07 09:09:04 - mmengine - INFO - Epoch(train) [8][1840/2119] lr: 3.2000e-02 eta: 1 day, 4:06:38 time: 0.3709 data_time: 0.0207 memory: 5826 grad_norm: 3.2703 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9290 loss: 2.9290 2022/10/07 09:09:11 - mmengine - INFO - Epoch(train) [8][1860/2119] lr: 3.2000e-02 eta: 1 day, 4:06:28 time: 0.3268 data_time: 0.0219 memory: 5826 grad_norm: 3.2286 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0090 loss: 3.0090 2022/10/07 09:09:17 - mmengine - INFO - Epoch(train) [8][1880/2119] lr: 3.2000e-02 eta: 1 day, 4:06:18 time: 0.3279 data_time: 0.0171 memory: 5826 grad_norm: 3.2870 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0570 loss: 3.0570 2022/10/07 09:09:24 - mmengine - INFO - Epoch(train) [8][1900/2119] lr: 3.2000e-02 eta: 1 day, 4:06:20 time: 0.3598 data_time: 0.0339 memory: 5826 grad_norm: 3.1957 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0004 loss: 3.0004 2022/10/07 09:09:31 - mmengine - INFO - Epoch(train) [8][1920/2119] lr: 3.2000e-02 eta: 1 day, 4:06:10 time: 0.3286 data_time: 0.0192 memory: 5826 grad_norm: 3.2150 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8162 loss: 2.8162 2022/10/07 09:09:37 - mmengine - INFO - Epoch(train) [8][1940/2119] lr: 3.2000e-02 eta: 1 day, 4:05:49 time: 0.2953 data_time: 0.0221 memory: 5826 grad_norm: 3.2127 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0292 loss: 3.0292 2022/10/07 09:09:43 - mmengine - INFO - Epoch(train) [8][1960/2119] lr: 3.2000e-02 eta: 1 day, 4:05:38 time: 0.3234 data_time: 0.0233 memory: 5826 grad_norm: 3.1654 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0184 loss: 3.0184 2022/10/07 09:09:50 - mmengine - INFO - Epoch(train) [8][1980/2119] lr: 3.2000e-02 eta: 1 day, 4:05:27 time: 0.3235 data_time: 0.0205 memory: 5826 grad_norm: 3.1977 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 3.0423 loss: 3.0423 2022/10/07 09:09:56 - mmengine - INFO - Epoch(train) [8][2000/2119] lr: 3.2000e-02 eta: 1 day, 4:05:16 time: 0.3255 data_time: 0.0193 memory: 5826 grad_norm: 3.2206 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1273 loss: 3.1273 2022/10/07 09:10:03 - mmengine - INFO - Epoch(train) [8][2020/2119] lr: 3.2000e-02 eta: 1 day, 4:05:15 time: 0.3513 data_time: 0.0170 memory: 5826 grad_norm: 3.2462 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8671 loss: 2.8671 2022/10/07 09:10:11 - mmengine - INFO - Epoch(train) [8][2040/2119] lr: 3.2000e-02 eta: 1 day, 4:05:16 time: 0.3565 data_time: 0.0192 memory: 5826 grad_norm: 3.2048 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7956 loss: 2.7956 2022/10/07 09:10:17 - mmengine - INFO - Epoch(train) [8][2060/2119] lr: 3.2000e-02 eta: 1 day, 4:04:56 time: 0.2997 data_time: 0.0192 memory: 5826 grad_norm: 3.2203 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7570 loss: 2.7570 2022/10/07 09:10:23 - mmengine - INFO - Epoch(train) [8][2080/2119] lr: 3.2000e-02 eta: 1 day, 4:04:52 time: 0.3444 data_time: 0.0198 memory: 5826 grad_norm: 3.2242 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0664 loss: 3.0664 2022/10/07 09:10:30 - mmengine - INFO - Epoch(train) [8][2100/2119] lr: 3.2000e-02 eta: 1 day, 4:04:52 time: 0.3550 data_time: 0.0223 memory: 5826 grad_norm: 3.2346 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9042 loss: 2.9042 2022/10/07 09:10:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 09:10:35 - mmengine - INFO - Epoch(train) [8][2119/2119] lr: 3.2000e-02 eta: 1 day, 4:04:52 time: 0.2711 data_time: 0.0166 memory: 5826 grad_norm: 3.2340 top1_acc: 0.4000 top5_acc: 0.4000 loss_cls: 2.8583 loss: 2.8583 2022/10/07 09:10:35 - mmengine - INFO - Saving checkpoint at 8 epochs 2022/10/07 09:10:50 - mmengine - INFO - Epoch(train) [9][20/2119] lr: 3.6000e-02 eta: 1 day, 4:03:05 time: 0.3900 data_time: 0.1690 memory: 5826 grad_norm: 3.1962 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9054 loss: 2.9054 2022/10/07 09:10:55 - mmengine - INFO - Epoch(train) [9][40/2119] lr: 3.6000e-02 eta: 1 day, 4:02:33 time: 0.2633 data_time: 0.0318 memory: 5826 grad_norm: 3.2633 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.0238 loss: 3.0238 2022/10/07 09:10:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 09:11:03 - mmengine - INFO - Epoch(train) [9][60/2119] lr: 3.6000e-02 eta: 1 day, 4:02:46 time: 0.3927 data_time: 0.0292 memory: 5826 grad_norm: 3.1669 top1_acc: 0.2500 top5_acc: 0.3125 loss_cls: 2.7618 loss: 2.7618 2022/10/07 09:11:09 - mmengine - INFO - Epoch(train) [9][80/2119] lr: 3.6000e-02 eta: 1 day, 4:02:30 time: 0.3088 data_time: 0.0216 memory: 5826 grad_norm: 3.1826 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9884 loss: 2.9884 2022/10/07 09:11:16 - mmengine - INFO - Epoch(train) [9][100/2119] lr: 3.6000e-02 eta: 1 day, 4:02:31 time: 0.3573 data_time: 0.0198 memory: 5826 grad_norm: 3.1989 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9432 loss: 2.9432 2022/10/07 09:11:23 - mmengine - INFO - Epoch(train) [9][120/2119] lr: 3.6000e-02 eta: 1 day, 4:02:28 time: 0.3442 data_time: 0.0212 memory: 5826 grad_norm: 3.2071 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0997 loss: 3.0997 2022/10/07 09:11:30 - mmengine - INFO - Epoch(train) [9][140/2119] lr: 3.6000e-02 eta: 1 day, 4:02:21 time: 0.3369 data_time: 0.0260 memory: 5826 grad_norm: 3.2059 top1_acc: 0.0625 top5_acc: 0.3750 loss_cls: 2.8848 loss: 2.8848 2022/10/07 09:11:36 - mmengine - INFO - Epoch(train) [9][160/2119] lr: 3.6000e-02 eta: 1 day, 4:02:13 time: 0.3316 data_time: 0.0245 memory: 5826 grad_norm: 3.2544 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9746 loss: 2.9746 2022/10/07 09:11:44 - mmengine - INFO - Epoch(train) [9][180/2119] lr: 3.6000e-02 eta: 1 day, 4:02:13 time: 0.3550 data_time: 0.0208 memory: 5826 grad_norm: 3.1588 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8163 loss: 2.8163 2022/10/07 09:11:50 - mmengine - INFO - Epoch(train) [9][200/2119] lr: 3.6000e-02 eta: 1 day, 4:02:02 time: 0.3240 data_time: 0.0236 memory: 5826 grad_norm: 3.2357 top1_acc: 0.2500 top5_acc: 0.3125 loss_cls: 3.1080 loss: 3.1080 2022/10/07 09:11:57 - mmengine - INFO - Epoch(train) [9][220/2119] lr: 3.6000e-02 eta: 1 day, 4:02:05 time: 0.3628 data_time: 0.0204 memory: 5826 grad_norm: 3.1548 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9420 loss: 2.9420 2022/10/07 09:12:03 - mmengine - INFO - Epoch(train) [9][240/2119] lr: 3.6000e-02 eta: 1 day, 4:01:49 time: 0.3082 data_time: 0.0249 memory: 5826 grad_norm: 3.2081 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.1833 loss: 3.1833 2022/10/07 09:12:11 - mmengine - INFO - Epoch(train) [9][260/2119] lr: 3.6000e-02 eta: 1 day, 4:01:59 time: 0.3851 data_time: 0.0206 memory: 5826 grad_norm: 3.1350 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8639 loss: 2.8639 2022/10/07 09:12:17 - mmengine - INFO - Epoch(train) [9][280/2119] lr: 3.6000e-02 eta: 1 day, 4:01:35 time: 0.2850 data_time: 0.0248 memory: 5826 grad_norm: 3.2243 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0702 loss: 3.0702 2022/10/07 09:12:24 - mmengine - INFO - Epoch(train) [9][300/2119] lr: 3.6000e-02 eta: 1 day, 4:01:42 time: 0.3749 data_time: 0.0172 memory: 5826 grad_norm: 3.1999 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.0906 loss: 3.0906 2022/10/07 09:12:31 - mmengine - INFO - Epoch(train) [9][320/2119] lr: 3.6000e-02 eta: 1 day, 4:01:33 time: 0.3295 data_time: 0.0263 memory: 5826 grad_norm: 3.1547 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0701 loss: 3.0701 2022/10/07 09:12:37 - mmengine - INFO - Epoch(train) [9][340/2119] lr: 3.6000e-02 eta: 1 day, 4:01:16 time: 0.3046 data_time: 0.0211 memory: 5826 grad_norm: 3.1498 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7304 loss: 2.7304 2022/10/07 09:12:44 - mmengine - INFO - Epoch(train) [9][360/2119] lr: 3.6000e-02 eta: 1 day, 4:01:16 time: 0.3572 data_time: 0.0197 memory: 5826 grad_norm: 3.1649 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8798 loss: 2.8798 2022/10/07 09:12:51 - mmengine - INFO - Epoch(train) [9][380/2119] lr: 3.6000e-02 eta: 1 day, 4:01:12 time: 0.3410 data_time: 0.0205 memory: 5826 grad_norm: 3.1926 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9534 loss: 2.9534 2022/10/07 09:12:57 - mmengine - INFO - Epoch(train) [9][400/2119] lr: 3.6000e-02 eta: 1 day, 4:00:52 time: 0.2997 data_time: 0.0336 memory: 5826 grad_norm: 3.1143 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8707 loss: 2.8707 2022/10/07 09:13:04 - mmengine - INFO - Epoch(train) [9][420/2119] lr: 3.6000e-02 eta: 1 day, 4:00:50 time: 0.3483 data_time: 0.0785 memory: 5826 grad_norm: 3.2342 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.2594 loss: 3.2594 2022/10/07 09:13:11 - mmengine - INFO - Epoch(train) [9][440/2119] lr: 3.6000e-02 eta: 1 day, 4:00:50 time: 0.3538 data_time: 0.1226 memory: 5826 grad_norm: 3.2181 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0958 loss: 3.0958 2022/10/07 09:13:17 - mmengine - INFO - Epoch(train) [9][460/2119] lr: 3.6000e-02 eta: 1 day, 4:00:36 time: 0.3162 data_time: 0.0850 memory: 5826 grad_norm: 3.1550 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.0435 loss: 3.0435 2022/10/07 09:13:24 - mmengine - INFO - Epoch(train) [9][480/2119] lr: 3.6000e-02 eta: 1 day, 4:00:30 time: 0.3363 data_time: 0.0968 memory: 5826 grad_norm: 3.1880 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.1648 loss: 3.1648 2022/10/07 09:13:31 - mmengine - INFO - Epoch(train) [9][500/2119] lr: 3.6000e-02 eta: 1 day, 4:00:19 time: 0.3244 data_time: 0.0854 memory: 5826 grad_norm: 3.1271 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.3082 loss: 3.3082 2022/10/07 09:13:38 - mmengine - INFO - Epoch(train) [9][520/2119] lr: 3.6000e-02 eta: 1 day, 4:00:18 time: 0.3522 data_time: 0.1203 memory: 5826 grad_norm: 3.1288 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0200 loss: 3.0200 2022/10/07 09:13:44 - mmengine - INFO - Epoch(train) [9][540/2119] lr: 3.6000e-02 eta: 1 day, 4:00:02 time: 0.3088 data_time: 0.0484 memory: 5826 grad_norm: 3.1672 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.1039 loss: 3.1039 2022/10/07 09:13:51 - mmengine - INFO - Epoch(train) [9][560/2119] lr: 3.6000e-02 eta: 1 day, 4:00:02 time: 0.3537 data_time: 0.0490 memory: 5826 grad_norm: 3.1978 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.1292 loss: 3.1292 2022/10/07 09:13:57 - mmengine - INFO - Epoch(train) [9][580/2119] lr: 3.6000e-02 eta: 1 day, 3:59:45 time: 0.3067 data_time: 0.0281 memory: 5826 grad_norm: 3.1073 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7247 loss: 2.7247 2022/10/07 09:14:04 - mmengine - INFO - Epoch(train) [9][600/2119] lr: 3.6000e-02 eta: 1 day, 3:59:39 time: 0.3383 data_time: 0.0232 memory: 5826 grad_norm: 3.1915 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 3.1038 loss: 3.1038 2022/10/07 09:14:11 - mmengine - INFO - Epoch(train) [9][620/2119] lr: 3.6000e-02 eta: 1 day, 3:59:35 time: 0.3431 data_time: 0.0526 memory: 5826 grad_norm: 3.1386 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9239 loss: 2.9239 2022/10/07 09:14:18 - mmengine - INFO - Epoch(train) [9][640/2119] lr: 3.6000e-02 eta: 1 day, 3:59:33 time: 0.3486 data_time: 0.1072 memory: 5826 grad_norm: 3.1555 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.8601 loss: 2.8601 2022/10/07 09:14:25 - mmengine - INFO - Epoch(train) [9][660/2119] lr: 3.6000e-02 eta: 1 day, 3:59:36 time: 0.3641 data_time: 0.0555 memory: 5826 grad_norm: 3.1273 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0239 loss: 3.0239 2022/10/07 09:14:32 - mmengine - INFO - Epoch(train) [9][680/2119] lr: 3.6000e-02 eta: 1 day, 3:59:43 time: 0.3765 data_time: 0.0253 memory: 5826 grad_norm: 3.1482 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7564 loss: 2.7564 2022/10/07 09:14:38 - mmengine - INFO - Epoch(train) [9][700/2119] lr: 3.6000e-02 eta: 1 day, 3:59:22 time: 0.2932 data_time: 0.0175 memory: 5826 grad_norm: 3.2169 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.9206 loss: 2.9206 2022/10/07 09:14:46 - mmengine - INFO - Epoch(train) [9][720/2119] lr: 3.6000e-02 eta: 1 day, 3:59:28 time: 0.3721 data_time: 0.0238 memory: 5826 grad_norm: 3.1459 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8272 loss: 2.8272 2022/10/07 09:14:52 - mmengine - INFO - Epoch(train) [9][740/2119] lr: 3.6000e-02 eta: 1 day, 3:59:06 time: 0.2928 data_time: 0.0210 memory: 5826 grad_norm: 3.1362 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8080 loss: 2.8080 2022/10/07 09:14:58 - mmengine - INFO - Epoch(train) [9][760/2119] lr: 3.6000e-02 eta: 1 day, 3:59:03 time: 0.3461 data_time: 0.0248 memory: 5826 grad_norm: 3.1277 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.0753 loss: 3.0753 2022/10/07 09:15:06 - mmengine - INFO - Epoch(train) [9][780/2119] lr: 3.6000e-02 eta: 1 day, 3:59:06 time: 0.3651 data_time: 0.0180 memory: 5826 grad_norm: 3.1704 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0794 loss: 3.0794 2022/10/07 09:15:12 - mmengine - INFO - Epoch(train) [9][800/2119] lr: 3.6000e-02 eta: 1 day, 3:58:46 time: 0.2959 data_time: 0.0254 memory: 5826 grad_norm: 3.1280 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.9042 loss: 2.9042 2022/10/07 09:15:18 - mmengine - INFO - Epoch(train) [9][820/2119] lr: 3.6000e-02 eta: 1 day, 3:58:35 time: 0.3236 data_time: 0.0234 memory: 5826 grad_norm: 3.0841 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0306 loss: 3.0306 2022/10/07 09:15:25 - mmengine - INFO - Epoch(train) [9][840/2119] lr: 3.6000e-02 eta: 1 day, 3:58:25 time: 0.3249 data_time: 0.0219 memory: 5826 grad_norm: 3.1194 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1719 loss: 3.1719 2022/10/07 09:15:31 - mmengine - INFO - Epoch(train) [9][860/2119] lr: 3.6000e-02 eta: 1 day, 3:58:13 time: 0.3187 data_time: 0.0238 memory: 5826 grad_norm: 3.1499 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1972 loss: 3.1972 2022/10/07 09:15:38 - mmengine - INFO - Epoch(train) [9][880/2119] lr: 3.6000e-02 eta: 1 day, 3:58:12 time: 0.3545 data_time: 0.0258 memory: 5826 grad_norm: 3.1536 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9261 loss: 2.9261 2022/10/07 09:15:45 - mmengine - INFO - Epoch(train) [9][900/2119] lr: 3.6000e-02 eta: 1 day, 3:58:15 time: 0.3644 data_time: 0.0193 memory: 5826 grad_norm: 3.1723 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.9890 loss: 2.9890 2022/10/07 09:15:52 - mmengine - INFO - Epoch(train) [9][920/2119] lr: 3.6000e-02 eta: 1 day, 3:58:02 time: 0.3166 data_time: 0.0220 memory: 5826 grad_norm: 3.1161 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8750 loss: 2.8750 2022/10/07 09:15:59 - mmengine - INFO - Epoch(train) [9][940/2119] lr: 3.6000e-02 eta: 1 day, 3:57:56 time: 0.3383 data_time: 0.0183 memory: 5826 grad_norm: 3.0994 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8173 loss: 2.8173 2022/10/07 09:16:06 - mmengine - INFO - Epoch(train) [9][960/2119] lr: 3.6000e-02 eta: 1 day, 3:57:55 time: 0.3524 data_time: 0.0238 memory: 5826 grad_norm: 3.1354 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0075 loss: 3.0075 2022/10/07 09:16:12 - mmengine - INFO - Epoch(train) [9][980/2119] lr: 3.6000e-02 eta: 1 day, 3:57:49 time: 0.3379 data_time: 0.0212 memory: 5826 grad_norm: 3.1504 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8718 loss: 2.8718 2022/10/07 09:16:19 - mmengine - INFO - Epoch(train) [9][1000/2119] lr: 3.6000e-02 eta: 1 day, 3:57:36 time: 0.3165 data_time: 0.0212 memory: 5826 grad_norm: 3.2025 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9709 loss: 2.9709 2022/10/07 09:16:26 - mmengine - INFO - Epoch(train) [9][1020/2119] lr: 3.6000e-02 eta: 1 day, 3:57:37 time: 0.3593 data_time: 0.0216 memory: 5826 grad_norm: 3.1056 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.3751 loss: 3.3751 2022/10/07 09:16:32 - mmengine - INFO - Epoch(train) [9][1040/2119] lr: 3.6000e-02 eta: 1 day, 3:57:25 time: 0.3174 data_time: 0.0206 memory: 5826 grad_norm: 3.1720 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 3.0227 loss: 3.0227 2022/10/07 09:16:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 09:16:39 - mmengine - INFO - Epoch(train) [9][1060/2119] lr: 3.6000e-02 eta: 1 day, 3:57:21 time: 0.3453 data_time: 0.0280 memory: 5826 grad_norm: 3.1606 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.9703 loss: 2.9703 2022/10/07 09:16:45 - mmengine - INFO - Epoch(train) [9][1080/2119] lr: 3.6000e-02 eta: 1 day, 3:57:03 time: 0.3012 data_time: 0.0187 memory: 5826 grad_norm: 3.1489 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8718 loss: 2.8718 2022/10/07 09:16:53 - mmengine - INFO - Epoch(train) [9][1100/2119] lr: 3.6000e-02 eta: 1 day, 3:57:10 time: 0.3780 data_time: 0.0156 memory: 5826 grad_norm: 3.1341 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9652 loss: 2.9652 2022/10/07 09:16:58 - mmengine - INFO - Epoch(train) [9][1120/2119] lr: 3.6000e-02 eta: 1 day, 3:56:44 time: 0.2759 data_time: 0.0228 memory: 5826 grad_norm: 3.1596 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8737 loss: 2.8737 2022/10/07 09:17:05 - mmengine - INFO - Epoch(train) [9][1140/2119] lr: 3.6000e-02 eta: 1 day, 3:56:40 time: 0.3451 data_time: 0.0183 memory: 5826 grad_norm: 3.0858 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9916 loss: 2.9916 2022/10/07 09:17:12 - mmengine - INFO - Epoch(train) [9][1160/2119] lr: 3.6000e-02 eta: 1 day, 3:56:33 time: 0.3348 data_time: 0.0255 memory: 5826 grad_norm: 3.1575 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7561 loss: 2.7561 2022/10/07 09:17:18 - mmengine - INFO - Epoch(train) [9][1180/2119] lr: 3.6000e-02 eta: 1 day, 3:56:23 time: 0.3262 data_time: 0.0211 memory: 5826 grad_norm: 3.0750 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0873 loss: 3.0873 2022/10/07 09:17:25 - mmengine - INFO - Epoch(train) [9][1200/2119] lr: 3.6000e-02 eta: 1 day, 3:56:16 time: 0.3348 data_time: 0.0306 memory: 5826 grad_norm: 3.1826 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0083 loss: 3.0083 2022/10/07 09:17:32 - mmengine - INFO - Epoch(train) [9][1220/2119] lr: 3.6000e-02 eta: 1 day, 3:56:11 time: 0.3398 data_time: 0.0226 memory: 5826 grad_norm: 3.1466 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8611 loss: 2.8611 2022/10/07 09:17:38 - mmengine - INFO - Epoch(train) [9][1240/2119] lr: 3.6000e-02 eta: 1 day, 3:56:02 time: 0.3274 data_time: 0.0199 memory: 5826 grad_norm: 3.1108 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 2.7829 loss: 2.7829 2022/10/07 09:17:46 - mmengine - INFO - Epoch(train) [9][1260/2119] lr: 3.6000e-02 eta: 1 day, 3:56:11 time: 0.3831 data_time: 0.0163 memory: 5826 grad_norm: 3.1088 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9221 loss: 2.9221 2022/10/07 09:17:52 - mmengine - INFO - Epoch(train) [9][1280/2119] lr: 3.6000e-02 eta: 1 day, 3:55:52 time: 0.2984 data_time: 0.0215 memory: 5826 grad_norm: 3.1095 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9444 loss: 2.9444 2022/10/07 09:17:59 - mmengine - INFO - Epoch(train) [9][1300/2119] lr: 3.6000e-02 eta: 1 day, 3:55:52 time: 0.3571 data_time: 0.0190 memory: 5826 grad_norm: 3.1363 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.9007 loss: 2.9007 2022/10/07 09:18:05 - mmengine - INFO - Epoch(train) [9][1320/2119] lr: 3.6000e-02 eta: 1 day, 3:55:34 time: 0.3015 data_time: 0.0194 memory: 5826 grad_norm: 3.1292 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1135 loss: 3.1135 2022/10/07 09:18:13 - mmengine - INFO - Epoch(train) [9][1340/2119] lr: 3.6000e-02 eta: 1 day, 3:55:46 time: 0.3915 data_time: 0.0198 memory: 5826 grad_norm: 3.1239 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8601 loss: 2.8601 2022/10/07 09:18:19 - mmengine - INFO - Epoch(train) [9][1360/2119] lr: 3.6000e-02 eta: 1 day, 3:55:28 time: 0.3002 data_time: 0.0240 memory: 5826 grad_norm: 3.1433 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.7766 loss: 2.7766 2022/10/07 09:18:27 - mmengine - INFO - Epoch(train) [9][1380/2119] lr: 3.6000e-02 eta: 1 day, 3:55:45 time: 0.4095 data_time: 0.0360 memory: 5826 grad_norm: 3.1194 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8674 loss: 2.8674 2022/10/07 09:18:34 - mmengine - INFO - Epoch(train) [9][1400/2119] lr: 3.6000e-02 eta: 1 day, 3:55:31 time: 0.3138 data_time: 0.0217 memory: 5826 grad_norm: 3.0769 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 3.0474 loss: 3.0474 2022/10/07 09:18:40 - mmengine - INFO - Epoch(train) [9][1420/2119] lr: 3.6000e-02 eta: 1 day, 3:55:28 time: 0.3482 data_time: 0.0211 memory: 5826 grad_norm: 3.1183 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9742 loss: 2.9742 2022/10/07 09:18:47 - mmengine - INFO - Epoch(train) [9][1440/2119] lr: 3.6000e-02 eta: 1 day, 3:55:14 time: 0.3112 data_time: 0.0196 memory: 5826 grad_norm: 3.1053 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.9681 loss: 2.9681 2022/10/07 09:18:54 - mmengine - INFO - Epoch(train) [9][1460/2119] lr: 3.6000e-02 eta: 1 day, 3:55:21 time: 0.3795 data_time: 0.0205 memory: 5826 grad_norm: 3.1152 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7598 loss: 2.7598 2022/10/07 09:19:01 - mmengine - INFO - Epoch(train) [9][1480/2119] lr: 3.6000e-02 eta: 1 day, 3:55:17 time: 0.3442 data_time: 0.0221 memory: 5826 grad_norm: 3.1565 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.9575 loss: 2.9575 2022/10/07 09:19:09 - mmengine - INFO - Epoch(train) [9][1500/2119] lr: 3.6000e-02 eta: 1 day, 3:55:29 time: 0.3911 data_time: 0.0208 memory: 5826 grad_norm: 3.1417 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9621 loss: 2.9621 2022/10/07 09:19:15 - mmengine - INFO - Epoch(train) [9][1520/2119] lr: 3.6000e-02 eta: 1 day, 3:55:09 time: 0.2975 data_time: 0.0213 memory: 5826 grad_norm: 3.0819 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9951 loss: 2.9951 2022/10/07 09:19:23 - mmengine - INFO - Epoch(train) [9][1540/2119] lr: 3.6000e-02 eta: 1 day, 3:55:20 time: 0.3875 data_time: 0.0215 memory: 5826 grad_norm: 3.0984 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.8983 loss: 2.8983 2022/10/07 09:19:29 - mmengine - INFO - Epoch(train) [9][1560/2119] lr: 3.6000e-02 eta: 1 day, 3:55:03 time: 0.3054 data_time: 0.0202 memory: 5826 grad_norm: 3.0924 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9323 loss: 2.9323 2022/10/07 09:19:35 - mmengine - INFO - Epoch(train) [9][1580/2119] lr: 3.6000e-02 eta: 1 day, 3:54:49 time: 0.3126 data_time: 0.0201 memory: 5826 grad_norm: 3.1232 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8626 loss: 2.8626 2022/10/07 09:19:41 - mmengine - INFO - Epoch(train) [9][1600/2119] lr: 3.6000e-02 eta: 1 day, 3:54:34 time: 0.3107 data_time: 0.0268 memory: 5826 grad_norm: 3.0970 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7960 loss: 2.7960 2022/10/07 09:19:48 - mmengine - INFO - Epoch(train) [9][1620/2119] lr: 3.6000e-02 eta: 1 day, 3:54:27 time: 0.3362 data_time: 0.0161 memory: 5826 grad_norm: 3.1428 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8591 loss: 2.8591 2022/10/07 09:19:54 - mmengine - INFO - Epoch(train) [9][1640/2119] lr: 3.6000e-02 eta: 1 day, 3:54:17 time: 0.3234 data_time: 0.0227 memory: 5826 grad_norm: 3.1619 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9199 loss: 2.9199 2022/10/07 09:20:01 - mmengine - INFO - Epoch(train) [9][1660/2119] lr: 3.6000e-02 eta: 1 day, 3:54:11 time: 0.3372 data_time: 0.0199 memory: 5826 grad_norm: 3.1415 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0036 loss: 3.0036 2022/10/07 09:20:07 - mmengine - INFO - Epoch(train) [9][1680/2119] lr: 3.6000e-02 eta: 1 day, 3:53:56 time: 0.3111 data_time: 0.0217 memory: 5826 grad_norm: 3.0804 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0357 loss: 3.0357 2022/10/07 09:20:14 - mmengine - INFO - Epoch(train) [9][1700/2119] lr: 3.6000e-02 eta: 1 day, 3:53:46 time: 0.3242 data_time: 0.0240 memory: 5826 grad_norm: 3.1198 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8438 loss: 2.8438 2022/10/07 09:20:26 - mmengine - INFO - Epoch(train) [9][1720/2119] lr: 3.6000e-02 eta: 1 day, 3:55:04 time: 0.6006 data_time: 0.0198 memory: 5826 grad_norm: 3.0957 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8640 loss: 2.8640 2022/10/07 09:20:33 - mmengine - INFO - Epoch(train) [9][1740/2119] lr: 3.6000e-02 eta: 1 day, 3:54:55 time: 0.3305 data_time: 0.0207 memory: 5826 grad_norm: 3.0703 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0178 loss: 3.0178 2022/10/07 09:20:40 - mmengine - INFO - Epoch(train) [9][1760/2119] lr: 3.6000e-02 eta: 1 day, 3:54:54 time: 0.3525 data_time: 0.0244 memory: 5826 grad_norm: 3.0690 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.9016 loss: 2.9016 2022/10/07 09:20:46 - mmengine - INFO - Epoch(train) [9][1780/2119] lr: 3.6000e-02 eta: 1 day, 3:54:48 time: 0.3401 data_time: 0.0231 memory: 5826 grad_norm: 3.0772 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9323 loss: 2.9323 2022/10/07 09:20:52 - mmengine - INFO - Epoch(train) [9][1800/2119] lr: 3.6000e-02 eta: 1 day, 3:54:24 time: 0.2807 data_time: 0.0182 memory: 5826 grad_norm: 3.1057 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 3.0945 loss: 3.0945 2022/10/07 09:20:59 - mmengine - INFO - Epoch(train) [9][1820/2119] lr: 3.6000e-02 eta: 1 day, 3:54:25 time: 0.3610 data_time: 0.0241 memory: 5826 grad_norm: 3.0509 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.1717 loss: 3.1717 2022/10/07 09:21:06 - mmengine - INFO - Epoch(train) [9][1840/2119] lr: 3.6000e-02 eta: 1 day, 3:54:22 time: 0.3480 data_time: 0.0242 memory: 5826 grad_norm: 3.1422 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0751 loss: 3.0751 2022/10/07 09:21:13 - mmengine - INFO - Epoch(train) [9][1860/2119] lr: 3.6000e-02 eta: 1 day, 3:54:21 time: 0.3520 data_time: 0.0188 memory: 5826 grad_norm: 3.1266 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8458 loss: 2.8458 2022/10/07 09:21:19 - mmengine - INFO - Epoch(train) [9][1880/2119] lr: 3.6000e-02 eta: 1 day, 3:54:05 time: 0.3068 data_time: 0.0347 memory: 5826 grad_norm: 3.0923 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9031 loss: 2.9031 2022/10/07 09:21:26 - mmengine - INFO - Epoch(train) [9][1900/2119] lr: 3.6000e-02 eta: 1 day, 3:54:00 time: 0.3412 data_time: 0.0212 memory: 5826 grad_norm: 3.0994 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9589 loss: 2.9589 2022/10/07 09:21:33 - mmengine - INFO - Epoch(train) [9][1920/2119] lr: 3.6000e-02 eta: 1 day, 3:53:53 time: 0.3340 data_time: 0.0233 memory: 5826 grad_norm: 3.0973 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8467 loss: 2.8467 2022/10/07 09:21:40 - mmengine - INFO - Epoch(train) [9][1940/2119] lr: 3.6000e-02 eta: 1 day, 3:53:57 time: 0.3712 data_time: 0.0248 memory: 5826 grad_norm: 3.0981 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 3.0288 loss: 3.0288 2022/10/07 09:21:47 - mmengine - INFO - Epoch(train) [9][1960/2119] lr: 3.6000e-02 eta: 1 day, 3:53:48 time: 0.3294 data_time: 0.0191 memory: 5826 grad_norm: 3.1085 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9737 loss: 2.9737 2022/10/07 09:21:54 - mmengine - INFO - Epoch(train) [9][1980/2119] lr: 3.6000e-02 eta: 1 day, 3:53:40 time: 0.3315 data_time: 0.0214 memory: 5826 grad_norm: 3.1308 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9744 loss: 2.9744 2022/10/07 09:22:00 - mmengine - INFO - Epoch(train) [9][2000/2119] lr: 3.6000e-02 eta: 1 day, 3:53:31 time: 0.3278 data_time: 0.0252 memory: 5826 grad_norm: 3.0811 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.1215 loss: 3.1215 2022/10/07 09:22:07 - mmengine - INFO - Epoch(train) [9][2020/2119] lr: 3.6000e-02 eta: 1 day, 3:53:23 time: 0.3326 data_time: 0.0184 memory: 5826 grad_norm: 3.0851 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0413 loss: 3.0413 2022/10/07 09:22:15 - mmengine - INFO - Epoch(train) [9][2040/2119] lr: 3.6000e-02 eta: 1 day, 3:53:39 time: 0.4087 data_time: 0.0199 memory: 5826 grad_norm: 3.0521 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.0657 loss: 3.0657 2022/10/07 09:22:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 09:22:22 - mmengine - INFO - Epoch(train) [9][2060/2119] lr: 3.6000e-02 eta: 1 day, 3:53:39 time: 0.3564 data_time: 0.0233 memory: 5826 grad_norm: 3.0454 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0832 loss: 3.0832 2022/10/07 09:22:29 - mmengine - INFO - Epoch(train) [9][2080/2119] lr: 3.6000e-02 eta: 1 day, 3:53:32 time: 0.3352 data_time: 0.0214 memory: 5826 grad_norm: 3.1112 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7296 loss: 2.7296 2022/10/07 09:22:36 - mmengine - INFO - Epoch(train) [9][2100/2119] lr: 3.6000e-02 eta: 1 day, 3:53:35 time: 0.3689 data_time: 0.0225 memory: 5826 grad_norm: 3.1351 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.1287 loss: 3.1287 2022/10/07 09:22:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 09:22:42 - mmengine - INFO - Epoch(train) [9][2119/2119] lr: 3.6000e-02 eta: 1 day, 3:53:35 time: 0.3058 data_time: 0.0168 memory: 5826 grad_norm: 3.1633 top1_acc: 0.3000 top5_acc: 0.5000 loss_cls: 3.1204 loss: 3.1204 2022/10/07 09:22:51 - mmengine - INFO - Epoch(train) [10][20/2119] lr: 4.0000e-02 eta: 1 day, 3:52:21 time: 0.4608 data_time: 0.1271 memory: 5826 grad_norm: 3.0894 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8214 loss: 2.8214 2022/10/07 09:22:57 - mmengine - INFO - Epoch(train) [10][40/2119] lr: 4.0000e-02 eta: 1 day, 3:52:08 time: 0.3138 data_time: 0.0228 memory: 5826 grad_norm: 3.1114 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.8947 loss: 2.8947 2022/10/07 09:23:05 - mmengine - INFO - Epoch(train) [10][60/2119] lr: 4.0000e-02 eta: 1 day, 3:52:11 time: 0.3682 data_time: 0.0252 memory: 5826 grad_norm: 3.0515 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1202 loss: 3.1202 2022/10/07 09:23:11 - mmengine - INFO - Epoch(train) [10][80/2119] lr: 4.0000e-02 eta: 1 day, 3:52:06 time: 0.3412 data_time: 0.0211 memory: 5826 grad_norm: 3.0745 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7969 loss: 2.7969 2022/10/07 09:23:18 - mmengine - INFO - Epoch(train) [10][100/2119] lr: 4.0000e-02 eta: 1 day, 3:52:04 time: 0.3519 data_time: 0.0202 memory: 5826 grad_norm: 3.1225 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8146 loss: 2.8146 2022/10/07 09:23:25 - mmengine - INFO - Epoch(train) [10][120/2119] lr: 4.0000e-02 eta: 1 day, 3:51:53 time: 0.3204 data_time: 0.0207 memory: 5826 grad_norm: 3.0838 top1_acc: 0.3125 top5_acc: 0.8750 loss_cls: 2.7960 loss: 2.7960 2022/10/07 09:23:32 - mmengine - INFO - Epoch(train) [10][140/2119] lr: 4.0000e-02 eta: 1 day, 3:51:59 time: 0.3787 data_time: 0.0178 memory: 5826 grad_norm: 3.0845 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.1035 loss: 3.1035 2022/10/07 09:23:45 - mmengine - INFO - Epoch(train) [10][160/2119] lr: 4.0000e-02 eta: 1 day, 3:53:30 time: 0.6483 data_time: 0.3027 memory: 5826 grad_norm: 3.1421 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.1345 loss: 3.1345 2022/10/07 09:23:50 - mmengine - INFO - Epoch(train) [10][180/2119] lr: 4.0000e-02 eta: 1 day, 3:52:58 time: 0.2565 data_time: 0.0235 memory: 5826 grad_norm: 3.0515 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.1005 loss: 3.1005 2022/10/07 09:23:56 - mmengine - INFO - Epoch(train) [10][200/2119] lr: 4.0000e-02 eta: 1 day, 3:52:38 time: 0.2935 data_time: 0.0627 memory: 5826 grad_norm: 3.0789 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.9682 loss: 2.9682 2022/10/07 09:24:04 - mmengine - INFO - Epoch(train) [10][220/2119] lr: 4.0000e-02 eta: 1 day, 3:52:43 time: 0.3742 data_time: 0.0328 memory: 5826 grad_norm: 3.0710 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9379 loss: 2.9379 2022/10/07 09:24:10 - mmengine - INFO - Epoch(train) [10][240/2119] lr: 4.0000e-02 eta: 1 day, 3:52:35 time: 0.3307 data_time: 0.0414 memory: 5826 grad_norm: 3.1143 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7686 loss: 2.7686 2022/10/07 09:24:17 - mmengine - INFO - Epoch(train) [10][260/2119] lr: 4.0000e-02 eta: 1 day, 3:52:32 time: 0.3470 data_time: 0.0177 memory: 5826 grad_norm: 3.0746 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9903 loss: 2.9903 2022/10/07 09:24:25 - mmengine - INFO - Epoch(train) [10][280/2119] lr: 4.0000e-02 eta: 1 day, 3:52:37 time: 0.3753 data_time: 0.0774 memory: 5826 grad_norm: 3.1233 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8938 loss: 2.8938 2022/10/07 09:24:32 - mmengine - INFO - Epoch(train) [10][300/2119] lr: 4.0000e-02 eta: 1 day, 3:52:38 time: 0.3625 data_time: 0.1263 memory: 5826 grad_norm: 3.0506 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.0077 loss: 3.0077 2022/10/07 09:24:38 - mmengine - INFO - Epoch(train) [10][320/2119] lr: 4.0000e-02 eta: 1 day, 3:52:22 time: 0.3054 data_time: 0.0760 memory: 5826 grad_norm: 3.0481 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8565 loss: 2.8565 2022/10/07 09:24:45 - mmengine - INFO - Epoch(train) [10][340/2119] lr: 4.0000e-02 eta: 1 day, 3:52:15 time: 0.3353 data_time: 0.0538 memory: 5826 grad_norm: 3.0178 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 3.0165 loss: 3.0165 2022/10/07 09:24:53 - mmengine - INFO - Epoch(train) [10][360/2119] lr: 4.0000e-02 eta: 1 day, 3:52:32 time: 0.4131 data_time: 0.0204 memory: 5826 grad_norm: 3.0624 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0994 loss: 3.0994 2022/10/07 09:25:00 - mmengine - INFO - Epoch(train) [10][380/2119] lr: 4.0000e-02 eta: 1 day, 3:52:28 time: 0.3453 data_time: 0.0252 memory: 5826 grad_norm: 3.0614 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8733 loss: 2.8733 2022/10/07 09:25:07 - mmengine - INFO - Epoch(train) [10][400/2119] lr: 4.0000e-02 eta: 1 day, 3:52:17 time: 0.3224 data_time: 0.0212 memory: 5826 grad_norm: 3.0635 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9404 loss: 2.9404 2022/10/07 09:25:14 - mmengine - INFO - Epoch(train) [10][420/2119] lr: 4.0000e-02 eta: 1 day, 3:52:20 time: 0.3668 data_time: 0.0187 memory: 5826 grad_norm: 3.0242 top1_acc: 0.0625 top5_acc: 0.2500 loss_cls: 2.9493 loss: 2.9493 2022/10/07 09:25:20 - mmengine - INFO - Epoch(train) [10][440/2119] lr: 4.0000e-02 eta: 1 day, 3:52:10 time: 0.3272 data_time: 0.0294 memory: 5826 grad_norm: 3.0157 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.1394 loss: 3.1394 2022/10/07 09:25:27 - mmengine - INFO - Epoch(train) [10][460/2119] lr: 4.0000e-02 eta: 1 day, 3:52:05 time: 0.3423 data_time: 0.0225 memory: 5826 grad_norm: 3.0216 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.5626 loss: 2.5626 2022/10/07 09:25:33 - mmengine - INFO - Epoch(train) [10][480/2119] lr: 4.0000e-02 eta: 1 day, 3:51:46 time: 0.2962 data_time: 0.0172 memory: 5826 grad_norm: 3.0632 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0089 loss: 3.0089 2022/10/07 09:25:40 - mmengine - INFO - Epoch(train) [10][500/2119] lr: 4.0000e-02 eta: 1 day, 3:51:38 time: 0.3295 data_time: 0.0228 memory: 5826 grad_norm: 3.0786 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.0299 loss: 3.0299 2022/10/07 09:25:46 - mmengine - INFO - Epoch(train) [10][520/2119] lr: 4.0000e-02 eta: 1 day, 3:51:29 time: 0.3284 data_time: 0.0223 memory: 5826 grad_norm: 3.0064 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0524 loss: 3.0524 2022/10/07 09:25:53 - mmengine - INFO - Epoch(train) [10][540/2119] lr: 4.0000e-02 eta: 1 day, 3:51:24 time: 0.3437 data_time: 0.0195 memory: 5826 grad_norm: 2.9981 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.9793 loss: 2.9793 2022/10/07 09:26:00 - mmengine - INFO - Epoch(train) [10][560/2119] lr: 4.0000e-02 eta: 1 day, 3:51:21 time: 0.3467 data_time: 0.0257 memory: 5826 grad_norm: 2.9720 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9175 loss: 2.9175 2022/10/07 09:26:08 - mmengine - INFO - Epoch(train) [10][580/2119] lr: 4.0000e-02 eta: 1 day, 3:51:36 time: 0.4097 data_time: 0.0182 memory: 5826 grad_norm: 3.0689 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9483 loss: 2.9483 2022/10/07 09:26:14 - mmengine - INFO - Epoch(train) [10][600/2119] lr: 4.0000e-02 eta: 1 day, 3:51:19 time: 0.3011 data_time: 0.0235 memory: 5826 grad_norm: 3.0752 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9625 loss: 2.9625 2022/10/07 09:26:22 - mmengine - INFO - Epoch(train) [10][620/2119] lr: 4.0000e-02 eta: 1 day, 3:51:24 time: 0.3757 data_time: 0.0218 memory: 5826 grad_norm: 3.0688 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9196 loss: 2.9196 2022/10/07 09:26:28 - mmengine - INFO - Epoch(train) [10][640/2119] lr: 4.0000e-02 eta: 1 day, 3:51:07 time: 0.3021 data_time: 0.0221 memory: 5826 grad_norm: 3.0378 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1418 loss: 3.1418 2022/10/07 09:26:35 - mmengine - INFO - Epoch(train) [10][660/2119] lr: 4.0000e-02 eta: 1 day, 3:50:59 time: 0.3329 data_time: 0.0189 memory: 5826 grad_norm: 3.0596 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0133 loss: 3.0133 2022/10/07 09:26:41 - mmengine - INFO - Epoch(train) [10][680/2119] lr: 4.0000e-02 eta: 1 day, 3:50:53 time: 0.3371 data_time: 0.0258 memory: 5826 grad_norm: 3.0404 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0879 loss: 3.0879 2022/10/07 09:26:48 - mmengine - INFO - Epoch(train) [10][700/2119] lr: 4.0000e-02 eta: 1 day, 3:50:45 time: 0.3350 data_time: 0.0242 memory: 5826 grad_norm: 3.0551 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0202 loss: 3.0202 2022/10/07 09:26:55 - mmengine - INFO - Epoch(train) [10][720/2119] lr: 4.0000e-02 eta: 1 day, 3:50:38 time: 0.3338 data_time: 0.0262 memory: 5826 grad_norm: 3.0145 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7870 loss: 2.7870 2022/10/07 09:27:01 - mmengine - INFO - Epoch(train) [10][740/2119] lr: 4.0000e-02 eta: 1 day, 3:50:27 time: 0.3238 data_time: 0.0237 memory: 5826 grad_norm: 3.0518 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9031 loss: 2.9031 2022/10/07 09:27:07 - mmengine - INFO - Epoch(train) [10][760/2119] lr: 4.0000e-02 eta: 1 day, 3:50:13 time: 0.3112 data_time: 0.0231 memory: 5826 grad_norm: 2.9859 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8458 loss: 2.8458 2022/10/07 09:27:14 - mmengine - INFO - Epoch(train) [10][780/2119] lr: 4.0000e-02 eta: 1 day, 3:50:04 time: 0.3268 data_time: 0.0180 memory: 5826 grad_norm: 2.9862 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.1877 loss: 3.1877 2022/10/07 09:27:21 - mmengine - INFO - Epoch(train) [10][800/2119] lr: 4.0000e-02 eta: 1 day, 3:50:01 time: 0.3486 data_time: 0.0230 memory: 5826 grad_norm: 3.0313 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7431 loss: 2.7431 2022/10/07 09:27:28 - mmengine - INFO - Epoch(train) [10][820/2119] lr: 4.0000e-02 eta: 1 day, 3:49:56 time: 0.3424 data_time: 0.0260 memory: 5826 grad_norm: 3.0548 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0331 loss: 3.0331 2022/10/07 09:27:35 - mmengine - INFO - Epoch(train) [10][840/2119] lr: 4.0000e-02 eta: 1 day, 3:49:56 time: 0.3609 data_time: 0.0238 memory: 5826 grad_norm: 3.0753 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9525 loss: 2.9525 2022/10/07 09:27:41 - mmengine - INFO - Epoch(train) [10][860/2119] lr: 4.0000e-02 eta: 1 day, 3:49:46 time: 0.3235 data_time: 0.0200 memory: 5826 grad_norm: 2.9881 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.8992 loss: 2.8992 2022/10/07 09:27:48 - mmengine - INFO - Epoch(train) [10][880/2119] lr: 4.0000e-02 eta: 1 day, 3:49:34 time: 0.3196 data_time: 0.0194 memory: 5826 grad_norm: 3.0225 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0523 loss: 3.0523 2022/10/07 09:27:54 - mmengine - INFO - Epoch(train) [10][900/2119] lr: 4.0000e-02 eta: 1 day, 3:49:22 time: 0.3198 data_time: 0.0198 memory: 5826 grad_norm: 3.0344 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0209 loss: 3.0209 2022/10/07 09:28:02 - mmengine - INFO - Epoch(train) [10][920/2119] lr: 4.0000e-02 eta: 1 day, 3:49:30 time: 0.3840 data_time: 0.0182 memory: 5826 grad_norm: 3.0374 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.1056 loss: 3.1056 2022/10/07 09:28:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 09:28:08 - mmengine - INFO - Epoch(train) [10][940/2119] lr: 4.0000e-02 eta: 1 day, 3:49:14 time: 0.3066 data_time: 0.0180 memory: 5826 grad_norm: 3.0582 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9205 loss: 2.9205 2022/10/07 09:28:15 - mmengine - INFO - Epoch(train) [10][960/2119] lr: 4.0000e-02 eta: 1 day, 3:49:10 time: 0.3451 data_time: 0.0226 memory: 5826 grad_norm: 3.0266 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9089 loss: 2.9089 2022/10/07 09:28:22 - mmengine - INFO - Epoch(train) [10][980/2119] lr: 4.0000e-02 eta: 1 day, 3:49:08 time: 0.3505 data_time: 0.0239 memory: 5826 grad_norm: 3.0844 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6494 loss: 2.6494 2022/10/07 09:28:29 - mmengine - INFO - Epoch(train) [10][1000/2119] lr: 4.0000e-02 eta: 1 day, 3:48:58 time: 0.3270 data_time: 0.0219 memory: 5826 grad_norm: 3.0685 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.3646 loss: 3.3646 2022/10/07 09:28:35 - mmengine - INFO - Epoch(train) [10][1020/2119] lr: 4.0000e-02 eta: 1 day, 3:48:53 time: 0.3424 data_time: 0.0202 memory: 5826 grad_norm: 3.0328 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9701 loss: 2.9701 2022/10/07 09:28:43 - mmengine - INFO - Epoch(train) [10][1040/2119] lr: 4.0000e-02 eta: 1 day, 3:48:53 time: 0.3576 data_time: 0.0206 memory: 5826 grad_norm: 2.9718 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.1192 loss: 3.1192 2022/10/07 09:28:49 - mmengine - INFO - Epoch(train) [10][1060/2119] lr: 4.0000e-02 eta: 1 day, 3:48:38 time: 0.3099 data_time: 0.0266 memory: 5826 grad_norm: 2.9830 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7163 loss: 2.7163 2022/10/07 09:28:56 - mmengine - INFO - Epoch(train) [10][1080/2119] lr: 4.0000e-02 eta: 1 day, 3:48:38 time: 0.3567 data_time: 0.0201 memory: 5826 grad_norm: 3.0214 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.9929 loss: 2.9929 2022/10/07 09:29:03 - mmengine - INFO - Epoch(train) [10][1100/2119] lr: 4.0000e-02 eta: 1 day, 3:48:32 time: 0.3395 data_time: 0.0204 memory: 5826 grad_norm: 2.9702 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9477 loss: 2.9477 2022/10/07 09:29:10 - mmengine - INFO - Epoch(train) [10][1120/2119] lr: 4.0000e-02 eta: 1 day, 3:48:37 time: 0.3772 data_time: 0.0220 memory: 5826 grad_norm: 2.9957 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8843 loss: 2.8843 2022/10/07 09:29:17 - mmengine - INFO - Epoch(train) [10][1140/2119] lr: 4.0000e-02 eta: 1 day, 3:48:27 time: 0.3229 data_time: 0.0179 memory: 5826 grad_norm: 3.0981 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7784 loss: 2.7784 2022/10/07 09:29:24 - mmengine - INFO - Epoch(train) [10][1160/2119] lr: 4.0000e-02 eta: 1 day, 3:48:36 time: 0.3916 data_time: 0.0214 memory: 5826 grad_norm: 2.9727 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.0637 loss: 3.0637 2022/10/07 09:29:31 - mmengine - INFO - Epoch(train) [10][1180/2119] lr: 4.0000e-02 eta: 1 day, 3:48:20 time: 0.3047 data_time: 0.0209 memory: 5826 grad_norm: 3.0159 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0429 loss: 3.0429 2022/10/07 09:29:37 - mmengine - INFO - Epoch(train) [10][1200/2119] lr: 4.0000e-02 eta: 1 day, 3:48:03 time: 0.3021 data_time: 0.0218 memory: 5826 grad_norm: 3.0517 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8618 loss: 2.8618 2022/10/07 09:29:43 - mmengine - INFO - Epoch(train) [10][1220/2119] lr: 4.0000e-02 eta: 1 day, 3:47:57 time: 0.3367 data_time: 0.0246 memory: 5826 grad_norm: 2.9986 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8327 loss: 2.8327 2022/10/07 09:29:50 - mmengine - INFO - Epoch(train) [10][1240/2119] lr: 4.0000e-02 eta: 1 day, 3:47:48 time: 0.3289 data_time: 0.0193 memory: 5826 grad_norm: 3.0173 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8637 loss: 2.8637 2022/10/07 09:29:56 - mmengine - INFO - Epoch(train) [10][1260/2119] lr: 4.0000e-02 eta: 1 day, 3:47:36 time: 0.3188 data_time: 0.0193 memory: 5826 grad_norm: 3.0226 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.2409 loss: 3.2409 2022/10/07 09:30:04 - mmengine - INFO - Epoch(train) [10][1280/2119] lr: 4.0000e-02 eta: 1 day, 3:47:45 time: 0.3917 data_time: 0.0214 memory: 5826 grad_norm: 3.0356 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.1155 loss: 3.1155 2022/10/07 09:30:23 - mmengine - INFO - Epoch(train) [10][1300/2119] lr: 4.0000e-02 eta: 1 day, 3:50:37 time: 0.9454 data_time: 0.6527 memory: 5826 grad_norm: 3.0241 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9226 loss: 2.9226 2022/10/07 09:30:28 - mmengine - INFO - Epoch(train) [10][1320/2119] lr: 4.0000e-02 eta: 1 day, 3:50:09 time: 0.2672 data_time: 0.0241 memory: 5826 grad_norm: 3.0088 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7745 loss: 2.7745 2022/10/07 09:30:34 - mmengine - INFO - Epoch(train) [10][1340/2119] lr: 4.0000e-02 eta: 1 day, 3:49:51 time: 0.2970 data_time: 0.0236 memory: 5826 grad_norm: 3.0698 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7920 loss: 2.7920 2022/10/07 09:30:42 - mmengine - INFO - Epoch(train) [10][1360/2119] lr: 4.0000e-02 eta: 1 day, 3:49:59 time: 0.3886 data_time: 0.0258 memory: 5826 grad_norm: 3.0058 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.1096 loss: 3.1096 2022/10/07 09:30:48 - mmengine - INFO - Epoch(train) [10][1380/2119] lr: 4.0000e-02 eta: 1 day, 3:49:44 time: 0.3070 data_time: 0.0182 memory: 5826 grad_norm: 2.9864 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 3.1791 loss: 3.1791 2022/10/07 09:30:56 - mmengine - INFO - Epoch(train) [10][1400/2119] lr: 4.0000e-02 eta: 1 day, 3:49:48 time: 0.3741 data_time: 0.0261 memory: 5826 grad_norm: 2.9746 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.0076 loss: 3.0076 2022/10/07 09:31:02 - mmengine - INFO - Epoch(train) [10][1420/2119] lr: 4.0000e-02 eta: 1 day, 3:49:29 time: 0.2934 data_time: 0.0200 memory: 5826 grad_norm: 2.9790 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.9845 loss: 2.9845 2022/10/07 09:31:08 - mmengine - INFO - Epoch(train) [10][1440/2119] lr: 4.0000e-02 eta: 1 day, 3:49:23 time: 0.3416 data_time: 0.0246 memory: 5826 grad_norm: 2.9854 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0744 loss: 3.0744 2022/10/07 09:31:15 - mmengine - INFO - Epoch(train) [10][1460/2119] lr: 4.0000e-02 eta: 1 day, 3:49:15 time: 0.3301 data_time: 0.0206 memory: 5826 grad_norm: 2.9391 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.7832 loss: 2.7832 2022/10/07 09:31:23 - mmengine - INFO - Epoch(train) [10][1480/2119] lr: 4.0000e-02 eta: 1 day, 3:49:22 time: 0.3848 data_time: 0.0210 memory: 5826 grad_norm: 3.0331 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.1323 loss: 3.1323 2022/10/07 09:31:29 - mmengine - INFO - Epoch(train) [10][1500/2119] lr: 4.0000e-02 eta: 1 day, 3:49:02 time: 0.2917 data_time: 0.0231 memory: 5826 grad_norm: 3.0237 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9638 loss: 2.9638 2022/10/07 09:31:35 - mmengine - INFO - Epoch(train) [10][1520/2119] lr: 4.0000e-02 eta: 1 day, 3:48:47 time: 0.3088 data_time: 0.0292 memory: 5826 grad_norm: 2.9990 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8191 loss: 2.8191 2022/10/07 09:31:42 - mmengine - INFO - Epoch(train) [10][1540/2119] lr: 4.0000e-02 eta: 1 day, 3:48:47 time: 0.3614 data_time: 0.0234 memory: 5826 grad_norm: 2.9856 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 3.1734 loss: 3.1734 2022/10/07 09:31:49 - mmengine - INFO - Epoch(train) [10][1560/2119] lr: 4.0000e-02 eta: 1 day, 3:48:38 time: 0.3291 data_time: 0.0261 memory: 5826 grad_norm: 3.0022 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9546 loss: 2.9546 2022/10/07 09:31:56 - mmengine - INFO - Epoch(train) [10][1580/2119] lr: 4.0000e-02 eta: 1 day, 3:48:36 time: 0.3509 data_time: 0.0129 memory: 5826 grad_norm: 3.0464 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.1401 loss: 3.1401 2022/10/07 09:32:02 - mmengine - INFO - Epoch(train) [10][1600/2119] lr: 4.0000e-02 eta: 1 day, 3:48:28 time: 0.3323 data_time: 0.0344 memory: 5826 grad_norm: 3.0098 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9956 loss: 2.9956 2022/10/07 09:32:08 - mmengine - INFO - Epoch(train) [10][1620/2119] lr: 4.0000e-02 eta: 1 day, 3:48:13 time: 0.3106 data_time: 0.0215 memory: 5826 grad_norm: 2.9861 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7571 loss: 2.7571 2022/10/07 09:32:15 - mmengine - INFO - Epoch(train) [10][1640/2119] lr: 4.0000e-02 eta: 1 day, 3:48:11 time: 0.3512 data_time: 0.0186 memory: 5826 grad_norm: 2.9803 top1_acc: 0.3750 top5_acc: 0.9375 loss_cls: 2.8433 loss: 2.8433 2022/10/07 09:32:21 - mmengine - INFO - Epoch(train) [10][1660/2119] lr: 4.0000e-02 eta: 1 day, 3:47:52 time: 0.2955 data_time: 0.0221 memory: 5826 grad_norm: 3.0518 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 3.0233 loss: 3.0233 2022/10/07 09:32:29 - mmengine - INFO - Epoch(train) [10][1680/2119] lr: 4.0000e-02 eta: 1 day, 3:48:01 time: 0.3893 data_time: 0.0313 memory: 5826 grad_norm: 3.0331 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9032 loss: 2.9032 2022/10/07 09:32:36 - mmengine - INFO - Epoch(train) [10][1700/2119] lr: 4.0000e-02 eta: 1 day, 3:47:49 time: 0.3184 data_time: 0.0155 memory: 5826 grad_norm: 2.9970 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0930 loss: 3.0930 2022/10/07 09:32:43 - mmengine - INFO - Epoch(train) [10][1720/2119] lr: 4.0000e-02 eta: 1 day, 3:47:55 time: 0.3817 data_time: 0.0237 memory: 5826 grad_norm: 3.0097 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9295 loss: 2.9295 2022/10/07 09:32:50 - mmengine - INFO - Epoch(train) [10][1740/2119] lr: 4.0000e-02 eta: 1 day, 3:47:43 time: 0.3188 data_time: 0.0141 memory: 5826 grad_norm: 2.9766 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6971 loss: 2.6971 2022/10/07 09:32:56 - mmengine - INFO - Epoch(train) [10][1760/2119] lr: 4.0000e-02 eta: 1 day, 3:47:29 time: 0.3127 data_time: 0.0221 memory: 5826 grad_norm: 2.9435 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9000 loss: 2.9000 2022/10/07 09:33:02 - mmengine - INFO - Epoch(train) [10][1780/2119] lr: 4.0000e-02 eta: 1 day, 3:47:17 time: 0.3190 data_time: 0.0237 memory: 5826 grad_norm: 3.0374 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9162 loss: 2.9162 2022/10/07 09:33:09 - mmengine - INFO - Epoch(train) [10][1800/2119] lr: 4.0000e-02 eta: 1 day, 3:47:14 time: 0.3494 data_time: 0.0209 memory: 5826 grad_norm: 3.0302 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8912 loss: 2.8912 2022/10/07 09:33:15 - mmengine - INFO - Epoch(train) [10][1820/2119] lr: 4.0000e-02 eta: 1 day, 3:47:00 time: 0.3124 data_time: 0.0294 memory: 5826 grad_norm: 2.9967 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8694 loss: 2.8694 2022/10/07 09:33:23 - mmengine - INFO - Epoch(train) [10][1840/2119] lr: 4.0000e-02 eta: 1 day, 3:47:02 time: 0.3646 data_time: 0.0225 memory: 5826 grad_norm: 3.0277 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9259 loss: 2.9259 2022/10/07 09:33:29 - mmengine - INFO - Epoch(train) [10][1860/2119] lr: 4.0000e-02 eta: 1 day, 3:46:51 time: 0.3237 data_time: 0.0238 memory: 5826 grad_norm: 2.9706 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0652 loss: 3.0652 2022/10/07 09:33:36 - mmengine - INFO - Epoch(train) [10][1880/2119] lr: 4.0000e-02 eta: 1 day, 3:46:47 time: 0.3467 data_time: 0.0237 memory: 5826 grad_norm: 3.0166 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2958 loss: 3.2958 2022/10/07 09:33:43 - mmengine - INFO - Epoch(train) [10][1900/2119] lr: 4.0000e-02 eta: 1 day, 3:46:44 time: 0.3495 data_time: 0.0168 memory: 5826 grad_norm: 2.9588 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 3.0785 loss: 3.0785 2022/10/07 09:33:50 - mmengine - INFO - Epoch(train) [10][1920/2119] lr: 4.0000e-02 eta: 1 day, 3:46:40 time: 0.3452 data_time: 0.0206 memory: 5826 grad_norm: 3.0104 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.0599 loss: 3.0599 2022/10/07 09:33:53 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 09:33:56 - mmengine - INFO - Epoch(train) [10][1940/2119] lr: 4.0000e-02 eta: 1 day, 3:46:18 time: 0.2855 data_time: 0.0223 memory: 5826 grad_norm: 2.9736 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 3.0183 loss: 3.0183 2022/10/07 09:34:03 - mmengine - INFO - Epoch(train) [10][1960/2119] lr: 4.0000e-02 eta: 1 day, 3:46:19 time: 0.3624 data_time: 0.0257 memory: 5826 grad_norm: 3.0132 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9416 loss: 2.9416 2022/10/07 09:34:09 - mmengine - INFO - Epoch(train) [10][1980/2119] lr: 4.0000e-02 eta: 1 day, 3:46:04 time: 0.3080 data_time: 0.0247 memory: 5826 grad_norm: 2.9204 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9000 loss: 2.9000 2022/10/07 09:34:16 - mmengine - INFO - Epoch(train) [10][2000/2119] lr: 4.0000e-02 eta: 1 day, 3:45:56 time: 0.3309 data_time: 0.0254 memory: 5826 grad_norm: 2.9984 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.9679 loss: 2.9679 2022/10/07 09:34:22 - mmengine - INFO - Epoch(train) [10][2020/2119] lr: 4.0000e-02 eta: 1 day, 3:45:44 time: 0.3208 data_time: 0.0237 memory: 5826 grad_norm: 3.0558 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7947 loss: 2.7947 2022/10/07 09:34:29 - mmengine - INFO - Epoch(train) [10][2040/2119] lr: 4.0000e-02 eta: 1 day, 3:45:42 time: 0.3526 data_time: 0.0200 memory: 5826 grad_norm: 2.9555 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8889 loss: 2.8889 2022/10/07 09:34:36 - mmengine - INFO - Epoch(train) [10][2060/2119] lr: 4.0000e-02 eta: 1 day, 3:45:34 time: 0.3319 data_time: 0.0189 memory: 5826 grad_norm: 2.9250 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7525 loss: 2.7525 2022/10/07 09:34:43 - mmengine - INFO - Epoch(train) [10][2080/2119] lr: 4.0000e-02 eta: 1 day, 3:45:30 time: 0.3472 data_time: 0.0230 memory: 5826 grad_norm: 2.9885 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6935 loss: 2.6935 2022/10/07 09:34:50 - mmengine - INFO - Epoch(train) [10][2100/2119] lr: 4.0000e-02 eta: 1 day, 3:45:25 time: 0.3429 data_time: 0.0163 memory: 5826 grad_norm: 2.9650 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1306 loss: 3.1306 2022/10/07 09:34:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 09:34:55 - mmengine - INFO - Epoch(train) [10][2119/2119] lr: 4.0000e-02 eta: 1 day, 3:45:25 time: 0.2962 data_time: 0.0158 memory: 5826 grad_norm: 2.9774 top1_acc: 0.3000 top5_acc: 0.6000 loss_cls: 3.0065 loss: 3.0065 2022/10/07 09:35:04 - mmengine - INFO - Epoch(val) [10][20/137] eta: 0:00:50 time: 0.4307 data_time: 0.3628 memory: 1241 2022/10/07 09:35:09 - mmengine - INFO - Epoch(val) [10][40/137] eta: 0:00:26 time: 0.2701 data_time: 0.2039 memory: 1241 2022/10/07 09:35:16 - mmengine - INFO - Epoch(val) [10][60/137] eta: 0:00:25 time: 0.3336 data_time: 0.2693 memory: 1241 2022/10/07 09:35:22 - mmengine - INFO - Epoch(val) [10][80/137] eta: 0:00:17 time: 0.3139 data_time: 0.2485 memory: 1241 2022/10/07 09:35:28 - mmengine - INFO - Epoch(val) [10][100/137] eta: 0:00:10 time: 0.2846 data_time: 0.2210 memory: 1241 2022/10/07 09:35:33 - mmengine - INFO - Epoch(val) [10][120/137] eta: 0:00:04 time: 0.2686 data_time: 0.2038 memory: 1241 2022/10/07 09:35:46 - mmengine - INFO - Epoch(val) [10][137/137] acc/top1: 0.3939 acc/top5: 0.6401 acc/mean1: 0.3937 2022/10/07 09:35:55 - mmengine - INFO - Epoch(train) [11][20/2119] lr: 4.0000e-02 eta: 1 day, 3:44:17 time: 0.4605 data_time: 0.1690 memory: 5826 grad_norm: 2.9588 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9127 loss: 2.9127 2022/10/07 09:36:01 - mmengine - INFO - Epoch(train) [11][40/2119] lr: 4.0000e-02 eta: 1 day, 3:44:03 time: 0.3092 data_time: 0.0313 memory: 5826 grad_norm: 2.9685 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8908 loss: 2.8908 2022/10/07 09:36:09 - mmengine - INFO - Epoch(train) [11][60/2119] lr: 4.0000e-02 eta: 1 day, 3:44:04 time: 0.3644 data_time: 0.0229 memory: 5826 grad_norm: 3.0025 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9799 loss: 2.9799 2022/10/07 09:36:16 - mmengine - INFO - Epoch(train) [11][80/2119] lr: 4.0000e-02 eta: 1 day, 3:44:08 time: 0.3743 data_time: 0.0167 memory: 5826 grad_norm: 2.9539 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9781 loss: 2.9781 2022/10/07 09:36:23 - mmengine - INFO - Epoch(train) [11][100/2119] lr: 4.0000e-02 eta: 1 day, 3:43:56 time: 0.3202 data_time: 0.0244 memory: 5826 grad_norm: 3.0183 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.8269 loss: 2.8269 2022/10/07 09:36:30 - mmengine - INFO - Epoch(train) [11][120/2119] lr: 4.0000e-02 eta: 1 day, 3:44:00 time: 0.3727 data_time: 0.0219 memory: 5826 grad_norm: 2.9689 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7150 loss: 2.7150 2022/10/07 09:36:37 - mmengine - INFO - Epoch(train) [11][140/2119] lr: 4.0000e-02 eta: 1 day, 3:43:50 time: 0.3261 data_time: 0.0237 memory: 5826 grad_norm: 2.9472 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6853 loss: 2.6853 2022/10/07 09:36:44 - mmengine - INFO - Epoch(train) [11][160/2119] lr: 4.0000e-02 eta: 1 day, 3:43:47 time: 0.3500 data_time: 0.0223 memory: 5826 grad_norm: 2.9702 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6619 loss: 2.6619 2022/10/07 09:36:50 - mmengine - INFO - Epoch(train) [11][180/2119] lr: 4.0000e-02 eta: 1 day, 3:43:37 time: 0.3240 data_time: 0.0216 memory: 5826 grad_norm: 3.0110 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.1015 loss: 3.1015 2022/10/07 09:36:57 - mmengine - INFO - Epoch(train) [11][200/2119] lr: 4.0000e-02 eta: 1 day, 3:43:36 time: 0.3603 data_time: 0.0200 memory: 5826 grad_norm: 3.0147 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9943 loss: 2.9943 2022/10/07 09:37:03 - mmengine - INFO - Epoch(train) [11][220/2119] lr: 4.0000e-02 eta: 1 day, 3:43:19 time: 0.2990 data_time: 0.0208 memory: 5826 grad_norm: 3.0064 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8340 loss: 2.8340 2022/10/07 09:37:09 - mmengine - INFO - Epoch(train) [11][240/2119] lr: 4.0000e-02 eta: 1 day, 3:43:06 time: 0.3144 data_time: 0.0247 memory: 5826 grad_norm: 2.9919 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8495 loss: 2.8495 2022/10/07 09:37:17 - mmengine - INFO - Epoch(train) [11][260/2119] lr: 4.0000e-02 eta: 1 day, 3:43:04 time: 0.3541 data_time: 0.0228 memory: 5826 grad_norm: 2.9251 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.1132 loss: 3.1132 2022/10/07 09:37:23 - mmengine - INFO - Epoch(train) [11][280/2119] lr: 4.0000e-02 eta: 1 day, 3:42:55 time: 0.3269 data_time: 0.0240 memory: 5826 grad_norm: 2.9251 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9040 loss: 2.9040 2022/10/07 09:37:30 - mmengine - INFO - Epoch(train) [11][300/2119] lr: 4.0000e-02 eta: 1 day, 3:42:57 time: 0.3665 data_time: 0.0227 memory: 5826 grad_norm: 2.9941 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9560 loss: 2.9560 2022/10/07 09:37:36 - mmengine - INFO - Epoch(train) [11][320/2119] lr: 4.0000e-02 eta: 1 day, 3:42:37 time: 0.2903 data_time: 0.0199 memory: 5826 grad_norm: 2.9936 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9216 loss: 2.9216 2022/10/07 09:37:43 - mmengine - INFO - Epoch(train) [11][340/2119] lr: 4.0000e-02 eta: 1 day, 3:42:28 time: 0.3269 data_time: 0.0195 memory: 5826 grad_norm: 3.0055 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9823 loss: 2.9823 2022/10/07 09:37:50 - mmengine - INFO - Epoch(train) [11][360/2119] lr: 4.0000e-02 eta: 1 day, 3:42:22 time: 0.3424 data_time: 0.0228 memory: 5826 grad_norm: 3.0131 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9697 loss: 2.9697 2022/10/07 09:37:56 - mmengine - INFO - Epoch(train) [11][380/2119] lr: 4.0000e-02 eta: 1 day, 3:42:11 time: 0.3205 data_time: 0.0165 memory: 5826 grad_norm: 2.9936 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.8467 loss: 2.8467 2022/10/07 09:38:04 - mmengine - INFO - Epoch(train) [11][400/2119] lr: 4.0000e-02 eta: 1 day, 3:42:18 time: 0.3873 data_time: 0.0170 memory: 5826 grad_norm: 3.0109 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0560 loss: 3.0560 2022/10/07 09:38:10 - mmengine - INFO - Epoch(train) [11][420/2119] lr: 4.0000e-02 eta: 1 day, 3:42:03 time: 0.3060 data_time: 0.0202 memory: 5826 grad_norm: 2.9671 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7992 loss: 2.7992 2022/10/07 09:38:17 - mmengine - INFO - Epoch(train) [11][440/2119] lr: 4.0000e-02 eta: 1 day, 3:42:06 time: 0.3706 data_time: 0.0245 memory: 5826 grad_norm: 3.0019 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8307 loss: 2.8307 2022/10/07 09:38:23 - mmengine - INFO - Epoch(train) [11][460/2119] lr: 4.0000e-02 eta: 1 day, 3:41:47 time: 0.2913 data_time: 0.0216 memory: 5826 grad_norm: 3.0197 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9901 loss: 2.9901 2022/10/07 09:38:30 - mmengine - INFO - Epoch(train) [11][480/2119] lr: 4.0000e-02 eta: 1 day, 3:41:40 time: 0.3367 data_time: 0.0166 memory: 5826 grad_norm: 2.9648 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 2.8508 loss: 2.8508 2022/10/07 09:38:37 - mmengine - INFO - Epoch(train) [11][500/2119] lr: 4.0000e-02 eta: 1 day, 3:41:33 time: 0.3367 data_time: 0.0220 memory: 5826 grad_norm: 2.9949 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9410 loss: 2.9410 2022/10/07 09:38:43 - mmengine - INFO - Epoch(train) [11][520/2119] lr: 4.0000e-02 eta: 1 day, 3:41:20 time: 0.3122 data_time: 0.0186 memory: 5826 grad_norm: 2.9874 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6424 loss: 2.6424 2022/10/07 09:38:50 - mmengine - INFO - Epoch(train) [11][540/2119] lr: 4.0000e-02 eta: 1 day, 3:41:14 time: 0.3413 data_time: 0.0210 memory: 5826 grad_norm: 2.9374 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8214 loss: 2.8214 2022/10/07 09:38:57 - mmengine - INFO - Epoch(train) [11][560/2119] lr: 4.0000e-02 eta: 1 day, 3:41:21 time: 0.3849 data_time: 0.0188 memory: 5826 grad_norm: 2.9821 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8306 loss: 2.8306 2022/10/07 09:39:03 - mmengine - INFO - Epoch(train) [11][580/2119] lr: 4.0000e-02 eta: 1 day, 3:40:55 time: 0.2651 data_time: 0.0242 memory: 5826 grad_norm: 2.9940 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8015 loss: 2.8015 2022/10/07 09:39:09 - mmengine - INFO - Epoch(train) [11][600/2119] lr: 4.0000e-02 eta: 1 day, 3:40:47 time: 0.3327 data_time: 0.0250 memory: 5826 grad_norm: 3.0509 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8127 loss: 2.8127 2022/10/07 09:39:16 - mmengine - INFO - Epoch(train) [11][620/2119] lr: 4.0000e-02 eta: 1 day, 3:40:42 time: 0.3432 data_time: 0.0227 memory: 5826 grad_norm: 2.9927 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7313 loss: 2.7313 2022/10/07 09:39:23 - mmengine - INFO - Epoch(train) [11][640/2119] lr: 4.0000e-02 eta: 1 day, 3:40:35 time: 0.3366 data_time: 0.0281 memory: 5826 grad_norm: 2.9680 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8637 loss: 2.8637 2022/10/07 09:39:29 - mmengine - INFO - Epoch(train) [11][660/2119] lr: 4.0000e-02 eta: 1 day, 3:40:21 time: 0.3098 data_time: 0.0192 memory: 5826 grad_norm: 2.9938 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9984 loss: 2.9984 2022/10/07 09:39:36 - mmengine - INFO - Epoch(train) [11][680/2119] lr: 4.0000e-02 eta: 1 day, 3:40:12 time: 0.3253 data_time: 0.0239 memory: 5826 grad_norm: 2.9661 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8015 loss: 2.8015 2022/10/07 09:39:43 - mmengine - INFO - Epoch(train) [11][700/2119] lr: 4.0000e-02 eta: 1 day, 3:40:14 time: 0.3715 data_time: 0.0221 memory: 5826 grad_norm: 2.9466 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0822 loss: 3.0822 2022/10/07 09:39:49 - mmengine - INFO - Epoch(train) [11][720/2119] lr: 4.0000e-02 eta: 1 day, 3:40:02 time: 0.3160 data_time: 0.0240 memory: 5826 grad_norm: 2.9934 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7872 loss: 2.7872 2022/10/07 09:39:56 - mmengine - INFO - Epoch(train) [11][740/2119] lr: 4.0000e-02 eta: 1 day, 3:39:55 time: 0.3357 data_time: 0.0210 memory: 5826 grad_norm: 3.0030 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8738 loss: 2.8738 2022/10/07 09:40:03 - mmengine - INFO - Epoch(train) [11][760/2119] lr: 4.0000e-02 eta: 1 day, 3:39:47 time: 0.3307 data_time: 0.0263 memory: 5826 grad_norm: 2.9249 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9214 loss: 2.9214 2022/10/07 09:40:10 - mmengine - INFO - Epoch(train) [11][780/2119] lr: 4.0000e-02 eta: 1 day, 3:39:46 time: 0.3592 data_time: 0.0178 memory: 5826 grad_norm: 2.9079 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0975 loss: 3.0975 2022/10/07 09:40:16 - mmengine - INFO - Epoch(train) [11][800/2119] lr: 4.0000e-02 eta: 1 day, 3:39:36 time: 0.3237 data_time: 0.0259 memory: 5826 grad_norm: 2.9372 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9387 loss: 2.9387 2022/10/07 09:40:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 09:40:23 - mmengine - INFO - Epoch(train) [11][820/2119] lr: 4.0000e-02 eta: 1 day, 3:39:34 time: 0.3533 data_time: 0.0196 memory: 5826 grad_norm: 2.8999 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0326 loss: 3.0326 2022/10/07 09:40:30 - mmengine - INFO - Epoch(train) [11][840/2119] lr: 4.0000e-02 eta: 1 day, 3:39:23 time: 0.3228 data_time: 0.0225 memory: 5826 grad_norm: 2.9934 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6796 loss: 2.6796 2022/10/07 09:40:37 - mmengine - INFO - Epoch(train) [11][860/2119] lr: 4.0000e-02 eta: 1 day, 3:39:25 time: 0.3701 data_time: 0.0185 memory: 5826 grad_norm: 2.9172 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8913 loss: 2.8913 2022/10/07 09:40:44 - mmengine - INFO - Epoch(train) [11][880/2119] lr: 4.0000e-02 eta: 1 day, 3:39:17 time: 0.3315 data_time: 0.0315 memory: 5826 grad_norm: 2.9759 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8457 loss: 2.8457 2022/10/07 09:40:50 - mmengine - INFO - Epoch(train) [11][900/2119] lr: 4.0000e-02 eta: 1 day, 3:38:55 time: 0.2776 data_time: 0.0217 memory: 5826 grad_norm: 2.9390 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9409 loss: 2.9409 2022/10/07 09:40:56 - mmengine - INFO - Epoch(train) [11][920/2119] lr: 4.0000e-02 eta: 1 day, 3:38:45 time: 0.3266 data_time: 0.0225 memory: 5826 grad_norm: 2.9386 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0250 loss: 3.0250 2022/10/07 09:41:03 - mmengine - INFO - Epoch(train) [11][940/2119] lr: 4.0000e-02 eta: 1 day, 3:38:39 time: 0.3389 data_time: 0.0229 memory: 5826 grad_norm: 2.9036 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.9418 loss: 2.9418 2022/10/07 09:41:10 - mmengine - INFO - Epoch(train) [11][960/2119] lr: 4.0000e-02 eta: 1 day, 3:38:36 time: 0.3501 data_time: 0.0264 memory: 5826 grad_norm: 3.0071 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9387 loss: 2.9387 2022/10/07 09:41:16 - mmengine - INFO - Epoch(train) [11][980/2119] lr: 4.0000e-02 eta: 1 day, 3:38:22 time: 0.3092 data_time: 0.0236 memory: 5826 grad_norm: 2.9148 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9659 loss: 2.9659 2022/10/07 09:41:25 - mmengine - INFO - Epoch(train) [11][1000/2119] lr: 4.0000e-02 eta: 1 day, 3:38:40 time: 0.4277 data_time: 0.0264 memory: 5826 grad_norm: 2.9147 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0809 loss: 3.0809 2022/10/07 09:41:30 - mmengine - INFO - Epoch(train) [11][1020/2119] lr: 4.0000e-02 eta: 1 day, 3:38:20 time: 0.2869 data_time: 0.0178 memory: 5826 grad_norm: 2.9115 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9374 loss: 2.9374 2022/10/07 09:41:37 - mmengine - INFO - Epoch(train) [11][1040/2119] lr: 4.0000e-02 eta: 1 day, 3:38:10 time: 0.3259 data_time: 0.0208 memory: 5826 grad_norm: 2.9179 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0775 loss: 3.0775 2022/10/07 09:41:43 - mmengine - INFO - Epoch(train) [11][1060/2119] lr: 4.0000e-02 eta: 1 day, 3:38:01 time: 0.3285 data_time: 0.0218 memory: 5826 grad_norm: 2.9762 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8866 loss: 2.8866 2022/10/07 09:41:50 - mmengine - INFO - Epoch(train) [11][1080/2119] lr: 4.0000e-02 eta: 1 day, 3:37:54 time: 0.3336 data_time: 0.0238 memory: 5826 grad_norm: 2.9608 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.9999 loss: 2.9999 2022/10/07 09:41:56 - mmengine - INFO - Epoch(train) [11][1100/2119] lr: 4.0000e-02 eta: 1 day, 3:37:42 time: 0.3158 data_time: 0.0231 memory: 5826 grad_norm: 2.9445 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9957 loss: 2.9957 2022/10/07 09:42:03 - mmengine - INFO - Epoch(train) [11][1120/2119] lr: 4.0000e-02 eta: 1 day, 3:37:30 time: 0.3162 data_time: 0.0199 memory: 5826 grad_norm: 2.9415 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 3.0396 loss: 3.0396 2022/10/07 09:42:09 - mmengine - INFO - Epoch(train) [11][1140/2119] lr: 4.0000e-02 eta: 1 day, 3:37:23 time: 0.3368 data_time: 0.0202 memory: 5826 grad_norm: 2.9481 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8486 loss: 2.8486 2022/10/07 09:42:16 - mmengine - INFO - Epoch(train) [11][1160/2119] lr: 4.0000e-02 eta: 1 day, 3:37:15 time: 0.3307 data_time: 0.0275 memory: 5826 grad_norm: 2.9520 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9442 loss: 2.9442 2022/10/07 09:42:22 - mmengine - INFO - Epoch(train) [11][1180/2119] lr: 4.0000e-02 eta: 1 day, 3:37:02 time: 0.3128 data_time: 0.0305 memory: 5826 grad_norm: 2.9727 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9216 loss: 2.9216 2022/10/07 09:42:29 - mmengine - INFO - Epoch(train) [11][1200/2119] lr: 4.0000e-02 eta: 1 day, 3:36:57 time: 0.3446 data_time: 0.0266 memory: 5826 grad_norm: 2.9633 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9777 loss: 2.9777 2022/10/07 09:42:36 - mmengine - INFO - Epoch(train) [11][1220/2119] lr: 4.0000e-02 eta: 1 day, 3:36:55 time: 0.3554 data_time: 0.0871 memory: 5826 grad_norm: 2.9568 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 3.0275 loss: 3.0275 2022/10/07 09:42:43 - mmengine - INFO - Epoch(train) [11][1240/2119] lr: 4.0000e-02 eta: 1 day, 3:36:53 time: 0.3538 data_time: 0.1205 memory: 5826 grad_norm: 2.9499 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0921 loss: 3.0921 2022/10/07 09:42:50 - mmengine - INFO - Epoch(train) [11][1260/2119] lr: 4.0000e-02 eta: 1 day, 3:36:39 time: 0.3084 data_time: 0.0634 memory: 5826 grad_norm: 2.9308 top1_acc: 0.3125 top5_acc: 0.3125 loss_cls: 3.2796 loss: 3.2796 2022/10/07 09:42:57 - mmengine - INFO - Epoch(train) [11][1280/2119] lr: 4.0000e-02 eta: 1 day, 3:36:43 time: 0.3781 data_time: 0.1021 memory: 5826 grad_norm: 2.9339 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9153 loss: 2.9153 2022/10/07 09:43:03 - mmengine - INFO - Epoch(train) [11][1300/2119] lr: 4.0000e-02 eta: 1 day, 3:36:30 time: 0.3112 data_time: 0.0481 memory: 5826 grad_norm: 2.9654 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8617 loss: 2.8617 2022/10/07 09:43:11 - mmengine - INFO - Epoch(train) [11][1320/2119] lr: 4.0000e-02 eta: 1 day, 3:36:31 time: 0.3666 data_time: 0.0173 memory: 5826 grad_norm: 2.9232 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8860 loss: 2.8860 2022/10/07 09:43:18 - mmengine - INFO - Epoch(train) [11][1340/2119] lr: 4.0000e-02 eta: 1 day, 3:36:33 time: 0.3702 data_time: 0.0196 memory: 5826 grad_norm: 2.9363 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.0763 loss: 3.0763 2022/10/07 09:43:25 - mmengine - INFO - Epoch(train) [11][1360/2119] lr: 4.0000e-02 eta: 1 day, 3:36:23 time: 0.3248 data_time: 0.0344 memory: 5826 grad_norm: 2.9383 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.1725 loss: 3.1725 2022/10/07 09:43:31 - mmengine - INFO - Epoch(train) [11][1380/2119] lr: 4.0000e-02 eta: 1 day, 3:36:10 time: 0.3129 data_time: 0.0224 memory: 5826 grad_norm: 2.9471 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9695 loss: 2.9695 2022/10/07 09:43:38 - mmengine - INFO - Epoch(train) [11][1400/2119] lr: 4.0000e-02 eta: 1 day, 3:36:08 time: 0.3538 data_time: 0.0224 memory: 5826 grad_norm: 2.9313 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7321 loss: 2.7321 2022/10/07 09:43:44 - mmengine - INFO - Epoch(train) [11][1420/2119] lr: 4.0000e-02 eta: 1 day, 3:35:59 time: 0.3256 data_time: 0.0214 memory: 5826 grad_norm: 2.9382 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9363 loss: 2.9363 2022/10/07 09:43:52 - mmengine - INFO - Epoch(train) [11][1440/2119] lr: 4.0000e-02 eta: 1 day, 3:35:57 time: 0.3578 data_time: 0.0211 memory: 5826 grad_norm: 2.9593 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7820 loss: 2.7820 2022/10/07 09:43:58 - mmengine - INFO - Epoch(train) [11][1460/2119] lr: 4.0000e-02 eta: 1 day, 3:35:40 time: 0.2967 data_time: 0.0253 memory: 5826 grad_norm: 2.9506 top1_acc: 0.0625 top5_acc: 0.1875 loss_cls: 2.9353 loss: 2.9353 2022/10/07 09:44:10 - mmengine - INFO - Epoch(train) [11][1480/2119] lr: 4.0000e-02 eta: 1 day, 3:36:47 time: 0.6180 data_time: 0.2168 memory: 5826 grad_norm: 2.9535 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0695 loss: 3.0695 2022/10/07 09:44:15 - mmengine - INFO - Epoch(train) [11][1500/2119] lr: 4.0000e-02 eta: 1 day, 3:36:21 time: 0.2646 data_time: 0.0245 memory: 5826 grad_norm: 2.9185 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8135 loss: 2.8135 2022/10/07 09:44:22 - mmengine - INFO - Epoch(train) [11][1520/2119] lr: 4.0000e-02 eta: 1 day, 3:36:18 time: 0.3513 data_time: 0.0334 memory: 5826 grad_norm: 2.9396 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8846 loss: 2.8846 2022/10/07 09:44:29 - mmengine - INFO - Epoch(train) [11][1540/2119] lr: 4.0000e-02 eta: 1 day, 3:36:15 time: 0.3509 data_time: 0.0225 memory: 5826 grad_norm: 2.9263 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9717 loss: 2.9717 2022/10/07 09:44:36 - mmengine - INFO - Epoch(train) [11][1560/2119] lr: 4.0000e-02 eta: 1 day, 3:36:03 time: 0.3151 data_time: 0.0195 memory: 5826 grad_norm: 2.9490 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8516 loss: 2.8516 2022/10/07 09:44:42 - mmengine - INFO - Epoch(train) [11][1580/2119] lr: 4.0000e-02 eta: 1 day, 3:35:59 time: 0.3470 data_time: 0.0179 memory: 5826 grad_norm: 2.8972 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8451 loss: 2.8451 2022/10/07 09:44:49 - mmengine - INFO - Epoch(train) [11][1600/2119] lr: 4.0000e-02 eta: 1 day, 3:35:47 time: 0.3174 data_time: 0.0269 memory: 5826 grad_norm: 2.9016 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8801 loss: 2.8801 2022/10/07 09:44:55 - mmengine - INFO - Epoch(train) [11][1620/2119] lr: 4.0000e-02 eta: 1 day, 3:35:36 time: 0.3191 data_time: 0.0230 memory: 5826 grad_norm: 2.9311 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8277 loss: 2.8277 2022/10/07 09:45:02 - mmengine - INFO - Epoch(train) [11][1640/2119] lr: 4.0000e-02 eta: 1 day, 3:35:32 time: 0.3467 data_time: 0.0266 memory: 5826 grad_norm: 2.9740 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9444 loss: 2.9444 2022/10/07 09:45:08 - mmengine - INFO - Epoch(train) [11][1660/2119] lr: 4.0000e-02 eta: 1 day, 3:35:19 time: 0.3128 data_time: 0.0196 memory: 5826 grad_norm: 2.9387 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5733 loss: 2.5733 2022/10/07 09:45:15 - mmengine - INFO - Epoch(train) [11][1680/2119] lr: 4.0000e-02 eta: 1 day, 3:35:14 time: 0.3434 data_time: 0.0267 memory: 5826 grad_norm: 2.9236 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0092 loss: 3.0092 2022/10/07 09:45:22 - mmengine - INFO - Epoch(train) [11][1700/2119] lr: 4.0000e-02 eta: 1 day, 3:35:06 time: 0.3324 data_time: 0.0172 memory: 5826 grad_norm: 2.9097 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0325 loss: 3.0325 2022/10/07 09:45:29 - mmengine - INFO - Epoch(train) [11][1720/2119] lr: 4.0000e-02 eta: 1 day, 3:35:04 time: 0.3557 data_time: 0.0192 memory: 5826 grad_norm: 2.9170 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 3.1227 loss: 3.1227 2022/10/07 09:45:36 - mmengine - INFO - Epoch(train) [11][1740/2119] lr: 4.0000e-02 eta: 1 day, 3:34:56 time: 0.3296 data_time: 0.0171 memory: 5826 grad_norm: 2.9607 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8811 loss: 2.8811 2022/10/07 09:45:42 - mmengine - INFO - Epoch(train) [11][1760/2119] lr: 4.0000e-02 eta: 1 day, 3:34:42 time: 0.3104 data_time: 0.0236 memory: 5826 grad_norm: 2.9148 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9735 loss: 2.9735 2022/10/07 09:45:50 - mmengine - INFO - Epoch(train) [11][1780/2119] lr: 4.0000e-02 eta: 1 day, 3:34:48 time: 0.3842 data_time: 0.0236 memory: 5826 grad_norm: 2.9428 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9377 loss: 2.9377 2022/10/07 09:45:56 - mmengine - INFO - Epoch(train) [11][1800/2119] lr: 4.0000e-02 eta: 1 day, 3:34:39 time: 0.3299 data_time: 0.0203 memory: 5826 grad_norm: 2.9552 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9695 loss: 2.9695 2022/10/07 09:45:59 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 09:46:03 - mmengine - INFO - Epoch(train) [11][1820/2119] lr: 4.0000e-02 eta: 1 day, 3:34:31 time: 0.3312 data_time: 0.0167 memory: 5826 grad_norm: 2.9911 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9709 loss: 2.9709 2022/10/07 09:46:09 - mmengine - INFO - Epoch(train) [11][1840/2119] lr: 4.0000e-02 eta: 1 day, 3:34:19 time: 0.3158 data_time: 0.0203 memory: 5826 grad_norm: 2.9358 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.1989 loss: 3.1989 2022/10/07 09:46:16 - mmengine - INFO - Epoch(train) [11][1860/2119] lr: 4.0000e-02 eta: 1 day, 3:34:13 time: 0.3401 data_time: 0.0234 memory: 5826 grad_norm: 2.8890 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7433 loss: 2.7433 2022/10/07 09:46:22 - mmengine - INFO - Epoch(train) [11][1880/2119] lr: 4.0000e-02 eta: 1 day, 3:33:56 time: 0.2954 data_time: 0.0213 memory: 5826 grad_norm: 2.9121 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.9916 loss: 2.9916 2022/10/07 09:46:28 - mmengine - INFO - Epoch(train) [11][1900/2119] lr: 4.0000e-02 eta: 1 day, 3:33:46 time: 0.3257 data_time: 0.0215 memory: 5826 grad_norm: 2.9332 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8914 loss: 2.8914 2022/10/07 09:46:35 - mmengine - INFO - Epoch(train) [11][1920/2119] lr: 4.0000e-02 eta: 1 day, 3:33:45 time: 0.3574 data_time: 0.0235 memory: 5826 grad_norm: 2.9146 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6353 loss: 2.6353 2022/10/07 09:46:41 - mmengine - INFO - Epoch(train) [11][1940/2119] lr: 4.0000e-02 eta: 1 day, 3:33:25 time: 0.2868 data_time: 0.0245 memory: 5826 grad_norm: 2.9839 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8408 loss: 2.8408 2022/10/07 09:46:48 - mmengine - INFO - Epoch(train) [11][1960/2119] lr: 4.0000e-02 eta: 1 day, 3:33:18 time: 0.3331 data_time: 0.0252 memory: 5826 grad_norm: 2.9488 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7323 loss: 2.7323 2022/10/07 09:46:55 - mmengine - INFO - Epoch(train) [11][1980/2119] lr: 4.0000e-02 eta: 1 day, 3:33:14 time: 0.3500 data_time: 0.0206 memory: 5826 grad_norm: 2.9341 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0156 loss: 3.0156 2022/10/07 09:47:01 - mmengine - INFO - Epoch(train) [11][2000/2119] lr: 4.0000e-02 eta: 1 day, 3:33:04 time: 0.3220 data_time: 0.0196 memory: 5826 grad_norm: 2.9046 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6724 loss: 2.6724 2022/10/07 09:47:08 - mmengine - INFO - Epoch(train) [11][2020/2119] lr: 4.0000e-02 eta: 1 day, 3:33:00 time: 0.3494 data_time: 0.0199 memory: 5826 grad_norm: 2.9542 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.9138 loss: 2.9138 2022/10/07 09:47:15 - mmengine - INFO - Epoch(train) [11][2040/2119] lr: 4.0000e-02 eta: 1 day, 3:33:00 time: 0.3608 data_time: 0.0195 memory: 5826 grad_norm: 2.9498 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9593 loss: 2.9593 2022/10/07 09:47:22 - mmengine - INFO - Epoch(train) [11][2060/2119] lr: 4.0000e-02 eta: 1 day, 3:32:46 time: 0.3066 data_time: 0.0235 memory: 5826 grad_norm: 2.9669 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0669 loss: 3.0669 2022/10/07 09:47:28 - mmengine - INFO - Epoch(train) [11][2080/2119] lr: 4.0000e-02 eta: 1 day, 3:32:40 time: 0.3414 data_time: 0.0214 memory: 5826 grad_norm: 2.9098 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7242 loss: 2.7242 2022/10/07 09:47:34 - mmengine - INFO - Epoch(train) [11][2100/2119] lr: 4.0000e-02 eta: 1 day, 3:32:24 time: 0.2994 data_time: 0.0218 memory: 5826 grad_norm: 2.9591 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0157 loss: 3.0157 2022/10/07 09:47:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 09:47:40 - mmengine - INFO - Epoch(train) [11][2119/2119] lr: 4.0000e-02 eta: 1 day, 3:32:24 time: 0.3022 data_time: 0.0202 memory: 5826 grad_norm: 2.9394 top1_acc: 0.5000 top5_acc: 0.6000 loss_cls: 2.9208 loss: 2.9208 2022/10/07 09:47:50 - mmengine - INFO - Epoch(train) [12][20/2119] lr: 4.0000e-02 eta: 1 day, 3:31:27 time: 0.4820 data_time: 0.1724 memory: 5826 grad_norm: 2.9007 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8523 loss: 2.8523 2022/10/07 09:47:56 - mmengine - INFO - Epoch(train) [12][40/2119] lr: 4.0000e-02 eta: 1 day, 3:31:15 time: 0.3162 data_time: 0.0325 memory: 5826 grad_norm: 2.8949 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0179 loss: 3.0179 2022/10/07 09:48:03 - mmengine - INFO - Epoch(train) [12][60/2119] lr: 4.0000e-02 eta: 1 day, 3:31:09 time: 0.3407 data_time: 0.0350 memory: 5826 grad_norm: 2.8934 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7513 loss: 2.7513 2022/10/07 09:48:10 - mmengine - INFO - Epoch(train) [12][80/2119] lr: 4.0000e-02 eta: 1 day, 3:31:02 time: 0.3348 data_time: 0.0180 memory: 5826 grad_norm: 2.9019 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6666 loss: 2.6666 2022/10/07 09:48:17 - mmengine - INFO - Epoch(train) [12][100/2119] lr: 4.0000e-02 eta: 1 day, 3:31:01 time: 0.3594 data_time: 0.0175 memory: 5826 grad_norm: 2.9579 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8434 loss: 2.8434 2022/10/07 09:48:23 - mmengine - INFO - Epoch(train) [12][120/2119] lr: 4.0000e-02 eta: 1 day, 3:30:49 time: 0.3166 data_time: 0.0256 memory: 5826 grad_norm: 2.8833 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7417 loss: 2.7417 2022/10/07 09:48:30 - mmengine - INFO - Epoch(train) [12][140/2119] lr: 4.0000e-02 eta: 1 day, 3:30:45 time: 0.3450 data_time: 0.0247 memory: 5826 grad_norm: 2.9094 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.1676 loss: 3.1676 2022/10/07 09:48:37 - mmengine - INFO - Epoch(train) [12][160/2119] lr: 4.0000e-02 eta: 1 day, 3:30:35 time: 0.3233 data_time: 0.0206 memory: 5826 grad_norm: 2.8675 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7622 loss: 2.7622 2022/10/07 09:48:43 - mmengine - INFO - Epoch(train) [12][180/2119] lr: 4.0000e-02 eta: 1 day, 3:30:25 time: 0.3260 data_time: 0.0204 memory: 5826 grad_norm: 2.9023 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.7208 loss: 2.7208 2022/10/07 09:48:49 - mmengine - INFO - Epoch(train) [12][200/2119] lr: 4.0000e-02 eta: 1 day, 3:30:10 time: 0.3031 data_time: 0.0265 memory: 5826 grad_norm: 2.9450 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9360 loss: 2.9360 2022/10/07 09:48:57 - mmengine - INFO - Epoch(train) [12][220/2119] lr: 4.0000e-02 eta: 1 day, 3:30:10 time: 0.3618 data_time: 0.0204 memory: 5826 grad_norm: 2.9506 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8949 loss: 2.8949 2022/10/07 09:49:04 - mmengine - INFO - Epoch(train) [12][240/2119] lr: 4.0000e-02 eta: 1 day, 3:30:13 time: 0.3735 data_time: 0.0221 memory: 5826 grad_norm: 2.9521 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6436 loss: 2.6436 2022/10/07 09:49:10 - mmengine - INFO - Epoch(train) [12][260/2119] lr: 4.0000e-02 eta: 1 day, 3:30:00 time: 0.3125 data_time: 0.0187 memory: 5826 grad_norm: 2.9296 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8831 loss: 2.8831 2022/10/07 09:49:17 - mmengine - INFO - Epoch(train) [12][280/2119] lr: 4.0000e-02 eta: 1 day, 3:29:56 time: 0.3465 data_time: 0.0232 memory: 5826 grad_norm: 2.9050 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8099 loss: 2.8099 2022/10/07 09:49:23 - mmengine - INFO - Epoch(train) [12][300/2119] lr: 4.0000e-02 eta: 1 day, 3:29:38 time: 0.2932 data_time: 0.0223 memory: 5826 grad_norm: 2.9217 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 3.0898 loss: 3.0898 2022/10/07 09:49:30 - mmengine - INFO - Epoch(train) [12][320/2119] lr: 4.0000e-02 eta: 1 day, 3:29:29 time: 0.3277 data_time: 0.0298 memory: 5826 grad_norm: 2.9196 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8581 loss: 2.8581 2022/10/07 09:49:36 - mmengine - INFO - Epoch(train) [12][340/2119] lr: 4.0000e-02 eta: 1 day, 3:29:15 time: 0.3046 data_time: 0.0274 memory: 5826 grad_norm: 2.9420 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7927 loss: 2.7927 2022/10/07 09:49:43 - mmengine - INFO - Epoch(train) [12][360/2119] lr: 4.0000e-02 eta: 1 day, 3:29:17 time: 0.3716 data_time: 0.0175 memory: 5826 grad_norm: 2.9420 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9383 loss: 2.9383 2022/10/07 09:49:49 - mmengine - INFO - Epoch(train) [12][380/2119] lr: 4.0000e-02 eta: 1 day, 3:29:03 time: 0.3085 data_time: 0.0194 memory: 5826 grad_norm: 2.9248 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8558 loss: 2.8558 2022/10/07 09:49:56 - mmengine - INFO - Epoch(train) [12][400/2119] lr: 4.0000e-02 eta: 1 day, 3:29:00 time: 0.3517 data_time: 0.0267 memory: 5826 grad_norm: 2.9112 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7783 loss: 2.7783 2022/10/07 09:50:03 - mmengine - INFO - Epoch(train) [12][420/2119] lr: 4.0000e-02 eta: 1 day, 3:28:52 time: 0.3299 data_time: 0.0395 memory: 5826 grad_norm: 2.9268 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8082 loss: 2.8082 2022/10/07 09:50:10 - mmengine - INFO - Epoch(train) [12][440/2119] lr: 4.0000e-02 eta: 1 day, 3:28:51 time: 0.3615 data_time: 0.0176 memory: 5826 grad_norm: 2.9553 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7839 loss: 2.7839 2022/10/07 09:50:16 - mmengine - INFO - Epoch(train) [12][460/2119] lr: 4.0000e-02 eta: 1 day, 3:28:32 time: 0.2852 data_time: 0.0252 memory: 5826 grad_norm: 2.9356 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9625 loss: 2.9625 2022/10/07 09:50:23 - mmengine - INFO - Epoch(train) [12][480/2119] lr: 4.0000e-02 eta: 1 day, 3:28:26 time: 0.3387 data_time: 0.0229 memory: 5826 grad_norm: 2.9105 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.9138 loss: 2.9138 2022/10/07 09:50:29 - mmengine - INFO - Epoch(train) [12][500/2119] lr: 4.0000e-02 eta: 1 day, 3:28:16 time: 0.3240 data_time: 0.0223 memory: 5826 grad_norm: 2.9600 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7357 loss: 2.7357 2022/10/07 09:50:36 - mmengine - INFO - Epoch(train) [12][520/2119] lr: 4.0000e-02 eta: 1 day, 3:28:11 time: 0.3429 data_time: 0.0176 memory: 5826 grad_norm: 2.9220 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0047 loss: 3.0047 2022/10/07 09:50:43 - mmengine - INFO - Epoch(train) [12][540/2119] lr: 4.0000e-02 eta: 1 day, 3:28:03 time: 0.3302 data_time: 0.0213 memory: 5826 grad_norm: 2.9573 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.1874 loss: 3.1874 2022/10/07 09:50:50 - mmengine - INFO - Epoch(train) [12][560/2119] lr: 4.0000e-02 eta: 1 day, 3:27:59 time: 0.3471 data_time: 0.0231 memory: 5826 grad_norm: 2.9641 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7051 loss: 2.7051 2022/10/07 09:50:56 - mmengine - INFO - Epoch(train) [12][580/2119] lr: 4.0000e-02 eta: 1 day, 3:27:54 time: 0.3447 data_time: 0.0290 memory: 5826 grad_norm: 2.9596 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9255 loss: 2.9255 2022/10/07 09:51:04 - mmengine - INFO - Epoch(train) [12][600/2119] lr: 4.0000e-02 eta: 1 day, 3:27:58 time: 0.3796 data_time: 0.0184 memory: 5826 grad_norm: 2.9298 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7399 loss: 2.7399 2022/10/07 09:51:10 - mmengine - INFO - Epoch(train) [12][620/2119] lr: 4.0000e-02 eta: 1 day, 3:27:44 time: 0.3083 data_time: 0.0236 memory: 5826 grad_norm: 2.9302 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0342 loss: 3.0342 2022/10/07 09:51:17 - mmengine - INFO - Epoch(train) [12][640/2119] lr: 4.0000e-02 eta: 1 day, 3:27:39 time: 0.3412 data_time: 0.0188 memory: 5826 grad_norm: 2.9000 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5431 loss: 2.5431 2022/10/07 09:51:24 - mmengine - INFO - Epoch(train) [12][660/2119] lr: 4.0000e-02 eta: 1 day, 3:27:30 time: 0.3282 data_time: 0.0259 memory: 5826 grad_norm: 2.9311 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8901 loss: 2.8901 2022/10/07 09:51:30 - mmengine - INFO - Epoch(train) [12][680/2119] lr: 4.0000e-02 eta: 1 day, 3:27:18 time: 0.3133 data_time: 0.0305 memory: 5826 grad_norm: 2.9403 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7345 loss: 2.7345 2022/10/07 09:51:33 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 09:51:36 - mmengine - INFO - Epoch(train) [12][700/2119] lr: 4.0000e-02 eta: 1 day, 3:27:04 time: 0.3077 data_time: 0.0253 memory: 5826 grad_norm: 2.9055 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9873 loss: 2.9873 2022/10/07 09:51:43 - mmengine - INFO - Epoch(train) [12][720/2119] lr: 4.0000e-02 eta: 1 day, 3:26:58 time: 0.3399 data_time: 0.0209 memory: 5826 grad_norm: 2.8837 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9061 loss: 2.9061 2022/10/07 09:51:49 - mmengine - INFO - Epoch(train) [12][740/2119] lr: 4.0000e-02 eta: 1 day, 3:26:49 time: 0.3263 data_time: 0.0586 memory: 5826 grad_norm: 2.9120 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8589 loss: 2.8589 2022/10/07 09:51:56 - mmengine - INFO - Epoch(train) [12][760/2119] lr: 4.0000e-02 eta: 1 day, 3:26:42 time: 0.3378 data_time: 0.0415 memory: 5826 grad_norm: 2.9461 top1_acc: 0.3125 top5_acc: 0.3125 loss_cls: 2.8798 loss: 2.8798 2022/10/07 09:52:03 - mmengine - INFO - Epoch(train) [12][780/2119] lr: 4.0000e-02 eta: 1 day, 3:26:43 time: 0.3644 data_time: 0.0906 memory: 5826 grad_norm: 2.9917 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9005 loss: 2.9005 2022/10/07 09:52:10 - mmengine - INFO - Epoch(train) [12][800/2119] lr: 4.0000e-02 eta: 1 day, 3:26:31 time: 0.3156 data_time: 0.0563 memory: 5826 grad_norm: 2.9192 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9799 loss: 2.9799 2022/10/07 09:52:16 - mmengine - INFO - Epoch(train) [12][820/2119] lr: 4.0000e-02 eta: 1 day, 3:26:19 time: 0.3144 data_time: 0.0272 memory: 5826 grad_norm: 2.9055 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7634 loss: 2.7634 2022/10/07 09:52:23 - mmengine - INFO - Epoch(train) [12][840/2119] lr: 4.0000e-02 eta: 1 day, 3:26:21 time: 0.3718 data_time: 0.0147 memory: 5826 grad_norm: 2.9403 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8370 loss: 2.8370 2022/10/07 09:52:29 - mmengine - INFO - Epoch(train) [12][860/2119] lr: 4.0000e-02 eta: 1 day, 3:26:01 time: 0.2817 data_time: 0.0197 memory: 5826 grad_norm: 2.9085 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8768 loss: 2.8768 2022/10/07 09:52:36 - mmengine - INFO - Epoch(train) [12][880/2119] lr: 4.0000e-02 eta: 1 day, 3:26:00 time: 0.3599 data_time: 0.0163 memory: 5826 grad_norm: 2.8969 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8938 loss: 2.8938 2022/10/07 09:52:42 - mmengine - INFO - Epoch(train) [12][900/2119] lr: 4.0000e-02 eta: 1 day, 3:25:47 time: 0.3108 data_time: 0.0237 memory: 5826 grad_norm: 2.9760 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8496 loss: 2.8496 2022/10/07 09:52:49 - mmengine - INFO - Epoch(train) [12][920/2119] lr: 4.0000e-02 eta: 1 day, 3:25:40 time: 0.3374 data_time: 0.0250 memory: 5826 grad_norm: 2.8834 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 3.0250 loss: 3.0250 2022/10/07 09:52:56 - mmengine - INFO - Epoch(train) [12][940/2119] lr: 4.0000e-02 eta: 1 day, 3:25:29 time: 0.3172 data_time: 0.0232 memory: 5826 grad_norm: 2.9567 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.9362 loss: 2.9362 2022/10/07 09:53:04 - mmengine - INFO - Epoch(train) [12][960/2119] lr: 4.0000e-02 eta: 1 day, 3:25:39 time: 0.4071 data_time: 0.0209 memory: 5826 grad_norm: 2.8960 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9131 loss: 2.9131 2022/10/07 09:53:10 - mmengine - INFO - Epoch(train) [12][980/2119] lr: 4.0000e-02 eta: 1 day, 3:25:22 time: 0.2914 data_time: 0.0272 memory: 5826 grad_norm: 2.8820 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7608 loss: 2.7608 2022/10/07 09:53:17 - mmengine - INFO - Epoch(train) [12][1000/2119] lr: 4.0000e-02 eta: 1 day, 3:25:29 time: 0.3952 data_time: 0.0178 memory: 5826 grad_norm: 2.8974 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7835 loss: 2.7835 2022/10/07 09:53:24 - mmengine - INFO - Epoch(train) [12][1020/2119] lr: 4.0000e-02 eta: 1 day, 3:25:21 time: 0.3294 data_time: 0.0288 memory: 5826 grad_norm: 2.9361 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0070 loss: 3.0070 2022/10/07 09:53:31 - mmengine - INFO - Epoch(train) [12][1040/2119] lr: 4.0000e-02 eta: 1 day, 3:25:19 time: 0.3589 data_time: 0.0159 memory: 5826 grad_norm: 2.9223 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8431 loss: 2.8431 2022/10/07 09:53:37 - mmengine - INFO - Epoch(train) [12][1060/2119] lr: 4.0000e-02 eta: 1 day, 3:25:06 time: 0.3091 data_time: 0.0220 memory: 5826 grad_norm: 2.9385 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9368 loss: 2.9368 2022/10/07 09:53:45 - mmengine - INFO - Epoch(train) [12][1080/2119] lr: 4.0000e-02 eta: 1 day, 3:25:06 time: 0.3626 data_time: 0.0325 memory: 5826 grad_norm: 2.9328 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8964 loss: 2.8964 2022/10/07 09:53:51 - mmengine - INFO - Epoch(train) [12][1100/2119] lr: 4.0000e-02 eta: 1 day, 3:25:00 time: 0.3401 data_time: 0.0229 memory: 5826 grad_norm: 2.9062 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9788 loss: 2.9788 2022/10/07 09:53:59 - mmengine - INFO - Epoch(train) [12][1120/2119] lr: 4.0000e-02 eta: 1 day, 3:25:00 time: 0.3659 data_time: 0.0220 memory: 5826 grad_norm: 2.9639 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7800 loss: 2.7800 2022/10/07 09:54:05 - mmengine - INFO - Epoch(train) [12][1140/2119] lr: 4.0000e-02 eta: 1 day, 3:24:47 time: 0.3084 data_time: 0.0246 memory: 5826 grad_norm: 3.0006 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8239 loss: 2.8239 2022/10/07 09:54:13 - mmengine - INFO - Epoch(train) [12][1160/2119] lr: 4.0000e-02 eta: 1 day, 3:24:54 time: 0.3947 data_time: 0.0229 memory: 5826 grad_norm: 2.9129 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0679 loss: 3.0679 2022/10/07 09:54:18 - mmengine - INFO - Epoch(train) [12][1180/2119] lr: 4.0000e-02 eta: 1 day, 3:24:31 time: 0.2687 data_time: 0.0239 memory: 5826 grad_norm: 2.8760 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7686 loss: 2.7686 2022/10/07 09:54:25 - mmengine - INFO - Epoch(train) [12][1200/2119] lr: 4.0000e-02 eta: 1 day, 3:24:25 time: 0.3386 data_time: 0.0241 memory: 5826 grad_norm: 2.9643 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8357 loss: 2.8357 2022/10/07 09:54:31 - mmengine - INFO - Epoch(train) [12][1220/2119] lr: 4.0000e-02 eta: 1 day, 3:24:15 time: 0.3232 data_time: 0.0186 memory: 5826 grad_norm: 2.9087 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9114 loss: 2.9114 2022/10/07 09:54:38 - mmengine - INFO - Epoch(train) [12][1240/2119] lr: 4.0000e-02 eta: 1 day, 3:24:07 time: 0.3297 data_time: 0.0216 memory: 5826 grad_norm: 2.9195 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8437 loss: 2.8437 2022/10/07 09:54:45 - mmengine - INFO - Epoch(train) [12][1260/2119] lr: 4.0000e-02 eta: 1 day, 3:24:06 time: 0.3619 data_time: 0.0251 memory: 5826 grad_norm: 2.8751 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6786 loss: 2.6786 2022/10/07 09:54:52 - mmengine - INFO - Epoch(train) [12][1280/2119] lr: 4.0000e-02 eta: 1 day, 3:24:05 time: 0.3592 data_time: 0.0213 memory: 5826 grad_norm: 2.8695 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8066 loss: 2.8066 2022/10/07 09:54:59 - mmengine - INFO - Epoch(train) [12][1300/2119] lr: 4.0000e-02 eta: 1 day, 3:23:51 time: 0.3076 data_time: 0.0217 memory: 5826 grad_norm: 2.8558 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8783 loss: 2.8783 2022/10/07 09:55:05 - mmengine - INFO - Epoch(train) [12][1320/2119] lr: 4.0000e-02 eta: 1 day, 3:23:44 time: 0.3332 data_time: 0.0219 memory: 5826 grad_norm: 2.9022 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9423 loss: 2.9423 2022/10/07 09:55:12 - mmengine - INFO - Epoch(train) [12][1340/2119] lr: 4.0000e-02 eta: 1 day, 3:23:34 time: 0.3251 data_time: 0.0178 memory: 5826 grad_norm: 2.8078 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7059 loss: 2.7059 2022/10/07 09:55:18 - mmengine - INFO - Epoch(train) [12][1360/2119] lr: 4.0000e-02 eta: 1 day, 3:23:28 time: 0.3364 data_time: 0.0194 memory: 5826 grad_norm: 2.8897 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.8265 loss: 2.8265 2022/10/07 09:55:25 - mmengine - INFO - Epoch(train) [12][1380/2119] lr: 4.0000e-02 eta: 1 day, 3:23:19 time: 0.3263 data_time: 0.0211 memory: 5826 grad_norm: 2.9088 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.9083 loss: 2.9083 2022/10/07 09:55:32 - mmengine - INFO - Epoch(train) [12][1400/2119] lr: 4.0000e-02 eta: 1 day, 3:23:17 time: 0.3585 data_time: 0.0230 memory: 5826 grad_norm: 2.9150 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8921 loss: 2.8921 2022/10/07 09:55:39 - mmengine - INFO - Epoch(train) [12][1420/2119] lr: 4.0000e-02 eta: 1 day, 3:23:09 time: 0.3314 data_time: 0.0246 memory: 5826 grad_norm: 2.8982 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7913 loss: 2.7913 2022/10/07 09:55:46 - mmengine - INFO - Epoch(train) [12][1440/2119] lr: 4.0000e-02 eta: 1 day, 3:23:03 time: 0.3362 data_time: 0.0247 memory: 5826 grad_norm: 2.9227 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8260 loss: 2.8260 2022/10/07 09:55:52 - mmengine - INFO - Epoch(train) [12][1460/2119] lr: 4.0000e-02 eta: 1 day, 3:22:55 time: 0.3339 data_time: 0.0252 memory: 5826 grad_norm: 2.9322 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1852 loss: 3.1852 2022/10/07 09:56:00 - mmengine - INFO - Epoch(train) [12][1480/2119] lr: 4.0000e-02 eta: 1 day, 3:22:56 time: 0.3681 data_time: 0.0191 memory: 5826 grad_norm: 2.9152 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6560 loss: 2.6560 2022/10/07 09:56:06 - mmengine - INFO - Epoch(train) [12][1500/2119] lr: 4.0000e-02 eta: 1 day, 3:22:45 time: 0.3183 data_time: 0.0197 memory: 5826 grad_norm: 2.9327 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8894 loss: 2.8894 2022/10/07 09:56:13 - mmengine - INFO - Epoch(train) [12][1520/2119] lr: 4.0000e-02 eta: 1 day, 3:22:44 time: 0.3601 data_time: 0.0180 memory: 5826 grad_norm: 2.8515 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7399 loss: 2.7399 2022/10/07 09:56:19 - mmengine - INFO - Epoch(train) [12][1540/2119] lr: 4.0000e-02 eta: 1 day, 3:22:32 time: 0.3152 data_time: 0.0192 memory: 5826 grad_norm: 2.8558 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9943 loss: 2.9943 2022/10/07 09:56:26 - mmengine - INFO - Epoch(train) [12][1560/2119] lr: 4.0000e-02 eta: 1 day, 3:22:26 time: 0.3397 data_time: 0.0194 memory: 5826 grad_norm: 2.9090 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8624 loss: 2.8624 2022/10/07 09:56:33 - mmengine - INFO - Epoch(train) [12][1580/2119] lr: 4.0000e-02 eta: 1 day, 3:22:20 time: 0.3382 data_time: 0.0212 memory: 5826 grad_norm: 2.8990 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7854 loss: 2.7854 2022/10/07 09:56:40 - mmengine - INFO - Epoch(train) [12][1600/2119] lr: 4.0000e-02 eta: 1 day, 3:22:16 time: 0.3488 data_time: 0.0187 memory: 5826 grad_norm: 2.9004 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.0223 loss: 3.0223 2022/10/07 09:56:47 - mmengine - INFO - Epoch(train) [12][1620/2119] lr: 4.0000e-02 eta: 1 day, 3:22:13 time: 0.3515 data_time: 0.0227 memory: 5826 grad_norm: 2.8762 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9055 loss: 2.9055 2022/10/07 09:56:54 - mmengine - INFO - Epoch(train) [12][1640/2119] lr: 4.0000e-02 eta: 1 day, 3:22:04 time: 0.3271 data_time: 0.0238 memory: 5826 grad_norm: 2.8990 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7593 loss: 2.7593 2022/10/07 09:57:00 - mmengine - INFO - Epoch(train) [12][1660/2119] lr: 4.0000e-02 eta: 1 day, 3:21:55 time: 0.3272 data_time: 0.0251 memory: 5826 grad_norm: 2.9336 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8788 loss: 2.8788 2022/10/07 09:57:07 - mmengine - INFO - Epoch(train) [12][1680/2119] lr: 4.0000e-02 eta: 1 day, 3:21:45 time: 0.3205 data_time: 0.0209 memory: 5826 grad_norm: 2.8607 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9092 loss: 2.9092 2022/10/07 09:57:10 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 09:57:13 - mmengine - INFO - Epoch(train) [12][1700/2119] lr: 4.0000e-02 eta: 1 day, 3:21:35 time: 0.3222 data_time: 0.0237 memory: 5826 grad_norm: 2.8532 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6239 loss: 2.6239 2022/10/07 09:57:20 - mmengine - INFO - Epoch(train) [12][1720/2119] lr: 4.0000e-02 eta: 1 day, 3:21:33 time: 0.3585 data_time: 0.0159 memory: 5826 grad_norm: 2.9401 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8219 loss: 2.8219 2022/10/07 09:57:26 - mmengine - INFO - Epoch(train) [12][1740/2119] lr: 4.0000e-02 eta: 1 day, 3:21:20 time: 0.3105 data_time: 0.0256 memory: 5826 grad_norm: 2.8941 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7163 loss: 2.7163 2022/10/07 09:57:34 - mmengine - INFO - Epoch(train) [12][1760/2119] lr: 4.0000e-02 eta: 1 day, 3:21:21 time: 0.3694 data_time: 0.0194 memory: 5826 grad_norm: 2.9011 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6969 loss: 2.6969 2022/10/07 09:57:40 - mmengine - INFO - Epoch(train) [12][1780/2119] lr: 4.0000e-02 eta: 1 day, 3:21:13 time: 0.3286 data_time: 0.0348 memory: 5826 grad_norm: 2.9741 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9787 loss: 2.9787 2022/10/07 09:57:47 - mmengine - INFO - Epoch(train) [12][1800/2119] lr: 4.0000e-02 eta: 1 day, 3:21:00 time: 0.3112 data_time: 0.0223 memory: 5826 grad_norm: 2.9467 top1_acc: 0.0625 top5_acc: 0.5000 loss_cls: 2.8950 loss: 2.8950 2022/10/07 09:57:53 - mmengine - INFO - Epoch(train) [12][1820/2119] lr: 4.0000e-02 eta: 1 day, 3:20:47 time: 0.3094 data_time: 0.0211 memory: 5826 grad_norm: 2.8690 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8831 loss: 2.8831 2022/10/07 09:58:01 - mmengine - INFO - Epoch(train) [12][1840/2119] lr: 4.0000e-02 eta: 1 day, 3:20:55 time: 0.3970 data_time: 0.0181 memory: 5826 grad_norm: 2.8902 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7318 loss: 2.7318 2022/10/07 09:58:07 - mmengine - INFO - Epoch(train) [12][1860/2119] lr: 4.0000e-02 eta: 1 day, 3:20:43 time: 0.3165 data_time: 0.0279 memory: 5826 grad_norm: 2.8899 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0241 loss: 3.0241 2022/10/07 09:58:15 - mmengine - INFO - Epoch(train) [12][1880/2119] lr: 4.0000e-02 eta: 1 day, 3:20:51 time: 0.3977 data_time: 0.0232 memory: 5826 grad_norm: 2.8768 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8853 loss: 2.8853 2022/10/07 09:58:21 - mmengine - INFO - Epoch(train) [12][1900/2119] lr: 4.0000e-02 eta: 1 day, 3:20:32 time: 0.2835 data_time: 0.0199 memory: 5826 grad_norm: 2.8993 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9751 loss: 2.9751 2022/10/07 09:58:27 - mmengine - INFO - Epoch(train) [12][1920/2119] lr: 4.0000e-02 eta: 1 day, 3:20:23 time: 0.3294 data_time: 0.0225 memory: 5826 grad_norm: 2.8947 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8533 loss: 2.8533 2022/10/07 09:58:35 - mmengine - INFO - Epoch(train) [12][1940/2119] lr: 4.0000e-02 eta: 1 day, 3:20:28 time: 0.3856 data_time: 0.0207 memory: 5826 grad_norm: 2.8278 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9140 loss: 2.9140 2022/10/07 09:58:42 - mmengine - INFO - Epoch(train) [12][1960/2119] lr: 4.0000e-02 eta: 1 day, 3:20:21 time: 0.3326 data_time: 0.0175 memory: 5826 grad_norm: 2.9508 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8152 loss: 2.8152 2022/10/07 09:58:48 - mmengine - INFO - Epoch(train) [12][1980/2119] lr: 4.0000e-02 eta: 1 day, 3:20:05 time: 0.2974 data_time: 0.0231 memory: 5826 grad_norm: 2.9303 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.1356 loss: 3.1356 2022/10/07 09:58:54 - mmengine - INFO - Epoch(train) [12][2000/2119] lr: 4.0000e-02 eta: 1 day, 3:19:58 time: 0.3383 data_time: 0.0250 memory: 5826 grad_norm: 2.8483 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8330 loss: 2.8330 2022/10/07 09:59:00 - mmengine - INFO - Epoch(train) [12][2020/2119] lr: 4.0000e-02 eta: 1 day, 3:19:46 time: 0.3092 data_time: 0.0222 memory: 5826 grad_norm: 2.8818 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.9361 loss: 2.9361 2022/10/07 09:59:08 - mmengine - INFO - Epoch(train) [12][2040/2119] lr: 4.0000e-02 eta: 1 day, 3:19:53 time: 0.3980 data_time: 0.0169 memory: 5826 grad_norm: 2.8429 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0926 loss: 3.0926 2022/10/07 09:59:14 - mmengine - INFO - Epoch(train) [12][2060/2119] lr: 4.0000e-02 eta: 1 day, 3:19:37 time: 0.2949 data_time: 0.0202 memory: 5826 grad_norm: 2.8472 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.8687 loss: 2.8687 2022/10/07 09:59:21 - mmengine - INFO - Epoch(train) [12][2080/2119] lr: 4.0000e-02 eta: 1 day, 3:19:31 time: 0.3400 data_time: 0.0187 memory: 5826 grad_norm: 2.9026 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8707 loss: 2.8707 2022/10/07 09:59:28 - mmengine - INFO - Epoch(train) [12][2100/2119] lr: 4.0000e-02 eta: 1 day, 3:19:23 time: 0.3323 data_time: 0.0216 memory: 5826 grad_norm: 2.8769 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8479 loss: 2.8479 2022/10/07 09:59:33 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 09:59:33 - mmengine - INFO - Epoch(train) [12][2119/2119] lr: 4.0000e-02 eta: 1 day, 3:19:23 time: 0.2695 data_time: 0.0125 memory: 5826 grad_norm: 2.9409 top1_acc: 0.3000 top5_acc: 0.6000 loss_cls: 2.8641 loss: 2.8641 2022/10/07 09:59:33 - mmengine - INFO - Saving checkpoint at 12 epochs 2022/10/07 09:59:43 - mmengine - INFO - Epoch(train) [13][20/2119] lr: 4.0000e-02 eta: 1 day, 3:18:19 time: 0.4342 data_time: 0.1949 memory: 5826 grad_norm: 2.8825 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.9529 loss: 2.9529 2022/10/07 09:59:49 - mmengine - INFO - Epoch(train) [13][40/2119] lr: 4.0000e-02 eta: 1 day, 3:18:09 time: 0.3195 data_time: 0.0766 memory: 5826 grad_norm: 2.9019 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9078 loss: 2.9078 2022/10/07 09:59:57 - mmengine - INFO - Epoch(train) [13][60/2119] lr: 4.0000e-02 eta: 1 day, 3:18:12 time: 0.3809 data_time: 0.1507 memory: 5826 grad_norm: 2.9221 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8785 loss: 2.8785 2022/10/07 10:00:04 - mmengine - INFO - Epoch(train) [13][80/2119] lr: 4.0000e-02 eta: 1 day, 3:18:10 time: 0.3564 data_time: 0.1341 memory: 5826 grad_norm: 2.8976 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7453 loss: 2.7453 2022/10/07 10:00:11 - mmengine - INFO - Epoch(train) [13][100/2119] lr: 4.0000e-02 eta: 1 day, 3:18:05 time: 0.3457 data_time: 0.1274 memory: 5826 grad_norm: 2.9413 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6664 loss: 2.6664 2022/10/07 10:00:17 - mmengine - INFO - Epoch(train) [13][120/2119] lr: 4.0000e-02 eta: 1 day, 3:17:52 time: 0.3081 data_time: 0.0607 memory: 5826 grad_norm: 2.9240 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0413 loss: 3.0413 2022/10/07 10:00:23 - mmengine - INFO - Epoch(train) [13][140/2119] lr: 4.0000e-02 eta: 1 day, 3:17:39 time: 0.3080 data_time: 0.0575 memory: 5826 grad_norm: 2.8496 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7496 loss: 2.7496 2022/10/07 10:00:30 - mmengine - INFO - Epoch(train) [13][160/2119] lr: 4.0000e-02 eta: 1 day, 3:17:29 time: 0.3234 data_time: 0.0495 memory: 5826 grad_norm: 2.8622 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6107 loss: 2.6107 2022/10/07 10:00:37 - mmengine - INFO - Epoch(train) [13][180/2119] lr: 4.0000e-02 eta: 1 day, 3:17:30 time: 0.3694 data_time: 0.0973 memory: 5826 grad_norm: 2.9390 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6587 loss: 2.6587 2022/10/07 10:00:44 - mmengine - INFO - Epoch(train) [13][200/2119] lr: 4.0000e-02 eta: 1 day, 3:17:24 time: 0.3390 data_time: 0.0161 memory: 5826 grad_norm: 2.8966 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8810 loss: 2.8810 2022/10/07 10:00:50 - mmengine - INFO - Epoch(train) [13][220/2119] lr: 4.0000e-02 eta: 1 day, 3:17:12 time: 0.3103 data_time: 0.0209 memory: 5826 grad_norm: 2.8882 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8474 loss: 2.8474 2022/10/07 10:00:57 - mmengine - INFO - Epoch(train) [13][240/2119] lr: 4.0000e-02 eta: 1 day, 3:17:00 time: 0.3126 data_time: 0.0218 memory: 5826 grad_norm: 2.8964 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6988 loss: 2.6988 2022/10/07 10:01:04 - mmengine - INFO - Epoch(train) [13][260/2119] lr: 4.0000e-02 eta: 1 day, 3:16:59 time: 0.3642 data_time: 0.0240 memory: 5826 grad_norm: 2.9187 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9738 loss: 2.9738 2022/10/07 10:01:10 - mmengine - INFO - Epoch(train) [13][280/2119] lr: 4.0000e-02 eta: 1 day, 3:16:48 time: 0.3179 data_time: 0.0175 memory: 5826 grad_norm: 2.8352 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9805 loss: 2.9805 2022/10/07 10:01:18 - mmengine - INFO - Epoch(train) [13][300/2119] lr: 4.0000e-02 eta: 1 day, 3:16:51 time: 0.3787 data_time: 0.0221 memory: 5826 grad_norm: 2.8623 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7824 loss: 2.7824 2022/10/07 10:01:24 - mmengine - INFO - Epoch(train) [13][320/2119] lr: 4.0000e-02 eta: 1 day, 3:16:38 time: 0.3067 data_time: 0.0197 memory: 5826 grad_norm: 2.9423 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9133 loss: 2.9133 2022/10/07 10:01:30 - mmengine - INFO - Epoch(train) [13][340/2119] lr: 4.0000e-02 eta: 1 day, 3:16:26 time: 0.3150 data_time: 0.0206 memory: 5826 grad_norm: 2.8657 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.9173 loss: 2.9173 2022/10/07 10:01:37 - mmengine - INFO - Epoch(train) [13][360/2119] lr: 4.0000e-02 eta: 1 day, 3:16:17 time: 0.3255 data_time: 0.0199 memory: 5826 grad_norm: 2.9012 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8046 loss: 2.8046 2022/10/07 10:01:43 - mmengine - INFO - Epoch(train) [13][380/2119] lr: 4.0000e-02 eta: 1 day, 3:16:05 time: 0.3103 data_time: 0.0230 memory: 5826 grad_norm: 2.8889 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8420 loss: 2.8420 2022/10/07 10:01:50 - mmengine - INFO - Epoch(train) [13][400/2119] lr: 4.0000e-02 eta: 1 day, 3:16:03 time: 0.3585 data_time: 0.0204 memory: 5826 grad_norm: 2.8438 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8072 loss: 2.8072 2022/10/07 10:01:57 - mmengine - INFO - Epoch(train) [13][420/2119] lr: 4.0000e-02 eta: 1 day, 3:15:54 time: 0.3281 data_time: 0.0327 memory: 5826 grad_norm: 2.9232 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7446 loss: 2.7446 2022/10/07 10:02:04 - mmengine - INFO - Epoch(train) [13][440/2119] lr: 4.0000e-02 eta: 1 day, 3:15:54 time: 0.3639 data_time: 0.0202 memory: 5826 grad_norm: 2.8861 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7430 loss: 2.7430 2022/10/07 10:02:10 - mmengine - INFO - Epoch(train) [13][460/2119] lr: 4.0000e-02 eta: 1 day, 3:15:43 time: 0.3159 data_time: 0.0216 memory: 5826 grad_norm: 2.8282 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7567 loss: 2.7567 2022/10/07 10:02:16 - mmengine - INFO - Epoch(train) [13][480/2119] lr: 4.0000e-02 eta: 1 day, 3:15:30 time: 0.3120 data_time: 0.0215 memory: 5826 grad_norm: 2.9261 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8712 loss: 2.8712 2022/10/07 10:02:23 - mmengine - INFO - Epoch(train) [13][500/2119] lr: 4.0000e-02 eta: 1 day, 3:15:21 time: 0.3229 data_time: 0.0194 memory: 5826 grad_norm: 2.9301 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0314 loss: 3.0314 2022/10/07 10:02:30 - mmengine - INFO - Epoch(train) [13][520/2119] lr: 4.0000e-02 eta: 1 day, 3:15:20 time: 0.3619 data_time: 0.0228 memory: 5826 grad_norm: 2.8959 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8238 loss: 2.8238 2022/10/07 10:02:36 - mmengine - INFO - Epoch(train) [13][540/2119] lr: 4.0000e-02 eta: 1 day, 3:15:05 time: 0.3003 data_time: 0.0205 memory: 5826 grad_norm: 2.9254 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8280 loss: 2.8280 2022/10/07 10:02:43 - mmengine - INFO - Epoch(train) [13][560/2119] lr: 4.0000e-02 eta: 1 day, 3:14:55 time: 0.3189 data_time: 0.0184 memory: 5826 grad_norm: 2.9079 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8000 loss: 2.8000 2022/10/07 10:02:47 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 10:02:50 - mmengine - INFO - Epoch(train) [13][580/2119] lr: 4.0000e-02 eta: 1 day, 3:14:51 time: 0.3494 data_time: 0.0190 memory: 5826 grad_norm: 2.9431 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9409 loss: 2.9409 2022/10/07 10:02:56 - mmengine - INFO - Epoch(train) [13][600/2119] lr: 4.0000e-02 eta: 1 day, 3:14:44 time: 0.3372 data_time: 0.0229 memory: 5826 grad_norm: 2.9445 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0198 loss: 3.0198 2022/10/07 10:03:03 - mmengine - INFO - Epoch(train) [13][620/2119] lr: 4.0000e-02 eta: 1 day, 3:14:36 time: 0.3299 data_time: 0.0280 memory: 5826 grad_norm: 2.9462 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9823 loss: 2.9823 2022/10/07 10:03:09 - mmengine - INFO - Epoch(train) [13][640/2119] lr: 4.0000e-02 eta: 1 day, 3:14:23 time: 0.3082 data_time: 0.0241 memory: 5826 grad_norm: 2.8925 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9700 loss: 2.9700 2022/10/07 10:03:16 - mmengine - INFO - Epoch(train) [13][660/2119] lr: 4.0000e-02 eta: 1 day, 3:14:15 time: 0.3283 data_time: 0.0223 memory: 5826 grad_norm: 2.9262 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.1686 loss: 3.1686 2022/10/07 10:03:22 - mmengine - INFO - Epoch(train) [13][680/2119] lr: 4.0000e-02 eta: 1 day, 3:14:04 time: 0.3190 data_time: 0.0209 memory: 5826 grad_norm: 2.8945 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9484 loss: 2.9484 2022/10/07 10:03:29 - mmengine - INFO - Epoch(train) [13][700/2119] lr: 4.0000e-02 eta: 1 day, 3:14:01 time: 0.3515 data_time: 0.0271 memory: 5826 grad_norm: 2.8675 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6497 loss: 2.6497 2022/10/07 10:03:35 - mmengine - INFO - Epoch(train) [13][720/2119] lr: 4.0000e-02 eta: 1 day, 3:13:51 time: 0.3227 data_time: 0.0200 memory: 5826 grad_norm: 2.9044 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8627 loss: 2.8627 2022/10/07 10:03:42 - mmengine - INFO - Epoch(train) [13][740/2119] lr: 4.0000e-02 eta: 1 day, 3:13:43 time: 0.3273 data_time: 0.0296 memory: 5826 grad_norm: 2.9246 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9139 loss: 2.9139 2022/10/07 10:03:50 - mmengine - INFO - Epoch(train) [13][760/2119] lr: 4.0000e-02 eta: 1 day, 3:13:45 time: 0.3788 data_time: 0.0180 memory: 5826 grad_norm: 2.8834 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8452 loss: 2.8452 2022/10/07 10:03:57 - mmengine - INFO - Epoch(train) [13][780/2119] lr: 4.0000e-02 eta: 1 day, 3:13:44 time: 0.3586 data_time: 0.0218 memory: 5826 grad_norm: 2.8916 top1_acc: 0.2500 top5_acc: 0.8125 loss_cls: 2.7892 loss: 2.7892 2022/10/07 10:04:04 - mmengine - INFO - Epoch(train) [13][800/2119] lr: 4.0000e-02 eta: 1 day, 3:13:45 time: 0.3716 data_time: 0.0204 memory: 5826 grad_norm: 2.9279 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7899 loss: 2.7899 2022/10/07 10:04:11 - mmengine - INFO - Epoch(train) [13][820/2119] lr: 4.0000e-02 eta: 1 day, 3:13:36 time: 0.3267 data_time: 0.0254 memory: 5826 grad_norm: 2.8634 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8663 loss: 2.8663 2022/10/07 10:04:18 - mmengine - INFO - Epoch(train) [13][840/2119] lr: 4.0000e-02 eta: 1 day, 3:13:33 time: 0.3513 data_time: 0.0170 memory: 5826 grad_norm: 2.8583 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7300 loss: 2.7300 2022/10/07 10:04:24 - mmengine - INFO - Epoch(train) [13][860/2119] lr: 4.0000e-02 eta: 1 day, 3:13:17 time: 0.2957 data_time: 0.0256 memory: 5826 grad_norm: 2.9228 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8799 loss: 2.8799 2022/10/07 10:04:30 - mmengine - INFO - Epoch(train) [13][880/2119] lr: 4.0000e-02 eta: 1 day, 3:13:10 time: 0.3333 data_time: 0.0230 memory: 5826 grad_norm: 2.8910 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6537 loss: 2.6537 2022/10/07 10:04:37 - mmengine - INFO - Epoch(train) [13][900/2119] lr: 4.0000e-02 eta: 1 day, 3:13:00 time: 0.3225 data_time: 0.0199 memory: 5826 grad_norm: 2.8920 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9447 loss: 2.9447 2022/10/07 10:04:44 - mmengine - INFO - Epoch(train) [13][920/2119] lr: 4.0000e-02 eta: 1 day, 3:12:58 time: 0.3582 data_time: 0.0186 memory: 5826 grad_norm: 2.9300 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5572 loss: 2.5572 2022/10/07 10:04:50 - mmengine - INFO - Epoch(train) [13][940/2119] lr: 4.0000e-02 eta: 1 day, 3:12:48 time: 0.3219 data_time: 0.0186 memory: 5826 grad_norm: 2.9330 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9500 loss: 2.9500 2022/10/07 10:05:03 - mmengine - INFO - Epoch(train) [13][960/2119] lr: 4.0000e-02 eta: 1 day, 3:13:49 time: 0.6411 data_time: 0.0164 memory: 5826 grad_norm: 2.9011 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6937 loss: 2.6937 2022/10/07 10:05:10 - mmengine - INFO - Epoch(train) [13][980/2119] lr: 4.0000e-02 eta: 1 day, 3:13:40 time: 0.3289 data_time: 0.0232 memory: 5826 grad_norm: 2.8501 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8265 loss: 2.8265 2022/10/07 10:05:18 - mmengine - INFO - Epoch(train) [13][1000/2119] lr: 4.0000e-02 eta: 1 day, 3:13:45 time: 0.3857 data_time: 0.0172 memory: 5826 grad_norm: 2.8680 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.8254 loss: 2.8254 2022/10/07 10:05:24 - mmengine - INFO - Epoch(train) [13][1020/2119] lr: 4.0000e-02 eta: 1 day, 3:13:32 time: 0.3104 data_time: 0.0269 memory: 5826 grad_norm: 2.8669 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0760 loss: 3.0760 2022/10/07 10:05:31 - mmengine - INFO - Epoch(train) [13][1040/2119] lr: 4.0000e-02 eta: 1 day, 3:13:31 time: 0.3633 data_time: 0.0167 memory: 5826 grad_norm: 2.8282 top1_acc: 0.0625 top5_acc: 0.2500 loss_cls: 2.9626 loss: 2.9626 2022/10/07 10:05:38 - mmengine - INFO - Epoch(train) [13][1060/2119] lr: 4.0000e-02 eta: 1 day, 3:13:29 time: 0.3555 data_time: 0.0199 memory: 5826 grad_norm: 2.9247 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.0299 loss: 3.0299 2022/10/07 10:05:45 - mmengine - INFO - Epoch(train) [13][1080/2119] lr: 4.0000e-02 eta: 1 day, 3:13:23 time: 0.3402 data_time: 0.0176 memory: 5826 grad_norm: 2.9181 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9282 loss: 2.9282 2022/10/07 10:05:51 - mmengine - INFO - Epoch(train) [13][1100/2119] lr: 4.0000e-02 eta: 1 day, 3:13:08 time: 0.2986 data_time: 0.0237 memory: 5826 grad_norm: 2.9169 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6145 loss: 2.6145 2022/10/07 10:05:58 - mmengine - INFO - Epoch(train) [13][1120/2119] lr: 4.0000e-02 eta: 1 day, 3:13:05 time: 0.3527 data_time: 0.0209 memory: 5826 grad_norm: 2.9311 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8057 loss: 2.8057 2022/10/07 10:06:04 - mmengine - INFO - Epoch(train) [13][1140/2119] lr: 4.0000e-02 eta: 1 day, 3:12:55 time: 0.3243 data_time: 0.0257 memory: 5826 grad_norm: 2.8670 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0015 loss: 3.0015 2022/10/07 10:06:11 - mmengine - INFO - Epoch(train) [13][1160/2119] lr: 4.0000e-02 eta: 1 day, 3:12:44 time: 0.3158 data_time: 0.0193 memory: 5826 grad_norm: 2.8741 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8092 loss: 2.8092 2022/10/07 10:06:18 - mmengine - INFO - Epoch(train) [13][1180/2119] lr: 4.0000e-02 eta: 1 day, 3:12:38 time: 0.3405 data_time: 0.0226 memory: 5826 grad_norm: 2.9194 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7320 loss: 2.7320 2022/10/07 10:06:24 - mmengine - INFO - Epoch(train) [13][1200/2119] lr: 4.0000e-02 eta: 1 day, 3:12:31 time: 0.3322 data_time: 0.0199 memory: 5826 grad_norm: 2.9031 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9015 loss: 2.9015 2022/10/07 10:06:30 - mmengine - INFO - Epoch(train) [13][1220/2119] lr: 4.0000e-02 eta: 1 day, 3:12:15 time: 0.2977 data_time: 0.0257 memory: 5826 grad_norm: 2.8367 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7196 loss: 2.7196 2022/10/07 10:06:37 - mmengine - INFO - Epoch(train) [13][1240/2119] lr: 4.0000e-02 eta: 1 day, 3:12:10 time: 0.3436 data_time: 0.0139 memory: 5826 grad_norm: 2.8846 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6562 loss: 2.6562 2022/10/07 10:06:44 - mmengine - INFO - Epoch(train) [13][1260/2119] lr: 4.0000e-02 eta: 1 day, 3:12:01 time: 0.3242 data_time: 0.0232 memory: 5826 grad_norm: 2.8972 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0268 loss: 3.0268 2022/10/07 10:06:50 - mmengine - INFO - Epoch(train) [13][1280/2119] lr: 4.0000e-02 eta: 1 day, 3:11:57 time: 0.3489 data_time: 0.0239 memory: 5826 grad_norm: 2.8879 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7534 loss: 2.7534 2022/10/07 10:06:57 - mmengine - INFO - Epoch(train) [13][1300/2119] lr: 4.0000e-02 eta: 1 day, 3:11:50 time: 0.3368 data_time: 0.0277 memory: 5826 grad_norm: 2.8981 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6854 loss: 2.6854 2022/10/07 10:07:05 - mmengine - INFO - Epoch(train) [13][1320/2119] lr: 4.0000e-02 eta: 1 day, 3:11:55 time: 0.3871 data_time: 0.0185 memory: 5826 grad_norm: 2.8666 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6032 loss: 2.6032 2022/10/07 10:07:11 - mmengine - INFO - Epoch(train) [13][1340/2119] lr: 4.0000e-02 eta: 1 day, 3:11:41 time: 0.3029 data_time: 0.0218 memory: 5826 grad_norm: 2.9585 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8050 loss: 2.8050 2022/10/07 10:07:18 - mmengine - INFO - Epoch(train) [13][1360/2119] lr: 4.0000e-02 eta: 1 day, 3:11:34 time: 0.3370 data_time: 0.0214 memory: 5826 grad_norm: 2.9515 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9387 loss: 2.9387 2022/10/07 10:07:25 - mmengine - INFO - Epoch(train) [13][1380/2119] lr: 4.0000e-02 eta: 1 day, 3:11:30 time: 0.3499 data_time: 0.0251 memory: 5826 grad_norm: 2.8924 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9254 loss: 2.9254 2022/10/07 10:07:32 - mmengine - INFO - Epoch(train) [13][1400/2119] lr: 4.0000e-02 eta: 1 day, 3:11:25 time: 0.3434 data_time: 0.0145 memory: 5826 grad_norm: 2.8501 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7058 loss: 2.7058 2022/10/07 10:07:37 - mmengine - INFO - Epoch(train) [13][1420/2119] lr: 4.0000e-02 eta: 1 day, 3:11:07 time: 0.2826 data_time: 0.0225 memory: 5826 grad_norm: 2.9403 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9234 loss: 2.9234 2022/10/07 10:07:45 - mmengine - INFO - Epoch(train) [13][1440/2119] lr: 4.0000e-02 eta: 1 day, 3:11:13 time: 0.3954 data_time: 0.0209 memory: 5826 grad_norm: 2.8738 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0750 loss: 3.0750 2022/10/07 10:07:51 - mmengine - INFO - Epoch(train) [13][1460/2119] lr: 4.0000e-02 eta: 1 day, 3:10:54 time: 0.2793 data_time: 0.0227 memory: 5826 grad_norm: 2.8267 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6437 loss: 2.6437 2022/10/07 10:07:58 - mmengine - INFO - Epoch(train) [13][1480/2119] lr: 4.0000e-02 eta: 1 day, 3:10:49 time: 0.3477 data_time: 0.0206 memory: 5826 grad_norm: 2.9015 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8070 loss: 2.8070 2022/10/07 10:08:05 - mmengine - INFO - Epoch(train) [13][1500/2119] lr: 4.0000e-02 eta: 1 day, 3:10:44 time: 0.3422 data_time: 0.0211 memory: 5826 grad_norm: 2.8835 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7951 loss: 2.7951 2022/10/07 10:08:11 - mmengine - INFO - Epoch(train) [13][1520/2119] lr: 4.0000e-02 eta: 1 day, 3:10:34 time: 0.3203 data_time: 0.0196 memory: 5826 grad_norm: 2.8570 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8105 loss: 2.8105 2022/10/07 10:08:17 - mmengine - INFO - Epoch(train) [13][1540/2119] lr: 4.0000e-02 eta: 1 day, 3:10:24 time: 0.3234 data_time: 0.0212 memory: 5826 grad_norm: 2.8897 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7632 loss: 2.7632 2022/10/07 10:08:24 - mmengine - INFO - Epoch(train) [13][1560/2119] lr: 4.0000e-02 eta: 1 day, 3:10:20 time: 0.3485 data_time: 0.0213 memory: 5826 grad_norm: 2.9077 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9715 loss: 2.9715 2022/10/07 10:08:28 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 10:08:31 - mmengine - INFO - Epoch(train) [13][1580/2119] lr: 4.0000e-02 eta: 1 day, 3:10:08 time: 0.3096 data_time: 0.0236 memory: 5826 grad_norm: 2.8390 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.8716 loss: 2.8716 2022/10/07 10:08:38 - mmengine - INFO - Epoch(train) [13][1600/2119] lr: 4.0000e-02 eta: 1 day, 3:10:06 time: 0.3583 data_time: 0.0226 memory: 5826 grad_norm: 2.8627 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 2.7135 loss: 2.7135 2022/10/07 10:08:44 - mmengine - INFO - Epoch(train) [13][1620/2119] lr: 4.0000e-02 eta: 1 day, 3:09:58 time: 0.3313 data_time: 0.0225 memory: 5826 grad_norm: 2.9498 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7158 loss: 2.7158 2022/10/07 10:08:51 - mmengine - INFO - Epoch(train) [13][1640/2119] lr: 4.0000e-02 eta: 1 day, 3:09:51 time: 0.3365 data_time: 0.0218 memory: 5826 grad_norm: 2.8977 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.1057 loss: 3.1057 2022/10/07 10:08:58 - mmengine - INFO - Epoch(train) [13][1660/2119] lr: 4.0000e-02 eta: 1 day, 3:09:43 time: 0.3312 data_time: 0.0240 memory: 5826 grad_norm: 2.9553 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9980 loss: 2.9980 2022/10/07 10:09:05 - mmengine - INFO - Epoch(train) [13][1680/2119] lr: 4.0000e-02 eta: 1 day, 3:09:42 time: 0.3589 data_time: 0.0207 memory: 5826 grad_norm: 2.8782 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6088 loss: 2.6088 2022/10/07 10:09:11 - mmengine - INFO - Epoch(train) [13][1700/2119] lr: 4.0000e-02 eta: 1 day, 3:09:26 time: 0.2947 data_time: 0.0207 memory: 5826 grad_norm: 2.9131 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9377 loss: 2.9377 2022/10/07 10:09:19 - mmengine - INFO - Epoch(train) [13][1720/2119] lr: 4.0000e-02 eta: 1 day, 3:09:31 time: 0.3929 data_time: 0.0192 memory: 5826 grad_norm: 2.9269 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4561 loss: 2.4561 2022/10/07 10:09:25 - mmengine - INFO - Epoch(train) [13][1740/2119] lr: 4.0000e-02 eta: 1 day, 3:09:21 time: 0.3180 data_time: 0.0290 memory: 5826 grad_norm: 2.9138 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8150 loss: 2.8150 2022/10/07 10:09:32 - mmengine - INFO - Epoch(train) [13][1760/2119] lr: 4.0000e-02 eta: 1 day, 3:09:18 time: 0.3569 data_time: 0.0212 memory: 5826 grad_norm: 2.8939 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9608 loss: 2.9608 2022/10/07 10:09:39 - mmengine - INFO - Epoch(train) [13][1780/2119] lr: 4.0000e-02 eta: 1 day, 3:09:14 time: 0.3472 data_time: 0.0241 memory: 5826 grad_norm: 2.9090 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8588 loss: 2.8588 2022/10/07 10:09:46 - mmengine - INFO - Epoch(train) [13][1800/2119] lr: 4.0000e-02 eta: 1 day, 3:09:09 time: 0.3435 data_time: 0.0190 memory: 5826 grad_norm: 2.8641 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6383 loss: 2.6383 2022/10/07 10:09:52 - mmengine - INFO - Epoch(train) [13][1820/2119] lr: 4.0000e-02 eta: 1 day, 3:08:56 time: 0.3085 data_time: 0.0242 memory: 5826 grad_norm: 2.9025 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7946 loss: 2.7946 2022/10/07 10:09:59 - mmengine - INFO - Epoch(train) [13][1840/2119] lr: 4.0000e-02 eta: 1 day, 3:08:54 time: 0.3572 data_time: 0.0184 memory: 5826 grad_norm: 2.8665 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8932 loss: 2.8932 2022/10/07 10:10:05 - mmengine - INFO - Epoch(train) [13][1860/2119] lr: 4.0000e-02 eta: 1 day, 3:08:41 time: 0.3062 data_time: 0.0251 memory: 5826 grad_norm: 2.8768 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8505 loss: 2.8505 2022/10/07 10:10:12 - mmengine - INFO - Epoch(train) [13][1880/2119] lr: 4.0000e-02 eta: 1 day, 3:08:37 time: 0.3490 data_time: 0.0231 memory: 5826 grad_norm: 2.9136 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7924 loss: 2.7924 2022/10/07 10:10:19 - mmengine - INFO - Epoch(train) [13][1900/2119] lr: 4.0000e-02 eta: 1 day, 3:08:29 time: 0.3340 data_time: 0.0302 memory: 5826 grad_norm: 2.8767 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9256 loss: 2.9256 2022/10/07 10:10:27 - mmengine - INFO - Epoch(train) [13][1920/2119] lr: 4.0000e-02 eta: 1 day, 3:08:37 time: 0.4030 data_time: 0.0661 memory: 5826 grad_norm: 2.9475 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8606 loss: 2.8606 2022/10/07 10:10:33 - mmengine - INFO - Epoch(train) [13][1940/2119] lr: 4.0000e-02 eta: 1 day, 3:08:19 time: 0.2823 data_time: 0.0231 memory: 5826 grad_norm: 2.9235 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 3.0260 loss: 3.0260 2022/10/07 10:10:39 - mmengine - INFO - Epoch(train) [13][1960/2119] lr: 4.0000e-02 eta: 1 day, 3:08:10 time: 0.3281 data_time: 0.0292 memory: 5826 grad_norm: 2.8204 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.5403 loss: 2.5403 2022/10/07 10:10:46 - mmengine - INFO - Epoch(train) [13][1980/2119] lr: 4.0000e-02 eta: 1 day, 3:08:06 time: 0.3490 data_time: 0.0209 memory: 5826 grad_norm: 2.8719 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6699 loss: 2.6699 2022/10/07 10:10:53 - mmengine - INFO - Epoch(train) [13][2000/2119] lr: 4.0000e-02 eta: 1 day, 3:08:03 time: 0.3519 data_time: 0.0151 memory: 5826 grad_norm: 2.9253 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8000 loss: 2.8000 2022/10/07 10:11:00 - mmengine - INFO - Epoch(train) [13][2020/2119] lr: 4.0000e-02 eta: 1 day, 3:07:51 time: 0.3111 data_time: 0.0255 memory: 5826 grad_norm: 2.8383 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.8647 loss: 2.8647 2022/10/07 10:11:06 - mmengine - INFO - Epoch(train) [13][2040/2119] lr: 4.0000e-02 eta: 1 day, 3:07:42 time: 0.3285 data_time: 0.0198 memory: 5826 grad_norm: 2.8529 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 3.0836 loss: 3.0836 2022/10/07 10:11:13 - mmengine - INFO - Epoch(train) [13][2060/2119] lr: 4.0000e-02 eta: 1 day, 3:07:35 time: 0.3349 data_time: 0.0213 memory: 5826 grad_norm: 2.8957 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5893 loss: 2.5893 2022/10/07 10:11:20 - mmengine - INFO - Epoch(train) [13][2080/2119] lr: 4.0000e-02 eta: 1 day, 3:07:27 time: 0.3298 data_time: 0.0231 memory: 5826 grad_norm: 2.8792 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8663 loss: 2.8663 2022/10/07 10:11:26 - mmengine - INFO - Epoch(train) [13][2100/2119] lr: 4.0000e-02 eta: 1 day, 3:07:18 time: 0.3253 data_time: 0.0227 memory: 5826 grad_norm: 2.9077 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6342 loss: 2.6342 2022/10/07 10:11:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 10:11:32 - mmengine - INFO - Epoch(train) [13][2119/2119] lr: 4.0000e-02 eta: 1 day, 3:07:18 time: 0.3116 data_time: 0.0144 memory: 5826 grad_norm: 2.9264 top1_acc: 0.2000 top5_acc: 0.5000 loss_cls: 2.7467 loss: 2.7467 2022/10/07 10:11:42 - mmengine - INFO - Epoch(train) [14][20/2119] lr: 4.0000e-02 eta: 1 day, 3:06:32 time: 0.5003 data_time: 0.1397 memory: 5826 grad_norm: 2.9086 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7910 loss: 2.7910 2022/10/07 10:11:49 - mmengine - INFO - Epoch(train) [14][40/2119] lr: 4.0000e-02 eta: 1 day, 3:06:23 time: 0.3221 data_time: 0.0182 memory: 5826 grad_norm: 2.8670 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7656 loss: 2.7656 2022/10/07 10:11:56 - mmengine - INFO - Epoch(train) [14][60/2119] lr: 4.0000e-02 eta: 1 day, 3:06:20 time: 0.3570 data_time: 0.0200 memory: 5826 grad_norm: 2.8785 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5939 loss: 2.5939 2022/10/07 10:12:02 - mmengine - INFO - Epoch(train) [14][80/2119] lr: 4.0000e-02 eta: 1 day, 3:06:11 time: 0.3225 data_time: 0.0195 memory: 5826 grad_norm: 2.8802 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9210 loss: 2.9210 2022/10/07 10:12:09 - mmengine - INFO - Epoch(train) [14][100/2119] lr: 4.0000e-02 eta: 1 day, 3:06:07 time: 0.3501 data_time: 0.0262 memory: 5826 grad_norm: 2.8750 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.5072 loss: 2.5072 2022/10/07 10:12:15 - mmengine - INFO - Epoch(train) [14][120/2119] lr: 4.0000e-02 eta: 1 day, 3:05:51 time: 0.2924 data_time: 0.0154 memory: 5826 grad_norm: 2.8738 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6885 loss: 2.6885 2022/10/07 10:12:22 - mmengine - INFO - Epoch(train) [14][140/2119] lr: 4.0000e-02 eta: 1 day, 3:05:48 time: 0.3526 data_time: 0.0213 memory: 5826 grad_norm: 2.8089 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8965 loss: 2.8965 2022/10/07 10:12:29 - mmengine - INFO - Epoch(train) [14][160/2119] lr: 4.0000e-02 eta: 1 day, 3:05:42 time: 0.3423 data_time: 0.0228 memory: 5826 grad_norm: 2.8394 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9263 loss: 2.9263 2022/10/07 10:12:36 - mmengine - INFO - Epoch(train) [14][180/2119] lr: 4.0000e-02 eta: 1 day, 3:05:36 time: 0.3369 data_time: 0.0201 memory: 5826 grad_norm: 2.8606 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5598 loss: 2.5598 2022/10/07 10:12:42 - mmengine - INFO - Epoch(train) [14][200/2119] lr: 4.0000e-02 eta: 1 day, 3:05:26 time: 0.3229 data_time: 0.0185 memory: 5826 grad_norm: 2.8667 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9225 loss: 2.9225 2022/10/07 10:12:49 - mmengine - INFO - Epoch(train) [14][220/2119] lr: 4.0000e-02 eta: 1 day, 3:05:21 time: 0.3431 data_time: 0.0237 memory: 5826 grad_norm: 2.9204 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0159 loss: 3.0159 2022/10/07 10:12:56 - mmengine - INFO - Epoch(train) [14][240/2119] lr: 4.0000e-02 eta: 1 day, 3:05:13 time: 0.3306 data_time: 0.0247 memory: 5826 grad_norm: 2.9046 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9635 loss: 2.9635 2022/10/07 10:13:01 - mmengine - INFO - Epoch(train) [14][260/2119] lr: 4.0000e-02 eta: 1 day, 3:04:54 time: 0.2760 data_time: 0.0199 memory: 5826 grad_norm: 2.8665 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6329 loss: 2.6329 2022/10/07 10:13:08 - mmengine - INFO - Epoch(train) [14][280/2119] lr: 4.0000e-02 eta: 1 day, 3:04:52 time: 0.3584 data_time: 0.0220 memory: 5826 grad_norm: 2.8788 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8555 loss: 2.8555 2022/10/07 10:13:16 - mmengine - INFO - Epoch(train) [14][300/2119] lr: 4.0000e-02 eta: 1 day, 3:04:51 time: 0.3674 data_time: 0.0277 memory: 5826 grad_norm: 2.8477 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9864 loss: 2.9864 2022/10/07 10:13:22 - mmengine - INFO - Epoch(train) [14][320/2119] lr: 4.0000e-02 eta: 1 day, 3:04:39 time: 0.3082 data_time: 0.0281 memory: 5826 grad_norm: 2.8956 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8211 loss: 2.8211 2022/10/07 10:13:28 - mmengine - INFO - Epoch(train) [14][340/2119] lr: 4.0000e-02 eta: 1 day, 3:04:28 time: 0.3179 data_time: 0.0175 memory: 5826 grad_norm: 2.8928 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.6802 loss: 2.6802 2022/10/07 10:13:35 - mmengine - INFO - Epoch(train) [14][360/2119] lr: 4.0000e-02 eta: 1 day, 3:04:22 time: 0.3402 data_time: 0.0187 memory: 5826 grad_norm: 2.8644 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8363 loss: 2.8363 2022/10/07 10:13:41 - mmengine - INFO - Epoch(train) [14][380/2119] lr: 4.0000e-02 eta: 1 day, 3:04:07 time: 0.2930 data_time: 0.0192 memory: 5826 grad_norm: 2.8979 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8010 loss: 2.8010 2022/10/07 10:13:48 - mmengine - INFO - Epoch(train) [14][400/2119] lr: 4.0000e-02 eta: 1 day, 3:04:01 time: 0.3391 data_time: 0.0254 memory: 5826 grad_norm: 2.8444 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8142 loss: 2.8142 2022/10/07 10:13:55 - mmengine - INFO - Epoch(train) [14][420/2119] lr: 4.0000e-02 eta: 1 day, 3:03:57 time: 0.3493 data_time: 0.0222 memory: 5826 grad_norm: 2.8672 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8826 loss: 2.8826 2022/10/07 10:14:01 - mmengine - INFO - Epoch(train) [14][440/2119] lr: 4.0000e-02 eta: 1 day, 3:03:51 time: 0.3434 data_time: 0.0183 memory: 5826 grad_norm: 2.8725 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8664 loss: 2.8664 2022/10/07 10:14:06 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 10:14:08 - mmengine - INFO - Epoch(train) [14][460/2119] lr: 4.0000e-02 eta: 1 day, 3:03:49 time: 0.3545 data_time: 0.0212 memory: 5826 grad_norm: 2.8706 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8395 loss: 2.8395 2022/10/07 10:14:14 - mmengine - INFO - Epoch(train) [14][480/2119] lr: 4.0000e-02 eta: 1 day, 3:03:31 time: 0.2861 data_time: 0.0243 memory: 5826 grad_norm: 2.9282 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8702 loss: 2.8702 2022/10/07 10:14:21 - mmengine - INFO - Epoch(train) [14][500/2119] lr: 4.0000e-02 eta: 1 day, 3:03:24 time: 0.3342 data_time: 0.0216 memory: 5826 grad_norm: 2.8514 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9638 loss: 2.9638 2022/10/07 10:14:28 - mmengine - INFO - Epoch(train) [14][520/2119] lr: 4.0000e-02 eta: 1 day, 3:03:19 time: 0.3422 data_time: 0.0229 memory: 5826 grad_norm: 2.8470 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9977 loss: 2.9977 2022/10/07 10:14:35 - mmengine - INFO - Epoch(train) [14][540/2119] lr: 4.0000e-02 eta: 1 day, 3:03:22 time: 0.3828 data_time: 0.0225 memory: 5826 grad_norm: 2.8861 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7750 loss: 2.7750 2022/10/07 10:14:41 - mmengine - INFO - Epoch(train) [14][560/2119] lr: 4.0000e-02 eta: 1 day, 3:03:08 time: 0.3010 data_time: 0.0204 memory: 5826 grad_norm: 2.8456 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.0439 loss: 3.0439 2022/10/07 10:14:48 - mmengine - INFO - Epoch(train) [14][580/2119] lr: 4.0000e-02 eta: 1 day, 3:03:04 time: 0.3520 data_time: 0.0217 memory: 5826 grad_norm: 2.8718 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7532 loss: 2.7532 2022/10/07 10:14:54 - mmengine - INFO - Epoch(train) [14][600/2119] lr: 4.0000e-02 eta: 1 day, 3:02:50 time: 0.3010 data_time: 0.0185 memory: 5826 grad_norm: 2.8482 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8579 loss: 2.8579 2022/10/07 10:15:02 - mmengine - INFO - Epoch(train) [14][620/2119] lr: 4.0000e-02 eta: 1 day, 3:02:55 time: 0.3914 data_time: 0.0224 memory: 5826 grad_norm: 2.8640 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9549 loss: 2.9549 2022/10/07 10:15:08 - mmengine - INFO - Epoch(train) [14][640/2119] lr: 4.0000e-02 eta: 1 day, 3:02:35 time: 0.2697 data_time: 0.0170 memory: 5826 grad_norm: 2.8911 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9962 loss: 2.9962 2022/10/07 10:15:15 - mmengine - INFO - Epoch(train) [14][660/2119] lr: 4.0000e-02 eta: 1 day, 3:02:34 time: 0.3674 data_time: 0.0185 memory: 5826 grad_norm: 2.8767 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9796 loss: 2.9796 2022/10/07 10:15:22 - mmengine - INFO - Epoch(train) [14][680/2119] lr: 4.0000e-02 eta: 1 day, 3:02:32 time: 0.3558 data_time: 0.0238 memory: 5826 grad_norm: 2.8433 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8896 loss: 2.8896 2022/10/07 10:15:29 - mmengine - INFO - Epoch(train) [14][700/2119] lr: 4.0000e-02 eta: 1 day, 3:02:23 time: 0.3261 data_time: 0.0230 memory: 5826 grad_norm: 2.9089 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7956 loss: 2.7956 2022/10/07 10:15:36 - mmengine - INFO - Epoch(train) [14][720/2119] lr: 4.0000e-02 eta: 1 day, 3:02:18 time: 0.3429 data_time: 0.0224 memory: 5826 grad_norm: 2.8321 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8718 loss: 2.8718 2022/10/07 10:15:42 - mmengine - INFO - Epoch(train) [14][740/2119] lr: 4.0000e-02 eta: 1 day, 3:02:03 time: 0.2996 data_time: 0.0234 memory: 5826 grad_norm: 2.8667 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6246 loss: 2.6246 2022/10/07 10:15:48 - mmengine - INFO - Epoch(train) [14][760/2119] lr: 4.0000e-02 eta: 1 day, 3:01:53 time: 0.3198 data_time: 0.0197 memory: 5826 grad_norm: 2.8360 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9044 loss: 2.9044 2022/10/07 10:15:55 - mmengine - INFO - Epoch(train) [14][780/2119] lr: 4.0000e-02 eta: 1 day, 3:01:46 time: 0.3314 data_time: 0.0293 memory: 5826 grad_norm: 2.8437 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8991 loss: 2.8991 2022/10/07 10:16:01 - mmengine - INFO - Epoch(train) [14][800/2119] lr: 4.0000e-02 eta: 1 day, 3:01:36 time: 0.3238 data_time: 0.0180 memory: 5826 grad_norm: 2.8967 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7264 loss: 2.7264 2022/10/07 10:16:08 - mmengine - INFO - Epoch(train) [14][820/2119] lr: 4.0000e-02 eta: 1 day, 3:01:33 time: 0.3527 data_time: 0.0245 memory: 5826 grad_norm: 2.9160 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7312 loss: 2.7312 2022/10/07 10:16:15 - mmengine - INFO - Epoch(train) [14][840/2119] lr: 4.0000e-02 eta: 1 day, 3:01:30 time: 0.3533 data_time: 0.0202 memory: 5826 grad_norm: 2.9056 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6821 loss: 2.6821 2022/10/07 10:16:23 - mmengine - INFO - Epoch(train) [14][860/2119] lr: 4.0000e-02 eta: 1 day, 3:01:31 time: 0.3731 data_time: 0.0227 memory: 5826 grad_norm: 2.9003 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6189 loss: 2.6189 2022/10/07 10:16:29 - mmengine - INFO - Epoch(train) [14][880/2119] lr: 4.0000e-02 eta: 1 day, 3:01:20 time: 0.3172 data_time: 0.0187 memory: 5826 grad_norm: 2.8782 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7897 loss: 2.7897 2022/10/07 10:16:36 - mmengine - INFO - Epoch(train) [14][900/2119] lr: 4.0000e-02 eta: 1 day, 3:01:12 time: 0.3293 data_time: 0.0192 memory: 5826 grad_norm: 2.9268 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 3.0174 loss: 3.0174 2022/10/07 10:16:42 - mmengine - INFO - Epoch(train) [14][920/2119] lr: 4.0000e-02 eta: 1 day, 3:01:04 time: 0.3285 data_time: 0.0226 memory: 5826 grad_norm: 2.8741 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0050 loss: 3.0050 2022/10/07 10:16:50 - mmengine - INFO - Epoch(train) [14][940/2119] lr: 4.0000e-02 eta: 1 day, 3:01:09 time: 0.3957 data_time: 0.0258 memory: 5826 grad_norm: 2.8473 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8312 loss: 2.8312 2022/10/07 10:16:56 - mmengine - INFO - Epoch(train) [14][960/2119] lr: 4.0000e-02 eta: 1 day, 3:00:53 time: 0.2919 data_time: 0.0235 memory: 5826 grad_norm: 2.8153 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6882 loss: 2.6882 2022/10/07 10:17:02 - mmengine - INFO - Epoch(train) [14][980/2119] lr: 4.0000e-02 eta: 1 day, 3:00:45 time: 0.3268 data_time: 0.0220 memory: 5826 grad_norm: 2.8610 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 3.0808 loss: 3.0808 2022/10/07 10:17:09 - mmengine - INFO - Epoch(train) [14][1000/2119] lr: 4.0000e-02 eta: 1 day, 3:00:36 time: 0.3278 data_time: 0.0220 memory: 5826 grad_norm: 2.8373 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7385 loss: 2.7385 2022/10/07 10:17:16 - mmengine - INFO - Epoch(train) [14][1020/2119] lr: 4.0000e-02 eta: 1 day, 3:00:36 time: 0.3653 data_time: 0.0203 memory: 5826 grad_norm: 2.8923 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6846 loss: 2.6846 2022/10/07 10:17:22 - mmengine - INFO - Epoch(train) [14][1040/2119] lr: 4.0000e-02 eta: 1 day, 3:00:22 time: 0.2998 data_time: 0.0244 memory: 5826 grad_norm: 2.8689 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.1095 loss: 3.1095 2022/10/07 10:17:29 - mmengine - INFO - Epoch(train) [14][1060/2119] lr: 4.0000e-02 eta: 1 day, 3:00:17 time: 0.3493 data_time: 0.0223 memory: 5826 grad_norm: 2.8609 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 2.7080 loss: 2.7080 2022/10/07 10:17:36 - mmengine - INFO - Epoch(train) [14][1080/2119] lr: 4.0000e-02 eta: 1 day, 3:00:07 time: 0.3154 data_time: 0.0211 memory: 5826 grad_norm: 2.8586 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9917 loss: 2.9917 2022/10/07 10:17:43 - mmengine - INFO - Epoch(train) [14][1100/2119] lr: 4.0000e-02 eta: 1 day, 3:00:02 time: 0.3467 data_time: 0.0221 memory: 5826 grad_norm: 2.8956 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7436 loss: 2.7436 2022/10/07 10:17:49 - mmengine - INFO - Epoch(train) [14][1120/2119] lr: 4.0000e-02 eta: 1 day, 2:59:56 time: 0.3399 data_time: 0.0161 memory: 5826 grad_norm: 2.8986 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8039 loss: 2.8039 2022/10/07 10:17:57 - mmengine - INFO - Epoch(train) [14][1140/2119] lr: 4.0000e-02 eta: 1 day, 2:59:56 time: 0.3689 data_time: 0.0186 memory: 5826 grad_norm: 2.9114 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.7364 loss: 2.7364 2022/10/07 10:18:03 - mmengine - INFO - Epoch(train) [14][1160/2119] lr: 4.0000e-02 eta: 1 day, 2:59:45 time: 0.3163 data_time: 0.0194 memory: 5826 grad_norm: 2.9041 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7329 loss: 2.7329 2022/10/07 10:18:11 - mmengine - INFO - Epoch(train) [14][1180/2119] lr: 4.0000e-02 eta: 1 day, 2:59:48 time: 0.3821 data_time: 0.0191 memory: 5826 grad_norm: 2.9217 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7424 loss: 2.7424 2022/10/07 10:18:17 - mmengine - INFO - Epoch(train) [14][1200/2119] lr: 4.0000e-02 eta: 1 day, 2:59:34 time: 0.3003 data_time: 0.0216 memory: 5826 grad_norm: 2.8943 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8423 loss: 2.8423 2022/10/07 10:18:23 - mmengine - INFO - Epoch(train) [14][1220/2119] lr: 4.0000e-02 eta: 1 day, 2:59:23 time: 0.3176 data_time: 0.0250 memory: 5826 grad_norm: 2.8486 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6481 loss: 2.6481 2022/10/07 10:18:30 - mmengine - INFO - Epoch(train) [14][1240/2119] lr: 4.0000e-02 eta: 1 day, 2:59:16 time: 0.3307 data_time: 0.0200 memory: 5826 grad_norm: 2.8842 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9203 loss: 2.9203 2022/10/07 10:18:36 - mmengine - INFO - Epoch(train) [14][1260/2119] lr: 4.0000e-02 eta: 1 day, 2:59:07 time: 0.3278 data_time: 0.0241 memory: 5826 grad_norm: 2.8932 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8052 loss: 2.8052 2022/10/07 10:18:42 - mmengine - INFO - Epoch(train) [14][1280/2119] lr: 4.0000e-02 eta: 1 day, 2:58:55 time: 0.3113 data_time: 0.0186 memory: 5826 grad_norm: 2.8760 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6953 loss: 2.6953 2022/10/07 10:18:50 - mmengine - INFO - Epoch(train) [14][1300/2119] lr: 4.0000e-02 eta: 1 day, 2:58:53 time: 0.3596 data_time: 0.0223 memory: 5826 grad_norm: 2.9256 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6299 loss: 2.6299 2022/10/07 10:18:57 - mmengine - INFO - Epoch(train) [14][1320/2119] lr: 4.0000e-02 eta: 1 day, 2:58:54 time: 0.3713 data_time: 0.0380 memory: 5826 grad_norm: 2.9467 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9318 loss: 2.9318 2022/10/07 10:19:03 - mmengine - INFO - Epoch(train) [14][1340/2119] lr: 4.0000e-02 eta: 1 day, 2:58:42 time: 0.3134 data_time: 0.0206 memory: 5826 grad_norm: 2.8559 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9256 loss: 2.9256 2022/10/07 10:19:10 - mmengine - INFO - Epoch(train) [14][1360/2119] lr: 4.0000e-02 eta: 1 day, 2:58:36 time: 0.3377 data_time: 0.0165 memory: 5826 grad_norm: 2.8865 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6110 loss: 2.6110 2022/10/07 10:19:18 - mmengine - INFO - Epoch(train) [14][1380/2119] lr: 4.0000e-02 eta: 1 day, 2:58:41 time: 0.3966 data_time: 0.0202 memory: 5826 grad_norm: 2.9081 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.8786 loss: 2.8786 2022/10/07 10:19:24 - mmengine - INFO - Epoch(train) [14][1400/2119] lr: 4.0000e-02 eta: 1 day, 2:58:27 time: 0.2953 data_time: 0.0229 memory: 5826 grad_norm: 2.8536 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8470 loss: 2.8470 2022/10/07 10:19:31 - mmengine - INFO - Epoch(train) [14][1420/2119] lr: 4.0000e-02 eta: 1 day, 2:58:21 time: 0.3408 data_time: 0.0251 memory: 5826 grad_norm: 2.8646 top1_acc: 0.3125 top5_acc: 0.8750 loss_cls: 2.8464 loss: 2.8464 2022/10/07 10:19:37 - mmengine - INFO - Epoch(train) [14][1440/2119] lr: 4.0000e-02 eta: 1 day, 2:58:11 time: 0.3195 data_time: 0.0210 memory: 5826 grad_norm: 2.8505 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6632 loss: 2.6632 2022/10/07 10:19:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 10:19:43 - mmengine - INFO - Epoch(train) [14][1460/2119] lr: 4.0000e-02 eta: 1 day, 2:58:01 time: 0.3187 data_time: 0.0228 memory: 5826 grad_norm: 2.8822 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.1021 loss: 3.1021 2022/10/07 10:19:51 - mmengine - INFO - Epoch(train) [14][1480/2119] lr: 4.0000e-02 eta: 1 day, 2:58:01 time: 0.3730 data_time: 0.0250 memory: 5826 grad_norm: 2.9412 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.9941 loss: 2.9941 2022/10/07 10:19:57 - mmengine - INFO - Epoch(train) [14][1500/2119] lr: 4.0000e-02 eta: 1 day, 2:57:50 time: 0.3124 data_time: 0.0230 memory: 5826 grad_norm: 2.8591 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8728 loss: 2.8728 2022/10/07 10:20:05 - mmengine - INFO - Epoch(train) [14][1520/2119] lr: 4.0000e-02 eta: 1 day, 2:57:50 time: 0.3724 data_time: 0.0166 memory: 5826 grad_norm: 2.8984 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8145 loss: 2.8145 2022/10/07 10:20:12 - mmengine - INFO - Epoch(train) [14][1540/2119] lr: 4.0000e-02 eta: 1 day, 2:57:47 time: 0.3548 data_time: 0.0162 memory: 5826 grad_norm: 2.8919 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.9065 loss: 2.9065 2022/10/07 10:20:19 - mmengine - INFO - Epoch(train) [14][1560/2119] lr: 4.0000e-02 eta: 1 day, 2:57:45 time: 0.3588 data_time: 0.0203 memory: 5826 grad_norm: 2.8978 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6697 loss: 2.6697 2022/10/07 10:20:26 - mmengine - INFO - Epoch(train) [14][1580/2119] lr: 4.0000e-02 eta: 1 day, 2:57:41 time: 0.3497 data_time: 0.0262 memory: 5826 grad_norm: 2.8626 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7703 loss: 2.7703 2022/10/07 10:20:32 - mmengine - INFO - Epoch(train) [14][1600/2119] lr: 4.0000e-02 eta: 1 day, 2:57:25 time: 0.2892 data_time: 0.0189 memory: 5826 grad_norm: 2.8753 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6887 loss: 2.6887 2022/10/07 10:20:38 - mmengine - INFO - Epoch(train) [14][1620/2119] lr: 4.0000e-02 eta: 1 day, 2:57:11 time: 0.3023 data_time: 0.0239 memory: 5826 grad_norm: 2.8956 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.8923 loss: 2.8923 2022/10/07 10:20:45 - mmengine - INFO - Epoch(train) [14][1640/2119] lr: 4.0000e-02 eta: 1 day, 2:57:11 time: 0.3660 data_time: 0.0178 memory: 5826 grad_norm: 2.8452 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8364 loss: 2.8364 2022/10/07 10:20:51 - mmengine - INFO - Epoch(train) [14][1660/2119] lr: 4.0000e-02 eta: 1 day, 2:57:00 time: 0.3174 data_time: 0.0217 memory: 5826 grad_norm: 2.8788 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9950 loss: 2.9950 2022/10/07 10:21:01 - mmengine - INFO - Epoch(train) [14][1680/2119] lr: 4.0000e-02 eta: 1 day, 2:57:21 time: 0.4729 data_time: 0.1979 memory: 5826 grad_norm: 2.8826 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7428 loss: 2.7428 2022/10/07 10:21:07 - mmengine - INFO - Epoch(train) [14][1700/2119] lr: 4.0000e-02 eta: 1 day, 2:57:05 time: 0.2896 data_time: 0.0270 memory: 5826 grad_norm: 2.8676 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7663 loss: 2.7663 2022/10/07 10:21:13 - mmengine - INFO - Epoch(train) [14][1720/2119] lr: 4.0000e-02 eta: 1 day, 2:56:56 time: 0.3242 data_time: 0.0175 memory: 5826 grad_norm: 2.8441 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8073 loss: 2.8073 2022/10/07 10:21:20 - mmengine - INFO - Epoch(train) [14][1740/2119] lr: 4.0000e-02 eta: 1 day, 2:56:50 time: 0.3407 data_time: 0.0167 memory: 5826 grad_norm: 2.9081 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0020 loss: 3.0020 2022/10/07 10:21:26 - mmengine - INFO - Epoch(train) [14][1760/2119] lr: 4.0000e-02 eta: 1 day, 2:56:39 time: 0.3155 data_time: 0.0213 memory: 5826 grad_norm: 2.8236 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0830 loss: 3.0830 2022/10/07 10:21:33 - mmengine - INFO - Epoch(train) [14][1780/2119] lr: 4.0000e-02 eta: 1 day, 2:56:33 time: 0.3408 data_time: 0.0207 memory: 5826 grad_norm: 2.8576 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6162 loss: 2.6162 2022/10/07 10:21:40 - mmengine - INFO - Epoch(train) [14][1800/2119] lr: 4.0000e-02 eta: 1 day, 2:56:30 time: 0.3570 data_time: 0.0163 memory: 5826 grad_norm: 2.8126 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.8818 loss: 2.8818 2022/10/07 10:21:47 - mmengine - INFO - Epoch(train) [14][1820/2119] lr: 4.0000e-02 eta: 1 day, 2:56:26 time: 0.3478 data_time: 0.0265 memory: 5826 grad_norm: 2.8109 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8806 loss: 2.8806 2022/10/07 10:21:54 - mmengine - INFO - Epoch(train) [14][1840/2119] lr: 4.0000e-02 eta: 1 day, 2:56:17 time: 0.3230 data_time: 0.0208 memory: 5826 grad_norm: 2.8307 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6822 loss: 2.6822 2022/10/07 10:22:01 - mmengine - INFO - Epoch(train) [14][1860/2119] lr: 4.0000e-02 eta: 1 day, 2:56:19 time: 0.3813 data_time: 0.0186 memory: 5826 grad_norm: 2.8429 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7379 loss: 2.7379 2022/10/07 10:22:08 - mmengine - INFO - Epoch(train) [14][1880/2119] lr: 4.0000e-02 eta: 1 day, 2:56:07 time: 0.3127 data_time: 0.0243 memory: 5826 grad_norm: 2.8453 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6790 loss: 2.6790 2022/10/07 10:22:15 - mmengine - INFO - Epoch(train) [14][1900/2119] lr: 4.0000e-02 eta: 1 day, 2:56:03 time: 0.3481 data_time: 0.0227 memory: 5826 grad_norm: 2.8058 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8124 loss: 2.8124 2022/10/07 10:22:21 - mmengine - INFO - Epoch(train) [14][1920/2119] lr: 4.0000e-02 eta: 1 day, 2:55:57 time: 0.3370 data_time: 0.0174 memory: 5826 grad_norm: 2.8834 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0675 loss: 3.0675 2022/10/07 10:22:28 - mmengine - INFO - Epoch(train) [14][1940/2119] lr: 4.0000e-02 eta: 1 day, 2:55:51 time: 0.3422 data_time: 0.0244 memory: 5826 grad_norm: 2.8469 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9401 loss: 2.9401 2022/10/07 10:22:35 - mmengine - INFO - Epoch(train) [14][1960/2119] lr: 4.0000e-02 eta: 1 day, 2:55:41 time: 0.3214 data_time: 0.0256 memory: 5826 grad_norm: 2.8505 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6298 loss: 2.6298 2022/10/07 10:22:42 - mmengine - INFO - Epoch(train) [14][1980/2119] lr: 4.0000e-02 eta: 1 day, 2:55:44 time: 0.3829 data_time: 0.0197 memory: 5826 grad_norm: 2.9084 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8251 loss: 2.8251 2022/10/07 10:22:48 - mmengine - INFO - Epoch(train) [14][2000/2119] lr: 4.0000e-02 eta: 1 day, 2:55:32 time: 0.3127 data_time: 0.0268 memory: 5826 grad_norm: 2.8844 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5999 loss: 2.5999 2022/10/07 10:22:56 - mmengine - INFO - Epoch(train) [14][2020/2119] lr: 4.0000e-02 eta: 1 day, 2:55:32 time: 0.3672 data_time: 0.0215 memory: 5826 grad_norm: 2.8674 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6272 loss: 2.6272 2022/10/07 10:23:02 - mmengine - INFO - Epoch(train) [14][2040/2119] lr: 4.0000e-02 eta: 1 day, 2:55:16 time: 0.2907 data_time: 0.0223 memory: 5826 grad_norm: 2.8422 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.9755 loss: 2.9755 2022/10/07 10:23:09 - mmengine - INFO - Epoch(train) [14][2060/2119] lr: 4.0000e-02 eta: 1 day, 2:55:19 time: 0.3849 data_time: 0.0223 memory: 5826 grad_norm: 2.8696 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7615 loss: 2.7615 2022/10/07 10:23:15 - mmengine - INFO - Epoch(train) [14][2080/2119] lr: 4.0000e-02 eta: 1 day, 2:55:03 time: 0.2896 data_time: 0.0245 memory: 5826 grad_norm: 2.8568 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9813 loss: 2.9813 2022/10/07 10:23:24 - mmengine - INFO - Epoch(train) [14][2100/2119] lr: 4.0000e-02 eta: 1 day, 2:55:13 time: 0.4213 data_time: 0.0198 memory: 5826 grad_norm: 2.8585 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8898 loss: 2.8898 2022/10/07 10:23:29 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 10:23:29 - mmengine - INFO - Epoch(train) [14][2119/2119] lr: 4.0000e-02 eta: 1 day, 2:55:13 time: 0.2751 data_time: 0.0191 memory: 5826 grad_norm: 2.9429 top1_acc: 0.6000 top5_acc: 0.7000 loss_cls: 2.5570 loss: 2.5570 2022/10/07 10:23:38 - mmengine - INFO - Epoch(train) [15][20/2119] lr: 4.0000e-02 eta: 1 day, 2:54:21 time: 0.4579 data_time: 0.1247 memory: 5826 grad_norm: 2.8472 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8955 loss: 2.8955 2022/10/07 10:23:45 - mmengine - INFO - Epoch(train) [15][40/2119] lr: 4.0000e-02 eta: 1 day, 2:54:19 time: 0.3603 data_time: 0.0238 memory: 5826 grad_norm: 2.8742 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8239 loss: 2.8239 2022/10/07 10:23:52 - mmengine - INFO - Epoch(train) [15][60/2119] lr: 4.0000e-02 eta: 1 day, 2:54:18 time: 0.3642 data_time: 0.0249 memory: 5826 grad_norm: 2.8422 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6631 loss: 2.6631 2022/10/07 10:23:59 - mmengine - INFO - Epoch(train) [15][80/2119] lr: 4.0000e-02 eta: 1 day, 2:54:08 time: 0.3213 data_time: 0.0221 memory: 5826 grad_norm: 2.8262 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.6539 loss: 2.6539 2022/10/07 10:24:06 - mmengine - INFO - Epoch(train) [15][100/2119] lr: 4.0000e-02 eta: 1 day, 2:54:05 time: 0.3521 data_time: 0.0251 memory: 5826 grad_norm: 2.8527 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7607 loss: 2.7607 2022/10/07 10:24:12 - mmengine - INFO - Epoch(train) [15][120/2119] lr: 4.0000e-02 eta: 1 day, 2:53:56 time: 0.3233 data_time: 0.0217 memory: 5826 grad_norm: 2.9127 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7154 loss: 2.7154 2022/10/07 10:24:20 - mmengine - INFO - Epoch(train) [15][140/2119] lr: 4.0000e-02 eta: 1 day, 2:53:53 time: 0.3586 data_time: 0.0241 memory: 5826 grad_norm: 2.8410 top1_acc: 0.3750 top5_acc: 0.9375 loss_cls: 2.7935 loss: 2.7935 2022/10/07 10:24:25 - mmengine - INFO - Epoch(train) [15][160/2119] lr: 4.0000e-02 eta: 1 day, 2:53:37 time: 0.2880 data_time: 0.0248 memory: 5826 grad_norm: 2.8953 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7609 loss: 2.7609 2022/10/07 10:24:32 - mmengine - INFO - Epoch(train) [15][180/2119] lr: 4.0000e-02 eta: 1 day, 2:53:31 time: 0.3401 data_time: 0.0250 memory: 5826 grad_norm: 2.8643 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8315 loss: 2.8315 2022/10/07 10:24:39 - mmengine - INFO - Epoch(train) [15][200/2119] lr: 4.0000e-02 eta: 1 day, 2:53:27 time: 0.3486 data_time: 0.0221 memory: 5826 grad_norm: 2.8599 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.9491 loss: 2.9491 2022/10/07 10:24:46 - mmengine - INFO - Epoch(train) [15][220/2119] lr: 4.0000e-02 eta: 1 day, 2:53:23 time: 0.3523 data_time: 0.0290 memory: 5826 grad_norm: 2.9196 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8267 loss: 2.8267 2022/10/07 10:24:52 - mmengine - INFO - Epoch(train) [15][240/2119] lr: 4.0000e-02 eta: 1 day, 2:53:10 time: 0.2996 data_time: 0.0186 memory: 5826 grad_norm: 2.8895 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7602 loss: 2.7602 2022/10/07 10:24:59 - mmengine - INFO - Epoch(train) [15][260/2119] lr: 4.0000e-02 eta: 1 day, 2:53:06 time: 0.3539 data_time: 0.0216 memory: 5826 grad_norm: 2.9225 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9557 loss: 2.9557 2022/10/07 10:25:06 - mmengine - INFO - Epoch(train) [15][280/2119] lr: 4.0000e-02 eta: 1 day, 2:52:58 time: 0.3310 data_time: 0.0224 memory: 5826 grad_norm: 2.9075 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9501 loss: 2.9501 2022/10/07 10:25:11 - mmengine - INFO - Epoch(train) [15][300/2119] lr: 4.0000e-02 eta: 1 day, 2:52:41 time: 0.2816 data_time: 0.0232 memory: 5826 grad_norm: 2.8477 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8939 loss: 2.8939 2022/10/07 10:25:19 - mmengine - INFO - Epoch(train) [15][320/2119] lr: 4.0000e-02 eta: 1 day, 2:52:40 time: 0.3635 data_time: 0.0189 memory: 5826 grad_norm: 2.8666 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7247 loss: 2.7247 2022/10/07 10:25:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 10:25:26 - mmengine - INFO - Epoch(train) [15][340/2119] lr: 4.0000e-02 eta: 1 day, 2:52:36 time: 0.3530 data_time: 0.0278 memory: 5826 grad_norm: 2.8421 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9166 loss: 2.9166 2022/10/07 10:25:32 - mmengine - INFO - Epoch(train) [15][360/2119] lr: 4.0000e-02 eta: 1 day, 2:52:26 time: 0.3192 data_time: 0.0198 memory: 5826 grad_norm: 2.9005 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8859 loss: 2.8859 2022/10/07 10:25:40 - mmengine - INFO - Epoch(train) [15][380/2119] lr: 4.0000e-02 eta: 1 day, 2:52:30 time: 0.3892 data_time: 0.0205 memory: 5826 grad_norm: 2.8500 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9051 loss: 2.9051 2022/10/07 10:25:47 - mmengine - INFO - Epoch(train) [15][400/2119] lr: 4.0000e-02 eta: 1 day, 2:52:22 time: 0.3288 data_time: 0.0297 memory: 5826 grad_norm: 2.8807 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7144 loss: 2.7144 2022/10/07 10:25:53 - mmengine - INFO - Epoch(train) [15][420/2119] lr: 4.0000e-02 eta: 1 day, 2:52:12 time: 0.3193 data_time: 0.0173 memory: 5826 grad_norm: 2.8747 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6691 loss: 2.6691 2022/10/07 10:26:01 - mmengine - INFO - Epoch(train) [15][440/2119] lr: 4.0000e-02 eta: 1 day, 2:52:16 time: 0.3940 data_time: 0.0229 memory: 5826 grad_norm: 2.8637 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8990 loss: 2.8990 2022/10/07 10:26:07 - mmengine - INFO - Epoch(train) [15][460/2119] lr: 4.0000e-02 eta: 1 day, 2:52:04 time: 0.3096 data_time: 0.0213 memory: 5826 grad_norm: 2.9044 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6493 loss: 2.6493 2022/10/07 10:26:14 - mmengine - INFO - Epoch(train) [15][480/2119] lr: 4.0000e-02 eta: 1 day, 2:52:05 time: 0.3729 data_time: 0.0222 memory: 5826 grad_norm: 2.8992 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7791 loss: 2.7791 2022/10/07 10:26:21 - mmengine - INFO - Epoch(train) [15][500/2119] lr: 4.0000e-02 eta: 1 day, 2:51:56 time: 0.3247 data_time: 0.0240 memory: 5826 grad_norm: 2.8713 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8083 loss: 2.8083 2022/10/07 10:26:28 - mmengine - INFO - Epoch(train) [15][520/2119] lr: 4.0000e-02 eta: 1 day, 2:51:56 time: 0.3726 data_time: 0.0226 memory: 5826 grad_norm: 2.8640 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7609 loss: 2.7609 2022/10/07 10:26:35 - mmengine - INFO - Epoch(train) [15][540/2119] lr: 4.0000e-02 eta: 1 day, 2:51:50 time: 0.3389 data_time: 0.0195 memory: 5826 grad_norm: 2.8731 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6512 loss: 2.6512 2022/10/07 10:26:42 - mmengine - INFO - Epoch(train) [15][560/2119] lr: 4.0000e-02 eta: 1 day, 2:51:46 time: 0.3528 data_time: 0.0244 memory: 5826 grad_norm: 2.8779 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7436 loss: 2.7436 2022/10/07 10:26:49 - mmengine - INFO - Epoch(train) [15][580/2119] lr: 4.0000e-02 eta: 1 day, 2:51:39 time: 0.3336 data_time: 0.0265 memory: 5826 grad_norm: 2.8114 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.7852 loss: 2.7852 2022/10/07 10:26:56 - mmengine - INFO - Epoch(train) [15][600/2119] lr: 4.0000e-02 eta: 1 day, 2:51:40 time: 0.3763 data_time: 0.0205 memory: 5826 grad_norm: 2.9165 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7185 loss: 2.7185 2022/10/07 10:27:03 - mmengine - INFO - Epoch(train) [15][620/2119] lr: 4.0000e-02 eta: 1 day, 2:51:28 time: 0.3116 data_time: 0.0196 memory: 5826 grad_norm: 2.8584 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7538 loss: 2.7538 2022/10/07 10:27:10 - mmengine - INFO - Epoch(train) [15][640/2119] lr: 4.0000e-02 eta: 1 day, 2:51:23 time: 0.3450 data_time: 0.0252 memory: 5826 grad_norm: 2.8954 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9978 loss: 2.9978 2022/10/07 10:27:16 - mmengine - INFO - Epoch(train) [15][660/2119] lr: 4.0000e-02 eta: 1 day, 2:51:18 time: 0.3431 data_time: 0.0205 memory: 5826 grad_norm: 2.8870 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.9084 loss: 2.9084 2022/10/07 10:27:23 - mmengine - INFO - Epoch(train) [15][680/2119] lr: 4.0000e-02 eta: 1 day, 2:51:12 time: 0.3394 data_time: 0.0252 memory: 5826 grad_norm: 2.8416 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.7845 loss: 2.7845 2022/10/07 10:27:29 - mmengine - INFO - Epoch(train) [15][700/2119] lr: 4.0000e-02 eta: 1 day, 2:50:58 time: 0.3004 data_time: 0.0208 memory: 5826 grad_norm: 2.8611 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9003 loss: 2.9003 2022/10/07 10:27:38 - mmengine - INFO - Epoch(train) [15][720/2119] lr: 4.0000e-02 eta: 1 day, 2:51:10 time: 0.4323 data_time: 0.0225 memory: 5826 grad_norm: 2.8508 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 3.0235 loss: 3.0235 2022/10/07 10:27:43 - mmengine - INFO - Epoch(train) [15][740/2119] lr: 4.0000e-02 eta: 1 day, 2:50:51 time: 0.2731 data_time: 0.0223 memory: 5826 grad_norm: 2.8543 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.8694 loss: 2.8694 2022/10/07 10:27:50 - mmengine - INFO - Epoch(train) [15][760/2119] lr: 4.0000e-02 eta: 1 day, 2:50:45 time: 0.3394 data_time: 0.0266 memory: 5826 grad_norm: 2.8691 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7175 loss: 2.7175 2022/10/07 10:27:57 - mmengine - INFO - Epoch(train) [15][780/2119] lr: 4.0000e-02 eta: 1 day, 2:50:37 time: 0.3304 data_time: 0.0330 memory: 5826 grad_norm: 2.8560 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8833 loss: 2.8833 2022/10/07 10:28:04 - mmengine - INFO - Epoch(train) [15][800/2119] lr: 4.0000e-02 eta: 1 day, 2:50:32 time: 0.3464 data_time: 0.0237 memory: 5826 grad_norm: 2.9195 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.7465 loss: 2.7465 2022/10/07 10:28:10 - mmengine - INFO - Epoch(train) [15][820/2119] lr: 4.0000e-02 eta: 1 day, 2:50:24 time: 0.3274 data_time: 0.0189 memory: 5826 grad_norm: 2.8421 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5159 loss: 2.5159 2022/10/07 10:28:18 - mmengine - INFO - Epoch(train) [15][840/2119] lr: 4.0000e-02 eta: 1 day, 2:50:23 time: 0.3649 data_time: 0.0244 memory: 5826 grad_norm: 2.9100 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9707 loss: 2.9707 2022/10/07 10:28:24 - mmengine - INFO - Epoch(train) [15][860/2119] lr: 4.0000e-02 eta: 1 day, 2:50:11 time: 0.3096 data_time: 0.0169 memory: 5826 grad_norm: 2.8475 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8862 loss: 2.8862 2022/10/07 10:28:30 - mmengine - INFO - Epoch(train) [15][880/2119] lr: 4.0000e-02 eta: 1 day, 2:50:00 time: 0.3139 data_time: 0.0307 memory: 5826 grad_norm: 2.8877 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6988 loss: 2.6988 2022/10/07 10:28:37 - mmengine - INFO - Epoch(train) [15][900/2119] lr: 4.0000e-02 eta: 1 day, 2:49:54 time: 0.3410 data_time: 0.0219 memory: 5826 grad_norm: 2.8527 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6164 loss: 2.6164 2022/10/07 10:28:43 - mmengine - INFO - Epoch(train) [15][920/2119] lr: 4.0000e-02 eta: 1 day, 2:49:45 time: 0.3254 data_time: 0.0204 memory: 5826 grad_norm: 2.9500 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7368 loss: 2.7368 2022/10/07 10:28:50 - mmengine - INFO - Epoch(train) [15][940/2119] lr: 4.0000e-02 eta: 1 day, 2:49:38 time: 0.3359 data_time: 0.0276 memory: 5826 grad_norm: 2.8455 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6479 loss: 2.6479 2022/10/07 10:28:57 - mmengine - INFO - Epoch(train) [15][960/2119] lr: 4.0000e-02 eta: 1 day, 2:49:31 time: 0.3337 data_time: 0.0222 memory: 5826 grad_norm: 2.7908 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6563 loss: 2.6563 2022/10/07 10:29:03 - mmengine - INFO - Epoch(train) [15][980/2119] lr: 4.0000e-02 eta: 1 day, 2:49:24 time: 0.3322 data_time: 0.0224 memory: 5826 grad_norm: 2.8625 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6549 loss: 2.6549 2022/10/07 10:29:10 - mmengine - INFO - Epoch(train) [15][1000/2119] lr: 4.0000e-02 eta: 1 day, 2:49:15 time: 0.3236 data_time: 0.0243 memory: 5826 grad_norm: 2.8570 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8962 loss: 2.8962 2022/10/07 10:29:16 - mmengine - INFO - Epoch(train) [15][1020/2119] lr: 4.0000e-02 eta: 1 day, 2:49:04 time: 0.3169 data_time: 0.0260 memory: 5826 grad_norm: 2.8938 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7370 loss: 2.7370 2022/10/07 10:29:23 - mmengine - INFO - Epoch(train) [15][1040/2119] lr: 4.0000e-02 eta: 1 day, 2:48:59 time: 0.3446 data_time: 0.0222 memory: 5826 grad_norm: 2.8860 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7309 loss: 2.7309 2022/10/07 10:29:29 - mmengine - INFO - Epoch(train) [15][1060/2119] lr: 4.0000e-02 eta: 1 day, 2:48:48 time: 0.3145 data_time: 0.0257 memory: 5826 grad_norm: 2.8264 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7217 loss: 2.7217 2022/10/07 10:29:37 - mmengine - INFO - Epoch(train) [15][1080/2119] lr: 4.0000e-02 eta: 1 day, 2:48:51 time: 0.3855 data_time: 0.0199 memory: 5826 grad_norm: 2.8623 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8351 loss: 2.8351 2022/10/07 10:29:43 - mmengine - INFO - Epoch(train) [15][1100/2119] lr: 4.0000e-02 eta: 1 day, 2:48:39 time: 0.3095 data_time: 0.0253 memory: 5826 grad_norm: 2.8588 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7095 loss: 2.7095 2022/10/07 10:29:50 - mmengine - INFO - Epoch(train) [15][1120/2119] lr: 4.0000e-02 eta: 1 day, 2:48:34 time: 0.3437 data_time: 0.0211 memory: 5826 grad_norm: 2.9128 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7832 loss: 2.7832 2022/10/07 10:29:57 - mmengine - INFO - Epoch(train) [15][1140/2119] lr: 4.0000e-02 eta: 1 day, 2:48:24 time: 0.3178 data_time: 0.0222 memory: 5826 grad_norm: 2.8098 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7268 loss: 2.7268 2022/10/07 10:30:04 - mmengine - INFO - Epoch(train) [15][1160/2119] lr: 4.0000e-02 eta: 1 day, 2:48:21 time: 0.3553 data_time: 0.0233 memory: 5826 grad_norm: 2.8814 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9695 loss: 2.9695 2022/10/07 10:30:10 - mmengine - INFO - Epoch(train) [15][1180/2119] lr: 4.0000e-02 eta: 1 day, 2:48:13 time: 0.3320 data_time: 0.0172 memory: 5826 grad_norm: 2.8588 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0550 loss: 3.0550 2022/10/07 10:30:17 - mmengine - INFO - Epoch(train) [15][1200/2119] lr: 4.0000e-02 eta: 1 day, 2:48:05 time: 0.3295 data_time: 0.0224 memory: 5826 grad_norm: 2.8730 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.8611 loss: 2.8611 2022/10/07 10:30:23 - mmengine - INFO - Epoch(train) [15][1220/2119] lr: 4.0000e-02 eta: 1 day, 2:47:54 time: 0.3116 data_time: 0.0186 memory: 5826 grad_norm: 2.8766 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7688 loss: 2.7688 2022/10/07 10:30:30 - mmengine - INFO - Epoch(train) [15][1240/2119] lr: 4.0000e-02 eta: 1 day, 2:47:47 time: 0.3337 data_time: 0.0290 memory: 5826 grad_norm: 2.8940 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8354 loss: 2.8354 2022/10/07 10:30:37 - mmengine - INFO - Epoch(train) [15][1260/2119] lr: 4.0000e-02 eta: 1 day, 2:47:47 time: 0.3721 data_time: 0.0383 memory: 5826 grad_norm: 2.8567 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7317 loss: 2.7317 2022/10/07 10:30:44 - mmengine - INFO - Epoch(train) [15][1280/2119] lr: 4.0000e-02 eta: 1 day, 2:47:41 time: 0.3410 data_time: 0.0200 memory: 5826 grad_norm: 2.8766 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8977 loss: 2.8977 2022/10/07 10:30:50 - mmengine - INFO - Epoch(train) [15][1300/2119] lr: 4.0000e-02 eta: 1 day, 2:47:27 time: 0.2998 data_time: 0.0196 memory: 5826 grad_norm: 2.8511 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9725 loss: 2.9725 2022/10/07 10:30:58 - mmengine - INFO - Epoch(train) [15][1320/2119] lr: 4.0000e-02 eta: 1 day, 2:47:31 time: 0.3916 data_time: 0.0222 memory: 5826 grad_norm: 2.8700 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.2753 loss: 3.2753 2022/10/07 10:31:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 10:31:04 - mmengine - INFO - Epoch(train) [15][1340/2119] lr: 4.0000e-02 eta: 1 day, 2:47:19 time: 0.3091 data_time: 0.0241 memory: 5826 grad_norm: 2.9498 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9116 loss: 2.9116 2022/10/07 10:31:11 - mmengine - INFO - Epoch(train) [15][1360/2119] lr: 4.0000e-02 eta: 1 day, 2:47:16 time: 0.3559 data_time: 0.0259 memory: 5826 grad_norm: 2.9011 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6797 loss: 2.6797 2022/10/07 10:31:18 - mmengine - INFO - Epoch(train) [15][1380/2119] lr: 4.0000e-02 eta: 1 day, 2:47:14 time: 0.3618 data_time: 0.0193 memory: 5826 grad_norm: 2.9361 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6865 loss: 2.6865 2022/10/07 10:31:24 - mmengine - INFO - Epoch(train) [15][1400/2119] lr: 4.0000e-02 eta: 1 day, 2:46:59 time: 0.2918 data_time: 0.0238 memory: 5826 grad_norm: 2.8701 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8366 loss: 2.8366 2022/10/07 10:31:31 - mmengine - INFO - Epoch(train) [15][1420/2119] lr: 4.0000e-02 eta: 1 day, 2:46:51 time: 0.3314 data_time: 0.0255 memory: 5826 grad_norm: 2.8870 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8498 loss: 2.8498 2022/10/07 10:31:37 - mmengine - INFO - Epoch(train) [15][1440/2119] lr: 4.0000e-02 eta: 1 day, 2:46:43 time: 0.3290 data_time: 0.0214 memory: 5826 grad_norm: 2.9215 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7666 loss: 2.7666 2022/10/07 10:31:44 - mmengine - INFO - Epoch(train) [15][1460/2119] lr: 4.0000e-02 eta: 1 day, 2:46:37 time: 0.3379 data_time: 0.0242 memory: 5826 grad_norm: 2.8721 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7915 loss: 2.7915 2022/10/07 10:31:51 - mmengine - INFO - Epoch(train) [15][1480/2119] lr: 4.0000e-02 eta: 1 day, 2:46:31 time: 0.3409 data_time: 0.0214 memory: 5826 grad_norm: 2.8786 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.9943 loss: 2.9943 2022/10/07 10:31:57 - mmengine - INFO - Epoch(train) [15][1500/2119] lr: 4.0000e-02 eta: 1 day, 2:46:22 time: 0.3222 data_time: 0.0226 memory: 5826 grad_norm: 2.9347 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7015 loss: 2.7015 2022/10/07 10:32:04 - mmengine - INFO - Epoch(train) [15][1520/2119] lr: 4.0000e-02 eta: 1 day, 2:46:13 time: 0.3248 data_time: 0.0227 memory: 5826 grad_norm: 2.8682 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5626 loss: 2.5626 2022/10/07 10:32:11 - mmengine - INFO - Epoch(train) [15][1540/2119] lr: 4.0000e-02 eta: 1 day, 2:46:08 time: 0.3472 data_time: 0.0226 memory: 5826 grad_norm: 2.8638 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8274 loss: 2.8274 2022/10/07 10:32:18 - mmengine - INFO - Epoch(train) [15][1560/2119] lr: 4.0000e-02 eta: 1 day, 2:46:03 time: 0.3433 data_time: 0.0210 memory: 5826 grad_norm: 2.8809 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6848 loss: 2.6848 2022/10/07 10:32:24 - mmengine - INFO - Epoch(train) [15][1580/2119] lr: 4.0000e-02 eta: 1 day, 2:45:54 time: 0.3255 data_time: 0.0165 memory: 5826 grad_norm: 2.9277 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7386 loss: 2.7386 2022/10/07 10:32:31 - mmengine - INFO - Epoch(train) [15][1600/2119] lr: 4.0000e-02 eta: 1 day, 2:45:50 time: 0.3512 data_time: 0.0621 memory: 5826 grad_norm: 2.8509 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6401 loss: 2.6401 2022/10/07 10:32:38 - mmengine - INFO - Epoch(train) [15][1620/2119] lr: 4.0000e-02 eta: 1 day, 2:45:39 time: 0.3109 data_time: 0.0332 memory: 5826 grad_norm: 2.8577 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9419 loss: 2.9419 2022/10/07 10:32:44 - mmengine - INFO - Epoch(train) [15][1640/2119] lr: 4.0000e-02 eta: 1 day, 2:45:34 time: 0.3459 data_time: 0.0210 memory: 5826 grad_norm: 2.8812 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7352 loss: 2.7352 2022/10/07 10:32:52 - mmengine - INFO - Epoch(train) [15][1660/2119] lr: 4.0000e-02 eta: 1 day, 2:45:32 time: 0.3602 data_time: 0.0197 memory: 5826 grad_norm: 2.8654 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9271 loss: 2.9271 2022/10/07 10:32:59 - mmengine - INFO - Epoch(train) [15][1680/2119] lr: 4.0000e-02 eta: 1 day, 2:45:33 time: 0.3830 data_time: 0.0201 memory: 5826 grad_norm: 2.8482 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8597 loss: 2.8597 2022/10/07 10:33:05 - mmengine - INFO - Epoch(train) [15][1700/2119] lr: 4.0000e-02 eta: 1 day, 2:45:16 time: 0.2797 data_time: 0.0219 memory: 5826 grad_norm: 2.8596 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0019 loss: 3.0019 2022/10/07 10:33:13 - mmengine - INFO - Epoch(train) [15][1720/2119] lr: 4.0000e-02 eta: 1 day, 2:45:18 time: 0.3807 data_time: 0.0222 memory: 5826 grad_norm: 2.9086 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9389 loss: 2.9389 2022/10/07 10:33:19 - mmengine - INFO - Epoch(train) [15][1740/2119] lr: 4.0000e-02 eta: 1 day, 2:45:12 time: 0.3433 data_time: 0.0256 memory: 5826 grad_norm: 2.8405 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7620 loss: 2.7620 2022/10/07 10:33:26 - mmengine - INFO - Epoch(train) [15][1760/2119] lr: 4.0000e-02 eta: 1 day, 2:45:08 time: 0.3501 data_time: 0.0190 memory: 5826 grad_norm: 2.8668 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9165 loss: 2.9165 2022/10/07 10:33:32 - mmengine - INFO - Epoch(train) [15][1780/2119] lr: 4.0000e-02 eta: 1 day, 2:44:49 time: 0.2702 data_time: 0.0235 memory: 5826 grad_norm: 2.9176 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8133 loss: 2.8133 2022/10/07 10:33:38 - mmengine - INFO - Epoch(train) [15][1800/2119] lr: 4.0000e-02 eta: 1 day, 2:44:40 time: 0.3237 data_time: 0.0229 memory: 5826 grad_norm: 2.8618 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8103 loss: 2.8103 2022/10/07 10:33:45 - mmengine - INFO - Epoch(train) [15][1820/2119] lr: 4.0000e-02 eta: 1 day, 2:44:37 time: 0.3550 data_time: 0.0262 memory: 5826 grad_norm: 2.8638 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5993 loss: 2.5993 2022/10/07 10:33:52 - mmengine - INFO - Epoch(train) [15][1840/2119] lr: 4.0000e-02 eta: 1 day, 2:44:33 time: 0.3536 data_time: 0.0178 memory: 5826 grad_norm: 2.8707 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7746 loss: 2.7746 2022/10/07 10:34:00 - mmengine - INFO - Epoch(train) [15][1860/2119] lr: 4.0000e-02 eta: 1 day, 2:44:37 time: 0.3944 data_time: 0.0196 memory: 5826 grad_norm: 2.8701 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5151 loss: 2.5151 2022/10/07 10:34:08 - mmengine - INFO - Epoch(train) [15][1880/2119] lr: 4.0000e-02 eta: 1 day, 2:44:35 time: 0.3621 data_time: 0.0224 memory: 5826 grad_norm: 2.8567 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8436 loss: 2.8436 2022/10/07 10:34:13 - mmengine - INFO - Epoch(train) [15][1900/2119] lr: 4.0000e-02 eta: 1 day, 2:44:13 time: 0.2514 data_time: 0.0263 memory: 5826 grad_norm: 2.8407 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8142 loss: 2.8142 2022/10/07 10:34:19 - mmengine - INFO - Epoch(train) [15][1920/2119] lr: 4.0000e-02 eta: 1 day, 2:44:07 time: 0.3378 data_time: 0.0280 memory: 5826 grad_norm: 2.8325 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6860 loss: 2.6860 2022/10/07 10:34:30 - mmengine - INFO - Epoch(train) [15][1940/2119] lr: 4.0000e-02 eta: 1 day, 2:44:34 time: 0.5248 data_time: 0.0620 memory: 5826 grad_norm: 2.9206 top1_acc: 0.1875 top5_acc: 0.2500 loss_cls: 2.8773 loss: 2.8773 2022/10/07 10:34:35 - mmengine - INFO - Epoch(train) [15][1960/2119] lr: 4.0000e-02 eta: 1 day, 2:44:15 time: 0.2673 data_time: 0.0234 memory: 5826 grad_norm: 2.8451 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7572 loss: 2.7572 2022/10/07 10:34:45 - mmengine - INFO - Epoch(train) [15][1980/2119] lr: 4.0000e-02 eta: 1 day, 2:44:33 time: 0.4746 data_time: 0.0221 memory: 5826 grad_norm: 2.8890 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8146 loss: 2.8146 2022/10/07 10:34:50 - mmengine - INFO - Epoch(train) [15][2000/2119] lr: 4.0000e-02 eta: 1 day, 2:44:18 time: 0.2869 data_time: 0.0258 memory: 5826 grad_norm: 2.8591 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6954 loss: 2.6954 2022/10/07 10:35:01 - mmengine - INFO - Epoch(train) [15][2020/2119] lr: 4.0000e-02 eta: 1 day, 2:44:45 time: 0.5278 data_time: 0.0309 memory: 5826 grad_norm: 2.8756 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7687 loss: 2.7687 2022/10/07 10:35:07 - mmengine - INFO - Epoch(train) [15][2040/2119] lr: 4.0000e-02 eta: 1 day, 2:44:33 time: 0.3068 data_time: 0.0264 memory: 5826 grad_norm: 2.9132 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9786 loss: 2.9786 2022/10/07 10:35:13 - mmengine - INFO - Epoch(train) [15][2060/2119] lr: 4.0000e-02 eta: 1 day, 2:44:21 time: 0.3047 data_time: 0.0241 memory: 5826 grad_norm: 2.9298 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.6461 loss: 2.6461 2022/10/07 10:35:21 - mmengine - INFO - Epoch(train) [15][2080/2119] lr: 4.0000e-02 eta: 1 day, 2:44:19 time: 0.3643 data_time: 0.0338 memory: 5826 grad_norm: 2.8818 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9511 loss: 2.9511 2022/10/07 10:35:26 - mmengine - INFO - Epoch(train) [15][2100/2119] lr: 4.0000e-02 eta: 1 day, 2:44:05 time: 0.2968 data_time: 0.0236 memory: 5826 grad_norm: 2.7931 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6745 loss: 2.6745 2022/10/07 10:35:33 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 10:35:33 - mmengine - INFO - Epoch(train) [15][2119/2119] lr: 4.0000e-02 eta: 1 day, 2:44:05 time: 0.3495 data_time: 0.0230 memory: 5826 grad_norm: 2.8971 top1_acc: 0.2000 top5_acc: 0.4000 loss_cls: 2.7510 loss: 2.7510 2022/10/07 10:35:44 - mmengine - INFO - Epoch(val) [15][20/137] eta: 0:01:02 time: 0.5355 data_time: 0.4591 memory: 1241 2022/10/07 10:35:49 - mmengine - INFO - Epoch(val) [15][40/137] eta: 0:00:25 time: 0.2607 data_time: 0.1941 memory: 1241 2022/10/07 10:35:56 - mmengine - INFO - Epoch(val) [15][60/137] eta: 0:00:27 time: 0.3541 data_time: 0.2749 memory: 1241 2022/10/07 10:36:02 - mmengine - INFO - Epoch(val) [15][80/137] eta: 0:00:15 time: 0.2677 data_time: 0.2030 memory: 1241 2022/10/07 10:36:08 - mmengine - INFO - Epoch(val) [15][100/137] eta: 0:00:11 time: 0.3223 data_time: 0.2499 memory: 1241 2022/10/07 10:36:13 - mmengine - INFO - Epoch(val) [15][120/137] eta: 0:00:04 time: 0.2592 data_time: 0.1920 memory: 1241 2022/10/07 10:36:26 - mmengine - INFO - Epoch(val) [15][137/137] acc/top1: 0.4151 acc/top5: 0.6586 acc/mean1: 0.4149 2022/10/07 10:36:26 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb/best_acc/top1_epoch_5.pth is removed 2022/10/07 10:36:28 - mmengine - INFO - The best checkpoint with 0.4151 acc/top1 at 15 epoch is saved to best_acc/top1_epoch_15.pth. 2022/10/07 10:36:37 - mmengine - INFO - Epoch(train) [16][20/2119] lr: 4.0000e-02 eta: 1 day, 2:43:18 time: 0.4672 data_time: 0.1642 memory: 5826 grad_norm: 2.8717 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5497 loss: 2.5497 2022/10/07 10:36:43 - mmengine - INFO - Epoch(train) [16][40/2119] lr: 4.0000e-02 eta: 1 day, 2:43:04 time: 0.2954 data_time: 0.0246 memory: 5826 grad_norm: 2.8520 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5624 loss: 2.5624 2022/10/07 10:36:55 - mmengine - INFO - Epoch(train) [16][60/2119] lr: 4.0000e-02 eta: 1 day, 2:43:45 time: 0.5991 data_time: 0.0268 memory: 5826 grad_norm: 2.8842 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6307 loss: 2.6307 2022/10/07 10:37:01 - mmengine - INFO - Epoch(train) [16][80/2119] lr: 4.0000e-02 eta: 1 day, 2:43:26 time: 0.2677 data_time: 0.0205 memory: 5826 grad_norm: 2.8320 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.7769 loss: 2.7769 2022/10/07 10:37:11 - mmengine - INFO - Epoch(train) [16][100/2119] lr: 4.0000e-02 eta: 1 day, 2:43:48 time: 0.4985 data_time: 0.0237 memory: 5826 grad_norm: 2.8708 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7642 loss: 2.7642 2022/10/07 10:37:18 - mmengine - INFO - Epoch(train) [16][120/2119] lr: 4.0000e-02 eta: 1 day, 2:43:45 time: 0.3555 data_time: 0.0215 memory: 5826 grad_norm: 2.8684 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8402 loss: 2.8402 2022/10/07 10:37:24 - mmengine - INFO - Epoch(train) [16][140/2119] lr: 4.0000e-02 eta: 1 day, 2:43:33 time: 0.3095 data_time: 0.0220 memory: 5826 grad_norm: 2.8112 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9549 loss: 2.9549 2022/10/07 10:37:32 - mmengine - INFO - Epoch(train) [16][160/2119] lr: 4.0000e-02 eta: 1 day, 2:43:37 time: 0.3946 data_time: 0.0320 memory: 5826 grad_norm: 2.8196 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7521 loss: 2.7521 2022/10/07 10:37:38 - mmengine - INFO - Epoch(train) [16][180/2119] lr: 4.0000e-02 eta: 1 day, 2:43:23 time: 0.2973 data_time: 0.0221 memory: 5826 grad_norm: 2.8691 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6400 loss: 2.6400 2022/10/07 10:37:44 - mmengine - INFO - Epoch(train) [16][200/2119] lr: 4.0000e-02 eta: 1 day, 2:43:15 time: 0.3277 data_time: 0.0232 memory: 5826 grad_norm: 2.8749 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7255 loss: 2.7255 2022/10/07 10:37:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 10:37:53 - mmengine - INFO - Epoch(train) [16][220/2119] lr: 4.0000e-02 eta: 1 day, 2:43:21 time: 0.4112 data_time: 0.0211 memory: 5826 grad_norm: 2.8616 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7521 loss: 2.7521 2022/10/07 10:38:00 - mmengine - INFO - Epoch(train) [16][240/2119] lr: 4.0000e-02 eta: 1 day, 2:43:25 time: 0.3932 data_time: 0.0199 memory: 5826 grad_norm: 2.8506 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6194 loss: 2.6194 2022/10/07 10:38:07 - mmengine - INFO - Epoch(train) [16][260/2119] lr: 4.0000e-02 eta: 1 day, 2:43:15 time: 0.3188 data_time: 0.0215 memory: 5826 grad_norm: 2.8672 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7324 loss: 2.7324 2022/10/07 10:38:14 - mmengine - INFO - Epoch(train) [16][280/2119] lr: 4.0000e-02 eta: 1 day, 2:43:15 time: 0.3764 data_time: 0.0203 memory: 5826 grad_norm: 2.8892 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8831 loss: 2.8831 2022/10/07 10:38:21 - mmengine - INFO - Epoch(train) [16][300/2119] lr: 4.0000e-02 eta: 1 day, 2:43:07 time: 0.3314 data_time: 0.0157 memory: 5826 grad_norm: 2.8333 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8520 loss: 2.8520 2022/10/07 10:38:28 - mmengine - INFO - Epoch(train) [16][320/2119] lr: 4.0000e-02 eta: 1 day, 2:43:03 time: 0.3495 data_time: 0.0224 memory: 5826 grad_norm: 2.8814 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7322 loss: 2.7322 2022/10/07 10:38:34 - mmengine - INFO - Epoch(train) [16][340/2119] lr: 4.0000e-02 eta: 1 day, 2:42:54 time: 0.3214 data_time: 0.0227 memory: 5826 grad_norm: 2.8637 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.8459 loss: 2.8459 2022/10/07 10:38:41 - mmengine - INFO - Epoch(train) [16][360/2119] lr: 4.0000e-02 eta: 1 day, 2:42:43 time: 0.3170 data_time: 0.0201 memory: 5826 grad_norm: 2.8976 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7588 loss: 2.7588 2022/10/07 10:38:47 - mmengine - INFO - Epoch(train) [16][380/2119] lr: 4.0000e-02 eta: 1 day, 2:42:33 time: 0.3173 data_time: 0.0216 memory: 5826 grad_norm: 2.8548 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9464 loss: 2.9464 2022/10/07 10:38:55 - mmengine - INFO - Epoch(train) [16][400/2119] lr: 4.0000e-02 eta: 1 day, 2:42:35 time: 0.3838 data_time: 0.0195 memory: 5826 grad_norm: 2.8602 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7090 loss: 2.7090 2022/10/07 10:39:01 - mmengine - INFO - Epoch(train) [16][420/2119] lr: 4.0000e-02 eta: 1 day, 2:42:20 time: 0.2932 data_time: 0.0170 memory: 5826 grad_norm: 2.9136 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9662 loss: 2.9662 2022/10/07 10:39:09 - mmengine - INFO - Epoch(train) [16][440/2119] lr: 4.0000e-02 eta: 1 day, 2:42:24 time: 0.3926 data_time: 0.0331 memory: 5826 grad_norm: 2.8628 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7163 loss: 2.7163 2022/10/07 10:39:14 - mmengine - INFO - Epoch(train) [16][460/2119] lr: 4.0000e-02 eta: 1 day, 2:42:08 time: 0.2859 data_time: 0.0243 memory: 5826 grad_norm: 2.8632 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.5011 loss: 2.5011 2022/10/07 10:39:21 - mmengine - INFO - Epoch(train) [16][480/2119] lr: 4.0000e-02 eta: 1 day, 2:42:04 time: 0.3535 data_time: 0.0227 memory: 5826 grad_norm: 2.8628 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6287 loss: 2.6287 2022/10/07 10:39:28 - mmengine - INFO - Epoch(train) [16][500/2119] lr: 4.0000e-02 eta: 1 day, 2:41:54 time: 0.3158 data_time: 0.0198 memory: 5826 grad_norm: 2.9003 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7523 loss: 2.7523 2022/10/07 10:39:35 - mmengine - INFO - Epoch(train) [16][520/2119] lr: 4.0000e-02 eta: 1 day, 2:41:50 time: 0.3520 data_time: 0.0252 memory: 5826 grad_norm: 2.8389 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7256 loss: 2.7256 2022/10/07 10:39:41 - mmengine - INFO - Epoch(train) [16][540/2119] lr: 4.0000e-02 eta: 1 day, 2:41:41 time: 0.3252 data_time: 0.0196 memory: 5826 grad_norm: 2.8877 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.5264 loss: 2.5264 2022/10/07 10:39:48 - mmengine - INFO - Epoch(train) [16][560/2119] lr: 4.0000e-02 eta: 1 day, 2:41:34 time: 0.3350 data_time: 0.0262 memory: 5826 grad_norm: 2.9150 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.1355 loss: 3.1355 2022/10/07 10:39:54 - mmengine - INFO - Epoch(train) [16][580/2119] lr: 4.0000e-02 eta: 1 day, 2:41:26 time: 0.3311 data_time: 0.0238 memory: 5826 grad_norm: 2.8948 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6520 loss: 2.6520 2022/10/07 10:40:01 - mmengine - INFO - Epoch(train) [16][600/2119] lr: 4.0000e-02 eta: 1 day, 2:41:19 time: 0.3332 data_time: 0.0197 memory: 5826 grad_norm: 2.8947 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8047 loss: 2.8047 2022/10/07 10:40:08 - mmengine - INFO - Epoch(train) [16][620/2119] lr: 4.0000e-02 eta: 1 day, 2:41:10 time: 0.3245 data_time: 0.0258 memory: 5826 grad_norm: 2.9003 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.9087 loss: 2.9087 2022/10/07 10:40:14 - mmengine - INFO - Epoch(train) [16][640/2119] lr: 4.0000e-02 eta: 1 day, 2:41:03 time: 0.3332 data_time: 0.0219 memory: 5826 grad_norm: 2.8699 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8826 loss: 2.8826 2022/10/07 10:40:22 - mmengine - INFO - Epoch(train) [16][660/2119] lr: 4.0000e-02 eta: 1 day, 2:41:02 time: 0.3711 data_time: 0.1130 memory: 5826 grad_norm: 2.9221 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.7554 loss: 2.7554 2022/10/07 10:40:28 - mmengine - INFO - Epoch(train) [16][680/2119] lr: 4.0000e-02 eta: 1 day, 2:40:53 time: 0.3229 data_time: 0.0260 memory: 5826 grad_norm: 2.9149 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8273 loss: 2.8273 2022/10/07 10:40:35 - mmengine - INFO - Epoch(train) [16][700/2119] lr: 4.0000e-02 eta: 1 day, 2:40:48 time: 0.3472 data_time: 0.0208 memory: 5826 grad_norm: 2.8792 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7201 loss: 2.7201 2022/10/07 10:40:41 - mmengine - INFO - Epoch(train) [16][720/2119] lr: 4.0000e-02 eta: 1 day, 2:40:38 time: 0.3173 data_time: 0.0254 memory: 5826 grad_norm: 2.8262 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.6336 loss: 2.6336 2022/10/07 10:40:49 - mmengine - INFO - Epoch(train) [16][740/2119] lr: 4.0000e-02 eta: 1 day, 2:40:37 time: 0.3704 data_time: 0.0181 memory: 5826 grad_norm: 2.8514 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8264 loss: 2.8264 2022/10/07 10:40:55 - mmengine - INFO - Epoch(train) [16][760/2119] lr: 4.0000e-02 eta: 1 day, 2:40:23 time: 0.2935 data_time: 0.0236 memory: 5826 grad_norm: 2.8600 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9372 loss: 2.9372 2022/10/07 10:41:02 - mmengine - INFO - Epoch(train) [16][780/2119] lr: 4.0000e-02 eta: 1 day, 2:40:19 time: 0.3501 data_time: 0.0189 memory: 5826 grad_norm: 2.9152 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8191 loss: 2.8191 2022/10/07 10:41:08 - mmengine - INFO - Epoch(train) [16][800/2119] lr: 4.0000e-02 eta: 1 day, 2:40:05 time: 0.2975 data_time: 0.0212 memory: 5826 grad_norm: 2.8905 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.9090 loss: 2.9090 2022/10/07 10:41:16 - mmengine - INFO - Epoch(train) [16][820/2119] lr: 4.0000e-02 eta: 1 day, 2:40:13 time: 0.4222 data_time: 0.0130 memory: 5826 grad_norm: 2.8847 top1_acc: 0.0625 top5_acc: 0.3750 loss_cls: 2.8255 loss: 2.8255 2022/10/07 10:41:22 - mmengine - INFO - Epoch(train) [16][840/2119] lr: 4.0000e-02 eta: 1 day, 2:39:59 time: 0.2943 data_time: 0.0213 memory: 5826 grad_norm: 2.8816 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8075 loss: 2.8075 2022/10/07 10:41:29 - mmengine - INFO - Epoch(train) [16][860/2119] lr: 4.0000e-02 eta: 1 day, 2:39:56 time: 0.3569 data_time: 0.0165 memory: 5826 grad_norm: 2.8791 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7553 loss: 2.7553 2022/10/07 10:41:36 - mmengine - INFO - Epoch(train) [16][880/2119] lr: 4.0000e-02 eta: 1 day, 2:39:48 time: 0.3282 data_time: 0.0196 memory: 5826 grad_norm: 2.8997 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6561 loss: 2.6561 2022/10/07 10:41:43 - mmengine - INFO - Epoch(train) [16][900/2119] lr: 4.0000e-02 eta: 1 day, 2:39:42 time: 0.3443 data_time: 0.0238 memory: 5826 grad_norm: 2.8808 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7998 loss: 2.7998 2022/10/07 10:41:49 - mmengine - INFO - Epoch(train) [16][920/2119] lr: 4.0000e-02 eta: 1 day, 2:39:29 time: 0.2967 data_time: 0.0213 memory: 5826 grad_norm: 2.8881 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8075 loss: 2.8075 2022/10/07 10:41:56 - mmengine - INFO - Epoch(train) [16][940/2119] lr: 4.0000e-02 eta: 1 day, 2:39:26 time: 0.3577 data_time: 0.0202 memory: 5826 grad_norm: 2.8960 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9008 loss: 2.9008 2022/10/07 10:42:02 - mmengine - INFO - Epoch(train) [16][960/2119] lr: 4.0000e-02 eta: 1 day, 2:39:13 time: 0.3041 data_time: 0.0275 memory: 5826 grad_norm: 2.8769 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6898 loss: 2.6898 2022/10/07 10:42:09 - mmengine - INFO - Epoch(train) [16][980/2119] lr: 4.0000e-02 eta: 1 day, 2:39:08 time: 0.3468 data_time: 0.0218 memory: 5826 grad_norm: 2.8715 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6899 loss: 2.6899 2022/10/07 10:42:15 - mmengine - INFO - Epoch(train) [16][1000/2119] lr: 4.0000e-02 eta: 1 day, 2:39:00 time: 0.3268 data_time: 0.0205 memory: 5826 grad_norm: 2.8810 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8692 loss: 2.8692 2022/10/07 10:42:22 - mmengine - INFO - Epoch(train) [16][1020/2119] lr: 4.0000e-02 eta: 1 day, 2:38:52 time: 0.3308 data_time: 0.0177 memory: 5826 grad_norm: 2.8902 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5814 loss: 2.5814 2022/10/07 10:42:30 - mmengine - INFO - Epoch(train) [16][1040/2119] lr: 4.0000e-02 eta: 1 day, 2:38:53 time: 0.3822 data_time: 0.0251 memory: 5826 grad_norm: 2.8948 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7642 loss: 2.7642 2022/10/07 10:42:36 - mmengine - INFO - Epoch(train) [16][1060/2119] lr: 4.0000e-02 eta: 1 day, 2:38:41 time: 0.3033 data_time: 0.0205 memory: 5826 grad_norm: 2.8435 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5992 loss: 2.5992 2022/10/07 10:42:43 - mmengine - INFO - Epoch(train) [16][1080/2119] lr: 4.0000e-02 eta: 1 day, 2:38:43 time: 0.3869 data_time: 0.0210 memory: 5826 grad_norm: 2.8964 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7363 loss: 2.7363 2022/10/07 10:42:49 - mmengine - INFO - Epoch(train) [16][1100/2119] lr: 4.0000e-02 eta: 1 day, 2:38:28 time: 0.2908 data_time: 0.0193 memory: 5826 grad_norm: 2.8951 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6407 loss: 2.6407 2022/10/07 10:42:56 - mmengine - INFO - Epoch(train) [16][1120/2119] lr: 4.0000e-02 eta: 1 day, 2:38:25 time: 0.3564 data_time: 0.0244 memory: 5826 grad_norm: 2.9125 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7551 loss: 2.7551 2022/10/07 10:43:03 - mmengine - INFO - Epoch(train) [16][1140/2119] lr: 4.0000e-02 eta: 1 day, 2:38:19 time: 0.3442 data_time: 0.0212 memory: 5826 grad_norm: 2.8565 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9716 loss: 2.9716 2022/10/07 10:43:10 - mmengine - INFO - Epoch(train) [16][1160/2119] lr: 4.0000e-02 eta: 1 day, 2:38:16 time: 0.3576 data_time: 0.0266 memory: 5826 grad_norm: 2.8641 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9231 loss: 2.9231 2022/10/07 10:43:17 - mmengine - INFO - Epoch(train) [16][1180/2119] lr: 4.0000e-02 eta: 1 day, 2:38:05 time: 0.3085 data_time: 0.0223 memory: 5826 grad_norm: 2.8901 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8386 loss: 2.8386 2022/10/07 10:43:23 - mmengine - INFO - Epoch(train) [16][1200/2119] lr: 4.0000e-02 eta: 1 day, 2:37:58 time: 0.3383 data_time: 0.0245 memory: 5826 grad_norm: 2.9246 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.5057 loss: 2.5057 2022/10/07 10:43:29 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 10:43:30 - mmengine - INFO - Epoch(train) [16][1220/2119] lr: 4.0000e-02 eta: 1 day, 2:37:52 time: 0.3394 data_time: 0.0185 memory: 5826 grad_norm: 2.8936 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6647 loss: 2.6647 2022/10/07 10:43:37 - mmengine - INFO - Epoch(train) [16][1240/2119] lr: 4.0000e-02 eta: 1 day, 2:37:49 time: 0.3588 data_time: 0.0282 memory: 5826 grad_norm: 2.8486 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9141 loss: 2.9141 2022/10/07 10:43:44 - mmengine - INFO - Epoch(train) [16][1260/2119] lr: 4.0000e-02 eta: 1 day, 2:37:41 time: 0.3308 data_time: 0.0227 memory: 5826 grad_norm: 2.8906 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8334 loss: 2.8334 2022/10/07 10:43:50 - mmengine - INFO - Epoch(train) [16][1280/2119] lr: 4.0000e-02 eta: 1 day, 2:37:33 time: 0.3294 data_time: 0.0213 memory: 5826 grad_norm: 2.8904 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6590 loss: 2.6590 2022/10/07 10:43:57 - mmengine - INFO - Epoch(train) [16][1300/2119] lr: 4.0000e-02 eta: 1 day, 2:37:24 time: 0.3231 data_time: 0.0218 memory: 5826 grad_norm: 2.8865 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9755 loss: 2.9755 2022/10/07 10:44:04 - mmengine - INFO - Epoch(train) [16][1320/2119] lr: 4.0000e-02 eta: 1 day, 2:37:19 time: 0.3468 data_time: 0.0220 memory: 5826 grad_norm: 2.8638 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9561 loss: 2.9561 2022/10/07 10:44:10 - mmengine - INFO - Epoch(train) [16][1340/2119] lr: 4.0000e-02 eta: 1 day, 2:37:11 time: 0.3277 data_time: 0.0207 memory: 5826 grad_norm: 2.8564 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7698 loss: 2.7698 2022/10/07 10:44:18 - mmengine - INFO - Epoch(train) [16][1360/2119] lr: 4.0000e-02 eta: 1 day, 2:37:09 time: 0.3613 data_time: 0.0283 memory: 5826 grad_norm: 2.8539 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.5848 loss: 2.5848 2022/10/07 10:44:24 - mmengine - INFO - Epoch(train) [16][1380/2119] lr: 4.0000e-02 eta: 1 day, 2:37:00 time: 0.3264 data_time: 0.0226 memory: 5826 grad_norm: 2.8564 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6564 loss: 2.6564 2022/10/07 10:44:31 - mmengine - INFO - Epoch(train) [16][1400/2119] lr: 4.0000e-02 eta: 1 day, 2:36:51 time: 0.3213 data_time: 0.0245 memory: 5826 grad_norm: 2.8295 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.9625 loss: 2.9625 2022/10/07 10:44:36 - mmengine - INFO - Epoch(train) [16][1420/2119] lr: 4.0000e-02 eta: 1 day, 2:36:36 time: 0.2869 data_time: 0.0201 memory: 5826 grad_norm: 2.8464 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7085 loss: 2.7085 2022/10/07 10:44:43 - mmengine - INFO - Epoch(train) [16][1440/2119] lr: 4.0000e-02 eta: 1 day, 2:36:27 time: 0.3255 data_time: 0.0224 memory: 5826 grad_norm: 2.8613 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5799 loss: 2.5799 2022/10/07 10:44:50 - mmengine - INFO - Epoch(train) [16][1460/2119] lr: 4.0000e-02 eta: 1 day, 2:36:20 time: 0.3347 data_time: 0.0190 memory: 5826 grad_norm: 2.8757 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7806 loss: 2.7806 2022/10/07 10:44:57 - mmengine - INFO - Epoch(train) [16][1480/2119] lr: 4.0000e-02 eta: 1 day, 2:36:16 time: 0.3540 data_time: 0.0212 memory: 5826 grad_norm: 2.8447 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7339 loss: 2.7339 2022/10/07 10:45:03 - mmengine - INFO - Epoch(train) [16][1500/2119] lr: 4.0000e-02 eta: 1 day, 2:36:07 time: 0.3199 data_time: 0.0202 memory: 5826 grad_norm: 2.8734 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7327 loss: 2.7327 2022/10/07 10:45:10 - mmengine - INFO - Epoch(train) [16][1520/2119] lr: 4.0000e-02 eta: 1 day, 2:36:03 time: 0.3539 data_time: 0.0436 memory: 5826 grad_norm: 2.8066 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7552 loss: 2.7552 2022/10/07 10:45:16 - mmengine - INFO - Epoch(train) [16][1540/2119] lr: 4.0000e-02 eta: 1 day, 2:35:50 time: 0.3018 data_time: 0.0178 memory: 5826 grad_norm: 2.8675 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.9305 loss: 2.9305 2022/10/07 10:45:23 - mmengine - INFO - Epoch(train) [16][1560/2119] lr: 4.0000e-02 eta: 1 day, 2:35:48 time: 0.3646 data_time: 0.0212 memory: 5826 grad_norm: 2.8603 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8046 loss: 2.8046 2022/10/07 10:45:30 - mmengine - INFO - Epoch(train) [16][1580/2119] lr: 4.0000e-02 eta: 1 day, 2:35:41 time: 0.3328 data_time: 0.0233 memory: 5826 grad_norm: 2.9120 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6991 loss: 2.6991 2022/10/07 10:45:37 - mmengine - INFO - Epoch(train) [16][1600/2119] lr: 4.0000e-02 eta: 1 day, 2:35:36 time: 0.3489 data_time: 0.0236 memory: 5826 grad_norm: 2.8526 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6900 loss: 2.6900 2022/10/07 10:45:45 - mmengine - INFO - Epoch(train) [16][1620/2119] lr: 4.0000e-02 eta: 1 day, 2:35:36 time: 0.3741 data_time: 0.0192 memory: 5826 grad_norm: 2.9296 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7906 loss: 2.7906 2022/10/07 10:45:52 - mmengine - INFO - Epoch(train) [16][1640/2119] lr: 4.0000e-02 eta: 1 day, 2:35:35 time: 0.3718 data_time: 0.0249 memory: 5826 grad_norm: 2.8684 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8383 loss: 2.8383 2022/10/07 10:46:03 - mmengine - INFO - Epoch(train) [16][1660/2119] lr: 4.0000e-02 eta: 1 day, 2:36:01 time: 0.5293 data_time: 0.0342 memory: 5826 grad_norm: 2.8957 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7392 loss: 2.7392 2022/10/07 10:46:09 - mmengine - INFO - Epoch(train) [16][1680/2119] lr: 4.0000e-02 eta: 1 day, 2:35:50 time: 0.3099 data_time: 0.0265 memory: 5826 grad_norm: 2.8538 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7687 loss: 2.7687 2022/10/07 10:46:15 - mmengine - INFO - Epoch(train) [16][1700/2119] lr: 4.0000e-02 eta: 1 day, 2:35:41 time: 0.3247 data_time: 0.0238 memory: 5826 grad_norm: 2.8486 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.9598 loss: 2.9598 2022/10/07 10:46:25 - mmengine - INFO - Epoch(train) [16][1720/2119] lr: 4.0000e-02 eta: 1 day, 2:36:02 time: 0.4992 data_time: 0.0335 memory: 5826 grad_norm: 2.8524 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.8639 loss: 2.8639 2022/10/07 10:46:32 - mmengine - INFO - Epoch(train) [16][1740/2119] lr: 4.0000e-02 eta: 1 day, 2:35:53 time: 0.3220 data_time: 0.0196 memory: 5826 grad_norm: 2.8362 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5966 loss: 2.5966 2022/10/07 10:46:40 - mmengine - INFO - Epoch(train) [16][1760/2119] lr: 4.0000e-02 eta: 1 day, 2:36:00 time: 0.4217 data_time: 0.0260 memory: 5826 grad_norm: 2.9006 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8263 loss: 2.8263 2022/10/07 10:46:45 - mmengine - INFO - Epoch(train) [16][1780/2119] lr: 4.0000e-02 eta: 1 day, 2:35:41 time: 0.2602 data_time: 0.0269 memory: 5826 grad_norm: 2.8497 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0065 loss: 3.0065 2022/10/07 10:46:53 - mmengine - INFO - Epoch(train) [16][1800/2119] lr: 4.0000e-02 eta: 1 day, 2:35:38 time: 0.3636 data_time: 0.0930 memory: 5826 grad_norm: 2.8258 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7604 loss: 2.7604 2022/10/07 10:46:59 - mmengine - INFO - Epoch(train) [16][1820/2119] lr: 4.0000e-02 eta: 1 day, 2:35:31 time: 0.3343 data_time: 0.0339 memory: 5826 grad_norm: 2.8091 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9484 loss: 2.9484 2022/10/07 10:47:06 - mmengine - INFO - Epoch(train) [16][1840/2119] lr: 4.0000e-02 eta: 1 day, 2:35:27 time: 0.3537 data_time: 0.0198 memory: 5826 grad_norm: 2.8700 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7426 loss: 2.7426 2022/10/07 10:47:13 - mmengine - INFO - Epoch(train) [16][1860/2119] lr: 4.0000e-02 eta: 1 day, 2:35:16 time: 0.3108 data_time: 0.0207 memory: 5826 grad_norm: 2.8401 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6912 loss: 2.6912 2022/10/07 10:47:23 - mmengine - INFO - Epoch(train) [16][1880/2119] lr: 4.0000e-02 eta: 1 day, 2:35:38 time: 0.5034 data_time: 0.0242 memory: 5826 grad_norm: 2.8605 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.1154 loss: 3.1154 2022/10/07 10:47:30 - mmengine - INFO - Epoch(train) [16][1900/2119] lr: 4.0000e-02 eta: 1 day, 2:35:36 time: 0.3668 data_time: 0.0190 memory: 5826 grad_norm: 2.8074 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7342 loss: 2.7342 2022/10/07 10:47:38 - mmengine - INFO - Epoch(train) [16][1920/2119] lr: 4.0000e-02 eta: 1 day, 2:35:42 time: 0.4117 data_time: 0.0217 memory: 5826 grad_norm: 2.8567 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9691 loss: 2.9691 2022/10/07 10:47:44 - mmengine - INFO - Epoch(train) [16][1940/2119] lr: 4.0000e-02 eta: 1 day, 2:35:23 time: 0.2675 data_time: 0.0240 memory: 5826 grad_norm: 2.8634 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4677 loss: 2.4677 2022/10/07 10:47:51 - mmengine - INFO - Epoch(train) [16][1960/2119] lr: 4.0000e-02 eta: 1 day, 2:35:20 time: 0.3579 data_time: 0.0233 memory: 5826 grad_norm: 2.8672 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.8047 loss: 2.8047 2022/10/07 10:47:57 - mmengine - INFO - Epoch(train) [16][1980/2119] lr: 4.0000e-02 eta: 1 day, 2:35:08 time: 0.3071 data_time: 0.0176 memory: 5826 grad_norm: 2.9042 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6656 loss: 2.6656 2022/10/07 10:48:04 - mmengine - INFO - Epoch(train) [16][2000/2119] lr: 4.0000e-02 eta: 1 day, 2:35:08 time: 0.3749 data_time: 0.0403 memory: 5826 grad_norm: 2.9000 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.0025 loss: 3.0025 2022/10/07 10:48:11 - mmengine - INFO - Epoch(train) [16][2020/2119] lr: 4.0000e-02 eta: 1 day, 2:35:04 time: 0.3517 data_time: 0.0196 memory: 5826 grad_norm: 2.8156 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6474 loss: 2.6474 2022/10/07 10:48:21 - mmengine - INFO - Epoch(train) [16][2040/2119] lr: 4.0000e-02 eta: 1 day, 2:35:19 time: 0.4657 data_time: 0.0240 memory: 5826 grad_norm: 2.8020 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6546 loss: 2.6546 2022/10/07 10:48:26 - mmengine - INFO - Epoch(train) [16][2060/2119] lr: 4.0000e-02 eta: 1 day, 2:34:57 time: 0.2463 data_time: 0.0183 memory: 5826 grad_norm: 2.8600 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7578 loss: 2.7578 2022/10/07 10:48:33 - mmengine - INFO - Epoch(train) [16][2080/2119] lr: 4.0000e-02 eta: 1 day, 2:34:55 time: 0.3642 data_time: 0.0356 memory: 5826 grad_norm: 2.8764 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6858 loss: 2.6858 2022/10/07 10:48:42 - mmengine - INFO - Epoch(train) [16][2100/2119] lr: 4.0000e-02 eta: 1 day, 2:35:07 time: 0.4482 data_time: 0.0222 memory: 5826 grad_norm: 2.8725 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8273 loss: 2.8273 2022/10/07 10:48:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 10:48:46 - mmengine - INFO - Epoch(train) [16][2119/2119] lr: 4.0000e-02 eta: 1 day, 2:35:07 time: 0.2284 data_time: 0.0179 memory: 5826 grad_norm: 2.9058 top1_acc: 0.3000 top5_acc: 0.6000 loss_cls: 2.7388 loss: 2.7388 2022/10/07 10:48:46 - mmengine - INFO - Saving checkpoint at 16 epochs 2022/10/07 10:49:10 - mmengine - INFO - Epoch(train) [17][20/2119] lr: 4.0000e-02 eta: 1 day, 2:34:57 time: 0.6758 data_time: 0.1922 memory: 5826 grad_norm: 2.8391 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4263 loss: 2.4263 2022/10/07 10:49:16 - mmengine - INFO - Epoch(train) [17][40/2119] lr: 4.0000e-02 eta: 1 day, 2:34:45 time: 0.3104 data_time: 0.0270 memory: 5826 grad_norm: 2.9371 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5938 loss: 2.5938 2022/10/07 10:49:22 - mmengine - INFO - Epoch(train) [17][60/2119] lr: 4.0000e-02 eta: 1 day, 2:34:36 time: 0.3245 data_time: 0.0287 memory: 5826 grad_norm: 2.8716 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0116 loss: 3.0116 2022/10/07 10:49:30 - mmengine - INFO - Epoch(train) [17][80/2119] lr: 4.0000e-02 eta: 1 day, 2:34:38 time: 0.3893 data_time: 0.0218 memory: 5826 grad_norm: 2.8515 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0644 loss: 3.0644 2022/10/07 10:49:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 10:49:38 - mmengine - INFO - Epoch(train) [17][100/2119] lr: 4.0000e-02 eta: 1 day, 2:34:44 time: 0.4079 data_time: 0.0225 memory: 5826 grad_norm: 2.9109 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8888 loss: 2.8888 2022/10/07 10:49:44 - mmengine - INFO - Epoch(train) [17][120/2119] lr: 4.0000e-02 eta: 1 day, 2:34:31 time: 0.2994 data_time: 0.0190 memory: 5826 grad_norm: 2.8436 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5567 loss: 2.5567 2022/10/07 10:49:52 - mmengine - INFO - Epoch(train) [17][140/2119] lr: 4.0000e-02 eta: 1 day, 2:34:34 time: 0.3974 data_time: 0.0223 memory: 5826 grad_norm: 2.8812 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9781 loss: 2.9781 2022/10/07 10:49:58 - mmengine - INFO - Epoch(train) [17][160/2119] lr: 4.0000e-02 eta: 1 day, 2:34:19 time: 0.2901 data_time: 0.0279 memory: 5826 grad_norm: 2.8894 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.4857 loss: 2.4857 2022/10/07 10:50:05 - mmengine - INFO - Epoch(train) [17][180/2119] lr: 4.0000e-02 eta: 1 day, 2:34:12 time: 0.3329 data_time: 0.0250 memory: 5826 grad_norm: 2.8893 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9188 loss: 2.9188 2022/10/07 10:50:12 - mmengine - INFO - Epoch(train) [17][200/2119] lr: 4.0000e-02 eta: 1 day, 2:34:08 time: 0.3534 data_time: 0.0186 memory: 5826 grad_norm: 2.8509 top1_acc: 0.0625 top5_acc: 0.4375 loss_cls: 2.7804 loss: 2.7804 2022/10/07 10:50:20 - mmengine - INFO - Epoch(train) [17][220/2119] lr: 4.0000e-02 eta: 1 day, 2:34:11 time: 0.3981 data_time: 0.0162 memory: 5826 grad_norm: 2.8860 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6676 loss: 2.6676 2022/10/07 10:50:26 - mmengine - INFO - Epoch(train) [17][240/2119] lr: 4.0000e-02 eta: 1 day, 2:33:57 time: 0.2924 data_time: 0.0223 memory: 5826 grad_norm: 2.9009 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.5711 loss: 2.5711 2022/10/07 10:50:33 - mmengine - INFO - Epoch(train) [17][260/2119] lr: 4.0000e-02 eta: 1 day, 2:33:53 time: 0.3543 data_time: 0.0163 memory: 5826 grad_norm: 2.8975 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7526 loss: 2.7526 2022/10/07 10:50:39 - mmengine - INFO - Epoch(train) [17][280/2119] lr: 4.0000e-02 eta: 1 day, 2:33:44 time: 0.3253 data_time: 0.0195 memory: 5826 grad_norm: 2.9041 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9216 loss: 2.9216 2022/10/07 10:50:46 - mmengine - INFO - Epoch(train) [17][300/2119] lr: 4.0000e-02 eta: 1 day, 2:33:37 time: 0.3336 data_time: 0.0227 memory: 5826 grad_norm: 2.8739 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8732 loss: 2.8732 2022/10/07 10:50:52 - mmengine - INFO - Epoch(train) [17][320/2119] lr: 4.0000e-02 eta: 1 day, 2:33:27 time: 0.3186 data_time: 0.0238 memory: 5826 grad_norm: 2.8553 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8362 loss: 2.8362 2022/10/07 10:50:59 - mmengine - INFO - Epoch(train) [17][340/2119] lr: 4.0000e-02 eta: 1 day, 2:33:25 time: 0.3609 data_time: 0.0182 memory: 5826 grad_norm: 2.8932 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7630 loss: 2.7630 2022/10/07 10:51:06 - mmengine - INFO - Epoch(train) [17][360/2119] lr: 4.0000e-02 eta: 1 day, 2:33:14 time: 0.3120 data_time: 0.0270 memory: 5826 grad_norm: 2.8578 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9351 loss: 2.9351 2022/10/07 10:51:12 - mmengine - INFO - Epoch(train) [17][380/2119] lr: 4.0000e-02 eta: 1 day, 2:33:04 time: 0.3225 data_time: 0.0293 memory: 5826 grad_norm: 2.8453 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7012 loss: 2.7012 2022/10/07 10:51:20 - mmengine - INFO - Epoch(train) [17][400/2119] lr: 4.0000e-02 eta: 1 day, 2:33:07 time: 0.3933 data_time: 0.0221 memory: 5826 grad_norm: 2.8459 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7209 loss: 2.7209 2022/10/07 10:51:26 - mmengine - INFO - Epoch(train) [17][420/2119] lr: 4.0000e-02 eta: 1 day, 2:32:53 time: 0.2938 data_time: 0.0192 memory: 5826 grad_norm: 2.8487 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6704 loss: 2.6704 2022/10/07 10:51:33 - mmengine - INFO - Epoch(train) [17][440/2119] lr: 4.0000e-02 eta: 1 day, 2:32:47 time: 0.3406 data_time: 0.0247 memory: 5826 grad_norm: 2.8910 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9603 loss: 2.9603 2022/10/07 10:51:39 - mmengine - INFO - Epoch(train) [17][460/2119] lr: 4.0000e-02 eta: 1 day, 2:32:39 time: 0.3269 data_time: 0.0214 memory: 5826 grad_norm: 2.8702 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9025 loss: 2.9025 2022/10/07 10:51:46 - mmengine - INFO - Epoch(train) [17][480/2119] lr: 4.0000e-02 eta: 1 day, 2:32:33 time: 0.3428 data_time: 0.0274 memory: 5826 grad_norm: 2.8353 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7520 loss: 2.7520 2022/10/07 10:51:52 - mmengine - INFO - Epoch(train) [17][500/2119] lr: 4.0000e-02 eta: 1 day, 2:32:20 time: 0.3031 data_time: 0.0169 memory: 5826 grad_norm: 2.9097 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7931 loss: 2.7931 2022/10/07 10:51:59 - mmengine - INFO - Epoch(train) [17][520/2119] lr: 4.0000e-02 eta: 1 day, 2:32:18 time: 0.3619 data_time: 0.0337 memory: 5826 grad_norm: 2.8396 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9904 loss: 2.9904 2022/10/07 10:52:06 - mmengine - INFO - Epoch(train) [17][540/2119] lr: 4.0000e-02 eta: 1 day, 2:32:09 time: 0.3259 data_time: 0.0228 memory: 5826 grad_norm: 2.8877 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9401 loss: 2.9401 2022/10/07 10:52:13 - mmengine - INFO - Epoch(train) [17][560/2119] lr: 4.0000e-02 eta: 1 day, 2:32:03 time: 0.3379 data_time: 0.0270 memory: 5826 grad_norm: 2.8262 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9601 loss: 2.9601 2022/10/07 10:52:19 - mmengine - INFO - Epoch(train) [17][580/2119] lr: 4.0000e-02 eta: 1 day, 2:31:54 time: 0.3266 data_time: 0.0259 memory: 5826 grad_norm: 2.8709 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7711 loss: 2.7711 2022/10/07 10:52:26 - mmengine - INFO - Epoch(train) [17][600/2119] lr: 4.0000e-02 eta: 1 day, 2:31:49 time: 0.3470 data_time: 0.0211 memory: 5826 grad_norm: 2.9015 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9299 loss: 2.9299 2022/10/07 10:52:32 - mmengine - INFO - Epoch(train) [17][620/2119] lr: 4.0000e-02 eta: 1 day, 2:31:36 time: 0.3002 data_time: 0.0214 memory: 5826 grad_norm: 2.8969 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7328 loss: 2.7328 2022/10/07 10:52:39 - mmengine - INFO - Epoch(train) [17][640/2119] lr: 4.0000e-02 eta: 1 day, 2:31:33 time: 0.3584 data_time: 0.0223 memory: 5826 grad_norm: 2.8173 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7432 loss: 2.7432 2022/10/07 10:52:46 - mmengine - INFO - Epoch(train) [17][660/2119] lr: 4.0000e-02 eta: 1 day, 2:31:29 time: 0.3527 data_time: 0.0189 memory: 5826 grad_norm: 2.8619 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6722 loss: 2.6722 2022/10/07 10:52:53 - mmengine - INFO - Epoch(train) [17][680/2119] lr: 4.0000e-02 eta: 1 day, 2:31:19 time: 0.3171 data_time: 0.0232 memory: 5826 grad_norm: 2.8657 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7216 loss: 2.7216 2022/10/07 10:52:59 - mmengine - INFO - Epoch(train) [17][700/2119] lr: 4.0000e-02 eta: 1 day, 2:31:11 time: 0.3279 data_time: 0.0233 memory: 5826 grad_norm: 2.8732 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8945 loss: 2.8945 2022/10/07 10:53:07 - mmengine - INFO - Epoch(train) [17][720/2119] lr: 4.0000e-02 eta: 1 day, 2:31:11 time: 0.3835 data_time: 0.0215 memory: 5826 grad_norm: 2.8654 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7141 loss: 2.7141 2022/10/07 10:53:13 - mmengine - INFO - Epoch(train) [17][740/2119] lr: 4.0000e-02 eta: 1 day, 2:31:02 time: 0.3212 data_time: 0.0233 memory: 5826 grad_norm: 2.8851 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7977 loss: 2.7977 2022/10/07 10:53:21 - mmengine - INFO - Epoch(train) [17][760/2119] lr: 4.0000e-02 eta: 1 day, 2:30:58 time: 0.3556 data_time: 0.0221 memory: 5826 grad_norm: 2.8547 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7010 loss: 2.7010 2022/10/07 10:53:27 - mmengine - INFO - Epoch(train) [17][780/2119] lr: 4.0000e-02 eta: 1 day, 2:30:52 time: 0.3372 data_time: 0.0223 memory: 5826 grad_norm: 2.8557 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6765 loss: 2.6765 2022/10/07 10:53:35 - mmengine - INFO - Epoch(train) [17][800/2119] lr: 4.0000e-02 eta: 1 day, 2:30:49 time: 0.3634 data_time: 0.0207 memory: 5826 grad_norm: 2.8350 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9022 loss: 2.9022 2022/10/07 10:53:41 - mmengine - INFO - Epoch(train) [17][820/2119] lr: 4.0000e-02 eta: 1 day, 2:30:41 time: 0.3268 data_time: 0.0198 memory: 5826 grad_norm: 2.8513 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6162 loss: 2.6162 2022/10/07 10:53:49 - mmengine - INFO - Epoch(train) [17][840/2119] lr: 4.0000e-02 eta: 1 day, 2:30:42 time: 0.3839 data_time: 0.0253 memory: 5826 grad_norm: 2.8905 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9429 loss: 2.9429 2022/10/07 10:53:55 - mmengine - INFO - Epoch(train) [17][860/2119] lr: 4.0000e-02 eta: 1 day, 2:30:27 time: 0.2890 data_time: 0.0192 memory: 5826 grad_norm: 2.8625 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5363 loss: 2.5363 2022/10/07 10:54:02 - mmengine - INFO - Epoch(train) [17][880/2119] lr: 4.0000e-02 eta: 1 day, 2:30:28 time: 0.3836 data_time: 0.0222 memory: 5826 grad_norm: 2.9372 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.9300 loss: 2.9300 2022/10/07 10:54:09 - mmengine - INFO - Epoch(train) [17][900/2119] lr: 4.0000e-02 eta: 1 day, 2:30:20 time: 0.3306 data_time: 0.0231 memory: 5826 grad_norm: 2.8344 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9142 loss: 2.9142 2022/10/07 10:54:15 - mmengine - INFO - Epoch(train) [17][920/2119] lr: 4.0000e-02 eta: 1 day, 2:30:10 time: 0.3149 data_time: 0.0273 memory: 5826 grad_norm: 2.8465 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.7045 loss: 2.7045 2022/10/07 10:54:22 - mmengine - INFO - Epoch(train) [17][940/2119] lr: 4.0000e-02 eta: 1 day, 2:30:04 time: 0.3458 data_time: 0.0201 memory: 5826 grad_norm: 2.8687 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7371 loss: 2.7371 2022/10/07 10:54:30 - mmengine - INFO - Epoch(train) [17][960/2119] lr: 4.0000e-02 eta: 1 day, 2:30:03 time: 0.3725 data_time: 0.0220 memory: 5826 grad_norm: 2.8311 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7138 loss: 2.7138 2022/10/07 10:54:36 - mmengine - INFO - Epoch(train) [17][980/2119] lr: 4.0000e-02 eta: 1 day, 2:29:56 time: 0.3320 data_time: 0.0142 memory: 5826 grad_norm: 2.9189 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6889 loss: 2.6889 2022/10/07 10:54:44 - mmengine - INFO - Epoch(train) [17][1000/2119] lr: 4.0000e-02 eta: 1 day, 2:29:55 time: 0.3733 data_time: 0.0276 memory: 5826 grad_norm: 2.9089 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.9886 loss: 2.9886 2022/10/07 10:54:50 - mmengine - INFO - Epoch(train) [17][1020/2119] lr: 4.0000e-02 eta: 1 day, 2:29:47 time: 0.3303 data_time: 0.0175 memory: 5826 grad_norm: 2.7860 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8329 loss: 2.8329 2022/10/07 10:54:57 - mmengine - INFO - Epoch(train) [17][1040/2119] lr: 4.0000e-02 eta: 1 day, 2:29:44 time: 0.3605 data_time: 0.0250 memory: 5826 grad_norm: 2.8248 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7187 loss: 2.7187 2022/10/07 10:55:04 - mmengine - INFO - Epoch(train) [17][1060/2119] lr: 4.0000e-02 eta: 1 day, 2:29:33 time: 0.3103 data_time: 0.0221 memory: 5826 grad_norm: 2.8994 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.2062 loss: 3.2062 2022/10/07 10:55:10 - mmengine - INFO - Epoch(train) [17][1080/2119] lr: 4.0000e-02 eta: 1 day, 2:29:26 time: 0.3332 data_time: 0.0243 memory: 5826 grad_norm: 2.8321 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7049 loss: 2.7049 2022/10/07 10:55:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 10:55:17 - mmengine - INFO - Epoch(train) [17][1100/2119] lr: 4.0000e-02 eta: 1 day, 2:29:17 time: 0.3255 data_time: 0.0226 memory: 5826 grad_norm: 2.9016 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8395 loss: 2.8395 2022/10/07 10:55:24 - mmengine - INFO - Epoch(train) [17][1120/2119] lr: 4.0000e-02 eta: 1 day, 2:29:15 time: 0.3654 data_time: 0.0228 memory: 5826 grad_norm: 2.8669 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8473 loss: 2.8473 2022/10/07 10:55:30 - mmengine - INFO - Epoch(train) [17][1140/2119] lr: 4.0000e-02 eta: 1 day, 2:29:03 time: 0.3043 data_time: 0.0225 memory: 5826 grad_norm: 2.8667 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7296 loss: 2.7296 2022/10/07 10:55:37 - mmengine - INFO - Epoch(train) [17][1160/2119] lr: 4.0000e-02 eta: 1 day, 2:28:54 time: 0.3236 data_time: 0.0230 memory: 5826 grad_norm: 2.8816 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5940 loss: 2.5940 2022/10/07 10:55:43 - mmengine - INFO - Epoch(train) [17][1180/2119] lr: 4.0000e-02 eta: 1 day, 2:28:47 time: 0.3335 data_time: 0.0191 memory: 5826 grad_norm: 2.8706 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8784 loss: 2.8784 2022/10/07 10:55:50 - mmengine - INFO - Epoch(train) [17][1200/2119] lr: 4.0000e-02 eta: 1 day, 2:28:38 time: 0.3255 data_time: 0.0229 memory: 5826 grad_norm: 2.8601 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.7098 loss: 2.7098 2022/10/07 10:55:57 - mmengine - INFO - Epoch(train) [17][1220/2119] lr: 4.0000e-02 eta: 1 day, 2:28:36 time: 0.3687 data_time: 0.0268 memory: 5826 grad_norm: 2.8406 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8501 loss: 2.8501 2022/10/07 10:56:04 - mmengine - INFO - Epoch(train) [17][1240/2119] lr: 4.0000e-02 eta: 1 day, 2:28:31 time: 0.3493 data_time: 0.0198 memory: 5826 grad_norm: 2.8977 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6447 loss: 2.6447 2022/10/07 10:56:12 - mmengine - INFO - Epoch(train) [17][1260/2119] lr: 4.0000e-02 eta: 1 day, 2:28:33 time: 0.3889 data_time: 0.0210 memory: 5826 grad_norm: 2.9010 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6727 loss: 2.6727 2022/10/07 10:56:18 - mmengine - INFO - Epoch(train) [17][1280/2119] lr: 4.0000e-02 eta: 1 day, 2:28:19 time: 0.2900 data_time: 0.0238 memory: 5826 grad_norm: 2.8656 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0104 loss: 3.0104 2022/10/07 10:56:24 - mmengine - INFO - Epoch(train) [17][1300/2119] lr: 4.0000e-02 eta: 1 day, 2:28:11 time: 0.3301 data_time: 0.0197 memory: 5826 grad_norm: 2.8978 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8027 loss: 2.8027 2022/10/07 10:56:31 - mmengine - INFO - Epoch(train) [17][1320/2119] lr: 4.0000e-02 eta: 1 day, 2:28:00 time: 0.3119 data_time: 0.0225 memory: 5826 grad_norm: 2.9088 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8706 loss: 2.8706 2022/10/07 10:56:38 - mmengine - INFO - Epoch(train) [17][1340/2119] lr: 4.0000e-02 eta: 1 day, 2:27:55 time: 0.3448 data_time: 0.0199 memory: 5826 grad_norm: 2.8214 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6896 loss: 2.6896 2022/10/07 10:56:44 - mmengine - INFO - Epoch(train) [17][1360/2119] lr: 4.0000e-02 eta: 1 day, 2:27:46 time: 0.3232 data_time: 0.0197 memory: 5826 grad_norm: 2.8537 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6929 loss: 2.6929 2022/10/07 10:56:51 - mmengine - INFO - Epoch(train) [17][1380/2119] lr: 4.0000e-02 eta: 1 day, 2:27:42 time: 0.3578 data_time: 0.0237 memory: 5826 grad_norm: 2.9146 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7638 loss: 2.7638 2022/10/07 10:56:58 - mmengine - INFO - Epoch(train) [17][1400/2119] lr: 4.0000e-02 eta: 1 day, 2:27:40 time: 0.3654 data_time: 0.0258 memory: 5826 grad_norm: 2.8493 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7083 loss: 2.7083 2022/10/07 10:57:05 - mmengine - INFO - Epoch(train) [17][1420/2119] lr: 4.0000e-02 eta: 1 day, 2:27:31 time: 0.3214 data_time: 0.0185 memory: 5826 grad_norm: 2.8982 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0427 loss: 3.0427 2022/10/07 10:57:12 - mmengine - INFO - Epoch(train) [17][1440/2119] lr: 4.0000e-02 eta: 1 day, 2:27:29 time: 0.3701 data_time: 0.0232 memory: 5826 grad_norm: 2.8544 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7574 loss: 2.7574 2022/10/07 10:57:18 - mmengine - INFO - Epoch(train) [17][1460/2119] lr: 4.0000e-02 eta: 1 day, 2:27:17 time: 0.3057 data_time: 0.0206 memory: 5826 grad_norm: 2.9160 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8363 loss: 2.8363 2022/10/07 10:57:26 - mmengine - INFO - Epoch(train) [17][1480/2119] lr: 4.0000e-02 eta: 1 day, 2:27:17 time: 0.3740 data_time: 0.0216 memory: 5826 grad_norm: 2.8485 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7529 loss: 2.7529 2022/10/07 10:57:32 - mmengine - INFO - Epoch(train) [17][1500/2119] lr: 4.0000e-02 eta: 1 day, 2:27:08 time: 0.3238 data_time: 0.0196 memory: 5826 grad_norm: 2.8598 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 3.1188 loss: 3.1188 2022/10/07 10:57:40 - mmengine - INFO - Epoch(train) [17][1520/2119] lr: 4.0000e-02 eta: 1 day, 2:27:11 time: 0.3983 data_time: 0.0222 memory: 5826 grad_norm: 2.8739 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8452 loss: 2.8452 2022/10/07 10:57:47 - mmengine - INFO - Epoch(train) [17][1540/2119] lr: 4.0000e-02 eta: 1 day, 2:27:01 time: 0.3160 data_time: 0.0145 memory: 5826 grad_norm: 2.8478 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7749 loss: 2.7749 2022/10/07 10:57:54 - mmengine - INFO - Epoch(train) [17][1560/2119] lr: 4.0000e-02 eta: 1 day, 2:26:59 time: 0.3724 data_time: 0.0214 memory: 5826 grad_norm: 2.8536 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6463 loss: 2.6463 2022/10/07 10:58:00 - mmengine - INFO - Epoch(train) [17][1580/2119] lr: 4.0000e-02 eta: 1 day, 2:26:46 time: 0.2950 data_time: 0.0226 memory: 5826 grad_norm: 2.9358 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9050 loss: 2.9050 2022/10/07 10:58:07 - mmengine - INFO - Epoch(train) [17][1600/2119] lr: 4.0000e-02 eta: 1 day, 2:26:45 time: 0.3731 data_time: 0.0242 memory: 5826 grad_norm: 2.8650 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8616 loss: 2.8616 2022/10/07 10:58:14 - mmengine - INFO - Epoch(train) [17][1620/2119] lr: 4.0000e-02 eta: 1 day, 2:26:37 time: 0.3279 data_time: 0.0195 memory: 5826 grad_norm: 2.8827 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7488 loss: 2.7488 2022/10/07 10:58:21 - mmengine - INFO - Epoch(train) [17][1640/2119] lr: 4.0000e-02 eta: 1 day, 2:26:33 time: 0.3567 data_time: 0.0194 memory: 5826 grad_norm: 2.8006 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7383 loss: 2.7383 2022/10/07 10:58:28 - mmengine - INFO - Epoch(train) [17][1660/2119] lr: 4.0000e-02 eta: 1 day, 2:26:25 time: 0.3268 data_time: 0.0186 memory: 5826 grad_norm: 2.8616 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8673 loss: 2.8673 2022/10/07 10:58:35 - mmengine - INFO - Epoch(train) [17][1680/2119] lr: 4.0000e-02 eta: 1 day, 2:26:21 time: 0.3571 data_time: 0.0229 memory: 5826 grad_norm: 2.8217 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8443 loss: 2.8443 2022/10/07 10:58:41 - mmengine - INFO - Epoch(train) [17][1700/2119] lr: 4.0000e-02 eta: 1 day, 2:26:12 time: 0.3206 data_time: 0.0172 memory: 5826 grad_norm: 2.9060 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7937 loss: 2.7937 2022/10/07 10:58:49 - mmengine - INFO - Epoch(train) [17][1720/2119] lr: 4.0000e-02 eta: 1 day, 2:26:11 time: 0.3742 data_time: 0.0258 memory: 5826 grad_norm: 2.8865 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0244 loss: 3.0244 2022/10/07 10:58:55 - mmengine - INFO - Epoch(train) [17][1740/2119] lr: 4.0000e-02 eta: 1 day, 2:25:57 time: 0.2912 data_time: 0.0171 memory: 5826 grad_norm: 2.8338 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8939 loss: 2.8939 2022/10/07 10:59:02 - mmengine - INFO - Epoch(train) [17][1760/2119] lr: 4.0000e-02 eta: 1 day, 2:25:53 time: 0.3534 data_time: 0.0257 memory: 5826 grad_norm: 2.8502 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7924 loss: 2.7924 2022/10/07 10:59:08 - mmengine - INFO - Epoch(train) [17][1780/2119] lr: 4.0000e-02 eta: 1 day, 2:25:39 time: 0.2947 data_time: 0.0250 memory: 5826 grad_norm: 2.8744 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9908 loss: 2.9908 2022/10/07 10:59:15 - mmengine - INFO - Epoch(train) [17][1800/2119] lr: 4.0000e-02 eta: 1 day, 2:25:38 time: 0.3747 data_time: 0.0176 memory: 5826 grad_norm: 2.8534 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7945 loss: 2.7945 2022/10/07 10:59:21 - mmengine - INFO - Epoch(train) [17][1820/2119] lr: 4.0000e-02 eta: 1 day, 2:25:29 time: 0.3203 data_time: 0.0169 memory: 5826 grad_norm: 2.8760 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8506 loss: 2.8506 2022/10/07 10:59:30 - mmengine - INFO - Epoch(train) [17][1840/2119] lr: 4.0000e-02 eta: 1 day, 2:25:36 time: 0.4238 data_time: 0.0216 memory: 5826 grad_norm: 2.8665 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7857 loss: 2.7857 2022/10/07 10:59:36 - mmengine - INFO - Epoch(train) [17][1860/2119] lr: 4.0000e-02 eta: 1 day, 2:25:24 time: 0.3070 data_time: 0.0177 memory: 5826 grad_norm: 2.8675 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7431 loss: 2.7431 2022/10/07 10:59:43 - mmengine - INFO - Epoch(train) [17][1880/2119] lr: 4.0000e-02 eta: 1 day, 2:25:17 time: 0.3320 data_time: 0.0235 memory: 5826 grad_norm: 2.8639 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9041 loss: 2.9041 2022/10/07 10:59:49 - mmengine - INFO - Epoch(train) [17][1900/2119] lr: 4.0000e-02 eta: 1 day, 2:25:06 time: 0.3132 data_time: 0.0202 memory: 5826 grad_norm: 2.8626 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8067 loss: 2.8067 2022/10/07 10:59:56 - mmengine - INFO - Epoch(train) [17][1920/2119] lr: 4.0000e-02 eta: 1 day, 2:25:02 time: 0.3528 data_time: 0.0236 memory: 5826 grad_norm: 2.8177 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0190 loss: 3.0190 2022/10/07 11:00:03 - mmengine - INFO - Epoch(train) [17][1940/2119] lr: 4.0000e-02 eta: 1 day, 2:24:56 time: 0.3394 data_time: 0.0226 memory: 5826 grad_norm: 2.8581 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7183 loss: 2.7183 2022/10/07 11:00:09 - mmengine - INFO - Epoch(train) [17][1960/2119] lr: 4.0000e-02 eta: 1 day, 2:24:48 time: 0.3300 data_time: 0.0197 memory: 5826 grad_norm: 2.8858 top1_acc: 0.3750 top5_acc: 0.9375 loss_cls: 2.6801 loss: 2.6801 2022/10/07 11:00:16 - mmengine - INFO - Epoch(train) [17][1980/2119] lr: 4.0000e-02 eta: 1 day, 2:24:37 time: 0.3108 data_time: 0.0194 memory: 5826 grad_norm: 2.8811 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7828 loss: 2.7828 2022/10/07 11:00:23 - mmengine - INFO - Epoch(train) [17][2000/2119] lr: 4.0000e-02 eta: 1 day, 2:24:35 time: 0.3691 data_time: 0.0242 memory: 5826 grad_norm: 2.9088 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8169 loss: 2.8169 2022/10/07 11:00:29 - mmengine - INFO - Epoch(train) [17][2020/2119] lr: 4.0000e-02 eta: 1 day, 2:24:25 time: 0.3147 data_time: 0.0185 memory: 5826 grad_norm: 2.8889 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7943 loss: 2.7943 2022/10/07 11:00:37 - mmengine - INFO - Epoch(train) [17][2040/2119] lr: 4.0000e-02 eta: 1 day, 2:24:22 time: 0.3647 data_time: 0.0232 memory: 5826 grad_norm: 2.9142 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9141 loss: 2.9141 2022/10/07 11:00:43 - mmengine - INFO - Epoch(train) [17][2060/2119] lr: 4.0000e-02 eta: 1 day, 2:24:12 time: 0.3146 data_time: 0.0222 memory: 5826 grad_norm: 2.8741 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7938 loss: 2.7938 2022/10/07 11:00:50 - mmengine - INFO - Epoch(train) [17][2080/2119] lr: 4.0000e-02 eta: 1 day, 2:24:08 time: 0.3551 data_time: 0.0230 memory: 5826 grad_norm: 2.8500 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6353 loss: 2.6353 2022/10/07 11:00:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 11:00:56 - mmengine - INFO - Epoch(train) [17][2100/2119] lr: 4.0000e-02 eta: 1 day, 2:23:55 time: 0.2940 data_time: 0.0234 memory: 5826 grad_norm: 2.8679 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7729 loss: 2.7729 2022/10/07 11:01:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 11:01:02 - mmengine - INFO - Epoch(train) [17][2119/2119] lr: 4.0000e-02 eta: 1 day, 2:23:55 time: 0.2976 data_time: 0.0196 memory: 5826 grad_norm: 2.8484 top1_acc: 0.5000 top5_acc: 0.6000 loss_cls: 2.9222 loss: 2.9222 2022/10/07 11:01:11 - mmengine - INFO - Epoch(train) [18][20/2119] lr: 4.0000e-02 eta: 1 day, 2:23:08 time: 0.4442 data_time: 0.1190 memory: 5826 grad_norm: 2.8384 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.9147 loss: 2.9147 2022/10/07 11:01:17 - mmengine - INFO - Epoch(train) [18][40/2119] lr: 4.0000e-02 eta: 1 day, 2:23:00 time: 0.3253 data_time: 0.0207 memory: 5826 grad_norm: 2.8426 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4794 loss: 2.4794 2022/10/07 11:01:25 - mmengine - INFO - Epoch(train) [18][60/2119] lr: 4.0000e-02 eta: 1 day, 2:23:02 time: 0.3959 data_time: 0.0180 memory: 5826 grad_norm: 2.8915 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7857 loss: 2.7857 2022/10/07 11:01:31 - mmengine - INFO - Epoch(train) [18][80/2119] lr: 4.0000e-02 eta: 1 day, 2:22:50 time: 0.3064 data_time: 0.0258 memory: 5826 grad_norm: 2.9049 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8441 loss: 2.8441 2022/10/07 11:01:37 - mmengine - INFO - Epoch(train) [18][100/2119] lr: 4.0000e-02 eta: 1 day, 2:22:41 time: 0.3171 data_time: 0.0213 memory: 5826 grad_norm: 2.8801 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5854 loss: 2.5854 2022/10/07 11:01:44 - mmengine - INFO - Epoch(train) [18][120/2119] lr: 4.0000e-02 eta: 1 day, 2:22:35 time: 0.3416 data_time: 0.0257 memory: 5826 grad_norm: 2.8784 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8231 loss: 2.8231 2022/10/07 11:01:51 - mmengine - INFO - Epoch(train) [18][140/2119] lr: 4.0000e-02 eta: 1 day, 2:22:31 time: 0.3601 data_time: 0.0234 memory: 5826 grad_norm: 2.8967 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8188 loss: 2.8188 2022/10/07 11:01:58 - mmengine - INFO - Epoch(train) [18][160/2119] lr: 4.0000e-02 eta: 1 day, 2:22:20 time: 0.3055 data_time: 0.0199 memory: 5826 grad_norm: 2.8862 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6193 loss: 2.6193 2022/10/07 11:02:05 - mmengine - INFO - Epoch(train) [18][180/2119] lr: 4.0000e-02 eta: 1 day, 2:22:15 time: 0.3475 data_time: 0.0238 memory: 5826 grad_norm: 2.9148 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7719 loss: 2.7719 2022/10/07 11:02:10 - mmengine - INFO - Epoch(train) [18][200/2119] lr: 4.0000e-02 eta: 1 day, 2:22:01 time: 0.2920 data_time: 0.0213 memory: 5826 grad_norm: 2.8988 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8984 loss: 2.8984 2022/10/07 11:02:17 - mmengine - INFO - Epoch(train) [18][220/2119] lr: 4.0000e-02 eta: 1 day, 2:21:55 time: 0.3411 data_time: 0.0218 memory: 5826 grad_norm: 2.8559 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6884 loss: 2.6884 2022/10/07 11:02:25 - mmengine - INFO - Epoch(train) [18][240/2119] lr: 4.0000e-02 eta: 1 day, 2:21:58 time: 0.4026 data_time: 0.0261 memory: 5826 grad_norm: 2.8579 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5218 loss: 2.5218 2022/10/07 11:02:32 - mmengine - INFO - Epoch(train) [18][260/2119] lr: 4.0000e-02 eta: 1 day, 2:21:48 time: 0.3154 data_time: 0.0189 memory: 5826 grad_norm: 2.8620 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6622 loss: 2.6622 2022/10/07 11:02:38 - mmengine - INFO - Epoch(train) [18][280/2119] lr: 4.0000e-02 eta: 1 day, 2:21:37 time: 0.3090 data_time: 0.0262 memory: 5826 grad_norm: 2.8495 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.3356 loss: 2.3356 2022/10/07 11:02:45 - mmengine - INFO - Epoch(train) [18][300/2119] lr: 4.0000e-02 eta: 1 day, 2:21:32 time: 0.3474 data_time: 0.0164 memory: 5826 grad_norm: 2.8833 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6943 loss: 2.6943 2022/10/07 11:02:58 - mmengine - INFO - Epoch(train) [18][320/2119] lr: 4.0000e-02 eta: 1 day, 2:22:15 time: 0.6591 data_time: 0.2570 memory: 5826 grad_norm: 2.8796 top1_acc: 0.3125 top5_acc: 0.3125 loss_cls: 2.7967 loss: 2.7967 2022/10/07 11:03:03 - mmengine - INFO - Epoch(train) [18][340/2119] lr: 4.0000e-02 eta: 1 day, 2:21:58 time: 0.2698 data_time: 0.0231 memory: 5826 grad_norm: 2.8131 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8094 loss: 2.8094 2022/10/07 11:03:10 - mmengine - INFO - Epoch(train) [18][360/2119] lr: 4.0000e-02 eta: 1 day, 2:21:52 time: 0.3415 data_time: 0.0263 memory: 5826 grad_norm: 2.8512 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8878 loss: 2.8878 2022/10/07 11:03:17 - mmengine - INFO - Epoch(train) [18][380/2119] lr: 4.0000e-02 eta: 1 day, 2:21:48 time: 0.3554 data_time: 0.0252 memory: 5826 grad_norm: 2.9079 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0313 loss: 3.0313 2022/10/07 11:03:25 - mmengine - INFO - Epoch(train) [18][400/2119] lr: 4.0000e-02 eta: 1 day, 2:21:46 time: 0.3684 data_time: 0.0181 memory: 5826 grad_norm: 2.8771 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8079 loss: 2.8079 2022/10/07 11:03:31 - mmengine - INFO - Epoch(train) [18][420/2119] lr: 4.0000e-02 eta: 1 day, 2:21:39 time: 0.3374 data_time: 0.0207 memory: 5826 grad_norm: 2.8944 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7127 loss: 2.7127 2022/10/07 11:03:38 - mmengine - INFO - Epoch(train) [18][440/2119] lr: 4.0000e-02 eta: 1 day, 2:21:31 time: 0.3300 data_time: 0.0336 memory: 5826 grad_norm: 2.8841 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6705 loss: 2.6705 2022/10/07 11:03:45 - mmengine - INFO - Epoch(train) [18][460/2119] lr: 4.0000e-02 eta: 1 day, 2:21:27 time: 0.3530 data_time: 0.0165 memory: 5826 grad_norm: 2.8852 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8310 loss: 2.8310 2022/10/07 11:03:52 - mmengine - INFO - Epoch(train) [18][480/2119] lr: 4.0000e-02 eta: 1 day, 2:21:20 time: 0.3377 data_time: 0.0172 memory: 5826 grad_norm: 2.8891 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7939 loss: 2.7939 2022/10/07 11:03:58 - mmengine - INFO - Epoch(train) [18][500/2119] lr: 4.0000e-02 eta: 1 day, 2:21:08 time: 0.2989 data_time: 0.0262 memory: 5826 grad_norm: 2.8876 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8184 loss: 2.8184 2022/10/07 11:04:05 - mmengine - INFO - Epoch(train) [18][520/2119] lr: 4.0000e-02 eta: 1 day, 2:21:06 time: 0.3728 data_time: 0.0222 memory: 5826 grad_norm: 2.9319 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7219 loss: 2.7219 2022/10/07 11:04:12 - mmengine - INFO - Epoch(train) [18][540/2119] lr: 4.0000e-02 eta: 1 day, 2:20:57 time: 0.3194 data_time: 0.0270 memory: 5826 grad_norm: 2.9012 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6559 loss: 2.6559 2022/10/07 11:04:18 - mmengine - INFO - Epoch(train) [18][560/2119] lr: 4.0000e-02 eta: 1 day, 2:20:48 time: 0.3258 data_time: 0.0207 memory: 5826 grad_norm: 2.8994 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6767 loss: 2.6767 2022/10/07 11:04:25 - mmengine - INFO - Epoch(train) [18][580/2119] lr: 4.0000e-02 eta: 1 day, 2:20:44 time: 0.3501 data_time: 0.0234 memory: 5826 grad_norm: 2.8632 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8057 loss: 2.8057 2022/10/07 11:04:32 - mmengine - INFO - Epoch(train) [18][600/2119] lr: 4.0000e-02 eta: 1 day, 2:20:36 time: 0.3347 data_time: 0.0204 memory: 5826 grad_norm: 2.9165 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8247 loss: 2.8247 2022/10/07 11:04:38 - mmengine - INFO - Epoch(train) [18][620/2119] lr: 4.0000e-02 eta: 1 day, 2:20:25 time: 0.3076 data_time: 0.0181 memory: 5826 grad_norm: 2.8434 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7557 loss: 2.7557 2022/10/07 11:04:46 - mmengine - INFO - Epoch(train) [18][640/2119] lr: 4.0000e-02 eta: 1 day, 2:20:26 time: 0.3859 data_time: 0.0246 memory: 5826 grad_norm: 2.9040 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6697 loss: 2.6697 2022/10/07 11:04:52 - mmengine - INFO - Epoch(train) [18][660/2119] lr: 4.0000e-02 eta: 1 day, 2:20:13 time: 0.2988 data_time: 0.0176 memory: 5826 grad_norm: 2.9325 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0160 loss: 3.0160 2022/10/07 11:05:00 - mmengine - INFO - Epoch(train) [18][680/2119] lr: 4.0000e-02 eta: 1 day, 2:20:19 time: 0.4195 data_time: 0.1528 memory: 5826 grad_norm: 2.8528 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7590 loss: 2.7590 2022/10/07 11:05:05 - mmengine - INFO - Epoch(train) [18][700/2119] lr: 4.0000e-02 eta: 1 day, 2:20:00 time: 0.2548 data_time: 0.0158 memory: 5826 grad_norm: 2.8320 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6839 loss: 2.6839 2022/10/07 11:05:13 - mmengine - INFO - Epoch(train) [18][720/2119] lr: 4.0000e-02 eta: 1 day, 2:19:58 time: 0.3698 data_time: 0.1251 memory: 5826 grad_norm: 2.8348 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6481 loss: 2.6481 2022/10/07 11:05:18 - mmengine - INFO - Epoch(train) [18][740/2119] lr: 4.0000e-02 eta: 1 day, 2:19:44 time: 0.2923 data_time: 0.0457 memory: 5826 grad_norm: 2.8655 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7180 loss: 2.7180 2022/10/07 11:05:26 - mmengine - INFO - Epoch(train) [18][760/2119] lr: 4.0000e-02 eta: 1 day, 2:19:47 time: 0.3966 data_time: 0.0370 memory: 5826 grad_norm: 2.8843 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7424 loss: 2.7424 2022/10/07 11:05:32 - mmengine - INFO - Epoch(train) [18][780/2119] lr: 4.0000e-02 eta: 1 day, 2:19:34 time: 0.2990 data_time: 0.0165 memory: 5826 grad_norm: 2.8665 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8619 loss: 2.8619 2022/10/07 11:05:39 - mmengine - INFO - Epoch(train) [18][800/2119] lr: 4.0000e-02 eta: 1 day, 2:19:30 time: 0.3532 data_time: 0.0232 memory: 5826 grad_norm: 2.9324 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6059 loss: 2.6059 2022/10/07 11:05:46 - mmengine - INFO - Epoch(train) [18][820/2119] lr: 4.0000e-02 eta: 1 day, 2:19:21 time: 0.3211 data_time: 0.0199 memory: 5826 grad_norm: 2.8972 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9215 loss: 2.9215 2022/10/07 11:05:53 - mmengine - INFO - Epoch(train) [18][840/2119] lr: 4.0000e-02 eta: 1 day, 2:19:15 time: 0.3433 data_time: 0.0225 memory: 5826 grad_norm: 2.9062 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7919 loss: 2.7919 2022/10/07 11:06:00 - mmengine - INFO - Epoch(train) [18][860/2119] lr: 4.0000e-02 eta: 1 day, 2:19:12 time: 0.3628 data_time: 0.0184 memory: 5826 grad_norm: 2.8329 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7728 loss: 2.7728 2022/10/07 11:06:08 - mmengine - INFO - Epoch(train) [18][880/2119] lr: 4.0000e-02 eta: 1 day, 2:19:15 time: 0.4009 data_time: 0.0182 memory: 5826 grad_norm: 2.9409 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9977 loss: 2.9977 2022/10/07 11:06:15 - mmengine - INFO - Epoch(train) [18][900/2119] lr: 4.0000e-02 eta: 1 day, 2:19:11 time: 0.3538 data_time: 0.0262 memory: 5826 grad_norm: 2.8257 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6672 loss: 2.6672 2022/10/07 11:06:23 - mmengine - INFO - Epoch(train) [18][920/2119] lr: 4.0000e-02 eta: 1 day, 2:19:13 time: 0.3954 data_time: 0.0168 memory: 5826 grad_norm: 2.9338 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8192 loss: 2.8192 2022/10/07 11:06:29 - mmengine - INFO - Epoch(train) [18][940/2119] lr: 4.0000e-02 eta: 1 day, 2:19:02 time: 0.3099 data_time: 0.0268 memory: 5826 grad_norm: 2.9716 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6185 loss: 2.6185 2022/10/07 11:06:36 - mmengine - INFO - Epoch(train) [18][960/2119] lr: 4.0000e-02 eta: 1 day, 2:18:55 time: 0.3346 data_time: 0.0246 memory: 5826 grad_norm: 2.8675 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5387 loss: 2.5387 2022/10/07 11:06:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 11:06:43 - mmengine - INFO - Epoch(train) [18][980/2119] lr: 4.0000e-02 eta: 1 day, 2:18:51 time: 0.3559 data_time: 0.0282 memory: 5826 grad_norm: 2.8468 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6596 loss: 2.6596 2022/10/07 11:06:50 - mmengine - INFO - Epoch(train) [18][1000/2119] lr: 4.0000e-02 eta: 1 day, 2:18:48 time: 0.3635 data_time: 0.0212 memory: 5826 grad_norm: 2.8357 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8549 loss: 2.8549 2022/10/07 11:07:05 - mmengine - INFO - Epoch(train) [18][1020/2119] lr: 4.0000e-02 eta: 1 day, 2:19:46 time: 0.7625 data_time: 0.4980 memory: 5826 grad_norm: 2.8925 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9053 loss: 2.9053 2022/10/07 11:07:12 - mmengine - INFO - Epoch(train) [18][1040/2119] lr: 4.0000e-02 eta: 1 day, 2:19:38 time: 0.3306 data_time: 0.0328 memory: 5826 grad_norm: 2.8505 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8682 loss: 2.8682 2022/10/07 11:07:19 - mmengine - INFO - Epoch(train) [18][1060/2119] lr: 4.0000e-02 eta: 1 day, 2:19:33 time: 0.3517 data_time: 0.0192 memory: 5826 grad_norm: 2.8352 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7475 loss: 2.7475 2022/10/07 11:07:26 - mmengine - INFO - Epoch(train) [18][1080/2119] lr: 4.0000e-02 eta: 1 day, 2:19:29 time: 0.3531 data_time: 0.0214 memory: 5826 grad_norm: 2.8516 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8580 loss: 2.8580 2022/10/07 11:07:32 - mmengine - INFO - Epoch(train) [18][1100/2119] lr: 4.0000e-02 eta: 1 day, 2:19:17 time: 0.3022 data_time: 0.0238 memory: 5826 grad_norm: 2.8579 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8729 loss: 2.8729 2022/10/07 11:07:40 - mmengine - INFO - Epoch(train) [18][1120/2119] lr: 4.0000e-02 eta: 1 day, 2:19:21 time: 0.4113 data_time: 0.0176 memory: 5826 grad_norm: 2.8789 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7632 loss: 2.7632 2022/10/07 11:07:46 - mmengine - INFO - Epoch(train) [18][1140/2119] lr: 4.0000e-02 eta: 1 day, 2:19:09 time: 0.3019 data_time: 0.0180 memory: 5826 grad_norm: 2.8648 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7003 loss: 2.7003 2022/10/07 11:07:54 - mmengine - INFO - Epoch(train) [18][1160/2119] lr: 4.0000e-02 eta: 1 day, 2:19:05 time: 0.3526 data_time: 0.0220 memory: 5826 grad_norm: 2.8707 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9823 loss: 2.9823 2022/10/07 11:08:01 - mmengine - INFO - Epoch(train) [18][1180/2119] lr: 4.0000e-02 eta: 1 day, 2:19:00 time: 0.3527 data_time: 0.0190 memory: 5826 grad_norm: 2.8689 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7445 loss: 2.7445 2022/10/07 11:08:08 - mmengine - INFO - Epoch(train) [18][1200/2119] lr: 4.0000e-02 eta: 1 day, 2:18:58 time: 0.3681 data_time: 0.0205 memory: 5826 grad_norm: 2.9075 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7694 loss: 2.7694 2022/10/07 11:08:15 - mmengine - INFO - Epoch(train) [18][1220/2119] lr: 4.0000e-02 eta: 1 day, 2:18:51 time: 0.3336 data_time: 0.0208 memory: 5826 grad_norm: 2.8435 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8251 loss: 2.8251 2022/10/07 11:08:22 - mmengine - INFO - Epoch(train) [18][1240/2119] lr: 4.0000e-02 eta: 1 day, 2:18:52 time: 0.3923 data_time: 0.0202 memory: 5826 grad_norm: 2.8958 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7616 loss: 2.7616 2022/10/07 11:08:29 - mmengine - INFO - Epoch(train) [18][1260/2119] lr: 4.0000e-02 eta: 1 day, 2:18:41 time: 0.3056 data_time: 0.0268 memory: 5826 grad_norm: 2.8649 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7728 loss: 2.7728 2022/10/07 11:08:35 - mmengine - INFO - Epoch(train) [18][1280/2119] lr: 4.0000e-02 eta: 1 day, 2:18:32 time: 0.3249 data_time: 0.0238 memory: 5826 grad_norm: 2.8752 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9054 loss: 2.9054 2022/10/07 11:08:42 - mmengine - INFO - Epoch(train) [18][1300/2119] lr: 4.0000e-02 eta: 1 day, 2:18:24 time: 0.3272 data_time: 0.0246 memory: 5826 grad_norm: 2.8340 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6690 loss: 2.6690 2022/10/07 11:08:49 - mmengine - INFO - Epoch(train) [18][1320/2119] lr: 4.0000e-02 eta: 1 day, 2:18:19 time: 0.3520 data_time: 0.0198 memory: 5826 grad_norm: 2.9111 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.0260 loss: 3.0260 2022/10/07 11:08:55 - mmengine - INFO - Epoch(train) [18][1340/2119] lr: 4.0000e-02 eta: 1 day, 2:18:13 time: 0.3398 data_time: 0.0239 memory: 5826 grad_norm: 2.8974 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8110 loss: 2.8110 2022/10/07 11:09:02 - mmengine - INFO - Epoch(train) [18][1360/2119] lr: 4.0000e-02 eta: 1 day, 2:18:07 time: 0.3478 data_time: 0.0267 memory: 5826 grad_norm: 2.9173 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7937 loss: 2.7937 2022/10/07 11:09:09 - mmengine - INFO - Epoch(train) [18][1380/2119] lr: 4.0000e-02 eta: 1 day, 2:17:58 time: 0.3177 data_time: 0.0189 memory: 5826 grad_norm: 2.8709 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6970 loss: 2.6970 2022/10/07 11:09:15 - mmengine - INFO - Epoch(train) [18][1400/2119] lr: 4.0000e-02 eta: 1 day, 2:17:47 time: 0.3132 data_time: 0.0248 memory: 5826 grad_norm: 2.9052 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8120 loss: 2.8120 2022/10/07 11:09:22 - mmengine - INFO - Epoch(train) [18][1420/2119] lr: 4.0000e-02 eta: 1 day, 2:17:40 time: 0.3329 data_time: 0.0224 memory: 5826 grad_norm: 2.8464 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0415 loss: 3.0415 2022/10/07 11:09:29 - mmengine - INFO - Epoch(train) [18][1440/2119] lr: 4.0000e-02 eta: 1 day, 2:17:35 time: 0.3533 data_time: 0.0214 memory: 5826 grad_norm: 2.8752 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7613 loss: 2.7613 2022/10/07 11:09:35 - mmengine - INFO - Epoch(train) [18][1460/2119] lr: 4.0000e-02 eta: 1 day, 2:17:25 time: 0.3131 data_time: 0.0269 memory: 5826 grad_norm: 2.8892 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0053 loss: 3.0053 2022/10/07 11:09:43 - mmengine - INFO - Epoch(train) [18][1480/2119] lr: 4.0000e-02 eta: 1 day, 2:17:26 time: 0.3890 data_time: 0.0203 memory: 5826 grad_norm: 2.8293 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7050 loss: 2.7050 2022/10/07 11:09:48 - mmengine - INFO - Epoch(train) [18][1500/2119] lr: 4.0000e-02 eta: 1 day, 2:17:11 time: 0.2833 data_time: 0.0276 memory: 5826 grad_norm: 2.8626 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6912 loss: 2.6912 2022/10/07 11:09:55 - mmengine - INFO - Epoch(train) [18][1520/2119] lr: 4.0000e-02 eta: 1 day, 2:17:06 time: 0.3507 data_time: 0.0215 memory: 5826 grad_norm: 2.8734 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7207 loss: 2.7207 2022/10/07 11:10:02 - mmengine - INFO - Epoch(train) [18][1540/2119] lr: 4.0000e-02 eta: 1 day, 2:16:57 time: 0.3234 data_time: 0.0184 memory: 5826 grad_norm: 2.8857 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6837 loss: 2.6837 2022/10/07 11:10:09 - mmengine - INFO - Epoch(train) [18][1560/2119] lr: 4.0000e-02 eta: 1 day, 2:16:54 time: 0.3618 data_time: 0.0243 memory: 5826 grad_norm: 2.8851 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0201 loss: 3.0201 2022/10/07 11:10:16 - mmengine - INFO - Epoch(train) [18][1580/2119] lr: 4.0000e-02 eta: 1 day, 2:16:46 time: 0.3271 data_time: 0.0228 memory: 5826 grad_norm: 2.8912 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8449 loss: 2.8449 2022/10/07 11:10:23 - mmengine - INFO - Epoch(train) [18][1600/2119] lr: 4.0000e-02 eta: 1 day, 2:16:42 time: 0.3567 data_time: 0.0202 memory: 5826 grad_norm: 2.8887 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9174 loss: 2.9174 2022/10/07 11:10:30 - mmengine - INFO - Epoch(train) [18][1620/2119] lr: 4.0000e-02 eta: 1 day, 2:16:40 time: 0.3727 data_time: 0.0215 memory: 5826 grad_norm: 2.8461 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8362 loss: 2.8362 2022/10/07 11:10:37 - mmengine - INFO - Epoch(train) [18][1640/2119] lr: 4.0000e-02 eta: 1 day, 2:16:32 time: 0.3230 data_time: 0.0224 memory: 5826 grad_norm: 2.8326 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6134 loss: 2.6134 2022/10/07 11:10:44 - mmengine - INFO - Epoch(train) [18][1660/2119] lr: 4.0000e-02 eta: 1 day, 2:16:25 time: 0.3391 data_time: 0.0194 memory: 5826 grad_norm: 2.8946 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8510 loss: 2.8510 2022/10/07 11:10:51 - mmengine - INFO - Epoch(train) [18][1680/2119] lr: 4.0000e-02 eta: 1 day, 2:16:21 time: 0.3591 data_time: 0.0344 memory: 5826 grad_norm: 2.8753 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6178 loss: 2.6178 2022/10/07 11:10:57 - mmengine - INFO - Epoch(train) [18][1700/2119] lr: 4.0000e-02 eta: 1 day, 2:16:09 time: 0.3004 data_time: 0.0202 memory: 5826 grad_norm: 2.8767 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7820 loss: 2.7820 2022/10/07 11:11:05 - mmengine - INFO - Epoch(train) [18][1720/2119] lr: 4.0000e-02 eta: 1 day, 2:16:10 time: 0.3916 data_time: 0.0203 memory: 5826 grad_norm: 2.8533 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5005 loss: 2.5005 2022/10/07 11:11:11 - mmengine - INFO - Epoch(train) [18][1740/2119] lr: 4.0000e-02 eta: 1 day, 2:16:02 time: 0.3238 data_time: 0.0208 memory: 5826 grad_norm: 2.8783 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7758 loss: 2.7758 2022/10/07 11:11:18 - mmengine - INFO - Epoch(train) [18][1760/2119] lr: 4.0000e-02 eta: 1 day, 2:15:58 time: 0.3610 data_time: 0.0262 memory: 5826 grad_norm: 2.9141 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7036 loss: 2.7036 2022/10/07 11:11:34 - mmengine - INFO - Epoch(train) [18][1780/2119] lr: 4.0000e-02 eta: 1 day, 2:16:59 time: 0.7890 data_time: 0.5241 memory: 5826 grad_norm: 2.9155 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7057 loss: 2.7057 2022/10/07 11:11:41 - mmengine - INFO - Epoch(train) [18][1800/2119] lr: 4.0000e-02 eta: 1 day, 2:16:49 time: 0.3216 data_time: 0.0335 memory: 5826 grad_norm: 2.8257 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7100 loss: 2.7100 2022/10/07 11:11:47 - mmengine - INFO - Epoch(train) [18][1820/2119] lr: 4.0000e-02 eta: 1 day, 2:16:42 time: 0.3351 data_time: 0.0197 memory: 5826 grad_norm: 2.9058 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7017 loss: 2.7017 2022/10/07 11:11:54 - mmengine - INFO - Epoch(train) [18][1840/2119] lr: 4.0000e-02 eta: 1 day, 2:16:37 time: 0.3454 data_time: 0.0272 memory: 5826 grad_norm: 2.8469 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7752 loss: 2.7752 2022/10/07 11:12:02 - mmengine - INFO - Epoch(train) [18][1860/2119] lr: 4.0000e-02 eta: 1 day, 2:16:36 time: 0.3809 data_time: 0.0210 memory: 5826 grad_norm: 2.9023 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8351 loss: 2.8351 2022/10/07 11:12:08 - mmengine - INFO - Epoch(train) [18][1880/2119] lr: 4.0000e-02 eta: 1 day, 2:16:28 time: 0.3306 data_time: 0.0256 memory: 5826 grad_norm: 2.8657 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9827 loss: 2.9827 2022/10/07 11:12:15 - mmengine - INFO - Epoch(train) [18][1900/2119] lr: 4.0000e-02 eta: 1 day, 2:16:21 time: 0.3337 data_time: 0.0262 memory: 5826 grad_norm: 2.8513 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7306 loss: 2.7306 2022/10/07 11:12:22 - mmengine - INFO - Epoch(train) [18][1920/2119] lr: 4.0000e-02 eta: 1 day, 2:16:17 time: 0.3540 data_time: 0.0234 memory: 5826 grad_norm: 2.9194 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.6255 loss: 2.6255 2022/10/07 11:12:29 - mmengine - INFO - Epoch(train) [18][1940/2119] lr: 4.0000e-02 eta: 1 day, 2:16:09 time: 0.3312 data_time: 0.0198 memory: 5826 grad_norm: 2.9032 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7451 loss: 2.7451 2022/10/07 11:12:35 - mmengine - INFO - Epoch(train) [18][1960/2119] lr: 4.0000e-02 eta: 1 day, 2:15:59 time: 0.3142 data_time: 0.0221 memory: 5826 grad_norm: 2.9027 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7584 loss: 2.7584 2022/10/07 11:12:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 11:12:42 - mmengine - INFO - Epoch(train) [18][1980/2119] lr: 4.0000e-02 eta: 1 day, 2:15:56 time: 0.3661 data_time: 0.0229 memory: 5826 grad_norm: 2.8368 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8086 loss: 2.8086 2022/10/07 11:12:49 - mmengine - INFO - Epoch(train) [18][2000/2119] lr: 4.0000e-02 eta: 1 day, 2:15:49 time: 0.3337 data_time: 0.0259 memory: 5826 grad_norm: 2.8627 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7088 loss: 2.7088 2022/10/07 11:12:55 - mmengine - INFO - Epoch(train) [18][2020/2119] lr: 4.0000e-02 eta: 1 day, 2:15:34 time: 0.2839 data_time: 0.0221 memory: 5826 grad_norm: 2.8871 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7219 loss: 2.7219 2022/10/07 11:13:02 - mmengine - INFO - Epoch(train) [18][2040/2119] lr: 4.0000e-02 eta: 1 day, 2:15:33 time: 0.3745 data_time: 0.0290 memory: 5826 grad_norm: 2.9013 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0388 loss: 3.0388 2022/10/07 11:13:09 - mmengine - INFO - Epoch(train) [18][2060/2119] lr: 4.0000e-02 eta: 1 day, 2:15:23 time: 0.3177 data_time: 0.0216 memory: 5826 grad_norm: 2.8300 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9738 loss: 2.9738 2022/10/07 11:13:16 - mmengine - INFO - Epoch(train) [18][2080/2119] lr: 4.0000e-02 eta: 1 day, 2:15:18 time: 0.3496 data_time: 0.0272 memory: 5826 grad_norm: 2.8219 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8405 loss: 2.8405 2022/10/07 11:13:22 - mmengine - INFO - Epoch(train) [18][2100/2119] lr: 4.0000e-02 eta: 1 day, 2:15:09 time: 0.3274 data_time: 0.0165 memory: 5826 grad_norm: 2.9058 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7844 loss: 2.7844 2022/10/07 11:13:28 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 11:13:28 - mmengine - INFO - Epoch(train) [18][2119/2119] lr: 4.0000e-02 eta: 1 day, 2:15:09 time: 0.3279 data_time: 0.0177 memory: 5826 grad_norm: 2.9127 top1_acc: 0.5000 top5_acc: 0.7000 loss_cls: 2.9238 loss: 2.9238 2022/10/07 11:13:38 - mmengine - INFO - Epoch(train) [19][20/2119] lr: 4.0000e-02 eta: 1 day, 2:14:30 time: 0.4807 data_time: 0.1424 memory: 5826 grad_norm: 2.8916 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9335 loss: 2.9335 2022/10/07 11:13:44 - mmengine - INFO - Epoch(train) [19][40/2119] lr: 4.0000e-02 eta: 1 day, 2:14:17 time: 0.2955 data_time: 0.0210 memory: 5826 grad_norm: 2.8712 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6288 loss: 2.6288 2022/10/07 11:13:52 - mmengine - INFO - Epoch(train) [19][60/2119] lr: 4.0000e-02 eta: 1 day, 2:14:22 time: 0.4134 data_time: 0.0311 memory: 5826 grad_norm: 2.8338 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7745 loss: 2.7745 2022/10/07 11:13:58 - mmengine - INFO - Epoch(train) [19][80/2119] lr: 4.0000e-02 eta: 1 day, 2:14:09 time: 0.2985 data_time: 0.0294 memory: 5826 grad_norm: 2.8984 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8954 loss: 2.8954 2022/10/07 11:14:05 - mmengine - INFO - Epoch(train) [19][100/2119] lr: 4.0000e-02 eta: 1 day, 2:14:06 time: 0.3604 data_time: 0.0252 memory: 5826 grad_norm: 2.8794 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5344 loss: 2.5344 2022/10/07 11:14:18 - mmengine - INFO - Epoch(train) [19][120/2119] lr: 4.0000e-02 eta: 1 day, 2:14:40 time: 0.6223 data_time: 0.2566 memory: 5826 grad_norm: 2.9162 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5497 loss: 2.5497 2022/10/07 11:14:23 - mmengine - INFO - Epoch(train) [19][140/2119] lr: 4.0000e-02 eta: 1 day, 2:14:24 time: 0.2721 data_time: 0.0217 memory: 5826 grad_norm: 2.8764 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6200 loss: 2.6200 2022/10/07 11:14:31 - mmengine - INFO - Epoch(train) [19][160/2119] lr: 4.0000e-02 eta: 1 day, 2:14:23 time: 0.3738 data_time: 0.0267 memory: 5826 grad_norm: 2.8352 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8279 loss: 2.8279 2022/10/07 11:14:37 - mmengine - INFO - Epoch(train) [19][180/2119] lr: 4.0000e-02 eta: 1 day, 2:14:10 time: 0.2966 data_time: 0.0190 memory: 5826 grad_norm: 2.8681 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6445 loss: 2.6445 2022/10/07 11:14:44 - mmengine - INFO - Epoch(train) [19][200/2119] lr: 4.0000e-02 eta: 1 day, 2:14:07 time: 0.3684 data_time: 0.0197 memory: 5826 grad_norm: 2.8371 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7516 loss: 2.7516 2022/10/07 11:14:51 - mmengine - INFO - Epoch(train) [19][220/2119] lr: 4.0000e-02 eta: 1 day, 2:14:01 time: 0.3378 data_time: 0.0340 memory: 5826 grad_norm: 2.9056 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6989 loss: 2.6989 2022/10/07 11:14:58 - mmengine - INFO - Epoch(train) [19][240/2119] lr: 4.0000e-02 eta: 1 day, 2:13:56 time: 0.3496 data_time: 0.0208 memory: 5826 grad_norm: 2.8705 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8066 loss: 2.8066 2022/10/07 11:15:05 - mmengine - INFO - Epoch(train) [19][260/2119] lr: 4.0000e-02 eta: 1 day, 2:13:49 time: 0.3363 data_time: 0.0220 memory: 5826 grad_norm: 2.8845 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7498 loss: 2.7498 2022/10/07 11:15:12 - mmengine - INFO - Epoch(train) [19][280/2119] lr: 4.0000e-02 eta: 1 day, 2:13:46 time: 0.3649 data_time: 0.0190 memory: 5826 grad_norm: 2.9202 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.5680 loss: 2.5680 2022/10/07 11:15:18 - mmengine - INFO - Epoch(train) [19][300/2119] lr: 4.0000e-02 eta: 1 day, 2:13:35 time: 0.3124 data_time: 0.0249 memory: 5826 grad_norm: 2.9106 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.6232 loss: 2.6232 2022/10/07 11:15:25 - mmengine - INFO - Epoch(train) [19][320/2119] lr: 4.0000e-02 eta: 1 day, 2:13:29 time: 0.3427 data_time: 0.0205 memory: 5826 grad_norm: 2.9026 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.6112 loss: 2.6112 2022/10/07 11:15:32 - mmengine - INFO - Epoch(train) [19][340/2119] lr: 4.0000e-02 eta: 1 day, 2:13:26 time: 0.3589 data_time: 0.0249 memory: 5826 grad_norm: 2.9281 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9487 loss: 2.9487 2022/10/07 11:15:40 - mmengine - INFO - Epoch(train) [19][360/2119] lr: 4.0000e-02 eta: 1 day, 2:13:24 time: 0.3746 data_time: 0.0221 memory: 5826 grad_norm: 2.8570 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9166 loss: 2.9166 2022/10/07 11:15:46 - mmengine - INFO - Epoch(train) [19][380/2119] lr: 4.0000e-02 eta: 1 day, 2:13:16 time: 0.3273 data_time: 0.0262 memory: 5826 grad_norm: 2.7980 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9093 loss: 2.9093 2022/10/07 11:15:54 - mmengine - INFO - Epoch(train) [19][400/2119] lr: 4.0000e-02 eta: 1 day, 2:13:15 time: 0.3791 data_time: 0.0197 memory: 5826 grad_norm: 2.8786 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8967 loss: 2.8967 2022/10/07 11:16:00 - mmengine - INFO - Epoch(train) [19][420/2119] lr: 4.0000e-02 eta: 1 day, 2:13:06 time: 0.3252 data_time: 0.0234 memory: 5826 grad_norm: 2.9044 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7681 loss: 2.7681 2022/10/07 11:16:07 - mmengine - INFO - Epoch(train) [19][440/2119] lr: 4.0000e-02 eta: 1 day, 2:13:00 time: 0.3439 data_time: 0.0215 memory: 5826 grad_norm: 2.8795 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9204 loss: 2.9204 2022/10/07 11:16:14 - mmengine - INFO - Epoch(train) [19][460/2119] lr: 4.0000e-02 eta: 1 day, 2:12:57 time: 0.3627 data_time: 0.0160 memory: 5826 grad_norm: 2.8599 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7133 loss: 2.7133 2022/10/07 11:16:22 - mmengine - INFO - Epoch(train) [19][480/2119] lr: 4.0000e-02 eta: 1 day, 2:12:54 time: 0.3649 data_time: 0.0209 memory: 5826 grad_norm: 2.8727 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6184 loss: 2.6184 2022/10/07 11:16:28 - mmengine - INFO - Epoch(train) [19][500/2119] lr: 4.0000e-02 eta: 1 day, 2:12:41 time: 0.2932 data_time: 0.0179 memory: 5826 grad_norm: 2.8506 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6537 loss: 2.6537 2022/10/07 11:16:35 - mmengine - INFO - Epoch(train) [19][520/2119] lr: 4.0000e-02 eta: 1 day, 2:12:40 time: 0.3734 data_time: 0.0210 memory: 5826 grad_norm: 2.8469 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6557 loss: 2.6557 2022/10/07 11:16:41 - mmengine - INFO - Epoch(train) [19][540/2119] lr: 4.0000e-02 eta: 1 day, 2:12:28 time: 0.3079 data_time: 0.0213 memory: 5826 grad_norm: 2.9264 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6356 loss: 2.6356 2022/10/07 11:16:48 - mmengine - INFO - Epoch(train) [19][560/2119] lr: 4.0000e-02 eta: 1 day, 2:12:23 time: 0.3463 data_time: 0.0192 memory: 5826 grad_norm: 2.8986 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6931 loss: 2.6931 2022/10/07 11:16:55 - mmengine - INFO - Epoch(train) [19][580/2119] lr: 4.0000e-02 eta: 1 day, 2:12:18 time: 0.3496 data_time: 0.0224 memory: 5826 grad_norm: 2.8796 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.9310 loss: 2.9310 2022/10/07 11:17:02 - mmengine - INFO - Epoch(train) [19][600/2119] lr: 4.0000e-02 eta: 1 day, 2:12:09 time: 0.3207 data_time: 0.0308 memory: 5826 grad_norm: 2.8484 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7171 loss: 2.7171 2022/10/07 11:17:09 - mmengine - INFO - Epoch(train) [19][620/2119] lr: 4.0000e-02 eta: 1 day, 2:12:06 time: 0.3669 data_time: 0.0205 memory: 5826 grad_norm: 2.8897 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8738 loss: 2.8738 2022/10/07 11:17:16 - mmengine - INFO - Epoch(train) [19][640/2119] lr: 4.0000e-02 eta: 1 day, 2:11:59 time: 0.3383 data_time: 0.0234 memory: 5826 grad_norm: 2.8615 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5721 loss: 2.5721 2022/10/07 11:17:22 - mmengine - INFO - Epoch(train) [19][660/2119] lr: 4.0000e-02 eta: 1 day, 2:11:51 time: 0.3298 data_time: 0.0235 memory: 5826 grad_norm: 2.8782 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8027 loss: 2.8027 2022/10/07 11:17:29 - mmengine - INFO - Epoch(train) [19][680/2119] lr: 4.0000e-02 eta: 1 day, 2:11:46 time: 0.3505 data_time: 0.0235 memory: 5826 grad_norm: 2.9119 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7101 loss: 2.7101 2022/10/07 11:17:35 - mmengine - INFO - Epoch(train) [19][700/2119] lr: 4.0000e-02 eta: 1 day, 2:11:35 time: 0.3079 data_time: 0.0181 memory: 5826 grad_norm: 2.8933 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.4287 loss: 2.4287 2022/10/07 11:17:43 - mmengine - INFO - Epoch(train) [19][720/2119] lr: 4.0000e-02 eta: 1 day, 2:11:36 time: 0.3897 data_time: 0.0169 memory: 5826 grad_norm: 2.8526 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.7138 loss: 2.7138 2022/10/07 11:17:49 - mmengine - INFO - Epoch(train) [19][740/2119] lr: 4.0000e-02 eta: 1 day, 2:11:23 time: 0.2976 data_time: 0.0198 memory: 5826 grad_norm: 2.9326 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7587 loss: 2.7587 2022/10/07 11:17:57 - mmengine - INFO - Epoch(train) [19][760/2119] lr: 4.0000e-02 eta: 1 day, 2:11:22 time: 0.3761 data_time: 0.0227 memory: 5826 grad_norm: 2.8989 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7025 loss: 2.7025 2022/10/07 11:18:03 - mmengine - INFO - Epoch(train) [19][780/2119] lr: 4.0000e-02 eta: 1 day, 2:11:14 time: 0.3259 data_time: 0.0203 memory: 5826 grad_norm: 2.8612 top1_acc: 0.2500 top5_acc: 0.8125 loss_cls: 2.8907 loss: 2.8907 2022/10/07 11:18:11 - mmengine - INFO - Epoch(train) [19][800/2119] lr: 4.0000e-02 eta: 1 day, 2:11:13 time: 0.3829 data_time: 0.0270 memory: 5826 grad_norm: 2.8798 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8688 loss: 2.8688 2022/10/07 11:18:17 - mmengine - INFO - Epoch(train) [19][820/2119] lr: 4.0000e-02 eta: 1 day, 2:11:05 time: 0.3291 data_time: 0.0183 memory: 5826 grad_norm: 2.8685 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5446 loss: 2.5446 2022/10/07 11:18:25 - mmengine - INFO - Epoch(train) [19][840/2119] lr: 4.0000e-02 eta: 1 day, 2:11:03 time: 0.3690 data_time: 0.0187 memory: 5826 grad_norm: 2.8426 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0443 loss: 3.0443 2022/10/07 11:18:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 11:18:32 - mmengine - INFO - Epoch(train) [19][860/2119] lr: 4.0000e-02 eta: 1 day, 2:10:56 time: 0.3361 data_time: 0.0247 memory: 5826 grad_norm: 2.8200 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6452 loss: 2.6452 2022/10/07 11:18:39 - mmengine - INFO - Epoch(train) [19][880/2119] lr: 4.0000e-02 eta: 1 day, 2:10:53 time: 0.3650 data_time: 0.0205 memory: 5826 grad_norm: 2.8777 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7415 loss: 2.7415 2022/10/07 11:18:45 - mmengine - INFO - Epoch(train) [19][900/2119] lr: 4.0000e-02 eta: 1 day, 2:10:42 time: 0.3083 data_time: 0.0251 memory: 5826 grad_norm: 2.9031 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0637 loss: 3.0637 2022/10/07 11:18:53 - mmengine - INFO - Epoch(train) [19][920/2119] lr: 4.0000e-02 eta: 1 day, 2:10:45 time: 0.4045 data_time: 0.0192 memory: 5826 grad_norm: 2.8810 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6934 loss: 2.6934 2022/10/07 11:18:59 - mmengine - INFO - Epoch(train) [19][940/2119] lr: 4.0000e-02 eta: 1 day, 2:10:33 time: 0.3050 data_time: 0.0197 memory: 5826 grad_norm: 2.8877 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6338 loss: 2.6338 2022/10/07 11:19:07 - mmengine - INFO - Epoch(train) [19][960/2119] lr: 4.0000e-02 eta: 1 day, 2:10:31 time: 0.3681 data_time: 0.0209 memory: 5826 grad_norm: 2.8491 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5788 loss: 2.5788 2022/10/07 11:19:12 - mmengine - INFO - Epoch(train) [19][980/2119] lr: 4.0000e-02 eta: 1 day, 2:10:16 time: 0.2837 data_time: 0.0208 memory: 5826 grad_norm: 2.9104 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7942 loss: 2.7942 2022/10/07 11:19:20 - mmengine - INFO - Epoch(train) [19][1000/2119] lr: 4.0000e-02 eta: 1 day, 2:10:13 time: 0.3625 data_time: 0.0346 memory: 5826 grad_norm: 2.9242 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6287 loss: 2.6287 2022/10/07 11:19:26 - mmengine - INFO - Epoch(train) [19][1020/2119] lr: 4.0000e-02 eta: 1 day, 2:10:05 time: 0.3272 data_time: 0.0195 memory: 5826 grad_norm: 2.8967 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7960 loss: 2.7960 2022/10/07 11:19:34 - mmengine - INFO - Epoch(train) [19][1040/2119] lr: 4.0000e-02 eta: 1 day, 2:10:03 time: 0.3709 data_time: 0.0202 memory: 5826 grad_norm: 2.8773 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6572 loss: 2.6572 2022/10/07 11:19:40 - mmengine - INFO - Epoch(train) [19][1060/2119] lr: 4.0000e-02 eta: 1 day, 2:09:55 time: 0.3338 data_time: 0.0215 memory: 5826 grad_norm: 2.9028 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7767 loss: 2.7767 2022/10/07 11:19:48 - mmengine - INFO - Epoch(train) [19][1080/2119] lr: 4.0000e-02 eta: 1 day, 2:09:55 time: 0.3863 data_time: 0.0207 memory: 5826 grad_norm: 2.8678 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8188 loss: 2.8188 2022/10/07 11:19:55 - mmengine - INFO - Epoch(train) [19][1100/2119] lr: 4.0000e-02 eta: 1 day, 2:09:48 time: 0.3350 data_time: 0.0191 memory: 5826 grad_norm: 2.8766 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6738 loss: 2.6738 2022/10/07 11:20:03 - mmengine - INFO - Epoch(train) [19][1120/2119] lr: 4.0000e-02 eta: 1 day, 2:09:50 time: 0.3992 data_time: 0.0200 memory: 5826 grad_norm: 2.8451 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6814 loss: 2.6814 2022/10/07 11:20:09 - mmengine - INFO - Epoch(train) [19][1140/2119] lr: 4.0000e-02 eta: 1 day, 2:09:38 time: 0.2983 data_time: 0.0192 memory: 5826 grad_norm: 2.8808 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8676 loss: 2.8676 2022/10/07 11:20:16 - mmengine - INFO - Epoch(train) [19][1160/2119] lr: 4.0000e-02 eta: 1 day, 2:09:34 time: 0.3609 data_time: 0.0295 memory: 5826 grad_norm: 2.8762 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8394 loss: 2.8394 2022/10/07 11:20:22 - mmengine - INFO - Epoch(train) [19][1180/2119] lr: 4.0000e-02 eta: 1 day, 2:09:26 time: 0.3280 data_time: 0.0219 memory: 5826 grad_norm: 2.8940 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6633 loss: 2.6633 2022/10/07 11:20:30 - mmengine - INFO - Epoch(train) [19][1200/2119] lr: 4.0000e-02 eta: 1 day, 2:09:22 time: 0.3608 data_time: 0.0193 memory: 5826 grad_norm: 2.9108 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8529 loss: 2.8529 2022/10/07 11:20:36 - mmengine - INFO - Epoch(train) [19][1220/2119] lr: 4.0000e-02 eta: 1 day, 2:09:15 time: 0.3308 data_time: 0.0219 memory: 5826 grad_norm: 2.8861 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7633 loss: 2.7633 2022/10/07 11:20:44 - mmengine - INFO - Epoch(train) [19][1240/2119] lr: 4.0000e-02 eta: 1 day, 2:09:17 time: 0.4026 data_time: 0.0217 memory: 5826 grad_norm: 2.9208 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6842 loss: 2.6842 2022/10/07 11:20:50 - mmengine - INFO - Epoch(train) [19][1260/2119] lr: 4.0000e-02 eta: 1 day, 2:09:02 time: 0.2816 data_time: 0.0213 memory: 5826 grad_norm: 2.9373 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5848 loss: 2.5848 2022/10/07 11:20:57 - mmengine - INFO - Epoch(train) [19][1280/2119] lr: 4.0000e-02 eta: 1 day, 2:08:58 time: 0.3544 data_time: 0.0254 memory: 5826 grad_norm: 2.9130 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5946 loss: 2.5946 2022/10/07 11:21:04 - mmengine - INFO - Epoch(train) [19][1300/2119] lr: 4.0000e-02 eta: 1 day, 2:08:56 time: 0.3714 data_time: 0.0208 memory: 5826 grad_norm: 2.9252 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6859 loss: 2.6859 2022/10/07 11:21:11 - mmengine - INFO - Epoch(train) [19][1320/2119] lr: 4.0000e-02 eta: 1 day, 2:08:51 time: 0.3540 data_time: 0.0212 memory: 5826 grad_norm: 2.9245 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7377 loss: 2.7377 2022/10/07 11:21:18 - mmengine - INFO - Epoch(train) [19][1340/2119] lr: 4.0000e-02 eta: 1 day, 2:08:42 time: 0.3239 data_time: 0.0213 memory: 5826 grad_norm: 2.8586 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6308 loss: 2.6308 2022/10/07 11:21:25 - mmengine - INFO - Epoch(train) [19][1360/2119] lr: 4.0000e-02 eta: 1 day, 2:08:37 time: 0.3445 data_time: 0.0269 memory: 5826 grad_norm: 2.8337 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8345 loss: 2.8345 2022/10/07 11:21:32 - mmengine - INFO - Epoch(train) [19][1380/2119] lr: 4.0000e-02 eta: 1 day, 2:08:31 time: 0.3432 data_time: 0.0239 memory: 5826 grad_norm: 2.8940 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6552 loss: 2.6552 2022/10/07 11:21:38 - mmengine - INFO - Epoch(train) [19][1400/2119] lr: 4.0000e-02 eta: 1 day, 2:08:23 time: 0.3334 data_time: 0.0245 memory: 5826 grad_norm: 2.9139 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7734 loss: 2.7734 2022/10/07 11:21:45 - mmengine - INFO - Epoch(train) [19][1420/2119] lr: 4.0000e-02 eta: 1 day, 2:08:15 time: 0.3276 data_time: 0.0205 memory: 5826 grad_norm: 2.8465 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7714 loss: 2.7714 2022/10/07 11:21:52 - mmengine - INFO - Epoch(train) [19][1440/2119] lr: 4.0000e-02 eta: 1 day, 2:08:10 time: 0.3539 data_time: 0.0221 memory: 5826 grad_norm: 2.8989 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8574 loss: 2.8574 2022/10/07 11:21:59 - mmengine - INFO - Epoch(train) [19][1460/2119] lr: 4.0000e-02 eta: 1 day, 2:08:04 time: 0.3384 data_time: 0.0189 memory: 5826 grad_norm: 2.8721 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8446 loss: 2.8446 2022/10/07 11:22:06 - mmengine - INFO - Epoch(train) [19][1480/2119] lr: 4.0000e-02 eta: 1 day, 2:07:59 time: 0.3562 data_time: 0.0247 memory: 5826 grad_norm: 2.9088 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9436 loss: 2.9436 2022/10/07 11:22:13 - mmengine - INFO - Epoch(train) [19][1500/2119] lr: 4.0000e-02 eta: 1 day, 2:07:53 time: 0.3413 data_time: 0.0258 memory: 5826 grad_norm: 2.8588 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7368 loss: 2.7368 2022/10/07 11:22:20 - mmengine - INFO - Epoch(train) [19][1520/2119] lr: 4.0000e-02 eta: 1 day, 2:07:52 time: 0.3785 data_time: 0.0221 memory: 5826 grad_norm: 2.8948 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9922 loss: 2.9922 2022/10/07 11:22:27 - mmengine - INFO - Epoch(train) [19][1540/2119] lr: 4.0000e-02 eta: 1 day, 2:07:43 time: 0.3231 data_time: 0.0243 memory: 5826 grad_norm: 2.8577 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7566 loss: 2.7566 2022/10/07 11:22:33 - mmengine - INFO - Epoch(train) [19][1560/2119] lr: 4.0000e-02 eta: 1 day, 2:07:34 time: 0.3213 data_time: 0.0254 memory: 5826 grad_norm: 2.8650 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7148 loss: 2.7148 2022/10/07 11:22:39 - mmengine - INFO - Epoch(train) [19][1580/2119] lr: 4.0000e-02 eta: 1 day, 2:07:24 time: 0.3125 data_time: 0.0189 memory: 5826 grad_norm: 2.8800 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7688 loss: 2.7688 2022/10/07 11:22:47 - mmengine - INFO - Epoch(train) [19][1600/2119] lr: 4.0000e-02 eta: 1 day, 2:07:20 time: 0.3575 data_time: 0.0243 memory: 5826 grad_norm: 2.9234 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6580 loss: 2.6580 2022/10/07 11:22:53 - mmengine - INFO - Epoch(train) [19][1620/2119] lr: 4.0000e-02 eta: 1 day, 2:07:08 time: 0.3067 data_time: 0.0197 memory: 5826 grad_norm: 2.8545 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.8563 loss: 2.8563 2022/10/07 11:23:00 - mmengine - INFO - Epoch(train) [19][1640/2119] lr: 4.0000e-02 eta: 1 day, 2:07:03 time: 0.3506 data_time: 0.0213 memory: 5826 grad_norm: 2.8719 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7836 loss: 2.7836 2022/10/07 11:23:06 - mmengine - INFO - Epoch(train) [19][1660/2119] lr: 4.0000e-02 eta: 1 day, 2:06:56 time: 0.3339 data_time: 0.0167 memory: 5826 grad_norm: 2.8963 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.7925 loss: 2.7925 2022/10/07 11:23:14 - mmengine - INFO - Epoch(train) [19][1680/2119] lr: 4.0000e-02 eta: 1 day, 2:06:52 time: 0.3596 data_time: 0.0184 memory: 5826 grad_norm: 2.8614 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.0427 loss: 3.0427 2022/10/07 11:23:20 - mmengine - INFO - Epoch(train) [19][1700/2119] lr: 4.0000e-02 eta: 1 day, 2:06:43 time: 0.3235 data_time: 0.0236 memory: 5826 grad_norm: 2.8822 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.6491 loss: 2.6491 2022/10/07 11:23:29 - mmengine - INFO - Epoch(train) [19][1720/2119] lr: 4.0000e-02 eta: 1 day, 2:06:54 time: 0.4633 data_time: 0.0173 memory: 5826 grad_norm: 2.8963 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0209 loss: 3.0209 2022/10/07 11:23:37 - mmengine - INFO - Epoch(train) [19][1740/2119] lr: 4.0000e-02 eta: 1 day, 2:06:51 time: 0.3622 data_time: 0.0211 memory: 5826 grad_norm: 2.9115 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7804 loss: 2.7804 2022/10/07 11:23:43 - mmengine - INFO - Epoch(train) [19][1760/2119] lr: 4.0000e-02 eta: 1 day, 2:06:40 time: 0.3094 data_time: 0.0212 memory: 5826 grad_norm: 2.8911 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9575 loss: 2.9575 2022/10/07 11:23:50 - mmengine - INFO - Epoch(train) [19][1780/2119] lr: 4.0000e-02 eta: 1 day, 2:06:36 time: 0.3613 data_time: 0.0227 memory: 5826 grad_norm: 2.8746 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8626 loss: 2.8626 2022/10/07 11:23:57 - mmengine - INFO - Epoch(train) [19][1800/2119] lr: 4.0000e-02 eta: 1 day, 2:06:30 time: 0.3396 data_time: 0.0204 memory: 5826 grad_norm: 2.8974 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7038 loss: 2.7038 2022/10/07 11:24:04 - mmengine - INFO - Epoch(train) [19][1820/2119] lr: 4.0000e-02 eta: 1 day, 2:06:27 time: 0.3658 data_time: 0.0360 memory: 5826 grad_norm: 2.9112 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9291 loss: 2.9291 2022/10/07 11:24:10 - mmengine - INFO - Epoch(train) [19][1840/2119] lr: 4.0000e-02 eta: 1 day, 2:06:17 time: 0.3137 data_time: 0.0270 memory: 5826 grad_norm: 2.8929 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6592 loss: 2.6592 2022/10/07 11:24:17 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 11:24:18 - mmengine - INFO - Epoch(train) [19][1860/2119] lr: 4.0000e-02 eta: 1 day, 2:06:14 time: 0.3693 data_time: 0.0263 memory: 5826 grad_norm: 2.8897 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.5873 loss: 2.5873 2022/10/07 11:24:24 - mmengine - INFO - Epoch(train) [19][1880/2119] lr: 4.0000e-02 eta: 1 day, 2:06:06 time: 0.3257 data_time: 0.0216 memory: 5826 grad_norm: 2.8724 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6905 loss: 2.6905 2022/10/07 11:24:31 - mmengine - INFO - Epoch(train) [19][1900/2119] lr: 4.0000e-02 eta: 1 day, 2:06:01 time: 0.3540 data_time: 0.0195 memory: 5826 grad_norm: 2.8474 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6892 loss: 2.6892 2022/10/07 11:24:38 - mmengine - INFO - Epoch(train) [19][1920/2119] lr: 4.0000e-02 eta: 1 day, 2:05:56 time: 0.3512 data_time: 0.0189 memory: 5826 grad_norm: 2.9356 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6050 loss: 2.6050 2022/10/07 11:24:45 - mmengine - INFO - Epoch(train) [19][1940/2119] lr: 4.0000e-02 eta: 1 day, 2:05:49 time: 0.3330 data_time: 0.0228 memory: 5826 grad_norm: 2.8746 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6839 loss: 2.6839 2022/10/07 11:24:52 - mmengine - INFO - Epoch(train) [19][1960/2119] lr: 4.0000e-02 eta: 1 day, 2:05:44 time: 0.3543 data_time: 0.0226 memory: 5826 grad_norm: 2.8603 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6951 loss: 2.6951 2022/10/07 11:24:59 - mmengine - INFO - Epoch(train) [19][1980/2119] lr: 4.0000e-02 eta: 1 day, 2:05:38 time: 0.3450 data_time: 0.0229 memory: 5826 grad_norm: 2.8613 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8642 loss: 2.8642 2022/10/07 11:25:07 - mmengine - INFO - Epoch(train) [19][2000/2119] lr: 4.0000e-02 eta: 1 day, 2:05:37 time: 0.3776 data_time: 0.0210 memory: 5826 grad_norm: 2.9099 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6998 loss: 2.6998 2022/10/07 11:25:12 - mmengine - INFO - Epoch(train) [19][2020/2119] lr: 4.0000e-02 eta: 1 day, 2:05:24 time: 0.2899 data_time: 0.0179 memory: 5826 grad_norm: 2.8744 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9030 loss: 2.9030 2022/10/07 11:25:20 - mmengine - INFO - Epoch(train) [19][2040/2119] lr: 4.0000e-02 eta: 1 day, 2:05:25 time: 0.3992 data_time: 0.0235 memory: 5826 grad_norm: 2.8929 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 2.7304 loss: 2.7304 2022/10/07 11:25:27 - mmengine - INFO - Epoch(train) [19][2060/2119] lr: 4.0000e-02 eta: 1 day, 2:05:14 time: 0.3074 data_time: 0.0183 memory: 5826 grad_norm: 2.9248 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6491 loss: 2.6491 2022/10/07 11:25:33 - mmengine - INFO - Epoch(train) [19][2080/2119] lr: 4.0000e-02 eta: 1 day, 2:05:05 time: 0.3173 data_time: 0.0213 memory: 5826 grad_norm: 2.8644 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6892 loss: 2.6892 2022/10/07 11:25:39 - mmengine - INFO - Epoch(train) [19][2100/2119] lr: 4.0000e-02 eta: 1 day, 2:04:54 time: 0.3113 data_time: 0.0340 memory: 5826 grad_norm: 2.9175 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.6881 loss: 2.6881 2022/10/07 11:25:45 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 11:25:45 - mmengine - INFO - Epoch(train) [19][2119/2119] lr: 4.0000e-02 eta: 1 day, 2:04:54 time: 0.3266 data_time: 0.0429 memory: 5826 grad_norm: 2.9063 top1_acc: 0.3000 top5_acc: 0.8000 loss_cls: 2.8100 loss: 2.8100 2022/10/07 11:25:54 - mmengine - INFO - Epoch(train) [20][20/2119] lr: 4.0000e-02 eta: 1 day, 2:04:11 time: 0.4448 data_time: 0.1830 memory: 5826 grad_norm: 2.8369 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7047 loss: 2.7047 2022/10/07 11:26:01 - mmengine - INFO - Epoch(train) [20][40/2119] lr: 4.0000e-02 eta: 1 day, 2:04:04 time: 0.3359 data_time: 0.0292 memory: 5826 grad_norm: 2.8565 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.7017 loss: 2.7017 2022/10/07 11:26:08 - mmengine - INFO - Epoch(train) [20][60/2119] lr: 4.0000e-02 eta: 1 day, 2:04:00 time: 0.3594 data_time: 0.0413 memory: 5826 grad_norm: 2.8448 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8316 loss: 2.8316 2022/10/07 11:26:15 - mmengine - INFO - Epoch(train) [20][80/2119] lr: 4.0000e-02 eta: 1 day, 2:03:51 time: 0.3215 data_time: 0.0243 memory: 5826 grad_norm: 2.8789 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7141 loss: 2.7141 2022/10/07 11:26:23 - mmengine - INFO - Epoch(train) [20][100/2119] lr: 4.0000e-02 eta: 1 day, 2:03:57 time: 0.4313 data_time: 0.1894 memory: 5826 grad_norm: 2.8666 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7036 loss: 2.7036 2022/10/07 11:26:30 - mmengine - INFO - Epoch(train) [20][120/2119] lr: 4.0000e-02 eta: 1 day, 2:03:47 time: 0.3141 data_time: 0.0923 memory: 5826 grad_norm: 2.8769 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.6437 loss: 2.6437 2022/10/07 11:26:36 - mmengine - INFO - Epoch(train) [20][140/2119] lr: 4.0000e-02 eta: 1 day, 2:03:41 time: 0.3421 data_time: 0.1103 memory: 5826 grad_norm: 2.9222 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4475 loss: 2.4475 2022/10/07 11:26:44 - mmengine - INFO - Epoch(train) [20][160/2119] lr: 4.0000e-02 eta: 1 day, 2:03:37 time: 0.3603 data_time: 0.1198 memory: 5826 grad_norm: 2.9108 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6478 loss: 2.6478 2022/10/07 11:26:49 - mmengine - INFO - Epoch(train) [20][180/2119] lr: 4.0000e-02 eta: 1 day, 2:03:23 time: 0.2861 data_time: 0.0605 memory: 5826 grad_norm: 2.8977 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6349 loss: 2.6349 2022/10/07 11:26:56 - mmengine - INFO - Epoch(train) [20][200/2119] lr: 4.0000e-02 eta: 1 day, 2:03:17 time: 0.3410 data_time: 0.0927 memory: 5826 grad_norm: 2.9205 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7274 loss: 2.7274 2022/10/07 11:27:03 - mmengine - INFO - Epoch(train) [20][220/2119] lr: 4.0000e-02 eta: 1 day, 2:03:11 time: 0.3424 data_time: 0.0449 memory: 5826 grad_norm: 2.9045 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6500 loss: 2.6500 2022/10/07 11:27:11 - mmengine - INFO - Epoch(train) [20][240/2119] lr: 4.0000e-02 eta: 1 day, 2:03:09 time: 0.3760 data_time: 0.0165 memory: 5826 grad_norm: 2.8488 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7542 loss: 2.7542 2022/10/07 11:27:16 - mmengine - INFO - Epoch(train) [20][260/2119] lr: 4.0000e-02 eta: 1 day, 2:02:56 time: 0.2902 data_time: 0.0206 memory: 5826 grad_norm: 2.9139 top1_acc: 0.0625 top5_acc: 0.6250 loss_cls: 2.8449 loss: 2.8449 2022/10/07 11:27:24 - mmengine - INFO - Epoch(train) [20][280/2119] lr: 4.0000e-02 eta: 1 day, 2:02:56 time: 0.3875 data_time: 0.0207 memory: 5826 grad_norm: 2.8893 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9590 loss: 2.9590 2022/10/07 11:27:31 - mmengine - INFO - Epoch(train) [20][300/2119] lr: 4.0000e-02 eta: 1 day, 2:02:50 time: 0.3472 data_time: 0.0208 memory: 5826 grad_norm: 2.8968 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8331 loss: 2.8331 2022/10/07 11:27:39 - mmengine - INFO - Epoch(train) [20][320/2119] lr: 4.0000e-02 eta: 1 day, 2:02:51 time: 0.3952 data_time: 0.0205 memory: 5826 grad_norm: 2.8968 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9494 loss: 2.9494 2022/10/07 11:27:46 - mmengine - INFO - Epoch(train) [20][340/2119] lr: 4.0000e-02 eta: 1 day, 2:02:43 time: 0.3269 data_time: 0.0192 memory: 5826 grad_norm: 2.8525 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6140 loss: 2.6140 2022/10/07 11:27:52 - mmengine - INFO - Epoch(train) [20][360/2119] lr: 4.0000e-02 eta: 1 day, 2:02:36 time: 0.3379 data_time: 0.0229 memory: 5826 grad_norm: 2.8608 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7643 loss: 2.7643 2022/10/07 11:27:59 - mmengine - INFO - Epoch(train) [20][380/2119] lr: 4.0000e-02 eta: 1 day, 2:02:30 time: 0.3383 data_time: 0.0257 memory: 5826 grad_norm: 2.8761 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7415 loss: 2.7415 2022/10/07 11:28:06 - mmengine - INFO - Epoch(train) [20][400/2119] lr: 4.0000e-02 eta: 1 day, 2:02:26 time: 0.3591 data_time: 0.0171 memory: 5826 grad_norm: 2.8908 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6485 loss: 2.6485 2022/10/07 11:28:13 - mmengine - INFO - Epoch(train) [20][420/2119] lr: 4.0000e-02 eta: 1 day, 2:02:17 time: 0.3212 data_time: 0.0218 memory: 5826 grad_norm: 2.8537 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6207 loss: 2.6207 2022/10/07 11:28:19 - mmengine - INFO - Epoch(train) [20][440/2119] lr: 4.0000e-02 eta: 1 day, 2:02:10 time: 0.3374 data_time: 0.0187 memory: 5826 grad_norm: 2.8982 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6324 loss: 2.6324 2022/10/07 11:28:27 - mmengine - INFO - Epoch(train) [20][460/2119] lr: 4.0000e-02 eta: 1 day, 2:02:09 time: 0.3802 data_time: 0.0206 memory: 5826 grad_norm: 2.8848 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4894 loss: 2.4894 2022/10/07 11:28:34 - mmengine - INFO - Epoch(train) [20][480/2119] lr: 4.0000e-02 eta: 1 day, 2:02:00 time: 0.3271 data_time: 0.0194 memory: 5826 grad_norm: 2.8672 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6512 loss: 2.6512 2022/10/07 11:28:40 - mmengine - INFO - Epoch(train) [20][500/2119] lr: 4.0000e-02 eta: 1 day, 2:01:54 time: 0.3406 data_time: 0.0253 memory: 5826 grad_norm: 2.8846 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8796 loss: 2.8796 2022/10/07 11:28:48 - mmengine - INFO - Epoch(train) [20][520/2119] lr: 4.0000e-02 eta: 1 day, 2:01:54 time: 0.3844 data_time: 0.0191 memory: 5826 grad_norm: 2.8785 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8526 loss: 2.8526 2022/10/07 11:28:55 - mmengine - INFO - Epoch(train) [20][540/2119] lr: 4.0000e-02 eta: 1 day, 2:01:47 time: 0.3415 data_time: 0.0161 memory: 5826 grad_norm: 2.8764 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8392 loss: 2.8392 2022/10/07 11:29:01 - mmengine - INFO - Epoch(train) [20][560/2119] lr: 4.0000e-02 eta: 1 day, 2:01:37 time: 0.3162 data_time: 0.0154 memory: 5826 grad_norm: 2.8809 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6774 loss: 2.6774 2022/10/07 11:29:08 - mmengine - INFO - Epoch(train) [20][580/2119] lr: 4.0000e-02 eta: 1 day, 2:01:31 time: 0.3382 data_time: 0.0206 memory: 5826 grad_norm: 2.8541 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6798 loss: 2.6798 2022/10/07 11:29:15 - mmengine - INFO - Epoch(train) [20][600/2119] lr: 4.0000e-02 eta: 1 day, 2:01:23 time: 0.3341 data_time: 0.0186 memory: 5826 grad_norm: 2.8765 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.7971 loss: 2.7971 2022/10/07 11:29:22 - mmengine - INFO - Epoch(train) [20][620/2119] lr: 4.0000e-02 eta: 1 day, 2:01:17 time: 0.3416 data_time: 0.0225 memory: 5826 grad_norm: 2.8582 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8287 loss: 2.8287 2022/10/07 11:29:29 - mmengine - INFO - Epoch(train) [20][640/2119] lr: 4.0000e-02 eta: 1 day, 2:01:17 time: 0.3902 data_time: 0.0183 memory: 5826 grad_norm: 2.9201 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7316 loss: 2.7316 2022/10/07 11:29:36 - mmengine - INFO - Epoch(train) [20][660/2119] lr: 4.0000e-02 eta: 1 day, 2:01:11 time: 0.3384 data_time: 0.0237 memory: 5826 grad_norm: 2.8662 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7092 loss: 2.7092 2022/10/07 11:29:42 - mmengine - INFO - Epoch(train) [20][680/2119] lr: 4.0000e-02 eta: 1 day, 2:01:00 time: 0.3101 data_time: 0.0238 memory: 5826 grad_norm: 2.8840 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.8227 loss: 2.8227 2022/10/07 11:29:49 - mmengine - INFO - Epoch(train) [20][700/2119] lr: 4.0000e-02 eta: 1 day, 2:00:55 time: 0.3543 data_time: 0.0214 memory: 5826 grad_norm: 2.8790 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6051 loss: 2.6051 2022/10/07 11:29:56 - mmengine - INFO - Epoch(train) [20][720/2119] lr: 4.0000e-02 eta: 1 day, 2:00:47 time: 0.3237 data_time: 0.0259 memory: 5826 grad_norm: 2.9193 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7182 loss: 2.7182 2022/10/07 11:30:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 11:30:02 - mmengine - INFO - Epoch(train) [20][740/2119] lr: 4.0000e-02 eta: 1 day, 2:00:38 time: 0.3253 data_time: 0.0224 memory: 5826 grad_norm: 2.9212 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7171 loss: 2.7171 2022/10/07 11:30:10 - mmengine - INFO - Epoch(train) [20][760/2119] lr: 4.0000e-02 eta: 1 day, 2:00:40 time: 0.3997 data_time: 0.0206 memory: 5826 grad_norm: 2.8910 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7534 loss: 2.7534 2022/10/07 11:30:17 - mmengine - INFO - Epoch(train) [20][780/2119] lr: 4.0000e-02 eta: 1 day, 2:00:29 time: 0.3058 data_time: 0.0221 memory: 5826 grad_norm: 2.8835 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5601 loss: 2.5601 2022/10/07 11:30:24 - mmengine - INFO - Epoch(train) [20][800/2119] lr: 4.0000e-02 eta: 1 day, 2:00:26 time: 0.3702 data_time: 0.0180 memory: 5826 grad_norm: 2.8609 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6974 loss: 2.6974 2022/10/07 11:30:30 - mmengine - INFO - Epoch(train) [20][820/2119] lr: 4.0000e-02 eta: 1 day, 2:00:13 time: 0.2916 data_time: 0.0275 memory: 5826 grad_norm: 2.9347 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9483 loss: 2.9483 2022/10/07 11:30:42 - mmengine - INFO - Epoch(train) [20][840/2119] lr: 4.0000e-02 eta: 1 day, 2:00:42 time: 0.6000 data_time: 0.2374 memory: 5826 grad_norm: 2.8387 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7218 loss: 2.7218 2022/10/07 11:30:48 - mmengine - INFO - Epoch(train) [20][860/2119] lr: 4.0000e-02 eta: 1 day, 2:00:31 time: 0.3097 data_time: 0.0283 memory: 5826 grad_norm: 2.8934 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8386 loss: 2.8386 2022/10/07 11:30:55 - mmengine - INFO - Epoch(train) [20][880/2119] lr: 4.0000e-02 eta: 1 day, 2:00:25 time: 0.3477 data_time: 0.0237 memory: 5826 grad_norm: 2.8946 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5765 loss: 2.5765 2022/10/07 11:31:02 - mmengine - INFO - Epoch(train) [20][900/2119] lr: 4.0000e-02 eta: 1 day, 2:00:20 time: 0.3492 data_time: 0.0229 memory: 5826 grad_norm: 2.8673 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7165 loss: 2.7165 2022/10/07 11:31:09 - mmengine - INFO - Epoch(train) [20][920/2119] lr: 4.0000e-02 eta: 1 day, 2:00:13 time: 0.3334 data_time: 0.0167 memory: 5826 grad_norm: 2.8701 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6351 loss: 2.6351 2022/10/07 11:31:16 - mmengine - INFO - Epoch(train) [20][940/2119] lr: 4.0000e-02 eta: 1 day, 2:00:10 time: 0.3700 data_time: 0.0190 memory: 5826 grad_norm: 2.9459 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5764 loss: 2.5764 2022/10/07 11:31:23 - mmengine - INFO - Epoch(train) [20][960/2119] lr: 4.0000e-02 eta: 1 day, 2:00:07 time: 0.3617 data_time: 0.0208 memory: 5826 grad_norm: 2.8930 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8017 loss: 2.8017 2022/10/07 11:31:30 - mmengine - INFO - Epoch(train) [20][980/2119] lr: 4.0000e-02 eta: 1 day, 2:00:00 time: 0.3412 data_time: 0.0213 memory: 5826 grad_norm: 2.9371 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7251 loss: 2.7251 2022/10/07 11:31:37 - mmengine - INFO - Epoch(train) [20][1000/2119] lr: 4.0000e-02 eta: 1 day, 1:59:58 time: 0.3706 data_time: 0.0252 memory: 5826 grad_norm: 2.8717 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5977 loss: 2.5977 2022/10/07 11:31:43 - mmengine - INFO - Epoch(train) [20][1020/2119] lr: 4.0000e-02 eta: 1 day, 1:59:45 time: 0.2977 data_time: 0.0216 memory: 5826 grad_norm: 2.8908 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8910 loss: 2.8910 2022/10/07 11:31:51 - mmengine - INFO - Epoch(train) [20][1040/2119] lr: 4.0000e-02 eta: 1 day, 1:59:42 time: 0.3592 data_time: 0.0209 memory: 5826 grad_norm: 2.8244 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6601 loss: 2.6601 2022/10/07 11:31:57 - mmengine - INFO - Epoch(train) [20][1060/2119] lr: 4.0000e-02 eta: 1 day, 1:59:35 time: 0.3437 data_time: 0.0201 memory: 5826 grad_norm: 2.8657 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7251 loss: 2.7251 2022/10/07 11:32:04 - mmengine - INFO - Epoch(train) [20][1080/2119] lr: 4.0000e-02 eta: 1 day, 1:59:30 time: 0.3505 data_time: 0.0254 memory: 5826 grad_norm: 2.8479 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9684 loss: 2.9684 2022/10/07 11:32:12 - mmengine - INFO - Epoch(train) [20][1100/2119] lr: 4.0000e-02 eta: 1 day, 1:59:27 time: 0.3631 data_time: 0.0219 memory: 5826 grad_norm: 2.8741 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7863 loss: 2.7863 2022/10/07 11:32:19 - mmengine - INFO - Epoch(train) [20][1120/2119] lr: 4.0000e-02 eta: 1 day, 1:59:25 time: 0.3761 data_time: 0.0249 memory: 5826 grad_norm: 2.8775 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.2690 loss: 3.2690 2022/10/07 11:32:25 - mmengine - INFO - Epoch(train) [20][1140/2119] lr: 4.0000e-02 eta: 1 day, 1:59:11 time: 0.2840 data_time: 0.0176 memory: 5826 grad_norm: 2.8825 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7557 loss: 2.7557 2022/10/07 11:32:32 - mmengine - INFO - Epoch(train) [20][1160/2119] lr: 4.0000e-02 eta: 1 day, 1:59:04 time: 0.3353 data_time: 0.0237 memory: 5826 grad_norm: 2.8959 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8769 loss: 2.8769 2022/10/07 11:32:39 - mmengine - INFO - Epoch(train) [20][1180/2119] lr: 4.0000e-02 eta: 1 day, 1:59:00 time: 0.3617 data_time: 0.0216 memory: 5826 grad_norm: 2.8976 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8138 loss: 2.8138 2022/10/07 11:32:46 - mmengine - INFO - Epoch(train) [20][1200/2119] lr: 4.0000e-02 eta: 1 day, 1:58:56 time: 0.3541 data_time: 0.0180 memory: 5826 grad_norm: 2.8625 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6714 loss: 2.6714 2022/10/07 11:32:52 - mmengine - INFO - Epoch(train) [20][1220/2119] lr: 4.0000e-02 eta: 1 day, 1:58:47 time: 0.3232 data_time: 0.0173 memory: 5826 grad_norm: 2.8535 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8737 loss: 2.8737 2022/10/07 11:33:00 - mmengine - INFO - Epoch(train) [20][1240/2119] lr: 4.0000e-02 eta: 1 day, 1:58:45 time: 0.3770 data_time: 0.0171 memory: 5826 grad_norm: 2.8590 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7734 loss: 2.7734 2022/10/07 11:33:06 - mmengine - INFO - Epoch(train) [20][1260/2119] lr: 4.0000e-02 eta: 1 day, 1:58:36 time: 0.3182 data_time: 0.0240 memory: 5826 grad_norm: 2.9415 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6241 loss: 2.6241 2022/10/07 11:33:14 - mmengine - INFO - Epoch(train) [20][1280/2119] lr: 4.0000e-02 eta: 1 day, 1:58:35 time: 0.3880 data_time: 0.0195 memory: 5826 grad_norm: 2.8771 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0946 loss: 3.0946 2022/10/07 11:33:21 - mmengine - INFO - Epoch(train) [20][1300/2119] lr: 4.0000e-02 eta: 1 day, 1:58:27 time: 0.3279 data_time: 0.0169 memory: 5826 grad_norm: 2.8962 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8404 loss: 2.8404 2022/10/07 11:33:28 - mmengine - INFO - Epoch(train) [20][1320/2119] lr: 4.0000e-02 eta: 1 day, 1:58:26 time: 0.3823 data_time: 0.0228 memory: 5826 grad_norm: 2.8573 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8719 loss: 2.8719 2022/10/07 11:33:35 - mmengine - INFO - Epoch(train) [20][1340/2119] lr: 4.0000e-02 eta: 1 day, 1:58:18 time: 0.3269 data_time: 0.0227 memory: 5826 grad_norm: 2.9411 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7402 loss: 2.7402 2022/10/07 11:33:48 - mmengine - INFO - Epoch(train) [20][1360/2119] lr: 4.0000e-02 eta: 1 day, 1:58:53 time: 0.6539 data_time: 0.2974 memory: 5826 grad_norm: 2.9398 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6184 loss: 2.6184 2022/10/07 11:33:53 - mmengine - INFO - Epoch(train) [20][1380/2119] lr: 4.0000e-02 eta: 1 day, 1:58:34 time: 0.2437 data_time: 0.0281 memory: 5826 grad_norm: 2.9358 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5896 loss: 2.5896 2022/10/07 11:33:59 - mmengine - INFO - Epoch(train) [20][1400/2119] lr: 4.0000e-02 eta: 1 day, 1:58:23 time: 0.3089 data_time: 0.0343 memory: 5826 grad_norm: 2.9365 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7027 loss: 2.7027 2022/10/07 11:34:07 - mmengine - INFO - Epoch(train) [20][1420/2119] lr: 4.0000e-02 eta: 1 day, 1:58:23 time: 0.3900 data_time: 0.0916 memory: 5826 grad_norm: 2.8748 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6672 loss: 2.6672 2022/10/07 11:34:13 - mmengine - INFO - Epoch(train) [20][1440/2119] lr: 4.0000e-02 eta: 1 day, 1:58:14 time: 0.3240 data_time: 0.0277 memory: 5826 grad_norm: 2.8894 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8060 loss: 2.8060 2022/10/07 11:34:20 - mmengine - INFO - Epoch(train) [20][1460/2119] lr: 4.0000e-02 eta: 1 day, 1:58:08 time: 0.3421 data_time: 0.0183 memory: 5826 grad_norm: 2.8784 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7782 loss: 2.7782 2022/10/07 11:34:27 - mmengine - INFO - Epoch(train) [20][1480/2119] lr: 4.0000e-02 eta: 1 day, 1:58:00 time: 0.3294 data_time: 0.0183 memory: 5826 grad_norm: 2.8504 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7766 loss: 2.7766 2022/10/07 11:34:35 - mmengine - INFO - Epoch(train) [20][1500/2119] lr: 4.0000e-02 eta: 1 day, 1:58:03 time: 0.4082 data_time: 0.0306 memory: 5826 grad_norm: 2.9150 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8796 loss: 2.8796 2022/10/07 11:34:40 - mmengine - INFO - Epoch(train) [20][1520/2119] lr: 4.0000e-02 eta: 1 day, 1:57:48 time: 0.2782 data_time: 0.0189 memory: 5826 grad_norm: 2.9614 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8169 loss: 2.8169 2022/10/07 11:34:48 - mmengine - INFO - Epoch(train) [20][1540/2119] lr: 4.0000e-02 eta: 1 day, 1:57:46 time: 0.3732 data_time: 0.0227 memory: 5826 grad_norm: 2.9273 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7255 loss: 2.7255 2022/10/07 11:34:54 - mmengine - INFO - Epoch(train) [20][1560/2119] lr: 4.0000e-02 eta: 1 day, 1:57:36 time: 0.3151 data_time: 0.0177 memory: 5826 grad_norm: 2.8771 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8642 loss: 2.8642 2022/10/07 11:35:02 - mmengine - INFO - Epoch(train) [20][1580/2119] lr: 4.0000e-02 eta: 1 day, 1:57:34 time: 0.3745 data_time: 0.0255 memory: 5826 grad_norm: 2.9030 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.1048 loss: 3.1048 2022/10/07 11:35:08 - mmengine - INFO - Epoch(train) [20][1600/2119] lr: 4.0000e-02 eta: 1 day, 1:57:23 time: 0.3068 data_time: 0.0216 memory: 5826 grad_norm: 2.8293 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7470 loss: 2.7470 2022/10/07 11:35:15 - mmengine - INFO - Epoch(train) [20][1620/2119] lr: 4.0000e-02 eta: 1 day, 1:57:16 time: 0.3394 data_time: 0.0234 memory: 5826 grad_norm: 2.8957 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7987 loss: 2.7987 2022/10/07 11:35:22 - mmengine - INFO - Epoch(train) [20][1640/2119] lr: 4.0000e-02 eta: 1 day, 1:57:11 time: 0.3495 data_time: 0.0210 memory: 5826 grad_norm: 2.8838 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.8651 loss: 2.8651 2022/10/07 11:35:29 - mmengine - INFO - Epoch(train) [20][1660/2119] lr: 4.0000e-02 eta: 1 day, 1:57:05 time: 0.3480 data_time: 0.0227 memory: 5826 grad_norm: 2.8747 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7422 loss: 2.7422 2022/10/07 11:35:35 - mmengine - INFO - Epoch(train) [20][1680/2119] lr: 4.0000e-02 eta: 1 day, 1:56:57 time: 0.3259 data_time: 0.0173 memory: 5826 grad_norm: 2.8904 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7843 loss: 2.7843 2022/10/07 11:35:43 - mmengine - INFO - Epoch(train) [20][1700/2119] lr: 4.0000e-02 eta: 1 day, 1:57:01 time: 0.4183 data_time: 0.0216 memory: 5826 grad_norm: 2.8841 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8000 loss: 2.8000 2022/10/07 11:35:50 - mmengine - INFO - Epoch(train) [20][1720/2119] lr: 4.0000e-02 eta: 1 day, 1:56:53 time: 0.3311 data_time: 0.0180 memory: 5826 grad_norm: 2.8603 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5726 loss: 2.5726 2022/10/07 11:35:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 11:35:57 - mmengine - INFO - Epoch(train) [20][1740/2119] lr: 4.0000e-02 eta: 1 day, 1:56:47 time: 0.3489 data_time: 0.0204 memory: 5826 grad_norm: 2.8744 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5960 loss: 2.5960 2022/10/07 11:36:04 - mmengine - INFO - Epoch(train) [20][1760/2119] lr: 4.0000e-02 eta: 1 day, 1:56:43 time: 0.3582 data_time: 0.0198 memory: 5826 grad_norm: 2.9139 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8953 loss: 2.8953 2022/10/07 11:36:11 - mmengine - INFO - Epoch(train) [20][1780/2119] lr: 4.0000e-02 eta: 1 day, 1:56:39 time: 0.3578 data_time: 0.0248 memory: 5826 grad_norm: 2.8801 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7722 loss: 2.7722 2022/10/07 11:36:17 - mmengine - INFO - Epoch(train) [20][1800/2119] lr: 4.0000e-02 eta: 1 day, 1:56:26 time: 0.2929 data_time: 0.0231 memory: 5826 grad_norm: 2.9048 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7546 loss: 2.7546 2022/10/07 11:36:24 - mmengine - INFO - Epoch(train) [20][1820/2119] lr: 4.0000e-02 eta: 1 day, 1:56:22 time: 0.3562 data_time: 0.0189 memory: 5826 grad_norm: 2.9456 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7054 loss: 2.7054 2022/10/07 11:36:31 - mmengine - INFO - Epoch(train) [20][1840/2119] lr: 4.0000e-02 eta: 1 day, 1:56:14 time: 0.3281 data_time: 0.0232 memory: 5826 grad_norm: 2.9510 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.6550 loss: 2.6550 2022/10/07 11:36:39 - mmengine - INFO - Epoch(train) [20][1860/2119] lr: 4.0000e-02 eta: 1 day, 1:56:15 time: 0.4011 data_time: 0.0193 memory: 5826 grad_norm: 2.9175 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7440 loss: 2.7440 2022/10/07 11:36:45 - mmengine - INFO - Epoch(train) [20][1880/2119] lr: 4.0000e-02 eta: 1 day, 1:56:02 time: 0.2935 data_time: 0.0230 memory: 5826 grad_norm: 2.9225 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8473 loss: 2.8473 2022/10/07 11:36:52 - mmengine - INFO - Epoch(train) [20][1900/2119] lr: 4.0000e-02 eta: 1 day, 1:55:59 time: 0.3665 data_time: 0.0236 memory: 5826 grad_norm: 2.8783 top1_acc: 0.0625 top5_acc: 0.4375 loss_cls: 2.9150 loss: 2.9150 2022/10/07 11:36:59 - mmengine - INFO - Epoch(train) [20][1920/2119] lr: 4.0000e-02 eta: 1 day, 1:55:51 time: 0.3297 data_time: 0.0205 memory: 5826 grad_norm: 2.9238 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8291 loss: 2.8291 2022/10/07 11:37:06 - mmengine - INFO - Epoch(train) [20][1940/2119] lr: 4.0000e-02 eta: 1 day, 1:55:44 time: 0.3381 data_time: 0.0276 memory: 5826 grad_norm: 2.8881 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.8104 loss: 2.8104 2022/10/07 11:37:12 - mmengine - INFO - Epoch(train) [20][1960/2119] lr: 4.0000e-02 eta: 1 day, 1:55:34 time: 0.3090 data_time: 0.0241 memory: 5826 grad_norm: 2.8797 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9471 loss: 2.9471 2022/10/07 11:37:19 - mmengine - INFO - Epoch(train) [20][1980/2119] lr: 4.0000e-02 eta: 1 day, 1:55:31 time: 0.3722 data_time: 0.0193 memory: 5826 grad_norm: 2.8880 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.9884 loss: 2.9884 2022/10/07 11:37:26 - mmengine - INFO - Epoch(train) [20][2000/2119] lr: 4.0000e-02 eta: 1 day, 1:55:25 time: 0.3452 data_time: 0.0189 memory: 5826 grad_norm: 2.9072 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8174 loss: 2.8174 2022/10/07 11:37:34 - mmengine - INFO - Epoch(train) [20][2020/2119] lr: 4.0000e-02 eta: 1 day, 1:55:24 time: 0.3770 data_time: 0.0186 memory: 5826 grad_norm: 2.8325 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8499 loss: 2.8499 2022/10/07 11:37:40 - mmengine - INFO - Epoch(train) [20][2040/2119] lr: 4.0000e-02 eta: 1 day, 1:55:13 time: 0.3082 data_time: 0.0207 memory: 5826 grad_norm: 2.8520 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7421 loss: 2.7421 2022/10/07 11:37:47 - mmengine - INFO - Epoch(train) [20][2060/2119] lr: 4.0000e-02 eta: 1 day, 1:55:08 time: 0.3537 data_time: 0.0187 memory: 5826 grad_norm: 2.9367 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6111 loss: 2.6111 2022/10/07 11:37:54 - mmengine - INFO - Epoch(train) [20][2080/2119] lr: 4.0000e-02 eta: 1 day, 1:55:04 time: 0.3585 data_time: 0.0205 memory: 5826 grad_norm: 2.9225 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9544 loss: 2.9544 2022/10/07 11:38:02 - mmengine - INFO - Epoch(train) [20][2100/2119] lr: 4.0000e-02 eta: 1 day, 1:55:02 time: 0.3787 data_time: 0.0244 memory: 5826 grad_norm: 2.9393 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6096 loss: 2.6096 2022/10/07 11:38:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 11:38:07 - mmengine - INFO - Epoch(train) [20][2119/2119] lr: 4.0000e-02 eta: 1 day, 1:55:02 time: 0.2746 data_time: 0.0216 memory: 5826 grad_norm: 2.8992 top1_acc: 0.4000 top5_acc: 0.7000 loss_cls: 2.7687 loss: 2.7687 2022/10/07 11:38:07 - mmengine - INFO - Saving checkpoint at 20 epochs 2022/10/07 11:38:18 - mmengine - INFO - Epoch(val) [20][20/137] eta: 0:00:47 time: 0.4023 data_time: 0.3315 memory: 1241 2022/10/07 11:38:23 - mmengine - INFO - Epoch(val) [20][40/137] eta: 0:00:25 time: 0.2673 data_time: 0.2027 memory: 1241 2022/10/07 11:38:30 - mmengine - INFO - Epoch(val) [20][60/137] eta: 0:00:26 time: 0.3444 data_time: 0.2766 memory: 1241 2022/10/07 11:38:36 - mmengine - INFO - Epoch(val) [20][80/137] eta: 0:00:16 time: 0.2823 data_time: 0.2150 memory: 1241 2022/10/07 11:38:43 - mmengine - INFO - Epoch(val) [20][100/137] eta: 0:00:13 time: 0.3677 data_time: 0.3024 memory: 1241 2022/10/07 11:38:48 - mmengine - INFO - Epoch(val) [20][120/137] eta: 0:00:04 time: 0.2571 data_time: 0.1907 memory: 1241 2022/10/07 11:38:58 - mmengine - INFO - Epoch(val) [20][137/137] acc/top1: 0.4175 acc/top5: 0.6651 acc/mean1: 0.4174 2022/10/07 11:38:58 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb/best_acc/top1_epoch_15.pth is removed 2022/10/07 11:39:04 - mmengine - INFO - The best checkpoint with 0.4175 acc/top1 at 20 epoch is saved to best_acc/top1_epoch_20.pth. 2022/10/07 11:39:14 - mmengine - INFO - Epoch(train) [21][20/2119] lr: 4.0000e-02 eta: 1 day, 1:54:26 time: 0.4792 data_time: 0.2631 memory: 5826 grad_norm: 2.8966 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8664 loss: 2.8664 2022/10/07 11:39:20 - mmengine - INFO - Epoch(train) [21][40/2119] lr: 4.0000e-02 eta: 1 day, 1:54:13 time: 0.2945 data_time: 0.0696 memory: 5826 grad_norm: 2.8930 top1_acc: 0.1875 top5_acc: 0.2500 loss_cls: 2.8644 loss: 2.8644 2022/10/07 11:39:27 - mmengine - INFO - Epoch(train) [21][60/2119] lr: 4.0000e-02 eta: 1 day, 1:54:09 time: 0.3620 data_time: 0.1334 memory: 5826 grad_norm: 2.8545 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.6930 loss: 2.6930 2022/10/07 11:39:34 - mmengine - INFO - Epoch(train) [21][80/2119] lr: 4.0000e-02 eta: 1 day, 1:54:01 time: 0.3265 data_time: 0.0751 memory: 5826 grad_norm: 2.9271 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7483 loss: 2.7483 2022/10/07 11:39:40 - mmengine - INFO - Epoch(train) [21][100/2119] lr: 4.0000e-02 eta: 1 day, 1:53:54 time: 0.3352 data_time: 0.0785 memory: 5826 grad_norm: 2.9195 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8037 loss: 2.8037 2022/10/07 11:39:47 - mmengine - INFO - Epoch(train) [21][120/2119] lr: 4.0000e-02 eta: 1 day, 1:53:44 time: 0.3128 data_time: 0.0449 memory: 5826 grad_norm: 2.8708 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7897 loss: 2.7897 2022/10/07 11:40:07 - mmengine - INFO - Epoch(train) [21][140/2119] lr: 4.0000e-02 eta: 1 day, 1:55:06 time: 1.0231 data_time: 0.7583 memory: 5826 grad_norm: 2.8926 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8097 loss: 2.8097 2022/10/07 11:40:13 - mmengine - INFO - Epoch(train) [21][160/2119] lr: 4.0000e-02 eta: 1 day, 1:54:55 time: 0.3097 data_time: 0.0814 memory: 5826 grad_norm: 2.9221 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9360 loss: 2.9360 2022/10/07 11:40:20 - mmengine - INFO - Epoch(train) [21][180/2119] lr: 4.0000e-02 eta: 1 day, 1:54:50 time: 0.3529 data_time: 0.1218 memory: 5826 grad_norm: 2.8837 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9015 loss: 2.9015 2022/10/07 11:40:27 - mmengine - INFO - Epoch(train) [21][200/2119] lr: 4.0000e-02 eta: 1 day, 1:54:41 time: 0.3188 data_time: 0.0783 memory: 5826 grad_norm: 2.9509 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.6288 loss: 2.6288 2022/10/07 11:40:33 - mmengine - INFO - Epoch(train) [21][220/2119] lr: 4.0000e-02 eta: 1 day, 1:54:32 time: 0.3242 data_time: 0.0877 memory: 5826 grad_norm: 2.9008 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7276 loss: 2.7276 2022/10/07 11:40:39 - mmengine - INFO - Epoch(train) [21][240/2119] lr: 4.0000e-02 eta: 1 day, 1:54:19 time: 0.2891 data_time: 0.0174 memory: 5826 grad_norm: 2.8744 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7239 loss: 2.7239 2022/10/07 11:40:47 - mmengine - INFO - Epoch(train) [21][260/2119] lr: 4.0000e-02 eta: 1 day, 1:54:20 time: 0.3995 data_time: 0.1503 memory: 5826 grad_norm: 2.8589 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5477 loss: 2.5477 2022/10/07 11:40:53 - mmengine - INFO - Epoch(train) [21][280/2119] lr: 4.0000e-02 eta: 1 day, 1:54:10 time: 0.3180 data_time: 0.0418 memory: 5826 grad_norm: 2.9156 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 3.0152 loss: 3.0152 2022/10/07 11:41:00 - mmengine - INFO - Epoch(train) [21][300/2119] lr: 4.0000e-02 eta: 1 day, 1:54:04 time: 0.3412 data_time: 0.0200 memory: 5826 grad_norm: 2.8684 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6575 loss: 2.6575 2022/10/07 11:41:07 - mmengine - INFO - Epoch(train) [21][320/2119] lr: 4.0000e-02 eta: 1 day, 1:53:58 time: 0.3455 data_time: 0.0169 memory: 5826 grad_norm: 2.9084 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7166 loss: 2.7166 2022/10/07 11:41:13 - mmengine - INFO - Epoch(train) [21][340/2119] lr: 4.0000e-02 eta: 1 day, 1:53:48 time: 0.3178 data_time: 0.0229 memory: 5826 grad_norm: 2.9220 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6226 loss: 2.6226 2022/10/07 11:41:21 - mmengine - INFO - Epoch(train) [21][360/2119] lr: 4.0000e-02 eta: 1 day, 1:53:48 time: 0.3913 data_time: 0.0200 memory: 5826 grad_norm: 2.9434 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6987 loss: 2.6987 2022/10/07 11:41:27 - mmengine - INFO - Epoch(train) [21][380/2119] lr: 4.0000e-02 eta: 1 day, 1:53:37 time: 0.3047 data_time: 0.0196 memory: 5826 grad_norm: 2.9039 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6631 loss: 2.6631 2022/10/07 11:41:35 - mmengine - INFO - Epoch(train) [21][400/2119] lr: 4.0000e-02 eta: 1 day, 1:53:37 time: 0.3929 data_time: 0.0274 memory: 5826 grad_norm: 2.8776 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7250 loss: 2.7250 2022/10/07 11:41:41 - mmengine - INFO - Epoch(train) [21][420/2119] lr: 4.0000e-02 eta: 1 day, 1:53:26 time: 0.3023 data_time: 0.0156 memory: 5826 grad_norm: 2.9248 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6822 loss: 2.6822 2022/10/07 11:41:49 - mmengine - INFO - Epoch(train) [21][440/2119] lr: 4.0000e-02 eta: 1 day, 1:53:25 time: 0.3863 data_time: 0.0259 memory: 5826 grad_norm: 2.8565 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.5585 loss: 2.5585 2022/10/07 11:41:55 - mmengine - INFO - Epoch(train) [21][460/2119] lr: 4.0000e-02 eta: 1 day, 1:53:17 time: 0.3282 data_time: 0.0179 memory: 5826 grad_norm: 2.8892 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8252 loss: 2.8252 2022/10/07 11:42:03 - mmengine - INFO - Epoch(train) [21][480/2119] lr: 4.0000e-02 eta: 1 day, 1:53:15 time: 0.3743 data_time: 0.0217 memory: 5826 grad_norm: 2.8694 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7336 loss: 2.7336 2022/10/07 11:42:09 - mmengine - INFO - Epoch(train) [21][500/2119] lr: 4.0000e-02 eta: 1 day, 1:53:04 time: 0.3099 data_time: 0.0301 memory: 5826 grad_norm: 2.8427 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5352 loss: 2.5352 2022/10/07 11:42:16 - mmengine - INFO - Epoch(train) [21][520/2119] lr: 4.0000e-02 eta: 1 day, 1:52:59 time: 0.3518 data_time: 0.0221 memory: 5826 grad_norm: 2.8646 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9127 loss: 2.9127 2022/10/07 11:42:23 - mmengine - INFO - Epoch(train) [21][540/2119] lr: 4.0000e-02 eta: 1 day, 1:52:51 time: 0.3247 data_time: 0.0285 memory: 5826 grad_norm: 2.9038 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7305 loss: 2.7305 2022/10/07 11:42:30 - mmengine - INFO - Epoch(train) [21][560/2119] lr: 4.0000e-02 eta: 1 day, 1:52:45 time: 0.3490 data_time: 0.0206 memory: 5826 grad_norm: 2.8879 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7541 loss: 2.7541 2022/10/07 11:42:37 - mmengine - INFO - Epoch(train) [21][580/2119] lr: 4.0000e-02 eta: 1 day, 1:52:39 time: 0.3460 data_time: 0.0201 memory: 5826 grad_norm: 2.8794 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7027 loss: 2.7027 2022/10/07 11:42:43 - mmengine - INFO - Epoch(train) [21][600/2119] lr: 4.0000e-02 eta: 1 day, 1:52:33 time: 0.3434 data_time: 0.0221 memory: 5826 grad_norm: 2.9116 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9350 loss: 2.9350 2022/10/07 11:42:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 11:42:50 - mmengine - INFO - Epoch(train) [21][620/2119] lr: 4.0000e-02 eta: 1 day, 1:52:26 time: 0.3362 data_time: 0.0230 memory: 5826 grad_norm: 2.8488 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5989 loss: 2.5989 2022/10/07 11:42:57 - mmengine - INFO - Epoch(train) [21][640/2119] lr: 4.0000e-02 eta: 1 day, 1:52:20 time: 0.3444 data_time: 0.0165 memory: 5826 grad_norm: 2.8838 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4851 loss: 2.4851 2022/10/07 11:43:04 - mmengine - INFO - Epoch(train) [21][660/2119] lr: 4.0000e-02 eta: 1 day, 1:52:15 time: 0.3524 data_time: 0.0221 memory: 5826 grad_norm: 2.8829 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8030 loss: 2.8030 2022/10/07 11:43:13 - mmengine - INFO - Epoch(train) [21][680/2119] lr: 4.0000e-02 eta: 1 day, 1:52:19 time: 0.4249 data_time: 0.0276 memory: 5826 grad_norm: 2.9531 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8305 loss: 2.8305 2022/10/07 11:43:19 - mmengine - INFO - Epoch(train) [21][700/2119] lr: 4.0000e-02 eta: 1 day, 1:52:10 time: 0.3203 data_time: 0.0218 memory: 5826 grad_norm: 2.9222 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 3.1317 loss: 3.1317 2022/10/07 11:43:27 - mmengine - INFO - Epoch(train) [21][720/2119] lr: 4.0000e-02 eta: 1 day, 1:52:09 time: 0.3834 data_time: 0.0170 memory: 5826 grad_norm: 2.8046 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9344 loss: 2.9344 2022/10/07 11:43:33 - mmengine - INFO - Epoch(train) [21][740/2119] lr: 4.0000e-02 eta: 1 day, 1:52:01 time: 0.3348 data_time: 0.0210 memory: 5826 grad_norm: 2.8487 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8454 loss: 2.8454 2022/10/07 11:43:40 - mmengine - INFO - Epoch(train) [21][760/2119] lr: 4.0000e-02 eta: 1 day, 1:51:57 time: 0.3552 data_time: 0.0182 memory: 5826 grad_norm: 2.8734 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7072 loss: 2.7072 2022/10/07 11:43:47 - mmengine - INFO - Epoch(train) [21][780/2119] lr: 4.0000e-02 eta: 1 day, 1:51:51 time: 0.3496 data_time: 0.0226 memory: 5826 grad_norm: 2.9520 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8351 loss: 2.8351 2022/10/07 11:43:54 - mmengine - INFO - Epoch(train) [21][800/2119] lr: 4.0000e-02 eta: 1 day, 1:51:45 time: 0.3402 data_time: 0.0212 memory: 5826 grad_norm: 2.8727 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6649 loss: 2.6649 2022/10/07 11:44:01 - mmengine - INFO - Epoch(train) [21][820/2119] lr: 4.0000e-02 eta: 1 day, 1:51:36 time: 0.3231 data_time: 0.0222 memory: 5826 grad_norm: 2.9227 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9062 loss: 2.9062 2022/10/07 11:44:08 - mmengine - INFO - Epoch(train) [21][840/2119] lr: 4.0000e-02 eta: 1 day, 1:51:33 time: 0.3715 data_time: 0.0246 memory: 5826 grad_norm: 2.9339 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7155 loss: 2.7155 2022/10/07 11:44:14 - mmengine - INFO - Epoch(train) [21][860/2119] lr: 4.0000e-02 eta: 1 day, 1:51:20 time: 0.2864 data_time: 0.0206 memory: 5826 grad_norm: 2.9216 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7364 loss: 2.7364 2022/10/07 11:44:22 - mmengine - INFO - Epoch(train) [21][880/2119] lr: 4.0000e-02 eta: 1 day, 1:51:19 time: 0.3900 data_time: 0.0194 memory: 5826 grad_norm: 2.8684 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5715 loss: 2.5715 2022/10/07 11:44:28 - mmengine - INFO - Epoch(train) [21][900/2119] lr: 4.0000e-02 eta: 1 day, 1:51:10 time: 0.3146 data_time: 0.0212 memory: 5826 grad_norm: 2.8715 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6570 loss: 2.6570 2022/10/07 11:44:35 - mmengine - INFO - Epoch(train) [21][920/2119] lr: 4.0000e-02 eta: 1 day, 1:51:05 time: 0.3554 data_time: 0.0188 memory: 5826 grad_norm: 2.8670 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7287 loss: 2.7287 2022/10/07 11:44:42 - mmengine - INFO - Epoch(train) [21][940/2119] lr: 4.0000e-02 eta: 1 day, 1:50:56 time: 0.3200 data_time: 0.0223 memory: 5826 grad_norm: 2.9187 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6638 loss: 2.6638 2022/10/07 11:44:50 - mmengine - INFO - Epoch(train) [21][960/2119] lr: 4.0000e-02 eta: 1 day, 1:50:57 time: 0.3990 data_time: 0.0210 memory: 5826 grad_norm: 2.9068 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7534 loss: 2.7534 2022/10/07 11:44:56 - mmengine - INFO - Epoch(train) [21][980/2119] lr: 4.0000e-02 eta: 1 day, 1:50:50 time: 0.3395 data_time: 0.0216 memory: 5826 grad_norm: 2.9035 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7820 loss: 2.7820 2022/10/07 11:45:04 - mmengine - INFO - Epoch(train) [21][1000/2119] lr: 4.0000e-02 eta: 1 day, 1:50:49 time: 0.3842 data_time: 0.0184 memory: 5826 grad_norm: 2.9175 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8397 loss: 2.8397 2022/10/07 11:45:09 - mmengine - INFO - Epoch(train) [21][1020/2119] lr: 4.0000e-02 eta: 1 day, 1:50:33 time: 0.2714 data_time: 0.0246 memory: 5826 grad_norm: 2.9274 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9797 loss: 2.9797 2022/10/07 11:45:17 - mmengine - INFO - Epoch(train) [21][1040/2119] lr: 4.0000e-02 eta: 1 day, 1:50:33 time: 0.3899 data_time: 0.0216 memory: 5826 grad_norm: 2.9145 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9480 loss: 2.9480 2022/10/07 11:45:25 - mmengine - INFO - Epoch(train) [21][1060/2119] lr: 4.0000e-02 eta: 1 day, 1:50:30 time: 0.3678 data_time: 0.0195 memory: 5826 grad_norm: 2.8283 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.5022 loss: 2.5022 2022/10/07 11:45:31 - mmengine - INFO - Epoch(train) [21][1080/2119] lr: 4.0000e-02 eta: 1 day, 1:50:19 time: 0.3031 data_time: 0.0252 memory: 5826 grad_norm: 2.8124 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6401 loss: 2.6401 2022/10/07 11:45:37 - mmengine - INFO - Epoch(train) [21][1100/2119] lr: 4.0000e-02 eta: 1 day, 1:50:09 time: 0.3182 data_time: 0.0258 memory: 5826 grad_norm: 2.8615 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6274 loss: 2.6274 2022/10/07 11:45:44 - mmengine - INFO - Epoch(train) [21][1120/2119] lr: 4.0000e-02 eta: 1 day, 1:50:06 time: 0.3696 data_time: 0.0217 memory: 5826 grad_norm: 2.9070 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9224 loss: 2.9224 2022/10/07 11:45:51 - mmengine - INFO - Epoch(train) [21][1140/2119] lr: 4.0000e-02 eta: 1 day, 1:49:58 time: 0.3239 data_time: 0.0241 memory: 5826 grad_norm: 2.9124 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5961 loss: 2.5961 2022/10/07 11:45:58 - mmengine - INFO - Epoch(train) [21][1160/2119] lr: 4.0000e-02 eta: 1 day, 1:49:52 time: 0.3478 data_time: 0.0245 memory: 5826 grad_norm: 2.8690 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8064 loss: 2.8064 2022/10/07 11:46:05 - mmengine - INFO - Epoch(train) [21][1180/2119] lr: 4.0000e-02 eta: 1 day, 1:49:48 time: 0.3582 data_time: 0.0238 memory: 5826 grad_norm: 2.8911 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8018 loss: 2.8018 2022/10/07 11:46:12 - mmengine - INFO - Epoch(train) [21][1200/2119] lr: 4.0000e-02 eta: 1 day, 1:49:39 time: 0.3256 data_time: 0.0248 memory: 5826 grad_norm: 2.9095 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7183 loss: 2.7183 2022/10/07 11:46:19 - mmengine - INFO - Epoch(train) [21][1220/2119] lr: 4.0000e-02 eta: 1 day, 1:49:34 time: 0.3547 data_time: 0.0363 memory: 5826 grad_norm: 2.8996 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6810 loss: 2.6810 2022/10/07 11:46:25 - mmengine - INFO - Epoch(train) [21][1240/2119] lr: 4.0000e-02 eta: 1 day, 1:49:28 time: 0.3399 data_time: 0.0191 memory: 5826 grad_norm: 2.9032 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9737 loss: 2.9737 2022/10/07 11:46:32 - mmengine - INFO - Epoch(train) [21][1260/2119] lr: 4.0000e-02 eta: 1 day, 1:49:22 time: 0.3491 data_time: 0.0274 memory: 5826 grad_norm: 2.9391 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9277 loss: 2.9277 2022/10/07 11:46:39 - mmengine - INFO - Epoch(train) [21][1280/2119] lr: 4.0000e-02 eta: 1 day, 1:49:12 time: 0.3141 data_time: 0.0213 memory: 5826 grad_norm: 2.9133 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7447 loss: 2.7447 2022/10/07 11:46:46 - mmengine - INFO - Epoch(train) [21][1300/2119] lr: 4.0000e-02 eta: 1 day, 1:49:07 time: 0.3510 data_time: 0.0172 memory: 5826 grad_norm: 2.9045 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6849 loss: 2.6849 2022/10/07 11:46:52 - mmengine - INFO - Epoch(train) [21][1320/2119] lr: 4.0000e-02 eta: 1 day, 1:49:00 time: 0.3360 data_time: 0.0272 memory: 5826 grad_norm: 2.8948 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.5550 loss: 2.5550 2022/10/07 11:47:00 - mmengine - INFO - Epoch(train) [21][1340/2119] lr: 4.0000e-02 eta: 1 day, 1:48:58 time: 0.3805 data_time: 0.0160 memory: 5826 grad_norm: 2.9532 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.9312 loss: 2.9312 2022/10/07 11:47:06 - mmengine - INFO - Epoch(train) [21][1360/2119] lr: 4.0000e-02 eta: 1 day, 1:48:47 time: 0.3058 data_time: 0.0209 memory: 5826 grad_norm: 2.9475 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8874 loss: 2.8874 2022/10/07 11:47:13 - mmengine - INFO - Epoch(train) [21][1380/2119] lr: 4.0000e-02 eta: 1 day, 1:48:42 time: 0.3533 data_time: 0.0260 memory: 5826 grad_norm: 2.8817 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7519 loss: 2.7519 2022/10/07 11:47:19 - mmengine - INFO - Epoch(train) [21][1400/2119] lr: 4.0000e-02 eta: 1 day, 1:48:31 time: 0.2993 data_time: 0.0268 memory: 5826 grad_norm: 2.8855 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6547 loss: 2.6547 2022/10/07 11:47:27 - mmengine - INFO - Epoch(train) [21][1420/2119] lr: 4.0000e-02 eta: 1 day, 1:48:28 time: 0.3751 data_time: 0.0251 memory: 5826 grad_norm: 2.8744 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8179 loss: 2.8179 2022/10/07 11:47:33 - mmengine - INFO - Epoch(train) [21][1440/2119] lr: 4.0000e-02 eta: 1 day, 1:48:18 time: 0.3106 data_time: 0.0269 memory: 5826 grad_norm: 2.9062 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6862 loss: 2.6862 2022/10/07 11:47:40 - mmengine - INFO - Epoch(train) [21][1460/2119] lr: 4.0000e-02 eta: 1 day, 1:48:13 time: 0.3519 data_time: 0.0373 memory: 5826 grad_norm: 2.8776 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8166 loss: 2.8166 2022/10/07 11:47:47 - mmengine - INFO - Epoch(train) [21][1480/2119] lr: 4.0000e-02 eta: 1 day, 1:48:07 time: 0.3436 data_time: 0.0237 memory: 5826 grad_norm: 2.9185 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8784 loss: 2.8784 2022/10/07 11:47:55 - mmengine - INFO - Epoch(train) [21][1500/2119] lr: 4.0000e-02 eta: 1 day, 1:48:06 time: 0.3902 data_time: 0.0186 memory: 5826 grad_norm: 2.9199 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6872 loss: 2.6872 2022/10/07 11:48:01 - mmengine - INFO - Epoch(train) [21][1520/2119] lr: 4.0000e-02 eta: 1 day, 1:47:55 time: 0.3056 data_time: 0.0262 memory: 5826 grad_norm: 2.9055 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8141 loss: 2.8141 2022/10/07 11:48:13 - mmengine - INFO - Epoch(train) [21][1540/2119] lr: 4.0000e-02 eta: 1 day, 1:48:20 time: 0.5940 data_time: 0.2973 memory: 5826 grad_norm: 2.9077 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8436 loss: 2.8436 2022/10/07 11:48:19 - mmengine - INFO - Epoch(train) [21][1560/2119] lr: 4.0000e-02 eta: 1 day, 1:48:10 time: 0.3109 data_time: 0.0222 memory: 5826 grad_norm: 2.8745 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7680 loss: 2.7680 2022/10/07 11:48:26 - mmengine - INFO - Epoch(train) [21][1580/2119] lr: 4.0000e-02 eta: 1 day, 1:48:08 time: 0.3761 data_time: 0.0212 memory: 5826 grad_norm: 2.8870 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6641 loss: 2.6641 2022/10/07 11:48:33 - mmengine - INFO - Epoch(train) [21][1600/2119] lr: 4.0000e-02 eta: 1 day, 1:48:00 time: 0.3283 data_time: 0.0229 memory: 5826 grad_norm: 2.8739 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9790 loss: 2.9790 2022/10/07 11:48:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 11:48:40 - mmengine - INFO - Epoch(train) [21][1620/2119] lr: 4.0000e-02 eta: 1 day, 1:47:53 time: 0.3383 data_time: 0.0181 memory: 5826 grad_norm: 2.8799 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8199 loss: 2.8199 2022/10/07 11:48:46 - mmengine - INFO - Epoch(train) [21][1640/2119] lr: 4.0000e-02 eta: 1 day, 1:47:45 time: 0.3328 data_time: 0.0241 memory: 5826 grad_norm: 2.8792 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.6595 loss: 2.6595 2022/10/07 11:48:54 - mmengine - INFO - Epoch(train) [21][1660/2119] lr: 4.0000e-02 eta: 1 day, 1:47:44 time: 0.3834 data_time: 0.0223 memory: 5826 grad_norm: 2.8783 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 3.0219 loss: 3.0219 2022/10/07 11:49:00 - mmengine - INFO - Epoch(train) [21][1680/2119] lr: 4.0000e-02 eta: 1 day, 1:47:34 time: 0.3149 data_time: 0.0201 memory: 5826 grad_norm: 2.8702 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9472 loss: 2.9472 2022/10/07 11:49:07 - mmengine - INFO - Epoch(train) [21][1700/2119] lr: 4.0000e-02 eta: 1 day, 1:47:27 time: 0.3333 data_time: 0.0214 memory: 5826 grad_norm: 2.8910 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8270 loss: 2.8270 2022/10/07 11:49:14 - mmengine - INFO - Epoch(train) [21][1720/2119] lr: 4.0000e-02 eta: 1 day, 1:47:24 time: 0.3693 data_time: 0.0171 memory: 5826 grad_norm: 2.8833 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8045 loss: 2.8045 2022/10/07 11:49:21 - mmengine - INFO - Epoch(train) [21][1740/2119] lr: 4.0000e-02 eta: 1 day, 1:47:18 time: 0.3479 data_time: 0.0214 memory: 5826 grad_norm: 2.9114 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7017 loss: 2.7017 2022/10/07 11:49:29 - mmengine - INFO - Epoch(train) [21][1760/2119] lr: 4.0000e-02 eta: 1 day, 1:47:14 time: 0.3593 data_time: 0.0212 memory: 5826 grad_norm: 2.9044 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7823 loss: 2.7823 2022/10/07 11:49:36 - mmengine - INFO - Epoch(train) [21][1780/2119] lr: 4.0000e-02 eta: 1 day, 1:47:09 time: 0.3561 data_time: 0.0211 memory: 5826 grad_norm: 2.8593 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6116 loss: 2.6116 2022/10/07 11:49:42 - mmengine - INFO - Epoch(train) [21][1800/2119] lr: 4.0000e-02 eta: 1 day, 1:47:01 time: 0.3321 data_time: 0.0226 memory: 5826 grad_norm: 2.8841 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5729 loss: 2.5729 2022/10/07 11:49:49 - mmengine - INFO - Epoch(train) [21][1820/2119] lr: 4.0000e-02 eta: 1 day, 1:46:53 time: 0.3297 data_time: 0.0213 memory: 5826 grad_norm: 2.8625 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7169 loss: 2.7169 2022/10/07 11:50:01 - mmengine - INFO - Epoch(train) [21][1840/2119] lr: 4.0000e-02 eta: 1 day, 1:47:20 time: 0.6131 data_time: 0.0254 memory: 5826 grad_norm: 2.9256 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8013 loss: 2.8013 2022/10/07 11:50:08 - mmengine - INFO - Epoch(train) [21][1860/2119] lr: 4.0000e-02 eta: 1 day, 1:47:12 time: 0.3261 data_time: 0.0246 memory: 5826 grad_norm: 2.9223 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7122 loss: 2.7122 2022/10/07 11:50:27 - mmengine - INFO - Epoch(train) [21][1880/2119] lr: 4.0000e-02 eta: 1 day, 1:48:20 time: 0.9426 data_time: 0.6804 memory: 5826 grad_norm: 2.9659 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.0199 loss: 3.0199 2022/10/07 11:50:31 - mmengine - INFO - Epoch(train) [21][1900/2119] lr: 4.0000e-02 eta: 1 day, 1:48:01 time: 0.2466 data_time: 0.0257 memory: 5826 grad_norm: 2.9207 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7334 loss: 2.7334 2022/10/07 11:50:38 - mmengine - INFO - Epoch(train) [21][1920/2119] lr: 4.0000e-02 eta: 1 day, 1:47:53 time: 0.3280 data_time: 0.0189 memory: 5826 grad_norm: 2.8862 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.0425 loss: 3.0425 2022/10/07 11:50:45 - mmengine - INFO - Epoch(train) [21][1940/2119] lr: 4.0000e-02 eta: 1 day, 1:47:47 time: 0.3482 data_time: 0.0377 memory: 5826 grad_norm: 2.8605 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5768 loss: 2.5768 2022/10/07 11:50:52 - mmengine - INFO - Epoch(train) [21][1960/2119] lr: 4.0000e-02 eta: 1 day, 1:47:39 time: 0.3260 data_time: 0.0222 memory: 5826 grad_norm: 2.8444 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8971 loss: 2.8971 2022/10/07 11:50:59 - mmengine - INFO - Epoch(train) [21][1980/2119] lr: 4.0000e-02 eta: 1 day, 1:47:36 time: 0.3740 data_time: 0.0241 memory: 5826 grad_norm: 2.8747 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6805 loss: 2.6805 2022/10/07 11:51:06 - mmengine - INFO - Epoch(train) [21][2000/2119] lr: 4.0000e-02 eta: 1 day, 1:47:32 time: 0.3590 data_time: 0.0229 memory: 5826 grad_norm: 2.9123 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7234 loss: 2.7234 2022/10/07 11:51:13 - mmengine - INFO - Epoch(train) [21][2020/2119] lr: 4.0000e-02 eta: 1 day, 1:47:23 time: 0.3232 data_time: 0.0240 memory: 5826 grad_norm: 2.8756 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6994 loss: 2.6994 2022/10/07 11:51:21 - mmengine - INFO - Epoch(train) [21][2040/2119] lr: 4.0000e-02 eta: 1 day, 1:47:27 time: 0.4221 data_time: 0.0175 memory: 5826 grad_norm: 2.8754 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7122 loss: 2.7122 2022/10/07 11:51:28 - mmengine - INFO - Epoch(train) [21][2060/2119] lr: 4.0000e-02 eta: 1 day, 1:47:18 time: 0.3256 data_time: 0.0193 memory: 5826 grad_norm: 2.8625 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7905 loss: 2.7905 2022/10/07 11:51:35 - mmengine - INFO - Epoch(train) [21][2080/2119] lr: 4.0000e-02 eta: 1 day, 1:47:17 time: 0.3856 data_time: 0.0214 memory: 5826 grad_norm: 2.8707 top1_acc: 0.1875 top5_acc: 0.7500 loss_cls: 2.9660 loss: 2.9660 2022/10/07 11:51:42 - mmengine - INFO - Epoch(train) [21][2100/2119] lr: 4.0000e-02 eta: 1 day, 1:47:07 time: 0.3151 data_time: 0.0210 memory: 5826 grad_norm: 2.8886 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8098 loss: 2.8098 2022/10/07 11:51:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 11:51:46 - mmengine - INFO - Epoch(train) [21][2119/2119] lr: 4.0000e-02 eta: 1 day, 1:47:07 time: 0.2506 data_time: 0.0211 memory: 5826 grad_norm: 2.9603 top1_acc: 0.2000 top5_acc: 0.3000 loss_cls: 3.1030 loss: 3.1030 2022/10/07 11:51:56 - mmengine - INFO - Epoch(train) [22][20/2119] lr: 4.0000e-02 eta: 1 day, 1:46:30 time: 0.4644 data_time: 0.1359 memory: 5826 grad_norm: 2.8971 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7747 loss: 2.7747 2022/10/07 11:52:03 - mmengine - INFO - Epoch(train) [22][40/2119] lr: 4.0000e-02 eta: 1 day, 1:46:23 time: 0.3419 data_time: 0.0157 memory: 5826 grad_norm: 2.8388 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6205 loss: 2.6205 2022/10/07 11:52:10 - mmengine - INFO - Epoch(train) [22][60/2119] lr: 4.0000e-02 eta: 1 day, 1:46:19 time: 0.3585 data_time: 0.0229 memory: 5826 grad_norm: 2.9914 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7545 loss: 2.7545 2022/10/07 11:52:17 - mmengine - INFO - Epoch(train) [22][80/2119] lr: 4.0000e-02 eta: 1 day, 1:46:13 time: 0.3457 data_time: 0.0261 memory: 5826 grad_norm: 2.8654 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6941 loss: 2.6941 2022/10/07 11:52:23 - mmengine - INFO - Epoch(train) [22][100/2119] lr: 4.0000e-02 eta: 1 day, 1:46:04 time: 0.3236 data_time: 0.0222 memory: 5826 grad_norm: 2.9591 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7191 loss: 2.7191 2022/10/07 11:52:30 - mmengine - INFO - Epoch(train) [22][120/2119] lr: 4.0000e-02 eta: 1 day, 1:45:59 time: 0.3558 data_time: 0.0215 memory: 5826 grad_norm: 2.9010 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7190 loss: 2.7190 2022/10/07 11:52:38 - mmengine - INFO - Epoch(train) [22][140/2119] lr: 4.0000e-02 eta: 1 day, 1:45:56 time: 0.3689 data_time: 0.0253 memory: 5826 grad_norm: 2.8894 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8110 loss: 2.8110 2022/10/07 11:52:45 - mmengine - INFO - Epoch(train) [22][160/2119] lr: 4.0000e-02 eta: 1 day, 1:45:52 time: 0.3639 data_time: 0.0199 memory: 5826 grad_norm: 2.9268 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6727 loss: 2.6727 2022/10/07 11:52:51 - mmengine - INFO - Epoch(train) [22][180/2119] lr: 4.0000e-02 eta: 1 day, 1:45:44 time: 0.3273 data_time: 0.0244 memory: 5826 grad_norm: 2.8970 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7400 loss: 2.7400 2022/10/07 11:52:58 - mmengine - INFO - Epoch(train) [22][200/2119] lr: 4.0000e-02 eta: 1 day, 1:45:37 time: 0.3421 data_time: 0.0227 memory: 5826 grad_norm: 2.9093 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5919 loss: 2.5919 2022/10/07 11:53:05 - mmengine - INFO - Epoch(train) [22][220/2119] lr: 4.0000e-02 eta: 1 day, 1:45:30 time: 0.3349 data_time: 0.0224 memory: 5826 grad_norm: 2.9112 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8376 loss: 2.8376 2022/10/07 11:53:11 - mmengine - INFO - Epoch(train) [22][240/2119] lr: 4.0000e-02 eta: 1 day, 1:45:20 time: 0.3086 data_time: 0.0206 memory: 5826 grad_norm: 2.8893 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6150 loss: 2.6150 2022/10/07 11:53:20 - mmengine - INFO - Epoch(train) [22][260/2119] lr: 4.0000e-02 eta: 1 day, 1:45:24 time: 0.4295 data_time: 0.0226 memory: 5826 grad_norm: 2.9393 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6107 loss: 2.6107 2022/10/07 11:53:26 - mmengine - INFO - Epoch(train) [22][280/2119] lr: 4.0000e-02 eta: 1 day, 1:45:15 time: 0.3210 data_time: 0.0193 memory: 5826 grad_norm: 2.9064 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7248 loss: 2.7248 2022/10/07 11:53:33 - mmengine - INFO - Epoch(train) [22][300/2119] lr: 4.0000e-02 eta: 1 day, 1:45:09 time: 0.3457 data_time: 0.0229 memory: 5826 grad_norm: 2.9158 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7331 loss: 2.7331 2022/10/07 11:53:40 - mmengine - INFO - Epoch(train) [22][320/2119] lr: 4.0000e-02 eta: 1 day, 1:45:04 time: 0.3535 data_time: 0.0196 memory: 5826 grad_norm: 2.9570 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7321 loss: 2.7321 2022/10/07 11:53:47 - mmengine - INFO - Epoch(train) [22][340/2119] lr: 4.0000e-02 eta: 1 day, 1:44:58 time: 0.3513 data_time: 0.0216 memory: 5826 grad_norm: 2.9380 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6154 loss: 2.6154 2022/10/07 11:53:54 - mmengine - INFO - Epoch(train) [22][360/2119] lr: 4.0000e-02 eta: 1 day, 1:44:53 time: 0.3505 data_time: 0.0182 memory: 5826 grad_norm: 2.9132 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5534 loss: 2.5534 2022/10/07 11:54:01 - mmengine - INFO - Epoch(train) [22][380/2119] lr: 4.0000e-02 eta: 1 day, 1:44:46 time: 0.3368 data_time: 0.0235 memory: 5826 grad_norm: 2.9135 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6296 loss: 2.6296 2022/10/07 11:54:08 - mmengine - INFO - Epoch(train) [22][400/2119] lr: 4.0000e-02 eta: 1 day, 1:44:39 time: 0.3375 data_time: 0.0196 memory: 5826 grad_norm: 2.8622 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8316 loss: 2.8316 2022/10/07 11:54:16 - mmengine - INFO - Epoch(train) [22][420/2119] lr: 4.0000e-02 eta: 1 day, 1:44:39 time: 0.4010 data_time: 0.0237 memory: 5826 grad_norm: 2.8557 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7519 loss: 2.7519 2022/10/07 11:54:22 - mmengine - INFO - Epoch(train) [22][440/2119] lr: 4.0000e-02 eta: 1 day, 1:44:29 time: 0.3118 data_time: 0.0278 memory: 5826 grad_norm: 2.9098 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6204 loss: 2.6204 2022/10/07 11:54:29 - mmengine - INFO - Epoch(train) [22][460/2119] lr: 4.0000e-02 eta: 1 day, 1:44:26 time: 0.3695 data_time: 0.0235 memory: 5826 grad_norm: 2.8992 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.9409 loss: 2.9409 2022/10/07 11:54:36 - mmengine - INFO - Epoch(train) [22][480/2119] lr: 4.0000e-02 eta: 1 day, 1:44:17 time: 0.3240 data_time: 0.0214 memory: 5826 grad_norm: 2.8837 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8889 loss: 2.8889 2022/10/07 11:54:43 - mmengine - INFO - Epoch(train) [22][500/2119] lr: 4.0000e-02 eta: 1 day, 1:44:14 time: 0.3649 data_time: 0.0209 memory: 5826 grad_norm: 2.8932 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7422 loss: 2.7422 2022/10/07 11:54:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 11:54:49 - mmengine - INFO - Epoch(train) [22][520/2119] lr: 4.0000e-02 eta: 1 day, 1:44:04 time: 0.3139 data_time: 0.0163 memory: 5826 grad_norm: 2.8969 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6552 loss: 2.6552 2022/10/07 11:54:56 - mmengine - INFO - Epoch(train) [22][540/2119] lr: 4.0000e-02 eta: 1 day, 1:43:56 time: 0.3304 data_time: 0.0279 memory: 5826 grad_norm: 2.9224 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7700 loss: 2.7700 2022/10/07 11:55:03 - mmengine - INFO - Epoch(train) [22][560/2119] lr: 4.0000e-02 eta: 1 day, 1:43:47 time: 0.3227 data_time: 0.0227 memory: 5826 grad_norm: 2.8981 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9101 loss: 2.9101 2022/10/07 11:55:10 - mmengine - INFO - Epoch(train) [22][580/2119] lr: 4.0000e-02 eta: 1 day, 1:43:43 time: 0.3617 data_time: 0.0264 memory: 5826 grad_norm: 2.9414 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8572 loss: 2.8572 2022/10/07 11:55:16 - mmengine - INFO - Epoch(train) [22][600/2119] lr: 4.0000e-02 eta: 1 day, 1:43:33 time: 0.3133 data_time: 0.0220 memory: 5826 grad_norm: 2.9071 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.1687 loss: 3.1687 2022/10/07 11:55:23 - mmengine - INFO - Epoch(train) [22][620/2119] lr: 4.0000e-02 eta: 1 day, 1:43:29 time: 0.3635 data_time: 0.0240 memory: 5826 grad_norm: 2.9185 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8097 loss: 2.8097 2022/10/07 11:55:30 - mmengine - INFO - Epoch(train) [22][640/2119] lr: 4.0000e-02 eta: 1 day, 1:43:22 time: 0.3346 data_time: 0.0223 memory: 5826 grad_norm: 2.9015 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7264 loss: 2.7264 2022/10/07 11:55:38 - mmengine - INFO - Epoch(train) [22][660/2119] lr: 4.0000e-02 eta: 1 day, 1:43:22 time: 0.3975 data_time: 0.0185 memory: 5826 grad_norm: 2.9213 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.9872 loss: 2.9872 2022/10/07 11:55:45 - mmengine - INFO - Epoch(train) [22][680/2119] lr: 4.0000e-02 eta: 1 day, 1:43:15 time: 0.3426 data_time: 0.0249 memory: 5826 grad_norm: 2.8828 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8184 loss: 2.8184 2022/10/07 11:55:51 - mmengine - INFO - Epoch(train) [22][700/2119] lr: 4.0000e-02 eta: 1 day, 1:43:08 time: 0.3352 data_time: 0.0220 memory: 5826 grad_norm: 2.8889 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.7239 loss: 2.7239 2022/10/07 11:55:59 - mmengine - INFO - Epoch(train) [22][720/2119] lr: 4.0000e-02 eta: 1 day, 1:43:04 time: 0.3621 data_time: 0.0240 memory: 5826 grad_norm: 2.9402 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9121 loss: 2.9121 2022/10/07 11:56:06 - mmengine - INFO - Epoch(train) [22][740/2119] lr: 4.0000e-02 eta: 1 day, 1:43:00 time: 0.3631 data_time: 0.0271 memory: 5826 grad_norm: 2.9392 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7776 loss: 2.7776 2022/10/07 11:56:12 - mmengine - INFO - Epoch(train) [22][760/2119] lr: 4.0000e-02 eta: 1 day, 1:42:48 time: 0.3005 data_time: 0.0225 memory: 5826 grad_norm: 2.9583 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8026 loss: 2.8026 2022/10/07 11:56:19 - mmengine - INFO - Epoch(train) [22][780/2119] lr: 4.0000e-02 eta: 1 day, 1:42:44 time: 0.3623 data_time: 0.0228 memory: 5826 grad_norm: 2.8496 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7180 loss: 2.7180 2022/10/07 11:56:25 - mmengine - INFO - Epoch(train) [22][800/2119] lr: 4.0000e-02 eta: 1 day, 1:42:34 time: 0.3088 data_time: 0.0212 memory: 5826 grad_norm: 2.8581 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9150 loss: 2.9150 2022/10/07 11:56:33 - mmengine - INFO - Epoch(train) [22][820/2119] lr: 4.0000e-02 eta: 1 day, 1:42:31 time: 0.3725 data_time: 0.0276 memory: 5826 grad_norm: 2.8482 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.0040 loss: 3.0040 2022/10/07 11:56:40 - mmengine - INFO - Epoch(train) [22][840/2119] lr: 4.0000e-02 eta: 1 day, 1:42:25 time: 0.3470 data_time: 0.0191 memory: 5826 grad_norm: 2.9075 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7572 loss: 2.7572 2022/10/07 11:56:47 - mmengine - INFO - Epoch(train) [22][860/2119] lr: 4.0000e-02 eta: 1 day, 1:42:23 time: 0.3742 data_time: 0.0185 memory: 5826 grad_norm: 2.9472 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9192 loss: 2.9192 2022/10/07 11:56:53 - mmengine - INFO - Epoch(train) [22][880/2119] lr: 4.0000e-02 eta: 1 day, 1:42:12 time: 0.3091 data_time: 0.0168 memory: 5826 grad_norm: 2.8702 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8925 loss: 2.8925 2022/10/07 11:57:01 - mmengine - INFO - Epoch(train) [22][900/2119] lr: 4.0000e-02 eta: 1 day, 1:42:08 time: 0.3661 data_time: 0.0245 memory: 5826 grad_norm: 2.9098 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6114 loss: 2.6114 2022/10/07 11:57:07 - mmengine - INFO - Epoch(train) [22][920/2119] lr: 4.0000e-02 eta: 1 day, 1:41:56 time: 0.2899 data_time: 0.0154 memory: 5826 grad_norm: 2.8967 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7651 loss: 2.7651 2022/10/07 11:57:14 - mmengine - INFO - Epoch(train) [22][940/2119] lr: 4.0000e-02 eta: 1 day, 1:41:51 time: 0.3594 data_time: 0.0211 memory: 5826 grad_norm: 2.8741 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9089 loss: 2.9089 2022/10/07 11:57:20 - mmengine - INFO - Epoch(train) [22][960/2119] lr: 4.0000e-02 eta: 1 day, 1:41:42 time: 0.3228 data_time: 0.0194 memory: 5826 grad_norm: 2.8957 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6682 loss: 2.6682 2022/10/07 11:57:28 - mmengine - INFO - Epoch(train) [22][980/2119] lr: 4.0000e-02 eta: 1 day, 1:41:39 time: 0.3674 data_time: 0.0250 memory: 5826 grad_norm: 2.9022 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0262 loss: 3.0262 2022/10/07 11:57:34 - mmengine - INFO - Epoch(train) [22][1000/2119] lr: 4.0000e-02 eta: 1 day, 1:41:28 time: 0.3032 data_time: 0.0216 memory: 5826 grad_norm: 2.8943 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6542 loss: 2.6542 2022/10/07 11:57:41 - mmengine - INFO - Epoch(train) [22][1020/2119] lr: 4.0000e-02 eta: 1 day, 1:41:25 time: 0.3699 data_time: 0.0252 memory: 5826 grad_norm: 2.9010 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7538 loss: 2.7538 2022/10/07 11:57:47 - mmengine - INFO - Epoch(train) [22][1040/2119] lr: 4.0000e-02 eta: 1 day, 1:41:16 time: 0.3195 data_time: 0.0161 memory: 5826 grad_norm: 2.8950 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6948 loss: 2.6948 2022/10/07 11:57:54 - mmengine - INFO - Epoch(train) [22][1060/2119] lr: 4.0000e-02 eta: 1 day, 1:41:08 time: 0.3307 data_time: 0.0229 memory: 5826 grad_norm: 2.9101 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7835 loss: 2.7835 2022/10/07 11:58:01 - mmengine - INFO - Epoch(train) [22][1080/2119] lr: 4.0000e-02 eta: 1 day, 1:41:01 time: 0.3388 data_time: 0.0178 memory: 5826 grad_norm: 2.8536 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9857 loss: 2.9857 2022/10/07 11:58:08 - mmengine - INFO - Epoch(train) [22][1100/2119] lr: 4.0000e-02 eta: 1 day, 1:40:59 time: 0.3798 data_time: 0.0234 memory: 5826 grad_norm: 2.8507 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8340 loss: 2.8340 2022/10/07 11:58:15 - mmengine - INFO - Epoch(train) [22][1120/2119] lr: 4.0000e-02 eta: 1 day, 1:40:48 time: 0.3083 data_time: 0.0173 memory: 5826 grad_norm: 2.8920 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0134 loss: 3.0134 2022/10/07 11:58:23 - mmengine - INFO - Epoch(train) [22][1140/2119] lr: 4.0000e-02 eta: 1 day, 1:40:49 time: 0.4064 data_time: 0.0215 memory: 5826 grad_norm: 2.9106 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6964 loss: 2.6964 2022/10/07 11:58:34 - mmengine - INFO - Epoch(train) [22][1160/2119] lr: 4.0000e-02 eta: 1 day, 1:41:07 time: 0.5442 data_time: 0.2354 memory: 5826 grad_norm: 2.8810 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6436 loss: 2.6436 2022/10/07 11:58:40 - mmengine - INFO - Epoch(train) [22][1180/2119] lr: 4.0000e-02 eta: 1 day, 1:40:56 time: 0.3042 data_time: 0.0241 memory: 5826 grad_norm: 2.9088 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.5019 loss: 2.5019 2022/10/07 11:58:47 - mmengine - INFO - Epoch(train) [22][1200/2119] lr: 4.0000e-02 eta: 1 day, 1:40:51 time: 0.3546 data_time: 0.0378 memory: 5826 grad_norm: 2.8942 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7230 loss: 2.7230 2022/10/07 11:58:54 - mmengine - INFO - Epoch(train) [22][1220/2119] lr: 4.0000e-02 eta: 1 day, 1:40:44 time: 0.3397 data_time: 0.0569 memory: 5826 grad_norm: 2.9353 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.8714 loss: 2.8714 2022/10/07 11:59:00 - mmengine - INFO - Epoch(train) [22][1240/2119] lr: 4.0000e-02 eta: 1 day, 1:40:36 time: 0.3271 data_time: 0.0816 memory: 5826 grad_norm: 2.9151 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7138 loss: 2.7138 2022/10/07 11:59:07 - mmengine - INFO - Epoch(train) [22][1260/2119] lr: 4.0000e-02 eta: 1 day, 1:40:30 time: 0.3439 data_time: 0.0937 memory: 5826 grad_norm: 2.8755 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6287 loss: 2.6287 2022/10/07 11:59:13 - mmengine - INFO - Epoch(train) [22][1280/2119] lr: 4.0000e-02 eta: 1 day, 1:40:20 time: 0.3122 data_time: 0.0491 memory: 5826 grad_norm: 2.9232 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8212 loss: 2.8212 2022/10/07 11:59:20 - mmengine - INFO - Epoch(train) [22][1300/2119] lr: 4.0000e-02 eta: 1 day, 1:40:12 time: 0.3374 data_time: 0.0740 memory: 5826 grad_norm: 2.8905 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6905 loss: 2.6905 2022/10/07 11:59:27 - mmengine - INFO - Epoch(train) [22][1320/2119] lr: 4.0000e-02 eta: 1 day, 1:40:08 time: 0.3597 data_time: 0.0142 memory: 5826 grad_norm: 2.9020 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5525 loss: 2.5525 2022/10/07 11:59:33 - mmengine - INFO - Epoch(train) [22][1340/2119] lr: 4.0000e-02 eta: 1 day, 1:39:57 time: 0.3043 data_time: 0.0266 memory: 5826 grad_norm: 2.8739 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8804 loss: 2.8804 2022/10/07 11:59:41 - mmengine - INFO - Epoch(train) [22][1360/2119] lr: 4.0000e-02 eta: 1 day, 1:39:56 time: 0.3887 data_time: 0.0127 memory: 5826 grad_norm: 2.8827 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7466 loss: 2.7466 2022/10/07 11:59:47 - mmengine - INFO - Epoch(train) [22][1380/2119] lr: 4.0000e-02 eta: 1 day, 1:39:46 time: 0.3110 data_time: 0.0250 memory: 5826 grad_norm: 2.8899 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7031 loss: 2.7031 2022/10/07 11:59:55 - mmengine - INFO - Epoch(train) [22][1400/2119] lr: 4.0000e-02 eta: 1 day, 1:39:46 time: 0.3977 data_time: 0.0189 memory: 5826 grad_norm: 2.9179 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6667 loss: 2.6667 2022/10/07 12:00:01 - mmengine - INFO - Epoch(train) [22][1420/2119] lr: 4.0000e-02 eta: 1 day, 1:39:34 time: 0.2943 data_time: 0.0238 memory: 5826 grad_norm: 2.9051 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7141 loss: 2.7141 2022/10/07 12:00:09 - mmengine - INFO - Epoch(train) [22][1440/2119] lr: 4.0000e-02 eta: 1 day, 1:39:32 time: 0.3829 data_time: 0.0245 memory: 5826 grad_norm: 2.8913 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5468 loss: 2.5468 2022/10/07 12:00:15 - mmengine - INFO - Epoch(train) [22][1460/2119] lr: 4.0000e-02 eta: 1 day, 1:39:21 time: 0.3015 data_time: 0.0214 memory: 5826 grad_norm: 2.9577 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7653 loss: 2.7653 2022/10/07 12:00:22 - mmengine - INFO - Epoch(train) [22][1480/2119] lr: 4.0000e-02 eta: 1 day, 1:39:16 time: 0.3533 data_time: 0.0255 memory: 5826 grad_norm: 2.9636 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6709 loss: 2.6709 2022/10/07 12:00:29 - mmengine - INFO - Epoch(train) [22][1500/2119] lr: 4.0000e-02 eta: 1 day, 1:39:09 time: 0.3393 data_time: 0.0212 memory: 5826 grad_norm: 2.8943 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7942 loss: 2.7942 2022/10/07 12:00:29 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 12:00:36 - mmengine - INFO - Epoch(train) [22][1520/2119] lr: 4.0000e-02 eta: 1 day, 1:39:06 time: 0.3755 data_time: 0.0189 memory: 5826 grad_norm: 2.9022 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8351 loss: 2.8351 2022/10/07 12:00:42 - mmengine - INFO - Epoch(train) [22][1540/2119] lr: 4.0000e-02 eta: 1 day, 1:38:55 time: 0.3053 data_time: 0.0244 memory: 5826 grad_norm: 2.8936 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7961 loss: 2.7961 2022/10/07 12:00:50 - mmengine - INFO - Epoch(train) [22][1560/2119] lr: 4.0000e-02 eta: 1 day, 1:38:51 time: 0.3618 data_time: 0.0290 memory: 5826 grad_norm: 2.9247 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8439 loss: 2.8439 2022/10/07 12:00:57 - mmengine - INFO - Epoch(train) [22][1580/2119] lr: 4.0000e-02 eta: 1 day, 1:38:46 time: 0.3574 data_time: 0.0276 memory: 5826 grad_norm: 2.9145 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5902 loss: 2.5902 2022/10/07 12:01:04 - mmengine - INFO - Epoch(train) [22][1600/2119] lr: 4.0000e-02 eta: 1 day, 1:38:40 time: 0.3423 data_time: 0.0256 memory: 5826 grad_norm: 2.9254 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.3943 loss: 2.3943 2022/10/07 12:01:11 - mmengine - INFO - Epoch(train) [22][1620/2119] lr: 4.0000e-02 eta: 1 day, 1:38:35 time: 0.3562 data_time: 0.0202 memory: 5826 grad_norm: 2.9107 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6068 loss: 2.6068 2022/10/07 12:01:17 - mmengine - INFO - Epoch(train) [22][1640/2119] lr: 4.0000e-02 eta: 1 day, 1:38:25 time: 0.3080 data_time: 0.0265 memory: 5826 grad_norm: 2.9179 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6358 loss: 2.6358 2022/10/07 12:01:24 - mmengine - INFO - Epoch(train) [22][1660/2119] lr: 4.0000e-02 eta: 1 day, 1:38:22 time: 0.3798 data_time: 0.0205 memory: 5826 grad_norm: 2.9521 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8183 loss: 2.8183 2022/10/07 12:01:31 - mmengine - INFO - Epoch(train) [22][1680/2119] lr: 4.0000e-02 eta: 1 day, 1:38:14 time: 0.3255 data_time: 0.0185 memory: 5826 grad_norm: 2.9509 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9175 loss: 2.9175 2022/10/07 12:01:38 - mmengine - INFO - Epoch(train) [22][1700/2119] lr: 4.0000e-02 eta: 1 day, 1:38:06 time: 0.3330 data_time: 0.0210 memory: 5826 grad_norm: 2.8865 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7893 loss: 2.7893 2022/10/07 12:01:44 - mmengine - INFO - Epoch(train) [22][1720/2119] lr: 4.0000e-02 eta: 1 day, 1:37:59 time: 0.3382 data_time: 0.0231 memory: 5826 grad_norm: 2.9254 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7013 loss: 2.7013 2022/10/07 12:01:51 - mmengine - INFO - Epoch(train) [22][1740/2119] lr: 4.0000e-02 eta: 1 day, 1:37:54 time: 0.3510 data_time: 0.0271 memory: 5826 grad_norm: 2.9336 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6954 loss: 2.6954 2022/10/07 12:01:58 - mmengine - INFO - Epoch(train) [22][1760/2119] lr: 4.0000e-02 eta: 1 day, 1:37:47 time: 0.3404 data_time: 0.0178 memory: 5826 grad_norm: 2.9079 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6956 loss: 2.6956 2022/10/07 12:02:05 - mmengine - INFO - Epoch(train) [22][1780/2119] lr: 4.0000e-02 eta: 1 day, 1:37:43 time: 0.3587 data_time: 0.0240 memory: 5826 grad_norm: 2.9341 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6380 loss: 2.6380 2022/10/07 12:02:11 - mmengine - INFO - Epoch(train) [22][1800/2119] lr: 4.0000e-02 eta: 1 day, 1:37:32 time: 0.3048 data_time: 0.0190 memory: 5826 grad_norm: 2.9540 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6306 loss: 2.6306 2022/10/07 12:02:19 - mmengine - INFO - Epoch(train) [22][1820/2119] lr: 4.0000e-02 eta: 1 day, 1:37:27 time: 0.3582 data_time: 0.0285 memory: 5826 grad_norm: 2.9474 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0211 loss: 3.0211 2022/10/07 12:02:25 - mmengine - INFO - Epoch(train) [22][1840/2119] lr: 4.0000e-02 eta: 1 day, 1:37:20 time: 0.3353 data_time: 0.0235 memory: 5826 grad_norm: 2.9409 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8682 loss: 2.8682 2022/10/07 12:02:32 - mmengine - INFO - Epoch(train) [22][1860/2119] lr: 4.0000e-02 eta: 1 day, 1:37:14 time: 0.3446 data_time: 0.0237 memory: 5826 grad_norm: 2.9427 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7866 loss: 2.7866 2022/10/07 12:02:39 - mmengine - INFO - Epoch(train) [22][1880/2119] lr: 4.0000e-02 eta: 1 day, 1:37:04 time: 0.3191 data_time: 0.0266 memory: 5826 grad_norm: 2.9194 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6312 loss: 2.6312 2022/10/07 12:02:45 - mmengine - INFO - Epoch(train) [22][1900/2119] lr: 4.0000e-02 eta: 1 day, 1:36:55 time: 0.3163 data_time: 0.0200 memory: 5826 grad_norm: 2.9225 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.0923 loss: 3.0923 2022/10/07 12:02:52 - mmengine - INFO - Epoch(train) [22][1920/2119] lr: 4.0000e-02 eta: 1 day, 1:36:49 time: 0.3434 data_time: 0.0222 memory: 5826 grad_norm: 2.9168 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1244 loss: 3.1244 2022/10/07 12:02:59 - mmengine - INFO - Epoch(train) [22][1940/2119] lr: 4.0000e-02 eta: 1 day, 1:36:42 time: 0.3431 data_time: 0.0242 memory: 5826 grad_norm: 2.9310 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6738 loss: 2.6738 2022/10/07 12:03:05 - mmengine - INFO - Epoch(train) [22][1960/2119] lr: 4.0000e-02 eta: 1 day, 1:36:35 time: 0.3329 data_time: 0.0244 memory: 5826 grad_norm: 2.9513 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6575 loss: 2.6575 2022/10/07 12:03:12 - mmengine - INFO - Epoch(train) [22][1980/2119] lr: 4.0000e-02 eta: 1 day, 1:36:27 time: 0.3316 data_time: 0.0249 memory: 5826 grad_norm: 2.8930 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9274 loss: 2.9274 2022/10/07 12:03:19 - mmengine - INFO - Epoch(train) [22][2000/2119] lr: 4.0000e-02 eta: 1 day, 1:36:20 time: 0.3361 data_time: 0.0194 memory: 5826 grad_norm: 2.8888 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8534 loss: 2.8534 2022/10/07 12:03:26 - mmengine - INFO - Epoch(train) [22][2020/2119] lr: 4.0000e-02 eta: 1 day, 1:36:15 time: 0.3566 data_time: 0.0249 memory: 5826 grad_norm: 2.9205 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.8560 loss: 2.8560 2022/10/07 12:03:31 - mmengine - INFO - Epoch(train) [22][2040/2119] lr: 4.0000e-02 eta: 1 day, 1:36:00 time: 0.2721 data_time: 0.0186 memory: 5826 grad_norm: 2.9325 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8701 loss: 2.8701 2022/10/07 12:03:38 - mmengine - INFO - Epoch(train) [22][2060/2119] lr: 4.0000e-02 eta: 1 day, 1:35:54 time: 0.3428 data_time: 0.0201 memory: 5826 grad_norm: 2.9475 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7810 loss: 2.7810 2022/10/07 12:03:45 - mmengine - INFO - Epoch(train) [22][2080/2119] lr: 4.0000e-02 eta: 1 day, 1:35:50 time: 0.3668 data_time: 0.0169 memory: 5826 grad_norm: 2.8932 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0054 loss: 3.0054 2022/10/07 12:03:53 - mmengine - INFO - Epoch(train) [22][2100/2119] lr: 4.0000e-02 eta: 1 day, 1:35:45 time: 0.3571 data_time: 0.0182 memory: 5826 grad_norm: 2.9374 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9091 loss: 2.9091 2022/10/07 12:03:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 12:03:58 - mmengine - INFO - Epoch(train) [22][2119/2119] lr: 4.0000e-02 eta: 1 day, 1:35:45 time: 0.2962 data_time: 0.0163 memory: 5826 grad_norm: 2.9295 top1_acc: 0.3000 top5_acc: 0.6000 loss_cls: 3.0956 loss: 3.0956 2022/10/07 12:04:08 - mmengine - INFO - Epoch(train) [23][20/2119] lr: 4.0000e-02 eta: 1 day, 1:35:08 time: 0.4563 data_time: 0.1286 memory: 5826 grad_norm: 2.8329 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7637 loss: 2.7637 2022/10/07 12:04:14 - mmengine - INFO - Epoch(train) [23][40/2119] lr: 4.0000e-02 eta: 1 day, 1:34:58 time: 0.3085 data_time: 0.0180 memory: 5826 grad_norm: 2.8467 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7321 loss: 2.7321 2022/10/07 12:04:21 - mmengine - INFO - Epoch(train) [23][60/2119] lr: 4.0000e-02 eta: 1 day, 1:34:54 time: 0.3632 data_time: 0.0340 memory: 5826 grad_norm: 2.9187 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7203 loss: 2.7203 2022/10/07 12:04:28 - mmengine - INFO - Epoch(train) [23][80/2119] lr: 4.0000e-02 eta: 1 day, 1:34:49 time: 0.3558 data_time: 0.0371 memory: 5826 grad_norm: 2.9118 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7767 loss: 2.7767 2022/10/07 12:04:34 - mmengine - INFO - Epoch(train) [23][100/2119] lr: 4.0000e-02 eta: 1 day, 1:34:38 time: 0.3039 data_time: 0.0306 memory: 5826 grad_norm: 2.9131 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7086 loss: 2.7086 2022/10/07 12:04:41 - mmengine - INFO - Epoch(train) [23][120/2119] lr: 4.0000e-02 eta: 1 day, 1:34:31 time: 0.3409 data_time: 0.0145 memory: 5826 grad_norm: 2.8929 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8457 loss: 2.8457 2022/10/07 12:04:48 - mmengine - INFO - Epoch(train) [23][140/2119] lr: 4.0000e-02 eta: 1 day, 1:34:23 time: 0.3294 data_time: 0.0219 memory: 5826 grad_norm: 2.8830 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5048 loss: 2.5048 2022/10/07 12:04:55 - mmengine - INFO - Epoch(train) [23][160/2119] lr: 4.0000e-02 eta: 1 day, 1:34:19 time: 0.3619 data_time: 0.0142 memory: 5826 grad_norm: 2.9096 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8300 loss: 2.8300 2022/10/07 12:05:02 - mmengine - INFO - Epoch(train) [23][180/2119] lr: 4.0000e-02 eta: 1 day, 1:34:12 time: 0.3426 data_time: 0.0221 memory: 5826 grad_norm: 2.8867 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6837 loss: 2.6837 2022/10/07 12:05:09 - mmengine - INFO - Epoch(train) [23][200/2119] lr: 4.0000e-02 eta: 1 day, 1:34:09 time: 0.3644 data_time: 0.0154 memory: 5826 grad_norm: 2.8875 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5249 loss: 2.5249 2022/10/07 12:05:17 - mmengine - INFO - Epoch(train) [23][220/2119] lr: 4.0000e-02 eta: 1 day, 1:34:09 time: 0.3985 data_time: 0.0222 memory: 5826 grad_norm: 2.9066 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4418 loss: 2.4418 2022/10/07 12:05:23 - mmengine - INFO - Epoch(train) [23][240/2119] lr: 4.0000e-02 eta: 1 day, 1:33:58 time: 0.3030 data_time: 0.0188 memory: 5826 grad_norm: 2.9567 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7784 loss: 2.7784 2022/10/07 12:05:31 - mmengine - INFO - Epoch(train) [23][260/2119] lr: 4.0000e-02 eta: 1 day, 1:33:55 time: 0.3785 data_time: 0.0234 memory: 5826 grad_norm: 2.9330 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8726 loss: 2.8726 2022/10/07 12:05:37 - mmengine - INFO - Epoch(train) [23][280/2119] lr: 4.0000e-02 eta: 1 day, 1:33:48 time: 0.3394 data_time: 0.0208 memory: 5826 grad_norm: 2.9010 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8038 loss: 2.8038 2022/10/07 12:05:44 - mmengine - INFO - Epoch(train) [23][300/2119] lr: 4.0000e-02 eta: 1 day, 1:33:43 time: 0.3496 data_time: 0.0253 memory: 5826 grad_norm: 2.8885 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8040 loss: 2.8040 2022/10/07 12:05:51 - mmengine - INFO - Epoch(train) [23][320/2119] lr: 4.0000e-02 eta: 1 day, 1:33:33 time: 0.3159 data_time: 0.0208 memory: 5826 grad_norm: 2.8627 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6939 loss: 2.6939 2022/10/07 12:05:58 - mmengine - INFO - Epoch(train) [23][340/2119] lr: 4.0000e-02 eta: 1 day, 1:33:28 time: 0.3506 data_time: 0.0233 memory: 5826 grad_norm: 2.9032 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9251 loss: 2.9251 2022/10/07 12:06:04 - mmengine - INFO - Epoch(train) [23][360/2119] lr: 4.0000e-02 eta: 1 day, 1:33:21 time: 0.3400 data_time: 0.0236 memory: 5826 grad_norm: 2.8327 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6137 loss: 2.6137 2022/10/07 12:06:12 - mmengine - INFO - Epoch(train) [23][380/2119] lr: 4.0000e-02 eta: 1 day, 1:33:20 time: 0.3929 data_time: 0.0211 memory: 5826 grad_norm: 2.9019 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6999 loss: 2.6999 2022/10/07 12:06:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 12:06:19 - mmengine - INFO - Epoch(train) [23][400/2119] lr: 4.0000e-02 eta: 1 day, 1:33:11 time: 0.3217 data_time: 0.0243 memory: 5826 grad_norm: 2.8764 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5789 loss: 2.5789 2022/10/07 12:06:26 - mmengine - INFO - Epoch(train) [23][420/2119] lr: 4.0000e-02 eta: 1 day, 1:33:06 time: 0.3541 data_time: 0.0230 memory: 5826 grad_norm: 2.8935 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9351 loss: 2.9351 2022/10/07 12:06:32 - mmengine - INFO - Epoch(train) [23][440/2119] lr: 4.0000e-02 eta: 1 day, 1:32:54 time: 0.2960 data_time: 0.0239 memory: 5826 grad_norm: 2.9171 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5838 loss: 2.5838 2022/10/07 12:06:40 - mmengine - INFO - Epoch(train) [23][460/2119] lr: 4.0000e-02 eta: 1 day, 1:32:57 time: 0.4183 data_time: 0.0241 memory: 5826 grad_norm: 2.9188 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6449 loss: 2.6449 2022/10/07 12:06:46 - mmengine - INFO - Epoch(train) [23][480/2119] lr: 4.0000e-02 eta: 1 day, 1:32:45 time: 0.2978 data_time: 0.0219 memory: 5826 grad_norm: 2.9384 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7155 loss: 2.7155 2022/10/07 12:06:53 - mmengine - INFO - Epoch(train) [23][500/2119] lr: 4.0000e-02 eta: 1 day, 1:32:40 time: 0.3541 data_time: 0.0179 memory: 5826 grad_norm: 2.9249 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7520 loss: 2.7520 2022/10/07 12:07:00 - mmengine - INFO - Epoch(train) [23][520/2119] lr: 4.0000e-02 eta: 1 day, 1:32:34 time: 0.3492 data_time: 0.0229 memory: 5826 grad_norm: 2.8998 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5344 loss: 2.5344 2022/10/07 12:07:08 - mmengine - INFO - Epoch(train) [23][540/2119] lr: 4.0000e-02 eta: 1 day, 1:32:32 time: 0.3802 data_time: 0.0217 memory: 5826 grad_norm: 2.9428 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6981 loss: 2.6981 2022/10/07 12:07:14 - mmengine - INFO - Epoch(train) [23][560/2119] lr: 4.0000e-02 eta: 1 day, 1:32:21 time: 0.2978 data_time: 0.0232 memory: 5826 grad_norm: 2.9500 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6733 loss: 2.6733 2022/10/07 12:07:21 - mmengine - INFO - Epoch(train) [23][580/2119] lr: 4.0000e-02 eta: 1 day, 1:32:18 time: 0.3753 data_time: 0.0245 memory: 5826 grad_norm: 2.9037 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.9966 loss: 2.9966 2022/10/07 12:07:27 - mmengine - INFO - Epoch(train) [23][600/2119] lr: 4.0000e-02 eta: 1 day, 1:32:05 time: 0.2908 data_time: 0.0163 memory: 5826 grad_norm: 2.9252 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6739 loss: 2.6739 2022/10/07 12:07:34 - mmengine - INFO - Epoch(train) [23][620/2119] lr: 4.0000e-02 eta: 1 day, 1:32:00 time: 0.3532 data_time: 0.0242 memory: 5826 grad_norm: 2.9190 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5801 loss: 2.5801 2022/10/07 12:07:41 - mmengine - INFO - Epoch(train) [23][640/2119] lr: 4.0000e-02 eta: 1 day, 1:31:52 time: 0.3267 data_time: 0.0184 memory: 5826 grad_norm: 2.9015 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5534 loss: 2.5534 2022/10/07 12:07:47 - mmengine - INFO - Epoch(train) [23][660/2119] lr: 4.0000e-02 eta: 1 day, 1:31:44 time: 0.3308 data_time: 0.0245 memory: 5826 grad_norm: 2.8865 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8772 loss: 2.8772 2022/10/07 12:07:54 - mmengine - INFO - Epoch(train) [23][680/2119] lr: 4.0000e-02 eta: 1 day, 1:31:36 time: 0.3305 data_time: 0.0239 memory: 5826 grad_norm: 2.8798 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5655 loss: 2.5655 2022/10/07 12:08:01 - mmengine - INFO - Epoch(train) [23][700/2119] lr: 4.0000e-02 eta: 1 day, 1:31:31 time: 0.3560 data_time: 0.0268 memory: 5826 grad_norm: 2.9035 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6711 loss: 2.6711 2022/10/07 12:08:08 - mmengine - INFO - Epoch(train) [23][720/2119] lr: 4.0000e-02 eta: 1 day, 1:31:24 time: 0.3372 data_time: 0.0204 memory: 5826 grad_norm: 2.8996 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6134 loss: 2.6134 2022/10/07 12:08:14 - mmengine - INFO - Epoch(train) [23][740/2119] lr: 4.0000e-02 eta: 1 day, 1:31:16 time: 0.3239 data_time: 0.0237 memory: 5826 grad_norm: 2.9810 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0501 loss: 3.0501 2022/10/07 12:08:22 - mmengine - INFO - Epoch(train) [23][760/2119] lr: 4.0000e-02 eta: 1 day, 1:31:14 time: 0.3881 data_time: 0.0235 memory: 5826 grad_norm: 2.9150 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9414 loss: 2.9414 2022/10/07 12:08:29 - mmengine - INFO - Epoch(train) [23][780/2119] lr: 4.0000e-02 eta: 1 day, 1:31:07 time: 0.3334 data_time: 0.0314 memory: 5826 grad_norm: 2.8421 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8250 loss: 2.8250 2022/10/07 12:08:36 - mmengine - INFO - Epoch(train) [23][800/2119] lr: 4.0000e-02 eta: 1 day, 1:31:03 time: 0.3627 data_time: 0.0209 memory: 5826 grad_norm: 2.9081 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6362 loss: 2.6362 2022/10/07 12:08:42 - mmengine - INFO - Epoch(train) [23][820/2119] lr: 4.0000e-02 eta: 1 day, 1:30:52 time: 0.3021 data_time: 0.0243 memory: 5826 grad_norm: 2.9366 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7957 loss: 2.7957 2022/10/07 12:08:49 - mmengine - INFO - Epoch(train) [23][840/2119] lr: 4.0000e-02 eta: 1 day, 1:30:45 time: 0.3408 data_time: 0.0235 memory: 5826 grad_norm: 2.9120 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6979 loss: 2.6979 2022/10/07 12:08:55 - mmengine - INFO - Epoch(train) [23][860/2119] lr: 4.0000e-02 eta: 1 day, 1:30:36 time: 0.3235 data_time: 0.0313 memory: 5826 grad_norm: 2.9519 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6508 loss: 2.6508 2022/10/07 12:09:03 - mmengine - INFO - Epoch(train) [23][880/2119] lr: 4.0000e-02 eta: 1 day, 1:30:33 time: 0.3672 data_time: 0.0205 memory: 5826 grad_norm: 2.8965 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6574 loss: 2.6574 2022/10/07 12:09:10 - mmengine - INFO - Epoch(train) [23][900/2119] lr: 4.0000e-02 eta: 1 day, 1:30:28 time: 0.3554 data_time: 0.0227 memory: 5826 grad_norm: 2.9273 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8465 loss: 2.8465 2022/10/07 12:09:17 - mmengine - INFO - Epoch(train) [23][920/2119] lr: 4.0000e-02 eta: 1 day, 1:30:21 time: 0.3420 data_time: 0.0232 memory: 5826 grad_norm: 2.9458 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6922 loss: 2.6922 2022/10/07 12:09:24 - mmengine - INFO - Epoch(train) [23][940/2119] lr: 4.0000e-02 eta: 1 day, 1:30:17 time: 0.3619 data_time: 0.0189 memory: 5826 grad_norm: 2.8956 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6607 loss: 2.6607 2022/10/07 12:09:30 - mmengine - INFO - Epoch(train) [23][960/2119] lr: 4.0000e-02 eta: 1 day, 1:30:08 time: 0.3198 data_time: 0.0197 memory: 5826 grad_norm: 2.8800 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7444 loss: 2.7444 2022/10/07 12:09:37 - mmengine - INFO - Epoch(train) [23][980/2119] lr: 4.0000e-02 eta: 1 day, 1:30:03 time: 0.3573 data_time: 0.0299 memory: 5826 grad_norm: 2.9649 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8413 loss: 2.8413 2022/10/07 12:09:44 - mmengine - INFO - Epoch(train) [23][1000/2119] lr: 4.0000e-02 eta: 1 day, 1:29:53 time: 0.3087 data_time: 0.0167 memory: 5826 grad_norm: 2.8795 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9210 loss: 2.9210 2022/10/07 12:09:51 - mmengine - INFO - Epoch(train) [23][1020/2119] lr: 4.0000e-02 eta: 1 day, 1:29:47 time: 0.3490 data_time: 0.0227 memory: 5826 grad_norm: 2.9198 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9716 loss: 2.9716 2022/10/07 12:09:57 - mmengine - INFO - Epoch(train) [23][1040/2119] lr: 4.0000e-02 eta: 1 day, 1:29:38 time: 0.3186 data_time: 0.0243 memory: 5826 grad_norm: 2.9471 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7608 loss: 2.7608 2022/10/07 12:10:04 - mmengine - INFO - Epoch(train) [23][1060/2119] lr: 4.0000e-02 eta: 1 day, 1:29:33 time: 0.3548 data_time: 0.0234 memory: 5826 grad_norm: 2.9029 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7105 loss: 2.7105 2022/10/07 12:10:10 - mmengine - INFO - Epoch(train) [23][1080/2119] lr: 4.0000e-02 eta: 1 day, 1:29:24 time: 0.3199 data_time: 0.0158 memory: 5826 grad_norm: 2.9148 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0222 loss: 3.0222 2022/10/07 12:10:18 - mmengine - INFO - Epoch(train) [23][1100/2119] lr: 4.0000e-02 eta: 1 day, 1:29:24 time: 0.4058 data_time: 0.0254 memory: 5826 grad_norm: 2.9561 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7987 loss: 2.7987 2022/10/07 12:10:25 - mmengine - INFO - Epoch(train) [23][1120/2119] lr: 4.0000e-02 eta: 1 day, 1:29:14 time: 0.3073 data_time: 0.0155 memory: 5826 grad_norm: 2.9018 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8895 loss: 2.8895 2022/10/07 12:10:32 - mmengine - INFO - Epoch(train) [23][1140/2119] lr: 4.0000e-02 eta: 1 day, 1:29:08 time: 0.3510 data_time: 0.0224 memory: 5826 grad_norm: 2.9320 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7660 loss: 2.7660 2022/10/07 12:10:38 - mmengine - INFO - Epoch(train) [23][1160/2119] lr: 4.0000e-02 eta: 1 day, 1:29:00 time: 0.3287 data_time: 0.0224 memory: 5826 grad_norm: 2.9423 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7805 loss: 2.7805 2022/10/07 12:10:45 - mmengine - INFO - Epoch(train) [23][1180/2119] lr: 4.0000e-02 eta: 1 day, 1:28:55 time: 0.3547 data_time: 0.0251 memory: 5826 grad_norm: 2.9460 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7789 loss: 2.7789 2022/10/07 12:10:52 - mmengine - INFO - Epoch(train) [23][1200/2119] lr: 4.0000e-02 eta: 1 day, 1:28:45 time: 0.3092 data_time: 0.0216 memory: 5826 grad_norm: 2.9300 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6978 loss: 2.6978 2022/10/07 12:10:59 - mmengine - INFO - Epoch(train) [23][1220/2119] lr: 4.0000e-02 eta: 1 day, 1:28:43 time: 0.3817 data_time: 0.0226 memory: 5826 grad_norm: 2.8822 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9339 loss: 2.9339 2022/10/07 12:11:05 - mmengine - INFO - Epoch(train) [23][1240/2119] lr: 4.0000e-02 eta: 1 day, 1:28:33 time: 0.3132 data_time: 0.0213 memory: 5826 grad_norm: 2.9243 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.6663 loss: 2.6663 2022/10/07 12:11:13 - mmengine - INFO - Epoch(train) [23][1260/2119] lr: 4.0000e-02 eta: 1 day, 1:28:29 time: 0.3601 data_time: 0.0254 memory: 5826 grad_norm: 2.8932 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 3.0329 loss: 3.0329 2022/10/07 12:11:20 - mmengine - INFO - Epoch(train) [23][1280/2119] lr: 4.0000e-02 eta: 1 day, 1:28:23 time: 0.3513 data_time: 0.0162 memory: 5826 grad_norm: 2.9401 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.9028 loss: 2.9028 2022/10/07 12:11:26 - mmengine - INFO - Epoch(train) [23][1300/2119] lr: 4.0000e-02 eta: 1 day, 1:28:17 time: 0.3416 data_time: 0.0229 memory: 5826 grad_norm: 2.9046 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6558 loss: 2.6558 2022/10/07 12:11:32 - mmengine - INFO - Epoch(train) [23][1320/2119] lr: 4.0000e-02 eta: 1 day, 1:28:05 time: 0.2970 data_time: 0.0230 memory: 5826 grad_norm: 2.9361 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8755 loss: 2.8755 2022/10/07 12:11:39 - mmengine - INFO - Epoch(train) [23][1340/2119] lr: 4.0000e-02 eta: 1 day, 1:27:57 time: 0.3329 data_time: 0.0258 memory: 5826 grad_norm: 2.9173 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7912 loss: 2.7912 2022/10/07 12:11:47 - mmengine - INFO - Epoch(train) [23][1360/2119] lr: 4.0000e-02 eta: 1 day, 1:27:54 time: 0.3706 data_time: 0.0201 memory: 5826 grad_norm: 2.9370 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7129 loss: 2.7129 2022/10/07 12:11:53 - mmengine - INFO - Epoch(train) [23][1380/2119] lr: 4.0000e-02 eta: 1 day, 1:27:43 time: 0.3006 data_time: 0.0216 memory: 5826 grad_norm: 2.9354 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7072 loss: 2.7072 2022/10/07 12:11:54 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 12:12:00 - mmengine - INFO - Epoch(train) [23][1400/2119] lr: 4.0000e-02 eta: 1 day, 1:27:39 time: 0.3609 data_time: 0.0218 memory: 5826 grad_norm: 2.9601 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8076 loss: 2.8076 2022/10/07 12:12:07 - mmengine - INFO - Epoch(train) [23][1420/2119] lr: 4.0000e-02 eta: 1 day, 1:27:32 time: 0.3404 data_time: 0.0250 memory: 5826 grad_norm: 2.9139 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6665 loss: 2.6665 2022/10/07 12:12:14 - mmengine - INFO - Epoch(train) [23][1440/2119] lr: 4.0000e-02 eta: 1 day, 1:27:28 time: 0.3664 data_time: 0.0282 memory: 5826 grad_norm: 2.9582 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8629 loss: 2.8629 2022/10/07 12:12:21 - mmengine - INFO - Epoch(train) [23][1460/2119] lr: 4.0000e-02 eta: 1 day, 1:27:21 time: 0.3349 data_time: 0.0212 memory: 5826 grad_norm: 2.9026 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8954 loss: 2.8954 2022/10/07 12:12:28 - mmengine - INFO - Epoch(train) [23][1480/2119] lr: 4.0000e-02 eta: 1 day, 1:27:16 time: 0.3573 data_time: 0.0238 memory: 5826 grad_norm: 2.9725 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6711 loss: 2.6711 2022/10/07 12:12:34 - mmengine - INFO - Epoch(train) [23][1500/2119] lr: 4.0000e-02 eta: 1 day, 1:27:06 time: 0.3101 data_time: 0.0245 memory: 5826 grad_norm: 2.8696 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9452 loss: 2.9452 2022/10/07 12:12:41 - mmengine - INFO - Epoch(train) [23][1520/2119] lr: 4.0000e-02 eta: 1 day, 1:27:00 time: 0.3505 data_time: 0.0202 memory: 5826 grad_norm: 2.8963 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6450 loss: 2.6450 2022/10/07 12:12:48 - mmengine - INFO - Epoch(train) [23][1540/2119] lr: 4.0000e-02 eta: 1 day, 1:26:53 time: 0.3373 data_time: 0.0249 memory: 5826 grad_norm: 2.9427 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8324 loss: 2.8324 2022/10/07 12:12:54 - mmengine - INFO - Epoch(train) [23][1560/2119] lr: 4.0000e-02 eta: 1 day, 1:26:44 time: 0.3188 data_time: 0.0194 memory: 5826 grad_norm: 2.9014 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7365 loss: 2.7365 2022/10/07 12:13:01 - mmengine - INFO - Epoch(train) [23][1580/2119] lr: 4.0000e-02 eta: 1 day, 1:26:38 time: 0.3485 data_time: 0.0220 memory: 5826 grad_norm: 2.8823 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5046 loss: 2.5046 2022/10/07 12:13:08 - mmengine - INFO - Epoch(train) [23][1600/2119] lr: 4.0000e-02 eta: 1 day, 1:26:32 time: 0.3494 data_time: 0.0209 memory: 5826 grad_norm: 2.9049 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.8638 loss: 2.8638 2022/10/07 12:13:15 - mmengine - INFO - Epoch(train) [23][1620/2119] lr: 4.0000e-02 eta: 1 day, 1:26:24 time: 0.3251 data_time: 0.0243 memory: 5826 grad_norm: 2.8761 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8478 loss: 2.8478 2022/10/07 12:13:22 - mmengine - INFO - Epoch(train) [23][1640/2119] lr: 4.0000e-02 eta: 1 day, 1:26:19 time: 0.3581 data_time: 0.0167 memory: 5826 grad_norm: 2.8957 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7963 loss: 2.7963 2022/10/07 12:13:30 - mmengine - INFO - Epoch(train) [23][1660/2119] lr: 4.0000e-02 eta: 1 day, 1:26:21 time: 0.4119 data_time: 0.0228 memory: 5826 grad_norm: 2.9232 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5726 loss: 2.5726 2022/10/07 12:13:36 - mmengine - INFO - Epoch(train) [23][1680/2119] lr: 4.0000e-02 eta: 1 day, 1:26:12 time: 0.3264 data_time: 0.0239 memory: 5826 grad_norm: 2.9404 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8528 loss: 2.8528 2022/10/07 12:13:45 - mmengine - INFO - Epoch(train) [23][1700/2119] lr: 4.0000e-02 eta: 1 day, 1:26:14 time: 0.4184 data_time: 0.0178 memory: 5826 grad_norm: 2.9122 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7429 loss: 2.7429 2022/10/07 12:13:51 - mmengine - INFO - Epoch(train) [23][1720/2119] lr: 4.0000e-02 eta: 1 day, 1:26:02 time: 0.2914 data_time: 0.0221 memory: 5826 grad_norm: 2.9071 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8070 loss: 2.8070 2022/10/07 12:13:58 - mmengine - INFO - Epoch(train) [23][1740/2119] lr: 4.0000e-02 eta: 1 day, 1:25:57 time: 0.3538 data_time: 0.0233 memory: 5826 grad_norm: 2.9428 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8194 loss: 2.8194 2022/10/07 12:14:04 - mmengine - INFO - Epoch(train) [23][1760/2119] lr: 4.0000e-02 eta: 1 day, 1:25:48 time: 0.3185 data_time: 0.0165 memory: 5826 grad_norm: 2.9059 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0153 loss: 3.0153 2022/10/07 12:14:12 - mmengine - INFO - Epoch(train) [23][1780/2119] lr: 4.0000e-02 eta: 1 day, 1:25:45 time: 0.3751 data_time: 0.0202 memory: 5826 grad_norm: 2.8604 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8638 loss: 2.8638 2022/10/07 12:14:18 - mmengine - INFO - Epoch(train) [23][1800/2119] lr: 4.0000e-02 eta: 1 day, 1:25:36 time: 0.3176 data_time: 0.0202 memory: 5826 grad_norm: 2.8440 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6303 loss: 2.6303 2022/10/07 12:14:25 - mmengine - INFO - Epoch(train) [23][1820/2119] lr: 4.0000e-02 eta: 1 day, 1:25:32 time: 0.3676 data_time: 0.0204 memory: 5826 grad_norm: 2.9506 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5874 loss: 2.5874 2022/10/07 12:14:32 - mmengine - INFO - Epoch(train) [23][1840/2119] lr: 4.0000e-02 eta: 1 day, 1:25:25 time: 0.3353 data_time: 0.0194 memory: 5826 grad_norm: 2.9273 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8221 loss: 2.8221 2022/10/07 12:14:40 - mmengine - INFO - Epoch(train) [23][1860/2119] lr: 4.0000e-02 eta: 1 day, 1:25:22 time: 0.3733 data_time: 0.0239 memory: 5826 grad_norm: 2.9149 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6806 loss: 2.6806 2022/10/07 12:14:46 - mmengine - INFO - Epoch(train) [23][1880/2119] lr: 4.0000e-02 eta: 1 day, 1:25:15 time: 0.3415 data_time: 0.0248 memory: 5826 grad_norm: 2.8850 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8325 loss: 2.8325 2022/10/07 12:14:53 - mmengine - INFO - Epoch(train) [23][1900/2119] lr: 4.0000e-02 eta: 1 day, 1:25:07 time: 0.3280 data_time: 0.0269 memory: 5826 grad_norm: 2.9425 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 3.0091 loss: 3.0091 2022/10/07 12:15:00 - mmengine - INFO - Epoch(train) [23][1920/2119] lr: 4.0000e-02 eta: 1 day, 1:25:01 time: 0.3457 data_time: 0.0149 memory: 5826 grad_norm: 2.8922 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9532 loss: 2.9532 2022/10/07 12:15:08 - mmengine - INFO - Epoch(train) [23][1940/2119] lr: 4.0000e-02 eta: 1 day, 1:24:59 time: 0.3864 data_time: 0.0331 memory: 5826 grad_norm: 2.9229 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8244 loss: 2.8244 2022/10/07 12:15:13 - mmengine - INFO - Epoch(train) [23][1960/2119] lr: 4.0000e-02 eta: 1 day, 1:24:47 time: 0.2926 data_time: 0.0234 memory: 5826 grad_norm: 2.9473 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9118 loss: 2.9118 2022/10/07 12:15:21 - mmengine - INFO - Epoch(train) [23][1980/2119] lr: 4.0000e-02 eta: 1 day, 1:24:44 time: 0.3708 data_time: 0.0260 memory: 5826 grad_norm: 2.8755 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7667 loss: 2.7667 2022/10/07 12:15:27 - mmengine - INFO - Epoch(train) [23][2000/2119] lr: 4.0000e-02 eta: 1 day, 1:24:33 time: 0.3073 data_time: 0.0245 memory: 5826 grad_norm: 2.9181 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7800 loss: 2.7800 2022/10/07 12:15:35 - mmengine - INFO - Epoch(train) [23][2020/2119] lr: 4.0000e-02 eta: 1 day, 1:24:31 time: 0.3783 data_time: 0.0232 memory: 5826 grad_norm: 2.9202 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8339 loss: 2.8339 2022/10/07 12:15:41 - mmengine - INFO - Epoch(train) [23][2040/2119] lr: 4.0000e-02 eta: 1 day, 1:24:23 time: 0.3303 data_time: 0.0193 memory: 5826 grad_norm: 2.9122 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8549 loss: 2.8549 2022/10/07 12:15:48 - mmengine - INFO - Epoch(train) [23][2060/2119] lr: 4.0000e-02 eta: 1 day, 1:24:19 time: 0.3616 data_time: 0.0256 memory: 5826 grad_norm: 2.8803 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4546 loss: 2.4546 2022/10/07 12:15:55 - mmengine - INFO - Epoch(train) [23][2080/2119] lr: 4.0000e-02 eta: 1 day, 1:24:11 time: 0.3323 data_time: 0.0155 memory: 5826 grad_norm: 2.9466 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8958 loss: 2.8958 2022/10/07 12:16:03 - mmengine - INFO - Epoch(train) [23][2100/2119] lr: 4.0000e-02 eta: 1 day, 1:24:09 time: 0.3875 data_time: 0.0221 memory: 5826 grad_norm: 2.8754 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7218 loss: 2.7218 2022/10/07 12:16:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 12:16:08 - mmengine - INFO - Epoch(train) [23][2119/2119] lr: 4.0000e-02 eta: 1 day, 1:24:09 time: 0.2822 data_time: 0.0182 memory: 5826 grad_norm: 2.9318 top1_acc: 0.4000 top5_acc: 0.7000 loss_cls: 2.6840 loss: 2.6840 2022/10/07 12:16:18 - mmengine - INFO - Epoch(train) [24][20/2119] lr: 4.0000e-02 eta: 1 day, 1:23:36 time: 0.4819 data_time: 0.1251 memory: 5826 grad_norm: 2.9369 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6701 loss: 2.6701 2022/10/07 12:16:25 - mmengine - INFO - Epoch(train) [24][40/2119] lr: 4.0000e-02 eta: 1 day, 1:23:30 time: 0.3459 data_time: 0.0192 memory: 5826 grad_norm: 2.8509 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7709 loss: 2.7709 2022/10/07 12:16:32 - mmengine - INFO - Epoch(train) [24][60/2119] lr: 4.0000e-02 eta: 1 day, 1:23:24 time: 0.3447 data_time: 0.0241 memory: 5826 grad_norm: 2.9399 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8679 loss: 2.8679 2022/10/07 12:16:38 - mmengine - INFO - Epoch(train) [24][80/2119] lr: 4.0000e-02 eta: 1 day, 1:23:13 time: 0.3035 data_time: 0.0261 memory: 5826 grad_norm: 2.8966 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.9109 loss: 2.9109 2022/10/07 12:16:46 - mmengine - INFO - Epoch(train) [24][100/2119] lr: 4.0000e-02 eta: 1 day, 1:23:11 time: 0.3868 data_time: 0.0237 memory: 5826 grad_norm: 2.9664 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8630 loss: 2.8630 2022/10/07 12:16:52 - mmengine - INFO - Epoch(train) [24][120/2119] lr: 4.0000e-02 eta: 1 day, 1:23:02 time: 0.3111 data_time: 0.0190 memory: 5826 grad_norm: 2.9210 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5299 loss: 2.5299 2022/10/07 12:16:59 - mmengine - INFO - Epoch(train) [24][140/2119] lr: 4.0000e-02 eta: 1 day, 1:22:59 time: 0.3780 data_time: 0.0213 memory: 5826 grad_norm: 2.9420 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6199 loss: 2.6199 2022/10/07 12:17:06 - mmengine - INFO - Epoch(train) [24][160/2119] lr: 4.0000e-02 eta: 1 day, 1:22:51 time: 0.3253 data_time: 0.0228 memory: 5826 grad_norm: 2.9192 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7539 loss: 2.7539 2022/10/07 12:17:13 - mmengine - INFO - Epoch(train) [24][180/2119] lr: 4.0000e-02 eta: 1 day, 1:22:45 time: 0.3483 data_time: 0.0200 memory: 5826 grad_norm: 2.9137 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6373 loss: 2.6373 2022/10/07 12:17:19 - mmengine - INFO - Epoch(train) [24][200/2119] lr: 4.0000e-02 eta: 1 day, 1:22:35 time: 0.3119 data_time: 0.0183 memory: 5826 grad_norm: 2.9551 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8640 loss: 2.8640 2022/10/07 12:17:26 - mmengine - INFO - Epoch(train) [24][220/2119] lr: 4.0000e-02 eta: 1 day, 1:22:30 time: 0.3585 data_time: 0.0194 memory: 5826 grad_norm: 2.9495 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6957 loss: 2.6957 2022/10/07 12:17:32 - mmengine - INFO - Epoch(train) [24][240/2119] lr: 4.0000e-02 eta: 1 day, 1:22:19 time: 0.3017 data_time: 0.0227 memory: 5826 grad_norm: 2.9716 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6570 loss: 2.6570 2022/10/07 12:17:40 - mmengine - INFO - Epoch(train) [24][260/2119] lr: 4.0000e-02 eta: 1 day, 1:22:16 time: 0.3704 data_time: 0.0248 memory: 5826 grad_norm: 2.8794 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0350 loss: 3.0350 2022/10/07 12:17:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 12:17:46 - mmengine - INFO - Epoch(train) [24][280/2119] lr: 4.0000e-02 eta: 1 day, 1:22:07 time: 0.3243 data_time: 0.0197 memory: 5826 grad_norm: 2.8776 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6151 loss: 2.6151 2022/10/07 12:17:53 - mmengine - INFO - Epoch(train) [24][300/2119] lr: 4.0000e-02 eta: 1 day, 1:22:01 time: 0.3480 data_time: 0.0215 memory: 5826 grad_norm: 2.9756 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6457 loss: 2.6457 2022/10/07 12:18:00 - mmengine - INFO - Epoch(train) [24][320/2119] lr: 4.0000e-02 eta: 1 day, 1:21:57 time: 0.3624 data_time: 0.0166 memory: 5826 grad_norm: 2.9362 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.9386 loss: 2.9386 2022/10/07 12:18:08 - mmengine - INFO - Epoch(train) [24][340/2119] lr: 4.0000e-02 eta: 1 day, 1:21:53 time: 0.3645 data_time: 0.0166 memory: 5826 grad_norm: 2.9110 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.7959 loss: 2.7959 2022/10/07 12:18:14 - mmengine - INFO - Epoch(train) [24][360/2119] lr: 4.0000e-02 eta: 1 day, 1:21:42 time: 0.2996 data_time: 0.0194 memory: 5826 grad_norm: 2.9025 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8577 loss: 2.8577 2022/10/07 12:18:21 - mmengine - INFO - Epoch(train) [24][380/2119] lr: 4.0000e-02 eta: 1 day, 1:21:39 time: 0.3767 data_time: 0.0203 memory: 5826 grad_norm: 2.9051 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.4991 loss: 2.4991 2022/10/07 12:18:28 - mmengine - INFO - Epoch(train) [24][400/2119] lr: 4.0000e-02 eta: 1 day, 1:21:31 time: 0.3248 data_time: 0.0204 memory: 5826 grad_norm: 2.9548 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7729 loss: 2.7729 2022/10/07 12:18:34 - mmengine - INFO - Epoch(train) [24][420/2119] lr: 4.0000e-02 eta: 1 day, 1:21:23 time: 0.3306 data_time: 0.0229 memory: 5826 grad_norm: 2.8913 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5191 loss: 2.5191 2022/10/07 12:18:41 - mmengine - INFO - Epoch(train) [24][440/2119] lr: 4.0000e-02 eta: 1 day, 1:21:18 time: 0.3570 data_time: 0.0172 memory: 5826 grad_norm: 2.9063 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8127 loss: 2.8127 2022/10/07 12:18:49 - mmengine - INFO - Epoch(train) [24][460/2119] lr: 4.0000e-02 eta: 1 day, 1:21:16 time: 0.3874 data_time: 0.0248 memory: 5826 grad_norm: 2.8920 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.5945 loss: 2.5945 2022/10/07 12:18:55 - mmengine - INFO - Epoch(train) [24][480/2119] lr: 4.0000e-02 eta: 1 day, 1:21:05 time: 0.3010 data_time: 0.0240 memory: 5826 grad_norm: 2.9207 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8217 loss: 2.8217 2022/10/07 12:19:03 - mmengine - INFO - Epoch(train) [24][500/2119] lr: 4.0000e-02 eta: 1 day, 1:21:03 time: 0.3846 data_time: 0.0219 memory: 5826 grad_norm: 2.9160 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9055 loss: 2.9055 2022/10/07 12:19:09 - mmengine - INFO - Epoch(train) [24][520/2119] lr: 4.0000e-02 eta: 1 day, 1:20:50 time: 0.2807 data_time: 0.0254 memory: 5826 grad_norm: 2.9363 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8719 loss: 2.8719 2022/10/07 12:19:15 - mmengine - INFO - Epoch(train) [24][540/2119] lr: 4.0000e-02 eta: 1 day, 1:20:41 time: 0.3143 data_time: 0.0182 memory: 5826 grad_norm: 2.9580 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7626 loss: 2.7626 2022/10/07 12:19:22 - mmengine - INFO - Epoch(train) [24][560/2119] lr: 4.0000e-02 eta: 1 day, 1:20:36 time: 0.3604 data_time: 0.0812 memory: 5826 grad_norm: 2.9336 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6396 loss: 2.6396 2022/10/07 12:19:29 - mmengine - INFO - Epoch(train) [24][580/2119] lr: 4.0000e-02 eta: 1 day, 1:20:28 time: 0.3277 data_time: 0.0285 memory: 5826 grad_norm: 2.9183 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0031 loss: 3.0031 2022/10/07 12:19:35 - mmengine - INFO - Epoch(train) [24][600/2119] lr: 4.0000e-02 eta: 1 day, 1:20:21 time: 0.3379 data_time: 0.0167 memory: 5826 grad_norm: 2.9418 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8046 loss: 2.8046 2022/10/07 12:19:42 - mmengine - INFO - Epoch(train) [24][620/2119] lr: 4.0000e-02 eta: 1 day, 1:20:14 time: 0.3352 data_time: 0.0202 memory: 5826 grad_norm: 2.9409 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6495 loss: 2.6495 2022/10/07 12:19:49 - mmengine - INFO - Epoch(train) [24][640/2119] lr: 4.0000e-02 eta: 1 day, 1:20:05 time: 0.3232 data_time: 0.0274 memory: 5826 grad_norm: 2.9278 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.7785 loss: 2.7785 2022/10/07 12:19:55 - mmengine - INFO - Epoch(train) [24][660/2119] lr: 4.0000e-02 eta: 1 day, 1:19:57 time: 0.3272 data_time: 0.0152 memory: 5826 grad_norm: 2.9050 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8987 loss: 2.8987 2022/10/07 12:20:02 - mmengine - INFO - Epoch(train) [24][680/2119] lr: 4.0000e-02 eta: 1 day, 1:19:50 time: 0.3356 data_time: 0.0222 memory: 5826 grad_norm: 2.9495 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6388 loss: 2.6388 2022/10/07 12:20:09 - mmengine - INFO - Epoch(train) [24][700/2119] lr: 4.0000e-02 eta: 1 day, 1:19:46 time: 0.3690 data_time: 0.0208 memory: 5826 grad_norm: 2.9862 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.8322 loss: 2.8322 2022/10/07 12:20:16 - mmengine - INFO - Epoch(train) [24][720/2119] lr: 4.0000e-02 eta: 1 day, 1:19:39 time: 0.3372 data_time: 0.0192 memory: 5826 grad_norm: 2.9147 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6545 loss: 2.6545 2022/10/07 12:20:22 - mmengine - INFO - Epoch(train) [24][740/2119] lr: 4.0000e-02 eta: 1 day, 1:19:30 time: 0.3214 data_time: 0.0245 memory: 5826 grad_norm: 2.9130 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8062 loss: 2.8062 2022/10/07 12:20:29 - mmengine - INFO - Epoch(train) [24][760/2119] lr: 4.0000e-02 eta: 1 day, 1:19:21 time: 0.3212 data_time: 0.0225 memory: 5826 grad_norm: 2.9304 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7634 loss: 2.7634 2022/10/07 12:20:35 - mmengine - INFO - Epoch(train) [24][780/2119] lr: 4.0000e-02 eta: 1 day, 1:19:14 time: 0.3321 data_time: 0.0202 memory: 5826 grad_norm: 2.9418 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8058 loss: 2.8058 2022/10/07 12:20:42 - mmengine - INFO - Epoch(train) [24][800/2119] lr: 4.0000e-02 eta: 1 day, 1:19:06 time: 0.3271 data_time: 0.0204 memory: 5826 grad_norm: 2.8999 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9936 loss: 2.9936 2022/10/07 12:20:49 - mmengine - INFO - Epoch(train) [24][820/2119] lr: 4.0000e-02 eta: 1 day, 1:19:00 time: 0.3493 data_time: 0.0245 memory: 5826 grad_norm: 2.9164 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.4892 loss: 2.4892 2022/10/07 12:20:55 - mmengine - INFO - Epoch(train) [24][840/2119] lr: 4.0000e-02 eta: 1 day, 1:18:51 time: 0.3160 data_time: 0.0187 memory: 5826 grad_norm: 2.9723 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9173 loss: 2.9173 2022/10/07 12:21:02 - mmengine - INFO - Epoch(train) [24][860/2119] lr: 4.0000e-02 eta: 1 day, 1:18:44 time: 0.3421 data_time: 0.0199 memory: 5826 grad_norm: 2.9268 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7473 loss: 2.7473 2022/10/07 12:21:09 - mmengine - INFO - Epoch(train) [24][880/2119] lr: 4.0000e-02 eta: 1 day, 1:18:39 time: 0.3555 data_time: 0.0197 memory: 5826 grad_norm: 2.8797 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7270 loss: 2.7270 2022/10/07 12:21:16 - mmengine - INFO - Epoch(train) [24][900/2119] lr: 4.0000e-02 eta: 1 day, 1:18:31 time: 0.3327 data_time: 0.0195 memory: 5826 grad_norm: 2.9156 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7451 loss: 2.7451 2022/10/07 12:21:23 - mmengine - INFO - Epoch(train) [24][920/2119] lr: 4.0000e-02 eta: 1 day, 1:18:28 time: 0.3709 data_time: 0.0200 memory: 5826 grad_norm: 2.8855 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7759 loss: 2.7759 2022/10/07 12:21:29 - mmengine - INFO - Epoch(train) [24][940/2119] lr: 4.0000e-02 eta: 1 day, 1:18:16 time: 0.2923 data_time: 0.0244 memory: 5826 grad_norm: 2.8820 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8075 loss: 2.8075 2022/10/07 12:21:36 - mmengine - INFO - Epoch(train) [24][960/2119] lr: 4.0000e-02 eta: 1 day, 1:18:10 time: 0.3511 data_time: 0.0212 memory: 5826 grad_norm: 2.9273 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6658 loss: 2.6658 2022/10/07 12:21:44 - mmengine - INFO - Epoch(train) [24][980/2119] lr: 4.0000e-02 eta: 1 day, 1:18:07 time: 0.3675 data_time: 0.0195 memory: 5826 grad_norm: 2.8956 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7187 loss: 2.7187 2022/10/07 12:21:50 - mmengine - INFO - Epoch(train) [24][1000/2119] lr: 4.0000e-02 eta: 1 day, 1:18:00 time: 0.3445 data_time: 0.0228 memory: 5826 grad_norm: 2.9351 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8883 loss: 2.8883 2022/10/07 12:21:58 - mmengine - INFO - Epoch(train) [24][1020/2119] lr: 4.0000e-02 eta: 1 day, 1:17:56 time: 0.3659 data_time: 0.0272 memory: 5826 grad_norm: 2.8565 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7670 loss: 2.7670 2022/10/07 12:22:04 - mmengine - INFO - Epoch(train) [24][1040/2119] lr: 4.0000e-02 eta: 1 day, 1:17:48 time: 0.3206 data_time: 0.0198 memory: 5826 grad_norm: 2.9200 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6576 loss: 2.6576 2022/10/07 12:22:11 - mmengine - INFO - Epoch(train) [24][1060/2119] lr: 4.0000e-02 eta: 1 day, 1:17:41 time: 0.3446 data_time: 0.0232 memory: 5826 grad_norm: 2.9245 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6275 loss: 2.6275 2022/10/07 12:22:17 - mmengine - INFO - Epoch(train) [24][1080/2119] lr: 4.0000e-02 eta: 1 day, 1:17:32 time: 0.3129 data_time: 0.0236 memory: 5826 grad_norm: 2.9227 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8527 loss: 2.8527 2022/10/07 12:22:25 - mmengine - INFO - Epoch(train) [24][1100/2119] lr: 4.0000e-02 eta: 1 day, 1:17:29 time: 0.3803 data_time: 0.0169 memory: 5826 grad_norm: 2.9492 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7650 loss: 2.7650 2022/10/07 12:22:32 - mmengine - INFO - Epoch(train) [24][1120/2119] lr: 4.0000e-02 eta: 1 day, 1:17:22 time: 0.3351 data_time: 0.0170 memory: 5826 grad_norm: 2.9329 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6977 loss: 2.6977 2022/10/07 12:22:39 - mmengine - INFO - Epoch(train) [24][1140/2119] lr: 4.0000e-02 eta: 1 day, 1:17:20 time: 0.3876 data_time: 0.0232 memory: 5826 grad_norm: 2.9159 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4593 loss: 2.4593 2022/10/07 12:22:46 - mmengine - INFO - Epoch(train) [24][1160/2119] lr: 4.0000e-02 eta: 1 day, 1:17:11 time: 0.3163 data_time: 0.0168 memory: 5826 grad_norm: 2.9774 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6816 loss: 2.6816 2022/10/07 12:22:53 - mmengine - INFO - Epoch(train) [24][1180/2119] lr: 4.0000e-02 eta: 1 day, 1:17:06 time: 0.3543 data_time: 0.0221 memory: 5826 grad_norm: 2.9435 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8411 loss: 2.8411 2022/10/07 12:22:59 - mmengine - INFO - Epoch(train) [24][1200/2119] lr: 4.0000e-02 eta: 1 day, 1:16:58 time: 0.3296 data_time: 0.0174 memory: 5826 grad_norm: 2.8718 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8053 loss: 2.8053 2022/10/07 12:23:07 - mmengine - INFO - Epoch(train) [24][1220/2119] lr: 4.0000e-02 eta: 1 day, 1:16:53 time: 0.3609 data_time: 0.0214 memory: 5826 grad_norm: 2.9005 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6933 loss: 2.6933 2022/10/07 12:23:13 - mmengine - INFO - Epoch(train) [24][1240/2119] lr: 4.0000e-02 eta: 1 day, 1:16:45 time: 0.3262 data_time: 0.0213 memory: 5826 grad_norm: 2.9100 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6968 loss: 2.6968 2022/10/07 12:23:20 - mmengine - INFO - Epoch(train) [24][1260/2119] lr: 4.0000e-02 eta: 1 day, 1:16:41 time: 0.3635 data_time: 0.0292 memory: 5826 grad_norm: 2.9535 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6676 loss: 2.6676 2022/10/07 12:23:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 12:23:27 - mmengine - INFO - Epoch(train) [24][1280/2119] lr: 4.0000e-02 eta: 1 day, 1:16:33 time: 0.3328 data_time: 0.0235 memory: 5826 grad_norm: 2.9000 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.9179 loss: 2.9179 2022/10/07 12:23:34 - mmengine - INFO - Epoch(train) [24][1300/2119] lr: 4.0000e-02 eta: 1 day, 1:16:26 time: 0.3336 data_time: 0.0223 memory: 5826 grad_norm: 2.8730 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9633 loss: 2.9633 2022/10/07 12:23:40 - mmengine - INFO - Epoch(train) [24][1320/2119] lr: 4.0000e-02 eta: 1 day, 1:16:16 time: 0.3142 data_time: 0.0212 memory: 5826 grad_norm: 2.8890 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7668 loss: 2.7668 2022/10/07 12:23:47 - mmengine - INFO - Epoch(train) [24][1340/2119] lr: 4.0000e-02 eta: 1 day, 1:16:12 time: 0.3658 data_time: 0.0207 memory: 5826 grad_norm: 2.9056 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8324 loss: 2.8324 2022/10/07 12:23:54 - mmengine - INFO - Epoch(train) [24][1360/2119] lr: 4.0000e-02 eta: 1 day, 1:16:06 time: 0.3472 data_time: 0.0223 memory: 5826 grad_norm: 2.9489 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9669 loss: 2.9669 2022/10/07 12:24:01 - mmengine - INFO - Epoch(train) [24][1380/2119] lr: 4.0000e-02 eta: 1 day, 1:16:00 time: 0.3460 data_time: 0.0220 memory: 5826 grad_norm: 2.9529 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8142 loss: 2.8142 2022/10/07 12:24:07 - mmengine - INFO - Epoch(train) [24][1400/2119] lr: 4.0000e-02 eta: 1 day, 1:15:50 time: 0.3037 data_time: 0.0203 memory: 5826 grad_norm: 2.9197 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6702 loss: 2.6702 2022/10/07 12:24:15 - mmengine - INFO - Epoch(train) [24][1420/2119] lr: 4.0000e-02 eta: 1 day, 1:15:46 time: 0.3718 data_time: 0.0229 memory: 5826 grad_norm: 2.9553 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8273 loss: 2.8273 2022/10/07 12:24:21 - mmengine - INFO - Epoch(train) [24][1440/2119] lr: 4.0000e-02 eta: 1 day, 1:15:36 time: 0.3051 data_time: 0.0241 memory: 5826 grad_norm: 2.9417 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9177 loss: 2.9177 2022/10/07 12:24:29 - mmengine - INFO - Epoch(train) [24][1460/2119] lr: 4.0000e-02 eta: 1 day, 1:15:35 time: 0.3975 data_time: 0.0193 memory: 5826 grad_norm: 2.9611 top1_acc: 0.0625 top5_acc: 0.5000 loss_cls: 2.8197 loss: 2.8197 2022/10/07 12:24:35 - mmengine - INFO - Epoch(train) [24][1480/2119] lr: 4.0000e-02 eta: 1 day, 1:15:24 time: 0.2964 data_time: 0.0185 memory: 5826 grad_norm: 2.9215 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6769 loss: 2.6769 2022/10/07 12:24:42 - mmengine - INFO - Epoch(train) [24][1500/2119] lr: 4.0000e-02 eta: 1 day, 1:15:20 time: 0.3740 data_time: 0.0198 memory: 5826 grad_norm: 2.9415 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6671 loss: 2.6671 2022/10/07 12:24:49 - mmengine - INFO - Epoch(train) [24][1520/2119] lr: 4.0000e-02 eta: 1 day, 1:15:13 time: 0.3350 data_time: 0.0207 memory: 5826 grad_norm: 2.9626 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7451 loss: 2.7451 2022/10/07 12:24:56 - mmengine - INFO - Epoch(train) [24][1540/2119] lr: 4.0000e-02 eta: 1 day, 1:15:06 time: 0.3386 data_time: 0.0226 memory: 5826 grad_norm: 2.8837 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0559 loss: 3.0559 2022/10/07 12:25:03 - mmengine - INFO - Epoch(train) [24][1560/2119] lr: 4.0000e-02 eta: 1 day, 1:15:01 time: 0.3500 data_time: 0.0210 memory: 5826 grad_norm: 2.8899 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6804 loss: 2.6804 2022/10/07 12:25:10 - mmengine - INFO - Epoch(train) [24][1580/2119] lr: 4.0000e-02 eta: 1 day, 1:14:55 time: 0.3558 data_time: 0.0233 memory: 5826 grad_norm: 2.9009 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7470 loss: 2.7470 2022/10/07 12:25:15 - mmengine - INFO - Epoch(train) [24][1600/2119] lr: 4.0000e-02 eta: 1 day, 1:14:42 time: 0.2808 data_time: 0.0245 memory: 5826 grad_norm: 2.8817 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9082 loss: 2.9082 2022/10/07 12:25:22 - mmengine - INFO - Epoch(train) [24][1620/2119] lr: 4.0000e-02 eta: 1 day, 1:14:33 time: 0.3194 data_time: 0.0197 memory: 5826 grad_norm: 2.9004 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6056 loss: 2.6056 2022/10/07 12:25:29 - mmengine - INFO - Epoch(train) [24][1640/2119] lr: 4.0000e-02 eta: 1 day, 1:14:28 time: 0.3545 data_time: 0.0219 memory: 5826 grad_norm: 2.9324 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9745 loss: 2.9745 2022/10/07 12:25:36 - mmengine - INFO - Epoch(train) [24][1660/2119] lr: 4.0000e-02 eta: 1 day, 1:14:21 time: 0.3371 data_time: 0.0298 memory: 5826 grad_norm: 2.8861 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6382 loss: 2.6382 2022/10/07 12:25:43 - mmengine - INFO - Epoch(train) [24][1680/2119] lr: 4.0000e-02 eta: 1 day, 1:14:18 time: 0.3702 data_time: 0.0182 memory: 5826 grad_norm: 2.9373 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7405 loss: 2.7405 2022/10/07 12:25:50 - mmengine - INFO - Epoch(train) [24][1700/2119] lr: 4.0000e-02 eta: 1 day, 1:14:12 time: 0.3477 data_time: 0.0220 memory: 5826 grad_norm: 2.9656 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7963 loss: 2.7963 2022/10/07 12:25:57 - mmengine - INFO - Epoch(train) [24][1720/2119] lr: 4.0000e-02 eta: 1 day, 1:14:04 time: 0.3292 data_time: 0.0239 memory: 5826 grad_norm: 2.9349 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7911 loss: 2.7911 2022/10/07 12:26:03 - mmengine - INFO - Epoch(train) [24][1740/2119] lr: 4.0000e-02 eta: 1 day, 1:13:56 time: 0.3306 data_time: 0.0240 memory: 5826 grad_norm: 2.9437 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8096 loss: 2.8096 2022/10/07 12:26:10 - mmengine - INFO - Epoch(train) [24][1760/2119] lr: 4.0000e-02 eta: 1 day, 1:13:48 time: 0.3320 data_time: 0.0195 memory: 5826 grad_norm: 2.9125 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6731 loss: 2.6731 2022/10/07 12:26:16 - mmengine - INFO - Epoch(train) [24][1780/2119] lr: 4.0000e-02 eta: 1 day, 1:13:38 time: 0.3062 data_time: 0.0237 memory: 5826 grad_norm: 2.9137 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8806 loss: 2.8806 2022/10/07 12:26:23 - mmengine - INFO - Epoch(train) [24][1800/2119] lr: 4.0000e-02 eta: 1 day, 1:13:32 time: 0.3452 data_time: 0.0190 memory: 5826 grad_norm: 2.8499 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9156 loss: 2.9156 2022/10/07 12:26:29 - mmengine - INFO - Epoch(train) [24][1820/2119] lr: 4.0000e-02 eta: 1 day, 1:13:23 time: 0.3202 data_time: 0.0228 memory: 5826 grad_norm: 2.8874 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0535 loss: 3.0535 2022/10/07 12:26:36 - mmengine - INFO - Epoch(train) [24][1840/2119] lr: 4.0000e-02 eta: 1 day, 1:13:16 time: 0.3340 data_time: 0.0265 memory: 5826 grad_norm: 2.8999 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.8654 loss: 2.8654 2022/10/07 12:26:43 - mmengine - INFO - Epoch(train) [24][1860/2119] lr: 4.0000e-02 eta: 1 day, 1:13:12 time: 0.3670 data_time: 0.0201 memory: 5826 grad_norm: 2.8742 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7820 loss: 2.7820 2022/10/07 12:26:49 - mmengine - INFO - Epoch(train) [24][1880/2119] lr: 4.0000e-02 eta: 1 day, 1:13:00 time: 0.2916 data_time: 0.0210 memory: 5826 grad_norm: 2.9259 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7208 loss: 2.7208 2022/10/07 12:26:56 - mmengine - INFO - Epoch(train) [24][1900/2119] lr: 4.0000e-02 eta: 1 day, 1:12:54 time: 0.3537 data_time: 0.0236 memory: 5826 grad_norm: 2.9293 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8442 loss: 2.8442 2022/10/07 12:27:03 - mmengine - INFO - Epoch(train) [24][1920/2119] lr: 4.0000e-02 eta: 1 day, 1:12:47 time: 0.3356 data_time: 0.0241 memory: 5826 grad_norm: 2.8960 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9460 loss: 2.9460 2022/10/07 12:27:10 - mmengine - INFO - Epoch(train) [24][1940/2119] lr: 4.0000e-02 eta: 1 day, 1:12:40 time: 0.3349 data_time: 0.0230 memory: 5826 grad_norm: 2.9134 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6709 loss: 2.6709 2022/10/07 12:27:16 - mmengine - INFO - Epoch(train) [24][1960/2119] lr: 4.0000e-02 eta: 1 day, 1:12:33 time: 0.3390 data_time: 0.0174 memory: 5826 grad_norm: 2.9322 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7518 loss: 2.7518 2022/10/07 12:27:24 - mmengine - INFO - Epoch(train) [24][1980/2119] lr: 4.0000e-02 eta: 1 day, 1:12:30 time: 0.3744 data_time: 0.0315 memory: 5826 grad_norm: 2.9041 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6509 loss: 2.6509 2022/10/07 12:27:30 - mmengine - INFO - Epoch(train) [24][2000/2119] lr: 4.0000e-02 eta: 1 day, 1:12:18 time: 0.2957 data_time: 0.0205 memory: 5826 grad_norm: 2.8868 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6721 loss: 2.6721 2022/10/07 12:27:37 - mmengine - INFO - Epoch(train) [24][2020/2119] lr: 4.0000e-02 eta: 1 day, 1:12:16 time: 0.3771 data_time: 0.0260 memory: 5826 grad_norm: 2.9005 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8877 loss: 2.8877 2022/10/07 12:27:43 - mmengine - INFO - Epoch(train) [24][2040/2119] lr: 4.0000e-02 eta: 1 day, 1:12:05 time: 0.3016 data_time: 0.0183 memory: 5826 grad_norm: 2.8679 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6558 loss: 2.6558 2022/10/07 12:27:50 - mmengine - INFO - Epoch(train) [24][2060/2119] lr: 4.0000e-02 eta: 1 day, 1:12:00 time: 0.3574 data_time: 0.0220 memory: 5826 grad_norm: 2.9160 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7358 loss: 2.7358 2022/10/07 12:27:57 - mmengine - INFO - Epoch(train) [24][2080/2119] lr: 4.0000e-02 eta: 1 day, 1:11:49 time: 0.3036 data_time: 0.0204 memory: 5826 grad_norm: 2.9377 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7664 loss: 2.7664 2022/10/07 12:28:03 - mmengine - INFO - Epoch(train) [24][2100/2119] lr: 4.0000e-02 eta: 1 day, 1:11:42 time: 0.3344 data_time: 0.0198 memory: 5826 grad_norm: 2.9373 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4528 loss: 2.4528 2022/10/07 12:28:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 12:28:09 - mmengine - INFO - Epoch(train) [24][2119/2119] lr: 4.0000e-02 eta: 1 day, 1:11:42 time: 0.3037 data_time: 0.0205 memory: 5826 grad_norm: 2.9208 top1_acc: 0.4000 top5_acc: 0.6000 loss_cls: 2.6600 loss: 2.6600 2022/10/07 12:28:09 - mmengine - INFO - Saving checkpoint at 24 epochs 2022/10/07 12:28:20 - mmengine - INFO - Epoch(train) [25][20/2119] lr: 4.0000e-02 eta: 1 day, 1:11:02 time: 0.4058 data_time: 0.1866 memory: 5826 grad_norm: 2.9127 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9029 loss: 2.9029 2022/10/07 12:28:26 - mmengine - INFO - Epoch(train) [25][40/2119] lr: 4.0000e-02 eta: 1 day, 1:10:51 time: 0.3046 data_time: 0.0322 memory: 5826 grad_norm: 2.9503 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.8533 loss: 2.8533 2022/10/07 12:28:33 - mmengine - INFO - Epoch(train) [25][60/2119] lr: 4.0000e-02 eta: 1 day, 1:10:46 time: 0.3508 data_time: 0.0224 memory: 5826 grad_norm: 2.9021 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7171 loss: 2.7171 2022/10/07 12:28:39 - mmengine - INFO - Epoch(train) [25][80/2119] lr: 4.0000e-02 eta: 1 day, 1:10:37 time: 0.3210 data_time: 0.0304 memory: 5826 grad_norm: 2.9101 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5980 loss: 2.5980 2022/10/07 12:28:46 - mmengine - INFO - Epoch(train) [25][100/2119] lr: 4.0000e-02 eta: 1 day, 1:10:31 time: 0.3509 data_time: 0.0248 memory: 5826 grad_norm: 2.9414 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.6826 loss: 2.6826 2022/10/07 12:28:53 - mmengine - INFO - Epoch(train) [25][120/2119] lr: 4.0000e-02 eta: 1 day, 1:10:25 time: 0.3472 data_time: 0.0279 memory: 5826 grad_norm: 2.9399 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6553 loss: 2.6553 2022/10/07 12:29:00 - mmengine - INFO - Epoch(train) [25][140/2119] lr: 4.0000e-02 eta: 1 day, 1:10:20 time: 0.3544 data_time: 0.0208 memory: 5826 grad_norm: 2.9343 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7290 loss: 2.7290 2022/10/07 12:29:01 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 12:29:07 - mmengine - INFO - Epoch(train) [25][160/2119] lr: 4.0000e-02 eta: 1 day, 1:10:12 time: 0.3310 data_time: 0.0203 memory: 5826 grad_norm: 2.9596 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9662 loss: 2.9662 2022/10/07 12:29:14 - mmengine - INFO - Epoch(train) [25][180/2119] lr: 4.0000e-02 eta: 1 day, 1:10:05 time: 0.3383 data_time: 0.0276 memory: 5826 grad_norm: 2.9161 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5122 loss: 2.5122 2022/10/07 12:29:20 - mmengine - INFO - Epoch(train) [25][200/2119] lr: 4.0000e-02 eta: 1 day, 1:09:55 time: 0.3056 data_time: 0.0272 memory: 5826 grad_norm: 2.8972 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7402 loss: 2.7402 2022/10/07 12:29:27 - mmengine - INFO - Epoch(train) [25][220/2119] lr: 4.0000e-02 eta: 1 day, 1:09:53 time: 0.3806 data_time: 0.0216 memory: 5826 grad_norm: 2.9423 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6869 loss: 2.6869 2022/10/07 12:29:34 - mmengine - INFO - Epoch(train) [25][240/2119] lr: 4.0000e-02 eta: 1 day, 1:09:43 time: 0.3145 data_time: 0.0192 memory: 5826 grad_norm: 2.9454 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7902 loss: 2.7902 2022/10/07 12:29:41 - mmengine - INFO - Epoch(train) [25][260/2119] lr: 4.0000e-02 eta: 1 day, 1:09:38 time: 0.3510 data_time: 0.0206 memory: 5826 grad_norm: 2.9828 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7064 loss: 2.7064 2022/10/07 12:29:47 - mmengine - INFO - Epoch(train) [25][280/2119] lr: 4.0000e-02 eta: 1 day, 1:09:31 time: 0.3438 data_time: 0.0274 memory: 5826 grad_norm: 2.9263 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8286 loss: 2.8286 2022/10/07 12:29:54 - mmengine - INFO - Epoch(train) [25][300/2119] lr: 4.0000e-02 eta: 1 day, 1:09:23 time: 0.3231 data_time: 0.0208 memory: 5826 grad_norm: 2.9039 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7670 loss: 2.7670 2022/10/07 12:30:00 - mmengine - INFO - Epoch(train) [25][320/2119] lr: 4.0000e-02 eta: 1 day, 1:09:15 time: 0.3297 data_time: 0.0196 memory: 5826 grad_norm: 2.9833 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7368 loss: 2.7368 2022/10/07 12:30:08 - mmengine - INFO - Epoch(train) [25][340/2119] lr: 4.0000e-02 eta: 1 day, 1:09:09 time: 0.3512 data_time: 0.0194 memory: 5826 grad_norm: 2.8729 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5076 loss: 2.5076 2022/10/07 12:30:14 - mmengine - INFO - Epoch(train) [25][360/2119] lr: 4.0000e-02 eta: 1 day, 1:08:59 time: 0.3072 data_time: 0.0208 memory: 5826 grad_norm: 2.9155 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6165 loss: 2.6165 2022/10/07 12:30:21 - mmengine - INFO - Epoch(train) [25][380/2119] lr: 4.0000e-02 eta: 1 day, 1:08:57 time: 0.3874 data_time: 0.0185 memory: 5826 grad_norm: 3.0039 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8437 loss: 2.8437 2022/10/07 12:30:28 - mmengine - INFO - Epoch(train) [25][400/2119] lr: 4.0000e-02 eta: 1 day, 1:08:49 time: 0.3276 data_time: 0.0313 memory: 5826 grad_norm: 2.9477 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7059 loss: 2.7059 2022/10/07 12:30:35 - mmengine - INFO - Epoch(train) [25][420/2119] lr: 4.0000e-02 eta: 1 day, 1:08:42 time: 0.3346 data_time: 0.0163 memory: 5826 grad_norm: 2.9674 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7599 loss: 2.7599 2022/10/07 12:30:41 - mmengine - INFO - Epoch(train) [25][440/2119] lr: 4.0000e-02 eta: 1 day, 1:08:34 time: 0.3306 data_time: 0.0195 memory: 5826 grad_norm: 2.8689 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7455 loss: 2.7455 2022/10/07 12:30:48 - mmengine - INFO - Epoch(train) [25][460/2119] lr: 4.0000e-02 eta: 1 day, 1:08:29 time: 0.3586 data_time: 0.0190 memory: 5826 grad_norm: 2.9037 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8976 loss: 2.8976 2022/10/07 12:30:55 - mmengine - INFO - Epoch(train) [25][480/2119] lr: 4.0000e-02 eta: 1 day, 1:08:23 time: 0.3395 data_time: 0.0312 memory: 5826 grad_norm: 2.9933 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8192 loss: 2.8192 2022/10/07 12:31:03 - mmengine - INFO - Epoch(train) [25][500/2119] lr: 4.0000e-02 eta: 1 day, 1:08:19 time: 0.3657 data_time: 0.0180 memory: 5826 grad_norm: 2.9263 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.6846 loss: 2.6846 2022/10/07 12:31:09 - mmengine - INFO - Epoch(train) [25][520/2119] lr: 4.0000e-02 eta: 1 day, 1:08:10 time: 0.3220 data_time: 0.0216 memory: 5826 grad_norm: 2.9766 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8769 loss: 2.8769 2022/10/07 12:31:16 - mmengine - INFO - Epoch(train) [25][540/2119] lr: 4.0000e-02 eta: 1 day, 1:08:03 time: 0.3338 data_time: 0.0244 memory: 5826 grad_norm: 2.9285 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7682 loss: 2.7682 2022/10/07 12:31:23 - mmengine - INFO - Epoch(train) [25][560/2119] lr: 4.0000e-02 eta: 1 day, 1:07:56 time: 0.3428 data_time: 0.0278 memory: 5826 grad_norm: 2.9584 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8552 loss: 2.8552 2022/10/07 12:31:30 - mmengine - INFO - Epoch(train) [25][580/2119] lr: 4.0000e-02 eta: 1 day, 1:07:53 time: 0.3768 data_time: 0.0213 memory: 5826 grad_norm: 2.9379 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6563 loss: 2.6563 2022/10/07 12:31:37 - mmengine - INFO - Epoch(train) [25][600/2119] lr: 4.0000e-02 eta: 1 day, 1:07:46 time: 0.3392 data_time: 0.0205 memory: 5826 grad_norm: 2.9129 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6904 loss: 2.6904 2022/10/07 12:31:44 - mmengine - INFO - Epoch(train) [25][620/2119] lr: 4.0000e-02 eta: 1 day, 1:07:43 time: 0.3755 data_time: 0.0170 memory: 5826 grad_norm: 2.8483 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6414 loss: 2.6414 2022/10/07 12:31:51 - mmengine - INFO - Epoch(train) [25][640/2119] lr: 4.0000e-02 eta: 1 day, 1:07:34 time: 0.3179 data_time: 0.0226 memory: 5826 grad_norm: 2.9793 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6197 loss: 2.6197 2022/10/07 12:31:57 - mmengine - INFO - Epoch(train) [25][660/2119] lr: 4.0000e-02 eta: 1 day, 1:07:26 time: 0.3266 data_time: 0.0235 memory: 5826 grad_norm: 2.9760 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6365 loss: 2.6365 2022/10/07 12:32:04 - mmengine - INFO - Epoch(train) [25][680/2119] lr: 4.0000e-02 eta: 1 day, 1:07:19 time: 0.3341 data_time: 0.0239 memory: 5826 grad_norm: 2.8817 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6408 loss: 2.6408 2022/10/07 12:32:11 - mmengine - INFO - Epoch(train) [25][700/2119] lr: 4.0000e-02 eta: 1 day, 1:07:16 time: 0.3750 data_time: 0.0204 memory: 5826 grad_norm: 2.9759 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6358 loss: 2.6358 2022/10/07 12:32:18 - mmengine - INFO - Epoch(train) [25][720/2119] lr: 4.0000e-02 eta: 1 day, 1:07:07 time: 0.3193 data_time: 0.0186 memory: 5826 grad_norm: 2.9513 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7363 loss: 2.7363 2022/10/07 12:32:25 - mmengine - INFO - Epoch(train) [25][740/2119] lr: 4.0000e-02 eta: 1 day, 1:07:01 time: 0.3534 data_time: 0.0216 memory: 5826 grad_norm: 2.9185 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6720 loss: 2.6720 2022/10/07 12:32:31 - mmengine - INFO - Epoch(train) [25][760/2119] lr: 4.0000e-02 eta: 1 day, 1:06:50 time: 0.2985 data_time: 0.0238 memory: 5826 grad_norm: 2.8858 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7105 loss: 2.7105 2022/10/07 12:32:38 - mmengine - INFO - Epoch(train) [25][780/2119] lr: 4.0000e-02 eta: 1 day, 1:06:43 time: 0.3332 data_time: 0.0208 memory: 5826 grad_norm: 2.9984 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7717 loss: 2.7717 2022/10/07 12:32:45 - mmengine - INFO - Epoch(train) [25][800/2119] lr: 4.0000e-02 eta: 1 day, 1:06:39 time: 0.3649 data_time: 0.0198 memory: 5826 grad_norm: 2.9673 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8053 loss: 2.8053 2022/10/07 12:32:52 - mmengine - INFO - Epoch(train) [25][820/2119] lr: 4.0000e-02 eta: 1 day, 1:06:33 time: 0.3481 data_time: 0.0210 memory: 5826 grad_norm: 2.9540 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6746 loss: 2.6746 2022/10/07 12:32:58 - mmengine - INFO - Epoch(train) [25][840/2119] lr: 4.0000e-02 eta: 1 day, 1:06:22 time: 0.3010 data_time: 0.0228 memory: 5826 grad_norm: 2.8844 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7518 loss: 2.7518 2022/10/07 12:33:05 - mmengine - INFO - Epoch(train) [25][860/2119] lr: 4.0000e-02 eta: 1 day, 1:06:17 time: 0.3549 data_time: 0.0220 memory: 5826 grad_norm: 2.9186 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7335 loss: 2.7335 2022/10/07 12:33:11 - mmengine - INFO - Epoch(train) [25][880/2119] lr: 4.0000e-02 eta: 1 day, 1:06:05 time: 0.2936 data_time: 0.0298 memory: 5826 grad_norm: 2.9512 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7432 loss: 2.7432 2022/10/07 12:33:19 - mmengine - INFO - Epoch(train) [25][900/2119] lr: 4.0000e-02 eta: 1 day, 1:06:03 time: 0.3861 data_time: 0.0217 memory: 5826 grad_norm: 2.9474 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6394 loss: 2.6394 2022/10/07 12:33:25 - mmengine - INFO - Epoch(train) [25][920/2119] lr: 4.0000e-02 eta: 1 day, 1:05:55 time: 0.3260 data_time: 0.0178 memory: 5826 grad_norm: 2.9550 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7880 loss: 2.7880 2022/10/07 12:33:33 - mmengine - INFO - Epoch(train) [25][940/2119] lr: 4.0000e-02 eta: 1 day, 1:05:53 time: 0.3834 data_time: 0.0219 memory: 5826 grad_norm: 2.9019 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7527 loss: 2.7527 2022/10/07 12:33:39 - mmengine - INFO - Epoch(train) [25][960/2119] lr: 4.0000e-02 eta: 1 day, 1:05:45 time: 0.3291 data_time: 0.0243 memory: 5826 grad_norm: 2.9116 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8442 loss: 2.8442 2022/10/07 12:33:46 - mmengine - INFO - Epoch(train) [25][980/2119] lr: 4.0000e-02 eta: 1 day, 1:05:39 time: 0.3454 data_time: 0.0205 memory: 5826 grad_norm: 2.9448 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5947 loss: 2.5947 2022/10/07 12:33:53 - mmengine - INFO - Epoch(train) [25][1000/2119] lr: 4.0000e-02 eta: 1 day, 1:05:30 time: 0.3237 data_time: 0.0223 memory: 5826 grad_norm: 2.8879 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7833 loss: 2.7833 2022/10/07 12:34:00 - mmengine - INFO - Epoch(train) [25][1020/2119] lr: 4.0000e-02 eta: 1 day, 1:05:25 time: 0.3526 data_time: 0.0190 memory: 5826 grad_norm: 2.9325 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8917 loss: 2.8917 2022/10/07 12:34:06 - mmengine - INFO - Epoch(train) [25][1040/2119] lr: 4.0000e-02 eta: 1 day, 1:05:18 time: 0.3347 data_time: 0.0205 memory: 5826 grad_norm: 2.9062 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7669 loss: 2.7669 2022/10/07 12:34:13 - mmengine - INFO - Epoch(train) [25][1060/2119] lr: 4.0000e-02 eta: 1 day, 1:05:11 time: 0.3400 data_time: 0.0206 memory: 5826 grad_norm: 2.9279 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6349 loss: 2.6349 2022/10/07 12:34:20 - mmengine - INFO - Epoch(train) [25][1080/2119] lr: 4.0000e-02 eta: 1 day, 1:05:06 time: 0.3605 data_time: 0.0216 memory: 5826 grad_norm: 3.0005 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8458 loss: 2.8458 2022/10/07 12:34:28 - mmengine - INFO - Epoch(train) [25][1100/2119] lr: 4.0000e-02 eta: 1 day, 1:05:06 time: 0.3998 data_time: 0.0202 memory: 5826 grad_norm: 2.9352 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.9281 loss: 2.9281 2022/10/07 12:34:35 - mmengine - INFO - Epoch(train) [25][1120/2119] lr: 4.0000e-02 eta: 1 day, 1:04:55 time: 0.3040 data_time: 0.0246 memory: 5826 grad_norm: 2.9545 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9079 loss: 2.9079 2022/10/07 12:34:42 - mmengine - INFO - Epoch(train) [25][1140/2119] lr: 4.0000e-02 eta: 1 day, 1:04:52 time: 0.3797 data_time: 0.0221 memory: 5826 grad_norm: 2.9809 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8747 loss: 2.8747 2022/10/07 12:34:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 12:34:49 - mmengine - INFO - Epoch(train) [25][1160/2119] lr: 4.0000e-02 eta: 1 day, 1:04:44 time: 0.3251 data_time: 0.0205 memory: 5826 grad_norm: 2.9347 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7331 loss: 2.7331 2022/10/07 12:34:56 - mmengine - INFO - Epoch(train) [25][1180/2119] lr: 4.0000e-02 eta: 1 day, 1:04:42 time: 0.3870 data_time: 0.0220 memory: 5826 grad_norm: 2.9287 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6384 loss: 2.6384 2022/10/07 12:35:03 - mmengine - INFO - Epoch(train) [25][1200/2119] lr: 4.0000e-02 eta: 1 day, 1:04:34 time: 0.3245 data_time: 0.0222 memory: 5826 grad_norm: 2.9659 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8104 loss: 2.8104 2022/10/07 12:35:10 - mmengine - INFO - Epoch(train) [25][1220/2119] lr: 4.0000e-02 eta: 1 day, 1:04:30 time: 0.3647 data_time: 0.0207 memory: 5826 grad_norm: 2.9150 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8502 loss: 2.8502 2022/10/07 12:35:16 - mmengine - INFO - Epoch(train) [25][1240/2119] lr: 4.0000e-02 eta: 1 day, 1:04:19 time: 0.3059 data_time: 0.0207 memory: 5826 grad_norm: 2.9229 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9197 loss: 2.9197 2022/10/07 12:35:24 - mmengine - INFO - Epoch(train) [25][1260/2119] lr: 4.0000e-02 eta: 1 day, 1:04:15 time: 0.3610 data_time: 0.0237 memory: 5826 grad_norm: 2.8876 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6026 loss: 2.6026 2022/10/07 12:35:30 - mmengine - INFO - Epoch(train) [25][1280/2119] lr: 4.0000e-02 eta: 1 day, 1:04:06 time: 0.3246 data_time: 0.0205 memory: 5826 grad_norm: 2.9089 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7974 loss: 2.7974 2022/10/07 12:35:37 - mmengine - INFO - Epoch(train) [25][1300/2119] lr: 4.0000e-02 eta: 1 day, 1:04:02 time: 0.3609 data_time: 0.0211 memory: 5826 grad_norm: 2.9745 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0011 loss: 3.0011 2022/10/07 12:35:44 - mmengine - INFO - Epoch(train) [25][1320/2119] lr: 4.0000e-02 eta: 1 day, 1:03:53 time: 0.3168 data_time: 0.0231 memory: 5826 grad_norm: 2.9298 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7248 loss: 2.7248 2022/10/07 12:35:50 - mmengine - INFO - Epoch(train) [25][1340/2119] lr: 4.0000e-02 eta: 1 day, 1:03:45 time: 0.3317 data_time: 0.0174 memory: 5826 grad_norm: 2.9359 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4517 loss: 2.4517 2022/10/07 12:35:57 - mmengine - INFO - Epoch(train) [25][1360/2119] lr: 4.0000e-02 eta: 1 day, 1:03:40 time: 0.3617 data_time: 0.0186 memory: 5826 grad_norm: 2.9653 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7678 loss: 2.7678 2022/10/07 12:36:04 - mmengine - INFO - Epoch(train) [25][1380/2119] lr: 4.0000e-02 eta: 1 day, 1:03:34 time: 0.3438 data_time: 0.0176 memory: 5826 grad_norm: 2.9275 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7711 loss: 2.7711 2022/10/07 12:36:12 - mmengine - INFO - Epoch(train) [25][1400/2119] lr: 4.0000e-02 eta: 1 day, 1:03:31 time: 0.3716 data_time: 0.0204 memory: 5826 grad_norm: 2.9709 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9078 loss: 2.9078 2022/10/07 12:36:19 - mmengine - INFO - Epoch(train) [25][1420/2119] lr: 4.0000e-02 eta: 1 day, 1:03:24 time: 0.3400 data_time: 0.0195 memory: 5826 grad_norm: 2.9623 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5986 loss: 2.5986 2022/10/07 12:36:26 - mmengine - INFO - Epoch(train) [25][1440/2119] lr: 4.0000e-02 eta: 1 day, 1:03:21 time: 0.3764 data_time: 0.0179 memory: 5826 grad_norm: 2.8682 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7999 loss: 2.7999 2022/10/07 12:36:33 - mmengine - INFO - Epoch(train) [25][1460/2119] lr: 4.0000e-02 eta: 1 day, 1:03:13 time: 0.3306 data_time: 0.0193 memory: 5826 grad_norm: 2.8597 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.7322 loss: 2.7322 2022/10/07 12:36:40 - mmengine - INFO - Epoch(train) [25][1480/2119] lr: 4.0000e-02 eta: 1 day, 1:03:11 time: 0.3870 data_time: 0.0239 memory: 5826 grad_norm: 2.9334 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7202 loss: 2.7202 2022/10/07 12:36:46 - mmengine - INFO - Epoch(train) [25][1500/2119] lr: 4.0000e-02 eta: 1 day, 1:02:58 time: 0.2758 data_time: 0.0274 memory: 5826 grad_norm: 2.9586 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6676 loss: 2.6676 2022/10/07 12:36:53 - mmengine - INFO - Epoch(train) [25][1520/2119] lr: 4.0000e-02 eta: 1 day, 1:02:52 time: 0.3525 data_time: 0.0285 memory: 5826 grad_norm: 2.9280 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7893 loss: 2.7893 2022/10/07 12:37:00 - mmengine - INFO - Epoch(train) [25][1540/2119] lr: 4.0000e-02 eta: 1 day, 1:02:44 time: 0.3269 data_time: 0.0202 memory: 5826 grad_norm: 2.9671 top1_acc: 0.2500 top5_acc: 0.3125 loss_cls: 3.0580 loss: 3.0580 2022/10/07 12:37:07 - mmengine - INFO - Epoch(train) [25][1560/2119] lr: 4.0000e-02 eta: 1 day, 1:02:41 time: 0.3714 data_time: 0.0243 memory: 5826 grad_norm: 2.9621 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9155 loss: 2.9155 2022/10/07 12:37:13 - mmengine - INFO - Epoch(train) [25][1580/2119] lr: 4.0000e-02 eta: 1 day, 1:02:32 time: 0.3179 data_time: 0.0228 memory: 5826 grad_norm: 2.9349 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6958 loss: 2.6958 2022/10/07 12:37:21 - mmengine - INFO - Epoch(train) [25][1600/2119] lr: 4.0000e-02 eta: 1 day, 1:02:29 time: 0.3797 data_time: 0.0180 memory: 5826 grad_norm: 2.9335 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5114 loss: 2.5114 2022/10/07 12:37:28 - mmengine - INFO - Epoch(train) [25][1620/2119] lr: 4.0000e-02 eta: 1 day, 1:02:21 time: 0.3312 data_time: 0.0196 memory: 5826 grad_norm: 2.9656 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7383 loss: 2.7383 2022/10/07 12:37:34 - mmengine - INFO - Epoch(train) [25][1640/2119] lr: 4.0000e-02 eta: 1 day, 1:02:15 time: 0.3459 data_time: 0.0184 memory: 5826 grad_norm: 2.9384 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6762 loss: 2.6762 2022/10/07 12:37:42 - mmengine - INFO - Epoch(train) [25][1660/2119] lr: 4.0000e-02 eta: 1 day, 1:02:13 time: 0.3822 data_time: 0.0205 memory: 5826 grad_norm: 2.8827 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7183 loss: 2.7183 2022/10/07 12:37:49 - mmengine - INFO - Epoch(train) [25][1680/2119] lr: 4.0000e-02 eta: 1 day, 1:02:04 time: 0.3233 data_time: 0.0246 memory: 5826 grad_norm: 2.9320 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7608 loss: 2.7608 2022/10/07 12:37:56 - mmengine - INFO - Epoch(train) [25][1700/2119] lr: 4.0000e-02 eta: 1 day, 1:02:01 time: 0.3725 data_time: 0.0188 memory: 5826 grad_norm: 2.8894 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.4934 loss: 2.4934 2022/10/07 12:38:02 - mmengine - INFO - Epoch(train) [25][1720/2119] lr: 4.0000e-02 eta: 1 day, 1:01:51 time: 0.3069 data_time: 0.0236 memory: 5826 grad_norm: 2.9375 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9675 loss: 2.9675 2022/10/07 12:38:09 - mmengine - INFO - Epoch(train) [25][1740/2119] lr: 4.0000e-02 eta: 1 day, 1:01:43 time: 0.3282 data_time: 0.0229 memory: 5826 grad_norm: 2.9080 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5970 loss: 2.5970 2022/10/07 12:38:15 - mmengine - INFO - Epoch(train) [25][1760/2119] lr: 4.0000e-02 eta: 1 day, 1:01:35 time: 0.3327 data_time: 0.0226 memory: 5826 grad_norm: 2.9715 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6664 loss: 2.6664 2022/10/07 12:38:23 - mmengine - INFO - Epoch(train) [25][1780/2119] lr: 4.0000e-02 eta: 1 day, 1:01:33 time: 0.3844 data_time: 0.0194 memory: 5826 grad_norm: 2.9331 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7621 loss: 2.7621 2022/10/07 12:38:30 - mmengine - INFO - Epoch(train) [25][1800/2119] lr: 4.0000e-02 eta: 1 day, 1:01:26 time: 0.3417 data_time: 0.0207 memory: 5826 grad_norm: 2.9105 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6936 loss: 2.6936 2022/10/07 12:38:37 - mmengine - INFO - Epoch(train) [25][1820/2119] lr: 4.0000e-02 eta: 1 day, 1:01:22 time: 0.3667 data_time: 0.0211 memory: 5826 grad_norm: 2.9215 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5314 loss: 2.5314 2022/10/07 12:38:44 - mmengine - INFO - Epoch(train) [25][1840/2119] lr: 4.0000e-02 eta: 1 day, 1:01:14 time: 0.3243 data_time: 0.0213 memory: 5826 grad_norm: 2.9187 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7381 loss: 2.7381 2022/10/07 12:38:51 - mmengine - INFO - Epoch(train) [25][1860/2119] lr: 4.0000e-02 eta: 1 day, 1:01:09 time: 0.3583 data_time: 0.0198 memory: 5826 grad_norm: 2.8828 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8398 loss: 2.8398 2022/10/07 12:38:57 - mmengine - INFO - Epoch(train) [25][1880/2119] lr: 4.0000e-02 eta: 1 day, 1:00:58 time: 0.2989 data_time: 0.0233 memory: 5826 grad_norm: 2.9341 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7723 loss: 2.7723 2022/10/07 12:39:04 - mmengine - INFO - Epoch(train) [25][1900/2119] lr: 4.0000e-02 eta: 1 day, 1:00:53 time: 0.3557 data_time: 0.0175 memory: 5826 grad_norm: 2.8884 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7057 loss: 2.7057 2022/10/07 12:39:10 - mmengine - INFO - Epoch(train) [25][1920/2119] lr: 4.0000e-02 eta: 1 day, 1:00:43 time: 0.3093 data_time: 0.0237 memory: 5826 grad_norm: 2.9561 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7864 loss: 2.7864 2022/10/07 12:39:17 - mmengine - INFO - Epoch(train) [25][1940/2119] lr: 4.0000e-02 eta: 1 day, 1:00:36 time: 0.3365 data_time: 0.0156 memory: 5826 grad_norm: 2.9343 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9265 loss: 2.9265 2022/10/07 12:39:24 - mmengine - INFO - Epoch(train) [25][1960/2119] lr: 4.0000e-02 eta: 1 day, 1:00:30 time: 0.3475 data_time: 0.0236 memory: 5826 grad_norm: 2.8959 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7835 loss: 2.7835 2022/10/07 12:39:31 - mmengine - INFO - Epoch(train) [25][1980/2119] lr: 4.0000e-02 eta: 1 day, 1:00:27 time: 0.3806 data_time: 0.0152 memory: 5826 grad_norm: 2.9304 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6499 loss: 2.6499 2022/10/07 12:39:38 - mmengine - INFO - Epoch(train) [25][2000/2119] lr: 4.0000e-02 eta: 1 day, 1:00:18 time: 0.3125 data_time: 0.0231 memory: 5826 grad_norm: 2.9453 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6673 loss: 2.6673 2022/10/07 12:39:45 - mmengine - INFO - Epoch(train) [25][2020/2119] lr: 4.0000e-02 eta: 1 day, 1:00:15 time: 0.3802 data_time: 0.0172 memory: 5826 grad_norm: 2.9281 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.9621 loss: 2.9621 2022/10/07 12:39:52 - mmengine - INFO - Epoch(train) [25][2040/2119] lr: 4.0000e-02 eta: 1 day, 1:00:06 time: 0.3162 data_time: 0.0224 memory: 5826 grad_norm: 2.9005 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.7816 loss: 2.7816 2022/10/07 12:39:59 - mmengine - INFO - Epoch(train) [25][2060/2119] lr: 4.0000e-02 eta: 1 day, 1:00:00 time: 0.3530 data_time: 0.0216 memory: 5826 grad_norm: 2.9248 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0106 loss: 3.0106 2022/10/07 12:40:05 - mmengine - INFO - Epoch(train) [25][2080/2119] lr: 4.0000e-02 eta: 1 day, 0:59:52 time: 0.3247 data_time: 0.0190 memory: 5826 grad_norm: 2.9500 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7778 loss: 2.7778 2022/10/07 12:40:12 - mmengine - INFO - Epoch(train) [25][2100/2119] lr: 4.0000e-02 eta: 1 day, 0:59:47 time: 0.3626 data_time: 0.0163 memory: 5826 grad_norm: 2.9809 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6164 loss: 2.6164 2022/10/07 12:40:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 12:40:18 - mmengine - INFO - Epoch(train) [25][2119/2119] lr: 4.0000e-02 eta: 1 day, 0:59:47 time: 0.2899 data_time: 0.0237 memory: 5826 grad_norm: 2.9796 top1_acc: 0.4000 top5_acc: 0.8000 loss_cls: 2.7870 loss: 2.7870 2022/10/07 12:40:26 - mmengine - INFO - Epoch(val) [25][20/137] eta: 0:00:47 time: 0.4098 data_time: 0.3336 memory: 1241 2022/10/07 12:40:32 - mmengine - INFO - Epoch(val) [25][40/137] eta: 0:00:28 time: 0.2966 data_time: 0.2276 memory: 1241 2022/10/07 12:40:39 - mmengine - INFO - Epoch(val) [25][60/137] eta: 0:00:26 time: 0.3485 data_time: 0.2796 memory: 1241 2022/10/07 12:40:44 - mmengine - INFO - Epoch(val) [25][80/137] eta: 0:00:15 time: 0.2643 data_time: 0.1971 memory: 1241 2022/10/07 12:40:51 - mmengine - INFO - Epoch(val) [25][100/137] eta: 0:00:12 time: 0.3490 data_time: 0.2828 memory: 1241 2022/10/07 12:40:57 - mmengine - INFO - Epoch(val) [25][120/137] eta: 0:00:04 time: 0.2852 data_time: 0.2199 memory: 1241 2022/10/07 12:41:08 - mmengine - INFO - Epoch(val) [25][137/137] acc/top1: 0.4238 acc/top5: 0.6680 acc/mean1: 0.4237 2022/10/07 12:41:08 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb/best_acc/top1_epoch_20.pth is removed 2022/10/07 12:41:14 - mmengine - INFO - The best checkpoint with 0.4238 acc/top1 at 25 epoch is saved to best_acc/top1_epoch_25.pth. 2022/10/07 12:41:21 - mmengine - INFO - Epoch(train) [26][20/2119] lr: 4.0000e-02 eta: 1 day, 0:59:03 time: 0.3483 data_time: 0.1417 memory: 5826 grad_norm: 2.8988 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7518 loss: 2.7518 2022/10/07 12:41:23 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 12:41:27 - mmengine - INFO - Epoch(train) [26][40/2119] lr: 4.0000e-02 eta: 1 day, 0:58:55 time: 0.3251 data_time: 0.0726 memory: 5826 grad_norm: 2.9110 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5986 loss: 2.5986 2022/10/07 12:41:35 - mmengine - INFO - Epoch(train) [26][60/2119] lr: 4.0000e-02 eta: 1 day, 0:58:50 time: 0.3651 data_time: 0.0216 memory: 5826 grad_norm: 2.9461 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6454 loss: 2.6454 2022/10/07 12:41:43 - mmengine - INFO - Epoch(train) [26][80/2119] lr: 4.0000e-02 eta: 1 day, 0:58:49 time: 0.3992 data_time: 0.0216 memory: 5826 grad_norm: 2.8969 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7895 loss: 2.7895 2022/10/07 12:41:49 - mmengine - INFO - Epoch(train) [26][100/2119] lr: 4.0000e-02 eta: 1 day, 0:58:41 time: 0.3231 data_time: 0.0229 memory: 5826 grad_norm: 2.9664 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.6211 loss: 2.6211 2022/10/07 12:41:56 - mmengine - INFO - Epoch(train) [26][120/2119] lr: 4.0000e-02 eta: 1 day, 0:58:36 time: 0.3598 data_time: 0.0222 memory: 5826 grad_norm: 2.9725 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6493 loss: 2.6493 2022/10/07 12:42:04 - mmengine - INFO - Epoch(train) [26][140/2119] lr: 4.0000e-02 eta: 1 day, 0:58:32 time: 0.3659 data_time: 0.0214 memory: 5826 grad_norm: 2.9414 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4983 loss: 2.4983 2022/10/07 12:42:11 - mmengine - INFO - Epoch(train) [26][160/2119] lr: 4.0000e-02 eta: 1 day, 0:58:28 time: 0.3644 data_time: 0.0267 memory: 5826 grad_norm: 2.9311 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8014 loss: 2.8014 2022/10/07 12:42:17 - mmengine - INFO - Epoch(train) [26][180/2119] lr: 4.0000e-02 eta: 1 day, 0:58:18 time: 0.3141 data_time: 0.0230 memory: 5826 grad_norm: 2.9512 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6228 loss: 2.6228 2022/10/07 12:42:24 - mmengine - INFO - Epoch(train) [26][200/2119] lr: 4.0000e-02 eta: 1 day, 0:58:13 time: 0.3535 data_time: 0.0247 memory: 5826 grad_norm: 2.9223 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9652 loss: 2.9652 2022/10/07 12:42:30 - mmengine - INFO - Epoch(train) [26][220/2119] lr: 4.0000e-02 eta: 1 day, 0:58:02 time: 0.2996 data_time: 0.0204 memory: 5826 grad_norm: 2.9237 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6887 loss: 2.6887 2022/10/07 12:42:38 - mmengine - INFO - Epoch(train) [26][240/2119] lr: 4.0000e-02 eta: 1 day, 0:58:00 time: 0.3901 data_time: 0.0237 memory: 5826 grad_norm: 2.9890 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9375 loss: 2.9375 2022/10/07 12:42:45 - mmengine - INFO - Epoch(train) [26][260/2119] lr: 4.0000e-02 eta: 1 day, 0:57:54 time: 0.3457 data_time: 0.0196 memory: 5826 grad_norm: 2.9607 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7862 loss: 2.7862 2022/10/07 12:42:52 - mmengine - INFO - Epoch(train) [26][280/2119] lr: 4.0000e-02 eta: 1 day, 0:57:47 time: 0.3319 data_time: 0.0209 memory: 5826 grad_norm: 2.9198 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6472 loss: 2.6472 2022/10/07 12:42:58 - mmengine - INFO - Epoch(train) [26][300/2119] lr: 4.0000e-02 eta: 1 day, 0:57:39 time: 0.3336 data_time: 0.0174 memory: 5826 grad_norm: 2.9440 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9225 loss: 2.9225 2022/10/07 12:43:05 - mmengine - INFO - Epoch(train) [26][320/2119] lr: 4.0000e-02 eta: 1 day, 0:57:33 time: 0.3464 data_time: 0.0318 memory: 5826 grad_norm: 2.9286 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5991 loss: 2.5991 2022/10/07 12:43:12 - mmengine - INFO - Epoch(train) [26][340/2119] lr: 4.0000e-02 eta: 1 day, 0:57:25 time: 0.3297 data_time: 0.0166 memory: 5826 grad_norm: 2.9288 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6802 loss: 2.6802 2022/10/07 12:43:19 - mmengine - INFO - Epoch(train) [26][360/2119] lr: 4.0000e-02 eta: 1 day, 0:57:20 time: 0.3519 data_time: 0.0241 memory: 5826 grad_norm: 2.9337 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.6985 loss: 2.6985 2022/10/07 12:43:25 - mmengine - INFO - Epoch(train) [26][380/2119] lr: 4.0000e-02 eta: 1 day, 0:57:08 time: 0.2929 data_time: 0.0235 memory: 5826 grad_norm: 2.9541 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6859 loss: 2.6859 2022/10/07 12:43:32 - mmengine - INFO - Epoch(train) [26][400/2119] lr: 4.0000e-02 eta: 1 day, 0:57:03 time: 0.3580 data_time: 0.0214 memory: 5826 grad_norm: 2.9067 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9173 loss: 2.9173 2022/10/07 12:43:39 - mmengine - INFO - Epoch(train) [26][420/2119] lr: 4.0000e-02 eta: 1 day, 0:56:59 time: 0.3592 data_time: 0.0185 memory: 5826 grad_norm: 2.9477 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7403 loss: 2.7403 2022/10/07 12:43:45 - mmengine - INFO - Epoch(train) [26][440/2119] lr: 4.0000e-02 eta: 1 day, 0:56:49 time: 0.3105 data_time: 0.0260 memory: 5826 grad_norm: 2.9639 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7087 loss: 2.7087 2022/10/07 12:43:52 - mmengine - INFO - Epoch(train) [26][460/2119] lr: 4.0000e-02 eta: 1 day, 0:56:42 time: 0.3430 data_time: 0.0216 memory: 5826 grad_norm: 2.9400 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0115 loss: 3.0115 2022/10/07 12:43:59 - mmengine - INFO - Epoch(train) [26][480/2119] lr: 4.0000e-02 eta: 1 day, 0:56:37 time: 0.3541 data_time: 0.0203 memory: 5826 grad_norm: 2.9725 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7938 loss: 2.7938 2022/10/07 12:44:06 - mmengine - INFO - Epoch(train) [26][500/2119] lr: 4.0000e-02 eta: 1 day, 0:56:30 time: 0.3379 data_time: 0.0196 memory: 5826 grad_norm: 2.9424 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9501 loss: 2.9501 2022/10/07 12:44:13 - mmengine - INFO - Epoch(train) [26][520/2119] lr: 4.0000e-02 eta: 1 day, 0:56:24 time: 0.3455 data_time: 0.0201 memory: 5826 grad_norm: 2.9305 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6262 loss: 2.6262 2022/10/07 12:44:20 - mmengine - INFO - Epoch(train) [26][540/2119] lr: 4.0000e-02 eta: 1 day, 0:56:16 time: 0.3288 data_time: 0.0215 memory: 5826 grad_norm: 2.9793 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7403 loss: 2.7403 2022/10/07 12:44:26 - mmengine - INFO - Epoch(train) [26][560/2119] lr: 4.0000e-02 eta: 1 day, 0:56:08 time: 0.3273 data_time: 0.0259 memory: 5826 grad_norm: 2.9219 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7043 loss: 2.7043 2022/10/07 12:44:32 - mmengine - INFO - Epoch(train) [26][580/2119] lr: 4.0000e-02 eta: 1 day, 0:55:59 time: 0.3173 data_time: 0.0191 memory: 5826 grad_norm: 2.9553 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9662 loss: 2.9662 2022/10/07 12:44:40 - mmengine - INFO - Epoch(train) [26][600/2119] lr: 4.0000e-02 eta: 1 day, 0:55:57 time: 0.3839 data_time: 0.0251 memory: 5826 grad_norm: 2.9202 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7480 loss: 2.7480 2022/10/07 12:44:47 - mmengine - INFO - Epoch(train) [26][620/2119] lr: 4.0000e-02 eta: 1 day, 0:55:51 time: 0.3539 data_time: 0.0193 memory: 5826 grad_norm: 2.9414 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7999 loss: 2.7999 2022/10/07 12:44:54 - mmengine - INFO - Epoch(train) [26][640/2119] lr: 4.0000e-02 eta: 1 day, 0:55:44 time: 0.3386 data_time: 0.0240 memory: 5826 grad_norm: 2.9913 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6135 loss: 2.6135 2022/10/07 12:45:00 - mmengine - INFO - Epoch(train) [26][660/2119] lr: 4.0000e-02 eta: 1 day, 0:55:33 time: 0.2909 data_time: 0.0237 memory: 5826 grad_norm: 2.9125 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.8303 loss: 2.8303 2022/10/07 12:45:07 - mmengine - INFO - Epoch(train) [26][680/2119] lr: 4.0000e-02 eta: 1 day, 0:55:26 time: 0.3422 data_time: 0.0216 memory: 5826 grad_norm: 2.9307 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8205 loss: 2.8205 2022/10/07 12:45:14 - mmengine - INFO - Epoch(train) [26][700/2119] lr: 4.0000e-02 eta: 1 day, 0:55:20 time: 0.3487 data_time: 0.0165 memory: 5826 grad_norm: 2.9703 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7452 loss: 2.7452 2022/10/07 12:45:21 - mmengine - INFO - Epoch(train) [26][720/2119] lr: 4.0000e-02 eta: 1 day, 0:55:16 time: 0.3610 data_time: 0.0205 memory: 5826 grad_norm: 2.9398 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7295 loss: 2.7295 2022/10/07 12:45:28 - mmengine - INFO - Epoch(train) [26][740/2119] lr: 4.0000e-02 eta: 1 day, 0:55:12 time: 0.3761 data_time: 0.0195 memory: 5826 grad_norm: 2.9403 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6457 loss: 2.6457 2022/10/07 12:45:36 - mmengine - INFO - Epoch(train) [26][760/2119] lr: 4.0000e-02 eta: 1 day, 0:55:07 time: 0.3578 data_time: 0.0184 memory: 5826 grad_norm: 2.9439 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6073 loss: 2.6073 2022/10/07 12:45:42 - mmengine - INFO - Epoch(train) [26][780/2119] lr: 4.0000e-02 eta: 1 day, 0:55:00 time: 0.3299 data_time: 0.0201 memory: 5826 grad_norm: 2.9210 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.7187 loss: 2.7187 2022/10/07 12:45:50 - mmengine - INFO - Epoch(train) [26][800/2119] lr: 4.0000e-02 eta: 1 day, 0:54:57 time: 0.3774 data_time: 0.0239 memory: 5826 grad_norm: 2.9668 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7400 loss: 2.7400 2022/10/07 12:45:56 - mmengine - INFO - Epoch(train) [26][820/2119] lr: 4.0000e-02 eta: 1 day, 0:54:49 time: 0.3290 data_time: 0.0175 memory: 5826 grad_norm: 2.9125 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5326 loss: 2.5326 2022/10/07 12:46:04 - mmengine - INFO - Epoch(train) [26][840/2119] lr: 4.0000e-02 eta: 1 day, 0:54:45 time: 0.3720 data_time: 0.0182 memory: 5826 grad_norm: 2.9525 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8910 loss: 2.8910 2022/10/07 12:46:11 - mmengine - INFO - Epoch(train) [26][860/2119] lr: 4.0000e-02 eta: 1 day, 0:54:38 time: 0.3417 data_time: 0.0187 memory: 5826 grad_norm: 2.9633 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4498 loss: 2.4498 2022/10/07 12:46:17 - mmengine - INFO - Epoch(train) [26][880/2119] lr: 4.0000e-02 eta: 1 day, 0:54:29 time: 0.3164 data_time: 0.0325 memory: 5826 grad_norm: 2.9286 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7344 loss: 2.7344 2022/10/07 12:46:24 - mmengine - INFO - Epoch(train) [26][900/2119] lr: 4.0000e-02 eta: 1 day, 0:54:23 time: 0.3487 data_time: 0.0172 memory: 5826 grad_norm: 2.9377 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7728 loss: 2.7728 2022/10/07 12:46:31 - mmengine - INFO - Epoch(train) [26][920/2119] lr: 4.0000e-02 eta: 1 day, 0:54:18 time: 0.3529 data_time: 0.0258 memory: 5826 grad_norm: 2.9769 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0002 loss: 3.0002 2022/10/07 12:46:37 - mmengine - INFO - Epoch(train) [26][940/2119] lr: 4.0000e-02 eta: 1 day, 0:54:08 time: 0.3095 data_time: 0.0177 memory: 5826 grad_norm: 2.9488 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8047 loss: 2.8047 2022/10/07 12:46:45 - mmengine - INFO - Epoch(train) [26][960/2119] lr: 4.0000e-02 eta: 1 day, 0:54:05 time: 0.3743 data_time: 0.0235 memory: 5826 grad_norm: 2.9902 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6814 loss: 2.6814 2022/10/07 12:46:51 - mmengine - INFO - Epoch(train) [26][980/2119] lr: 4.0000e-02 eta: 1 day, 0:53:58 time: 0.3410 data_time: 0.0190 memory: 5826 grad_norm: 2.9536 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.9769 loss: 2.9769 2022/10/07 12:46:59 - mmengine - INFO - Epoch(train) [26][1000/2119] lr: 4.0000e-02 eta: 1 day, 0:53:54 time: 0.3691 data_time: 0.0252 memory: 5826 grad_norm: 2.9735 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8829 loss: 2.8829 2022/10/07 12:47:05 - mmengine - INFO - Epoch(train) [26][1020/2119] lr: 4.0000e-02 eta: 1 day, 0:53:46 time: 0.3207 data_time: 0.0194 memory: 5826 grad_norm: 2.9881 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7971 loss: 2.7971 2022/10/07 12:47:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 12:47:13 - mmengine - INFO - Epoch(train) [26][1040/2119] lr: 4.0000e-02 eta: 1 day, 0:53:42 time: 0.3723 data_time: 0.0185 memory: 5826 grad_norm: 2.9557 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.8360 loss: 2.8360 2022/10/07 12:47:20 - mmengine - INFO - Epoch(train) [26][1060/2119] lr: 4.0000e-02 eta: 1 day, 0:53:36 time: 0.3461 data_time: 0.0189 memory: 5826 grad_norm: 2.9376 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.1154 loss: 3.1154 2022/10/07 12:47:28 - mmengine - INFO - Epoch(train) [26][1080/2119] lr: 4.0000e-02 eta: 1 day, 0:53:37 time: 0.4163 data_time: 0.0198 memory: 5826 grad_norm: 2.9276 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.9190 loss: 2.9190 2022/10/07 12:47:34 - mmengine - INFO - Epoch(train) [26][1100/2119] lr: 4.0000e-02 eta: 1 day, 0:53:26 time: 0.3051 data_time: 0.0193 memory: 5826 grad_norm: 2.8582 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7496 loss: 2.7496 2022/10/07 12:47:42 - mmengine - INFO - Epoch(train) [26][1120/2119] lr: 4.0000e-02 eta: 1 day, 0:53:25 time: 0.3945 data_time: 0.0211 memory: 5826 grad_norm: 3.0109 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6536 loss: 2.6536 2022/10/07 12:47:48 - mmengine - INFO - Epoch(train) [26][1140/2119] lr: 4.0000e-02 eta: 1 day, 0:53:16 time: 0.3194 data_time: 0.0209 memory: 5826 grad_norm: 2.9317 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5647 loss: 2.5647 2022/10/07 12:47:55 - mmengine - INFO - Epoch(train) [26][1160/2119] lr: 4.0000e-02 eta: 1 day, 0:53:10 time: 0.3428 data_time: 0.0242 memory: 5826 grad_norm: 2.9838 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8317 loss: 2.8317 2022/10/07 12:48:02 - mmengine - INFO - Epoch(train) [26][1180/2119] lr: 4.0000e-02 eta: 1 day, 0:53:03 time: 0.3464 data_time: 0.0229 memory: 5826 grad_norm: 2.9756 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.1452 loss: 3.1452 2022/10/07 12:48:09 - mmengine - INFO - Epoch(train) [26][1200/2119] lr: 4.0000e-02 eta: 1 day, 0:52:59 time: 0.3682 data_time: 0.0229 memory: 5826 grad_norm: 2.9231 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9322 loss: 2.9322 2022/10/07 12:48:16 - mmengine - INFO - Epoch(train) [26][1220/2119] lr: 4.0000e-02 eta: 1 day, 0:52:49 time: 0.3071 data_time: 0.0177 memory: 5826 grad_norm: 2.9096 top1_acc: 0.0625 top5_acc: 0.4375 loss_cls: 2.6573 loss: 2.6573 2022/10/07 12:48:22 - mmengine - INFO - Epoch(train) [26][1240/2119] lr: 4.0000e-02 eta: 1 day, 0:52:42 time: 0.3367 data_time: 0.0265 memory: 5826 grad_norm: 2.9079 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6914 loss: 2.6914 2022/10/07 12:48:29 - mmengine - INFO - Epoch(train) [26][1260/2119] lr: 4.0000e-02 eta: 1 day, 0:52:35 time: 0.3313 data_time: 0.0176 memory: 5826 grad_norm: 2.9376 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7989 loss: 2.7989 2022/10/07 12:48:35 - mmengine - INFO - Epoch(train) [26][1280/2119] lr: 4.0000e-02 eta: 1 day, 0:52:26 time: 0.3200 data_time: 0.0235 memory: 5826 grad_norm: 2.9291 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.9247 loss: 2.9247 2022/10/07 12:48:42 - mmengine - INFO - Epoch(train) [26][1300/2119] lr: 4.0000e-02 eta: 1 day, 0:52:19 time: 0.3416 data_time: 0.0156 memory: 5826 grad_norm: 2.9279 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9438 loss: 2.9438 2022/10/07 12:48:49 - mmengine - INFO - Epoch(train) [26][1320/2119] lr: 4.0000e-02 eta: 1 day, 0:52:13 time: 0.3453 data_time: 0.0279 memory: 5826 grad_norm: 2.9568 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.9003 loss: 2.9003 2022/10/07 12:48:56 - mmengine - INFO - Epoch(train) [26][1340/2119] lr: 4.0000e-02 eta: 1 day, 0:52:05 time: 0.3263 data_time: 0.0144 memory: 5826 grad_norm: 2.8995 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 2.6144 loss: 2.6144 2022/10/07 12:49:03 - mmengine - INFO - Epoch(train) [26][1360/2119] lr: 4.0000e-02 eta: 1 day, 0:51:59 time: 0.3475 data_time: 0.0232 memory: 5826 grad_norm: 2.8937 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8719 loss: 2.8719 2022/10/07 12:49:09 - mmengine - INFO - Epoch(train) [26][1380/2119] lr: 4.0000e-02 eta: 1 day, 0:51:51 time: 0.3243 data_time: 0.0177 memory: 5826 grad_norm: 2.9565 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7367 loss: 2.7367 2022/10/07 12:49:16 - mmengine - INFO - Epoch(train) [26][1400/2119] lr: 4.0000e-02 eta: 1 day, 0:51:45 time: 0.3531 data_time: 0.0271 memory: 5826 grad_norm: 2.8785 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5848 loss: 2.5848 2022/10/07 12:49:23 - mmengine - INFO - Epoch(train) [26][1420/2119] lr: 4.0000e-02 eta: 1 day, 0:51:40 time: 0.3510 data_time: 0.0165 memory: 5826 grad_norm: 2.9339 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7266 loss: 2.7266 2022/10/07 12:49:30 - mmengine - INFO - Epoch(train) [26][1440/2119] lr: 4.0000e-02 eta: 1 day, 0:51:32 time: 0.3318 data_time: 0.0239 memory: 5826 grad_norm: 2.9206 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5949 loss: 2.5949 2022/10/07 12:49:37 - mmengine - INFO - Epoch(train) [26][1460/2119] lr: 4.0000e-02 eta: 1 day, 0:51:25 time: 0.3426 data_time: 0.0207 memory: 5826 grad_norm: 2.8462 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7745 loss: 2.7745 2022/10/07 12:49:43 - mmengine - INFO - Epoch(train) [26][1480/2119] lr: 4.0000e-02 eta: 1 day, 0:51:18 time: 0.3303 data_time: 0.0222 memory: 5826 grad_norm: 2.8878 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7280 loss: 2.7280 2022/10/07 12:49:50 - mmengine - INFO - Epoch(train) [26][1500/2119] lr: 4.0000e-02 eta: 1 day, 0:51:10 time: 0.3293 data_time: 0.0179 memory: 5826 grad_norm: 2.9338 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7556 loss: 2.7556 2022/10/07 12:49:56 - mmengine - INFO - Epoch(train) [26][1520/2119] lr: 4.0000e-02 eta: 1 day, 0:51:02 time: 0.3275 data_time: 0.0248 memory: 5826 grad_norm: 2.9718 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7145 loss: 2.7145 2022/10/07 12:50:04 - mmengine - INFO - Epoch(train) [26][1540/2119] lr: 4.0000e-02 eta: 1 day, 0:51:01 time: 0.3970 data_time: 0.0216 memory: 5826 grad_norm: 2.9738 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.2509 loss: 3.2509 2022/10/07 12:50:11 - mmengine - INFO - Epoch(train) [26][1560/2119] lr: 4.0000e-02 eta: 1 day, 0:50:51 time: 0.3102 data_time: 0.0231 memory: 5826 grad_norm: 2.9730 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0368 loss: 3.0368 2022/10/07 12:50:18 - mmengine - INFO - Epoch(train) [26][1580/2119] lr: 4.0000e-02 eta: 1 day, 0:50:46 time: 0.3539 data_time: 0.0214 memory: 5826 grad_norm: 2.9571 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6882 loss: 2.6882 2022/10/07 12:50:24 - mmengine - INFO - Epoch(train) [26][1600/2119] lr: 4.0000e-02 eta: 1 day, 0:50:37 time: 0.3231 data_time: 0.0232 memory: 5826 grad_norm: 2.9544 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8131 loss: 2.8131 2022/10/07 12:50:32 - mmengine - INFO - Epoch(train) [26][1620/2119] lr: 4.0000e-02 eta: 1 day, 0:50:35 time: 0.3835 data_time: 0.0219 memory: 5826 grad_norm: 2.9407 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7875 loss: 2.7875 2022/10/07 12:50:38 - mmengine - INFO - Epoch(train) [26][1640/2119] lr: 4.0000e-02 eta: 1 day, 0:50:24 time: 0.3029 data_time: 0.0194 memory: 5826 grad_norm: 2.9072 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6746 loss: 2.6746 2022/10/07 12:50:45 - mmengine - INFO - Epoch(train) [26][1660/2119] lr: 4.0000e-02 eta: 1 day, 0:50:17 time: 0.3362 data_time: 0.0328 memory: 5826 grad_norm: 2.9399 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8799 loss: 2.8799 2022/10/07 12:50:51 - mmengine - INFO - Epoch(train) [26][1680/2119] lr: 4.0000e-02 eta: 1 day, 0:50:11 time: 0.3419 data_time: 0.0238 memory: 5826 grad_norm: 2.9050 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6982 loss: 2.6982 2022/10/07 12:50:58 - mmengine - INFO - Epoch(train) [26][1700/2119] lr: 4.0000e-02 eta: 1 day, 0:50:02 time: 0.3196 data_time: 0.0187 memory: 5826 grad_norm: 2.9132 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8304 loss: 2.8304 2022/10/07 12:51:05 - mmengine - INFO - Epoch(train) [26][1720/2119] lr: 4.0000e-02 eta: 1 day, 0:49:57 time: 0.3630 data_time: 0.0235 memory: 5826 grad_norm: 2.9338 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.6156 loss: 2.6156 2022/10/07 12:51:11 - mmengine - INFO - Epoch(train) [26][1740/2119] lr: 4.0000e-02 eta: 1 day, 0:49:49 time: 0.3243 data_time: 0.0179 memory: 5826 grad_norm: 2.9001 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8629 loss: 2.8629 2022/10/07 12:51:19 - mmengine - INFO - Epoch(train) [26][1760/2119] lr: 4.0000e-02 eta: 1 day, 0:49:46 time: 0.3732 data_time: 0.0247 memory: 5826 grad_norm: 2.9753 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8195 loss: 2.8195 2022/10/07 12:51:26 - mmengine - INFO - Epoch(train) [26][1780/2119] lr: 4.0000e-02 eta: 1 day, 0:49:40 time: 0.3573 data_time: 0.0184 memory: 5826 grad_norm: 2.9158 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5594 loss: 2.5594 2022/10/07 12:51:34 - mmengine - INFO - Epoch(train) [26][1800/2119] lr: 4.0000e-02 eta: 1 day, 0:49:39 time: 0.3999 data_time: 0.0226 memory: 5826 grad_norm: 2.9298 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9799 loss: 2.9799 2022/10/07 12:51:41 - mmengine - INFO - Epoch(train) [26][1820/2119] lr: 4.0000e-02 eta: 1 day, 0:49:32 time: 0.3369 data_time: 0.0264 memory: 5826 grad_norm: 2.9018 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 3.0267 loss: 3.0267 2022/10/07 12:51:47 - mmengine - INFO - Epoch(train) [26][1840/2119] lr: 4.0000e-02 eta: 1 day, 0:49:24 time: 0.3225 data_time: 0.0185 memory: 5826 grad_norm: 2.9448 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.6952 loss: 2.6952 2022/10/07 12:51:53 - mmengine - INFO - Epoch(train) [26][1860/2119] lr: 4.0000e-02 eta: 1 day, 0:49:13 time: 0.2983 data_time: 0.0227 memory: 5826 grad_norm: 2.9327 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8601 loss: 2.8601 2022/10/07 12:52:00 - mmengine - INFO - Epoch(train) [26][1880/2119] lr: 4.0000e-02 eta: 1 day, 0:49:06 time: 0.3400 data_time: 0.0244 memory: 5826 grad_norm: 2.8794 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8667 loss: 2.8667 2022/10/07 12:52:07 - mmengine - INFO - Epoch(train) [26][1900/2119] lr: 4.0000e-02 eta: 1 day, 0:49:01 time: 0.3558 data_time: 0.0298 memory: 5826 grad_norm: 2.9388 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6538 loss: 2.6538 2022/10/07 12:52:15 - mmengine - INFO - Epoch(train) [26][1920/2119] lr: 4.0000e-02 eta: 1 day, 0:48:58 time: 0.3794 data_time: 0.0217 memory: 5826 grad_norm: 2.9717 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7224 loss: 2.7224 2022/10/07 12:52:22 - mmengine - INFO - Epoch(train) [26][1940/2119] lr: 4.0000e-02 eta: 1 day, 0:48:55 time: 0.3813 data_time: 0.0165 memory: 5826 grad_norm: 2.9120 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6371 loss: 2.6371 2022/10/07 12:52:29 - mmengine - INFO - Epoch(train) [26][1960/2119] lr: 4.0000e-02 eta: 1 day, 0:48:47 time: 0.3290 data_time: 0.0252 memory: 5826 grad_norm: 2.9526 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7944 loss: 2.7944 2022/10/07 12:52:35 - mmengine - INFO - Epoch(train) [26][1980/2119] lr: 4.0000e-02 eta: 1 day, 0:48:39 time: 0.3232 data_time: 0.0179 memory: 5826 grad_norm: 2.9765 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8877 loss: 2.8877 2022/10/07 12:52:42 - mmengine - INFO - Epoch(train) [26][2000/2119] lr: 4.0000e-02 eta: 1 day, 0:48:31 time: 0.3256 data_time: 0.0225 memory: 5826 grad_norm: 2.9519 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8297 loss: 2.8297 2022/10/07 12:52:49 - mmengine - INFO - Epoch(train) [26][2020/2119] lr: 4.0000e-02 eta: 1 day, 0:48:24 time: 0.3363 data_time: 0.0196 memory: 5826 grad_norm: 2.9381 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8580 loss: 2.8580 2022/10/07 12:52:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 12:52:56 - mmengine - INFO - Epoch(train) [26][2040/2119] lr: 4.0000e-02 eta: 1 day, 0:48:19 time: 0.3645 data_time: 0.0259 memory: 5826 grad_norm: 2.9722 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5761 loss: 2.5761 2022/10/07 12:53:03 - mmengine - INFO - Epoch(train) [26][2060/2119] lr: 4.0000e-02 eta: 1 day, 0:48:12 time: 0.3314 data_time: 0.0190 memory: 5826 grad_norm: 2.9490 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8357 loss: 2.8357 2022/10/07 12:53:09 - mmengine - INFO - Epoch(train) [26][2080/2119] lr: 4.0000e-02 eta: 1 day, 0:48:05 time: 0.3386 data_time: 0.0198 memory: 5826 grad_norm: 2.9966 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7202 loss: 2.7202 2022/10/07 12:53:16 - mmengine - INFO - Epoch(train) [26][2100/2119] lr: 4.0000e-02 eta: 1 day, 0:47:56 time: 0.3184 data_time: 0.0208 memory: 5826 grad_norm: 2.9105 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9095 loss: 2.9095 2022/10/07 12:53:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 12:53:22 - mmengine - INFO - Epoch(train) [26][2119/2119] lr: 4.0000e-02 eta: 1 day, 0:47:56 time: 0.3245 data_time: 0.0204 memory: 5826 grad_norm: 2.9127 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6904 loss: 2.6904 2022/10/07 12:53:32 - mmengine - INFO - Epoch(train) [27][20/2119] lr: 4.0000e-02 eta: 1 day, 0:47:26 time: 0.4824 data_time: 0.2017 memory: 5826 grad_norm: 2.9320 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.5807 loss: 2.5807 2022/10/07 12:53:38 - mmengine - INFO - Epoch(train) [27][40/2119] lr: 4.0000e-02 eta: 1 day, 0:47:15 time: 0.3007 data_time: 0.0208 memory: 5826 grad_norm: 2.9285 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7438 loss: 2.7438 2022/10/07 12:53:45 - mmengine - INFO - Epoch(train) [27][60/2119] lr: 4.0000e-02 eta: 1 day, 0:47:11 time: 0.3696 data_time: 0.0261 memory: 5826 grad_norm: 2.9572 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4245 loss: 2.4245 2022/10/07 12:53:51 - mmengine - INFO - Epoch(train) [27][80/2119] lr: 4.0000e-02 eta: 1 day, 0:47:02 time: 0.3099 data_time: 0.0245 memory: 5826 grad_norm: 2.8865 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5796 loss: 2.5796 2022/10/07 12:53:59 - mmengine - INFO - Epoch(train) [27][100/2119] lr: 4.0000e-02 eta: 1 day, 0:46:57 time: 0.3674 data_time: 0.0223 memory: 5826 grad_norm: 2.9257 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.4998 loss: 2.4998 2022/10/07 12:54:05 - mmengine - INFO - Epoch(train) [27][120/2119] lr: 4.0000e-02 eta: 1 day, 0:46:51 time: 0.3417 data_time: 0.0295 memory: 5826 grad_norm: 3.0140 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6649 loss: 2.6649 2022/10/07 12:54:12 - mmengine - INFO - Epoch(train) [27][140/2119] lr: 4.0000e-02 eta: 1 day, 0:46:45 time: 0.3502 data_time: 0.0262 memory: 5826 grad_norm: 2.9928 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8735 loss: 2.8735 2022/10/07 12:54:18 - mmengine - INFO - Epoch(train) [27][160/2119] lr: 4.0000e-02 eta: 1 day, 0:46:34 time: 0.2973 data_time: 0.0195 memory: 5826 grad_norm: 2.9717 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8563 loss: 2.8563 2022/10/07 12:54:26 - mmengine - INFO - Epoch(train) [27][180/2119] lr: 4.0000e-02 eta: 1 day, 0:46:31 time: 0.3786 data_time: 0.0216 memory: 5826 grad_norm: 2.9601 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6269 loss: 2.6269 2022/10/07 12:54:32 - mmengine - INFO - Epoch(train) [27][200/2119] lr: 4.0000e-02 eta: 1 day, 0:46:23 time: 0.3231 data_time: 0.0236 memory: 5826 grad_norm: 3.1345 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6891 loss: 2.6891 2022/10/07 12:54:39 - mmengine - INFO - Epoch(train) [27][220/2119] lr: 4.0000e-02 eta: 1 day, 0:46:15 time: 0.3348 data_time: 0.0250 memory: 5826 grad_norm: 2.9912 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9068 loss: 2.9068 2022/10/07 12:54:46 - mmengine - INFO - Epoch(train) [27][240/2119] lr: 4.0000e-02 eta: 1 day, 0:46:10 time: 0.3533 data_time: 0.0192 memory: 5826 grad_norm: 2.9766 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8644 loss: 2.8644 2022/10/07 12:54:53 - mmengine - INFO - Epoch(train) [27][260/2119] lr: 4.0000e-02 eta: 1 day, 0:46:02 time: 0.3246 data_time: 0.0199 memory: 5826 grad_norm: 2.9221 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6361 loss: 2.6361 2022/10/07 12:54:59 - mmengine - INFO - Epoch(train) [27][280/2119] lr: 4.0000e-02 eta: 1 day, 0:45:54 time: 0.3324 data_time: 0.0227 memory: 5826 grad_norm: 2.9663 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8296 loss: 2.8296 2022/10/07 12:55:07 - mmengine - INFO - Epoch(train) [27][300/2119] lr: 4.0000e-02 eta: 1 day, 0:45:54 time: 0.4059 data_time: 0.0192 memory: 5826 grad_norm: 2.9723 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6756 loss: 2.6756 2022/10/07 12:55:14 - mmengine - INFO - Epoch(train) [27][320/2119] lr: 4.0000e-02 eta: 1 day, 0:45:45 time: 0.3160 data_time: 0.0229 memory: 5826 grad_norm: 2.9459 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5467 loss: 2.5467 2022/10/07 12:55:22 - mmengine - INFO - Epoch(train) [27][340/2119] lr: 4.0000e-02 eta: 1 day, 0:45:42 time: 0.3869 data_time: 0.0232 memory: 5826 grad_norm: 2.8898 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7834 loss: 2.7834 2022/10/07 12:55:27 - mmengine - INFO - Epoch(train) [27][360/2119] lr: 4.0000e-02 eta: 1 day, 0:45:31 time: 0.2910 data_time: 0.0267 memory: 5826 grad_norm: 2.9254 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8021 loss: 2.8021 2022/10/07 12:55:35 - mmengine - INFO - Epoch(train) [27][380/2119] lr: 4.0000e-02 eta: 1 day, 0:45:28 time: 0.3800 data_time: 0.0218 memory: 5826 grad_norm: 2.9756 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5840 loss: 2.5840 2022/10/07 12:55:41 - mmengine - INFO - Epoch(train) [27][400/2119] lr: 4.0000e-02 eta: 1 day, 0:45:19 time: 0.3168 data_time: 0.0217 memory: 5826 grad_norm: 2.9222 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6575 loss: 2.6575 2022/10/07 12:55:49 - mmengine - INFO - Epoch(train) [27][420/2119] lr: 4.0000e-02 eta: 1 day, 0:45:14 time: 0.3606 data_time: 0.0203 memory: 5826 grad_norm: 2.9479 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8133 loss: 2.8133 2022/10/07 12:55:55 - mmengine - INFO - Epoch(train) [27][440/2119] lr: 4.0000e-02 eta: 1 day, 0:45:05 time: 0.3186 data_time: 0.0203 memory: 5826 grad_norm: 2.9641 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7940 loss: 2.7940 2022/10/07 12:56:02 - mmengine - INFO - Epoch(train) [27][460/2119] lr: 4.0000e-02 eta: 1 day, 0:45:02 time: 0.3752 data_time: 0.0191 memory: 5826 grad_norm: 2.9424 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.5510 loss: 2.5510 2022/10/07 12:56:09 - mmengine - INFO - Epoch(train) [27][480/2119] lr: 4.0000e-02 eta: 1 day, 0:44:53 time: 0.3187 data_time: 0.0246 memory: 5826 grad_norm: 2.9575 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8159 loss: 2.8159 2022/10/07 12:56:15 - mmengine - INFO - Epoch(train) [27][500/2119] lr: 4.0000e-02 eta: 1 day, 0:44:45 time: 0.3289 data_time: 0.0217 memory: 5826 grad_norm: 2.9873 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.5812 loss: 2.5812 2022/10/07 12:56:23 - mmengine - INFO - Epoch(train) [27][520/2119] lr: 4.0000e-02 eta: 1 day, 0:44:42 time: 0.3793 data_time: 0.0229 memory: 5826 grad_norm: 2.9567 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8573 loss: 2.8573 2022/10/07 12:56:30 - mmengine - INFO - Epoch(train) [27][540/2119] lr: 4.0000e-02 eta: 1 day, 0:44:37 time: 0.3508 data_time: 0.0197 memory: 5826 grad_norm: 2.9845 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6665 loss: 2.6665 2022/10/07 12:56:37 - mmengine - INFO - Epoch(train) [27][560/2119] lr: 4.0000e-02 eta: 1 day, 0:44:31 time: 0.3485 data_time: 0.0224 memory: 5826 grad_norm: 2.9270 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8015 loss: 2.8015 2022/10/07 12:56:44 - mmengine - INFO - Epoch(train) [27][580/2119] lr: 4.0000e-02 eta: 1 day, 0:44:25 time: 0.3517 data_time: 0.0211 memory: 5826 grad_norm: 2.9815 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7156 loss: 2.7156 2022/10/07 12:56:51 - mmengine - INFO - Epoch(train) [27][600/2119] lr: 4.0000e-02 eta: 1 day, 0:44:17 time: 0.3276 data_time: 0.0245 memory: 5826 grad_norm: 2.9288 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7406 loss: 2.7406 2022/10/07 12:56:57 - mmengine - INFO - Epoch(train) [27][620/2119] lr: 4.0000e-02 eta: 1 day, 0:44:09 time: 0.3303 data_time: 0.0169 memory: 5826 grad_norm: 2.9468 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4961 loss: 2.4961 2022/10/07 12:57:03 - mmengine - INFO - Epoch(train) [27][640/2119] lr: 4.0000e-02 eta: 1 day, 0:44:00 time: 0.3131 data_time: 0.0250 memory: 5826 grad_norm: 2.9463 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5649 loss: 2.5649 2022/10/07 12:57:10 - mmengine - INFO - Epoch(train) [27][660/2119] lr: 4.0000e-02 eta: 1 day, 0:43:51 time: 0.3180 data_time: 0.0433 memory: 5826 grad_norm: 2.9936 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.6790 loss: 2.6790 2022/10/07 12:57:16 - mmengine - INFO - Epoch(train) [27][680/2119] lr: 4.0000e-02 eta: 1 day, 0:43:44 time: 0.3367 data_time: 0.0236 memory: 5826 grad_norm: 2.9398 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6877 loss: 2.6877 2022/10/07 12:57:24 - mmengine - INFO - Epoch(train) [27][700/2119] lr: 4.0000e-02 eta: 1 day, 0:43:40 time: 0.3703 data_time: 0.0143 memory: 5826 grad_norm: 3.0101 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9321 loss: 2.9321 2022/10/07 12:57:31 - mmengine - INFO - Epoch(train) [27][720/2119] lr: 4.0000e-02 eta: 1 day, 0:43:34 time: 0.3464 data_time: 0.0207 memory: 5826 grad_norm: 2.9208 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7338 loss: 2.7338 2022/10/07 12:57:37 - mmengine - INFO - Epoch(train) [27][740/2119] lr: 4.0000e-02 eta: 1 day, 0:43:24 time: 0.3079 data_time: 0.0143 memory: 5826 grad_norm: 2.9420 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9471 loss: 2.9471 2022/10/07 12:57:44 - mmengine - INFO - Epoch(train) [27][760/2119] lr: 4.0000e-02 eta: 1 day, 0:43:21 time: 0.3760 data_time: 0.0256 memory: 5826 grad_norm: 2.9737 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4702 loss: 2.4702 2022/10/07 12:57:51 - mmengine - INFO - Epoch(train) [27][780/2119] lr: 4.0000e-02 eta: 1 day, 0:43:13 time: 0.3276 data_time: 0.0168 memory: 5826 grad_norm: 2.9381 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7674 loss: 2.7674 2022/10/07 12:57:59 - mmengine - INFO - Epoch(train) [27][800/2119] lr: 4.0000e-02 eta: 1 day, 0:43:10 time: 0.3755 data_time: 0.0244 memory: 5826 grad_norm: 2.9847 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8502 loss: 2.8502 2022/10/07 12:58:05 - mmengine - INFO - Epoch(train) [27][820/2119] lr: 4.0000e-02 eta: 1 day, 0:43:01 time: 0.3174 data_time: 0.0228 memory: 5826 grad_norm: 2.9853 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8398 loss: 2.8398 2022/10/07 12:58:12 - mmengine - INFO - Epoch(train) [27][840/2119] lr: 4.0000e-02 eta: 1 day, 0:42:55 time: 0.3518 data_time: 0.0213 memory: 5826 grad_norm: 2.9461 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.6633 loss: 2.6633 2022/10/07 12:58:18 - mmengine - INFO - Epoch(train) [27][860/2119] lr: 4.0000e-02 eta: 1 day, 0:42:46 time: 0.3216 data_time: 0.0198 memory: 5826 grad_norm: 2.9997 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8183 loss: 2.8183 2022/10/07 12:58:26 - mmengine - INFO - Epoch(train) [27][880/2119] lr: 4.0000e-02 eta: 1 day, 0:42:42 time: 0.3665 data_time: 0.0240 memory: 5826 grad_norm: 2.9349 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7034 loss: 2.7034 2022/10/07 12:58:33 - mmengine - INFO - Epoch(train) [27][900/2119] lr: 4.0000e-02 eta: 1 day, 0:42:36 time: 0.3468 data_time: 0.0196 memory: 5826 grad_norm: 2.9549 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8895 loss: 2.8895 2022/10/07 12:58:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 12:58:40 - mmengine - INFO - Epoch(train) [27][920/2119] lr: 4.0000e-02 eta: 1 day, 0:42:33 time: 0.3810 data_time: 0.0258 memory: 5826 grad_norm: 2.9140 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8767 loss: 2.8767 2022/10/07 12:58:47 - mmengine - INFO - Epoch(train) [27][940/2119] lr: 4.0000e-02 eta: 1 day, 0:42:24 time: 0.3164 data_time: 0.0157 memory: 5826 grad_norm: 2.9793 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8212 loss: 2.8212 2022/10/07 12:58:54 - mmengine - INFO - Epoch(train) [27][960/2119] lr: 4.0000e-02 eta: 1 day, 0:42:18 time: 0.3510 data_time: 0.0263 memory: 5826 grad_norm: 2.9954 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8472 loss: 2.8472 2022/10/07 12:59:00 - mmengine - INFO - Epoch(train) [27][980/2119] lr: 4.0000e-02 eta: 1 day, 0:42:11 time: 0.3319 data_time: 0.0176 memory: 5826 grad_norm: 2.9288 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8640 loss: 2.8640 2022/10/07 12:59:08 - mmengine - INFO - Epoch(train) [27][1000/2119] lr: 4.0000e-02 eta: 1 day, 0:42:07 time: 0.3664 data_time: 0.0227 memory: 5826 grad_norm: 2.9783 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6893 loss: 2.6893 2022/10/07 12:59:14 - mmengine - INFO - Epoch(train) [27][1020/2119] lr: 4.0000e-02 eta: 1 day, 0:41:59 time: 0.3338 data_time: 0.0144 memory: 5826 grad_norm: 2.9919 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9220 loss: 2.9220 2022/10/07 12:59:22 - mmengine - INFO - Epoch(train) [27][1040/2119] lr: 4.0000e-02 eta: 1 day, 0:41:55 time: 0.3623 data_time: 0.0251 memory: 5826 grad_norm: 2.9509 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 3.0005 loss: 3.0005 2022/10/07 12:59:28 - mmengine - INFO - Epoch(train) [27][1060/2119] lr: 4.0000e-02 eta: 1 day, 0:41:44 time: 0.3041 data_time: 0.0225 memory: 5826 grad_norm: 2.9545 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9458 loss: 2.9458 2022/10/07 12:59:35 - mmengine - INFO - Epoch(train) [27][1080/2119] lr: 4.0000e-02 eta: 1 day, 0:41:41 time: 0.3805 data_time: 0.0195 memory: 5826 grad_norm: 2.9476 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.6556 loss: 2.6556 2022/10/07 12:59:42 - mmengine - INFO - Epoch(train) [27][1100/2119] lr: 4.0000e-02 eta: 1 day, 0:41:35 time: 0.3466 data_time: 0.0188 memory: 5826 grad_norm: 3.0210 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8633 loss: 2.8633 2022/10/07 12:59:49 - mmengine - INFO - Epoch(train) [27][1120/2119] lr: 4.0000e-02 eta: 1 day, 0:41:29 time: 0.3454 data_time: 0.0221 memory: 5826 grad_norm: 2.9606 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7414 loss: 2.7414 2022/10/07 12:59:56 - mmengine - INFO - Epoch(train) [27][1140/2119] lr: 4.0000e-02 eta: 1 day, 0:41:21 time: 0.3312 data_time: 0.0206 memory: 5826 grad_norm: 2.9592 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6952 loss: 2.6952 2022/10/07 13:00:04 - mmengine - INFO - Epoch(train) [27][1160/2119] lr: 4.0000e-02 eta: 1 day, 0:41:20 time: 0.3975 data_time: 0.0208 memory: 5826 grad_norm: 2.9592 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7234 loss: 2.7234 2022/10/07 13:00:10 - mmengine - INFO - Epoch(train) [27][1180/2119] lr: 4.0000e-02 eta: 1 day, 0:41:11 time: 0.3134 data_time: 0.0186 memory: 5826 grad_norm: 2.9555 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7649 loss: 2.7649 2022/10/07 13:00:17 - mmengine - INFO - Epoch(train) [27][1200/2119] lr: 4.0000e-02 eta: 1 day, 0:41:05 time: 0.3512 data_time: 0.0231 memory: 5826 grad_norm: 2.9214 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5817 loss: 2.5817 2022/10/07 13:00:24 - mmengine - INFO - Epoch(train) [27][1220/2119] lr: 4.0000e-02 eta: 1 day, 0:40:58 time: 0.3338 data_time: 0.0177 memory: 5826 grad_norm: 3.0612 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7542 loss: 2.7542 2022/10/07 13:00:31 - mmengine - INFO - Epoch(train) [27][1240/2119] lr: 4.0000e-02 eta: 1 day, 0:40:52 time: 0.3566 data_time: 0.0230 memory: 5826 grad_norm: 2.9950 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.7571 loss: 2.7571 2022/10/07 13:00:37 - mmengine - INFO - Epoch(train) [27][1260/2119] lr: 4.0000e-02 eta: 1 day, 0:40:43 time: 0.3122 data_time: 0.0217 memory: 5826 grad_norm: 2.9346 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6577 loss: 2.6577 2022/10/07 13:00:44 - mmengine - INFO - Epoch(train) [27][1280/2119] lr: 4.0000e-02 eta: 1 day, 0:40:37 time: 0.3498 data_time: 0.0254 memory: 5826 grad_norm: 2.9991 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5892 loss: 2.5892 2022/10/07 13:00:51 - mmengine - INFO - Epoch(train) [27][1300/2119] lr: 4.0000e-02 eta: 1 day, 0:40:29 time: 0.3259 data_time: 0.0159 memory: 5826 grad_norm: 3.0149 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7858 loss: 2.7858 2022/10/07 13:00:57 - mmengine - INFO - Epoch(train) [27][1320/2119] lr: 4.0000e-02 eta: 1 day, 0:40:22 time: 0.3368 data_time: 0.0213 memory: 5826 grad_norm: 2.9711 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9953 loss: 2.9953 2022/10/07 13:01:04 - mmengine - INFO - Epoch(train) [27][1340/2119] lr: 4.0000e-02 eta: 1 day, 0:40:15 time: 0.3414 data_time: 0.0128 memory: 5826 grad_norm: 2.9562 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9585 loss: 2.9585 2022/10/07 13:01:11 - mmengine - INFO - Epoch(train) [27][1360/2119] lr: 4.0000e-02 eta: 1 day, 0:40:10 time: 0.3509 data_time: 0.0250 memory: 5826 grad_norm: 2.9061 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8091 loss: 2.8091 2022/10/07 13:01:18 - mmengine - INFO - Epoch(train) [27][1380/2119] lr: 4.0000e-02 eta: 1 day, 0:40:01 time: 0.3200 data_time: 0.0224 memory: 5826 grad_norm: 2.9482 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6034 loss: 2.6034 2022/10/07 13:01:25 - mmengine - INFO - Epoch(train) [27][1400/2119] lr: 4.0000e-02 eta: 1 day, 0:39:55 time: 0.3511 data_time: 0.0242 memory: 5826 grad_norm: 3.0285 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8081 loss: 2.8081 2022/10/07 13:01:31 - mmengine - INFO - Epoch(train) [27][1420/2119] lr: 4.0000e-02 eta: 1 day, 0:39:49 time: 0.3467 data_time: 0.0187 memory: 5826 grad_norm: 2.9150 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9667 loss: 2.9667 2022/10/07 13:01:38 - mmengine - INFO - Epoch(train) [27][1440/2119] lr: 4.0000e-02 eta: 1 day, 0:39:42 time: 0.3343 data_time: 0.0245 memory: 5826 grad_norm: 2.9062 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0801 loss: 3.0801 2022/10/07 13:01:46 - mmengine - INFO - Epoch(train) [27][1460/2119] lr: 4.0000e-02 eta: 1 day, 0:39:38 time: 0.3755 data_time: 0.0246 memory: 5826 grad_norm: 2.9666 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8643 loss: 2.8643 2022/10/07 13:01:52 - mmengine - INFO - Epoch(train) [27][1480/2119] lr: 4.0000e-02 eta: 1 day, 0:39:29 time: 0.3119 data_time: 0.0281 memory: 5826 grad_norm: 2.9740 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9012 loss: 2.9012 2022/10/07 13:01:59 - mmengine - INFO - Epoch(train) [27][1500/2119] lr: 4.0000e-02 eta: 1 day, 0:39:22 time: 0.3353 data_time: 0.0241 memory: 5826 grad_norm: 2.9585 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7707 loss: 2.7707 2022/10/07 13:02:06 - mmengine - INFO - Epoch(train) [27][1520/2119] lr: 4.0000e-02 eta: 1 day, 0:39:17 time: 0.3598 data_time: 0.0268 memory: 5826 grad_norm: 2.9459 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8432 loss: 2.8432 2022/10/07 13:02:13 - mmengine - INFO - Epoch(train) [27][1540/2119] lr: 4.0000e-02 eta: 1 day, 0:39:12 time: 0.3604 data_time: 0.0136 memory: 5826 grad_norm: 2.9544 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6694 loss: 2.6694 2022/10/07 13:02:19 - mmengine - INFO - Epoch(train) [27][1560/2119] lr: 4.0000e-02 eta: 1 day, 0:39:03 time: 0.3132 data_time: 0.0281 memory: 5826 grad_norm: 2.9154 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8287 loss: 2.8287 2022/10/07 13:02:27 - mmengine - INFO - Epoch(train) [27][1580/2119] lr: 4.0000e-02 eta: 1 day, 0:38:58 time: 0.3661 data_time: 0.0209 memory: 5826 grad_norm: 2.9860 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9981 loss: 2.9981 2022/10/07 13:02:34 - mmengine - INFO - Epoch(train) [27][1600/2119] lr: 4.0000e-02 eta: 1 day, 0:38:52 time: 0.3450 data_time: 0.0284 memory: 5826 grad_norm: 2.9521 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8191 loss: 2.8191 2022/10/07 13:02:41 - mmengine - INFO - Epoch(train) [27][1620/2119] lr: 4.0000e-02 eta: 1 day, 0:38:46 time: 0.3511 data_time: 0.0178 memory: 5826 grad_norm: 2.9497 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7119 loss: 2.7119 2022/10/07 13:02:48 - mmengine - INFO - Epoch(train) [27][1640/2119] lr: 4.0000e-02 eta: 1 day, 0:38:41 time: 0.3566 data_time: 0.0204 memory: 5826 grad_norm: 2.9353 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9095 loss: 2.9095 2022/10/07 13:02:55 - mmengine - INFO - Epoch(train) [27][1660/2119] lr: 4.0000e-02 eta: 1 day, 0:38:36 time: 0.3556 data_time: 0.0241 memory: 5826 grad_norm: 2.9413 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8877 loss: 2.8877 2022/10/07 13:03:02 - mmengine - INFO - Epoch(train) [27][1680/2119] lr: 4.0000e-02 eta: 1 day, 0:38:32 time: 0.3700 data_time: 0.0220 memory: 5826 grad_norm: 2.9274 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7771 loss: 2.7771 2022/10/07 13:03:08 - mmengine - INFO - Epoch(train) [27][1700/2119] lr: 4.0000e-02 eta: 1 day, 0:38:22 time: 0.3105 data_time: 0.0177 memory: 5826 grad_norm: 3.0085 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6796 loss: 2.6796 2022/10/07 13:03:16 - mmengine - INFO - Epoch(train) [27][1720/2119] lr: 4.0000e-02 eta: 1 day, 0:38:19 time: 0.3779 data_time: 0.0266 memory: 5826 grad_norm: 2.9847 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.8764 loss: 2.8764 2022/10/07 13:03:22 - mmengine - INFO - Epoch(train) [27][1740/2119] lr: 4.0000e-02 eta: 1 day, 0:38:07 time: 0.2862 data_time: 0.0214 memory: 5826 grad_norm: 2.9637 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7925 loss: 2.7925 2022/10/07 13:03:28 - mmengine - INFO - Epoch(train) [27][1760/2119] lr: 4.0000e-02 eta: 1 day, 0:38:00 time: 0.3376 data_time: 0.0242 memory: 5826 grad_norm: 2.9065 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7095 loss: 2.7095 2022/10/07 13:03:35 - mmengine - INFO - Epoch(train) [27][1780/2119] lr: 4.0000e-02 eta: 1 day, 0:37:52 time: 0.3286 data_time: 0.0167 memory: 5826 grad_norm: 2.9701 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7402 loss: 2.7402 2022/10/07 13:03:42 - mmengine - INFO - Epoch(train) [27][1800/2119] lr: 4.0000e-02 eta: 1 day, 0:37:45 time: 0.3347 data_time: 0.0318 memory: 5826 grad_norm: 3.0031 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7665 loss: 2.7665 2022/10/07 13:03:49 - mmengine - INFO - Epoch(train) [27][1820/2119] lr: 4.0000e-02 eta: 1 day, 0:37:38 time: 0.3413 data_time: 0.0173 memory: 5826 grad_norm: 3.0410 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.9983 loss: 2.9983 2022/10/07 13:03:56 - mmengine - INFO - Epoch(train) [27][1840/2119] lr: 4.0000e-02 eta: 1 day, 0:37:33 time: 0.3588 data_time: 0.0214 memory: 5826 grad_norm: 2.9722 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8815 loss: 2.8815 2022/10/07 13:04:02 - mmengine - INFO - Epoch(train) [27][1860/2119] lr: 4.0000e-02 eta: 1 day, 0:37:26 time: 0.3387 data_time: 0.0199 memory: 5826 grad_norm: 2.9354 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6064 loss: 2.6064 2022/10/07 13:04:09 - mmengine - INFO - Epoch(train) [27][1880/2119] lr: 4.0000e-02 eta: 1 day, 0:37:19 time: 0.3306 data_time: 0.0285 memory: 5826 grad_norm: 2.9062 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8327 loss: 2.8327 2022/10/07 13:04:16 - mmengine - INFO - Epoch(train) [27][1900/2119] lr: 4.0000e-02 eta: 1 day, 0:37:13 time: 0.3496 data_time: 0.0213 memory: 5826 grad_norm: 2.9604 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7191 loss: 2.7191 2022/10/07 13:04:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 13:04:24 - mmengine - INFO - Epoch(train) [27][1920/2119] lr: 4.0000e-02 eta: 1 day, 0:37:11 time: 0.3882 data_time: 0.0208 memory: 5826 grad_norm: 2.9581 top1_acc: 0.2500 top5_acc: 0.3125 loss_cls: 2.5149 loss: 2.5149 2022/10/07 13:04:30 - mmengine - INFO - Epoch(train) [27][1940/2119] lr: 4.0000e-02 eta: 1 day, 0:37:01 time: 0.3065 data_time: 0.0198 memory: 5826 grad_norm: 2.9898 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8099 loss: 2.8099 2022/10/07 13:04:37 - mmengine - INFO - Epoch(train) [27][1960/2119] lr: 4.0000e-02 eta: 1 day, 0:36:56 time: 0.3637 data_time: 0.0208 memory: 5826 grad_norm: 2.9848 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8243 loss: 2.8243 2022/10/07 13:04:44 - mmengine - INFO - Epoch(train) [27][1980/2119] lr: 4.0000e-02 eta: 1 day, 0:36:49 time: 0.3317 data_time: 0.0247 memory: 5826 grad_norm: 2.9431 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7467 loss: 2.7467 2022/10/07 13:04:52 - mmengine - INFO - Epoch(train) [27][2000/2119] lr: 4.0000e-02 eta: 1 day, 0:36:46 time: 0.3827 data_time: 0.0224 memory: 5826 grad_norm: 2.9722 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8499 loss: 2.8499 2022/10/07 13:04:58 - mmengine - INFO - Epoch(train) [27][2020/2119] lr: 4.0000e-02 eta: 1 day, 0:36:36 time: 0.3128 data_time: 0.0293 memory: 5826 grad_norm: 2.9564 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 2.7353 loss: 2.7353 2022/10/07 13:05:04 - mmengine - INFO - Epoch(train) [27][2040/2119] lr: 4.0000e-02 eta: 1 day, 0:36:27 time: 0.3090 data_time: 0.0200 memory: 5826 grad_norm: 2.9603 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7542 loss: 2.7542 2022/10/07 13:05:11 - mmengine - INFO - Epoch(train) [27][2060/2119] lr: 4.0000e-02 eta: 1 day, 0:36:22 time: 0.3584 data_time: 0.0278 memory: 5826 grad_norm: 2.9529 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.4407 loss: 2.4407 2022/10/07 13:05:18 - mmengine - INFO - Epoch(train) [27][2080/2119] lr: 4.0000e-02 eta: 1 day, 0:36:14 time: 0.3269 data_time: 0.0272 memory: 5826 grad_norm: 2.9054 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7258 loss: 2.7258 2022/10/07 13:05:24 - mmengine - INFO - Epoch(train) [27][2100/2119] lr: 4.0000e-02 eta: 1 day, 0:36:06 time: 0.3346 data_time: 0.0261 memory: 5826 grad_norm: 2.9336 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8361 loss: 2.8361 2022/10/07 13:05:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 13:05:31 - mmengine - INFO - Epoch(train) [27][2119/2119] lr: 4.0000e-02 eta: 1 day, 0:36:06 time: 0.3204 data_time: 0.0192 memory: 5826 grad_norm: 2.9888 top1_acc: 0.3000 top5_acc: 0.6000 loss_cls: 2.9135 loss: 2.9135 2022/10/07 13:05:40 - mmengine - INFO - Epoch(train) [28][20/2119] lr: 4.0000e-02 eta: 1 day, 0:35:38 time: 0.4925 data_time: 0.2061 memory: 5826 grad_norm: 2.9463 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8630 loss: 2.8630 2022/10/07 13:05:47 - mmengine - INFO - Epoch(train) [28][40/2119] lr: 4.0000e-02 eta: 1 day, 0:35:31 time: 0.3409 data_time: 0.0296 memory: 5826 grad_norm: 2.9386 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 3.0262 loss: 3.0262 2022/10/07 13:05:54 - mmengine - INFO - Epoch(train) [28][60/2119] lr: 4.0000e-02 eta: 1 day, 0:35:24 time: 0.3390 data_time: 0.0215 memory: 5826 grad_norm: 2.9346 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8003 loss: 2.8003 2022/10/07 13:06:01 - mmengine - INFO - Epoch(train) [28][80/2119] lr: 4.0000e-02 eta: 1 day, 0:35:20 time: 0.3657 data_time: 0.0194 memory: 5826 grad_norm: 2.9760 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5926 loss: 2.5926 2022/10/07 13:06:08 - mmengine - INFO - Epoch(train) [28][100/2119] lr: 4.0000e-02 eta: 1 day, 0:35:14 time: 0.3517 data_time: 0.0230 memory: 5826 grad_norm: 2.9064 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9149 loss: 2.9149 2022/10/07 13:06:16 - mmengine - INFO - Epoch(train) [28][120/2119] lr: 4.0000e-02 eta: 1 day, 0:35:11 time: 0.3813 data_time: 0.0214 memory: 5826 grad_norm: 2.9186 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6597 loss: 2.6597 2022/10/07 13:06:22 - mmengine - INFO - Epoch(train) [28][140/2119] lr: 4.0000e-02 eta: 1 day, 0:35:02 time: 0.3129 data_time: 0.0228 memory: 5826 grad_norm: 3.0076 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7069 loss: 2.7069 2022/10/07 13:06:29 - mmengine - INFO - Epoch(train) [28][160/2119] lr: 4.0000e-02 eta: 1 day, 0:34:56 time: 0.3535 data_time: 0.0215 memory: 5826 grad_norm: 2.9804 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6391 loss: 2.6391 2022/10/07 13:06:35 - mmengine - INFO - Epoch(train) [28][180/2119] lr: 4.0000e-02 eta: 1 day, 0:34:44 time: 0.2834 data_time: 0.0217 memory: 5826 grad_norm: 2.9238 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6787 loss: 2.6787 2022/10/07 13:06:43 - mmengine - INFO - Epoch(train) [28][200/2119] lr: 4.0000e-02 eta: 1 day, 0:34:43 time: 0.3993 data_time: 0.0235 memory: 5826 grad_norm: 2.9550 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9372 loss: 2.9372 2022/10/07 13:06:49 - mmengine - INFO - Epoch(train) [28][220/2119] lr: 4.0000e-02 eta: 1 day, 0:34:34 time: 0.3150 data_time: 0.0217 memory: 5826 grad_norm: 2.9472 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5830 loss: 2.5830 2022/10/07 13:06:56 - mmengine - INFO - Epoch(train) [28][240/2119] lr: 4.0000e-02 eta: 1 day, 0:34:28 time: 0.3489 data_time: 0.0195 memory: 5826 grad_norm: 3.0209 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8611 loss: 2.8611 2022/10/07 13:07:03 - mmengine - INFO - Epoch(train) [28][260/2119] lr: 4.0000e-02 eta: 1 day, 0:34:22 time: 0.3524 data_time: 0.0250 memory: 5826 grad_norm: 2.9051 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9666 loss: 2.9666 2022/10/07 13:07:11 - mmengine - INFO - Epoch(train) [28][280/2119] lr: 4.0000e-02 eta: 1 day, 0:34:18 time: 0.3698 data_time: 0.0174 memory: 5826 grad_norm: 2.9636 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6927 loss: 2.6927 2022/10/07 13:07:17 - mmengine - INFO - Epoch(train) [28][300/2119] lr: 4.0000e-02 eta: 1 day, 0:34:10 time: 0.3270 data_time: 0.0149 memory: 5826 grad_norm: 2.9352 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6486 loss: 2.6486 2022/10/07 13:07:25 - mmengine - INFO - Epoch(train) [28][320/2119] lr: 4.0000e-02 eta: 1 day, 0:34:07 time: 0.3787 data_time: 0.0257 memory: 5826 grad_norm: 2.9457 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7816 loss: 2.7816 2022/10/07 13:07:31 - mmengine - INFO - Epoch(train) [28][340/2119] lr: 4.0000e-02 eta: 1 day, 0:33:58 time: 0.3113 data_time: 0.0167 memory: 5826 grad_norm: 2.9068 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8589 loss: 2.8589 2022/10/07 13:07:39 - mmengine - INFO - Epoch(train) [28][360/2119] lr: 4.0000e-02 eta: 1 day, 0:33:54 time: 0.3720 data_time: 0.0217 memory: 5826 grad_norm: 3.0144 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7130 loss: 2.7130 2022/10/07 13:07:45 - mmengine - INFO - Epoch(train) [28][380/2119] lr: 4.0000e-02 eta: 1 day, 0:33:46 time: 0.3243 data_time: 0.0187 memory: 5826 grad_norm: 2.9663 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7527 loss: 2.7527 2022/10/07 13:07:52 - mmengine - INFO - Epoch(train) [28][400/2119] lr: 4.0000e-02 eta: 1 day, 0:33:41 time: 0.3673 data_time: 0.0196 memory: 5826 grad_norm: 2.9002 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8018 loss: 2.8018 2022/10/07 13:07:58 - mmengine - INFO - Epoch(train) [28][420/2119] lr: 4.0000e-02 eta: 1 day, 0:33:31 time: 0.3019 data_time: 0.0237 memory: 5826 grad_norm: 2.9719 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6152 loss: 2.6152 2022/10/07 13:08:05 - mmengine - INFO - Epoch(train) [28][440/2119] lr: 4.0000e-02 eta: 1 day, 0:33:24 time: 0.3335 data_time: 0.0227 memory: 5826 grad_norm: 2.9142 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4604 loss: 2.4604 2022/10/07 13:08:12 - mmengine - INFO - Epoch(train) [28][460/2119] lr: 4.0000e-02 eta: 1 day, 0:33:17 time: 0.3369 data_time: 0.0201 memory: 5826 grad_norm: 2.9440 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.7856 loss: 2.7856 2022/10/07 13:08:18 - mmengine - INFO - Epoch(train) [28][480/2119] lr: 4.0000e-02 eta: 1 day, 0:33:09 time: 0.3295 data_time: 0.0214 memory: 5826 grad_norm: 2.9498 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7521 loss: 2.7521 2022/10/07 13:08:26 - mmengine - INFO - Epoch(train) [28][500/2119] lr: 4.0000e-02 eta: 1 day, 0:33:04 time: 0.3588 data_time: 0.0204 memory: 5826 grad_norm: 2.9580 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7743 loss: 2.7743 2022/10/07 13:08:33 - mmengine - INFO - Epoch(train) [28][520/2119] lr: 4.0000e-02 eta: 1 day, 0:32:59 time: 0.3659 data_time: 0.0171 memory: 5826 grad_norm: 2.9469 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9124 loss: 2.9124 2022/10/07 13:08:39 - mmengine - INFO - Epoch(train) [28][540/2119] lr: 4.0000e-02 eta: 1 day, 0:32:49 time: 0.3049 data_time: 0.0221 memory: 5826 grad_norm: 2.9260 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8408 loss: 2.8408 2022/10/07 13:08:47 - mmengine - INFO - Epoch(train) [28][560/2119] lr: 4.0000e-02 eta: 1 day, 0:32:46 time: 0.3736 data_time: 0.0180 memory: 5826 grad_norm: 2.9198 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8793 loss: 2.8793 2022/10/07 13:08:53 - mmengine - INFO - Epoch(train) [28][580/2119] lr: 4.0000e-02 eta: 1 day, 0:32:36 time: 0.3098 data_time: 0.0213 memory: 5826 grad_norm: 2.9617 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7117 loss: 2.7117 2022/10/07 13:09:00 - mmengine - INFO - Epoch(train) [28][600/2119] lr: 4.0000e-02 eta: 1 day, 0:32:30 time: 0.3428 data_time: 0.0217 memory: 5826 grad_norm: 2.9762 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7656 loss: 2.7656 2022/10/07 13:09:06 - mmengine - INFO - Epoch(train) [28][620/2119] lr: 4.0000e-02 eta: 1 day, 0:32:22 time: 0.3320 data_time: 0.0176 memory: 5826 grad_norm: 3.0164 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7335 loss: 2.7335 2022/10/07 13:09:14 - mmengine - INFO - Epoch(train) [28][640/2119] lr: 4.0000e-02 eta: 1 day, 0:32:18 time: 0.3645 data_time: 0.0165 memory: 5826 grad_norm: 2.9755 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8176 loss: 2.8176 2022/10/07 13:09:20 - mmengine - INFO - Epoch(train) [28][660/2119] lr: 4.0000e-02 eta: 1 day, 0:32:08 time: 0.3089 data_time: 0.0214 memory: 5826 grad_norm: 2.9674 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8898 loss: 2.8898 2022/10/07 13:09:26 - mmengine - INFO - Epoch(train) [28][680/2119] lr: 4.0000e-02 eta: 1 day, 0:32:00 time: 0.3222 data_time: 0.0247 memory: 5826 grad_norm: 2.9232 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7787 loss: 2.7787 2022/10/07 13:09:33 - mmengine - INFO - Epoch(train) [28][700/2119] lr: 4.0000e-02 eta: 1 day, 0:31:53 time: 0.3443 data_time: 0.0252 memory: 5826 grad_norm: 2.9385 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8599 loss: 2.8599 2022/10/07 13:09:40 - mmengine - INFO - Epoch(train) [28][720/2119] lr: 4.0000e-02 eta: 1 day, 0:31:48 time: 0.3565 data_time: 0.0248 memory: 5826 grad_norm: 2.9171 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5862 loss: 2.5862 2022/10/07 13:09:46 - mmengine - INFO - Epoch(train) [28][740/2119] lr: 4.0000e-02 eta: 1 day, 0:31:36 time: 0.2775 data_time: 0.0174 memory: 5826 grad_norm: 2.9368 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.5578 loss: 2.5578 2022/10/07 13:09:53 - mmengine - INFO - Epoch(train) [28][760/2119] lr: 4.0000e-02 eta: 1 day, 0:31:33 time: 0.3878 data_time: 0.0287 memory: 5826 grad_norm: 2.9498 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9280 loss: 2.9280 2022/10/07 13:09:59 - mmengine - INFO - Epoch(train) [28][780/2119] lr: 4.0000e-02 eta: 1 day, 0:31:22 time: 0.2959 data_time: 0.0180 memory: 5826 grad_norm: 2.9480 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6063 loss: 2.6063 2022/10/07 13:10:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 13:10:08 - mmengine - INFO - Epoch(train) [28][800/2119] lr: 4.0000e-02 eta: 1 day, 0:31:22 time: 0.4124 data_time: 0.0234 memory: 5826 grad_norm: 2.9356 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7737 loss: 2.7737 2022/10/07 13:10:14 - mmengine - INFO - Epoch(train) [28][820/2119] lr: 4.0000e-02 eta: 1 day, 0:31:14 time: 0.3222 data_time: 0.0223 memory: 5826 grad_norm: 2.9408 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6628 loss: 2.6628 2022/10/07 13:10:21 - mmengine - INFO - Epoch(train) [28][840/2119] lr: 4.0000e-02 eta: 1 day, 0:31:08 time: 0.3509 data_time: 0.0200 memory: 5826 grad_norm: 2.9527 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7415 loss: 2.7415 2022/10/07 13:10:27 - mmengine - INFO - Epoch(train) [28][860/2119] lr: 4.0000e-02 eta: 1 day, 0:30:58 time: 0.3050 data_time: 0.0243 memory: 5826 grad_norm: 2.9786 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8430 loss: 2.8430 2022/10/07 13:10:35 - mmengine - INFO - Epoch(train) [28][880/2119] lr: 4.0000e-02 eta: 1 day, 0:30:54 time: 0.3755 data_time: 0.0182 memory: 5826 grad_norm: 2.9784 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.7068 loss: 2.7068 2022/10/07 13:10:41 - mmengine - INFO - Epoch(train) [28][900/2119] lr: 4.0000e-02 eta: 1 day, 0:30:44 time: 0.3029 data_time: 0.0202 memory: 5826 grad_norm: 2.9873 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6171 loss: 2.6171 2022/10/07 13:10:48 - mmengine - INFO - Epoch(train) [28][920/2119] lr: 4.0000e-02 eta: 1 day, 0:30:41 time: 0.3741 data_time: 0.0195 memory: 5826 grad_norm: 2.9583 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6963 loss: 2.6963 2022/10/07 13:10:54 - mmengine - INFO - Epoch(train) [28][940/2119] lr: 4.0000e-02 eta: 1 day, 0:30:31 time: 0.3065 data_time: 0.0244 memory: 5826 grad_norm: 2.9250 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8619 loss: 2.8619 2022/10/07 13:11:01 - mmengine - INFO - Epoch(train) [28][960/2119] lr: 4.0000e-02 eta: 1 day, 0:30:25 time: 0.3444 data_time: 0.0235 memory: 5826 grad_norm: 2.9464 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7581 loss: 2.7581 2022/10/07 13:11:08 - mmengine - INFO - Epoch(train) [28][980/2119] lr: 4.0000e-02 eta: 1 day, 0:30:16 time: 0.3202 data_time: 0.0206 memory: 5826 grad_norm: 2.9665 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7014 loss: 2.7014 2022/10/07 13:11:15 - mmengine - INFO - Epoch(train) [28][1000/2119] lr: 4.0000e-02 eta: 1 day, 0:30:12 time: 0.3712 data_time: 0.0277 memory: 5826 grad_norm: 2.8821 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6392 loss: 2.6392 2022/10/07 13:11:21 - mmengine - INFO - Epoch(train) [28][1020/2119] lr: 4.0000e-02 eta: 1 day, 0:30:03 time: 0.3157 data_time: 0.0161 memory: 5826 grad_norm: 3.0220 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6056 loss: 2.6056 2022/10/07 13:11:29 - mmengine - INFO - Epoch(train) [28][1040/2119] lr: 4.0000e-02 eta: 1 day, 0:29:59 time: 0.3748 data_time: 0.0227 memory: 5826 grad_norm: 2.9860 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8597 loss: 2.8597 2022/10/07 13:11:35 - mmengine - INFO - Epoch(train) [28][1060/2119] lr: 4.0000e-02 eta: 1 day, 0:29:51 time: 0.3219 data_time: 0.0192 memory: 5826 grad_norm: 2.9833 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7837 loss: 2.7837 2022/10/07 13:11:42 - mmengine - INFO - Epoch(train) [28][1080/2119] lr: 4.0000e-02 eta: 1 day, 0:29:43 time: 0.3274 data_time: 0.0204 memory: 5826 grad_norm: 2.9603 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7041 loss: 2.7041 2022/10/07 13:11:48 - mmengine - INFO - Epoch(train) [28][1100/2119] lr: 4.0000e-02 eta: 1 day, 0:29:35 time: 0.3205 data_time: 0.0204 memory: 5826 grad_norm: 2.9620 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8765 loss: 2.8765 2022/10/07 13:11:56 - mmengine - INFO - Epoch(train) [28][1120/2119] lr: 4.0000e-02 eta: 1 day, 0:29:30 time: 0.3639 data_time: 0.0224 memory: 5826 grad_norm: 2.9626 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6864 loss: 2.6864 2022/10/07 13:12:02 - mmengine - INFO - Epoch(train) [28][1140/2119] lr: 4.0000e-02 eta: 1 day, 0:29:22 time: 0.3267 data_time: 0.0203 memory: 5826 grad_norm: 2.9197 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6234 loss: 2.6234 2022/10/07 13:12:09 - mmengine - INFO - Epoch(train) [28][1160/2119] lr: 4.0000e-02 eta: 1 day, 0:29:16 time: 0.3502 data_time: 0.0208 memory: 5826 grad_norm: 2.9564 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7471 loss: 2.7471 2022/10/07 13:12:15 - mmengine - INFO - Epoch(train) [28][1180/2119] lr: 4.0000e-02 eta: 1 day, 0:29:07 time: 0.3133 data_time: 0.0255 memory: 5826 grad_norm: 3.0099 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6939 loss: 2.6939 2022/10/07 13:12:23 - mmengine - INFO - Epoch(train) [28][1200/2119] lr: 4.0000e-02 eta: 1 day, 0:29:06 time: 0.3998 data_time: 0.0186 memory: 5826 grad_norm: 3.0012 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7083 loss: 2.7083 2022/10/07 13:12:30 - mmengine - INFO - Epoch(train) [28][1220/2119] lr: 4.0000e-02 eta: 1 day, 0:28:57 time: 0.3221 data_time: 0.0182 memory: 5826 grad_norm: 2.9913 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9269 loss: 2.9269 2022/10/07 13:12:37 - mmengine - INFO - Epoch(train) [28][1240/2119] lr: 4.0000e-02 eta: 1 day, 0:28:51 time: 0.3455 data_time: 0.0226 memory: 5826 grad_norm: 2.9376 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9174 loss: 2.9174 2022/10/07 13:12:44 - mmengine - INFO - Epoch(train) [28][1260/2119] lr: 4.0000e-02 eta: 1 day, 0:28:45 time: 0.3468 data_time: 0.0224 memory: 5826 grad_norm: 2.9796 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8135 loss: 2.8135 2022/10/07 13:12:51 - mmengine - INFO - Epoch(train) [28][1280/2119] lr: 4.0000e-02 eta: 1 day, 0:28:40 time: 0.3580 data_time: 0.0210 memory: 5826 grad_norm: 2.9861 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8510 loss: 2.8510 2022/10/07 13:12:56 - mmengine - INFO - Epoch(train) [28][1300/2119] lr: 4.0000e-02 eta: 1 day, 0:28:27 time: 0.2759 data_time: 0.0290 memory: 5826 grad_norm: 3.0266 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9269 loss: 2.9269 2022/10/07 13:13:04 - mmengine - INFO - Epoch(train) [28][1320/2119] lr: 4.0000e-02 eta: 1 day, 0:28:24 time: 0.3846 data_time: 0.0184 memory: 5826 grad_norm: 2.9803 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8469 loss: 2.8469 2022/10/07 13:13:10 - mmengine - INFO - Epoch(train) [28][1340/2119] lr: 4.0000e-02 eta: 1 day, 0:28:12 time: 0.2802 data_time: 0.0206 memory: 5826 grad_norm: 2.9568 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8410 loss: 2.8410 2022/10/07 13:13:17 - mmengine - INFO - Epoch(train) [28][1360/2119] lr: 4.0000e-02 eta: 1 day, 0:28:08 time: 0.3730 data_time: 0.0231 memory: 5826 grad_norm: 3.0108 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7964 loss: 2.7964 2022/10/07 13:13:24 - mmengine - INFO - Epoch(train) [28][1380/2119] lr: 4.0000e-02 eta: 1 day, 0:28:02 time: 0.3482 data_time: 0.0202 memory: 5826 grad_norm: 2.9771 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7834 loss: 2.7834 2022/10/07 13:13:31 - mmengine - INFO - Epoch(train) [28][1400/2119] lr: 4.0000e-02 eta: 1 day, 0:27:55 time: 0.3384 data_time: 0.0206 memory: 5826 grad_norm: 2.9480 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7223 loss: 2.7223 2022/10/07 13:13:38 - mmengine - INFO - Epoch(train) [28][1420/2119] lr: 4.0000e-02 eta: 1 day, 0:27:48 time: 0.3343 data_time: 0.0195 memory: 5826 grad_norm: 2.9450 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8397 loss: 2.8397 2022/10/07 13:13:45 - mmengine - INFO - Epoch(train) [28][1440/2119] lr: 4.0000e-02 eta: 1 day, 0:27:46 time: 0.3891 data_time: 0.0273 memory: 5826 grad_norm: 2.9420 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8897 loss: 2.8897 2022/10/07 13:13:51 - mmengine - INFO - Epoch(train) [28][1460/2119] lr: 4.0000e-02 eta: 1 day, 0:27:36 time: 0.3054 data_time: 0.0177 memory: 5826 grad_norm: 2.9615 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8820 loss: 2.8820 2022/10/07 13:13:59 - mmengine - INFO - Epoch(train) [28][1480/2119] lr: 4.0000e-02 eta: 1 day, 0:27:31 time: 0.3564 data_time: 0.0285 memory: 5826 grad_norm: 2.9238 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6105 loss: 2.6105 2022/10/07 13:14:06 - mmengine - INFO - Epoch(train) [28][1500/2119] lr: 4.0000e-02 eta: 1 day, 0:27:27 time: 0.3784 data_time: 0.0236 memory: 5826 grad_norm: 2.9163 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7398 loss: 2.7398 2022/10/07 13:14:14 - mmengine - INFO - Epoch(train) [28][1520/2119] lr: 4.0000e-02 eta: 1 day, 0:27:26 time: 0.3996 data_time: 0.0237 memory: 5826 grad_norm: 2.9825 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.7431 loss: 2.7431 2022/10/07 13:14:20 - mmengine - INFO - Epoch(train) [28][1540/2119] lr: 4.0000e-02 eta: 1 day, 0:27:14 time: 0.2849 data_time: 0.0205 memory: 5826 grad_norm: 2.9886 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8014 loss: 2.8014 2022/10/07 13:14:28 - mmengine - INFO - Epoch(train) [28][1560/2119] lr: 4.0000e-02 eta: 1 day, 0:27:12 time: 0.3889 data_time: 0.0229 memory: 5826 grad_norm: 2.9597 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6948 loss: 2.6948 2022/10/07 13:14:34 - mmengine - INFO - Epoch(train) [28][1580/2119] lr: 4.0000e-02 eta: 1 day, 0:27:03 time: 0.3245 data_time: 0.0193 memory: 5826 grad_norm: 2.9416 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8903 loss: 2.8903 2022/10/07 13:14:41 - mmengine - INFO - Epoch(train) [28][1600/2119] lr: 4.0000e-02 eta: 1 day, 0:26:56 time: 0.3358 data_time: 0.0192 memory: 5826 grad_norm: 2.9425 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8655 loss: 2.8655 2022/10/07 13:14:47 - mmengine - INFO - Epoch(train) [28][1620/2119] lr: 4.0000e-02 eta: 1 day, 0:26:47 time: 0.3100 data_time: 0.0202 memory: 5826 grad_norm: 2.9751 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7084 loss: 2.7084 2022/10/07 13:14:54 - mmengine - INFO - Epoch(train) [28][1640/2119] lr: 4.0000e-02 eta: 1 day, 0:26:40 time: 0.3392 data_time: 0.0172 memory: 5826 grad_norm: 3.0235 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9736 loss: 2.9736 2022/10/07 13:15:01 - mmengine - INFO - Epoch(train) [28][1660/2119] lr: 4.0000e-02 eta: 1 day, 0:26:33 time: 0.3362 data_time: 0.0182 memory: 5826 grad_norm: 2.9202 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6829 loss: 2.6829 2022/10/07 13:15:08 - mmengine - INFO - Epoch(train) [28][1680/2119] lr: 4.0000e-02 eta: 1 day, 0:26:29 time: 0.3731 data_time: 0.0270 memory: 5826 grad_norm: 2.9502 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5905 loss: 2.5905 2022/10/07 13:15:14 - mmengine - INFO - Epoch(train) [28][1700/2119] lr: 4.0000e-02 eta: 1 day, 0:26:20 time: 0.3108 data_time: 0.0223 memory: 5826 grad_norm: 2.9199 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8036 loss: 2.8036 2022/10/07 13:15:22 - mmengine - INFO - Epoch(train) [28][1720/2119] lr: 4.0000e-02 eta: 1 day, 0:26:19 time: 0.4093 data_time: 0.0231 memory: 5826 grad_norm: 2.8962 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7116 loss: 2.7116 2022/10/07 13:15:28 - mmengine - INFO - Epoch(train) [28][1740/2119] lr: 4.0000e-02 eta: 1 day, 0:26:08 time: 0.2921 data_time: 0.0253 memory: 5826 grad_norm: 2.9799 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7783 loss: 2.7783 2022/10/07 13:15:36 - mmengine - INFO - Epoch(train) [28][1760/2119] lr: 4.0000e-02 eta: 1 day, 0:26:05 time: 0.3883 data_time: 0.0220 memory: 5826 grad_norm: 2.9767 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6683 loss: 2.6683 2022/10/07 13:15:42 - mmengine - INFO - Epoch(train) [28][1780/2119] lr: 4.0000e-02 eta: 1 day, 0:25:56 time: 0.3149 data_time: 0.0219 memory: 5826 grad_norm: 2.9545 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8808 loss: 2.8808 2022/10/07 13:15:45 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 13:15:50 - mmengine - INFO - Epoch(train) [28][1800/2119] lr: 4.0000e-02 eta: 1 day, 0:25:53 time: 0.3776 data_time: 0.0200 memory: 5826 grad_norm: 2.9552 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7005 loss: 2.7005 2022/10/07 13:15:56 - mmengine - INFO - Epoch(train) [28][1820/2119] lr: 4.0000e-02 eta: 1 day, 0:25:44 time: 0.3195 data_time: 0.0165 memory: 5826 grad_norm: 2.9425 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8722 loss: 2.8722 2022/10/07 13:16:04 - mmengine - INFO - Epoch(train) [28][1840/2119] lr: 4.0000e-02 eta: 1 day, 0:25:39 time: 0.3613 data_time: 0.0187 memory: 5826 grad_norm: 2.9781 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6008 loss: 2.6008 2022/10/07 13:16:10 - mmengine - INFO - Epoch(train) [28][1860/2119] lr: 4.0000e-02 eta: 1 day, 0:25:32 time: 0.3301 data_time: 0.0179 memory: 5826 grad_norm: 2.9948 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6183 loss: 2.6183 2022/10/07 13:16:17 - mmengine - INFO - Epoch(train) [28][1880/2119] lr: 4.0000e-02 eta: 1 day, 0:25:27 time: 0.3582 data_time: 0.0209 memory: 5826 grad_norm: 2.9451 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7975 loss: 2.7975 2022/10/07 13:16:24 - mmengine - INFO - Epoch(train) [28][1900/2119] lr: 4.0000e-02 eta: 1 day, 0:25:19 time: 0.3246 data_time: 0.0278 memory: 5826 grad_norm: 2.9695 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.8415 loss: 2.8415 2022/10/07 13:16:31 - mmengine - INFO - Epoch(train) [28][1920/2119] lr: 4.0000e-02 eta: 1 day, 0:25:12 time: 0.3438 data_time: 0.0252 memory: 5826 grad_norm: 2.9736 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1689 loss: 3.1689 2022/10/07 13:16:37 - mmengine - INFO - Epoch(train) [28][1940/2119] lr: 4.0000e-02 eta: 1 day, 0:25:03 time: 0.3155 data_time: 0.0235 memory: 5826 grad_norm: 2.9345 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6795 loss: 2.6795 2022/10/07 13:16:44 - mmengine - INFO - Epoch(train) [28][1960/2119] lr: 4.0000e-02 eta: 1 day, 0:24:57 time: 0.3485 data_time: 0.0214 memory: 5826 grad_norm: 2.9800 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6651 loss: 2.6651 2022/10/07 13:16:50 - mmengine - INFO - Epoch(train) [28][1980/2119] lr: 4.0000e-02 eta: 1 day, 0:24:49 time: 0.3264 data_time: 0.0213 memory: 5826 grad_norm: 2.9077 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5414 loss: 2.5414 2022/10/07 13:16:58 - mmengine - INFO - Epoch(train) [28][2000/2119] lr: 4.0000e-02 eta: 1 day, 0:24:45 time: 0.3738 data_time: 0.0208 memory: 5826 grad_norm: 2.9199 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8056 loss: 2.8056 2022/10/07 13:17:05 - mmengine - INFO - Epoch(train) [28][2020/2119] lr: 4.0000e-02 eta: 1 day, 0:24:38 time: 0.3280 data_time: 0.0186 memory: 5826 grad_norm: 2.9844 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6800 loss: 2.6800 2022/10/07 13:17:12 - mmengine - INFO - Epoch(train) [28][2040/2119] lr: 4.0000e-02 eta: 1 day, 0:24:34 time: 0.3767 data_time: 0.0263 memory: 5826 grad_norm: 2.9366 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9178 loss: 2.9178 2022/10/07 13:17:18 - mmengine - INFO - Epoch(train) [28][2060/2119] lr: 4.0000e-02 eta: 1 day, 0:24:24 time: 0.3089 data_time: 0.0192 memory: 5826 grad_norm: 2.9106 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6440 loss: 2.6440 2022/10/07 13:17:26 - mmengine - INFO - Epoch(train) [28][2080/2119] lr: 4.0000e-02 eta: 1 day, 0:24:20 time: 0.3681 data_time: 0.0206 memory: 5826 grad_norm: 2.9804 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.9232 loss: 2.9232 2022/10/07 13:17:32 - mmengine - INFO - Epoch(train) [28][2100/2119] lr: 4.0000e-02 eta: 1 day, 0:24:11 time: 0.3108 data_time: 0.0216 memory: 5826 grad_norm: 2.9484 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8452 loss: 2.8452 2022/10/07 13:17:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 13:17:38 - mmengine - INFO - Epoch(train) [28][2119/2119] lr: 4.0000e-02 eta: 1 day, 0:24:11 time: 0.3132 data_time: 0.0178 memory: 5826 grad_norm: 3.0136 top1_acc: 0.4000 top5_acc: 0.6000 loss_cls: 2.7692 loss: 2.7692 2022/10/07 13:17:38 - mmengine - INFO - Saving checkpoint at 28 epochs 2022/10/07 13:17:57 - mmengine - INFO - Epoch(train) [29][20/2119] lr: 4.0000e-02 eta: 1 day, 0:23:34 time: 0.3920 data_time: 0.1784 memory: 5826 grad_norm: 2.9335 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5716 loss: 2.5716 2022/10/07 13:18:03 - mmengine - INFO - Epoch(train) [29][40/2119] lr: 4.0000e-02 eta: 1 day, 0:23:24 time: 0.3024 data_time: 0.0648 memory: 5826 grad_norm: 3.0046 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9400 loss: 2.9400 2022/10/07 13:18:10 - mmengine - INFO - Epoch(train) [29][60/2119] lr: 4.0000e-02 eta: 1 day, 0:23:19 time: 0.3620 data_time: 0.0393 memory: 5826 grad_norm: 2.9544 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8046 loss: 2.8046 2022/10/07 13:18:17 - mmengine - INFO - Epoch(train) [29][80/2119] lr: 4.0000e-02 eta: 1 day, 0:23:14 time: 0.3614 data_time: 0.0206 memory: 5826 grad_norm: 2.9710 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4535 loss: 2.4535 2022/10/07 13:18:24 - mmengine - INFO - Epoch(train) [29][100/2119] lr: 4.0000e-02 eta: 1 day, 0:23:06 time: 0.3254 data_time: 0.0194 memory: 5826 grad_norm: 2.9620 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5723 loss: 2.5723 2022/10/07 13:18:31 - mmengine - INFO - Epoch(train) [29][120/2119] lr: 4.0000e-02 eta: 1 day, 0:23:01 time: 0.3550 data_time: 0.0206 memory: 5826 grad_norm: 2.9856 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6647 loss: 2.6647 2022/10/07 13:18:37 - mmengine - INFO - Epoch(train) [29][140/2119] lr: 4.0000e-02 eta: 1 day, 0:22:50 time: 0.3007 data_time: 0.0250 memory: 5826 grad_norm: 2.9348 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8581 loss: 2.8581 2022/10/07 13:18:45 - mmengine - INFO - Epoch(train) [29][160/2119] lr: 4.0000e-02 eta: 1 day, 0:22:48 time: 0.3944 data_time: 0.0195 memory: 5826 grad_norm: 2.9752 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7119 loss: 2.7119 2022/10/07 13:18:50 - mmengine - INFO - Epoch(train) [29][180/2119] lr: 4.0000e-02 eta: 1 day, 0:22:36 time: 0.2791 data_time: 0.0192 memory: 5826 grad_norm: 2.9618 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5314 loss: 2.5314 2022/10/07 13:18:58 - mmengine - INFO - Epoch(train) [29][200/2119] lr: 4.0000e-02 eta: 1 day, 0:22:33 time: 0.3764 data_time: 0.0203 memory: 5826 grad_norm: 3.0005 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6611 loss: 2.6611 2022/10/07 13:19:05 - mmengine - INFO - Epoch(train) [29][220/2119] lr: 4.0000e-02 eta: 1 day, 0:22:26 time: 0.3374 data_time: 0.0202 memory: 5826 grad_norm: 2.9486 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8883 loss: 2.8883 2022/10/07 13:19:12 - mmengine - INFO - Epoch(train) [29][240/2119] lr: 4.0000e-02 eta: 1 day, 0:22:21 time: 0.3582 data_time: 0.0208 memory: 5826 grad_norm: 2.9589 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8053 loss: 2.8053 2022/10/07 13:19:19 - mmengine - INFO - Epoch(train) [29][260/2119] lr: 4.0000e-02 eta: 1 day, 0:22:13 time: 0.3332 data_time: 0.0190 memory: 5826 grad_norm: 2.9106 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6951 loss: 2.6951 2022/10/07 13:19:26 - mmengine - INFO - Epoch(train) [29][280/2119] lr: 4.0000e-02 eta: 1 day, 0:22:11 time: 0.3953 data_time: 0.0188 memory: 5826 grad_norm: 2.9685 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7975 loss: 2.7975 2022/10/07 13:19:34 - mmengine - INFO - Epoch(train) [29][300/2119] lr: 4.0000e-02 eta: 1 day, 0:22:06 time: 0.3576 data_time: 0.0262 memory: 5826 grad_norm: 2.9643 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7896 loss: 2.7896 2022/10/07 13:19:40 - mmengine - INFO - Epoch(train) [29][320/2119] lr: 4.0000e-02 eta: 1 day, 0:21:59 time: 0.3375 data_time: 0.0242 memory: 5826 grad_norm: 2.9826 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7480 loss: 2.7480 2022/10/07 13:19:47 - mmengine - INFO - Epoch(train) [29][340/2119] lr: 4.0000e-02 eta: 1 day, 0:21:53 time: 0.3435 data_time: 0.0196 memory: 5826 grad_norm: 2.9708 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7181 loss: 2.7181 2022/10/07 13:19:54 - mmengine - INFO - Epoch(train) [29][360/2119] lr: 4.0000e-02 eta: 1 day, 0:21:46 time: 0.3383 data_time: 0.0207 memory: 5826 grad_norm: 2.9404 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7885 loss: 2.7885 2022/10/07 13:20:00 - mmengine - INFO - Epoch(train) [29][380/2119] lr: 4.0000e-02 eta: 1 day, 0:21:37 time: 0.3154 data_time: 0.0199 memory: 5826 grad_norm: 2.9625 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7620 loss: 2.7620 2022/10/07 13:20:07 - mmengine - INFO - Epoch(train) [29][400/2119] lr: 4.0000e-02 eta: 1 day, 0:21:31 time: 0.3464 data_time: 0.0199 memory: 5826 grad_norm: 2.9991 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7629 loss: 2.7629 2022/10/07 13:20:13 - mmengine - INFO - Epoch(train) [29][420/2119] lr: 4.0000e-02 eta: 1 day, 0:21:20 time: 0.3013 data_time: 0.0246 memory: 5826 grad_norm: 2.9679 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7698 loss: 2.7698 2022/10/07 13:20:20 - mmengine - INFO - Epoch(train) [29][440/2119] lr: 4.0000e-02 eta: 1 day, 0:21:15 time: 0.3564 data_time: 0.0175 memory: 5826 grad_norm: 2.9870 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9492 loss: 2.9492 2022/10/07 13:20:27 - mmengine - INFO - Epoch(train) [29][460/2119] lr: 4.0000e-02 eta: 1 day, 0:21:08 time: 0.3415 data_time: 0.0255 memory: 5826 grad_norm: 2.9922 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.9965 loss: 2.9965 2022/10/07 13:20:35 - mmengine - INFO - Epoch(train) [29][480/2119] lr: 4.0000e-02 eta: 1 day, 0:21:07 time: 0.4032 data_time: 0.0201 memory: 5826 grad_norm: 3.0178 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9281 loss: 2.9281 2022/10/07 13:20:42 - mmengine - INFO - Epoch(train) [29][500/2119] lr: 4.0000e-02 eta: 1 day, 0:20:58 time: 0.3109 data_time: 0.0206 memory: 5826 grad_norm: 2.9744 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6367 loss: 2.6367 2022/10/07 13:20:48 - mmengine - INFO - Epoch(train) [29][520/2119] lr: 4.0000e-02 eta: 1 day, 0:20:51 time: 0.3419 data_time: 0.0247 memory: 5826 grad_norm: 2.9816 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0315 loss: 3.0315 2022/10/07 13:20:55 - mmengine - INFO - Epoch(train) [29][540/2119] lr: 4.0000e-02 eta: 1 day, 0:20:45 time: 0.3469 data_time: 0.0198 memory: 5826 grad_norm: 2.9494 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6956 loss: 2.6956 2022/10/07 13:21:02 - mmengine - INFO - Epoch(train) [29][560/2119] lr: 4.0000e-02 eta: 1 day, 0:20:38 time: 0.3387 data_time: 0.0228 memory: 5826 grad_norm: 2.9439 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7303 loss: 2.7303 2022/10/07 13:21:09 - mmengine - INFO - Epoch(train) [29][580/2119] lr: 4.0000e-02 eta: 1 day, 0:20:32 time: 0.3459 data_time: 0.0291 memory: 5826 grad_norm: 2.9996 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8713 loss: 2.8713 2022/10/07 13:21:17 - mmengine - INFO - Epoch(train) [29][600/2119] lr: 4.0000e-02 eta: 1 day, 0:20:30 time: 0.3982 data_time: 0.0183 memory: 5826 grad_norm: 3.0004 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7479 loss: 2.7479 2022/10/07 13:21:23 - mmengine - INFO - Epoch(train) [29][620/2119] lr: 4.0000e-02 eta: 1 day, 0:20:22 time: 0.3234 data_time: 0.0242 memory: 5826 grad_norm: 2.9856 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7099 loss: 2.7099 2022/10/07 13:21:30 - mmengine - INFO - Epoch(train) [29][640/2119] lr: 4.0000e-02 eta: 1 day, 0:20:14 time: 0.3321 data_time: 0.0202 memory: 5826 grad_norm: 2.9931 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6443 loss: 2.6443 2022/10/07 13:21:37 - mmengine - INFO - Epoch(train) [29][660/2119] lr: 4.0000e-02 eta: 1 day, 0:20:08 time: 0.3425 data_time: 0.0254 memory: 5826 grad_norm: 3.0208 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7404 loss: 2.7404 2022/10/07 13:21:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 13:21:45 - mmengine - INFO - Epoch(train) [29][680/2119] lr: 4.0000e-02 eta: 1 day, 0:20:07 time: 0.4040 data_time: 0.0209 memory: 5826 grad_norm: 3.0102 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7168 loss: 2.7168 2022/10/07 13:21:51 - mmengine - INFO - Epoch(train) [29][700/2119] lr: 4.0000e-02 eta: 1 day, 0:19:55 time: 0.2798 data_time: 0.0229 memory: 5826 grad_norm: 3.0247 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7844 loss: 2.7844 2022/10/07 13:21:57 - mmengine - INFO - Epoch(train) [29][720/2119] lr: 4.0000e-02 eta: 1 day, 0:19:47 time: 0.3254 data_time: 0.0219 memory: 5826 grad_norm: 3.0131 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6677 loss: 2.6677 2022/10/07 13:22:04 - mmengine - INFO - Epoch(train) [29][740/2119] lr: 4.0000e-02 eta: 1 day, 0:19:39 time: 0.3330 data_time: 0.0229 memory: 5826 grad_norm: 2.9493 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.4299 loss: 2.4299 2022/10/07 13:22:10 - mmengine - INFO - Epoch(train) [29][760/2119] lr: 4.0000e-02 eta: 1 day, 0:19:31 time: 0.3235 data_time: 0.0207 memory: 5826 grad_norm: 2.9475 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8282 loss: 2.8282 2022/10/07 13:22:18 - mmengine - INFO - Epoch(train) [29][780/2119] lr: 4.0000e-02 eta: 1 day, 0:19:26 time: 0.3620 data_time: 0.0192 memory: 5826 grad_norm: 2.9557 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6151 loss: 2.6151 2022/10/07 13:22:24 - mmengine - INFO - Epoch(train) [29][800/2119] lr: 4.0000e-02 eta: 1 day, 0:19:19 time: 0.3294 data_time: 0.0215 memory: 5826 grad_norm: 2.9827 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7190 loss: 2.7190 2022/10/07 13:22:31 - mmengine - INFO - Epoch(train) [29][820/2119] lr: 4.0000e-02 eta: 1 day, 0:19:10 time: 0.3236 data_time: 0.0190 memory: 5826 grad_norm: 2.9886 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6252 loss: 2.6252 2022/10/07 13:22:38 - mmengine - INFO - Epoch(train) [29][840/2119] lr: 4.0000e-02 eta: 1 day, 0:19:04 time: 0.3466 data_time: 0.0212 memory: 5826 grad_norm: 3.0018 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7419 loss: 2.7419 2022/10/07 13:22:44 - mmengine - INFO - Epoch(train) [29][860/2119] lr: 4.0000e-02 eta: 1 day, 0:18:56 time: 0.3197 data_time: 0.0269 memory: 5826 grad_norm: 3.0296 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7116 loss: 2.7116 2022/10/07 13:22:52 - mmengine - INFO - Epoch(train) [29][880/2119] lr: 4.0000e-02 eta: 1 day, 0:18:53 time: 0.3916 data_time: 0.0245 memory: 5826 grad_norm: 3.0119 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 2.7366 loss: 2.7366 2022/10/07 13:22:58 - mmengine - INFO - Epoch(train) [29][900/2119] lr: 4.0000e-02 eta: 1 day, 0:18:46 time: 0.3303 data_time: 0.0251 memory: 5826 grad_norm: 2.9831 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6654 loss: 2.6654 2022/10/07 13:23:05 - mmengine - INFO - Epoch(train) [29][920/2119] lr: 4.0000e-02 eta: 1 day, 0:18:38 time: 0.3304 data_time: 0.0206 memory: 5826 grad_norm: 2.9923 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8807 loss: 2.8807 2022/10/07 13:23:12 - mmengine - INFO - Epoch(train) [29][940/2119] lr: 4.0000e-02 eta: 1 day, 0:18:32 time: 0.3506 data_time: 0.0215 memory: 5826 grad_norm: 2.9959 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.9837 loss: 2.9837 2022/10/07 13:23:20 - mmengine - INFO - Epoch(train) [29][960/2119] lr: 4.0000e-02 eta: 1 day, 0:18:31 time: 0.4098 data_time: 0.0184 memory: 5826 grad_norm: 3.0101 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8894 loss: 2.8894 2022/10/07 13:23:27 - mmengine - INFO - Epoch(train) [29][980/2119] lr: 4.0000e-02 eta: 1 day, 0:18:23 time: 0.3161 data_time: 0.0268 memory: 5826 grad_norm: 2.9544 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.6509 loss: 2.6509 2022/10/07 13:23:34 - mmengine - INFO - Epoch(train) [29][1000/2119] lr: 4.0000e-02 eta: 1 day, 0:18:20 time: 0.3871 data_time: 0.0209 memory: 5826 grad_norm: 2.9412 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5916 loss: 2.5916 2022/10/07 13:23:40 - mmengine - INFO - Epoch(train) [29][1020/2119] lr: 4.0000e-02 eta: 1 day, 0:18:10 time: 0.3088 data_time: 0.0243 memory: 5826 grad_norm: 2.9949 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8155 loss: 2.8155 2022/10/07 13:23:47 - mmengine - INFO - Epoch(train) [29][1040/2119] lr: 4.0000e-02 eta: 1 day, 0:18:04 time: 0.3394 data_time: 0.0207 memory: 5826 grad_norm: 2.9709 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6442 loss: 2.6442 2022/10/07 13:23:54 - mmengine - INFO - Epoch(train) [29][1060/2119] lr: 4.0000e-02 eta: 1 day, 0:17:58 time: 0.3581 data_time: 0.0239 memory: 5826 grad_norm: 2.9855 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8080 loss: 2.8080 2022/10/07 13:24:02 - mmengine - INFO - Epoch(train) [29][1080/2119] lr: 4.0000e-02 eta: 1 day, 0:17:56 time: 0.3980 data_time: 0.0202 memory: 5826 grad_norm: 2.9832 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1345 loss: 3.1345 2022/10/07 13:24:09 - mmengine - INFO - Epoch(train) [29][1100/2119] lr: 4.0000e-02 eta: 1 day, 0:17:50 time: 0.3478 data_time: 0.0194 memory: 5826 grad_norm: 2.9482 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8368 loss: 2.8368 2022/10/07 13:24:16 - mmengine - INFO - Epoch(train) [29][1120/2119] lr: 4.0000e-02 eta: 1 day, 0:17:42 time: 0.3225 data_time: 0.0238 memory: 5826 grad_norm: 2.9427 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.5424 loss: 2.5424 2022/10/07 13:24:23 - mmengine - INFO - Epoch(train) [29][1140/2119] lr: 4.0000e-02 eta: 1 day, 0:17:38 time: 0.3762 data_time: 0.0241 memory: 5826 grad_norm: 2.9796 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6995 loss: 2.6995 2022/10/07 13:24:30 - mmengine - INFO - Epoch(train) [29][1160/2119] lr: 4.0000e-02 eta: 1 day, 0:17:32 time: 0.3505 data_time: 0.0186 memory: 5826 grad_norm: 3.0331 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.9533 loss: 2.9533 2022/10/07 13:24:37 - mmengine - INFO - Epoch(train) [29][1180/2119] lr: 4.0000e-02 eta: 1 day, 0:17:25 time: 0.3372 data_time: 0.0348 memory: 5826 grad_norm: 2.9965 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7739 loss: 2.7739 2022/10/07 13:24:43 - mmengine - INFO - Epoch(train) [29][1200/2119] lr: 4.0000e-02 eta: 1 day, 0:17:17 time: 0.3213 data_time: 0.0166 memory: 5826 grad_norm: 2.9546 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9965 loss: 2.9965 2022/10/07 13:24:50 - mmengine - INFO - Epoch(train) [29][1220/2119] lr: 4.0000e-02 eta: 1 day, 0:17:07 time: 0.3018 data_time: 0.0239 memory: 5826 grad_norm: 2.9038 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8544 loss: 2.8544 2022/10/07 13:24:56 - mmengine - INFO - Epoch(train) [29][1240/2119] lr: 4.0000e-02 eta: 1 day, 0:17:00 time: 0.3418 data_time: 0.0192 memory: 5826 grad_norm: 2.9913 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9756 loss: 2.9756 2022/10/07 13:25:03 - mmengine - INFO - Epoch(train) [29][1260/2119] lr: 4.0000e-02 eta: 1 day, 0:16:52 time: 0.3239 data_time: 0.0232 memory: 5826 grad_norm: 2.9686 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.5983 loss: 2.5983 2022/10/07 13:25:10 - mmengine - INFO - Epoch(train) [29][1280/2119] lr: 4.0000e-02 eta: 1 day, 0:16:48 time: 0.3634 data_time: 0.0220 memory: 5826 grad_norm: 2.9434 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7522 loss: 2.7522 2022/10/07 13:25:18 - mmengine - INFO - Epoch(train) [29][1300/2119] lr: 4.0000e-02 eta: 1 day, 0:16:43 time: 0.3721 data_time: 0.0203 memory: 5826 grad_norm: 3.0251 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.0264 loss: 3.0264 2022/10/07 13:25:25 - mmengine - INFO - Epoch(train) [29][1320/2119] lr: 4.0000e-02 eta: 1 day, 0:16:37 time: 0.3477 data_time: 0.0244 memory: 5826 grad_norm: 2.9226 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6224 loss: 2.6224 2022/10/07 13:25:31 - mmengine - INFO - Epoch(train) [29][1340/2119] lr: 4.0000e-02 eta: 1 day, 0:16:29 time: 0.3204 data_time: 0.0190 memory: 5826 grad_norm: 2.9599 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6704 loss: 2.6704 2022/10/07 13:25:38 - mmengine - INFO - Epoch(train) [29][1360/2119] lr: 4.0000e-02 eta: 1 day, 0:16:24 time: 0.3567 data_time: 0.0226 memory: 5826 grad_norm: 2.9823 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8947 loss: 2.8947 2022/10/07 13:25:45 - mmengine - INFO - Epoch(train) [29][1380/2119] lr: 4.0000e-02 eta: 1 day, 0:16:16 time: 0.3339 data_time: 0.0280 memory: 5826 grad_norm: 3.0046 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.6885 loss: 2.6885 2022/10/07 13:25:52 - mmengine - INFO - Epoch(train) [29][1400/2119] lr: 4.0000e-02 eta: 1 day, 0:16:11 time: 0.3535 data_time: 0.0253 memory: 5826 grad_norm: 2.9734 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6315 loss: 2.6315 2022/10/07 13:25:59 - mmengine - INFO - Epoch(train) [29][1420/2119] lr: 4.0000e-02 eta: 1 day, 0:16:06 time: 0.3620 data_time: 0.0230 memory: 5826 grad_norm: 2.9976 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7176 loss: 2.7176 2022/10/07 13:26:06 - mmengine - INFO - Epoch(train) [29][1440/2119] lr: 4.0000e-02 eta: 1 day, 0:15:58 time: 0.3265 data_time: 0.0210 memory: 5826 grad_norm: 2.9822 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.8628 loss: 2.8628 2022/10/07 13:26:13 - mmengine - INFO - Epoch(train) [29][1460/2119] lr: 4.0000e-02 eta: 1 day, 0:15:53 time: 0.3590 data_time: 0.0200 memory: 5826 grad_norm: 2.9208 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8598 loss: 2.8598 2022/10/07 13:26:20 - mmengine - INFO - Epoch(train) [29][1480/2119] lr: 4.0000e-02 eta: 1 day, 0:15:46 time: 0.3406 data_time: 0.0287 memory: 5826 grad_norm: 3.0020 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7211 loss: 2.7211 2022/10/07 13:26:26 - mmengine - INFO - Epoch(train) [29][1500/2119] lr: 4.0000e-02 eta: 1 day, 0:15:37 time: 0.3201 data_time: 0.0237 memory: 5826 grad_norm: 2.9216 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6239 loss: 2.6239 2022/10/07 13:26:35 - mmengine - INFO - Epoch(train) [29][1520/2119] lr: 4.0000e-02 eta: 1 day, 0:15:38 time: 0.4283 data_time: 0.0199 memory: 5826 grad_norm: 2.9397 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8784 loss: 2.8784 2022/10/07 13:26:40 - mmengine - INFO - Epoch(train) [29][1540/2119] lr: 4.0000e-02 eta: 1 day, 0:15:27 time: 0.2936 data_time: 0.0183 memory: 5826 grad_norm: 2.9627 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7413 loss: 2.7413 2022/10/07 13:26:48 - mmengine - INFO - Epoch(train) [29][1560/2119] lr: 4.0000e-02 eta: 1 day, 0:15:23 time: 0.3644 data_time: 0.0239 memory: 5826 grad_norm: 2.9640 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6086 loss: 2.6086 2022/10/07 13:26:54 - mmengine - INFO - Epoch(train) [29][1580/2119] lr: 4.0000e-02 eta: 1 day, 0:15:15 time: 0.3324 data_time: 0.0206 memory: 5826 grad_norm: 2.9052 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.9856 loss: 2.9856 2022/10/07 13:27:02 - mmengine - INFO - Epoch(train) [29][1600/2119] lr: 4.0000e-02 eta: 1 day, 0:15:11 time: 0.3652 data_time: 0.0260 memory: 5826 grad_norm: 2.9357 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9143 loss: 2.9143 2022/10/07 13:27:08 - mmengine - INFO - Epoch(train) [29][1620/2119] lr: 4.0000e-02 eta: 1 day, 0:15:00 time: 0.2951 data_time: 0.0234 memory: 5826 grad_norm: 2.9700 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6490 loss: 2.6490 2022/10/07 13:27:16 - mmengine - INFO - Epoch(train) [29][1640/2119] lr: 4.0000e-02 eta: 1 day, 0:14:58 time: 0.3998 data_time: 0.0188 memory: 5826 grad_norm: 2.9246 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7583 loss: 2.7583 2022/10/07 13:27:22 - mmengine - INFO - Epoch(train) [29][1660/2119] lr: 4.0000e-02 eta: 1 day, 0:14:48 time: 0.3042 data_time: 0.0198 memory: 5826 grad_norm: 2.9016 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8736 loss: 2.8736 2022/10/07 13:27:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 13:27:29 - mmengine - INFO - Epoch(train) [29][1680/2119] lr: 4.0000e-02 eta: 1 day, 0:14:43 time: 0.3526 data_time: 0.0234 memory: 5826 grad_norm: 2.8615 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6994 loss: 2.6994 2022/10/07 13:27:35 - mmengine - INFO - Epoch(train) [29][1700/2119] lr: 4.0000e-02 eta: 1 day, 0:14:34 time: 0.3208 data_time: 0.0231 memory: 5826 grad_norm: 2.9769 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8191 loss: 2.8191 2022/10/07 13:27:41 - mmengine - INFO - Epoch(train) [29][1720/2119] lr: 4.0000e-02 eta: 1 day, 0:14:26 time: 0.3162 data_time: 0.0155 memory: 5826 grad_norm: 2.9980 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6979 loss: 2.6979 2022/10/07 13:27:48 - mmengine - INFO - Epoch(train) [29][1740/2119] lr: 4.0000e-02 eta: 1 day, 0:14:19 time: 0.3371 data_time: 0.0236 memory: 5826 grad_norm: 2.9878 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8431 loss: 2.8431 2022/10/07 13:27:56 - mmengine - INFO - Epoch(train) [29][1760/2119] lr: 4.0000e-02 eta: 1 day, 0:14:15 time: 0.3810 data_time: 0.0194 memory: 5826 grad_norm: 3.0045 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7668 loss: 2.7668 2022/10/07 13:28:03 - mmengine - INFO - Epoch(train) [29][1780/2119] lr: 4.0000e-02 eta: 1 day, 0:14:08 time: 0.3348 data_time: 0.0281 memory: 5826 grad_norm: 2.9024 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7013 loss: 2.7013 2022/10/07 13:28:10 - mmengine - INFO - Epoch(train) [29][1800/2119] lr: 4.0000e-02 eta: 1 day, 0:14:05 time: 0.3869 data_time: 0.0176 memory: 5826 grad_norm: 2.9358 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7153 loss: 2.7153 2022/10/07 13:28:17 - mmengine - INFO - Epoch(train) [29][1820/2119] lr: 4.0000e-02 eta: 1 day, 0:13:57 time: 0.3201 data_time: 0.0307 memory: 5826 grad_norm: 2.9503 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6839 loss: 2.6839 2022/10/07 13:28:24 - mmengine - INFO - Epoch(train) [29][1840/2119] lr: 4.0000e-02 eta: 1 day, 0:13:54 time: 0.3843 data_time: 0.0214 memory: 5826 grad_norm: 2.9484 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8689 loss: 2.8689 2022/10/07 13:28:31 - mmengine - INFO - Epoch(train) [29][1860/2119] lr: 4.0000e-02 eta: 1 day, 0:13:46 time: 0.3263 data_time: 0.0240 memory: 5826 grad_norm: 2.9952 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7707 loss: 2.7707 2022/10/07 13:28:38 - mmengine - INFO - Epoch(train) [29][1880/2119] lr: 4.0000e-02 eta: 1 day, 0:13:40 time: 0.3561 data_time: 0.0177 memory: 5826 grad_norm: 2.9689 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5874 loss: 2.5874 2022/10/07 13:28:44 - mmengine - INFO - Epoch(train) [29][1900/2119] lr: 4.0000e-02 eta: 1 day, 0:13:31 time: 0.3161 data_time: 0.0203 memory: 5826 grad_norm: 2.9663 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8605 loss: 2.8605 2022/10/07 13:28:51 - mmengine - INFO - Epoch(train) [29][1920/2119] lr: 4.0000e-02 eta: 1 day, 0:13:24 time: 0.3381 data_time: 0.0222 memory: 5826 grad_norm: 2.9311 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.8542 loss: 2.8542 2022/10/07 13:28:58 - mmengine - INFO - Epoch(train) [29][1940/2119] lr: 4.0000e-02 eta: 1 day, 0:13:19 time: 0.3611 data_time: 0.0212 memory: 5826 grad_norm: 2.9416 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7144 loss: 2.7144 2022/10/07 13:29:05 - mmengine - INFO - Epoch(train) [29][1960/2119] lr: 4.0000e-02 eta: 1 day, 0:13:14 time: 0.3559 data_time: 0.0187 memory: 5826 grad_norm: 2.9433 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8528 loss: 2.8528 2022/10/07 13:29:11 - mmengine - INFO - Epoch(train) [29][1980/2119] lr: 4.0000e-02 eta: 1 day, 0:13:04 time: 0.2960 data_time: 0.0217 memory: 5826 grad_norm: 2.9667 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5769 loss: 2.5769 2022/10/07 13:29:19 - mmengine - INFO - Epoch(train) [29][2000/2119] lr: 4.0000e-02 eta: 1 day, 0:12:59 time: 0.3645 data_time: 0.0194 memory: 5826 grad_norm: 2.9769 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8196 loss: 2.8196 2022/10/07 13:29:25 - mmengine - INFO - Epoch(train) [29][2020/2119] lr: 4.0000e-02 eta: 1 day, 0:12:50 time: 0.3136 data_time: 0.0215 memory: 5826 grad_norm: 2.9272 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8228 loss: 2.8228 2022/10/07 13:29:32 - mmengine - INFO - Epoch(train) [29][2040/2119] lr: 4.0000e-02 eta: 1 day, 0:12:45 time: 0.3671 data_time: 0.0248 memory: 5826 grad_norm: 2.9835 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7889 loss: 2.7889 2022/10/07 13:29:39 - mmengine - INFO - Epoch(train) [29][2060/2119] lr: 4.0000e-02 eta: 1 day, 0:12:37 time: 0.3256 data_time: 0.0170 memory: 5826 grad_norm: 2.9492 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7277 loss: 2.7277 2022/10/07 13:29:46 - mmengine - INFO - Epoch(train) [29][2080/2119] lr: 4.0000e-02 eta: 1 day, 0:12:30 time: 0.3386 data_time: 0.0205 memory: 5826 grad_norm: 2.9736 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8704 loss: 2.8704 2022/10/07 13:29:52 - mmengine - INFO - Epoch(train) [29][2100/2119] lr: 4.0000e-02 eta: 1 day, 0:12:22 time: 0.3210 data_time: 0.0251 memory: 5826 grad_norm: 2.9721 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7329 loss: 2.7329 2022/10/07 13:29:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 13:29:58 - mmengine - INFO - Epoch(train) [29][2119/2119] lr: 4.0000e-02 eta: 1 day, 0:12:22 time: 0.3058 data_time: 0.0165 memory: 5826 grad_norm: 3.0176 top1_acc: 0.4000 top5_acc: 0.8000 loss_cls: 2.9222 loss: 2.9222 2022/10/07 13:30:08 - mmengine - INFO - Epoch(train) [30][20/2119] lr: 4.0000e-02 eta: 1 day, 0:11:55 time: 0.5004 data_time: 0.1260 memory: 5826 grad_norm: 2.9644 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7665 loss: 2.7665 2022/10/07 13:30:14 - mmengine - INFO - Epoch(train) [30][40/2119] lr: 4.0000e-02 eta: 1 day, 0:11:47 time: 0.3189 data_time: 0.0169 memory: 5826 grad_norm: 2.9459 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.8075 loss: 2.8075 2022/10/07 13:30:22 - mmengine - INFO - Epoch(train) [30][60/2119] lr: 4.0000e-02 eta: 1 day, 0:11:44 time: 0.3941 data_time: 0.0195 memory: 5826 grad_norm: 2.9568 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7803 loss: 2.7803 2022/10/07 13:30:29 - mmengine - INFO - Epoch(train) [30][80/2119] lr: 4.0000e-02 eta: 1 day, 0:11:36 time: 0.3205 data_time: 0.0221 memory: 5826 grad_norm: 2.9662 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9762 loss: 2.9762 2022/10/07 13:30:36 - mmengine - INFO - Epoch(train) [30][100/2119] lr: 4.0000e-02 eta: 1 day, 0:11:32 time: 0.3732 data_time: 0.0214 memory: 5826 grad_norm: 2.9857 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7652 loss: 2.7652 2022/10/07 13:30:42 - mmengine - INFO - Epoch(train) [30][120/2119] lr: 4.0000e-02 eta: 1 day, 0:11:21 time: 0.2855 data_time: 0.0189 memory: 5826 grad_norm: 3.0026 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7541 loss: 2.7541 2022/10/07 13:30:48 - mmengine - INFO - Epoch(train) [30][140/2119] lr: 4.0000e-02 eta: 1 day, 0:11:13 time: 0.3295 data_time: 0.0265 memory: 5826 grad_norm: 2.9251 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8702 loss: 2.8702 2022/10/07 13:30:55 - mmengine - INFO - Epoch(train) [30][160/2119] lr: 4.0000e-02 eta: 1 day, 0:11:06 time: 0.3425 data_time: 0.0250 memory: 5826 grad_norm: 2.9760 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7190 loss: 2.7190 2022/10/07 13:31:03 - mmengine - INFO - Epoch(train) [30][180/2119] lr: 4.0000e-02 eta: 1 day, 0:11:02 time: 0.3648 data_time: 0.0223 memory: 5826 grad_norm: 2.9292 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5270 loss: 2.5270 2022/10/07 13:31:08 - mmengine - INFO - Epoch(train) [30][200/2119] lr: 4.0000e-02 eta: 1 day, 0:10:51 time: 0.2962 data_time: 0.0239 memory: 5826 grad_norm: 2.9938 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7378 loss: 2.7378 2022/10/07 13:31:16 - mmengine - INFO - Epoch(train) [30][220/2119] lr: 4.0000e-02 eta: 1 day, 0:10:47 time: 0.3643 data_time: 0.0185 memory: 5826 grad_norm: 3.0477 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8718 loss: 2.8718 2022/10/07 13:31:22 - mmengine - INFO - Epoch(train) [30][240/2119] lr: 4.0000e-02 eta: 1 day, 0:10:37 time: 0.3039 data_time: 0.0245 memory: 5826 grad_norm: 2.9733 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8268 loss: 2.8268 2022/10/07 13:31:29 - mmengine - INFO - Epoch(train) [30][260/2119] lr: 4.0000e-02 eta: 1 day, 0:10:30 time: 0.3386 data_time: 0.0222 memory: 5826 grad_norm: 3.0039 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7856 loss: 2.7856 2022/10/07 13:31:36 - mmengine - INFO - Epoch(train) [30][280/2119] lr: 4.0000e-02 eta: 1 day, 0:10:27 time: 0.3906 data_time: 0.0167 memory: 5826 grad_norm: 2.9608 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5857 loss: 2.5857 2022/10/07 13:31:43 - mmengine - INFO - Epoch(train) [30][300/2119] lr: 4.0000e-02 eta: 1 day, 0:10:19 time: 0.3205 data_time: 0.0213 memory: 5826 grad_norm: 3.0264 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8941 loss: 2.8941 2022/10/07 13:31:49 - mmengine - INFO - Epoch(train) [30][320/2119] lr: 4.0000e-02 eta: 1 day, 0:10:11 time: 0.3262 data_time: 0.0302 memory: 5826 grad_norm: 2.9418 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7189 loss: 2.7189 2022/10/07 13:31:57 - mmengine - INFO - Epoch(train) [30][340/2119] lr: 4.0000e-02 eta: 1 day, 0:10:06 time: 0.3660 data_time: 0.0182 memory: 5826 grad_norm: 2.9817 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5991 loss: 2.5991 2022/10/07 13:32:05 - mmengine - INFO - Epoch(train) [30][360/2119] lr: 4.0000e-02 eta: 1 day, 0:10:04 time: 0.3918 data_time: 0.0238 memory: 5826 grad_norm: 2.9550 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6777 loss: 2.6777 2022/10/07 13:32:11 - mmengine - INFO - Epoch(train) [30][380/2119] lr: 4.0000e-02 eta: 1 day, 0:09:56 time: 0.3210 data_time: 0.0188 memory: 5826 grad_norm: 2.9076 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7797 loss: 2.7797 2022/10/07 13:32:19 - mmengine - INFO - Epoch(train) [30][400/2119] lr: 4.0000e-02 eta: 1 day, 0:09:53 time: 0.3930 data_time: 0.0161 memory: 5826 grad_norm: 3.0164 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9083 loss: 2.9083 2022/10/07 13:32:25 - mmengine - INFO - Epoch(train) [30][420/2119] lr: 4.0000e-02 eta: 1 day, 0:09:45 time: 0.3255 data_time: 0.0269 memory: 5826 grad_norm: 3.0351 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7475 loss: 2.7475 2022/10/07 13:32:32 - mmengine - INFO - Epoch(train) [30][440/2119] lr: 4.0000e-02 eta: 1 day, 0:09:39 time: 0.3435 data_time: 0.0198 memory: 5826 grad_norm: 2.9422 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9091 loss: 2.9091 2022/10/07 13:32:39 - mmengine - INFO - Epoch(train) [30][460/2119] lr: 4.0000e-02 eta: 1 day, 0:09:33 time: 0.3526 data_time: 0.0188 memory: 5826 grad_norm: 2.9750 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4380 loss: 2.4380 2022/10/07 13:32:46 - mmengine - INFO - Epoch(train) [30][480/2119] lr: 4.0000e-02 eta: 1 day, 0:09:26 time: 0.3397 data_time: 0.0252 memory: 5826 grad_norm: 2.9753 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9117 loss: 2.9117 2022/10/07 13:32:52 - mmengine - INFO - Epoch(train) [30][500/2119] lr: 4.0000e-02 eta: 1 day, 0:09:16 time: 0.2946 data_time: 0.0239 memory: 5826 grad_norm: 3.0058 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8143 loss: 2.8143 2022/10/07 13:33:00 - mmengine - INFO - Epoch(train) [30][520/2119] lr: 4.0000e-02 eta: 1 day, 0:09:13 time: 0.3901 data_time: 0.0162 memory: 5826 grad_norm: 2.9636 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9689 loss: 2.9689 2022/10/07 13:33:07 - mmengine - INFO - Epoch(train) [30][540/2119] lr: 4.0000e-02 eta: 1 day, 0:09:06 time: 0.3429 data_time: 0.0213 memory: 5826 grad_norm: 3.0157 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8407 loss: 2.8407 2022/10/07 13:33:10 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 13:33:13 - mmengine - INFO - Epoch(train) [30][560/2119] lr: 4.0000e-02 eta: 1 day, 0:08:59 time: 0.3333 data_time: 0.0248 memory: 5826 grad_norm: 2.9920 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8741 loss: 2.8741 2022/10/07 13:33:20 - mmengine - INFO - Epoch(train) [30][580/2119] lr: 4.0000e-02 eta: 1 day, 0:08:54 time: 0.3586 data_time: 0.0265 memory: 5826 grad_norm: 2.9655 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7385 loss: 2.7385 2022/10/07 13:33:28 - mmengine - INFO - Epoch(train) [30][600/2119] lr: 4.0000e-02 eta: 1 day, 0:08:50 time: 0.3804 data_time: 0.0189 memory: 5826 grad_norm: 3.0600 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5646 loss: 2.5646 2022/10/07 13:33:34 - mmengine - INFO - Epoch(train) [30][620/2119] lr: 4.0000e-02 eta: 1 day, 0:08:41 time: 0.3048 data_time: 0.0196 memory: 5826 grad_norm: 2.9912 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8252 loss: 2.8252 2022/10/07 13:33:41 - mmengine - INFO - Epoch(train) [30][640/2119] lr: 4.0000e-02 eta: 1 day, 0:08:35 time: 0.3487 data_time: 0.0154 memory: 5826 grad_norm: 3.0010 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7330 loss: 2.7330 2022/10/07 13:33:48 - mmengine - INFO - Epoch(train) [30][660/2119] lr: 4.0000e-02 eta: 1 day, 0:08:28 time: 0.3425 data_time: 0.0209 memory: 5826 grad_norm: 2.8837 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8371 loss: 2.8371 2022/10/07 13:33:55 - mmengine - INFO - Epoch(train) [30][680/2119] lr: 4.0000e-02 eta: 1 day, 0:08:22 time: 0.3476 data_time: 0.0233 memory: 5826 grad_norm: 2.9769 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6372 loss: 2.6372 2022/10/07 13:34:02 - mmengine - INFO - Epoch(train) [30][700/2119] lr: 4.0000e-02 eta: 1 day, 0:08:18 time: 0.3724 data_time: 0.0195 memory: 5826 grad_norm: 3.0914 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0210 loss: 3.0210 2022/10/07 13:34:09 - mmengine - INFO - Epoch(train) [30][720/2119] lr: 4.0000e-02 eta: 1 day, 0:08:12 time: 0.3548 data_time: 0.0205 memory: 5826 grad_norm: 2.9018 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8141 loss: 2.8141 2022/10/07 13:34:16 - mmengine - INFO - Epoch(train) [30][740/2119] lr: 4.0000e-02 eta: 1 day, 0:08:05 time: 0.3314 data_time: 0.0286 memory: 5826 grad_norm: 2.9959 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5153 loss: 2.5153 2022/10/07 13:34:22 - mmengine - INFO - Epoch(train) [30][760/2119] lr: 4.0000e-02 eta: 1 day, 0:07:56 time: 0.3140 data_time: 0.0181 memory: 5826 grad_norm: 3.0177 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7785 loss: 2.7785 2022/10/07 13:34:29 - mmengine - INFO - Epoch(train) [30][780/2119] lr: 4.0000e-02 eta: 1 day, 0:07:48 time: 0.3315 data_time: 0.0232 memory: 5826 grad_norm: 2.9936 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6109 loss: 2.6109 2022/10/07 13:34:37 - mmengine - INFO - Epoch(train) [30][800/2119] lr: 4.0000e-02 eta: 1 day, 0:07:46 time: 0.3937 data_time: 0.0353 memory: 5826 grad_norm: 2.9749 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9395 loss: 2.9395 2022/10/07 13:34:43 - mmengine - INFO - Epoch(train) [30][820/2119] lr: 4.0000e-02 eta: 1 day, 0:07:38 time: 0.3291 data_time: 0.0211 memory: 5826 grad_norm: 3.0291 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7728 loss: 2.7728 2022/10/07 13:34:51 - mmengine - INFO - Epoch(train) [30][840/2119] lr: 4.0000e-02 eta: 1 day, 0:07:33 time: 0.3619 data_time: 0.0215 memory: 5826 grad_norm: 2.9990 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9313 loss: 2.9313 2022/10/07 13:34:56 - mmengine - INFO - Epoch(train) [30][860/2119] lr: 4.0000e-02 eta: 1 day, 0:07:21 time: 0.2756 data_time: 0.0218 memory: 5826 grad_norm: 3.0287 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6263 loss: 2.6263 2022/10/07 13:35:04 - mmengine - INFO - Epoch(train) [30][880/2119] lr: 4.0000e-02 eta: 1 day, 0:07:20 time: 0.4039 data_time: 0.0172 memory: 5826 grad_norm: 3.0165 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7688 loss: 2.7688 2022/10/07 13:35:10 - mmengine - INFO - Epoch(train) [30][900/2119] lr: 4.0000e-02 eta: 1 day, 0:07:10 time: 0.2996 data_time: 0.0237 memory: 5826 grad_norm: 3.0323 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8865 loss: 2.8865 2022/10/07 13:35:18 - mmengine - INFO - Epoch(train) [30][920/2119] lr: 4.0000e-02 eta: 1 day, 0:07:05 time: 0.3644 data_time: 0.0173 memory: 5826 grad_norm: 2.9632 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6914 loss: 2.6914 2022/10/07 13:35:24 - mmengine - INFO - Epoch(train) [30][940/2119] lr: 4.0000e-02 eta: 1 day, 0:06:58 time: 0.3390 data_time: 0.0263 memory: 5826 grad_norm: 2.9711 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6208 loss: 2.6208 2022/10/07 13:35:31 - mmengine - INFO - Epoch(train) [30][960/2119] lr: 4.0000e-02 eta: 1 day, 0:06:52 time: 0.3513 data_time: 0.0160 memory: 5826 grad_norm: 2.9616 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9163 loss: 2.9163 2022/10/07 13:35:38 - mmengine - INFO - Epoch(train) [30][980/2119] lr: 4.0000e-02 eta: 1 day, 0:06:44 time: 0.3205 data_time: 0.0222 memory: 5826 grad_norm: 2.9826 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.5184 loss: 2.5184 2022/10/07 13:35:46 - mmengine - INFO - Epoch(train) [30][1000/2119] lr: 4.0000e-02 eta: 1 day, 0:06:41 time: 0.3859 data_time: 0.0246 memory: 5826 grad_norm: 2.9809 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6925 loss: 2.6925 2022/10/07 13:35:52 - mmengine - INFO - Epoch(train) [30][1020/2119] lr: 4.0000e-02 eta: 1 day, 0:06:33 time: 0.3346 data_time: 0.0213 memory: 5826 grad_norm: 2.9583 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5686 loss: 2.5686 2022/10/07 13:35:59 - mmengine - INFO - Epoch(train) [30][1040/2119] lr: 4.0000e-02 eta: 1 day, 0:06:28 time: 0.3562 data_time: 0.0224 memory: 5826 grad_norm: 2.9359 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5852 loss: 2.5852 2022/10/07 13:36:06 - mmengine - INFO - Epoch(train) [30][1060/2119] lr: 4.0000e-02 eta: 1 day, 0:06:22 time: 0.3461 data_time: 0.0188 memory: 5826 grad_norm: 2.9647 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8046 loss: 2.8046 2022/10/07 13:36:14 - mmengine - INFO - Epoch(train) [30][1080/2119] lr: 4.0000e-02 eta: 1 day, 0:06:17 time: 0.3662 data_time: 0.0216 memory: 5826 grad_norm: 3.0182 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6660 loss: 2.6660 2022/10/07 13:36:20 - mmengine - INFO - Epoch(train) [30][1100/2119] lr: 4.0000e-02 eta: 1 day, 0:06:07 time: 0.3026 data_time: 0.0218 memory: 5826 grad_norm: 2.9501 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8945 loss: 2.8945 2022/10/07 13:36:27 - mmengine - INFO - Epoch(train) [30][1120/2119] lr: 4.0000e-02 eta: 1 day, 0:06:02 time: 0.3641 data_time: 0.0196 memory: 5826 grad_norm: 2.9854 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8449 loss: 2.8449 2022/10/07 13:36:33 - mmengine - INFO - Epoch(train) [30][1140/2119] lr: 4.0000e-02 eta: 1 day, 0:05:52 time: 0.3008 data_time: 0.0233 memory: 5826 grad_norm: 3.0251 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7711 loss: 2.7711 2022/10/07 13:36:40 - mmengine - INFO - Epoch(train) [30][1160/2119] lr: 4.0000e-02 eta: 1 day, 0:05:46 time: 0.3421 data_time: 0.0206 memory: 5826 grad_norm: 3.0384 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8397 loss: 2.8397 2022/10/07 13:36:47 - mmengine - INFO - Epoch(train) [30][1180/2119] lr: 4.0000e-02 eta: 1 day, 0:05:42 time: 0.3744 data_time: 0.0229 memory: 5826 grad_norm: 2.9977 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8887 loss: 2.8887 2022/10/07 13:36:54 - mmengine - INFO - Epoch(train) [30][1200/2119] lr: 4.0000e-02 eta: 1 day, 0:05:35 time: 0.3422 data_time: 0.0262 memory: 5826 grad_norm: 3.0286 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9025 loss: 2.9025 2022/10/07 13:37:00 - mmengine - INFO - Epoch(train) [30][1220/2119] lr: 4.0000e-02 eta: 1 day, 0:05:25 time: 0.3036 data_time: 0.0200 memory: 5826 grad_norm: 2.9319 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7287 loss: 2.7287 2022/10/07 13:37:07 - mmengine - INFO - Epoch(train) [30][1240/2119] lr: 4.0000e-02 eta: 1 day, 0:05:17 time: 0.3253 data_time: 0.0185 memory: 5826 grad_norm: 3.0131 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6378 loss: 2.6378 2022/10/07 13:37:14 - mmengine - INFO - Epoch(train) [30][1260/2119] lr: 4.0000e-02 eta: 1 day, 0:05:14 time: 0.3814 data_time: 0.0318 memory: 5826 grad_norm: 3.0275 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8230 loss: 2.8230 2022/10/07 13:37:21 - mmengine - INFO - Epoch(train) [30][1280/2119] lr: 4.0000e-02 eta: 1 day, 0:05:05 time: 0.3110 data_time: 0.0248 memory: 5826 grad_norm: 3.0294 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6266 loss: 2.6266 2022/10/07 13:37:28 - mmengine - INFO - Epoch(train) [30][1300/2119] lr: 4.0000e-02 eta: 1 day, 0:05:03 time: 0.3956 data_time: 0.0270 memory: 5826 grad_norm: 3.0024 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9318 loss: 2.9318 2022/10/07 13:37:35 - mmengine - INFO - Epoch(train) [30][1320/2119] lr: 4.0000e-02 eta: 1 day, 0:04:54 time: 0.3170 data_time: 0.0192 memory: 5826 grad_norm: 3.0241 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9881 loss: 2.9881 2022/10/07 13:37:41 - mmengine - INFO - Epoch(train) [30][1340/2119] lr: 4.0000e-02 eta: 1 day, 0:04:46 time: 0.3210 data_time: 0.0212 memory: 5826 grad_norm: 2.9966 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0250 loss: 3.0250 2022/10/07 13:37:48 - mmengine - INFO - Epoch(train) [30][1360/2119] lr: 4.0000e-02 eta: 1 day, 0:04:37 time: 0.3164 data_time: 0.0240 memory: 5826 grad_norm: 2.9747 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9777 loss: 2.9777 2022/10/07 13:37:55 - mmengine - INFO - Epoch(train) [30][1380/2119] lr: 4.0000e-02 eta: 1 day, 0:04:34 time: 0.3882 data_time: 0.0265 memory: 5826 grad_norm: 3.0503 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.6501 loss: 2.6501 2022/10/07 13:38:01 - mmengine - INFO - Epoch(train) [30][1400/2119] lr: 4.0000e-02 eta: 1 day, 0:04:24 time: 0.2988 data_time: 0.0249 memory: 5826 grad_norm: 2.9415 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 2.5885 loss: 2.5885 2022/10/07 13:38:09 - mmengine - INFO - Epoch(train) [30][1420/2119] lr: 4.0000e-02 eta: 1 day, 0:04:20 time: 0.3730 data_time: 0.0225 memory: 5826 grad_norm: 2.9548 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6510 loss: 2.6510 2022/10/07 13:38:16 - mmengine - INFO - Epoch(train) [30][1440/2119] lr: 4.0000e-02 eta: 1 day, 0:04:13 time: 0.3393 data_time: 0.0218 memory: 5826 grad_norm: 2.9754 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6944 loss: 2.6944 2022/10/07 13:38:22 - mmengine - INFO - Epoch(train) [30][1460/2119] lr: 4.0000e-02 eta: 1 day, 0:04:06 time: 0.3339 data_time: 0.0237 memory: 5826 grad_norm: 2.9692 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.7456 loss: 2.7456 2022/10/07 13:38:29 - mmengine - INFO - Epoch(train) [30][1480/2119] lr: 4.0000e-02 eta: 1 day, 0:03:58 time: 0.3334 data_time: 0.0247 memory: 5826 grad_norm: 2.9582 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9556 loss: 2.9556 2022/10/07 13:38:36 - mmengine - INFO - Epoch(train) [30][1500/2119] lr: 4.0000e-02 eta: 1 day, 0:03:52 time: 0.3498 data_time: 0.0209 memory: 5826 grad_norm: 2.9973 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9531 loss: 2.9531 2022/10/07 13:38:43 - mmengine - INFO - Epoch(train) [30][1520/2119] lr: 4.0000e-02 eta: 1 day, 0:03:46 time: 0.3444 data_time: 0.0197 memory: 5826 grad_norm: 2.9621 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6542 loss: 2.6542 2022/10/07 13:38:50 - mmengine - INFO - Epoch(train) [30][1540/2119] lr: 4.0000e-02 eta: 1 day, 0:03:40 time: 0.3529 data_time: 0.0207 memory: 5826 grad_norm: 2.9765 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8523 loss: 2.8523 2022/10/07 13:38:53 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 13:38:56 - mmengine - INFO - Epoch(train) [30][1560/2119] lr: 4.0000e-02 eta: 1 day, 0:03:32 time: 0.3250 data_time: 0.0236 memory: 5826 grad_norm: 2.9802 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6963 loss: 2.6963 2022/10/07 13:39:04 - mmengine - INFO - Epoch(train) [30][1580/2119] lr: 4.0000e-02 eta: 1 day, 0:03:29 time: 0.3827 data_time: 0.0247 memory: 5826 grad_norm: 3.0383 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7124 loss: 2.7124 2022/10/07 13:39:11 - mmengine - INFO - Epoch(train) [30][1600/2119] lr: 4.0000e-02 eta: 1 day, 0:03:25 time: 0.3714 data_time: 0.0185 memory: 5826 grad_norm: 2.9561 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8117 loss: 2.8117 2022/10/07 13:39:19 - mmengine - INFO - Epoch(train) [30][1620/2119] lr: 4.0000e-02 eta: 1 day, 0:03:23 time: 0.3989 data_time: 0.0222 memory: 5826 grad_norm: 3.0002 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.7934 loss: 2.7934 2022/10/07 13:39:27 - mmengine - INFO - Epoch(train) [30][1640/2119] lr: 4.0000e-02 eta: 1 day, 0:03:19 time: 0.3848 data_time: 0.0238 memory: 5826 grad_norm: 2.9596 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8782 loss: 2.8782 2022/10/07 13:39:34 - mmengine - INFO - Epoch(train) [30][1660/2119] lr: 4.0000e-02 eta: 1 day, 0:03:13 time: 0.3387 data_time: 0.0260 memory: 5826 grad_norm: 2.8801 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9317 loss: 2.9317 2022/10/07 13:39:40 - mmengine - INFO - Epoch(train) [30][1680/2119] lr: 4.0000e-02 eta: 1 day, 0:03:03 time: 0.3100 data_time: 0.0210 memory: 5826 grad_norm: 2.9443 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8200 loss: 2.8200 2022/10/07 13:39:47 - mmengine - INFO - Epoch(train) [30][1700/2119] lr: 4.0000e-02 eta: 1 day, 0:02:58 time: 0.3542 data_time: 0.0316 memory: 5826 grad_norm: 2.9763 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8314 loss: 2.8314 2022/10/07 13:39:53 - mmengine - INFO - Epoch(train) [30][1720/2119] lr: 4.0000e-02 eta: 1 day, 0:02:49 time: 0.3149 data_time: 0.0213 memory: 5826 grad_norm: 3.0031 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7404 loss: 2.7404 2022/10/07 13:40:01 - mmengine - INFO - Epoch(train) [30][1740/2119] lr: 4.0000e-02 eta: 1 day, 0:02:45 time: 0.3786 data_time: 0.0220 memory: 5826 grad_norm: 3.0234 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8349 loss: 2.8349 2022/10/07 13:40:08 - mmengine - INFO - Epoch(train) [30][1760/2119] lr: 4.0000e-02 eta: 1 day, 0:02:38 time: 0.3333 data_time: 0.0190 memory: 5826 grad_norm: 2.9742 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7848 loss: 2.7848 2022/10/07 13:40:15 - mmengine - INFO - Epoch(train) [30][1780/2119] lr: 4.0000e-02 eta: 1 day, 0:02:34 time: 0.3785 data_time: 0.0176 memory: 5826 grad_norm: 2.9996 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6150 loss: 2.6150 2022/10/07 13:40:21 - mmengine - INFO - Epoch(train) [30][1800/2119] lr: 4.0000e-02 eta: 1 day, 0:02:21 time: 0.2629 data_time: 0.0246 memory: 5826 grad_norm: 2.8966 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8225 loss: 2.8225 2022/10/07 13:40:28 - mmengine - INFO - Epoch(train) [30][1820/2119] lr: 4.0000e-02 eta: 1 day, 0:02:18 time: 0.3799 data_time: 0.0258 memory: 5826 grad_norm: 2.9540 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8110 loss: 2.8110 2022/10/07 13:40:35 - mmengine - INFO - Epoch(train) [30][1840/2119] lr: 4.0000e-02 eta: 1 day, 0:02:12 time: 0.3530 data_time: 0.0310 memory: 5826 grad_norm: 2.9816 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9540 loss: 2.9540 2022/10/07 13:40:41 - mmengine - INFO - Epoch(train) [30][1860/2119] lr: 4.0000e-02 eta: 1 day, 0:02:02 time: 0.2988 data_time: 0.0227 memory: 5826 grad_norm: 2.9495 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6892 loss: 2.6892 2022/10/07 13:40:48 - mmengine - INFO - Epoch(train) [30][1880/2119] lr: 4.0000e-02 eta: 1 day, 0:01:56 time: 0.3536 data_time: 0.0243 memory: 5826 grad_norm: 2.9816 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5905 loss: 2.5905 2022/10/07 13:40:56 - mmengine - INFO - Epoch(train) [30][1900/2119] lr: 4.0000e-02 eta: 1 day, 0:01:51 time: 0.3647 data_time: 0.0216 memory: 5826 grad_norm: 2.9221 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6232 loss: 2.6232 2022/10/07 13:41:02 - mmengine - INFO - Epoch(train) [30][1920/2119] lr: 4.0000e-02 eta: 1 day, 0:01:44 time: 0.3392 data_time: 0.0216 memory: 5826 grad_norm: 2.9941 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8641 loss: 2.8641 2022/10/07 13:41:09 - mmengine - INFO - Epoch(train) [30][1940/2119] lr: 4.0000e-02 eta: 1 day, 0:01:38 time: 0.3495 data_time: 0.0169 memory: 5826 grad_norm: 2.9377 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.9156 loss: 2.9156 2022/10/07 13:41:16 - mmengine - INFO - Epoch(train) [30][1960/2119] lr: 4.0000e-02 eta: 1 day, 0:01:31 time: 0.3351 data_time: 0.0221 memory: 5826 grad_norm: 3.0395 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8536 loss: 2.8536 2022/10/07 13:41:23 - mmengine - INFO - Epoch(train) [30][1980/2119] lr: 4.0000e-02 eta: 1 day, 0:01:24 time: 0.3387 data_time: 0.0223 memory: 5826 grad_norm: 3.0044 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0057 loss: 3.0057 2022/10/07 13:41:29 - mmengine - INFO - Epoch(train) [30][2000/2119] lr: 4.0000e-02 eta: 1 day, 0:01:17 time: 0.3321 data_time: 0.0224 memory: 5826 grad_norm: 2.9826 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7463 loss: 2.7463 2022/10/07 13:41:36 - mmengine - INFO - Epoch(train) [30][2020/2119] lr: 4.0000e-02 eta: 1 day, 0:01:08 time: 0.3141 data_time: 0.0296 memory: 5826 grad_norm: 2.9482 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6665 loss: 2.6665 2022/10/07 13:41:44 - mmengine - INFO - Epoch(train) [30][2040/2119] lr: 4.0000e-02 eta: 1 day, 0:01:06 time: 0.3980 data_time: 0.0211 memory: 5826 grad_norm: 3.0273 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8643 loss: 2.8643 2022/10/07 13:41:51 - mmengine - INFO - Epoch(train) [30][2060/2119] lr: 4.0000e-02 eta: 1 day, 0:01:00 time: 0.3538 data_time: 0.0203 memory: 5826 grad_norm: 2.9753 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.1002 loss: 3.1002 2022/10/07 13:41:58 - mmengine - INFO - Epoch(train) [30][2080/2119] lr: 4.0000e-02 eta: 1 day, 0:00:54 time: 0.3504 data_time: 0.0212 memory: 5826 grad_norm: 3.0285 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9832 loss: 2.9832 2022/10/07 13:42:04 - mmengine - INFO - Epoch(train) [30][2100/2119] lr: 4.0000e-02 eta: 1 day, 0:00:45 time: 0.3085 data_time: 0.0257 memory: 5826 grad_norm: 2.9397 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8553 loss: 2.8553 2022/10/07 13:42:10 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 13:42:10 - mmengine - INFO - Epoch(train) [30][2119/2119] lr: 4.0000e-02 eta: 1 day, 0:00:45 time: 0.2907 data_time: 0.0172 memory: 5826 grad_norm: 3.0224 top1_acc: 0.7000 top5_acc: 0.8000 loss_cls: 2.6720 loss: 2.6720 2022/10/07 13:42:19 - mmengine - INFO - Epoch(val) [30][20/137] eta: 0:00:52 time: 0.4482 data_time: 0.3810 memory: 1241 2022/10/07 13:42:24 - mmengine - INFO - Epoch(val) [30][40/137] eta: 0:00:24 time: 0.2573 data_time: 0.1912 memory: 1241 2022/10/07 13:42:31 - mmengine - INFO - Epoch(val) [30][60/137] eta: 0:00:26 time: 0.3468 data_time: 0.2831 memory: 1241 2022/10/07 13:42:36 - mmengine - INFO - Epoch(val) [30][80/137] eta: 0:00:15 time: 0.2784 data_time: 0.2122 memory: 1241 2022/10/07 13:42:42 - mmengine - INFO - Epoch(val) [30][100/137] eta: 0:00:11 time: 0.3134 data_time: 0.2488 memory: 1241 2022/10/07 13:42:47 - mmengine - INFO - Epoch(val) [30][120/137] eta: 0:00:04 time: 0.2499 data_time: 0.1843 memory: 1241 2022/10/07 13:43:00 - mmengine - INFO - Epoch(val) [30][137/137] acc/top1: 0.4174 acc/top5: 0.6619 acc/mean1: 0.4172 2022/10/07 13:43:10 - mmengine - INFO - Epoch(train) [31][20/2119] lr: 4.0000e-02 eta: 1 day, 0:00:19 time: 0.5097 data_time: 0.1610 memory: 5826 grad_norm: 2.9669 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6167 loss: 2.6167 2022/10/07 13:43:16 - mmengine - INFO - Epoch(train) [31][40/2119] lr: 4.0000e-02 eta: 1 day, 0:00:09 time: 0.2947 data_time: 0.0248 memory: 5826 grad_norm: 2.9653 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.9033 loss: 2.9033 2022/10/07 13:43:24 - mmengine - INFO - Epoch(train) [31][60/2119] lr: 4.0000e-02 eta: 1 day, 0:00:05 time: 0.3725 data_time: 0.0223 memory: 5826 grad_norm: 2.9417 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.5797 loss: 2.5797 2022/10/07 13:43:30 - mmengine - INFO - Epoch(train) [31][80/2119] lr: 4.0000e-02 eta: 23:59:57 time: 0.3290 data_time: 0.0214 memory: 5826 grad_norm: 2.9798 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8100 loss: 2.8100 2022/10/07 13:43:38 - mmengine - INFO - Epoch(train) [31][100/2119] lr: 4.0000e-02 eta: 23:59:53 time: 0.3790 data_time: 0.0248 memory: 5826 grad_norm: 2.9905 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7180 loss: 2.7180 2022/10/07 13:43:44 - mmengine - INFO - Epoch(train) [31][120/2119] lr: 4.0000e-02 eta: 23:59:42 time: 0.2859 data_time: 0.0223 memory: 5826 grad_norm: 3.0078 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7411 loss: 2.7411 2022/10/07 13:43:51 - mmengine - INFO - Epoch(train) [31][140/2119] lr: 4.0000e-02 eta: 23:59:38 time: 0.3675 data_time: 0.0227 memory: 5826 grad_norm: 2.9610 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6859 loss: 2.6859 2022/10/07 13:43:58 - mmengine - INFO - Epoch(train) [31][160/2119] lr: 4.0000e-02 eta: 23:59:30 time: 0.3348 data_time: 0.0204 memory: 5826 grad_norm: 2.9655 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8576 loss: 2.8576 2022/10/07 13:44:05 - mmengine - INFO - Epoch(train) [31][180/2119] lr: 4.0000e-02 eta: 23:59:25 time: 0.3570 data_time: 0.0197 memory: 5826 grad_norm: 2.9527 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6217 loss: 2.6217 2022/10/07 13:44:11 - mmengine - INFO - Epoch(train) [31][200/2119] lr: 4.0000e-02 eta: 23:59:16 time: 0.3178 data_time: 0.0200 memory: 5826 grad_norm: 2.9747 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.4652 loss: 2.4652 2022/10/07 13:44:18 - mmengine - INFO - Epoch(train) [31][220/2119] lr: 4.0000e-02 eta: 23:59:10 time: 0.3436 data_time: 0.0255 memory: 5826 grad_norm: 2.9590 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6632 loss: 2.6632 2022/10/07 13:44:25 - mmengine - INFO - Epoch(train) [31][240/2119] lr: 4.0000e-02 eta: 23:59:03 time: 0.3375 data_time: 0.0217 memory: 5826 grad_norm: 2.9776 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0151 loss: 3.0151 2022/10/07 13:44:32 - mmengine - INFO - Epoch(train) [31][260/2119] lr: 4.0000e-02 eta: 23:58:58 time: 0.3601 data_time: 0.0220 memory: 5826 grad_norm: 2.9675 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7607 loss: 2.7607 2022/10/07 13:44:39 - mmengine - INFO - Epoch(train) [31][280/2119] lr: 4.0000e-02 eta: 23:58:53 time: 0.3603 data_time: 0.0214 memory: 5826 grad_norm: 3.0232 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9469 loss: 2.9469 2022/10/07 13:44:47 - mmengine - INFO - Epoch(train) [31][300/2119] lr: 4.0000e-02 eta: 23:58:50 time: 0.3950 data_time: 0.0221 memory: 5826 grad_norm: 2.9782 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9451 loss: 2.9451 2022/10/07 13:44:53 - mmengine - INFO - Epoch(train) [31][320/2119] lr: 4.0000e-02 eta: 23:58:42 time: 0.3181 data_time: 0.0226 memory: 5826 grad_norm: 3.0111 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.9256 loss: 2.9256 2022/10/07 13:45:01 - mmengine - INFO - Epoch(train) [31][340/2119] lr: 4.0000e-02 eta: 23:58:39 time: 0.3943 data_time: 0.0214 memory: 5826 grad_norm: 3.0058 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9404 loss: 2.9404 2022/10/07 13:45:08 - mmengine - INFO - Epoch(train) [31][360/2119] lr: 4.0000e-02 eta: 23:58:30 time: 0.3146 data_time: 0.0237 memory: 5826 grad_norm: 3.0306 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.8365 loss: 2.8365 2022/10/07 13:45:15 - mmengine - INFO - Epoch(train) [31][380/2119] lr: 4.0000e-02 eta: 23:58:27 time: 0.3833 data_time: 0.0200 memory: 5826 grad_norm: 2.9518 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.6679 loss: 2.6679 2022/10/07 13:45:22 - mmengine - INFO - Epoch(train) [31][400/2119] lr: 4.0000e-02 eta: 23:58:21 time: 0.3524 data_time: 0.0214 memory: 5826 grad_norm: 2.9742 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5804 loss: 2.5804 2022/10/07 13:45:30 - mmengine - INFO - Epoch(train) [31][420/2119] lr: 4.0000e-02 eta: 23:58:17 time: 0.3689 data_time: 0.0199 memory: 5826 grad_norm: 3.0101 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7369 loss: 2.7369 2022/10/07 13:45:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 13:45:36 - mmengine - INFO - Epoch(train) [31][440/2119] lr: 4.0000e-02 eta: 23:58:09 time: 0.3326 data_time: 0.0211 memory: 5826 grad_norm: 2.9843 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9085 loss: 2.9085 2022/10/07 13:45:44 - mmengine - INFO - Epoch(train) [31][460/2119] lr: 4.0000e-02 eta: 23:58:05 time: 0.3770 data_time: 0.0256 memory: 5826 grad_norm: 2.9626 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6523 loss: 2.6523 2022/10/07 13:45:50 - mmengine - INFO - Epoch(train) [31][480/2119] lr: 4.0000e-02 eta: 23:57:57 time: 0.3157 data_time: 0.0186 memory: 5826 grad_norm: 3.0443 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9266 loss: 2.9266 2022/10/07 13:45:58 - mmengine - INFO - Epoch(train) [31][500/2119] lr: 4.0000e-02 eta: 23:57:53 time: 0.3762 data_time: 0.0203 memory: 5826 grad_norm: 2.9951 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6143 loss: 2.6143 2022/10/07 13:46:04 - mmengine - INFO - Epoch(train) [31][520/2119] lr: 4.0000e-02 eta: 23:57:45 time: 0.3285 data_time: 0.0207 memory: 5826 grad_norm: 3.0531 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.9354 loss: 2.9354 2022/10/07 13:46:12 - mmengine - INFO - Epoch(train) [31][540/2119] lr: 4.0000e-02 eta: 23:57:41 time: 0.3712 data_time: 0.0266 memory: 5826 grad_norm: 2.9962 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8739 loss: 2.8739 2022/10/07 13:46:18 - mmengine - INFO - Epoch(train) [31][560/2119] lr: 4.0000e-02 eta: 23:57:31 time: 0.3009 data_time: 0.0265 memory: 5826 grad_norm: 3.0818 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.1053 loss: 3.1053 2022/10/07 13:46:24 - mmengine - INFO - Epoch(train) [31][580/2119] lr: 4.0000e-02 eta: 23:57:23 time: 0.3316 data_time: 0.0259 memory: 5826 grad_norm: 2.9858 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7460 loss: 2.7460 2022/10/07 13:46:31 - mmengine - INFO - Epoch(train) [31][600/2119] lr: 4.0000e-02 eta: 23:57:17 time: 0.3402 data_time: 0.0177 memory: 5826 grad_norm: 3.0609 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6001 loss: 2.6001 2022/10/07 13:46:39 - mmengine - INFO - Epoch(train) [31][620/2119] lr: 4.0000e-02 eta: 23:57:15 time: 0.4029 data_time: 0.0206 memory: 5826 grad_norm: 3.0659 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9195 loss: 2.9195 2022/10/07 13:46:46 - mmengine - INFO - Epoch(train) [31][640/2119] lr: 4.0000e-02 eta: 23:57:06 time: 0.3132 data_time: 0.0204 memory: 5826 grad_norm: 3.0284 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7975 loss: 2.7975 2022/10/07 13:46:53 - mmengine - INFO - Epoch(train) [31][660/2119] lr: 4.0000e-02 eta: 23:57:01 time: 0.3630 data_time: 0.0203 memory: 5826 grad_norm: 2.9531 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7018 loss: 2.7018 2022/10/07 13:46:59 - mmengine - INFO - Epoch(train) [31][680/2119] lr: 4.0000e-02 eta: 23:56:53 time: 0.3273 data_time: 0.0241 memory: 5826 grad_norm: 2.9880 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9718 loss: 2.9718 2022/10/07 13:47:07 - mmengine - INFO - Epoch(train) [31][700/2119] lr: 4.0000e-02 eta: 23:56:51 time: 0.3923 data_time: 0.0248 memory: 5826 grad_norm: 2.9886 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7652 loss: 2.7652 2022/10/07 13:47:13 - mmengine - INFO - Epoch(train) [31][720/2119] lr: 4.0000e-02 eta: 23:56:42 time: 0.3151 data_time: 0.0209 memory: 5826 grad_norm: 2.9591 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7098 loss: 2.7098 2022/10/07 13:47:21 - mmengine - INFO - Epoch(train) [31][740/2119] lr: 4.0000e-02 eta: 23:56:37 time: 0.3719 data_time: 0.0228 memory: 5826 grad_norm: 2.9719 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 3.0089 loss: 3.0089 2022/10/07 13:47:28 - mmengine - INFO - Epoch(train) [31][760/2119] lr: 4.0000e-02 eta: 23:56:31 time: 0.3420 data_time: 0.0198 memory: 5826 grad_norm: 2.9918 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7825 loss: 2.7825 2022/10/07 13:47:35 - mmengine - INFO - Epoch(train) [31][780/2119] lr: 4.0000e-02 eta: 23:56:26 time: 0.3600 data_time: 0.0312 memory: 5826 grad_norm: 2.9801 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8405 loss: 2.8405 2022/10/07 13:47:42 - mmengine - INFO - Epoch(train) [31][800/2119] lr: 4.0000e-02 eta: 23:56:20 time: 0.3587 data_time: 0.0160 memory: 5826 grad_norm: 3.0036 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.5762 loss: 2.5762 2022/10/07 13:47:48 - mmengine - INFO - Epoch(train) [31][820/2119] lr: 4.0000e-02 eta: 23:56:10 time: 0.2982 data_time: 0.0249 memory: 5826 grad_norm: 3.0201 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.8245 loss: 2.8245 2022/10/07 13:47:55 - mmengine - INFO - Epoch(train) [31][840/2119] lr: 4.0000e-02 eta: 23:56:03 time: 0.3403 data_time: 0.0234 memory: 5826 grad_norm: 3.0263 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8183 loss: 2.8183 2022/10/07 13:48:03 - mmengine - INFO - Epoch(train) [31][860/2119] lr: 4.0000e-02 eta: 23:56:00 time: 0.3810 data_time: 0.0166 memory: 5826 grad_norm: 2.9915 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8037 loss: 2.8037 2022/10/07 13:48:09 - mmengine - INFO - Epoch(train) [31][880/2119] lr: 4.0000e-02 eta: 23:55:50 time: 0.2991 data_time: 0.0240 memory: 5826 grad_norm: 2.9478 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8954 loss: 2.8954 2022/10/07 13:48:16 - mmengine - INFO - Epoch(train) [31][900/2119] lr: 4.0000e-02 eta: 23:55:48 time: 0.3983 data_time: 0.0203 memory: 5826 grad_norm: 3.0382 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6887 loss: 2.6887 2022/10/07 13:48:22 - mmengine - INFO - Epoch(train) [31][920/2119] lr: 4.0000e-02 eta: 23:55:36 time: 0.2799 data_time: 0.0253 memory: 5826 grad_norm: 2.9483 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7944 loss: 2.7944 2022/10/07 13:48:29 - mmengine - INFO - Epoch(train) [31][940/2119] lr: 4.0000e-02 eta: 23:55:31 time: 0.3651 data_time: 0.0206 memory: 5826 grad_norm: 2.9713 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7639 loss: 2.7639 2022/10/07 13:48:36 - mmengine - INFO - Epoch(train) [31][960/2119] lr: 4.0000e-02 eta: 23:55:23 time: 0.3223 data_time: 0.0196 memory: 5826 grad_norm: 3.0021 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7301 loss: 2.7301 2022/10/07 13:48:43 - mmengine - INFO - Epoch(train) [31][980/2119] lr: 4.0000e-02 eta: 23:55:19 time: 0.3798 data_time: 0.0157 memory: 5826 grad_norm: 2.9711 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6956 loss: 2.6956 2022/10/07 13:48:50 - mmengine - INFO - Epoch(train) [31][1000/2119] lr: 4.0000e-02 eta: 23:55:10 time: 0.3043 data_time: 0.0223 memory: 5826 grad_norm: 2.9806 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.5637 loss: 2.5637 2022/10/07 13:48:57 - mmengine - INFO - Epoch(train) [31][1020/2119] lr: 4.0000e-02 eta: 23:55:04 time: 0.3589 data_time: 0.0206 memory: 5826 grad_norm: 3.0088 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8402 loss: 2.8402 2022/10/07 13:49:03 - mmengine - INFO - Epoch(train) [31][1040/2119] lr: 4.0000e-02 eta: 23:54:55 time: 0.3096 data_time: 0.0243 memory: 5826 grad_norm: 3.0130 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7764 loss: 2.7764 2022/10/07 13:49:10 - mmengine - INFO - Epoch(train) [31][1060/2119] lr: 4.0000e-02 eta: 23:54:51 time: 0.3659 data_time: 0.0257 memory: 5826 grad_norm: 2.9602 top1_acc: 0.2500 top5_acc: 0.3125 loss_cls: 2.6887 loss: 2.6887 2022/10/07 13:49:17 - mmengine - INFO - Epoch(train) [31][1080/2119] lr: 4.0000e-02 eta: 23:54:45 time: 0.3504 data_time: 0.0201 memory: 5826 grad_norm: 2.9595 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7823 loss: 2.7823 2022/10/07 13:49:24 - mmengine - INFO - Epoch(train) [31][1100/2119] lr: 4.0000e-02 eta: 23:54:36 time: 0.3213 data_time: 0.0235 memory: 5826 grad_norm: 3.0137 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6851 loss: 2.6851 2022/10/07 13:49:30 - mmengine - INFO - Epoch(train) [31][1120/2119] lr: 4.0000e-02 eta: 23:54:27 time: 0.3076 data_time: 0.0260 memory: 5826 grad_norm: 2.9966 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6594 loss: 2.6594 2022/10/07 13:49:37 - mmengine - INFO - Epoch(train) [31][1140/2119] lr: 4.0000e-02 eta: 23:54:21 time: 0.3566 data_time: 0.0248 memory: 5826 grad_norm: 3.0075 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5043 loss: 2.5043 2022/10/07 13:49:43 - mmengine - INFO - Epoch(train) [31][1160/2119] lr: 4.0000e-02 eta: 23:54:13 time: 0.3211 data_time: 0.0212 memory: 5826 grad_norm: 2.9682 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9369 loss: 2.9369 2022/10/07 13:49:51 - mmengine - INFO - Epoch(train) [31][1180/2119] lr: 4.0000e-02 eta: 23:54:10 time: 0.3862 data_time: 0.0208 memory: 5826 grad_norm: 3.0041 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9080 loss: 2.9080 2022/10/07 13:49:58 - mmengine - INFO - Epoch(train) [31][1200/2119] lr: 4.0000e-02 eta: 23:54:03 time: 0.3341 data_time: 0.0240 memory: 5826 grad_norm: 3.0357 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9055 loss: 2.9055 2022/10/07 13:50:05 - mmengine - INFO - Epoch(train) [31][1220/2119] lr: 4.0000e-02 eta: 23:53:57 time: 0.3570 data_time: 0.0210 memory: 5826 grad_norm: 2.9610 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8411 loss: 2.8411 2022/10/07 13:50:11 - mmengine - INFO - Epoch(train) [31][1240/2119] lr: 4.0000e-02 eta: 23:53:48 time: 0.3130 data_time: 0.0219 memory: 5826 grad_norm: 2.9645 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5576 loss: 2.5576 2022/10/07 13:50:19 - mmengine - INFO - Epoch(train) [31][1260/2119] lr: 4.0000e-02 eta: 23:53:47 time: 0.4040 data_time: 0.0229 memory: 5826 grad_norm: 2.9833 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8022 loss: 2.8022 2022/10/07 13:50:25 - mmengine - INFO - Epoch(train) [31][1280/2119] lr: 4.0000e-02 eta: 23:53:37 time: 0.3089 data_time: 0.0224 memory: 5826 grad_norm: 3.0186 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7803 loss: 2.7803 2022/10/07 13:50:32 - mmengine - INFO - Epoch(train) [31][1300/2119] lr: 4.0000e-02 eta: 23:53:30 time: 0.3364 data_time: 0.0228 memory: 5826 grad_norm: 2.9712 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6956 loss: 2.6956 2022/10/07 13:50:39 - mmengine - INFO - Epoch(train) [31][1320/2119] lr: 4.0000e-02 eta: 23:53:22 time: 0.3178 data_time: 0.0249 memory: 5826 grad_norm: 2.9667 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7276 loss: 2.7276 2022/10/07 13:50:46 - mmengine - INFO - Epoch(train) [31][1340/2119] lr: 4.0000e-02 eta: 23:53:18 time: 0.3775 data_time: 0.0215 memory: 5826 grad_norm: 2.9870 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7185 loss: 2.7185 2022/10/07 13:50:52 - mmengine - INFO - Epoch(train) [31][1360/2119] lr: 4.0000e-02 eta: 23:53:09 time: 0.3107 data_time: 0.0172 memory: 5826 grad_norm: 2.9349 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8286 loss: 2.8286 2022/10/07 13:50:59 - mmengine - INFO - Epoch(train) [31][1380/2119] lr: 4.0000e-02 eta: 23:53:04 time: 0.3597 data_time: 0.0227 memory: 5826 grad_norm: 2.9700 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5736 loss: 2.5736 2022/10/07 13:51:06 - mmengine - INFO - Epoch(train) [31][1400/2119] lr: 4.0000e-02 eta: 23:52:57 time: 0.3414 data_time: 0.0206 memory: 5826 grad_norm: 2.9959 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5029 loss: 2.5029 2022/10/07 13:51:13 - mmengine - INFO - Epoch(train) [31][1420/2119] lr: 4.0000e-02 eta: 23:52:50 time: 0.3366 data_time: 0.0260 memory: 5826 grad_norm: 3.0195 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4484 loss: 2.4484 2022/10/07 13:51:17 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 13:51:20 - mmengine - INFO - Epoch(train) [31][1440/2119] lr: 4.0000e-02 eta: 23:52:44 time: 0.3516 data_time: 0.0248 memory: 5826 grad_norm: 3.0532 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6416 loss: 2.6416 2022/10/07 13:51:27 - mmengine - INFO - Epoch(train) [31][1460/2119] lr: 4.0000e-02 eta: 23:52:38 time: 0.3469 data_time: 0.0232 memory: 5826 grad_norm: 3.0204 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9291 loss: 2.9291 2022/10/07 13:51:34 - mmengine - INFO - Epoch(train) [31][1480/2119] lr: 4.0000e-02 eta: 23:52:30 time: 0.3312 data_time: 0.0201 memory: 5826 grad_norm: 2.9393 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7370 loss: 2.7370 2022/10/07 13:51:42 - mmengine - INFO - Epoch(train) [31][1500/2119] lr: 4.0000e-02 eta: 23:52:27 time: 0.3933 data_time: 0.0193 memory: 5826 grad_norm: 2.9535 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7779 loss: 2.7779 2022/10/07 13:51:48 - mmengine - INFO - Epoch(train) [31][1520/2119] lr: 4.0000e-02 eta: 23:52:18 time: 0.3114 data_time: 0.0269 memory: 5826 grad_norm: 2.9890 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.0504 loss: 3.0504 2022/10/07 13:51:55 - mmengine - INFO - Epoch(train) [31][1540/2119] lr: 4.0000e-02 eta: 23:52:13 time: 0.3587 data_time: 0.0228 memory: 5826 grad_norm: 2.9782 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7551 loss: 2.7551 2022/10/07 13:52:01 - mmengine - INFO - Epoch(train) [31][1560/2119] lr: 4.0000e-02 eta: 23:52:05 time: 0.3274 data_time: 0.0266 memory: 5826 grad_norm: 2.9821 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7374 loss: 2.7374 2022/10/07 13:52:09 - mmengine - INFO - Epoch(train) [31][1580/2119] lr: 4.0000e-02 eta: 23:51:59 time: 0.3524 data_time: 0.0236 memory: 5826 grad_norm: 3.0354 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.8447 loss: 2.8447 2022/10/07 13:52:15 - mmengine - INFO - Epoch(train) [31][1600/2119] lr: 4.0000e-02 eta: 23:51:52 time: 0.3339 data_time: 0.0220 memory: 5826 grad_norm: 3.0372 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9146 loss: 2.9146 2022/10/07 13:52:22 - mmengine - INFO - Epoch(train) [31][1620/2119] lr: 4.0000e-02 eta: 23:51:47 time: 0.3628 data_time: 0.0186 memory: 5826 grad_norm: 3.0459 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7870 loss: 2.7870 2022/10/07 13:52:29 - mmengine - INFO - Epoch(train) [31][1640/2119] lr: 4.0000e-02 eta: 23:51:40 time: 0.3337 data_time: 0.0293 memory: 5826 grad_norm: 2.9393 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8295 loss: 2.8295 2022/10/07 13:52:36 - mmengine - INFO - Epoch(train) [31][1660/2119] lr: 4.0000e-02 eta: 23:51:34 time: 0.3552 data_time: 0.0208 memory: 5826 grad_norm: 2.9998 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5782 loss: 2.5782 2022/10/07 13:52:43 - mmengine - INFO - Epoch(train) [31][1680/2119] lr: 4.0000e-02 eta: 23:51:29 time: 0.3557 data_time: 0.0147 memory: 5826 grad_norm: 3.0039 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7140 loss: 2.7140 2022/10/07 13:52:50 - mmengine - INFO - Epoch(train) [31][1700/2119] lr: 4.0000e-02 eta: 23:51:22 time: 0.3359 data_time: 0.0229 memory: 5826 grad_norm: 2.9867 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7665 loss: 2.7665 2022/10/07 13:52:56 - mmengine - INFO - Epoch(train) [31][1720/2119] lr: 4.0000e-02 eta: 23:51:13 time: 0.3194 data_time: 0.0267 memory: 5826 grad_norm: 2.9525 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8220 loss: 2.8220 2022/10/07 13:53:04 - mmengine - INFO - Epoch(train) [31][1740/2119] lr: 4.0000e-02 eta: 23:51:07 time: 0.3515 data_time: 0.0207 memory: 5826 grad_norm: 2.9765 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7499 loss: 2.7499 2022/10/07 13:53:10 - mmengine - INFO - Epoch(train) [31][1760/2119] lr: 4.0000e-02 eta: 23:51:01 time: 0.3471 data_time: 0.0235 memory: 5826 grad_norm: 3.0059 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8783 loss: 2.8783 2022/10/07 13:53:18 - mmengine - INFO - Epoch(train) [31][1780/2119] lr: 4.0000e-02 eta: 23:50:57 time: 0.3731 data_time: 0.0197 memory: 5826 grad_norm: 3.0365 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9657 loss: 2.9657 2022/10/07 13:53:25 - mmengine - INFO - Epoch(train) [31][1800/2119] lr: 4.0000e-02 eta: 23:50:49 time: 0.3298 data_time: 0.0199 memory: 5826 grad_norm: 2.9848 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8346 loss: 2.8346 2022/10/07 13:53:32 - mmengine - INFO - Epoch(train) [31][1820/2119] lr: 4.0000e-02 eta: 23:50:46 time: 0.3858 data_time: 0.0222 memory: 5826 grad_norm: 2.9990 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.2111 loss: 3.2111 2022/10/07 13:53:38 - mmengine - INFO - Epoch(train) [31][1840/2119] lr: 4.0000e-02 eta: 23:50:36 time: 0.2959 data_time: 0.0196 memory: 5826 grad_norm: 3.0179 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0909 loss: 3.0909 2022/10/07 13:53:46 - mmengine - INFO - Epoch(train) [31][1860/2119] lr: 4.0000e-02 eta: 23:50:31 time: 0.3736 data_time: 0.0206 memory: 5826 grad_norm: 2.9645 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8791 loss: 2.8791 2022/10/07 13:53:52 - mmengine - INFO - Epoch(train) [31][1880/2119] lr: 4.0000e-02 eta: 23:50:23 time: 0.3206 data_time: 0.0201 memory: 5826 grad_norm: 2.9907 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8065 loss: 2.8065 2022/10/07 13:54:00 - mmengine - INFO - Epoch(train) [31][1900/2119] lr: 4.0000e-02 eta: 23:50:22 time: 0.4092 data_time: 0.0183 memory: 5826 grad_norm: 3.0172 top1_acc: 0.1875 top5_acc: 0.2500 loss_cls: 3.1549 loss: 3.1549 2022/10/07 13:54:07 - mmengine - INFO - Epoch(train) [31][1920/2119] lr: 4.0000e-02 eta: 23:50:13 time: 0.3174 data_time: 0.0220 memory: 5826 grad_norm: 2.9828 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8888 loss: 2.8888 2022/10/07 13:54:13 - mmengine - INFO - Epoch(train) [31][1940/2119] lr: 4.0000e-02 eta: 23:50:03 time: 0.3017 data_time: 0.0211 memory: 5826 grad_norm: 2.9526 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5619 loss: 2.5619 2022/10/07 13:54:19 - mmengine - INFO - Epoch(train) [31][1960/2119] lr: 4.0000e-02 eta: 23:49:56 time: 0.3276 data_time: 0.0204 memory: 5826 grad_norm: 2.9747 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7050 loss: 2.7050 2022/10/07 13:54:26 - mmengine - INFO - Epoch(train) [31][1980/2119] lr: 4.0000e-02 eta: 23:49:49 time: 0.3433 data_time: 0.0190 memory: 5826 grad_norm: 2.9461 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9739 loss: 2.9739 2022/10/07 13:54:33 - mmengine - INFO - Epoch(train) [31][2000/2119] lr: 4.0000e-02 eta: 23:49:42 time: 0.3364 data_time: 0.0205 memory: 5826 grad_norm: 3.0314 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7341 loss: 2.7341 2022/10/07 13:54:39 - mmengine - INFO - Epoch(train) [31][2020/2119] lr: 4.0000e-02 eta: 23:49:35 time: 0.3349 data_time: 0.0219 memory: 5826 grad_norm: 2.9170 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6095 loss: 2.6095 2022/10/07 13:54:46 - mmengine - INFO - Epoch(train) [31][2040/2119] lr: 4.0000e-02 eta: 23:49:29 time: 0.3489 data_time: 0.0187 memory: 5826 grad_norm: 2.9762 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.1340 loss: 3.1340 2022/10/07 13:54:53 - mmengine - INFO - Epoch(train) [31][2060/2119] lr: 4.0000e-02 eta: 23:49:20 time: 0.3128 data_time: 0.0211 memory: 5826 grad_norm: 2.9616 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7927 loss: 2.7927 2022/10/07 13:55:00 - mmengine - INFO - Epoch(train) [31][2080/2119] lr: 4.0000e-02 eta: 23:49:15 time: 0.3632 data_time: 0.0177 memory: 5826 grad_norm: 3.0131 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6839 loss: 2.6839 2022/10/07 13:55:06 - mmengine - INFO - Epoch(train) [31][2100/2119] lr: 4.0000e-02 eta: 23:49:06 time: 0.3153 data_time: 0.0173 memory: 5826 grad_norm: 3.0656 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9578 loss: 2.9578 2022/10/07 13:55:12 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 13:55:12 - mmengine - INFO - Epoch(train) [31][2119/2119] lr: 4.0000e-02 eta: 23:49:06 time: 0.2896 data_time: 0.0179 memory: 5826 grad_norm: 3.0069 top1_acc: 0.3000 top5_acc: 0.6000 loss_cls: 2.7651 loss: 2.7651 2022/10/07 13:55:21 - mmengine - INFO - Epoch(train) [32][20/2119] lr: 4.0000e-02 eta: 23:48:39 time: 0.4774 data_time: 0.1476 memory: 5826 grad_norm: 2.9307 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5241 loss: 2.5241 2022/10/07 13:55:28 - mmengine - INFO - Epoch(train) [32][40/2119] lr: 4.0000e-02 eta: 23:48:31 time: 0.3318 data_time: 0.0225 memory: 5826 grad_norm: 2.9931 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7593 loss: 2.7593 2022/10/07 13:55:37 - mmengine - INFO - Epoch(train) [32][60/2119] lr: 4.0000e-02 eta: 23:48:31 time: 0.4271 data_time: 0.0197 memory: 5826 grad_norm: 2.9759 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8471 loss: 2.8471 2022/10/07 13:55:42 - mmengine - INFO - Epoch(train) [32][80/2119] lr: 4.0000e-02 eta: 23:48:21 time: 0.2924 data_time: 0.0204 memory: 5826 grad_norm: 2.9309 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.6154 loss: 2.6154 2022/10/07 13:55:50 - mmengine - INFO - Epoch(train) [32][100/2119] lr: 4.0000e-02 eta: 23:48:15 time: 0.3554 data_time: 0.0226 memory: 5826 grad_norm: 2.9546 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0289 loss: 3.0289 2022/10/07 13:55:57 - mmengine - INFO - Epoch(train) [32][120/2119] lr: 4.0000e-02 eta: 23:48:10 time: 0.3698 data_time: 0.0216 memory: 5826 grad_norm: 2.9278 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.8863 loss: 2.8863 2022/10/07 13:56:04 - mmengine - INFO - Epoch(train) [32][140/2119] lr: 4.0000e-02 eta: 23:48:04 time: 0.3384 data_time: 0.0158 memory: 5826 grad_norm: 2.9943 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9826 loss: 2.9826 2022/10/07 13:56:11 - mmengine - INFO - Epoch(train) [32][160/2119] lr: 4.0000e-02 eta: 23:47:57 time: 0.3472 data_time: 0.0219 memory: 5826 grad_norm: 2.9401 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5408 loss: 2.5408 2022/10/07 13:56:19 - mmengine - INFO - Epoch(train) [32][180/2119] lr: 4.0000e-02 eta: 23:47:55 time: 0.3941 data_time: 0.0167 memory: 5826 grad_norm: 2.9821 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7872 loss: 2.7872 2022/10/07 13:56:25 - mmengine - INFO - Epoch(train) [32][200/2119] lr: 4.0000e-02 eta: 23:47:47 time: 0.3303 data_time: 0.0195 memory: 5826 grad_norm: 3.0319 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8711 loss: 2.8711 2022/10/07 13:56:32 - mmengine - INFO - Epoch(train) [32][220/2119] lr: 4.0000e-02 eta: 23:47:41 time: 0.3466 data_time: 0.0200 memory: 5826 grad_norm: 2.9790 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9164 loss: 2.9164 2022/10/07 13:56:39 - mmengine - INFO - Epoch(train) [32][240/2119] lr: 4.0000e-02 eta: 23:47:36 time: 0.3700 data_time: 0.0207 memory: 5826 grad_norm: 3.0653 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8228 loss: 2.8228 2022/10/07 13:56:47 - mmengine - INFO - Epoch(train) [32][260/2119] lr: 4.0000e-02 eta: 23:47:33 time: 0.3902 data_time: 0.0219 memory: 5826 grad_norm: 2.9845 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6308 loss: 2.6308 2022/10/07 13:56:54 - mmengine - INFO - Epoch(train) [32][280/2119] lr: 4.0000e-02 eta: 23:47:26 time: 0.3271 data_time: 0.0226 memory: 5826 grad_norm: 3.0195 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7141 loss: 2.7141 2022/10/07 13:57:01 - mmengine - INFO - Epoch(train) [32][300/2119] lr: 4.0000e-02 eta: 23:47:19 time: 0.3454 data_time: 0.0230 memory: 5826 grad_norm: 3.0220 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8413 loss: 2.8413 2022/10/07 13:57:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 13:57:07 - mmengine - INFO - Epoch(train) [32][320/2119] lr: 4.0000e-02 eta: 23:47:10 time: 0.3119 data_time: 0.0243 memory: 5826 grad_norm: 2.9629 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6882 loss: 2.6882 2022/10/07 13:57:14 - mmengine - INFO - Epoch(train) [32][340/2119] lr: 4.0000e-02 eta: 23:47:03 time: 0.3331 data_time: 0.0205 memory: 5826 grad_norm: 2.9564 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7505 loss: 2.7505 2022/10/07 13:57:20 - mmengine - INFO - Epoch(train) [32][360/2119] lr: 4.0000e-02 eta: 23:46:56 time: 0.3370 data_time: 0.0231 memory: 5826 grad_norm: 3.0383 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7712 loss: 2.7712 2022/10/07 13:57:28 - mmengine - INFO - Epoch(train) [32][380/2119] lr: 4.0000e-02 eta: 23:46:51 time: 0.3660 data_time: 0.0207 memory: 5826 grad_norm: 2.9615 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6838 loss: 2.6838 2022/10/07 13:57:35 - mmengine - INFO - Epoch(train) [32][400/2119] lr: 4.0000e-02 eta: 23:46:46 time: 0.3578 data_time: 0.0255 memory: 5826 grad_norm: 3.0161 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9585 loss: 2.9585 2022/10/07 13:57:42 - mmengine - INFO - Epoch(train) [32][420/2119] lr: 4.0000e-02 eta: 23:46:41 time: 0.3682 data_time: 0.0186 memory: 5826 grad_norm: 3.0298 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8382 loss: 2.8382 2022/10/07 13:57:48 - mmengine - INFO - Epoch(train) [32][440/2119] lr: 4.0000e-02 eta: 23:46:32 time: 0.3070 data_time: 0.0267 memory: 5826 grad_norm: 3.0118 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.4383 loss: 2.4383 2022/10/07 13:57:55 - mmengine - INFO - Epoch(train) [32][460/2119] lr: 4.0000e-02 eta: 23:46:25 time: 0.3382 data_time: 0.0202 memory: 5826 grad_norm: 3.0188 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7234 loss: 2.7234 2022/10/07 13:58:02 - mmengine - INFO - Epoch(train) [32][480/2119] lr: 4.0000e-02 eta: 23:46:17 time: 0.3253 data_time: 0.0203 memory: 5826 grad_norm: 3.0221 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.8200 loss: 2.8200 2022/10/07 13:58:09 - mmengine - INFO - Epoch(train) [32][500/2119] lr: 4.0000e-02 eta: 23:46:11 time: 0.3552 data_time: 0.0205 memory: 5826 grad_norm: 3.0433 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9848 loss: 2.9848 2022/10/07 13:58:16 - mmengine - INFO - Epoch(train) [32][520/2119] lr: 4.0000e-02 eta: 23:46:07 time: 0.3766 data_time: 0.0198 memory: 5826 grad_norm: 2.9685 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8942 loss: 2.8942 2022/10/07 13:58:24 - mmengine - INFO - Epoch(train) [32][540/2119] lr: 4.0000e-02 eta: 23:46:02 time: 0.3614 data_time: 0.0205 memory: 5826 grad_norm: 2.9957 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8232 loss: 2.8232 2022/10/07 13:58:30 - mmengine - INFO - Epoch(train) [32][560/2119] lr: 4.0000e-02 eta: 23:45:52 time: 0.3019 data_time: 0.0191 memory: 5826 grad_norm: 3.0033 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0410 loss: 3.0410 2022/10/07 13:58:38 - mmengine - INFO - Epoch(train) [32][580/2119] lr: 4.0000e-02 eta: 23:45:52 time: 0.4235 data_time: 0.0192 memory: 5826 grad_norm: 2.9453 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8641 loss: 2.8641 2022/10/07 13:58:44 - mmengine - INFO - Epoch(train) [32][600/2119] lr: 4.0000e-02 eta: 23:45:43 time: 0.3134 data_time: 0.0199 memory: 5826 grad_norm: 2.9888 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5958 loss: 2.5958 2022/10/07 13:58:51 - mmengine - INFO - Epoch(train) [32][620/2119] lr: 4.0000e-02 eta: 23:45:37 time: 0.3460 data_time: 0.0196 memory: 5826 grad_norm: 3.0086 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7120 loss: 2.7120 2022/10/07 13:58:59 - mmengine - INFO - Epoch(train) [32][640/2119] lr: 4.0000e-02 eta: 23:45:32 time: 0.3713 data_time: 0.0191 memory: 5826 grad_norm: 2.9395 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6406 loss: 2.6406 2022/10/07 13:59:06 - mmengine - INFO - Epoch(train) [32][660/2119] lr: 4.0000e-02 eta: 23:45:26 time: 0.3535 data_time: 0.0187 memory: 5826 grad_norm: 3.0336 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8038 loss: 2.8038 2022/10/07 13:59:12 - mmengine - INFO - Epoch(train) [32][680/2119] lr: 4.0000e-02 eta: 23:45:18 time: 0.3166 data_time: 0.0208 memory: 5826 grad_norm: 2.9787 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6227 loss: 2.6227 2022/10/07 13:59:20 - mmengine - INFO - Epoch(train) [32][700/2119] lr: 4.0000e-02 eta: 23:45:14 time: 0.3828 data_time: 0.0210 memory: 5826 grad_norm: 2.9902 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7812 loss: 2.7812 2022/10/07 13:59:26 - mmengine - INFO - Epoch(train) [32][720/2119] lr: 4.0000e-02 eta: 23:45:04 time: 0.2990 data_time: 0.0203 memory: 5826 grad_norm: 2.9779 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7320 loss: 2.7320 2022/10/07 13:59:33 - mmengine - INFO - Epoch(train) [32][740/2119] lr: 4.0000e-02 eta: 23:44:59 time: 0.3624 data_time: 0.0194 memory: 5826 grad_norm: 2.9541 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6941 loss: 2.6941 2022/10/07 13:59:40 - mmengine - INFO - Epoch(train) [32][760/2119] lr: 4.0000e-02 eta: 23:44:52 time: 0.3349 data_time: 0.0221 memory: 5826 grad_norm: 2.9984 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7809 loss: 2.7809 2022/10/07 13:59:47 - mmengine - INFO - Epoch(train) [32][780/2119] lr: 4.0000e-02 eta: 23:44:48 time: 0.3833 data_time: 0.0178 memory: 5826 grad_norm: 2.9964 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7126 loss: 2.7126 2022/10/07 13:59:53 - mmengine - INFO - Epoch(train) [32][800/2119] lr: 4.0000e-02 eta: 23:44:37 time: 0.2820 data_time: 0.0251 memory: 5826 grad_norm: 3.0405 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7395 loss: 2.7395 2022/10/07 14:00:01 - mmengine - INFO - Epoch(train) [32][820/2119] lr: 4.0000e-02 eta: 23:44:34 time: 0.3817 data_time: 0.0225 memory: 5826 grad_norm: 2.9942 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9170 loss: 2.9170 2022/10/07 14:00:07 - mmengine - INFO - Epoch(train) [32][840/2119] lr: 4.0000e-02 eta: 23:44:25 time: 0.3104 data_time: 0.0217 memory: 5826 grad_norm: 3.0222 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8019 loss: 2.8019 2022/10/07 14:00:14 - mmengine - INFO - Epoch(train) [32][860/2119] lr: 4.0000e-02 eta: 23:44:21 time: 0.3810 data_time: 0.0208 memory: 5826 grad_norm: 3.0260 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9593 loss: 2.9593 2022/10/07 14:00:21 - mmengine - INFO - Epoch(train) [32][880/2119] lr: 4.0000e-02 eta: 23:44:13 time: 0.3298 data_time: 0.0251 memory: 5826 grad_norm: 3.0263 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8937 loss: 2.8937 2022/10/07 14:00:28 - mmengine - INFO - Epoch(train) [32][900/2119] lr: 4.0000e-02 eta: 23:44:08 time: 0.3587 data_time: 0.0244 memory: 5826 grad_norm: 2.9947 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6922 loss: 2.6922 2022/10/07 14:00:35 - mmengine - INFO - Epoch(train) [32][920/2119] lr: 4.0000e-02 eta: 23:44:01 time: 0.3367 data_time: 0.0244 memory: 5826 grad_norm: 2.9655 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9541 loss: 2.9541 2022/10/07 14:00:42 - mmengine - INFO - Epoch(train) [32][940/2119] lr: 4.0000e-02 eta: 23:43:54 time: 0.3363 data_time: 0.0229 memory: 5826 grad_norm: 3.0361 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9096 loss: 2.9096 2022/10/07 14:00:49 - mmengine - INFO - Epoch(train) [32][960/2119] lr: 4.0000e-02 eta: 23:43:48 time: 0.3488 data_time: 0.0235 memory: 5826 grad_norm: 3.0067 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7694 loss: 2.7694 2022/10/07 14:00:56 - mmengine - INFO - Epoch(train) [32][980/2119] lr: 4.0000e-02 eta: 23:43:43 time: 0.3691 data_time: 0.0235 memory: 5826 grad_norm: 2.9775 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0100 loss: 3.0100 2022/10/07 14:01:03 - mmengine - INFO - Epoch(train) [32][1000/2119] lr: 4.0000e-02 eta: 23:43:37 time: 0.3504 data_time: 0.0190 memory: 5826 grad_norm: 2.9835 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9970 loss: 2.9970 2022/10/07 14:01:10 - mmengine - INFO - Epoch(train) [32][1020/2119] lr: 4.0000e-02 eta: 23:43:29 time: 0.3229 data_time: 0.0170 memory: 5826 grad_norm: 3.0505 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7379 loss: 2.7379 2022/10/07 14:01:16 - mmengine - INFO - Epoch(train) [32][1040/2119] lr: 4.0000e-02 eta: 23:43:21 time: 0.3297 data_time: 0.0235 memory: 5826 grad_norm: 2.9924 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7385 loss: 2.7385 2022/10/07 14:01:23 - mmengine - INFO - Epoch(train) [32][1060/2119] lr: 4.0000e-02 eta: 23:43:16 time: 0.3585 data_time: 0.0296 memory: 5826 grad_norm: 3.0067 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7920 loss: 2.7920 2022/10/07 14:01:30 - mmengine - INFO - Epoch(train) [32][1080/2119] lr: 4.0000e-02 eta: 23:43:08 time: 0.3236 data_time: 0.0248 memory: 5826 grad_norm: 2.9982 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9649 loss: 2.9649 2022/10/07 14:01:38 - mmengine - INFO - Epoch(train) [32][1100/2119] lr: 4.0000e-02 eta: 23:43:05 time: 0.3982 data_time: 0.0254 memory: 5826 grad_norm: 3.0488 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8975 loss: 2.8975 2022/10/07 14:01:45 - mmengine - INFO - Epoch(train) [32][1120/2119] lr: 4.0000e-02 eta: 23:42:59 time: 0.3405 data_time: 0.0168 memory: 5826 grad_norm: 2.9605 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5459 loss: 2.5459 2022/10/07 14:01:52 - mmengine - INFO - Epoch(train) [32][1140/2119] lr: 4.0000e-02 eta: 23:42:52 time: 0.3480 data_time: 0.0195 memory: 5826 grad_norm: 3.0308 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8845 loss: 2.8845 2022/10/07 14:01:58 - mmengine - INFO - Epoch(train) [32][1160/2119] lr: 4.0000e-02 eta: 23:42:43 time: 0.3066 data_time: 0.0238 memory: 5826 grad_norm: 3.0249 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6505 loss: 2.6505 2022/10/07 14:02:05 - mmengine - INFO - Epoch(train) [32][1180/2119] lr: 4.0000e-02 eta: 23:42:37 time: 0.3496 data_time: 0.0250 memory: 5826 grad_norm: 3.0135 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7299 loss: 2.7299 2022/10/07 14:02:12 - mmengine - INFO - Epoch(train) [32][1200/2119] lr: 4.0000e-02 eta: 23:42:31 time: 0.3465 data_time: 0.0320 memory: 5826 grad_norm: 3.0000 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4773 loss: 2.4773 2022/10/07 14:02:18 - mmengine - INFO - Epoch(train) [32][1220/2119] lr: 4.0000e-02 eta: 23:42:23 time: 0.3281 data_time: 0.0169 memory: 5826 grad_norm: 2.9758 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6980 loss: 2.6980 2022/10/07 14:02:25 - mmengine - INFO - Epoch(train) [32][1240/2119] lr: 4.0000e-02 eta: 23:42:18 time: 0.3641 data_time: 0.0258 memory: 5826 grad_norm: 2.9852 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5924 loss: 2.5924 2022/10/07 14:02:32 - mmengine - INFO - Epoch(train) [32][1260/2119] lr: 4.0000e-02 eta: 23:42:09 time: 0.3081 data_time: 0.0204 memory: 5826 grad_norm: 2.9766 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7999 loss: 2.7999 2022/10/07 14:02:39 - mmengine - INFO - Epoch(train) [32][1280/2119] lr: 4.0000e-02 eta: 23:42:03 time: 0.3511 data_time: 0.0222 memory: 5826 grad_norm: 3.0372 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8802 loss: 2.8802 2022/10/07 14:02:45 - mmengine - INFO - Epoch(train) [32][1300/2119] lr: 4.0000e-02 eta: 23:41:55 time: 0.3255 data_time: 0.0205 memory: 5826 grad_norm: 3.0292 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9783 loss: 2.9783 2022/10/07 14:02:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 14:02:52 - mmengine - INFO - Epoch(train) [32][1320/2119] lr: 4.0000e-02 eta: 23:41:49 time: 0.3552 data_time: 0.0206 memory: 5826 grad_norm: 3.0285 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6363 loss: 2.6363 2022/10/07 14:02:59 - mmengine - INFO - Epoch(train) [32][1340/2119] lr: 4.0000e-02 eta: 23:41:41 time: 0.3270 data_time: 0.0206 memory: 5826 grad_norm: 3.0288 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6770 loss: 2.6770 2022/10/07 14:03:06 - mmengine - INFO - Epoch(train) [32][1360/2119] lr: 4.0000e-02 eta: 23:41:36 time: 0.3631 data_time: 0.0186 memory: 5826 grad_norm: 2.9691 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.5995 loss: 2.5995 2022/10/07 14:03:12 - mmengine - INFO - Epoch(train) [32][1380/2119] lr: 4.0000e-02 eta: 23:41:26 time: 0.2974 data_time: 0.0214 memory: 5826 grad_norm: 2.9671 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7749 loss: 2.7749 2022/10/07 14:03:19 - mmengine - INFO - Epoch(train) [32][1400/2119] lr: 4.0000e-02 eta: 23:41:22 time: 0.3745 data_time: 0.0238 memory: 5826 grad_norm: 3.0446 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6326 loss: 2.6326 2022/10/07 14:03:26 - mmengine - INFO - Epoch(train) [32][1420/2119] lr: 4.0000e-02 eta: 23:41:14 time: 0.3232 data_time: 0.0182 memory: 5826 grad_norm: 3.0249 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.9358 loss: 2.9358 2022/10/07 14:03:33 - mmengine - INFO - Epoch(train) [32][1440/2119] lr: 4.0000e-02 eta: 23:41:08 time: 0.3440 data_time: 0.0254 memory: 5826 grad_norm: 2.9932 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6458 loss: 2.6458 2022/10/07 14:03:40 - mmengine - INFO - Epoch(train) [32][1460/2119] lr: 4.0000e-02 eta: 23:41:03 time: 0.3660 data_time: 0.0199 memory: 5826 grad_norm: 3.0028 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6956 loss: 2.6956 2022/10/07 14:03:47 - mmengine - INFO - Epoch(train) [32][1480/2119] lr: 4.0000e-02 eta: 23:40:56 time: 0.3362 data_time: 0.0215 memory: 5826 grad_norm: 3.0082 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8897 loss: 2.8897 2022/10/07 14:03:54 - mmengine - INFO - Epoch(train) [32][1500/2119] lr: 4.0000e-02 eta: 23:40:51 time: 0.3682 data_time: 0.0206 memory: 5826 grad_norm: 2.9999 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8797 loss: 2.8797 2022/10/07 14:04:00 - mmengine - INFO - Epoch(train) [32][1520/2119] lr: 4.0000e-02 eta: 23:40:41 time: 0.2997 data_time: 0.0208 memory: 5826 grad_norm: 3.0226 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7058 loss: 2.7058 2022/10/07 14:04:08 - mmengine - INFO - Epoch(train) [32][1540/2119] lr: 4.0000e-02 eta: 23:40:37 time: 0.3774 data_time: 0.0292 memory: 5826 grad_norm: 2.9763 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7509 loss: 2.7509 2022/10/07 14:04:14 - mmengine - INFO - Epoch(train) [32][1560/2119] lr: 4.0000e-02 eta: 23:40:28 time: 0.3114 data_time: 0.0234 memory: 5826 grad_norm: 2.9933 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7871 loss: 2.7871 2022/10/07 14:04:21 - mmengine - INFO - Epoch(train) [32][1580/2119] lr: 4.0000e-02 eta: 23:40:22 time: 0.3533 data_time: 0.0206 memory: 5826 grad_norm: 3.0425 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7593 loss: 2.7593 2022/10/07 14:04:28 - mmengine - INFO - Epoch(train) [32][1600/2119] lr: 4.0000e-02 eta: 23:40:17 time: 0.3673 data_time: 0.0230 memory: 5826 grad_norm: 3.0041 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8707 loss: 2.8707 2022/10/07 14:04:35 - mmengine - INFO - Epoch(train) [32][1620/2119] lr: 4.0000e-02 eta: 23:40:10 time: 0.3248 data_time: 0.0235 memory: 5826 grad_norm: 2.9869 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8584 loss: 2.8584 2022/10/07 14:04:42 - mmengine - INFO - Epoch(train) [32][1640/2119] lr: 4.0000e-02 eta: 23:40:05 time: 0.3675 data_time: 0.0266 memory: 5826 grad_norm: 2.9323 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8601 loss: 2.8601 2022/10/07 14:04:49 - mmengine - INFO - Epoch(train) [32][1660/2119] lr: 4.0000e-02 eta: 23:39:59 time: 0.3492 data_time: 0.0215 memory: 5826 grad_norm: 3.0520 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7997 loss: 2.7997 2022/10/07 14:04:56 - mmengine - INFO - Epoch(train) [32][1680/2119] lr: 4.0000e-02 eta: 23:39:51 time: 0.3323 data_time: 0.0192 memory: 5826 grad_norm: 2.9933 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7329 loss: 2.7329 2022/10/07 14:05:03 - mmengine - INFO - Epoch(train) [32][1700/2119] lr: 4.0000e-02 eta: 23:39:44 time: 0.3369 data_time: 0.0195 memory: 5826 grad_norm: 2.9730 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7840 loss: 2.7840 2022/10/07 14:05:10 - mmengine - INFO - Epoch(train) [32][1720/2119] lr: 4.0000e-02 eta: 23:39:39 time: 0.3569 data_time: 0.0233 memory: 5826 grad_norm: 2.9628 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6867 loss: 2.6867 2022/10/07 14:05:16 - mmengine - INFO - Epoch(train) [32][1740/2119] lr: 4.0000e-02 eta: 23:39:30 time: 0.3123 data_time: 0.0237 memory: 5826 grad_norm: 2.9553 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.3557 loss: 2.3557 2022/10/07 14:05:23 - mmengine - INFO - Epoch(train) [32][1760/2119] lr: 4.0000e-02 eta: 23:39:25 time: 0.3606 data_time: 0.0237 memory: 5826 grad_norm: 3.0194 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.5583 loss: 2.5583 2022/10/07 14:05:30 - mmengine - INFO - Epoch(train) [32][1780/2119] lr: 4.0000e-02 eta: 23:39:18 time: 0.3369 data_time: 0.0257 memory: 5826 grad_norm: 2.9803 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8657 loss: 2.8657 2022/10/07 14:05:37 - mmengine - INFO - Epoch(train) [32][1800/2119] lr: 4.0000e-02 eta: 23:39:10 time: 0.3269 data_time: 0.0248 memory: 5826 grad_norm: 3.0340 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7757 loss: 2.7757 2022/10/07 14:05:44 - mmengine - INFO - Epoch(train) [32][1820/2119] lr: 4.0000e-02 eta: 23:39:04 time: 0.3554 data_time: 0.0214 memory: 5826 grad_norm: 2.9605 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0674 loss: 3.0674 2022/10/07 14:05:50 - mmengine - INFO - Epoch(train) [32][1840/2119] lr: 4.0000e-02 eta: 23:38:57 time: 0.3326 data_time: 0.0254 memory: 5826 grad_norm: 3.0180 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7508 loss: 2.7508 2022/10/07 14:05:58 - mmengine - INFO - Epoch(train) [32][1860/2119] lr: 4.0000e-02 eta: 23:38:55 time: 0.4062 data_time: 0.0210 memory: 5826 grad_norm: 3.0411 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7435 loss: 2.7435 2022/10/07 14:06:04 - mmengine - INFO - Epoch(train) [32][1880/2119] lr: 4.0000e-02 eta: 23:38:45 time: 0.3016 data_time: 0.0193 memory: 5826 grad_norm: 3.0434 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9160 loss: 2.9160 2022/10/07 14:06:12 - mmengine - INFO - Epoch(train) [32][1900/2119] lr: 4.0000e-02 eta: 23:38:41 time: 0.3761 data_time: 0.0227 memory: 5826 grad_norm: 3.0177 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7838 loss: 2.7838 2022/10/07 14:06:19 - mmengine - INFO - Epoch(train) [32][1920/2119] lr: 4.0000e-02 eta: 23:38:33 time: 0.3259 data_time: 0.0193 memory: 5826 grad_norm: 2.9600 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7434 loss: 2.7434 2022/10/07 14:06:25 - mmengine - INFO - Epoch(train) [32][1940/2119] lr: 4.0000e-02 eta: 23:38:26 time: 0.3382 data_time: 0.0192 memory: 5826 grad_norm: 2.9697 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7923 loss: 2.7923 2022/10/07 14:06:31 - mmengine - INFO - Epoch(train) [32][1960/2119] lr: 4.0000e-02 eta: 23:38:17 time: 0.3043 data_time: 0.0216 memory: 5826 grad_norm: 3.0080 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6776 loss: 2.6776 2022/10/07 14:06:39 - mmengine - INFO - Epoch(train) [32][1980/2119] lr: 4.0000e-02 eta: 23:38:11 time: 0.3597 data_time: 0.0199 memory: 5826 grad_norm: 3.0012 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8646 loss: 2.8646 2022/10/07 14:06:45 - mmengine - INFO - Epoch(train) [32][2000/2119] lr: 4.0000e-02 eta: 23:38:04 time: 0.3376 data_time: 0.0217 memory: 5826 grad_norm: 3.0324 top1_acc: 0.1250 top5_acc: 0.1875 loss_cls: 3.0704 loss: 3.0704 2022/10/07 14:06:53 - mmengine - INFO - Epoch(train) [32][2020/2119] lr: 4.0000e-02 eta: 23:37:59 time: 0.3649 data_time: 0.0206 memory: 5826 grad_norm: 3.0120 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5608 loss: 2.5608 2022/10/07 14:06:59 - mmengine - INFO - Epoch(train) [32][2040/2119] lr: 4.0000e-02 eta: 23:37:52 time: 0.3363 data_time: 0.0225 memory: 5826 grad_norm: 2.9311 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8852 loss: 2.8852 2022/10/07 14:07:06 - mmengine - INFO - Epoch(train) [32][2060/2119] lr: 4.0000e-02 eta: 23:37:46 time: 0.3495 data_time: 0.0202 memory: 5826 grad_norm: 2.9603 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8059 loss: 2.8059 2022/10/07 14:07:13 - mmengine - INFO - Epoch(train) [32][2080/2119] lr: 4.0000e-02 eta: 23:37:38 time: 0.3232 data_time: 0.0186 memory: 5826 grad_norm: 3.0127 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8859 loss: 2.8859 2022/10/07 14:07:20 - mmengine - INFO - Epoch(train) [32][2100/2119] lr: 4.0000e-02 eta: 23:37:32 time: 0.3450 data_time: 0.0342 memory: 5826 grad_norm: 2.9587 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6791 loss: 2.6791 2022/10/07 14:07:25 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 14:07:25 - mmengine - INFO - Epoch(train) [32][2119/2119] lr: 4.0000e-02 eta: 23:37:32 time: 0.2917 data_time: 0.0175 memory: 5826 grad_norm: 3.0511 top1_acc: 0.3000 top5_acc: 0.7000 loss_cls: 2.5953 loss: 2.5953 2022/10/07 14:07:25 - mmengine - INFO - Saving checkpoint at 32 epochs 2022/10/07 14:07:36 - mmengine - INFO - Epoch(train) [33][20/2119] lr: 4.0000e-02 eta: 23:37:01 time: 0.4232 data_time: 0.2017 memory: 5826 grad_norm: 3.0279 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6609 loss: 2.6609 2022/10/07 14:07:42 - mmengine - INFO - Epoch(train) [33][40/2119] lr: 4.0000e-02 eta: 23:36:51 time: 0.2993 data_time: 0.0716 memory: 5826 grad_norm: 3.0679 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6984 loss: 2.6984 2022/10/07 14:07:49 - mmengine - INFO - Epoch(train) [33][60/2119] lr: 4.0000e-02 eta: 23:36:48 time: 0.3859 data_time: 0.1024 memory: 5826 grad_norm: 3.0204 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9552 loss: 2.9552 2022/10/07 14:07:55 - mmengine - INFO - Epoch(train) [33][80/2119] lr: 4.0000e-02 eta: 23:36:38 time: 0.3033 data_time: 0.0208 memory: 5826 grad_norm: 3.0497 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6586 loss: 2.6586 2022/10/07 14:08:02 - mmengine - INFO - Epoch(train) [33][100/2119] lr: 4.0000e-02 eta: 23:36:32 time: 0.3464 data_time: 0.0166 memory: 5826 grad_norm: 3.0256 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.8036 loss: 2.8036 2022/10/07 14:08:09 - mmengine - INFO - Epoch(train) [33][120/2119] lr: 4.0000e-02 eta: 23:36:25 time: 0.3432 data_time: 0.0189 memory: 5826 grad_norm: 3.0306 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 2.5799 loss: 2.5799 2022/10/07 14:08:16 - mmengine - INFO - Epoch(train) [33][140/2119] lr: 4.0000e-02 eta: 23:36:20 time: 0.3583 data_time: 0.0280 memory: 5826 grad_norm: 2.9869 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4763 loss: 2.4763 2022/10/07 14:08:22 - mmengine - INFO - Epoch(train) [33][160/2119] lr: 4.0000e-02 eta: 23:36:10 time: 0.2959 data_time: 0.0239 memory: 5826 grad_norm: 2.9993 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5727 loss: 2.5727 2022/10/07 14:08:30 - mmengine - INFO - Epoch(train) [33][180/2119] lr: 4.0000e-02 eta: 23:36:05 time: 0.3734 data_time: 0.0197 memory: 5826 grad_norm: 2.9966 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7726 loss: 2.7726 2022/10/07 14:08:33 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 14:08:36 - mmengine - INFO - Epoch(train) [33][200/2119] lr: 4.0000e-02 eta: 23:35:56 time: 0.3004 data_time: 0.0232 memory: 5826 grad_norm: 2.9834 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.9215 loss: 2.9215 2022/10/07 14:08:44 - mmengine - INFO - Epoch(train) [33][220/2119] lr: 4.0000e-02 eta: 23:35:53 time: 0.3914 data_time: 0.0220 memory: 5826 grad_norm: 3.0009 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8300 loss: 2.8300 2022/10/07 14:08:50 - mmengine - INFO - Epoch(train) [33][240/2119] lr: 4.0000e-02 eta: 23:35:44 time: 0.3148 data_time: 0.0238 memory: 5826 grad_norm: 3.0345 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7126 loss: 2.7126 2022/10/07 14:08:58 - mmengine - INFO - Epoch(train) [33][260/2119] lr: 4.0000e-02 eta: 23:35:42 time: 0.4102 data_time: 0.0184 memory: 5826 grad_norm: 3.0346 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.8083 loss: 2.8083 2022/10/07 14:09:05 - mmengine - INFO - Epoch(train) [33][280/2119] lr: 4.0000e-02 eta: 23:35:35 time: 0.3333 data_time: 0.0173 memory: 5826 grad_norm: 2.9353 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4646 loss: 2.4646 2022/10/07 14:09:12 - mmengine - INFO - Epoch(train) [33][300/2119] lr: 4.0000e-02 eta: 23:35:29 time: 0.3532 data_time: 0.0213 memory: 5826 grad_norm: 3.0224 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8407 loss: 2.8407 2022/10/07 14:09:19 - mmengine - INFO - Epoch(train) [33][320/2119] lr: 4.0000e-02 eta: 23:35:24 time: 0.3621 data_time: 0.0220 memory: 5826 grad_norm: 3.0300 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6836 loss: 2.6836 2022/10/07 14:09:26 - mmengine - INFO - Epoch(train) [33][340/2119] lr: 4.0000e-02 eta: 23:35:18 time: 0.3581 data_time: 0.0204 memory: 5826 grad_norm: 3.0268 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7407 loss: 2.7407 2022/10/07 14:09:32 - mmengine - INFO - Epoch(train) [33][360/2119] lr: 4.0000e-02 eta: 23:35:09 time: 0.2986 data_time: 0.0196 memory: 5826 grad_norm: 2.9746 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8488 loss: 2.8488 2022/10/07 14:09:39 - mmengine - INFO - Epoch(train) [33][380/2119] lr: 4.0000e-02 eta: 23:35:02 time: 0.3480 data_time: 0.0201 memory: 5826 grad_norm: 3.0438 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9870 loss: 2.9870 2022/10/07 14:09:45 - mmengine - INFO - Epoch(train) [33][400/2119] lr: 4.0000e-02 eta: 23:34:53 time: 0.3115 data_time: 0.0235 memory: 5826 grad_norm: 3.0163 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5803 loss: 2.5803 2022/10/07 14:09:53 - mmengine - INFO - Epoch(train) [33][420/2119] lr: 4.0000e-02 eta: 23:34:51 time: 0.3991 data_time: 0.0162 memory: 5826 grad_norm: 3.0119 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6191 loss: 2.6191 2022/10/07 14:10:00 - mmengine - INFO - Epoch(train) [33][440/2119] lr: 4.0000e-02 eta: 23:34:44 time: 0.3429 data_time: 0.0275 memory: 5826 grad_norm: 3.0034 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8546 loss: 2.8546 2022/10/07 14:10:08 - mmengine - INFO - Epoch(train) [33][460/2119] lr: 4.0000e-02 eta: 23:34:40 time: 0.3676 data_time: 0.0190 memory: 5826 grad_norm: 3.0160 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9080 loss: 2.9080 2022/10/07 14:10:14 - mmengine - INFO - Epoch(train) [33][480/2119] lr: 4.0000e-02 eta: 23:34:33 time: 0.3388 data_time: 0.0234 memory: 5826 grad_norm: 3.0412 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9298 loss: 2.9298 2022/10/07 14:10:22 - mmengine - INFO - Epoch(train) [33][500/2119] lr: 4.0000e-02 eta: 23:34:28 time: 0.3752 data_time: 0.0300 memory: 5826 grad_norm: 3.0195 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.7599 loss: 2.7599 2022/10/07 14:10:29 - mmengine - INFO - Epoch(train) [33][520/2119] lr: 4.0000e-02 eta: 23:34:22 time: 0.3468 data_time: 0.0233 memory: 5826 grad_norm: 3.0130 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6521 loss: 2.6521 2022/10/07 14:10:36 - mmengine - INFO - Epoch(train) [33][540/2119] lr: 4.0000e-02 eta: 23:34:18 time: 0.3738 data_time: 0.0245 memory: 5826 grad_norm: 3.0233 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6383 loss: 2.6383 2022/10/07 14:10:43 - mmengine - INFO - Epoch(train) [33][560/2119] lr: 4.0000e-02 eta: 23:34:11 time: 0.3357 data_time: 0.0203 memory: 5826 grad_norm: 3.0088 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8616 loss: 2.8616 2022/10/07 14:10:50 - mmengine - INFO - Epoch(train) [33][580/2119] lr: 4.0000e-02 eta: 23:34:05 time: 0.3509 data_time: 0.0191 memory: 5826 grad_norm: 3.0314 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.8821 loss: 2.8821 2022/10/07 14:10:57 - mmengine - INFO - Epoch(train) [33][600/2119] lr: 4.0000e-02 eta: 23:33:59 time: 0.3596 data_time: 0.0233 memory: 5826 grad_norm: 3.0279 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8001 loss: 2.8001 2022/10/07 14:11:04 - mmengine - INFO - Epoch(train) [33][620/2119] lr: 4.0000e-02 eta: 23:33:53 time: 0.3505 data_time: 0.0192 memory: 5826 grad_norm: 3.0299 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8970 loss: 2.8970 2022/10/07 14:11:11 - mmengine - INFO - Epoch(train) [33][640/2119] lr: 4.0000e-02 eta: 23:33:45 time: 0.3238 data_time: 0.0208 memory: 5826 grad_norm: 3.0405 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8929 loss: 2.8929 2022/10/07 14:11:17 - mmengine - INFO - Epoch(train) [33][660/2119] lr: 4.0000e-02 eta: 23:33:36 time: 0.3116 data_time: 0.0222 memory: 5826 grad_norm: 3.0531 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6827 loss: 2.6827 2022/10/07 14:11:24 - mmengine - INFO - Epoch(train) [33][680/2119] lr: 4.0000e-02 eta: 23:33:30 time: 0.3438 data_time: 0.0239 memory: 5826 grad_norm: 3.0054 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7847 loss: 2.7847 2022/10/07 14:11:31 - mmengine - INFO - Epoch(train) [33][700/2119] lr: 4.0000e-02 eta: 23:33:24 time: 0.3481 data_time: 0.0188 memory: 5826 grad_norm: 3.0349 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7235 loss: 2.7235 2022/10/07 14:11:37 - mmengine - INFO - Epoch(train) [33][720/2119] lr: 4.0000e-02 eta: 23:33:16 time: 0.3308 data_time: 0.0210 memory: 5826 grad_norm: 3.0146 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6260 loss: 2.6260 2022/10/07 14:11:44 - mmengine - INFO - Epoch(train) [33][740/2119] lr: 4.0000e-02 eta: 23:33:09 time: 0.3345 data_time: 0.0243 memory: 5826 grad_norm: 3.0748 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8927 loss: 2.8927 2022/10/07 14:11:50 - mmengine - INFO - Epoch(train) [33][760/2119] lr: 4.0000e-02 eta: 23:32:58 time: 0.2821 data_time: 0.0242 memory: 5826 grad_norm: 2.9925 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.7669 loss: 2.7669 2022/10/07 14:11:57 - mmengine - INFO - Epoch(train) [33][780/2119] lr: 4.0000e-02 eta: 23:32:53 time: 0.3711 data_time: 0.0254 memory: 5826 grad_norm: 3.0167 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5518 loss: 2.5518 2022/10/07 14:12:04 - mmengine - INFO - Epoch(train) [33][800/2119] lr: 4.0000e-02 eta: 23:32:46 time: 0.3354 data_time: 0.0203 memory: 5826 grad_norm: 2.9978 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8614 loss: 2.8614 2022/10/07 14:12:10 - mmengine - INFO - Epoch(train) [33][820/2119] lr: 4.0000e-02 eta: 23:32:38 time: 0.3199 data_time: 0.0285 memory: 5826 grad_norm: 3.0095 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7259 loss: 2.7259 2022/10/07 14:12:18 - mmengine - INFO - Epoch(train) [33][840/2119] lr: 4.0000e-02 eta: 23:32:34 time: 0.3784 data_time: 0.0271 memory: 5826 grad_norm: 3.0377 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7982 loss: 2.7982 2022/10/07 14:12:25 - mmengine - INFO - Epoch(train) [33][860/2119] lr: 4.0000e-02 eta: 23:32:27 time: 0.3385 data_time: 0.0165 memory: 5826 grad_norm: 3.0721 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6234 loss: 2.6234 2022/10/07 14:12:32 - mmengine - INFO - Epoch(train) [33][880/2119] lr: 4.0000e-02 eta: 23:32:21 time: 0.3528 data_time: 0.0205 memory: 5826 grad_norm: 3.0521 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6293 loss: 2.6293 2022/10/07 14:12:39 - mmengine - INFO - Epoch(train) [33][900/2119] lr: 4.0000e-02 eta: 23:32:15 time: 0.3530 data_time: 0.0251 memory: 5826 grad_norm: 3.0169 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7322 loss: 2.7322 2022/10/07 14:12:46 - mmengine - INFO - Epoch(train) [33][920/2119] lr: 4.0000e-02 eta: 23:32:10 time: 0.3553 data_time: 0.0195 memory: 5826 grad_norm: 3.0888 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6766 loss: 2.6766 2022/10/07 14:12:52 - mmengine - INFO - Epoch(train) [33][940/2119] lr: 4.0000e-02 eta: 23:32:00 time: 0.3034 data_time: 0.0215 memory: 5826 grad_norm: 3.0267 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6881 loss: 2.6881 2022/10/07 14:12:59 - mmengine - INFO - Epoch(train) [33][960/2119] lr: 4.0000e-02 eta: 23:31:54 time: 0.3506 data_time: 0.0272 memory: 5826 grad_norm: 3.0296 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6133 loss: 2.6133 2022/10/07 14:13:06 - mmengine - INFO - Epoch(train) [33][980/2119] lr: 4.0000e-02 eta: 23:31:50 time: 0.3710 data_time: 0.0224 memory: 5826 grad_norm: 2.9830 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8592 loss: 2.8592 2022/10/07 14:13:13 - mmengine - INFO - Epoch(train) [33][1000/2119] lr: 4.0000e-02 eta: 23:31:41 time: 0.3135 data_time: 0.0226 memory: 5826 grad_norm: 3.0696 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6686 loss: 2.6686 2022/10/07 14:13:20 - mmengine - INFO - Epoch(train) [33][1020/2119] lr: 4.0000e-02 eta: 23:31:36 time: 0.3736 data_time: 0.0246 memory: 5826 grad_norm: 3.0015 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8843 loss: 2.8843 2022/10/07 14:13:27 - mmengine - INFO - Epoch(train) [33][1040/2119] lr: 4.0000e-02 eta: 23:31:30 time: 0.3485 data_time: 0.0230 memory: 5826 grad_norm: 3.0189 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7928 loss: 2.7928 2022/10/07 14:13:34 - mmengine - INFO - Epoch(train) [33][1060/2119] lr: 4.0000e-02 eta: 23:31:24 time: 0.3513 data_time: 0.0182 memory: 5826 grad_norm: 3.0428 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7717 loss: 2.7717 2022/10/07 14:13:40 - mmengine - INFO - Epoch(train) [33][1080/2119] lr: 4.0000e-02 eta: 23:31:16 time: 0.3184 data_time: 0.0224 memory: 5826 grad_norm: 3.0149 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7298 loss: 2.7298 2022/10/07 14:13:48 - mmengine - INFO - Epoch(train) [33][1100/2119] lr: 4.0000e-02 eta: 23:31:13 time: 0.3943 data_time: 0.0233 memory: 5826 grad_norm: 3.0229 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7293 loss: 2.7293 2022/10/07 14:13:55 - mmengine - INFO - Epoch(train) [33][1120/2119] lr: 4.0000e-02 eta: 23:31:05 time: 0.3244 data_time: 0.0213 memory: 5826 grad_norm: 3.0715 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9262 loss: 2.9262 2022/10/07 14:14:02 - mmengine - INFO - Epoch(train) [33][1140/2119] lr: 4.0000e-02 eta: 23:30:58 time: 0.3404 data_time: 0.0204 memory: 5826 grad_norm: 3.0057 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6588 loss: 2.6588 2022/10/07 14:14:08 - mmengine - INFO - Epoch(train) [33][1160/2119] lr: 4.0000e-02 eta: 23:30:49 time: 0.3058 data_time: 0.0235 memory: 5826 grad_norm: 2.9892 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8697 loss: 2.8697 2022/10/07 14:14:14 - mmengine - INFO - Epoch(train) [33][1180/2119] lr: 4.0000e-02 eta: 23:30:41 time: 0.3305 data_time: 0.0252 memory: 5826 grad_norm: 2.9998 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8191 loss: 2.8191 2022/10/07 14:14:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 14:14:21 - mmengine - INFO - Epoch(train) [33][1200/2119] lr: 4.0000e-02 eta: 23:30:35 time: 0.3441 data_time: 0.0254 memory: 5826 grad_norm: 3.0263 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6424 loss: 2.6424 2022/10/07 14:14:29 - mmengine - INFO - Epoch(train) [33][1220/2119] lr: 4.0000e-02 eta: 23:30:30 time: 0.3634 data_time: 0.0235 memory: 5826 grad_norm: 3.0280 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8123 loss: 2.8123 2022/10/07 14:14:35 - mmengine - INFO - Epoch(train) [33][1240/2119] lr: 4.0000e-02 eta: 23:30:22 time: 0.3257 data_time: 0.0221 memory: 5826 grad_norm: 3.0078 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7674 loss: 2.7674 2022/10/07 14:14:43 - mmengine - INFO - Epoch(train) [33][1260/2119] lr: 4.0000e-02 eta: 23:30:18 time: 0.3744 data_time: 0.0199 memory: 5826 grad_norm: 3.0083 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8011 loss: 2.8011 2022/10/07 14:14:49 - mmengine - INFO - Epoch(train) [33][1280/2119] lr: 4.0000e-02 eta: 23:30:10 time: 0.3273 data_time: 0.0205 memory: 5826 grad_norm: 2.9936 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7696 loss: 2.7696 2022/10/07 14:14:56 - mmengine - INFO - Epoch(train) [33][1300/2119] lr: 4.0000e-02 eta: 23:30:05 time: 0.3698 data_time: 0.0204 memory: 5826 grad_norm: 3.0054 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8542 loss: 2.8542 2022/10/07 14:15:03 - mmengine - INFO - Epoch(train) [33][1320/2119] lr: 4.0000e-02 eta: 23:29:56 time: 0.3119 data_time: 0.0205 memory: 5826 grad_norm: 3.0310 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8276 loss: 2.8276 2022/10/07 14:15:10 - mmengine - INFO - Epoch(train) [33][1340/2119] lr: 4.0000e-02 eta: 23:29:51 time: 0.3535 data_time: 0.0233 memory: 5826 grad_norm: 2.9910 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7711 loss: 2.7711 2022/10/07 14:15:16 - mmengine - INFO - Epoch(train) [33][1360/2119] lr: 4.0000e-02 eta: 23:29:43 time: 0.3331 data_time: 0.0192 memory: 5826 grad_norm: 3.0085 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.6133 loss: 2.6133 2022/10/07 14:15:24 - mmengine - INFO - Epoch(train) [33][1380/2119] lr: 4.0000e-02 eta: 23:29:39 time: 0.3705 data_time: 0.0209 memory: 5826 grad_norm: 3.1192 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9223 loss: 2.9223 2022/10/07 14:15:31 - mmengine - INFO - Epoch(train) [33][1400/2119] lr: 4.0000e-02 eta: 23:29:34 time: 0.3656 data_time: 0.0234 memory: 5826 grad_norm: 3.0226 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8573 loss: 2.8573 2022/10/07 14:15:38 - mmengine - INFO - Epoch(train) [33][1420/2119] lr: 4.0000e-02 eta: 23:29:27 time: 0.3410 data_time: 0.0175 memory: 5826 grad_norm: 3.0190 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6662 loss: 2.6662 2022/10/07 14:15:44 - mmengine - INFO - Epoch(train) [33][1440/2119] lr: 4.0000e-02 eta: 23:29:16 time: 0.2866 data_time: 0.0250 memory: 5826 grad_norm: 3.0239 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.0097 loss: 3.0097 2022/10/07 14:15:52 - mmengine - INFO - Epoch(train) [33][1460/2119] lr: 4.0000e-02 eta: 23:29:16 time: 0.4320 data_time: 0.0181 memory: 5826 grad_norm: 2.9703 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.9654 loss: 2.9654 2022/10/07 14:15:59 - mmengine - INFO - Epoch(train) [33][1480/2119] lr: 4.0000e-02 eta: 23:29:09 time: 0.3308 data_time: 0.0191 memory: 5826 grad_norm: 3.0089 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6732 loss: 2.6732 2022/10/07 14:16:06 - mmengine - INFO - Epoch(train) [33][1500/2119] lr: 4.0000e-02 eta: 23:29:02 time: 0.3486 data_time: 0.0188 memory: 5826 grad_norm: 2.9805 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5293 loss: 2.5293 2022/10/07 14:16:13 - mmengine - INFO - Epoch(train) [33][1520/2119] lr: 4.0000e-02 eta: 23:28:58 time: 0.3675 data_time: 0.0202 memory: 5826 grad_norm: 3.0046 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7757 loss: 2.7757 2022/10/07 14:16:21 - mmengine - INFO - Epoch(train) [33][1540/2119] lr: 4.0000e-02 eta: 23:28:53 time: 0.3761 data_time: 0.0161 memory: 5826 grad_norm: 3.0605 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6601 loss: 2.6601 2022/10/07 14:16:27 - mmengine - INFO - Epoch(train) [33][1560/2119] lr: 4.0000e-02 eta: 23:28:45 time: 0.3132 data_time: 0.0253 memory: 5826 grad_norm: 3.0209 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7843 loss: 2.7843 2022/10/07 14:16:34 - mmengine - INFO - Epoch(train) [33][1580/2119] lr: 4.0000e-02 eta: 23:28:39 time: 0.3619 data_time: 0.0182 memory: 5826 grad_norm: 2.9947 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9476 loss: 2.9476 2022/10/07 14:16:41 - mmengine - INFO - Epoch(train) [33][1600/2119] lr: 4.0000e-02 eta: 23:28:31 time: 0.3235 data_time: 0.0228 memory: 5826 grad_norm: 3.0019 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7617 loss: 2.7617 2022/10/07 14:16:47 - mmengine - INFO - Epoch(train) [33][1620/2119] lr: 4.0000e-02 eta: 23:28:23 time: 0.3136 data_time: 0.0190 memory: 5826 grad_norm: 2.9999 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6724 loss: 2.6724 2022/10/07 14:16:54 - mmengine - INFO - Epoch(train) [33][1640/2119] lr: 4.0000e-02 eta: 23:28:16 time: 0.3457 data_time: 0.0236 memory: 5826 grad_norm: 2.9874 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6953 loss: 2.6953 2022/10/07 14:17:01 - mmengine - INFO - Epoch(train) [33][1660/2119] lr: 4.0000e-02 eta: 23:28:11 time: 0.3607 data_time: 0.0241 memory: 5826 grad_norm: 3.0420 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7707 loss: 2.7707 2022/10/07 14:17:07 - mmengine - INFO - Epoch(train) [33][1680/2119] lr: 4.0000e-02 eta: 23:28:01 time: 0.2957 data_time: 0.0226 memory: 5826 grad_norm: 3.0057 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4818 loss: 2.4818 2022/10/07 14:17:14 - mmengine - INFO - Epoch(train) [33][1700/2119] lr: 4.0000e-02 eta: 23:27:55 time: 0.3591 data_time: 0.0198 memory: 5826 grad_norm: 3.0201 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6676 loss: 2.6676 2022/10/07 14:17:21 - mmengine - INFO - Epoch(train) [33][1720/2119] lr: 4.0000e-02 eta: 23:27:49 time: 0.3405 data_time: 0.0225 memory: 5826 grad_norm: 2.9902 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7323 loss: 2.7323 2022/10/07 14:17:28 - mmengine - INFO - Epoch(train) [33][1740/2119] lr: 4.0000e-02 eta: 23:27:41 time: 0.3284 data_time: 0.0171 memory: 5826 grad_norm: 2.9854 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7777 loss: 2.7777 2022/10/07 14:17:34 - mmengine - INFO - Epoch(train) [33][1760/2119] lr: 4.0000e-02 eta: 23:27:34 time: 0.3378 data_time: 0.0234 memory: 5826 grad_norm: 3.0507 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5761 loss: 2.5761 2022/10/07 14:17:42 - mmengine - INFO - Epoch(train) [33][1780/2119] lr: 4.0000e-02 eta: 23:27:31 time: 0.3918 data_time: 0.0167 memory: 5826 grad_norm: 3.0282 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9120 loss: 2.9120 2022/10/07 14:17:48 - mmengine - INFO - Epoch(train) [33][1800/2119] lr: 4.0000e-02 eta: 23:27:22 time: 0.3039 data_time: 0.0216 memory: 5826 grad_norm: 3.0478 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8125 loss: 2.8125 2022/10/07 14:17:55 - mmengine - INFO - Epoch(train) [33][1820/2119] lr: 4.0000e-02 eta: 23:27:16 time: 0.3554 data_time: 0.0245 memory: 5826 grad_norm: 3.0200 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6457 loss: 2.6457 2022/10/07 14:18:02 - mmengine - INFO - Epoch(train) [33][1840/2119] lr: 4.0000e-02 eta: 23:27:09 time: 0.3336 data_time: 0.0191 memory: 5826 grad_norm: 3.0219 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6614 loss: 2.6614 2022/10/07 14:18:09 - mmengine - INFO - Epoch(train) [33][1860/2119] lr: 4.0000e-02 eta: 23:27:03 time: 0.3526 data_time: 0.0219 memory: 5826 grad_norm: 3.0295 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8205 loss: 2.8205 2022/10/07 14:18:15 - mmengine - INFO - Epoch(train) [33][1880/2119] lr: 4.0000e-02 eta: 23:26:53 time: 0.2990 data_time: 0.0199 memory: 5826 grad_norm: 3.0415 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6700 loss: 2.6700 2022/10/07 14:18:22 - mmengine - INFO - Epoch(train) [33][1900/2119] lr: 4.0000e-02 eta: 23:26:45 time: 0.3250 data_time: 0.0183 memory: 5826 grad_norm: 3.0054 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0387 loss: 3.0387 2022/10/07 14:18:28 - mmengine - INFO - Epoch(train) [33][1920/2119] lr: 4.0000e-02 eta: 23:26:37 time: 0.3272 data_time: 0.0234 memory: 5826 grad_norm: 3.0501 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6649 loss: 2.6649 2022/10/07 14:18:36 - mmengine - INFO - Epoch(train) [33][1940/2119] lr: 4.0000e-02 eta: 23:26:33 time: 0.3803 data_time: 0.0162 memory: 5826 grad_norm: 3.0300 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8230 loss: 2.8230 2022/10/07 14:18:42 - mmengine - INFO - Epoch(train) [33][1960/2119] lr: 4.0000e-02 eta: 23:26:25 time: 0.3201 data_time: 0.0208 memory: 5826 grad_norm: 2.9654 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6266 loss: 2.6266 2022/10/07 14:18:49 - mmengine - INFO - Epoch(train) [33][1980/2119] lr: 4.0000e-02 eta: 23:26:18 time: 0.3363 data_time: 0.0212 memory: 5826 grad_norm: 3.0636 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6812 loss: 2.6812 2022/10/07 14:18:55 - mmengine - INFO - Epoch(train) [33][2000/2119] lr: 4.0000e-02 eta: 23:26:10 time: 0.3160 data_time: 0.0237 memory: 5826 grad_norm: 2.9478 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7922 loss: 2.7922 2022/10/07 14:19:03 - mmengine - INFO - Epoch(train) [33][2020/2119] lr: 4.0000e-02 eta: 23:26:06 time: 0.3833 data_time: 0.0214 memory: 5826 grad_norm: 2.9593 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5979 loss: 2.5979 2022/10/07 14:19:10 - mmengine - INFO - Epoch(train) [33][2040/2119] lr: 4.0000e-02 eta: 23:26:00 time: 0.3522 data_time: 0.0214 memory: 5826 grad_norm: 3.0412 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8419 loss: 2.8419 2022/10/07 14:19:17 - mmengine - INFO - Epoch(train) [33][2060/2119] lr: 4.0000e-02 eta: 23:25:53 time: 0.3463 data_time: 0.0178 memory: 5826 grad_norm: 3.0142 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6911 loss: 2.6911 2022/10/07 14:19:24 - mmengine - INFO - Epoch(train) [33][2080/2119] lr: 4.0000e-02 eta: 23:25:46 time: 0.3358 data_time: 0.0203 memory: 5826 grad_norm: 3.0186 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9813 loss: 2.9813 2022/10/07 14:19:31 - mmengine - INFO - Epoch(train) [33][2100/2119] lr: 4.0000e-02 eta: 23:25:40 time: 0.3471 data_time: 0.0171 memory: 5826 grad_norm: 2.9535 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0263 loss: 3.0263 2022/10/07 14:19:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 14:19:36 - mmengine - INFO - Epoch(train) [33][2119/2119] lr: 4.0000e-02 eta: 23:25:40 time: 0.2865 data_time: 0.0162 memory: 5826 grad_norm: 2.9849 top1_acc: 0.5000 top5_acc: 0.6000 loss_cls: 2.7956 loss: 2.7956 2022/10/07 14:19:46 - mmengine - INFO - Epoch(train) [34][20/2119] lr: 4.0000e-02 eta: 23:25:14 time: 0.4808 data_time: 0.1348 memory: 5826 grad_norm: 3.0290 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.6759 loss: 2.6759 2022/10/07 14:19:52 - mmengine - INFO - Epoch(train) [34][40/2119] lr: 4.0000e-02 eta: 23:25:05 time: 0.3042 data_time: 0.0230 memory: 5826 grad_norm: 3.0005 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7396 loss: 2.7396 2022/10/07 14:19:59 - mmengine - INFO - Epoch(train) [34][60/2119] lr: 4.0000e-02 eta: 23:24:59 time: 0.3606 data_time: 0.0239 memory: 5826 grad_norm: 2.9686 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5718 loss: 2.5718 2022/10/07 14:20:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 14:20:06 - mmengine - INFO - Epoch(train) [34][80/2119] lr: 4.0000e-02 eta: 23:24:51 time: 0.3253 data_time: 0.0222 memory: 5826 grad_norm: 3.0200 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.7230 loss: 2.7230 2022/10/07 14:20:14 - mmengine - INFO - Epoch(train) [34][100/2119] lr: 4.0000e-02 eta: 23:24:49 time: 0.4027 data_time: 0.0176 memory: 5826 grad_norm: 3.0719 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6147 loss: 2.6147 2022/10/07 14:20:20 - mmengine - INFO - Epoch(train) [34][120/2119] lr: 4.0000e-02 eta: 23:24:39 time: 0.2991 data_time: 0.0168 memory: 5826 grad_norm: 2.9656 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8062 loss: 2.8062 2022/10/07 14:20:27 - mmengine - INFO - Epoch(train) [34][140/2119] lr: 4.0000e-02 eta: 23:24:35 time: 0.3767 data_time: 0.0255 memory: 5826 grad_norm: 3.0047 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6740 loss: 2.6740 2022/10/07 14:20:34 - mmengine - INFO - Epoch(train) [34][160/2119] lr: 4.0000e-02 eta: 23:24:28 time: 0.3361 data_time: 0.0216 memory: 5826 grad_norm: 3.0385 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7834 loss: 2.7834 2022/10/07 14:20:41 - mmengine - INFO - Epoch(train) [34][180/2119] lr: 4.0000e-02 eta: 23:24:23 time: 0.3647 data_time: 0.0252 memory: 5826 grad_norm: 3.0479 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7270 loss: 2.7270 2022/10/07 14:20:47 - mmengine - INFO - Epoch(train) [34][200/2119] lr: 4.0000e-02 eta: 23:24:14 time: 0.3066 data_time: 0.0259 memory: 5826 grad_norm: 2.9490 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7937 loss: 2.7937 2022/10/07 14:20:54 - mmengine - INFO - Epoch(train) [34][220/2119] lr: 4.0000e-02 eta: 23:24:08 time: 0.3511 data_time: 0.0191 memory: 5826 grad_norm: 2.9937 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6659 loss: 2.6659 2022/10/07 14:21:02 - mmengine - INFO - Epoch(train) [34][240/2119] lr: 4.0000e-02 eta: 23:24:02 time: 0.3631 data_time: 0.0179 memory: 5826 grad_norm: 3.0180 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5386 loss: 2.5386 2022/10/07 14:21:08 - mmengine - INFO - Epoch(train) [34][260/2119] lr: 4.0000e-02 eta: 23:23:56 time: 0.3400 data_time: 0.0192 memory: 5826 grad_norm: 3.0014 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6638 loss: 2.6638 2022/10/07 14:21:15 - mmengine - INFO - Epoch(train) [34][280/2119] lr: 4.0000e-02 eta: 23:23:46 time: 0.3044 data_time: 0.0274 memory: 5826 grad_norm: 2.9941 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.5497 loss: 2.5497 2022/10/07 14:21:21 - mmengine - INFO - Epoch(train) [34][300/2119] lr: 4.0000e-02 eta: 23:23:40 time: 0.3423 data_time: 0.0184 memory: 5826 grad_norm: 3.0275 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0027 loss: 3.0027 2022/10/07 14:21:29 - mmengine - INFO - Epoch(train) [34][320/2119] lr: 4.0000e-02 eta: 23:23:35 time: 0.3732 data_time: 0.0232 memory: 5826 grad_norm: 3.0012 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8189 loss: 2.8189 2022/10/07 14:21:35 - mmengine - INFO - Epoch(train) [34][340/2119] lr: 4.0000e-02 eta: 23:23:25 time: 0.2980 data_time: 0.0236 memory: 5826 grad_norm: 2.9722 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7020 loss: 2.7020 2022/10/07 14:21:42 - mmengine - INFO - Epoch(train) [34][360/2119] lr: 4.0000e-02 eta: 23:23:22 time: 0.3805 data_time: 0.0244 memory: 5826 grad_norm: 2.9870 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8463 loss: 2.8463 2022/10/07 14:21:49 - mmengine - INFO - Epoch(train) [34][380/2119] lr: 4.0000e-02 eta: 23:23:12 time: 0.3064 data_time: 0.0212 memory: 5826 grad_norm: 3.0065 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7886 loss: 2.7886 2022/10/07 14:21:55 - mmengine - INFO - Epoch(train) [34][400/2119] lr: 4.0000e-02 eta: 23:23:05 time: 0.3273 data_time: 0.0195 memory: 5826 grad_norm: 3.0757 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9254 loss: 2.9254 2022/10/07 14:22:02 - mmengine - INFO - Epoch(train) [34][420/2119] lr: 4.0000e-02 eta: 23:22:58 time: 0.3409 data_time: 0.0206 memory: 5826 grad_norm: 3.0084 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7746 loss: 2.7746 2022/10/07 14:22:09 - mmengine - INFO - Epoch(train) [34][440/2119] lr: 4.0000e-02 eta: 23:22:52 time: 0.3494 data_time: 0.0219 memory: 5826 grad_norm: 3.0460 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8802 loss: 2.8802 2022/10/07 14:22:16 - mmengine - INFO - Epoch(train) [34][460/2119] lr: 4.0000e-02 eta: 23:22:45 time: 0.3462 data_time: 0.0237 memory: 5826 grad_norm: 3.0332 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.9085 loss: 2.9085 2022/10/07 14:22:23 - mmengine - INFO - Epoch(train) [34][480/2119] lr: 4.0000e-02 eta: 23:22:39 time: 0.3524 data_time: 0.0164 memory: 5826 grad_norm: 3.0661 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7060 loss: 2.7060 2022/10/07 14:22:30 - mmengine - INFO - Epoch(train) [34][500/2119] lr: 4.0000e-02 eta: 23:22:34 time: 0.3606 data_time: 0.0270 memory: 5826 grad_norm: 3.0179 top1_acc: 0.3125 top5_acc: 0.8750 loss_cls: 2.7674 loss: 2.7674 2022/10/07 14:22:36 - mmengine - INFO - Epoch(train) [34][520/2119] lr: 4.0000e-02 eta: 23:22:23 time: 0.2743 data_time: 0.0236 memory: 5826 grad_norm: 3.0664 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8106 loss: 2.8106 2022/10/07 14:22:43 - mmengine - INFO - Epoch(train) [34][540/2119] lr: 4.0000e-02 eta: 23:22:18 time: 0.3686 data_time: 0.0204 memory: 5826 grad_norm: 3.0324 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7956 loss: 2.7956 2022/10/07 14:22:50 - mmengine - INFO - Epoch(train) [34][560/2119] lr: 4.0000e-02 eta: 23:22:11 time: 0.3442 data_time: 0.0250 memory: 5826 grad_norm: 3.0151 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8158 loss: 2.8158 2022/10/07 14:22:57 - mmengine - INFO - Epoch(train) [34][580/2119] lr: 4.0000e-02 eta: 23:22:05 time: 0.3433 data_time: 0.0210 memory: 5826 grad_norm: 3.0603 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4884 loss: 2.4884 2022/10/07 14:23:04 - mmengine - INFO - Epoch(train) [34][600/2119] lr: 4.0000e-02 eta: 23:21:59 time: 0.3529 data_time: 0.0199 memory: 5826 grad_norm: 3.0578 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5943 loss: 2.5943 2022/10/07 14:23:10 - mmengine - INFO - Epoch(train) [34][620/2119] lr: 4.0000e-02 eta: 23:21:52 time: 0.3355 data_time: 0.0186 memory: 5826 grad_norm: 3.0294 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5650 loss: 2.5650 2022/10/07 14:23:17 - mmengine - INFO - Epoch(train) [34][640/2119] lr: 4.0000e-02 eta: 23:21:44 time: 0.3315 data_time: 0.0293 memory: 5826 grad_norm: 3.0714 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7369 loss: 2.7369 2022/10/07 14:23:24 - mmengine - INFO - Epoch(train) [34][660/2119] lr: 4.0000e-02 eta: 23:21:38 time: 0.3521 data_time: 0.0192 memory: 5826 grad_norm: 3.0493 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9725 loss: 2.9725 2022/10/07 14:23:31 - mmengine - INFO - Epoch(train) [34][680/2119] lr: 4.0000e-02 eta: 23:21:31 time: 0.3311 data_time: 0.0228 memory: 5826 grad_norm: 3.0467 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4510 loss: 2.4510 2022/10/07 14:23:37 - mmengine - INFO - Epoch(train) [34][700/2119] lr: 4.0000e-02 eta: 23:21:22 time: 0.3155 data_time: 0.0176 memory: 5826 grad_norm: 3.0204 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6811 loss: 2.6811 2022/10/07 14:23:44 - mmengine - INFO - Epoch(train) [34][720/2119] lr: 4.0000e-02 eta: 23:21:15 time: 0.3311 data_time: 0.0272 memory: 5826 grad_norm: 3.0004 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7764 loss: 2.7764 2022/10/07 14:23:51 - mmengine - INFO - Epoch(train) [34][740/2119] lr: 4.0000e-02 eta: 23:21:09 time: 0.3577 data_time: 0.0232 memory: 5826 grad_norm: 3.0379 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7448 loss: 2.7448 2022/10/07 14:23:57 - mmengine - INFO - Epoch(train) [34][760/2119] lr: 4.0000e-02 eta: 23:21:01 time: 0.3215 data_time: 0.0310 memory: 5826 grad_norm: 3.0563 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5426 loss: 2.5426 2022/10/07 14:24:04 - mmengine - INFO - Epoch(train) [34][780/2119] lr: 4.0000e-02 eta: 23:20:53 time: 0.3146 data_time: 0.0210 memory: 5826 grad_norm: 3.0424 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.0056 loss: 3.0056 2022/10/07 14:24:12 - mmengine - INFO - Epoch(train) [34][800/2119] lr: 4.0000e-02 eta: 23:20:50 time: 0.3992 data_time: 0.0195 memory: 5826 grad_norm: 3.0186 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8351 loss: 2.8351 2022/10/07 14:24:18 - mmengine - INFO - Epoch(train) [34][820/2119] lr: 4.0000e-02 eta: 23:20:42 time: 0.3207 data_time: 0.0215 memory: 5826 grad_norm: 3.0089 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6891 loss: 2.6891 2022/10/07 14:24:25 - mmengine - INFO - Epoch(train) [34][840/2119] lr: 4.0000e-02 eta: 23:20:36 time: 0.3515 data_time: 0.0205 memory: 5826 grad_norm: 3.0334 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8518 loss: 2.8518 2022/10/07 14:24:31 - mmengine - INFO - Epoch(train) [34][860/2119] lr: 4.0000e-02 eta: 23:20:27 time: 0.3165 data_time: 0.0223 memory: 5826 grad_norm: 3.0206 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6307 loss: 2.6307 2022/10/07 14:24:39 - mmengine - INFO - Epoch(train) [34][880/2119] lr: 4.0000e-02 eta: 23:20:25 time: 0.3998 data_time: 0.0254 memory: 5826 grad_norm: 3.0454 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7356 loss: 2.7356 2022/10/07 14:24:45 - mmengine - INFO - Epoch(train) [34][900/2119] lr: 4.0000e-02 eta: 23:20:13 time: 0.2743 data_time: 0.0210 memory: 5826 grad_norm: 3.0503 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0039 loss: 3.0039 2022/10/07 14:24:52 - mmengine - INFO - Epoch(train) [34][920/2119] lr: 4.0000e-02 eta: 23:20:09 time: 0.3754 data_time: 0.0225 memory: 5826 grad_norm: 3.0021 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9918 loss: 2.9918 2022/10/07 14:24:58 - mmengine - INFO - Epoch(train) [34][940/2119] lr: 4.0000e-02 eta: 23:19:59 time: 0.2917 data_time: 0.0198 memory: 5826 grad_norm: 3.0164 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8456 loss: 2.8456 2022/10/07 14:25:06 - mmengine - INFO - Epoch(train) [34][960/2119] lr: 4.0000e-02 eta: 23:19:57 time: 0.4121 data_time: 0.0249 memory: 5826 grad_norm: 3.0459 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6310 loss: 2.6310 2022/10/07 14:25:12 - mmengine - INFO - Epoch(train) [34][980/2119] lr: 4.0000e-02 eta: 23:19:47 time: 0.2926 data_time: 0.0174 memory: 5826 grad_norm: 3.0220 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.8741 loss: 2.8741 2022/10/07 14:25:19 - mmengine - INFO - Epoch(train) [34][1000/2119] lr: 4.0000e-02 eta: 23:19:41 time: 0.3497 data_time: 0.0247 memory: 5826 grad_norm: 3.0493 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9019 loss: 2.9019 2022/10/07 14:25:27 - mmengine - INFO - Epoch(train) [34][1020/2119] lr: 4.0000e-02 eta: 23:19:36 time: 0.3656 data_time: 0.0184 memory: 5826 grad_norm: 3.0391 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7239 loss: 2.7239 2022/10/07 14:25:33 - mmengine - INFO - Epoch(train) [34][1040/2119] lr: 4.0000e-02 eta: 23:19:29 time: 0.3421 data_time: 0.0236 memory: 5826 grad_norm: 3.0174 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.4419 loss: 2.4419 2022/10/07 14:25:41 - mmengine - INFO - Epoch(train) [34][1060/2119] lr: 4.0000e-02 eta: 23:19:24 time: 0.3645 data_time: 0.0363 memory: 5826 grad_norm: 3.0114 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9116 loss: 2.9116 2022/10/07 14:25:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 14:25:48 - mmengine - INFO - Epoch(train) [34][1080/2119] lr: 4.0000e-02 eta: 23:19:18 time: 0.3500 data_time: 0.0212 memory: 5826 grad_norm: 3.0019 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8702 loss: 2.8702 2022/10/07 14:25:55 - mmengine - INFO - Epoch(train) [34][1100/2119] lr: 4.0000e-02 eta: 23:19:11 time: 0.3385 data_time: 0.0168 memory: 5826 grad_norm: 2.9714 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7324 loss: 2.7324 2022/10/07 14:26:02 - mmengine - INFO - Epoch(train) [34][1120/2119] lr: 4.0000e-02 eta: 23:19:07 time: 0.3846 data_time: 0.0192 memory: 5826 grad_norm: 2.9993 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7945 loss: 2.7945 2022/10/07 14:26:09 - mmengine - INFO - Epoch(train) [34][1140/2119] lr: 4.0000e-02 eta: 23:19:00 time: 0.3363 data_time: 0.0166 memory: 5826 grad_norm: 3.0480 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6052 loss: 2.6052 2022/10/07 14:26:15 - mmengine - INFO - Epoch(train) [34][1160/2119] lr: 4.0000e-02 eta: 23:18:52 time: 0.3130 data_time: 0.0279 memory: 5826 grad_norm: 3.0052 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8623 loss: 2.8623 2022/10/07 14:26:22 - mmengine - INFO - Epoch(train) [34][1180/2119] lr: 4.0000e-02 eta: 23:18:44 time: 0.3318 data_time: 0.0175 memory: 5826 grad_norm: 2.9776 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8343 loss: 2.8343 2022/10/07 14:26:29 - mmengine - INFO - Epoch(train) [34][1200/2119] lr: 4.0000e-02 eta: 23:18:39 time: 0.3588 data_time: 0.0244 memory: 5826 grad_norm: 3.0424 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0147 loss: 3.0147 2022/10/07 14:26:36 - mmengine - INFO - Epoch(train) [34][1220/2119] lr: 4.0000e-02 eta: 23:18:33 time: 0.3523 data_time: 0.0267 memory: 5826 grad_norm: 3.0377 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6129 loss: 2.6129 2022/10/07 14:26:44 - mmengine - INFO - Epoch(train) [34][1240/2119] lr: 4.0000e-02 eta: 23:18:28 time: 0.3736 data_time: 0.0230 memory: 5826 grad_norm: 3.0145 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9288 loss: 2.9288 2022/10/07 14:26:50 - mmengine - INFO - Epoch(train) [34][1260/2119] lr: 4.0000e-02 eta: 23:18:19 time: 0.2988 data_time: 0.0181 memory: 5826 grad_norm: 3.0290 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7542 loss: 2.7542 2022/10/07 14:26:57 - mmengine - INFO - Epoch(train) [34][1280/2119] lr: 4.0000e-02 eta: 23:18:15 time: 0.3908 data_time: 0.0221 memory: 5826 grad_norm: 3.0400 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8974 loss: 2.8974 2022/10/07 14:27:04 - mmengine - INFO - Epoch(train) [34][1300/2119] lr: 4.0000e-02 eta: 23:18:07 time: 0.3158 data_time: 0.0164 memory: 5826 grad_norm: 3.0123 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7084 loss: 2.7084 2022/10/07 14:27:11 - mmengine - INFO - Epoch(train) [34][1320/2119] lr: 4.0000e-02 eta: 23:18:01 time: 0.3567 data_time: 0.0225 memory: 5826 grad_norm: 2.9886 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0267 loss: 3.0267 2022/10/07 14:27:18 - mmengine - INFO - Epoch(train) [34][1340/2119] lr: 4.0000e-02 eta: 23:17:55 time: 0.3448 data_time: 0.0206 memory: 5826 grad_norm: 3.0293 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6427 loss: 2.6427 2022/10/07 14:27:24 - mmengine - INFO - Epoch(train) [34][1360/2119] lr: 4.0000e-02 eta: 23:17:47 time: 0.3312 data_time: 0.0236 memory: 5826 grad_norm: 3.0173 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6817 loss: 2.6817 2022/10/07 14:27:31 - mmengine - INFO - Epoch(train) [34][1380/2119] lr: 4.0000e-02 eta: 23:17:39 time: 0.3250 data_time: 0.0216 memory: 5826 grad_norm: 3.0362 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6171 loss: 2.6171 2022/10/07 14:27:38 - mmengine - INFO - Epoch(train) [34][1400/2119] lr: 4.0000e-02 eta: 23:17:34 time: 0.3628 data_time: 0.0210 memory: 5826 grad_norm: 2.9614 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8930 loss: 2.8930 2022/10/07 14:27:45 - mmengine - INFO - Epoch(train) [34][1420/2119] lr: 4.0000e-02 eta: 23:17:26 time: 0.3213 data_time: 0.0210 memory: 5826 grad_norm: 2.9828 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7755 loss: 2.7755 2022/10/07 14:27:52 - mmengine - INFO - Epoch(train) [34][1440/2119] lr: 4.0000e-02 eta: 23:17:21 time: 0.3715 data_time: 0.0230 memory: 5826 grad_norm: 3.0368 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6421 loss: 2.6421 2022/10/07 14:27:58 - mmengine - INFO - Epoch(train) [34][1460/2119] lr: 4.0000e-02 eta: 23:17:11 time: 0.2889 data_time: 0.0243 memory: 5826 grad_norm: 3.0555 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6570 loss: 2.6570 2022/10/07 14:28:05 - mmengine - INFO - Epoch(train) [34][1480/2119] lr: 4.0000e-02 eta: 23:17:06 time: 0.3641 data_time: 0.0201 memory: 5826 grad_norm: 3.1099 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.9787 loss: 2.9787 2022/10/07 14:28:11 - mmengine - INFO - Epoch(train) [34][1500/2119] lr: 4.0000e-02 eta: 23:16:58 time: 0.3205 data_time: 0.0246 memory: 5826 grad_norm: 3.0253 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0033 loss: 3.0033 2022/10/07 14:28:18 - mmengine - INFO - Epoch(train) [34][1520/2119] lr: 4.0000e-02 eta: 23:16:49 time: 0.3103 data_time: 0.0243 memory: 5826 grad_norm: 3.0215 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7176 loss: 2.7176 2022/10/07 14:28:25 - mmengine - INFO - Epoch(train) [34][1540/2119] lr: 4.0000e-02 eta: 23:16:45 time: 0.3771 data_time: 0.0182 memory: 5826 grad_norm: 3.0909 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7597 loss: 2.7597 2022/10/07 14:28:32 - mmengine - INFO - Epoch(train) [34][1560/2119] lr: 4.0000e-02 eta: 23:16:36 time: 0.3206 data_time: 0.0222 memory: 5826 grad_norm: 3.0001 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6062 loss: 2.6062 2022/10/07 14:28:39 - mmengine - INFO - Epoch(train) [34][1580/2119] lr: 4.0000e-02 eta: 23:16:31 time: 0.3639 data_time: 0.0228 memory: 5826 grad_norm: 3.0166 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.9035 loss: 2.9035 2022/10/07 14:28:46 - mmengine - INFO - Epoch(train) [34][1600/2119] lr: 4.0000e-02 eta: 23:16:26 time: 0.3625 data_time: 0.0190 memory: 5826 grad_norm: 3.0377 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.7156 loss: 2.7156 2022/10/07 14:28:53 - mmengine - INFO - Epoch(train) [34][1620/2119] lr: 4.0000e-02 eta: 23:16:18 time: 0.3288 data_time: 0.0179 memory: 5826 grad_norm: 3.0148 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7817 loss: 2.7817 2022/10/07 14:29:00 - mmengine - INFO - Epoch(train) [34][1640/2119] lr: 4.0000e-02 eta: 23:16:12 time: 0.3495 data_time: 0.0190 memory: 5826 grad_norm: 2.9797 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 2.7468 loss: 2.7468 2022/10/07 14:29:07 - mmengine - INFO - Epoch(train) [34][1660/2119] lr: 4.0000e-02 eta: 23:16:06 time: 0.3465 data_time: 0.0203 memory: 5826 grad_norm: 2.9525 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8375 loss: 2.8375 2022/10/07 14:29:13 - mmengine - INFO - Epoch(train) [34][1680/2119] lr: 4.0000e-02 eta: 23:15:58 time: 0.3305 data_time: 0.0210 memory: 5826 grad_norm: 3.0327 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6168 loss: 2.6168 2022/10/07 14:29:21 - mmengine - INFO - Epoch(train) [34][1700/2119] lr: 4.0000e-02 eta: 23:15:55 time: 0.3902 data_time: 0.0186 memory: 5826 grad_norm: 3.0765 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8528 loss: 2.8528 2022/10/07 14:29:27 - mmengine - INFO - Epoch(train) [34][1720/2119] lr: 4.0000e-02 eta: 23:15:46 time: 0.3002 data_time: 0.0185 memory: 5826 grad_norm: 3.0005 top1_acc: 0.0625 top5_acc: 0.3750 loss_cls: 2.7686 loss: 2.7686 2022/10/07 14:29:35 - mmengine - INFO - Epoch(train) [34][1740/2119] lr: 4.0000e-02 eta: 23:15:42 time: 0.3852 data_time: 0.0210 memory: 5826 grad_norm: 3.0120 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7079 loss: 2.7079 2022/10/07 14:29:41 - mmengine - INFO - Epoch(train) [34][1760/2119] lr: 4.0000e-02 eta: 23:15:33 time: 0.3134 data_time: 0.0267 memory: 5826 grad_norm: 3.0057 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7020 loss: 2.7020 2022/10/07 14:29:49 - mmengine - INFO - Epoch(train) [34][1780/2119] lr: 4.0000e-02 eta: 23:15:31 time: 0.4025 data_time: 0.0240 memory: 5826 grad_norm: 3.0300 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 3.0683 loss: 3.0683 2022/10/07 14:29:55 - mmengine - INFO - Epoch(train) [34][1800/2119] lr: 4.0000e-02 eta: 23:15:21 time: 0.2969 data_time: 0.0237 memory: 5826 grad_norm: 3.0232 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5974 loss: 2.5974 2022/10/07 14:30:03 - mmengine - INFO - Epoch(train) [34][1820/2119] lr: 4.0000e-02 eta: 23:15:19 time: 0.4097 data_time: 0.0174 memory: 5826 grad_norm: 3.0512 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5921 loss: 2.5921 2022/10/07 14:30:10 - mmengine - INFO - Epoch(train) [34][1840/2119] lr: 4.0000e-02 eta: 23:15:12 time: 0.3345 data_time: 0.0268 memory: 5826 grad_norm: 3.0505 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7574 loss: 2.7574 2022/10/07 14:30:16 - mmengine - INFO - Epoch(train) [34][1860/2119] lr: 4.0000e-02 eta: 23:15:02 time: 0.2984 data_time: 0.0188 memory: 5826 grad_norm: 3.0342 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9066 loss: 2.9066 2022/10/07 14:30:23 - mmengine - INFO - Epoch(train) [34][1880/2119] lr: 4.0000e-02 eta: 23:14:56 time: 0.3486 data_time: 0.0251 memory: 5826 grad_norm: 2.9798 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6416 loss: 2.6416 2022/10/07 14:30:30 - mmengine - INFO - Epoch(train) [34][1900/2119] lr: 4.0000e-02 eta: 23:14:50 time: 0.3526 data_time: 0.0182 memory: 5826 grad_norm: 2.9927 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9339 loss: 2.9339 2022/10/07 14:30:37 - mmengine - INFO - Epoch(train) [34][1920/2119] lr: 4.0000e-02 eta: 23:14:43 time: 0.3455 data_time: 0.0233 memory: 5826 grad_norm: 3.0048 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7349 loss: 2.7349 2022/10/07 14:30:44 - mmengine - INFO - Epoch(train) [34][1940/2119] lr: 4.0000e-02 eta: 23:14:37 time: 0.3529 data_time: 0.0232 memory: 5826 grad_norm: 3.0800 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7843 loss: 2.7843 2022/10/07 14:30:51 - mmengine - INFO - Epoch(train) [34][1960/2119] lr: 4.0000e-02 eta: 23:14:33 time: 0.3726 data_time: 0.0264 memory: 5826 grad_norm: 3.0018 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7433 loss: 2.7433 2022/10/07 14:30:58 - mmengine - INFO - Epoch(train) [34][1980/2119] lr: 4.0000e-02 eta: 23:14:24 time: 0.3093 data_time: 0.0231 memory: 5826 grad_norm: 2.9896 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7413 loss: 2.7413 2022/10/07 14:31:05 - mmengine - INFO - Epoch(train) [34][2000/2119] lr: 4.0000e-02 eta: 23:14:18 time: 0.3526 data_time: 0.0223 memory: 5826 grad_norm: 3.0572 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6735 loss: 2.6735 2022/10/07 14:31:12 - mmengine - INFO - Epoch(train) [34][2020/2119] lr: 4.0000e-02 eta: 23:14:12 time: 0.3552 data_time: 0.0160 memory: 5826 grad_norm: 3.0609 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6641 loss: 2.6641 2022/10/07 14:31:17 - mmengine - INFO - Epoch(train) [34][2040/2119] lr: 4.0000e-02 eta: 23:14:01 time: 0.2770 data_time: 0.0232 memory: 5826 grad_norm: 3.0023 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6959 loss: 2.6959 2022/10/07 14:31:25 - mmengine - INFO - Epoch(train) [34][2060/2119] lr: 4.0000e-02 eta: 23:13:58 time: 0.3969 data_time: 0.0242 memory: 5826 grad_norm: 3.0231 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6086 loss: 2.6086 2022/10/07 14:31:29 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 14:31:32 - mmengine - INFO - Epoch(train) [34][2080/2119] lr: 4.0000e-02 eta: 23:13:50 time: 0.3203 data_time: 0.0205 memory: 5826 grad_norm: 3.0290 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.6824 loss: 2.6824 2022/10/07 14:31:39 - mmengine - INFO - Epoch(train) [34][2100/2119] lr: 4.0000e-02 eta: 23:13:46 time: 0.3769 data_time: 0.0233 memory: 5826 grad_norm: 3.0778 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8533 loss: 2.8533 2022/10/07 14:31:45 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 14:31:45 - mmengine - INFO - Epoch(train) [34][2119/2119] lr: 4.0000e-02 eta: 23:13:46 time: 0.3318 data_time: 0.0178 memory: 5826 grad_norm: 3.0499 top1_acc: 0.3000 top5_acc: 0.6000 loss_cls: 2.8769 loss: 2.8769 2022/10/07 14:31:54 - mmengine - INFO - Epoch(train) [35][20/2119] lr: 4.0000e-02 eta: 23:13:19 time: 0.4657 data_time: 0.1303 memory: 5826 grad_norm: 3.0132 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0039 loss: 3.0039 2022/10/07 14:32:02 - mmengine - INFO - Epoch(train) [35][40/2119] lr: 4.0000e-02 eta: 23:13:15 time: 0.3772 data_time: 0.0206 memory: 5826 grad_norm: 3.0904 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4962 loss: 2.4962 2022/10/07 14:32:09 - mmengine - INFO - Epoch(train) [35][60/2119] lr: 4.0000e-02 eta: 23:13:08 time: 0.3353 data_time: 0.0247 memory: 5826 grad_norm: 3.0491 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.6515 loss: 2.6515 2022/10/07 14:32:15 - mmengine - INFO - Epoch(train) [35][80/2119] lr: 4.0000e-02 eta: 23:12:59 time: 0.3194 data_time: 0.0276 memory: 5826 grad_norm: 3.0353 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6675 loss: 2.6675 2022/10/07 14:32:22 - mmengine - INFO - Epoch(train) [35][100/2119] lr: 4.0000e-02 eta: 23:12:54 time: 0.3592 data_time: 0.0216 memory: 5826 grad_norm: 3.0557 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8195 loss: 2.8195 2022/10/07 14:32:29 - mmengine - INFO - Epoch(train) [35][120/2119] lr: 4.0000e-02 eta: 23:12:46 time: 0.3285 data_time: 0.0204 memory: 5826 grad_norm: 3.0076 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6629 loss: 2.6629 2022/10/07 14:32:36 - mmengine - INFO - Epoch(train) [35][140/2119] lr: 4.0000e-02 eta: 23:12:39 time: 0.3409 data_time: 0.0190 memory: 5826 grad_norm: 2.9894 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9102 loss: 2.9102 2022/10/07 14:32:42 - mmengine - INFO - Epoch(train) [35][160/2119] lr: 4.0000e-02 eta: 23:12:31 time: 0.3188 data_time: 0.0340 memory: 5826 grad_norm: 3.0176 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8866 loss: 2.8866 2022/10/07 14:32:49 - mmengine - INFO - Epoch(train) [35][180/2119] lr: 4.0000e-02 eta: 23:12:26 time: 0.3564 data_time: 0.0184 memory: 5826 grad_norm: 3.0883 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7466 loss: 2.7466 2022/10/07 14:32:56 - mmengine - INFO - Epoch(train) [35][200/2119] lr: 4.0000e-02 eta: 23:12:19 time: 0.3468 data_time: 0.0244 memory: 5826 grad_norm: 3.0592 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7137 loss: 2.7137 2022/10/07 14:33:03 - mmengine - INFO - Epoch(train) [35][220/2119] lr: 4.0000e-02 eta: 23:12:11 time: 0.3229 data_time: 0.0196 memory: 5826 grad_norm: 2.9809 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6183 loss: 2.6183 2022/10/07 14:33:09 - mmengine - INFO - Epoch(train) [35][240/2119] lr: 4.0000e-02 eta: 23:12:02 time: 0.3116 data_time: 0.0315 memory: 5826 grad_norm: 3.0184 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8345 loss: 2.8345 2022/10/07 14:33:16 - mmengine - INFO - Epoch(train) [35][260/2119] lr: 4.0000e-02 eta: 23:11:58 time: 0.3706 data_time: 0.0190 memory: 5826 grad_norm: 3.0008 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6592 loss: 2.6592 2022/10/07 14:33:22 - mmengine - INFO - Epoch(train) [35][280/2119] lr: 4.0000e-02 eta: 23:11:49 time: 0.3072 data_time: 0.0294 memory: 5826 grad_norm: 3.0639 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 3.0500 loss: 3.0500 2022/10/07 14:33:29 - mmengine - INFO - Epoch(train) [35][300/2119] lr: 4.0000e-02 eta: 23:11:42 time: 0.3447 data_time: 0.0246 memory: 5826 grad_norm: 3.0598 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6975 loss: 2.6975 2022/10/07 14:33:36 - mmengine - INFO - Epoch(train) [35][320/2119] lr: 4.0000e-02 eta: 23:11:34 time: 0.3263 data_time: 0.0175 memory: 5826 grad_norm: 3.0259 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5570 loss: 2.5570 2022/10/07 14:33:44 - mmengine - INFO - Epoch(train) [35][340/2119] lr: 4.0000e-02 eta: 23:11:31 time: 0.3863 data_time: 0.0250 memory: 5826 grad_norm: 3.0226 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8451 loss: 2.8451 2022/10/07 14:33:50 - mmengine - INFO - Epoch(train) [35][360/2119] lr: 4.0000e-02 eta: 23:11:23 time: 0.3189 data_time: 0.0230 memory: 5826 grad_norm: 3.0244 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6886 loss: 2.6886 2022/10/07 14:33:57 - mmengine - INFO - Epoch(train) [35][380/2119] lr: 4.0000e-02 eta: 23:11:18 time: 0.3713 data_time: 0.0245 memory: 5826 grad_norm: 3.0408 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6581 loss: 2.6581 2022/10/07 14:34:04 - mmengine - INFO - Epoch(train) [35][400/2119] lr: 4.0000e-02 eta: 23:11:11 time: 0.3432 data_time: 0.0205 memory: 5826 grad_norm: 3.0202 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5970 loss: 2.5970 2022/10/07 14:34:12 - mmengine - INFO - Epoch(train) [35][420/2119] lr: 4.0000e-02 eta: 23:11:07 time: 0.3825 data_time: 0.0240 memory: 5826 grad_norm: 2.9721 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.4547 loss: 2.4547 2022/10/07 14:34:18 - mmengine - INFO - Epoch(train) [35][440/2119] lr: 4.0000e-02 eta: 23:10:57 time: 0.2938 data_time: 0.0200 memory: 5826 grad_norm: 2.9821 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6962 loss: 2.6962 2022/10/07 14:34:25 - mmengine - INFO - Epoch(train) [35][460/2119] lr: 4.0000e-02 eta: 23:10:52 time: 0.3603 data_time: 0.0242 memory: 5826 grad_norm: 2.9873 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6399 loss: 2.6399 2022/10/07 14:34:32 - mmengine - INFO - Epoch(train) [35][480/2119] lr: 4.0000e-02 eta: 23:10:45 time: 0.3451 data_time: 0.0349 memory: 5826 grad_norm: 3.0837 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9217 loss: 2.9217 2022/10/07 14:34:38 - mmengine - INFO - Epoch(train) [35][500/2119] lr: 4.0000e-02 eta: 23:10:37 time: 0.3167 data_time: 0.0233 memory: 5826 grad_norm: 3.0558 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.8273 loss: 2.8273 2022/10/07 14:34:45 - mmengine - INFO - Epoch(train) [35][520/2119] lr: 4.0000e-02 eta: 23:10:32 time: 0.3627 data_time: 0.0238 memory: 5826 grad_norm: 3.1226 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9383 loss: 2.9383 2022/10/07 14:34:52 - mmengine - INFO - Epoch(train) [35][540/2119] lr: 4.0000e-02 eta: 23:10:25 time: 0.3372 data_time: 0.0212 memory: 5826 grad_norm: 3.0706 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8453 loss: 2.8453 2022/10/07 14:35:00 - mmengine - INFO - Epoch(train) [35][560/2119] lr: 4.0000e-02 eta: 23:10:20 time: 0.3711 data_time: 0.0207 memory: 5826 grad_norm: 2.9985 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7839 loss: 2.7839 2022/10/07 14:35:06 - mmengine - INFO - Epoch(train) [35][580/2119] lr: 4.0000e-02 eta: 23:10:12 time: 0.3241 data_time: 0.0210 memory: 5826 grad_norm: 3.0174 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7169 loss: 2.7169 2022/10/07 14:35:14 - mmengine - INFO - Epoch(train) [35][600/2119] lr: 4.0000e-02 eta: 23:10:08 time: 0.3814 data_time: 0.0210 memory: 5826 grad_norm: 3.0068 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8026 loss: 2.8026 2022/10/07 14:35:21 - mmengine - INFO - Epoch(train) [35][620/2119] lr: 4.0000e-02 eta: 23:10:01 time: 0.3395 data_time: 0.0179 memory: 5826 grad_norm: 3.0584 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4121 loss: 2.4121 2022/10/07 14:35:27 - mmengine - INFO - Epoch(train) [35][640/2119] lr: 4.0000e-02 eta: 23:09:54 time: 0.3366 data_time: 0.0238 memory: 5826 grad_norm: 3.0512 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8645 loss: 2.8645 2022/10/07 14:35:34 - mmengine - INFO - Epoch(train) [35][660/2119] lr: 4.0000e-02 eta: 23:09:46 time: 0.3198 data_time: 0.0182 memory: 5826 grad_norm: 3.0509 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9676 loss: 2.9676 2022/10/07 14:35:41 - mmengine - INFO - Epoch(train) [35][680/2119] lr: 4.0000e-02 eta: 23:09:42 time: 0.3810 data_time: 0.0255 memory: 5826 grad_norm: 3.0902 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.0619 loss: 3.0619 2022/10/07 14:35:47 - mmengine - INFO - Epoch(train) [35][700/2119] lr: 4.0000e-02 eta: 23:09:33 time: 0.3030 data_time: 0.0208 memory: 5826 grad_norm: 3.0631 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8787 loss: 2.8787 2022/10/07 14:35:55 - mmengine - INFO - Epoch(train) [35][720/2119] lr: 4.0000e-02 eta: 23:09:28 time: 0.3639 data_time: 0.0250 memory: 5826 grad_norm: 3.0862 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.8874 loss: 2.8874 2022/10/07 14:36:02 - mmengine - INFO - Epoch(train) [35][740/2119] lr: 4.0000e-02 eta: 23:09:22 time: 0.3565 data_time: 0.0201 memory: 5826 grad_norm: 3.0222 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8600 loss: 2.8600 2022/10/07 14:36:09 - mmengine - INFO - Epoch(train) [35][760/2119] lr: 4.0000e-02 eta: 23:09:15 time: 0.3430 data_time: 0.0213 memory: 5826 grad_norm: 3.0638 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7640 loss: 2.7640 2022/10/07 14:36:15 - mmengine - INFO - Epoch(train) [35][780/2119] lr: 4.0000e-02 eta: 23:09:08 time: 0.3336 data_time: 0.0205 memory: 5826 grad_norm: 3.0927 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6158 loss: 2.6158 2022/10/07 14:36:23 - mmengine - INFO - Epoch(train) [35][800/2119] lr: 4.0000e-02 eta: 23:09:04 time: 0.3761 data_time: 0.0210 memory: 5826 grad_norm: 3.0136 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8243 loss: 2.8243 2022/10/07 14:36:29 - mmengine - INFO - Epoch(train) [35][820/2119] lr: 4.0000e-02 eta: 23:08:54 time: 0.3047 data_time: 0.0171 memory: 5826 grad_norm: 3.0267 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6988 loss: 2.6988 2022/10/07 14:36:36 - mmengine - INFO - Epoch(train) [35][840/2119] lr: 4.0000e-02 eta: 23:08:47 time: 0.3367 data_time: 0.0226 memory: 5826 grad_norm: 2.9838 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7418 loss: 2.7418 2022/10/07 14:36:42 - mmengine - INFO - Epoch(train) [35][860/2119] lr: 4.0000e-02 eta: 23:08:39 time: 0.3149 data_time: 0.0188 memory: 5826 grad_norm: 3.0226 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7639 loss: 2.7639 2022/10/07 14:36:49 - mmengine - INFO - Epoch(train) [35][880/2119] lr: 4.0000e-02 eta: 23:08:33 time: 0.3524 data_time: 0.0192 memory: 5826 grad_norm: 3.0342 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7113 loss: 2.7113 2022/10/07 14:36:56 - mmengine - INFO - Epoch(train) [35][900/2119] lr: 4.0000e-02 eta: 23:08:26 time: 0.3458 data_time: 0.0202 memory: 5826 grad_norm: 3.0529 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6170 loss: 2.6170 2022/10/07 14:37:04 - mmengine - INFO - Epoch(train) [35][920/2119] lr: 4.0000e-02 eta: 23:08:22 time: 0.3802 data_time: 0.0188 memory: 5826 grad_norm: 3.0591 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7149 loss: 2.7149 2022/10/07 14:37:10 - mmengine - INFO - Epoch(train) [35][940/2119] lr: 4.0000e-02 eta: 23:08:13 time: 0.2987 data_time: 0.0185 memory: 5826 grad_norm: 3.0290 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7942 loss: 2.7942 2022/10/07 14:37:15 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 14:37:17 - mmengine - INFO - Epoch(train) [35][960/2119] lr: 4.0000e-02 eta: 23:08:09 time: 0.3902 data_time: 0.0252 memory: 5826 grad_norm: 3.0323 top1_acc: 0.1250 top5_acc: 0.6875 loss_cls: 2.9544 loss: 2.9544 2022/10/07 14:37:24 - mmengine - INFO - Epoch(train) [35][980/2119] lr: 4.0000e-02 eta: 23:08:01 time: 0.3182 data_time: 0.0167 memory: 5826 grad_norm: 2.9975 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7552 loss: 2.7552 2022/10/07 14:37:31 - mmengine - INFO - Epoch(train) [35][1000/2119] lr: 4.0000e-02 eta: 23:07:56 time: 0.3724 data_time: 0.0238 memory: 5826 grad_norm: 2.9880 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7940 loss: 2.7940 2022/10/07 14:37:37 - mmengine - INFO - Epoch(train) [35][1020/2119] lr: 4.0000e-02 eta: 23:07:47 time: 0.2997 data_time: 0.0180 memory: 5826 grad_norm: 3.0171 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6561 loss: 2.6561 2022/10/07 14:37:44 - mmengine - INFO - Epoch(train) [35][1040/2119] lr: 4.0000e-02 eta: 23:07:41 time: 0.3550 data_time: 0.0225 memory: 5826 grad_norm: 3.0527 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7557 loss: 2.7557 2022/10/07 14:37:51 - mmengine - INFO - Epoch(train) [35][1060/2119] lr: 4.0000e-02 eta: 23:07:33 time: 0.3203 data_time: 0.0240 memory: 5826 grad_norm: 2.9723 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5934 loss: 2.5934 2022/10/07 14:37:57 - mmengine - INFO - Epoch(train) [35][1080/2119] lr: 4.0000e-02 eta: 23:07:26 time: 0.3359 data_time: 0.0239 memory: 5826 grad_norm: 3.0249 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6166 loss: 2.6166 2022/10/07 14:38:04 - mmengine - INFO - Epoch(train) [35][1100/2119] lr: 4.0000e-02 eta: 23:07:17 time: 0.3075 data_time: 0.0235 memory: 5826 grad_norm: 3.0082 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8767 loss: 2.8767 2022/10/07 14:38:11 - mmengine - INFO - Epoch(train) [35][1120/2119] lr: 4.0000e-02 eta: 23:07:12 time: 0.3653 data_time: 0.0299 memory: 5826 grad_norm: 3.0631 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9186 loss: 2.9186 2022/10/07 14:38:17 - mmengine - INFO - Epoch(train) [35][1140/2119] lr: 4.0000e-02 eta: 23:07:03 time: 0.3083 data_time: 0.0167 memory: 5826 grad_norm: 3.0327 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8812 loss: 2.8812 2022/10/07 14:38:24 - mmengine - INFO - Epoch(train) [35][1160/2119] lr: 4.0000e-02 eta: 23:06:57 time: 0.3600 data_time: 0.0215 memory: 5826 grad_norm: 2.9909 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7909 loss: 2.7909 2022/10/07 14:38:30 - mmengine - INFO - Epoch(train) [35][1180/2119] lr: 4.0000e-02 eta: 23:06:48 time: 0.3038 data_time: 0.0215 memory: 5826 grad_norm: 3.0168 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6528 loss: 2.6528 2022/10/07 14:38:37 - mmengine - INFO - Epoch(train) [35][1200/2119] lr: 4.0000e-02 eta: 23:06:40 time: 0.3207 data_time: 0.0289 memory: 5826 grad_norm: 3.0246 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8266 loss: 2.8266 2022/10/07 14:38:43 - mmengine - INFO - Epoch(train) [35][1220/2119] lr: 4.0000e-02 eta: 23:06:31 time: 0.3021 data_time: 0.0236 memory: 5826 grad_norm: 2.9880 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8044 loss: 2.8044 2022/10/07 14:38:51 - mmengine - INFO - Epoch(train) [35][1240/2119] lr: 4.0000e-02 eta: 23:06:29 time: 0.4201 data_time: 0.0231 memory: 5826 grad_norm: 3.0427 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6425 loss: 2.6425 2022/10/07 14:38:57 - mmengine - INFO - Epoch(train) [35][1260/2119] lr: 4.0000e-02 eta: 23:06:20 time: 0.3023 data_time: 0.0250 memory: 5826 grad_norm: 3.0266 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5967 loss: 2.5967 2022/10/07 14:39:04 - mmengine - INFO - Epoch(train) [35][1280/2119] lr: 4.0000e-02 eta: 23:06:13 time: 0.3418 data_time: 0.0246 memory: 5826 grad_norm: 3.0791 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6959 loss: 2.6959 2022/10/07 14:39:11 - mmengine - INFO - Epoch(train) [35][1300/2119] lr: 4.0000e-02 eta: 23:06:08 time: 0.3621 data_time: 0.0209 memory: 5826 grad_norm: 3.0854 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8004 loss: 2.8004 2022/10/07 14:39:18 - mmengine - INFO - Epoch(train) [35][1320/2119] lr: 4.0000e-02 eta: 23:06:00 time: 0.3172 data_time: 0.0240 memory: 5826 grad_norm: 3.0235 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7911 loss: 2.7911 2022/10/07 14:39:24 - mmengine - INFO - Epoch(train) [35][1340/2119] lr: 4.0000e-02 eta: 23:05:53 time: 0.3405 data_time: 0.0185 memory: 5826 grad_norm: 2.9967 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6636 loss: 2.6636 2022/10/07 14:39:32 - mmengine - INFO - Epoch(train) [35][1360/2119] lr: 4.0000e-02 eta: 23:05:49 time: 0.3928 data_time: 0.0200 memory: 5826 grad_norm: 3.0474 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8800 loss: 2.8800 2022/10/07 14:39:39 - mmengine - INFO - Epoch(train) [35][1380/2119] lr: 4.0000e-02 eta: 23:05:42 time: 0.3317 data_time: 0.0190 memory: 5826 grad_norm: 3.0573 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8434 loss: 2.8434 2022/10/07 14:39:46 - mmengine - INFO - Epoch(train) [35][1400/2119] lr: 4.0000e-02 eta: 23:05:35 time: 0.3403 data_time: 0.0217 memory: 5826 grad_norm: 3.0239 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7744 loss: 2.7744 2022/10/07 14:39:52 - mmengine - INFO - Epoch(train) [35][1420/2119] lr: 4.0000e-02 eta: 23:05:28 time: 0.3316 data_time: 0.0198 memory: 5826 grad_norm: 3.0832 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7218 loss: 2.7218 2022/10/07 14:40:01 - mmengine - INFO - Epoch(train) [35][1440/2119] lr: 4.0000e-02 eta: 23:05:26 time: 0.4192 data_time: 0.0223 memory: 5826 grad_norm: 3.0520 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9735 loss: 2.9735 2022/10/07 14:40:07 - mmengine - INFO - Epoch(train) [35][1460/2119] lr: 4.0000e-02 eta: 23:05:17 time: 0.2977 data_time: 0.0217 memory: 5826 grad_norm: 3.0508 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8767 loss: 2.8767 2022/10/07 14:40:14 - mmengine - INFO - Epoch(train) [35][1480/2119] lr: 4.0000e-02 eta: 23:05:13 time: 0.3790 data_time: 0.0224 memory: 5826 grad_norm: 3.0586 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4325 loss: 2.4325 2022/10/07 14:40:21 - mmengine - INFO - Epoch(train) [35][1500/2119] lr: 4.0000e-02 eta: 23:05:06 time: 0.3437 data_time: 0.0184 memory: 5826 grad_norm: 3.0119 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7932 loss: 2.7932 2022/10/07 14:40:28 - mmengine - INFO - Epoch(train) [35][1520/2119] lr: 4.0000e-02 eta: 23:04:59 time: 0.3381 data_time: 0.0239 memory: 5826 grad_norm: 3.0104 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7929 loss: 2.7929 2022/10/07 14:40:34 - mmengine - INFO - Epoch(train) [35][1540/2119] lr: 4.0000e-02 eta: 23:04:50 time: 0.3070 data_time: 0.0209 memory: 5826 grad_norm: 3.0946 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8623 loss: 2.8623 2022/10/07 14:40:41 - mmengine - INFO - Epoch(train) [35][1560/2119] lr: 4.0000e-02 eta: 23:04:45 time: 0.3609 data_time: 0.0207 memory: 5826 grad_norm: 2.9871 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8244 loss: 2.8244 2022/10/07 14:40:48 - mmengine - INFO - Epoch(train) [35][1580/2119] lr: 4.0000e-02 eta: 23:04:38 time: 0.3483 data_time: 0.0171 memory: 5826 grad_norm: 3.0322 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7849 loss: 2.7849 2022/10/07 14:40:56 - mmengine - INFO - Epoch(train) [35][1600/2119] lr: 4.0000e-02 eta: 23:04:34 time: 0.3793 data_time: 0.0198 memory: 5826 grad_norm: 3.0531 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9120 loss: 2.9120 2022/10/07 14:41:02 - mmengine - INFO - Epoch(train) [35][1620/2119] lr: 4.0000e-02 eta: 23:04:26 time: 0.3215 data_time: 0.0244 memory: 5826 grad_norm: 3.0534 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8514 loss: 2.8514 2022/10/07 14:41:09 - mmengine - INFO - Epoch(train) [35][1640/2119] lr: 4.0000e-02 eta: 23:04:20 time: 0.3586 data_time: 0.0214 memory: 5826 grad_norm: 3.0267 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9159 loss: 2.9159 2022/10/07 14:41:16 - mmengine - INFO - Epoch(train) [35][1660/2119] lr: 4.0000e-02 eta: 23:04:13 time: 0.3313 data_time: 0.0267 memory: 5826 grad_norm: 2.9435 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8435 loss: 2.8435 2022/10/07 14:41:24 - mmengine - INFO - Epoch(train) [35][1680/2119] lr: 4.0000e-02 eta: 23:04:09 time: 0.3782 data_time: 0.0241 memory: 5826 grad_norm: 3.0436 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8823 loss: 2.8823 2022/10/07 14:41:31 - mmengine - INFO - Epoch(train) [35][1700/2119] lr: 4.0000e-02 eta: 23:04:02 time: 0.3452 data_time: 0.0215 memory: 5826 grad_norm: 3.0448 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8501 loss: 2.8501 2022/10/07 14:41:38 - mmengine - INFO - Epoch(train) [35][1720/2119] lr: 4.0000e-02 eta: 23:03:57 time: 0.3552 data_time: 0.0244 memory: 5826 grad_norm: 3.0690 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8615 loss: 2.8615 2022/10/07 14:41:44 - mmengine - INFO - Epoch(train) [35][1740/2119] lr: 4.0000e-02 eta: 23:03:50 time: 0.3397 data_time: 0.0185 memory: 5826 grad_norm: 2.9714 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.9485 loss: 2.9485 2022/10/07 14:41:52 - mmengine - INFO - Epoch(train) [35][1760/2119] lr: 4.0000e-02 eta: 23:03:44 time: 0.3595 data_time: 0.0233 memory: 5826 grad_norm: 2.9617 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6175 loss: 2.6175 2022/10/07 14:41:58 - mmengine - INFO - Epoch(train) [35][1780/2119] lr: 4.0000e-02 eta: 23:03:36 time: 0.3146 data_time: 0.0159 memory: 5826 grad_norm: 3.0650 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9325 loss: 2.9325 2022/10/07 14:42:05 - mmengine - INFO - Epoch(train) [35][1800/2119] lr: 4.0000e-02 eta: 23:03:31 time: 0.3710 data_time: 0.0233 memory: 5826 grad_norm: 3.0076 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8917 loss: 2.8917 2022/10/07 14:42:12 - mmengine - INFO - Epoch(train) [35][1820/2119] lr: 4.0000e-02 eta: 23:03:23 time: 0.3294 data_time: 0.0183 memory: 5826 grad_norm: 3.0209 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8894 loss: 2.8894 2022/10/07 14:42:20 - mmengine - INFO - Epoch(train) [35][1840/2119] lr: 4.0000e-02 eta: 23:03:20 time: 0.3862 data_time: 0.0367 memory: 5826 grad_norm: 3.0030 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6544 loss: 2.6544 2022/10/07 14:42:27 - mmengine - INFO - Epoch(train) [35][1860/2119] lr: 4.0000e-02 eta: 23:03:13 time: 0.3451 data_time: 0.0298 memory: 5826 grad_norm: 2.9739 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9152 loss: 2.9152 2022/10/07 14:42:34 - mmengine - INFO - Epoch(train) [35][1880/2119] lr: 4.0000e-02 eta: 23:03:08 time: 0.3650 data_time: 0.0212 memory: 5826 grad_norm: 3.0287 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8139 loss: 2.8139 2022/10/07 14:42:41 - mmengine - INFO - Epoch(train) [35][1900/2119] lr: 4.0000e-02 eta: 23:03:01 time: 0.3384 data_time: 0.0149 memory: 5826 grad_norm: 2.9961 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8247 loss: 2.8247 2022/10/07 14:42:48 - mmengine - INFO - Epoch(train) [35][1920/2119] lr: 4.0000e-02 eta: 23:02:55 time: 0.3467 data_time: 0.0222 memory: 5826 grad_norm: 3.0437 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8495 loss: 2.8495 2022/10/07 14:42:55 - mmengine - INFO - Epoch(train) [35][1940/2119] lr: 4.0000e-02 eta: 23:02:48 time: 0.3459 data_time: 0.0306 memory: 5826 grad_norm: 3.0352 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8390 loss: 2.8390 2022/10/07 14:43:00 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 14:43:02 - mmengine - INFO - Epoch(train) [35][1960/2119] lr: 4.0000e-02 eta: 23:02:42 time: 0.3493 data_time: 0.0498 memory: 5826 grad_norm: 2.9929 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6687 loss: 2.6687 2022/10/07 14:43:08 - mmengine - INFO - Epoch(train) [35][1980/2119] lr: 4.0000e-02 eta: 23:02:34 time: 0.3177 data_time: 0.0409 memory: 5826 grad_norm: 3.0593 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7151 loss: 2.7151 2022/10/07 14:43:16 - mmengine - INFO - Epoch(train) [35][2000/2119] lr: 4.0000e-02 eta: 23:02:31 time: 0.4070 data_time: 0.0237 memory: 5826 grad_norm: 3.0654 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.6348 loss: 2.6348 2022/10/07 14:43:22 - mmengine - INFO - Epoch(train) [35][2020/2119] lr: 4.0000e-02 eta: 23:02:23 time: 0.3217 data_time: 0.0154 memory: 5826 grad_norm: 3.1290 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9099 loss: 2.9099 2022/10/07 14:43:31 - mmengine - INFO - Epoch(train) [35][2040/2119] lr: 4.0000e-02 eta: 23:02:22 time: 0.4193 data_time: 0.0232 memory: 5826 grad_norm: 3.0391 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7245 loss: 2.7245 2022/10/07 14:43:37 - mmengine - INFO - Epoch(train) [35][2060/2119] lr: 4.0000e-02 eta: 23:02:13 time: 0.3048 data_time: 0.0159 memory: 5826 grad_norm: 3.0255 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9467 loss: 2.9467 2022/10/07 14:43:44 - mmengine - INFO - Epoch(train) [35][2080/2119] lr: 4.0000e-02 eta: 23:02:08 time: 0.3765 data_time: 0.0237 memory: 5826 grad_norm: 3.0347 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8816 loss: 2.8816 2022/10/07 14:43:51 - mmengine - INFO - Epoch(train) [35][2100/2119] lr: 4.0000e-02 eta: 23:02:01 time: 0.3383 data_time: 0.0148 memory: 5826 grad_norm: 3.0215 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.5563 loss: 2.5563 2022/10/07 14:43:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 14:43:56 - mmengine - INFO - Epoch(train) [35][2119/2119] lr: 4.0000e-02 eta: 23:02:01 time: 0.2735 data_time: 0.0159 memory: 5826 grad_norm: 3.0808 top1_acc: 0.3000 top5_acc: 0.5000 loss_cls: 2.6786 loss: 2.6786 2022/10/07 14:44:05 - mmengine - INFO - Epoch(val) [35][20/137] eta: 0:00:51 time: 0.4440 data_time: 0.3761 memory: 1241 2022/10/07 14:44:12 - mmengine - INFO - Epoch(val) [35][40/137] eta: 0:00:30 time: 0.3109 data_time: 0.2390 memory: 1241 2022/10/07 14:44:20 - mmengine - INFO - Epoch(val) [35][60/137] eta: 0:00:32 time: 0.4212 data_time: 0.3553 memory: 1241 2022/10/07 14:44:26 - mmengine - INFO - Epoch(val) [35][80/137] eta: 0:00:17 time: 0.3120 data_time: 0.2464 memory: 1241 2022/10/07 14:44:35 - mmengine - INFO - Epoch(val) [35][100/137] eta: 0:00:15 time: 0.4264 data_time: 0.3578 memory: 1241 2022/10/07 14:44:41 - mmengine - INFO - Epoch(val) [35][120/137] eta: 0:00:05 time: 0.3013 data_time: 0.2353 memory: 1241 2022/10/07 14:44:51 - mmengine - INFO - Epoch(val) [35][137/137] acc/top1: 0.4169 acc/top5: 0.6606 acc/mean1: 0.4168 2022/10/07 14:45:01 - mmengine - INFO - Epoch(train) [36][20/2119] lr: 4.0000e-02 eta: 23:01:37 time: 0.5035 data_time: 0.2546 memory: 5826 grad_norm: 2.9838 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7986 loss: 2.7986 2022/10/07 14:45:08 - mmengine - INFO - Epoch(train) [36][40/2119] lr: 4.0000e-02 eta: 23:01:30 time: 0.3302 data_time: 0.0899 memory: 5826 grad_norm: 3.0596 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7138 loss: 2.7138 2022/10/07 14:45:17 - mmengine - INFO - Epoch(train) [36][60/2119] lr: 4.0000e-02 eta: 23:01:29 time: 0.4335 data_time: 0.0721 memory: 5826 grad_norm: 3.0407 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4672 loss: 2.4672 2022/10/07 14:45:23 - mmengine - INFO - Epoch(train) [36][80/2119] lr: 4.0000e-02 eta: 23:01:22 time: 0.3288 data_time: 0.0221 memory: 5826 grad_norm: 3.0247 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5963 loss: 2.5963 2022/10/07 14:45:31 - mmengine - INFO - Epoch(train) [36][100/2119] lr: 4.0000e-02 eta: 23:01:17 time: 0.3764 data_time: 0.0222 memory: 5826 grad_norm: 3.0630 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8331 loss: 2.8331 2022/10/07 14:45:37 - mmengine - INFO - Epoch(train) [36][120/2119] lr: 4.0000e-02 eta: 23:01:08 time: 0.2996 data_time: 0.0243 memory: 5826 grad_norm: 3.0852 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.6788 loss: 2.6788 2022/10/07 14:45:44 - mmengine - INFO - Epoch(train) [36][140/2119] lr: 4.0000e-02 eta: 23:01:02 time: 0.3483 data_time: 0.0197 memory: 5826 grad_norm: 3.0300 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5134 loss: 2.5134 2022/10/07 14:45:51 - mmengine - INFO - Epoch(train) [36][160/2119] lr: 4.0000e-02 eta: 23:00:56 time: 0.3652 data_time: 0.0260 memory: 5826 grad_norm: 3.0641 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6667 loss: 2.6667 2022/10/07 14:45:58 - mmengine - INFO - Epoch(train) [36][180/2119] lr: 4.0000e-02 eta: 23:00:49 time: 0.3390 data_time: 0.0165 memory: 5826 grad_norm: 3.0371 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8888 loss: 2.8888 2022/10/07 14:46:06 - mmengine - INFO - Epoch(train) [36][200/2119] lr: 4.0000e-02 eta: 23:00:46 time: 0.3944 data_time: 0.0212 memory: 5826 grad_norm: 3.0786 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8462 loss: 2.8462 2022/10/07 14:46:13 - mmengine - INFO - Epoch(train) [36][220/2119] lr: 4.0000e-02 eta: 23:00:42 time: 0.3825 data_time: 0.0157 memory: 5826 grad_norm: 3.0032 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.5126 loss: 2.5126 2022/10/07 14:46:20 - mmengine - INFO - Epoch(train) [36][240/2119] lr: 4.0000e-02 eta: 23:00:34 time: 0.3122 data_time: 0.0185 memory: 5826 grad_norm: 3.0944 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7978 loss: 2.7978 2022/10/07 14:46:27 - mmengine - INFO - Epoch(train) [36][260/2119] lr: 4.0000e-02 eta: 23:00:29 time: 0.3803 data_time: 0.0195 memory: 5826 grad_norm: 3.0554 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9025 loss: 2.9025 2022/10/07 14:46:34 - mmengine - INFO - Epoch(train) [36][280/2119] lr: 4.0000e-02 eta: 23:00:23 time: 0.3486 data_time: 0.0248 memory: 5826 grad_norm: 3.0588 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8222 loss: 2.8222 2022/10/07 14:46:43 - mmengine - INFO - Epoch(train) [36][300/2119] lr: 4.0000e-02 eta: 23:00:22 time: 0.4285 data_time: 0.0218 memory: 5826 grad_norm: 3.0051 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7300 loss: 2.7300 2022/10/07 14:46:49 - mmengine - INFO - Epoch(train) [36][320/2119] lr: 4.0000e-02 eta: 23:00:13 time: 0.2990 data_time: 0.0236 memory: 5826 grad_norm: 3.0774 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5834 loss: 2.5834 2022/10/07 14:46:56 - mmengine - INFO - Epoch(train) [36][340/2119] lr: 4.0000e-02 eta: 23:00:06 time: 0.3465 data_time: 0.0245 memory: 5826 grad_norm: 3.0316 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7228 loss: 2.7228 2022/10/07 14:47:02 - mmengine - INFO - Epoch(train) [36][360/2119] lr: 4.0000e-02 eta: 22:59:58 time: 0.3150 data_time: 0.0350 memory: 5826 grad_norm: 3.0600 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7875 loss: 2.7875 2022/10/07 14:47:09 - mmengine - INFO - Epoch(train) [36][380/2119] lr: 4.0000e-02 eta: 22:59:52 time: 0.3549 data_time: 0.0227 memory: 5826 grad_norm: 3.0505 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8868 loss: 2.8868 2022/10/07 14:47:15 - mmengine - INFO - Epoch(train) [36][400/2119] lr: 4.0000e-02 eta: 22:59:43 time: 0.3091 data_time: 0.0217 memory: 5826 grad_norm: 3.0382 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8066 loss: 2.8066 2022/10/07 14:47:23 - mmengine - INFO - Epoch(train) [36][420/2119] lr: 4.0000e-02 eta: 22:59:39 time: 0.3876 data_time: 0.0288 memory: 5826 grad_norm: 2.9941 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6901 loss: 2.6901 2022/10/07 14:47:30 - mmengine - INFO - Epoch(train) [36][440/2119] lr: 4.0000e-02 eta: 22:59:32 time: 0.3303 data_time: 0.0186 memory: 5826 grad_norm: 3.0416 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8290 loss: 2.8290 2022/10/07 14:47:37 - mmengine - INFO - Epoch(train) [36][460/2119] lr: 4.0000e-02 eta: 22:59:25 time: 0.3433 data_time: 0.0219 memory: 5826 grad_norm: 3.0591 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7003 loss: 2.7003 2022/10/07 14:47:44 - mmengine - INFO - Epoch(train) [36][480/2119] lr: 4.0000e-02 eta: 22:59:20 time: 0.3680 data_time: 0.0218 memory: 5826 grad_norm: 2.9766 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6983 loss: 2.6983 2022/10/07 14:47:51 - mmengine - INFO - Epoch(train) [36][500/2119] lr: 4.0000e-02 eta: 22:59:15 time: 0.3692 data_time: 0.0271 memory: 5826 grad_norm: 3.0166 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.1695 loss: 3.1695 2022/10/07 14:47:58 - mmengine - INFO - Epoch(train) [36][520/2119] lr: 4.0000e-02 eta: 22:59:07 time: 0.3178 data_time: 0.0246 memory: 5826 grad_norm: 3.0314 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.9664 loss: 2.9664 2022/10/07 14:48:06 - mmengine - INFO - Epoch(train) [36][540/2119] lr: 4.0000e-02 eta: 22:59:06 time: 0.4290 data_time: 0.0206 memory: 5826 grad_norm: 3.0467 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6410 loss: 2.6410 2022/10/07 14:48:13 - mmengine - INFO - Epoch(train) [36][560/2119] lr: 4.0000e-02 eta: 22:58:58 time: 0.3179 data_time: 0.0233 memory: 5826 grad_norm: 3.0323 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6307 loss: 2.6307 2022/10/07 14:48:20 - mmengine - INFO - Epoch(train) [36][580/2119] lr: 4.0000e-02 eta: 22:58:52 time: 0.3598 data_time: 0.0198 memory: 5826 grad_norm: 3.0600 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9299 loss: 2.9299 2022/10/07 14:48:27 - mmengine - INFO - Epoch(train) [36][600/2119] lr: 4.0000e-02 eta: 22:58:45 time: 0.3357 data_time: 0.0235 memory: 5826 grad_norm: 3.0437 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6395 loss: 2.6395 2022/10/07 14:48:34 - mmengine - INFO - Epoch(train) [36][620/2119] lr: 4.0000e-02 eta: 22:58:42 time: 0.3900 data_time: 0.0308 memory: 5826 grad_norm: 3.0216 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9013 loss: 2.9013 2022/10/07 14:48:41 - mmengine - INFO - Epoch(train) [36][640/2119] lr: 4.0000e-02 eta: 22:58:34 time: 0.3241 data_time: 0.0263 memory: 5826 grad_norm: 3.0270 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8291 loss: 2.8291 2022/10/07 14:48:49 - mmengine - INFO - Epoch(train) [36][660/2119] lr: 4.0000e-02 eta: 22:58:32 time: 0.4126 data_time: 0.0185 memory: 5826 grad_norm: 3.0144 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7928 loss: 2.7928 2022/10/07 14:48:55 - mmengine - INFO - Epoch(train) [36][680/2119] lr: 4.0000e-02 eta: 22:58:22 time: 0.3038 data_time: 0.0196 memory: 5826 grad_norm: 2.9867 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8649 loss: 2.8649 2022/10/07 14:49:02 - mmengine - INFO - Epoch(train) [36][700/2119] lr: 4.0000e-02 eta: 22:58:17 time: 0.3632 data_time: 0.0196 memory: 5826 grad_norm: 3.0142 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8697 loss: 2.8697 2022/10/07 14:49:10 - mmengine - INFO - Epoch(train) [36][720/2119] lr: 4.0000e-02 eta: 22:58:12 time: 0.3660 data_time: 0.0234 memory: 5826 grad_norm: 3.1030 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6997 loss: 2.6997 2022/10/07 14:49:17 - mmengine - INFO - Epoch(train) [36][740/2119] lr: 4.0000e-02 eta: 22:58:07 time: 0.3696 data_time: 0.0234 memory: 5826 grad_norm: 3.0680 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6850 loss: 2.6850 2022/10/07 14:49:24 - mmengine - INFO - Epoch(train) [36][760/2119] lr: 4.0000e-02 eta: 22:58:01 time: 0.3528 data_time: 0.0266 memory: 5826 grad_norm: 3.0181 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7012 loss: 2.7012 2022/10/07 14:49:32 - mmengine - INFO - Epoch(train) [36][780/2119] lr: 4.0000e-02 eta: 22:57:56 time: 0.3656 data_time: 0.0216 memory: 5826 grad_norm: 3.0765 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.8919 loss: 2.8919 2022/10/07 14:49:38 - mmengine - INFO - Epoch(train) [36][800/2119] lr: 4.0000e-02 eta: 22:57:48 time: 0.3176 data_time: 0.0191 memory: 5826 grad_norm: 3.0290 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7726 loss: 2.7726 2022/10/07 14:49:47 - mmengine - INFO - Epoch(train) [36][820/2119] lr: 4.0000e-02 eta: 22:57:47 time: 0.4422 data_time: 0.0240 memory: 5826 grad_norm: 3.0054 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7308 loss: 2.7308 2022/10/07 14:49:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 14:49:53 - mmengine - INFO - Epoch(train) [36][840/2119] lr: 4.0000e-02 eta: 22:57:39 time: 0.3148 data_time: 0.0233 memory: 5826 grad_norm: 2.9801 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8689 loss: 2.8689 2022/10/07 14:50:00 - mmengine - INFO - Epoch(train) [36][860/2119] lr: 4.0000e-02 eta: 22:57:34 time: 0.3734 data_time: 0.0214 memory: 5826 grad_norm: 3.0080 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8233 loss: 2.8233 2022/10/07 14:50:07 - mmengine - INFO - Epoch(train) [36][880/2119] lr: 4.0000e-02 eta: 22:57:28 time: 0.3467 data_time: 0.0221 memory: 5826 grad_norm: 3.0682 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9277 loss: 2.9277 2022/10/07 14:50:15 - mmengine - INFO - Epoch(train) [36][900/2119] lr: 4.0000e-02 eta: 22:57:23 time: 0.3789 data_time: 0.0215 memory: 5826 grad_norm: 3.0892 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5968 loss: 2.5968 2022/10/07 14:50:22 - mmengine - INFO - Epoch(train) [36][920/2119] lr: 4.0000e-02 eta: 22:57:17 time: 0.3447 data_time: 0.0251 memory: 5826 grad_norm: 3.0207 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8290 loss: 2.8290 2022/10/07 14:50:29 - mmengine - INFO - Epoch(train) [36][940/2119] lr: 4.0000e-02 eta: 22:57:11 time: 0.3493 data_time: 0.0211 memory: 5826 grad_norm: 3.1158 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9110 loss: 2.9110 2022/10/07 14:50:35 - mmengine - INFO - Epoch(train) [36][960/2119] lr: 4.0000e-02 eta: 22:57:03 time: 0.3239 data_time: 0.0228 memory: 5826 grad_norm: 3.0106 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8152 loss: 2.8152 2022/10/07 14:50:43 - mmengine - INFO - Epoch(train) [36][980/2119] lr: 4.0000e-02 eta: 22:56:58 time: 0.3734 data_time: 0.0236 memory: 5826 grad_norm: 2.9950 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5714 loss: 2.5714 2022/10/07 14:50:50 - mmengine - INFO - Epoch(train) [36][1000/2119] lr: 4.0000e-02 eta: 22:56:51 time: 0.3373 data_time: 0.0192 memory: 5826 grad_norm: 3.1097 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7125 loss: 2.7125 2022/10/07 14:50:57 - mmengine - INFO - Epoch(train) [36][1020/2119] lr: 4.0000e-02 eta: 22:56:47 time: 0.3847 data_time: 0.0245 memory: 5826 grad_norm: 3.0260 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8717 loss: 2.8717 2022/10/07 14:51:04 - mmengine - INFO - Epoch(train) [36][1040/2119] lr: 4.0000e-02 eta: 22:56:41 time: 0.3491 data_time: 0.0270 memory: 5826 grad_norm: 3.0436 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6072 loss: 2.6072 2022/10/07 14:51:12 - mmengine - INFO - Epoch(train) [36][1060/2119] lr: 4.0000e-02 eta: 22:56:36 time: 0.3752 data_time: 0.0229 memory: 5826 grad_norm: 2.9879 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7902 loss: 2.7902 2022/10/07 14:51:18 - mmengine - INFO - Epoch(train) [36][1080/2119] lr: 4.0000e-02 eta: 22:56:29 time: 0.3364 data_time: 0.0244 memory: 5826 grad_norm: 3.0527 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8467 loss: 2.8467 2022/10/07 14:51:27 - mmengine - INFO - Epoch(train) [36][1100/2119] lr: 4.0000e-02 eta: 22:56:27 time: 0.4170 data_time: 0.0196 memory: 5826 grad_norm: 3.0813 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6330 loss: 2.6330 2022/10/07 14:51:34 - mmengine - INFO - Epoch(train) [36][1120/2119] lr: 4.0000e-02 eta: 22:56:22 time: 0.3578 data_time: 0.0206 memory: 5826 grad_norm: 3.0486 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7212 loss: 2.7212 2022/10/07 14:51:40 - mmengine - INFO - Epoch(train) [36][1140/2119] lr: 4.0000e-02 eta: 22:56:12 time: 0.2954 data_time: 0.0253 memory: 5826 grad_norm: 3.1129 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8718 loss: 2.8718 2022/10/07 14:51:47 - mmengine - INFO - Epoch(train) [36][1160/2119] lr: 4.0000e-02 eta: 22:56:06 time: 0.3473 data_time: 0.0224 memory: 5826 grad_norm: 3.0100 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.4958 loss: 2.4958 2022/10/07 14:51:54 - mmengine - INFO - Epoch(train) [36][1180/2119] lr: 4.0000e-02 eta: 22:56:01 time: 0.3759 data_time: 0.0288 memory: 5826 grad_norm: 3.0521 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6657 loss: 2.6657 2022/10/07 14:52:01 - mmengine - INFO - Epoch(train) [36][1200/2119] lr: 4.0000e-02 eta: 22:55:55 time: 0.3496 data_time: 0.0159 memory: 5826 grad_norm: 3.0093 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7537 loss: 2.7537 2022/10/07 14:52:08 - mmengine - INFO - Epoch(train) [36][1220/2119] lr: 4.0000e-02 eta: 22:55:47 time: 0.3304 data_time: 0.0190 memory: 5826 grad_norm: 3.0561 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.5008 loss: 2.5008 2022/10/07 14:52:16 - mmengine - INFO - Epoch(train) [36][1240/2119] lr: 4.0000e-02 eta: 22:55:45 time: 0.4061 data_time: 0.0217 memory: 5826 grad_norm: 3.0980 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7711 loss: 2.7711 2022/10/07 14:52:22 - mmengine - INFO - Epoch(train) [36][1260/2119] lr: 4.0000e-02 eta: 22:55:36 time: 0.3152 data_time: 0.0241 memory: 5826 grad_norm: 3.0917 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6518 loss: 2.6518 2022/10/07 14:52:30 - mmengine - INFO - Epoch(train) [36][1280/2119] lr: 4.0000e-02 eta: 22:55:32 time: 0.3831 data_time: 0.0194 memory: 5826 grad_norm: 3.0172 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6646 loss: 2.6646 2022/10/07 14:52:37 - mmengine - INFO - Epoch(train) [36][1300/2119] lr: 4.0000e-02 eta: 22:55:24 time: 0.3213 data_time: 0.0228 memory: 5826 grad_norm: 3.0641 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9374 loss: 2.9374 2022/10/07 14:52:44 - mmengine - INFO - Epoch(train) [36][1320/2119] lr: 4.0000e-02 eta: 22:55:19 time: 0.3567 data_time: 0.0208 memory: 5826 grad_norm: 3.0432 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9276 loss: 2.9276 2022/10/07 14:52:50 - mmengine - INFO - Epoch(train) [36][1340/2119] lr: 4.0000e-02 eta: 22:55:11 time: 0.3287 data_time: 0.0192 memory: 5826 grad_norm: 3.0231 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9141 loss: 2.9141 2022/10/07 14:52:57 - mmengine - INFO - Epoch(train) [36][1360/2119] lr: 4.0000e-02 eta: 22:55:05 time: 0.3598 data_time: 0.0179 memory: 5826 grad_norm: 3.0652 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7290 loss: 2.7290 2022/10/07 14:53:03 - mmengine - INFO - Epoch(train) [36][1380/2119] lr: 4.0000e-02 eta: 22:54:56 time: 0.3002 data_time: 0.0208 memory: 5826 grad_norm: 3.0407 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7385 loss: 2.7385 2022/10/07 14:53:11 - mmengine - INFO - Epoch(train) [36][1400/2119] lr: 4.0000e-02 eta: 22:54:51 time: 0.3675 data_time: 0.0194 memory: 5826 grad_norm: 3.0350 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6894 loss: 2.6894 2022/10/07 14:53:18 - mmengine - INFO - Epoch(train) [36][1420/2119] lr: 4.0000e-02 eta: 22:54:44 time: 0.3400 data_time: 0.0215 memory: 5826 grad_norm: 2.9610 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.5751 loss: 2.5751 2022/10/07 14:53:25 - mmengine - INFO - Epoch(train) [36][1440/2119] lr: 4.0000e-02 eta: 22:54:40 time: 0.3853 data_time: 0.0191 memory: 5826 grad_norm: 3.0123 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6318 loss: 2.6318 2022/10/07 14:53:31 - mmengine - INFO - Epoch(train) [36][1460/2119] lr: 4.0000e-02 eta: 22:54:30 time: 0.2882 data_time: 0.0214 memory: 5826 grad_norm: 3.0831 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5999 loss: 2.5999 2022/10/07 14:53:38 - mmengine - INFO - Epoch(train) [36][1480/2119] lr: 4.0000e-02 eta: 22:54:24 time: 0.3482 data_time: 0.0185 memory: 5826 grad_norm: 3.0591 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6929 loss: 2.6929 2022/10/07 14:53:45 - mmengine - INFO - Epoch(train) [36][1500/2119] lr: 4.0000e-02 eta: 22:54:17 time: 0.3457 data_time: 0.0214 memory: 5826 grad_norm: 3.0806 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9507 loss: 2.9507 2022/10/07 14:53:52 - mmengine - INFO - Epoch(train) [36][1520/2119] lr: 4.0000e-02 eta: 22:54:12 time: 0.3606 data_time: 0.0221 memory: 5826 grad_norm: 3.0642 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7963 loss: 2.7963 2022/10/07 14:53:59 - mmengine - INFO - Epoch(train) [36][1540/2119] lr: 4.0000e-02 eta: 22:54:05 time: 0.3364 data_time: 0.0201 memory: 5826 grad_norm: 3.0225 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6397 loss: 2.6397 2022/10/07 14:54:05 - mmengine - INFO - Epoch(train) [36][1560/2119] lr: 4.0000e-02 eta: 22:53:57 time: 0.3285 data_time: 0.0204 memory: 5826 grad_norm: 3.0230 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9236 loss: 2.9236 2022/10/07 14:54:13 - mmengine - INFO - Epoch(train) [36][1580/2119] lr: 4.0000e-02 eta: 22:53:52 time: 0.3626 data_time: 0.0201 memory: 5826 grad_norm: 3.0639 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7774 loss: 2.7774 2022/10/07 14:54:20 - mmengine - INFO - Epoch(train) [36][1600/2119] lr: 4.0000e-02 eta: 22:53:46 time: 0.3628 data_time: 0.0214 memory: 5826 grad_norm: 3.0305 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8433 loss: 2.8433 2022/10/07 14:54:27 - mmengine - INFO - Epoch(train) [36][1620/2119] lr: 4.0000e-02 eta: 22:53:40 time: 0.3465 data_time: 0.0173 memory: 5826 grad_norm: 3.0608 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.9073 loss: 2.9073 2022/10/07 14:54:35 - mmengine - INFO - Epoch(train) [36][1640/2119] lr: 4.0000e-02 eta: 22:53:37 time: 0.3950 data_time: 0.0219 memory: 5826 grad_norm: 3.0508 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6750 loss: 2.6750 2022/10/07 14:54:42 - mmengine - INFO - Epoch(train) [36][1660/2119] lr: 4.0000e-02 eta: 22:53:31 time: 0.3644 data_time: 0.0237 memory: 5826 grad_norm: 3.0201 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8606 loss: 2.8606 2022/10/07 14:54:49 - mmengine - INFO - Epoch(train) [36][1680/2119] lr: 4.0000e-02 eta: 22:53:26 time: 0.3582 data_time: 0.0176 memory: 5826 grad_norm: 3.0513 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9496 loss: 2.9496 2022/10/07 14:54:55 - mmengine - INFO - Epoch(train) [36][1700/2119] lr: 4.0000e-02 eta: 22:53:16 time: 0.3031 data_time: 0.0211 memory: 5826 grad_norm: 3.0565 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8789 loss: 2.8789 2022/10/07 14:55:03 - mmengine - INFO - Epoch(train) [36][1720/2119] lr: 4.0000e-02 eta: 22:53:12 time: 0.3832 data_time: 0.0185 memory: 5826 grad_norm: 3.0722 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9329 loss: 2.9329 2022/10/07 14:55:09 - mmengine - INFO - Epoch(train) [36][1740/2119] lr: 4.0000e-02 eta: 22:53:04 time: 0.3150 data_time: 0.0190 memory: 5826 grad_norm: 3.1012 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7510 loss: 2.7510 2022/10/07 14:55:16 - mmengine - INFO - Epoch(train) [36][1760/2119] lr: 4.0000e-02 eta: 22:52:57 time: 0.3340 data_time: 0.0211 memory: 5826 grad_norm: 3.0010 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9185 loss: 2.9185 2022/10/07 14:55:23 - mmengine - INFO - Epoch(train) [36][1780/2119] lr: 4.0000e-02 eta: 22:52:51 time: 0.3606 data_time: 0.0278 memory: 5826 grad_norm: 3.0454 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7521 loss: 2.7521 2022/10/07 14:55:30 - mmengine - INFO - Epoch(train) [36][1800/2119] lr: 4.0000e-02 eta: 22:52:44 time: 0.3392 data_time: 0.0185 memory: 5826 grad_norm: 3.0758 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0198 loss: 3.0198 2022/10/07 14:55:36 - mmengine - INFO - Epoch(train) [36][1820/2119] lr: 4.0000e-02 eta: 22:52:36 time: 0.3171 data_time: 0.0228 memory: 5826 grad_norm: 3.0736 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7149 loss: 2.7149 2022/10/07 14:55:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 14:55:44 - mmengine - INFO - Epoch(train) [36][1840/2119] lr: 4.0000e-02 eta: 22:52:31 time: 0.3769 data_time: 0.0236 memory: 5826 grad_norm: 3.0115 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.0275 loss: 3.0275 2022/10/07 14:55:51 - mmengine - INFO - Epoch(train) [36][1860/2119] lr: 4.0000e-02 eta: 22:52:26 time: 0.3559 data_time: 0.0213 memory: 5826 grad_norm: 3.0245 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9917 loss: 2.9917 2022/10/07 14:55:58 - mmengine - INFO - Epoch(train) [36][1880/2119] lr: 4.0000e-02 eta: 22:52:19 time: 0.3436 data_time: 0.0204 memory: 5826 grad_norm: 3.0419 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8478 loss: 2.8478 2022/10/07 14:56:04 - mmengine - INFO - Epoch(train) [36][1900/2119] lr: 4.0000e-02 eta: 22:52:10 time: 0.3090 data_time: 0.0195 memory: 5826 grad_norm: 3.0243 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6977 loss: 2.6977 2022/10/07 14:56:12 - mmengine - INFO - Epoch(train) [36][1920/2119] lr: 4.0000e-02 eta: 22:52:05 time: 0.3742 data_time: 0.0211 memory: 5826 grad_norm: 3.0435 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6868 loss: 2.6868 2022/10/07 14:56:17 - mmengine - INFO - Epoch(train) [36][1940/2119] lr: 4.0000e-02 eta: 22:51:56 time: 0.2947 data_time: 0.0166 memory: 5826 grad_norm: 3.0439 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6781 loss: 2.6781 2022/10/07 14:56:25 - mmengine - INFO - Epoch(train) [36][1960/2119] lr: 4.0000e-02 eta: 22:51:53 time: 0.3962 data_time: 0.0171 memory: 5826 grad_norm: 3.0514 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.7178 loss: 2.7178 2022/10/07 14:56:32 - mmengine - INFO - Epoch(train) [36][1980/2119] lr: 4.0000e-02 eta: 22:51:45 time: 0.3354 data_time: 0.0191 memory: 5826 grad_norm: 3.0641 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.5611 loss: 2.5611 2022/10/07 14:56:38 - mmengine - INFO - Epoch(train) [36][2000/2119] lr: 4.0000e-02 eta: 22:51:37 time: 0.3142 data_time: 0.0218 memory: 5826 grad_norm: 3.0638 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.8815 loss: 2.8815 2022/10/07 14:56:45 - mmengine - INFO - Epoch(train) [36][2020/2119] lr: 4.0000e-02 eta: 22:51:31 time: 0.3491 data_time: 0.0201 memory: 5826 grad_norm: 2.9796 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6894 loss: 2.6894 2022/10/07 14:56:53 - mmengine - INFO - Epoch(train) [36][2040/2119] lr: 4.0000e-02 eta: 22:51:26 time: 0.3765 data_time: 0.0244 memory: 5826 grad_norm: 3.0737 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8203 loss: 2.8203 2022/10/07 14:56:59 - mmengine - INFO - Epoch(train) [36][2060/2119] lr: 4.0000e-02 eta: 22:51:18 time: 0.3248 data_time: 0.0201 memory: 5826 grad_norm: 3.0237 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8036 loss: 2.8036 2022/10/07 14:57:06 - mmengine - INFO - Epoch(train) [36][2080/2119] lr: 4.0000e-02 eta: 22:51:10 time: 0.3195 data_time: 0.0217 memory: 5826 grad_norm: 3.0378 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.9225 loss: 2.9225 2022/10/07 14:57:12 - mmengine - INFO - Epoch(train) [36][2100/2119] lr: 4.0000e-02 eta: 22:51:02 time: 0.3260 data_time: 0.0309 memory: 5826 grad_norm: 3.0615 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7973 loss: 2.7973 2022/10/07 14:57:17 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 14:57:17 - mmengine - INFO - Epoch(train) [36][2119/2119] lr: 4.0000e-02 eta: 22:51:02 time: 0.2697 data_time: 0.0190 memory: 5826 grad_norm: 3.0353 top1_acc: 0.6000 top5_acc: 0.6000 loss_cls: 2.7332 loss: 2.7332 2022/10/07 14:57:17 - mmengine - INFO - Saving checkpoint at 36 epochs 2022/10/07 14:57:35 - mmengine - INFO - Epoch(train) [37][20/2119] lr: 4.0000e-02 eta: 22:50:34 time: 0.4212 data_time: 0.1845 memory: 5826 grad_norm: 3.0815 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7085 loss: 2.7085 2022/10/07 14:57:42 - mmengine - INFO - Epoch(train) [37][40/2119] lr: 4.0000e-02 eta: 22:50:26 time: 0.3312 data_time: 0.1025 memory: 5826 grad_norm: 3.0703 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7500 loss: 2.7500 2022/10/07 14:57:49 - mmengine - INFO - Epoch(train) [37][60/2119] lr: 4.0000e-02 eta: 22:50:21 time: 0.3577 data_time: 0.1303 memory: 5826 grad_norm: 3.0145 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6570 loss: 2.6570 2022/10/07 14:57:55 - mmengine - INFO - Epoch(train) [37][80/2119] lr: 4.0000e-02 eta: 22:50:11 time: 0.2911 data_time: 0.0464 memory: 5826 grad_norm: 3.0750 top1_acc: 0.0625 top5_acc: 0.6250 loss_cls: 2.8572 loss: 2.8572 2022/10/07 14:58:02 - mmengine - INFO - Epoch(train) [37][100/2119] lr: 4.0000e-02 eta: 22:50:03 time: 0.3232 data_time: 0.0853 memory: 5826 grad_norm: 3.0201 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.8177 loss: 2.8177 2022/10/07 14:58:08 - mmengine - INFO - Epoch(train) [37][120/2119] lr: 4.0000e-02 eta: 22:49:56 time: 0.3352 data_time: 0.0168 memory: 5826 grad_norm: 2.9998 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7245 loss: 2.7245 2022/10/07 14:58:15 - mmengine - INFO - Epoch(train) [37][140/2119] lr: 4.0000e-02 eta: 22:49:50 time: 0.3513 data_time: 0.0250 memory: 5826 grad_norm: 3.0340 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7175 loss: 2.7175 2022/10/07 14:58:23 - mmengine - INFO - Epoch(train) [37][160/2119] lr: 4.0000e-02 eta: 22:49:46 time: 0.3991 data_time: 0.0222 memory: 5826 grad_norm: 3.0185 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6600 loss: 2.6600 2022/10/07 14:58:29 - mmengine - INFO - Epoch(train) [37][180/2119] lr: 4.0000e-02 eta: 22:49:37 time: 0.2980 data_time: 0.0208 memory: 5826 grad_norm: 3.0709 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8476 loss: 2.8476 2022/10/07 14:58:37 - mmengine - INFO - Epoch(train) [37][200/2119] lr: 4.0000e-02 eta: 22:49:32 time: 0.3629 data_time: 0.0180 memory: 5826 grad_norm: 3.0206 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9126 loss: 2.9126 2022/10/07 14:58:44 - mmengine - INFO - Epoch(train) [37][220/2119] lr: 4.0000e-02 eta: 22:49:26 time: 0.3583 data_time: 0.0210 memory: 5826 grad_norm: 3.0688 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9040 loss: 2.9040 2022/10/07 14:58:51 - mmengine - INFO - Epoch(train) [37][240/2119] lr: 4.0000e-02 eta: 22:49:19 time: 0.3424 data_time: 0.0219 memory: 5826 grad_norm: 3.0474 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8344 loss: 2.8344 2022/10/07 14:58:57 - mmengine - INFO - Epoch(train) [37][260/2119] lr: 4.0000e-02 eta: 22:49:12 time: 0.3333 data_time: 0.0213 memory: 5826 grad_norm: 3.0586 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.9171 loss: 2.9171 2022/10/07 14:59:04 - mmengine - INFO - Epoch(train) [37][280/2119] lr: 4.0000e-02 eta: 22:49:06 time: 0.3504 data_time: 0.0350 memory: 5826 grad_norm: 3.0042 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5882 loss: 2.5882 2022/10/07 14:59:11 - mmengine - INFO - Epoch(train) [37][300/2119] lr: 4.0000e-02 eta: 22:49:00 time: 0.3516 data_time: 0.0233 memory: 5826 grad_norm: 3.0413 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7278 loss: 2.7278 2022/10/07 14:59:18 - mmengine - INFO - Epoch(train) [37][320/2119] lr: 4.0000e-02 eta: 22:48:54 time: 0.3567 data_time: 0.0209 memory: 5826 grad_norm: 3.0465 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9116 loss: 2.9116 2022/10/07 14:59:25 - mmengine - INFO - Epoch(train) [37][340/2119] lr: 4.0000e-02 eta: 22:48:47 time: 0.3458 data_time: 0.0211 memory: 5826 grad_norm: 3.0114 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7300 loss: 2.7300 2022/10/07 14:59:32 - mmengine - INFO - Epoch(train) [37][360/2119] lr: 4.0000e-02 eta: 22:48:39 time: 0.3152 data_time: 0.0201 memory: 5826 grad_norm: 3.0094 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6208 loss: 2.6208 2022/10/07 14:59:38 - mmengine - INFO - Epoch(train) [37][380/2119] lr: 4.0000e-02 eta: 22:48:30 time: 0.3136 data_time: 0.0249 memory: 5826 grad_norm: 3.0460 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8127 loss: 2.8127 2022/10/07 14:59:45 - mmengine - INFO - Epoch(train) [37][400/2119] lr: 4.0000e-02 eta: 22:48:26 time: 0.3792 data_time: 0.0215 memory: 5826 grad_norm: 3.0445 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5623 loss: 2.5623 2022/10/07 14:59:51 - mmengine - INFO - Epoch(train) [37][420/2119] lr: 4.0000e-02 eta: 22:48:16 time: 0.2920 data_time: 0.0272 memory: 5826 grad_norm: 3.0563 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8509 loss: 2.8509 2022/10/07 14:59:58 - mmengine - INFO - Epoch(train) [37][440/2119] lr: 4.0000e-02 eta: 22:48:10 time: 0.3526 data_time: 0.0199 memory: 5826 grad_norm: 3.0652 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7013 loss: 2.7013 2022/10/07 15:00:06 - mmengine - INFO - Epoch(train) [37][460/2119] lr: 4.0000e-02 eta: 22:48:05 time: 0.3702 data_time: 0.0232 memory: 5826 grad_norm: 3.0319 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9357 loss: 2.9357 2022/10/07 15:00:12 - mmengine - INFO - Epoch(train) [37][480/2119] lr: 4.0000e-02 eta: 22:47:56 time: 0.2984 data_time: 0.0242 memory: 5826 grad_norm: 3.0896 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7689 loss: 2.7689 2022/10/07 15:00:18 - mmengine - INFO - Epoch(train) [37][500/2119] lr: 4.0000e-02 eta: 22:47:47 time: 0.3066 data_time: 0.0206 memory: 5826 grad_norm: 2.9835 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8944 loss: 2.8944 2022/10/07 15:00:25 - mmengine - INFO - Epoch(train) [37][520/2119] lr: 4.0000e-02 eta: 22:47:41 time: 0.3496 data_time: 0.0236 memory: 5826 grad_norm: 3.0084 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6760 loss: 2.6760 2022/10/07 15:00:32 - mmengine - INFO - Epoch(train) [37][540/2119] lr: 4.0000e-02 eta: 22:47:34 time: 0.3436 data_time: 0.0184 memory: 5826 grad_norm: 3.1436 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7391 loss: 2.7391 2022/10/07 15:00:39 - mmengine - INFO - Epoch(train) [37][560/2119] lr: 4.0000e-02 eta: 22:47:28 time: 0.3513 data_time: 0.0212 memory: 5826 grad_norm: 3.0256 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7667 loss: 2.7667 2022/10/07 15:00:46 - mmengine - INFO - Epoch(train) [37][580/2119] lr: 4.0000e-02 eta: 22:47:23 time: 0.3642 data_time: 0.0223 memory: 5826 grad_norm: 3.0448 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.7076 loss: 2.7076 2022/10/07 15:00:52 - mmengine - INFO - Epoch(train) [37][600/2119] lr: 4.0000e-02 eta: 22:47:14 time: 0.3055 data_time: 0.0183 memory: 5826 grad_norm: 3.0340 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6827 loss: 2.6827 2022/10/07 15:00:59 - mmengine - INFO - Epoch(train) [37][620/2119] lr: 4.0000e-02 eta: 22:47:06 time: 0.3206 data_time: 0.0276 memory: 5826 grad_norm: 3.0277 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7105 loss: 2.7105 2022/10/07 15:01:06 - mmengine - INFO - Epoch(train) [37][640/2119] lr: 4.0000e-02 eta: 22:47:02 time: 0.3908 data_time: 0.0192 memory: 5826 grad_norm: 3.0470 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6590 loss: 2.6590 2022/10/07 15:01:13 - mmengine - INFO - Epoch(train) [37][660/2119] lr: 4.0000e-02 eta: 22:46:53 time: 0.3128 data_time: 0.0220 memory: 5826 grad_norm: 3.0262 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5601 loss: 2.5601 2022/10/07 15:01:20 - mmengine - INFO - Epoch(train) [37][680/2119] lr: 4.0000e-02 eta: 22:46:48 time: 0.3690 data_time: 0.0208 memory: 5826 grad_norm: 3.0515 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.6912 loss: 2.6912 2022/10/07 15:01:26 - mmengine - INFO - Epoch(train) [37][700/2119] lr: 4.0000e-02 eta: 22:46:39 time: 0.3027 data_time: 0.0269 memory: 5826 grad_norm: 3.0386 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6727 loss: 2.6727 2022/10/07 15:01:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 15:01:34 - mmengine - INFO - Epoch(train) [37][720/2119] lr: 4.0000e-02 eta: 22:46:36 time: 0.4009 data_time: 0.0215 memory: 5826 grad_norm: 3.0219 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0190 loss: 3.0190 2022/10/07 15:01:40 - mmengine - INFO - Epoch(train) [37][740/2119] lr: 4.0000e-02 eta: 22:46:28 time: 0.3128 data_time: 0.0198 memory: 5826 grad_norm: 3.0343 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.7903 loss: 2.7903 2022/10/07 15:01:48 - mmengine - INFO - Epoch(train) [37][760/2119] lr: 4.0000e-02 eta: 22:46:23 time: 0.3779 data_time: 0.0175 memory: 5826 grad_norm: 3.0485 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7798 loss: 2.7798 2022/10/07 15:01:55 - mmengine - INFO - Epoch(train) [37][780/2119] lr: 4.0000e-02 eta: 22:46:16 time: 0.3374 data_time: 0.0195 memory: 5826 grad_norm: 3.0809 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7641 loss: 2.7641 2022/10/07 15:02:01 - mmengine - INFO - Epoch(train) [37][800/2119] lr: 4.0000e-02 eta: 22:46:09 time: 0.3378 data_time: 0.0240 memory: 5826 grad_norm: 3.0506 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8585 loss: 2.8585 2022/10/07 15:02:08 - mmengine - INFO - Epoch(train) [37][820/2119] lr: 4.0000e-02 eta: 22:46:02 time: 0.3271 data_time: 0.0261 memory: 5826 grad_norm: 3.0789 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7861 loss: 2.7861 2022/10/07 15:02:15 - mmengine - INFO - Epoch(train) [37][840/2119] lr: 4.0000e-02 eta: 22:45:57 time: 0.3741 data_time: 0.0226 memory: 5826 grad_norm: 3.1139 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6911 loss: 2.6911 2022/10/07 15:02:23 - mmengine - INFO - Epoch(train) [37][860/2119] lr: 4.0000e-02 eta: 22:45:52 time: 0.3732 data_time: 0.0257 memory: 5826 grad_norm: 3.0169 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8154 loss: 2.8154 2022/10/07 15:02:29 - mmengine - INFO - Epoch(train) [37][880/2119] lr: 4.0000e-02 eta: 22:45:44 time: 0.3137 data_time: 0.0203 memory: 5826 grad_norm: 3.0160 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.8180 loss: 2.8180 2022/10/07 15:02:36 - mmengine - INFO - Epoch(train) [37][900/2119] lr: 4.0000e-02 eta: 22:45:37 time: 0.3512 data_time: 0.0196 memory: 5826 grad_norm: 3.0400 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6838 loss: 2.6838 2022/10/07 15:02:43 - mmengine - INFO - Epoch(train) [37][920/2119] lr: 4.0000e-02 eta: 22:45:31 time: 0.3502 data_time: 0.0190 memory: 5826 grad_norm: 3.0631 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9624 loss: 2.9624 2022/10/07 15:02:49 - mmengine - INFO - Epoch(train) [37][940/2119] lr: 4.0000e-02 eta: 22:45:23 time: 0.3122 data_time: 0.0253 memory: 5826 grad_norm: 3.0726 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7627 loss: 2.7627 2022/10/07 15:02:57 - mmengine - INFO - Epoch(train) [37][960/2119] lr: 4.0000e-02 eta: 22:45:18 time: 0.3753 data_time: 0.0209 memory: 5826 grad_norm: 3.0446 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8377 loss: 2.8377 2022/10/07 15:03:04 - mmengine - INFO - Epoch(train) [37][980/2119] lr: 4.0000e-02 eta: 22:45:11 time: 0.3333 data_time: 0.0284 memory: 5826 grad_norm: 3.0595 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7248 loss: 2.7248 2022/10/07 15:03:10 - mmengine - INFO - Epoch(train) [37][1000/2119] lr: 4.0000e-02 eta: 22:45:03 time: 0.3274 data_time: 0.0238 memory: 5826 grad_norm: 3.0054 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7622 loss: 2.7622 2022/10/07 15:03:17 - mmengine - INFO - Epoch(train) [37][1020/2119] lr: 4.0000e-02 eta: 22:44:56 time: 0.3277 data_time: 0.0206 memory: 5826 grad_norm: 3.0547 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7825 loss: 2.7825 2022/10/07 15:03:24 - mmengine - INFO - Epoch(train) [37][1040/2119] lr: 4.0000e-02 eta: 22:44:51 time: 0.3699 data_time: 0.0200 memory: 5826 grad_norm: 3.1104 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8082 loss: 2.8082 2022/10/07 15:03:31 - mmengine - INFO - Epoch(train) [37][1060/2119] lr: 4.0000e-02 eta: 22:44:43 time: 0.3207 data_time: 0.0244 memory: 5826 grad_norm: 3.0262 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7823 loss: 2.7823 2022/10/07 15:03:39 - mmengine - INFO - Epoch(train) [37][1080/2119] lr: 4.0000e-02 eta: 22:44:41 time: 0.4317 data_time: 0.0167 memory: 5826 grad_norm: 3.0231 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9744 loss: 2.9744 2022/10/07 15:03:45 - mmengine - INFO - Epoch(train) [37][1100/2119] lr: 4.0000e-02 eta: 22:44:33 time: 0.3115 data_time: 0.0210 memory: 5826 grad_norm: 3.0405 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7425 loss: 2.7425 2022/10/07 15:03:53 - mmengine - INFO - Epoch(train) [37][1120/2119] lr: 4.0000e-02 eta: 22:44:28 time: 0.3718 data_time: 0.0248 memory: 5826 grad_norm: 3.0803 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6586 loss: 2.6586 2022/10/07 15:03:59 - mmengine - INFO - Epoch(train) [37][1140/2119] lr: 4.0000e-02 eta: 22:44:19 time: 0.3104 data_time: 0.0190 memory: 5826 grad_norm: 3.0111 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6030 loss: 2.6030 2022/10/07 15:04:07 - mmengine - INFO - Epoch(train) [37][1160/2119] lr: 4.0000e-02 eta: 22:44:15 time: 0.3895 data_time: 0.0314 memory: 5826 grad_norm: 3.0051 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6952 loss: 2.6952 2022/10/07 15:04:14 - mmengine - INFO - Epoch(train) [37][1180/2119] lr: 4.0000e-02 eta: 22:44:11 time: 0.3739 data_time: 0.0230 memory: 5826 grad_norm: 3.1660 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7606 loss: 2.7606 2022/10/07 15:04:22 - mmengine - INFO - Epoch(train) [37][1200/2119] lr: 4.0000e-02 eta: 22:44:06 time: 0.3802 data_time: 0.0293 memory: 5826 grad_norm: 3.0767 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7269 loss: 2.7269 2022/10/07 15:04:29 - mmengine - INFO - Epoch(train) [37][1220/2119] lr: 4.0000e-02 eta: 22:43:59 time: 0.3368 data_time: 0.0220 memory: 5826 grad_norm: 3.0464 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9416 loss: 2.9416 2022/10/07 15:04:36 - mmengine - INFO - Epoch(train) [37][1240/2119] lr: 4.0000e-02 eta: 22:43:54 time: 0.3578 data_time: 0.0198 memory: 5826 grad_norm: 3.0355 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6450 loss: 2.6450 2022/10/07 15:04:43 - mmengine - INFO - Epoch(train) [37][1260/2119] lr: 4.0000e-02 eta: 22:43:47 time: 0.3410 data_time: 0.0192 memory: 5826 grad_norm: 3.0583 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7587 loss: 2.7587 2022/10/07 15:04:49 - mmengine - INFO - Epoch(train) [37][1280/2119] lr: 4.0000e-02 eta: 22:43:40 time: 0.3347 data_time: 0.0232 memory: 5826 grad_norm: 3.0593 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7733 loss: 2.7733 2022/10/07 15:04:56 - mmengine - INFO - Epoch(train) [37][1300/2119] lr: 4.0000e-02 eta: 22:43:32 time: 0.3229 data_time: 0.0197 memory: 5826 grad_norm: 3.0459 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7619 loss: 2.7619 2022/10/07 15:05:04 - mmengine - INFO - Epoch(train) [37][1320/2119] lr: 4.0000e-02 eta: 22:43:29 time: 0.3996 data_time: 0.0308 memory: 5826 grad_norm: 3.0294 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7794 loss: 2.7794 2022/10/07 15:05:11 - mmengine - INFO - Epoch(train) [37][1340/2119] lr: 4.0000e-02 eta: 22:43:22 time: 0.3473 data_time: 0.0222 memory: 5826 grad_norm: 3.0255 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6977 loss: 2.6977 2022/10/07 15:05:18 - mmengine - INFO - Epoch(train) [37][1360/2119] lr: 4.0000e-02 eta: 22:43:18 time: 0.3824 data_time: 0.0176 memory: 5826 grad_norm: 3.0533 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8268 loss: 2.8268 2022/10/07 15:05:25 - mmengine - INFO - Epoch(train) [37][1380/2119] lr: 4.0000e-02 eta: 22:43:10 time: 0.3294 data_time: 0.0218 memory: 5826 grad_norm: 3.0341 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.5051 loss: 2.5051 2022/10/07 15:05:32 - mmengine - INFO - Epoch(train) [37][1400/2119] lr: 4.0000e-02 eta: 22:43:05 time: 0.3620 data_time: 0.0206 memory: 5826 grad_norm: 3.0272 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8126 loss: 2.8126 2022/10/07 15:05:39 - mmengine - INFO - Epoch(train) [37][1420/2119] lr: 4.0000e-02 eta: 22:42:57 time: 0.3272 data_time: 0.0227 memory: 5826 grad_norm: 3.0287 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8072 loss: 2.8072 2022/10/07 15:05:47 - mmengine - INFO - Epoch(train) [37][1440/2119] lr: 4.0000e-02 eta: 22:42:54 time: 0.3923 data_time: 0.0220 memory: 5826 grad_norm: 3.0572 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6201 loss: 2.6201 2022/10/07 15:05:53 - mmengine - INFO - Epoch(train) [37][1460/2119] lr: 4.0000e-02 eta: 22:42:46 time: 0.3262 data_time: 0.0373 memory: 5826 grad_norm: 3.0347 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8958 loss: 2.8958 2022/10/07 15:06:01 - mmengine - INFO - Epoch(train) [37][1480/2119] lr: 4.0000e-02 eta: 22:42:41 time: 0.3730 data_time: 0.0191 memory: 5826 grad_norm: 3.0192 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9767 loss: 2.9767 2022/10/07 15:06:07 - mmengine - INFO - Epoch(train) [37][1500/2119] lr: 4.0000e-02 eta: 22:42:33 time: 0.3117 data_time: 0.0264 memory: 5826 grad_norm: 3.0163 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8322 loss: 2.8322 2022/10/07 15:06:14 - mmengine - INFO - Epoch(train) [37][1520/2119] lr: 4.0000e-02 eta: 22:42:28 time: 0.3743 data_time: 0.0186 memory: 5826 grad_norm: 3.0097 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6939 loss: 2.6939 2022/10/07 15:06:20 - mmengine - INFO - Epoch(train) [37][1540/2119] lr: 4.0000e-02 eta: 22:42:18 time: 0.2942 data_time: 0.0222 memory: 5826 grad_norm: 3.0305 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5300 loss: 2.5300 2022/10/07 15:06:28 - mmengine - INFO - Epoch(train) [37][1560/2119] lr: 4.0000e-02 eta: 22:42:14 time: 0.3774 data_time: 0.0236 memory: 5826 grad_norm: 3.0856 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5811 loss: 2.5811 2022/10/07 15:06:34 - mmengine - INFO - Epoch(train) [37][1580/2119] lr: 4.0000e-02 eta: 22:42:06 time: 0.3201 data_time: 0.0269 memory: 5826 grad_norm: 3.0317 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6474 loss: 2.6474 2022/10/07 15:06:41 - mmengine - INFO - Epoch(train) [37][1600/2119] lr: 4.0000e-02 eta: 22:42:00 time: 0.3563 data_time: 0.0225 memory: 5826 grad_norm: 3.0133 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6732 loss: 2.6732 2022/10/07 15:06:48 - mmengine - INFO - Epoch(train) [37][1620/2119] lr: 4.0000e-02 eta: 22:41:53 time: 0.3355 data_time: 0.0165 memory: 5826 grad_norm: 3.0017 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8313 loss: 2.8313 2022/10/07 15:06:55 - mmengine - INFO - Epoch(train) [37][1640/2119] lr: 4.0000e-02 eta: 22:41:46 time: 0.3485 data_time: 0.0203 memory: 5826 grad_norm: 3.0450 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7320 loss: 2.7320 2022/10/07 15:07:02 - mmengine - INFO - Epoch(train) [37][1660/2119] lr: 4.0000e-02 eta: 22:41:39 time: 0.3250 data_time: 0.0240 memory: 5826 grad_norm: 3.0627 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8504 loss: 2.8504 2022/10/07 15:07:10 - mmengine - INFO - Epoch(train) [37][1680/2119] lr: 4.0000e-02 eta: 22:41:36 time: 0.4127 data_time: 0.0233 memory: 5826 grad_norm: 3.0346 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7438 loss: 2.7438 2022/10/07 15:07:17 - mmengine - INFO - Epoch(train) [37][1700/2119] lr: 4.0000e-02 eta: 22:41:29 time: 0.3370 data_time: 0.0260 memory: 5826 grad_norm: 3.0788 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7796 loss: 2.7796 2022/10/07 15:07:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 15:07:23 - mmengine - INFO - Epoch(train) [37][1720/2119] lr: 4.0000e-02 eta: 22:41:21 time: 0.3194 data_time: 0.0250 memory: 5826 grad_norm: 3.0520 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7119 loss: 2.7119 2022/10/07 15:07:30 - mmengine - INFO - Epoch(train) [37][1740/2119] lr: 4.0000e-02 eta: 22:41:14 time: 0.3348 data_time: 0.0255 memory: 5826 grad_norm: 3.1246 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7621 loss: 2.7621 2022/10/07 15:07:38 - mmengine - INFO - Epoch(train) [37][1760/2119] lr: 4.0000e-02 eta: 22:41:12 time: 0.4138 data_time: 0.0233 memory: 5826 grad_norm: 3.0363 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.7686 loss: 2.7686 2022/10/07 15:07:45 - mmengine - INFO - Epoch(train) [37][1780/2119] lr: 4.0000e-02 eta: 22:41:04 time: 0.3329 data_time: 0.0218 memory: 5826 grad_norm: 3.0514 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7644 loss: 2.7644 2022/10/07 15:07:52 - mmengine - INFO - Epoch(train) [37][1800/2119] lr: 4.0000e-02 eta: 22:40:58 time: 0.3464 data_time: 0.0226 memory: 5826 grad_norm: 3.0182 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6750 loss: 2.6750 2022/10/07 15:07:58 - mmengine - INFO - Epoch(train) [37][1820/2119] lr: 4.0000e-02 eta: 22:40:49 time: 0.3140 data_time: 0.0216 memory: 5826 grad_norm: 3.0780 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9091 loss: 2.9091 2022/10/07 15:08:05 - mmengine - INFO - Epoch(train) [37][1840/2119] lr: 4.0000e-02 eta: 22:40:45 time: 0.3822 data_time: 0.0270 memory: 5826 grad_norm: 3.0815 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8425 loss: 2.8425 2022/10/07 15:08:12 - mmengine - INFO - Epoch(train) [37][1860/2119] lr: 4.0000e-02 eta: 22:40:37 time: 0.3191 data_time: 0.0264 memory: 5826 grad_norm: 3.0591 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.7004 loss: 2.7004 2022/10/07 15:08:20 - mmengine - INFO - Epoch(train) [37][1880/2119] lr: 4.0000e-02 eta: 22:40:33 time: 0.3923 data_time: 0.0296 memory: 5826 grad_norm: 3.0632 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9151 loss: 2.9151 2022/10/07 15:08:27 - mmengine - INFO - Epoch(train) [37][1900/2119] lr: 4.0000e-02 eta: 22:40:27 time: 0.3466 data_time: 0.0224 memory: 5826 grad_norm: 3.0896 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8317 loss: 2.8317 2022/10/07 15:08:35 - mmengine - INFO - Epoch(train) [37][1920/2119] lr: 4.0000e-02 eta: 22:40:24 time: 0.4029 data_time: 0.0205 memory: 5826 grad_norm: 3.0403 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 3.0235 loss: 3.0235 2022/10/07 15:08:41 - mmengine - INFO - Epoch(train) [37][1940/2119] lr: 4.0000e-02 eta: 22:40:16 time: 0.3143 data_time: 0.0265 memory: 5826 grad_norm: 3.1167 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0348 loss: 3.0348 2022/10/07 15:08:49 - mmengine - INFO - Epoch(train) [37][1960/2119] lr: 4.0000e-02 eta: 22:40:11 time: 0.3790 data_time: 0.0223 memory: 5826 grad_norm: 3.0519 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6594 loss: 2.6594 2022/10/07 15:08:55 - mmengine - INFO - Epoch(train) [37][1980/2119] lr: 4.0000e-02 eta: 22:40:04 time: 0.3292 data_time: 0.0184 memory: 5826 grad_norm: 3.0909 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8989 loss: 2.8989 2022/10/07 15:09:03 - mmengine - INFO - Epoch(train) [37][2000/2119] lr: 4.0000e-02 eta: 22:39:59 time: 0.3820 data_time: 0.0187 memory: 5826 grad_norm: 3.0405 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7963 loss: 2.7963 2022/10/07 15:09:10 - mmengine - INFO - Epoch(train) [37][2020/2119] lr: 4.0000e-02 eta: 22:39:53 time: 0.3541 data_time: 0.0184 memory: 5826 grad_norm: 3.1065 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6508 loss: 2.6508 2022/10/07 15:09:17 - mmengine - INFO - Epoch(train) [37][2040/2119] lr: 4.0000e-02 eta: 22:39:48 time: 0.3657 data_time: 0.0222 memory: 5826 grad_norm: 3.1099 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9383 loss: 2.9383 2022/10/07 15:09:25 - mmengine - INFO - Epoch(train) [37][2060/2119] lr: 4.0000e-02 eta: 22:39:44 time: 0.3933 data_time: 0.0221 memory: 5826 grad_norm: 3.0676 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5471 loss: 2.5471 2022/10/07 15:09:32 - mmengine - INFO - Epoch(train) [37][2080/2119] lr: 4.0000e-02 eta: 22:39:39 time: 0.3708 data_time: 0.0227 memory: 5826 grad_norm: 3.0283 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9163 loss: 2.9163 2022/10/07 15:09:39 - mmengine - INFO - Epoch(train) [37][2100/2119] lr: 4.0000e-02 eta: 22:39:32 time: 0.3362 data_time: 0.0231 memory: 5826 grad_norm: 3.0376 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9709 loss: 2.9709 2022/10/07 15:09:45 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 15:09:45 - mmengine - INFO - Epoch(train) [37][2119/2119] lr: 4.0000e-02 eta: 22:39:32 time: 0.3148 data_time: 0.0210 memory: 5826 grad_norm: 3.0795 top1_acc: 0.2000 top5_acc: 0.5000 loss_cls: 2.9432 loss: 2.9432 2022/10/07 15:09:55 - mmengine - INFO - Epoch(train) [38][20/2119] lr: 4.0000e-02 eta: 22:39:09 time: 0.5062 data_time: 0.1316 memory: 5826 grad_norm: 3.0680 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6478 loss: 2.6478 2022/10/07 15:10:03 - mmengine - INFO - Epoch(train) [38][40/2119] lr: 4.0000e-02 eta: 22:39:04 time: 0.3556 data_time: 0.0218 memory: 5826 grad_norm: 3.0811 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.0384 loss: 3.0384 2022/10/07 15:10:10 - mmengine - INFO - Epoch(train) [38][60/2119] lr: 4.0000e-02 eta: 22:38:59 time: 0.3820 data_time: 0.0269 memory: 5826 grad_norm: 3.0197 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6355 loss: 2.6355 2022/10/07 15:10:17 - mmengine - INFO - Epoch(train) [38][80/2119] lr: 4.0000e-02 eta: 22:38:53 time: 0.3425 data_time: 0.0203 memory: 5826 grad_norm: 3.0373 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8755 loss: 2.8755 2022/10/07 15:10:26 - mmengine - INFO - Epoch(train) [38][100/2119] lr: 4.0000e-02 eta: 22:38:51 time: 0.4297 data_time: 0.0163 memory: 5826 grad_norm: 3.0371 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4692 loss: 2.4692 2022/10/07 15:10:34 - mmengine - INFO - Epoch(train) [38][120/2119] lr: 4.0000e-02 eta: 22:38:48 time: 0.3924 data_time: 0.0169 memory: 5826 grad_norm: 3.0924 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8043 loss: 2.8043 2022/10/07 15:10:42 - mmengine - INFO - Epoch(train) [38][140/2119] lr: 4.0000e-02 eta: 22:38:44 time: 0.4019 data_time: 0.0166 memory: 5826 grad_norm: 3.0729 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6152 loss: 2.6152 2022/10/07 15:10:48 - mmengine - INFO - Epoch(train) [38][160/2119] lr: 4.0000e-02 eta: 22:38:36 time: 0.3083 data_time: 0.0207 memory: 5826 grad_norm: 3.0972 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8198 loss: 2.8198 2022/10/07 15:10:55 - mmengine - INFO - Epoch(train) [38][180/2119] lr: 4.0000e-02 eta: 22:38:31 time: 0.3682 data_time: 0.0325 memory: 5826 grad_norm: 3.0834 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6938 loss: 2.6938 2022/10/07 15:11:02 - mmengine - INFO - Epoch(train) [38][200/2119] lr: 4.0000e-02 eta: 22:38:23 time: 0.3311 data_time: 0.0202 memory: 5826 grad_norm: 3.0450 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6206 loss: 2.6206 2022/10/07 15:11:09 - mmengine - INFO - Epoch(train) [38][220/2119] lr: 4.0000e-02 eta: 22:38:19 time: 0.3800 data_time: 0.0208 memory: 5826 grad_norm: 3.1216 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.8280 loss: 2.8280 2022/10/07 15:11:16 - mmengine - INFO - Epoch(train) [38][240/2119] lr: 4.0000e-02 eta: 22:38:12 time: 0.3357 data_time: 0.0203 memory: 5826 grad_norm: 3.0742 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6254 loss: 2.6254 2022/10/07 15:11:24 - mmengine - INFO - Epoch(train) [38][260/2119] lr: 4.0000e-02 eta: 22:38:09 time: 0.4047 data_time: 0.0203 memory: 5826 grad_norm: 3.0592 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7462 loss: 2.7462 2022/10/07 15:11:31 - mmengine - INFO - Epoch(train) [38][280/2119] lr: 4.0000e-02 eta: 22:38:01 time: 0.3243 data_time: 0.0277 memory: 5826 grad_norm: 3.0664 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8104 loss: 2.8104 2022/10/07 15:11:39 - mmengine - INFO - Epoch(train) [38][300/2119] lr: 4.0000e-02 eta: 22:37:59 time: 0.4231 data_time: 0.0189 memory: 5826 grad_norm: 3.1068 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9381 loss: 2.9381 2022/10/07 15:11:46 - mmengine - INFO - Epoch(train) [38][320/2119] lr: 4.0000e-02 eta: 22:37:52 time: 0.3429 data_time: 0.0242 memory: 5826 grad_norm: 3.0563 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8232 loss: 2.8232 2022/10/07 15:11:54 - mmengine - INFO - Epoch(train) [38][340/2119] lr: 4.0000e-02 eta: 22:37:51 time: 0.4256 data_time: 0.0274 memory: 5826 grad_norm: 3.0250 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7015 loss: 2.7015 2022/10/07 15:12:01 - mmengine - INFO - Epoch(train) [38][360/2119] lr: 4.0000e-02 eta: 22:37:42 time: 0.3175 data_time: 0.0194 memory: 5826 grad_norm: 3.0747 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8646 loss: 2.8646 2022/10/07 15:12:09 - mmengine - INFO - Epoch(train) [38][380/2119] lr: 4.0000e-02 eta: 22:37:39 time: 0.3973 data_time: 0.0176 memory: 5826 grad_norm: 2.9953 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7877 loss: 2.7877 2022/10/07 15:12:16 - mmengine - INFO - Epoch(train) [38][400/2119] lr: 4.0000e-02 eta: 22:37:34 time: 0.3611 data_time: 0.0208 memory: 5826 grad_norm: 3.0273 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6565 loss: 2.6565 2022/10/07 15:12:23 - mmengine - INFO - Epoch(train) [38][420/2119] lr: 4.0000e-02 eta: 22:37:26 time: 0.3326 data_time: 0.0240 memory: 5826 grad_norm: 3.0546 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6404 loss: 2.6404 2022/10/07 15:12:29 - mmengine - INFO - Epoch(train) [38][440/2119] lr: 4.0000e-02 eta: 22:37:19 time: 0.3365 data_time: 0.0218 memory: 5826 grad_norm: 3.1349 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9234 loss: 2.9234 2022/10/07 15:12:36 - mmengine - INFO - Epoch(train) [38][460/2119] lr: 4.0000e-02 eta: 22:37:13 time: 0.3474 data_time: 0.0237 memory: 5826 grad_norm: 3.0698 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7551 loss: 2.7551 2022/10/07 15:12:44 - mmengine - INFO - Epoch(train) [38][480/2119] lr: 4.0000e-02 eta: 22:37:09 time: 0.3892 data_time: 0.0242 memory: 5826 grad_norm: 3.0674 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7962 loss: 2.7962 2022/10/07 15:12:52 - mmengine - INFO - Epoch(train) [38][500/2119] lr: 4.0000e-02 eta: 22:37:06 time: 0.4053 data_time: 0.0244 memory: 5826 grad_norm: 3.0140 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7024 loss: 2.7024 2022/10/07 15:13:00 - mmengine - INFO - Epoch(train) [38][520/2119] lr: 4.0000e-02 eta: 22:37:01 time: 0.3718 data_time: 0.0238 memory: 5826 grad_norm: 3.0450 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6874 loss: 2.6874 2022/10/07 15:13:08 - mmengine - INFO - Epoch(train) [38][540/2119] lr: 4.0000e-02 eta: 22:36:57 time: 0.3945 data_time: 0.0233 memory: 5826 grad_norm: 3.1174 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7724 loss: 2.7724 2022/10/07 15:13:15 - mmengine - INFO - Epoch(train) [38][560/2119] lr: 4.0000e-02 eta: 22:36:54 time: 0.3906 data_time: 0.0271 memory: 5826 grad_norm: 3.0627 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9243 loss: 2.9243 2022/10/07 15:13:22 - mmengine - INFO - Epoch(train) [38][580/2119] lr: 4.0000e-02 eta: 22:36:47 time: 0.3385 data_time: 0.0189 memory: 5826 grad_norm: 3.0400 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6405 loss: 2.6405 2022/10/07 15:13:28 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 15:13:29 - mmengine - INFO - Epoch(train) [38][600/2119] lr: 4.0000e-02 eta: 22:36:40 time: 0.3419 data_time: 0.0229 memory: 5826 grad_norm: 3.0095 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5943 loss: 2.5943 2022/10/07 15:13:38 - mmengine - INFO - Epoch(train) [38][620/2119] lr: 4.0000e-02 eta: 22:36:41 time: 0.4691 data_time: 0.0297 memory: 5826 grad_norm: 3.0090 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7194 loss: 2.7194 2022/10/07 15:13:45 - mmengine - INFO - Epoch(train) [38][640/2119] lr: 4.0000e-02 eta: 22:36:33 time: 0.3168 data_time: 0.0200 memory: 5826 grad_norm: 2.9980 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8130 loss: 2.8130 2022/10/07 15:13:54 - mmengine - INFO - Epoch(train) [38][660/2119] lr: 4.0000e-02 eta: 22:36:34 time: 0.4729 data_time: 0.0248 memory: 5826 grad_norm: 3.0587 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7861 loss: 2.7861 2022/10/07 15:14:01 - mmengine - INFO - Epoch(train) [38][680/2119] lr: 4.0000e-02 eta: 22:36:26 time: 0.3316 data_time: 0.0251 memory: 5826 grad_norm: 3.0602 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6349 loss: 2.6349 2022/10/07 15:14:08 - mmengine - INFO - Epoch(train) [38][700/2119] lr: 4.0000e-02 eta: 22:36:22 time: 0.3819 data_time: 0.0261 memory: 5826 grad_norm: 3.0439 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6932 loss: 2.6932 2022/10/07 15:14:15 - mmengine - INFO - Epoch(train) [38][720/2119] lr: 4.0000e-02 eta: 22:36:15 time: 0.3436 data_time: 0.0207 memory: 5826 grad_norm: 2.9956 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8628 loss: 2.8628 2022/10/07 15:14:24 - mmengine - INFO - Epoch(train) [38][740/2119] lr: 4.0000e-02 eta: 22:36:13 time: 0.4195 data_time: 0.0188 memory: 5826 grad_norm: 3.0686 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7899 loss: 2.7899 2022/10/07 15:14:30 - mmengine - INFO - Epoch(train) [38][760/2119] lr: 4.0000e-02 eta: 22:36:04 time: 0.2956 data_time: 0.0226 memory: 5826 grad_norm: 3.0953 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7906 loss: 2.7906 2022/10/07 15:14:37 - mmengine - INFO - Epoch(train) [38][780/2119] lr: 4.0000e-02 eta: 22:35:58 time: 0.3611 data_time: 0.0229 memory: 5826 grad_norm: 3.0496 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8854 loss: 2.8854 2022/10/07 15:14:43 - mmengine - INFO - Epoch(train) [38][800/2119] lr: 4.0000e-02 eta: 22:35:50 time: 0.3160 data_time: 0.0226 memory: 5826 grad_norm: 3.0823 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9634 loss: 2.9634 2022/10/07 15:14:50 - mmengine - INFO - Epoch(train) [38][820/2119] lr: 4.0000e-02 eta: 22:35:42 time: 0.3197 data_time: 0.0228 memory: 5826 grad_norm: 3.0143 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7296 loss: 2.7296 2022/10/07 15:14:57 - mmengine - INFO - Epoch(train) [38][840/2119] lr: 4.0000e-02 eta: 22:35:36 time: 0.3515 data_time: 0.0204 memory: 5826 grad_norm: 3.0493 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7549 loss: 2.7549 2022/10/07 15:15:03 - mmengine - INFO - Epoch(train) [38][860/2119] lr: 4.0000e-02 eta: 22:35:28 time: 0.3239 data_time: 0.0225 memory: 5826 grad_norm: 3.1283 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9690 loss: 2.9690 2022/10/07 15:15:10 - mmengine - INFO - Epoch(train) [38][880/2119] lr: 4.0000e-02 eta: 22:35:20 time: 0.3240 data_time: 0.0235 memory: 5826 grad_norm: 3.0736 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7900 loss: 2.7900 2022/10/07 15:15:17 - mmengine - INFO - Epoch(train) [38][900/2119] lr: 4.0000e-02 eta: 22:35:16 time: 0.3887 data_time: 0.0155 memory: 5826 grad_norm: 3.0403 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9206 loss: 2.9206 2022/10/07 15:15:24 - mmengine - INFO - Epoch(train) [38][920/2119] lr: 4.0000e-02 eta: 22:35:08 time: 0.3227 data_time: 0.0266 memory: 5826 grad_norm: 3.0637 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7005 loss: 2.7005 2022/10/07 15:15:30 - mmengine - INFO - Epoch(train) [38][940/2119] lr: 4.0000e-02 eta: 22:35:01 time: 0.3354 data_time: 0.0222 memory: 5826 grad_norm: 3.0756 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7770 loss: 2.7770 2022/10/07 15:15:37 - mmengine - INFO - Epoch(train) [38][960/2119] lr: 4.0000e-02 eta: 22:34:55 time: 0.3492 data_time: 0.0358 memory: 5826 grad_norm: 3.0034 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8516 loss: 2.8516 2022/10/07 15:15:45 - mmengine - INFO - Epoch(train) [38][980/2119] lr: 4.0000e-02 eta: 22:34:51 time: 0.3881 data_time: 0.0215 memory: 5826 grad_norm: 3.0622 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0805 loss: 3.0805 2022/10/07 15:15:51 - mmengine - INFO - Epoch(train) [38][1000/2119] lr: 4.0000e-02 eta: 22:34:41 time: 0.2872 data_time: 0.0238 memory: 5826 grad_norm: 3.1087 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9977 loss: 2.9977 2022/10/07 15:15:59 - mmengine - INFO - Epoch(train) [38][1020/2119] lr: 4.0000e-02 eta: 22:34:38 time: 0.4124 data_time: 0.0207 memory: 5826 grad_norm: 3.0783 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6159 loss: 2.6159 2022/10/07 15:16:06 - mmengine - INFO - Epoch(train) [38][1040/2119] lr: 4.0000e-02 eta: 22:34:31 time: 0.3315 data_time: 0.0205 memory: 5826 grad_norm: 3.1052 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8357 loss: 2.8357 2022/10/07 15:16:13 - mmengine - INFO - Epoch(train) [38][1060/2119] lr: 4.0000e-02 eta: 22:34:26 time: 0.3705 data_time: 0.0194 memory: 5826 grad_norm: 3.0676 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8166 loss: 2.8166 2022/10/07 15:16:20 - mmengine - INFO - Epoch(train) [38][1080/2119] lr: 4.0000e-02 eta: 22:34:17 time: 0.3125 data_time: 0.0203 memory: 5826 grad_norm: 3.0748 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0998 loss: 3.0998 2022/10/07 15:16:26 - mmengine - INFO - Epoch(train) [38][1100/2119] lr: 4.0000e-02 eta: 22:34:11 time: 0.3477 data_time: 0.0232 memory: 5826 grad_norm: 3.0111 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8278 loss: 2.8278 2022/10/07 15:16:33 - mmengine - INFO - Epoch(train) [38][1120/2119] lr: 4.0000e-02 eta: 22:34:03 time: 0.3187 data_time: 0.0220 memory: 5826 grad_norm: 3.0671 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6307 loss: 2.6307 2022/10/07 15:16:39 - mmengine - INFO - Epoch(train) [38][1140/2119] lr: 4.0000e-02 eta: 22:33:54 time: 0.3096 data_time: 0.0190 memory: 5826 grad_norm: 3.1012 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.0275 loss: 3.0275 2022/10/07 15:16:46 - mmengine - INFO - Epoch(train) [38][1160/2119] lr: 4.0000e-02 eta: 22:33:48 time: 0.3526 data_time: 0.0260 memory: 5826 grad_norm: 3.0811 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.4598 loss: 2.4598 2022/10/07 15:16:53 - mmengine - INFO - Epoch(train) [38][1180/2119] lr: 4.0000e-02 eta: 22:33:40 time: 0.3234 data_time: 0.0255 memory: 5826 grad_norm: 3.0959 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6690 loss: 2.6690 2022/10/07 15:16:59 - mmengine - INFO - Epoch(train) [38][1200/2119] lr: 4.0000e-02 eta: 22:33:33 time: 0.3437 data_time: 0.0216 memory: 5826 grad_norm: 3.0541 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8335 loss: 2.8335 2022/10/07 15:17:06 - mmengine - INFO - Epoch(train) [38][1220/2119] lr: 4.0000e-02 eta: 22:33:26 time: 0.3282 data_time: 0.0163 memory: 5826 grad_norm: 3.0127 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7740 loss: 2.7740 2022/10/07 15:17:13 - mmengine - INFO - Epoch(train) [38][1240/2119] lr: 4.0000e-02 eta: 22:33:18 time: 0.3296 data_time: 0.0206 memory: 5826 grad_norm: 3.1223 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9988 loss: 2.9988 2022/10/07 15:17:20 - mmengine - INFO - Epoch(train) [38][1260/2119] lr: 4.0000e-02 eta: 22:33:13 time: 0.3702 data_time: 0.0208 memory: 5826 grad_norm: 3.0544 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7143 loss: 2.7143 2022/10/07 15:17:26 - mmengine - INFO - Epoch(train) [38][1280/2119] lr: 4.0000e-02 eta: 22:33:04 time: 0.3070 data_time: 0.0296 memory: 5826 grad_norm: 3.0910 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8882 loss: 2.8882 2022/10/07 15:17:32 - mmengine - INFO - Epoch(train) [38][1300/2119] lr: 4.0000e-02 eta: 22:32:56 time: 0.3108 data_time: 0.0202 memory: 5826 grad_norm: 3.0496 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7424 loss: 2.7424 2022/10/07 15:17:40 - mmengine - INFO - Epoch(train) [38][1320/2119] lr: 4.0000e-02 eta: 22:32:51 time: 0.3702 data_time: 0.0218 memory: 5826 grad_norm: 3.0759 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5386 loss: 2.5386 2022/10/07 15:17:46 - mmengine - INFO - Epoch(train) [38][1340/2119] lr: 4.0000e-02 eta: 22:32:43 time: 0.3206 data_time: 0.0240 memory: 5826 grad_norm: 3.0608 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7437 loss: 2.7437 2022/10/07 15:17:53 - mmengine - INFO - Epoch(train) [38][1360/2119] lr: 4.0000e-02 eta: 22:32:35 time: 0.3363 data_time: 0.0248 memory: 5826 grad_norm: 3.0029 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7397 loss: 2.7397 2022/10/07 15:18:00 - mmengine - INFO - Epoch(train) [38][1380/2119] lr: 4.0000e-02 eta: 22:32:29 time: 0.3427 data_time: 0.0217 memory: 5826 grad_norm: 3.0663 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8861 loss: 2.8861 2022/10/07 15:18:07 - mmengine - INFO - Epoch(train) [38][1400/2119] lr: 4.0000e-02 eta: 22:32:23 time: 0.3635 data_time: 0.0262 memory: 5826 grad_norm: 3.0642 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7070 loss: 2.7070 2022/10/07 15:18:13 - mmengine - INFO - Epoch(train) [38][1420/2119] lr: 4.0000e-02 eta: 22:32:14 time: 0.2981 data_time: 0.0245 memory: 5826 grad_norm: 3.0559 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7788 loss: 2.7788 2022/10/07 15:18:21 - mmengine - INFO - Epoch(train) [38][1440/2119] lr: 4.0000e-02 eta: 22:32:09 time: 0.3777 data_time: 0.0312 memory: 5826 grad_norm: 3.0982 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8156 loss: 2.8156 2022/10/07 15:18:27 - mmengine - INFO - Epoch(train) [38][1460/2119] lr: 4.0000e-02 eta: 22:32:02 time: 0.3278 data_time: 0.0216 memory: 5826 grad_norm: 3.0761 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0583 loss: 3.0583 2022/10/07 15:18:34 - mmengine - INFO - Epoch(train) [38][1480/2119] lr: 4.0000e-02 eta: 22:31:54 time: 0.3244 data_time: 0.0233 memory: 5826 grad_norm: 3.1073 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7438 loss: 2.7438 2022/10/07 15:18:42 - mmengine - INFO - Epoch(train) [38][1500/2119] lr: 4.0000e-02 eta: 22:31:51 time: 0.4052 data_time: 0.0290 memory: 5826 grad_norm: 3.0651 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6356 loss: 2.6356 2022/10/07 15:18:48 - mmengine - INFO - Epoch(train) [38][1520/2119] lr: 4.0000e-02 eta: 22:31:42 time: 0.3020 data_time: 0.0255 memory: 5826 grad_norm: 3.0905 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7462 loss: 2.7462 2022/10/07 15:18:55 - mmengine - INFO - Epoch(train) [38][1540/2119] lr: 4.0000e-02 eta: 22:31:37 time: 0.3764 data_time: 0.0288 memory: 5826 grad_norm: 3.1061 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9130 loss: 2.9130 2022/10/07 15:19:01 - mmengine - INFO - Epoch(train) [38][1560/2119] lr: 4.0000e-02 eta: 22:31:28 time: 0.3045 data_time: 0.0240 memory: 5826 grad_norm: 3.0485 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6016 loss: 2.6016 2022/10/07 15:19:09 - mmengine - INFO - Epoch(train) [38][1580/2119] lr: 4.0000e-02 eta: 22:31:23 time: 0.3709 data_time: 0.0262 memory: 5826 grad_norm: 3.0209 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9282 loss: 2.9282 2022/10/07 15:19:15 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 15:19:15 - mmengine - INFO - Epoch(train) [38][1600/2119] lr: 4.0000e-02 eta: 22:31:16 time: 0.3299 data_time: 0.0269 memory: 5826 grad_norm: 3.0711 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5137 loss: 2.5137 2022/10/07 15:19:23 - mmengine - INFO - Epoch(train) [38][1620/2119] lr: 4.0000e-02 eta: 22:31:11 time: 0.3724 data_time: 0.0189 memory: 5826 grad_norm: 3.0763 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8465 loss: 2.8465 2022/10/07 15:19:29 - mmengine - INFO - Epoch(train) [38][1640/2119] lr: 4.0000e-02 eta: 22:31:03 time: 0.3254 data_time: 0.0444 memory: 5826 grad_norm: 3.0883 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6559 loss: 2.6559 2022/10/07 15:19:46 - mmengine - INFO - Epoch(train) [38][1660/2119] lr: 4.0000e-02 eta: 22:31:26 time: 0.8458 data_time: 0.0289 memory: 5826 grad_norm: 3.0603 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6351 loss: 2.6351 2022/10/07 15:19:52 - mmengine - INFO - Epoch(train) [38][1680/2119] lr: 4.0000e-02 eta: 22:31:17 time: 0.2977 data_time: 0.0247 memory: 5826 grad_norm: 3.0620 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7609 loss: 2.7609 2022/10/07 15:20:00 - mmengine - INFO - Epoch(train) [38][1700/2119] lr: 4.0000e-02 eta: 22:31:12 time: 0.3733 data_time: 0.0211 memory: 5826 grad_norm: 3.0287 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8770 loss: 2.8770 2022/10/07 15:20:08 - mmengine - INFO - Epoch(train) [38][1720/2119] lr: 4.0000e-02 eta: 22:31:09 time: 0.4082 data_time: 0.0248 memory: 5826 grad_norm: 3.0480 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7050 loss: 2.7050 2022/10/07 15:20:16 - mmengine - INFO - Epoch(train) [38][1740/2119] lr: 4.0000e-02 eta: 22:31:05 time: 0.3938 data_time: 0.0216 memory: 5826 grad_norm: 3.1269 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5536 loss: 2.5536 2022/10/07 15:20:22 - mmengine - INFO - Epoch(train) [38][1760/2119] lr: 4.0000e-02 eta: 22:30:57 time: 0.3223 data_time: 0.0194 memory: 5826 grad_norm: 3.0897 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9044 loss: 2.9044 2022/10/07 15:20:29 - mmengine - INFO - Epoch(train) [38][1780/2119] lr: 4.0000e-02 eta: 22:30:51 time: 0.3463 data_time: 0.0237 memory: 5826 grad_norm: 3.0828 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8261 loss: 2.8261 2022/10/07 15:20:37 - mmengine - INFO - Epoch(train) [38][1800/2119] lr: 4.0000e-02 eta: 22:30:47 time: 0.3930 data_time: 0.0249 memory: 5826 grad_norm: 3.0496 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9549 loss: 2.9549 2022/10/07 15:20:43 - mmengine - INFO - Epoch(train) [38][1820/2119] lr: 4.0000e-02 eta: 22:30:38 time: 0.3039 data_time: 0.0228 memory: 5826 grad_norm: 3.0132 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8250 loss: 2.8250 2022/10/07 15:20:50 - mmengine - INFO - Epoch(train) [38][1840/2119] lr: 4.0000e-02 eta: 22:30:33 time: 0.3645 data_time: 0.0257 memory: 5826 grad_norm: 3.0298 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 3.0071 loss: 3.0071 2022/10/07 15:21:02 - mmengine - INFO - Epoch(train) [38][1860/2119] lr: 4.0000e-02 eta: 22:30:40 time: 0.5879 data_time: 0.0243 memory: 5826 grad_norm: 3.1010 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.8223 loss: 2.8223 2022/10/07 15:21:08 - mmengine - INFO - Epoch(train) [38][1880/2119] lr: 4.0000e-02 eta: 22:30:31 time: 0.3006 data_time: 0.0255 memory: 5826 grad_norm: 3.1016 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9349 loss: 2.9349 2022/10/07 15:21:19 - mmengine - INFO - Epoch(train) [38][1900/2119] lr: 4.0000e-02 eta: 22:30:37 time: 0.5479 data_time: 0.0242 memory: 5826 grad_norm: 3.0109 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.9184 loss: 2.9184 2022/10/07 15:21:24 - mmengine - INFO - Epoch(train) [38][1920/2119] lr: 4.0000e-02 eta: 22:30:25 time: 0.2535 data_time: 0.0210 memory: 5826 grad_norm: 3.0079 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8558 loss: 2.8558 2022/10/07 15:21:32 - mmengine - INFO - Epoch(train) [38][1940/2119] lr: 4.0000e-02 eta: 22:30:20 time: 0.3743 data_time: 0.0249 memory: 5826 grad_norm: 3.0594 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7937 loss: 2.7937 2022/10/07 15:21:39 - mmengine - INFO - Epoch(train) [38][1960/2119] lr: 4.0000e-02 eta: 22:30:13 time: 0.3474 data_time: 0.0253 memory: 5826 grad_norm: 3.0765 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6999 loss: 2.6999 2022/10/07 15:21:45 - mmengine - INFO - Epoch(train) [38][1980/2119] lr: 4.0000e-02 eta: 22:30:06 time: 0.3262 data_time: 0.0235 memory: 5826 grad_norm: 3.0876 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8399 loss: 2.8399 2022/10/07 15:21:51 - mmengine - INFO - Epoch(train) [38][2000/2119] lr: 4.0000e-02 eta: 22:29:57 time: 0.3090 data_time: 0.0211 memory: 5826 grad_norm: 2.9837 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7120 loss: 2.7120 2022/10/07 15:22:01 - mmengine - INFO - Epoch(train) [38][2020/2119] lr: 4.0000e-02 eta: 22:29:58 time: 0.4715 data_time: 0.0196 memory: 5826 grad_norm: 3.1016 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5342 loss: 2.5342 2022/10/07 15:22:07 - mmengine - INFO - Epoch(train) [38][2040/2119] lr: 4.0000e-02 eta: 22:29:48 time: 0.2874 data_time: 0.0232 memory: 5826 grad_norm: 3.0661 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0541 loss: 3.0541 2022/10/07 15:22:13 - mmengine - INFO - Epoch(train) [38][2060/2119] lr: 4.0000e-02 eta: 22:29:41 time: 0.3346 data_time: 0.0248 memory: 5826 grad_norm: 3.0604 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.4110 loss: 2.4110 2022/10/07 15:22:23 - mmengine - INFO - Epoch(train) [38][2080/2119] lr: 4.0000e-02 eta: 22:29:42 time: 0.4830 data_time: 0.0235 memory: 5826 grad_norm: 3.0030 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.8934 loss: 2.8934 2022/10/07 15:22:29 - mmengine - INFO - Epoch(train) [38][2100/2119] lr: 4.0000e-02 eta: 22:29:34 time: 0.3181 data_time: 0.0253 memory: 5826 grad_norm: 3.0608 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7405 loss: 2.7405 2022/10/07 15:22:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 15:22:38 - mmengine - INFO - Epoch(train) [38][2119/2119] lr: 4.0000e-02 eta: 22:29:34 time: 0.4627 data_time: 0.0264 memory: 5826 grad_norm: 3.0585 top1_acc: 0.4000 top5_acc: 0.7000 loss_cls: 2.8681 loss: 2.8681 2022/10/07 15:22:51 - mmengine - INFO - Epoch(train) [39][20/2119] lr: 4.0000e-02 eta: 22:29:18 time: 0.6184 data_time: 0.1077 memory: 5826 grad_norm: 3.0245 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8886 loss: 2.8886 2022/10/07 15:23:01 - mmengine - INFO - Epoch(train) [39][40/2119] lr: 4.0000e-02 eta: 22:29:20 time: 0.4982 data_time: 0.0282 memory: 5826 grad_norm: 3.1308 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8971 loss: 2.8971 2022/10/07 15:23:07 - mmengine - INFO - Epoch(train) [39][60/2119] lr: 4.0000e-02 eta: 22:29:11 time: 0.2977 data_time: 0.0254 memory: 5826 grad_norm: 3.0826 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7419 loss: 2.7419 2022/10/07 15:23:13 - mmengine - INFO - Epoch(train) [39][80/2119] lr: 4.0000e-02 eta: 22:29:04 time: 0.3351 data_time: 0.0212 memory: 5826 grad_norm: 3.0220 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9944 loss: 2.9944 2022/10/07 15:23:20 - mmengine - INFO - Epoch(train) [39][100/2119] lr: 4.0000e-02 eta: 22:28:58 time: 0.3542 data_time: 0.0191 memory: 5826 grad_norm: 3.0271 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7447 loss: 2.7447 2022/10/07 15:23:27 - mmengine - INFO - Epoch(train) [39][120/2119] lr: 4.0000e-02 eta: 22:28:50 time: 0.3327 data_time: 0.0241 memory: 5826 grad_norm: 3.0442 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6741 loss: 2.6741 2022/10/07 15:23:35 - mmengine - INFO - Epoch(train) [39][140/2119] lr: 4.0000e-02 eta: 22:28:45 time: 0.3687 data_time: 0.0206 memory: 5826 grad_norm: 3.0948 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8951 loss: 2.8951 2022/10/07 15:23:41 - mmengine - INFO - Epoch(train) [39][160/2119] lr: 4.0000e-02 eta: 22:28:36 time: 0.3077 data_time: 0.0275 memory: 5826 grad_norm: 3.0204 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7060 loss: 2.7060 2022/10/07 15:23:47 - mmengine - INFO - Epoch(train) [39][180/2119] lr: 4.0000e-02 eta: 22:28:29 time: 0.3371 data_time: 0.0252 memory: 5826 grad_norm: 3.0369 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.5819 loss: 2.5819 2022/10/07 15:23:55 - mmengine - INFO - Epoch(train) [39][200/2119] lr: 4.0000e-02 eta: 22:28:26 time: 0.4040 data_time: 0.0216 memory: 5826 grad_norm: 2.9927 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6629 loss: 2.6629 2022/10/07 15:24:02 - mmengine - INFO - Epoch(train) [39][220/2119] lr: 4.0000e-02 eta: 22:28:19 time: 0.3376 data_time: 0.0167 memory: 5826 grad_norm: 3.0713 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7010 loss: 2.7010 2022/10/07 15:24:09 - mmengine - INFO - Epoch(train) [39][240/2119] lr: 4.0000e-02 eta: 22:28:12 time: 0.3313 data_time: 0.0219 memory: 5826 grad_norm: 3.1112 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6236 loss: 2.6236 2022/10/07 15:24:15 - mmengine - INFO - Epoch(train) [39][260/2119] lr: 4.0000e-02 eta: 22:28:03 time: 0.3162 data_time: 0.0191 memory: 5826 grad_norm: 3.0290 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8270 loss: 2.8270 2022/10/07 15:24:22 - mmengine - INFO - Epoch(train) [39][280/2119] lr: 4.0000e-02 eta: 22:27:56 time: 0.3379 data_time: 0.0187 memory: 5826 grad_norm: 3.0224 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.5736 loss: 2.5736 2022/10/07 15:24:29 - mmengine - INFO - Epoch(train) [39][300/2119] lr: 4.0000e-02 eta: 22:27:51 time: 0.3684 data_time: 0.0217 memory: 5826 grad_norm: 3.0535 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6505 loss: 2.6505 2022/10/07 15:24:36 - mmengine - INFO - Epoch(train) [39][320/2119] lr: 4.0000e-02 eta: 22:27:44 time: 0.3354 data_time: 0.0192 memory: 5826 grad_norm: 3.0797 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8856 loss: 2.8856 2022/10/07 15:24:44 - mmengine - INFO - Epoch(train) [39][340/2119] lr: 4.0000e-02 eta: 22:27:40 time: 0.3837 data_time: 0.0231 memory: 5826 grad_norm: 3.0298 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7021 loss: 2.7021 2022/10/07 15:24:50 - mmengine - INFO - Epoch(train) [39][360/2119] lr: 4.0000e-02 eta: 22:27:32 time: 0.3313 data_time: 0.0176 memory: 5826 grad_norm: 3.1155 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6609 loss: 2.6609 2022/10/07 15:24:58 - mmengine - INFO - Epoch(train) [39][380/2119] lr: 4.0000e-02 eta: 22:27:29 time: 0.3994 data_time: 0.0214 memory: 5826 grad_norm: 3.0636 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5434 loss: 2.5434 2022/10/07 15:25:04 - mmengine - INFO - Epoch(train) [39][400/2119] lr: 4.0000e-02 eta: 22:27:19 time: 0.2879 data_time: 0.0237 memory: 5826 grad_norm: 3.0265 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 3.0518 loss: 3.0518 2022/10/07 15:25:10 - mmengine - INFO - Epoch(train) [39][420/2119] lr: 4.0000e-02 eta: 22:27:11 time: 0.3167 data_time: 0.0291 memory: 5826 grad_norm: 3.0528 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6679 loss: 2.6679 2022/10/07 15:25:17 - mmengine - INFO - Epoch(train) [39][440/2119] lr: 4.0000e-02 eta: 22:27:04 time: 0.3366 data_time: 0.0176 memory: 5826 grad_norm: 3.1073 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.5537 loss: 2.5537 2022/10/07 15:25:24 - mmengine - INFO - Epoch(train) [39][460/2119] lr: 4.0000e-02 eta: 22:26:57 time: 0.3456 data_time: 0.0233 memory: 5826 grad_norm: 3.0852 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7174 loss: 2.7174 2022/10/07 15:25:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 15:25:31 - mmengine - INFO - Epoch(train) [39][480/2119] lr: 4.0000e-02 eta: 22:26:49 time: 0.3291 data_time: 0.0237 memory: 5826 grad_norm: 3.0631 top1_acc: 0.3125 top5_acc: 0.8750 loss_cls: 2.8601 loss: 2.8601 2022/10/07 15:25:38 - mmengine - INFO - Epoch(train) [39][500/2119] lr: 4.0000e-02 eta: 22:26:44 time: 0.3710 data_time: 0.0227 memory: 5826 grad_norm: 3.0994 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8087 loss: 2.8087 2022/10/07 15:25:45 - mmengine - INFO - Epoch(train) [39][520/2119] lr: 4.0000e-02 eta: 22:26:38 time: 0.3430 data_time: 0.0197 memory: 5826 grad_norm: 3.0755 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8661 loss: 2.8661 2022/10/07 15:25:53 - mmengine - INFO - Epoch(train) [39][540/2119] lr: 4.0000e-02 eta: 22:26:33 time: 0.3812 data_time: 0.0223 memory: 5826 grad_norm: 3.0848 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7890 loss: 2.7890 2022/10/07 15:25:59 - mmengine - INFO - Epoch(train) [39][560/2119] lr: 4.0000e-02 eta: 22:26:25 time: 0.3148 data_time: 0.0219 memory: 5826 grad_norm: 3.1252 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9178 loss: 2.9178 2022/10/07 15:26:06 - mmengine - INFO - Epoch(train) [39][580/2119] lr: 4.0000e-02 eta: 22:26:20 time: 0.3688 data_time: 0.0306 memory: 5826 grad_norm: 3.0806 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8909 loss: 2.8909 2022/10/07 15:26:12 - mmengine - INFO - Epoch(train) [39][600/2119] lr: 4.0000e-02 eta: 22:26:10 time: 0.2881 data_time: 0.0206 memory: 5826 grad_norm: 3.0903 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7948 loss: 2.7948 2022/10/07 15:26:19 - mmengine - INFO - Epoch(train) [39][620/2119] lr: 4.0000e-02 eta: 22:26:04 time: 0.3614 data_time: 0.0193 memory: 5826 grad_norm: 3.0468 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8566 loss: 2.8566 2022/10/07 15:26:26 - mmengine - INFO - Epoch(train) [39][640/2119] lr: 4.0000e-02 eta: 22:25:56 time: 0.3243 data_time: 0.0172 memory: 5826 grad_norm: 3.1032 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7813 loss: 2.7813 2022/10/07 15:26:33 - mmengine - INFO - Epoch(train) [39][660/2119] lr: 4.0000e-02 eta: 22:25:50 time: 0.3459 data_time: 0.0228 memory: 5826 grad_norm: 3.0360 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7436 loss: 2.7436 2022/10/07 15:26:39 - mmengine - INFO - Epoch(train) [39][680/2119] lr: 4.0000e-02 eta: 22:25:43 time: 0.3384 data_time: 0.0227 memory: 5826 grad_norm: 3.0718 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.4921 loss: 2.4921 2022/10/07 15:26:47 - mmengine - INFO - Epoch(train) [39][700/2119] lr: 4.0000e-02 eta: 22:25:38 time: 0.3856 data_time: 0.0197 memory: 5826 grad_norm: 3.0739 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6260 loss: 2.6260 2022/10/07 15:26:53 - mmengine - INFO - Epoch(train) [39][720/2119] lr: 4.0000e-02 eta: 22:25:30 time: 0.3156 data_time: 0.0189 memory: 5826 grad_norm: 3.0114 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7120 loss: 2.7120 2022/10/07 15:27:00 - mmengine - INFO - Epoch(train) [39][740/2119] lr: 4.0000e-02 eta: 22:25:23 time: 0.3296 data_time: 0.0167 memory: 5826 grad_norm: 3.0835 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9463 loss: 2.9463 2022/10/07 15:27:06 - mmengine - INFO - Epoch(train) [39][760/2119] lr: 4.0000e-02 eta: 22:25:14 time: 0.3168 data_time: 0.0269 memory: 5826 grad_norm: 3.0628 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6840 loss: 2.6840 2022/10/07 15:27:13 - mmengine - INFO - Epoch(train) [39][780/2119] lr: 4.0000e-02 eta: 22:25:08 time: 0.3409 data_time: 0.0232 memory: 5826 grad_norm: 3.0351 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7268 loss: 2.7268 2022/10/07 15:27:20 - mmengine - INFO - Epoch(train) [39][800/2119] lr: 4.0000e-02 eta: 22:25:01 time: 0.3398 data_time: 0.0182 memory: 5826 grad_norm: 3.0117 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6826 loss: 2.6826 2022/10/07 15:27:27 - mmengine - INFO - Epoch(train) [39][820/2119] lr: 4.0000e-02 eta: 22:24:53 time: 0.3292 data_time: 0.0191 memory: 5826 grad_norm: 3.1355 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8183 loss: 2.8183 2022/10/07 15:27:34 - mmengine - INFO - Epoch(train) [39][840/2119] lr: 4.0000e-02 eta: 22:24:48 time: 0.3724 data_time: 0.0215 memory: 5826 grad_norm: 3.0257 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7203 loss: 2.7203 2022/10/07 15:27:41 - mmengine - INFO - Epoch(train) [39][860/2119] lr: 4.0000e-02 eta: 22:24:41 time: 0.3319 data_time: 0.0228 memory: 5826 grad_norm: 3.0341 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8377 loss: 2.8377 2022/10/07 15:27:48 - mmengine - INFO - Epoch(train) [39][880/2119] lr: 4.0000e-02 eta: 22:24:36 time: 0.3702 data_time: 0.0255 memory: 5826 grad_norm: 3.0878 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6463 loss: 2.6463 2022/10/07 15:27:54 - mmengine - INFO - Epoch(train) [39][900/2119] lr: 4.0000e-02 eta: 22:24:27 time: 0.3063 data_time: 0.0243 memory: 5826 grad_norm: 3.0588 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7120 loss: 2.7120 2022/10/07 15:28:01 - mmengine - INFO - Epoch(train) [39][920/2119] lr: 4.0000e-02 eta: 22:24:21 time: 0.3611 data_time: 0.0221 memory: 5826 grad_norm: 3.1029 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8409 loss: 2.8409 2022/10/07 15:28:08 - mmengine - INFO - Epoch(train) [39][940/2119] lr: 4.0000e-02 eta: 22:24:13 time: 0.3212 data_time: 0.0241 memory: 5826 grad_norm: 3.0816 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9073 loss: 2.9073 2022/10/07 15:28:15 - mmengine - INFO - Epoch(train) [39][960/2119] lr: 4.0000e-02 eta: 22:24:07 time: 0.3527 data_time: 0.0239 memory: 5826 grad_norm: 3.0798 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7388 loss: 2.7388 2022/10/07 15:28:23 - mmengine - INFO - Epoch(train) [39][980/2119] lr: 4.0000e-02 eta: 22:24:03 time: 0.3950 data_time: 0.0281 memory: 5826 grad_norm: 3.0322 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7600 loss: 2.7600 2022/10/07 15:28:30 - mmengine - INFO - Epoch(train) [39][1000/2119] lr: 4.0000e-02 eta: 22:23:56 time: 0.3384 data_time: 0.0173 memory: 5826 grad_norm: 3.0492 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5152 loss: 2.5152 2022/10/07 15:28:37 - mmengine - INFO - Epoch(train) [39][1020/2119] lr: 4.0000e-02 eta: 22:23:51 time: 0.3706 data_time: 0.0227 memory: 5826 grad_norm: 3.0648 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7367 loss: 2.7367 2022/10/07 15:28:43 - mmengine - INFO - Epoch(train) [39][1040/2119] lr: 4.0000e-02 eta: 22:23:42 time: 0.3088 data_time: 0.0243 memory: 5826 grad_norm: 3.0201 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5789 loss: 2.5789 2022/10/07 15:28:50 - mmengine - INFO - Epoch(train) [39][1060/2119] lr: 4.0000e-02 eta: 22:23:37 time: 0.3644 data_time: 0.0241 memory: 5826 grad_norm: 3.0307 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6598 loss: 2.6598 2022/10/07 15:28:57 - mmengine - INFO - Epoch(train) [39][1080/2119] lr: 4.0000e-02 eta: 22:23:30 time: 0.3440 data_time: 0.0167 memory: 5826 grad_norm: 3.0924 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8455 loss: 2.8455 2022/10/07 15:29:04 - mmengine - INFO - Epoch(train) [39][1100/2119] lr: 4.0000e-02 eta: 22:23:24 time: 0.3506 data_time: 0.0191 memory: 5826 grad_norm: 3.0786 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8160 loss: 2.8160 2022/10/07 15:29:12 - mmengine - INFO - Epoch(train) [39][1120/2119] lr: 4.0000e-02 eta: 22:23:19 time: 0.3660 data_time: 0.0216 memory: 5826 grad_norm: 3.0216 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7967 loss: 2.7967 2022/10/07 15:29:19 - mmengine - INFO - Epoch(train) [39][1140/2119] lr: 4.0000e-02 eta: 22:23:13 time: 0.3590 data_time: 0.0241 memory: 5826 grad_norm: 3.0202 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8075 loss: 2.8075 2022/10/07 15:29:26 - mmengine - INFO - Epoch(train) [39][1160/2119] lr: 4.0000e-02 eta: 22:23:05 time: 0.3326 data_time: 0.0229 memory: 5826 grad_norm: 3.0476 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8024 loss: 2.8024 2022/10/07 15:29:33 - mmengine - INFO - Epoch(train) [39][1180/2119] lr: 4.0000e-02 eta: 22:22:59 time: 0.3553 data_time: 0.0208 memory: 5826 grad_norm: 3.0883 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8023 loss: 2.8023 2022/10/07 15:29:40 - mmengine - INFO - Epoch(train) [39][1200/2119] lr: 4.0000e-02 eta: 22:22:54 time: 0.3590 data_time: 0.0215 memory: 5826 grad_norm: 3.0954 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0566 loss: 3.0566 2022/10/07 15:29:47 - mmengine - INFO - Epoch(train) [39][1220/2119] lr: 4.0000e-02 eta: 22:22:48 time: 0.3598 data_time: 0.0223 memory: 5826 grad_norm: 3.0380 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7044 loss: 2.7044 2022/10/07 15:29:53 - mmengine - INFO - Epoch(train) [39][1240/2119] lr: 4.0000e-02 eta: 22:22:39 time: 0.3037 data_time: 0.0240 memory: 5826 grad_norm: 3.0706 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8300 loss: 2.8300 2022/10/07 15:30:01 - mmengine - INFO - Epoch(train) [39][1260/2119] lr: 4.0000e-02 eta: 22:22:36 time: 0.4123 data_time: 0.0225 memory: 5826 grad_norm: 3.0952 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9514 loss: 2.9514 2022/10/07 15:30:09 - mmengine - INFO - Epoch(train) [39][1280/2119] lr: 4.0000e-02 eta: 22:22:32 time: 0.3798 data_time: 0.0225 memory: 5826 grad_norm: 3.0665 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8299 loss: 2.8299 2022/10/07 15:30:16 - mmengine - INFO - Epoch(train) [39][1300/2119] lr: 4.0000e-02 eta: 22:22:26 time: 0.3683 data_time: 0.0249 memory: 5826 grad_norm: 2.9990 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.7293 loss: 2.7293 2022/10/07 15:30:22 - mmengine - INFO - Epoch(train) [39][1320/2119] lr: 4.0000e-02 eta: 22:22:18 time: 0.3079 data_time: 0.0203 memory: 5826 grad_norm: 3.0756 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7802 loss: 2.7802 2022/10/07 15:30:30 - mmengine - INFO - Epoch(train) [39][1340/2119] lr: 4.0000e-02 eta: 22:22:13 time: 0.3802 data_time: 0.0219 memory: 5826 grad_norm: 3.0257 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6374 loss: 2.6374 2022/10/07 15:30:37 - mmengine - INFO - Epoch(train) [39][1360/2119] lr: 4.0000e-02 eta: 22:22:05 time: 0.3255 data_time: 0.0179 memory: 5826 grad_norm: 3.0314 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.6974 loss: 2.6974 2022/10/07 15:30:45 - mmengine - INFO - Epoch(train) [39][1380/2119] lr: 4.0000e-02 eta: 22:22:02 time: 0.3961 data_time: 0.0198 memory: 5826 grad_norm: 3.0515 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0166 loss: 3.0166 2022/10/07 15:30:51 - mmengine - INFO - Epoch(train) [39][1400/2119] lr: 4.0000e-02 eta: 22:21:55 time: 0.3464 data_time: 0.0191 memory: 5826 grad_norm: 3.0755 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8931 loss: 2.8931 2022/10/07 15:30:59 - mmengine - INFO - Epoch(train) [39][1420/2119] lr: 4.0000e-02 eta: 22:21:49 time: 0.3516 data_time: 0.0218 memory: 5826 grad_norm: 3.0793 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8567 loss: 2.8567 2022/10/07 15:31:05 - mmengine - INFO - Epoch(train) [39][1440/2119] lr: 4.0000e-02 eta: 22:21:40 time: 0.3123 data_time: 0.0208 memory: 5826 grad_norm: 3.1096 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.8533 loss: 2.8533 2022/10/07 15:31:12 - mmengine - INFO - Epoch(train) [39][1460/2119] lr: 4.0000e-02 eta: 22:21:34 time: 0.3423 data_time: 0.0261 memory: 5826 grad_norm: 3.0732 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6919 loss: 2.6919 2022/10/07 15:31:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 15:31:18 - mmengine - INFO - Epoch(train) [39][1480/2119] lr: 4.0000e-02 eta: 22:21:26 time: 0.3319 data_time: 0.0225 memory: 5826 grad_norm: 3.0799 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6649 loss: 2.6649 2022/10/07 15:31:25 - mmengine - INFO - Epoch(train) [39][1500/2119] lr: 4.0000e-02 eta: 22:21:19 time: 0.3386 data_time: 0.0222 memory: 5826 grad_norm: 3.0878 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7068 loss: 2.7068 2022/10/07 15:31:32 - mmengine - INFO - Epoch(train) [39][1520/2119] lr: 4.0000e-02 eta: 22:21:12 time: 0.3269 data_time: 0.0176 memory: 5826 grad_norm: 3.1245 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.7720 loss: 2.7720 2022/10/07 15:31:39 - mmengine - INFO - Epoch(train) [39][1540/2119] lr: 4.0000e-02 eta: 22:21:07 time: 0.3743 data_time: 0.0219 memory: 5826 grad_norm: 3.0560 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9010 loss: 2.9010 2022/10/07 15:31:46 - mmengine - INFO - Epoch(train) [39][1560/2119] lr: 4.0000e-02 eta: 22:20:59 time: 0.3252 data_time: 0.0184 memory: 5826 grad_norm: 3.1101 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8475 loss: 2.8475 2022/10/07 15:31:53 - mmengine - INFO - Epoch(train) [39][1580/2119] lr: 4.0000e-02 eta: 22:20:54 time: 0.3726 data_time: 0.0206 memory: 5826 grad_norm: 3.1290 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7851 loss: 2.7851 2022/10/07 15:31:59 - mmengine - INFO - Epoch(train) [39][1600/2119] lr: 4.0000e-02 eta: 22:20:46 time: 0.3209 data_time: 0.0243 memory: 5826 grad_norm: 3.0752 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9364 loss: 2.9364 2022/10/07 15:32:07 - mmengine - INFO - Epoch(train) [39][1620/2119] lr: 4.0000e-02 eta: 22:20:41 time: 0.3667 data_time: 0.0242 memory: 5826 grad_norm: 3.0444 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8245 loss: 2.8245 2022/10/07 15:32:13 - mmengine - INFO - Epoch(train) [39][1640/2119] lr: 4.0000e-02 eta: 22:20:33 time: 0.3347 data_time: 0.0184 memory: 5826 grad_norm: 3.0604 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8586 loss: 2.8586 2022/10/07 15:32:21 - mmengine - INFO - Epoch(train) [39][1660/2119] lr: 4.0000e-02 eta: 22:20:27 time: 0.3583 data_time: 0.0289 memory: 5826 grad_norm: 3.1287 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8347 loss: 2.8347 2022/10/07 15:32:28 - mmengine - INFO - Epoch(train) [39][1680/2119] lr: 4.0000e-02 eta: 22:20:22 time: 0.3604 data_time: 0.0163 memory: 5826 grad_norm: 3.1015 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7988 loss: 2.7988 2022/10/07 15:32:35 - mmengine - INFO - Epoch(train) [39][1700/2119] lr: 4.0000e-02 eta: 22:20:16 time: 0.3674 data_time: 0.0249 memory: 5826 grad_norm: 3.0995 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8961 loss: 2.8961 2022/10/07 15:32:42 - mmengine - INFO - Epoch(train) [39][1720/2119] lr: 4.0000e-02 eta: 22:20:09 time: 0.3276 data_time: 0.0229 memory: 5826 grad_norm: 3.1091 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7661 loss: 2.7661 2022/10/07 15:32:49 - mmengine - INFO - Epoch(train) [39][1740/2119] lr: 4.0000e-02 eta: 22:20:03 time: 0.3610 data_time: 0.0221 memory: 5826 grad_norm: 3.1074 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9071 loss: 2.9071 2022/10/07 15:32:56 - mmengine - INFO - Epoch(train) [39][1760/2119] lr: 4.0000e-02 eta: 22:19:57 time: 0.3516 data_time: 0.0254 memory: 5826 grad_norm: 3.0254 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7916 loss: 2.7916 2022/10/07 15:33:03 - mmengine - INFO - Epoch(train) [39][1780/2119] lr: 4.0000e-02 eta: 22:19:51 time: 0.3503 data_time: 0.0228 memory: 5826 grad_norm: 3.0712 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8828 loss: 2.8828 2022/10/07 15:33:10 - mmengine - INFO - Epoch(train) [39][1800/2119] lr: 4.0000e-02 eta: 22:19:43 time: 0.3255 data_time: 0.0172 memory: 5826 grad_norm: 3.0408 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6025 loss: 2.6025 2022/10/07 15:33:17 - mmengine - INFO - Epoch(train) [39][1820/2119] lr: 4.0000e-02 eta: 22:19:37 time: 0.3508 data_time: 0.0248 memory: 5826 grad_norm: 3.0546 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9520 loss: 2.9520 2022/10/07 15:33:23 - mmengine - INFO - Epoch(train) [39][1840/2119] lr: 4.0000e-02 eta: 22:19:29 time: 0.3343 data_time: 0.0267 memory: 5826 grad_norm: 3.0824 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9701 loss: 2.9701 2022/10/07 15:33:31 - mmengine - INFO - Epoch(train) [39][1860/2119] lr: 4.0000e-02 eta: 22:19:26 time: 0.3958 data_time: 0.0243 memory: 5826 grad_norm: 3.1447 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8401 loss: 2.8401 2022/10/07 15:33:37 - mmengine - INFO - Epoch(train) [39][1880/2119] lr: 4.0000e-02 eta: 22:19:17 time: 0.3014 data_time: 0.0224 memory: 5826 grad_norm: 3.0874 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.6475 loss: 2.6475 2022/10/07 15:33:44 - mmengine - INFO - Epoch(train) [39][1900/2119] lr: 4.0000e-02 eta: 22:19:10 time: 0.3396 data_time: 0.0242 memory: 5826 grad_norm: 3.1087 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0456 loss: 3.0456 2022/10/07 15:33:50 - mmengine - INFO - Epoch(train) [39][1920/2119] lr: 4.0000e-02 eta: 22:19:02 time: 0.3201 data_time: 0.0262 memory: 5826 grad_norm: 3.0948 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7935 loss: 2.7935 2022/10/07 15:33:58 - mmengine - INFO - Epoch(train) [39][1940/2119] lr: 4.0000e-02 eta: 22:18:56 time: 0.3637 data_time: 0.0246 memory: 5826 grad_norm: 3.0575 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7020 loss: 2.7020 2022/10/07 15:34:04 - mmengine - INFO - Epoch(train) [39][1960/2119] lr: 4.0000e-02 eta: 22:18:48 time: 0.3158 data_time: 0.0196 memory: 5826 grad_norm: 3.0099 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4773 loss: 2.4773 2022/10/07 15:34:11 - mmengine - INFO - Epoch(train) [39][1980/2119] lr: 4.0000e-02 eta: 22:18:42 time: 0.3624 data_time: 0.0312 memory: 5826 grad_norm: 3.0398 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7492 loss: 2.7492 2022/10/07 15:34:18 - mmengine - INFO - Epoch(train) [39][2000/2119] lr: 4.0000e-02 eta: 22:18:36 time: 0.3459 data_time: 0.0209 memory: 5826 grad_norm: 3.0659 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8565 loss: 2.8565 2022/10/07 15:34:27 - mmengine - INFO - Epoch(train) [39][2020/2119] lr: 4.0000e-02 eta: 22:18:33 time: 0.4181 data_time: 0.0245 memory: 5826 grad_norm: 3.0226 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6729 loss: 2.6729 2022/10/07 15:34:33 - mmengine - INFO - Epoch(train) [39][2040/2119] lr: 4.0000e-02 eta: 22:18:25 time: 0.3221 data_time: 0.0187 memory: 5826 grad_norm: 3.0489 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8510 loss: 2.8510 2022/10/07 15:34:40 - mmengine - INFO - Epoch(train) [39][2060/2119] lr: 4.0000e-02 eta: 22:18:18 time: 0.3286 data_time: 0.0226 memory: 5826 grad_norm: 3.0531 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8995 loss: 2.8995 2022/10/07 15:34:46 - mmengine - INFO - Epoch(train) [39][2080/2119] lr: 4.0000e-02 eta: 22:18:10 time: 0.3321 data_time: 0.0228 memory: 5826 grad_norm: 3.0481 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.1230 loss: 3.1230 2022/10/07 15:34:53 - mmengine - INFO - Epoch(train) [39][2100/2119] lr: 4.0000e-02 eta: 22:18:03 time: 0.3405 data_time: 0.0225 memory: 5826 grad_norm: 3.0058 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6668 loss: 2.6668 2022/10/07 15:34:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 15:34:58 - mmengine - INFO - Epoch(train) [39][2119/2119] lr: 4.0000e-02 eta: 22:18:03 time: 0.2643 data_time: 0.0165 memory: 5826 grad_norm: 3.1246 top1_acc: 0.2000 top5_acc: 0.4000 loss_cls: 2.9307 loss: 2.9307 2022/10/07 15:35:08 - mmengine - INFO - Epoch(train) [40][20/2119] lr: 4.0000e-02 eta: 22:17:39 time: 0.4755 data_time: 0.1487 memory: 5826 grad_norm: 3.0992 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7266 loss: 2.7266 2022/10/07 15:35:15 - mmengine - INFO - Epoch(train) [40][40/2119] lr: 4.0000e-02 eta: 22:17:33 time: 0.3581 data_time: 0.0242 memory: 5826 grad_norm: 3.0533 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9529 loss: 2.9529 2022/10/07 15:35:23 - mmengine - INFO - Epoch(train) [40][60/2119] lr: 4.0000e-02 eta: 22:17:29 time: 0.3908 data_time: 0.0171 memory: 5826 grad_norm: 3.1008 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6446 loss: 2.6446 2022/10/07 15:35:29 - mmengine - INFO - Epoch(train) [40][80/2119] lr: 4.0000e-02 eta: 22:17:22 time: 0.3232 data_time: 0.0213 memory: 5826 grad_norm: 3.0308 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7723 loss: 2.7723 2022/10/07 15:35:37 - mmengine - INFO - Epoch(train) [40][100/2119] lr: 4.0000e-02 eta: 22:17:18 time: 0.3978 data_time: 0.0218 memory: 5826 grad_norm: 3.0565 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4751 loss: 2.4751 2022/10/07 15:35:43 - mmengine - INFO - Epoch(train) [40][120/2119] lr: 4.0000e-02 eta: 22:17:09 time: 0.3116 data_time: 0.0237 memory: 5826 grad_norm: 3.0675 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6431 loss: 2.6431 2022/10/07 15:35:50 - mmengine - INFO - Epoch(train) [40][140/2119] lr: 4.0000e-02 eta: 22:17:02 time: 0.3368 data_time: 0.0193 memory: 5826 grad_norm: 3.0244 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8326 loss: 2.8326 2022/10/07 15:35:57 - mmengine - INFO - Epoch(train) [40][160/2119] lr: 4.0000e-02 eta: 22:16:55 time: 0.3313 data_time: 0.0249 memory: 5826 grad_norm: 3.0860 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8002 loss: 2.8002 2022/10/07 15:36:05 - mmengine - INFO - Epoch(train) [40][180/2119] lr: 4.0000e-02 eta: 22:16:52 time: 0.4061 data_time: 0.0203 memory: 5826 grad_norm: 3.0385 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9426 loss: 2.9426 2022/10/07 15:36:11 - mmengine - INFO - Epoch(train) [40][200/2119] lr: 4.0000e-02 eta: 22:16:44 time: 0.3223 data_time: 0.0239 memory: 5826 grad_norm: 3.0524 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5707 loss: 2.5707 2022/10/07 15:36:18 - mmengine - INFO - Epoch(train) [40][220/2119] lr: 4.0000e-02 eta: 22:16:38 time: 0.3650 data_time: 0.0221 memory: 5826 grad_norm: 3.0662 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.6338 loss: 2.6338 2022/10/07 15:36:25 - mmengine - INFO - Epoch(train) [40][240/2119] lr: 4.0000e-02 eta: 22:16:30 time: 0.3112 data_time: 0.0220 memory: 5826 grad_norm: 3.0342 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5412 loss: 2.5412 2022/10/07 15:36:32 - mmengine - INFO - Epoch(train) [40][260/2119] lr: 4.0000e-02 eta: 22:16:26 time: 0.3875 data_time: 0.0199 memory: 5826 grad_norm: 3.0854 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6859 loss: 2.6859 2022/10/07 15:36:39 - mmengine - INFO - Epoch(train) [40][280/2119] lr: 4.0000e-02 eta: 22:16:18 time: 0.3251 data_time: 0.0179 memory: 5826 grad_norm: 3.0511 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6748 loss: 2.6748 2022/10/07 15:36:46 - mmengine - INFO - Epoch(train) [40][300/2119] lr: 4.0000e-02 eta: 22:16:12 time: 0.3538 data_time: 0.0197 memory: 5826 grad_norm: 3.1187 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7003 loss: 2.7003 2022/10/07 15:36:52 - mmengine - INFO - Epoch(train) [40][320/2119] lr: 4.0000e-02 eta: 22:16:03 time: 0.3120 data_time: 0.0207 memory: 5826 grad_norm: 3.0954 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8987 loss: 2.8987 2022/10/07 15:37:01 - mmengine - INFO - Epoch(train) [40][340/2119] lr: 4.0000e-02 eta: 22:16:01 time: 0.4143 data_time: 0.0192 memory: 5826 grad_norm: 3.0519 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6697 loss: 2.6697 2022/10/07 15:37:06 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 15:37:07 - mmengine - INFO - Epoch(train) [40][360/2119] lr: 4.0000e-02 eta: 22:15:51 time: 0.2977 data_time: 0.0238 memory: 5826 grad_norm: 3.0832 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9258 loss: 2.9258 2022/10/07 15:37:13 - mmengine - INFO - Epoch(train) [40][380/2119] lr: 4.0000e-02 eta: 22:15:43 time: 0.3074 data_time: 0.0192 memory: 5826 grad_norm: 3.1233 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7554 loss: 2.7554 2022/10/07 15:37:21 - mmengine - INFO - Epoch(train) [40][400/2119] lr: 4.0000e-02 eta: 22:15:40 time: 0.4175 data_time: 0.0227 memory: 5826 grad_norm: 3.0501 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7383 loss: 2.7383 2022/10/07 15:37:28 - mmengine - INFO - Epoch(train) [40][420/2119] lr: 4.0000e-02 eta: 22:15:33 time: 0.3363 data_time: 0.0226 memory: 5826 grad_norm: 3.0821 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8933 loss: 2.8933 2022/10/07 15:37:35 - mmengine - INFO - Epoch(train) [40][440/2119] lr: 4.0000e-02 eta: 22:15:27 time: 0.3474 data_time: 0.0223 memory: 5826 grad_norm: 3.0805 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5550 loss: 2.5550 2022/10/07 15:37:42 - mmengine - INFO - Epoch(train) [40][460/2119] lr: 4.0000e-02 eta: 22:15:20 time: 0.3548 data_time: 0.0256 memory: 5826 grad_norm: 3.0622 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8735 loss: 2.8735 2022/10/07 15:37:48 - mmengine - INFO - Epoch(train) [40][480/2119] lr: 4.0000e-02 eta: 22:15:13 time: 0.3327 data_time: 0.0245 memory: 5826 grad_norm: 3.0606 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7053 loss: 2.7053 2022/10/07 15:37:55 - mmengine - INFO - Epoch(train) [40][500/2119] lr: 4.0000e-02 eta: 22:15:07 time: 0.3500 data_time: 0.0330 memory: 5826 grad_norm: 3.0654 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6287 loss: 2.6287 2022/10/07 15:38:03 - mmengine - INFO - Epoch(train) [40][520/2119] lr: 4.0000e-02 eta: 22:15:01 time: 0.3591 data_time: 0.0244 memory: 5826 grad_norm: 3.1038 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7609 loss: 2.7609 2022/10/07 15:38:09 - mmengine - INFO - Epoch(train) [40][540/2119] lr: 4.0000e-02 eta: 22:14:54 time: 0.3361 data_time: 0.0215 memory: 5826 grad_norm: 3.0826 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6826 loss: 2.6826 2022/10/07 15:38:17 - mmengine - INFO - Epoch(train) [40][560/2119] lr: 4.0000e-02 eta: 22:14:50 time: 0.3859 data_time: 0.0208 memory: 5826 grad_norm: 3.0534 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8002 loss: 2.8002 2022/10/07 15:38:24 - mmengine - INFO - Epoch(train) [40][580/2119] lr: 4.0000e-02 eta: 22:14:42 time: 0.3223 data_time: 0.0164 memory: 5826 grad_norm: 3.0283 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7897 loss: 2.7897 2022/10/07 15:38:30 - mmengine - INFO - Epoch(train) [40][600/2119] lr: 4.0000e-02 eta: 22:14:35 time: 0.3472 data_time: 0.0222 memory: 5826 grad_norm: 3.1908 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6246 loss: 2.6246 2022/10/07 15:38:38 - mmengine - INFO - Epoch(train) [40][620/2119] lr: 4.0000e-02 eta: 22:14:30 time: 0.3705 data_time: 0.0194 memory: 5826 grad_norm: 3.0970 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 2.8265 loss: 2.8265 2022/10/07 15:38:44 - mmengine - INFO - Epoch(train) [40][640/2119] lr: 4.0000e-02 eta: 22:14:21 time: 0.3096 data_time: 0.0288 memory: 5826 grad_norm: 2.9946 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9065 loss: 2.9065 2022/10/07 15:38:50 - mmengine - INFO - Epoch(train) [40][660/2119] lr: 4.0000e-02 eta: 22:14:12 time: 0.3007 data_time: 0.0226 memory: 5826 grad_norm: 3.0307 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6223 loss: 2.6223 2022/10/07 15:38:57 - mmengine - INFO - Epoch(train) [40][680/2119] lr: 4.0000e-02 eta: 22:14:06 time: 0.3599 data_time: 0.0208 memory: 5826 grad_norm: 3.0720 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7878 loss: 2.7878 2022/10/07 15:39:04 - mmengine - INFO - Epoch(train) [40][700/2119] lr: 4.0000e-02 eta: 22:14:00 time: 0.3413 data_time: 0.0210 memory: 5826 grad_norm: 3.0506 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6847 loss: 2.6847 2022/10/07 15:39:11 - mmengine - INFO - Epoch(train) [40][720/2119] lr: 4.0000e-02 eta: 22:13:53 time: 0.3445 data_time: 0.0259 memory: 5826 grad_norm: 3.0818 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0979 loss: 3.0979 2022/10/07 15:39:18 - mmengine - INFO - Epoch(train) [40][740/2119] lr: 4.0000e-02 eta: 22:13:47 time: 0.3561 data_time: 0.0190 memory: 5826 grad_norm: 3.0345 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6042 loss: 2.6042 2022/10/07 15:39:24 - mmengine - INFO - Epoch(train) [40][760/2119] lr: 4.0000e-02 eta: 22:13:39 time: 0.3114 data_time: 0.0187 memory: 5826 grad_norm: 3.1151 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7767 loss: 2.7767 2022/10/07 15:39:32 - mmengine - INFO - Epoch(train) [40][780/2119] lr: 4.0000e-02 eta: 22:13:33 time: 0.3575 data_time: 0.0174 memory: 5826 grad_norm: 3.0274 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7492 loss: 2.7492 2022/10/07 15:39:39 - mmengine - INFO - Epoch(train) [40][800/2119] lr: 4.0000e-02 eta: 22:13:26 time: 0.3478 data_time: 0.0227 memory: 5826 grad_norm: 3.1408 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7417 loss: 2.7417 2022/10/07 15:39:45 - mmengine - INFO - Epoch(train) [40][820/2119] lr: 4.0000e-02 eta: 22:13:19 time: 0.3314 data_time: 0.0200 memory: 5826 grad_norm: 3.0679 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9070 loss: 2.9070 2022/10/07 15:39:52 - mmengine - INFO - Epoch(train) [40][840/2119] lr: 4.0000e-02 eta: 22:13:12 time: 0.3476 data_time: 0.0216 memory: 5826 grad_norm: 3.1247 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7754 loss: 2.7754 2022/10/07 15:39:58 - mmengine - INFO - Epoch(train) [40][860/2119] lr: 4.0000e-02 eta: 22:13:03 time: 0.3006 data_time: 0.0172 memory: 5826 grad_norm: 3.1182 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6499 loss: 2.6499 2022/10/07 15:40:05 - mmengine - INFO - Epoch(train) [40][880/2119] lr: 4.0000e-02 eta: 22:12:57 time: 0.3621 data_time: 0.0253 memory: 5826 grad_norm: 3.0760 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7594 loss: 2.7594 2022/10/07 15:40:12 - mmengine - INFO - Epoch(train) [40][900/2119] lr: 4.0000e-02 eta: 22:12:50 time: 0.3273 data_time: 0.0213 memory: 5826 grad_norm: 3.0808 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8853 loss: 2.8853 2022/10/07 15:40:19 - mmengine - INFO - Epoch(train) [40][920/2119] lr: 4.0000e-02 eta: 22:12:43 time: 0.3484 data_time: 0.0229 memory: 5826 grad_norm: 3.0689 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5803 loss: 2.5803 2022/10/07 15:40:26 - mmengine - INFO - Epoch(train) [40][940/2119] lr: 4.0000e-02 eta: 22:12:37 time: 0.3543 data_time: 0.0214 memory: 5826 grad_norm: 3.0771 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7693 loss: 2.7693 2022/10/07 15:40:33 - mmengine - INFO - Epoch(train) [40][960/2119] lr: 4.0000e-02 eta: 22:12:32 time: 0.3761 data_time: 0.0192 memory: 5826 grad_norm: 3.0896 top1_acc: 0.1875 top5_acc: 0.7500 loss_cls: 2.6387 loss: 2.6387 2022/10/07 15:40:41 - mmengine - INFO - Epoch(train) [40][980/2119] lr: 4.0000e-02 eta: 22:12:26 time: 0.3526 data_time: 0.0213 memory: 5826 grad_norm: 3.0506 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5511 loss: 2.5511 2022/10/07 15:40:47 - mmengine - INFO - Epoch(train) [40][1000/2119] lr: 4.0000e-02 eta: 22:12:19 time: 0.3359 data_time: 0.0217 memory: 5826 grad_norm: 3.0931 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8118 loss: 2.8118 2022/10/07 15:40:55 - mmengine - INFO - Epoch(train) [40][1020/2119] lr: 4.0000e-02 eta: 22:12:14 time: 0.3766 data_time: 0.0251 memory: 5826 grad_norm: 3.0797 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7793 loss: 2.7793 2022/10/07 15:41:01 - mmengine - INFO - Epoch(train) [40][1040/2119] lr: 4.0000e-02 eta: 22:12:06 time: 0.3232 data_time: 0.0228 memory: 5826 grad_norm: 3.1135 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5959 loss: 2.5959 2022/10/07 15:41:08 - mmengine - INFO - Epoch(train) [40][1060/2119] lr: 4.0000e-02 eta: 22:11:59 time: 0.3364 data_time: 0.0146 memory: 5826 grad_norm: 3.1150 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9554 loss: 2.9554 2022/10/07 15:41:15 - mmengine - INFO - Epoch(train) [40][1080/2119] lr: 4.0000e-02 eta: 22:11:52 time: 0.3305 data_time: 0.0193 memory: 5826 grad_norm: 3.1191 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 2.7748 loss: 2.7748 2022/10/07 15:41:21 - mmengine - INFO - Epoch(train) [40][1100/2119] lr: 4.0000e-02 eta: 22:11:44 time: 0.3168 data_time: 0.0207 memory: 5826 grad_norm: 2.9974 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8758 loss: 2.8758 2022/10/07 15:41:28 - mmengine - INFO - Epoch(train) [40][1120/2119] lr: 4.0000e-02 eta: 22:11:36 time: 0.3283 data_time: 0.0212 memory: 5826 grad_norm: 3.0633 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7342 loss: 2.7342 2022/10/07 15:41:34 - mmengine - INFO - Epoch(train) [40][1140/2119] lr: 4.0000e-02 eta: 22:11:28 time: 0.3139 data_time: 0.0214 memory: 5826 grad_norm: 3.1508 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9852 loss: 2.9852 2022/10/07 15:41:41 - mmengine - INFO - Epoch(train) [40][1160/2119] lr: 4.0000e-02 eta: 22:11:22 time: 0.3607 data_time: 0.0192 memory: 5826 grad_norm: 3.0646 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6564 loss: 2.6564 2022/10/07 15:41:48 - mmengine - INFO - Epoch(train) [40][1180/2119] lr: 4.0000e-02 eta: 22:11:16 time: 0.3519 data_time: 0.0222 memory: 5826 grad_norm: 3.0579 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8386 loss: 2.8386 2022/10/07 15:41:55 - mmengine - INFO - Epoch(train) [40][1200/2119] lr: 4.0000e-02 eta: 22:11:08 time: 0.3317 data_time: 0.0184 memory: 5826 grad_norm: 3.0959 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9291 loss: 2.9291 2022/10/07 15:42:01 - mmengine - INFO - Epoch(train) [40][1220/2119] lr: 4.0000e-02 eta: 22:11:01 time: 0.3358 data_time: 0.0203 memory: 5826 grad_norm: 3.0390 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7869 loss: 2.7869 2022/10/07 15:42:08 - mmengine - INFO - Epoch(train) [40][1240/2119] lr: 4.0000e-02 eta: 22:10:55 time: 0.3432 data_time: 0.0209 memory: 5826 grad_norm: 3.0604 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6761 loss: 2.6761 2022/10/07 15:42:15 - mmengine - INFO - Epoch(train) [40][1260/2119] lr: 4.0000e-02 eta: 22:10:48 time: 0.3423 data_time: 0.0173 memory: 5826 grad_norm: 3.0545 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5491 loss: 2.5491 2022/10/07 15:42:22 - mmengine - INFO - Epoch(train) [40][1280/2119] lr: 4.0000e-02 eta: 22:10:42 time: 0.3517 data_time: 0.0240 memory: 5826 grad_norm: 3.0525 top1_acc: 0.1875 top5_acc: 0.7500 loss_cls: 2.9382 loss: 2.9382 2022/10/07 15:42:29 - mmengine - INFO - Epoch(train) [40][1300/2119] lr: 4.0000e-02 eta: 22:10:36 time: 0.3607 data_time: 0.0208 memory: 5826 grad_norm: 3.0561 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5894 loss: 2.5894 2022/10/07 15:42:36 - mmengine - INFO - Epoch(train) [40][1320/2119] lr: 4.0000e-02 eta: 22:10:28 time: 0.3306 data_time: 0.0309 memory: 5826 grad_norm: 3.1278 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7777 loss: 2.7777 2022/10/07 15:42:43 - mmengine - INFO - Epoch(train) [40][1340/2119] lr: 4.0000e-02 eta: 22:10:21 time: 0.3379 data_time: 0.0298 memory: 5826 grad_norm: 3.0551 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 2.8537 loss: 2.8537 2022/10/07 15:42:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 15:42:49 - mmengine - INFO - Epoch(train) [40][1360/2119] lr: 4.0000e-02 eta: 22:10:14 time: 0.3297 data_time: 0.0268 memory: 5826 grad_norm: 3.1215 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8838 loss: 2.8838 2022/10/07 15:42:57 - mmengine - INFO - Epoch(train) [40][1380/2119] lr: 4.0000e-02 eta: 22:10:08 time: 0.3602 data_time: 0.0247 memory: 5826 grad_norm: 2.9642 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8763 loss: 2.8763 2022/10/07 15:43:04 - mmengine - INFO - Epoch(train) [40][1400/2119] lr: 4.0000e-02 eta: 22:10:02 time: 0.3540 data_time: 0.0221 memory: 5826 grad_norm: 3.0688 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6193 loss: 2.6193 2022/10/07 15:43:11 - mmengine - INFO - Epoch(train) [40][1420/2119] lr: 4.0000e-02 eta: 22:09:57 time: 0.3811 data_time: 0.0199 memory: 5826 grad_norm: 3.0946 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9278 loss: 2.9278 2022/10/07 15:43:17 - mmengine - INFO - Epoch(train) [40][1440/2119] lr: 4.0000e-02 eta: 22:09:49 time: 0.3036 data_time: 0.0216 memory: 5826 grad_norm: 3.1241 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8500 loss: 2.8500 2022/10/07 15:43:25 - mmengine - INFO - Epoch(train) [40][1460/2119] lr: 4.0000e-02 eta: 22:09:44 time: 0.3778 data_time: 0.0204 memory: 5826 grad_norm: 3.0538 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.0163 loss: 3.0163 2022/10/07 15:43:31 - mmengine - INFO - Epoch(train) [40][1480/2119] lr: 4.0000e-02 eta: 22:09:35 time: 0.3104 data_time: 0.0214 memory: 5826 grad_norm: 3.0450 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9481 loss: 2.9481 2022/10/07 15:43:39 - mmengine - INFO - Epoch(train) [40][1500/2119] lr: 4.0000e-02 eta: 22:09:31 time: 0.3905 data_time: 0.0215 memory: 5826 grad_norm: 3.0592 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7341 loss: 2.7341 2022/10/07 15:43:45 - mmengine - INFO - Epoch(train) [40][1520/2119] lr: 4.0000e-02 eta: 22:09:23 time: 0.3217 data_time: 0.0201 memory: 5826 grad_norm: 3.0840 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8127 loss: 2.8127 2022/10/07 15:43:53 - mmengine - INFO - Epoch(train) [40][1540/2119] lr: 4.0000e-02 eta: 22:09:19 time: 0.3872 data_time: 0.0181 memory: 5826 grad_norm: 3.0688 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8601 loss: 2.8601 2022/10/07 15:44:00 - mmengine - INFO - Epoch(train) [40][1560/2119] lr: 4.0000e-02 eta: 22:09:11 time: 0.3237 data_time: 0.0231 memory: 5826 grad_norm: 3.0129 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7999 loss: 2.7999 2022/10/07 15:44:07 - mmengine - INFO - Epoch(train) [40][1580/2119] lr: 4.0000e-02 eta: 22:09:07 time: 0.3905 data_time: 0.0222 memory: 5826 grad_norm: 3.0730 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8767 loss: 2.8767 2022/10/07 15:44:14 - mmengine - INFO - Epoch(train) [40][1600/2119] lr: 4.0000e-02 eta: 22:08:59 time: 0.3144 data_time: 0.0180 memory: 5826 grad_norm: 3.1145 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0005 loss: 3.0005 2022/10/07 15:44:21 - mmengine - INFO - Epoch(train) [40][1620/2119] lr: 4.0000e-02 eta: 22:08:52 time: 0.3425 data_time: 0.0231 memory: 5826 grad_norm: 3.0476 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6970 loss: 2.6970 2022/10/07 15:44:27 - mmengine - INFO - Epoch(train) [40][1640/2119] lr: 4.0000e-02 eta: 22:08:44 time: 0.3252 data_time: 0.0231 memory: 5826 grad_norm: 3.0641 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1309 loss: 3.1309 2022/10/07 15:44:35 - mmengine - INFO - Epoch(train) [40][1660/2119] lr: 4.0000e-02 eta: 22:08:40 time: 0.3865 data_time: 0.0220 memory: 5826 grad_norm: 3.0342 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6641 loss: 2.6641 2022/10/07 15:44:41 - mmengine - INFO - Epoch(train) [40][1680/2119] lr: 4.0000e-02 eta: 22:08:31 time: 0.3061 data_time: 0.0206 memory: 5826 grad_norm: 3.0178 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7958 loss: 2.7958 2022/10/07 15:44:48 - mmengine - INFO - Epoch(train) [40][1700/2119] lr: 4.0000e-02 eta: 22:08:26 time: 0.3787 data_time: 0.0200 memory: 5826 grad_norm: 3.0817 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8571 loss: 2.8571 2022/10/07 15:44:55 - mmengine - INFO - Epoch(train) [40][1720/2119] lr: 4.0000e-02 eta: 22:08:19 time: 0.3369 data_time: 0.0221 memory: 5826 grad_norm: 3.0665 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.5887 loss: 2.5887 2022/10/07 15:45:02 - mmengine - INFO - Epoch(train) [40][1740/2119] lr: 4.0000e-02 eta: 22:08:12 time: 0.3332 data_time: 0.0194 memory: 5826 grad_norm: 3.0567 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8346 loss: 2.8346 2022/10/07 15:45:08 - mmengine - INFO - Epoch(train) [40][1760/2119] lr: 4.0000e-02 eta: 22:08:04 time: 0.3125 data_time: 0.0217 memory: 5826 grad_norm: 3.0665 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7819 loss: 2.7819 2022/10/07 15:45:16 - mmengine - INFO - Epoch(train) [40][1780/2119] lr: 4.0000e-02 eta: 22:08:00 time: 0.3917 data_time: 0.0143 memory: 5826 grad_norm: 3.0144 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9545 loss: 2.9545 2022/10/07 15:45:23 - mmengine - INFO - Epoch(train) [40][1800/2119] lr: 4.0000e-02 eta: 22:07:52 time: 0.3337 data_time: 0.0249 memory: 5826 grad_norm: 3.0743 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7450 loss: 2.7450 2022/10/07 15:45:30 - mmengine - INFO - Epoch(train) [40][1820/2119] lr: 4.0000e-02 eta: 22:07:46 time: 0.3490 data_time: 0.0163 memory: 5826 grad_norm: 3.0120 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7327 loss: 2.7327 2022/10/07 15:45:36 - mmengine - INFO - Epoch(train) [40][1840/2119] lr: 4.0000e-02 eta: 22:07:37 time: 0.3069 data_time: 0.0266 memory: 5826 grad_norm: 3.0901 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7176 loss: 2.7176 2022/10/07 15:45:43 - mmengine - INFO - Epoch(train) [40][1860/2119] lr: 4.0000e-02 eta: 22:07:30 time: 0.3394 data_time: 0.0220 memory: 5826 grad_norm: 3.1064 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6950 loss: 2.6950 2022/10/07 15:45:49 - mmengine - INFO - Epoch(train) [40][1880/2119] lr: 4.0000e-02 eta: 22:07:23 time: 0.3424 data_time: 0.0208 memory: 5826 grad_norm: 3.0676 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9438 loss: 2.9438 2022/10/07 15:45:56 - mmengine - INFO - Epoch(train) [40][1900/2119] lr: 4.0000e-02 eta: 22:07:17 time: 0.3482 data_time: 0.0203 memory: 5826 grad_norm: 3.0048 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.1117 loss: 3.1117 2022/10/07 15:46:04 - mmengine - INFO - Epoch(train) [40][1920/2119] lr: 4.0000e-02 eta: 22:07:12 time: 0.3793 data_time: 0.0189 memory: 5826 grad_norm: 3.0227 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8989 loss: 2.8989 2022/10/07 15:46:10 - mmengine - INFO - Epoch(train) [40][1940/2119] lr: 4.0000e-02 eta: 22:07:03 time: 0.3054 data_time: 0.0197 memory: 5826 grad_norm: 3.0571 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7896 loss: 2.7896 2022/10/07 15:46:17 - mmengine - INFO - Epoch(train) [40][1960/2119] lr: 4.0000e-02 eta: 22:06:58 time: 0.3583 data_time: 0.0213 memory: 5826 grad_norm: 3.0797 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6471 loss: 2.6471 2022/10/07 15:46:24 - mmengine - INFO - Epoch(train) [40][1980/2119] lr: 4.0000e-02 eta: 22:06:50 time: 0.3207 data_time: 0.0226 memory: 5826 grad_norm: 3.0988 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8273 loss: 2.8273 2022/10/07 15:46:30 - mmengine - INFO - Epoch(train) [40][2000/2119] lr: 4.0000e-02 eta: 22:06:41 time: 0.3173 data_time: 0.0243 memory: 5826 grad_norm: 3.0520 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7364 loss: 2.7364 2022/10/07 15:46:37 - mmengine - INFO - Epoch(train) [40][2020/2119] lr: 4.0000e-02 eta: 22:06:36 time: 0.3638 data_time: 0.0184 memory: 5826 grad_norm: 3.0358 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5875 loss: 2.5875 2022/10/07 15:46:44 - mmengine - INFO - Epoch(train) [40][2040/2119] lr: 4.0000e-02 eta: 22:06:29 time: 0.3338 data_time: 0.0204 memory: 5826 grad_norm: 3.0479 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8333 loss: 2.8333 2022/10/07 15:46:50 - mmengine - INFO - Epoch(train) [40][2060/2119] lr: 4.0000e-02 eta: 22:06:20 time: 0.3109 data_time: 0.0192 memory: 5826 grad_norm: 3.0945 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8968 loss: 2.8968 2022/10/07 15:46:58 - mmengine - INFO - Epoch(train) [40][2080/2119] lr: 4.0000e-02 eta: 22:06:15 time: 0.3758 data_time: 0.0191 memory: 5826 grad_norm: 3.1384 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0210 loss: 3.0210 2022/10/07 15:47:04 - mmengine - INFO - Epoch(train) [40][2100/2119] lr: 4.0000e-02 eta: 22:06:07 time: 0.3106 data_time: 0.0187 memory: 5826 grad_norm: 3.0197 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9220 loss: 2.9220 2022/10/07 15:47:10 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 15:47:10 - mmengine - INFO - Epoch(train) [40][2119/2119] lr: 4.0000e-02 eta: 22:06:07 time: 0.3281 data_time: 0.0178 memory: 5826 grad_norm: 3.1164 top1_acc: 0.5000 top5_acc: 0.6000 loss_cls: 2.9812 loss: 2.9812 2022/10/07 15:47:10 - mmengine - INFO - Saving checkpoint at 40 epochs 2022/10/07 15:47:31 - mmengine - INFO - Epoch(val) [40][20/137] eta: 0:00:47 time: 0.4067 data_time: 0.3315 memory: 1241 2022/10/07 15:47:37 - mmengine - INFO - Epoch(val) [40][40/137] eta: 0:00:26 time: 0.2703 data_time: 0.2026 memory: 1241 2022/10/07 15:47:44 - mmengine - INFO - Epoch(val) [40][60/137] eta: 0:00:27 time: 0.3601 data_time: 0.2905 memory: 1241 2022/10/07 15:47:49 - mmengine - INFO - Epoch(val) [40][80/137] eta: 0:00:13 time: 0.2287 data_time: 0.1658 memory: 1241 2022/10/07 15:47:55 - mmengine - INFO - Epoch(val) [40][100/137] eta: 0:00:11 time: 0.3123 data_time: 0.2481 memory: 1241 2022/10/07 15:48:00 - mmengine - INFO - Epoch(val) [40][120/137] eta: 0:00:03 time: 0.2331 data_time: 0.1670 memory: 1241 2022/10/07 15:48:09 - mmengine - INFO - Epoch(val) [40][137/137] acc/top1: 0.4188 acc/top5: 0.6676 acc/mean1: 0.4187 2022/10/07 15:48:23 - mmengine - INFO - Epoch(train) [41][20/2119] lr: 4.0000e-02 eta: 22:05:56 time: 0.7223 data_time: 0.1303 memory: 5826 grad_norm: 3.0934 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7097 loss: 2.7097 2022/10/07 15:48:30 - mmengine - INFO - Epoch(train) [41][40/2119] lr: 4.0000e-02 eta: 22:05:48 time: 0.3190 data_time: 0.0327 memory: 5826 grad_norm: 3.0853 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.7706 loss: 2.7706 2022/10/07 15:48:38 - mmengine - INFO - Epoch(train) [41][60/2119] lr: 4.0000e-02 eta: 22:05:44 time: 0.3891 data_time: 0.0187 memory: 5826 grad_norm: 3.0078 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6432 loss: 2.6432 2022/10/07 15:48:44 - mmengine - INFO - Epoch(train) [41][80/2119] lr: 4.0000e-02 eta: 22:05:36 time: 0.3094 data_time: 0.0209 memory: 5826 grad_norm: 3.0523 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.7661 loss: 2.7661 2022/10/07 15:48:54 - mmengine - INFO - Epoch(train) [41][100/2119] lr: 4.0000e-02 eta: 22:05:37 time: 0.4993 data_time: 0.0427 memory: 5826 grad_norm: 3.0778 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6856 loss: 2.6856 2022/10/07 15:49:06 - mmengine - INFO - Epoch(train) [41][120/2119] lr: 4.0000e-02 eta: 22:05:45 time: 0.6098 data_time: 0.0233 memory: 5826 grad_norm: 3.0466 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6974 loss: 2.6974 2022/10/07 15:49:13 - mmengine - INFO - Epoch(train) [41][140/2119] lr: 4.0000e-02 eta: 22:05:40 time: 0.3690 data_time: 0.0223 memory: 5826 grad_norm: 3.0886 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7803 loss: 2.7803 2022/10/07 15:49:21 - mmengine - INFO - Epoch(train) [41][160/2119] lr: 4.0000e-02 eta: 22:05:36 time: 0.3915 data_time: 0.0258 memory: 5826 grad_norm: 3.1210 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7463 loss: 2.7463 2022/10/07 15:49:28 - mmengine - INFO - Epoch(train) [41][180/2119] lr: 4.0000e-02 eta: 22:05:29 time: 0.3330 data_time: 0.0226 memory: 5826 grad_norm: 3.1476 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7502 loss: 2.7502 2022/10/07 15:49:35 - mmengine - INFO - Epoch(train) [41][200/2119] lr: 4.0000e-02 eta: 22:05:21 time: 0.3347 data_time: 0.0230 memory: 5826 grad_norm: 3.1009 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0864 loss: 3.0864 2022/10/07 15:49:41 - mmengine - INFO - Epoch(train) [41][220/2119] lr: 4.0000e-02 eta: 22:05:14 time: 0.3301 data_time: 0.0234 memory: 5826 grad_norm: 3.0011 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9329 loss: 2.9329 2022/10/07 15:49:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 15:49:51 - mmengine - INFO - Epoch(train) [41][240/2119] lr: 4.0000e-02 eta: 22:05:15 time: 0.4869 data_time: 0.0301 memory: 5826 grad_norm: 3.0311 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8577 loss: 2.8577 2022/10/07 15:49:56 - mmengine - INFO - Epoch(train) [41][260/2119] lr: 4.0000e-02 eta: 22:05:03 time: 0.2472 data_time: 0.0299 memory: 5826 grad_norm: 3.0584 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0408 loss: 3.0408 2022/10/07 15:50:03 - mmengine - INFO - Epoch(train) [41][280/2119] lr: 4.0000e-02 eta: 22:04:56 time: 0.3441 data_time: 0.0236 memory: 5826 grad_norm: 3.0544 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.1395 loss: 3.1395 2022/10/07 15:50:12 - mmengine - INFO - Epoch(train) [41][300/2119] lr: 4.0000e-02 eta: 22:04:55 time: 0.4414 data_time: 0.0169 memory: 5826 grad_norm: 3.0344 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7443 loss: 2.7443 2022/10/07 15:50:19 - mmengine - INFO - Epoch(train) [41][320/2119] lr: 4.0000e-02 eta: 22:04:51 time: 0.3957 data_time: 0.0194 memory: 5826 grad_norm: 3.0634 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8013 loss: 2.8013 2022/10/07 15:50:25 - mmengine - INFO - Epoch(train) [41][340/2119] lr: 4.0000e-02 eta: 22:04:42 time: 0.2908 data_time: 0.0213 memory: 5826 grad_norm: 3.0740 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7659 loss: 2.7659 2022/10/07 15:50:33 - mmengine - INFO - Epoch(train) [41][360/2119] lr: 4.0000e-02 eta: 22:04:38 time: 0.4083 data_time: 0.0199 memory: 5826 grad_norm: 3.0805 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7597 loss: 2.7597 2022/10/07 15:50:42 - mmengine - INFO - Epoch(train) [41][380/2119] lr: 4.0000e-02 eta: 22:04:35 time: 0.4045 data_time: 0.0240 memory: 5826 grad_norm: 3.0592 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6088 loss: 2.6088 2022/10/07 15:50:48 - mmengine - INFO - Epoch(train) [41][400/2119] lr: 4.0000e-02 eta: 22:04:27 time: 0.3214 data_time: 0.0303 memory: 5826 grad_norm: 3.0650 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8970 loss: 2.8970 2022/10/07 15:50:55 - mmengine - INFO - Epoch(train) [41][420/2119] lr: 4.0000e-02 eta: 22:04:22 time: 0.3726 data_time: 0.0215 memory: 5826 grad_norm: 3.0481 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6319 loss: 2.6319 2022/10/07 15:51:08 - mmengine - INFO - Epoch(train) [41][440/2119] lr: 4.0000e-02 eta: 22:04:31 time: 0.6316 data_time: 0.0515 memory: 5826 grad_norm: 3.0916 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9121 loss: 2.9121 2022/10/07 15:51:14 - mmengine - INFO - Epoch(train) [41][460/2119] lr: 4.0000e-02 eta: 22:04:22 time: 0.2999 data_time: 0.0255 memory: 5826 grad_norm: 3.0864 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8538 loss: 2.8538 2022/10/07 15:51:24 - mmengine - INFO - Epoch(train) [41][480/2119] lr: 4.0000e-02 eta: 22:04:23 time: 0.4909 data_time: 0.0303 memory: 5826 grad_norm: 3.0986 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9577 loss: 2.9577 2022/10/07 15:51:29 - mmengine - INFO - Epoch(train) [41][500/2119] lr: 4.0000e-02 eta: 22:04:13 time: 0.2761 data_time: 0.0212 memory: 5826 grad_norm: 3.0902 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7904 loss: 2.7904 2022/10/07 15:51:36 - mmengine - INFO - Epoch(train) [41][520/2119] lr: 4.0000e-02 eta: 22:04:05 time: 0.3280 data_time: 0.0373 memory: 5826 grad_norm: 3.0390 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8488 loss: 2.8488 2022/10/07 15:51:43 - mmengine - INFO - Epoch(train) [41][540/2119] lr: 4.0000e-02 eta: 22:04:00 time: 0.3709 data_time: 0.0179 memory: 5826 grad_norm: 3.1000 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7164 loss: 2.7164 2022/10/07 15:51:50 - mmengine - INFO - Epoch(train) [41][560/2119] lr: 4.0000e-02 eta: 22:03:53 time: 0.3452 data_time: 0.0208 memory: 5826 grad_norm: 3.0524 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8578 loss: 2.8578 2022/10/07 15:51:57 - mmengine - INFO - Epoch(train) [41][580/2119] lr: 4.0000e-02 eta: 22:03:45 time: 0.3187 data_time: 0.0223 memory: 5826 grad_norm: 3.0775 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9553 loss: 2.9553 2022/10/07 15:52:04 - mmengine - INFO - Epoch(train) [41][600/2119] lr: 4.0000e-02 eta: 22:03:39 time: 0.3460 data_time: 0.0222 memory: 5826 grad_norm: 3.0671 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0519 loss: 3.0519 2022/10/07 15:52:10 - mmengine - INFO - Epoch(train) [41][620/2119] lr: 4.0000e-02 eta: 22:03:32 time: 0.3412 data_time: 0.0191 memory: 5826 grad_norm: 3.0614 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7723 loss: 2.7723 2022/10/07 15:52:18 - mmengine - INFO - Epoch(train) [41][640/2119] lr: 4.0000e-02 eta: 22:03:27 time: 0.3720 data_time: 0.0181 memory: 5826 grad_norm: 3.0533 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5514 loss: 2.5514 2022/10/07 15:52:24 - mmengine - INFO - Epoch(train) [41][660/2119] lr: 4.0000e-02 eta: 22:03:18 time: 0.3085 data_time: 0.0179 memory: 5826 grad_norm: 3.0785 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6986 loss: 2.6986 2022/10/07 15:52:31 - mmengine - INFO - Epoch(train) [41][680/2119] lr: 4.0000e-02 eta: 22:03:11 time: 0.3367 data_time: 0.0148 memory: 5826 grad_norm: 3.0763 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6130 loss: 2.6130 2022/10/07 15:52:39 - mmengine - INFO - Epoch(train) [41][700/2119] lr: 4.0000e-02 eta: 22:03:07 time: 0.3933 data_time: 0.0221 memory: 5826 grad_norm: 3.1243 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8646 loss: 2.8646 2022/10/07 15:52:44 - mmengine - INFO - Epoch(train) [41][720/2119] lr: 4.0000e-02 eta: 22:02:57 time: 0.2831 data_time: 0.0217 memory: 5826 grad_norm: 3.0585 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8271 loss: 2.8271 2022/10/07 15:52:52 - mmengine - INFO - Epoch(train) [41][740/2119] lr: 4.0000e-02 eta: 22:02:53 time: 0.3937 data_time: 0.0215 memory: 5826 grad_norm: 3.1150 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7982 loss: 2.7982 2022/10/07 15:52:58 - mmengine - INFO - Epoch(train) [41][760/2119] lr: 4.0000e-02 eta: 22:02:45 time: 0.3125 data_time: 0.0188 memory: 5826 grad_norm: 3.0922 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.9386 loss: 2.9386 2022/10/07 15:53:05 - mmengine - INFO - Epoch(train) [41][780/2119] lr: 4.0000e-02 eta: 22:02:38 time: 0.3493 data_time: 0.0205 memory: 5826 grad_norm: 3.0824 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7416 loss: 2.7416 2022/10/07 15:53:12 - mmengine - INFO - Epoch(train) [41][800/2119] lr: 4.0000e-02 eta: 22:02:29 time: 0.3092 data_time: 0.0205 memory: 5826 grad_norm: 3.1148 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7706 loss: 2.7706 2022/10/07 15:53:19 - mmengine - INFO - Epoch(train) [41][820/2119] lr: 4.0000e-02 eta: 22:02:25 time: 0.3825 data_time: 0.0254 memory: 5826 grad_norm: 3.0909 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6235 loss: 2.6235 2022/10/07 15:53:25 - mmengine - INFO - Epoch(train) [41][840/2119] lr: 4.0000e-02 eta: 22:02:14 time: 0.2757 data_time: 0.0175 memory: 5826 grad_norm: 3.0809 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.7757 loss: 2.7757 2022/10/07 15:53:32 - mmengine - INFO - Epoch(train) [41][860/2119] lr: 4.0000e-02 eta: 22:02:10 time: 0.3807 data_time: 0.0280 memory: 5826 grad_norm: 3.1135 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.9026 loss: 2.9026 2022/10/07 15:53:39 - mmengine - INFO - Epoch(train) [41][880/2119] lr: 4.0000e-02 eta: 22:02:03 time: 0.3485 data_time: 0.0204 memory: 5826 grad_norm: 3.1230 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8543 loss: 2.8543 2022/10/07 15:53:47 - mmengine - INFO - Epoch(train) [41][900/2119] lr: 4.0000e-02 eta: 22:01:59 time: 0.3796 data_time: 0.0184 memory: 5826 grad_norm: 3.1164 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8439 loss: 2.8439 2022/10/07 15:53:53 - mmengine - INFO - Epoch(train) [41][920/2119] lr: 4.0000e-02 eta: 22:01:50 time: 0.3029 data_time: 0.0233 memory: 5826 grad_norm: 3.0918 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9113 loss: 2.9113 2022/10/07 15:54:01 - mmengine - INFO - Epoch(train) [41][940/2119] lr: 4.0000e-02 eta: 22:01:45 time: 0.3889 data_time: 0.0177 memory: 5826 grad_norm: 3.0766 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9368 loss: 2.9368 2022/10/07 15:54:08 - mmengine - INFO - Epoch(train) [41][960/2119] lr: 4.0000e-02 eta: 22:01:38 time: 0.3416 data_time: 0.0239 memory: 5826 grad_norm: 3.1038 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8052 loss: 2.8052 2022/10/07 15:54:15 - mmengine - INFO - Epoch(train) [41][980/2119] lr: 4.0000e-02 eta: 22:01:32 time: 0.3543 data_time: 0.0197 memory: 5826 grad_norm: 3.0575 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8806 loss: 2.8806 2022/10/07 15:54:21 - mmengine - INFO - Epoch(train) [41][1000/2119] lr: 4.0000e-02 eta: 22:01:24 time: 0.3053 data_time: 0.0194 memory: 5826 grad_norm: 3.0994 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7360 loss: 2.7360 2022/10/07 15:54:28 - mmengine - INFO - Epoch(train) [41][1020/2119] lr: 4.0000e-02 eta: 22:01:17 time: 0.3510 data_time: 0.0211 memory: 5826 grad_norm: 3.0661 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8542 loss: 2.8542 2022/10/07 15:54:34 - mmengine - INFO - Epoch(train) [41][1040/2119] lr: 4.0000e-02 eta: 22:01:09 time: 0.3068 data_time: 0.0241 memory: 5826 grad_norm: 3.1279 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6958 loss: 2.6958 2022/10/07 15:54:42 - mmengine - INFO - Epoch(train) [41][1060/2119] lr: 4.0000e-02 eta: 22:01:04 time: 0.3851 data_time: 0.0214 memory: 5826 grad_norm: 3.0524 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7990 loss: 2.7990 2022/10/07 15:54:48 - mmengine - INFO - Epoch(train) [41][1080/2119] lr: 4.0000e-02 eta: 22:00:55 time: 0.2961 data_time: 0.0191 memory: 5826 grad_norm: 3.1231 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5988 loss: 2.5988 2022/10/07 15:54:55 - mmengine - INFO - Epoch(train) [41][1100/2119] lr: 4.0000e-02 eta: 22:00:50 time: 0.3850 data_time: 0.0216 memory: 5826 grad_norm: 3.0722 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7609 loss: 2.7609 2022/10/07 15:55:02 - mmengine - INFO - Epoch(train) [41][1120/2119] lr: 4.0000e-02 eta: 22:00:43 time: 0.3373 data_time: 0.0205 memory: 5826 grad_norm: 3.0441 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6828 loss: 2.6828 2022/10/07 15:55:09 - mmengine - INFO - Epoch(train) [41][1140/2119] lr: 4.0000e-02 eta: 22:00:36 time: 0.3444 data_time: 0.0190 memory: 5826 grad_norm: 3.1774 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7447 loss: 2.7447 2022/10/07 15:55:16 - mmengine - INFO - Epoch(train) [41][1160/2119] lr: 4.0000e-02 eta: 22:00:29 time: 0.3361 data_time: 0.0226 memory: 5826 grad_norm: 3.1128 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8204 loss: 2.8204 2022/10/07 15:55:23 - mmengine - INFO - Epoch(train) [41][1180/2119] lr: 4.0000e-02 eta: 22:00:23 time: 0.3486 data_time: 0.0212 memory: 5826 grad_norm: 3.0978 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8331 loss: 2.8331 2022/10/07 15:55:30 - mmengine - INFO - Epoch(train) [41][1200/2119] lr: 4.0000e-02 eta: 22:00:16 time: 0.3457 data_time: 0.0289 memory: 5826 grad_norm: 3.0462 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7179 loss: 2.7179 2022/10/07 15:55:36 - mmengine - INFO - Epoch(train) [41][1220/2119] lr: 4.0000e-02 eta: 22:00:07 time: 0.3045 data_time: 0.0251 memory: 5826 grad_norm: 3.0735 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8080 loss: 2.8080 2022/10/07 15:55:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 15:55:43 - mmengine - INFO - Epoch(train) [41][1240/2119] lr: 4.0000e-02 eta: 22:00:01 time: 0.3490 data_time: 0.0208 memory: 5826 grad_norm: 3.0414 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7746 loss: 2.7746 2022/10/07 15:55:51 - mmengine - INFO - Epoch(train) [41][1260/2119] lr: 4.0000e-02 eta: 21:59:58 time: 0.4090 data_time: 0.0220 memory: 5826 grad_norm: 3.0714 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9330 loss: 2.9330 2022/10/07 15:55:57 - mmengine - INFO - Epoch(train) [41][1280/2119] lr: 4.0000e-02 eta: 21:59:49 time: 0.3035 data_time: 0.0273 memory: 5826 grad_norm: 3.0875 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8374 loss: 2.8374 2022/10/07 15:56:15 - mmengine - INFO - Epoch(train) [41][1300/2119] lr: 4.0000e-02 eta: 22:00:13 time: 0.9074 data_time: 0.1152 memory: 5826 grad_norm: 3.0461 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8409 loss: 2.8409 2022/10/07 15:56:30 - mmengine - INFO - Epoch(train) [41][1320/2119] lr: 4.0000e-02 eta: 22:00:28 time: 0.7467 data_time: 0.0515 memory: 5826 grad_norm: 3.0926 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7690 loss: 2.7690 2022/10/07 15:56:36 - mmengine - INFO - Epoch(train) [41][1340/2119] lr: 4.0000e-02 eta: 22:00:19 time: 0.3119 data_time: 0.0682 memory: 5826 grad_norm: 3.0696 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6162 loss: 2.6162 2022/10/07 15:56:44 - mmengine - INFO - Epoch(train) [41][1360/2119] lr: 4.0000e-02 eta: 22:00:16 time: 0.4029 data_time: 0.1499 memory: 5826 grad_norm: 3.0574 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8029 loss: 2.8029 2022/10/07 15:56:50 - mmengine - INFO - Epoch(train) [41][1380/2119] lr: 4.0000e-02 eta: 22:00:07 time: 0.3077 data_time: 0.0291 memory: 5826 grad_norm: 3.0085 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5664 loss: 2.5664 2022/10/07 15:56:58 - mmengine - INFO - Epoch(train) [41][1400/2119] lr: 4.0000e-02 eta: 22:00:02 time: 0.3859 data_time: 0.0229 memory: 5826 grad_norm: 3.0325 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6229 loss: 2.6229 2022/10/07 15:57:04 - mmengine - INFO - Epoch(train) [41][1420/2119] lr: 4.0000e-02 eta: 21:59:52 time: 0.2677 data_time: 0.0243 memory: 5826 grad_norm: 3.0085 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4970 loss: 2.4970 2022/10/07 15:57:18 - mmengine - INFO - Epoch(train) [41][1440/2119] lr: 4.0000e-02 eta: 22:00:05 time: 0.7162 data_time: 0.0268 memory: 5826 grad_norm: 3.1099 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.8341 loss: 2.8341 2022/10/07 15:57:38 - mmengine - INFO - Epoch(train) [41][1460/2119] lr: 4.0000e-02 eta: 22:00:33 time: 0.9945 data_time: 0.0180 memory: 5826 grad_norm: 3.0701 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.5578 loss: 2.5578 2022/10/07 15:57:50 - mmengine - INFO - Epoch(train) [41][1480/2119] lr: 4.0000e-02 eta: 22:00:42 time: 0.6325 data_time: 0.2020 memory: 5826 grad_norm: 3.0696 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8831 loss: 2.8831 2022/10/07 15:57:56 - mmengine - INFO - Epoch(train) [41][1500/2119] lr: 4.0000e-02 eta: 22:00:31 time: 0.2705 data_time: 0.0208 memory: 5826 grad_norm: 3.0624 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6269 loss: 2.6269 2022/10/07 15:58:08 - mmengine - INFO - Epoch(train) [41][1520/2119] lr: 4.0000e-02 eta: 22:00:39 time: 0.6167 data_time: 0.0446 memory: 5826 grad_norm: 3.1090 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7832 loss: 2.7832 2022/10/07 15:58:14 - mmengine - INFO - Epoch(train) [41][1540/2119] lr: 4.0000e-02 eta: 22:00:30 time: 0.2945 data_time: 0.0321 memory: 5826 grad_norm: 3.0473 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6697 loss: 2.6697 2022/10/07 15:58:21 - mmengine - INFO - Epoch(train) [41][1560/2119] lr: 4.0000e-02 eta: 22:00:23 time: 0.3472 data_time: 0.0499 memory: 5826 grad_norm: 3.1022 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9577 loss: 2.9577 2022/10/07 15:58:29 - mmengine - INFO - Epoch(train) [41][1580/2119] lr: 4.0000e-02 eta: 22:00:18 time: 0.3822 data_time: 0.0178 memory: 5826 grad_norm: 3.0899 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5775 loss: 2.5775 2022/10/07 15:58:35 - mmengine - INFO - Epoch(train) [41][1600/2119] lr: 4.0000e-02 eta: 22:00:10 time: 0.3165 data_time: 0.0187 memory: 5826 grad_norm: 3.1158 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.1170 loss: 3.1170 2022/10/07 15:58:42 - mmengine - INFO - Epoch(train) [41][1620/2119] lr: 4.0000e-02 eta: 22:00:05 time: 0.3738 data_time: 0.0272 memory: 5826 grad_norm: 3.0945 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8373 loss: 2.8373 2022/10/07 15:58:49 - mmengine - INFO - Epoch(train) [41][1640/2119] lr: 4.0000e-02 eta: 21:59:56 time: 0.3066 data_time: 0.0174 memory: 5826 grad_norm: 3.0912 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7882 loss: 2.7882 2022/10/07 15:58:56 - mmengine - INFO - Epoch(train) [41][1660/2119] lr: 4.0000e-02 eta: 21:59:50 time: 0.3518 data_time: 0.0247 memory: 5826 grad_norm: 3.0622 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7852 loss: 2.7852 2022/10/07 15:59:02 - mmengine - INFO - Epoch(train) [41][1680/2119] lr: 4.0000e-02 eta: 21:59:42 time: 0.3288 data_time: 0.0246 memory: 5826 grad_norm: 3.0617 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6010 loss: 2.6010 2022/10/07 15:59:09 - mmengine - INFO - Epoch(train) [41][1700/2119] lr: 4.0000e-02 eta: 21:59:36 time: 0.3517 data_time: 0.0220 memory: 5826 grad_norm: 3.0176 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7883 loss: 2.7883 2022/10/07 15:59:16 - mmengine - INFO - Epoch(train) [41][1720/2119] lr: 4.0000e-02 eta: 21:59:28 time: 0.3138 data_time: 0.0192 memory: 5826 grad_norm: 3.0815 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7966 loss: 2.7966 2022/10/07 15:59:23 - mmengine - INFO - Epoch(train) [41][1740/2119] lr: 4.0000e-02 eta: 21:59:21 time: 0.3524 data_time: 0.0239 memory: 5826 grad_norm: 3.1164 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8921 loss: 2.8921 2022/10/07 15:59:29 - mmengine - INFO - Epoch(train) [41][1760/2119] lr: 4.0000e-02 eta: 21:59:12 time: 0.3034 data_time: 0.0281 memory: 5826 grad_norm: 3.0548 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6370 loss: 2.6370 2022/10/07 15:59:36 - mmengine - INFO - Epoch(train) [41][1780/2119] lr: 4.0000e-02 eta: 21:59:06 time: 0.3444 data_time: 0.0185 memory: 5826 grad_norm: 3.1101 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7478 loss: 2.7478 2022/10/07 15:59:42 - mmengine - INFO - Epoch(train) [41][1800/2119] lr: 4.0000e-02 eta: 21:58:59 time: 0.3392 data_time: 0.0298 memory: 5826 grad_norm: 3.0635 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7752 loss: 2.7752 2022/10/07 15:59:50 - mmengine - INFO - Epoch(train) [41][1820/2119] lr: 4.0000e-02 eta: 21:58:53 time: 0.3615 data_time: 0.0216 memory: 5826 grad_norm: 3.0413 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8618 loss: 2.8618 2022/10/07 15:59:56 - mmengine - INFO - Epoch(train) [41][1840/2119] lr: 4.0000e-02 eta: 21:58:46 time: 0.3325 data_time: 0.0232 memory: 5826 grad_norm: 3.0719 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9038 loss: 2.9038 2022/10/07 16:00:03 - mmengine - INFO - Epoch(train) [41][1860/2119] lr: 4.0000e-02 eta: 21:58:38 time: 0.3374 data_time: 0.0210 memory: 5826 grad_norm: 3.1242 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7050 loss: 2.7050 2022/10/07 16:00:10 - mmengine - INFO - Epoch(train) [41][1880/2119] lr: 4.0000e-02 eta: 21:58:32 time: 0.3434 data_time: 0.0207 memory: 5826 grad_norm: 3.1526 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5739 loss: 2.5739 2022/10/07 16:00:17 - mmengine - INFO - Epoch(train) [41][1900/2119] lr: 4.0000e-02 eta: 21:58:25 time: 0.3537 data_time: 0.0200 memory: 5826 grad_norm: 3.1409 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7214 loss: 2.7214 2022/10/07 16:00:23 - mmengine - INFO - Epoch(train) [41][1920/2119] lr: 4.0000e-02 eta: 21:58:18 time: 0.3289 data_time: 0.0217 memory: 5826 grad_norm: 3.0751 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6035 loss: 2.6035 2022/10/07 16:00:31 - mmengine - INFO - Epoch(train) [41][1940/2119] lr: 4.0000e-02 eta: 21:58:12 time: 0.3582 data_time: 0.0166 memory: 5826 grad_norm: 3.0657 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8979 loss: 2.8979 2022/10/07 16:00:37 - mmengine - INFO - Epoch(train) [41][1960/2119] lr: 4.0000e-02 eta: 21:58:03 time: 0.2936 data_time: 0.0237 memory: 5826 grad_norm: 3.0277 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7358 loss: 2.7358 2022/10/07 16:00:44 - mmengine - INFO - Epoch(train) [41][1980/2119] lr: 4.0000e-02 eta: 21:57:57 time: 0.3678 data_time: 0.0183 memory: 5826 grad_norm: 3.0217 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8112 loss: 2.8112 2022/10/07 16:00:50 - mmengine - INFO - Epoch(train) [41][2000/2119] lr: 4.0000e-02 eta: 21:57:49 time: 0.3237 data_time: 0.0236 memory: 5826 grad_norm: 3.1293 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.6034 loss: 2.6034 2022/10/07 16:00:57 - mmengine - INFO - Epoch(train) [41][2020/2119] lr: 4.0000e-02 eta: 21:57:43 time: 0.3448 data_time: 0.0282 memory: 5826 grad_norm: 3.0929 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7050 loss: 2.7050 2022/10/07 16:01:04 - mmengine - INFO - Epoch(train) [41][2040/2119] lr: 4.0000e-02 eta: 21:57:34 time: 0.3134 data_time: 0.0271 memory: 5826 grad_norm: 3.0362 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8873 loss: 2.8873 2022/10/07 16:01:11 - mmengine - INFO - Epoch(train) [41][2060/2119] lr: 4.0000e-02 eta: 21:57:29 time: 0.3665 data_time: 0.0201 memory: 5826 grad_norm: 3.1205 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6791 loss: 2.6791 2022/10/07 16:01:18 - mmengine - INFO - Epoch(train) [41][2080/2119] lr: 4.0000e-02 eta: 21:57:22 time: 0.3476 data_time: 0.0197 memory: 5826 grad_norm: 3.0818 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8430 loss: 2.8430 2022/10/07 16:01:25 - mmengine - INFO - Epoch(train) [41][2100/2119] lr: 4.0000e-02 eta: 21:57:16 time: 0.3554 data_time: 0.0209 memory: 5826 grad_norm: 3.1062 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8444 loss: 2.8444 2022/10/07 16:01:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 16:01:30 - mmengine - INFO - Epoch(train) [41][2119/2119] lr: 4.0000e-02 eta: 21:57:16 time: 0.2807 data_time: 0.0152 memory: 5826 grad_norm: 3.1586 top1_acc: 0.5000 top5_acc: 0.8000 loss_cls: 2.7256 loss: 2.7256 2022/10/07 16:01:40 - mmengine - INFO - Epoch(train) [42][20/2119] lr: 4.0000e-02 eta: 21:56:52 time: 0.4705 data_time: 0.1535 memory: 5826 grad_norm: 3.0614 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8747 loss: 2.8747 2022/10/07 16:01:46 - mmengine - INFO - Epoch(train) [42][40/2119] lr: 4.0000e-02 eta: 21:56:43 time: 0.2970 data_time: 0.0156 memory: 5826 grad_norm: 3.0957 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8913 loss: 2.8913 2022/10/07 16:01:53 - mmengine - INFO - Epoch(train) [42][60/2119] lr: 4.0000e-02 eta: 21:56:37 time: 0.3611 data_time: 0.0387 memory: 5826 grad_norm: 3.1126 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8090 loss: 2.8090 2022/10/07 16:02:00 - mmengine - INFO - Epoch(train) [42][80/2119] lr: 4.0000e-02 eta: 21:56:30 time: 0.3345 data_time: 0.0227 memory: 5826 grad_norm: 3.0172 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7888 loss: 2.7888 2022/10/07 16:02:07 - mmengine - INFO - Epoch(train) [42][100/2119] lr: 4.0000e-02 eta: 21:56:24 time: 0.3581 data_time: 0.0230 memory: 5826 grad_norm: 3.0924 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6858 loss: 2.6858 2022/10/07 16:02:14 - mmengine - INFO - Epoch(train) [42][120/2119] lr: 4.0000e-02 eta: 21:56:17 time: 0.3449 data_time: 0.0297 memory: 5826 grad_norm: 3.1306 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8678 loss: 2.8678 2022/10/07 16:02:14 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 16:02:21 - mmengine - INFO - Epoch(train) [42][140/2119] lr: 4.0000e-02 eta: 21:56:11 time: 0.3545 data_time: 0.0250 memory: 5826 grad_norm: 3.1256 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8390 loss: 2.8390 2022/10/07 16:02:31 - mmengine - INFO - Epoch(train) [42][160/2119] lr: 4.0000e-02 eta: 21:56:13 time: 0.5088 data_time: 0.0237 memory: 5826 grad_norm: 3.0687 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6895 loss: 2.6895 2022/10/07 16:02:44 - mmengine - INFO - Epoch(train) [42][180/2119] lr: 4.0000e-02 eta: 21:56:21 time: 0.6270 data_time: 0.0249 memory: 5826 grad_norm: 3.1119 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7928 loss: 2.7928 2022/10/07 16:02:57 - mmengine - INFO - Epoch(train) [42][200/2119] lr: 4.0000e-02 eta: 21:56:33 time: 0.6941 data_time: 0.0280 memory: 5826 grad_norm: 3.0949 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9116 loss: 2.9116 2022/10/07 16:03:03 - mmengine - INFO - Epoch(train) [42][220/2119] lr: 4.0000e-02 eta: 21:56:23 time: 0.2849 data_time: 0.0344 memory: 5826 grad_norm: 3.0881 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8947 loss: 2.8947 2022/10/07 16:03:12 - mmengine - INFO - Epoch(train) [42][240/2119] lr: 4.0000e-02 eta: 21:56:20 time: 0.4171 data_time: 0.0241 memory: 5826 grad_norm: 3.0542 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8483 loss: 2.8483 2022/10/07 16:03:21 - mmengine - INFO - Epoch(train) [42][260/2119] lr: 4.0000e-02 eta: 21:56:19 time: 0.4522 data_time: 0.0232 memory: 5826 grad_norm: 3.0741 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7508 loss: 2.7508 2022/10/07 16:03:27 - mmengine - INFO - Epoch(train) [42][280/2119] lr: 4.0000e-02 eta: 21:56:11 time: 0.3249 data_time: 0.0378 memory: 5826 grad_norm: 3.0804 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5705 loss: 2.5705 2022/10/07 16:03:34 - mmengine - INFO - Epoch(train) [42][300/2119] lr: 4.0000e-02 eta: 21:56:05 time: 0.3568 data_time: 0.0227 memory: 5826 grad_norm: 3.0632 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.4771 loss: 2.4771 2022/10/07 16:03:41 - mmengine - INFO - Epoch(train) [42][320/2119] lr: 4.0000e-02 eta: 21:55:58 time: 0.3404 data_time: 0.0224 memory: 5826 grad_norm: 3.0146 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8442 loss: 2.8442 2022/10/07 16:03:47 - mmengine - INFO - Epoch(train) [42][340/2119] lr: 4.0000e-02 eta: 21:55:51 time: 0.3234 data_time: 0.0263 memory: 5826 grad_norm: 3.1299 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7851 loss: 2.7851 2022/10/07 16:03:55 - mmengine - INFO - Epoch(train) [42][360/2119] lr: 4.0000e-02 eta: 21:55:45 time: 0.3628 data_time: 0.0174 memory: 5826 grad_norm: 3.0641 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6259 loss: 2.6259 2022/10/07 16:04:02 - mmengine - INFO - Epoch(train) [42][380/2119] lr: 4.0000e-02 eta: 21:55:39 time: 0.3567 data_time: 0.0208 memory: 5826 grad_norm: 3.0476 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8766 loss: 2.8766 2022/10/07 16:04:15 - mmengine - INFO - Epoch(train) [42][400/2119] lr: 4.0000e-02 eta: 21:55:48 time: 0.6543 data_time: 0.0248 memory: 5826 grad_norm: 3.1138 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8496 loss: 2.8496 2022/10/07 16:04:22 - mmengine - INFO - Epoch(train) [42][420/2119] lr: 4.0000e-02 eta: 21:55:41 time: 0.3307 data_time: 0.0234 memory: 5826 grad_norm: 3.0893 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7267 loss: 2.7267 2022/10/07 16:04:31 - mmengine - INFO - Epoch(train) [42][440/2119] lr: 4.0000e-02 eta: 21:55:42 time: 0.4939 data_time: 0.0211 memory: 5826 grad_norm: 3.0879 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7374 loss: 2.7374 2022/10/07 16:04:37 - mmengine - INFO - Epoch(train) [42][460/2119] lr: 4.0000e-02 eta: 21:55:31 time: 0.2557 data_time: 0.0275 memory: 5826 grad_norm: 3.0521 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.7182 loss: 2.7182 2022/10/07 16:04:48 - mmengine - INFO - Epoch(train) [42][480/2119] lr: 4.0000e-02 eta: 21:55:37 time: 0.5853 data_time: 0.0528 memory: 5826 grad_norm: 3.0892 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5664 loss: 2.5664 2022/10/07 16:04:54 - mmengine - INFO - Epoch(train) [42][500/2119] lr: 4.0000e-02 eta: 21:55:27 time: 0.2859 data_time: 0.0287 memory: 5826 grad_norm: 3.1099 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8241 loss: 2.8241 2022/10/07 16:05:02 - mmengine - INFO - Epoch(train) [42][520/2119] lr: 4.0000e-02 eta: 21:55:23 time: 0.4001 data_time: 0.0591 memory: 5826 grad_norm: 3.0616 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8475 loss: 2.8475 2022/10/07 16:05:08 - mmengine - INFO - Epoch(train) [42][540/2119] lr: 4.0000e-02 eta: 21:55:14 time: 0.3064 data_time: 0.0171 memory: 5826 grad_norm: 3.0958 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6885 loss: 2.6885 2022/10/07 16:05:15 - mmengine - INFO - Epoch(train) [42][560/2119] lr: 4.0000e-02 eta: 21:55:07 time: 0.3347 data_time: 0.0237 memory: 5826 grad_norm: 3.1001 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6391 loss: 2.6391 2022/10/07 16:05:22 - mmengine - INFO - Epoch(train) [42][580/2119] lr: 4.0000e-02 eta: 21:55:01 time: 0.3640 data_time: 0.0189 memory: 5826 grad_norm: 3.0597 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9649 loss: 2.9649 2022/10/07 16:05:28 - mmengine - INFO - Epoch(train) [42][600/2119] lr: 4.0000e-02 eta: 21:54:51 time: 0.2789 data_time: 0.0253 memory: 5826 grad_norm: 3.0820 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7299 loss: 2.7299 2022/10/07 16:05:35 - mmengine - INFO - Epoch(train) [42][620/2119] lr: 4.0000e-02 eta: 21:54:46 time: 0.3788 data_time: 0.0215 memory: 5826 grad_norm: 3.0730 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.5233 loss: 2.5233 2022/10/07 16:05:43 - mmengine - INFO - Epoch(train) [42][640/2119] lr: 4.0000e-02 eta: 21:54:40 time: 0.3613 data_time: 0.0196 memory: 5826 grad_norm: 3.0261 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7089 loss: 2.7089 2022/10/07 16:05:50 - mmengine - INFO - Epoch(train) [42][660/2119] lr: 4.0000e-02 eta: 21:54:34 time: 0.3609 data_time: 0.0216 memory: 5826 grad_norm: 3.1299 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8566 loss: 2.8566 2022/10/07 16:05:56 - mmengine - INFO - Epoch(train) [42][680/2119] lr: 4.0000e-02 eta: 21:54:25 time: 0.2970 data_time: 0.0276 memory: 5826 grad_norm: 3.0979 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0283 loss: 3.0283 2022/10/07 16:06:03 - mmengine - INFO - Epoch(train) [42][700/2119] lr: 4.0000e-02 eta: 21:54:19 time: 0.3588 data_time: 0.0304 memory: 5826 grad_norm: 3.0992 top1_acc: 0.1875 top5_acc: 0.8125 loss_cls: 2.9084 loss: 2.9084 2022/10/07 16:06:10 - mmengine - INFO - Epoch(train) [42][720/2119] lr: 4.0000e-02 eta: 21:54:13 time: 0.3492 data_time: 0.0175 memory: 5826 grad_norm: 3.0809 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6706 loss: 2.6706 2022/10/07 16:06:17 - mmengine - INFO - Epoch(train) [42][740/2119] lr: 4.0000e-02 eta: 21:54:06 time: 0.3424 data_time: 0.0222 memory: 5826 grad_norm: 3.0868 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.9365 loss: 2.9365 2022/10/07 16:06:23 - mmengine - INFO - Epoch(train) [42][760/2119] lr: 4.0000e-02 eta: 21:53:57 time: 0.3020 data_time: 0.0243 memory: 5826 grad_norm: 3.1072 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7767 loss: 2.7767 2022/10/07 16:06:30 - mmengine - INFO - Epoch(train) [42][780/2119] lr: 4.0000e-02 eta: 21:53:50 time: 0.3521 data_time: 0.0218 memory: 5826 grad_norm: 3.0314 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5667 loss: 2.5667 2022/10/07 16:06:36 - mmengine - INFO - Epoch(train) [42][800/2119] lr: 4.0000e-02 eta: 21:53:43 time: 0.3293 data_time: 0.0206 memory: 5826 grad_norm: 3.0527 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.6329 loss: 2.6329 2022/10/07 16:06:43 - mmengine - INFO - Epoch(train) [42][820/2119] lr: 4.0000e-02 eta: 21:53:36 time: 0.3405 data_time: 0.0251 memory: 5826 grad_norm: 3.1090 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.9319 loss: 2.9319 2022/10/07 16:06:50 - mmengine - INFO - Epoch(train) [42][840/2119] lr: 4.0000e-02 eta: 21:53:30 time: 0.3553 data_time: 0.0225 memory: 5826 grad_norm: 3.0830 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7615 loss: 2.7615 2022/10/07 16:06:57 - mmengine - INFO - Epoch(train) [42][860/2119] lr: 4.0000e-02 eta: 21:53:23 time: 0.3465 data_time: 0.0198 memory: 5826 grad_norm: 3.0440 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8917 loss: 2.8917 2022/10/07 16:07:05 - mmengine - INFO - Epoch(train) [42][880/2119] lr: 4.0000e-02 eta: 21:53:18 time: 0.3680 data_time: 0.0239 memory: 5826 grad_norm: 3.0903 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.6967 loss: 2.6967 2022/10/07 16:07:12 - mmengine - INFO - Epoch(train) [42][900/2119] lr: 4.0000e-02 eta: 21:53:11 time: 0.3484 data_time: 0.0215 memory: 5826 grad_norm: 3.1614 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8178 loss: 2.8178 2022/10/07 16:07:19 - mmengine - INFO - Epoch(train) [42][920/2119] lr: 4.0000e-02 eta: 21:53:06 time: 0.3861 data_time: 0.0260 memory: 5826 grad_norm: 3.0415 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8383 loss: 2.8383 2022/10/07 16:07:26 - mmengine - INFO - Epoch(train) [42][940/2119] lr: 4.0000e-02 eta: 21:52:58 time: 0.3180 data_time: 0.0234 memory: 5826 grad_norm: 3.0301 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5694 loss: 2.5694 2022/10/07 16:07:33 - mmengine - INFO - Epoch(train) [42][960/2119] lr: 4.0000e-02 eta: 21:52:52 time: 0.3438 data_time: 0.0203 memory: 5826 grad_norm: 2.9847 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6019 loss: 2.6019 2022/10/07 16:07:40 - mmengine - INFO - Epoch(train) [42][980/2119] lr: 4.0000e-02 eta: 21:52:45 time: 0.3558 data_time: 0.0245 memory: 5826 grad_norm: 3.1329 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6426 loss: 2.6426 2022/10/07 16:07:46 - mmengine - INFO - Epoch(train) [42][1000/2119] lr: 4.0000e-02 eta: 21:52:37 time: 0.3146 data_time: 0.0307 memory: 5826 grad_norm: 3.1495 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9478 loss: 2.9478 2022/10/07 16:07:53 - mmengine - INFO - Epoch(train) [42][1020/2119] lr: 4.0000e-02 eta: 21:52:31 time: 0.3534 data_time: 0.0236 memory: 5826 grad_norm: 3.0711 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7821 loss: 2.7821 2022/10/07 16:07:59 - mmengine - INFO - Epoch(train) [42][1040/2119] lr: 4.0000e-02 eta: 21:52:22 time: 0.3086 data_time: 0.0221 memory: 5826 grad_norm: 3.0816 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8221 loss: 2.8221 2022/10/07 16:08:06 - mmengine - INFO - Epoch(train) [42][1060/2119] lr: 4.0000e-02 eta: 21:52:16 time: 0.3559 data_time: 0.0233 memory: 5826 grad_norm: 3.0877 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8483 loss: 2.8483 2022/10/07 16:08:12 - mmengine - INFO - Epoch(train) [42][1080/2119] lr: 4.0000e-02 eta: 21:52:07 time: 0.3062 data_time: 0.0206 memory: 5826 grad_norm: 3.0804 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9007 loss: 2.9007 2022/10/07 16:08:20 - mmengine - INFO - Epoch(train) [42][1100/2119] lr: 4.0000e-02 eta: 21:52:02 time: 0.3696 data_time: 0.0239 memory: 5826 grad_norm: 3.0743 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7386 loss: 2.7386 2022/10/07 16:08:27 - mmengine - INFO - Epoch(train) [42][1120/2119] lr: 4.0000e-02 eta: 21:51:56 time: 0.3589 data_time: 0.0194 memory: 5826 grad_norm: 3.0651 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6916 loss: 2.6916 2022/10/07 16:08:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 16:08:34 - mmengine - INFO - Epoch(train) [42][1140/2119] lr: 4.0000e-02 eta: 21:51:50 time: 0.3572 data_time: 0.0202 memory: 5826 grad_norm: 3.0825 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.6867 loss: 2.6867 2022/10/07 16:08:42 - mmengine - INFO - Epoch(train) [42][1160/2119] lr: 4.0000e-02 eta: 21:51:46 time: 0.4024 data_time: 0.0214 memory: 5826 grad_norm: 3.1043 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.6088 loss: 2.6088 2022/10/07 16:08:48 - mmengine - INFO - Epoch(train) [42][1180/2119] lr: 4.0000e-02 eta: 21:51:38 time: 0.3131 data_time: 0.0244 memory: 5826 grad_norm: 3.1530 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7927 loss: 2.7927 2022/10/07 16:08:56 - mmengine - INFO - Epoch(train) [42][1200/2119] lr: 4.0000e-02 eta: 21:51:31 time: 0.3527 data_time: 0.0207 memory: 5826 grad_norm: 3.0915 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8252 loss: 2.8252 2022/10/07 16:09:02 - mmengine - INFO - Epoch(train) [42][1220/2119] lr: 4.0000e-02 eta: 21:51:24 time: 0.3403 data_time: 0.0241 memory: 5826 grad_norm: 3.1193 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.7373 loss: 2.7373 2022/10/07 16:09:09 - mmengine - INFO - Epoch(train) [42][1240/2119] lr: 4.0000e-02 eta: 21:51:18 time: 0.3490 data_time: 0.0225 memory: 5826 grad_norm: 3.0506 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5457 loss: 2.5457 2022/10/07 16:09:15 - mmengine - INFO - Epoch(train) [42][1260/2119] lr: 4.0000e-02 eta: 21:51:08 time: 0.2824 data_time: 0.0189 memory: 5826 grad_norm: 3.0892 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8986 loss: 2.8986 2022/10/07 16:09:23 - mmengine - INFO - Epoch(train) [42][1280/2119] lr: 4.0000e-02 eta: 21:51:03 time: 0.3794 data_time: 0.0278 memory: 5826 grad_norm: 3.0313 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 2.7310 loss: 2.7310 2022/10/07 16:09:28 - mmengine - INFO - Epoch(train) [42][1300/2119] lr: 4.0000e-02 eta: 21:50:53 time: 0.2850 data_time: 0.0177 memory: 5826 grad_norm: 3.0842 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8198 loss: 2.8198 2022/10/07 16:09:34 - mmengine - INFO - Epoch(train) [42][1320/2119] lr: 4.0000e-02 eta: 21:50:45 time: 0.3114 data_time: 0.0221 memory: 5826 grad_norm: 3.1078 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4849 loss: 2.4849 2022/10/07 16:09:42 - mmengine - INFO - Epoch(train) [42][1340/2119] lr: 4.0000e-02 eta: 21:50:39 time: 0.3663 data_time: 0.0192 memory: 5826 grad_norm: 3.0313 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.8234 loss: 2.8234 2022/10/07 16:09:48 - mmengine - INFO - Epoch(train) [42][1360/2119] lr: 4.0000e-02 eta: 21:50:30 time: 0.2931 data_time: 0.0240 memory: 5826 grad_norm: 3.1048 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8633 loss: 2.8633 2022/10/07 16:09:54 - mmengine - INFO - Epoch(train) [42][1380/2119] lr: 4.0000e-02 eta: 21:50:23 time: 0.3370 data_time: 0.0205 memory: 5826 grad_norm: 3.1009 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7227 loss: 2.7227 2022/10/07 16:10:02 - mmengine - INFO - Epoch(train) [42][1400/2119] lr: 4.0000e-02 eta: 21:50:17 time: 0.3750 data_time: 0.0222 memory: 5826 grad_norm: 3.1363 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9099 loss: 2.9099 2022/10/07 16:10:08 - mmengine - INFO - Epoch(train) [42][1420/2119] lr: 4.0000e-02 eta: 21:50:09 time: 0.3070 data_time: 0.0229 memory: 5826 grad_norm: 3.1015 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9091 loss: 2.9091 2022/10/07 16:10:15 - mmengine - INFO - Epoch(train) [42][1440/2119] lr: 4.0000e-02 eta: 21:50:02 time: 0.3542 data_time: 0.0231 memory: 5826 grad_norm: 3.0932 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9129 loss: 2.9129 2022/10/07 16:10:23 - mmengine - INFO - Epoch(train) [42][1460/2119] lr: 4.0000e-02 eta: 21:49:57 time: 0.3700 data_time: 0.0175 memory: 5826 grad_norm: 3.0556 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8595 loss: 2.8595 2022/10/07 16:10:29 - mmengine - INFO - Epoch(train) [42][1480/2119] lr: 4.0000e-02 eta: 21:49:49 time: 0.3166 data_time: 0.0198 memory: 5826 grad_norm: 3.0599 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0197 loss: 3.0197 2022/10/07 16:10:36 - mmengine - INFO - Epoch(train) [42][1500/2119] lr: 4.0000e-02 eta: 21:49:43 time: 0.3578 data_time: 0.0200 memory: 5826 grad_norm: 3.1242 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7462 loss: 2.7462 2022/10/07 16:10:46 - mmengine - INFO - Epoch(train) [42][1520/2119] lr: 4.0000e-02 eta: 21:49:45 time: 0.5108 data_time: 0.0434 memory: 5826 grad_norm: 3.0147 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8857 loss: 2.8857 2022/10/07 16:10:56 - mmengine - INFO - Epoch(train) [42][1540/2119] lr: 4.0000e-02 eta: 21:49:47 time: 0.5109 data_time: 0.0254 memory: 5826 grad_norm: 3.0543 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7460 loss: 2.7460 2022/10/07 16:11:04 - mmengine - INFO - Epoch(train) [42][1560/2119] lr: 4.0000e-02 eta: 21:49:41 time: 0.3631 data_time: 0.0286 memory: 5826 grad_norm: 3.0803 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9118 loss: 2.9118 2022/10/07 16:11:24 - mmengine - INFO - Epoch(train) [42][1580/2119] lr: 4.0000e-02 eta: 21:50:09 time: 1.0116 data_time: 0.0188 memory: 5826 grad_norm: 3.0455 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8338 loss: 2.8338 2022/10/07 16:11:38 - mmengine - INFO - Epoch(train) [42][1600/2119] lr: 4.0000e-02 eta: 21:50:20 time: 0.6879 data_time: 0.3672 memory: 5826 grad_norm: 3.0782 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9550 loss: 2.9550 2022/10/07 16:11:44 - mmengine - INFO - Epoch(train) [42][1620/2119] lr: 4.0000e-02 eta: 21:50:10 time: 0.2952 data_time: 0.0197 memory: 5826 grad_norm: 3.0960 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6427 loss: 2.6427 2022/10/07 16:11:51 - mmengine - INFO - Epoch(train) [42][1640/2119] lr: 4.0000e-02 eta: 21:50:05 time: 0.3685 data_time: 0.0185 memory: 5826 grad_norm: 3.0014 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6472 loss: 2.6472 2022/10/07 16:11:57 - mmengine - INFO - Epoch(train) [42][1660/2119] lr: 4.0000e-02 eta: 21:49:57 time: 0.3181 data_time: 0.0227 memory: 5826 grad_norm: 3.0718 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5779 loss: 2.5779 2022/10/07 16:12:07 - mmengine - INFO - Epoch(train) [42][1680/2119] lr: 4.0000e-02 eta: 21:49:56 time: 0.4552 data_time: 0.0277 memory: 5826 grad_norm: 3.0659 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6885 loss: 2.6885 2022/10/07 16:12:13 - mmengine - INFO - Epoch(train) [42][1700/2119] lr: 4.0000e-02 eta: 21:49:48 time: 0.3245 data_time: 0.0272 memory: 5826 grad_norm: 3.0972 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7860 loss: 2.7860 2022/10/07 16:12:22 - mmengine - INFO - Epoch(train) [42][1720/2119] lr: 4.0000e-02 eta: 21:49:47 time: 0.4583 data_time: 0.0206 memory: 5826 grad_norm: 3.1057 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6561 loss: 2.6561 2022/10/07 16:12:29 - mmengine - INFO - Epoch(train) [42][1740/2119] lr: 4.0000e-02 eta: 21:49:41 time: 0.3658 data_time: 0.0235 memory: 5826 grad_norm: 3.1283 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6893 loss: 2.6893 2022/10/07 16:12:35 - mmengine - INFO - Epoch(train) [42][1760/2119] lr: 4.0000e-02 eta: 21:49:32 time: 0.2926 data_time: 0.0204 memory: 5826 grad_norm: 3.0346 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.0048 loss: 3.0048 2022/10/07 16:12:54 - mmengine - INFO - Epoch(train) [42][1780/2119] lr: 4.0000e-02 eta: 21:49:55 time: 0.9280 data_time: 0.0299 memory: 5826 grad_norm: 3.1256 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 3.0397 loss: 3.0397 2022/10/07 16:13:14 - mmengine - INFO - Epoch(train) [42][1800/2119] lr: 4.0000e-02 eta: 21:50:24 time: 1.0243 data_time: 0.6052 memory: 5826 grad_norm: 3.0815 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.8332 loss: 2.8332 2022/10/07 16:13:20 - mmengine - INFO - Epoch(train) [42][1820/2119] lr: 4.0000e-02 eta: 21:50:13 time: 0.2700 data_time: 0.0312 memory: 5826 grad_norm: 3.0802 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9345 loss: 2.9345 2022/10/07 16:13:28 - mmengine - INFO - Epoch(train) [42][1840/2119] lr: 4.0000e-02 eta: 21:50:09 time: 0.3982 data_time: 0.0221 memory: 5826 grad_norm: 3.1378 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9003 loss: 2.9003 2022/10/07 16:13:34 - mmengine - INFO - Epoch(train) [42][1860/2119] lr: 4.0000e-02 eta: 21:50:01 time: 0.3241 data_time: 0.0209 memory: 5826 grad_norm: 3.0059 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6270 loss: 2.6270 2022/10/07 16:13:42 - mmengine - INFO - Epoch(train) [42][1880/2119] lr: 4.0000e-02 eta: 21:49:55 time: 0.3620 data_time: 0.0229 memory: 5826 grad_norm: 2.9696 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.6658 loss: 2.6658 2022/10/07 16:13:48 - mmengine - INFO - Epoch(train) [42][1900/2119] lr: 4.0000e-02 eta: 21:49:48 time: 0.3296 data_time: 0.0267 memory: 5826 grad_norm: 3.0866 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9190 loss: 2.9190 2022/10/07 16:13:54 - mmengine - INFO - Epoch(train) [42][1920/2119] lr: 4.0000e-02 eta: 21:49:39 time: 0.3032 data_time: 0.0246 memory: 5826 grad_norm: 3.0918 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8346 loss: 2.8346 2022/10/07 16:14:01 - mmengine - INFO - Epoch(train) [42][1940/2119] lr: 4.0000e-02 eta: 21:49:32 time: 0.3458 data_time: 0.0215 memory: 5826 grad_norm: 3.0567 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7940 loss: 2.7940 2022/10/07 16:14:08 - mmengine - INFO - Epoch(train) [42][1960/2119] lr: 4.0000e-02 eta: 21:49:27 time: 0.3681 data_time: 0.0345 memory: 5826 grad_norm: 3.0846 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9484 loss: 2.9484 2022/10/07 16:14:15 - mmengine - INFO - Epoch(train) [42][1980/2119] lr: 4.0000e-02 eta: 21:49:19 time: 0.3240 data_time: 0.0258 memory: 5826 grad_norm: 3.0762 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5664 loss: 2.5664 2022/10/07 16:14:21 - mmengine - INFO - Epoch(train) [42][2000/2119] lr: 4.0000e-02 eta: 21:49:11 time: 0.3209 data_time: 0.0239 memory: 5826 grad_norm: 3.0614 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7749 loss: 2.7749 2022/10/07 16:14:28 - mmengine - INFO - Epoch(train) [42][2020/2119] lr: 4.0000e-02 eta: 21:49:03 time: 0.3268 data_time: 0.0244 memory: 5826 grad_norm: 3.0544 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6266 loss: 2.6266 2022/10/07 16:14:35 - mmengine - INFO - Epoch(train) [42][2040/2119] lr: 4.0000e-02 eta: 21:48:57 time: 0.3524 data_time: 0.0194 memory: 5826 grad_norm: 3.1041 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.2225 loss: 3.2225 2022/10/07 16:14:41 - mmengine - INFO - Epoch(train) [42][2060/2119] lr: 4.0000e-02 eta: 21:48:48 time: 0.3167 data_time: 0.0242 memory: 5826 grad_norm: 3.0370 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8025 loss: 2.8025 2022/10/07 16:14:48 - mmengine - INFO - Epoch(train) [42][2080/2119] lr: 4.0000e-02 eta: 21:48:42 time: 0.3460 data_time: 0.0279 memory: 5826 grad_norm: 3.1228 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7453 loss: 2.7453 2022/10/07 16:14:55 - mmengine - INFO - Epoch(train) [42][2100/2119] lr: 4.0000e-02 eta: 21:48:35 time: 0.3506 data_time: 0.0192 memory: 5826 grad_norm: 3.1050 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9582 loss: 2.9582 2022/10/07 16:15:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 16:15:02 - mmengine - INFO - Epoch(train) [42][2119/2119] lr: 4.0000e-02 eta: 21:48:35 time: 0.3425 data_time: 0.0204 memory: 5826 grad_norm: 3.0704 top1_acc: 0.4000 top5_acc: 0.7000 loss_cls: 2.8923 loss: 2.8923 2022/10/07 16:15:05 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 16:15:12 - mmengine - INFO - Epoch(train) [43][20/2119] lr: 4.0000e-02 eta: 21:48:13 time: 0.4897 data_time: 0.1070 memory: 5826 grad_norm: 3.0851 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8956 loss: 2.8956 2022/10/07 16:15:18 - mmengine - INFO - Epoch(train) [43][40/2119] lr: 4.0000e-02 eta: 21:48:04 time: 0.3110 data_time: 0.0198 memory: 5826 grad_norm: 3.1350 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9234 loss: 2.9234 2022/10/07 16:15:25 - mmengine - INFO - Epoch(train) [43][60/2119] lr: 4.0000e-02 eta: 21:47:57 time: 0.3409 data_time: 0.0214 memory: 5826 grad_norm: 3.1085 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6021 loss: 2.6021 2022/10/07 16:15:31 - mmengine - INFO - Epoch(train) [43][80/2119] lr: 4.0000e-02 eta: 21:47:49 time: 0.3210 data_time: 0.0206 memory: 5826 grad_norm: 3.0933 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9048 loss: 2.9048 2022/10/07 16:15:39 - mmengine - INFO - Epoch(train) [43][100/2119] lr: 4.0000e-02 eta: 21:47:44 time: 0.3724 data_time: 0.0203 memory: 5826 grad_norm: 3.0324 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8526 loss: 2.8526 2022/10/07 16:15:45 - mmengine - INFO - Epoch(train) [43][120/2119] lr: 4.0000e-02 eta: 21:47:36 time: 0.3205 data_time: 0.0218 memory: 5826 grad_norm: 3.0838 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.6955 loss: 2.6955 2022/10/07 16:15:52 - mmengine - INFO - Epoch(train) [43][140/2119] lr: 4.0000e-02 eta: 21:47:28 time: 0.3325 data_time: 0.0207 memory: 5826 grad_norm: 3.0981 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.4649 loss: 2.4649 2022/10/07 16:15:58 - mmengine - INFO - Epoch(train) [43][160/2119] lr: 4.0000e-02 eta: 21:47:19 time: 0.3003 data_time: 0.0256 memory: 5826 grad_norm: 3.0720 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5189 loss: 2.5189 2022/10/07 16:16:05 - mmengine - INFO - Epoch(train) [43][180/2119] lr: 4.0000e-02 eta: 21:47:13 time: 0.3530 data_time: 0.0211 memory: 5826 grad_norm: 3.0781 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7555 loss: 2.7555 2022/10/07 16:16:12 - mmengine - INFO - Epoch(train) [43][200/2119] lr: 4.0000e-02 eta: 21:47:06 time: 0.3387 data_time: 0.0213 memory: 5826 grad_norm: 3.0950 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6867 loss: 2.6867 2022/10/07 16:16:19 - mmengine - INFO - Epoch(train) [43][220/2119] lr: 4.0000e-02 eta: 21:47:01 time: 0.3772 data_time: 0.0172 memory: 5826 grad_norm: 3.0691 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.2254 loss: 3.2254 2022/10/07 16:16:26 - mmengine - INFO - Epoch(train) [43][240/2119] lr: 4.0000e-02 eta: 21:46:53 time: 0.3223 data_time: 0.0193 memory: 5826 grad_norm: 3.1047 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8777 loss: 2.8777 2022/10/07 16:16:32 - mmengine - INFO - Epoch(train) [43][260/2119] lr: 4.0000e-02 eta: 21:46:44 time: 0.3136 data_time: 0.0224 memory: 5826 grad_norm: 3.0658 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6391 loss: 2.6391 2022/10/07 16:16:38 - mmengine - INFO - Epoch(train) [43][280/2119] lr: 4.0000e-02 eta: 21:46:36 time: 0.3185 data_time: 0.0201 memory: 5826 grad_norm: 3.0730 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.8109 loss: 2.8109 2022/10/07 16:16:45 - mmengine - INFO - Epoch(train) [43][300/2119] lr: 4.0000e-02 eta: 21:46:29 time: 0.3377 data_time: 0.0170 memory: 5826 grad_norm: 3.0626 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.5464 loss: 2.5464 2022/10/07 16:16:52 - mmengine - INFO - Epoch(train) [43][320/2119] lr: 4.0000e-02 eta: 21:46:22 time: 0.3421 data_time: 0.0235 memory: 5826 grad_norm: 3.1300 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9748 loss: 2.9748 2022/10/07 16:16:59 - mmengine - INFO - Epoch(train) [43][340/2119] lr: 4.0000e-02 eta: 21:46:16 time: 0.3569 data_time: 0.0243 memory: 5826 grad_norm: 3.0764 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7393 loss: 2.7393 2022/10/07 16:17:05 - mmengine - INFO - Epoch(train) [43][360/2119] lr: 4.0000e-02 eta: 21:46:09 time: 0.3274 data_time: 0.0249 memory: 5826 grad_norm: 3.1740 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8081 loss: 2.8081 2022/10/07 16:17:12 - mmengine - INFO - Epoch(train) [43][380/2119] lr: 4.0000e-02 eta: 21:46:02 time: 0.3506 data_time: 0.0235 memory: 5826 grad_norm: 3.0387 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7445 loss: 2.7445 2022/10/07 16:17:19 - mmengine - INFO - Epoch(train) [43][400/2119] lr: 4.0000e-02 eta: 21:45:54 time: 0.3114 data_time: 0.0216 memory: 5826 grad_norm: 3.0747 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7321 loss: 2.7321 2022/10/07 16:17:25 - mmengine - INFO - Epoch(train) [43][420/2119] lr: 4.0000e-02 eta: 21:45:46 time: 0.3346 data_time: 0.0254 memory: 5826 grad_norm: 3.1013 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7382 loss: 2.7382 2022/10/07 16:17:32 - mmengine - INFO - Epoch(train) [43][440/2119] lr: 4.0000e-02 eta: 21:45:39 time: 0.3352 data_time: 0.0279 memory: 5826 grad_norm: 3.0700 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8259 loss: 2.8259 2022/10/07 16:17:39 - mmengine - INFO - Epoch(train) [43][460/2119] lr: 4.0000e-02 eta: 21:45:32 time: 0.3301 data_time: 0.0240 memory: 5826 grad_norm: 3.0699 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8306 loss: 2.8306 2022/10/07 16:17:47 - mmengine - INFO - Epoch(train) [43][480/2119] lr: 4.0000e-02 eta: 21:45:28 time: 0.3990 data_time: 0.0194 memory: 5826 grad_norm: 3.1417 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7365 loss: 2.7365 2022/10/07 16:17:54 - mmengine - INFO - Epoch(train) [43][500/2119] lr: 4.0000e-02 eta: 21:45:22 time: 0.3635 data_time: 0.0220 memory: 5826 grad_norm: 3.0894 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8130 loss: 2.8130 2022/10/07 16:18:01 - mmengine - INFO - Epoch(train) [43][520/2119] lr: 4.0000e-02 eta: 21:45:15 time: 0.3450 data_time: 0.0222 memory: 5826 grad_norm: 3.1388 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6676 loss: 2.6676 2022/10/07 16:18:07 - mmengine - INFO - Epoch(train) [43][540/2119] lr: 4.0000e-02 eta: 21:45:05 time: 0.2907 data_time: 0.0219 memory: 5826 grad_norm: 3.0838 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7783 loss: 2.7783 2022/10/07 16:18:14 - mmengine - INFO - Epoch(train) [43][560/2119] lr: 4.0000e-02 eta: 21:45:00 time: 0.3716 data_time: 0.0217 memory: 5826 grad_norm: 3.1217 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6960 loss: 2.6960 2022/10/07 16:18:20 - mmengine - INFO - Epoch(train) [43][580/2119] lr: 4.0000e-02 eta: 21:44:52 time: 0.3133 data_time: 0.0243 memory: 5826 grad_norm: 3.1014 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8732 loss: 2.8732 2022/10/07 16:18:27 - mmengine - INFO - Epoch(train) [43][600/2119] lr: 4.0000e-02 eta: 21:44:45 time: 0.3409 data_time: 0.0242 memory: 5826 grad_norm: 3.0985 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7492 loss: 2.7492 2022/10/07 16:18:35 - mmengine - INFO - Epoch(train) [43][620/2119] lr: 4.0000e-02 eta: 21:44:40 time: 0.3771 data_time: 0.0190 memory: 5826 grad_norm: 3.1609 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7644 loss: 2.7644 2022/10/07 16:18:42 - mmengine - INFO - Epoch(train) [43][640/2119] lr: 4.0000e-02 eta: 21:44:33 time: 0.3398 data_time: 0.0222 memory: 5826 grad_norm: 3.0805 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6411 loss: 2.6411 2022/10/07 16:18:48 - mmengine - INFO - Epoch(train) [43][660/2119] lr: 4.0000e-02 eta: 21:44:25 time: 0.3238 data_time: 0.0216 memory: 5826 grad_norm: 3.0602 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8244 loss: 2.8244 2022/10/07 16:18:55 - mmengine - INFO - Epoch(train) [43][680/2119] lr: 4.0000e-02 eta: 21:44:17 time: 0.3274 data_time: 0.0214 memory: 5826 grad_norm: 3.0945 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7553 loss: 2.7553 2022/10/07 16:19:02 - mmengine - INFO - Epoch(train) [43][700/2119] lr: 4.0000e-02 eta: 21:44:11 time: 0.3503 data_time: 0.0247 memory: 5826 grad_norm: 3.0578 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7591 loss: 2.7591 2022/10/07 16:19:08 - mmengine - INFO - Epoch(train) [43][720/2119] lr: 4.0000e-02 eta: 21:44:02 time: 0.3164 data_time: 0.0228 memory: 5826 grad_norm: 3.0900 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8302 loss: 2.8302 2022/10/07 16:19:15 - mmengine - INFO - Epoch(train) [43][740/2119] lr: 4.0000e-02 eta: 21:43:56 time: 0.3479 data_time: 0.0189 memory: 5826 grad_norm: 3.0887 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5609 loss: 2.5609 2022/10/07 16:19:21 - mmengine - INFO - Epoch(train) [43][760/2119] lr: 4.0000e-02 eta: 21:43:47 time: 0.3137 data_time: 0.0197 memory: 5826 grad_norm: 3.0629 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 3.0097 loss: 3.0097 2022/10/07 16:19:28 - mmengine - INFO - Epoch(train) [43][780/2119] lr: 4.0000e-02 eta: 21:43:42 time: 0.3631 data_time: 0.0179 memory: 5826 grad_norm: 3.1254 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5472 loss: 2.5472 2022/10/07 16:19:35 - mmengine - INFO - Epoch(train) [43][800/2119] lr: 4.0000e-02 eta: 21:43:33 time: 0.3150 data_time: 0.0224 memory: 5826 grad_norm: 3.0844 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6673 loss: 2.6673 2022/10/07 16:19:41 - mmengine - INFO - Epoch(train) [43][820/2119] lr: 4.0000e-02 eta: 21:43:24 time: 0.3042 data_time: 0.0198 memory: 5826 grad_norm: 3.0881 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8163 loss: 2.8163 2022/10/07 16:19:48 - mmengine - INFO - Epoch(train) [43][840/2119] lr: 4.0000e-02 eta: 21:43:18 time: 0.3420 data_time: 0.0241 memory: 5826 grad_norm: 3.1579 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7435 loss: 2.7435 2022/10/07 16:19:56 - mmengine - INFO - Epoch(train) [43][860/2119] lr: 4.0000e-02 eta: 21:43:14 time: 0.4105 data_time: 0.0217 memory: 5826 grad_norm: 3.1235 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8207 loss: 2.8207 2022/10/07 16:20:01 - mmengine - INFO - Epoch(train) [43][880/2119] lr: 4.0000e-02 eta: 21:43:04 time: 0.2742 data_time: 0.0236 memory: 5826 grad_norm: 3.1759 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9175 loss: 2.9175 2022/10/07 16:20:09 - mmengine - INFO - Epoch(train) [43][900/2119] lr: 4.0000e-02 eta: 21:42:58 time: 0.3662 data_time: 0.0262 memory: 5826 grad_norm: 3.0743 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7984 loss: 2.7984 2022/10/07 16:20:15 - mmengine - INFO - Epoch(train) [43][920/2119] lr: 4.0000e-02 eta: 21:42:50 time: 0.3231 data_time: 0.0260 memory: 5826 grad_norm: 3.0329 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6419 loss: 2.6419 2022/10/07 16:20:22 - mmengine - INFO - Epoch(train) [43][940/2119] lr: 4.0000e-02 eta: 21:42:42 time: 0.3199 data_time: 0.0246 memory: 5826 grad_norm: 3.0755 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9428 loss: 2.9428 2022/10/07 16:20:28 - mmengine - INFO - Epoch(train) [43][960/2119] lr: 4.0000e-02 eta: 21:42:34 time: 0.3170 data_time: 0.0290 memory: 5826 grad_norm: 3.1203 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7740 loss: 2.7740 2022/10/07 16:20:35 - mmengine - INFO - Epoch(train) [43][980/2119] lr: 4.0000e-02 eta: 21:42:27 time: 0.3397 data_time: 0.0215 memory: 5826 grad_norm: 3.1174 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7755 loss: 2.7755 2022/10/07 16:20:42 - mmengine - INFO - Epoch(train) [43][1000/2119] lr: 4.0000e-02 eta: 21:42:21 time: 0.3682 data_time: 0.0156 memory: 5826 grad_norm: 3.0963 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8253 loss: 2.8253 2022/10/07 16:20:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 16:20:49 - mmengine - INFO - Epoch(train) [43][1020/2119] lr: 4.0000e-02 eta: 21:42:14 time: 0.3332 data_time: 0.0227 memory: 5826 grad_norm: 3.1045 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7709 loss: 2.7709 2022/10/07 16:20:55 - mmengine - INFO - Epoch(train) [43][1040/2119] lr: 4.0000e-02 eta: 21:42:06 time: 0.3183 data_time: 0.0191 memory: 5826 grad_norm: 3.1375 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9649 loss: 2.9649 2022/10/07 16:21:03 - mmengine - INFO - Epoch(train) [43][1060/2119] lr: 4.0000e-02 eta: 21:42:01 time: 0.3710 data_time: 0.0219 memory: 5826 grad_norm: 3.1102 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9897 loss: 2.9897 2022/10/07 16:21:08 - mmengine - INFO - Epoch(train) [43][1080/2119] lr: 4.0000e-02 eta: 21:41:50 time: 0.2701 data_time: 0.0237 memory: 5826 grad_norm: 3.1018 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6973 loss: 2.6973 2022/10/07 16:21:15 - mmengine - INFO - Epoch(train) [43][1100/2119] lr: 4.0000e-02 eta: 21:41:45 time: 0.3749 data_time: 0.0259 memory: 5826 grad_norm: 3.0820 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6117 loss: 2.6117 2022/10/07 16:21:22 - mmengine - INFO - Epoch(train) [43][1120/2119] lr: 4.0000e-02 eta: 21:41:38 time: 0.3409 data_time: 0.0182 memory: 5826 grad_norm: 3.0658 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.9270 loss: 2.9270 2022/10/07 16:21:29 - mmengine - INFO - Epoch(train) [43][1140/2119] lr: 4.0000e-02 eta: 21:41:30 time: 0.3336 data_time: 0.0209 memory: 5826 grad_norm: 3.0887 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6888 loss: 2.6888 2022/10/07 16:21:35 - mmengine - INFO - Epoch(train) [43][1160/2119] lr: 4.0000e-02 eta: 21:41:22 time: 0.3092 data_time: 0.0283 memory: 5826 grad_norm: 3.1264 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9319 loss: 2.9319 2022/10/07 16:21:42 - mmengine - INFO - Epoch(train) [43][1180/2119] lr: 4.0000e-02 eta: 21:41:16 time: 0.3642 data_time: 0.0233 memory: 5826 grad_norm: 3.1180 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8901 loss: 2.8901 2022/10/07 16:21:49 - mmengine - INFO - Epoch(train) [43][1200/2119] lr: 4.0000e-02 eta: 21:41:09 time: 0.3286 data_time: 0.0195 memory: 5826 grad_norm: 3.0568 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6196 loss: 2.6196 2022/10/07 16:21:56 - mmengine - INFO - Epoch(train) [43][1220/2119] lr: 4.0000e-02 eta: 21:41:01 time: 0.3365 data_time: 0.0252 memory: 5826 grad_norm: 3.0644 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7351 loss: 2.7351 2022/10/07 16:22:03 - mmengine - INFO - Epoch(train) [43][1240/2119] lr: 4.0000e-02 eta: 21:40:56 time: 0.3804 data_time: 0.0224 memory: 5826 grad_norm: 3.0632 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6608 loss: 2.6608 2022/10/07 16:22:09 - mmengine - INFO - Epoch(train) [43][1260/2119] lr: 4.0000e-02 eta: 21:40:48 time: 0.3067 data_time: 0.0214 memory: 5826 grad_norm: 3.0380 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8516 loss: 2.8516 2022/10/07 16:22:17 - mmengine - INFO - Epoch(train) [43][1280/2119] lr: 4.0000e-02 eta: 21:40:42 time: 0.3729 data_time: 0.0195 memory: 5826 grad_norm: 3.0780 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9703 loss: 2.9703 2022/10/07 16:22:23 - mmengine - INFO - Epoch(train) [43][1300/2119] lr: 4.0000e-02 eta: 21:40:33 time: 0.2963 data_time: 0.0183 memory: 5826 grad_norm: 3.0564 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8359 loss: 2.8359 2022/10/07 16:22:30 - mmengine - INFO - Epoch(train) [43][1320/2119] lr: 4.0000e-02 eta: 21:40:28 time: 0.3709 data_time: 0.0205 memory: 5826 grad_norm: 3.0869 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8310 loss: 2.8310 2022/10/07 16:22:36 - mmengine - INFO - Epoch(train) [43][1340/2119] lr: 4.0000e-02 eta: 21:40:18 time: 0.2837 data_time: 0.0232 memory: 5826 grad_norm: 3.0955 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7101 loss: 2.7101 2022/10/07 16:22:44 - mmengine - INFO - Epoch(train) [43][1360/2119] lr: 4.0000e-02 eta: 21:40:13 time: 0.3910 data_time: 0.0385 memory: 5826 grad_norm: 3.0813 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6208 loss: 2.6208 2022/10/07 16:22:51 - mmengine - INFO - Epoch(train) [43][1380/2119] lr: 4.0000e-02 eta: 21:40:07 time: 0.3532 data_time: 0.0254 memory: 5826 grad_norm: 3.1173 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8583 loss: 2.8583 2022/10/07 16:22:57 - mmengine - INFO - Epoch(train) [43][1400/2119] lr: 4.0000e-02 eta: 21:39:59 time: 0.3128 data_time: 0.0214 memory: 5826 grad_norm: 3.0805 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7135 loss: 2.7135 2022/10/07 16:23:05 - mmengine - INFO - Epoch(train) [43][1420/2119] lr: 4.0000e-02 eta: 21:39:54 time: 0.3859 data_time: 0.0211 memory: 5826 grad_norm: 3.0434 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8468 loss: 2.8468 2022/10/07 16:23:11 - mmengine - INFO - Epoch(train) [43][1440/2119] lr: 4.0000e-02 eta: 21:39:45 time: 0.2954 data_time: 0.0230 memory: 5826 grad_norm: 3.0718 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8744 loss: 2.8744 2022/10/07 16:23:18 - mmengine - INFO - Epoch(train) [43][1460/2119] lr: 4.0000e-02 eta: 21:39:38 time: 0.3450 data_time: 0.0192 memory: 5826 grad_norm: 3.0638 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5500 loss: 2.5500 2022/10/07 16:23:24 - mmengine - INFO - Epoch(train) [43][1480/2119] lr: 4.0000e-02 eta: 21:39:31 time: 0.3385 data_time: 0.0244 memory: 5826 grad_norm: 3.0709 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7894 loss: 2.7894 2022/10/07 16:23:31 - mmengine - INFO - Epoch(train) [43][1500/2119] lr: 4.0000e-02 eta: 21:39:23 time: 0.3271 data_time: 0.0181 memory: 5826 grad_norm: 3.0801 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8762 loss: 2.8762 2022/10/07 16:23:38 - mmengine - INFO - Epoch(train) [43][1520/2119] lr: 4.0000e-02 eta: 21:39:17 time: 0.3468 data_time: 0.0258 memory: 5826 grad_norm: 3.0227 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.3423 loss: 2.3423 2022/10/07 16:23:46 - mmengine - INFO - Epoch(train) [43][1540/2119] lr: 4.0000e-02 eta: 21:39:12 time: 0.3942 data_time: 0.0179 memory: 5826 grad_norm: 3.1122 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.8213 loss: 2.8213 2022/10/07 16:23:53 - mmengine - INFO - Epoch(train) [43][1560/2119] lr: 4.0000e-02 eta: 21:39:05 time: 0.3411 data_time: 0.0195 memory: 5826 grad_norm: 3.0483 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7266 loss: 2.7266 2022/10/07 16:24:00 - mmengine - INFO - Epoch(train) [43][1580/2119] lr: 4.0000e-02 eta: 21:38:59 time: 0.3491 data_time: 0.0216 memory: 5826 grad_norm: 3.0728 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7328 loss: 2.7328 2022/10/07 16:24:05 - mmengine - INFO - Epoch(train) [43][1600/2119] lr: 4.0000e-02 eta: 21:38:50 time: 0.2958 data_time: 0.0255 memory: 5826 grad_norm: 3.1065 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0590 loss: 3.0590 2022/10/07 16:24:13 - mmengine - INFO - Epoch(train) [43][1620/2119] lr: 4.0000e-02 eta: 21:38:43 time: 0.3510 data_time: 0.0238 memory: 5826 grad_norm: 3.0844 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6076 loss: 2.6076 2022/10/07 16:24:19 - mmengine - INFO - Epoch(train) [43][1640/2119] lr: 4.0000e-02 eta: 21:38:36 time: 0.3367 data_time: 0.0205 memory: 5826 grad_norm: 3.0625 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9394 loss: 2.9394 2022/10/07 16:24:26 - mmengine - INFO - Epoch(train) [43][1660/2119] lr: 4.0000e-02 eta: 21:38:29 time: 0.3503 data_time: 0.0189 memory: 5826 grad_norm: 3.0824 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8699 loss: 2.8699 2022/10/07 16:24:33 - mmengine - INFO - Epoch(train) [43][1680/2119] lr: 4.0000e-02 eta: 21:38:23 time: 0.3590 data_time: 0.0202 memory: 5826 grad_norm: 3.1129 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8750 loss: 2.8750 2022/10/07 16:24:40 - mmengine - INFO - Epoch(train) [43][1700/2119] lr: 4.0000e-02 eta: 21:38:15 time: 0.3134 data_time: 0.0204 memory: 5826 grad_norm: 3.1403 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7269 loss: 2.7269 2022/10/07 16:24:47 - mmengine - INFO - Epoch(train) [43][1720/2119] lr: 4.0000e-02 eta: 21:38:10 time: 0.3754 data_time: 0.0256 memory: 5826 grad_norm: 3.1122 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7587 loss: 2.7587 2022/10/07 16:24:53 - mmengine - INFO - Epoch(train) [43][1740/2119] lr: 4.0000e-02 eta: 21:38:01 time: 0.3079 data_time: 0.0188 memory: 5826 grad_norm: 3.0621 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6505 loss: 2.6505 2022/10/07 16:25:01 - mmengine - INFO - Epoch(train) [43][1760/2119] lr: 4.0000e-02 eta: 21:37:56 time: 0.3677 data_time: 0.0238 memory: 5826 grad_norm: 3.0365 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.6628 loss: 2.6628 2022/10/07 16:25:07 - mmengine - INFO - Epoch(train) [43][1780/2119] lr: 4.0000e-02 eta: 21:37:48 time: 0.3327 data_time: 0.0186 memory: 5826 grad_norm: 3.0672 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7393 loss: 2.7393 2022/10/07 16:25:14 - mmengine - INFO - Epoch(train) [43][1800/2119] lr: 4.0000e-02 eta: 21:37:41 time: 0.3376 data_time: 0.0209 memory: 5826 grad_norm: 3.0180 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8542 loss: 2.8542 2022/10/07 16:25:21 - mmengine - INFO - Epoch(train) [43][1820/2119] lr: 4.0000e-02 eta: 21:37:34 time: 0.3474 data_time: 0.0217 memory: 5826 grad_norm: 3.0673 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.8745 loss: 2.8745 2022/10/07 16:25:28 - mmengine - INFO - Epoch(train) [43][1840/2119] lr: 4.0000e-02 eta: 21:37:27 time: 0.3249 data_time: 0.0228 memory: 5826 grad_norm: 3.1636 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7267 loss: 2.7267 2022/10/07 16:25:33 - mmengine - INFO - Epoch(train) [43][1860/2119] lr: 4.0000e-02 eta: 21:37:17 time: 0.2933 data_time: 0.0232 memory: 5826 grad_norm: 3.1092 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0011 loss: 3.0011 2022/10/07 16:25:40 - mmengine - INFO - Epoch(train) [43][1880/2119] lr: 4.0000e-02 eta: 21:37:11 time: 0.3430 data_time: 0.0210 memory: 5826 grad_norm: 3.1100 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7272 loss: 2.7272 2022/10/07 16:25:48 - mmengine - INFO - Epoch(train) [43][1900/2119] lr: 4.0000e-02 eta: 21:37:05 time: 0.3623 data_time: 0.0196 memory: 5826 grad_norm: 2.9970 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6785 loss: 2.6785 2022/10/07 16:25:55 - mmengine - INFO - Epoch(train) [43][1920/2119] lr: 4.0000e-02 eta: 21:36:58 time: 0.3494 data_time: 0.0199 memory: 5826 grad_norm: 3.0648 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9097 loss: 2.9097 2022/10/07 16:26:00 - mmengine - INFO - Epoch(train) [43][1940/2119] lr: 4.0000e-02 eta: 21:36:48 time: 0.2859 data_time: 0.0184 memory: 5826 grad_norm: 3.0821 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5784 loss: 2.5784 2022/10/07 16:26:08 - mmengine - INFO - Epoch(train) [43][1960/2119] lr: 4.0000e-02 eta: 21:36:44 time: 0.3833 data_time: 0.0213 memory: 5826 grad_norm: 3.0504 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.6635 loss: 2.6635 2022/10/07 16:26:15 - mmengine - INFO - Epoch(train) [43][1980/2119] lr: 4.0000e-02 eta: 21:36:36 time: 0.3386 data_time: 0.0233 memory: 5826 grad_norm: 3.1221 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7141 loss: 2.7141 2022/10/07 16:26:22 - mmengine - INFO - Epoch(train) [43][2000/2119] lr: 4.0000e-02 eta: 21:36:30 time: 0.3487 data_time: 0.0186 memory: 5826 grad_norm: 3.0915 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6169 loss: 2.6169 2022/10/07 16:26:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 16:26:29 - mmengine - INFO - Epoch(train) [43][2020/2119] lr: 4.0000e-02 eta: 21:36:24 time: 0.3644 data_time: 0.0194 memory: 5826 grad_norm: 3.0564 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8655 loss: 2.8655 2022/10/07 16:26:36 - mmengine - INFO - Epoch(train) [43][2040/2119] lr: 4.0000e-02 eta: 21:36:17 time: 0.3362 data_time: 0.0249 memory: 5826 grad_norm: 3.0751 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8361 loss: 2.8361 2022/10/07 16:26:43 - mmengine - INFO - Epoch(train) [43][2060/2119] lr: 4.0000e-02 eta: 21:36:10 time: 0.3390 data_time: 0.0251 memory: 5826 grad_norm: 3.1753 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7310 loss: 2.7310 2022/10/07 16:26:50 - mmengine - INFO - Epoch(train) [43][2080/2119] lr: 4.0000e-02 eta: 21:36:04 time: 0.3718 data_time: 0.0191 memory: 5826 grad_norm: 3.0947 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6560 loss: 2.6560 2022/10/07 16:26:56 - mmengine - INFO - Epoch(train) [43][2100/2119] lr: 4.0000e-02 eta: 21:35:56 time: 0.3159 data_time: 0.0188 memory: 5826 grad_norm: 3.1219 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9078 loss: 2.9078 2022/10/07 16:27:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 16:27:03 - mmengine - INFO - Epoch(train) [43][2119/2119] lr: 4.0000e-02 eta: 21:35:56 time: 0.3356 data_time: 0.0157 memory: 5826 grad_norm: 3.1698 top1_acc: 0.1000 top5_acc: 0.6000 loss_cls: 2.7323 loss: 2.7323 2022/10/07 16:27:12 - mmengine - INFO - Epoch(train) [44][20/2119] lr: 4.0000e-02 eta: 21:35:32 time: 0.4468 data_time: 0.1714 memory: 5826 grad_norm: 3.0963 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9144 loss: 2.9144 2022/10/07 16:27:18 - mmengine - INFO - Epoch(train) [44][40/2119] lr: 4.0000e-02 eta: 21:35:25 time: 0.3348 data_time: 0.0152 memory: 5826 grad_norm: 3.0844 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.7669 loss: 2.7669 2022/10/07 16:27:26 - mmengine - INFO - Epoch(train) [44][60/2119] lr: 4.0000e-02 eta: 21:35:18 time: 0.3539 data_time: 0.0230 memory: 5826 grad_norm: 3.0596 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8231 loss: 2.8231 2022/10/07 16:27:33 - mmengine - INFO - Epoch(train) [44][80/2119] lr: 4.0000e-02 eta: 21:35:12 time: 0.3575 data_time: 0.0154 memory: 5826 grad_norm: 3.0482 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8908 loss: 2.8908 2022/10/07 16:27:39 - mmengine - INFO - Epoch(train) [44][100/2119] lr: 4.0000e-02 eta: 21:35:04 time: 0.3132 data_time: 0.0213 memory: 5826 grad_norm: 3.1239 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.5930 loss: 2.5930 2022/10/07 16:27:46 - mmengine - INFO - Epoch(train) [44][120/2119] lr: 4.0000e-02 eta: 21:34:58 time: 0.3592 data_time: 0.0196 memory: 5826 grad_norm: 3.1285 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7870 loss: 2.7870 2022/10/07 16:27:53 - mmengine - INFO - Epoch(train) [44][140/2119] lr: 4.0000e-02 eta: 21:34:51 time: 0.3507 data_time: 0.0229 memory: 5826 grad_norm: 3.0167 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5146 loss: 2.5146 2022/10/07 16:28:00 - mmengine - INFO - Epoch(train) [44][160/2119] lr: 4.0000e-02 eta: 21:34:44 time: 0.3429 data_time: 0.0249 memory: 5826 grad_norm: 3.1267 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.8958 loss: 2.8958 2022/10/07 16:28:07 - mmengine - INFO - Epoch(train) [44][180/2119] lr: 4.0000e-02 eta: 21:34:37 time: 0.3344 data_time: 0.0259 memory: 5826 grad_norm: 3.1759 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5564 loss: 2.5564 2022/10/07 16:28:15 - mmengine - INFO - Epoch(train) [44][200/2119] lr: 4.0000e-02 eta: 21:34:33 time: 0.3942 data_time: 0.0198 memory: 5826 grad_norm: 3.0743 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.8528 loss: 2.8528 2022/10/07 16:28:20 - mmengine - INFO - Epoch(train) [44][220/2119] lr: 4.0000e-02 eta: 21:34:23 time: 0.2763 data_time: 0.0208 memory: 5826 grad_norm: 3.1102 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9564 loss: 2.9564 2022/10/07 16:28:28 - mmengine - INFO - Epoch(train) [44][240/2119] lr: 4.0000e-02 eta: 21:34:18 time: 0.3844 data_time: 0.0263 memory: 5826 grad_norm: 3.1138 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7338 loss: 2.7338 2022/10/07 16:28:34 - mmengine - INFO - Epoch(train) [44][260/2119] lr: 4.0000e-02 eta: 21:34:10 time: 0.3272 data_time: 0.0190 memory: 5826 grad_norm: 3.0738 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7887 loss: 2.7887 2022/10/07 16:28:42 - mmengine - INFO - Epoch(train) [44][280/2119] lr: 4.0000e-02 eta: 21:34:04 time: 0.3610 data_time: 0.0213 memory: 5826 grad_norm: 3.1408 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9406 loss: 2.9406 2022/10/07 16:28:48 - mmengine - INFO - Epoch(train) [44][300/2119] lr: 4.0000e-02 eta: 21:33:57 time: 0.3351 data_time: 0.0187 memory: 5826 grad_norm: 3.0636 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6888 loss: 2.6888 2022/10/07 16:28:56 - mmengine - INFO - Epoch(train) [44][320/2119] lr: 4.0000e-02 eta: 21:33:52 time: 0.3758 data_time: 0.0187 memory: 5826 grad_norm: 3.0422 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6440 loss: 2.6440 2022/10/07 16:29:02 - mmengine - INFO - Epoch(train) [44][340/2119] lr: 4.0000e-02 eta: 21:33:42 time: 0.2844 data_time: 0.0179 memory: 5826 grad_norm: 3.0486 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8936 loss: 2.8936 2022/10/07 16:29:09 - mmengine - INFO - Epoch(train) [44][360/2119] lr: 4.0000e-02 eta: 21:33:36 time: 0.3496 data_time: 0.0221 memory: 5826 grad_norm: 3.0623 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0005 loss: 3.0005 2022/10/07 16:29:15 - mmengine - INFO - Epoch(train) [44][380/2119] lr: 4.0000e-02 eta: 21:33:29 time: 0.3470 data_time: 0.0226 memory: 5826 grad_norm: 3.1062 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5291 loss: 2.5291 2022/10/07 16:29:22 - mmengine - INFO - Epoch(train) [44][400/2119] lr: 4.0000e-02 eta: 21:33:22 time: 0.3339 data_time: 0.0134 memory: 5826 grad_norm: 3.0560 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6282 loss: 2.6282 2022/10/07 16:29:29 - mmengine - INFO - Epoch(train) [44][420/2119] lr: 4.0000e-02 eta: 21:33:14 time: 0.3241 data_time: 0.0242 memory: 5826 grad_norm: 3.0680 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8463 loss: 2.8463 2022/10/07 16:29:36 - mmengine - INFO - Epoch(train) [44][440/2119] lr: 4.0000e-02 eta: 21:33:08 time: 0.3712 data_time: 0.0258 memory: 5826 grad_norm: 3.1079 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6359 loss: 2.6359 2022/10/07 16:29:43 - mmengine - INFO - Epoch(train) [44][460/2119] lr: 4.0000e-02 eta: 21:33:01 time: 0.3419 data_time: 0.0242 memory: 5826 grad_norm: 3.0852 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8383 loss: 2.8383 2022/10/07 16:29:50 - mmengine - INFO - Epoch(train) [44][480/2119] lr: 4.0000e-02 eta: 21:32:56 time: 0.3768 data_time: 0.0178 memory: 5826 grad_norm: 3.1157 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6732 loss: 2.6732 2022/10/07 16:29:56 - mmengine - INFO - Epoch(train) [44][500/2119] lr: 4.0000e-02 eta: 21:32:47 time: 0.3004 data_time: 0.0249 memory: 5826 grad_norm: 3.0275 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6723 loss: 2.6723 2022/10/07 16:30:05 - mmengine - INFO - Epoch(train) [44][520/2119] lr: 4.0000e-02 eta: 21:32:43 time: 0.4043 data_time: 0.0194 memory: 5826 grad_norm: 3.0337 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8303 loss: 2.8303 2022/10/07 16:30:11 - mmengine - INFO - Epoch(train) [44][540/2119] lr: 4.0000e-02 eta: 21:32:36 time: 0.3357 data_time: 0.0230 memory: 5826 grad_norm: 3.0381 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7691 loss: 2.7691 2022/10/07 16:30:17 - mmengine - INFO - Epoch(train) [44][560/2119] lr: 4.0000e-02 eta: 21:32:28 time: 0.3071 data_time: 0.0163 memory: 5826 grad_norm: 3.1868 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7586 loss: 2.7586 2022/10/07 16:30:24 - mmengine - INFO - Epoch(train) [44][580/2119] lr: 4.0000e-02 eta: 21:32:20 time: 0.3354 data_time: 0.0245 memory: 5826 grad_norm: 3.1505 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0008 loss: 3.0008 2022/10/07 16:30:32 - mmengine - INFO - Epoch(train) [44][600/2119] lr: 4.0000e-02 eta: 21:32:16 time: 0.3871 data_time: 0.0215 memory: 5826 grad_norm: 3.0586 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6353 loss: 2.6353 2022/10/07 16:30:38 - mmengine - INFO - Epoch(train) [44][620/2119] lr: 4.0000e-02 eta: 21:32:07 time: 0.3088 data_time: 0.0244 memory: 5826 grad_norm: 3.0726 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4507 loss: 2.4507 2022/10/07 16:30:46 - mmengine - INFO - Epoch(train) [44][640/2119] lr: 4.0000e-02 eta: 21:32:02 time: 0.3786 data_time: 0.0306 memory: 5826 grad_norm: 3.1240 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8047 loss: 2.8047 2022/10/07 16:30:52 - mmengine - INFO - Epoch(train) [44][660/2119] lr: 4.0000e-02 eta: 21:31:54 time: 0.3250 data_time: 0.0224 memory: 5826 grad_norm: 3.0768 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7355 loss: 2.7355 2022/10/07 16:30:59 - mmengine - INFO - Epoch(train) [44][680/2119] lr: 4.0000e-02 eta: 21:31:47 time: 0.3409 data_time: 0.0251 memory: 5826 grad_norm: 3.0579 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9329 loss: 2.9329 2022/10/07 16:31:06 - mmengine - INFO - Epoch(train) [44][700/2119] lr: 4.0000e-02 eta: 21:31:42 time: 0.3644 data_time: 0.0330 memory: 5826 grad_norm: 3.0864 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9043 loss: 2.9043 2022/10/07 16:31:13 - mmengine - INFO - Epoch(train) [44][720/2119] lr: 4.0000e-02 eta: 21:31:35 time: 0.3399 data_time: 0.0178 memory: 5826 grad_norm: 3.1032 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8901 loss: 2.8901 2022/10/07 16:31:20 - mmengine - INFO - Epoch(train) [44][740/2119] lr: 4.0000e-02 eta: 21:31:27 time: 0.3256 data_time: 0.0233 memory: 5826 grad_norm: 3.0787 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6106 loss: 2.6106 2022/10/07 16:31:27 - mmengine - INFO - Epoch(train) [44][760/2119] lr: 4.0000e-02 eta: 21:31:20 time: 0.3522 data_time: 0.0196 memory: 5826 grad_norm: 3.0866 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9331 loss: 2.9331 2022/10/07 16:31:34 - mmengine - INFO - Epoch(train) [44][780/2119] lr: 4.0000e-02 eta: 21:31:15 time: 0.3756 data_time: 0.0234 memory: 5826 grad_norm: 3.0565 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9434 loss: 2.9434 2022/10/07 16:31:40 - mmengine - INFO - Epoch(train) [44][800/2119] lr: 4.0000e-02 eta: 21:31:06 time: 0.2855 data_time: 0.0215 memory: 5826 grad_norm: 3.1073 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8328 loss: 2.8328 2022/10/07 16:31:47 - mmengine - INFO - Epoch(train) [44][820/2119] lr: 4.0000e-02 eta: 21:31:00 time: 0.3682 data_time: 0.0242 memory: 5826 grad_norm: 3.0776 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7140 loss: 2.7140 2022/10/07 16:31:54 - mmengine - INFO - Epoch(train) [44][840/2119] lr: 4.0000e-02 eta: 21:30:52 time: 0.3293 data_time: 0.0216 memory: 5826 grad_norm: 3.0887 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.8259 loss: 2.8259 2022/10/07 16:32:01 - mmengine - INFO - Epoch(train) [44][860/2119] lr: 4.0000e-02 eta: 21:30:46 time: 0.3516 data_time: 0.0197 memory: 5826 grad_norm: 3.1595 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8447 loss: 2.8447 2022/10/07 16:32:08 - mmengine - INFO - Epoch(train) [44][880/2119] lr: 4.0000e-02 eta: 21:30:40 time: 0.3603 data_time: 0.0189 memory: 5826 grad_norm: 3.0872 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0925 loss: 3.0925 2022/10/07 16:32:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 16:32:15 - mmengine - INFO - Epoch(train) [44][900/2119] lr: 4.0000e-02 eta: 21:30:33 time: 0.3332 data_time: 0.0236 memory: 5826 grad_norm: 3.1097 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6161 loss: 2.6161 2022/10/07 16:32:21 - mmengine - INFO - Epoch(train) [44][920/2119] lr: 4.0000e-02 eta: 21:30:26 time: 0.3370 data_time: 0.0202 memory: 5826 grad_norm: 3.1351 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7845 loss: 2.7845 2022/10/07 16:32:28 - mmengine - INFO - Epoch(train) [44][940/2119] lr: 4.0000e-02 eta: 21:30:17 time: 0.3150 data_time: 0.0199 memory: 5826 grad_norm: 3.0990 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8366 loss: 2.8366 2022/10/07 16:32:35 - mmengine - INFO - Epoch(train) [44][960/2119] lr: 4.0000e-02 eta: 21:30:11 time: 0.3527 data_time: 0.0242 memory: 5826 grad_norm: 3.0500 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9250 loss: 2.9250 2022/10/07 16:32:41 - mmengine - INFO - Epoch(train) [44][980/2119] lr: 4.0000e-02 eta: 21:30:02 time: 0.2928 data_time: 0.0226 memory: 5826 grad_norm: 3.0938 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8531 loss: 2.8531 2022/10/07 16:32:47 - mmengine - INFO - Epoch(train) [44][1000/2119] lr: 4.0000e-02 eta: 21:29:55 time: 0.3421 data_time: 0.0195 memory: 5826 grad_norm: 3.0656 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7126 loss: 2.7126 2022/10/07 16:32:54 - mmengine - INFO - Epoch(train) [44][1020/2119] lr: 4.0000e-02 eta: 21:29:48 time: 0.3374 data_time: 0.0203 memory: 5826 grad_norm: 3.0751 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7511 loss: 2.7511 2022/10/07 16:33:02 - mmengine - INFO - Epoch(train) [44][1040/2119] lr: 4.0000e-02 eta: 21:29:42 time: 0.3632 data_time: 0.0214 memory: 5826 grad_norm: 3.0856 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8956 loss: 2.8956 2022/10/07 16:33:08 - mmengine - INFO - Epoch(train) [44][1060/2119] lr: 4.0000e-02 eta: 21:29:35 time: 0.3423 data_time: 0.0217 memory: 5826 grad_norm: 3.1003 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8126 loss: 2.8126 2022/10/07 16:33:15 - mmengine - INFO - Epoch(train) [44][1080/2119] lr: 4.0000e-02 eta: 21:29:27 time: 0.3300 data_time: 0.0212 memory: 5826 grad_norm: 3.1195 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.8985 loss: 2.8985 2022/10/07 16:33:21 - mmengine - INFO - Epoch(train) [44][1100/2119] lr: 4.0000e-02 eta: 21:29:20 time: 0.3245 data_time: 0.0225 memory: 5826 grad_norm: 3.0940 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9827 loss: 2.9827 2022/10/07 16:33:29 - mmengine - INFO - Epoch(train) [44][1120/2119] lr: 4.0000e-02 eta: 21:29:14 time: 0.3682 data_time: 0.0234 memory: 5826 grad_norm: 3.1054 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7219 loss: 2.7219 2022/10/07 16:33:35 - mmengine - INFO - Epoch(train) [44][1140/2119] lr: 4.0000e-02 eta: 21:29:06 time: 0.3273 data_time: 0.0205 memory: 5826 grad_norm: 3.1807 top1_acc: 0.2500 top5_acc: 0.3125 loss_cls: 2.8356 loss: 2.8356 2022/10/07 16:33:43 - mmengine - INFO - Epoch(train) [44][1160/2119] lr: 4.0000e-02 eta: 21:29:01 time: 0.3636 data_time: 0.0303 memory: 5826 grad_norm: 3.1455 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.0217 loss: 3.0217 2022/10/07 16:33:49 - mmengine - INFO - Epoch(train) [44][1180/2119] lr: 4.0000e-02 eta: 21:28:53 time: 0.3228 data_time: 0.0270 memory: 5826 grad_norm: 3.0976 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7092 loss: 2.7092 2022/10/07 16:33:56 - mmengine - INFO - Epoch(train) [44][1200/2119] lr: 4.0000e-02 eta: 21:28:46 time: 0.3454 data_time: 0.0225 memory: 5826 grad_norm: 3.0964 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8582 loss: 2.8582 2022/10/07 16:34:03 - mmengine - INFO - Epoch(train) [44][1220/2119] lr: 4.0000e-02 eta: 21:28:40 time: 0.3698 data_time: 0.0294 memory: 5826 grad_norm: 3.1562 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6706 loss: 2.6706 2022/10/07 16:34:10 - mmengine - INFO - Epoch(train) [44][1240/2119] lr: 4.0000e-02 eta: 21:28:33 time: 0.3226 data_time: 0.0174 memory: 5826 grad_norm: 3.1198 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6248 loss: 2.6248 2022/10/07 16:34:17 - mmengine - INFO - Epoch(train) [44][1260/2119] lr: 4.0000e-02 eta: 21:28:26 time: 0.3567 data_time: 0.0249 memory: 5826 grad_norm: 3.1598 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.2260 loss: 3.2260 2022/10/07 16:34:24 - mmengine - INFO - Epoch(train) [44][1280/2119] lr: 4.0000e-02 eta: 21:28:19 time: 0.3328 data_time: 0.0251 memory: 5826 grad_norm: 3.1085 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.0546 loss: 3.0546 2022/10/07 16:34:31 - mmengine - INFO - Epoch(train) [44][1300/2119] lr: 4.0000e-02 eta: 21:28:12 time: 0.3441 data_time: 0.0198 memory: 5826 grad_norm: 3.1529 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9166 loss: 2.9166 2022/10/07 16:34:37 - mmengine - INFO - Epoch(train) [44][1320/2119] lr: 4.0000e-02 eta: 21:28:03 time: 0.3015 data_time: 0.0216 memory: 5826 grad_norm: 3.1077 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7595 loss: 2.7595 2022/10/07 16:34:44 - mmengine - INFO - Epoch(train) [44][1340/2119] lr: 4.0000e-02 eta: 21:27:58 time: 0.3726 data_time: 0.0247 memory: 5826 grad_norm: 3.0801 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7992 loss: 2.7992 2022/10/07 16:34:50 - mmengine - INFO - Epoch(train) [44][1360/2119] lr: 4.0000e-02 eta: 21:27:50 time: 0.3137 data_time: 0.0219 memory: 5826 grad_norm: 3.1051 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7719 loss: 2.7719 2022/10/07 16:34:58 - mmengine - INFO - Epoch(train) [44][1380/2119] lr: 4.0000e-02 eta: 21:27:44 time: 0.3670 data_time: 0.0233 memory: 5826 grad_norm: 3.1061 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.7602 loss: 2.7602 2022/10/07 16:35:05 - mmengine - INFO - Epoch(train) [44][1400/2119] lr: 4.0000e-02 eta: 21:27:39 time: 0.3762 data_time: 0.0166 memory: 5826 grad_norm: 3.0922 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9923 loss: 2.9923 2022/10/07 16:35:11 - mmengine - INFO - Epoch(train) [44][1420/2119] lr: 4.0000e-02 eta: 21:27:30 time: 0.3005 data_time: 0.0257 memory: 5826 grad_norm: 3.0509 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7010 loss: 2.7010 2022/10/07 16:35:18 - mmengine - INFO - Epoch(train) [44][1440/2119] lr: 4.0000e-02 eta: 21:27:22 time: 0.3291 data_time: 0.0243 memory: 5826 grad_norm: 3.1373 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6702 loss: 2.6702 2022/10/07 16:35:25 - mmengine - INFO - Epoch(train) [44][1460/2119] lr: 4.0000e-02 eta: 21:27:17 time: 0.3729 data_time: 0.0276 memory: 5826 grad_norm: 3.1294 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8764 loss: 2.8764 2022/10/07 16:35:32 - mmengine - INFO - Epoch(train) [44][1480/2119] lr: 4.0000e-02 eta: 21:27:10 time: 0.3502 data_time: 0.0195 memory: 5826 grad_norm: 3.2050 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8693 loss: 2.8693 2022/10/07 16:35:39 - mmengine - INFO - Epoch(train) [44][1500/2119] lr: 4.0000e-02 eta: 21:27:03 time: 0.3324 data_time: 0.0214 memory: 5826 grad_norm: 3.0475 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7689 loss: 2.7689 2022/10/07 16:35:46 - mmengine - INFO - Epoch(train) [44][1520/2119] lr: 4.0000e-02 eta: 21:26:56 time: 0.3489 data_time: 0.0241 memory: 5826 grad_norm: 3.1599 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7150 loss: 2.7150 2022/10/07 16:35:53 - mmengine - INFO - Epoch(train) [44][1540/2119] lr: 4.0000e-02 eta: 21:26:50 time: 0.3599 data_time: 0.0251 memory: 5826 grad_norm: 3.0607 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7025 loss: 2.7025 2022/10/07 16:35:59 - mmengine - INFO - Epoch(train) [44][1560/2119] lr: 4.0000e-02 eta: 21:26:42 time: 0.3200 data_time: 0.0186 memory: 5826 grad_norm: 3.0450 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6892 loss: 2.6892 2022/10/07 16:36:06 - mmengine - INFO - Epoch(train) [44][1580/2119] lr: 4.0000e-02 eta: 21:26:35 time: 0.3373 data_time: 0.0247 memory: 5826 grad_norm: 3.0767 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9214 loss: 2.9214 2022/10/07 16:36:13 - mmengine - INFO - Epoch(train) [44][1600/2119] lr: 4.0000e-02 eta: 21:26:29 time: 0.3599 data_time: 0.0253 memory: 5826 grad_norm: 3.0853 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8205 loss: 2.8205 2022/10/07 16:36:20 - mmengine - INFO - Epoch(train) [44][1620/2119] lr: 4.0000e-02 eta: 21:26:21 time: 0.3182 data_time: 0.0206 memory: 5826 grad_norm: 3.1204 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7547 loss: 2.7547 2022/10/07 16:36:27 - mmengine - INFO - Epoch(train) [44][1640/2119] lr: 4.0000e-02 eta: 21:26:14 time: 0.3378 data_time: 0.0212 memory: 5826 grad_norm: 3.1232 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.6932 loss: 2.6932 2022/10/07 16:36:33 - mmengine - INFO - Epoch(train) [44][1660/2119] lr: 4.0000e-02 eta: 21:26:07 time: 0.3429 data_time: 0.0225 memory: 5826 grad_norm: 3.0502 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7600 loss: 2.7600 2022/10/07 16:36:40 - mmengine - INFO - Epoch(train) [44][1680/2119] lr: 4.0000e-02 eta: 21:26:01 time: 0.3461 data_time: 0.0223 memory: 5826 grad_norm: 3.1165 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8847 loss: 2.8847 2022/10/07 16:36:47 - mmengine - INFO - Epoch(train) [44][1700/2119] lr: 4.0000e-02 eta: 21:25:53 time: 0.3228 data_time: 0.0272 memory: 5826 grad_norm: 3.0231 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5894 loss: 2.5894 2022/10/07 16:36:54 - mmengine - INFO - Epoch(train) [44][1720/2119] lr: 4.0000e-02 eta: 21:25:47 time: 0.3722 data_time: 0.0219 memory: 5826 grad_norm: 3.0727 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7241 loss: 2.7241 2022/10/07 16:37:00 - mmengine - INFO - Epoch(train) [44][1740/2119] lr: 4.0000e-02 eta: 21:25:39 time: 0.3087 data_time: 0.0182 memory: 5826 grad_norm: 3.0781 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6478 loss: 2.6478 2022/10/07 16:37:07 - mmengine - INFO - Epoch(train) [44][1760/2119] lr: 4.0000e-02 eta: 21:25:32 time: 0.3456 data_time: 0.0236 memory: 5826 grad_norm: 3.1267 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6231 loss: 2.6231 2022/10/07 16:37:15 - mmengine - INFO - Epoch(train) [44][1780/2119] lr: 4.0000e-02 eta: 21:25:26 time: 0.3608 data_time: 0.0242 memory: 5826 grad_norm: 3.1272 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7675 loss: 2.7675 2022/10/07 16:37:21 - mmengine - INFO - Epoch(train) [44][1800/2119] lr: 4.0000e-02 eta: 21:25:17 time: 0.3045 data_time: 0.0219 memory: 5826 grad_norm: 3.1014 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8584 loss: 2.8584 2022/10/07 16:37:29 - mmengine - INFO - Epoch(train) [44][1820/2119] lr: 4.0000e-02 eta: 21:25:14 time: 0.4044 data_time: 0.0253 memory: 5826 grad_norm: 3.0875 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7480 loss: 2.7480 2022/10/07 16:37:35 - mmengine - INFO - Epoch(train) [44][1840/2119] lr: 4.0000e-02 eta: 21:25:06 time: 0.3298 data_time: 0.0229 memory: 5826 grad_norm: 3.0550 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9679 loss: 2.9679 2022/10/07 16:37:44 - mmengine - INFO - Epoch(train) [44][1860/2119] lr: 4.0000e-02 eta: 21:25:03 time: 0.4154 data_time: 0.0234 memory: 5826 grad_norm: 3.0730 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8631 loss: 2.8631 2022/10/07 16:37:50 - mmengine - INFO - Epoch(train) [44][1880/2119] lr: 4.0000e-02 eta: 21:24:55 time: 0.3242 data_time: 0.0232 memory: 5826 grad_norm: 3.0955 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7014 loss: 2.7014 2022/10/07 16:37:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 16:37:57 - mmengine - INFO - Epoch(train) [44][1900/2119] lr: 4.0000e-02 eta: 21:24:49 time: 0.3619 data_time: 0.0256 memory: 5826 grad_norm: 3.0713 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8946 loss: 2.8946 2022/10/07 16:38:04 - mmengine - INFO - Epoch(train) [44][1920/2119] lr: 4.0000e-02 eta: 21:24:42 time: 0.3359 data_time: 0.0212 memory: 5826 grad_norm: 3.0864 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0336 loss: 3.0336 2022/10/07 16:38:12 - mmengine - INFO - Epoch(train) [44][1940/2119] lr: 4.0000e-02 eta: 21:24:37 time: 0.3873 data_time: 0.0223 memory: 5826 grad_norm: 3.0987 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8634 loss: 2.8634 2022/10/07 16:38:18 - mmengine - INFO - Epoch(train) [44][1960/2119] lr: 4.0000e-02 eta: 21:24:29 time: 0.3175 data_time: 0.0235 memory: 5826 grad_norm: 3.0010 top1_acc: 0.2500 top5_acc: 0.8125 loss_cls: 2.5954 loss: 2.5954 2022/10/07 16:38:26 - mmengine - INFO - Epoch(train) [44][1980/2119] lr: 4.0000e-02 eta: 21:24:24 time: 0.3803 data_time: 0.0271 memory: 5826 grad_norm: 3.0927 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7614 loss: 2.7614 2022/10/07 16:38:32 - mmengine - INFO - Epoch(train) [44][2000/2119] lr: 4.0000e-02 eta: 21:24:15 time: 0.3046 data_time: 0.0225 memory: 5826 grad_norm: 3.0848 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7179 loss: 2.7179 2022/10/07 16:38:39 - mmengine - INFO - Epoch(train) [44][2020/2119] lr: 4.0000e-02 eta: 21:24:08 time: 0.3314 data_time: 0.0201 memory: 5826 grad_norm: 3.0787 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0316 loss: 3.0316 2022/10/07 16:38:46 - mmengine - INFO - Epoch(train) [44][2040/2119] lr: 4.0000e-02 eta: 21:24:03 time: 0.3919 data_time: 0.0235 memory: 5826 grad_norm: 3.0781 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5768 loss: 2.5768 2022/10/07 16:38:52 - mmengine - INFO - Epoch(train) [44][2060/2119] lr: 4.0000e-02 eta: 21:23:55 time: 0.3035 data_time: 0.0226 memory: 5826 grad_norm: 3.1064 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.9304 loss: 2.9304 2022/10/07 16:38:59 - mmengine - INFO - Epoch(train) [44][2080/2119] lr: 4.0000e-02 eta: 21:23:47 time: 0.3336 data_time: 0.0220 memory: 5826 grad_norm: 3.0714 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6705 loss: 2.6705 2022/10/07 16:39:06 - mmengine - INFO - Epoch(train) [44][2100/2119] lr: 4.0000e-02 eta: 21:23:40 time: 0.3317 data_time: 0.0231 memory: 5826 grad_norm: 3.0636 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.9254 loss: 2.9254 2022/10/07 16:39:11 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 16:39:11 - mmengine - INFO - Epoch(train) [44][2119/2119] lr: 4.0000e-02 eta: 21:23:40 time: 0.2577 data_time: 0.0213 memory: 5826 grad_norm: 3.1354 top1_acc: 0.6000 top5_acc: 0.7000 loss_cls: 2.9273 loss: 2.9273 2022/10/07 16:39:11 - mmengine - INFO - Saving checkpoint at 44 epochs 2022/10/07 16:39:22 - mmengine - INFO - Epoch(train) [45][20/2119] lr: 4.0000e-02 eta: 21:23:14 time: 0.4174 data_time: 0.2111 memory: 5826 grad_norm: 3.0728 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.9259 loss: 2.9259 2022/10/07 16:39:29 - mmengine - INFO - Epoch(train) [45][40/2119] lr: 4.0000e-02 eta: 21:23:06 time: 0.3050 data_time: 0.0786 memory: 5826 grad_norm: 3.1048 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5633 loss: 2.5633 2022/10/07 16:39:35 - mmengine - INFO - Epoch(train) [45][60/2119] lr: 4.0000e-02 eta: 21:22:58 time: 0.3320 data_time: 0.0924 memory: 5826 grad_norm: 3.0698 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8043 loss: 2.8043 2022/10/07 16:39:42 - mmengine - INFO - Epoch(train) [45][80/2119] lr: 4.0000e-02 eta: 21:22:51 time: 0.3428 data_time: 0.0653 memory: 5826 grad_norm: 3.0512 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8500 loss: 2.8500 2022/10/07 16:39:49 - mmengine - INFO - Epoch(train) [45][100/2119] lr: 4.0000e-02 eta: 21:22:44 time: 0.3251 data_time: 0.0202 memory: 5826 grad_norm: 3.1386 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6103 loss: 2.6103 2022/10/07 16:39:56 - mmengine - INFO - Epoch(train) [45][120/2119] lr: 4.0000e-02 eta: 21:22:37 time: 0.3539 data_time: 0.0169 memory: 5826 grad_norm: 3.1213 top1_acc: 0.2500 top5_acc: 0.3125 loss_cls: 2.7356 loss: 2.7356 2022/10/07 16:40:03 - mmengine - INFO - Epoch(train) [45][140/2119] lr: 4.0000e-02 eta: 21:22:33 time: 0.3829 data_time: 0.0724 memory: 5826 grad_norm: 3.0907 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7531 loss: 2.7531 2022/10/07 16:40:10 - mmengine - INFO - Epoch(train) [45][160/2119] lr: 4.0000e-02 eta: 21:22:25 time: 0.3244 data_time: 0.0168 memory: 5826 grad_norm: 3.1187 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7769 loss: 2.7769 2022/10/07 16:40:17 - mmengine - INFO - Epoch(train) [45][180/2119] lr: 4.0000e-02 eta: 21:22:19 time: 0.3610 data_time: 0.0214 memory: 5826 grad_norm: 3.1153 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6798 loss: 2.6798 2022/10/07 16:40:24 - mmengine - INFO - Epoch(train) [45][200/2119] lr: 4.0000e-02 eta: 21:22:12 time: 0.3393 data_time: 0.0218 memory: 5826 grad_norm: 3.0378 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8783 loss: 2.8783 2022/10/07 16:40:30 - mmengine - INFO - Epoch(train) [45][220/2119] lr: 4.0000e-02 eta: 21:22:03 time: 0.3120 data_time: 0.0184 memory: 5826 grad_norm: 3.0788 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5799 loss: 2.5799 2022/10/07 16:40:37 - mmengine - INFO - Epoch(train) [45][240/2119] lr: 4.0000e-02 eta: 21:21:57 time: 0.3502 data_time: 0.0211 memory: 5826 grad_norm: 3.0869 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6497 loss: 2.6497 2022/10/07 16:40:44 - mmengine - INFO - Epoch(train) [45][260/2119] lr: 4.0000e-02 eta: 21:21:51 time: 0.3615 data_time: 0.0201 memory: 5826 grad_norm: 3.1349 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8064 loss: 2.8064 2022/10/07 16:40:51 - mmengine - INFO - Epoch(train) [45][280/2119] lr: 4.0000e-02 eta: 21:21:44 time: 0.3385 data_time: 0.0229 memory: 5826 grad_norm: 3.1038 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8921 loss: 2.8921 2022/10/07 16:40:58 - mmengine - INFO - Epoch(train) [45][300/2119] lr: 4.0000e-02 eta: 21:21:37 time: 0.3474 data_time: 0.0201 memory: 5826 grad_norm: 3.0449 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5674 loss: 2.5674 2022/10/07 16:41:05 - mmengine - INFO - Epoch(train) [45][320/2119] lr: 4.0000e-02 eta: 21:21:30 time: 0.3327 data_time: 0.0243 memory: 5826 grad_norm: 3.0225 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6211 loss: 2.6211 2022/10/07 16:41:12 - mmengine - INFO - Epoch(train) [45][340/2119] lr: 4.0000e-02 eta: 21:21:23 time: 0.3463 data_time: 0.0198 memory: 5826 grad_norm: 3.0363 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4865 loss: 2.4865 2022/10/07 16:41:19 - mmengine - INFO - Epoch(train) [45][360/2119] lr: 4.0000e-02 eta: 21:21:18 time: 0.3800 data_time: 0.0213 memory: 5826 grad_norm: 3.0384 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9893 loss: 2.9893 2022/10/07 16:41:26 - mmengine - INFO - Epoch(train) [45][380/2119] lr: 4.0000e-02 eta: 21:21:11 time: 0.3371 data_time: 0.0206 memory: 5826 grad_norm: 3.1213 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7525 loss: 2.7525 2022/10/07 16:41:34 - mmengine - INFO - Epoch(train) [45][400/2119] lr: 4.0000e-02 eta: 21:21:06 time: 0.3880 data_time: 0.0188 memory: 5826 grad_norm: 3.0783 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9305 loss: 2.9305 2022/10/07 16:41:40 - mmengine - INFO - Epoch(train) [45][420/2119] lr: 4.0000e-02 eta: 21:20:58 time: 0.3179 data_time: 0.0211 memory: 5826 grad_norm: 3.0754 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7230 loss: 2.7230 2022/10/07 16:41:47 - mmengine - INFO - Epoch(train) [45][440/2119] lr: 4.0000e-02 eta: 21:20:52 time: 0.3465 data_time: 0.0222 memory: 5826 grad_norm: 3.0280 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8918 loss: 2.8918 2022/10/07 16:41:55 - mmengine - INFO - Epoch(train) [45][460/2119] lr: 4.0000e-02 eta: 21:20:46 time: 0.3741 data_time: 0.0252 memory: 5826 grad_norm: 3.1126 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.5310 loss: 2.5310 2022/10/07 16:42:01 - mmengine - INFO - Epoch(train) [45][480/2119] lr: 4.0000e-02 eta: 21:20:38 time: 0.3203 data_time: 0.0207 memory: 5826 grad_norm: 3.0940 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8467 loss: 2.8467 2022/10/07 16:42:08 - mmengine - INFO - Epoch(train) [45][500/2119] lr: 4.0000e-02 eta: 21:20:32 time: 0.3494 data_time: 0.0207 memory: 5826 grad_norm: 3.1111 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7773 loss: 2.7773 2022/10/07 16:42:15 - mmengine - INFO - Epoch(train) [45][520/2119] lr: 4.0000e-02 eta: 21:20:25 time: 0.3511 data_time: 0.0293 memory: 5826 grad_norm: 3.0240 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7375 loss: 2.7375 2022/10/07 16:42:22 - mmengine - INFO - Epoch(train) [45][540/2119] lr: 4.0000e-02 eta: 21:20:19 time: 0.3440 data_time: 0.0162 memory: 5826 grad_norm: 3.1296 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4631 loss: 2.4631 2022/10/07 16:42:29 - mmengine - INFO - Epoch(train) [45][560/2119] lr: 4.0000e-02 eta: 21:20:12 time: 0.3513 data_time: 0.0223 memory: 5826 grad_norm: 3.1381 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9744 loss: 2.9744 2022/10/07 16:42:35 - mmengine - INFO - Epoch(train) [45][580/2119] lr: 4.0000e-02 eta: 21:20:04 time: 0.3177 data_time: 0.0246 memory: 5826 grad_norm: 3.1027 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8166 loss: 2.8166 2022/10/07 16:42:42 - mmengine - INFO - Epoch(train) [45][600/2119] lr: 4.0000e-02 eta: 21:19:58 time: 0.3568 data_time: 0.0235 memory: 5826 grad_norm: 3.1092 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9472 loss: 2.9472 2022/10/07 16:42:49 - mmengine - INFO - Epoch(train) [45][620/2119] lr: 4.0000e-02 eta: 21:19:51 time: 0.3391 data_time: 0.0295 memory: 5826 grad_norm: 3.0681 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.9358 loss: 2.9358 2022/10/07 16:42:56 - mmengine - INFO - Epoch(train) [45][640/2119] lr: 4.0000e-02 eta: 21:19:44 time: 0.3488 data_time: 0.0176 memory: 5826 grad_norm: 3.1099 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8051 loss: 2.8051 2022/10/07 16:43:03 - mmengine - INFO - Epoch(train) [45][660/2119] lr: 4.0000e-02 eta: 21:19:36 time: 0.3225 data_time: 0.0198 memory: 5826 grad_norm: 3.1030 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.0149 loss: 3.0149 2022/10/07 16:43:09 - mmengine - INFO - Epoch(train) [45][680/2119] lr: 4.0000e-02 eta: 21:19:29 time: 0.3261 data_time: 0.0253 memory: 5826 grad_norm: 3.1207 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7942 loss: 2.7942 2022/10/07 16:43:17 - mmengine - INFO - Epoch(train) [45][700/2119] lr: 4.0000e-02 eta: 21:19:23 time: 0.3703 data_time: 0.0230 memory: 5826 grad_norm: 3.0688 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7385 loss: 2.7385 2022/10/07 16:43:24 - mmengine - INFO - Epoch(train) [45][720/2119] lr: 4.0000e-02 eta: 21:19:18 time: 0.3747 data_time: 0.0232 memory: 5826 grad_norm: 3.0753 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7357 loss: 2.7357 2022/10/07 16:43:31 - mmengine - INFO - Epoch(train) [45][740/2119] lr: 4.0000e-02 eta: 21:19:11 time: 0.3518 data_time: 0.0234 memory: 5826 grad_norm: 3.1027 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9032 loss: 2.9032 2022/10/07 16:43:37 - mmengine - INFO - Epoch(train) [45][760/2119] lr: 4.0000e-02 eta: 21:19:02 time: 0.2967 data_time: 0.0212 memory: 5826 grad_norm: 3.0504 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9361 loss: 2.9361 2022/10/07 16:43:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 16:43:45 - mmengine - INFO - Epoch(train) [45][780/2119] lr: 4.0000e-02 eta: 21:18:57 time: 0.3817 data_time: 0.0217 memory: 5826 grad_norm: 3.0548 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7185 loss: 2.7185 2022/10/07 16:43:50 - mmengine - INFO - Epoch(train) [45][800/2119] lr: 4.0000e-02 eta: 21:18:47 time: 0.2775 data_time: 0.0222 memory: 5826 grad_norm: 3.0715 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7546 loss: 2.7546 2022/10/07 16:43:57 - mmengine - INFO - Epoch(train) [45][820/2119] lr: 4.0000e-02 eta: 21:18:40 time: 0.3408 data_time: 0.0220 memory: 5826 grad_norm: 3.1572 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.6795 loss: 2.6795 2022/10/07 16:44:03 - mmengine - INFO - Epoch(train) [45][840/2119] lr: 4.0000e-02 eta: 21:18:32 time: 0.3092 data_time: 0.0190 memory: 5826 grad_norm: 3.0723 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8306 loss: 2.8306 2022/10/07 16:44:10 - mmengine - INFO - Epoch(train) [45][860/2119] lr: 4.0000e-02 eta: 21:18:25 time: 0.3489 data_time: 0.0247 memory: 5826 grad_norm: 3.0598 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7952 loss: 2.7952 2022/10/07 16:44:17 - mmengine - INFO - Epoch(train) [45][880/2119] lr: 4.0000e-02 eta: 21:18:19 time: 0.3574 data_time: 0.0227 memory: 5826 grad_norm: 3.1247 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6824 loss: 2.6824 2022/10/07 16:44:24 - mmengine - INFO - Epoch(train) [45][900/2119] lr: 4.0000e-02 eta: 21:18:12 time: 0.3404 data_time: 0.0244 memory: 5826 grad_norm: 3.0972 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7741 loss: 2.7741 2022/10/07 16:44:31 - mmengine - INFO - Epoch(train) [45][920/2119] lr: 4.0000e-02 eta: 21:18:05 time: 0.3275 data_time: 0.0201 memory: 5826 grad_norm: 3.0966 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 3.0642 loss: 3.0642 2022/10/07 16:44:38 - mmengine - INFO - Epoch(train) [45][940/2119] lr: 4.0000e-02 eta: 21:17:58 time: 0.3414 data_time: 0.0194 memory: 5826 grad_norm: 3.0590 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6864 loss: 2.6864 2022/10/07 16:44:45 - mmengine - INFO - Epoch(train) [45][960/2119] lr: 4.0000e-02 eta: 21:17:51 time: 0.3529 data_time: 0.0158 memory: 5826 grad_norm: 3.0967 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6564 loss: 2.6564 2022/10/07 16:44:51 - mmengine - INFO - Epoch(train) [45][980/2119] lr: 4.0000e-02 eta: 21:17:44 time: 0.3286 data_time: 0.0224 memory: 5826 grad_norm: 3.0848 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7928 loss: 2.7928 2022/10/07 16:44:58 - mmengine - INFO - Epoch(train) [45][1000/2119] lr: 4.0000e-02 eta: 21:17:37 time: 0.3412 data_time: 0.0197 memory: 5826 grad_norm: 3.0692 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8614 loss: 2.8614 2022/10/07 16:45:05 - mmengine - INFO - Epoch(train) [45][1020/2119] lr: 4.0000e-02 eta: 21:17:31 time: 0.3725 data_time: 0.0220 memory: 5826 grad_norm: 3.1217 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7261 loss: 2.7261 2022/10/07 16:45:12 - mmengine - INFO - Epoch(train) [45][1040/2119] lr: 4.0000e-02 eta: 21:17:24 time: 0.3286 data_time: 0.0246 memory: 5826 grad_norm: 3.0612 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7321 loss: 2.7321 2022/10/07 16:45:19 - mmengine - INFO - Epoch(train) [45][1060/2119] lr: 4.0000e-02 eta: 21:17:17 time: 0.3358 data_time: 0.0218 memory: 5826 grad_norm: 3.0768 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8929 loss: 2.8929 2022/10/07 16:45:25 - mmengine - INFO - Epoch(train) [45][1080/2119] lr: 4.0000e-02 eta: 21:17:09 time: 0.3270 data_time: 0.0213 memory: 5826 grad_norm: 3.0698 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7551 loss: 2.7551 2022/10/07 16:45:32 - mmengine - INFO - Epoch(train) [45][1100/2119] lr: 4.0000e-02 eta: 21:17:02 time: 0.3435 data_time: 0.0215 memory: 5826 grad_norm: 3.0562 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7933 loss: 2.7933 2022/10/07 16:45:38 - mmengine - INFO - Epoch(train) [45][1120/2119] lr: 4.0000e-02 eta: 21:16:54 time: 0.3097 data_time: 0.0191 memory: 5826 grad_norm: 3.0494 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.7215 loss: 2.7215 2022/10/07 16:45:46 - mmengine - INFO - Epoch(train) [45][1140/2119] lr: 4.0000e-02 eta: 21:16:48 time: 0.3687 data_time: 0.0175 memory: 5826 grad_norm: 3.1057 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8519 loss: 2.8519 2022/10/07 16:45:53 - mmengine - INFO - Epoch(train) [45][1160/2119] lr: 4.0000e-02 eta: 21:16:42 time: 0.3505 data_time: 0.0278 memory: 5826 grad_norm: 3.1465 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.8824 loss: 2.8824 2022/10/07 16:46:00 - mmengine - INFO - Epoch(train) [45][1180/2119] lr: 4.0000e-02 eta: 21:16:36 time: 0.3595 data_time: 0.0199 memory: 5826 grad_norm: 3.0869 top1_acc: 0.1875 top5_acc: 0.9375 loss_cls: 2.7769 loss: 2.7769 2022/10/07 16:46:06 - mmengine - INFO - Epoch(train) [45][1200/2119] lr: 4.0000e-02 eta: 21:16:27 time: 0.3069 data_time: 0.0218 memory: 5826 grad_norm: 3.0620 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6931 loss: 2.6931 2022/10/07 16:46:14 - mmengine - INFO - Epoch(train) [45][1220/2119] lr: 4.0000e-02 eta: 21:16:23 time: 0.3901 data_time: 0.0250 memory: 5826 grad_norm: 3.0507 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7980 loss: 2.7980 2022/10/07 16:46:20 - mmengine - INFO - Epoch(train) [45][1240/2119] lr: 4.0000e-02 eta: 21:16:14 time: 0.3150 data_time: 0.0203 memory: 5826 grad_norm: 3.0636 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8436 loss: 2.8436 2022/10/07 16:46:27 - mmengine - INFO - Epoch(train) [45][1260/2119] lr: 4.0000e-02 eta: 21:16:08 time: 0.3609 data_time: 0.0292 memory: 5826 grad_norm: 3.1204 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6517 loss: 2.6517 2022/10/07 16:46:34 - mmengine - INFO - Epoch(train) [45][1280/2119] lr: 4.0000e-02 eta: 21:16:01 time: 0.3312 data_time: 0.0221 memory: 5826 grad_norm: 3.0685 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7747 loss: 2.7747 2022/10/07 16:46:40 - mmengine - INFO - Epoch(train) [45][1300/2119] lr: 4.0000e-02 eta: 21:15:53 time: 0.3217 data_time: 0.0296 memory: 5826 grad_norm: 3.1266 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9525 loss: 2.9525 2022/10/07 16:46:47 - mmengine - INFO - Epoch(train) [45][1320/2119] lr: 4.0000e-02 eta: 21:15:46 time: 0.3314 data_time: 0.0188 memory: 5826 grad_norm: 2.9729 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8334 loss: 2.8334 2022/10/07 16:46:54 - mmengine - INFO - Epoch(train) [45][1340/2119] lr: 4.0000e-02 eta: 21:15:40 time: 0.3605 data_time: 0.0216 memory: 5826 grad_norm: 3.0922 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7035 loss: 2.7035 2022/10/07 16:47:01 - mmengine - INFO - Epoch(train) [45][1360/2119] lr: 4.0000e-02 eta: 21:15:32 time: 0.3204 data_time: 0.0197 memory: 5826 grad_norm: 3.0391 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.3940 loss: 2.3940 2022/10/07 16:47:08 - mmengine - INFO - Epoch(train) [45][1380/2119] lr: 4.0000e-02 eta: 21:15:26 time: 0.3636 data_time: 0.0205 memory: 5826 grad_norm: 3.0696 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7776 loss: 2.7776 2022/10/07 16:47:15 - mmengine - INFO - Epoch(train) [45][1400/2119] lr: 4.0000e-02 eta: 21:15:20 time: 0.3673 data_time: 0.0199 memory: 5826 grad_norm: 3.0969 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7370 loss: 2.7370 2022/10/07 16:47:23 - mmengine - INFO - Epoch(train) [45][1420/2119] lr: 4.0000e-02 eta: 21:15:15 time: 0.3777 data_time: 0.0232 memory: 5826 grad_norm: 3.0212 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5895 loss: 2.5895 2022/10/07 16:47:30 - mmengine - INFO - Epoch(train) [45][1440/2119] lr: 4.0000e-02 eta: 21:15:08 time: 0.3317 data_time: 0.0230 memory: 5826 grad_norm: 3.0446 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.6457 loss: 2.6457 2022/10/07 16:47:36 - mmengine - INFO - Epoch(train) [45][1460/2119] lr: 4.0000e-02 eta: 21:15:00 time: 0.3360 data_time: 0.0247 memory: 5826 grad_norm: 3.0893 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7435 loss: 2.7435 2022/10/07 16:47:43 - mmengine - INFO - Epoch(train) [45][1480/2119] lr: 4.0000e-02 eta: 21:14:54 time: 0.3456 data_time: 0.0228 memory: 5826 grad_norm: 3.0950 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.8204 loss: 2.8204 2022/10/07 16:47:50 - mmengine - INFO - Epoch(train) [45][1500/2119] lr: 4.0000e-02 eta: 21:14:46 time: 0.3347 data_time: 0.0231 memory: 5826 grad_norm: 3.1415 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8777 loss: 2.8777 2022/10/07 16:47:57 - mmengine - INFO - Epoch(train) [45][1520/2119] lr: 4.0000e-02 eta: 21:14:39 time: 0.3374 data_time: 0.0167 memory: 5826 grad_norm: 3.0789 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.9358 loss: 2.9358 2022/10/07 16:48:03 - mmengine - INFO - Epoch(train) [45][1540/2119] lr: 4.0000e-02 eta: 21:14:32 time: 0.3420 data_time: 0.0351 memory: 5826 grad_norm: 3.0267 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.4379 loss: 2.4379 2022/10/07 16:48:10 - mmengine - INFO - Epoch(train) [45][1560/2119] lr: 4.0000e-02 eta: 21:14:24 time: 0.3062 data_time: 0.0214 memory: 5826 grad_norm: 3.0988 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6598 loss: 2.6598 2022/10/07 16:48:16 - mmengine - INFO - Epoch(train) [45][1580/2119] lr: 4.0000e-02 eta: 21:14:17 time: 0.3459 data_time: 0.0274 memory: 5826 grad_norm: 3.1391 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8257 loss: 2.8257 2022/10/07 16:48:24 - mmengine - INFO - Epoch(train) [45][1600/2119] lr: 4.0000e-02 eta: 21:14:12 time: 0.3682 data_time: 0.0269 memory: 5826 grad_norm: 3.1381 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8402 loss: 2.8402 2022/10/07 16:48:31 - mmengine - INFO - Epoch(train) [45][1620/2119] lr: 4.0000e-02 eta: 21:14:04 time: 0.3354 data_time: 0.0204 memory: 5826 grad_norm: 3.0384 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6945 loss: 2.6945 2022/10/07 16:48:37 - mmengine - INFO - Epoch(train) [45][1640/2119] lr: 4.0000e-02 eta: 21:13:57 time: 0.3338 data_time: 0.0249 memory: 5826 grad_norm: 3.1224 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8319 loss: 2.8319 2022/10/07 16:48:44 - mmengine - INFO - Epoch(train) [45][1660/2119] lr: 4.0000e-02 eta: 21:13:50 time: 0.3434 data_time: 0.0261 memory: 5826 grad_norm: 3.0731 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8017 loss: 2.8017 2022/10/07 16:48:51 - mmengine - INFO - Epoch(train) [45][1680/2119] lr: 4.0000e-02 eta: 21:13:44 time: 0.3566 data_time: 0.0239 memory: 5826 grad_norm: 3.0473 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8447 loss: 2.8447 2022/10/07 16:48:59 - mmengine - INFO - Epoch(train) [45][1700/2119] lr: 4.0000e-02 eta: 21:13:38 time: 0.3661 data_time: 0.0259 memory: 5826 grad_norm: 3.0017 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8983 loss: 2.8983 2022/10/07 16:49:05 - mmengine - INFO - Epoch(train) [45][1720/2119] lr: 4.0000e-02 eta: 21:13:30 time: 0.3150 data_time: 0.0227 memory: 5826 grad_norm: 3.0624 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6192 loss: 2.6192 2022/10/07 16:49:12 - mmengine - INFO - Epoch(train) [45][1740/2119] lr: 4.0000e-02 eta: 21:13:23 time: 0.3384 data_time: 0.0285 memory: 5826 grad_norm: 3.0303 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7782 loss: 2.7782 2022/10/07 16:49:18 - mmengine - INFO - Epoch(train) [45][1760/2119] lr: 4.0000e-02 eta: 21:13:15 time: 0.3286 data_time: 0.0225 memory: 5826 grad_norm: 3.1166 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6457 loss: 2.6457 2022/10/07 16:49:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 16:49:26 - mmengine - INFO - Epoch(train) [45][1780/2119] lr: 4.0000e-02 eta: 21:13:10 time: 0.3727 data_time: 0.0260 memory: 5826 grad_norm: 3.1153 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8453 loss: 2.8453 2022/10/07 16:49:32 - mmengine - INFO - Epoch(train) [45][1800/2119] lr: 4.0000e-02 eta: 21:13:02 time: 0.3190 data_time: 0.0206 memory: 5826 grad_norm: 3.1080 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7283 loss: 2.7283 2022/10/07 16:49:39 - mmengine - INFO - Epoch(train) [45][1820/2119] lr: 4.0000e-02 eta: 21:12:56 time: 0.3565 data_time: 0.0185 memory: 5826 grad_norm: 3.0819 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7987 loss: 2.7987 2022/10/07 16:49:46 - mmengine - INFO - Epoch(train) [45][1840/2119] lr: 4.0000e-02 eta: 21:12:49 time: 0.3424 data_time: 0.0196 memory: 5826 grad_norm: 3.0898 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8045 loss: 2.8045 2022/10/07 16:49:53 - mmengine - INFO - Epoch(train) [45][1860/2119] lr: 4.0000e-02 eta: 21:12:42 time: 0.3431 data_time: 0.0265 memory: 5826 grad_norm: 3.1368 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7495 loss: 2.7495 2022/10/07 16:49:59 - mmengine - INFO - Epoch(train) [45][1880/2119] lr: 4.0000e-02 eta: 21:12:34 time: 0.3136 data_time: 0.0237 memory: 5826 grad_norm: 3.1141 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8004 loss: 2.8004 2022/10/07 16:50:06 - mmengine - INFO - Epoch(train) [45][1900/2119] lr: 4.0000e-02 eta: 21:12:28 time: 0.3552 data_time: 0.0229 memory: 5826 grad_norm: 3.1815 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7230 loss: 2.7230 2022/10/07 16:50:13 - mmengine - INFO - Epoch(train) [45][1920/2119] lr: 4.0000e-02 eta: 21:12:20 time: 0.3304 data_time: 0.0209 memory: 5826 grad_norm: 3.1047 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7517 loss: 2.7517 2022/10/07 16:50:20 - mmengine - INFO - Epoch(train) [45][1940/2119] lr: 4.0000e-02 eta: 21:12:13 time: 0.3359 data_time: 0.0234 memory: 5826 grad_norm: 3.1417 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8735 loss: 2.8735 2022/10/07 16:50:26 - mmengine - INFO - Epoch(train) [45][1960/2119] lr: 4.0000e-02 eta: 21:12:05 time: 0.3237 data_time: 0.0248 memory: 5826 grad_norm: 3.0874 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7739 loss: 2.7739 2022/10/07 16:50:34 - mmengine - INFO - Epoch(train) [45][1980/2119] lr: 4.0000e-02 eta: 21:12:01 time: 0.3926 data_time: 0.0186 memory: 5826 grad_norm: 3.1274 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0158 loss: 3.0158 2022/10/07 16:50:40 - mmengine - INFO - Epoch(train) [45][2000/2119] lr: 4.0000e-02 eta: 21:11:53 time: 0.3161 data_time: 0.0208 memory: 5826 grad_norm: 3.1123 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6752 loss: 2.6752 2022/10/07 16:50:47 - mmengine - INFO - Epoch(train) [45][2020/2119] lr: 4.0000e-02 eta: 21:11:46 time: 0.3541 data_time: 0.0229 memory: 5826 grad_norm: 3.0552 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8937 loss: 2.8937 2022/10/07 16:50:54 - mmengine - INFO - Epoch(train) [45][2040/2119] lr: 4.0000e-02 eta: 21:11:38 time: 0.3081 data_time: 0.0206 memory: 5826 grad_norm: 3.0838 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0242 loss: 3.0242 2022/10/07 16:51:01 - mmengine - INFO - Epoch(train) [45][2060/2119] lr: 4.0000e-02 eta: 21:11:32 time: 0.3659 data_time: 0.0236 memory: 5826 grad_norm: 3.0518 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6939 loss: 2.6939 2022/10/07 16:51:07 - mmengine - INFO - Epoch(train) [45][2080/2119] lr: 4.0000e-02 eta: 21:11:25 time: 0.3299 data_time: 0.0229 memory: 5826 grad_norm: 3.0652 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0144 loss: 3.0144 2022/10/07 16:51:15 - mmengine - INFO - Epoch(train) [45][2100/2119] lr: 4.0000e-02 eta: 21:11:18 time: 0.3543 data_time: 0.0242 memory: 5826 grad_norm: 3.0649 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7928 loss: 2.7928 2022/10/07 16:51:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 16:51:20 - mmengine - INFO - Epoch(train) [45][2119/2119] lr: 4.0000e-02 eta: 21:11:18 time: 0.2864 data_time: 0.0215 memory: 5826 grad_norm: 3.1183 top1_acc: 0.3000 top5_acc: 0.6000 loss_cls: 2.9268 loss: 2.9268 2022/10/07 16:51:28 - mmengine - INFO - Epoch(val) [45][20/137] eta: 0:00:47 time: 0.4088 data_time: 0.3382 memory: 1241 2022/10/07 16:51:34 - mmengine - INFO - Epoch(val) [45][40/137] eta: 0:00:27 time: 0.2797 data_time: 0.2108 memory: 1241 2022/10/07 16:51:41 - mmengine - INFO - Epoch(val) [45][60/137] eta: 0:00:26 time: 0.3486 data_time: 0.2849 memory: 1241 2022/10/07 16:51:46 - mmengine - INFO - Epoch(val) [45][80/137] eta: 0:00:15 time: 0.2770 data_time: 0.2104 memory: 1241 2022/10/07 16:51:52 - mmengine - INFO - Epoch(val) [45][100/137] eta: 0:00:10 time: 0.2811 data_time: 0.2174 memory: 1241 2022/10/07 16:51:59 - mmengine - INFO - Epoch(val) [45][120/137] eta: 0:00:05 time: 0.3419 data_time: 0.2769 memory: 1241 2022/10/07 16:52:09 - mmengine - INFO - Epoch(val) [45][137/137] acc/top1: 0.4199 acc/top5: 0.6685 acc/mean1: 0.4198 2022/10/07 16:52:19 - mmengine - INFO - Epoch(train) [46][20/2119] lr: 4.0000e-02 eta: 21:10:56 time: 0.4714 data_time: 0.1374 memory: 5826 grad_norm: 3.0794 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8967 loss: 2.8967 2022/10/07 16:52:26 - mmengine - INFO - Epoch(train) [46][40/2119] lr: 4.0000e-02 eta: 21:10:49 time: 0.3411 data_time: 0.0204 memory: 5826 grad_norm: 3.0878 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7421 loss: 2.7421 2022/10/07 16:52:34 - mmengine - INFO - Epoch(train) [46][60/2119] lr: 4.0000e-02 eta: 21:10:44 time: 0.3926 data_time: 0.0241 memory: 5826 grad_norm: 3.0308 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9005 loss: 2.9005 2022/10/07 16:52:40 - mmengine - INFO - Epoch(train) [46][80/2119] lr: 4.0000e-02 eta: 21:10:36 time: 0.3224 data_time: 0.0169 memory: 5826 grad_norm: 3.0257 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7125 loss: 2.7125 2022/10/07 16:52:46 - mmengine - INFO - Epoch(train) [46][100/2119] lr: 4.0000e-02 eta: 21:10:27 time: 0.2979 data_time: 0.0301 memory: 5826 grad_norm: 3.0867 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5556 loss: 2.5556 2022/10/07 16:52:53 - mmengine - INFO - Epoch(train) [46][120/2119] lr: 4.0000e-02 eta: 21:10:20 time: 0.3382 data_time: 0.0171 memory: 5826 grad_norm: 3.1433 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9580 loss: 2.9580 2022/10/07 16:53:00 - mmengine - INFO - Epoch(train) [46][140/2119] lr: 4.0000e-02 eta: 21:10:14 time: 0.3453 data_time: 0.0189 memory: 5826 grad_norm: 3.0911 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.5871 loss: 2.5871 2022/10/07 16:53:07 - mmengine - INFO - Epoch(train) [46][160/2119] lr: 4.0000e-02 eta: 21:10:07 time: 0.3546 data_time: 0.0150 memory: 5826 grad_norm: 3.0867 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7780 loss: 2.7780 2022/10/07 16:53:13 - mmengine - INFO - Epoch(train) [46][180/2119] lr: 4.0000e-02 eta: 21:09:58 time: 0.2841 data_time: 0.0244 memory: 5826 grad_norm: 3.0966 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9429 loss: 2.9429 2022/10/07 16:53:20 - mmengine - INFO - Epoch(train) [46][200/2119] lr: 4.0000e-02 eta: 21:09:52 time: 0.3556 data_time: 0.0131 memory: 5826 grad_norm: 3.0567 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8527 loss: 2.8527 2022/10/07 16:53:27 - mmengine - INFO - Epoch(train) [46][220/2119] lr: 4.0000e-02 eta: 21:09:47 time: 0.3857 data_time: 0.0203 memory: 5826 grad_norm: 3.0615 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7028 loss: 2.7028 2022/10/07 16:53:34 - mmengine - INFO - Epoch(train) [46][240/2119] lr: 4.0000e-02 eta: 21:09:40 time: 0.3485 data_time: 0.0169 memory: 5826 grad_norm: 3.0742 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7820 loss: 2.7820 2022/10/07 16:53:41 - mmengine - INFO - Epoch(train) [46][260/2119] lr: 4.0000e-02 eta: 21:09:32 time: 0.3219 data_time: 0.0218 memory: 5826 grad_norm: 3.0642 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.6658 loss: 2.6658 2022/10/07 16:53:48 - mmengine - INFO - Epoch(train) [46][280/2119] lr: 4.0000e-02 eta: 21:09:26 time: 0.3638 data_time: 0.0165 memory: 5826 grad_norm: 3.0819 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.5147 loss: 2.5147 2022/10/07 16:53:55 - mmengine - INFO - Epoch(train) [46][300/2119] lr: 4.0000e-02 eta: 21:09:20 time: 0.3599 data_time: 0.0242 memory: 5826 grad_norm: 3.0787 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.6390 loss: 2.6390 2022/10/07 16:54:02 - mmengine - INFO - Epoch(train) [46][320/2119] lr: 4.0000e-02 eta: 21:09:13 time: 0.3254 data_time: 0.0219 memory: 5826 grad_norm: 3.1010 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.6780 loss: 2.6780 2022/10/07 16:54:09 - mmengine - INFO - Epoch(train) [46][340/2119] lr: 4.0000e-02 eta: 21:09:08 time: 0.3869 data_time: 0.0263 memory: 5826 grad_norm: 3.0829 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8722 loss: 2.8722 2022/10/07 16:54:16 - mmengine - INFO - Epoch(train) [46][360/2119] lr: 4.0000e-02 eta: 21:09:01 time: 0.3362 data_time: 0.0218 memory: 5826 grad_norm: 3.0345 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7364 loss: 2.7364 2022/10/07 16:54:24 - mmengine - INFO - Epoch(train) [46][380/2119] lr: 4.0000e-02 eta: 21:08:56 time: 0.3804 data_time: 0.0247 memory: 5826 grad_norm: 3.1196 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9887 loss: 2.9887 2022/10/07 16:54:30 - mmengine - INFO - Epoch(train) [46][400/2119] lr: 4.0000e-02 eta: 21:08:47 time: 0.3151 data_time: 0.0216 memory: 5826 grad_norm: 3.0928 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8848 loss: 2.8848 2022/10/07 16:54:38 - mmengine - INFO - Epoch(train) [46][420/2119] lr: 4.0000e-02 eta: 21:08:42 time: 0.3708 data_time: 0.0239 memory: 5826 grad_norm: 3.1179 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8702 loss: 2.8702 2022/10/07 16:54:44 - mmengine - INFO - Epoch(train) [46][440/2119] lr: 4.0000e-02 eta: 21:08:34 time: 0.3198 data_time: 0.0325 memory: 5826 grad_norm: 3.0773 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.9280 loss: 2.9280 2022/10/07 16:54:51 - mmengine - INFO - Epoch(train) [46][460/2119] lr: 4.0000e-02 eta: 21:08:29 time: 0.3753 data_time: 0.0247 memory: 5826 grad_norm: 3.0903 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8032 loss: 2.8032 2022/10/07 16:54:58 - mmengine - INFO - Epoch(train) [46][480/2119] lr: 4.0000e-02 eta: 21:08:22 time: 0.3429 data_time: 0.0194 memory: 5826 grad_norm: 3.0734 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8069 loss: 2.8069 2022/10/07 16:55:05 - mmengine - INFO - Epoch(train) [46][500/2119] lr: 4.0000e-02 eta: 21:08:15 time: 0.3500 data_time: 0.0218 memory: 5826 grad_norm: 3.1578 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7077 loss: 2.7077 2022/10/07 16:55:11 - mmengine - INFO - Epoch(train) [46][520/2119] lr: 4.0000e-02 eta: 21:08:06 time: 0.2819 data_time: 0.0168 memory: 5826 grad_norm: 3.0837 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7697 loss: 2.7697 2022/10/07 16:55:18 - mmengine - INFO - Epoch(train) [46][540/2119] lr: 4.0000e-02 eta: 21:08:00 time: 0.3661 data_time: 0.0235 memory: 5826 grad_norm: 3.0633 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7832 loss: 2.7832 2022/10/07 16:55:25 - mmengine - INFO - Epoch(train) [46][560/2119] lr: 4.0000e-02 eta: 21:07:53 time: 0.3374 data_time: 0.0191 memory: 5826 grad_norm: 3.0524 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5570 loss: 2.5570 2022/10/07 16:55:32 - mmengine - INFO - Epoch(train) [46][580/2119] lr: 4.0000e-02 eta: 21:07:47 time: 0.3627 data_time: 0.0265 memory: 5826 grad_norm: 3.0982 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7104 loss: 2.7104 2022/10/07 16:55:39 - mmengine - INFO - Epoch(train) [46][600/2119] lr: 4.0000e-02 eta: 21:07:40 time: 0.3343 data_time: 0.0235 memory: 5826 grad_norm: 3.1565 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6534 loss: 2.6534 2022/10/07 16:55:46 - mmengine - INFO - Epoch(train) [46][620/2119] lr: 4.0000e-02 eta: 21:07:32 time: 0.3365 data_time: 0.0254 memory: 5826 grad_norm: 3.0771 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7319 loss: 2.7319 2022/10/07 16:55:52 - mmengine - INFO - Epoch(train) [46][640/2119] lr: 4.0000e-02 eta: 21:07:24 time: 0.3103 data_time: 0.0237 memory: 5826 grad_norm: 3.0981 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7695 loss: 2.7695 2022/10/07 16:55:54 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 16:55:59 - mmengine - INFO - Epoch(train) [46][660/2119] lr: 4.0000e-02 eta: 21:07:18 time: 0.3666 data_time: 0.0187 memory: 5826 grad_norm: 3.0809 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8478 loss: 2.8478 2022/10/07 16:56:06 - mmengine - INFO - Epoch(train) [46][680/2119] lr: 4.0000e-02 eta: 21:07:10 time: 0.3184 data_time: 0.0204 memory: 5826 grad_norm: 3.1124 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5250 loss: 2.5250 2022/10/07 16:56:13 - mmengine - INFO - Epoch(train) [46][700/2119] lr: 4.0000e-02 eta: 21:07:04 time: 0.3473 data_time: 0.0241 memory: 5826 grad_norm: 3.1257 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7515 loss: 2.7515 2022/10/07 16:56:20 - mmengine - INFO - Epoch(train) [46][720/2119] lr: 4.0000e-02 eta: 21:06:58 time: 0.3710 data_time: 0.0228 memory: 5826 grad_norm: 3.0881 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8009 loss: 2.8009 2022/10/07 16:56:26 - mmengine - INFO - Epoch(train) [46][740/2119] lr: 4.0000e-02 eta: 21:06:50 time: 0.3210 data_time: 0.0189 memory: 5826 grad_norm: 3.1289 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7089 loss: 2.7089 2022/10/07 16:56:33 - mmengine - INFO - Epoch(train) [46][760/2119] lr: 4.0000e-02 eta: 21:06:43 time: 0.3352 data_time: 0.0255 memory: 5826 grad_norm: 3.1259 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7872 loss: 2.7872 2022/10/07 16:56:40 - mmengine - INFO - Epoch(train) [46][780/2119] lr: 4.0000e-02 eta: 21:06:36 time: 0.3419 data_time: 0.0180 memory: 5826 grad_norm: 3.0478 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7027 loss: 2.7027 2022/10/07 16:56:47 - mmengine - INFO - Epoch(train) [46][800/2119] lr: 4.0000e-02 eta: 21:06:29 time: 0.3295 data_time: 0.0230 memory: 5826 grad_norm: 3.0783 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6676 loss: 2.6676 2022/10/07 16:56:55 - mmengine - INFO - Epoch(train) [46][820/2119] lr: 4.0000e-02 eta: 21:06:25 time: 0.4043 data_time: 0.0247 memory: 5826 grad_norm: 3.1438 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7801 loss: 2.7801 2022/10/07 16:57:01 - mmengine - INFO - Epoch(train) [46][840/2119] lr: 4.0000e-02 eta: 21:06:17 time: 0.3152 data_time: 0.0210 memory: 5826 grad_norm: 3.0754 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7262 loss: 2.7262 2022/10/07 16:57:08 - mmengine - INFO - Epoch(train) [46][860/2119] lr: 4.0000e-02 eta: 21:06:11 time: 0.3638 data_time: 0.0207 memory: 5826 grad_norm: 3.1041 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.4532 loss: 2.4532 2022/10/07 16:57:15 - mmengine - INFO - Epoch(train) [46][880/2119] lr: 4.0000e-02 eta: 21:06:03 time: 0.3312 data_time: 0.0303 memory: 5826 grad_norm: 3.0960 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6937 loss: 2.6937 2022/10/07 16:57:22 - mmengine - INFO - Epoch(train) [46][900/2119] lr: 4.0000e-02 eta: 21:05:56 time: 0.3411 data_time: 0.0220 memory: 5826 grad_norm: 3.1008 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7308 loss: 2.7308 2022/10/07 16:57:28 - mmengine - INFO - Epoch(train) [46][920/2119] lr: 4.0000e-02 eta: 21:05:49 time: 0.3379 data_time: 0.0215 memory: 5826 grad_norm: 3.0733 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7478 loss: 2.7478 2022/10/07 16:57:36 - mmengine - INFO - Epoch(train) [46][940/2119] lr: 4.0000e-02 eta: 21:05:44 time: 0.3796 data_time: 0.0196 memory: 5826 grad_norm: 3.0858 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7165 loss: 2.7165 2022/10/07 16:57:42 - mmengine - INFO - Epoch(train) [46][960/2119] lr: 4.0000e-02 eta: 21:05:36 time: 0.3177 data_time: 0.0213 memory: 5826 grad_norm: 3.0570 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.8149 loss: 2.8149 2022/10/07 16:57:50 - mmengine - INFO - Epoch(train) [46][980/2119] lr: 4.0000e-02 eta: 21:05:31 time: 0.3793 data_time: 0.0234 memory: 5826 grad_norm: 3.0688 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6190 loss: 2.6190 2022/10/07 16:57:56 - mmengine - INFO - Epoch(train) [46][1000/2119] lr: 4.0000e-02 eta: 21:05:22 time: 0.3072 data_time: 0.0179 memory: 5826 grad_norm: 3.1500 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6570 loss: 2.6570 2022/10/07 16:58:02 - mmengine - INFO - Epoch(train) [46][1020/2119] lr: 4.0000e-02 eta: 21:05:14 time: 0.3176 data_time: 0.0243 memory: 5826 grad_norm: 3.0832 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6805 loss: 2.6805 2022/10/07 16:58:10 - mmengine - INFO - Epoch(train) [46][1040/2119] lr: 4.0000e-02 eta: 21:05:10 time: 0.3870 data_time: 0.0425 memory: 5826 grad_norm: 3.0772 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.8179 loss: 2.8179 2022/10/07 16:58:17 - mmengine - INFO - Epoch(train) [46][1060/2119] lr: 4.0000e-02 eta: 21:05:03 time: 0.3399 data_time: 0.0324 memory: 5826 grad_norm: 3.1093 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6833 loss: 2.6833 2022/10/07 16:58:24 - mmengine - INFO - Epoch(train) [46][1080/2119] lr: 4.0000e-02 eta: 21:04:56 time: 0.3541 data_time: 0.0214 memory: 5826 grad_norm: 3.1089 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7532 loss: 2.7532 2022/10/07 16:58:30 - mmengine - INFO - Epoch(train) [46][1100/2119] lr: 4.0000e-02 eta: 21:04:47 time: 0.2886 data_time: 0.0265 memory: 5826 grad_norm: 3.0287 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8093 loss: 2.8093 2022/10/07 16:58:37 - mmengine - INFO - Epoch(train) [46][1120/2119] lr: 4.0000e-02 eta: 21:04:41 time: 0.3732 data_time: 0.0232 memory: 5826 grad_norm: 3.0857 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8432 loss: 2.8432 2022/10/07 16:58:44 - mmengine - INFO - Epoch(train) [46][1140/2119] lr: 4.0000e-02 eta: 21:04:35 time: 0.3531 data_time: 0.0224 memory: 5826 grad_norm: 3.1279 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8303 loss: 2.8303 2022/10/07 16:58:52 - mmengine - INFO - Epoch(train) [46][1160/2119] lr: 4.0000e-02 eta: 21:04:29 time: 0.3579 data_time: 0.0200 memory: 5826 grad_norm: 3.1316 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8379 loss: 2.8379 2022/10/07 16:58:59 - mmengine - INFO - Epoch(train) [46][1180/2119] lr: 4.0000e-02 eta: 21:04:22 time: 0.3473 data_time: 0.0253 memory: 5826 grad_norm: 3.0803 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6539 loss: 2.6539 2022/10/07 16:59:05 - mmengine - INFO - Epoch(train) [46][1200/2119] lr: 4.0000e-02 eta: 21:04:15 time: 0.3263 data_time: 0.0213 memory: 5826 grad_norm: 3.0891 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7429 loss: 2.7429 2022/10/07 16:59:12 - mmengine - INFO - Epoch(train) [46][1220/2119] lr: 4.0000e-02 eta: 21:04:08 time: 0.3543 data_time: 0.0206 memory: 5826 grad_norm: 3.0124 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5543 loss: 2.5543 2022/10/07 16:59:18 - mmengine - INFO - Epoch(train) [46][1240/2119] lr: 4.0000e-02 eta: 21:04:00 time: 0.3138 data_time: 0.0211 memory: 5826 grad_norm: 3.0696 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6294 loss: 2.6294 2022/10/07 16:59:26 - mmengine - INFO - Epoch(train) [46][1260/2119] lr: 4.0000e-02 eta: 21:03:54 time: 0.3681 data_time: 0.0233 memory: 5826 grad_norm: 3.0939 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9104 loss: 2.9104 2022/10/07 16:59:32 - mmengine - INFO - Epoch(train) [46][1280/2119] lr: 4.0000e-02 eta: 21:03:46 time: 0.3102 data_time: 0.0198 memory: 5826 grad_norm: 3.0620 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7451 loss: 2.7451 2022/10/07 16:59:40 - mmengine - INFO - Epoch(train) [46][1300/2119] lr: 4.0000e-02 eta: 21:03:41 time: 0.3872 data_time: 0.0257 memory: 5826 grad_norm: 3.0570 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8781 loss: 2.8781 2022/10/07 16:59:46 - mmengine - INFO - Epoch(train) [46][1320/2119] lr: 4.0000e-02 eta: 21:03:33 time: 0.3160 data_time: 0.0227 memory: 5826 grad_norm: 3.0930 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7388 loss: 2.7388 2022/10/07 16:59:52 - mmengine - INFO - Epoch(train) [46][1340/2119] lr: 4.0000e-02 eta: 21:03:25 time: 0.3195 data_time: 0.0230 memory: 5826 grad_norm: 3.0473 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8705 loss: 2.8705 2022/10/07 17:00:00 - mmengine - INFO - Epoch(train) [46][1360/2119] lr: 4.0000e-02 eta: 21:03:19 time: 0.3512 data_time: 0.0339 memory: 5826 grad_norm: 3.0999 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6712 loss: 2.6712 2022/10/07 17:00:06 - mmengine - INFO - Epoch(train) [46][1380/2119] lr: 4.0000e-02 eta: 21:03:11 time: 0.3231 data_time: 0.0224 memory: 5826 grad_norm: 3.0532 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9431 loss: 2.9431 2022/10/07 17:00:13 - mmengine - INFO - Epoch(train) [46][1400/2119] lr: 4.0000e-02 eta: 21:03:06 time: 0.3729 data_time: 0.0206 memory: 5826 grad_norm: 3.0887 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7858 loss: 2.7858 2022/10/07 17:00:21 - mmengine - INFO - Epoch(train) [46][1420/2119] lr: 4.0000e-02 eta: 21:03:00 time: 0.3612 data_time: 0.0213 memory: 5826 grad_norm: 3.1632 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0398 loss: 3.0398 2022/10/07 17:00:27 - mmengine - INFO - Epoch(train) [46][1440/2119] lr: 4.0000e-02 eta: 21:02:51 time: 0.3061 data_time: 0.0218 memory: 5826 grad_norm: 3.1183 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7082 loss: 2.7082 2022/10/07 17:00:35 - mmengine - INFO - Epoch(train) [46][1460/2119] lr: 4.0000e-02 eta: 21:02:46 time: 0.3872 data_time: 0.0197 memory: 5826 grad_norm: 3.0441 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.7083 loss: 2.7083 2022/10/07 17:00:41 - mmengine - INFO - Epoch(train) [46][1480/2119] lr: 4.0000e-02 eta: 21:02:39 time: 0.3352 data_time: 0.0206 memory: 5826 grad_norm: 3.1127 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0487 loss: 3.0487 2022/10/07 17:00:48 - mmengine - INFO - Epoch(train) [46][1500/2119] lr: 4.0000e-02 eta: 21:02:31 time: 0.3222 data_time: 0.0246 memory: 5826 grad_norm: 3.1524 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8751 loss: 2.8751 2022/10/07 17:00:54 - mmengine - INFO - Epoch(train) [46][1520/2119] lr: 4.0000e-02 eta: 21:02:24 time: 0.3260 data_time: 0.0227 memory: 5826 grad_norm: 3.0607 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6594 loss: 2.6594 2022/10/07 17:01:01 - mmengine - INFO - Epoch(train) [46][1540/2119] lr: 4.0000e-02 eta: 21:02:17 time: 0.3493 data_time: 0.0264 memory: 5826 grad_norm: 3.1012 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5835 loss: 2.5835 2022/10/07 17:01:08 - mmengine - INFO - Epoch(train) [46][1560/2119] lr: 4.0000e-02 eta: 21:02:11 time: 0.3556 data_time: 0.0180 memory: 5826 grad_norm: 3.0786 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8299 loss: 2.8299 2022/10/07 17:01:16 - mmengine - INFO - Epoch(train) [46][1580/2119] lr: 4.0000e-02 eta: 21:02:05 time: 0.3615 data_time: 0.0197 memory: 5826 grad_norm: 3.0496 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7842 loss: 2.7842 2022/10/07 17:01:22 - mmengine - INFO - Epoch(train) [46][1600/2119] lr: 4.0000e-02 eta: 21:01:56 time: 0.3055 data_time: 0.0207 memory: 5826 grad_norm: 3.1308 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7665 loss: 2.7665 2022/10/07 17:01:29 - mmengine - INFO - Epoch(train) [46][1620/2119] lr: 4.0000e-02 eta: 21:01:50 time: 0.3676 data_time: 0.0230 memory: 5826 grad_norm: 3.0847 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6366 loss: 2.6366 2022/10/07 17:01:36 - mmengine - INFO - Epoch(train) [46][1640/2119] lr: 4.0000e-02 eta: 21:01:44 time: 0.3428 data_time: 0.0226 memory: 5826 grad_norm: 3.0836 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6292 loss: 2.6292 2022/10/07 17:01:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 17:01:43 - mmengine - INFO - Epoch(train) [46][1660/2119] lr: 4.0000e-02 eta: 21:01:37 time: 0.3561 data_time: 0.0183 memory: 5826 grad_norm: 3.0769 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9163 loss: 2.9163 2022/10/07 17:01:49 - mmengine - INFO - Epoch(train) [46][1680/2119] lr: 4.0000e-02 eta: 21:01:30 time: 0.3244 data_time: 0.0236 memory: 5826 grad_norm: 3.0883 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7511 loss: 2.7511 2022/10/07 17:01:58 - mmengine - INFO - Epoch(train) [46][1700/2119] lr: 4.0000e-02 eta: 21:01:25 time: 0.4008 data_time: 0.0203 memory: 5826 grad_norm: 3.0606 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8031 loss: 2.8031 2022/10/07 17:02:04 - mmengine - INFO - Epoch(train) [46][1720/2119] lr: 4.0000e-02 eta: 21:01:19 time: 0.3415 data_time: 0.0193 memory: 5826 grad_norm: 3.1172 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4776 loss: 2.4776 2022/10/07 17:02:10 - mmengine - INFO - Epoch(train) [46][1740/2119] lr: 4.0000e-02 eta: 21:01:09 time: 0.2853 data_time: 0.0214 memory: 5826 grad_norm: 3.1039 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6400 loss: 2.6400 2022/10/07 17:02:17 - mmengine - INFO - Epoch(train) [46][1760/2119] lr: 4.0000e-02 eta: 21:01:03 time: 0.3694 data_time: 0.0227 memory: 5826 grad_norm: 3.0250 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7579 loss: 2.7579 2022/10/07 17:02:24 - mmengine - INFO - Epoch(train) [46][1780/2119] lr: 4.0000e-02 eta: 21:00:57 time: 0.3453 data_time: 0.0238 memory: 5826 grad_norm: 3.0833 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8590 loss: 2.8590 2022/10/07 17:02:31 - mmengine - INFO - Epoch(train) [46][1800/2119] lr: 4.0000e-02 eta: 21:00:49 time: 0.3217 data_time: 0.0245 memory: 5826 grad_norm: 3.0495 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7694 loss: 2.7694 2022/10/07 17:02:38 - mmengine - INFO - Epoch(train) [46][1820/2119] lr: 4.0000e-02 eta: 21:00:42 time: 0.3435 data_time: 0.0203 memory: 5826 grad_norm: 3.0732 top1_acc: 0.0625 top5_acc: 0.3750 loss_cls: 2.8048 loss: 2.8048 2022/10/07 17:02:45 - mmengine - INFO - Epoch(train) [46][1840/2119] lr: 4.0000e-02 eta: 21:00:37 time: 0.3900 data_time: 0.0252 memory: 5826 grad_norm: 3.0817 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6495 loss: 2.6495 2022/10/07 17:02:53 - mmengine - INFO - Epoch(train) [46][1860/2119] lr: 4.0000e-02 eta: 21:00:32 time: 0.3735 data_time: 0.0236 memory: 5826 grad_norm: 3.1105 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8754 loss: 2.8754 2022/10/07 17:03:00 - mmengine - INFO - Epoch(train) [46][1880/2119] lr: 4.0000e-02 eta: 21:00:25 time: 0.3364 data_time: 0.0205 memory: 5826 grad_norm: 3.0487 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8083 loss: 2.8083 2022/10/07 17:03:07 - mmengine - INFO - Epoch(train) [46][1900/2119] lr: 4.0000e-02 eta: 21:00:18 time: 0.3494 data_time: 0.0186 memory: 5826 grad_norm: 3.0873 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8611 loss: 2.8611 2022/10/07 17:03:13 - mmengine - INFO - Epoch(train) [46][1920/2119] lr: 4.0000e-02 eta: 21:00:11 time: 0.3391 data_time: 0.0232 memory: 5826 grad_norm: 3.1044 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7573 loss: 2.7573 2022/10/07 17:03:20 - mmengine - INFO - Epoch(train) [46][1940/2119] lr: 4.0000e-02 eta: 21:00:04 time: 0.3352 data_time: 0.0214 memory: 5826 grad_norm: 3.0581 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.0297 loss: 3.0297 2022/10/07 17:03:27 - mmengine - INFO - Epoch(train) [46][1960/2119] lr: 4.0000e-02 eta: 20:59:56 time: 0.3242 data_time: 0.0228 memory: 5826 grad_norm: 3.0659 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8677 loss: 2.8677 2022/10/07 17:03:33 - mmengine - INFO - Epoch(train) [46][1980/2119] lr: 4.0000e-02 eta: 20:59:48 time: 0.3081 data_time: 0.0257 memory: 5826 grad_norm: 3.0776 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9248 loss: 2.9248 2022/10/07 17:03:40 - mmengine - INFO - Epoch(train) [46][2000/2119] lr: 4.0000e-02 eta: 20:59:42 time: 0.3554 data_time: 0.0201 memory: 5826 grad_norm: 3.0785 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8089 loss: 2.8089 2022/10/07 17:03:47 - mmengine - INFO - Epoch(train) [46][2020/2119] lr: 4.0000e-02 eta: 20:59:36 time: 0.3775 data_time: 0.0194 memory: 5826 grad_norm: 3.1080 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9553 loss: 2.9553 2022/10/07 17:03:54 - mmengine - INFO - Epoch(train) [46][2040/2119] lr: 4.0000e-02 eta: 20:59:29 time: 0.3415 data_time: 0.0244 memory: 5826 grad_norm: 3.0899 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6929 loss: 2.6929 2022/10/07 17:04:01 - mmengine - INFO - Epoch(train) [46][2060/2119] lr: 4.0000e-02 eta: 20:59:23 time: 0.3440 data_time: 0.0256 memory: 5826 grad_norm: 3.1195 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8229 loss: 2.8229 2022/10/07 17:04:09 - mmengine - INFO - Epoch(train) [46][2080/2119] lr: 4.0000e-02 eta: 20:59:17 time: 0.3721 data_time: 0.0233 memory: 5826 grad_norm: 3.1158 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.7817 loss: 2.7817 2022/10/07 17:04:16 - mmengine - INFO - Epoch(train) [46][2100/2119] lr: 4.0000e-02 eta: 20:59:10 time: 0.3471 data_time: 0.0250 memory: 5826 grad_norm: 3.0873 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8703 loss: 2.8703 2022/10/07 17:04:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 17:04:21 - mmengine - INFO - Epoch(train) [46][2119/2119] lr: 4.0000e-02 eta: 20:59:10 time: 0.3159 data_time: 0.0163 memory: 5826 grad_norm: 3.1088 top1_acc: 0.3000 top5_acc: 0.6000 loss_cls: 2.9779 loss: 2.9779 2022/10/07 17:04:31 - mmengine - INFO - Epoch(train) [47][20/2119] lr: 4.0000e-02 eta: 20:58:49 time: 0.4915 data_time: 0.1307 memory: 5826 grad_norm: 3.1255 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6693 loss: 2.6693 2022/10/07 17:04:38 - mmengine - INFO - Epoch(train) [47][40/2119] lr: 4.0000e-02 eta: 20:58:42 time: 0.3419 data_time: 0.0300 memory: 5826 grad_norm: 3.1136 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9463 loss: 2.9463 2022/10/07 17:04:46 - mmengine - INFO - Epoch(train) [47][60/2119] lr: 4.0000e-02 eta: 20:58:38 time: 0.3929 data_time: 0.0245 memory: 5826 grad_norm: 3.0968 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7887 loss: 2.7887 2022/10/07 17:04:51 - mmengine - INFO - Epoch(train) [47][80/2119] lr: 4.0000e-02 eta: 20:58:28 time: 0.2763 data_time: 0.0223 memory: 5826 grad_norm: 3.1236 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6121 loss: 2.6121 2022/10/07 17:04:58 - mmengine - INFO - Epoch(train) [47][100/2119] lr: 4.0000e-02 eta: 20:58:21 time: 0.3514 data_time: 0.0230 memory: 5826 grad_norm: 3.0662 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7545 loss: 2.7545 2022/10/07 17:05:05 - mmengine - INFO - Epoch(train) [47][120/2119] lr: 4.0000e-02 eta: 20:58:15 time: 0.3576 data_time: 0.0211 memory: 5826 grad_norm: 3.0927 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9175 loss: 2.9175 2022/10/07 17:05:11 - mmengine - INFO - Epoch(train) [47][140/2119] lr: 4.0000e-02 eta: 20:58:06 time: 0.2999 data_time: 0.0219 memory: 5826 grad_norm: 3.0826 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.5776 loss: 2.5776 2022/10/07 17:05:20 - mmengine - INFO - Epoch(train) [47][160/2119] lr: 4.0000e-02 eta: 20:58:03 time: 0.4138 data_time: 0.0226 memory: 5826 grad_norm: 3.0988 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6310 loss: 2.6310 2022/10/07 17:05:26 - mmengine - INFO - Epoch(train) [47][180/2119] lr: 4.0000e-02 eta: 20:57:55 time: 0.3266 data_time: 0.0212 memory: 5826 grad_norm: 3.0585 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7977 loss: 2.7977 2022/10/07 17:05:34 - mmengine - INFO - Epoch(train) [47][200/2119] lr: 4.0000e-02 eta: 20:57:51 time: 0.3959 data_time: 0.0260 memory: 5826 grad_norm: 3.0283 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6522 loss: 2.6522 2022/10/07 17:05:41 - mmengine - INFO - Epoch(train) [47][220/2119] lr: 4.0000e-02 eta: 20:57:44 time: 0.3415 data_time: 0.0224 memory: 5826 grad_norm: 3.0119 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6472 loss: 2.6472 2022/10/07 17:05:48 - mmengine - INFO - Epoch(train) [47][240/2119] lr: 4.0000e-02 eta: 20:57:37 time: 0.3494 data_time: 0.0178 memory: 5826 grad_norm: 3.1120 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7913 loss: 2.7913 2022/10/07 17:05:55 - mmengine - INFO - Epoch(train) [47][260/2119] lr: 4.0000e-02 eta: 20:57:30 time: 0.3375 data_time: 0.0317 memory: 5826 grad_norm: 3.1311 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8896 loss: 2.8896 2022/10/07 17:06:02 - mmengine - INFO - Epoch(train) [47][280/2119] lr: 4.0000e-02 eta: 20:57:25 time: 0.3762 data_time: 0.0208 memory: 5826 grad_norm: 3.1080 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0191 loss: 3.0191 2022/10/07 17:06:08 - mmengine - INFO - Epoch(train) [47][300/2119] lr: 4.0000e-02 eta: 20:57:15 time: 0.2863 data_time: 0.0248 memory: 5826 grad_norm: 3.0524 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8169 loss: 2.8169 2022/10/07 17:06:15 - mmengine - INFO - Epoch(train) [47][320/2119] lr: 4.0000e-02 eta: 20:57:09 time: 0.3613 data_time: 0.0240 memory: 5826 grad_norm: 3.1623 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8098 loss: 2.8098 2022/10/07 17:06:21 - mmengine - INFO - Epoch(train) [47][340/2119] lr: 4.0000e-02 eta: 20:57:01 time: 0.3066 data_time: 0.0228 memory: 5826 grad_norm: 3.1306 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7437 loss: 2.7437 2022/10/07 17:06:29 - mmengine - INFO - Epoch(train) [47][360/2119] lr: 4.0000e-02 eta: 20:56:56 time: 0.4016 data_time: 0.0203 memory: 5826 grad_norm: 3.1708 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7402 loss: 2.7402 2022/10/07 17:06:35 - mmengine - INFO - Epoch(train) [47][380/2119] lr: 4.0000e-02 eta: 20:56:48 time: 0.3006 data_time: 0.0206 memory: 5826 grad_norm: 3.0800 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7823 loss: 2.7823 2022/10/07 17:06:43 - mmengine - INFO - Epoch(train) [47][400/2119] lr: 4.0000e-02 eta: 20:56:42 time: 0.3645 data_time: 0.0237 memory: 5826 grad_norm: 3.1218 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8492 loss: 2.8492 2022/10/07 17:06:49 - mmengine - INFO - Epoch(train) [47][420/2119] lr: 4.0000e-02 eta: 20:56:34 time: 0.3275 data_time: 0.0280 memory: 5826 grad_norm: 3.0665 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7857 loss: 2.7857 2022/10/07 17:06:57 - mmengine - INFO - Epoch(train) [47][440/2119] lr: 4.0000e-02 eta: 20:56:29 time: 0.3756 data_time: 0.0175 memory: 5826 grad_norm: 3.0568 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8878 loss: 2.8878 2022/10/07 17:07:03 - mmengine - INFO - Epoch(train) [47][460/2119] lr: 4.0000e-02 eta: 20:56:21 time: 0.3098 data_time: 0.0229 memory: 5826 grad_norm: 3.1671 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8860 loss: 2.8860 2022/10/07 17:07:10 - mmengine - INFO - Epoch(train) [47][480/2119] lr: 4.0000e-02 eta: 20:56:15 time: 0.3615 data_time: 0.0219 memory: 5826 grad_norm: 3.0857 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8565 loss: 2.8565 2022/10/07 17:07:17 - mmengine - INFO - Epoch(train) [47][500/2119] lr: 4.0000e-02 eta: 20:56:08 time: 0.3496 data_time: 0.0203 memory: 5826 grad_norm: 3.1110 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0475 loss: 3.0475 2022/10/07 17:07:25 - mmengine - INFO - Epoch(train) [47][520/2119] lr: 4.0000e-02 eta: 20:56:03 time: 0.3758 data_time: 0.0242 memory: 5826 grad_norm: 3.1122 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8610 loss: 2.8610 2022/10/07 17:07:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 17:07:31 - mmengine - INFO - Epoch(train) [47][540/2119] lr: 4.0000e-02 eta: 20:55:54 time: 0.2995 data_time: 0.0280 memory: 5826 grad_norm: 3.0520 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6175 loss: 2.6175 2022/10/07 17:07:38 - mmengine - INFO - Epoch(train) [47][560/2119] lr: 4.0000e-02 eta: 20:55:48 time: 0.3659 data_time: 0.0159 memory: 5826 grad_norm: 3.1494 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9760 loss: 2.9760 2022/10/07 17:07:45 - mmengine - INFO - Epoch(train) [47][580/2119] lr: 4.0000e-02 eta: 20:55:42 time: 0.3686 data_time: 0.0260 memory: 5826 grad_norm: 3.0733 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7639 loss: 2.7639 2022/10/07 17:07:51 - mmengine - INFO - Epoch(train) [47][600/2119] lr: 4.0000e-02 eta: 20:55:34 time: 0.2998 data_time: 0.0212 memory: 5826 grad_norm: 3.1198 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8869 loss: 2.8869 2022/10/07 17:07:58 - mmengine - INFO - Epoch(train) [47][620/2119] lr: 4.0000e-02 eta: 20:55:26 time: 0.3338 data_time: 0.0242 memory: 5826 grad_norm: 3.0924 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7138 loss: 2.7138 2022/10/07 17:08:06 - mmengine - INFO - Epoch(train) [47][640/2119] lr: 4.0000e-02 eta: 20:55:22 time: 0.4091 data_time: 0.0202 memory: 5826 grad_norm: 3.1763 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9042 loss: 2.9042 2022/10/07 17:08:12 - mmengine - INFO - Epoch(train) [47][660/2119] lr: 4.0000e-02 eta: 20:55:14 time: 0.3109 data_time: 0.0263 memory: 5826 grad_norm: 3.0882 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8019 loss: 2.8019 2022/10/07 17:08:20 - mmengine - INFO - Epoch(train) [47][680/2119] lr: 4.0000e-02 eta: 20:55:08 time: 0.3672 data_time: 0.0205 memory: 5826 grad_norm: 3.0778 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7458 loss: 2.7458 2022/10/07 17:08:26 - mmengine - INFO - Epoch(train) [47][700/2119] lr: 4.0000e-02 eta: 20:55:01 time: 0.3402 data_time: 0.0209 memory: 5826 grad_norm: 3.0756 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7501 loss: 2.7501 2022/10/07 17:08:33 - mmengine - INFO - Epoch(train) [47][720/2119] lr: 4.0000e-02 eta: 20:54:53 time: 0.3070 data_time: 0.0239 memory: 5826 grad_norm: 3.0747 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7236 loss: 2.7236 2022/10/07 17:08:39 - mmengine - INFO - Epoch(train) [47][740/2119] lr: 4.0000e-02 eta: 20:54:44 time: 0.3056 data_time: 0.0252 memory: 5826 grad_norm: 3.1052 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7713 loss: 2.7713 2022/10/07 17:08:45 - mmengine - INFO - Epoch(train) [47][760/2119] lr: 4.0000e-02 eta: 20:54:37 time: 0.3333 data_time: 0.0244 memory: 5826 grad_norm: 3.0451 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7471 loss: 2.7471 2022/10/07 17:08:53 - mmengine - INFO - Epoch(train) [47][780/2119] lr: 4.0000e-02 eta: 20:54:31 time: 0.3696 data_time: 0.0272 memory: 5826 grad_norm: 3.0861 top1_acc: 0.3125 top5_acc: 0.8750 loss_cls: 2.4716 loss: 2.4716 2022/10/07 17:09:00 - mmengine - INFO - Epoch(train) [47][800/2119] lr: 4.0000e-02 eta: 20:54:25 time: 0.3439 data_time: 0.0198 memory: 5826 grad_norm: 3.0699 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6878 loss: 2.6878 2022/10/07 17:09:07 - mmengine - INFO - Epoch(train) [47][820/2119] lr: 4.0000e-02 eta: 20:54:18 time: 0.3563 data_time: 0.0194 memory: 5826 grad_norm: 3.1111 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8158 loss: 2.8158 2022/10/07 17:09:13 - mmengine - INFO - Epoch(train) [47][840/2119] lr: 4.0000e-02 eta: 20:54:09 time: 0.2898 data_time: 0.0218 memory: 5826 grad_norm: 3.0859 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6991 loss: 2.6991 2022/10/07 17:09:20 - mmengine - INFO - Epoch(train) [47][860/2119] lr: 4.0000e-02 eta: 20:54:03 time: 0.3531 data_time: 0.0294 memory: 5826 grad_norm: 3.1004 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8421 loss: 2.8421 2022/10/07 17:09:26 - mmengine - INFO - Epoch(train) [47][880/2119] lr: 4.0000e-02 eta: 20:53:56 time: 0.3342 data_time: 0.0230 memory: 5826 grad_norm: 3.0839 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7457 loss: 2.7457 2022/10/07 17:09:33 - mmengine - INFO - Epoch(train) [47][900/2119] lr: 4.0000e-02 eta: 20:53:49 time: 0.3557 data_time: 0.0215 memory: 5826 grad_norm: 3.1143 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8364 loss: 2.8364 2022/10/07 17:09:40 - mmengine - INFO - Epoch(train) [47][920/2119] lr: 4.0000e-02 eta: 20:53:42 time: 0.3293 data_time: 0.0205 memory: 5826 grad_norm: 3.1014 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.7499 loss: 2.7499 2022/10/07 17:09:47 - mmengine - INFO - Epoch(train) [47][940/2119] lr: 4.0000e-02 eta: 20:53:35 time: 0.3381 data_time: 0.0219 memory: 5826 grad_norm: 3.1225 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6482 loss: 2.6482 2022/10/07 17:09:53 - mmengine - INFO - Epoch(train) [47][960/2119] lr: 4.0000e-02 eta: 20:53:27 time: 0.3136 data_time: 0.0213 memory: 5826 grad_norm: 3.0638 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6768 loss: 2.6768 2022/10/07 17:10:00 - mmengine - INFO - Epoch(train) [47][980/2119] lr: 4.0000e-02 eta: 20:53:20 time: 0.3405 data_time: 0.0239 memory: 5826 grad_norm: 3.1353 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9094 loss: 2.9094 2022/10/07 17:10:07 - mmengine - INFO - Epoch(train) [47][1000/2119] lr: 4.0000e-02 eta: 20:53:14 time: 0.3744 data_time: 0.0368 memory: 5826 grad_norm: 3.0420 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8910 loss: 2.8910 2022/10/07 17:10:14 - mmengine - INFO - Epoch(train) [47][1020/2119] lr: 4.0000e-02 eta: 20:53:07 time: 0.3453 data_time: 0.0260 memory: 5826 grad_norm: 3.1110 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8145 loss: 2.8145 2022/10/07 17:10:21 - mmengine - INFO - Epoch(train) [47][1040/2119] lr: 4.0000e-02 eta: 20:53:01 time: 0.3438 data_time: 0.0224 memory: 5826 grad_norm: 3.0900 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6839 loss: 2.6839 2022/10/07 17:10:28 - mmengine - INFO - Epoch(train) [47][1060/2119] lr: 4.0000e-02 eta: 20:52:53 time: 0.3304 data_time: 0.0197 memory: 5826 grad_norm: 3.0603 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8293 loss: 2.8293 2022/10/07 17:10:35 - mmengine - INFO - Epoch(train) [47][1080/2119] lr: 4.0000e-02 eta: 20:52:47 time: 0.3496 data_time: 0.0216 memory: 5826 grad_norm: 3.0920 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8197 loss: 2.8197 2022/10/07 17:10:42 - mmengine - INFO - Epoch(train) [47][1100/2119] lr: 4.0000e-02 eta: 20:52:40 time: 0.3409 data_time: 0.0258 memory: 5826 grad_norm: 3.0632 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5528 loss: 2.5528 2022/10/07 17:10:48 - mmengine - INFO - Epoch(train) [47][1120/2119] lr: 4.0000e-02 eta: 20:52:33 time: 0.3376 data_time: 0.0257 memory: 5826 grad_norm: 3.1350 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9487 loss: 2.9487 2022/10/07 17:10:55 - mmengine - INFO - Epoch(train) [47][1140/2119] lr: 4.0000e-02 eta: 20:52:26 time: 0.3398 data_time: 0.0225 memory: 5826 grad_norm: 3.0904 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7463 loss: 2.7463 2022/10/07 17:11:03 - mmengine - INFO - Epoch(train) [47][1160/2119] lr: 4.0000e-02 eta: 20:52:21 time: 0.3813 data_time: 0.0247 memory: 5826 grad_norm: 3.0571 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5413 loss: 2.5413 2022/10/07 17:11:09 - mmengine - INFO - Epoch(train) [47][1180/2119] lr: 4.0000e-02 eta: 20:52:13 time: 0.3243 data_time: 0.0213 memory: 5826 grad_norm: 3.0958 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9103 loss: 2.9103 2022/10/07 17:11:16 - mmengine - INFO - Epoch(train) [47][1200/2119] lr: 4.0000e-02 eta: 20:52:05 time: 0.3155 data_time: 0.0212 memory: 5826 grad_norm: 3.1001 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9185 loss: 2.9185 2022/10/07 17:11:22 - mmengine - INFO - Epoch(train) [47][1220/2119] lr: 4.0000e-02 eta: 20:51:58 time: 0.3431 data_time: 0.0268 memory: 5826 grad_norm: 3.0887 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7168 loss: 2.7168 2022/10/07 17:11:30 - mmengine - INFO - Epoch(train) [47][1240/2119] lr: 4.0000e-02 eta: 20:51:52 time: 0.3572 data_time: 0.0185 memory: 5826 grad_norm: 3.0985 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7129 loss: 2.7129 2022/10/07 17:11:36 - mmengine - INFO - Epoch(train) [47][1260/2119] lr: 4.0000e-02 eta: 20:51:44 time: 0.3296 data_time: 0.0222 memory: 5826 grad_norm: 3.0246 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8489 loss: 2.8489 2022/10/07 17:11:43 - mmengine - INFO - Epoch(train) [47][1280/2119] lr: 4.0000e-02 eta: 20:51:37 time: 0.3393 data_time: 0.0183 memory: 5826 grad_norm: 3.0966 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9901 loss: 2.9901 2022/10/07 17:11:50 - mmengine - INFO - Epoch(train) [47][1300/2119] lr: 4.0000e-02 eta: 20:51:31 time: 0.3549 data_time: 0.0187 memory: 5826 grad_norm: 3.1029 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6696 loss: 2.6696 2022/10/07 17:11:57 - mmengine - INFO - Epoch(train) [47][1320/2119] lr: 4.0000e-02 eta: 20:51:24 time: 0.3383 data_time: 0.0199 memory: 5826 grad_norm: 3.0969 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6738 loss: 2.6738 2022/10/07 17:12:05 - mmengine - INFO - Epoch(train) [47][1340/2119] lr: 4.0000e-02 eta: 20:51:19 time: 0.3870 data_time: 0.0266 memory: 5826 grad_norm: 3.1256 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7798 loss: 2.7798 2022/10/07 17:12:11 - mmengine - INFO - Epoch(train) [47][1360/2119] lr: 4.0000e-02 eta: 20:51:10 time: 0.2977 data_time: 0.0212 memory: 5826 grad_norm: 3.0825 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8870 loss: 2.8870 2022/10/07 17:12:18 - mmengine - INFO - Epoch(train) [47][1380/2119] lr: 4.0000e-02 eta: 20:51:05 time: 0.3826 data_time: 0.0181 memory: 5826 grad_norm: 3.0732 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7767 loss: 2.7767 2022/10/07 17:12:25 - mmengine - INFO - Epoch(train) [47][1400/2119] lr: 4.0000e-02 eta: 20:50:59 time: 0.3520 data_time: 0.0236 memory: 5826 grad_norm: 3.0804 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8552 loss: 2.8552 2022/10/07 17:12:32 - mmengine - INFO - Epoch(train) [47][1420/2119] lr: 4.0000e-02 eta: 20:50:51 time: 0.3231 data_time: 0.0220 memory: 5826 grad_norm: 3.1064 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5875 loss: 2.5875 2022/10/07 17:12:38 - mmengine - INFO - Epoch(train) [47][1440/2119] lr: 4.0000e-02 eta: 20:50:42 time: 0.2947 data_time: 0.0229 memory: 5826 grad_norm: 3.0536 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7165 loss: 2.7165 2022/10/07 17:12:45 - mmengine - INFO - Epoch(train) [47][1460/2119] lr: 4.0000e-02 eta: 20:50:37 time: 0.3755 data_time: 0.0273 memory: 5826 grad_norm: 3.0976 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7222 loss: 2.7222 2022/10/07 17:12:52 - mmengine - INFO - Epoch(train) [47][1480/2119] lr: 4.0000e-02 eta: 20:50:29 time: 0.3337 data_time: 0.0163 memory: 5826 grad_norm: 3.1374 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7632 loss: 2.7632 2022/10/07 17:12:59 - mmengine - INFO - Epoch(train) [47][1500/2119] lr: 4.0000e-02 eta: 20:50:22 time: 0.3423 data_time: 0.0250 memory: 5826 grad_norm: 3.1451 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8175 loss: 2.8175 2022/10/07 17:13:05 - mmengine - INFO - Epoch(train) [47][1520/2119] lr: 4.0000e-02 eta: 20:50:15 time: 0.3267 data_time: 0.0220 memory: 5826 grad_norm: 3.1123 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6920 loss: 2.6920 2022/10/07 17:13:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 17:13:12 - mmengine - INFO - Epoch(train) [47][1540/2119] lr: 4.0000e-02 eta: 20:50:07 time: 0.3292 data_time: 0.0220 memory: 5826 grad_norm: 3.1007 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9458 loss: 2.9458 2022/10/07 17:13:20 - mmengine - INFO - Epoch(train) [47][1560/2119] lr: 4.0000e-02 eta: 20:50:03 time: 0.3887 data_time: 0.0222 memory: 5826 grad_norm: 3.1018 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8177 loss: 2.8177 2022/10/07 17:13:26 - mmengine - INFO - Epoch(train) [47][1580/2119] lr: 4.0000e-02 eta: 20:49:55 time: 0.3249 data_time: 0.0219 memory: 5826 grad_norm: 3.0606 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7538 loss: 2.7538 2022/10/07 17:13:33 - mmengine - INFO - Epoch(train) [47][1600/2119] lr: 4.0000e-02 eta: 20:49:49 time: 0.3639 data_time: 0.0180 memory: 5826 grad_norm: 3.1392 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7550 loss: 2.7550 2022/10/07 17:13:40 - mmengine - INFO - Epoch(train) [47][1620/2119] lr: 4.0000e-02 eta: 20:49:42 time: 0.3405 data_time: 0.0273 memory: 5826 grad_norm: 3.0605 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6980 loss: 2.6980 2022/10/07 17:13:47 - mmengine - INFO - Epoch(train) [47][1640/2119] lr: 4.0000e-02 eta: 20:49:35 time: 0.3470 data_time: 0.0156 memory: 5826 grad_norm: 3.1024 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8078 loss: 2.8078 2022/10/07 17:13:54 - mmengine - INFO - Epoch(train) [47][1660/2119] lr: 4.0000e-02 eta: 20:49:29 time: 0.3574 data_time: 0.0229 memory: 5826 grad_norm: 3.0898 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9250 loss: 2.9250 2022/10/07 17:14:01 - mmengine - INFO - Epoch(train) [47][1680/2119] lr: 4.0000e-02 eta: 20:49:22 time: 0.3378 data_time: 0.0190 memory: 5826 grad_norm: 3.1346 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0424 loss: 3.0424 2022/10/07 17:14:08 - mmengine - INFO - Epoch(train) [47][1700/2119] lr: 4.0000e-02 eta: 20:49:15 time: 0.3354 data_time: 0.0185 memory: 5826 grad_norm: 3.0916 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8557 loss: 2.8557 2022/10/07 17:14:15 - mmengine - INFO - Epoch(train) [47][1720/2119] lr: 4.0000e-02 eta: 20:49:08 time: 0.3423 data_time: 0.0265 memory: 5826 grad_norm: 3.1367 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8654 loss: 2.8654 2022/10/07 17:14:22 - mmengine - INFO - Epoch(train) [47][1740/2119] lr: 4.0000e-02 eta: 20:49:03 time: 0.3796 data_time: 0.0201 memory: 5826 grad_norm: 3.0618 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8435 loss: 2.8435 2022/10/07 17:14:29 - mmengine - INFO - Epoch(train) [47][1760/2119] lr: 4.0000e-02 eta: 20:48:56 time: 0.3476 data_time: 0.0183 memory: 5826 grad_norm: 3.0507 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8291 loss: 2.8291 2022/10/07 17:14:36 - mmengine - INFO - Epoch(train) [47][1780/2119] lr: 4.0000e-02 eta: 20:48:50 time: 0.3506 data_time: 0.0230 memory: 5826 grad_norm: 3.1038 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8000 loss: 2.8000 2022/10/07 17:14:43 - mmengine - INFO - Epoch(train) [47][1800/2119] lr: 4.0000e-02 eta: 20:48:43 time: 0.3519 data_time: 0.0195 memory: 5826 grad_norm: 3.0877 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7186 loss: 2.7186 2022/10/07 17:14:50 - mmengine - INFO - Epoch(train) [47][1820/2119] lr: 4.0000e-02 eta: 20:48:36 time: 0.3263 data_time: 0.0248 memory: 5826 grad_norm: 3.1398 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8021 loss: 2.8021 2022/10/07 17:14:57 - mmengine - INFO - Epoch(train) [47][1840/2119] lr: 4.0000e-02 eta: 20:48:30 time: 0.3630 data_time: 0.0187 memory: 5826 grad_norm: 3.1092 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7170 loss: 2.7170 2022/10/07 17:15:04 - mmengine - INFO - Epoch(train) [47][1860/2119] lr: 4.0000e-02 eta: 20:48:22 time: 0.3342 data_time: 0.0240 memory: 5826 grad_norm: 3.0980 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6641 loss: 2.6641 2022/10/07 17:15:11 - mmengine - INFO - Epoch(train) [47][1880/2119] lr: 4.0000e-02 eta: 20:48:16 time: 0.3512 data_time: 0.0223 memory: 5826 grad_norm: 3.0565 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7376 loss: 2.7376 2022/10/07 17:15:18 - mmengine - INFO - Epoch(train) [47][1900/2119] lr: 4.0000e-02 eta: 20:48:11 time: 0.3807 data_time: 0.0248 memory: 5826 grad_norm: 3.0988 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7111 loss: 2.7111 2022/10/07 17:15:24 - mmengine - INFO - Epoch(train) [47][1920/2119] lr: 4.0000e-02 eta: 20:48:02 time: 0.3048 data_time: 0.0222 memory: 5826 grad_norm: 3.0222 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8512 loss: 2.8512 2022/10/07 17:15:32 - mmengine - INFO - Epoch(train) [47][1940/2119] lr: 4.0000e-02 eta: 20:47:56 time: 0.3623 data_time: 0.0239 memory: 5826 grad_norm: 3.0569 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7130 loss: 2.7130 2022/10/07 17:15:38 - mmengine - INFO - Epoch(train) [47][1960/2119] lr: 4.0000e-02 eta: 20:47:49 time: 0.3330 data_time: 0.0193 memory: 5826 grad_norm: 3.1046 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8185 loss: 2.8185 2022/10/07 17:15:46 - mmengine - INFO - Epoch(train) [47][1980/2119] lr: 4.0000e-02 eta: 20:47:43 time: 0.3712 data_time: 0.0221 memory: 5826 grad_norm: 3.0960 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7136 loss: 2.7136 2022/10/07 17:15:52 - mmengine - INFO - Epoch(train) [47][2000/2119] lr: 4.0000e-02 eta: 20:47:34 time: 0.2918 data_time: 0.0249 memory: 5826 grad_norm: 3.0809 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8593 loss: 2.8593 2022/10/07 17:15:59 - mmengine - INFO - Epoch(train) [47][2020/2119] lr: 4.0000e-02 eta: 20:47:28 time: 0.3479 data_time: 0.0275 memory: 5826 grad_norm: 3.1466 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9253 loss: 2.9253 2022/10/07 17:16:05 - mmengine - INFO - Epoch(train) [47][2040/2119] lr: 4.0000e-02 eta: 20:47:21 time: 0.3455 data_time: 0.0147 memory: 5826 grad_norm: 3.1348 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7484 loss: 2.7484 2022/10/07 17:16:12 - mmengine - INFO - Epoch(train) [47][2060/2119] lr: 4.0000e-02 eta: 20:47:14 time: 0.3346 data_time: 0.0217 memory: 5826 grad_norm: 3.0618 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7876 loss: 2.7876 2022/10/07 17:16:19 - mmengine - INFO - Epoch(train) [47][2080/2119] lr: 4.0000e-02 eta: 20:47:07 time: 0.3517 data_time: 0.0206 memory: 5826 grad_norm: 3.0667 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0445 loss: 3.0445 2022/10/07 17:16:27 - mmengine - INFO - Epoch(train) [47][2100/2119] lr: 4.0000e-02 eta: 20:47:02 time: 0.3916 data_time: 0.0210 memory: 5826 grad_norm: 3.1047 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8235 loss: 2.8235 2022/10/07 17:16:33 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 17:16:33 - mmengine - INFO - Epoch(train) [47][2119/2119] lr: 4.0000e-02 eta: 20:47:02 time: 0.2927 data_time: 0.0200 memory: 5826 grad_norm: 3.1709 top1_acc: 0.1000 top5_acc: 0.8000 loss_cls: 2.9641 loss: 2.9641 2022/10/07 17:16:42 - mmengine - INFO - Epoch(train) [48][20/2119] lr: 4.0000e-02 eta: 20:46:41 time: 0.4770 data_time: 0.1262 memory: 5826 grad_norm: 3.1240 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6676 loss: 2.6676 2022/10/07 17:16:49 - mmengine - INFO - Epoch(train) [48][40/2119] lr: 4.0000e-02 eta: 20:46:33 time: 0.3123 data_time: 0.0166 memory: 5826 grad_norm: 3.1231 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7514 loss: 2.7514 2022/10/07 17:16:56 - mmengine - INFO - Epoch(train) [48][60/2119] lr: 4.0000e-02 eta: 20:46:27 time: 0.3797 data_time: 0.0230 memory: 5826 grad_norm: 3.0449 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6667 loss: 2.6667 2022/10/07 17:17:03 - mmengine - INFO - Epoch(train) [48][80/2119] lr: 4.0000e-02 eta: 20:46:19 time: 0.3201 data_time: 0.0222 memory: 5826 grad_norm: 3.1395 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8713 loss: 2.8713 2022/10/07 17:17:10 - mmengine - INFO - Epoch(train) [48][100/2119] lr: 4.0000e-02 eta: 20:46:13 time: 0.3544 data_time: 0.0228 memory: 5826 grad_norm: 3.0884 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7058 loss: 2.7058 2022/10/07 17:17:16 - mmengine - INFO - Epoch(train) [48][120/2119] lr: 4.0000e-02 eta: 20:46:06 time: 0.3393 data_time: 0.0204 memory: 5826 grad_norm: 3.0913 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7626 loss: 2.7626 2022/10/07 17:17:24 - mmengine - INFO - Epoch(train) [48][140/2119] lr: 4.0000e-02 eta: 20:46:00 time: 0.3709 data_time: 0.0235 memory: 5826 grad_norm: 3.0976 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7116 loss: 2.7116 2022/10/07 17:17:30 - mmengine - INFO - Epoch(train) [48][160/2119] lr: 4.0000e-02 eta: 20:45:52 time: 0.3031 data_time: 0.0210 memory: 5826 grad_norm: 3.0712 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.9399 loss: 2.9399 2022/10/07 17:17:37 - mmengine - INFO - Epoch(train) [48][180/2119] lr: 4.0000e-02 eta: 20:45:47 time: 0.3797 data_time: 0.0200 memory: 5826 grad_norm: 3.1126 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6608 loss: 2.6608 2022/10/07 17:17:43 - mmengine - INFO - Epoch(train) [48][200/2119] lr: 4.0000e-02 eta: 20:45:37 time: 0.2727 data_time: 0.0243 memory: 5826 grad_norm: 3.1089 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5167 loss: 2.5167 2022/10/07 17:17:51 - mmengine - INFO - Epoch(train) [48][220/2119] lr: 4.0000e-02 eta: 20:45:32 time: 0.3943 data_time: 0.0225 memory: 5826 grad_norm: 3.0619 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9370 loss: 2.9370 2022/10/07 17:17:58 - mmengine - INFO - Epoch(train) [48][240/2119] lr: 4.0000e-02 eta: 20:45:25 time: 0.3330 data_time: 0.0176 memory: 5826 grad_norm: 3.1675 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8261 loss: 2.8261 2022/10/07 17:18:05 - mmengine - INFO - Epoch(train) [48][260/2119] lr: 4.0000e-02 eta: 20:45:19 time: 0.3698 data_time: 0.0235 memory: 5826 grad_norm: 3.0620 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9432 loss: 2.9432 2022/10/07 17:18:12 - mmengine - INFO - Epoch(train) [48][280/2119] lr: 4.0000e-02 eta: 20:45:12 time: 0.3370 data_time: 0.0161 memory: 5826 grad_norm: 3.1353 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7557 loss: 2.7557 2022/10/07 17:18:18 - mmengine - INFO - Epoch(train) [48][300/2119] lr: 4.0000e-02 eta: 20:45:05 time: 0.3390 data_time: 0.0214 memory: 5826 grad_norm: 3.0381 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5739 loss: 2.5739 2022/10/07 17:18:25 - mmengine - INFO - Epoch(train) [48][320/2119] lr: 4.0000e-02 eta: 20:44:57 time: 0.3237 data_time: 0.0182 memory: 5826 grad_norm: 3.0658 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6382 loss: 2.6382 2022/10/07 17:18:32 - mmengine - INFO - Epoch(train) [48][340/2119] lr: 4.0000e-02 eta: 20:44:51 time: 0.3656 data_time: 0.0213 memory: 5826 grad_norm: 3.1005 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7199 loss: 2.7199 2022/10/07 17:18:39 - mmengine - INFO - Epoch(train) [48][360/2119] lr: 4.0000e-02 eta: 20:44:45 time: 0.3423 data_time: 0.0252 memory: 5826 grad_norm: 3.1583 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6377 loss: 2.6377 2022/10/07 17:18:46 - mmengine - INFO - Epoch(train) [48][380/2119] lr: 4.0000e-02 eta: 20:44:38 time: 0.3582 data_time: 0.0165 memory: 5826 grad_norm: 3.1331 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7132 loss: 2.7132 2022/10/07 17:18:52 - mmengine - INFO - Epoch(train) [48][400/2119] lr: 4.0000e-02 eta: 20:44:30 time: 0.3004 data_time: 0.0235 memory: 5826 grad_norm: 3.0590 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9252 loss: 2.9252 2022/10/07 17:18:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 17:19:00 - mmengine - INFO - Epoch(train) [48][420/2119] lr: 4.0000e-02 eta: 20:44:25 time: 0.3804 data_time: 0.0200 memory: 5826 grad_norm: 3.1410 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6023 loss: 2.6023 2022/10/07 17:19:06 - mmengine - INFO - Epoch(train) [48][440/2119] lr: 4.0000e-02 eta: 20:44:17 time: 0.3222 data_time: 0.0195 memory: 5826 grad_norm: 3.1100 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5861 loss: 2.5861 2022/10/07 17:19:13 - mmengine - INFO - Epoch(train) [48][460/2119] lr: 4.0000e-02 eta: 20:44:10 time: 0.3523 data_time: 0.0193 memory: 5826 grad_norm: 3.0899 top1_acc: 0.0625 top5_acc: 0.2500 loss_cls: 2.8120 loss: 2.8120 2022/10/07 17:19:20 - mmengine - INFO - Epoch(train) [48][480/2119] lr: 4.0000e-02 eta: 20:44:03 time: 0.3387 data_time: 0.0230 memory: 5826 grad_norm: 3.0356 top1_acc: 0.2500 top5_acc: 0.8125 loss_cls: 2.7484 loss: 2.7484 2022/10/07 17:19:27 - mmengine - INFO - Epoch(train) [48][500/2119] lr: 4.0000e-02 eta: 20:43:56 time: 0.3225 data_time: 0.0264 memory: 5826 grad_norm: 3.0561 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6554 loss: 2.6554 2022/10/07 17:19:33 - mmengine - INFO - Epoch(train) [48][520/2119] lr: 4.0000e-02 eta: 20:43:48 time: 0.3302 data_time: 0.0186 memory: 5826 grad_norm: 3.0225 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5077 loss: 2.5077 2022/10/07 17:19:40 - mmengine - INFO - Epoch(train) [48][540/2119] lr: 4.0000e-02 eta: 20:43:42 time: 0.3568 data_time: 0.0218 memory: 5826 grad_norm: 3.0628 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7410 loss: 2.7410 2022/10/07 17:19:47 - mmengine - INFO - Epoch(train) [48][560/2119] lr: 4.0000e-02 eta: 20:43:34 time: 0.3273 data_time: 0.0186 memory: 5826 grad_norm: 3.0256 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6088 loss: 2.6088 2022/10/07 17:19:54 - mmengine - INFO - Epoch(train) [48][580/2119] lr: 4.0000e-02 eta: 20:43:27 time: 0.3359 data_time: 0.0211 memory: 5826 grad_norm: 3.1555 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7615 loss: 2.7615 2022/10/07 17:20:01 - mmengine - INFO - Epoch(train) [48][600/2119] lr: 4.0000e-02 eta: 20:43:22 time: 0.3866 data_time: 0.0231 memory: 5826 grad_norm: 3.0679 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8075 loss: 2.8075 2022/10/07 17:20:08 - mmengine - INFO - Epoch(train) [48][620/2119] lr: 4.0000e-02 eta: 20:43:15 time: 0.3270 data_time: 0.0198 memory: 5826 grad_norm: 3.0748 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6158 loss: 2.6158 2022/10/07 17:20:15 - mmengine - INFO - Epoch(train) [48][640/2119] lr: 4.0000e-02 eta: 20:43:08 time: 0.3383 data_time: 0.0197 memory: 5826 grad_norm: 3.1367 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.8565 loss: 2.8565 2022/10/07 17:20:21 - mmengine - INFO - Epoch(train) [48][660/2119] lr: 4.0000e-02 eta: 20:43:00 time: 0.3173 data_time: 0.0209 memory: 5826 grad_norm: 3.0670 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8177 loss: 2.8177 2022/10/07 17:20:28 - mmengine - INFO - Epoch(train) [48][680/2119] lr: 4.0000e-02 eta: 20:42:54 time: 0.3675 data_time: 0.0187 memory: 5826 grad_norm: 3.1453 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6221 loss: 2.6221 2022/10/07 17:20:34 - mmengine - INFO - Epoch(train) [48][700/2119] lr: 4.0000e-02 eta: 20:42:45 time: 0.3009 data_time: 0.0196 memory: 5826 grad_norm: 3.1859 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9234 loss: 2.9234 2022/10/07 17:20:41 - mmengine - INFO - Epoch(train) [48][720/2119] lr: 4.0000e-02 eta: 20:42:38 time: 0.3356 data_time: 0.0268 memory: 5826 grad_norm: 3.1054 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7962 loss: 2.7962 2022/10/07 17:20:48 - mmengine - INFO - Epoch(train) [48][740/2119] lr: 4.0000e-02 eta: 20:42:32 time: 0.3565 data_time: 0.0197 memory: 5826 grad_norm: 3.0666 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6480 loss: 2.6480 2022/10/07 17:20:55 - mmengine - INFO - Epoch(train) [48][760/2119] lr: 4.0000e-02 eta: 20:42:24 time: 0.3258 data_time: 0.0207 memory: 5826 grad_norm: 3.0570 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8499 loss: 2.8499 2022/10/07 17:21:02 - mmengine - INFO - Epoch(train) [48][780/2119] lr: 4.0000e-02 eta: 20:42:18 time: 0.3634 data_time: 0.0231 memory: 5826 grad_norm: 3.1319 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7016 loss: 2.7016 2022/10/07 17:21:08 - mmengine - INFO - Epoch(train) [48][800/2119] lr: 4.0000e-02 eta: 20:42:10 time: 0.3143 data_time: 0.0254 memory: 5826 grad_norm: 3.0538 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8511 loss: 2.8511 2022/10/07 17:21:15 - mmengine - INFO - Epoch(train) [48][820/2119] lr: 4.0000e-02 eta: 20:42:04 time: 0.3580 data_time: 0.0227 memory: 5826 grad_norm: 3.2076 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7838 loss: 2.7838 2022/10/07 17:21:22 - mmengine - INFO - Epoch(train) [48][840/2119] lr: 4.0000e-02 eta: 20:41:57 time: 0.3304 data_time: 0.0190 memory: 5826 grad_norm: 3.0439 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4883 loss: 2.4883 2022/10/07 17:21:29 - mmengine - INFO - Epoch(train) [48][860/2119] lr: 4.0000e-02 eta: 20:41:49 time: 0.3297 data_time: 0.0228 memory: 5826 grad_norm: 3.1133 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9721 loss: 2.9721 2022/10/07 17:21:35 - mmengine - INFO - Epoch(train) [48][880/2119] lr: 4.0000e-02 eta: 20:41:41 time: 0.3093 data_time: 0.0236 memory: 5826 grad_norm: 3.0870 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6403 loss: 2.6403 2022/10/07 17:21:42 - mmengine - INFO - Epoch(train) [48][900/2119] lr: 4.0000e-02 eta: 20:41:35 time: 0.3715 data_time: 0.0285 memory: 5826 grad_norm: 3.0772 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4605 loss: 2.4605 2022/10/07 17:21:49 - mmengine - INFO - Epoch(train) [48][920/2119] lr: 4.0000e-02 eta: 20:41:28 time: 0.3429 data_time: 0.0130 memory: 5826 grad_norm: 3.1192 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6080 loss: 2.6080 2022/10/07 17:21:57 - mmengine - INFO - Epoch(train) [48][940/2119] lr: 4.0000e-02 eta: 20:41:24 time: 0.4083 data_time: 0.0243 memory: 5826 grad_norm: 3.0946 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9372 loss: 2.9372 2022/10/07 17:22:03 - mmengine - INFO - Epoch(train) [48][960/2119] lr: 4.0000e-02 eta: 20:41:15 time: 0.2914 data_time: 0.0220 memory: 5826 grad_norm: 3.1482 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6471 loss: 2.6471 2022/10/07 17:22:10 - mmengine - INFO - Epoch(train) [48][980/2119] lr: 4.0000e-02 eta: 20:41:08 time: 0.3271 data_time: 0.0200 memory: 5826 grad_norm: 3.0929 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7059 loss: 2.7059 2022/10/07 17:22:17 - mmengine - INFO - Epoch(train) [48][1000/2119] lr: 4.0000e-02 eta: 20:41:02 time: 0.3601 data_time: 0.0191 memory: 5826 grad_norm: 3.0449 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5932 loss: 2.5932 2022/10/07 17:22:23 - mmengine - INFO - Epoch(train) [48][1020/2119] lr: 4.0000e-02 eta: 20:40:54 time: 0.3107 data_time: 0.0205 memory: 5826 grad_norm: 3.1037 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5500 loss: 2.5500 2022/10/07 17:22:30 - mmengine - INFO - Epoch(train) [48][1040/2119] lr: 4.0000e-02 eta: 20:40:47 time: 0.3530 data_time: 0.0244 memory: 5826 grad_norm: 3.1089 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6534 loss: 2.6534 2022/10/07 17:22:38 - mmengine - INFO - Epoch(train) [48][1060/2119] lr: 4.0000e-02 eta: 20:40:41 time: 0.3676 data_time: 0.0252 memory: 5826 grad_norm: 3.1073 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0379 loss: 3.0379 2022/10/07 17:22:45 - mmengine - INFO - Epoch(train) [48][1080/2119] lr: 4.0000e-02 eta: 20:40:35 time: 0.3618 data_time: 0.0183 memory: 5826 grad_norm: 3.0992 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9455 loss: 2.9455 2022/10/07 17:22:51 - mmengine - INFO - Epoch(train) [48][1100/2119] lr: 4.0000e-02 eta: 20:40:26 time: 0.2900 data_time: 0.0218 memory: 5826 grad_norm: 3.1468 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6601 loss: 2.6601 2022/10/07 17:22:58 - mmengine - INFO - Epoch(train) [48][1120/2119] lr: 4.0000e-02 eta: 20:40:20 time: 0.3654 data_time: 0.0194 memory: 5826 grad_norm: 3.0849 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6099 loss: 2.6099 2022/10/07 17:23:04 - mmengine - INFO - Epoch(train) [48][1140/2119] lr: 4.0000e-02 eta: 20:40:12 time: 0.3065 data_time: 0.0217 memory: 5826 grad_norm: 3.0667 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9875 loss: 2.9875 2022/10/07 17:23:12 - mmengine - INFO - Epoch(train) [48][1160/2119] lr: 4.0000e-02 eta: 20:40:07 time: 0.3780 data_time: 0.0239 memory: 5826 grad_norm: 3.0500 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7365 loss: 2.7365 2022/10/07 17:23:18 - mmengine - INFO - Epoch(train) [48][1180/2119] lr: 4.0000e-02 eta: 20:39:59 time: 0.3257 data_time: 0.0248 memory: 5826 grad_norm: 3.0591 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6672 loss: 2.6672 2022/10/07 17:23:25 - mmengine - INFO - Epoch(train) [48][1200/2119] lr: 4.0000e-02 eta: 20:39:53 time: 0.3545 data_time: 0.0189 memory: 5826 grad_norm: 3.1319 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6133 loss: 2.6133 2022/10/07 17:23:32 - mmengine - INFO - Epoch(train) [48][1220/2119] lr: 4.0000e-02 eta: 20:39:46 time: 0.3558 data_time: 0.0277 memory: 5826 grad_norm: 3.1553 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8365 loss: 2.8365 2022/10/07 17:23:41 - mmengine - INFO - Epoch(train) [48][1240/2119] lr: 4.0000e-02 eta: 20:39:43 time: 0.4198 data_time: 0.0174 memory: 5826 grad_norm: 3.0818 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8153 loss: 2.8153 2022/10/07 17:23:47 - mmengine - INFO - Epoch(train) [48][1260/2119] lr: 4.0000e-02 eta: 20:39:35 time: 0.3216 data_time: 0.0257 memory: 5826 grad_norm: 3.0840 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.9980 loss: 2.9980 2022/10/07 17:23:54 - mmengine - INFO - Epoch(train) [48][1280/2119] lr: 4.0000e-02 eta: 20:39:29 time: 0.3542 data_time: 0.0173 memory: 5826 grad_norm: 3.1333 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0122 loss: 3.0122 2022/10/07 17:24:00 - mmengine - INFO - Epoch(train) [48][1300/2119] lr: 4.0000e-02 eta: 20:39:20 time: 0.3038 data_time: 0.0225 memory: 5826 grad_norm: 3.1601 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.0114 loss: 3.0114 2022/10/07 17:24:08 - mmengine - INFO - Epoch(train) [48][1320/2119] lr: 4.0000e-02 eta: 20:39:15 time: 0.3921 data_time: 0.0200 memory: 5826 grad_norm: 3.1155 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7706 loss: 2.7706 2022/10/07 17:24:15 - mmengine - INFO - Epoch(train) [48][1340/2119] lr: 4.0000e-02 eta: 20:39:07 time: 0.3182 data_time: 0.0248 memory: 5826 grad_norm: 3.1277 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6762 loss: 2.6762 2022/10/07 17:24:22 - mmengine - INFO - Epoch(train) [48][1360/2119] lr: 4.0000e-02 eta: 20:39:03 time: 0.3909 data_time: 0.0201 memory: 5826 grad_norm: 3.1227 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6058 loss: 2.6058 2022/10/07 17:24:29 - mmengine - INFO - Epoch(train) [48][1380/2119] lr: 4.0000e-02 eta: 20:38:55 time: 0.3260 data_time: 0.0223 memory: 5826 grad_norm: 3.1197 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0368 loss: 3.0368 2022/10/07 17:24:37 - mmengine - INFO - Epoch(train) [48][1400/2119] lr: 4.0000e-02 eta: 20:38:50 time: 0.3922 data_time: 0.0198 memory: 5826 grad_norm: 3.0768 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.8523 loss: 2.8523 2022/10/07 17:24:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 17:24:43 - mmengine - INFO - Epoch(train) [48][1420/2119] lr: 4.0000e-02 eta: 20:38:41 time: 0.2926 data_time: 0.0198 memory: 5826 grad_norm: 3.1252 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 2.7486 loss: 2.7486 2022/10/07 17:24:50 - mmengine - INFO - Epoch(train) [48][1440/2119] lr: 4.0000e-02 eta: 20:38:35 time: 0.3594 data_time: 0.0196 memory: 5826 grad_norm: 3.0762 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6282 loss: 2.6282 2022/10/07 17:24:57 - mmengine - INFO - Epoch(train) [48][1460/2119] lr: 4.0000e-02 eta: 20:38:29 time: 0.3475 data_time: 0.0250 memory: 5826 grad_norm: 3.0921 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5927 loss: 2.5927 2022/10/07 17:25:04 - mmengine - INFO - Epoch(train) [48][1480/2119] lr: 4.0000e-02 eta: 20:38:23 time: 0.3776 data_time: 0.0203 memory: 5826 grad_norm: 3.0811 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5173 loss: 2.5173 2022/10/07 17:25:11 - mmengine - INFO - Epoch(train) [48][1500/2119] lr: 4.0000e-02 eta: 20:38:16 time: 0.3437 data_time: 0.0201 memory: 5826 grad_norm: 3.1049 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.9301 loss: 2.9301 2022/10/07 17:25:20 - mmengine - INFO - Epoch(train) [48][1520/2119] lr: 4.0000e-02 eta: 20:38:13 time: 0.4186 data_time: 0.0203 memory: 5826 grad_norm: 3.1090 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.4698 loss: 2.4698 2022/10/07 17:25:26 - mmengine - INFO - Epoch(train) [48][1540/2119] lr: 4.0000e-02 eta: 20:38:05 time: 0.3194 data_time: 0.0217 memory: 5826 grad_norm: 3.0951 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7401 loss: 2.7401 2022/10/07 17:25:33 - mmengine - INFO - Epoch(train) [48][1560/2119] lr: 4.0000e-02 eta: 20:37:59 time: 0.3646 data_time: 0.0272 memory: 5826 grad_norm: 3.0842 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7316 loss: 2.7316 2022/10/07 17:25:40 - mmengine - INFO - Epoch(train) [48][1580/2119] lr: 4.0000e-02 eta: 20:37:51 time: 0.3228 data_time: 0.0228 memory: 5826 grad_norm: 3.1420 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7220 loss: 2.7220 2022/10/07 17:25:47 - mmengine - INFO - Epoch(train) [48][1600/2119] lr: 4.0000e-02 eta: 20:37:45 time: 0.3454 data_time: 0.0246 memory: 5826 grad_norm: 3.0621 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8039 loss: 2.8039 2022/10/07 17:25:54 - mmengine - INFO - Epoch(train) [48][1620/2119] lr: 4.0000e-02 eta: 20:37:39 time: 0.3671 data_time: 0.0232 memory: 5826 grad_norm: 3.0790 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8022 loss: 2.8022 2022/10/07 17:26:00 - mmengine - INFO - Epoch(train) [48][1640/2119] lr: 4.0000e-02 eta: 20:37:31 time: 0.3164 data_time: 0.0216 memory: 5826 grad_norm: 3.1417 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9833 loss: 2.9833 2022/10/07 17:26:08 - mmengine - INFO - Epoch(train) [48][1660/2119] lr: 4.0000e-02 eta: 20:37:25 time: 0.3651 data_time: 0.0250 memory: 5826 grad_norm: 3.0474 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9660 loss: 2.9660 2022/10/07 17:26:14 - mmengine - INFO - Epoch(train) [48][1680/2119] lr: 4.0000e-02 eta: 20:37:17 time: 0.3201 data_time: 0.0180 memory: 5826 grad_norm: 3.0768 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8311 loss: 2.8311 2022/10/07 17:26:21 - mmengine - INFO - Epoch(train) [48][1700/2119] lr: 4.0000e-02 eta: 20:37:11 time: 0.3732 data_time: 0.0261 memory: 5826 grad_norm: 3.0425 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7955 loss: 2.7955 2022/10/07 17:26:28 - mmengine - INFO - Epoch(train) [48][1720/2119] lr: 4.0000e-02 eta: 20:37:04 time: 0.3302 data_time: 0.0213 memory: 5826 grad_norm: 3.1596 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7430 loss: 2.7430 2022/10/07 17:26:35 - mmengine - INFO - Epoch(train) [48][1740/2119] lr: 4.0000e-02 eta: 20:36:58 time: 0.3541 data_time: 0.0258 memory: 5826 grad_norm: 3.1218 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8528 loss: 2.8528 2022/10/07 17:26:42 - mmengine - INFO - Epoch(train) [48][1760/2119] lr: 4.0000e-02 eta: 20:36:51 time: 0.3567 data_time: 0.0179 memory: 5826 grad_norm: 3.1109 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8409 loss: 2.8409 2022/10/07 17:26:49 - mmengine - INFO - Epoch(train) [48][1780/2119] lr: 4.0000e-02 eta: 20:36:43 time: 0.3135 data_time: 0.0231 memory: 5826 grad_norm: 3.0683 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6886 loss: 2.6886 2022/10/07 17:26:55 - mmengine - INFO - Epoch(train) [48][1800/2119] lr: 4.0000e-02 eta: 20:36:36 time: 0.3292 data_time: 0.0226 memory: 5826 grad_norm: 3.0915 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8294 loss: 2.8294 2022/10/07 17:27:02 - mmengine - INFO - Epoch(train) [48][1820/2119] lr: 4.0000e-02 eta: 20:36:30 time: 0.3629 data_time: 0.0263 memory: 5826 grad_norm: 3.1420 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8620 loss: 2.8620 2022/10/07 17:27:09 - mmengine - INFO - Epoch(train) [48][1840/2119] lr: 4.0000e-02 eta: 20:36:23 time: 0.3336 data_time: 0.0182 memory: 5826 grad_norm: 3.0941 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7177 loss: 2.7177 2022/10/07 17:27:17 - mmengine - INFO - Epoch(train) [48][1860/2119] lr: 4.0000e-02 eta: 20:36:17 time: 0.3789 data_time: 0.0213 memory: 5826 grad_norm: 3.1217 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6074 loss: 2.6074 2022/10/07 17:27:23 - mmengine - INFO - Epoch(train) [48][1880/2119] lr: 4.0000e-02 eta: 20:36:09 time: 0.3137 data_time: 0.0231 memory: 5826 grad_norm: 3.0396 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9861 loss: 2.9861 2022/10/07 17:27:30 - mmengine - INFO - Epoch(train) [48][1900/2119] lr: 4.0000e-02 eta: 20:36:02 time: 0.3360 data_time: 0.0209 memory: 5826 grad_norm: 3.1301 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8012 loss: 2.8012 2022/10/07 17:27:37 - mmengine - INFO - Epoch(train) [48][1920/2119] lr: 4.0000e-02 eta: 20:35:57 time: 0.3864 data_time: 0.0205 memory: 5826 grad_norm: 3.0932 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7887 loss: 2.7887 2022/10/07 17:27:43 - mmengine - INFO - Epoch(train) [48][1940/2119] lr: 4.0000e-02 eta: 20:35:49 time: 0.3049 data_time: 0.0223 memory: 5826 grad_norm: 3.0242 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6561 loss: 2.6561 2022/10/07 17:27:50 - mmengine - INFO - Epoch(train) [48][1960/2119] lr: 4.0000e-02 eta: 20:35:41 time: 0.3178 data_time: 0.0234 memory: 5826 grad_norm: 3.1068 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6773 loss: 2.6773 2022/10/07 17:27:58 - mmengine - INFO - Epoch(train) [48][1980/2119] lr: 4.0000e-02 eta: 20:35:36 time: 0.3874 data_time: 0.0210 memory: 5826 grad_norm: 3.1061 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9933 loss: 2.9933 2022/10/07 17:28:04 - mmengine - INFO - Epoch(train) [48][2000/2119] lr: 4.0000e-02 eta: 20:35:28 time: 0.3262 data_time: 0.0181 memory: 5826 grad_norm: 3.0170 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6640 loss: 2.6640 2022/10/07 17:28:11 - mmengine - INFO - Epoch(train) [48][2020/2119] lr: 4.0000e-02 eta: 20:35:21 time: 0.3449 data_time: 0.0217 memory: 5826 grad_norm: 3.0413 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6075 loss: 2.6075 2022/10/07 17:28:17 - mmengine - INFO - Epoch(train) [48][2040/2119] lr: 4.0000e-02 eta: 20:35:14 time: 0.3206 data_time: 0.0170 memory: 5826 grad_norm: 3.0910 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7479 loss: 2.7479 2022/10/07 17:28:24 - mmengine - INFO - Epoch(train) [48][2060/2119] lr: 4.0000e-02 eta: 20:35:06 time: 0.3301 data_time: 0.0219 memory: 5826 grad_norm: 3.1291 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9864 loss: 2.9864 2022/10/07 17:28:30 - mmengine - INFO - Epoch(train) [48][2080/2119] lr: 4.0000e-02 eta: 20:34:58 time: 0.3174 data_time: 0.0214 memory: 5826 grad_norm: 3.0692 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6216 loss: 2.6216 2022/10/07 17:28:38 - mmengine - INFO - Epoch(train) [48][2100/2119] lr: 4.0000e-02 eta: 20:34:53 time: 0.3844 data_time: 0.0226 memory: 5826 grad_norm: 3.0502 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5893 loss: 2.5893 2022/10/07 17:28:44 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 17:28:44 - mmengine - INFO - Epoch(train) [48][2119/2119] lr: 4.0000e-02 eta: 20:34:53 time: 0.3055 data_time: 0.0223 memory: 5826 grad_norm: 3.1531 top1_acc: 0.5000 top5_acc: 0.7000 loss_cls: 2.6339 loss: 2.6339 2022/10/07 17:28:44 - mmengine - INFO - Saving checkpoint at 48 epochs 2022/10/07 17:28:55 - mmengine - INFO - Epoch(train) [49][20/2119] lr: 4.0000e-02 eta: 20:34:27 time: 0.3705 data_time: 0.1606 memory: 5826 grad_norm: 3.0802 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8876 loss: 2.8876 2022/10/07 17:29:01 - mmengine - INFO - Epoch(train) [49][40/2119] lr: 4.0000e-02 eta: 20:34:19 time: 0.3125 data_time: 0.0855 memory: 5826 grad_norm: 3.1097 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6819 loss: 2.6819 2022/10/07 17:29:08 - mmengine - INFO - Epoch(train) [49][60/2119] lr: 4.0000e-02 eta: 20:34:13 time: 0.3580 data_time: 0.0253 memory: 5826 grad_norm: 3.1006 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9734 loss: 2.9734 2022/10/07 17:29:15 - mmengine - INFO - Epoch(train) [49][80/2119] lr: 4.0000e-02 eta: 20:34:05 time: 0.3196 data_time: 0.0220 memory: 5826 grad_norm: 3.0919 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6862 loss: 2.6862 2022/10/07 17:29:22 - mmengine - INFO - Epoch(train) [49][100/2119] lr: 4.0000e-02 eta: 20:33:58 time: 0.3434 data_time: 0.0243 memory: 5826 grad_norm: 3.0957 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6118 loss: 2.6118 2022/10/07 17:29:28 - mmengine - INFO - Epoch(train) [49][120/2119] lr: 4.0000e-02 eta: 20:33:50 time: 0.3200 data_time: 0.0213 memory: 5826 grad_norm: 3.1443 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8614 loss: 2.8614 2022/10/07 17:29:35 - mmengine - INFO - Epoch(train) [49][140/2119] lr: 4.0000e-02 eta: 20:33:44 time: 0.3529 data_time: 0.0226 memory: 5826 grad_norm: 3.0962 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8258 loss: 2.8258 2022/10/07 17:29:42 - mmengine - INFO - Epoch(train) [49][160/2119] lr: 4.0000e-02 eta: 20:33:38 time: 0.3539 data_time: 0.0272 memory: 5826 grad_norm: 3.0536 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 3.0526 loss: 3.0526 2022/10/07 17:29:49 - mmengine - INFO - Epoch(train) [49][180/2119] lr: 4.0000e-02 eta: 20:33:32 time: 0.3632 data_time: 0.0213 memory: 5826 grad_norm: 3.1097 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8519 loss: 2.8519 2022/10/07 17:29:56 - mmengine - INFO - Epoch(train) [49][200/2119] lr: 4.0000e-02 eta: 20:33:24 time: 0.3149 data_time: 0.0203 memory: 5826 grad_norm: 3.0882 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5984 loss: 2.5984 2022/10/07 17:30:04 - mmengine - INFO - Epoch(train) [49][220/2119] lr: 4.0000e-02 eta: 20:33:19 time: 0.4062 data_time: 0.0210 memory: 5826 grad_norm: 3.1320 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8276 loss: 2.8276 2022/10/07 17:30:10 - mmengine - INFO - Epoch(train) [49][240/2119] lr: 4.0000e-02 eta: 20:33:12 time: 0.3282 data_time: 0.0185 memory: 5826 grad_norm: 3.1149 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8123 loss: 2.8123 2022/10/07 17:30:18 - mmengine - INFO - Epoch(train) [49][260/2119] lr: 4.0000e-02 eta: 20:33:07 time: 0.3779 data_time: 0.0265 memory: 5826 grad_norm: 3.1244 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 3.0440 loss: 3.0440 2022/10/07 17:30:24 - mmengine - INFO - Epoch(train) [49][280/2119] lr: 4.0000e-02 eta: 20:32:59 time: 0.3217 data_time: 0.0243 memory: 5826 grad_norm: 3.0637 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6571 loss: 2.6571 2022/10/07 17:30:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 17:30:31 - mmengine - INFO - Epoch(train) [49][300/2119] lr: 4.0000e-02 eta: 20:32:51 time: 0.3239 data_time: 0.0230 memory: 5826 grad_norm: 3.0803 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6688 loss: 2.6688 2022/10/07 17:30:38 - mmengine - INFO - Epoch(train) [49][320/2119] lr: 4.0000e-02 eta: 20:32:44 time: 0.3438 data_time: 0.0239 memory: 5826 grad_norm: 3.0880 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7131 loss: 2.7131 2022/10/07 17:30:46 - mmengine - INFO - Epoch(train) [49][340/2119] lr: 4.0000e-02 eta: 20:32:40 time: 0.3969 data_time: 0.0230 memory: 5826 grad_norm: 3.1014 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8529 loss: 2.8529 2022/10/07 17:30:52 - mmengine - INFO - Epoch(train) [49][360/2119] lr: 4.0000e-02 eta: 20:32:31 time: 0.3005 data_time: 0.0200 memory: 5826 grad_norm: 3.0890 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8438 loss: 2.8438 2022/10/07 17:31:00 - mmengine - INFO - Epoch(train) [49][380/2119] lr: 4.0000e-02 eta: 20:32:28 time: 0.4333 data_time: 0.0188 memory: 5826 grad_norm: 3.1528 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6268 loss: 2.6268 2022/10/07 17:31:06 - mmengine - INFO - Epoch(train) [49][400/2119] lr: 4.0000e-02 eta: 20:32:19 time: 0.2793 data_time: 0.0227 memory: 5826 grad_norm: 3.0801 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7363 loss: 2.7363 2022/10/07 17:31:13 - mmengine - INFO - Epoch(train) [49][420/2119] lr: 4.0000e-02 eta: 20:32:13 time: 0.3705 data_time: 0.0249 memory: 5826 grad_norm: 3.0747 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7585 loss: 2.7585 2022/10/07 17:31:20 - mmengine - INFO - Epoch(train) [49][440/2119] lr: 4.0000e-02 eta: 20:32:06 time: 0.3399 data_time: 0.0199 memory: 5826 grad_norm: 3.1218 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9128 loss: 2.9128 2022/10/07 17:31:27 - mmengine - INFO - Epoch(train) [49][460/2119] lr: 4.0000e-02 eta: 20:31:59 time: 0.3500 data_time: 0.0239 memory: 5826 grad_norm: 3.1129 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7668 loss: 2.7668 2022/10/07 17:31:34 - mmengine - INFO - Epoch(train) [49][480/2119] lr: 4.0000e-02 eta: 20:31:53 time: 0.3439 data_time: 0.0217 memory: 5826 grad_norm: 3.1054 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9346 loss: 2.9346 2022/10/07 17:31:40 - mmengine - INFO - Epoch(train) [49][500/2119] lr: 4.0000e-02 eta: 20:31:45 time: 0.3187 data_time: 0.0184 memory: 5826 grad_norm: 3.1134 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8050 loss: 2.8050 2022/10/07 17:31:47 - mmengine - INFO - Epoch(train) [49][520/2119] lr: 4.0000e-02 eta: 20:31:37 time: 0.3214 data_time: 0.0233 memory: 5826 grad_norm: 3.1035 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7202 loss: 2.7202 2022/10/07 17:31:54 - mmengine - INFO - Epoch(train) [49][540/2119] lr: 4.0000e-02 eta: 20:31:31 time: 0.3582 data_time: 0.0223 memory: 5826 grad_norm: 3.1024 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8947 loss: 2.8947 2022/10/07 17:32:01 - mmengine - INFO - Epoch(train) [49][560/2119] lr: 4.0000e-02 eta: 20:31:24 time: 0.3461 data_time: 0.0284 memory: 5826 grad_norm: 3.0627 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6277 loss: 2.6277 2022/10/07 17:32:08 - mmengine - INFO - Epoch(train) [49][580/2119] lr: 4.0000e-02 eta: 20:31:18 time: 0.3657 data_time: 0.0198 memory: 5826 grad_norm: 3.1320 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7745 loss: 2.7745 2022/10/07 17:32:14 - mmengine - INFO - Epoch(train) [49][600/2119] lr: 4.0000e-02 eta: 20:31:09 time: 0.2938 data_time: 0.0229 memory: 5826 grad_norm: 3.1355 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.8504 loss: 2.8504 2022/10/07 17:32:22 - mmengine - INFO - Epoch(train) [49][620/2119] lr: 4.0000e-02 eta: 20:31:05 time: 0.3940 data_time: 0.0261 memory: 5826 grad_norm: 3.0765 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9272 loss: 2.9272 2022/10/07 17:32:28 - mmengine - INFO - Epoch(train) [49][640/2119] lr: 4.0000e-02 eta: 20:30:56 time: 0.2967 data_time: 0.0198 memory: 5826 grad_norm: 3.1061 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7260 loss: 2.7260 2022/10/07 17:32:35 - mmengine - INFO - Epoch(train) [49][660/2119] lr: 4.0000e-02 eta: 20:30:49 time: 0.3460 data_time: 0.0195 memory: 5826 grad_norm: 3.0515 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5095 loss: 2.5095 2022/10/07 17:32:41 - mmengine - INFO - Epoch(train) [49][680/2119] lr: 4.0000e-02 eta: 20:30:41 time: 0.3222 data_time: 0.0277 memory: 5826 grad_norm: 3.1713 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6033 loss: 2.6033 2022/10/07 17:32:49 - mmengine - INFO - Epoch(train) [49][700/2119] lr: 4.0000e-02 eta: 20:30:35 time: 0.3642 data_time: 0.0230 memory: 5826 grad_norm: 3.0997 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7398 loss: 2.7398 2022/10/07 17:32:55 - mmengine - INFO - Epoch(train) [49][720/2119] lr: 4.0000e-02 eta: 20:30:28 time: 0.3286 data_time: 0.0264 memory: 5826 grad_norm: 3.1022 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6699 loss: 2.6699 2022/10/07 17:33:02 - mmengine - INFO - Epoch(train) [49][740/2119] lr: 4.0000e-02 eta: 20:30:21 time: 0.3459 data_time: 0.0223 memory: 5826 grad_norm: 3.0809 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6897 loss: 2.6897 2022/10/07 17:33:11 - mmengine - INFO - Epoch(train) [49][760/2119] lr: 4.0000e-02 eta: 20:30:20 time: 0.4675 data_time: 0.0182 memory: 5826 grad_norm: 3.0961 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7886 loss: 2.7886 2022/10/07 17:33:18 - mmengine - INFO - Epoch(train) [49][780/2119] lr: 4.0000e-02 eta: 20:30:13 time: 0.3373 data_time: 0.0242 memory: 5826 grad_norm: 3.0754 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6756 loss: 2.6756 2022/10/07 17:33:24 - mmengine - INFO - Epoch(train) [49][800/2119] lr: 4.0000e-02 eta: 20:30:04 time: 0.3047 data_time: 0.0259 memory: 5826 grad_norm: 3.0632 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7478 loss: 2.7478 2022/10/07 17:33:32 - mmengine - INFO - Epoch(train) [49][820/2119] lr: 4.0000e-02 eta: 20:30:00 time: 0.4011 data_time: 0.0158 memory: 5826 grad_norm: 3.0601 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7931 loss: 2.7931 2022/10/07 17:33:38 - mmengine - INFO - Epoch(train) [49][840/2119] lr: 4.0000e-02 eta: 20:29:51 time: 0.2958 data_time: 0.0479 memory: 5826 grad_norm: 3.1265 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.6873 loss: 2.6873 2022/10/07 17:33:46 - mmengine - INFO - Epoch(train) [49][860/2119] lr: 4.0000e-02 eta: 20:29:45 time: 0.3732 data_time: 0.0205 memory: 5826 grad_norm: 3.1421 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7849 loss: 2.7849 2022/10/07 17:33:53 - mmengine - INFO - Epoch(train) [49][880/2119] lr: 4.0000e-02 eta: 20:29:39 time: 0.3686 data_time: 0.0237 memory: 5826 grad_norm: 3.0960 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7461 loss: 2.7461 2022/10/07 17:34:04 - mmengine - INFO - Epoch(train) [49][900/2119] lr: 4.0000e-02 eta: 20:29:41 time: 0.5517 data_time: 0.1178 memory: 5826 grad_norm: 3.0814 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9662 loss: 2.9662 2022/10/07 17:34:43 - mmengine - INFO - Epoch(train) [49][920/2119] lr: 4.0000e-02 eta: 20:30:41 time: 1.9171 data_time: 0.0879 memory: 5826 grad_norm: 3.0832 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6019 loss: 2.6019 2022/10/07 17:34:51 - mmengine - INFO - Epoch(train) [49][940/2119] lr: 4.0000e-02 eta: 20:30:37 time: 0.4159 data_time: 0.1438 memory: 5826 grad_norm: 3.1531 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7352 loss: 2.7352 2022/10/07 17:34:56 - mmengine - INFO - Epoch(train) [49][960/2119] lr: 4.0000e-02 eta: 20:30:26 time: 0.2562 data_time: 0.0182 memory: 5826 grad_norm: 3.1322 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.0546 loss: 3.0546 2022/10/07 17:35:12 - mmengine - INFO - Epoch(train) [49][980/2119] lr: 4.0000e-02 eta: 20:30:38 time: 0.7947 data_time: 0.0248 memory: 5826 grad_norm: 3.0590 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.8215 loss: 2.8215 2022/10/07 17:35:19 - mmengine - INFO - Epoch(train) [49][1000/2119] lr: 4.0000e-02 eta: 20:30:32 time: 0.3549 data_time: 0.0362 memory: 5826 grad_norm: 3.0498 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7594 loss: 2.7594 2022/10/07 17:35:24 - mmengine - INFO - Epoch(train) [49][1020/2119] lr: 4.0000e-02 eta: 20:30:22 time: 0.2741 data_time: 0.0173 memory: 5826 grad_norm: 3.0781 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6537 loss: 2.6537 2022/10/07 17:35:35 - mmengine - INFO - Epoch(train) [49][1040/2119] lr: 4.0000e-02 eta: 20:30:23 time: 0.5253 data_time: 0.0255 memory: 5826 grad_norm: 3.1128 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7303 loss: 2.7303 2022/10/07 17:35:45 - mmengine - INFO - Epoch(train) [49][1060/2119] lr: 4.0000e-02 eta: 20:30:23 time: 0.5152 data_time: 0.0398 memory: 5826 grad_norm: 3.1380 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7729 loss: 2.7729 2022/10/07 17:35:51 - mmengine - INFO - Epoch(train) [49][1080/2119] lr: 4.0000e-02 eta: 20:30:14 time: 0.2876 data_time: 0.0220 memory: 5826 grad_norm: 3.1004 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0754 loss: 3.0754 2022/10/07 17:36:00 - mmengine - INFO - Epoch(train) [49][1100/2119] lr: 4.0000e-02 eta: 20:30:11 time: 0.4309 data_time: 0.0209 memory: 5826 grad_norm: 3.1212 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8051 loss: 2.8051 2022/10/07 17:36:06 - mmengine - INFO - Epoch(train) [49][1120/2119] lr: 4.0000e-02 eta: 20:30:03 time: 0.3306 data_time: 0.0276 memory: 5826 grad_norm: 3.0969 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9521 loss: 2.9521 2022/10/07 17:36:30 - mmengine - INFO - Epoch(train) [49][1140/2119] lr: 4.0000e-02 eta: 20:30:24 time: 0.9931 data_time: 0.0187 memory: 5826 grad_norm: 3.1296 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7296 loss: 2.7296 2022/10/07 17:37:03 - mmengine - INFO - Epoch(train) [49][1160/2119] lr: 4.0000e-02 eta: 20:31:19 time: 1.8268 data_time: 0.3212 memory: 5826 grad_norm: 3.1100 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6433 loss: 2.6433 2022/10/07 17:37:09 - mmengine - INFO - Epoch(train) [49][1180/2119] lr: 4.0000e-02 eta: 20:31:10 time: 0.2968 data_time: 0.0381 memory: 5826 grad_norm: 3.1394 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9590 loss: 2.9590 2022/10/07 17:37:16 - mmengine - INFO - Epoch(train) [49][1200/2119] lr: 4.0000e-02 eta: 20:31:05 time: 0.3849 data_time: 0.0254 memory: 5826 grad_norm: 3.1520 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 2.9036 loss: 2.9036 2022/10/07 17:37:34 - mmengine - INFO - Epoch(train) [49][1220/2119] lr: 4.0000e-02 eta: 20:31:20 time: 0.8723 data_time: 0.0445 memory: 5826 grad_norm: 3.1202 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8993 loss: 2.8993 2022/10/07 17:37:40 - mmengine - INFO - Epoch(train) [49][1240/2119] lr: 4.0000e-02 eta: 20:31:13 time: 0.3371 data_time: 0.0303 memory: 5826 grad_norm: 3.1096 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6639 loss: 2.6639 2022/10/07 17:37:52 - mmengine - INFO - Epoch(train) [49][1260/2119] lr: 4.0000e-02 eta: 20:31:16 time: 0.5751 data_time: 0.0296 memory: 5826 grad_norm: 3.1016 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6971 loss: 2.6971 2022/10/07 17:37:57 - mmengine - INFO - Epoch(train) [49][1280/2119] lr: 4.0000e-02 eta: 20:31:05 time: 0.2532 data_time: 0.0264 memory: 5826 grad_norm: 3.0856 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7316 loss: 2.7316 2022/10/07 17:38:00 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 17:38:04 - mmengine - INFO - Epoch(train) [49][1300/2119] lr: 4.0000e-02 eta: 20:30:59 time: 0.3571 data_time: 0.0211 memory: 5826 grad_norm: 3.0900 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8966 loss: 2.8966 2022/10/07 17:38:11 - mmengine - INFO - Epoch(train) [49][1320/2119] lr: 4.0000e-02 eta: 20:30:53 time: 0.3582 data_time: 0.0193 memory: 5826 grad_norm: 3.0792 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7053 loss: 2.7053 2022/10/07 17:38:18 - mmengine - INFO - Epoch(train) [49][1340/2119] lr: 4.0000e-02 eta: 20:30:45 time: 0.3282 data_time: 0.0198 memory: 5826 grad_norm: 3.1186 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6307 loss: 2.6307 2022/10/07 17:38:25 - mmengine - INFO - Epoch(train) [49][1360/2119] lr: 4.0000e-02 eta: 20:30:38 time: 0.3410 data_time: 0.0230 memory: 5826 grad_norm: 3.0676 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8044 loss: 2.8044 2022/10/07 17:38:32 - mmengine - INFO - Epoch(train) [49][1380/2119] lr: 4.0000e-02 eta: 20:30:31 time: 0.3408 data_time: 0.0219 memory: 5826 grad_norm: 3.0711 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6970 loss: 2.6970 2022/10/07 17:38:39 - mmengine - INFO - Epoch(train) [49][1400/2119] lr: 4.0000e-02 eta: 20:30:26 time: 0.3961 data_time: 0.0286 memory: 5826 grad_norm: 3.0959 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8106 loss: 2.8106 2022/10/07 17:38:46 - mmengine - INFO - Epoch(train) [49][1420/2119] lr: 4.0000e-02 eta: 20:30:19 time: 0.3373 data_time: 0.0221 memory: 5826 grad_norm: 3.0665 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6602 loss: 2.6602 2022/10/07 17:38:53 - mmengine - INFO - Epoch(train) [49][1440/2119] lr: 4.0000e-02 eta: 20:30:11 time: 0.3238 data_time: 0.0273 memory: 5826 grad_norm: 3.0689 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7570 loss: 2.7570 2022/10/07 17:39:00 - mmengine - INFO - Epoch(train) [49][1460/2119] lr: 4.0000e-02 eta: 20:30:06 time: 0.3783 data_time: 0.0176 memory: 5826 grad_norm: 3.0905 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8719 loss: 2.8719 2022/10/07 17:39:08 - mmengine - INFO - Epoch(train) [49][1480/2119] lr: 4.0000e-02 eta: 20:30:02 time: 0.4017 data_time: 0.0247 memory: 5826 grad_norm: 3.1606 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9645 loss: 2.9645 2022/10/07 17:39:15 - mmengine - INFO - Epoch(train) [49][1500/2119] lr: 4.0000e-02 eta: 20:29:54 time: 0.3259 data_time: 0.0192 memory: 5826 grad_norm: 3.0777 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6960 loss: 2.6960 2022/10/07 17:39:22 - mmengine - INFO - Epoch(train) [49][1520/2119] lr: 4.0000e-02 eta: 20:29:47 time: 0.3361 data_time: 0.0240 memory: 5826 grad_norm: 3.0916 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7579 loss: 2.7579 2022/10/07 17:39:29 - mmengine - INFO - Epoch(train) [49][1540/2119] lr: 4.0000e-02 eta: 20:29:40 time: 0.3540 data_time: 0.0247 memory: 5826 grad_norm: 3.0569 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5853 loss: 2.5853 2022/10/07 17:39:35 - mmengine - INFO - Epoch(train) [49][1560/2119] lr: 4.0000e-02 eta: 20:29:32 time: 0.3211 data_time: 0.0263 memory: 5826 grad_norm: 3.0577 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8697 loss: 2.8697 2022/10/07 17:39:42 - mmengine - INFO - Epoch(train) [49][1580/2119] lr: 4.0000e-02 eta: 20:29:26 time: 0.3457 data_time: 0.0202 memory: 5826 grad_norm: 3.1021 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8807 loss: 2.8807 2022/10/07 17:39:50 - mmengine - INFO - Epoch(train) [49][1600/2119] lr: 4.0000e-02 eta: 20:29:21 time: 0.3980 data_time: 0.0192 memory: 5826 grad_norm: 3.1050 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.7801 loss: 2.7801 2022/10/07 17:39:56 - mmengine - INFO - Epoch(train) [49][1620/2119] lr: 4.0000e-02 eta: 20:29:12 time: 0.2896 data_time: 0.0265 memory: 5826 grad_norm: 3.1258 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8173 loss: 2.8173 2022/10/07 17:40:03 - mmengine - INFO - Epoch(train) [49][1640/2119] lr: 4.0000e-02 eta: 20:29:05 time: 0.3410 data_time: 0.0221 memory: 5826 grad_norm: 3.0873 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9682 loss: 2.9682 2022/10/07 17:40:09 - mmengine - INFO - Epoch(train) [49][1660/2119] lr: 4.0000e-02 eta: 20:28:56 time: 0.3059 data_time: 0.0219 memory: 5826 grad_norm: 3.0782 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8510 loss: 2.8510 2022/10/07 17:40:15 - mmengine - INFO - Epoch(train) [49][1680/2119] lr: 4.0000e-02 eta: 20:28:49 time: 0.3322 data_time: 0.0255 memory: 5826 grad_norm: 3.0878 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6078 loss: 2.6078 2022/10/07 17:40:22 - mmengine - INFO - Epoch(train) [49][1700/2119] lr: 4.0000e-02 eta: 20:28:43 time: 0.3509 data_time: 0.0304 memory: 5826 grad_norm: 3.0928 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8239 loss: 2.8239 2022/10/07 17:40:30 - mmengine - INFO - Epoch(train) [49][1720/2119] lr: 4.0000e-02 eta: 20:28:37 time: 0.3686 data_time: 0.0277 memory: 5826 grad_norm: 3.1252 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8451 loss: 2.8451 2022/10/07 17:40:37 - mmengine - INFO - Epoch(train) [49][1740/2119] lr: 4.0000e-02 eta: 20:28:30 time: 0.3550 data_time: 0.0177 memory: 5826 grad_norm: 3.0602 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6591 loss: 2.6591 2022/10/07 17:40:43 - mmengine - INFO - Epoch(train) [49][1760/2119] lr: 4.0000e-02 eta: 20:28:22 time: 0.3059 data_time: 0.0303 memory: 5826 grad_norm: 3.1309 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8236 loss: 2.8236 2022/10/07 17:40:49 - mmengine - INFO - Epoch(train) [49][1780/2119] lr: 4.0000e-02 eta: 20:28:13 time: 0.3012 data_time: 0.0250 memory: 5826 grad_norm: 3.1113 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6539 loss: 2.6539 2022/10/07 17:40:55 - mmengine - INFO - Epoch(train) [49][1800/2119] lr: 4.0000e-02 eta: 20:28:06 time: 0.3248 data_time: 0.0235 memory: 5826 grad_norm: 3.0848 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9287 loss: 2.9287 2022/10/07 17:41:04 - mmengine - INFO - Epoch(train) [49][1820/2119] lr: 4.0000e-02 eta: 20:28:01 time: 0.4022 data_time: 0.0192 memory: 5826 grad_norm: 3.0350 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8557 loss: 2.8557 2022/10/07 17:41:10 - mmengine - INFO - Epoch(train) [49][1840/2119] lr: 4.0000e-02 eta: 20:27:52 time: 0.3019 data_time: 0.0241 memory: 5826 grad_norm: 3.1032 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7243 loss: 2.7243 2022/10/07 17:41:17 - mmengine - INFO - Epoch(train) [49][1860/2119] lr: 4.0000e-02 eta: 20:27:47 time: 0.3679 data_time: 0.0202 memory: 5826 grad_norm: 3.1088 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7439 loss: 2.7439 2022/10/07 17:41:24 - mmengine - INFO - Epoch(train) [49][1880/2119] lr: 4.0000e-02 eta: 20:27:39 time: 0.3306 data_time: 0.0294 memory: 5826 grad_norm: 3.0673 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8743 loss: 2.8743 2022/10/07 17:41:31 - mmengine - INFO - Epoch(train) [49][1900/2119] lr: 4.0000e-02 eta: 20:27:33 time: 0.3499 data_time: 0.0181 memory: 5826 grad_norm: 3.0987 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8205 loss: 2.8205 2022/10/07 17:41:36 - mmengine - INFO - Epoch(train) [49][1920/2119] lr: 4.0000e-02 eta: 20:27:23 time: 0.2798 data_time: 0.0243 memory: 5826 grad_norm: 3.0702 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7778 loss: 2.7778 2022/10/07 17:41:43 - mmengine - INFO - Epoch(train) [49][1940/2119] lr: 4.0000e-02 eta: 20:27:16 time: 0.3421 data_time: 0.0189 memory: 5826 grad_norm: 3.1079 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8083 loss: 2.8083 2022/10/07 17:41:51 - mmengine - INFO - Epoch(train) [49][1960/2119] lr: 4.0000e-02 eta: 20:27:11 time: 0.3788 data_time: 0.0222 memory: 5826 grad_norm: 3.1073 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6743 loss: 2.6743 2022/10/07 17:41:57 - mmengine - INFO - Epoch(train) [49][1980/2119] lr: 4.0000e-02 eta: 20:27:02 time: 0.3069 data_time: 0.0189 memory: 5826 grad_norm: 3.0971 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6265 loss: 2.6265 2022/10/07 17:42:04 - mmengine - INFO - Epoch(train) [49][2000/2119] lr: 4.0000e-02 eta: 20:26:56 time: 0.3499 data_time: 0.0245 memory: 5826 grad_norm: 3.1128 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.9449 loss: 2.9449 2022/10/07 17:42:10 - mmengine - INFO - Epoch(train) [49][2020/2119] lr: 4.0000e-02 eta: 20:26:48 time: 0.3272 data_time: 0.0182 memory: 5826 grad_norm: 3.0588 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9061 loss: 2.9061 2022/10/07 17:42:18 - mmengine - INFO - Epoch(train) [49][2040/2119] lr: 4.0000e-02 eta: 20:26:42 time: 0.3658 data_time: 0.0266 memory: 5826 grad_norm: 3.0382 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7828 loss: 2.7828 2022/10/07 17:42:24 - mmengine - INFO - Epoch(train) [49][2060/2119] lr: 4.0000e-02 eta: 20:26:34 time: 0.3246 data_time: 0.0199 memory: 5826 grad_norm: 3.1633 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7403 loss: 2.7403 2022/10/07 17:42:31 - mmengine - INFO - Epoch(train) [49][2080/2119] lr: 4.0000e-02 eta: 20:26:28 time: 0.3576 data_time: 0.0226 memory: 5826 grad_norm: 3.0735 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5532 loss: 2.5532 2022/10/07 17:42:39 - mmengine - INFO - Epoch(train) [49][2100/2119] lr: 4.0000e-02 eta: 20:26:22 time: 0.3712 data_time: 0.0184 memory: 5826 grad_norm: 3.0396 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7655 loss: 2.7655 2022/10/07 17:42:44 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 17:42:44 - mmengine - INFO - Epoch(train) [49][2119/2119] lr: 4.0000e-02 eta: 20:26:22 time: 0.3001 data_time: 0.0187 memory: 5826 grad_norm: 3.0633 top1_acc: 0.5000 top5_acc: 0.8000 loss_cls: 2.8964 loss: 2.8964 2022/10/07 17:42:54 - mmengine - INFO - Epoch(train) [50][20/2119] lr: 4.0000e-02 eta: 20:26:02 time: 0.4904 data_time: 0.1254 memory: 5826 grad_norm: 3.0335 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7313 loss: 2.7313 2022/10/07 17:43:01 - mmengine - INFO - Epoch(train) [50][40/2119] lr: 4.0000e-02 eta: 20:25:55 time: 0.3406 data_time: 0.0238 memory: 5826 grad_norm: 3.0603 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6519 loss: 2.6519 2022/10/07 17:43:08 - mmengine - INFO - Epoch(train) [50][60/2119] lr: 4.0000e-02 eta: 20:25:49 time: 0.3673 data_time: 0.0245 memory: 5826 grad_norm: 3.1850 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7005 loss: 2.7005 2022/10/07 17:43:14 - mmengine - INFO - Epoch(train) [50][80/2119] lr: 4.0000e-02 eta: 20:25:40 time: 0.2924 data_time: 0.0194 memory: 5826 grad_norm: 3.1035 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7238 loss: 2.7238 2022/10/07 17:43:22 - mmengine - INFO - Epoch(train) [50][100/2119] lr: 4.0000e-02 eta: 20:25:35 time: 0.3945 data_time: 0.0233 memory: 5826 grad_norm: 3.1089 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6533 loss: 2.6533 2022/10/07 17:43:29 - mmengine - INFO - Epoch(train) [50][120/2119] lr: 4.0000e-02 eta: 20:25:28 time: 0.3392 data_time: 0.0226 memory: 5826 grad_norm: 3.1191 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9292 loss: 2.9292 2022/10/07 17:43:35 - mmengine - INFO - Epoch(train) [50][140/2119] lr: 4.0000e-02 eta: 20:25:20 time: 0.3172 data_time: 0.0213 memory: 5826 grad_norm: 3.0889 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6131 loss: 2.6131 2022/10/07 17:43:43 - mmengine - INFO - Epoch(train) [50][160/2119] lr: 4.0000e-02 eta: 20:25:14 time: 0.3600 data_time: 0.0208 memory: 5826 grad_norm: 3.1126 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9051 loss: 2.9051 2022/10/07 17:43:45 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 17:43:49 - mmengine - INFO - Epoch(train) [50][180/2119] lr: 4.0000e-02 eta: 20:25:06 time: 0.3173 data_time: 0.0204 memory: 5826 grad_norm: 3.0605 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4977 loss: 2.4977 2022/10/07 17:43:56 - mmengine - INFO - Epoch(train) [50][200/2119] lr: 4.0000e-02 eta: 20:24:59 time: 0.3532 data_time: 0.0263 memory: 5826 grad_norm: 3.1126 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6763 loss: 2.6763 2022/10/07 17:44:03 - mmengine - INFO - Epoch(train) [50][220/2119] lr: 4.0000e-02 eta: 20:24:52 time: 0.3468 data_time: 0.0154 memory: 5826 grad_norm: 3.1004 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9252 loss: 2.9252 2022/10/07 17:44:10 - mmengine - INFO - Epoch(train) [50][240/2119] lr: 4.0000e-02 eta: 20:24:46 time: 0.3522 data_time: 0.0263 memory: 5826 grad_norm: 3.1438 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8259 loss: 2.8259 2022/10/07 17:44:16 - mmengine - INFO - Epoch(train) [50][260/2119] lr: 4.0000e-02 eta: 20:24:38 time: 0.3272 data_time: 0.0215 memory: 5826 grad_norm: 3.2044 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7121 loss: 2.7121 2022/10/07 17:44:23 - mmengine - INFO - Epoch(train) [50][280/2119] lr: 4.0000e-02 eta: 20:24:31 time: 0.3423 data_time: 0.0219 memory: 5826 grad_norm: 3.0712 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7174 loss: 2.7174 2022/10/07 17:44:30 - mmengine - INFO - Epoch(train) [50][300/2119] lr: 4.0000e-02 eta: 20:24:24 time: 0.3355 data_time: 0.0217 memory: 5826 grad_norm: 3.1286 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6833 loss: 2.6833 2022/10/07 17:44:37 - mmengine - INFO - Epoch(train) [50][320/2119] lr: 4.0000e-02 eta: 20:24:17 time: 0.3299 data_time: 0.0238 memory: 5826 grad_norm: 3.1884 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6308 loss: 2.6308 2022/10/07 17:44:44 - mmengine - INFO - Epoch(train) [50][340/2119] lr: 4.0000e-02 eta: 20:24:11 time: 0.3752 data_time: 0.0208 memory: 5826 grad_norm: 3.0909 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8137 loss: 2.8137 2022/10/07 17:44:51 - mmengine - INFO - Epoch(train) [50][360/2119] lr: 4.0000e-02 eta: 20:24:04 time: 0.3391 data_time: 0.0225 memory: 5826 grad_norm: 3.0822 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7410 loss: 2.7410 2022/10/07 17:44:57 - mmengine - INFO - Epoch(train) [50][380/2119] lr: 4.0000e-02 eta: 20:23:56 time: 0.3021 data_time: 0.0212 memory: 5826 grad_norm: 3.0683 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6297 loss: 2.6297 2022/10/07 17:45:04 - mmengine - INFO - Epoch(train) [50][400/2119] lr: 4.0000e-02 eta: 20:23:50 time: 0.3711 data_time: 0.0214 memory: 5826 grad_norm: 3.0709 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8789 loss: 2.8789 2022/10/07 17:45:11 - mmengine - INFO - Epoch(train) [50][420/2119] lr: 4.0000e-02 eta: 20:23:42 time: 0.3167 data_time: 0.0157 memory: 5826 grad_norm: 3.1142 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7320 loss: 2.7320 2022/10/07 17:45:17 - mmengine - INFO - Epoch(train) [50][440/2119] lr: 4.0000e-02 eta: 20:23:35 time: 0.3356 data_time: 0.0221 memory: 5826 grad_norm: 3.0570 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6701 loss: 2.6701 2022/10/07 17:45:25 - mmengine - INFO - Epoch(train) [50][460/2119] lr: 4.0000e-02 eta: 20:23:28 time: 0.3551 data_time: 0.0152 memory: 5826 grad_norm: 3.0455 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8623 loss: 2.8623 2022/10/07 17:45:32 - mmengine - INFO - Epoch(train) [50][480/2119] lr: 4.0000e-02 eta: 20:23:22 time: 0.3670 data_time: 0.0264 memory: 5826 grad_norm: 3.1029 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6208 loss: 2.6208 2022/10/07 17:45:38 - mmengine - INFO - Epoch(train) [50][500/2119] lr: 4.0000e-02 eta: 20:23:15 time: 0.3252 data_time: 0.0187 memory: 5826 grad_norm: 3.0938 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.6131 loss: 2.6131 2022/10/07 17:45:45 - mmengine - INFO - Epoch(train) [50][520/2119] lr: 4.0000e-02 eta: 20:23:08 time: 0.3505 data_time: 0.0202 memory: 5826 grad_norm: 3.1623 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7532 loss: 2.7532 2022/10/07 17:45:52 - mmengine - INFO - Epoch(train) [50][540/2119] lr: 4.0000e-02 eta: 20:23:00 time: 0.3201 data_time: 0.0225 memory: 5826 grad_norm: 3.1116 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.6876 loss: 2.6876 2022/10/07 17:46:00 - mmengine - INFO - Epoch(train) [50][560/2119] lr: 4.0000e-02 eta: 20:22:56 time: 0.4108 data_time: 0.0318 memory: 5826 grad_norm: 3.1039 top1_acc: 0.1250 top5_acc: 0.6875 loss_cls: 2.9100 loss: 2.9100 2022/10/07 17:46:06 - mmengine - INFO - Epoch(train) [50][580/2119] lr: 4.0000e-02 eta: 20:22:48 time: 0.3138 data_time: 0.0233 memory: 5826 grad_norm: 3.0914 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8919 loss: 2.8919 2022/10/07 17:46:17 - mmengine - INFO - Epoch(train) [50][600/2119] lr: 4.0000e-02 eta: 20:22:48 time: 0.5054 data_time: 0.0612 memory: 5826 grad_norm: 3.1516 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6385 loss: 2.6385 2022/10/07 17:46:24 - mmengine - INFO - Epoch(train) [50][620/2119] lr: 4.0000e-02 eta: 20:22:42 time: 0.3790 data_time: 0.0375 memory: 5826 grad_norm: 3.1004 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.5882 loss: 2.5882 2022/10/07 17:46:32 - mmengine - INFO - Epoch(train) [50][640/2119] lr: 4.0000e-02 eta: 20:22:37 time: 0.3746 data_time: 0.0182 memory: 5826 grad_norm: 3.0558 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8464 loss: 2.8464 2022/10/07 17:46:47 - mmengine - INFO - Epoch(train) [50][660/2119] lr: 4.0000e-02 eta: 20:22:46 time: 0.7512 data_time: 0.0196 memory: 5826 grad_norm: 3.0645 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7492 loss: 2.7492 2022/10/07 17:47:38 - mmengine - INFO - Epoch(train) [50][680/2119] lr: 4.0000e-02 eta: 20:24:09 time: 2.5380 data_time: 0.1873 memory: 5826 grad_norm: 3.0845 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7237 loss: 2.7237 2022/10/07 17:47:43 - mmengine - INFO - Epoch(train) [50][700/2119] lr: 4.0000e-02 eta: 20:24:00 time: 0.2917 data_time: 0.0674 memory: 5826 grad_norm: 3.1305 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6458 loss: 2.6458 2022/10/07 17:48:08 - mmengine - INFO - Epoch(train) [50][720/2119] lr: 4.0000e-02 eta: 20:24:29 time: 1.2122 data_time: 0.0405 memory: 5826 grad_norm: 3.0692 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.8309 loss: 2.8309 2022/10/07 17:48:14 - mmengine - INFO - Epoch(train) [50][740/2119] lr: 4.0000e-02 eta: 20:24:21 time: 0.3299 data_time: 0.0495 memory: 5826 grad_norm: 3.0724 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8553 loss: 2.8553 2022/10/07 17:48:21 - mmengine - INFO - Epoch(train) [50][760/2119] lr: 4.0000e-02 eta: 20:24:14 time: 0.3499 data_time: 0.0220 memory: 5826 grad_norm: 3.0950 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6469 loss: 2.6469 2022/10/07 17:48:27 - mmengine - INFO - Epoch(train) [50][780/2119] lr: 4.0000e-02 eta: 20:24:06 time: 0.3036 data_time: 0.0247 memory: 5826 grad_norm: 3.0794 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9168 loss: 2.9168 2022/10/07 17:48:47 - mmengine - INFO - Epoch(train) [50][800/2119] lr: 4.0000e-02 eta: 20:24:25 time: 0.9835 data_time: 0.0335 memory: 5826 grad_norm: 3.0721 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 3.0838 loss: 3.0838 2022/10/07 17:48:53 - mmengine - INFO - Epoch(train) [50][820/2119] lr: 4.0000e-02 eta: 20:24:17 time: 0.3114 data_time: 0.0494 memory: 5826 grad_norm: 3.0961 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7581 loss: 2.7581 2022/10/07 17:49:01 - mmengine - INFO - Epoch(train) [50][840/2119] lr: 4.0000e-02 eta: 20:24:12 time: 0.3986 data_time: 0.0196 memory: 5826 grad_norm: 3.0914 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8535 loss: 2.8535 2022/10/07 17:49:08 - mmengine - INFO - Epoch(train) [50][860/2119] lr: 4.0000e-02 eta: 20:24:05 time: 0.3488 data_time: 0.0225 memory: 5826 grad_norm: 3.0624 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7426 loss: 2.7426 2022/10/07 17:49:16 - mmengine - INFO - Epoch(train) [50][880/2119] lr: 4.0000e-02 eta: 20:24:02 time: 0.4199 data_time: 0.0215 memory: 5826 grad_norm: 3.0369 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7838 loss: 2.7838 2022/10/07 17:49:54 - mmengine - INFO - Epoch(train) [50][900/2119] lr: 4.0000e-02 eta: 20:24:57 time: 1.8650 data_time: 0.2158 memory: 5826 grad_norm: 3.1099 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8889 loss: 2.8889 2022/10/07 17:50:00 - mmengine - INFO - Epoch(train) [50][920/2119] lr: 4.0000e-02 eta: 20:24:48 time: 0.3162 data_time: 0.0470 memory: 5826 grad_norm: 3.0278 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7566 loss: 2.7566 2022/10/07 17:50:07 - mmengine - INFO - Epoch(train) [50][940/2119] lr: 4.0000e-02 eta: 20:24:41 time: 0.3294 data_time: 0.0263 memory: 5826 grad_norm: 3.0976 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6261 loss: 2.6261 2022/10/07 17:50:15 - mmengine - INFO - Epoch(train) [50][960/2119] lr: 4.0000e-02 eta: 20:24:37 time: 0.4151 data_time: 0.0286 memory: 5826 grad_norm: 3.1350 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6601 loss: 2.6601 2022/10/07 17:50:21 - mmengine - INFO - Epoch(train) [50][980/2119] lr: 4.0000e-02 eta: 20:24:29 time: 0.3263 data_time: 0.0314 memory: 5826 grad_norm: 3.0843 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.7292 loss: 2.7292 2022/10/07 17:50:33 - mmengine - INFO - Epoch(train) [50][1000/2119] lr: 4.0000e-02 eta: 20:24:32 time: 0.5835 data_time: 0.0262 memory: 5826 grad_norm: 3.0737 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7278 loss: 2.7278 2022/10/07 17:50:38 - mmengine - INFO - Epoch(train) [50][1020/2119] lr: 4.0000e-02 eta: 20:24:22 time: 0.2599 data_time: 0.0260 memory: 5826 grad_norm: 3.1255 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6747 loss: 2.6747 2022/10/07 17:50:45 - mmengine - INFO - Epoch(train) [50][1040/2119] lr: 4.0000e-02 eta: 20:24:14 time: 0.3277 data_time: 0.0351 memory: 5826 grad_norm: 3.1379 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0681 loss: 3.0681 2022/10/07 17:50:52 - mmengine - INFO - Epoch(train) [50][1060/2119] lr: 4.0000e-02 eta: 20:24:08 time: 0.3538 data_time: 0.0183 memory: 5826 grad_norm: 3.0835 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6945 loss: 2.6945 2022/10/07 17:50:59 - mmengine - INFO - Epoch(train) [50][1080/2119] lr: 4.0000e-02 eta: 20:24:00 time: 0.3389 data_time: 0.0266 memory: 5826 grad_norm: 3.0902 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7242 loss: 2.7242 2022/10/07 17:51:06 - mmengine - INFO - Epoch(train) [50][1100/2119] lr: 4.0000e-02 eta: 20:23:55 time: 0.3686 data_time: 0.0200 memory: 5826 grad_norm: 3.0756 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8882 loss: 2.8882 2022/10/07 17:51:12 - mmengine - INFO - Epoch(train) [50][1120/2119] lr: 4.0000e-02 eta: 20:23:47 time: 0.3206 data_time: 0.0220 memory: 5826 grad_norm: 3.0844 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6238 loss: 2.6238 2022/10/07 17:51:20 - mmengine - INFO - Epoch(train) [50][1140/2119] lr: 4.0000e-02 eta: 20:23:40 time: 0.3540 data_time: 0.0226 memory: 5826 grad_norm: 3.0970 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7880 loss: 2.7880 2022/10/07 17:51:26 - mmengine - INFO - Epoch(train) [50][1160/2119] lr: 4.0000e-02 eta: 20:23:32 time: 0.3082 data_time: 0.0255 memory: 5826 grad_norm: 3.0963 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8668 loss: 2.8668 2022/10/07 17:51:29 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 17:51:33 - mmengine - INFO - Epoch(train) [50][1180/2119] lr: 4.0000e-02 eta: 20:23:25 time: 0.3472 data_time: 0.0151 memory: 5826 grad_norm: 3.1317 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6616 loss: 2.6616 2022/10/07 17:51:40 - mmengine - INFO - Epoch(train) [50][1200/2119] lr: 4.0000e-02 eta: 20:23:19 time: 0.3645 data_time: 0.0228 memory: 5826 grad_norm: 3.1717 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7098 loss: 2.7098 2022/10/07 17:51:46 - mmengine - INFO - Epoch(train) [50][1220/2119] lr: 4.0000e-02 eta: 20:23:11 time: 0.3207 data_time: 0.0259 memory: 5826 grad_norm: 3.0961 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6834 loss: 2.6834 2022/10/07 17:51:53 - mmengine - INFO - Epoch(train) [50][1240/2119] lr: 4.0000e-02 eta: 20:23:04 time: 0.3466 data_time: 0.0256 memory: 5826 grad_norm: 3.1238 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8843 loss: 2.8843 2022/10/07 17:52:00 - mmengine - INFO - Epoch(train) [50][1260/2119] lr: 4.0000e-02 eta: 20:22:57 time: 0.3424 data_time: 0.0249 memory: 5826 grad_norm: 3.1333 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.1030 loss: 3.1030 2022/10/07 17:52:07 - mmengine - INFO - Epoch(train) [50][1280/2119] lr: 4.0000e-02 eta: 20:22:49 time: 0.3190 data_time: 0.0175 memory: 5826 grad_norm: 3.1511 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8382 loss: 2.8382 2022/10/07 17:52:14 - mmengine - INFO - Epoch(train) [50][1300/2119] lr: 4.0000e-02 eta: 20:22:43 time: 0.3633 data_time: 0.0214 memory: 5826 grad_norm: 3.0286 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6678 loss: 2.6678 2022/10/07 17:52:20 - mmengine - INFO - Epoch(train) [50][1320/2119] lr: 4.0000e-02 eta: 20:22:35 time: 0.3265 data_time: 0.0273 memory: 5826 grad_norm: 3.1081 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8026 loss: 2.8026 2022/10/07 17:52:27 - mmengine - INFO - Epoch(train) [50][1340/2119] lr: 4.0000e-02 eta: 20:22:28 time: 0.3337 data_time: 0.0184 memory: 5826 grad_norm: 3.1254 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0522 loss: 3.0522 2022/10/07 17:52:34 - mmengine - INFO - Epoch(train) [50][1360/2119] lr: 4.0000e-02 eta: 20:22:22 time: 0.3587 data_time: 0.0175 memory: 5826 grad_norm: 3.1034 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5197 loss: 2.5197 2022/10/07 17:52:40 - mmengine - INFO - Epoch(train) [50][1380/2119] lr: 4.0000e-02 eta: 20:22:13 time: 0.3047 data_time: 0.0215 memory: 5826 grad_norm: 3.1003 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0177 loss: 3.0177 2022/10/07 17:52:47 - mmengine - INFO - Epoch(train) [50][1400/2119] lr: 4.0000e-02 eta: 20:22:05 time: 0.3211 data_time: 0.0210 memory: 5826 grad_norm: 3.0478 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8119 loss: 2.8119 2022/10/07 17:52:54 - mmengine - INFO - Epoch(train) [50][1420/2119] lr: 4.0000e-02 eta: 20:21:59 time: 0.3508 data_time: 0.0244 memory: 5826 grad_norm: 3.0802 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.8202 loss: 2.8202 2022/10/07 17:53:01 - mmengine - INFO - Epoch(train) [50][1440/2119] lr: 4.0000e-02 eta: 20:21:52 time: 0.3482 data_time: 0.0243 memory: 5826 grad_norm: 3.0663 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7007 loss: 2.7007 2022/10/07 17:53:07 - mmengine - INFO - Epoch(train) [50][1460/2119] lr: 4.0000e-02 eta: 20:21:44 time: 0.3317 data_time: 0.0202 memory: 5826 grad_norm: 3.1005 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7274 loss: 2.7274 2022/10/07 17:53:14 - mmengine - INFO - Epoch(train) [50][1480/2119] lr: 4.0000e-02 eta: 20:21:38 time: 0.3508 data_time: 0.0206 memory: 5826 grad_norm: 3.0472 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7515 loss: 2.7515 2022/10/07 17:53:22 - mmengine - INFO - Epoch(train) [50][1500/2119] lr: 4.0000e-02 eta: 20:21:32 time: 0.3714 data_time: 0.0220 memory: 5826 grad_norm: 3.1537 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5828 loss: 2.5828 2022/10/07 17:53:29 - mmengine - INFO - Epoch(train) [50][1520/2119] lr: 4.0000e-02 eta: 20:21:26 time: 0.3684 data_time: 0.0230 memory: 5826 grad_norm: 3.1020 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5568 loss: 2.5568 2022/10/07 17:53:36 - mmengine - INFO - Epoch(train) [50][1540/2119] lr: 4.0000e-02 eta: 20:21:19 time: 0.3308 data_time: 0.0218 memory: 5826 grad_norm: 3.1045 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6499 loss: 2.6499 2022/10/07 17:53:45 - mmengine - INFO - Epoch(train) [50][1560/2119] lr: 4.0000e-02 eta: 20:21:16 time: 0.4489 data_time: 0.0171 memory: 5826 grad_norm: 3.0802 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5798 loss: 2.5798 2022/10/07 17:53:51 - mmengine - INFO - Epoch(train) [50][1580/2119] lr: 4.0000e-02 eta: 20:21:07 time: 0.2976 data_time: 0.0252 memory: 5826 grad_norm: 3.1269 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7376 loss: 2.7376 2022/10/07 17:53:58 - mmengine - INFO - Epoch(train) [50][1600/2119] lr: 4.0000e-02 eta: 20:21:01 time: 0.3581 data_time: 0.0321 memory: 5826 grad_norm: 3.1068 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9627 loss: 2.9627 2022/10/07 17:54:05 - mmengine - INFO - Epoch(train) [50][1620/2119] lr: 4.0000e-02 eta: 20:20:53 time: 0.3368 data_time: 0.0157 memory: 5826 grad_norm: 3.0193 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6935 loss: 2.6935 2022/10/07 17:54:12 - mmengine - INFO - Epoch(train) [50][1640/2119] lr: 4.0000e-02 eta: 20:20:47 time: 0.3485 data_time: 0.0210 memory: 5826 grad_norm: 3.0583 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9731 loss: 2.9731 2022/10/07 17:54:18 - mmengine - INFO - Epoch(train) [50][1660/2119] lr: 4.0000e-02 eta: 20:20:40 time: 0.3410 data_time: 0.0225 memory: 5826 grad_norm: 3.0677 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6471 loss: 2.6471 2022/10/07 17:54:25 - mmengine - INFO - Epoch(train) [50][1680/2119] lr: 4.0000e-02 eta: 20:20:32 time: 0.3383 data_time: 0.0212 memory: 5826 grad_norm: 3.1154 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5311 loss: 2.5311 2022/10/07 17:54:32 - mmengine - INFO - Epoch(train) [50][1700/2119] lr: 4.0000e-02 eta: 20:20:25 time: 0.3280 data_time: 0.0214 memory: 5826 grad_norm: 3.0917 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7792 loss: 2.7792 2022/10/07 17:54:39 - mmengine - INFO - Epoch(train) [50][1720/2119] lr: 4.0000e-02 eta: 20:20:19 time: 0.3578 data_time: 0.0213 memory: 5826 grad_norm: 3.1311 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7895 loss: 2.7895 2022/10/07 17:54:46 - mmengine - INFO - Epoch(train) [50][1740/2119] lr: 4.0000e-02 eta: 20:20:11 time: 0.3390 data_time: 0.0230 memory: 5826 grad_norm: 3.0527 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9667 loss: 2.9667 2022/10/07 17:54:53 - mmengine - INFO - Epoch(train) [50][1760/2119] lr: 4.0000e-02 eta: 20:20:06 time: 0.3823 data_time: 0.0208 memory: 5826 grad_norm: 3.0951 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6954 loss: 2.6954 2022/10/07 17:54:59 - mmengine - INFO - Epoch(train) [50][1780/2119] lr: 4.0000e-02 eta: 20:19:57 time: 0.3024 data_time: 0.0221 memory: 5826 grad_norm: 3.0842 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.7327 loss: 2.7327 2022/10/07 17:55:07 - mmengine - INFO - Epoch(train) [50][1800/2119] lr: 4.0000e-02 eta: 20:19:52 time: 0.3869 data_time: 0.0213 memory: 5826 grad_norm: 3.0905 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0538 loss: 3.0538 2022/10/07 17:55:14 - mmengine - INFO - Epoch(train) [50][1820/2119] lr: 4.0000e-02 eta: 20:19:45 time: 0.3297 data_time: 0.0188 memory: 5826 grad_norm: 3.0879 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5299 loss: 2.5299 2022/10/07 17:55:22 - mmengine - INFO - Epoch(train) [50][1840/2119] lr: 4.0000e-02 eta: 20:19:40 time: 0.3921 data_time: 0.0229 memory: 5826 grad_norm: 3.1150 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6964 loss: 2.6964 2022/10/07 17:55:28 - mmengine - INFO - Epoch(train) [50][1860/2119] lr: 4.0000e-02 eta: 20:19:32 time: 0.3190 data_time: 0.0261 memory: 5826 grad_norm: 3.0932 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.9521 loss: 2.9521 2022/10/07 17:55:36 - mmengine - INFO - Epoch(train) [50][1880/2119] lr: 4.0000e-02 eta: 20:19:27 time: 0.4086 data_time: 0.0232 memory: 5826 grad_norm: 3.0462 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5610 loss: 2.5610 2022/10/07 17:55:43 - mmengine - INFO - Epoch(train) [50][1900/2119] lr: 4.0000e-02 eta: 20:19:20 time: 0.3400 data_time: 0.0184 memory: 5826 grad_norm: 3.1085 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6121 loss: 2.6121 2022/10/07 17:55:50 - mmengine - INFO - Epoch(train) [50][1920/2119] lr: 4.0000e-02 eta: 20:19:14 time: 0.3613 data_time: 0.0227 memory: 5826 grad_norm: 3.1106 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8996 loss: 2.8996 2022/10/07 17:55:56 - mmengine - INFO - Epoch(train) [50][1940/2119] lr: 4.0000e-02 eta: 20:19:05 time: 0.2941 data_time: 0.0200 memory: 5826 grad_norm: 3.1151 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5810 loss: 2.5810 2022/10/07 17:56:03 - mmengine - INFO - Epoch(train) [50][1960/2119] lr: 4.0000e-02 eta: 20:18:58 time: 0.3474 data_time: 0.0189 memory: 5826 grad_norm: 3.0968 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8515 loss: 2.8515 2022/10/07 17:56:10 - mmengine - INFO - Epoch(train) [50][1980/2119] lr: 4.0000e-02 eta: 20:18:51 time: 0.3421 data_time: 0.0203 memory: 5826 grad_norm: 3.0590 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8043 loss: 2.8043 2022/10/07 17:56:17 - mmengine - INFO - Epoch(train) [50][2000/2119] lr: 4.0000e-02 eta: 20:18:45 time: 0.3509 data_time: 0.0264 memory: 5826 grad_norm: 3.0369 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6499 loss: 2.6499 2022/10/07 17:56:24 - mmengine - INFO - Epoch(train) [50][2020/2119] lr: 4.0000e-02 eta: 20:18:38 time: 0.3439 data_time: 0.0175 memory: 5826 grad_norm: 3.0565 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 3.0465 loss: 3.0465 2022/10/07 17:56:31 - mmengine - INFO - Epoch(train) [50][2040/2119] lr: 4.0000e-02 eta: 20:18:31 time: 0.3499 data_time: 0.0198 memory: 5826 grad_norm: 3.1369 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9546 loss: 2.9546 2022/10/07 17:56:38 - mmengine - INFO - Epoch(train) [50][2060/2119] lr: 4.0000e-02 eta: 20:18:24 time: 0.3534 data_time: 0.0237 memory: 5826 grad_norm: 3.0878 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8989 loss: 2.8989 2022/10/07 17:56:45 - mmengine - INFO - Epoch(train) [50][2080/2119] lr: 4.0000e-02 eta: 20:18:18 time: 0.3502 data_time: 0.0211 memory: 5826 grad_norm: 3.0549 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6816 loss: 2.6816 2022/10/07 17:56:51 - mmengine - INFO - Epoch(train) [50][2100/2119] lr: 4.0000e-02 eta: 20:18:10 time: 0.3186 data_time: 0.0183 memory: 5826 grad_norm: 3.0897 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9167 loss: 2.9167 2022/10/07 17:56:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 17:56:56 - mmengine - INFO - Epoch(train) [50][2119/2119] lr: 4.0000e-02 eta: 20:18:10 time: 0.2689 data_time: 0.0217 memory: 5826 grad_norm: 3.1897 top1_acc: 0.3000 top5_acc: 0.7000 loss_cls: 2.6724 loss: 2.6724 2022/10/07 17:57:05 - mmengine - INFO - Epoch(val) [50][20/137] eta: 0:00:50 time: 0.4305 data_time: 0.3625 memory: 1241 2022/10/07 17:57:11 - mmengine - INFO - Epoch(val) [50][40/137] eta: 0:00:27 time: 0.2813 data_time: 0.2103 memory: 1241 2022/10/07 17:57:17 - mmengine - INFO - Epoch(val) [50][60/137] eta: 0:00:26 time: 0.3393 data_time: 0.2738 memory: 1241 2022/10/07 17:57:23 - mmengine - INFO - Epoch(val) [50][80/137] eta: 0:00:16 time: 0.2946 data_time: 0.2281 memory: 1241 2022/10/07 17:57:31 - mmengine - INFO - Epoch(val) [50][100/137] eta: 0:00:13 time: 0.3590 data_time: 0.2933 memory: 1241 2022/10/07 17:57:35 - mmengine - INFO - Epoch(val) [50][120/137] eta: 0:00:04 time: 0.2469 data_time: 0.1794 memory: 1241 2022/10/07 17:57:47 - mmengine - INFO - Epoch(val) [50][137/137] acc/top1: 0.4204 acc/top5: 0.6637 acc/mean1: 0.4204 2022/10/07 17:57:56 - mmengine - INFO - Epoch(train) [51][20/2119] lr: 4.0000e-02 eta: 20:17:48 time: 0.4629 data_time: 0.1255 memory: 5826 grad_norm: 3.1275 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7845 loss: 2.7845 2022/10/07 17:58:04 - mmengine - INFO - Epoch(train) [51][40/2119] lr: 4.0000e-02 eta: 20:17:42 time: 0.3752 data_time: 0.0228 memory: 5826 grad_norm: 3.1434 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6156 loss: 2.6156 2022/10/07 17:58:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 17:58:11 - mmengine - INFO - Epoch(train) [51][60/2119] lr: 4.0000e-02 eta: 20:17:37 time: 0.3760 data_time: 0.0220 memory: 5826 grad_norm: 3.1052 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.7007 loss: 2.7007 2022/10/07 17:58:18 - mmengine - INFO - Epoch(train) [51][80/2119] lr: 4.0000e-02 eta: 20:17:29 time: 0.3348 data_time: 0.0165 memory: 5826 grad_norm: 3.0427 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6840 loss: 2.6840 2022/10/07 17:58:25 - mmengine - INFO - Epoch(train) [51][100/2119] lr: 4.0000e-02 eta: 20:17:22 time: 0.3264 data_time: 0.0259 memory: 5826 grad_norm: 3.0829 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5193 loss: 2.5193 2022/10/07 17:58:32 - mmengine - INFO - Epoch(train) [51][120/2119] lr: 4.0000e-02 eta: 20:17:15 time: 0.3471 data_time: 0.0208 memory: 5826 grad_norm: 3.1320 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8294 loss: 2.8294 2022/10/07 17:58:39 - mmengine - INFO - Epoch(train) [51][140/2119] lr: 4.0000e-02 eta: 20:17:09 time: 0.3714 data_time: 0.0234 memory: 5826 grad_norm: 3.1008 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8677 loss: 2.8677 2022/10/07 17:58:45 - mmengine - INFO - Epoch(train) [51][160/2119] lr: 4.0000e-02 eta: 20:17:01 time: 0.3109 data_time: 0.0207 memory: 5826 grad_norm: 3.1122 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7405 loss: 2.7405 2022/10/07 17:58:53 - mmengine - INFO - Epoch(train) [51][180/2119] lr: 4.0000e-02 eta: 20:16:54 time: 0.3523 data_time: 0.0216 memory: 5826 grad_norm: 3.1389 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8468 loss: 2.8468 2022/10/07 17:59:00 - mmengine - INFO - Epoch(train) [51][200/2119] lr: 4.0000e-02 eta: 20:16:49 time: 0.3948 data_time: 0.0292 memory: 5826 grad_norm: 3.1460 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6313 loss: 2.6313 2022/10/07 17:59:07 - mmengine - INFO - Epoch(train) [51][220/2119] lr: 4.0000e-02 eta: 20:16:41 time: 0.3128 data_time: 0.0253 memory: 5826 grad_norm: 3.1186 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8688 loss: 2.8688 2022/10/07 17:59:14 - mmengine - INFO - Epoch(train) [51][240/2119] lr: 4.0000e-02 eta: 20:16:35 time: 0.3732 data_time: 0.0779 memory: 5826 grad_norm: 3.1155 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6266 loss: 2.6266 2022/10/07 17:59:20 - mmengine - INFO - Epoch(train) [51][260/2119] lr: 4.0000e-02 eta: 20:16:26 time: 0.2906 data_time: 0.0311 memory: 5826 grad_norm: 3.1246 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7677 loss: 2.7677 2022/10/07 17:59:27 - mmengine - INFO - Epoch(train) [51][280/2119] lr: 4.0000e-02 eta: 20:16:20 time: 0.3548 data_time: 0.0238 memory: 5826 grad_norm: 3.1411 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0228 loss: 3.0228 2022/10/07 17:59:35 - mmengine - INFO - Epoch(train) [51][300/2119] lr: 4.0000e-02 eta: 20:16:15 time: 0.3890 data_time: 0.0273 memory: 5826 grad_norm: 3.1150 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6058 loss: 2.6058 2022/10/07 17:59:42 - mmengine - INFO - Epoch(train) [51][320/2119] lr: 4.0000e-02 eta: 20:16:09 time: 0.3717 data_time: 0.0206 memory: 5826 grad_norm: 3.1213 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7325 loss: 2.7325 2022/10/07 17:59:58 - mmengine - INFO - Epoch(train) [51][340/2119] lr: 4.0000e-02 eta: 20:16:19 time: 0.7667 data_time: 0.0557 memory: 5826 grad_norm: 3.0565 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.5736 loss: 2.5736 2022/10/07 18:01:08 - mmengine - INFO - Epoch(train) [51][360/2119] lr: 4.0000e-02 eta: 20:18:18 time: 3.5271 data_time: 0.2441 memory: 5826 grad_norm: 3.0784 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9420 loss: 2.9420 2022/10/07 18:01:13 - mmengine - INFO - Epoch(train) [51][380/2119] lr: 4.0000e-02 eta: 20:18:09 time: 0.2713 data_time: 0.0362 memory: 5826 grad_norm: 3.1258 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7409 loss: 2.7409 2022/10/07 18:01:24 - mmengine - INFO - Epoch(train) [51][400/2119] lr: 4.0000e-02 eta: 20:18:09 time: 0.5265 data_time: 0.0269 memory: 5826 grad_norm: 3.1606 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7829 loss: 2.7829 2022/10/07 18:01:29 - mmengine - INFO - Epoch(train) [51][420/2119] lr: 4.0000e-02 eta: 20:17:58 time: 0.2434 data_time: 0.0201 memory: 5826 grad_norm: 3.0977 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.9044 loss: 2.9044 2022/10/07 18:01:36 - mmengine - INFO - Epoch(train) [51][440/2119] lr: 4.0000e-02 eta: 20:17:51 time: 0.3424 data_time: 0.0266 memory: 5826 grad_norm: 3.0658 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8104 loss: 2.8104 2022/10/07 18:02:32 - mmengine - INFO - Epoch(train) [51][460/2119] lr: 4.0000e-02 eta: 20:19:19 time: 2.7239 data_time: 0.0868 memory: 5826 grad_norm: 3.0276 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8270 loss: 2.8270 2022/10/07 18:02:45 - mmengine - INFO - Epoch(train) [51][480/2119] lr: 4.0000e-02 eta: 20:19:28 time: 0.7494 data_time: 0.2190 memory: 5826 grad_norm: 3.0532 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5543 loss: 2.5543 2022/10/07 18:02:51 - mmengine - INFO - Epoch(train) [51][500/2119] lr: 4.0000e-02 eta: 20:19:19 time: 0.2921 data_time: 0.0359 memory: 5826 grad_norm: 3.1262 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5894 loss: 2.5894 2022/10/07 18:02:57 - mmengine - INFO - Epoch(train) [51][520/2119] lr: 4.0000e-02 eta: 20:19:09 time: 0.2812 data_time: 0.0300 memory: 5826 grad_norm: 3.1560 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7648 loss: 2.7648 2022/10/07 18:03:04 - mmengine - INFO - Epoch(train) [51][540/2119] lr: 4.0000e-02 eta: 20:19:03 time: 0.3715 data_time: 0.0183 memory: 5826 grad_norm: 3.0780 top1_acc: 0.2500 top5_acc: 0.3125 loss_cls: 2.8976 loss: 2.8976 2022/10/07 18:03:12 - mmengine - INFO - Epoch(train) [51][560/2119] lr: 4.0000e-02 eta: 20:18:58 time: 0.3944 data_time: 0.0366 memory: 5826 grad_norm: 3.1336 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6160 loss: 2.6160 2022/10/07 18:03:18 - mmengine - INFO - Epoch(train) [51][580/2119] lr: 4.0000e-02 eta: 20:18:50 time: 0.3060 data_time: 0.0229 memory: 5826 grad_norm: 3.1115 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4805 loss: 2.4805 2022/10/07 18:03:26 - mmengine - INFO - Epoch(train) [51][600/2119] lr: 4.0000e-02 eta: 20:18:44 time: 0.3784 data_time: 0.0225 memory: 5826 grad_norm: 3.0855 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6214 loss: 2.6214 2022/10/07 18:03:34 - mmengine - INFO - Epoch(train) [51][620/2119] lr: 4.0000e-02 eta: 20:18:39 time: 0.3926 data_time: 0.0315 memory: 5826 grad_norm: 3.1122 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8352 loss: 2.8352 2022/10/07 18:03:39 - mmengine - INFO - Epoch(train) [51][640/2119] lr: 4.0000e-02 eta: 20:18:29 time: 0.2769 data_time: 0.0244 memory: 5826 grad_norm: 3.1075 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7372 loss: 2.7372 2022/10/07 18:03:46 - mmengine - INFO - Epoch(train) [51][660/2119] lr: 4.0000e-02 eta: 20:18:22 time: 0.3504 data_time: 0.0213 memory: 5826 grad_norm: 3.1267 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6960 loss: 2.6960 2022/10/07 18:03:53 - mmengine - INFO - Epoch(train) [51][680/2119] lr: 4.0000e-02 eta: 20:18:16 time: 0.3535 data_time: 0.0396 memory: 5826 grad_norm: 3.1337 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7519 loss: 2.7519 2022/10/07 18:04:01 - mmengine - INFO - Epoch(train) [51][700/2119] lr: 4.0000e-02 eta: 20:18:10 time: 0.3689 data_time: 0.0199 memory: 5826 grad_norm: 3.1024 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0037 loss: 3.0037 2022/10/07 18:04:07 - mmengine - INFO - Epoch(train) [51][720/2119] lr: 4.0000e-02 eta: 20:18:03 time: 0.3366 data_time: 0.0217 memory: 5826 grad_norm: 3.1050 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7728 loss: 2.7728 2022/10/07 18:04:14 - mmengine - INFO - Epoch(train) [51][740/2119] lr: 4.0000e-02 eta: 20:17:55 time: 0.3233 data_time: 0.0238 memory: 5826 grad_norm: 3.0540 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6009 loss: 2.6009 2022/10/07 18:04:22 - mmengine - INFO - Epoch(train) [51][760/2119] lr: 4.0000e-02 eta: 20:17:50 time: 0.3916 data_time: 0.0233 memory: 5826 grad_norm: 3.1498 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9138 loss: 2.9138 2022/10/07 18:04:28 - mmengine - INFO - Epoch(train) [51][780/2119] lr: 4.0000e-02 eta: 20:17:42 time: 0.3314 data_time: 0.0215 memory: 5826 grad_norm: 3.0759 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9202 loss: 2.9202 2022/10/07 18:04:35 - mmengine - INFO - Epoch(train) [51][800/2119] lr: 4.0000e-02 eta: 20:17:34 time: 0.3206 data_time: 0.0199 memory: 5826 grad_norm: 3.0403 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7988 loss: 2.7988 2022/10/07 18:04:42 - mmengine - INFO - Epoch(train) [51][820/2119] lr: 4.0000e-02 eta: 20:17:28 time: 0.3586 data_time: 0.0264 memory: 5826 grad_norm: 3.0167 top1_acc: 0.1875 top5_acc: 0.2500 loss_cls: 2.8443 loss: 2.8443 2022/10/07 18:04:49 - mmengine - INFO - Epoch(train) [51][840/2119] lr: 4.0000e-02 eta: 20:17:21 time: 0.3497 data_time: 0.0219 memory: 5826 grad_norm: 3.0925 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7266 loss: 2.7266 2022/10/07 18:04:55 - mmengine - INFO - Epoch(train) [51][860/2119] lr: 4.0000e-02 eta: 20:17:13 time: 0.3114 data_time: 0.0192 memory: 5826 grad_norm: 3.1055 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.9645 loss: 2.9645 2022/10/07 18:05:02 - mmengine - INFO - Epoch(train) [51][880/2119] lr: 4.0000e-02 eta: 20:17:06 time: 0.3565 data_time: 0.0249 memory: 5826 grad_norm: 3.1110 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8397 loss: 2.8397 2022/10/07 18:05:10 - mmengine - INFO - Epoch(train) [51][900/2119] lr: 4.0000e-02 eta: 20:17:00 time: 0.3728 data_time: 0.0220 memory: 5826 grad_norm: 3.0990 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8981 loss: 2.8981 2022/10/07 18:05:16 - mmengine - INFO - Epoch(train) [51][920/2119] lr: 4.0000e-02 eta: 20:16:53 time: 0.3269 data_time: 0.0238 memory: 5826 grad_norm: 3.1281 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6319 loss: 2.6319 2022/10/07 18:05:23 - mmengine - INFO - Epoch(train) [51][940/2119] lr: 4.0000e-02 eta: 20:16:46 time: 0.3637 data_time: 0.0235 memory: 5826 grad_norm: 3.0965 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6287 loss: 2.6287 2022/10/07 18:05:31 - mmengine - INFO - Epoch(train) [51][960/2119] lr: 4.0000e-02 eta: 20:16:40 time: 0.3566 data_time: 0.0230 memory: 5826 grad_norm: 3.0913 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8740 loss: 2.8740 2022/10/07 18:05:37 - mmengine - INFO - Epoch(train) [51][980/2119] lr: 4.0000e-02 eta: 20:16:32 time: 0.3314 data_time: 0.0263 memory: 5826 grad_norm: 3.0993 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5447 loss: 2.5447 2022/10/07 18:05:44 - mmengine - INFO - Epoch(train) [51][1000/2119] lr: 4.0000e-02 eta: 20:16:24 time: 0.3172 data_time: 0.0202 memory: 5826 grad_norm: 3.1551 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6692 loss: 2.6692 2022/10/07 18:05:51 - mmengine - INFO - Epoch(train) [51][1020/2119] lr: 4.0000e-02 eta: 20:16:18 time: 0.3572 data_time: 0.0234 memory: 5826 grad_norm: 3.0708 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8147 loss: 2.8147 2022/10/07 18:05:58 - mmengine - INFO - Epoch(train) [51][1040/2119] lr: 4.0000e-02 eta: 20:16:12 time: 0.3639 data_time: 0.0221 memory: 5826 grad_norm: 3.0238 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8541 loss: 2.8541 2022/10/07 18:06:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 18:06:05 - mmengine - INFO - Epoch(train) [51][1060/2119] lr: 4.0000e-02 eta: 20:16:05 time: 0.3552 data_time: 0.0238 memory: 5826 grad_norm: 3.1098 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5704 loss: 2.5704 2022/10/07 18:06:11 - mmengine - INFO - Epoch(train) [51][1080/2119] lr: 4.0000e-02 eta: 20:15:57 time: 0.3182 data_time: 0.0269 memory: 5826 grad_norm: 3.1085 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6695 loss: 2.6695 2022/10/07 18:06:18 - mmengine - INFO - Epoch(train) [51][1100/2119] lr: 4.0000e-02 eta: 20:15:49 time: 0.3213 data_time: 0.0235 memory: 5826 grad_norm: 3.1041 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.9932 loss: 2.9932 2022/10/07 18:06:26 - mmengine - INFO - Epoch(train) [51][1120/2119] lr: 4.0000e-02 eta: 20:15:44 time: 0.3930 data_time: 0.0235 memory: 5826 grad_norm: 3.0524 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4948 loss: 2.4948 2022/10/07 18:06:32 - mmengine - INFO - Epoch(train) [51][1140/2119] lr: 4.0000e-02 eta: 20:15:36 time: 0.3229 data_time: 0.0251 memory: 5826 grad_norm: 3.0643 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9281 loss: 2.9281 2022/10/07 18:06:39 - mmengine - INFO - Epoch(train) [51][1160/2119] lr: 4.0000e-02 eta: 20:15:29 time: 0.3316 data_time: 0.0218 memory: 5826 grad_norm: 3.1107 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6643 loss: 2.6643 2022/10/07 18:06:47 - mmengine - INFO - Epoch(train) [51][1180/2119] lr: 4.0000e-02 eta: 20:15:24 time: 0.3887 data_time: 0.0245 memory: 5826 grad_norm: 3.0194 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8272 loss: 2.8272 2022/10/07 18:06:52 - mmengine - INFO - Epoch(train) [51][1200/2119] lr: 4.0000e-02 eta: 20:15:14 time: 0.2922 data_time: 0.0201 memory: 5826 grad_norm: 3.1371 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7325 loss: 2.7325 2022/10/07 18:07:00 - mmengine - INFO - Epoch(train) [51][1220/2119] lr: 4.0000e-02 eta: 20:15:09 time: 0.3855 data_time: 0.0234 memory: 5826 grad_norm: 3.0674 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6975 loss: 2.6975 2022/10/07 18:07:07 - mmengine - INFO - Epoch(train) [51][1240/2119] lr: 4.0000e-02 eta: 20:15:02 time: 0.3308 data_time: 0.0223 memory: 5826 grad_norm: 3.1057 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6626 loss: 2.6626 2022/10/07 18:07:13 - mmengine - INFO - Epoch(train) [51][1260/2119] lr: 4.0000e-02 eta: 20:14:54 time: 0.3172 data_time: 0.0231 memory: 5826 grad_norm: 3.1323 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8366 loss: 2.8366 2022/10/07 18:07:21 - mmengine - INFO - Epoch(train) [51][1280/2119] lr: 4.0000e-02 eta: 20:14:48 time: 0.3826 data_time: 0.0249 memory: 5826 grad_norm: 3.0606 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.8535 loss: 2.8535 2022/10/07 18:07:27 - mmengine - INFO - Epoch(train) [51][1300/2119] lr: 4.0000e-02 eta: 20:14:40 time: 0.3284 data_time: 0.0257 memory: 5826 grad_norm: 3.1236 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6795 loss: 2.6795 2022/10/07 18:07:34 - mmengine - INFO - Epoch(train) [51][1320/2119] lr: 4.0000e-02 eta: 20:14:33 time: 0.3353 data_time: 0.0182 memory: 5826 grad_norm: 3.0995 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.7225 loss: 2.7225 2022/10/07 18:07:41 - mmengine - INFO - Epoch(train) [51][1340/2119] lr: 4.0000e-02 eta: 20:14:27 time: 0.3697 data_time: 0.0235 memory: 5826 grad_norm: 3.0865 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.7292 loss: 2.7292 2022/10/07 18:07:47 - mmengine - INFO - Epoch(train) [51][1360/2119] lr: 4.0000e-02 eta: 20:14:18 time: 0.2848 data_time: 0.0247 memory: 5826 grad_norm: 3.0593 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6426 loss: 2.6426 2022/10/07 18:07:55 - mmengine - INFO - Epoch(train) [51][1380/2119] lr: 4.0000e-02 eta: 20:14:12 time: 0.3698 data_time: 0.0210 memory: 5826 grad_norm: 3.0915 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6927 loss: 2.6927 2022/10/07 18:08:01 - mmengine - INFO - Epoch(train) [51][1400/2119] lr: 4.0000e-02 eta: 20:14:05 time: 0.3412 data_time: 0.0187 memory: 5826 grad_norm: 3.0891 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7910 loss: 2.7910 2022/10/07 18:08:08 - mmengine - INFO - Epoch(train) [51][1420/2119] lr: 4.0000e-02 eta: 20:13:58 time: 0.3462 data_time: 0.0217 memory: 5826 grad_norm: 3.0772 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9465 loss: 2.9465 2022/10/07 18:08:15 - mmengine - INFO - Epoch(train) [51][1440/2119] lr: 4.0000e-02 eta: 20:13:51 time: 0.3496 data_time: 0.0244 memory: 5826 grad_norm: 3.0890 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8373 loss: 2.8373 2022/10/07 18:08:22 - mmengine - INFO - Epoch(train) [51][1460/2119] lr: 4.0000e-02 eta: 20:13:44 time: 0.3508 data_time: 0.0252 memory: 5826 grad_norm: 3.0742 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5889 loss: 2.5889 2022/10/07 18:08:29 - mmengine - INFO - Epoch(train) [51][1480/2119] lr: 4.0000e-02 eta: 20:13:36 time: 0.3233 data_time: 0.0179 memory: 5826 grad_norm: 3.1043 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8626 loss: 2.8626 2022/10/07 18:08:36 - mmengine - INFO - Epoch(train) [51][1500/2119] lr: 4.0000e-02 eta: 20:13:29 time: 0.3436 data_time: 0.0240 memory: 5826 grad_norm: 3.0729 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9102 loss: 2.9102 2022/10/07 18:08:43 - mmengine - INFO - Epoch(train) [51][1520/2119] lr: 4.0000e-02 eta: 20:13:23 time: 0.3460 data_time: 0.0233 memory: 5826 grad_norm: 3.0830 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7229 loss: 2.7229 2022/10/07 18:08:49 - mmengine - INFO - Epoch(train) [51][1540/2119] lr: 4.0000e-02 eta: 20:13:15 time: 0.3363 data_time: 0.0230 memory: 5826 grad_norm: 3.1153 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6902 loss: 2.6902 2022/10/07 18:08:57 - mmengine - INFO - Epoch(train) [51][1560/2119] lr: 4.0000e-02 eta: 20:13:10 time: 0.3803 data_time: 0.0211 memory: 5826 grad_norm: 3.1307 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6751 loss: 2.6751 2022/10/07 18:09:04 - mmengine - INFO - Epoch(train) [51][1580/2119] lr: 4.0000e-02 eta: 20:13:03 time: 0.3505 data_time: 0.0233 memory: 5826 grad_norm: 3.1202 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8356 loss: 2.8356 2022/10/07 18:09:11 - mmengine - INFO - Epoch(train) [51][1600/2119] lr: 4.0000e-02 eta: 20:12:55 time: 0.3286 data_time: 0.0212 memory: 5826 grad_norm: 3.1142 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6526 loss: 2.6526 2022/10/07 18:09:18 - mmengine - INFO - Epoch(train) [51][1620/2119] lr: 4.0000e-02 eta: 20:12:49 time: 0.3534 data_time: 0.0182 memory: 5826 grad_norm: 3.1203 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6015 loss: 2.6015 2022/10/07 18:09:24 - mmengine - INFO - Epoch(train) [51][1640/2119] lr: 4.0000e-02 eta: 20:12:41 time: 0.3327 data_time: 0.0243 memory: 5826 grad_norm: 3.0852 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6666 loss: 2.6666 2022/10/07 18:09:31 - mmengine - INFO - Epoch(train) [51][1660/2119] lr: 4.0000e-02 eta: 20:12:34 time: 0.3436 data_time: 0.0289 memory: 5826 grad_norm: 3.0971 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8153 loss: 2.8153 2022/10/07 18:09:38 - mmengine - INFO - Epoch(train) [51][1680/2119] lr: 4.0000e-02 eta: 20:12:28 time: 0.3547 data_time: 0.0216 memory: 5826 grad_norm: 3.1291 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8373 loss: 2.8373 2022/10/07 18:09:45 - mmengine - INFO - Epoch(train) [51][1700/2119] lr: 4.0000e-02 eta: 20:12:20 time: 0.3357 data_time: 0.0252 memory: 5826 grad_norm: 3.1488 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9345 loss: 2.9345 2022/10/07 18:09:52 - mmengine - INFO - Epoch(train) [51][1720/2119] lr: 4.0000e-02 eta: 20:12:13 time: 0.3314 data_time: 0.0275 memory: 5826 grad_norm: 3.1362 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.4615 loss: 2.4615 2022/10/07 18:09:58 - mmengine - INFO - Epoch(train) [51][1740/2119] lr: 4.0000e-02 eta: 20:12:05 time: 0.3184 data_time: 0.0170 memory: 5826 grad_norm: 3.0821 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.0448 loss: 3.0448 2022/10/07 18:10:05 - mmengine - INFO - Epoch(train) [51][1760/2119] lr: 4.0000e-02 eta: 20:11:58 time: 0.3527 data_time: 0.0219 memory: 5826 grad_norm: 3.0753 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8583 loss: 2.8583 2022/10/07 18:10:12 - mmengine - INFO - Epoch(train) [51][1780/2119] lr: 4.0000e-02 eta: 20:11:52 time: 0.3566 data_time: 0.0232 memory: 5826 grad_norm: 3.1026 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6047 loss: 2.6047 2022/10/07 18:10:19 - mmengine - INFO - Epoch(train) [51][1800/2119] lr: 4.0000e-02 eta: 20:11:45 time: 0.3518 data_time: 0.0179 memory: 5826 grad_norm: 3.1795 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6457 loss: 2.6457 2022/10/07 18:10:27 - mmengine - INFO - Epoch(train) [51][1820/2119] lr: 4.0000e-02 eta: 20:11:39 time: 0.3657 data_time: 0.0366 memory: 5826 grad_norm: 3.1026 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8179 loss: 2.8179 2022/10/07 18:10:33 - mmengine - INFO - Epoch(train) [51][1840/2119] lr: 4.0000e-02 eta: 20:11:31 time: 0.3240 data_time: 0.0219 memory: 5826 grad_norm: 3.0650 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8496 loss: 2.8496 2022/10/07 18:10:39 - mmengine - INFO - Epoch(train) [51][1860/2119] lr: 4.0000e-02 eta: 20:11:23 time: 0.3218 data_time: 0.0209 memory: 5826 grad_norm: 3.0606 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8543 loss: 2.8543 2022/10/07 18:10:46 - mmengine - INFO - Epoch(train) [51][1880/2119] lr: 4.0000e-02 eta: 20:11:16 time: 0.3354 data_time: 0.0270 memory: 5826 grad_norm: 3.0907 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7893 loss: 2.7893 2022/10/07 18:10:54 - mmengine - INFO - Epoch(train) [51][1900/2119] lr: 4.0000e-02 eta: 20:11:10 time: 0.3795 data_time: 0.0244 memory: 5826 grad_norm: 3.1039 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9815 loss: 2.9815 2022/10/07 18:11:01 - mmengine - INFO - Epoch(train) [51][1920/2119] lr: 4.0000e-02 eta: 20:11:04 time: 0.3568 data_time: 0.0175 memory: 5826 grad_norm: 3.0834 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5707 loss: 2.5707 2022/10/07 18:11:08 - mmengine - INFO - Epoch(train) [51][1940/2119] lr: 4.0000e-02 eta: 20:10:58 time: 0.3781 data_time: 0.0238 memory: 5826 grad_norm: 2.9885 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6395 loss: 2.6395 2022/10/07 18:11:14 - mmengine - INFO - Epoch(train) [51][1960/2119] lr: 4.0000e-02 eta: 20:10:49 time: 0.2921 data_time: 0.0191 memory: 5826 grad_norm: 3.0990 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9501 loss: 2.9501 2022/10/07 18:11:22 - mmengine - INFO - Epoch(train) [51][1980/2119] lr: 4.0000e-02 eta: 20:10:44 time: 0.3842 data_time: 0.0259 memory: 5826 grad_norm: 3.0501 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6878 loss: 2.6878 2022/10/07 18:11:29 - mmengine - INFO - Epoch(train) [51][2000/2119] lr: 4.0000e-02 eta: 20:10:36 time: 0.3287 data_time: 0.0240 memory: 5826 grad_norm: 3.0640 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9108 loss: 2.9108 2022/10/07 18:11:35 - mmengine - INFO - Epoch(train) [51][2020/2119] lr: 4.0000e-02 eta: 20:10:28 time: 0.3210 data_time: 0.0224 memory: 5826 grad_norm: 3.0703 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6857 loss: 2.6857 2022/10/07 18:11:43 - mmengine - INFO - Epoch(train) [51][2040/2119] lr: 4.0000e-02 eta: 20:10:24 time: 0.4132 data_time: 0.0267 memory: 5826 grad_norm: 3.1145 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7795 loss: 2.7795 2022/10/07 18:11:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 18:11:50 - mmengine - INFO - Epoch(train) [51][2060/2119] lr: 4.0000e-02 eta: 20:10:16 time: 0.3247 data_time: 0.0234 memory: 5826 grad_norm: 3.1208 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0343 loss: 3.0343 2022/10/07 18:11:56 - mmengine - INFO - Epoch(train) [51][2080/2119] lr: 4.0000e-02 eta: 20:10:08 time: 0.3139 data_time: 0.0226 memory: 5826 grad_norm: 3.0944 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6832 loss: 2.6832 2022/10/07 18:12:04 - mmengine - INFO - Epoch(train) [51][2100/2119] lr: 4.0000e-02 eta: 20:10:02 time: 0.3756 data_time: 0.0232 memory: 5826 grad_norm: 3.1547 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6838 loss: 2.6838 2022/10/07 18:12:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 18:12:09 - mmengine - INFO - Epoch(train) [51][2119/2119] lr: 4.0000e-02 eta: 20:10:02 time: 0.2846 data_time: 0.0161 memory: 5826 grad_norm: 3.0851 top1_acc: 0.0000 top5_acc: 0.6000 loss_cls: 2.7058 loss: 2.7058 2022/10/07 18:12:19 - mmengine - INFO - Epoch(train) [52][20/2119] lr: 4.0000e-02 eta: 20:09:41 time: 0.4797 data_time: 0.1223 memory: 5826 grad_norm: 2.9935 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8218 loss: 2.8218 2022/10/07 18:12:26 - mmengine - INFO - Epoch(train) [52][40/2119] lr: 4.0000e-02 eta: 20:09:34 time: 0.3440 data_time: 0.0184 memory: 5826 grad_norm: 3.1297 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6185 loss: 2.6185 2022/10/07 18:12:34 - mmengine - INFO - Epoch(train) [52][60/2119] lr: 4.0000e-02 eta: 20:09:30 time: 0.4134 data_time: 0.0308 memory: 5826 grad_norm: 3.0936 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6094 loss: 2.6094 2022/10/07 18:12:41 - mmengine - INFO - Epoch(train) [52][80/2119] lr: 4.0000e-02 eta: 20:09:23 time: 0.3621 data_time: 0.0258 memory: 5826 grad_norm: 3.0382 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7717 loss: 2.7717 2022/10/07 18:12:49 - mmengine - INFO - Epoch(train) [52][100/2119] lr: 4.0000e-02 eta: 20:09:18 time: 0.3872 data_time: 0.0207 memory: 5826 grad_norm: 3.0745 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7528 loss: 2.7528 2022/10/07 18:12:55 - mmengine - INFO - Epoch(train) [52][120/2119] lr: 4.0000e-02 eta: 20:09:10 time: 0.3280 data_time: 0.0192 memory: 5826 grad_norm: 3.1211 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7507 loss: 2.7507 2022/10/07 18:13:02 - mmengine - INFO - Epoch(train) [52][140/2119] lr: 4.0000e-02 eta: 20:09:03 time: 0.3252 data_time: 0.0224 memory: 5826 grad_norm: 3.1121 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7188 loss: 2.7188 2022/10/07 18:13:08 - mmengine - INFO - Epoch(train) [52][160/2119] lr: 4.0000e-02 eta: 20:08:55 time: 0.3275 data_time: 0.0242 memory: 5826 grad_norm: 3.0553 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6932 loss: 2.6932 2022/10/07 18:13:16 - mmengine - INFO - Epoch(train) [52][180/2119] lr: 4.0000e-02 eta: 20:08:49 time: 0.3644 data_time: 0.0192 memory: 5826 grad_norm: 3.1377 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6593 loss: 2.6593 2022/10/07 18:13:22 - mmengine - INFO - Epoch(train) [52][200/2119] lr: 4.0000e-02 eta: 20:08:41 time: 0.3333 data_time: 0.0225 memory: 5826 grad_norm: 3.1278 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7284 loss: 2.7284 2022/10/07 18:13:29 - mmengine - INFO - Epoch(train) [52][220/2119] lr: 4.0000e-02 eta: 20:08:35 time: 0.3482 data_time: 0.0259 memory: 5826 grad_norm: 3.0817 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7964 loss: 2.7964 2022/10/07 18:13:37 - mmengine - INFO - Epoch(train) [52][240/2119] lr: 4.0000e-02 eta: 20:08:28 time: 0.3610 data_time: 0.0178 memory: 5826 grad_norm: 3.0720 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6774 loss: 2.6774 2022/10/07 18:13:44 - mmengine - INFO - Epoch(train) [52][260/2119] lr: 4.0000e-02 eta: 20:08:23 time: 0.3826 data_time: 0.0364 memory: 5826 grad_norm: 3.0966 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6456 loss: 2.6456 2022/10/07 18:13:50 - mmengine - INFO - Epoch(train) [52][280/2119] lr: 4.0000e-02 eta: 20:08:14 time: 0.3092 data_time: 0.0203 memory: 5826 grad_norm: 3.2069 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8163 loss: 2.8163 2022/10/07 18:13:57 - mmengine - INFO - Epoch(train) [52][300/2119] lr: 4.0000e-02 eta: 20:08:08 time: 0.3501 data_time: 0.0200 memory: 5826 grad_norm: 3.1405 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9434 loss: 2.9434 2022/10/07 18:14:04 - mmengine - INFO - Epoch(train) [52][320/2119] lr: 4.0000e-02 eta: 20:08:00 time: 0.3264 data_time: 0.0204 memory: 5826 grad_norm: 3.1485 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6697 loss: 2.6697 2022/10/07 18:14:12 - mmengine - INFO - Epoch(train) [52][340/2119] lr: 4.0000e-02 eta: 20:07:55 time: 0.4014 data_time: 0.0181 memory: 5826 grad_norm: 3.0967 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7668 loss: 2.7668 2022/10/07 18:14:19 - mmengine - INFO - Epoch(train) [52][360/2119] lr: 4.0000e-02 eta: 20:07:48 time: 0.3496 data_time: 0.0169 memory: 5826 grad_norm: 3.1193 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6094 loss: 2.6094 2022/10/07 18:14:25 - mmengine - INFO - Epoch(train) [52][380/2119] lr: 4.0000e-02 eta: 20:07:41 time: 0.3215 data_time: 0.0257 memory: 5826 grad_norm: 3.1273 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7112 loss: 2.7112 2022/10/07 18:14:32 - mmengine - INFO - Epoch(train) [52][400/2119] lr: 4.0000e-02 eta: 20:07:34 time: 0.3460 data_time: 0.0244 memory: 5826 grad_norm: 3.1151 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8044 loss: 2.8044 2022/10/07 18:14:40 - mmengine - INFO - Epoch(train) [52][420/2119] lr: 4.0000e-02 eta: 20:07:27 time: 0.3641 data_time: 0.0197 memory: 5826 grad_norm: 3.0563 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7104 loss: 2.7104 2022/10/07 18:14:46 - mmengine - INFO - Epoch(train) [52][440/2119] lr: 4.0000e-02 eta: 20:07:20 time: 0.3382 data_time: 0.0258 memory: 5826 grad_norm: 3.0673 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8468 loss: 2.8468 2022/10/07 18:14:53 - mmengine - INFO - Epoch(train) [52][460/2119] lr: 4.0000e-02 eta: 20:07:13 time: 0.3364 data_time: 0.0257 memory: 5826 grad_norm: 3.1800 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7296 loss: 2.7296 2022/10/07 18:14:59 - mmengine - INFO - Epoch(train) [52][480/2119] lr: 4.0000e-02 eta: 20:07:04 time: 0.2862 data_time: 0.0239 memory: 5826 grad_norm: 3.0775 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6029 loss: 2.6029 2022/10/07 18:15:06 - mmengine - INFO - Epoch(train) [52][500/2119] lr: 4.0000e-02 eta: 20:06:57 time: 0.3410 data_time: 0.0248 memory: 5826 grad_norm: 3.1442 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7701 loss: 2.7701 2022/10/07 18:15:14 - mmengine - INFO - Epoch(train) [52][520/2119] lr: 4.0000e-02 eta: 20:06:51 time: 0.3936 data_time: 0.0191 memory: 5826 grad_norm: 3.1532 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9070 loss: 2.9070 2022/10/07 18:15:20 - mmengine - INFO - Epoch(train) [52][540/2119] lr: 4.0000e-02 eta: 20:06:44 time: 0.3331 data_time: 0.0196 memory: 5826 grad_norm: 3.0947 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7259 loss: 2.7259 2022/10/07 18:15:28 - mmengine - INFO - Epoch(train) [52][560/2119] lr: 4.0000e-02 eta: 20:06:38 time: 0.3780 data_time: 0.0173 memory: 5826 grad_norm: 3.0989 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7244 loss: 2.7244 2022/10/07 18:15:34 - mmengine - INFO - Epoch(train) [52][580/2119] lr: 4.0000e-02 eta: 20:06:31 time: 0.3242 data_time: 0.0263 memory: 5826 grad_norm: 3.1120 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6944 loss: 2.6944 2022/10/07 18:15:42 - mmengine - INFO - Epoch(train) [52][600/2119] lr: 4.0000e-02 eta: 20:06:25 time: 0.3815 data_time: 0.0236 memory: 5826 grad_norm: 3.1332 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6643 loss: 2.6643 2022/10/07 18:15:49 - mmengine - INFO - Epoch(train) [52][620/2119] lr: 4.0000e-02 eta: 20:06:18 time: 0.3399 data_time: 0.0227 memory: 5826 grad_norm: 3.1364 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7524 loss: 2.7524 2022/10/07 18:15:55 - mmengine - INFO - Epoch(train) [52][640/2119] lr: 4.0000e-02 eta: 20:06:10 time: 0.3184 data_time: 0.0167 memory: 5826 grad_norm: 3.0853 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7196 loss: 2.7196 2022/10/07 18:16:03 - mmengine - INFO - Epoch(train) [52][660/2119] lr: 4.0000e-02 eta: 20:06:05 time: 0.3925 data_time: 0.0200 memory: 5826 grad_norm: 3.1271 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5398 loss: 2.5398 2022/10/07 18:16:10 - mmengine - INFO - Epoch(train) [52][680/2119] lr: 4.0000e-02 eta: 20:05:57 time: 0.3381 data_time: 0.0214 memory: 5826 grad_norm: 3.1057 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8910 loss: 2.8910 2022/10/07 18:16:17 - mmengine - INFO - Epoch(train) [52][700/2119] lr: 4.0000e-02 eta: 20:05:51 time: 0.3555 data_time: 0.0193 memory: 5826 grad_norm: 3.0983 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8749 loss: 2.8749 2022/10/07 18:16:24 - mmengine - INFO - Epoch(train) [52][720/2119] lr: 4.0000e-02 eta: 20:05:44 time: 0.3386 data_time: 0.0247 memory: 5826 grad_norm: 3.1440 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8890 loss: 2.8890 2022/10/07 18:16:30 - mmengine - INFO - Epoch(train) [52][740/2119] lr: 4.0000e-02 eta: 20:05:35 time: 0.3115 data_time: 0.0237 memory: 5826 grad_norm: 3.0515 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9489 loss: 2.9489 2022/10/07 18:16:37 - mmengine - INFO - Epoch(train) [52][760/2119] lr: 4.0000e-02 eta: 20:05:28 time: 0.3444 data_time: 0.0258 memory: 5826 grad_norm: 3.0922 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7347 loss: 2.7347 2022/10/07 18:16:44 - mmengine - INFO - Epoch(train) [52][780/2119] lr: 4.0000e-02 eta: 20:05:22 time: 0.3486 data_time: 0.0271 memory: 5826 grad_norm: 3.0931 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5677 loss: 2.5677 2022/10/07 18:16:51 - mmengine - INFO - Epoch(train) [52][800/2119] lr: 4.0000e-02 eta: 20:05:15 time: 0.3415 data_time: 0.0219 memory: 5826 grad_norm: 3.1099 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7633 loss: 2.7633 2022/10/07 18:16:58 - mmengine - INFO - Epoch(train) [52][820/2119] lr: 4.0000e-02 eta: 20:05:09 time: 0.3856 data_time: 0.0188 memory: 5826 grad_norm: 3.1128 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7336 loss: 2.7336 2022/10/07 18:17:05 - mmengine - INFO - Epoch(train) [52][840/2119] lr: 4.0000e-02 eta: 20:05:03 time: 0.3571 data_time: 0.0204 memory: 5826 grad_norm: 3.0690 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6152 loss: 2.6152 2022/10/07 18:17:12 - mmengine - INFO - Epoch(train) [52][860/2119] lr: 4.0000e-02 eta: 20:04:55 time: 0.3283 data_time: 0.0167 memory: 5826 grad_norm: 3.1317 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7731 loss: 2.7731 2022/10/07 18:17:19 - mmengine - INFO - Epoch(train) [52][880/2119] lr: 4.0000e-02 eta: 20:04:48 time: 0.3339 data_time: 0.0249 memory: 5826 grad_norm: 3.1071 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.9341 loss: 2.9341 2022/10/07 18:17:25 - mmengine - INFO - Epoch(train) [52][900/2119] lr: 4.0000e-02 eta: 20:04:40 time: 0.3337 data_time: 0.0193 memory: 5826 grad_norm: 3.0597 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6074 loss: 2.6074 2022/10/07 18:17:33 - mmengine - INFO - Epoch(train) [52][920/2119] lr: 4.0000e-02 eta: 20:04:35 time: 0.3939 data_time: 0.0200 memory: 5826 grad_norm: 3.1216 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8552 loss: 2.8552 2022/10/07 18:17:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 18:17:41 - mmengine - INFO - Epoch(train) [52][940/2119] lr: 4.0000e-02 eta: 20:04:30 time: 0.3918 data_time: 0.0196 memory: 5826 grad_norm: 3.0950 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8238 loss: 2.8238 2022/10/07 18:17:47 - mmengine - INFO - Epoch(train) [52][960/2119] lr: 4.0000e-02 eta: 20:04:22 time: 0.3131 data_time: 0.0234 memory: 5826 grad_norm: 3.0688 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9553 loss: 2.9553 2022/10/07 18:17:55 - mmengine - INFO - Epoch(train) [52][980/2119] lr: 4.0000e-02 eta: 20:04:16 time: 0.3669 data_time: 0.0205 memory: 5826 grad_norm: 3.0870 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6100 loss: 2.6100 2022/10/07 18:18:02 - mmengine - INFO - Epoch(train) [52][1000/2119] lr: 4.0000e-02 eta: 20:04:09 time: 0.3438 data_time: 0.0202 memory: 5826 grad_norm: 3.1334 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7651 loss: 2.7651 2022/10/07 18:18:08 - mmengine - INFO - Epoch(train) [52][1020/2119] lr: 4.0000e-02 eta: 20:04:02 time: 0.3398 data_time: 0.0222 memory: 5826 grad_norm: 3.0930 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9531 loss: 2.9531 2022/10/07 18:18:15 - mmengine - INFO - Epoch(train) [52][1040/2119] lr: 4.0000e-02 eta: 20:03:55 time: 0.3575 data_time: 0.0229 memory: 5826 grad_norm: 3.0957 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8932 loss: 2.8932 2022/10/07 18:18:23 - mmengine - INFO - Epoch(train) [52][1060/2119] lr: 4.0000e-02 eta: 20:03:49 time: 0.3666 data_time: 0.0235 memory: 5826 grad_norm: 3.0538 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.7680 loss: 2.7680 2022/10/07 18:18:29 - mmengine - INFO - Epoch(train) [52][1080/2119] lr: 4.0000e-02 eta: 20:03:40 time: 0.3054 data_time: 0.0176 memory: 5826 grad_norm: 3.0845 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6879 loss: 2.6879 2022/10/07 18:18:35 - mmengine - INFO - Epoch(train) [52][1100/2119] lr: 4.0000e-02 eta: 20:03:33 time: 0.3252 data_time: 0.0200 memory: 5826 grad_norm: 3.1362 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8669 loss: 2.8669 2022/10/07 18:18:43 - mmengine - INFO - Epoch(train) [52][1120/2119] lr: 4.0000e-02 eta: 20:03:26 time: 0.3554 data_time: 0.0315 memory: 5826 grad_norm: 3.1008 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7504 loss: 2.7504 2022/10/07 18:18:50 - mmengine - INFO - Epoch(train) [52][1140/2119] lr: 4.0000e-02 eta: 20:03:21 time: 0.3787 data_time: 0.0204 memory: 5826 grad_norm: 3.0930 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8083 loss: 2.8083 2022/10/07 18:18:57 - mmengine - INFO - Epoch(train) [52][1160/2119] lr: 4.0000e-02 eta: 20:03:13 time: 0.3299 data_time: 0.0206 memory: 5826 grad_norm: 3.1433 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.0232 loss: 3.0232 2022/10/07 18:19:04 - mmengine - INFO - Epoch(train) [52][1180/2119] lr: 4.0000e-02 eta: 20:03:06 time: 0.3520 data_time: 0.0221 memory: 5826 grad_norm: 3.1078 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7672 loss: 2.7672 2022/10/07 18:19:11 - mmengine - INFO - Epoch(train) [52][1200/2119] lr: 4.0000e-02 eta: 20:03:00 time: 0.3614 data_time: 0.0212 memory: 5826 grad_norm: 3.0715 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8048 loss: 2.8048 2022/10/07 18:19:18 - mmengine - INFO - Epoch(train) [52][1220/2119] lr: 4.0000e-02 eta: 20:02:52 time: 0.3317 data_time: 0.0243 memory: 5826 grad_norm: 3.1036 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7713 loss: 2.7713 2022/10/07 18:19:25 - mmengine - INFO - Epoch(train) [52][1240/2119] lr: 4.0000e-02 eta: 20:02:46 time: 0.3527 data_time: 0.0176 memory: 5826 grad_norm: 3.0829 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7077 loss: 2.7077 2022/10/07 18:19:33 - mmengine - INFO - Epoch(train) [52][1260/2119] lr: 4.0000e-02 eta: 20:02:41 time: 0.3952 data_time: 0.0264 memory: 5826 grad_norm: 3.1409 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7238 loss: 2.7238 2022/10/07 18:19:40 - mmengine - INFO - Epoch(train) [52][1280/2119] lr: 4.0000e-02 eta: 20:02:34 time: 0.3626 data_time: 0.0217 memory: 5826 grad_norm: 3.0968 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9621 loss: 2.9621 2022/10/07 18:19:47 - mmengine - INFO - Epoch(train) [52][1300/2119] lr: 4.0000e-02 eta: 20:02:28 time: 0.3578 data_time: 0.0218 memory: 5826 grad_norm: 3.1418 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6683 loss: 2.6683 2022/10/07 18:19:54 - mmengine - INFO - Epoch(train) [52][1320/2119] lr: 4.0000e-02 eta: 20:02:21 time: 0.3460 data_time: 0.0204 memory: 5826 grad_norm: 3.0887 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8781 loss: 2.8781 2022/10/07 18:20:02 - mmengine - INFO - Epoch(train) [52][1340/2119] lr: 4.0000e-02 eta: 20:02:16 time: 0.3893 data_time: 0.0187 memory: 5826 grad_norm: 3.0956 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6410 loss: 2.6410 2022/10/07 18:20:08 - mmengine - INFO - Epoch(train) [52][1360/2119] lr: 4.0000e-02 eta: 20:02:07 time: 0.3037 data_time: 0.0224 memory: 5826 grad_norm: 3.1158 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7745 loss: 2.7745 2022/10/07 18:20:16 - mmengine - INFO - Epoch(train) [52][1380/2119] lr: 4.0000e-02 eta: 20:02:03 time: 0.4147 data_time: 0.0151 memory: 5826 grad_norm: 3.1025 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.9037 loss: 2.9037 2022/10/07 18:20:24 - mmengine - INFO - Epoch(train) [52][1400/2119] lr: 4.0000e-02 eta: 20:01:57 time: 0.3720 data_time: 0.0220 memory: 5826 grad_norm: 3.1091 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6273 loss: 2.6273 2022/10/07 18:20:29 - mmengine - INFO - Epoch(train) [52][1420/2119] lr: 4.0000e-02 eta: 20:01:48 time: 0.2863 data_time: 0.0237 memory: 5826 grad_norm: 3.1386 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7889 loss: 2.7889 2022/10/07 18:20:36 - mmengine - INFO - Epoch(train) [52][1440/2119] lr: 4.0000e-02 eta: 20:01:41 time: 0.3465 data_time: 0.0239 memory: 5826 grad_norm: 3.0724 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6744 loss: 2.6744 2022/10/07 18:20:44 - mmengine - INFO - Epoch(train) [52][1460/2119] lr: 4.0000e-02 eta: 20:01:35 time: 0.3779 data_time: 0.0252 memory: 5826 grad_norm: 3.0589 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7857 loss: 2.7857 2022/10/07 18:20:50 - mmengine - INFO - Epoch(train) [52][1480/2119] lr: 4.0000e-02 eta: 20:01:27 time: 0.3133 data_time: 0.0182 memory: 5826 grad_norm: 3.1245 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0499 loss: 3.0499 2022/10/07 18:20:58 - mmengine - INFO - Epoch(train) [52][1500/2119] lr: 4.0000e-02 eta: 20:01:21 time: 0.3766 data_time: 0.0188 memory: 5826 grad_norm: 3.0696 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6921 loss: 2.6921 2022/10/07 18:21:04 - mmengine - INFO - Epoch(train) [52][1520/2119] lr: 4.0000e-02 eta: 20:01:14 time: 0.3444 data_time: 0.0206 memory: 5826 grad_norm: 3.1580 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7849 loss: 2.7849 2022/10/07 18:21:11 - mmengine - INFO - Epoch(train) [52][1540/2119] lr: 4.0000e-02 eta: 20:01:06 time: 0.3168 data_time: 0.0239 memory: 5826 grad_norm: 3.1122 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8126 loss: 2.8126 2022/10/07 18:21:18 - mmengine - INFO - Epoch(train) [52][1560/2119] lr: 4.0000e-02 eta: 20:00:59 time: 0.3478 data_time: 0.0171 memory: 5826 grad_norm: 3.0989 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6579 loss: 2.6579 2022/10/07 18:21:25 - mmengine - INFO - Epoch(train) [52][1580/2119] lr: 4.0000e-02 eta: 20:00:53 time: 0.3497 data_time: 0.0225 memory: 5826 grad_norm: 2.9883 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8437 loss: 2.8437 2022/10/07 18:21:32 - mmengine - INFO - Epoch(train) [52][1600/2119] lr: 4.0000e-02 eta: 20:00:47 time: 0.3714 data_time: 0.0162 memory: 5826 grad_norm: 3.1111 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7720 loss: 2.7720 2022/10/07 18:21:39 - mmengine - INFO - Epoch(train) [52][1620/2119] lr: 4.0000e-02 eta: 20:00:40 time: 0.3426 data_time: 0.0241 memory: 5826 grad_norm: 3.1463 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8979 loss: 2.8979 2022/10/07 18:21:47 - mmengine - INFO - Epoch(train) [52][1640/2119] lr: 4.0000e-02 eta: 20:00:34 time: 0.3882 data_time: 0.0163 memory: 5826 grad_norm: 3.1548 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7681 loss: 2.7681 2022/10/07 18:21:53 - mmengine - INFO - Epoch(train) [52][1660/2119] lr: 4.0000e-02 eta: 20:00:27 time: 0.3267 data_time: 0.0226 memory: 5826 grad_norm: 3.1014 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8380 loss: 2.8380 2022/10/07 18:22:01 - mmengine - INFO - Epoch(train) [52][1680/2119] lr: 4.0000e-02 eta: 20:00:21 time: 0.3870 data_time: 0.0169 memory: 5826 grad_norm: 3.1108 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7354 loss: 2.7354 2022/10/07 18:22:08 - mmengine - INFO - Epoch(train) [52][1700/2119] lr: 4.0000e-02 eta: 20:00:15 time: 0.3532 data_time: 0.0231 memory: 5826 grad_norm: 3.1305 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8418 loss: 2.8418 2022/10/07 18:22:16 - mmengine - INFO - Epoch(train) [52][1720/2119] lr: 4.0000e-02 eta: 20:00:09 time: 0.3834 data_time: 0.0200 memory: 5826 grad_norm: 3.1175 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6687 loss: 2.6687 2022/10/07 18:22:22 - mmengine - INFO - Epoch(train) [52][1740/2119] lr: 4.0000e-02 eta: 20:00:01 time: 0.3256 data_time: 0.0183 memory: 5826 grad_norm: 3.0749 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7037 loss: 2.7037 2022/10/07 18:22:30 - mmengine - INFO - Epoch(train) [52][1760/2119] lr: 4.0000e-02 eta: 19:59:56 time: 0.3814 data_time: 0.0178 memory: 5826 grad_norm: 3.0868 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6745 loss: 2.6745 2022/10/07 18:22:36 - mmengine - INFO - Epoch(train) [52][1780/2119] lr: 4.0000e-02 eta: 19:59:47 time: 0.2932 data_time: 0.0190 memory: 5826 grad_norm: 3.1165 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8462 loss: 2.8462 2022/10/07 18:22:44 - mmengine - INFO - Epoch(train) [52][1800/2119] lr: 4.0000e-02 eta: 19:59:42 time: 0.3952 data_time: 0.0229 memory: 5826 grad_norm: 3.1161 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7594 loss: 2.7594 2022/10/07 18:22:50 - mmengine - INFO - Epoch(train) [52][1820/2119] lr: 4.0000e-02 eta: 19:59:34 time: 0.3266 data_time: 0.0238 memory: 5826 grad_norm: 3.1082 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6949 loss: 2.6949 2022/10/07 18:22:58 - mmengine - INFO - Epoch(train) [52][1840/2119] lr: 4.0000e-02 eta: 19:59:28 time: 0.3601 data_time: 0.0267 memory: 5826 grad_norm: 3.0439 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7012 loss: 2.7012 2022/10/07 18:23:04 - mmengine - INFO - Epoch(train) [52][1860/2119] lr: 4.0000e-02 eta: 19:59:21 time: 0.3461 data_time: 0.0201 memory: 5826 grad_norm: 3.1321 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7489 loss: 2.7489 2022/10/07 18:23:13 - mmengine - INFO - Epoch(train) [52][1880/2119] lr: 4.0000e-02 eta: 19:59:16 time: 0.4045 data_time: 0.0183 memory: 5826 grad_norm: 3.0564 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5914 loss: 2.5914 2022/10/07 18:23:18 - mmengine - INFO - Epoch(train) [52][1900/2119] lr: 4.0000e-02 eta: 19:59:07 time: 0.2753 data_time: 0.0230 memory: 5826 grad_norm: 3.0916 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9960 loss: 2.9960 2022/10/07 18:23:25 - mmengine - INFO - Epoch(train) [52][1920/2119] lr: 4.0000e-02 eta: 19:59:00 time: 0.3533 data_time: 0.0199 memory: 5826 grad_norm: 3.1290 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.1576 loss: 3.1576 2022/10/07 18:23:28 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 18:23:31 - mmengine - INFO - Epoch(train) [52][1940/2119] lr: 4.0000e-02 eta: 19:58:51 time: 0.3009 data_time: 0.0229 memory: 5826 grad_norm: 3.1361 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5921 loss: 2.5921 2022/10/07 18:23:38 - mmengine - INFO - Epoch(train) [52][1960/2119] lr: 4.0000e-02 eta: 19:58:45 time: 0.3672 data_time: 0.0193 memory: 5826 grad_norm: 3.0925 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8409 loss: 2.8409 2022/10/07 18:23:45 - mmengine - INFO - Epoch(train) [52][1980/2119] lr: 4.0000e-02 eta: 19:58:38 time: 0.3336 data_time: 0.0233 memory: 5826 grad_norm: 3.0544 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.3495 loss: 2.3495 2022/10/07 18:23:53 - mmengine - INFO - Epoch(train) [52][2000/2119] lr: 4.0000e-02 eta: 19:58:32 time: 0.3816 data_time: 0.0223 memory: 5826 grad_norm: 3.0958 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8512 loss: 2.8512 2022/10/07 18:23:59 - mmengine - INFO - Epoch(train) [52][2020/2119] lr: 4.0000e-02 eta: 19:58:24 time: 0.3067 data_time: 0.0206 memory: 5826 grad_norm: 3.0854 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6455 loss: 2.6455 2022/10/07 18:24:06 - mmengine - INFO - Epoch(train) [52][2040/2119] lr: 4.0000e-02 eta: 19:58:18 time: 0.3669 data_time: 0.0223 memory: 5826 grad_norm: 3.1618 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6863 loss: 2.6863 2022/10/07 18:24:13 - mmengine - INFO - Epoch(train) [52][2060/2119] lr: 4.0000e-02 eta: 19:58:10 time: 0.3317 data_time: 0.0246 memory: 5826 grad_norm: 3.0419 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7938 loss: 2.7938 2022/10/07 18:24:20 - mmengine - INFO - Epoch(train) [52][2080/2119] lr: 4.0000e-02 eta: 19:58:04 time: 0.3620 data_time: 0.0194 memory: 5826 grad_norm: 3.0835 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7597 loss: 2.7597 2022/10/07 18:24:27 - mmengine - INFO - Epoch(train) [52][2100/2119] lr: 4.0000e-02 eta: 19:57:56 time: 0.3273 data_time: 0.0203 memory: 5826 grad_norm: 3.1775 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7194 loss: 2.7194 2022/10/07 18:24:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 18:24:32 - mmengine - INFO - Epoch(train) [52][2119/2119] lr: 4.0000e-02 eta: 19:57:56 time: 0.3118 data_time: 0.0196 memory: 5826 grad_norm: 3.1216 top1_acc: 0.0000 top5_acc: 0.1000 loss_cls: 3.0750 loss: 3.0750 2022/10/07 18:24:33 - mmengine - INFO - Saving checkpoint at 52 epochs 2022/10/07 18:24:45 - mmengine - INFO - Epoch(train) [53][20/2119] lr: 4.0000e-02 eta: 19:57:34 time: 0.4343 data_time: 0.2054 memory: 5826 grad_norm: 3.0309 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7289 loss: 2.7289 2022/10/07 18:24:50 - mmengine - INFO - Epoch(train) [53][40/2119] lr: 4.0000e-02 eta: 19:57:24 time: 0.2831 data_time: 0.0572 memory: 5826 grad_norm: 3.1208 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5283 loss: 2.5283 2022/10/07 18:24:57 - mmengine - INFO - Epoch(train) [53][60/2119] lr: 4.0000e-02 eta: 19:57:16 time: 0.3160 data_time: 0.0602 memory: 5826 grad_norm: 3.0216 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7625 loss: 2.7625 2022/10/07 18:25:04 - mmengine - INFO - Epoch(train) [53][80/2119] lr: 4.0000e-02 eta: 19:57:10 time: 0.3745 data_time: 0.0170 memory: 5826 grad_norm: 3.0538 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6314 loss: 2.6314 2022/10/07 18:25:10 - mmengine - INFO - Epoch(train) [53][100/2119] lr: 4.0000e-02 eta: 19:57:03 time: 0.3197 data_time: 0.0233 memory: 5826 grad_norm: 3.1192 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9049 loss: 2.9049 2022/10/07 18:25:19 - mmengine - INFO - Epoch(train) [53][120/2119] lr: 4.0000e-02 eta: 19:56:58 time: 0.4022 data_time: 0.0173 memory: 5826 grad_norm: 3.1095 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8709 loss: 2.8709 2022/10/07 18:25:25 - mmengine - INFO - Epoch(train) [53][140/2119] lr: 4.0000e-02 eta: 19:56:50 time: 0.3325 data_time: 0.0302 memory: 5826 grad_norm: 3.1019 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7747 loss: 2.7747 2022/10/07 18:25:32 - mmengine - INFO - Epoch(train) [53][160/2119] lr: 4.0000e-02 eta: 19:56:43 time: 0.3454 data_time: 0.0194 memory: 5826 grad_norm: 3.0882 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6224 loss: 2.6224 2022/10/07 18:25:39 - mmengine - INFO - Epoch(train) [53][180/2119] lr: 4.0000e-02 eta: 19:56:36 time: 0.3217 data_time: 0.0252 memory: 5826 grad_norm: 3.1328 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.6423 loss: 2.6423 2022/10/07 18:25:46 - mmengine - INFO - Epoch(train) [53][200/2119] lr: 4.0000e-02 eta: 19:56:29 time: 0.3677 data_time: 0.0225 memory: 5826 grad_norm: 3.1077 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7748 loss: 2.7748 2022/10/07 18:25:53 - mmengine - INFO - Epoch(train) [53][220/2119] lr: 4.0000e-02 eta: 19:56:22 time: 0.3405 data_time: 0.0216 memory: 5826 grad_norm: 3.0092 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7873 loss: 2.7873 2022/10/07 18:26:00 - mmengine - INFO - Epoch(train) [53][240/2119] lr: 4.0000e-02 eta: 19:56:16 time: 0.3519 data_time: 0.0206 memory: 5826 grad_norm: 3.0718 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8553 loss: 2.8553 2022/10/07 18:26:07 - mmengine - INFO - Epoch(train) [53][260/2119] lr: 4.0000e-02 eta: 19:56:09 time: 0.3487 data_time: 0.0226 memory: 5826 grad_norm: 3.0987 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7629 loss: 2.7629 2022/10/07 18:26:13 - mmengine - INFO - Epoch(train) [53][280/2119] lr: 4.0000e-02 eta: 19:56:01 time: 0.3309 data_time: 0.0265 memory: 5826 grad_norm: 3.1561 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7225 loss: 2.7225 2022/10/07 18:26:20 - mmengine - INFO - Epoch(train) [53][300/2119] lr: 4.0000e-02 eta: 19:55:54 time: 0.3242 data_time: 0.0266 memory: 5826 grad_norm: 3.1680 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.6387 loss: 2.6387 2022/10/07 18:26:28 - mmengine - INFO - Epoch(train) [53][320/2119] lr: 4.0000e-02 eta: 19:55:49 time: 0.4090 data_time: 0.0206 memory: 5826 grad_norm: 3.1343 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9417 loss: 2.9417 2022/10/07 18:26:34 - mmengine - INFO - Epoch(train) [53][340/2119] lr: 4.0000e-02 eta: 19:55:40 time: 0.3018 data_time: 0.0254 memory: 5826 grad_norm: 3.1188 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6524 loss: 2.6524 2022/10/07 18:26:40 - mmengine - INFO - Epoch(train) [53][360/2119] lr: 4.0000e-02 eta: 19:55:33 time: 0.3211 data_time: 0.0237 memory: 5826 grad_norm: 3.1362 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7558 loss: 2.7558 2022/10/07 18:26:48 - mmengine - INFO - Epoch(train) [53][380/2119] lr: 4.0000e-02 eta: 19:55:26 time: 0.3645 data_time: 0.0219 memory: 5826 grad_norm: 3.1254 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6835 loss: 2.6835 2022/10/07 18:26:55 - mmengine - INFO - Epoch(train) [53][400/2119] lr: 4.0000e-02 eta: 19:55:19 time: 0.3388 data_time: 0.0216 memory: 5826 grad_norm: 3.1310 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7045 loss: 2.7045 2022/10/07 18:27:01 - mmengine - INFO - Epoch(train) [53][420/2119] lr: 4.0000e-02 eta: 19:55:11 time: 0.3179 data_time: 0.0243 memory: 5826 grad_norm: 3.1110 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9436 loss: 2.9436 2022/10/07 18:27:08 - mmengine - INFO - Epoch(train) [53][440/2119] lr: 4.0000e-02 eta: 19:55:05 time: 0.3547 data_time: 0.0205 memory: 5826 grad_norm: 3.0478 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7001 loss: 2.7001 2022/10/07 18:27:15 - mmengine - INFO - Epoch(train) [53][460/2119] lr: 4.0000e-02 eta: 19:54:58 time: 0.3475 data_time: 0.0182 memory: 5826 grad_norm: 3.0832 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8152 loss: 2.8152 2022/10/07 18:27:22 - mmengine - INFO - Epoch(train) [53][480/2119] lr: 4.0000e-02 eta: 19:54:52 time: 0.3746 data_time: 0.0272 memory: 5826 grad_norm: 3.1189 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9776 loss: 2.9776 2022/10/07 18:27:28 - mmengine - INFO - Epoch(train) [53][500/2119] lr: 4.0000e-02 eta: 19:54:43 time: 0.2943 data_time: 0.0219 memory: 5826 grad_norm: 3.0397 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5522 loss: 2.5522 2022/10/07 18:27:36 - mmengine - INFO - Epoch(train) [53][520/2119] lr: 4.0000e-02 eta: 19:54:38 time: 0.4043 data_time: 0.0257 memory: 5826 grad_norm: 3.1010 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5507 loss: 2.5507 2022/10/07 18:27:43 - mmengine - INFO - Epoch(train) [53][540/2119] lr: 4.0000e-02 eta: 19:54:30 time: 0.3129 data_time: 0.0216 memory: 5826 grad_norm: 3.1363 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7134 loss: 2.7134 2022/10/07 18:27:50 - mmengine - INFO - Epoch(train) [53][560/2119] lr: 4.0000e-02 eta: 19:54:23 time: 0.3521 data_time: 0.0254 memory: 5826 grad_norm: 3.1274 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7326 loss: 2.7326 2022/10/07 18:27:56 - mmengine - INFO - Epoch(train) [53][580/2119] lr: 4.0000e-02 eta: 19:54:15 time: 0.3131 data_time: 0.0207 memory: 5826 grad_norm: 3.0453 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7104 loss: 2.7104 2022/10/07 18:28:03 - mmengine - INFO - Epoch(train) [53][600/2119] lr: 4.0000e-02 eta: 19:54:09 time: 0.3717 data_time: 0.0186 memory: 5826 grad_norm: 3.1053 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6912 loss: 2.6912 2022/10/07 18:28:10 - mmengine - INFO - Epoch(train) [53][620/2119] lr: 4.0000e-02 eta: 19:54:01 time: 0.3021 data_time: 0.0221 memory: 5826 grad_norm: 3.0741 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5797 loss: 2.5797 2022/10/07 18:28:17 - mmengine - INFO - Epoch(train) [53][640/2119] lr: 4.0000e-02 eta: 19:53:55 time: 0.3770 data_time: 0.0193 memory: 5826 grad_norm: 3.0946 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8270 loss: 2.8270 2022/10/07 18:28:24 - mmengine - INFO - Epoch(train) [53][660/2119] lr: 4.0000e-02 eta: 19:53:48 time: 0.3328 data_time: 0.0240 memory: 5826 grad_norm: 3.1458 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7316 loss: 2.7316 2022/10/07 18:28:31 - mmengine - INFO - Epoch(train) [53][680/2119] lr: 4.0000e-02 eta: 19:53:40 time: 0.3415 data_time: 0.0251 memory: 5826 grad_norm: 3.1930 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8579 loss: 2.8579 2022/10/07 18:28:37 - mmengine - INFO - Epoch(train) [53][700/2119] lr: 4.0000e-02 eta: 19:53:32 time: 0.2991 data_time: 0.0218 memory: 5826 grad_norm: 3.0845 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9177 loss: 2.9177 2022/10/07 18:28:44 - mmengine - INFO - Epoch(train) [53][720/2119] lr: 4.0000e-02 eta: 19:53:26 time: 0.3713 data_time: 0.0221 memory: 5826 grad_norm: 3.1102 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8382 loss: 2.8382 2022/10/07 18:28:51 - mmengine - INFO - Epoch(train) [53][740/2119] lr: 4.0000e-02 eta: 19:53:20 time: 0.3645 data_time: 0.0215 memory: 5826 grad_norm: 3.0535 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8978 loss: 2.8978 2022/10/07 18:28:59 - mmengine - INFO - Epoch(train) [53][760/2119] lr: 4.0000e-02 eta: 19:53:14 time: 0.3743 data_time: 0.0233 memory: 5826 grad_norm: 3.1397 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7619 loss: 2.7619 2022/10/07 18:29:04 - mmengine - INFO - Epoch(train) [53][780/2119] lr: 4.0000e-02 eta: 19:53:04 time: 0.2792 data_time: 0.0299 memory: 5826 grad_norm: 3.1301 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8028 loss: 2.8028 2022/10/07 18:29:11 - mmengine - INFO - Epoch(train) [53][800/2119] lr: 4.0000e-02 eta: 19:52:57 time: 0.3370 data_time: 0.0196 memory: 5826 grad_norm: 3.1186 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6545 loss: 2.6545 2022/10/07 18:29:15 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 18:29:19 - mmengine - INFO - Epoch(train) [53][820/2119] lr: 4.0000e-02 eta: 19:52:51 time: 0.3777 data_time: 0.0237 memory: 5826 grad_norm: 3.0920 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6154 loss: 2.6154 2022/10/07 18:29:25 - mmengine - INFO - Epoch(train) [53][840/2119] lr: 4.0000e-02 eta: 19:52:44 time: 0.3393 data_time: 0.0218 memory: 5826 grad_norm: 3.0697 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9072 loss: 2.9072 2022/10/07 18:29:33 - mmengine - INFO - Epoch(train) [53][860/2119] lr: 4.0000e-02 eta: 19:52:38 time: 0.3647 data_time: 0.0192 memory: 5826 grad_norm: 3.1550 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8467 loss: 2.8467 2022/10/07 18:29:39 - mmengine - INFO - Epoch(train) [53][880/2119] lr: 4.0000e-02 eta: 19:52:31 time: 0.3356 data_time: 0.0211 memory: 5826 grad_norm: 3.0800 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9210 loss: 2.9210 2022/10/07 18:29:47 - mmengine - INFO - Epoch(train) [53][900/2119] lr: 4.0000e-02 eta: 19:52:25 time: 0.3824 data_time: 0.0218 memory: 5826 grad_norm: 3.0815 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9720 loss: 2.9720 2022/10/07 18:29:54 - mmengine - INFO - Epoch(train) [53][920/2119] lr: 4.0000e-02 eta: 19:52:17 time: 0.3271 data_time: 0.0272 memory: 5826 grad_norm: 3.1045 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6072 loss: 2.6072 2022/10/07 18:30:00 - mmengine - INFO - Epoch(train) [53][940/2119] lr: 4.0000e-02 eta: 19:52:09 time: 0.3070 data_time: 0.0230 memory: 5826 grad_norm: 3.0804 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7381 loss: 2.7381 2022/10/07 18:30:06 - mmengine - INFO - Epoch(train) [53][960/2119] lr: 4.0000e-02 eta: 19:52:01 time: 0.3249 data_time: 0.0242 memory: 5826 grad_norm: 3.0806 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.6073 loss: 2.6073 2022/10/07 18:30:14 - mmengine - INFO - Epoch(train) [53][980/2119] lr: 4.0000e-02 eta: 19:51:55 time: 0.3717 data_time: 0.0229 memory: 5826 grad_norm: 3.1042 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6784 loss: 2.6784 2022/10/07 18:30:20 - mmengine - INFO - Epoch(train) [53][1000/2119] lr: 4.0000e-02 eta: 19:51:48 time: 0.3390 data_time: 0.0260 memory: 5826 grad_norm: 3.0746 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8674 loss: 2.8674 2022/10/07 18:30:27 - mmengine - INFO - Epoch(train) [53][1020/2119] lr: 4.0000e-02 eta: 19:51:40 time: 0.3193 data_time: 0.0250 memory: 5826 grad_norm: 3.1277 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8352 loss: 2.8352 2022/10/07 18:30:34 - mmengine - INFO - Epoch(train) [53][1040/2119] lr: 4.0000e-02 eta: 19:51:33 time: 0.3373 data_time: 0.0247 memory: 5826 grad_norm: 3.1770 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7951 loss: 2.7951 2022/10/07 18:30:40 - mmengine - INFO - Epoch(train) [53][1060/2119] lr: 4.0000e-02 eta: 19:51:25 time: 0.3224 data_time: 0.0187 memory: 5826 grad_norm: 3.1274 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5429 loss: 2.5429 2022/10/07 18:30:48 - mmengine - INFO - Epoch(train) [53][1080/2119] lr: 4.0000e-02 eta: 19:51:19 time: 0.3779 data_time: 0.0207 memory: 5826 grad_norm: 3.1075 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6385 loss: 2.6385 2022/10/07 18:30:54 - mmengine - INFO - Epoch(train) [53][1100/2119] lr: 4.0000e-02 eta: 19:51:11 time: 0.2996 data_time: 0.0238 memory: 5826 grad_norm: 3.1016 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7838 loss: 2.7838 2022/10/07 18:31:01 - mmengine - INFO - Epoch(train) [53][1120/2119] lr: 4.0000e-02 eta: 19:51:04 time: 0.3444 data_time: 0.0256 memory: 5826 grad_norm: 3.1149 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9051 loss: 2.9051 2022/10/07 18:31:08 - mmengine - INFO - Epoch(train) [53][1140/2119] lr: 4.0000e-02 eta: 19:50:58 time: 0.3864 data_time: 0.0228 memory: 5826 grad_norm: 3.0716 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7228 loss: 2.7228 2022/10/07 18:31:15 - mmengine - INFO - Epoch(train) [53][1160/2119] lr: 4.0000e-02 eta: 19:50:51 time: 0.3228 data_time: 0.0253 memory: 5826 grad_norm: 3.0778 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7162 loss: 2.7162 2022/10/07 18:31:22 - mmengine - INFO - Epoch(train) [53][1180/2119] lr: 4.0000e-02 eta: 19:50:44 time: 0.3520 data_time: 0.0195 memory: 5826 grad_norm: 3.0852 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5597 loss: 2.5597 2022/10/07 18:31:29 - mmengine - INFO - Epoch(train) [53][1200/2119] lr: 4.0000e-02 eta: 19:50:37 time: 0.3506 data_time: 0.0210 memory: 5826 grad_norm: 3.0387 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6222 loss: 2.6222 2022/10/07 18:31:36 - mmengine - INFO - Epoch(train) [53][1220/2119] lr: 4.0000e-02 eta: 19:50:30 time: 0.3460 data_time: 0.0266 memory: 5826 grad_norm: 3.1505 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6558 loss: 2.6558 2022/10/07 18:31:43 - mmengine - INFO - Epoch(train) [53][1240/2119] lr: 4.0000e-02 eta: 19:50:24 time: 0.3661 data_time: 0.0174 memory: 5826 grad_norm: 3.1023 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7301 loss: 2.7301 2022/10/07 18:31:50 - mmengine - INFO - Epoch(train) [53][1260/2119] lr: 4.0000e-02 eta: 19:50:16 time: 0.3250 data_time: 0.0211 memory: 5826 grad_norm: 3.1013 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4618 loss: 2.4618 2022/10/07 18:31:58 - mmengine - INFO - Epoch(train) [53][1280/2119] lr: 4.0000e-02 eta: 19:50:11 time: 0.3992 data_time: 0.0214 memory: 5826 grad_norm: 3.1095 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5956 loss: 2.5956 2022/10/07 18:32:04 - mmengine - INFO - Epoch(train) [53][1300/2119] lr: 4.0000e-02 eta: 19:50:04 time: 0.3262 data_time: 0.0228 memory: 5826 grad_norm: 3.0719 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0913 loss: 3.0913 2022/10/07 18:32:11 - mmengine - INFO - Epoch(train) [53][1320/2119] lr: 4.0000e-02 eta: 19:49:57 time: 0.3549 data_time: 0.0225 memory: 5826 grad_norm: 3.1655 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7687 loss: 2.7687 2022/10/07 18:32:18 - mmengine - INFO - Epoch(train) [53][1340/2119] lr: 4.0000e-02 eta: 19:49:50 time: 0.3456 data_time: 0.0218 memory: 5826 grad_norm: 3.1702 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6356 loss: 2.6356 2022/10/07 18:32:25 - mmengine - INFO - Epoch(train) [53][1360/2119] lr: 4.0000e-02 eta: 19:49:44 time: 0.3653 data_time: 0.0229 memory: 5826 grad_norm: 3.1156 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7541 loss: 2.7541 2022/10/07 18:32:31 - mmengine - INFO - Epoch(train) [53][1380/2119] lr: 4.0000e-02 eta: 19:49:35 time: 0.2971 data_time: 0.0241 memory: 5826 grad_norm: 3.0976 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8561 loss: 2.8561 2022/10/07 18:32:39 - mmengine - INFO - Epoch(train) [53][1400/2119] lr: 4.0000e-02 eta: 19:49:29 time: 0.3707 data_time: 0.0205 memory: 5826 grad_norm: 3.1561 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5711 loss: 2.5711 2022/10/07 18:32:46 - mmengine - INFO - Epoch(train) [53][1420/2119] lr: 4.0000e-02 eta: 19:49:24 time: 0.3785 data_time: 0.0218 memory: 5826 grad_norm: 3.1037 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6603 loss: 2.6603 2022/10/07 18:32:53 - mmengine - INFO - Epoch(train) [53][1440/2119] lr: 4.0000e-02 eta: 19:49:16 time: 0.3344 data_time: 0.0191 memory: 5826 grad_norm: 3.0599 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9852 loss: 2.9852 2022/10/07 18:33:00 - mmengine - INFO - Epoch(train) [53][1460/2119] lr: 4.0000e-02 eta: 19:49:09 time: 0.3499 data_time: 0.0266 memory: 5826 grad_norm: 3.1728 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8230 loss: 2.8230 2022/10/07 18:33:06 - mmengine - INFO - Epoch(train) [53][1480/2119] lr: 4.0000e-02 eta: 19:49:02 time: 0.3228 data_time: 0.0214 memory: 5826 grad_norm: 3.1808 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8362 loss: 2.8362 2022/10/07 18:33:15 - mmengine - INFO - Epoch(train) [53][1500/2119] lr: 4.0000e-02 eta: 19:48:57 time: 0.4014 data_time: 0.0191 memory: 5826 grad_norm: 3.0379 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8708 loss: 2.8708 2022/10/07 18:33:21 - mmengine - INFO - Epoch(train) [53][1520/2119] lr: 4.0000e-02 eta: 19:48:49 time: 0.3145 data_time: 0.0237 memory: 5826 grad_norm: 3.0918 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7393 loss: 2.7393 2022/10/07 18:33:29 - mmengine - INFO - Epoch(train) [53][1540/2119] lr: 4.0000e-02 eta: 19:48:43 time: 0.3851 data_time: 0.0292 memory: 5826 grad_norm: 3.1595 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8748 loss: 2.8748 2022/10/07 18:33:36 - mmengine - INFO - Epoch(train) [53][1560/2119] lr: 4.0000e-02 eta: 19:48:37 time: 0.3587 data_time: 0.0222 memory: 5826 grad_norm: 3.1784 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6241 loss: 2.6241 2022/10/07 18:33:42 - mmengine - INFO - Epoch(train) [53][1580/2119] lr: 4.0000e-02 eta: 19:48:30 time: 0.3363 data_time: 0.0250 memory: 5826 grad_norm: 3.1294 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7039 loss: 2.7039 2022/10/07 18:33:49 - mmengine - INFO - Epoch(train) [53][1600/2119] lr: 4.0000e-02 eta: 19:48:22 time: 0.3186 data_time: 0.0245 memory: 5826 grad_norm: 3.0541 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8298 loss: 2.8298 2022/10/07 18:33:56 - mmengine - INFO - Epoch(train) [53][1620/2119] lr: 4.0000e-02 eta: 19:48:16 time: 0.3833 data_time: 0.0223 memory: 5826 grad_norm: 3.1530 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6619 loss: 2.6619 2022/10/07 18:34:03 - mmengine - INFO - Epoch(train) [53][1640/2119] lr: 4.0000e-02 eta: 19:48:08 time: 0.3062 data_time: 0.0249 memory: 5826 grad_norm: 3.1276 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.9726 loss: 2.9726 2022/10/07 18:34:11 - mmengine - INFO - Epoch(train) [53][1660/2119] lr: 4.0000e-02 eta: 19:48:03 time: 0.3983 data_time: 0.0229 memory: 5826 grad_norm: 3.0618 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7526 loss: 2.7526 2022/10/07 18:34:17 - mmengine - INFO - Epoch(train) [53][1680/2119] lr: 4.0000e-02 eta: 19:47:56 time: 0.3424 data_time: 0.0237 memory: 5826 grad_norm: 3.1052 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5044 loss: 2.5044 2022/10/07 18:34:25 - mmengine - INFO - Epoch(train) [53][1700/2119] lr: 4.0000e-02 eta: 19:47:50 time: 0.3901 data_time: 0.0233 memory: 5826 grad_norm: 3.1530 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9294 loss: 2.9294 2022/10/07 18:34:32 - mmengine - INFO - Epoch(train) [53][1720/2119] lr: 4.0000e-02 eta: 19:47:43 time: 0.3481 data_time: 0.0252 memory: 5826 grad_norm: 3.1264 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7017 loss: 2.7017 2022/10/07 18:34:39 - mmengine - INFO - Epoch(train) [53][1740/2119] lr: 4.0000e-02 eta: 19:47:36 time: 0.3337 data_time: 0.0225 memory: 5826 grad_norm: 3.1345 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8697 loss: 2.8697 2022/10/07 18:34:45 - mmengine - INFO - Epoch(train) [53][1760/2119] lr: 4.0000e-02 eta: 19:47:28 time: 0.3199 data_time: 0.0213 memory: 5826 grad_norm: 3.0750 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4962 loss: 2.4962 2022/10/07 18:34:53 - mmengine - INFO - Epoch(train) [53][1780/2119] lr: 4.0000e-02 eta: 19:47:22 time: 0.3778 data_time: 0.0209 memory: 5826 grad_norm: 3.0908 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7693 loss: 2.7693 2022/10/07 18:34:59 - mmengine - INFO - Epoch(train) [53][1800/2119] lr: 4.0000e-02 eta: 19:47:14 time: 0.3001 data_time: 0.0223 memory: 5826 grad_norm: 3.1114 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7660 loss: 2.7660 2022/10/07 18:35:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 18:35:06 - mmengine - INFO - Epoch(train) [53][1820/2119] lr: 4.0000e-02 eta: 19:47:08 time: 0.3732 data_time: 0.0220 memory: 5826 grad_norm: 3.1314 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8690 loss: 2.8690 2022/10/07 18:35:12 - mmengine - INFO - Epoch(train) [53][1840/2119] lr: 4.0000e-02 eta: 19:47:00 time: 0.3094 data_time: 0.0287 memory: 5826 grad_norm: 3.0942 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9638 loss: 2.9638 2022/10/07 18:35:20 - mmengine - INFO - Epoch(train) [53][1860/2119] lr: 4.0000e-02 eta: 19:46:54 time: 0.3841 data_time: 0.1155 memory: 5826 grad_norm: 3.1204 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.7967 loss: 2.7967 2022/10/07 18:35:27 - mmengine - INFO - Epoch(train) [53][1880/2119] lr: 4.0000e-02 eta: 19:46:46 time: 0.3244 data_time: 0.0164 memory: 5826 grad_norm: 3.0569 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0395 loss: 3.0395 2022/10/07 18:35:34 - mmengine - INFO - Epoch(train) [53][1900/2119] lr: 4.0000e-02 eta: 19:46:40 time: 0.3517 data_time: 0.0210 memory: 5826 grad_norm: 3.1398 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.8635 loss: 2.8635 2022/10/07 18:35:43 - mmengine - INFO - Epoch(train) [53][1920/2119] lr: 4.0000e-02 eta: 19:46:36 time: 0.4463 data_time: 0.0148 memory: 5826 grad_norm: 3.1655 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8648 loss: 2.8648 2022/10/07 18:35:49 - mmengine - INFO - Epoch(train) [53][1940/2119] lr: 4.0000e-02 eta: 19:46:29 time: 0.3212 data_time: 0.0194 memory: 5826 grad_norm: 3.0664 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7682 loss: 2.7682 2022/10/07 18:35:56 - mmengine - INFO - Epoch(train) [53][1960/2119] lr: 4.0000e-02 eta: 19:46:23 time: 0.3682 data_time: 0.0177 memory: 5826 grad_norm: 3.0498 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9468 loss: 2.9468 2022/10/07 18:36:04 - mmengine - INFO - Epoch(train) [53][1980/2119] lr: 4.0000e-02 eta: 19:46:18 time: 0.4001 data_time: 0.0222 memory: 5826 grad_norm: 3.1062 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.1077 loss: 3.1077 2022/10/07 18:36:11 - mmengine - INFO - Epoch(train) [53][2000/2119] lr: 4.0000e-02 eta: 19:46:10 time: 0.3282 data_time: 0.0193 memory: 5826 grad_norm: 3.0638 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6763 loss: 2.6763 2022/10/07 18:36:18 - mmengine - INFO - Epoch(train) [53][2020/2119] lr: 4.0000e-02 eta: 19:46:02 time: 0.3265 data_time: 0.0217 memory: 5826 grad_norm: 3.0645 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8342 loss: 2.8342 2022/10/07 18:36:25 - mmengine - INFO - Epoch(train) [53][2040/2119] lr: 4.0000e-02 eta: 19:45:56 time: 0.3483 data_time: 0.0282 memory: 5826 grad_norm: 3.0564 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6821 loss: 2.6821 2022/10/07 18:36:31 - mmengine - INFO - Epoch(train) [53][2060/2119] lr: 4.0000e-02 eta: 19:45:48 time: 0.3401 data_time: 0.0218 memory: 5826 grad_norm: 3.0633 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8174 loss: 2.8174 2022/10/07 18:36:39 - mmengine - INFO - Epoch(train) [53][2080/2119] lr: 4.0000e-02 eta: 19:45:42 time: 0.3702 data_time: 0.0155 memory: 5826 grad_norm: 3.0843 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6730 loss: 2.6730 2022/10/07 18:36:45 - mmengine - INFO - Epoch(train) [53][2100/2119] lr: 4.0000e-02 eta: 19:45:35 time: 0.3342 data_time: 0.0234 memory: 5826 grad_norm: 3.1518 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9345 loss: 2.9345 2022/10/07 18:36:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 18:36:51 - mmengine - INFO - Epoch(train) [53][2119/2119] lr: 4.0000e-02 eta: 19:45:35 time: 0.2699 data_time: 0.0146 memory: 5826 grad_norm: 3.1846 top1_acc: 0.7000 top5_acc: 0.9000 loss_cls: 2.8473 loss: 2.8473 2022/10/07 18:37:00 - mmengine - INFO - Epoch(train) [54][20/2119] lr: 4.0000e-02 eta: 19:45:14 time: 0.4779 data_time: 0.1213 memory: 5826 grad_norm: 3.1564 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8749 loss: 2.8749 2022/10/07 18:37:07 - mmengine - INFO - Epoch(train) [54][40/2119] lr: 4.0000e-02 eta: 19:45:07 time: 0.3388 data_time: 0.0172 memory: 5826 grad_norm: 3.1128 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7821 loss: 2.7821 2022/10/07 18:37:14 - mmengine - INFO - Epoch(train) [54][60/2119] lr: 4.0000e-02 eta: 19:45:01 time: 0.3767 data_time: 0.0264 memory: 5826 grad_norm: 3.0652 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8162 loss: 2.8162 2022/10/07 18:37:21 - mmengine - INFO - Epoch(train) [54][80/2119] lr: 4.0000e-02 eta: 19:44:54 time: 0.3321 data_time: 0.0193 memory: 5826 grad_norm: 3.0893 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7190 loss: 2.7190 2022/10/07 18:37:28 - mmengine - INFO - Epoch(train) [54][100/2119] lr: 4.0000e-02 eta: 19:44:47 time: 0.3369 data_time: 0.0228 memory: 5826 grad_norm: 3.0702 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7296 loss: 2.7296 2022/10/07 18:37:34 - mmengine - INFO - Epoch(train) [54][120/2119] lr: 4.0000e-02 eta: 19:44:39 time: 0.3227 data_time: 0.0242 memory: 5826 grad_norm: 3.1198 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7064 loss: 2.7064 2022/10/07 18:37:43 - mmengine - INFO - Epoch(train) [54][140/2119] lr: 4.0000e-02 eta: 19:44:35 time: 0.4226 data_time: 0.0196 memory: 5826 grad_norm: 3.0496 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0212 loss: 3.0212 2022/10/07 18:37:49 - mmengine - INFO - Epoch(train) [54][160/2119] lr: 4.0000e-02 eta: 19:44:27 time: 0.3301 data_time: 0.0192 memory: 5826 grad_norm: 3.0990 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7023 loss: 2.7023 2022/10/07 18:37:57 - mmengine - INFO - Epoch(train) [54][180/2119] lr: 4.0000e-02 eta: 19:44:21 time: 0.3745 data_time: 0.0228 memory: 5826 grad_norm: 3.1167 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5582 loss: 2.5582 2022/10/07 18:38:02 - mmengine - INFO - Epoch(train) [54][200/2119] lr: 4.0000e-02 eta: 19:44:12 time: 0.2799 data_time: 0.0243 memory: 5826 grad_norm: 3.1688 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7118 loss: 2.7118 2022/10/07 18:38:10 - mmengine - INFO - Epoch(train) [54][220/2119] lr: 4.0000e-02 eta: 19:44:05 time: 0.3556 data_time: 0.0298 memory: 5826 grad_norm: 3.1079 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5362 loss: 2.5362 2022/10/07 18:38:17 - mmengine - INFO - Epoch(train) [54][240/2119] lr: 4.0000e-02 eta: 19:43:59 time: 0.3557 data_time: 0.0200 memory: 5826 grad_norm: 3.0955 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.5544 loss: 2.5544 2022/10/07 18:38:24 - mmengine - INFO - Epoch(train) [54][260/2119] lr: 4.0000e-02 eta: 19:43:52 time: 0.3536 data_time: 0.0315 memory: 5826 grad_norm: 3.0985 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6836 loss: 2.6836 2022/10/07 18:38:30 - mmengine - INFO - Epoch(train) [54][280/2119] lr: 4.0000e-02 eta: 19:43:44 time: 0.3194 data_time: 0.0272 memory: 5826 grad_norm: 3.1709 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8273 loss: 2.8273 2022/10/07 18:38:37 - mmengine - INFO - Epoch(train) [54][300/2119] lr: 4.0000e-02 eta: 19:43:38 time: 0.3483 data_time: 0.0223 memory: 5826 grad_norm: 3.0920 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8724 loss: 2.8724 2022/10/07 18:38:44 - mmengine - INFO - Epoch(train) [54][320/2119] lr: 4.0000e-02 eta: 19:43:30 time: 0.3235 data_time: 0.0260 memory: 5826 grad_norm: 3.0992 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8824 loss: 2.8824 2022/10/07 18:38:51 - mmengine - INFO - Epoch(train) [54][340/2119] lr: 4.0000e-02 eta: 19:43:24 time: 0.3663 data_time: 0.0205 memory: 5826 grad_norm: 3.0747 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8756 loss: 2.8756 2022/10/07 18:38:58 - mmengine - INFO - Epoch(train) [54][360/2119] lr: 4.0000e-02 eta: 19:43:17 time: 0.3427 data_time: 0.0188 memory: 5826 grad_norm: 3.1429 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7757 loss: 2.7757 2022/10/07 18:39:05 - mmengine - INFO - Epoch(train) [54][380/2119] lr: 4.0000e-02 eta: 19:43:11 time: 0.3713 data_time: 0.0258 memory: 5826 grad_norm: 3.0819 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6476 loss: 2.6476 2022/10/07 18:39:12 - mmengine - INFO - Epoch(train) [54][400/2119] lr: 4.0000e-02 eta: 19:43:03 time: 0.3199 data_time: 0.0274 memory: 5826 grad_norm: 3.0782 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6579 loss: 2.6579 2022/10/07 18:39:20 - mmengine - INFO - Epoch(train) [54][420/2119] lr: 4.0000e-02 eta: 19:42:58 time: 0.4050 data_time: 0.0244 memory: 5826 grad_norm: 3.1822 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8976 loss: 2.8976 2022/10/07 18:39:26 - mmengine - INFO - Epoch(train) [54][440/2119] lr: 4.0000e-02 eta: 19:42:50 time: 0.3082 data_time: 0.0213 memory: 5826 grad_norm: 3.1511 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.0270 loss: 3.0270 2022/10/07 18:39:34 - mmengine - INFO - Epoch(train) [54][460/2119] lr: 4.0000e-02 eta: 19:42:45 time: 0.4150 data_time: 0.0229 memory: 5826 grad_norm: 3.0968 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6053 loss: 2.6053 2022/10/07 18:39:40 - mmengine - INFO - Epoch(train) [54][480/2119] lr: 4.0000e-02 eta: 19:42:37 time: 0.2987 data_time: 0.0222 memory: 5826 grad_norm: 3.1020 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7606 loss: 2.7606 2022/10/07 18:39:47 - mmengine - INFO - Epoch(train) [54][500/2119] lr: 4.0000e-02 eta: 19:42:30 time: 0.3526 data_time: 0.0191 memory: 5826 grad_norm: 3.0979 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5468 loss: 2.5468 2022/10/07 18:39:54 - mmengine - INFO - Epoch(train) [54][520/2119] lr: 4.0000e-02 eta: 19:42:23 time: 0.3341 data_time: 0.0233 memory: 5826 grad_norm: 3.1346 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7100 loss: 2.7100 2022/10/07 18:40:01 - mmengine - INFO - Epoch(train) [54][540/2119] lr: 4.0000e-02 eta: 19:42:15 time: 0.3425 data_time: 0.0253 memory: 5826 grad_norm: 3.0935 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.7579 loss: 2.7579 2022/10/07 18:40:08 - mmengine - INFO - Epoch(train) [54][560/2119] lr: 4.0000e-02 eta: 19:42:08 time: 0.3365 data_time: 0.0229 memory: 5826 grad_norm: 3.0981 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6016 loss: 2.6016 2022/10/07 18:40:14 - mmengine - INFO - Epoch(train) [54][580/2119] lr: 4.0000e-02 eta: 19:42:00 time: 0.3154 data_time: 0.0257 memory: 5826 grad_norm: 3.0484 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8642 loss: 2.8642 2022/10/07 18:40:22 - mmengine - INFO - Epoch(train) [54][600/2119] lr: 4.0000e-02 eta: 19:41:55 time: 0.3936 data_time: 0.0256 memory: 5826 grad_norm: 3.0564 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6985 loss: 2.6985 2022/10/07 18:40:28 - mmengine - INFO - Epoch(train) [54][620/2119] lr: 4.0000e-02 eta: 19:41:48 time: 0.3363 data_time: 0.0215 memory: 5826 grad_norm: 3.1471 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8387 loss: 2.8387 2022/10/07 18:40:36 - mmengine - INFO - Epoch(train) [54][640/2119] lr: 4.0000e-02 eta: 19:41:42 time: 0.3792 data_time: 0.0257 memory: 5826 grad_norm: 3.1323 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6647 loss: 2.6647 2022/10/07 18:40:43 - mmengine - INFO - Epoch(train) [54][660/2119] lr: 4.0000e-02 eta: 19:41:34 time: 0.3245 data_time: 0.0229 memory: 5826 grad_norm: 3.0976 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7781 loss: 2.7781 2022/10/07 18:40:49 - mmengine - INFO - Epoch(train) [54][680/2119] lr: 4.0000e-02 eta: 19:41:27 time: 0.3307 data_time: 0.0184 memory: 5826 grad_norm: 3.1068 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7747 loss: 2.7747 2022/10/07 18:40:53 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 18:40:56 - mmengine - INFO - Epoch(train) [54][700/2119] lr: 4.0000e-02 eta: 19:41:20 time: 0.3468 data_time: 0.0222 memory: 5826 grad_norm: 3.1513 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6095 loss: 2.6095 2022/10/07 18:41:04 - mmengine - INFO - Epoch(train) [54][720/2119] lr: 4.0000e-02 eta: 19:41:14 time: 0.3730 data_time: 0.0202 memory: 5826 grad_norm: 3.1421 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9127 loss: 2.9127 2022/10/07 18:41:10 - mmengine - INFO - Epoch(train) [54][740/2119] lr: 4.0000e-02 eta: 19:41:07 time: 0.3436 data_time: 0.0234 memory: 5826 grad_norm: 3.0314 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9341 loss: 2.9341 2022/10/07 18:41:18 - mmengine - INFO - Epoch(train) [54][760/2119] lr: 4.0000e-02 eta: 19:41:00 time: 0.3537 data_time: 0.0178 memory: 5826 grad_norm: 3.0704 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9612 loss: 2.9612 2022/10/07 18:41:24 - mmengine - INFO - Epoch(train) [54][780/2119] lr: 4.0000e-02 eta: 19:40:53 time: 0.3430 data_time: 0.0204 memory: 5826 grad_norm: 3.0890 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7085 loss: 2.7085 2022/10/07 18:41:31 - mmengine - INFO - Epoch(train) [54][800/2119] lr: 4.0000e-02 eta: 19:40:46 time: 0.3398 data_time: 0.0159 memory: 5826 grad_norm: 3.1314 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8114 loss: 2.8114 2022/10/07 18:41:38 - mmengine - INFO - Epoch(train) [54][820/2119] lr: 4.0000e-02 eta: 19:40:38 time: 0.3214 data_time: 0.0200 memory: 5826 grad_norm: 3.1337 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7300 loss: 2.7300 2022/10/07 18:41:45 - mmengine - INFO - Epoch(train) [54][840/2119] lr: 4.0000e-02 eta: 19:40:32 time: 0.3535 data_time: 0.0164 memory: 5826 grad_norm: 3.0692 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6911 loss: 2.6911 2022/10/07 18:41:51 - mmengine - INFO - Epoch(train) [54][860/2119] lr: 4.0000e-02 eta: 19:40:24 time: 0.3248 data_time: 0.0237 memory: 5826 grad_norm: 3.0511 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5689 loss: 2.5689 2022/10/07 18:41:59 - mmengine - INFO - Epoch(train) [54][880/2119] lr: 4.0000e-02 eta: 19:40:18 time: 0.3736 data_time: 0.0195 memory: 5826 grad_norm: 3.1377 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6284 loss: 2.6284 2022/10/07 18:42:05 - mmengine - INFO - Epoch(train) [54][900/2119] lr: 4.0000e-02 eta: 19:40:10 time: 0.3247 data_time: 0.0225 memory: 5826 grad_norm: 3.1039 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7279 loss: 2.7279 2022/10/07 18:42:12 - mmengine - INFO - Epoch(train) [54][920/2119] lr: 4.0000e-02 eta: 19:40:03 time: 0.3325 data_time: 0.0186 memory: 5826 grad_norm: 3.1067 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9136 loss: 2.9136 2022/10/07 18:42:19 - mmengine - INFO - Epoch(train) [54][940/2119] lr: 4.0000e-02 eta: 19:39:56 time: 0.3448 data_time: 0.0314 memory: 5826 grad_norm: 3.1157 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8720 loss: 2.8720 2022/10/07 18:42:25 - mmengine - INFO - Epoch(train) [54][960/2119] lr: 4.0000e-02 eta: 19:39:49 time: 0.3298 data_time: 0.0238 memory: 5826 grad_norm: 3.1779 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.6418 loss: 2.6418 2022/10/07 18:42:32 - mmengine - INFO - Epoch(train) [54][980/2119] lr: 4.0000e-02 eta: 19:39:42 time: 0.3452 data_time: 0.0219 memory: 5826 grad_norm: 3.0888 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.3363 loss: 2.3363 2022/10/07 18:42:40 - mmengine - INFO - Epoch(train) [54][1000/2119] lr: 4.0000e-02 eta: 19:39:36 time: 0.3834 data_time: 0.0200 memory: 5826 grad_norm: 2.9968 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4835 loss: 2.4835 2022/10/07 18:42:46 - mmengine - INFO - Epoch(train) [54][1020/2119] lr: 4.0000e-02 eta: 19:39:28 time: 0.3215 data_time: 0.0193 memory: 5826 grad_norm: 3.0870 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6783 loss: 2.6783 2022/10/07 18:42:54 - mmengine - INFO - Epoch(train) [54][1040/2119] lr: 4.0000e-02 eta: 19:39:22 time: 0.3632 data_time: 0.0191 memory: 5826 grad_norm: 3.0754 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4944 loss: 2.4944 2022/10/07 18:43:00 - mmengine - INFO - Epoch(train) [54][1060/2119] lr: 4.0000e-02 eta: 19:39:14 time: 0.3325 data_time: 0.0217 memory: 5826 grad_norm: 3.1368 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.8160 loss: 2.8160 2022/10/07 18:43:06 - mmengine - INFO - Epoch(train) [54][1080/2119] lr: 4.0000e-02 eta: 19:39:06 time: 0.3043 data_time: 0.0273 memory: 5826 grad_norm: 3.1155 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5866 loss: 2.5866 2022/10/07 18:43:14 - mmengine - INFO - Epoch(train) [54][1100/2119] lr: 4.0000e-02 eta: 19:39:00 time: 0.3779 data_time: 0.0275 memory: 5826 grad_norm: 3.1272 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5246 loss: 2.5246 2022/10/07 18:43:21 - mmengine - INFO - Epoch(train) [54][1120/2119] lr: 4.0000e-02 eta: 19:38:53 time: 0.3307 data_time: 0.0227 memory: 5826 grad_norm: 3.1206 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8457 loss: 2.8457 2022/10/07 18:43:27 - mmengine - INFO - Epoch(train) [54][1140/2119] lr: 4.0000e-02 eta: 19:38:45 time: 0.3312 data_time: 0.0241 memory: 5826 grad_norm: 3.0903 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5784 loss: 2.5784 2022/10/07 18:43:34 - mmengine - INFO - Epoch(train) [54][1160/2119] lr: 4.0000e-02 eta: 19:38:38 time: 0.3361 data_time: 0.0241 memory: 5826 grad_norm: 3.0566 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7516 loss: 2.7516 2022/10/07 18:43:41 - mmengine - INFO - Epoch(train) [54][1180/2119] lr: 4.0000e-02 eta: 19:38:31 time: 0.3468 data_time: 0.0198 memory: 5826 grad_norm: 3.0940 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6950 loss: 2.6950 2022/10/07 18:43:48 - mmengine - INFO - Epoch(train) [54][1200/2119] lr: 4.0000e-02 eta: 19:38:25 time: 0.3548 data_time: 0.0279 memory: 5826 grad_norm: 3.0766 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8192 loss: 2.8192 2022/10/07 18:43:55 - mmengine - INFO - Epoch(train) [54][1220/2119] lr: 4.0000e-02 eta: 19:38:18 time: 0.3491 data_time: 0.0237 memory: 5826 grad_norm: 3.0602 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9600 loss: 2.9600 2022/10/07 18:44:01 - mmengine - INFO - Epoch(train) [54][1240/2119] lr: 4.0000e-02 eta: 19:38:10 time: 0.3217 data_time: 0.0256 memory: 5826 grad_norm: 3.0686 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5177 loss: 2.5177 2022/10/07 18:44:08 - mmengine - INFO - Epoch(train) [54][1260/2119] lr: 4.0000e-02 eta: 19:38:03 time: 0.3464 data_time: 0.0220 memory: 5826 grad_norm: 3.0967 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.7659 loss: 2.7659 2022/10/07 18:44:15 - mmengine - INFO - Epoch(train) [54][1280/2119] lr: 4.0000e-02 eta: 19:37:56 time: 0.3392 data_time: 0.0221 memory: 5826 grad_norm: 3.0338 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6311 loss: 2.6311 2022/10/07 18:44:22 - mmengine - INFO - Epoch(train) [54][1300/2119] lr: 4.0000e-02 eta: 19:37:49 time: 0.3418 data_time: 0.0184 memory: 5826 grad_norm: 3.1221 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0288 loss: 3.0288 2022/10/07 18:44:28 - mmengine - INFO - Epoch(train) [54][1320/2119] lr: 4.0000e-02 eta: 19:37:41 time: 0.3264 data_time: 0.0247 memory: 5826 grad_norm: 3.1489 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8214 loss: 2.8214 2022/10/07 18:44:35 - mmengine - INFO - Epoch(train) [54][1340/2119] lr: 4.0000e-02 eta: 19:37:34 time: 0.3383 data_time: 0.0344 memory: 5826 grad_norm: 3.1137 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.8134 loss: 2.8134 2022/10/07 18:44:42 - mmengine - INFO - Epoch(train) [54][1360/2119] lr: 4.0000e-02 eta: 19:37:27 time: 0.3401 data_time: 0.0208 memory: 5826 grad_norm: 3.0746 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8258 loss: 2.8258 2022/10/07 18:44:49 - mmengine - INFO - Epoch(train) [54][1380/2119] lr: 4.0000e-02 eta: 19:37:20 time: 0.3456 data_time: 0.0238 memory: 5826 grad_norm: 3.1282 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7485 loss: 2.7485 2022/10/07 18:44:56 - mmengine - INFO - Epoch(train) [54][1400/2119] lr: 4.0000e-02 eta: 19:37:13 time: 0.3539 data_time: 0.0301 memory: 5826 grad_norm: 3.0818 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9864 loss: 2.9864 2022/10/07 18:45:03 - mmengine - INFO - Epoch(train) [54][1420/2119] lr: 4.0000e-02 eta: 19:37:07 time: 0.3720 data_time: 0.0213 memory: 5826 grad_norm: 3.0897 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8054 loss: 2.8054 2022/10/07 18:45:10 - mmengine - INFO - Epoch(train) [54][1440/2119] lr: 4.0000e-02 eta: 19:36:59 time: 0.3191 data_time: 0.0264 memory: 5826 grad_norm: 3.0989 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9532 loss: 2.9532 2022/10/07 18:45:17 - mmengine - INFO - Epoch(train) [54][1460/2119] lr: 4.0000e-02 eta: 19:36:53 time: 0.3661 data_time: 0.0208 memory: 5826 grad_norm: 3.1406 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6064 loss: 2.6064 2022/10/07 18:45:24 - mmengine - INFO - Epoch(train) [54][1480/2119] lr: 4.0000e-02 eta: 19:36:47 time: 0.3569 data_time: 0.0215 memory: 5826 grad_norm: 3.1494 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9317 loss: 2.9317 2022/10/07 18:45:31 - mmengine - INFO - Epoch(train) [54][1500/2119] lr: 4.0000e-02 eta: 19:36:40 time: 0.3595 data_time: 0.0238 memory: 5826 grad_norm: 3.0746 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4861 loss: 2.4861 2022/10/07 18:45:39 - mmengine - INFO - Epoch(train) [54][1520/2119] lr: 4.0000e-02 eta: 19:36:34 time: 0.3716 data_time: 0.0225 memory: 5826 grad_norm: 3.0495 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6480 loss: 2.6480 2022/10/07 18:45:45 - mmengine - INFO - Epoch(train) [54][1540/2119] lr: 4.0000e-02 eta: 19:36:26 time: 0.3199 data_time: 0.0200 memory: 5826 grad_norm: 3.1343 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6414 loss: 2.6414 2022/10/07 18:45:52 - mmengine - INFO - Epoch(train) [54][1560/2119] lr: 4.0000e-02 eta: 19:36:19 time: 0.3382 data_time: 0.0257 memory: 5826 grad_norm: 3.0962 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9034 loss: 2.9034 2022/10/07 18:45:59 - mmengine - INFO - Epoch(train) [54][1580/2119] lr: 4.0000e-02 eta: 19:36:12 time: 0.3388 data_time: 0.0258 memory: 5826 grad_norm: 3.0868 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6418 loss: 2.6418 2022/10/07 18:46:06 - mmengine - INFO - Epoch(train) [54][1600/2119] lr: 4.0000e-02 eta: 19:36:05 time: 0.3449 data_time: 0.0239 memory: 5826 grad_norm: 3.1635 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6180 loss: 2.6180 2022/10/07 18:46:12 - mmengine - INFO - Epoch(train) [54][1620/2119] lr: 4.0000e-02 eta: 19:35:57 time: 0.3263 data_time: 0.0187 memory: 5826 grad_norm: 3.1031 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7001 loss: 2.7001 2022/10/07 18:46:20 - mmengine - INFO - Epoch(train) [54][1640/2119] lr: 4.0000e-02 eta: 19:35:52 time: 0.3856 data_time: 0.0208 memory: 5826 grad_norm: 3.0970 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8032 loss: 2.8032 2022/10/07 18:46:26 - mmengine - INFO - Epoch(train) [54][1660/2119] lr: 4.0000e-02 eta: 19:35:44 time: 0.3149 data_time: 0.0243 memory: 5826 grad_norm: 3.2111 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7780 loss: 2.7780 2022/10/07 18:46:35 - mmengine - INFO - Epoch(train) [54][1680/2119] lr: 4.0000e-02 eta: 19:35:40 time: 0.4193 data_time: 0.0212 memory: 5826 grad_norm: 3.0915 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7555 loss: 2.7555 2022/10/07 18:46:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 18:46:42 - mmengine - INFO - Epoch(train) [54][1700/2119] lr: 4.0000e-02 eta: 19:35:33 time: 0.3404 data_time: 0.0226 memory: 5826 grad_norm: 3.0875 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8991 loss: 2.8991 2022/10/07 18:46:48 - mmengine - INFO - Epoch(train) [54][1720/2119] lr: 4.0000e-02 eta: 19:35:25 time: 0.3279 data_time: 0.0230 memory: 5826 grad_norm: 3.0503 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6082 loss: 2.6082 2022/10/07 18:46:54 - mmengine - INFO - Epoch(train) [54][1740/2119] lr: 4.0000e-02 eta: 19:35:17 time: 0.3187 data_time: 0.0214 memory: 5826 grad_norm: 3.1259 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7517 loss: 2.7517 2022/10/07 18:47:01 - mmengine - INFO - Epoch(train) [54][1760/2119] lr: 4.0000e-02 eta: 19:35:09 time: 0.3160 data_time: 0.0268 memory: 5826 grad_norm: 3.0695 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8508 loss: 2.8508 2022/10/07 18:47:08 - mmengine - INFO - Epoch(train) [54][1780/2119] lr: 4.0000e-02 eta: 19:35:03 time: 0.3593 data_time: 0.0216 memory: 5826 grad_norm: 3.0549 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8727 loss: 2.8727 2022/10/07 18:47:16 - mmengine - INFO - Epoch(train) [54][1800/2119] lr: 4.0000e-02 eta: 19:34:58 time: 0.4071 data_time: 0.0237 memory: 5826 grad_norm: 3.0677 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7099 loss: 2.7099 2022/10/07 18:47:23 - mmengine - INFO - Epoch(train) [54][1820/2119] lr: 4.0000e-02 eta: 19:34:50 time: 0.3296 data_time: 0.0236 memory: 5826 grad_norm: 3.1256 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9260 loss: 2.9260 2022/10/07 18:47:30 - mmengine - INFO - Epoch(train) [54][1840/2119] lr: 4.0000e-02 eta: 19:34:45 time: 0.3762 data_time: 0.0227 memory: 5826 grad_norm: 3.0909 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9501 loss: 2.9501 2022/10/07 18:47:37 - mmengine - INFO - Epoch(train) [54][1860/2119] lr: 4.0000e-02 eta: 19:34:37 time: 0.3355 data_time: 0.0264 memory: 5826 grad_norm: 3.0492 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8535 loss: 2.8535 2022/10/07 18:47:44 - mmengine - INFO - Epoch(train) [54][1880/2119] lr: 4.0000e-02 eta: 19:34:31 time: 0.3668 data_time: 0.0224 memory: 5826 grad_norm: 3.1380 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8711 loss: 2.8711 2022/10/07 18:47:50 - mmengine - INFO - Epoch(train) [54][1900/2119] lr: 4.0000e-02 eta: 19:34:22 time: 0.2998 data_time: 0.0196 memory: 5826 grad_norm: 3.1305 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8194 loss: 2.8194 2022/10/07 18:47:58 - mmengine - INFO - Epoch(train) [54][1920/2119] lr: 4.0000e-02 eta: 19:34:18 time: 0.4092 data_time: 0.0202 memory: 5826 grad_norm: 3.0658 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7521 loss: 2.7521 2022/10/07 18:48:06 - mmengine - INFO - Epoch(train) [54][1940/2119] lr: 4.0000e-02 eta: 19:34:11 time: 0.3520 data_time: 0.0299 memory: 5826 grad_norm: 3.1412 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8321 loss: 2.8321 2022/10/07 18:48:12 - mmengine - INFO - Epoch(train) [54][1960/2119] lr: 4.0000e-02 eta: 19:34:04 time: 0.3423 data_time: 0.0209 memory: 5826 grad_norm: 3.1475 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7667 loss: 2.7667 2022/10/07 18:48:19 - mmengine - INFO - Epoch(train) [54][1980/2119] lr: 4.0000e-02 eta: 19:33:57 time: 0.3310 data_time: 0.0201 memory: 5826 grad_norm: 3.0662 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8589 loss: 2.8589 2022/10/07 18:48:26 - mmengine - INFO - Epoch(train) [54][2000/2119] lr: 4.0000e-02 eta: 19:33:50 time: 0.3462 data_time: 0.0210 memory: 5826 grad_norm: 3.0702 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8797 loss: 2.8797 2022/10/07 18:48:32 - mmengine - INFO - Epoch(train) [54][2020/2119] lr: 4.0000e-02 eta: 19:33:42 time: 0.3142 data_time: 0.0231 memory: 5826 grad_norm: 3.1273 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8706 loss: 2.8706 2022/10/07 18:48:40 - mmengine - INFO - Epoch(train) [54][2040/2119] lr: 4.0000e-02 eta: 19:33:36 time: 0.3826 data_time: 0.0174 memory: 5826 grad_norm: 3.1472 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7862 loss: 2.7862 2022/10/07 18:48:47 - mmengine - INFO - Epoch(train) [54][2060/2119] lr: 4.0000e-02 eta: 19:33:29 time: 0.3457 data_time: 0.0188 memory: 5826 grad_norm: 3.1010 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8543 loss: 2.8543 2022/10/07 18:48:54 - mmengine - INFO - Epoch(train) [54][2080/2119] lr: 4.0000e-02 eta: 19:33:23 time: 0.3662 data_time: 0.0203 memory: 5826 grad_norm: 3.1137 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9468 loss: 2.9468 2022/10/07 18:49:01 - mmengine - INFO - Epoch(train) [54][2100/2119] lr: 4.0000e-02 eta: 19:33:16 time: 0.3351 data_time: 0.0226 memory: 5826 grad_norm: 3.0917 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7711 loss: 2.7711 2022/10/07 18:49:06 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 18:49:06 - mmengine - INFO - Epoch(train) [54][2119/2119] lr: 4.0000e-02 eta: 19:33:16 time: 0.2725 data_time: 0.0138 memory: 5826 grad_norm: 3.1298 top1_acc: 0.4000 top5_acc: 0.6000 loss_cls: 2.9139 loss: 2.9139 2022/10/07 18:49:16 - mmengine - INFO - Epoch(train) [55][20/2119] lr: 4.0000e-02 eta: 19:32:56 time: 0.5043 data_time: 0.1215 memory: 5826 grad_norm: 3.0949 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6693 loss: 2.6693 2022/10/07 18:49:23 - mmengine - INFO - Epoch(train) [55][40/2119] lr: 4.0000e-02 eta: 19:32:49 time: 0.3536 data_time: 0.0210 memory: 5826 grad_norm: 3.1169 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.8837 loss: 2.8837 2022/10/07 18:49:30 - mmengine - INFO - Epoch(train) [55][60/2119] lr: 4.0000e-02 eta: 19:32:42 time: 0.3228 data_time: 0.0301 memory: 5826 grad_norm: 3.0524 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8629 loss: 2.8629 2022/10/07 18:49:37 - mmengine - INFO - Epoch(train) [55][80/2119] lr: 4.0000e-02 eta: 19:32:34 time: 0.3393 data_time: 0.0163 memory: 5826 grad_norm: 3.0806 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7869 loss: 2.7869 2022/10/07 18:49:44 - mmengine - INFO - Epoch(train) [55][100/2119] lr: 4.0000e-02 eta: 19:32:29 time: 0.3892 data_time: 0.0225 memory: 5826 grad_norm: 3.1284 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.5708 loss: 2.5708 2022/10/07 18:49:50 - mmengine - INFO - Epoch(train) [55][120/2119] lr: 4.0000e-02 eta: 19:32:21 time: 0.3075 data_time: 0.0214 memory: 5826 grad_norm: 3.1271 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9883 loss: 2.9883 2022/10/07 18:49:58 - mmengine - INFO - Epoch(train) [55][140/2119] lr: 4.0000e-02 eta: 19:32:15 time: 0.3729 data_time: 0.0265 memory: 5826 grad_norm: 3.0922 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7356 loss: 2.7356 2022/10/07 18:50:05 - mmengine - INFO - Epoch(train) [55][160/2119] lr: 4.0000e-02 eta: 19:32:08 time: 0.3456 data_time: 0.0249 memory: 5826 grad_norm: 3.1564 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9426 loss: 2.9426 2022/10/07 18:50:12 - mmengine - INFO - Epoch(train) [55][180/2119] lr: 4.0000e-02 eta: 19:32:01 time: 0.3411 data_time: 0.0225 memory: 5826 grad_norm: 3.1596 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6673 loss: 2.6673 2022/10/07 18:50:19 - mmengine - INFO - Epoch(train) [55][200/2119] lr: 4.0000e-02 eta: 19:31:54 time: 0.3485 data_time: 0.0409 memory: 5826 grad_norm: 3.0590 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6797 loss: 2.6797 2022/10/07 18:50:25 - mmengine - INFO - Epoch(train) [55][220/2119] lr: 4.0000e-02 eta: 19:31:47 time: 0.3412 data_time: 0.0218 memory: 5826 grad_norm: 3.0748 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5315 loss: 2.5315 2022/10/07 18:50:33 - mmengine - INFO - Epoch(train) [55][240/2119] lr: 4.0000e-02 eta: 19:31:41 time: 0.3669 data_time: 0.0192 memory: 5826 grad_norm: 3.0814 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5618 loss: 2.5618 2022/10/07 18:50:40 - mmengine - INFO - Epoch(train) [55][260/2119] lr: 4.0000e-02 eta: 19:31:34 time: 0.3452 data_time: 0.0216 memory: 5826 grad_norm: 3.0761 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7905 loss: 2.7905 2022/10/07 18:50:47 - mmengine - INFO - Epoch(train) [55][280/2119] lr: 4.0000e-02 eta: 19:31:27 time: 0.3624 data_time: 0.0245 memory: 5826 grad_norm: 3.1145 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9860 loss: 2.9860 2022/10/07 18:50:53 - mmengine - INFO - Epoch(train) [55][300/2119] lr: 4.0000e-02 eta: 19:31:20 time: 0.3228 data_time: 0.0216 memory: 5826 grad_norm: 3.0995 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6434 loss: 2.6434 2022/10/07 18:51:01 - mmengine - INFO - Epoch(train) [55][320/2119] lr: 4.0000e-02 eta: 19:31:14 time: 0.3811 data_time: 0.0209 memory: 5826 grad_norm: 3.1136 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 2.8374 loss: 2.8374 2022/10/07 18:51:07 - mmengine - INFO - Epoch(train) [55][340/2119] lr: 4.0000e-02 eta: 19:31:05 time: 0.2956 data_time: 0.0215 memory: 5826 grad_norm: 3.1576 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9296 loss: 2.9296 2022/10/07 18:51:15 - mmengine - INFO - Epoch(train) [55][360/2119] lr: 4.0000e-02 eta: 19:31:00 time: 0.3841 data_time: 0.0289 memory: 5826 grad_norm: 3.1259 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7933 loss: 2.7933 2022/10/07 18:51:22 - mmengine - INFO - Epoch(train) [55][380/2119] lr: 4.0000e-02 eta: 19:30:53 time: 0.3601 data_time: 0.0173 memory: 5826 grad_norm: 3.1181 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6961 loss: 2.6961 2022/10/07 18:51:28 - mmengine - INFO - Epoch(train) [55][400/2119] lr: 4.0000e-02 eta: 19:30:46 time: 0.3232 data_time: 0.0221 memory: 5826 grad_norm: 3.0675 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7593 loss: 2.7593 2022/10/07 18:51:36 - mmengine - INFO - Epoch(train) [55][420/2119] lr: 4.0000e-02 eta: 19:30:39 time: 0.3689 data_time: 0.0247 memory: 5826 grad_norm: 3.1477 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6690 loss: 2.6690 2022/10/07 18:51:43 - mmengine - INFO - Epoch(train) [55][440/2119] lr: 4.0000e-02 eta: 19:30:33 time: 0.3527 data_time: 0.0219 memory: 5826 grad_norm: 3.0893 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7313 loss: 2.7313 2022/10/07 18:51:49 - mmengine - INFO - Epoch(train) [55][460/2119] lr: 4.0000e-02 eta: 19:30:25 time: 0.3141 data_time: 0.0204 memory: 5826 grad_norm: 3.1021 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6382 loss: 2.6382 2022/10/07 18:51:56 - mmengine - INFO - Epoch(train) [55][480/2119] lr: 4.0000e-02 eta: 19:30:18 time: 0.3607 data_time: 0.0259 memory: 5826 grad_norm: 3.1137 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5388 loss: 2.5388 2022/10/07 18:52:03 - mmengine - INFO - Epoch(train) [55][500/2119] lr: 4.0000e-02 eta: 19:30:10 time: 0.3150 data_time: 0.0226 memory: 5826 grad_norm: 3.0930 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8045 loss: 2.8045 2022/10/07 18:52:10 - mmengine - INFO - Epoch(train) [55][520/2119] lr: 4.0000e-02 eta: 19:30:05 time: 0.3860 data_time: 0.0236 memory: 5826 grad_norm: 3.1176 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6485 loss: 2.6485 2022/10/07 18:52:17 - mmengine - INFO - Epoch(train) [55][540/2119] lr: 4.0000e-02 eta: 19:29:58 time: 0.3416 data_time: 0.0188 memory: 5826 grad_norm: 3.0890 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6944 loss: 2.6944 2022/10/07 18:52:24 - mmengine - INFO - Epoch(train) [55][560/2119] lr: 4.0000e-02 eta: 19:29:52 time: 0.3688 data_time: 0.0322 memory: 5826 grad_norm: 3.1409 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7806 loss: 2.7806 2022/10/07 18:52:29 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 18:52:31 - mmengine - INFO - Epoch(train) [55][580/2119] lr: 4.0000e-02 eta: 19:29:44 time: 0.3293 data_time: 0.0180 memory: 5826 grad_norm: 3.0793 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8333 loss: 2.8333 2022/10/07 18:52:38 - mmengine - INFO - Epoch(train) [55][600/2119] lr: 4.0000e-02 eta: 19:29:37 time: 0.3492 data_time: 0.0187 memory: 5826 grad_norm: 3.0926 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7218 loss: 2.7218 2022/10/07 18:52:45 - mmengine - INFO - Epoch(train) [55][620/2119] lr: 4.0000e-02 eta: 19:29:30 time: 0.3376 data_time: 0.0248 memory: 5826 grad_norm: 3.1113 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7398 loss: 2.7398 2022/10/07 18:52:52 - mmengine - INFO - Epoch(train) [55][640/2119] lr: 4.0000e-02 eta: 19:29:23 time: 0.3368 data_time: 0.0171 memory: 5826 grad_norm: 3.0655 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.9058 loss: 2.9058 2022/10/07 18:52:58 - mmengine - INFO - Epoch(train) [55][660/2119] lr: 4.0000e-02 eta: 19:29:15 time: 0.3315 data_time: 0.0185 memory: 5826 grad_norm: 3.0740 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7951 loss: 2.7951 2022/10/07 18:53:05 - mmengine - INFO - Epoch(train) [55][680/2119] lr: 4.0000e-02 eta: 19:29:09 time: 0.3473 data_time: 0.0247 memory: 5826 grad_norm: 3.0598 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8555 loss: 2.8555 2022/10/07 18:53:12 - mmengine - INFO - Epoch(train) [55][700/2119] lr: 4.0000e-02 eta: 19:29:01 time: 0.3390 data_time: 0.0211 memory: 5826 grad_norm: 3.0861 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9214 loss: 2.9214 2022/10/07 18:53:19 - mmengine - INFO - Epoch(train) [55][720/2119] lr: 4.0000e-02 eta: 19:28:54 time: 0.3414 data_time: 0.0209 memory: 5826 grad_norm: 3.1196 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 2.4382 loss: 2.4382 2022/10/07 18:53:26 - mmengine - INFO - Epoch(train) [55][740/2119] lr: 4.0000e-02 eta: 19:28:47 time: 0.3457 data_time: 0.0258 memory: 5826 grad_norm: 3.0921 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7714 loss: 2.7714 2022/10/07 18:53:32 - mmengine - INFO - Epoch(train) [55][760/2119] lr: 4.0000e-02 eta: 19:28:40 time: 0.3286 data_time: 0.0221 memory: 5826 grad_norm: 3.1122 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7368 loss: 2.7368 2022/10/07 18:53:39 - mmengine - INFO - Epoch(train) [55][780/2119] lr: 4.0000e-02 eta: 19:28:33 time: 0.3357 data_time: 0.0190 memory: 5826 grad_norm: 3.1493 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9235 loss: 2.9235 2022/10/07 18:53:46 - mmengine - INFO - Epoch(train) [55][800/2119] lr: 4.0000e-02 eta: 19:28:25 time: 0.3269 data_time: 0.0236 memory: 5826 grad_norm: 3.1555 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8664 loss: 2.8664 2022/10/07 18:53:52 - mmengine - INFO - Epoch(train) [55][820/2119] lr: 4.0000e-02 eta: 19:28:18 time: 0.3457 data_time: 0.0217 memory: 5826 grad_norm: 3.0603 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6824 loss: 2.6824 2022/10/07 18:54:00 - mmengine - INFO - Epoch(train) [55][840/2119] lr: 4.0000e-02 eta: 19:28:12 time: 0.3721 data_time: 0.0170 memory: 5826 grad_norm: 3.0949 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7993 loss: 2.7993 2022/10/07 18:54:07 - mmengine - INFO - Epoch(train) [55][860/2119] lr: 4.0000e-02 eta: 19:28:05 time: 0.3371 data_time: 0.0238 memory: 5826 grad_norm: 3.0996 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7343 loss: 2.7343 2022/10/07 18:54:13 - mmengine - INFO - Epoch(train) [55][880/2119] lr: 4.0000e-02 eta: 19:27:57 time: 0.3213 data_time: 0.0242 memory: 5826 grad_norm: 3.1605 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6971 loss: 2.6971 2022/10/07 18:54:20 - mmengine - INFO - Epoch(train) [55][900/2119] lr: 4.0000e-02 eta: 19:27:50 time: 0.3415 data_time: 0.0183 memory: 5826 grad_norm: 3.0650 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7657 loss: 2.7657 2022/10/07 18:54:27 - mmengine - INFO - Epoch(train) [55][920/2119] lr: 4.0000e-02 eta: 19:27:43 time: 0.3530 data_time: 0.0254 memory: 5826 grad_norm: 3.0957 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.5776 loss: 2.5776 2022/10/07 18:54:35 - mmengine - INFO - Epoch(train) [55][940/2119] lr: 4.0000e-02 eta: 19:27:38 time: 0.3999 data_time: 0.0206 memory: 5826 grad_norm: 3.1147 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6384 loss: 2.6384 2022/10/07 18:54:42 - mmengine - INFO - Epoch(train) [55][960/2119] lr: 4.0000e-02 eta: 19:27:32 time: 0.3582 data_time: 0.0240 memory: 5826 grad_norm: 3.1381 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7672 loss: 2.7672 2022/10/07 18:54:50 - mmengine - INFO - Epoch(train) [55][980/2119] lr: 4.0000e-02 eta: 19:27:26 time: 0.3691 data_time: 0.0200 memory: 5826 grad_norm: 3.0508 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9817 loss: 2.9817 2022/10/07 18:54:57 - mmengine - INFO - Epoch(train) [55][1000/2119] lr: 4.0000e-02 eta: 19:27:19 time: 0.3545 data_time: 0.0242 memory: 5826 grad_norm: 3.0732 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9456 loss: 2.9456 2022/10/07 18:55:03 - mmengine - INFO - Epoch(train) [55][1020/2119] lr: 4.0000e-02 eta: 19:27:10 time: 0.3004 data_time: 0.0268 memory: 5826 grad_norm: 3.1731 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.7933 loss: 2.7933 2022/10/07 18:55:10 - mmengine - INFO - Epoch(train) [55][1040/2119] lr: 4.0000e-02 eta: 19:27:05 time: 0.3770 data_time: 0.0215 memory: 5826 grad_norm: 3.1215 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7052 loss: 2.7052 2022/10/07 18:55:17 - mmengine - INFO - Epoch(train) [55][1060/2119] lr: 4.0000e-02 eta: 19:26:57 time: 0.3332 data_time: 0.0256 memory: 5826 grad_norm: 3.1004 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6493 loss: 2.6493 2022/10/07 18:55:24 - mmengine - INFO - Epoch(train) [55][1080/2119] lr: 4.0000e-02 eta: 19:26:51 time: 0.3711 data_time: 0.0216 memory: 5826 grad_norm: 3.0791 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7252 loss: 2.7252 2022/10/07 18:55:31 - mmengine - INFO - Epoch(train) [55][1100/2119] lr: 4.0000e-02 eta: 19:26:43 time: 0.3187 data_time: 0.0199 memory: 5826 grad_norm: 3.0649 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8102 loss: 2.8102 2022/10/07 18:55:37 - mmengine - INFO - Epoch(train) [55][1120/2119] lr: 4.0000e-02 eta: 19:26:36 time: 0.3370 data_time: 0.0326 memory: 5826 grad_norm: 3.1291 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9434 loss: 2.9434 2022/10/07 18:55:44 - mmengine - INFO - Epoch(train) [55][1140/2119] lr: 4.0000e-02 eta: 19:26:29 time: 0.3400 data_time: 0.0254 memory: 5826 grad_norm: 3.1121 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7324 loss: 2.7324 2022/10/07 18:55:52 - mmengine - INFO - Epoch(train) [55][1160/2119] lr: 4.0000e-02 eta: 19:26:24 time: 0.3898 data_time: 0.0227 memory: 5826 grad_norm: 3.1725 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.8013 loss: 2.8013 2022/10/07 18:55:59 - mmengine - INFO - Epoch(train) [55][1180/2119] lr: 4.0000e-02 eta: 19:26:17 time: 0.3445 data_time: 0.0241 memory: 5826 grad_norm: 3.0406 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.5805 loss: 2.5805 2022/10/07 18:56:07 - mmengine - INFO - Epoch(train) [55][1200/2119] lr: 4.0000e-02 eta: 19:26:11 time: 0.3825 data_time: 0.0239 memory: 5826 grad_norm: 3.1144 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9169 loss: 2.9169 2022/10/07 18:56:13 - mmengine - INFO - Epoch(train) [55][1220/2119] lr: 4.0000e-02 eta: 19:26:03 time: 0.3241 data_time: 0.0210 memory: 5826 grad_norm: 3.1120 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7460 loss: 2.7460 2022/10/07 18:56:21 - mmengine - INFO - Epoch(train) [55][1240/2119] lr: 4.0000e-02 eta: 19:25:59 time: 0.4076 data_time: 0.0259 memory: 5826 grad_norm: 3.0951 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7930 loss: 2.7930 2022/10/07 18:56:28 - mmengine - INFO - Epoch(train) [55][1260/2119] lr: 4.0000e-02 eta: 19:25:51 time: 0.3291 data_time: 0.0203 memory: 5826 grad_norm: 3.1258 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7630 loss: 2.7630 2022/10/07 18:56:35 - mmengine - INFO - Epoch(train) [55][1280/2119] lr: 4.0000e-02 eta: 19:25:44 time: 0.3474 data_time: 0.0244 memory: 5826 grad_norm: 3.0885 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7094 loss: 2.7094 2022/10/07 18:56:41 - mmengine - INFO - Epoch(train) [55][1300/2119] lr: 4.0000e-02 eta: 19:25:36 time: 0.2980 data_time: 0.0232 memory: 5826 grad_norm: 3.0390 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8678 loss: 2.8678 2022/10/07 18:56:48 - mmengine - INFO - Epoch(train) [55][1320/2119] lr: 4.0000e-02 eta: 19:25:30 time: 0.3751 data_time: 0.0229 memory: 5826 grad_norm: 3.1316 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7657 loss: 2.7657 2022/10/07 18:56:55 - mmengine - INFO - Epoch(train) [55][1340/2119] lr: 4.0000e-02 eta: 19:25:22 time: 0.3368 data_time: 0.0287 memory: 5826 grad_norm: 3.1082 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7487 loss: 2.7487 2022/10/07 18:57:03 - mmengine - INFO - Epoch(train) [55][1360/2119] lr: 4.0000e-02 eta: 19:25:17 time: 0.3807 data_time: 0.0233 memory: 5826 grad_norm: 3.1674 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8987 loss: 2.8987 2022/10/07 18:57:08 - mmengine - INFO - Epoch(train) [55][1380/2119] lr: 4.0000e-02 eta: 19:25:07 time: 0.2780 data_time: 0.0225 memory: 5826 grad_norm: 3.0508 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8598 loss: 2.8598 2022/10/07 18:57:16 - mmengine - INFO - Epoch(train) [55][1400/2119] lr: 4.0000e-02 eta: 19:25:02 time: 0.3852 data_time: 0.0264 memory: 5826 grad_norm: 3.1272 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7405 loss: 2.7405 2022/10/07 18:57:23 - mmengine - INFO - Epoch(train) [55][1420/2119] lr: 4.0000e-02 eta: 19:24:55 time: 0.3563 data_time: 0.0224 memory: 5826 grad_norm: 3.1214 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8235 loss: 2.8235 2022/10/07 18:57:31 - mmengine - INFO - Epoch(train) [55][1440/2119] lr: 4.0000e-02 eta: 19:24:50 time: 0.3798 data_time: 0.0216 memory: 5826 grad_norm: 3.1057 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6591 loss: 2.6591 2022/10/07 18:57:38 - mmengine - INFO - Epoch(train) [55][1460/2119] lr: 4.0000e-02 eta: 19:24:43 time: 0.3594 data_time: 0.0259 memory: 5826 grad_norm: 3.0985 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5680 loss: 2.5680 2022/10/07 18:57:44 - mmengine - INFO - Epoch(train) [55][1480/2119] lr: 4.0000e-02 eta: 19:24:35 time: 0.3227 data_time: 0.0267 memory: 5826 grad_norm: 3.0725 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7928 loss: 2.7928 2022/10/07 18:57:50 - mmengine - INFO - Epoch(train) [55][1500/2119] lr: 4.0000e-02 eta: 19:24:27 time: 0.2981 data_time: 0.0233 memory: 5826 grad_norm: 3.1117 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7695 loss: 2.7695 2022/10/07 18:57:58 - mmengine - INFO - Epoch(train) [55][1520/2119] lr: 4.0000e-02 eta: 19:24:21 time: 0.3680 data_time: 0.0324 memory: 5826 grad_norm: 3.0887 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7846 loss: 2.7846 2022/10/07 18:58:04 - mmengine - INFO - Epoch(train) [55][1540/2119] lr: 4.0000e-02 eta: 19:24:13 time: 0.3314 data_time: 0.0243 memory: 5826 grad_norm: 3.0954 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9049 loss: 2.9049 2022/10/07 18:58:12 - mmengine - INFO - Epoch(train) [55][1560/2119] lr: 4.0000e-02 eta: 19:24:07 time: 0.3691 data_time: 0.0248 memory: 5826 grad_norm: 3.0789 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8512 loss: 2.8512 2022/10/07 18:58:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 18:58:19 - mmengine - INFO - Epoch(train) [55][1580/2119] lr: 4.0000e-02 eta: 19:24:01 time: 0.3677 data_time: 0.0241 memory: 5826 grad_norm: 3.1339 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8265 loss: 2.8265 2022/10/07 18:58:26 - mmengine - INFO - Epoch(train) [55][1600/2119] lr: 4.0000e-02 eta: 19:23:54 time: 0.3600 data_time: 0.0226 memory: 5826 grad_norm: 3.0669 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 3.0178 loss: 3.0178 2022/10/07 18:58:33 - mmengine - INFO - Epoch(train) [55][1620/2119] lr: 4.0000e-02 eta: 19:23:47 time: 0.3344 data_time: 0.0214 memory: 5826 grad_norm: 3.1043 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6759 loss: 2.6759 2022/10/07 18:58:40 - mmengine - INFO - Epoch(train) [55][1640/2119] lr: 4.0000e-02 eta: 19:23:41 time: 0.3684 data_time: 0.0228 memory: 5826 grad_norm: 3.0619 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8125 loss: 2.8125 2022/10/07 18:58:47 - mmengine - INFO - Epoch(train) [55][1660/2119] lr: 4.0000e-02 eta: 19:23:33 time: 0.3180 data_time: 0.0201 memory: 5826 grad_norm: 3.0585 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8381 loss: 2.8381 2022/10/07 18:58:53 - mmengine - INFO - Epoch(train) [55][1680/2119] lr: 4.0000e-02 eta: 19:23:26 time: 0.3380 data_time: 0.0213 memory: 5826 grad_norm: 3.1537 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8376 loss: 2.8376 2022/10/07 18:59:00 - mmengine - INFO - Epoch(train) [55][1700/2119] lr: 4.0000e-02 eta: 19:23:18 time: 0.3280 data_time: 0.0253 memory: 5826 grad_norm: 3.0540 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9385 loss: 2.9385 2022/10/07 18:59:07 - mmengine - INFO - Epoch(train) [55][1720/2119] lr: 4.0000e-02 eta: 19:23:12 time: 0.3510 data_time: 0.0186 memory: 5826 grad_norm: 3.1045 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7656 loss: 2.7656 2022/10/07 18:59:13 - mmengine - INFO - Epoch(train) [55][1740/2119] lr: 4.0000e-02 eta: 19:23:04 time: 0.3252 data_time: 0.0249 memory: 5826 grad_norm: 3.0669 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9028 loss: 2.9028 2022/10/07 18:59:21 - mmengine - INFO - Epoch(train) [55][1760/2119] lr: 4.0000e-02 eta: 19:22:58 time: 0.3826 data_time: 0.0216 memory: 5826 grad_norm: 3.1083 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4606 loss: 2.4606 2022/10/07 18:59:28 - mmengine - INFO - Epoch(train) [55][1780/2119] lr: 4.0000e-02 eta: 19:22:51 time: 0.3336 data_time: 0.0198 memory: 5826 grad_norm: 3.1637 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7769 loss: 2.7769 2022/10/07 18:59:35 - mmengine - INFO - Epoch(train) [55][1800/2119] lr: 4.0000e-02 eta: 19:22:45 time: 0.3618 data_time: 0.0188 memory: 5826 grad_norm: 3.1113 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9867 loss: 2.9867 2022/10/07 18:59:42 - mmengine - INFO - Epoch(train) [55][1820/2119] lr: 4.0000e-02 eta: 19:22:38 time: 0.3621 data_time: 0.0225 memory: 5826 grad_norm: 3.1086 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6499 loss: 2.6499 2022/10/07 18:59:49 - mmengine - INFO - Epoch(train) [55][1840/2119] lr: 4.0000e-02 eta: 19:22:32 time: 0.3573 data_time: 0.0208 memory: 5826 grad_norm: 3.0937 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7733 loss: 2.7733 2022/10/07 18:59:56 - mmengine - INFO - Epoch(train) [55][1860/2119] lr: 4.0000e-02 eta: 19:22:24 time: 0.3179 data_time: 0.0228 memory: 5826 grad_norm: 3.0723 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8481 loss: 2.8481 2022/10/07 19:00:03 - mmengine - INFO - Epoch(train) [55][1880/2119] lr: 4.0000e-02 eta: 19:22:17 time: 0.3590 data_time: 0.0249 memory: 5826 grad_norm: 3.0925 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8533 loss: 2.8533 2022/10/07 19:00:09 - mmengine - INFO - Epoch(train) [55][1900/2119] lr: 4.0000e-02 eta: 19:22:10 time: 0.3246 data_time: 0.0192 memory: 5826 grad_norm: 3.0347 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5314 loss: 2.5314 2022/10/07 19:00:16 - mmengine - INFO - Epoch(train) [55][1920/2119] lr: 4.0000e-02 eta: 19:22:03 time: 0.3549 data_time: 0.0267 memory: 5826 grad_norm: 3.0981 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8035 loss: 2.8035 2022/10/07 19:00:23 - mmengine - INFO - Epoch(train) [55][1940/2119] lr: 4.0000e-02 eta: 19:21:56 time: 0.3413 data_time: 0.0220 memory: 5826 grad_norm: 3.0683 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7725 loss: 2.7725 2022/10/07 19:00:30 - mmengine - INFO - Epoch(train) [55][1960/2119] lr: 4.0000e-02 eta: 19:21:49 time: 0.3441 data_time: 0.0260 memory: 5826 grad_norm: 3.1037 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4831 loss: 2.4831 2022/10/07 19:00:37 - mmengine - INFO - Epoch(train) [55][1980/2119] lr: 4.0000e-02 eta: 19:21:42 time: 0.3332 data_time: 0.0208 memory: 5826 grad_norm: 3.0656 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5645 loss: 2.5645 2022/10/07 19:00:45 - mmengine - INFO - Epoch(train) [55][2000/2119] lr: 4.0000e-02 eta: 19:21:36 time: 0.3865 data_time: 0.0278 memory: 5826 grad_norm: 3.1153 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7745 loss: 2.7745 2022/10/07 19:00:51 - mmengine - INFO - Epoch(train) [55][2020/2119] lr: 4.0000e-02 eta: 19:21:28 time: 0.3041 data_time: 0.0194 memory: 5826 grad_norm: 3.0799 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8361 loss: 2.8361 2022/10/07 19:00:58 - mmengine - INFO - Epoch(train) [55][2040/2119] lr: 4.0000e-02 eta: 19:21:22 time: 0.3662 data_time: 0.0285 memory: 5826 grad_norm: 3.1246 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7227 loss: 2.7227 2022/10/07 19:01:04 - mmengine - INFO - Epoch(train) [55][2060/2119] lr: 4.0000e-02 eta: 19:21:14 time: 0.3236 data_time: 0.0232 memory: 5826 grad_norm: 3.1105 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7188 loss: 2.7188 2022/10/07 19:01:11 - mmengine - INFO - Epoch(train) [55][2080/2119] lr: 4.0000e-02 eta: 19:21:06 time: 0.3323 data_time: 0.0219 memory: 5826 grad_norm: 3.1053 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7961 loss: 2.7961 2022/10/07 19:01:18 - mmengine - INFO - Epoch(train) [55][2100/2119] lr: 4.0000e-02 eta: 19:20:59 time: 0.3395 data_time: 0.0308 memory: 5826 grad_norm: 3.1626 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7815 loss: 2.7815 2022/10/07 19:01:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 19:01:24 - mmengine - INFO - Epoch(train) [55][2119/2119] lr: 4.0000e-02 eta: 19:20:59 time: 0.3398 data_time: 0.0218 memory: 5826 grad_norm: 3.1382 top1_acc: 0.2000 top5_acc: 0.6000 loss_cls: 2.9116 loss: 2.9116 2022/10/07 19:01:33 - mmengine - INFO - Epoch(val) [55][20/137] eta: 0:00:48 time: 0.4108 data_time: 0.3327 memory: 1241 2022/10/07 19:01:39 - mmengine - INFO - Epoch(val) [55][40/137] eta: 0:00:30 time: 0.3150 data_time: 0.2487 memory: 1241 2022/10/07 19:01:46 - mmengine - INFO - Epoch(val) [55][60/137] eta: 0:00:26 time: 0.3451 data_time: 0.2790 memory: 1241 2022/10/07 19:01:51 - mmengine - INFO - Epoch(val) [55][80/137] eta: 0:00:14 time: 0.2543 data_time: 0.1890 memory: 1241 2022/10/07 19:01:58 - mmengine - INFO - Epoch(val) [55][100/137] eta: 0:00:12 time: 0.3480 data_time: 0.2841 memory: 1241 2022/10/07 19:02:04 - mmengine - INFO - Epoch(val) [55][120/137] eta: 0:00:05 time: 0.3005 data_time: 0.2373 memory: 1241 2022/10/07 19:02:16 - mmengine - INFO - Epoch(val) [55][137/137] acc/top1: 0.4168 acc/top5: 0.6614 acc/mean1: 0.4167 2022/10/07 19:02:26 - mmengine - INFO - Epoch(train) [56][20/2119] lr: 4.0000e-02 eta: 19:20:40 time: 0.4941 data_time: 0.1430 memory: 5826 grad_norm: 3.0328 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.6257 loss: 2.6257 2022/10/07 19:02:32 - mmengine - INFO - Epoch(train) [56][40/2119] lr: 4.0000e-02 eta: 19:20:31 time: 0.3123 data_time: 0.0397 memory: 5826 grad_norm: 3.0649 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8399 loss: 2.8399 2022/10/07 19:02:40 - mmengine - INFO - Epoch(train) [56][60/2119] lr: 4.0000e-02 eta: 19:20:26 time: 0.3773 data_time: 0.0159 memory: 5826 grad_norm: 3.0543 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7414 loss: 2.7414 2022/10/07 19:02:47 - mmengine - INFO - Epoch(train) [56][80/2119] lr: 4.0000e-02 eta: 19:20:20 time: 0.3699 data_time: 0.0212 memory: 5826 grad_norm: 3.0270 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6010 loss: 2.6010 2022/10/07 19:02:53 - mmengine - INFO - Epoch(train) [56][100/2119] lr: 4.0000e-02 eta: 19:20:11 time: 0.3091 data_time: 0.0187 memory: 5826 grad_norm: 3.1206 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4031 loss: 2.4031 2022/10/07 19:03:01 - mmengine - INFO - Epoch(train) [56][120/2119] lr: 4.0000e-02 eta: 19:20:06 time: 0.3785 data_time: 0.0199 memory: 5826 grad_norm: 3.1409 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7193 loss: 2.7193 2022/10/07 19:03:07 - mmengine - INFO - Epoch(train) [56][140/2119] lr: 4.0000e-02 eta: 19:19:57 time: 0.3111 data_time: 0.0251 memory: 5826 grad_norm: 3.0705 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6824 loss: 2.6824 2022/10/07 19:03:14 - mmengine - INFO - Epoch(train) [56][160/2119] lr: 4.0000e-02 eta: 19:19:50 time: 0.3354 data_time: 0.0212 memory: 5826 grad_norm: 3.1205 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7300 loss: 2.7300 2022/10/07 19:03:21 - mmengine - INFO - Epoch(train) [56][180/2119] lr: 4.0000e-02 eta: 19:19:43 time: 0.3383 data_time: 0.0225 memory: 5826 grad_norm: 3.1130 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5362 loss: 2.5362 2022/10/07 19:03:29 - mmengine - INFO - Epoch(train) [56][200/2119] lr: 4.0000e-02 eta: 19:19:38 time: 0.3952 data_time: 0.0243 memory: 5826 grad_norm: 3.0871 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7534 loss: 2.7534 2022/10/07 19:03:35 - mmengine - INFO - Epoch(train) [56][220/2119] lr: 4.0000e-02 eta: 19:19:30 time: 0.3271 data_time: 0.0221 memory: 5826 grad_norm: 3.1282 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6826 loss: 2.6826 2022/10/07 19:03:42 - mmengine - INFO - Epoch(train) [56][240/2119] lr: 4.0000e-02 eta: 19:19:23 time: 0.3524 data_time: 0.0227 memory: 5826 grad_norm: 3.1199 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7808 loss: 2.7808 2022/10/07 19:03:49 - mmengine - INFO - Epoch(train) [56][260/2119] lr: 4.0000e-02 eta: 19:19:17 time: 0.3519 data_time: 0.0236 memory: 5826 grad_norm: 3.1436 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5209 loss: 2.5209 2022/10/07 19:03:56 - mmengine - INFO - Epoch(train) [56][280/2119] lr: 4.0000e-02 eta: 19:19:10 time: 0.3448 data_time: 0.0177 memory: 5826 grad_norm: 3.0916 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7794 loss: 2.7794 2022/10/07 19:04:03 - mmengine - INFO - Epoch(train) [56][300/2119] lr: 4.0000e-02 eta: 19:19:03 time: 0.3493 data_time: 0.0221 memory: 5826 grad_norm: 3.0651 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6815 loss: 2.6815 2022/10/07 19:04:10 - mmengine - INFO - Epoch(train) [56][320/2119] lr: 4.0000e-02 eta: 19:18:56 time: 0.3370 data_time: 0.0211 memory: 5826 grad_norm: 3.1344 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7826 loss: 2.7826 2022/10/07 19:04:17 - mmengine - INFO - Epoch(train) [56][340/2119] lr: 4.0000e-02 eta: 19:18:49 time: 0.3575 data_time: 0.0270 memory: 5826 grad_norm: 3.1328 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.8005 loss: 2.8005 2022/10/07 19:04:24 - mmengine - INFO - Epoch(train) [56][360/2119] lr: 4.0000e-02 eta: 19:18:42 time: 0.3499 data_time: 0.0259 memory: 5826 grad_norm: 3.1321 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.5573 loss: 2.5573 2022/10/07 19:04:30 - mmengine - INFO - Epoch(train) [56][380/2119] lr: 4.0000e-02 eta: 19:18:34 time: 0.3139 data_time: 0.0259 memory: 5826 grad_norm: 3.0934 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7482 loss: 2.7482 2022/10/07 19:04:37 - mmengine - INFO - Epoch(train) [56][400/2119] lr: 4.0000e-02 eta: 19:18:28 time: 0.3492 data_time: 0.0239 memory: 5826 grad_norm: 3.0881 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6571 loss: 2.6571 2022/10/07 19:04:44 - mmengine - INFO - Epoch(train) [56][420/2119] lr: 4.0000e-02 eta: 19:18:21 time: 0.3493 data_time: 0.0216 memory: 5826 grad_norm: 3.0564 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9396 loss: 2.9396 2022/10/07 19:04:51 - mmengine - INFO - Epoch(train) [56][440/2119] lr: 4.0000e-02 eta: 19:18:14 time: 0.3534 data_time: 0.0186 memory: 5826 grad_norm: 3.0583 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7529 loss: 2.7529 2022/10/07 19:04:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 19:04:58 - mmengine - INFO - Epoch(train) [56][460/2119] lr: 4.0000e-02 eta: 19:18:07 time: 0.3475 data_time: 0.0245 memory: 5826 grad_norm: 3.1107 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7010 loss: 2.7010 2022/10/07 19:05:05 - mmengine - INFO - Epoch(train) [56][480/2119] lr: 4.0000e-02 eta: 19:18:00 time: 0.3426 data_time: 0.0197 memory: 5826 grad_norm: 3.1329 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8763 loss: 2.8763 2022/10/07 19:05:12 - mmengine - INFO - Epoch(train) [56][500/2119] lr: 4.0000e-02 eta: 19:17:54 time: 0.3544 data_time: 0.0205 memory: 5826 grad_norm: 3.0986 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8405 loss: 2.8405 2022/10/07 19:05:19 - mmengine - INFO - Epoch(train) [56][520/2119] lr: 4.0000e-02 eta: 19:17:47 time: 0.3410 data_time: 0.0226 memory: 5826 grad_norm: 3.0940 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7415 loss: 2.7415 2022/10/07 19:05:26 - mmengine - INFO - Epoch(train) [56][540/2119] lr: 4.0000e-02 eta: 19:17:40 time: 0.3667 data_time: 0.0250 memory: 5826 grad_norm: 3.0904 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7938 loss: 2.7938 2022/10/07 19:05:32 - mmengine - INFO - Epoch(train) [56][560/2119] lr: 4.0000e-02 eta: 19:17:31 time: 0.2841 data_time: 0.0180 memory: 5826 grad_norm: 3.1209 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8764 loss: 2.8764 2022/10/07 19:05:39 - mmengine - INFO - Epoch(train) [56][580/2119] lr: 4.0000e-02 eta: 19:17:25 time: 0.3636 data_time: 0.0217 memory: 5826 grad_norm: 3.0932 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7814 loss: 2.7814 2022/10/07 19:05:46 - mmengine - INFO - Epoch(train) [56][600/2119] lr: 4.0000e-02 eta: 19:17:17 time: 0.3253 data_time: 0.0205 memory: 5826 grad_norm: 3.1013 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7435 loss: 2.7435 2022/10/07 19:05:53 - mmengine - INFO - Epoch(train) [56][620/2119] lr: 4.0000e-02 eta: 19:17:11 time: 0.3579 data_time: 0.0177 memory: 5826 grad_norm: 3.1095 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7507 loss: 2.7507 2022/10/07 19:06:00 - mmengine - INFO - Epoch(train) [56][640/2119] lr: 4.0000e-02 eta: 19:17:04 time: 0.3632 data_time: 0.0187 memory: 5826 grad_norm: 3.1151 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4936 loss: 2.4936 2022/10/07 19:06:08 - mmengine - INFO - Epoch(train) [56][660/2119] lr: 4.0000e-02 eta: 19:16:58 time: 0.3596 data_time: 0.0195 memory: 5826 grad_norm: 3.0764 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5416 loss: 2.5416 2022/10/07 19:06:14 - mmengine - INFO - Epoch(train) [56][680/2119] lr: 4.0000e-02 eta: 19:16:51 time: 0.3394 data_time: 0.0187 memory: 5826 grad_norm: 3.0802 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4329 loss: 2.4329 2022/10/07 19:06:23 - mmengine - INFO - Epoch(train) [56][700/2119] lr: 4.0000e-02 eta: 19:16:46 time: 0.4196 data_time: 0.0227 memory: 5826 grad_norm: 3.0930 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8212 loss: 2.8212 2022/10/07 19:06:29 - mmengine - INFO - Epoch(train) [56][720/2119] lr: 4.0000e-02 eta: 19:16:39 time: 0.3297 data_time: 0.0217 memory: 5826 grad_norm: 3.1707 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9897 loss: 2.9897 2022/10/07 19:06:36 - mmengine - INFO - Epoch(train) [56][740/2119] lr: 4.0000e-02 eta: 19:16:31 time: 0.3252 data_time: 0.0213 memory: 5826 grad_norm: 3.1192 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8088 loss: 2.8088 2022/10/07 19:06:42 - mmengine - INFO - Epoch(train) [56][760/2119] lr: 4.0000e-02 eta: 19:16:24 time: 0.3292 data_time: 0.0223 memory: 5826 grad_norm: 3.1217 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.5432 loss: 2.5432 2022/10/07 19:06:51 - mmengine - INFO - Epoch(train) [56][780/2119] lr: 4.0000e-02 eta: 19:16:19 time: 0.4161 data_time: 0.0206 memory: 5826 grad_norm: 3.0756 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.7773 loss: 2.7773 2022/10/07 19:06:57 - mmengine - INFO - Epoch(train) [56][800/2119] lr: 4.0000e-02 eta: 19:16:12 time: 0.3212 data_time: 0.0216 memory: 5826 grad_norm: 3.1135 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7307 loss: 2.7307 2022/10/07 19:07:04 - mmengine - INFO - Epoch(train) [56][820/2119] lr: 4.0000e-02 eta: 19:16:04 time: 0.3379 data_time: 0.0182 memory: 5826 grad_norm: 3.0988 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.5943 loss: 2.5943 2022/10/07 19:07:10 - mmengine - INFO - Epoch(train) [56][840/2119] lr: 4.0000e-02 eta: 19:15:57 time: 0.3235 data_time: 0.0285 memory: 5826 grad_norm: 3.0808 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6881 loss: 2.6881 2022/10/07 19:07:18 - mmengine - INFO - Epoch(train) [56][860/2119] lr: 4.0000e-02 eta: 19:15:51 time: 0.3722 data_time: 0.0298 memory: 5826 grad_norm: 3.1599 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7095 loss: 2.7095 2022/10/07 19:07:25 - mmengine - INFO - Epoch(train) [56][880/2119] lr: 4.0000e-02 eta: 19:15:44 time: 0.3525 data_time: 0.0223 memory: 5826 grad_norm: 3.1560 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6912 loss: 2.6912 2022/10/07 19:07:32 - mmengine - INFO - Epoch(train) [56][900/2119] lr: 4.0000e-02 eta: 19:15:37 time: 0.3349 data_time: 0.0256 memory: 5826 grad_norm: 3.0966 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8680 loss: 2.8680 2022/10/07 19:07:38 - mmengine - INFO - Epoch(train) [56][920/2119] lr: 4.0000e-02 eta: 19:15:29 time: 0.3322 data_time: 0.0225 memory: 5826 grad_norm: 3.1377 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7974 loss: 2.7974 2022/10/07 19:07:45 - mmengine - INFO - Epoch(train) [56][940/2119] lr: 4.0000e-02 eta: 19:15:23 time: 0.3610 data_time: 0.0153 memory: 5826 grad_norm: 3.0783 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7848 loss: 2.7848 2022/10/07 19:07:53 - mmengine - INFO - Epoch(train) [56][960/2119] lr: 4.0000e-02 eta: 19:15:17 time: 0.3660 data_time: 0.0223 memory: 5826 grad_norm: 3.0759 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6443 loss: 2.6443 2022/10/07 19:08:00 - mmengine - INFO - Epoch(train) [56][980/2119] lr: 4.0000e-02 eta: 19:15:11 time: 0.3695 data_time: 0.0205 memory: 5826 grad_norm: 3.0964 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6438 loss: 2.6438 2022/10/07 19:08:07 - mmengine - INFO - Epoch(train) [56][1000/2119] lr: 4.0000e-02 eta: 19:15:03 time: 0.3342 data_time: 0.0199 memory: 5826 grad_norm: 3.0993 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5157 loss: 2.5157 2022/10/07 19:08:14 - mmengine - INFO - Epoch(train) [56][1020/2119] lr: 4.0000e-02 eta: 19:14:56 time: 0.3424 data_time: 0.0257 memory: 5826 grad_norm: 3.1987 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7437 loss: 2.7437 2022/10/07 19:08:21 - mmengine - INFO - Epoch(train) [56][1040/2119] lr: 4.0000e-02 eta: 19:14:49 time: 0.3422 data_time: 0.0201 memory: 5826 grad_norm: 3.1488 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.0560 loss: 3.0560 2022/10/07 19:08:27 - mmengine - INFO - Epoch(train) [56][1060/2119] lr: 4.0000e-02 eta: 19:14:42 time: 0.3461 data_time: 0.0253 memory: 5826 grad_norm: 3.1322 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0014 loss: 3.0014 2022/10/07 19:08:34 - mmengine - INFO - Epoch(train) [56][1080/2119] lr: 4.0000e-02 eta: 19:14:35 time: 0.3293 data_time: 0.0234 memory: 5826 grad_norm: 3.1240 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.5251 loss: 2.5251 2022/10/07 19:08:41 - mmengine - INFO - Epoch(train) [56][1100/2119] lr: 4.0000e-02 eta: 19:14:28 time: 0.3412 data_time: 0.0216 memory: 5826 grad_norm: 3.1021 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6364 loss: 2.6364 2022/10/07 19:08:48 - mmengine - INFO - Epoch(train) [56][1120/2119] lr: 4.0000e-02 eta: 19:14:21 time: 0.3480 data_time: 0.0248 memory: 5826 grad_norm: 3.1433 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7917 loss: 2.7917 2022/10/07 19:08:54 - mmengine - INFO - Epoch(train) [56][1140/2119] lr: 4.0000e-02 eta: 19:14:12 time: 0.2862 data_time: 0.0246 memory: 5826 grad_norm: 3.0652 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6057 loss: 2.6057 2022/10/07 19:09:02 - mmengine - INFO - Epoch(train) [56][1160/2119] lr: 4.0000e-02 eta: 19:14:07 time: 0.4044 data_time: 0.0245 memory: 5826 grad_norm: 3.1146 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7578 loss: 2.7578 2022/10/07 19:09:08 - mmengine - INFO - Epoch(train) [56][1180/2119] lr: 4.0000e-02 eta: 19:13:58 time: 0.3008 data_time: 0.0208 memory: 5826 grad_norm: 3.1418 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6134 loss: 2.6134 2022/10/07 19:09:15 - mmengine - INFO - Epoch(train) [56][1200/2119] lr: 4.0000e-02 eta: 19:13:52 time: 0.3586 data_time: 0.0195 memory: 5826 grad_norm: 3.1513 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5836 loss: 2.5836 2022/10/07 19:09:22 - mmengine - INFO - Epoch(train) [56][1220/2119] lr: 4.0000e-02 eta: 19:13:45 time: 0.3419 data_time: 0.0216 memory: 5826 grad_norm: 3.0950 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7270 loss: 2.7270 2022/10/07 19:09:29 - mmengine - INFO - Epoch(train) [56][1240/2119] lr: 4.0000e-02 eta: 19:13:38 time: 0.3535 data_time: 0.0222 memory: 5826 grad_norm: 3.0652 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7077 loss: 2.7077 2022/10/07 19:09:36 - mmengine - INFO - Epoch(train) [56][1260/2119] lr: 4.0000e-02 eta: 19:13:32 time: 0.3567 data_time: 0.0222 memory: 5826 grad_norm: 3.1726 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6540 loss: 2.6540 2022/10/07 19:09:43 - mmengine - INFO - Epoch(train) [56][1280/2119] lr: 4.0000e-02 eta: 19:13:24 time: 0.3383 data_time: 0.0237 memory: 5826 grad_norm: 3.1229 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6911 loss: 2.6911 2022/10/07 19:09:49 - mmengine - INFO - Epoch(train) [56][1300/2119] lr: 4.0000e-02 eta: 19:13:17 time: 0.3311 data_time: 0.0348 memory: 5826 grad_norm: 3.1263 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6143 loss: 2.6143 2022/10/07 19:09:57 - mmengine - INFO - Epoch(train) [56][1320/2119] lr: 4.0000e-02 eta: 19:13:11 time: 0.3610 data_time: 0.0196 memory: 5826 grad_norm: 3.1136 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7966 loss: 2.7966 2022/10/07 19:10:03 - mmengine - INFO - Epoch(train) [56][1340/2119] lr: 4.0000e-02 eta: 19:13:03 time: 0.3367 data_time: 0.0196 memory: 5826 grad_norm: 3.0985 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.0352 loss: 3.0352 2022/10/07 19:10:10 - mmengine - INFO - Epoch(train) [56][1360/2119] lr: 4.0000e-02 eta: 19:12:57 time: 0.3572 data_time: 0.0203 memory: 5826 grad_norm: 3.0964 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7196 loss: 2.7196 2022/10/07 19:10:17 - mmengine - INFO - Epoch(train) [56][1380/2119] lr: 4.0000e-02 eta: 19:12:50 time: 0.3380 data_time: 0.0236 memory: 5826 grad_norm: 3.1449 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6485 loss: 2.6485 2022/10/07 19:10:24 - mmengine - INFO - Epoch(train) [56][1400/2119] lr: 4.0000e-02 eta: 19:12:43 time: 0.3388 data_time: 0.0255 memory: 5826 grad_norm: 3.1508 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7458 loss: 2.7458 2022/10/07 19:10:30 - mmengine - INFO - Epoch(train) [56][1420/2119] lr: 4.0000e-02 eta: 19:12:34 time: 0.3030 data_time: 0.0248 memory: 5826 grad_norm: 3.1597 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7150 loss: 2.7150 2022/10/07 19:10:38 - mmengine - INFO - Epoch(train) [56][1440/2119] lr: 4.0000e-02 eta: 19:12:29 time: 0.4073 data_time: 0.0219 memory: 5826 grad_norm: 3.0697 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7500 loss: 2.7500 2022/10/07 19:10:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 19:10:45 - mmengine - INFO - Epoch(train) [56][1460/2119] lr: 4.0000e-02 eta: 19:12:21 time: 0.3191 data_time: 0.0199 memory: 5826 grad_norm: 3.1148 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6652 loss: 2.6652 2022/10/07 19:10:52 - mmengine - INFO - Epoch(train) [56][1480/2119] lr: 4.0000e-02 eta: 19:12:15 time: 0.3583 data_time: 0.0233 memory: 5826 grad_norm: 3.0624 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9624 loss: 2.9624 2022/10/07 19:10:58 - mmengine - INFO - Epoch(train) [56][1500/2119] lr: 4.0000e-02 eta: 19:12:07 time: 0.3090 data_time: 0.0189 memory: 5826 grad_norm: 3.0910 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8121 loss: 2.8121 2022/10/07 19:11:06 - mmengine - INFO - Epoch(train) [56][1520/2119] lr: 4.0000e-02 eta: 19:12:02 time: 0.3986 data_time: 0.0199 memory: 5826 grad_norm: 3.0919 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.8159 loss: 2.8159 2022/10/07 19:11:12 - mmengine - INFO - Epoch(train) [56][1540/2119] lr: 4.0000e-02 eta: 19:11:54 time: 0.3172 data_time: 0.0242 memory: 5826 grad_norm: 3.0513 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7656 loss: 2.7656 2022/10/07 19:11:19 - mmengine - INFO - Epoch(train) [56][1560/2119] lr: 4.0000e-02 eta: 19:11:47 time: 0.3443 data_time: 0.0248 memory: 5826 grad_norm: 3.1301 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8974 loss: 2.8974 2022/10/07 19:11:25 - mmengine - INFO - Epoch(train) [56][1580/2119] lr: 4.0000e-02 eta: 19:11:38 time: 0.3040 data_time: 0.0248 memory: 5826 grad_norm: 3.1182 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6072 loss: 2.6072 2022/10/07 19:11:33 - mmengine - INFO - Epoch(train) [56][1600/2119] lr: 4.0000e-02 eta: 19:11:32 time: 0.3649 data_time: 0.0229 memory: 5826 grad_norm: 3.0889 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7131 loss: 2.7131 2022/10/07 19:11:39 - mmengine - INFO - Epoch(train) [56][1620/2119] lr: 4.0000e-02 eta: 19:11:25 time: 0.3263 data_time: 0.0222 memory: 5826 grad_norm: 3.0619 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7633 loss: 2.7633 2022/10/07 19:11:46 - mmengine - INFO - Epoch(train) [56][1640/2119] lr: 4.0000e-02 eta: 19:11:18 time: 0.3459 data_time: 0.0216 memory: 5826 grad_norm: 3.0749 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7967 loss: 2.7967 2022/10/07 19:11:53 - mmengine - INFO - Epoch(train) [56][1660/2119] lr: 4.0000e-02 eta: 19:11:10 time: 0.3266 data_time: 0.0232 memory: 5826 grad_norm: 3.1550 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9288 loss: 2.9288 2022/10/07 19:12:00 - mmengine - INFO - Epoch(train) [56][1680/2119] lr: 4.0000e-02 eta: 19:11:04 time: 0.3611 data_time: 0.0273 memory: 5826 grad_norm: 3.1525 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.8483 loss: 2.8483 2022/10/07 19:12:06 - mmengine - INFO - Epoch(train) [56][1700/2119] lr: 4.0000e-02 eta: 19:10:56 time: 0.3132 data_time: 0.0238 memory: 5826 grad_norm: 3.1452 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6908 loss: 2.6908 2022/10/07 19:12:13 - mmengine - INFO - Epoch(train) [56][1720/2119] lr: 4.0000e-02 eta: 19:10:49 time: 0.3421 data_time: 0.0246 memory: 5826 grad_norm: 3.0548 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7040 loss: 2.7040 2022/10/07 19:12:20 - mmengine - INFO - Epoch(train) [56][1740/2119] lr: 4.0000e-02 eta: 19:10:43 time: 0.3715 data_time: 0.0225 memory: 5826 grad_norm: 3.1210 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8420 loss: 2.8420 2022/10/07 19:12:28 - mmengine - INFO - Epoch(train) [56][1760/2119] lr: 4.0000e-02 eta: 19:10:36 time: 0.3672 data_time: 0.0204 memory: 5826 grad_norm: 3.0941 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5711 loss: 2.5711 2022/10/07 19:12:33 - mmengine - INFO - Epoch(train) [56][1780/2119] lr: 4.0000e-02 eta: 19:10:27 time: 0.2857 data_time: 0.0209 memory: 5826 grad_norm: 3.0785 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8671 loss: 2.8671 2022/10/07 19:12:41 - mmengine - INFO - Epoch(train) [56][1800/2119] lr: 4.0000e-02 eta: 19:10:22 time: 0.3963 data_time: 0.0204 memory: 5826 grad_norm: 3.0994 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6488 loss: 2.6488 2022/10/07 19:12:48 - mmengine - INFO - Epoch(train) [56][1820/2119] lr: 4.0000e-02 eta: 19:10:14 time: 0.3139 data_time: 0.0207 memory: 5826 grad_norm: 3.1156 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5751 loss: 2.5751 2022/10/07 19:12:55 - mmengine - INFO - Epoch(train) [56][1840/2119] lr: 4.0000e-02 eta: 19:10:08 time: 0.3656 data_time: 0.0241 memory: 5826 grad_norm: 3.1200 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5453 loss: 2.5453 2022/10/07 19:13:02 - mmengine - INFO - Epoch(train) [56][1860/2119] lr: 4.0000e-02 eta: 19:10:02 time: 0.3653 data_time: 0.0259 memory: 5826 grad_norm: 3.0878 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8084 loss: 2.8084 2022/10/07 19:13:09 - mmengine - INFO - Epoch(train) [56][1880/2119] lr: 4.0000e-02 eta: 19:09:55 time: 0.3476 data_time: 0.0244 memory: 5826 grad_norm: 3.0947 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9310 loss: 2.9310 2022/10/07 19:13:16 - mmengine - INFO - Epoch(train) [56][1900/2119] lr: 4.0000e-02 eta: 19:09:47 time: 0.3238 data_time: 0.0233 memory: 5826 grad_norm: 3.0890 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7755 loss: 2.7755 2022/10/07 19:13:23 - mmengine - INFO - Epoch(train) [56][1920/2119] lr: 4.0000e-02 eta: 19:09:41 time: 0.3695 data_time: 0.0262 memory: 5826 grad_norm: 3.1050 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8526 loss: 2.8526 2022/10/07 19:13:29 - mmengine - INFO - Epoch(train) [56][1940/2119] lr: 4.0000e-02 eta: 19:09:33 time: 0.3225 data_time: 0.0198 memory: 5826 grad_norm: 3.0347 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7863 loss: 2.7863 2022/10/07 19:13:38 - mmengine - INFO - Epoch(train) [56][1960/2119] lr: 4.0000e-02 eta: 19:09:29 time: 0.4297 data_time: 0.0188 memory: 5826 grad_norm: 3.1413 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6847 loss: 2.6847 2022/10/07 19:13:43 - mmengine - INFO - Epoch(train) [56][1980/2119] lr: 4.0000e-02 eta: 19:09:20 time: 0.2698 data_time: 0.0251 memory: 5826 grad_norm: 3.1183 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7540 loss: 2.7540 2022/10/07 19:13:51 - mmengine - INFO - Epoch(train) [56][2000/2119] lr: 4.0000e-02 eta: 19:09:13 time: 0.3666 data_time: 0.0194 memory: 5826 grad_norm: 3.0943 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7630 loss: 2.7630 2022/10/07 19:13:57 - mmengine - INFO - Epoch(train) [56][2020/2119] lr: 4.0000e-02 eta: 19:09:06 time: 0.3323 data_time: 0.0207 memory: 5826 grad_norm: 3.1210 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7991 loss: 2.7991 2022/10/07 19:14:04 - mmengine - INFO - Epoch(train) [56][2040/2119] lr: 4.0000e-02 eta: 19:08:59 time: 0.3510 data_time: 0.0198 memory: 5826 grad_norm: 3.0888 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8204 loss: 2.8204 2022/10/07 19:14:11 - mmengine - INFO - Epoch(train) [56][2060/2119] lr: 4.0000e-02 eta: 19:08:52 time: 0.3247 data_time: 0.0240 memory: 5826 grad_norm: 3.1099 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5902 loss: 2.5902 2022/10/07 19:14:19 - mmengine - INFO - Epoch(train) [56][2080/2119] lr: 4.0000e-02 eta: 19:08:46 time: 0.3804 data_time: 0.0230 memory: 5826 grad_norm: 3.0903 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6641 loss: 2.6641 2022/10/07 19:14:25 - mmengine - INFO - Epoch(train) [56][2100/2119] lr: 4.0000e-02 eta: 19:08:38 time: 0.3218 data_time: 0.0262 memory: 5826 grad_norm: 3.0777 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7901 loss: 2.7901 2022/10/07 19:14:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 19:14:31 - mmengine - INFO - Epoch(train) [56][2119/2119] lr: 4.0000e-02 eta: 19:08:38 time: 0.3086 data_time: 0.0172 memory: 5826 grad_norm: 3.1580 top1_acc: 0.4000 top5_acc: 0.6000 loss_cls: 2.8827 loss: 2.8827 2022/10/07 19:14:31 - mmengine - INFO - Saving checkpoint at 56 epochs 2022/10/07 19:14:48 - mmengine - INFO - Epoch(train) [57][20/2119] lr: 4.0000e-02 eta: 19:08:14 time: 0.3697 data_time: 0.1352 memory: 5826 grad_norm: 3.0553 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7174 loss: 2.7174 2022/10/07 19:14:54 - mmengine - INFO - Epoch(train) [57][40/2119] lr: 4.0000e-02 eta: 19:08:06 time: 0.2985 data_time: 0.0734 memory: 5826 grad_norm: 3.0725 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7189 loss: 2.7189 2022/10/07 19:15:02 - mmengine - INFO - Epoch(train) [57][60/2119] lr: 4.0000e-02 eta: 19:08:00 time: 0.3801 data_time: 0.0262 memory: 5826 grad_norm: 3.0869 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.4705 loss: 2.4705 2022/10/07 19:15:08 - mmengine - INFO - Epoch(train) [57][80/2119] lr: 4.0000e-02 eta: 19:07:53 time: 0.3292 data_time: 0.0220 memory: 5826 grad_norm: 3.1411 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7156 loss: 2.7156 2022/10/07 19:15:15 - mmengine - INFO - Epoch(train) [57][100/2119] lr: 4.0000e-02 eta: 19:07:46 time: 0.3420 data_time: 0.0226 memory: 5826 grad_norm: 3.1320 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4798 loss: 2.4798 2022/10/07 19:15:22 - mmengine - INFO - Epoch(train) [57][120/2119] lr: 4.0000e-02 eta: 19:07:39 time: 0.3459 data_time: 0.0229 memory: 5826 grad_norm: 3.1214 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8118 loss: 2.8118 2022/10/07 19:15:29 - mmengine - INFO - Epoch(train) [57][140/2119] lr: 4.0000e-02 eta: 19:07:31 time: 0.3348 data_time: 0.0225 memory: 5826 grad_norm: 3.1087 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7856 loss: 2.7856 2022/10/07 19:15:35 - mmengine - INFO - Epoch(train) [57][160/2119] lr: 4.0000e-02 eta: 19:07:24 time: 0.3293 data_time: 0.0262 memory: 5826 grad_norm: 3.1406 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7337 loss: 2.7337 2022/10/07 19:15:42 - mmengine - INFO - Epoch(train) [57][180/2119] lr: 4.0000e-02 eta: 19:07:17 time: 0.3495 data_time: 0.0212 memory: 5826 grad_norm: 3.0979 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5811 loss: 2.5811 2022/10/07 19:15:49 - mmengine - INFO - Epoch(train) [57][200/2119] lr: 4.0000e-02 eta: 19:07:10 time: 0.3251 data_time: 0.0205 memory: 5826 grad_norm: 3.1438 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.3791 loss: 2.3791 2022/10/07 19:15:56 - mmengine - INFO - Epoch(train) [57][220/2119] lr: 4.0000e-02 eta: 19:07:02 time: 0.3297 data_time: 0.0247 memory: 5826 grad_norm: 3.1342 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7816 loss: 2.7816 2022/10/07 19:16:03 - mmengine - INFO - Epoch(train) [57][240/2119] lr: 4.0000e-02 eta: 19:06:56 time: 0.3712 data_time: 0.0186 memory: 5826 grad_norm: 3.0875 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9045 loss: 2.9045 2022/10/07 19:16:09 - mmengine - INFO - Epoch(train) [57][260/2119] lr: 4.0000e-02 eta: 19:06:48 time: 0.3026 data_time: 0.0210 memory: 5826 grad_norm: 3.1345 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6051 loss: 2.6051 2022/10/07 19:16:17 - mmengine - INFO - Epoch(train) [57][280/2119] lr: 4.0000e-02 eta: 19:06:43 time: 0.4105 data_time: 0.0250 memory: 5826 grad_norm: 3.1034 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6188 loss: 2.6188 2022/10/07 19:16:24 - mmengine - INFO - Epoch(train) [57][300/2119] lr: 4.0000e-02 eta: 19:06:35 time: 0.3302 data_time: 0.0230 memory: 5826 grad_norm: 3.0785 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7048 loss: 2.7048 2022/10/07 19:16:31 - mmengine - INFO - Epoch(train) [57][320/2119] lr: 4.0000e-02 eta: 19:06:29 time: 0.3498 data_time: 0.0221 memory: 5826 grad_norm: 3.1196 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9057 loss: 2.9057 2022/10/07 19:16:37 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 19:16:38 - mmengine - INFO - Epoch(train) [57][340/2119] lr: 4.0000e-02 eta: 19:06:22 time: 0.3437 data_time: 0.0182 memory: 5826 grad_norm: 3.1363 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7497 loss: 2.7497 2022/10/07 19:16:45 - mmengine - INFO - Epoch(train) [57][360/2119] lr: 4.0000e-02 eta: 19:06:16 time: 0.3793 data_time: 0.0184 memory: 5826 grad_norm: 3.1048 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6370 loss: 2.6370 2022/10/07 19:16:52 - mmengine - INFO - Epoch(train) [57][380/2119] lr: 4.0000e-02 eta: 19:06:08 time: 0.3154 data_time: 0.0270 memory: 5826 grad_norm: 3.1207 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8951 loss: 2.8951 2022/10/07 19:17:00 - mmengine - INFO - Epoch(train) [57][400/2119] lr: 4.0000e-02 eta: 19:06:03 time: 0.3926 data_time: 0.0386 memory: 5826 grad_norm: 3.0888 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.6123 loss: 2.6123 2022/10/07 19:17:05 - mmengine - INFO - Epoch(train) [57][420/2119] lr: 4.0000e-02 eta: 19:05:53 time: 0.2772 data_time: 0.0185 memory: 5826 grad_norm: 3.0914 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8377 loss: 2.8377 2022/10/07 19:17:12 - mmengine - INFO - Epoch(train) [57][440/2119] lr: 4.0000e-02 eta: 19:05:46 time: 0.3413 data_time: 0.0250 memory: 5826 grad_norm: 3.1175 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7009 loss: 2.7009 2022/10/07 19:17:19 - mmengine - INFO - Epoch(train) [57][460/2119] lr: 4.0000e-02 eta: 19:05:40 time: 0.3728 data_time: 0.0321 memory: 5826 grad_norm: 3.1083 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6526 loss: 2.6526 2022/10/07 19:17:26 - mmengine - INFO - Epoch(train) [57][480/2119] lr: 4.0000e-02 eta: 19:05:34 time: 0.3561 data_time: 0.0218 memory: 5826 grad_norm: 3.1460 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7174 loss: 2.7174 2022/10/07 19:17:32 - mmengine - INFO - Epoch(train) [57][500/2119] lr: 4.0000e-02 eta: 19:05:25 time: 0.2970 data_time: 0.0229 memory: 5826 grad_norm: 3.1703 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6441 loss: 2.6441 2022/10/07 19:17:40 - mmengine - INFO - Epoch(train) [57][520/2119] lr: 4.0000e-02 eta: 19:05:20 time: 0.3921 data_time: 0.0232 memory: 5826 grad_norm: 3.1380 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7886 loss: 2.7886 2022/10/07 19:17:47 - mmengine - INFO - Epoch(train) [57][540/2119] lr: 4.0000e-02 eta: 19:05:12 time: 0.3225 data_time: 0.0213 memory: 5826 grad_norm: 3.0601 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9318 loss: 2.9318 2022/10/07 19:17:54 - mmengine - INFO - Epoch(train) [57][560/2119] lr: 4.0000e-02 eta: 19:05:06 time: 0.3563 data_time: 0.0182 memory: 5826 grad_norm: 3.1344 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6416 loss: 2.6416 2022/10/07 19:18:01 - mmengine - INFO - Epoch(train) [57][580/2119] lr: 4.0000e-02 eta: 19:05:00 time: 0.3760 data_time: 0.0242 memory: 5826 grad_norm: 3.0903 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6663 loss: 2.6663 2022/10/07 19:18:08 - mmengine - INFO - Epoch(train) [57][600/2119] lr: 4.0000e-02 eta: 19:04:51 time: 0.3093 data_time: 0.0211 memory: 5826 grad_norm: 3.1003 top1_acc: 0.3125 top5_acc: 0.3125 loss_cls: 2.7022 loss: 2.7022 2022/10/07 19:18:15 - mmengine - INFO - Epoch(train) [57][620/2119] lr: 4.0000e-02 eta: 19:04:45 time: 0.3493 data_time: 0.0215 memory: 5826 grad_norm: 3.1345 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8745 loss: 2.8745 2022/10/07 19:18:22 - mmengine - INFO - Epoch(train) [57][640/2119] lr: 4.0000e-02 eta: 19:04:39 time: 0.3897 data_time: 0.0243 memory: 5826 grad_norm: 3.0938 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.6655 loss: 2.6655 2022/10/07 19:18:29 - mmengine - INFO - Epoch(train) [57][660/2119] lr: 4.0000e-02 eta: 19:04:32 time: 0.3402 data_time: 0.0223 memory: 5826 grad_norm: 3.1686 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7773 loss: 2.7773 2022/10/07 19:18:36 - mmengine - INFO - Epoch(train) [57][680/2119] lr: 4.0000e-02 eta: 19:04:25 time: 0.3368 data_time: 0.0208 memory: 5826 grad_norm: 3.1476 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9663 loss: 2.9663 2022/10/07 19:18:43 - mmengine - INFO - Epoch(train) [57][700/2119] lr: 4.0000e-02 eta: 19:04:18 time: 0.3327 data_time: 0.0343 memory: 5826 grad_norm: 3.1503 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6678 loss: 2.6678 2022/10/07 19:18:50 - mmengine - INFO - Epoch(train) [57][720/2119] lr: 4.0000e-02 eta: 19:04:11 time: 0.3488 data_time: 0.0227 memory: 5826 grad_norm: 3.0714 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6135 loss: 2.6135 2022/10/07 19:18:56 - mmengine - INFO - Epoch(train) [57][740/2119] lr: 4.0000e-02 eta: 19:04:02 time: 0.3056 data_time: 0.0248 memory: 5826 grad_norm: 3.1687 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.4833 loss: 2.4833 2022/10/07 19:19:03 - mmengine - INFO - Epoch(train) [57][760/2119] lr: 4.0000e-02 eta: 19:03:57 time: 0.3769 data_time: 0.0233 memory: 5826 grad_norm: 3.1142 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7773 loss: 2.7773 2022/10/07 19:19:09 - mmengine - INFO - Epoch(train) [57][780/2119] lr: 4.0000e-02 eta: 19:03:48 time: 0.3076 data_time: 0.0294 memory: 5826 grad_norm: 3.1289 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7302 loss: 2.7302 2022/10/07 19:19:17 - mmengine - INFO - Epoch(train) [57][800/2119] lr: 4.0000e-02 eta: 19:03:43 time: 0.3849 data_time: 0.0247 memory: 5826 grad_norm: 3.0992 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6290 loss: 2.6290 2022/10/07 19:19:23 - mmengine - INFO - Epoch(train) [57][820/2119] lr: 4.0000e-02 eta: 19:03:35 time: 0.3179 data_time: 0.0157 memory: 5826 grad_norm: 3.0533 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6553 loss: 2.6553 2022/10/07 19:19:31 - mmengine - INFO - Epoch(train) [57][840/2119] lr: 4.0000e-02 eta: 19:03:29 time: 0.3653 data_time: 0.0224 memory: 5826 grad_norm: 3.0832 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.4034 loss: 2.4034 2022/10/07 19:19:38 - mmengine - INFO - Epoch(train) [57][860/2119] lr: 4.0000e-02 eta: 19:03:22 time: 0.3434 data_time: 0.0228 memory: 5826 grad_norm: 3.1115 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7293 loss: 2.7293 2022/10/07 19:19:45 - mmengine - INFO - Epoch(train) [57][880/2119] lr: 4.0000e-02 eta: 19:03:15 time: 0.3678 data_time: 0.0205 memory: 5826 grad_norm: 3.1795 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7179 loss: 2.7179 2022/10/07 19:19:51 - mmengine - INFO - Epoch(train) [57][900/2119] lr: 4.0000e-02 eta: 19:03:07 time: 0.2944 data_time: 0.0212 memory: 5826 grad_norm: 3.1179 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7905 loss: 2.7905 2022/10/07 19:19:59 - mmengine - INFO - Epoch(train) [57][920/2119] lr: 4.0000e-02 eta: 19:03:01 time: 0.3893 data_time: 0.0242 memory: 5826 grad_norm: 3.0949 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8117 loss: 2.8117 2022/10/07 19:20:05 - mmengine - INFO - Epoch(train) [57][940/2119] lr: 4.0000e-02 eta: 19:02:54 time: 0.3263 data_time: 0.0162 memory: 5826 grad_norm: 3.1461 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9635 loss: 2.9635 2022/10/07 19:20:12 - mmengine - INFO - Epoch(train) [57][960/2119] lr: 4.0000e-02 eta: 19:02:47 time: 0.3485 data_time: 0.0182 memory: 5826 grad_norm: 3.0791 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8349 loss: 2.8349 2022/10/07 19:20:19 - mmengine - INFO - Epoch(train) [57][980/2119] lr: 4.0000e-02 eta: 19:02:40 time: 0.3407 data_time: 0.0238 memory: 5826 grad_norm: 3.1085 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7258 loss: 2.7258 2022/10/07 19:20:26 - mmengine - INFO - Epoch(train) [57][1000/2119] lr: 4.0000e-02 eta: 19:02:33 time: 0.3598 data_time: 0.0253 memory: 5826 grad_norm: 3.1266 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.0871 loss: 3.0871 2022/10/07 19:20:33 - mmengine - INFO - Epoch(train) [57][1020/2119] lr: 4.0000e-02 eta: 19:02:26 time: 0.3199 data_time: 0.0222 memory: 5826 grad_norm: 3.1565 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7664 loss: 2.7664 2022/10/07 19:20:40 - mmengine - INFO - Epoch(train) [57][1040/2119] lr: 4.0000e-02 eta: 19:02:19 time: 0.3549 data_time: 0.0248 memory: 5826 grad_norm: 3.1376 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8125 loss: 2.8125 2022/10/07 19:20:47 - mmengine - INFO - Epoch(train) [57][1060/2119] lr: 4.0000e-02 eta: 19:02:12 time: 0.3438 data_time: 0.0280 memory: 5826 grad_norm: 3.1608 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6904 loss: 2.6904 2022/10/07 19:20:54 - mmengine - INFO - Epoch(train) [57][1080/2119] lr: 4.0000e-02 eta: 19:02:06 time: 0.3804 data_time: 0.0176 memory: 5826 grad_norm: 3.1197 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8272 loss: 2.8272 2022/10/07 19:21:02 - mmengine - INFO - Epoch(train) [57][1100/2119] lr: 4.0000e-02 eta: 19:02:01 time: 0.3869 data_time: 0.0194 memory: 5826 grad_norm: 3.0514 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7816 loss: 2.7816 2022/10/07 19:21:08 - mmengine - INFO - Epoch(train) [57][1120/2119] lr: 4.0000e-02 eta: 19:01:53 time: 0.3101 data_time: 0.0255 memory: 5826 grad_norm: 3.1484 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9712 loss: 2.9712 2022/10/07 19:21:15 - mmengine - INFO - Epoch(train) [57][1140/2119] lr: 4.0000e-02 eta: 19:01:46 time: 0.3554 data_time: 0.0214 memory: 5826 grad_norm: 3.1015 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9256 loss: 2.9256 2022/10/07 19:21:22 - mmengine - INFO - Epoch(train) [57][1160/2119] lr: 4.0000e-02 eta: 19:01:40 time: 0.3635 data_time: 0.0217 memory: 5826 grad_norm: 3.0527 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8081 loss: 2.8081 2022/10/07 19:21:30 - mmengine - INFO - Epoch(train) [57][1180/2119] lr: 4.0000e-02 eta: 19:01:33 time: 0.3610 data_time: 0.0218 memory: 5826 grad_norm: 3.1242 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9748 loss: 2.9748 2022/10/07 19:21:36 - mmengine - INFO - Epoch(train) [57][1200/2119] lr: 4.0000e-02 eta: 19:01:26 time: 0.3374 data_time: 0.0197 memory: 5826 grad_norm: 3.0924 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7260 loss: 2.7260 2022/10/07 19:21:45 - mmengine - INFO - Epoch(train) [57][1220/2119] lr: 4.0000e-02 eta: 19:01:21 time: 0.4193 data_time: 0.0306 memory: 5826 grad_norm: 3.0641 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7609 loss: 2.7609 2022/10/07 19:21:51 - mmengine - INFO - Epoch(train) [57][1240/2119] lr: 4.0000e-02 eta: 19:01:14 time: 0.3229 data_time: 0.0202 memory: 5826 grad_norm: 3.1670 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7755 loss: 2.7755 2022/10/07 19:21:59 - mmengine - INFO - Epoch(train) [57][1260/2119] lr: 4.0000e-02 eta: 19:01:08 time: 0.3736 data_time: 0.0178 memory: 5826 grad_norm: 3.0979 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6786 loss: 2.6786 2022/10/07 19:22:05 - mmengine - INFO - Epoch(train) [57][1280/2119] lr: 4.0000e-02 eta: 19:01:00 time: 0.3189 data_time: 0.0238 memory: 5826 grad_norm: 3.0694 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8822 loss: 2.8822 2022/10/07 19:22:13 - mmengine - INFO - Epoch(train) [57][1300/2119] lr: 4.0000e-02 eta: 19:00:54 time: 0.3872 data_time: 0.0195 memory: 5826 grad_norm: 3.1536 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.9799 loss: 2.9799 2022/10/07 19:22:19 - mmengine - INFO - Epoch(train) [57][1320/2119] lr: 4.0000e-02 eta: 19:00:45 time: 0.2810 data_time: 0.0273 memory: 5826 grad_norm: 3.0381 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9473 loss: 2.9473 2022/10/07 19:22:25 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 19:22:27 - mmengine - INFO - Epoch(train) [57][1340/2119] lr: 4.0000e-02 eta: 19:00:40 time: 0.3986 data_time: 0.0235 memory: 5826 grad_norm: 3.0874 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 2.7370 loss: 2.7370 2022/10/07 19:22:33 - mmengine - INFO - Epoch(train) [57][1360/2119] lr: 4.0000e-02 eta: 19:00:32 time: 0.3036 data_time: 0.0295 memory: 5826 grad_norm: 3.0605 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7460 loss: 2.7460 2022/10/07 19:22:40 - mmengine - INFO - Epoch(train) [57][1380/2119] lr: 4.0000e-02 eta: 19:00:26 time: 0.3866 data_time: 0.0181 memory: 5826 grad_norm: 3.0986 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7980 loss: 2.7980 2022/10/07 19:22:46 - mmengine - INFO - Epoch(train) [57][1400/2119] lr: 4.0000e-02 eta: 19:00:18 time: 0.3037 data_time: 0.0222 memory: 5826 grad_norm: 3.1192 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9211 loss: 2.9211 2022/10/07 19:22:53 - mmengine - INFO - Epoch(train) [57][1420/2119] lr: 4.0000e-02 eta: 19:00:10 time: 0.3194 data_time: 0.0248 memory: 5826 grad_norm: 3.0889 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 3.1115 loss: 3.1115 2022/10/07 19:23:01 - mmengine - INFO - Epoch(train) [57][1440/2119] lr: 4.0000e-02 eta: 19:00:05 time: 0.3965 data_time: 0.0242 memory: 5826 grad_norm: 3.0760 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4987 loss: 2.4987 2022/10/07 19:23:07 - mmengine - INFO - Epoch(train) [57][1460/2119] lr: 4.0000e-02 eta: 18:59:58 time: 0.3344 data_time: 0.0208 memory: 5826 grad_norm: 3.0986 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8446 loss: 2.8446 2022/10/07 19:23:14 - mmengine - INFO - Epoch(train) [57][1480/2119] lr: 4.0000e-02 eta: 18:59:51 time: 0.3484 data_time: 0.0212 memory: 5826 grad_norm: 3.0391 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9836 loss: 2.9836 2022/10/07 19:23:22 - mmengine - INFO - Epoch(train) [57][1500/2119] lr: 4.0000e-02 eta: 18:59:44 time: 0.3574 data_time: 0.0224 memory: 5826 grad_norm: 3.0638 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6099 loss: 2.6099 2022/10/07 19:23:29 - mmengine - INFO - Epoch(train) [57][1520/2119] lr: 4.0000e-02 eta: 18:59:38 time: 0.3607 data_time: 0.0207 memory: 5826 grad_norm: 3.0947 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5181 loss: 2.5181 2022/10/07 19:23:35 - mmengine - INFO - Epoch(train) [57][1540/2119] lr: 4.0000e-02 eta: 18:59:29 time: 0.2972 data_time: 0.0255 memory: 5826 grad_norm: 3.0808 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9297 loss: 2.9297 2022/10/07 19:23:42 - mmengine - INFO - Epoch(train) [57][1560/2119] lr: 4.0000e-02 eta: 18:59:23 time: 0.3756 data_time: 0.0273 memory: 5826 grad_norm: 3.0951 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8504 loss: 2.8504 2022/10/07 19:23:49 - mmengine - INFO - Epoch(train) [57][1580/2119] lr: 4.0000e-02 eta: 18:59:16 time: 0.3451 data_time: 0.0219 memory: 5826 grad_norm: 3.1322 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9030 loss: 2.9030 2022/10/07 19:23:55 - mmengine - INFO - Epoch(train) [57][1600/2119] lr: 4.0000e-02 eta: 18:59:08 time: 0.3110 data_time: 0.0287 memory: 5826 grad_norm: 3.0810 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6743 loss: 2.6743 2022/10/07 19:24:03 - mmengine - INFO - Epoch(train) [57][1620/2119] lr: 4.0000e-02 eta: 18:59:02 time: 0.3750 data_time: 0.0225 memory: 5826 grad_norm: 3.0899 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6490 loss: 2.6490 2022/10/07 19:24:10 - mmengine - INFO - Epoch(train) [57][1640/2119] lr: 4.0000e-02 eta: 18:58:56 time: 0.3479 data_time: 0.0236 memory: 5826 grad_norm: 3.0644 top1_acc: 0.1875 top5_acc: 0.8125 loss_cls: 2.7049 loss: 2.7049 2022/10/07 19:24:17 - mmengine - INFO - Epoch(train) [57][1660/2119] lr: 4.0000e-02 eta: 18:58:49 time: 0.3475 data_time: 0.0217 memory: 5826 grad_norm: 3.0900 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6391 loss: 2.6391 2022/10/07 19:24:24 - mmengine - INFO - Epoch(train) [57][1680/2119] lr: 4.0000e-02 eta: 18:58:42 time: 0.3402 data_time: 0.0274 memory: 5826 grad_norm: 3.0771 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6840 loss: 2.6840 2022/10/07 19:24:31 - mmengine - INFO - Epoch(train) [57][1700/2119] lr: 4.0000e-02 eta: 18:58:35 time: 0.3571 data_time: 0.0203 memory: 5826 grad_norm: 3.1483 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6829 loss: 2.6829 2022/10/07 19:24:38 - mmengine - INFO - Epoch(train) [57][1720/2119] lr: 4.0000e-02 eta: 18:58:29 time: 0.3622 data_time: 0.0197 memory: 5826 grad_norm: 3.1591 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7329 loss: 2.7329 2022/10/07 19:24:45 - mmengine - INFO - Epoch(train) [57][1740/2119] lr: 4.0000e-02 eta: 18:58:22 time: 0.3647 data_time: 0.0227 memory: 5826 grad_norm: 3.1470 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7931 loss: 2.7931 2022/10/07 19:24:52 - mmengine - INFO - Epoch(train) [57][1760/2119] lr: 4.0000e-02 eta: 18:58:14 time: 0.3151 data_time: 0.0205 memory: 5826 grad_norm: 3.0895 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6482 loss: 2.6482 2022/10/07 19:24:59 - mmengine - INFO - Epoch(train) [57][1780/2119] lr: 4.0000e-02 eta: 18:58:08 time: 0.3719 data_time: 0.0176 memory: 5826 grad_norm: 3.1411 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6400 loss: 2.6400 2022/10/07 19:25:05 - mmengine - INFO - Epoch(train) [57][1800/2119] lr: 4.0000e-02 eta: 18:58:00 time: 0.3142 data_time: 0.0214 memory: 5826 grad_norm: 3.0863 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7634 loss: 2.7634 2022/10/07 19:25:13 - mmengine - INFO - Epoch(train) [57][1820/2119] lr: 4.0000e-02 eta: 18:57:54 time: 0.3681 data_time: 0.0199 memory: 5826 grad_norm: 3.0622 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5654 loss: 2.5654 2022/10/07 19:25:19 - mmengine - INFO - Epoch(train) [57][1840/2119] lr: 4.0000e-02 eta: 18:57:45 time: 0.2922 data_time: 0.0171 memory: 5826 grad_norm: 3.1082 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8318 loss: 2.8318 2022/10/07 19:25:26 - mmengine - INFO - Epoch(train) [57][1860/2119] lr: 4.0000e-02 eta: 18:57:39 time: 0.3556 data_time: 0.0233 memory: 5826 grad_norm: 3.2053 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9188 loss: 2.9188 2022/10/07 19:25:33 - mmengine - INFO - Epoch(train) [57][1880/2119] lr: 4.0000e-02 eta: 18:57:32 time: 0.3450 data_time: 0.0225 memory: 5826 grad_norm: 3.0586 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7462 loss: 2.7462 2022/10/07 19:25:41 - mmengine - INFO - Epoch(train) [57][1900/2119] lr: 4.0000e-02 eta: 18:57:27 time: 0.3989 data_time: 0.0246 memory: 5826 grad_norm: 3.1125 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6844 loss: 2.6844 2022/10/07 19:25:47 - mmengine - INFO - Epoch(train) [57][1920/2119] lr: 4.0000e-02 eta: 18:57:19 time: 0.3214 data_time: 0.0234 memory: 5826 grad_norm: 3.1367 top1_acc: 0.1875 top5_acc: 0.7500 loss_cls: 2.6089 loss: 2.6089 2022/10/07 19:25:54 - mmengine - INFO - Epoch(train) [57][1940/2119] lr: 4.0000e-02 eta: 18:57:12 time: 0.3347 data_time: 0.0255 memory: 5826 grad_norm: 3.1130 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5163 loss: 2.5163 2022/10/07 19:26:00 - mmengine - INFO - Epoch(train) [57][1960/2119] lr: 4.0000e-02 eta: 18:57:04 time: 0.3251 data_time: 0.0256 memory: 5826 grad_norm: 3.1277 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8243 loss: 2.8243 2022/10/07 19:26:07 - mmengine - INFO - Epoch(train) [57][1980/2119] lr: 4.0000e-02 eta: 18:56:57 time: 0.3371 data_time: 0.0180 memory: 5826 grad_norm: 3.1207 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9023 loss: 2.9023 2022/10/07 19:26:14 - mmengine - INFO - Epoch(train) [57][2000/2119] lr: 4.0000e-02 eta: 18:56:50 time: 0.3442 data_time: 0.0251 memory: 5826 grad_norm: 3.0866 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8847 loss: 2.8847 2022/10/07 19:26:21 - mmengine - INFO - Epoch(train) [57][2020/2119] lr: 4.0000e-02 eta: 18:56:43 time: 0.3543 data_time: 0.0218 memory: 5826 grad_norm: 3.1501 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5932 loss: 2.5932 2022/10/07 19:26:28 - mmengine - INFO - Epoch(train) [57][2040/2119] lr: 4.0000e-02 eta: 18:56:37 time: 0.3499 data_time: 0.0249 memory: 5826 grad_norm: 3.1340 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8242 loss: 2.8242 2022/10/07 19:26:35 - mmengine - INFO - Epoch(train) [57][2060/2119] lr: 4.0000e-02 eta: 18:56:30 time: 0.3670 data_time: 0.0198 memory: 5826 grad_norm: 3.1202 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7066 loss: 2.7066 2022/10/07 19:26:42 - mmengine - INFO - Epoch(train) [57][2080/2119] lr: 4.0000e-02 eta: 18:56:23 time: 0.3358 data_time: 0.0242 memory: 5826 grad_norm: 3.0534 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8467 loss: 2.8467 2022/10/07 19:26:49 - mmengine - INFO - Epoch(train) [57][2100/2119] lr: 4.0000e-02 eta: 18:56:16 time: 0.3378 data_time: 0.0263 memory: 5826 grad_norm: 3.0861 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9178 loss: 2.9178 2022/10/07 19:26:54 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 19:26:54 - mmengine - INFO - Epoch(train) [57][2119/2119] lr: 4.0000e-02 eta: 18:56:16 time: 0.2880 data_time: 0.0147 memory: 5826 grad_norm: 3.0946 top1_acc: 0.7000 top5_acc: 0.8000 loss_cls: 2.4885 loss: 2.4885 2022/10/07 19:27:04 - mmengine - INFO - Epoch(train) [58][20/2119] lr: 4.0000e-02 eta: 18:55:56 time: 0.4843 data_time: 0.1216 memory: 5826 grad_norm: 3.0671 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5505 loss: 2.5505 2022/10/07 19:27:10 - mmengine - INFO - Epoch(train) [58][40/2119] lr: 4.0000e-02 eta: 18:55:48 time: 0.3153 data_time: 0.0222 memory: 5826 grad_norm: 3.0678 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6466 loss: 2.6466 2022/10/07 19:27:18 - mmengine - INFO - Epoch(train) [58][60/2119] lr: 4.0000e-02 eta: 18:55:42 time: 0.3685 data_time: 0.0233 memory: 5826 grad_norm: 3.0142 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7044 loss: 2.7044 2022/10/07 19:27:24 - mmengine - INFO - Epoch(train) [58][80/2119] lr: 4.0000e-02 eta: 18:55:33 time: 0.2933 data_time: 0.0245 memory: 5826 grad_norm: 3.0868 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6329 loss: 2.6329 2022/10/07 19:27:31 - mmengine - INFO - Epoch(train) [58][100/2119] lr: 4.0000e-02 eta: 18:55:27 time: 0.3740 data_time: 0.0214 memory: 5826 grad_norm: 3.1391 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6736 loss: 2.6736 2022/10/07 19:27:38 - mmengine - INFO - Epoch(train) [58][120/2119] lr: 4.0000e-02 eta: 18:55:20 time: 0.3390 data_time: 0.0331 memory: 5826 grad_norm: 3.1178 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5107 loss: 2.5107 2022/10/07 19:27:46 - mmengine - INFO - Epoch(train) [58][140/2119] lr: 4.0000e-02 eta: 18:55:14 time: 0.3798 data_time: 0.0276 memory: 5826 grad_norm: 3.0927 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.8634 loss: 2.8634 2022/10/07 19:27:52 - mmengine - INFO - Epoch(train) [58][160/2119] lr: 4.0000e-02 eta: 18:55:07 time: 0.3370 data_time: 0.0183 memory: 5826 grad_norm: 3.1502 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7798 loss: 2.7798 2022/10/07 19:27:59 - mmengine - INFO - Epoch(train) [58][180/2119] lr: 4.0000e-02 eta: 18:55:01 time: 0.3591 data_time: 0.0219 memory: 5826 grad_norm: 3.1478 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9642 loss: 2.9642 2022/10/07 19:28:06 - mmengine - INFO - Epoch(train) [58][200/2119] lr: 4.0000e-02 eta: 18:54:53 time: 0.3068 data_time: 0.0215 memory: 5826 grad_norm: 3.1079 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8568 loss: 2.8568 2022/10/07 19:28:12 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 19:28:13 - mmengine - INFO - Epoch(train) [58][220/2119] lr: 4.0000e-02 eta: 18:54:47 time: 0.3860 data_time: 0.0215 memory: 5826 grad_norm: 3.1686 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7707 loss: 2.7707 2022/10/07 19:28:20 - mmengine - INFO - Epoch(train) [58][240/2119] lr: 4.0000e-02 eta: 18:54:40 time: 0.3410 data_time: 0.0195 memory: 5826 grad_norm: 3.1104 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8027 loss: 2.8027 2022/10/07 19:28:28 - mmengine - INFO - Epoch(train) [58][260/2119] lr: 4.0000e-02 eta: 18:54:34 time: 0.3891 data_time: 0.0211 memory: 5826 grad_norm: 3.1779 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7597 loss: 2.7597 2022/10/07 19:28:34 - mmengine - INFO - Epoch(train) [58][280/2119] lr: 4.0000e-02 eta: 18:54:26 time: 0.3006 data_time: 0.0253 memory: 5826 grad_norm: 3.1239 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7314 loss: 2.7314 2022/10/07 19:28:41 - mmengine - INFO - Epoch(train) [58][300/2119] lr: 4.0000e-02 eta: 18:54:19 time: 0.3415 data_time: 0.0227 memory: 5826 grad_norm: 3.1647 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6427 loss: 2.6427 2022/10/07 19:28:47 - mmengine - INFO - Epoch(train) [58][320/2119] lr: 4.0000e-02 eta: 18:54:12 time: 0.3348 data_time: 0.0259 memory: 5826 grad_norm: 3.1134 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6341 loss: 2.6341 2022/10/07 19:28:54 - mmengine - INFO - Epoch(train) [58][340/2119] lr: 4.0000e-02 eta: 18:54:04 time: 0.3240 data_time: 0.0234 memory: 5826 grad_norm: 3.1034 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7372 loss: 2.7372 2022/10/07 19:29:01 - mmengine - INFO - Epoch(train) [58][360/2119] lr: 4.0000e-02 eta: 18:53:57 time: 0.3433 data_time: 0.0230 memory: 5826 grad_norm: 3.1748 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5912 loss: 2.5912 2022/10/07 19:29:08 - mmengine - INFO - Epoch(train) [58][380/2119] lr: 4.0000e-02 eta: 18:53:51 time: 0.3581 data_time: 0.0255 memory: 5826 grad_norm: 3.1752 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8424 loss: 2.8424 2022/10/07 19:29:16 - mmengine - INFO - Epoch(train) [58][400/2119] lr: 4.0000e-02 eta: 18:53:45 time: 0.3915 data_time: 0.0215 memory: 5826 grad_norm: 3.1393 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6585 loss: 2.6585 2022/10/07 19:29:22 - mmengine - INFO - Epoch(train) [58][420/2119] lr: 4.0000e-02 eta: 18:53:37 time: 0.3162 data_time: 0.0183 memory: 5826 grad_norm: 3.0895 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7824 loss: 2.7824 2022/10/07 19:29:29 - mmengine - INFO - Epoch(train) [58][440/2119] lr: 4.0000e-02 eta: 18:53:30 time: 0.3447 data_time: 0.0248 memory: 5826 grad_norm: 3.0792 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7128 loss: 2.7128 2022/10/07 19:29:35 - mmengine - INFO - Epoch(train) [58][460/2119] lr: 4.0000e-02 eta: 18:53:22 time: 0.3205 data_time: 0.0219 memory: 5826 grad_norm: 3.1074 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8797 loss: 2.8797 2022/10/07 19:29:43 - mmengine - INFO - Epoch(train) [58][480/2119] lr: 4.0000e-02 eta: 18:53:16 time: 0.3542 data_time: 0.0249 memory: 5826 grad_norm: 3.1271 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7310 loss: 2.7310 2022/10/07 19:29:49 - mmengine - INFO - Epoch(train) [58][500/2119] lr: 4.0000e-02 eta: 18:53:08 time: 0.3308 data_time: 0.0230 memory: 5826 grad_norm: 3.0614 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7558 loss: 2.7558 2022/10/07 19:29:56 - mmengine - INFO - Epoch(train) [58][520/2119] lr: 4.0000e-02 eta: 18:53:01 time: 0.3366 data_time: 0.0197 memory: 5826 grad_norm: 3.0815 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5175 loss: 2.5175 2022/10/07 19:30:03 - mmengine - INFO - Epoch(train) [58][540/2119] lr: 4.0000e-02 eta: 18:52:54 time: 0.3494 data_time: 0.0250 memory: 5826 grad_norm: 3.1726 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6658 loss: 2.6658 2022/10/07 19:30:10 - mmengine - INFO - Epoch(train) [58][560/2119] lr: 4.0000e-02 eta: 18:52:47 time: 0.3398 data_time: 0.0268 memory: 5826 grad_norm: 3.0558 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7954 loss: 2.7954 2022/10/07 19:30:16 - mmengine - INFO - Epoch(train) [58][580/2119] lr: 4.0000e-02 eta: 18:52:40 time: 0.3256 data_time: 0.0208 memory: 5826 grad_norm: 3.1052 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.4657 loss: 2.4657 2022/10/07 19:30:24 - mmengine - INFO - Epoch(train) [58][600/2119] lr: 4.0000e-02 eta: 18:52:34 time: 0.3840 data_time: 0.0206 memory: 5826 grad_norm: 3.0999 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5692 loss: 2.5692 2022/10/07 19:30:30 - mmengine - INFO - Epoch(train) [58][620/2119] lr: 4.0000e-02 eta: 18:52:27 time: 0.3297 data_time: 0.0195 memory: 5826 grad_norm: 3.1766 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.6737 loss: 2.6737 2022/10/07 19:30:37 - mmengine - INFO - Epoch(train) [58][640/2119] lr: 4.0000e-02 eta: 18:52:20 time: 0.3410 data_time: 0.0275 memory: 5826 grad_norm: 3.1640 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9270 loss: 2.9270 2022/10/07 19:30:44 - mmengine - INFO - Epoch(train) [58][660/2119] lr: 4.0000e-02 eta: 18:52:13 time: 0.3513 data_time: 0.0176 memory: 5826 grad_norm: 3.1383 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7920 loss: 2.7920 2022/10/07 19:30:51 - mmengine - INFO - Epoch(train) [58][680/2119] lr: 4.0000e-02 eta: 18:52:06 time: 0.3545 data_time: 0.0213 memory: 5826 grad_norm: 3.0951 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7667 loss: 2.7667 2022/10/07 19:30:58 - mmengine - INFO - Epoch(train) [58][700/2119] lr: 4.0000e-02 eta: 18:51:58 time: 0.3227 data_time: 0.0257 memory: 5826 grad_norm: 3.1927 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6483 loss: 2.6483 2022/10/07 19:31:05 - mmengine - INFO - Epoch(train) [58][720/2119] lr: 4.0000e-02 eta: 18:51:52 time: 0.3607 data_time: 0.0227 memory: 5826 grad_norm: 3.1317 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5905 loss: 2.5905 2022/10/07 19:31:13 - mmengine - INFO - Epoch(train) [58][740/2119] lr: 4.0000e-02 eta: 18:51:47 time: 0.3935 data_time: 0.0176 memory: 5826 grad_norm: 3.1471 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9551 loss: 2.9551 2022/10/07 19:31:20 - mmengine - INFO - Epoch(train) [58][760/2119] lr: 4.0000e-02 eta: 18:51:40 time: 0.3532 data_time: 0.0199 memory: 5826 grad_norm: 3.1298 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8001 loss: 2.8001 2022/10/07 19:31:28 - mmengine - INFO - Epoch(train) [58][780/2119] lr: 4.0000e-02 eta: 18:51:34 time: 0.3801 data_time: 0.0194 memory: 5826 grad_norm: 3.1013 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8118 loss: 2.8118 2022/10/07 19:31:34 - mmengine - INFO - Epoch(train) [58][800/2119] lr: 4.0000e-02 eta: 18:51:26 time: 0.3155 data_time: 0.0179 memory: 5826 grad_norm: 3.1515 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7655 loss: 2.7655 2022/10/07 19:31:41 - mmengine - INFO - Epoch(train) [58][820/2119] lr: 4.0000e-02 eta: 18:51:20 time: 0.3548 data_time: 0.0236 memory: 5826 grad_norm: 3.1712 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5817 loss: 2.5817 2022/10/07 19:31:47 - mmengine - INFO - Epoch(train) [58][840/2119] lr: 4.0000e-02 eta: 18:51:12 time: 0.3131 data_time: 0.0222 memory: 5826 grad_norm: 3.1196 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6322 loss: 2.6322 2022/10/07 19:31:54 - mmengine - INFO - Epoch(train) [58][860/2119] lr: 4.0000e-02 eta: 18:51:05 time: 0.3472 data_time: 0.0225 memory: 5826 grad_norm: 3.1084 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7513 loss: 2.7513 2022/10/07 19:32:01 - mmengine - INFO - Epoch(train) [58][880/2119] lr: 4.0000e-02 eta: 18:50:58 time: 0.3575 data_time: 0.0179 memory: 5826 grad_norm: 3.0658 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7660 loss: 2.7660 2022/10/07 19:32:08 - mmengine - INFO - Epoch(train) [58][900/2119] lr: 4.0000e-02 eta: 18:50:51 time: 0.3221 data_time: 0.0260 memory: 5826 grad_norm: 3.1280 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6970 loss: 2.6970 2022/10/07 19:32:14 - mmengine - INFO - Epoch(train) [58][920/2119] lr: 4.0000e-02 eta: 18:50:43 time: 0.3278 data_time: 0.0221 memory: 5826 grad_norm: 3.0880 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6207 loss: 2.6207 2022/10/07 19:32:22 - mmengine - INFO - Epoch(train) [58][940/2119] lr: 4.0000e-02 eta: 18:50:37 time: 0.3773 data_time: 0.0156 memory: 5826 grad_norm: 3.1362 top1_acc: 0.0625 top5_acc: 0.3750 loss_cls: 3.1114 loss: 3.1114 2022/10/07 19:32:29 - mmengine - INFO - Epoch(train) [58][960/2119] lr: 4.0000e-02 eta: 18:50:30 time: 0.3380 data_time: 0.0270 memory: 5826 grad_norm: 3.1492 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8427 loss: 2.8427 2022/10/07 19:32:36 - mmengine - INFO - Epoch(train) [58][980/2119] lr: 4.0000e-02 eta: 18:50:23 time: 0.3457 data_time: 0.0251 memory: 5826 grad_norm: 3.0852 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7191 loss: 2.7191 2022/10/07 19:32:42 - mmengine - INFO - Epoch(train) [58][1000/2119] lr: 4.0000e-02 eta: 18:50:16 time: 0.3319 data_time: 0.0194 memory: 5826 grad_norm: 3.0295 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7261 loss: 2.7261 2022/10/07 19:32:49 - mmengine - INFO - Epoch(train) [58][1020/2119] lr: 4.0000e-02 eta: 18:50:08 time: 0.3246 data_time: 0.0202 memory: 5826 grad_norm: 3.0827 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6312 loss: 2.6312 2022/10/07 19:32:55 - mmengine - INFO - Epoch(train) [58][1040/2119] lr: 4.0000e-02 eta: 18:50:00 time: 0.3180 data_time: 0.0218 memory: 5826 grad_norm: 3.0975 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7833 loss: 2.7833 2022/10/07 19:33:03 - mmengine - INFO - Epoch(train) [58][1060/2119] lr: 4.0000e-02 eta: 18:49:56 time: 0.4146 data_time: 0.0187 memory: 5826 grad_norm: 3.1397 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5193 loss: 2.5193 2022/10/07 19:33:10 - mmengine - INFO - Epoch(train) [58][1080/2119] lr: 4.0000e-02 eta: 18:49:48 time: 0.3395 data_time: 0.0259 memory: 5826 grad_norm: 3.1486 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7357 loss: 2.7357 2022/10/07 19:33:17 - mmengine - INFO - Epoch(train) [58][1100/2119] lr: 4.0000e-02 eta: 18:49:41 time: 0.3385 data_time: 0.0215 memory: 5826 grad_norm: 3.1431 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 2.9869 loss: 2.9869 2022/10/07 19:33:24 - mmengine - INFO - Epoch(train) [58][1120/2119] lr: 4.0000e-02 eta: 18:49:34 time: 0.3261 data_time: 0.0239 memory: 5826 grad_norm: 3.1167 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8628 loss: 2.8628 2022/10/07 19:33:31 - mmengine - INFO - Epoch(train) [58][1140/2119] lr: 4.0000e-02 eta: 18:49:28 time: 0.3861 data_time: 0.0191 memory: 5826 grad_norm: 3.1243 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7977 loss: 2.7977 2022/10/07 19:33:37 - mmengine - INFO - Epoch(train) [58][1160/2119] lr: 4.0000e-02 eta: 18:49:20 time: 0.3071 data_time: 0.0236 memory: 5826 grad_norm: 3.1175 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7427 loss: 2.7427 2022/10/07 19:33:45 - mmengine - INFO - Epoch(train) [58][1180/2119] lr: 4.0000e-02 eta: 18:49:14 time: 0.3666 data_time: 0.0199 memory: 5826 grad_norm: 3.1575 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5888 loss: 2.5888 2022/10/07 19:33:51 - mmengine - INFO - Epoch(train) [58][1200/2119] lr: 4.0000e-02 eta: 18:49:06 time: 0.3255 data_time: 0.0221 memory: 5826 grad_norm: 3.1657 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8485 loss: 2.8485 2022/10/07 19:33:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 19:33:59 - mmengine - INFO - Epoch(train) [58][1220/2119] lr: 4.0000e-02 eta: 18:49:00 time: 0.3676 data_time: 0.0189 memory: 5826 grad_norm: 3.0392 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6852 loss: 2.6852 2022/10/07 19:34:05 - mmengine - INFO - Epoch(train) [58][1240/2119] lr: 4.0000e-02 eta: 18:48:52 time: 0.3051 data_time: 0.0224 memory: 5826 grad_norm: 3.0936 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8697 loss: 2.8697 2022/10/07 19:34:13 - mmengine - INFO - Epoch(train) [58][1260/2119] lr: 4.0000e-02 eta: 18:48:46 time: 0.3879 data_time: 0.0220 memory: 5826 grad_norm: 3.1769 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9005 loss: 2.9005 2022/10/07 19:34:19 - mmengine - INFO - Epoch(train) [58][1280/2119] lr: 4.0000e-02 eta: 18:48:38 time: 0.3044 data_time: 0.0258 memory: 5826 grad_norm: 3.1274 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.5468 loss: 2.5468 2022/10/07 19:34:26 - mmengine - INFO - Epoch(train) [58][1300/2119] lr: 4.0000e-02 eta: 18:48:32 time: 0.3940 data_time: 0.0181 memory: 5826 grad_norm: 3.0750 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8496 loss: 2.8496 2022/10/07 19:34:32 - mmengine - INFO - Epoch(train) [58][1320/2119] lr: 4.0000e-02 eta: 18:48:24 time: 0.2887 data_time: 0.0229 memory: 5826 grad_norm: 3.0468 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7318 loss: 2.7318 2022/10/07 19:34:40 - mmengine - INFO - Epoch(train) [58][1340/2119] lr: 4.0000e-02 eta: 18:48:18 time: 0.3808 data_time: 0.0186 memory: 5826 grad_norm: 3.1435 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7892 loss: 2.7892 2022/10/07 19:34:47 - mmengine - INFO - Epoch(train) [58][1360/2119] lr: 4.0000e-02 eta: 18:48:11 time: 0.3418 data_time: 0.0217 memory: 5826 grad_norm: 3.1239 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.7060 loss: 2.7060 2022/10/07 19:34:54 - mmengine - INFO - Epoch(train) [58][1380/2119] lr: 4.0000e-02 eta: 18:48:05 time: 0.3670 data_time: 0.0159 memory: 5826 grad_norm: 3.0972 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9100 loss: 2.9100 2022/10/07 19:35:01 - mmengine - INFO - Epoch(train) [58][1400/2119] lr: 4.0000e-02 eta: 18:47:58 time: 0.3638 data_time: 0.0217 memory: 5826 grad_norm: 3.1054 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8316 loss: 2.8316 2022/10/07 19:35:09 - mmengine - INFO - Epoch(train) [58][1420/2119] lr: 4.0000e-02 eta: 18:47:53 time: 0.3882 data_time: 0.0204 memory: 5826 grad_norm: 3.1105 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7411 loss: 2.7411 2022/10/07 19:35:16 - mmengine - INFO - Epoch(train) [58][1440/2119] lr: 4.0000e-02 eta: 18:47:45 time: 0.3262 data_time: 0.0203 memory: 5826 grad_norm: 3.1124 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6954 loss: 2.6954 2022/10/07 19:35:24 - mmengine - INFO - Epoch(train) [58][1460/2119] lr: 4.0000e-02 eta: 18:47:40 time: 0.4120 data_time: 0.0197 memory: 5826 grad_norm: 3.0402 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6199 loss: 2.6199 2022/10/07 19:35:31 - mmengine - INFO - Epoch(train) [58][1480/2119] lr: 4.0000e-02 eta: 18:47:33 time: 0.3362 data_time: 0.0200 memory: 5826 grad_norm: 3.1129 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8087 loss: 2.8087 2022/10/07 19:35:38 - mmengine - INFO - Epoch(train) [58][1500/2119] lr: 4.0000e-02 eta: 18:47:26 time: 0.3502 data_time: 0.0186 memory: 5826 grad_norm: 3.0990 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7626 loss: 2.7626 2022/10/07 19:35:44 - mmengine - INFO - Epoch(train) [58][1520/2119] lr: 4.0000e-02 eta: 18:47:19 time: 0.3345 data_time: 0.0235 memory: 5826 grad_norm: 3.0831 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7072 loss: 2.7072 2022/10/07 19:35:52 - mmengine - INFO - Epoch(train) [58][1540/2119] lr: 4.0000e-02 eta: 18:47:13 time: 0.3795 data_time: 0.0219 memory: 5826 grad_norm: 3.1061 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.4401 loss: 2.4401 2022/10/07 19:35:59 - mmengine - INFO - Epoch(train) [58][1560/2119] lr: 4.0000e-02 eta: 18:47:07 time: 0.3664 data_time: 0.0191 memory: 5826 grad_norm: 3.0918 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7925 loss: 2.7925 2022/10/07 19:36:08 - mmengine - INFO - Epoch(train) [58][1580/2119] lr: 4.0000e-02 eta: 18:47:02 time: 0.4152 data_time: 0.0238 memory: 5826 grad_norm: 3.1134 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7595 loss: 2.7595 2022/10/07 19:36:14 - mmengine - INFO - Epoch(train) [58][1600/2119] lr: 4.0000e-02 eta: 18:46:55 time: 0.3330 data_time: 0.0218 memory: 5826 grad_norm: 3.1122 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7845 loss: 2.7845 2022/10/07 19:36:21 - mmengine - INFO - Epoch(train) [58][1620/2119] lr: 4.0000e-02 eta: 18:46:48 time: 0.3294 data_time: 0.0178 memory: 5826 grad_norm: 3.1150 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9674 loss: 2.9674 2022/10/07 19:36:27 - mmengine - INFO - Epoch(train) [58][1640/2119] lr: 4.0000e-02 eta: 18:46:40 time: 0.3298 data_time: 0.0262 memory: 5826 grad_norm: 3.0821 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6299 loss: 2.6299 2022/10/07 19:36:34 - mmengine - INFO - Epoch(train) [58][1660/2119] lr: 4.0000e-02 eta: 18:46:32 time: 0.3207 data_time: 0.0234 memory: 5826 grad_norm: 3.1211 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7281 loss: 2.7281 2022/10/07 19:36:41 - mmengine - INFO - Epoch(train) [58][1680/2119] lr: 4.0000e-02 eta: 18:46:26 time: 0.3510 data_time: 0.0292 memory: 5826 grad_norm: 3.1060 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6554 loss: 2.6554 2022/10/07 19:36:48 - mmengine - INFO - Epoch(train) [58][1700/2119] lr: 4.0000e-02 eta: 18:46:19 time: 0.3698 data_time: 0.0199 memory: 5826 grad_norm: 3.0673 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8030 loss: 2.8030 2022/10/07 19:36:55 - mmengine - INFO - Epoch(train) [58][1720/2119] lr: 4.0000e-02 eta: 18:46:12 time: 0.3390 data_time: 0.0251 memory: 5826 grad_norm: 3.1204 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8784 loss: 2.8784 2022/10/07 19:37:01 - mmengine - INFO - Epoch(train) [58][1740/2119] lr: 4.0000e-02 eta: 18:46:04 time: 0.3027 data_time: 0.0183 memory: 5826 grad_norm: 3.0529 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7027 loss: 2.7027 2022/10/07 19:37:08 - mmengine - INFO - Epoch(train) [58][1760/2119] lr: 4.0000e-02 eta: 18:45:57 time: 0.3410 data_time: 0.0249 memory: 5826 grad_norm: 3.1482 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8735 loss: 2.8735 2022/10/07 19:37:15 - mmengine - INFO - Epoch(train) [58][1780/2119] lr: 4.0000e-02 eta: 18:45:51 time: 0.3700 data_time: 0.0173 memory: 5826 grad_norm: 3.1149 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8320 loss: 2.8320 2022/10/07 19:37:22 - mmengine - INFO - Epoch(train) [58][1800/2119] lr: 4.0000e-02 eta: 18:45:43 time: 0.3259 data_time: 0.0230 memory: 5826 grad_norm: 3.0814 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6578 loss: 2.6578 2022/10/07 19:37:29 - mmengine - INFO - Epoch(train) [58][1820/2119] lr: 4.0000e-02 eta: 18:45:37 time: 0.3812 data_time: 0.0205 memory: 5826 grad_norm: 3.1282 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8977 loss: 2.8977 2022/10/07 19:37:36 - mmengine - INFO - Epoch(train) [58][1840/2119] lr: 4.0000e-02 eta: 18:45:30 time: 0.3235 data_time: 0.0187 memory: 5826 grad_norm: 3.1558 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7157 loss: 2.7157 2022/10/07 19:37:44 - mmengine - INFO - Epoch(train) [58][1860/2119] lr: 4.0000e-02 eta: 18:45:25 time: 0.4049 data_time: 0.0269 memory: 5826 grad_norm: 3.1257 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8389 loss: 2.8389 2022/10/07 19:37:51 - mmengine - INFO - Epoch(train) [58][1880/2119] lr: 4.0000e-02 eta: 18:45:18 time: 0.3413 data_time: 0.0236 memory: 5826 grad_norm: 3.0493 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7785 loss: 2.7785 2022/10/07 19:37:58 - mmengine - INFO - Epoch(train) [58][1900/2119] lr: 4.0000e-02 eta: 18:45:11 time: 0.3506 data_time: 0.0202 memory: 5826 grad_norm: 3.1524 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7518 loss: 2.7518 2022/10/07 19:38:05 - mmengine - INFO - Epoch(train) [58][1920/2119] lr: 4.0000e-02 eta: 18:45:04 time: 0.3419 data_time: 0.0245 memory: 5826 grad_norm: 3.0810 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.8289 loss: 2.8289 2022/10/07 19:38:12 - mmengine - INFO - Epoch(train) [58][1940/2119] lr: 4.0000e-02 eta: 18:44:58 time: 0.3702 data_time: 0.0252 memory: 5826 grad_norm: 3.0883 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7187 loss: 2.7187 2022/10/07 19:38:18 - mmengine - INFO - Epoch(train) [58][1960/2119] lr: 4.0000e-02 eta: 18:44:49 time: 0.2831 data_time: 0.0284 memory: 5826 grad_norm: 3.1537 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5729 loss: 2.5729 2022/10/07 19:38:26 - mmengine - INFO - Epoch(train) [58][1980/2119] lr: 4.0000e-02 eta: 18:44:44 time: 0.3964 data_time: 0.0234 memory: 5826 grad_norm: 3.1321 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8560 loss: 2.8560 2022/10/07 19:38:33 - mmengine - INFO - Epoch(train) [58][2000/2119] lr: 4.0000e-02 eta: 18:44:37 time: 0.3435 data_time: 0.0240 memory: 5826 grad_norm: 3.1050 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8841 loss: 2.8841 2022/10/07 19:38:40 - mmengine - INFO - Epoch(train) [58][2020/2119] lr: 4.0000e-02 eta: 18:44:31 time: 0.3867 data_time: 0.0218 memory: 5826 grad_norm: 3.1146 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7922 loss: 2.7922 2022/10/07 19:38:47 - mmengine - INFO - Epoch(train) [58][2040/2119] lr: 4.0000e-02 eta: 18:44:24 time: 0.3429 data_time: 0.0227 memory: 5826 grad_norm: 3.0976 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5655 loss: 2.5655 2022/10/07 19:38:55 - mmengine - INFO - Epoch(train) [58][2060/2119] lr: 4.0000e-02 eta: 18:44:18 time: 0.3822 data_time: 0.0227 memory: 5826 grad_norm: 3.1322 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.4668 loss: 2.4668 2022/10/07 19:39:02 - mmengine - INFO - Epoch(train) [58][2080/2119] lr: 4.0000e-02 eta: 18:44:11 time: 0.3513 data_time: 0.0192 memory: 5826 grad_norm: 3.0996 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7144 loss: 2.7144 2022/10/07 19:39:10 - mmengine - INFO - Epoch(train) [58][2100/2119] lr: 4.0000e-02 eta: 18:44:07 time: 0.4128 data_time: 0.0191 memory: 5826 grad_norm: 3.0876 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8684 loss: 2.8684 2022/10/07 19:39:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 19:39:16 - mmengine - INFO - Epoch(train) [58][2119/2119] lr: 4.0000e-02 eta: 18:44:07 time: 0.3159 data_time: 0.0194 memory: 5826 grad_norm: 3.2297 top1_acc: 0.6000 top5_acc: 0.7000 loss_cls: 2.9210 loss: 2.9210 2022/10/07 19:39:26 - mmengine - INFO - Epoch(train) [59][20/2119] lr: 4.0000e-02 eta: 18:43:48 time: 0.5027 data_time: 0.1220 memory: 5826 grad_norm: 3.1282 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6874 loss: 2.6874 2022/10/07 19:39:33 - mmengine - INFO - Epoch(train) [59][40/2119] lr: 4.0000e-02 eta: 18:43:40 time: 0.3170 data_time: 0.0268 memory: 5826 grad_norm: 3.0480 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6647 loss: 2.6647 2022/10/07 19:39:40 - mmengine - INFO - Epoch(train) [59][60/2119] lr: 4.0000e-02 eta: 18:43:33 time: 0.3552 data_time: 0.0258 memory: 5826 grad_norm: 3.0712 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7944 loss: 2.7944 2022/10/07 19:39:46 - mmengine - INFO - Epoch(train) [59][80/2119] lr: 4.0000e-02 eta: 18:43:26 time: 0.3222 data_time: 0.0265 memory: 5826 grad_norm: 3.0736 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7209 loss: 2.7209 2022/10/07 19:39:54 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 19:39:54 - mmengine - INFO - Epoch(train) [59][100/2119] lr: 4.0000e-02 eta: 18:43:20 time: 0.4034 data_time: 0.0221 memory: 5826 grad_norm: 3.1372 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7559 loss: 2.7559 2022/10/07 19:40:02 - mmengine - INFO - Epoch(train) [59][120/2119] lr: 4.0000e-02 eta: 18:43:14 time: 0.3652 data_time: 0.0233 memory: 5826 grad_norm: 3.0620 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8679 loss: 2.8679 2022/10/07 19:40:09 - mmengine - INFO - Epoch(train) [59][140/2119] lr: 4.0000e-02 eta: 18:43:08 time: 0.3588 data_time: 0.0239 memory: 5826 grad_norm: 3.1532 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.9461 loss: 2.9461 2022/10/07 19:40:14 - mmengine - INFO - Epoch(train) [59][160/2119] lr: 4.0000e-02 eta: 18:42:59 time: 0.2798 data_time: 0.0228 memory: 5826 grad_norm: 3.0948 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7752 loss: 2.7752 2022/10/07 19:40:23 - mmengine - INFO - Epoch(train) [59][180/2119] lr: 4.0000e-02 eta: 18:42:54 time: 0.4192 data_time: 0.0275 memory: 5826 grad_norm: 3.0965 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6329 loss: 2.6329 2022/10/07 19:40:29 - mmengine - INFO - Epoch(train) [59][200/2119] lr: 4.0000e-02 eta: 18:42:45 time: 0.2877 data_time: 0.0262 memory: 5826 grad_norm: 3.0592 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.7556 loss: 2.7556 2022/10/07 19:40:36 - mmengine - INFO - Epoch(train) [59][220/2119] lr: 4.0000e-02 eta: 18:42:39 time: 0.3735 data_time: 0.0219 memory: 5826 grad_norm: 3.0327 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9520 loss: 2.9520 2022/10/07 19:40:43 - mmengine - INFO - Epoch(train) [59][240/2119] lr: 4.0000e-02 eta: 18:42:32 time: 0.3312 data_time: 0.0239 memory: 5826 grad_norm: 3.0682 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7697 loss: 2.7697 2022/10/07 19:40:50 - mmengine - INFO - Epoch(train) [59][260/2119] lr: 4.0000e-02 eta: 18:42:26 time: 0.3784 data_time: 0.0225 memory: 5826 grad_norm: 3.1145 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9019 loss: 2.9019 2022/10/07 19:40:57 - mmengine - INFO - Epoch(train) [59][280/2119] lr: 4.0000e-02 eta: 18:42:18 time: 0.3199 data_time: 0.0244 memory: 5826 grad_norm: 3.0753 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8069 loss: 2.8069 2022/10/07 19:41:04 - mmengine - INFO - Epoch(train) [59][300/2119] lr: 4.0000e-02 eta: 18:42:12 time: 0.3803 data_time: 0.0173 memory: 5826 grad_norm: 3.1721 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7624 loss: 2.7624 2022/10/07 19:41:11 - mmengine - INFO - Epoch(train) [59][320/2119] lr: 4.0000e-02 eta: 18:42:05 time: 0.3401 data_time: 0.0226 memory: 5826 grad_norm: 3.1028 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9731 loss: 2.9731 2022/10/07 19:41:18 - mmengine - INFO - Epoch(train) [59][340/2119] lr: 4.0000e-02 eta: 18:41:58 time: 0.3374 data_time: 0.0206 memory: 5826 grad_norm: 3.1217 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7812 loss: 2.7812 2022/10/07 19:41:24 - mmengine - INFO - Epoch(train) [59][360/2119] lr: 4.0000e-02 eta: 18:41:50 time: 0.3117 data_time: 0.0271 memory: 5826 grad_norm: 3.1190 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.4676 loss: 2.4676 2022/10/07 19:41:32 - mmengine - INFO - Epoch(train) [59][380/2119] lr: 4.0000e-02 eta: 18:41:44 time: 0.3781 data_time: 0.0200 memory: 5826 grad_norm: 3.1196 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7020 loss: 2.7020 2022/10/07 19:41:38 - mmengine - INFO - Epoch(train) [59][400/2119] lr: 4.0000e-02 eta: 18:41:36 time: 0.3134 data_time: 0.0259 memory: 5826 grad_norm: 3.0979 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5090 loss: 2.5090 2022/10/07 19:41:46 - mmengine - INFO - Epoch(train) [59][420/2119] lr: 4.0000e-02 eta: 18:41:31 time: 0.3961 data_time: 0.0288 memory: 5826 grad_norm: 3.0908 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8601 loss: 2.8601 2022/10/07 19:41:52 - mmengine - INFO - Epoch(train) [59][440/2119] lr: 4.0000e-02 eta: 18:41:23 time: 0.3222 data_time: 0.0214 memory: 5826 grad_norm: 3.1115 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7745 loss: 2.7745 2022/10/07 19:42:00 - mmengine - INFO - Epoch(train) [59][460/2119] lr: 4.0000e-02 eta: 18:41:17 time: 0.3836 data_time: 0.0227 memory: 5826 grad_norm: 3.0348 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.3763 loss: 2.3763 2022/10/07 19:42:06 - mmengine - INFO - Epoch(train) [59][480/2119] lr: 4.0000e-02 eta: 18:41:10 time: 0.3257 data_time: 0.0204 memory: 5826 grad_norm: 3.1032 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7275 loss: 2.7275 2022/10/07 19:42:13 - mmengine - INFO - Epoch(train) [59][500/2119] lr: 4.0000e-02 eta: 18:41:03 time: 0.3431 data_time: 0.0210 memory: 5826 grad_norm: 3.0966 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8846 loss: 2.8846 2022/10/07 19:42:19 - mmengine - INFO - Epoch(train) [59][520/2119] lr: 4.0000e-02 eta: 18:40:55 time: 0.3044 data_time: 0.0287 memory: 5826 grad_norm: 3.0546 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5684 loss: 2.5684 2022/10/07 19:42:28 - mmengine - INFO - Epoch(train) [59][540/2119] lr: 4.0000e-02 eta: 18:40:50 time: 0.4234 data_time: 0.0229 memory: 5826 grad_norm: 3.0616 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.9693 loss: 2.9693 2022/10/07 19:42:34 - mmengine - INFO - Epoch(train) [59][560/2119] lr: 4.0000e-02 eta: 18:40:41 time: 0.2873 data_time: 0.0214 memory: 5826 grad_norm: 3.1746 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8452 loss: 2.8452 2022/10/07 19:42:41 - mmengine - INFO - Epoch(train) [59][580/2119] lr: 4.0000e-02 eta: 18:40:35 time: 0.3747 data_time: 0.0356 memory: 5826 grad_norm: 3.1087 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.1341 loss: 3.1341 2022/10/07 19:42:47 - mmengine - INFO - Epoch(train) [59][600/2119] lr: 4.0000e-02 eta: 18:40:27 time: 0.3120 data_time: 0.0212 memory: 5826 grad_norm: 3.0851 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5441 loss: 2.5441 2022/10/07 19:42:54 - mmengine - INFO - Epoch(train) [59][620/2119] lr: 4.0000e-02 eta: 18:40:21 time: 0.3522 data_time: 0.0249 memory: 5826 grad_norm: 3.1490 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7793 loss: 2.7793 2022/10/07 19:43:01 - mmengine - INFO - Epoch(train) [59][640/2119] lr: 4.0000e-02 eta: 18:40:14 time: 0.3491 data_time: 0.0247 memory: 5826 grad_norm: 3.1275 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6624 loss: 2.6624 2022/10/07 19:43:09 - mmengine - INFO - Epoch(train) [59][660/2119] lr: 4.0000e-02 eta: 18:40:08 time: 0.3639 data_time: 0.0194 memory: 5826 grad_norm: 3.0711 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8276 loss: 2.8276 2022/10/07 19:43:15 - mmengine - INFO - Epoch(train) [59][680/2119] lr: 4.0000e-02 eta: 18:40:00 time: 0.3166 data_time: 0.0276 memory: 5826 grad_norm: 3.1184 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5960 loss: 2.5960 2022/10/07 19:43:22 - mmengine - INFO - Epoch(train) [59][700/2119] lr: 4.0000e-02 eta: 18:39:54 time: 0.3692 data_time: 0.0148 memory: 5826 grad_norm: 3.1172 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5870 loss: 2.5870 2022/10/07 19:43:29 - mmengine - INFO - Epoch(train) [59][720/2119] lr: 4.0000e-02 eta: 18:39:46 time: 0.3301 data_time: 0.0240 memory: 5826 grad_norm: 3.1416 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7914 loss: 2.7914 2022/10/07 19:43:37 - mmengine - INFO - Epoch(train) [59][740/2119] lr: 4.0000e-02 eta: 18:39:41 time: 0.3889 data_time: 0.0142 memory: 5826 grad_norm: 3.0806 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8002 loss: 2.8002 2022/10/07 19:43:44 - mmengine - INFO - Epoch(train) [59][760/2119] lr: 4.0000e-02 eta: 18:39:34 time: 0.3531 data_time: 0.0241 memory: 5826 grad_norm: 3.1072 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8876 loss: 2.8876 2022/10/07 19:43:52 - mmengine - INFO - Epoch(train) [59][780/2119] lr: 4.0000e-02 eta: 18:39:29 time: 0.4068 data_time: 0.0178 memory: 5826 grad_norm: 3.0956 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6182 loss: 2.6182 2022/10/07 19:43:58 - mmengine - INFO - Epoch(train) [59][800/2119] lr: 4.0000e-02 eta: 18:39:21 time: 0.3148 data_time: 0.0247 memory: 5826 grad_norm: 3.1033 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7308 loss: 2.7308 2022/10/07 19:44:06 - mmengine - INFO - Epoch(train) [59][820/2119] lr: 4.0000e-02 eta: 18:39:15 time: 0.3658 data_time: 0.0222 memory: 5826 grad_norm: 3.1097 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6306 loss: 2.6306 2022/10/07 19:44:12 - mmengine - INFO - Epoch(train) [59][840/2119] lr: 4.0000e-02 eta: 18:39:07 time: 0.3101 data_time: 0.0227 memory: 5826 grad_norm: 3.0784 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6238 loss: 2.6238 2022/10/07 19:44:18 - mmengine - INFO - Epoch(train) [59][860/2119] lr: 4.0000e-02 eta: 18:38:59 time: 0.3304 data_time: 0.0154 memory: 5826 grad_norm: 3.1624 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8554 loss: 2.8554 2022/10/07 19:44:25 - mmengine - INFO - Epoch(train) [59][880/2119] lr: 4.0000e-02 eta: 18:38:52 time: 0.3293 data_time: 0.0266 memory: 5826 grad_norm: 3.1049 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6704 loss: 2.6704 2022/10/07 19:44:32 - mmengine - INFO - Epoch(train) [59][900/2119] lr: 4.0000e-02 eta: 18:38:45 time: 0.3644 data_time: 0.0238 memory: 5826 grad_norm: 3.1062 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7643 loss: 2.7643 2022/10/07 19:44:39 - mmengine - INFO - Epoch(train) [59][920/2119] lr: 4.0000e-02 eta: 18:38:38 time: 0.3377 data_time: 0.0287 memory: 5826 grad_norm: 3.0994 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7688 loss: 2.7688 2022/10/07 19:44:47 - mmengine - INFO - Epoch(train) [59][940/2119] lr: 4.0000e-02 eta: 18:38:33 time: 0.3901 data_time: 0.0195 memory: 5826 grad_norm: 3.1131 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8089 loss: 2.8089 2022/10/07 19:44:54 - mmengine - INFO - Epoch(train) [59][960/2119] lr: 4.0000e-02 eta: 18:38:26 time: 0.3396 data_time: 0.0232 memory: 5826 grad_norm: 3.1327 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7881 loss: 2.7881 2022/10/07 19:45:01 - mmengine - INFO - Epoch(train) [59][980/2119] lr: 4.0000e-02 eta: 18:38:19 time: 0.3706 data_time: 0.0247 memory: 5826 grad_norm: 3.0976 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5026 loss: 2.5026 2022/10/07 19:45:07 - mmengine - INFO - Epoch(train) [59][1000/2119] lr: 4.0000e-02 eta: 18:38:12 time: 0.3173 data_time: 0.0237 memory: 5826 grad_norm: 3.1331 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9008 loss: 2.9008 2022/10/07 19:45:16 - mmengine - INFO - Epoch(train) [59][1020/2119] lr: 4.0000e-02 eta: 18:38:07 time: 0.4173 data_time: 0.0204 memory: 5826 grad_norm: 3.0879 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6911 loss: 2.6911 2022/10/07 19:45:23 - mmengine - INFO - Epoch(train) [59][1040/2119] lr: 4.0000e-02 eta: 18:38:00 time: 0.3481 data_time: 0.0237 memory: 5826 grad_norm: 3.1698 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.9073 loss: 2.9073 2022/10/07 19:45:31 - mmengine - INFO - Epoch(train) [59][1060/2119] lr: 4.0000e-02 eta: 18:37:55 time: 0.3909 data_time: 0.0177 memory: 5826 grad_norm: 3.0958 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7125 loss: 2.7125 2022/10/07 19:45:37 - mmengine - INFO - Epoch(train) [59][1080/2119] lr: 4.0000e-02 eta: 18:37:47 time: 0.3202 data_time: 0.0203 memory: 5826 grad_norm: 3.0834 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6113 loss: 2.6113 2022/10/07 19:45:44 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 19:45:45 - mmengine - INFO - Epoch(train) [59][1100/2119] lr: 4.0000e-02 eta: 18:37:41 time: 0.3861 data_time: 0.0233 memory: 5826 grad_norm: 3.1262 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6281 loss: 2.6281 2022/10/07 19:45:51 - mmengine - INFO - Epoch(train) [59][1120/2119] lr: 4.0000e-02 eta: 18:37:33 time: 0.3159 data_time: 0.0245 memory: 5826 grad_norm: 3.1130 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8603 loss: 2.8603 2022/10/07 19:45:59 - mmengine - INFO - Epoch(train) [59][1140/2119] lr: 4.0000e-02 eta: 18:37:27 time: 0.3800 data_time: 0.0196 memory: 5826 grad_norm: 3.0936 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7823 loss: 2.7823 2022/10/07 19:46:06 - mmengine - INFO - Epoch(train) [59][1160/2119] lr: 4.0000e-02 eta: 18:37:22 time: 0.3817 data_time: 0.0236 memory: 5826 grad_norm: 3.1349 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6315 loss: 2.6315 2022/10/07 19:46:13 - mmengine - INFO - Epoch(train) [59][1180/2119] lr: 4.0000e-02 eta: 18:37:15 time: 0.3435 data_time: 0.0208 memory: 5826 grad_norm: 3.1725 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6560 loss: 2.6560 2022/10/07 19:46:19 - mmengine - INFO - Epoch(train) [59][1200/2119] lr: 4.0000e-02 eta: 18:37:06 time: 0.2793 data_time: 0.0243 memory: 5826 grad_norm: 3.1065 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8142 loss: 2.8142 2022/10/07 19:46:27 - mmengine - INFO - Epoch(train) [59][1220/2119] lr: 4.0000e-02 eta: 18:37:01 time: 0.4175 data_time: 0.0334 memory: 5826 grad_norm: 3.1432 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7394 loss: 2.7394 2022/10/07 19:46:33 - mmengine - INFO - Epoch(train) [59][1240/2119] lr: 4.0000e-02 eta: 18:36:53 time: 0.3106 data_time: 0.0214 memory: 5826 grad_norm: 3.1057 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.4684 loss: 2.4684 2022/10/07 19:46:40 - mmengine - INFO - Epoch(train) [59][1260/2119] lr: 4.0000e-02 eta: 18:36:46 time: 0.3522 data_time: 0.0242 memory: 5826 grad_norm: 3.0898 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8994 loss: 2.8994 2022/10/07 19:46:47 - mmengine - INFO - Epoch(train) [59][1280/2119] lr: 4.0000e-02 eta: 18:36:39 time: 0.3354 data_time: 0.0273 memory: 5826 grad_norm: 3.1212 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6700 loss: 2.6700 2022/10/07 19:46:54 - mmengine - INFO - Epoch(train) [59][1300/2119] lr: 4.0000e-02 eta: 18:36:32 time: 0.3481 data_time: 0.0182 memory: 5826 grad_norm: 3.0788 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.6493 loss: 2.6493 2022/10/07 19:47:01 - mmengine - INFO - Epoch(train) [59][1320/2119] lr: 4.0000e-02 eta: 18:36:26 time: 0.3616 data_time: 0.0230 memory: 5826 grad_norm: 3.0581 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6304 loss: 2.6304 2022/10/07 19:47:10 - mmengine - INFO - Epoch(train) [59][1340/2119] lr: 4.0000e-02 eta: 18:36:21 time: 0.4295 data_time: 0.0180 memory: 5826 grad_norm: 3.0683 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7697 loss: 2.7697 2022/10/07 19:47:17 - mmengine - INFO - Epoch(train) [59][1360/2119] lr: 4.0000e-02 eta: 18:36:14 time: 0.3347 data_time: 0.0205 memory: 5826 grad_norm: 3.1365 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7357 loss: 2.7357 2022/10/07 19:47:23 - mmengine - INFO - Epoch(train) [59][1380/2119] lr: 4.0000e-02 eta: 18:36:07 time: 0.3438 data_time: 0.0201 memory: 5826 grad_norm: 3.1601 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5480 loss: 2.5480 2022/10/07 19:47:30 - mmengine - INFO - Epoch(train) [59][1400/2119] lr: 4.0000e-02 eta: 18:36:00 time: 0.3362 data_time: 0.0170 memory: 5826 grad_norm: 3.1227 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.7726 loss: 2.7726 2022/10/07 19:47:37 - mmengine - INFO - Epoch(train) [59][1420/2119] lr: 4.0000e-02 eta: 18:35:53 time: 0.3563 data_time: 0.0225 memory: 5826 grad_norm: 3.1475 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6435 loss: 2.6435 2022/10/07 19:47:44 - mmengine - INFO - Epoch(train) [59][1440/2119] lr: 4.0000e-02 eta: 18:35:47 time: 0.3583 data_time: 0.0215 memory: 5826 grad_norm: 3.1643 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8003 loss: 2.8003 2022/10/07 19:47:52 - mmengine - INFO - Epoch(train) [59][1460/2119] lr: 4.0000e-02 eta: 18:35:40 time: 0.3579 data_time: 0.0192 memory: 5826 grad_norm: 3.1377 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7295 loss: 2.7295 2022/10/07 19:47:58 - mmengine - INFO - Epoch(train) [59][1480/2119] lr: 4.0000e-02 eta: 18:35:32 time: 0.3156 data_time: 0.0299 memory: 5826 grad_norm: 3.1340 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6698 loss: 2.6698 2022/10/07 19:48:06 - mmengine - INFO - Epoch(train) [59][1500/2119] lr: 4.0000e-02 eta: 18:35:27 time: 0.3803 data_time: 0.0164 memory: 5826 grad_norm: 3.1015 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5998 loss: 2.5998 2022/10/07 19:48:12 - mmengine - INFO - Epoch(train) [59][1520/2119] lr: 4.0000e-02 eta: 18:35:19 time: 0.3308 data_time: 0.0242 memory: 5826 grad_norm: 3.0648 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6422 loss: 2.6422 2022/10/07 19:48:20 - mmengine - INFO - Epoch(train) [59][1540/2119] lr: 4.0000e-02 eta: 18:35:14 time: 0.3880 data_time: 0.0197 memory: 5826 grad_norm: 3.1335 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8470 loss: 2.8470 2022/10/07 19:48:26 - mmengine - INFO - Epoch(train) [59][1560/2119] lr: 4.0000e-02 eta: 18:35:05 time: 0.3064 data_time: 0.0217 memory: 5826 grad_norm: 3.0976 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7868 loss: 2.7868 2022/10/07 19:48:33 - mmengine - INFO - Epoch(train) [59][1580/2119] lr: 4.0000e-02 eta: 18:34:59 time: 0.3526 data_time: 0.0180 memory: 5826 grad_norm: 3.1502 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8386 loss: 2.8386 2022/10/07 19:48:40 - mmengine - INFO - Epoch(train) [59][1600/2119] lr: 4.0000e-02 eta: 18:34:51 time: 0.3297 data_time: 0.0205 memory: 5826 grad_norm: 3.0779 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7619 loss: 2.7619 2022/10/07 19:48:48 - mmengine - INFO - Epoch(train) [59][1620/2119] lr: 4.0000e-02 eta: 18:34:46 time: 0.3986 data_time: 0.0210 memory: 5826 grad_norm: 3.0941 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7797 loss: 2.7797 2022/10/07 19:48:54 - mmengine - INFO - Epoch(train) [59][1640/2119] lr: 4.0000e-02 eta: 18:34:38 time: 0.3094 data_time: 0.0206 memory: 5826 grad_norm: 3.0787 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.8055 loss: 2.8055 2022/10/07 19:49:02 - mmengine - INFO - Epoch(train) [59][1660/2119] lr: 4.0000e-02 eta: 18:34:33 time: 0.4150 data_time: 0.0182 memory: 5826 grad_norm: 3.0924 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5131 loss: 2.5131 2022/10/07 19:49:09 - mmengine - INFO - Epoch(train) [59][1680/2119] lr: 4.0000e-02 eta: 18:34:25 time: 0.3210 data_time: 0.0217 memory: 5826 grad_norm: 3.1032 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8202 loss: 2.8202 2022/10/07 19:49:16 - mmengine - INFO - Epoch(train) [59][1700/2119] lr: 4.0000e-02 eta: 18:34:20 time: 0.3822 data_time: 0.0194 memory: 5826 grad_norm: 3.1173 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.6948 loss: 2.6948 2022/10/07 19:49:23 - mmengine - INFO - Epoch(train) [59][1720/2119] lr: 4.0000e-02 eta: 18:34:12 time: 0.3226 data_time: 0.0271 memory: 5826 grad_norm: 3.0766 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9945 loss: 2.9945 2022/10/07 19:49:31 - mmengine - INFO - Epoch(train) [59][1740/2119] lr: 4.0000e-02 eta: 18:34:07 time: 0.3968 data_time: 0.0215 memory: 5826 grad_norm: 3.1080 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7046 loss: 2.7046 2022/10/07 19:49:36 - mmengine - INFO - Epoch(train) [59][1760/2119] lr: 4.0000e-02 eta: 18:33:57 time: 0.2730 data_time: 0.0272 memory: 5826 grad_norm: 3.1229 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9437 loss: 2.9437 2022/10/07 19:49:44 - mmengine - INFO - Epoch(train) [59][1780/2119] lr: 4.0000e-02 eta: 18:33:51 time: 0.3712 data_time: 0.0218 memory: 5826 grad_norm: 3.1352 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8318 loss: 2.8318 2022/10/07 19:49:51 - mmengine - INFO - Epoch(train) [59][1800/2119] lr: 4.0000e-02 eta: 18:33:44 time: 0.3474 data_time: 0.0256 memory: 5826 grad_norm: 3.0926 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7841 loss: 2.7841 2022/10/07 19:49:57 - mmengine - INFO - Epoch(train) [59][1820/2119] lr: 4.0000e-02 eta: 18:33:37 time: 0.3446 data_time: 0.0224 memory: 5826 grad_norm: 3.0388 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6185 loss: 2.6185 2022/10/07 19:50:05 - mmengine - INFO - Epoch(train) [59][1840/2119] lr: 4.0000e-02 eta: 18:33:31 time: 0.3560 data_time: 0.0209 memory: 5826 grad_norm: 3.1116 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6812 loss: 2.6812 2022/10/07 19:50:12 - mmengine - INFO - Epoch(train) [59][1860/2119] lr: 4.0000e-02 eta: 18:33:24 time: 0.3627 data_time: 0.0223 memory: 5826 grad_norm: 3.1139 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8273 loss: 2.8273 2022/10/07 19:50:19 - mmengine - INFO - Epoch(train) [59][1880/2119] lr: 4.0000e-02 eta: 18:33:17 time: 0.3391 data_time: 0.0203 memory: 5826 grad_norm: 3.1088 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4223 loss: 2.4223 2022/10/07 19:50:26 - mmengine - INFO - Epoch(train) [59][1900/2119] lr: 4.0000e-02 eta: 18:33:11 time: 0.3712 data_time: 0.0198 memory: 5826 grad_norm: 3.0896 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7916 loss: 2.7916 2022/10/07 19:50:32 - mmengine - INFO - Epoch(train) [59][1920/2119] lr: 4.0000e-02 eta: 18:33:03 time: 0.2987 data_time: 0.0252 memory: 5826 grad_norm: 3.1082 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7810 loss: 2.7810 2022/10/07 19:50:40 - mmengine - INFO - Epoch(train) [59][1940/2119] lr: 4.0000e-02 eta: 18:32:58 time: 0.3991 data_time: 0.0213 memory: 5826 grad_norm: 3.0645 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6179 loss: 2.6179 2022/10/07 19:50:46 - mmengine - INFO - Epoch(train) [59][1960/2119] lr: 4.0000e-02 eta: 18:32:50 time: 0.3116 data_time: 0.0242 memory: 5826 grad_norm: 3.0959 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7235 loss: 2.7235 2022/10/07 19:50:53 - mmengine - INFO - Epoch(train) [59][1980/2119] lr: 4.0000e-02 eta: 18:32:43 time: 0.3476 data_time: 0.0201 memory: 5826 grad_norm: 3.1369 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7426 loss: 2.7426 2022/10/07 19:51:01 - mmengine - INFO - Epoch(train) [59][2000/2119] lr: 4.0000e-02 eta: 18:32:36 time: 0.3665 data_time: 0.0244 memory: 5826 grad_norm: 3.0981 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 3.0503 loss: 3.0503 2022/10/07 19:51:07 - mmengine - INFO - Epoch(train) [59][2020/2119] lr: 4.0000e-02 eta: 18:32:29 time: 0.3222 data_time: 0.0232 memory: 5826 grad_norm: 3.1226 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.7954 loss: 2.7954 2022/10/07 19:51:14 - mmengine - INFO - Epoch(train) [59][2040/2119] lr: 4.0000e-02 eta: 18:32:22 time: 0.3592 data_time: 0.0214 memory: 5826 grad_norm: 3.0934 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7462 loss: 2.7462 2022/10/07 19:51:21 - mmengine - INFO - Epoch(train) [59][2060/2119] lr: 4.0000e-02 eta: 18:32:16 time: 0.3643 data_time: 0.0223 memory: 5826 grad_norm: 3.1759 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.5184 loss: 2.5184 2022/10/07 19:51:29 - mmengine - INFO - Epoch(train) [59][2080/2119] lr: 4.0000e-02 eta: 18:32:11 time: 0.3969 data_time: 0.0223 memory: 5826 grad_norm: 3.1436 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7736 loss: 2.7736 2022/10/07 19:51:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 19:51:36 - mmengine - INFO - Epoch(train) [59][2100/2119] lr: 4.0000e-02 eta: 18:32:04 time: 0.3460 data_time: 0.0223 memory: 5826 grad_norm: 3.0977 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6711 loss: 2.6711 2022/10/07 19:51:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 19:51:42 - mmengine - INFO - Epoch(train) [59][2119/2119] lr: 4.0000e-02 eta: 18:32:04 time: 0.2827 data_time: 0.0216 memory: 5826 grad_norm: 3.0887 top1_acc: 0.3000 top5_acc: 0.7000 loss_cls: 2.6955 loss: 2.6955 2022/10/07 19:51:52 - mmengine - INFO - Epoch(train) [60][20/2119] lr: 4.0000e-02 eta: 18:31:46 time: 0.5269 data_time: 0.2746 memory: 5826 grad_norm: 3.1190 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8407 loss: 2.8407 2022/10/07 19:51:59 - mmengine - INFO - Epoch(train) [60][40/2119] lr: 4.0000e-02 eta: 18:31:38 time: 0.3263 data_time: 0.0663 memory: 5826 grad_norm: 3.1049 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6837 loss: 2.6837 2022/10/07 19:52:06 - mmengine - INFO - Epoch(train) [60][60/2119] lr: 4.0000e-02 eta: 18:31:31 time: 0.3554 data_time: 0.0853 memory: 5826 grad_norm: 3.1683 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8700 loss: 2.8700 2022/10/07 19:52:13 - mmengine - INFO - Epoch(train) [60][80/2119] lr: 4.0000e-02 eta: 18:31:24 time: 0.3285 data_time: 0.0869 memory: 5826 grad_norm: 3.1755 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8297 loss: 2.8297 2022/10/07 19:52:19 - mmengine - INFO - Epoch(train) [60][100/2119] lr: 4.0000e-02 eta: 18:31:17 time: 0.3449 data_time: 0.0471 memory: 5826 grad_norm: 3.1188 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7549 loss: 2.7549 2022/10/07 19:52:26 - mmengine - INFO - Epoch(train) [60][120/2119] lr: 4.0000e-02 eta: 18:31:10 time: 0.3484 data_time: 0.0173 memory: 5826 grad_norm: 3.0956 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5284 loss: 2.5284 2022/10/07 19:52:34 - mmengine - INFO - Epoch(train) [60][140/2119] lr: 4.0000e-02 eta: 18:31:05 time: 0.3926 data_time: 0.0191 memory: 5826 grad_norm: 3.0874 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7816 loss: 2.7816 2022/10/07 19:52:42 - mmengine - INFO - Epoch(train) [60][160/2119] lr: 4.0000e-02 eta: 18:30:59 time: 0.3790 data_time: 0.0175 memory: 5826 grad_norm: 3.0780 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7112 loss: 2.7112 2022/10/07 19:52:49 - mmengine - INFO - Epoch(train) [60][180/2119] lr: 4.0000e-02 eta: 18:30:52 time: 0.3447 data_time: 0.0181 memory: 5826 grad_norm: 3.0376 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7429 loss: 2.7429 2022/10/07 19:52:55 - mmengine - INFO - Epoch(train) [60][200/2119] lr: 4.0000e-02 eta: 18:30:43 time: 0.2942 data_time: 0.0228 memory: 5826 grad_norm: 3.0923 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7306 loss: 2.7306 2022/10/07 19:53:02 - mmengine - INFO - Epoch(train) [60][220/2119] lr: 4.0000e-02 eta: 18:30:37 time: 0.3570 data_time: 0.0353 memory: 5826 grad_norm: 3.1358 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7538 loss: 2.7538 2022/10/07 19:53:08 - mmengine - INFO - Epoch(train) [60][240/2119] lr: 4.0000e-02 eta: 18:30:29 time: 0.3341 data_time: 0.0215 memory: 5826 grad_norm: 3.0348 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7821 loss: 2.7821 2022/10/07 19:53:17 - mmengine - INFO - Epoch(train) [60][260/2119] lr: 4.0000e-02 eta: 18:30:24 time: 0.4067 data_time: 0.0177 memory: 5826 grad_norm: 3.1232 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7180 loss: 2.7180 2022/10/07 19:53:23 - mmengine - INFO - Epoch(train) [60][280/2119] lr: 4.0000e-02 eta: 18:30:17 time: 0.3306 data_time: 0.0204 memory: 5826 grad_norm: 3.0945 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7243 loss: 2.7243 2022/10/07 19:53:29 - mmengine - INFO - Epoch(train) [60][300/2119] lr: 4.0000e-02 eta: 18:30:09 time: 0.3003 data_time: 0.0205 memory: 5826 grad_norm: 3.1209 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7095 loss: 2.7095 2022/10/07 19:53:36 - mmengine - INFO - Epoch(train) [60][320/2119] lr: 4.0000e-02 eta: 18:30:02 time: 0.3453 data_time: 0.0265 memory: 5826 grad_norm: 3.1138 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6931 loss: 2.6931 2022/10/07 19:53:43 - mmengine - INFO - Epoch(train) [60][340/2119] lr: 4.0000e-02 eta: 18:29:55 time: 0.3622 data_time: 0.0211 memory: 5826 grad_norm: 3.1125 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6556 loss: 2.6556 2022/10/07 19:53:50 - mmengine - INFO - Epoch(train) [60][360/2119] lr: 4.0000e-02 eta: 18:29:48 time: 0.3460 data_time: 0.0249 memory: 5826 grad_norm: 3.1444 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5928 loss: 2.5928 2022/10/07 19:53:57 - mmengine - INFO - Epoch(train) [60][380/2119] lr: 4.0000e-02 eta: 18:29:41 time: 0.3303 data_time: 0.0211 memory: 5826 grad_norm: 3.1852 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.8785 loss: 2.8785 2022/10/07 19:54:03 - mmengine - INFO - Epoch(train) [60][400/2119] lr: 4.0000e-02 eta: 18:29:33 time: 0.3274 data_time: 0.0261 memory: 5826 grad_norm: 3.1422 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7762 loss: 2.7762 2022/10/07 19:54:10 - mmengine - INFO - Epoch(train) [60][420/2119] lr: 4.0000e-02 eta: 18:29:26 time: 0.3399 data_time: 0.0243 memory: 5826 grad_norm: 3.1559 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6845 loss: 2.6845 2022/10/07 19:54:17 - mmengine - INFO - Epoch(train) [60][440/2119] lr: 4.0000e-02 eta: 18:29:19 time: 0.3273 data_time: 0.0407 memory: 5826 grad_norm: 3.1346 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7823 loss: 2.7823 2022/10/07 19:54:24 - mmengine - INFO - Epoch(train) [60][460/2119] lr: 4.0000e-02 eta: 18:29:13 time: 0.3743 data_time: 0.0241 memory: 5826 grad_norm: 3.1175 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4981 loss: 2.4981 2022/10/07 19:54:30 - mmengine - INFO - Epoch(train) [60][480/2119] lr: 4.0000e-02 eta: 18:29:04 time: 0.2933 data_time: 0.0229 memory: 5826 grad_norm: 3.1599 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.9045 loss: 2.9045 2022/10/07 19:54:37 - mmengine - INFO - Epoch(train) [60][500/2119] lr: 4.0000e-02 eta: 18:28:58 time: 0.3645 data_time: 0.0228 memory: 5826 grad_norm: 3.1521 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8910 loss: 2.8910 2022/10/07 19:54:43 - mmengine - INFO - Epoch(train) [60][520/2119] lr: 4.0000e-02 eta: 18:28:50 time: 0.2969 data_time: 0.0199 memory: 5826 grad_norm: 3.1466 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7346 loss: 2.7346 2022/10/07 19:54:51 - mmengine - INFO - Epoch(train) [60][540/2119] lr: 4.0000e-02 eta: 18:28:44 time: 0.4020 data_time: 0.0228 memory: 5826 grad_norm: 3.0739 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8080 loss: 2.8080 2022/10/07 19:54:57 - mmengine - INFO - Epoch(train) [60][560/2119] lr: 4.0000e-02 eta: 18:28:36 time: 0.2979 data_time: 0.0232 memory: 5826 grad_norm: 3.1504 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6890 loss: 2.6890 2022/10/07 19:55:05 - mmengine - INFO - Epoch(train) [60][580/2119] lr: 4.0000e-02 eta: 18:28:30 time: 0.3760 data_time: 0.0305 memory: 5826 grad_norm: 3.1807 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5828 loss: 2.5828 2022/10/07 19:55:12 - mmengine - INFO - Epoch(train) [60][600/2119] lr: 4.0000e-02 eta: 18:28:23 time: 0.3604 data_time: 0.0211 memory: 5826 grad_norm: 3.0955 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7367 loss: 2.7367 2022/10/07 19:55:19 - mmengine - INFO - Epoch(train) [60][620/2119] lr: 4.0000e-02 eta: 18:28:16 time: 0.3202 data_time: 0.0191 memory: 5826 grad_norm: 3.1470 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6094 loss: 2.6094 2022/10/07 19:55:25 - mmengine - INFO - Epoch(train) [60][640/2119] lr: 4.0000e-02 eta: 18:28:09 time: 0.3410 data_time: 0.0281 memory: 5826 grad_norm: 3.1037 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8909 loss: 2.8909 2022/10/07 19:55:33 - mmengine - INFO - Epoch(train) [60][660/2119] lr: 4.0000e-02 eta: 18:28:03 time: 0.3956 data_time: 0.0194 memory: 5826 grad_norm: 3.0648 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9460 loss: 2.9460 2022/10/07 19:55:39 - mmengine - INFO - Epoch(train) [60][680/2119] lr: 4.0000e-02 eta: 18:27:55 time: 0.2981 data_time: 0.0242 memory: 5826 grad_norm: 3.1866 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7075 loss: 2.7075 2022/10/07 19:55:47 - mmengine - INFO - Epoch(train) [60][700/2119] lr: 4.0000e-02 eta: 18:27:50 time: 0.3973 data_time: 0.0337 memory: 5826 grad_norm: 3.1186 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6321 loss: 2.6321 2022/10/07 19:55:53 - mmengine - INFO - Epoch(train) [60][720/2119] lr: 4.0000e-02 eta: 18:27:42 time: 0.3110 data_time: 0.0237 memory: 5826 grad_norm: 3.0684 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6732 loss: 2.6732 2022/10/07 19:56:01 - mmengine - INFO - Epoch(train) [60][740/2119] lr: 4.0000e-02 eta: 18:27:36 time: 0.3976 data_time: 0.0154 memory: 5826 grad_norm: 3.1503 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5093 loss: 2.5093 2022/10/07 19:56:08 - mmengine - INFO - Epoch(train) [60][760/2119] lr: 4.0000e-02 eta: 18:27:29 time: 0.3337 data_time: 0.0237 memory: 5826 grad_norm: 3.1242 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6218 loss: 2.6218 2022/10/07 19:56:15 - mmengine - INFO - Epoch(train) [60][780/2119] lr: 4.0000e-02 eta: 18:27:22 time: 0.3375 data_time: 0.0210 memory: 5826 grad_norm: 3.1590 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8473 loss: 2.8473 2022/10/07 19:56:22 - mmengine - INFO - Epoch(train) [60][800/2119] lr: 4.0000e-02 eta: 18:27:15 time: 0.3633 data_time: 0.0189 memory: 5826 grad_norm: 3.0641 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7343 loss: 2.7343 2022/10/07 19:56:29 - mmengine - INFO - Epoch(train) [60][820/2119] lr: 4.0000e-02 eta: 18:27:08 time: 0.3414 data_time: 0.0197 memory: 5826 grad_norm: 3.1108 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6913 loss: 2.6913 2022/10/07 19:56:36 - mmengine - INFO - Epoch(train) [60][840/2119] lr: 4.0000e-02 eta: 18:27:01 time: 0.3303 data_time: 0.0228 memory: 5826 grad_norm: 3.0864 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.5072 loss: 2.5072 2022/10/07 19:56:42 - mmengine - INFO - Epoch(train) [60][860/2119] lr: 4.0000e-02 eta: 18:26:54 time: 0.3444 data_time: 0.0183 memory: 5826 grad_norm: 3.1264 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8902 loss: 2.8902 2022/10/07 19:56:49 - mmengine - INFO - Epoch(train) [60][880/2119] lr: 4.0000e-02 eta: 18:26:47 time: 0.3392 data_time: 0.0230 memory: 5826 grad_norm: 3.1343 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7531 loss: 2.7531 2022/10/07 19:56:56 - mmengine - INFO - Epoch(train) [60][900/2119] lr: 4.0000e-02 eta: 18:26:39 time: 0.3249 data_time: 0.0235 memory: 5826 grad_norm: 3.1399 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7295 loss: 2.7295 2022/10/07 19:57:03 - mmengine - INFO - Epoch(train) [60][920/2119] lr: 4.0000e-02 eta: 18:26:33 time: 0.3712 data_time: 0.0222 memory: 5826 grad_norm: 3.1643 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6147 loss: 2.6147 2022/10/07 19:57:10 - mmengine - INFO - Epoch(train) [60][940/2119] lr: 4.0000e-02 eta: 18:26:26 time: 0.3387 data_time: 0.0206 memory: 5826 grad_norm: 3.1409 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9029 loss: 2.9029 2022/10/07 19:57:17 - mmengine - INFO - Epoch(train) [60][960/2119] lr: 4.0000e-02 eta: 18:26:20 time: 0.3702 data_time: 0.0229 memory: 5826 grad_norm: 3.0871 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6883 loss: 2.6883 2022/10/07 19:57:23 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 19:57:24 - mmengine - INFO - Epoch(train) [60][980/2119] lr: 4.0000e-02 eta: 18:26:12 time: 0.3138 data_time: 0.0268 memory: 5826 grad_norm: 3.0680 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7599 loss: 2.7599 2022/10/07 19:57:31 - mmengine - INFO - Epoch(train) [60][1000/2119] lr: 4.0000e-02 eta: 18:26:06 time: 0.3686 data_time: 0.0231 memory: 5826 grad_norm: 3.1104 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8434 loss: 2.8434 2022/10/07 19:57:38 - mmengine - INFO - Epoch(train) [60][1020/2119] lr: 4.0000e-02 eta: 18:25:59 time: 0.3625 data_time: 0.0186 memory: 5826 grad_norm: 3.1201 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8098 loss: 2.8098 2022/10/07 19:57:46 - mmengine - INFO - Epoch(train) [60][1040/2119] lr: 4.0000e-02 eta: 18:25:54 time: 0.3949 data_time: 0.0250 memory: 5826 grad_norm: 3.1505 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.5667 loss: 2.5667 2022/10/07 19:57:54 - mmengine - INFO - Epoch(train) [60][1060/2119] lr: 4.0000e-02 eta: 18:25:49 time: 0.4048 data_time: 0.0175 memory: 5826 grad_norm: 3.2029 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9389 loss: 2.9389 2022/10/07 19:58:00 - mmengine - INFO - Epoch(train) [60][1080/2119] lr: 4.0000e-02 eta: 18:25:41 time: 0.3118 data_time: 0.0221 memory: 5826 grad_norm: 3.0713 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4955 loss: 2.4955 2022/10/07 19:58:07 - mmengine - INFO - Epoch(train) [60][1100/2119] lr: 4.0000e-02 eta: 18:25:33 time: 0.3361 data_time: 0.0215 memory: 5826 grad_norm: 3.0960 top1_acc: 0.2500 top5_acc: 0.3125 loss_cls: 2.9532 loss: 2.9532 2022/10/07 19:58:14 - mmengine - INFO - Epoch(train) [60][1120/2119] lr: 4.0000e-02 eta: 18:25:27 time: 0.3503 data_time: 0.0235 memory: 5826 grad_norm: 3.1005 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7475 loss: 2.7475 2022/10/07 19:58:22 - mmengine - INFO - Epoch(train) [60][1140/2119] lr: 4.0000e-02 eta: 18:25:21 time: 0.3747 data_time: 0.0212 memory: 5826 grad_norm: 3.0979 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7954 loss: 2.7954 2022/10/07 19:58:29 - mmengine - INFO - Epoch(train) [60][1160/2119] lr: 4.0000e-02 eta: 18:25:14 time: 0.3467 data_time: 0.0226 memory: 5826 grad_norm: 3.1163 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.7601 loss: 2.7601 2022/10/07 19:58:36 - mmengine - INFO - Epoch(train) [60][1180/2119] lr: 4.0000e-02 eta: 18:25:07 time: 0.3572 data_time: 0.0200 memory: 5826 grad_norm: 3.1012 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7676 loss: 2.7676 2022/10/07 19:58:42 - mmengine - INFO - Epoch(train) [60][1200/2119] lr: 4.0000e-02 eta: 18:25:00 time: 0.3246 data_time: 0.0232 memory: 5826 grad_norm: 3.1115 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7880 loss: 2.7880 2022/10/07 19:58:51 - mmengine - INFO - Epoch(train) [60][1220/2119] lr: 4.0000e-02 eta: 18:24:55 time: 0.4138 data_time: 0.0189 memory: 5826 grad_norm: 3.0751 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6867 loss: 2.6867 2022/10/07 19:58:57 - mmengine - INFO - Epoch(train) [60][1240/2119] lr: 4.0000e-02 eta: 18:24:47 time: 0.3253 data_time: 0.0248 memory: 5826 grad_norm: 3.0843 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8006 loss: 2.8006 2022/10/07 19:59:04 - mmengine - INFO - Epoch(train) [60][1260/2119] lr: 4.0000e-02 eta: 18:24:40 time: 0.3369 data_time: 0.0205 memory: 5826 grad_norm: 3.1899 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5450 loss: 2.5450 2022/10/07 19:59:11 - mmengine - INFO - Epoch(train) [60][1280/2119] lr: 4.0000e-02 eta: 18:24:33 time: 0.3413 data_time: 0.0246 memory: 5826 grad_norm: 3.1598 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6357 loss: 2.6357 2022/10/07 19:59:18 - mmengine - INFO - Epoch(train) [60][1300/2119] lr: 4.0000e-02 eta: 18:24:27 time: 0.3736 data_time: 0.0206 memory: 5826 grad_norm: 3.0827 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5587 loss: 2.5587 2022/10/07 19:59:25 - mmengine - INFO - Epoch(train) [60][1320/2119] lr: 4.0000e-02 eta: 18:24:19 time: 0.3255 data_time: 0.0250 memory: 5826 grad_norm: 3.1590 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7611 loss: 2.7611 2022/10/07 19:59:31 - mmengine - INFO - Epoch(train) [60][1340/2119] lr: 4.0000e-02 eta: 18:24:12 time: 0.3405 data_time: 0.0224 memory: 5826 grad_norm: 3.0962 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8117 loss: 2.8117 2022/10/07 19:59:38 - mmengine - INFO - Epoch(train) [60][1360/2119] lr: 4.0000e-02 eta: 18:24:05 time: 0.3365 data_time: 0.0196 memory: 5826 grad_norm: 3.0875 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5303 loss: 2.5303 2022/10/07 19:59:46 - mmengine - INFO - Epoch(train) [60][1380/2119] lr: 4.0000e-02 eta: 18:24:00 time: 0.3935 data_time: 0.0235 memory: 5826 grad_norm: 3.1278 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9218 loss: 2.9218 2022/10/07 19:59:53 - mmengine - INFO - Epoch(train) [60][1400/2119] lr: 4.0000e-02 eta: 18:23:52 time: 0.3290 data_time: 0.0220 memory: 5826 grad_norm: 3.0932 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8579 loss: 2.8579 2022/10/07 20:00:00 - mmengine - INFO - Epoch(train) [60][1420/2119] lr: 4.0000e-02 eta: 18:23:46 time: 0.3609 data_time: 0.0181 memory: 5826 grad_norm: 3.1479 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.7970 loss: 2.7970 2022/10/07 20:00:07 - mmengine - INFO - Epoch(train) [60][1440/2119] lr: 4.0000e-02 eta: 18:23:40 time: 0.3767 data_time: 0.0197 memory: 5826 grad_norm: 3.1098 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6937 loss: 2.6937 2022/10/07 20:00:16 - mmengine - INFO - Epoch(train) [60][1460/2119] lr: 4.0000e-02 eta: 18:23:35 time: 0.4171 data_time: 0.0173 memory: 5826 grad_norm: 3.1070 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8532 loss: 2.8532 2022/10/07 20:00:23 - mmengine - INFO - Epoch(train) [60][1480/2119] lr: 4.0000e-02 eta: 18:23:29 time: 0.3661 data_time: 0.0217 memory: 5826 grad_norm: 3.0981 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8573 loss: 2.8573 2022/10/07 20:00:30 - mmengine - INFO - Epoch(train) [60][1500/2119] lr: 4.0000e-02 eta: 18:23:22 time: 0.3612 data_time: 0.0221 memory: 5826 grad_norm: 3.1214 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.6233 loss: 2.6233 2022/10/07 20:00:36 - mmengine - INFO - Epoch(train) [60][1520/2119] lr: 4.0000e-02 eta: 18:23:14 time: 0.3014 data_time: 0.0193 memory: 5826 grad_norm: 3.1428 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9547 loss: 2.9547 2022/10/07 20:00:44 - mmengine - INFO - Epoch(train) [60][1540/2119] lr: 4.0000e-02 eta: 18:23:08 time: 0.3673 data_time: 0.0235 memory: 5826 grad_norm: 3.1448 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7224 loss: 2.7224 2022/10/07 20:00:50 - mmengine - INFO - Epoch(train) [60][1560/2119] lr: 4.0000e-02 eta: 18:22:59 time: 0.3069 data_time: 0.0242 memory: 5826 grad_norm: 3.1097 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7071 loss: 2.7071 2022/10/07 20:00:58 - mmengine - INFO - Epoch(train) [60][1580/2119] lr: 4.0000e-02 eta: 18:22:54 time: 0.3895 data_time: 0.0252 memory: 5826 grad_norm: 3.1157 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7866 loss: 2.7866 2022/10/07 20:01:04 - mmengine - INFO - Epoch(train) [60][1600/2119] lr: 4.0000e-02 eta: 18:22:46 time: 0.3093 data_time: 0.0264 memory: 5826 grad_norm: 3.1264 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6935 loss: 2.6935 2022/10/07 20:01:12 - mmengine - INFO - Epoch(train) [60][1620/2119] lr: 4.0000e-02 eta: 18:22:40 time: 0.3840 data_time: 0.0228 memory: 5826 grad_norm: 3.1210 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6589 loss: 2.6589 2022/10/07 20:01:18 - mmengine - INFO - Epoch(train) [60][1640/2119] lr: 4.0000e-02 eta: 18:22:33 time: 0.3307 data_time: 0.0261 memory: 5826 grad_norm: 3.0517 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8891 loss: 2.8891 2022/10/07 20:01:26 - mmengine - INFO - Epoch(train) [60][1660/2119] lr: 4.0000e-02 eta: 18:22:27 time: 0.3744 data_time: 0.0229 memory: 5826 grad_norm: 3.1319 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7712 loss: 2.7712 2022/10/07 20:01:33 - mmengine - INFO - Epoch(train) [60][1680/2119] lr: 4.0000e-02 eta: 18:22:20 time: 0.3665 data_time: 0.0206 memory: 5826 grad_norm: 3.1274 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9462 loss: 2.9462 2022/10/07 20:01:41 - mmengine - INFO - Epoch(train) [60][1700/2119] lr: 4.0000e-02 eta: 18:22:15 time: 0.3938 data_time: 0.0207 memory: 5826 grad_norm: 3.0888 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6029 loss: 2.6029 2022/10/07 20:01:47 - mmengine - INFO - Epoch(train) [60][1720/2119] lr: 4.0000e-02 eta: 18:22:07 time: 0.3219 data_time: 0.0206 memory: 5826 grad_norm: 3.1573 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7061 loss: 2.7061 2022/10/07 20:01:54 - mmengine - INFO - Epoch(train) [60][1740/2119] lr: 4.0000e-02 eta: 18:22:00 time: 0.3464 data_time: 0.0209 memory: 5826 grad_norm: 3.1012 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8494 loss: 2.8494 2022/10/07 20:02:00 - mmengine - INFO - Epoch(train) [60][1760/2119] lr: 4.0000e-02 eta: 18:21:52 time: 0.3035 data_time: 0.0233 memory: 5826 grad_norm: 3.0358 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9955 loss: 2.9955 2022/10/07 20:02:07 - mmengine - INFO - Epoch(train) [60][1780/2119] lr: 4.0000e-02 eta: 18:21:45 time: 0.3447 data_time: 0.0213 memory: 5826 grad_norm: 3.1069 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6067 loss: 2.6067 2022/10/07 20:02:14 - mmengine - INFO - Epoch(train) [60][1800/2119] lr: 4.0000e-02 eta: 18:21:38 time: 0.3498 data_time: 0.0245 memory: 5826 grad_norm: 3.1366 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8843 loss: 2.8843 2022/10/07 20:02:21 - mmengine - INFO - Epoch(train) [60][1820/2119] lr: 4.0000e-02 eta: 18:21:32 time: 0.3512 data_time: 0.0197 memory: 5826 grad_norm: 3.1397 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8075 loss: 2.8075 2022/10/07 20:02:28 - mmengine - INFO - Epoch(train) [60][1840/2119] lr: 4.0000e-02 eta: 18:21:25 time: 0.3485 data_time: 0.0203 memory: 5826 grad_norm: 3.1291 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7582 loss: 2.7582 2022/10/07 20:02:35 - mmengine - INFO - Epoch(train) [60][1860/2119] lr: 4.0000e-02 eta: 18:21:18 time: 0.3388 data_time: 0.0281 memory: 5826 grad_norm: 3.1136 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8344 loss: 2.8344 2022/10/07 20:02:42 - mmengine - INFO - Epoch(train) [60][1880/2119] lr: 4.0000e-02 eta: 18:21:11 time: 0.3655 data_time: 0.0222 memory: 5826 grad_norm: 3.1207 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6876 loss: 2.6876 2022/10/07 20:02:51 - mmengine - INFO - Epoch(train) [60][1900/2119] lr: 4.0000e-02 eta: 18:21:07 time: 0.4414 data_time: 0.0188 memory: 5826 grad_norm: 3.0616 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7918 loss: 2.7918 2022/10/07 20:02:57 - mmengine - INFO - Epoch(train) [60][1920/2119] lr: 4.0000e-02 eta: 18:20:59 time: 0.3024 data_time: 0.0240 memory: 5826 grad_norm: 3.0841 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9730 loss: 2.9730 2022/10/07 20:03:05 - mmengine - INFO - Epoch(train) [60][1940/2119] lr: 4.0000e-02 eta: 18:20:54 time: 0.3960 data_time: 0.0156 memory: 5826 grad_norm: 3.1033 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5731 loss: 2.5731 2022/10/07 20:03:13 - mmengine - INFO - Epoch(train) [60][1960/2119] lr: 4.0000e-02 eta: 18:20:48 time: 0.3924 data_time: 0.0219 memory: 5826 grad_norm: 3.1338 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7978 loss: 2.7978 2022/10/07 20:03:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 20:03:20 - mmengine - INFO - Epoch(train) [60][1980/2119] lr: 4.0000e-02 eta: 18:20:41 time: 0.3592 data_time: 0.0202 memory: 5826 grad_norm: 3.1781 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7652 loss: 2.7652 2022/10/07 20:03:28 - mmengine - INFO - Epoch(train) [60][2000/2119] lr: 4.0000e-02 eta: 18:20:35 time: 0.3740 data_time: 0.0183 memory: 5826 grad_norm: 3.0964 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7763 loss: 2.7763 2022/10/07 20:03:35 - mmengine - INFO - Epoch(train) [60][2020/2119] lr: 4.0000e-02 eta: 18:20:29 time: 0.3542 data_time: 0.0240 memory: 5826 grad_norm: 3.1698 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8922 loss: 2.8922 2022/10/07 20:03:41 - mmengine - INFO - Epoch(train) [60][2040/2119] lr: 4.0000e-02 eta: 18:20:21 time: 0.3046 data_time: 0.0206 memory: 5826 grad_norm: 3.1041 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.6122 loss: 2.6122 2022/10/07 20:03:47 - mmengine - INFO - Epoch(train) [60][2060/2119] lr: 4.0000e-02 eta: 18:20:13 time: 0.3137 data_time: 0.0196 memory: 5826 grad_norm: 3.1035 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8096 loss: 2.8096 2022/10/07 20:03:55 - mmengine - INFO - Epoch(train) [60][2080/2119] lr: 4.0000e-02 eta: 18:20:07 time: 0.3791 data_time: 0.0236 memory: 5826 grad_norm: 3.0617 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7379 loss: 2.7379 2022/10/07 20:04:03 - mmengine - INFO - Epoch(train) [60][2100/2119] lr: 4.0000e-02 eta: 18:20:01 time: 0.4000 data_time: 0.0203 memory: 5826 grad_norm: 3.0556 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8907 loss: 2.8907 2022/10/07 20:04:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 20:04:08 - mmengine - INFO - Epoch(train) [60][2119/2119] lr: 4.0000e-02 eta: 18:20:01 time: 0.3153 data_time: 0.0167 memory: 5826 grad_norm: 3.1788 top1_acc: 0.6000 top5_acc: 0.8000 loss_cls: 2.7392 loss: 2.7392 2022/10/07 20:04:08 - mmengine - INFO - Saving checkpoint at 60 epochs 2022/10/07 20:04:18 - mmengine - INFO - Epoch(val) [60][20/137] eta: 0:00:48 time: 0.4162 data_time: 0.3515 memory: 1241 2022/10/07 20:04:24 - mmengine - INFO - Epoch(val) [60][40/137] eta: 0:00:28 time: 0.2957 data_time: 0.2279 memory: 1241 2022/10/07 20:04:32 - mmengine - INFO - Epoch(val) [60][60/137] eta: 0:00:29 time: 0.3876 data_time: 0.3237 memory: 1241 2022/10/07 20:04:37 - mmengine - INFO - Epoch(val) [60][80/137] eta: 0:00:15 time: 0.2728 data_time: 0.2053 memory: 1241 2022/10/07 20:04:45 - mmengine - INFO - Epoch(val) [60][100/137] eta: 0:00:13 time: 0.3686 data_time: 0.3021 memory: 1241 2022/10/07 20:04:50 - mmengine - INFO - Epoch(val) [60][120/137] eta: 0:00:04 time: 0.2725 data_time: 0.2094 memory: 1241 2022/10/07 20:04:59 - mmengine - INFO - Epoch(val) [60][137/137] acc/top1: 0.4142 acc/top5: 0.6525 acc/mean1: 0.4141 2022/10/07 20:05:09 - mmengine - INFO - Epoch(train) [61][20/2119] lr: 4.0000e-02 eta: 18:19:42 time: 0.4684 data_time: 0.2128 memory: 5826 grad_norm: 3.0817 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5824 loss: 2.5824 2022/10/07 20:05:15 - mmengine - INFO - Epoch(train) [61][40/2119] lr: 4.0000e-02 eta: 18:19:35 time: 0.3396 data_time: 0.0287 memory: 5826 grad_norm: 3.1127 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8203 loss: 2.8203 2022/10/07 20:05:22 - mmengine - INFO - Epoch(train) [61][60/2119] lr: 4.0000e-02 eta: 18:19:28 time: 0.3525 data_time: 0.0263 memory: 5826 grad_norm: 3.0983 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5344 loss: 2.5344 2022/10/07 20:05:30 - mmengine - INFO - Epoch(train) [61][80/2119] lr: 4.0000e-02 eta: 18:19:22 time: 0.3727 data_time: 0.0182 memory: 5826 grad_norm: 3.1213 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7082 loss: 2.7082 2022/10/07 20:05:36 - mmengine - INFO - Epoch(train) [61][100/2119] lr: 4.0000e-02 eta: 18:19:13 time: 0.2983 data_time: 0.0395 memory: 5826 grad_norm: 3.1387 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6037 loss: 2.6037 2022/10/07 20:05:43 - mmengine - INFO - Epoch(train) [61][120/2119] lr: 4.0000e-02 eta: 18:19:07 time: 0.3552 data_time: 0.0577 memory: 5826 grad_norm: 3.1092 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7535 loss: 2.7535 2022/10/07 20:05:50 - mmengine - INFO - Epoch(train) [61][140/2119] lr: 4.0000e-02 eta: 18:19:00 time: 0.3633 data_time: 0.0337 memory: 5826 grad_norm: 3.1062 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7208 loss: 2.7208 2022/10/07 20:05:57 - mmengine - INFO - Epoch(train) [61][160/2119] lr: 4.0000e-02 eta: 18:18:53 time: 0.3242 data_time: 0.0422 memory: 5826 grad_norm: 3.1322 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5709 loss: 2.5709 2022/10/07 20:06:05 - mmengine - INFO - Epoch(train) [61][180/2119] lr: 4.0000e-02 eta: 18:18:47 time: 0.3881 data_time: 0.0216 memory: 5826 grad_norm: 3.0933 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5410 loss: 2.5410 2022/10/07 20:06:12 - mmengine - INFO - Epoch(train) [61][200/2119] lr: 4.0000e-02 eta: 18:18:41 time: 0.3697 data_time: 0.0142 memory: 5826 grad_norm: 3.1250 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8915 loss: 2.8915 2022/10/07 20:06:19 - mmengine - INFO - Epoch(train) [61][220/2119] lr: 4.0000e-02 eta: 18:18:34 time: 0.3432 data_time: 0.0241 memory: 5826 grad_norm: 3.0980 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6820 loss: 2.6820 2022/10/07 20:06:25 - mmengine - INFO - Epoch(train) [61][240/2119] lr: 4.0000e-02 eta: 18:18:26 time: 0.3174 data_time: 0.0233 memory: 5826 grad_norm: 3.1063 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6412 loss: 2.6412 2022/10/07 20:06:32 - mmengine - INFO - Epoch(train) [61][260/2119] lr: 4.0000e-02 eta: 18:18:20 time: 0.3662 data_time: 0.0197 memory: 5826 grad_norm: 3.1164 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5836 loss: 2.5836 2022/10/07 20:06:39 - mmengine - INFO - Epoch(train) [61][280/2119] lr: 4.0000e-02 eta: 18:18:12 time: 0.3188 data_time: 0.0248 memory: 5826 grad_norm: 3.0848 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6449 loss: 2.6449 2022/10/07 20:06:47 - mmengine - INFO - Epoch(train) [61][300/2119] lr: 4.0000e-02 eta: 18:18:06 time: 0.3899 data_time: 0.0237 memory: 5826 grad_norm: 3.1237 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6457 loss: 2.6457 2022/10/07 20:06:53 - mmengine - INFO - Epoch(train) [61][320/2119] lr: 4.0000e-02 eta: 18:17:59 time: 0.3120 data_time: 0.0221 memory: 5826 grad_norm: 3.1285 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6472 loss: 2.6472 2022/10/07 20:07:00 - mmengine - INFO - Epoch(train) [61][340/2119] lr: 4.0000e-02 eta: 18:17:53 time: 0.3781 data_time: 0.0246 memory: 5826 grad_norm: 3.1048 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.9391 loss: 2.9391 2022/10/07 20:07:06 - mmengine - INFO - Epoch(train) [61][360/2119] lr: 4.0000e-02 eta: 18:17:44 time: 0.3002 data_time: 0.0143 memory: 5826 grad_norm: 3.1059 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.5998 loss: 2.5998 2022/10/07 20:07:14 - mmengine - INFO - Epoch(train) [61][380/2119] lr: 4.0000e-02 eta: 18:17:39 time: 0.3843 data_time: 0.0185 memory: 5826 grad_norm: 3.1354 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6904 loss: 2.6904 2022/10/07 20:07:21 - mmengine - INFO - Epoch(train) [61][400/2119] lr: 4.0000e-02 eta: 18:17:32 time: 0.3489 data_time: 0.0212 memory: 5826 grad_norm: 3.1596 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6904 loss: 2.6904 2022/10/07 20:07:27 - mmengine - INFO - Epoch(train) [61][420/2119] lr: 4.0000e-02 eta: 18:17:24 time: 0.3122 data_time: 0.0226 memory: 5826 grad_norm: 3.0643 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8436 loss: 2.8436 2022/10/07 20:07:35 - mmengine - INFO - Epoch(train) [61][440/2119] lr: 4.0000e-02 eta: 18:17:17 time: 0.3595 data_time: 0.0168 memory: 5826 grad_norm: 3.1209 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6758 loss: 2.6758 2022/10/07 20:07:41 - mmengine - INFO - Epoch(train) [61][460/2119] lr: 4.0000e-02 eta: 18:17:10 time: 0.3432 data_time: 0.0164 memory: 5826 grad_norm: 3.1146 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8296 loss: 2.8296 2022/10/07 20:07:50 - mmengine - INFO - Epoch(train) [61][480/2119] lr: 4.0000e-02 eta: 18:17:06 time: 0.4327 data_time: 0.0166 memory: 5826 grad_norm: 3.1017 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5886 loss: 2.5886 2022/10/07 20:07:57 - mmengine - INFO - Epoch(train) [61][500/2119] lr: 4.0000e-02 eta: 18:16:59 time: 0.3379 data_time: 0.0202 memory: 5826 grad_norm: 3.1567 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6271 loss: 2.6271 2022/10/07 20:08:04 - mmengine - INFO - Epoch(train) [61][520/2119] lr: 4.0000e-02 eta: 18:16:52 time: 0.3571 data_time: 0.0236 memory: 5826 grad_norm: 3.1351 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6240 loss: 2.6240 2022/10/07 20:08:10 - mmengine - INFO - Epoch(train) [61][540/2119] lr: 4.0000e-02 eta: 18:16:44 time: 0.3180 data_time: 0.0215 memory: 5826 grad_norm: 3.0828 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6176 loss: 2.6176 2022/10/07 20:08:18 - mmengine - INFO - Epoch(train) [61][560/2119] lr: 4.0000e-02 eta: 18:16:38 time: 0.3720 data_time: 0.0223 memory: 5826 grad_norm: 3.1126 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4877 loss: 2.4877 2022/10/07 20:08:25 - mmengine - INFO - Epoch(train) [61][580/2119] lr: 4.0000e-02 eta: 18:16:32 time: 0.3753 data_time: 0.0341 memory: 5826 grad_norm: 3.1809 top1_acc: 0.2500 top5_acc: 0.8125 loss_cls: 2.8029 loss: 2.8029 2022/10/07 20:08:33 - mmengine - INFO - Epoch(train) [61][600/2119] lr: 4.0000e-02 eta: 18:16:26 time: 0.3779 data_time: 0.0211 memory: 5826 grad_norm: 3.0989 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7318 loss: 2.7318 2022/10/07 20:08:39 - mmengine - INFO - Epoch(train) [61][620/2119] lr: 4.0000e-02 eta: 18:16:18 time: 0.3120 data_time: 0.0301 memory: 5826 grad_norm: 3.0502 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8573 loss: 2.8573 2022/10/07 20:08:46 - mmengine - INFO - Epoch(train) [61][640/2119] lr: 4.0000e-02 eta: 18:16:11 time: 0.3491 data_time: 0.0259 memory: 5826 grad_norm: 3.1129 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6617 loss: 2.6617 2022/10/07 20:08:54 - mmengine - INFO - Epoch(train) [61][660/2119] lr: 4.0000e-02 eta: 18:16:05 time: 0.3728 data_time: 0.0194 memory: 5826 grad_norm: 3.0527 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5381 loss: 2.5381 2022/10/07 20:09:01 - mmengine - INFO - Epoch(train) [61][680/2119] lr: 4.0000e-02 eta: 18:15:59 time: 0.3521 data_time: 0.0209 memory: 5826 grad_norm: 3.1609 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8830 loss: 2.8830 2022/10/07 20:09:07 - mmengine - INFO - Epoch(train) [61][700/2119] lr: 4.0000e-02 eta: 18:15:51 time: 0.3161 data_time: 0.0228 memory: 5826 grad_norm: 3.1768 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8759 loss: 2.8759 2022/10/07 20:09:14 - mmengine - INFO - Epoch(train) [61][720/2119] lr: 4.0000e-02 eta: 18:15:44 time: 0.3654 data_time: 0.0196 memory: 5826 grad_norm: 3.1297 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.5190 loss: 2.5190 2022/10/07 20:09:21 - mmengine - INFO - Epoch(train) [61][740/2119] lr: 4.0000e-02 eta: 18:15:37 time: 0.3201 data_time: 0.0257 memory: 5826 grad_norm: 3.1033 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7241 loss: 2.7241 2022/10/07 20:09:28 - mmengine - INFO - Epoch(train) [61][760/2119] lr: 4.0000e-02 eta: 18:15:31 time: 0.3813 data_time: 0.0220 memory: 5826 grad_norm: 3.0935 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6027 loss: 2.6027 2022/10/07 20:09:35 - mmengine - INFO - Epoch(train) [61][780/2119] lr: 4.0000e-02 eta: 18:15:23 time: 0.3284 data_time: 0.0221 memory: 5826 grad_norm: 3.1196 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8044 loss: 2.8044 2022/10/07 20:09:42 - mmengine - INFO - Epoch(train) [61][800/2119] lr: 4.0000e-02 eta: 18:15:17 time: 0.3705 data_time: 0.0245 memory: 5826 grad_norm: 3.1439 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6694 loss: 2.6694 2022/10/07 20:09:49 - mmengine - INFO - Epoch(train) [61][820/2119] lr: 4.0000e-02 eta: 18:15:10 time: 0.3244 data_time: 0.0270 memory: 5826 grad_norm: 3.1740 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7955 loss: 2.7955 2022/10/07 20:09:56 - mmengine - INFO - Epoch(train) [61][840/2119] lr: 4.0000e-02 eta: 18:15:04 time: 0.3722 data_time: 0.0216 memory: 5826 grad_norm: 3.1500 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7323 loss: 2.7323 2022/10/07 20:10:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 20:10:03 - mmengine - INFO - Epoch(train) [61][860/2119] lr: 4.0000e-02 eta: 18:14:56 time: 0.3192 data_time: 0.0213 memory: 5826 grad_norm: 3.1280 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8772 loss: 2.8772 2022/10/07 20:10:10 - mmengine - INFO - Epoch(train) [61][880/2119] lr: 4.0000e-02 eta: 18:14:49 time: 0.3610 data_time: 0.0168 memory: 5826 grad_norm: 3.1203 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.8813 loss: 2.8813 2022/10/07 20:10:16 - mmengine - INFO - Epoch(train) [61][900/2119] lr: 4.0000e-02 eta: 18:14:42 time: 0.3292 data_time: 0.0274 memory: 5826 grad_norm: 3.1737 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5722 loss: 2.5722 2022/10/07 20:10:23 - mmengine - INFO - Epoch(train) [61][920/2119] lr: 4.0000e-02 eta: 18:14:34 time: 0.3291 data_time: 0.0165 memory: 5826 grad_norm: 3.1250 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6307 loss: 2.6307 2022/10/07 20:10:30 - mmengine - INFO - Epoch(train) [61][940/2119] lr: 4.0000e-02 eta: 18:14:28 time: 0.3583 data_time: 0.0240 memory: 5826 grad_norm: 3.1155 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9480 loss: 2.9480 2022/10/07 20:10:38 - mmengine - INFO - Epoch(train) [61][960/2119] lr: 4.0000e-02 eta: 18:14:22 time: 0.3716 data_time: 0.0186 memory: 5826 grad_norm: 3.0633 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8526 loss: 2.8526 2022/10/07 20:10:44 - mmengine - INFO - Epoch(train) [61][980/2119] lr: 4.0000e-02 eta: 18:14:14 time: 0.3332 data_time: 0.0234 memory: 5826 grad_norm: 3.1244 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5435 loss: 2.5435 2022/10/07 20:10:52 - mmengine - INFO - Epoch(train) [61][1000/2119] lr: 4.0000e-02 eta: 18:14:08 time: 0.3644 data_time: 0.0189 memory: 5826 grad_norm: 3.1403 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6829 loss: 2.6829 2022/10/07 20:10:58 - mmengine - INFO - Epoch(train) [61][1020/2119] lr: 4.0000e-02 eta: 18:14:00 time: 0.3146 data_time: 0.0260 memory: 5826 grad_norm: 3.1141 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9602 loss: 2.9602 2022/10/07 20:11:05 - mmengine - INFO - Epoch(train) [61][1040/2119] lr: 4.0000e-02 eta: 18:13:53 time: 0.3358 data_time: 0.0222 memory: 5826 grad_norm: 3.0972 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7220 loss: 2.7220 2022/10/07 20:11:11 - mmengine - INFO - Epoch(train) [61][1060/2119] lr: 4.0000e-02 eta: 18:13:46 time: 0.3411 data_time: 0.0258 memory: 5826 grad_norm: 3.1159 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7869 loss: 2.7869 2022/10/07 20:11:19 - mmengine - INFO - Epoch(train) [61][1080/2119] lr: 4.0000e-02 eta: 18:13:40 time: 0.3753 data_time: 0.0174 memory: 5826 grad_norm: 3.1158 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8615 loss: 2.8615 2022/10/07 20:11:26 - mmengine - INFO - Epoch(train) [61][1100/2119] lr: 4.0000e-02 eta: 18:13:34 time: 0.3681 data_time: 0.0246 memory: 5826 grad_norm: 3.1450 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8982 loss: 2.8982 2022/10/07 20:11:32 - mmengine - INFO - Epoch(train) [61][1120/2119] lr: 4.0000e-02 eta: 18:13:26 time: 0.3070 data_time: 0.0216 memory: 5826 grad_norm: 3.1123 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7760 loss: 2.7760 2022/10/07 20:11:40 - mmengine - INFO - Epoch(train) [61][1140/2119] lr: 4.0000e-02 eta: 18:13:19 time: 0.3628 data_time: 0.0242 memory: 5826 grad_norm: 3.0905 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7164 loss: 2.7164 2022/10/07 20:11:46 - mmengine - INFO - Epoch(train) [61][1160/2119] lr: 4.0000e-02 eta: 18:13:11 time: 0.3225 data_time: 0.0218 memory: 5826 grad_norm: 3.1910 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9891 loss: 2.9891 2022/10/07 20:11:53 - mmengine - INFO - Epoch(train) [61][1180/2119] lr: 4.0000e-02 eta: 18:13:05 time: 0.3441 data_time: 0.0205 memory: 5826 grad_norm: 3.1201 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6182 loss: 2.6182 2022/10/07 20:12:00 - mmengine - INFO - Epoch(train) [61][1200/2119] lr: 4.0000e-02 eta: 18:12:58 time: 0.3580 data_time: 0.0265 memory: 5826 grad_norm: 3.1303 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9792 loss: 2.9792 2022/10/07 20:12:07 - mmengine - INFO - Epoch(train) [61][1220/2119] lr: 4.0000e-02 eta: 18:12:50 time: 0.3242 data_time: 0.0224 memory: 5826 grad_norm: 3.1940 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9026 loss: 2.9026 2022/10/07 20:12:14 - mmengine - INFO - Epoch(train) [61][1240/2119] lr: 4.0000e-02 eta: 18:12:44 time: 0.3727 data_time: 0.0336 memory: 5826 grad_norm: 3.0805 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6112 loss: 2.6112 2022/10/07 20:12:21 - mmengine - INFO - Epoch(train) [61][1260/2119] lr: 4.0000e-02 eta: 18:12:36 time: 0.3171 data_time: 0.0257 memory: 5826 grad_norm: 3.0532 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8841 loss: 2.8841 2022/10/07 20:12:28 - mmengine - INFO - Epoch(train) [61][1280/2119] lr: 4.0000e-02 eta: 18:12:30 time: 0.3684 data_time: 0.0165 memory: 5826 grad_norm: 3.0731 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8540 loss: 2.8540 2022/10/07 20:12:35 - mmengine - INFO - Epoch(train) [61][1300/2119] lr: 4.0000e-02 eta: 18:12:23 time: 0.3494 data_time: 0.0207 memory: 5826 grad_norm: 3.1528 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5036 loss: 2.5036 2022/10/07 20:12:42 - mmengine - INFO - Epoch(train) [61][1320/2119] lr: 4.0000e-02 eta: 18:12:17 time: 0.3543 data_time: 0.0195 memory: 5826 grad_norm: 3.0527 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8687 loss: 2.8687 2022/10/07 20:12:49 - mmengine - INFO - Epoch(train) [61][1340/2119] lr: 4.0000e-02 eta: 18:12:10 time: 0.3466 data_time: 0.0231 memory: 5826 grad_norm: 3.1360 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9902 loss: 2.9902 2022/10/07 20:12:56 - mmengine - INFO - Epoch(train) [61][1360/2119] lr: 4.0000e-02 eta: 18:12:03 time: 0.3340 data_time: 0.0236 memory: 5826 grad_norm: 3.1478 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6533 loss: 2.6533 2022/10/07 20:13:02 - mmengine - INFO - Epoch(train) [61][1380/2119] lr: 4.0000e-02 eta: 18:11:55 time: 0.3333 data_time: 0.0267 memory: 5826 grad_norm: 3.0430 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7549 loss: 2.7549 2022/10/07 20:13:09 - mmengine - INFO - Epoch(train) [61][1400/2119] lr: 4.0000e-02 eta: 18:11:47 time: 0.3159 data_time: 0.0245 memory: 5826 grad_norm: 3.1017 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6189 loss: 2.6189 2022/10/07 20:13:15 - mmengine - INFO - Epoch(train) [61][1420/2119] lr: 4.0000e-02 eta: 18:11:40 time: 0.3353 data_time: 0.0254 memory: 5826 grad_norm: 3.1355 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9374 loss: 2.9374 2022/10/07 20:13:23 - mmengine - INFO - Epoch(train) [61][1440/2119] lr: 4.0000e-02 eta: 18:11:34 time: 0.3775 data_time: 0.0207 memory: 5826 grad_norm: 3.0970 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6669 loss: 2.6669 2022/10/07 20:13:30 - mmengine - INFO - Epoch(train) [61][1460/2119] lr: 4.0000e-02 eta: 18:11:27 time: 0.3415 data_time: 0.0207 memory: 5826 grad_norm: 3.0907 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7057 loss: 2.7057 2022/10/07 20:13:36 - mmengine - INFO - Epoch(train) [61][1480/2119] lr: 4.0000e-02 eta: 18:11:20 time: 0.3378 data_time: 0.0190 memory: 5826 grad_norm: 3.0992 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7448 loss: 2.7448 2022/10/07 20:13:44 - mmengine - INFO - Epoch(train) [61][1500/2119] lr: 4.0000e-02 eta: 18:11:14 time: 0.3721 data_time: 0.0251 memory: 5826 grad_norm: 3.1615 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6751 loss: 2.6751 2022/10/07 20:13:51 - mmengine - INFO - Epoch(train) [61][1520/2119] lr: 4.0000e-02 eta: 18:11:07 time: 0.3537 data_time: 0.0229 memory: 5826 grad_norm: 3.0883 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6318 loss: 2.6318 2022/10/07 20:13:57 - mmengine - INFO - Epoch(train) [61][1540/2119] lr: 4.0000e-02 eta: 18:10:59 time: 0.3041 data_time: 0.0211 memory: 5826 grad_norm: 3.1242 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5616 loss: 2.5616 2022/10/07 20:14:04 - mmengine - INFO - Epoch(train) [61][1560/2119] lr: 4.0000e-02 eta: 18:10:53 time: 0.3705 data_time: 0.0205 memory: 5826 grad_norm: 3.1774 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7520 loss: 2.7520 2022/10/07 20:14:11 - mmengine - INFO - Epoch(train) [61][1580/2119] lr: 4.0000e-02 eta: 18:10:45 time: 0.3144 data_time: 0.0216 memory: 5826 grad_norm: 3.0728 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7042 loss: 2.7042 2022/10/07 20:14:18 - mmengine - INFO - Epoch(train) [61][1600/2119] lr: 4.0000e-02 eta: 18:10:38 time: 0.3427 data_time: 0.0238 memory: 5826 grad_norm: 3.0825 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7164 loss: 2.7164 2022/10/07 20:14:25 - mmengine - INFO - Epoch(train) [61][1620/2119] lr: 4.0000e-02 eta: 18:10:31 time: 0.3476 data_time: 0.0186 memory: 5826 grad_norm: 3.1264 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9539 loss: 2.9539 2022/10/07 20:14:32 - mmengine - INFO - Epoch(train) [61][1640/2119] lr: 4.0000e-02 eta: 18:10:24 time: 0.3473 data_time: 0.0206 memory: 5826 grad_norm: 3.1296 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7481 loss: 2.7481 2022/10/07 20:14:38 - mmengine - INFO - Epoch(train) [61][1660/2119] lr: 4.0000e-02 eta: 18:10:17 time: 0.3378 data_time: 0.0229 memory: 5826 grad_norm: 3.1244 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9432 loss: 2.9432 2022/10/07 20:14:46 - mmengine - INFO - Epoch(train) [61][1680/2119] lr: 4.0000e-02 eta: 18:10:11 time: 0.3688 data_time: 0.0196 memory: 5826 grad_norm: 3.0784 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7203 loss: 2.7203 2022/10/07 20:14:52 - mmengine - INFO - Epoch(train) [61][1700/2119] lr: 4.0000e-02 eta: 18:10:03 time: 0.3255 data_time: 0.0272 memory: 5826 grad_norm: 3.0790 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6911 loss: 2.6911 2022/10/07 20:15:00 - mmengine - INFO - Epoch(train) [61][1720/2119] lr: 4.0000e-02 eta: 18:09:57 time: 0.3797 data_time: 0.0204 memory: 5826 grad_norm: 3.1042 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5793 loss: 2.5793 2022/10/07 20:15:07 - mmengine - INFO - Epoch(train) [61][1740/2119] lr: 4.0000e-02 eta: 18:09:50 time: 0.3353 data_time: 0.0197 memory: 5826 grad_norm: 3.0744 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5002 loss: 2.5002 2022/10/07 20:15:14 - mmengine - INFO - Epoch(train) [61][1760/2119] lr: 4.0000e-02 eta: 18:09:43 time: 0.3551 data_time: 0.0249 memory: 5826 grad_norm: 3.1111 top1_acc: 0.0625 top5_acc: 0.3750 loss_cls: 2.6901 loss: 2.6901 2022/10/07 20:15:20 - mmengine - INFO - Epoch(train) [61][1780/2119] lr: 4.0000e-02 eta: 18:09:36 time: 0.3240 data_time: 0.0228 memory: 5826 grad_norm: 3.1505 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8221 loss: 2.8221 2022/10/07 20:15:28 - mmengine - INFO - Epoch(train) [61][1800/2119] lr: 4.0000e-02 eta: 18:09:30 time: 0.3764 data_time: 0.0234 memory: 5826 grad_norm: 3.0580 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7567 loss: 2.7567 2022/10/07 20:15:34 - mmengine - INFO - Epoch(train) [61][1820/2119] lr: 4.0000e-02 eta: 18:09:22 time: 0.3182 data_time: 0.0270 memory: 5826 grad_norm: 3.0936 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8401 loss: 2.8401 2022/10/07 20:15:41 - mmengine - INFO - Epoch(train) [61][1840/2119] lr: 4.0000e-02 eta: 18:09:15 time: 0.3537 data_time: 0.0254 memory: 5826 grad_norm: 3.1041 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7341 loss: 2.7341 2022/10/07 20:15:48 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 20:15:48 - mmengine - INFO - Epoch(train) [61][1860/2119] lr: 4.0000e-02 eta: 18:09:08 time: 0.3385 data_time: 0.0228 memory: 5826 grad_norm: 3.1162 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4924 loss: 2.4924 2022/10/07 20:15:55 - mmengine - INFO - Epoch(train) [61][1880/2119] lr: 4.0000e-02 eta: 18:09:02 time: 0.3730 data_time: 0.0188 memory: 5826 grad_norm: 3.1793 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.8291 loss: 2.8291 2022/10/07 20:16:03 - mmengine - INFO - Epoch(train) [61][1900/2119] lr: 4.0000e-02 eta: 18:08:56 time: 0.3700 data_time: 0.0239 memory: 5826 grad_norm: 3.1359 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6369 loss: 2.6369 2022/10/07 20:16:11 - mmengine - INFO - Epoch(train) [61][1920/2119] lr: 4.0000e-02 eta: 18:08:50 time: 0.3903 data_time: 0.0245 memory: 5826 grad_norm: 3.1064 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8699 loss: 2.8699 2022/10/07 20:16:17 - mmengine - INFO - Epoch(train) [61][1940/2119] lr: 4.0000e-02 eta: 18:08:43 time: 0.3431 data_time: 0.0243 memory: 5826 grad_norm: 3.1003 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6653 loss: 2.6653 2022/10/07 20:16:25 - mmengine - INFO - Epoch(train) [61][1960/2119] lr: 4.0000e-02 eta: 18:08:37 time: 0.3548 data_time: 0.0188 memory: 5826 grad_norm: 3.1265 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6604 loss: 2.6604 2022/10/07 20:16:31 - mmengine - INFO - Epoch(train) [61][1980/2119] lr: 4.0000e-02 eta: 18:08:30 time: 0.3457 data_time: 0.0204 memory: 5826 grad_norm: 3.1183 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7700 loss: 2.7700 2022/10/07 20:16:39 - mmengine - INFO - Epoch(train) [61][2000/2119] lr: 4.0000e-02 eta: 18:08:24 time: 0.3778 data_time: 0.0222 memory: 5826 grad_norm: 3.0613 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.5545 loss: 2.5545 2022/10/07 20:16:46 - mmengine - INFO - Epoch(train) [61][2020/2119] lr: 4.0000e-02 eta: 18:08:17 time: 0.3395 data_time: 0.0219 memory: 5826 grad_norm: 3.0958 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8452 loss: 2.8452 2022/10/07 20:16:53 - mmengine - INFO - Epoch(train) [61][2040/2119] lr: 4.0000e-02 eta: 18:08:10 time: 0.3465 data_time: 0.0188 memory: 5826 grad_norm: 3.1292 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7269 loss: 2.7269 2022/10/07 20:16:59 - mmengine - INFO - Epoch(train) [61][2060/2119] lr: 4.0000e-02 eta: 18:08:02 time: 0.3175 data_time: 0.0307 memory: 5826 grad_norm: 3.1051 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 3.1399 loss: 3.1399 2022/10/07 20:17:07 - mmengine - INFO - Epoch(train) [61][2080/2119] lr: 4.0000e-02 eta: 18:07:56 time: 0.3949 data_time: 0.0212 memory: 5826 grad_norm: 3.0356 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5796 loss: 2.5796 2022/10/07 20:17:13 - mmengine - INFO - Epoch(train) [61][2100/2119] lr: 4.0000e-02 eta: 18:07:48 time: 0.2941 data_time: 0.0230 memory: 5826 grad_norm: 3.1263 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7531 loss: 2.7531 2022/10/07 20:17:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 20:17:20 - mmengine - INFO - Epoch(train) [61][2119/2119] lr: 4.0000e-02 eta: 18:07:48 time: 0.3649 data_time: 0.0149 memory: 5826 grad_norm: 3.1039 top1_acc: 0.2000 top5_acc: 0.4000 loss_cls: 2.9929 loss: 2.9929 2022/10/07 20:17:30 - mmengine - INFO - Epoch(train) [62][20/2119] lr: 4.0000e-02 eta: 18:07:29 time: 0.4795 data_time: 0.1415 memory: 5826 grad_norm: 3.0761 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6899 loss: 2.6899 2022/10/07 20:17:36 - mmengine - INFO - Epoch(train) [62][40/2119] lr: 4.0000e-02 eta: 18:07:21 time: 0.3157 data_time: 0.0177 memory: 5826 grad_norm: 3.0856 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7172 loss: 2.7172 2022/10/07 20:17:43 - mmengine - INFO - Epoch(train) [62][60/2119] lr: 4.0000e-02 eta: 18:07:15 time: 0.3683 data_time: 0.0253 memory: 5826 grad_norm: 3.1153 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.5708 loss: 2.5708 2022/10/07 20:17:50 - mmengine - INFO - Epoch(train) [62][80/2119] lr: 4.0000e-02 eta: 18:07:07 time: 0.3189 data_time: 0.0178 memory: 5826 grad_norm: 3.1279 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8189 loss: 2.8189 2022/10/07 20:17:57 - mmengine - INFO - Epoch(train) [62][100/2119] lr: 4.0000e-02 eta: 18:07:01 time: 0.3637 data_time: 0.0252 memory: 5826 grad_norm: 3.0729 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5424 loss: 2.5424 2022/10/07 20:18:03 - mmengine - INFO - Epoch(train) [62][120/2119] lr: 4.0000e-02 eta: 18:06:53 time: 0.3268 data_time: 0.0237 memory: 5826 grad_norm: 3.0746 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7378 loss: 2.7378 2022/10/07 20:18:10 - mmengine - INFO - Epoch(train) [62][140/2119] lr: 4.0000e-02 eta: 18:06:46 time: 0.3329 data_time: 0.0257 memory: 5826 grad_norm: 3.1395 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6157 loss: 2.6157 2022/10/07 20:18:17 - mmengine - INFO - Epoch(train) [62][160/2119] lr: 4.0000e-02 eta: 18:06:38 time: 0.3297 data_time: 0.0155 memory: 5826 grad_norm: 3.0830 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8628 loss: 2.8628 2022/10/07 20:18:24 - mmengine - INFO - Epoch(train) [62][180/2119] lr: 4.0000e-02 eta: 18:06:32 time: 0.3607 data_time: 0.0198 memory: 5826 grad_norm: 3.1046 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8165 loss: 2.8165 2022/10/07 20:18:31 - mmengine - INFO - Epoch(train) [62][200/2119] lr: 4.0000e-02 eta: 18:06:25 time: 0.3445 data_time: 0.0159 memory: 5826 grad_norm: 3.0929 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9203 loss: 2.9203 2022/10/07 20:18:38 - mmengine - INFO - Epoch(train) [62][220/2119] lr: 4.0000e-02 eta: 18:06:19 time: 0.3680 data_time: 0.0238 memory: 5826 grad_norm: 3.1612 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.5473 loss: 2.5473 2022/10/07 20:18:45 - mmengine - INFO - Epoch(train) [62][240/2119] lr: 4.0000e-02 eta: 18:06:12 time: 0.3519 data_time: 0.0213 memory: 5826 grad_norm: 3.1072 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7257 loss: 2.7257 2022/10/07 20:18:52 - mmengine - INFO - Epoch(train) [62][260/2119] lr: 4.0000e-02 eta: 18:06:05 time: 0.3400 data_time: 0.0246 memory: 5826 grad_norm: 3.0930 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6548 loss: 2.6548 2022/10/07 20:18:59 - mmengine - INFO - Epoch(train) [62][280/2119] lr: 4.0000e-02 eta: 18:05:58 time: 0.3379 data_time: 0.0187 memory: 5826 grad_norm: 3.0999 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6496 loss: 2.6496 2022/10/07 20:19:06 - mmengine - INFO - Epoch(train) [62][300/2119] lr: 4.0000e-02 eta: 18:05:51 time: 0.3414 data_time: 0.0257 memory: 5826 grad_norm: 3.1755 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6329 loss: 2.6329 2022/10/07 20:19:13 - mmengine - INFO - Epoch(train) [62][320/2119] lr: 4.0000e-02 eta: 18:05:44 time: 0.3618 data_time: 0.0185 memory: 5826 grad_norm: 3.1408 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8484 loss: 2.8484 2022/10/07 20:19:19 - mmengine - INFO - Epoch(train) [62][340/2119] lr: 4.0000e-02 eta: 18:05:37 time: 0.3261 data_time: 0.0207 memory: 5826 grad_norm: 3.2190 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8199 loss: 2.8199 2022/10/07 20:19:26 - mmengine - INFO - Epoch(train) [62][360/2119] lr: 4.0000e-02 eta: 18:05:30 time: 0.3424 data_time: 0.0194 memory: 5826 grad_norm: 3.1437 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.8948 loss: 2.8948 2022/10/07 20:19:32 - mmengine - INFO - Epoch(train) [62][380/2119] lr: 4.0000e-02 eta: 18:05:22 time: 0.3094 data_time: 0.0227 memory: 5826 grad_norm: 3.1173 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.8836 loss: 2.8836 2022/10/07 20:19:40 - mmengine - INFO - Epoch(train) [62][400/2119] lr: 4.0000e-02 eta: 18:05:16 time: 0.3850 data_time: 0.0186 memory: 5826 grad_norm: 3.0599 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6717 loss: 2.6717 2022/10/07 20:19:47 - mmengine - INFO - Epoch(train) [62][420/2119] lr: 4.0000e-02 eta: 18:05:08 time: 0.3219 data_time: 0.0243 memory: 5826 grad_norm: 3.1029 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8623 loss: 2.8623 2022/10/07 20:19:54 - mmengine - INFO - Epoch(train) [62][440/2119] lr: 4.0000e-02 eta: 18:05:02 time: 0.3880 data_time: 0.0168 memory: 5826 grad_norm: 3.1563 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4244 loss: 2.4244 2022/10/07 20:20:01 - mmengine - INFO - Epoch(train) [62][460/2119] lr: 4.0000e-02 eta: 18:04:55 time: 0.3214 data_time: 0.0241 memory: 5826 grad_norm: 3.1901 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8699 loss: 2.8699 2022/10/07 20:20:09 - mmengine - INFO - Epoch(train) [62][480/2119] lr: 4.0000e-02 eta: 18:04:49 time: 0.3861 data_time: 0.0162 memory: 5826 grad_norm: 3.1590 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7990 loss: 2.7990 2022/10/07 20:20:15 - mmengine - INFO - Epoch(train) [62][500/2119] lr: 4.0000e-02 eta: 18:04:42 time: 0.3469 data_time: 0.0182 memory: 5826 grad_norm: 3.1034 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6441 loss: 2.6441 2022/10/07 20:20:23 - mmengine - INFO - Epoch(train) [62][520/2119] lr: 4.0000e-02 eta: 18:04:37 time: 0.3985 data_time: 0.0203 memory: 5826 grad_norm: 3.1233 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9203 loss: 2.9203 2022/10/07 20:20:29 - mmengine - INFO - Epoch(train) [62][540/2119] lr: 4.0000e-02 eta: 18:04:29 time: 0.3011 data_time: 0.0210 memory: 5826 grad_norm: 3.1157 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8096 loss: 2.8096 2022/10/07 20:20:36 - mmengine - INFO - Epoch(train) [62][560/2119] lr: 4.0000e-02 eta: 18:04:22 time: 0.3521 data_time: 0.0171 memory: 5826 grad_norm: 3.1121 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6167 loss: 2.6167 2022/10/07 20:20:43 - mmengine - INFO - Epoch(train) [62][580/2119] lr: 4.0000e-02 eta: 18:04:15 time: 0.3361 data_time: 0.0244 memory: 5826 grad_norm: 3.1006 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6636 loss: 2.6636 2022/10/07 20:20:51 - mmengine - INFO - Epoch(train) [62][600/2119] lr: 4.0000e-02 eta: 18:04:08 time: 0.3725 data_time: 0.0199 memory: 5826 grad_norm: 3.1769 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6921 loss: 2.6921 2022/10/07 20:20:57 - mmengine - INFO - Epoch(train) [62][620/2119] lr: 4.0000e-02 eta: 18:04:01 time: 0.3340 data_time: 0.0229 memory: 5826 grad_norm: 3.0728 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.3933 loss: 2.3933 2022/10/07 20:21:05 - mmengine - INFO - Epoch(train) [62][640/2119] lr: 4.0000e-02 eta: 18:03:55 time: 0.3651 data_time: 0.0208 memory: 5826 grad_norm: 3.1049 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7339 loss: 2.7339 2022/10/07 20:21:11 - mmengine - INFO - Epoch(train) [62][660/2119] lr: 4.0000e-02 eta: 18:03:47 time: 0.3141 data_time: 0.0249 memory: 5826 grad_norm: 3.1572 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8361 loss: 2.8361 2022/10/07 20:21:19 - mmengine - INFO - Epoch(train) [62][680/2119] lr: 4.0000e-02 eta: 18:03:41 time: 0.3825 data_time: 0.0241 memory: 5826 grad_norm: 3.0846 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8239 loss: 2.8239 2022/10/07 20:21:25 - mmengine - INFO - Epoch(train) [62][700/2119] lr: 4.0000e-02 eta: 18:03:34 time: 0.3315 data_time: 0.0238 memory: 5826 grad_norm: 3.0875 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.5906 loss: 2.5906 2022/10/07 20:21:33 - mmengine - INFO - Epoch(train) [62][720/2119] lr: 4.0000e-02 eta: 18:03:28 time: 0.3825 data_time: 0.0231 memory: 5826 grad_norm: 3.0630 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6350 loss: 2.6350 2022/10/07 20:21:39 - mmengine - INFO - Epoch(train) [62][740/2119] lr: 4.0000e-02 eta: 18:03:20 time: 0.3226 data_time: 0.0184 memory: 5826 grad_norm: 3.1518 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9602 loss: 2.9602 2022/10/07 20:21:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 20:21:46 - mmengine - INFO - Epoch(train) [62][760/2119] lr: 4.0000e-02 eta: 18:03:14 time: 0.3525 data_time: 0.0265 memory: 5826 grad_norm: 3.1196 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8609 loss: 2.8609 2022/10/07 20:21:52 - mmengine - INFO - Epoch(train) [62][780/2119] lr: 4.0000e-02 eta: 18:03:05 time: 0.3013 data_time: 0.0192 memory: 5826 grad_norm: 3.1700 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0313 loss: 3.0313 2022/10/07 20:22:00 - mmengine - INFO - Epoch(train) [62][800/2119] lr: 4.0000e-02 eta: 18:02:59 time: 0.3818 data_time: 0.0230 memory: 5826 grad_norm: 3.1695 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8179 loss: 2.8179 2022/10/07 20:22:07 - mmengine - INFO - Epoch(train) [62][820/2119] lr: 4.0000e-02 eta: 18:02:52 time: 0.3219 data_time: 0.0233 memory: 5826 grad_norm: 3.1295 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7030 loss: 2.7030 2022/10/07 20:22:15 - mmengine - INFO - Epoch(train) [62][840/2119] lr: 4.0000e-02 eta: 18:02:47 time: 0.4084 data_time: 0.0160 memory: 5826 grad_norm: 3.1277 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.9843 loss: 2.9843 2022/10/07 20:22:20 - mmengine - INFO - Epoch(train) [62][860/2119] lr: 4.0000e-02 eta: 18:02:38 time: 0.2897 data_time: 0.0209 memory: 5826 grad_norm: 3.1563 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6537 loss: 2.6537 2022/10/07 20:22:27 - mmengine - INFO - Epoch(train) [62][880/2119] lr: 4.0000e-02 eta: 18:02:31 time: 0.3383 data_time: 0.0266 memory: 5826 grad_norm: 3.1829 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6841 loss: 2.6841 2022/10/07 20:22:34 - mmengine - INFO - Epoch(train) [62][900/2119] lr: 4.0000e-02 eta: 18:02:23 time: 0.3146 data_time: 0.0201 memory: 5826 grad_norm: 3.0756 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9478 loss: 2.9478 2022/10/07 20:22:41 - mmengine - INFO - Epoch(train) [62][920/2119] lr: 4.0000e-02 eta: 18:02:17 time: 0.3752 data_time: 0.0221 memory: 5826 grad_norm: 3.1533 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7913 loss: 2.7913 2022/10/07 20:22:48 - mmengine - INFO - Epoch(train) [62][940/2119] lr: 4.0000e-02 eta: 18:02:10 time: 0.3445 data_time: 0.0209 memory: 5826 grad_norm: 3.0678 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6269 loss: 2.6269 2022/10/07 20:22:56 - mmengine - INFO - Epoch(train) [62][960/2119] lr: 4.0000e-02 eta: 18:02:04 time: 0.3823 data_time: 0.0196 memory: 5826 grad_norm: 3.1341 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4558 loss: 2.4558 2022/10/07 20:23:03 - mmengine - INFO - Epoch(train) [62][980/2119] lr: 4.0000e-02 eta: 18:01:58 time: 0.3648 data_time: 0.0225 memory: 5826 grad_norm: 3.1332 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6201 loss: 2.6201 2022/10/07 20:23:09 - mmengine - INFO - Epoch(train) [62][1000/2119] lr: 4.0000e-02 eta: 18:01:50 time: 0.3128 data_time: 0.0234 memory: 5826 grad_norm: 3.0946 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6063 loss: 2.6063 2022/10/07 20:23:15 - mmengine - INFO - Epoch(train) [62][1020/2119] lr: 4.0000e-02 eta: 18:01:42 time: 0.3018 data_time: 0.0284 memory: 5826 grad_norm: 3.1634 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7682 loss: 2.7682 2022/10/07 20:23:23 - mmengine - INFO - Epoch(train) [62][1040/2119] lr: 4.0000e-02 eta: 18:01:36 time: 0.3811 data_time: 0.0179 memory: 5826 grad_norm: 3.1394 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7775 loss: 2.7775 2022/10/07 20:23:30 - mmengine - INFO - Epoch(train) [62][1060/2119] lr: 4.0000e-02 eta: 18:01:29 time: 0.3495 data_time: 0.0241 memory: 5826 grad_norm: 3.1189 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8462 loss: 2.8462 2022/10/07 20:23:37 - mmengine - INFO - Epoch(train) [62][1080/2119] lr: 4.0000e-02 eta: 18:01:23 time: 0.3555 data_time: 0.0250 memory: 5826 grad_norm: 3.1577 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6901 loss: 2.6901 2022/10/07 20:23:43 - mmengine - INFO - Epoch(train) [62][1100/2119] lr: 4.0000e-02 eta: 18:01:15 time: 0.3194 data_time: 0.0187 memory: 5826 grad_norm: 3.0734 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6300 loss: 2.6300 2022/10/07 20:23:50 - mmengine - INFO - Epoch(train) [62][1120/2119] lr: 4.0000e-02 eta: 18:01:08 time: 0.3532 data_time: 0.0206 memory: 5826 grad_norm: 3.1128 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4981 loss: 2.4981 2022/10/07 20:23:58 - mmengine - INFO - Epoch(train) [62][1140/2119] lr: 4.0000e-02 eta: 18:01:02 time: 0.3572 data_time: 0.0244 memory: 5826 grad_norm: 3.1322 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8819 loss: 2.8819 2022/10/07 20:24:06 - mmengine - INFO - Epoch(train) [62][1160/2119] lr: 4.0000e-02 eta: 18:00:57 time: 0.4282 data_time: 0.0173 memory: 5826 grad_norm: 3.0962 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6674 loss: 2.6674 2022/10/07 20:24:12 - mmengine - INFO - Epoch(train) [62][1180/2119] lr: 4.0000e-02 eta: 18:00:49 time: 0.3116 data_time: 0.0182 memory: 5826 grad_norm: 3.1231 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9957 loss: 2.9957 2022/10/07 20:24:20 - mmengine - INFO - Epoch(train) [62][1200/2119] lr: 4.0000e-02 eta: 18:00:43 time: 0.3633 data_time: 0.0225 memory: 5826 grad_norm: 3.0786 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6654 loss: 2.6654 2022/10/07 20:24:27 - mmengine - INFO - Epoch(train) [62][1220/2119] lr: 4.0000e-02 eta: 18:00:36 time: 0.3457 data_time: 0.0231 memory: 5826 grad_norm: 3.0827 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.7532 loss: 2.7532 2022/10/07 20:24:34 - mmengine - INFO - Epoch(train) [62][1240/2119] lr: 4.0000e-02 eta: 18:00:29 time: 0.3704 data_time: 0.0190 memory: 5826 grad_norm: 3.1135 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6029 loss: 2.6029 2022/10/07 20:24:40 - mmengine - INFO - Epoch(train) [62][1260/2119] lr: 4.0000e-02 eta: 18:00:21 time: 0.2878 data_time: 0.0287 memory: 5826 grad_norm: 3.1097 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6825 loss: 2.6825 2022/10/07 20:24:47 - mmengine - INFO - Epoch(train) [62][1280/2119] lr: 4.0000e-02 eta: 18:00:14 time: 0.3555 data_time: 0.0219 memory: 5826 grad_norm: 3.1308 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8702 loss: 2.8702 2022/10/07 20:24:54 - mmengine - INFO - Epoch(train) [62][1300/2119] lr: 4.0000e-02 eta: 18:00:07 time: 0.3435 data_time: 0.0259 memory: 5826 grad_norm: 3.1067 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8167 loss: 2.8167 2022/10/07 20:25:00 - mmengine - INFO - Epoch(train) [62][1320/2119] lr: 4.0000e-02 eta: 18:00:00 time: 0.3342 data_time: 0.0171 memory: 5826 grad_norm: 3.0675 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9080 loss: 2.9080 2022/10/07 20:25:07 - mmengine - INFO - Epoch(train) [62][1340/2119] lr: 4.0000e-02 eta: 17:59:53 time: 0.3480 data_time: 0.0271 memory: 5826 grad_norm: 3.0606 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6987 loss: 2.6987 2022/10/07 20:25:15 - mmengine - INFO - Epoch(train) [62][1360/2119] lr: 4.0000e-02 eta: 17:59:47 time: 0.3579 data_time: 0.0168 memory: 5826 grad_norm: 3.0748 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6603 loss: 2.6603 2022/10/07 20:25:22 - mmengine - INFO - Epoch(train) [62][1380/2119] lr: 4.0000e-02 eta: 17:59:40 time: 0.3547 data_time: 0.0259 memory: 5826 grad_norm: 3.1015 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9252 loss: 2.9252 2022/10/07 20:25:28 - mmengine - INFO - Epoch(train) [62][1400/2119] lr: 4.0000e-02 eta: 17:59:33 time: 0.3392 data_time: 0.0223 memory: 5826 grad_norm: 3.1838 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6786 loss: 2.6786 2022/10/07 20:25:36 - mmengine - INFO - Epoch(train) [62][1420/2119] lr: 4.0000e-02 eta: 17:59:26 time: 0.3686 data_time: 0.0242 memory: 5826 grad_norm: 3.1281 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6674 loss: 2.6674 2022/10/07 20:25:43 - mmengine - INFO - Epoch(train) [62][1440/2119] lr: 4.0000e-02 eta: 17:59:20 time: 0.3477 data_time: 0.0242 memory: 5826 grad_norm: 3.1206 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9897 loss: 2.9897 2022/10/07 20:25:49 - mmengine - INFO - Epoch(train) [62][1460/2119] lr: 4.0000e-02 eta: 17:59:12 time: 0.3269 data_time: 0.0222 memory: 5826 grad_norm: 3.0689 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6145 loss: 2.6145 2022/10/07 20:25:57 - mmengine - INFO - Epoch(train) [62][1480/2119] lr: 4.0000e-02 eta: 17:59:06 time: 0.3784 data_time: 0.0242 memory: 5826 grad_norm: 3.0629 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6660 loss: 2.6660 2022/10/07 20:26:04 - mmengine - INFO - Epoch(train) [62][1500/2119] lr: 4.0000e-02 eta: 17:58:59 time: 0.3403 data_time: 0.0258 memory: 5826 grad_norm: 3.1357 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.5747 loss: 2.5747 2022/10/07 20:26:10 - mmengine - INFO - Epoch(train) [62][1520/2119] lr: 4.0000e-02 eta: 17:58:51 time: 0.3239 data_time: 0.0219 memory: 5826 grad_norm: 3.1731 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9774 loss: 2.9774 2022/10/07 20:26:17 - mmengine - INFO - Epoch(train) [62][1540/2119] lr: 4.0000e-02 eta: 17:58:44 time: 0.3432 data_time: 0.0220 memory: 5826 grad_norm: 3.0727 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6116 loss: 2.6116 2022/10/07 20:26:24 - mmengine - INFO - Epoch(train) [62][1560/2119] lr: 4.0000e-02 eta: 17:58:38 time: 0.3699 data_time: 0.0227 memory: 5826 grad_norm: 3.0786 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8290 loss: 2.8290 2022/10/07 20:26:31 - mmengine - INFO - Epoch(train) [62][1580/2119] lr: 4.0000e-02 eta: 17:58:30 time: 0.3108 data_time: 0.0195 memory: 5826 grad_norm: 3.0669 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9565 loss: 2.9565 2022/10/07 20:26:38 - mmengine - INFO - Epoch(train) [62][1600/2119] lr: 4.0000e-02 eta: 17:58:25 time: 0.3879 data_time: 0.0235 memory: 5826 grad_norm: 3.1013 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7341 loss: 2.7341 2022/10/07 20:26:45 - mmengine - INFO - Epoch(train) [62][1620/2119] lr: 4.0000e-02 eta: 17:58:17 time: 0.3293 data_time: 0.0211 memory: 5826 grad_norm: 3.1396 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8842 loss: 2.8842 2022/10/07 20:26:52 - mmengine - INFO - Epoch(train) [62][1640/2119] lr: 4.0000e-02 eta: 17:58:10 time: 0.3439 data_time: 0.0248 memory: 5826 grad_norm: 3.0514 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8839 loss: 2.8839 2022/10/07 20:26:59 - mmengine - INFO - Epoch(train) [62][1660/2119] lr: 4.0000e-02 eta: 17:58:04 time: 0.3594 data_time: 0.0243 memory: 5826 grad_norm: 3.0877 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 2.4532 loss: 2.4532 2022/10/07 20:27:06 - mmengine - INFO - Epoch(train) [62][1680/2119] lr: 4.0000e-02 eta: 17:57:56 time: 0.3334 data_time: 0.0201 memory: 5826 grad_norm: 3.1111 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0497 loss: 3.0497 2022/10/07 20:27:12 - mmengine - INFO - Epoch(train) [62][1700/2119] lr: 4.0000e-02 eta: 17:57:48 time: 0.3022 data_time: 0.0267 memory: 5826 grad_norm: 3.1405 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7960 loss: 2.7960 2022/10/07 20:27:20 - mmengine - INFO - Epoch(train) [62][1720/2119] lr: 4.0000e-02 eta: 17:57:43 time: 0.3968 data_time: 0.0222 memory: 5826 grad_norm: 3.1054 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7779 loss: 2.7779 2022/10/07 20:27:26 - mmengine - INFO - Epoch(train) [62][1740/2119] lr: 4.0000e-02 eta: 17:57:35 time: 0.3156 data_time: 0.0255 memory: 5826 grad_norm: 3.1186 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8400 loss: 2.8400 2022/10/07 20:27:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 20:27:34 - mmengine - INFO - Epoch(train) [62][1760/2119] lr: 4.0000e-02 eta: 17:57:30 time: 0.4107 data_time: 0.0255 memory: 5826 grad_norm: 3.0844 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7545 loss: 2.7545 2022/10/07 20:27:41 - mmengine - INFO - Epoch(train) [62][1780/2119] lr: 4.0000e-02 eta: 17:57:23 time: 0.3305 data_time: 0.0233 memory: 5826 grad_norm: 3.1009 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8371 loss: 2.8371 2022/10/07 20:27:48 - mmengine - INFO - Epoch(train) [62][1800/2119] lr: 4.0000e-02 eta: 17:57:16 time: 0.3570 data_time: 0.0233 memory: 5826 grad_norm: 3.1520 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7077 loss: 2.7077 2022/10/07 20:27:54 - mmengine - INFO - Epoch(train) [62][1820/2119] lr: 4.0000e-02 eta: 17:57:08 time: 0.3150 data_time: 0.0248 memory: 5826 grad_norm: 3.0752 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6495 loss: 2.6495 2022/10/07 20:28:02 - mmengine - INFO - Epoch(train) [62][1840/2119] lr: 4.0000e-02 eta: 17:57:02 time: 0.3833 data_time: 0.0248 memory: 5826 grad_norm: 3.0705 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.7494 loss: 2.7494 2022/10/07 20:28:09 - mmengine - INFO - Epoch(train) [62][1860/2119] lr: 4.0000e-02 eta: 17:56:55 time: 0.3258 data_time: 0.0249 memory: 5826 grad_norm: 3.1110 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.7529 loss: 2.7529 2022/10/07 20:28:17 - mmengine - INFO - Epoch(train) [62][1880/2119] lr: 4.0000e-02 eta: 17:56:49 time: 0.4022 data_time: 0.0256 memory: 5826 grad_norm: 3.0585 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8379 loss: 2.8379 2022/10/07 20:28:23 - mmengine - INFO - Epoch(train) [62][1900/2119] lr: 4.0000e-02 eta: 17:56:42 time: 0.3394 data_time: 0.0220 memory: 5826 grad_norm: 3.0903 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7194 loss: 2.7194 2022/10/07 20:28:32 - mmengine - INFO - Epoch(train) [62][1920/2119] lr: 4.0000e-02 eta: 17:56:38 time: 0.4315 data_time: 0.0201 memory: 5826 grad_norm: 3.0499 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5721 loss: 2.5721 2022/10/07 20:28:39 - mmengine - INFO - Epoch(train) [62][1940/2119] lr: 4.0000e-02 eta: 17:56:31 time: 0.3444 data_time: 0.0200 memory: 5826 grad_norm: 3.0703 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8311 loss: 2.8311 2022/10/07 20:28:46 - mmengine - INFO - Epoch(train) [62][1960/2119] lr: 4.0000e-02 eta: 17:56:24 time: 0.3604 data_time: 0.0217 memory: 5826 grad_norm: 3.1264 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6210 loss: 2.6210 2022/10/07 20:28:52 - mmengine - INFO - Epoch(train) [62][1980/2119] lr: 4.0000e-02 eta: 17:56:16 time: 0.3099 data_time: 0.0298 memory: 5826 grad_norm: 3.1338 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7800 loss: 2.7800 2022/10/07 20:28:59 - mmengine - INFO - Epoch(train) [62][2000/2119] lr: 4.0000e-02 eta: 17:56:10 time: 0.3541 data_time: 0.0203 memory: 5826 grad_norm: 3.1512 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7526 loss: 2.7526 2022/10/07 20:29:06 - mmengine - INFO - Epoch(train) [62][2020/2119] lr: 4.0000e-02 eta: 17:56:02 time: 0.3257 data_time: 0.0285 memory: 5826 grad_norm: 3.1421 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7224 loss: 2.7224 2022/10/07 20:29:13 - mmengine - INFO - Epoch(train) [62][2040/2119] lr: 4.0000e-02 eta: 17:55:56 time: 0.3603 data_time: 0.0165 memory: 5826 grad_norm: 3.1115 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6648 loss: 2.6648 2022/10/07 20:29:20 - mmengine - INFO - Epoch(train) [62][2060/2119] lr: 4.0000e-02 eta: 17:55:48 time: 0.3290 data_time: 0.0281 memory: 5826 grad_norm: 3.0953 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8711 loss: 2.8711 2022/10/07 20:29:27 - mmengine - INFO - Epoch(train) [62][2080/2119] lr: 4.0000e-02 eta: 17:55:42 time: 0.3630 data_time: 0.0194 memory: 5826 grad_norm: 3.1023 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7120 loss: 2.7120 2022/10/07 20:29:34 - mmengine - INFO - Epoch(train) [62][2100/2119] lr: 4.0000e-02 eta: 17:55:35 time: 0.3594 data_time: 0.0234 memory: 5826 grad_norm: 3.0762 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9429 loss: 2.9429 2022/10/07 20:29:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 20:29:40 - mmengine - INFO - Epoch(train) [62][2119/2119] lr: 4.0000e-02 eta: 17:55:35 time: 0.3537 data_time: 0.0175 memory: 5826 grad_norm: 3.1180 top1_acc: 0.6000 top5_acc: 0.8000 loss_cls: 2.8649 loss: 2.8649 2022/10/07 20:29:50 - mmengine - INFO - Epoch(train) [63][20/2119] lr: 4.0000e-02 eta: 17:55:16 time: 0.4876 data_time: 0.1127 memory: 5826 grad_norm: 3.0581 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7989 loss: 2.7989 2022/10/07 20:29:57 - mmengine - INFO - Epoch(train) [63][40/2119] lr: 4.0000e-02 eta: 17:55:09 time: 0.3370 data_time: 0.0197 memory: 5826 grad_norm: 3.0659 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5729 loss: 2.5729 2022/10/07 20:30:04 - mmengine - INFO - Epoch(train) [63][60/2119] lr: 4.0000e-02 eta: 17:55:03 time: 0.3777 data_time: 0.0242 memory: 5826 grad_norm: 3.1563 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8794 loss: 2.8794 2022/10/07 20:30:10 - mmengine - INFO - Epoch(train) [63][80/2119] lr: 4.0000e-02 eta: 17:54:55 time: 0.3070 data_time: 0.0192 memory: 5826 grad_norm: 3.1025 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8321 loss: 2.8321 2022/10/07 20:30:17 - mmengine - INFO - Epoch(train) [63][100/2119] lr: 4.0000e-02 eta: 17:54:49 time: 0.3538 data_time: 0.0257 memory: 5826 grad_norm: 3.1186 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7944 loss: 2.7944 2022/10/07 20:30:24 - mmengine - INFO - Epoch(train) [63][120/2119] lr: 4.0000e-02 eta: 17:54:41 time: 0.3327 data_time: 0.0196 memory: 5826 grad_norm: 3.0859 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6246 loss: 2.6246 2022/10/07 20:30:31 - mmengine - INFO - Epoch(train) [63][140/2119] lr: 4.0000e-02 eta: 17:54:34 time: 0.3279 data_time: 0.0268 memory: 5826 grad_norm: 3.0808 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6513 loss: 2.6513 2022/10/07 20:30:39 - mmengine - INFO - Epoch(train) [63][160/2119] lr: 4.0000e-02 eta: 17:54:29 time: 0.4045 data_time: 0.0239 memory: 5826 grad_norm: 3.1312 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8241 loss: 2.8241 2022/10/07 20:30:45 - mmengine - INFO - Epoch(train) [63][180/2119] lr: 4.0000e-02 eta: 17:54:21 time: 0.3383 data_time: 0.0222 memory: 5826 grad_norm: 3.1070 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5399 loss: 2.5399 2022/10/07 20:30:52 - mmengine - INFO - Epoch(train) [63][200/2119] lr: 4.0000e-02 eta: 17:54:14 time: 0.3286 data_time: 0.0208 memory: 5826 grad_norm: 3.1272 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6189 loss: 2.6189 2022/10/07 20:30:58 - mmengine - INFO - Epoch(train) [63][220/2119] lr: 4.0000e-02 eta: 17:54:06 time: 0.3223 data_time: 0.0255 memory: 5826 grad_norm: 3.1334 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6559 loss: 2.6559 2022/10/07 20:31:06 - mmengine - INFO - Epoch(train) [63][240/2119] lr: 4.0000e-02 eta: 17:54:00 time: 0.3801 data_time: 0.0182 memory: 5826 grad_norm: 3.1477 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6777 loss: 2.6777 2022/10/07 20:31:13 - mmengine - INFO - Epoch(train) [63][260/2119] lr: 4.0000e-02 eta: 17:53:53 time: 0.3246 data_time: 0.0205 memory: 5826 grad_norm: 3.0623 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7430 loss: 2.7430 2022/10/07 20:31:20 - mmengine - INFO - Epoch(train) [63][280/2119] lr: 4.0000e-02 eta: 17:53:46 time: 0.3604 data_time: 0.0226 memory: 5826 grad_norm: 3.0725 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6628 loss: 2.6628 2022/10/07 20:31:27 - mmengine - INFO - Epoch(train) [63][300/2119] lr: 4.0000e-02 eta: 17:53:39 time: 0.3444 data_time: 0.0303 memory: 5826 grad_norm: 3.1119 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4780 loss: 2.4780 2022/10/07 20:31:33 - mmengine - INFO - Epoch(train) [63][320/2119] lr: 4.0000e-02 eta: 17:53:32 time: 0.3399 data_time: 0.0267 memory: 5826 grad_norm: 3.0922 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7686 loss: 2.7686 2022/10/07 20:31:40 - mmengine - INFO - Epoch(train) [63][340/2119] lr: 4.0000e-02 eta: 17:53:25 time: 0.3344 data_time: 0.0266 memory: 5826 grad_norm: 3.1251 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6506 loss: 2.6506 2022/10/07 20:31:47 - mmengine - INFO - Epoch(train) [63][360/2119] lr: 4.0000e-02 eta: 17:53:18 time: 0.3550 data_time: 0.0177 memory: 5826 grad_norm: 3.0646 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8385 loss: 2.8385 2022/10/07 20:31:54 - mmengine - INFO - Epoch(train) [63][380/2119] lr: 4.0000e-02 eta: 17:53:11 time: 0.3241 data_time: 0.0253 memory: 5826 grad_norm: 3.1673 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.8109 loss: 2.8109 2022/10/07 20:32:01 - mmengine - INFO - Epoch(train) [63][400/2119] lr: 4.0000e-02 eta: 17:53:04 time: 0.3503 data_time: 0.0196 memory: 5826 grad_norm: 3.1037 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6066 loss: 2.6066 2022/10/07 20:32:08 - mmengine - INFO - Epoch(train) [63][420/2119] lr: 4.0000e-02 eta: 17:52:57 time: 0.3549 data_time: 0.0229 memory: 5826 grad_norm: 3.0997 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8294 loss: 2.8294 2022/10/07 20:32:16 - mmengine - INFO - Epoch(train) [63][440/2119] lr: 4.0000e-02 eta: 17:52:52 time: 0.4110 data_time: 0.0183 memory: 5826 grad_norm: 3.0804 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6227 loss: 2.6227 2022/10/07 20:32:23 - mmengine - INFO - Epoch(train) [63][460/2119] lr: 4.0000e-02 eta: 17:52:46 time: 0.3494 data_time: 0.0197 memory: 5826 grad_norm: 3.0447 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5221 loss: 2.5221 2022/10/07 20:32:30 - mmengine - INFO - Epoch(train) [63][480/2119] lr: 4.0000e-02 eta: 17:52:39 time: 0.3645 data_time: 0.0214 memory: 5826 grad_norm: 3.1576 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.8461 loss: 2.8461 2022/10/07 20:32:37 - mmengine - INFO - Epoch(train) [63][500/2119] lr: 4.0000e-02 eta: 17:52:32 time: 0.3510 data_time: 0.0240 memory: 5826 grad_norm: 3.1642 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7318 loss: 2.7318 2022/10/07 20:32:46 - mmengine - INFO - Epoch(train) [63][520/2119] lr: 4.0000e-02 eta: 17:52:27 time: 0.4133 data_time: 0.0207 memory: 5826 grad_norm: 3.1034 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6485 loss: 2.6485 2022/10/07 20:32:52 - mmengine - INFO - Epoch(train) [63][540/2119] lr: 4.0000e-02 eta: 17:52:20 time: 0.3301 data_time: 0.0203 memory: 5826 grad_norm: 3.1069 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8574 loss: 2.8574 2022/10/07 20:32:59 - mmengine - INFO - Epoch(train) [63][560/2119] lr: 4.0000e-02 eta: 17:52:13 time: 0.3424 data_time: 0.0208 memory: 5826 grad_norm: 3.1114 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6684 loss: 2.6684 2022/10/07 20:33:05 - mmengine - INFO - Epoch(train) [63][580/2119] lr: 4.0000e-02 eta: 17:52:05 time: 0.3007 data_time: 0.0244 memory: 5826 grad_norm: 3.0591 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6193 loss: 2.6193 2022/10/07 20:33:12 - mmengine - INFO - Epoch(train) [63][600/2119] lr: 4.0000e-02 eta: 17:51:58 time: 0.3438 data_time: 0.0184 memory: 5826 grad_norm: 3.1935 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5005 loss: 2.5005 2022/10/07 20:33:19 - mmengine - INFO - Epoch(train) [63][620/2119] lr: 4.0000e-02 eta: 17:51:51 time: 0.3550 data_time: 0.0240 memory: 5826 grad_norm: 3.1685 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8062 loss: 2.8062 2022/10/07 20:33:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 20:33:26 - mmengine - INFO - Epoch(train) [63][640/2119] lr: 4.0000e-02 eta: 17:51:44 time: 0.3259 data_time: 0.0211 memory: 5826 grad_norm: 3.0909 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7488 loss: 2.7488 2022/10/07 20:33:32 - mmengine - INFO - Epoch(train) [63][660/2119] lr: 4.0000e-02 eta: 17:51:36 time: 0.3276 data_time: 0.0243 memory: 5826 grad_norm: 3.0689 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0026 loss: 3.0026 2022/10/07 20:33:39 - mmengine - INFO - Epoch(train) [63][680/2119] lr: 4.0000e-02 eta: 17:51:30 time: 0.3625 data_time: 0.0186 memory: 5826 grad_norm: 3.1043 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9550 loss: 2.9550 2022/10/07 20:33:46 - mmengine - INFO - Epoch(train) [63][700/2119] lr: 4.0000e-02 eta: 17:51:23 time: 0.3430 data_time: 0.0232 memory: 5826 grad_norm: 3.1009 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6352 loss: 2.6352 2022/10/07 20:33:54 - mmengine - INFO - Epoch(train) [63][720/2119] lr: 4.0000e-02 eta: 17:51:17 time: 0.4019 data_time: 0.0202 memory: 5826 grad_norm: 3.1091 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6615 loss: 2.6615 2022/10/07 20:34:01 - mmengine - INFO - Epoch(train) [63][740/2119] lr: 4.0000e-02 eta: 17:51:10 time: 0.3273 data_time: 0.0243 memory: 5826 grad_norm: 3.0912 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.6695 loss: 2.6695 2022/10/07 20:34:09 - mmengine - INFO - Epoch(train) [63][760/2119] lr: 4.0000e-02 eta: 17:51:04 time: 0.3953 data_time: 0.0223 memory: 5826 grad_norm: 3.1112 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7571 loss: 2.7571 2022/10/07 20:34:15 - mmengine - INFO - Epoch(train) [63][780/2119] lr: 4.0000e-02 eta: 17:50:57 time: 0.3269 data_time: 0.0265 memory: 5826 grad_norm: 3.1577 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7154 loss: 2.7154 2022/10/07 20:34:23 - mmengine - INFO - Epoch(train) [63][800/2119] lr: 4.0000e-02 eta: 17:50:51 time: 0.3791 data_time: 0.0183 memory: 5826 grad_norm: 3.0881 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5045 loss: 2.5045 2022/10/07 20:34:30 - mmengine - INFO - Epoch(train) [63][820/2119] lr: 4.0000e-02 eta: 17:50:45 time: 0.3693 data_time: 0.0185 memory: 5826 grad_norm: 3.0517 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6249 loss: 2.6249 2022/10/07 20:34:37 - mmengine - INFO - Epoch(train) [63][840/2119] lr: 4.0000e-02 eta: 17:50:38 time: 0.3509 data_time: 0.0184 memory: 5826 grad_norm: 3.1018 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7189 loss: 2.7189 2022/10/07 20:34:44 - mmengine - INFO - Epoch(train) [63][860/2119] lr: 4.0000e-02 eta: 17:50:30 time: 0.3056 data_time: 0.0230 memory: 5826 grad_norm: 3.1276 top1_acc: 0.1250 top5_acc: 0.6875 loss_cls: 2.8005 loss: 2.8005 2022/10/07 20:34:51 - mmengine - INFO - Epoch(train) [63][880/2119] lr: 4.0000e-02 eta: 17:50:23 time: 0.3531 data_time: 0.0197 memory: 5826 grad_norm: 3.1231 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7506 loss: 2.7506 2022/10/07 20:34:58 - mmengine - INFO - Epoch(train) [63][900/2119] lr: 4.0000e-02 eta: 17:50:17 time: 0.3728 data_time: 0.0265 memory: 5826 grad_norm: 3.0391 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7824 loss: 2.7824 2022/10/07 20:35:05 - mmengine - INFO - Epoch(train) [63][920/2119] lr: 4.0000e-02 eta: 17:50:09 time: 0.3244 data_time: 0.0171 memory: 5826 grad_norm: 3.1143 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7381 loss: 2.7381 2022/10/07 20:35:11 - mmengine - INFO - Epoch(train) [63][940/2119] lr: 4.0000e-02 eta: 17:50:02 time: 0.3458 data_time: 0.0274 memory: 5826 grad_norm: 3.0720 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8099 loss: 2.8099 2022/10/07 20:35:19 - mmengine - INFO - Epoch(train) [63][960/2119] lr: 4.0000e-02 eta: 17:49:56 time: 0.3603 data_time: 0.0157 memory: 5826 grad_norm: 3.1277 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6594 loss: 2.6594 2022/10/07 20:35:26 - mmengine - INFO - Epoch(train) [63][980/2119] lr: 4.0000e-02 eta: 17:49:49 time: 0.3494 data_time: 0.0304 memory: 5826 grad_norm: 3.0849 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9755 loss: 2.9755 2022/10/07 20:35:32 - mmengine - INFO - Epoch(train) [63][1000/2119] lr: 4.0000e-02 eta: 17:49:42 time: 0.3230 data_time: 0.0174 memory: 5826 grad_norm: 3.1622 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7065 loss: 2.7065 2022/10/07 20:35:38 - mmengine - INFO - Epoch(train) [63][1020/2119] lr: 4.0000e-02 eta: 17:49:33 time: 0.3053 data_time: 0.0250 memory: 5826 grad_norm: 3.1409 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7369 loss: 2.7369 2022/10/07 20:35:45 - mmengine - INFO - Epoch(train) [63][1040/2119] lr: 4.0000e-02 eta: 17:49:27 time: 0.3608 data_time: 0.0193 memory: 5826 grad_norm: 3.0913 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6597 loss: 2.6597 2022/10/07 20:35:52 - mmengine - INFO - Epoch(train) [63][1060/2119] lr: 4.0000e-02 eta: 17:49:19 time: 0.3053 data_time: 0.0319 memory: 5826 grad_norm: 3.1545 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6857 loss: 2.6857 2022/10/07 20:35:59 - mmengine - INFO - Epoch(train) [63][1080/2119] lr: 4.0000e-02 eta: 17:49:13 time: 0.3868 data_time: 0.0191 memory: 5826 grad_norm: 3.1053 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7778 loss: 2.7778 2022/10/07 20:36:06 - mmengine - INFO - Epoch(train) [63][1100/2119] lr: 4.0000e-02 eta: 17:49:06 time: 0.3285 data_time: 0.0255 memory: 5826 grad_norm: 3.1568 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6701 loss: 2.6701 2022/10/07 20:36:12 - mmengine - INFO - Epoch(train) [63][1120/2119] lr: 4.0000e-02 eta: 17:48:58 time: 0.3281 data_time: 0.0253 memory: 5826 grad_norm: 3.0372 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4851 loss: 2.4851 2022/10/07 20:36:19 - mmengine - INFO - Epoch(train) [63][1140/2119] lr: 4.0000e-02 eta: 17:48:51 time: 0.3474 data_time: 0.0243 memory: 5826 grad_norm: 3.1364 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6909 loss: 2.6909 2022/10/07 20:36:27 - mmengine - INFO - Epoch(train) [63][1160/2119] lr: 4.0000e-02 eta: 17:48:45 time: 0.3742 data_time: 0.0199 memory: 5826 grad_norm: 3.1123 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9723 loss: 2.9723 2022/10/07 20:36:33 - mmengine - INFO - Epoch(train) [63][1180/2119] lr: 4.0000e-02 eta: 17:48:38 time: 0.3208 data_time: 0.0221 memory: 5826 grad_norm: 3.1848 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8734 loss: 2.8734 2022/10/07 20:36:41 - mmengine - INFO - Epoch(train) [63][1200/2119] lr: 4.0000e-02 eta: 17:48:31 time: 0.3614 data_time: 0.0232 memory: 5826 grad_norm: 3.1557 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9200 loss: 2.9200 2022/10/07 20:36:47 - mmengine - INFO - Epoch(train) [63][1220/2119] lr: 4.0000e-02 eta: 17:48:24 time: 0.3338 data_time: 0.0242 memory: 5826 grad_norm: 3.1279 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.5857 loss: 2.5857 2022/10/07 20:36:55 - mmengine - INFO - Epoch(train) [63][1240/2119] lr: 4.0000e-02 eta: 17:48:19 time: 0.4110 data_time: 0.0196 memory: 5826 grad_norm: 3.1219 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7289 loss: 2.7289 2022/10/07 20:37:01 - mmengine - INFO - Epoch(train) [63][1260/2119] lr: 4.0000e-02 eta: 17:48:10 time: 0.2795 data_time: 0.0224 memory: 5826 grad_norm: 3.0505 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7578 loss: 2.7578 2022/10/07 20:37:10 - mmengine - INFO - Epoch(train) [63][1280/2119] lr: 4.0000e-02 eta: 17:48:06 time: 0.4425 data_time: 0.0208 memory: 5826 grad_norm: 3.1242 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8777 loss: 2.8777 2022/10/07 20:37:17 - mmengine - INFO - Epoch(train) [63][1300/2119] lr: 4.0000e-02 eta: 17:47:59 time: 0.3369 data_time: 0.0195 memory: 5826 grad_norm: 3.1175 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7430 loss: 2.7430 2022/10/07 20:37:24 - mmengine - INFO - Epoch(train) [63][1320/2119] lr: 4.0000e-02 eta: 17:47:52 time: 0.3723 data_time: 0.0235 memory: 5826 grad_norm: 3.0673 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5932 loss: 2.5932 2022/10/07 20:37:31 - mmengine - INFO - Epoch(train) [63][1340/2119] lr: 4.0000e-02 eta: 17:47:45 time: 0.3416 data_time: 0.0265 memory: 5826 grad_norm: 3.0998 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8078 loss: 2.8078 2022/10/07 20:37:39 - mmengine - INFO - Epoch(train) [63][1360/2119] lr: 4.0000e-02 eta: 17:47:40 time: 0.3866 data_time: 0.0236 memory: 5826 grad_norm: 3.0454 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6091 loss: 2.6091 2022/10/07 20:37:46 - mmengine - INFO - Epoch(train) [63][1380/2119] lr: 4.0000e-02 eta: 17:47:33 time: 0.3474 data_time: 0.0267 memory: 5826 grad_norm: 3.0534 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7718 loss: 2.7718 2022/10/07 20:37:53 - mmengine - INFO - Epoch(train) [63][1400/2119] lr: 4.0000e-02 eta: 17:47:26 time: 0.3613 data_time: 0.0217 memory: 5826 grad_norm: 3.0912 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8347 loss: 2.8347 2022/10/07 20:37:59 - mmengine - INFO - Epoch(train) [63][1420/2119] lr: 4.0000e-02 eta: 17:47:19 time: 0.3295 data_time: 0.0214 memory: 5826 grad_norm: 3.0698 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6944 loss: 2.6944 2022/10/07 20:38:07 - mmengine - INFO - Epoch(train) [63][1440/2119] lr: 4.0000e-02 eta: 17:47:12 time: 0.3639 data_time: 0.0217 memory: 5826 grad_norm: 3.1900 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5563 loss: 2.5563 2022/10/07 20:38:13 - mmengine - INFO - Epoch(train) [63][1460/2119] lr: 4.0000e-02 eta: 17:47:05 time: 0.3256 data_time: 0.0237 memory: 5826 grad_norm: 3.1243 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6023 loss: 2.6023 2022/10/07 20:38:21 - mmengine - INFO - Epoch(train) [63][1480/2119] lr: 4.0000e-02 eta: 17:46:59 time: 0.3878 data_time: 0.0162 memory: 5826 grad_norm: 3.1294 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8455 loss: 2.8455 2022/10/07 20:38:27 - mmengine - INFO - Epoch(train) [63][1500/2119] lr: 4.0000e-02 eta: 17:46:51 time: 0.2948 data_time: 0.0261 memory: 5826 grad_norm: 3.1610 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6595 loss: 2.6595 2022/10/07 20:38:34 - mmengine - INFO - Epoch(train) [63][1520/2119] lr: 4.0000e-02 eta: 17:46:45 time: 0.3781 data_time: 0.0239 memory: 5826 grad_norm: 3.0364 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7667 loss: 2.7667 2022/10/07 20:38:40 - mmengine - INFO - Epoch(train) [63][1540/2119] lr: 4.0000e-02 eta: 17:46:37 time: 0.3005 data_time: 0.0176 memory: 5826 grad_norm: 3.1088 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6980 loss: 2.6980 2022/10/07 20:38:49 - mmengine - INFO - Epoch(train) [63][1560/2119] lr: 4.0000e-02 eta: 17:46:31 time: 0.4011 data_time: 0.0209 memory: 5826 grad_norm: 3.1729 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0532 loss: 3.0532 2022/10/07 20:38:56 - mmengine - INFO - Epoch(train) [63][1580/2119] lr: 4.0000e-02 eta: 17:46:25 time: 0.3742 data_time: 0.0259 memory: 5826 grad_norm: 3.1637 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5297 loss: 2.5297 2022/10/07 20:39:03 - mmengine - INFO - Epoch(train) [63][1600/2119] lr: 4.0000e-02 eta: 17:46:18 time: 0.3418 data_time: 0.0221 memory: 5826 grad_norm: 3.0923 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7769 loss: 2.7769 2022/10/07 20:39:09 - mmengine - INFO - Epoch(train) [63][1620/2119] lr: 4.0000e-02 eta: 17:46:10 time: 0.3187 data_time: 0.0217 memory: 5826 grad_norm: 3.0859 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6754 loss: 2.6754 2022/10/07 20:39:10 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 20:39:18 - mmengine - INFO - Epoch(train) [63][1640/2119] lr: 4.0000e-02 eta: 17:46:06 time: 0.4421 data_time: 0.0194 memory: 5826 grad_norm: 3.1476 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8259 loss: 2.8259 2022/10/07 20:39:25 - mmengine - INFO - Epoch(train) [63][1660/2119] lr: 4.0000e-02 eta: 17:45:59 time: 0.3346 data_time: 0.0229 memory: 5826 grad_norm: 3.1677 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7100 loss: 2.7100 2022/10/07 20:39:31 - mmengine - INFO - Epoch(train) [63][1680/2119] lr: 4.0000e-02 eta: 17:45:51 time: 0.3270 data_time: 0.0243 memory: 5826 grad_norm: 3.1694 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6053 loss: 2.6053 2022/10/07 20:39:38 - mmengine - INFO - Epoch(train) [63][1700/2119] lr: 4.0000e-02 eta: 17:45:44 time: 0.3319 data_time: 0.0243 memory: 5826 grad_norm: 3.0596 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7723 loss: 2.7723 2022/10/07 20:39:46 - mmengine - INFO - Epoch(train) [63][1720/2119] lr: 4.0000e-02 eta: 17:45:38 time: 0.3794 data_time: 0.0159 memory: 5826 grad_norm: 3.1422 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8676 loss: 2.8676 2022/10/07 20:39:52 - mmengine - INFO - Epoch(train) [63][1740/2119] lr: 4.0000e-02 eta: 17:45:31 time: 0.3350 data_time: 0.0249 memory: 5826 grad_norm: 3.1308 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.0005 loss: 3.0005 2022/10/07 20:39:59 - mmengine - INFO - Epoch(train) [63][1760/2119] lr: 4.0000e-02 eta: 17:45:24 time: 0.3529 data_time: 0.0218 memory: 5826 grad_norm: 3.0920 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6649 loss: 2.6649 2022/10/07 20:40:06 - mmengine - INFO - Epoch(train) [63][1780/2119] lr: 4.0000e-02 eta: 17:45:17 time: 0.3557 data_time: 0.0229 memory: 5826 grad_norm: 3.1245 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.6572 loss: 2.6572 2022/10/07 20:40:13 - mmengine - INFO - Epoch(train) [63][1800/2119] lr: 4.0000e-02 eta: 17:45:10 time: 0.3098 data_time: 0.0174 memory: 5826 grad_norm: 3.1160 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4248 loss: 2.4248 2022/10/07 20:40:20 - mmengine - INFO - Epoch(train) [63][1820/2119] lr: 4.0000e-02 eta: 17:45:03 time: 0.3697 data_time: 0.0254 memory: 5826 grad_norm: 3.0976 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6256 loss: 2.6256 2022/10/07 20:40:27 - mmengine - INFO - Epoch(train) [63][1840/2119] lr: 4.0000e-02 eta: 17:44:57 time: 0.3649 data_time: 0.0212 memory: 5826 grad_norm: 3.0755 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7054 loss: 2.7054 2022/10/07 20:40:33 - mmengine - INFO - Epoch(train) [63][1860/2119] lr: 4.0000e-02 eta: 17:44:49 time: 0.3046 data_time: 0.0282 memory: 5826 grad_norm: 3.1385 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.9183 loss: 2.9183 2022/10/07 20:40:41 - mmengine - INFO - Epoch(train) [63][1880/2119] lr: 4.0000e-02 eta: 17:44:42 time: 0.3608 data_time: 0.0254 memory: 5826 grad_norm: 3.1301 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8168 loss: 2.8168 2022/10/07 20:40:48 - mmengine - INFO - Epoch(train) [63][1900/2119] lr: 4.0000e-02 eta: 17:44:35 time: 0.3434 data_time: 0.0308 memory: 5826 grad_norm: 3.0811 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8512 loss: 2.8512 2022/10/07 20:40:54 - mmengine - INFO - Epoch(train) [63][1920/2119] lr: 4.0000e-02 eta: 17:44:28 time: 0.3452 data_time: 0.0202 memory: 5826 grad_norm: 3.0771 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7660 loss: 2.7660 2022/10/07 20:41:01 - mmengine - INFO - Epoch(train) [63][1940/2119] lr: 4.0000e-02 eta: 17:44:21 time: 0.3291 data_time: 0.0295 memory: 5826 grad_norm: 3.0748 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8923 loss: 2.8923 2022/10/07 20:41:09 - mmengine - INFO - Epoch(train) [63][1960/2119] lr: 4.0000e-02 eta: 17:44:15 time: 0.3807 data_time: 0.0212 memory: 5826 grad_norm: 3.1153 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6192 loss: 2.6192 2022/10/07 20:41:15 - mmengine - INFO - Epoch(train) [63][1980/2119] lr: 4.0000e-02 eta: 17:44:07 time: 0.3055 data_time: 0.0238 memory: 5826 grad_norm: 3.0659 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8176 loss: 2.8176 2022/10/07 20:41:23 - mmengine - INFO - Epoch(train) [63][2000/2119] lr: 4.0000e-02 eta: 17:44:01 time: 0.3915 data_time: 0.0185 memory: 5826 grad_norm: 3.1177 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7980 loss: 2.7980 2022/10/07 20:41:29 - mmengine - INFO - Epoch(train) [63][2020/2119] lr: 4.0000e-02 eta: 17:43:54 time: 0.3245 data_time: 0.0236 memory: 5826 grad_norm: 3.0843 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8175 loss: 2.8175 2022/10/07 20:41:36 - mmengine - INFO - Epoch(train) [63][2040/2119] lr: 4.0000e-02 eta: 17:43:47 time: 0.3655 data_time: 0.0231 memory: 5826 grad_norm: 3.0976 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7726 loss: 2.7726 2022/10/07 20:41:42 - mmengine - INFO - Epoch(train) [63][2060/2119] lr: 4.0000e-02 eta: 17:43:39 time: 0.2821 data_time: 0.0201 memory: 5826 grad_norm: 3.1513 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7403 loss: 2.7403 2022/10/07 20:41:50 - mmengine - INFO - Epoch(train) [63][2080/2119] lr: 4.0000e-02 eta: 17:43:33 time: 0.3855 data_time: 0.0248 memory: 5826 grad_norm: 3.1173 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8967 loss: 2.8967 2022/10/07 20:41:56 - mmengine - INFO - Epoch(train) [63][2100/2119] lr: 4.0000e-02 eta: 17:43:25 time: 0.3246 data_time: 0.0219 memory: 5826 grad_norm: 3.1454 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9612 loss: 2.9612 2022/10/07 20:42:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 20:42:02 - mmengine - INFO - Epoch(train) [63][2119/2119] lr: 4.0000e-02 eta: 17:43:25 time: 0.3081 data_time: 0.0186 memory: 5826 grad_norm: 3.1567 top1_acc: 0.4000 top5_acc: 0.6000 loss_cls: 2.9344 loss: 2.9344 2022/10/07 20:42:12 - mmengine - INFO - Epoch(train) [64][20/2119] lr: 4.0000e-02 eta: 17:43:06 time: 0.4720 data_time: 0.1178 memory: 5826 grad_norm: 3.0317 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6481 loss: 2.6481 2022/10/07 20:42:19 - mmengine - INFO - Epoch(train) [64][40/2119] lr: 4.0000e-02 eta: 17:43:00 time: 0.3539 data_time: 0.0186 memory: 5826 grad_norm: 3.1306 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8832 loss: 2.8832 2022/10/07 20:42:26 - mmengine - INFO - Epoch(train) [64][60/2119] lr: 4.0000e-02 eta: 17:42:53 time: 0.3480 data_time: 0.0226 memory: 5826 grad_norm: 3.0685 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7840 loss: 2.7840 2022/10/07 20:42:33 - mmengine - INFO - Epoch(train) [64][80/2119] lr: 4.0000e-02 eta: 17:42:46 time: 0.3442 data_time: 0.0279 memory: 5826 grad_norm: 2.9805 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5775 loss: 2.5775 2022/10/07 20:42:40 - mmengine - INFO - Epoch(train) [64][100/2119] lr: 4.0000e-02 eta: 17:42:40 time: 0.3855 data_time: 0.0180 memory: 5826 grad_norm: 3.1380 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7390 loss: 2.7390 2022/10/07 20:42:47 - mmengine - INFO - Epoch(train) [64][120/2119] lr: 4.0000e-02 eta: 17:42:32 time: 0.3242 data_time: 0.0209 memory: 5826 grad_norm: 3.1774 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7107 loss: 2.7107 2022/10/07 20:42:54 - mmengine - INFO - Epoch(train) [64][140/2119] lr: 4.0000e-02 eta: 17:42:25 time: 0.3381 data_time: 0.0259 memory: 5826 grad_norm: 3.1067 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8280 loss: 2.8280 2022/10/07 20:43:00 - mmengine - INFO - Epoch(train) [64][160/2119] lr: 4.0000e-02 eta: 17:42:18 time: 0.3329 data_time: 0.0165 memory: 5826 grad_norm: 3.1385 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6647 loss: 2.6647 2022/10/07 20:43:08 - mmengine - INFO - Epoch(train) [64][180/2119] lr: 4.0000e-02 eta: 17:42:12 time: 0.3787 data_time: 0.0211 memory: 5826 grad_norm: 3.0754 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7923 loss: 2.7923 2022/10/07 20:43:14 - mmengine - INFO - Epoch(train) [64][200/2119] lr: 4.0000e-02 eta: 17:42:04 time: 0.3022 data_time: 0.0208 memory: 5826 grad_norm: 3.0783 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5590 loss: 2.5590 2022/10/07 20:43:21 - mmengine - INFO - Epoch(train) [64][220/2119] lr: 4.0000e-02 eta: 17:41:57 time: 0.3493 data_time: 0.0321 memory: 5826 grad_norm: 3.1578 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6533 loss: 2.6533 2022/10/07 20:43:28 - mmengine - INFO - Epoch(train) [64][240/2119] lr: 4.0000e-02 eta: 17:41:50 time: 0.3286 data_time: 0.0165 memory: 5826 grad_norm: 3.1126 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4889 loss: 2.4889 2022/10/07 20:43:34 - mmengine - INFO - Epoch(train) [64][260/2119] lr: 4.0000e-02 eta: 17:41:42 time: 0.3397 data_time: 0.0224 memory: 5826 grad_norm: 3.0700 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5574 loss: 2.5574 2022/10/07 20:43:42 - mmengine - INFO - Epoch(train) [64][280/2119] lr: 4.0000e-02 eta: 17:41:36 time: 0.3676 data_time: 0.0192 memory: 5826 grad_norm: 3.1424 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4633 loss: 2.4633 2022/10/07 20:43:49 - mmengine - INFO - Epoch(train) [64][300/2119] lr: 4.0000e-02 eta: 17:41:29 time: 0.3425 data_time: 0.0229 memory: 5826 grad_norm: 3.1199 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5914 loss: 2.5914 2022/10/07 20:43:56 - mmengine - INFO - Epoch(train) [64][320/2119] lr: 4.0000e-02 eta: 17:41:23 time: 0.3617 data_time: 0.0223 memory: 5826 grad_norm: 3.1402 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7150 loss: 2.7150 2022/10/07 20:44:03 - mmengine - INFO - Epoch(train) [64][340/2119] lr: 4.0000e-02 eta: 17:41:16 time: 0.3615 data_time: 0.0195 memory: 5826 grad_norm: 3.1317 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6659 loss: 2.6659 2022/10/07 20:44:10 - mmengine - INFO - Epoch(train) [64][360/2119] lr: 4.0000e-02 eta: 17:41:09 time: 0.3513 data_time: 0.0189 memory: 5826 grad_norm: 3.1185 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8508 loss: 2.8508 2022/10/07 20:44:17 - mmengine - INFO - Epoch(train) [64][380/2119] lr: 4.0000e-02 eta: 17:41:03 time: 0.3714 data_time: 0.0276 memory: 5826 grad_norm: 3.1473 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6225 loss: 2.6225 2022/10/07 20:44:25 - mmengine - INFO - Epoch(train) [64][400/2119] lr: 4.0000e-02 eta: 17:40:57 time: 0.3887 data_time: 0.0157 memory: 5826 grad_norm: 3.1325 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7622 loss: 2.7622 2022/10/07 20:44:32 - mmengine - INFO - Epoch(train) [64][420/2119] lr: 4.0000e-02 eta: 17:40:50 time: 0.3196 data_time: 0.0225 memory: 5826 grad_norm: 3.0930 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8303 loss: 2.8303 2022/10/07 20:44:39 - mmengine - INFO - Epoch(train) [64][440/2119] lr: 4.0000e-02 eta: 17:40:44 time: 0.3823 data_time: 0.0187 memory: 5826 grad_norm: 3.0744 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8229 loss: 2.8229 2022/10/07 20:44:46 - mmengine - INFO - Epoch(train) [64][460/2119] lr: 4.0000e-02 eta: 17:40:37 time: 0.3459 data_time: 0.0244 memory: 5826 grad_norm: 3.1132 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5361 loss: 2.5361 2022/10/07 20:44:54 - mmengine - INFO - Epoch(train) [64][480/2119] lr: 4.0000e-02 eta: 17:40:31 time: 0.3719 data_time: 0.0181 memory: 5826 grad_norm: 3.1081 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6656 loss: 2.6656 2022/10/07 20:45:00 - mmengine - INFO - Epoch(train) [64][500/2119] lr: 4.0000e-02 eta: 17:40:23 time: 0.3301 data_time: 0.0214 memory: 5826 grad_norm: 3.1579 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.8268 loss: 2.8268 2022/10/07 20:45:01 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 20:45:08 - mmengine - INFO - Epoch(train) [64][520/2119] lr: 4.0000e-02 eta: 17:40:17 time: 0.3725 data_time: 0.0185 memory: 5826 grad_norm: 3.1353 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 2.5507 loss: 2.5507 2022/10/07 20:45:14 - mmengine - INFO - Epoch(train) [64][540/2119] lr: 4.0000e-02 eta: 17:40:09 time: 0.2900 data_time: 0.0244 memory: 5826 grad_norm: 3.1438 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4282 loss: 2.4282 2022/10/07 20:45:21 - mmengine - INFO - Epoch(train) [64][560/2119] lr: 4.0000e-02 eta: 17:40:02 time: 0.3564 data_time: 0.0186 memory: 5826 grad_norm: 3.0922 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6913 loss: 2.6913 2022/10/07 20:45:27 - mmengine - INFO - Epoch(train) [64][580/2119] lr: 4.0000e-02 eta: 17:39:55 time: 0.3278 data_time: 0.0218 memory: 5826 grad_norm: 3.1349 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9429 loss: 2.9429 2022/10/07 20:45:35 - mmengine - INFO - Epoch(train) [64][600/2119] lr: 4.0000e-02 eta: 17:39:49 time: 0.4031 data_time: 0.0207 memory: 5826 grad_norm: 3.1159 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7457 loss: 2.7457 2022/10/07 20:45:41 - mmengine - INFO - Epoch(train) [64][620/2119] lr: 4.0000e-02 eta: 17:39:41 time: 0.3028 data_time: 0.0197 memory: 5826 grad_norm: 3.0780 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8054 loss: 2.8054 2022/10/07 20:45:48 - mmengine - INFO - Epoch(train) [64][640/2119] lr: 4.0000e-02 eta: 17:39:34 time: 0.3431 data_time: 0.0200 memory: 5826 grad_norm: 3.1273 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5990 loss: 2.5990 2022/10/07 20:45:55 - mmengine - INFO - Epoch(train) [64][660/2119] lr: 4.0000e-02 eta: 17:39:28 time: 0.3574 data_time: 0.0187 memory: 5826 grad_norm: 3.1184 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6112 loss: 2.6112 2022/10/07 20:46:02 - mmengine - INFO - Epoch(train) [64][680/2119] lr: 4.0000e-02 eta: 17:39:21 time: 0.3443 data_time: 0.0205 memory: 5826 grad_norm: 3.0935 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6127 loss: 2.6127 2022/10/07 20:46:08 - mmengine - INFO - Epoch(train) [64][700/2119] lr: 4.0000e-02 eta: 17:39:13 time: 0.3072 data_time: 0.0219 memory: 5826 grad_norm: 3.0966 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8378 loss: 2.8378 2022/10/07 20:46:16 - mmengine - INFO - Epoch(train) [64][720/2119] lr: 4.0000e-02 eta: 17:39:07 time: 0.3931 data_time: 0.0179 memory: 5826 grad_norm: 3.1193 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6045 loss: 2.6045 2022/10/07 20:46:23 - mmengine - INFO - Epoch(train) [64][740/2119] lr: 4.0000e-02 eta: 17:39:00 time: 0.3542 data_time: 0.0227 memory: 5826 grad_norm: 3.1259 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6791 loss: 2.6791 2022/10/07 20:46:30 - mmengine - INFO - Epoch(train) [64][760/2119] lr: 4.0000e-02 eta: 17:38:53 time: 0.3367 data_time: 0.0202 memory: 5826 grad_norm: 3.1716 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0260 loss: 3.0260 2022/10/07 20:46:38 - mmengine - INFO - Epoch(train) [64][780/2119] lr: 4.0000e-02 eta: 17:38:47 time: 0.3888 data_time: 0.0220 memory: 5826 grad_norm: 3.0899 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4947 loss: 2.4947 2022/10/07 20:46:44 - mmengine - INFO - Epoch(train) [64][800/2119] lr: 4.0000e-02 eta: 17:38:39 time: 0.3049 data_time: 0.0192 memory: 5826 grad_norm: 3.0927 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7387 loss: 2.7387 2022/10/07 20:46:51 - mmengine - INFO - Epoch(train) [64][820/2119] lr: 4.0000e-02 eta: 17:38:33 time: 0.3689 data_time: 0.0207 memory: 5826 grad_norm: 3.1590 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5727 loss: 2.5727 2022/10/07 20:46:58 - mmengine - INFO - Epoch(train) [64][840/2119] lr: 4.0000e-02 eta: 17:38:25 time: 0.3192 data_time: 0.0258 memory: 5826 grad_norm: 3.1550 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7776 loss: 2.7776 2022/10/07 20:47:05 - mmengine - INFO - Epoch(train) [64][860/2119] lr: 4.0000e-02 eta: 17:38:18 time: 0.3377 data_time: 0.0242 memory: 5826 grad_norm: 3.1165 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5382 loss: 2.5382 2022/10/07 20:47:11 - mmengine - INFO - Epoch(train) [64][880/2119] lr: 4.0000e-02 eta: 17:38:11 time: 0.3345 data_time: 0.0247 memory: 5826 grad_norm: 3.0695 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6326 loss: 2.6326 2022/10/07 20:47:18 - mmengine - INFO - Epoch(train) [64][900/2119] lr: 4.0000e-02 eta: 17:38:04 time: 0.3354 data_time: 0.0208 memory: 5826 grad_norm: 3.1805 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5871 loss: 2.5871 2022/10/07 20:47:26 - mmengine - INFO - Epoch(train) [64][920/2119] lr: 4.0000e-02 eta: 17:37:59 time: 0.4190 data_time: 0.0205 memory: 5826 grad_norm: 3.1152 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8144 loss: 2.8144 2022/10/07 20:47:33 - mmengine - INFO - Epoch(train) [64][940/2119] lr: 4.0000e-02 eta: 17:37:51 time: 0.3188 data_time: 0.0248 memory: 5826 grad_norm: 3.0782 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8290 loss: 2.8290 2022/10/07 20:47:41 - mmengine - INFO - Epoch(train) [64][960/2119] lr: 4.0000e-02 eta: 17:37:46 time: 0.3966 data_time: 0.0158 memory: 5826 grad_norm: 3.0552 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7680 loss: 2.7680 2022/10/07 20:47:47 - mmengine - INFO - Epoch(train) [64][980/2119] lr: 4.0000e-02 eta: 17:37:38 time: 0.3237 data_time: 0.0233 memory: 5826 grad_norm: 3.1633 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7149 loss: 2.7149 2022/10/07 20:47:54 - mmengine - INFO - Epoch(train) [64][1000/2119] lr: 4.0000e-02 eta: 17:37:31 time: 0.3362 data_time: 0.0242 memory: 5826 grad_norm: 3.0966 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8352 loss: 2.8352 2022/10/07 20:48:00 - mmengine - INFO - Epoch(train) [64][1020/2119] lr: 4.0000e-02 eta: 17:37:23 time: 0.3194 data_time: 0.0270 memory: 5826 grad_norm: 3.1326 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7408 loss: 2.7408 2022/10/07 20:48:08 - mmengine - INFO - Epoch(train) [64][1040/2119] lr: 4.0000e-02 eta: 17:37:17 time: 0.3815 data_time: 0.0238 memory: 5826 grad_norm: 3.1133 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6537 loss: 2.6537 2022/10/07 20:48:14 - mmengine - INFO - Epoch(train) [64][1060/2119] lr: 4.0000e-02 eta: 17:37:09 time: 0.3045 data_time: 0.0194 memory: 5826 grad_norm: 3.0220 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7600 loss: 2.7600 2022/10/07 20:48:21 - mmengine - INFO - Epoch(train) [64][1080/2119] lr: 4.0000e-02 eta: 17:37:03 time: 0.3572 data_time: 0.0212 memory: 5826 grad_norm: 3.0780 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6430 loss: 2.6430 2022/10/07 20:48:28 - mmengine - INFO - Epoch(train) [64][1100/2119] lr: 4.0000e-02 eta: 17:36:56 time: 0.3425 data_time: 0.0277 memory: 5826 grad_norm: 3.1386 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6406 loss: 2.6406 2022/10/07 20:48:36 - mmengine - INFO - Epoch(train) [64][1120/2119] lr: 4.0000e-02 eta: 17:36:50 time: 0.3798 data_time: 0.0243 memory: 5826 grad_norm: 3.0658 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7439 loss: 2.7439 2022/10/07 20:48:42 - mmengine - INFO - Epoch(train) [64][1140/2119] lr: 4.0000e-02 eta: 17:36:42 time: 0.3369 data_time: 0.0238 memory: 5826 grad_norm: 3.1300 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9711 loss: 2.9711 2022/10/07 20:48:49 - mmengine - INFO - Epoch(train) [64][1160/2119] lr: 4.0000e-02 eta: 17:36:35 time: 0.3453 data_time: 0.0213 memory: 5826 grad_norm: 3.1289 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7665 loss: 2.7665 2022/10/07 20:48:55 - mmengine - INFO - Epoch(train) [64][1180/2119] lr: 4.0000e-02 eta: 17:36:27 time: 0.2945 data_time: 0.0240 memory: 5826 grad_norm: 3.1349 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.6186 loss: 2.6186 2022/10/07 20:49:02 - mmengine - INFO - Epoch(train) [64][1200/2119] lr: 4.0000e-02 eta: 17:36:20 time: 0.3426 data_time: 0.0237 memory: 5826 grad_norm: 3.1412 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9878 loss: 2.9878 2022/10/07 20:49:10 - mmengine - INFO - Epoch(train) [64][1220/2119] lr: 4.0000e-02 eta: 17:36:14 time: 0.3939 data_time: 0.0257 memory: 5826 grad_norm: 3.1303 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9626 loss: 2.9626 2022/10/07 20:49:16 - mmengine - INFO - Epoch(train) [64][1240/2119] lr: 4.0000e-02 eta: 17:36:07 time: 0.3310 data_time: 0.0211 memory: 5826 grad_norm: 3.1013 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.8795 loss: 2.8795 2022/10/07 20:49:23 - mmengine - INFO - Epoch(train) [64][1260/2119] lr: 4.0000e-02 eta: 17:36:00 time: 0.3482 data_time: 0.0230 memory: 5826 grad_norm: 3.1391 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7573 loss: 2.7573 2022/10/07 20:49:30 - mmengine - INFO - Epoch(train) [64][1280/2119] lr: 4.0000e-02 eta: 17:35:54 time: 0.3528 data_time: 0.0202 memory: 5826 grad_norm: 3.1188 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6531 loss: 2.6531 2022/10/07 20:49:38 - mmengine - INFO - Epoch(train) [64][1300/2119] lr: 4.0000e-02 eta: 17:35:47 time: 0.3779 data_time: 0.0243 memory: 5826 grad_norm: 3.0320 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6296 loss: 2.6296 2022/10/07 20:49:46 - mmengine - INFO - Epoch(train) [64][1320/2119] lr: 4.0000e-02 eta: 17:35:42 time: 0.4011 data_time: 0.0226 memory: 5826 grad_norm: 3.0951 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6547 loss: 2.6547 2022/10/07 20:49:52 - mmengine - INFO - Epoch(train) [64][1340/2119] lr: 4.0000e-02 eta: 17:35:34 time: 0.3006 data_time: 0.0227 memory: 5826 grad_norm: 3.1142 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6607 loss: 2.6607 2022/10/07 20:49:59 - mmengine - INFO - Epoch(train) [64][1360/2119] lr: 4.0000e-02 eta: 17:35:28 time: 0.3684 data_time: 0.0205 memory: 5826 grad_norm: 3.0725 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6448 loss: 2.6448 2022/10/07 20:50:07 - mmengine - INFO - Epoch(train) [64][1380/2119] lr: 4.0000e-02 eta: 17:35:21 time: 0.3624 data_time: 0.0201 memory: 5826 grad_norm: 3.1216 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8743 loss: 2.8743 2022/10/07 20:50:14 - mmengine - INFO - Epoch(train) [64][1400/2119] lr: 4.0000e-02 eta: 17:35:15 time: 0.3750 data_time: 0.0245 memory: 5826 grad_norm: 3.1342 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8537 loss: 2.8537 2022/10/07 20:50:22 - mmengine - INFO - Epoch(train) [64][1420/2119] lr: 4.0000e-02 eta: 17:35:09 time: 0.3702 data_time: 0.0188 memory: 5826 grad_norm: 3.0837 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 2.7639 loss: 2.7639 2022/10/07 20:50:29 - mmengine - INFO - Epoch(train) [64][1440/2119] lr: 4.0000e-02 eta: 17:35:02 time: 0.3454 data_time: 0.0217 memory: 5826 grad_norm: 3.1185 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7641 loss: 2.7641 2022/10/07 20:50:35 - mmengine - INFO - Epoch(train) [64][1460/2119] lr: 4.0000e-02 eta: 17:34:54 time: 0.3329 data_time: 0.0247 memory: 5826 grad_norm: 3.1018 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6825 loss: 2.6825 2022/10/07 20:50:43 - mmengine - INFO - Epoch(train) [64][1480/2119] lr: 4.0000e-02 eta: 17:34:48 time: 0.3752 data_time: 0.0275 memory: 5826 grad_norm: 3.1070 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8744 loss: 2.8744 2022/10/07 20:50:49 - mmengine - INFO - Epoch(train) [64][1500/2119] lr: 4.0000e-02 eta: 17:34:41 time: 0.3247 data_time: 0.0205 memory: 5826 grad_norm: 3.1399 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4897 loss: 2.4897 2022/10/07 20:50:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 20:50:57 - mmengine - INFO - Epoch(train) [64][1520/2119] lr: 4.0000e-02 eta: 17:34:36 time: 0.4092 data_time: 0.0206 memory: 5826 grad_norm: 3.0843 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7659 loss: 2.7659 2022/10/07 20:51:04 - mmengine - INFO - Epoch(train) [64][1540/2119] lr: 4.0000e-02 eta: 17:34:28 time: 0.3126 data_time: 0.0233 memory: 5826 grad_norm: 3.1285 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5572 loss: 2.5572 2022/10/07 20:51:12 - mmengine - INFO - Epoch(train) [64][1560/2119] lr: 4.0000e-02 eta: 17:34:23 time: 0.4102 data_time: 0.0221 memory: 5826 grad_norm: 3.1034 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7016 loss: 2.7016 2022/10/07 20:51:18 - mmengine - INFO - Epoch(train) [64][1580/2119] lr: 4.0000e-02 eta: 17:34:15 time: 0.3135 data_time: 0.0334 memory: 5826 grad_norm: 3.1270 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6536 loss: 2.6536 2022/10/07 20:51:25 - mmengine - INFO - Epoch(train) [64][1600/2119] lr: 4.0000e-02 eta: 17:34:08 time: 0.3316 data_time: 0.0247 memory: 5826 grad_norm: 3.1309 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7601 loss: 2.7601 2022/10/07 20:51:31 - mmengine - INFO - Epoch(train) [64][1620/2119] lr: 4.0000e-02 eta: 17:34:00 time: 0.3294 data_time: 0.0228 memory: 5826 grad_norm: 3.1070 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7554 loss: 2.7554 2022/10/07 20:51:39 - mmengine - INFO - Epoch(train) [64][1640/2119] lr: 4.0000e-02 eta: 17:33:54 time: 0.3799 data_time: 0.0193 memory: 5826 grad_norm: 3.0905 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8797 loss: 2.8797 2022/10/07 20:51:46 - mmengine - INFO - Epoch(train) [64][1660/2119] lr: 4.0000e-02 eta: 17:33:47 time: 0.3361 data_time: 0.0248 memory: 5826 grad_norm: 3.1644 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8599 loss: 2.8599 2022/10/07 20:51:53 - mmengine - INFO - Epoch(train) [64][1680/2119] lr: 4.0000e-02 eta: 17:33:40 time: 0.3635 data_time: 0.0208 memory: 5826 grad_norm: 3.1673 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0352 loss: 3.0352 2022/10/07 20:52:00 - mmengine - INFO - Epoch(train) [64][1700/2119] lr: 4.0000e-02 eta: 17:33:34 time: 0.3456 data_time: 0.0226 memory: 5826 grad_norm: 3.1657 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7990 loss: 2.7990 2022/10/07 20:52:07 - mmengine - INFO - Epoch(train) [64][1720/2119] lr: 4.0000e-02 eta: 17:33:27 time: 0.3621 data_time: 0.0193 memory: 5826 grad_norm: 3.1204 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6376 loss: 2.6376 2022/10/07 20:52:14 - mmengine - INFO - Epoch(train) [64][1740/2119] lr: 4.0000e-02 eta: 17:33:20 time: 0.3469 data_time: 0.0223 memory: 5826 grad_norm: 3.1198 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7484 loss: 2.7484 2022/10/07 20:52:22 - mmengine - INFO - Epoch(train) [64][1760/2119] lr: 4.0000e-02 eta: 17:33:15 time: 0.4108 data_time: 0.0205 memory: 5826 grad_norm: 3.1162 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5620 loss: 2.5620 2022/10/07 20:52:29 - mmengine - INFO - Epoch(train) [64][1780/2119] lr: 4.0000e-02 eta: 17:33:08 time: 0.3250 data_time: 0.0192 memory: 5826 grad_norm: 3.1604 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5839 loss: 2.5839 2022/10/07 20:52:36 - mmengine - INFO - Epoch(train) [64][1800/2119] lr: 4.0000e-02 eta: 17:33:01 time: 0.3730 data_time: 0.0217 memory: 5826 grad_norm: 3.1478 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7101 loss: 2.7101 2022/10/07 20:52:43 - mmengine - INFO - Epoch(train) [64][1820/2119] lr: 4.0000e-02 eta: 17:32:54 time: 0.3357 data_time: 0.0227 memory: 5826 grad_norm: 3.0862 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.9645 loss: 2.9645 2022/10/07 20:52:50 - mmengine - INFO - Epoch(train) [64][1840/2119] lr: 4.0000e-02 eta: 17:32:48 time: 0.3613 data_time: 0.0217 memory: 5826 grad_norm: 3.1121 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6407 loss: 2.6407 2022/10/07 20:52:58 - mmengine - INFO - Epoch(train) [64][1860/2119] lr: 4.0000e-02 eta: 17:32:41 time: 0.3724 data_time: 0.0233 memory: 5826 grad_norm: 3.0406 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5663 loss: 2.5663 2022/10/07 20:53:05 - mmengine - INFO - Epoch(train) [64][1880/2119] lr: 4.0000e-02 eta: 17:32:35 time: 0.3626 data_time: 0.0220 memory: 5826 grad_norm: 3.1201 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8203 loss: 2.8203 2022/10/07 20:53:11 - mmengine - INFO - Epoch(train) [64][1900/2119] lr: 4.0000e-02 eta: 17:32:26 time: 0.2868 data_time: 0.0225 memory: 5826 grad_norm: 3.0805 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6644 loss: 2.6644 2022/10/07 20:53:18 - mmengine - INFO - Epoch(train) [64][1920/2119] lr: 4.0000e-02 eta: 17:32:21 time: 0.3855 data_time: 0.0197 memory: 5826 grad_norm: 3.1070 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7087 loss: 2.7087 2022/10/07 20:53:25 - mmengine - INFO - Epoch(train) [64][1940/2119] lr: 4.0000e-02 eta: 17:32:13 time: 0.3287 data_time: 0.0229 memory: 5826 grad_norm: 3.1277 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6641 loss: 2.6641 2022/10/07 20:53:32 - mmengine - INFO - Epoch(train) [64][1960/2119] lr: 4.0000e-02 eta: 17:32:07 time: 0.3678 data_time: 0.0244 memory: 5826 grad_norm: 3.1498 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7670 loss: 2.7670 2022/10/07 20:53:39 - mmengine - INFO - Epoch(train) [64][1980/2119] lr: 4.0000e-02 eta: 17:32:00 time: 0.3392 data_time: 0.0256 memory: 5826 grad_norm: 3.1418 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6812 loss: 2.6812 2022/10/07 20:53:47 - mmengine - INFO - Epoch(train) [64][2000/2119] lr: 4.0000e-02 eta: 17:31:54 time: 0.4073 data_time: 0.0187 memory: 5826 grad_norm: 3.1500 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8518 loss: 2.8518 2022/10/07 20:53:53 - mmengine - INFO - Epoch(train) [64][2020/2119] lr: 4.0000e-02 eta: 17:31:46 time: 0.2927 data_time: 0.0252 memory: 5826 grad_norm: 3.1258 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.0049 loss: 3.0049 2022/10/07 20:54:01 - mmengine - INFO - Epoch(train) [64][2040/2119] lr: 4.0000e-02 eta: 17:31:41 time: 0.4157 data_time: 0.0194 memory: 5826 grad_norm: 3.0732 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6246 loss: 2.6246 2022/10/07 20:54:09 - mmengine - INFO - Epoch(train) [64][2060/2119] lr: 4.0000e-02 eta: 17:31:35 time: 0.3687 data_time: 0.0268 memory: 5826 grad_norm: 3.0948 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9051 loss: 2.9051 2022/10/07 20:54:16 - mmengine - INFO - Epoch(train) [64][2080/2119] lr: 4.0000e-02 eta: 17:31:28 time: 0.3676 data_time: 0.0231 memory: 5826 grad_norm: 3.1386 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6538 loss: 2.6538 2022/10/07 20:54:23 - mmengine - INFO - Epoch(train) [64][2100/2119] lr: 4.0000e-02 eta: 17:31:21 time: 0.3408 data_time: 0.0222 memory: 5826 grad_norm: 3.0600 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4299 loss: 2.4299 2022/10/07 20:54:28 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 20:54:28 - mmengine - INFO - Epoch(train) [64][2119/2119] lr: 4.0000e-02 eta: 17:31:21 time: 0.2844 data_time: 0.0158 memory: 5826 grad_norm: 3.0696 top1_acc: 0.4000 top5_acc: 0.6000 loss_cls: 2.7955 loss: 2.7955 2022/10/07 20:54:29 - mmengine - INFO - Saving checkpoint at 64 epochs 2022/10/07 20:54:40 - mmengine - INFO - Epoch(train) [65][20/2119] lr: 4.0000e-02 eta: 17:31:00 time: 0.4000 data_time: 0.1816 memory: 5826 grad_norm: 3.0632 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7372 loss: 2.7372 2022/10/07 20:54:46 - mmengine - INFO - Epoch(train) [65][40/2119] lr: 4.0000e-02 eta: 17:30:53 time: 0.3104 data_time: 0.0572 memory: 5826 grad_norm: 3.1198 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6057 loss: 2.6057 2022/10/07 20:54:54 - mmengine - INFO - Epoch(train) [65][60/2119] lr: 4.0000e-02 eta: 17:30:47 time: 0.3953 data_time: 0.0806 memory: 5826 grad_norm: 3.0976 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7014 loss: 2.7014 2022/10/07 20:55:01 - mmengine - INFO - Epoch(train) [65][80/2119] lr: 4.0000e-02 eta: 17:30:39 time: 0.3254 data_time: 0.0163 memory: 5826 grad_norm: 3.0356 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7379 loss: 2.7379 2022/10/07 20:55:08 - mmengine - INFO - Epoch(train) [65][100/2119] lr: 4.0000e-02 eta: 17:30:33 time: 0.3530 data_time: 0.0233 memory: 5826 grad_norm: 3.0248 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.5826 loss: 2.5826 2022/10/07 20:55:15 - mmengine - INFO - Epoch(train) [65][120/2119] lr: 4.0000e-02 eta: 17:30:25 time: 0.3337 data_time: 0.0199 memory: 5826 grad_norm: 3.0971 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7935 loss: 2.7935 2022/10/07 20:55:22 - mmengine - INFO - Epoch(train) [65][140/2119] lr: 4.0000e-02 eta: 17:30:19 time: 0.3578 data_time: 0.0205 memory: 5826 grad_norm: 3.1289 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.6444 loss: 2.6444 2022/10/07 20:55:28 - mmengine - INFO - Epoch(train) [65][160/2119] lr: 4.0000e-02 eta: 17:30:11 time: 0.3251 data_time: 0.0247 memory: 5826 grad_norm: 3.1140 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7510 loss: 2.7510 2022/10/07 20:55:36 - mmengine - INFO - Epoch(train) [65][180/2119] lr: 4.0000e-02 eta: 17:30:05 time: 0.3817 data_time: 0.0215 memory: 5826 grad_norm: 3.1057 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.7273 loss: 2.7273 2022/10/07 20:55:42 - mmengine - INFO - Epoch(train) [65][200/2119] lr: 4.0000e-02 eta: 17:29:58 time: 0.3129 data_time: 0.0217 memory: 5826 grad_norm: 3.1417 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8957 loss: 2.8957 2022/10/07 20:55:49 - mmengine - INFO - Epoch(train) [65][220/2119] lr: 4.0000e-02 eta: 17:29:51 time: 0.3577 data_time: 0.0268 memory: 5826 grad_norm: 3.1300 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5824 loss: 2.5824 2022/10/07 20:55:55 - mmengine - INFO - Epoch(train) [65][240/2119] lr: 4.0000e-02 eta: 17:29:43 time: 0.2974 data_time: 0.0220 memory: 5826 grad_norm: 3.0922 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8112 loss: 2.8112 2022/10/07 20:56:03 - mmengine - INFO - Epoch(train) [65][260/2119] lr: 4.0000e-02 eta: 17:29:37 time: 0.3888 data_time: 0.0210 memory: 5826 grad_norm: 3.1613 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8731 loss: 2.8731 2022/10/07 20:56:10 - mmengine - INFO - Epoch(train) [65][280/2119] lr: 4.0000e-02 eta: 17:29:30 time: 0.3357 data_time: 0.0250 memory: 5826 grad_norm: 3.0807 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6041 loss: 2.6041 2022/10/07 20:56:18 - mmengine - INFO - Epoch(train) [65][300/2119] lr: 4.0000e-02 eta: 17:29:24 time: 0.3893 data_time: 0.0202 memory: 5826 grad_norm: 3.1081 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7461 loss: 2.7461 2022/10/07 20:56:23 - mmengine - INFO - Epoch(train) [65][320/2119] lr: 4.0000e-02 eta: 17:29:15 time: 0.2869 data_time: 0.0207 memory: 5826 grad_norm: 3.1115 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8824 loss: 2.8824 2022/10/07 20:56:31 - mmengine - INFO - Epoch(train) [65][340/2119] lr: 4.0000e-02 eta: 17:29:10 time: 0.3830 data_time: 0.0198 memory: 5826 grad_norm: 3.1386 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8143 loss: 2.8143 2022/10/07 20:56:38 - mmengine - INFO - Epoch(train) [65][360/2119] lr: 4.0000e-02 eta: 17:29:02 time: 0.3336 data_time: 0.0256 memory: 5826 grad_norm: 3.0896 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0612 loss: 3.0612 2022/10/07 20:56:44 - mmengine - INFO - Epoch(train) [65][380/2119] lr: 4.0000e-02 eta: 17:28:55 time: 0.3391 data_time: 0.0255 memory: 5826 grad_norm: 3.0720 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8696 loss: 2.8696 2022/10/07 20:56:45 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 20:56:52 - mmengine - INFO - Epoch(train) [65][400/2119] lr: 4.0000e-02 eta: 17:28:49 time: 0.3640 data_time: 0.0230 memory: 5826 grad_norm: 3.1204 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7569 loss: 2.7569 2022/10/07 20:57:00 - mmengine - INFO - Epoch(train) [65][420/2119] lr: 4.0000e-02 eta: 17:28:43 time: 0.3909 data_time: 0.0174 memory: 5826 grad_norm: 3.1679 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8704 loss: 2.8704 2022/10/07 20:57:06 - mmengine - INFO - Epoch(train) [65][440/2119] lr: 4.0000e-02 eta: 17:28:35 time: 0.3183 data_time: 0.0273 memory: 5826 grad_norm: 3.1250 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5751 loss: 2.5751 2022/10/07 20:57:13 - mmengine - INFO - Epoch(train) [65][460/2119] lr: 4.0000e-02 eta: 17:28:28 time: 0.3429 data_time: 0.0216 memory: 5826 grad_norm: 3.1633 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8762 loss: 2.8762 2022/10/07 20:57:20 - mmengine - INFO - Epoch(train) [65][480/2119] lr: 4.0000e-02 eta: 17:28:21 time: 0.3450 data_time: 0.0253 memory: 5826 grad_norm: 3.1947 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9078 loss: 2.9078 2022/10/07 20:57:27 - mmengine - INFO - Epoch(train) [65][500/2119] lr: 4.0000e-02 eta: 17:28:16 time: 0.3908 data_time: 0.0234 memory: 5826 grad_norm: 3.1439 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7386 loss: 2.7386 2022/10/07 20:57:34 - mmengine - INFO - Epoch(train) [65][520/2119] lr: 4.0000e-02 eta: 17:28:08 time: 0.3033 data_time: 0.0195 memory: 5826 grad_norm: 3.1350 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6203 loss: 2.6203 2022/10/07 20:57:42 - mmengine - INFO - Epoch(train) [65][540/2119] lr: 4.0000e-02 eta: 17:28:02 time: 0.4005 data_time: 0.0241 memory: 5826 grad_norm: 3.1172 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6082 loss: 2.6082 2022/10/07 20:57:48 - mmengine - INFO - Epoch(train) [65][560/2119] lr: 4.0000e-02 eta: 17:27:55 time: 0.3303 data_time: 0.0210 memory: 5826 grad_norm: 3.1021 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5829 loss: 2.5829 2022/10/07 20:57:56 - mmengine - INFO - Epoch(train) [65][580/2119] lr: 4.0000e-02 eta: 17:27:49 time: 0.3785 data_time: 0.0198 memory: 5826 grad_norm: 3.1340 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7742 loss: 2.7742 2022/10/07 20:58:02 - mmengine - INFO - Epoch(train) [65][600/2119] lr: 4.0000e-02 eta: 17:27:41 time: 0.3222 data_time: 0.0273 memory: 5826 grad_norm: 3.1298 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7238 loss: 2.7238 2022/10/07 20:58:10 - mmengine - INFO - Epoch(train) [65][620/2119] lr: 4.0000e-02 eta: 17:27:35 time: 0.3810 data_time: 0.0188 memory: 5826 grad_norm: 3.1791 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6849 loss: 2.6849 2022/10/07 20:58:17 - mmengine - INFO - Epoch(train) [65][640/2119] lr: 4.0000e-02 eta: 17:27:28 time: 0.3545 data_time: 0.0231 memory: 5826 grad_norm: 3.0924 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5920 loss: 2.5920 2022/10/07 20:58:24 - mmengine - INFO - Epoch(train) [65][660/2119] lr: 4.0000e-02 eta: 17:27:22 time: 0.3778 data_time: 0.0194 memory: 5826 grad_norm: 3.0628 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7473 loss: 2.7473 2022/10/07 20:58:31 - mmengine - INFO - Epoch(train) [65][680/2119] lr: 4.0000e-02 eta: 17:27:15 time: 0.3291 data_time: 0.0231 memory: 5826 grad_norm: 3.1359 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.7838 loss: 2.7838 2022/10/07 20:58:40 - mmengine - INFO - Epoch(train) [65][700/2119] lr: 4.0000e-02 eta: 17:27:10 time: 0.4313 data_time: 0.0186 memory: 5826 grad_norm: 3.0678 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7243 loss: 2.7243 2022/10/07 20:58:46 - mmengine - INFO - Epoch(train) [65][720/2119] lr: 4.0000e-02 eta: 17:27:03 time: 0.3399 data_time: 0.0204 memory: 5826 grad_norm: 3.0971 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7446 loss: 2.7446 2022/10/07 20:58:54 - mmengine - INFO - Epoch(train) [65][740/2119] lr: 4.0000e-02 eta: 17:26:57 time: 0.3572 data_time: 0.0178 memory: 5826 grad_norm: 3.1808 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6819 loss: 2.6819 2022/10/07 20:59:00 - mmengine - INFO - Epoch(train) [65][760/2119] lr: 4.0000e-02 eta: 17:26:49 time: 0.3196 data_time: 0.0214 memory: 5826 grad_norm: 3.1160 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8572 loss: 2.8572 2022/10/07 20:59:06 - mmengine - INFO - Epoch(train) [65][780/2119] lr: 4.0000e-02 eta: 17:26:41 time: 0.3154 data_time: 0.0224 memory: 5826 grad_norm: 3.1516 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8642 loss: 2.8642 2022/10/07 20:59:14 - mmengine - INFO - Epoch(train) [65][800/2119] lr: 4.0000e-02 eta: 17:26:35 time: 0.3629 data_time: 0.0236 memory: 5826 grad_norm: 3.1077 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5436 loss: 2.5436 2022/10/07 20:59:21 - mmengine - INFO - Epoch(train) [65][820/2119] lr: 4.0000e-02 eta: 17:26:29 time: 0.3861 data_time: 0.0187 memory: 5826 grad_norm: 3.1950 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.8238 loss: 2.8238 2022/10/07 20:59:28 - mmengine - INFO - Epoch(train) [65][840/2119] lr: 4.0000e-02 eta: 17:26:21 time: 0.3135 data_time: 0.0234 memory: 5826 grad_norm: 3.0746 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4424 loss: 2.4424 2022/10/07 20:59:35 - mmengine - INFO - Epoch(train) [65][860/2119] lr: 4.0000e-02 eta: 17:26:15 time: 0.3655 data_time: 0.0224 memory: 5826 grad_norm: 3.1459 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7872 loss: 2.7872 2022/10/07 20:59:41 - mmengine - INFO - Epoch(train) [65][880/2119] lr: 4.0000e-02 eta: 17:26:07 time: 0.3238 data_time: 0.0225 memory: 5826 grad_norm: 3.1635 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7473 loss: 2.7473 2022/10/07 20:59:48 - mmengine - INFO - Epoch(train) [65][900/2119] lr: 4.0000e-02 eta: 17:26:01 time: 0.3540 data_time: 0.0225 memory: 5826 grad_norm: 3.1478 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7756 loss: 2.7756 2022/10/07 20:59:55 - mmengine - INFO - Epoch(train) [65][920/2119] lr: 4.0000e-02 eta: 17:25:53 time: 0.3231 data_time: 0.0209 memory: 5826 grad_norm: 3.1464 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7574 loss: 2.7574 2022/10/07 21:00:03 - mmengine - INFO - Epoch(train) [65][940/2119] lr: 4.0000e-02 eta: 17:25:47 time: 0.3914 data_time: 0.0216 memory: 5826 grad_norm: 3.1122 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6962 loss: 2.6962 2022/10/07 21:00:10 - mmengine - INFO - Epoch(train) [65][960/2119] lr: 4.0000e-02 eta: 17:25:40 time: 0.3406 data_time: 0.0268 memory: 5826 grad_norm: 3.1162 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8895 loss: 2.8895 2022/10/07 21:00:17 - mmengine - INFO - Epoch(train) [65][980/2119] lr: 4.0000e-02 eta: 17:25:34 time: 0.3672 data_time: 0.0187 memory: 5826 grad_norm: 3.0842 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6251 loss: 2.6251 2022/10/07 21:00:24 - mmengine - INFO - Epoch(train) [65][1000/2119] lr: 4.0000e-02 eta: 17:25:27 time: 0.3594 data_time: 0.0204 memory: 5826 grad_norm: 3.1184 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6421 loss: 2.6421 2022/10/07 21:00:32 - mmengine - INFO - Epoch(train) [65][1020/2119] lr: 4.0000e-02 eta: 17:25:22 time: 0.4025 data_time: 0.0183 memory: 5826 grad_norm: 3.1199 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7124 loss: 2.7124 2022/10/07 21:00:38 - mmengine - INFO - Epoch(train) [65][1040/2119] lr: 4.0000e-02 eta: 17:25:14 time: 0.2995 data_time: 0.0251 memory: 5826 grad_norm: 3.1358 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7110 loss: 2.7110 2022/10/07 21:00:45 - mmengine - INFO - Epoch(train) [65][1060/2119] lr: 4.0000e-02 eta: 17:25:07 time: 0.3495 data_time: 0.0248 memory: 5826 grad_norm: 3.1406 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6634 loss: 2.6634 2022/10/07 21:00:52 - mmengine - INFO - Epoch(train) [65][1080/2119] lr: 4.0000e-02 eta: 17:25:00 time: 0.3350 data_time: 0.0209 memory: 5826 grad_norm: 3.1014 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6099 loss: 2.6099 2022/10/07 21:01:00 - mmengine - INFO - Epoch(train) [65][1100/2119] lr: 4.0000e-02 eta: 17:24:54 time: 0.3876 data_time: 0.0415 memory: 5826 grad_norm: 3.1177 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9311 loss: 2.9311 2022/10/07 21:01:05 - mmengine - INFO - Epoch(train) [65][1120/2119] lr: 4.0000e-02 eta: 17:24:45 time: 0.2850 data_time: 0.0232 memory: 5826 grad_norm: 3.1313 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7101 loss: 2.7101 2022/10/07 21:01:13 - mmengine - INFO - Epoch(train) [65][1140/2119] lr: 4.0000e-02 eta: 17:24:39 time: 0.3794 data_time: 0.0173 memory: 5826 grad_norm: 3.1123 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7523 loss: 2.7523 2022/10/07 21:01:20 - mmengine - INFO - Epoch(train) [65][1160/2119] lr: 4.0000e-02 eta: 17:24:32 time: 0.3351 data_time: 0.0224 memory: 5826 grad_norm: 3.0870 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7485 loss: 2.7485 2022/10/07 21:01:27 - mmengine - INFO - Epoch(train) [65][1180/2119] lr: 4.0000e-02 eta: 17:24:26 time: 0.3726 data_time: 0.0224 memory: 5826 grad_norm: 3.1532 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7542 loss: 2.7542 2022/10/07 21:01:34 - mmengine - INFO - Epoch(train) [65][1200/2119] lr: 4.0000e-02 eta: 17:24:18 time: 0.3212 data_time: 0.0207 memory: 5826 grad_norm: 3.1460 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6877 loss: 2.6877 2022/10/07 21:01:41 - mmengine - INFO - Epoch(train) [65][1220/2119] lr: 4.0000e-02 eta: 17:24:12 time: 0.3731 data_time: 0.0240 memory: 5826 grad_norm: 3.1328 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6320 loss: 2.6320 2022/10/07 21:01:48 - mmengine - INFO - Epoch(train) [65][1240/2119] lr: 4.0000e-02 eta: 17:24:06 time: 0.3711 data_time: 0.0232 memory: 5826 grad_norm: 3.0828 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7440 loss: 2.7440 2022/10/07 21:01:55 - mmengine - INFO - Epoch(train) [65][1260/2119] lr: 4.0000e-02 eta: 17:23:59 time: 0.3448 data_time: 0.0217 memory: 5826 grad_norm: 3.1676 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.6875 loss: 2.6875 2022/10/07 21:02:02 - mmengine - INFO - Epoch(train) [65][1280/2119] lr: 4.0000e-02 eta: 17:23:52 time: 0.3575 data_time: 0.0263 memory: 5826 grad_norm: 3.1165 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6596 loss: 2.6596 2022/10/07 21:02:08 - mmengine - INFO - Epoch(train) [65][1300/2119] lr: 4.0000e-02 eta: 17:23:44 time: 0.2977 data_time: 0.0179 memory: 5826 grad_norm: 3.1644 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8521 loss: 2.8521 2022/10/07 21:02:15 - mmengine - INFO - Epoch(train) [65][1320/2119] lr: 4.0000e-02 eta: 17:23:36 time: 0.3198 data_time: 0.0271 memory: 5826 grad_norm: 3.1271 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9060 loss: 2.9060 2022/10/07 21:02:22 - mmengine - INFO - Epoch(train) [65][1340/2119] lr: 4.0000e-02 eta: 17:23:29 time: 0.3419 data_time: 0.0238 memory: 5826 grad_norm: 3.0711 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7922 loss: 2.7922 2022/10/07 21:02:29 - mmengine - INFO - Epoch(train) [65][1360/2119] lr: 4.0000e-02 eta: 17:23:23 time: 0.3519 data_time: 0.0669 memory: 5826 grad_norm: 3.0923 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0068 loss: 3.0068 2022/10/07 21:02:36 - mmengine - INFO - Epoch(train) [65][1380/2119] lr: 4.0000e-02 eta: 17:23:15 time: 0.3395 data_time: 0.0942 memory: 5826 grad_norm: 3.1246 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8961 loss: 2.8961 2022/10/07 21:02:37 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 21:02:43 - mmengine - INFO - Epoch(train) [65][1400/2119] lr: 4.0000e-02 eta: 17:23:09 time: 0.3504 data_time: 0.1143 memory: 5826 grad_norm: 3.1756 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8400 loss: 2.8400 2022/10/07 21:02:49 - mmengine - INFO - Epoch(train) [65][1420/2119] lr: 4.0000e-02 eta: 17:23:02 time: 0.3382 data_time: 0.0810 memory: 5826 grad_norm: 3.1429 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6523 loss: 2.6523 2022/10/07 21:02:57 - mmengine - INFO - Epoch(train) [65][1440/2119] lr: 4.0000e-02 eta: 17:22:55 time: 0.3712 data_time: 0.0400 memory: 5826 grad_norm: 3.1153 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6262 loss: 2.6262 2022/10/07 21:03:04 - mmengine - INFO - Epoch(train) [65][1460/2119] lr: 4.0000e-02 eta: 17:22:48 time: 0.3426 data_time: 0.0146 memory: 5826 grad_norm: 3.1694 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6662 loss: 2.6662 2022/10/07 21:03:10 - mmengine - INFO - Epoch(train) [65][1480/2119] lr: 4.0000e-02 eta: 17:22:41 time: 0.3338 data_time: 0.0249 memory: 5826 grad_norm: 3.1195 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7821 loss: 2.7821 2022/10/07 21:03:18 - mmengine - INFO - Epoch(train) [65][1500/2119] lr: 4.0000e-02 eta: 17:22:35 time: 0.3969 data_time: 0.0169 memory: 5826 grad_norm: 3.1003 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9225 loss: 2.9225 2022/10/07 21:03:24 - mmengine - INFO - Epoch(train) [65][1520/2119] lr: 4.0000e-02 eta: 17:22:27 time: 0.2932 data_time: 0.0225 memory: 5826 grad_norm: 3.1236 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7397 loss: 2.7397 2022/10/07 21:03:31 - mmengine - INFO - Epoch(train) [65][1540/2119] lr: 4.0000e-02 eta: 17:22:21 time: 0.3695 data_time: 0.0229 memory: 5826 grad_norm: 3.1382 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9818 loss: 2.9818 2022/10/07 21:03:38 - mmengine - INFO - Epoch(train) [65][1560/2119] lr: 4.0000e-02 eta: 17:22:14 time: 0.3473 data_time: 0.0243 memory: 5826 grad_norm: 3.1530 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7774 loss: 2.7774 2022/10/07 21:03:45 - mmengine - INFO - Epoch(train) [65][1580/2119] lr: 4.0000e-02 eta: 17:22:06 time: 0.3244 data_time: 0.0219 memory: 5826 grad_norm: 3.1013 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.6195 loss: 2.6195 2022/10/07 21:03:52 - mmengine - INFO - Epoch(train) [65][1600/2119] lr: 4.0000e-02 eta: 17:21:59 time: 0.3430 data_time: 0.0289 memory: 5826 grad_norm: 3.1112 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7557 loss: 2.7557 2022/10/07 21:03:59 - mmengine - INFO - Epoch(train) [65][1620/2119] lr: 4.0000e-02 eta: 17:21:53 time: 0.3511 data_time: 0.0213 memory: 5826 grad_norm: 3.1477 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6469 loss: 2.6469 2022/10/07 21:04:06 - mmengine - INFO - Epoch(train) [65][1640/2119] lr: 4.0000e-02 eta: 17:21:46 time: 0.3496 data_time: 0.0200 memory: 5826 grad_norm: 3.1069 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6808 loss: 2.6808 2022/10/07 21:04:12 - mmengine - INFO - Epoch(train) [65][1660/2119] lr: 4.0000e-02 eta: 17:21:38 time: 0.3197 data_time: 0.0214 memory: 5826 grad_norm: 3.1332 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8056 loss: 2.8056 2022/10/07 21:04:20 - mmengine - INFO - Epoch(train) [65][1680/2119] lr: 4.0000e-02 eta: 17:21:33 time: 0.3994 data_time: 0.0282 memory: 5826 grad_norm: 3.1227 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.8866 loss: 2.8866 2022/10/07 21:04:26 - mmengine - INFO - Epoch(train) [65][1700/2119] lr: 4.0000e-02 eta: 17:21:24 time: 0.2969 data_time: 0.0241 memory: 5826 grad_norm: 3.0848 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8947 loss: 2.8947 2022/10/07 21:04:33 - mmengine - INFO - Epoch(train) [65][1720/2119] lr: 4.0000e-02 eta: 17:21:18 time: 0.3460 data_time: 0.0208 memory: 5826 grad_norm: 3.1374 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8244 loss: 2.8244 2022/10/07 21:04:40 - mmengine - INFO - Epoch(train) [65][1740/2119] lr: 4.0000e-02 eta: 17:21:11 time: 0.3478 data_time: 0.0204 memory: 5826 grad_norm: 3.0735 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8474 loss: 2.8474 2022/10/07 21:04:47 - mmengine - INFO - Epoch(train) [65][1760/2119] lr: 4.0000e-02 eta: 17:21:04 time: 0.3718 data_time: 0.0172 memory: 5826 grad_norm: 3.0987 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5174 loss: 2.5174 2022/10/07 21:04:54 - mmengine - INFO - Epoch(train) [65][1780/2119] lr: 4.0000e-02 eta: 17:20:57 time: 0.3384 data_time: 0.0252 memory: 5826 grad_norm: 3.1412 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6267 loss: 2.6267 2022/10/07 21:05:00 - mmengine - INFO - Epoch(train) [65][1800/2119] lr: 4.0000e-02 eta: 17:20:49 time: 0.3075 data_time: 0.0267 memory: 5826 grad_norm: 3.1617 top1_acc: 0.3125 top5_acc: 0.3125 loss_cls: 2.7072 loss: 2.7072 2022/10/07 21:05:08 - mmengine - INFO - Epoch(train) [65][1820/2119] lr: 4.0000e-02 eta: 17:20:43 time: 0.3845 data_time: 0.0231 memory: 5826 grad_norm: 3.1337 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7384 loss: 2.7384 2022/10/07 21:05:14 - mmengine - INFO - Epoch(train) [65][1840/2119] lr: 4.0000e-02 eta: 17:20:36 time: 0.3165 data_time: 0.0220 memory: 5826 grad_norm: 3.1083 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6066 loss: 2.6066 2022/10/07 21:05:21 - mmengine - INFO - Epoch(train) [65][1860/2119] lr: 4.0000e-02 eta: 17:20:29 time: 0.3446 data_time: 0.0255 memory: 5826 grad_norm: 3.1547 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6341 loss: 2.6341 2022/10/07 21:05:28 - mmengine - INFO - Epoch(train) [65][1880/2119] lr: 4.0000e-02 eta: 17:20:22 time: 0.3586 data_time: 0.0199 memory: 5826 grad_norm: 3.1414 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.9096 loss: 2.9096 2022/10/07 21:05:36 - mmengine - INFO - Epoch(train) [65][1900/2119] lr: 4.0000e-02 eta: 17:20:16 time: 0.3630 data_time: 0.0264 memory: 5826 grad_norm: 3.0856 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6565 loss: 2.6565 2022/10/07 21:05:42 - mmengine - INFO - Epoch(train) [65][1920/2119] lr: 4.0000e-02 eta: 17:20:08 time: 0.3287 data_time: 0.0216 memory: 5826 grad_norm: 3.1395 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7623 loss: 2.7623 2022/10/07 21:05:50 - mmengine - INFO - Epoch(train) [65][1940/2119] lr: 4.0000e-02 eta: 17:20:02 time: 0.3788 data_time: 0.0233 memory: 5826 grad_norm: 3.1358 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.1135 loss: 3.1135 2022/10/07 21:05:56 - mmengine - INFO - Epoch(train) [65][1960/2119] lr: 4.0000e-02 eta: 17:19:55 time: 0.3236 data_time: 0.0264 memory: 5826 grad_norm: 3.1235 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7456 loss: 2.7456 2022/10/07 21:06:04 - mmengine - INFO - Epoch(train) [65][1980/2119] lr: 4.0000e-02 eta: 17:19:49 time: 0.3798 data_time: 0.0206 memory: 5826 grad_norm: 3.1101 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7620 loss: 2.7620 2022/10/07 21:06:11 - mmengine - INFO - Epoch(train) [65][2000/2119] lr: 4.0000e-02 eta: 17:19:41 time: 0.3296 data_time: 0.0202 memory: 5826 grad_norm: 3.0897 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.9180 loss: 2.9180 2022/10/07 21:06:17 - mmengine - INFO - Epoch(train) [65][2020/2119] lr: 4.0000e-02 eta: 17:19:34 time: 0.3286 data_time: 0.0225 memory: 5826 grad_norm: 3.1310 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6667 loss: 2.6667 2022/10/07 21:06:24 - mmengine - INFO - Epoch(train) [65][2040/2119] lr: 4.0000e-02 eta: 17:19:27 time: 0.3477 data_time: 0.0223 memory: 5826 grad_norm: 3.1361 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6965 loss: 2.6965 2022/10/07 21:06:31 - mmengine - INFO - Epoch(train) [65][2060/2119] lr: 4.0000e-02 eta: 17:19:21 time: 0.3652 data_time: 0.0203 memory: 5826 grad_norm: 3.0893 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7672 loss: 2.7672 2022/10/07 21:06:39 - mmengine - INFO - Epoch(train) [65][2080/2119] lr: 4.0000e-02 eta: 17:19:15 time: 0.3843 data_time: 0.0231 memory: 5826 grad_norm: 3.1190 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8678 loss: 2.8678 2022/10/07 21:06:46 - mmengine - INFO - Epoch(train) [65][2100/2119] lr: 4.0000e-02 eta: 17:19:07 time: 0.3316 data_time: 0.0180 memory: 5826 grad_norm: 3.1418 top1_acc: 0.5625 top5_acc: 1.0000 loss_cls: 2.6294 loss: 2.6294 2022/10/07 21:06:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 21:06:51 - mmengine - INFO - Epoch(train) [65][2119/2119] lr: 4.0000e-02 eta: 17:19:07 time: 0.2973 data_time: 0.0205 memory: 5826 grad_norm: 3.1576 top1_acc: 0.4000 top5_acc: 0.5000 loss_cls: 2.8681 loss: 2.8681 2022/10/07 21:06:59 - mmengine - INFO - Epoch(val) [65][20/137] eta: 0:00:46 time: 0.3948 data_time: 0.3270 memory: 1241 2022/10/07 21:07:05 - mmengine - INFO - Epoch(val) [65][40/137] eta: 0:00:26 time: 0.2694 data_time: 0.2046 memory: 1241 2022/10/07 21:07:12 - mmengine - INFO - Epoch(val) [65][60/137] eta: 0:00:28 time: 0.3681 data_time: 0.3006 memory: 1241 2022/10/07 21:07:17 - mmengine - INFO - Epoch(val) [65][80/137] eta: 0:00:14 time: 0.2481 data_time: 0.1834 memory: 1241 2022/10/07 21:07:24 - mmengine - INFO - Epoch(val) [65][100/137] eta: 0:00:13 time: 0.3570 data_time: 0.2924 memory: 1241 2022/10/07 21:07:30 - mmengine - INFO - Epoch(val) [65][120/137] eta: 0:00:04 time: 0.2805 data_time: 0.2143 memory: 1241 2022/10/07 21:07:42 - mmengine - INFO - Epoch(val) [65][137/137] acc/top1: 0.4351 acc/top5: 0.6725 acc/mean1: 0.4350 2022/10/07 21:07:42 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb/best_acc/top1_epoch_25.pth is removed 2022/10/07 21:07:45 - mmengine - INFO - The best checkpoint with 0.4351 acc/top1 at 65 epoch is saved to best_acc/top1_epoch_65.pth. 2022/10/07 21:07:54 - mmengine - INFO - Epoch(train) [66][20/2119] lr: 4.0000e-02 eta: 17:18:48 time: 0.4478 data_time: 0.2290 memory: 5826 grad_norm: 3.0343 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.4519 loss: 2.4519 2022/10/07 21:08:00 - mmengine - INFO - Epoch(train) [66][40/2119] lr: 4.0000e-02 eta: 17:18:40 time: 0.2885 data_time: 0.0523 memory: 5826 grad_norm: 3.1302 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5971 loss: 2.5971 2022/10/07 21:08:06 - mmengine - INFO - Epoch(train) [66][60/2119] lr: 4.0000e-02 eta: 17:18:32 time: 0.3050 data_time: 0.0668 memory: 5826 grad_norm: 3.1017 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8400 loss: 2.8400 2022/10/07 21:08:13 - mmengine - INFO - Epoch(train) [66][80/2119] lr: 4.0000e-02 eta: 17:18:25 time: 0.3665 data_time: 0.0330 memory: 5826 grad_norm: 3.0475 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6185 loss: 2.6185 2022/10/07 21:08:20 - mmengine - INFO - Epoch(train) [66][100/2119] lr: 4.0000e-02 eta: 17:18:18 time: 0.3502 data_time: 0.0231 memory: 5826 grad_norm: 3.0882 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8646 loss: 2.8646 2022/10/07 21:08:27 - mmengine - INFO - Epoch(train) [66][120/2119] lr: 4.0000e-02 eta: 17:18:12 time: 0.3729 data_time: 0.0238 memory: 5826 grad_norm: 3.0674 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7347 loss: 2.7347 2022/10/07 21:08:34 - mmengine - INFO - Epoch(train) [66][140/2119] lr: 4.0000e-02 eta: 17:18:04 time: 0.3085 data_time: 0.0258 memory: 5826 grad_norm: 3.1509 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5649 loss: 2.5649 2022/10/07 21:08:40 - mmengine - INFO - Epoch(train) [66][160/2119] lr: 4.0000e-02 eta: 17:17:57 time: 0.3357 data_time: 0.0262 memory: 5826 grad_norm: 3.1177 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6934 loss: 2.6934 2022/10/07 21:08:47 - mmengine - INFO - Epoch(train) [66][180/2119] lr: 4.0000e-02 eta: 17:17:50 time: 0.3337 data_time: 0.0191 memory: 5826 grad_norm: 3.2079 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5670 loss: 2.5670 2022/10/07 21:08:54 - mmengine - INFO - Epoch(train) [66][200/2119] lr: 4.0000e-02 eta: 17:17:43 time: 0.3629 data_time: 0.0226 memory: 5826 grad_norm: 3.0987 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5984 loss: 2.5984 2022/10/07 21:09:01 - mmengine - INFO - Epoch(train) [66][220/2119] lr: 4.0000e-02 eta: 17:17:36 time: 0.3227 data_time: 0.0221 memory: 5826 grad_norm: 3.0997 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8571 loss: 2.8571 2022/10/07 21:09:08 - mmengine - INFO - Epoch(train) [66][240/2119] lr: 4.0000e-02 eta: 17:17:30 time: 0.3730 data_time: 0.0240 memory: 5826 grad_norm: 3.0954 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6801 loss: 2.6801 2022/10/07 21:09:15 - mmengine - INFO - Epoch(train) [66][260/2119] lr: 4.0000e-02 eta: 17:17:22 time: 0.3390 data_time: 0.0154 memory: 5826 grad_norm: 3.0789 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7416 loss: 2.7416 2022/10/07 21:09:17 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 21:09:22 - mmengine - INFO - Epoch(train) [66][280/2119] lr: 4.0000e-02 eta: 17:17:15 time: 0.3362 data_time: 0.0213 memory: 5826 grad_norm: 3.1374 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7910 loss: 2.7910 2022/10/07 21:09:29 - mmengine - INFO - Epoch(train) [66][300/2119] lr: 4.0000e-02 eta: 17:17:09 time: 0.3711 data_time: 0.0230 memory: 5826 grad_norm: 3.1329 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7302 loss: 2.7302 2022/10/07 21:09:36 - mmengine - INFO - Epoch(train) [66][320/2119] lr: 4.0000e-02 eta: 17:17:01 time: 0.3206 data_time: 0.0205 memory: 5826 grad_norm: 3.0877 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7759 loss: 2.7759 2022/10/07 21:09:42 - mmengine - INFO - Epoch(train) [66][340/2119] lr: 4.0000e-02 eta: 17:16:54 time: 0.3384 data_time: 0.0228 memory: 5826 grad_norm: 3.0935 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7577 loss: 2.7577 2022/10/07 21:09:50 - mmengine - INFO - Epoch(train) [66][360/2119] lr: 4.0000e-02 eta: 17:16:48 time: 0.3694 data_time: 0.0228 memory: 5826 grad_norm: 3.1355 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7428 loss: 2.7428 2022/10/07 21:09:56 - mmengine - INFO - Epoch(train) [66][380/2119] lr: 4.0000e-02 eta: 17:16:41 time: 0.3264 data_time: 0.0222 memory: 5826 grad_norm: 3.1344 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7214 loss: 2.7214 2022/10/07 21:10:03 - mmengine - INFO - Epoch(train) [66][400/2119] lr: 4.0000e-02 eta: 17:16:33 time: 0.3245 data_time: 0.0267 memory: 5826 grad_norm: 3.1762 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8198 loss: 2.8198 2022/10/07 21:10:10 - mmengine - INFO - Epoch(train) [66][420/2119] lr: 4.0000e-02 eta: 17:16:27 time: 0.3621 data_time: 0.0160 memory: 5826 grad_norm: 3.1568 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.3874 loss: 2.3874 2022/10/07 21:10:16 - mmengine - INFO - Epoch(train) [66][440/2119] lr: 4.0000e-02 eta: 17:16:19 time: 0.3175 data_time: 0.0192 memory: 5826 grad_norm: 3.1220 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0774 loss: 3.0774 2022/10/07 21:10:24 - mmengine - INFO - Epoch(train) [66][460/2119] lr: 4.0000e-02 eta: 17:16:12 time: 0.3603 data_time: 0.0229 memory: 5826 grad_norm: 3.0745 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8931 loss: 2.8931 2022/10/07 21:10:30 - mmengine - INFO - Epoch(train) [66][480/2119] lr: 4.0000e-02 eta: 17:16:05 time: 0.3293 data_time: 0.0220 memory: 5826 grad_norm: 3.1578 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6387 loss: 2.6387 2022/10/07 21:10:37 - mmengine - INFO - Epoch(train) [66][500/2119] lr: 4.0000e-02 eta: 17:15:59 time: 0.3668 data_time: 0.0256 memory: 5826 grad_norm: 3.1625 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7473 loss: 2.7473 2022/10/07 21:10:44 - mmengine - INFO - Epoch(train) [66][520/2119] lr: 4.0000e-02 eta: 17:15:52 time: 0.3493 data_time: 0.0245 memory: 5826 grad_norm: 3.0877 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.6691 loss: 2.6691 2022/10/07 21:10:52 - mmengine - INFO - Epoch(train) [66][540/2119] lr: 4.0000e-02 eta: 17:15:46 time: 0.3847 data_time: 0.0150 memory: 5826 grad_norm: 3.0594 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9409 loss: 2.9409 2022/10/07 21:10:59 - mmengine - INFO - Epoch(train) [66][560/2119] lr: 4.0000e-02 eta: 17:15:39 time: 0.3328 data_time: 0.0200 memory: 5826 grad_norm: 3.1259 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7230 loss: 2.7230 2022/10/07 21:11:06 - mmengine - INFO - Epoch(train) [66][580/2119] lr: 4.0000e-02 eta: 17:15:32 time: 0.3714 data_time: 0.0265 memory: 5826 grad_norm: 3.0971 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6134 loss: 2.6134 2022/10/07 21:11:13 - mmengine - INFO - Epoch(train) [66][600/2119] lr: 4.0000e-02 eta: 17:15:25 time: 0.3494 data_time: 0.0206 memory: 5826 grad_norm: 3.1449 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7712 loss: 2.7712 2022/10/07 21:11:21 - mmengine - INFO - Epoch(train) [66][620/2119] lr: 4.0000e-02 eta: 17:15:19 time: 0.3811 data_time: 0.0337 memory: 5826 grad_norm: 3.1461 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6713 loss: 2.6713 2022/10/07 21:11:27 - mmengine - INFO - Epoch(train) [66][640/2119] lr: 4.0000e-02 eta: 17:15:11 time: 0.2970 data_time: 0.0245 memory: 5826 grad_norm: 3.1538 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5246 loss: 2.5246 2022/10/07 21:11:35 - mmengine - INFO - Epoch(train) [66][660/2119] lr: 4.0000e-02 eta: 17:15:07 time: 0.4314 data_time: 0.0201 memory: 5826 grad_norm: 3.1637 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5918 loss: 2.5918 2022/10/07 21:11:42 - mmengine - INFO - Epoch(train) [66][680/2119] lr: 4.0000e-02 eta: 17:14:59 time: 0.3369 data_time: 0.0210 memory: 5826 grad_norm: 3.0676 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7772 loss: 2.7772 2022/10/07 21:11:50 - mmengine - INFO - Epoch(train) [66][700/2119] lr: 4.0000e-02 eta: 17:14:54 time: 0.3889 data_time: 0.0200 memory: 5826 grad_norm: 3.1659 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5594 loss: 2.5594 2022/10/07 21:11:56 - mmengine - INFO - Epoch(train) [66][720/2119] lr: 4.0000e-02 eta: 17:14:46 time: 0.3036 data_time: 0.0214 memory: 5826 grad_norm: 3.1690 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7711 loss: 2.7711 2022/10/07 21:12:03 - mmengine - INFO - Epoch(train) [66][740/2119] lr: 4.0000e-02 eta: 17:14:39 time: 0.3530 data_time: 0.0248 memory: 5826 grad_norm: 3.0837 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7180 loss: 2.7180 2022/10/07 21:12:10 - mmengine - INFO - Epoch(train) [66][760/2119] lr: 4.0000e-02 eta: 17:14:31 time: 0.3218 data_time: 0.0204 memory: 5826 grad_norm: 3.0214 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8216 loss: 2.8216 2022/10/07 21:12:17 - mmengine - INFO - Epoch(train) [66][780/2119] lr: 4.0000e-02 eta: 17:14:24 time: 0.3483 data_time: 0.0216 memory: 5826 grad_norm: 3.1156 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6476 loss: 2.6476 2022/10/07 21:12:23 - mmengine - INFO - Epoch(train) [66][800/2119] lr: 4.0000e-02 eta: 17:14:17 time: 0.3421 data_time: 0.0185 memory: 5826 grad_norm: 3.1092 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7900 loss: 2.7900 2022/10/07 21:12:31 - mmengine - INFO - Epoch(train) [66][820/2119] lr: 4.0000e-02 eta: 17:14:11 time: 0.3728 data_time: 0.0202 memory: 5826 grad_norm: 3.1223 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8109 loss: 2.8109 2022/10/07 21:12:37 - mmengine - INFO - Epoch(train) [66][840/2119] lr: 4.0000e-02 eta: 17:14:04 time: 0.3245 data_time: 0.0235 memory: 5826 grad_norm: 3.0773 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.5856 loss: 2.5856 2022/10/07 21:12:45 - mmengine - INFO - Epoch(train) [66][860/2119] lr: 4.0000e-02 eta: 17:13:57 time: 0.3659 data_time: 0.0190 memory: 5826 grad_norm: 3.1639 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7029 loss: 2.7029 2022/10/07 21:12:52 - mmengine - INFO - Epoch(train) [66][880/2119] lr: 4.0000e-02 eta: 17:13:50 time: 0.3459 data_time: 0.0273 memory: 5826 grad_norm: 3.0942 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8276 loss: 2.8276 2022/10/07 21:12:59 - mmengine - INFO - Epoch(train) [66][900/2119] lr: 4.0000e-02 eta: 17:13:44 time: 0.3747 data_time: 0.0234 memory: 5826 grad_norm: 3.1359 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7834 loss: 2.7834 2022/10/07 21:13:06 - mmengine - INFO - Epoch(train) [66][920/2119] lr: 4.0000e-02 eta: 17:13:37 time: 0.3264 data_time: 0.0251 memory: 5826 grad_norm: 3.1521 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9171 loss: 2.9171 2022/10/07 21:13:12 - mmengine - INFO - Epoch(train) [66][940/2119] lr: 4.0000e-02 eta: 17:13:29 time: 0.3328 data_time: 0.0252 memory: 5826 grad_norm: 3.1159 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9510 loss: 2.9510 2022/10/07 21:13:19 - mmengine - INFO - Epoch(train) [66][960/2119] lr: 4.0000e-02 eta: 17:13:22 time: 0.3283 data_time: 0.0268 memory: 5826 grad_norm: 3.1571 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6404 loss: 2.6404 2022/10/07 21:13:26 - mmengine - INFO - Epoch(train) [66][980/2119] lr: 4.0000e-02 eta: 17:13:16 time: 0.3610 data_time: 0.0230 memory: 5826 grad_norm: 3.1060 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9122 loss: 2.9122 2022/10/07 21:13:33 - mmengine - INFO - Epoch(train) [66][1000/2119] lr: 4.0000e-02 eta: 17:13:09 time: 0.3422 data_time: 0.0268 memory: 5826 grad_norm: 3.1494 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6758 loss: 2.6758 2022/10/07 21:13:41 - mmengine - INFO - Epoch(train) [66][1020/2119] lr: 4.0000e-02 eta: 17:13:03 time: 0.3828 data_time: 0.0238 memory: 5826 grad_norm: 3.1137 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.1035 loss: 3.1035 2022/10/07 21:13:47 - mmengine - INFO - Epoch(train) [66][1040/2119] lr: 4.0000e-02 eta: 17:12:55 time: 0.3334 data_time: 0.0222 memory: 5826 grad_norm: 3.1374 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.8547 loss: 2.8547 2022/10/07 21:13:54 - mmengine - INFO - Epoch(train) [66][1060/2119] lr: 4.0000e-02 eta: 17:12:49 time: 0.3617 data_time: 0.0195 memory: 5826 grad_norm: 3.1723 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7741 loss: 2.7741 2022/10/07 21:14:01 - mmengine - INFO - Epoch(train) [66][1080/2119] lr: 4.0000e-02 eta: 17:12:42 time: 0.3415 data_time: 0.0236 memory: 5826 grad_norm: 3.1288 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9985 loss: 2.9985 2022/10/07 21:14:09 - mmengine - INFO - Epoch(train) [66][1100/2119] lr: 4.0000e-02 eta: 17:12:36 time: 0.3780 data_time: 0.0183 memory: 5826 grad_norm: 3.0711 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4414 loss: 2.4414 2022/10/07 21:14:15 - mmengine - INFO - Epoch(train) [66][1120/2119] lr: 4.0000e-02 eta: 17:12:28 time: 0.3203 data_time: 0.0175 memory: 5826 grad_norm: 3.1524 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7529 loss: 2.7529 2022/10/07 21:14:23 - mmengine - INFO - Epoch(train) [66][1140/2119] lr: 4.0000e-02 eta: 17:12:22 time: 0.3763 data_time: 0.0220 memory: 5826 grad_norm: 3.1634 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7631 loss: 2.7631 2022/10/07 21:14:30 - mmengine - INFO - Epoch(train) [66][1160/2119] lr: 4.0000e-02 eta: 17:12:15 time: 0.3356 data_time: 0.0218 memory: 5826 grad_norm: 3.1288 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6607 loss: 2.6607 2022/10/07 21:14:36 - mmengine - INFO - Epoch(train) [66][1180/2119] lr: 4.0000e-02 eta: 17:12:08 time: 0.3433 data_time: 0.0189 memory: 5826 grad_norm: 3.0670 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7716 loss: 2.7716 2022/10/07 21:14:43 - mmengine - INFO - Epoch(train) [66][1200/2119] lr: 4.0000e-02 eta: 17:12:00 time: 0.3328 data_time: 0.0269 memory: 5826 grad_norm: 3.1316 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6033 loss: 2.6033 2022/10/07 21:14:50 - mmengine - INFO - Epoch(train) [66][1220/2119] lr: 4.0000e-02 eta: 17:11:54 time: 0.3678 data_time: 0.0321 memory: 5826 grad_norm: 3.1547 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7498 loss: 2.7498 2022/10/07 21:14:57 - mmengine - INFO - Epoch(train) [66][1240/2119] lr: 4.0000e-02 eta: 17:11:47 time: 0.3524 data_time: 0.0266 memory: 5826 grad_norm: 3.0709 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8906 loss: 2.8906 2022/10/07 21:15:04 - mmengine - INFO - Epoch(train) [66][1260/2119] lr: 4.0000e-02 eta: 17:11:40 time: 0.3338 data_time: 0.0259 memory: 5826 grad_norm: 3.1352 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6681 loss: 2.6681 2022/10/07 21:15:05 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 21:15:11 - mmengine - INFO - Epoch(train) [66][1280/2119] lr: 4.0000e-02 eta: 17:11:34 time: 0.3599 data_time: 0.0240 memory: 5826 grad_norm: 3.1305 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7518 loss: 2.7518 2022/10/07 21:15:18 - mmengine - INFO - Epoch(train) [66][1300/2119] lr: 4.0000e-02 eta: 17:11:26 time: 0.3336 data_time: 0.0167 memory: 5826 grad_norm: 3.1811 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5882 loss: 2.5882 2022/10/07 21:15:25 - mmengine - INFO - Epoch(train) [66][1320/2119] lr: 4.0000e-02 eta: 17:11:19 time: 0.3236 data_time: 0.0236 memory: 5826 grad_norm: 3.1042 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9075 loss: 2.9075 2022/10/07 21:15:32 - mmengine - INFO - Epoch(train) [66][1340/2119] lr: 4.0000e-02 eta: 17:11:12 time: 0.3562 data_time: 0.0210 memory: 5826 grad_norm: 3.1140 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.0060 loss: 3.0060 2022/10/07 21:15:38 - mmengine - INFO - Epoch(train) [66][1360/2119] lr: 4.0000e-02 eta: 17:11:04 time: 0.2998 data_time: 0.0219 memory: 5826 grad_norm: 3.1506 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9572 loss: 2.9572 2022/10/07 21:15:45 - mmengine - INFO - Epoch(train) [66][1380/2119] lr: 4.0000e-02 eta: 17:10:58 time: 0.3765 data_time: 0.0204 memory: 5826 grad_norm: 3.0934 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8217 loss: 2.8217 2022/10/07 21:15:52 - mmengine - INFO - Epoch(train) [66][1400/2119] lr: 4.0000e-02 eta: 17:10:51 time: 0.3378 data_time: 0.0300 memory: 5826 grad_norm: 3.0734 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6648 loss: 2.6648 2022/10/07 21:15:59 - mmengine - INFO - Epoch(train) [66][1420/2119] lr: 4.0000e-02 eta: 17:10:44 time: 0.3374 data_time: 0.0210 memory: 5826 grad_norm: 3.1205 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5717 loss: 2.5717 2022/10/07 21:16:05 - mmengine - INFO - Epoch(train) [66][1440/2119] lr: 4.0000e-02 eta: 17:10:36 time: 0.3254 data_time: 0.0242 memory: 5826 grad_norm: 3.1573 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7357 loss: 2.7357 2022/10/07 21:16:12 - mmengine - INFO - Epoch(train) [66][1460/2119] lr: 4.0000e-02 eta: 17:10:29 time: 0.3455 data_time: 0.0232 memory: 5826 grad_norm: 3.1229 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.5484 loss: 2.5484 2022/10/07 21:16:19 - mmengine - INFO - Epoch(train) [66][1480/2119] lr: 4.0000e-02 eta: 17:10:22 time: 0.3299 data_time: 0.0284 memory: 5826 grad_norm: 3.1628 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8249 loss: 2.8249 2022/10/07 21:16:26 - mmengine - INFO - Epoch(train) [66][1500/2119] lr: 4.0000e-02 eta: 17:10:16 time: 0.3728 data_time: 0.0180 memory: 5826 grad_norm: 3.1036 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.0016 loss: 3.0016 2022/10/07 21:16:33 - mmengine - INFO - Epoch(train) [66][1520/2119] lr: 4.0000e-02 eta: 17:10:08 time: 0.3300 data_time: 0.0265 memory: 5826 grad_norm: 3.0911 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7431 loss: 2.7431 2022/10/07 21:16:41 - mmengine - INFO - Epoch(train) [66][1540/2119] lr: 4.0000e-02 eta: 17:10:02 time: 0.3884 data_time: 0.0214 memory: 5826 grad_norm: 3.0878 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7701 loss: 2.7701 2022/10/07 21:16:48 - mmengine - INFO - Epoch(train) [66][1560/2119] lr: 4.0000e-02 eta: 17:09:56 time: 0.3771 data_time: 0.0239 memory: 5826 grad_norm: 3.1460 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5898 loss: 2.5898 2022/10/07 21:16:55 - mmengine - INFO - Epoch(train) [66][1580/2119] lr: 4.0000e-02 eta: 17:09:50 time: 0.3541 data_time: 0.0197 memory: 5826 grad_norm: 3.1186 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6863 loss: 2.6863 2022/10/07 21:17:01 - mmengine - INFO - Epoch(train) [66][1600/2119] lr: 4.0000e-02 eta: 17:09:41 time: 0.2983 data_time: 0.0231 memory: 5826 grad_norm: 3.0265 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9042 loss: 2.9042 2022/10/07 21:17:08 - mmengine - INFO - Epoch(train) [66][1620/2119] lr: 4.0000e-02 eta: 17:09:35 time: 0.3589 data_time: 0.0248 memory: 5826 grad_norm: 3.1306 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6333 loss: 2.6333 2022/10/07 21:17:16 - mmengine - INFO - Epoch(train) [66][1640/2119] lr: 4.0000e-02 eta: 17:09:28 time: 0.3589 data_time: 0.0235 memory: 5826 grad_norm: 3.1533 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6043 loss: 2.6043 2022/10/07 21:17:23 - mmengine - INFO - Epoch(train) [66][1660/2119] lr: 4.0000e-02 eta: 17:09:22 time: 0.3526 data_time: 0.0228 memory: 5826 grad_norm: 3.1411 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7566 loss: 2.7566 2022/10/07 21:17:29 - mmengine - INFO - Epoch(train) [66][1680/2119] lr: 4.0000e-02 eta: 17:09:14 time: 0.3318 data_time: 0.0272 memory: 5826 grad_norm: 3.0926 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7247 loss: 2.7247 2022/10/07 21:17:37 - mmengine - INFO - Epoch(train) [66][1700/2119] lr: 4.0000e-02 eta: 17:09:08 time: 0.3716 data_time: 0.0201 memory: 5826 grad_norm: 3.0788 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8117 loss: 2.8117 2022/10/07 21:17:44 - mmengine - INFO - Epoch(train) [66][1720/2119] lr: 4.0000e-02 eta: 17:09:01 time: 0.3426 data_time: 0.0279 memory: 5826 grad_norm: 3.1935 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7843 loss: 2.7843 2022/10/07 21:17:50 - mmengine - INFO - Epoch(train) [66][1740/2119] lr: 4.0000e-02 eta: 17:08:54 time: 0.3393 data_time: 0.0226 memory: 5826 grad_norm: 3.0246 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7160 loss: 2.7160 2022/10/07 21:17:57 - mmengine - INFO - Epoch(train) [66][1760/2119] lr: 4.0000e-02 eta: 17:08:46 time: 0.3173 data_time: 0.0258 memory: 5826 grad_norm: 3.1271 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9221 loss: 2.9221 2022/10/07 21:18:04 - mmengine - INFO - Epoch(train) [66][1780/2119] lr: 4.0000e-02 eta: 17:08:40 time: 0.3771 data_time: 0.0236 memory: 5826 grad_norm: 3.0581 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7340 loss: 2.7340 2022/10/07 21:18:11 - mmengine - INFO - Epoch(train) [66][1800/2119] lr: 4.0000e-02 eta: 17:08:32 time: 0.3173 data_time: 0.0185 memory: 5826 grad_norm: 3.1066 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7431 loss: 2.7431 2022/10/07 21:18:18 - mmengine - INFO - Epoch(train) [66][1820/2119] lr: 4.0000e-02 eta: 17:08:26 time: 0.3541 data_time: 0.0253 memory: 5826 grad_norm: 3.1716 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6851 loss: 2.6851 2022/10/07 21:18:24 - mmengine - INFO - Epoch(train) [66][1840/2119] lr: 4.0000e-02 eta: 17:08:19 time: 0.3367 data_time: 0.0235 memory: 5826 grad_norm: 3.1487 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7803 loss: 2.7803 2022/10/07 21:18:31 - mmengine - INFO - Epoch(train) [66][1860/2119] lr: 4.0000e-02 eta: 17:08:12 time: 0.3497 data_time: 0.0211 memory: 5826 grad_norm: 3.1251 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8785 loss: 2.8785 2022/10/07 21:18:38 - mmengine - INFO - Epoch(train) [66][1880/2119] lr: 4.0000e-02 eta: 17:08:05 time: 0.3376 data_time: 0.0234 memory: 5826 grad_norm: 3.1372 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7452 loss: 2.7452 2022/10/07 21:18:46 - mmengine - INFO - Epoch(train) [66][1900/2119] lr: 4.0000e-02 eta: 17:07:59 time: 0.3824 data_time: 0.0229 memory: 5826 grad_norm: 3.1141 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7297 loss: 2.7297 2022/10/07 21:18:53 - mmengine - INFO - Epoch(train) [66][1920/2119] lr: 4.0000e-02 eta: 17:07:52 time: 0.3522 data_time: 0.0235 memory: 5826 grad_norm: 3.0823 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6959 loss: 2.6959 2022/10/07 21:19:01 - mmengine - INFO - Epoch(train) [66][1940/2119] lr: 4.0000e-02 eta: 17:07:46 time: 0.4002 data_time: 0.0242 memory: 5826 grad_norm: 3.1236 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.9006 loss: 2.9006 2022/10/07 21:19:07 - mmengine - INFO - Epoch(train) [66][1960/2119] lr: 4.0000e-02 eta: 17:07:38 time: 0.2960 data_time: 0.0295 memory: 5826 grad_norm: 3.1154 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.0630 loss: 3.0630 2022/10/07 21:19:14 - mmengine - INFO - Epoch(train) [66][1980/2119] lr: 4.0000e-02 eta: 17:07:31 time: 0.3507 data_time: 0.0255 memory: 5826 grad_norm: 3.0879 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 2.6899 loss: 2.6899 2022/10/07 21:19:20 - mmengine - INFO - Epoch(train) [66][2000/2119] lr: 4.0000e-02 eta: 17:07:23 time: 0.3081 data_time: 0.0220 memory: 5826 grad_norm: 3.1425 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6466 loss: 2.6466 2022/10/07 21:19:29 - mmengine - INFO - Epoch(train) [66][2020/2119] lr: 4.0000e-02 eta: 17:07:19 time: 0.4261 data_time: 0.0216 memory: 5826 grad_norm: 3.0881 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6068 loss: 2.6068 2022/10/07 21:19:35 - mmengine - INFO - Epoch(train) [66][2040/2119] lr: 4.0000e-02 eta: 17:07:11 time: 0.3102 data_time: 0.0243 memory: 5826 grad_norm: 3.1398 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7096 loss: 2.7096 2022/10/07 21:19:42 - mmengine - INFO - Epoch(train) [66][2060/2119] lr: 4.0000e-02 eta: 17:07:04 time: 0.3555 data_time: 0.0209 memory: 5826 grad_norm: 3.0960 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7061 loss: 2.7061 2022/10/07 21:19:49 - mmengine - INFO - Epoch(train) [66][2080/2119] lr: 4.0000e-02 eta: 17:06:57 time: 0.3533 data_time: 0.0261 memory: 5826 grad_norm: 3.0916 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6702 loss: 2.6702 2022/10/07 21:19:56 - mmengine - INFO - Epoch(train) [66][2100/2119] lr: 4.0000e-02 eta: 17:06:51 time: 0.3641 data_time: 0.0264 memory: 5826 grad_norm: 3.1161 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7027 loss: 2.7027 2022/10/07 21:20:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 21:20:02 - mmengine - INFO - Epoch(train) [66][2119/2119] lr: 4.0000e-02 eta: 17:06:51 time: 0.2777 data_time: 0.0157 memory: 5826 grad_norm: 3.1448 top1_acc: 0.2000 top5_acc: 0.6000 loss_cls: 2.9185 loss: 2.9185 2022/10/07 21:20:11 - mmengine - INFO - Epoch(train) [67][20/2119] lr: 4.0000e-02 eta: 17:06:32 time: 0.4614 data_time: 0.1171 memory: 5826 grad_norm: 3.1194 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7807 loss: 2.7807 2022/10/07 21:20:17 - mmengine - INFO - Epoch(train) [67][40/2119] lr: 4.0000e-02 eta: 17:06:25 time: 0.3306 data_time: 0.0230 memory: 5826 grad_norm: 3.1325 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5426 loss: 2.5426 2022/10/07 21:20:25 - mmengine - INFO - Epoch(train) [67][60/2119] lr: 4.0000e-02 eta: 17:06:19 time: 0.4023 data_time: 0.0187 memory: 5826 grad_norm: 3.1147 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7844 loss: 2.7844 2022/10/07 21:20:32 - mmengine - INFO - Epoch(train) [67][80/2119] lr: 4.0000e-02 eta: 17:06:12 time: 0.3249 data_time: 0.0257 memory: 5826 grad_norm: 3.0998 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.4983 loss: 2.4983 2022/10/07 21:20:40 - mmengine - INFO - Epoch(train) [67][100/2119] lr: 4.0000e-02 eta: 17:06:06 time: 0.3930 data_time: 0.0181 memory: 5826 grad_norm: 3.1069 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7299 loss: 2.7299 2022/10/07 21:20:46 - mmengine - INFO - Epoch(train) [67][120/2119] lr: 4.0000e-02 eta: 17:05:58 time: 0.3080 data_time: 0.0283 memory: 5826 grad_norm: 3.1343 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8347 loss: 2.8347 2022/10/07 21:20:54 - mmengine - INFO - Epoch(train) [67][140/2119] lr: 4.0000e-02 eta: 17:05:52 time: 0.3901 data_time: 0.0234 memory: 5826 grad_norm: 3.1217 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7895 loss: 2.7895 2022/10/07 21:20:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 21:21:00 - mmengine - INFO - Epoch(train) [67][160/2119] lr: 4.0000e-02 eta: 17:05:45 time: 0.3274 data_time: 0.0215 memory: 5826 grad_norm: 3.1005 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6788 loss: 2.6788 2022/10/07 21:21:06 - mmengine - INFO - Epoch(train) [67][180/2119] lr: 4.0000e-02 eta: 17:05:37 time: 0.3046 data_time: 0.0267 memory: 5826 grad_norm: 3.0949 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5871 loss: 2.5871 2022/10/07 21:21:13 - mmengine - INFO - Epoch(train) [67][200/2119] lr: 4.0000e-02 eta: 17:05:30 time: 0.3413 data_time: 0.0215 memory: 5826 grad_norm: 3.1634 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5770 loss: 2.5770 2022/10/07 21:21:21 - mmengine - INFO - Epoch(train) [67][220/2119] lr: 4.0000e-02 eta: 17:05:24 time: 0.4017 data_time: 0.0187 memory: 5826 grad_norm: 3.1340 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5197 loss: 2.5197 2022/10/07 21:21:28 - mmengine - INFO - Epoch(train) [67][240/2119] lr: 4.0000e-02 eta: 17:05:17 time: 0.3454 data_time: 0.0181 memory: 5826 grad_norm: 3.1539 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9622 loss: 2.9622 2022/10/07 21:21:35 - mmengine - INFO - Epoch(train) [67][260/2119] lr: 4.0000e-02 eta: 17:05:10 time: 0.3488 data_time: 0.0254 memory: 5826 grad_norm: 3.1374 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6463 loss: 2.6463 2022/10/07 21:21:42 - mmengine - INFO - Epoch(train) [67][280/2119] lr: 4.0000e-02 eta: 17:05:03 time: 0.3194 data_time: 0.0219 memory: 5826 grad_norm: 3.1301 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8139 loss: 2.8139 2022/10/07 21:21:49 - mmengine - INFO - Epoch(train) [67][300/2119] lr: 4.0000e-02 eta: 17:04:57 time: 0.3726 data_time: 0.0183 memory: 5826 grad_norm: 3.0335 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.3729 loss: 2.3729 2022/10/07 21:21:55 - mmengine - INFO - Epoch(train) [67][320/2119] lr: 4.0000e-02 eta: 17:04:49 time: 0.3184 data_time: 0.0244 memory: 5826 grad_norm: 3.0922 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6848 loss: 2.6848 2022/10/07 21:22:03 - mmengine - INFO - Epoch(train) [67][340/2119] lr: 4.0000e-02 eta: 17:04:43 time: 0.3744 data_time: 0.0227 memory: 5826 grad_norm: 3.1162 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9439 loss: 2.9439 2022/10/07 21:22:09 - mmengine - INFO - Epoch(train) [67][360/2119] lr: 4.0000e-02 eta: 17:04:35 time: 0.3143 data_time: 0.0263 memory: 5826 grad_norm: 3.1357 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7373 loss: 2.7373 2022/10/07 21:22:18 - mmengine - INFO - Epoch(train) [67][380/2119] lr: 4.0000e-02 eta: 17:04:30 time: 0.4219 data_time: 0.0202 memory: 5826 grad_norm: 3.1084 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9022 loss: 2.9022 2022/10/07 21:22:25 - mmengine - INFO - Epoch(train) [67][400/2119] lr: 4.0000e-02 eta: 17:04:23 time: 0.3513 data_time: 0.0277 memory: 5826 grad_norm: 3.1533 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7134 loss: 2.7134 2022/10/07 21:22:32 - mmengine - INFO - Epoch(train) [67][420/2119] lr: 4.0000e-02 eta: 17:04:17 time: 0.3836 data_time: 0.0173 memory: 5826 grad_norm: 3.1485 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7828 loss: 2.7828 2022/10/07 21:22:39 - mmengine - INFO - Epoch(train) [67][440/2119] lr: 4.0000e-02 eta: 17:04:11 time: 0.3542 data_time: 0.0244 memory: 5826 grad_norm: 3.1289 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7247 loss: 2.7247 2022/10/07 21:22:48 - mmengine - INFO - Epoch(train) [67][460/2119] lr: 4.0000e-02 eta: 17:04:05 time: 0.4047 data_time: 0.0182 memory: 5826 grad_norm: 3.1684 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6523 loss: 2.6523 2022/10/07 21:22:54 - mmengine - INFO - Epoch(train) [67][480/2119] lr: 4.0000e-02 eta: 17:03:58 time: 0.3225 data_time: 0.0227 memory: 5826 grad_norm: 3.1675 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5214 loss: 2.5214 2022/10/07 21:23:01 - mmengine - INFO - Epoch(train) [67][500/2119] lr: 4.0000e-02 eta: 17:03:51 time: 0.3728 data_time: 0.0196 memory: 5826 grad_norm: 3.1492 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9168 loss: 2.9168 2022/10/07 21:23:08 - mmengine - INFO - Epoch(train) [67][520/2119] lr: 4.0000e-02 eta: 17:03:45 time: 0.3496 data_time: 0.0217 memory: 5826 grad_norm: 3.1419 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6909 loss: 2.6909 2022/10/07 21:23:15 - mmengine - INFO - Epoch(train) [67][540/2119] lr: 4.0000e-02 eta: 17:03:38 time: 0.3465 data_time: 0.0224 memory: 5826 grad_norm: 3.1543 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8470 loss: 2.8470 2022/10/07 21:23:22 - mmengine - INFO - Epoch(train) [67][560/2119] lr: 4.0000e-02 eta: 17:03:31 time: 0.3419 data_time: 0.0313 memory: 5826 grad_norm: 3.1412 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7650 loss: 2.7650 2022/10/07 21:23:30 - mmengine - INFO - Epoch(train) [67][580/2119] lr: 4.0000e-02 eta: 17:03:24 time: 0.3723 data_time: 0.0214 memory: 5826 grad_norm: 3.1522 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8379 loss: 2.8379 2022/10/07 21:23:35 - mmengine - INFO - Epoch(train) [67][600/2119] lr: 4.0000e-02 eta: 17:03:15 time: 0.2690 data_time: 0.0266 memory: 5826 grad_norm: 3.0736 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4949 loss: 2.4949 2022/10/07 21:23:42 - mmengine - INFO - Epoch(train) [67][620/2119] lr: 4.0000e-02 eta: 17:03:09 time: 0.3624 data_time: 0.0176 memory: 5826 grad_norm: 3.1362 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6438 loss: 2.6438 2022/10/07 21:23:49 - mmengine - INFO - Epoch(train) [67][640/2119] lr: 4.0000e-02 eta: 17:03:02 time: 0.3476 data_time: 0.0260 memory: 5826 grad_norm: 3.1597 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9275 loss: 2.9275 2022/10/07 21:23:57 - mmengine - INFO - Epoch(train) [67][660/2119] lr: 4.0000e-02 eta: 17:02:56 time: 0.3652 data_time: 0.0160 memory: 5826 grad_norm: 3.1413 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9073 loss: 2.9073 2022/10/07 21:24:03 - mmengine - INFO - Epoch(train) [67][680/2119] lr: 4.0000e-02 eta: 17:02:48 time: 0.3286 data_time: 0.0272 memory: 5826 grad_norm: 3.1728 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8748 loss: 2.8748 2022/10/07 21:24:10 - mmengine - INFO - Epoch(train) [67][700/2119] lr: 4.0000e-02 eta: 17:02:42 time: 0.3583 data_time: 0.0162 memory: 5826 grad_norm: 3.0794 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.9838 loss: 2.9838 2022/10/07 21:24:17 - mmengine - INFO - Epoch(train) [67][720/2119] lr: 4.0000e-02 eta: 17:02:34 time: 0.3344 data_time: 0.0180 memory: 5826 grad_norm: 3.1493 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6048 loss: 2.6048 2022/10/07 21:24:25 - mmengine - INFO - Epoch(train) [67][740/2119] lr: 4.0000e-02 eta: 17:02:29 time: 0.4069 data_time: 0.0247 memory: 5826 grad_norm: 3.1212 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5654 loss: 2.5654 2022/10/07 21:24:31 - mmengine - INFO - Epoch(train) [67][760/2119] lr: 4.0000e-02 eta: 17:02:21 time: 0.3001 data_time: 0.0195 memory: 5826 grad_norm: 3.1663 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6014 loss: 2.6014 2022/10/07 21:24:38 - mmengine - INFO - Epoch(train) [67][780/2119] lr: 4.0000e-02 eta: 17:02:14 time: 0.3290 data_time: 0.0238 memory: 5826 grad_norm: 3.1300 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6547 loss: 2.6547 2022/10/07 21:24:45 - mmengine - INFO - Epoch(train) [67][800/2119] lr: 4.0000e-02 eta: 17:02:07 time: 0.3679 data_time: 0.0237 memory: 5826 grad_norm: 3.0655 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5748 loss: 2.5748 2022/10/07 21:24:53 - mmengine - INFO - Epoch(train) [67][820/2119] lr: 4.0000e-02 eta: 17:02:02 time: 0.3958 data_time: 0.0252 memory: 5826 grad_norm: 3.1063 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8512 loss: 2.8512 2022/10/07 21:25:00 - mmengine - INFO - Epoch(train) [67][840/2119] lr: 4.0000e-02 eta: 17:01:54 time: 0.3334 data_time: 0.0205 memory: 5826 grad_norm: 3.1270 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7341 loss: 2.7341 2022/10/07 21:25:06 - mmengine - INFO - Epoch(train) [67][860/2119] lr: 4.0000e-02 eta: 17:01:47 time: 0.3213 data_time: 0.0219 memory: 5826 grad_norm: 3.1016 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6784 loss: 2.6784 2022/10/07 21:25:13 - mmengine - INFO - Epoch(train) [67][880/2119] lr: 4.0000e-02 eta: 17:01:40 time: 0.3330 data_time: 0.0269 memory: 5826 grad_norm: 3.0694 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7552 loss: 2.7552 2022/10/07 21:25:20 - mmengine - INFO - Epoch(train) [67][900/2119] lr: 4.0000e-02 eta: 17:01:33 time: 0.3417 data_time: 0.0243 memory: 5826 grad_norm: 3.0950 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7363 loss: 2.7363 2022/10/07 21:25:27 - mmengine - INFO - Epoch(train) [67][920/2119] lr: 4.0000e-02 eta: 17:01:26 time: 0.3640 data_time: 0.0172 memory: 5826 grad_norm: 3.0561 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5334 loss: 2.5334 2022/10/07 21:25:34 - mmengine - INFO - Epoch(train) [67][940/2119] lr: 4.0000e-02 eta: 17:01:19 time: 0.3339 data_time: 0.0263 memory: 5826 grad_norm: 3.0688 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6072 loss: 2.6072 2022/10/07 21:25:40 - mmengine - INFO - Epoch(train) [67][960/2119] lr: 4.0000e-02 eta: 17:01:12 time: 0.3341 data_time: 0.0205 memory: 5826 grad_norm: 3.0624 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6540 loss: 2.6540 2022/10/07 21:25:47 - mmengine - INFO - Epoch(train) [67][980/2119] lr: 4.0000e-02 eta: 17:01:05 time: 0.3570 data_time: 0.0210 memory: 5826 grad_norm: 3.0466 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8769 loss: 2.8769 2022/10/07 21:25:55 - mmengine - INFO - Epoch(train) [67][1000/2119] lr: 4.0000e-02 eta: 17:00:59 time: 0.3794 data_time: 0.0298 memory: 5826 grad_norm: 3.1219 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6189 loss: 2.6189 2022/10/07 21:26:02 - mmengine - INFO - Epoch(train) [67][1020/2119] lr: 4.0000e-02 eta: 17:00:52 time: 0.3332 data_time: 0.0215 memory: 5826 grad_norm: 3.0972 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.8990 loss: 2.8990 2022/10/07 21:26:09 - mmengine - INFO - Epoch(train) [67][1040/2119] lr: 4.0000e-02 eta: 17:00:45 time: 0.3613 data_time: 0.0201 memory: 5826 grad_norm: 3.1200 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7673 loss: 2.7673 2022/10/07 21:26:15 - mmengine - INFO - Epoch(train) [67][1060/2119] lr: 4.0000e-02 eta: 17:00:37 time: 0.3122 data_time: 0.0222 memory: 5826 grad_norm: 3.1346 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6803 loss: 2.6803 2022/10/07 21:26:22 - mmengine - INFO - Epoch(train) [67][1080/2119] lr: 4.0000e-02 eta: 17:00:30 time: 0.3487 data_time: 0.0228 memory: 5826 grad_norm: 3.1808 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8333 loss: 2.8333 2022/10/07 21:26:30 - mmengine - INFO - Epoch(train) [67][1100/2119] lr: 4.0000e-02 eta: 17:00:25 time: 0.3889 data_time: 0.0164 memory: 5826 grad_norm: 3.1231 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6695 loss: 2.6695 2022/10/07 21:26:37 - mmengine - INFO - Epoch(train) [67][1120/2119] lr: 4.0000e-02 eta: 17:00:18 time: 0.3467 data_time: 0.0227 memory: 5826 grad_norm: 3.0507 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7403 loss: 2.7403 2022/10/07 21:26:44 - mmengine - INFO - Epoch(train) [67][1140/2119] lr: 4.0000e-02 eta: 17:00:11 time: 0.3732 data_time: 0.0318 memory: 5826 grad_norm: 3.1118 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7541 loss: 2.7541 2022/10/07 21:26:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 21:26:51 - mmengine - INFO - Epoch(train) [67][1160/2119] lr: 4.0000e-02 eta: 17:00:04 time: 0.3296 data_time: 0.0216 memory: 5826 grad_norm: 3.1229 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1322 loss: 3.1322 2022/10/07 21:26:58 - mmengine - INFO - Epoch(train) [67][1180/2119] lr: 4.0000e-02 eta: 16:59:57 time: 0.3339 data_time: 0.0231 memory: 5826 grad_norm: 3.0597 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6175 loss: 2.6175 2022/10/07 21:27:05 - mmengine - INFO - Epoch(train) [67][1200/2119] lr: 4.0000e-02 eta: 16:59:50 time: 0.3453 data_time: 0.0218 memory: 5826 grad_norm: 3.0886 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.5776 loss: 2.5776 2022/10/07 21:27:12 - mmengine - INFO - Epoch(train) [67][1220/2119] lr: 4.0000e-02 eta: 16:59:43 time: 0.3603 data_time: 0.0293 memory: 5826 grad_norm: 3.0987 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4811 loss: 2.4811 2022/10/07 21:27:18 - mmengine - INFO - Epoch(train) [67][1240/2119] lr: 4.0000e-02 eta: 16:59:35 time: 0.2936 data_time: 0.0276 memory: 5826 grad_norm: 3.1332 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5943 loss: 2.5943 2022/10/07 21:27:25 - mmengine - INFO - Epoch(train) [67][1260/2119] lr: 4.0000e-02 eta: 16:59:29 time: 0.3747 data_time: 0.0204 memory: 5826 grad_norm: 3.1024 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6494 loss: 2.6494 2022/10/07 21:27:32 - mmengine - INFO - Epoch(train) [67][1280/2119] lr: 4.0000e-02 eta: 16:59:22 time: 0.3503 data_time: 0.0264 memory: 5826 grad_norm: 3.1159 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.9081 loss: 2.9081 2022/10/07 21:27:39 - mmengine - INFO - Epoch(train) [67][1300/2119] lr: 4.0000e-02 eta: 16:59:15 time: 0.3537 data_time: 0.0208 memory: 5826 grad_norm: 3.1307 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6230 loss: 2.6230 2022/10/07 21:27:46 - mmengine - INFO - Epoch(train) [67][1320/2119] lr: 4.0000e-02 eta: 16:59:08 time: 0.3367 data_time: 0.0234 memory: 5826 grad_norm: 3.1514 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8151 loss: 2.8151 2022/10/07 21:27:53 - mmengine - INFO - Epoch(train) [67][1340/2119] lr: 4.0000e-02 eta: 16:59:01 time: 0.3392 data_time: 0.0213 memory: 5826 grad_norm: 3.1547 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6656 loss: 2.6656 2022/10/07 21:28:00 - mmengine - INFO - Epoch(train) [67][1360/2119] lr: 4.0000e-02 eta: 16:58:54 time: 0.3556 data_time: 0.0224 memory: 5826 grad_norm: 3.1720 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8228 loss: 2.8228 2022/10/07 21:28:06 - mmengine - INFO - Epoch(train) [67][1380/2119] lr: 4.0000e-02 eta: 16:58:47 time: 0.3190 data_time: 0.0199 memory: 5826 grad_norm: 3.1259 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8814 loss: 2.8814 2022/10/07 21:28:14 - mmengine - INFO - Epoch(train) [67][1400/2119] lr: 4.0000e-02 eta: 16:58:41 time: 0.3734 data_time: 0.0228 memory: 5826 grad_norm: 3.1050 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8070 loss: 2.8070 2022/10/07 21:28:20 - mmengine - INFO - Epoch(train) [67][1420/2119] lr: 4.0000e-02 eta: 16:58:33 time: 0.3160 data_time: 0.0187 memory: 5826 grad_norm: 3.1232 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8404 loss: 2.8404 2022/10/07 21:28:27 - mmengine - INFO - Epoch(train) [67][1440/2119] lr: 4.0000e-02 eta: 16:58:26 time: 0.3601 data_time: 0.0268 memory: 5826 grad_norm: 3.1061 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6804 loss: 2.6804 2022/10/07 21:28:34 - mmengine - INFO - Epoch(train) [67][1460/2119] lr: 4.0000e-02 eta: 16:58:19 time: 0.3134 data_time: 0.0186 memory: 5826 grad_norm: 3.1719 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8566 loss: 2.8566 2022/10/07 21:28:41 - mmengine - INFO - Epoch(train) [67][1480/2119] lr: 4.0000e-02 eta: 16:58:13 time: 0.3984 data_time: 0.0219 memory: 5826 grad_norm: 3.1294 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6672 loss: 2.6672 2022/10/07 21:28:48 - mmengine - INFO - Epoch(train) [67][1500/2119] lr: 4.0000e-02 eta: 16:58:06 time: 0.3235 data_time: 0.0229 memory: 5826 grad_norm: 3.1474 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8217 loss: 2.8217 2022/10/07 21:28:56 - mmengine - INFO - Epoch(train) [67][1520/2119] lr: 4.0000e-02 eta: 16:57:59 time: 0.3804 data_time: 0.0342 memory: 5826 grad_norm: 3.0892 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5493 loss: 2.5493 2022/10/07 21:29:02 - mmengine - INFO - Epoch(train) [67][1540/2119] lr: 4.0000e-02 eta: 16:57:52 time: 0.3120 data_time: 0.0196 memory: 5826 grad_norm: 3.0555 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5637 loss: 2.5637 2022/10/07 21:29:08 - mmengine - INFO - Epoch(train) [67][1560/2119] lr: 4.0000e-02 eta: 16:57:44 time: 0.3221 data_time: 0.0295 memory: 5826 grad_norm: 3.1722 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0395 loss: 3.0395 2022/10/07 21:29:15 - mmengine - INFO - Epoch(train) [67][1580/2119] lr: 4.0000e-02 eta: 16:57:37 time: 0.3229 data_time: 0.0180 memory: 5826 grad_norm: 3.1699 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6026 loss: 2.6026 2022/10/07 21:29:22 - mmengine - INFO - Epoch(train) [67][1600/2119] lr: 4.0000e-02 eta: 16:57:30 time: 0.3747 data_time: 0.0283 memory: 5826 grad_norm: 3.1151 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6500 loss: 2.6500 2022/10/07 21:29:29 - mmengine - INFO - Epoch(train) [67][1620/2119] lr: 4.0000e-02 eta: 16:57:23 time: 0.3302 data_time: 0.0199 memory: 5826 grad_norm: 3.1086 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8828 loss: 2.8828 2022/10/07 21:29:37 - mmengine - INFO - Epoch(train) [67][1640/2119] lr: 4.0000e-02 eta: 16:57:17 time: 0.3833 data_time: 0.0216 memory: 5826 grad_norm: 3.1940 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.7969 loss: 2.7969 2022/10/07 21:29:45 - mmengine - INFO - Epoch(train) [67][1660/2119] lr: 4.0000e-02 eta: 16:57:12 time: 0.4238 data_time: 0.0205 memory: 5826 grad_norm: 3.1105 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7368 loss: 2.7368 2022/10/07 21:29:51 - mmengine - INFO - Epoch(train) [67][1680/2119] lr: 4.0000e-02 eta: 16:57:04 time: 0.3016 data_time: 0.0242 memory: 5826 grad_norm: 3.1380 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0137 loss: 3.0137 2022/10/07 21:29:59 - mmengine - INFO - Epoch(train) [67][1700/2119] lr: 4.0000e-02 eta: 16:56:58 time: 0.3802 data_time: 0.0260 memory: 5826 grad_norm: 3.1838 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9156 loss: 2.9156 2022/10/07 21:30:05 - mmengine - INFO - Epoch(train) [67][1720/2119] lr: 4.0000e-02 eta: 16:56:51 time: 0.3257 data_time: 0.0315 memory: 5826 grad_norm: 3.1029 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6455 loss: 2.6455 2022/10/07 21:30:12 - mmengine - INFO - Epoch(train) [67][1740/2119] lr: 4.0000e-02 eta: 16:56:44 time: 0.3390 data_time: 0.0224 memory: 5826 grad_norm: 3.0681 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5592 loss: 2.5592 2022/10/07 21:30:18 - mmengine - INFO - Epoch(train) [67][1760/2119] lr: 4.0000e-02 eta: 16:56:36 time: 0.3052 data_time: 0.0254 memory: 5826 grad_norm: 3.1574 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5404 loss: 2.5404 2022/10/07 21:30:26 - mmengine - INFO - Epoch(train) [67][1780/2119] lr: 4.0000e-02 eta: 16:56:30 time: 0.4031 data_time: 0.0215 memory: 5826 grad_norm: 3.0932 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 3.0518 loss: 3.0518 2022/10/07 21:30:33 - mmengine - INFO - Epoch(train) [67][1800/2119] lr: 4.0000e-02 eta: 16:56:23 time: 0.3337 data_time: 0.0226 memory: 5826 grad_norm: 3.1270 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7048 loss: 2.7048 2022/10/07 21:30:41 - mmengine - INFO - Epoch(train) [67][1820/2119] lr: 4.0000e-02 eta: 16:56:17 time: 0.3928 data_time: 0.0226 memory: 5826 grad_norm: 3.1246 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6167 loss: 2.6167 2022/10/07 21:30:47 - mmengine - INFO - Epoch(train) [67][1840/2119] lr: 4.0000e-02 eta: 16:56:09 time: 0.3046 data_time: 0.0227 memory: 5826 grad_norm: 3.0727 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7133 loss: 2.7133 2022/10/07 21:30:54 - mmengine - INFO - Epoch(train) [67][1860/2119] lr: 4.0000e-02 eta: 16:56:02 time: 0.3395 data_time: 0.0229 memory: 5826 grad_norm: 3.1149 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6231 loss: 2.6231 2022/10/07 21:31:00 - mmengine - INFO - Epoch(train) [67][1880/2119] lr: 4.0000e-02 eta: 16:55:54 time: 0.3169 data_time: 0.0240 memory: 5826 grad_norm: 3.1319 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6370 loss: 2.6370 2022/10/07 21:31:07 - mmengine - INFO - Epoch(train) [67][1900/2119] lr: 4.0000e-02 eta: 16:55:48 time: 0.3505 data_time: 0.0190 memory: 5826 grad_norm: 3.1389 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6488 loss: 2.6488 2022/10/07 21:31:13 - mmengine - INFO - Epoch(train) [67][1920/2119] lr: 4.0000e-02 eta: 16:55:40 time: 0.3173 data_time: 0.0275 memory: 5826 grad_norm: 3.1342 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6469 loss: 2.6469 2022/10/07 21:31:21 - mmengine - INFO - Epoch(train) [67][1940/2119] lr: 4.0000e-02 eta: 16:55:35 time: 0.4110 data_time: 0.0204 memory: 5826 grad_norm: 3.1059 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7245 loss: 2.7245 2022/10/07 21:31:28 - mmengine - INFO - Epoch(train) [67][1960/2119] lr: 4.0000e-02 eta: 16:55:27 time: 0.3235 data_time: 0.0247 memory: 5826 grad_norm: 3.1359 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7641 loss: 2.7641 2022/10/07 21:31:35 - mmengine - INFO - Epoch(train) [67][1980/2119] lr: 4.0000e-02 eta: 16:55:21 time: 0.3665 data_time: 0.0219 memory: 5826 grad_norm: 3.0882 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6813 loss: 2.6813 2022/10/07 21:31:42 - mmengine - INFO - Epoch(train) [67][2000/2119] lr: 4.0000e-02 eta: 16:55:13 time: 0.3115 data_time: 0.0232 memory: 5826 grad_norm: 3.1137 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8516 loss: 2.8516 2022/10/07 21:31:49 - mmengine - INFO - Epoch(train) [67][2020/2119] lr: 4.0000e-02 eta: 16:55:07 time: 0.3742 data_time: 0.0199 memory: 5826 grad_norm: 3.1593 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7897 loss: 2.7897 2022/10/07 21:31:55 - mmengine - INFO - Epoch(train) [67][2040/2119] lr: 4.0000e-02 eta: 16:54:59 time: 0.3162 data_time: 0.0248 memory: 5826 grad_norm: 3.1336 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6546 loss: 2.6546 2022/10/07 21:32:02 - mmengine - INFO - Epoch(train) [67][2060/2119] lr: 4.0000e-02 eta: 16:54:52 time: 0.3344 data_time: 0.0311 memory: 5826 grad_norm: 3.0678 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7045 loss: 2.7045 2022/10/07 21:32:08 - mmengine - INFO - Epoch(train) [67][2080/2119] lr: 4.0000e-02 eta: 16:54:44 time: 0.3053 data_time: 0.0275 memory: 5826 grad_norm: 3.1460 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5744 loss: 2.5744 2022/10/07 21:32:15 - mmengine - INFO - Epoch(train) [67][2100/2119] lr: 4.0000e-02 eta: 16:54:37 time: 0.3618 data_time: 0.0212 memory: 5826 grad_norm: 3.1543 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8465 loss: 2.8465 2022/10/07 21:32:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 21:32:22 - mmengine - INFO - Epoch(train) [67][2119/2119] lr: 4.0000e-02 eta: 16:54:37 time: 0.3272 data_time: 0.0217 memory: 5826 grad_norm: 3.1267 top1_acc: 0.5000 top5_acc: 0.6000 loss_cls: 2.8407 loss: 2.8407 2022/10/07 21:32:32 - mmengine - INFO - Epoch(train) [68][20/2119] lr: 4.0000e-02 eta: 16:54:19 time: 0.4940 data_time: 0.1760 memory: 5826 grad_norm: 3.0899 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5973 loss: 2.5973 2022/10/07 21:32:34 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 21:32:37 - mmengine - INFO - Epoch(train) [68][40/2119] lr: 4.0000e-02 eta: 16:54:11 time: 0.2935 data_time: 0.0176 memory: 5826 grad_norm: 3.0869 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5440 loss: 2.5440 2022/10/07 21:32:45 - mmengine - INFO - Epoch(train) [68][60/2119] lr: 4.0000e-02 eta: 16:54:05 time: 0.3823 data_time: 0.0221 memory: 5826 grad_norm: 3.1272 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6895 loss: 2.6895 2022/10/07 21:32:52 - mmengine - INFO - Epoch(train) [68][80/2119] lr: 4.0000e-02 eta: 16:53:58 time: 0.3408 data_time: 0.0277 memory: 5826 grad_norm: 3.1281 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4813 loss: 2.4813 2022/10/07 21:32:59 - mmengine - INFO - Epoch(train) [68][100/2119] lr: 4.0000e-02 eta: 16:53:52 time: 0.3594 data_time: 0.0278 memory: 5826 grad_norm: 3.1597 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8967 loss: 2.8967 2022/10/07 21:33:06 - mmengine - INFO - Epoch(train) [68][120/2119] lr: 4.0000e-02 eta: 16:53:45 time: 0.3682 data_time: 0.0238 memory: 5826 grad_norm: 3.0842 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5955 loss: 2.5955 2022/10/07 21:33:14 - mmengine - INFO - Epoch(train) [68][140/2119] lr: 4.0000e-02 eta: 16:53:39 time: 0.3927 data_time: 0.0194 memory: 5826 grad_norm: 3.1511 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8417 loss: 2.8417 2022/10/07 21:33:21 - mmengine - INFO - Epoch(train) [68][160/2119] lr: 4.0000e-02 eta: 16:53:33 time: 0.3528 data_time: 0.0234 memory: 5826 grad_norm: 3.1051 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8629 loss: 2.8629 2022/10/07 21:33:29 - mmengine - INFO - Epoch(train) [68][180/2119] lr: 4.0000e-02 eta: 16:53:27 time: 0.3830 data_time: 0.0189 memory: 5826 grad_norm: 3.1614 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9845 loss: 2.9845 2022/10/07 21:33:35 - mmengine - INFO - Epoch(train) [68][200/2119] lr: 4.0000e-02 eta: 16:53:18 time: 0.2912 data_time: 0.0243 memory: 5826 grad_norm: 3.0925 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7999 loss: 2.7999 2022/10/07 21:33:42 - mmengine - INFO - Epoch(train) [68][220/2119] lr: 4.0000e-02 eta: 16:53:11 time: 0.3423 data_time: 0.0261 memory: 5826 grad_norm: 3.0987 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6217 loss: 2.6217 2022/10/07 21:33:48 - mmengine - INFO - Epoch(train) [68][240/2119] lr: 4.0000e-02 eta: 16:53:04 time: 0.3140 data_time: 0.0264 memory: 5826 grad_norm: 3.0781 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.9620 loss: 2.9620 2022/10/07 21:33:56 - mmengine - INFO - Epoch(train) [68][260/2119] lr: 4.0000e-02 eta: 16:52:57 time: 0.3751 data_time: 0.0251 memory: 5826 grad_norm: 3.1220 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6306 loss: 2.6306 2022/10/07 21:34:03 - mmengine - INFO - Epoch(train) [68][280/2119] lr: 4.0000e-02 eta: 16:52:51 time: 0.3825 data_time: 0.0272 memory: 5826 grad_norm: 3.0971 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5798 loss: 2.5798 2022/10/07 21:34:11 - mmengine - INFO - Epoch(train) [68][300/2119] lr: 4.0000e-02 eta: 16:52:46 time: 0.3910 data_time: 0.0217 memory: 5826 grad_norm: 3.1260 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8068 loss: 2.8068 2022/10/07 21:34:17 - mmengine - INFO - Epoch(train) [68][320/2119] lr: 4.0000e-02 eta: 16:52:38 time: 0.3015 data_time: 0.0224 memory: 5826 grad_norm: 3.1389 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.4193 loss: 2.4193 2022/10/07 21:34:24 - mmengine - INFO - Epoch(train) [68][340/2119] lr: 4.0000e-02 eta: 16:52:30 time: 0.3296 data_time: 0.0200 memory: 5826 grad_norm: 3.1190 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6592 loss: 2.6592 2022/10/07 21:34:31 - mmengine - INFO - Epoch(train) [68][360/2119] lr: 4.0000e-02 eta: 16:52:24 time: 0.3759 data_time: 0.0259 memory: 5826 grad_norm: 3.1018 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6915 loss: 2.6915 2022/10/07 21:34:37 - mmengine - INFO - Epoch(train) [68][380/2119] lr: 4.0000e-02 eta: 16:52:16 time: 0.3118 data_time: 0.0254 memory: 5826 grad_norm: 3.0837 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6816 loss: 2.6816 2022/10/07 21:34:45 - mmengine - INFO - Epoch(train) [68][400/2119] lr: 4.0000e-02 eta: 16:52:10 time: 0.3871 data_time: 0.0242 memory: 5826 grad_norm: 3.0827 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8587 loss: 2.8587 2022/10/07 21:34:52 - mmengine - INFO - Epoch(train) [68][420/2119] lr: 4.0000e-02 eta: 16:52:03 time: 0.3200 data_time: 0.0305 memory: 5826 grad_norm: 3.1198 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6295 loss: 2.6295 2022/10/07 21:34:59 - mmengine - INFO - Epoch(train) [68][440/2119] lr: 4.0000e-02 eta: 16:51:57 time: 0.3800 data_time: 0.0242 memory: 5826 grad_norm: 3.1940 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8165 loss: 2.8165 2022/10/07 21:35:06 - mmengine - INFO - Epoch(train) [68][460/2119] lr: 4.0000e-02 eta: 16:51:50 time: 0.3598 data_time: 0.0167 memory: 5826 grad_norm: 3.1251 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6748 loss: 2.6748 2022/10/07 21:35:14 - mmengine - INFO - Epoch(train) [68][480/2119] lr: 4.0000e-02 eta: 16:51:44 time: 0.3660 data_time: 0.0242 memory: 5826 grad_norm: 3.1419 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6664 loss: 2.6664 2022/10/07 21:35:21 - mmengine - INFO - Epoch(train) [68][500/2119] lr: 4.0000e-02 eta: 16:51:37 time: 0.3600 data_time: 0.0253 memory: 5826 grad_norm: 3.1489 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7223 loss: 2.7223 2022/10/07 21:35:28 - mmengine - INFO - Epoch(train) [68][520/2119] lr: 4.0000e-02 eta: 16:51:31 time: 0.3607 data_time: 0.0247 memory: 5826 grad_norm: 3.1396 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7758 loss: 2.7758 2022/10/07 21:35:35 - mmengine - INFO - Epoch(train) [68][540/2119] lr: 4.0000e-02 eta: 16:51:24 time: 0.3457 data_time: 0.0186 memory: 5826 grad_norm: 3.0689 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7207 loss: 2.7207 2022/10/07 21:35:42 - mmengine - INFO - Epoch(train) [68][560/2119] lr: 4.0000e-02 eta: 16:51:17 time: 0.3545 data_time: 0.0232 memory: 5826 grad_norm: 3.1110 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.7083 loss: 2.7083 2022/10/07 21:35:49 - mmengine - INFO - Epoch(train) [68][580/2119] lr: 4.0000e-02 eta: 16:51:10 time: 0.3362 data_time: 0.0230 memory: 5826 grad_norm: 3.1362 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9541 loss: 2.9541 2022/10/07 21:35:57 - mmengine - INFO - Epoch(train) [68][600/2119] lr: 4.0000e-02 eta: 16:51:04 time: 0.3860 data_time: 0.0228 memory: 5826 grad_norm: 3.0566 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7430 loss: 2.7430 2022/10/07 21:36:03 - mmengine - INFO - Epoch(train) [68][620/2119] lr: 4.0000e-02 eta: 16:50:56 time: 0.3256 data_time: 0.0241 memory: 5826 grad_norm: 3.1171 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7633 loss: 2.7633 2022/10/07 21:36:10 - mmengine - INFO - Epoch(train) [68][640/2119] lr: 4.0000e-02 eta: 16:50:50 time: 0.3528 data_time: 0.0244 memory: 5826 grad_norm: 3.1506 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6960 loss: 2.6960 2022/10/07 21:36:17 - mmengine - INFO - Epoch(train) [68][660/2119] lr: 4.0000e-02 eta: 16:50:42 time: 0.3211 data_time: 0.0214 memory: 5826 grad_norm: 3.1290 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 2.5485 loss: 2.5485 2022/10/07 21:36:24 - mmengine - INFO - Epoch(train) [68][680/2119] lr: 4.0000e-02 eta: 16:50:36 time: 0.3799 data_time: 0.0203 memory: 5826 grad_norm: 3.0916 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7891 loss: 2.7891 2022/10/07 21:36:31 - mmengine - INFO - Epoch(train) [68][700/2119] lr: 4.0000e-02 eta: 16:50:29 time: 0.3384 data_time: 0.0240 memory: 5826 grad_norm: 3.0696 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4379 loss: 2.4379 2022/10/07 21:36:38 - mmengine - INFO - Epoch(train) [68][720/2119] lr: 4.0000e-02 eta: 16:50:22 time: 0.3653 data_time: 0.0285 memory: 5826 grad_norm: 3.0963 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6763 loss: 2.6763 2022/10/07 21:36:45 - mmengine - INFO - Epoch(train) [68][740/2119] lr: 4.0000e-02 eta: 16:50:15 time: 0.3255 data_time: 0.0147 memory: 5826 grad_norm: 3.1295 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9057 loss: 2.9057 2022/10/07 21:36:52 - mmengine - INFO - Epoch(train) [68][760/2119] lr: 4.0000e-02 eta: 16:50:08 time: 0.3420 data_time: 0.0264 memory: 5826 grad_norm: 3.2029 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8505 loss: 2.8505 2022/10/07 21:36:58 - mmengine - INFO - Epoch(train) [68][780/2119] lr: 4.0000e-02 eta: 16:50:00 time: 0.3115 data_time: 0.0207 memory: 5826 grad_norm: 3.0791 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6832 loss: 2.6832 2022/10/07 21:37:05 - mmengine - INFO - Epoch(train) [68][800/2119] lr: 4.0000e-02 eta: 16:49:54 time: 0.3588 data_time: 0.0262 memory: 5826 grad_norm: 3.1135 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7174 loss: 2.7174 2022/10/07 21:37:12 - mmengine - INFO - Epoch(train) [68][820/2119] lr: 4.0000e-02 eta: 16:49:47 time: 0.3516 data_time: 0.0279 memory: 5826 grad_norm: 3.1043 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4740 loss: 2.4740 2022/10/07 21:37:18 - mmengine - INFO - Epoch(train) [68][840/2119] lr: 4.0000e-02 eta: 16:49:39 time: 0.3102 data_time: 0.0263 memory: 5826 grad_norm: 3.1378 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7692 loss: 2.7692 2022/10/07 21:37:26 - mmengine - INFO - Epoch(train) [68][860/2119] lr: 4.0000e-02 eta: 16:49:33 time: 0.3686 data_time: 0.0185 memory: 5826 grad_norm: 3.1139 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7193 loss: 2.7193 2022/10/07 21:37:33 - mmengine - INFO - Epoch(train) [68][880/2119] lr: 4.0000e-02 eta: 16:49:27 time: 0.3898 data_time: 0.0230 memory: 5826 grad_norm: 3.1724 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9460 loss: 2.9460 2022/10/07 21:37:41 - mmengine - INFO - Epoch(train) [68][900/2119] lr: 4.0000e-02 eta: 16:49:21 time: 0.3877 data_time: 0.0228 memory: 5826 grad_norm: 3.0352 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6686 loss: 2.6686 2022/10/07 21:37:47 - mmengine - INFO - Epoch(train) [68][920/2119] lr: 4.0000e-02 eta: 16:49:13 time: 0.2901 data_time: 0.0226 memory: 5826 grad_norm: 3.1206 top1_acc: 0.0625 top5_acc: 0.2500 loss_cls: 2.9034 loss: 2.9034 2022/10/07 21:37:54 - mmengine - INFO - Epoch(train) [68][940/2119] lr: 4.0000e-02 eta: 16:49:06 time: 0.3667 data_time: 0.0206 memory: 5826 grad_norm: 3.1345 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.6896 loss: 2.6896 2022/10/07 21:38:01 - mmengine - INFO - Epoch(train) [68][960/2119] lr: 4.0000e-02 eta: 16:48:59 time: 0.3203 data_time: 0.0287 memory: 5826 grad_norm: 3.1751 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6544 loss: 2.6544 2022/10/07 21:38:08 - mmengine - INFO - Epoch(train) [68][980/2119] lr: 4.0000e-02 eta: 16:48:52 time: 0.3491 data_time: 0.0209 memory: 5826 grad_norm: 3.1337 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.9713 loss: 2.9713 2022/10/07 21:38:14 - mmengine - INFO - Epoch(train) [68][1000/2119] lr: 4.0000e-02 eta: 16:48:44 time: 0.3042 data_time: 0.0249 memory: 5826 grad_norm: 3.0922 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6736 loss: 2.6736 2022/10/07 21:38:21 - mmengine - INFO - Epoch(train) [68][1020/2119] lr: 4.0000e-02 eta: 16:48:38 time: 0.3780 data_time: 0.0325 memory: 5826 grad_norm: 3.1716 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7461 loss: 2.7461 2022/10/07 21:38:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 21:38:28 - mmengine - INFO - Epoch(train) [68][1040/2119] lr: 4.0000e-02 eta: 16:48:30 time: 0.3181 data_time: 0.0210 memory: 5826 grad_norm: 3.0740 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6810 loss: 2.6810 2022/10/07 21:38:35 - mmengine - INFO - Epoch(train) [68][1060/2119] lr: 4.0000e-02 eta: 16:48:23 time: 0.3558 data_time: 0.0247 memory: 5826 grad_norm: 3.0922 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8207 loss: 2.8207 2022/10/07 21:38:42 - mmengine - INFO - Epoch(train) [68][1080/2119] lr: 4.0000e-02 eta: 16:48:17 time: 0.3554 data_time: 0.0251 memory: 5826 grad_norm: 3.1671 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8498 loss: 2.8498 2022/10/07 21:38:49 - mmengine - INFO - Epoch(train) [68][1100/2119] lr: 4.0000e-02 eta: 16:48:10 time: 0.3520 data_time: 0.0261 memory: 5826 grad_norm: 3.1583 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8066 loss: 2.8066 2022/10/07 21:38:55 - mmengine - INFO - Epoch(train) [68][1120/2119] lr: 4.0000e-02 eta: 16:48:02 time: 0.3024 data_time: 0.0222 memory: 5826 grad_norm: 3.0734 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6003 loss: 2.6003 2022/10/07 21:39:03 - mmengine - INFO - Epoch(train) [68][1140/2119] lr: 4.0000e-02 eta: 16:47:56 time: 0.3833 data_time: 0.0255 memory: 5826 grad_norm: 3.0845 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8009 loss: 2.8009 2022/10/07 21:39:09 - mmengine - INFO - Epoch(train) [68][1160/2119] lr: 4.0000e-02 eta: 16:47:48 time: 0.3169 data_time: 0.0218 memory: 5826 grad_norm: 3.1483 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5047 loss: 2.5047 2022/10/07 21:39:17 - mmengine - INFO - Epoch(train) [68][1180/2119] lr: 4.0000e-02 eta: 16:47:42 time: 0.3713 data_time: 0.0217 memory: 5826 grad_norm: 3.1288 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7092 loss: 2.7092 2022/10/07 21:39:23 - mmengine - INFO - Epoch(train) [68][1200/2119] lr: 4.0000e-02 eta: 16:47:34 time: 0.3136 data_time: 0.0203 memory: 5826 grad_norm: 3.1341 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7234 loss: 2.7234 2022/10/07 21:39:30 - mmengine - INFO - Epoch(train) [68][1220/2119] lr: 4.0000e-02 eta: 16:47:27 time: 0.3411 data_time: 0.0197 memory: 5826 grad_norm: 3.0939 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7400 loss: 2.7400 2022/10/07 21:39:36 - mmengine - INFO - Epoch(train) [68][1240/2119] lr: 4.0000e-02 eta: 16:47:19 time: 0.3111 data_time: 0.0268 memory: 5826 grad_norm: 3.0600 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6124 loss: 2.6124 2022/10/07 21:39:43 - mmengine - INFO - Epoch(train) [68][1260/2119] lr: 4.0000e-02 eta: 16:47:13 time: 0.3792 data_time: 0.0190 memory: 5826 grad_norm: 3.0889 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5795 loss: 2.5795 2022/10/07 21:39:50 - mmengine - INFO - Epoch(train) [68][1280/2119] lr: 4.0000e-02 eta: 16:47:06 time: 0.3288 data_time: 0.0243 memory: 5826 grad_norm: 3.0685 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7534 loss: 2.7534 2022/10/07 21:39:57 - mmengine - INFO - Epoch(train) [68][1300/2119] lr: 4.0000e-02 eta: 16:46:59 time: 0.3602 data_time: 0.0288 memory: 5826 grad_norm: 3.1543 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3926 loss: 2.3926 2022/10/07 21:40:04 - mmengine - INFO - Epoch(train) [68][1320/2119] lr: 4.0000e-02 eta: 16:46:52 time: 0.3420 data_time: 0.0239 memory: 5826 grad_norm: 3.1949 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9469 loss: 2.9469 2022/10/07 21:40:11 - mmengine - INFO - Epoch(train) [68][1340/2119] lr: 4.0000e-02 eta: 16:46:46 time: 0.3622 data_time: 0.0220 memory: 5826 grad_norm: 3.1014 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7963 loss: 2.7963 2022/10/07 21:40:18 - mmengine - INFO - Epoch(train) [68][1360/2119] lr: 4.0000e-02 eta: 16:46:39 time: 0.3357 data_time: 0.0182 memory: 5826 grad_norm: 3.1378 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7954 loss: 2.7954 2022/10/07 21:40:25 - mmengine - INFO - Epoch(train) [68][1380/2119] lr: 4.0000e-02 eta: 16:46:32 time: 0.3480 data_time: 0.0216 memory: 5826 grad_norm: 3.1463 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6519 loss: 2.6519 2022/10/07 21:40:32 - mmengine - INFO - Epoch(train) [68][1400/2119] lr: 4.0000e-02 eta: 16:46:25 time: 0.3492 data_time: 0.0245 memory: 5826 grad_norm: 3.1405 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6754 loss: 2.6754 2022/10/07 21:40:40 - mmengine - INFO - Epoch(train) [68][1420/2119] lr: 4.0000e-02 eta: 16:46:19 time: 0.3892 data_time: 0.0224 memory: 5826 grad_norm: 3.1447 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9463 loss: 2.9463 2022/10/07 21:40:46 - mmengine - INFO - Epoch(train) [68][1440/2119] lr: 4.0000e-02 eta: 16:46:12 time: 0.3245 data_time: 0.0300 memory: 5826 grad_norm: 3.1427 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8267 loss: 2.8267 2022/10/07 21:40:54 - mmengine - INFO - Epoch(train) [68][1460/2119] lr: 4.0000e-02 eta: 16:46:05 time: 0.3761 data_time: 0.0196 memory: 5826 grad_norm: 3.1257 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7188 loss: 2.7188 2022/10/07 21:41:00 - mmengine - INFO - Epoch(train) [68][1480/2119] lr: 4.0000e-02 eta: 16:45:57 time: 0.3018 data_time: 0.0263 memory: 5826 grad_norm: 3.1147 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4521 loss: 2.4521 2022/10/07 21:41:07 - mmengine - INFO - Epoch(train) [68][1500/2119] lr: 4.0000e-02 eta: 16:45:50 time: 0.3405 data_time: 0.0221 memory: 5826 grad_norm: 3.1704 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.7947 loss: 2.7947 2022/10/07 21:41:14 - mmengine - INFO - Epoch(train) [68][1520/2119] lr: 4.0000e-02 eta: 16:45:43 time: 0.3439 data_time: 0.0252 memory: 5826 grad_norm: 3.1538 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7325 loss: 2.7325 2022/10/07 21:41:20 - mmengine - INFO - Epoch(train) [68][1540/2119] lr: 4.0000e-02 eta: 16:45:36 time: 0.3397 data_time: 0.0234 memory: 5826 grad_norm: 3.0855 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5391 loss: 2.5391 2022/10/07 21:41:27 - mmengine - INFO - Epoch(train) [68][1560/2119] lr: 4.0000e-02 eta: 16:45:29 time: 0.3371 data_time: 0.0251 memory: 5826 grad_norm: 3.1115 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7946 loss: 2.7946 2022/10/07 21:41:35 - mmengine - INFO - Epoch(train) [68][1580/2119] lr: 4.0000e-02 eta: 16:45:24 time: 0.4057 data_time: 0.0245 memory: 5826 grad_norm: 3.1264 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.8112 loss: 2.8112 2022/10/07 21:41:42 - mmengine - INFO - Epoch(train) [68][1600/2119] lr: 4.0000e-02 eta: 16:45:17 time: 0.3566 data_time: 0.0253 memory: 5826 grad_norm: 3.1194 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7335 loss: 2.7335 2022/10/07 21:41:50 - mmengine - INFO - Epoch(train) [68][1620/2119] lr: 4.0000e-02 eta: 16:45:11 time: 0.3768 data_time: 0.0194 memory: 5826 grad_norm: 3.0671 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5964 loss: 2.5964 2022/10/07 21:41:56 - mmengine - INFO - Epoch(train) [68][1640/2119] lr: 4.0000e-02 eta: 16:45:03 time: 0.2976 data_time: 0.0236 memory: 5826 grad_norm: 3.0577 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6369 loss: 2.6369 2022/10/07 21:42:04 - mmengine - INFO - Epoch(train) [68][1660/2119] lr: 4.0000e-02 eta: 16:44:57 time: 0.4048 data_time: 0.0210 memory: 5826 grad_norm: 3.1276 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9697 loss: 2.9697 2022/10/07 21:42:10 - mmengine - INFO - Epoch(train) [68][1680/2119] lr: 4.0000e-02 eta: 16:44:49 time: 0.2822 data_time: 0.0236 memory: 5826 grad_norm: 3.1346 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5250 loss: 2.5250 2022/10/07 21:42:17 - mmengine - INFO - Epoch(train) [68][1700/2119] lr: 4.0000e-02 eta: 16:44:42 time: 0.3564 data_time: 0.0222 memory: 5826 grad_norm: 3.1161 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9188 loss: 2.9188 2022/10/07 21:42:24 - mmengine - INFO - Epoch(train) [68][1720/2119] lr: 4.0000e-02 eta: 16:44:35 time: 0.3551 data_time: 0.0253 memory: 5826 grad_norm: 3.1247 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7012 loss: 2.7012 2022/10/07 21:42:31 - mmengine - INFO - Epoch(train) [68][1740/2119] lr: 4.0000e-02 eta: 16:44:29 time: 0.3671 data_time: 0.0220 memory: 5826 grad_norm: 3.0817 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8667 loss: 2.8667 2022/10/07 21:42:37 - mmengine - INFO - Epoch(train) [68][1760/2119] lr: 4.0000e-02 eta: 16:44:21 time: 0.2924 data_time: 0.0279 memory: 5826 grad_norm: 3.0921 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.7614 loss: 2.7614 2022/10/07 21:42:45 - mmengine - INFO - Epoch(train) [68][1780/2119] lr: 4.0000e-02 eta: 16:44:15 time: 0.3771 data_time: 0.0241 memory: 5826 grad_norm: 3.0359 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7438 loss: 2.7438 2022/10/07 21:42:51 - mmengine - INFO - Epoch(train) [68][1800/2119] lr: 4.0000e-02 eta: 16:44:07 time: 0.3333 data_time: 0.0198 memory: 5826 grad_norm: 3.1796 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7001 loss: 2.7001 2022/10/07 21:42:58 - mmengine - INFO - Epoch(train) [68][1820/2119] lr: 4.0000e-02 eta: 16:44:00 time: 0.3316 data_time: 0.0170 memory: 5826 grad_norm: 3.1953 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8307 loss: 2.8307 2022/10/07 21:43:05 - mmengine - INFO - Epoch(train) [68][1840/2119] lr: 4.0000e-02 eta: 16:43:53 time: 0.3452 data_time: 0.0252 memory: 5826 grad_norm: 3.1297 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6752 loss: 2.6752 2022/10/07 21:43:13 - mmengine - INFO - Epoch(train) [68][1860/2119] lr: 4.0000e-02 eta: 16:43:47 time: 0.3894 data_time: 0.0267 memory: 5826 grad_norm: 3.1838 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6228 loss: 2.6228 2022/10/07 21:43:19 - mmengine - INFO - Epoch(train) [68][1880/2119] lr: 4.0000e-02 eta: 16:43:39 time: 0.3092 data_time: 0.0263 memory: 5826 grad_norm: 3.1064 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8329 loss: 2.8329 2022/10/07 21:43:26 - mmengine - INFO - Epoch(train) [68][1900/2119] lr: 4.0000e-02 eta: 16:43:33 time: 0.3667 data_time: 0.0163 memory: 5826 grad_norm: 3.0780 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6481 loss: 2.6481 2022/10/07 21:43:33 - mmengine - INFO - Epoch(train) [68][1920/2119] lr: 4.0000e-02 eta: 16:43:25 time: 0.3182 data_time: 0.0256 memory: 5826 grad_norm: 3.1536 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8893 loss: 2.8893 2022/10/07 21:43:40 - mmengine - INFO - Epoch(train) [68][1940/2119] lr: 4.0000e-02 eta: 16:43:19 time: 0.3731 data_time: 0.0226 memory: 5826 grad_norm: 3.0417 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5827 loss: 2.5827 2022/10/07 21:43:46 - mmengine - INFO - Epoch(train) [68][1960/2119] lr: 4.0000e-02 eta: 16:43:12 time: 0.3195 data_time: 0.0223 memory: 5826 grad_norm: 3.1156 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6525 loss: 2.6525 2022/10/07 21:43:54 - mmengine - INFO - Epoch(train) [68][1980/2119] lr: 4.0000e-02 eta: 16:43:06 time: 0.3841 data_time: 0.0193 memory: 5826 grad_norm: 3.1861 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.7839 loss: 2.7839 2022/10/07 21:44:01 - mmengine - INFO - Epoch(train) [68][2000/2119] lr: 4.0000e-02 eta: 16:42:58 time: 0.3300 data_time: 0.0219 memory: 5826 grad_norm: 3.0836 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7967 loss: 2.7967 2022/10/07 21:44:08 - mmengine - INFO - Epoch(train) [68][2020/2119] lr: 4.0000e-02 eta: 16:42:52 time: 0.3549 data_time: 0.0223 memory: 5826 grad_norm: 3.1244 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6574 loss: 2.6574 2022/10/07 21:44:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 21:44:15 - mmengine - INFO - Epoch(train) [68][2040/2119] lr: 4.0000e-02 eta: 16:42:45 time: 0.3428 data_time: 0.0214 memory: 5826 grad_norm: 3.0957 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7815 loss: 2.7815 2022/10/07 21:44:21 - mmengine - INFO - Epoch(train) [68][2060/2119] lr: 4.0000e-02 eta: 16:42:37 time: 0.3206 data_time: 0.0175 memory: 5826 grad_norm: 3.0548 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7210 loss: 2.7210 2022/10/07 21:44:28 - mmengine - INFO - Epoch(train) [68][2080/2119] lr: 4.0000e-02 eta: 16:42:30 time: 0.3356 data_time: 0.0287 memory: 5826 grad_norm: 3.1296 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8672 loss: 2.8672 2022/10/07 21:44:34 - mmengine - INFO - Epoch(train) [68][2100/2119] lr: 4.0000e-02 eta: 16:42:22 time: 0.3253 data_time: 0.0195 memory: 5826 grad_norm: 3.1923 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.7872 loss: 2.7872 2022/10/07 21:44:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 21:44:40 - mmengine - INFO - Epoch(train) [68][2119/2119] lr: 4.0000e-02 eta: 16:42:22 time: 0.2995 data_time: 0.0201 memory: 5826 grad_norm: 3.0948 top1_acc: 0.6000 top5_acc: 0.7000 loss_cls: 2.8427 loss: 2.8427 2022/10/07 21:44:40 - mmengine - INFO - Saving checkpoint at 68 epochs 2022/10/07 21:45:00 - mmengine - INFO - Epoch(train) [69][20/2119] lr: 4.0000e-02 eta: 16:42:03 time: 0.4471 data_time: 0.2322 memory: 5826 grad_norm: 3.0494 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7061 loss: 2.7061 2022/10/07 21:45:06 - mmengine - INFO - Epoch(train) [69][40/2119] lr: 4.0000e-02 eta: 16:41:56 time: 0.3066 data_time: 0.0740 memory: 5826 grad_norm: 3.0732 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8039 loss: 2.8039 2022/10/07 21:45:13 - mmengine - INFO - Epoch(train) [69][60/2119] lr: 4.0000e-02 eta: 16:41:48 time: 0.3302 data_time: 0.1062 memory: 5826 grad_norm: 3.0789 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7177 loss: 2.7177 2022/10/07 21:45:19 - mmengine - INFO - Epoch(train) [69][80/2119] lr: 4.0000e-02 eta: 16:41:41 time: 0.3163 data_time: 0.0819 memory: 5826 grad_norm: 3.1102 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6678 loss: 2.6678 2022/10/07 21:45:26 - mmengine - INFO - Epoch(train) [69][100/2119] lr: 4.0000e-02 eta: 16:41:34 time: 0.3721 data_time: 0.0280 memory: 5826 grad_norm: 3.0660 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6053 loss: 2.6053 2022/10/07 21:45:33 - mmengine - INFO - Epoch(train) [69][120/2119] lr: 4.0000e-02 eta: 16:41:27 time: 0.3357 data_time: 0.0181 memory: 5826 grad_norm: 3.1386 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8626 loss: 2.8626 2022/10/07 21:45:40 - mmengine - INFO - Epoch(train) [69][140/2119] lr: 4.0000e-02 eta: 16:41:20 time: 0.3288 data_time: 0.0264 memory: 5826 grad_norm: 3.1421 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7309 loss: 2.7309 2022/10/07 21:45:48 - mmengine - INFO - Epoch(train) [69][160/2119] lr: 4.0000e-02 eta: 16:41:14 time: 0.4006 data_time: 0.0203 memory: 5826 grad_norm: 3.1444 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7603 loss: 2.7603 2022/10/07 21:45:55 - mmengine - INFO - Epoch(train) [69][180/2119] lr: 4.0000e-02 eta: 16:41:07 time: 0.3450 data_time: 0.0237 memory: 5826 grad_norm: 3.0944 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6783 loss: 2.6783 2022/10/07 21:46:02 - mmengine - INFO - Epoch(train) [69][200/2119] lr: 4.0000e-02 eta: 16:41:01 time: 0.3828 data_time: 0.0219 memory: 5826 grad_norm: 3.1573 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7870 loss: 2.7870 2022/10/07 21:46:09 - mmengine - INFO - Epoch(train) [69][220/2119] lr: 4.0000e-02 eta: 16:40:54 time: 0.3138 data_time: 0.0202 memory: 5826 grad_norm: 3.0988 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5053 loss: 2.5053 2022/10/07 21:46:15 - mmengine - INFO - Epoch(train) [69][240/2119] lr: 4.0000e-02 eta: 16:40:46 time: 0.3250 data_time: 0.0271 memory: 5826 grad_norm: 3.1511 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8658 loss: 2.8658 2022/10/07 21:46:23 - mmengine - INFO - Epoch(train) [69][260/2119] lr: 4.0000e-02 eta: 16:40:40 time: 0.3728 data_time: 0.0257 memory: 5826 grad_norm: 3.1184 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6608 loss: 2.6608 2022/10/07 21:46:29 - mmengine - INFO - Epoch(train) [69][280/2119] lr: 4.0000e-02 eta: 16:40:33 time: 0.3331 data_time: 0.0227 memory: 5826 grad_norm: 3.0894 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8362 loss: 2.8362 2022/10/07 21:46:36 - mmengine - INFO - Epoch(train) [69][300/2119] lr: 4.0000e-02 eta: 16:40:25 time: 0.3356 data_time: 0.0259 memory: 5826 grad_norm: 3.1002 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4315 loss: 2.4315 2022/10/07 21:46:43 - mmengine - INFO - Epoch(train) [69][320/2119] lr: 4.0000e-02 eta: 16:40:19 time: 0.3502 data_time: 0.0210 memory: 5826 grad_norm: 3.1802 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.0598 loss: 3.0598 2022/10/07 21:46:49 - mmengine - INFO - Epoch(train) [69][340/2119] lr: 4.0000e-02 eta: 16:40:10 time: 0.2850 data_time: 0.0216 memory: 5826 grad_norm: 3.1002 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7724 loss: 2.7724 2022/10/07 21:46:56 - mmengine - INFO - Epoch(train) [69][360/2119] lr: 4.0000e-02 eta: 16:40:04 time: 0.3760 data_time: 0.0203 memory: 5826 grad_norm: 3.0916 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6415 loss: 2.6415 2022/10/07 21:47:03 - mmengine - INFO - Epoch(train) [69][380/2119] lr: 4.0000e-02 eta: 16:39:57 time: 0.3259 data_time: 0.0229 memory: 5826 grad_norm: 3.0931 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5971 loss: 2.5971 2022/10/07 21:47:10 - mmengine - INFO - Epoch(train) [69][400/2119] lr: 4.0000e-02 eta: 16:39:50 time: 0.3735 data_time: 0.0253 memory: 5826 grad_norm: 3.0971 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6000 loss: 2.6000 2022/10/07 21:47:17 - mmengine - INFO - Epoch(train) [69][420/2119] lr: 4.0000e-02 eta: 16:39:43 time: 0.3203 data_time: 0.0224 memory: 5826 grad_norm: 3.1094 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8483 loss: 2.8483 2022/10/07 21:47:24 - mmengine - INFO - Epoch(train) [69][440/2119] lr: 4.0000e-02 eta: 16:39:37 time: 0.3760 data_time: 0.0231 memory: 5826 grad_norm: 3.1356 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7856 loss: 2.7856 2022/10/07 21:47:30 - mmengine - INFO - Epoch(train) [69][460/2119] lr: 4.0000e-02 eta: 16:39:29 time: 0.3049 data_time: 0.0214 memory: 5826 grad_norm: 3.1420 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6459 loss: 2.6459 2022/10/07 21:47:37 - mmengine - INFO - Epoch(train) [69][480/2119] lr: 4.0000e-02 eta: 16:39:22 time: 0.3566 data_time: 0.0209 memory: 5826 grad_norm: 3.1624 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8239 loss: 2.8239 2022/10/07 21:47:45 - mmengine - INFO - Epoch(train) [69][500/2119] lr: 4.0000e-02 eta: 16:39:16 time: 0.3630 data_time: 0.0246 memory: 5826 grad_norm: 3.1093 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8752 loss: 2.8752 2022/10/07 21:47:52 - mmengine - INFO - Epoch(train) [69][520/2119] lr: 4.0000e-02 eta: 16:39:10 time: 0.3842 data_time: 0.0214 memory: 5826 grad_norm: 3.1415 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6768 loss: 2.6768 2022/10/07 21:47:58 - mmengine - INFO - Epoch(train) [69][540/2119] lr: 4.0000e-02 eta: 16:39:01 time: 0.2880 data_time: 0.0218 memory: 5826 grad_norm: 3.1527 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6968 loss: 2.6968 2022/10/07 21:48:05 - mmengine - INFO - Epoch(train) [69][560/2119] lr: 4.0000e-02 eta: 16:38:55 time: 0.3650 data_time: 0.0210 memory: 5826 grad_norm: 3.0704 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8612 loss: 2.8612 2022/10/07 21:48:12 - mmengine - INFO - Epoch(train) [69][580/2119] lr: 4.0000e-02 eta: 16:38:47 time: 0.3225 data_time: 0.0249 memory: 5826 grad_norm: 3.0952 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6855 loss: 2.6855 2022/10/07 21:48:19 - mmengine - INFO - Epoch(train) [69][600/2119] lr: 4.0000e-02 eta: 16:38:40 time: 0.3353 data_time: 0.0248 memory: 5826 grad_norm: 3.1135 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.7545 loss: 2.7545 2022/10/07 21:48:26 - mmengine - INFO - Epoch(train) [69][620/2119] lr: 4.0000e-02 eta: 16:38:34 time: 0.3790 data_time: 0.0232 memory: 5826 grad_norm: 3.1012 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 2.7349 loss: 2.7349 2022/10/07 21:48:33 - mmengine - INFO - Epoch(train) [69][640/2119] lr: 4.0000e-02 eta: 16:38:27 time: 0.3655 data_time: 0.0245 memory: 5826 grad_norm: 3.1301 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6092 loss: 2.6092 2022/10/07 21:48:40 - mmengine - INFO - Epoch(train) [69][660/2119] lr: 4.0000e-02 eta: 16:38:20 time: 0.3021 data_time: 0.0236 memory: 5826 grad_norm: 3.1361 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9346 loss: 2.9346 2022/10/07 21:48:47 - mmengine - INFO - Epoch(train) [69][680/2119] lr: 4.0000e-02 eta: 16:38:14 time: 0.3840 data_time: 0.0217 memory: 5826 grad_norm: 3.1296 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7277 loss: 2.7277 2022/10/07 21:48:53 - mmengine - INFO - Epoch(train) [69][700/2119] lr: 4.0000e-02 eta: 16:38:06 time: 0.3071 data_time: 0.0241 memory: 5826 grad_norm: 3.1670 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8894 loss: 2.8894 2022/10/07 21:49:01 - mmengine - INFO - Epoch(train) [69][720/2119] lr: 4.0000e-02 eta: 16:37:59 time: 0.3630 data_time: 0.0201 memory: 5826 grad_norm: 3.1389 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7118 loss: 2.7118 2022/10/07 21:49:07 - mmengine - INFO - Epoch(train) [69][740/2119] lr: 4.0000e-02 eta: 16:37:51 time: 0.3097 data_time: 0.0231 memory: 5826 grad_norm: 3.0504 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5467 loss: 2.5467 2022/10/07 21:49:13 - mmengine - INFO - Epoch(train) [69][760/2119] lr: 4.0000e-02 eta: 16:37:44 time: 0.3261 data_time: 0.0178 memory: 5826 grad_norm: 3.0513 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6749 loss: 2.6749 2022/10/07 21:49:20 - mmengine - INFO - Epoch(train) [69][780/2119] lr: 4.0000e-02 eta: 16:37:37 time: 0.3489 data_time: 0.0247 memory: 5826 grad_norm: 3.0964 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5268 loss: 2.5268 2022/10/07 21:49:28 - mmengine - INFO - Epoch(train) [69][800/2119] lr: 4.0000e-02 eta: 16:37:31 time: 0.3824 data_time: 0.0184 memory: 5826 grad_norm: 3.1656 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9749 loss: 2.9749 2022/10/07 21:49:35 - mmengine - INFO - Epoch(train) [69][820/2119] lr: 4.0000e-02 eta: 16:37:25 time: 0.3694 data_time: 0.0238 memory: 5826 grad_norm: 3.0405 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8730 loss: 2.8730 2022/10/07 21:49:42 - mmengine - INFO - Epoch(train) [69][840/2119] lr: 4.0000e-02 eta: 16:37:17 time: 0.3113 data_time: 0.0309 memory: 5826 grad_norm: 3.1092 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7072 loss: 2.7072 2022/10/07 21:49:49 - mmengine - INFO - Epoch(train) [69][860/2119] lr: 4.0000e-02 eta: 16:37:10 time: 0.3473 data_time: 0.0223 memory: 5826 grad_norm: 3.1323 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9198 loss: 2.9198 2022/10/07 21:49:55 - mmengine - INFO - Epoch(train) [69][880/2119] lr: 4.0000e-02 eta: 16:37:03 time: 0.3309 data_time: 0.0221 memory: 5826 grad_norm: 3.0865 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9042 loss: 2.9042 2022/10/07 21:50:02 - mmengine - INFO - Epoch(train) [69][900/2119] lr: 4.0000e-02 eta: 16:36:55 time: 0.3299 data_time: 0.0246 memory: 5826 grad_norm: 3.1490 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6628 loss: 2.6628 2022/10/07 21:50:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 21:50:08 - mmengine - INFO - Epoch(train) [69][920/2119] lr: 4.0000e-02 eta: 16:36:48 time: 0.3218 data_time: 0.0224 memory: 5826 grad_norm: 3.0630 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6292 loss: 2.6292 2022/10/07 21:50:15 - mmengine - INFO - Epoch(train) [69][940/2119] lr: 4.0000e-02 eta: 16:36:41 time: 0.3243 data_time: 0.0250 memory: 5826 grad_norm: 3.1231 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6951 loss: 2.6951 2022/10/07 21:50:23 - mmengine - INFO - Epoch(train) [69][960/2119] lr: 4.0000e-02 eta: 16:36:35 time: 0.4044 data_time: 0.0182 memory: 5826 grad_norm: 3.1241 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8167 loss: 2.8167 2022/10/07 21:50:29 - mmengine - INFO - Epoch(train) [69][980/2119] lr: 4.0000e-02 eta: 16:36:27 time: 0.3020 data_time: 0.0229 memory: 5826 grad_norm: 3.0865 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5729 loss: 2.5729 2022/10/07 21:50:37 - mmengine - INFO - Epoch(train) [69][1000/2119] lr: 4.0000e-02 eta: 16:36:22 time: 0.4253 data_time: 0.0221 memory: 5826 grad_norm: 3.1242 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7181 loss: 2.7181 2022/10/07 21:50:44 - mmengine - INFO - Epoch(train) [69][1020/2119] lr: 4.0000e-02 eta: 16:36:14 time: 0.3106 data_time: 0.0261 memory: 5826 grad_norm: 3.1078 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7779 loss: 2.7779 2022/10/07 21:50:51 - mmengine - INFO - Epoch(train) [69][1040/2119] lr: 4.0000e-02 eta: 16:36:08 time: 0.3933 data_time: 0.0239 memory: 5826 grad_norm: 3.0716 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5429 loss: 2.5429 2022/10/07 21:50:58 - mmengine - INFO - Epoch(train) [69][1060/2119] lr: 4.0000e-02 eta: 16:36:02 time: 0.3467 data_time: 0.0232 memory: 5826 grad_norm: 3.1066 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.7217 loss: 2.7217 2022/10/07 21:51:06 - mmengine - INFO - Epoch(train) [69][1080/2119] lr: 4.0000e-02 eta: 16:35:56 time: 0.3877 data_time: 0.0245 memory: 5826 grad_norm: 3.1006 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7098 loss: 2.7098 2022/10/07 21:51:13 - mmengine - INFO - Epoch(train) [69][1100/2119] lr: 4.0000e-02 eta: 16:35:48 time: 0.3225 data_time: 0.0210 memory: 5826 grad_norm: 3.1880 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7647 loss: 2.7647 2022/10/07 21:51:19 - mmengine - INFO - Epoch(train) [69][1120/2119] lr: 4.0000e-02 eta: 16:35:41 time: 0.3446 data_time: 0.0275 memory: 5826 grad_norm: 3.1357 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9303 loss: 2.9303 2022/10/07 21:51:26 - mmengine - INFO - Epoch(train) [69][1140/2119] lr: 4.0000e-02 eta: 16:35:34 time: 0.3377 data_time: 0.0219 memory: 5826 grad_norm: 3.0936 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9960 loss: 2.9960 2022/10/07 21:51:33 - mmengine - INFO - Epoch(train) [69][1160/2119] lr: 4.0000e-02 eta: 16:35:27 time: 0.3388 data_time: 0.0228 memory: 5826 grad_norm: 3.1314 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6595 loss: 2.6595 2022/10/07 21:51:40 - mmengine - INFO - Epoch(train) [69][1180/2119] lr: 4.0000e-02 eta: 16:35:20 time: 0.3368 data_time: 0.0209 memory: 5826 grad_norm: 3.0877 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8808 loss: 2.8808 2022/10/07 21:51:47 - mmengine - INFO - Epoch(train) [69][1200/2119] lr: 4.0000e-02 eta: 16:35:14 time: 0.3831 data_time: 0.0227 memory: 5826 grad_norm: 3.1163 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7099 loss: 2.7099 2022/10/07 21:51:54 - mmengine - INFO - Epoch(train) [69][1220/2119] lr: 4.0000e-02 eta: 16:35:06 time: 0.3231 data_time: 0.0209 memory: 5826 grad_norm: 3.0861 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7509 loss: 2.7509 2022/10/07 21:52:03 - mmengine - INFO - Epoch(train) [69][1240/2119] lr: 4.0000e-02 eta: 16:35:02 time: 0.4366 data_time: 0.0226 memory: 5826 grad_norm: 3.0845 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6566 loss: 2.6566 2022/10/07 21:52:08 - mmengine - INFO - Epoch(train) [69][1260/2119] lr: 4.0000e-02 eta: 16:34:53 time: 0.2920 data_time: 0.0257 memory: 5826 grad_norm: 3.1627 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8127 loss: 2.8127 2022/10/07 21:52:17 - mmengine - INFO - Epoch(train) [69][1280/2119] lr: 4.0000e-02 eta: 16:34:48 time: 0.4077 data_time: 0.0211 memory: 5826 grad_norm: 3.1112 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7506 loss: 2.7506 2022/10/07 21:52:23 - mmengine - INFO - Epoch(train) [69][1300/2119] lr: 4.0000e-02 eta: 16:34:40 time: 0.3233 data_time: 0.0248 memory: 5826 grad_norm: 3.0941 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6780 loss: 2.6780 2022/10/07 21:52:29 - mmengine - INFO - Epoch(train) [69][1320/2119] lr: 4.0000e-02 eta: 16:34:33 time: 0.3150 data_time: 0.0176 memory: 5826 grad_norm: 3.2214 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7348 loss: 2.7348 2022/10/07 21:52:36 - mmengine - INFO - Epoch(train) [69][1340/2119] lr: 4.0000e-02 eta: 16:34:26 time: 0.3345 data_time: 0.0277 memory: 5826 grad_norm: 3.1358 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5791 loss: 2.5791 2022/10/07 21:52:44 - mmengine - INFO - Epoch(train) [69][1360/2119] lr: 4.0000e-02 eta: 16:34:19 time: 0.3695 data_time: 0.0277 memory: 5826 grad_norm: 3.0947 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5246 loss: 2.5246 2022/10/07 21:52:50 - mmengine - INFO - Epoch(train) [69][1380/2119] lr: 4.0000e-02 eta: 16:34:12 time: 0.3435 data_time: 0.0252 memory: 5826 grad_norm: 3.0455 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7470 loss: 2.7470 2022/10/07 21:52:57 - mmengine - INFO - Epoch(train) [69][1400/2119] lr: 4.0000e-02 eta: 16:34:05 time: 0.3212 data_time: 0.0231 memory: 5826 grad_norm: 3.1085 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7862 loss: 2.7862 2022/10/07 21:53:04 - mmengine - INFO - Epoch(train) [69][1420/2119] lr: 4.0000e-02 eta: 16:33:58 time: 0.3557 data_time: 0.0199 memory: 5826 grad_norm: 3.1113 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8322 loss: 2.8322 2022/10/07 21:53:11 - mmengine - INFO - Epoch(train) [69][1440/2119] lr: 4.0000e-02 eta: 16:33:51 time: 0.3393 data_time: 0.0253 memory: 5826 grad_norm: 3.1286 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7896 loss: 2.7896 2022/10/07 21:53:17 - mmengine - INFO - Epoch(train) [69][1460/2119] lr: 4.0000e-02 eta: 16:33:43 time: 0.3216 data_time: 0.0199 memory: 5826 grad_norm: 3.1260 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.7156 loss: 2.7156 2022/10/07 21:53:24 - mmengine - INFO - Epoch(train) [69][1480/2119] lr: 4.0000e-02 eta: 16:33:37 time: 0.3509 data_time: 0.0225 memory: 5826 grad_norm: 3.1539 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7411 loss: 2.7411 2022/10/07 21:53:31 - mmengine - INFO - Epoch(train) [69][1500/2119] lr: 4.0000e-02 eta: 16:33:29 time: 0.3203 data_time: 0.0280 memory: 5826 grad_norm: 3.0895 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8702 loss: 2.8702 2022/10/07 21:53:38 - mmengine - INFO - Epoch(train) [69][1520/2119] lr: 4.0000e-02 eta: 16:33:23 time: 0.3758 data_time: 0.0221 memory: 5826 grad_norm: 3.0989 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.9604 loss: 2.9604 2022/10/07 21:53:45 - mmengine - INFO - Epoch(train) [69][1540/2119] lr: 4.0000e-02 eta: 16:33:16 time: 0.3296 data_time: 0.0206 memory: 5826 grad_norm: 3.0951 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5577 loss: 2.5577 2022/10/07 21:53:52 - mmengine - INFO - Epoch(train) [69][1560/2119] lr: 4.0000e-02 eta: 16:33:09 time: 0.3610 data_time: 0.0188 memory: 5826 grad_norm: 3.0559 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5076 loss: 2.5076 2022/10/07 21:53:59 - mmengine - INFO - Epoch(train) [69][1580/2119] lr: 4.0000e-02 eta: 16:33:02 time: 0.3338 data_time: 0.0219 memory: 5826 grad_norm: 3.0868 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9611 loss: 2.9611 2022/10/07 21:54:06 - mmengine - INFO - Epoch(train) [69][1600/2119] lr: 4.0000e-02 eta: 16:32:55 time: 0.3619 data_time: 0.0196 memory: 5826 grad_norm: 3.1043 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.5104 loss: 2.5104 2022/10/07 21:54:13 - mmengine - INFO - Epoch(train) [69][1620/2119] lr: 4.0000e-02 eta: 16:32:49 time: 0.3704 data_time: 0.0233 memory: 5826 grad_norm: 3.0964 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7343 loss: 2.7343 2022/10/07 21:54:19 - mmengine - INFO - Epoch(train) [69][1640/2119] lr: 4.0000e-02 eta: 16:32:41 time: 0.2876 data_time: 0.0187 memory: 5826 grad_norm: 3.0861 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.6301 loss: 2.6301 2022/10/07 21:54:27 - mmengine - INFO - Epoch(train) [69][1660/2119] lr: 4.0000e-02 eta: 16:32:35 time: 0.3840 data_time: 0.0261 memory: 5826 grad_norm: 3.1631 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.6024 loss: 2.6024 2022/10/07 21:54:33 - mmengine - INFO - Epoch(train) [69][1680/2119] lr: 4.0000e-02 eta: 16:32:27 time: 0.3287 data_time: 0.0262 memory: 5826 grad_norm: 3.1869 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6718 loss: 2.6718 2022/10/07 21:54:40 - mmengine - INFO - Epoch(train) [69][1700/2119] lr: 4.0000e-02 eta: 16:32:20 time: 0.3197 data_time: 0.0228 memory: 5826 grad_norm: 3.1540 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8863 loss: 2.8863 2022/10/07 21:54:47 - mmengine - INFO - Epoch(train) [69][1720/2119] lr: 4.0000e-02 eta: 16:32:13 time: 0.3701 data_time: 0.0236 memory: 5826 grad_norm: 3.1211 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6237 loss: 2.6237 2022/10/07 21:54:54 - mmengine - INFO - Epoch(train) [69][1740/2119] lr: 4.0000e-02 eta: 16:32:06 time: 0.3273 data_time: 0.0215 memory: 5826 grad_norm: 3.1012 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7841 loss: 2.7841 2022/10/07 21:55:02 - mmengine - INFO - Epoch(train) [69][1760/2119] lr: 4.0000e-02 eta: 16:32:00 time: 0.3946 data_time: 0.0195 memory: 5826 grad_norm: 3.1623 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7000 loss: 2.7000 2022/10/07 21:55:08 - mmengine - INFO - Epoch(train) [69][1780/2119] lr: 4.0000e-02 eta: 16:31:53 time: 0.3283 data_time: 0.0244 memory: 5826 grad_norm: 3.1849 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.9347 loss: 2.9347 2022/10/07 21:55:16 - mmengine - INFO - Epoch(train) [69][1800/2119] lr: 4.0000e-02 eta: 16:31:46 time: 0.3697 data_time: 0.0233 memory: 5826 grad_norm: 3.1122 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4638 loss: 2.4638 2022/10/07 21:55:23 - mmengine - INFO - Epoch(train) [69][1820/2119] lr: 4.0000e-02 eta: 16:31:40 time: 0.3574 data_time: 0.0252 memory: 5826 grad_norm: 3.1418 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6721 loss: 2.6721 2022/10/07 21:55:30 - mmengine - INFO - Epoch(train) [69][1840/2119] lr: 4.0000e-02 eta: 16:31:34 time: 0.3757 data_time: 0.0223 memory: 5826 grad_norm: 3.1100 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7865 loss: 2.7865 2022/10/07 21:55:36 - mmengine - INFO - Epoch(train) [69][1860/2119] lr: 4.0000e-02 eta: 16:31:25 time: 0.2868 data_time: 0.0282 memory: 5826 grad_norm: 3.0752 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9723 loss: 2.9723 2022/10/07 21:55:44 - mmengine - INFO - Epoch(train) [69][1880/2119] lr: 4.0000e-02 eta: 16:31:20 time: 0.4183 data_time: 0.0264 memory: 5826 grad_norm: 3.0610 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8227 loss: 2.8227 2022/10/07 21:55:50 - mmengine - INFO - Epoch(train) [69][1900/2119] lr: 4.0000e-02 eta: 16:31:12 time: 0.2903 data_time: 0.0271 memory: 5826 grad_norm: 3.1264 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7545 loss: 2.7545 2022/10/07 21:55:53 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 21:55:57 - mmengine - INFO - Epoch(train) [69][1920/2119] lr: 4.0000e-02 eta: 16:31:05 time: 0.3545 data_time: 0.0244 memory: 5826 grad_norm: 3.1673 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5592 loss: 2.5592 2022/10/07 21:56:04 - mmengine - INFO - Epoch(train) [69][1940/2119] lr: 4.0000e-02 eta: 16:30:58 time: 0.3482 data_time: 0.0213 memory: 5826 grad_norm: 3.1460 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.8307 loss: 2.8307 2022/10/07 21:56:11 - mmengine - INFO - Epoch(train) [69][1960/2119] lr: 4.0000e-02 eta: 16:30:52 time: 0.3604 data_time: 0.0170 memory: 5826 grad_norm: 3.0507 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7365 loss: 2.7365 2022/10/07 21:56:18 - mmengine - INFO - Epoch(train) [69][1980/2119] lr: 4.0000e-02 eta: 16:30:44 time: 0.3258 data_time: 0.0236 memory: 5826 grad_norm: 3.1686 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.7323 loss: 2.7323 2022/10/07 21:56:25 - mmengine - INFO - Epoch(train) [69][2000/2119] lr: 4.0000e-02 eta: 16:30:38 time: 0.3756 data_time: 0.0224 memory: 5826 grad_norm: 3.1112 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6758 loss: 2.6758 2022/10/07 21:56:32 - mmengine - INFO - Epoch(train) [69][2020/2119] lr: 4.0000e-02 eta: 16:30:30 time: 0.3053 data_time: 0.0215 memory: 5826 grad_norm: 3.0919 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8779 loss: 2.8779 2022/10/07 21:56:39 - mmengine - INFO - Epoch(train) [69][2040/2119] lr: 4.0000e-02 eta: 16:30:24 time: 0.3742 data_time: 0.0219 memory: 5826 grad_norm: 3.1244 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7141 loss: 2.7141 2022/10/07 21:56:45 - mmengine - INFO - Epoch(train) [69][2060/2119] lr: 4.0000e-02 eta: 16:30:16 time: 0.2901 data_time: 0.0265 memory: 5826 grad_norm: 3.1108 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8382 loss: 2.8382 2022/10/07 21:56:52 - mmengine - INFO - Epoch(train) [69][2080/2119] lr: 4.0000e-02 eta: 16:30:09 time: 0.3772 data_time: 0.0220 memory: 5826 grad_norm: 3.1545 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6235 loss: 2.6235 2022/10/07 21:56:59 - mmengine - INFO - Epoch(train) [69][2100/2119] lr: 4.0000e-02 eta: 16:30:02 time: 0.3188 data_time: 0.0181 memory: 5826 grad_norm: 3.1082 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7205 loss: 2.7205 2022/10/07 21:57:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 21:57:04 - mmengine - INFO - Epoch(train) [69][2119/2119] lr: 4.0000e-02 eta: 16:30:02 time: 0.2953 data_time: 0.0219 memory: 5826 grad_norm: 3.1821 top1_acc: 0.4000 top5_acc: 0.7000 loss_cls: 2.6806 loss: 2.6806 2022/10/07 21:57:14 - mmengine - INFO - Epoch(train) [70][20/2119] lr: 4.0000e-02 eta: 16:29:44 time: 0.4870 data_time: 0.1283 memory: 5826 grad_norm: 3.1329 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7332 loss: 2.7332 2022/10/07 21:57:21 - mmengine - INFO - Epoch(train) [70][40/2119] lr: 4.0000e-02 eta: 16:29:37 time: 0.3230 data_time: 0.0194 memory: 5826 grad_norm: 3.1040 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8160 loss: 2.8160 2022/10/07 21:57:28 - mmengine - INFO - Epoch(train) [70][60/2119] lr: 4.0000e-02 eta: 16:29:30 time: 0.3666 data_time: 0.0205 memory: 5826 grad_norm: 3.0834 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7057 loss: 2.7057 2022/10/07 21:57:35 - mmengine - INFO - Epoch(train) [70][80/2119] lr: 4.0000e-02 eta: 16:29:23 time: 0.3248 data_time: 0.0238 memory: 5826 grad_norm: 3.0682 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7528 loss: 2.7528 2022/10/07 21:57:42 - mmengine - INFO - Epoch(train) [70][100/2119] lr: 4.0000e-02 eta: 16:29:16 time: 0.3584 data_time: 0.0224 memory: 5826 grad_norm: 3.1329 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8873 loss: 2.8873 2022/10/07 21:57:48 - mmengine - INFO - Epoch(train) [70][120/2119] lr: 4.0000e-02 eta: 16:29:09 time: 0.3258 data_time: 0.0191 memory: 5826 grad_norm: 3.1295 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6375 loss: 2.6375 2022/10/07 21:57:55 - mmengine - INFO - Epoch(train) [70][140/2119] lr: 4.0000e-02 eta: 16:29:01 time: 0.3285 data_time: 0.0256 memory: 5826 grad_norm: 3.0836 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6321 loss: 2.6321 2022/10/07 21:58:02 - mmengine - INFO - Epoch(train) [70][160/2119] lr: 4.0000e-02 eta: 16:28:54 time: 0.3461 data_time: 0.0235 memory: 5826 grad_norm: 3.1378 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6021 loss: 2.6021 2022/10/07 21:58:09 - mmengine - INFO - Epoch(train) [70][180/2119] lr: 4.0000e-02 eta: 16:28:48 time: 0.3552 data_time: 0.0205 memory: 5826 grad_norm: 3.1270 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7100 loss: 2.7100 2022/10/07 21:58:16 - mmengine - INFO - Epoch(train) [70][200/2119] lr: 4.0000e-02 eta: 16:28:41 time: 0.3632 data_time: 0.0314 memory: 5826 grad_norm: 3.1940 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5593 loss: 2.5593 2022/10/07 21:58:23 - mmengine - INFO - Epoch(train) [70][220/2119] lr: 4.0000e-02 eta: 16:28:34 time: 0.3345 data_time: 0.0263 memory: 5826 grad_norm: 3.1123 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7402 loss: 2.7402 2022/10/07 21:58:30 - mmengine - INFO - Epoch(train) [70][240/2119] lr: 4.0000e-02 eta: 16:28:27 time: 0.3363 data_time: 0.0217 memory: 5826 grad_norm: 3.1566 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5009 loss: 2.5009 2022/10/07 21:58:36 - mmengine - INFO - Epoch(train) [70][260/2119] lr: 4.0000e-02 eta: 16:28:19 time: 0.3170 data_time: 0.0227 memory: 5826 grad_norm: 3.1762 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5698 loss: 2.5698 2022/10/07 21:58:43 - mmengine - INFO - Epoch(train) [70][280/2119] lr: 4.0000e-02 eta: 16:28:13 time: 0.3550 data_time: 0.0240 memory: 5826 grad_norm: 3.2022 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7087 loss: 2.7087 2022/10/07 21:58:50 - mmengine - INFO - Epoch(train) [70][300/2119] lr: 4.0000e-02 eta: 16:28:05 time: 0.3285 data_time: 0.0183 memory: 5826 grad_norm: 3.1162 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6552 loss: 2.6552 2022/10/07 21:58:57 - mmengine - INFO - Epoch(train) [70][320/2119] lr: 4.0000e-02 eta: 16:27:58 time: 0.3483 data_time: 0.0250 memory: 5826 grad_norm: 3.1782 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7730 loss: 2.7730 2022/10/07 21:59:03 - mmengine - INFO - Epoch(train) [70][340/2119] lr: 4.0000e-02 eta: 16:27:51 time: 0.3455 data_time: 0.0170 memory: 5826 grad_norm: 3.1075 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9521 loss: 2.9521 2022/10/07 21:59:11 - mmengine - INFO - Epoch(train) [70][360/2119] lr: 4.0000e-02 eta: 16:27:45 time: 0.3666 data_time: 0.0289 memory: 5826 grad_norm: 3.0795 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5855 loss: 2.5855 2022/10/07 21:59:17 - mmengine - INFO - Epoch(train) [70][380/2119] lr: 4.0000e-02 eta: 16:27:37 time: 0.3138 data_time: 0.0193 memory: 5826 grad_norm: 3.1359 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8303 loss: 2.8303 2022/10/07 21:59:25 - mmengine - INFO - Epoch(train) [70][400/2119] lr: 4.0000e-02 eta: 16:27:31 time: 0.3802 data_time: 0.0226 memory: 5826 grad_norm: 3.0782 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7780 loss: 2.7780 2022/10/07 21:59:31 - mmengine - INFO - Epoch(train) [70][420/2119] lr: 4.0000e-02 eta: 16:27:23 time: 0.3076 data_time: 0.0211 memory: 5826 grad_norm: 3.0734 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.5880 loss: 2.5880 2022/10/07 21:59:38 - mmengine - INFO - Epoch(train) [70][440/2119] lr: 4.0000e-02 eta: 16:27:16 time: 0.3395 data_time: 0.0227 memory: 5826 grad_norm: 3.0851 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9155 loss: 2.9155 2022/10/07 21:59:45 - mmengine - INFO - Epoch(train) [70][460/2119] lr: 4.0000e-02 eta: 16:27:10 time: 0.3604 data_time: 0.0249 memory: 5826 grad_norm: 3.1077 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.5695 loss: 2.5695 2022/10/07 21:59:52 - mmengine - INFO - Epoch(train) [70][480/2119] lr: 4.0000e-02 eta: 16:27:03 time: 0.3364 data_time: 0.0267 memory: 5826 grad_norm: 3.1203 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 2.4944 loss: 2.4944 2022/10/07 21:59:58 - mmengine - INFO - Epoch(train) [70][500/2119] lr: 4.0000e-02 eta: 16:26:55 time: 0.3242 data_time: 0.0209 memory: 5826 grad_norm: 3.1433 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7109 loss: 2.7109 2022/10/07 22:00:07 - mmengine - INFO - Epoch(train) [70][520/2119] lr: 4.0000e-02 eta: 16:26:50 time: 0.4299 data_time: 0.0237 memory: 5826 grad_norm: 3.1012 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6613 loss: 2.6613 2022/10/07 22:00:13 - mmengine - INFO - Epoch(train) [70][540/2119] lr: 4.0000e-02 eta: 16:26:43 time: 0.3396 data_time: 0.0210 memory: 5826 grad_norm: 3.0674 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6055 loss: 2.6055 2022/10/07 22:00:21 - mmengine - INFO - Epoch(train) [70][560/2119] lr: 4.0000e-02 eta: 16:26:37 time: 0.3767 data_time: 0.0276 memory: 5826 grad_norm: 3.0803 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.7216 loss: 2.7216 2022/10/07 22:00:27 - mmengine - INFO - Epoch(train) [70][580/2119] lr: 4.0000e-02 eta: 16:26:29 time: 0.3136 data_time: 0.0235 memory: 5826 grad_norm: 3.1279 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7818 loss: 2.7818 2022/10/07 22:00:35 - mmengine - INFO - Epoch(train) [70][600/2119] lr: 4.0000e-02 eta: 16:26:23 time: 0.3690 data_time: 0.0261 memory: 5826 grad_norm: 3.0695 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7844 loss: 2.7844 2022/10/07 22:00:40 - mmengine - INFO - Epoch(train) [70][620/2119] lr: 4.0000e-02 eta: 16:26:15 time: 0.2883 data_time: 0.0239 memory: 5826 grad_norm: 3.1363 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7420 loss: 2.7420 2022/10/07 22:00:47 - mmengine - INFO - Epoch(train) [70][640/2119] lr: 4.0000e-02 eta: 16:26:08 time: 0.3407 data_time: 0.0262 memory: 5826 grad_norm: 3.0966 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6454 loss: 2.6454 2022/10/07 22:00:54 - mmengine - INFO - Epoch(train) [70][660/2119] lr: 4.0000e-02 eta: 16:26:00 time: 0.3224 data_time: 0.0330 memory: 5826 grad_norm: 3.1586 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.7015 loss: 2.7015 2022/10/07 22:01:01 - mmengine - INFO - Epoch(train) [70][680/2119] lr: 4.0000e-02 eta: 16:25:53 time: 0.3574 data_time: 0.0262 memory: 5826 grad_norm: 3.1208 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8013 loss: 2.8013 2022/10/07 22:01:08 - mmengine - INFO - Epoch(train) [70][700/2119] lr: 4.0000e-02 eta: 16:25:47 time: 0.3475 data_time: 0.0277 memory: 5826 grad_norm: 3.1905 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.9450 loss: 2.9450 2022/10/07 22:01:15 - mmengine - INFO - Epoch(train) [70][720/2119] lr: 4.0000e-02 eta: 16:25:40 time: 0.3710 data_time: 0.0224 memory: 5826 grad_norm: 3.1440 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0760 loss: 3.0760 2022/10/07 22:01:22 - mmengine - INFO - Epoch(train) [70][740/2119] lr: 4.0000e-02 eta: 16:25:33 time: 0.3515 data_time: 0.0210 memory: 5826 grad_norm: 3.1317 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7198 loss: 2.7198 2022/10/07 22:01:29 - mmengine - INFO - Epoch(train) [70][760/2119] lr: 4.0000e-02 eta: 16:25:26 time: 0.3374 data_time: 0.0242 memory: 5826 grad_norm: 3.1341 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5462 loss: 2.5462 2022/10/07 22:01:36 - mmengine - INFO - Epoch(train) [70][780/2119] lr: 4.0000e-02 eta: 16:25:19 time: 0.3406 data_time: 0.0274 memory: 5826 grad_norm: 3.1700 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5386 loss: 2.5386 2022/10/07 22:01:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 22:01:42 - mmengine - INFO - Epoch(train) [70][800/2119] lr: 4.0000e-02 eta: 16:25:12 time: 0.3240 data_time: 0.0253 memory: 5826 grad_norm: 3.1231 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9404 loss: 2.9404 2022/10/07 22:01:49 - mmengine - INFO - Epoch(train) [70][820/2119] lr: 4.0000e-02 eta: 16:25:05 time: 0.3543 data_time: 0.0188 memory: 5826 grad_norm: 3.1225 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.5312 loss: 2.5312 2022/10/07 22:01:56 - mmengine - INFO - Epoch(train) [70][840/2119] lr: 4.0000e-02 eta: 16:24:58 time: 0.3377 data_time: 0.0284 memory: 5826 grad_norm: 3.0812 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.5012 loss: 2.5012 2022/10/07 22:02:02 - mmengine - INFO - Epoch(train) [70][860/2119] lr: 4.0000e-02 eta: 16:24:50 time: 0.3062 data_time: 0.0259 memory: 5826 grad_norm: 3.1505 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5558 loss: 2.5558 2022/10/07 22:02:10 - mmengine - INFO - Epoch(train) [70][880/2119] lr: 4.0000e-02 eta: 16:24:44 time: 0.3791 data_time: 0.0162 memory: 5826 grad_norm: 3.1075 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7148 loss: 2.7148 2022/10/07 22:02:17 - mmengine - INFO - Epoch(train) [70][900/2119] lr: 4.0000e-02 eta: 16:24:37 time: 0.3410 data_time: 0.0294 memory: 5826 grad_norm: 3.1232 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6281 loss: 2.6281 2022/10/07 22:02:23 - mmengine - INFO - Epoch(train) [70][920/2119] lr: 4.0000e-02 eta: 16:24:29 time: 0.3089 data_time: 0.0216 memory: 5826 grad_norm: 3.2030 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.9300 loss: 2.9300 2022/10/07 22:02:29 - mmengine - INFO - Epoch(train) [70][940/2119] lr: 4.0000e-02 eta: 16:24:22 time: 0.3250 data_time: 0.0218 memory: 5826 grad_norm: 3.0782 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6320 loss: 2.6320 2022/10/07 22:02:37 - mmengine - INFO - Epoch(train) [70][960/2119] lr: 4.0000e-02 eta: 16:24:16 time: 0.3895 data_time: 0.0229 memory: 5826 grad_norm: 3.1324 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7498 loss: 2.7498 2022/10/07 22:02:43 - mmengine - INFO - Epoch(train) [70][980/2119] lr: 4.0000e-02 eta: 16:24:08 time: 0.3016 data_time: 0.0220 memory: 5826 grad_norm: 3.0764 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.5715 loss: 2.5715 2022/10/07 22:02:50 - mmengine - INFO - Epoch(train) [70][1000/2119] lr: 4.0000e-02 eta: 16:24:01 time: 0.3535 data_time: 0.0198 memory: 5826 grad_norm: 3.1253 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.0182 loss: 3.0182 2022/10/07 22:02:57 - mmengine - INFO - Epoch(train) [70][1020/2119] lr: 4.0000e-02 eta: 16:23:54 time: 0.3383 data_time: 0.0303 memory: 5826 grad_norm: 3.1551 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7061 loss: 2.7061 2022/10/07 22:03:04 - mmengine - INFO - Epoch(train) [70][1040/2119] lr: 4.0000e-02 eta: 16:23:48 time: 0.3678 data_time: 0.0182 memory: 5826 grad_norm: 3.1414 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9011 loss: 2.9011 2022/10/07 22:03:11 - mmengine - INFO - Epoch(train) [70][1060/2119] lr: 4.0000e-02 eta: 16:23:40 time: 0.3035 data_time: 0.0223 memory: 5826 grad_norm: 3.1788 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8321 loss: 2.8321 2022/10/07 22:03:19 - mmengine - INFO - Epoch(train) [70][1080/2119] lr: 4.0000e-02 eta: 16:23:34 time: 0.4000 data_time: 0.0212 memory: 5826 grad_norm: 3.1301 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.8834 loss: 2.8834 2022/10/07 22:03:26 - mmengine - INFO - Epoch(train) [70][1100/2119] lr: 4.0000e-02 eta: 16:23:28 time: 0.3648 data_time: 0.0196 memory: 5826 grad_norm: 3.1195 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7709 loss: 2.7709 2022/10/07 22:03:33 - mmengine - INFO - Epoch(train) [70][1120/2119] lr: 4.0000e-02 eta: 16:23:21 time: 0.3665 data_time: 0.0208 memory: 5826 grad_norm: 3.0944 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6928 loss: 2.6928 2022/10/07 22:03:40 - mmengine - INFO - Epoch(train) [70][1140/2119] lr: 4.0000e-02 eta: 16:23:14 time: 0.3244 data_time: 0.0224 memory: 5826 grad_norm: 3.0842 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.5735 loss: 2.5735 2022/10/07 22:03:48 - mmengine - INFO - Epoch(train) [70][1160/2119] lr: 4.0000e-02 eta: 16:23:08 time: 0.4085 data_time: 0.0258 memory: 5826 grad_norm: 3.1010 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6743 loss: 2.6743 2022/10/07 22:03:55 - mmengine - INFO - Epoch(train) [70][1180/2119] lr: 4.0000e-02 eta: 16:23:01 time: 0.3528 data_time: 0.0248 memory: 5826 grad_norm: 3.1308 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6554 loss: 2.6554 2022/10/07 22:04:02 - mmengine - INFO - Epoch(train) [70][1200/2119] lr: 4.0000e-02 eta: 16:22:55 time: 0.3586 data_time: 0.0274 memory: 5826 grad_norm: 3.1073 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.4857 loss: 2.4857 2022/10/07 22:04:09 - mmengine - INFO - Epoch(train) [70][1220/2119] lr: 4.0000e-02 eta: 16:22:48 time: 0.3320 data_time: 0.0213 memory: 5826 grad_norm: 3.1254 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6690 loss: 2.6690 2022/10/07 22:04:16 - mmengine - INFO - Epoch(train) [70][1240/2119] lr: 4.0000e-02 eta: 16:22:41 time: 0.3825 data_time: 0.0272 memory: 5826 grad_norm: 3.0787 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7958 loss: 2.7958 2022/10/07 22:04:23 - mmengine - INFO - Epoch(train) [70][1260/2119] lr: 4.0000e-02 eta: 16:22:34 time: 0.3272 data_time: 0.0257 memory: 5826 grad_norm: 3.1466 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5180 loss: 2.5180 2022/10/07 22:04:30 - mmengine - INFO - Epoch(train) [70][1280/2119] lr: 4.0000e-02 eta: 16:22:28 time: 0.3692 data_time: 0.0255 memory: 5826 grad_norm: 3.1778 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.8624 loss: 2.8624 2022/10/07 22:04:37 - mmengine - INFO - Epoch(train) [70][1300/2119] lr: 4.0000e-02 eta: 16:22:20 time: 0.3160 data_time: 0.0210 memory: 5826 grad_norm: 3.1995 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.4793 loss: 2.4793 2022/10/07 22:04:44 - mmengine - INFO - Epoch(train) [70][1320/2119] lr: 4.0000e-02 eta: 16:22:13 time: 0.3552 data_time: 0.0237 memory: 5826 grad_norm: 3.1209 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5794 loss: 2.5794 2022/10/07 22:04:51 - mmengine - INFO - Epoch(train) [70][1340/2119] lr: 4.0000e-02 eta: 16:22:06 time: 0.3432 data_time: 0.0348 memory: 5826 grad_norm: 3.0597 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8583 loss: 2.8583 2022/10/07 22:04:58 - mmengine - INFO - Epoch(train) [70][1360/2119] lr: 4.0000e-02 eta: 16:22:00 time: 0.3474 data_time: 0.0224 memory: 5826 grad_norm: 3.1508 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6196 loss: 2.6196 2022/10/07 22:05:03 - mmengine - INFO - Epoch(train) [70][1380/2119] lr: 4.0000e-02 eta: 16:21:51 time: 0.2911 data_time: 0.0265 memory: 5826 grad_norm: 3.1516 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6147 loss: 2.6147 2022/10/07 22:05:11 - mmengine - INFO - Epoch(train) [70][1400/2119] lr: 4.0000e-02 eta: 16:21:46 time: 0.3975 data_time: 0.0184 memory: 5826 grad_norm: 3.1024 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.5833 loss: 2.5833 2022/10/07 22:05:18 - mmengine - INFO - Epoch(train) [70][1420/2119] lr: 4.0000e-02 eta: 16:21:39 time: 0.3442 data_time: 0.0178 memory: 5826 grad_norm: 3.1069 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5068 loss: 2.5068 2022/10/07 22:05:25 - mmengine - INFO - Epoch(train) [70][1440/2119] lr: 4.0000e-02 eta: 16:21:32 time: 0.3522 data_time: 0.0247 memory: 5826 grad_norm: 3.1547 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6633 loss: 2.6633 2022/10/07 22:05:32 - mmengine - INFO - Epoch(train) [70][1460/2119] lr: 4.0000e-02 eta: 16:21:25 time: 0.3286 data_time: 0.0250 memory: 5826 grad_norm: 3.0732 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7223 loss: 2.7223 2022/10/07 22:05:39 - mmengine - INFO - Epoch(train) [70][1480/2119] lr: 4.0000e-02 eta: 16:21:18 time: 0.3475 data_time: 0.0254 memory: 5826 grad_norm: 3.0718 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7823 loss: 2.7823 2022/10/07 22:05:46 - mmengine - INFO - Epoch(train) [70][1500/2119] lr: 4.0000e-02 eta: 16:21:11 time: 0.3540 data_time: 0.0242 memory: 5826 grad_norm: 3.1593 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9268 loss: 2.9268 2022/10/07 22:05:52 - mmengine - INFO - Epoch(train) [70][1520/2119] lr: 4.0000e-02 eta: 16:21:03 time: 0.3204 data_time: 0.0246 memory: 5826 grad_norm: 3.1914 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5776 loss: 2.5776 2022/10/07 22:06:00 - mmengine - INFO - Epoch(train) [70][1540/2119] lr: 4.0000e-02 eta: 16:20:57 time: 0.3843 data_time: 0.0211 memory: 5826 grad_norm: 3.1035 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8373 loss: 2.8373 2022/10/07 22:06:07 - mmengine - INFO - Epoch(train) [70][1560/2119] lr: 4.0000e-02 eta: 16:20:50 time: 0.3348 data_time: 0.0255 memory: 5826 grad_norm: 3.0940 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8801 loss: 2.8801 2022/10/07 22:06:13 - mmengine - INFO - Epoch(train) [70][1580/2119] lr: 4.0000e-02 eta: 16:20:43 time: 0.3269 data_time: 0.0192 memory: 5826 grad_norm: 3.1028 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6305 loss: 2.6305 2022/10/07 22:06:21 - mmengine - INFO - Epoch(train) [70][1600/2119] lr: 4.0000e-02 eta: 16:20:37 time: 0.3846 data_time: 0.0228 memory: 5826 grad_norm: 3.1859 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.6111 loss: 2.6111 2022/10/07 22:06:27 - mmengine - INFO - Epoch(train) [70][1620/2119] lr: 4.0000e-02 eta: 16:20:29 time: 0.3097 data_time: 0.0242 memory: 5826 grad_norm: 3.1496 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7639 loss: 2.7639 2022/10/07 22:06:35 - mmengine - INFO - Epoch(train) [70][1640/2119] lr: 4.0000e-02 eta: 16:20:23 time: 0.3744 data_time: 0.0248 memory: 5826 grad_norm: 3.1612 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7351 loss: 2.7351 2022/10/07 22:06:40 - mmengine - INFO - Epoch(train) [70][1660/2119] lr: 4.0000e-02 eta: 16:20:15 time: 0.2870 data_time: 0.0275 memory: 5826 grad_norm: 3.1399 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.4751 loss: 2.4751 2022/10/07 22:06:48 - mmengine - INFO - Epoch(train) [70][1680/2119] lr: 4.0000e-02 eta: 16:20:08 time: 0.3730 data_time: 0.0205 memory: 5826 grad_norm: 3.1011 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7466 loss: 2.7466 2022/10/07 22:06:55 - mmengine - INFO - Epoch(train) [70][1700/2119] lr: 4.0000e-02 eta: 16:20:01 time: 0.3398 data_time: 0.0267 memory: 5826 grad_norm: 3.1475 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7569 loss: 2.7569 2022/10/07 22:07:02 - mmengine - INFO - Epoch(train) [70][1720/2119] lr: 4.0000e-02 eta: 16:19:55 time: 0.3728 data_time: 0.0183 memory: 5826 grad_norm: 3.0846 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7120 loss: 2.7120 2022/10/07 22:07:08 - mmengine - INFO - Epoch(train) [70][1740/2119] lr: 4.0000e-02 eta: 16:19:47 time: 0.3160 data_time: 0.0272 memory: 5826 grad_norm: 3.1128 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9388 loss: 2.9388 2022/10/07 22:07:15 - mmengine - INFO - Epoch(train) [70][1760/2119] lr: 4.0000e-02 eta: 16:19:40 time: 0.3417 data_time: 0.0209 memory: 5826 grad_norm: 3.1160 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6460 loss: 2.6460 2022/10/07 22:07:21 - mmengine - INFO - Epoch(train) [70][1780/2119] lr: 4.0000e-02 eta: 16:19:32 time: 0.3045 data_time: 0.0293 memory: 5826 grad_norm: 3.1438 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9400 loss: 2.9400 2022/10/07 22:07:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 22:07:29 - mmengine - INFO - Epoch(train) [70][1800/2119] lr: 4.0000e-02 eta: 16:19:27 time: 0.3960 data_time: 0.0207 memory: 5826 grad_norm: 3.1280 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6474 loss: 2.6474 2022/10/07 22:07:36 - mmengine - INFO - Epoch(train) [70][1820/2119] lr: 4.0000e-02 eta: 16:19:20 time: 0.3452 data_time: 0.0274 memory: 5826 grad_norm: 3.1058 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6301 loss: 2.6301 2022/10/07 22:07:43 - mmengine - INFO - Epoch(train) [70][1840/2119] lr: 4.0000e-02 eta: 16:19:13 time: 0.3455 data_time: 0.0249 memory: 5826 grad_norm: 3.0940 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7289 loss: 2.7289 2022/10/07 22:07:49 - mmengine - INFO - Epoch(train) [70][1860/2119] lr: 4.0000e-02 eta: 16:19:05 time: 0.3158 data_time: 0.0244 memory: 5826 grad_norm: 3.2300 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5427 loss: 2.5427 2022/10/07 22:07:57 - mmengine - INFO - Epoch(train) [70][1880/2119] lr: 4.0000e-02 eta: 16:18:59 time: 0.3700 data_time: 0.0268 memory: 5826 grad_norm: 3.1385 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 3.0250 loss: 3.0250 2022/10/07 22:08:04 - mmengine - INFO - Epoch(train) [70][1900/2119] lr: 4.0000e-02 eta: 16:18:52 time: 0.3348 data_time: 0.0223 memory: 5826 grad_norm: 3.0910 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9136 loss: 2.9136 2022/10/07 22:08:11 - mmengine - INFO - Epoch(train) [70][1920/2119] lr: 4.0000e-02 eta: 16:18:45 time: 0.3506 data_time: 0.0260 memory: 5826 grad_norm: 3.1179 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8263 loss: 2.8263 2022/10/07 22:08:17 - mmengine - INFO - Epoch(train) [70][1940/2119] lr: 4.0000e-02 eta: 16:18:38 time: 0.3331 data_time: 0.0207 memory: 5826 grad_norm: 3.0823 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.6407 loss: 2.6407 2022/10/07 22:08:24 - mmengine - INFO - Epoch(train) [70][1960/2119] lr: 4.0000e-02 eta: 16:18:31 time: 0.3564 data_time: 0.0246 memory: 5826 grad_norm: 3.1363 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8641 loss: 2.8641 2022/10/07 22:08:30 - mmengine - INFO - Epoch(train) [70][1980/2119] lr: 4.0000e-02 eta: 16:18:23 time: 0.3063 data_time: 0.0253 memory: 5826 grad_norm: 3.0966 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6444 loss: 2.6444 2022/10/07 22:08:38 - mmengine - INFO - Epoch(train) [70][2000/2119] lr: 4.0000e-02 eta: 16:18:17 time: 0.3655 data_time: 0.0216 memory: 5826 grad_norm: 3.1350 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8179 loss: 2.8179 2022/10/07 22:08:44 - mmengine - INFO - Epoch(train) [70][2020/2119] lr: 4.0000e-02 eta: 16:18:09 time: 0.3212 data_time: 0.0239 memory: 5826 grad_norm: 3.0869 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7792 loss: 2.7792 2022/10/07 22:08:51 - mmengine - INFO - Epoch(train) [70][2040/2119] lr: 4.0000e-02 eta: 16:18:02 time: 0.3610 data_time: 0.0262 memory: 5826 grad_norm: 3.0563 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6839 loss: 2.6839 2022/10/07 22:08:58 - mmengine - INFO - Epoch(train) [70][2060/2119] lr: 4.0000e-02 eta: 16:17:55 time: 0.3271 data_time: 0.0268 memory: 5826 grad_norm: 3.1082 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.8615 loss: 2.8615 2022/10/07 22:09:05 - mmengine - INFO - Epoch(train) [70][2080/2119] lr: 4.0000e-02 eta: 16:17:48 time: 0.3475 data_time: 0.0253 memory: 5826 grad_norm: 3.1134 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7256 loss: 2.7256 2022/10/07 22:09:11 - mmengine - INFO - Epoch(train) [70][2100/2119] lr: 4.0000e-02 eta: 16:17:41 time: 0.3171 data_time: 0.0237 memory: 5826 grad_norm: 3.0767 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7383 loss: 2.7383 2022/10/07 22:09:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 22:09:18 - mmengine - INFO - Epoch(train) [70][2119/2119] lr: 4.0000e-02 eta: 16:17:41 time: 0.3637 data_time: 0.0169 memory: 5826 grad_norm: 3.1632 top1_acc: 0.3000 top5_acc: 0.7000 loss_cls: 2.7730 loss: 2.7730 2022/10/07 22:09:27 - mmengine - INFO - Epoch(val) [70][20/137] eta: 0:00:50 time: 0.4337 data_time: 0.3670 memory: 1241 2022/10/07 22:09:32 - mmengine - INFO - Epoch(val) [70][40/137] eta: 0:00:26 time: 0.2727 data_time: 0.2064 memory: 1241 2022/10/07 22:09:39 - mmengine - INFO - Epoch(val) [70][60/137] eta: 0:00:26 time: 0.3403 data_time: 0.2735 memory: 1241 2022/10/07 22:09:45 - mmengine - INFO - Epoch(val) [70][80/137] eta: 0:00:16 time: 0.2831 data_time: 0.2183 memory: 1241 2022/10/07 22:09:51 - mmengine - INFO - Epoch(val) [70][100/137] eta: 0:00:11 time: 0.3040 data_time: 0.2411 memory: 1241 2022/10/07 22:09:56 - mmengine - INFO - Epoch(val) [70][120/137] eta: 0:00:04 time: 0.2446 data_time: 0.1778 memory: 1241 2022/10/07 22:10:09 - mmengine - INFO - Epoch(val) [70][137/137] acc/top1: 0.4133 acc/top5: 0.6544 acc/mean1: 0.4131 2022/10/07 22:10:18 - mmengine - INFO - Epoch(train) [71][20/2119] lr: 4.0000e-02 eta: 16:17:22 time: 0.4611 data_time: 0.1836 memory: 5826 grad_norm: 3.1054 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8154 loss: 2.8154 2022/10/07 22:10:25 - mmengine - INFO - Epoch(train) [71][40/2119] lr: 4.0000e-02 eta: 16:17:15 time: 0.3327 data_time: 0.0207 memory: 5826 grad_norm: 3.0998 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6432 loss: 2.6432 2022/10/07 22:10:32 - mmengine - INFO - Epoch(train) [71][60/2119] lr: 4.0000e-02 eta: 16:17:08 time: 0.3550 data_time: 0.0260 memory: 5826 grad_norm: 3.1236 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7288 loss: 2.7288 2022/10/07 22:10:39 - mmengine - INFO - Epoch(train) [71][80/2119] lr: 4.0000e-02 eta: 16:17:02 time: 0.3534 data_time: 0.0354 memory: 5826 grad_norm: 3.1822 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.7684 loss: 2.7684 2022/10/07 22:10:46 - mmengine - INFO - Epoch(train) [71][100/2119] lr: 4.0000e-02 eta: 16:16:54 time: 0.3304 data_time: 0.0251 memory: 5826 grad_norm: 3.0923 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5344 loss: 2.5344 2022/10/07 22:10:53 - mmengine - INFO - Epoch(train) [71][120/2119] lr: 4.0000e-02 eta: 16:16:48 time: 0.3591 data_time: 0.0201 memory: 5826 grad_norm: 3.0769 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7898 loss: 2.7898 2022/10/07 22:10:59 - mmengine - INFO - Epoch(train) [71][140/2119] lr: 4.0000e-02 eta: 16:16:40 time: 0.3255 data_time: 0.0259 memory: 5826 grad_norm: 3.0864 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7725 loss: 2.7725 2022/10/07 22:11:07 - mmengine - INFO - Epoch(train) [71][160/2119] lr: 4.0000e-02 eta: 16:16:34 time: 0.3597 data_time: 0.0206 memory: 5826 grad_norm: 3.1047 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8209 loss: 2.8209 2022/10/07 22:11:14 - mmengine - INFO - Epoch(train) [71][180/2119] lr: 4.0000e-02 eta: 16:16:27 time: 0.3628 data_time: 0.0294 memory: 5826 grad_norm: 3.1828 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6284 loss: 2.6284 2022/10/07 22:11:21 - mmengine - INFO - Epoch(train) [71][200/2119] lr: 4.0000e-02 eta: 16:16:20 time: 0.3466 data_time: 0.0209 memory: 5826 grad_norm: 3.1324 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6584 loss: 2.6584 2022/10/07 22:11:27 - mmengine - INFO - Epoch(train) [71][220/2119] lr: 4.0000e-02 eta: 16:16:13 time: 0.3134 data_time: 0.0255 memory: 5826 grad_norm: 3.1435 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 3.0306 loss: 3.0306 2022/10/07 22:11:35 - mmengine - INFO - Epoch(train) [71][240/2119] lr: 4.0000e-02 eta: 16:16:06 time: 0.3748 data_time: 0.0368 memory: 5826 grad_norm: 3.1006 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4863 loss: 2.4863 2022/10/07 22:11:41 - mmengine - INFO - Epoch(train) [71][260/2119] lr: 4.0000e-02 eta: 16:15:59 time: 0.3371 data_time: 0.0226 memory: 5826 grad_norm: 3.1596 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3879 loss: 2.3879 2022/10/07 22:11:48 - mmengine - INFO - Epoch(train) [71][280/2119] lr: 4.0000e-02 eta: 16:15:52 time: 0.3257 data_time: 0.0200 memory: 5826 grad_norm: 3.0797 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8498 loss: 2.8498 2022/10/07 22:11:55 - mmengine - INFO - Epoch(train) [71][300/2119] lr: 4.0000e-02 eta: 16:15:45 time: 0.3519 data_time: 0.0260 memory: 5826 grad_norm: 3.0982 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6877 loss: 2.6877 2022/10/07 22:12:01 - mmengine - INFO - Epoch(train) [71][320/2119] lr: 4.0000e-02 eta: 16:15:38 time: 0.3239 data_time: 0.0235 memory: 5826 grad_norm: 3.1061 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6485 loss: 2.6485 2022/10/07 22:12:08 - mmengine - INFO - Epoch(train) [71][340/2119] lr: 4.0000e-02 eta: 16:15:30 time: 0.3296 data_time: 0.0270 memory: 5826 grad_norm: 3.1052 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7174 loss: 2.7174 2022/10/07 22:12:16 - mmengine - INFO - Epoch(train) [71][360/2119] lr: 4.0000e-02 eta: 16:15:24 time: 0.3794 data_time: 0.0214 memory: 5826 grad_norm: 3.1371 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7284 loss: 2.7284 2022/10/07 22:12:22 - mmengine - INFO - Epoch(train) [71][380/2119] lr: 4.0000e-02 eta: 16:15:17 time: 0.3327 data_time: 0.0266 memory: 5826 grad_norm: 3.1407 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7082 loss: 2.7082 2022/10/07 22:12:29 - mmengine - INFO - Epoch(train) [71][400/2119] lr: 4.0000e-02 eta: 16:15:10 time: 0.3522 data_time: 0.0210 memory: 5826 grad_norm: 3.1121 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6006 loss: 2.6006 2022/10/07 22:12:36 - mmengine - INFO - Epoch(train) [71][420/2119] lr: 4.0000e-02 eta: 16:15:03 time: 0.3441 data_time: 0.0236 memory: 5826 grad_norm: 3.1207 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8044 loss: 2.8044 2022/10/07 22:12:43 - mmengine - INFO - Epoch(train) [71][440/2119] lr: 4.0000e-02 eta: 16:14:56 time: 0.3424 data_time: 0.0228 memory: 5826 grad_norm: 3.0997 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7319 loss: 2.7319 2022/10/07 22:12:49 - mmengine - INFO - Epoch(train) [71][460/2119] lr: 4.0000e-02 eta: 16:14:49 time: 0.3202 data_time: 0.0253 memory: 5826 grad_norm: 3.0943 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6765 loss: 2.6765 2022/10/07 22:12:57 - mmengine - INFO - Epoch(train) [71][480/2119] lr: 4.0000e-02 eta: 16:14:43 time: 0.3863 data_time: 0.0199 memory: 5826 grad_norm: 3.0851 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6488 loss: 2.6488 2022/10/07 22:13:03 - mmengine - INFO - Epoch(train) [71][500/2119] lr: 4.0000e-02 eta: 16:14:34 time: 0.2850 data_time: 0.0270 memory: 5826 grad_norm: 3.1007 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8991 loss: 2.8991 2022/10/07 22:13:10 - mmengine - INFO - Epoch(train) [71][520/2119] lr: 4.0000e-02 eta: 16:14:28 time: 0.3504 data_time: 0.0227 memory: 5826 grad_norm: 3.1033 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9052 loss: 2.9052 2022/10/07 22:13:17 - mmengine - INFO - Epoch(train) [71][540/2119] lr: 4.0000e-02 eta: 16:14:21 time: 0.3524 data_time: 0.0239 memory: 5826 grad_norm: 3.1270 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7159 loss: 2.7159 2022/10/07 22:13:25 - mmengine - INFO - Epoch(train) [71][560/2119] lr: 4.0000e-02 eta: 16:14:15 time: 0.3873 data_time: 0.0192 memory: 5826 grad_norm: 3.1453 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8912 loss: 2.8912 2022/10/07 22:13:32 - mmengine - INFO - Epoch(train) [71][580/2119] lr: 4.0000e-02 eta: 16:14:08 time: 0.3379 data_time: 0.0205 memory: 5826 grad_norm: 3.1459 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6685 loss: 2.6685 2022/10/07 22:13:39 - mmengine - INFO - Epoch(train) [71][600/2119] lr: 4.0000e-02 eta: 16:14:01 time: 0.3699 data_time: 0.0164 memory: 5826 grad_norm: 3.1128 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6232 loss: 2.6232 2022/10/07 22:13:46 - mmengine - INFO - Epoch(train) [71][620/2119] lr: 4.0000e-02 eta: 16:13:54 time: 0.3384 data_time: 0.0292 memory: 5826 grad_norm: 3.1394 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6805 loss: 2.6805 2022/10/07 22:13:53 - mmengine - INFO - Epoch(train) [71][640/2119] lr: 4.0000e-02 eta: 16:13:48 time: 0.3699 data_time: 0.0184 memory: 5826 grad_norm: 3.1806 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6833 loss: 2.6833 2022/10/07 22:14:00 - mmengine - INFO - Epoch(train) [71][660/2119] lr: 4.0000e-02 eta: 16:13:41 time: 0.3459 data_time: 0.0247 memory: 5826 grad_norm: 3.0772 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7945 loss: 2.7945 2022/10/07 22:14:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 22:14:08 - mmengine - INFO - Epoch(train) [71][680/2119] lr: 4.0000e-02 eta: 16:13:35 time: 0.3773 data_time: 0.0165 memory: 5826 grad_norm: 3.0904 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7882 loss: 2.7882 2022/10/07 22:14:13 - mmengine - INFO - Epoch(train) [71][700/2119] lr: 4.0000e-02 eta: 16:13:27 time: 0.2908 data_time: 0.0262 memory: 5826 grad_norm: 3.1313 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7694 loss: 2.7694 2022/10/07 22:14:21 - mmengine - INFO - Epoch(train) [71][720/2119] lr: 4.0000e-02 eta: 16:13:20 time: 0.3764 data_time: 0.0221 memory: 5826 grad_norm: 3.1266 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6742 loss: 2.6742 2022/10/07 22:14:27 - mmengine - INFO - Epoch(train) [71][740/2119] lr: 4.0000e-02 eta: 16:13:13 time: 0.3276 data_time: 0.0252 memory: 5826 grad_norm: 3.1774 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6588 loss: 2.6588 2022/10/07 22:14:35 - mmengine - INFO - Epoch(train) [71][760/2119] lr: 4.0000e-02 eta: 16:13:06 time: 0.3520 data_time: 0.0275 memory: 5826 grad_norm: 3.1054 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7722 loss: 2.7722 2022/10/07 22:14:41 - mmengine - INFO - Epoch(train) [71][780/2119] lr: 4.0000e-02 eta: 16:12:59 time: 0.3282 data_time: 0.0237 memory: 5826 grad_norm: 3.0786 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6136 loss: 2.6136 2022/10/07 22:14:48 - mmengine - INFO - Epoch(train) [71][800/2119] lr: 4.0000e-02 eta: 16:12:52 time: 0.3638 data_time: 0.0236 memory: 5826 grad_norm: 3.1112 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6740 loss: 2.6740 2022/10/07 22:14:55 - mmengine - INFO - Epoch(train) [71][820/2119] lr: 4.0000e-02 eta: 16:12:45 time: 0.3355 data_time: 0.0275 memory: 5826 grad_norm: 3.0939 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6964 loss: 2.6964 2022/10/07 22:15:01 - mmengine - INFO - Epoch(train) [71][840/2119] lr: 4.0000e-02 eta: 16:12:37 time: 0.2834 data_time: 0.0281 memory: 5826 grad_norm: 3.1044 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.7156 loss: 2.7156 2022/10/07 22:15:08 - mmengine - INFO - Epoch(train) [71][860/2119] lr: 4.0000e-02 eta: 16:12:30 time: 0.3447 data_time: 0.0289 memory: 5826 grad_norm: 3.0990 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5392 loss: 2.5392 2022/10/07 22:15:15 - mmengine - INFO - Epoch(train) [71][880/2119] lr: 4.0000e-02 eta: 16:12:24 time: 0.3779 data_time: 0.0188 memory: 5826 grad_norm: 3.1436 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9143 loss: 2.9143 2022/10/07 22:15:21 - mmengine - INFO - Epoch(train) [71][900/2119] lr: 4.0000e-02 eta: 16:12:16 time: 0.3111 data_time: 0.0265 memory: 5826 grad_norm: 3.0716 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6960 loss: 2.6960 2022/10/07 22:15:29 - mmengine - INFO - Epoch(train) [71][920/2119] lr: 4.0000e-02 eta: 16:12:10 time: 0.3983 data_time: 0.0266 memory: 5826 grad_norm: 3.1458 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5879 loss: 2.5879 2022/10/07 22:15:36 - mmengine - INFO - Epoch(train) [71][940/2119] lr: 4.0000e-02 eta: 16:12:03 time: 0.3432 data_time: 0.0224 memory: 5826 grad_norm: 3.1512 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5588 loss: 2.5588 2022/10/07 22:15:44 - mmengine - INFO - Epoch(train) [71][960/2119] lr: 4.0000e-02 eta: 16:11:57 time: 0.3911 data_time: 0.0213 memory: 5826 grad_norm: 3.1555 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9237 loss: 2.9237 2022/10/07 22:15:51 - mmengine - INFO - Epoch(train) [71][980/2119] lr: 4.0000e-02 eta: 16:11:50 time: 0.3358 data_time: 0.0279 memory: 5826 grad_norm: 3.1241 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0488 loss: 3.0488 2022/10/07 22:15:58 - mmengine - INFO - Epoch(train) [71][1000/2119] lr: 4.0000e-02 eta: 16:11:43 time: 0.3326 data_time: 0.0214 memory: 5826 grad_norm: 3.0824 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5139 loss: 2.5139 2022/10/07 22:16:04 - mmengine - INFO - Epoch(train) [71][1020/2119] lr: 4.0000e-02 eta: 16:11:36 time: 0.3337 data_time: 0.0228 memory: 5826 grad_norm: 3.1594 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7962 loss: 2.7962 2022/10/07 22:16:11 - mmengine - INFO - Epoch(train) [71][1040/2119] lr: 4.0000e-02 eta: 16:11:29 time: 0.3587 data_time: 0.0190 memory: 5826 grad_norm: 3.1772 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8947 loss: 2.8947 2022/10/07 22:16:18 - mmengine - INFO - Epoch(train) [71][1060/2119] lr: 4.0000e-02 eta: 16:11:22 time: 0.3412 data_time: 0.0181 memory: 5826 grad_norm: 3.1884 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7464 loss: 2.7464 2022/10/07 22:16:25 - mmengine - INFO - Epoch(train) [71][1080/2119] lr: 4.0000e-02 eta: 16:11:16 time: 0.3590 data_time: 0.0207 memory: 5826 grad_norm: 3.1298 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5572 loss: 2.5572 2022/10/07 22:16:32 - mmengine - INFO - Epoch(train) [71][1100/2119] lr: 4.0000e-02 eta: 16:11:08 time: 0.3207 data_time: 0.0243 memory: 5826 grad_norm: 3.1811 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6554 loss: 2.6554 2022/10/07 22:16:39 - mmengine - INFO - Epoch(train) [71][1120/2119] lr: 4.0000e-02 eta: 16:11:01 time: 0.3580 data_time: 0.0217 memory: 5826 grad_norm: 3.1575 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6737 loss: 2.6737 2022/10/07 22:16:46 - mmengine - INFO - Epoch(train) [71][1140/2119] lr: 4.0000e-02 eta: 16:10:55 time: 0.3745 data_time: 0.0216 memory: 5826 grad_norm: 3.1273 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.6523 loss: 2.6523 2022/10/07 22:16:53 - mmengine - INFO - Epoch(train) [71][1160/2119] lr: 4.0000e-02 eta: 16:10:47 time: 0.3105 data_time: 0.0251 memory: 5826 grad_norm: 3.1306 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6560 loss: 2.6560 2022/10/07 22:17:01 - mmengine - INFO - Epoch(train) [71][1180/2119] lr: 4.0000e-02 eta: 16:10:42 time: 0.4037 data_time: 0.0210 memory: 5826 grad_norm: 3.1123 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7329 loss: 2.7329 2022/10/07 22:17:07 - mmengine - INFO - Epoch(train) [71][1200/2119] lr: 4.0000e-02 eta: 16:10:34 time: 0.3042 data_time: 0.0232 memory: 5826 grad_norm: 3.0738 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5140 loss: 2.5140 2022/10/07 22:17:14 - mmengine - INFO - Epoch(train) [71][1220/2119] lr: 4.0000e-02 eta: 16:10:27 time: 0.3330 data_time: 0.0237 memory: 5826 grad_norm: 3.0632 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6543 loss: 2.6543 2022/10/07 22:17:20 - mmengine - INFO - Epoch(train) [71][1240/2119] lr: 4.0000e-02 eta: 16:10:20 time: 0.3463 data_time: 0.0257 memory: 5826 grad_norm: 3.0679 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4870 loss: 2.4870 2022/10/07 22:17:27 - mmengine - INFO - Epoch(train) [71][1260/2119] lr: 4.0000e-02 eta: 16:10:12 time: 0.3266 data_time: 0.0282 memory: 5826 grad_norm: 3.1770 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7180 loss: 2.7180 2022/10/07 22:17:35 - mmengine - INFO - Epoch(train) [71][1280/2119] lr: 4.0000e-02 eta: 16:10:07 time: 0.4076 data_time: 0.0153 memory: 5826 grad_norm: 3.1228 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7738 loss: 2.7738 2022/10/07 22:17:42 - mmengine - INFO - Epoch(train) [71][1300/2119] lr: 4.0000e-02 eta: 16:10:00 time: 0.3264 data_time: 0.0272 memory: 5826 grad_norm: 3.1904 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5975 loss: 2.5975 2022/10/07 22:17:49 - mmengine - INFO - Epoch(train) [71][1320/2119] lr: 4.0000e-02 eta: 16:09:53 time: 0.3532 data_time: 0.0186 memory: 5826 grad_norm: 3.0462 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8281 loss: 2.8281 2022/10/07 22:17:55 - mmengine - INFO - Epoch(train) [71][1340/2119] lr: 4.0000e-02 eta: 16:09:45 time: 0.3220 data_time: 0.0426 memory: 5826 grad_norm: 3.1821 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8009 loss: 2.8009 2022/10/07 22:18:02 - mmengine - INFO - Epoch(train) [71][1360/2119] lr: 4.0000e-02 eta: 16:09:39 time: 0.3524 data_time: 0.0212 memory: 5826 grad_norm: 3.1622 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.6078 loss: 2.6078 2022/10/07 22:18:09 - mmengine - INFO - Epoch(train) [71][1380/2119] lr: 4.0000e-02 eta: 16:09:32 time: 0.3561 data_time: 0.0262 memory: 5826 grad_norm: 3.0710 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7904 loss: 2.7904 2022/10/07 22:18:17 - mmengine - INFO - Epoch(train) [71][1400/2119] lr: 4.0000e-02 eta: 16:09:25 time: 0.3578 data_time: 0.0226 memory: 5826 grad_norm: 3.1624 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7265 loss: 2.7265 2022/10/07 22:18:24 - mmengine - INFO - Epoch(train) [71][1420/2119] lr: 4.0000e-02 eta: 16:09:18 time: 0.3509 data_time: 0.0239 memory: 5826 grad_norm: 3.1217 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7319 loss: 2.7319 2022/10/07 22:18:31 - mmengine - INFO - Epoch(train) [71][1440/2119] lr: 4.0000e-02 eta: 16:09:12 time: 0.3700 data_time: 0.0160 memory: 5826 grad_norm: 3.0950 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8580 loss: 2.8580 2022/10/07 22:18:38 - mmengine - INFO - Epoch(train) [71][1460/2119] lr: 4.0000e-02 eta: 16:09:05 time: 0.3514 data_time: 0.0215 memory: 5826 grad_norm: 3.0782 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6710 loss: 2.6710 2022/10/07 22:18:45 - mmengine - INFO - Epoch(train) [71][1480/2119] lr: 4.0000e-02 eta: 16:08:59 time: 0.3677 data_time: 0.0223 memory: 5826 grad_norm: 3.1167 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6948 loss: 2.6948 2022/10/07 22:18:52 - mmengine - INFO - Epoch(train) [71][1500/2119] lr: 4.0000e-02 eta: 16:08:51 time: 0.3102 data_time: 0.0291 memory: 5826 grad_norm: 3.0749 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8093 loss: 2.8093 2022/10/07 22:18:59 - mmengine - INFO - Epoch(train) [71][1520/2119] lr: 4.0000e-02 eta: 16:08:45 time: 0.3868 data_time: 0.0161 memory: 5826 grad_norm: 3.1378 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9707 loss: 2.9707 2022/10/07 22:19:06 - mmengine - INFO - Epoch(train) [71][1540/2119] lr: 4.0000e-02 eta: 16:08:38 time: 0.3452 data_time: 0.0248 memory: 5826 grad_norm: 3.0654 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8955 loss: 2.8955 2022/10/07 22:19:13 - mmengine - INFO - Epoch(train) [71][1560/2119] lr: 4.0000e-02 eta: 16:08:32 time: 0.3606 data_time: 0.0247 memory: 5826 grad_norm: 3.1065 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7233 loss: 2.7233 2022/10/07 22:19:20 - mmengine - INFO - Epoch(train) [71][1580/2119] lr: 4.0000e-02 eta: 16:08:24 time: 0.3280 data_time: 0.0290 memory: 5826 grad_norm: 3.1634 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9546 loss: 2.9546 2022/10/07 22:19:28 - mmengine - INFO - Epoch(train) [71][1600/2119] lr: 4.0000e-02 eta: 16:08:19 time: 0.3986 data_time: 0.0200 memory: 5826 grad_norm: 3.1627 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9837 loss: 2.9837 2022/10/07 22:19:34 - mmengine - INFO - Epoch(train) [71][1620/2119] lr: 4.0000e-02 eta: 16:08:11 time: 0.3246 data_time: 0.0307 memory: 5826 grad_norm: 3.1405 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7364 loss: 2.7364 2022/10/07 22:19:42 - mmengine - INFO - Epoch(train) [71][1640/2119] lr: 4.0000e-02 eta: 16:08:05 time: 0.3947 data_time: 0.0209 memory: 5826 grad_norm: 3.1522 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5954 loss: 2.5954 2022/10/07 22:19:49 - mmengine - INFO - Epoch(train) [71][1660/2119] lr: 4.0000e-02 eta: 16:07:58 time: 0.3095 data_time: 0.0221 memory: 5826 grad_norm: 3.0866 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7702 loss: 2.7702 2022/10/07 22:19:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 22:19:57 - mmengine - INFO - Epoch(train) [71][1680/2119] lr: 4.0000e-02 eta: 16:07:52 time: 0.4054 data_time: 0.0238 memory: 5826 grad_norm: 3.1422 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7225 loss: 2.7225 2022/10/07 22:20:03 - mmengine - INFO - Epoch(train) [71][1700/2119] lr: 4.0000e-02 eta: 16:07:44 time: 0.3157 data_time: 0.0236 memory: 5826 grad_norm: 3.1005 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.7682 loss: 2.7682 2022/10/07 22:20:10 - mmengine - INFO - Epoch(train) [71][1720/2119] lr: 4.0000e-02 eta: 16:07:38 time: 0.3673 data_time: 0.0265 memory: 5826 grad_norm: 3.1114 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5199 loss: 2.5199 2022/10/07 22:20:17 - mmengine - INFO - Epoch(train) [71][1740/2119] lr: 4.0000e-02 eta: 16:07:31 time: 0.3342 data_time: 0.0208 memory: 5826 grad_norm: 3.1168 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7324 loss: 2.7324 2022/10/07 22:20:23 - mmengine - INFO - Epoch(train) [71][1760/2119] lr: 4.0000e-02 eta: 16:07:23 time: 0.3130 data_time: 0.0243 memory: 5826 grad_norm: 3.1673 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7708 loss: 2.7708 2022/10/07 22:20:30 - mmengine - INFO - Epoch(train) [71][1780/2119] lr: 4.0000e-02 eta: 16:07:16 time: 0.3456 data_time: 0.0269 memory: 5826 grad_norm: 3.1444 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.7845 loss: 2.7845 2022/10/07 22:20:39 - mmengine - INFO - Epoch(train) [71][1800/2119] lr: 4.0000e-02 eta: 16:07:11 time: 0.4304 data_time: 0.0178 memory: 5826 grad_norm: 3.0888 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.6859 loss: 2.6859 2022/10/07 22:20:46 - mmengine - INFO - Epoch(train) [71][1820/2119] lr: 4.0000e-02 eta: 16:07:04 time: 0.3533 data_time: 0.0271 memory: 5826 grad_norm: 3.1539 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6575 loss: 2.6575 2022/10/07 22:20:52 - mmengine - INFO - Epoch(train) [71][1840/2119] lr: 4.0000e-02 eta: 16:06:56 time: 0.2911 data_time: 0.0206 memory: 5826 grad_norm: 3.1639 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.9132 loss: 2.9132 2022/10/07 22:20:59 - mmengine - INFO - Epoch(train) [71][1860/2119] lr: 4.0000e-02 eta: 16:06:50 time: 0.3646 data_time: 0.0300 memory: 5826 grad_norm: 3.0449 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.0021 loss: 3.0021 2022/10/07 22:21:06 - mmengine - INFO - Epoch(train) [71][1880/2119] lr: 4.0000e-02 eta: 16:06:43 time: 0.3639 data_time: 0.0219 memory: 5826 grad_norm: 3.1644 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7208 loss: 2.7208 2022/10/07 22:21:12 - mmengine - INFO - Epoch(train) [71][1900/2119] lr: 4.0000e-02 eta: 16:06:35 time: 0.3036 data_time: 0.0271 memory: 5826 grad_norm: 3.1389 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6464 loss: 2.6464 2022/10/07 22:21:20 - mmengine - INFO - Epoch(train) [71][1920/2119] lr: 4.0000e-02 eta: 16:06:30 time: 0.4044 data_time: 0.0176 memory: 5826 grad_norm: 3.1222 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0417 loss: 3.0417 2022/10/07 22:21:27 - mmengine - INFO - Epoch(train) [71][1940/2119] lr: 4.0000e-02 eta: 16:06:22 time: 0.3312 data_time: 0.0215 memory: 5826 grad_norm: 3.1030 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6181 loss: 2.6181 2022/10/07 22:21:35 - mmengine - INFO - Epoch(train) [71][1960/2119] lr: 4.0000e-02 eta: 16:06:17 time: 0.3933 data_time: 0.0202 memory: 5826 grad_norm: 3.0660 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5514 loss: 2.5514 2022/10/07 22:21:41 - mmengine - INFO - Epoch(train) [71][1980/2119] lr: 4.0000e-02 eta: 16:06:09 time: 0.2943 data_time: 0.0246 memory: 5826 grad_norm: 3.0434 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5198 loss: 2.5198 2022/10/07 22:21:48 - mmengine - INFO - Epoch(train) [71][2000/2119] lr: 4.0000e-02 eta: 16:06:02 time: 0.3600 data_time: 0.0201 memory: 5826 grad_norm: 3.1110 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0390 loss: 3.0390 2022/10/07 22:21:55 - mmengine - INFO - Epoch(train) [71][2020/2119] lr: 4.0000e-02 eta: 16:05:55 time: 0.3317 data_time: 0.0301 memory: 5826 grad_norm: 3.1721 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8920 loss: 2.8920 2022/10/07 22:22:02 - mmengine - INFO - Epoch(train) [71][2040/2119] lr: 4.0000e-02 eta: 16:05:48 time: 0.3405 data_time: 0.0244 memory: 5826 grad_norm: 3.1339 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7099 loss: 2.7099 2022/10/07 22:22:08 - mmengine - INFO - Epoch(train) [71][2060/2119] lr: 4.0000e-02 eta: 16:05:40 time: 0.3170 data_time: 0.0243 memory: 5826 grad_norm: 3.1100 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7142 loss: 2.7142 2022/10/07 22:22:16 - mmengine - INFO - Epoch(train) [71][2080/2119] lr: 4.0000e-02 eta: 16:05:34 time: 0.3920 data_time: 0.0173 memory: 5826 grad_norm: 3.0892 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6376 loss: 2.6376 2022/10/07 22:22:22 - mmengine - INFO - Epoch(train) [71][2100/2119] lr: 4.0000e-02 eta: 16:05:26 time: 0.3035 data_time: 0.0210 memory: 5826 grad_norm: 3.1146 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5753 loss: 2.5753 2022/10/07 22:22:28 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 22:22:28 - mmengine - INFO - Epoch(train) [71][2119/2119] lr: 4.0000e-02 eta: 16:05:26 time: 0.3164 data_time: 0.0177 memory: 5826 grad_norm: 3.1820 top1_acc: 0.4000 top5_acc: 0.5000 loss_cls: 2.6884 loss: 2.6884 2022/10/07 22:22:38 - mmengine - INFO - Epoch(train) [72][20/2119] lr: 4.0000e-02 eta: 16:05:09 time: 0.4896 data_time: 0.1204 memory: 5826 grad_norm: 3.1704 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.1224 loss: 3.1224 2022/10/07 22:22:45 - mmengine - INFO - Epoch(train) [72][40/2119] lr: 4.0000e-02 eta: 16:05:02 time: 0.3574 data_time: 0.0187 memory: 5826 grad_norm: 3.1659 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7285 loss: 2.7285 2022/10/07 22:22:52 - mmengine - INFO - Epoch(train) [72][60/2119] lr: 4.0000e-02 eta: 16:04:55 time: 0.3489 data_time: 0.0224 memory: 5826 grad_norm: 3.1591 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.6231 loss: 2.6231 2022/10/07 22:22:58 - mmengine - INFO - Epoch(train) [72][80/2119] lr: 4.0000e-02 eta: 16:04:48 time: 0.3179 data_time: 0.0269 memory: 5826 grad_norm: 3.1654 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6235 loss: 2.6235 2022/10/07 22:23:05 - mmengine - INFO - Epoch(train) [72][100/2119] lr: 4.0000e-02 eta: 16:04:41 time: 0.3535 data_time: 0.0242 memory: 5826 grad_norm: 3.1163 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5158 loss: 2.5158 2022/10/07 22:23:12 - mmengine - INFO - Epoch(train) [72][120/2119] lr: 4.0000e-02 eta: 16:04:33 time: 0.3238 data_time: 0.0244 memory: 5826 grad_norm: 3.0830 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5494 loss: 2.5494 2022/10/07 22:23:19 - mmengine - INFO - Epoch(train) [72][140/2119] lr: 4.0000e-02 eta: 16:04:27 time: 0.3514 data_time: 0.0277 memory: 5826 grad_norm: 3.1999 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7232 loss: 2.7232 2022/10/07 22:23:26 - mmengine - INFO - Epoch(train) [72][160/2119] lr: 4.0000e-02 eta: 16:04:20 time: 0.3379 data_time: 0.0237 memory: 5826 grad_norm: 3.0841 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6924 loss: 2.6924 2022/10/07 22:23:32 - mmengine - INFO - Epoch(train) [72][180/2119] lr: 4.0000e-02 eta: 16:04:12 time: 0.3374 data_time: 0.0199 memory: 5826 grad_norm: 3.1269 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6195 loss: 2.6195 2022/10/07 22:23:39 - mmengine - INFO - Epoch(train) [72][200/2119] lr: 4.0000e-02 eta: 16:04:06 time: 0.3520 data_time: 0.0228 memory: 5826 grad_norm: 3.1490 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5989 loss: 2.5989 2022/10/07 22:23:47 - mmengine - INFO - Epoch(train) [72][220/2119] lr: 4.0000e-02 eta: 16:03:59 time: 0.3581 data_time: 0.0238 memory: 5826 grad_norm: 3.1094 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8756 loss: 2.8756 2022/10/07 22:23:53 - mmengine - INFO - Epoch(train) [72][240/2119] lr: 4.0000e-02 eta: 16:03:52 time: 0.3278 data_time: 0.0210 memory: 5826 grad_norm: 3.1379 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7132 loss: 2.7132 2022/10/07 22:24:01 - mmengine - INFO - Epoch(train) [72][260/2119] lr: 4.0000e-02 eta: 16:03:46 time: 0.3924 data_time: 0.0279 memory: 5826 grad_norm: 3.1262 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6355 loss: 2.6355 2022/10/07 22:24:07 - mmengine - INFO - Epoch(train) [72][280/2119] lr: 4.0000e-02 eta: 16:03:38 time: 0.3050 data_time: 0.0261 memory: 5826 grad_norm: 3.0835 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7133 loss: 2.7133 2022/10/07 22:24:14 - mmengine - INFO - Epoch(train) [72][300/2119] lr: 4.0000e-02 eta: 16:03:31 time: 0.3231 data_time: 0.0255 memory: 5826 grad_norm: 3.1273 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5964 loss: 2.5964 2022/10/07 22:24:21 - mmengine - INFO - Epoch(train) [72][320/2119] lr: 4.0000e-02 eta: 16:03:24 time: 0.3766 data_time: 0.0226 memory: 5826 grad_norm: 3.1383 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6483 loss: 2.6483 2022/10/07 22:24:28 - mmengine - INFO - Epoch(train) [72][340/2119] lr: 4.0000e-02 eta: 16:03:17 time: 0.3215 data_time: 0.0224 memory: 5826 grad_norm: 3.1700 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8276 loss: 2.8276 2022/10/07 22:24:37 - mmengine - INFO - Epoch(train) [72][360/2119] lr: 4.0000e-02 eta: 16:03:12 time: 0.4482 data_time: 0.0244 memory: 5826 grad_norm: 3.1434 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5961 loss: 2.5961 2022/10/07 22:24:42 - mmengine - INFO - Epoch(train) [72][380/2119] lr: 4.0000e-02 eta: 16:03:04 time: 0.2869 data_time: 0.0250 memory: 5826 grad_norm: 3.1300 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7920 loss: 2.7920 2022/10/07 22:24:49 - mmengine - INFO - Epoch(train) [72][400/2119] lr: 4.0000e-02 eta: 16:02:57 time: 0.3511 data_time: 0.0212 memory: 5826 grad_norm: 3.0893 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6005 loss: 2.6005 2022/10/07 22:24:55 - mmengine - INFO - Epoch(train) [72][420/2119] lr: 4.0000e-02 eta: 16:02:49 time: 0.3103 data_time: 0.0266 memory: 5826 grad_norm: 3.1559 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8531 loss: 2.8531 2022/10/07 22:25:03 - mmengine - INFO - Epoch(train) [72][440/2119] lr: 4.0000e-02 eta: 16:02:43 time: 0.3575 data_time: 0.0224 memory: 5826 grad_norm: 3.1287 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9266 loss: 2.9266 2022/10/07 22:25:09 - mmengine - INFO - Epoch(train) [72][460/2119] lr: 4.0000e-02 eta: 16:02:36 time: 0.3356 data_time: 0.0232 memory: 5826 grad_norm: 3.0499 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8380 loss: 2.8380 2022/10/07 22:25:17 - mmengine - INFO - Epoch(train) [72][480/2119] lr: 4.0000e-02 eta: 16:02:30 time: 0.3942 data_time: 0.0213 memory: 5826 grad_norm: 3.1060 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4950 loss: 2.4950 2022/10/07 22:25:23 - mmengine - INFO - Epoch(train) [72][500/2119] lr: 4.0000e-02 eta: 16:02:22 time: 0.3030 data_time: 0.0257 memory: 5826 grad_norm: 3.1981 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6304 loss: 2.6304 2022/10/07 22:25:30 - mmengine - INFO - Epoch(train) [72][520/2119] lr: 4.0000e-02 eta: 16:02:15 time: 0.3518 data_time: 0.0251 memory: 5826 grad_norm: 3.1620 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7672 loss: 2.7672 2022/10/07 22:25:37 - mmengine - INFO - Epoch(train) [72][540/2119] lr: 4.0000e-02 eta: 16:02:08 time: 0.3391 data_time: 0.0277 memory: 5826 grad_norm: 3.0889 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5158 loss: 2.5158 2022/10/07 22:25:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 22:25:44 - mmengine - INFO - Epoch(train) [72][560/2119] lr: 4.0000e-02 eta: 16:02:02 time: 0.3621 data_time: 0.0202 memory: 5826 grad_norm: 3.1074 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8472 loss: 2.8472 2022/10/07 22:25:51 - mmengine - INFO - Epoch(train) [72][580/2119] lr: 4.0000e-02 eta: 16:01:55 time: 0.3530 data_time: 0.0285 memory: 5826 grad_norm: 3.1233 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6840 loss: 2.6840 2022/10/07 22:26:00 - mmengine - INFO - Epoch(train) [72][600/2119] lr: 4.0000e-02 eta: 16:01:49 time: 0.4027 data_time: 0.0186 memory: 5826 grad_norm: 3.1645 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8385 loss: 2.8385 2022/10/07 22:26:06 - mmengine - INFO - Epoch(train) [72][620/2119] lr: 4.0000e-02 eta: 16:01:42 time: 0.3324 data_time: 0.0235 memory: 5826 grad_norm: 3.1131 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6430 loss: 2.6430 2022/10/07 22:26:14 - mmengine - INFO - Epoch(train) [72][640/2119] lr: 4.0000e-02 eta: 16:01:36 time: 0.3882 data_time: 0.0177 memory: 5826 grad_norm: 3.2061 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6198 loss: 2.6198 2022/10/07 22:26:20 - mmengine - INFO - Epoch(train) [72][660/2119] lr: 4.0000e-02 eta: 16:01:28 time: 0.3085 data_time: 0.0233 memory: 5826 grad_norm: 3.1353 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7579 loss: 2.7579 2022/10/07 22:26:27 - mmengine - INFO - Epoch(train) [72][680/2119] lr: 4.0000e-02 eta: 16:01:21 time: 0.3551 data_time: 0.0266 memory: 5826 grad_norm: 3.0879 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3731 loss: 2.3731 2022/10/07 22:26:34 - mmengine - INFO - Epoch(train) [72][700/2119] lr: 4.0000e-02 eta: 16:01:14 time: 0.3410 data_time: 0.0218 memory: 5826 grad_norm: 3.1333 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7666 loss: 2.7666 2022/10/07 22:26:42 - mmengine - INFO - Epoch(train) [72][720/2119] lr: 4.0000e-02 eta: 16:01:08 time: 0.3818 data_time: 0.0359 memory: 5826 grad_norm: 3.0974 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5095 loss: 2.5095 2022/10/07 22:26:48 - mmengine - INFO - Epoch(train) [72][740/2119] lr: 4.0000e-02 eta: 16:01:01 time: 0.3408 data_time: 0.0200 memory: 5826 grad_norm: 3.1015 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6672 loss: 2.6672 2022/10/07 22:26:57 - mmengine - INFO - Epoch(train) [72][760/2119] lr: 4.0000e-02 eta: 16:00:56 time: 0.4033 data_time: 0.0220 memory: 5826 grad_norm: 3.1364 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8360 loss: 2.8360 2022/10/07 22:27:03 - mmengine - INFO - Epoch(train) [72][780/2119] lr: 4.0000e-02 eta: 16:00:48 time: 0.3249 data_time: 0.0242 memory: 5826 grad_norm: 3.1684 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7540 loss: 2.7540 2022/10/07 22:27:11 - mmengine - INFO - Epoch(train) [72][800/2119] lr: 4.0000e-02 eta: 16:00:43 time: 0.4051 data_time: 0.0217 memory: 5826 grad_norm: 3.1309 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8117 loss: 2.8117 2022/10/07 22:27:17 - mmengine - INFO - Epoch(train) [72][820/2119] lr: 4.0000e-02 eta: 16:00:35 time: 0.2949 data_time: 0.0240 memory: 5826 grad_norm: 3.0790 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8305 loss: 2.8305 2022/10/07 22:27:25 - mmengine - INFO - Epoch(train) [72][840/2119] lr: 4.0000e-02 eta: 16:00:29 time: 0.3980 data_time: 0.0198 memory: 5826 grad_norm: 3.1179 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8534 loss: 2.8534 2022/10/07 22:27:31 - mmengine - INFO - Epoch(train) [72][860/2119] lr: 4.0000e-02 eta: 16:00:21 time: 0.3218 data_time: 0.0250 memory: 5826 grad_norm: 3.0591 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9896 loss: 2.9896 2022/10/07 22:27:40 - mmengine - INFO - Epoch(train) [72][880/2119] lr: 4.0000e-02 eta: 16:00:16 time: 0.4014 data_time: 0.0236 memory: 5826 grad_norm: 3.1281 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.5675 loss: 2.5675 2022/10/07 22:27:47 - mmengine - INFO - Epoch(train) [72][900/2119] lr: 4.0000e-02 eta: 16:00:09 time: 0.3766 data_time: 0.0242 memory: 5826 grad_norm: 3.1388 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5474 loss: 2.5474 2022/10/07 22:27:54 - mmengine - INFO - Epoch(train) [72][920/2119] lr: 4.0000e-02 eta: 16:00:03 time: 0.3553 data_time: 0.0178 memory: 5826 grad_norm: 3.1523 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7134 loss: 2.7134 2022/10/07 22:28:02 - mmengine - INFO - Epoch(train) [72][940/2119] lr: 4.0000e-02 eta: 15:59:56 time: 0.3818 data_time: 0.0226 memory: 5826 grad_norm: 3.0763 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6854 loss: 2.6854 2022/10/07 22:28:09 - mmengine - INFO - Epoch(train) [72][960/2119] lr: 4.0000e-02 eta: 15:59:50 time: 0.3636 data_time: 0.0248 memory: 5826 grad_norm: 3.1440 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5841 loss: 2.5841 2022/10/07 22:28:17 - mmengine - INFO - Epoch(train) [72][980/2119] lr: 4.0000e-02 eta: 15:59:44 time: 0.3758 data_time: 0.0271 memory: 5826 grad_norm: 3.0922 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8578 loss: 2.8578 2022/10/07 22:28:24 - mmengine - INFO - Epoch(train) [72][1000/2119] lr: 4.0000e-02 eta: 15:59:38 time: 0.3939 data_time: 0.0198 memory: 5826 grad_norm: 3.1044 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9956 loss: 2.9956 2022/10/07 22:28:31 - mmengine - INFO - Epoch(train) [72][1020/2119] lr: 4.0000e-02 eta: 15:59:31 time: 0.3353 data_time: 0.0186 memory: 5826 grad_norm: 3.1043 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6588 loss: 2.6588 2022/10/07 22:28:39 - mmengine - INFO - Epoch(train) [72][1040/2119] lr: 4.0000e-02 eta: 15:59:24 time: 0.3740 data_time: 0.0207 memory: 5826 grad_norm: 3.1302 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9117 loss: 2.9117 2022/10/07 22:28:45 - mmengine - INFO - Epoch(train) [72][1060/2119] lr: 4.0000e-02 eta: 15:59:17 time: 0.3327 data_time: 0.0232 memory: 5826 grad_norm: 3.1159 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8591 loss: 2.8591 2022/10/07 22:28:53 - mmengine - INFO - Epoch(train) [72][1080/2119] lr: 4.0000e-02 eta: 15:59:11 time: 0.4034 data_time: 0.0236 memory: 5826 grad_norm: 3.1156 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5843 loss: 2.5843 2022/10/07 22:29:00 - mmengine - INFO - Epoch(train) [72][1100/2119] lr: 4.0000e-02 eta: 15:59:04 time: 0.3250 data_time: 0.0220 memory: 5826 grad_norm: 3.1692 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8146 loss: 2.8146 2022/10/07 22:29:08 - mmengine - INFO - Epoch(train) [72][1120/2119] lr: 4.0000e-02 eta: 15:58:58 time: 0.3848 data_time: 0.0185 memory: 5826 grad_norm: 3.1205 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8950 loss: 2.8950 2022/10/07 22:29:14 - mmengine - INFO - Epoch(train) [72][1140/2119] lr: 4.0000e-02 eta: 15:58:51 time: 0.3219 data_time: 0.0209 memory: 5826 grad_norm: 3.0545 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7056 loss: 2.7056 2022/10/07 22:29:22 - mmengine - INFO - Epoch(train) [72][1160/2119] lr: 4.0000e-02 eta: 15:58:44 time: 0.3813 data_time: 0.0253 memory: 5826 grad_norm: 3.1356 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7248 loss: 2.7248 2022/10/07 22:29:29 - mmengine - INFO - Epoch(train) [72][1180/2119] lr: 4.0000e-02 eta: 15:58:38 time: 0.3496 data_time: 0.0232 memory: 5826 grad_norm: 3.1032 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7570 loss: 2.7570 2022/10/07 22:29:36 - mmengine - INFO - Epoch(train) [72][1200/2119] lr: 4.0000e-02 eta: 15:58:31 time: 0.3728 data_time: 0.0262 memory: 5826 grad_norm: 3.1231 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9685 loss: 2.9685 2022/10/07 22:29:42 - mmengine - INFO - Epoch(train) [72][1220/2119] lr: 4.0000e-02 eta: 15:58:24 time: 0.3115 data_time: 0.0262 memory: 5826 grad_norm: 3.1329 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7905 loss: 2.7905 2022/10/07 22:29:50 - mmengine - INFO - Epoch(train) [72][1240/2119] lr: 4.0000e-02 eta: 15:58:17 time: 0.3705 data_time: 0.0231 memory: 5826 grad_norm: 3.1212 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5975 loss: 2.5975 2022/10/07 22:29:56 - mmengine - INFO - Epoch(train) [72][1260/2119] lr: 4.0000e-02 eta: 15:58:09 time: 0.2873 data_time: 0.0246 memory: 5826 grad_norm: 3.0998 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.7337 loss: 2.7337 2022/10/07 22:30:02 - mmengine - INFO - Epoch(train) [72][1280/2119] lr: 4.0000e-02 eta: 15:58:02 time: 0.3450 data_time: 0.0277 memory: 5826 grad_norm: 3.1793 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0075 loss: 3.0075 2022/10/07 22:30:10 - mmengine - INFO - Epoch(train) [72][1300/2119] lr: 4.0000e-02 eta: 15:57:56 time: 0.3780 data_time: 0.0268 memory: 5826 grad_norm: 3.1447 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9195 loss: 2.9195 2022/10/07 22:30:17 - mmengine - INFO - Epoch(train) [72][1320/2119] lr: 4.0000e-02 eta: 15:57:49 time: 0.3345 data_time: 0.0300 memory: 5826 grad_norm: 3.1299 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6786 loss: 2.6786 2022/10/07 22:30:23 - mmengine - INFO - Epoch(train) [72][1340/2119] lr: 4.0000e-02 eta: 15:57:41 time: 0.3235 data_time: 0.0286 memory: 5826 grad_norm: 3.1212 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7397 loss: 2.7397 2022/10/07 22:30:31 - mmengine - INFO - Epoch(train) [72][1360/2119] lr: 4.0000e-02 eta: 15:57:35 time: 0.3781 data_time: 0.0214 memory: 5826 grad_norm: 3.1469 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6117 loss: 2.6117 2022/10/07 22:30:37 - mmengine - INFO - Epoch(train) [72][1380/2119] lr: 4.0000e-02 eta: 15:57:28 time: 0.3289 data_time: 0.0232 memory: 5826 grad_norm: 3.1930 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9242 loss: 2.9242 2022/10/07 22:30:45 - mmengine - INFO - Epoch(train) [72][1400/2119] lr: 4.0000e-02 eta: 15:57:21 time: 0.3724 data_time: 0.0191 memory: 5826 grad_norm: 3.1388 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5179 loss: 2.5179 2022/10/07 22:30:51 - mmengine - INFO - Epoch(train) [72][1420/2119] lr: 4.0000e-02 eta: 15:57:14 time: 0.3061 data_time: 0.0272 memory: 5826 grad_norm: 3.1459 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5717 loss: 2.5717 2022/10/07 22:30:58 - mmengine - INFO - Epoch(train) [72][1440/2119] lr: 4.0000e-02 eta: 15:57:06 time: 0.3366 data_time: 0.0219 memory: 5826 grad_norm: 3.0867 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6300 loss: 2.6300 2022/10/07 22:31:05 - mmengine - INFO - Epoch(train) [72][1460/2119] lr: 4.0000e-02 eta: 15:57:00 time: 0.3523 data_time: 0.0213 memory: 5826 grad_norm: 3.0790 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4480 loss: 2.4480 2022/10/07 22:31:11 - mmengine - INFO - Epoch(train) [72][1480/2119] lr: 4.0000e-02 eta: 15:56:52 time: 0.3030 data_time: 0.0209 memory: 5826 grad_norm: 3.1276 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8001 loss: 2.8001 2022/10/07 22:31:18 - mmengine - INFO - Epoch(train) [72][1500/2119] lr: 4.0000e-02 eta: 15:56:45 time: 0.3530 data_time: 0.0299 memory: 5826 grad_norm: 3.0831 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.5450 loss: 2.5450 2022/10/07 22:31:25 - mmengine - INFO - Epoch(train) [72][1520/2119] lr: 4.0000e-02 eta: 15:56:39 time: 0.3704 data_time: 0.0209 memory: 5826 grad_norm: 3.0763 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7565 loss: 2.7565 2022/10/07 22:31:32 - mmengine - INFO - Epoch(train) [72][1540/2119] lr: 4.0000e-02 eta: 15:56:31 time: 0.3312 data_time: 0.0275 memory: 5826 grad_norm: 3.0634 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7126 loss: 2.7126 2022/10/07 22:31:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 22:31:40 - mmengine - INFO - Epoch(train) [72][1560/2119] lr: 4.0000e-02 eta: 15:56:25 time: 0.3829 data_time: 0.0196 memory: 5826 grad_norm: 3.1020 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7081 loss: 2.7081 2022/10/07 22:31:46 - mmengine - INFO - Epoch(train) [72][1580/2119] lr: 4.0000e-02 eta: 15:56:18 time: 0.3144 data_time: 0.0223 memory: 5826 grad_norm: 3.0896 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5890 loss: 2.5890 2022/10/07 22:31:54 - mmengine - INFO - Epoch(train) [72][1600/2119] lr: 4.0000e-02 eta: 15:56:12 time: 0.3879 data_time: 0.0236 memory: 5826 grad_norm: 3.1433 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6644 loss: 2.6644 2022/10/07 22:32:00 - mmengine - INFO - Epoch(train) [72][1620/2119] lr: 4.0000e-02 eta: 15:56:04 time: 0.2950 data_time: 0.0204 memory: 5826 grad_norm: 3.1436 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9829 loss: 2.9829 2022/10/07 22:32:07 - mmengine - INFO - Epoch(train) [72][1640/2119] lr: 4.0000e-02 eta: 15:55:58 time: 0.3874 data_time: 0.0222 memory: 5826 grad_norm: 3.1179 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5940 loss: 2.5940 2022/10/07 22:32:13 - mmengine - INFO - Epoch(train) [72][1660/2119] lr: 4.0000e-02 eta: 15:55:50 time: 0.3009 data_time: 0.0246 memory: 5826 grad_norm: 3.1296 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6434 loss: 2.6434 2022/10/07 22:32:21 - mmengine - INFO - Epoch(train) [72][1680/2119] lr: 4.0000e-02 eta: 15:55:44 time: 0.3844 data_time: 0.0194 memory: 5826 grad_norm: 3.0894 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6565 loss: 2.6565 2022/10/07 22:32:27 - mmengine - INFO - Epoch(train) [72][1700/2119] lr: 4.0000e-02 eta: 15:55:36 time: 0.3225 data_time: 0.0225 memory: 5826 grad_norm: 3.1485 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7351 loss: 2.7351 2022/10/07 22:32:35 - mmengine - INFO - Epoch(train) [72][1720/2119] lr: 4.0000e-02 eta: 15:55:30 time: 0.3662 data_time: 0.0221 memory: 5826 grad_norm: 3.0999 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7796 loss: 2.7796 2022/10/07 22:32:41 - mmengine - INFO - Epoch(train) [72][1740/2119] lr: 4.0000e-02 eta: 15:55:22 time: 0.2987 data_time: 0.0273 memory: 5826 grad_norm: 3.1478 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7728 loss: 2.7728 2022/10/07 22:32:48 - mmengine - INFO - Epoch(train) [72][1760/2119] lr: 4.0000e-02 eta: 15:55:15 time: 0.3726 data_time: 0.0222 memory: 5826 grad_norm: 3.1194 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6760 loss: 2.6760 2022/10/07 22:32:55 - mmengine - INFO - Epoch(train) [72][1780/2119] lr: 4.0000e-02 eta: 15:55:08 time: 0.3251 data_time: 0.0242 memory: 5826 grad_norm: 3.1008 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5844 loss: 2.5844 2022/10/07 22:33:02 - mmengine - INFO - Epoch(train) [72][1800/2119] lr: 4.0000e-02 eta: 15:55:02 time: 0.3648 data_time: 0.0195 memory: 5826 grad_norm: 3.1945 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7982 loss: 2.7982 2022/10/07 22:33:08 - mmengine - INFO - Epoch(train) [72][1820/2119] lr: 4.0000e-02 eta: 15:54:54 time: 0.3200 data_time: 0.0245 memory: 5826 grad_norm: 3.1741 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6308 loss: 2.6308 2022/10/07 22:33:15 - mmengine - INFO - Epoch(train) [72][1840/2119] lr: 4.0000e-02 eta: 15:54:46 time: 0.3148 data_time: 0.0194 memory: 5826 grad_norm: 3.1040 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7966 loss: 2.7966 2022/10/07 22:33:22 - mmengine - INFO - Epoch(train) [72][1860/2119] lr: 4.0000e-02 eta: 15:54:40 time: 0.3588 data_time: 0.0289 memory: 5826 grad_norm: 3.1047 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5620 loss: 2.5620 2022/10/07 22:33:28 - mmengine - INFO - Epoch(train) [72][1880/2119] lr: 4.0000e-02 eta: 15:54:32 time: 0.3114 data_time: 0.0223 memory: 5826 grad_norm: 3.1376 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5874 loss: 2.5874 2022/10/07 22:33:36 - mmengine - INFO - Epoch(train) [72][1900/2119] lr: 4.0000e-02 eta: 15:54:26 time: 0.3875 data_time: 0.0239 memory: 5826 grad_norm: 3.1195 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6008 loss: 2.6008 2022/10/07 22:33:42 - mmengine - INFO - Epoch(train) [72][1920/2119] lr: 4.0000e-02 eta: 15:54:18 time: 0.3082 data_time: 0.0204 memory: 5826 grad_norm: 3.1269 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5344 loss: 2.5344 2022/10/07 22:33:49 - mmengine - INFO - Epoch(train) [72][1940/2119] lr: 4.0000e-02 eta: 15:54:12 time: 0.3485 data_time: 0.0271 memory: 5826 grad_norm: 3.0699 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7720 loss: 2.7720 2022/10/07 22:33:56 - mmengine - INFO - Epoch(train) [72][1960/2119] lr: 4.0000e-02 eta: 15:54:04 time: 0.3335 data_time: 0.0265 memory: 5826 grad_norm: 3.1563 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8744 loss: 2.8744 2022/10/07 22:34:03 - mmengine - INFO - Epoch(train) [72][1980/2119] lr: 4.0000e-02 eta: 15:53:57 time: 0.3395 data_time: 0.0261 memory: 5826 grad_norm: 3.0906 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6581 loss: 2.6581 2022/10/07 22:34:09 - mmengine - INFO - Epoch(train) [72][2000/2119] lr: 4.0000e-02 eta: 15:53:50 time: 0.3122 data_time: 0.0222 memory: 5826 grad_norm: 3.1609 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.8400 loss: 2.8400 2022/10/07 22:34:17 - mmengine - INFO - Epoch(train) [72][2020/2119] lr: 4.0000e-02 eta: 15:53:44 time: 0.3977 data_time: 0.0267 memory: 5826 grad_norm: 3.1245 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6821 loss: 2.6821 2022/10/07 22:34:23 - mmengine - INFO - Epoch(train) [72][2040/2119] lr: 4.0000e-02 eta: 15:53:36 time: 0.3196 data_time: 0.0221 memory: 5826 grad_norm: 3.0906 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6126 loss: 2.6126 2022/10/07 22:34:30 - mmengine - INFO - Epoch(train) [72][2060/2119] lr: 4.0000e-02 eta: 15:53:29 time: 0.3360 data_time: 0.0270 memory: 5826 grad_norm: 3.0863 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9051 loss: 2.9051 2022/10/07 22:34:36 - mmengine - INFO - Epoch(train) [72][2080/2119] lr: 4.0000e-02 eta: 15:53:22 time: 0.3224 data_time: 0.0251 memory: 5826 grad_norm: 3.1429 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7962 loss: 2.7962 2022/10/07 22:34:43 - mmengine - INFO - Epoch(train) [72][2100/2119] lr: 4.0000e-02 eta: 15:53:15 time: 0.3476 data_time: 0.0245 memory: 5826 grad_norm: 3.1494 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8054 loss: 2.8054 2022/10/07 22:34:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 22:34:49 - mmengine - INFO - Epoch(train) [72][2119/2119] lr: 4.0000e-02 eta: 15:53:15 time: 0.3153 data_time: 0.0213 memory: 5826 grad_norm: 3.1667 top1_acc: 0.4000 top5_acc: 0.5000 loss_cls: 2.8468 loss: 2.8468 2022/10/07 22:34:49 - mmengine - INFO - Saving checkpoint at 72 epochs 2022/10/07 22:35:08 - mmengine - INFO - Epoch(train) [73][20/2119] lr: 4.0000e-02 eta: 15:52:55 time: 0.3926 data_time: 0.1600 memory: 5826 grad_norm: 3.0938 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6908 loss: 2.6908 2022/10/07 22:35:14 - mmengine - INFO - Epoch(train) [73][40/2119] lr: 4.0000e-02 eta: 15:52:48 time: 0.3099 data_time: 0.0786 memory: 5826 grad_norm: 3.1093 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6853 loss: 2.6853 2022/10/07 22:35:21 - mmengine - INFO - Epoch(train) [73][60/2119] lr: 4.0000e-02 eta: 15:52:40 time: 0.3289 data_time: 0.0383 memory: 5826 grad_norm: 3.0675 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5896 loss: 2.5896 2022/10/07 22:35:27 - mmengine - INFO - Epoch(train) [73][80/2119] lr: 4.0000e-02 eta: 15:52:33 time: 0.3353 data_time: 0.0216 memory: 5826 grad_norm: 3.1135 top1_acc: 0.1875 top5_acc: 0.7500 loss_cls: 2.7873 loss: 2.7873 2022/10/07 22:35:35 - mmengine - INFO - Epoch(train) [73][100/2119] lr: 4.0000e-02 eta: 15:52:27 time: 0.3657 data_time: 0.0236 memory: 5826 grad_norm: 3.1150 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6799 loss: 2.6799 2022/10/07 22:35:42 - mmengine - INFO - Epoch(train) [73][120/2119] lr: 4.0000e-02 eta: 15:52:20 time: 0.3405 data_time: 0.0245 memory: 5826 grad_norm: 3.1760 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5359 loss: 2.5359 2022/10/07 22:35:49 - mmengine - INFO - Epoch(train) [73][140/2119] lr: 4.0000e-02 eta: 15:52:13 time: 0.3598 data_time: 0.0241 memory: 5826 grad_norm: 3.0990 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8571 loss: 2.8571 2022/10/07 22:35:55 - mmengine - INFO - Epoch(train) [73][160/2119] lr: 4.0000e-02 eta: 15:52:06 time: 0.3245 data_time: 0.0243 memory: 5826 grad_norm: 3.1112 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8959 loss: 2.8959 2022/10/07 22:36:03 - mmengine - INFO - Epoch(train) [73][180/2119] lr: 4.0000e-02 eta: 15:51:59 time: 0.3760 data_time: 0.0229 memory: 5826 grad_norm: 3.0460 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7214 loss: 2.7214 2022/10/07 22:36:09 - mmengine - INFO - Epoch(train) [73][200/2119] lr: 4.0000e-02 eta: 15:51:52 time: 0.3192 data_time: 0.0239 memory: 5826 grad_norm: 3.0698 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5790 loss: 2.5790 2022/10/07 22:36:16 - mmengine - INFO - Epoch(train) [73][220/2119] lr: 4.0000e-02 eta: 15:51:45 time: 0.3419 data_time: 0.0333 memory: 5826 grad_norm: 3.1519 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.5973 loss: 2.5973 2022/10/07 22:36:23 - mmengine - INFO - Epoch(train) [73][240/2119] lr: 4.0000e-02 eta: 15:51:38 time: 0.3498 data_time: 0.0241 memory: 5826 grad_norm: 3.1880 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7623 loss: 2.7623 2022/10/07 22:36:30 - mmengine - INFO - Epoch(train) [73][260/2119] lr: 4.0000e-02 eta: 15:51:31 time: 0.3469 data_time: 0.0198 memory: 5826 grad_norm: 3.1804 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8860 loss: 2.8860 2022/10/07 22:36:37 - mmengine - INFO - Epoch(train) [73][280/2119] lr: 4.0000e-02 eta: 15:51:24 time: 0.3318 data_time: 0.0259 memory: 5826 grad_norm: 3.1009 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6904 loss: 2.6904 2022/10/07 22:36:44 - mmengine - INFO - Epoch(train) [73][300/2119] lr: 4.0000e-02 eta: 15:51:17 time: 0.3568 data_time: 0.0228 memory: 5826 grad_norm: 3.1220 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7322 loss: 2.7322 2022/10/07 22:36:49 - mmengine - INFO - Epoch(train) [73][320/2119] lr: 4.0000e-02 eta: 15:51:09 time: 0.2854 data_time: 0.0212 memory: 5826 grad_norm: 3.1445 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6966 loss: 2.6966 2022/10/07 22:36:57 - mmengine - INFO - Epoch(train) [73][340/2119] lr: 4.0000e-02 eta: 15:51:02 time: 0.3680 data_time: 0.0256 memory: 5826 grad_norm: 3.0936 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5134 loss: 2.5134 2022/10/07 22:37:03 - mmengine - INFO - Epoch(train) [73][360/2119] lr: 4.0000e-02 eta: 15:50:55 time: 0.3237 data_time: 0.0281 memory: 5826 grad_norm: 3.1785 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8950 loss: 2.8950 2022/10/07 22:37:10 - mmengine - INFO - Epoch(train) [73][380/2119] lr: 4.0000e-02 eta: 15:50:48 time: 0.3538 data_time: 0.0195 memory: 5826 grad_norm: 3.1150 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8916 loss: 2.8916 2022/10/07 22:37:17 - mmengine - INFO - Epoch(train) [73][400/2119] lr: 4.0000e-02 eta: 15:50:41 time: 0.3233 data_time: 0.0308 memory: 5826 grad_norm: 3.1536 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8163 loss: 2.8163 2022/10/07 22:37:24 - mmengine - INFO - Epoch(train) [73][420/2119] lr: 4.0000e-02 eta: 15:50:34 time: 0.3448 data_time: 0.0220 memory: 5826 grad_norm: 3.1312 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7424 loss: 2.7424 2022/10/07 22:37:28 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 22:37:30 - mmengine - INFO - Epoch(train) [73][440/2119] lr: 4.0000e-02 eta: 15:50:27 time: 0.3370 data_time: 0.0277 memory: 5826 grad_norm: 3.1767 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5678 loss: 2.5678 2022/10/07 22:37:38 - mmengine - INFO - Epoch(train) [73][460/2119] lr: 4.0000e-02 eta: 15:50:21 time: 0.3953 data_time: 0.0279 memory: 5826 grad_norm: 3.1062 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9901 loss: 2.9901 2022/10/07 22:37:45 - mmengine - INFO - Epoch(train) [73][480/2119] lr: 4.0000e-02 eta: 15:50:14 time: 0.3199 data_time: 0.0201 memory: 5826 grad_norm: 3.1321 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7423 loss: 2.7423 2022/10/07 22:37:53 - mmengine - INFO - Epoch(train) [73][500/2119] lr: 4.0000e-02 eta: 15:50:07 time: 0.3868 data_time: 0.0233 memory: 5826 grad_norm: 3.0686 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6638 loss: 2.6638 2022/10/07 22:37:58 - mmengine - INFO - Epoch(train) [73][520/2119] lr: 4.0000e-02 eta: 15:49:59 time: 0.2796 data_time: 0.0240 memory: 5826 grad_norm: 3.1099 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6886 loss: 2.6886 2022/10/07 22:38:06 - mmengine - INFO - Epoch(train) [73][540/2119] lr: 4.0000e-02 eta: 15:49:53 time: 0.3748 data_time: 0.0218 memory: 5826 grad_norm: 3.1186 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8382 loss: 2.8382 2022/10/07 22:38:13 - mmengine - INFO - Epoch(train) [73][560/2119] lr: 4.0000e-02 eta: 15:49:46 time: 0.3499 data_time: 0.0277 memory: 5826 grad_norm: 3.0974 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4676 loss: 2.4676 2022/10/07 22:38:20 - mmengine - INFO - Epoch(train) [73][580/2119] lr: 4.0000e-02 eta: 15:49:39 time: 0.3467 data_time: 0.0204 memory: 5826 grad_norm: 3.1266 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9544 loss: 2.9544 2022/10/07 22:38:26 - mmengine - INFO - Epoch(train) [73][600/2119] lr: 4.0000e-02 eta: 15:49:31 time: 0.3019 data_time: 0.0298 memory: 5826 grad_norm: 3.1451 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 3.0133 loss: 3.0133 2022/10/07 22:38:32 - mmengine - INFO - Epoch(train) [73][620/2119] lr: 4.0000e-02 eta: 15:49:24 time: 0.3422 data_time: 0.0233 memory: 5826 grad_norm: 3.1556 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8790 loss: 2.8790 2022/10/07 22:38:40 - mmengine - INFO - Epoch(train) [73][640/2119] lr: 4.0000e-02 eta: 15:49:18 time: 0.3725 data_time: 0.0265 memory: 5826 grad_norm: 3.1503 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7242 loss: 2.7242 2022/10/07 22:38:46 - mmengine - INFO - Epoch(train) [73][660/2119] lr: 4.0000e-02 eta: 15:49:10 time: 0.3081 data_time: 0.0259 memory: 5826 grad_norm: 3.1077 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5404 loss: 2.5404 2022/10/07 22:38:53 - mmengine - INFO - Epoch(train) [73][680/2119] lr: 4.0000e-02 eta: 15:49:03 time: 0.3299 data_time: 0.0280 memory: 5826 grad_norm: 3.1622 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8514 loss: 2.8514 2022/10/07 22:39:00 - mmengine - INFO - Epoch(train) [73][700/2119] lr: 4.0000e-02 eta: 15:48:57 time: 0.3771 data_time: 0.0237 memory: 5826 grad_norm: 3.1448 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6991 loss: 2.6991 2022/10/07 22:39:07 - mmengine - INFO - Epoch(train) [73][720/2119] lr: 4.0000e-02 eta: 15:48:50 time: 0.3450 data_time: 0.0236 memory: 5826 grad_norm: 3.0714 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.9640 loss: 2.9640 2022/10/07 22:39:13 - mmengine - INFO - Epoch(train) [73][740/2119] lr: 4.0000e-02 eta: 15:48:42 time: 0.3134 data_time: 0.0235 memory: 5826 grad_norm: 3.1431 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7539 loss: 2.7539 2022/10/07 22:39:21 - mmengine - INFO - Epoch(train) [73][760/2119] lr: 4.0000e-02 eta: 15:48:35 time: 0.3555 data_time: 0.0203 memory: 5826 grad_norm: 3.1077 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6708 loss: 2.6708 2022/10/07 22:39:27 - mmengine - INFO - Epoch(train) [73][780/2119] lr: 4.0000e-02 eta: 15:48:28 time: 0.3444 data_time: 0.0238 memory: 5826 grad_norm: 3.0866 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7116 loss: 2.7116 2022/10/07 22:39:34 - mmengine - INFO - Epoch(train) [73][800/2119] lr: 4.0000e-02 eta: 15:48:21 time: 0.3280 data_time: 0.0258 memory: 5826 grad_norm: 3.1104 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.7318 loss: 2.7318 2022/10/07 22:39:41 - mmengine - INFO - Epoch(train) [73][820/2119] lr: 4.0000e-02 eta: 15:48:15 time: 0.3643 data_time: 0.0180 memory: 5826 grad_norm: 3.1293 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8761 loss: 2.8761 2022/10/07 22:39:48 - mmengine - INFO - Epoch(train) [73][840/2119] lr: 4.0000e-02 eta: 15:48:08 time: 0.3510 data_time: 0.0230 memory: 5826 grad_norm: 3.0699 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6540 loss: 2.6540 2022/10/07 22:39:55 - mmengine - INFO - Epoch(train) [73][860/2119] lr: 4.0000e-02 eta: 15:48:01 time: 0.3368 data_time: 0.0246 memory: 5826 grad_norm: 3.0472 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8888 loss: 2.8888 2022/10/07 22:40:02 - mmengine - INFO - Epoch(train) [73][880/2119] lr: 4.0000e-02 eta: 15:47:53 time: 0.3282 data_time: 0.0244 memory: 5826 grad_norm: 3.1279 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8602 loss: 2.8602 2022/10/07 22:40:08 - mmengine - INFO - Epoch(train) [73][900/2119] lr: 4.0000e-02 eta: 15:47:46 time: 0.3369 data_time: 0.0263 memory: 5826 grad_norm: 3.1230 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7505 loss: 2.7505 2022/10/07 22:40:15 - mmengine - INFO - Epoch(train) [73][920/2119] lr: 4.0000e-02 eta: 15:47:39 time: 0.3348 data_time: 0.0238 memory: 5826 grad_norm: 3.0986 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6679 loss: 2.6679 2022/10/07 22:40:23 - mmengine - INFO - Epoch(train) [73][940/2119] lr: 4.0000e-02 eta: 15:47:33 time: 0.4055 data_time: 0.0230 memory: 5826 grad_norm: 3.0970 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7732 loss: 2.7732 2022/10/07 22:40:30 - mmengine - INFO - Epoch(train) [73][960/2119] lr: 4.0000e-02 eta: 15:47:26 time: 0.3275 data_time: 0.0209 memory: 5826 grad_norm: 3.1465 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4954 loss: 2.4954 2022/10/07 22:40:37 - mmengine - INFO - Epoch(train) [73][980/2119] lr: 4.0000e-02 eta: 15:47:19 time: 0.3567 data_time: 0.0230 memory: 5826 grad_norm: 3.1639 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6870 loss: 2.6870 2022/10/07 22:40:43 - mmengine - INFO - Epoch(train) [73][1000/2119] lr: 4.0000e-02 eta: 15:47:12 time: 0.3288 data_time: 0.0211 memory: 5826 grad_norm: 3.0927 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7522 loss: 2.7522 2022/10/07 22:40:51 - mmengine - INFO - Epoch(train) [73][1020/2119] lr: 4.0000e-02 eta: 15:47:06 time: 0.3962 data_time: 0.0238 memory: 5826 grad_norm: 3.1583 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7778 loss: 2.7778 2022/10/07 22:40:57 - mmengine - INFO - Epoch(train) [73][1040/2119] lr: 4.0000e-02 eta: 15:46:58 time: 0.2833 data_time: 0.0248 memory: 5826 grad_norm: 3.1119 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.5994 loss: 2.5994 2022/10/07 22:41:05 - mmengine - INFO - Epoch(train) [73][1060/2119] lr: 4.0000e-02 eta: 15:46:52 time: 0.3760 data_time: 0.0330 memory: 5826 grad_norm: 3.1415 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6376 loss: 2.6376 2022/10/07 22:41:11 - mmengine - INFO - Epoch(train) [73][1080/2119] lr: 4.0000e-02 eta: 15:46:44 time: 0.3106 data_time: 0.0247 memory: 5826 grad_norm: 3.1162 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5878 loss: 2.5878 2022/10/07 22:41:18 - mmengine - INFO - Epoch(train) [73][1100/2119] lr: 4.0000e-02 eta: 15:46:38 time: 0.3829 data_time: 0.0199 memory: 5826 grad_norm: 3.0769 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7293 loss: 2.7293 2022/10/07 22:41:25 - mmengine - INFO - Epoch(train) [73][1120/2119] lr: 4.0000e-02 eta: 15:46:31 time: 0.3273 data_time: 0.0216 memory: 5826 grad_norm: 3.1308 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6294 loss: 2.6294 2022/10/07 22:41:32 - mmengine - INFO - Epoch(train) [73][1140/2119] lr: 4.0000e-02 eta: 15:46:24 time: 0.3387 data_time: 0.0233 memory: 5826 grad_norm: 3.1408 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 2.6891 loss: 2.6891 2022/10/07 22:41:39 - mmengine - INFO - Epoch(train) [73][1160/2119] lr: 4.0000e-02 eta: 15:46:17 time: 0.3510 data_time: 0.0241 memory: 5826 grad_norm: 3.1060 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8792 loss: 2.8792 2022/10/07 22:41:47 - mmengine - INFO - Epoch(train) [73][1180/2119] lr: 4.0000e-02 eta: 15:46:11 time: 0.3891 data_time: 0.0227 memory: 5826 grad_norm: 3.0595 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7148 loss: 2.7148 2022/10/07 22:41:53 - mmengine - INFO - Epoch(train) [73][1200/2119] lr: 4.0000e-02 eta: 15:46:03 time: 0.3128 data_time: 0.0224 memory: 5826 grad_norm: 3.0804 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6992 loss: 2.6992 2022/10/07 22:42:00 - mmengine - INFO - Epoch(train) [73][1220/2119] lr: 4.0000e-02 eta: 15:45:57 time: 0.3639 data_time: 0.0257 memory: 5826 grad_norm: 3.2290 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7565 loss: 2.7565 2022/10/07 22:42:07 - mmengine - INFO - Epoch(train) [73][1240/2119] lr: 4.0000e-02 eta: 15:45:49 time: 0.3354 data_time: 0.0301 memory: 5826 grad_norm: 3.1077 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4640 loss: 2.4640 2022/10/07 22:42:14 - mmengine - INFO - Epoch(train) [73][1260/2119] lr: 4.0000e-02 eta: 15:45:43 time: 0.3510 data_time: 0.0200 memory: 5826 grad_norm: 3.1070 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5157 loss: 2.5157 2022/10/07 22:42:21 - mmengine - INFO - Epoch(train) [73][1280/2119] lr: 4.0000e-02 eta: 15:45:36 time: 0.3523 data_time: 0.0276 memory: 5826 grad_norm: 3.1230 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6898 loss: 2.6898 2022/10/07 22:42:28 - mmengine - INFO - Epoch(train) [73][1300/2119] lr: 4.0000e-02 eta: 15:45:29 time: 0.3665 data_time: 0.0207 memory: 5826 grad_norm: 3.1642 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9785 loss: 2.9785 2022/10/07 22:42:35 - mmengine - INFO - Epoch(train) [73][1320/2119] lr: 4.0000e-02 eta: 15:45:22 time: 0.3170 data_time: 0.0234 memory: 5826 grad_norm: 3.1996 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8543 loss: 2.8543 2022/10/07 22:42:41 - mmengine - INFO - Epoch(train) [73][1340/2119] lr: 4.0000e-02 eta: 15:45:15 time: 0.3347 data_time: 0.0243 memory: 5826 grad_norm: 3.0751 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7366 loss: 2.7366 2022/10/07 22:42:49 - mmengine - INFO - Epoch(train) [73][1360/2119] lr: 4.0000e-02 eta: 15:45:09 time: 0.3843 data_time: 0.0224 memory: 5826 grad_norm: 3.1237 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8572 loss: 2.8572 2022/10/07 22:42:55 - mmengine - INFO - Epoch(train) [73][1380/2119] lr: 4.0000e-02 eta: 15:45:01 time: 0.3020 data_time: 0.0252 memory: 5826 grad_norm: 3.1202 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6664 loss: 2.6664 2022/10/07 22:43:02 - mmengine - INFO - Epoch(train) [73][1400/2119] lr: 4.0000e-02 eta: 15:44:54 time: 0.3536 data_time: 0.0265 memory: 5826 grad_norm: 3.1494 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8502 loss: 2.8502 2022/10/07 22:43:09 - mmengine - INFO - Epoch(train) [73][1420/2119] lr: 4.0000e-02 eta: 15:44:47 time: 0.3621 data_time: 0.0327 memory: 5826 grad_norm: 3.1424 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.7869 loss: 2.7869 2022/10/07 22:43:14 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 22:43:16 - mmengine - INFO - Epoch(train) [73][1440/2119] lr: 4.0000e-02 eta: 15:44:41 time: 0.3493 data_time: 0.0199 memory: 5826 grad_norm: 3.1358 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6788 loss: 2.6788 2022/10/07 22:43:23 - mmengine - INFO - Epoch(train) [73][1460/2119] lr: 4.0000e-02 eta: 15:44:34 time: 0.3515 data_time: 0.0226 memory: 5826 grad_norm: 3.1168 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8232 loss: 2.8232 2022/10/07 22:43:30 - mmengine - INFO - Epoch(train) [73][1480/2119] lr: 4.0000e-02 eta: 15:44:27 time: 0.3488 data_time: 0.0233 memory: 5826 grad_norm: 3.1327 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7596 loss: 2.7596 2022/10/07 22:43:38 - mmengine - INFO - Epoch(train) [73][1500/2119] lr: 4.0000e-02 eta: 15:44:21 time: 0.3944 data_time: 0.0207 memory: 5826 grad_norm: 3.1312 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9265 loss: 2.9265 2022/10/07 22:43:45 - mmengine - INFO - Epoch(train) [73][1520/2119] lr: 4.0000e-02 eta: 15:44:14 time: 0.3277 data_time: 0.0184 memory: 5826 grad_norm: 3.0518 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6086 loss: 2.6086 2022/10/07 22:43:51 - mmengine - INFO - Epoch(train) [73][1540/2119] lr: 4.0000e-02 eta: 15:44:07 time: 0.3324 data_time: 0.0280 memory: 5826 grad_norm: 3.0751 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7685 loss: 2.7685 2022/10/07 22:44:00 - mmengine - INFO - Epoch(train) [73][1560/2119] lr: 4.0000e-02 eta: 15:44:01 time: 0.4000 data_time: 0.0213 memory: 5826 grad_norm: 3.1776 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7654 loss: 2.7654 2022/10/07 22:44:06 - mmengine - INFO - Epoch(train) [73][1580/2119] lr: 4.0000e-02 eta: 15:43:54 time: 0.3410 data_time: 0.0229 memory: 5826 grad_norm: 3.1397 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9105 loss: 2.9105 2022/10/07 22:44:14 - mmengine - INFO - Epoch(train) [73][1600/2119] lr: 4.0000e-02 eta: 15:43:47 time: 0.3655 data_time: 0.0207 memory: 5826 grad_norm: 3.0953 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6255 loss: 2.6255 2022/10/07 22:44:21 - mmengine - INFO - Epoch(train) [73][1620/2119] lr: 4.0000e-02 eta: 15:43:41 time: 0.3610 data_time: 0.0228 memory: 5826 grad_norm: 3.1654 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7535 loss: 2.7535 2022/10/07 22:44:27 - mmengine - INFO - Epoch(train) [73][1640/2119] lr: 4.0000e-02 eta: 15:43:33 time: 0.3096 data_time: 0.0226 memory: 5826 grad_norm: 3.1383 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6445 loss: 2.6445 2022/10/07 22:44:34 - mmengine - INFO - Epoch(train) [73][1660/2119] lr: 4.0000e-02 eta: 15:43:26 time: 0.3492 data_time: 0.0247 memory: 5826 grad_norm: 3.1680 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5602 loss: 2.5602 2022/10/07 22:44:41 - mmengine - INFO - Epoch(train) [73][1680/2119] lr: 4.0000e-02 eta: 15:43:19 time: 0.3605 data_time: 0.0235 memory: 5826 grad_norm: 3.1538 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7289 loss: 2.7289 2022/10/07 22:44:48 - mmengine - INFO - Epoch(train) [73][1700/2119] lr: 4.0000e-02 eta: 15:43:12 time: 0.3412 data_time: 0.0254 memory: 5826 grad_norm: 3.0926 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4596 loss: 2.4596 2022/10/07 22:44:55 - mmengine - INFO - Epoch(train) [73][1720/2119] lr: 4.0000e-02 eta: 15:43:05 time: 0.3366 data_time: 0.0228 memory: 5826 grad_norm: 3.0731 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8027 loss: 2.8027 2022/10/07 22:45:03 - mmengine - INFO - Epoch(train) [73][1740/2119] lr: 4.0000e-02 eta: 15:43:00 time: 0.4023 data_time: 0.0226 memory: 5826 grad_norm: 3.1339 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5980 loss: 2.5980 2022/10/07 22:45:10 - mmengine - INFO - Epoch(train) [73][1760/2119] lr: 4.0000e-02 eta: 15:42:53 time: 0.3472 data_time: 0.0259 memory: 5826 grad_norm: 3.0551 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6510 loss: 2.6510 2022/10/07 22:45:18 - mmengine - INFO - Epoch(train) [73][1780/2119] lr: 4.0000e-02 eta: 15:42:48 time: 0.4293 data_time: 0.0206 memory: 5826 grad_norm: 3.0845 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5958 loss: 2.5958 2022/10/07 22:45:25 - mmengine - INFO - Epoch(train) [73][1800/2119] lr: 4.0000e-02 eta: 15:42:40 time: 0.3066 data_time: 0.0244 memory: 5826 grad_norm: 3.0970 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4996 loss: 2.4996 2022/10/07 22:45:33 - mmengine - INFO - Epoch(train) [73][1820/2119] lr: 4.0000e-02 eta: 15:42:34 time: 0.4084 data_time: 0.0192 memory: 5826 grad_norm: 3.1357 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5368 loss: 2.5368 2022/10/07 22:45:40 - mmengine - INFO - Epoch(train) [73][1840/2119] lr: 4.0000e-02 eta: 15:42:28 time: 0.3619 data_time: 0.0192 memory: 5826 grad_norm: 3.0827 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6564 loss: 2.6564 2022/10/07 22:45:46 - mmengine - INFO - Epoch(train) [73][1860/2119] lr: 4.0000e-02 eta: 15:42:20 time: 0.3084 data_time: 0.0235 memory: 5826 grad_norm: 3.0998 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7372 loss: 2.7372 2022/10/07 22:45:53 - mmengine - INFO - Epoch(train) [73][1880/2119] lr: 4.0000e-02 eta: 15:42:13 time: 0.3382 data_time: 0.0193 memory: 5826 grad_norm: 3.1103 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0226 loss: 3.0226 2022/10/07 22:46:01 - mmengine - INFO - Epoch(train) [73][1900/2119] lr: 4.0000e-02 eta: 15:42:07 time: 0.3917 data_time: 0.0225 memory: 5826 grad_norm: 3.1436 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7603 loss: 2.7603 2022/10/07 22:46:08 - mmengine - INFO - Epoch(train) [73][1920/2119] lr: 4.0000e-02 eta: 15:42:00 time: 0.3421 data_time: 0.0232 memory: 5826 grad_norm: 3.1140 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8020 loss: 2.8020 2022/10/07 22:46:15 - mmengine - INFO - Epoch(train) [73][1940/2119] lr: 4.0000e-02 eta: 15:41:54 time: 0.3836 data_time: 0.0228 memory: 5826 grad_norm: 3.1424 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7741 loss: 2.7741 2022/10/07 22:46:23 - mmengine - INFO - Epoch(train) [73][1960/2119] lr: 4.0000e-02 eta: 15:41:47 time: 0.3684 data_time: 0.0273 memory: 5826 grad_norm: 3.0955 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9551 loss: 2.9551 2022/10/07 22:46:30 - mmengine - INFO - Epoch(train) [73][1980/2119] lr: 4.0000e-02 eta: 15:41:41 time: 0.3756 data_time: 0.0231 memory: 5826 grad_norm: 3.1083 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5390 loss: 2.5390 2022/10/07 22:46:36 - mmengine - INFO - Epoch(train) [73][2000/2119] lr: 4.0000e-02 eta: 15:41:33 time: 0.3063 data_time: 0.0246 memory: 5826 grad_norm: 3.1095 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.4959 loss: 2.4959 2022/10/07 22:46:44 - mmengine - INFO - Epoch(train) [73][2020/2119] lr: 4.0000e-02 eta: 15:41:27 time: 0.3763 data_time: 0.0228 memory: 5826 grad_norm: 3.1652 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7564 loss: 2.7564 2022/10/07 22:46:51 - mmengine - INFO - Epoch(train) [73][2040/2119] lr: 4.0000e-02 eta: 15:41:20 time: 0.3474 data_time: 0.0272 memory: 5826 grad_norm: 3.1526 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8271 loss: 2.8271 2022/10/07 22:47:00 - mmengine - INFO - Epoch(train) [73][2060/2119] lr: 4.0000e-02 eta: 15:41:15 time: 0.4416 data_time: 0.0216 memory: 5826 grad_norm: 3.1647 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.8107 loss: 2.8107 2022/10/07 22:47:06 - mmengine - INFO - Epoch(train) [73][2080/2119] lr: 4.0000e-02 eta: 15:41:08 time: 0.3403 data_time: 0.0187 memory: 5826 grad_norm: 3.1279 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7719 loss: 2.7719 2022/10/07 22:47:13 - mmengine - INFO - Epoch(train) [73][2100/2119] lr: 4.0000e-02 eta: 15:41:01 time: 0.3526 data_time: 0.0221 memory: 5826 grad_norm: 3.0945 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5811 loss: 2.5811 2022/10/07 22:47:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 22:47:20 - mmengine - INFO - Epoch(train) [73][2119/2119] lr: 4.0000e-02 eta: 15:41:01 time: 0.3353 data_time: 0.0226 memory: 5826 grad_norm: 3.1691 top1_acc: 0.6000 top5_acc: 0.8000 loss_cls: 2.6542 loss: 2.6542 2022/10/07 22:47:29 - mmengine - INFO - Epoch(train) [74][20/2119] lr: 4.0000e-02 eta: 15:40:44 time: 0.4733 data_time: 0.1967 memory: 5826 grad_norm: 3.1063 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6285 loss: 2.6285 2022/10/07 22:47:36 - mmengine - INFO - Epoch(train) [74][40/2119] lr: 4.0000e-02 eta: 15:40:36 time: 0.3162 data_time: 0.0163 memory: 5826 grad_norm: 3.1165 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9190 loss: 2.9190 2022/10/07 22:47:44 - mmengine - INFO - Epoch(train) [74][60/2119] lr: 4.0000e-02 eta: 15:40:31 time: 0.4157 data_time: 0.0216 memory: 5826 grad_norm: 3.0868 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8531 loss: 2.8531 2022/10/07 22:47:51 - mmengine - INFO - Epoch(train) [74][80/2119] lr: 4.0000e-02 eta: 15:40:23 time: 0.3278 data_time: 0.0236 memory: 5826 grad_norm: 3.0732 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5006 loss: 2.5006 2022/10/07 22:47:58 - mmengine - INFO - Epoch(train) [74][100/2119] lr: 4.0000e-02 eta: 15:40:17 time: 0.3806 data_time: 0.0239 memory: 5826 grad_norm: 3.1566 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5292 loss: 2.5292 2022/10/07 22:48:04 - mmengine - INFO - Epoch(train) [74][120/2119] lr: 4.0000e-02 eta: 15:40:09 time: 0.3009 data_time: 0.0258 memory: 5826 grad_norm: 3.1204 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4844 loss: 2.4844 2022/10/07 22:48:13 - mmengine - INFO - Epoch(train) [74][140/2119] lr: 4.0000e-02 eta: 15:40:04 time: 0.4265 data_time: 0.0217 memory: 5826 grad_norm: 3.1003 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8077 loss: 2.8077 2022/10/07 22:48:19 - mmengine - INFO - Epoch(train) [74][160/2119] lr: 4.0000e-02 eta: 15:39:57 time: 0.3305 data_time: 0.0262 memory: 5826 grad_norm: 3.1177 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7004 loss: 2.7004 2022/10/07 22:48:26 - mmengine - INFO - Epoch(train) [74][180/2119] lr: 4.0000e-02 eta: 15:39:49 time: 0.3233 data_time: 0.0310 memory: 5826 grad_norm: 3.1782 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9003 loss: 2.9003 2022/10/07 22:48:32 - mmengine - INFO - Epoch(train) [74][200/2119] lr: 4.0000e-02 eta: 15:39:42 time: 0.3034 data_time: 0.0152 memory: 5826 grad_norm: 3.1578 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6135 loss: 2.6135 2022/10/07 22:48:40 - mmengine - INFO - Epoch(train) [74][220/2119] lr: 4.0000e-02 eta: 15:39:36 time: 0.4072 data_time: 0.0253 memory: 5826 grad_norm: 3.1038 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8408 loss: 2.8408 2022/10/07 22:48:47 - mmengine - INFO - Epoch(train) [74][240/2119] lr: 4.0000e-02 eta: 15:39:28 time: 0.3194 data_time: 0.0203 memory: 5826 grad_norm: 3.1242 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6070 loss: 2.6070 2022/10/07 22:48:54 - mmengine - INFO - Epoch(train) [74][260/2119] lr: 4.0000e-02 eta: 15:39:22 time: 0.3551 data_time: 0.0263 memory: 5826 grad_norm: 3.0808 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7430 loss: 2.7430 2022/10/07 22:49:01 - mmengine - INFO - Epoch(train) [74][280/2119] lr: 4.0000e-02 eta: 15:39:15 time: 0.3530 data_time: 0.0269 memory: 5826 grad_norm: 3.1431 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6529 loss: 2.6529 2022/10/07 22:49:07 - mmengine - INFO - Epoch(train) [74][300/2119] lr: 4.0000e-02 eta: 15:39:08 time: 0.3387 data_time: 0.0293 memory: 5826 grad_norm: 3.1209 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7453 loss: 2.7453 2022/10/07 22:49:12 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 22:49:15 - mmengine - INFO - Epoch(train) [74][320/2119] lr: 4.0000e-02 eta: 15:39:01 time: 0.3611 data_time: 0.0201 memory: 5826 grad_norm: 3.0935 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5337 loss: 2.5337 2022/10/07 22:49:22 - mmengine - INFO - Epoch(train) [74][340/2119] lr: 4.0000e-02 eta: 15:38:55 time: 0.3560 data_time: 0.0228 memory: 5826 grad_norm: 3.0775 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6738 loss: 2.6738 2022/10/07 22:49:29 - mmengine - INFO - Epoch(train) [74][360/2119] lr: 4.0000e-02 eta: 15:38:48 time: 0.3480 data_time: 0.0277 memory: 5826 grad_norm: 3.1751 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7314 loss: 2.7314 2022/10/07 22:49:36 - mmengine - INFO - Epoch(train) [74][380/2119] lr: 4.0000e-02 eta: 15:38:41 time: 0.3457 data_time: 0.0247 memory: 5826 grad_norm: 3.1890 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5869 loss: 2.5869 2022/10/07 22:49:42 - mmengine - INFO - Epoch(train) [74][400/2119] lr: 4.0000e-02 eta: 15:38:34 time: 0.3377 data_time: 0.0191 memory: 5826 grad_norm: 3.1932 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7196 loss: 2.7196 2022/10/07 22:49:50 - mmengine - INFO - Epoch(train) [74][420/2119] lr: 4.0000e-02 eta: 15:38:27 time: 0.3661 data_time: 0.0276 memory: 5826 grad_norm: 3.1572 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7325 loss: 2.7325 2022/10/07 22:49:56 - mmengine - INFO - Epoch(train) [74][440/2119] lr: 4.0000e-02 eta: 15:38:19 time: 0.2922 data_time: 0.0255 memory: 5826 grad_norm: 3.1479 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5933 loss: 2.5933 2022/10/07 22:50:02 - mmengine - INFO - Epoch(train) [74][460/2119] lr: 4.0000e-02 eta: 15:38:12 time: 0.3295 data_time: 0.0289 memory: 5826 grad_norm: 3.1288 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9063 loss: 2.9063 2022/10/07 22:50:09 - mmengine - INFO - Epoch(train) [74][480/2119] lr: 4.0000e-02 eta: 15:38:05 time: 0.3525 data_time: 0.0206 memory: 5826 grad_norm: 3.1102 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6266 loss: 2.6266 2022/10/07 22:50:15 - mmengine - INFO - Epoch(train) [74][500/2119] lr: 4.0000e-02 eta: 15:37:57 time: 0.3019 data_time: 0.0245 memory: 5826 grad_norm: 3.0915 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7572 loss: 2.7572 2022/10/07 22:50:23 - mmengine - INFO - Epoch(train) [74][520/2119] lr: 4.0000e-02 eta: 15:37:51 time: 0.3606 data_time: 0.0310 memory: 5826 grad_norm: 3.0982 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7904 loss: 2.7904 2022/10/07 22:50:30 - mmengine - INFO - Epoch(train) [74][540/2119] lr: 4.0000e-02 eta: 15:37:45 time: 0.3908 data_time: 0.0186 memory: 5826 grad_norm: 3.0894 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9349 loss: 2.9349 2022/10/07 22:50:36 - mmengine - INFO - Epoch(train) [74][560/2119] lr: 4.0000e-02 eta: 15:37:36 time: 0.2738 data_time: 0.0245 memory: 5826 grad_norm: 3.0803 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6699 loss: 2.6699 2022/10/07 22:50:43 - mmengine - INFO - Epoch(train) [74][580/2119] lr: 4.0000e-02 eta: 15:37:30 time: 0.3637 data_time: 0.0392 memory: 5826 grad_norm: 3.1031 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9502 loss: 2.9502 2022/10/07 22:50:50 - mmengine - INFO - Epoch(train) [74][600/2119] lr: 4.0000e-02 eta: 15:37:22 time: 0.3206 data_time: 0.0251 memory: 5826 grad_norm: 3.1379 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 3.0167 loss: 3.0167 2022/10/07 22:50:57 - mmengine - INFO - Epoch(train) [74][620/2119] lr: 4.0000e-02 eta: 15:37:16 time: 0.3918 data_time: 0.0267 memory: 5826 grad_norm: 3.1120 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9626 loss: 2.9626 2022/10/07 22:51:04 - mmengine - INFO - Epoch(train) [74][640/2119] lr: 4.0000e-02 eta: 15:37:09 time: 0.3269 data_time: 0.0219 memory: 5826 grad_norm: 3.1271 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7455 loss: 2.7455 2022/10/07 22:51:12 - mmengine - INFO - Epoch(train) [74][660/2119] lr: 4.0000e-02 eta: 15:37:03 time: 0.3777 data_time: 0.0249 memory: 5826 grad_norm: 3.1007 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5638 loss: 2.5638 2022/10/07 22:51:18 - mmengine - INFO - Epoch(train) [74][680/2119] lr: 4.0000e-02 eta: 15:36:56 time: 0.3459 data_time: 0.0271 memory: 5826 grad_norm: 3.1136 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7654 loss: 2.7654 2022/10/07 22:51:25 - mmengine - INFO - Epoch(train) [74][700/2119] lr: 4.0000e-02 eta: 15:36:49 time: 0.3353 data_time: 0.0194 memory: 5826 grad_norm: 3.1509 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7248 loss: 2.7248 2022/10/07 22:51:32 - mmengine - INFO - Epoch(train) [74][720/2119] lr: 4.0000e-02 eta: 15:36:42 time: 0.3581 data_time: 0.0238 memory: 5826 grad_norm: 3.1116 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7126 loss: 2.7126 2022/10/07 22:51:41 - mmengine - INFO - Epoch(train) [74][740/2119] lr: 4.0000e-02 eta: 15:36:37 time: 0.4439 data_time: 0.0208 memory: 5826 grad_norm: 3.1662 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6445 loss: 2.6445 2022/10/07 22:51:47 - mmengine - INFO - Epoch(train) [74][760/2119] lr: 4.0000e-02 eta: 15:36:29 time: 0.3108 data_time: 0.0232 memory: 5826 grad_norm: 3.1099 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6528 loss: 2.6528 2022/10/07 22:51:55 - mmengine - INFO - Epoch(train) [74][780/2119] lr: 4.0000e-02 eta: 15:36:23 time: 0.3801 data_time: 0.0250 memory: 5826 grad_norm: 3.1211 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6436 loss: 2.6436 2022/10/07 22:52:02 - mmengine - INFO - Epoch(train) [74][800/2119] lr: 4.0000e-02 eta: 15:36:16 time: 0.3438 data_time: 0.0233 memory: 5826 grad_norm: 3.1231 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5152 loss: 2.5152 2022/10/07 22:52:09 - mmengine - INFO - Epoch(train) [74][820/2119] lr: 4.0000e-02 eta: 15:36:09 time: 0.3432 data_time: 0.0232 memory: 5826 grad_norm: 3.1325 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4346 loss: 2.4346 2022/10/07 22:52:15 - mmengine - INFO - Epoch(train) [74][840/2119] lr: 4.0000e-02 eta: 15:36:01 time: 0.2915 data_time: 0.0242 memory: 5826 grad_norm: 3.0825 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6830 loss: 2.6830 2022/10/07 22:52:23 - mmengine - INFO - Epoch(train) [74][860/2119] lr: 4.0000e-02 eta: 15:35:55 time: 0.3938 data_time: 0.0215 memory: 5826 grad_norm: 3.2054 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6155 loss: 2.6155 2022/10/07 22:52:29 - mmengine - INFO - Epoch(train) [74][880/2119] lr: 4.0000e-02 eta: 15:35:48 time: 0.3195 data_time: 0.0228 memory: 5826 grad_norm: 3.0806 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5741 loss: 2.5741 2022/10/07 22:52:35 - mmengine - INFO - Epoch(train) [74][900/2119] lr: 4.0000e-02 eta: 15:35:40 time: 0.3221 data_time: 0.0213 memory: 5826 grad_norm: 3.1242 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4721 loss: 2.4721 2022/10/07 22:52:44 - mmengine - INFO - Epoch(train) [74][920/2119] lr: 4.0000e-02 eta: 15:35:35 time: 0.4159 data_time: 0.0219 memory: 5826 grad_norm: 3.1555 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7755 loss: 2.7755 2022/10/07 22:52:50 - mmengine - INFO - Epoch(train) [74][940/2119] lr: 4.0000e-02 eta: 15:35:28 time: 0.3254 data_time: 0.0295 memory: 5826 grad_norm: 3.1260 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8022 loss: 2.8022 2022/10/07 22:52:59 - mmengine - INFO - Epoch(train) [74][960/2119] lr: 4.0000e-02 eta: 15:35:22 time: 0.4191 data_time: 0.0262 memory: 5826 grad_norm: 3.1006 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7602 loss: 2.7602 2022/10/07 22:53:05 - mmengine - INFO - Epoch(train) [74][980/2119] lr: 4.0000e-02 eta: 15:35:14 time: 0.2998 data_time: 0.0250 memory: 5826 grad_norm: 3.1499 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8312 loss: 2.8312 2022/10/07 22:53:11 - mmengine - INFO - Epoch(train) [74][1000/2119] lr: 4.0000e-02 eta: 15:35:06 time: 0.2971 data_time: 0.0258 memory: 5826 grad_norm: 3.1870 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6087 loss: 2.6087 2022/10/07 22:53:18 - mmengine - INFO - Epoch(train) [74][1020/2119] lr: 4.0000e-02 eta: 15:35:00 time: 0.3943 data_time: 0.0239 memory: 5826 grad_norm: 3.1214 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7836 loss: 2.7836 2022/10/07 22:53:25 - mmengine - INFO - Epoch(train) [74][1040/2119] lr: 4.0000e-02 eta: 15:34:54 time: 0.3499 data_time: 0.0235 memory: 5826 grad_norm: 3.1042 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6872 loss: 2.6872 2022/10/07 22:53:32 - mmengine - INFO - Epoch(train) [74][1060/2119] lr: 4.0000e-02 eta: 15:34:47 time: 0.3530 data_time: 0.0212 memory: 5826 grad_norm: 3.1649 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8986 loss: 2.8986 2022/10/07 22:53:39 - mmengine - INFO - Epoch(train) [74][1080/2119] lr: 4.0000e-02 eta: 15:34:40 time: 0.3460 data_time: 0.0220 memory: 5826 grad_norm: 3.1400 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6883 loss: 2.6883 2022/10/07 22:53:46 - mmengine - INFO - Epoch(train) [74][1100/2119] lr: 4.0000e-02 eta: 15:34:33 time: 0.3486 data_time: 0.0179 memory: 5826 grad_norm: 3.1688 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6822 loss: 2.6822 2022/10/07 22:53:53 - mmengine - INFO - Epoch(train) [74][1120/2119] lr: 4.0000e-02 eta: 15:34:26 time: 0.3510 data_time: 0.0257 memory: 5826 grad_norm: 3.1755 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7522 loss: 2.7522 2022/10/07 22:54:00 - mmengine - INFO - Epoch(train) [74][1140/2119] lr: 4.0000e-02 eta: 15:34:19 time: 0.3434 data_time: 0.0327 memory: 5826 grad_norm: 3.1140 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8659 loss: 2.8659 2022/10/07 22:54:07 - mmengine - INFO - Epoch(train) [74][1160/2119] lr: 4.0000e-02 eta: 15:34:12 time: 0.3255 data_time: 0.0270 memory: 5826 grad_norm: 3.1140 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6854 loss: 2.6854 2022/10/07 22:54:16 - mmengine - INFO - Epoch(train) [74][1180/2119] lr: 4.0000e-02 eta: 15:34:07 time: 0.4508 data_time: 0.0218 memory: 5826 grad_norm: 3.0721 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6379 loss: 2.6379 2022/10/07 22:54:22 - mmengine - INFO - Epoch(train) [74][1200/2119] lr: 4.0000e-02 eta: 15:34:00 time: 0.3267 data_time: 0.0235 memory: 5826 grad_norm: 3.1337 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9580 loss: 2.9580 2022/10/07 22:54:29 - mmengine - INFO - Epoch(train) [74][1220/2119] lr: 4.0000e-02 eta: 15:33:53 time: 0.3415 data_time: 0.0213 memory: 5826 grad_norm: 3.1787 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7029 loss: 2.7029 2022/10/07 22:54:36 - mmengine - INFO - Epoch(train) [74][1240/2119] lr: 4.0000e-02 eta: 15:33:45 time: 0.3151 data_time: 0.0248 memory: 5826 grad_norm: 3.1204 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.8934 loss: 2.8934 2022/10/07 22:54:42 - mmengine - INFO - Epoch(train) [74][1260/2119] lr: 4.0000e-02 eta: 15:33:38 time: 0.3470 data_time: 0.0228 memory: 5826 grad_norm: 3.0912 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8218 loss: 2.8218 2022/10/07 22:54:49 - mmengine - INFO - Epoch(train) [74][1280/2119] lr: 4.0000e-02 eta: 15:33:31 time: 0.3395 data_time: 0.0237 memory: 5826 grad_norm: 3.0590 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5838 loss: 2.5838 2022/10/07 22:54:56 - mmengine - INFO - Epoch(train) [74][1300/2119] lr: 4.0000e-02 eta: 15:33:24 time: 0.3337 data_time: 0.0231 memory: 5826 grad_norm: 3.1843 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6010 loss: 2.6010 2022/10/07 22:55:01 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 22:55:03 - mmengine - INFO - Epoch(train) [74][1320/2119] lr: 4.0000e-02 eta: 15:33:17 time: 0.3368 data_time: 0.0257 memory: 5826 grad_norm: 3.1823 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8811 loss: 2.8811 2022/10/07 22:55:11 - mmengine - INFO - Epoch(train) [74][1340/2119] lr: 4.0000e-02 eta: 15:33:11 time: 0.4031 data_time: 0.0241 memory: 5826 grad_norm: 3.1718 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8340 loss: 2.8340 2022/10/07 22:55:18 - mmengine - INFO - Epoch(train) [74][1360/2119] lr: 4.0000e-02 eta: 15:33:05 time: 0.3745 data_time: 0.0186 memory: 5826 grad_norm: 3.1327 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8651 loss: 2.8651 2022/10/07 22:55:25 - mmengine - INFO - Epoch(train) [74][1380/2119] lr: 4.0000e-02 eta: 15:32:58 time: 0.3471 data_time: 0.0260 memory: 5826 grad_norm: 3.1252 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9027 loss: 2.9027 2022/10/07 22:55:31 - mmengine - INFO - Epoch(train) [74][1400/2119] lr: 4.0000e-02 eta: 15:32:50 time: 0.2936 data_time: 0.0242 memory: 5826 grad_norm: 3.0753 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.9327 loss: 2.9327 2022/10/07 22:55:39 - mmengine - INFO - Epoch(train) [74][1420/2119] lr: 4.0000e-02 eta: 15:32:44 time: 0.3765 data_time: 0.0206 memory: 5826 grad_norm: 3.0666 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7159 loss: 2.7159 2022/10/07 22:55:45 - mmengine - INFO - Epoch(train) [74][1440/2119] lr: 4.0000e-02 eta: 15:32:36 time: 0.3040 data_time: 0.0254 memory: 5826 grad_norm: 3.1101 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8467 loss: 2.8467 2022/10/07 22:55:52 - mmengine - INFO - Epoch(train) [74][1460/2119] lr: 4.0000e-02 eta: 15:32:30 time: 0.3672 data_time: 0.0257 memory: 5826 grad_norm: 3.1156 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6793 loss: 2.6793 2022/10/07 22:55:59 - mmengine - INFO - Epoch(train) [74][1480/2119] lr: 4.0000e-02 eta: 15:32:22 time: 0.3322 data_time: 0.0240 memory: 5826 grad_norm: 3.1676 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7923 loss: 2.7923 2022/10/07 22:56:06 - mmengine - INFO - Epoch(train) [74][1500/2119] lr: 4.0000e-02 eta: 15:32:15 time: 0.3459 data_time: 0.0213 memory: 5826 grad_norm: 3.0913 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7191 loss: 2.7191 2022/10/07 22:56:12 - mmengine - INFO - Epoch(train) [74][1520/2119] lr: 4.0000e-02 eta: 15:32:08 time: 0.3298 data_time: 0.0230 memory: 5826 grad_norm: 3.1070 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9747 loss: 2.9747 2022/10/07 22:56:20 - mmengine - INFO - Epoch(train) [74][1540/2119] lr: 4.0000e-02 eta: 15:32:02 time: 0.3685 data_time: 0.0263 memory: 5826 grad_norm: 3.0964 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9302 loss: 2.9302 2022/10/07 22:56:26 - mmengine - INFO - Epoch(train) [74][1560/2119] lr: 4.0000e-02 eta: 15:31:54 time: 0.3114 data_time: 0.0226 memory: 5826 grad_norm: 3.0891 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4486 loss: 2.4486 2022/10/07 22:56:33 - mmengine - INFO - Epoch(train) [74][1580/2119] lr: 4.0000e-02 eta: 15:31:48 time: 0.3797 data_time: 0.0206 memory: 5826 grad_norm: 3.1206 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7867 loss: 2.7867 2022/10/07 22:56:40 - mmengine - INFO - Epoch(train) [74][1600/2119] lr: 4.0000e-02 eta: 15:31:41 time: 0.3513 data_time: 0.0262 memory: 5826 grad_norm: 3.1628 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2801 loss: 2.2801 2022/10/07 22:56:48 - mmengine - INFO - Epoch(train) [74][1620/2119] lr: 4.0000e-02 eta: 15:31:34 time: 0.3550 data_time: 0.0223 memory: 5826 grad_norm: 3.1608 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.8367 loss: 2.8367 2022/10/07 22:56:54 - mmengine - INFO - Epoch(train) [74][1640/2119] lr: 4.0000e-02 eta: 15:31:27 time: 0.3425 data_time: 0.0218 memory: 5826 grad_norm: 3.1531 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6440 loss: 2.6440 2022/10/07 22:57:01 - mmengine - INFO - Epoch(train) [74][1660/2119] lr: 4.0000e-02 eta: 15:31:20 time: 0.3424 data_time: 0.0260 memory: 5826 grad_norm: 3.1035 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7002 loss: 2.7002 2022/10/07 22:57:07 - mmengine - INFO - Epoch(train) [74][1680/2119] lr: 4.0000e-02 eta: 15:31:13 time: 0.3100 data_time: 0.0269 memory: 5826 grad_norm: 3.1229 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6225 loss: 2.6225 2022/10/07 22:57:15 - mmengine - INFO - Epoch(train) [74][1700/2119] lr: 4.0000e-02 eta: 15:31:06 time: 0.3826 data_time: 0.0204 memory: 5826 grad_norm: 3.1837 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7859 loss: 2.7859 2022/10/07 22:57:23 - mmengine - INFO - Epoch(train) [74][1720/2119] lr: 4.0000e-02 eta: 15:31:00 time: 0.3876 data_time: 0.0206 memory: 5826 grad_norm: 3.0898 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.5852 loss: 2.5852 2022/10/07 22:57:29 - mmengine - INFO - Epoch(train) [74][1740/2119] lr: 4.0000e-02 eta: 15:30:53 time: 0.3135 data_time: 0.0230 memory: 5826 grad_norm: 3.1020 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7558 loss: 2.7558 2022/10/07 22:57:36 - mmengine - INFO - Epoch(train) [74][1760/2119] lr: 4.0000e-02 eta: 15:30:46 time: 0.3303 data_time: 0.0237 memory: 5826 grad_norm: 3.0898 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6638 loss: 2.6638 2022/10/07 22:57:44 - mmengine - INFO - Epoch(train) [74][1780/2119] lr: 4.0000e-02 eta: 15:30:40 time: 0.3991 data_time: 0.0189 memory: 5826 grad_norm: 3.1221 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8457 loss: 2.8457 2022/10/07 22:57:49 - mmengine - INFO - Epoch(train) [74][1800/2119] lr: 4.0000e-02 eta: 15:30:31 time: 0.2819 data_time: 0.0216 memory: 5826 grad_norm: 3.1072 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5850 loss: 2.5850 2022/10/07 22:57:57 - mmengine - INFO - Epoch(train) [74][1820/2119] lr: 4.0000e-02 eta: 15:30:25 time: 0.3748 data_time: 0.0291 memory: 5826 grad_norm: 3.1212 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8098 loss: 2.8098 2022/10/07 22:58:04 - mmengine - INFO - Epoch(train) [74][1840/2119] lr: 4.0000e-02 eta: 15:30:18 time: 0.3521 data_time: 0.0193 memory: 5826 grad_norm: 3.1139 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6598 loss: 2.6598 2022/10/07 22:58:11 - mmengine - INFO - Epoch(train) [74][1860/2119] lr: 4.0000e-02 eta: 15:30:11 time: 0.3418 data_time: 0.0266 memory: 5826 grad_norm: 3.1290 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7468 loss: 2.7468 2022/10/07 22:58:17 - mmengine - INFO - Epoch(train) [74][1880/2119] lr: 4.0000e-02 eta: 15:30:04 time: 0.3182 data_time: 0.0213 memory: 5826 grad_norm: 3.0676 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7962 loss: 2.7962 2022/10/07 22:58:25 - mmengine - INFO - Epoch(train) [74][1900/2119] lr: 4.0000e-02 eta: 15:29:57 time: 0.3714 data_time: 0.0266 memory: 5826 grad_norm: 3.0765 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6887 loss: 2.6887 2022/10/07 22:58:31 - mmengine - INFO - Epoch(train) [74][1920/2119] lr: 4.0000e-02 eta: 15:29:50 time: 0.3317 data_time: 0.0278 memory: 5826 grad_norm: 3.1089 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7438 loss: 2.7438 2022/10/07 22:58:38 - mmengine - INFO - Epoch(train) [74][1940/2119] lr: 4.0000e-02 eta: 15:29:43 time: 0.3272 data_time: 0.0249 memory: 5826 grad_norm: 3.0364 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7109 loss: 2.7109 2022/10/07 22:58:45 - mmengine - INFO - Epoch(train) [74][1960/2119] lr: 4.0000e-02 eta: 15:29:36 time: 0.3678 data_time: 0.0255 memory: 5826 grad_norm: 3.1796 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7554 loss: 2.7554 2022/10/07 22:58:52 - mmengine - INFO - Epoch(train) [74][1980/2119] lr: 4.0000e-02 eta: 15:29:29 time: 0.3382 data_time: 0.0302 memory: 5826 grad_norm: 3.1325 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6708 loss: 2.6708 2022/10/07 22:58:59 - mmengine - INFO - Epoch(train) [74][2000/2119] lr: 4.0000e-02 eta: 15:29:23 time: 0.3606 data_time: 0.0234 memory: 5826 grad_norm: 3.1422 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7070 loss: 2.7070 2022/10/07 22:59:06 - mmengine - INFO - Epoch(train) [74][2020/2119] lr: 4.0000e-02 eta: 15:29:16 time: 0.3656 data_time: 0.0179 memory: 5826 grad_norm: 3.1404 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7019 loss: 2.7019 2022/10/07 22:59:14 - mmengine - INFO - Epoch(train) [74][2040/2119] lr: 4.0000e-02 eta: 15:29:10 time: 0.3579 data_time: 0.0227 memory: 5826 grad_norm: 3.1164 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6314 loss: 2.6314 2022/10/07 22:59:22 - mmengine - INFO - Epoch(train) [74][2060/2119] lr: 4.0000e-02 eta: 15:29:04 time: 0.4121 data_time: 0.0257 memory: 5826 grad_norm: 3.1235 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7409 loss: 2.7409 2022/10/07 22:59:28 - mmengine - INFO - Epoch(train) [74][2080/2119] lr: 4.0000e-02 eta: 15:28:57 time: 0.3254 data_time: 0.0190 memory: 5826 grad_norm: 3.1523 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 3.0890 loss: 3.0890 2022/10/07 22:59:35 - mmengine - INFO - Epoch(train) [74][2100/2119] lr: 4.0000e-02 eta: 15:28:49 time: 0.3071 data_time: 0.0271 memory: 5826 grad_norm: 3.1453 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8998 loss: 2.8998 2022/10/07 22:59:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 22:59:40 - mmengine - INFO - Epoch(train) [74][2119/2119] lr: 4.0000e-02 eta: 15:28:49 time: 0.3118 data_time: 0.0196 memory: 5826 grad_norm: 3.1580 top1_acc: 0.5000 top5_acc: 0.7000 loss_cls: 2.5480 loss: 2.5480 2022/10/07 22:59:50 - mmengine - INFO - Epoch(train) [75][20/2119] lr: 4.0000e-02 eta: 15:28:32 time: 0.4921 data_time: 0.1071 memory: 5826 grad_norm: 3.1268 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7654 loss: 2.7654 2022/10/07 22:59:57 - mmengine - INFO - Epoch(train) [75][40/2119] lr: 4.0000e-02 eta: 15:28:25 time: 0.3375 data_time: 0.0228 memory: 5826 grad_norm: 3.1785 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8903 loss: 2.8903 2022/10/07 23:00:05 - mmengine - INFO - Epoch(train) [75][60/2119] lr: 4.0000e-02 eta: 15:28:19 time: 0.4119 data_time: 0.0201 memory: 5826 grad_norm: 3.1303 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7979 loss: 2.7979 2022/10/07 23:00:12 - mmengine - INFO - Epoch(train) [75][80/2119] lr: 4.0000e-02 eta: 15:28:12 time: 0.3274 data_time: 0.0205 memory: 5826 grad_norm: 3.1241 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5836 loss: 2.5836 2022/10/07 23:00:19 - mmengine - INFO - Epoch(train) [75][100/2119] lr: 4.0000e-02 eta: 15:28:05 time: 0.3641 data_time: 0.0210 memory: 5826 grad_norm: 3.2151 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9583 loss: 2.9583 2022/10/07 23:00:26 - mmengine - INFO - Epoch(train) [75][120/2119] lr: 4.0000e-02 eta: 15:27:58 time: 0.3205 data_time: 0.0267 memory: 5826 grad_norm: 3.0814 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6571 loss: 2.6571 2022/10/07 23:00:33 - mmengine - INFO - Epoch(train) [75][140/2119] lr: 4.0000e-02 eta: 15:27:52 time: 0.3799 data_time: 0.0234 memory: 5826 grad_norm: 3.1101 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7213 loss: 2.7213 2022/10/07 23:00:39 - mmengine - INFO - Epoch(train) [75][160/2119] lr: 4.0000e-02 eta: 15:27:44 time: 0.3058 data_time: 0.0230 memory: 5826 grad_norm: 3.1616 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8258 loss: 2.8258 2022/10/07 23:00:48 - mmengine - INFO - Epoch(train) [75][180/2119] lr: 4.0000e-02 eta: 15:27:38 time: 0.4079 data_time: 0.0247 memory: 5826 grad_norm: 3.1367 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7371 loss: 2.7371 2022/10/07 23:00:53 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 23:00:54 - mmengine - INFO - Epoch(train) [75][200/2119] lr: 4.0000e-02 eta: 15:27:31 time: 0.3279 data_time: 0.0238 memory: 5826 grad_norm: 3.0994 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6251 loss: 2.6251 2022/10/07 23:01:01 - mmengine - INFO - Epoch(train) [75][220/2119] lr: 4.0000e-02 eta: 15:27:24 time: 0.3347 data_time: 0.0219 memory: 5826 grad_norm: 3.1165 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5788 loss: 2.5788 2022/10/07 23:01:07 - mmengine - INFO - Epoch(train) [75][240/2119] lr: 4.0000e-02 eta: 15:27:16 time: 0.3252 data_time: 0.0239 memory: 5826 grad_norm: 3.1019 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7297 loss: 2.7297 2022/10/07 23:01:15 - mmengine - INFO - Epoch(train) [75][260/2119] lr: 4.0000e-02 eta: 15:27:10 time: 0.3607 data_time: 0.0212 memory: 5826 grad_norm: 3.1509 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8101 loss: 2.8101 2022/10/07 23:01:22 - mmengine - INFO - Epoch(train) [75][280/2119] lr: 4.0000e-02 eta: 15:27:04 time: 0.3814 data_time: 0.0240 memory: 5826 grad_norm: 3.0373 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8495 loss: 2.8495 2022/10/07 23:01:29 - mmengine - INFO - Epoch(train) [75][300/2119] lr: 4.0000e-02 eta: 15:26:56 time: 0.3175 data_time: 0.0201 memory: 5826 grad_norm: 3.1053 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6998 loss: 2.6998 2022/10/07 23:01:35 - mmengine - INFO - Epoch(train) [75][320/2119] lr: 4.0000e-02 eta: 15:26:49 time: 0.3312 data_time: 0.0205 memory: 5826 grad_norm: 3.1699 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7008 loss: 2.7008 2022/10/07 23:01:44 - mmengine - INFO - Epoch(train) [75][340/2119] lr: 4.0000e-02 eta: 15:26:43 time: 0.4203 data_time: 0.0189 memory: 5826 grad_norm: 3.1831 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.7501 loss: 2.7501 2022/10/07 23:01:51 - mmengine - INFO - Epoch(train) [75][360/2119] lr: 4.0000e-02 eta: 15:26:36 time: 0.3441 data_time: 0.0276 memory: 5826 grad_norm: 3.1143 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6683 loss: 2.6683 2022/10/07 23:01:58 - mmengine - INFO - Epoch(train) [75][380/2119] lr: 4.0000e-02 eta: 15:26:30 time: 0.3547 data_time: 0.0256 memory: 5826 grad_norm: 3.1273 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6438 loss: 2.6438 2022/10/07 23:02:05 - mmengine - INFO - Epoch(train) [75][400/2119] lr: 4.0000e-02 eta: 15:26:23 time: 0.3542 data_time: 0.0245 memory: 5826 grad_norm: 3.1299 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7275 loss: 2.7275 2022/10/07 23:02:12 - mmengine - INFO - Epoch(train) [75][420/2119] lr: 4.0000e-02 eta: 15:26:17 time: 0.3851 data_time: 0.0207 memory: 5826 grad_norm: 3.1295 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5977 loss: 2.5977 2022/10/07 23:02:19 - mmengine - INFO - Epoch(train) [75][440/2119] lr: 4.0000e-02 eta: 15:26:10 time: 0.3391 data_time: 0.0220 memory: 5826 grad_norm: 3.1549 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5232 loss: 2.5232 2022/10/07 23:02:26 - mmengine - INFO - Epoch(train) [75][460/2119] lr: 4.0000e-02 eta: 15:26:03 time: 0.3617 data_time: 0.0221 memory: 5826 grad_norm: 3.1568 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7063 loss: 2.7063 2022/10/07 23:02:32 - mmengine - INFO - Epoch(train) [75][480/2119] lr: 4.0000e-02 eta: 15:25:55 time: 0.3004 data_time: 0.0244 memory: 5826 grad_norm: 3.1355 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7677 loss: 2.7677 2022/10/07 23:02:41 - mmengine - INFO - Epoch(train) [75][500/2119] lr: 4.0000e-02 eta: 15:25:50 time: 0.4077 data_time: 0.0246 memory: 5826 grad_norm: 3.1458 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.4653 loss: 2.4653 2022/10/07 23:02:47 - mmengine - INFO - Epoch(train) [75][520/2119] lr: 4.0000e-02 eta: 15:25:42 time: 0.3049 data_time: 0.0247 memory: 5826 grad_norm: 3.1682 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8078 loss: 2.8078 2022/10/07 23:02:54 - mmengine - INFO - Epoch(train) [75][540/2119] lr: 4.0000e-02 eta: 15:25:35 time: 0.3595 data_time: 0.0239 memory: 5826 grad_norm: 3.1726 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6626 loss: 2.6626 2022/10/07 23:03:01 - mmengine - INFO - Epoch(train) [75][560/2119] lr: 4.0000e-02 eta: 15:25:29 time: 0.3709 data_time: 0.0248 memory: 5826 grad_norm: 3.1450 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8274 loss: 2.8274 2022/10/07 23:03:09 - mmengine - INFO - Epoch(train) [75][580/2119] lr: 4.0000e-02 eta: 15:25:23 time: 0.3911 data_time: 0.0254 memory: 5826 grad_norm: 3.1292 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.5872 loss: 2.5872 2022/10/07 23:03:15 - mmengine - INFO - Epoch(train) [75][600/2119] lr: 4.0000e-02 eta: 15:25:15 time: 0.3155 data_time: 0.0227 memory: 5826 grad_norm: 3.1873 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7956 loss: 2.7956 2022/10/07 23:03:23 - mmengine - INFO - Epoch(train) [75][620/2119] lr: 4.0000e-02 eta: 15:25:09 time: 0.3726 data_time: 0.0220 memory: 5826 grad_norm: 3.1193 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6346 loss: 2.6346 2022/10/07 23:03:30 - mmengine - INFO - Epoch(train) [75][640/2119] lr: 4.0000e-02 eta: 15:25:02 time: 0.3557 data_time: 0.0234 memory: 5826 grad_norm: 3.1103 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8087 loss: 2.8087 2022/10/07 23:03:38 - mmengine - INFO - Epoch(train) [75][660/2119] lr: 4.0000e-02 eta: 15:24:56 time: 0.3885 data_time: 0.0259 memory: 5826 grad_norm: 3.1297 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6036 loss: 2.6036 2022/10/07 23:03:44 - mmengine - INFO - Epoch(train) [75][680/2119] lr: 4.0000e-02 eta: 15:24:49 time: 0.3325 data_time: 0.0227 memory: 5826 grad_norm: 3.1113 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5682 loss: 2.5682 2022/10/07 23:03:51 - mmengine - INFO - Epoch(train) [75][700/2119] lr: 4.0000e-02 eta: 15:24:42 time: 0.3493 data_time: 0.0200 memory: 5826 grad_norm: 3.1060 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6746 loss: 2.6746 2022/10/07 23:03:58 - mmengine - INFO - Epoch(train) [75][720/2119] lr: 4.0000e-02 eta: 15:24:35 time: 0.3487 data_time: 0.0250 memory: 5826 grad_norm: 3.1575 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7386 loss: 2.7386 2022/10/07 23:04:07 - mmengine - INFO - Epoch(train) [75][740/2119] lr: 4.0000e-02 eta: 15:24:30 time: 0.4101 data_time: 0.0196 memory: 5826 grad_norm: 3.1266 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5230 loss: 2.5230 2022/10/07 23:04:13 - mmengine - INFO - Epoch(train) [75][760/2119] lr: 4.0000e-02 eta: 15:24:22 time: 0.3203 data_time: 0.0230 memory: 5826 grad_norm: 3.0980 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8011 loss: 2.8011 2022/10/07 23:04:21 - mmengine - INFO - Epoch(train) [75][780/2119] lr: 4.0000e-02 eta: 15:24:16 time: 0.4030 data_time: 0.0296 memory: 5826 grad_norm: 3.1279 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8923 loss: 2.8923 2022/10/07 23:04:28 - mmengine - INFO - Epoch(train) [75][800/2119] lr: 4.0000e-02 eta: 15:24:09 time: 0.3301 data_time: 0.0224 memory: 5826 grad_norm: 3.0983 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7133 loss: 2.7133 2022/10/07 23:04:35 - mmengine - INFO - Epoch(train) [75][820/2119] lr: 4.0000e-02 eta: 15:24:03 time: 0.3696 data_time: 0.0191 memory: 5826 grad_norm: 3.0974 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6495 loss: 2.6495 2022/10/07 23:04:41 - mmengine - INFO - Epoch(train) [75][840/2119] lr: 4.0000e-02 eta: 15:23:55 time: 0.2832 data_time: 0.0259 memory: 5826 grad_norm: 3.1448 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 2.4737 loss: 2.4737 2022/10/07 23:04:48 - mmengine - INFO - Epoch(train) [75][860/2119] lr: 4.0000e-02 eta: 15:23:48 time: 0.3512 data_time: 0.0266 memory: 5826 grad_norm: 3.0816 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6068 loss: 2.6068 2022/10/07 23:04:54 - mmengine - INFO - Epoch(train) [75][880/2119] lr: 4.0000e-02 eta: 15:23:40 time: 0.3264 data_time: 0.0248 memory: 5826 grad_norm: 3.1721 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7517 loss: 2.7517 2022/10/07 23:05:02 - mmengine - INFO - Epoch(train) [75][900/2119] lr: 4.0000e-02 eta: 15:23:34 time: 0.3745 data_time: 0.0254 memory: 5826 grad_norm: 3.1019 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6998 loss: 2.6998 2022/10/07 23:05:09 - mmengine - INFO - Epoch(train) [75][920/2119] lr: 4.0000e-02 eta: 15:23:27 time: 0.3584 data_time: 0.0313 memory: 5826 grad_norm: 3.1912 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 3.0348 loss: 3.0348 2022/10/07 23:05:16 - mmengine - INFO - Epoch(train) [75][940/2119] lr: 4.0000e-02 eta: 15:23:21 time: 0.3713 data_time: 0.0244 memory: 5826 grad_norm: 3.1410 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7165 loss: 2.7165 2022/10/07 23:05:24 - mmengine - INFO - Epoch(train) [75][960/2119] lr: 4.0000e-02 eta: 15:23:14 time: 0.3614 data_time: 0.0290 memory: 5826 grad_norm: 3.1301 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8011 loss: 2.8011 2022/10/07 23:05:31 - mmengine - INFO - Epoch(train) [75][980/2119] lr: 4.0000e-02 eta: 15:23:08 time: 0.3488 data_time: 0.0222 memory: 5826 grad_norm: 3.1593 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9327 loss: 2.9327 2022/10/07 23:05:38 - mmengine - INFO - Epoch(train) [75][1000/2119] lr: 4.0000e-02 eta: 15:23:01 time: 0.3736 data_time: 0.0222 memory: 5826 grad_norm: 3.1072 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8971 loss: 2.8971 2022/10/07 23:05:46 - mmengine - INFO - Epoch(train) [75][1020/2119] lr: 4.0000e-02 eta: 15:22:55 time: 0.3717 data_time: 0.0277 memory: 5826 grad_norm: 3.1680 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6838 loss: 2.6838 2022/10/07 23:05:52 - mmengine - INFO - Epoch(train) [75][1040/2119] lr: 4.0000e-02 eta: 15:22:48 time: 0.3361 data_time: 0.0246 memory: 5826 grad_norm: 3.0956 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7355 loss: 2.7355 2022/10/07 23:06:00 - mmengine - INFO - Epoch(train) [75][1060/2119] lr: 4.0000e-02 eta: 15:22:41 time: 0.3769 data_time: 0.0181 memory: 5826 grad_norm: 3.1699 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7617 loss: 2.7617 2022/10/07 23:06:06 - mmengine - INFO - Epoch(train) [75][1080/2119] lr: 4.0000e-02 eta: 15:22:34 time: 0.3038 data_time: 0.0250 memory: 5826 grad_norm: 3.1753 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6919 loss: 2.6919 2022/10/07 23:06:14 - mmengine - INFO - Epoch(train) [75][1100/2119] lr: 4.0000e-02 eta: 15:22:27 time: 0.3783 data_time: 0.0200 memory: 5826 grad_norm: 3.1111 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7805 loss: 2.7805 2022/10/07 23:06:21 - mmengine - INFO - Epoch(train) [75][1120/2119] lr: 4.0000e-02 eta: 15:22:21 time: 0.3576 data_time: 0.0211 memory: 5826 grad_norm: 3.1295 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7083 loss: 2.7083 2022/10/07 23:06:28 - mmengine - INFO - Epoch(train) [75][1140/2119] lr: 4.0000e-02 eta: 15:22:14 time: 0.3497 data_time: 0.0250 memory: 5826 grad_norm: 3.1277 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5922 loss: 2.5922 2022/10/07 23:06:35 - mmengine - INFO - Epoch(train) [75][1160/2119] lr: 4.0000e-02 eta: 15:22:07 time: 0.3476 data_time: 0.0230 memory: 5826 grad_norm: 3.2016 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.7421 loss: 2.7421 2022/10/07 23:06:42 - mmengine - INFO - Epoch(train) [75][1180/2119] lr: 4.0000e-02 eta: 15:22:00 time: 0.3649 data_time: 0.0202 memory: 5826 grad_norm: 3.0768 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9295 loss: 2.9295 2022/10/07 23:06:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 23:06:49 - mmengine - INFO - Epoch(train) [75][1200/2119] lr: 4.0000e-02 eta: 15:21:54 time: 0.3750 data_time: 0.0223 memory: 5826 grad_norm: 3.1120 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7503 loss: 2.7503 2022/10/07 23:06:57 - mmengine - INFO - Epoch(train) [75][1220/2119] lr: 4.0000e-02 eta: 15:21:48 time: 0.3690 data_time: 0.0215 memory: 5826 grad_norm: 3.1246 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7256 loss: 2.7256 2022/10/07 23:07:03 - mmengine - INFO - Epoch(train) [75][1240/2119] lr: 4.0000e-02 eta: 15:21:40 time: 0.3238 data_time: 0.0236 memory: 5826 grad_norm: 3.1322 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4809 loss: 2.4809 2022/10/07 23:07:10 - mmengine - INFO - Epoch(train) [75][1260/2119] lr: 4.0000e-02 eta: 15:21:33 time: 0.3587 data_time: 0.0230 memory: 5826 grad_norm: 3.0841 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8493 loss: 2.8493 2022/10/07 23:07:17 - mmengine - INFO - Epoch(train) [75][1280/2119] lr: 4.0000e-02 eta: 15:21:26 time: 0.3363 data_time: 0.0241 memory: 5826 grad_norm: 3.0779 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8371 loss: 2.8371 2022/10/07 23:07:25 - mmengine - INFO - Epoch(train) [75][1300/2119] lr: 4.0000e-02 eta: 15:21:20 time: 0.3892 data_time: 0.0274 memory: 5826 grad_norm: 3.1186 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0451 loss: 3.0451 2022/10/07 23:07:32 - mmengine - INFO - Epoch(train) [75][1320/2119] lr: 4.0000e-02 eta: 15:21:13 time: 0.3391 data_time: 0.0228 memory: 5826 grad_norm: 3.0971 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6862 loss: 2.6862 2022/10/07 23:07:40 - mmengine - INFO - Epoch(train) [75][1340/2119] lr: 4.0000e-02 eta: 15:21:08 time: 0.4195 data_time: 0.0234 memory: 5826 grad_norm: 3.1893 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4666 loss: 2.4666 2022/10/07 23:07:46 - mmengine - INFO - Epoch(train) [75][1360/2119] lr: 4.0000e-02 eta: 15:20:59 time: 0.2707 data_time: 0.0253 memory: 5826 grad_norm: 3.0687 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8617 loss: 2.8617 2022/10/07 23:07:53 - mmengine - INFO - Epoch(train) [75][1380/2119] lr: 4.0000e-02 eta: 15:20:53 time: 0.3727 data_time: 0.0222 memory: 5826 grad_norm: 3.1543 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7571 loss: 2.7571 2022/10/07 23:08:00 - mmengine - INFO - Epoch(train) [75][1400/2119] lr: 4.0000e-02 eta: 15:20:46 time: 0.3495 data_time: 0.0246 memory: 5826 grad_norm: 3.1336 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6923 loss: 2.6923 2022/10/07 23:08:07 - mmengine - INFO - Epoch(train) [75][1420/2119] lr: 4.0000e-02 eta: 15:20:39 time: 0.3376 data_time: 0.0230 memory: 5826 grad_norm: 3.1329 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7521 loss: 2.7521 2022/10/07 23:08:14 - mmengine - INFO - Epoch(train) [75][1440/2119] lr: 4.0000e-02 eta: 15:20:32 time: 0.3456 data_time: 0.0287 memory: 5826 grad_norm: 3.1890 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5171 loss: 2.5171 2022/10/07 23:08:21 - mmengine - INFO - Epoch(train) [75][1460/2119] lr: 4.0000e-02 eta: 15:20:25 time: 0.3534 data_time: 0.0213 memory: 5826 grad_norm: 3.1452 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7261 loss: 2.7261 2022/10/07 23:08:27 - mmengine - INFO - Epoch(train) [75][1480/2119] lr: 4.0000e-02 eta: 15:20:18 time: 0.3046 data_time: 0.0354 memory: 5826 grad_norm: 3.0951 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6744 loss: 2.6744 2022/10/07 23:08:35 - mmengine - INFO - Epoch(train) [75][1500/2119] lr: 4.0000e-02 eta: 15:20:11 time: 0.3852 data_time: 0.0256 memory: 5826 grad_norm: 3.0352 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7176 loss: 2.7176 2022/10/07 23:08:41 - mmengine - INFO - Epoch(train) [75][1520/2119] lr: 4.0000e-02 eta: 15:20:04 time: 0.3357 data_time: 0.0268 memory: 5826 grad_norm: 3.0857 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6907 loss: 2.6907 2022/10/07 23:08:48 - mmengine - INFO - Epoch(train) [75][1540/2119] lr: 4.0000e-02 eta: 15:19:57 time: 0.3504 data_time: 0.0195 memory: 5826 grad_norm: 3.0697 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7445 loss: 2.7445 2022/10/07 23:08:55 - mmengine - INFO - Epoch(train) [75][1560/2119] lr: 4.0000e-02 eta: 15:19:51 time: 0.3483 data_time: 0.0264 memory: 5826 grad_norm: 3.1261 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.7201 loss: 2.7201 2022/10/07 23:09:03 - mmengine - INFO - Epoch(train) [75][1580/2119] lr: 4.0000e-02 eta: 15:19:45 time: 0.3886 data_time: 0.0346 memory: 5826 grad_norm: 3.1907 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7638 loss: 2.7638 2022/10/07 23:09:10 - mmengine - INFO - Epoch(train) [75][1600/2119] lr: 4.0000e-02 eta: 15:19:37 time: 0.3211 data_time: 0.0302 memory: 5826 grad_norm: 3.1531 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6178 loss: 2.6178 2022/10/07 23:09:16 - mmengine - INFO - Epoch(train) [75][1620/2119] lr: 4.0000e-02 eta: 15:19:30 time: 0.3335 data_time: 0.0222 memory: 5826 grad_norm: 3.1252 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6098 loss: 2.6098 2022/10/07 23:09:23 - mmengine - INFO - Epoch(train) [75][1640/2119] lr: 4.0000e-02 eta: 15:19:23 time: 0.3394 data_time: 0.0257 memory: 5826 grad_norm: 3.1424 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7541 loss: 2.7541 2022/10/07 23:09:30 - mmengine - INFO - Epoch(train) [75][1660/2119] lr: 4.0000e-02 eta: 15:19:16 time: 0.3647 data_time: 0.0220 memory: 5826 grad_norm: 3.0780 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7403 loss: 2.7403 2022/10/07 23:09:37 - mmengine - INFO - Epoch(train) [75][1680/2119] lr: 4.0000e-02 eta: 15:19:09 time: 0.3262 data_time: 0.0256 memory: 5826 grad_norm: 3.1488 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7089 loss: 2.7089 2022/10/07 23:09:44 - mmengine - INFO - Epoch(train) [75][1700/2119] lr: 4.0000e-02 eta: 15:19:03 time: 0.3776 data_time: 0.0227 memory: 5826 grad_norm: 3.0787 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7643 loss: 2.7643 2022/10/07 23:09:51 - mmengine - INFO - Epoch(train) [75][1720/2119] lr: 4.0000e-02 eta: 15:18:56 time: 0.3454 data_time: 0.0226 memory: 5826 grad_norm: 3.1331 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7942 loss: 2.7942 2022/10/07 23:09:59 - mmengine - INFO - Epoch(train) [75][1740/2119] lr: 4.0000e-02 eta: 15:18:49 time: 0.3765 data_time: 0.0218 memory: 5826 grad_norm: 3.1082 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6540 loss: 2.6540 2022/10/07 23:10:05 - mmengine - INFO - Epoch(train) [75][1760/2119] lr: 4.0000e-02 eta: 15:18:42 time: 0.3293 data_time: 0.0233 memory: 5826 grad_norm: 3.1228 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5084 loss: 2.5084 2022/10/07 23:10:14 - mmengine - INFO - Epoch(train) [75][1780/2119] lr: 4.0000e-02 eta: 15:18:36 time: 0.4043 data_time: 0.0292 memory: 5826 grad_norm: 3.1109 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.4928 loss: 2.4928 2022/10/07 23:10:20 - mmengine - INFO - Epoch(train) [75][1800/2119] lr: 4.0000e-02 eta: 15:18:29 time: 0.3273 data_time: 0.0212 memory: 5826 grad_norm: 3.1355 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7535 loss: 2.7535 2022/10/07 23:10:28 - mmengine - INFO - Epoch(train) [75][1820/2119] lr: 4.0000e-02 eta: 15:18:23 time: 0.3894 data_time: 0.0225 memory: 5826 grad_norm: 3.1389 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6111 loss: 2.6111 2022/10/07 23:10:34 - mmengine - INFO - Epoch(train) [75][1840/2119] lr: 4.0000e-02 eta: 15:18:16 time: 0.3269 data_time: 0.0234 memory: 5826 grad_norm: 3.0865 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5768 loss: 2.5768 2022/10/07 23:10:42 - mmengine - INFO - Epoch(train) [75][1860/2119] lr: 4.0000e-02 eta: 15:18:10 time: 0.3859 data_time: 0.0203 memory: 5826 grad_norm: 3.1558 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7163 loss: 2.7163 2022/10/07 23:10:49 - mmengine - INFO - Epoch(train) [75][1880/2119] lr: 4.0000e-02 eta: 15:18:02 time: 0.3225 data_time: 0.0265 memory: 5826 grad_norm: 3.0915 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9875 loss: 2.9875 2022/10/07 23:10:56 - mmengine - INFO - Epoch(train) [75][1900/2119] lr: 4.0000e-02 eta: 15:17:56 time: 0.3805 data_time: 0.0212 memory: 5826 grad_norm: 3.1465 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8132 loss: 2.8132 2022/10/07 23:11:04 - mmengine - INFO - Epoch(train) [75][1920/2119] lr: 4.0000e-02 eta: 15:17:50 time: 0.3750 data_time: 0.0221 memory: 5826 grad_norm: 3.1840 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7183 loss: 2.7183 2022/10/07 23:11:12 - mmengine - INFO - Epoch(train) [75][1940/2119] lr: 4.0000e-02 eta: 15:17:44 time: 0.3908 data_time: 0.0267 memory: 5826 grad_norm: 3.0785 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0790 loss: 3.0790 2022/10/07 23:11:18 - mmengine - INFO - Epoch(train) [75][1960/2119] lr: 4.0000e-02 eta: 15:17:36 time: 0.3283 data_time: 0.0234 memory: 5826 grad_norm: 3.1022 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8739 loss: 2.8739 2022/10/07 23:11:26 - mmengine - INFO - Epoch(train) [75][1980/2119] lr: 4.0000e-02 eta: 15:17:31 time: 0.3983 data_time: 0.0220 memory: 5826 grad_norm: 3.1219 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7658 loss: 2.7658 2022/10/07 23:11:32 - mmengine - INFO - Epoch(train) [75][2000/2119] lr: 4.0000e-02 eta: 15:17:23 time: 0.3064 data_time: 0.0224 memory: 5826 grad_norm: 3.1300 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6085 loss: 2.6085 2022/10/07 23:11:40 - mmengine - INFO - Epoch(train) [75][2020/2119] lr: 4.0000e-02 eta: 15:17:16 time: 0.3723 data_time: 0.0235 memory: 5826 grad_norm: 3.1453 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6833 loss: 2.6833 2022/10/07 23:11:47 - mmengine - INFO - Epoch(train) [75][2040/2119] lr: 4.0000e-02 eta: 15:17:10 time: 0.3450 data_time: 0.0237 memory: 5826 grad_norm: 3.1744 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8585 loss: 2.8585 2022/10/07 23:11:54 - mmengine - INFO - Epoch(train) [75][2060/2119] lr: 4.0000e-02 eta: 15:17:03 time: 0.3555 data_time: 0.0267 memory: 5826 grad_norm: 3.1113 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6554 loss: 2.6554 2022/10/07 23:12:01 - mmengine - INFO - Epoch(train) [75][2080/2119] lr: 4.0000e-02 eta: 15:16:56 time: 0.3584 data_time: 0.0219 memory: 5826 grad_norm: 3.1616 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6536 loss: 2.6536 2022/10/07 23:12:09 - mmengine - INFO - Epoch(train) [75][2100/2119] lr: 4.0000e-02 eta: 15:16:50 time: 0.3971 data_time: 0.0233 memory: 5826 grad_norm: 3.1001 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6899 loss: 2.6899 2022/10/07 23:12:15 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 23:12:15 - mmengine - INFO - Epoch(train) [75][2119/2119] lr: 4.0000e-02 eta: 15:16:50 time: 0.3029 data_time: 0.0206 memory: 5826 grad_norm: 3.1674 top1_acc: 0.5000 top5_acc: 0.6000 loss_cls: 2.7867 loss: 2.7867 2022/10/07 23:12:23 - mmengine - INFO - Epoch(val) [75][20/137] eta: 0:00:48 time: 0.4148 data_time: 0.3470 memory: 1241 2022/10/07 23:12:28 - mmengine - INFO - Epoch(val) [75][40/137] eta: 0:00:25 time: 0.2671 data_time: 0.2029 memory: 1241 2022/10/07 23:12:35 - mmengine - INFO - Epoch(val) [75][60/137] eta: 0:00:26 time: 0.3448 data_time: 0.2790 memory: 1241 2022/10/07 23:12:42 - mmengine - INFO - Epoch(val) [75][80/137] eta: 0:00:19 time: 0.3471 data_time: 0.2823 memory: 1241 2022/10/07 23:12:49 - mmengine - INFO - Epoch(val) [75][100/137] eta: 0:00:12 time: 0.3243 data_time: 0.2612 memory: 1241 2022/10/07 23:12:54 - mmengine - INFO - Epoch(val) [75][120/137] eta: 0:00:04 time: 0.2575 data_time: 0.1675 memory: 1241 2022/10/07 23:13:06 - mmengine - INFO - Epoch(val) [75][137/137] acc/top1: 0.4323 acc/top5: 0.6761 acc/mean1: 0.4323 2022/10/07 23:13:15 - mmengine - INFO - Epoch(train) [76][20/2119] lr: 4.0000e-02 eta: 15:16:32 time: 0.4625 data_time: 0.2044 memory: 5826 grad_norm: 3.1516 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7410 loss: 2.7410 2022/10/07 23:13:22 - mmengine - INFO - Epoch(train) [76][40/2119] lr: 4.0000e-02 eta: 15:16:26 time: 0.3571 data_time: 0.0815 memory: 5826 grad_norm: 3.1043 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7189 loss: 2.7189 2022/10/07 23:13:29 - mmengine - INFO - Epoch(train) [76][60/2119] lr: 4.0000e-02 eta: 15:16:19 time: 0.3625 data_time: 0.0318 memory: 5826 grad_norm: 3.0616 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8472 loss: 2.8472 2022/10/07 23:13:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 23:13:36 - mmengine - INFO - Epoch(train) [76][80/2119] lr: 4.0000e-02 eta: 15:16:12 time: 0.3367 data_time: 0.0146 memory: 5826 grad_norm: 3.1008 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7272 loss: 2.7272 2022/10/07 23:13:44 - mmengine - INFO - Epoch(train) [76][100/2119] lr: 4.0000e-02 eta: 15:16:06 time: 0.3767 data_time: 0.0197 memory: 5826 grad_norm: 3.1019 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7923 loss: 2.7923 2022/10/07 23:13:50 - mmengine - INFO - Epoch(train) [76][120/2119] lr: 4.0000e-02 eta: 15:15:59 time: 0.3426 data_time: 0.0230 memory: 5826 grad_norm: 3.1723 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8438 loss: 2.8438 2022/10/07 23:13:57 - mmengine - INFO - Epoch(train) [76][140/2119] lr: 4.0000e-02 eta: 15:15:52 time: 0.3439 data_time: 0.0236 memory: 5826 grad_norm: 3.0806 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7881 loss: 2.7881 2022/10/07 23:14:05 - mmengine - INFO - Epoch(train) [76][160/2119] lr: 4.0000e-02 eta: 15:15:46 time: 0.3781 data_time: 0.0203 memory: 5826 grad_norm: 3.1587 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8201 loss: 2.8201 2022/10/07 23:14:12 - mmengine - INFO - Epoch(train) [76][180/2119] lr: 4.0000e-02 eta: 15:15:39 time: 0.3593 data_time: 0.0249 memory: 5826 grad_norm: 3.1492 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4263 loss: 2.4263 2022/10/07 23:14:18 - mmengine - INFO - Epoch(train) [76][200/2119] lr: 4.0000e-02 eta: 15:15:31 time: 0.3031 data_time: 0.0243 memory: 5826 grad_norm: 3.0751 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7868 loss: 2.7868 2022/10/07 23:14:26 - mmengine - INFO - Epoch(train) [76][220/2119] lr: 4.0000e-02 eta: 15:15:25 time: 0.3782 data_time: 0.0259 memory: 5826 grad_norm: 3.1700 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6100 loss: 2.6100 2022/10/07 23:14:33 - mmengine - INFO - Epoch(train) [76][240/2119] lr: 4.0000e-02 eta: 15:15:18 time: 0.3565 data_time: 0.0253 memory: 5826 grad_norm: 3.1629 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5550 loss: 2.5550 2022/10/07 23:14:41 - mmengine - INFO - Epoch(train) [76][260/2119] lr: 4.0000e-02 eta: 15:15:12 time: 0.3965 data_time: 0.0236 memory: 5826 grad_norm: 3.0966 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.3974 loss: 2.3974 2022/10/07 23:14:48 - mmengine - INFO - Epoch(train) [76][280/2119] lr: 4.0000e-02 eta: 15:15:05 time: 0.3424 data_time: 0.0232 memory: 5826 grad_norm: 3.1029 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7408 loss: 2.7408 2022/10/07 23:14:55 - mmengine - INFO - Epoch(train) [76][300/2119] lr: 4.0000e-02 eta: 15:14:59 time: 0.3913 data_time: 0.0222 memory: 5826 grad_norm: 3.1897 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5622 loss: 2.5622 2022/10/07 23:15:02 - mmengine - INFO - Epoch(train) [76][320/2119] lr: 4.0000e-02 eta: 15:14:52 time: 0.3319 data_time: 0.0231 memory: 5826 grad_norm: 3.1924 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5471 loss: 2.5471 2022/10/07 23:15:10 - mmengine - INFO - Epoch(train) [76][340/2119] lr: 4.0000e-02 eta: 15:14:46 time: 0.3831 data_time: 0.0236 memory: 5826 grad_norm: 3.1882 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6404 loss: 2.6404 2022/10/07 23:15:16 - mmengine - INFO - Epoch(train) [76][360/2119] lr: 4.0000e-02 eta: 15:14:39 time: 0.3318 data_time: 0.0221 memory: 5826 grad_norm: 3.1227 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5981 loss: 2.5981 2022/10/07 23:15:24 - mmengine - INFO - Epoch(train) [76][380/2119] lr: 4.0000e-02 eta: 15:14:32 time: 0.3685 data_time: 0.0323 memory: 5826 grad_norm: 3.1788 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.7354 loss: 2.7354 2022/10/07 23:15:30 - mmengine - INFO - Epoch(train) [76][400/2119] lr: 4.0000e-02 eta: 15:14:24 time: 0.3015 data_time: 0.0211 memory: 5826 grad_norm: 3.1251 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5848 loss: 2.5848 2022/10/07 23:15:37 - mmengine - INFO - Epoch(train) [76][420/2119] lr: 4.0000e-02 eta: 15:14:18 time: 0.3674 data_time: 0.0221 memory: 5826 grad_norm: 3.1208 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7150 loss: 2.7150 2022/10/07 23:15:44 - mmengine - INFO - Epoch(train) [76][440/2119] lr: 4.0000e-02 eta: 15:14:11 time: 0.3535 data_time: 0.0192 memory: 5826 grad_norm: 3.0388 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.9192 loss: 2.9192 2022/10/07 23:15:51 - mmengine - INFO - Epoch(train) [76][460/2119] lr: 4.0000e-02 eta: 15:14:04 time: 0.3428 data_time: 0.0212 memory: 5826 grad_norm: 3.1598 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6993 loss: 2.6993 2022/10/07 23:15:58 - mmengine - INFO - Epoch(train) [76][480/2119] lr: 4.0000e-02 eta: 15:13:57 time: 0.3381 data_time: 0.0224 memory: 5826 grad_norm: 3.1497 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9483 loss: 2.9483 2022/10/07 23:16:05 - mmengine - INFO - Epoch(train) [76][500/2119] lr: 4.0000e-02 eta: 15:13:50 time: 0.3578 data_time: 0.0248 memory: 5826 grad_norm: 3.1153 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6184 loss: 2.6184 2022/10/07 23:16:12 - mmengine - INFO - Epoch(train) [76][520/2119] lr: 4.0000e-02 eta: 15:13:43 time: 0.3544 data_time: 0.0197 memory: 5826 grad_norm: 3.0869 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7397 loss: 2.7397 2022/10/07 23:16:20 - mmengine - INFO - Epoch(train) [76][540/2119] lr: 4.0000e-02 eta: 15:13:38 time: 0.4018 data_time: 0.0204 memory: 5826 grad_norm: 3.0818 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7660 loss: 2.7660 2022/10/07 23:16:27 - mmengine - INFO - Epoch(train) [76][560/2119] lr: 4.0000e-02 eta: 15:13:30 time: 0.3193 data_time: 0.0235 memory: 5826 grad_norm: 3.1249 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7954 loss: 2.7954 2022/10/07 23:16:33 - mmengine - INFO - Epoch(train) [76][580/2119] lr: 4.0000e-02 eta: 15:13:23 time: 0.3411 data_time: 0.0249 memory: 5826 grad_norm: 3.1378 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8430 loss: 2.8430 2022/10/07 23:16:41 - mmengine - INFO - Epoch(train) [76][600/2119] lr: 4.0000e-02 eta: 15:13:17 time: 0.3647 data_time: 0.0237 memory: 5826 grad_norm: 3.1398 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.6357 loss: 2.6357 2022/10/07 23:16:47 - mmengine - INFO - Epoch(train) [76][620/2119] lr: 4.0000e-02 eta: 15:13:09 time: 0.3161 data_time: 0.0234 memory: 5826 grad_norm: 3.1380 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7249 loss: 2.7249 2022/10/07 23:16:54 - mmengine - INFO - Epoch(train) [76][640/2119] lr: 4.0000e-02 eta: 15:13:02 time: 0.3456 data_time: 0.0236 memory: 5826 grad_norm: 3.0896 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7514 loss: 2.7514 2022/10/07 23:17:01 - mmengine - INFO - Epoch(train) [76][660/2119] lr: 4.0000e-02 eta: 15:12:55 time: 0.3527 data_time: 0.0246 memory: 5826 grad_norm: 3.1505 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8010 loss: 2.8010 2022/10/07 23:17:08 - mmengine - INFO - Epoch(train) [76][680/2119] lr: 4.0000e-02 eta: 15:12:49 time: 0.3505 data_time: 0.0238 memory: 5826 grad_norm: 3.0683 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9254 loss: 2.9254 2022/10/07 23:17:16 - mmengine - INFO - Epoch(train) [76][700/2119] lr: 4.0000e-02 eta: 15:12:42 time: 0.3771 data_time: 0.0227 memory: 5826 grad_norm: 3.1146 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.6647 loss: 2.6647 2022/10/07 23:17:23 - mmengine - INFO - Epoch(train) [76][720/2119] lr: 4.0000e-02 eta: 15:12:36 time: 0.3870 data_time: 0.0211 memory: 5826 grad_norm: 3.0936 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6976 loss: 2.6976 2022/10/07 23:17:30 - mmengine - INFO - Epoch(train) [76][740/2119] lr: 4.0000e-02 eta: 15:12:29 time: 0.3384 data_time: 0.0243 memory: 5826 grad_norm: 3.0776 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7330 loss: 2.7330 2022/10/07 23:17:37 - mmengine - INFO - Epoch(train) [76][760/2119] lr: 4.0000e-02 eta: 15:12:22 time: 0.3231 data_time: 0.0228 memory: 5826 grad_norm: 3.1167 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7800 loss: 2.7800 2022/10/07 23:17:43 - mmengine - INFO - Epoch(train) [76][780/2119] lr: 4.0000e-02 eta: 15:12:15 time: 0.3401 data_time: 0.0190 memory: 5826 grad_norm: 3.0788 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6402 loss: 2.6402 2022/10/07 23:17:51 - mmengine - INFO - Epoch(train) [76][800/2119] lr: 4.0000e-02 eta: 15:12:08 time: 0.3600 data_time: 0.0232 memory: 5826 grad_norm: 3.0983 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6096 loss: 2.6096 2022/10/07 23:17:57 - mmengine - INFO - Epoch(train) [76][820/2119] lr: 4.0000e-02 eta: 15:12:01 time: 0.3370 data_time: 0.0233 memory: 5826 grad_norm: 3.0577 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7687 loss: 2.7687 2022/10/07 23:18:04 - mmengine - INFO - Epoch(train) [76][840/2119] lr: 4.0000e-02 eta: 15:11:54 time: 0.3286 data_time: 0.0220 memory: 5826 grad_norm: 3.1725 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.9551 loss: 2.9551 2022/10/07 23:18:11 - mmengine - INFO - Epoch(train) [76][860/2119] lr: 4.0000e-02 eta: 15:11:47 time: 0.3668 data_time: 0.0224 memory: 5826 grad_norm: 3.1416 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5945 loss: 2.5945 2022/10/07 23:18:18 - mmengine - INFO - Epoch(train) [76][880/2119] lr: 4.0000e-02 eta: 15:11:40 time: 0.3518 data_time: 0.0238 memory: 5826 grad_norm: 3.1753 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6817 loss: 2.6817 2022/10/07 23:18:26 - mmengine - INFO - Epoch(train) [76][900/2119] lr: 4.0000e-02 eta: 15:11:34 time: 0.3825 data_time: 0.0180 memory: 5826 grad_norm: 3.1237 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5200 loss: 2.5200 2022/10/07 23:18:32 - mmengine - INFO - Epoch(train) [76][920/2119] lr: 4.0000e-02 eta: 15:11:26 time: 0.3116 data_time: 0.0241 memory: 5826 grad_norm: 3.1169 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6689 loss: 2.6689 2022/10/07 23:18:40 - mmengine - INFO - Epoch(train) [76][940/2119] lr: 4.0000e-02 eta: 15:11:20 time: 0.3752 data_time: 0.0199 memory: 5826 grad_norm: 3.1394 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6838 loss: 2.6838 2022/10/07 23:18:46 - mmengine - INFO - Epoch(train) [76][960/2119] lr: 4.0000e-02 eta: 15:11:12 time: 0.3076 data_time: 0.0201 memory: 5826 grad_norm: 3.1356 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9076 loss: 2.9076 2022/10/07 23:18:54 - mmengine - INFO - Epoch(train) [76][980/2119] lr: 4.0000e-02 eta: 15:11:07 time: 0.3980 data_time: 0.0283 memory: 5826 grad_norm: 3.2287 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6917 loss: 2.6917 2022/10/07 23:19:01 - mmengine - INFO - Epoch(train) [76][1000/2119] lr: 4.0000e-02 eta: 15:11:00 time: 0.3449 data_time: 0.0189 memory: 5826 grad_norm: 3.1371 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6355 loss: 2.6355 2022/10/07 23:19:08 - mmengine - INFO - Epoch(train) [76][1020/2119] lr: 4.0000e-02 eta: 15:10:53 time: 0.3506 data_time: 0.0217 memory: 5826 grad_norm: 3.1530 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6206 loss: 2.6206 2022/10/07 23:19:14 - mmengine - INFO - Epoch(train) [76][1040/2119] lr: 4.0000e-02 eta: 15:10:46 time: 0.3345 data_time: 0.0224 memory: 5826 grad_norm: 3.1169 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9222 loss: 2.9222 2022/10/07 23:19:22 - mmengine - INFO - Epoch(train) [76][1060/2119] lr: 4.0000e-02 eta: 15:10:40 time: 0.3916 data_time: 0.0203 memory: 5826 grad_norm: 3.0884 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6823 loss: 2.6823 2022/10/07 23:19:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 23:19:29 - mmengine - INFO - Epoch(train) [76][1080/2119] lr: 4.0000e-02 eta: 15:10:32 time: 0.3276 data_time: 0.0211 memory: 5826 grad_norm: 3.2031 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7619 loss: 2.7619 2022/10/07 23:19:36 - mmengine - INFO - Epoch(train) [76][1100/2119] lr: 4.0000e-02 eta: 15:10:25 time: 0.3439 data_time: 0.0208 memory: 5826 grad_norm: 3.1681 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6393 loss: 2.6393 2022/10/07 23:19:42 - mmengine - INFO - Epoch(train) [76][1120/2119] lr: 4.0000e-02 eta: 15:10:18 time: 0.3050 data_time: 0.0221 memory: 5826 grad_norm: 3.0850 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.8838 loss: 2.8838 2022/10/07 23:19:50 - mmengine - INFO - Epoch(train) [76][1140/2119] lr: 4.0000e-02 eta: 15:10:12 time: 0.3946 data_time: 0.0245 memory: 5826 grad_norm: 3.2024 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6571 loss: 2.6571 2022/10/07 23:19:56 - mmengine - INFO - Epoch(train) [76][1160/2119] lr: 4.0000e-02 eta: 15:10:04 time: 0.3335 data_time: 0.0229 memory: 5826 grad_norm: 3.1452 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6251 loss: 2.6251 2022/10/07 23:20:04 - mmengine - INFO - Epoch(train) [76][1180/2119] lr: 4.0000e-02 eta: 15:09:58 time: 0.3889 data_time: 0.0268 memory: 5826 grad_norm: 3.1140 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6001 loss: 2.6001 2022/10/07 23:20:11 - mmengine - INFO - Epoch(train) [76][1200/2119] lr: 4.0000e-02 eta: 15:09:51 time: 0.3220 data_time: 0.0192 memory: 5826 grad_norm: 3.1404 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6883 loss: 2.6883 2022/10/07 23:20:18 - mmengine - INFO - Epoch(train) [76][1220/2119] lr: 4.0000e-02 eta: 15:09:45 time: 0.3945 data_time: 0.0199 memory: 5826 grad_norm: 3.0848 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9208 loss: 2.9208 2022/10/07 23:20:25 - mmengine - INFO - Epoch(train) [76][1240/2119] lr: 4.0000e-02 eta: 15:09:38 time: 0.3431 data_time: 0.0227 memory: 5826 grad_norm: 3.1253 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4554 loss: 2.4554 2022/10/07 23:20:32 - mmengine - INFO - Epoch(train) [76][1260/2119] lr: 4.0000e-02 eta: 15:09:31 time: 0.3551 data_time: 0.0197 memory: 5826 grad_norm: 3.0931 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5545 loss: 2.5545 2022/10/07 23:20:38 - mmengine - INFO - Epoch(train) [76][1280/2119] lr: 4.0000e-02 eta: 15:09:23 time: 0.3004 data_time: 0.0240 memory: 5826 grad_norm: 3.1384 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8010 loss: 2.8010 2022/10/07 23:20:46 - mmengine - INFO - Epoch(train) [76][1300/2119] lr: 4.0000e-02 eta: 15:09:17 time: 0.3830 data_time: 0.0220 memory: 5826 grad_norm: 3.1133 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8055 loss: 2.8055 2022/10/07 23:20:53 - mmengine - INFO - Epoch(train) [76][1320/2119] lr: 4.0000e-02 eta: 15:09:10 time: 0.3412 data_time: 0.0224 memory: 5826 grad_norm: 3.1557 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6302 loss: 2.6302 2022/10/07 23:21:01 - mmengine - INFO - Epoch(train) [76][1340/2119] lr: 4.0000e-02 eta: 15:09:04 time: 0.3806 data_time: 0.0269 memory: 5826 grad_norm: 3.1217 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5888 loss: 2.5888 2022/10/07 23:21:07 - mmengine - INFO - Epoch(train) [76][1360/2119] lr: 4.0000e-02 eta: 15:08:56 time: 0.3089 data_time: 0.0246 memory: 5826 grad_norm: 3.1239 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.5714 loss: 2.5714 2022/10/07 23:21:15 - mmengine - INFO - Epoch(train) [76][1380/2119] lr: 4.0000e-02 eta: 15:08:50 time: 0.3951 data_time: 0.0342 memory: 5826 grad_norm: 3.1050 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5439 loss: 2.5439 2022/10/07 23:21:21 - mmengine - INFO - Epoch(train) [76][1400/2119] lr: 4.0000e-02 eta: 15:08:43 time: 0.3369 data_time: 0.0197 memory: 5826 grad_norm: 3.0517 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9515 loss: 2.9515 2022/10/07 23:21:29 - mmengine - INFO - Epoch(train) [76][1420/2119] lr: 4.0000e-02 eta: 15:08:37 time: 0.3559 data_time: 0.0231 memory: 5826 grad_norm: 3.1011 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6024 loss: 2.6024 2022/10/07 23:21:35 - mmengine - INFO - Epoch(train) [76][1440/2119] lr: 4.0000e-02 eta: 15:08:29 time: 0.3299 data_time: 0.0231 memory: 5826 grad_norm: 3.0945 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8061 loss: 2.8061 2022/10/07 23:21:42 - mmengine - INFO - Epoch(train) [76][1460/2119] lr: 4.0000e-02 eta: 15:08:22 time: 0.3243 data_time: 0.0241 memory: 5826 grad_norm: 3.0777 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7078 loss: 2.7078 2022/10/07 23:21:49 - mmengine - INFO - Epoch(train) [76][1480/2119] lr: 4.0000e-02 eta: 15:08:15 time: 0.3515 data_time: 0.0197 memory: 5826 grad_norm: 3.0856 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.5983 loss: 2.5983 2022/10/07 23:21:55 - mmengine - INFO - Epoch(train) [76][1500/2119] lr: 4.0000e-02 eta: 15:08:08 time: 0.3125 data_time: 0.0255 memory: 5826 grad_norm: 3.1538 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6077 loss: 2.6077 2022/10/07 23:22:02 - mmengine - INFO - Epoch(train) [76][1520/2119] lr: 4.0000e-02 eta: 15:08:01 time: 0.3622 data_time: 0.0244 memory: 5826 grad_norm: 3.1014 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8080 loss: 2.8080 2022/10/07 23:22:09 - mmengine - INFO - Epoch(train) [76][1540/2119] lr: 4.0000e-02 eta: 15:07:54 time: 0.3510 data_time: 0.0201 memory: 5826 grad_norm: 3.1458 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7016 loss: 2.7016 2022/10/07 23:22:16 - mmengine - INFO - Epoch(train) [76][1560/2119] lr: 4.0000e-02 eta: 15:07:48 time: 0.3627 data_time: 0.0234 memory: 5826 grad_norm: 3.1236 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7075 loss: 2.7075 2022/10/07 23:22:24 - mmengine - INFO - Epoch(train) [76][1580/2119] lr: 4.0000e-02 eta: 15:07:41 time: 0.3797 data_time: 0.0246 memory: 5826 grad_norm: 3.0872 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7184 loss: 2.7184 2022/10/07 23:22:31 - mmengine - INFO - Epoch(train) [76][1600/2119] lr: 4.0000e-02 eta: 15:07:34 time: 0.3462 data_time: 0.0261 memory: 5826 grad_norm: 3.1362 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8729 loss: 2.8729 2022/10/07 23:22:38 - mmengine - INFO - Epoch(train) [76][1620/2119] lr: 4.0000e-02 eta: 15:07:27 time: 0.3313 data_time: 0.0247 memory: 5826 grad_norm: 3.1302 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5730 loss: 2.5730 2022/10/07 23:22:45 - mmengine - INFO - Epoch(train) [76][1640/2119] lr: 4.0000e-02 eta: 15:07:21 time: 0.3931 data_time: 0.0187 memory: 5826 grad_norm: 3.1535 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9187 loss: 2.9187 2022/10/07 23:22:51 - mmengine - INFO - Epoch(train) [76][1660/2119] lr: 4.0000e-02 eta: 15:07:13 time: 0.3001 data_time: 0.0248 memory: 5826 grad_norm: 3.0550 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.5406 loss: 2.5406 2022/10/07 23:22:58 - mmengine - INFO - Epoch(train) [76][1680/2119] lr: 4.0000e-02 eta: 15:07:06 time: 0.3205 data_time: 0.0208 memory: 5826 grad_norm: 3.0675 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7280 loss: 2.7280 2022/10/07 23:23:05 - mmengine - INFO - Epoch(train) [76][1700/2119] lr: 4.0000e-02 eta: 15:06:59 time: 0.3637 data_time: 0.0236 memory: 5826 grad_norm: 3.1200 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.3462 loss: 2.3462 2022/10/07 23:23:13 - mmengine - INFO - Epoch(train) [76][1720/2119] lr: 4.0000e-02 eta: 15:06:53 time: 0.3776 data_time: 0.0225 memory: 5826 grad_norm: 3.1423 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9598 loss: 2.9598 2022/10/07 23:23:19 - mmengine - INFO - Epoch(train) [76][1740/2119] lr: 4.0000e-02 eta: 15:06:45 time: 0.3026 data_time: 0.0269 memory: 5826 grad_norm: 3.1240 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6310 loss: 2.6310 2022/10/07 23:23:27 - mmengine - INFO - Epoch(train) [76][1760/2119] lr: 4.0000e-02 eta: 15:06:40 time: 0.4077 data_time: 0.0209 memory: 5826 grad_norm: 3.0978 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5845 loss: 2.5845 2022/10/07 23:23:33 - mmengine - INFO - Epoch(train) [76][1780/2119] lr: 4.0000e-02 eta: 15:06:32 time: 0.3087 data_time: 0.0205 memory: 5826 grad_norm: 3.2015 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7002 loss: 2.7002 2022/10/07 23:23:40 - mmengine - INFO - Epoch(train) [76][1800/2119] lr: 4.0000e-02 eta: 15:06:25 time: 0.3524 data_time: 0.0227 memory: 5826 grad_norm: 3.1603 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7660 loss: 2.7660 2022/10/07 23:23:48 - mmengine - INFO - Epoch(train) [76][1820/2119] lr: 4.0000e-02 eta: 15:06:19 time: 0.3718 data_time: 0.0239 memory: 5826 grad_norm: 3.1177 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7206 loss: 2.7206 2022/10/07 23:23:55 - mmengine - INFO - Epoch(train) [76][1840/2119] lr: 4.0000e-02 eta: 15:06:12 time: 0.3448 data_time: 0.0195 memory: 5826 grad_norm: 3.0931 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5152 loss: 2.5152 2022/10/07 23:24:02 - mmengine - INFO - Epoch(train) [76][1860/2119] lr: 4.0000e-02 eta: 15:06:05 time: 0.3500 data_time: 0.0279 memory: 5826 grad_norm: 3.1085 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6584 loss: 2.6584 2022/10/07 23:24:09 - mmengine - INFO - Epoch(train) [76][1880/2119] lr: 4.0000e-02 eta: 15:05:59 time: 0.3890 data_time: 0.0249 memory: 5826 grad_norm: 3.0542 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8914 loss: 2.8914 2022/10/07 23:24:16 - mmengine - INFO - Epoch(train) [76][1900/2119] lr: 4.0000e-02 eta: 15:05:52 time: 0.3317 data_time: 0.0212 memory: 5826 grad_norm: 3.1140 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7008 loss: 2.7008 2022/10/07 23:24:23 - mmengine - INFO - Epoch(train) [76][1920/2119] lr: 4.0000e-02 eta: 15:05:45 time: 0.3590 data_time: 0.0273 memory: 5826 grad_norm: 3.1307 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7855 loss: 2.7855 2022/10/07 23:24:30 - mmengine - INFO - Epoch(train) [76][1940/2119] lr: 4.0000e-02 eta: 15:05:37 time: 0.3194 data_time: 0.0207 memory: 5826 grad_norm: 3.0948 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8590 loss: 2.8590 2022/10/07 23:24:36 - mmengine - INFO - Epoch(train) [76][1960/2119] lr: 4.0000e-02 eta: 15:05:30 time: 0.3186 data_time: 0.0244 memory: 5826 grad_norm: 3.1085 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5756 loss: 2.5756 2022/10/07 23:24:43 - mmengine - INFO - Epoch(train) [76][1980/2119] lr: 4.0000e-02 eta: 15:05:23 time: 0.3464 data_time: 0.0229 memory: 5826 grad_norm: 3.0939 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7374 loss: 2.7374 2022/10/07 23:24:50 - mmengine - INFO - Epoch(train) [76][2000/2119] lr: 4.0000e-02 eta: 15:05:17 time: 0.3792 data_time: 0.0207 memory: 5826 grad_norm: 3.0965 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6810 loss: 2.6810 2022/10/07 23:24:57 - mmengine - INFO - Epoch(train) [76][2020/2119] lr: 4.0000e-02 eta: 15:05:09 time: 0.3212 data_time: 0.0217 memory: 5826 grad_norm: 3.1120 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6186 loss: 2.6186 2022/10/07 23:25:05 - mmengine - INFO - Epoch(train) [76][2040/2119] lr: 4.0000e-02 eta: 15:05:03 time: 0.3921 data_time: 0.0233 memory: 5826 grad_norm: 3.0885 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5060 loss: 2.5060 2022/10/07 23:25:12 - mmengine - INFO - Epoch(train) [76][2060/2119] lr: 4.0000e-02 eta: 15:04:56 time: 0.3492 data_time: 0.0226 memory: 5826 grad_norm: 3.1545 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8340 loss: 2.8340 2022/10/07 23:25:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 23:25:19 - mmengine - INFO - Epoch(train) [76][2080/2119] lr: 4.0000e-02 eta: 15:04:50 time: 0.3432 data_time: 0.0250 memory: 5826 grad_norm: 3.1484 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7382 loss: 2.7382 2022/10/07 23:25:26 - mmengine - INFO - Epoch(train) [76][2100/2119] lr: 4.0000e-02 eta: 15:04:43 time: 0.3664 data_time: 0.0245 memory: 5826 grad_norm: 3.1135 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6270 loss: 2.6270 2022/10/07 23:25:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 23:25:32 - mmengine - INFO - Epoch(train) [76][2119/2119] lr: 4.0000e-02 eta: 15:04:43 time: 0.3443 data_time: 0.0170 memory: 5826 grad_norm: 3.1879 top1_acc: 0.4000 top5_acc: 0.7000 loss_cls: 2.5704 loss: 2.5704 2022/10/07 23:25:32 - mmengine - INFO - Saving checkpoint at 76 epochs 2022/10/07 23:25:43 - mmengine - INFO - Epoch(train) [77][20/2119] lr: 4.0000e-02 eta: 15:04:25 time: 0.4347 data_time: 0.2147 memory: 5826 grad_norm: 3.0884 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 2.6230 loss: 2.6230 2022/10/07 23:25:48 - mmengine - INFO - Epoch(train) [77][40/2119] lr: 4.0000e-02 eta: 15:04:16 time: 0.2549 data_time: 0.0331 memory: 5826 grad_norm: 3.1635 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6728 loss: 2.6728 2022/10/07 23:25:55 - mmengine - INFO - Epoch(train) [77][60/2119] lr: 4.0000e-02 eta: 15:04:10 time: 0.3637 data_time: 0.0609 memory: 5826 grad_norm: 3.0562 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7011 loss: 2.7011 2022/10/07 23:26:02 - mmengine - INFO - Epoch(train) [77][80/2119] lr: 4.0000e-02 eta: 15:04:03 time: 0.3461 data_time: 0.0201 memory: 5826 grad_norm: 3.1469 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4842 loss: 2.4842 2022/10/07 23:26:09 - mmengine - INFO - Epoch(train) [77][100/2119] lr: 4.0000e-02 eta: 15:03:56 time: 0.3622 data_time: 0.0255 memory: 5826 grad_norm: 3.1245 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8878 loss: 2.8878 2022/10/07 23:26:16 - mmengine - INFO - Epoch(train) [77][120/2119] lr: 4.0000e-02 eta: 15:03:49 time: 0.3488 data_time: 0.0265 memory: 5826 grad_norm: 3.0959 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5089 loss: 2.5089 2022/10/07 23:26:23 - mmengine - INFO - Epoch(train) [77][140/2119] lr: 4.0000e-02 eta: 15:03:42 time: 0.3548 data_time: 0.0221 memory: 5826 grad_norm: 3.1326 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8562 loss: 2.8562 2022/10/07 23:26:31 - mmengine - INFO - Epoch(train) [77][160/2119] lr: 4.0000e-02 eta: 15:03:36 time: 0.3721 data_time: 0.0226 memory: 5826 grad_norm: 3.0885 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.4717 loss: 2.4717 2022/10/07 23:26:38 - mmengine - INFO - Epoch(train) [77][180/2119] lr: 4.0000e-02 eta: 15:03:29 time: 0.3702 data_time: 0.0221 memory: 5826 grad_norm: 3.1580 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6567 loss: 2.6567 2022/10/07 23:26:46 - mmengine - INFO - Epoch(train) [77][200/2119] lr: 4.0000e-02 eta: 15:03:23 time: 0.3667 data_time: 0.0190 memory: 5826 grad_norm: 3.1010 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4841 loss: 2.4841 2022/10/07 23:26:52 - mmengine - INFO - Epoch(train) [77][220/2119] lr: 4.0000e-02 eta: 15:03:16 time: 0.3422 data_time: 0.0237 memory: 5826 grad_norm: 3.1481 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4758 loss: 2.4758 2022/10/07 23:27:00 - mmengine - INFO - Epoch(train) [77][240/2119] lr: 4.0000e-02 eta: 15:03:09 time: 0.3614 data_time: 0.0240 memory: 5826 grad_norm: 3.0638 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6529 loss: 2.6529 2022/10/07 23:27:07 - mmengine - INFO - Epoch(train) [77][260/2119] lr: 4.0000e-02 eta: 15:03:02 time: 0.3456 data_time: 0.0243 memory: 5826 grad_norm: 3.0905 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7624 loss: 2.7624 2022/10/07 23:27:15 - mmengine - INFO - Epoch(train) [77][280/2119] lr: 4.0000e-02 eta: 15:02:56 time: 0.3961 data_time: 0.0202 memory: 5826 grad_norm: 3.1226 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7651 loss: 2.7651 2022/10/07 23:27:21 - mmengine - INFO - Epoch(train) [77][300/2119] lr: 4.0000e-02 eta: 15:02:49 time: 0.3221 data_time: 0.0280 memory: 5826 grad_norm: 3.1491 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5460 loss: 2.5460 2022/10/07 23:27:28 - mmengine - INFO - Epoch(train) [77][320/2119] lr: 4.0000e-02 eta: 15:02:42 time: 0.3629 data_time: 0.0203 memory: 5826 grad_norm: 3.0707 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9775 loss: 2.9775 2022/10/07 23:27:36 - mmengine - INFO - Epoch(train) [77][340/2119] lr: 4.0000e-02 eta: 15:02:36 time: 0.3659 data_time: 0.0202 memory: 5826 grad_norm: 3.1149 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5299 loss: 2.5299 2022/10/07 23:27:43 - mmengine - INFO - Epoch(train) [77][360/2119] lr: 4.0000e-02 eta: 15:02:30 time: 0.3878 data_time: 0.0236 memory: 5826 grad_norm: 3.1126 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6170 loss: 2.6170 2022/10/07 23:27:50 - mmengine - INFO - Epoch(train) [77][380/2119] lr: 4.0000e-02 eta: 15:02:23 time: 0.3295 data_time: 0.0198 memory: 5826 grad_norm: 3.1204 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7043 loss: 2.7043 2022/10/07 23:27:58 - mmengine - INFO - Epoch(train) [77][400/2119] lr: 4.0000e-02 eta: 15:02:17 time: 0.3898 data_time: 0.0222 memory: 5826 grad_norm: 3.0655 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5316 loss: 2.5316 2022/10/07 23:28:05 - mmengine - INFO - Epoch(train) [77][420/2119] lr: 4.0000e-02 eta: 15:02:10 time: 0.3571 data_time: 0.0210 memory: 5826 grad_norm: 3.1302 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8324 loss: 2.8324 2022/10/07 23:28:13 - mmengine - INFO - Epoch(train) [77][440/2119] lr: 4.0000e-02 eta: 15:02:04 time: 0.4048 data_time: 0.0231 memory: 5826 grad_norm: 3.1608 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8597 loss: 2.8597 2022/10/07 23:28:19 - mmengine - INFO - Epoch(train) [77][460/2119] lr: 4.0000e-02 eta: 15:01:56 time: 0.3148 data_time: 0.0285 memory: 5826 grad_norm: 3.1339 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7684 loss: 2.7684 2022/10/07 23:28:28 - mmengine - INFO - Epoch(train) [77][480/2119] lr: 4.0000e-02 eta: 15:01:51 time: 0.4112 data_time: 0.0210 memory: 5826 grad_norm: 3.1473 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7273 loss: 2.7273 2022/10/07 23:28:34 - mmengine - INFO - Epoch(train) [77][500/2119] lr: 4.0000e-02 eta: 15:01:43 time: 0.3187 data_time: 0.0220 memory: 5826 grad_norm: 3.1666 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0089 loss: 3.0089 2022/10/07 23:28:41 - mmengine - INFO - Epoch(train) [77][520/2119] lr: 4.0000e-02 eta: 15:01:37 time: 0.3581 data_time: 0.0263 memory: 5826 grad_norm: 3.1708 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7881 loss: 2.7881 2022/10/07 23:28:48 - mmengine - INFO - Epoch(train) [77][540/2119] lr: 4.0000e-02 eta: 15:01:30 time: 0.3363 data_time: 0.0243 memory: 5826 grad_norm: 3.1502 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8021 loss: 2.8021 2022/10/07 23:28:55 - mmengine - INFO - Epoch(train) [77][560/2119] lr: 4.0000e-02 eta: 15:01:23 time: 0.3531 data_time: 0.0211 memory: 5826 grad_norm: 3.1316 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6261 loss: 2.6261 2022/10/07 23:29:02 - mmengine - INFO - Epoch(train) [77][580/2119] lr: 4.0000e-02 eta: 15:01:16 time: 0.3646 data_time: 0.0278 memory: 5826 grad_norm: 3.1248 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6477 loss: 2.6477 2022/10/07 23:29:09 - mmengine - INFO - Epoch(train) [77][600/2119] lr: 4.0000e-02 eta: 15:01:09 time: 0.3209 data_time: 0.0249 memory: 5826 grad_norm: 3.1472 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5493 loss: 2.5493 2022/10/07 23:29:16 - mmengine - INFO - Epoch(train) [77][620/2119] lr: 4.0000e-02 eta: 15:01:03 time: 0.3795 data_time: 0.0265 memory: 5826 grad_norm: 3.1308 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5770 loss: 2.5770 2022/10/07 23:29:24 - mmengine - INFO - Epoch(train) [77][640/2119] lr: 4.0000e-02 eta: 15:00:56 time: 0.3699 data_time: 0.0260 memory: 5826 grad_norm: 3.0865 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9930 loss: 2.9930 2022/10/07 23:29:29 - mmengine - INFO - Epoch(train) [77][660/2119] lr: 4.0000e-02 eta: 15:00:48 time: 0.2728 data_time: 0.0221 memory: 5826 grad_norm: 3.1010 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7305 loss: 2.7305 2022/10/07 23:29:36 - mmengine - INFO - Epoch(train) [77][680/2119] lr: 4.0000e-02 eta: 15:00:41 time: 0.3416 data_time: 0.0257 memory: 5826 grad_norm: 3.0771 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5719 loss: 2.5719 2022/10/07 23:29:43 - mmengine - INFO - Epoch(train) [77][700/2119] lr: 4.0000e-02 eta: 15:00:34 time: 0.3713 data_time: 0.0225 memory: 5826 grad_norm: 3.1391 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7341 loss: 2.7341 2022/10/07 23:29:50 - mmengine - INFO - Epoch(train) [77][720/2119] lr: 4.0000e-02 eta: 15:00:27 time: 0.3314 data_time: 0.0232 memory: 5826 grad_norm: 3.1204 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.9962 loss: 2.9962 2022/10/07 23:29:57 - mmengine - INFO - Epoch(train) [77][740/2119] lr: 4.0000e-02 eta: 15:00:20 time: 0.3521 data_time: 0.0229 memory: 5826 grad_norm: 3.1285 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7407 loss: 2.7407 2022/10/07 23:30:04 - mmengine - INFO - Epoch(train) [77][760/2119] lr: 4.0000e-02 eta: 15:00:14 time: 0.3616 data_time: 0.0231 memory: 5826 grad_norm: 3.1089 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7357 loss: 2.7357 2022/10/07 23:30:12 - mmengine - INFO - Epoch(train) [77][780/2119] lr: 4.0000e-02 eta: 15:00:07 time: 0.3665 data_time: 0.0251 memory: 5826 grad_norm: 3.0924 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6063 loss: 2.6063 2022/10/07 23:30:18 - mmengine - INFO - Epoch(train) [77][800/2119] lr: 4.0000e-02 eta: 15:00:00 time: 0.3320 data_time: 0.0272 memory: 5826 grad_norm: 3.1313 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.9675 loss: 2.9675 2022/10/07 23:30:25 - mmengine - INFO - Epoch(train) [77][820/2119] lr: 4.0000e-02 eta: 14:59:53 time: 0.3618 data_time: 0.0318 memory: 5826 grad_norm: 3.0747 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9628 loss: 2.9628 2022/10/07 23:30:32 - mmengine - INFO - Epoch(train) [77][840/2119] lr: 4.0000e-02 eta: 14:59:46 time: 0.3303 data_time: 0.0270 memory: 5826 grad_norm: 3.1123 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.7349 loss: 2.7349 2022/10/07 23:30:40 - mmengine - INFO - Epoch(train) [77][860/2119] lr: 4.0000e-02 eta: 14:59:40 time: 0.3809 data_time: 0.0265 memory: 5826 grad_norm: 3.1171 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7703 loss: 2.7703 2022/10/07 23:30:47 - mmengine - INFO - Epoch(train) [77][880/2119] lr: 4.0000e-02 eta: 14:59:33 time: 0.3663 data_time: 0.0280 memory: 5826 grad_norm: 3.1173 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9512 loss: 2.9512 2022/10/07 23:30:55 - mmengine - INFO - Epoch(train) [77][900/2119] lr: 4.0000e-02 eta: 14:59:27 time: 0.3863 data_time: 0.0220 memory: 5826 grad_norm: 3.0771 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5774 loss: 2.5774 2022/10/07 23:31:01 - mmengine - INFO - Epoch(train) [77][920/2119] lr: 4.0000e-02 eta: 14:59:20 time: 0.3132 data_time: 0.0272 memory: 5826 grad_norm: 3.1269 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8719 loss: 2.8719 2022/10/07 23:31:08 - mmengine - INFO - Epoch(train) [77][940/2119] lr: 4.0000e-02 eta: 14:59:12 time: 0.3336 data_time: 0.0218 memory: 5826 grad_norm: 3.0740 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8420 loss: 2.8420 2022/10/07 23:31:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 23:31:15 - mmengine - INFO - Epoch(train) [77][960/2119] lr: 4.0000e-02 eta: 14:59:06 time: 0.3674 data_time: 0.0213 memory: 5826 grad_norm: 3.0920 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6562 loss: 2.6562 2022/10/07 23:31:22 - mmengine - INFO - Epoch(train) [77][980/2119] lr: 4.0000e-02 eta: 14:58:59 time: 0.3475 data_time: 0.0265 memory: 5826 grad_norm: 3.0829 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5680 loss: 2.5680 2022/10/07 23:31:29 - mmengine - INFO - Epoch(train) [77][1000/2119] lr: 4.0000e-02 eta: 14:58:53 time: 0.3725 data_time: 0.0220 memory: 5826 grad_norm: 3.1440 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7490 loss: 2.7490 2022/10/07 23:31:36 - mmengine - INFO - Epoch(train) [77][1020/2119] lr: 4.0000e-02 eta: 14:58:46 time: 0.3487 data_time: 0.0208 memory: 5826 grad_norm: 3.1054 top1_acc: 0.1250 top5_acc: 0.6875 loss_cls: 2.6027 loss: 2.6027 2022/10/07 23:31:44 - mmengine - INFO - Epoch(train) [77][1040/2119] lr: 4.0000e-02 eta: 14:58:40 time: 0.3918 data_time: 0.0193 memory: 5826 grad_norm: 3.1256 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6116 loss: 2.6116 2022/10/07 23:31:51 - mmengine - INFO - Epoch(train) [77][1060/2119] lr: 4.0000e-02 eta: 14:58:32 time: 0.3179 data_time: 0.0275 memory: 5826 grad_norm: 3.1140 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6301 loss: 2.6301 2022/10/07 23:31:58 - mmengine - INFO - Epoch(train) [77][1080/2119] lr: 4.0000e-02 eta: 14:58:26 time: 0.3858 data_time: 0.0217 memory: 5826 grad_norm: 3.1101 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.7693 loss: 2.7693 2022/10/07 23:32:05 - mmengine - INFO - Epoch(train) [77][1100/2119] lr: 4.0000e-02 eta: 14:58:19 time: 0.3323 data_time: 0.0222 memory: 5826 grad_norm: 3.0876 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.7136 loss: 2.7136 2022/10/07 23:32:12 - mmengine - INFO - Epoch(train) [77][1120/2119] lr: 4.0000e-02 eta: 14:58:12 time: 0.3655 data_time: 0.0274 memory: 5826 grad_norm: 3.1119 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5867 loss: 2.5867 2022/10/07 23:32:18 - mmengine - INFO - Epoch(train) [77][1140/2119] lr: 4.0000e-02 eta: 14:58:04 time: 0.3001 data_time: 0.0247 memory: 5826 grad_norm: 3.1045 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9178 loss: 2.9178 2022/10/07 23:32:26 - mmengine - INFO - Epoch(train) [77][1160/2119] lr: 4.0000e-02 eta: 14:57:58 time: 0.3689 data_time: 0.0258 memory: 5826 grad_norm: 3.1118 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5897 loss: 2.5897 2022/10/07 23:32:33 - mmengine - INFO - Epoch(train) [77][1180/2119] lr: 4.0000e-02 eta: 14:57:51 time: 0.3528 data_time: 0.0252 memory: 5826 grad_norm: 3.1099 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4095 loss: 2.4095 2022/10/07 23:32:40 - mmengine - INFO - Epoch(train) [77][1200/2119] lr: 4.0000e-02 eta: 14:57:44 time: 0.3441 data_time: 0.0195 memory: 5826 grad_norm: 3.1048 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8728 loss: 2.8728 2022/10/07 23:32:47 - mmengine - INFO - Epoch(train) [77][1220/2119] lr: 4.0000e-02 eta: 14:57:38 time: 0.3568 data_time: 0.0188 memory: 5826 grad_norm: 3.1145 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6393 loss: 2.6393 2022/10/07 23:32:54 - mmengine - INFO - Epoch(train) [77][1240/2119] lr: 4.0000e-02 eta: 14:57:31 time: 0.3470 data_time: 0.0190 memory: 5826 grad_norm: 3.1561 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6246 loss: 2.6246 2022/10/07 23:33:01 - mmengine - INFO - Epoch(train) [77][1260/2119] lr: 4.0000e-02 eta: 14:57:24 time: 0.3589 data_time: 0.0247 memory: 5826 grad_norm: 3.0963 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6002 loss: 2.6002 2022/10/07 23:33:10 - mmengine - INFO - Epoch(train) [77][1280/2119] lr: 4.0000e-02 eta: 14:57:19 time: 0.4413 data_time: 0.0276 memory: 5826 grad_norm: 3.2021 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8381 loss: 2.8381 2022/10/07 23:33:17 - mmengine - INFO - Epoch(train) [77][1300/2119] lr: 4.0000e-02 eta: 14:57:12 time: 0.3741 data_time: 0.0207 memory: 5826 grad_norm: 3.0974 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7577 loss: 2.7577 2022/10/07 23:33:25 - mmengine - INFO - Epoch(train) [77][1320/2119] lr: 4.0000e-02 eta: 14:57:07 time: 0.4026 data_time: 0.0232 memory: 5826 grad_norm: 3.1065 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8349 loss: 2.8349 2022/10/07 23:33:31 - mmengine - INFO - Epoch(train) [77][1340/2119] lr: 4.0000e-02 eta: 14:56:59 time: 0.3019 data_time: 0.0236 memory: 5826 grad_norm: 3.1619 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6378 loss: 2.6378 2022/10/07 23:33:38 - mmengine - INFO - Epoch(train) [77][1360/2119] lr: 4.0000e-02 eta: 14:56:52 time: 0.3397 data_time: 0.0262 memory: 5826 grad_norm: 3.1606 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9471 loss: 2.9471 2022/10/07 23:33:45 - mmengine - INFO - Epoch(train) [77][1380/2119] lr: 4.0000e-02 eta: 14:56:45 time: 0.3546 data_time: 0.0290 memory: 5826 grad_norm: 3.1253 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5664 loss: 2.5664 2022/10/07 23:33:53 - mmengine - INFO - Epoch(train) [77][1400/2119] lr: 4.0000e-02 eta: 14:56:39 time: 0.3970 data_time: 0.0269 memory: 5826 grad_norm: 3.1380 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6800 loss: 2.6800 2022/10/07 23:34:00 - mmengine - INFO - Epoch(train) [77][1420/2119] lr: 4.0000e-02 eta: 14:56:32 time: 0.3307 data_time: 0.0266 memory: 5826 grad_norm: 3.1112 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6214 loss: 2.6214 2022/10/07 23:34:08 - mmengine - INFO - Epoch(train) [77][1440/2119] lr: 4.0000e-02 eta: 14:56:26 time: 0.4074 data_time: 0.0236 memory: 5826 grad_norm: 3.1418 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7111 loss: 2.7111 2022/10/07 23:34:15 - mmengine - INFO - Epoch(train) [77][1460/2119] lr: 4.0000e-02 eta: 14:56:19 time: 0.3409 data_time: 0.0247 memory: 5826 grad_norm: 3.0644 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7057 loss: 2.7057 2022/10/07 23:34:23 - mmengine - INFO - Epoch(train) [77][1480/2119] lr: 4.0000e-02 eta: 14:56:13 time: 0.3939 data_time: 0.0244 memory: 5826 grad_norm: 3.0936 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6504 loss: 2.6504 2022/10/07 23:34:29 - mmengine - INFO - Epoch(train) [77][1500/2119] lr: 4.0000e-02 eta: 14:56:06 time: 0.3158 data_time: 0.0223 memory: 5826 grad_norm: 3.1487 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.1226 loss: 3.1226 2022/10/07 23:34:37 - mmengine - INFO - Epoch(train) [77][1520/2119] lr: 4.0000e-02 eta: 14:55:59 time: 0.3773 data_time: 0.0196 memory: 5826 grad_norm: 3.1081 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.5971 loss: 2.5971 2022/10/07 23:34:43 - mmengine - INFO - Epoch(train) [77][1540/2119] lr: 4.0000e-02 eta: 14:55:51 time: 0.2980 data_time: 0.0228 memory: 5826 grad_norm: 3.1745 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7450 loss: 2.7450 2022/10/07 23:34:50 - mmengine - INFO - Epoch(train) [77][1560/2119] lr: 4.0000e-02 eta: 14:55:45 time: 0.3711 data_time: 0.0266 memory: 5826 grad_norm: 3.0883 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.6443 loss: 2.6443 2022/10/07 23:34:57 - mmengine - INFO - Epoch(train) [77][1580/2119] lr: 4.0000e-02 eta: 14:55:38 time: 0.3344 data_time: 0.0249 memory: 5826 grad_norm: 3.1334 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7153 loss: 2.7153 2022/10/07 23:35:04 - mmengine - INFO - Epoch(train) [77][1600/2119] lr: 4.0000e-02 eta: 14:55:31 time: 0.3588 data_time: 0.0202 memory: 5826 grad_norm: 3.1189 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6614 loss: 2.6614 2022/10/07 23:35:10 - mmengine - INFO - Epoch(train) [77][1620/2119] lr: 4.0000e-02 eta: 14:55:24 time: 0.3154 data_time: 0.0218 memory: 5826 grad_norm: 3.1585 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4988 loss: 2.4988 2022/10/07 23:35:18 - mmengine - INFO - Epoch(train) [77][1640/2119] lr: 4.0000e-02 eta: 14:55:17 time: 0.3667 data_time: 0.0230 memory: 5826 grad_norm: 3.1543 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8829 loss: 2.8829 2022/10/07 23:35:24 - mmengine - INFO - Epoch(train) [77][1660/2119] lr: 4.0000e-02 eta: 14:55:10 time: 0.3230 data_time: 0.0256 memory: 5826 grad_norm: 3.0896 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8017 loss: 2.8017 2022/10/07 23:35:31 - mmengine - INFO - Epoch(train) [77][1680/2119] lr: 4.0000e-02 eta: 14:55:03 time: 0.3572 data_time: 0.0285 memory: 5826 grad_norm: 3.0977 top1_acc: 0.1875 top5_acc: 0.7500 loss_cls: 2.6614 loss: 2.6614 2022/10/07 23:35:38 - mmengine - INFO - Epoch(train) [77][1700/2119] lr: 4.0000e-02 eta: 14:54:56 time: 0.3551 data_time: 0.0195 memory: 5826 grad_norm: 3.1337 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.4573 loss: 2.4573 2022/10/07 23:35:45 - mmengine - INFO - Epoch(train) [77][1720/2119] lr: 4.0000e-02 eta: 14:54:49 time: 0.3558 data_time: 0.0342 memory: 5826 grad_norm: 3.0709 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7393 loss: 2.7393 2022/10/07 23:35:52 - mmengine - INFO - Epoch(train) [77][1740/2119] lr: 4.0000e-02 eta: 14:54:42 time: 0.3386 data_time: 0.0222 memory: 5826 grad_norm: 3.0758 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6118 loss: 2.6118 2022/10/07 23:36:00 - mmengine - INFO - Epoch(train) [77][1760/2119] lr: 4.0000e-02 eta: 14:54:36 time: 0.3686 data_time: 0.0229 memory: 5826 grad_norm: 3.1734 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8099 loss: 2.8099 2022/10/07 23:36:07 - mmengine - INFO - Epoch(train) [77][1780/2119] lr: 4.0000e-02 eta: 14:54:29 time: 0.3531 data_time: 0.0233 memory: 5826 grad_norm: 3.0968 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7931 loss: 2.7931 2022/10/07 23:36:13 - mmengine - INFO - Epoch(train) [77][1800/2119] lr: 4.0000e-02 eta: 14:54:22 time: 0.3431 data_time: 0.0222 memory: 5826 grad_norm: 3.0638 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7990 loss: 2.7990 2022/10/07 23:36:20 - mmengine - INFO - Epoch(train) [77][1820/2119] lr: 4.0000e-02 eta: 14:54:14 time: 0.3074 data_time: 0.0275 memory: 5826 grad_norm: 3.1380 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7184 loss: 2.7184 2022/10/07 23:36:28 - mmengine - INFO - Epoch(train) [77][1840/2119] lr: 4.0000e-02 eta: 14:54:08 time: 0.3961 data_time: 0.0251 memory: 5826 grad_norm: 3.0760 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7693 loss: 2.7693 2022/10/07 23:36:35 - mmengine - INFO - Epoch(train) [77][1860/2119] lr: 4.0000e-02 eta: 14:54:02 time: 0.3495 data_time: 0.0209 memory: 5826 grad_norm: 3.1332 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8584 loss: 2.8584 2022/10/07 23:36:42 - mmengine - INFO - Epoch(train) [77][1880/2119] lr: 4.0000e-02 eta: 14:53:55 time: 0.3835 data_time: 0.0200 memory: 5826 grad_norm: 3.1209 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7268 loss: 2.7268 2022/10/07 23:36:49 - mmengine - INFO - Epoch(train) [77][1900/2119] lr: 4.0000e-02 eta: 14:53:48 time: 0.3223 data_time: 0.0274 memory: 5826 grad_norm: 3.1462 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7127 loss: 2.7127 2022/10/07 23:36:56 - mmengine - INFO - Epoch(train) [77][1920/2119] lr: 4.0000e-02 eta: 14:53:42 time: 0.3797 data_time: 0.0202 memory: 5826 grad_norm: 3.0832 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5960 loss: 2.5960 2022/10/07 23:37:02 - mmengine - INFO - Epoch(train) [77][1940/2119] lr: 4.0000e-02 eta: 14:53:34 time: 0.3056 data_time: 0.0234 memory: 5826 grad_norm: 3.0721 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7886 loss: 2.7886 2022/10/07 23:37:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 23:37:10 - mmengine - INFO - Epoch(train) [77][1960/2119] lr: 4.0000e-02 eta: 14:53:28 time: 0.3740 data_time: 0.0204 memory: 5826 grad_norm: 3.1544 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7706 loss: 2.7706 2022/10/07 23:37:17 - mmengine - INFO - Epoch(train) [77][1980/2119] lr: 4.0000e-02 eta: 14:53:21 time: 0.3655 data_time: 0.0222 memory: 5826 grad_norm: 3.1009 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8450 loss: 2.8450 2022/10/07 23:37:24 - mmengine - INFO - Epoch(train) [77][2000/2119] lr: 4.0000e-02 eta: 14:53:14 time: 0.3459 data_time: 0.0234 memory: 5826 grad_norm: 3.1621 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7019 loss: 2.7019 2022/10/07 23:37:31 - mmengine - INFO - Epoch(train) [77][2020/2119] lr: 4.0000e-02 eta: 14:53:07 time: 0.3594 data_time: 0.0202 memory: 5826 grad_norm: 3.1015 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7622 loss: 2.7622 2022/10/07 23:37:38 - mmengine - INFO - Epoch(train) [77][2040/2119] lr: 4.0000e-02 eta: 14:53:01 time: 0.3521 data_time: 0.0224 memory: 5826 grad_norm: 3.1555 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.7938 loss: 2.7938 2022/10/07 23:37:45 - mmengine - INFO - Epoch(train) [77][2060/2119] lr: 4.0000e-02 eta: 14:52:54 time: 0.3356 data_time: 0.0234 memory: 5826 grad_norm: 3.0810 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4362 loss: 2.4362 2022/10/07 23:37:53 - mmengine - INFO - Epoch(train) [77][2080/2119] lr: 4.0000e-02 eta: 14:52:48 time: 0.4012 data_time: 0.0259 memory: 5826 grad_norm: 3.1097 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7202 loss: 2.7202 2022/10/07 23:38:00 - mmengine - INFO - Epoch(train) [77][2100/2119] lr: 4.0000e-02 eta: 14:52:41 time: 0.3434 data_time: 0.0198 memory: 5826 grad_norm: 3.2128 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8951 loss: 2.8951 2022/10/07 23:38:06 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 23:38:06 - mmengine - INFO - Epoch(train) [77][2119/2119] lr: 4.0000e-02 eta: 14:52:41 time: 0.3333 data_time: 0.0220 memory: 5826 grad_norm: 3.1984 top1_acc: 0.6000 top5_acc: 0.8000 loss_cls: 2.5029 loss: 2.5029 2022/10/07 23:38:16 - mmengine - INFO - Epoch(train) [78][20/2119] lr: 4.0000e-02 eta: 14:52:23 time: 0.4643 data_time: 0.1105 memory: 5826 grad_norm: 3.0864 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4329 loss: 2.4329 2022/10/07 23:38:23 - mmengine - INFO - Epoch(train) [78][40/2119] lr: 4.0000e-02 eta: 14:52:17 time: 0.3733 data_time: 0.0229 memory: 5826 grad_norm: 3.1256 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9276 loss: 2.9276 2022/10/07 23:38:30 - mmengine - INFO - Epoch(train) [78][60/2119] lr: 4.0000e-02 eta: 14:52:10 time: 0.3432 data_time: 0.0209 memory: 5826 grad_norm: 3.1401 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.9426 loss: 2.9426 2022/10/07 23:38:37 - mmengine - INFO - Epoch(train) [78][80/2119] lr: 4.0000e-02 eta: 14:52:03 time: 0.3473 data_time: 0.0220 memory: 5826 grad_norm: 3.1067 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8413 loss: 2.8413 2022/10/07 23:38:44 - mmengine - INFO - Epoch(train) [78][100/2119] lr: 4.0000e-02 eta: 14:51:56 time: 0.3422 data_time: 0.0229 memory: 5826 grad_norm: 3.0989 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7042 loss: 2.7042 2022/10/07 23:38:51 - mmengine - INFO - Epoch(train) [78][120/2119] lr: 4.0000e-02 eta: 14:51:50 time: 0.3791 data_time: 0.0226 memory: 5826 grad_norm: 3.0842 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8279 loss: 2.8279 2022/10/07 23:38:59 - mmengine - INFO - Epoch(train) [78][140/2119] lr: 4.0000e-02 eta: 14:51:43 time: 0.3810 data_time: 0.0248 memory: 5826 grad_norm: 3.1720 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7726 loss: 2.7726 2022/10/07 23:39:07 - mmengine - INFO - Epoch(train) [78][160/2119] lr: 4.0000e-02 eta: 14:51:37 time: 0.4015 data_time: 0.0265 memory: 5826 grad_norm: 3.1768 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5721 loss: 2.5721 2022/10/07 23:39:14 - mmengine - INFO - Epoch(train) [78][180/2119] lr: 4.0000e-02 eta: 14:51:31 time: 0.3547 data_time: 0.0191 memory: 5826 grad_norm: 3.1255 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7036 loss: 2.7036 2022/10/07 23:39:22 - mmengine - INFO - Epoch(train) [78][200/2119] lr: 4.0000e-02 eta: 14:51:25 time: 0.4027 data_time: 0.0227 memory: 5826 grad_norm: 3.0798 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6214 loss: 2.6214 2022/10/07 23:39:29 - mmengine - INFO - Epoch(train) [78][220/2119] lr: 4.0000e-02 eta: 14:51:17 time: 0.3185 data_time: 0.0203 memory: 5826 grad_norm: 3.1674 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7822 loss: 2.7822 2022/10/07 23:39:37 - mmengine - INFO - Epoch(train) [78][240/2119] lr: 4.0000e-02 eta: 14:51:11 time: 0.3942 data_time: 0.0264 memory: 5826 grad_norm: 3.0759 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6760 loss: 2.6760 2022/10/07 23:39:43 - mmengine - INFO - Epoch(train) [78][260/2119] lr: 4.0000e-02 eta: 14:51:04 time: 0.2990 data_time: 0.0262 memory: 5826 grad_norm: 3.1119 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.7854 loss: 2.7854 2022/10/07 23:39:49 - mmengine - INFO - Epoch(train) [78][280/2119] lr: 4.0000e-02 eta: 14:50:56 time: 0.3319 data_time: 0.0265 memory: 5826 grad_norm: 3.1894 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8863 loss: 2.8863 2022/10/07 23:39:56 - mmengine - INFO - Epoch(train) [78][300/2119] lr: 4.0000e-02 eta: 14:50:50 time: 0.3556 data_time: 0.0312 memory: 5826 grad_norm: 3.1188 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6354 loss: 2.6354 2022/10/07 23:40:03 - mmengine - INFO - Epoch(train) [78][320/2119] lr: 4.0000e-02 eta: 14:50:43 time: 0.3507 data_time: 0.0252 memory: 5826 grad_norm: 3.1212 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.3283 loss: 2.3283 2022/10/07 23:40:10 - mmengine - INFO - Epoch(train) [78][340/2119] lr: 4.0000e-02 eta: 14:50:36 time: 0.3352 data_time: 0.0243 memory: 5826 grad_norm: 3.1054 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5003 loss: 2.5003 2022/10/07 23:40:19 - mmengine - INFO - Epoch(train) [78][360/2119] lr: 4.0000e-02 eta: 14:50:30 time: 0.4355 data_time: 0.0344 memory: 5826 grad_norm: 3.1337 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6675 loss: 2.6675 2022/10/07 23:40:25 - mmengine - INFO - Epoch(train) [78][380/2119] lr: 4.0000e-02 eta: 14:50:23 time: 0.3153 data_time: 0.0201 memory: 5826 grad_norm: 3.1468 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8556 loss: 2.8556 2022/10/07 23:40:33 - mmengine - INFO - Epoch(train) [78][400/2119] lr: 4.0000e-02 eta: 14:50:17 time: 0.4039 data_time: 0.0288 memory: 5826 grad_norm: 3.1626 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.5023 loss: 2.5023 2022/10/07 23:40:39 - mmengine - INFO - Epoch(train) [78][420/2119] lr: 4.0000e-02 eta: 14:50:09 time: 0.2982 data_time: 0.0184 memory: 5826 grad_norm: 3.0978 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6812 loss: 2.6812 2022/10/07 23:40:46 - mmengine - INFO - Epoch(train) [78][440/2119] lr: 4.0000e-02 eta: 14:50:02 time: 0.3550 data_time: 0.0349 memory: 5826 grad_norm: 3.1529 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7256 loss: 2.7256 2022/10/07 23:40:53 - mmengine - INFO - Epoch(train) [78][460/2119] lr: 4.0000e-02 eta: 14:49:55 time: 0.3385 data_time: 0.0254 memory: 5826 grad_norm: 3.1253 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6620 loss: 2.6620 2022/10/07 23:41:00 - mmengine - INFO - Epoch(train) [78][480/2119] lr: 4.0000e-02 eta: 14:49:49 time: 0.3545 data_time: 0.0227 memory: 5826 grad_norm: 3.1326 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7973 loss: 2.7973 2022/10/07 23:41:07 - mmengine - INFO - Epoch(train) [78][500/2119] lr: 4.0000e-02 eta: 14:49:41 time: 0.3206 data_time: 0.0239 memory: 5826 grad_norm: 3.1463 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5851 loss: 2.5851 2022/10/07 23:41:14 - mmengine - INFO - Epoch(train) [78][520/2119] lr: 4.0000e-02 eta: 14:49:35 time: 0.3641 data_time: 0.0275 memory: 5826 grad_norm: 3.1576 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8810 loss: 2.8810 2022/10/07 23:41:20 - mmengine - INFO - Epoch(train) [78][540/2119] lr: 4.0000e-02 eta: 14:49:27 time: 0.3292 data_time: 0.0234 memory: 5826 grad_norm: 3.1070 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6576 loss: 2.6576 2022/10/07 23:41:28 - mmengine - INFO - Epoch(train) [78][560/2119] lr: 4.0000e-02 eta: 14:49:21 time: 0.3727 data_time: 0.0256 memory: 5826 grad_norm: 3.1379 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5733 loss: 2.5733 2022/10/07 23:41:34 - mmengine - INFO - Epoch(train) [78][580/2119] lr: 4.0000e-02 eta: 14:49:14 time: 0.3298 data_time: 0.0225 memory: 5826 grad_norm: 3.0606 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6268 loss: 2.6268 2022/10/07 23:41:42 - mmengine - INFO - Epoch(train) [78][600/2119] lr: 4.0000e-02 eta: 14:49:07 time: 0.3569 data_time: 0.0236 memory: 5826 grad_norm: 3.0966 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6810 loss: 2.6810 2022/10/07 23:41:48 - mmengine - INFO - Epoch(train) [78][620/2119] lr: 4.0000e-02 eta: 14:49:00 time: 0.3353 data_time: 0.0237 memory: 5826 grad_norm: 3.2029 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.4827 loss: 2.4827 2022/10/07 23:41:56 - mmengine - INFO - Epoch(train) [78][640/2119] lr: 4.0000e-02 eta: 14:48:54 time: 0.3840 data_time: 0.0225 memory: 5826 grad_norm: 3.1465 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7129 loss: 2.7129 2022/10/07 23:42:03 - mmengine - INFO - Epoch(train) [78][660/2119] lr: 4.0000e-02 eta: 14:48:47 time: 0.3344 data_time: 0.0263 memory: 5826 grad_norm: 3.1015 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6137 loss: 2.6137 2022/10/07 23:42:10 - mmengine - INFO - Epoch(train) [78][680/2119] lr: 4.0000e-02 eta: 14:48:40 time: 0.3643 data_time: 0.0185 memory: 5826 grad_norm: 3.1208 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6010 loss: 2.6010 2022/10/07 23:42:18 - mmengine - INFO - Epoch(train) [78][700/2119] lr: 4.0000e-02 eta: 14:48:34 time: 0.3858 data_time: 0.0241 memory: 5826 grad_norm: 3.1736 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5514 loss: 2.5514 2022/10/07 23:42:24 - mmengine - INFO - Epoch(train) [78][720/2119] lr: 4.0000e-02 eta: 14:48:26 time: 0.3094 data_time: 0.0257 memory: 5826 grad_norm: 3.1679 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6005 loss: 2.6005 2022/10/07 23:42:31 - mmengine - INFO - Epoch(train) [78][740/2119] lr: 4.0000e-02 eta: 14:48:19 time: 0.3453 data_time: 0.0228 memory: 5826 grad_norm: 3.1054 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7273 loss: 2.7273 2022/10/07 23:42:39 - mmengine - INFO - Epoch(train) [78][760/2119] lr: 4.0000e-02 eta: 14:48:13 time: 0.3961 data_time: 0.0236 memory: 5826 grad_norm: 3.1326 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.5843 loss: 2.5843 2022/10/07 23:42:46 - mmengine - INFO - Epoch(train) [78][780/2119] lr: 4.0000e-02 eta: 14:48:06 time: 0.3399 data_time: 0.0238 memory: 5826 grad_norm: 3.1718 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6136 loss: 2.6136 2022/10/07 23:42:53 - mmengine - INFO - Epoch(train) [78][800/2119] lr: 4.0000e-02 eta: 14:48:00 time: 0.3841 data_time: 0.0190 memory: 5826 grad_norm: 3.1493 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6471 loss: 2.6471 2022/10/07 23:42:59 - mmengine - INFO - Epoch(train) [78][820/2119] lr: 4.0000e-02 eta: 14:47:52 time: 0.2982 data_time: 0.0231 memory: 5826 grad_norm: 3.1249 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.5766 loss: 2.5766 2022/10/07 23:43:06 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 23:43:07 - mmengine - INFO - Epoch(train) [78][840/2119] lr: 4.0000e-02 eta: 14:47:46 time: 0.3934 data_time: 0.0224 memory: 5826 grad_norm: 3.0862 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5240 loss: 2.5240 2022/10/07 23:43:13 - mmengine - INFO - Epoch(train) [78][860/2119] lr: 4.0000e-02 eta: 14:47:38 time: 0.3052 data_time: 0.0234 memory: 5826 grad_norm: 3.0652 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7453 loss: 2.7453 2022/10/07 23:43:21 - mmengine - INFO - Epoch(train) [78][880/2119] lr: 4.0000e-02 eta: 14:47:32 time: 0.3706 data_time: 0.0237 memory: 5826 grad_norm: 3.0774 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5899 loss: 2.5899 2022/10/07 23:43:27 - mmengine - INFO - Epoch(train) [78][900/2119] lr: 4.0000e-02 eta: 14:47:25 time: 0.3280 data_time: 0.0230 memory: 5826 grad_norm: 3.1853 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8107 loss: 2.8107 2022/10/07 23:43:35 - mmengine - INFO - Epoch(train) [78][920/2119] lr: 4.0000e-02 eta: 14:47:19 time: 0.3954 data_time: 0.0260 memory: 5826 grad_norm: 3.1717 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6144 loss: 2.6144 2022/10/07 23:43:42 - mmengine - INFO - Epoch(train) [78][940/2119] lr: 4.0000e-02 eta: 14:47:12 time: 0.3688 data_time: 0.0190 memory: 5826 grad_norm: 3.1579 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7116 loss: 2.7116 2022/10/07 23:43:50 - mmengine - INFO - Epoch(train) [78][960/2119] lr: 4.0000e-02 eta: 14:47:06 time: 0.3847 data_time: 0.0231 memory: 5826 grad_norm: 3.1667 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9197 loss: 2.9197 2022/10/07 23:43:57 - mmengine - INFO - Epoch(train) [78][980/2119] lr: 4.0000e-02 eta: 14:46:59 time: 0.3487 data_time: 0.0212 memory: 5826 grad_norm: 3.1288 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4237 loss: 2.4237 2022/10/07 23:44:04 - mmengine - INFO - Epoch(train) [78][1000/2119] lr: 4.0000e-02 eta: 14:46:53 time: 0.3664 data_time: 0.0218 memory: 5826 grad_norm: 3.1253 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7681 loss: 2.7681 2022/10/07 23:44:11 - mmengine - INFO - Epoch(train) [78][1020/2119] lr: 4.0000e-02 eta: 14:46:45 time: 0.3314 data_time: 0.0262 memory: 5826 grad_norm: 3.1311 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.5800 loss: 2.5800 2022/10/07 23:44:18 - mmengine - INFO - Epoch(train) [78][1040/2119] lr: 4.0000e-02 eta: 14:46:39 time: 0.3700 data_time: 0.0295 memory: 5826 grad_norm: 3.1660 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5822 loss: 2.5822 2022/10/07 23:44:25 - mmengine - INFO - Epoch(train) [78][1060/2119] lr: 4.0000e-02 eta: 14:46:32 time: 0.3427 data_time: 0.0246 memory: 5826 grad_norm: 3.1050 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7901 loss: 2.7901 2022/10/07 23:44:33 - mmengine - INFO - Epoch(train) [78][1080/2119] lr: 4.0000e-02 eta: 14:46:26 time: 0.3882 data_time: 0.0299 memory: 5826 grad_norm: 3.0784 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8726 loss: 2.8726 2022/10/07 23:44:40 - mmengine - INFO - Epoch(train) [78][1100/2119] lr: 4.0000e-02 eta: 14:46:19 time: 0.3445 data_time: 0.0237 memory: 5826 grad_norm: 3.1707 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7977 loss: 2.7977 2022/10/07 23:44:47 - mmengine - INFO - Epoch(train) [78][1120/2119] lr: 4.0000e-02 eta: 14:46:12 time: 0.3389 data_time: 0.0229 memory: 5826 grad_norm: 3.1150 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5898 loss: 2.5898 2022/10/07 23:44:54 - mmengine - INFO - Epoch(train) [78][1140/2119] lr: 4.0000e-02 eta: 14:46:05 time: 0.3481 data_time: 0.0256 memory: 5826 grad_norm: 3.0912 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.8095 loss: 2.8095 2022/10/07 23:45:01 - mmengine - INFO - Epoch(train) [78][1160/2119] lr: 4.0000e-02 eta: 14:45:58 time: 0.3530 data_time: 0.0268 memory: 5826 grad_norm: 3.1273 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6577 loss: 2.6577 2022/10/07 23:45:08 - mmengine - INFO - Epoch(train) [78][1180/2119] lr: 4.0000e-02 eta: 14:45:51 time: 0.3394 data_time: 0.0261 memory: 5826 grad_norm: 3.2027 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.7471 loss: 2.7471 2022/10/07 23:45:15 - mmengine - INFO - Epoch(train) [78][1200/2119] lr: 4.0000e-02 eta: 14:45:44 time: 0.3689 data_time: 0.0245 memory: 5826 grad_norm: 3.1488 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9926 loss: 2.9926 2022/10/07 23:45:22 - mmengine - INFO - Epoch(train) [78][1220/2119] lr: 4.0000e-02 eta: 14:45:38 time: 0.3483 data_time: 0.0262 memory: 5826 grad_norm: 3.0846 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6010 loss: 2.6010 2022/10/07 23:45:29 - mmengine - INFO - Epoch(train) [78][1240/2119] lr: 4.0000e-02 eta: 14:45:31 time: 0.3705 data_time: 0.0179 memory: 5826 grad_norm: 3.1100 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6327 loss: 2.6327 2022/10/07 23:45:36 - mmengine - INFO - Epoch(train) [78][1260/2119] lr: 4.0000e-02 eta: 14:45:24 time: 0.3495 data_time: 0.0208 memory: 5826 grad_norm: 3.1446 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4624 loss: 2.4624 2022/10/07 23:45:44 - mmengine - INFO - Epoch(train) [78][1280/2119] lr: 4.0000e-02 eta: 14:45:18 time: 0.3687 data_time: 0.0230 memory: 5826 grad_norm: 3.1558 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6633 loss: 2.6633 2022/10/07 23:45:49 - mmengine - INFO - Epoch(train) [78][1300/2119] lr: 4.0000e-02 eta: 14:45:10 time: 0.2809 data_time: 0.0239 memory: 5826 grad_norm: 3.0898 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.1776 loss: 3.1776 2022/10/07 23:45:57 - mmengine - INFO - Epoch(train) [78][1320/2119] lr: 4.0000e-02 eta: 14:45:03 time: 0.3687 data_time: 0.0223 memory: 5826 grad_norm: 3.0759 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4939 loss: 2.4939 2022/10/07 23:46:04 - mmengine - INFO - Epoch(train) [78][1340/2119] lr: 4.0000e-02 eta: 14:44:56 time: 0.3482 data_time: 0.0232 memory: 5826 grad_norm: 3.1011 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5431 loss: 2.5431 2022/10/07 23:46:11 - mmengine - INFO - Epoch(train) [78][1360/2119] lr: 4.0000e-02 eta: 14:44:50 time: 0.3640 data_time: 0.0236 memory: 5826 grad_norm: 3.0958 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6367 loss: 2.6367 2022/10/07 23:46:18 - mmengine - INFO - Epoch(train) [78][1380/2119] lr: 4.0000e-02 eta: 14:44:43 time: 0.3381 data_time: 0.0229 memory: 5826 grad_norm: 3.1273 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5653 loss: 2.5653 2022/10/07 23:46:26 - mmengine - INFO - Epoch(train) [78][1400/2119] lr: 4.0000e-02 eta: 14:44:37 time: 0.4309 data_time: 0.0245 memory: 5826 grad_norm: 3.1269 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5669 loss: 2.5669 2022/10/07 23:46:33 - mmengine - INFO - Epoch(train) [78][1420/2119] lr: 4.0000e-02 eta: 14:44:30 time: 0.3401 data_time: 0.0259 memory: 5826 grad_norm: 3.0986 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6451 loss: 2.6451 2022/10/07 23:46:40 - mmengine - INFO - Epoch(train) [78][1440/2119] lr: 4.0000e-02 eta: 14:44:23 time: 0.3299 data_time: 0.0249 memory: 5826 grad_norm: 3.1033 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7511 loss: 2.7511 2022/10/07 23:46:46 - mmengine - INFO - Epoch(train) [78][1460/2119] lr: 4.0000e-02 eta: 14:44:15 time: 0.3058 data_time: 0.0208 memory: 5826 grad_norm: 3.0969 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.4684 loss: 2.4684 2022/10/07 23:46:54 - mmengine - INFO - Epoch(train) [78][1480/2119] lr: 4.0000e-02 eta: 14:44:09 time: 0.3817 data_time: 0.0277 memory: 5826 grad_norm: 3.1282 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5478 loss: 2.5478 2022/10/07 23:47:00 - mmengine - INFO - Epoch(train) [78][1500/2119] lr: 4.0000e-02 eta: 14:44:01 time: 0.3084 data_time: 0.0260 memory: 5826 grad_norm: 3.1144 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6424 loss: 2.6424 2022/10/07 23:47:07 - mmengine - INFO - Epoch(train) [78][1520/2119] lr: 4.0000e-02 eta: 14:43:55 time: 0.3628 data_time: 0.0231 memory: 5826 grad_norm: 3.1178 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5988 loss: 2.5988 2022/10/07 23:47:14 - mmengine - INFO - Epoch(train) [78][1540/2119] lr: 4.0000e-02 eta: 14:43:48 time: 0.3554 data_time: 0.0223 memory: 5826 grad_norm: 3.1262 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8826 loss: 2.8826 2022/10/07 23:47:23 - mmengine - INFO - Epoch(train) [78][1560/2119] lr: 4.0000e-02 eta: 14:43:42 time: 0.4189 data_time: 0.0208 memory: 5826 grad_norm: 3.1223 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9005 loss: 2.9005 2022/10/07 23:47:29 - mmengine - INFO - Epoch(train) [78][1580/2119] lr: 4.0000e-02 eta: 14:43:35 time: 0.3174 data_time: 0.0214 memory: 5826 grad_norm: 3.1170 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7595 loss: 2.7595 2022/10/07 23:47:37 - mmengine - INFO - Epoch(train) [78][1600/2119] lr: 4.0000e-02 eta: 14:43:29 time: 0.3985 data_time: 0.0237 memory: 5826 grad_norm: 3.1209 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.9324 loss: 2.9324 2022/10/07 23:47:44 - mmengine - INFO - Epoch(train) [78][1620/2119] lr: 4.0000e-02 eta: 14:43:22 time: 0.3333 data_time: 0.0212 memory: 5826 grad_norm: 3.1252 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4813 loss: 2.4813 2022/10/07 23:47:51 - mmengine - INFO - Epoch(train) [78][1640/2119] lr: 4.0000e-02 eta: 14:43:15 time: 0.3731 data_time: 0.0215 memory: 5826 grad_norm: 3.1715 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7337 loss: 2.7337 2022/10/07 23:47:58 - mmengine - INFO - Epoch(train) [78][1660/2119] lr: 4.0000e-02 eta: 14:43:09 time: 0.3693 data_time: 0.0215 memory: 5826 grad_norm: 3.1113 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8177 loss: 2.8177 2022/10/07 23:48:06 - mmengine - INFO - Epoch(train) [78][1680/2119] lr: 4.0000e-02 eta: 14:43:02 time: 0.3755 data_time: 0.0217 memory: 5826 grad_norm: 3.0647 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6611 loss: 2.6611 2022/10/07 23:48:13 - mmengine - INFO - Epoch(train) [78][1700/2119] lr: 4.0000e-02 eta: 14:42:56 time: 0.3463 data_time: 0.0248 memory: 5826 grad_norm: 3.0566 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4901 loss: 2.4901 2022/10/07 23:48:21 - mmengine - INFO - Epoch(train) [78][1720/2119] lr: 4.0000e-02 eta: 14:42:50 time: 0.3945 data_time: 0.0195 memory: 5826 grad_norm: 3.1290 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 3.0504 loss: 3.0504 2022/10/07 23:48:27 - mmengine - INFO - Epoch(train) [78][1740/2119] lr: 4.0000e-02 eta: 14:42:42 time: 0.3082 data_time: 0.0254 memory: 5826 grad_norm: 3.1591 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7224 loss: 2.7224 2022/10/07 23:48:35 - mmengine - INFO - Epoch(train) [78][1760/2119] lr: 4.0000e-02 eta: 14:42:36 time: 0.3842 data_time: 0.0246 memory: 5826 grad_norm: 3.1092 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8283 loss: 2.8283 2022/10/07 23:48:41 - mmengine - INFO - Epoch(train) [78][1780/2119] lr: 4.0000e-02 eta: 14:42:28 time: 0.3132 data_time: 0.0174 memory: 5826 grad_norm: 3.0934 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6684 loss: 2.6684 2022/10/07 23:48:49 - mmengine - INFO - Epoch(train) [78][1800/2119] lr: 4.0000e-02 eta: 14:42:22 time: 0.3973 data_time: 0.0229 memory: 5826 grad_norm: 3.0913 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5470 loss: 2.5470 2022/10/07 23:48:55 - mmengine - INFO - Epoch(train) [78][1820/2119] lr: 4.0000e-02 eta: 14:42:15 time: 0.3320 data_time: 0.0261 memory: 5826 grad_norm: 3.1392 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4452 loss: 2.4452 2022/10/07 23:49:01 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 23:49:02 - mmengine - INFO - Epoch(train) [78][1840/2119] lr: 4.0000e-02 eta: 14:42:08 time: 0.3432 data_time: 0.0248 memory: 5826 grad_norm: 3.1498 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9025 loss: 2.9025 2022/10/07 23:49:08 - mmengine - INFO - Epoch(train) [78][1860/2119] lr: 4.0000e-02 eta: 14:42:00 time: 0.3015 data_time: 0.0257 memory: 5826 grad_norm: 3.0998 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6077 loss: 2.6077 2022/10/07 23:49:16 - mmengine - INFO - Epoch(train) [78][1880/2119] lr: 4.0000e-02 eta: 14:41:54 time: 0.3659 data_time: 0.0192 memory: 5826 grad_norm: 3.1445 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7318 loss: 2.7318 2022/10/07 23:49:23 - mmengine - INFO - Epoch(train) [78][1900/2119] lr: 4.0000e-02 eta: 14:41:47 time: 0.3548 data_time: 0.0243 memory: 5826 grad_norm: 3.0753 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6289 loss: 2.6289 2022/10/07 23:49:30 - mmengine - INFO - Epoch(train) [78][1920/2119] lr: 4.0000e-02 eta: 14:41:41 time: 0.3849 data_time: 0.0216 memory: 5826 grad_norm: 3.1895 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8708 loss: 2.8708 2022/10/07 23:49:38 - mmengine - INFO - Epoch(train) [78][1940/2119] lr: 4.0000e-02 eta: 14:41:34 time: 0.3836 data_time: 0.0186 memory: 5826 grad_norm: 3.1396 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7834 loss: 2.7834 2022/10/07 23:49:45 - mmengine - INFO - Epoch(train) [78][1960/2119] lr: 4.0000e-02 eta: 14:41:28 time: 0.3507 data_time: 0.0240 memory: 5826 grad_norm: 3.0978 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5999 loss: 2.5999 2022/10/07 23:49:52 - mmengine - INFO - Epoch(train) [78][1980/2119] lr: 4.0000e-02 eta: 14:41:20 time: 0.3170 data_time: 0.0233 memory: 5826 grad_norm: 3.1213 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7711 loss: 2.7711 2022/10/07 23:50:00 - mmengine - INFO - Epoch(train) [78][2000/2119] lr: 4.0000e-02 eta: 14:41:15 time: 0.4222 data_time: 0.0196 memory: 5826 grad_norm: 3.0970 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6179 loss: 2.6179 2022/10/07 23:50:07 - mmengine - INFO - Epoch(train) [78][2020/2119] lr: 4.0000e-02 eta: 14:41:08 time: 0.3394 data_time: 0.0207 memory: 5826 grad_norm: 3.1535 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6851 loss: 2.6851 2022/10/07 23:50:14 - mmengine - INFO - Epoch(train) [78][2040/2119] lr: 4.0000e-02 eta: 14:41:01 time: 0.3648 data_time: 0.0262 memory: 5826 grad_norm: 3.1476 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8338 loss: 2.8338 2022/10/07 23:50:21 - mmengine - INFO - Epoch(train) [78][2060/2119] lr: 4.0000e-02 eta: 14:40:54 time: 0.3329 data_time: 0.0215 memory: 5826 grad_norm: 3.1607 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8761 loss: 2.8761 2022/10/07 23:50:28 - mmengine - INFO - Epoch(train) [78][2080/2119] lr: 4.0000e-02 eta: 14:40:47 time: 0.3678 data_time: 0.0234 memory: 5826 grad_norm: 3.1032 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7822 loss: 2.7822 2022/10/07 23:50:35 - mmengine - INFO - Epoch(train) [78][2100/2119] lr: 4.0000e-02 eta: 14:40:40 time: 0.3389 data_time: 0.0197 memory: 5826 grad_norm: 3.1042 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7439 loss: 2.7439 2022/10/07 23:50:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 23:50:41 - mmengine - INFO - Epoch(train) [78][2119/2119] lr: 4.0000e-02 eta: 14:40:40 time: 0.3219 data_time: 0.0217 memory: 5826 grad_norm: 3.1400 top1_acc: 0.2000 top5_acc: 0.4000 loss_cls: 2.7813 loss: 2.7813 2022/10/07 23:50:50 - mmengine - INFO - Epoch(train) [79][20/2119] lr: 4.0000e-02 eta: 14:40:23 time: 0.4573 data_time: 0.1182 memory: 5826 grad_norm: 3.1319 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5444 loss: 2.5444 2022/10/07 23:50:58 - mmengine - INFO - Epoch(train) [79][40/2119] lr: 4.0000e-02 eta: 14:40:16 time: 0.3712 data_time: 0.0201 memory: 5826 grad_norm: 3.1073 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5393 loss: 2.5393 2022/10/07 23:51:05 - mmengine - INFO - Epoch(train) [79][60/2119] lr: 4.0000e-02 eta: 14:40:09 time: 0.3477 data_time: 0.0237 memory: 5826 grad_norm: 3.1348 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4972 loss: 2.4972 2022/10/07 23:51:11 - mmengine - INFO - Epoch(train) [79][80/2119] lr: 4.0000e-02 eta: 14:40:02 time: 0.3360 data_time: 0.0204 memory: 5826 grad_norm: 3.0694 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7184 loss: 2.7184 2022/10/07 23:51:19 - mmengine - INFO - Epoch(train) [79][100/2119] lr: 4.0000e-02 eta: 14:39:56 time: 0.3604 data_time: 0.0216 memory: 5826 grad_norm: 3.0741 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7983 loss: 2.7983 2022/10/07 23:51:26 - mmengine - INFO - Epoch(train) [79][120/2119] lr: 4.0000e-02 eta: 14:39:49 time: 0.3525 data_time: 0.0204 memory: 5826 grad_norm: 3.1595 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7372 loss: 2.7372 2022/10/07 23:51:33 - mmengine - INFO - Epoch(train) [79][140/2119] lr: 4.0000e-02 eta: 14:39:42 time: 0.3564 data_time: 0.0211 memory: 5826 grad_norm: 3.1748 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9101 loss: 2.9101 2022/10/07 23:51:40 - mmengine - INFO - Epoch(train) [79][160/2119] lr: 4.0000e-02 eta: 14:39:35 time: 0.3572 data_time: 0.0222 memory: 5826 grad_norm: 3.1542 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9757 loss: 2.9757 2022/10/07 23:51:47 - mmengine - INFO - Epoch(train) [79][180/2119] lr: 4.0000e-02 eta: 14:39:28 time: 0.3495 data_time: 0.0212 memory: 5826 grad_norm: 3.1178 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7508 loss: 2.7508 2022/10/07 23:51:54 - mmengine - INFO - Epoch(train) [79][200/2119] lr: 4.0000e-02 eta: 14:39:22 time: 0.3509 data_time: 0.0284 memory: 5826 grad_norm: 3.1178 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8333 loss: 2.8333 2022/10/07 23:52:01 - mmengine - INFO - Epoch(train) [79][220/2119] lr: 4.0000e-02 eta: 14:39:15 time: 0.3429 data_time: 0.0190 memory: 5826 grad_norm: 3.1205 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.8300 loss: 2.8300 2022/10/07 23:52:07 - mmengine - INFO - Epoch(train) [79][240/2119] lr: 4.0000e-02 eta: 14:39:07 time: 0.3314 data_time: 0.0263 memory: 5826 grad_norm: 3.1148 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.7261 loss: 2.7261 2022/10/07 23:52:15 - mmengine - INFO - Epoch(train) [79][260/2119] lr: 4.0000e-02 eta: 14:39:01 time: 0.3764 data_time: 0.0220 memory: 5826 grad_norm: 3.0872 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9739 loss: 2.9739 2022/10/07 23:52:22 - mmengine - INFO - Epoch(train) [79][280/2119] lr: 4.0000e-02 eta: 14:38:54 time: 0.3266 data_time: 0.0225 memory: 5826 grad_norm: 3.1638 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6021 loss: 2.6021 2022/10/07 23:52:28 - mmengine - INFO - Epoch(train) [79][300/2119] lr: 4.0000e-02 eta: 14:38:46 time: 0.3270 data_time: 0.0204 memory: 5826 grad_norm: 3.1636 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7868 loss: 2.7868 2022/10/07 23:52:36 - mmengine - INFO - Epoch(train) [79][320/2119] lr: 4.0000e-02 eta: 14:38:40 time: 0.3893 data_time: 0.0224 memory: 5826 grad_norm: 3.1356 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9275 loss: 2.9275 2022/10/07 23:52:42 - mmengine - INFO - Epoch(train) [79][340/2119] lr: 4.0000e-02 eta: 14:38:33 time: 0.3178 data_time: 0.0278 memory: 5826 grad_norm: 3.1578 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.8359 loss: 2.8359 2022/10/07 23:52:50 - mmengine - INFO - Epoch(train) [79][360/2119] lr: 4.0000e-02 eta: 14:38:26 time: 0.3744 data_time: 0.0220 memory: 5826 grad_norm: 3.1417 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8026 loss: 2.8026 2022/10/07 23:52:57 - mmengine - INFO - Epoch(train) [79][380/2119] lr: 4.0000e-02 eta: 14:38:20 time: 0.3492 data_time: 0.0306 memory: 5826 grad_norm: 3.0900 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8206 loss: 2.8206 2022/10/07 23:53:04 - mmengine - INFO - Epoch(train) [79][400/2119] lr: 4.0000e-02 eta: 14:38:13 time: 0.3462 data_time: 0.0266 memory: 5826 grad_norm: 3.1361 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8629 loss: 2.8629 2022/10/07 23:53:10 - mmengine - INFO - Epoch(train) [79][420/2119] lr: 4.0000e-02 eta: 14:38:05 time: 0.3257 data_time: 0.0243 memory: 5826 grad_norm: 3.0588 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6387 loss: 2.6387 2022/10/07 23:53:17 - mmengine - INFO - Epoch(train) [79][440/2119] lr: 4.0000e-02 eta: 14:37:59 time: 0.3637 data_time: 0.0252 memory: 5826 grad_norm: 3.0724 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6862 loss: 2.6862 2022/10/07 23:53:25 - mmengine - INFO - Epoch(train) [79][460/2119] lr: 4.0000e-02 eta: 14:37:52 time: 0.3747 data_time: 0.0212 memory: 5826 grad_norm: 3.1465 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7479 loss: 2.7479 2022/10/07 23:53:32 - mmengine - INFO - Epoch(train) [79][480/2119] lr: 4.0000e-02 eta: 14:37:46 time: 0.3620 data_time: 0.0227 memory: 5826 grad_norm: 3.1661 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7377 loss: 2.7377 2022/10/07 23:53:40 - mmengine - INFO - Epoch(train) [79][500/2119] lr: 4.0000e-02 eta: 14:37:39 time: 0.3811 data_time: 0.0202 memory: 5826 grad_norm: 3.0988 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5229 loss: 2.5229 2022/10/07 23:53:47 - mmengine - INFO - Epoch(train) [79][520/2119] lr: 4.0000e-02 eta: 14:37:33 time: 0.3533 data_time: 0.0241 memory: 5826 grad_norm: 3.1218 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6247 loss: 2.6247 2022/10/07 23:53:54 - mmengine - INFO - Epoch(train) [79][540/2119] lr: 4.0000e-02 eta: 14:37:26 time: 0.3475 data_time: 0.0275 memory: 5826 grad_norm: 3.1365 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4660 loss: 2.4660 2022/10/07 23:54:01 - mmengine - INFO - Epoch(train) [79][560/2119] lr: 4.0000e-02 eta: 14:37:19 time: 0.3777 data_time: 0.0230 memory: 5826 grad_norm: 3.1550 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4653 loss: 2.4653 2022/10/07 23:54:08 - mmengine - INFO - Epoch(train) [79][580/2119] lr: 4.0000e-02 eta: 14:37:12 time: 0.3429 data_time: 0.0232 memory: 5826 grad_norm: 3.1316 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7000 loss: 2.7000 2022/10/07 23:54:16 - mmengine - INFO - Epoch(train) [79][600/2119] lr: 4.0000e-02 eta: 14:37:06 time: 0.3939 data_time: 0.0220 memory: 5826 grad_norm: 3.1483 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8396 loss: 2.8396 2022/10/07 23:54:23 - mmengine - INFO - Epoch(train) [79][620/2119] lr: 4.0000e-02 eta: 14:37:00 time: 0.3541 data_time: 0.0223 memory: 5826 grad_norm: 3.0904 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7420 loss: 2.7420 2022/10/07 23:54:29 - mmengine - INFO - Epoch(train) [79][640/2119] lr: 4.0000e-02 eta: 14:36:52 time: 0.3076 data_time: 0.0197 memory: 5826 grad_norm: 3.1142 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7074 loss: 2.7074 2022/10/07 23:54:36 - mmengine - INFO - Epoch(train) [79][660/2119] lr: 4.0000e-02 eta: 14:36:45 time: 0.3269 data_time: 0.0224 memory: 5826 grad_norm: 3.2095 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6636 loss: 2.6636 2022/10/07 23:54:43 - mmengine - INFO - Epoch(train) [79][680/2119] lr: 4.0000e-02 eta: 14:36:38 time: 0.3574 data_time: 0.0246 memory: 5826 grad_norm: 3.1601 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6309 loss: 2.6309 2022/10/07 23:54:50 - mmengine - INFO - Epoch(train) [79][700/2119] lr: 4.0000e-02 eta: 14:36:31 time: 0.3538 data_time: 0.0295 memory: 5826 grad_norm: 3.1707 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7023 loss: 2.7023 2022/10/07 23:54:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/07 23:54:59 - mmengine - INFO - Epoch(train) [79][720/2119] lr: 4.0000e-02 eta: 14:36:26 time: 0.4413 data_time: 0.0235 memory: 5826 grad_norm: 3.1311 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6345 loss: 2.6345 2022/10/07 23:55:06 - mmengine - INFO - Epoch(train) [79][740/2119] lr: 4.0000e-02 eta: 14:36:19 time: 0.3277 data_time: 0.0237 memory: 5826 grad_norm: 3.1356 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7605 loss: 2.7605 2022/10/07 23:55:13 - mmengine - INFO - Epoch(train) [79][760/2119] lr: 4.0000e-02 eta: 14:36:12 time: 0.3681 data_time: 0.0257 memory: 5826 grad_norm: 3.1407 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8437 loss: 2.8437 2022/10/07 23:55:19 - mmengine - INFO - Epoch(train) [79][780/2119] lr: 4.0000e-02 eta: 14:36:04 time: 0.3059 data_time: 0.0249 memory: 5826 grad_norm: 3.1595 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6738 loss: 2.6738 2022/10/07 23:55:27 - mmengine - INFO - Epoch(train) [79][800/2119] lr: 4.0000e-02 eta: 14:35:58 time: 0.3904 data_time: 0.0220 memory: 5826 grad_norm: 3.1263 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7945 loss: 2.7945 2022/10/07 23:55:33 - mmengine - INFO - Epoch(train) [79][820/2119] lr: 4.0000e-02 eta: 14:35:51 time: 0.3202 data_time: 0.0275 memory: 5826 grad_norm: 3.1130 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6019 loss: 2.6019 2022/10/07 23:55:40 - mmengine - INFO - Epoch(train) [79][840/2119] lr: 4.0000e-02 eta: 14:35:44 time: 0.3518 data_time: 0.0219 memory: 5826 grad_norm: 3.1492 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9518 loss: 2.9518 2022/10/07 23:55:47 - mmengine - INFO - Epoch(train) [79][860/2119] lr: 4.0000e-02 eta: 14:35:37 time: 0.3338 data_time: 0.0248 memory: 5826 grad_norm: 3.1445 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.5683 loss: 2.5683 2022/10/07 23:55:55 - mmengine - INFO - Epoch(train) [79][880/2119] lr: 4.0000e-02 eta: 14:35:31 time: 0.3796 data_time: 0.0245 memory: 5826 grad_norm: 3.1498 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6177 loss: 2.6177 2022/10/07 23:56:01 - mmengine - INFO - Epoch(train) [79][900/2119] lr: 4.0000e-02 eta: 14:35:23 time: 0.3155 data_time: 0.0214 memory: 5826 grad_norm: 3.0832 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6468 loss: 2.6468 2022/10/07 23:56:09 - mmengine - INFO - Epoch(train) [79][920/2119] lr: 4.0000e-02 eta: 14:35:17 time: 0.3812 data_time: 0.0239 memory: 5826 grad_norm: 3.1416 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9107 loss: 2.9107 2022/10/07 23:56:15 - mmengine - INFO - Epoch(train) [79][940/2119] lr: 4.0000e-02 eta: 14:35:09 time: 0.3136 data_time: 0.0217 memory: 5826 grad_norm: 3.1035 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8787 loss: 2.8787 2022/10/07 23:56:23 - mmengine - INFO - Epoch(train) [79][960/2119] lr: 4.0000e-02 eta: 14:35:04 time: 0.4192 data_time: 0.0214 memory: 5826 grad_norm: 3.0967 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8170 loss: 2.8170 2022/10/07 23:56:29 - mmengine - INFO - Epoch(train) [79][980/2119] lr: 4.0000e-02 eta: 14:34:56 time: 0.3057 data_time: 0.0286 memory: 5826 grad_norm: 3.1456 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6134 loss: 2.6134 2022/10/07 23:56:36 - mmengine - INFO - Epoch(train) [79][1000/2119] lr: 4.0000e-02 eta: 14:34:49 time: 0.3341 data_time: 0.0214 memory: 5826 grad_norm: 3.1665 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7682 loss: 2.7682 2022/10/07 23:56:43 - mmengine - INFO - Epoch(train) [79][1020/2119] lr: 4.0000e-02 eta: 14:34:42 time: 0.3538 data_time: 0.0252 memory: 5826 grad_norm: 3.1224 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4070 loss: 2.4070 2022/10/07 23:56:51 - mmengine - INFO - Epoch(train) [79][1040/2119] lr: 4.0000e-02 eta: 14:34:36 time: 0.3787 data_time: 0.0185 memory: 5826 grad_norm: 3.1786 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7945 loss: 2.7945 2022/10/07 23:56:57 - mmengine - INFO - Epoch(train) [79][1060/2119] lr: 4.0000e-02 eta: 14:34:28 time: 0.3032 data_time: 0.0246 memory: 5826 grad_norm: 3.1220 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7511 loss: 2.7511 2022/10/07 23:57:05 - mmengine - INFO - Epoch(train) [79][1080/2119] lr: 4.0000e-02 eta: 14:34:22 time: 0.3935 data_time: 0.0230 memory: 5826 grad_norm: 3.0298 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7818 loss: 2.7818 2022/10/07 23:57:11 - mmengine - INFO - Epoch(train) [79][1100/2119] lr: 4.0000e-02 eta: 14:34:15 time: 0.3298 data_time: 0.0222 memory: 5826 grad_norm: 3.0953 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6418 loss: 2.6418 2022/10/07 23:57:20 - mmengine - INFO - Epoch(train) [79][1120/2119] lr: 4.0000e-02 eta: 14:34:09 time: 0.4144 data_time: 0.0197 memory: 5826 grad_norm: 3.0970 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8764 loss: 2.8764 2022/10/07 23:57:26 - mmengine - INFO - Epoch(train) [79][1140/2119] lr: 4.0000e-02 eta: 14:34:02 time: 0.3139 data_time: 0.0287 memory: 5826 grad_norm: 3.1428 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6491 loss: 2.6491 2022/10/07 23:57:34 - mmengine - INFO - Epoch(train) [79][1160/2119] lr: 4.0000e-02 eta: 14:33:56 time: 0.4132 data_time: 0.0250 memory: 5826 grad_norm: 3.1332 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6573 loss: 2.6573 2022/10/07 23:57:40 - mmengine - INFO - Epoch(train) [79][1180/2119] lr: 4.0000e-02 eta: 14:33:48 time: 0.2757 data_time: 0.0251 memory: 5826 grad_norm: 3.1775 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7471 loss: 2.7471 2022/10/07 23:57:47 - mmengine - INFO - Epoch(train) [79][1200/2119] lr: 4.0000e-02 eta: 14:33:41 time: 0.3504 data_time: 0.0229 memory: 5826 grad_norm: 3.1473 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7350 loss: 2.7350 2022/10/07 23:57:54 - mmengine - INFO - Epoch(train) [79][1220/2119] lr: 4.0000e-02 eta: 14:33:35 time: 0.3804 data_time: 0.0220 memory: 5826 grad_norm: 3.1217 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8189 loss: 2.8189 2022/10/07 23:58:01 - mmengine - INFO - Epoch(train) [79][1240/2119] lr: 4.0000e-02 eta: 14:33:28 time: 0.3582 data_time: 0.0238 memory: 5826 grad_norm: 3.1763 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6704 loss: 2.6704 2022/10/07 23:58:08 - mmengine - INFO - Epoch(train) [79][1260/2119] lr: 4.0000e-02 eta: 14:33:21 time: 0.3333 data_time: 0.0280 memory: 5826 grad_norm: 3.1679 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7742 loss: 2.7742 2022/10/07 23:58:16 - mmengine - INFO - Epoch(train) [79][1280/2119] lr: 4.0000e-02 eta: 14:33:15 time: 0.3925 data_time: 0.0187 memory: 5826 grad_norm: 3.0977 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5431 loss: 2.5431 2022/10/07 23:58:23 - mmengine - INFO - Epoch(train) [79][1300/2119] lr: 4.0000e-02 eta: 14:33:08 time: 0.3423 data_time: 0.0242 memory: 5826 grad_norm: 3.1629 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7642 loss: 2.7642 2022/10/07 23:58:30 - mmengine - INFO - Epoch(train) [79][1320/2119] lr: 4.0000e-02 eta: 14:33:01 time: 0.3615 data_time: 0.0267 memory: 5826 grad_norm: 3.1182 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.1778 loss: 3.1778 2022/10/07 23:58:36 - mmengine - INFO - Epoch(train) [79][1340/2119] lr: 4.0000e-02 eta: 14:32:53 time: 0.3203 data_time: 0.0266 memory: 5826 grad_norm: 3.1150 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7419 loss: 2.7419 2022/10/07 23:58:43 - mmengine - INFO - Epoch(train) [79][1360/2119] lr: 4.0000e-02 eta: 14:32:46 time: 0.3247 data_time: 0.0269 memory: 5826 grad_norm: 3.1610 top1_acc: 0.0625 top5_acc: 0.3125 loss_cls: 2.6999 loss: 2.6999 2022/10/07 23:58:50 - mmengine - INFO - Epoch(train) [79][1380/2119] lr: 4.0000e-02 eta: 14:32:40 time: 0.3765 data_time: 0.0280 memory: 5826 grad_norm: 3.1606 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.5465 loss: 2.5465 2022/10/07 23:58:58 - mmengine - INFO - Epoch(train) [79][1400/2119] lr: 4.0000e-02 eta: 14:32:33 time: 0.3562 data_time: 0.0220 memory: 5826 grad_norm: 3.1337 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7259 loss: 2.7259 2022/10/07 23:59:05 - mmengine - INFO - Epoch(train) [79][1420/2119] lr: 4.0000e-02 eta: 14:32:27 time: 0.3729 data_time: 0.0272 memory: 5826 grad_norm: 3.1180 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4914 loss: 2.4914 2022/10/07 23:59:12 - mmengine - INFO - Epoch(train) [79][1440/2119] lr: 4.0000e-02 eta: 14:32:20 time: 0.3705 data_time: 0.0246 memory: 5826 grad_norm: 3.1150 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6311 loss: 2.6311 2022/10/07 23:59:20 - mmengine - INFO - Epoch(train) [79][1460/2119] lr: 4.0000e-02 eta: 14:32:14 time: 0.3685 data_time: 0.0193 memory: 5826 grad_norm: 3.1868 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.4947 loss: 2.4947 2022/10/07 23:59:26 - mmengine - INFO - Epoch(train) [79][1480/2119] lr: 4.0000e-02 eta: 14:32:06 time: 0.3258 data_time: 0.0283 memory: 5826 grad_norm: 3.1542 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9283 loss: 2.9283 2022/10/07 23:59:33 - mmengine - INFO - Epoch(train) [79][1500/2119] lr: 4.0000e-02 eta: 14:31:59 time: 0.3454 data_time: 0.0253 memory: 5826 grad_norm: 3.1303 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7482 loss: 2.7482 2022/10/07 23:59:41 - mmengine - INFO - Epoch(train) [79][1520/2119] lr: 4.0000e-02 eta: 14:31:53 time: 0.3744 data_time: 0.0184 memory: 5826 grad_norm: 3.0810 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6645 loss: 2.6645 2022/10/07 23:59:47 - mmengine - INFO - Epoch(train) [79][1540/2119] lr: 4.0000e-02 eta: 14:31:46 time: 0.3344 data_time: 0.0330 memory: 5826 grad_norm: 3.1315 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9587 loss: 2.9587 2022/10/07 23:59:55 - mmengine - INFO - Epoch(train) [79][1560/2119] lr: 4.0000e-02 eta: 14:31:40 time: 0.3955 data_time: 0.0188 memory: 5826 grad_norm: 3.1599 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6279 loss: 2.6279 2022/10/08 00:00:05 - mmengine - INFO - Epoch(train) [79][1580/2119] lr: 4.0000e-02 eta: 14:31:36 time: 0.4945 data_time: 0.0246 memory: 5826 grad_norm: 3.1733 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5033 loss: 2.5033 2022/10/08 00:00:10 - mmengine - INFO - Epoch(train) [79][1600/2119] lr: 4.0000e-02 eta: 14:31:27 time: 0.2450 data_time: 0.0252 memory: 5826 grad_norm: 3.1816 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8973 loss: 2.8973 2022/10/08 00:00:17 - mmengine - INFO - Epoch(train) [79][1620/2119] lr: 4.0000e-02 eta: 14:31:20 time: 0.3586 data_time: 0.0330 memory: 5826 grad_norm: 3.1467 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7391 loss: 2.7391 2022/10/08 00:00:25 - mmengine - INFO - Epoch(train) [79][1640/2119] lr: 4.0000e-02 eta: 14:31:13 time: 0.3574 data_time: 0.0179 memory: 5826 grad_norm: 3.1153 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7348 loss: 2.7348 2022/10/08 00:00:32 - mmengine - INFO - Epoch(train) [79][1660/2119] lr: 4.0000e-02 eta: 14:31:07 time: 0.3581 data_time: 0.0218 memory: 5826 grad_norm: 3.0788 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.5176 loss: 2.5176 2022/10/08 00:00:39 - mmengine - INFO - Epoch(train) [79][1680/2119] lr: 4.0000e-02 eta: 14:31:00 time: 0.3626 data_time: 0.0216 memory: 5826 grad_norm: 3.1175 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7322 loss: 2.7322 2022/10/08 00:00:46 - mmengine - INFO - Epoch(train) [79][1700/2119] lr: 4.0000e-02 eta: 14:30:53 time: 0.3583 data_time: 0.0220 memory: 5826 grad_norm: 3.1217 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5747 loss: 2.5747 2022/10/08 00:00:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 00:00:52 - mmengine - INFO - Epoch(train) [79][1720/2119] lr: 4.0000e-02 eta: 14:30:46 time: 0.3044 data_time: 0.0221 memory: 5826 grad_norm: 3.0818 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5919 loss: 2.5919 2022/10/08 00:00:59 - mmengine - INFO - Epoch(train) [79][1740/2119] lr: 4.0000e-02 eta: 14:30:39 time: 0.3431 data_time: 0.0232 memory: 5826 grad_norm: 3.0177 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6207 loss: 2.6207 2022/10/08 00:01:07 - mmengine - INFO - Epoch(train) [79][1760/2119] lr: 4.0000e-02 eta: 14:30:32 time: 0.3787 data_time: 0.0162 memory: 5826 grad_norm: 3.1663 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8870 loss: 2.8870 2022/10/08 00:01:14 - mmengine - INFO - Epoch(train) [79][1780/2119] lr: 4.0000e-02 eta: 14:30:26 time: 0.3878 data_time: 0.0230 memory: 5826 grad_norm: 3.1329 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6075 loss: 2.6075 2022/10/08 00:01:21 - mmengine - INFO - Epoch(train) [79][1800/2119] lr: 4.0000e-02 eta: 14:30:19 time: 0.3479 data_time: 0.0260 memory: 5826 grad_norm: 3.1397 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4298 loss: 2.4298 2022/10/08 00:01:28 - mmengine - INFO - Epoch(train) [79][1820/2119] lr: 4.0000e-02 eta: 14:30:12 time: 0.3166 data_time: 0.0282 memory: 5826 grad_norm: 3.1000 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9446 loss: 2.9446 2022/10/08 00:01:35 - mmengine - INFO - Epoch(train) [79][1840/2119] lr: 4.0000e-02 eta: 14:30:05 time: 0.3784 data_time: 0.0212 memory: 5826 grad_norm: 3.1481 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7270 loss: 2.7270 2022/10/08 00:01:42 - mmengine - INFO - Epoch(train) [79][1860/2119] lr: 4.0000e-02 eta: 14:29:58 time: 0.3280 data_time: 0.0213 memory: 5826 grad_norm: 3.1754 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6935 loss: 2.6935 2022/10/08 00:01:49 - mmengine - INFO - Epoch(train) [79][1880/2119] lr: 4.0000e-02 eta: 14:29:52 time: 0.3697 data_time: 0.0196 memory: 5826 grad_norm: 3.1251 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9669 loss: 2.9669 2022/10/08 00:01:57 - mmengine - INFO - Epoch(train) [79][1900/2119] lr: 4.0000e-02 eta: 14:29:45 time: 0.3815 data_time: 0.0224 memory: 5826 grad_norm: 3.1407 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5958 loss: 2.5958 2022/10/08 00:02:04 - mmengine - INFO - Epoch(train) [79][1920/2119] lr: 4.0000e-02 eta: 14:29:39 time: 0.3580 data_time: 0.0226 memory: 5826 grad_norm: 3.1155 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8397 loss: 2.8397 2022/10/08 00:02:10 - mmengine - INFO - Epoch(train) [79][1940/2119] lr: 4.0000e-02 eta: 14:29:31 time: 0.3156 data_time: 0.0271 memory: 5826 grad_norm: 3.0990 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6605 loss: 2.6605 2022/10/08 00:02:17 - mmengine - INFO - Epoch(train) [79][1960/2119] lr: 4.0000e-02 eta: 14:29:24 time: 0.3463 data_time: 0.0212 memory: 5826 grad_norm: 3.0633 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.7862 loss: 2.7862 2022/10/08 00:02:24 - mmengine - INFO - Epoch(train) [79][1980/2119] lr: 4.0000e-02 eta: 14:29:17 time: 0.3428 data_time: 0.0286 memory: 5826 grad_norm: 3.1444 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8622 loss: 2.8622 2022/10/08 00:02:31 - mmengine - INFO - Epoch(train) [79][2000/2119] lr: 4.0000e-02 eta: 14:29:11 time: 0.3642 data_time: 0.0207 memory: 5826 grad_norm: 3.1600 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9089 loss: 2.9089 2022/10/08 00:02:38 - mmengine - INFO - Epoch(train) [79][2020/2119] lr: 4.0000e-02 eta: 14:29:03 time: 0.3359 data_time: 0.0206 memory: 5826 grad_norm: 3.1448 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.9289 loss: 2.9289 2022/10/08 00:02:45 - mmengine - INFO - Epoch(train) [79][2040/2119] lr: 4.0000e-02 eta: 14:28:57 time: 0.3618 data_time: 0.0224 memory: 5826 grad_norm: 3.1861 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6206 loss: 2.6206 2022/10/08 00:02:52 - mmengine - INFO - Epoch(train) [79][2060/2119] lr: 4.0000e-02 eta: 14:28:49 time: 0.3251 data_time: 0.0256 memory: 5826 grad_norm: 3.1635 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9077 loss: 2.9077 2022/10/08 00:02:59 - mmengine - INFO - Epoch(train) [79][2080/2119] lr: 4.0000e-02 eta: 14:28:43 time: 0.3529 data_time: 0.0218 memory: 5826 grad_norm: 3.1508 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4752 loss: 2.4752 2022/10/08 00:03:06 - mmengine - INFO - Epoch(train) [79][2100/2119] lr: 4.0000e-02 eta: 14:28:35 time: 0.3307 data_time: 0.0295 memory: 5826 grad_norm: 3.1578 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6483 loss: 2.6483 2022/10/08 00:03:12 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 00:03:12 - mmengine - INFO - Epoch(train) [79][2119/2119] lr: 4.0000e-02 eta: 14:28:35 time: 0.3488 data_time: 0.0224 memory: 5826 grad_norm: 3.2240 top1_acc: 0.4000 top5_acc: 0.7000 loss_cls: 2.5977 loss: 2.5977 2022/10/08 00:03:22 - mmengine - INFO - Epoch(train) [80][20/2119] lr: 4.0000e-02 eta: 14:28:19 time: 0.4909 data_time: 0.1277 memory: 5826 grad_norm: 3.0724 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7496 loss: 2.7496 2022/10/08 00:03:29 - mmengine - INFO - Epoch(train) [80][40/2119] lr: 4.0000e-02 eta: 14:28:11 time: 0.3317 data_time: 0.0221 memory: 5826 grad_norm: 3.0279 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6109 loss: 2.6109 2022/10/08 00:03:36 - mmengine - INFO - Epoch(train) [80][60/2119] lr: 4.0000e-02 eta: 14:28:05 time: 0.3716 data_time: 0.0287 memory: 5826 grad_norm: 3.1660 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6929 loss: 2.6929 2022/10/08 00:03:43 - mmengine - INFO - Epoch(train) [80][80/2119] lr: 4.0000e-02 eta: 14:27:58 time: 0.3199 data_time: 0.0237 memory: 5826 grad_norm: 3.1110 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5395 loss: 2.5395 2022/10/08 00:03:51 - mmengine - INFO - Epoch(train) [80][100/2119] lr: 4.0000e-02 eta: 14:27:51 time: 0.3930 data_time: 0.0178 memory: 5826 grad_norm: 3.1238 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6523 loss: 2.6523 2022/10/08 00:03:57 - mmengine - INFO - Epoch(train) [80][120/2119] lr: 4.0000e-02 eta: 14:27:44 time: 0.3414 data_time: 0.0264 memory: 5826 grad_norm: 3.1630 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7165 loss: 2.7165 2022/10/08 00:04:05 - mmengine - INFO - Epoch(train) [80][140/2119] lr: 4.0000e-02 eta: 14:27:38 time: 0.3773 data_time: 0.0299 memory: 5826 grad_norm: 3.1062 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7732 loss: 2.7732 2022/10/08 00:04:12 - mmengine - INFO - Epoch(train) [80][160/2119] lr: 4.0000e-02 eta: 14:27:31 time: 0.3557 data_time: 0.0230 memory: 5826 grad_norm: 3.0595 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6217 loss: 2.6217 2022/10/08 00:04:19 - mmengine - INFO - Epoch(train) [80][180/2119] lr: 4.0000e-02 eta: 14:27:24 time: 0.3237 data_time: 0.0255 memory: 5826 grad_norm: 3.1567 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.7644 loss: 2.7644 2022/10/08 00:04:26 - mmengine - INFO - Epoch(train) [80][200/2119] lr: 4.0000e-02 eta: 14:27:18 time: 0.3899 data_time: 0.0216 memory: 5826 grad_norm: 3.1172 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9240 loss: 2.9240 2022/10/08 00:04:33 - mmengine - INFO - Epoch(train) [80][220/2119] lr: 4.0000e-02 eta: 14:27:11 time: 0.3439 data_time: 0.0223 memory: 5826 grad_norm: 3.1861 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6523 loss: 2.6523 2022/10/08 00:04:42 - mmengine - INFO - Epoch(train) [80][240/2119] lr: 4.0000e-02 eta: 14:27:06 time: 0.4397 data_time: 0.0210 memory: 5826 grad_norm: 3.1512 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5539 loss: 2.5539 2022/10/08 00:04:48 - mmengine - INFO - Epoch(train) [80][260/2119] lr: 4.0000e-02 eta: 14:26:58 time: 0.2930 data_time: 0.0209 memory: 5826 grad_norm: 3.1314 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6860 loss: 2.6860 2022/10/08 00:04:55 - mmengine - INFO - Epoch(train) [80][280/2119] lr: 4.0000e-02 eta: 14:26:51 time: 0.3561 data_time: 0.0208 memory: 5826 grad_norm: 3.2015 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4861 loss: 2.4861 2022/10/08 00:05:02 - mmengine - INFO - Epoch(train) [80][300/2119] lr: 4.0000e-02 eta: 14:26:44 time: 0.3270 data_time: 0.0238 memory: 5826 grad_norm: 3.1237 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5867 loss: 2.5867 2022/10/08 00:05:08 - mmengine - INFO - Epoch(train) [80][320/2119] lr: 4.0000e-02 eta: 14:26:37 time: 0.3306 data_time: 0.0289 memory: 5826 grad_norm: 3.1419 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7575 loss: 2.7575 2022/10/08 00:05:16 - mmengine - INFO - Epoch(train) [80][340/2119] lr: 4.0000e-02 eta: 14:26:30 time: 0.3864 data_time: 0.0231 memory: 5826 grad_norm: 3.1648 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8261 loss: 2.8261 2022/10/08 00:05:23 - mmengine - INFO - Epoch(train) [80][360/2119] lr: 4.0000e-02 eta: 14:26:23 time: 0.3456 data_time: 0.0293 memory: 5826 grad_norm: 3.1085 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8950 loss: 2.8950 2022/10/08 00:05:30 - mmengine - INFO - Epoch(train) [80][380/2119] lr: 4.0000e-02 eta: 14:26:17 time: 0.3677 data_time: 0.0223 memory: 5826 grad_norm: 3.1083 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8186 loss: 2.8186 2022/10/08 00:05:38 - mmengine - INFO - Epoch(train) [80][400/2119] lr: 4.0000e-02 eta: 14:26:11 time: 0.4000 data_time: 0.0257 memory: 5826 grad_norm: 3.1074 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6931 loss: 2.6931 2022/10/08 00:05:45 - mmengine - INFO - Epoch(train) [80][420/2119] lr: 4.0000e-02 eta: 14:26:04 time: 0.3286 data_time: 0.0264 memory: 5826 grad_norm: 3.1010 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7651 loss: 2.7651 2022/10/08 00:05:53 - mmengine - INFO - Epoch(train) [80][440/2119] lr: 4.0000e-02 eta: 14:25:58 time: 0.4078 data_time: 0.0196 memory: 5826 grad_norm: 3.1601 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 3.0125 loss: 3.0125 2022/10/08 00:06:00 - mmengine - INFO - Epoch(train) [80][460/2119] lr: 4.0000e-02 eta: 14:25:51 time: 0.3713 data_time: 0.0224 memory: 5826 grad_norm: 3.1049 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5418 loss: 2.5418 2022/10/08 00:06:08 - mmengine - INFO - Epoch(train) [80][480/2119] lr: 4.0000e-02 eta: 14:25:45 time: 0.4042 data_time: 0.0226 memory: 5826 grad_norm: 3.1164 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8590 loss: 2.8590 2022/10/08 00:06:15 - mmengine - INFO - Epoch(train) [80][500/2119] lr: 4.0000e-02 eta: 14:25:38 time: 0.3306 data_time: 0.0229 memory: 5826 grad_norm: 3.2112 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8612 loss: 2.8612 2022/10/08 00:06:22 - mmengine - INFO - Epoch(train) [80][520/2119] lr: 4.0000e-02 eta: 14:25:31 time: 0.3241 data_time: 0.0219 memory: 5826 grad_norm: 3.1374 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6235 loss: 2.6235 2022/10/08 00:06:28 - mmengine - INFO - Epoch(train) [80][540/2119] lr: 4.0000e-02 eta: 14:25:24 time: 0.3433 data_time: 0.0241 memory: 5826 grad_norm: 3.2169 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8360 loss: 2.8360 2022/10/08 00:06:35 - mmengine - INFO - Epoch(train) [80][560/2119] lr: 4.0000e-02 eta: 14:25:17 time: 0.3501 data_time: 0.0270 memory: 5826 grad_norm: 3.0870 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5350 loss: 2.5350 2022/10/08 00:06:42 - mmengine - INFO - Epoch(train) [80][580/2119] lr: 4.0000e-02 eta: 14:25:10 time: 0.3432 data_time: 0.0234 memory: 5826 grad_norm: 3.1441 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.4970 loss: 2.4970 2022/10/08 00:06:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 00:06:49 - mmengine - INFO - Epoch(train) [80][600/2119] lr: 4.0000e-02 eta: 14:25:03 time: 0.3480 data_time: 0.0231 memory: 5826 grad_norm: 3.0777 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7449 loss: 2.7449 2022/10/08 00:06:56 - mmengine - INFO - Epoch(train) [80][620/2119] lr: 4.0000e-02 eta: 14:24:56 time: 0.3318 data_time: 0.0230 memory: 5826 grad_norm: 3.0548 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7731 loss: 2.7731 2022/10/08 00:07:03 - mmengine - INFO - Epoch(train) [80][640/2119] lr: 4.0000e-02 eta: 14:24:49 time: 0.3545 data_time: 0.0267 memory: 5826 grad_norm: 3.0831 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6072 loss: 2.6072 2022/10/08 00:07:10 - mmengine - INFO - Epoch(train) [80][660/2119] lr: 4.0000e-02 eta: 14:24:42 time: 0.3559 data_time: 0.0255 memory: 5826 grad_norm: 3.1462 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6075 loss: 2.6075 2022/10/08 00:07:18 - mmengine - INFO - Epoch(train) [80][680/2119] lr: 4.0000e-02 eta: 14:24:37 time: 0.4074 data_time: 0.0220 memory: 5826 grad_norm: 3.0991 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8336 loss: 2.8336 2022/10/08 00:07:25 - mmengine - INFO - Epoch(train) [80][700/2119] lr: 4.0000e-02 eta: 14:24:30 time: 0.3395 data_time: 0.0237 memory: 5826 grad_norm: 3.1080 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5881 loss: 2.5881 2022/10/08 00:07:32 - mmengine - INFO - Epoch(train) [80][720/2119] lr: 4.0000e-02 eta: 14:24:22 time: 0.3290 data_time: 0.0245 memory: 5826 grad_norm: 3.0838 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6402 loss: 2.6402 2022/10/08 00:07:39 - mmengine - INFO - Epoch(train) [80][740/2119] lr: 4.0000e-02 eta: 14:24:15 time: 0.3480 data_time: 0.0231 memory: 5826 grad_norm: 3.1703 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.9472 loss: 2.9472 2022/10/08 00:07:47 - mmengine - INFO - Epoch(train) [80][760/2119] lr: 4.0000e-02 eta: 14:24:10 time: 0.4115 data_time: 0.0241 memory: 5826 grad_norm: 3.1475 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.5345 loss: 2.5345 2022/10/08 00:07:54 - mmengine - INFO - Epoch(train) [80][780/2119] lr: 4.0000e-02 eta: 14:24:03 time: 0.3778 data_time: 0.0227 memory: 5826 grad_norm: 3.1201 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7198 loss: 2.7198 2022/10/08 00:08:02 - mmengine - INFO - Epoch(train) [80][800/2119] lr: 4.0000e-02 eta: 14:23:57 time: 0.3944 data_time: 0.0225 memory: 5826 grad_norm: 3.1287 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6555 loss: 2.6555 2022/10/08 00:08:09 - mmengine - INFO - Epoch(train) [80][820/2119] lr: 4.0000e-02 eta: 14:23:50 time: 0.3510 data_time: 0.0262 memory: 5826 grad_norm: 3.1432 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.9158 loss: 2.9158 2022/10/08 00:08:17 - mmengine - INFO - Epoch(train) [80][840/2119] lr: 4.0000e-02 eta: 14:23:44 time: 0.3827 data_time: 0.0197 memory: 5826 grad_norm: 3.1352 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6337 loss: 2.6337 2022/10/08 00:08:24 - mmengine - INFO - Epoch(train) [80][860/2119] lr: 4.0000e-02 eta: 14:23:37 time: 0.3458 data_time: 0.0207 memory: 5826 grad_norm: 3.0876 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7863 loss: 2.7863 2022/10/08 00:08:32 - mmengine - INFO - Epoch(train) [80][880/2119] lr: 4.0000e-02 eta: 14:23:31 time: 0.4042 data_time: 0.0252 memory: 5826 grad_norm: 3.0773 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6846 loss: 2.6846 2022/10/08 00:08:38 - mmengine - INFO - Epoch(train) [80][900/2119] lr: 4.0000e-02 eta: 14:23:24 time: 0.3084 data_time: 0.0277 memory: 5826 grad_norm: 3.1400 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.5596 loss: 2.5596 2022/10/08 00:08:46 - mmengine - INFO - Epoch(train) [80][920/2119] lr: 4.0000e-02 eta: 14:23:18 time: 0.4040 data_time: 0.0192 memory: 5826 grad_norm: 3.1091 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8293 loss: 2.8293 2022/10/08 00:08:53 - mmengine - INFO - Epoch(train) [80][940/2119] lr: 4.0000e-02 eta: 14:23:11 time: 0.3318 data_time: 0.0204 memory: 5826 grad_norm: 3.1336 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7513 loss: 2.7513 2022/10/08 00:09:00 - mmengine - INFO - Epoch(train) [80][960/2119] lr: 4.0000e-02 eta: 14:23:03 time: 0.3392 data_time: 0.0221 memory: 5826 grad_norm: 3.0979 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.4852 loss: 2.4852 2022/10/08 00:09:06 - mmengine - INFO - Epoch(train) [80][980/2119] lr: 4.0000e-02 eta: 14:22:56 time: 0.3152 data_time: 0.0266 memory: 5826 grad_norm: 3.1074 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6634 loss: 2.6634 2022/10/08 00:09:12 - mmengine - INFO - Epoch(train) [80][1000/2119] lr: 4.0000e-02 eta: 14:22:48 time: 0.3029 data_time: 0.0251 memory: 5826 grad_norm: 3.0864 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6569 loss: 2.6569 2022/10/08 00:09:19 - mmengine - INFO - Epoch(train) [80][1020/2119] lr: 4.0000e-02 eta: 14:22:42 time: 0.3591 data_time: 0.0246 memory: 5826 grad_norm: 3.1618 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.9737 loss: 2.9737 2022/10/08 00:09:27 - mmengine - INFO - Epoch(train) [80][1040/2119] lr: 4.0000e-02 eta: 14:22:35 time: 0.3742 data_time: 0.0249 memory: 5826 grad_norm: 3.1176 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6922 loss: 2.6922 2022/10/08 00:09:34 - mmengine - INFO - Epoch(train) [80][1060/2119] lr: 4.0000e-02 eta: 14:22:29 time: 0.3847 data_time: 0.0257 memory: 5826 grad_norm: 3.1215 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6310 loss: 2.6310 2022/10/08 00:09:40 - mmengine - INFO - Epoch(train) [80][1080/2119] lr: 4.0000e-02 eta: 14:22:21 time: 0.2798 data_time: 0.0286 memory: 5826 grad_norm: 3.1408 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8382 loss: 2.8382 2022/10/08 00:09:47 - mmengine - INFO - Epoch(train) [80][1100/2119] lr: 4.0000e-02 eta: 14:22:14 time: 0.3644 data_time: 0.0226 memory: 5826 grad_norm: 3.1516 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6932 loss: 2.6932 2022/10/08 00:09:55 - mmengine - INFO - Epoch(train) [80][1120/2119] lr: 4.0000e-02 eta: 14:22:08 time: 0.4029 data_time: 0.0240 memory: 5826 grad_norm: 3.0793 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6333 loss: 2.6333 2022/10/08 00:10:02 - mmengine - INFO - Epoch(train) [80][1140/2119] lr: 4.0000e-02 eta: 14:22:01 time: 0.3289 data_time: 0.0237 memory: 5826 grad_norm: 3.1555 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8285 loss: 2.8285 2022/10/08 00:10:10 - mmengine - INFO - Epoch(train) [80][1160/2119] lr: 4.0000e-02 eta: 14:21:55 time: 0.4024 data_time: 0.0208 memory: 5826 grad_norm: 3.1255 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6532 loss: 2.6532 2022/10/08 00:10:17 - mmengine - INFO - Epoch(train) [80][1180/2119] lr: 4.0000e-02 eta: 14:21:48 time: 0.3558 data_time: 0.0181 memory: 5826 grad_norm: 3.0711 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6633 loss: 2.6633 2022/10/08 00:10:25 - mmengine - INFO - Epoch(train) [80][1200/2119] lr: 4.0000e-02 eta: 14:21:42 time: 0.3849 data_time: 0.0238 memory: 5826 grad_norm: 3.0766 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6176 loss: 2.6176 2022/10/08 00:10:31 - mmengine - INFO - Epoch(train) [80][1220/2119] lr: 4.0000e-02 eta: 14:21:35 time: 0.3255 data_time: 0.0257 memory: 5826 grad_norm: 3.1591 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6290 loss: 2.6290 2022/10/08 00:10:38 - mmengine - INFO - Epoch(train) [80][1240/2119] lr: 4.0000e-02 eta: 14:21:28 time: 0.3289 data_time: 0.0263 memory: 5826 grad_norm: 3.0474 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.6607 loss: 2.6607 2022/10/08 00:10:45 - mmengine - INFO - Epoch(train) [80][1260/2119] lr: 4.0000e-02 eta: 14:21:21 time: 0.3566 data_time: 0.0158 memory: 5826 grad_norm: 3.1210 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8076 loss: 2.8076 2022/10/08 00:10:54 - mmengine - INFO - Epoch(train) [80][1280/2119] lr: 4.0000e-02 eta: 14:21:16 time: 0.4424 data_time: 0.0203 memory: 5826 grad_norm: 3.1045 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8346 loss: 2.8346 2022/10/08 00:11:00 - mmengine - INFO - Epoch(train) [80][1300/2119] lr: 4.0000e-02 eta: 14:21:08 time: 0.2937 data_time: 0.0238 memory: 5826 grad_norm: 3.1187 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6665 loss: 2.6665 2022/10/08 00:11:08 - mmengine - INFO - Epoch(train) [80][1320/2119] lr: 4.0000e-02 eta: 14:21:02 time: 0.4086 data_time: 0.0206 memory: 5826 grad_norm: 3.2125 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9781 loss: 2.9781 2022/10/08 00:11:14 - mmengine - INFO - Epoch(train) [80][1340/2119] lr: 4.0000e-02 eta: 14:20:54 time: 0.3128 data_time: 0.0234 memory: 5826 grad_norm: 3.1053 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6764 loss: 2.6764 2022/10/08 00:11:22 - mmengine - INFO - Epoch(train) [80][1360/2119] lr: 4.0000e-02 eta: 14:20:48 time: 0.3700 data_time: 0.0233 memory: 5826 grad_norm: 3.1389 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7094 loss: 2.7094 2022/10/08 00:11:29 - mmengine - INFO - Epoch(train) [80][1380/2119] lr: 4.0000e-02 eta: 14:20:41 time: 0.3510 data_time: 0.0263 memory: 5826 grad_norm: 3.1674 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6564 loss: 2.6564 2022/10/08 00:11:36 - mmengine - INFO - Epoch(train) [80][1400/2119] lr: 4.0000e-02 eta: 14:20:34 time: 0.3572 data_time: 0.0213 memory: 5826 grad_norm: 3.1038 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7387 loss: 2.7387 2022/10/08 00:11:43 - mmengine - INFO - Epoch(train) [80][1420/2119] lr: 4.0000e-02 eta: 14:20:27 time: 0.3425 data_time: 0.0230 memory: 5826 grad_norm: 3.1807 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9878 loss: 2.9878 2022/10/08 00:11:50 - mmengine - INFO - Epoch(train) [80][1440/2119] lr: 4.0000e-02 eta: 14:20:21 time: 0.3687 data_time: 0.0174 memory: 5826 grad_norm: 3.1178 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8413 loss: 2.8413 2022/10/08 00:11:57 - mmengine - INFO - Epoch(train) [80][1460/2119] lr: 4.0000e-02 eta: 14:20:14 time: 0.3365 data_time: 0.0277 memory: 5826 grad_norm: 3.1157 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6841 loss: 2.6841 2022/10/08 00:12:05 - mmengine - INFO - Epoch(train) [80][1480/2119] lr: 4.0000e-02 eta: 14:20:08 time: 0.4227 data_time: 0.0179 memory: 5826 grad_norm: 3.1505 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5827 loss: 2.5827 2022/10/08 00:12:11 - mmengine - INFO - Epoch(train) [80][1500/2119] lr: 4.0000e-02 eta: 14:20:00 time: 0.3081 data_time: 0.0232 memory: 5826 grad_norm: 3.0923 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6959 loss: 2.6959 2022/10/08 00:12:19 - mmengine - INFO - Epoch(train) [80][1520/2119] lr: 4.0000e-02 eta: 14:19:54 time: 0.3856 data_time: 0.0286 memory: 5826 grad_norm: 3.1422 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7315 loss: 2.7315 2022/10/08 00:12:26 - mmengine - INFO - Epoch(train) [80][1540/2119] lr: 4.0000e-02 eta: 14:19:47 time: 0.3241 data_time: 0.0205 memory: 5826 grad_norm: 3.0972 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0808 loss: 3.0808 2022/10/08 00:12:33 - mmengine - INFO - Epoch(train) [80][1560/2119] lr: 4.0000e-02 eta: 14:19:40 time: 0.3766 data_time: 0.0229 memory: 5826 grad_norm: 3.0778 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7749 loss: 2.7749 2022/10/08 00:12:39 - mmengine - INFO - Epoch(train) [80][1580/2119] lr: 4.0000e-02 eta: 14:19:33 time: 0.2992 data_time: 0.0222 memory: 5826 grad_norm: 3.0966 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6329 loss: 2.6329 2022/10/08 00:12:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 00:12:46 - mmengine - INFO - Epoch(train) [80][1600/2119] lr: 4.0000e-02 eta: 14:19:26 time: 0.3511 data_time: 0.0238 memory: 5826 grad_norm: 3.1079 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5825 loss: 2.5825 2022/10/08 00:12:54 - mmengine - INFO - Epoch(train) [80][1620/2119] lr: 4.0000e-02 eta: 14:19:20 time: 0.3827 data_time: 0.0195 memory: 5826 grad_norm: 3.0980 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8970 loss: 2.8970 2022/10/08 00:13:00 - mmengine - INFO - Epoch(train) [80][1640/2119] lr: 4.0000e-02 eta: 14:19:12 time: 0.3066 data_time: 0.0216 memory: 5826 grad_norm: 3.1537 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6331 loss: 2.6331 2022/10/08 00:13:07 - mmengine - INFO - Epoch(train) [80][1660/2119] lr: 4.0000e-02 eta: 14:19:05 time: 0.3569 data_time: 0.0280 memory: 5826 grad_norm: 3.1506 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8305 loss: 2.8305 2022/10/08 00:13:14 - mmengine - INFO - Epoch(train) [80][1680/2119] lr: 4.0000e-02 eta: 14:18:58 time: 0.3536 data_time: 0.0198 memory: 5826 grad_norm: 3.1353 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8934 loss: 2.8934 2022/10/08 00:13:21 - mmengine - INFO - Epoch(train) [80][1700/2119] lr: 4.0000e-02 eta: 14:18:51 time: 0.3457 data_time: 0.0203 memory: 5826 grad_norm: 3.0855 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4869 loss: 2.4869 2022/10/08 00:13:28 - mmengine - INFO - Epoch(train) [80][1720/2119] lr: 4.0000e-02 eta: 14:18:45 time: 0.3557 data_time: 0.0268 memory: 5826 grad_norm: 3.1329 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6125 loss: 2.6125 2022/10/08 00:13:35 - mmengine - INFO - Epoch(train) [80][1740/2119] lr: 4.0000e-02 eta: 14:18:37 time: 0.3180 data_time: 0.0161 memory: 5826 grad_norm: 3.1153 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6565 loss: 2.6565 2022/10/08 00:13:42 - mmengine - INFO - Epoch(train) [80][1760/2119] lr: 4.0000e-02 eta: 14:18:31 time: 0.3606 data_time: 0.0213 memory: 5826 grad_norm: 3.1341 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7644 loss: 2.7644 2022/10/08 00:13:49 - mmengine - INFO - Epoch(train) [80][1780/2119] lr: 4.0000e-02 eta: 14:18:24 time: 0.3486 data_time: 0.0294 memory: 5826 grad_norm: 3.1906 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4940 loss: 2.4940 2022/10/08 00:13:57 - mmengine - INFO - Epoch(train) [80][1800/2119] lr: 4.0000e-02 eta: 14:18:18 time: 0.4194 data_time: 0.0196 memory: 5826 grad_norm: 3.1508 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7076 loss: 2.7076 2022/10/08 00:14:04 - mmengine - INFO - Epoch(train) [80][1820/2119] lr: 4.0000e-02 eta: 14:18:11 time: 0.3200 data_time: 0.0158 memory: 5826 grad_norm: 3.1016 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8148 loss: 2.8148 2022/10/08 00:14:11 - mmengine - INFO - Epoch(train) [80][1840/2119] lr: 4.0000e-02 eta: 14:18:04 time: 0.3892 data_time: 0.0214 memory: 5826 grad_norm: 3.0741 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9410 loss: 2.9410 2022/10/08 00:14:18 - mmengine - INFO - Epoch(train) [80][1860/2119] lr: 4.0000e-02 eta: 14:17:57 time: 0.3041 data_time: 0.0303 memory: 5826 grad_norm: 3.1278 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6371 loss: 2.6371 2022/10/08 00:14:24 - mmengine - INFO - Epoch(train) [80][1880/2119] lr: 4.0000e-02 eta: 14:17:49 time: 0.3243 data_time: 0.0230 memory: 5826 grad_norm: 3.0822 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9704 loss: 2.9704 2022/10/08 00:14:32 - mmengine - INFO - Epoch(train) [80][1900/2119] lr: 4.0000e-02 eta: 14:17:43 time: 0.3872 data_time: 0.0263 memory: 5826 grad_norm: 3.1368 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9549 loss: 2.9549 2022/10/08 00:14:39 - mmengine - INFO - Epoch(train) [80][1920/2119] lr: 4.0000e-02 eta: 14:17:37 time: 0.3712 data_time: 0.0246 memory: 5826 grad_norm: 3.1159 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5168 loss: 2.5168 2022/10/08 00:14:46 - mmengine - INFO - Epoch(train) [80][1940/2119] lr: 4.0000e-02 eta: 14:17:30 time: 0.3507 data_time: 0.0229 memory: 5826 grad_norm: 3.0675 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4191 loss: 2.4191 2022/10/08 00:14:55 - mmengine - INFO - Epoch(train) [80][1960/2119] lr: 4.0000e-02 eta: 14:17:24 time: 0.4180 data_time: 0.0195 memory: 5826 grad_norm: 3.1374 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4951 loss: 2.4951 2022/10/08 00:15:02 - mmengine - INFO - Epoch(train) [80][1980/2119] lr: 4.0000e-02 eta: 14:17:17 time: 0.3574 data_time: 0.0222 memory: 5826 grad_norm: 3.1624 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.8273 loss: 2.8273 2022/10/08 00:15:10 - mmengine - INFO - Epoch(train) [80][2000/2119] lr: 4.0000e-02 eta: 14:17:11 time: 0.3982 data_time: 0.0251 memory: 5826 grad_norm: 3.1084 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6338 loss: 2.6338 2022/10/08 00:15:16 - mmengine - INFO - Epoch(train) [80][2020/2119] lr: 4.0000e-02 eta: 14:17:04 time: 0.3196 data_time: 0.0230 memory: 5826 grad_norm: 3.0837 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6653 loss: 2.6653 2022/10/08 00:15:24 - mmengine - INFO - Epoch(train) [80][2040/2119] lr: 4.0000e-02 eta: 14:16:58 time: 0.3837 data_time: 0.0172 memory: 5826 grad_norm: 3.0672 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.5095 loss: 2.5095 2022/10/08 00:15:31 - mmengine - INFO - Epoch(train) [80][2060/2119] lr: 4.0000e-02 eta: 14:16:51 time: 0.3411 data_time: 0.0207 memory: 5826 grad_norm: 3.0576 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6023 loss: 2.6023 2022/10/08 00:15:37 - mmengine - INFO - Epoch(train) [80][2080/2119] lr: 4.0000e-02 eta: 14:16:44 time: 0.3378 data_time: 0.0211 memory: 5826 grad_norm: 3.1273 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5166 loss: 2.5166 2022/10/08 00:15:44 - mmengine - INFO - Epoch(train) [80][2100/2119] lr: 4.0000e-02 eta: 14:16:37 time: 0.3457 data_time: 0.0255 memory: 5826 grad_norm: 3.1892 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8971 loss: 2.8971 2022/10/08 00:15:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 00:15:51 - mmengine - INFO - Epoch(train) [80][2119/2119] lr: 4.0000e-02 eta: 14:16:37 time: 0.3356 data_time: 0.0166 memory: 5826 grad_norm: 3.2453 top1_acc: 0.3000 top5_acc: 0.5000 loss_cls: 2.6121 loss: 2.6121 2022/10/08 00:15:51 - mmengine - INFO - Saving checkpoint at 80 epochs 2022/10/08 00:16:00 - mmengine - INFO - Epoch(val) [80][20/137] eta: 0:00:48 time: 0.4122 data_time: 0.3455 memory: 1241 2022/10/08 00:16:06 - mmengine - INFO - Epoch(val) [80][40/137] eta: 0:00:28 time: 0.2986 data_time: 0.2316 memory: 1241 2022/10/08 00:16:14 - mmengine - INFO - Epoch(val) [80][60/137] eta: 0:00:28 time: 0.3742 data_time: 0.3085 memory: 1241 2022/10/08 00:16:19 - mmengine - INFO - Epoch(val) [80][80/137] eta: 0:00:14 time: 0.2474 data_time: 0.1812 memory: 1241 2022/10/08 00:16:27 - mmengine - INFO - Epoch(val) [80][100/137] eta: 0:00:15 time: 0.4096 data_time: 0.3425 memory: 1241 2022/10/08 00:16:32 - mmengine - INFO - Epoch(val) [80][120/137] eta: 0:00:04 time: 0.2644 data_time: 0.1981 memory: 1241 2022/10/08 00:16:42 - mmengine - INFO - Epoch(val) [80][137/137] acc/top1: 0.4297 acc/top5: 0.6748 acc/mean1: 0.4296 2022/10/08 00:16:52 - mmengine - INFO - Epoch(train) [81][20/2119] lr: 4.0000e-02 eta: 14:16:20 time: 0.4699 data_time: 0.1298 memory: 5826 grad_norm: 3.0733 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9243 loss: 2.9243 2022/10/08 00:16:59 - mmengine - INFO - Epoch(train) [81][40/2119] lr: 4.0000e-02 eta: 14:16:13 time: 0.3481 data_time: 0.0319 memory: 5826 grad_norm: 3.1013 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6416 loss: 2.6416 2022/10/08 00:17:07 - mmengine - INFO - Epoch(train) [81][60/2119] lr: 4.0000e-02 eta: 14:16:07 time: 0.4057 data_time: 0.0178 memory: 5826 grad_norm: 3.1330 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6252 loss: 2.6252 2022/10/08 00:17:13 - mmengine - INFO - Epoch(train) [81][80/2119] lr: 4.0000e-02 eta: 14:15:59 time: 0.2884 data_time: 0.0233 memory: 5826 grad_norm: 3.0977 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6029 loss: 2.6029 2022/10/08 00:17:20 - mmengine - INFO - Epoch(train) [81][100/2119] lr: 4.0000e-02 eta: 14:15:52 time: 0.3631 data_time: 0.0201 memory: 5826 grad_norm: 3.1238 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5827 loss: 2.5827 2022/10/08 00:17:27 - mmengine - INFO - Epoch(train) [81][120/2119] lr: 4.0000e-02 eta: 14:15:45 time: 0.3432 data_time: 0.0226 memory: 5826 grad_norm: 3.1858 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7746 loss: 2.7746 2022/10/08 00:17:35 - mmengine - INFO - Epoch(train) [81][140/2119] lr: 4.0000e-02 eta: 14:15:39 time: 0.3792 data_time: 0.0179 memory: 5826 grad_norm: 3.0927 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5942 loss: 2.5942 2022/10/08 00:17:41 - mmengine - INFO - Epoch(train) [81][160/2119] lr: 4.0000e-02 eta: 14:15:32 time: 0.3438 data_time: 0.0279 memory: 5826 grad_norm: 3.1404 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8284 loss: 2.8284 2022/10/08 00:17:49 - mmengine - INFO - Epoch(train) [81][180/2119] lr: 4.0000e-02 eta: 14:15:26 time: 0.3742 data_time: 0.0212 memory: 5826 grad_norm: 3.1181 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7966 loss: 2.7966 2022/10/08 00:17:55 - mmengine - INFO - Epoch(train) [81][200/2119] lr: 4.0000e-02 eta: 14:15:18 time: 0.3158 data_time: 0.0213 memory: 5826 grad_norm: 3.0989 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6954 loss: 2.6954 2022/10/08 00:18:03 - mmengine - INFO - Epoch(train) [81][220/2119] lr: 4.0000e-02 eta: 14:15:12 time: 0.3862 data_time: 0.0283 memory: 5826 grad_norm: 3.1779 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7886 loss: 2.7886 2022/10/08 00:18:09 - mmengine - INFO - Epoch(train) [81][240/2119] lr: 4.0000e-02 eta: 14:15:04 time: 0.3114 data_time: 0.0241 memory: 5826 grad_norm: 3.0275 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7564 loss: 2.7564 2022/10/08 00:18:17 - mmengine - INFO - Epoch(train) [81][260/2119] lr: 4.0000e-02 eta: 14:14:58 time: 0.4099 data_time: 0.0248 memory: 5826 grad_norm: 3.1706 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7200 loss: 2.7200 2022/10/08 00:18:24 - mmengine - INFO - Epoch(train) [81][280/2119] lr: 4.0000e-02 eta: 14:14:51 time: 0.3096 data_time: 0.0233 memory: 5826 grad_norm: 3.1645 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8514 loss: 2.8514 2022/10/08 00:18:31 - mmengine - INFO - Epoch(train) [81][300/2119] lr: 4.0000e-02 eta: 14:14:44 time: 0.3762 data_time: 0.0269 memory: 5826 grad_norm: 3.1117 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5656 loss: 2.5656 2022/10/08 00:18:39 - mmengine - INFO - Epoch(train) [81][320/2119] lr: 4.0000e-02 eta: 14:14:38 time: 0.3723 data_time: 0.0254 memory: 5826 grad_norm: 3.1449 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.4759 loss: 2.4759 2022/10/08 00:18:45 - mmengine - INFO - Epoch(train) [81][340/2119] lr: 4.0000e-02 eta: 14:14:31 time: 0.3248 data_time: 0.0258 memory: 5826 grad_norm: 3.0564 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6047 loss: 2.6047 2022/10/08 00:18:52 - mmengine - INFO - Epoch(train) [81][360/2119] lr: 4.0000e-02 eta: 14:14:23 time: 0.3203 data_time: 0.0241 memory: 5826 grad_norm: 3.0821 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3785 loss: 2.3785 2022/10/08 00:18:59 - mmengine - INFO - Epoch(train) [81][380/2119] lr: 4.0000e-02 eta: 14:14:17 time: 0.3730 data_time: 0.0244 memory: 5826 grad_norm: 3.1824 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6097 loss: 2.6097 2022/10/08 00:19:06 - mmengine - INFO - Epoch(train) [81][400/2119] lr: 4.0000e-02 eta: 14:14:10 time: 0.3330 data_time: 0.0194 memory: 5826 grad_norm: 3.1324 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5672 loss: 2.5672 2022/10/08 00:19:13 - mmengine - INFO - Epoch(train) [81][420/2119] lr: 4.0000e-02 eta: 14:14:03 time: 0.3740 data_time: 0.0273 memory: 5826 grad_norm: 3.1537 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4881 loss: 2.4881 2022/10/08 00:19:20 - mmengine - INFO - Epoch(train) [81][440/2119] lr: 4.0000e-02 eta: 14:13:56 time: 0.3233 data_time: 0.0272 memory: 5826 grad_norm: 3.1485 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9865 loss: 2.9865 2022/10/08 00:19:27 - mmengine - INFO - Epoch(train) [81][460/2119] lr: 4.0000e-02 eta: 14:13:49 time: 0.3548 data_time: 0.0237 memory: 5826 grad_norm: 3.1275 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6769 loss: 2.6769 2022/10/08 00:19:34 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 00:19:34 - mmengine - INFO - Epoch(train) [81][480/2119] lr: 4.0000e-02 eta: 14:13:42 time: 0.3546 data_time: 0.0313 memory: 5826 grad_norm: 3.1138 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7356 loss: 2.7356 2022/10/08 00:19:41 - mmengine - INFO - Epoch(train) [81][500/2119] lr: 4.0000e-02 eta: 14:13:36 time: 0.3686 data_time: 0.0232 memory: 5826 grad_norm: 3.0779 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8582 loss: 2.8582 2022/10/08 00:19:48 - mmengine - INFO - Epoch(train) [81][520/2119] lr: 4.0000e-02 eta: 14:13:28 time: 0.3245 data_time: 0.0293 memory: 5826 grad_norm: 3.0921 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5478 loss: 2.5478 2022/10/08 00:19:55 - mmengine - INFO - Epoch(train) [81][540/2119] lr: 4.0000e-02 eta: 14:13:22 time: 0.3465 data_time: 0.0200 memory: 5826 grad_norm: 3.1322 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7107 loss: 2.7107 2022/10/08 00:20:02 - mmengine - INFO - Epoch(train) [81][560/2119] lr: 4.0000e-02 eta: 14:13:15 time: 0.3675 data_time: 0.0256 memory: 5826 grad_norm: 3.1732 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6564 loss: 2.6564 2022/10/08 00:20:10 - mmengine - INFO - Epoch(train) [81][580/2119] lr: 4.0000e-02 eta: 14:13:09 time: 0.3829 data_time: 0.0263 memory: 5826 grad_norm: 3.1430 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7095 loss: 2.7095 2022/10/08 00:20:16 - mmengine - INFO - Epoch(train) [81][600/2119] lr: 4.0000e-02 eta: 14:13:01 time: 0.3213 data_time: 0.0264 memory: 5826 grad_norm: 3.0903 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8551 loss: 2.8551 2022/10/08 00:20:23 - mmengine - INFO - Epoch(train) [81][620/2119] lr: 4.0000e-02 eta: 14:12:55 time: 0.3539 data_time: 0.0215 memory: 5826 grad_norm: 3.1750 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8202 loss: 2.8202 2022/10/08 00:20:30 - mmengine - INFO - Epoch(train) [81][640/2119] lr: 4.0000e-02 eta: 14:12:47 time: 0.3416 data_time: 0.0241 memory: 5826 grad_norm: 3.1262 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8385 loss: 2.8385 2022/10/08 00:20:38 - mmengine - INFO - Epoch(train) [81][660/2119] lr: 4.0000e-02 eta: 14:12:41 time: 0.3739 data_time: 0.0210 memory: 5826 grad_norm: 3.1033 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7352 loss: 2.7352 2022/10/08 00:20:44 - mmengine - INFO - Epoch(train) [81][680/2119] lr: 4.0000e-02 eta: 14:12:34 time: 0.3199 data_time: 0.0236 memory: 5826 grad_norm: 3.0909 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6340 loss: 2.6340 2022/10/08 00:20:51 - mmengine - INFO - Epoch(train) [81][700/2119] lr: 4.0000e-02 eta: 14:12:27 time: 0.3408 data_time: 0.0223 memory: 5826 grad_norm: 3.1586 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7063 loss: 2.7063 2022/10/08 00:20:57 - mmengine - INFO - Epoch(train) [81][720/2119] lr: 4.0000e-02 eta: 14:12:19 time: 0.3282 data_time: 0.0283 memory: 5826 grad_norm: 3.2107 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8728 loss: 2.8728 2022/10/08 00:21:05 - mmengine - INFO - Epoch(train) [81][740/2119] lr: 4.0000e-02 eta: 14:12:13 time: 0.3692 data_time: 0.0248 memory: 5826 grad_norm: 3.0618 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7887 loss: 2.7887 2022/10/08 00:21:11 - mmengine - INFO - Epoch(train) [81][760/2119] lr: 4.0000e-02 eta: 14:12:06 time: 0.3277 data_time: 0.0253 memory: 5826 grad_norm: 3.1015 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7803 loss: 2.7803 2022/10/08 00:21:19 - mmengine - INFO - Epoch(train) [81][780/2119] lr: 4.0000e-02 eta: 14:11:59 time: 0.3732 data_time: 0.0221 memory: 5826 grad_norm: 3.1637 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7469 loss: 2.7469 2022/10/08 00:21:26 - mmengine - INFO - Epoch(train) [81][800/2119] lr: 4.0000e-02 eta: 14:11:52 time: 0.3450 data_time: 0.0208 memory: 5826 grad_norm: 3.0973 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7561 loss: 2.7561 2022/10/08 00:21:33 - mmengine - INFO - Epoch(train) [81][820/2119] lr: 4.0000e-02 eta: 14:11:46 time: 0.3625 data_time: 0.0292 memory: 5826 grad_norm: 3.0845 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9217 loss: 2.9217 2022/10/08 00:21:40 - mmengine - INFO - Epoch(train) [81][840/2119] lr: 4.0000e-02 eta: 14:11:39 time: 0.3653 data_time: 0.0221 memory: 5826 grad_norm: 3.1234 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9883 loss: 2.9883 2022/10/08 00:21:48 - mmengine - INFO - Epoch(train) [81][860/2119] lr: 4.0000e-02 eta: 14:11:32 time: 0.3720 data_time: 0.0238 memory: 5826 grad_norm: 3.1007 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.7352 loss: 2.7352 2022/10/08 00:21:54 - mmengine - INFO - Epoch(train) [81][880/2119] lr: 4.0000e-02 eta: 14:11:25 time: 0.3371 data_time: 0.0242 memory: 5826 grad_norm: 3.1466 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9002 loss: 2.9002 2022/10/08 00:22:02 - mmengine - INFO - Epoch(train) [81][900/2119] lr: 4.0000e-02 eta: 14:11:19 time: 0.3634 data_time: 0.0243 memory: 5826 grad_norm: 3.1241 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9510 loss: 2.9510 2022/10/08 00:22:09 - mmengine - INFO - Epoch(train) [81][920/2119] lr: 4.0000e-02 eta: 14:11:12 time: 0.3441 data_time: 0.0178 memory: 5826 grad_norm: 3.1393 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8314 loss: 2.8314 2022/10/08 00:22:16 - mmengine - INFO - Epoch(train) [81][940/2119] lr: 4.0000e-02 eta: 14:11:05 time: 0.3487 data_time: 0.0254 memory: 5826 grad_norm: 3.1054 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7822 loss: 2.7822 2022/10/08 00:22:22 - mmengine - INFO - Epoch(train) [81][960/2119] lr: 4.0000e-02 eta: 14:10:58 time: 0.3333 data_time: 0.0246 memory: 5826 grad_norm: 3.0800 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7311 loss: 2.7311 2022/10/08 00:22:30 - mmengine - INFO - Epoch(train) [81][980/2119] lr: 4.0000e-02 eta: 14:10:51 time: 0.3724 data_time: 0.0199 memory: 5826 grad_norm: 3.0864 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8273 loss: 2.8273 2022/10/08 00:22:36 - mmengine - INFO - Epoch(train) [81][1000/2119] lr: 4.0000e-02 eta: 14:10:44 time: 0.3084 data_time: 0.0229 memory: 5826 grad_norm: 3.1243 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8790 loss: 2.8790 2022/10/08 00:22:43 - mmengine - INFO - Epoch(train) [81][1020/2119] lr: 4.0000e-02 eta: 14:10:37 time: 0.3718 data_time: 0.0234 memory: 5826 grad_norm: 3.0755 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8716 loss: 2.8716 2022/10/08 00:22:50 - mmengine - INFO - Epoch(train) [81][1040/2119] lr: 4.0000e-02 eta: 14:10:30 time: 0.3308 data_time: 0.0194 memory: 5826 grad_norm: 3.1284 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6393 loss: 2.6393 2022/10/08 00:22:58 - mmengine - INFO - Epoch(train) [81][1060/2119] lr: 4.0000e-02 eta: 14:10:24 time: 0.3879 data_time: 0.0209 memory: 5826 grad_norm: 3.1876 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5554 loss: 2.5554 2022/10/08 00:23:05 - mmengine - INFO - Epoch(train) [81][1080/2119] lr: 4.0000e-02 eta: 14:10:17 time: 0.3431 data_time: 0.0204 memory: 5826 grad_norm: 3.1257 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7371 loss: 2.7371 2022/10/08 00:23:11 - mmengine - INFO - Epoch(train) [81][1100/2119] lr: 4.0000e-02 eta: 14:10:10 time: 0.3410 data_time: 0.0343 memory: 5826 grad_norm: 3.1435 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7678 loss: 2.7678 2022/10/08 00:23:18 - mmengine - INFO - Epoch(train) [81][1120/2119] lr: 4.0000e-02 eta: 14:10:02 time: 0.3309 data_time: 0.0251 memory: 5826 grad_norm: 3.1087 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6918 loss: 2.6918 2022/10/08 00:23:25 - mmengine - INFO - Epoch(train) [81][1140/2119] lr: 4.0000e-02 eta: 14:09:56 time: 0.3592 data_time: 0.0225 memory: 5826 grad_norm: 3.1477 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7163 loss: 2.7163 2022/10/08 00:23:33 - mmengine - INFO - Epoch(train) [81][1160/2119] lr: 4.0000e-02 eta: 14:09:50 time: 0.3900 data_time: 0.0239 memory: 5826 grad_norm: 3.1672 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.1227 loss: 3.1227 2022/10/08 00:23:40 - mmengine - INFO - Epoch(train) [81][1180/2119] lr: 4.0000e-02 eta: 14:09:43 time: 0.3570 data_time: 0.0261 memory: 5826 grad_norm: 3.0784 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5570 loss: 2.5570 2022/10/08 00:23:47 - mmengine - INFO - Epoch(train) [81][1200/2119] lr: 4.0000e-02 eta: 14:09:36 time: 0.3529 data_time: 0.0224 memory: 5826 grad_norm: 3.1156 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.4793 loss: 2.4793 2022/10/08 00:23:54 - mmengine - INFO - Epoch(train) [81][1220/2119] lr: 4.0000e-02 eta: 14:09:29 time: 0.3496 data_time: 0.0265 memory: 5826 grad_norm: 3.1532 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7528 loss: 2.7528 2022/10/08 00:24:01 - mmengine - INFO - Epoch(train) [81][1240/2119] lr: 4.0000e-02 eta: 14:09:22 time: 0.3230 data_time: 0.0254 memory: 5826 grad_norm: 3.1661 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.9389 loss: 2.9389 2022/10/08 00:24:08 - mmengine - INFO - Epoch(train) [81][1260/2119] lr: 4.0000e-02 eta: 14:09:16 time: 0.3919 data_time: 0.0424 memory: 5826 grad_norm: 3.1249 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.6764 loss: 2.6764 2022/10/08 00:24:15 - mmengine - INFO - Epoch(train) [81][1280/2119] lr: 4.0000e-02 eta: 14:09:09 time: 0.3354 data_time: 0.0227 memory: 5826 grad_norm: 3.1011 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.3876 loss: 2.3876 2022/10/08 00:24:23 - mmengine - INFO - Epoch(train) [81][1300/2119] lr: 4.0000e-02 eta: 14:09:03 time: 0.4094 data_time: 0.0225 memory: 5826 grad_norm: 3.1327 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6669 loss: 2.6669 2022/10/08 00:24:31 - mmengine - INFO - Epoch(train) [81][1320/2119] lr: 4.0000e-02 eta: 14:08:56 time: 0.3563 data_time: 0.0276 memory: 5826 grad_norm: 3.1648 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.7104 loss: 2.7104 2022/10/08 00:24:38 - mmengine - INFO - Epoch(train) [81][1340/2119] lr: 4.0000e-02 eta: 14:08:50 time: 0.3794 data_time: 0.0208 memory: 5826 grad_norm: 3.1448 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5767 loss: 2.5767 2022/10/08 00:24:44 - mmengine - INFO - Epoch(train) [81][1360/2119] lr: 4.0000e-02 eta: 14:08:42 time: 0.3129 data_time: 0.0184 memory: 5826 grad_norm: 3.1439 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8197 loss: 2.8197 2022/10/08 00:24:52 - mmengine - INFO - Epoch(train) [81][1380/2119] lr: 4.0000e-02 eta: 14:08:36 time: 0.3983 data_time: 0.0241 memory: 5826 grad_norm: 3.1562 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8559 loss: 2.8559 2022/10/08 00:25:00 - mmengine - INFO - Epoch(train) [81][1400/2119] lr: 4.0000e-02 eta: 14:08:30 time: 0.3691 data_time: 0.0238 memory: 5826 grad_norm: 3.0831 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5904 loss: 2.5904 2022/10/08 00:25:08 - mmengine - INFO - Epoch(train) [81][1420/2119] lr: 4.0000e-02 eta: 14:08:24 time: 0.4103 data_time: 0.0247 memory: 5826 grad_norm: 3.1324 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8229 loss: 2.8229 2022/10/08 00:25:14 - mmengine - INFO - Epoch(train) [81][1440/2119] lr: 4.0000e-02 eta: 14:08:16 time: 0.3032 data_time: 0.0228 memory: 5826 grad_norm: 3.1294 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7509 loss: 2.7509 2022/10/08 00:25:22 - mmengine - INFO - Epoch(train) [81][1460/2119] lr: 4.0000e-02 eta: 14:08:10 time: 0.3836 data_time: 0.0262 memory: 5826 grad_norm: 3.1226 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.7342 loss: 2.7342 2022/10/08 00:25:28 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 00:25:28 - mmengine - INFO - Epoch(train) [81][1480/2119] lr: 4.0000e-02 eta: 14:08:02 time: 0.3086 data_time: 0.0243 memory: 5826 grad_norm: 3.1003 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7127 loss: 2.7127 2022/10/08 00:25:35 - mmengine - INFO - Epoch(train) [81][1500/2119] lr: 4.0000e-02 eta: 14:07:55 time: 0.3451 data_time: 0.0242 memory: 5826 grad_norm: 3.1773 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6031 loss: 2.6031 2022/10/08 00:25:42 - mmengine - INFO - Epoch(train) [81][1520/2119] lr: 4.0000e-02 eta: 14:07:48 time: 0.3412 data_time: 0.0215 memory: 5826 grad_norm: 3.1024 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8289 loss: 2.8289 2022/10/08 00:25:49 - mmengine - INFO - Epoch(train) [81][1540/2119] lr: 4.0000e-02 eta: 14:07:42 time: 0.3798 data_time: 0.0234 memory: 5826 grad_norm: 3.0988 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.5479 loss: 2.5479 2022/10/08 00:25:55 - mmengine - INFO - Epoch(train) [81][1560/2119] lr: 4.0000e-02 eta: 14:07:34 time: 0.3136 data_time: 0.0244 memory: 5826 grad_norm: 3.1713 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8521 loss: 2.8521 2022/10/08 00:26:03 - mmengine - INFO - Epoch(train) [81][1580/2119] lr: 4.0000e-02 eta: 14:07:28 time: 0.3653 data_time: 0.0220 memory: 5826 grad_norm: 3.1200 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6237 loss: 2.6237 2022/10/08 00:26:09 - mmengine - INFO - Epoch(train) [81][1600/2119] lr: 4.0000e-02 eta: 14:07:21 time: 0.3333 data_time: 0.0234 memory: 5826 grad_norm: 3.1408 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7211 loss: 2.7211 2022/10/08 00:26:18 - mmengine - INFO - Epoch(train) [81][1620/2119] lr: 4.0000e-02 eta: 14:07:15 time: 0.4381 data_time: 0.0220 memory: 5826 grad_norm: 3.1363 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7582 loss: 2.7582 2022/10/08 00:26:25 - mmengine - INFO - Epoch(train) [81][1640/2119] lr: 4.0000e-02 eta: 14:07:08 time: 0.3449 data_time: 0.0217 memory: 5826 grad_norm: 3.1392 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7365 loss: 2.7365 2022/10/08 00:26:33 - mmengine - INFO - Epoch(train) [81][1660/2119] lr: 4.0000e-02 eta: 14:07:02 time: 0.3813 data_time: 0.0219 memory: 5826 grad_norm: 3.0933 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7018 loss: 2.7018 2022/10/08 00:26:40 - mmengine - INFO - Epoch(train) [81][1680/2119] lr: 4.0000e-02 eta: 14:06:55 time: 0.3548 data_time: 0.0227 memory: 5826 grad_norm: 3.0971 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8154 loss: 2.8154 2022/10/08 00:26:47 - mmengine - INFO - Epoch(train) [81][1700/2119] lr: 4.0000e-02 eta: 14:06:49 time: 0.3768 data_time: 0.0214 memory: 5826 grad_norm: 3.1470 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6060 loss: 2.6060 2022/10/08 00:26:53 - mmengine - INFO - Epoch(train) [81][1720/2119] lr: 4.0000e-02 eta: 14:06:41 time: 0.2836 data_time: 0.0249 memory: 5826 grad_norm: 3.1123 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6868 loss: 2.6868 2022/10/08 00:27:01 - mmengine - INFO - Epoch(train) [81][1740/2119] lr: 4.0000e-02 eta: 14:06:34 time: 0.3762 data_time: 0.0212 memory: 5826 grad_norm: 3.0872 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7559 loss: 2.7559 2022/10/08 00:27:07 - mmengine - INFO - Epoch(train) [81][1760/2119] lr: 4.0000e-02 eta: 14:06:26 time: 0.2931 data_time: 0.0277 memory: 5826 grad_norm: 3.0627 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8666 loss: 2.8666 2022/10/08 00:27:14 - mmengine - INFO - Epoch(train) [81][1780/2119] lr: 4.0000e-02 eta: 14:06:20 time: 0.3880 data_time: 0.0219 memory: 5826 grad_norm: 3.1018 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5877 loss: 2.5877 2022/10/08 00:27:22 - mmengine - INFO - Epoch(train) [81][1800/2119] lr: 4.0000e-02 eta: 14:06:14 time: 0.3665 data_time: 0.0313 memory: 5826 grad_norm: 3.2024 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5695 loss: 2.5695 2022/10/08 00:27:29 - mmengine - INFO - Epoch(train) [81][1820/2119] lr: 4.0000e-02 eta: 14:06:07 time: 0.3780 data_time: 0.0251 memory: 5826 grad_norm: 3.0974 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6551 loss: 2.6551 2022/10/08 00:27:35 - mmengine - INFO - Epoch(train) [81][1840/2119] lr: 4.0000e-02 eta: 14:05:59 time: 0.3005 data_time: 0.0233 memory: 5826 grad_norm: 3.1183 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8511 loss: 2.8511 2022/10/08 00:27:43 - mmengine - INFO - Epoch(train) [81][1860/2119] lr: 4.0000e-02 eta: 14:05:53 time: 0.3856 data_time: 0.0221 memory: 5826 grad_norm: 3.1889 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5931 loss: 2.5931 2022/10/08 00:27:50 - mmengine - INFO - Epoch(train) [81][1880/2119] lr: 4.0000e-02 eta: 14:05:46 time: 0.3366 data_time: 0.0274 memory: 5826 grad_norm: 3.0868 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6407 loss: 2.6407 2022/10/08 00:27:58 - mmengine - INFO - Epoch(train) [81][1900/2119] lr: 4.0000e-02 eta: 14:05:40 time: 0.4151 data_time: 0.0264 memory: 5826 grad_norm: 3.0958 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6555 loss: 2.6555 2022/10/08 00:28:03 - mmengine - INFO - Epoch(train) [81][1920/2119] lr: 4.0000e-02 eta: 14:05:32 time: 0.2494 data_time: 0.0259 memory: 5826 grad_norm: 3.1082 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8175 loss: 2.8175 2022/10/08 00:28:10 - mmengine - INFO - Epoch(train) [81][1940/2119] lr: 4.0000e-02 eta: 14:05:25 time: 0.3389 data_time: 0.0232 memory: 5826 grad_norm: 3.2015 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.5495 loss: 2.5495 2022/10/08 00:28:17 - mmengine - INFO - Epoch(train) [81][1960/2119] lr: 4.0000e-02 eta: 14:05:18 time: 0.3591 data_time: 0.0235 memory: 5826 grad_norm: 3.1698 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8035 loss: 2.8035 2022/10/08 00:28:24 - mmengine - INFO - Epoch(train) [81][1980/2119] lr: 4.0000e-02 eta: 14:05:11 time: 0.3654 data_time: 0.0191 memory: 5826 grad_norm: 3.1331 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6128 loss: 2.6128 2022/10/08 00:28:31 - mmengine - INFO - Epoch(train) [81][2000/2119] lr: 4.0000e-02 eta: 14:05:04 time: 0.3396 data_time: 0.0208 memory: 5826 grad_norm: 3.1104 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8275 loss: 2.8275 2022/10/08 00:28:38 - mmengine - INFO - Epoch(train) [81][2020/2119] lr: 4.0000e-02 eta: 14:04:57 time: 0.3339 data_time: 0.0224 memory: 5826 grad_norm: 3.1224 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6793 loss: 2.6793 2022/10/08 00:28:44 - mmengine - INFO - Epoch(train) [81][2040/2119] lr: 4.0000e-02 eta: 14:04:50 time: 0.3360 data_time: 0.0216 memory: 5826 grad_norm: 3.1492 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6841 loss: 2.6841 2022/10/08 00:28:52 - mmengine - INFO - Epoch(train) [81][2060/2119] lr: 4.0000e-02 eta: 14:04:44 time: 0.3668 data_time: 0.0187 memory: 5826 grad_norm: 3.1816 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.6586 loss: 2.6586 2022/10/08 00:28:59 - mmengine - INFO - Epoch(train) [81][2080/2119] lr: 4.0000e-02 eta: 14:04:37 time: 0.3565 data_time: 0.0265 memory: 5826 grad_norm: 3.1377 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9343 loss: 2.9343 2022/10/08 00:29:06 - mmengine - INFO - Epoch(train) [81][2100/2119] lr: 4.0000e-02 eta: 14:04:30 time: 0.3495 data_time: 0.0225 memory: 5826 grad_norm: 3.1863 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7133 loss: 2.7133 2022/10/08 00:29:12 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 00:29:12 - mmengine - INFO - Epoch(train) [81][2119/2119] lr: 4.0000e-02 eta: 14:04:30 time: 0.3281 data_time: 0.0141 memory: 5826 grad_norm: 3.2047 top1_acc: 0.4000 top5_acc: 0.7000 loss_cls: 2.6567 loss: 2.6567 2022/10/08 00:29:21 - mmengine - INFO - Epoch(train) [82][20/2119] lr: 4.0000e-02 eta: 14:04:12 time: 0.4483 data_time: 0.1481 memory: 5826 grad_norm: 3.1427 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5309 loss: 2.5309 2022/10/08 00:29:29 - mmengine - INFO - Epoch(train) [82][40/2119] lr: 4.0000e-02 eta: 14:04:06 time: 0.3633 data_time: 0.0237 memory: 5826 grad_norm: 3.1508 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7317 loss: 2.7317 2022/10/08 00:29:36 - mmengine - INFO - Epoch(train) [82][60/2119] lr: 4.0000e-02 eta: 14:03:59 time: 0.3571 data_time: 0.0266 memory: 5826 grad_norm: 3.1954 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7267 loss: 2.7267 2022/10/08 00:29:43 - mmengine - INFO - Epoch(train) [82][80/2119] lr: 4.0000e-02 eta: 14:03:52 time: 0.3449 data_time: 0.0224 memory: 5826 grad_norm: 3.0821 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7767 loss: 2.7767 2022/10/08 00:29:49 - mmengine - INFO - Epoch(train) [82][100/2119] lr: 4.0000e-02 eta: 14:03:45 time: 0.3197 data_time: 0.0251 memory: 5826 grad_norm: 3.0782 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7793 loss: 2.7793 2022/10/08 00:29:56 - mmengine - INFO - Epoch(train) [82][120/2119] lr: 4.0000e-02 eta: 14:03:38 time: 0.3436 data_time: 0.0276 memory: 5826 grad_norm: 3.1570 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4547 loss: 2.4547 2022/10/08 00:30:02 - mmengine - INFO - Epoch(train) [82][140/2119] lr: 4.0000e-02 eta: 14:03:30 time: 0.3189 data_time: 0.0241 memory: 5826 grad_norm: 3.1901 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8744 loss: 2.8744 2022/10/08 00:30:09 - mmengine - INFO - Epoch(train) [82][160/2119] lr: 4.0000e-02 eta: 14:03:23 time: 0.3461 data_time: 0.0304 memory: 5826 grad_norm: 3.0640 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7538 loss: 2.7538 2022/10/08 00:30:16 - mmengine - INFO - Epoch(train) [82][180/2119] lr: 4.0000e-02 eta: 14:03:17 time: 0.3560 data_time: 0.0245 memory: 5826 grad_norm: 3.0974 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6710 loss: 2.6710 2022/10/08 00:30:23 - mmengine - INFO - Epoch(train) [82][200/2119] lr: 4.0000e-02 eta: 14:03:10 time: 0.3330 data_time: 0.0245 memory: 5826 grad_norm: 3.0847 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.5999 loss: 2.5999 2022/10/08 00:30:31 - mmengine - INFO - Epoch(train) [82][220/2119] lr: 4.0000e-02 eta: 14:03:03 time: 0.3871 data_time: 0.0202 memory: 5826 grad_norm: 3.1141 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8246 loss: 2.8246 2022/10/08 00:30:38 - mmengine - INFO - Epoch(train) [82][240/2119] lr: 4.0000e-02 eta: 14:02:56 time: 0.3368 data_time: 0.0228 memory: 5826 grad_norm: 3.1644 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4539 loss: 2.4539 2022/10/08 00:30:44 - mmengine - INFO - Epoch(train) [82][260/2119] lr: 4.0000e-02 eta: 14:02:49 time: 0.3345 data_time: 0.0231 memory: 5826 grad_norm: 3.0950 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5139 loss: 2.5139 2022/10/08 00:30:51 - mmengine - INFO - Epoch(train) [82][280/2119] lr: 4.0000e-02 eta: 14:02:42 time: 0.3476 data_time: 0.0226 memory: 5826 grad_norm: 3.1353 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8457 loss: 2.8457 2022/10/08 00:30:59 - mmengine - INFO - Epoch(train) [82][300/2119] lr: 4.0000e-02 eta: 14:02:35 time: 0.3630 data_time: 0.0277 memory: 5826 grad_norm: 3.0581 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9986 loss: 2.9986 2022/10/08 00:31:04 - mmengine - INFO - Epoch(train) [82][320/2119] lr: 4.0000e-02 eta: 14:02:28 time: 0.2960 data_time: 0.0235 memory: 5826 grad_norm: 3.1987 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9301 loss: 2.9301 2022/10/08 00:31:13 - mmengine - INFO - Epoch(train) [82][340/2119] lr: 4.0000e-02 eta: 14:02:22 time: 0.4092 data_time: 0.0224 memory: 5826 grad_norm: 3.1775 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6056 loss: 2.6056 2022/10/08 00:31:20 - mmengine - INFO - Epoch(train) [82][360/2119] lr: 4.0000e-02 eta: 14:02:15 time: 0.3660 data_time: 0.0195 memory: 5826 grad_norm: 3.1497 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7465 loss: 2.7465 2022/10/08 00:31:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 00:31:27 - mmengine - INFO - Epoch(train) [82][380/2119] lr: 4.0000e-02 eta: 14:02:08 time: 0.3428 data_time: 0.0242 memory: 5826 grad_norm: 3.0966 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5187 loss: 2.5187 2022/10/08 00:31:34 - mmengine - INFO - Epoch(train) [82][400/2119] lr: 4.0000e-02 eta: 14:02:01 time: 0.3357 data_time: 0.0284 memory: 5826 grad_norm: 3.0925 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7330 loss: 2.7330 2022/10/08 00:31:41 - mmengine - INFO - Epoch(train) [82][420/2119] lr: 4.0000e-02 eta: 14:01:55 time: 0.3813 data_time: 0.0230 memory: 5826 grad_norm: 3.1404 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5958 loss: 2.5958 2022/10/08 00:31:48 - mmengine - INFO - Epoch(train) [82][440/2119] lr: 4.0000e-02 eta: 14:01:48 time: 0.3374 data_time: 0.0232 memory: 5826 grad_norm: 3.1441 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8266 loss: 2.8266 2022/10/08 00:31:56 - mmengine - INFO - Epoch(train) [82][460/2119] lr: 4.0000e-02 eta: 14:01:41 time: 0.3832 data_time: 0.0230 memory: 5826 grad_norm: 3.1636 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7418 loss: 2.7418 2022/10/08 00:32:02 - mmengine - INFO - Epoch(train) [82][480/2119] lr: 4.0000e-02 eta: 14:01:34 time: 0.3108 data_time: 0.0210 memory: 5826 grad_norm: 3.0548 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6337 loss: 2.6337 2022/10/08 00:32:09 - mmengine - INFO - Epoch(train) [82][500/2119] lr: 4.0000e-02 eta: 14:01:27 time: 0.3601 data_time: 0.0197 memory: 5826 grad_norm: 3.1486 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6296 loss: 2.6296 2022/10/08 00:32:16 - mmengine - INFO - Epoch(train) [82][520/2119] lr: 4.0000e-02 eta: 14:01:20 time: 0.3447 data_time: 0.0267 memory: 5826 grad_norm: 3.1011 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6024 loss: 2.6024 2022/10/08 00:32:23 - mmengine - INFO - Epoch(train) [82][540/2119] lr: 4.0000e-02 eta: 14:01:13 time: 0.3538 data_time: 0.0225 memory: 5826 grad_norm: 3.1338 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6534 loss: 2.6534 2022/10/08 00:32:29 - mmengine - INFO - Epoch(train) [82][560/2119] lr: 4.0000e-02 eta: 14:01:06 time: 0.3070 data_time: 0.0230 memory: 5826 grad_norm: 3.0698 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0384 loss: 3.0384 2022/10/08 00:32:37 - mmengine - INFO - Epoch(train) [82][580/2119] lr: 4.0000e-02 eta: 14:01:00 time: 0.3919 data_time: 0.0235 memory: 5826 grad_norm: 3.1522 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9030 loss: 2.9030 2022/10/08 00:32:43 - mmengine - INFO - Epoch(train) [82][600/2119] lr: 4.0000e-02 eta: 14:00:52 time: 0.3105 data_time: 0.0275 memory: 5826 grad_norm: 3.1702 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7311 loss: 2.7311 2022/10/08 00:32:51 - mmengine - INFO - Epoch(train) [82][620/2119] lr: 4.0000e-02 eta: 14:00:46 time: 0.3811 data_time: 0.0258 memory: 5826 grad_norm: 3.1351 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.4440 loss: 2.4440 2022/10/08 00:32:58 - mmengine - INFO - Epoch(train) [82][640/2119] lr: 4.0000e-02 eta: 14:00:39 time: 0.3495 data_time: 0.0249 memory: 5826 grad_norm: 3.1633 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9030 loss: 2.9030 2022/10/08 00:33:05 - mmengine - INFO - Epoch(train) [82][660/2119] lr: 4.0000e-02 eta: 14:00:32 time: 0.3646 data_time: 0.0217 memory: 5826 grad_norm: 3.0249 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7467 loss: 2.7467 2022/10/08 00:33:12 - mmengine - INFO - Epoch(train) [82][680/2119] lr: 4.0000e-02 eta: 14:00:25 time: 0.3239 data_time: 0.0254 memory: 5826 grad_norm: 3.0994 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5793 loss: 2.5793 2022/10/08 00:33:19 - mmengine - INFO - Epoch(train) [82][700/2119] lr: 4.0000e-02 eta: 14:00:18 time: 0.3691 data_time: 0.0216 memory: 5826 grad_norm: 3.1548 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5427 loss: 2.5427 2022/10/08 00:33:25 - mmengine - INFO - Epoch(train) [82][720/2119] lr: 4.0000e-02 eta: 14:00:11 time: 0.3111 data_time: 0.0235 memory: 5826 grad_norm: 3.1332 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7920 loss: 2.7920 2022/10/08 00:33:33 - mmengine - INFO - Epoch(train) [82][740/2119] lr: 4.0000e-02 eta: 14:00:05 time: 0.3831 data_time: 0.0195 memory: 5826 grad_norm: 3.1121 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6332 loss: 2.6332 2022/10/08 00:33:40 - mmengine - INFO - Epoch(train) [82][760/2119] lr: 4.0000e-02 eta: 13:59:57 time: 0.3317 data_time: 0.0288 memory: 5826 grad_norm: 3.1128 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7549 loss: 2.7549 2022/10/08 00:33:47 - mmengine - INFO - Epoch(train) [82][780/2119] lr: 4.0000e-02 eta: 13:59:51 time: 0.3578 data_time: 0.0218 memory: 5826 grad_norm: 3.1145 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8646 loss: 2.8646 2022/10/08 00:33:53 - mmengine - INFO - Epoch(train) [82][800/2119] lr: 4.0000e-02 eta: 13:59:43 time: 0.3342 data_time: 0.0255 memory: 5826 grad_norm: 3.0742 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6676 loss: 2.6676 2022/10/08 00:34:01 - mmengine - INFO - Epoch(train) [82][820/2119] lr: 4.0000e-02 eta: 13:59:37 time: 0.3640 data_time: 0.0238 memory: 5826 grad_norm: 3.1143 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5134 loss: 2.5134 2022/10/08 00:34:08 - mmengine - INFO - Epoch(train) [82][840/2119] lr: 4.0000e-02 eta: 13:59:30 time: 0.3631 data_time: 0.0276 memory: 5826 grad_norm: 3.1052 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3534 loss: 2.3534 2022/10/08 00:34:15 - mmengine - INFO - Epoch(train) [82][860/2119] lr: 4.0000e-02 eta: 13:59:24 time: 0.3610 data_time: 0.0184 memory: 5826 grad_norm: 3.1915 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8146 loss: 2.8146 2022/10/08 00:34:22 - mmengine - INFO - Epoch(train) [82][880/2119] lr: 4.0000e-02 eta: 13:59:16 time: 0.3380 data_time: 0.0221 memory: 5826 grad_norm: 3.1035 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7922 loss: 2.7922 2022/10/08 00:34:29 - mmengine - INFO - Epoch(train) [82][900/2119] lr: 4.0000e-02 eta: 13:59:10 time: 0.3751 data_time: 0.0278 memory: 5826 grad_norm: 3.1508 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6193 loss: 2.6193 2022/10/08 00:34:36 - mmengine - INFO - Epoch(train) [82][920/2119] lr: 4.0000e-02 eta: 13:59:03 time: 0.3166 data_time: 0.0239 memory: 5826 grad_norm: 3.1073 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5679 loss: 2.5679 2022/10/08 00:34:43 - mmengine - INFO - Epoch(train) [82][940/2119] lr: 4.0000e-02 eta: 13:58:56 time: 0.3727 data_time: 0.0191 memory: 5826 grad_norm: 3.2048 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7356 loss: 2.7356 2022/10/08 00:34:50 - mmengine - INFO - Epoch(train) [82][960/2119] lr: 4.0000e-02 eta: 13:58:49 time: 0.3220 data_time: 0.0299 memory: 5826 grad_norm: 3.1181 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.7462 loss: 2.7462 2022/10/08 00:34:56 - mmengine - INFO - Epoch(train) [82][980/2119] lr: 4.0000e-02 eta: 13:58:42 time: 0.3372 data_time: 0.0164 memory: 5826 grad_norm: 3.1313 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 3.0087 loss: 3.0087 2022/10/08 00:35:03 - mmengine - INFO - Epoch(train) [82][1000/2119] lr: 4.0000e-02 eta: 13:58:35 time: 0.3335 data_time: 0.0265 memory: 5826 grad_norm: 3.1106 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0325 loss: 3.0325 2022/10/08 00:35:10 - mmengine - INFO - Epoch(train) [82][1020/2119] lr: 4.0000e-02 eta: 13:58:28 time: 0.3439 data_time: 0.0245 memory: 5826 grad_norm: 3.1544 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7386 loss: 2.7386 2022/10/08 00:35:17 - mmengine - INFO - Epoch(train) [82][1040/2119] lr: 4.0000e-02 eta: 13:58:21 time: 0.3444 data_time: 0.0284 memory: 5826 grad_norm: 3.1003 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.6530 loss: 2.6530 2022/10/08 00:35:24 - mmengine - INFO - Epoch(train) [82][1060/2119] lr: 4.0000e-02 eta: 13:58:14 time: 0.3590 data_time: 0.0246 memory: 5826 grad_norm: 3.0924 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.3683 loss: 2.3683 2022/10/08 00:35:31 - mmengine - INFO - Epoch(train) [82][1080/2119] lr: 4.0000e-02 eta: 13:58:07 time: 0.3319 data_time: 0.0237 memory: 5826 grad_norm: 3.0984 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6978 loss: 2.6978 2022/10/08 00:35:38 - mmengine - INFO - Epoch(train) [82][1100/2119] lr: 4.0000e-02 eta: 13:58:00 time: 0.3549 data_time: 0.0250 memory: 5826 grad_norm: 3.1202 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7683 loss: 2.7683 2022/10/08 00:35:44 - mmengine - INFO - Epoch(train) [82][1120/2119] lr: 4.0000e-02 eta: 13:57:53 time: 0.3328 data_time: 0.0249 memory: 5826 grad_norm: 3.0961 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.7771 loss: 2.7771 2022/10/08 00:35:52 - mmengine - INFO - Epoch(train) [82][1140/2119] lr: 4.0000e-02 eta: 13:57:46 time: 0.3591 data_time: 0.0256 memory: 5826 grad_norm: 3.1313 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7175 loss: 2.7175 2022/10/08 00:35:58 - mmengine - INFO - Epoch(train) [82][1160/2119] lr: 4.0000e-02 eta: 13:57:38 time: 0.3017 data_time: 0.0267 memory: 5826 grad_norm: 3.0738 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7696 loss: 2.7696 2022/10/08 00:36:05 - mmengine - INFO - Epoch(train) [82][1180/2119] lr: 4.0000e-02 eta: 13:57:32 time: 0.3884 data_time: 0.0227 memory: 5826 grad_norm: 3.1938 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5974 loss: 2.5974 2022/10/08 00:36:12 - mmengine - INFO - Epoch(train) [82][1200/2119] lr: 4.0000e-02 eta: 13:57:25 time: 0.3410 data_time: 0.0222 memory: 5826 grad_norm: 3.1233 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9268 loss: 2.9268 2022/10/08 00:36:20 - mmengine - INFO - Epoch(train) [82][1220/2119] lr: 4.0000e-02 eta: 13:57:19 time: 0.3787 data_time: 0.0206 memory: 5826 grad_norm: 3.0945 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7510 loss: 2.7510 2022/10/08 00:36:26 - mmengine - INFO - Epoch(train) [82][1240/2119] lr: 4.0000e-02 eta: 13:57:11 time: 0.3267 data_time: 0.0268 memory: 5826 grad_norm: 3.1885 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9169 loss: 2.9169 2022/10/08 00:36:35 - mmengine - INFO - Epoch(train) [82][1260/2119] lr: 4.0000e-02 eta: 13:57:06 time: 0.4149 data_time: 0.0249 memory: 5826 grad_norm: 3.0911 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5565 loss: 2.5565 2022/10/08 00:36:42 - mmengine - INFO - Epoch(train) [82][1280/2119] lr: 4.0000e-02 eta: 13:56:59 time: 0.3575 data_time: 0.0200 memory: 5826 grad_norm: 3.0836 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8101 loss: 2.8101 2022/10/08 00:36:50 - mmengine - INFO - Epoch(train) [82][1300/2119] lr: 4.0000e-02 eta: 13:56:53 time: 0.3929 data_time: 0.0222 memory: 5826 grad_norm: 3.1457 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9718 loss: 2.9718 2022/10/08 00:36:56 - mmengine - INFO - Epoch(train) [82][1320/2119] lr: 4.0000e-02 eta: 13:56:45 time: 0.3053 data_time: 0.0266 memory: 5826 grad_norm: 3.1879 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.4344 loss: 2.4344 2022/10/08 00:37:03 - mmengine - INFO - Epoch(train) [82][1340/2119] lr: 4.0000e-02 eta: 13:56:38 time: 0.3529 data_time: 0.0238 memory: 5826 grad_norm: 3.1683 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5703 loss: 2.5703 2022/10/08 00:37:10 - mmengine - INFO - Epoch(train) [82][1360/2119] lr: 4.0000e-02 eta: 13:56:32 time: 0.3699 data_time: 0.0291 memory: 5826 grad_norm: 3.1067 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6637 loss: 2.6637 2022/10/08 00:37:11 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 00:37:17 - mmengine - INFO - Epoch(train) [82][1380/2119] lr: 4.0000e-02 eta: 13:56:25 time: 0.3332 data_time: 0.0230 memory: 5826 grad_norm: 3.1726 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7378 loss: 2.7378 2022/10/08 00:37:24 - mmengine - INFO - Epoch(train) [82][1400/2119] lr: 4.0000e-02 eta: 13:56:17 time: 0.3248 data_time: 0.0222 memory: 5826 grad_norm: 3.1531 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.7217 loss: 2.7217 2022/10/08 00:37:32 - mmengine - INFO - Epoch(train) [82][1420/2119] lr: 4.0000e-02 eta: 13:56:12 time: 0.4211 data_time: 0.0218 memory: 5826 grad_norm: 3.0763 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7388 loss: 2.7388 2022/10/08 00:37:38 - mmengine - INFO - Epoch(train) [82][1440/2119] lr: 4.0000e-02 eta: 13:56:04 time: 0.3280 data_time: 0.0254 memory: 5826 grad_norm: 3.1177 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7552 loss: 2.7552 2022/10/08 00:37:45 - mmengine - INFO - Epoch(train) [82][1460/2119] lr: 4.0000e-02 eta: 13:55:57 time: 0.3448 data_time: 0.0250 memory: 5826 grad_norm: 3.0925 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6759 loss: 2.6759 2022/10/08 00:37:52 - mmengine - INFO - Epoch(train) [82][1480/2119] lr: 4.0000e-02 eta: 13:55:50 time: 0.3250 data_time: 0.0240 memory: 5826 grad_norm: 3.0736 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7572 loss: 2.7572 2022/10/08 00:37:59 - mmengine - INFO - Epoch(train) [82][1500/2119] lr: 4.0000e-02 eta: 13:55:43 time: 0.3628 data_time: 0.0282 memory: 5826 grad_norm: 3.0732 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9061 loss: 2.9061 2022/10/08 00:38:06 - mmengine - INFO - Epoch(train) [82][1520/2119] lr: 4.0000e-02 eta: 13:55:36 time: 0.3280 data_time: 0.0196 memory: 5826 grad_norm: 3.1035 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6872 loss: 2.6872 2022/10/08 00:38:14 - mmengine - INFO - Epoch(train) [82][1540/2119] lr: 4.0000e-02 eta: 13:55:30 time: 0.3958 data_time: 0.0260 memory: 5826 grad_norm: 3.1297 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7857 loss: 2.7857 2022/10/08 00:38:20 - mmengine - INFO - Epoch(train) [82][1560/2119] lr: 4.0000e-02 eta: 13:55:23 time: 0.3140 data_time: 0.0248 memory: 5826 grad_norm: 3.1294 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7801 loss: 2.7801 2022/10/08 00:38:27 - mmengine - INFO - Epoch(train) [82][1580/2119] lr: 4.0000e-02 eta: 13:55:16 time: 0.3553 data_time: 0.0250 memory: 5826 grad_norm: 3.0765 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7869 loss: 2.7869 2022/10/08 00:38:34 - mmengine - INFO - Epoch(train) [82][1600/2119] lr: 4.0000e-02 eta: 13:55:09 time: 0.3551 data_time: 0.0249 memory: 5826 grad_norm: 3.1411 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5415 loss: 2.5415 2022/10/08 00:38:42 - mmengine - INFO - Epoch(train) [82][1620/2119] lr: 4.0000e-02 eta: 13:55:03 time: 0.3776 data_time: 0.0269 memory: 5826 grad_norm: 3.1024 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8131 loss: 2.8131 2022/10/08 00:38:49 - mmengine - INFO - Epoch(train) [82][1640/2119] lr: 4.0000e-02 eta: 13:54:56 time: 0.3388 data_time: 0.0210 memory: 5826 grad_norm: 3.1516 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6825 loss: 2.6825 2022/10/08 00:38:55 - mmengine - INFO - Epoch(train) [82][1660/2119] lr: 4.0000e-02 eta: 13:54:48 time: 0.3134 data_time: 0.0203 memory: 5826 grad_norm: 3.1826 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 3.0100 loss: 3.0100 2022/10/08 00:39:02 - mmengine - INFO - Epoch(train) [82][1680/2119] lr: 4.0000e-02 eta: 13:54:41 time: 0.3536 data_time: 0.0268 memory: 5826 grad_norm: 3.1508 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7014 loss: 2.7014 2022/10/08 00:39:09 - mmengine - INFO - Epoch(train) [82][1700/2119] lr: 4.0000e-02 eta: 13:54:34 time: 0.3430 data_time: 0.0225 memory: 5826 grad_norm: 3.1210 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5316 loss: 2.5316 2022/10/08 00:39:15 - mmengine - INFO - Epoch(train) [82][1720/2119] lr: 4.0000e-02 eta: 13:54:27 time: 0.3249 data_time: 0.0215 memory: 5826 grad_norm: 3.0644 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7363 loss: 2.7363 2022/10/08 00:39:23 - mmengine - INFO - Epoch(train) [82][1740/2119] lr: 4.0000e-02 eta: 13:54:20 time: 0.3675 data_time: 0.0335 memory: 5826 grad_norm: 3.0742 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6230 loss: 2.6230 2022/10/08 00:39:30 - mmengine - INFO - Epoch(train) [82][1760/2119] lr: 4.0000e-02 eta: 13:54:14 time: 0.3472 data_time: 0.0232 memory: 5826 grad_norm: 3.0786 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5815 loss: 2.5815 2022/10/08 00:39:36 - mmengine - INFO - Epoch(train) [82][1780/2119] lr: 4.0000e-02 eta: 13:54:06 time: 0.3370 data_time: 0.0242 memory: 5826 grad_norm: 3.0894 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8445 loss: 2.8445 2022/10/08 00:39:44 - mmengine - INFO - Epoch(train) [82][1800/2119] lr: 4.0000e-02 eta: 13:54:00 time: 0.3629 data_time: 0.0220 memory: 5826 grad_norm: 3.1148 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7372 loss: 2.7372 2022/10/08 00:39:51 - mmengine - INFO - Epoch(train) [82][1820/2119] lr: 4.0000e-02 eta: 13:53:53 time: 0.3842 data_time: 0.0264 memory: 5826 grad_norm: 3.1570 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4942 loss: 2.4942 2022/10/08 00:39:57 - mmengine - INFO - Epoch(train) [82][1840/2119] lr: 4.0000e-02 eta: 13:53:46 time: 0.3076 data_time: 0.0233 memory: 5826 grad_norm: 3.1579 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5047 loss: 2.5047 2022/10/08 00:40:05 - mmengine - INFO - Epoch(train) [82][1860/2119] lr: 4.0000e-02 eta: 13:53:40 time: 0.3865 data_time: 0.0325 memory: 5826 grad_norm: 3.0970 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6821 loss: 2.6821 2022/10/08 00:40:12 - mmengine - INFO - Epoch(train) [82][1880/2119] lr: 4.0000e-02 eta: 13:53:33 time: 0.3582 data_time: 0.0241 memory: 5826 grad_norm: 3.1227 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7478 loss: 2.7478 2022/10/08 00:40:20 - mmengine - INFO - Epoch(train) [82][1900/2119] lr: 4.0000e-02 eta: 13:53:27 time: 0.3837 data_time: 0.0217 memory: 5826 grad_norm: 3.0998 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7390 loss: 2.7390 2022/10/08 00:40:26 - mmengine - INFO - Epoch(train) [82][1920/2119] lr: 4.0000e-02 eta: 13:53:19 time: 0.3117 data_time: 0.0185 memory: 5826 grad_norm: 3.1966 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8190 loss: 2.8190 2022/10/08 00:40:34 - mmengine - INFO - Epoch(train) [82][1940/2119] lr: 4.0000e-02 eta: 13:53:13 time: 0.3879 data_time: 0.0217 memory: 5826 grad_norm: 3.1374 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9519 loss: 2.9519 2022/10/08 00:40:40 - mmengine - INFO - Epoch(train) [82][1960/2119] lr: 4.0000e-02 eta: 13:53:05 time: 0.3066 data_time: 0.0235 memory: 5826 grad_norm: 3.1350 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6563 loss: 2.6563 2022/10/08 00:40:48 - mmengine - INFO - Epoch(train) [82][1980/2119] lr: 4.0000e-02 eta: 13:52:59 time: 0.3920 data_time: 0.0224 memory: 5826 grad_norm: 3.1525 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7877 loss: 2.7877 2022/10/08 00:40:54 - mmengine - INFO - Epoch(train) [82][2000/2119] lr: 4.0000e-02 eta: 13:52:52 time: 0.3233 data_time: 0.0201 memory: 5826 grad_norm: 3.0879 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6219 loss: 2.6219 2022/10/08 00:41:02 - mmengine - INFO - Epoch(train) [82][2020/2119] lr: 4.0000e-02 eta: 13:52:45 time: 0.3713 data_time: 0.0256 memory: 5826 grad_norm: 3.1275 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7519 loss: 2.7519 2022/10/08 00:41:08 - mmengine - INFO - Epoch(train) [82][2040/2119] lr: 4.0000e-02 eta: 13:52:38 time: 0.3026 data_time: 0.0248 memory: 5826 grad_norm: 3.1354 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7199 loss: 2.7199 2022/10/08 00:41:16 - mmengine - INFO - Epoch(train) [82][2060/2119] lr: 4.0000e-02 eta: 13:52:31 time: 0.3817 data_time: 0.0219 memory: 5826 grad_norm: 3.1397 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4881 loss: 2.4881 2022/10/08 00:41:22 - mmengine - INFO - Epoch(train) [82][2080/2119] lr: 4.0000e-02 eta: 13:52:24 time: 0.3079 data_time: 0.0200 memory: 5826 grad_norm: 3.0884 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7138 loss: 2.7138 2022/10/08 00:41:29 - mmengine - INFO - Epoch(train) [82][2100/2119] lr: 4.0000e-02 eta: 13:52:17 time: 0.3592 data_time: 0.0233 memory: 5826 grad_norm: 3.1785 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7331 loss: 2.7331 2022/10/08 00:41:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 00:41:35 - mmengine - INFO - Epoch(train) [82][2119/2119] lr: 4.0000e-02 eta: 13:52:17 time: 0.3015 data_time: 0.0181 memory: 5826 grad_norm: 3.0993 top1_acc: 0.3000 top5_acc: 0.8000 loss_cls: 2.9406 loss: 2.9406 2022/10/08 00:41:45 - mmengine - INFO - Epoch(train) [83][20/2119] lr: 4.0000e-02 eta: 13:52:00 time: 0.4947 data_time: 0.1180 memory: 5826 grad_norm: 3.1245 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6214 loss: 2.6214 2022/10/08 00:41:51 - mmengine - INFO - Epoch(train) [83][40/2119] lr: 4.0000e-02 eta: 13:51:53 time: 0.3285 data_time: 0.0230 memory: 5826 grad_norm: 3.1441 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6754 loss: 2.6754 2022/10/08 00:41:59 - mmengine - INFO - Epoch(train) [83][60/2119] lr: 4.0000e-02 eta: 13:51:47 time: 0.3782 data_time: 0.0236 memory: 5826 grad_norm: 3.1093 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7259 loss: 2.7259 2022/10/08 00:42:05 - mmengine - INFO - Epoch(train) [83][80/2119] lr: 4.0000e-02 eta: 13:51:40 time: 0.3257 data_time: 0.0221 memory: 5826 grad_norm: 3.1164 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7617 loss: 2.7617 2022/10/08 00:42:12 - mmengine - INFO - Epoch(train) [83][100/2119] lr: 4.0000e-02 eta: 13:51:33 time: 0.3557 data_time: 0.0203 memory: 5826 grad_norm: 3.0974 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7913 loss: 2.7913 2022/10/08 00:42:20 - mmengine - INFO - Epoch(train) [83][120/2119] lr: 4.0000e-02 eta: 13:51:26 time: 0.3578 data_time: 0.0238 memory: 5826 grad_norm: 3.1049 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5838 loss: 2.5838 2022/10/08 00:42:27 - mmengine - INFO - Epoch(train) [83][140/2119] lr: 4.0000e-02 eta: 13:51:20 time: 0.3734 data_time: 0.0246 memory: 5826 grad_norm: 3.0943 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7862 loss: 2.7862 2022/10/08 00:42:34 - mmengine - INFO - Epoch(train) [83][160/2119] lr: 4.0000e-02 eta: 13:51:13 time: 0.3645 data_time: 0.0206 memory: 5826 grad_norm: 3.1342 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8488 loss: 2.8488 2022/10/08 00:42:42 - mmengine - INFO - Epoch(train) [83][180/2119] lr: 4.0000e-02 eta: 13:51:06 time: 0.3595 data_time: 0.0220 memory: 5826 grad_norm: 3.1636 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7928 loss: 2.7928 2022/10/08 00:42:48 - mmengine - INFO - Epoch(train) [83][200/2119] lr: 4.0000e-02 eta: 13:50:58 time: 0.2994 data_time: 0.0259 memory: 5826 grad_norm: 3.1342 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9281 loss: 2.9281 2022/10/08 00:42:55 - mmengine - INFO - Epoch(train) [83][220/2119] lr: 4.0000e-02 eta: 13:50:52 time: 0.3715 data_time: 0.0222 memory: 5826 grad_norm: 3.1639 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8202 loss: 2.8202 2022/10/08 00:43:01 - mmengine - INFO - Epoch(train) [83][240/2119] lr: 4.0000e-02 eta: 13:50:44 time: 0.2992 data_time: 0.0243 memory: 5826 grad_norm: 3.1808 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6097 loss: 2.6097 2022/10/08 00:43:01 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 00:43:09 - mmengine - INFO - Epoch(train) [83][260/2119] lr: 4.0000e-02 eta: 13:50:38 time: 0.3896 data_time: 0.0298 memory: 5826 grad_norm: 3.1771 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8851 loss: 2.8851 2022/10/08 00:43:15 - mmengine - INFO - Epoch(train) [83][280/2119] lr: 4.0000e-02 eta: 13:50:31 time: 0.3321 data_time: 0.0185 memory: 5826 grad_norm: 3.1582 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5295 loss: 2.5295 2022/10/08 00:43:23 - mmengine - INFO - Epoch(train) [83][300/2119] lr: 4.0000e-02 eta: 13:50:24 time: 0.3612 data_time: 0.0239 memory: 5826 grad_norm: 3.1371 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6500 loss: 2.6500 2022/10/08 00:43:29 - mmengine - INFO - Epoch(train) [83][320/2119] lr: 4.0000e-02 eta: 13:50:17 time: 0.3416 data_time: 0.0230 memory: 5826 grad_norm: 3.2055 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5223 loss: 2.5223 2022/10/08 00:43:37 - mmengine - INFO - Epoch(train) [83][340/2119] lr: 4.0000e-02 eta: 13:50:10 time: 0.3597 data_time: 0.0211 memory: 5826 grad_norm: 3.0582 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9429 loss: 2.9429 2022/10/08 00:43:43 - mmengine - INFO - Epoch(train) [83][360/2119] lr: 4.0000e-02 eta: 13:50:03 time: 0.3315 data_time: 0.0199 memory: 5826 grad_norm: 3.1648 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6923 loss: 2.6923 2022/10/08 00:43:49 - mmengine - INFO - Epoch(train) [83][380/2119] lr: 4.0000e-02 eta: 13:49:56 time: 0.3037 data_time: 0.0256 memory: 5826 grad_norm: 3.1513 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6047 loss: 2.6047 2022/10/08 00:43:56 - mmengine - INFO - Epoch(train) [83][400/2119] lr: 4.0000e-02 eta: 13:49:49 time: 0.3470 data_time: 0.0209 memory: 5826 grad_norm: 3.1639 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7730 loss: 2.7730 2022/10/08 00:44:04 - mmengine - INFO - Epoch(train) [83][420/2119] lr: 4.0000e-02 eta: 13:49:42 time: 0.3764 data_time: 0.0225 memory: 5826 grad_norm: 3.0843 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 2.6736 loss: 2.6736 2022/10/08 00:44:10 - mmengine - INFO - Epoch(train) [83][440/2119] lr: 4.0000e-02 eta: 13:49:35 time: 0.3306 data_time: 0.0227 memory: 5826 grad_norm: 3.1576 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6454 loss: 2.6454 2022/10/08 00:44:18 - mmengine - INFO - Epoch(train) [83][460/2119] lr: 4.0000e-02 eta: 13:49:29 time: 0.3997 data_time: 0.0203 memory: 5826 grad_norm: 3.0932 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8086 loss: 2.8086 2022/10/08 00:44:25 - mmengine - INFO - Epoch(train) [83][480/2119] lr: 4.0000e-02 eta: 13:49:22 time: 0.3479 data_time: 0.0193 memory: 5826 grad_norm: 3.1015 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5629 loss: 2.5629 2022/10/08 00:44:33 - mmengine - INFO - Epoch(train) [83][500/2119] lr: 4.0000e-02 eta: 13:49:16 time: 0.3788 data_time: 0.0208 memory: 5826 grad_norm: 3.1778 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8591 loss: 2.8591 2022/10/08 00:44:39 - mmengine - INFO - Epoch(train) [83][520/2119] lr: 4.0000e-02 eta: 13:49:08 time: 0.3213 data_time: 0.0314 memory: 5826 grad_norm: 3.1409 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.6295 loss: 2.6295 2022/10/08 00:44:47 - mmengine - INFO - Epoch(train) [83][540/2119] lr: 4.0000e-02 eta: 13:49:02 time: 0.3562 data_time: 0.0264 memory: 5826 grad_norm: 3.1292 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6424 loss: 2.6424 2022/10/08 00:44:53 - mmengine - INFO - Epoch(train) [83][560/2119] lr: 4.0000e-02 eta: 13:48:54 time: 0.3249 data_time: 0.0267 memory: 5826 grad_norm: 3.1511 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8401 loss: 2.8401 2022/10/08 00:45:00 - mmengine - INFO - Epoch(train) [83][580/2119] lr: 4.0000e-02 eta: 13:48:47 time: 0.3408 data_time: 0.0231 memory: 5826 grad_norm: 3.1801 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.7141 loss: 2.7141 2022/10/08 00:45:06 - mmengine - INFO - Epoch(train) [83][600/2119] lr: 4.0000e-02 eta: 13:48:40 time: 0.3214 data_time: 0.0194 memory: 5826 grad_norm: 3.1184 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.2463 loss: 2.2463 2022/10/08 00:45:14 - mmengine - INFO - Epoch(train) [83][620/2119] lr: 4.0000e-02 eta: 13:48:34 time: 0.3835 data_time: 0.0246 memory: 5826 grad_norm: 3.1877 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5558 loss: 2.5558 2022/10/08 00:45:20 - mmengine - INFO - Epoch(train) [83][640/2119] lr: 4.0000e-02 eta: 13:48:26 time: 0.3233 data_time: 0.0304 memory: 5826 grad_norm: 3.0978 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6125 loss: 2.6125 2022/10/08 00:45:28 - mmengine - INFO - Epoch(train) [83][660/2119] lr: 4.0000e-02 eta: 13:48:20 time: 0.3890 data_time: 0.0280 memory: 5826 grad_norm: 3.1461 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6164 loss: 2.6164 2022/10/08 00:45:34 - mmengine - INFO - Epoch(train) [83][680/2119] lr: 4.0000e-02 eta: 13:48:13 time: 0.3089 data_time: 0.0244 memory: 5826 grad_norm: 3.1584 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.5368 loss: 2.5368 2022/10/08 00:45:43 - mmengine - INFO - Epoch(train) [83][700/2119] lr: 4.0000e-02 eta: 13:48:07 time: 0.4018 data_time: 0.0230 memory: 5826 grad_norm: 3.1086 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6965 loss: 2.6965 2022/10/08 00:45:49 - mmengine - INFO - Epoch(train) [83][720/2119] lr: 4.0000e-02 eta: 13:47:59 time: 0.3176 data_time: 0.0281 memory: 5826 grad_norm: 3.0686 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6656 loss: 2.6656 2022/10/08 00:45:56 - mmengine - INFO - Epoch(train) [83][740/2119] lr: 4.0000e-02 eta: 13:47:52 time: 0.3651 data_time: 0.0243 memory: 5826 grad_norm: 3.1604 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7237 loss: 2.7237 2022/10/08 00:46:03 - mmengine - INFO - Epoch(train) [83][760/2119] lr: 4.0000e-02 eta: 13:47:45 time: 0.3287 data_time: 0.0236 memory: 5826 grad_norm: 3.1373 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4084 loss: 2.4084 2022/10/08 00:46:10 - mmengine - INFO - Epoch(train) [83][780/2119] lr: 4.0000e-02 eta: 13:47:39 time: 0.3652 data_time: 0.0203 memory: 5826 grad_norm: 3.0977 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7239 loss: 2.7239 2022/10/08 00:46:17 - mmengine - INFO - Epoch(train) [83][800/2119] lr: 4.0000e-02 eta: 13:47:31 time: 0.3323 data_time: 0.0266 memory: 5826 grad_norm: 3.0713 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7662 loss: 2.7662 2022/10/08 00:46:24 - mmengine - INFO - Epoch(train) [83][820/2119] lr: 4.0000e-02 eta: 13:47:25 time: 0.3813 data_time: 0.0222 memory: 5826 grad_norm: 3.1667 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6241 loss: 2.6241 2022/10/08 00:46:31 - mmengine - INFO - Epoch(train) [83][840/2119] lr: 4.0000e-02 eta: 13:47:18 time: 0.3105 data_time: 0.0273 memory: 5826 grad_norm: 3.1484 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6368 loss: 2.6368 2022/10/08 00:46:38 - mmengine - INFO - Epoch(train) [83][860/2119] lr: 4.0000e-02 eta: 13:47:11 time: 0.3470 data_time: 0.0284 memory: 5826 grad_norm: 3.1941 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7816 loss: 2.7816 2022/10/08 00:46:44 - mmengine - INFO - Epoch(train) [83][880/2119] lr: 4.0000e-02 eta: 13:47:04 time: 0.3458 data_time: 0.0247 memory: 5826 grad_norm: 3.1439 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5772 loss: 2.5772 2022/10/08 00:46:52 - mmengine - INFO - Epoch(train) [83][900/2119] lr: 4.0000e-02 eta: 13:46:57 time: 0.3557 data_time: 0.0228 memory: 5826 grad_norm: 3.1267 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9153 loss: 2.9153 2022/10/08 00:46:58 - mmengine - INFO - Epoch(train) [83][920/2119] lr: 4.0000e-02 eta: 13:46:49 time: 0.3147 data_time: 0.0254 memory: 5826 grad_norm: 3.1532 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9080 loss: 2.9080 2022/10/08 00:47:05 - mmengine - INFO - Epoch(train) [83][940/2119] lr: 4.0000e-02 eta: 13:46:43 time: 0.3612 data_time: 0.0234 memory: 5826 grad_norm: 3.1449 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6390 loss: 2.6390 2022/10/08 00:47:12 - mmengine - INFO - Epoch(train) [83][960/2119] lr: 4.0000e-02 eta: 13:46:36 time: 0.3420 data_time: 0.0241 memory: 5826 grad_norm: 3.1377 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5920 loss: 2.5920 2022/10/08 00:47:19 - mmengine - INFO - Epoch(train) [83][980/2119] lr: 4.0000e-02 eta: 13:46:29 time: 0.3657 data_time: 0.0241 memory: 5826 grad_norm: 3.1066 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8179 loss: 2.8179 2022/10/08 00:47:26 - mmengine - INFO - Epoch(train) [83][1000/2119] lr: 4.0000e-02 eta: 13:46:22 time: 0.3526 data_time: 0.0196 memory: 5826 grad_norm: 3.1315 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7376 loss: 2.7376 2022/10/08 00:47:33 - mmengine - INFO - Epoch(train) [83][1020/2119] lr: 4.0000e-02 eta: 13:46:15 time: 0.3232 data_time: 0.0232 memory: 5826 grad_norm: 3.1425 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.8116 loss: 2.8116 2022/10/08 00:47:41 - mmengine - INFO - Epoch(train) [83][1040/2119] lr: 4.0000e-02 eta: 13:46:09 time: 0.3971 data_time: 0.0456 memory: 5826 grad_norm: 3.0734 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7005 loss: 2.7005 2022/10/08 00:47:48 - mmengine - INFO - Epoch(train) [83][1060/2119] lr: 4.0000e-02 eta: 13:46:02 time: 0.3409 data_time: 0.0162 memory: 5826 grad_norm: 3.0807 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8170 loss: 2.8170 2022/10/08 00:47:54 - mmengine - INFO - Epoch(train) [83][1080/2119] lr: 4.0000e-02 eta: 13:45:55 time: 0.3239 data_time: 0.0218 memory: 5826 grad_norm: 3.1808 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6886 loss: 2.6886 2022/10/08 00:48:02 - mmengine - INFO - Epoch(train) [83][1100/2119] lr: 4.0000e-02 eta: 13:45:48 time: 0.3836 data_time: 0.0216 memory: 5826 grad_norm: 3.1884 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7006 loss: 2.7006 2022/10/08 00:48:09 - mmengine - INFO - Epoch(train) [83][1120/2119] lr: 4.0000e-02 eta: 13:45:42 time: 0.3589 data_time: 0.0251 memory: 5826 grad_norm: 3.1525 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.7611 loss: 2.7611 2022/10/08 00:48:16 - mmengine - INFO - Epoch(train) [83][1140/2119] lr: 4.0000e-02 eta: 13:45:35 time: 0.3516 data_time: 0.0208 memory: 5826 grad_norm: 3.1608 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8617 loss: 2.8617 2022/10/08 00:48:23 - mmengine - INFO - Epoch(train) [83][1160/2119] lr: 4.0000e-02 eta: 13:45:28 time: 0.3379 data_time: 0.0244 memory: 5826 grad_norm: 3.1786 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7043 loss: 2.7043 2022/10/08 00:48:30 - mmengine - INFO - Epoch(train) [83][1180/2119] lr: 4.0000e-02 eta: 13:45:21 time: 0.3867 data_time: 0.0254 memory: 5826 grad_norm: 3.0743 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6561 loss: 2.6561 2022/10/08 00:48:37 - mmengine - INFO - Epoch(train) [83][1200/2119] lr: 4.0000e-02 eta: 13:45:14 time: 0.3440 data_time: 0.0263 memory: 5826 grad_norm: 3.1438 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6276 loss: 2.6276 2022/10/08 00:48:44 - mmengine - INFO - Epoch(train) [83][1220/2119] lr: 4.0000e-02 eta: 13:45:08 time: 0.3538 data_time: 0.0224 memory: 5826 grad_norm: 3.1080 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.5518 loss: 2.5518 2022/10/08 00:48:51 - mmengine - INFO - Epoch(train) [83][1240/2119] lr: 4.0000e-02 eta: 13:45:00 time: 0.3277 data_time: 0.0228 memory: 5826 grad_norm: 3.1917 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7543 loss: 2.7543 2022/10/08 00:48:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 00:48:59 - mmengine - INFO - Epoch(train) [83][1260/2119] lr: 4.0000e-02 eta: 13:44:54 time: 0.3978 data_time: 0.0212 memory: 5826 grad_norm: 3.1675 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7087 loss: 2.7087 2022/10/08 00:49:06 - mmengine - INFO - Epoch(train) [83][1280/2119] lr: 4.0000e-02 eta: 13:44:48 time: 0.3686 data_time: 0.0224 memory: 5826 grad_norm: 3.1215 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8330 loss: 2.8330 2022/10/08 00:49:14 - mmengine - INFO - Epoch(train) [83][1300/2119] lr: 4.0000e-02 eta: 13:44:41 time: 0.3665 data_time: 0.0235 memory: 5826 grad_norm: 3.1841 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7970 loss: 2.7970 2022/10/08 00:49:20 - mmengine - INFO - Epoch(train) [83][1320/2119] lr: 4.0000e-02 eta: 13:44:33 time: 0.2975 data_time: 0.0250 memory: 5826 grad_norm: 3.0625 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7493 loss: 2.7493 2022/10/08 00:49:28 - mmengine - INFO - Epoch(train) [83][1340/2119] lr: 4.0000e-02 eta: 13:44:27 time: 0.3980 data_time: 0.0207 memory: 5826 grad_norm: 3.1485 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7384 loss: 2.7384 2022/10/08 00:49:34 - mmengine - INFO - Epoch(train) [83][1360/2119] lr: 4.0000e-02 eta: 13:44:20 time: 0.3201 data_time: 0.0246 memory: 5826 grad_norm: 3.1348 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5375 loss: 2.5375 2022/10/08 00:49:40 - mmengine - INFO - Epoch(train) [83][1380/2119] lr: 4.0000e-02 eta: 13:44:13 time: 0.3245 data_time: 0.0324 memory: 5826 grad_norm: 3.1538 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.7493 loss: 2.7493 2022/10/08 00:49:48 - mmengine - INFO - Epoch(train) [83][1400/2119] lr: 4.0000e-02 eta: 13:44:06 time: 0.3843 data_time: 0.0255 memory: 5826 grad_norm: 3.1623 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7157 loss: 2.7157 2022/10/08 00:49:54 - mmengine - INFO - Epoch(train) [83][1420/2119] lr: 4.0000e-02 eta: 13:43:59 time: 0.2936 data_time: 0.0208 memory: 5826 grad_norm: 3.1825 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8378 loss: 2.8378 2022/10/08 00:50:02 - mmengine - INFO - Epoch(train) [83][1440/2119] lr: 4.0000e-02 eta: 13:43:52 time: 0.3877 data_time: 0.0251 memory: 5826 grad_norm: 3.0878 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5845 loss: 2.5845 2022/10/08 00:50:08 - mmengine - INFO - Epoch(train) [83][1460/2119] lr: 4.0000e-02 eta: 13:43:45 time: 0.3117 data_time: 0.0173 memory: 5826 grad_norm: 3.1339 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7460 loss: 2.7460 2022/10/08 00:50:15 - mmengine - INFO - Epoch(train) [83][1480/2119] lr: 4.0000e-02 eta: 13:43:38 time: 0.3627 data_time: 0.0237 memory: 5826 grad_norm: 3.1432 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6876 loss: 2.6876 2022/10/08 00:50:22 - mmengine - INFO - Epoch(train) [83][1500/2119] lr: 4.0000e-02 eta: 13:43:31 time: 0.3245 data_time: 0.0219 memory: 5826 grad_norm: 3.1321 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6126 loss: 2.6126 2022/10/08 00:50:29 - mmengine - INFO - Epoch(train) [83][1520/2119] lr: 4.0000e-02 eta: 13:43:24 time: 0.3790 data_time: 0.0287 memory: 5826 grad_norm: 3.1058 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7118 loss: 2.7118 2022/10/08 00:50:36 - mmengine - INFO - Epoch(train) [83][1540/2119] lr: 4.0000e-02 eta: 13:43:17 time: 0.3464 data_time: 0.0227 memory: 5826 grad_norm: 3.0928 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.4045 loss: 2.4045 2022/10/08 00:50:43 - mmengine - INFO - Epoch(train) [83][1560/2119] lr: 4.0000e-02 eta: 13:43:10 time: 0.3206 data_time: 0.0213 memory: 5826 grad_norm: 3.1248 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6687 loss: 2.6687 2022/10/08 00:50:51 - mmengine - INFO - Epoch(train) [83][1580/2119] lr: 4.0000e-02 eta: 13:43:05 time: 0.4327 data_time: 0.0222 memory: 5826 grad_norm: 3.1531 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8070 loss: 2.8070 2022/10/08 00:50:58 - mmengine - INFO - Epoch(train) [83][1600/2119] lr: 4.0000e-02 eta: 13:42:57 time: 0.3076 data_time: 0.0201 memory: 5826 grad_norm: 3.1221 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7141 loss: 2.7141 2022/10/08 00:51:05 - mmengine - INFO - Epoch(train) [83][1620/2119] lr: 4.0000e-02 eta: 13:42:50 time: 0.3519 data_time: 0.0234 memory: 5826 grad_norm: 3.1284 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6681 loss: 2.6681 2022/10/08 00:51:11 - mmengine - INFO - Epoch(train) [83][1640/2119] lr: 4.0000e-02 eta: 13:42:43 time: 0.3296 data_time: 0.0316 memory: 5826 grad_norm: 3.1507 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8454 loss: 2.8454 2022/10/08 00:51:18 - mmengine - INFO - Epoch(train) [83][1660/2119] lr: 4.0000e-02 eta: 13:42:36 time: 0.3586 data_time: 0.0243 memory: 5826 grad_norm: 3.1842 top1_acc: 0.0625 top5_acc: 0.5625 loss_cls: 2.5963 loss: 2.5963 2022/10/08 00:51:25 - mmengine - INFO - Epoch(train) [83][1680/2119] lr: 4.0000e-02 eta: 13:42:29 time: 0.3366 data_time: 0.0264 memory: 5826 grad_norm: 3.1079 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.5780 loss: 2.5780 2022/10/08 00:51:33 - mmengine - INFO - Epoch(train) [83][1700/2119] lr: 4.0000e-02 eta: 13:42:23 time: 0.3845 data_time: 0.0207 memory: 5826 grad_norm: 3.1739 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8237 loss: 2.8237 2022/10/08 00:51:40 - mmengine - INFO - Epoch(train) [83][1720/2119] lr: 4.0000e-02 eta: 13:42:16 time: 0.3436 data_time: 0.0246 memory: 5826 grad_norm: 3.1362 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7127 loss: 2.7127 2022/10/08 00:51:47 - mmengine - INFO - Epoch(train) [83][1740/2119] lr: 4.0000e-02 eta: 13:42:09 time: 0.3763 data_time: 0.0230 memory: 5826 grad_norm: 3.1672 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8724 loss: 2.8724 2022/10/08 00:51:53 - mmengine - INFO - Epoch(train) [83][1760/2119] lr: 4.0000e-02 eta: 13:42:02 time: 0.3053 data_time: 0.0298 memory: 5826 grad_norm: 3.1416 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8136 loss: 2.8136 2022/10/08 00:52:00 - mmengine - INFO - Epoch(train) [83][1780/2119] lr: 4.0000e-02 eta: 13:41:55 time: 0.3579 data_time: 0.0243 memory: 5826 grad_norm: 3.1191 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9550 loss: 2.9550 2022/10/08 00:52:07 - mmengine - INFO - Epoch(train) [83][1800/2119] lr: 4.0000e-02 eta: 13:41:48 time: 0.3400 data_time: 0.0209 memory: 5826 grad_norm: 3.1577 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.7061 loss: 2.7061 2022/10/08 00:52:15 - mmengine - INFO - Epoch(train) [83][1820/2119] lr: 4.0000e-02 eta: 13:41:42 time: 0.4005 data_time: 0.0293 memory: 5826 grad_norm: 3.1674 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8670 loss: 2.8670 2022/10/08 00:52:22 - mmengine - INFO - Epoch(train) [83][1840/2119] lr: 4.0000e-02 eta: 13:41:35 time: 0.3229 data_time: 0.0216 memory: 5826 grad_norm: 3.1122 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5237 loss: 2.5237 2022/10/08 00:52:29 - mmengine - INFO - Epoch(train) [83][1860/2119] lr: 4.0000e-02 eta: 13:41:28 time: 0.3590 data_time: 0.0233 memory: 5826 grad_norm: 3.1407 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6711 loss: 2.6711 2022/10/08 00:52:36 - mmengine - INFO - Epoch(train) [83][1880/2119] lr: 4.0000e-02 eta: 13:41:21 time: 0.3273 data_time: 0.0223 memory: 5826 grad_norm: 3.0937 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5897 loss: 2.5897 2022/10/08 00:52:43 - mmengine - INFO - Epoch(train) [83][1900/2119] lr: 4.0000e-02 eta: 13:41:14 time: 0.3642 data_time: 0.0173 memory: 5826 grad_norm: 3.1199 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7163 loss: 2.7163 2022/10/08 00:52:49 - mmengine - INFO - Epoch(train) [83][1920/2119] lr: 4.0000e-02 eta: 13:41:06 time: 0.2986 data_time: 0.0241 memory: 5826 grad_norm: 3.1549 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7926 loss: 2.7926 2022/10/08 00:52:56 - mmengine - INFO - Epoch(train) [83][1940/2119] lr: 4.0000e-02 eta: 13:41:00 time: 0.3689 data_time: 0.0260 memory: 5826 grad_norm: 3.1027 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6536 loss: 2.6536 2022/10/08 00:53:03 - mmengine - INFO - Epoch(train) [83][1960/2119] lr: 4.0000e-02 eta: 13:40:53 time: 0.3302 data_time: 0.0226 memory: 5826 grad_norm: 3.0534 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7493 loss: 2.7493 2022/10/08 00:53:10 - mmengine - INFO - Epoch(train) [83][1980/2119] lr: 4.0000e-02 eta: 13:40:46 time: 0.3541 data_time: 0.0197 memory: 5826 grad_norm: 3.1141 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5214 loss: 2.5214 2022/10/08 00:53:17 - mmengine - INFO - Epoch(train) [83][2000/2119] lr: 4.0000e-02 eta: 13:40:39 time: 0.3383 data_time: 0.0212 memory: 5826 grad_norm: 3.1229 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6572 loss: 2.6572 2022/10/08 00:53:24 - mmengine - INFO - Epoch(train) [83][2020/2119] lr: 4.0000e-02 eta: 13:40:32 time: 0.3780 data_time: 0.0227 memory: 5826 grad_norm: 3.1425 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6811 loss: 2.6811 2022/10/08 00:53:31 - mmengine - INFO - Epoch(train) [83][2040/2119] lr: 4.0000e-02 eta: 13:40:25 time: 0.3163 data_time: 0.0230 memory: 5826 grad_norm: 3.0741 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.2606 loss: 2.2606 2022/10/08 00:53:38 - mmengine - INFO - Epoch(train) [83][2060/2119] lr: 4.0000e-02 eta: 13:40:18 time: 0.3654 data_time: 0.0251 memory: 5826 grad_norm: 3.1080 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5286 loss: 2.5286 2022/10/08 00:53:44 - mmengine - INFO - Epoch(train) [83][2080/2119] lr: 4.0000e-02 eta: 13:40:11 time: 0.3154 data_time: 0.0292 memory: 5826 grad_norm: 3.1127 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7860 loss: 2.7860 2022/10/08 00:53:52 - mmengine - INFO - Epoch(train) [83][2100/2119] lr: 4.0000e-02 eta: 13:40:04 time: 0.3832 data_time: 0.0252 memory: 5826 grad_norm: 3.0880 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5997 loss: 2.5997 2022/10/08 00:53:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 00:53:57 - mmengine - INFO - Epoch(train) [83][2119/2119] lr: 4.0000e-02 eta: 13:40:04 time: 0.2910 data_time: 0.0198 memory: 5826 grad_norm: 3.1641 top1_acc: 0.3000 top5_acc: 0.5000 loss_cls: 2.8776 loss: 2.8776 2022/10/08 00:54:08 - mmengine - INFO - Epoch(train) [84][20/2119] lr: 4.0000e-02 eta: 13:39:48 time: 0.5087 data_time: 0.2766 memory: 5826 grad_norm: 3.1244 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.8051 loss: 2.8051 2022/10/08 00:54:15 - mmengine - INFO - Epoch(train) [84][40/2119] lr: 4.0000e-02 eta: 13:39:42 time: 0.3686 data_time: 0.1437 memory: 5826 grad_norm: 3.1213 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8036 loss: 2.8036 2022/10/08 00:54:23 - mmengine - INFO - Epoch(train) [84][60/2119] lr: 4.0000e-02 eta: 13:39:35 time: 0.3929 data_time: 0.1409 memory: 5826 grad_norm: 3.0467 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5390 loss: 2.5390 2022/10/08 00:54:29 - mmengine - INFO - Epoch(train) [84][80/2119] lr: 4.0000e-02 eta: 13:39:28 time: 0.3080 data_time: 0.0807 memory: 5826 grad_norm: 3.1211 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5004 loss: 2.5004 2022/10/08 00:54:37 - mmengine - INFO - Epoch(train) [84][100/2119] lr: 4.0000e-02 eta: 13:39:22 time: 0.4016 data_time: 0.1726 memory: 5826 grad_norm: 3.0502 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5585 loss: 2.5585 2022/10/08 00:54:44 - mmengine - INFO - Epoch(train) [84][120/2119] lr: 4.0000e-02 eta: 13:39:15 time: 0.3268 data_time: 0.0968 memory: 5826 grad_norm: 3.1501 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6390 loss: 2.6390 2022/10/08 00:54:45 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 00:54:51 - mmengine - INFO - Epoch(train) [84][140/2119] lr: 4.0000e-02 eta: 13:39:08 time: 0.3631 data_time: 0.1134 memory: 5826 grad_norm: 3.1592 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5784 loss: 2.5784 2022/10/08 00:54:57 - mmengine - INFO - Epoch(train) [84][160/2119] lr: 4.0000e-02 eta: 13:39:00 time: 0.3097 data_time: 0.0724 memory: 5826 grad_norm: 3.1582 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6985 loss: 2.6985 2022/10/08 00:55:04 - mmengine - INFO - Epoch(train) [84][180/2119] lr: 4.0000e-02 eta: 13:38:53 time: 0.3377 data_time: 0.0838 memory: 5826 grad_norm: 3.0826 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7466 loss: 2.7466 2022/10/08 00:55:10 - mmengine - INFO - Epoch(train) [84][200/2119] lr: 4.0000e-02 eta: 13:38:46 time: 0.3291 data_time: 0.0323 memory: 5826 grad_norm: 3.1683 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6857 loss: 2.6857 2022/10/08 00:55:18 - mmengine - INFO - Epoch(train) [84][220/2119] lr: 4.0000e-02 eta: 13:38:39 time: 0.3619 data_time: 0.0424 memory: 5826 grad_norm: 3.1438 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5297 loss: 2.5297 2022/10/08 00:55:25 - mmengine - INFO - Epoch(train) [84][240/2119] lr: 4.0000e-02 eta: 13:38:33 time: 0.3590 data_time: 0.0207 memory: 5826 grad_norm: 3.1000 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6421 loss: 2.6421 2022/10/08 00:55:31 - mmengine - INFO - Epoch(train) [84][260/2119] lr: 4.0000e-02 eta: 13:38:25 time: 0.3241 data_time: 0.0212 memory: 5826 grad_norm: 3.0944 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5066 loss: 2.5066 2022/10/08 00:55:40 - mmengine - INFO - Epoch(train) [84][280/2119] lr: 4.0000e-02 eta: 13:38:20 time: 0.4337 data_time: 0.0196 memory: 5826 grad_norm: 3.1005 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6857 loss: 2.6857 2022/10/08 00:55:46 - mmengine - INFO - Epoch(train) [84][300/2119] lr: 4.0000e-02 eta: 13:38:12 time: 0.2810 data_time: 0.0170 memory: 5826 grad_norm: 3.1833 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8810 loss: 2.8810 2022/10/08 00:55:53 - mmengine - INFO - Epoch(train) [84][320/2119] lr: 4.0000e-02 eta: 13:38:05 time: 0.3509 data_time: 0.0250 memory: 5826 grad_norm: 3.1574 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6365 loss: 2.6365 2022/10/08 00:56:00 - mmengine - INFO - Epoch(train) [84][340/2119] lr: 4.0000e-02 eta: 13:37:58 time: 0.3596 data_time: 0.0231 memory: 5826 grad_norm: 3.1916 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4965 loss: 2.4965 2022/10/08 00:56:07 - mmengine - INFO - Epoch(train) [84][360/2119] lr: 4.0000e-02 eta: 13:37:52 time: 0.3728 data_time: 0.0252 memory: 5826 grad_norm: 3.0861 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4267 loss: 2.4267 2022/10/08 00:56:16 - mmengine - INFO - Epoch(train) [84][380/2119] lr: 4.0000e-02 eta: 13:37:46 time: 0.4080 data_time: 0.0184 memory: 5826 grad_norm: 3.0960 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7525 loss: 2.7525 2022/10/08 00:56:22 - mmengine - INFO - Epoch(train) [84][400/2119] lr: 4.0000e-02 eta: 13:37:39 time: 0.3263 data_time: 0.0255 memory: 5826 grad_norm: 3.1718 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9156 loss: 2.9156 2022/10/08 00:56:29 - mmengine - INFO - Epoch(train) [84][420/2119] lr: 4.0000e-02 eta: 13:37:32 time: 0.3452 data_time: 0.0226 memory: 5826 grad_norm: 3.1773 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.6321 loss: 2.6321 2022/10/08 00:56:35 - mmengine - INFO - Epoch(train) [84][440/2119] lr: 4.0000e-02 eta: 13:37:24 time: 0.3179 data_time: 0.0299 memory: 5826 grad_norm: 3.0944 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8773 loss: 2.8773 2022/10/08 00:56:42 - mmengine - INFO - Epoch(train) [84][460/2119] lr: 4.0000e-02 eta: 13:37:17 time: 0.3471 data_time: 0.0280 memory: 5826 grad_norm: 3.0947 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5707 loss: 2.5707 2022/10/08 00:56:49 - mmengine - INFO - Epoch(train) [84][480/2119] lr: 4.0000e-02 eta: 13:37:10 time: 0.3291 data_time: 0.0194 memory: 5826 grad_norm: 3.1214 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5970 loss: 2.5970 2022/10/08 00:56:56 - mmengine - INFO - Epoch(train) [84][500/2119] lr: 4.0000e-02 eta: 13:37:04 time: 0.3700 data_time: 0.0235 memory: 5826 grad_norm: 3.1428 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5869 loss: 2.5869 2022/10/08 00:57:03 - mmengine - INFO - Epoch(train) [84][520/2119] lr: 4.0000e-02 eta: 13:36:57 time: 0.3382 data_time: 0.0254 memory: 5826 grad_norm: 3.1272 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6889 loss: 2.6889 2022/10/08 00:57:11 - mmengine - INFO - Epoch(train) [84][540/2119] lr: 4.0000e-02 eta: 13:36:50 time: 0.3763 data_time: 0.0253 memory: 5826 grad_norm: 3.1895 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.6684 loss: 2.6684 2022/10/08 00:57:17 - mmengine - INFO - Epoch(train) [84][560/2119] lr: 4.0000e-02 eta: 13:36:43 time: 0.3297 data_time: 0.0308 memory: 5826 grad_norm: 3.1592 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7599 loss: 2.7599 2022/10/08 00:57:25 - mmengine - INFO - Epoch(train) [84][580/2119] lr: 4.0000e-02 eta: 13:36:37 time: 0.3868 data_time: 0.0202 memory: 5826 grad_norm: 3.1764 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7745 loss: 2.7745 2022/10/08 00:57:32 - mmengine - INFO - Epoch(train) [84][600/2119] lr: 4.0000e-02 eta: 13:36:30 time: 0.3569 data_time: 0.0254 memory: 5826 grad_norm: 3.1038 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7281 loss: 2.7281 2022/10/08 00:57:39 - mmengine - INFO - Epoch(train) [84][620/2119] lr: 4.0000e-02 eta: 13:36:23 time: 0.3303 data_time: 0.0235 memory: 5826 grad_norm: 3.0678 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7766 loss: 2.7766 2022/10/08 00:57:46 - mmengine - INFO - Epoch(train) [84][640/2119] lr: 4.0000e-02 eta: 13:36:16 time: 0.3559 data_time: 0.0248 memory: 5826 grad_norm: 3.1548 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7074 loss: 2.7074 2022/10/08 00:57:53 - mmengine - INFO - Epoch(train) [84][660/2119] lr: 4.0000e-02 eta: 13:36:09 time: 0.3514 data_time: 0.0214 memory: 5826 grad_norm: 3.1607 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6562 loss: 2.6562 2022/10/08 00:57:59 - mmengine - INFO - Epoch(train) [84][680/2119] lr: 4.0000e-02 eta: 13:36:02 time: 0.3130 data_time: 0.0237 memory: 5826 grad_norm: 3.1580 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8030 loss: 2.8030 2022/10/08 00:58:06 - mmengine - INFO - Epoch(train) [84][700/2119] lr: 4.0000e-02 eta: 13:35:55 time: 0.3676 data_time: 0.0202 memory: 5826 grad_norm: 3.1294 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8863 loss: 2.8863 2022/10/08 00:58:13 - mmengine - INFO - Epoch(train) [84][720/2119] lr: 4.0000e-02 eta: 13:35:48 time: 0.3496 data_time: 0.0223 memory: 5826 grad_norm: 3.1069 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6541 loss: 2.6541 2022/10/08 00:58:21 - mmengine - INFO - Epoch(train) [84][740/2119] lr: 4.0000e-02 eta: 13:35:41 time: 0.3537 data_time: 0.0285 memory: 5826 grad_norm: 3.1126 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9005 loss: 2.9005 2022/10/08 00:58:27 - mmengine - INFO - Epoch(train) [84][760/2119] lr: 4.0000e-02 eta: 13:35:34 time: 0.3472 data_time: 0.0223 memory: 5826 grad_norm: 3.0993 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5337 loss: 2.5337 2022/10/08 00:58:34 - mmengine - INFO - Epoch(train) [84][780/2119] lr: 4.0000e-02 eta: 13:35:27 time: 0.3424 data_time: 0.0272 memory: 5826 grad_norm: 3.1231 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7937 loss: 2.7937 2022/10/08 00:58:42 - mmengine - INFO - Epoch(train) [84][800/2119] lr: 4.0000e-02 eta: 13:35:21 time: 0.4064 data_time: 0.0244 memory: 5826 grad_norm: 3.1526 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6066 loss: 2.6066 2022/10/08 00:58:50 - mmengine - INFO - Epoch(train) [84][820/2119] lr: 4.0000e-02 eta: 13:35:15 time: 0.3641 data_time: 0.0191 memory: 5826 grad_norm: 3.1972 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7431 loss: 2.7431 2022/10/08 00:58:57 - mmengine - INFO - Epoch(train) [84][840/2119] lr: 4.0000e-02 eta: 13:35:08 time: 0.3514 data_time: 0.0253 memory: 5826 grad_norm: 3.1388 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9000 loss: 2.9000 2022/10/08 00:59:04 - mmengine - INFO - Epoch(train) [84][860/2119] lr: 4.0000e-02 eta: 13:35:01 time: 0.3358 data_time: 0.0217 memory: 5826 grad_norm: 3.1479 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8481 loss: 2.8481 2022/10/08 00:59:12 - mmengine - INFO - Epoch(train) [84][880/2119] lr: 4.0000e-02 eta: 13:34:55 time: 0.4085 data_time: 0.0255 memory: 5826 grad_norm: 3.1921 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9017 loss: 2.9017 2022/10/08 00:59:17 - mmengine - INFO - Epoch(train) [84][900/2119] lr: 4.0000e-02 eta: 13:34:46 time: 0.2531 data_time: 0.0210 memory: 5826 grad_norm: 3.1511 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.9958 loss: 2.9958 2022/10/08 00:59:24 - mmengine - INFO - Epoch(train) [84][920/2119] lr: 4.0000e-02 eta: 13:34:40 time: 0.3490 data_time: 0.0391 memory: 5826 grad_norm: 3.1783 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7435 loss: 2.7435 2022/10/08 00:59:32 - mmengine - INFO - Epoch(train) [84][940/2119] lr: 4.0000e-02 eta: 13:34:33 time: 0.3968 data_time: 0.1214 memory: 5826 grad_norm: 3.1792 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.4191 loss: 2.4191 2022/10/08 00:59:38 - mmengine - INFO - Epoch(train) [84][960/2119] lr: 4.0000e-02 eta: 13:34:26 time: 0.3354 data_time: 0.0999 memory: 5826 grad_norm: 3.1144 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6915 loss: 2.6915 2022/10/08 00:59:46 - mmengine - INFO - Epoch(train) [84][980/2119] lr: 4.0000e-02 eta: 13:34:20 time: 0.3657 data_time: 0.1105 memory: 5826 grad_norm: 3.0807 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7807 loss: 2.7807 2022/10/08 00:59:52 - mmengine - INFO - Epoch(train) [84][1000/2119] lr: 4.0000e-02 eta: 13:34:13 time: 0.3320 data_time: 0.0662 memory: 5826 grad_norm: 3.1616 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6255 loss: 2.6255 2022/10/08 00:59:59 - mmengine - INFO - Epoch(train) [84][1020/2119] lr: 4.0000e-02 eta: 13:34:06 time: 0.3491 data_time: 0.0244 memory: 5826 grad_norm: 3.1727 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8025 loss: 2.8025 2022/10/08 01:00:06 - mmengine - INFO - Epoch(train) [84][1040/2119] lr: 4.0000e-02 eta: 13:33:58 time: 0.3247 data_time: 0.0250 memory: 5826 grad_norm: 3.1224 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8277 loss: 2.8277 2022/10/08 01:00:13 - mmengine - INFO - Epoch(train) [84][1060/2119] lr: 4.0000e-02 eta: 13:33:52 time: 0.3691 data_time: 0.0178 memory: 5826 grad_norm: 3.1649 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7080 loss: 2.7080 2022/10/08 01:00:20 - mmengine - INFO - Epoch(train) [84][1080/2119] lr: 4.0000e-02 eta: 13:33:45 time: 0.3412 data_time: 0.0254 memory: 5826 grad_norm: 3.1339 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6167 loss: 2.6167 2022/10/08 01:00:28 - mmengine - INFO - Epoch(train) [84][1100/2119] lr: 4.0000e-02 eta: 13:33:39 time: 0.3968 data_time: 0.0213 memory: 5826 grad_norm: 3.1725 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6432 loss: 2.6432 2022/10/08 01:00:35 - mmengine - INFO - Epoch(train) [84][1120/2119] lr: 4.0000e-02 eta: 13:33:32 time: 0.3470 data_time: 0.0261 memory: 5826 grad_norm: 3.1439 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6561 loss: 2.6561 2022/10/08 01:00:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 01:00:43 - mmengine - INFO - Epoch(train) [84][1140/2119] lr: 4.0000e-02 eta: 13:33:26 time: 0.3923 data_time: 0.0193 memory: 5826 grad_norm: 3.1078 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6194 loss: 2.6194 2022/10/08 01:00:48 - mmengine - INFO - Epoch(train) [84][1160/2119] lr: 4.0000e-02 eta: 13:33:18 time: 0.2829 data_time: 0.0205 memory: 5826 grad_norm: 3.0834 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7549 loss: 2.7549 2022/10/08 01:00:57 - mmengine - INFO - Epoch(train) [84][1180/2119] lr: 4.0000e-02 eta: 13:33:12 time: 0.4033 data_time: 0.0215 memory: 5826 grad_norm: 3.1427 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7067 loss: 2.7067 2022/10/08 01:01:03 - mmengine - INFO - Epoch(train) [84][1200/2119] lr: 4.0000e-02 eta: 13:33:04 time: 0.3335 data_time: 0.0262 memory: 5826 grad_norm: 3.1915 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7023 loss: 2.7023 2022/10/08 01:01:11 - mmengine - INFO - Epoch(train) [84][1220/2119] lr: 4.0000e-02 eta: 13:32:58 time: 0.3818 data_time: 0.0201 memory: 5826 grad_norm: 3.1592 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7760 loss: 2.7760 2022/10/08 01:01:17 - mmengine - INFO - Epoch(train) [84][1240/2119] lr: 4.0000e-02 eta: 13:32:50 time: 0.2948 data_time: 0.0206 memory: 5826 grad_norm: 3.1145 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7646 loss: 2.7646 2022/10/08 01:01:25 - mmengine - INFO - Epoch(train) [84][1260/2119] lr: 4.0000e-02 eta: 13:32:44 time: 0.3945 data_time: 0.0255 memory: 5826 grad_norm: 3.1099 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7710 loss: 2.7710 2022/10/08 01:01:31 - mmengine - INFO - Epoch(train) [84][1280/2119] lr: 4.0000e-02 eta: 13:32:37 time: 0.3302 data_time: 0.0287 memory: 5826 grad_norm: 3.0711 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.7128 loss: 2.7128 2022/10/08 01:01:38 - mmengine - INFO - Epoch(train) [84][1300/2119] lr: 4.0000e-02 eta: 13:32:30 time: 0.3461 data_time: 0.0246 memory: 5826 grad_norm: 3.1163 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8009 loss: 2.8009 2022/10/08 01:01:46 - mmengine - INFO - Epoch(train) [84][1320/2119] lr: 4.0000e-02 eta: 13:32:23 time: 0.3700 data_time: 0.0286 memory: 5826 grad_norm: 3.0748 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4450 loss: 2.4450 2022/10/08 01:01:53 - mmengine - INFO - Epoch(train) [84][1340/2119] lr: 4.0000e-02 eta: 13:32:17 time: 0.3797 data_time: 0.0222 memory: 5826 grad_norm: 3.1212 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6876 loss: 2.6876 2022/10/08 01:02:00 - mmengine - INFO - Epoch(train) [84][1360/2119] lr: 4.0000e-02 eta: 13:32:10 time: 0.3300 data_time: 0.0209 memory: 5826 grad_norm: 3.1447 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9185 loss: 2.9185 2022/10/08 01:02:07 - mmengine - INFO - Epoch(train) [84][1380/2119] lr: 4.0000e-02 eta: 13:32:03 time: 0.3566 data_time: 0.0217 memory: 5826 grad_norm: 3.1934 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9839 loss: 2.9839 2022/10/08 01:02:13 - mmengine - INFO - Epoch(train) [84][1400/2119] lr: 4.0000e-02 eta: 13:31:55 time: 0.3059 data_time: 0.0242 memory: 5826 grad_norm: 3.1431 top1_acc: 0.2500 top5_acc: 0.3125 loss_cls: 2.6939 loss: 2.6939 2022/10/08 01:02:20 - mmengine - INFO - Epoch(train) [84][1420/2119] lr: 4.0000e-02 eta: 13:31:49 time: 0.3511 data_time: 0.0244 memory: 5826 grad_norm: 3.1400 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6012 loss: 2.6012 2022/10/08 01:02:27 - mmengine - INFO - Epoch(train) [84][1440/2119] lr: 4.0000e-02 eta: 13:31:42 time: 0.3549 data_time: 0.0207 memory: 5826 grad_norm: 3.1502 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6348 loss: 2.6348 2022/10/08 01:02:35 - mmengine - INFO - Epoch(train) [84][1460/2119] lr: 4.0000e-02 eta: 13:31:35 time: 0.3764 data_time: 0.0257 memory: 5826 grad_norm: 3.1710 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9019 loss: 2.9019 2022/10/08 01:02:42 - mmengine - INFO - Epoch(train) [84][1480/2119] lr: 4.0000e-02 eta: 13:31:29 time: 0.3580 data_time: 0.0254 memory: 5826 grad_norm: 3.1042 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7408 loss: 2.7408 2022/10/08 01:02:49 - mmengine - INFO - Epoch(train) [84][1500/2119] lr: 4.0000e-02 eta: 13:31:22 time: 0.3609 data_time: 0.0209 memory: 5826 grad_norm: 3.1384 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7853 loss: 2.7853 2022/10/08 01:02:56 - mmengine - INFO - Epoch(train) [84][1520/2119] lr: 4.0000e-02 eta: 13:31:15 time: 0.3276 data_time: 0.0223 memory: 5826 grad_norm: 3.1347 top1_acc: 0.3125 top5_acc: 0.8750 loss_cls: 2.7117 loss: 2.7117 2022/10/08 01:03:04 - mmengine - INFO - Epoch(train) [84][1540/2119] lr: 4.0000e-02 eta: 13:31:09 time: 0.4320 data_time: 0.0203 memory: 5826 grad_norm: 3.0902 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3382 loss: 2.3382 2022/10/08 01:03:11 - mmengine - INFO - Epoch(train) [84][1560/2119] lr: 4.0000e-02 eta: 13:31:02 time: 0.3530 data_time: 0.0304 memory: 5826 grad_norm: 3.1603 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6749 loss: 2.6749 2022/10/08 01:03:19 - mmengine - INFO - Epoch(train) [84][1580/2119] lr: 4.0000e-02 eta: 13:30:56 time: 0.3890 data_time: 0.0195 memory: 5826 grad_norm: 3.1112 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7667 loss: 2.7667 2022/10/08 01:03:26 - mmengine - INFO - Epoch(train) [84][1600/2119] lr: 4.0000e-02 eta: 13:30:49 time: 0.3521 data_time: 0.0202 memory: 5826 grad_norm: 3.1334 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5832 loss: 2.5832 2022/10/08 01:03:34 - mmengine - INFO - Epoch(train) [84][1620/2119] lr: 4.0000e-02 eta: 13:30:43 time: 0.3707 data_time: 0.0212 memory: 5826 grad_norm: 3.1695 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7803 loss: 2.7803 2022/10/08 01:03:40 - mmengine - INFO - Epoch(train) [84][1640/2119] lr: 4.0000e-02 eta: 13:30:35 time: 0.3293 data_time: 0.0214 memory: 5826 grad_norm: 3.1081 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9251 loss: 2.9251 2022/10/08 01:03:48 - mmengine - INFO - Epoch(train) [84][1660/2119] lr: 4.0000e-02 eta: 13:30:29 time: 0.3644 data_time: 0.0241 memory: 5826 grad_norm: 3.1462 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6773 loss: 2.6773 2022/10/08 01:03:55 - mmengine - INFO - Epoch(train) [84][1680/2119] lr: 4.0000e-02 eta: 13:30:22 time: 0.3574 data_time: 0.0215 memory: 5826 grad_norm: 3.1317 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.9116 loss: 2.9116 2022/10/08 01:04:02 - mmengine - INFO - Epoch(train) [84][1700/2119] lr: 4.0000e-02 eta: 13:30:15 time: 0.3621 data_time: 0.0260 memory: 5826 grad_norm: 3.1336 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7187 loss: 2.7187 2022/10/08 01:04:08 - mmengine - INFO - Epoch(train) [84][1720/2119] lr: 4.0000e-02 eta: 13:30:08 time: 0.3113 data_time: 0.0245 memory: 5826 grad_norm: 3.0964 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8312 loss: 2.8312 2022/10/08 01:04:16 - mmengine - INFO - Epoch(train) [84][1740/2119] lr: 4.0000e-02 eta: 13:30:02 time: 0.4063 data_time: 0.0242 memory: 5826 grad_norm: 3.1429 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7889 loss: 2.7889 2022/10/08 01:04:23 - mmengine - INFO - Epoch(train) [84][1760/2119] lr: 4.0000e-02 eta: 13:29:55 time: 0.3279 data_time: 0.0291 memory: 5826 grad_norm: 3.1449 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6678 loss: 2.6678 2022/10/08 01:04:31 - mmengine - INFO - Epoch(train) [84][1780/2119] lr: 4.0000e-02 eta: 13:29:49 time: 0.4028 data_time: 0.0222 memory: 5826 grad_norm: 3.1615 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6817 loss: 2.6817 2022/10/08 01:04:37 - mmengine - INFO - Epoch(train) [84][1800/2119] lr: 4.0000e-02 eta: 13:29:41 time: 0.2891 data_time: 0.0198 memory: 5826 grad_norm: 3.1189 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7644 loss: 2.7644 2022/10/08 01:04:45 - mmengine - INFO - Epoch(train) [84][1820/2119] lr: 4.0000e-02 eta: 13:29:35 time: 0.4178 data_time: 0.0219 memory: 5826 grad_norm: 3.1236 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6931 loss: 2.6931 2022/10/08 01:04:52 - mmengine - INFO - Epoch(train) [84][1840/2119] lr: 4.0000e-02 eta: 13:29:28 time: 0.3587 data_time: 0.0223 memory: 5826 grad_norm: 3.0975 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7370 loss: 2.7370 2022/10/08 01:04:59 - mmengine - INFO - Epoch(train) [84][1860/2119] lr: 4.0000e-02 eta: 13:29:21 time: 0.3572 data_time: 0.0245 memory: 5826 grad_norm: 3.1016 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7100 loss: 2.7100 2022/10/08 01:05:07 - mmengine - INFO - Epoch(train) [84][1880/2119] lr: 4.0000e-02 eta: 13:29:15 time: 0.3746 data_time: 0.0247 memory: 5826 grad_norm: 3.1281 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8141 loss: 2.8141 2022/10/08 01:05:15 - mmengine - INFO - Epoch(train) [84][1900/2119] lr: 4.0000e-02 eta: 13:29:09 time: 0.4052 data_time: 0.0262 memory: 5826 grad_norm: 3.1069 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6572 loss: 2.6572 2022/10/08 01:05:21 - mmengine - INFO - Epoch(train) [84][1920/2119] lr: 4.0000e-02 eta: 13:29:01 time: 0.3163 data_time: 0.0286 memory: 5826 grad_norm: 3.0854 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7047 loss: 2.7047 2022/10/08 01:05:28 - mmengine - INFO - Epoch(train) [84][1940/2119] lr: 4.0000e-02 eta: 13:28:54 time: 0.3419 data_time: 0.0306 memory: 5826 grad_norm: 3.1286 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4730 loss: 2.4730 2022/10/08 01:05:35 - mmengine - INFO - Epoch(train) [84][1960/2119] lr: 4.0000e-02 eta: 13:28:47 time: 0.3250 data_time: 0.0254 memory: 5826 grad_norm: 3.1709 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7806 loss: 2.7806 2022/10/08 01:05:42 - mmengine - INFO - Epoch(train) [84][1980/2119] lr: 4.0000e-02 eta: 13:28:41 time: 0.3871 data_time: 0.0219 memory: 5826 grad_norm: 3.0996 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8501 loss: 2.8501 2022/10/08 01:05:49 - mmengine - INFO - Epoch(train) [84][2000/2119] lr: 4.0000e-02 eta: 13:28:34 time: 0.3235 data_time: 0.0221 memory: 5826 grad_norm: 3.1197 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5113 loss: 2.5113 2022/10/08 01:05:55 - mmengine - INFO - Epoch(train) [84][2020/2119] lr: 4.0000e-02 eta: 13:28:26 time: 0.3116 data_time: 0.0216 memory: 5826 grad_norm: 3.1466 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5217 loss: 2.5217 2022/10/08 01:06:04 - mmengine - INFO - Epoch(train) [84][2040/2119] lr: 4.0000e-02 eta: 13:28:20 time: 0.4180 data_time: 0.0203 memory: 5826 grad_norm: 3.0820 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8143 loss: 2.8143 2022/10/08 01:06:11 - mmengine - INFO - Epoch(train) [84][2060/2119] lr: 4.0000e-02 eta: 13:28:14 time: 0.3906 data_time: 0.0177 memory: 5826 grad_norm: 3.1626 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8477 loss: 2.8477 2022/10/08 01:06:19 - mmengine - INFO - Epoch(train) [84][2080/2119] lr: 4.0000e-02 eta: 13:28:07 time: 0.3674 data_time: 0.0215 memory: 5826 grad_norm: 3.1516 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6271 loss: 2.6271 2022/10/08 01:06:26 - mmengine - INFO - Epoch(train) [84][2100/2119] lr: 4.0000e-02 eta: 13:28:01 time: 0.3570 data_time: 0.0189 memory: 5826 grad_norm: 3.1468 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8147 loss: 2.8147 2022/10/08 01:06:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 01:06:32 - mmengine - INFO - Epoch(train) [84][2119/2119] lr: 4.0000e-02 eta: 13:28:01 time: 0.3623 data_time: 0.0245 memory: 5826 grad_norm: 3.1723 top1_acc: 0.3000 top5_acc: 0.5000 loss_cls: 2.6275 loss: 2.6275 2022/10/08 01:06:32 - mmengine - INFO - Saving checkpoint at 84 epochs 2022/10/08 01:06:47 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 01:06:52 - mmengine - INFO - Epoch(train) [85][20/2119] lr: 4.0000e-02 eta: 13:27:44 time: 0.4538 data_time: 0.2140 memory: 5826 grad_norm: 3.0488 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2939 loss: 2.2939 2022/10/08 01:06:58 - mmengine - INFO - Epoch(train) [85][40/2119] lr: 4.0000e-02 eta: 13:27:36 time: 0.3247 data_time: 0.0915 memory: 5826 grad_norm: 3.0982 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6104 loss: 2.6104 2022/10/08 01:07:05 - mmengine - INFO - Epoch(train) [85][60/2119] lr: 4.0000e-02 eta: 13:27:29 time: 0.3366 data_time: 0.0944 memory: 5826 grad_norm: 3.0781 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7308 loss: 2.7308 2022/10/08 01:07:12 - mmengine - INFO - Epoch(train) [85][80/2119] lr: 4.0000e-02 eta: 13:27:22 time: 0.3362 data_time: 0.0286 memory: 5826 grad_norm: 3.0876 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7161 loss: 2.7161 2022/10/08 01:07:20 - mmengine - INFO - Epoch(train) [85][100/2119] lr: 4.0000e-02 eta: 13:27:16 time: 0.3876 data_time: 0.0204 memory: 5826 grad_norm: 3.1395 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7365 loss: 2.7365 2022/10/08 01:07:26 - mmengine - INFO - Epoch(train) [85][120/2119] lr: 4.0000e-02 eta: 13:27:09 time: 0.3296 data_time: 0.0230 memory: 5826 grad_norm: 3.1232 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9182 loss: 2.9182 2022/10/08 01:07:33 - mmengine - INFO - Epoch(train) [85][140/2119] lr: 4.0000e-02 eta: 13:27:01 time: 0.3183 data_time: 0.0280 memory: 5826 grad_norm: 3.0609 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4864 loss: 2.4864 2022/10/08 01:07:39 - mmengine - INFO - Epoch(train) [85][160/2119] lr: 4.0000e-02 eta: 13:26:54 time: 0.3295 data_time: 0.0290 memory: 5826 grad_norm: 3.0857 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7434 loss: 2.7434 2022/10/08 01:07:46 - mmengine - INFO - Epoch(train) [85][180/2119] lr: 4.0000e-02 eta: 13:26:47 time: 0.3415 data_time: 0.0282 memory: 5826 grad_norm: 3.1263 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7551 loss: 2.7551 2022/10/08 01:07:54 - mmengine - INFO - Epoch(train) [85][200/2119] lr: 4.0000e-02 eta: 13:26:41 time: 0.3697 data_time: 0.0258 memory: 5826 grad_norm: 3.1374 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8429 loss: 2.8429 2022/10/08 01:08:00 - mmengine - INFO - Epoch(train) [85][220/2119] lr: 4.0000e-02 eta: 13:26:34 time: 0.3473 data_time: 0.0235 memory: 5826 grad_norm: 3.1237 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9871 loss: 2.9871 2022/10/08 01:08:07 - mmengine - INFO - Epoch(train) [85][240/2119] lr: 4.0000e-02 eta: 13:26:27 time: 0.3368 data_time: 0.0257 memory: 5826 grad_norm: 3.1503 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.7051 loss: 2.7051 2022/10/08 01:08:14 - mmengine - INFO - Epoch(train) [85][260/2119] lr: 4.0000e-02 eta: 13:26:19 time: 0.3254 data_time: 0.0249 memory: 5826 grad_norm: 3.1666 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6703 loss: 2.6703 2022/10/08 01:08:21 - mmengine - INFO - Epoch(train) [85][280/2119] lr: 4.0000e-02 eta: 13:26:13 time: 0.3686 data_time: 0.0216 memory: 5826 grad_norm: 3.1207 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4517 loss: 2.4517 2022/10/08 01:08:29 - mmengine - INFO - Epoch(train) [85][300/2119] lr: 4.0000e-02 eta: 13:26:07 time: 0.4116 data_time: 0.0208 memory: 5826 grad_norm: 3.1232 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7480 loss: 2.7480 2022/10/08 01:08:36 - mmengine - INFO - Epoch(train) [85][320/2119] lr: 4.0000e-02 eta: 13:25:59 time: 0.3150 data_time: 0.0240 memory: 5826 grad_norm: 3.1203 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5372 loss: 2.5372 2022/10/08 01:08:43 - mmengine - INFO - Epoch(train) [85][340/2119] lr: 4.0000e-02 eta: 13:25:53 time: 0.3498 data_time: 0.0228 memory: 5826 grad_norm: 3.1934 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8334 loss: 2.8334 2022/10/08 01:08:49 - mmengine - INFO - Epoch(train) [85][360/2119] lr: 4.0000e-02 eta: 13:25:45 time: 0.3337 data_time: 0.0209 memory: 5826 grad_norm: 3.1891 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5154 loss: 2.5154 2022/10/08 01:08:56 - mmengine - INFO - Epoch(train) [85][380/2119] lr: 4.0000e-02 eta: 13:25:38 time: 0.3462 data_time: 0.0198 memory: 5826 grad_norm: 3.1327 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5636 loss: 2.5636 2022/10/08 01:09:03 - mmengine - INFO - Epoch(train) [85][400/2119] lr: 4.0000e-02 eta: 13:25:32 time: 0.3442 data_time: 0.0227 memory: 5826 grad_norm: 3.1188 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6377 loss: 2.6377 2022/10/08 01:09:11 - mmengine - INFO - Epoch(train) [85][420/2119] lr: 4.0000e-02 eta: 13:25:25 time: 0.3912 data_time: 0.0228 memory: 5826 grad_norm: 3.0882 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6904 loss: 2.6904 2022/10/08 01:09:17 - mmengine - INFO - Epoch(train) [85][440/2119] lr: 4.0000e-02 eta: 13:25:18 time: 0.3130 data_time: 0.0212 memory: 5826 grad_norm: 3.1303 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7629 loss: 2.7629 2022/10/08 01:09:24 - mmengine - INFO - Epoch(train) [85][460/2119] lr: 4.0000e-02 eta: 13:25:11 time: 0.3537 data_time: 0.0264 memory: 5826 grad_norm: 3.1625 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.7822 loss: 2.7822 2022/10/08 01:09:32 - mmengine - INFO - Epoch(train) [85][480/2119] lr: 4.0000e-02 eta: 13:25:04 time: 0.3640 data_time: 0.0222 memory: 5826 grad_norm: 3.1264 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6712 loss: 2.6712 2022/10/08 01:09:38 - mmengine - INFO - Epoch(train) [85][500/2119] lr: 4.0000e-02 eta: 13:24:57 time: 0.3269 data_time: 0.0260 memory: 5826 grad_norm: 3.1126 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7005 loss: 2.7005 2022/10/08 01:09:46 - mmengine - INFO - Epoch(train) [85][520/2119] lr: 4.0000e-02 eta: 13:24:51 time: 0.3740 data_time: 0.0234 memory: 5826 grad_norm: 3.0760 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7259 loss: 2.7259 2022/10/08 01:09:53 - mmengine - INFO - Epoch(train) [85][540/2119] lr: 4.0000e-02 eta: 13:24:44 time: 0.3759 data_time: 0.0247 memory: 5826 grad_norm: 3.1316 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9405 loss: 2.9405 2022/10/08 01:10:00 - mmengine - INFO - Epoch(train) [85][560/2119] lr: 4.0000e-02 eta: 13:24:37 time: 0.3650 data_time: 0.0199 memory: 5826 grad_norm: 3.0994 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9145 loss: 2.9145 2022/10/08 01:10:07 - mmengine - INFO - Epoch(train) [85][580/2119] lr: 4.0000e-02 eta: 13:24:30 time: 0.3189 data_time: 0.0254 memory: 5826 grad_norm: 3.1109 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.5687 loss: 2.5687 2022/10/08 01:10:14 - mmengine - INFO - Epoch(train) [85][600/2119] lr: 4.0000e-02 eta: 13:24:23 time: 0.3530 data_time: 0.0253 memory: 5826 grad_norm: 3.1238 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6483 loss: 2.6483 2022/10/08 01:10:21 - mmengine - INFO - Epoch(train) [85][620/2119] lr: 4.0000e-02 eta: 13:24:16 time: 0.3420 data_time: 0.0224 memory: 5826 grad_norm: 3.1090 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9285 loss: 2.9285 2022/10/08 01:10:28 - mmengine - INFO - Epoch(train) [85][640/2119] lr: 4.0000e-02 eta: 13:24:10 time: 0.3755 data_time: 0.0259 memory: 5826 grad_norm: 3.0927 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5261 loss: 2.5261 2022/10/08 01:10:35 - mmengine - INFO - Epoch(train) [85][660/2119] lr: 4.0000e-02 eta: 13:24:03 time: 0.3324 data_time: 0.0258 memory: 5826 grad_norm: 3.1407 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7231 loss: 2.7231 2022/10/08 01:10:42 - mmengine - INFO - Epoch(train) [85][680/2119] lr: 4.0000e-02 eta: 13:23:56 time: 0.3628 data_time: 0.0246 memory: 5826 grad_norm: 3.0959 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7759 loss: 2.7759 2022/10/08 01:10:49 - mmengine - INFO - Epoch(train) [85][700/2119] lr: 4.0000e-02 eta: 13:23:49 time: 0.3460 data_time: 0.0236 memory: 5826 grad_norm: 3.1228 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5836 loss: 2.5836 2022/10/08 01:10:57 - mmengine - INFO - Epoch(train) [85][720/2119] lr: 4.0000e-02 eta: 13:23:43 time: 0.3871 data_time: 0.0229 memory: 5826 grad_norm: 3.1095 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7276 loss: 2.7276 2022/10/08 01:11:03 - mmengine - INFO - Epoch(train) [85][740/2119] lr: 4.0000e-02 eta: 13:23:36 time: 0.3291 data_time: 0.0208 memory: 5826 grad_norm: 3.1617 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7387 loss: 2.7387 2022/10/08 01:11:11 - mmengine - INFO - Epoch(train) [85][760/2119] lr: 4.0000e-02 eta: 13:23:29 time: 0.3597 data_time: 0.0211 memory: 5826 grad_norm: 3.0898 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5525 loss: 2.5525 2022/10/08 01:11:17 - mmengine - INFO - Epoch(train) [85][780/2119] lr: 4.0000e-02 eta: 13:23:22 time: 0.3324 data_time: 0.0233 memory: 5826 grad_norm: 3.1244 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6752 loss: 2.6752 2022/10/08 01:11:25 - mmengine - INFO - Epoch(train) [85][800/2119] lr: 4.0000e-02 eta: 13:23:16 time: 0.4036 data_time: 0.0246 memory: 5826 grad_norm: 3.1317 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9557 loss: 2.9557 2022/10/08 01:11:33 - mmengine - INFO - Epoch(train) [85][820/2119] lr: 4.0000e-02 eta: 13:23:09 time: 0.3685 data_time: 0.0215 memory: 5826 grad_norm: 3.1731 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.5965 loss: 2.5965 2022/10/08 01:11:39 - mmengine - INFO - Epoch(train) [85][840/2119] lr: 4.0000e-02 eta: 13:23:02 time: 0.3212 data_time: 0.0249 memory: 5826 grad_norm: 3.1347 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8381 loss: 2.8381 2022/10/08 01:11:46 - mmengine - INFO - Epoch(train) [85][860/2119] lr: 4.0000e-02 eta: 13:22:54 time: 0.3247 data_time: 0.0221 memory: 5826 grad_norm: 3.1173 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9770 loss: 2.9770 2022/10/08 01:11:53 - mmengine - INFO - Epoch(train) [85][880/2119] lr: 4.0000e-02 eta: 13:22:48 time: 0.3857 data_time: 0.0223 memory: 5826 grad_norm: 3.1794 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7323 loss: 2.7323 2022/10/08 01:12:00 - mmengine - INFO - Epoch(train) [85][900/2119] lr: 4.0000e-02 eta: 13:22:41 time: 0.3061 data_time: 0.0192 memory: 5826 grad_norm: 3.1516 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.5477 loss: 2.5477 2022/10/08 01:12:08 - mmengine - INFO - Epoch(train) [85][920/2119] lr: 4.0000e-02 eta: 13:22:35 time: 0.4109 data_time: 0.0219 memory: 5826 grad_norm: 3.1654 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6992 loss: 2.6992 2022/10/08 01:12:14 - mmengine - INFO - Epoch(train) [85][940/2119] lr: 4.0000e-02 eta: 13:22:27 time: 0.3258 data_time: 0.0207 memory: 5826 grad_norm: 3.1206 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8387 loss: 2.8387 2022/10/08 01:12:21 - mmengine - INFO - Epoch(train) [85][960/2119] lr: 4.0000e-02 eta: 13:22:21 time: 0.3597 data_time: 0.0251 memory: 5826 grad_norm: 3.1514 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7380 loss: 2.7380 2022/10/08 01:12:28 - mmengine - INFO - Epoch(train) [85][980/2119] lr: 4.0000e-02 eta: 13:22:13 time: 0.3338 data_time: 0.0249 memory: 5826 grad_norm: 3.1816 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8473 loss: 2.8473 2022/10/08 01:12:35 - mmengine - INFO - Epoch(train) [85][1000/2119] lr: 4.0000e-02 eta: 13:22:06 time: 0.3416 data_time: 0.0230 memory: 5826 grad_norm: 3.1480 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8693 loss: 2.8693 2022/10/08 01:12:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 01:12:42 - mmengine - INFO - Epoch(train) [85][1020/2119] lr: 4.0000e-02 eta: 13:22:00 time: 0.3702 data_time: 0.0260 memory: 5826 grad_norm: 3.1464 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5751 loss: 2.5751 2022/10/08 01:12:49 - mmengine - INFO - Epoch(train) [85][1040/2119] lr: 4.0000e-02 eta: 13:21:53 time: 0.3328 data_time: 0.0247 memory: 5826 grad_norm: 3.0793 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8363 loss: 2.8363 2022/10/08 01:12:56 - mmengine - INFO - Epoch(train) [85][1060/2119] lr: 4.0000e-02 eta: 13:21:46 time: 0.3652 data_time: 0.0223 memory: 5826 grad_norm: 3.1130 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7611 loss: 2.7611 2022/10/08 01:13:03 - mmengine - INFO - Epoch(train) [85][1080/2119] lr: 4.0000e-02 eta: 13:21:39 time: 0.3352 data_time: 0.0262 memory: 5826 grad_norm: 3.1555 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9546 loss: 2.9546 2022/10/08 01:13:10 - mmengine - INFO - Epoch(train) [85][1100/2119] lr: 4.0000e-02 eta: 13:21:32 time: 0.3663 data_time: 0.0215 memory: 5826 grad_norm: 3.1452 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7944 loss: 2.7944 2022/10/08 01:13:18 - mmengine - INFO - Epoch(train) [85][1120/2119] lr: 4.0000e-02 eta: 13:21:26 time: 0.3591 data_time: 0.0264 memory: 5826 grad_norm: 3.1360 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6926 loss: 2.6926 2022/10/08 01:13:25 - mmengine - INFO - Epoch(train) [85][1140/2119] lr: 4.0000e-02 eta: 13:21:19 time: 0.3766 data_time: 0.0189 memory: 5826 grad_norm: 3.1905 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.8775 loss: 2.8775 2022/10/08 01:13:32 - mmengine - INFO - Epoch(train) [85][1160/2119] lr: 4.0000e-02 eta: 13:21:12 time: 0.3276 data_time: 0.0193 memory: 5826 grad_norm: 3.1340 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.6396 loss: 2.6396 2022/10/08 01:13:39 - mmengine - INFO - Epoch(train) [85][1180/2119] lr: 4.0000e-02 eta: 13:21:05 time: 0.3579 data_time: 0.0222 memory: 5826 grad_norm: 3.1339 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7531 loss: 2.7531 2022/10/08 01:13:45 - mmengine - INFO - Epoch(train) [85][1200/2119] lr: 4.0000e-02 eta: 13:20:58 time: 0.3094 data_time: 0.0254 memory: 5826 grad_norm: 3.1116 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7765 loss: 2.7765 2022/10/08 01:13:52 - mmengine - INFO - Epoch(train) [85][1220/2119] lr: 4.0000e-02 eta: 13:20:51 time: 0.3546 data_time: 0.0256 memory: 5826 grad_norm: 3.1476 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.3900 loss: 2.3900 2022/10/08 01:13:59 - mmengine - INFO - Epoch(train) [85][1240/2119] lr: 4.0000e-02 eta: 13:20:44 time: 0.3338 data_time: 0.0194 memory: 5826 grad_norm: 3.1242 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8625 loss: 2.8625 2022/10/08 01:14:06 - mmengine - INFO - Epoch(train) [85][1260/2119] lr: 4.0000e-02 eta: 13:20:37 time: 0.3815 data_time: 0.0234 memory: 5826 grad_norm: 3.1623 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5951 loss: 2.5951 2022/10/08 01:14:14 - mmengine - INFO - Epoch(train) [85][1280/2119] lr: 4.0000e-02 eta: 13:20:31 time: 0.3712 data_time: 0.0238 memory: 5826 grad_norm: 3.1460 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6836 loss: 2.6836 2022/10/08 01:14:22 - mmengine - INFO - Epoch(train) [85][1300/2119] lr: 4.0000e-02 eta: 13:20:25 time: 0.4026 data_time: 0.0202 memory: 5826 grad_norm: 3.1681 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.7969 loss: 2.7969 2022/10/08 01:14:28 - mmengine - INFO - Epoch(train) [85][1320/2119] lr: 4.0000e-02 eta: 13:20:17 time: 0.3070 data_time: 0.0265 memory: 5826 grad_norm: 3.1218 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6376 loss: 2.6376 2022/10/08 01:14:36 - mmengine - INFO - Epoch(train) [85][1340/2119] lr: 4.0000e-02 eta: 13:20:11 time: 0.4156 data_time: 0.0237 memory: 5826 grad_norm: 3.0917 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9040 loss: 2.9040 2022/10/08 01:14:43 - mmengine - INFO - Epoch(train) [85][1360/2119] lr: 4.0000e-02 eta: 13:20:04 time: 0.3220 data_time: 0.0207 memory: 5826 grad_norm: 3.1710 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8441 loss: 2.8441 2022/10/08 01:14:49 - mmengine - INFO - Epoch(train) [85][1380/2119] lr: 4.0000e-02 eta: 13:19:57 time: 0.3231 data_time: 0.0240 memory: 5826 grad_norm: 3.1576 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5789 loss: 2.5789 2022/10/08 01:14:56 - mmengine - INFO - Epoch(train) [85][1400/2119] lr: 4.0000e-02 eta: 13:19:49 time: 0.3243 data_time: 0.0292 memory: 5826 grad_norm: 3.0790 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6478 loss: 2.6478 2022/10/08 01:15:03 - mmengine - INFO - Epoch(train) [85][1420/2119] lr: 4.0000e-02 eta: 13:19:43 time: 0.3646 data_time: 0.0219 memory: 5826 grad_norm: 3.1630 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6035 loss: 2.6035 2022/10/08 01:15:10 - mmengine - INFO - Epoch(train) [85][1440/2119] lr: 4.0000e-02 eta: 13:19:36 time: 0.3385 data_time: 0.0182 memory: 5826 grad_norm: 3.0977 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7482 loss: 2.7482 2022/10/08 01:15:17 - mmengine - INFO - Epoch(train) [85][1460/2119] lr: 4.0000e-02 eta: 13:19:29 time: 0.3562 data_time: 0.0221 memory: 5826 grad_norm: 3.1348 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5485 loss: 2.5485 2022/10/08 01:15:25 - mmengine - INFO - Epoch(train) [85][1480/2119] lr: 4.0000e-02 eta: 13:19:22 time: 0.3736 data_time: 0.0171 memory: 5826 grad_norm: 3.1912 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7296 loss: 2.7296 2022/10/08 01:15:31 - mmengine - INFO - Epoch(train) [85][1500/2119] lr: 4.0000e-02 eta: 13:19:15 time: 0.3328 data_time: 0.0249 memory: 5826 grad_norm: 3.1066 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8832 loss: 2.8832 2022/10/08 01:15:39 - mmengine - INFO - Epoch(train) [85][1520/2119] lr: 4.0000e-02 eta: 13:19:09 time: 0.3704 data_time: 0.0249 memory: 5826 grad_norm: 3.1329 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7836 loss: 2.7836 2022/10/08 01:15:45 - mmengine - INFO - Epoch(train) [85][1540/2119] lr: 4.0000e-02 eta: 13:19:01 time: 0.3214 data_time: 0.0259 memory: 5826 grad_norm: 3.1278 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6566 loss: 2.6566 2022/10/08 01:15:52 - mmengine - INFO - Epoch(train) [85][1560/2119] lr: 4.0000e-02 eta: 13:18:54 time: 0.3390 data_time: 0.0315 memory: 5826 grad_norm: 3.1070 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6844 loss: 2.6844 2022/10/08 01:15:59 - mmengine - INFO - Epoch(train) [85][1580/2119] lr: 4.0000e-02 eta: 13:18:47 time: 0.3535 data_time: 0.0200 memory: 5826 grad_norm: 3.1148 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8753 loss: 2.8753 2022/10/08 01:16:06 - mmengine - INFO - Epoch(train) [85][1600/2119] lr: 4.0000e-02 eta: 13:18:41 time: 0.3556 data_time: 0.0201 memory: 5826 grad_norm: 3.0699 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7445 loss: 2.7445 2022/10/08 01:16:13 - mmengine - INFO - Epoch(train) [85][1620/2119] lr: 4.0000e-02 eta: 13:18:34 time: 0.3568 data_time: 0.0211 memory: 5826 grad_norm: 3.1359 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7201 loss: 2.7201 2022/10/08 01:16:20 - mmengine - INFO - Epoch(train) [85][1640/2119] lr: 4.0000e-02 eta: 13:18:27 time: 0.3387 data_time: 0.0243 memory: 5826 grad_norm: 3.0741 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8221 loss: 2.8221 2022/10/08 01:16:28 - mmengine - INFO - Epoch(train) [85][1660/2119] lr: 4.0000e-02 eta: 13:18:21 time: 0.4004 data_time: 0.0255 memory: 5826 grad_norm: 3.0827 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6150 loss: 2.6150 2022/10/08 01:16:34 - mmengine - INFO - Epoch(train) [85][1680/2119] lr: 4.0000e-02 eta: 13:18:13 time: 0.3174 data_time: 0.0220 memory: 5826 grad_norm: 3.1235 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7565 loss: 2.7565 2022/10/08 01:16:42 - mmengine - INFO - Epoch(train) [85][1700/2119] lr: 4.0000e-02 eta: 13:18:07 time: 0.3664 data_time: 0.0179 memory: 5826 grad_norm: 3.1020 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7613 loss: 2.7613 2022/10/08 01:16:48 - mmengine - INFO - Epoch(train) [85][1720/2119] lr: 4.0000e-02 eta: 13:17:59 time: 0.3094 data_time: 0.0264 memory: 5826 grad_norm: 3.1515 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.0062 loss: 3.0062 2022/10/08 01:16:55 - mmengine - INFO - Epoch(train) [85][1740/2119] lr: 4.0000e-02 eta: 13:17:53 time: 0.3619 data_time: 0.0217 memory: 5826 grad_norm: 3.1332 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.8228 loss: 2.8228 2022/10/08 01:17:03 - mmengine - INFO - Epoch(train) [85][1760/2119] lr: 4.0000e-02 eta: 13:17:46 time: 0.3928 data_time: 0.0185 memory: 5826 grad_norm: 3.1379 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7203 loss: 2.7203 2022/10/08 01:17:10 - mmengine - INFO - Epoch(train) [85][1780/2119] lr: 4.0000e-02 eta: 13:17:39 time: 0.3289 data_time: 0.0257 memory: 5826 grad_norm: 3.1602 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7890 loss: 2.7890 2022/10/08 01:17:16 - mmengine - INFO - Epoch(train) [85][1800/2119] lr: 4.0000e-02 eta: 13:17:32 time: 0.3331 data_time: 0.0203 memory: 5826 grad_norm: 3.0843 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7370 loss: 2.7370 2022/10/08 01:17:24 - mmengine - INFO - Epoch(train) [85][1820/2119] lr: 4.0000e-02 eta: 13:17:25 time: 0.3736 data_time: 0.0198 memory: 5826 grad_norm: 3.1141 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7849 loss: 2.7849 2022/10/08 01:17:30 - mmengine - INFO - Epoch(train) [85][1840/2119] lr: 4.0000e-02 eta: 13:17:18 time: 0.3390 data_time: 0.0223 memory: 5826 grad_norm: 3.1768 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6306 loss: 2.6306 2022/10/08 01:17:38 - mmengine - INFO - Epoch(train) [85][1860/2119] lr: 4.0000e-02 eta: 13:17:12 time: 0.3789 data_time: 0.0211 memory: 5826 grad_norm: 3.1878 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8301 loss: 2.8301 2022/10/08 01:17:44 - mmengine - INFO - Epoch(train) [85][1880/2119] lr: 4.0000e-02 eta: 13:17:05 time: 0.3157 data_time: 0.0265 memory: 5826 grad_norm: 3.0449 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8215 loss: 2.8215 2022/10/08 01:17:52 - mmengine - INFO - Epoch(train) [85][1900/2119] lr: 4.0000e-02 eta: 13:16:58 time: 0.3998 data_time: 0.0225 memory: 5826 grad_norm: 3.1447 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9037 loss: 2.9037 2022/10/08 01:17:59 - mmengine - INFO - Epoch(train) [85][1920/2119] lr: 4.0000e-02 eta: 13:16:51 time: 0.3234 data_time: 0.0278 memory: 5826 grad_norm: 3.0507 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7304 loss: 2.7304 2022/10/08 01:18:06 - mmengine - INFO - Epoch(train) [85][1940/2119] lr: 4.0000e-02 eta: 13:16:45 time: 0.3726 data_time: 0.0220 memory: 5826 grad_norm: 3.1265 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8828 loss: 2.8828 2022/10/08 01:18:13 - mmengine - INFO - Epoch(train) [85][1960/2119] lr: 4.0000e-02 eta: 13:16:38 time: 0.3411 data_time: 0.0283 memory: 5826 grad_norm: 3.1185 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6315 loss: 2.6315 2022/10/08 01:18:21 - mmengine - INFO - Epoch(train) [85][1980/2119] lr: 4.0000e-02 eta: 13:16:31 time: 0.3839 data_time: 0.0239 memory: 5826 grad_norm: 3.0698 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6736 loss: 2.6736 2022/10/08 01:18:27 - mmengine - INFO - Epoch(train) [85][2000/2119] lr: 4.0000e-02 eta: 13:16:24 time: 0.3233 data_time: 0.0218 memory: 5826 grad_norm: 3.0426 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6380 loss: 2.6380 2022/10/08 01:18:29 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 01:18:34 - mmengine - INFO - Epoch(train) [85][2020/2119] lr: 4.0000e-02 eta: 13:16:17 time: 0.3534 data_time: 0.0245 memory: 5826 grad_norm: 3.1336 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8451 loss: 2.8451 2022/10/08 01:18:41 - mmengine - INFO - Epoch(train) [85][2040/2119] lr: 4.0000e-02 eta: 13:16:10 time: 0.3482 data_time: 0.0238 memory: 5826 grad_norm: 3.1854 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7156 loss: 2.7156 2022/10/08 01:18:49 - mmengine - INFO - Epoch(train) [85][2060/2119] lr: 4.0000e-02 eta: 13:16:04 time: 0.3900 data_time: 0.0205 memory: 5826 grad_norm: 3.1076 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7383 loss: 2.7383 2022/10/08 01:18:55 - mmengine - INFO - Epoch(train) [85][2080/2119] lr: 4.0000e-02 eta: 13:15:56 time: 0.2970 data_time: 0.0238 memory: 5826 grad_norm: 3.1008 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6186 loss: 2.6186 2022/10/08 01:19:03 - mmengine - INFO - Epoch(train) [85][2100/2119] lr: 4.0000e-02 eta: 13:15:50 time: 0.3712 data_time: 0.0297 memory: 5826 grad_norm: 3.0808 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6509 loss: 2.6509 2022/10/08 01:19:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 01:19:08 - mmengine - INFO - Epoch(train) [85][2119/2119] lr: 4.0000e-02 eta: 13:15:50 time: 0.3246 data_time: 0.0155 memory: 5826 grad_norm: 3.1195 top1_acc: 0.5000 top5_acc: 0.7000 loss_cls: 2.7959 loss: 2.7959 2022/10/08 01:19:16 - mmengine - INFO - Epoch(val) [85][20/137] eta: 0:00:46 time: 0.4000 data_time: 0.3328 memory: 1241 2022/10/08 01:19:22 - mmengine - INFO - Epoch(val) [85][40/137] eta: 0:00:28 time: 0.2887 data_time: 0.2054 memory: 1241 2022/10/08 01:19:29 - mmengine - INFO - Epoch(val) [85][60/137] eta: 0:00:26 time: 0.3398 data_time: 0.2740 memory: 1241 2022/10/08 01:19:34 - mmengine - INFO - Epoch(val) [85][80/137] eta: 0:00:15 time: 0.2795 data_time: 0.2142 memory: 1241 2022/10/08 01:19:41 - mmengine - INFO - Epoch(val) [85][100/137] eta: 0:00:12 time: 0.3456 data_time: 0.2813 memory: 1241 2022/10/08 01:19:46 - mmengine - INFO - Epoch(val) [85][120/137] eta: 0:00:03 time: 0.2312 data_time: 0.1560 memory: 1241 2022/10/08 01:20:00 - mmengine - INFO - Epoch(val) [85][137/137] acc/top1: 0.4318 acc/top5: 0.6763 acc/mean1: 0.4317 2022/10/08 01:20:09 - mmengine - INFO - Epoch(train) [86][20/2119] lr: 4.0000e-02 eta: 13:15:33 time: 0.4721 data_time: 0.1601 memory: 5826 grad_norm: 3.1174 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6964 loss: 2.6964 2022/10/08 01:20:16 - mmengine - INFO - Epoch(train) [86][40/2119] lr: 4.0000e-02 eta: 13:15:26 time: 0.3308 data_time: 0.0452 memory: 5826 grad_norm: 3.1489 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6599 loss: 2.6599 2022/10/08 01:20:24 - mmengine - INFO - Epoch(train) [86][60/2119] lr: 4.0000e-02 eta: 13:15:19 time: 0.3775 data_time: 0.0254 memory: 5826 grad_norm: 3.0658 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4954 loss: 2.4954 2022/10/08 01:20:30 - mmengine - INFO - Epoch(train) [86][80/2119] lr: 4.0000e-02 eta: 13:15:12 time: 0.3235 data_time: 0.0136 memory: 5826 grad_norm: 3.0774 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7485 loss: 2.7485 2022/10/08 01:20:37 - mmengine - INFO - Epoch(train) [86][100/2119] lr: 4.0000e-02 eta: 13:15:05 time: 0.3631 data_time: 0.0224 memory: 5826 grad_norm: 3.1167 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5871 loss: 2.5871 2022/10/08 01:20:44 - mmengine - INFO - Epoch(train) [86][120/2119] lr: 4.0000e-02 eta: 13:14:58 time: 0.3354 data_time: 0.0247 memory: 5826 grad_norm: 3.1311 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.7041 loss: 2.7041 2022/10/08 01:20:51 - mmengine - INFO - Epoch(train) [86][140/2119] lr: 4.0000e-02 eta: 13:14:51 time: 0.3271 data_time: 0.0240 memory: 5826 grad_norm: 3.0716 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8141 loss: 2.8141 2022/10/08 01:20:58 - mmengine - INFO - Epoch(train) [86][160/2119] lr: 4.0000e-02 eta: 13:14:45 time: 0.3752 data_time: 0.0167 memory: 5826 grad_norm: 3.1157 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6028 loss: 2.6028 2022/10/08 01:21:05 - mmengine - INFO - Epoch(train) [86][180/2119] lr: 4.0000e-02 eta: 13:14:38 time: 0.3361 data_time: 0.0279 memory: 5826 grad_norm: 3.1027 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5508 loss: 2.5508 2022/10/08 01:21:12 - mmengine - INFO - Epoch(train) [86][200/2119] lr: 4.0000e-02 eta: 13:14:30 time: 0.3348 data_time: 0.0149 memory: 5826 grad_norm: 3.1199 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6186 loss: 2.6186 2022/10/08 01:21:19 - mmengine - INFO - Epoch(train) [86][220/2119] lr: 4.0000e-02 eta: 13:14:24 time: 0.3717 data_time: 0.0210 memory: 5826 grad_norm: 3.1392 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7407 loss: 2.7407 2022/10/08 01:21:26 - mmengine - INFO - Epoch(train) [86][240/2119] lr: 4.0000e-02 eta: 13:14:17 time: 0.3394 data_time: 0.0264 memory: 5826 grad_norm: 3.1360 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8486 loss: 2.8486 2022/10/08 01:21:33 - mmengine - INFO - Epoch(train) [86][260/2119] lr: 4.0000e-02 eta: 13:14:10 time: 0.3487 data_time: 0.0230 memory: 5826 grad_norm: 3.1483 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5889 loss: 2.5889 2022/10/08 01:21:40 - mmengine - INFO - Epoch(train) [86][280/2119] lr: 4.0000e-02 eta: 13:14:03 time: 0.3755 data_time: 0.0251 memory: 5826 grad_norm: 3.0575 top1_acc: 0.1250 top5_acc: 0.6875 loss_cls: 2.5756 loss: 2.5756 2022/10/08 01:21:47 - mmengine - INFO - Epoch(train) [86][300/2119] lr: 4.0000e-02 eta: 13:13:56 time: 0.3391 data_time: 0.0219 memory: 5826 grad_norm: 3.1639 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8211 loss: 2.8211 2022/10/08 01:21:54 - mmengine - INFO - Epoch(train) [86][320/2119] lr: 4.0000e-02 eta: 13:13:49 time: 0.3329 data_time: 0.0239 memory: 5826 grad_norm: 3.1405 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5607 loss: 2.5607 2022/10/08 01:22:00 - mmengine - INFO - Epoch(train) [86][340/2119] lr: 4.0000e-02 eta: 13:13:42 time: 0.3044 data_time: 0.0269 memory: 5826 grad_norm: 3.1328 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.6739 loss: 2.6739 2022/10/08 01:22:07 - mmengine - INFO - Epoch(train) [86][360/2119] lr: 4.0000e-02 eta: 13:13:35 time: 0.3776 data_time: 0.0201 memory: 5826 grad_norm: 3.1247 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7594 loss: 2.7594 2022/10/08 01:22:14 - mmengine - INFO - Epoch(train) [86][380/2119] lr: 4.0000e-02 eta: 13:13:28 time: 0.3357 data_time: 0.0372 memory: 5826 grad_norm: 3.1794 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7794 loss: 2.7794 2022/10/08 01:22:21 - mmengine - INFO - Epoch(train) [86][400/2119] lr: 4.0000e-02 eta: 13:13:21 time: 0.3638 data_time: 0.0205 memory: 5826 grad_norm: 3.1748 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4368 loss: 2.4368 2022/10/08 01:22:28 - mmengine - INFO - Epoch(train) [86][420/2119] lr: 4.0000e-02 eta: 13:13:14 time: 0.3110 data_time: 0.0254 memory: 5826 grad_norm: 3.1727 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6798 loss: 2.6798 2022/10/08 01:22:36 - mmengine - INFO - Epoch(train) [86][440/2119] lr: 4.0000e-02 eta: 13:13:08 time: 0.3964 data_time: 0.0270 memory: 5826 grad_norm: 3.1231 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7569 loss: 2.7569 2022/10/08 01:22:42 - mmengine - INFO - Epoch(train) [86][460/2119] lr: 4.0000e-02 eta: 13:13:01 time: 0.3428 data_time: 0.0247 memory: 5826 grad_norm: 3.1145 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.9729 loss: 2.9729 2022/10/08 01:22:50 - mmengine - INFO - Epoch(train) [86][480/2119] lr: 4.0000e-02 eta: 13:12:54 time: 0.3795 data_time: 0.0236 memory: 5826 grad_norm: 3.1681 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7519 loss: 2.7519 2022/10/08 01:22:57 - mmengine - INFO - Epoch(train) [86][500/2119] lr: 4.0000e-02 eta: 13:12:47 time: 0.3418 data_time: 0.0263 memory: 5826 grad_norm: 3.1135 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7528 loss: 2.7528 2022/10/08 01:23:05 - mmengine - INFO - Epoch(train) [86][520/2119] lr: 4.0000e-02 eta: 13:12:42 time: 0.4198 data_time: 0.0241 memory: 5826 grad_norm: 3.1641 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7889 loss: 2.7889 2022/10/08 01:23:11 - mmengine - INFO - Epoch(train) [86][540/2119] lr: 4.0000e-02 eta: 13:12:34 time: 0.3096 data_time: 0.0251 memory: 5826 grad_norm: 3.1398 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6710 loss: 2.6710 2022/10/08 01:23:19 - mmengine - INFO - Epoch(train) [86][560/2119] lr: 4.0000e-02 eta: 13:12:28 time: 0.3928 data_time: 0.0222 memory: 5826 grad_norm: 3.1342 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7503 loss: 2.7503 2022/10/08 01:23:26 - mmengine - INFO - Epoch(train) [86][580/2119] lr: 4.0000e-02 eta: 13:12:20 time: 0.3116 data_time: 0.0275 memory: 5826 grad_norm: 3.1022 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7378 loss: 2.7378 2022/10/08 01:23:33 - mmengine - INFO - Epoch(train) [86][600/2119] lr: 4.0000e-02 eta: 13:12:14 time: 0.3955 data_time: 0.0221 memory: 5826 grad_norm: 3.1112 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6490 loss: 2.6490 2022/10/08 01:23:39 - mmengine - INFO - Epoch(train) [86][620/2119] lr: 4.0000e-02 eta: 13:12:06 time: 0.2703 data_time: 0.0235 memory: 5826 grad_norm: 3.1227 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7866 loss: 2.7866 2022/10/08 01:23:46 - mmengine - INFO - Epoch(train) [86][640/2119] lr: 4.0000e-02 eta: 13:12:00 time: 0.3777 data_time: 0.0238 memory: 5826 grad_norm: 3.0991 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6275 loss: 2.6275 2022/10/08 01:23:54 - mmengine - INFO - Epoch(train) [86][660/2119] lr: 4.0000e-02 eta: 13:11:53 time: 0.3573 data_time: 0.0199 memory: 5826 grad_norm: 3.1119 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5288 loss: 2.5288 2022/10/08 01:24:00 - mmengine - INFO - Epoch(train) [86][680/2119] lr: 4.0000e-02 eta: 13:11:46 time: 0.3411 data_time: 0.0231 memory: 5826 grad_norm: 3.1256 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6887 loss: 2.6887 2022/10/08 01:24:07 - mmengine - INFO - Epoch(train) [86][700/2119] lr: 4.0000e-02 eta: 13:11:38 time: 0.3075 data_time: 0.0236 memory: 5826 grad_norm: 3.1291 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6438 loss: 2.6438 2022/10/08 01:24:14 - mmengine - INFO - Epoch(train) [86][720/2119] lr: 4.0000e-02 eta: 13:11:32 time: 0.3701 data_time: 0.0217 memory: 5826 grad_norm: 3.1888 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9698 loss: 2.9698 2022/10/08 01:24:21 - mmengine - INFO - Epoch(train) [86][740/2119] lr: 4.0000e-02 eta: 13:11:25 time: 0.3316 data_time: 0.0225 memory: 5826 grad_norm: 3.1400 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7531 loss: 2.7531 2022/10/08 01:24:28 - mmengine - INFO - Epoch(train) [86][760/2119] lr: 4.0000e-02 eta: 13:11:18 time: 0.3484 data_time: 0.0258 memory: 5826 grad_norm: 3.1269 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5937 loss: 2.5937 2022/10/08 01:24:35 - mmengine - INFO - Epoch(train) [86][780/2119] lr: 4.0000e-02 eta: 13:11:11 time: 0.3637 data_time: 0.0249 memory: 5826 grad_norm: 3.1474 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8567 loss: 2.8567 2022/10/08 01:24:42 - mmengine - INFO - Epoch(train) [86][800/2119] lr: 4.0000e-02 eta: 13:11:04 time: 0.3436 data_time: 0.0239 memory: 5826 grad_norm: 3.1789 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6087 loss: 2.6087 2022/10/08 01:24:49 - mmengine - INFO - Epoch(train) [86][820/2119] lr: 4.0000e-02 eta: 13:10:57 time: 0.3449 data_time: 0.0370 memory: 5826 grad_norm: 3.0873 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6566 loss: 2.6566 2022/10/08 01:24:56 - mmengine - INFO - Epoch(train) [86][840/2119] lr: 4.0000e-02 eta: 13:10:51 time: 0.3727 data_time: 0.0243 memory: 5826 grad_norm: 3.0966 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6415 loss: 2.6415 2022/10/08 01:25:02 - mmengine - INFO - Epoch(train) [86][860/2119] lr: 4.0000e-02 eta: 13:10:43 time: 0.3049 data_time: 0.0225 memory: 5826 grad_norm: 3.1572 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.7551 loss: 2.7551 2022/10/08 01:25:11 - mmengine - INFO - Epoch(train) [86][880/2119] lr: 4.0000e-02 eta: 13:10:37 time: 0.4275 data_time: 0.0225 memory: 5826 grad_norm: 3.1074 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8286 loss: 2.8286 2022/10/08 01:25:12 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 01:25:17 - mmengine - INFO - Epoch(train) [86][900/2119] lr: 4.0000e-02 eta: 13:10:29 time: 0.2894 data_time: 0.0227 memory: 5826 grad_norm: 3.1529 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6351 loss: 2.6351 2022/10/08 01:25:23 - mmengine - INFO - Epoch(train) [86][920/2119] lr: 4.0000e-02 eta: 13:10:22 time: 0.3292 data_time: 0.0239 memory: 5826 grad_norm: 3.1503 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6624 loss: 2.6624 2022/10/08 01:25:30 - mmengine - INFO - Epoch(train) [86][940/2119] lr: 4.0000e-02 eta: 13:10:16 time: 0.3587 data_time: 0.0218 memory: 5826 grad_norm: 3.0682 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9216 loss: 2.9216 2022/10/08 01:25:37 - mmengine - INFO - Epoch(train) [86][960/2119] lr: 4.0000e-02 eta: 13:10:09 time: 0.3467 data_time: 0.0209 memory: 5826 grad_norm: 3.1300 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6271 loss: 2.6271 2022/10/08 01:25:44 - mmengine - INFO - Epoch(train) [86][980/2119] lr: 4.0000e-02 eta: 13:10:02 time: 0.3525 data_time: 0.0304 memory: 5826 grad_norm: 3.1179 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5002 loss: 2.5002 2022/10/08 01:25:51 - mmengine - INFO - Epoch(train) [86][1000/2119] lr: 4.0000e-02 eta: 13:09:55 time: 0.3467 data_time: 0.0182 memory: 5826 grad_norm: 3.1295 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7516 loss: 2.7516 2022/10/08 01:25:59 - mmengine - INFO - Epoch(train) [86][1020/2119] lr: 4.0000e-02 eta: 13:09:48 time: 0.3735 data_time: 0.0225 memory: 5826 grad_norm: 3.1398 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8134 loss: 2.8134 2022/10/08 01:26:05 - mmengine - INFO - Epoch(train) [86][1040/2119] lr: 4.0000e-02 eta: 13:09:41 time: 0.3029 data_time: 0.0240 memory: 5826 grad_norm: 3.1201 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9536 loss: 2.9536 2022/10/08 01:26:12 - mmengine - INFO - Epoch(train) [86][1060/2119] lr: 4.0000e-02 eta: 13:09:34 time: 0.3573 data_time: 0.0283 memory: 5826 grad_norm: 3.0952 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6476 loss: 2.6476 2022/10/08 01:26:19 - mmengine - INFO - Epoch(train) [86][1080/2119] lr: 4.0000e-02 eta: 13:09:27 time: 0.3662 data_time: 0.0180 memory: 5826 grad_norm: 3.1286 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7533 loss: 2.7533 2022/10/08 01:26:26 - mmengine - INFO - Epoch(train) [86][1100/2119] lr: 4.0000e-02 eta: 13:09:20 time: 0.3314 data_time: 0.0330 memory: 5826 grad_norm: 3.1765 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6442 loss: 2.6442 2022/10/08 01:26:33 - mmengine - INFO - Epoch(train) [86][1120/2119] lr: 4.0000e-02 eta: 13:09:13 time: 0.3278 data_time: 0.0289 memory: 5826 grad_norm: 3.1385 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6039 loss: 2.6039 2022/10/08 01:26:40 - mmengine - INFO - Epoch(train) [86][1140/2119] lr: 4.0000e-02 eta: 13:09:06 time: 0.3505 data_time: 0.0262 memory: 5826 grad_norm: 3.1263 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8737 loss: 2.8737 2022/10/08 01:26:47 - mmengine - INFO - Epoch(train) [86][1160/2119] lr: 4.0000e-02 eta: 13:09:00 time: 0.3785 data_time: 0.0180 memory: 5826 grad_norm: 3.1365 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.7249 loss: 2.7249 2022/10/08 01:26:55 - mmengine - INFO - Epoch(train) [86][1180/2119] lr: 4.0000e-02 eta: 13:08:53 time: 0.3811 data_time: 0.0248 memory: 5826 grad_norm: 3.1531 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7588 loss: 2.7588 2022/10/08 01:27:01 - mmengine - INFO - Epoch(train) [86][1200/2119] lr: 4.0000e-02 eta: 13:08:46 time: 0.3070 data_time: 0.0259 memory: 5826 grad_norm: 3.1319 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8605 loss: 2.8605 2022/10/08 01:27:08 - mmengine - INFO - Epoch(train) [86][1220/2119] lr: 4.0000e-02 eta: 13:08:39 time: 0.3483 data_time: 0.0236 memory: 5826 grad_norm: 3.1838 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8134 loss: 2.8134 2022/10/08 01:27:14 - mmengine - INFO - Epoch(train) [86][1240/2119] lr: 4.0000e-02 eta: 13:08:32 time: 0.3277 data_time: 0.0230 memory: 5826 grad_norm: 3.0973 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6673 loss: 2.6673 2022/10/08 01:27:21 - mmengine - INFO - Epoch(train) [86][1260/2119] lr: 4.0000e-02 eta: 13:08:24 time: 0.3294 data_time: 0.0238 memory: 5826 grad_norm: 3.1433 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7098 loss: 2.7098 2022/10/08 01:27:28 - mmengine - INFO - Epoch(train) [86][1280/2119] lr: 4.0000e-02 eta: 13:08:17 time: 0.3315 data_time: 0.0238 memory: 5826 grad_norm: 3.1122 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6412 loss: 2.6412 2022/10/08 01:27:36 - mmengine - INFO - Epoch(train) [86][1300/2119] lr: 4.0000e-02 eta: 13:08:11 time: 0.3984 data_time: 0.0237 memory: 5826 grad_norm: 3.0926 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7017 loss: 2.7017 2022/10/08 01:27:42 - mmengine - INFO - Epoch(train) [86][1320/2119] lr: 4.0000e-02 eta: 13:08:03 time: 0.3053 data_time: 0.0252 memory: 5826 grad_norm: 3.1477 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8385 loss: 2.8385 2022/10/08 01:27:48 - mmengine - INFO - Epoch(train) [86][1340/2119] lr: 4.0000e-02 eta: 13:07:56 time: 0.3196 data_time: 0.0234 memory: 5826 grad_norm: 3.1432 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8104 loss: 2.8104 2022/10/08 01:27:55 - mmengine - INFO - Epoch(train) [86][1360/2119] lr: 4.0000e-02 eta: 13:07:49 time: 0.3284 data_time: 0.0241 memory: 5826 grad_norm: 3.1375 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6404 loss: 2.6404 2022/10/08 01:28:03 - mmengine - INFO - Epoch(train) [86][1380/2119] lr: 4.0000e-02 eta: 13:07:43 time: 0.4140 data_time: 0.0268 memory: 5826 grad_norm: 3.2069 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6322 loss: 2.6322 2022/10/08 01:28:10 - mmengine - INFO - Epoch(train) [86][1400/2119] lr: 4.0000e-02 eta: 13:07:36 time: 0.3334 data_time: 0.0229 memory: 5826 grad_norm: 3.1118 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4777 loss: 2.4777 2022/10/08 01:28:16 - mmengine - INFO - Epoch(train) [86][1420/2119] lr: 4.0000e-02 eta: 13:07:29 time: 0.3340 data_time: 0.0230 memory: 5826 grad_norm: 3.1541 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6142 loss: 2.6142 2022/10/08 01:28:23 - mmengine - INFO - Epoch(train) [86][1440/2119] lr: 4.0000e-02 eta: 13:07:22 time: 0.3314 data_time: 0.0344 memory: 5826 grad_norm: 3.1542 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7230 loss: 2.7230 2022/10/08 01:28:30 - mmengine - INFO - Epoch(train) [86][1460/2119] lr: 4.0000e-02 eta: 13:07:15 time: 0.3563 data_time: 0.0236 memory: 5826 grad_norm: 3.1189 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7010 loss: 2.7010 2022/10/08 01:28:37 - mmengine - INFO - Epoch(train) [86][1480/2119] lr: 4.0000e-02 eta: 13:07:08 time: 0.3669 data_time: 0.0223 memory: 5826 grad_norm: 3.0727 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.4486 loss: 2.4486 2022/10/08 01:28:44 - mmengine - INFO - Epoch(train) [86][1500/2119] lr: 4.0000e-02 eta: 13:07:01 time: 0.3182 data_time: 0.0233 memory: 5826 grad_norm: 3.2470 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0512 loss: 3.0512 2022/10/08 01:28:50 - mmengine - INFO - Epoch(train) [86][1520/2119] lr: 4.0000e-02 eta: 13:06:54 time: 0.3325 data_time: 0.0180 memory: 5826 grad_norm: 3.1850 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8268 loss: 2.8268 2022/10/08 01:28:57 - mmengine - INFO - Epoch(train) [86][1540/2119] lr: 4.0000e-02 eta: 13:06:46 time: 0.3244 data_time: 0.0779 memory: 5826 grad_norm: 3.1628 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7964 loss: 2.7964 2022/10/08 01:29:04 - mmengine - INFO - Epoch(train) [86][1560/2119] lr: 4.0000e-02 eta: 13:06:40 time: 0.3570 data_time: 0.0322 memory: 5826 grad_norm: 3.1632 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5543 loss: 2.5543 2022/10/08 01:29:10 - mmengine - INFO - Epoch(train) [86][1580/2119] lr: 4.0000e-02 eta: 13:06:32 time: 0.3170 data_time: 0.0213 memory: 5826 grad_norm: 3.1167 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5457 loss: 2.5457 2022/10/08 01:29:18 - mmengine - INFO - Epoch(train) [86][1600/2119] lr: 4.0000e-02 eta: 13:06:26 time: 0.3949 data_time: 0.0140 memory: 5826 grad_norm: 3.1726 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5670 loss: 2.5670 2022/10/08 01:29:25 - mmengine - INFO - Epoch(train) [86][1620/2119] lr: 4.0000e-02 eta: 13:06:19 time: 0.3180 data_time: 0.0263 memory: 5826 grad_norm: 3.1576 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7051 loss: 2.7051 2022/10/08 01:29:32 - mmengine - INFO - Epoch(train) [86][1640/2119] lr: 4.0000e-02 eta: 13:06:12 time: 0.3772 data_time: 0.0284 memory: 5826 grad_norm: 3.1394 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7571 loss: 2.7571 2022/10/08 01:29:38 - mmengine - INFO - Epoch(train) [86][1660/2119] lr: 4.0000e-02 eta: 13:06:05 time: 0.3060 data_time: 0.0224 memory: 5826 grad_norm: 3.1439 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6974 loss: 2.6974 2022/10/08 01:29:47 - mmengine - INFO - Epoch(train) [86][1680/2119] lr: 4.0000e-02 eta: 13:05:59 time: 0.4123 data_time: 0.0226 memory: 5826 grad_norm: 3.0988 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.6275 loss: 2.6275 2022/10/08 01:29:53 - mmengine - INFO - Epoch(train) [86][1700/2119] lr: 4.0000e-02 eta: 13:05:51 time: 0.3239 data_time: 0.0220 memory: 5826 grad_norm: 3.1445 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6339 loss: 2.6339 2022/10/08 01:30:01 - mmengine - INFO - Epoch(train) [86][1720/2119] lr: 4.0000e-02 eta: 13:05:45 time: 0.4065 data_time: 0.0205 memory: 5826 grad_norm: 3.1525 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8198 loss: 2.8198 2022/10/08 01:30:08 - mmengine - INFO - Epoch(train) [86][1740/2119] lr: 4.0000e-02 eta: 13:05:38 time: 0.3316 data_time: 0.0259 memory: 5826 grad_norm: 3.1508 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8098 loss: 2.8098 2022/10/08 01:30:15 - mmengine - INFO - Epoch(train) [86][1760/2119] lr: 4.0000e-02 eta: 13:05:31 time: 0.3570 data_time: 0.0209 memory: 5826 grad_norm: 3.0869 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7139 loss: 2.7139 2022/10/08 01:30:22 - mmengine - INFO - Epoch(train) [86][1780/2119] lr: 4.0000e-02 eta: 13:05:24 time: 0.3283 data_time: 0.0218 memory: 5826 grad_norm: 3.1281 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7564 loss: 2.7564 2022/10/08 01:30:28 - mmengine - INFO - Epoch(train) [86][1800/2119] lr: 4.0000e-02 eta: 13:05:17 time: 0.3196 data_time: 0.0232 memory: 5826 grad_norm: 3.1083 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0013 loss: 3.0013 2022/10/08 01:30:35 - mmengine - INFO - Epoch(train) [86][1820/2119] lr: 4.0000e-02 eta: 13:05:10 time: 0.3394 data_time: 0.0324 memory: 5826 grad_norm: 3.1527 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8838 loss: 2.8838 2022/10/08 01:30:42 - mmengine - INFO - Epoch(train) [86][1840/2119] lr: 4.0000e-02 eta: 13:05:03 time: 0.3709 data_time: 0.0284 memory: 5826 grad_norm: 3.1130 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7557 loss: 2.7557 2022/10/08 01:30:49 - mmengine - INFO - Epoch(train) [86][1860/2119] lr: 4.0000e-02 eta: 13:04:56 time: 0.3199 data_time: 0.0243 memory: 5826 grad_norm: 3.1533 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7080 loss: 2.7080 2022/10/08 01:30:56 - mmengine - INFO - Epoch(train) [86][1880/2119] lr: 4.0000e-02 eta: 13:04:49 time: 0.3762 data_time: 0.0161 memory: 5826 grad_norm: 3.1314 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9030 loss: 2.9030 2022/10/08 01:30:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 01:31:03 - mmengine - INFO - Epoch(train) [86][1900/2119] lr: 4.0000e-02 eta: 13:04:42 time: 0.3150 data_time: 0.0251 memory: 5826 grad_norm: 3.1065 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6213 loss: 2.6213 2022/10/08 01:31:09 - mmengine - INFO - Epoch(train) [86][1920/2119] lr: 4.0000e-02 eta: 13:04:35 time: 0.3491 data_time: 0.0212 memory: 5826 grad_norm: 3.1249 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.8037 loss: 2.8037 2022/10/08 01:31:16 - mmengine - INFO - Epoch(train) [86][1940/2119] lr: 4.0000e-02 eta: 13:04:28 time: 0.3347 data_time: 0.0270 memory: 5826 grad_norm: 3.1645 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6925 loss: 2.6925 2022/10/08 01:31:24 - mmengine - INFO - Epoch(train) [86][1960/2119] lr: 4.0000e-02 eta: 13:04:22 time: 0.3809 data_time: 0.0230 memory: 5826 grad_norm: 3.1493 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7874 loss: 2.7874 2022/10/08 01:31:30 - mmengine - INFO - Epoch(train) [86][1980/2119] lr: 4.0000e-02 eta: 13:04:14 time: 0.3111 data_time: 0.0224 memory: 5826 grad_norm: 3.1472 top1_acc: 0.1875 top5_acc: 0.8125 loss_cls: 2.5113 loss: 2.5113 2022/10/08 01:31:37 - mmengine - INFO - Epoch(train) [86][2000/2119] lr: 4.0000e-02 eta: 13:04:08 time: 0.3685 data_time: 0.0175 memory: 5826 grad_norm: 3.1177 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7636 loss: 2.7636 2022/10/08 01:31:44 - mmengine - INFO - Epoch(train) [86][2020/2119] lr: 4.0000e-02 eta: 13:04:00 time: 0.3084 data_time: 0.0240 memory: 5826 grad_norm: 3.1872 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7392 loss: 2.7392 2022/10/08 01:31:51 - mmengine - INFO - Epoch(train) [86][2040/2119] lr: 4.0000e-02 eta: 13:03:54 time: 0.3776 data_time: 0.0209 memory: 5826 grad_norm: 3.1237 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7750 loss: 2.7750 2022/10/08 01:31:58 - mmengine - INFO - Epoch(train) [86][2060/2119] lr: 4.0000e-02 eta: 13:03:46 time: 0.3334 data_time: 0.0253 memory: 5826 grad_norm: 3.1038 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9304 loss: 2.9304 2022/10/08 01:32:06 - mmengine - INFO - Epoch(train) [86][2080/2119] lr: 4.0000e-02 eta: 13:03:40 time: 0.3951 data_time: 0.0180 memory: 5826 grad_norm: 3.1488 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8336 loss: 2.8336 2022/10/08 01:32:12 - mmengine - INFO - Epoch(train) [86][2100/2119] lr: 4.0000e-02 eta: 13:03:33 time: 0.3274 data_time: 0.0211 memory: 5826 grad_norm: 3.1777 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6801 loss: 2.6801 2022/10/08 01:32:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 01:32:19 - mmengine - INFO - Epoch(train) [86][2119/2119] lr: 4.0000e-02 eta: 13:03:33 time: 0.3303 data_time: 0.0190 memory: 5826 grad_norm: 3.1488 top1_acc: 0.2000 top5_acc: 0.4000 loss_cls: 2.5837 loss: 2.5837 2022/10/08 01:32:28 - mmengine - INFO - Epoch(train) [87][20/2119] lr: 4.0000e-02 eta: 13:03:17 time: 0.4795 data_time: 0.1470 memory: 5826 grad_norm: 3.0989 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7304 loss: 2.7304 2022/10/08 01:32:35 - mmengine - INFO - Epoch(train) [87][40/2119] lr: 4.0000e-02 eta: 13:03:09 time: 0.3096 data_time: 0.0207 memory: 5826 grad_norm: 3.0909 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5572 loss: 2.5572 2022/10/08 01:32:42 - mmengine - INFO - Epoch(train) [87][60/2119] lr: 4.0000e-02 eta: 13:03:02 time: 0.3663 data_time: 0.0229 memory: 5826 grad_norm: 3.2225 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8352 loss: 2.8352 2022/10/08 01:32:49 - mmengine - INFO - Epoch(train) [87][80/2119] lr: 4.0000e-02 eta: 13:02:55 time: 0.3295 data_time: 0.0293 memory: 5826 grad_norm: 3.1685 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6728 loss: 2.6728 2022/10/08 01:32:57 - mmengine - INFO - Epoch(train) [87][100/2119] lr: 4.0000e-02 eta: 13:02:49 time: 0.4051 data_time: 0.0229 memory: 5826 grad_norm: 3.1178 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5087 loss: 2.5087 2022/10/08 01:33:03 - mmengine - INFO - Epoch(train) [87][120/2119] lr: 4.0000e-02 eta: 13:02:42 time: 0.3325 data_time: 0.0206 memory: 5826 grad_norm: 3.1559 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7251 loss: 2.7251 2022/10/08 01:33:10 - mmengine - INFO - Epoch(train) [87][140/2119] lr: 4.0000e-02 eta: 13:02:35 time: 0.3556 data_time: 0.0210 memory: 5826 grad_norm: 3.1219 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6914 loss: 2.6914 2022/10/08 01:33:17 - mmengine - INFO - Epoch(train) [87][160/2119] lr: 4.0000e-02 eta: 13:02:28 time: 0.3413 data_time: 0.0256 memory: 5826 grad_norm: 3.1547 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6153 loss: 2.6153 2022/10/08 01:33:25 - mmengine - INFO - Epoch(train) [87][180/2119] lr: 4.0000e-02 eta: 13:02:22 time: 0.3840 data_time: 0.0213 memory: 5826 grad_norm: 3.0732 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.6888 loss: 2.6888 2022/10/08 01:33:32 - mmengine - INFO - Epoch(train) [87][200/2119] lr: 4.0000e-02 eta: 13:02:15 time: 0.3367 data_time: 0.0234 memory: 5826 grad_norm: 3.1733 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6055 loss: 2.6055 2022/10/08 01:33:39 - mmengine - INFO - Epoch(train) [87][220/2119] lr: 4.0000e-02 eta: 13:02:08 time: 0.3697 data_time: 0.0252 memory: 5826 grad_norm: 3.1285 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7613 loss: 2.7613 2022/10/08 01:33:46 - mmengine - INFO - Epoch(train) [87][240/2119] lr: 4.0000e-02 eta: 13:02:02 time: 0.3605 data_time: 0.0235 memory: 5826 grad_norm: 3.1497 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7118 loss: 2.7118 2022/10/08 01:33:53 - mmengine - INFO - Epoch(train) [87][260/2119] lr: 4.0000e-02 eta: 13:01:54 time: 0.3320 data_time: 0.0317 memory: 5826 grad_norm: 3.1002 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5917 loss: 2.5917 2022/10/08 01:34:00 - mmengine - INFO - Epoch(train) [87][280/2119] lr: 4.0000e-02 eta: 13:01:47 time: 0.3274 data_time: 0.0225 memory: 5826 grad_norm: 3.1177 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7934 loss: 2.7934 2022/10/08 01:34:07 - mmengine - INFO - Epoch(train) [87][300/2119] lr: 4.0000e-02 eta: 13:01:41 time: 0.3795 data_time: 0.0252 memory: 5826 grad_norm: 3.1121 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5732 loss: 2.5732 2022/10/08 01:34:14 - mmengine - INFO - Epoch(train) [87][320/2119] lr: 4.0000e-02 eta: 13:01:34 time: 0.3540 data_time: 0.0221 memory: 5826 grad_norm: 3.1507 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6325 loss: 2.6325 2022/10/08 01:34:22 - mmengine - INFO - Epoch(train) [87][340/2119] lr: 4.0000e-02 eta: 13:01:27 time: 0.3663 data_time: 0.0269 memory: 5826 grad_norm: 3.0447 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6432 loss: 2.6432 2022/10/08 01:34:28 - mmengine - INFO - Epoch(train) [87][360/2119] lr: 4.0000e-02 eta: 13:01:20 time: 0.3189 data_time: 0.0159 memory: 5826 grad_norm: 3.1149 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8293 loss: 2.8293 2022/10/08 01:34:34 - mmengine - INFO - Epoch(train) [87][380/2119] lr: 4.0000e-02 eta: 13:01:13 time: 0.3146 data_time: 0.0245 memory: 5826 grad_norm: 3.1120 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8358 loss: 2.8358 2022/10/08 01:34:42 - mmengine - INFO - Epoch(train) [87][400/2119] lr: 4.0000e-02 eta: 13:01:06 time: 0.3704 data_time: 0.0221 memory: 5826 grad_norm: 3.1242 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4994 loss: 2.4994 2022/10/08 01:34:48 - mmengine - INFO - Epoch(train) [87][420/2119] lr: 4.0000e-02 eta: 13:00:59 time: 0.3385 data_time: 0.0268 memory: 5826 grad_norm: 3.1263 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6951 loss: 2.6951 2022/10/08 01:34:56 - mmengine - INFO - Epoch(train) [87][440/2119] lr: 4.0000e-02 eta: 13:00:53 time: 0.3887 data_time: 0.0189 memory: 5826 grad_norm: 3.1672 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7491 loss: 2.7491 2022/10/08 01:35:03 - mmengine - INFO - Epoch(train) [87][460/2119] lr: 4.0000e-02 eta: 13:00:45 time: 0.3159 data_time: 0.0246 memory: 5826 grad_norm: 3.1270 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5102 loss: 2.5102 2022/10/08 01:35:10 - mmengine - INFO - Epoch(train) [87][480/2119] lr: 4.0000e-02 eta: 13:00:38 time: 0.3524 data_time: 0.0201 memory: 5826 grad_norm: 3.0848 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6960 loss: 2.6960 2022/10/08 01:35:17 - mmengine - INFO - Epoch(train) [87][500/2119] lr: 4.0000e-02 eta: 13:00:31 time: 0.3468 data_time: 0.0212 memory: 5826 grad_norm: 3.1416 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5979 loss: 2.5979 2022/10/08 01:35:23 - mmengine - INFO - Epoch(train) [87][520/2119] lr: 4.0000e-02 eta: 13:00:24 time: 0.3275 data_time: 0.0204 memory: 5826 grad_norm: 3.1238 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7537 loss: 2.7537 2022/10/08 01:35:30 - mmengine - INFO - Epoch(train) [87][540/2119] lr: 4.0000e-02 eta: 13:00:18 time: 0.3678 data_time: 0.0210 memory: 5826 grad_norm: 3.2066 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7859 loss: 2.7859 2022/10/08 01:35:37 - mmengine - INFO - Epoch(train) [87][560/2119] lr: 4.0000e-02 eta: 13:00:10 time: 0.3373 data_time: 0.0213 memory: 5826 grad_norm: 3.1550 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7908 loss: 2.7908 2022/10/08 01:35:44 - mmengine - INFO - Epoch(train) [87][580/2119] lr: 4.0000e-02 eta: 13:00:03 time: 0.3391 data_time: 0.0256 memory: 5826 grad_norm: 3.1426 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7624 loss: 2.7624 2022/10/08 01:35:52 - mmengine - INFO - Epoch(train) [87][600/2119] lr: 4.0000e-02 eta: 12:59:57 time: 0.3767 data_time: 0.0184 memory: 5826 grad_norm: 3.1179 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5586 loss: 2.5586 2022/10/08 01:35:59 - mmengine - INFO - Epoch(train) [87][620/2119] lr: 4.0000e-02 eta: 12:59:50 time: 0.3647 data_time: 0.0319 memory: 5826 grad_norm: 3.1063 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6217 loss: 2.6217 2022/10/08 01:36:05 - mmengine - INFO - Epoch(train) [87][640/2119] lr: 4.0000e-02 eta: 12:59:43 time: 0.3305 data_time: 0.0212 memory: 5826 grad_norm: 3.1236 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6094 loss: 2.6094 2022/10/08 01:36:12 - mmengine - INFO - Epoch(train) [87][660/2119] lr: 4.0000e-02 eta: 12:59:36 time: 0.3298 data_time: 0.0335 memory: 5826 grad_norm: 3.0802 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8104 loss: 2.8104 2022/10/08 01:36:20 - mmengine - INFO - Epoch(train) [87][680/2119] lr: 4.0000e-02 eta: 12:59:29 time: 0.3748 data_time: 0.0187 memory: 5826 grad_norm: 3.0916 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6590 loss: 2.6590 2022/10/08 01:36:26 - mmengine - INFO - Epoch(train) [87][700/2119] lr: 4.0000e-02 eta: 12:59:22 time: 0.3256 data_time: 0.0292 memory: 5826 grad_norm: 3.1198 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5047 loss: 2.5047 2022/10/08 01:36:34 - mmengine - INFO - Epoch(train) [87][720/2119] lr: 4.0000e-02 eta: 12:59:16 time: 0.4116 data_time: 0.0248 memory: 5826 grad_norm: 3.2004 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6419 loss: 2.6419 2022/10/08 01:36:40 - mmengine - INFO - Epoch(train) [87][740/2119] lr: 4.0000e-02 eta: 12:59:09 time: 0.3030 data_time: 0.0234 memory: 5826 grad_norm: 3.1220 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7037 loss: 2.7037 2022/10/08 01:36:48 - mmengine - INFO - Epoch(train) [87][760/2119] lr: 4.0000e-02 eta: 12:59:02 time: 0.3846 data_time: 0.0219 memory: 5826 grad_norm: 3.1507 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5814 loss: 2.5814 2022/10/08 01:36:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 01:36:54 - mmengine - INFO - Epoch(train) [87][780/2119] lr: 4.0000e-02 eta: 12:58:55 time: 0.2947 data_time: 0.0277 memory: 5826 grad_norm: 3.1186 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7505 loss: 2.7505 2022/10/08 01:37:01 - mmengine - INFO - Epoch(train) [87][800/2119] lr: 4.0000e-02 eta: 12:58:48 time: 0.3679 data_time: 0.0247 memory: 5826 grad_norm: 3.1037 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4428 loss: 2.4428 2022/10/08 01:37:07 - mmengine - INFO - Epoch(train) [87][820/2119] lr: 4.0000e-02 eta: 12:58:40 time: 0.3037 data_time: 0.0266 memory: 5826 grad_norm: 3.1492 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7062 loss: 2.7062 2022/10/08 01:37:16 - mmengine - INFO - Epoch(train) [87][840/2119] lr: 4.0000e-02 eta: 12:58:34 time: 0.4105 data_time: 0.0155 memory: 5826 grad_norm: 3.0800 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6123 loss: 2.6123 2022/10/08 01:37:22 - mmengine - INFO - Epoch(train) [87][860/2119] lr: 4.0000e-02 eta: 12:58:27 time: 0.3217 data_time: 0.0224 memory: 5826 grad_norm: 3.1175 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6806 loss: 2.6806 2022/10/08 01:37:29 - mmengine - INFO - Epoch(train) [87][880/2119] lr: 4.0000e-02 eta: 12:58:20 time: 0.3518 data_time: 0.0228 memory: 5826 grad_norm: 3.1057 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7105 loss: 2.7105 2022/10/08 01:37:36 - mmengine - INFO - Epoch(train) [87][900/2119] lr: 4.0000e-02 eta: 12:58:13 time: 0.3249 data_time: 0.0259 memory: 5826 grad_norm: 3.1410 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6845 loss: 2.6845 2022/10/08 01:37:43 - mmengine - INFO - Epoch(train) [87][920/2119] lr: 4.0000e-02 eta: 12:58:06 time: 0.3592 data_time: 0.0230 memory: 5826 grad_norm: 3.1016 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4979 loss: 2.4979 2022/10/08 01:37:50 - mmengine - INFO - Epoch(train) [87][940/2119] lr: 4.0000e-02 eta: 12:57:59 time: 0.3528 data_time: 0.0261 memory: 5826 grad_norm: 3.1002 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7994 loss: 2.7994 2022/10/08 01:37:57 - mmengine - INFO - Epoch(train) [87][960/2119] lr: 4.0000e-02 eta: 12:57:53 time: 0.3675 data_time: 0.0253 memory: 5826 grad_norm: 3.1473 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5874 loss: 2.5874 2022/10/08 01:38:04 - mmengine - INFO - Epoch(train) [87][980/2119] lr: 4.0000e-02 eta: 12:57:46 time: 0.3379 data_time: 0.0265 memory: 5826 grad_norm: 3.1109 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8722 loss: 2.8722 2022/10/08 01:38:11 - mmengine - INFO - Epoch(train) [87][1000/2119] lr: 4.0000e-02 eta: 12:57:39 time: 0.3450 data_time: 0.0223 memory: 5826 grad_norm: 3.1213 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5754 loss: 2.5754 2022/10/08 01:38:18 - mmengine - INFO - Epoch(train) [87][1020/2119] lr: 4.0000e-02 eta: 12:57:32 time: 0.3661 data_time: 0.0293 memory: 5826 grad_norm: 3.1374 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7869 loss: 2.7869 2022/10/08 01:38:25 - mmengine - INFO - Epoch(train) [87][1040/2119] lr: 4.0000e-02 eta: 12:57:25 time: 0.3352 data_time: 0.0224 memory: 5826 grad_norm: 3.0886 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8657 loss: 2.8657 2022/10/08 01:38:31 - mmengine - INFO - Epoch(train) [87][1060/2119] lr: 4.0000e-02 eta: 12:57:17 time: 0.3001 data_time: 0.0325 memory: 5826 grad_norm: 3.0870 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6395 loss: 2.6395 2022/10/08 01:38:38 - mmengine - INFO - Epoch(train) [87][1080/2119] lr: 4.0000e-02 eta: 12:57:11 time: 0.3641 data_time: 0.0186 memory: 5826 grad_norm: 3.0634 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9696 loss: 2.9696 2022/10/08 01:38:45 - mmengine - INFO - Epoch(train) [87][1100/2119] lr: 4.0000e-02 eta: 12:57:04 time: 0.3477 data_time: 0.0227 memory: 5826 grad_norm: 3.1060 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5732 loss: 2.5732 2022/10/08 01:38:52 - mmengine - INFO - Epoch(train) [87][1120/2119] lr: 4.0000e-02 eta: 12:56:57 time: 0.3430 data_time: 0.0239 memory: 5826 grad_norm: 3.1282 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7567 loss: 2.7567 2022/10/08 01:38:59 - mmengine - INFO - Epoch(train) [87][1140/2119] lr: 4.0000e-02 eta: 12:56:50 time: 0.3499 data_time: 0.0333 memory: 5826 grad_norm: 3.1478 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9529 loss: 2.9529 2022/10/08 01:39:07 - mmengine - INFO - Epoch(train) [87][1160/2119] lr: 4.0000e-02 eta: 12:56:44 time: 0.3831 data_time: 0.0187 memory: 5826 grad_norm: 3.1407 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6928 loss: 2.6928 2022/10/08 01:39:13 - mmengine - INFO - Epoch(train) [87][1180/2119] lr: 4.0000e-02 eta: 12:56:36 time: 0.3115 data_time: 0.0271 memory: 5826 grad_norm: 3.2511 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.6497 loss: 2.6497 2022/10/08 01:39:20 - mmengine - INFO - Epoch(train) [87][1200/2119] lr: 4.0000e-02 eta: 12:56:30 time: 0.3722 data_time: 0.0205 memory: 5826 grad_norm: 3.1499 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5594 loss: 2.5594 2022/10/08 01:39:27 - mmengine - INFO - Epoch(train) [87][1220/2119] lr: 4.0000e-02 eta: 12:56:22 time: 0.3252 data_time: 0.0271 memory: 5826 grad_norm: 3.0991 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7566 loss: 2.7566 2022/10/08 01:39:35 - mmengine - INFO - Epoch(train) [87][1240/2119] lr: 4.0000e-02 eta: 12:56:16 time: 0.3894 data_time: 0.0258 memory: 5826 grad_norm: 3.1082 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6510 loss: 2.6510 2022/10/08 01:39:41 - mmengine - INFO - Epoch(train) [87][1260/2119] lr: 4.0000e-02 eta: 12:56:08 time: 0.3000 data_time: 0.0274 memory: 5826 grad_norm: 3.1627 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5190 loss: 2.5190 2022/10/08 01:39:48 - mmengine - INFO - Epoch(train) [87][1280/2119] lr: 4.0000e-02 eta: 12:56:01 time: 0.3398 data_time: 0.0269 memory: 5826 grad_norm: 3.1689 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6896 loss: 2.6896 2022/10/08 01:39:54 - mmengine - INFO - Epoch(train) [87][1300/2119] lr: 4.0000e-02 eta: 12:55:54 time: 0.3232 data_time: 0.0268 memory: 5826 grad_norm: 3.1200 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8977 loss: 2.8977 2022/10/08 01:40:01 - mmengine - INFO - Epoch(train) [87][1320/2119] lr: 4.0000e-02 eta: 12:55:47 time: 0.3461 data_time: 0.0187 memory: 5826 grad_norm: 3.0405 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8102 loss: 2.8102 2022/10/08 01:40:08 - mmengine - INFO - Epoch(train) [87][1340/2119] lr: 4.0000e-02 eta: 12:55:40 time: 0.3598 data_time: 0.0207 memory: 5826 grad_norm: 3.1079 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6769 loss: 2.6769 2022/10/08 01:40:15 - mmengine - INFO - Epoch(train) [87][1360/2119] lr: 4.0000e-02 eta: 12:55:34 time: 0.3603 data_time: 0.0210 memory: 5826 grad_norm: 3.1617 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6678 loss: 2.6678 2022/10/08 01:40:22 - mmengine - INFO - Epoch(train) [87][1380/2119] lr: 4.0000e-02 eta: 12:55:26 time: 0.3136 data_time: 0.0260 memory: 5826 grad_norm: 3.1339 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7192 loss: 2.7192 2022/10/08 01:40:29 - mmengine - INFO - Epoch(train) [87][1400/2119] lr: 4.0000e-02 eta: 12:55:20 time: 0.3629 data_time: 0.0236 memory: 5826 grad_norm: 3.1928 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7346 loss: 2.7346 2022/10/08 01:40:37 - mmengine - INFO - Epoch(train) [87][1420/2119] lr: 4.0000e-02 eta: 12:55:13 time: 0.3848 data_time: 0.0262 memory: 5826 grad_norm: 3.1648 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4865 loss: 2.4865 2022/10/08 01:40:44 - mmengine - INFO - Epoch(train) [87][1440/2119] lr: 4.0000e-02 eta: 12:55:06 time: 0.3482 data_time: 0.0257 memory: 5826 grad_norm: 3.0969 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.7146 loss: 2.7146 2022/10/08 01:40:50 - mmengine - INFO - Epoch(train) [87][1460/2119] lr: 4.0000e-02 eta: 12:54:59 time: 0.3096 data_time: 0.0218 memory: 5826 grad_norm: 3.1345 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6937 loss: 2.6937 2022/10/08 01:40:58 - mmengine - INFO - Epoch(train) [87][1480/2119] lr: 4.0000e-02 eta: 12:54:53 time: 0.3972 data_time: 0.0222 memory: 5826 grad_norm: 3.1804 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7431 loss: 2.7431 2022/10/08 01:41:04 - mmengine - INFO - Epoch(train) [87][1500/2119] lr: 4.0000e-02 eta: 12:54:45 time: 0.3201 data_time: 0.0231 memory: 5826 grad_norm: 3.1442 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8078 loss: 2.8078 2022/10/08 01:41:12 - mmengine - INFO - Epoch(train) [87][1520/2119] lr: 4.0000e-02 eta: 12:54:39 time: 0.3784 data_time: 0.0212 memory: 5826 grad_norm: 3.1435 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6494 loss: 2.6494 2022/10/08 01:41:19 - mmengine - INFO - Epoch(train) [87][1540/2119] lr: 4.0000e-02 eta: 12:54:32 time: 0.3429 data_time: 0.0215 memory: 5826 grad_norm: 3.1386 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.6526 loss: 2.6526 2022/10/08 01:41:26 - mmengine - INFO - Epoch(train) [87][1560/2119] lr: 4.0000e-02 eta: 12:54:25 time: 0.3536 data_time: 0.0275 memory: 5826 grad_norm: 3.1680 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8960 loss: 2.8960 2022/10/08 01:41:32 - mmengine - INFO - Epoch(train) [87][1580/2119] lr: 4.0000e-02 eta: 12:54:18 time: 0.3381 data_time: 0.0299 memory: 5826 grad_norm: 3.1176 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6923 loss: 2.6923 2022/10/08 01:41:40 - mmengine - INFO - Epoch(train) [87][1600/2119] lr: 4.0000e-02 eta: 12:54:12 time: 0.3845 data_time: 0.0237 memory: 5826 grad_norm: 3.1307 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6984 loss: 2.6984 2022/10/08 01:41:46 - mmengine - INFO - Epoch(train) [87][1620/2119] lr: 4.0000e-02 eta: 12:54:04 time: 0.3053 data_time: 0.0245 memory: 5826 grad_norm: 3.1709 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7770 loss: 2.7770 2022/10/08 01:41:53 - mmengine - INFO - Epoch(train) [87][1640/2119] lr: 4.0000e-02 eta: 12:53:57 time: 0.3591 data_time: 0.0247 memory: 5826 grad_norm: 3.1528 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5211 loss: 2.5211 2022/10/08 01:42:00 - mmengine - INFO - Epoch(train) [87][1660/2119] lr: 4.0000e-02 eta: 12:53:50 time: 0.3178 data_time: 0.0273 memory: 5826 grad_norm: 3.1492 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6382 loss: 2.6382 2022/10/08 01:42:07 - mmengine - INFO - Epoch(train) [87][1680/2119] lr: 4.0000e-02 eta: 12:53:44 time: 0.3852 data_time: 0.0207 memory: 5826 grad_norm: 3.1645 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8821 loss: 2.8821 2022/10/08 01:42:14 - mmengine - INFO - Epoch(train) [87][1700/2119] lr: 4.0000e-02 eta: 12:53:36 time: 0.3292 data_time: 0.0366 memory: 5826 grad_norm: 3.1127 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9926 loss: 2.9926 2022/10/08 01:42:21 - mmengine - INFO - Epoch(train) [87][1720/2119] lr: 4.0000e-02 eta: 12:53:29 time: 0.3434 data_time: 0.0172 memory: 5826 grad_norm: 3.1308 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7438 loss: 2.7438 2022/10/08 01:42:28 - mmengine - INFO - Epoch(train) [87][1740/2119] lr: 4.0000e-02 eta: 12:53:23 time: 0.3598 data_time: 0.0229 memory: 5826 grad_norm: 3.1466 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5898 loss: 2.5898 2022/10/08 01:42:35 - mmengine - INFO - Epoch(train) [87][1760/2119] lr: 4.0000e-02 eta: 12:53:16 time: 0.3547 data_time: 0.0218 memory: 5826 grad_norm: 3.1353 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6616 loss: 2.6616 2022/10/08 01:42:37 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 01:42:41 - mmengine - INFO - Epoch(train) [87][1780/2119] lr: 4.0000e-02 eta: 12:53:08 time: 0.2971 data_time: 0.0220 memory: 5826 grad_norm: 3.1329 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5172 loss: 2.5172 2022/10/08 01:42:48 - mmengine - INFO - Epoch(train) [87][1800/2119] lr: 4.0000e-02 eta: 12:53:01 time: 0.3597 data_time: 0.0260 memory: 5826 grad_norm: 3.1655 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9909 loss: 2.9909 2022/10/08 01:42:56 - mmengine - INFO - Epoch(train) [87][1820/2119] lr: 4.0000e-02 eta: 12:52:55 time: 0.3604 data_time: 0.0277 memory: 5826 grad_norm: 3.1535 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6926 loss: 2.6926 2022/10/08 01:43:03 - mmengine - INFO - Epoch(train) [87][1840/2119] lr: 4.0000e-02 eta: 12:52:48 time: 0.3562 data_time: 0.0198 memory: 5826 grad_norm: 3.1038 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0438 loss: 3.0438 2022/10/08 01:43:09 - mmengine - INFO - Epoch(train) [87][1860/2119] lr: 4.0000e-02 eta: 12:52:41 time: 0.3302 data_time: 0.0227 memory: 5826 grad_norm: 3.1801 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0211 loss: 3.0211 2022/10/08 01:43:17 - mmengine - INFO - Epoch(train) [87][1880/2119] lr: 4.0000e-02 eta: 12:52:34 time: 0.3686 data_time: 0.0231 memory: 5826 grad_norm: 3.1109 top1_acc: 0.1875 top5_acc: 0.6875 loss_cls: 2.9383 loss: 2.9383 2022/10/08 01:43:24 - mmengine - INFO - Epoch(train) [87][1900/2119] lr: 4.0000e-02 eta: 12:52:27 time: 0.3613 data_time: 0.0269 memory: 5826 grad_norm: 3.1008 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7316 loss: 2.7316 2022/10/08 01:43:31 - mmengine - INFO - Epoch(train) [87][1920/2119] lr: 4.0000e-02 eta: 12:52:21 time: 0.3490 data_time: 0.0174 memory: 5826 grad_norm: 3.1132 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8972 loss: 2.8972 2022/10/08 01:43:37 - mmengine - INFO - Epoch(train) [87][1940/2119] lr: 4.0000e-02 eta: 12:52:13 time: 0.3192 data_time: 0.0304 memory: 5826 grad_norm: 3.1275 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5649 loss: 2.5649 2022/10/08 01:43:45 - mmengine - INFO - Epoch(train) [87][1960/2119] lr: 4.0000e-02 eta: 12:52:07 time: 0.3980 data_time: 0.0198 memory: 5826 grad_norm: 3.0984 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6898 loss: 2.6898 2022/10/08 01:43:52 - mmengine - INFO - Epoch(train) [87][1980/2119] lr: 4.0000e-02 eta: 12:52:00 time: 0.3383 data_time: 0.0204 memory: 5826 grad_norm: 3.1607 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6702 loss: 2.6702 2022/10/08 01:44:00 - mmengine - INFO - Epoch(train) [87][2000/2119] lr: 4.0000e-02 eta: 12:51:53 time: 0.3788 data_time: 0.0195 memory: 5826 grad_norm: 3.1357 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7409 loss: 2.7409 2022/10/08 01:44:07 - mmengine - INFO - Epoch(train) [87][2020/2119] lr: 4.0000e-02 eta: 12:51:47 time: 0.3462 data_time: 0.0223 memory: 5826 grad_norm: 3.1158 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4780 loss: 2.4780 2022/10/08 01:44:15 - mmengine - INFO - Epoch(train) [87][2040/2119] lr: 4.0000e-02 eta: 12:51:41 time: 0.4182 data_time: 0.0175 memory: 5826 grad_norm: 3.0911 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.7575 loss: 2.7575 2022/10/08 01:44:21 - mmengine - INFO - Epoch(train) [87][2060/2119] lr: 4.0000e-02 eta: 12:51:33 time: 0.3008 data_time: 0.0288 memory: 5826 grad_norm: 3.1023 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9902 loss: 2.9902 2022/10/08 01:44:29 - mmengine - INFO - Epoch(train) [87][2080/2119] lr: 4.0000e-02 eta: 12:51:27 time: 0.3808 data_time: 0.0168 memory: 5826 grad_norm: 3.1164 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.7895 loss: 2.7895 2022/10/08 01:44:35 - mmengine - INFO - Epoch(train) [87][2100/2119] lr: 4.0000e-02 eta: 12:51:19 time: 0.3197 data_time: 0.0324 memory: 5826 grad_norm: 3.0806 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7548 loss: 2.7548 2022/10/08 01:44:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 01:44:40 - mmengine - INFO - Epoch(train) [87][2119/2119] lr: 4.0000e-02 eta: 12:51:19 time: 0.2801 data_time: 0.0214 memory: 5826 grad_norm: 3.1822 top1_acc: 0.3000 top5_acc: 0.6000 loss_cls: 2.5686 loss: 2.5686 2022/10/08 01:44:50 - mmengine - INFO - Epoch(train) [88][20/2119] lr: 4.0000e-02 eta: 12:51:03 time: 0.4710 data_time: 0.1304 memory: 5826 grad_norm: 3.1211 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7936 loss: 2.7936 2022/10/08 01:44:57 - mmengine - INFO - Epoch(train) [88][40/2119] lr: 4.0000e-02 eta: 12:50:56 time: 0.3621 data_time: 0.0161 memory: 5826 grad_norm: 3.0677 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4723 loss: 2.4723 2022/10/08 01:45:04 - mmengine - INFO - Epoch(train) [88][60/2119] lr: 4.0000e-02 eta: 12:50:49 time: 0.3640 data_time: 0.0265 memory: 5826 grad_norm: 3.1282 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6578 loss: 2.6578 2022/10/08 01:45:11 - mmengine - INFO - Epoch(train) [88][80/2119] lr: 4.0000e-02 eta: 12:50:42 time: 0.3210 data_time: 0.0220 memory: 5826 grad_norm: 3.1676 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6799 loss: 2.6799 2022/10/08 01:45:18 - mmengine - INFO - Epoch(train) [88][100/2119] lr: 4.0000e-02 eta: 12:50:35 time: 0.3623 data_time: 0.0234 memory: 5826 grad_norm: 3.2203 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6255 loss: 2.6255 2022/10/08 01:45:25 - mmengine - INFO - Epoch(train) [88][120/2119] lr: 4.0000e-02 eta: 12:50:29 time: 0.3487 data_time: 0.0208 memory: 5826 grad_norm: 3.1639 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6864 loss: 2.6864 2022/10/08 01:45:32 - mmengine - INFO - Epoch(train) [88][140/2119] lr: 4.0000e-02 eta: 12:50:22 time: 0.3503 data_time: 0.0267 memory: 5826 grad_norm: 3.1510 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8174 loss: 2.8174 2022/10/08 01:45:39 - mmengine - INFO - Epoch(train) [88][160/2119] lr: 4.0000e-02 eta: 12:50:15 time: 0.3365 data_time: 0.0258 memory: 5826 grad_norm: 3.1273 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7312 loss: 2.7312 2022/10/08 01:45:46 - mmengine - INFO - Epoch(train) [88][180/2119] lr: 4.0000e-02 eta: 12:50:08 time: 0.3695 data_time: 0.0229 memory: 5826 grad_norm: 3.0657 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4993 loss: 2.4993 2022/10/08 01:45:52 - mmengine - INFO - Epoch(train) [88][200/2119] lr: 4.0000e-02 eta: 12:50:00 time: 0.2886 data_time: 0.0232 memory: 5826 grad_norm: 3.1466 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6803 loss: 2.6803 2022/10/08 01:46:00 - mmengine - INFO - Epoch(train) [88][220/2119] lr: 4.0000e-02 eta: 12:49:54 time: 0.3911 data_time: 0.0250 memory: 5826 grad_norm: 3.1439 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7513 loss: 2.7513 2022/10/08 01:46:07 - mmengine - INFO - Epoch(train) [88][240/2119] lr: 4.0000e-02 eta: 12:49:47 time: 0.3471 data_time: 0.0207 memory: 5826 grad_norm: 3.1328 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5754 loss: 2.5754 2022/10/08 01:46:14 - mmengine - INFO - Epoch(train) [88][260/2119] lr: 4.0000e-02 eta: 12:49:40 time: 0.3676 data_time: 0.0210 memory: 5826 grad_norm: 3.1512 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6722 loss: 2.6722 2022/10/08 01:46:21 - mmengine - INFO - Epoch(train) [88][280/2119] lr: 4.0000e-02 eta: 12:49:34 time: 0.3552 data_time: 0.0259 memory: 5826 grad_norm: 3.0472 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4949 loss: 2.4949 2022/10/08 01:46:28 - mmengine - INFO - Epoch(train) [88][300/2119] lr: 4.0000e-02 eta: 12:49:26 time: 0.3216 data_time: 0.0265 memory: 5826 grad_norm: 3.1005 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6856 loss: 2.6856 2022/10/08 01:46:36 - mmengine - INFO - Epoch(train) [88][320/2119] lr: 4.0000e-02 eta: 12:49:20 time: 0.3997 data_time: 0.0284 memory: 5826 grad_norm: 3.1460 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8844 loss: 2.8844 2022/10/08 01:46:42 - mmengine - INFO - Epoch(train) [88][340/2119] lr: 4.0000e-02 eta: 12:49:13 time: 0.3043 data_time: 0.0247 memory: 5826 grad_norm: 3.1402 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.3884 loss: 2.3884 2022/10/08 01:46:49 - mmengine - INFO - Epoch(train) [88][360/2119] lr: 4.0000e-02 eta: 12:49:06 time: 0.3713 data_time: 0.0200 memory: 5826 grad_norm: 3.1817 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.6402 loss: 2.6402 2022/10/08 01:46:57 - mmengine - INFO - Epoch(train) [88][380/2119] lr: 4.0000e-02 eta: 12:48:59 time: 0.3791 data_time: 0.0243 memory: 5826 grad_norm: 3.1730 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8170 loss: 2.8170 2022/10/08 01:47:03 - mmengine - INFO - Epoch(train) [88][400/2119] lr: 4.0000e-02 eta: 12:48:52 time: 0.3081 data_time: 0.0249 memory: 5826 grad_norm: 3.1739 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7806 loss: 2.7806 2022/10/08 01:47:09 - mmengine - INFO - Epoch(train) [88][420/2119] lr: 4.0000e-02 eta: 12:48:45 time: 0.3204 data_time: 0.0251 memory: 5826 grad_norm: 3.1149 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7253 loss: 2.7253 2022/10/08 01:47:17 - mmengine - INFO - Epoch(train) [88][440/2119] lr: 4.0000e-02 eta: 12:48:38 time: 0.3928 data_time: 0.0228 memory: 5826 grad_norm: 3.1296 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5971 loss: 2.5971 2022/10/08 01:47:23 - mmengine - INFO - Epoch(train) [88][460/2119] lr: 4.0000e-02 eta: 12:48:31 time: 0.3142 data_time: 0.0189 memory: 5826 grad_norm: 3.1562 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5946 loss: 2.5946 2022/10/08 01:47:32 - mmengine - INFO - Epoch(train) [88][480/2119] lr: 4.0000e-02 eta: 12:48:25 time: 0.4075 data_time: 0.0180 memory: 5826 grad_norm: 3.1163 top1_acc: 0.3125 top5_acc: 0.3125 loss_cls: 2.8850 loss: 2.8850 2022/10/08 01:47:39 - mmengine - INFO - Epoch(train) [88][500/2119] lr: 4.0000e-02 eta: 12:48:19 time: 0.3793 data_time: 0.0229 memory: 5826 grad_norm: 3.1664 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7125 loss: 2.7125 2022/10/08 01:47:46 - mmengine - INFO - Epoch(train) [88][520/2119] lr: 4.0000e-02 eta: 12:48:11 time: 0.3277 data_time: 0.0227 memory: 5826 grad_norm: 3.1686 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7553 loss: 2.7553 2022/10/08 01:47:52 - mmengine - INFO - Epoch(train) [88][540/2119] lr: 4.0000e-02 eta: 12:48:04 time: 0.3224 data_time: 0.0266 memory: 5826 grad_norm: 3.1915 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6248 loss: 2.6248 2022/10/08 01:48:01 - mmengine - INFO - Epoch(train) [88][560/2119] lr: 4.0000e-02 eta: 12:47:58 time: 0.4262 data_time: 0.0176 memory: 5826 grad_norm: 3.1712 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.2207 loss: 2.2207 2022/10/08 01:48:07 - mmengine - INFO - Epoch(train) [88][580/2119] lr: 4.0000e-02 eta: 12:47:51 time: 0.3058 data_time: 0.0257 memory: 5826 grad_norm: 3.1543 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7967 loss: 2.7967 2022/10/08 01:48:14 - mmengine - INFO - Epoch(train) [88][600/2119] lr: 4.0000e-02 eta: 12:47:44 time: 0.3471 data_time: 0.0204 memory: 5826 grad_norm: 3.1473 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7523 loss: 2.7523 2022/10/08 01:48:21 - mmengine - INFO - Epoch(train) [88][620/2119] lr: 4.0000e-02 eta: 12:47:37 time: 0.3613 data_time: 0.0256 memory: 5826 grad_norm: 3.1935 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6642 loss: 2.6642 2022/10/08 01:48:28 - mmengine - INFO - Epoch(train) [88][640/2119] lr: 4.0000e-02 eta: 12:47:30 time: 0.3473 data_time: 0.0243 memory: 5826 grad_norm: 3.1895 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8072 loss: 2.8072 2022/10/08 01:48:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 01:48:35 - mmengine - INFO - Epoch(train) [88][660/2119] lr: 4.0000e-02 eta: 12:47:23 time: 0.3248 data_time: 0.0250 memory: 5826 grad_norm: 3.1914 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5941 loss: 2.5941 2022/10/08 01:48:42 - mmengine - INFO - Epoch(train) [88][680/2119] lr: 4.0000e-02 eta: 12:47:16 time: 0.3810 data_time: 0.0269 memory: 5826 grad_norm: 3.0715 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7053 loss: 2.7053 2022/10/08 01:48:48 - mmengine - INFO - Epoch(train) [88][700/2119] lr: 4.0000e-02 eta: 12:47:09 time: 0.2966 data_time: 0.0256 memory: 5826 grad_norm: 3.0857 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5121 loss: 2.5121 2022/10/08 01:48:56 - mmengine - INFO - Epoch(train) [88][720/2119] lr: 4.0000e-02 eta: 12:47:03 time: 0.4048 data_time: 0.0200 memory: 5826 grad_norm: 3.1487 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.7796 loss: 2.7796 2022/10/08 01:49:03 - mmengine - INFO - Epoch(train) [88][740/2119] lr: 4.0000e-02 eta: 12:46:56 time: 0.3315 data_time: 0.0229 memory: 5826 grad_norm: 3.1599 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6760 loss: 2.6760 2022/10/08 01:49:10 - mmengine - INFO - Epoch(train) [88][760/2119] lr: 4.0000e-02 eta: 12:46:49 time: 0.3737 data_time: 0.0209 memory: 5826 grad_norm: 3.1474 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7016 loss: 2.7016 2022/10/08 01:49:17 - mmengine - INFO - Epoch(train) [88][780/2119] lr: 4.0000e-02 eta: 12:46:42 time: 0.3161 data_time: 0.0232 memory: 5826 grad_norm: 3.2032 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.6315 loss: 2.6315 2022/10/08 01:49:24 - mmengine - INFO - Epoch(train) [88][800/2119] lr: 4.0000e-02 eta: 12:46:35 time: 0.3645 data_time: 0.0191 memory: 5826 grad_norm: 3.1309 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7890 loss: 2.7890 2022/10/08 01:49:31 - mmengine - INFO - Epoch(train) [88][820/2119] lr: 4.0000e-02 eta: 12:46:28 time: 0.3536 data_time: 0.0214 memory: 5826 grad_norm: 3.1082 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6999 loss: 2.6999 2022/10/08 01:49:38 - mmengine - INFO - Epoch(train) [88][840/2119] lr: 4.0000e-02 eta: 12:46:21 time: 0.3533 data_time: 0.0235 memory: 5826 grad_norm: 3.0870 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7532 loss: 2.7532 2022/10/08 01:49:44 - mmengine - INFO - Epoch(train) [88][860/2119] lr: 4.0000e-02 eta: 12:46:13 time: 0.2849 data_time: 0.0249 memory: 5826 grad_norm: 3.1323 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.0526 loss: 3.0526 2022/10/08 01:49:51 - mmengine - INFO - Epoch(train) [88][880/2119] lr: 4.0000e-02 eta: 12:46:07 time: 0.3472 data_time: 0.0240 memory: 5826 grad_norm: 3.0769 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8105 loss: 2.8105 2022/10/08 01:49:58 - mmengine - INFO - Epoch(train) [88][900/2119] lr: 4.0000e-02 eta: 12:46:00 time: 0.3662 data_time: 0.0246 memory: 5826 grad_norm: 3.0573 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.7494 loss: 2.7494 2022/10/08 01:50:05 - mmengine - INFO - Epoch(train) [88][920/2119] lr: 4.0000e-02 eta: 12:45:53 time: 0.3569 data_time: 0.0200 memory: 5826 grad_norm: 3.1456 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.5882 loss: 2.5882 2022/10/08 01:50:13 - mmengine - INFO - Epoch(train) [88][940/2119] lr: 4.0000e-02 eta: 12:45:47 time: 0.3747 data_time: 0.0257 memory: 5826 grad_norm: 3.0899 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6501 loss: 2.6501 2022/10/08 01:50:19 - mmengine - INFO - Epoch(train) [88][960/2119] lr: 4.0000e-02 eta: 12:45:39 time: 0.3156 data_time: 0.0286 memory: 5826 grad_norm: 3.1097 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5398 loss: 2.5398 2022/10/08 01:50:26 - mmengine - INFO - Epoch(train) [88][980/2119] lr: 4.0000e-02 eta: 12:45:32 time: 0.3395 data_time: 0.0225 memory: 5826 grad_norm: 3.1172 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6810 loss: 2.6810 2022/10/08 01:50:33 - mmengine - INFO - Epoch(train) [88][1000/2119] lr: 4.0000e-02 eta: 12:45:25 time: 0.3445 data_time: 0.0348 memory: 5826 grad_norm: 3.0812 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.5740 loss: 2.5740 2022/10/08 01:50:40 - mmengine - INFO - Epoch(train) [88][1020/2119] lr: 4.0000e-02 eta: 12:45:19 time: 0.3627 data_time: 0.0307 memory: 5826 grad_norm: 3.0894 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6437 loss: 2.6437 2022/10/08 01:50:47 - mmengine - INFO - Epoch(train) [88][1040/2119] lr: 4.0000e-02 eta: 12:45:12 time: 0.3633 data_time: 0.0211 memory: 5826 grad_norm: 3.1004 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5883 loss: 2.5883 2022/10/08 01:50:54 - mmengine - INFO - Epoch(train) [88][1060/2119] lr: 4.0000e-02 eta: 12:45:05 time: 0.3457 data_time: 0.0213 memory: 5826 grad_norm: 3.1388 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.8869 loss: 2.8869 2022/10/08 01:51:02 - mmengine - INFO - Epoch(train) [88][1080/2119] lr: 4.0000e-02 eta: 12:44:59 time: 0.3928 data_time: 0.0239 memory: 5826 grad_norm: 3.1165 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7775 loss: 2.7775 2022/10/08 01:51:08 - mmengine - INFO - Epoch(train) [88][1100/2119] lr: 4.0000e-02 eta: 12:44:51 time: 0.3141 data_time: 0.0230 memory: 5826 grad_norm: 3.1225 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8460 loss: 2.8460 2022/10/08 01:51:16 - mmengine - INFO - Epoch(train) [88][1120/2119] lr: 4.0000e-02 eta: 12:44:45 time: 0.3849 data_time: 0.0201 memory: 5826 grad_norm: 3.0983 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8681 loss: 2.8681 2022/10/08 01:51:22 - mmengine - INFO - Epoch(train) [88][1140/2119] lr: 4.0000e-02 eta: 12:44:37 time: 0.3169 data_time: 0.0245 memory: 5826 grad_norm: 3.1049 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7886 loss: 2.7886 2022/10/08 01:51:30 - mmengine - INFO - Epoch(train) [88][1160/2119] lr: 4.0000e-02 eta: 12:44:31 time: 0.3704 data_time: 0.0225 memory: 5826 grad_norm: 3.0728 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6235 loss: 2.6235 2022/10/08 01:51:36 - mmengine - INFO - Epoch(train) [88][1180/2119] lr: 4.0000e-02 eta: 12:44:24 time: 0.3185 data_time: 0.0221 memory: 5826 grad_norm: 3.1589 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6918 loss: 2.6918 2022/10/08 01:51:44 - mmengine - INFO - Epoch(train) [88][1200/2119] lr: 4.0000e-02 eta: 12:44:17 time: 0.3697 data_time: 0.0211 memory: 5826 grad_norm: 3.0954 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4553 loss: 2.4553 2022/10/08 01:51:50 - mmengine - INFO - Epoch(train) [88][1220/2119] lr: 4.0000e-02 eta: 12:44:10 time: 0.3366 data_time: 0.0217 memory: 5826 grad_norm: 3.1043 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4471 loss: 2.4471 2022/10/08 01:51:57 - mmengine - INFO - Epoch(train) [88][1240/2119] lr: 4.0000e-02 eta: 12:44:03 time: 0.3421 data_time: 0.0217 memory: 5826 grad_norm: 3.0974 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9016 loss: 2.9016 2022/10/08 01:52:04 - mmengine - INFO - Epoch(train) [88][1260/2119] lr: 4.0000e-02 eta: 12:43:56 time: 0.3416 data_time: 0.0175 memory: 5826 grad_norm: 3.1613 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6809 loss: 2.6809 2022/10/08 01:52:12 - mmengine - INFO - Epoch(train) [88][1280/2119] lr: 4.0000e-02 eta: 12:43:50 time: 0.3891 data_time: 0.0209 memory: 5826 grad_norm: 3.1879 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8001 loss: 2.8001 2022/10/08 01:52:19 - mmengine - INFO - Epoch(train) [88][1300/2119] lr: 4.0000e-02 eta: 12:43:42 time: 0.3368 data_time: 0.0258 memory: 5826 grad_norm: 3.1383 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6025 loss: 2.6025 2022/10/08 01:52:26 - mmengine - INFO - Epoch(train) [88][1320/2119] lr: 4.0000e-02 eta: 12:43:36 time: 0.3958 data_time: 0.0244 memory: 5826 grad_norm: 3.1174 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5924 loss: 2.5924 2022/10/08 01:52:34 - mmengine - INFO - Epoch(train) [88][1340/2119] lr: 4.0000e-02 eta: 12:43:29 time: 0.3580 data_time: 0.0235 memory: 5826 grad_norm: 3.1585 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9510 loss: 2.9510 2022/10/08 01:52:41 - mmengine - INFO - Epoch(train) [88][1360/2119] lr: 4.0000e-02 eta: 12:43:23 time: 0.3560 data_time: 0.0238 memory: 5826 grad_norm: 3.1275 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5918 loss: 2.5918 2022/10/08 01:52:48 - mmengine - INFO - Epoch(train) [88][1380/2119] lr: 4.0000e-02 eta: 12:43:16 time: 0.3500 data_time: 0.0265 memory: 5826 grad_norm: 3.0951 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9687 loss: 2.9687 2022/10/08 01:52:55 - mmengine - INFO - Epoch(train) [88][1400/2119] lr: 4.0000e-02 eta: 12:43:09 time: 0.3716 data_time: 0.0211 memory: 5826 grad_norm: 3.1232 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7829 loss: 2.7829 2022/10/08 01:53:01 - mmengine - INFO - Epoch(train) [88][1420/2119] lr: 4.0000e-02 eta: 12:43:02 time: 0.2985 data_time: 0.0281 memory: 5826 grad_norm: 3.0910 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.7033 loss: 2.7033 2022/10/08 01:53:09 - mmengine - INFO - Epoch(train) [88][1440/2119] lr: 4.0000e-02 eta: 12:42:55 time: 0.3697 data_time: 0.0212 memory: 5826 grad_norm: 3.1273 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6477 loss: 2.6477 2022/10/08 01:53:15 - mmengine - INFO - Epoch(train) [88][1460/2119] lr: 4.0000e-02 eta: 12:42:48 time: 0.3277 data_time: 0.0215 memory: 5826 grad_norm: 3.0909 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7949 loss: 2.7949 2022/10/08 01:53:23 - mmengine - INFO - Epoch(train) [88][1480/2119] lr: 4.0000e-02 eta: 12:42:41 time: 0.3822 data_time: 0.0220 memory: 5826 grad_norm: 3.1849 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6142 loss: 2.6142 2022/10/08 01:53:29 - mmengine - INFO - Epoch(train) [88][1500/2119] lr: 4.0000e-02 eta: 12:42:34 time: 0.3064 data_time: 0.0207 memory: 5826 grad_norm: 3.1525 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6960 loss: 2.6960 2022/10/08 01:53:37 - mmengine - INFO - Epoch(train) [88][1520/2119] lr: 4.0000e-02 eta: 12:42:27 time: 0.3872 data_time: 0.0202 memory: 5826 grad_norm: 3.1598 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8469 loss: 2.8469 2022/10/08 01:53:44 - mmengine - INFO - Epoch(train) [88][1540/2119] lr: 4.0000e-02 eta: 12:42:21 time: 0.3594 data_time: 0.0225 memory: 5826 grad_norm: 3.1201 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7383 loss: 2.7383 2022/10/08 01:53:51 - mmengine - INFO - Epoch(train) [88][1560/2119] lr: 4.0000e-02 eta: 12:42:14 time: 0.3490 data_time: 0.0245 memory: 5826 grad_norm: 3.0807 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6742 loss: 2.6742 2022/10/08 01:53:58 - mmengine - INFO - Epoch(train) [88][1580/2119] lr: 4.0000e-02 eta: 12:42:07 time: 0.3392 data_time: 0.0245 memory: 5826 grad_norm: 3.1941 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7730 loss: 2.7730 2022/10/08 01:54:05 - mmengine - INFO - Epoch(train) [88][1600/2119] lr: 4.0000e-02 eta: 12:42:00 time: 0.3444 data_time: 0.0216 memory: 5826 grad_norm: 3.2643 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 3.0136 loss: 3.0136 2022/10/08 01:54:12 - mmengine - INFO - Epoch(train) [88][1620/2119] lr: 4.0000e-02 eta: 12:41:53 time: 0.3506 data_time: 0.0232 memory: 5826 grad_norm: 3.1079 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4286 loss: 2.4286 2022/10/08 01:54:19 - mmengine - INFO - Epoch(train) [88][1640/2119] lr: 4.0000e-02 eta: 12:41:46 time: 0.3746 data_time: 0.0257 memory: 5826 grad_norm: 3.1509 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7540 loss: 2.7540 2022/10/08 01:54:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 01:54:26 - mmengine - INFO - Epoch(train) [88][1660/2119] lr: 4.0000e-02 eta: 12:41:39 time: 0.3294 data_time: 0.0211 memory: 5826 grad_norm: 3.1703 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7362 loss: 2.7362 2022/10/08 01:54:33 - mmengine - INFO - Epoch(train) [88][1680/2119] lr: 4.0000e-02 eta: 12:41:33 time: 0.3687 data_time: 0.0204 memory: 5826 grad_norm: 3.1321 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.1089 loss: 3.1089 2022/10/08 01:54:39 - mmengine - INFO - Epoch(train) [88][1700/2119] lr: 4.0000e-02 eta: 12:41:25 time: 0.2842 data_time: 0.0235 memory: 5826 grad_norm: 3.1233 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9333 loss: 2.9333 2022/10/08 01:54:46 - mmengine - INFO - Epoch(train) [88][1720/2119] lr: 4.0000e-02 eta: 12:41:18 time: 0.3840 data_time: 0.0239 memory: 5826 grad_norm: 3.1122 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7864 loss: 2.7864 2022/10/08 01:54:53 - mmengine - INFO - Epoch(train) [88][1740/2119] lr: 4.0000e-02 eta: 12:41:11 time: 0.3237 data_time: 0.0209 memory: 5826 grad_norm: 3.0716 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.8384 loss: 2.8384 2022/10/08 01:55:00 - mmengine - INFO - Epoch(train) [88][1760/2119] lr: 4.0000e-02 eta: 12:41:04 time: 0.3475 data_time: 0.0266 memory: 5826 grad_norm: 3.1071 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7686 loss: 2.7686 2022/10/08 01:55:07 - mmengine - INFO - Epoch(train) [88][1780/2119] lr: 4.0000e-02 eta: 12:40:57 time: 0.3600 data_time: 0.0372 memory: 5826 grad_norm: 3.0935 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.3614 loss: 2.3614 2022/10/08 01:55:14 - mmengine - INFO - Epoch(train) [88][1800/2119] lr: 4.0000e-02 eta: 12:40:51 time: 0.3586 data_time: 0.0251 memory: 5826 grad_norm: 3.1490 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6372 loss: 2.6372 2022/10/08 01:55:21 - mmengine - INFO - Epoch(train) [88][1820/2119] lr: 4.0000e-02 eta: 12:40:44 time: 0.3458 data_time: 0.0225 memory: 5826 grad_norm: 3.1521 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8937 loss: 2.8937 2022/10/08 01:55:29 - mmengine - INFO - Epoch(train) [88][1840/2119] lr: 4.0000e-02 eta: 12:40:37 time: 0.3917 data_time: 0.0201 memory: 5826 grad_norm: 3.1067 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5875 loss: 2.5875 2022/10/08 01:55:36 - mmengine - INFO - Epoch(train) [88][1860/2119] lr: 4.0000e-02 eta: 12:40:30 time: 0.3400 data_time: 0.0210 memory: 5826 grad_norm: 3.1105 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7725 loss: 2.7725 2022/10/08 01:55:42 - mmengine - INFO - Epoch(train) [88][1880/2119] lr: 4.0000e-02 eta: 12:40:23 time: 0.3213 data_time: 0.0185 memory: 5826 grad_norm: 3.1520 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7909 loss: 2.7909 2022/10/08 01:55:49 - mmengine - INFO - Epoch(train) [88][1900/2119] lr: 4.0000e-02 eta: 12:40:16 time: 0.3240 data_time: 0.0267 memory: 5826 grad_norm: 3.1396 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7211 loss: 2.7211 2022/10/08 01:55:56 - mmengine - INFO - Epoch(train) [88][1920/2119] lr: 4.0000e-02 eta: 12:40:09 time: 0.3534 data_time: 0.0224 memory: 5826 grad_norm: 3.1833 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5168 loss: 2.5168 2022/10/08 01:56:03 - mmengine - INFO - Epoch(train) [88][1940/2119] lr: 4.0000e-02 eta: 12:40:02 time: 0.3427 data_time: 0.0270 memory: 5826 grad_norm: 3.1189 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7373 loss: 2.7373 2022/10/08 01:56:10 - mmengine - INFO - Epoch(train) [88][1960/2119] lr: 4.0000e-02 eta: 12:39:55 time: 0.3482 data_time: 0.0239 memory: 5826 grad_norm: 3.1823 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8255 loss: 2.8255 2022/10/08 01:56:17 - mmengine - INFO - Epoch(train) [88][1980/2119] lr: 4.0000e-02 eta: 12:39:48 time: 0.3559 data_time: 0.0207 memory: 5826 grad_norm: 3.1155 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8364 loss: 2.8364 2022/10/08 01:56:25 - mmengine - INFO - Epoch(train) [88][2000/2119] lr: 4.0000e-02 eta: 12:39:42 time: 0.3933 data_time: 0.0235 memory: 5826 grad_norm: 3.1020 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9789 loss: 2.9789 2022/10/08 01:56:31 - mmengine - INFO - Epoch(train) [88][2020/2119] lr: 4.0000e-02 eta: 12:39:35 time: 0.3408 data_time: 0.0245 memory: 5826 grad_norm: 3.1323 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8502 loss: 2.8502 2022/10/08 01:56:39 - mmengine - INFO - Epoch(train) [88][2040/2119] lr: 4.0000e-02 eta: 12:39:28 time: 0.3611 data_time: 0.0265 memory: 5826 grad_norm: 3.1099 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5118 loss: 2.5118 2022/10/08 01:56:46 - mmengine - INFO - Epoch(train) [88][2060/2119] lr: 4.0000e-02 eta: 12:39:21 time: 0.3433 data_time: 0.0227 memory: 5826 grad_norm: 3.1289 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6788 loss: 2.6788 2022/10/08 01:56:53 - mmengine - INFO - Epoch(train) [88][2080/2119] lr: 4.0000e-02 eta: 12:39:15 time: 0.3731 data_time: 0.0218 memory: 5826 grad_norm: 3.1034 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6047 loss: 2.6047 2022/10/08 01:57:00 - mmengine - INFO - Epoch(train) [88][2100/2119] lr: 4.0000e-02 eta: 12:39:08 time: 0.3324 data_time: 0.0233 memory: 5826 grad_norm: 3.1542 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6216 loss: 2.6216 2022/10/08 01:57:06 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 01:57:06 - mmengine - INFO - Epoch(train) [88][2119/2119] lr: 4.0000e-02 eta: 12:39:08 time: 0.3149 data_time: 0.0224 memory: 5826 grad_norm: 3.1955 top1_acc: 0.5000 top5_acc: 0.6000 loss_cls: 2.7428 loss: 2.7428 2022/10/08 01:57:06 - mmengine - INFO - Saving checkpoint at 88 epochs 2022/10/08 01:57:17 - mmengine - INFO - Epoch(train) [89][20/2119] lr: 4.0000e-02 eta: 12:38:50 time: 0.3711 data_time: 0.1584 memory: 5826 grad_norm: 3.0870 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7123 loss: 2.7123 2022/10/08 01:57:24 - mmengine - INFO - Epoch(train) [89][40/2119] lr: 4.0000e-02 eta: 12:38:43 time: 0.3427 data_time: 0.1160 memory: 5826 grad_norm: 3.1156 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8232 loss: 2.8232 2022/10/08 01:57:32 - mmengine - INFO - Epoch(train) [89][60/2119] lr: 4.0000e-02 eta: 12:38:37 time: 0.4153 data_time: 0.0550 memory: 5826 grad_norm: 3.0958 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8461 loss: 2.8461 2022/10/08 01:57:38 - mmengine - INFO - Epoch(train) [89][80/2119] lr: 4.0000e-02 eta: 12:38:29 time: 0.2893 data_time: 0.0230 memory: 5826 grad_norm: 3.0715 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7426 loss: 2.7426 2022/10/08 01:57:46 - mmengine - INFO - Epoch(train) [89][100/2119] lr: 4.0000e-02 eta: 12:38:23 time: 0.3864 data_time: 0.0240 memory: 5826 grad_norm: 3.0659 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.5964 loss: 2.5964 2022/10/08 01:57:51 - mmengine - INFO - Epoch(train) [89][120/2119] lr: 4.0000e-02 eta: 12:38:15 time: 0.2916 data_time: 0.0233 memory: 5826 grad_norm: 3.1573 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7894 loss: 2.7894 2022/10/08 01:57:59 - mmengine - INFO - Epoch(train) [89][140/2119] lr: 4.0000e-02 eta: 12:38:09 time: 0.3851 data_time: 0.0250 memory: 5826 grad_norm: 3.0981 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8000 loss: 2.8000 2022/10/08 01:58:05 - mmengine - INFO - Epoch(train) [89][160/2119] lr: 4.0000e-02 eta: 12:38:01 time: 0.3155 data_time: 0.0247 memory: 5826 grad_norm: 3.1174 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6746 loss: 2.6746 2022/10/08 01:58:13 - mmengine - INFO - Epoch(train) [89][180/2119] lr: 4.0000e-02 eta: 12:37:55 time: 0.3865 data_time: 0.0197 memory: 5826 grad_norm: 3.1633 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6014 loss: 2.6014 2022/10/08 01:58:20 - mmengine - INFO - Epoch(train) [89][200/2119] lr: 4.0000e-02 eta: 12:37:48 time: 0.3278 data_time: 0.0237 memory: 5826 grad_norm: 3.1058 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6875 loss: 2.6875 2022/10/08 01:58:27 - mmengine - INFO - Epoch(train) [89][220/2119] lr: 4.0000e-02 eta: 12:37:41 time: 0.3809 data_time: 0.0246 memory: 5826 grad_norm: 3.0721 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7068 loss: 2.7068 2022/10/08 01:58:33 - mmengine - INFO - Epoch(train) [89][240/2119] lr: 4.0000e-02 eta: 12:37:34 time: 0.2907 data_time: 0.0242 memory: 5826 grad_norm: 3.1166 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5983 loss: 2.5983 2022/10/08 01:58:41 - mmengine - INFO - Epoch(train) [89][260/2119] lr: 4.0000e-02 eta: 12:37:27 time: 0.3762 data_time: 0.0200 memory: 5826 grad_norm: 3.0688 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6574 loss: 2.6574 2022/10/08 01:58:48 - mmengine - INFO - Epoch(train) [89][280/2119] lr: 4.0000e-02 eta: 12:37:20 time: 0.3473 data_time: 0.0264 memory: 5826 grad_norm: 3.1663 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5700 loss: 2.5700 2022/10/08 01:58:55 - mmengine - INFO - Epoch(train) [89][300/2119] lr: 4.0000e-02 eta: 12:37:13 time: 0.3612 data_time: 0.0194 memory: 5826 grad_norm: 3.1630 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8059 loss: 2.8059 2022/10/08 01:59:01 - mmengine - INFO - Epoch(train) [89][320/2119] lr: 4.0000e-02 eta: 12:37:06 time: 0.3210 data_time: 0.0206 memory: 5826 grad_norm: 3.1365 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.4315 loss: 2.4315 2022/10/08 01:59:09 - mmengine - INFO - Epoch(train) [89][340/2119] lr: 4.0000e-02 eta: 12:36:59 time: 0.3589 data_time: 0.0237 memory: 5826 grad_norm: 3.1337 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6974 loss: 2.6974 2022/10/08 01:59:15 - mmengine - INFO - Epoch(train) [89][360/2119] lr: 4.0000e-02 eta: 12:36:52 time: 0.3236 data_time: 0.0221 memory: 5826 grad_norm: 3.1429 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7354 loss: 2.7354 2022/10/08 01:59:22 - mmengine - INFO - Epoch(train) [89][380/2119] lr: 4.0000e-02 eta: 12:36:45 time: 0.3497 data_time: 0.0220 memory: 5826 grad_norm: 3.1505 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8830 loss: 2.8830 2022/10/08 01:59:30 - mmengine - INFO - Epoch(train) [89][400/2119] lr: 4.0000e-02 eta: 12:36:39 time: 0.3815 data_time: 0.0226 memory: 5826 grad_norm: 3.1020 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6350 loss: 2.6350 2022/10/08 01:59:37 - mmengine - INFO - Epoch(train) [89][420/2119] lr: 4.0000e-02 eta: 12:36:32 time: 0.3634 data_time: 0.0203 memory: 5826 grad_norm: 3.0969 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6381 loss: 2.6381 2022/10/08 01:59:44 - mmengine - INFO - Epoch(train) [89][440/2119] lr: 4.0000e-02 eta: 12:36:25 time: 0.3353 data_time: 0.0251 memory: 5826 grad_norm: 3.1426 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7308 loss: 2.7308 2022/10/08 01:59:52 - mmengine - INFO - Epoch(train) [89][460/2119] lr: 4.0000e-02 eta: 12:36:19 time: 0.4314 data_time: 0.0198 memory: 5826 grad_norm: 3.0845 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7293 loss: 2.7293 2022/10/08 01:59:58 - mmengine - INFO - Epoch(train) [89][480/2119] lr: 4.0000e-02 eta: 12:36:12 time: 0.3031 data_time: 0.0233 memory: 5826 grad_norm: 3.1461 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5239 loss: 2.5239 2022/10/08 02:00:09 - mmengine - INFO - Epoch(train) [89][500/2119] lr: 4.0000e-02 eta: 12:36:08 time: 0.5447 data_time: 0.0228 memory: 5826 grad_norm: 3.1510 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6192 loss: 2.6192 2022/10/08 02:00:15 - mmengine - INFO - Epoch(train) [89][520/2119] lr: 4.0000e-02 eta: 12:36:00 time: 0.2826 data_time: 0.0270 memory: 5826 grad_norm: 3.1312 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4969 loss: 2.4969 2022/10/08 02:00:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 02:00:22 - mmengine - INFO - Epoch(train) [89][540/2119] lr: 4.0000e-02 eta: 12:35:53 time: 0.3394 data_time: 0.0216 memory: 5826 grad_norm: 3.1546 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7232 loss: 2.7232 2022/10/08 02:00:29 - mmengine - INFO - Epoch(train) [89][560/2119] lr: 4.0000e-02 eta: 12:35:46 time: 0.3451 data_time: 0.0258 memory: 5826 grad_norm: 3.1444 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7926 loss: 2.7926 2022/10/08 02:00:36 - mmengine - INFO - Epoch(train) [89][580/2119] lr: 4.0000e-02 eta: 12:35:39 time: 0.3935 data_time: 0.0324 memory: 5826 grad_norm: 3.1632 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8143 loss: 2.8143 2022/10/08 02:00:43 - mmengine - INFO - Epoch(train) [89][600/2119] lr: 4.0000e-02 eta: 12:35:32 time: 0.3300 data_time: 0.0219 memory: 5826 grad_norm: 3.1832 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5994 loss: 2.5994 2022/10/08 02:00:51 - mmengine - INFO - Epoch(train) [89][620/2119] lr: 4.0000e-02 eta: 12:35:26 time: 0.3829 data_time: 0.0266 memory: 5826 grad_norm: 3.1530 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8666 loss: 2.8666 2022/10/08 02:00:57 - mmengine - INFO - Epoch(train) [89][640/2119] lr: 4.0000e-02 eta: 12:35:19 time: 0.3367 data_time: 0.0222 memory: 5826 grad_norm: 3.2077 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7018 loss: 2.7018 2022/10/08 02:01:04 - mmengine - INFO - Epoch(train) [89][660/2119] lr: 4.0000e-02 eta: 12:35:12 time: 0.3435 data_time: 0.0202 memory: 5826 grad_norm: 3.1769 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7282 loss: 2.7282 2022/10/08 02:01:11 - mmengine - INFO - Epoch(train) [89][680/2119] lr: 4.0000e-02 eta: 12:35:05 time: 0.3439 data_time: 0.0233 memory: 5826 grad_norm: 3.0961 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.8475 loss: 2.8475 2022/10/08 02:01:19 - mmengine - INFO - Epoch(train) [89][700/2119] lr: 4.0000e-02 eta: 12:34:58 time: 0.3760 data_time: 0.0198 memory: 5826 grad_norm: 3.0855 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5139 loss: 2.5139 2022/10/08 02:01:26 - mmengine - INFO - Epoch(train) [89][720/2119] lr: 4.0000e-02 eta: 12:34:52 time: 0.3656 data_time: 0.0201 memory: 5826 grad_norm: 3.1784 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5752 loss: 2.5752 2022/10/08 02:01:33 - mmengine - INFO - Epoch(train) [89][740/2119] lr: 4.0000e-02 eta: 12:34:44 time: 0.3239 data_time: 0.0277 memory: 5826 grad_norm: 3.1263 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6195 loss: 2.6195 2022/10/08 02:01:40 - mmengine - INFO - Epoch(train) [89][760/2119] lr: 4.0000e-02 eta: 12:34:38 time: 0.3679 data_time: 0.0222 memory: 5826 grad_norm: 3.1783 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9114 loss: 2.9114 2022/10/08 02:01:47 - mmengine - INFO - Epoch(train) [89][780/2119] lr: 4.0000e-02 eta: 12:34:31 time: 0.3471 data_time: 0.0246 memory: 5826 grad_norm: 3.2203 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7355 loss: 2.7355 2022/10/08 02:01:54 - mmengine - INFO - Epoch(train) [89][800/2119] lr: 4.0000e-02 eta: 12:34:24 time: 0.3768 data_time: 0.0205 memory: 5826 grad_norm: 3.0874 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6652 loss: 2.6652 2022/10/08 02:02:01 - mmengine - INFO - Epoch(train) [89][820/2119] lr: 4.0000e-02 eta: 12:34:17 time: 0.3238 data_time: 0.0199 memory: 5826 grad_norm: 3.1037 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7583 loss: 2.7583 2022/10/08 02:02:08 - mmengine - INFO - Epoch(train) [89][840/2119] lr: 4.0000e-02 eta: 12:34:10 time: 0.3591 data_time: 0.0259 memory: 5826 grad_norm: 3.1572 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.9409 loss: 2.9409 2022/10/08 02:02:15 - mmengine - INFO - Epoch(train) [89][860/2119] lr: 4.0000e-02 eta: 12:34:03 time: 0.3499 data_time: 0.0250 memory: 5826 grad_norm: 3.1825 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7432 loss: 2.7432 2022/10/08 02:02:23 - mmengine - INFO - Epoch(train) [89][880/2119] lr: 4.0000e-02 eta: 12:33:57 time: 0.3829 data_time: 0.0236 memory: 5826 grad_norm: 3.1438 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6069 loss: 2.6069 2022/10/08 02:02:30 - mmengine - INFO - Epoch(train) [89][900/2119] lr: 4.0000e-02 eta: 12:33:50 time: 0.3398 data_time: 0.0227 memory: 5826 grad_norm: 3.1613 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7844 loss: 2.7844 2022/10/08 02:02:37 - mmengine - INFO - Epoch(train) [89][920/2119] lr: 4.0000e-02 eta: 12:33:43 time: 0.3731 data_time: 0.0248 memory: 5826 grad_norm: 3.1202 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9093 loss: 2.9093 2022/10/08 02:02:43 - mmengine - INFO - Epoch(train) [89][940/2119] lr: 4.0000e-02 eta: 12:33:36 time: 0.3142 data_time: 0.0236 memory: 5826 grad_norm: 3.2107 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7562 loss: 2.7562 2022/10/08 02:02:51 - mmengine - INFO - Epoch(train) [89][960/2119] lr: 4.0000e-02 eta: 12:33:29 time: 0.3688 data_time: 0.0224 memory: 5826 grad_norm: 3.1373 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.9217 loss: 2.9217 2022/10/08 02:02:57 - mmengine - INFO - Epoch(train) [89][980/2119] lr: 4.0000e-02 eta: 12:33:22 time: 0.3337 data_time: 0.0226 memory: 5826 grad_norm: 3.1563 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8307 loss: 2.8307 2022/10/08 02:03:05 - mmengine - INFO - Epoch(train) [89][1000/2119] lr: 4.0000e-02 eta: 12:33:16 time: 0.3739 data_time: 0.0210 memory: 5826 grad_norm: 3.1495 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.8186 loss: 2.8186 2022/10/08 02:03:12 - mmengine - INFO - Epoch(train) [89][1020/2119] lr: 4.0000e-02 eta: 12:33:09 time: 0.3402 data_time: 0.0224 memory: 5826 grad_norm: 3.0960 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6414 loss: 2.6414 2022/10/08 02:03:20 - mmengine - INFO - Epoch(train) [89][1040/2119] lr: 4.0000e-02 eta: 12:33:03 time: 0.4147 data_time: 0.0251 memory: 5826 grad_norm: 3.2116 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.6366 loss: 2.6366 2022/10/08 02:03:27 - mmengine - INFO - Epoch(train) [89][1060/2119] lr: 4.0000e-02 eta: 12:32:56 time: 0.3256 data_time: 0.0289 memory: 5826 grad_norm: 3.1462 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6845 loss: 2.6845 2022/10/08 02:03:33 - mmengine - INFO - Epoch(train) [89][1080/2119] lr: 4.0000e-02 eta: 12:32:48 time: 0.3176 data_time: 0.0207 memory: 5826 grad_norm: 3.0668 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5550 loss: 2.5550 2022/10/08 02:03:40 - mmengine - INFO - Epoch(train) [89][1100/2119] lr: 4.0000e-02 eta: 12:32:42 time: 0.3706 data_time: 0.0252 memory: 5826 grad_norm: 3.0945 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6123 loss: 2.6123 2022/10/08 02:03:48 - mmengine - INFO - Epoch(train) [89][1120/2119] lr: 4.0000e-02 eta: 12:32:35 time: 0.3915 data_time: 0.0294 memory: 5826 grad_norm: 3.1828 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7732 loss: 2.7732 2022/10/08 02:03:54 - mmengine - INFO - Epoch(train) [89][1140/2119] lr: 4.0000e-02 eta: 12:32:28 time: 0.3069 data_time: 0.0254 memory: 5826 grad_norm: 3.1296 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7717 loss: 2.7717 2022/10/08 02:04:01 - mmengine - INFO - Epoch(train) [89][1160/2119] lr: 4.0000e-02 eta: 12:32:21 time: 0.3545 data_time: 0.0263 memory: 5826 grad_norm: 3.0774 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6699 loss: 2.6699 2022/10/08 02:04:08 - mmengine - INFO - Epoch(train) [89][1180/2119] lr: 4.0000e-02 eta: 12:32:14 time: 0.3257 data_time: 0.0230 memory: 5826 grad_norm: 3.0996 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.6555 loss: 2.6555 2022/10/08 02:04:15 - mmengine - INFO - Epoch(train) [89][1200/2119] lr: 4.0000e-02 eta: 12:32:07 time: 0.3659 data_time: 0.0335 memory: 5826 grad_norm: 3.1748 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8218 loss: 2.8218 2022/10/08 02:04:22 - mmengine - INFO - Epoch(train) [89][1220/2119] lr: 4.0000e-02 eta: 12:32:00 time: 0.3465 data_time: 0.0226 memory: 5826 grad_norm: 3.1607 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9887 loss: 2.9887 2022/10/08 02:04:29 - mmengine - INFO - Epoch(train) [89][1240/2119] lr: 4.0000e-02 eta: 12:31:53 time: 0.3310 data_time: 0.0289 memory: 5826 grad_norm: 3.1372 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7256 loss: 2.7256 2022/10/08 02:04:36 - mmengine - INFO - Epoch(train) [89][1260/2119] lr: 4.0000e-02 eta: 12:31:46 time: 0.3525 data_time: 0.0179 memory: 5826 grad_norm: 3.0932 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6734 loss: 2.6734 2022/10/08 02:04:43 - mmengine - INFO - Epoch(train) [89][1280/2119] lr: 4.0000e-02 eta: 12:31:39 time: 0.3515 data_time: 0.0210 memory: 5826 grad_norm: 3.1605 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8061 loss: 2.8061 2022/10/08 02:04:48 - mmengine - INFO - Epoch(train) [89][1300/2119] lr: 4.0000e-02 eta: 12:31:31 time: 0.2746 data_time: 0.0255 memory: 5826 grad_norm: 3.1532 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6148 loss: 2.6148 2022/10/08 02:04:57 - mmengine - INFO - Epoch(train) [89][1320/2119] lr: 4.0000e-02 eta: 12:31:25 time: 0.4245 data_time: 0.0245 memory: 5826 grad_norm: 3.1287 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6358 loss: 2.6358 2022/10/08 02:05:03 - mmengine - INFO - Epoch(train) [89][1340/2119] lr: 4.0000e-02 eta: 12:31:18 time: 0.3198 data_time: 0.0290 memory: 5826 grad_norm: 3.0674 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7470 loss: 2.7470 2022/10/08 02:05:11 - mmengine - INFO - Epoch(train) [89][1360/2119] lr: 4.0000e-02 eta: 12:31:12 time: 0.3865 data_time: 0.0250 memory: 5826 grad_norm: 3.1049 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5521 loss: 2.5521 2022/10/08 02:05:18 - mmengine - INFO - Epoch(train) [89][1380/2119] lr: 4.0000e-02 eta: 12:31:05 time: 0.3673 data_time: 0.0213 memory: 5826 grad_norm: 3.0783 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8374 loss: 2.8374 2022/10/08 02:05:25 - mmengine - INFO - Epoch(train) [89][1400/2119] lr: 4.0000e-02 eta: 12:30:58 time: 0.3512 data_time: 0.0231 memory: 5826 grad_norm: 3.1085 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8689 loss: 2.8689 2022/10/08 02:05:31 - mmengine - INFO - Epoch(train) [89][1420/2119] lr: 4.0000e-02 eta: 12:30:51 time: 0.2977 data_time: 0.0261 memory: 5826 grad_norm: 3.1223 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.9190 loss: 2.9190 2022/10/08 02:05:39 - mmengine - INFO - Epoch(train) [89][1440/2119] lr: 4.0000e-02 eta: 12:30:44 time: 0.3988 data_time: 0.0324 memory: 5826 grad_norm: 3.0820 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7555 loss: 2.7555 2022/10/08 02:05:46 - mmengine - INFO - Epoch(train) [89][1460/2119] lr: 4.0000e-02 eta: 12:30:37 time: 0.3151 data_time: 0.0224 memory: 5826 grad_norm: 3.1422 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.4722 loss: 2.4722 2022/10/08 02:05:53 - mmengine - INFO - Epoch(train) [89][1480/2119] lr: 4.0000e-02 eta: 12:30:30 time: 0.3524 data_time: 0.0258 memory: 5826 grad_norm: 3.1103 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7869 loss: 2.7869 2022/10/08 02:05:59 - mmengine - INFO - Epoch(train) [89][1500/2119] lr: 4.0000e-02 eta: 12:30:23 time: 0.3334 data_time: 0.0273 memory: 5826 grad_norm: 3.1884 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5237 loss: 2.5237 2022/10/08 02:06:06 - mmengine - INFO - Epoch(train) [89][1520/2119] lr: 4.0000e-02 eta: 12:30:16 time: 0.3503 data_time: 0.0208 memory: 5826 grad_norm: 3.1712 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6675 loss: 2.6675 2022/10/08 02:06:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 02:06:14 - mmengine - INFO - Epoch(train) [89][1540/2119] lr: 4.0000e-02 eta: 12:30:10 time: 0.3663 data_time: 0.0199 memory: 5826 grad_norm: 3.1473 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6483 loss: 2.6483 2022/10/08 02:06:20 - mmengine - INFO - Epoch(train) [89][1560/2119] lr: 4.0000e-02 eta: 12:30:03 time: 0.3381 data_time: 0.0256 memory: 5826 grad_norm: 3.1514 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7984 loss: 2.7984 2022/10/08 02:06:27 - mmengine - INFO - Epoch(train) [89][1580/2119] lr: 4.0000e-02 eta: 12:29:56 time: 0.3491 data_time: 0.0241 memory: 5826 grad_norm: 3.2363 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8333 loss: 2.8333 2022/10/08 02:06:34 - mmengine - INFO - Epoch(train) [89][1600/2119] lr: 4.0000e-02 eta: 12:29:49 time: 0.3375 data_time: 0.0215 memory: 5826 grad_norm: 3.1483 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7029 loss: 2.7029 2022/10/08 02:06:41 - mmengine - INFO - Epoch(train) [89][1620/2119] lr: 4.0000e-02 eta: 12:29:42 time: 0.3426 data_time: 0.0220 memory: 5826 grad_norm: 3.1295 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6922 loss: 2.6922 2022/10/08 02:06:49 - mmengine - INFO - Epoch(train) [89][1640/2119] lr: 4.0000e-02 eta: 12:29:35 time: 0.4056 data_time: 0.0248 memory: 5826 grad_norm: 3.1283 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.4236 loss: 2.4236 2022/10/08 02:06:55 - mmengine - INFO - Epoch(train) [89][1660/2119] lr: 4.0000e-02 eta: 12:29:28 time: 0.2959 data_time: 0.0206 memory: 5826 grad_norm: 3.1575 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7933 loss: 2.7933 2022/10/08 02:07:04 - mmengine - INFO - Epoch(train) [89][1680/2119] lr: 4.0000e-02 eta: 12:29:22 time: 0.4277 data_time: 0.0228 memory: 5826 grad_norm: 3.0770 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6205 loss: 2.6205 2022/10/08 02:07:10 - mmengine - INFO - Epoch(train) [89][1700/2119] lr: 4.0000e-02 eta: 12:29:15 time: 0.3202 data_time: 0.0192 memory: 5826 grad_norm: 3.1629 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8795 loss: 2.8795 2022/10/08 02:07:17 - mmengine - INFO - Epoch(train) [89][1720/2119] lr: 4.0000e-02 eta: 12:29:08 time: 0.3613 data_time: 0.0187 memory: 5826 grad_norm: 3.1539 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6935 loss: 2.6935 2022/10/08 02:07:23 - mmengine - INFO - Epoch(train) [89][1740/2119] lr: 4.0000e-02 eta: 12:29:00 time: 0.3010 data_time: 0.0280 memory: 5826 grad_norm: 3.1217 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7663 loss: 2.7663 2022/10/08 02:07:31 - mmengine - INFO - Epoch(train) [89][1760/2119] lr: 4.0000e-02 eta: 12:28:54 time: 0.4036 data_time: 0.0233 memory: 5826 grad_norm: 3.1320 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6967 loss: 2.6967 2022/10/08 02:07:38 - mmengine - INFO - Epoch(train) [89][1780/2119] lr: 4.0000e-02 eta: 12:28:47 time: 0.3135 data_time: 0.0246 memory: 5826 grad_norm: 3.1226 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7902 loss: 2.7902 2022/10/08 02:07:44 - mmengine - INFO - Epoch(train) [89][1800/2119] lr: 4.0000e-02 eta: 12:28:40 time: 0.3317 data_time: 0.0250 memory: 5826 grad_norm: 3.1570 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5490 loss: 2.5490 2022/10/08 02:07:51 - mmengine - INFO - Epoch(train) [89][1820/2119] lr: 4.0000e-02 eta: 12:28:33 time: 0.3491 data_time: 0.0296 memory: 5826 grad_norm: 3.0939 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6723 loss: 2.6723 2022/10/08 02:07:58 - mmengine - INFO - Epoch(train) [89][1840/2119] lr: 4.0000e-02 eta: 12:28:26 time: 0.3406 data_time: 0.0233 memory: 5826 grad_norm: 3.1485 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8303 loss: 2.8303 2022/10/08 02:08:05 - mmengine - INFO - Epoch(train) [89][1860/2119] lr: 4.0000e-02 eta: 12:28:19 time: 0.3347 data_time: 0.0271 memory: 5826 grad_norm: 3.1212 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7505 loss: 2.7505 2022/10/08 02:08:13 - mmengine - INFO - Epoch(train) [89][1880/2119] lr: 4.0000e-02 eta: 12:28:13 time: 0.4036 data_time: 0.0248 memory: 5826 grad_norm: 3.1207 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7502 loss: 2.7502 2022/10/08 02:08:19 - mmengine - INFO - Epoch(train) [89][1900/2119] lr: 4.0000e-02 eta: 12:28:05 time: 0.3032 data_time: 0.0237 memory: 5826 grad_norm: 3.1038 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7704 loss: 2.7704 2022/10/08 02:08:26 - mmengine - INFO - Epoch(train) [89][1920/2119] lr: 4.0000e-02 eta: 12:27:58 time: 0.3381 data_time: 0.0243 memory: 5826 grad_norm: 3.0763 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6844 loss: 2.6844 2022/10/08 02:08:33 - mmengine - INFO - Epoch(train) [89][1940/2119] lr: 4.0000e-02 eta: 12:27:51 time: 0.3432 data_time: 0.0284 memory: 5826 grad_norm: 3.1295 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5063 loss: 2.5063 2022/10/08 02:08:40 - mmengine - INFO - Epoch(train) [89][1960/2119] lr: 4.0000e-02 eta: 12:27:44 time: 0.3599 data_time: 0.0193 memory: 5826 grad_norm: 3.1330 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8534 loss: 2.8534 2022/10/08 02:08:47 - mmengine - INFO - Epoch(train) [89][1980/2119] lr: 4.0000e-02 eta: 12:27:37 time: 0.3481 data_time: 0.0209 memory: 5826 grad_norm: 3.1876 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6766 loss: 2.6766 2022/10/08 02:08:55 - mmengine - INFO - Epoch(train) [89][2000/2119] lr: 4.0000e-02 eta: 12:27:31 time: 0.4000 data_time: 0.0210 memory: 5826 grad_norm: 3.1168 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7088 loss: 2.7088 2022/10/08 02:09:00 - mmengine - INFO - Epoch(train) [89][2020/2119] lr: 4.0000e-02 eta: 12:27:23 time: 0.2817 data_time: 0.0271 memory: 5826 grad_norm: 3.1035 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7545 loss: 2.7545 2022/10/08 02:09:08 - mmengine - INFO - Epoch(train) [89][2040/2119] lr: 4.0000e-02 eta: 12:27:17 time: 0.3889 data_time: 0.0232 memory: 5826 grad_norm: 3.0943 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8635 loss: 2.8635 2022/10/08 02:09:15 - mmengine - INFO - Epoch(train) [89][2060/2119] lr: 4.0000e-02 eta: 12:27:10 time: 0.3325 data_time: 0.0204 memory: 5826 grad_norm: 3.1934 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5488 loss: 2.5488 2022/10/08 02:09:22 - mmengine - INFO - Epoch(train) [89][2080/2119] lr: 4.0000e-02 eta: 12:27:03 time: 0.3674 data_time: 0.0285 memory: 5826 grad_norm: 3.1352 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7523 loss: 2.7523 2022/10/08 02:09:30 - mmengine - INFO - Epoch(train) [89][2100/2119] lr: 4.0000e-02 eta: 12:26:57 time: 0.3739 data_time: 0.0226 memory: 5826 grad_norm: 3.0758 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8616 loss: 2.8616 2022/10/08 02:09:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 02:09:35 - mmengine - INFO - Epoch(train) [89][2119/2119] lr: 4.0000e-02 eta: 12:26:57 time: 0.2764 data_time: 0.0195 memory: 5826 grad_norm: 3.1464 top1_acc: 0.4000 top5_acc: 0.5000 loss_cls: 2.7802 loss: 2.7802 2022/10/08 02:09:45 - mmengine - INFO - Epoch(train) [90][20/2119] lr: 4.0000e-02 eta: 12:26:40 time: 0.4683 data_time: 0.1401 memory: 5826 grad_norm: 3.1007 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5758 loss: 2.5758 2022/10/08 02:09:52 - mmengine - INFO - Epoch(train) [90][40/2119] lr: 4.0000e-02 eta: 12:26:34 time: 0.3612 data_time: 0.0245 memory: 5826 grad_norm: 3.1115 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 3.0322 loss: 3.0322 2022/10/08 02:09:59 - mmengine - INFO - Epoch(train) [90][60/2119] lr: 4.0000e-02 eta: 12:26:27 time: 0.3531 data_time: 0.0233 memory: 5826 grad_norm: 3.1114 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7536 loss: 2.7536 2022/10/08 02:10:06 - mmengine - INFO - Epoch(train) [90][80/2119] lr: 4.0000e-02 eta: 12:26:20 time: 0.3500 data_time: 0.0243 memory: 5826 grad_norm: 3.1136 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5914 loss: 2.5914 2022/10/08 02:10:14 - mmengine - INFO - Epoch(train) [90][100/2119] lr: 4.0000e-02 eta: 12:26:14 time: 0.3995 data_time: 0.0255 memory: 5826 grad_norm: 3.1736 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8217 loss: 2.8217 2022/10/08 02:10:20 - mmengine - INFO - Epoch(train) [90][120/2119] lr: 4.0000e-02 eta: 12:26:06 time: 0.3047 data_time: 0.0244 memory: 5826 grad_norm: 3.0952 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7724 loss: 2.7724 2022/10/08 02:10:28 - mmengine - INFO - Epoch(train) [90][140/2119] lr: 4.0000e-02 eta: 12:26:00 time: 0.3799 data_time: 0.0229 memory: 5826 grad_norm: 3.0189 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7336 loss: 2.7336 2022/10/08 02:10:34 - mmengine - INFO - Epoch(train) [90][160/2119] lr: 4.0000e-02 eta: 12:25:52 time: 0.2989 data_time: 0.0242 memory: 5826 grad_norm: 3.1622 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8961 loss: 2.8961 2022/10/08 02:10:41 - mmengine - INFO - Epoch(train) [90][180/2119] lr: 4.0000e-02 eta: 12:25:46 time: 0.3917 data_time: 0.0208 memory: 5826 grad_norm: 3.1243 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5884 loss: 2.5884 2022/10/08 02:10:49 - mmengine - INFO - Epoch(train) [90][200/2119] lr: 4.0000e-02 eta: 12:25:39 time: 0.3765 data_time: 0.0241 memory: 5826 grad_norm: 3.1154 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4124 loss: 2.4124 2022/10/08 02:10:56 - mmengine - INFO - Epoch(train) [90][220/2119] lr: 4.0000e-02 eta: 12:25:32 time: 0.3517 data_time: 0.0226 memory: 5826 grad_norm: 3.1552 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9347 loss: 2.9347 2022/10/08 02:11:02 - mmengine - INFO - Epoch(train) [90][240/2119] lr: 4.0000e-02 eta: 12:25:25 time: 0.3264 data_time: 0.0264 memory: 5826 grad_norm: 3.1275 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6638 loss: 2.6638 2022/10/08 02:11:09 - mmengine - INFO - Epoch(train) [90][260/2119] lr: 4.0000e-02 eta: 12:25:18 time: 0.3318 data_time: 0.0288 memory: 5826 grad_norm: 3.0837 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.4574 loss: 2.4574 2022/10/08 02:11:16 - mmengine - INFO - Epoch(train) [90][280/2119] lr: 4.0000e-02 eta: 12:25:11 time: 0.3378 data_time: 0.0198 memory: 5826 grad_norm: 3.1058 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.4260 loss: 2.4260 2022/10/08 02:11:24 - mmengine - INFO - Epoch(train) [90][300/2119] lr: 4.0000e-02 eta: 12:25:05 time: 0.3948 data_time: 0.0161 memory: 5826 grad_norm: 3.1432 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8591 loss: 2.8591 2022/10/08 02:11:30 - mmengine - INFO - Epoch(train) [90][320/2119] lr: 4.0000e-02 eta: 12:24:57 time: 0.3252 data_time: 0.0275 memory: 5826 grad_norm: 3.1531 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6744 loss: 2.6744 2022/10/08 02:11:38 - mmengine - INFO - Epoch(train) [90][340/2119] lr: 4.0000e-02 eta: 12:24:51 time: 0.3888 data_time: 0.0210 memory: 5826 grad_norm: 3.1810 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7059 loss: 2.7059 2022/10/08 02:11:44 - mmengine - INFO - Epoch(train) [90][360/2119] lr: 4.0000e-02 eta: 12:24:43 time: 0.2997 data_time: 0.0272 memory: 5826 grad_norm: 3.1586 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6640 loss: 2.6640 2022/10/08 02:11:52 - mmengine - INFO - Epoch(train) [90][380/2119] lr: 4.0000e-02 eta: 12:24:37 time: 0.3846 data_time: 0.0241 memory: 5826 grad_norm: 3.1470 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4656 loss: 2.4656 2022/10/08 02:11:58 - mmengine - INFO - Epoch(train) [90][400/2119] lr: 4.0000e-02 eta: 12:24:30 time: 0.3204 data_time: 0.0210 memory: 5826 grad_norm: 3.1034 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7963 loss: 2.7963 2022/10/08 02:12:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 02:12:05 - mmengine - INFO - Epoch(train) [90][420/2119] lr: 4.0000e-02 eta: 12:24:23 time: 0.3339 data_time: 0.0217 memory: 5826 grad_norm: 3.1686 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5715 loss: 2.5715 2022/10/08 02:12:12 - mmengine - INFO - Epoch(train) [90][440/2119] lr: 4.0000e-02 eta: 12:24:16 time: 0.3517 data_time: 0.0232 memory: 5826 grad_norm: 3.0917 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9715 loss: 2.9715 2022/10/08 02:12:19 - mmengine - INFO - Epoch(train) [90][460/2119] lr: 4.0000e-02 eta: 12:24:09 time: 0.3431 data_time: 0.0271 memory: 5826 grad_norm: 3.1348 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6686 loss: 2.6686 2022/10/08 02:12:26 - mmengine - INFO - Epoch(train) [90][480/2119] lr: 4.0000e-02 eta: 12:24:02 time: 0.3566 data_time: 0.0239 memory: 5826 grad_norm: 3.1638 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6114 loss: 2.6114 2022/10/08 02:12:34 - mmengine - INFO - Epoch(train) [90][500/2119] lr: 4.0000e-02 eta: 12:23:56 time: 0.3810 data_time: 0.0214 memory: 5826 grad_norm: 3.1740 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6479 loss: 2.6479 2022/10/08 02:12:40 - mmengine - INFO - Epoch(train) [90][520/2119] lr: 4.0000e-02 eta: 12:23:48 time: 0.3131 data_time: 0.0327 memory: 5826 grad_norm: 3.0972 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.5418 loss: 2.5418 2022/10/08 02:12:48 - mmengine - INFO - Epoch(train) [90][540/2119] lr: 4.0000e-02 eta: 12:23:42 time: 0.4167 data_time: 0.0217 memory: 5826 grad_norm: 3.1236 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9996 loss: 2.9996 2022/10/08 02:12:54 - mmengine - INFO - Epoch(train) [90][560/2119] lr: 4.0000e-02 eta: 12:23:35 time: 0.2942 data_time: 0.0213 memory: 5826 grad_norm: 3.1208 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.6282 loss: 2.6282 2022/10/08 02:13:01 - mmengine - INFO - Epoch(train) [90][580/2119] lr: 4.0000e-02 eta: 12:23:28 time: 0.3533 data_time: 0.0246 memory: 5826 grad_norm: 3.1455 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6349 loss: 2.6349 2022/10/08 02:13:08 - mmengine - INFO - Epoch(train) [90][600/2119] lr: 4.0000e-02 eta: 12:23:21 time: 0.3410 data_time: 0.0277 memory: 5826 grad_norm: 3.1844 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.5915 loss: 2.5915 2022/10/08 02:13:14 - mmengine - INFO - Epoch(train) [90][620/2119] lr: 4.0000e-02 eta: 12:23:13 time: 0.3156 data_time: 0.0256 memory: 5826 grad_norm: 3.1338 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8426 loss: 2.8426 2022/10/08 02:13:21 - mmengine - INFO - Epoch(train) [90][640/2119] lr: 4.0000e-02 eta: 12:23:06 time: 0.3397 data_time: 0.0226 memory: 5826 grad_norm: 3.1748 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7090 loss: 2.7090 2022/10/08 02:13:28 - mmengine - INFO - Epoch(train) [90][660/2119] lr: 4.0000e-02 eta: 12:22:59 time: 0.3556 data_time: 0.0189 memory: 5826 grad_norm: 3.1664 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8048 loss: 2.8048 2022/10/08 02:13:35 - mmengine - INFO - Epoch(train) [90][680/2119] lr: 4.0000e-02 eta: 12:22:52 time: 0.3228 data_time: 0.0261 memory: 5826 grad_norm: 3.1543 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.6982 loss: 2.6982 2022/10/08 02:13:42 - mmengine - INFO - Epoch(train) [90][700/2119] lr: 4.0000e-02 eta: 12:22:46 time: 0.3862 data_time: 0.0220 memory: 5826 grad_norm: 3.1135 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.5196 loss: 2.5196 2022/10/08 02:13:49 - mmengine - INFO - Epoch(train) [90][720/2119] lr: 4.0000e-02 eta: 12:22:39 time: 0.3443 data_time: 0.0268 memory: 5826 grad_norm: 3.1421 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7197 loss: 2.7197 2022/10/08 02:13:56 - mmengine - INFO - Epoch(train) [90][740/2119] lr: 4.0000e-02 eta: 12:22:32 time: 0.3307 data_time: 0.0233 memory: 5826 grad_norm: 3.1120 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7598 loss: 2.7598 2022/10/08 02:14:03 - mmengine - INFO - Epoch(train) [90][760/2119] lr: 4.0000e-02 eta: 12:22:25 time: 0.3344 data_time: 0.0243 memory: 5826 grad_norm: 3.1121 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6698 loss: 2.6698 2022/10/08 02:14:10 - mmengine - INFO - Epoch(train) [90][780/2119] lr: 4.0000e-02 eta: 12:22:18 time: 0.3908 data_time: 0.0259 memory: 5826 grad_norm: 3.1324 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6618 loss: 2.6618 2022/10/08 02:14:16 - mmengine - INFO - Epoch(train) [90][800/2119] lr: 4.0000e-02 eta: 12:22:11 time: 0.3032 data_time: 0.0234 memory: 5826 grad_norm: 3.1633 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0407 loss: 3.0407 2022/10/08 02:14:24 - mmengine - INFO - Epoch(train) [90][820/2119] lr: 4.0000e-02 eta: 12:22:04 time: 0.3818 data_time: 0.0223 memory: 5826 grad_norm: 3.1616 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7276 loss: 2.7276 2022/10/08 02:14:31 - mmengine - INFO - Epoch(train) [90][840/2119] lr: 4.0000e-02 eta: 12:21:57 time: 0.3209 data_time: 0.0217 memory: 5826 grad_norm: 3.1072 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8136 loss: 2.8136 2022/10/08 02:14:38 - mmengine - INFO - Epoch(train) [90][860/2119] lr: 4.0000e-02 eta: 12:21:50 time: 0.3657 data_time: 0.0227 memory: 5826 grad_norm: 3.1321 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7440 loss: 2.7440 2022/10/08 02:14:45 - mmengine - INFO - Epoch(train) [90][880/2119] lr: 4.0000e-02 eta: 12:21:43 time: 0.3487 data_time: 0.0220 memory: 5826 grad_norm: 3.0689 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8301 loss: 2.8301 2022/10/08 02:14:53 - mmengine - INFO - Epoch(train) [90][900/2119] lr: 4.0000e-02 eta: 12:21:37 time: 0.3852 data_time: 0.0236 memory: 5826 grad_norm: 3.1274 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7383 loss: 2.7383 2022/10/08 02:14:59 - mmengine - INFO - Epoch(train) [90][920/2119] lr: 4.0000e-02 eta: 12:21:30 time: 0.3200 data_time: 0.0211 memory: 5826 grad_norm: 3.1739 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8983 loss: 2.8983 2022/10/08 02:15:06 - mmengine - INFO - Epoch(train) [90][940/2119] lr: 4.0000e-02 eta: 12:21:23 time: 0.3281 data_time: 0.0294 memory: 5826 grad_norm: 3.1270 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7975 loss: 2.7975 2022/10/08 02:15:12 - mmengine - INFO - Epoch(train) [90][960/2119] lr: 4.0000e-02 eta: 12:21:15 time: 0.3232 data_time: 0.0240 memory: 5826 grad_norm: 3.0838 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7109 loss: 2.7109 2022/10/08 02:15:20 - mmengine - INFO - Epoch(train) [90][980/2119] lr: 4.0000e-02 eta: 12:21:09 time: 0.3751 data_time: 0.0753 memory: 5826 grad_norm: 3.0989 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6815 loss: 2.6815 2022/10/08 02:15:26 - mmengine - INFO - Epoch(train) [90][1000/2119] lr: 4.0000e-02 eta: 12:21:02 time: 0.3413 data_time: 0.0642 memory: 5826 grad_norm: 3.1377 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8790 loss: 2.8790 2022/10/08 02:15:33 - mmengine - INFO - Epoch(train) [90][1020/2119] lr: 4.0000e-02 eta: 12:20:55 time: 0.3274 data_time: 0.0447 memory: 5826 grad_norm: 3.0979 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6544 loss: 2.6544 2022/10/08 02:15:40 - mmengine - INFO - Epoch(train) [90][1040/2119] lr: 4.0000e-02 eta: 12:20:48 time: 0.3637 data_time: 0.0522 memory: 5826 grad_norm: 3.1200 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7984 loss: 2.7984 2022/10/08 02:15:47 - mmengine - INFO - Epoch(train) [90][1060/2119] lr: 4.0000e-02 eta: 12:20:41 time: 0.3550 data_time: 0.0155 memory: 5826 grad_norm: 3.1168 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5225 loss: 2.5225 2022/10/08 02:15:54 - mmengine - INFO - Epoch(train) [90][1080/2119] lr: 4.0000e-02 eta: 12:20:34 time: 0.3341 data_time: 0.0218 memory: 5826 grad_norm: 3.0997 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4505 loss: 2.4505 2022/10/08 02:16:02 - mmengine - INFO - Epoch(train) [90][1100/2119] lr: 4.0000e-02 eta: 12:20:28 time: 0.4044 data_time: 0.0202 memory: 5826 grad_norm: 3.0966 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6094 loss: 2.6094 2022/10/08 02:16:08 - mmengine - INFO - Epoch(train) [90][1120/2119] lr: 4.0000e-02 eta: 12:20:20 time: 0.2969 data_time: 0.0220 memory: 5826 grad_norm: 3.1095 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7362 loss: 2.7362 2022/10/08 02:16:14 - mmengine - INFO - Epoch(train) [90][1140/2119] lr: 4.0000e-02 eta: 12:20:13 time: 0.3222 data_time: 0.0179 memory: 5826 grad_norm: 3.1693 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6179 loss: 2.6179 2022/10/08 02:16:22 - mmengine - INFO - Epoch(train) [90][1160/2119] lr: 4.0000e-02 eta: 12:20:06 time: 0.3551 data_time: 0.0244 memory: 5826 grad_norm: 3.1831 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7712 loss: 2.7712 2022/10/08 02:16:29 - mmengine - INFO - Epoch(train) [90][1180/2119] lr: 4.0000e-02 eta: 12:19:59 time: 0.3698 data_time: 0.0190 memory: 5826 grad_norm: 3.1205 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5598 loss: 2.5598 2022/10/08 02:16:36 - mmengine - INFO - Epoch(train) [90][1200/2119] lr: 4.0000e-02 eta: 12:19:52 time: 0.3307 data_time: 0.0240 memory: 5826 grad_norm: 3.1628 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7808 loss: 2.7808 2022/10/08 02:16:43 - mmengine - INFO - Epoch(train) [90][1220/2119] lr: 4.0000e-02 eta: 12:19:46 time: 0.3819 data_time: 0.0176 memory: 5826 grad_norm: 3.1849 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.7742 loss: 2.7742 2022/10/08 02:16:50 - mmengine - INFO - Epoch(train) [90][1240/2119] lr: 4.0000e-02 eta: 12:19:39 time: 0.3373 data_time: 0.0213 memory: 5826 grad_norm: 3.1408 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8576 loss: 2.8576 2022/10/08 02:16:57 - mmengine - INFO - Epoch(train) [90][1260/2119] lr: 4.0000e-02 eta: 12:19:32 time: 0.3505 data_time: 0.0242 memory: 5826 grad_norm: 3.1471 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6347 loss: 2.6347 2022/10/08 02:17:04 - mmengine - INFO - Epoch(train) [90][1280/2119] lr: 4.0000e-02 eta: 12:19:25 time: 0.3374 data_time: 0.0234 memory: 5826 grad_norm: 3.1128 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7035 loss: 2.7035 2022/10/08 02:17:11 - mmengine - INFO - Epoch(train) [90][1300/2119] lr: 4.0000e-02 eta: 12:19:18 time: 0.3463 data_time: 0.0129 memory: 5826 grad_norm: 3.1191 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9094 loss: 2.9094 2022/10/08 02:17:18 - mmengine - INFO - Epoch(train) [90][1320/2119] lr: 4.0000e-02 eta: 12:19:11 time: 0.3540 data_time: 0.0270 memory: 5826 grad_norm: 3.0234 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6847 loss: 2.6847 2022/10/08 02:17:25 - mmengine - INFO - Epoch(train) [90][1340/2119] lr: 4.0000e-02 eta: 12:19:04 time: 0.3459 data_time: 0.0218 memory: 5826 grad_norm: 3.0951 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5676 loss: 2.5676 2022/10/08 02:17:31 - mmengine - INFO - Epoch(train) [90][1360/2119] lr: 4.0000e-02 eta: 12:18:57 time: 0.3110 data_time: 0.0258 memory: 5826 grad_norm: 3.1210 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9044 loss: 2.9044 2022/10/08 02:17:38 - mmengine - INFO - Epoch(train) [90][1380/2119] lr: 4.0000e-02 eta: 12:18:50 time: 0.3762 data_time: 0.0315 memory: 5826 grad_norm: 3.1269 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8475 loss: 2.8475 2022/10/08 02:17:45 - mmengine - INFO - Epoch(train) [90][1400/2119] lr: 4.0000e-02 eta: 12:18:43 time: 0.3337 data_time: 0.0237 memory: 5826 grad_norm: 3.1756 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6725 loss: 2.6725 2022/10/08 02:17:48 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 02:17:52 - mmengine - INFO - Epoch(train) [90][1420/2119] lr: 4.0000e-02 eta: 12:18:36 time: 0.3613 data_time: 0.0186 memory: 5826 grad_norm: 3.1334 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8825 loss: 2.8825 2022/10/08 02:17:59 - mmengine - INFO - Epoch(train) [90][1440/2119] lr: 4.0000e-02 eta: 12:18:29 time: 0.3142 data_time: 0.0252 memory: 5826 grad_norm: 3.0861 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7156 loss: 2.7156 2022/10/08 02:18:06 - mmengine - INFO - Epoch(train) [90][1460/2119] lr: 4.0000e-02 eta: 12:18:22 time: 0.3456 data_time: 0.0195 memory: 5826 grad_norm: 3.1511 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6799 loss: 2.6799 2022/10/08 02:18:12 - mmengine - INFO - Epoch(train) [90][1480/2119] lr: 4.0000e-02 eta: 12:18:15 time: 0.3360 data_time: 0.0224 memory: 5826 grad_norm: 3.1014 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6507 loss: 2.6507 2022/10/08 02:18:19 - mmengine - INFO - Epoch(train) [90][1500/2119] lr: 4.0000e-02 eta: 12:18:08 time: 0.3440 data_time: 0.0327 memory: 5826 grad_norm: 3.1017 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8703 loss: 2.8703 2022/10/08 02:18:26 - mmengine - INFO - Epoch(train) [90][1520/2119] lr: 4.0000e-02 eta: 12:18:01 time: 0.3523 data_time: 0.0277 memory: 5826 grad_norm: 3.0879 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5034 loss: 2.5034 2022/10/08 02:18:33 - mmengine - INFO - Epoch(train) [90][1540/2119] lr: 4.0000e-02 eta: 12:17:54 time: 0.3292 data_time: 0.0238 memory: 5826 grad_norm: 3.1720 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6009 loss: 2.6009 2022/10/08 02:18:41 - mmengine - INFO - Epoch(train) [90][1560/2119] lr: 4.0000e-02 eta: 12:17:48 time: 0.3878 data_time: 0.0267 memory: 5826 grad_norm: 3.1315 top1_acc: 0.1875 top5_acc: 0.3125 loss_cls: 2.5765 loss: 2.5765 2022/10/08 02:18:47 - mmengine - INFO - Epoch(train) [90][1580/2119] lr: 4.0000e-02 eta: 12:17:40 time: 0.3307 data_time: 0.0198 memory: 5826 grad_norm: 3.1471 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7461 loss: 2.7461 2022/10/08 02:18:54 - mmengine - INFO - Epoch(train) [90][1600/2119] lr: 4.0000e-02 eta: 12:17:34 time: 0.3612 data_time: 0.0310 memory: 5826 grad_norm: 3.1429 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9466 loss: 2.9466 2022/10/08 02:19:02 - mmengine - INFO - Epoch(train) [90][1620/2119] lr: 4.0000e-02 eta: 12:17:27 time: 0.3793 data_time: 0.0219 memory: 5826 grad_norm: 3.0864 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6065 loss: 2.6065 2022/10/08 02:19:08 - mmengine - INFO - Epoch(train) [90][1640/2119] lr: 4.0000e-02 eta: 12:17:20 time: 0.3170 data_time: 0.0270 memory: 5826 grad_norm: 3.0661 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7738 loss: 2.7738 2022/10/08 02:19:16 - mmengine - INFO - Epoch(train) [90][1660/2119] lr: 4.0000e-02 eta: 12:17:13 time: 0.3875 data_time: 0.0204 memory: 5826 grad_norm: 3.0909 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8485 loss: 2.8485 2022/10/08 02:19:22 - mmengine - INFO - Epoch(train) [90][1680/2119] lr: 4.0000e-02 eta: 12:17:06 time: 0.3066 data_time: 0.0199 memory: 5826 grad_norm: 3.1123 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8124 loss: 2.8124 2022/10/08 02:19:30 - mmengine - INFO - Epoch(train) [90][1700/2119] lr: 4.0000e-02 eta: 12:17:00 time: 0.3886 data_time: 0.0204 memory: 5826 grad_norm: 3.1821 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7256 loss: 2.7256 2022/10/08 02:19:36 - mmengine - INFO - Epoch(train) [90][1720/2119] lr: 4.0000e-02 eta: 12:16:52 time: 0.3184 data_time: 0.0288 memory: 5826 grad_norm: 3.1207 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7254 loss: 2.7254 2022/10/08 02:19:45 - mmengine - INFO - Epoch(train) [90][1740/2119] lr: 4.0000e-02 eta: 12:16:46 time: 0.4068 data_time: 0.0235 memory: 5826 grad_norm: 3.1349 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9177 loss: 2.9177 2022/10/08 02:19:51 - mmengine - INFO - Epoch(train) [90][1760/2119] lr: 4.0000e-02 eta: 12:16:39 time: 0.3312 data_time: 0.0222 memory: 5826 grad_norm: 3.1067 top1_acc: 0.5625 top5_acc: 1.0000 loss_cls: 2.5768 loss: 2.5768 2022/10/08 02:19:59 - mmengine - INFO - Epoch(train) [90][1780/2119] lr: 4.0000e-02 eta: 12:16:33 time: 0.3828 data_time: 0.0233 memory: 5826 grad_norm: 3.0960 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6721 loss: 2.6721 2022/10/08 02:20:06 - mmengine - INFO - Epoch(train) [90][1800/2119] lr: 4.0000e-02 eta: 12:16:25 time: 0.3329 data_time: 0.0280 memory: 5826 grad_norm: 3.0722 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8996 loss: 2.8996 2022/10/08 02:20:13 - mmengine - INFO - Epoch(train) [90][1820/2119] lr: 4.0000e-02 eta: 12:16:19 time: 0.3716 data_time: 0.0258 memory: 5826 grad_norm: 3.2028 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.9520 loss: 2.9520 2022/10/08 02:20:20 - mmengine - INFO - Epoch(train) [90][1840/2119] lr: 4.0000e-02 eta: 12:16:12 time: 0.3548 data_time: 0.0203 memory: 5826 grad_norm: 3.1167 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8486 loss: 2.8486 2022/10/08 02:20:27 - mmengine - INFO - Epoch(train) [90][1860/2119] lr: 4.0000e-02 eta: 12:16:05 time: 0.3593 data_time: 0.0245 memory: 5826 grad_norm: 3.1195 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7119 loss: 2.7119 2022/10/08 02:20:34 - mmengine - INFO - Epoch(train) [90][1880/2119] lr: 4.0000e-02 eta: 12:15:58 time: 0.3170 data_time: 0.0201 memory: 5826 grad_norm: 3.0987 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5984 loss: 2.5984 2022/10/08 02:20:42 - mmengine - INFO - Epoch(train) [90][1900/2119] lr: 4.0000e-02 eta: 12:15:52 time: 0.3936 data_time: 0.0206 memory: 5826 grad_norm: 3.1249 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.8368 loss: 2.8368 2022/10/08 02:20:47 - mmengine - INFO - Epoch(train) [90][1920/2119] lr: 4.0000e-02 eta: 12:15:44 time: 0.2980 data_time: 0.0246 memory: 5826 grad_norm: 3.1359 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9446 loss: 2.9446 2022/10/08 02:20:55 - mmengine - INFO - Epoch(train) [90][1940/2119] lr: 4.0000e-02 eta: 12:15:37 time: 0.3726 data_time: 0.0261 memory: 5826 grad_norm: 3.1180 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7114 loss: 2.7114 2022/10/08 02:21:02 - mmengine - INFO - Epoch(train) [90][1960/2119] lr: 4.0000e-02 eta: 12:15:30 time: 0.3426 data_time: 0.0211 memory: 5826 grad_norm: 3.1147 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8239 loss: 2.8239 2022/10/08 02:21:09 - mmengine - INFO - Epoch(train) [90][1980/2119] lr: 4.0000e-02 eta: 12:15:24 time: 0.3762 data_time: 0.0246 memory: 5826 grad_norm: 3.1534 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5048 loss: 2.5048 2022/10/08 02:21:16 - mmengine - INFO - Epoch(train) [90][2000/2119] lr: 4.0000e-02 eta: 12:15:17 time: 0.3413 data_time: 0.0230 memory: 5826 grad_norm: 3.2029 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6957 loss: 2.6957 2022/10/08 02:21:24 - mmengine - INFO - Epoch(train) [90][2020/2119] lr: 4.0000e-02 eta: 12:15:10 time: 0.3788 data_time: 0.0259 memory: 5826 grad_norm: 3.1669 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7127 loss: 2.7127 2022/10/08 02:21:30 - mmengine - INFO - Epoch(train) [90][2040/2119] lr: 4.0000e-02 eta: 12:15:03 time: 0.3368 data_time: 0.0228 memory: 5826 grad_norm: 3.1378 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8729 loss: 2.8729 2022/10/08 02:21:37 - mmengine - INFO - Epoch(train) [90][2060/2119] lr: 4.0000e-02 eta: 12:14:56 time: 0.3461 data_time: 0.0226 memory: 5826 grad_norm: 3.0905 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.9458 loss: 2.9458 2022/10/08 02:21:44 - mmengine - INFO - Epoch(train) [90][2080/2119] lr: 4.0000e-02 eta: 12:14:49 time: 0.3071 data_time: 0.0231 memory: 5826 grad_norm: 3.1057 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7730 loss: 2.7730 2022/10/08 02:21:52 - mmengine - INFO - Epoch(train) [90][2100/2119] lr: 4.0000e-02 eta: 12:14:43 time: 0.4096 data_time: 0.0194 memory: 5826 grad_norm: 3.0862 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.5337 loss: 2.5337 2022/10/08 02:21:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 02:21:57 - mmengine - INFO - Epoch(train) [90][2119/2119] lr: 4.0000e-02 eta: 12:14:43 time: 0.2850 data_time: 0.0215 memory: 5826 grad_norm: 3.1016 top1_acc: 0.2000 top5_acc: 0.7000 loss_cls: 2.7277 loss: 2.7277 2022/10/08 02:22:06 - mmengine - INFO - Epoch(val) [90][20/137] eta: 0:00:49 time: 0.4236 data_time: 0.3540 memory: 1241 2022/10/08 02:22:12 - mmengine - INFO - Epoch(val) [90][40/137] eta: 0:00:28 time: 0.2978 data_time: 0.2334 memory: 1241 2022/10/08 02:22:19 - mmengine - INFO - Epoch(val) [90][60/137] eta: 0:00:27 time: 0.3559 data_time: 0.2907 memory: 1241 2022/10/08 02:22:24 - mmengine - INFO - Epoch(val) [90][80/137] eta: 0:00:14 time: 0.2526 data_time: 0.1889 memory: 1241 2022/10/08 02:22:31 - mmengine - INFO - Epoch(val) [90][100/137] eta: 0:00:13 time: 0.3637 data_time: 0.2979 memory: 1241 2022/10/08 02:22:36 - mmengine - INFO - Epoch(val) [90][120/137] eta: 0:00:04 time: 0.2368 data_time: 0.1720 memory: 1241 2022/10/08 02:22:48 - mmengine - INFO - Epoch(val) [90][137/137] acc/top1: 0.4356 acc/top5: 0.6746 acc/mean1: 0.4355 2022/10/08 02:22:48 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb/best_acc/top1_epoch_65.pth is removed 2022/10/08 02:22:56 - mmengine - INFO - The best checkpoint with 0.4356 acc/top1 at 90 epoch is saved to best_acc/top1_epoch_90.pth. 2022/10/08 02:23:04 - mmengine - INFO - Epoch(train) [91][20/2119] lr: 4.0000e-02 eta: 12:14:26 time: 0.4020 data_time: 0.1802 memory: 5826 grad_norm: 3.1161 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6741 loss: 2.6741 2022/10/08 02:23:10 - mmengine - INFO - Epoch(train) [91][40/2119] lr: 4.0000e-02 eta: 12:14:18 time: 0.2852 data_time: 0.0633 memory: 5826 grad_norm: 3.1869 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7044 loss: 2.7044 2022/10/08 02:23:17 - mmengine - INFO - Epoch(train) [91][60/2119] lr: 4.0000e-02 eta: 12:14:11 time: 0.3718 data_time: 0.0583 memory: 5826 grad_norm: 3.1253 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6287 loss: 2.6287 2022/10/08 02:23:24 - mmengine - INFO - Epoch(train) [91][80/2119] lr: 4.0000e-02 eta: 12:14:04 time: 0.3350 data_time: 0.0242 memory: 5826 grad_norm: 3.0384 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.4620 loss: 2.4620 2022/10/08 02:23:31 - mmengine - INFO - Epoch(train) [91][100/2119] lr: 4.0000e-02 eta: 12:13:57 time: 0.3502 data_time: 0.0225 memory: 5826 grad_norm: 3.1325 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5564 loss: 2.5564 2022/10/08 02:23:37 - mmengine - INFO - Epoch(train) [91][120/2119] lr: 4.0000e-02 eta: 12:13:50 time: 0.3188 data_time: 0.0230 memory: 5826 grad_norm: 3.1273 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5996 loss: 2.5996 2022/10/08 02:23:45 - mmengine - INFO - Epoch(train) [91][140/2119] lr: 4.0000e-02 eta: 12:13:44 time: 0.3821 data_time: 0.0219 memory: 5826 grad_norm: 3.1410 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5145 loss: 2.5145 2022/10/08 02:23:51 - mmengine - INFO - Epoch(train) [91][160/2119] lr: 4.0000e-02 eta: 12:13:36 time: 0.3224 data_time: 0.0258 memory: 5826 grad_norm: 3.1503 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6544 loss: 2.6544 2022/10/08 02:23:59 - mmengine - INFO - Epoch(train) [91][180/2119] lr: 4.0000e-02 eta: 12:13:30 time: 0.3916 data_time: 0.0251 memory: 5826 grad_norm: 3.0301 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.5340 loss: 2.5340 2022/10/08 02:24:05 - mmengine - INFO - Epoch(train) [91][200/2119] lr: 4.0000e-02 eta: 12:13:22 time: 0.2995 data_time: 0.0235 memory: 5826 grad_norm: 3.1583 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8841 loss: 2.8841 2022/10/08 02:24:13 - mmengine - INFO - Epoch(train) [91][220/2119] lr: 4.0000e-02 eta: 12:13:16 time: 0.3855 data_time: 0.0208 memory: 5826 grad_norm: 3.1210 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7152 loss: 2.7152 2022/10/08 02:24:20 - mmengine - INFO - Epoch(train) [91][240/2119] lr: 4.0000e-02 eta: 12:13:09 time: 0.3375 data_time: 0.0297 memory: 5826 grad_norm: 3.1751 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.9046 loss: 2.9046 2022/10/08 02:24:27 - mmengine - INFO - Epoch(train) [91][260/2119] lr: 4.0000e-02 eta: 12:13:02 time: 0.3511 data_time: 0.0231 memory: 5826 grad_norm: 3.1820 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6972 loss: 2.6972 2022/10/08 02:24:32 - mmengine - INFO - Epoch(train) [91][280/2119] lr: 4.0000e-02 eta: 12:12:55 time: 0.2979 data_time: 0.0240 memory: 5826 grad_norm: 3.1589 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5185 loss: 2.5185 2022/10/08 02:24:37 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 02:24:41 - mmengine - INFO - Epoch(train) [91][300/2119] lr: 4.0000e-02 eta: 12:12:48 time: 0.4064 data_time: 0.0199 memory: 5826 grad_norm: 3.1183 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.5893 loss: 2.5893 2022/10/08 02:24:47 - mmengine - INFO - Epoch(train) [91][320/2119] lr: 4.0000e-02 eta: 12:12:41 time: 0.3224 data_time: 0.0217 memory: 5826 grad_norm: 3.1662 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.7475 loss: 2.7475 2022/10/08 02:24:55 - mmengine - INFO - Epoch(train) [91][340/2119] lr: 4.0000e-02 eta: 12:12:35 time: 0.3820 data_time: 0.0290 memory: 5826 grad_norm: 3.1469 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9710 loss: 2.9710 2022/10/08 02:25:01 - mmengine - INFO - Epoch(train) [91][360/2119] lr: 4.0000e-02 eta: 12:12:27 time: 0.3130 data_time: 0.0412 memory: 5826 grad_norm: 3.1341 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8559 loss: 2.8559 2022/10/08 02:25:08 - mmengine - INFO - Epoch(train) [91][380/2119] lr: 4.0000e-02 eta: 12:12:21 time: 0.3654 data_time: 0.0229 memory: 5826 grad_norm: 3.1476 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6210 loss: 2.6210 2022/10/08 02:25:14 - mmengine - INFO - Epoch(train) [91][400/2119] lr: 4.0000e-02 eta: 12:12:13 time: 0.2985 data_time: 0.0236 memory: 5826 grad_norm: 3.1444 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5045 loss: 2.5045 2022/10/08 02:25:22 - mmengine - INFO - Epoch(train) [91][420/2119] lr: 4.0000e-02 eta: 12:12:07 time: 0.3888 data_time: 0.0323 memory: 5826 grad_norm: 3.1444 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.6268 loss: 2.6268 2022/10/08 02:25:29 - mmengine - INFO - Epoch(train) [91][440/2119] lr: 4.0000e-02 eta: 12:12:00 time: 0.3370 data_time: 0.0241 memory: 5826 grad_norm: 3.1075 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.4725 loss: 2.4725 2022/10/08 02:25:37 - mmengine - INFO - Epoch(train) [91][460/2119] lr: 4.0000e-02 eta: 12:11:53 time: 0.3916 data_time: 0.0206 memory: 5826 grad_norm: 3.1553 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.7963 loss: 2.7963 2022/10/08 02:25:44 - mmengine - INFO - Epoch(train) [91][480/2119] lr: 4.0000e-02 eta: 12:11:46 time: 0.3548 data_time: 0.0233 memory: 5826 grad_norm: 3.1343 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6159 loss: 2.6159 2022/10/08 02:25:51 - mmengine - INFO - Epoch(train) [91][500/2119] lr: 4.0000e-02 eta: 12:11:39 time: 0.3442 data_time: 0.0209 memory: 5826 grad_norm: 3.0698 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4945 loss: 2.4945 2022/10/08 02:25:57 - mmengine - INFO - Epoch(train) [91][520/2119] lr: 4.0000e-02 eta: 12:11:32 time: 0.3252 data_time: 0.0220 memory: 5826 grad_norm: 3.1457 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6319 loss: 2.6319 2022/10/08 02:26:05 - mmengine - INFO - Epoch(train) [91][540/2119] lr: 4.0000e-02 eta: 12:11:26 time: 0.3925 data_time: 0.0209 memory: 5826 grad_norm: 3.1021 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5416 loss: 2.5416 2022/10/08 02:26:11 - mmengine - INFO - Epoch(train) [91][560/2119] lr: 4.0000e-02 eta: 12:11:18 time: 0.3021 data_time: 0.0264 memory: 5826 grad_norm: 3.1332 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9365 loss: 2.9365 2022/10/08 02:26:18 - mmengine - INFO - Epoch(train) [91][580/2119] lr: 4.0000e-02 eta: 12:11:12 time: 0.3639 data_time: 0.0223 memory: 5826 grad_norm: 3.1864 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.6210 loss: 2.6210 2022/10/08 02:26:25 - mmengine - INFO - Epoch(train) [91][600/2119] lr: 4.0000e-02 eta: 12:11:05 time: 0.3476 data_time: 0.0204 memory: 5826 grad_norm: 3.0909 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5999 loss: 2.5999 2022/10/08 02:26:32 - mmengine - INFO - Epoch(train) [91][620/2119] lr: 4.0000e-02 eta: 12:10:58 time: 0.3266 data_time: 0.0255 memory: 5826 grad_norm: 3.1726 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7530 loss: 2.7530 2022/10/08 02:26:39 - mmengine - INFO - Epoch(train) [91][640/2119] lr: 4.0000e-02 eta: 12:10:51 time: 0.3516 data_time: 0.0223 memory: 5826 grad_norm: 3.1996 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6876 loss: 2.6876 2022/10/08 02:26:45 - mmengine - INFO - Epoch(train) [91][660/2119] lr: 4.0000e-02 eta: 12:10:43 time: 0.3243 data_time: 0.0223 memory: 5826 grad_norm: 3.1121 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7587 loss: 2.7587 2022/10/08 02:26:52 - mmengine - INFO - Epoch(train) [91][680/2119] lr: 4.0000e-02 eta: 12:10:37 time: 0.3433 data_time: 0.0203 memory: 5826 grad_norm: 3.1779 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6470 loss: 2.6470 2022/10/08 02:27:01 - mmengine - INFO - Epoch(train) [91][700/2119] lr: 4.0000e-02 eta: 12:10:30 time: 0.4150 data_time: 0.0233 memory: 5826 grad_norm: 3.1559 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7097 loss: 2.7097 2022/10/08 02:27:08 - mmengine - INFO - Epoch(train) [91][720/2119] lr: 4.0000e-02 eta: 12:10:24 time: 0.3591 data_time: 0.0286 memory: 5826 grad_norm: 3.1043 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7266 loss: 2.7266 2022/10/08 02:27:15 - mmengine - INFO - Epoch(train) [91][740/2119] lr: 4.0000e-02 eta: 12:10:17 time: 0.3552 data_time: 0.0153 memory: 5826 grad_norm: 3.1237 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7386 loss: 2.7386 2022/10/08 02:27:22 - mmengine - INFO - Epoch(train) [91][760/2119] lr: 4.0000e-02 eta: 12:10:10 time: 0.3626 data_time: 0.0404 memory: 5826 grad_norm: 3.1328 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7859 loss: 2.7859 2022/10/08 02:27:28 - mmengine - INFO - Epoch(train) [91][780/2119] lr: 4.0000e-02 eta: 12:10:03 time: 0.3032 data_time: 0.0168 memory: 5826 grad_norm: 3.1357 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8310 loss: 2.8310 2022/10/08 02:27:35 - mmengine - INFO - Epoch(train) [91][800/2119] lr: 4.0000e-02 eta: 12:09:56 time: 0.3544 data_time: 0.0260 memory: 5826 grad_norm: 3.1008 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7512 loss: 2.7512 2022/10/08 02:27:43 - mmengine - INFO - Epoch(train) [91][820/2119] lr: 4.0000e-02 eta: 12:09:49 time: 0.3777 data_time: 0.0179 memory: 5826 grad_norm: 3.1833 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7705 loss: 2.7705 2022/10/08 02:27:50 - mmengine - INFO - Epoch(train) [91][840/2119] lr: 4.0000e-02 eta: 12:09:42 time: 0.3389 data_time: 0.0248 memory: 5826 grad_norm: 3.1419 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6293 loss: 2.6293 2022/10/08 02:27:56 - mmengine - INFO - Epoch(train) [91][860/2119] lr: 4.0000e-02 eta: 12:09:35 time: 0.3208 data_time: 0.0164 memory: 5826 grad_norm: 3.1406 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6734 loss: 2.6734 2022/10/08 02:28:04 - mmengine - INFO - Epoch(train) [91][880/2119] lr: 4.0000e-02 eta: 12:09:28 time: 0.3740 data_time: 0.0216 memory: 5826 grad_norm: 3.1782 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6252 loss: 2.6252 2022/10/08 02:28:11 - mmengine - INFO - Epoch(train) [91][900/2119] lr: 4.0000e-02 eta: 12:09:22 time: 0.3615 data_time: 0.0160 memory: 5826 grad_norm: 3.1216 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6173 loss: 2.6173 2022/10/08 02:28:18 - mmengine - INFO - Epoch(train) [91][920/2119] lr: 4.0000e-02 eta: 12:09:15 time: 0.3536 data_time: 0.0207 memory: 5826 grad_norm: 3.1850 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7675 loss: 2.7675 2022/10/08 02:28:25 - mmengine - INFO - Epoch(train) [91][940/2119] lr: 4.0000e-02 eta: 12:09:08 time: 0.3804 data_time: 0.0181 memory: 5826 grad_norm: 3.1092 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8519 loss: 2.8519 2022/10/08 02:28:32 - mmengine - INFO - Epoch(train) [91][960/2119] lr: 4.0000e-02 eta: 12:09:01 time: 0.3424 data_time: 0.0312 memory: 5826 grad_norm: 3.0579 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9178 loss: 2.9178 2022/10/08 02:28:39 - mmengine - INFO - Epoch(train) [91][980/2119] lr: 4.0000e-02 eta: 12:08:54 time: 0.3344 data_time: 0.0198 memory: 5826 grad_norm: 3.2317 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9036 loss: 2.9036 2022/10/08 02:28:45 - mmengine - INFO - Epoch(train) [91][1000/2119] lr: 4.0000e-02 eta: 12:08:47 time: 0.3218 data_time: 0.0241 memory: 5826 grad_norm: 3.0868 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5951 loss: 2.5951 2022/10/08 02:28:53 - mmengine - INFO - Epoch(train) [91][1020/2119] lr: 4.0000e-02 eta: 12:08:40 time: 0.3770 data_time: 0.0201 memory: 5826 grad_norm: 3.1557 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.1293 loss: 3.1293 2022/10/08 02:29:00 - mmengine - INFO - Epoch(train) [91][1040/2119] lr: 4.0000e-02 eta: 12:08:34 time: 0.3540 data_time: 0.0255 memory: 5826 grad_norm: 3.1581 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7093 loss: 2.7093 2022/10/08 02:29:06 - mmengine - INFO - Epoch(train) [91][1060/2119] lr: 4.0000e-02 eta: 12:08:26 time: 0.3036 data_time: 0.0242 memory: 5826 grad_norm: 3.0959 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6461 loss: 2.6461 2022/10/08 02:29:13 - mmengine - INFO - Epoch(train) [91][1080/2119] lr: 4.0000e-02 eta: 12:08:19 time: 0.3301 data_time: 0.0301 memory: 5826 grad_norm: 3.1406 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8346 loss: 2.8346 2022/10/08 02:29:20 - mmengine - INFO - Epoch(train) [91][1100/2119] lr: 4.0000e-02 eta: 12:08:12 time: 0.3770 data_time: 0.0233 memory: 5826 grad_norm: 3.1253 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0169 loss: 3.0169 2022/10/08 02:29:27 - mmengine - INFO - Epoch(train) [91][1120/2119] lr: 4.0000e-02 eta: 12:08:05 time: 0.3264 data_time: 0.0248 memory: 5826 grad_norm: 3.0718 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6652 loss: 2.6652 2022/10/08 02:29:35 - mmengine - INFO - Epoch(train) [91][1140/2119] lr: 4.0000e-02 eta: 12:07:59 time: 0.4179 data_time: 0.0176 memory: 5826 grad_norm: 3.1162 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5683 loss: 2.5683 2022/10/08 02:29:42 - mmengine - INFO - Epoch(train) [91][1160/2119] lr: 4.0000e-02 eta: 12:07:52 time: 0.3243 data_time: 0.0242 memory: 5826 grad_norm: 3.1533 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7954 loss: 2.7954 2022/10/08 02:29:49 - mmengine - INFO - Epoch(train) [91][1180/2119] lr: 4.0000e-02 eta: 12:07:46 time: 0.3805 data_time: 0.0217 memory: 5826 grad_norm: 3.1510 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8321 loss: 2.8321 2022/10/08 02:29:56 - mmengine - INFO - Epoch(train) [91][1200/2119] lr: 4.0000e-02 eta: 12:07:38 time: 0.3218 data_time: 0.0255 memory: 5826 grad_norm: 3.0905 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8214 loss: 2.8214 2022/10/08 02:30:03 - mmengine - INFO - Epoch(train) [91][1220/2119] lr: 4.0000e-02 eta: 12:07:32 time: 0.3854 data_time: 0.0183 memory: 5826 grad_norm: 3.1680 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7955 loss: 2.7955 2022/10/08 02:30:10 - mmengine - INFO - Epoch(train) [91][1240/2119] lr: 4.0000e-02 eta: 12:07:25 time: 0.3305 data_time: 0.0254 memory: 5826 grad_norm: 3.0991 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7912 loss: 2.7912 2022/10/08 02:30:17 - mmengine - INFO - Epoch(train) [91][1260/2119] lr: 4.0000e-02 eta: 12:07:18 time: 0.3589 data_time: 0.0184 memory: 5826 grad_norm: 3.1482 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.5562 loss: 2.5562 2022/10/08 02:30:25 - mmengine - INFO - Epoch(train) [91][1280/2119] lr: 4.0000e-02 eta: 12:07:11 time: 0.3634 data_time: 0.0206 memory: 5826 grad_norm: 3.2225 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7406 loss: 2.7406 2022/10/08 02:30:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 02:30:32 - mmengine - INFO - Epoch(train) [91][1300/2119] lr: 4.0000e-02 eta: 12:07:05 time: 0.3784 data_time: 0.0184 memory: 5826 grad_norm: 3.1127 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5343 loss: 2.5343 2022/10/08 02:30:38 - mmengine - INFO - Epoch(train) [91][1320/2119] lr: 4.0000e-02 eta: 12:06:57 time: 0.2989 data_time: 0.0274 memory: 5826 grad_norm: 3.1308 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7116 loss: 2.7116 2022/10/08 02:30:45 - mmengine - INFO - Epoch(train) [91][1340/2119] lr: 4.0000e-02 eta: 12:06:50 time: 0.3424 data_time: 0.0252 memory: 5826 grad_norm: 3.2005 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7487 loss: 2.7487 2022/10/08 02:30:52 - mmengine - INFO - Epoch(train) [91][1360/2119] lr: 4.0000e-02 eta: 12:06:43 time: 0.3342 data_time: 0.0245 memory: 5826 grad_norm: 3.1312 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7534 loss: 2.7534 2022/10/08 02:30:59 - mmengine - INFO - Epoch(train) [91][1380/2119] lr: 4.0000e-02 eta: 12:06:36 time: 0.3480 data_time: 0.0239 memory: 5826 grad_norm: 3.0442 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.4736 loss: 2.4736 2022/10/08 02:31:05 - mmengine - INFO - Epoch(train) [91][1400/2119] lr: 4.0000e-02 eta: 12:06:29 time: 0.3366 data_time: 0.0229 memory: 5826 grad_norm: 3.1205 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6802 loss: 2.6802 2022/10/08 02:31:12 - mmengine - INFO - Epoch(train) [91][1420/2119] lr: 4.0000e-02 eta: 12:06:22 time: 0.3277 data_time: 0.0227 memory: 5826 grad_norm: 3.1694 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7395 loss: 2.7395 2022/10/08 02:31:18 - mmengine - INFO - Epoch(train) [91][1440/2119] lr: 4.0000e-02 eta: 12:06:14 time: 0.3103 data_time: 0.0287 memory: 5826 grad_norm: 3.1351 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8455 loss: 2.8455 2022/10/08 02:31:26 - mmengine - INFO - Epoch(train) [91][1460/2119] lr: 4.0000e-02 eta: 12:06:08 time: 0.4172 data_time: 0.0244 memory: 5826 grad_norm: 3.1839 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7538 loss: 2.7538 2022/10/08 02:31:33 - mmengine - INFO - Epoch(train) [91][1480/2119] lr: 4.0000e-02 eta: 12:06:01 time: 0.3063 data_time: 0.0268 memory: 5826 grad_norm: 3.1685 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7321 loss: 2.7321 2022/10/08 02:31:41 - mmengine - INFO - Epoch(train) [91][1500/2119] lr: 4.0000e-02 eta: 12:05:55 time: 0.4085 data_time: 0.0242 memory: 5826 grad_norm: 3.1652 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7941 loss: 2.7941 2022/10/08 02:31:47 - mmengine - INFO - Epoch(train) [91][1520/2119] lr: 4.0000e-02 eta: 12:05:48 time: 0.3348 data_time: 0.0181 memory: 5826 grad_norm: 3.1167 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6535 loss: 2.6535 2022/10/08 02:31:54 - mmengine - INFO - Epoch(train) [91][1540/2119] lr: 4.0000e-02 eta: 12:05:41 time: 0.3294 data_time: 0.0239 memory: 5826 grad_norm: 3.1311 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7785 loss: 2.7785 2022/10/08 02:32:01 - mmengine - INFO - Epoch(train) [91][1560/2119] lr: 4.0000e-02 eta: 12:05:34 time: 0.3548 data_time: 0.0263 memory: 5826 grad_norm: 3.1475 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5107 loss: 2.5107 2022/10/08 02:32:08 - mmengine - INFO - Epoch(train) [91][1580/2119] lr: 4.0000e-02 eta: 12:05:27 time: 0.3566 data_time: 0.0201 memory: 5826 grad_norm: 3.1261 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6305 loss: 2.6305 2022/10/08 02:32:15 - mmengine - INFO - Epoch(train) [91][1600/2119] lr: 4.0000e-02 eta: 12:05:20 time: 0.3270 data_time: 0.0245 memory: 5826 grad_norm: 3.1176 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7844 loss: 2.7844 2022/10/08 02:32:22 - mmengine - INFO - Epoch(train) [91][1620/2119] lr: 4.0000e-02 eta: 12:05:13 time: 0.3694 data_time: 0.0388 memory: 5826 grad_norm: 3.0945 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.8777 loss: 2.8777 2022/10/08 02:32:29 - mmengine - INFO - Epoch(train) [91][1640/2119] lr: 4.0000e-02 eta: 12:05:06 time: 0.3548 data_time: 0.0269 memory: 5826 grad_norm: 3.1472 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7694 loss: 2.7694 2022/10/08 02:32:36 - mmengine - INFO - Epoch(train) [91][1660/2119] lr: 4.0000e-02 eta: 12:05:00 time: 0.3519 data_time: 0.0226 memory: 5826 grad_norm: 3.0730 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6871 loss: 2.6871 2022/10/08 02:32:43 - mmengine - INFO - Epoch(train) [91][1680/2119] lr: 4.0000e-02 eta: 12:04:52 time: 0.3392 data_time: 0.0249 memory: 5826 grad_norm: 3.1348 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7103 loss: 2.7103 2022/10/08 02:32:50 - mmengine - INFO - Epoch(train) [91][1700/2119] lr: 4.0000e-02 eta: 12:04:46 time: 0.3616 data_time: 0.0205 memory: 5826 grad_norm: 3.0832 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8001 loss: 2.8001 2022/10/08 02:32:57 - mmengine - INFO - Epoch(train) [91][1720/2119] lr: 4.0000e-02 eta: 12:04:38 time: 0.3109 data_time: 0.0228 memory: 5826 grad_norm: 3.2165 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9790 loss: 2.9790 2022/10/08 02:33:04 - mmengine - INFO - Epoch(train) [91][1740/2119] lr: 4.0000e-02 eta: 12:04:32 time: 0.3700 data_time: 0.0239 memory: 5826 grad_norm: 3.0668 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.5987 loss: 2.5987 2022/10/08 02:33:11 - mmengine - INFO - Epoch(train) [91][1760/2119] lr: 4.0000e-02 eta: 12:04:25 time: 0.3514 data_time: 0.0227 memory: 5826 grad_norm: 3.0803 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7161 loss: 2.7161 2022/10/08 02:33:19 - mmengine - INFO - Epoch(train) [91][1780/2119] lr: 4.0000e-02 eta: 12:04:18 time: 0.3811 data_time: 0.0180 memory: 5826 grad_norm: 3.1259 top1_acc: 0.0625 top5_acc: 0.3750 loss_cls: 2.5842 loss: 2.5842 2022/10/08 02:33:25 - mmengine - INFO - Epoch(train) [91][1800/2119] lr: 4.0000e-02 eta: 12:04:11 time: 0.3179 data_time: 0.0278 memory: 5826 grad_norm: 3.1365 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6943 loss: 2.6943 2022/10/08 02:33:32 - mmengine - INFO - Epoch(train) [91][1820/2119] lr: 4.0000e-02 eta: 12:04:04 time: 0.3648 data_time: 0.0201 memory: 5826 grad_norm: 3.1139 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8375 loss: 2.8375 2022/10/08 02:33:39 - mmengine - INFO - Epoch(train) [91][1840/2119] lr: 4.0000e-02 eta: 12:03:57 time: 0.3126 data_time: 0.0260 memory: 5826 grad_norm: 3.1080 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8645 loss: 2.8645 2022/10/08 02:33:46 - mmengine - INFO - Epoch(train) [91][1860/2119] lr: 4.0000e-02 eta: 12:03:50 time: 0.3695 data_time: 0.0177 memory: 5826 grad_norm: 3.1179 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9049 loss: 2.9049 2022/10/08 02:33:53 - mmengine - INFO - Epoch(train) [91][1880/2119] lr: 4.0000e-02 eta: 12:03:43 time: 0.3260 data_time: 0.0302 memory: 5826 grad_norm: 3.1352 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.6597 loss: 2.6597 2022/10/08 02:34:00 - mmengine - INFO - Epoch(train) [91][1900/2119] lr: 4.0000e-02 eta: 12:03:36 time: 0.3608 data_time: 0.0168 memory: 5826 grad_norm: 3.0926 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5683 loss: 2.5683 2022/10/08 02:34:06 - mmengine - INFO - Epoch(train) [91][1920/2119] lr: 4.0000e-02 eta: 12:03:29 time: 0.3321 data_time: 0.0296 memory: 5826 grad_norm: 3.1784 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5791 loss: 2.5791 2022/10/08 02:34:13 - mmengine - INFO - Epoch(train) [91][1940/2119] lr: 4.0000e-02 eta: 12:03:22 time: 0.3401 data_time: 0.0206 memory: 5826 grad_norm: 3.1104 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.7999 loss: 2.7999 2022/10/08 02:34:20 - mmengine - INFO - Epoch(train) [91][1960/2119] lr: 4.0000e-02 eta: 12:03:15 time: 0.3538 data_time: 0.0265 memory: 5826 grad_norm: 3.1435 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5052 loss: 2.5052 2022/10/08 02:34:27 - mmengine - INFO - Epoch(train) [91][1980/2119] lr: 4.0000e-02 eta: 12:03:09 time: 0.3514 data_time: 0.0215 memory: 5826 grad_norm: 3.1718 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5758 loss: 2.5758 2022/10/08 02:34:34 - mmengine - INFO - Epoch(train) [91][2000/2119] lr: 4.0000e-02 eta: 12:03:01 time: 0.3116 data_time: 0.0218 memory: 5826 grad_norm: 3.1484 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.8783 loss: 2.8783 2022/10/08 02:34:41 - mmengine - INFO - Epoch(train) [91][2020/2119] lr: 4.0000e-02 eta: 12:02:55 time: 0.3704 data_time: 0.0291 memory: 5826 grad_norm: 3.1200 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8615 loss: 2.8615 2022/10/08 02:34:47 - mmengine - INFO - Epoch(train) [91][2040/2119] lr: 4.0000e-02 eta: 12:02:47 time: 0.3169 data_time: 0.0233 memory: 5826 grad_norm: 3.1506 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6887 loss: 2.6887 2022/10/08 02:34:54 - mmengine - INFO - Epoch(train) [91][2060/2119] lr: 4.0000e-02 eta: 12:02:40 time: 0.3365 data_time: 0.0239 memory: 5826 grad_norm: 3.1863 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8185 loss: 2.8185 2022/10/08 02:35:01 - mmengine - INFO - Epoch(train) [91][2080/2119] lr: 4.0000e-02 eta: 12:02:33 time: 0.3390 data_time: 0.0275 memory: 5826 grad_norm: 3.1478 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6046 loss: 2.6046 2022/10/08 02:35:08 - mmengine - INFO - Epoch(train) [91][2100/2119] lr: 4.0000e-02 eta: 12:02:26 time: 0.3726 data_time: 0.0206 memory: 5826 grad_norm: 3.1170 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9610 loss: 2.9610 2022/10/08 02:35:14 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 02:35:14 - mmengine - INFO - Epoch(train) [91][2119/2119] lr: 4.0000e-02 eta: 12:02:26 time: 0.2878 data_time: 0.0195 memory: 5826 grad_norm: 3.2480 top1_acc: 0.5000 top5_acc: 0.8000 loss_cls: 2.7114 loss: 2.7114 2022/10/08 02:35:24 - mmengine - INFO - Epoch(train) [92][20/2119] lr: 4.0000e-02 eta: 12:02:10 time: 0.4806 data_time: 0.2084 memory: 5826 grad_norm: 3.1022 top1_acc: 0.1875 top5_acc: 0.2500 loss_cls: 2.8192 loss: 2.8192 2022/10/08 02:35:30 - mmengine - INFO - Epoch(train) [92][40/2119] lr: 4.0000e-02 eta: 12:02:03 time: 0.3282 data_time: 0.0659 memory: 5826 grad_norm: 3.1013 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5029 loss: 2.5029 2022/10/08 02:35:37 - mmengine - INFO - Epoch(train) [92][60/2119] lr: 4.0000e-02 eta: 12:01:56 time: 0.3544 data_time: 0.0936 memory: 5826 grad_norm: 3.0793 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7451 loss: 2.7451 2022/10/08 02:35:45 - mmengine - INFO - Epoch(train) [92][80/2119] lr: 4.0000e-02 eta: 12:01:50 time: 0.3766 data_time: 0.0775 memory: 5826 grad_norm: 3.1119 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6460 loss: 2.6460 2022/10/08 02:35:52 - mmengine - INFO - Epoch(train) [92][100/2119] lr: 4.0000e-02 eta: 12:01:43 time: 0.3611 data_time: 0.0186 memory: 5826 grad_norm: 3.1424 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7011 loss: 2.7011 2022/10/08 02:35:58 - mmengine - INFO - Epoch(train) [92][120/2119] lr: 4.0000e-02 eta: 12:01:36 time: 0.2979 data_time: 0.0312 memory: 5826 grad_norm: 3.1305 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6430 loss: 2.6430 2022/10/08 02:36:06 - mmengine - INFO - Epoch(train) [92][140/2119] lr: 4.0000e-02 eta: 12:01:29 time: 0.3869 data_time: 0.0260 memory: 5826 grad_norm: 3.1710 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4494 loss: 2.4494 2022/10/08 02:36:12 - mmengine - INFO - Epoch(train) [92][160/2119] lr: 4.0000e-02 eta: 12:01:22 time: 0.3293 data_time: 0.0178 memory: 5826 grad_norm: 3.1758 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8493 loss: 2.8493 2022/10/08 02:36:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 02:36:20 - mmengine - INFO - Epoch(train) [92][180/2119] lr: 4.0000e-02 eta: 12:01:15 time: 0.3719 data_time: 0.0194 memory: 5826 grad_norm: 3.1257 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5870 loss: 2.5870 2022/10/08 02:36:26 - mmengine - INFO - Epoch(train) [92][200/2119] lr: 4.0000e-02 eta: 12:01:08 time: 0.3202 data_time: 0.0207 memory: 5826 grad_norm: 3.1368 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.8343 loss: 2.8343 2022/10/08 02:36:33 - mmengine - INFO - Epoch(train) [92][220/2119] lr: 4.0000e-02 eta: 12:01:01 time: 0.3526 data_time: 0.0214 memory: 5826 grad_norm: 3.1727 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8146 loss: 2.8146 2022/10/08 02:36:40 - mmengine - INFO - Epoch(train) [92][240/2119] lr: 4.0000e-02 eta: 12:00:54 time: 0.3559 data_time: 0.0243 memory: 5826 grad_norm: 3.1237 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7927 loss: 2.7927 2022/10/08 02:36:48 - mmengine - INFO - Epoch(train) [92][260/2119] lr: 4.0000e-02 eta: 12:00:48 time: 0.4017 data_time: 0.0208 memory: 5826 grad_norm: 3.1515 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5005 loss: 2.5005 2022/10/08 02:36:55 - mmengine - INFO - Epoch(train) [92][280/2119] lr: 4.0000e-02 eta: 12:00:41 time: 0.3265 data_time: 0.0281 memory: 5826 grad_norm: 3.1507 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7278 loss: 2.7278 2022/10/08 02:37:02 - mmengine - INFO - Epoch(train) [92][300/2119] lr: 4.0000e-02 eta: 12:00:34 time: 0.3723 data_time: 0.0212 memory: 5826 grad_norm: 3.1270 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4778 loss: 2.4778 2022/10/08 02:37:10 - mmengine - INFO - Epoch(train) [92][320/2119] lr: 4.0000e-02 eta: 12:00:28 time: 0.3662 data_time: 0.0222 memory: 5826 grad_norm: 3.1162 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7656 loss: 2.7656 2022/10/08 02:37:17 - mmengine - INFO - Epoch(train) [92][340/2119] lr: 4.0000e-02 eta: 12:00:21 time: 0.3626 data_time: 0.0264 memory: 5826 grad_norm: 3.0994 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6066 loss: 2.6066 2022/10/08 02:37:23 - mmengine - INFO - Epoch(train) [92][360/2119] lr: 4.0000e-02 eta: 12:00:14 time: 0.3211 data_time: 0.0268 memory: 5826 grad_norm: 3.1169 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6398 loss: 2.6398 2022/10/08 02:37:30 - mmengine - INFO - Epoch(train) [92][380/2119] lr: 4.0000e-02 eta: 12:00:07 time: 0.3462 data_time: 0.0248 memory: 5826 grad_norm: 3.1416 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7107 loss: 2.7107 2022/10/08 02:37:37 - mmengine - INFO - Epoch(train) [92][400/2119] lr: 4.0000e-02 eta: 12:00:00 time: 0.3249 data_time: 0.0224 memory: 5826 grad_norm: 3.1258 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5775 loss: 2.5775 2022/10/08 02:37:45 - mmengine - INFO - Epoch(train) [92][420/2119] lr: 4.0000e-02 eta: 11:59:53 time: 0.3818 data_time: 0.0219 memory: 5826 grad_norm: 3.1575 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8422 loss: 2.8422 2022/10/08 02:37:52 - mmengine - INFO - Epoch(train) [92][440/2119] lr: 4.0000e-02 eta: 11:59:46 time: 0.3630 data_time: 0.0217 memory: 5826 grad_norm: 3.1612 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.8117 loss: 2.8117 2022/10/08 02:37:59 - mmengine - INFO - Epoch(train) [92][460/2119] lr: 4.0000e-02 eta: 11:59:40 time: 0.3523 data_time: 0.0186 memory: 5826 grad_norm: 3.1006 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6195 loss: 2.6195 2022/10/08 02:38:06 - mmengine - INFO - Epoch(train) [92][480/2119] lr: 4.0000e-02 eta: 11:59:32 time: 0.3365 data_time: 0.0261 memory: 5826 grad_norm: 3.1622 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5932 loss: 2.5932 2022/10/08 02:38:14 - mmengine - INFO - Epoch(train) [92][500/2119] lr: 4.0000e-02 eta: 11:59:26 time: 0.3970 data_time: 0.0219 memory: 5826 grad_norm: 3.1584 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6638 loss: 2.6638 2022/10/08 02:38:21 - mmengine - INFO - Epoch(train) [92][520/2119] lr: 4.0000e-02 eta: 11:59:19 time: 0.3500 data_time: 0.0217 memory: 5826 grad_norm: 3.1227 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.8251 loss: 2.8251 2022/10/08 02:38:28 - mmengine - INFO - Epoch(train) [92][540/2119] lr: 4.0000e-02 eta: 11:59:12 time: 0.3541 data_time: 0.0221 memory: 5826 grad_norm: 3.0888 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6388 loss: 2.6388 2022/10/08 02:38:34 - mmengine - INFO - Epoch(train) [92][560/2119] lr: 4.0000e-02 eta: 11:59:05 time: 0.3112 data_time: 0.0308 memory: 5826 grad_norm: 3.1321 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6743 loss: 2.6743 2022/10/08 02:38:41 - mmengine - INFO - Epoch(train) [92][580/2119] lr: 4.0000e-02 eta: 11:58:58 time: 0.3664 data_time: 0.0272 memory: 5826 grad_norm: 3.0895 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7554 loss: 2.7554 2022/10/08 02:38:47 - mmengine - INFO - Epoch(train) [92][600/2119] lr: 4.0000e-02 eta: 11:58:51 time: 0.3125 data_time: 0.0205 memory: 5826 grad_norm: 3.1833 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5028 loss: 2.5028 2022/10/08 02:38:56 - mmengine - INFO - Epoch(train) [92][620/2119] lr: 4.0000e-02 eta: 11:58:45 time: 0.4295 data_time: 0.0209 memory: 5826 grad_norm: 3.1248 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5057 loss: 2.5057 2022/10/08 02:39:03 - mmengine - INFO - Epoch(train) [92][640/2119] lr: 4.0000e-02 eta: 11:58:38 time: 0.3311 data_time: 0.0241 memory: 5826 grad_norm: 3.1249 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4892 loss: 2.4892 2022/10/08 02:39:11 - mmengine - INFO - Epoch(train) [92][660/2119] lr: 4.0000e-02 eta: 11:58:32 time: 0.4089 data_time: 0.0203 memory: 5826 grad_norm: 3.0949 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6808 loss: 2.6808 2022/10/08 02:39:17 - mmengine - INFO - Epoch(train) [92][680/2119] lr: 4.0000e-02 eta: 11:58:25 time: 0.3107 data_time: 0.0233 memory: 5826 grad_norm: 3.1178 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5193 loss: 2.5193 2022/10/08 02:39:24 - mmengine - INFO - Epoch(train) [92][700/2119] lr: 4.0000e-02 eta: 11:58:18 time: 0.3453 data_time: 0.0291 memory: 5826 grad_norm: 3.1862 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7950 loss: 2.7950 2022/10/08 02:39:31 - mmengine - INFO - Epoch(train) [92][720/2119] lr: 4.0000e-02 eta: 11:58:11 time: 0.3526 data_time: 0.0205 memory: 5826 grad_norm: 3.1368 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.9112 loss: 2.9112 2022/10/08 02:39:38 - mmengine - INFO - Epoch(train) [92][740/2119] lr: 4.0000e-02 eta: 11:58:04 time: 0.3287 data_time: 0.0201 memory: 5826 grad_norm: 3.1250 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6033 loss: 2.6033 2022/10/08 02:39:44 - mmengine - INFO - Epoch(train) [92][760/2119] lr: 4.0000e-02 eta: 11:57:56 time: 0.3365 data_time: 0.0278 memory: 5826 grad_norm: 3.1227 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5347 loss: 2.5347 2022/10/08 02:39:51 - mmengine - INFO - Epoch(train) [92][780/2119] lr: 4.0000e-02 eta: 11:57:50 time: 0.3476 data_time: 0.0262 memory: 5826 grad_norm: 3.1294 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.7607 loss: 2.7607 2022/10/08 02:39:58 - mmengine - INFO - Epoch(train) [92][800/2119] lr: 4.0000e-02 eta: 11:57:42 time: 0.3342 data_time: 0.0229 memory: 5826 grad_norm: 3.1412 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7854 loss: 2.7854 2022/10/08 02:40:06 - mmengine - INFO - Epoch(train) [92][820/2119] lr: 4.0000e-02 eta: 11:57:36 time: 0.3793 data_time: 0.0227 memory: 5826 grad_norm: 3.1274 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4888 loss: 2.4888 2022/10/08 02:40:12 - mmengine - INFO - Epoch(train) [92][840/2119] lr: 4.0000e-02 eta: 11:57:29 time: 0.3432 data_time: 0.0245 memory: 5826 grad_norm: 3.1549 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6065 loss: 2.6065 2022/10/08 02:40:21 - mmengine - INFO - Epoch(train) [92][860/2119] lr: 4.0000e-02 eta: 11:57:23 time: 0.4105 data_time: 0.0243 memory: 5826 grad_norm: 3.1263 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7514 loss: 2.7514 2022/10/08 02:40:27 - mmengine - INFO - Epoch(train) [92][880/2119] lr: 4.0000e-02 eta: 11:57:16 time: 0.3308 data_time: 0.0263 memory: 5826 grad_norm: 3.1181 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7077 loss: 2.7077 2022/10/08 02:40:34 - mmengine - INFO - Epoch(train) [92][900/2119] lr: 4.0000e-02 eta: 11:57:09 time: 0.3449 data_time: 0.0181 memory: 5826 grad_norm: 3.1662 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9905 loss: 2.9905 2022/10/08 02:40:41 - mmengine - INFO - Epoch(train) [92][920/2119] lr: 4.0000e-02 eta: 11:57:01 time: 0.3156 data_time: 0.0221 memory: 5826 grad_norm: 3.1326 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.6905 loss: 2.6905 2022/10/08 02:40:47 - mmengine - INFO - Epoch(train) [92][940/2119] lr: 4.0000e-02 eta: 11:56:55 time: 0.3472 data_time: 0.0218 memory: 5826 grad_norm: 3.2013 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7934 loss: 2.7934 2022/10/08 02:40:54 - mmengine - INFO - Epoch(train) [92][960/2119] lr: 4.0000e-02 eta: 11:56:47 time: 0.3335 data_time: 0.0241 memory: 5826 grad_norm: 3.1281 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.9564 loss: 2.9564 2022/10/08 02:41:02 - mmengine - INFO - Epoch(train) [92][980/2119] lr: 4.0000e-02 eta: 11:56:41 time: 0.3760 data_time: 0.0235 memory: 5826 grad_norm: 3.0238 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6720 loss: 2.6720 2022/10/08 02:41:08 - mmengine - INFO - Epoch(train) [92][1000/2119] lr: 4.0000e-02 eta: 11:56:34 time: 0.3264 data_time: 0.0257 memory: 5826 grad_norm: 3.0966 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9303 loss: 2.9303 2022/10/08 02:41:16 - mmengine - INFO - Epoch(train) [92][1020/2119] lr: 4.0000e-02 eta: 11:56:27 time: 0.3779 data_time: 0.0226 memory: 5826 grad_norm: 3.1250 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6009 loss: 2.6009 2022/10/08 02:41:23 - mmengine - INFO - Epoch(train) [92][1040/2119] lr: 4.0000e-02 eta: 11:56:20 time: 0.3535 data_time: 0.0249 memory: 5826 grad_norm: 3.1356 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6958 loss: 2.6958 2022/10/08 02:41:31 - mmengine - INFO - Epoch(train) [92][1060/2119] lr: 4.0000e-02 eta: 11:56:14 time: 0.3895 data_time: 0.0212 memory: 5826 grad_norm: 3.1679 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.5726 loss: 2.5726 2022/10/08 02:41:36 - mmengine - INFO - Epoch(train) [92][1080/2119] lr: 4.0000e-02 eta: 11:56:06 time: 0.2669 data_time: 0.0266 memory: 5826 grad_norm: 3.1692 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8726 loss: 2.8726 2022/10/08 02:41:44 - mmengine - INFO - Epoch(train) [92][1100/2119] lr: 4.0000e-02 eta: 11:56:00 time: 0.3935 data_time: 0.0221 memory: 5826 grad_norm: 3.1652 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5917 loss: 2.5917 2022/10/08 02:41:51 - mmengine - INFO - Epoch(train) [92][1120/2119] lr: 4.0000e-02 eta: 11:55:53 time: 0.3550 data_time: 0.0225 memory: 5826 grad_norm: 3.1237 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6534 loss: 2.6534 2022/10/08 02:41:58 - mmengine - INFO - Epoch(train) [92][1140/2119] lr: 4.0000e-02 eta: 11:55:46 time: 0.3417 data_time: 0.0238 memory: 5826 grad_norm: 3.1303 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5950 loss: 2.5950 2022/10/08 02:42:05 - mmengine - INFO - Epoch(train) [92][1160/2119] lr: 4.0000e-02 eta: 11:55:39 time: 0.3391 data_time: 0.0220 memory: 5826 grad_norm: 3.1409 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6863 loss: 2.6863 2022/10/08 02:42:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 02:42:12 - mmengine - INFO - Epoch(train) [92][1180/2119] lr: 4.0000e-02 eta: 11:55:32 time: 0.3451 data_time: 0.0210 memory: 5826 grad_norm: 3.1222 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6671 loss: 2.6671 2022/10/08 02:42:19 - mmengine - INFO - Epoch(train) [92][1200/2119] lr: 4.0000e-02 eta: 11:55:25 time: 0.3592 data_time: 0.0226 memory: 5826 grad_norm: 3.0799 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.3769 loss: 2.3769 2022/10/08 02:42:25 - mmengine - INFO - Epoch(train) [92][1220/2119] lr: 4.0000e-02 eta: 11:55:17 time: 0.2906 data_time: 0.0278 memory: 5826 grad_norm: 3.1567 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8237 loss: 2.8237 2022/10/08 02:42:32 - mmengine - INFO - Epoch(train) [92][1240/2119] lr: 4.0000e-02 eta: 11:55:11 time: 0.3651 data_time: 0.0183 memory: 5826 grad_norm: 3.1004 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6504 loss: 2.6504 2022/10/08 02:42:38 - mmengine - INFO - Epoch(train) [92][1260/2119] lr: 4.0000e-02 eta: 11:55:03 time: 0.3178 data_time: 0.0210 memory: 5826 grad_norm: 3.1631 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.8496 loss: 2.8496 2022/10/08 02:42:46 - mmengine - INFO - Epoch(train) [92][1280/2119] lr: 4.0000e-02 eta: 11:54:57 time: 0.3904 data_time: 0.0361 memory: 5826 grad_norm: 3.2094 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5583 loss: 2.5583 2022/10/08 02:42:53 - mmengine - INFO - Epoch(train) [92][1300/2119] lr: 4.0000e-02 eta: 11:54:50 time: 0.3363 data_time: 0.0193 memory: 5826 grad_norm: 3.1674 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7488 loss: 2.7488 2022/10/08 02:43:00 - mmengine - INFO - Epoch(train) [92][1320/2119] lr: 4.0000e-02 eta: 11:54:43 time: 0.3459 data_time: 0.0165 memory: 5826 grad_norm: 3.1479 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7870 loss: 2.7870 2022/10/08 02:43:07 - mmengine - INFO - Epoch(train) [92][1340/2119] lr: 4.0000e-02 eta: 11:54:36 time: 0.3731 data_time: 0.0311 memory: 5826 grad_norm: 3.1282 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9328 loss: 2.9328 2022/10/08 02:43:13 - mmengine - INFO - Epoch(train) [92][1360/2119] lr: 4.0000e-02 eta: 11:54:29 time: 0.3116 data_time: 0.0198 memory: 5826 grad_norm: 3.1677 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7471 loss: 2.7471 2022/10/08 02:43:21 - mmengine - INFO - Epoch(train) [92][1380/2119] lr: 4.0000e-02 eta: 11:54:22 time: 0.3551 data_time: 0.0194 memory: 5826 grad_norm: 3.1549 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9575 loss: 2.9575 2022/10/08 02:43:28 - mmengine - INFO - Epoch(train) [92][1400/2119] lr: 4.0000e-02 eta: 11:54:16 time: 0.3880 data_time: 0.0214 memory: 5826 grad_norm: 3.1060 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6118 loss: 2.6118 2022/10/08 02:43:35 - mmengine - INFO - Epoch(train) [92][1420/2119] lr: 4.0000e-02 eta: 11:54:08 time: 0.3162 data_time: 0.0286 memory: 5826 grad_norm: 3.1624 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6628 loss: 2.6628 2022/10/08 02:43:42 - mmengine - INFO - Epoch(train) [92][1440/2119] lr: 4.0000e-02 eta: 11:54:02 time: 0.3615 data_time: 0.0280 memory: 5826 grad_norm: 3.2025 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8230 loss: 2.8230 2022/10/08 02:43:49 - mmengine - INFO - Epoch(train) [92][1460/2119] lr: 4.0000e-02 eta: 11:53:55 time: 0.3334 data_time: 0.0196 memory: 5826 grad_norm: 3.1456 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8618 loss: 2.8618 2022/10/08 02:43:55 - mmengine - INFO - Epoch(train) [92][1480/2119] lr: 4.0000e-02 eta: 11:53:48 time: 0.3438 data_time: 0.0243 memory: 5826 grad_norm: 3.1937 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6743 loss: 2.6743 2022/10/08 02:44:03 - mmengine - INFO - Epoch(train) [92][1500/2119] lr: 4.0000e-02 eta: 11:53:41 time: 0.3712 data_time: 0.0307 memory: 5826 grad_norm: 3.1717 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6251 loss: 2.6251 2022/10/08 02:44:09 - mmengine - INFO - Epoch(train) [92][1520/2119] lr: 4.0000e-02 eta: 11:53:34 time: 0.3280 data_time: 0.0244 memory: 5826 grad_norm: 3.1081 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6921 loss: 2.6921 2022/10/08 02:44:16 - mmengine - INFO - Epoch(train) [92][1540/2119] lr: 4.0000e-02 eta: 11:53:27 time: 0.3486 data_time: 0.0255 memory: 5826 grad_norm: 3.1431 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8652 loss: 2.8652 2022/10/08 02:44:24 - mmengine - INFO - Epoch(train) [92][1560/2119] lr: 4.0000e-02 eta: 11:53:20 time: 0.3666 data_time: 0.0242 memory: 5826 grad_norm: 3.1251 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4870 loss: 2.4870 2022/10/08 02:44:31 - mmengine - INFO - Epoch(train) [92][1580/2119] lr: 4.0000e-02 eta: 11:53:13 time: 0.3437 data_time: 0.0207 memory: 5826 grad_norm: 3.0975 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7567 loss: 2.7567 2022/10/08 02:44:38 - mmengine - INFO - Epoch(train) [92][1600/2119] lr: 4.0000e-02 eta: 11:53:07 time: 0.3654 data_time: 0.0233 memory: 5826 grad_norm: 3.1535 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.5444 loss: 2.5444 2022/10/08 02:44:44 - mmengine - INFO - Epoch(train) [92][1620/2119] lr: 4.0000e-02 eta: 11:52:59 time: 0.3224 data_time: 0.0215 memory: 5826 grad_norm: 3.0907 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6290 loss: 2.6290 2022/10/08 02:44:52 - mmengine - INFO - Epoch(train) [92][1640/2119] lr: 4.0000e-02 eta: 11:52:53 time: 0.3615 data_time: 0.0225 memory: 5826 grad_norm: 3.1537 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6982 loss: 2.6982 2022/10/08 02:44:58 - mmengine - INFO - Epoch(train) [92][1660/2119] lr: 4.0000e-02 eta: 11:52:45 time: 0.3307 data_time: 0.0222 memory: 5826 grad_norm: 3.1931 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6078 loss: 2.6078 2022/10/08 02:45:06 - mmengine - INFO - Epoch(train) [92][1680/2119] lr: 4.0000e-02 eta: 11:52:39 time: 0.3760 data_time: 0.0316 memory: 5826 grad_norm: 3.1243 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7137 loss: 2.7137 2022/10/08 02:45:12 - mmengine - INFO - Epoch(train) [92][1700/2119] lr: 4.0000e-02 eta: 11:52:32 time: 0.3178 data_time: 0.0240 memory: 5826 grad_norm: 3.1464 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6669 loss: 2.6669 2022/10/08 02:45:20 - mmengine - INFO - Epoch(train) [92][1720/2119] lr: 4.0000e-02 eta: 11:52:25 time: 0.3712 data_time: 0.0268 memory: 5826 grad_norm: 3.1346 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5821 loss: 2.5821 2022/10/08 02:45:26 - mmengine - INFO - Epoch(train) [92][1740/2119] lr: 4.0000e-02 eta: 11:52:18 time: 0.3110 data_time: 0.0246 memory: 5826 grad_norm: 3.1624 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7311 loss: 2.7311 2022/10/08 02:45:33 - mmengine - INFO - Epoch(train) [92][1760/2119] lr: 4.0000e-02 eta: 11:52:11 time: 0.3621 data_time: 0.0214 memory: 5826 grad_norm: 3.0996 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7159 loss: 2.7159 2022/10/08 02:45:40 - mmengine - INFO - Epoch(train) [92][1780/2119] lr: 4.0000e-02 eta: 11:52:04 time: 0.3487 data_time: 0.0197 memory: 5826 grad_norm: 3.0968 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7197 loss: 2.7197 2022/10/08 02:45:47 - mmengine - INFO - Epoch(train) [92][1800/2119] lr: 4.0000e-02 eta: 11:51:57 time: 0.3605 data_time: 0.0231 memory: 5826 grad_norm: 3.0657 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4410 loss: 2.4410 2022/10/08 02:45:54 - mmengine - INFO - Epoch(train) [92][1820/2119] lr: 4.0000e-02 eta: 11:51:50 time: 0.3399 data_time: 0.0227 memory: 5826 grad_norm: 3.1391 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6349 loss: 2.6349 2022/10/08 02:46:01 - mmengine - INFO - Epoch(train) [92][1840/2119] lr: 4.0000e-02 eta: 11:51:43 time: 0.3446 data_time: 0.0239 memory: 5826 grad_norm: 3.1448 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 3.0119 loss: 3.0119 2022/10/08 02:46:08 - mmengine - INFO - Epoch(train) [92][1860/2119] lr: 4.0000e-02 eta: 11:51:36 time: 0.3402 data_time: 0.0183 memory: 5826 grad_norm: 3.1017 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5704 loss: 2.5704 2022/10/08 02:46:15 - mmengine - INFO - Epoch(train) [92][1880/2119] lr: 4.0000e-02 eta: 11:51:30 time: 0.3714 data_time: 0.0237 memory: 5826 grad_norm: 3.1563 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7087 loss: 2.7087 2022/10/08 02:46:23 - mmengine - INFO - Epoch(train) [92][1900/2119] lr: 4.0000e-02 eta: 11:51:23 time: 0.3736 data_time: 0.0270 memory: 5826 grad_norm: 3.1741 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8436 loss: 2.8436 2022/10/08 02:46:29 - mmengine - INFO - Epoch(train) [92][1920/2119] lr: 4.0000e-02 eta: 11:51:16 time: 0.3304 data_time: 0.0254 memory: 5826 grad_norm: 3.1393 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.8508 loss: 2.8508 2022/10/08 02:46:36 - mmengine - INFO - Epoch(train) [92][1940/2119] lr: 4.0000e-02 eta: 11:51:09 time: 0.3360 data_time: 0.0231 memory: 5826 grad_norm: 3.1464 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7933 loss: 2.7933 2022/10/08 02:46:43 - mmengine - INFO - Epoch(train) [92][1960/2119] lr: 4.0000e-02 eta: 11:51:02 time: 0.3612 data_time: 0.0270 memory: 5826 grad_norm: 3.1276 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7103 loss: 2.7103 2022/10/08 02:46:50 - mmengine - INFO - Epoch(train) [92][1980/2119] lr: 4.0000e-02 eta: 11:50:55 time: 0.3515 data_time: 0.0185 memory: 5826 grad_norm: 3.0841 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7081 loss: 2.7081 2022/10/08 02:46:57 - mmengine - INFO - Epoch(train) [92][2000/2119] lr: 4.0000e-02 eta: 11:50:48 time: 0.3448 data_time: 0.0229 memory: 5826 grad_norm: 3.2073 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7838 loss: 2.7838 2022/10/08 02:47:05 - mmengine - INFO - Epoch(train) [92][2020/2119] lr: 4.0000e-02 eta: 11:50:42 time: 0.3792 data_time: 0.0221 memory: 5826 grad_norm: 3.1309 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7803 loss: 2.7803 2022/10/08 02:47:11 - mmengine - INFO - Epoch(train) [92][2040/2119] lr: 4.0000e-02 eta: 11:50:34 time: 0.3236 data_time: 0.0264 memory: 5826 grad_norm: 3.1330 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7811 loss: 2.7811 2022/10/08 02:47:17 - mmengine - INFO - Epoch(train) [92][2060/2119] lr: 4.0000e-02 eta: 11:50:27 time: 0.3078 data_time: 0.0252 memory: 5826 grad_norm: 3.1689 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6616 loss: 2.6616 2022/10/08 02:47:24 - mmengine - INFO - Epoch(train) [92][2080/2119] lr: 4.0000e-02 eta: 11:50:20 time: 0.3288 data_time: 0.0265 memory: 5826 grad_norm: 3.1122 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8867 loss: 2.8867 2022/10/08 02:47:32 - mmengine - INFO - Epoch(train) [92][2100/2119] lr: 4.0000e-02 eta: 11:50:13 time: 0.3794 data_time: 0.0279 memory: 5826 grad_norm: 3.1176 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.6495 loss: 2.6495 2022/10/08 02:47:37 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 02:47:37 - mmengine - INFO - Epoch(train) [92][2119/2119] lr: 4.0000e-02 eta: 11:50:13 time: 0.2633 data_time: 0.0152 memory: 5826 grad_norm: 3.1391 top1_acc: 0.5000 top5_acc: 0.7000 loss_cls: 2.6473 loss: 2.6473 2022/10/08 02:47:37 - mmengine - INFO - Saving checkpoint at 92 epochs 2022/10/08 02:47:47 - mmengine - INFO - Epoch(train) [93][20/2119] lr: 4.0000e-02 eta: 11:49:56 time: 0.4046 data_time: 0.1847 memory: 5826 grad_norm: 3.1116 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.5899 loss: 2.5899 2022/10/08 02:47:54 - mmengine - INFO - Epoch(train) [93][40/2119] lr: 4.0000e-02 eta: 11:49:50 time: 0.3689 data_time: 0.0796 memory: 5826 grad_norm: 3.1687 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6896 loss: 2.6896 2022/10/08 02:47:59 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 02:48:02 - mmengine - INFO - Epoch(train) [93][60/2119] lr: 4.0000e-02 eta: 11:49:43 time: 0.3752 data_time: 0.1466 memory: 5826 grad_norm: 3.1105 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7419 loss: 2.7419 2022/10/08 02:48:08 - mmengine - INFO - Epoch(train) [93][80/2119] lr: 4.0000e-02 eta: 11:49:36 time: 0.3089 data_time: 0.0681 memory: 5826 grad_norm: 3.0944 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6797 loss: 2.6797 2022/10/08 02:48:15 - mmengine - INFO - Epoch(train) [93][100/2119] lr: 4.0000e-02 eta: 11:49:29 time: 0.3594 data_time: 0.0912 memory: 5826 grad_norm: 3.1808 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0147 loss: 3.0147 2022/10/08 02:48:22 - mmengine - INFO - Epoch(train) [93][120/2119] lr: 4.0000e-02 eta: 11:49:22 time: 0.3492 data_time: 0.1152 memory: 5826 grad_norm: 3.1181 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6481 loss: 2.6481 2022/10/08 02:48:29 - mmengine - INFO - Epoch(train) [93][140/2119] lr: 4.0000e-02 eta: 11:49:15 time: 0.3559 data_time: 0.0942 memory: 5826 grad_norm: 3.1336 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5527 loss: 2.5527 2022/10/08 02:48:35 - mmengine - INFO - Epoch(train) [93][160/2119] lr: 4.0000e-02 eta: 11:49:08 time: 0.3160 data_time: 0.0676 memory: 5826 grad_norm: 3.1551 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8071 loss: 2.8071 2022/10/08 02:48:43 - mmengine - INFO - Epoch(train) [93][180/2119] lr: 4.0000e-02 eta: 11:49:01 time: 0.3737 data_time: 0.1291 memory: 5826 grad_norm: 3.1678 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7498 loss: 2.7498 2022/10/08 02:48:50 - mmengine - INFO - Epoch(train) [93][200/2119] lr: 4.0000e-02 eta: 11:48:54 time: 0.3449 data_time: 0.1117 memory: 5826 grad_norm: 3.1877 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.5927 loss: 2.5927 2022/10/08 02:48:56 - mmengine - INFO - Epoch(train) [93][220/2119] lr: 4.0000e-02 eta: 11:48:47 time: 0.3291 data_time: 0.0386 memory: 5826 grad_norm: 3.1712 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7465 loss: 2.7465 2022/10/08 02:49:04 - mmengine - INFO - Epoch(train) [93][240/2119] lr: 4.0000e-02 eta: 11:48:40 time: 0.3603 data_time: 0.0243 memory: 5826 grad_norm: 3.1094 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7408 loss: 2.7408 2022/10/08 02:49:11 - mmengine - INFO - Epoch(train) [93][260/2119] lr: 4.0000e-02 eta: 11:48:34 time: 0.3426 data_time: 0.0244 memory: 5826 grad_norm: 3.1261 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7442 loss: 2.7442 2022/10/08 02:49:17 - mmengine - INFO - Epoch(train) [93][280/2119] lr: 4.0000e-02 eta: 11:48:26 time: 0.3214 data_time: 0.0278 memory: 5826 grad_norm: 3.1548 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6467 loss: 2.6467 2022/10/08 02:49:24 - mmengine - INFO - Epoch(train) [93][300/2119] lr: 4.0000e-02 eta: 11:48:20 time: 0.3759 data_time: 0.0894 memory: 5826 grad_norm: 3.1483 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6967 loss: 2.6967 2022/10/08 02:49:32 - mmengine - INFO - Epoch(train) [93][320/2119] lr: 4.0000e-02 eta: 11:48:13 time: 0.3783 data_time: 0.0148 memory: 5826 grad_norm: 3.1350 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6614 loss: 2.6614 2022/10/08 02:49:39 - mmengine - INFO - Epoch(train) [93][340/2119] lr: 4.0000e-02 eta: 11:48:06 time: 0.3226 data_time: 0.0671 memory: 5826 grad_norm: 3.1354 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7342 loss: 2.7342 2022/10/08 02:49:45 - mmengine - INFO - Epoch(train) [93][360/2119] lr: 4.0000e-02 eta: 11:47:59 time: 0.3291 data_time: 0.0638 memory: 5826 grad_norm: 3.1010 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7851 loss: 2.7851 2022/10/08 02:49:53 - mmengine - INFO - Epoch(train) [93][380/2119] lr: 4.0000e-02 eta: 11:47:52 time: 0.3895 data_time: 0.0369 memory: 5826 grad_norm: 3.1488 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8721 loss: 2.8721 2022/10/08 02:49:59 - mmengine - INFO - Epoch(train) [93][400/2119] lr: 4.0000e-02 eta: 11:47:45 time: 0.3169 data_time: 0.0177 memory: 5826 grad_norm: 3.1813 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7152 loss: 2.7152 2022/10/08 02:50:07 - mmengine - INFO - Epoch(train) [93][420/2119] lr: 4.0000e-02 eta: 11:47:39 time: 0.3966 data_time: 0.0230 memory: 5826 grad_norm: 3.0688 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7355 loss: 2.7355 2022/10/08 02:50:14 - mmengine - INFO - Epoch(train) [93][440/2119] lr: 4.0000e-02 eta: 11:47:32 time: 0.3281 data_time: 0.0282 memory: 5826 grad_norm: 3.1746 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7201 loss: 2.7201 2022/10/08 02:50:22 - mmengine - INFO - Epoch(train) [93][460/2119] lr: 4.0000e-02 eta: 11:47:25 time: 0.4012 data_time: 0.0212 memory: 5826 grad_norm: 3.1072 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7536 loss: 2.7536 2022/10/08 02:50:28 - mmengine - INFO - Epoch(train) [93][480/2119] lr: 4.0000e-02 eta: 11:47:18 time: 0.2894 data_time: 0.0210 memory: 5826 grad_norm: 3.0829 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7131 loss: 2.7131 2022/10/08 02:50:34 - mmengine - INFO - Epoch(train) [93][500/2119] lr: 4.0000e-02 eta: 11:47:11 time: 0.3369 data_time: 0.0241 memory: 5826 grad_norm: 3.1086 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8728 loss: 2.8728 2022/10/08 02:50:42 - mmengine - INFO - Epoch(train) [93][520/2119] lr: 4.0000e-02 eta: 11:47:04 time: 0.3886 data_time: 0.0278 memory: 5826 grad_norm: 3.1311 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9327 loss: 2.9327 2022/10/08 02:50:48 - mmengine - INFO - Epoch(train) [93][540/2119] lr: 4.0000e-02 eta: 11:46:57 time: 0.3142 data_time: 0.0228 memory: 5826 grad_norm: 3.1341 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6571 loss: 2.6571 2022/10/08 02:50:55 - mmengine - INFO - Epoch(train) [93][560/2119] lr: 4.0000e-02 eta: 11:46:50 time: 0.3386 data_time: 0.0252 memory: 5826 grad_norm: 3.1658 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6474 loss: 2.6474 2022/10/08 02:51:02 - mmengine - INFO - Epoch(train) [93][580/2119] lr: 4.0000e-02 eta: 11:46:43 time: 0.3535 data_time: 0.0234 memory: 5826 grad_norm: 3.1751 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7181 loss: 2.7181 2022/10/08 02:51:09 - mmengine - INFO - Epoch(train) [93][600/2119] lr: 4.0000e-02 eta: 11:46:36 time: 0.3465 data_time: 0.0218 memory: 5826 grad_norm: 3.1020 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6933 loss: 2.6933 2022/10/08 02:51:17 - mmengine - INFO - Epoch(train) [93][620/2119] lr: 4.0000e-02 eta: 11:46:30 time: 0.3847 data_time: 0.0224 memory: 5826 grad_norm: 3.0964 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6455 loss: 2.6455 2022/10/08 02:51:24 - mmengine - INFO - Epoch(train) [93][640/2119] lr: 4.0000e-02 eta: 11:46:23 time: 0.3447 data_time: 0.0219 memory: 5826 grad_norm: 3.1051 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7421 loss: 2.7421 2022/10/08 02:51:30 - mmengine - INFO - Epoch(train) [93][660/2119] lr: 4.0000e-02 eta: 11:46:15 time: 0.3245 data_time: 0.0224 memory: 5826 grad_norm: 3.0988 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.4973 loss: 2.4973 2022/10/08 02:51:37 - mmengine - INFO - Epoch(train) [93][680/2119] lr: 4.0000e-02 eta: 11:46:08 time: 0.3242 data_time: 0.0203 memory: 5826 grad_norm: 3.1431 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.4900 loss: 2.4900 2022/10/08 02:51:44 - mmengine - INFO - Epoch(train) [93][700/2119] lr: 4.0000e-02 eta: 11:46:01 time: 0.3536 data_time: 0.0285 memory: 5826 grad_norm: 3.1872 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7254 loss: 2.7254 2022/10/08 02:51:51 - mmengine - INFO - Epoch(train) [93][720/2119] lr: 4.0000e-02 eta: 11:45:54 time: 0.3412 data_time: 0.0261 memory: 5826 grad_norm: 3.1163 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6623 loss: 2.6623 2022/10/08 02:51:58 - mmengine - INFO - Epoch(train) [93][740/2119] lr: 4.0000e-02 eta: 11:45:48 time: 0.3623 data_time: 0.0225 memory: 5826 grad_norm: 3.0985 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6796 loss: 2.6796 2022/10/08 02:52:05 - mmengine - INFO - Epoch(train) [93][760/2119] lr: 4.0000e-02 eta: 11:45:41 time: 0.3346 data_time: 0.0194 memory: 5826 grad_norm: 3.1001 top1_acc: 0.3125 top5_acc: 0.8750 loss_cls: 2.4257 loss: 2.4257 2022/10/08 02:52:11 - mmengine - INFO - Epoch(train) [93][780/2119] lr: 4.0000e-02 eta: 11:45:33 time: 0.3358 data_time: 0.0241 memory: 5826 grad_norm: 3.1543 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8693 loss: 2.8693 2022/10/08 02:52:18 - mmengine - INFO - Epoch(train) [93][800/2119] lr: 4.0000e-02 eta: 11:45:27 time: 0.3477 data_time: 0.0220 memory: 5826 grad_norm: 3.1588 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5197 loss: 2.5197 2022/10/08 02:52:26 - mmengine - INFO - Epoch(train) [93][820/2119] lr: 4.0000e-02 eta: 11:45:20 time: 0.3818 data_time: 0.0236 memory: 5826 grad_norm: 3.1716 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7008 loss: 2.7008 2022/10/08 02:52:32 - mmengine - INFO - Epoch(train) [93][840/2119] lr: 4.0000e-02 eta: 11:45:13 time: 0.3104 data_time: 0.0228 memory: 5826 grad_norm: 3.1336 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5999 loss: 2.5999 2022/10/08 02:52:39 - mmengine - INFO - Epoch(train) [93][860/2119] lr: 4.0000e-02 eta: 11:45:06 time: 0.3614 data_time: 0.0211 memory: 5826 grad_norm: 3.1011 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6951 loss: 2.6951 2022/10/08 02:52:47 - mmengine - INFO - Epoch(train) [93][880/2119] lr: 4.0000e-02 eta: 11:45:00 time: 0.3892 data_time: 0.0281 memory: 5826 grad_norm: 3.1418 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.8198 loss: 2.8198 2022/10/08 02:52:54 - mmengine - INFO - Epoch(train) [93][900/2119] lr: 4.0000e-02 eta: 11:44:52 time: 0.3160 data_time: 0.0310 memory: 5826 grad_norm: 3.0964 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7796 loss: 2.7796 2022/10/08 02:53:00 - mmengine - INFO - Epoch(train) [93][920/2119] lr: 4.0000e-02 eta: 11:44:45 time: 0.3220 data_time: 0.0244 memory: 5826 grad_norm: 3.0749 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6951 loss: 2.6951 2022/10/08 02:53:07 - mmengine - INFO - Epoch(train) [93][940/2119] lr: 4.0000e-02 eta: 11:44:38 time: 0.3739 data_time: 0.0213 memory: 5826 grad_norm: 3.1513 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.9217 loss: 2.9217 2022/10/08 02:53:14 - mmengine - INFO - Epoch(train) [93][960/2119] lr: 4.0000e-02 eta: 11:44:31 time: 0.3396 data_time: 0.0253 memory: 5826 grad_norm: 3.1406 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6392 loss: 2.6392 2022/10/08 02:53:21 - mmengine - INFO - Epoch(train) [93][980/2119] lr: 4.0000e-02 eta: 11:44:24 time: 0.3434 data_time: 0.0216 memory: 5826 grad_norm: 3.1289 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8056 loss: 2.8056 2022/10/08 02:53:28 - mmengine - INFO - Epoch(train) [93][1000/2119] lr: 4.0000e-02 eta: 11:44:18 time: 0.3598 data_time: 0.0224 memory: 5826 grad_norm: 3.1388 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6731 loss: 2.6731 2022/10/08 02:53:35 - mmengine - INFO - Epoch(train) [93][1020/2119] lr: 4.0000e-02 eta: 11:44:10 time: 0.3250 data_time: 0.0208 memory: 5826 grad_norm: 3.1565 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7240 loss: 2.7240 2022/10/08 02:53:42 - mmengine - INFO - Epoch(train) [93][1040/2119] lr: 4.0000e-02 eta: 11:44:04 time: 0.3615 data_time: 0.0215 memory: 5826 grad_norm: 3.2024 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7238 loss: 2.7238 2022/10/08 02:53:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 02:53:49 - mmengine - INFO - Epoch(train) [93][1060/2119] lr: 4.0000e-02 eta: 11:43:57 time: 0.3538 data_time: 0.0269 memory: 5826 grad_norm: 3.1013 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6446 loss: 2.6446 2022/10/08 02:53:56 - mmengine - INFO - Epoch(train) [93][1080/2119] lr: 4.0000e-02 eta: 11:43:50 time: 0.3412 data_time: 0.0229 memory: 5826 grad_norm: 3.0816 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7419 loss: 2.7419 2022/10/08 02:54:03 - mmengine - INFO - Epoch(train) [93][1100/2119] lr: 4.0000e-02 eta: 11:43:43 time: 0.3655 data_time: 0.0204 memory: 5826 grad_norm: 3.1087 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8014 loss: 2.8014 2022/10/08 02:54:10 - mmengine - INFO - Epoch(train) [93][1120/2119] lr: 4.0000e-02 eta: 11:43:36 time: 0.3188 data_time: 0.0251 memory: 5826 grad_norm: 3.1712 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7767 loss: 2.7767 2022/10/08 02:54:17 - mmengine - INFO - Epoch(train) [93][1140/2119] lr: 4.0000e-02 eta: 11:43:29 time: 0.3698 data_time: 0.0291 memory: 5826 grad_norm: 3.1344 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6402 loss: 2.6402 2022/10/08 02:54:24 - mmengine - INFO - Epoch(train) [93][1160/2119] lr: 4.0000e-02 eta: 11:43:22 time: 0.3285 data_time: 0.0223 memory: 5826 grad_norm: 3.1175 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7409 loss: 2.7409 2022/10/08 02:54:31 - mmengine - INFO - Epoch(train) [93][1180/2119] lr: 4.0000e-02 eta: 11:43:16 time: 0.3818 data_time: 0.0233 memory: 5826 grad_norm: 3.1243 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8776 loss: 2.8776 2022/10/08 02:54:38 - mmengine - INFO - Epoch(train) [93][1200/2119] lr: 4.0000e-02 eta: 11:43:09 time: 0.3376 data_time: 0.0236 memory: 5826 grad_norm: 3.1392 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6626 loss: 2.6626 2022/10/08 02:54:45 - mmengine - INFO - Epoch(train) [93][1220/2119] lr: 4.0000e-02 eta: 11:43:02 time: 0.3618 data_time: 0.0208 memory: 5826 grad_norm: 3.1586 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5070 loss: 2.5070 2022/10/08 02:54:52 - mmengine - INFO - Epoch(train) [93][1240/2119] lr: 4.0000e-02 eta: 11:42:55 time: 0.3480 data_time: 0.0208 memory: 5826 grad_norm: 3.1189 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6783 loss: 2.6783 2022/10/08 02:54:59 - mmengine - INFO - Epoch(train) [93][1260/2119] lr: 4.0000e-02 eta: 11:42:48 time: 0.3416 data_time: 0.0226 memory: 5826 grad_norm: 3.1365 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.9422 loss: 2.9422 2022/10/08 02:55:06 - mmengine - INFO - Epoch(train) [93][1280/2119] lr: 4.0000e-02 eta: 11:42:41 time: 0.3280 data_time: 0.0236 memory: 5826 grad_norm: 3.1282 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7143 loss: 2.7143 2022/10/08 02:55:13 - mmengine - INFO - Epoch(train) [93][1300/2119] lr: 4.0000e-02 eta: 11:42:34 time: 0.3655 data_time: 0.0317 memory: 5826 grad_norm: 3.1624 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7297 loss: 2.7297 2022/10/08 02:55:19 - mmengine - INFO - Epoch(train) [93][1320/2119] lr: 4.0000e-02 eta: 11:42:27 time: 0.3208 data_time: 0.0204 memory: 5826 grad_norm: 3.1699 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.6752 loss: 2.6752 2022/10/08 02:55:26 - mmengine - INFO - Epoch(train) [93][1340/2119] lr: 4.0000e-02 eta: 11:42:20 time: 0.3528 data_time: 0.0207 memory: 5826 grad_norm: 3.1389 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.4666 loss: 2.4666 2022/10/08 02:55:34 - mmengine - INFO - Epoch(train) [93][1360/2119] lr: 4.0000e-02 eta: 11:42:13 time: 0.3690 data_time: 0.0236 memory: 5826 grad_norm: 3.1714 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7529 loss: 2.7529 2022/10/08 02:55:41 - mmengine - INFO - Epoch(train) [93][1380/2119] lr: 4.0000e-02 eta: 11:42:06 time: 0.3593 data_time: 0.0251 memory: 5826 grad_norm: 3.1151 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7481 loss: 2.7481 2022/10/08 02:55:48 - mmengine - INFO - Epoch(train) [93][1400/2119] lr: 4.0000e-02 eta: 11:42:00 time: 0.3706 data_time: 0.0206 memory: 5826 grad_norm: 3.0932 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6070 loss: 2.6070 2022/10/08 02:55:55 - mmengine - INFO - Epoch(train) [93][1420/2119] lr: 4.0000e-02 eta: 11:41:52 time: 0.3144 data_time: 0.0255 memory: 5826 grad_norm: 3.1043 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5601 loss: 2.5601 2022/10/08 02:56:03 - mmengine - INFO - Epoch(train) [93][1440/2119] lr: 4.0000e-02 eta: 11:41:46 time: 0.3895 data_time: 0.0249 memory: 5826 grad_norm: 3.1771 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6437 loss: 2.6437 2022/10/08 02:56:09 - mmengine - INFO - Epoch(train) [93][1460/2119] lr: 4.0000e-02 eta: 11:41:39 time: 0.3136 data_time: 0.0235 memory: 5826 grad_norm: 3.1230 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.8637 loss: 2.8637 2022/10/08 02:56:16 - mmengine - INFO - Epoch(train) [93][1480/2119] lr: 4.0000e-02 eta: 11:41:32 time: 0.3801 data_time: 0.0243 memory: 5826 grad_norm: 3.1575 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9262 loss: 2.9262 2022/10/08 02:56:23 - mmengine - INFO - Epoch(train) [93][1500/2119] lr: 4.0000e-02 eta: 11:41:25 time: 0.3407 data_time: 0.0248 memory: 5826 grad_norm: 3.1554 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6337 loss: 2.6337 2022/10/08 02:56:30 - mmengine - INFO - Epoch(train) [93][1520/2119] lr: 4.0000e-02 eta: 11:41:18 time: 0.3383 data_time: 0.0230 memory: 5826 grad_norm: 3.1313 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.9619 loss: 2.9619 2022/10/08 02:56:37 - mmengine - INFO - Epoch(train) [93][1540/2119] lr: 4.0000e-02 eta: 11:41:11 time: 0.3445 data_time: 0.0267 memory: 5826 grad_norm: 3.0930 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6762 loss: 2.6762 2022/10/08 02:56:45 - mmengine - INFO - Epoch(train) [93][1560/2119] lr: 4.0000e-02 eta: 11:41:05 time: 0.4201 data_time: 0.0221 memory: 5826 grad_norm: 3.0952 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6904 loss: 2.6904 2022/10/08 02:56:51 - mmengine - INFO - Epoch(train) [93][1580/2119] lr: 4.0000e-02 eta: 11:40:58 time: 0.3064 data_time: 0.0228 memory: 5826 grad_norm: 3.1052 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7567 loss: 2.7567 2022/10/08 02:56:58 - mmengine - INFO - Epoch(train) [93][1600/2119] lr: 4.0000e-02 eta: 11:40:51 time: 0.3239 data_time: 0.0256 memory: 5826 grad_norm: 3.1508 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7944 loss: 2.7944 2022/10/08 02:57:06 - mmengine - INFO - Epoch(train) [93][1620/2119] lr: 4.0000e-02 eta: 11:40:44 time: 0.4082 data_time: 0.0200 memory: 5826 grad_norm: 3.0926 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7670 loss: 2.7670 2022/10/08 02:57:13 - mmengine - INFO - Epoch(train) [93][1640/2119] lr: 4.0000e-02 eta: 11:40:37 time: 0.3421 data_time: 0.0263 memory: 5826 grad_norm: 3.1249 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7110 loss: 2.7110 2022/10/08 02:57:20 - mmengine - INFO - Epoch(train) [93][1660/2119] lr: 4.0000e-02 eta: 11:40:30 time: 0.3461 data_time: 0.0219 memory: 5826 grad_norm: 3.0886 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7635 loss: 2.7635 2022/10/08 02:57:27 - mmengine - INFO - Epoch(train) [93][1680/2119] lr: 4.0000e-02 eta: 11:40:24 time: 0.3631 data_time: 0.0213 memory: 5826 grad_norm: 3.1830 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7542 loss: 2.7542 2022/10/08 02:57:34 - mmengine - INFO - Epoch(train) [93][1700/2119] lr: 4.0000e-02 eta: 11:40:17 time: 0.3262 data_time: 0.0268 memory: 5826 grad_norm: 3.1424 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6033 loss: 2.6033 2022/10/08 02:57:41 - mmengine - INFO - Epoch(train) [93][1720/2119] lr: 4.0000e-02 eta: 11:40:10 time: 0.3582 data_time: 0.0186 memory: 5826 grad_norm: 3.1420 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.8817 loss: 2.8817 2022/10/08 02:57:48 - mmengine - INFO - Epoch(train) [93][1740/2119] lr: 4.0000e-02 eta: 11:40:03 time: 0.3340 data_time: 0.0189 memory: 5826 grad_norm: 3.1211 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6618 loss: 2.6618 2022/10/08 02:57:56 - mmengine - INFO - Epoch(train) [93][1760/2119] lr: 4.0000e-02 eta: 11:39:57 time: 0.4123 data_time: 0.0232 memory: 5826 grad_norm: 3.0888 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8079 loss: 2.8079 2022/10/08 02:58:03 - mmengine - INFO - Epoch(train) [93][1780/2119] lr: 4.0000e-02 eta: 11:39:50 time: 0.3538 data_time: 0.0240 memory: 5826 grad_norm: 3.1561 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8001 loss: 2.8001 2022/10/08 02:58:09 - mmengine - INFO - Epoch(train) [93][1800/2119] lr: 4.0000e-02 eta: 11:39:42 time: 0.3060 data_time: 0.0221 memory: 5826 grad_norm: 3.1603 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6494 loss: 2.6494 2022/10/08 02:58:16 - mmengine - INFO - Epoch(train) [93][1820/2119] lr: 4.0000e-02 eta: 11:39:35 time: 0.3298 data_time: 0.0203 memory: 5826 grad_norm: 3.0662 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.0685 loss: 3.0685 2022/10/08 02:58:23 - mmengine - INFO - Epoch(train) [93][1840/2119] lr: 4.0000e-02 eta: 11:39:28 time: 0.3599 data_time: 0.0257 memory: 5826 grad_norm: 3.1175 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5082 loss: 2.5082 2022/10/08 02:58:29 - mmengine - INFO - Epoch(train) [93][1860/2119] lr: 4.0000e-02 eta: 11:39:21 time: 0.3236 data_time: 0.0247 memory: 5826 grad_norm: 3.1076 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7542 loss: 2.7542 2022/10/08 02:58:37 - mmengine - INFO - Epoch(train) [93][1880/2119] lr: 4.0000e-02 eta: 11:39:15 time: 0.3746 data_time: 0.0258 memory: 5826 grad_norm: 3.1569 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8096 loss: 2.8096 2022/10/08 02:58:44 - mmengine - INFO - Epoch(train) [93][1900/2119] lr: 4.0000e-02 eta: 11:39:08 time: 0.3667 data_time: 0.0245 memory: 5826 grad_norm: 3.0593 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6760 loss: 2.6760 2022/10/08 02:58:52 - mmengine - INFO - Epoch(train) [93][1920/2119] lr: 4.0000e-02 eta: 11:39:01 time: 0.3731 data_time: 0.0218 memory: 5826 grad_norm: 3.1027 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9557 loss: 2.9557 2022/10/08 02:58:57 - mmengine - INFO - Epoch(train) [93][1940/2119] lr: 4.0000e-02 eta: 11:38:54 time: 0.2871 data_time: 0.0244 memory: 5826 grad_norm: 3.0901 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6990 loss: 2.6990 2022/10/08 02:59:05 - mmengine - INFO - Epoch(train) [93][1960/2119] lr: 4.0000e-02 eta: 11:38:47 time: 0.3722 data_time: 0.0271 memory: 5826 grad_norm: 3.0977 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5059 loss: 2.5059 2022/10/08 02:59:11 - mmengine - INFO - Epoch(train) [93][1980/2119] lr: 4.0000e-02 eta: 11:38:40 time: 0.3268 data_time: 0.0305 memory: 5826 grad_norm: 3.1768 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7597 loss: 2.7597 2022/10/08 02:59:19 - mmengine - INFO - Epoch(train) [93][2000/2119] lr: 4.0000e-02 eta: 11:38:33 time: 0.3680 data_time: 0.0245 memory: 5826 grad_norm: 3.0848 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7317 loss: 2.7317 2022/10/08 02:59:25 - mmengine - INFO - Epoch(train) [93][2020/2119] lr: 4.0000e-02 eta: 11:38:26 time: 0.3269 data_time: 0.0308 memory: 5826 grad_norm: 3.1543 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.9401 loss: 2.9401 2022/10/08 02:59:32 - mmengine - INFO - Epoch(train) [93][2040/2119] lr: 4.0000e-02 eta: 11:38:19 time: 0.3581 data_time: 0.0208 memory: 5826 grad_norm: 3.1296 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7881 loss: 2.7881 2022/10/08 02:59:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 02:59:39 - mmengine - INFO - Epoch(train) [93][2060/2119] lr: 4.0000e-02 eta: 11:38:12 time: 0.3027 data_time: 0.0263 memory: 5826 grad_norm: 3.1902 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9001 loss: 2.9001 2022/10/08 02:59:46 - mmengine - INFO - Epoch(train) [93][2080/2119] lr: 4.0000e-02 eta: 11:38:05 time: 0.3659 data_time: 0.0258 memory: 5826 grad_norm: 3.1014 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7306 loss: 2.7306 2022/10/08 02:59:53 - mmengine - INFO - Epoch(train) [93][2100/2119] lr: 4.0000e-02 eta: 11:37:58 time: 0.3775 data_time: 0.0272 memory: 5826 grad_norm: 3.1105 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 2.9161 loss: 2.9161 2022/10/08 02:59:59 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 02:59:59 - mmengine - INFO - Epoch(train) [93][2119/2119] lr: 4.0000e-02 eta: 11:37:58 time: 0.3144 data_time: 0.0246 memory: 5826 grad_norm: 3.1830 top1_acc: 0.3000 top5_acc: 0.6000 loss_cls: 2.7470 loss: 2.7470 2022/10/08 03:00:10 - mmengine - INFO - Epoch(train) [94][20/2119] lr: 4.0000e-02 eta: 11:37:43 time: 0.5114 data_time: 0.1208 memory: 5826 grad_norm: 3.1847 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6178 loss: 2.6178 2022/10/08 03:00:15 - mmengine - INFO - Epoch(train) [94][40/2119] lr: 4.0000e-02 eta: 11:37:35 time: 0.2867 data_time: 0.0321 memory: 5826 grad_norm: 3.1166 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7069 loss: 2.7069 2022/10/08 03:00:23 - mmengine - INFO - Epoch(train) [94][60/2119] lr: 4.0000e-02 eta: 11:37:29 time: 0.3992 data_time: 0.0199 memory: 5826 grad_norm: 3.0988 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6753 loss: 2.6753 2022/10/08 03:00:30 - mmengine - INFO - Epoch(train) [94][80/2119] lr: 4.0000e-02 eta: 11:37:22 time: 0.3398 data_time: 0.0249 memory: 5826 grad_norm: 3.1725 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8436 loss: 2.8436 2022/10/08 03:00:37 - mmengine - INFO - Epoch(train) [94][100/2119] lr: 4.0000e-02 eta: 11:37:15 time: 0.3548 data_time: 0.0248 memory: 5826 grad_norm: 3.1205 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6688 loss: 2.6688 2022/10/08 03:00:45 - mmengine - INFO - Epoch(train) [94][120/2119] lr: 4.0000e-02 eta: 11:37:09 time: 0.3976 data_time: 0.0245 memory: 5826 grad_norm: 3.1321 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.6063 loss: 2.6063 2022/10/08 03:00:51 - mmengine - INFO - Epoch(train) [94][140/2119] lr: 4.0000e-02 eta: 11:37:01 time: 0.2926 data_time: 0.0211 memory: 5826 grad_norm: 3.1529 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6339 loss: 2.6339 2022/10/08 03:00:59 - mmengine - INFO - Epoch(train) [94][160/2119] lr: 4.0000e-02 eta: 11:36:55 time: 0.3907 data_time: 0.0261 memory: 5826 grad_norm: 3.1281 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7672 loss: 2.7672 2022/10/08 03:01:06 - mmengine - INFO - Epoch(train) [94][180/2119] lr: 4.0000e-02 eta: 11:36:48 time: 0.3481 data_time: 0.0225 memory: 5826 grad_norm: 3.0953 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.3627 loss: 2.3627 2022/10/08 03:01:13 - mmengine - INFO - Epoch(train) [94][200/2119] lr: 4.0000e-02 eta: 11:36:41 time: 0.3749 data_time: 0.0263 memory: 5826 grad_norm: 3.1189 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.5896 loss: 2.5896 2022/10/08 03:01:20 - mmengine - INFO - Epoch(train) [94][220/2119] lr: 4.0000e-02 eta: 11:36:34 time: 0.3147 data_time: 0.0183 memory: 5826 grad_norm: 3.0849 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4624 loss: 2.4624 2022/10/08 03:01:28 - mmengine - INFO - Epoch(train) [94][240/2119] lr: 4.0000e-02 eta: 11:36:28 time: 0.3993 data_time: 0.0254 memory: 5826 grad_norm: 3.1358 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.5625 loss: 2.5625 2022/10/08 03:01:34 - mmengine - INFO - Epoch(train) [94][260/2119] lr: 4.0000e-02 eta: 11:36:20 time: 0.3218 data_time: 0.0320 memory: 5826 grad_norm: 3.0935 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5866 loss: 2.5866 2022/10/08 03:01:43 - mmengine - INFO - Epoch(train) [94][280/2119] lr: 4.0000e-02 eta: 11:36:14 time: 0.4151 data_time: 0.0263 memory: 5826 grad_norm: 3.0972 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6330 loss: 2.6330 2022/10/08 03:01:49 - mmengine - INFO - Epoch(train) [94][300/2119] lr: 4.0000e-02 eta: 11:36:07 time: 0.3435 data_time: 0.0226 memory: 5826 grad_norm: 3.1502 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4391 loss: 2.4391 2022/10/08 03:01:56 - mmengine - INFO - Epoch(train) [94][320/2119] lr: 4.0000e-02 eta: 11:36:00 time: 0.3116 data_time: 0.0271 memory: 5826 grad_norm: 3.1342 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7373 loss: 2.7373 2022/10/08 03:02:03 - mmengine - INFO - Epoch(train) [94][340/2119] lr: 4.0000e-02 eta: 11:35:53 time: 0.3753 data_time: 0.0273 memory: 5826 grad_norm: 3.1297 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6884 loss: 2.6884 2022/10/08 03:02:10 - mmengine - INFO - Epoch(train) [94][360/2119] lr: 4.0000e-02 eta: 11:35:46 time: 0.3487 data_time: 0.0276 memory: 5826 grad_norm: 3.1151 top1_acc: 0.3750 top5_acc: 0.9375 loss_cls: 2.4841 loss: 2.4841 2022/10/08 03:02:17 - mmengine - INFO - Epoch(train) [94][380/2119] lr: 4.0000e-02 eta: 11:35:39 time: 0.3368 data_time: 0.0188 memory: 5826 grad_norm: 3.0879 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5011 loss: 2.5011 2022/10/08 03:02:25 - mmengine - INFO - Epoch(train) [94][400/2119] lr: 4.0000e-02 eta: 11:35:33 time: 0.3912 data_time: 0.0272 memory: 5826 grad_norm: 3.1543 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5550 loss: 2.5550 2022/10/08 03:02:31 - mmengine - INFO - Epoch(train) [94][420/2119] lr: 4.0000e-02 eta: 11:35:26 time: 0.3099 data_time: 0.0238 memory: 5826 grad_norm: 3.0391 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7267 loss: 2.7267 2022/10/08 03:02:38 - mmengine - INFO - Epoch(train) [94][440/2119] lr: 4.0000e-02 eta: 11:35:19 time: 0.3784 data_time: 0.0226 memory: 5826 grad_norm: 3.1218 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5259 loss: 2.5259 2022/10/08 03:02:46 - mmengine - INFO - Epoch(train) [94][460/2119] lr: 4.0000e-02 eta: 11:35:12 time: 0.3576 data_time: 0.0195 memory: 5826 grad_norm: 3.1559 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.6871 loss: 2.6871 2022/10/08 03:02:53 - mmengine - INFO - Epoch(train) [94][480/2119] lr: 4.0000e-02 eta: 11:35:06 time: 0.3775 data_time: 0.0262 memory: 5826 grad_norm: 3.1341 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7079 loss: 2.7079 2022/10/08 03:03:00 - mmengine - INFO - Epoch(train) [94][500/2119] lr: 4.0000e-02 eta: 11:34:58 time: 0.3203 data_time: 0.0264 memory: 5826 grad_norm: 3.0979 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8302 loss: 2.8302 2022/10/08 03:03:06 - mmengine - INFO - Epoch(train) [94][520/2119] lr: 4.0000e-02 eta: 11:34:51 time: 0.3404 data_time: 0.0227 memory: 5826 grad_norm: 3.1659 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6041 loss: 2.6041 2022/10/08 03:03:12 - mmengine - INFO - Epoch(train) [94][540/2119] lr: 4.0000e-02 eta: 11:34:44 time: 0.3018 data_time: 0.0296 memory: 5826 grad_norm: 3.1254 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.8122 loss: 2.8122 2022/10/08 03:03:20 - mmengine - INFO - Epoch(train) [94][560/2119] lr: 4.0000e-02 eta: 11:34:37 time: 0.3572 data_time: 0.0269 memory: 5826 grad_norm: 3.1617 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7550 loss: 2.7550 2022/10/08 03:03:27 - mmengine - INFO - Epoch(train) [94][580/2119] lr: 4.0000e-02 eta: 11:34:31 time: 0.3762 data_time: 0.0260 memory: 5826 grad_norm: 3.1424 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.9187 loss: 2.9187 2022/10/08 03:03:33 - mmengine - INFO - Epoch(train) [94][600/2119] lr: 4.0000e-02 eta: 11:34:23 time: 0.3166 data_time: 0.0206 memory: 5826 grad_norm: 3.1441 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6768 loss: 2.6768 2022/10/08 03:03:40 - mmengine - INFO - Epoch(train) [94][620/2119] lr: 4.0000e-02 eta: 11:34:16 time: 0.3341 data_time: 0.0277 memory: 5826 grad_norm: 3.1457 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5781 loss: 2.5781 2022/10/08 03:03:47 - mmengine - INFO - Epoch(train) [94][640/2119] lr: 4.0000e-02 eta: 11:34:09 time: 0.3632 data_time: 0.0245 memory: 5826 grad_norm: 3.0967 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6550 loss: 2.6550 2022/10/08 03:03:54 - mmengine - INFO - Epoch(train) [94][660/2119] lr: 4.0000e-02 eta: 11:34:02 time: 0.3360 data_time: 0.0245 memory: 5826 grad_norm: 3.1724 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7793 loss: 2.7793 2022/10/08 03:04:01 - mmengine - INFO - Epoch(train) [94][680/2119] lr: 4.0000e-02 eta: 11:33:55 time: 0.3467 data_time: 0.0208 memory: 5826 grad_norm: 3.2088 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5799 loss: 2.5799 2022/10/08 03:04:09 - mmengine - INFO - Epoch(train) [94][700/2119] lr: 4.0000e-02 eta: 11:33:49 time: 0.3762 data_time: 0.0241 memory: 5826 grad_norm: 3.1291 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6073 loss: 2.6073 2022/10/08 03:04:16 - mmengine - INFO - Epoch(train) [94][720/2119] lr: 4.0000e-02 eta: 11:33:42 time: 0.3447 data_time: 0.0222 memory: 5826 grad_norm: 3.1496 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.6296 loss: 2.6296 2022/10/08 03:04:23 - mmengine - INFO - Epoch(train) [94][740/2119] lr: 4.0000e-02 eta: 11:33:35 time: 0.3736 data_time: 0.0241 memory: 5826 grad_norm: 3.1099 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5609 loss: 2.5609 2022/10/08 03:04:31 - mmengine - INFO - Epoch(train) [94][760/2119] lr: 4.0000e-02 eta: 11:33:29 time: 0.3747 data_time: 0.0186 memory: 5826 grad_norm: 3.0745 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6509 loss: 2.6509 2022/10/08 03:04:38 - mmengine - INFO - Epoch(train) [94][780/2119] lr: 4.0000e-02 eta: 11:33:22 time: 0.3530 data_time: 0.0206 memory: 5826 grad_norm: 3.1525 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.5529 loss: 2.5529 2022/10/08 03:04:44 - mmengine - INFO - Epoch(train) [94][800/2119] lr: 4.0000e-02 eta: 11:33:15 time: 0.3310 data_time: 0.0215 memory: 5826 grad_norm: 3.0679 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6251 loss: 2.6251 2022/10/08 03:04:52 - mmengine - INFO - Epoch(train) [94][820/2119] lr: 4.0000e-02 eta: 11:33:08 time: 0.3961 data_time: 0.0223 memory: 5826 grad_norm: 3.1595 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8171 loss: 2.8171 2022/10/08 03:04:58 - mmengine - INFO - Epoch(train) [94][840/2119] lr: 4.0000e-02 eta: 11:33:01 time: 0.2987 data_time: 0.0256 memory: 5826 grad_norm: 3.1013 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6861 loss: 2.6861 2022/10/08 03:05:06 - mmengine - INFO - Epoch(train) [94][860/2119] lr: 4.0000e-02 eta: 11:32:55 time: 0.4101 data_time: 0.0195 memory: 5826 grad_norm: 3.1373 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.8716 loss: 2.8716 2022/10/08 03:05:14 - mmengine - INFO - Epoch(train) [94][880/2119] lr: 4.0000e-02 eta: 11:32:48 time: 0.3660 data_time: 0.0269 memory: 5826 grad_norm: 3.1648 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6207 loss: 2.6207 2022/10/08 03:05:20 - mmengine - INFO - Epoch(train) [94][900/2119] lr: 4.0000e-02 eta: 11:32:41 time: 0.3369 data_time: 0.0247 memory: 5826 grad_norm: 3.1554 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.0251 loss: 3.0251 2022/10/08 03:05:27 - mmengine - INFO - Epoch(train) [94][920/2119] lr: 4.0000e-02 eta: 11:32:34 time: 0.3338 data_time: 0.0259 memory: 5826 grad_norm: 3.1112 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7049 loss: 2.7049 2022/10/08 03:05:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 03:05:34 - mmengine - INFO - Epoch(train) [94][940/2119] lr: 4.0000e-02 eta: 11:32:27 time: 0.3304 data_time: 0.0245 memory: 5826 grad_norm: 3.1321 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7228 loss: 2.7228 2022/10/08 03:05:41 - mmengine - INFO - Epoch(train) [94][960/2119] lr: 4.0000e-02 eta: 11:32:20 time: 0.3464 data_time: 0.0204 memory: 5826 grad_norm: 3.1992 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8405 loss: 2.8405 2022/10/08 03:05:48 - mmengine - INFO - Epoch(train) [94][980/2119] lr: 4.0000e-02 eta: 11:32:13 time: 0.3644 data_time: 0.0211 memory: 5826 grad_norm: 3.1154 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6793 loss: 2.6793 2022/10/08 03:05:56 - mmengine - INFO - Epoch(train) [94][1000/2119] lr: 4.0000e-02 eta: 11:32:07 time: 0.3799 data_time: 0.0247 memory: 5826 grad_norm: 3.1561 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4888 loss: 2.4888 2022/10/08 03:06:02 - mmengine - INFO - Epoch(train) [94][1020/2119] lr: 4.0000e-02 eta: 11:31:59 time: 0.3241 data_time: 0.0263 memory: 5826 grad_norm: 3.1294 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7130 loss: 2.7130 2022/10/08 03:06:10 - mmengine - INFO - Epoch(train) [94][1040/2119] lr: 4.0000e-02 eta: 11:31:53 time: 0.3917 data_time: 0.0230 memory: 5826 grad_norm: 3.1186 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9220 loss: 2.9220 2022/10/08 03:06:16 - mmengine - INFO - Epoch(train) [94][1060/2119] lr: 4.0000e-02 eta: 11:31:46 time: 0.3275 data_time: 0.0258 memory: 5826 grad_norm: 3.0665 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6586 loss: 2.6586 2022/10/08 03:06:24 - mmengine - INFO - Epoch(train) [94][1080/2119] lr: 4.0000e-02 eta: 11:31:39 time: 0.3533 data_time: 0.0249 memory: 5826 grad_norm: 3.2063 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6291 loss: 2.6291 2022/10/08 03:06:30 - mmengine - INFO - Epoch(train) [94][1100/2119] lr: 4.0000e-02 eta: 11:31:32 time: 0.3334 data_time: 0.0189 memory: 5826 grad_norm: 3.2096 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6204 loss: 2.6204 2022/10/08 03:06:38 - mmengine - INFO - Epoch(train) [94][1120/2119] lr: 4.0000e-02 eta: 11:31:25 time: 0.3870 data_time: 0.0251 memory: 5826 grad_norm: 3.1594 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9309 loss: 2.9309 2022/10/08 03:06:44 - mmengine - INFO - Epoch(train) [94][1140/2119] lr: 4.0000e-02 eta: 11:31:18 time: 0.3017 data_time: 0.0238 memory: 5826 grad_norm: 3.1509 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.8598 loss: 2.8598 2022/10/08 03:06:52 - mmengine - INFO - Epoch(train) [94][1160/2119] lr: 4.0000e-02 eta: 11:31:12 time: 0.4118 data_time: 0.0256 memory: 5826 grad_norm: 3.0631 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6659 loss: 2.6659 2022/10/08 03:06:58 - mmengine - INFO - Epoch(train) [94][1180/2119] lr: 4.0000e-02 eta: 11:31:04 time: 0.3135 data_time: 0.0207 memory: 5826 grad_norm: 3.0924 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6438 loss: 2.6438 2022/10/08 03:07:06 - mmengine - INFO - Epoch(train) [94][1200/2119] lr: 4.0000e-02 eta: 11:30:58 time: 0.3526 data_time: 0.0235 memory: 5826 grad_norm: 3.1524 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6459 loss: 2.6459 2022/10/08 03:07:12 - mmengine - INFO - Epoch(train) [94][1220/2119] lr: 4.0000e-02 eta: 11:30:50 time: 0.3255 data_time: 0.0231 memory: 5826 grad_norm: 3.1334 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6562 loss: 2.6562 2022/10/08 03:07:20 - mmengine - INFO - Epoch(train) [94][1240/2119] lr: 4.0000e-02 eta: 11:30:44 time: 0.3858 data_time: 0.0276 memory: 5826 grad_norm: 3.1476 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7975 loss: 2.7975 2022/10/08 03:07:27 - mmengine - INFO - Epoch(train) [94][1260/2119] lr: 4.0000e-02 eta: 11:30:37 time: 0.3570 data_time: 0.0246 memory: 5826 grad_norm: 3.1310 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7782 loss: 2.7782 2022/10/08 03:07:34 - mmengine - INFO - Epoch(train) [94][1280/2119] lr: 4.0000e-02 eta: 11:30:30 time: 0.3474 data_time: 0.0222 memory: 5826 grad_norm: 3.1299 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7622 loss: 2.7622 2022/10/08 03:07:40 - mmengine - INFO - Epoch(train) [94][1300/2119] lr: 4.0000e-02 eta: 11:30:23 time: 0.3119 data_time: 0.0206 memory: 5826 grad_norm: 3.1561 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8753 loss: 2.8753 2022/10/08 03:07:48 - mmengine - INFO - Epoch(train) [94][1320/2119] lr: 4.0000e-02 eta: 11:30:16 time: 0.3895 data_time: 0.0228 memory: 5826 grad_norm: 3.1139 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6707 loss: 2.6707 2022/10/08 03:07:55 - mmengine - INFO - Epoch(train) [94][1340/2119] lr: 4.0000e-02 eta: 11:30:09 time: 0.3386 data_time: 0.0274 memory: 5826 grad_norm: 3.1071 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7063 loss: 2.7063 2022/10/08 03:08:02 - mmengine - INFO - Epoch(train) [94][1360/2119] lr: 4.0000e-02 eta: 11:30:03 time: 0.3700 data_time: 0.0258 memory: 5826 grad_norm: 3.1033 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7443 loss: 2.7443 2022/10/08 03:08:08 - mmengine - INFO - Epoch(train) [94][1380/2119] lr: 4.0000e-02 eta: 11:29:55 time: 0.3054 data_time: 0.0215 memory: 5826 grad_norm: 3.1427 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6235 loss: 2.6235 2022/10/08 03:08:15 - mmengine - INFO - Epoch(train) [94][1400/2119] lr: 4.0000e-02 eta: 11:29:48 time: 0.3497 data_time: 0.0281 memory: 5826 grad_norm: 3.1594 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8321 loss: 2.8321 2022/10/08 03:08:22 - mmengine - INFO - Epoch(train) [94][1420/2119] lr: 4.0000e-02 eta: 11:29:41 time: 0.3168 data_time: 0.0303 memory: 5826 grad_norm: 3.1327 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6807 loss: 2.6807 2022/10/08 03:08:29 - mmengine - INFO - Epoch(train) [94][1440/2119] lr: 4.0000e-02 eta: 11:29:34 time: 0.3521 data_time: 0.0264 memory: 5826 grad_norm: 3.1403 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.9044 loss: 2.9044 2022/10/08 03:08:36 - mmengine - INFO - Epoch(train) [94][1460/2119] lr: 4.0000e-02 eta: 11:29:28 time: 0.3650 data_time: 0.0204 memory: 5826 grad_norm: 3.1318 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6970 loss: 2.6970 2022/10/08 03:08:43 - mmengine - INFO - Epoch(train) [94][1480/2119] lr: 4.0000e-02 eta: 11:29:21 time: 0.3554 data_time: 0.0251 memory: 5826 grad_norm: 3.1205 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6654 loss: 2.6654 2022/10/08 03:08:50 - mmengine - INFO - Epoch(train) [94][1500/2119] lr: 4.0000e-02 eta: 11:29:14 time: 0.3556 data_time: 0.0240 memory: 5826 grad_norm: 3.0949 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6115 loss: 2.6115 2022/10/08 03:08:57 - mmengine - INFO - Epoch(train) [94][1520/2119] lr: 4.0000e-02 eta: 11:29:07 time: 0.3162 data_time: 0.0272 memory: 5826 grad_norm: 3.1024 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7808 loss: 2.7808 2022/10/08 03:09:04 - mmengine - INFO - Epoch(train) [94][1540/2119] lr: 4.0000e-02 eta: 11:29:00 time: 0.3671 data_time: 0.0411 memory: 5826 grad_norm: 3.1607 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6171 loss: 2.6171 2022/10/08 03:09:11 - mmengine - INFO - Epoch(train) [94][1560/2119] lr: 4.0000e-02 eta: 11:28:53 time: 0.3367 data_time: 0.0207 memory: 5826 grad_norm: 3.1153 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7620 loss: 2.7620 2022/10/08 03:09:17 - mmengine - INFO - Epoch(train) [94][1580/2119] lr: 4.0000e-02 eta: 11:28:46 time: 0.3247 data_time: 0.0293 memory: 5826 grad_norm: 3.0542 top1_acc: 0.1250 top5_acc: 0.5625 loss_cls: 2.6466 loss: 2.6466 2022/10/08 03:09:24 - mmengine - INFO - Epoch(train) [94][1600/2119] lr: 4.0000e-02 eta: 11:28:39 time: 0.3687 data_time: 0.0260 memory: 5826 grad_norm: 3.0780 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7169 loss: 2.7169 2022/10/08 03:09:31 - mmengine - INFO - Epoch(train) [94][1620/2119] lr: 4.0000e-02 eta: 11:28:32 time: 0.3480 data_time: 0.0236 memory: 5826 grad_norm: 3.1463 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.9986 loss: 2.9986 2022/10/08 03:09:39 - mmengine - INFO - Epoch(train) [94][1640/2119] lr: 4.0000e-02 eta: 11:28:25 time: 0.3531 data_time: 0.0215 memory: 5826 grad_norm: 3.1551 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7049 loss: 2.7049 2022/10/08 03:09:46 - mmengine - INFO - Epoch(train) [94][1660/2119] lr: 4.0000e-02 eta: 11:28:19 time: 0.3637 data_time: 0.0272 memory: 5826 grad_norm: 3.1313 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5324 loss: 2.5324 2022/10/08 03:09:53 - mmengine - INFO - Epoch(train) [94][1680/2119] lr: 4.0000e-02 eta: 11:28:12 time: 0.3748 data_time: 0.0203 memory: 5826 grad_norm: 3.1504 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8375 loss: 2.8375 2022/10/08 03:10:00 - mmengine - INFO - Epoch(train) [94][1700/2119] lr: 4.0000e-02 eta: 11:28:05 time: 0.3174 data_time: 0.0215 memory: 5826 grad_norm: 3.1661 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7417 loss: 2.7417 2022/10/08 03:10:07 - mmengine - INFO - Epoch(train) [94][1720/2119] lr: 4.0000e-02 eta: 11:27:58 time: 0.3614 data_time: 0.0254 memory: 5826 grad_norm: 3.1092 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.4839 loss: 2.4839 2022/10/08 03:10:14 - mmengine - INFO - Epoch(train) [94][1740/2119] lr: 4.0000e-02 eta: 11:27:51 time: 0.3602 data_time: 0.0231 memory: 5826 grad_norm: 3.1953 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7222 loss: 2.7222 2022/10/08 03:10:21 - mmengine - INFO - Epoch(train) [94][1760/2119] lr: 4.0000e-02 eta: 11:27:44 time: 0.3469 data_time: 0.0228 memory: 5826 grad_norm: 3.1408 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9274 loss: 2.9274 2022/10/08 03:10:27 - mmengine - INFO - Epoch(train) [94][1780/2119] lr: 4.0000e-02 eta: 11:27:37 time: 0.3178 data_time: 0.0236 memory: 5826 grad_norm: 3.1728 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7269 loss: 2.7269 2022/10/08 03:10:35 - mmengine - INFO - Epoch(train) [94][1800/2119] lr: 4.0000e-02 eta: 11:27:30 time: 0.3695 data_time: 0.0200 memory: 5826 grad_norm: 3.1732 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.8491 loss: 2.8491 2022/10/08 03:10:41 - mmengine - INFO - Epoch(train) [94][1820/2119] lr: 4.0000e-02 eta: 11:27:23 time: 0.3175 data_time: 0.0229 memory: 5826 grad_norm: 3.1438 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8556 loss: 2.8556 2022/10/08 03:10:49 - mmengine - INFO - Epoch(train) [94][1840/2119] lr: 4.0000e-02 eta: 11:27:17 time: 0.4114 data_time: 0.0265 memory: 5826 grad_norm: 3.1889 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.5903 loss: 2.5903 2022/10/08 03:10:56 - mmengine - INFO - Epoch(train) [94][1860/2119] lr: 4.0000e-02 eta: 11:27:09 time: 0.3131 data_time: 0.0201 memory: 5826 grad_norm: 3.1117 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6455 loss: 2.6455 2022/10/08 03:11:04 - mmengine - INFO - Epoch(train) [94][1880/2119] lr: 4.0000e-02 eta: 11:27:03 time: 0.3970 data_time: 0.0287 memory: 5826 grad_norm: 3.1120 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7254 loss: 2.7254 2022/10/08 03:11:09 - mmengine - INFO - Epoch(train) [94][1900/2119] lr: 4.0000e-02 eta: 11:26:55 time: 0.2492 data_time: 0.0200 memory: 5826 grad_norm: 3.1455 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7256 loss: 2.7256 2022/10/08 03:11:16 - mmengine - INFO - Epoch(train) [94][1920/2119] lr: 4.0000e-02 eta: 11:26:49 time: 0.3839 data_time: 0.0218 memory: 5826 grad_norm: 3.1002 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.8803 loss: 2.8803 2022/10/08 03:11:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 03:11:23 - mmengine - INFO - Epoch(train) [94][1940/2119] lr: 4.0000e-02 eta: 11:26:42 time: 0.3517 data_time: 0.0246 memory: 5826 grad_norm: 3.1554 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6399 loss: 2.6399 2022/10/08 03:11:30 - mmengine - INFO - Epoch(train) [94][1960/2119] lr: 4.0000e-02 eta: 11:26:35 time: 0.3420 data_time: 0.0279 memory: 5826 grad_norm: 3.1883 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4974 loss: 2.4974 2022/10/08 03:11:37 - mmengine - INFO - Epoch(train) [94][1980/2119] lr: 4.0000e-02 eta: 11:26:28 time: 0.3281 data_time: 0.0237 memory: 5826 grad_norm: 3.1436 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7845 loss: 2.7845 2022/10/08 03:11:44 - mmengine - INFO - Epoch(train) [94][2000/2119] lr: 4.0000e-02 eta: 11:26:21 time: 0.3765 data_time: 0.0257 memory: 5826 grad_norm: 3.1492 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7567 loss: 2.7567 2022/10/08 03:11:51 - mmengine - INFO - Epoch(train) [94][2020/2119] lr: 4.0000e-02 eta: 11:26:14 time: 0.3121 data_time: 0.0228 memory: 5826 grad_norm: 3.1704 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5237 loss: 2.5237 2022/10/08 03:11:58 - mmengine - INFO - Epoch(train) [94][2040/2119] lr: 4.0000e-02 eta: 11:26:07 time: 0.3595 data_time: 0.0240 memory: 5826 grad_norm: 3.1285 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7627 loss: 2.7627 2022/10/08 03:12:04 - mmengine - INFO - Epoch(train) [94][2060/2119] lr: 4.0000e-02 eta: 11:26:00 time: 0.3291 data_time: 0.0222 memory: 5826 grad_norm: 3.1197 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6381 loss: 2.6381 2022/10/08 03:12:11 - mmengine - INFO - Epoch(train) [94][2080/2119] lr: 4.0000e-02 eta: 11:25:53 time: 0.3509 data_time: 0.0229 memory: 5826 grad_norm: 3.1390 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7285 loss: 2.7285 2022/10/08 03:12:18 - mmengine - INFO - Epoch(train) [94][2100/2119] lr: 4.0000e-02 eta: 11:25:46 time: 0.3188 data_time: 0.0223 memory: 5826 grad_norm: 3.1084 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6776 loss: 2.6776 2022/10/08 03:12:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 03:12:26 - mmengine - INFO - Epoch(train) [94][2119/2119] lr: 4.0000e-02 eta: 11:25:46 time: 0.4083 data_time: 0.0232 memory: 5826 grad_norm: 3.1449 top1_acc: 0.2000 top5_acc: 0.8000 loss_cls: 2.8875 loss: 2.8875 2022/10/08 03:12:35 - mmengine - INFO - Epoch(train) [95][20/2119] lr: 4.0000e-02 eta: 11:25:29 time: 0.4561 data_time: 0.1263 memory: 5826 grad_norm: 3.1126 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5182 loss: 2.5182 2022/10/08 03:12:42 - mmengine - INFO - Epoch(train) [95][40/2119] lr: 4.0000e-02 eta: 11:25:23 time: 0.3526 data_time: 0.0255 memory: 5826 grad_norm: 3.0796 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5131 loss: 2.5131 2022/10/08 03:12:50 - mmengine - INFO - Epoch(train) [95][60/2119] lr: 4.0000e-02 eta: 11:25:16 time: 0.3936 data_time: 0.0273 memory: 5826 grad_norm: 3.1695 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6469 loss: 2.6469 2022/10/08 03:12:56 - mmengine - INFO - Epoch(train) [95][80/2119] lr: 4.0000e-02 eta: 11:25:09 time: 0.3215 data_time: 0.0269 memory: 5826 grad_norm: 3.1857 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6297 loss: 2.6297 2022/10/08 03:13:04 - mmengine - INFO - Epoch(train) [95][100/2119] lr: 4.0000e-02 eta: 11:25:02 time: 0.3684 data_time: 0.0257 memory: 5826 grad_norm: 3.1383 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9301 loss: 2.9301 2022/10/08 03:13:10 - mmengine - INFO - Epoch(train) [95][120/2119] lr: 4.0000e-02 eta: 11:24:55 time: 0.3268 data_time: 0.0226 memory: 5826 grad_norm: 3.1496 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7002 loss: 2.7002 2022/10/08 03:13:17 - mmengine - INFO - Epoch(train) [95][140/2119] lr: 4.0000e-02 eta: 11:24:48 time: 0.3267 data_time: 0.0218 memory: 5826 grad_norm: 3.1119 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6605 loss: 2.6605 2022/10/08 03:13:24 - mmengine - INFO - Epoch(train) [95][160/2119] lr: 4.0000e-02 eta: 11:24:41 time: 0.3681 data_time: 0.0217 memory: 5826 grad_norm: 3.1559 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8191 loss: 2.8191 2022/10/08 03:13:30 - mmengine - INFO - Epoch(train) [95][180/2119] lr: 4.0000e-02 eta: 11:24:34 time: 0.3162 data_time: 0.0220 memory: 5826 grad_norm: 3.0734 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5646 loss: 2.5646 2022/10/08 03:13:38 - mmengine - INFO - Epoch(train) [95][200/2119] lr: 4.0000e-02 eta: 11:24:27 time: 0.3832 data_time: 0.0193 memory: 5826 grad_norm: 3.1541 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5135 loss: 2.5135 2022/10/08 03:13:45 - mmengine - INFO - Epoch(train) [95][220/2119] lr: 4.0000e-02 eta: 11:24:21 time: 0.3495 data_time: 0.0225 memory: 5826 grad_norm: 3.1628 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7527 loss: 2.7527 2022/10/08 03:13:52 - mmengine - INFO - Epoch(train) [95][240/2119] lr: 4.0000e-02 eta: 11:24:13 time: 0.3244 data_time: 0.0235 memory: 5826 grad_norm: 3.1345 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6467 loss: 2.6467 2022/10/08 03:13:58 - mmengine - INFO - Epoch(train) [95][260/2119] lr: 4.0000e-02 eta: 11:24:06 time: 0.3401 data_time: 0.0190 memory: 5826 grad_norm: 3.1757 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.9486 loss: 2.9486 2022/10/08 03:14:06 - mmengine - INFO - Epoch(train) [95][280/2119] lr: 4.0000e-02 eta: 11:24:00 time: 0.3637 data_time: 0.0232 memory: 5826 grad_norm: 3.0729 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5351 loss: 2.5351 2022/10/08 03:14:13 - mmengine - INFO - Epoch(train) [95][300/2119] lr: 4.0000e-02 eta: 11:23:53 time: 0.3661 data_time: 0.0236 memory: 5826 grad_norm: 3.1582 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4414 loss: 2.4414 2022/10/08 03:14:20 - mmengine - INFO - Epoch(train) [95][320/2119] lr: 4.0000e-02 eta: 11:23:46 time: 0.3701 data_time: 0.0197 memory: 5826 grad_norm: 3.1851 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6989 loss: 2.6989 2022/10/08 03:14:27 - mmengine - INFO - Epoch(train) [95][340/2119] lr: 4.0000e-02 eta: 11:23:39 time: 0.3155 data_time: 0.0194 memory: 5826 grad_norm: 3.1593 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.9414 loss: 2.9414 2022/10/08 03:14:34 - mmengine - INFO - Epoch(train) [95][360/2119] lr: 4.0000e-02 eta: 11:23:32 time: 0.3867 data_time: 0.0188 memory: 5826 grad_norm: 3.1820 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5700 loss: 2.5700 2022/10/08 03:14:41 - mmengine - INFO - Epoch(train) [95][380/2119] lr: 4.0000e-02 eta: 11:23:25 time: 0.3088 data_time: 0.0224 memory: 5826 grad_norm: 3.2090 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5420 loss: 2.5420 2022/10/08 03:14:48 - mmengine - INFO - Epoch(train) [95][400/2119] lr: 4.0000e-02 eta: 11:23:18 time: 0.3678 data_time: 0.0212 memory: 5826 grad_norm: 3.1507 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7250 loss: 2.7250 2022/10/08 03:14:54 - mmengine - INFO - Epoch(train) [95][420/2119] lr: 4.0000e-02 eta: 11:23:11 time: 0.3278 data_time: 0.0231 memory: 5826 grad_norm: 3.1319 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6210 loss: 2.6210 2022/10/08 03:15:02 - mmengine - INFO - Epoch(train) [95][440/2119] lr: 4.0000e-02 eta: 11:23:04 time: 0.3620 data_time: 0.0196 memory: 5826 grad_norm: 3.1864 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6303 loss: 2.6303 2022/10/08 03:15:08 - mmengine - INFO - Epoch(train) [95][460/2119] lr: 4.0000e-02 eta: 11:22:57 time: 0.3076 data_time: 0.0210 memory: 5826 grad_norm: 3.1602 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7936 loss: 2.7936 2022/10/08 03:15:16 - mmengine - INFO - Epoch(train) [95][480/2119] lr: 4.0000e-02 eta: 11:22:51 time: 0.4007 data_time: 0.0204 memory: 5826 grad_norm: 3.1241 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.4936 loss: 2.4936 2022/10/08 03:15:23 - mmengine - INFO - Epoch(train) [95][500/2119] lr: 4.0000e-02 eta: 11:22:44 time: 0.3363 data_time: 0.0293 memory: 5826 grad_norm: 3.1960 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8772 loss: 2.8772 2022/10/08 03:15:29 - mmengine - INFO - Epoch(train) [95][520/2119] lr: 4.0000e-02 eta: 11:22:37 time: 0.3358 data_time: 0.0236 memory: 5826 grad_norm: 3.1209 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7594 loss: 2.7594 2022/10/08 03:15:35 - mmengine - INFO - Epoch(train) [95][540/2119] lr: 4.0000e-02 eta: 11:22:29 time: 0.3024 data_time: 0.0239 memory: 5826 grad_norm: 3.1702 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.7334 loss: 2.7334 2022/10/08 03:15:43 - mmengine - INFO - Epoch(train) [95][560/2119] lr: 4.0000e-02 eta: 11:22:23 time: 0.3700 data_time: 0.0203 memory: 5826 grad_norm: 3.1832 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7553 loss: 2.7553 2022/10/08 03:15:50 - mmengine - INFO - Epoch(train) [95][580/2119] lr: 4.0000e-02 eta: 11:22:15 time: 0.3344 data_time: 0.0216 memory: 5826 grad_norm: 3.1746 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5123 loss: 2.5123 2022/10/08 03:15:57 - mmengine - INFO - Epoch(train) [95][600/2119] lr: 4.0000e-02 eta: 11:22:09 time: 0.3787 data_time: 0.0255 memory: 5826 grad_norm: 3.1593 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7160 loss: 2.7160 2022/10/08 03:16:03 - mmengine - INFO - Epoch(train) [95][620/2119] lr: 4.0000e-02 eta: 11:22:02 time: 0.3109 data_time: 0.0236 memory: 5826 grad_norm: 3.1395 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4034 loss: 2.4034 2022/10/08 03:16:10 - mmengine - INFO - Epoch(train) [95][640/2119] lr: 4.0000e-02 eta: 11:21:54 time: 0.3353 data_time: 0.0292 memory: 5826 grad_norm: 3.1612 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8075 loss: 2.8075 2022/10/08 03:16:16 - mmengine - INFO - Epoch(train) [95][660/2119] lr: 4.0000e-02 eta: 11:21:47 time: 0.3121 data_time: 0.0229 memory: 5826 grad_norm: 3.1173 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7729 loss: 2.7729 2022/10/08 03:16:24 - mmengine - INFO - Epoch(train) [95][680/2119] lr: 4.0000e-02 eta: 11:21:41 time: 0.3932 data_time: 0.0219 memory: 5826 grad_norm: 3.0919 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6842 loss: 2.6842 2022/10/08 03:16:31 - mmengine - INFO - Epoch(train) [95][700/2119] lr: 4.0000e-02 eta: 11:21:34 time: 0.3475 data_time: 0.0208 memory: 5826 grad_norm: 3.1344 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5830 loss: 2.5830 2022/10/08 03:16:38 - mmengine - INFO - Epoch(train) [95][720/2119] lr: 4.0000e-02 eta: 11:21:27 time: 0.3514 data_time: 0.0222 memory: 5826 grad_norm: 3.1500 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7823 loss: 2.7823 2022/10/08 03:16:45 - mmengine - INFO - Epoch(train) [95][740/2119] lr: 4.0000e-02 eta: 11:21:20 time: 0.3505 data_time: 0.0186 memory: 5826 grad_norm: 3.1350 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6871 loss: 2.6871 2022/10/08 03:16:52 - mmengine - INFO - Epoch(train) [95][760/2119] lr: 4.0000e-02 eta: 11:21:13 time: 0.3587 data_time: 0.0277 memory: 5826 grad_norm: 3.1440 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8711 loss: 2.8711 2022/10/08 03:16:59 - mmengine - INFO - Epoch(train) [95][780/2119] lr: 4.0000e-02 eta: 11:21:06 time: 0.3313 data_time: 0.0185 memory: 5826 grad_norm: 3.1713 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8729 loss: 2.8729 2022/10/08 03:17:07 - mmengine - INFO - Epoch(train) [95][800/2119] lr: 4.0000e-02 eta: 11:21:00 time: 0.3994 data_time: 0.0235 memory: 5826 grad_norm: 3.1370 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6232 loss: 2.6232 2022/10/08 03:17:12 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 03:17:13 - mmengine - INFO - Epoch(train) [95][820/2119] lr: 4.0000e-02 eta: 11:20:53 time: 0.3211 data_time: 0.0218 memory: 5826 grad_norm: 3.1232 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7405 loss: 2.7405 2022/10/08 03:17:21 - mmengine - INFO - Epoch(train) [95][840/2119] lr: 4.0000e-02 eta: 11:20:46 time: 0.3881 data_time: 0.0243 memory: 5826 grad_norm: 3.1016 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6461 loss: 2.6461 2022/10/08 03:17:28 - mmengine - INFO - Epoch(train) [95][860/2119] lr: 4.0000e-02 eta: 11:20:39 time: 0.3207 data_time: 0.0281 memory: 5826 grad_norm: 3.0307 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7490 loss: 2.7490 2022/10/08 03:17:36 - mmengine - INFO - Epoch(train) [95][880/2119] lr: 4.0000e-02 eta: 11:20:33 time: 0.4040 data_time: 0.0251 memory: 5826 grad_norm: 3.1729 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8436 loss: 2.8436 2022/10/08 03:17:42 - mmengine - INFO - Epoch(train) [95][900/2119] lr: 4.0000e-02 eta: 11:20:26 time: 0.3304 data_time: 0.0261 memory: 5826 grad_norm: 3.1304 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7406 loss: 2.7406 2022/10/08 03:17:49 - mmengine - INFO - Epoch(train) [95][920/2119] lr: 4.0000e-02 eta: 11:20:19 time: 0.3534 data_time: 0.0247 memory: 5826 grad_norm: 3.1764 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8842 loss: 2.8842 2022/10/08 03:17:56 - mmengine - INFO - Epoch(train) [95][940/2119] lr: 4.0000e-02 eta: 11:20:12 time: 0.3289 data_time: 0.0224 memory: 5826 grad_norm: 3.1009 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5636 loss: 2.5636 2022/10/08 03:18:05 - mmengine - INFO - Epoch(train) [95][960/2119] lr: 4.0000e-02 eta: 11:20:06 time: 0.4364 data_time: 0.0208 memory: 5826 grad_norm: 3.1488 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6320 loss: 2.6320 2022/10/08 03:18:10 - mmengine - INFO - Epoch(train) [95][980/2119] lr: 4.0000e-02 eta: 11:19:58 time: 0.2871 data_time: 0.0193 memory: 5826 grad_norm: 3.1428 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7501 loss: 2.7501 2022/10/08 03:18:18 - mmengine - INFO - Epoch(train) [95][1000/2119] lr: 4.0000e-02 eta: 11:19:51 time: 0.3674 data_time: 0.0273 memory: 5826 grad_norm: 3.0959 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8295 loss: 2.8295 2022/10/08 03:18:24 - mmengine - INFO - Epoch(train) [95][1020/2119] lr: 4.0000e-02 eta: 11:19:44 time: 0.3328 data_time: 0.0255 memory: 5826 grad_norm: 3.1692 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7324 loss: 2.7324 2022/10/08 03:18:31 - mmengine - INFO - Epoch(train) [95][1040/2119] lr: 4.0000e-02 eta: 11:19:37 time: 0.3227 data_time: 0.0288 memory: 5826 grad_norm: 3.1191 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6374 loss: 2.6374 2022/10/08 03:18:37 - mmengine - INFO - Epoch(train) [95][1060/2119] lr: 4.0000e-02 eta: 11:19:30 time: 0.3235 data_time: 0.0221 memory: 5826 grad_norm: 3.1700 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8771 loss: 2.8771 2022/10/08 03:18:45 - mmengine - INFO - Epoch(train) [95][1080/2119] lr: 4.0000e-02 eta: 11:19:23 time: 0.3715 data_time: 0.0256 memory: 5826 grad_norm: 3.1650 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8887 loss: 2.8887 2022/10/08 03:18:51 - mmengine - INFO - Epoch(train) [95][1100/2119] lr: 4.0000e-02 eta: 11:19:16 time: 0.3193 data_time: 0.0250 memory: 5826 grad_norm: 3.2091 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6263 loss: 2.6263 2022/10/08 03:18:58 - mmengine - INFO - Epoch(train) [95][1120/2119] lr: 4.0000e-02 eta: 11:19:09 time: 0.3476 data_time: 0.0214 memory: 5826 grad_norm: 3.1147 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.7330 loss: 2.7330 2022/10/08 03:19:05 - mmengine - INFO - Epoch(train) [95][1140/2119] lr: 4.0000e-02 eta: 11:19:02 time: 0.3384 data_time: 0.0275 memory: 5826 grad_norm: 3.1207 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6497 loss: 2.6497 2022/10/08 03:19:12 - mmengine - INFO - Epoch(train) [95][1160/2119] lr: 4.0000e-02 eta: 11:18:55 time: 0.3704 data_time: 0.0212 memory: 5826 grad_norm: 3.1331 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7688 loss: 2.7688 2022/10/08 03:19:19 - mmengine - INFO - Epoch(train) [95][1180/2119] lr: 4.0000e-02 eta: 11:18:48 time: 0.3483 data_time: 0.0227 memory: 5826 grad_norm: 3.1674 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8571 loss: 2.8571 2022/10/08 03:19:28 - mmengine - INFO - Epoch(train) [95][1200/2119] lr: 4.0000e-02 eta: 11:18:42 time: 0.4196 data_time: 0.0235 memory: 5826 grad_norm: 3.0736 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6998 loss: 2.6998 2022/10/08 03:19:35 - mmengine - INFO - Epoch(train) [95][1220/2119] lr: 4.0000e-02 eta: 11:18:36 time: 0.3705 data_time: 0.0228 memory: 5826 grad_norm: 3.1382 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8441 loss: 2.8441 2022/10/08 03:19:42 - mmengine - INFO - Epoch(train) [95][1240/2119] lr: 4.0000e-02 eta: 11:18:29 time: 0.3522 data_time: 0.0225 memory: 5826 grad_norm: 3.1184 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9186 loss: 2.9186 2022/10/08 03:19:48 - mmengine - INFO - Epoch(train) [95][1260/2119] lr: 4.0000e-02 eta: 11:18:21 time: 0.3095 data_time: 0.0245 memory: 5826 grad_norm: 3.1156 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7523 loss: 2.7523 2022/10/08 03:19:56 - mmengine - INFO - Epoch(train) [95][1280/2119] lr: 4.0000e-02 eta: 11:18:15 time: 0.3684 data_time: 0.0219 memory: 5826 grad_norm: 3.0809 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4541 loss: 2.4541 2022/10/08 03:20:03 - mmengine - INFO - Epoch(train) [95][1300/2119] lr: 4.0000e-02 eta: 11:18:08 time: 0.3356 data_time: 0.0263 memory: 5826 grad_norm: 3.1356 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5955 loss: 2.5955 2022/10/08 03:20:10 - mmengine - INFO - Epoch(train) [95][1320/2119] lr: 4.0000e-02 eta: 11:18:01 time: 0.3586 data_time: 0.0221 memory: 5826 grad_norm: 3.1280 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7458 loss: 2.7458 2022/10/08 03:20:17 - mmengine - INFO - Epoch(train) [95][1340/2119] lr: 4.0000e-02 eta: 11:17:54 time: 0.3669 data_time: 0.0184 memory: 5826 grad_norm: 3.1280 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8010 loss: 2.8010 2022/10/08 03:20:25 - mmengine - INFO - Epoch(train) [95][1360/2119] lr: 4.0000e-02 eta: 11:17:48 time: 0.4013 data_time: 0.0246 memory: 5826 grad_norm: 3.1388 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9089 loss: 2.9089 2022/10/08 03:20:31 - mmengine - INFO - Epoch(train) [95][1380/2119] lr: 4.0000e-02 eta: 11:17:41 time: 0.3149 data_time: 0.0244 memory: 5826 grad_norm: 3.1495 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6711 loss: 2.6711 2022/10/08 03:20:39 - mmengine - INFO - Epoch(train) [95][1400/2119] lr: 4.0000e-02 eta: 11:17:34 time: 0.3710 data_time: 0.0245 memory: 5826 grad_norm: 3.1428 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5905 loss: 2.5905 2022/10/08 03:20:46 - mmengine - INFO - Epoch(train) [95][1420/2119] lr: 4.0000e-02 eta: 11:17:27 time: 0.3528 data_time: 0.0187 memory: 5826 grad_norm: 3.1448 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8332 loss: 2.8332 2022/10/08 03:20:53 - mmengine - INFO - Epoch(train) [95][1440/2119] lr: 4.0000e-02 eta: 11:17:20 time: 0.3353 data_time: 0.0274 memory: 5826 grad_norm: 3.1619 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7730 loss: 2.7730 2022/10/08 03:20:59 - mmengine - INFO - Epoch(train) [95][1460/2119] lr: 4.0000e-02 eta: 11:17:13 time: 0.3148 data_time: 0.0243 memory: 5826 grad_norm: 3.1591 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8113 loss: 2.8113 2022/10/08 03:21:06 - mmengine - INFO - Epoch(train) [95][1480/2119] lr: 4.0000e-02 eta: 11:17:06 time: 0.3731 data_time: 0.0203 memory: 5826 grad_norm: 3.1489 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6119 loss: 2.6119 2022/10/08 03:21:13 - mmengine - INFO - Epoch(train) [95][1500/2119] lr: 4.0000e-02 eta: 11:16:59 time: 0.3319 data_time: 0.0225 memory: 5826 grad_norm: 3.1695 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8091 loss: 2.8091 2022/10/08 03:21:21 - mmengine - INFO - Epoch(train) [95][1520/2119] lr: 4.0000e-02 eta: 11:16:53 time: 0.4101 data_time: 0.0247 memory: 5826 grad_norm: 3.0804 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6985 loss: 2.6985 2022/10/08 03:21:27 - mmengine - INFO - Epoch(train) [95][1540/2119] lr: 4.0000e-02 eta: 11:16:45 time: 0.3112 data_time: 0.0215 memory: 5826 grad_norm: 3.0784 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7000 loss: 2.7000 2022/10/08 03:21:35 - mmengine - INFO - Epoch(train) [95][1560/2119] lr: 4.0000e-02 eta: 11:16:39 time: 0.3720 data_time: 0.0223 memory: 5826 grad_norm: 3.1582 top1_acc: 0.1250 top5_acc: 0.3125 loss_cls: 3.1034 loss: 3.1034 2022/10/08 03:21:42 - mmengine - INFO - Epoch(train) [95][1580/2119] lr: 4.0000e-02 eta: 11:16:32 time: 0.3463 data_time: 0.0229 memory: 5826 grad_norm: 3.1777 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8052 loss: 2.8052 2022/10/08 03:21:49 - mmengine - INFO - Epoch(train) [95][1600/2119] lr: 4.0000e-02 eta: 11:16:25 time: 0.3368 data_time: 0.0213 memory: 5826 grad_norm: 3.1814 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.7658 loss: 2.7658 2022/10/08 03:21:56 - mmengine - INFO - Epoch(train) [95][1620/2119] lr: 4.0000e-02 eta: 11:16:18 time: 0.3727 data_time: 0.0228 memory: 5826 grad_norm: 3.1178 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7660 loss: 2.7660 2022/10/08 03:22:03 - mmengine - INFO - Epoch(train) [95][1640/2119] lr: 4.0000e-02 eta: 11:16:11 time: 0.3283 data_time: 0.0245 memory: 5826 grad_norm: 3.1181 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.8628 loss: 2.8628 2022/10/08 03:22:10 - mmengine - INFO - Epoch(train) [95][1660/2119] lr: 4.0000e-02 eta: 11:16:04 time: 0.3500 data_time: 0.0212 memory: 5826 grad_norm: 3.1619 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5357 loss: 2.5357 2022/10/08 03:22:17 - mmengine - INFO - Epoch(train) [95][1680/2119] lr: 4.0000e-02 eta: 11:15:57 time: 0.3588 data_time: 0.0265 memory: 5826 grad_norm: 3.1426 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4330 loss: 2.4330 2022/10/08 03:22:23 - mmengine - INFO - Epoch(train) [95][1700/2119] lr: 4.0000e-02 eta: 11:15:50 time: 0.3040 data_time: 0.0264 memory: 5826 grad_norm: 3.1031 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5589 loss: 2.5589 2022/10/08 03:22:31 - mmengine - INFO - Epoch(train) [95][1720/2119] lr: 4.0000e-02 eta: 11:15:44 time: 0.4017 data_time: 0.0255 memory: 5826 grad_norm: 3.1036 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7445 loss: 2.7445 2022/10/08 03:22:38 - mmengine - INFO - Epoch(train) [95][1740/2119] lr: 4.0000e-02 eta: 11:15:37 time: 0.3595 data_time: 0.0240 memory: 5826 grad_norm: 3.1908 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9697 loss: 2.9697 2022/10/08 03:22:45 - mmengine - INFO - Epoch(train) [95][1760/2119] lr: 4.0000e-02 eta: 11:15:30 time: 0.3630 data_time: 0.0237 memory: 5826 grad_norm: 3.1035 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4727 loss: 2.4727 2022/10/08 03:22:52 - mmengine - INFO - Epoch(train) [95][1780/2119] lr: 4.0000e-02 eta: 11:15:23 time: 0.3114 data_time: 0.0261 memory: 5826 grad_norm: 3.1127 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7971 loss: 2.7971 2022/10/08 03:22:59 - mmengine - INFO - Epoch(train) [95][1800/2119] lr: 4.0000e-02 eta: 11:15:16 time: 0.3689 data_time: 0.0228 memory: 5826 grad_norm: 3.1136 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8544 loss: 2.8544 2022/10/08 03:23:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 03:23:05 - mmengine - INFO - Epoch(train) [95][1820/2119] lr: 4.0000e-02 eta: 11:15:09 time: 0.3179 data_time: 0.0297 memory: 5826 grad_norm: 3.0804 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.5694 loss: 2.5694 2022/10/08 03:23:12 - mmengine - INFO - Epoch(train) [95][1840/2119] lr: 4.0000e-02 eta: 11:15:02 time: 0.3536 data_time: 0.0220 memory: 5826 grad_norm: 3.1291 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7536 loss: 2.7536 2022/10/08 03:23:20 - mmengine - INFO - Epoch(train) [95][1860/2119] lr: 4.0000e-02 eta: 11:14:55 time: 0.3685 data_time: 0.0212 memory: 5826 grad_norm: 3.1618 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5900 loss: 2.5900 2022/10/08 03:23:27 - mmengine - INFO - Epoch(train) [95][1880/2119] lr: 4.0000e-02 eta: 11:14:48 time: 0.3490 data_time: 0.0271 memory: 5826 grad_norm: 3.1549 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6963 loss: 2.6963 2022/10/08 03:23:34 - mmengine - INFO - Epoch(train) [95][1900/2119] lr: 4.0000e-02 eta: 11:14:41 time: 0.3467 data_time: 0.0269 memory: 5826 grad_norm: 3.1287 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7635 loss: 2.7635 2022/10/08 03:23:40 - mmengine - INFO - Epoch(train) [95][1920/2119] lr: 4.0000e-02 eta: 11:14:34 time: 0.3081 data_time: 0.0278 memory: 5826 grad_norm: 3.1440 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8783 loss: 2.8783 2022/10/08 03:23:47 - mmengine - INFO - Epoch(train) [95][1940/2119] lr: 4.0000e-02 eta: 11:14:27 time: 0.3378 data_time: 0.0246 memory: 5826 grad_norm: 3.1788 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9061 loss: 2.9061 2022/10/08 03:23:54 - mmengine - INFO - Epoch(train) [95][1960/2119] lr: 4.0000e-02 eta: 11:14:21 time: 0.3894 data_time: 0.0204 memory: 5826 grad_norm: 3.1079 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6790 loss: 2.6790 2022/10/08 03:24:01 - mmengine - INFO - Epoch(train) [95][1980/2119] lr: 4.0000e-02 eta: 11:14:13 time: 0.3094 data_time: 0.0272 memory: 5826 grad_norm: 3.1845 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.8193 loss: 2.8193 2022/10/08 03:24:07 - mmengine - INFO - Epoch(train) [95][2000/2119] lr: 4.0000e-02 eta: 11:14:06 time: 0.3344 data_time: 0.0232 memory: 5826 grad_norm: 3.1334 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6393 loss: 2.6393 2022/10/08 03:24:15 - mmengine - INFO - Epoch(train) [95][2020/2119] lr: 4.0000e-02 eta: 11:13:59 time: 0.3596 data_time: 0.0215 memory: 5826 grad_norm: 3.1419 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6997 loss: 2.6997 2022/10/08 03:24:22 - mmengine - INFO - Epoch(train) [95][2040/2119] lr: 4.0000e-02 eta: 11:13:53 time: 0.3571 data_time: 0.0190 memory: 5826 grad_norm: 3.1008 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6188 loss: 2.6188 2022/10/08 03:24:28 - mmengine - INFO - Epoch(train) [95][2060/2119] lr: 4.0000e-02 eta: 11:13:45 time: 0.3249 data_time: 0.0196 memory: 5826 grad_norm: 3.1439 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.8683 loss: 2.8683 2022/10/08 03:24:36 - mmengine - INFO - Epoch(train) [95][2080/2119] lr: 4.0000e-02 eta: 11:13:39 time: 0.3721 data_time: 0.0230 memory: 5826 grad_norm: 3.0789 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7391 loss: 2.7391 2022/10/08 03:24:42 - mmengine - INFO - Epoch(train) [95][2100/2119] lr: 4.0000e-02 eta: 11:13:31 time: 0.3215 data_time: 0.0269 memory: 5826 grad_norm: 3.1792 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7257 loss: 2.7257 2022/10/08 03:24:48 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 03:24:48 - mmengine - INFO - Epoch(train) [95][2119/2119] lr: 4.0000e-02 eta: 11:13:31 time: 0.2918 data_time: 0.0210 memory: 5826 grad_norm: 3.1977 top1_acc: 0.1000 top5_acc: 0.2000 loss_cls: 2.7932 loss: 2.7932 2022/10/08 03:24:56 - mmengine - INFO - Epoch(val) [95][20/137] eta: 0:00:50 time: 0.4357 data_time: 0.3621 memory: 1241 2022/10/08 03:25:02 - mmengine - INFO - Epoch(val) [95][40/137] eta: 0:00:26 time: 0.2774 data_time: 0.2097 memory: 1241 2022/10/08 03:25:09 - mmengine - INFO - Epoch(val) [95][60/137] eta: 0:00:26 time: 0.3457 data_time: 0.2748 memory: 1241 2022/10/08 03:25:15 - mmengine - INFO - Epoch(val) [95][80/137] eta: 0:00:16 time: 0.2961 data_time: 0.2289 memory: 1241 2022/10/08 03:25:22 - mmengine - INFO - Epoch(val) [95][100/137] eta: 0:00:13 time: 0.3554 data_time: 0.2893 memory: 1241 2022/10/08 03:25:28 - mmengine - INFO - Epoch(val) [95][120/137] eta: 0:00:04 time: 0.2791 data_time: 0.2137 memory: 1241 2022/10/08 03:25:39 - mmengine - INFO - Epoch(val) [95][137/137] acc/top1: 0.4176 acc/top5: 0.6602 acc/mean1: 0.4175 2022/10/08 03:25:50 - mmengine - INFO - Epoch(train) [96][20/2119] lr: 4.0000e-02 eta: 11:13:16 time: 0.5253 data_time: 0.1523 memory: 5826 grad_norm: 3.1395 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6978 loss: 2.6978 2022/10/08 03:25:56 - mmengine - INFO - Epoch(train) [96][40/2119] lr: 4.0000e-02 eta: 11:13:09 time: 0.3180 data_time: 0.0231 memory: 5826 grad_norm: 3.1619 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4930 loss: 2.4930 2022/10/08 03:26:03 - mmengine - INFO - Epoch(train) [96][60/2119] lr: 4.0000e-02 eta: 11:13:02 time: 0.3563 data_time: 0.0223 memory: 5826 grad_norm: 3.1015 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2765 loss: 2.2765 2022/10/08 03:26:10 - mmengine - INFO - Epoch(train) [96][80/2119] lr: 4.0000e-02 eta: 11:12:55 time: 0.3163 data_time: 0.0235 memory: 5826 grad_norm: 3.0809 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7853 loss: 2.7853 2022/10/08 03:26:17 - mmengine - INFO - Epoch(train) [96][100/2119] lr: 4.0000e-02 eta: 11:12:48 time: 0.3784 data_time: 0.0257 memory: 5826 grad_norm: 3.1516 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.5997 loss: 2.5997 2022/10/08 03:26:24 - mmengine - INFO - Epoch(train) [96][120/2119] lr: 4.0000e-02 eta: 11:12:41 time: 0.3550 data_time: 0.0241 memory: 5826 grad_norm: 3.1279 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6154 loss: 2.6154 2022/10/08 03:26:31 - mmengine - INFO - Epoch(train) [96][140/2119] lr: 4.0000e-02 eta: 11:12:35 time: 0.3534 data_time: 0.0240 memory: 5826 grad_norm: 3.1616 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9011 loss: 2.9011 2022/10/08 03:26:39 - mmengine - INFO - Epoch(train) [96][160/2119] lr: 4.0000e-02 eta: 11:12:28 time: 0.3532 data_time: 0.0233 memory: 5826 grad_norm: 3.1592 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5630 loss: 2.5630 2022/10/08 03:26:46 - mmengine - INFO - Epoch(train) [96][180/2119] lr: 4.0000e-02 eta: 11:12:21 time: 0.3628 data_time: 0.0191 memory: 5826 grad_norm: 3.1815 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.8822 loss: 2.8822 2022/10/08 03:26:52 - mmengine - INFO - Epoch(train) [96][200/2119] lr: 4.0000e-02 eta: 11:12:14 time: 0.3049 data_time: 0.0251 memory: 5826 grad_norm: 3.1304 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6195 loss: 2.6195 2022/10/08 03:27:00 - mmengine - INFO - Epoch(train) [96][220/2119] lr: 4.0000e-02 eta: 11:12:07 time: 0.3784 data_time: 0.0225 memory: 5826 grad_norm: 3.1027 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7131 loss: 2.7131 2022/10/08 03:27:06 - mmengine - INFO - Epoch(train) [96][240/2119] lr: 4.0000e-02 eta: 11:12:00 time: 0.3377 data_time: 0.0243 memory: 5826 grad_norm: 3.1100 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5739 loss: 2.5739 2022/10/08 03:27:14 - mmengine - INFO - Epoch(train) [96][260/2119] lr: 4.0000e-02 eta: 11:11:53 time: 0.3730 data_time: 0.0242 memory: 5826 grad_norm: 3.1379 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6380 loss: 2.6380 2022/10/08 03:27:20 - mmengine - INFO - Epoch(train) [96][280/2119] lr: 4.0000e-02 eta: 11:11:46 time: 0.3323 data_time: 0.0396 memory: 5826 grad_norm: 3.1256 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6854 loss: 2.6854 2022/10/08 03:27:28 - mmengine - INFO - Epoch(train) [96][300/2119] lr: 4.0000e-02 eta: 11:11:40 time: 0.3656 data_time: 0.0188 memory: 5826 grad_norm: 3.1253 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6810 loss: 2.6810 2022/10/08 03:27:34 - mmengine - INFO - Epoch(train) [96][320/2119] lr: 4.0000e-02 eta: 11:11:32 time: 0.3357 data_time: 0.0228 memory: 5826 grad_norm: 3.0800 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7873 loss: 2.7873 2022/10/08 03:27:42 - mmengine - INFO - Epoch(train) [96][340/2119] lr: 4.0000e-02 eta: 11:11:26 time: 0.3563 data_time: 0.0225 memory: 5826 grad_norm: 3.1492 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.7437 loss: 2.7437 2022/10/08 03:27:48 - mmengine - INFO - Epoch(train) [96][360/2119] lr: 4.0000e-02 eta: 11:11:18 time: 0.3225 data_time: 0.0219 memory: 5826 grad_norm: 3.1082 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7965 loss: 2.7965 2022/10/08 03:27:56 - mmengine - INFO - Epoch(train) [96][380/2119] lr: 4.0000e-02 eta: 11:11:12 time: 0.3798 data_time: 0.0216 memory: 5826 grad_norm: 3.1461 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7649 loss: 2.7649 2022/10/08 03:28:02 - mmengine - INFO - Epoch(train) [96][400/2119] lr: 4.0000e-02 eta: 11:11:05 time: 0.3227 data_time: 0.0226 memory: 5826 grad_norm: 3.1055 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6462 loss: 2.6462 2022/10/08 03:28:09 - mmengine - INFO - Epoch(train) [96][420/2119] lr: 4.0000e-02 eta: 11:10:58 time: 0.3518 data_time: 0.0243 memory: 5826 grad_norm: 3.1351 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5643 loss: 2.5643 2022/10/08 03:28:15 - mmengine - INFO - Epoch(train) [96][440/2119] lr: 4.0000e-02 eta: 11:10:50 time: 0.3136 data_time: 0.0232 memory: 5826 grad_norm: 3.1062 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7401 loss: 2.7401 2022/10/08 03:28:23 - mmengine - INFO - Epoch(train) [96][460/2119] lr: 4.0000e-02 eta: 11:10:44 time: 0.3689 data_time: 0.0269 memory: 5826 grad_norm: 3.1327 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.6258 loss: 2.6258 2022/10/08 03:28:29 - mmengine - INFO - Epoch(train) [96][480/2119] lr: 4.0000e-02 eta: 11:10:37 time: 0.3253 data_time: 0.0212 memory: 5826 grad_norm: 3.1308 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8327 loss: 2.8327 2022/10/08 03:28:37 - mmengine - INFO - Epoch(train) [96][500/2119] lr: 4.0000e-02 eta: 11:10:30 time: 0.3627 data_time: 0.0238 memory: 5826 grad_norm: 3.1493 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4880 loss: 2.4880 2022/10/08 03:28:43 - mmengine - INFO - Epoch(train) [96][520/2119] lr: 4.0000e-02 eta: 11:10:23 time: 0.3161 data_time: 0.0251 memory: 5826 grad_norm: 3.1578 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6931 loss: 2.6931 2022/10/08 03:28:50 - mmengine - INFO - Epoch(train) [96][540/2119] lr: 4.0000e-02 eta: 11:10:16 time: 0.3378 data_time: 0.0237 memory: 5826 grad_norm: 3.2081 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7999 loss: 2.7999 2022/10/08 03:28:57 - mmengine - INFO - Epoch(train) [96][560/2119] lr: 4.0000e-02 eta: 11:10:09 time: 0.3865 data_time: 0.0217 memory: 5826 grad_norm: 3.1426 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7838 loss: 2.7838 2022/10/08 03:29:04 - mmengine - INFO - Epoch(train) [96][580/2119] lr: 4.0000e-02 eta: 11:10:02 time: 0.3125 data_time: 0.0285 memory: 5826 grad_norm: 3.1248 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8001 loss: 2.8001 2022/10/08 03:29:11 - mmengine - INFO - Epoch(train) [96][600/2119] lr: 4.0000e-02 eta: 11:09:55 time: 0.3788 data_time: 0.0210 memory: 5826 grad_norm: 3.1358 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5970 loss: 2.5970 2022/10/08 03:29:18 - mmengine - INFO - Epoch(train) [96][620/2119] lr: 4.0000e-02 eta: 11:09:48 time: 0.3282 data_time: 0.0207 memory: 5826 grad_norm: 3.1718 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6842 loss: 2.6842 2022/10/08 03:29:25 - mmengine - INFO - Epoch(train) [96][640/2119] lr: 4.0000e-02 eta: 11:09:41 time: 0.3764 data_time: 0.0234 memory: 5826 grad_norm: 3.1419 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7586 loss: 2.7586 2022/10/08 03:29:32 - mmengine - INFO - Epoch(train) [96][660/2119] lr: 4.0000e-02 eta: 11:09:34 time: 0.3364 data_time: 0.0252 memory: 5826 grad_norm: 3.1170 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7525 loss: 2.7525 2022/10/08 03:29:40 - mmengine - INFO - Epoch(train) [96][680/2119] lr: 4.0000e-02 eta: 11:09:28 time: 0.3900 data_time: 0.0261 memory: 5826 grad_norm: 3.1544 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7254 loss: 2.7254 2022/10/08 03:29:45 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 03:29:46 - mmengine - INFO - Epoch(train) [96][700/2119] lr: 4.0000e-02 eta: 11:09:21 time: 0.3101 data_time: 0.0243 memory: 5826 grad_norm: 3.0770 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6754 loss: 2.6754 2022/10/08 03:29:53 - mmengine - INFO - Epoch(train) [96][720/2119] lr: 4.0000e-02 eta: 11:09:14 time: 0.3582 data_time: 0.0231 memory: 5826 grad_norm: 3.1229 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7875 loss: 2.7875 2022/10/08 03:30:00 - mmengine - INFO - Epoch(train) [96][740/2119] lr: 4.0000e-02 eta: 11:09:07 time: 0.3172 data_time: 0.0236 memory: 5826 grad_norm: 3.1072 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8200 loss: 2.8200 2022/10/08 03:30:07 - mmengine - INFO - Epoch(train) [96][760/2119] lr: 4.0000e-02 eta: 11:09:00 time: 0.3834 data_time: 0.0239 memory: 5826 grad_norm: 3.1258 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7238 loss: 2.7238 2022/10/08 03:30:14 - mmengine - INFO - Epoch(train) [96][780/2119] lr: 4.0000e-02 eta: 11:08:53 time: 0.3577 data_time: 0.0209 memory: 5826 grad_norm: 3.1281 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5919 loss: 2.5919 2022/10/08 03:30:21 - mmengine - INFO - Epoch(train) [96][800/2119] lr: 4.0000e-02 eta: 11:08:46 time: 0.3511 data_time: 0.0221 memory: 5826 grad_norm: 3.1641 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8149 loss: 2.8149 2022/10/08 03:30:28 - mmengine - INFO - Epoch(train) [96][820/2119] lr: 4.0000e-02 eta: 11:08:39 time: 0.3347 data_time: 0.0233 memory: 5826 grad_norm: 3.1920 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7344 loss: 2.7344 2022/10/08 03:30:36 - mmengine - INFO - Epoch(train) [96][840/2119] lr: 4.0000e-02 eta: 11:08:33 time: 0.4096 data_time: 0.0268 memory: 5826 grad_norm: 3.1557 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6921 loss: 2.6921 2022/10/08 03:30:43 - mmengine - INFO - Epoch(train) [96][860/2119] lr: 4.0000e-02 eta: 11:08:26 time: 0.3204 data_time: 0.0216 memory: 5826 grad_norm: 3.1062 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6822 loss: 2.6822 2022/10/08 03:30:50 - mmengine - INFO - Epoch(train) [96][880/2119] lr: 4.0000e-02 eta: 11:08:19 time: 0.3558 data_time: 0.0205 memory: 5826 grad_norm: 3.1786 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7839 loss: 2.7839 2022/10/08 03:30:57 - mmengine - INFO - Epoch(train) [96][900/2119] lr: 4.0000e-02 eta: 11:08:12 time: 0.3513 data_time: 0.0237 memory: 5826 grad_norm: 3.0889 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5270 loss: 2.5270 2022/10/08 03:31:04 - mmengine - INFO - Epoch(train) [96][920/2119] lr: 4.0000e-02 eta: 11:08:05 time: 0.3340 data_time: 0.0266 memory: 5826 grad_norm: 3.0880 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5762 loss: 2.5762 2022/10/08 03:31:10 - mmengine - INFO - Epoch(train) [96][940/2119] lr: 4.0000e-02 eta: 11:07:58 time: 0.3331 data_time: 0.0278 memory: 5826 grad_norm: 3.1484 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.9016 loss: 2.9016 2022/10/08 03:31:18 - mmengine - INFO - Epoch(train) [96][960/2119] lr: 4.0000e-02 eta: 11:07:52 time: 0.3966 data_time: 0.0253 memory: 5826 grad_norm: 3.0984 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.5551 loss: 2.5551 2022/10/08 03:31:25 - mmengine - INFO - Epoch(train) [96][980/2119] lr: 4.0000e-02 eta: 11:07:44 time: 0.3170 data_time: 0.0199 memory: 5826 grad_norm: 3.0970 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5658 loss: 2.5658 2022/10/08 03:31:31 - mmengine - INFO - Epoch(train) [96][1000/2119] lr: 4.0000e-02 eta: 11:07:37 time: 0.3404 data_time: 0.0244 memory: 5826 grad_norm: 3.1273 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4266 loss: 2.4266 2022/10/08 03:31:39 - mmengine - INFO - Epoch(train) [96][1020/2119] lr: 4.0000e-02 eta: 11:07:31 time: 0.3783 data_time: 0.0275 memory: 5826 grad_norm: 3.0797 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6990 loss: 2.6990 2022/10/08 03:31:45 - mmengine - INFO - Epoch(train) [96][1040/2119] lr: 4.0000e-02 eta: 11:07:23 time: 0.3171 data_time: 0.0286 memory: 5826 grad_norm: 3.0788 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.5376 loss: 2.5376 2022/10/08 03:31:53 - mmengine - INFO - Epoch(train) [96][1060/2119] lr: 4.0000e-02 eta: 11:07:17 time: 0.3593 data_time: 0.0217 memory: 5826 grad_norm: 3.1348 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6671 loss: 2.6671 2022/10/08 03:32:00 - mmengine - INFO - Epoch(train) [96][1080/2119] lr: 4.0000e-02 eta: 11:07:10 time: 0.3636 data_time: 0.0285 memory: 5826 grad_norm: 3.1582 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.7780 loss: 2.7780 2022/10/08 03:32:07 - mmengine - INFO - Epoch(train) [96][1100/2119] lr: 4.0000e-02 eta: 11:07:03 time: 0.3787 data_time: 0.0252 memory: 5826 grad_norm: 3.1836 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7549 loss: 2.7549 2022/10/08 03:32:14 - mmengine - INFO - Epoch(train) [96][1120/2119] lr: 4.0000e-02 eta: 11:06:56 time: 0.3372 data_time: 0.0223 memory: 5826 grad_norm: 3.1394 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4193 loss: 2.4193 2022/10/08 03:32:21 - mmengine - INFO - Epoch(train) [96][1140/2119] lr: 4.0000e-02 eta: 11:06:49 time: 0.3246 data_time: 0.0221 memory: 5826 grad_norm: 3.1962 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6756 loss: 2.6756 2022/10/08 03:32:29 - mmengine - INFO - Epoch(train) [96][1160/2119] lr: 4.0000e-02 eta: 11:06:43 time: 0.4013 data_time: 0.0248 memory: 5826 grad_norm: 3.1599 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5725 loss: 2.5725 2022/10/08 03:32:35 - mmengine - INFO - Epoch(train) [96][1180/2119] lr: 4.0000e-02 eta: 11:06:36 time: 0.3158 data_time: 0.0226 memory: 5826 grad_norm: 3.1668 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9185 loss: 2.9185 2022/10/08 03:32:42 - mmengine - INFO - Epoch(train) [96][1200/2119] lr: 4.0000e-02 eta: 11:06:29 time: 0.3626 data_time: 0.0221 memory: 5826 grad_norm: 3.0903 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5124 loss: 2.5124 2022/10/08 03:32:48 - mmengine - INFO - Epoch(train) [96][1220/2119] lr: 4.0000e-02 eta: 11:06:21 time: 0.2941 data_time: 0.0294 memory: 5826 grad_norm: 3.1741 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7416 loss: 2.7416 2022/10/08 03:32:56 - mmengine - INFO - Epoch(train) [96][1240/2119] lr: 4.0000e-02 eta: 11:06:15 time: 0.3900 data_time: 0.0204 memory: 5826 grad_norm: 3.1327 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6926 loss: 2.6926 2022/10/08 03:33:02 - mmengine - INFO - Epoch(train) [96][1260/2119] lr: 4.0000e-02 eta: 11:06:08 time: 0.3187 data_time: 0.0231 memory: 5826 grad_norm: 3.1212 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7851 loss: 2.7851 2022/10/08 03:33:10 - mmengine - INFO - Epoch(train) [96][1280/2119] lr: 4.0000e-02 eta: 11:06:01 time: 0.3773 data_time: 0.0264 memory: 5826 grad_norm: 3.1792 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.7773 loss: 2.7773 2022/10/08 03:33:16 - mmengine - INFO - Epoch(train) [96][1300/2119] lr: 4.0000e-02 eta: 11:05:54 time: 0.3297 data_time: 0.0218 memory: 5826 grad_norm: 3.1125 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8221 loss: 2.8221 2022/10/08 03:33:24 - mmengine - INFO - Epoch(train) [96][1320/2119] lr: 4.0000e-02 eta: 11:05:47 time: 0.3744 data_time: 0.0249 memory: 5826 grad_norm: 3.1169 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6613 loss: 2.6613 2022/10/08 03:33:31 - mmengine - INFO - Epoch(train) [96][1340/2119] lr: 4.0000e-02 eta: 11:05:40 time: 0.3405 data_time: 0.0256 memory: 5826 grad_norm: 3.1578 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6416 loss: 2.6416 2022/10/08 03:33:38 - mmengine - INFO - Epoch(train) [96][1360/2119] lr: 4.0000e-02 eta: 11:05:33 time: 0.3623 data_time: 0.0216 memory: 5826 grad_norm: 3.1872 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5758 loss: 2.5758 2022/10/08 03:33:44 - mmengine - INFO - Epoch(train) [96][1380/2119] lr: 4.0000e-02 eta: 11:05:26 time: 0.3163 data_time: 0.0208 memory: 5826 grad_norm: 3.1948 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5804 loss: 2.5804 2022/10/08 03:33:52 - mmengine - INFO - Epoch(train) [96][1400/2119] lr: 4.0000e-02 eta: 11:05:19 time: 0.3606 data_time: 0.0299 memory: 5826 grad_norm: 3.1141 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.8752 loss: 2.8752 2022/10/08 03:33:59 - mmengine - INFO - Epoch(train) [96][1420/2119] lr: 4.0000e-02 eta: 11:05:13 time: 0.3564 data_time: 0.0201 memory: 5826 grad_norm: 3.1304 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6942 loss: 2.6942 2022/10/08 03:34:06 - mmengine - INFO - Epoch(train) [96][1440/2119] lr: 4.0000e-02 eta: 11:05:06 time: 0.3583 data_time: 0.0236 memory: 5826 grad_norm: 3.1697 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5853 loss: 2.5853 2022/10/08 03:34:12 - mmengine - INFO - Epoch(train) [96][1460/2119] lr: 4.0000e-02 eta: 11:04:58 time: 0.2991 data_time: 0.0265 memory: 5826 grad_norm: 3.1284 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6077 loss: 2.6077 2022/10/08 03:34:19 - mmengine - INFO - Epoch(train) [96][1480/2119] lr: 4.0000e-02 eta: 11:04:51 time: 0.3536 data_time: 0.0236 memory: 5826 grad_norm: 3.0982 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7981 loss: 2.7981 2022/10/08 03:34:26 - mmengine - INFO - Epoch(train) [96][1500/2119] lr: 4.0000e-02 eta: 11:04:45 time: 0.3683 data_time: 0.0211 memory: 5826 grad_norm: 3.1577 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6878 loss: 2.6878 2022/10/08 03:34:33 - mmengine - INFO - Epoch(train) [96][1520/2119] lr: 4.0000e-02 eta: 11:04:38 time: 0.3466 data_time: 0.0223 memory: 5826 grad_norm: 3.0889 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.9286 loss: 2.9286 2022/10/08 03:34:40 - mmengine - INFO - Epoch(train) [96][1540/2119] lr: 4.0000e-02 eta: 11:04:31 time: 0.3496 data_time: 0.0280 memory: 5826 grad_norm: 3.0722 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8363 loss: 2.8363 2022/10/08 03:34:47 - mmengine - INFO - Epoch(train) [96][1560/2119] lr: 4.0000e-02 eta: 11:04:24 time: 0.3476 data_time: 0.0189 memory: 5826 grad_norm: 3.1899 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8144 loss: 2.8144 2022/10/08 03:34:55 - mmengine - INFO - Epoch(train) [96][1580/2119] lr: 4.0000e-02 eta: 11:04:18 time: 0.3862 data_time: 0.0317 memory: 5826 grad_norm: 3.1109 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8019 loss: 2.8019 2022/10/08 03:35:02 - mmengine - INFO - Epoch(train) [96][1600/2119] lr: 4.0000e-02 eta: 11:04:10 time: 0.3334 data_time: 0.0247 memory: 5826 grad_norm: 3.1569 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.7376 loss: 2.7376 2022/10/08 03:35:09 - mmengine - INFO - Epoch(train) [96][1620/2119] lr: 4.0000e-02 eta: 11:04:04 time: 0.3554 data_time: 0.0238 memory: 5826 grad_norm: 3.1549 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5195 loss: 2.5195 2022/10/08 03:35:17 - mmengine - INFO - Epoch(train) [96][1640/2119] lr: 4.0000e-02 eta: 11:03:57 time: 0.4188 data_time: 0.0235 memory: 5826 grad_norm: 3.1191 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9139 loss: 2.9139 2022/10/08 03:35:23 - mmengine - INFO - Epoch(train) [96][1660/2119] lr: 4.0000e-02 eta: 11:03:50 time: 0.2835 data_time: 0.0189 memory: 5826 grad_norm: 3.1317 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.1522 loss: 3.1522 2022/10/08 03:35:30 - mmengine - INFO - Epoch(train) [96][1680/2119] lr: 4.0000e-02 eta: 11:03:43 time: 0.3436 data_time: 0.0289 memory: 5826 grad_norm: 3.1646 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6778 loss: 2.6778 2022/10/08 03:35:34 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 03:35:37 - mmengine - INFO - Epoch(train) [96][1700/2119] lr: 4.0000e-02 eta: 11:03:36 time: 0.3610 data_time: 0.0244 memory: 5826 grad_norm: 3.2429 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.9580 loss: 2.9580 2022/10/08 03:35:44 - mmengine - INFO - Epoch(train) [96][1720/2119] lr: 4.0000e-02 eta: 11:03:29 time: 0.3442 data_time: 0.0236 memory: 5826 grad_norm: 3.1324 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4737 loss: 2.4737 2022/10/08 03:35:51 - mmengine - INFO - Epoch(train) [96][1740/2119] lr: 4.0000e-02 eta: 11:03:22 time: 0.3661 data_time: 0.0205 memory: 5826 grad_norm: 3.1945 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6494 loss: 2.6494 2022/10/08 03:35:59 - mmengine - INFO - Epoch(train) [96][1760/2119] lr: 4.0000e-02 eta: 11:03:16 time: 0.3923 data_time: 0.0223 memory: 5826 grad_norm: 3.1774 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6514 loss: 2.6514 2022/10/08 03:36:05 - mmengine - INFO - Epoch(train) [96][1780/2119] lr: 4.0000e-02 eta: 11:03:09 time: 0.3088 data_time: 0.0226 memory: 5826 grad_norm: 3.1832 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.8264 loss: 2.8264 2022/10/08 03:36:13 - mmengine - INFO - Epoch(train) [96][1800/2119] lr: 4.0000e-02 eta: 11:03:02 time: 0.3769 data_time: 0.0215 memory: 5826 grad_norm: 3.1061 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.9220 loss: 2.9220 2022/10/08 03:36:20 - mmengine - INFO - Epoch(train) [96][1820/2119] lr: 4.0000e-02 eta: 11:02:55 time: 0.3704 data_time: 0.0259 memory: 5826 grad_norm: 3.1173 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0528 loss: 3.0528 2022/10/08 03:36:27 - mmengine - INFO - Epoch(train) [96][1840/2119] lr: 4.0000e-02 eta: 11:02:48 time: 0.3392 data_time: 0.0245 memory: 5826 grad_norm: 3.1178 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.8038 loss: 2.8038 2022/10/08 03:36:33 - mmengine - INFO - Epoch(train) [96][1860/2119] lr: 4.0000e-02 eta: 11:02:41 time: 0.3209 data_time: 0.0261 memory: 5826 grad_norm: 3.1110 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6322 loss: 2.6322 2022/10/08 03:36:41 - mmengine - INFO - Epoch(train) [96][1880/2119] lr: 4.0000e-02 eta: 11:02:34 time: 0.3737 data_time: 0.0235 memory: 5826 grad_norm: 3.1340 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6739 loss: 2.6739 2022/10/08 03:36:48 - mmengine - INFO - Epoch(train) [96][1900/2119] lr: 4.0000e-02 eta: 11:02:28 time: 0.3440 data_time: 0.0213 memory: 5826 grad_norm: 3.1439 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7309 loss: 2.7309 2022/10/08 03:36:55 - mmengine - INFO - Epoch(train) [96][1920/2119] lr: 4.0000e-02 eta: 11:02:21 time: 0.3454 data_time: 0.0217 memory: 5826 grad_norm: 3.1487 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7950 loss: 2.7950 2022/10/08 03:37:02 - mmengine - INFO - Epoch(train) [96][1940/2119] lr: 4.0000e-02 eta: 11:02:14 time: 0.3555 data_time: 0.0219 memory: 5826 grad_norm: 3.1149 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4749 loss: 2.4749 2022/10/08 03:37:09 - mmengine - INFO - Epoch(train) [96][1960/2119] lr: 4.0000e-02 eta: 11:02:07 time: 0.3602 data_time: 0.0215 memory: 5826 grad_norm: 3.1511 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.5368 loss: 2.5368 2022/10/08 03:37:15 - mmengine - INFO - Epoch(train) [96][1980/2119] lr: 4.0000e-02 eta: 11:02:00 time: 0.3136 data_time: 0.0206 memory: 5826 grad_norm: 3.1420 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.8936 loss: 2.8936 2022/10/08 03:37:23 - mmengine - INFO - Epoch(train) [96][2000/2119] lr: 4.0000e-02 eta: 11:01:53 time: 0.3899 data_time: 0.0244 memory: 5826 grad_norm: 3.0963 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7155 loss: 2.7155 2022/10/08 03:37:29 - mmengine - INFO - Epoch(train) [96][2020/2119] lr: 4.0000e-02 eta: 11:01:46 time: 0.3128 data_time: 0.0268 memory: 5826 grad_norm: 3.1020 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8146 loss: 2.8146 2022/10/08 03:37:38 - mmengine - INFO - Epoch(train) [96][2040/2119] lr: 4.0000e-02 eta: 11:01:40 time: 0.4236 data_time: 0.0249 memory: 5826 grad_norm: 3.1496 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7729 loss: 2.7729 2022/10/08 03:37:43 - mmengine - INFO - Epoch(train) [96][2060/2119] lr: 4.0000e-02 eta: 11:01:32 time: 0.2837 data_time: 0.0248 memory: 5826 grad_norm: 3.1549 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6147 loss: 2.6147 2022/10/08 03:37:51 - mmengine - INFO - Epoch(train) [96][2080/2119] lr: 4.0000e-02 eta: 11:01:25 time: 0.3568 data_time: 0.0246 memory: 5826 grad_norm: 3.0773 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5578 loss: 2.5578 2022/10/08 03:37:58 - mmengine - INFO - Epoch(train) [96][2100/2119] lr: 4.0000e-02 eta: 11:01:19 time: 0.3582 data_time: 0.0220 memory: 5826 grad_norm: 3.1576 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8140 loss: 2.8140 2022/10/08 03:38:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 03:38:04 - mmengine - INFO - Epoch(train) [96][2119/2119] lr: 4.0000e-02 eta: 11:01:19 time: 0.3189 data_time: 0.0190 memory: 5826 grad_norm: 3.1788 top1_acc: 0.4000 top5_acc: 0.5000 loss_cls: 2.5847 loss: 2.5847 2022/10/08 03:38:04 - mmengine - INFO - Saving checkpoint at 96 epochs 2022/10/08 03:38:26 - mmengine - INFO - Epoch(train) [97][20/2119] lr: 4.0000e-02 eta: 11:01:03 time: 0.4598 data_time: 0.2093 memory: 5826 grad_norm: 3.1397 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.4826 loss: 2.4826 2022/10/08 03:38:31 - mmengine - INFO - Epoch(train) [97][40/2119] lr: 4.0000e-02 eta: 11:00:55 time: 0.2827 data_time: 0.0533 memory: 5826 grad_norm: 3.1285 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6965 loss: 2.6965 2022/10/08 03:38:39 - mmengine - INFO - Epoch(train) [97][60/2119] lr: 4.0000e-02 eta: 11:00:48 time: 0.3644 data_time: 0.1022 memory: 5826 grad_norm: 3.0660 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.8277 loss: 2.8277 2022/10/08 03:38:45 - mmengine - INFO - Epoch(train) [97][80/2119] lr: 4.0000e-02 eta: 11:00:41 time: 0.3290 data_time: 0.0598 memory: 5826 grad_norm: 3.1368 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7757 loss: 2.7757 2022/10/08 03:38:53 - mmengine - INFO - Epoch(train) [97][100/2119] lr: 4.0000e-02 eta: 11:00:35 time: 0.3797 data_time: 0.0186 memory: 5826 grad_norm: 3.0900 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6950 loss: 2.6950 2022/10/08 03:38:59 - mmengine - INFO - Epoch(train) [97][120/2119] lr: 4.0000e-02 eta: 11:00:27 time: 0.3252 data_time: 0.0379 memory: 5826 grad_norm: 3.1672 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7889 loss: 2.7889 2022/10/08 03:39:07 - mmengine - INFO - Epoch(train) [97][140/2119] lr: 4.0000e-02 eta: 11:00:21 time: 0.3617 data_time: 0.0265 memory: 5826 grad_norm: 3.0936 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6316 loss: 2.6316 2022/10/08 03:39:13 - mmengine - INFO - Epoch(train) [97][160/2119] lr: 4.0000e-02 eta: 11:00:13 time: 0.3097 data_time: 0.0231 memory: 5826 grad_norm: 3.1130 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9625 loss: 2.9625 2022/10/08 03:39:20 - mmengine - INFO - Epoch(train) [97][180/2119] lr: 4.0000e-02 eta: 11:00:07 time: 0.3676 data_time: 0.0209 memory: 5826 grad_norm: 3.0909 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.4586 loss: 2.4586 2022/10/08 03:39:27 - mmengine - INFO - Epoch(train) [97][200/2119] lr: 4.0000e-02 eta: 11:00:00 time: 0.3534 data_time: 0.0255 memory: 5826 grad_norm: 3.1389 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7319 loss: 2.7319 2022/10/08 03:39:35 - mmengine - INFO - Epoch(train) [97][220/2119] lr: 4.0000e-02 eta: 10:59:53 time: 0.3839 data_time: 0.0295 memory: 5826 grad_norm: 3.1398 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8372 loss: 2.8372 2022/10/08 03:39:42 - mmengine - INFO - Epoch(train) [97][240/2119] lr: 4.0000e-02 eta: 10:59:46 time: 0.3389 data_time: 0.0213 memory: 5826 grad_norm: 3.1229 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7488 loss: 2.7488 2022/10/08 03:39:49 - mmengine - INFO - Epoch(train) [97][260/2119] lr: 4.0000e-02 eta: 10:59:40 time: 0.3746 data_time: 0.0225 memory: 5826 grad_norm: 3.0710 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5233 loss: 2.5233 2022/10/08 03:39:57 - mmengine - INFO - Epoch(train) [97][280/2119] lr: 4.0000e-02 eta: 10:59:33 time: 0.3966 data_time: 0.0236 memory: 5826 grad_norm: 3.1472 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5721 loss: 2.5721 2022/10/08 03:40:03 - mmengine - INFO - Epoch(train) [97][300/2119] lr: 4.0000e-02 eta: 10:59:26 time: 0.3004 data_time: 0.0286 memory: 5826 grad_norm: 3.1894 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6560 loss: 2.6560 2022/10/08 03:40:10 - mmengine - INFO - Epoch(train) [97][320/2119] lr: 4.0000e-02 eta: 10:59:19 time: 0.3587 data_time: 0.0198 memory: 5826 grad_norm: 3.1265 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6716 loss: 2.6716 2022/10/08 03:40:18 - mmengine - INFO - Epoch(train) [97][340/2119] lr: 4.0000e-02 eta: 10:59:12 time: 0.3630 data_time: 0.0244 memory: 5826 grad_norm: 3.1217 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7996 loss: 2.7996 2022/10/08 03:40:24 - mmengine - INFO - Epoch(train) [97][360/2119] lr: 4.0000e-02 eta: 10:59:05 time: 0.3156 data_time: 0.0203 memory: 5826 grad_norm: 3.1595 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6798 loss: 2.6798 2022/10/08 03:40:32 - mmengine - INFO - Epoch(train) [97][380/2119] lr: 4.0000e-02 eta: 10:58:58 time: 0.3882 data_time: 0.0209 memory: 5826 grad_norm: 3.1400 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6595 loss: 2.6595 2022/10/08 03:40:38 - mmengine - INFO - Epoch(train) [97][400/2119] lr: 4.0000e-02 eta: 10:58:51 time: 0.3402 data_time: 0.0189 memory: 5826 grad_norm: 3.0621 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6225 loss: 2.6225 2022/10/08 03:40:46 - mmengine - INFO - Epoch(train) [97][420/2119] lr: 4.0000e-02 eta: 10:58:45 time: 0.3839 data_time: 0.0252 memory: 5826 grad_norm: 3.1317 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6398 loss: 2.6398 2022/10/08 03:40:53 - mmengine - INFO - Epoch(train) [97][440/2119] lr: 4.0000e-02 eta: 10:58:38 time: 0.3547 data_time: 0.0196 memory: 5826 grad_norm: 3.1698 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6982 loss: 2.6982 2022/10/08 03:41:02 - mmengine - INFO - Epoch(train) [97][460/2119] lr: 4.0000e-02 eta: 10:58:32 time: 0.4123 data_time: 0.0292 memory: 5826 grad_norm: 3.1279 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6337 loss: 2.6337 2022/10/08 03:41:08 - mmengine - INFO - Epoch(train) [97][480/2119] lr: 4.0000e-02 eta: 10:58:25 time: 0.3208 data_time: 0.0243 memory: 5826 grad_norm: 3.1262 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8612 loss: 2.8612 2022/10/08 03:41:15 - mmengine - INFO - Epoch(train) [97][500/2119] lr: 4.0000e-02 eta: 10:58:18 time: 0.3510 data_time: 0.0233 memory: 5826 grad_norm: 3.1233 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6068 loss: 2.6068 2022/10/08 03:41:22 - mmengine - INFO - Epoch(train) [97][520/2119] lr: 4.0000e-02 eta: 10:58:11 time: 0.3434 data_time: 0.0322 memory: 5826 grad_norm: 3.1303 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7457 loss: 2.7457 2022/10/08 03:41:30 - mmengine - INFO - Epoch(train) [97][540/2119] lr: 4.0000e-02 eta: 10:58:04 time: 0.3868 data_time: 0.0229 memory: 5826 grad_norm: 3.1314 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6573 loss: 2.6573 2022/10/08 03:41:36 - mmengine - INFO - Epoch(train) [97][560/2119] lr: 4.0000e-02 eta: 10:57:57 time: 0.3071 data_time: 0.0203 memory: 5826 grad_norm: 3.1502 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6425 loss: 2.6425 2022/10/08 03:41:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 03:41:44 - mmengine - INFO - Epoch(train) [97][580/2119] lr: 4.0000e-02 eta: 10:57:51 time: 0.4175 data_time: 0.0221 memory: 5826 grad_norm: 3.1572 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7133 loss: 2.7133 2022/10/08 03:41:50 - mmengine - INFO - Epoch(train) [97][600/2119] lr: 4.0000e-02 eta: 10:57:43 time: 0.3182 data_time: 0.0215 memory: 5826 grad_norm: 3.1745 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7613 loss: 2.7613 2022/10/08 03:41:58 - mmengine - INFO - Epoch(train) [97][620/2119] lr: 4.0000e-02 eta: 10:57:37 time: 0.3898 data_time: 0.0254 memory: 5826 grad_norm: 3.1572 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8352 loss: 2.8352 2022/10/08 03:42:06 - mmengine - INFO - Epoch(train) [97][640/2119] lr: 4.0000e-02 eta: 10:57:31 time: 0.4012 data_time: 0.0208 memory: 5826 grad_norm: 3.1496 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9842 loss: 2.9842 2022/10/08 03:42:13 - mmengine - INFO - Epoch(train) [97][660/2119] lr: 4.0000e-02 eta: 10:57:24 time: 0.3292 data_time: 0.0212 memory: 5826 grad_norm: 3.1458 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8077 loss: 2.8077 2022/10/08 03:42:20 - mmengine - INFO - Epoch(train) [97][680/2119] lr: 4.0000e-02 eta: 10:57:16 time: 0.3311 data_time: 0.0239 memory: 5826 grad_norm: 3.1002 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7743 loss: 2.7743 2022/10/08 03:42:27 - mmengine - INFO - Epoch(train) [97][700/2119] lr: 4.0000e-02 eta: 10:57:10 time: 0.3836 data_time: 0.0219 memory: 5826 grad_norm: 3.1324 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7321 loss: 2.7321 2022/10/08 03:42:34 - mmengine - INFO - Epoch(train) [97][720/2119] lr: 4.0000e-02 eta: 10:57:03 time: 0.3498 data_time: 0.0218 memory: 5826 grad_norm: 3.1411 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5075 loss: 2.5075 2022/10/08 03:42:42 - mmengine - INFO - Epoch(train) [97][740/2119] lr: 4.0000e-02 eta: 10:56:57 time: 0.3851 data_time: 0.0227 memory: 5826 grad_norm: 3.1470 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7255 loss: 2.7255 2022/10/08 03:42:49 - mmengine - INFO - Epoch(train) [97][760/2119] lr: 4.0000e-02 eta: 10:56:49 time: 0.3364 data_time: 0.0232 memory: 5826 grad_norm: 3.1263 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.8355 loss: 2.8355 2022/10/08 03:42:57 - mmengine - INFO - Epoch(train) [97][780/2119] lr: 4.0000e-02 eta: 10:56:43 time: 0.3986 data_time: 0.0188 memory: 5826 grad_norm: 3.1227 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8399 loss: 2.8399 2022/10/08 03:43:03 - mmengine - INFO - Epoch(train) [97][800/2119] lr: 4.0000e-02 eta: 10:56:36 time: 0.3354 data_time: 0.0236 memory: 5826 grad_norm: 3.1230 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8005 loss: 2.8005 2022/10/08 03:43:12 - mmengine - INFO - Epoch(train) [97][820/2119] lr: 4.0000e-02 eta: 10:56:30 time: 0.4083 data_time: 0.0192 memory: 5826 grad_norm: 3.2016 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.3976 loss: 2.3976 2022/10/08 03:43:18 - mmengine - INFO - Epoch(train) [97][840/2119] lr: 4.0000e-02 eta: 10:56:23 time: 0.3431 data_time: 0.0222 memory: 5826 grad_norm: 3.1380 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7284 loss: 2.7284 2022/10/08 03:43:25 - mmengine - INFO - Epoch(train) [97][860/2119] lr: 4.0000e-02 eta: 10:56:16 time: 0.3365 data_time: 0.0247 memory: 5826 grad_norm: 3.1048 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4812 loss: 2.4812 2022/10/08 03:43:31 - mmengine - INFO - Epoch(train) [97][880/2119] lr: 4.0000e-02 eta: 10:56:08 time: 0.3037 data_time: 0.0244 memory: 5826 grad_norm: 3.1697 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7224 loss: 2.7224 2022/10/08 03:43:38 - mmengine - INFO - Epoch(train) [97][900/2119] lr: 4.0000e-02 eta: 10:56:01 time: 0.3499 data_time: 0.0348 memory: 5826 grad_norm: 3.1370 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6150 loss: 2.6150 2022/10/08 03:43:45 - mmengine - INFO - Epoch(train) [97][920/2119] lr: 4.0000e-02 eta: 10:55:55 time: 0.3555 data_time: 0.0221 memory: 5826 grad_norm: 3.1771 top1_acc: 0.1250 top5_acc: 0.6875 loss_cls: 2.6098 loss: 2.6098 2022/10/08 03:43:53 - mmengine - INFO - Epoch(train) [97][940/2119] lr: 4.0000e-02 eta: 10:55:48 time: 0.3832 data_time: 0.0197 memory: 5826 grad_norm: 3.1343 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6073 loss: 2.6073 2022/10/08 03:44:00 - mmengine - INFO - Epoch(train) [97][960/2119] lr: 4.0000e-02 eta: 10:55:41 time: 0.3360 data_time: 0.0241 memory: 5826 grad_norm: 3.1450 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.5193 loss: 2.5193 2022/10/08 03:44:07 - mmengine - INFO - Epoch(train) [97][980/2119] lr: 4.0000e-02 eta: 10:55:34 time: 0.3622 data_time: 0.0242 memory: 5826 grad_norm: 3.1303 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7005 loss: 2.7005 2022/10/08 03:44:14 - mmengine - INFO - Epoch(train) [97][1000/2119] lr: 4.0000e-02 eta: 10:55:27 time: 0.3281 data_time: 0.0199 memory: 5826 grad_norm: 3.1046 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6667 loss: 2.6667 2022/10/08 03:44:21 - mmengine - INFO - Epoch(train) [97][1020/2119] lr: 4.0000e-02 eta: 10:55:21 time: 0.3925 data_time: 0.0241 memory: 5826 grad_norm: 3.1456 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8570 loss: 2.8570 2022/10/08 03:44:28 - mmengine - INFO - Epoch(train) [97][1040/2119] lr: 4.0000e-02 eta: 10:55:14 time: 0.3222 data_time: 0.0253 memory: 5826 grad_norm: 3.1632 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6449 loss: 2.6449 2022/10/08 03:44:35 - mmengine - INFO - Epoch(train) [97][1060/2119] lr: 4.0000e-02 eta: 10:55:07 time: 0.3733 data_time: 0.0218 memory: 5826 grad_norm: 3.0887 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6144 loss: 2.6144 2022/10/08 03:44:42 - mmengine - INFO - Epoch(train) [97][1080/2119] lr: 4.0000e-02 eta: 10:55:00 time: 0.3167 data_time: 0.0263 memory: 5826 grad_norm: 3.1300 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6998 loss: 2.6998 2022/10/08 03:44:49 - mmengine - INFO - Epoch(train) [97][1100/2119] lr: 4.0000e-02 eta: 10:54:53 time: 0.3678 data_time: 0.0231 memory: 5826 grad_norm: 3.1412 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5578 loss: 2.5578 2022/10/08 03:44:56 - mmengine - INFO - Epoch(train) [97][1120/2119] lr: 4.0000e-02 eta: 10:54:46 time: 0.3523 data_time: 0.0249 memory: 5826 grad_norm: 3.1393 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.8457 loss: 2.8457 2022/10/08 03:45:04 - mmengine - INFO - Epoch(train) [97][1140/2119] lr: 4.0000e-02 eta: 10:54:39 time: 0.3720 data_time: 0.0288 memory: 5826 grad_norm: 3.1133 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.7051 loss: 2.7051 2022/10/08 03:45:11 - mmengine - INFO - Epoch(train) [97][1160/2119] lr: 4.0000e-02 eta: 10:54:33 time: 0.3552 data_time: 0.0201 memory: 5826 grad_norm: 3.1740 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6718 loss: 2.6718 2022/10/08 03:45:18 - mmengine - INFO - Epoch(train) [97][1180/2119] lr: 4.0000e-02 eta: 10:54:26 time: 0.3853 data_time: 0.0260 memory: 5826 grad_norm: 3.1803 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7708 loss: 2.7708 2022/10/08 03:45:24 - mmengine - INFO - Epoch(train) [97][1200/2119] lr: 4.0000e-02 eta: 10:54:18 time: 0.2890 data_time: 0.0214 memory: 5826 grad_norm: 3.0741 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7383 loss: 2.7383 2022/10/08 03:45:32 - mmengine - INFO - Epoch(train) [97][1220/2119] lr: 4.0000e-02 eta: 10:54:12 time: 0.3886 data_time: 0.0304 memory: 5826 grad_norm: 3.1577 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5035 loss: 2.5035 2022/10/08 03:45:39 - mmengine - INFO - Epoch(train) [97][1240/2119] lr: 4.0000e-02 eta: 10:54:05 time: 0.3648 data_time: 0.0234 memory: 5826 grad_norm: 3.1820 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 3.0881 loss: 3.0881 2022/10/08 03:45:46 - mmengine - INFO - Epoch(train) [97][1260/2119] lr: 4.0000e-02 eta: 10:53:58 time: 0.3460 data_time: 0.0192 memory: 5826 grad_norm: 3.1698 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7622 loss: 2.7622 2022/10/08 03:45:52 - mmengine - INFO - Epoch(train) [97][1280/2119] lr: 4.0000e-02 eta: 10:53:51 time: 0.3133 data_time: 0.0222 memory: 5826 grad_norm: 3.1929 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8391 loss: 2.8391 2022/10/08 03:46:00 - mmengine - INFO - Epoch(train) [97][1300/2119] lr: 4.0000e-02 eta: 10:53:45 time: 0.4002 data_time: 0.0229 memory: 5826 grad_norm: 3.1755 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4712 loss: 2.4712 2022/10/08 03:46:07 - mmengine - INFO - Epoch(train) [97][1320/2119] lr: 4.0000e-02 eta: 10:53:38 time: 0.3355 data_time: 0.0274 memory: 5826 grad_norm: 3.1421 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9462 loss: 2.9462 2022/10/08 03:46:14 - mmengine - INFO - Epoch(train) [97][1340/2119] lr: 4.0000e-02 eta: 10:53:31 time: 0.3514 data_time: 0.0212 memory: 5826 grad_norm: 3.0872 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7442 loss: 2.7442 2022/10/08 03:46:21 - mmengine - INFO - Epoch(train) [97][1360/2119] lr: 4.0000e-02 eta: 10:53:24 time: 0.3303 data_time: 0.0194 memory: 5826 grad_norm: 3.1610 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6628 loss: 2.6628 2022/10/08 03:46:29 - mmengine - INFO - Epoch(train) [97][1380/2119] lr: 4.0000e-02 eta: 10:53:17 time: 0.3869 data_time: 0.0227 memory: 5826 grad_norm: 3.1998 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7494 loss: 2.7494 2022/10/08 03:46:35 - mmengine - INFO - Epoch(train) [97][1400/2119] lr: 4.0000e-02 eta: 10:53:10 time: 0.3139 data_time: 0.0217 memory: 5826 grad_norm: 3.1337 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8957 loss: 2.8957 2022/10/08 03:46:42 - mmengine - INFO - Epoch(train) [97][1420/2119] lr: 4.0000e-02 eta: 10:53:03 time: 0.3718 data_time: 0.0204 memory: 5826 grad_norm: 3.1551 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7266 loss: 2.7266 2022/10/08 03:46:49 - mmengine - INFO - Epoch(train) [97][1440/2119] lr: 4.0000e-02 eta: 10:52:56 time: 0.3364 data_time: 0.0248 memory: 5826 grad_norm: 3.1569 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7345 loss: 2.7345 2022/10/08 03:46:57 - mmengine - INFO - Epoch(train) [97][1460/2119] lr: 4.0000e-02 eta: 10:52:50 time: 0.3930 data_time: 0.0219 memory: 5826 grad_norm: 3.1430 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.9025 loss: 2.9025 2022/10/08 03:47:03 - mmengine - INFO - Epoch(train) [97][1480/2119] lr: 4.0000e-02 eta: 10:52:42 time: 0.2870 data_time: 0.0238 memory: 5826 grad_norm: 3.1269 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6341 loss: 2.6341 2022/10/08 03:47:10 - mmengine - INFO - Epoch(train) [97][1500/2119] lr: 4.0000e-02 eta: 10:52:35 time: 0.3507 data_time: 0.0228 memory: 5826 grad_norm: 3.0718 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7455 loss: 2.7455 2022/10/08 03:47:17 - mmengine - INFO - Epoch(train) [97][1520/2119] lr: 4.0000e-02 eta: 10:52:28 time: 0.3584 data_time: 0.0230 memory: 5826 grad_norm: 3.1380 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6540 loss: 2.6540 2022/10/08 03:47:24 - mmengine - INFO - Epoch(train) [97][1540/2119] lr: 4.0000e-02 eta: 10:52:22 time: 0.3804 data_time: 0.0190 memory: 5826 grad_norm: 3.1627 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6865 loss: 2.6865 2022/10/08 03:47:31 - mmengine - INFO - Epoch(train) [97][1560/2119] lr: 4.0000e-02 eta: 10:52:15 time: 0.3263 data_time: 0.0185 memory: 5826 grad_norm: 3.1426 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7407 loss: 2.7407 2022/10/08 03:47:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 03:47:38 - mmengine - INFO - Epoch(train) [97][1580/2119] lr: 4.0000e-02 eta: 10:52:08 time: 0.3569 data_time: 0.0247 memory: 5826 grad_norm: 3.2113 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6362 loss: 2.6362 2022/10/08 03:47:45 - mmengine - INFO - Epoch(train) [97][1600/2119] lr: 4.0000e-02 eta: 10:52:01 time: 0.3437 data_time: 0.0228 memory: 5826 grad_norm: 3.1596 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8728 loss: 2.8728 2022/10/08 03:47:53 - mmengine - INFO - Epoch(train) [97][1620/2119] lr: 4.0000e-02 eta: 10:51:55 time: 0.4162 data_time: 0.0184 memory: 5826 grad_norm: 3.1160 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5759 loss: 2.5759 2022/10/08 03:48:00 - mmengine - INFO - Epoch(train) [97][1640/2119] lr: 4.0000e-02 eta: 10:51:48 time: 0.3327 data_time: 0.0234 memory: 5826 grad_norm: 3.1275 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.6136 loss: 2.6136 2022/10/08 03:48:07 - mmengine - INFO - Epoch(train) [97][1660/2119] lr: 4.0000e-02 eta: 10:51:41 time: 0.3664 data_time: 0.0250 memory: 5826 grad_norm: 3.0726 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.8767 loss: 2.8767 2022/10/08 03:48:13 - mmengine - INFO - Epoch(train) [97][1680/2119] lr: 4.0000e-02 eta: 10:51:33 time: 0.2940 data_time: 0.0222 memory: 5826 grad_norm: 3.1455 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6271 loss: 2.6271 2022/10/08 03:48:21 - mmengine - INFO - Epoch(train) [97][1700/2119] lr: 4.0000e-02 eta: 10:51:27 time: 0.3696 data_time: 0.0260 memory: 5826 grad_norm: 3.1651 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6116 loss: 2.6116 2022/10/08 03:48:27 - mmengine - INFO - Epoch(train) [97][1720/2119] lr: 4.0000e-02 eta: 10:51:19 time: 0.3214 data_time: 0.0227 memory: 5826 grad_norm: 3.1638 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.8113 loss: 2.8113 2022/10/08 03:48:35 - mmengine - INFO - Epoch(train) [97][1740/2119] lr: 4.0000e-02 eta: 10:51:13 time: 0.4169 data_time: 0.0226 memory: 5826 grad_norm: 3.1248 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5168 loss: 2.5168 2022/10/08 03:48:42 - mmengine - INFO - Epoch(train) [97][1760/2119] lr: 4.0000e-02 eta: 10:51:06 time: 0.3302 data_time: 0.0212 memory: 5826 grad_norm: 3.0690 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0976 loss: 3.0976 2022/10/08 03:48:49 - mmengine - INFO - Epoch(train) [97][1780/2119] lr: 4.0000e-02 eta: 10:51:00 time: 0.3689 data_time: 0.0218 memory: 5826 grad_norm: 3.1113 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.6749 loss: 2.6749 2022/10/08 03:48:56 - mmengine - INFO - Epoch(train) [97][1800/2119] lr: 4.0000e-02 eta: 10:50:52 time: 0.3187 data_time: 0.0252 memory: 5826 grad_norm: 3.1207 top1_acc: 0.1250 top5_acc: 0.4375 loss_cls: 2.9605 loss: 2.9605 2022/10/08 03:49:04 - mmengine - INFO - Epoch(train) [97][1820/2119] lr: 4.0000e-02 eta: 10:50:46 time: 0.4165 data_time: 0.0219 memory: 5826 grad_norm: 3.1221 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7601 loss: 2.7601 2022/10/08 03:49:11 - mmengine - INFO - Epoch(train) [97][1840/2119] lr: 4.0000e-02 eta: 10:50:39 time: 0.3354 data_time: 0.0215 memory: 5826 grad_norm: 3.1430 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7992 loss: 2.7992 2022/10/08 03:49:18 - mmengine - INFO - Epoch(train) [97][1860/2119] lr: 4.0000e-02 eta: 10:50:32 time: 0.3803 data_time: 0.0214 memory: 5826 grad_norm: 3.1677 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8098 loss: 2.8098 2022/10/08 03:49:26 - mmengine - INFO - Epoch(train) [97][1880/2119] lr: 4.0000e-02 eta: 10:50:26 time: 0.3921 data_time: 0.0236 memory: 5826 grad_norm: 3.1069 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4994 loss: 2.4994 2022/10/08 03:49:34 - mmengine - INFO - Epoch(train) [97][1900/2119] lr: 4.0000e-02 eta: 10:50:20 time: 0.3881 data_time: 0.0216 memory: 5826 grad_norm: 3.0869 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6616 loss: 2.6616 2022/10/08 03:49:41 - mmengine - INFO - Epoch(train) [97][1920/2119] lr: 4.0000e-02 eta: 10:50:13 time: 0.3645 data_time: 0.0192 memory: 5826 grad_norm: 3.1579 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5407 loss: 2.5407 2022/10/08 03:49:50 - mmengine - INFO - Epoch(train) [97][1940/2119] lr: 4.0000e-02 eta: 10:50:07 time: 0.4253 data_time: 0.0246 memory: 5826 grad_norm: 3.1127 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6972 loss: 2.6972 2022/10/08 03:49:57 - mmengine - INFO - Epoch(train) [97][1960/2119] lr: 4.0000e-02 eta: 10:50:00 time: 0.3598 data_time: 0.0201 memory: 5826 grad_norm: 3.1012 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6090 loss: 2.6090 2022/10/08 03:50:05 - mmengine - INFO - Epoch(train) [97][1980/2119] lr: 4.0000e-02 eta: 10:49:53 time: 0.3778 data_time: 0.0279 memory: 5826 grad_norm: 3.1378 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7588 loss: 2.7588 2022/10/08 03:50:11 - mmengine - INFO - Epoch(train) [97][2000/2119] lr: 4.0000e-02 eta: 10:49:46 time: 0.3279 data_time: 0.0264 memory: 5826 grad_norm: 3.0574 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6370 loss: 2.6370 2022/10/08 03:50:19 - mmengine - INFO - Epoch(train) [97][2020/2119] lr: 4.0000e-02 eta: 10:49:40 time: 0.4001 data_time: 0.0207 memory: 5826 grad_norm: 3.1485 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.5701 loss: 2.5701 2022/10/08 03:50:26 - mmengine - INFO - Epoch(train) [97][2040/2119] lr: 4.0000e-02 eta: 10:49:33 time: 0.3430 data_time: 0.0205 memory: 5826 grad_norm: 3.2123 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7496 loss: 2.7496 2022/10/08 03:50:34 - mmengine - INFO - Epoch(train) [97][2060/2119] lr: 4.0000e-02 eta: 10:49:26 time: 0.3778 data_time: 0.0219 memory: 5826 grad_norm: 3.0988 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8341 loss: 2.8341 2022/10/08 03:50:41 - mmengine - INFO - Epoch(train) [97][2080/2119] lr: 4.0000e-02 eta: 10:49:19 time: 0.3524 data_time: 0.0179 memory: 5826 grad_norm: 3.1488 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7569 loss: 2.7569 2022/10/08 03:50:49 - mmengine - INFO - Epoch(train) [97][2100/2119] lr: 4.0000e-02 eta: 10:49:13 time: 0.4008 data_time: 0.0279 memory: 5826 grad_norm: 3.0823 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.7660 loss: 2.7660 2022/10/08 03:50:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 03:50:55 - mmengine - INFO - Epoch(train) [97][2119/2119] lr: 4.0000e-02 eta: 10:49:13 time: 0.3122 data_time: 0.0206 memory: 5826 grad_norm: 3.2054 top1_acc: 0.2000 top5_acc: 0.3000 loss_cls: 2.5899 loss: 2.5899 2022/10/08 03:51:05 - mmengine - INFO - Epoch(train) [98][20/2119] lr: 4.0000e-02 eta: 10:48:58 time: 0.5320 data_time: 0.1501 memory: 5826 grad_norm: 3.1265 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5131 loss: 2.5131 2022/10/08 03:51:11 - mmengine - INFO - Epoch(train) [98][40/2119] lr: 4.0000e-02 eta: 10:48:50 time: 0.2949 data_time: 0.0221 memory: 5826 grad_norm: 3.1606 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8575 loss: 2.8575 2022/10/08 03:51:18 - mmengine - INFO - Epoch(train) [98][60/2119] lr: 4.0000e-02 eta: 10:48:44 time: 0.3536 data_time: 0.0269 memory: 5826 grad_norm: 3.1180 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4483 loss: 2.4483 2022/10/08 03:51:25 - mmengine - INFO - Epoch(train) [98][80/2119] lr: 4.0000e-02 eta: 10:48:37 time: 0.3409 data_time: 0.0191 memory: 5826 grad_norm: 3.0952 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6267 loss: 2.6267 2022/10/08 03:51:33 - mmengine - INFO - Epoch(train) [98][100/2119] lr: 4.0000e-02 eta: 10:48:30 time: 0.4086 data_time: 0.0218 memory: 5826 grad_norm: 3.1731 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5264 loss: 2.5264 2022/10/08 03:51:40 - mmengine - INFO - Epoch(train) [98][120/2119] lr: 4.0000e-02 eta: 10:48:23 time: 0.3121 data_time: 0.0209 memory: 5826 grad_norm: 3.1386 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7682 loss: 2.7682 2022/10/08 03:51:47 - mmengine - INFO - Epoch(train) [98][140/2119] lr: 4.0000e-02 eta: 10:48:16 time: 0.3587 data_time: 0.0259 memory: 5826 grad_norm: 3.1102 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.5134 loss: 2.5134 2022/10/08 03:51:54 - mmengine - INFO - Epoch(train) [98][160/2119] lr: 4.0000e-02 eta: 10:48:09 time: 0.3387 data_time: 0.0238 memory: 5826 grad_norm: 3.1426 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7930 loss: 2.7930 2022/10/08 03:52:01 - mmengine - INFO - Epoch(train) [98][180/2119] lr: 4.0000e-02 eta: 10:48:03 time: 0.3908 data_time: 0.0215 memory: 5826 grad_norm: 3.1918 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.8151 loss: 2.8151 2022/10/08 03:52:08 - mmengine - INFO - Epoch(train) [98][200/2119] lr: 4.0000e-02 eta: 10:47:55 time: 0.3087 data_time: 0.0245 memory: 5826 grad_norm: 3.1048 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5608 loss: 2.5608 2022/10/08 03:52:14 - mmengine - INFO - Epoch(train) [98][220/2119] lr: 4.0000e-02 eta: 10:47:48 time: 0.3446 data_time: 0.0230 memory: 5826 grad_norm: 3.1544 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 3.0510 loss: 3.0510 2022/10/08 03:52:22 - mmengine - INFO - Epoch(train) [98][240/2119] lr: 4.0000e-02 eta: 10:47:42 time: 0.3568 data_time: 0.0264 memory: 5826 grad_norm: 3.1788 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9889 loss: 2.9889 2022/10/08 03:52:29 - mmengine - INFO - Epoch(train) [98][260/2119] lr: 4.0000e-02 eta: 10:47:35 time: 0.3465 data_time: 0.0175 memory: 5826 grad_norm: 3.1113 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7422 loss: 2.7422 2022/10/08 03:52:36 - mmengine - INFO - Epoch(train) [98][280/2119] lr: 4.0000e-02 eta: 10:47:28 time: 0.3481 data_time: 0.0211 memory: 5826 grad_norm: 3.2054 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6198 loss: 2.6198 2022/10/08 03:52:43 - mmengine - INFO - Epoch(train) [98][300/2119] lr: 4.0000e-02 eta: 10:47:21 time: 0.3814 data_time: 0.0236 memory: 5826 grad_norm: 3.1149 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7109 loss: 2.7109 2022/10/08 03:52:50 - mmengine - INFO - Epoch(train) [98][320/2119] lr: 4.0000e-02 eta: 10:47:14 time: 0.3427 data_time: 0.0294 memory: 5826 grad_norm: 3.1115 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7261 loss: 2.7261 2022/10/08 03:52:58 - mmengine - INFO - Epoch(train) [98][340/2119] lr: 4.0000e-02 eta: 10:47:08 time: 0.4081 data_time: 0.0246 memory: 5826 grad_norm: 3.1445 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6271 loss: 2.6271 2022/10/08 03:53:04 - mmengine - INFO - Epoch(train) [98][360/2119] lr: 4.0000e-02 eta: 10:47:00 time: 0.2835 data_time: 0.0244 memory: 5826 grad_norm: 3.1262 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9152 loss: 2.9152 2022/10/08 03:53:12 - mmengine - INFO - Epoch(train) [98][380/2119] lr: 4.0000e-02 eta: 10:46:54 time: 0.3877 data_time: 0.0217 memory: 5826 grad_norm: 3.1361 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4346 loss: 2.4346 2022/10/08 03:53:17 - mmengine - INFO - Epoch(train) [98][400/2119] lr: 4.0000e-02 eta: 10:46:46 time: 0.2670 data_time: 0.0262 memory: 5826 grad_norm: 3.1148 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7023 loss: 2.7023 2022/10/08 03:53:25 - mmengine - INFO - Epoch(train) [98][420/2119] lr: 4.0000e-02 eta: 10:46:40 time: 0.3856 data_time: 0.0265 memory: 5826 grad_norm: 3.0885 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8441 loss: 2.8441 2022/10/08 03:53:31 - mmengine - INFO - Epoch(train) [98][440/2119] lr: 4.0000e-02 eta: 10:46:32 time: 0.3275 data_time: 0.0281 memory: 5826 grad_norm: 3.1337 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7557 loss: 2.7557 2022/10/08 03:53:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 03:53:39 - mmengine - INFO - Epoch(train) [98][460/2119] lr: 4.0000e-02 eta: 10:46:26 time: 0.4124 data_time: 0.0177 memory: 5826 grad_norm: 3.1445 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6706 loss: 2.6706 2022/10/08 03:53:46 - mmengine - INFO - Epoch(train) [98][480/2119] lr: 4.0000e-02 eta: 10:46:19 time: 0.3135 data_time: 0.0223 memory: 5826 grad_norm: 3.1411 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.6886 loss: 2.6886 2022/10/08 03:53:53 - mmengine - INFO - Epoch(train) [98][500/2119] lr: 4.0000e-02 eta: 10:46:12 time: 0.3850 data_time: 0.0208 memory: 5826 grad_norm: 3.1568 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5516 loss: 2.5516 2022/10/08 03:54:00 - mmengine - INFO - Epoch(train) [98][520/2119] lr: 4.0000e-02 eta: 10:46:05 time: 0.3175 data_time: 0.0237 memory: 5826 grad_norm: 3.1585 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7557 loss: 2.7557 2022/10/08 03:54:08 - mmengine - INFO - Epoch(train) [98][540/2119] lr: 4.0000e-02 eta: 10:45:59 time: 0.3967 data_time: 0.0209 memory: 5826 grad_norm: 3.1426 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7139 loss: 2.7139 2022/10/08 03:54:14 - mmengine - INFO - Epoch(train) [98][560/2119] lr: 4.0000e-02 eta: 10:45:51 time: 0.2979 data_time: 0.0263 memory: 5826 grad_norm: 3.1146 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5655 loss: 2.5655 2022/10/08 03:54:21 - mmengine - INFO - Epoch(train) [98][580/2119] lr: 4.0000e-02 eta: 10:45:44 time: 0.3614 data_time: 0.0221 memory: 5826 grad_norm: 3.1861 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6374 loss: 2.6374 2022/10/08 03:54:28 - mmengine - INFO - Epoch(train) [98][600/2119] lr: 4.0000e-02 eta: 10:45:37 time: 0.3330 data_time: 0.0221 memory: 5826 grad_norm: 3.1204 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6570 loss: 2.6570 2022/10/08 03:54:34 - mmengine - INFO - Epoch(train) [98][620/2119] lr: 4.0000e-02 eta: 10:45:30 time: 0.3292 data_time: 0.0263 memory: 5826 grad_norm: 3.1278 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7048 loss: 2.7048 2022/10/08 03:54:41 - mmengine - INFO - Epoch(train) [98][640/2119] lr: 4.0000e-02 eta: 10:45:23 time: 0.3582 data_time: 0.0244 memory: 5826 grad_norm: 3.2156 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7548 loss: 2.7548 2022/10/08 03:54:48 - mmengine - INFO - Epoch(train) [98][660/2119] lr: 4.0000e-02 eta: 10:45:16 time: 0.3477 data_time: 0.0174 memory: 5826 grad_norm: 3.1024 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.4460 loss: 2.4460 2022/10/08 03:54:55 - mmengine - INFO - Epoch(train) [98][680/2119] lr: 4.0000e-02 eta: 10:45:09 time: 0.3420 data_time: 0.0237 memory: 5826 grad_norm: 3.1972 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7810 loss: 2.7810 2022/10/08 03:55:03 - mmengine - INFO - Epoch(train) [98][700/2119] lr: 4.0000e-02 eta: 10:45:03 time: 0.3728 data_time: 0.0226 memory: 5826 grad_norm: 3.1850 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8377 loss: 2.8377 2022/10/08 03:55:10 - mmengine - INFO - Epoch(train) [98][720/2119] lr: 4.0000e-02 eta: 10:44:56 time: 0.3445 data_time: 0.0294 memory: 5826 grad_norm: 3.1704 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7109 loss: 2.7109 2022/10/08 03:55:16 - mmengine - INFO - Epoch(train) [98][740/2119] lr: 4.0000e-02 eta: 10:44:49 time: 0.3233 data_time: 0.0186 memory: 5826 grad_norm: 3.1335 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6061 loss: 2.6061 2022/10/08 03:55:23 - mmengine - INFO - Epoch(train) [98][760/2119] lr: 4.0000e-02 eta: 10:44:42 time: 0.3555 data_time: 0.0245 memory: 5826 grad_norm: 3.0921 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6025 loss: 2.6025 2022/10/08 03:55:30 - mmengine - INFO - Epoch(train) [98][780/2119] lr: 4.0000e-02 eta: 10:44:35 time: 0.3642 data_time: 0.0302 memory: 5826 grad_norm: 3.0671 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5780 loss: 2.5780 2022/10/08 03:55:37 - mmengine - INFO - Epoch(train) [98][800/2119] lr: 4.0000e-02 eta: 10:44:28 time: 0.3412 data_time: 0.0238 memory: 5826 grad_norm: 3.1468 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.5870 loss: 2.5870 2022/10/08 03:55:45 - mmengine - INFO - Epoch(train) [98][820/2119] lr: 4.0000e-02 eta: 10:44:22 time: 0.3848 data_time: 0.0265 memory: 5826 grad_norm: 3.1483 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5548 loss: 2.5548 2022/10/08 03:55:51 - mmengine - INFO - Epoch(train) [98][840/2119] lr: 4.0000e-02 eta: 10:44:14 time: 0.3217 data_time: 0.0212 memory: 5826 grad_norm: 3.1385 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7951 loss: 2.7951 2022/10/08 03:55:59 - mmengine - INFO - Epoch(train) [98][860/2119] lr: 4.0000e-02 eta: 10:44:08 time: 0.3634 data_time: 0.0249 memory: 5826 grad_norm: 3.1535 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4968 loss: 2.4968 2022/10/08 03:56:06 - mmengine - INFO - Epoch(train) [98][880/2119] lr: 4.0000e-02 eta: 10:44:01 time: 0.3601 data_time: 0.0240 memory: 5826 grad_norm: 3.0933 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8669 loss: 2.8669 2022/10/08 03:56:12 - mmengine - INFO - Epoch(train) [98][900/2119] lr: 4.0000e-02 eta: 10:43:54 time: 0.3264 data_time: 0.0192 memory: 5826 grad_norm: 3.1669 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.7690 loss: 2.7690 2022/10/08 03:56:19 - mmengine - INFO - Epoch(train) [98][920/2119] lr: 4.0000e-02 eta: 10:43:46 time: 0.3234 data_time: 0.0289 memory: 5826 grad_norm: 3.1252 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.8997 loss: 2.8997 2022/10/08 03:56:26 - mmengine - INFO - Epoch(train) [98][940/2119] lr: 4.0000e-02 eta: 10:43:40 time: 0.3442 data_time: 0.0243 memory: 5826 grad_norm: 3.1274 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5227 loss: 2.5227 2022/10/08 03:56:33 - mmengine - INFO - Epoch(train) [98][960/2119] lr: 4.0000e-02 eta: 10:43:33 time: 0.3727 data_time: 0.0264 memory: 5826 grad_norm: 3.1661 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8428 loss: 2.8428 2022/10/08 03:56:40 - mmengine - INFO - Epoch(train) [98][980/2119] lr: 4.0000e-02 eta: 10:43:26 time: 0.3437 data_time: 0.0204 memory: 5826 grad_norm: 3.0854 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6659 loss: 2.6659 2022/10/08 03:56:46 - mmengine - INFO - Epoch(train) [98][1000/2119] lr: 4.0000e-02 eta: 10:43:19 time: 0.3071 data_time: 0.0283 memory: 5826 grad_norm: 3.1099 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.7608 loss: 2.7608 2022/10/08 03:56:54 - mmengine - INFO - Epoch(train) [98][1020/2119] lr: 4.0000e-02 eta: 10:43:12 time: 0.3788 data_time: 0.0225 memory: 5826 grad_norm: 3.1635 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 3.0720 loss: 3.0720 2022/10/08 03:57:01 - mmengine - INFO - Epoch(train) [98][1040/2119] lr: 4.0000e-02 eta: 10:43:05 time: 0.3397 data_time: 0.0400 memory: 5826 grad_norm: 3.1536 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9706 loss: 2.9706 2022/10/08 03:57:08 - mmengine - INFO - Epoch(train) [98][1060/2119] lr: 4.0000e-02 eta: 10:42:58 time: 0.3755 data_time: 0.0259 memory: 5826 grad_norm: 3.0971 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6108 loss: 2.6108 2022/10/08 03:57:15 - mmengine - INFO - Epoch(train) [98][1080/2119] lr: 4.0000e-02 eta: 10:42:51 time: 0.3473 data_time: 0.0224 memory: 5826 grad_norm: 3.1941 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 3.0264 loss: 3.0264 2022/10/08 03:57:22 - mmengine - INFO - Epoch(train) [98][1100/2119] lr: 4.0000e-02 eta: 10:42:44 time: 0.3422 data_time: 0.0238 memory: 5826 grad_norm: 3.1472 top1_acc: 0.3125 top5_acc: 0.3125 loss_cls: 2.7135 loss: 2.7135 2022/10/08 03:57:29 - mmengine - INFO - Epoch(train) [98][1120/2119] lr: 4.0000e-02 eta: 10:42:38 time: 0.3541 data_time: 0.0287 memory: 5826 grad_norm: 3.1121 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7435 loss: 2.7435 2022/10/08 03:57:37 - mmengine - INFO - Epoch(train) [98][1140/2119] lr: 4.0000e-02 eta: 10:42:31 time: 0.3967 data_time: 0.0215 memory: 5826 grad_norm: 3.1591 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.6975 loss: 2.6975 2022/10/08 03:57:43 - mmengine - INFO - Epoch(train) [98][1160/2119] lr: 4.0000e-02 eta: 10:42:24 time: 0.3202 data_time: 0.0211 memory: 5826 grad_norm: 3.1490 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7408 loss: 2.7408 2022/10/08 03:57:51 - mmengine - INFO - Epoch(train) [98][1180/2119] lr: 4.0000e-02 eta: 10:42:18 time: 0.3972 data_time: 0.0246 memory: 5826 grad_norm: 3.0884 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7216 loss: 2.7216 2022/10/08 03:57:58 - mmengine - INFO - Epoch(train) [98][1200/2119] lr: 4.0000e-02 eta: 10:42:11 time: 0.3460 data_time: 0.0204 memory: 5826 grad_norm: 3.0974 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8822 loss: 2.8822 2022/10/08 03:58:05 - mmengine - INFO - Epoch(train) [98][1220/2119] lr: 4.0000e-02 eta: 10:42:04 time: 0.3542 data_time: 0.0212 memory: 5826 grad_norm: 3.1171 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5056 loss: 2.5056 2022/10/08 03:58:12 - mmengine - INFO - Epoch(train) [98][1240/2119] lr: 4.0000e-02 eta: 10:41:56 time: 0.3092 data_time: 0.0258 memory: 5826 grad_norm: 3.1665 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.8342 loss: 2.8342 2022/10/08 03:58:19 - mmengine - INFO - Epoch(train) [98][1260/2119] lr: 4.0000e-02 eta: 10:41:50 time: 0.3764 data_time: 0.0215 memory: 5826 grad_norm: 3.1725 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6891 loss: 2.6891 2022/10/08 03:58:25 - mmengine - INFO - Epoch(train) [98][1280/2119] lr: 4.0000e-02 eta: 10:41:42 time: 0.3170 data_time: 0.0268 memory: 5826 grad_norm: 3.0927 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6319 loss: 2.6319 2022/10/08 03:58:33 - mmengine - INFO - Epoch(train) [98][1300/2119] lr: 4.0000e-02 eta: 10:41:36 time: 0.3525 data_time: 0.0261 memory: 5826 grad_norm: 3.1273 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5868 loss: 2.5868 2022/10/08 03:58:39 - mmengine - INFO - Epoch(train) [98][1320/2119] lr: 4.0000e-02 eta: 10:41:29 time: 0.3421 data_time: 0.0262 memory: 5826 grad_norm: 3.1367 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6284 loss: 2.6284 2022/10/08 03:58:46 - mmengine - INFO - Epoch(train) [98][1340/2119] lr: 4.0000e-02 eta: 10:41:22 time: 0.3418 data_time: 0.0238 memory: 5826 grad_norm: 3.1072 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6668 loss: 2.6668 2022/10/08 03:58:53 - mmengine - INFO - Epoch(train) [98][1360/2119] lr: 4.0000e-02 eta: 10:41:14 time: 0.3269 data_time: 0.0227 memory: 5826 grad_norm: 3.0972 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6006 loss: 2.6006 2022/10/08 03:59:00 - mmengine - INFO - Epoch(train) [98][1380/2119] lr: 4.0000e-02 eta: 10:41:08 time: 0.3855 data_time: 0.0244 memory: 5826 grad_norm: 3.1334 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.7327 loss: 2.7327 2022/10/08 03:59:08 - mmengine - INFO - Epoch(train) [98][1400/2119] lr: 4.0000e-02 eta: 10:41:01 time: 0.3536 data_time: 0.0221 memory: 5826 grad_norm: 3.0840 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6905 loss: 2.6905 2022/10/08 03:59:15 - mmengine - INFO - Epoch(train) [98][1420/2119] lr: 4.0000e-02 eta: 10:40:54 time: 0.3653 data_time: 0.0260 memory: 5826 grad_norm: 3.0939 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7216 loss: 2.7216 2022/10/08 03:59:22 - mmengine - INFO - Epoch(train) [98][1440/2119] lr: 4.0000e-02 eta: 10:40:47 time: 0.3383 data_time: 0.0275 memory: 5826 grad_norm: 3.1320 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5053 loss: 2.5053 2022/10/08 03:59:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 03:59:31 - mmengine - INFO - Epoch(train) [98][1460/2119] lr: 4.0000e-02 eta: 10:40:41 time: 0.4443 data_time: 0.0204 memory: 5826 grad_norm: 3.1384 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5776 loss: 2.5776 2022/10/08 03:59:37 - mmengine - INFO - Epoch(train) [98][1480/2119] lr: 4.0000e-02 eta: 10:40:34 time: 0.3340 data_time: 0.0194 memory: 5826 grad_norm: 3.1645 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7433 loss: 2.7433 2022/10/08 03:59:44 - mmengine - INFO - Epoch(train) [98][1500/2119] lr: 4.0000e-02 eta: 10:40:28 time: 0.3624 data_time: 0.0218 memory: 5826 grad_norm: 3.1365 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9182 loss: 2.9182 2022/10/08 03:59:59 - mmengine - INFO - Epoch(train) [98][1520/2119] lr: 4.0000e-02 eta: 10:40:25 time: 0.7428 data_time: 0.0506 memory: 5826 grad_norm: 3.1277 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6559 loss: 2.6559 2022/10/08 04:00:05 - mmengine - INFO - Epoch(train) [98][1540/2119] lr: 4.0000e-02 eta: 10:40:17 time: 0.2866 data_time: 0.0246 memory: 5826 grad_norm: 3.1563 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7251 loss: 2.7251 2022/10/08 04:00:14 - mmengine - INFO - Epoch(train) [98][1560/2119] lr: 4.0000e-02 eta: 10:40:12 time: 0.4535 data_time: 0.0194 memory: 5826 grad_norm: 3.1216 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7125 loss: 2.7125 2022/10/08 04:00:20 - mmengine - INFO - Epoch(train) [98][1580/2119] lr: 4.0000e-02 eta: 10:40:04 time: 0.3108 data_time: 0.0292 memory: 5826 grad_norm: 3.1447 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6382 loss: 2.6382 2022/10/08 04:00:30 - mmengine - INFO - Epoch(train) [98][1600/2119] lr: 4.0000e-02 eta: 10:39:59 time: 0.4944 data_time: 0.0250 memory: 5826 grad_norm: 3.1579 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7465 loss: 2.7465 2022/10/08 04:00:35 - mmengine - INFO - Epoch(train) [98][1620/2119] lr: 4.0000e-02 eta: 10:39:51 time: 0.2492 data_time: 0.0223 memory: 5826 grad_norm: 3.0984 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6381 loss: 2.6381 2022/10/08 04:00:44 - mmengine - INFO - Epoch(train) [98][1640/2119] lr: 4.0000e-02 eta: 10:39:45 time: 0.4101 data_time: 0.0219 memory: 5826 grad_norm: 3.1653 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6865 loss: 2.6865 2022/10/08 04:00:51 - mmengine - INFO - Epoch(train) [98][1660/2119] lr: 4.0000e-02 eta: 10:39:38 time: 0.3872 data_time: 0.0225 memory: 5826 grad_norm: 3.1714 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5958 loss: 2.5958 2022/10/08 04:00:58 - mmengine - INFO - Epoch(train) [98][1680/2119] lr: 4.0000e-02 eta: 10:39:31 time: 0.3409 data_time: 0.0256 memory: 5826 grad_norm: 3.1886 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8673 loss: 2.8673 2022/10/08 04:01:06 - mmengine - INFO - Epoch(train) [98][1700/2119] lr: 4.0000e-02 eta: 10:39:25 time: 0.4024 data_time: 0.0271 memory: 5826 grad_norm: 3.0746 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6308 loss: 2.6308 2022/10/08 04:01:14 - mmengine - INFO - Epoch(train) [98][1720/2119] lr: 4.0000e-02 eta: 10:39:18 time: 0.4032 data_time: 0.0174 memory: 5826 grad_norm: 3.1024 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6006 loss: 2.6006 2022/10/08 04:01:22 - mmengine - INFO - Epoch(train) [98][1740/2119] lr: 4.0000e-02 eta: 10:39:12 time: 0.3998 data_time: 0.0240 memory: 5826 grad_norm: 3.1175 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6826 loss: 2.6826 2022/10/08 04:01:30 - mmengine - INFO - Epoch(train) [98][1760/2119] lr: 4.0000e-02 eta: 10:39:05 time: 0.3798 data_time: 0.0161 memory: 5826 grad_norm: 3.1131 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6274 loss: 2.6274 2022/10/08 04:01:38 - mmengine - INFO - Epoch(train) [98][1780/2119] lr: 4.0000e-02 eta: 10:38:59 time: 0.3953 data_time: 0.0248 memory: 5826 grad_norm: 3.1427 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7770 loss: 2.7770 2022/10/08 04:01:44 - mmengine - INFO - Epoch(train) [98][1800/2119] lr: 4.0000e-02 eta: 10:38:52 time: 0.3252 data_time: 0.0219 memory: 5826 grad_norm: 3.1062 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6282 loss: 2.6282 2022/10/08 04:01:51 - mmengine - INFO - Epoch(train) [98][1820/2119] lr: 4.0000e-02 eta: 10:38:45 time: 0.3619 data_time: 0.0268 memory: 5826 grad_norm: 3.1292 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7150 loss: 2.7150 2022/10/08 04:01:58 - mmengine - INFO - Epoch(train) [98][1840/2119] lr: 4.0000e-02 eta: 10:38:38 time: 0.3247 data_time: 0.0238 memory: 5826 grad_norm: 3.1473 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7308 loss: 2.7308 2022/10/08 04:02:05 - mmengine - INFO - Epoch(train) [98][1860/2119] lr: 4.0000e-02 eta: 10:38:31 time: 0.3596 data_time: 0.0229 memory: 5826 grad_norm: 3.0992 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7468 loss: 2.7468 2022/10/08 04:02:12 - mmengine - INFO - Epoch(train) [98][1880/2119] lr: 4.0000e-02 eta: 10:38:24 time: 0.3365 data_time: 0.0247 memory: 5826 grad_norm: 3.0598 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7211 loss: 2.7211 2022/10/08 04:02:20 - mmengine - INFO - Epoch(train) [98][1900/2119] lr: 4.0000e-02 eta: 10:38:18 time: 0.3894 data_time: 0.0187 memory: 5826 grad_norm: 3.1412 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5404 loss: 2.5404 2022/10/08 04:02:25 - mmengine - INFO - Epoch(train) [98][1920/2119] lr: 4.0000e-02 eta: 10:38:10 time: 0.2871 data_time: 0.0191 memory: 5826 grad_norm: 3.1138 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.8712 loss: 2.8712 2022/10/08 04:02:33 - mmengine - INFO - Epoch(train) [98][1940/2119] lr: 4.0000e-02 eta: 10:38:04 time: 0.3957 data_time: 0.0270 memory: 5826 grad_norm: 3.1517 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8693 loss: 2.8693 2022/10/08 04:02:41 - mmengine - INFO - Epoch(train) [98][1960/2119] lr: 4.0000e-02 eta: 10:37:57 time: 0.3748 data_time: 0.0240 memory: 5826 grad_norm: 3.1547 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7575 loss: 2.7575 2022/10/08 04:02:49 - mmengine - INFO - Epoch(train) [98][1980/2119] lr: 4.0000e-02 eta: 10:37:51 time: 0.4152 data_time: 0.0284 memory: 5826 grad_norm: 3.1007 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.6593 loss: 2.6593 2022/10/08 04:02:55 - mmengine - INFO - Epoch(train) [98][2000/2119] lr: 4.0000e-02 eta: 10:37:43 time: 0.3081 data_time: 0.0219 memory: 5826 grad_norm: 3.1227 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7910 loss: 2.7910 2022/10/08 04:03:03 - mmengine - INFO - Epoch(train) [98][2020/2119] lr: 4.0000e-02 eta: 10:37:37 time: 0.3674 data_time: 0.0276 memory: 5826 grad_norm: 3.1058 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6590 loss: 2.6590 2022/10/08 04:03:10 - mmengine - INFO - Epoch(train) [98][2040/2119] lr: 4.0000e-02 eta: 10:37:30 time: 0.3500 data_time: 0.0196 memory: 5826 grad_norm: 3.0728 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6394 loss: 2.6394 2022/10/08 04:03:17 - mmengine - INFO - Epoch(train) [98][2060/2119] lr: 4.0000e-02 eta: 10:37:23 time: 0.3437 data_time: 0.0301 memory: 5826 grad_norm: 3.0593 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6870 loss: 2.6870 2022/10/08 04:03:23 - mmengine - INFO - Epoch(train) [98][2080/2119] lr: 4.0000e-02 eta: 10:37:16 time: 0.3223 data_time: 0.0206 memory: 5826 grad_norm: 3.1882 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8149 loss: 2.8149 2022/10/08 04:03:30 - mmengine - INFO - Epoch(train) [98][2100/2119] lr: 4.0000e-02 eta: 10:37:09 time: 0.3585 data_time: 0.0254 memory: 5826 grad_norm: 3.1434 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.6910 loss: 2.6910 2022/10/08 04:03:37 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 04:03:37 - mmengine - INFO - Epoch(train) [98][2119/2119] lr: 4.0000e-02 eta: 10:37:09 time: 0.3555 data_time: 0.0233 memory: 5826 grad_norm: 3.1458 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.7046 loss: 2.7046 2022/10/08 04:03:47 - mmengine - INFO - Epoch(train) [99][20/2119] lr: 4.0000e-02 eta: 10:36:53 time: 0.5091 data_time: 0.1075 memory: 5826 grad_norm: 3.0805 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.6428 loss: 2.6428 2022/10/08 04:03:54 - mmengine - INFO - Epoch(train) [99][40/2119] lr: 4.0000e-02 eta: 10:36:47 time: 0.3574 data_time: 0.0260 memory: 5826 grad_norm: 3.0705 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 2.6419 loss: 2.6419 2022/10/08 04:04:02 - mmengine - INFO - Epoch(train) [99][60/2119] lr: 4.0000e-02 eta: 10:36:40 time: 0.3748 data_time: 0.0211 memory: 5826 grad_norm: 3.1600 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7828 loss: 2.7828 2022/10/08 04:04:09 - mmengine - INFO - Epoch(train) [99][80/2119] lr: 4.0000e-02 eta: 10:36:33 time: 0.3498 data_time: 0.0251 memory: 5826 grad_norm: 3.0735 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6986 loss: 2.6986 2022/10/08 04:04:17 - mmengine - INFO - Epoch(train) [99][100/2119] lr: 4.0000e-02 eta: 10:36:27 time: 0.3849 data_time: 0.0200 memory: 5826 grad_norm: 3.0791 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5391 loss: 2.5391 2022/10/08 04:04:23 - mmengine - INFO - Epoch(train) [99][120/2119] lr: 4.0000e-02 eta: 10:36:19 time: 0.3190 data_time: 0.0249 memory: 5826 grad_norm: 3.1016 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5331 loss: 2.5331 2022/10/08 04:04:32 - mmengine - INFO - Epoch(train) [99][140/2119] lr: 4.0000e-02 eta: 10:36:14 time: 0.4680 data_time: 0.0170 memory: 5826 grad_norm: 3.1992 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7172 loss: 2.7172 2022/10/08 04:04:39 - mmengine - INFO - Epoch(train) [99][160/2119] lr: 4.0000e-02 eta: 10:36:07 time: 0.3512 data_time: 0.0235 memory: 5826 grad_norm: 3.1021 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4446 loss: 2.4446 2022/10/08 04:04:46 - mmengine - INFO - Epoch(train) [99][180/2119] lr: 4.0000e-02 eta: 10:36:00 time: 0.3441 data_time: 0.0183 memory: 5826 grad_norm: 3.1334 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6411 loss: 2.6411 2022/10/08 04:04:53 - mmengine - INFO - Epoch(train) [99][200/2119] lr: 4.0000e-02 eta: 10:35:53 time: 0.3213 data_time: 0.0208 memory: 5826 grad_norm: 3.1249 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4945 loss: 2.4945 2022/10/08 04:05:00 - mmengine - INFO - Epoch(train) [99][220/2119] lr: 4.0000e-02 eta: 10:35:46 time: 0.3727 data_time: 0.0307 memory: 5826 grad_norm: 3.0710 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.8144 loss: 2.8144 2022/10/08 04:05:07 - mmengine - INFO - Epoch(train) [99][240/2119] lr: 4.0000e-02 eta: 10:35:39 time: 0.3528 data_time: 0.0201 memory: 5826 grad_norm: 3.1197 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7517 loss: 2.7517 2022/10/08 04:05:14 - mmengine - INFO - Epoch(train) [99][260/2119] lr: 4.0000e-02 eta: 10:35:32 time: 0.3316 data_time: 0.0195 memory: 5826 grad_norm: 3.1786 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6332 loss: 2.6332 2022/10/08 04:05:21 - mmengine - INFO - Epoch(train) [99][280/2119] lr: 4.0000e-02 eta: 10:35:25 time: 0.3541 data_time: 0.0242 memory: 5826 grad_norm: 3.1195 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6018 loss: 2.6018 2022/10/08 04:05:28 - mmengine - INFO - Epoch(train) [99][300/2119] lr: 4.0000e-02 eta: 10:35:18 time: 0.3633 data_time: 0.0250 memory: 5826 grad_norm: 3.1126 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6643 loss: 2.6643 2022/10/08 04:05:34 - mmengine - INFO - Epoch(train) [99][320/2119] lr: 4.0000e-02 eta: 10:35:11 time: 0.3081 data_time: 0.0251 memory: 5826 grad_norm: 3.1180 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6230 loss: 2.6230 2022/10/08 04:05:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 04:05:42 - mmengine - INFO - Epoch(train) [99][340/2119] lr: 4.0000e-02 eta: 10:35:04 time: 0.3629 data_time: 0.0202 memory: 5826 grad_norm: 3.1529 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.9335 loss: 2.9335 2022/10/08 04:05:49 - mmengine - INFO - Epoch(train) [99][360/2119] lr: 4.0000e-02 eta: 10:34:57 time: 0.3421 data_time: 0.0281 memory: 5826 grad_norm: 3.1304 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6773 loss: 2.6773 2022/10/08 04:05:55 - mmengine - INFO - Epoch(train) [99][380/2119] lr: 4.0000e-02 eta: 10:34:50 time: 0.3352 data_time: 0.0196 memory: 5826 grad_norm: 3.1303 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7223 loss: 2.7223 2022/10/08 04:06:02 - mmengine - INFO - Epoch(train) [99][400/2119] lr: 4.0000e-02 eta: 10:34:43 time: 0.3201 data_time: 0.0227 memory: 5826 grad_norm: 3.0811 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7268 loss: 2.7268 2022/10/08 04:06:10 - mmengine - INFO - Epoch(train) [99][420/2119] lr: 4.0000e-02 eta: 10:34:37 time: 0.4099 data_time: 0.0298 memory: 5826 grad_norm: 3.0922 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.7234 loss: 2.7234 2022/10/08 04:06:16 - mmengine - INFO - Epoch(train) [99][440/2119] lr: 4.0000e-02 eta: 10:34:30 time: 0.3252 data_time: 0.0213 memory: 5826 grad_norm: 3.1328 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.9460 loss: 2.9460 2022/10/08 04:06:24 - mmengine - INFO - Epoch(train) [99][460/2119] lr: 4.0000e-02 eta: 10:34:23 time: 0.3770 data_time: 0.0182 memory: 5826 grad_norm: 3.1409 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.6787 loss: 2.6787 2022/10/08 04:06:31 - mmengine - INFO - Epoch(train) [99][480/2119] lr: 4.0000e-02 eta: 10:34:16 time: 0.3536 data_time: 0.0276 memory: 5826 grad_norm: 3.1011 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6560 loss: 2.6560 2022/10/08 04:06:37 - mmengine - INFO - Epoch(train) [99][500/2119] lr: 4.0000e-02 eta: 10:34:09 time: 0.3198 data_time: 0.0244 memory: 5826 grad_norm: 3.1611 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6084 loss: 2.6084 2022/10/08 04:06:45 - mmengine - INFO - Epoch(train) [99][520/2119] lr: 4.0000e-02 eta: 10:34:02 time: 0.3842 data_time: 0.0240 memory: 5826 grad_norm: 3.1242 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7989 loss: 2.7989 2022/10/08 04:06:52 - mmengine - INFO - Epoch(train) [99][540/2119] lr: 4.0000e-02 eta: 10:33:55 time: 0.3284 data_time: 0.0264 memory: 5826 grad_norm: 3.2031 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.5894 loss: 2.5894 2022/10/08 04:06:58 - mmengine - INFO - Epoch(train) [99][560/2119] lr: 4.0000e-02 eta: 10:33:48 time: 0.3212 data_time: 0.0245 memory: 5826 grad_norm: 3.0946 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7664 loss: 2.7664 2022/10/08 04:07:06 - mmengine - INFO - Epoch(train) [99][580/2119] lr: 4.0000e-02 eta: 10:33:42 time: 0.3995 data_time: 0.0222 memory: 5826 grad_norm: 3.1265 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.7593 loss: 2.7593 2022/10/08 04:07:13 - mmengine - INFO - Epoch(train) [99][600/2119] lr: 4.0000e-02 eta: 10:33:34 time: 0.3297 data_time: 0.0272 memory: 5826 grad_norm: 3.1533 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7915 loss: 2.7915 2022/10/08 04:07:20 - mmengine - INFO - Epoch(train) [99][620/2119] lr: 4.0000e-02 eta: 10:33:28 time: 0.3698 data_time: 0.0200 memory: 5826 grad_norm: 3.1054 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.6225 loss: 2.6225 2022/10/08 04:07:28 - mmengine - INFO - Epoch(train) [99][640/2119] lr: 4.0000e-02 eta: 10:33:21 time: 0.3674 data_time: 0.0258 memory: 5826 grad_norm: 3.2047 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6437 loss: 2.6437 2022/10/08 04:07:34 - mmengine - INFO - Epoch(train) [99][660/2119] lr: 4.0000e-02 eta: 10:33:14 time: 0.3309 data_time: 0.0271 memory: 5826 grad_norm: 3.0614 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.6256 loss: 2.6256 2022/10/08 04:07:42 - mmengine - INFO - Epoch(train) [99][680/2119] lr: 4.0000e-02 eta: 10:33:07 time: 0.3750 data_time: 0.0259 memory: 5826 grad_norm: 3.1620 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4625 loss: 2.4625 2022/10/08 04:07:48 - mmengine - INFO - Epoch(train) [99][700/2119] lr: 4.0000e-02 eta: 10:33:00 time: 0.3019 data_time: 0.0259 memory: 5826 grad_norm: 3.1172 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.4978 loss: 2.4978 2022/10/08 04:07:55 - mmengine - INFO - Epoch(train) [99][720/2119] lr: 4.0000e-02 eta: 10:32:53 time: 0.3639 data_time: 0.0325 memory: 5826 grad_norm: 3.1571 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.8304 loss: 2.8304 2022/10/08 04:08:03 - mmengine - INFO - Epoch(train) [99][740/2119] lr: 4.0000e-02 eta: 10:32:47 time: 0.3988 data_time: 0.0274 memory: 5826 grad_norm: 3.1060 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7428 loss: 2.7428 2022/10/08 04:08:10 - mmengine - INFO - Epoch(train) [99][760/2119] lr: 4.0000e-02 eta: 10:32:40 time: 0.3669 data_time: 0.0229 memory: 5826 grad_norm: 3.1840 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9123 loss: 2.9123 2022/10/08 04:08:17 - mmengine - INFO - Epoch(train) [99][780/2119] lr: 4.0000e-02 eta: 10:32:33 time: 0.3273 data_time: 0.0333 memory: 5826 grad_norm: 3.1635 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2593 loss: 2.2593 2022/10/08 04:08:24 - mmengine - INFO - Epoch(train) [99][800/2119] lr: 4.0000e-02 eta: 10:32:26 time: 0.3332 data_time: 0.0267 memory: 5826 grad_norm: 3.1617 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.5914 loss: 2.5914 2022/10/08 04:08:31 - mmengine - INFO - Epoch(train) [99][820/2119] lr: 4.0000e-02 eta: 10:32:19 time: 0.3666 data_time: 0.0229 memory: 5826 grad_norm: 3.1337 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6034 loss: 2.6034 2022/10/08 04:08:37 - mmengine - INFO - Epoch(train) [99][840/2119] lr: 4.0000e-02 eta: 10:32:12 time: 0.3052 data_time: 0.0268 memory: 5826 grad_norm: 3.1078 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.7792 loss: 2.7792 2022/10/08 04:08:44 - mmengine - INFO - Epoch(train) [99][860/2119] lr: 4.0000e-02 eta: 10:32:05 time: 0.3651 data_time: 0.0211 memory: 5826 grad_norm: 3.2357 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.9016 loss: 2.9016 2022/10/08 04:08:51 - mmengine - INFO - Epoch(train) [99][880/2119] lr: 4.0000e-02 eta: 10:31:58 time: 0.3338 data_time: 0.0286 memory: 5826 grad_norm: 3.1365 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6522 loss: 2.6522 2022/10/08 04:08:58 - mmengine - INFO - Epoch(train) [99][900/2119] lr: 4.0000e-02 eta: 10:31:51 time: 0.3707 data_time: 0.0272 memory: 5826 grad_norm: 3.1211 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.9411 loss: 2.9411 2022/10/08 04:09:05 - mmengine - INFO - Epoch(train) [99][920/2119] lr: 4.0000e-02 eta: 10:31:44 time: 0.3271 data_time: 0.0255 memory: 5826 grad_norm: 3.0799 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.6075 loss: 2.6075 2022/10/08 04:09:12 - mmengine - INFO - Epoch(train) [99][940/2119] lr: 4.0000e-02 eta: 10:31:37 time: 0.3720 data_time: 0.0225 memory: 5826 grad_norm: 3.1641 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7430 loss: 2.7430 2022/10/08 04:09:19 - mmengine - INFO - Epoch(train) [99][960/2119] lr: 4.0000e-02 eta: 10:31:30 time: 0.3184 data_time: 0.0257 memory: 5826 grad_norm: 3.2102 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6808 loss: 2.6808 2022/10/08 04:09:26 - mmengine - INFO - Epoch(train) [99][980/2119] lr: 4.0000e-02 eta: 10:31:23 time: 0.3551 data_time: 0.0202 memory: 5826 grad_norm: 3.1556 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7196 loss: 2.7196 2022/10/08 04:09:33 - mmengine - INFO - Epoch(train) [99][1000/2119] lr: 4.0000e-02 eta: 10:31:16 time: 0.3433 data_time: 0.0246 memory: 5826 grad_norm: 3.1255 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.6717 loss: 2.6717 2022/10/08 04:09:39 - mmengine - INFO - Epoch(train) [99][1020/2119] lr: 4.0000e-02 eta: 10:31:09 time: 0.3279 data_time: 0.0240 memory: 5826 grad_norm: 3.1006 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.7965 loss: 2.7965 2022/10/08 04:09:47 - mmengine - INFO - Epoch(train) [99][1040/2119] lr: 4.0000e-02 eta: 10:31:02 time: 0.3630 data_time: 0.0231 memory: 5826 grad_norm: 3.1933 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7278 loss: 2.7278 2022/10/08 04:09:53 - mmengine - INFO - Epoch(train) [99][1060/2119] lr: 4.0000e-02 eta: 10:30:55 time: 0.3454 data_time: 0.0238 memory: 5826 grad_norm: 3.0929 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8387 loss: 2.8387 2022/10/08 04:10:01 - mmengine - INFO - Epoch(train) [99][1080/2119] lr: 4.0000e-02 eta: 10:30:49 time: 0.3628 data_time: 0.0273 memory: 5826 grad_norm: 3.1302 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7748 loss: 2.7748 2022/10/08 04:10:08 - mmengine - INFO - Epoch(train) [99][1100/2119] lr: 4.0000e-02 eta: 10:30:42 time: 0.3710 data_time: 0.0274 memory: 5826 grad_norm: 3.1255 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.8275 loss: 2.8275 2022/10/08 04:10:14 - mmengine - INFO - Epoch(train) [99][1120/2119] lr: 4.0000e-02 eta: 10:30:34 time: 0.2969 data_time: 0.0278 memory: 5826 grad_norm: 3.1267 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5636 loss: 2.5636 2022/10/08 04:10:22 - mmengine - INFO - Epoch(train) [99][1140/2119] lr: 4.0000e-02 eta: 10:30:28 time: 0.3866 data_time: 0.0251 memory: 5826 grad_norm: 3.1818 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.6627 loss: 2.6627 2022/10/08 04:10:28 - mmengine - INFO - Epoch(train) [99][1160/2119] lr: 4.0000e-02 eta: 10:30:21 time: 0.3019 data_time: 0.0256 memory: 5826 grad_norm: 3.1043 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.7315 loss: 2.7315 2022/10/08 04:10:35 - mmengine - INFO - Epoch(train) [99][1180/2119] lr: 4.0000e-02 eta: 10:30:14 time: 0.3582 data_time: 0.0222 memory: 5826 grad_norm: 3.1156 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7050 loss: 2.7050 2022/10/08 04:10:42 - mmengine - INFO - Epoch(train) [99][1200/2119] lr: 4.0000e-02 eta: 10:30:07 time: 0.3670 data_time: 0.0193 memory: 5826 grad_norm: 3.1149 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5050 loss: 2.5050 2022/10/08 04:10:49 - mmengine - INFO - Epoch(train) [99][1220/2119] lr: 4.0000e-02 eta: 10:30:00 time: 0.3463 data_time: 0.0206 memory: 5826 grad_norm: 3.0873 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.6612 loss: 2.6612 2022/10/08 04:10:56 - mmengine - INFO - Epoch(train) [99][1240/2119] lr: 4.0000e-02 eta: 10:29:53 time: 0.3460 data_time: 0.0215 memory: 5826 grad_norm: 3.1541 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5607 loss: 2.5607 2022/10/08 04:11:04 - mmengine - INFO - Epoch(train) [99][1260/2119] lr: 4.0000e-02 eta: 10:29:47 time: 0.3866 data_time: 0.0214 memory: 5826 grad_norm: 3.0852 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6148 loss: 2.6148 2022/10/08 04:11:10 - mmengine - INFO - Epoch(train) [99][1280/2119] lr: 4.0000e-02 eta: 10:29:39 time: 0.2791 data_time: 0.0224 memory: 5826 grad_norm: 3.1654 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.5090 loss: 2.5090 2022/10/08 04:11:17 - mmengine - INFO - Epoch(train) [99][1300/2119] lr: 4.0000e-02 eta: 10:29:32 time: 0.3706 data_time: 0.0246 memory: 5826 grad_norm: 3.1850 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7086 loss: 2.7086 2022/10/08 04:11:24 - mmengine - INFO - Epoch(train) [99][1320/2119] lr: 4.0000e-02 eta: 10:29:25 time: 0.3314 data_time: 0.0258 memory: 5826 grad_norm: 3.1938 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5886 loss: 2.5886 2022/10/08 04:11:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 04:11:31 - mmengine - INFO - Epoch(train) [99][1340/2119] lr: 4.0000e-02 eta: 10:29:19 time: 0.3754 data_time: 0.0280 memory: 5826 grad_norm: 3.1523 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5181 loss: 2.5181 2022/10/08 04:11:38 - mmengine - INFO - Epoch(train) [99][1360/2119] lr: 4.0000e-02 eta: 10:29:12 time: 0.3562 data_time: 0.0244 memory: 5826 grad_norm: 3.1769 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0008 loss: 3.0008 2022/10/08 04:11:45 - mmengine - INFO - Epoch(train) [99][1380/2119] lr: 4.0000e-02 eta: 10:29:05 time: 0.3376 data_time: 0.0181 memory: 5826 grad_norm: 3.1390 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6957 loss: 2.6957 2022/10/08 04:11:52 - mmengine - INFO - Epoch(train) [99][1400/2119] lr: 4.0000e-02 eta: 10:28:58 time: 0.3409 data_time: 0.0278 memory: 5826 grad_norm: 3.1325 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6982 loss: 2.6982 2022/10/08 04:12:00 - mmengine - INFO - Epoch(train) [99][1420/2119] lr: 4.0000e-02 eta: 10:28:52 time: 0.4279 data_time: 0.0201 memory: 5826 grad_norm: 3.1172 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.6898 loss: 2.6898 2022/10/08 04:12:07 - mmengine - INFO - Epoch(train) [99][1440/2119] lr: 4.0000e-02 eta: 10:28:44 time: 0.3368 data_time: 0.0222 memory: 5826 grad_norm: 3.1625 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.8738 loss: 2.8738 2022/10/08 04:12:15 - mmengine - INFO - Epoch(train) [99][1460/2119] lr: 4.0000e-02 eta: 10:28:38 time: 0.3776 data_time: 0.0177 memory: 5826 grad_norm: 3.1238 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.8225 loss: 2.8225 2022/10/08 04:12:21 - mmengine - INFO - Epoch(train) [99][1480/2119] lr: 4.0000e-02 eta: 10:28:31 time: 0.3302 data_time: 0.0271 memory: 5826 grad_norm: 3.1973 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8285 loss: 2.8285 2022/10/08 04:12:29 - mmengine - INFO - Epoch(train) [99][1500/2119] lr: 4.0000e-02 eta: 10:28:24 time: 0.3585 data_time: 0.0225 memory: 5826 grad_norm: 3.0994 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7575 loss: 2.7575 2022/10/08 04:12:35 - mmengine - INFO - Epoch(train) [99][1520/2119] lr: 4.0000e-02 eta: 10:28:17 time: 0.3236 data_time: 0.0252 memory: 5826 grad_norm: 3.1568 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8226 loss: 2.8226 2022/10/08 04:12:43 - mmengine - INFO - Epoch(train) [99][1540/2119] lr: 4.0000e-02 eta: 10:28:10 time: 0.4031 data_time: 0.0149 memory: 5826 grad_norm: 3.1241 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6131 loss: 2.6131 2022/10/08 04:12:49 - mmengine - INFO - Epoch(train) [99][1560/2119] lr: 4.0000e-02 eta: 10:28:03 time: 0.3020 data_time: 0.0232 memory: 5826 grad_norm: 3.1368 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6572 loss: 2.6572 2022/10/08 04:12:58 - mmengine - INFO - Epoch(train) [99][1580/2119] lr: 4.0000e-02 eta: 10:27:57 time: 0.4278 data_time: 0.0160 memory: 5826 grad_norm: 3.2194 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9288 loss: 2.9288 2022/10/08 04:13:04 - mmengine - INFO - Epoch(train) [99][1600/2119] lr: 4.0000e-02 eta: 10:27:50 time: 0.3309 data_time: 0.0218 memory: 5826 grad_norm: 3.1166 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6548 loss: 2.6548 2022/10/08 04:13:12 - mmengine - INFO - Epoch(train) [99][1620/2119] lr: 4.0000e-02 eta: 10:27:43 time: 0.3918 data_time: 0.0161 memory: 5826 grad_norm: 3.1472 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7534 loss: 2.7534 2022/10/08 04:13:20 - mmengine - INFO - Epoch(train) [99][1640/2119] lr: 4.0000e-02 eta: 10:27:37 time: 0.3665 data_time: 0.0220 memory: 5826 grad_norm: 3.0987 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.7282 loss: 2.7282 2022/10/08 04:13:26 - mmengine - INFO - Epoch(train) [99][1660/2119] lr: 4.0000e-02 eta: 10:27:29 time: 0.3254 data_time: 0.0165 memory: 5826 grad_norm: 3.1595 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6258 loss: 2.6258 2022/10/08 04:13:33 - mmengine - INFO - Epoch(train) [99][1680/2119] lr: 4.0000e-02 eta: 10:27:22 time: 0.3249 data_time: 0.0249 memory: 5826 grad_norm: 3.1366 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.4866 loss: 2.4866 2022/10/08 04:13:40 - mmengine - INFO - Epoch(train) [99][1700/2119] lr: 4.0000e-02 eta: 10:27:15 time: 0.3527 data_time: 0.0242 memory: 5826 grad_norm: 3.1393 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5332 loss: 2.5332 2022/10/08 04:13:46 - mmengine - INFO - Epoch(train) [99][1720/2119] lr: 4.0000e-02 eta: 10:27:08 time: 0.3271 data_time: 0.0232 memory: 5826 grad_norm: 3.1317 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.8821 loss: 2.8821 2022/10/08 04:13:54 - mmengine - INFO - Epoch(train) [99][1740/2119] lr: 4.0000e-02 eta: 10:27:02 time: 0.4017 data_time: 0.0176 memory: 5826 grad_norm: 3.0627 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6013 loss: 2.6013 2022/10/08 04:14:01 - mmengine - INFO - Epoch(train) [99][1760/2119] lr: 4.0000e-02 eta: 10:26:55 time: 0.3342 data_time: 0.0224 memory: 5826 grad_norm: 3.0898 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.4648 loss: 2.4648 2022/10/08 04:14:08 - mmengine - INFO - Epoch(train) [99][1780/2119] lr: 4.0000e-02 eta: 10:26:48 time: 0.3426 data_time: 0.0219 memory: 5826 grad_norm: 3.1779 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6062 loss: 2.6062 2022/10/08 04:14:14 - mmengine - INFO - Epoch(train) [99][1800/2119] lr: 4.0000e-02 eta: 10:26:41 time: 0.3292 data_time: 0.0267 memory: 5826 grad_norm: 3.1197 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7159 loss: 2.7159 2022/10/08 04:14:23 - mmengine - INFO - Epoch(train) [99][1820/2119] lr: 4.0000e-02 eta: 10:26:34 time: 0.4123 data_time: 0.0192 memory: 5826 grad_norm: 3.1845 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7813 loss: 2.7813 2022/10/08 04:14:29 - mmengine - INFO - Epoch(train) [99][1840/2119] lr: 4.0000e-02 eta: 10:26:27 time: 0.3222 data_time: 0.0241 memory: 5826 grad_norm: 3.1367 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6123 loss: 2.6123 2022/10/08 04:14:36 - mmengine - INFO - Epoch(train) [99][1860/2119] lr: 4.0000e-02 eta: 10:26:20 time: 0.3621 data_time: 0.0249 memory: 5826 grad_norm: 3.1350 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5526 loss: 2.5526 2022/10/08 04:14:43 - mmengine - INFO - Epoch(train) [99][1880/2119] lr: 4.0000e-02 eta: 10:26:13 time: 0.3256 data_time: 0.0246 memory: 5826 grad_norm: 3.2399 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.6533 loss: 2.6533 2022/10/08 04:14:49 - mmengine - INFO - Epoch(train) [99][1900/2119] lr: 4.0000e-02 eta: 10:26:06 time: 0.3197 data_time: 0.0245 memory: 5826 grad_norm: 3.1728 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 3.0083 loss: 3.0083 2022/10/08 04:14:56 - mmengine - INFO - Epoch(train) [99][1920/2119] lr: 4.0000e-02 eta: 10:25:59 time: 0.3531 data_time: 0.0275 memory: 5826 grad_norm: 3.1509 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.8619 loss: 2.8619 2022/10/08 04:15:04 - mmengine - INFO - Epoch(train) [99][1940/2119] lr: 4.0000e-02 eta: 10:25:53 time: 0.3919 data_time: 0.0238 memory: 5826 grad_norm: 3.0929 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6744 loss: 2.6744 2022/10/08 04:15:11 - mmengine - INFO - Epoch(train) [99][1960/2119] lr: 4.0000e-02 eta: 10:25:46 time: 0.3479 data_time: 0.0280 memory: 5826 grad_norm: 3.1004 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.6140 loss: 2.6140 2022/10/08 04:15:18 - mmengine - INFO - Epoch(train) [99][1980/2119] lr: 4.0000e-02 eta: 10:25:39 time: 0.3619 data_time: 0.0201 memory: 5826 grad_norm: 3.0803 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6635 loss: 2.6635 2022/10/08 04:15:25 - mmengine - INFO - Epoch(train) [99][2000/2119] lr: 4.0000e-02 eta: 10:25:32 time: 0.3480 data_time: 0.0231 memory: 5826 grad_norm: 3.1470 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0077 loss: 3.0077 2022/10/08 04:15:33 - mmengine - INFO - Epoch(train) [99][2020/2119] lr: 4.0000e-02 eta: 10:25:26 time: 0.4005 data_time: 0.0228 memory: 5826 grad_norm: 3.1344 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.4149 loss: 2.4149 2022/10/08 04:15:40 - mmengine - INFO - Epoch(train) [99][2040/2119] lr: 4.0000e-02 eta: 10:25:19 time: 0.3228 data_time: 0.0248 memory: 5826 grad_norm: 3.1699 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9654 loss: 2.9654 2022/10/08 04:15:47 - mmengine - INFO - Epoch(train) [99][2060/2119] lr: 4.0000e-02 eta: 10:25:12 time: 0.3642 data_time: 0.0264 memory: 5826 grad_norm: 3.0970 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9646 loss: 2.9646 2022/10/08 04:15:53 - mmengine - INFO - Epoch(train) [99][2080/2119] lr: 4.0000e-02 eta: 10:25:04 time: 0.3006 data_time: 0.0258 memory: 5826 grad_norm: 3.1111 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5876 loss: 2.5876 2022/10/08 04:16:01 - mmengine - INFO - Epoch(train) [99][2100/2119] lr: 4.0000e-02 eta: 10:24:58 time: 0.3781 data_time: 0.0228 memory: 5826 grad_norm: 3.0949 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.4166 loss: 2.4166 2022/10/08 04:16:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 04:16:07 - mmengine - INFO - Epoch(train) [99][2119/2119] lr: 4.0000e-02 eta: 10:24:58 time: 0.3261 data_time: 0.0248 memory: 5826 grad_norm: 3.1793 top1_acc: 0.5000 top5_acc: 0.8000 loss_cls: 2.6177 loss: 2.6177 2022/10/08 04:16:17 - mmengine - INFO - Epoch(train) [100][20/2119] lr: 4.0000e-02 eta: 10:24:42 time: 0.4897 data_time: 0.2294 memory: 5826 grad_norm: 3.1725 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5441 loss: 2.5441 2022/10/08 04:16:24 - mmengine - INFO - Epoch(train) [100][40/2119] lr: 4.0000e-02 eta: 10:24:36 time: 0.3686 data_time: 0.0532 memory: 5826 grad_norm: 3.0827 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6441 loss: 2.6441 2022/10/08 04:16:32 - mmengine - INFO - Epoch(train) [100][60/2119] lr: 4.0000e-02 eta: 10:24:29 time: 0.3874 data_time: 0.0147 memory: 5826 grad_norm: 3.0721 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.4356 loss: 2.4356 2022/10/08 04:16:38 - mmengine - INFO - Epoch(train) [100][80/2119] lr: 4.0000e-02 eta: 10:24:22 time: 0.3115 data_time: 0.0242 memory: 5826 grad_norm: 3.1174 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8919 loss: 2.8919 2022/10/08 04:16:45 - mmengine - INFO - Epoch(train) [100][100/2119] lr: 4.0000e-02 eta: 10:24:15 time: 0.3641 data_time: 0.0236 memory: 5826 grad_norm: 3.1118 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7740 loss: 2.7740 2022/10/08 04:16:53 - mmengine - INFO - Epoch(train) [100][120/2119] lr: 4.0000e-02 eta: 10:24:08 time: 0.3677 data_time: 0.0191 memory: 5826 grad_norm: 3.1344 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7183 loss: 2.7183 2022/10/08 04:17:01 - mmengine - INFO - Epoch(train) [100][140/2119] lr: 4.0000e-02 eta: 10:24:02 time: 0.4135 data_time: 0.0316 memory: 5826 grad_norm: 3.1602 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5846 loss: 2.5846 2022/10/08 04:17:08 - mmengine - INFO - Epoch(train) [100][160/2119] lr: 4.0000e-02 eta: 10:23:55 time: 0.3459 data_time: 0.0202 memory: 5826 grad_norm: 3.1368 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.7828 loss: 2.7828 2022/10/08 04:17:16 - mmengine - INFO - Epoch(train) [100][180/2119] lr: 4.0000e-02 eta: 10:23:48 time: 0.3785 data_time: 0.0213 memory: 5826 grad_norm: 3.1103 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6241 loss: 2.6241 2022/10/08 04:17:22 - mmengine - INFO - Epoch(train) [100][200/2119] lr: 4.0000e-02 eta: 10:23:42 time: 0.3486 data_time: 0.0276 memory: 5826 grad_norm: 3.1024 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6551 loss: 2.6551 2022/10/08 04:17:29 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 04:17:30 - mmengine - INFO - Epoch(train) [100][220/2119] lr: 4.0000e-02 eta: 10:23:35 time: 0.3735 data_time: 0.0196 memory: 5826 grad_norm: 3.0806 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.9459 loss: 2.9459 2022/10/08 04:17:37 - mmengine - INFO - Epoch(train) [100][240/2119] lr: 4.0000e-02 eta: 10:23:28 time: 0.3541 data_time: 0.0230 memory: 5826 grad_norm: 3.1436 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7094 loss: 2.7094 2022/10/08 04:17:44 - mmengine - INFO - Epoch(train) [100][260/2119] lr: 4.0000e-02 eta: 10:23:21 time: 0.3475 data_time: 0.0226 memory: 5826 grad_norm: 3.1694 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.9187 loss: 2.9187 2022/10/08 04:17:50 - mmengine - INFO - Epoch(train) [100][280/2119] lr: 4.0000e-02 eta: 10:23:14 time: 0.3091 data_time: 0.0249 memory: 5826 grad_norm: 3.1789 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.8209 loss: 2.8209 2022/10/08 04:17:58 - mmengine - INFO - Epoch(train) [100][300/2119] lr: 4.0000e-02 eta: 10:23:07 time: 0.4043 data_time: 0.0191 memory: 5826 grad_norm: 3.1714 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5073 loss: 2.5073 2022/10/08 04:18:05 - mmengine - INFO - Epoch(train) [100][320/2119] lr: 4.0000e-02 eta: 10:23:01 time: 0.3589 data_time: 0.0208 memory: 5826 grad_norm: 3.1411 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.6994 loss: 2.6994 2022/10/08 04:18:13 - mmengine - INFO - Epoch(train) [100][340/2119] lr: 4.0000e-02 eta: 10:22:54 time: 0.3689 data_time: 0.0197 memory: 5826 grad_norm: 3.2022 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5360 loss: 2.5360 2022/10/08 04:18:19 - mmengine - INFO - Epoch(train) [100][360/2119] lr: 4.0000e-02 eta: 10:22:47 time: 0.3278 data_time: 0.0213 memory: 5826 grad_norm: 3.1916 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.5859 loss: 2.5859 2022/10/08 04:18:27 - mmengine - INFO - Epoch(train) [100][380/2119] lr: 4.0000e-02 eta: 10:22:40 time: 0.3999 data_time: 0.0203 memory: 5826 grad_norm: 3.1361 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8235 loss: 2.8235 2022/10/08 04:18:34 - mmengine - INFO - Epoch(train) [100][400/2119] lr: 4.0000e-02 eta: 10:22:33 time: 0.3353 data_time: 0.0243 memory: 5826 grad_norm: 3.1371 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.7892 loss: 2.7892 2022/10/08 04:18:43 - mmengine - INFO - Epoch(train) [100][420/2119] lr: 4.0000e-02 eta: 10:22:27 time: 0.4270 data_time: 0.0214 memory: 5826 grad_norm: 3.1691 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6496 loss: 2.6496 2022/10/08 04:18:50 - mmengine - INFO - Epoch(train) [100][440/2119] lr: 4.0000e-02 eta: 10:22:20 time: 0.3595 data_time: 0.0210 memory: 5826 grad_norm: 3.1680 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7772 loss: 2.7772 2022/10/08 04:18:57 - mmengine - INFO - Epoch(train) [100][460/2119] lr: 4.0000e-02 eta: 10:22:13 time: 0.3341 data_time: 0.0215 memory: 5826 grad_norm: 3.1828 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8434 loss: 2.8434 2022/10/08 04:19:04 - mmengine - INFO - Epoch(train) [100][480/2119] lr: 4.0000e-02 eta: 10:22:06 time: 0.3518 data_time: 0.0213 memory: 5826 grad_norm: 3.1549 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5385 loss: 2.5385 2022/10/08 04:19:12 - mmengine - INFO - Epoch(train) [100][500/2119] lr: 4.0000e-02 eta: 10:22:00 time: 0.3970 data_time: 0.0222 memory: 5826 grad_norm: 3.1768 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9061 loss: 2.9061 2022/10/08 04:19:18 - mmengine - INFO - Epoch(train) [100][520/2119] lr: 4.0000e-02 eta: 10:21:53 time: 0.3252 data_time: 0.0268 memory: 5826 grad_norm: 3.2222 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.7200 loss: 2.7200 2022/10/08 04:19:26 - mmengine - INFO - Epoch(train) [100][540/2119] lr: 4.0000e-02 eta: 10:21:46 time: 0.3944 data_time: 0.0211 memory: 5826 grad_norm: 3.0913 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6080 loss: 2.6080 2022/10/08 04:19:33 - mmengine - INFO - Epoch(train) [100][560/2119] lr: 4.0000e-02 eta: 10:21:39 time: 0.3315 data_time: 0.0285 memory: 5826 grad_norm: 3.1932 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.6056 loss: 2.6056 2022/10/08 04:19:41 - mmengine - INFO - Epoch(train) [100][580/2119] lr: 4.0000e-02 eta: 10:21:33 time: 0.4169 data_time: 0.0260 memory: 5826 grad_norm: 3.1154 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.6214 loss: 2.6214 2022/10/08 04:19:47 - mmengine - INFO - Epoch(train) [100][600/2119] lr: 4.0000e-02 eta: 10:21:26 time: 0.3225 data_time: 0.0195 memory: 5826 grad_norm: 3.1512 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6656 loss: 2.6656 2022/10/08 04:19:54 - mmengine - INFO - Epoch(train) [100][620/2119] lr: 4.0000e-02 eta: 10:21:18 time: 0.3047 data_time: 0.0247 memory: 5826 grad_norm: 3.1390 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.7994 loss: 2.7994 2022/10/08 04:20:00 - mmengine - INFO - Epoch(train) [100][640/2119] lr: 4.0000e-02 eta: 10:21:11 time: 0.3329 data_time: 0.0299 memory: 5826 grad_norm: 3.1070 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8670 loss: 2.8670 2022/10/08 04:20:08 - mmengine - INFO - Epoch(train) [100][660/2119] lr: 4.0000e-02 eta: 10:21:05 time: 0.3681 data_time: 0.0250 memory: 5826 grad_norm: 3.1064 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8931 loss: 2.8931 2022/10/08 04:20:15 - mmengine - INFO - Epoch(train) [100][680/2119] lr: 4.0000e-02 eta: 10:20:58 time: 0.3741 data_time: 0.0192 memory: 5826 grad_norm: 3.1599 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.6544 loss: 2.6544 2022/10/08 04:20:22 - mmengine - INFO - Epoch(train) [100][700/2119] lr: 4.0000e-02 eta: 10:20:51 time: 0.3342 data_time: 0.0274 memory: 5826 grad_norm: 3.1173 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7342 loss: 2.7342 2022/10/08 04:20:29 - mmengine - INFO - Epoch(train) [100][720/2119] lr: 4.0000e-02 eta: 10:20:44 time: 0.3663 data_time: 0.0240 memory: 5826 grad_norm: 3.2024 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6592 loss: 2.6592 2022/10/08 04:20:35 - mmengine - INFO - Epoch(train) [100][740/2119] lr: 4.0000e-02 eta: 10:20:37 time: 0.3069 data_time: 0.0222 memory: 5826 grad_norm: 3.1662 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5939 loss: 2.5939 2022/10/08 04:20:43 - mmengine - INFO - Epoch(train) [100][760/2119] lr: 4.0000e-02 eta: 10:20:30 time: 0.3769 data_time: 0.0277 memory: 5826 grad_norm: 3.1769 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.5527 loss: 2.5527 2022/10/08 04:20:49 - mmengine - INFO - Epoch(train) [100][780/2119] lr: 4.0000e-02 eta: 10:20:23 time: 0.3148 data_time: 0.0173 memory: 5826 grad_norm: 3.1395 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.7609 loss: 2.7609 2022/10/08 04:20:56 - mmengine - INFO - Epoch(train) [100][800/2119] lr: 4.0000e-02 eta: 10:20:16 time: 0.3489 data_time: 0.0262 memory: 5826 grad_norm: 3.1650 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7825 loss: 2.7825 2022/10/08 04:21:03 - mmengine - INFO - Epoch(train) [100][820/2119] lr: 4.0000e-02 eta: 10:20:09 time: 0.3677 data_time: 0.0236 memory: 5826 grad_norm: 3.1121 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.7838 loss: 2.7838 2022/10/08 04:21:10 - mmengine - INFO - Epoch(train) [100][840/2119] lr: 4.0000e-02 eta: 10:20:02 time: 0.3432 data_time: 0.0236 memory: 5826 grad_norm: 3.1344 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6661 loss: 2.6661 2022/10/08 04:21:17 - mmengine - INFO - Epoch(train) [100][860/2119] lr: 4.0000e-02 eta: 10:19:55 time: 0.3601 data_time: 0.0225 memory: 5826 grad_norm: 3.2475 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.6560 loss: 2.6560 2022/10/08 04:21:25 - mmengine - INFO - Epoch(train) [100][880/2119] lr: 4.0000e-02 eta: 10:19:49 time: 0.3744 data_time: 0.0221 memory: 5826 grad_norm: 3.1992 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5382 loss: 2.5382 2022/10/08 04:21:32 - mmengine - INFO - Epoch(train) [100][900/2119] lr: 4.0000e-02 eta: 10:19:42 time: 0.3717 data_time: 0.0239 memory: 5826 grad_norm: 3.0952 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.8070 loss: 2.8070 2022/10/08 04:21:40 - mmengine - INFO - Epoch(train) [100][920/2119] lr: 4.0000e-02 eta: 10:19:36 time: 0.3822 data_time: 0.0235 memory: 5826 grad_norm: 3.1716 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5735 loss: 2.5735 2022/10/08 04:21:47 - mmengine - INFO - Epoch(train) [100][940/2119] lr: 4.0000e-02 eta: 10:19:29 time: 0.3638 data_time: 0.0240 memory: 5826 grad_norm: 3.1486 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.7860 loss: 2.7860 2022/10/08 04:21:54 - mmengine - INFO - Epoch(train) [100][960/2119] lr: 4.0000e-02 eta: 10:19:21 time: 0.3108 data_time: 0.0249 memory: 5826 grad_norm: 3.1086 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6443 loss: 2.6443 2022/10/08 04:22:01 - mmengine - INFO - Epoch(train) [100][980/2119] lr: 4.0000e-02 eta: 10:19:15 time: 0.3938 data_time: 0.0265 memory: 5826 grad_norm: 3.1096 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.6843 loss: 2.6843 2022/10/08 04:22:08 - mmengine - INFO - Epoch(train) [100][1000/2119] lr: 4.0000e-02 eta: 10:19:08 time: 0.3122 data_time: 0.0172 memory: 5826 grad_norm: 3.1489 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.9310 loss: 2.9310 2022/10/08 04:22:15 - mmengine - INFO - Epoch(train) [100][1020/2119] lr: 4.0000e-02 eta: 10:19:01 time: 0.3838 data_time: 0.0222 memory: 5826 grad_norm: 3.1270 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6878 loss: 2.6878 2022/10/08 04:22:22 - mmengine - INFO - Epoch(train) [100][1040/2119] lr: 4.0000e-02 eta: 10:18:54 time: 0.3431 data_time: 0.0276 memory: 5826 grad_norm: 3.1551 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6459 loss: 2.6459 2022/10/08 04:22:29 - mmengine - INFO - Epoch(train) [100][1060/2119] lr: 4.0000e-02 eta: 10:18:47 time: 0.3363 data_time: 0.0194 memory: 5826 grad_norm: 3.1429 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.9345 loss: 2.9345 2022/10/08 04:22:36 - mmengine - INFO - Epoch(train) [100][1080/2119] lr: 4.0000e-02 eta: 10:18:40 time: 0.3316 data_time: 0.0221 memory: 5826 grad_norm: 3.0824 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7678 loss: 2.7678 2022/10/08 04:22:43 - mmengine - INFO - Epoch(train) [100][1100/2119] lr: 4.0000e-02 eta: 10:18:33 time: 0.3817 data_time: 0.0252 memory: 5826 grad_norm: 3.1758 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8170 loss: 2.8170 2022/10/08 04:22:50 - mmengine - INFO - Epoch(train) [100][1120/2119] lr: 4.0000e-02 eta: 10:18:26 time: 0.3123 data_time: 0.0232 memory: 5826 grad_norm: 3.1905 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7094 loss: 2.7094 2022/10/08 04:22:57 - mmengine - INFO - Epoch(train) [100][1140/2119] lr: 4.0000e-02 eta: 10:18:19 time: 0.3696 data_time: 0.0240 memory: 5826 grad_norm: 3.0831 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7082 loss: 2.7082 2022/10/08 04:23:04 - mmengine - INFO - Epoch(train) [100][1160/2119] lr: 4.0000e-02 eta: 10:18:13 time: 0.3741 data_time: 0.0232 memory: 5826 grad_norm: 3.1281 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5188 loss: 2.5188 2022/10/08 04:23:12 - mmengine - INFO - Epoch(train) [100][1180/2119] lr: 4.0000e-02 eta: 10:18:06 time: 0.3963 data_time: 0.0229 memory: 5826 grad_norm: 3.1324 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.7086 loss: 2.7086 2022/10/08 04:23:18 - mmengine - INFO - Epoch(train) [100][1200/2119] lr: 4.0000e-02 eta: 10:17:59 time: 0.2984 data_time: 0.0238 memory: 5826 grad_norm: 3.1182 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.3815 loss: 2.3815 2022/10/08 04:23:25 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 04:23:26 - mmengine - INFO - Epoch(train) [100][1220/2119] lr: 4.0000e-02 eta: 10:17:52 time: 0.3833 data_time: 0.0184 memory: 5826 grad_norm: 3.0973 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5928 loss: 2.5928 2022/10/08 04:23:32 - mmengine - INFO - Epoch(train) [100][1240/2119] lr: 4.0000e-02 eta: 10:17:45 time: 0.3138 data_time: 0.0269 memory: 5826 grad_norm: 3.1502 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6635 loss: 2.6635 2022/10/08 04:23:41 - mmengine - INFO - Epoch(train) [100][1260/2119] lr: 4.0000e-02 eta: 10:17:39 time: 0.4120 data_time: 0.0269 memory: 5826 grad_norm: 3.1857 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9992 loss: 2.9992 2022/10/08 04:23:47 - mmengine - INFO - Epoch(train) [100][1280/2119] lr: 4.0000e-02 eta: 10:17:32 time: 0.3230 data_time: 0.0217 memory: 5826 grad_norm: 3.1108 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.5082 loss: 2.5082 2022/10/08 04:23:54 - mmengine - INFO - Epoch(train) [100][1300/2119] lr: 4.0000e-02 eta: 10:17:25 time: 0.3708 data_time: 0.0221 memory: 5826 grad_norm: 3.1550 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.8251 loss: 2.8251 2022/10/08 04:24:01 - mmengine - INFO - Epoch(train) [100][1320/2119] lr: 4.0000e-02 eta: 10:17:18 time: 0.3360 data_time: 0.0192 memory: 5826 grad_norm: 3.0673 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5874 loss: 2.5874 2022/10/08 04:24:08 - mmengine - INFO - Epoch(train) [100][1340/2119] lr: 4.0000e-02 eta: 10:17:11 time: 0.3511 data_time: 0.0249 memory: 5826 grad_norm: 3.1974 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6735 loss: 2.6735 2022/10/08 04:24:15 - mmengine - INFO - Epoch(train) [100][1360/2119] lr: 4.0000e-02 eta: 10:17:04 time: 0.3526 data_time: 0.0210 memory: 5826 grad_norm: 3.0764 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7032 loss: 2.7032 2022/10/08 04:24:22 - mmengine - INFO - Epoch(train) [100][1380/2119] lr: 4.0000e-02 eta: 10:16:57 time: 0.3294 data_time: 0.0228 memory: 5826 grad_norm: 3.1459 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4715 loss: 2.4715 2022/10/08 04:24:29 - mmengine - INFO - Epoch(train) [100][1400/2119] lr: 4.0000e-02 eta: 10:16:50 time: 0.3417 data_time: 0.0216 memory: 5826 grad_norm: 3.1306 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5510 loss: 2.5510 2022/10/08 04:24:37 - mmengine - INFO - Epoch(train) [100][1420/2119] lr: 4.0000e-02 eta: 10:16:44 time: 0.3988 data_time: 0.0219 memory: 5826 grad_norm: 3.1967 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6853 loss: 2.6853 2022/10/08 04:24:43 - mmengine - INFO - Epoch(train) [100][1440/2119] lr: 4.0000e-02 eta: 10:16:36 time: 0.3296 data_time: 0.0345 memory: 5826 grad_norm: 3.0749 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4988 loss: 2.4988 2022/10/08 04:24:51 - mmengine - INFO - Epoch(train) [100][1460/2119] lr: 4.0000e-02 eta: 10:16:30 time: 0.3905 data_time: 0.0232 memory: 5826 grad_norm: 3.1604 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6341 loss: 2.6341 2022/10/08 04:24:57 - mmengine - INFO - Epoch(train) [100][1480/2119] lr: 4.0000e-02 eta: 10:16:23 time: 0.3150 data_time: 0.0252 memory: 5826 grad_norm: 3.1823 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7805 loss: 2.7805 2022/10/08 04:25:04 - mmengine - INFO - Epoch(train) [100][1500/2119] lr: 4.0000e-02 eta: 10:16:16 time: 0.3362 data_time: 0.0214 memory: 5826 grad_norm: 3.0998 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.9199 loss: 2.9199 2022/10/08 04:25:12 - mmengine - INFO - Epoch(train) [100][1520/2119] lr: 4.0000e-02 eta: 10:16:09 time: 0.3812 data_time: 0.0202 memory: 5826 grad_norm: 3.0904 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.9085 loss: 2.9085 2022/10/08 04:25:19 - mmengine - INFO - Epoch(train) [100][1540/2119] lr: 4.0000e-02 eta: 10:16:02 time: 0.3705 data_time: 0.0210 memory: 5826 grad_norm: 3.1164 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.7512 loss: 2.7512 2022/10/08 04:25:25 - mmengine - INFO - Epoch(train) [100][1560/2119] lr: 4.0000e-02 eta: 10:15:55 time: 0.2934 data_time: 0.0230 memory: 5826 grad_norm: 3.1429 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 2.6198 loss: 2.6198 2022/10/08 04:25:33 - mmengine - INFO - Epoch(train) [100][1580/2119] lr: 4.0000e-02 eta: 10:15:48 time: 0.3966 data_time: 0.0221 memory: 5826 grad_norm: 3.1974 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.6839 loss: 2.6839 2022/10/08 04:25:39 - mmengine - INFO - Epoch(train) [100][1600/2119] lr: 4.0000e-02 eta: 10:15:41 time: 0.2972 data_time: 0.0216 memory: 5826 grad_norm: 3.0924 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6635 loss: 2.6635 2022/10/08 04:25:46 - mmengine - INFO - Epoch(train) [100][1620/2119] lr: 4.0000e-02 eta: 10:15:34 time: 0.3667 data_time: 0.0348 memory: 5826 grad_norm: 3.0825 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.8739 loss: 2.8739 2022/10/08 04:25:53 - mmengine - INFO - Epoch(train) [100][1640/2119] lr: 4.0000e-02 eta: 10:15:27 time: 0.3257 data_time: 0.0224 memory: 5826 grad_norm: 3.1240 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7901 loss: 2.7901 2022/10/08 04:26:00 - mmengine - INFO - Epoch(train) [100][1660/2119] lr: 4.0000e-02 eta: 10:15:20 time: 0.3742 data_time: 0.0216 memory: 5826 grad_norm: 3.0860 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6743 loss: 2.6743 2022/10/08 04:26:07 - mmengine - INFO - Epoch(train) [100][1680/2119] lr: 4.0000e-02 eta: 10:15:14 time: 0.3580 data_time: 0.0266 memory: 5826 grad_norm: 3.1533 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7041 loss: 2.7041 2022/10/08 04:26:15 - mmengine - INFO - Epoch(train) [100][1700/2119] lr: 4.0000e-02 eta: 10:15:07 time: 0.3624 data_time: 0.0299 memory: 5826 grad_norm: 3.0811 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.7411 loss: 2.7411 2022/10/08 04:26:22 - mmengine - INFO - Epoch(train) [100][1720/2119] lr: 4.0000e-02 eta: 10:15:00 time: 0.3532 data_time: 0.0238 memory: 5826 grad_norm: 3.1164 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.7167 loss: 2.7167 2022/10/08 04:26:29 - mmengine - INFO - Epoch(train) [100][1740/2119] lr: 4.0000e-02 eta: 10:14:53 time: 0.3821 data_time: 0.0213 memory: 5826 grad_norm: 3.1203 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5971 loss: 2.5971 2022/10/08 04:26:37 - mmengine - INFO - Epoch(train) [100][1760/2119] lr: 4.0000e-02 eta: 10:14:46 time: 0.3554 data_time: 0.0258 memory: 5826 grad_norm: 3.1303 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7388 loss: 2.7388 2022/10/08 04:26:45 - mmengine - INFO - Epoch(train) [100][1780/2119] lr: 4.0000e-02 eta: 10:14:40 time: 0.4108 data_time: 0.0196 memory: 5826 grad_norm: 3.1568 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7599 loss: 2.7599 2022/10/08 04:26:51 - mmengine - INFO - Epoch(train) [100][1800/2119] lr: 4.0000e-02 eta: 10:14:33 time: 0.3302 data_time: 0.0233 memory: 5826 grad_norm: 3.1833 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6141 loss: 2.6141 2022/10/08 04:26:58 - mmengine - INFO - Epoch(train) [100][1820/2119] lr: 4.0000e-02 eta: 10:14:26 time: 0.3276 data_time: 0.0221 memory: 5826 grad_norm: 3.1116 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7127 loss: 2.7127 2022/10/08 04:27:05 - mmengine - INFO - Epoch(train) [100][1840/2119] lr: 4.0000e-02 eta: 10:14:19 time: 0.3569 data_time: 0.0272 memory: 5826 grad_norm: 3.1548 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5451 loss: 2.5451 2022/10/08 04:27:13 - mmengine - INFO - Epoch(train) [100][1860/2119] lr: 4.0000e-02 eta: 10:14:13 time: 0.3807 data_time: 0.0214 memory: 5826 grad_norm: 3.1216 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.6035 loss: 2.6035 2022/10/08 04:27:19 - mmengine - INFO - Epoch(train) [100][1880/2119] lr: 4.0000e-02 eta: 10:14:05 time: 0.3077 data_time: 0.0232 memory: 5826 grad_norm: 3.1372 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.9575 loss: 2.9575 2022/10/08 04:27:27 - mmengine - INFO - Epoch(train) [100][1900/2119] lr: 4.0000e-02 eta: 10:13:59 time: 0.3839 data_time: 0.0234 memory: 5826 grad_norm: 3.0769 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6490 loss: 2.6490 2022/10/08 04:27:33 - mmengine - INFO - Epoch(train) [100][1920/2119] lr: 4.0000e-02 eta: 10:13:52 time: 0.3330 data_time: 0.0223 memory: 5826 grad_norm: 3.1107 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.7549 loss: 2.7549 2022/10/08 04:27:41 - mmengine - INFO - Epoch(train) [100][1940/2119] lr: 4.0000e-02 eta: 10:13:45 time: 0.3991 data_time: 0.0188 memory: 5826 grad_norm: 3.1386 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.6723 loss: 2.6723 2022/10/08 04:27:48 - mmengine - INFO - Epoch(train) [100][1960/2119] lr: 4.0000e-02 eta: 10:13:38 time: 0.3323 data_time: 0.0197 memory: 5826 grad_norm: 3.1981 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5973 loss: 2.5973 2022/10/08 04:27:55 - mmengine - INFO - Epoch(train) [100][1980/2119] lr: 4.0000e-02 eta: 10:13:31 time: 0.3423 data_time: 0.0204 memory: 5826 grad_norm: 3.0918 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5500 loss: 2.5500 2022/10/08 04:28:02 - mmengine - INFO - Epoch(train) [100][2000/2119] lr: 4.0000e-02 eta: 10:13:24 time: 0.3629 data_time: 0.0247 memory: 5826 grad_norm: 3.1746 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.7318 loss: 2.7318 2022/10/08 04:28:08 - mmengine - INFO - Epoch(train) [100][2020/2119] lr: 4.0000e-02 eta: 10:13:17 time: 0.3236 data_time: 0.0247 memory: 5826 grad_norm: 3.0542 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.7483 loss: 2.7483 2022/10/08 04:28:15 - mmengine - INFO - Epoch(train) [100][2040/2119] lr: 4.0000e-02 eta: 10:13:10 time: 0.3247 data_time: 0.0258 memory: 5826 grad_norm: 3.0536 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7327 loss: 2.7327 2022/10/08 04:28:22 - mmengine - INFO - Epoch(train) [100][2060/2119] lr: 4.0000e-02 eta: 10:13:03 time: 0.3459 data_time: 0.0292 memory: 5826 grad_norm: 3.1013 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5682 loss: 2.5682 2022/10/08 04:28:29 - mmengine - INFO - Epoch(train) [100][2080/2119] lr: 4.0000e-02 eta: 10:12:56 time: 0.3537 data_time: 0.0275 memory: 5826 grad_norm: 3.2045 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.5963 loss: 2.5963 2022/10/08 04:28:36 - mmengine - INFO - Epoch(train) [100][2100/2119] lr: 4.0000e-02 eta: 10:12:49 time: 0.3628 data_time: 0.0300 memory: 5826 grad_norm: 3.1689 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.5701 loss: 2.5701 2022/10/08 04:28:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 04:28:42 - mmengine - INFO - Epoch(train) [100][2119/2119] lr: 4.0000e-02 eta: 10:12:49 time: 0.3074 data_time: 0.0190 memory: 5826 grad_norm: 3.1519 top1_acc: 0.4000 top5_acc: 0.5000 loss_cls: 2.6106 loss: 2.6106 2022/10/08 04:28:42 - mmengine - INFO - Saving checkpoint at 100 epochs 2022/10/08 04:28:54 - mmengine - INFO - Epoch(val) [100][20/137] eta: 0:00:48 time: 0.4183 data_time: 0.3507 memory: 1241 2022/10/08 04:29:00 - mmengine - INFO - Epoch(val) [100][40/137] eta: 0:00:27 time: 0.2797 data_time: 0.2132 memory: 1241 2022/10/08 04:29:07 - mmengine - INFO - Epoch(val) [100][60/137] eta: 0:00:28 time: 0.3662 data_time: 0.2999 memory: 1241 2022/10/08 04:29:13 - mmengine - INFO - Epoch(val) [100][80/137] eta: 0:00:16 time: 0.2836 data_time: 0.2167 memory: 1241 2022/10/08 04:29:20 - mmengine - INFO - Epoch(val) [100][100/137] eta: 0:00:12 time: 0.3369 data_time: 0.2699 memory: 1241 2022/10/08 04:29:25 - mmengine - INFO - Epoch(val) [100][120/137] eta: 0:00:04 time: 0.2526 data_time: 0.1873 memory: 1241 2022/10/08 04:29:34 - mmengine - INFO - Epoch(val) [100][137/137] acc/top1: 0.4284 acc/top5: 0.6715 acc/mean1: 0.4282 2022/10/08 04:29:44 - mmengine - INFO - Epoch(train) [101][20/2119] lr: 4.0000e-03 eta: 10:12:34 time: 0.4995 data_time: 0.1699 memory: 5826 grad_norm: 3.1125 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.7189 loss: 2.7189 2022/10/08 04:29:51 - mmengine - INFO - Epoch(train) [101][40/2119] lr: 4.0000e-03 eta: 10:12:27 time: 0.3451 data_time: 0.0290 memory: 5826 grad_norm: 3.0256 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4126 loss: 2.4126 2022/10/08 04:29:59 - mmengine - INFO - Epoch(train) [101][60/2119] lr: 4.0000e-03 eta: 10:12:20 time: 0.3643 data_time: 0.0201 memory: 5826 grad_norm: 3.0118 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5950 loss: 2.5950 2022/10/08 04:30:06 - mmengine - INFO - Epoch(train) [101][80/2119] lr: 4.0000e-03 eta: 10:12:13 time: 0.3536 data_time: 0.0166 memory: 5826 grad_norm: 3.0320 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.6813 loss: 2.6813 2022/10/08 04:30:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 04:30:13 - mmengine - INFO - Epoch(train) [101][100/2119] lr: 4.0000e-03 eta: 10:12:07 time: 0.3517 data_time: 0.0243 memory: 5826 grad_norm: 3.0071 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.3600 loss: 2.3600 2022/10/08 04:30:19 - mmengine - INFO - Epoch(train) [101][120/2119] lr: 4.0000e-03 eta: 10:11:59 time: 0.3343 data_time: 0.0224 memory: 5826 grad_norm: 3.0314 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.4081 loss: 2.4081 2022/10/08 04:30:28 - mmengine - INFO - Epoch(train) [101][140/2119] lr: 4.0000e-03 eta: 10:11:53 time: 0.4116 data_time: 0.0227 memory: 5826 grad_norm: 3.0122 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.5359 loss: 2.5359 2022/10/08 04:30:34 - mmengine - INFO - Epoch(train) [101][160/2119] lr: 4.0000e-03 eta: 10:11:46 time: 0.3106 data_time: 0.0201 memory: 5826 grad_norm: 2.9669 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1425 loss: 2.1425 2022/10/08 04:30:42 - mmengine - INFO - Epoch(train) [101][180/2119] lr: 4.0000e-03 eta: 10:11:39 time: 0.3894 data_time: 0.0265 memory: 5826 grad_norm: 3.0393 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6323 loss: 2.6323 2022/10/08 04:30:48 - mmengine - INFO - Epoch(train) [101][200/2119] lr: 4.0000e-03 eta: 10:11:32 time: 0.3056 data_time: 0.0235 memory: 5826 grad_norm: 3.0808 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.6642 loss: 2.6642 2022/10/08 04:30:55 - mmengine - INFO - Epoch(train) [101][220/2119] lr: 4.0000e-03 eta: 10:11:25 time: 0.3460 data_time: 0.0215 memory: 5826 grad_norm: 3.0119 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6342 loss: 2.6342 2022/10/08 04:31:02 - mmengine - INFO - Epoch(train) [101][240/2119] lr: 4.0000e-03 eta: 10:11:18 time: 0.3537 data_time: 0.0223 memory: 5826 grad_norm: 2.9961 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.4286 loss: 2.4286 2022/10/08 04:31:09 - mmengine - INFO - Epoch(train) [101][260/2119] lr: 4.0000e-03 eta: 10:11:11 time: 0.3722 data_time: 0.0219 memory: 5826 grad_norm: 3.0338 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.3415 loss: 2.3415 2022/10/08 04:31:16 - mmengine - INFO - Epoch(train) [101][280/2119] lr: 4.0000e-03 eta: 10:11:04 time: 0.3170 data_time: 0.0309 memory: 5826 grad_norm: 3.0652 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.5330 loss: 2.5330 2022/10/08 04:31:23 - mmengine - INFO - Epoch(train) [101][300/2119] lr: 4.0000e-03 eta: 10:10:58 time: 0.3919 data_time: 0.0222 memory: 5826 grad_norm: 3.0452 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.5054 loss: 2.5054 2022/10/08 04:31:30 - mmengine - INFO - Epoch(train) [101][320/2119] lr: 4.0000e-03 eta: 10:10:51 time: 0.3281 data_time: 0.0217 memory: 5826 grad_norm: 3.0547 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.2250 loss: 2.2250 2022/10/08 04:31:37 - mmengine - INFO - Epoch(train) [101][340/2119] lr: 4.0000e-03 eta: 10:10:44 time: 0.3659 data_time: 0.0185 memory: 5826 grad_norm: 3.0577 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5558 loss: 2.5558 2022/10/08 04:31:45 - mmengine - INFO - Epoch(train) [101][360/2119] lr: 4.0000e-03 eta: 10:10:37 time: 0.3752 data_time: 0.0210 memory: 5826 grad_norm: 3.0400 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.3201 loss: 2.3201 2022/10/08 04:31:52 - mmengine - INFO - Epoch(train) [101][380/2119] lr: 4.0000e-03 eta: 10:10:31 time: 0.3753 data_time: 0.0249 memory: 5826 grad_norm: 3.0756 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4078 loss: 2.4078 2022/10/08 04:31:59 - mmengine - INFO - Epoch(train) [101][400/2119] lr: 4.0000e-03 eta: 10:10:24 time: 0.3440 data_time: 0.0218 memory: 5826 grad_norm: 3.0216 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.2176 loss: 2.2176 2022/10/08 04:32:07 - mmengine - INFO - Epoch(train) [101][420/2119] lr: 4.0000e-03 eta: 10:10:17 time: 0.3831 data_time: 0.0293 memory: 5826 grad_norm: 3.0273 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.4893 loss: 2.4893 2022/10/08 04:32:13 - mmengine - INFO - Epoch(train) [101][440/2119] lr: 4.0000e-03 eta: 10:10:10 time: 0.3102 data_time: 0.0239 memory: 5826 grad_norm: 3.0970 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5736 loss: 2.5736 2022/10/08 04:32:22 - mmengine - INFO - Epoch(train) [101][460/2119] lr: 4.0000e-03 eta: 10:10:04 time: 0.4429 data_time: 0.0226 memory: 5826 grad_norm: 3.1043 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4166 loss: 2.4166 2022/10/08 04:32:28 - mmengine - INFO - Epoch(train) [101][480/2119] lr: 4.0000e-03 eta: 10:09:56 time: 0.2992 data_time: 0.0240 memory: 5826 grad_norm: 3.0720 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.4797 loss: 2.4797 2022/10/08 04:32:35 - mmengine - INFO - Epoch(train) [101][500/2119] lr: 4.0000e-03 eta: 10:09:50 time: 0.3636 data_time: 0.0200 memory: 5826 grad_norm: 3.0667 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4183 loss: 2.4183 2022/10/08 04:32:42 - mmengine - INFO - Epoch(train) [101][520/2119] lr: 4.0000e-03 eta: 10:09:43 time: 0.3630 data_time: 0.0225 memory: 5826 grad_norm: 3.0687 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2835 loss: 2.2835 2022/10/08 04:32:49 - mmengine - INFO - Epoch(train) [101][540/2119] lr: 4.0000e-03 eta: 10:09:36 time: 0.3406 data_time: 0.0211 memory: 5826 grad_norm: 3.0717 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.2601 loss: 2.2601 2022/10/08 04:32:56 - mmengine - INFO - Epoch(train) [101][560/2119] lr: 4.0000e-03 eta: 10:09:29 time: 0.3544 data_time: 0.0217 memory: 5826 grad_norm: 3.1142 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6103 loss: 2.6103 2022/10/08 04:33:05 - mmengine - INFO - Epoch(train) [101][580/2119] lr: 4.0000e-03 eta: 10:09:23 time: 0.4096 data_time: 0.0235 memory: 5826 grad_norm: 3.0894 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3419 loss: 2.3419 2022/10/08 04:33:11 - mmengine - INFO - Epoch(train) [101][600/2119] lr: 4.0000e-03 eta: 10:09:15 time: 0.3184 data_time: 0.0192 memory: 5826 grad_norm: 3.0510 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3498 loss: 2.3498 2022/10/08 04:33:18 - mmengine - INFO - Epoch(train) [101][620/2119] lr: 4.0000e-03 eta: 10:09:09 time: 0.3772 data_time: 0.0260 memory: 5826 grad_norm: 3.0834 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3589 loss: 2.3589 2022/10/08 04:33:25 - mmengine - INFO - Epoch(train) [101][640/2119] lr: 4.0000e-03 eta: 10:09:02 time: 0.3386 data_time: 0.0274 memory: 5826 grad_norm: 3.1207 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2409 loss: 2.2409 2022/10/08 04:33:34 - mmengine - INFO - Epoch(train) [101][660/2119] lr: 4.0000e-03 eta: 10:08:56 time: 0.4258 data_time: 0.0229 memory: 5826 grad_norm: 3.0883 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.5605 loss: 2.5605 2022/10/08 04:33:40 - mmengine - INFO - Epoch(train) [101][680/2119] lr: 4.0000e-03 eta: 10:08:48 time: 0.3343 data_time: 0.0187 memory: 5826 grad_norm: 3.1277 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.2083 loss: 2.2083 2022/10/08 04:33:48 - mmengine - INFO - Epoch(train) [101][700/2119] lr: 4.0000e-03 eta: 10:08:42 time: 0.3706 data_time: 0.0201 memory: 5826 grad_norm: 3.1029 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.5652 loss: 2.5652 2022/10/08 04:33:54 - mmengine - INFO - Epoch(train) [101][720/2119] lr: 4.0000e-03 eta: 10:08:34 time: 0.3166 data_time: 0.0260 memory: 5826 grad_norm: 3.1132 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5032 loss: 2.5032 2022/10/08 04:34:02 - mmengine - INFO - Epoch(train) [101][740/2119] lr: 4.0000e-03 eta: 10:08:28 time: 0.3773 data_time: 0.0224 memory: 5826 grad_norm: 3.0524 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.1858 loss: 2.1858 2022/10/08 04:34:08 - mmengine - INFO - Epoch(train) [101][760/2119] lr: 4.0000e-03 eta: 10:08:21 time: 0.3124 data_time: 0.0263 memory: 5826 grad_norm: 3.0602 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0849 loss: 2.0849 2022/10/08 04:34:16 - mmengine - INFO - Epoch(train) [101][780/2119] lr: 4.0000e-03 eta: 10:08:14 time: 0.3990 data_time: 0.0220 memory: 5826 grad_norm: 3.1295 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5222 loss: 2.5222 2022/10/08 04:34:23 - mmengine - INFO - Epoch(train) [101][800/2119] lr: 4.0000e-03 eta: 10:08:07 time: 0.3529 data_time: 0.0260 memory: 5826 grad_norm: 3.1365 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3279 loss: 2.3279 2022/10/08 04:34:30 - mmengine - INFO - Epoch(train) [101][820/2119] lr: 4.0000e-03 eta: 10:08:01 time: 0.3690 data_time: 0.0266 memory: 5826 grad_norm: 3.0758 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.3512 loss: 2.3512 2022/10/08 04:34:37 - mmengine - INFO - Epoch(train) [101][840/2119] lr: 4.0000e-03 eta: 10:07:53 time: 0.3129 data_time: 0.0201 memory: 5826 grad_norm: 3.1370 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.2728 loss: 2.2728 2022/10/08 04:34:45 - mmengine - INFO - Epoch(train) [101][860/2119] lr: 4.0000e-03 eta: 10:07:47 time: 0.3922 data_time: 0.0194 memory: 5826 grad_norm: 3.1315 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.3204 loss: 2.3204 2022/10/08 04:34:51 - mmengine - INFO - Epoch(train) [101][880/2119] lr: 4.0000e-03 eta: 10:07:40 time: 0.3230 data_time: 0.0208 memory: 5826 grad_norm: 3.1658 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.5854 loss: 2.5854 2022/10/08 04:34:58 - mmengine - INFO - Epoch(train) [101][900/2119] lr: 4.0000e-03 eta: 10:07:33 time: 0.3561 data_time: 0.0232 memory: 5826 grad_norm: 3.1835 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2896 loss: 2.2896 2022/10/08 04:35:06 - mmengine - INFO - Epoch(train) [101][920/2119] lr: 4.0000e-03 eta: 10:07:26 time: 0.3658 data_time: 0.0222 memory: 5826 grad_norm: 3.1611 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.3322 loss: 2.3322 2022/10/08 04:35:13 - mmengine - INFO - Epoch(train) [101][940/2119] lr: 4.0000e-03 eta: 10:07:19 time: 0.3751 data_time: 0.0196 memory: 5826 grad_norm: 3.1681 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.1416 loss: 2.1416 2022/10/08 04:35:19 - mmengine - INFO - Epoch(train) [101][960/2119] lr: 4.0000e-03 eta: 10:07:12 time: 0.3096 data_time: 0.0207 memory: 5826 grad_norm: 3.1553 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2213 loss: 2.2213 2022/10/08 04:35:27 - mmengine - INFO - Epoch(train) [101][980/2119] lr: 4.0000e-03 eta: 10:07:06 time: 0.3996 data_time: 0.0208 memory: 5826 grad_norm: 3.1347 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 2.3214 loss: 2.3214 2022/10/08 04:35:33 - mmengine - INFO - Epoch(train) [101][1000/2119] lr: 4.0000e-03 eta: 10:06:58 time: 0.3130 data_time: 0.0236 memory: 5826 grad_norm: 3.1197 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.2415 loss: 2.2415 2022/10/08 04:35:41 - mmengine - INFO - Epoch(train) [101][1020/2119] lr: 4.0000e-03 eta: 10:06:52 time: 0.3797 data_time: 0.0225 memory: 5826 grad_norm: 3.1492 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4161 loss: 2.4161 2022/10/08 04:35:49 - mmengine - INFO - Epoch(train) [101][1040/2119] lr: 4.0000e-03 eta: 10:06:45 time: 0.3726 data_time: 0.0271 memory: 5826 grad_norm: 3.1612 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2960 loss: 2.2960 2022/10/08 04:35:55 - mmengine - INFO - Epoch(train) [101][1060/2119] lr: 4.0000e-03 eta: 10:06:38 time: 0.3450 data_time: 0.0172 memory: 5826 grad_norm: 3.2023 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2020 loss: 2.2020 2022/10/08 04:36:02 - mmengine - INFO - Epoch(train) [101][1080/2119] lr: 4.0000e-03 eta: 10:06:31 time: 0.3336 data_time: 0.0259 memory: 5826 grad_norm: 3.1403 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2189 loss: 2.2189 2022/10/08 04:36:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 04:36:09 - mmengine - INFO - Epoch(train) [101][1100/2119] lr: 4.0000e-03 eta: 10:06:24 time: 0.3407 data_time: 0.0200 memory: 5826 grad_norm: 3.1331 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5562 loss: 2.5562 2022/10/08 04:36:16 - mmengine - INFO - Epoch(train) [101][1120/2119] lr: 4.0000e-03 eta: 10:06:17 time: 0.3658 data_time: 0.0196 memory: 5826 grad_norm: 3.1809 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1320 loss: 2.1320 2022/10/08 04:36:23 - mmengine - INFO - Epoch(train) [101][1140/2119] lr: 4.0000e-03 eta: 10:06:10 time: 0.3554 data_time: 0.0185 memory: 5826 grad_norm: 3.1775 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 2.3939 loss: 2.3939 2022/10/08 04:36:31 - mmengine - INFO - Epoch(train) [101][1160/2119] lr: 4.0000e-03 eta: 10:06:04 time: 0.3661 data_time: 0.0217 memory: 5826 grad_norm: 3.1654 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0225 loss: 2.0225 2022/10/08 04:36:37 - mmengine - INFO - Epoch(train) [101][1180/2119] lr: 4.0000e-03 eta: 10:05:56 time: 0.3018 data_time: 0.0215 memory: 5826 grad_norm: 3.1683 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.3710 loss: 2.3710 2022/10/08 04:36:45 - mmengine - INFO - Epoch(train) [101][1200/2119] lr: 4.0000e-03 eta: 10:05:50 time: 0.4139 data_time: 0.0241 memory: 5826 grad_norm: 3.1235 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.4627 loss: 2.4627 2022/10/08 04:36:52 - mmengine - INFO - Epoch(train) [101][1220/2119] lr: 4.0000e-03 eta: 10:05:43 time: 0.3439 data_time: 0.0202 memory: 5826 grad_norm: 3.1186 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4153 loss: 2.4153 2022/10/08 04:37:00 - mmengine - INFO - Epoch(train) [101][1240/2119] lr: 4.0000e-03 eta: 10:05:36 time: 0.3791 data_time: 0.0250 memory: 5826 grad_norm: 3.1383 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.3276 loss: 2.3276 2022/10/08 04:37:06 - mmengine - INFO - Epoch(train) [101][1260/2119] lr: 4.0000e-03 eta: 10:05:29 time: 0.3439 data_time: 0.0214 memory: 5826 grad_norm: 3.1191 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.3135 loss: 2.3135 2022/10/08 04:37:14 - mmengine - INFO - Epoch(train) [101][1280/2119] lr: 4.0000e-03 eta: 10:05:23 time: 0.3712 data_time: 0.0219 memory: 5826 grad_norm: 3.2236 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.3717 loss: 2.3717 2022/10/08 04:37:20 - mmengine - INFO - Epoch(train) [101][1300/2119] lr: 4.0000e-03 eta: 10:05:15 time: 0.2882 data_time: 0.0179 memory: 5826 grad_norm: 3.1641 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.3990 loss: 2.3990 2022/10/08 04:37:27 - mmengine - INFO - Epoch(train) [101][1320/2119] lr: 4.0000e-03 eta: 10:05:08 time: 0.3621 data_time: 0.0298 memory: 5826 grad_norm: 3.1610 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3766 loss: 2.3766 2022/10/08 04:37:34 - mmengine - INFO - Epoch(train) [101][1340/2119] lr: 4.0000e-03 eta: 10:05:02 time: 0.3672 data_time: 0.0225 memory: 5826 grad_norm: 3.1630 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2139 loss: 2.2139 2022/10/08 04:37:41 - mmengine - INFO - Epoch(train) [101][1360/2119] lr: 4.0000e-03 eta: 10:04:54 time: 0.3196 data_time: 0.0230 memory: 5826 grad_norm: 3.2271 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.3984 loss: 2.3984 2022/10/08 04:37:47 - mmengine - INFO - Epoch(train) [101][1380/2119] lr: 4.0000e-03 eta: 10:04:47 time: 0.3389 data_time: 0.0177 memory: 5826 grad_norm: 3.1416 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5234 loss: 2.5234 2022/10/08 04:37:55 - mmengine - INFO - Epoch(train) [101][1400/2119] lr: 4.0000e-03 eta: 10:04:41 time: 0.3732 data_time: 0.0223 memory: 5826 grad_norm: 3.1130 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.2638 loss: 2.2638 2022/10/08 04:38:02 - mmengine - INFO - Epoch(train) [101][1420/2119] lr: 4.0000e-03 eta: 10:04:34 time: 0.3423 data_time: 0.0205 memory: 5826 grad_norm: 3.1860 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1306 loss: 2.1306 2022/10/08 04:38:09 - mmengine - INFO - Epoch(train) [101][1440/2119] lr: 4.0000e-03 eta: 10:04:27 time: 0.3456 data_time: 0.0222 memory: 5826 grad_norm: 3.2356 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4942 loss: 2.4942 2022/10/08 04:38:16 - mmengine - INFO - Epoch(train) [101][1460/2119] lr: 4.0000e-03 eta: 10:04:20 time: 0.3763 data_time: 0.0212 memory: 5826 grad_norm: 3.1402 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.1855 loss: 2.1855 2022/10/08 04:38:23 - mmengine - INFO - Epoch(train) [101][1480/2119] lr: 4.0000e-03 eta: 10:04:13 time: 0.3297 data_time: 0.0303 memory: 5826 grad_norm: 3.2218 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.3533 loss: 2.3533 2022/10/08 04:38:30 - mmengine - INFO - Epoch(train) [101][1500/2119] lr: 4.0000e-03 eta: 10:04:06 time: 0.3670 data_time: 0.0163 memory: 5826 grad_norm: 3.1434 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.2525 loss: 2.2525 2022/10/08 04:38:36 - mmengine - INFO - Epoch(train) [101][1520/2119] lr: 4.0000e-03 eta: 10:03:59 time: 0.3129 data_time: 0.0196 memory: 5826 grad_norm: 3.1433 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.3693 loss: 2.3693 2022/10/08 04:38:45 - mmengine - INFO - Epoch(train) [101][1540/2119] lr: 4.0000e-03 eta: 10:03:53 time: 0.4092 data_time: 0.0173 memory: 5826 grad_norm: 3.1598 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.2464 loss: 2.2464 2022/10/08 04:38:51 - mmengine - INFO - Epoch(train) [101][1560/2119] lr: 4.0000e-03 eta: 10:03:46 time: 0.3262 data_time: 0.0203 memory: 5826 grad_norm: 3.1693 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4219 loss: 2.4219 2022/10/08 04:38:59 - mmengine - INFO - Epoch(train) [101][1580/2119] lr: 4.0000e-03 eta: 10:03:39 time: 0.3702 data_time: 0.0220 memory: 5826 grad_norm: 3.1794 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.2437 loss: 2.2437 2022/10/08 04:39:05 - mmengine - INFO - Epoch(train) [101][1600/2119] lr: 4.0000e-03 eta: 10:03:32 time: 0.3458 data_time: 0.0213 memory: 5826 grad_norm: 3.1272 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.3043 loss: 2.3043 2022/10/08 04:39:13 - mmengine - INFO - Epoch(train) [101][1620/2119] lr: 4.0000e-03 eta: 10:03:25 time: 0.3700 data_time: 0.0208 memory: 5826 grad_norm: 3.2658 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1537 loss: 2.1537 2022/10/08 04:39:19 - mmengine - INFO - Epoch(train) [101][1640/2119] lr: 4.0000e-03 eta: 10:03:18 time: 0.3182 data_time: 0.0212 memory: 5826 grad_norm: 3.2017 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4594 loss: 2.4594 2022/10/08 04:39:27 - mmengine - INFO - Epoch(train) [101][1660/2119] lr: 4.0000e-03 eta: 10:03:11 time: 0.3706 data_time: 0.0205 memory: 5826 grad_norm: 3.2170 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5893 loss: 2.5893 2022/10/08 04:39:33 - mmengine - INFO - Epoch(train) [101][1680/2119] lr: 4.0000e-03 eta: 10:03:04 time: 0.3122 data_time: 0.0230 memory: 5826 grad_norm: 3.1801 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1557 loss: 2.1557 2022/10/08 04:39:40 - mmengine - INFO - Epoch(train) [101][1700/2119] lr: 4.0000e-03 eta: 10:02:57 time: 0.3797 data_time: 0.0228 memory: 5826 grad_norm: 3.1900 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0929 loss: 2.0929 2022/10/08 04:39:48 - mmengine - INFO - Epoch(train) [101][1720/2119] lr: 4.0000e-03 eta: 10:02:50 time: 0.3561 data_time: 0.0241 memory: 5826 grad_norm: 3.1747 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3752 loss: 2.3752 2022/10/08 04:39:55 - mmengine - INFO - Epoch(train) [101][1740/2119] lr: 4.0000e-03 eta: 10:02:44 time: 0.3712 data_time: 0.0226 memory: 5826 grad_norm: 3.1315 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.1364 loss: 2.1364 2022/10/08 04:40:02 - mmengine - INFO - Epoch(train) [101][1760/2119] lr: 4.0000e-03 eta: 10:02:37 time: 0.3428 data_time: 0.0269 memory: 5826 grad_norm: 3.1406 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.1484 loss: 2.1484 2022/10/08 04:40:09 - mmengine - INFO - Epoch(train) [101][1780/2119] lr: 4.0000e-03 eta: 10:02:30 time: 0.3617 data_time: 0.0210 memory: 5826 grad_norm: 3.2063 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1292 loss: 2.1292 2022/10/08 04:40:15 - mmengine - INFO - Epoch(train) [101][1800/2119] lr: 4.0000e-03 eta: 10:02:22 time: 0.2788 data_time: 0.0205 memory: 5826 grad_norm: 3.2091 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0736 loss: 2.0736 2022/10/08 04:40:22 - mmengine - INFO - Epoch(train) [101][1820/2119] lr: 4.0000e-03 eta: 10:02:16 time: 0.3837 data_time: 0.0249 memory: 5826 grad_norm: 3.2195 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4179 loss: 2.4179 2022/10/08 04:40:30 - mmengine - INFO - Epoch(train) [101][1840/2119] lr: 4.0000e-03 eta: 10:02:09 time: 0.3560 data_time: 0.0258 memory: 5826 grad_norm: 3.2114 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4208 loss: 2.4208 2022/10/08 04:40:37 - mmengine - INFO - Epoch(train) [101][1860/2119] lr: 4.0000e-03 eta: 10:02:02 time: 0.3712 data_time: 0.0183 memory: 5826 grad_norm: 3.2095 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4391 loss: 2.4391 2022/10/08 04:40:44 - mmengine - INFO - Epoch(train) [101][1880/2119] lr: 4.0000e-03 eta: 10:01:55 time: 0.3355 data_time: 0.0240 memory: 5826 grad_norm: 3.1653 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4666 loss: 2.4666 2022/10/08 04:40:51 - mmengine - INFO - Epoch(train) [101][1900/2119] lr: 4.0000e-03 eta: 10:01:48 time: 0.3477 data_time: 0.0202 memory: 5826 grad_norm: 3.1541 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.0498 loss: 2.0498 2022/10/08 04:40:57 - mmengine - INFO - Epoch(train) [101][1920/2119] lr: 4.0000e-03 eta: 10:01:41 time: 0.3244 data_time: 0.0213 memory: 5826 grad_norm: 3.2201 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.3222 loss: 2.3222 2022/10/08 04:41:05 - mmengine - INFO - Epoch(train) [101][1940/2119] lr: 4.0000e-03 eta: 10:01:35 time: 0.4112 data_time: 0.0191 memory: 5826 grad_norm: 3.1643 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.0823 loss: 2.0823 2022/10/08 04:41:12 - mmengine - INFO - Epoch(train) [101][1960/2119] lr: 4.0000e-03 eta: 10:01:28 time: 0.3266 data_time: 0.0251 memory: 5826 grad_norm: 3.1713 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1878 loss: 2.1878 2022/10/08 04:41:19 - mmengine - INFO - Epoch(train) [101][1980/2119] lr: 4.0000e-03 eta: 10:01:21 time: 0.3505 data_time: 0.0215 memory: 5826 grad_norm: 3.2271 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.3244 loss: 2.3244 2022/10/08 04:41:26 - mmengine - INFO - Epoch(train) [101][2000/2119] lr: 4.0000e-03 eta: 10:01:14 time: 0.3406 data_time: 0.0261 memory: 5826 grad_norm: 3.1940 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1707 loss: 2.1707 2022/10/08 04:41:33 - mmengine - INFO - Epoch(train) [101][2020/2119] lr: 4.0000e-03 eta: 10:01:07 time: 0.3575 data_time: 0.0207 memory: 5826 grad_norm: 3.1898 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.3600 loss: 2.3600 2022/10/08 04:41:39 - mmengine - INFO - Epoch(train) [101][2040/2119] lr: 4.0000e-03 eta: 10:01:00 time: 0.3102 data_time: 0.0241 memory: 5826 grad_norm: 3.1903 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2985 loss: 2.2985 2022/10/08 04:41:46 - mmengine - INFO - Epoch(train) [101][2060/2119] lr: 4.0000e-03 eta: 10:00:53 time: 0.3575 data_time: 0.0191 memory: 5826 grad_norm: 3.1942 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1343 loss: 2.1343 2022/10/08 04:41:53 - mmengine - INFO - Epoch(train) [101][2080/2119] lr: 4.0000e-03 eta: 10:00:46 time: 0.3351 data_time: 0.0239 memory: 5826 grad_norm: 3.2454 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5118 loss: 2.5118 2022/10/08 04:42:00 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 04:42:00 - mmengine - INFO - Epoch(train) [101][2100/2119] lr: 4.0000e-03 eta: 10:00:39 time: 0.3653 data_time: 0.0208 memory: 5826 grad_norm: 3.2165 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2802 loss: 2.2802 2022/10/08 04:42:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 04:42:07 - mmengine - INFO - Epoch(train) [101][2119/2119] lr: 4.0000e-03 eta: 10:00:39 time: 0.3463 data_time: 0.0230 memory: 5826 grad_norm: 3.2567 top1_acc: 0.3000 top5_acc: 0.6000 loss_cls: 2.2764 loss: 2.2764 2022/10/08 04:42:16 - mmengine - INFO - Epoch(train) [102][20/2119] lr: 4.0000e-03 eta: 10:00:24 time: 0.4879 data_time: 0.1168 memory: 5826 grad_norm: 3.1974 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.2593 loss: 2.2593 2022/10/08 04:42:23 - mmengine - INFO - Epoch(train) [102][40/2119] lr: 4.0000e-03 eta: 10:00:17 time: 0.3493 data_time: 0.0219 memory: 5826 grad_norm: 3.1945 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3681 loss: 2.3681 2022/10/08 04:42:31 - mmengine - INFO - Epoch(train) [102][60/2119] lr: 4.0000e-03 eta: 10:00:10 time: 0.3551 data_time: 0.0232 memory: 5826 grad_norm: 3.2434 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1578 loss: 2.1578 2022/10/08 04:42:37 - mmengine - INFO - Epoch(train) [102][80/2119] lr: 4.0000e-03 eta: 10:00:02 time: 0.2999 data_time: 0.0185 memory: 5826 grad_norm: 3.2286 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.3042 loss: 2.3042 2022/10/08 04:42:44 - mmengine - INFO - Epoch(train) [102][100/2119] lr: 4.0000e-03 eta: 9:59:56 time: 0.3849 data_time: 0.0191 memory: 5826 grad_norm: 3.1888 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4642 loss: 2.4642 2022/10/08 04:42:51 - mmengine - INFO - Epoch(train) [102][120/2119] lr: 4.0000e-03 eta: 9:59:49 time: 0.3428 data_time: 0.0196 memory: 5826 grad_norm: 3.1982 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3132 loss: 2.3132 2022/10/08 04:42:58 - mmengine - INFO - Epoch(train) [102][140/2119] lr: 4.0000e-03 eta: 9:59:42 time: 0.3410 data_time: 0.0228 memory: 5826 grad_norm: 3.2194 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3190 loss: 2.3190 2022/10/08 04:43:04 - mmengine - INFO - Epoch(train) [102][160/2119] lr: 4.0000e-03 eta: 9:59:35 time: 0.3125 data_time: 0.0232 memory: 5826 grad_norm: 3.1949 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.2512 loss: 2.2512 2022/10/08 04:43:12 - mmengine - INFO - Epoch(train) [102][180/2119] lr: 4.0000e-03 eta: 9:59:28 time: 0.3975 data_time: 0.0278 memory: 5826 grad_norm: 3.1649 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.2403 loss: 2.2403 2022/10/08 04:43:19 - mmengine - INFO - Epoch(train) [102][200/2119] lr: 4.0000e-03 eta: 9:59:21 time: 0.3284 data_time: 0.0227 memory: 5826 grad_norm: 3.2309 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.2121 loss: 2.2121 2022/10/08 04:43:25 - mmengine - INFO - Epoch(train) [102][220/2119] lr: 4.0000e-03 eta: 9:59:14 time: 0.3217 data_time: 0.0185 memory: 5826 grad_norm: 3.2436 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.3672 loss: 2.3672 2022/10/08 04:43:33 - mmengine - INFO - Epoch(train) [102][240/2119] lr: 4.0000e-03 eta: 9:59:07 time: 0.3694 data_time: 0.0250 memory: 5826 grad_norm: 3.2160 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.3680 loss: 2.3680 2022/10/08 04:43:39 - mmengine - INFO - Epoch(train) [102][260/2119] lr: 4.0000e-03 eta: 9:59:00 time: 0.3164 data_time: 0.0182 memory: 5826 grad_norm: 3.2807 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2822 loss: 2.2822 2022/10/08 04:43:46 - mmengine - INFO - Epoch(train) [102][280/2119] lr: 4.0000e-03 eta: 9:58:53 time: 0.3655 data_time: 0.0220 memory: 5826 grad_norm: 3.2359 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9693 loss: 1.9693 2022/10/08 04:43:53 - mmengine - INFO - Epoch(train) [102][300/2119] lr: 4.0000e-03 eta: 9:58:46 time: 0.3390 data_time: 0.0253 memory: 5826 grad_norm: 3.2043 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4350 loss: 2.4350 2022/10/08 04:44:00 - mmengine - INFO - Epoch(train) [102][320/2119] lr: 4.0000e-03 eta: 9:58:39 time: 0.3495 data_time: 0.0216 memory: 5826 grad_norm: 3.2546 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.1977 loss: 2.1977 2022/10/08 04:44:07 - mmengine - INFO - Epoch(train) [102][340/2119] lr: 4.0000e-03 eta: 9:58:32 time: 0.3478 data_time: 0.0272 memory: 5826 grad_norm: 3.2245 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.3708 loss: 2.3708 2022/10/08 04:44:15 - mmengine - INFO - Epoch(train) [102][360/2119] lr: 4.0000e-03 eta: 9:58:26 time: 0.3835 data_time: 0.0232 memory: 5826 grad_norm: 3.2251 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1131 loss: 2.1131 2022/10/08 04:44:21 - mmengine - INFO - Epoch(train) [102][380/2119] lr: 4.0000e-03 eta: 9:58:19 time: 0.3328 data_time: 0.0290 memory: 5826 grad_norm: 3.2888 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2185 loss: 2.2185 2022/10/08 04:44:29 - mmengine - INFO - Epoch(train) [102][400/2119] lr: 4.0000e-03 eta: 9:58:12 time: 0.3792 data_time: 0.0190 memory: 5826 grad_norm: 3.2756 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9720 loss: 1.9720 2022/10/08 04:44:35 - mmengine - INFO - Epoch(train) [102][420/2119] lr: 4.0000e-03 eta: 9:58:05 time: 0.3103 data_time: 0.0198 memory: 5826 grad_norm: 3.2710 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3295 loss: 2.3295 2022/10/08 04:44:43 - mmengine - INFO - Epoch(train) [102][440/2119] lr: 4.0000e-03 eta: 9:57:58 time: 0.4173 data_time: 0.0237 memory: 5826 grad_norm: 3.2245 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.3649 loss: 2.3649 2022/10/08 04:44:51 - mmengine - INFO - Epoch(train) [102][460/2119] lr: 4.0000e-03 eta: 9:57:52 time: 0.3682 data_time: 0.0187 memory: 5826 grad_norm: 3.2575 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.2526 loss: 2.2526 2022/10/08 04:44:58 - mmengine - INFO - Epoch(train) [102][480/2119] lr: 4.0000e-03 eta: 9:57:45 time: 0.3705 data_time: 0.0262 memory: 5826 grad_norm: 3.2341 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1034 loss: 2.1034 2022/10/08 04:45:06 - mmengine - INFO - Epoch(train) [102][500/2119] lr: 4.0000e-03 eta: 9:57:38 time: 0.3665 data_time: 0.0188 memory: 5826 grad_norm: 3.2848 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.3724 loss: 2.3724 2022/10/08 04:45:13 - mmengine - INFO - Epoch(train) [102][520/2119] lr: 4.0000e-03 eta: 9:57:31 time: 0.3486 data_time: 0.0242 memory: 5826 grad_norm: 3.2088 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.2140 loss: 2.2140 2022/10/08 04:45:20 - mmengine - INFO - Epoch(train) [102][540/2119] lr: 4.0000e-03 eta: 9:57:24 time: 0.3515 data_time: 0.0232 memory: 5826 grad_norm: 3.2496 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.3041 loss: 2.3041 2022/10/08 04:45:27 - mmengine - INFO - Epoch(train) [102][560/2119] lr: 4.0000e-03 eta: 9:57:17 time: 0.3504 data_time: 0.0237 memory: 5826 grad_norm: 3.2658 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0638 loss: 2.0638 2022/10/08 04:45:34 - mmengine - INFO - Epoch(train) [102][580/2119] lr: 4.0000e-03 eta: 9:57:11 time: 0.3604 data_time: 0.0207 memory: 5826 grad_norm: 3.2681 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.3200 loss: 2.3200 2022/10/08 04:45:41 - mmengine - INFO - Epoch(train) [102][600/2119] lr: 4.0000e-03 eta: 9:57:04 time: 0.3565 data_time: 0.0192 memory: 5826 grad_norm: 3.1828 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1197 loss: 2.1197 2022/10/08 04:45:47 - mmengine - INFO - Epoch(train) [102][620/2119] lr: 4.0000e-03 eta: 9:56:56 time: 0.3121 data_time: 0.0250 memory: 5826 grad_norm: 3.2448 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9623 loss: 1.9623 2022/10/08 04:45:55 - mmengine - INFO - Epoch(train) [102][640/2119] lr: 4.0000e-03 eta: 9:56:50 time: 0.3718 data_time: 0.0207 memory: 5826 grad_norm: 3.2661 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.2983 loss: 2.2983 2022/10/08 04:46:01 - mmengine - INFO - Epoch(train) [102][660/2119] lr: 4.0000e-03 eta: 9:56:42 time: 0.2979 data_time: 0.0233 memory: 5826 grad_norm: 3.2160 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.2279 loss: 2.2279 2022/10/08 04:46:09 - mmengine - INFO - Epoch(train) [102][680/2119] lr: 4.0000e-03 eta: 9:56:36 time: 0.4000 data_time: 0.0244 memory: 5826 grad_norm: 3.3053 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1447 loss: 2.1447 2022/10/08 04:46:15 - mmengine - INFO - Epoch(train) [102][700/2119] lr: 4.0000e-03 eta: 9:56:29 time: 0.3328 data_time: 0.0184 memory: 5826 grad_norm: 3.2379 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.2850 loss: 2.2850 2022/10/08 04:46:23 - mmengine - INFO - Epoch(train) [102][720/2119] lr: 4.0000e-03 eta: 9:56:22 time: 0.3793 data_time: 0.0239 memory: 5826 grad_norm: 3.2441 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1356 loss: 2.1356 2022/10/08 04:46:29 - mmengine - INFO - Epoch(train) [102][740/2119] lr: 4.0000e-03 eta: 9:56:15 time: 0.3191 data_time: 0.0185 memory: 5826 grad_norm: 3.2789 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.4076 loss: 2.4076 2022/10/08 04:46:37 - mmengine - INFO - Epoch(train) [102][760/2119] lr: 4.0000e-03 eta: 9:56:08 time: 0.3788 data_time: 0.0195 memory: 5826 grad_norm: 3.2467 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.1203 loss: 2.1203 2022/10/08 04:46:44 - mmengine - INFO - Epoch(train) [102][780/2119] lr: 4.0000e-03 eta: 9:56:01 time: 0.3560 data_time: 0.0213 memory: 5826 grad_norm: 3.3504 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1991 loss: 2.1991 2022/10/08 04:46:51 - mmengine - INFO - Epoch(train) [102][800/2119] lr: 4.0000e-03 eta: 9:55:55 time: 0.3541 data_time: 0.0283 memory: 5826 grad_norm: 3.2001 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1894 loss: 2.1894 2022/10/08 04:46:57 - mmengine - INFO - Epoch(train) [102][820/2119] lr: 4.0000e-03 eta: 9:55:47 time: 0.3016 data_time: 0.0211 memory: 5826 grad_norm: 3.2259 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1216 loss: 2.1216 2022/10/08 04:47:05 - mmengine - INFO - Epoch(train) [102][840/2119] lr: 4.0000e-03 eta: 9:55:41 time: 0.3701 data_time: 0.0233 memory: 5826 grad_norm: 3.2813 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.5321 loss: 2.5321 2022/10/08 04:47:11 - mmengine - INFO - Epoch(train) [102][860/2119] lr: 4.0000e-03 eta: 9:55:34 time: 0.3457 data_time: 0.0203 memory: 5826 grad_norm: 3.2622 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2119 loss: 2.2119 2022/10/08 04:47:19 - mmengine - INFO - Epoch(train) [102][880/2119] lr: 4.0000e-03 eta: 9:55:27 time: 0.3701 data_time: 0.0213 memory: 5826 grad_norm: 3.2664 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1942 loss: 2.1942 2022/10/08 04:47:25 - mmengine - INFO - Epoch(train) [102][900/2119] lr: 4.0000e-03 eta: 9:55:20 time: 0.3083 data_time: 0.0273 memory: 5826 grad_norm: 3.1995 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4956 loss: 2.4956 2022/10/08 04:47:33 - mmengine - INFO - Epoch(train) [102][920/2119] lr: 4.0000e-03 eta: 9:55:13 time: 0.3894 data_time: 0.0208 memory: 5826 grad_norm: 3.2756 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4909 loss: 2.4909 2022/10/08 04:47:40 - mmengine - INFO - Epoch(train) [102][940/2119] lr: 4.0000e-03 eta: 9:55:06 time: 0.3588 data_time: 0.0180 memory: 5826 grad_norm: 3.2847 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.2508 loss: 2.2508 2022/10/08 04:47:48 - mmengine - INFO - Epoch(train) [102][960/2119] lr: 4.0000e-03 eta: 9:55:00 time: 0.3799 data_time: 0.0236 memory: 5826 grad_norm: 3.2797 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4409 loss: 2.4409 2022/10/08 04:47:54 - mmengine - INFO - Epoch(train) [102][980/2119] lr: 4.0000e-03 eta: 9:54:52 time: 0.3133 data_time: 0.0240 memory: 5826 grad_norm: 3.2659 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4127 loss: 2.4127 2022/10/08 04:47:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 04:48:02 - mmengine - INFO - Epoch(train) [102][1000/2119] lr: 4.0000e-03 eta: 9:54:46 time: 0.3876 data_time: 0.0222 memory: 5826 grad_norm: 3.2568 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3767 loss: 2.3767 2022/10/08 04:48:08 - mmengine - INFO - Epoch(train) [102][1020/2119] lr: 4.0000e-03 eta: 9:54:39 time: 0.3293 data_time: 0.0210 memory: 5826 grad_norm: 3.2850 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.1321 loss: 2.1321 2022/10/08 04:48:16 - mmengine - INFO - Epoch(train) [102][1040/2119] lr: 4.0000e-03 eta: 9:54:32 time: 0.3650 data_time: 0.0272 memory: 5826 grad_norm: 3.2488 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2897 loss: 2.2897 2022/10/08 04:48:22 - mmengine - INFO - Epoch(train) [102][1060/2119] lr: 4.0000e-03 eta: 9:54:25 time: 0.3438 data_time: 0.0219 memory: 5826 grad_norm: 3.2893 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.2725 loss: 2.2725 2022/10/08 04:48:30 - mmengine - INFO - Epoch(train) [102][1080/2119] lr: 4.0000e-03 eta: 9:54:18 time: 0.3653 data_time: 0.0223 memory: 5826 grad_norm: 3.2464 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8824 loss: 1.8824 2022/10/08 04:48:36 - mmengine - INFO - Epoch(train) [102][1100/2119] lr: 4.0000e-03 eta: 9:54:11 time: 0.3227 data_time: 0.0287 memory: 5826 grad_norm: 3.2460 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0726 loss: 2.0726 2022/10/08 04:48:45 - mmengine - INFO - Epoch(train) [102][1120/2119] lr: 4.0000e-03 eta: 9:54:05 time: 0.4192 data_time: 0.0206 memory: 5826 grad_norm: 3.2744 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.3124 loss: 2.3124 2022/10/08 04:48:51 - mmengine - INFO - Epoch(train) [102][1140/2119] lr: 4.0000e-03 eta: 9:53:57 time: 0.3075 data_time: 0.0257 memory: 5826 grad_norm: 3.2231 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1217 loss: 2.1217 2022/10/08 04:48:59 - mmengine - INFO - Epoch(train) [102][1160/2119] lr: 4.0000e-03 eta: 9:53:51 time: 0.3912 data_time: 0.0223 memory: 5826 grad_norm: 3.2565 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9696 loss: 1.9696 2022/10/08 04:49:06 - mmengine - INFO - Epoch(train) [102][1180/2119] lr: 4.0000e-03 eta: 9:53:44 time: 0.3474 data_time: 0.0214 memory: 5826 grad_norm: 3.3193 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.2198 loss: 2.2198 2022/10/08 04:49:14 - mmengine - INFO - Epoch(train) [102][1200/2119] lr: 4.0000e-03 eta: 9:53:38 time: 0.4307 data_time: 0.0246 memory: 5826 grad_norm: 3.2958 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.3833 loss: 2.3833 2022/10/08 04:49:20 - mmengine - INFO - Epoch(train) [102][1220/2119] lr: 4.0000e-03 eta: 9:53:31 time: 0.3118 data_time: 0.0203 memory: 5826 grad_norm: 3.2791 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1949 loss: 2.1949 2022/10/08 04:49:27 - mmengine - INFO - Epoch(train) [102][1240/2119] lr: 4.0000e-03 eta: 9:53:24 time: 0.3419 data_time: 0.0228 memory: 5826 grad_norm: 3.2567 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9614 loss: 1.9614 2022/10/08 04:49:34 - mmengine - INFO - Epoch(train) [102][1260/2119] lr: 4.0000e-03 eta: 9:53:17 time: 0.3415 data_time: 0.0260 memory: 5826 grad_norm: 3.3048 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2750 loss: 2.2750 2022/10/08 04:49:41 - mmengine - INFO - Epoch(train) [102][1280/2119] lr: 4.0000e-03 eta: 9:53:10 time: 0.3467 data_time: 0.0200 memory: 5826 grad_norm: 3.2778 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.2726 loss: 2.2726 2022/10/08 04:49:49 - mmengine - INFO - Epoch(train) [102][1300/2119] lr: 4.0000e-03 eta: 9:53:03 time: 0.3830 data_time: 0.0199 memory: 5826 grad_norm: 3.2767 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2246 loss: 2.2246 2022/10/08 04:49:56 - mmengine - INFO - Epoch(train) [102][1320/2119] lr: 4.0000e-03 eta: 9:52:56 time: 0.3744 data_time: 0.0199 memory: 5826 grad_norm: 3.3375 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5041 loss: 2.5041 2022/10/08 04:50:03 - mmengine - INFO - Epoch(train) [102][1340/2119] lr: 4.0000e-03 eta: 9:52:49 time: 0.3386 data_time: 0.0262 memory: 5826 grad_norm: 3.2845 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2624 loss: 2.2624 2022/10/08 04:50:10 - mmengine - INFO - Epoch(train) [102][1360/2119] lr: 4.0000e-03 eta: 9:52:42 time: 0.3326 data_time: 0.0196 memory: 5826 grad_norm: 3.3191 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.2253 loss: 2.2253 2022/10/08 04:50:17 - mmengine - INFO - Epoch(train) [102][1380/2119] lr: 4.0000e-03 eta: 9:52:35 time: 0.3583 data_time: 0.0230 memory: 5826 grad_norm: 3.2836 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2615 loss: 2.2615 2022/10/08 04:50:24 - mmengine - INFO - Epoch(train) [102][1400/2119] lr: 4.0000e-03 eta: 9:52:28 time: 0.3454 data_time: 0.0215 memory: 5826 grad_norm: 3.3263 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.2769 loss: 2.2769 2022/10/08 04:50:30 - mmengine - INFO - Epoch(train) [102][1420/2119] lr: 4.0000e-03 eta: 9:52:21 time: 0.3339 data_time: 0.0197 memory: 5826 grad_norm: 3.2435 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.3917 loss: 2.3917 2022/10/08 04:50:38 - mmengine - INFO - Epoch(train) [102][1440/2119] lr: 4.0000e-03 eta: 9:52:15 time: 0.3962 data_time: 0.0253 memory: 5826 grad_norm: 3.3313 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3622 loss: 2.3622 2022/10/08 04:50:46 - mmengine - INFO - Epoch(train) [102][1460/2119] lr: 4.0000e-03 eta: 9:52:08 time: 0.3595 data_time: 0.0206 memory: 5826 grad_norm: 3.2986 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2164 loss: 2.2164 2022/10/08 04:50:52 - mmengine - INFO - Epoch(train) [102][1480/2119] lr: 4.0000e-03 eta: 9:52:01 time: 0.3069 data_time: 0.0277 memory: 5826 grad_norm: 3.3148 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2400 loss: 2.2400 2022/10/08 04:50:59 - mmengine - INFO - Epoch(train) [102][1500/2119] lr: 4.0000e-03 eta: 9:51:54 time: 0.3577 data_time: 0.0203 memory: 5826 grad_norm: 3.2520 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.2994 loss: 2.2994 2022/10/08 04:51:07 - mmengine - INFO - Epoch(train) [102][1520/2119] lr: 4.0000e-03 eta: 9:51:47 time: 0.3992 data_time: 0.0234 memory: 5826 grad_norm: 3.3275 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.3106 loss: 2.3106 2022/10/08 04:51:14 - mmengine - INFO - Epoch(train) [102][1540/2119] lr: 4.0000e-03 eta: 9:51:41 time: 0.3584 data_time: 0.0272 memory: 5826 grad_norm: 3.2903 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.5047 loss: 2.5047 2022/10/08 04:51:21 - mmengine - INFO - Epoch(train) [102][1560/2119] lr: 4.0000e-03 eta: 9:51:34 time: 0.3386 data_time: 0.0216 memory: 5826 grad_norm: 3.3243 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1946 loss: 2.1946 2022/10/08 04:51:28 - mmengine - INFO - Epoch(train) [102][1580/2119] lr: 4.0000e-03 eta: 9:51:27 time: 0.3423 data_time: 0.0227 memory: 5826 grad_norm: 3.3277 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1281 loss: 2.1281 2022/10/08 04:51:35 - mmengine - INFO - Epoch(train) [102][1600/2119] lr: 4.0000e-03 eta: 9:51:20 time: 0.3478 data_time: 0.0246 memory: 5826 grad_norm: 3.2938 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0069 loss: 2.0069 2022/10/08 04:51:41 - mmengine - INFO - Epoch(train) [102][1620/2119] lr: 4.0000e-03 eta: 9:51:13 time: 0.3363 data_time: 0.0207 memory: 5826 grad_norm: 3.2767 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3994 loss: 2.3994 2022/10/08 04:51:49 - mmengine - INFO - Epoch(train) [102][1640/2119] lr: 4.0000e-03 eta: 9:51:06 time: 0.3758 data_time: 0.0211 memory: 5826 grad_norm: 3.3327 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1701 loss: 2.1701 2022/10/08 04:51:56 - mmengine - INFO - Epoch(train) [102][1660/2119] lr: 4.0000e-03 eta: 9:50:59 time: 0.3396 data_time: 0.0197 memory: 5826 grad_norm: 3.2948 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.3614 loss: 2.3614 2022/10/08 04:52:03 - mmengine - INFO - Epoch(train) [102][1680/2119] lr: 4.0000e-03 eta: 9:50:52 time: 0.3776 data_time: 0.0212 memory: 5826 grad_norm: 3.3048 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.3539 loss: 2.3539 2022/10/08 04:52:09 - mmengine - INFO - Epoch(train) [102][1700/2119] lr: 4.0000e-03 eta: 9:50:45 time: 0.3042 data_time: 0.0181 memory: 5826 grad_norm: 3.3010 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1234 loss: 2.1234 2022/10/08 04:52:17 - mmengine - INFO - Epoch(train) [102][1720/2119] lr: 4.0000e-03 eta: 9:50:38 time: 0.3858 data_time: 0.0244 memory: 5826 grad_norm: 3.2915 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1847 loss: 2.1847 2022/10/08 04:52:24 - mmengine - INFO - Epoch(train) [102][1740/2119] lr: 4.0000e-03 eta: 9:50:32 time: 0.3555 data_time: 0.0187 memory: 5826 grad_norm: 3.3408 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.1839 loss: 2.1839 2022/10/08 04:52:32 - mmengine - INFO - Epoch(train) [102][1760/2119] lr: 4.0000e-03 eta: 9:50:25 time: 0.3788 data_time: 0.0245 memory: 5826 grad_norm: 3.2977 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4438 loss: 2.4438 2022/10/08 04:52:39 - mmengine - INFO - Epoch(train) [102][1780/2119] lr: 4.0000e-03 eta: 9:50:18 time: 0.3601 data_time: 0.0178 memory: 5826 grad_norm: 3.3025 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4085 loss: 2.4085 2022/10/08 04:52:46 - mmengine - INFO - Epoch(train) [102][1800/2119] lr: 4.0000e-03 eta: 9:50:11 time: 0.3728 data_time: 0.0195 memory: 5826 grad_norm: 3.2686 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2367 loss: 2.2367 2022/10/08 04:52:53 - mmengine - INFO - Epoch(train) [102][1820/2119] lr: 4.0000e-03 eta: 9:50:04 time: 0.3490 data_time: 0.0229 memory: 5826 grad_norm: 3.2764 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.2127 loss: 2.2127 2022/10/08 04:53:00 - mmengine - INFO - Epoch(train) [102][1840/2119] lr: 4.0000e-03 eta: 9:49:58 time: 0.3507 data_time: 0.0249 memory: 5826 grad_norm: 3.3266 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2828 loss: 2.2828 2022/10/08 04:53:06 - mmengine - INFO - Epoch(train) [102][1860/2119] lr: 4.0000e-03 eta: 9:49:50 time: 0.3003 data_time: 0.0248 memory: 5826 grad_norm: 3.3310 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1703 loss: 2.1703 2022/10/08 04:53:15 - mmengine - INFO - Epoch(train) [102][1880/2119] lr: 4.0000e-03 eta: 9:49:44 time: 0.4065 data_time: 0.0211 memory: 5826 grad_norm: 3.2948 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1305 loss: 2.1305 2022/10/08 04:53:21 - mmengine - INFO - Epoch(train) [102][1900/2119] lr: 4.0000e-03 eta: 9:49:37 time: 0.3368 data_time: 0.0175 memory: 5826 grad_norm: 3.2952 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2117 loss: 2.2117 2022/10/08 04:53:29 - mmengine - INFO - Epoch(train) [102][1920/2119] lr: 4.0000e-03 eta: 9:49:30 time: 0.3802 data_time: 0.0334 memory: 5826 grad_norm: 3.2559 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2586 loss: 2.2586 2022/10/08 04:53:36 - mmengine - INFO - Epoch(train) [102][1940/2119] lr: 4.0000e-03 eta: 9:49:23 time: 0.3429 data_time: 0.0230 memory: 5826 grad_norm: 3.3021 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4711 loss: 2.4711 2022/10/08 04:53:43 - mmengine - INFO - Epoch(train) [102][1960/2119] lr: 4.0000e-03 eta: 9:49:16 time: 0.3584 data_time: 0.0338 memory: 5826 grad_norm: 3.4245 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4939 loss: 2.4939 2022/10/08 04:53:49 - mmengine - INFO - Epoch(train) [102][1980/2119] lr: 4.0000e-03 eta: 9:49:09 time: 0.3080 data_time: 0.0213 memory: 5826 grad_norm: 3.3642 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.3111 loss: 2.3111 2022/10/08 04:53:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 04:53:57 - mmengine - INFO - Epoch(train) [102][2000/2119] lr: 4.0000e-03 eta: 9:49:02 time: 0.3704 data_time: 0.0228 memory: 5826 grad_norm: 3.2669 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.2338 loss: 2.2338 2022/10/08 04:54:04 - mmengine - INFO - Epoch(train) [102][2020/2119] lr: 4.0000e-03 eta: 9:48:55 time: 0.3617 data_time: 0.0216 memory: 5826 grad_norm: 3.3596 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1104 loss: 2.1104 2022/10/08 04:54:10 - mmengine - INFO - Epoch(train) [102][2040/2119] lr: 4.0000e-03 eta: 9:48:48 time: 0.3078 data_time: 0.0299 memory: 5826 grad_norm: 3.2864 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1577 loss: 2.1577 2022/10/08 04:54:17 - mmengine - INFO - Epoch(train) [102][2060/2119] lr: 4.0000e-03 eta: 9:48:41 time: 0.3556 data_time: 0.0180 memory: 5826 grad_norm: 3.2871 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2642 loss: 2.2642 2022/10/08 04:54:25 - mmengine - INFO - Epoch(train) [102][2080/2119] lr: 4.0000e-03 eta: 9:48:35 time: 0.3772 data_time: 0.0242 memory: 5826 grad_norm: 3.3762 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2583 loss: 2.2583 2022/10/08 04:54:31 - mmengine - INFO - Epoch(train) [102][2100/2119] lr: 4.0000e-03 eta: 9:48:28 time: 0.3397 data_time: 0.0209 memory: 5826 grad_norm: 3.3105 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.4551 loss: 2.4551 2022/10/08 04:54:37 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 04:54:37 - mmengine - INFO - Epoch(train) [102][2119/2119] lr: 4.0000e-03 eta: 9:48:28 time: 0.3039 data_time: 0.0167 memory: 5826 grad_norm: 3.3193 top1_acc: 0.6000 top5_acc: 0.8000 loss_cls: 2.5872 loss: 2.5872 2022/10/08 04:54:47 - mmengine - INFO - Epoch(train) [103][20/2119] lr: 4.0000e-03 eta: 9:48:12 time: 0.5098 data_time: 0.1132 memory: 5826 grad_norm: 3.3278 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.2819 loss: 2.2819 2022/10/08 04:54:54 - mmengine - INFO - Epoch(train) [103][40/2119] lr: 4.0000e-03 eta: 9:48:05 time: 0.3294 data_time: 0.0197 memory: 5826 grad_norm: 3.2969 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.2697 loss: 2.2697 2022/10/08 04:55:02 - mmengine - INFO - Epoch(train) [103][60/2119] lr: 4.0000e-03 eta: 9:47:59 time: 0.4096 data_time: 0.0315 memory: 5826 grad_norm: 3.3704 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.1327 loss: 2.1327 2022/10/08 04:55:09 - mmengine - INFO - Epoch(train) [103][80/2119] lr: 4.0000e-03 eta: 9:47:52 time: 0.3394 data_time: 0.0254 memory: 5826 grad_norm: 3.2627 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.1922 loss: 2.1922 2022/10/08 04:55:16 - mmengine - INFO - Epoch(train) [103][100/2119] lr: 4.0000e-03 eta: 9:47:45 time: 0.3539 data_time: 0.0252 memory: 5826 grad_norm: 3.3740 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.0735 loss: 2.0735 2022/10/08 04:55:23 - mmengine - INFO - Epoch(train) [103][120/2119] lr: 4.0000e-03 eta: 9:47:38 time: 0.3179 data_time: 0.0257 memory: 5826 grad_norm: 3.3232 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4779 loss: 2.4779 2022/10/08 04:55:30 - mmengine - INFO - Epoch(train) [103][140/2119] lr: 4.0000e-03 eta: 9:47:31 time: 0.3544 data_time: 0.0249 memory: 5826 grad_norm: 3.3727 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.4979 loss: 2.4979 2022/10/08 04:55:37 - mmengine - INFO - Epoch(train) [103][160/2119] lr: 4.0000e-03 eta: 9:47:24 time: 0.3475 data_time: 0.0240 memory: 5826 grad_norm: 3.3326 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.6430 loss: 2.6430 2022/10/08 04:55:44 - mmengine - INFO - Epoch(train) [103][180/2119] lr: 4.0000e-03 eta: 9:47:17 time: 0.3507 data_time: 0.0212 memory: 5826 grad_norm: 3.3529 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0578 loss: 2.0578 2022/10/08 04:55:50 - mmengine - INFO - Epoch(train) [103][200/2119] lr: 4.0000e-03 eta: 9:47:10 time: 0.3435 data_time: 0.0224 memory: 5826 grad_norm: 3.3318 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.1864 loss: 2.1864 2022/10/08 04:55:57 - mmengine - INFO - Epoch(train) [103][220/2119] lr: 4.0000e-03 eta: 9:47:03 time: 0.3347 data_time: 0.0265 memory: 5826 grad_norm: 3.3374 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0877 loss: 2.0877 2022/10/08 04:56:05 - mmengine - INFO - Epoch(train) [103][240/2119] lr: 4.0000e-03 eta: 9:46:56 time: 0.3719 data_time: 0.0230 memory: 5826 grad_norm: 3.3268 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.2019 loss: 2.2019 2022/10/08 04:56:11 - mmengine - INFO - Epoch(train) [103][260/2119] lr: 4.0000e-03 eta: 9:46:49 time: 0.3273 data_time: 0.0237 memory: 5826 grad_norm: 3.2267 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7972 loss: 1.7972 2022/10/08 04:56:19 - mmengine - INFO - Epoch(train) [103][280/2119] lr: 4.0000e-03 eta: 9:46:43 time: 0.3909 data_time: 0.0243 memory: 5826 grad_norm: 3.3332 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.1831 loss: 2.1831 2022/10/08 04:56:26 - mmengine - INFO - Epoch(train) [103][300/2119] lr: 4.0000e-03 eta: 9:46:36 time: 0.3367 data_time: 0.0235 memory: 5826 grad_norm: 3.3614 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.2322 loss: 2.2322 2022/10/08 04:56:33 - mmengine - INFO - Epoch(train) [103][320/2119] lr: 4.0000e-03 eta: 9:46:29 time: 0.3461 data_time: 0.0223 memory: 5826 grad_norm: 3.3121 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.2375 loss: 2.2375 2022/10/08 04:56:40 - mmengine - INFO - Epoch(train) [103][340/2119] lr: 4.0000e-03 eta: 9:46:22 time: 0.3536 data_time: 0.0229 memory: 5826 grad_norm: 3.3068 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1054 loss: 2.1054 2022/10/08 04:56:48 - mmengine - INFO - Epoch(train) [103][360/2119] lr: 4.0000e-03 eta: 9:46:15 time: 0.3933 data_time: 0.0192 memory: 5826 grad_norm: 3.3667 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1182 loss: 2.1182 2022/10/08 04:56:54 - mmengine - INFO - Epoch(train) [103][380/2119] lr: 4.0000e-03 eta: 9:46:08 time: 0.3387 data_time: 0.0236 memory: 5826 grad_norm: 3.3701 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1701 loss: 2.1701 2022/10/08 04:57:01 - mmengine - INFO - Epoch(train) [103][400/2119] lr: 4.0000e-03 eta: 9:46:01 time: 0.3472 data_time: 0.0239 memory: 5826 grad_norm: 3.3031 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.2285 loss: 2.2285 2022/10/08 04:57:08 - mmengine - INFO - Epoch(train) [103][420/2119] lr: 4.0000e-03 eta: 9:45:54 time: 0.3321 data_time: 0.0234 memory: 5826 grad_norm: 3.4034 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0128 loss: 2.0128 2022/10/08 04:57:16 - mmengine - INFO - Epoch(train) [103][440/2119] lr: 4.0000e-03 eta: 9:45:48 time: 0.3823 data_time: 0.0252 memory: 5826 grad_norm: 3.3427 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0663 loss: 2.0663 2022/10/08 04:57:22 - mmengine - INFO - Epoch(train) [103][460/2119] lr: 4.0000e-03 eta: 9:45:41 time: 0.3307 data_time: 0.0235 memory: 5826 grad_norm: 3.3360 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9191 loss: 1.9191 2022/10/08 04:57:29 - mmengine - INFO - Epoch(train) [103][480/2119] lr: 4.0000e-03 eta: 9:45:34 time: 0.3422 data_time: 0.0235 memory: 5826 grad_norm: 3.3531 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.1408 loss: 2.1408 2022/10/08 04:57:36 - mmengine - INFO - Epoch(train) [103][500/2119] lr: 4.0000e-03 eta: 9:45:27 time: 0.3547 data_time: 0.0203 memory: 5826 grad_norm: 3.3314 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.0552 loss: 2.0552 2022/10/08 04:57:44 - mmengine - INFO - Epoch(train) [103][520/2119] lr: 4.0000e-03 eta: 9:45:20 time: 0.3853 data_time: 0.0223 memory: 5826 grad_norm: 3.3589 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4473 loss: 2.4473 2022/10/08 04:57:50 - mmengine - INFO - Epoch(train) [103][540/2119] lr: 4.0000e-03 eta: 9:45:13 time: 0.3207 data_time: 0.0180 memory: 5826 grad_norm: 3.3511 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9846 loss: 1.9846 2022/10/08 04:57:57 - mmengine - INFO - Epoch(train) [103][560/2119] lr: 4.0000e-03 eta: 9:45:06 time: 0.3430 data_time: 0.0266 memory: 5826 grad_norm: 3.3181 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3666 loss: 2.3666 2022/10/08 04:58:05 - mmengine - INFO - Epoch(train) [103][580/2119] lr: 4.0000e-03 eta: 9:44:59 time: 0.3677 data_time: 0.0243 memory: 5826 grad_norm: 3.3058 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0063 loss: 2.0063 2022/10/08 04:58:12 - mmengine - INFO - Epoch(train) [103][600/2119] lr: 4.0000e-03 eta: 9:44:52 time: 0.3572 data_time: 0.0209 memory: 5826 grad_norm: 3.3417 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.1545 loss: 2.1545 2022/10/08 04:58:18 - mmengine - INFO - Epoch(train) [103][620/2119] lr: 4.0000e-03 eta: 9:44:45 time: 0.3220 data_time: 0.0251 memory: 5826 grad_norm: 3.3280 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1849 loss: 2.1849 2022/10/08 04:58:26 - mmengine - INFO - Epoch(train) [103][640/2119] lr: 4.0000e-03 eta: 9:44:39 time: 0.4030 data_time: 0.0219 memory: 5826 grad_norm: 3.3822 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.2295 loss: 2.2295 2022/10/08 04:58:33 - mmengine - INFO - Epoch(train) [103][660/2119] lr: 4.0000e-03 eta: 9:44:32 time: 0.3243 data_time: 0.0236 memory: 5826 grad_norm: 3.3648 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.3722 loss: 2.3722 2022/10/08 04:58:40 - mmengine - INFO - Epoch(train) [103][680/2119] lr: 4.0000e-03 eta: 9:44:25 time: 0.3589 data_time: 0.0255 memory: 5826 grad_norm: 3.3537 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1749 loss: 2.1749 2022/10/08 04:58:47 - mmengine - INFO - Epoch(train) [103][700/2119] lr: 4.0000e-03 eta: 9:44:18 time: 0.3480 data_time: 0.0232 memory: 5826 grad_norm: 3.3387 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0806 loss: 2.0806 2022/10/08 04:58:54 - mmengine - INFO - Epoch(train) [103][720/2119] lr: 4.0000e-03 eta: 9:44:11 time: 0.3593 data_time: 0.0209 memory: 5826 grad_norm: 3.3577 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0789 loss: 2.0789 2022/10/08 04:59:01 - mmengine - INFO - Epoch(train) [103][740/2119] lr: 4.0000e-03 eta: 9:44:04 time: 0.3225 data_time: 0.0202 memory: 5826 grad_norm: 3.4226 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 2.2267 loss: 2.2267 2022/10/08 04:59:08 - mmengine - INFO - Epoch(train) [103][760/2119] lr: 4.0000e-03 eta: 9:43:57 time: 0.3915 data_time: 0.0257 memory: 5826 grad_norm: 3.3631 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.2794 loss: 2.2794 2022/10/08 04:59:16 - mmengine - INFO - Epoch(train) [103][780/2119] lr: 4.0000e-03 eta: 9:43:51 time: 0.3646 data_time: 0.0228 memory: 5826 grad_norm: 3.3261 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9954 loss: 1.9954 2022/10/08 04:59:23 - mmengine - INFO - Epoch(train) [103][800/2119] lr: 4.0000e-03 eta: 9:43:44 time: 0.3694 data_time: 0.0228 memory: 5826 grad_norm: 3.3252 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2413 loss: 2.2413 2022/10/08 04:59:29 - mmengine - INFO - Epoch(train) [103][820/2119] lr: 4.0000e-03 eta: 9:43:37 time: 0.2974 data_time: 0.0216 memory: 5826 grad_norm: 3.3023 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.5147 loss: 2.5147 2022/10/08 04:59:36 - mmengine - INFO - Epoch(train) [103][840/2119] lr: 4.0000e-03 eta: 9:43:30 time: 0.3487 data_time: 0.0184 memory: 5826 grad_norm: 3.2946 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.3676 loss: 2.3676 2022/10/08 04:59:42 - mmengine - INFO - Epoch(train) [103][860/2119] lr: 4.0000e-03 eta: 9:43:22 time: 0.3117 data_time: 0.0312 memory: 5826 grad_norm: 3.3629 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1620 loss: 2.1620 2022/10/08 04:59:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 04:59:50 - mmengine - INFO - Epoch(train) [103][880/2119] lr: 4.0000e-03 eta: 9:43:16 time: 0.3741 data_time: 0.0216 memory: 5826 grad_norm: 3.4112 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.1246 loss: 2.1246 2022/10/08 04:59:57 - mmengine - INFO - Epoch(train) [103][900/2119] lr: 4.0000e-03 eta: 9:43:09 time: 0.3532 data_time: 0.0259 memory: 5826 grad_norm: 3.3658 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1777 loss: 2.1777 2022/10/08 05:00:04 - mmengine - INFO - Epoch(train) [103][920/2119] lr: 4.0000e-03 eta: 9:43:02 time: 0.3755 data_time: 0.0201 memory: 5826 grad_norm: 3.3959 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1753 loss: 2.1753 2022/10/08 05:00:11 - mmengine - INFO - Epoch(train) [103][940/2119] lr: 4.0000e-03 eta: 9:42:55 time: 0.3184 data_time: 0.0253 memory: 5826 grad_norm: 3.3345 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1068 loss: 2.1068 2022/10/08 05:00:18 - mmengine - INFO - Epoch(train) [103][960/2119] lr: 4.0000e-03 eta: 9:42:48 time: 0.3528 data_time: 0.0219 memory: 5826 grad_norm: 3.3591 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.3769 loss: 2.3769 2022/10/08 05:00:25 - mmengine - INFO - Epoch(train) [103][980/2119] lr: 4.0000e-03 eta: 9:42:41 time: 0.3645 data_time: 0.0249 memory: 5826 grad_norm: 3.3071 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0853 loss: 2.0853 2022/10/08 05:00:31 - mmengine - INFO - Epoch(train) [103][1000/2119] lr: 4.0000e-03 eta: 9:42:34 time: 0.3184 data_time: 0.0234 memory: 5826 grad_norm: 3.3290 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0964 loss: 2.0964 2022/10/08 05:00:39 - mmengine - INFO - Epoch(train) [103][1020/2119] lr: 4.0000e-03 eta: 9:42:27 time: 0.3711 data_time: 0.0210 memory: 5826 grad_norm: 3.3346 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4492 loss: 2.4492 2022/10/08 05:00:47 - mmengine - INFO - Epoch(train) [103][1040/2119] lr: 4.0000e-03 eta: 9:42:21 time: 0.3962 data_time: 0.0266 memory: 5826 grad_norm: 3.3579 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8788 loss: 1.8788 2022/10/08 05:00:53 - mmengine - INFO - Epoch(train) [103][1060/2119] lr: 4.0000e-03 eta: 9:42:13 time: 0.3012 data_time: 0.0181 memory: 5826 grad_norm: 3.4077 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.2201 loss: 2.2201 2022/10/08 05:01:02 - mmengine - INFO - Epoch(train) [103][1080/2119] lr: 4.0000e-03 eta: 9:42:07 time: 0.4399 data_time: 0.0230 memory: 5826 grad_norm: 3.3841 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0820 loss: 2.0820 2022/10/08 05:01:08 - mmengine - INFO - Epoch(train) [103][1100/2119] lr: 4.0000e-03 eta: 9:42:00 time: 0.3120 data_time: 0.0219 memory: 5826 grad_norm: 3.3443 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.2819 loss: 2.2819 2022/10/08 05:01:15 - mmengine - INFO - Epoch(train) [103][1120/2119] lr: 4.0000e-03 eta: 9:41:53 time: 0.3622 data_time: 0.0272 memory: 5826 grad_norm: 3.3491 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.3504 loss: 2.3504 2022/10/08 05:01:22 - mmengine - INFO - Epoch(train) [103][1140/2119] lr: 4.0000e-03 eta: 9:41:46 time: 0.3435 data_time: 0.0238 memory: 5826 grad_norm: 3.3409 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.2473 loss: 2.2473 2022/10/08 05:01:29 - mmengine - INFO - Epoch(train) [103][1160/2119] lr: 4.0000e-03 eta: 9:41:39 time: 0.3594 data_time: 0.0206 memory: 5826 grad_norm: 3.4143 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.2160 loss: 2.2160 2022/10/08 05:01:36 - mmengine - INFO - Epoch(train) [103][1180/2119] lr: 4.0000e-03 eta: 9:41:33 time: 0.3472 data_time: 0.0240 memory: 5826 grad_norm: 3.3268 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.0674 loss: 2.0674 2022/10/08 05:01:43 - mmengine - INFO - Epoch(train) [103][1200/2119] lr: 4.0000e-03 eta: 9:41:26 time: 0.3556 data_time: 0.0311 memory: 5826 grad_norm: 3.3762 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1590 loss: 2.1590 2022/10/08 05:01:50 - mmengine - INFO - Epoch(train) [103][1220/2119] lr: 4.0000e-03 eta: 9:41:19 time: 0.3362 data_time: 0.0182 memory: 5826 grad_norm: 3.3794 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1821 loss: 2.1821 2022/10/08 05:01:57 - mmengine - INFO - Epoch(train) [103][1240/2119] lr: 4.0000e-03 eta: 9:41:12 time: 0.3618 data_time: 0.0227 memory: 5826 grad_norm: 3.3492 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1949 loss: 2.1949 2022/10/08 05:02:05 - mmengine - INFO - Epoch(train) [103][1260/2119] lr: 4.0000e-03 eta: 9:41:05 time: 0.3929 data_time: 0.0222 memory: 5826 grad_norm: 3.4143 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.1601 loss: 2.1601 2022/10/08 05:02:13 - mmengine - INFO - Epoch(train) [103][1280/2119] lr: 4.0000e-03 eta: 9:40:59 time: 0.3860 data_time: 0.0219 memory: 5826 grad_norm: 3.3531 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.2604 loss: 2.2604 2022/10/08 05:02:20 - mmengine - INFO - Epoch(train) [103][1300/2119] lr: 4.0000e-03 eta: 9:40:52 time: 0.3534 data_time: 0.0185 memory: 5826 grad_norm: 3.3152 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0051 loss: 2.0051 2022/10/08 05:02:28 - mmengine - INFO - Epoch(train) [103][1320/2119] lr: 4.0000e-03 eta: 9:40:45 time: 0.3898 data_time: 0.0217 memory: 5826 grad_norm: 3.3404 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.2084 loss: 2.2084 2022/10/08 05:02:34 - mmengine - INFO - Epoch(train) [103][1340/2119] lr: 4.0000e-03 eta: 9:40:38 time: 0.3334 data_time: 0.0300 memory: 5826 grad_norm: 3.3897 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.3009 loss: 2.3009 2022/10/08 05:02:41 - mmengine - INFO - Epoch(train) [103][1360/2119] lr: 4.0000e-03 eta: 9:40:31 time: 0.3266 data_time: 0.0205 memory: 5826 grad_norm: 3.3546 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0395 loss: 2.0395 2022/10/08 05:02:48 - mmengine - INFO - Epoch(train) [103][1380/2119] lr: 4.0000e-03 eta: 9:40:24 time: 0.3417 data_time: 0.0214 memory: 5826 grad_norm: 3.3993 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2175 loss: 2.2175 2022/10/08 05:02:55 - mmengine - INFO - Epoch(train) [103][1400/2119] lr: 4.0000e-03 eta: 9:40:17 time: 0.3840 data_time: 0.0304 memory: 5826 grad_norm: 3.3988 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4850 loss: 2.4850 2022/10/08 05:03:02 - mmengine - INFO - Epoch(train) [103][1420/2119] lr: 4.0000e-03 eta: 9:40:11 time: 0.3421 data_time: 0.0244 memory: 5826 grad_norm: 3.3869 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.2165 loss: 2.2165 2022/10/08 05:03:10 - mmengine - INFO - Epoch(train) [103][1440/2119] lr: 4.0000e-03 eta: 9:40:04 time: 0.3733 data_time: 0.0203 memory: 5826 grad_norm: 3.3233 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0925 loss: 2.0925 2022/10/08 05:03:16 - mmengine - INFO - Epoch(train) [103][1460/2119] lr: 4.0000e-03 eta: 9:39:56 time: 0.3000 data_time: 0.0208 memory: 5826 grad_norm: 3.3932 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.1234 loss: 2.1234 2022/10/08 05:03:24 - mmengine - INFO - Epoch(train) [103][1480/2119] lr: 4.0000e-03 eta: 9:39:50 time: 0.4086 data_time: 0.0198 memory: 5826 grad_norm: 3.4087 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1197 loss: 2.1197 2022/10/08 05:03:30 - mmengine - INFO - Epoch(train) [103][1500/2119] lr: 4.0000e-03 eta: 9:39:43 time: 0.3074 data_time: 0.0234 memory: 5826 grad_norm: 3.3753 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1013 loss: 2.1013 2022/10/08 05:03:38 - mmengine - INFO - Epoch(train) [103][1520/2119] lr: 4.0000e-03 eta: 9:39:36 time: 0.3851 data_time: 0.0212 memory: 5826 grad_norm: 3.4275 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0827 loss: 2.0827 2022/10/08 05:03:44 - mmengine - INFO - Epoch(train) [103][1540/2119] lr: 4.0000e-03 eta: 9:39:29 time: 0.3189 data_time: 0.0228 memory: 5826 grad_norm: 3.4191 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3230 loss: 2.3230 2022/10/08 05:03:52 - mmengine - INFO - Epoch(train) [103][1560/2119] lr: 4.0000e-03 eta: 9:39:23 time: 0.4088 data_time: 0.0258 memory: 5826 grad_norm: 3.3807 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.2329 loss: 2.2329 2022/10/08 05:03:59 - mmengine - INFO - Epoch(train) [103][1580/2119] lr: 4.0000e-03 eta: 9:39:15 time: 0.3298 data_time: 0.0235 memory: 5826 grad_norm: 3.4212 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.2238 loss: 2.2238 2022/10/08 05:04:07 - mmengine - INFO - Epoch(train) [103][1600/2119] lr: 4.0000e-03 eta: 9:39:09 time: 0.4077 data_time: 0.0214 memory: 5826 grad_norm: 3.4205 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.2086 loss: 2.2086 2022/10/08 05:04:14 - mmengine - INFO - Epoch(train) [103][1620/2119] lr: 4.0000e-03 eta: 9:39:02 time: 0.3519 data_time: 0.0214 memory: 5826 grad_norm: 3.3688 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9495 loss: 1.9495 2022/10/08 05:04:21 - mmengine - INFO - Epoch(train) [103][1640/2119] lr: 4.0000e-03 eta: 9:38:55 time: 0.3424 data_time: 0.0246 memory: 5826 grad_norm: 3.3992 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1051 loss: 2.1051 2022/10/08 05:04:28 - mmengine - INFO - Epoch(train) [103][1660/2119] lr: 4.0000e-03 eta: 9:38:48 time: 0.3464 data_time: 0.0226 memory: 5826 grad_norm: 3.4229 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.3282 loss: 2.3282 2022/10/08 05:04:36 - mmengine - INFO - Epoch(train) [103][1680/2119] lr: 4.0000e-03 eta: 9:38:42 time: 0.3853 data_time: 0.0200 memory: 5826 grad_norm: 3.3400 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1831 loss: 2.1831 2022/10/08 05:04:42 - mmengine - INFO - Epoch(train) [103][1700/2119] lr: 4.0000e-03 eta: 9:38:34 time: 0.3188 data_time: 0.0219 memory: 5826 grad_norm: 3.4278 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2378 loss: 2.2378 2022/10/08 05:04:50 - mmengine - INFO - Epoch(train) [103][1720/2119] lr: 4.0000e-03 eta: 9:38:28 time: 0.4015 data_time: 0.0173 memory: 5826 grad_norm: 3.4180 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1736 loss: 2.1736 2022/10/08 05:04:58 - mmengine - INFO - Epoch(train) [103][1740/2119] lr: 4.0000e-03 eta: 9:38:21 time: 0.3703 data_time: 0.0238 memory: 5826 grad_norm: 3.3409 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.2414 loss: 2.2414 2022/10/08 05:05:05 - mmengine - INFO - Epoch(train) [103][1760/2119] lr: 4.0000e-03 eta: 9:38:15 time: 0.3845 data_time: 0.0234 memory: 5826 grad_norm: 3.3813 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0400 loss: 2.0400 2022/10/08 05:05:12 - mmengine - INFO - Epoch(train) [103][1780/2119] lr: 4.0000e-03 eta: 9:38:08 time: 0.3497 data_time: 0.0216 memory: 5826 grad_norm: 3.4024 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0149 loss: 2.0149 2022/10/08 05:05:19 - mmengine - INFO - Epoch(train) [103][1800/2119] lr: 4.0000e-03 eta: 9:38:01 time: 0.3374 data_time: 0.0209 memory: 5826 grad_norm: 3.3901 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1730 loss: 2.1730 2022/10/08 05:05:25 - mmengine - INFO - Epoch(train) [103][1820/2119] lr: 4.0000e-03 eta: 9:37:53 time: 0.2964 data_time: 0.0292 memory: 5826 grad_norm: 3.3187 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1716 loss: 2.1716 2022/10/08 05:05:33 - mmengine - INFO - Epoch(train) [103][1840/2119] lr: 4.0000e-03 eta: 9:37:47 time: 0.3998 data_time: 0.0230 memory: 5826 grad_norm: 3.4074 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0195 loss: 2.0195 2022/10/08 05:05:40 - mmengine - INFO - Epoch(train) [103][1860/2119] lr: 4.0000e-03 eta: 9:37:40 time: 0.3433 data_time: 0.0213 memory: 5826 grad_norm: 3.4397 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.1264 loss: 2.1264 2022/10/08 05:05:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 05:05:48 - mmengine - INFO - Epoch(train) [103][1880/2119] lr: 4.0000e-03 eta: 9:37:33 time: 0.3910 data_time: 0.0167 memory: 5826 grad_norm: 3.4139 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1411 loss: 2.1411 2022/10/08 05:05:54 - mmengine - INFO - Epoch(train) [103][1900/2119] lr: 4.0000e-03 eta: 9:37:26 time: 0.3268 data_time: 0.0180 memory: 5826 grad_norm: 3.3703 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1827 loss: 2.1827 2022/10/08 05:06:01 - mmengine - INFO - Epoch(train) [103][1920/2119] lr: 4.0000e-03 eta: 9:37:19 time: 0.3528 data_time: 0.0234 memory: 5826 grad_norm: 3.3904 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3169 loss: 2.3169 2022/10/08 05:06:09 - mmengine - INFO - Epoch(train) [103][1940/2119] lr: 4.0000e-03 eta: 9:37:13 time: 0.3716 data_time: 0.0252 memory: 5826 grad_norm: 3.3757 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2642 loss: 2.2642 2022/10/08 05:06:16 - mmengine - INFO - Epoch(train) [103][1960/2119] lr: 4.0000e-03 eta: 9:37:06 time: 0.3528 data_time: 0.0403 memory: 5826 grad_norm: 3.3806 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2113 loss: 2.2113 2022/10/08 05:06:22 - mmengine - INFO - Epoch(train) [103][1980/2119] lr: 4.0000e-03 eta: 9:36:58 time: 0.2899 data_time: 0.0280 memory: 5826 grad_norm: 3.3793 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1790 loss: 2.1790 2022/10/08 05:06:30 - mmengine - INFO - Epoch(train) [103][2000/2119] lr: 4.0000e-03 eta: 9:36:52 time: 0.3978 data_time: 0.0275 memory: 5826 grad_norm: 3.3847 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1287 loss: 2.1287 2022/10/08 05:06:36 - mmengine - INFO - Epoch(train) [103][2020/2119] lr: 4.0000e-03 eta: 9:36:44 time: 0.3077 data_time: 0.0234 memory: 5826 grad_norm: 3.3718 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1193 loss: 2.1193 2022/10/08 05:06:43 - mmengine - INFO - Epoch(train) [103][2040/2119] lr: 4.0000e-03 eta: 9:36:38 time: 0.3432 data_time: 0.0237 memory: 5826 grad_norm: 3.3750 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1416 loss: 2.1416 2022/10/08 05:06:49 - mmengine - INFO - Epoch(train) [103][2060/2119] lr: 4.0000e-03 eta: 9:36:30 time: 0.3332 data_time: 0.0232 memory: 5826 grad_norm: 3.4101 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1512 loss: 2.1512 2022/10/08 05:06:56 - mmengine - INFO - Epoch(train) [103][2080/2119] lr: 4.0000e-03 eta: 9:36:23 time: 0.3475 data_time: 0.0236 memory: 5826 grad_norm: 3.3987 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4023 loss: 2.4023 2022/10/08 05:07:03 - mmengine - INFO - Epoch(train) [103][2100/2119] lr: 4.0000e-03 eta: 9:36:16 time: 0.3336 data_time: 0.0219 memory: 5826 grad_norm: 3.4370 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.2390 loss: 2.2390 2022/10/08 05:07:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 05:07:09 - mmengine - INFO - Epoch(train) [103][2119/2119] lr: 4.0000e-03 eta: 9:36:16 time: 0.3185 data_time: 0.0256 memory: 5826 grad_norm: 3.3676 top1_acc: 0.4000 top5_acc: 0.6000 loss_cls: 2.1420 loss: 2.1420 2022/10/08 05:07:18 - mmengine - INFO - Epoch(train) [104][20/2119] lr: 4.0000e-03 eta: 9:36:01 time: 0.4699 data_time: 0.1271 memory: 5826 grad_norm: 3.4026 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.3405 loss: 2.3405 2022/10/08 05:07:26 - mmengine - INFO - Epoch(train) [104][40/2119] lr: 4.0000e-03 eta: 9:35:54 time: 0.3555 data_time: 0.0257 memory: 5826 grad_norm: 3.3266 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2193 loss: 2.2193 2022/10/08 05:07:33 - mmengine - INFO - Epoch(train) [104][60/2119] lr: 4.0000e-03 eta: 9:35:47 time: 0.3594 data_time: 0.0216 memory: 5826 grad_norm: 3.4256 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.4301 loss: 2.4301 2022/10/08 05:07:39 - mmengine - INFO - Epoch(train) [104][80/2119] lr: 4.0000e-03 eta: 9:35:40 time: 0.3319 data_time: 0.0241 memory: 5826 grad_norm: 3.4329 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.2124 loss: 2.2124 2022/10/08 05:07:46 - mmengine - INFO - Epoch(train) [104][100/2119] lr: 4.0000e-03 eta: 9:35:33 time: 0.3477 data_time: 0.0258 memory: 5826 grad_norm: 3.4097 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2552 loss: 2.2552 2022/10/08 05:07:54 - mmengine - INFO - Epoch(train) [104][120/2119] lr: 4.0000e-03 eta: 9:35:26 time: 0.3600 data_time: 0.0183 memory: 5826 grad_norm: 3.3962 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1493 loss: 2.1493 2022/10/08 05:08:01 - mmengine - INFO - Epoch(train) [104][140/2119] lr: 4.0000e-03 eta: 9:35:20 time: 0.3870 data_time: 0.0170 memory: 5826 grad_norm: 3.3974 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.2128 loss: 2.2128 2022/10/08 05:08:08 - mmengine - INFO - Epoch(train) [104][160/2119] lr: 4.0000e-03 eta: 9:35:13 time: 0.3224 data_time: 0.0258 memory: 5826 grad_norm: 3.4008 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.3778 loss: 2.3778 2022/10/08 05:08:16 - mmengine - INFO - Epoch(train) [104][180/2119] lr: 4.0000e-03 eta: 9:35:06 time: 0.3991 data_time: 0.0228 memory: 5826 grad_norm: 3.4208 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1397 loss: 2.1397 2022/10/08 05:08:22 - mmengine - INFO - Epoch(train) [104][200/2119] lr: 4.0000e-03 eta: 9:34:59 time: 0.3140 data_time: 0.0193 memory: 5826 grad_norm: 3.4244 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9176 loss: 1.9176 2022/10/08 05:08:29 - mmengine - INFO - Epoch(train) [104][220/2119] lr: 4.0000e-03 eta: 9:34:52 time: 0.3655 data_time: 0.0254 memory: 5826 grad_norm: 3.3948 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.2597 loss: 2.2597 2022/10/08 05:08:36 - mmengine - INFO - Epoch(train) [104][240/2119] lr: 4.0000e-03 eta: 9:34:45 time: 0.3509 data_time: 0.0201 memory: 5826 grad_norm: 3.3642 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2313 loss: 2.2313 2022/10/08 05:08:43 - mmengine - INFO - Epoch(train) [104][260/2119] lr: 4.0000e-03 eta: 9:34:38 time: 0.3233 data_time: 0.0255 memory: 5826 grad_norm: 3.4642 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.3275 loss: 2.3275 2022/10/08 05:08:50 - mmengine - INFO - Epoch(train) [104][280/2119] lr: 4.0000e-03 eta: 9:34:31 time: 0.3437 data_time: 0.0188 memory: 5826 grad_norm: 3.3923 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9002 loss: 1.9002 2022/10/08 05:08:58 - mmengine - INFO - Epoch(train) [104][300/2119] lr: 4.0000e-03 eta: 9:34:25 time: 0.3959 data_time: 0.0229 memory: 5826 grad_norm: 3.4354 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1956 loss: 2.1956 2022/10/08 05:09:04 - mmengine - INFO - Epoch(train) [104][320/2119] lr: 4.0000e-03 eta: 9:34:18 time: 0.3392 data_time: 0.0256 memory: 5826 grad_norm: 3.4050 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.2882 loss: 2.2882 2022/10/08 05:09:12 - mmengine - INFO - Epoch(train) [104][340/2119] lr: 4.0000e-03 eta: 9:34:11 time: 0.3579 data_time: 0.0184 memory: 5826 grad_norm: 3.3550 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1843 loss: 2.1843 2022/10/08 05:09:19 - mmengine - INFO - Epoch(train) [104][360/2119] lr: 4.0000e-03 eta: 9:34:04 time: 0.3521 data_time: 0.0209 memory: 5826 grad_norm: 3.3672 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.2089 loss: 2.2089 2022/10/08 05:09:27 - mmengine - INFO - Epoch(train) [104][380/2119] lr: 4.0000e-03 eta: 9:33:57 time: 0.4000 data_time: 0.0203 memory: 5826 grad_norm: 3.4806 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2053 loss: 2.2053 2022/10/08 05:09:33 - mmengine - INFO - Epoch(train) [104][400/2119] lr: 4.0000e-03 eta: 9:33:50 time: 0.3346 data_time: 0.0243 memory: 5826 grad_norm: 3.3869 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.2338 loss: 2.2338 2022/10/08 05:09:42 - mmengine - INFO - Epoch(train) [104][420/2119] lr: 4.0000e-03 eta: 9:33:44 time: 0.4297 data_time: 0.0228 memory: 5826 grad_norm: 3.4351 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1156 loss: 2.1156 2022/10/08 05:09:48 - mmengine - INFO - Epoch(train) [104][440/2119] lr: 4.0000e-03 eta: 9:33:37 time: 0.3116 data_time: 0.0244 memory: 5826 grad_norm: 3.4111 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2139 loss: 2.2139 2022/10/08 05:09:56 - mmengine - INFO - Epoch(train) [104][460/2119] lr: 4.0000e-03 eta: 9:33:30 time: 0.3810 data_time: 0.0262 memory: 5826 grad_norm: 3.4327 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2109 loss: 2.2109 2022/10/08 05:10:02 - mmengine - INFO - Epoch(train) [104][480/2119] lr: 4.0000e-03 eta: 9:33:23 time: 0.3178 data_time: 0.0263 memory: 5826 grad_norm: 3.4492 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.1002 loss: 2.1002 2022/10/08 05:10:10 - mmengine - INFO - Epoch(train) [104][500/2119] lr: 4.0000e-03 eta: 9:33:16 time: 0.3780 data_time: 0.0236 memory: 5826 grad_norm: 3.4648 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.2733 loss: 2.2733 2022/10/08 05:10:16 - mmengine - INFO - Epoch(train) [104][520/2119] lr: 4.0000e-03 eta: 9:33:09 time: 0.3354 data_time: 0.0194 memory: 5826 grad_norm: 3.4381 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.2274 loss: 2.2274 2022/10/08 05:10:24 - mmengine - INFO - Epoch(train) [104][540/2119] lr: 4.0000e-03 eta: 9:33:03 time: 0.3587 data_time: 0.0199 memory: 5826 grad_norm: 3.4164 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.2163 loss: 2.2163 2022/10/08 05:10:30 - mmengine - INFO - Epoch(train) [104][560/2119] lr: 4.0000e-03 eta: 9:32:56 time: 0.3412 data_time: 0.0216 memory: 5826 grad_norm: 3.4510 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5003 loss: 2.5003 2022/10/08 05:10:39 - mmengine - INFO - Epoch(train) [104][580/2119] lr: 4.0000e-03 eta: 9:32:49 time: 0.4349 data_time: 0.0217 memory: 5826 grad_norm: 3.4344 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0156 loss: 2.0156 2022/10/08 05:10:45 - mmengine - INFO - Epoch(train) [104][600/2119] lr: 4.0000e-03 eta: 9:32:42 time: 0.2893 data_time: 0.0247 memory: 5826 grad_norm: 3.4645 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1322 loss: 2.1322 2022/10/08 05:10:52 - mmengine - INFO - Epoch(train) [104][620/2119] lr: 4.0000e-03 eta: 9:32:35 time: 0.3742 data_time: 0.0259 memory: 5826 grad_norm: 3.4030 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0602 loss: 2.0602 2022/10/08 05:10:59 - mmengine - INFO - Epoch(train) [104][640/2119] lr: 4.0000e-03 eta: 9:32:28 time: 0.3209 data_time: 0.0208 memory: 5826 grad_norm: 3.4765 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0190 loss: 2.0190 2022/10/08 05:11:07 - mmengine - INFO - Epoch(train) [104][660/2119] lr: 4.0000e-03 eta: 9:32:22 time: 0.3975 data_time: 0.0237 memory: 5826 grad_norm: 3.4449 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.2509 loss: 2.2509 2022/10/08 05:11:13 - mmengine - INFO - Epoch(train) [104][680/2119] lr: 4.0000e-03 eta: 9:32:14 time: 0.3096 data_time: 0.0224 memory: 5826 grad_norm: 3.4572 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1108 loss: 2.1108 2022/10/08 05:11:21 - mmengine - INFO - Epoch(train) [104][700/2119] lr: 4.0000e-03 eta: 9:32:08 time: 0.3728 data_time: 0.0224 memory: 5826 grad_norm: 3.4624 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2416 loss: 2.2416 2022/10/08 05:11:27 - mmengine - INFO - Epoch(train) [104][720/2119] lr: 4.0000e-03 eta: 9:32:00 time: 0.3203 data_time: 0.0238 memory: 5826 grad_norm: 3.4148 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.2766 loss: 2.2766 2022/10/08 05:11:35 - mmengine - INFO - Epoch(train) [104][740/2119] lr: 4.0000e-03 eta: 9:31:54 time: 0.3833 data_time: 0.0202 memory: 5826 grad_norm: 3.4612 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2183 loss: 2.2183 2022/10/08 05:11:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 05:11:41 - mmengine - INFO - Epoch(train) [104][760/2119] lr: 4.0000e-03 eta: 9:31:47 time: 0.3352 data_time: 0.0245 memory: 5826 grad_norm: 3.3788 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1051 loss: 2.1051 2022/10/08 05:11:48 - mmengine - INFO - Epoch(train) [104][780/2119] lr: 4.0000e-03 eta: 9:31:40 time: 0.3567 data_time: 0.0254 memory: 5826 grad_norm: 3.4511 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1530 loss: 2.1530 2022/10/08 05:11:54 - mmengine - INFO - Epoch(train) [104][800/2119] lr: 4.0000e-03 eta: 9:31:33 time: 0.2973 data_time: 0.0213 memory: 5826 grad_norm: 3.4647 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9616 loss: 1.9616 2022/10/08 05:12:02 - mmengine - INFO - Epoch(train) [104][820/2119] lr: 4.0000e-03 eta: 9:31:26 time: 0.4016 data_time: 0.0183 memory: 5826 grad_norm: 3.4697 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.2285 loss: 2.2285 2022/10/08 05:12:10 - mmengine - INFO - Epoch(train) [104][840/2119] lr: 4.0000e-03 eta: 9:31:19 time: 0.3573 data_time: 0.0241 memory: 5826 grad_norm: 3.4493 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2344 loss: 2.2344 2022/10/08 05:12:17 - mmengine - INFO - Epoch(train) [104][860/2119] lr: 4.0000e-03 eta: 9:31:12 time: 0.3501 data_time: 0.0209 memory: 5826 grad_norm: 3.4471 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0183 loss: 2.0183 2022/10/08 05:12:23 - mmengine - INFO - Epoch(train) [104][880/2119] lr: 4.0000e-03 eta: 9:31:05 time: 0.3315 data_time: 0.0215 memory: 5826 grad_norm: 3.4494 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.1730 loss: 2.1730 2022/10/08 05:12:30 - mmengine - INFO - Epoch(train) [104][900/2119] lr: 4.0000e-03 eta: 9:30:58 time: 0.3564 data_time: 0.0248 memory: 5826 grad_norm: 3.4632 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8524 loss: 1.8524 2022/10/08 05:12:38 - mmengine - INFO - Epoch(train) [104][920/2119] lr: 4.0000e-03 eta: 9:30:52 time: 0.3605 data_time: 0.0191 memory: 5826 grad_norm: 3.4458 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.3043 loss: 2.3043 2022/10/08 05:12:44 - mmengine - INFO - Epoch(train) [104][940/2119] lr: 4.0000e-03 eta: 9:30:44 time: 0.3232 data_time: 0.0178 memory: 5826 grad_norm: 3.4262 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.2415 loss: 2.2415 2022/10/08 05:12:51 - mmengine - INFO - Epoch(train) [104][960/2119] lr: 4.0000e-03 eta: 9:30:37 time: 0.3418 data_time: 0.0187 memory: 5826 grad_norm: 3.4614 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9121 loss: 1.9121 2022/10/08 05:12:59 - mmengine - INFO - Epoch(train) [104][980/2119] lr: 4.0000e-03 eta: 9:30:31 time: 0.3902 data_time: 0.0267 memory: 5826 grad_norm: 3.4305 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.2006 loss: 2.2006 2022/10/08 05:13:06 - mmengine - INFO - Epoch(train) [104][1000/2119] lr: 4.0000e-03 eta: 9:30:24 time: 0.3567 data_time: 0.0193 memory: 5826 grad_norm: 3.4547 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0579 loss: 2.0579 2022/10/08 05:13:13 - mmengine - INFO - Epoch(train) [104][1020/2119] lr: 4.0000e-03 eta: 9:30:17 time: 0.3404 data_time: 0.0268 memory: 5826 grad_norm: 3.4573 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1761 loss: 2.1761 2022/10/08 05:13:19 - mmengine - INFO - Epoch(train) [104][1040/2119] lr: 4.0000e-03 eta: 9:30:10 time: 0.3254 data_time: 0.0260 memory: 5826 grad_norm: 3.4145 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.2278 loss: 2.2278 2022/10/08 05:13:26 - mmengine - INFO - Epoch(train) [104][1060/2119] lr: 4.0000e-03 eta: 9:30:03 time: 0.3556 data_time: 0.0212 memory: 5826 grad_norm: 3.4578 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.4562 loss: 2.4562 2022/10/08 05:13:34 - mmengine - INFO - Epoch(train) [104][1080/2119] lr: 4.0000e-03 eta: 9:29:56 time: 0.3656 data_time: 0.0273 memory: 5826 grad_norm: 3.4725 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9823 loss: 1.9823 2022/10/08 05:13:40 - mmengine - INFO - Epoch(train) [104][1100/2119] lr: 4.0000e-03 eta: 9:29:49 time: 0.3037 data_time: 0.0208 memory: 5826 grad_norm: 3.4072 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.1632 loss: 2.1632 2022/10/08 05:13:48 - mmengine - INFO - Epoch(train) [104][1120/2119] lr: 4.0000e-03 eta: 9:29:42 time: 0.3931 data_time: 0.0274 memory: 5826 grad_norm: 3.4725 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.3609 loss: 2.3609 2022/10/08 05:13:54 - mmengine - INFO - Epoch(train) [104][1140/2119] lr: 4.0000e-03 eta: 9:29:35 time: 0.3111 data_time: 0.0198 memory: 5826 grad_norm: 3.4453 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1393 loss: 2.1393 2022/10/08 05:14:01 - mmengine - INFO - Epoch(train) [104][1160/2119] lr: 4.0000e-03 eta: 9:29:28 time: 0.3707 data_time: 0.0247 memory: 5826 grad_norm: 3.4730 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1494 loss: 2.1494 2022/10/08 05:14:08 - mmengine - INFO - Epoch(train) [104][1180/2119] lr: 4.0000e-03 eta: 9:29:22 time: 0.3615 data_time: 0.0208 memory: 5826 grad_norm: 3.5144 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2344 loss: 2.2344 2022/10/08 05:14:16 - mmengine - INFO - Epoch(train) [104][1200/2119] lr: 4.0000e-03 eta: 9:29:15 time: 0.3535 data_time: 0.0194 memory: 5826 grad_norm: 3.5411 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.2285 loss: 2.2285 2022/10/08 05:14:22 - mmengine - INFO - Epoch(train) [104][1220/2119] lr: 4.0000e-03 eta: 9:29:08 time: 0.3391 data_time: 0.0184 memory: 5826 grad_norm: 3.4265 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.0690 loss: 2.0690 2022/10/08 05:14:29 - mmengine - INFO - Epoch(train) [104][1240/2119] lr: 4.0000e-03 eta: 9:29:01 time: 0.3470 data_time: 0.0221 memory: 5826 grad_norm: 3.4776 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.1783 loss: 2.1783 2022/10/08 05:14:37 - mmengine - INFO - Epoch(train) [104][1260/2119] lr: 4.0000e-03 eta: 9:28:54 time: 0.3985 data_time: 0.0239 memory: 5826 grad_norm: 3.4486 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0866 loss: 2.0866 2022/10/08 05:14:43 - mmengine - INFO - Epoch(train) [104][1280/2119] lr: 4.0000e-03 eta: 9:28:47 time: 0.2919 data_time: 0.0217 memory: 5826 grad_norm: 3.4775 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.1802 loss: 2.1802 2022/10/08 05:14:50 - mmengine - INFO - Epoch(train) [104][1300/2119] lr: 4.0000e-03 eta: 9:28:40 time: 0.3508 data_time: 0.0245 memory: 5826 grad_norm: 3.4816 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9002 loss: 1.9002 2022/10/08 05:14:57 - mmengine - INFO - Epoch(train) [104][1320/2119] lr: 4.0000e-03 eta: 9:28:33 time: 0.3647 data_time: 0.0247 memory: 5826 grad_norm: 3.3960 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3315 loss: 2.3315 2022/10/08 05:15:05 - mmengine - INFO - Epoch(train) [104][1340/2119] lr: 4.0000e-03 eta: 9:28:26 time: 0.3660 data_time: 0.0260 memory: 5826 grad_norm: 3.4773 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2097 loss: 2.2097 2022/10/08 05:15:12 - mmengine - INFO - Epoch(train) [104][1360/2119] lr: 4.0000e-03 eta: 9:28:19 time: 0.3455 data_time: 0.0227 memory: 5826 grad_norm: 3.4963 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9705 loss: 1.9705 2022/10/08 05:15:19 - mmengine - INFO - Epoch(train) [104][1380/2119] lr: 4.0000e-03 eta: 9:28:13 time: 0.3683 data_time: 0.0178 memory: 5826 grad_norm: 3.4364 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 2.0012 loss: 2.0012 2022/10/08 05:15:26 - mmengine - INFO - Epoch(train) [104][1400/2119] lr: 4.0000e-03 eta: 9:28:06 time: 0.3471 data_time: 0.0242 memory: 5826 grad_norm: 3.4786 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2989 loss: 2.2989 2022/10/08 05:15:33 - mmengine - INFO - Epoch(train) [104][1420/2119] lr: 4.0000e-03 eta: 9:27:59 time: 0.3669 data_time: 0.0268 memory: 5826 grad_norm: 3.4865 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0908 loss: 2.0908 2022/10/08 05:15:39 - mmengine - INFO - Epoch(train) [104][1440/2119] lr: 4.0000e-03 eta: 9:27:52 time: 0.3066 data_time: 0.0230 memory: 5826 grad_norm: 3.4633 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1623 loss: 2.1623 2022/10/08 05:15:47 - mmengine - INFO - Epoch(train) [104][1460/2119] lr: 4.0000e-03 eta: 9:27:45 time: 0.3825 data_time: 0.0202 memory: 5826 grad_norm: 3.4917 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0191 loss: 2.0191 2022/10/08 05:15:54 - mmengine - INFO - Epoch(train) [104][1480/2119] lr: 4.0000e-03 eta: 9:27:38 time: 0.3495 data_time: 0.0244 memory: 5826 grad_norm: 3.4729 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1104 loss: 2.1104 2022/10/08 05:16:01 - mmengine - INFO - Epoch(train) [104][1500/2119] lr: 4.0000e-03 eta: 9:27:31 time: 0.3633 data_time: 0.0225 memory: 5826 grad_norm: 3.4529 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2173 loss: 2.2173 2022/10/08 05:16:08 - mmengine - INFO - Epoch(train) [104][1520/2119] lr: 4.0000e-03 eta: 9:27:24 time: 0.3343 data_time: 0.0199 memory: 5826 grad_norm: 3.4547 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3118 loss: 2.3118 2022/10/08 05:16:16 - mmengine - INFO - Epoch(train) [104][1540/2119] lr: 4.0000e-03 eta: 9:27:18 time: 0.3902 data_time: 0.0215 memory: 5826 grad_norm: 3.4293 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9364 loss: 1.9364 2022/10/08 05:16:23 - mmengine - INFO - Epoch(train) [104][1560/2119] lr: 4.0000e-03 eta: 9:27:11 time: 0.3375 data_time: 0.0212 memory: 5826 grad_norm: 3.4579 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2569 loss: 2.2569 2022/10/08 05:16:31 - mmengine - INFO - Epoch(train) [104][1580/2119] lr: 4.0000e-03 eta: 9:27:04 time: 0.3910 data_time: 0.0211 memory: 5826 grad_norm: 3.4785 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9664 loss: 1.9664 2022/10/08 05:16:37 - mmengine - INFO - Epoch(train) [104][1600/2119] lr: 4.0000e-03 eta: 9:26:57 time: 0.3284 data_time: 0.0236 memory: 5826 grad_norm: 3.4771 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1696 loss: 2.1696 2022/10/08 05:16:46 - mmengine - INFO - Epoch(train) [104][1620/2119] lr: 4.0000e-03 eta: 9:26:51 time: 0.4595 data_time: 0.0202 memory: 5826 grad_norm: 3.4516 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0485 loss: 2.0485 2022/10/08 05:16:52 - mmengine - INFO - Epoch(train) [104][1640/2119] lr: 4.0000e-03 eta: 9:26:43 time: 0.2852 data_time: 0.0216 memory: 5826 grad_norm: 3.4824 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0132 loss: 2.0132 2022/10/08 05:16:59 - mmengine - INFO - Epoch(train) [104][1660/2119] lr: 4.0000e-03 eta: 9:26:37 time: 0.3696 data_time: 0.0196 memory: 5826 grad_norm: 3.4509 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.3634 loss: 2.3634 2022/10/08 05:17:06 - mmengine - INFO - Epoch(train) [104][1680/2119] lr: 4.0000e-03 eta: 9:26:30 time: 0.3423 data_time: 0.0216 memory: 5826 grad_norm: 3.5130 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.2879 loss: 2.2879 2022/10/08 05:17:13 - mmengine - INFO - Epoch(train) [104][1700/2119] lr: 4.0000e-03 eta: 9:26:23 time: 0.3611 data_time: 0.0205 memory: 5826 grad_norm: 3.4587 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.3125 loss: 2.3125 2022/10/08 05:17:21 - mmengine - INFO - Epoch(train) [104][1720/2119] lr: 4.0000e-03 eta: 9:26:16 time: 0.3753 data_time: 0.0257 memory: 5826 grad_norm: 3.4978 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.2078 loss: 2.2078 2022/10/08 05:17:28 - mmengine - INFO - Epoch(train) [104][1740/2119] lr: 4.0000e-03 eta: 9:26:09 time: 0.3347 data_time: 0.0192 memory: 5826 grad_norm: 3.5424 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1552 loss: 2.1552 2022/10/08 05:17:29 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 05:17:36 - mmengine - INFO - Epoch(train) [104][1760/2119] lr: 4.0000e-03 eta: 9:26:03 time: 0.3995 data_time: 0.0265 memory: 5826 grad_norm: 3.5072 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.1168 loss: 2.1168 2022/10/08 05:17:41 - mmengine - INFO - Epoch(train) [104][1780/2119] lr: 4.0000e-03 eta: 9:25:55 time: 0.2842 data_time: 0.0230 memory: 5826 grad_norm: 3.4450 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.1608 loss: 2.1608 2022/10/08 05:17:49 - mmengine - INFO - Epoch(train) [104][1800/2119] lr: 4.0000e-03 eta: 9:25:49 time: 0.3922 data_time: 0.0232 memory: 5826 grad_norm: 3.4461 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.2160 loss: 2.2160 2022/10/08 05:17:57 - mmengine - INFO - Epoch(train) [104][1820/2119] lr: 4.0000e-03 eta: 9:25:42 time: 0.3658 data_time: 0.0210 memory: 5826 grad_norm: 3.4624 top1_acc: 0.2500 top5_acc: 0.8125 loss_cls: 2.1668 loss: 2.1668 2022/10/08 05:18:03 - mmengine - INFO - Epoch(train) [104][1840/2119] lr: 4.0000e-03 eta: 9:25:35 time: 0.3430 data_time: 0.0221 memory: 5826 grad_norm: 3.4942 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.3449 loss: 2.3449 2022/10/08 05:18:10 - mmengine - INFO - Epoch(train) [104][1860/2119] lr: 4.0000e-03 eta: 9:25:28 time: 0.3439 data_time: 0.0326 memory: 5826 grad_norm: 3.5343 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0986 loss: 2.0986 2022/10/08 05:18:19 - mmengine - INFO - Epoch(train) [104][1880/2119] lr: 4.0000e-03 eta: 9:25:22 time: 0.4165 data_time: 0.0236 memory: 5826 grad_norm: 3.5217 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.6425 loss: 2.6425 2022/10/08 05:18:25 - mmengine - INFO - Epoch(train) [104][1900/2119] lr: 4.0000e-03 eta: 9:25:14 time: 0.3111 data_time: 0.0202 memory: 5826 grad_norm: 3.4197 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.1945 loss: 2.1945 2022/10/08 05:18:32 - mmengine - INFO - Epoch(train) [104][1920/2119] lr: 4.0000e-03 eta: 9:25:07 time: 0.3577 data_time: 0.0211 memory: 5826 grad_norm: 3.4893 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0954 loss: 2.0954 2022/10/08 05:18:39 - mmengine - INFO - Epoch(train) [104][1940/2119] lr: 4.0000e-03 eta: 9:25:01 time: 0.3629 data_time: 0.0193 memory: 5826 grad_norm: 3.5259 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0885 loss: 2.0885 2022/10/08 05:18:47 - mmengine - INFO - Epoch(train) [104][1960/2119] lr: 4.0000e-03 eta: 9:24:54 time: 0.3784 data_time: 0.0225 memory: 5826 grad_norm: 3.5087 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.3635 loss: 2.3635 2022/10/08 05:18:53 - mmengine - INFO - Epoch(train) [104][1980/2119] lr: 4.0000e-03 eta: 9:24:47 time: 0.3163 data_time: 0.0228 memory: 5826 grad_norm: 3.5104 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0687 loss: 2.0687 2022/10/08 05:19:01 - mmengine - INFO - Epoch(train) [104][2000/2119] lr: 4.0000e-03 eta: 9:24:40 time: 0.3763 data_time: 0.0229 memory: 5826 grad_norm: 3.4882 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2852 loss: 2.2852 2022/10/08 05:19:07 - mmengine - INFO - Epoch(train) [104][2020/2119] lr: 4.0000e-03 eta: 9:24:33 time: 0.3033 data_time: 0.0243 memory: 5826 grad_norm: 3.5453 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8687 loss: 1.8687 2022/10/08 05:19:14 - mmengine - INFO - Epoch(train) [104][2040/2119] lr: 4.0000e-03 eta: 9:24:26 time: 0.3808 data_time: 0.0200 memory: 5826 grad_norm: 3.4637 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0092 loss: 2.0092 2022/10/08 05:19:22 - mmengine - INFO - Epoch(train) [104][2060/2119] lr: 4.0000e-03 eta: 9:24:19 time: 0.3640 data_time: 0.0196 memory: 5826 grad_norm: 3.5417 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0269 loss: 2.0269 2022/10/08 05:19:29 - mmengine - INFO - Epoch(train) [104][2080/2119] lr: 4.0000e-03 eta: 9:24:12 time: 0.3577 data_time: 0.0204 memory: 5826 grad_norm: 3.5255 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0724 loss: 2.0724 2022/10/08 05:19:35 - mmengine - INFO - Epoch(train) [104][2100/2119] lr: 4.0000e-03 eta: 9:24:05 time: 0.3147 data_time: 0.0201 memory: 5826 grad_norm: 3.4833 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 2.2440 loss: 2.2440 2022/10/08 05:19:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 05:19:41 - mmengine - INFO - Epoch(train) [104][2119/2119] lr: 4.0000e-03 eta: 9:24:05 time: 0.3183 data_time: 0.0214 memory: 5826 grad_norm: 3.4980 top1_acc: 0.5000 top5_acc: 0.8000 loss_cls: 2.2255 loss: 2.2255 2022/10/08 05:19:41 - mmengine - INFO - Saving checkpoint at 104 epochs 2022/10/08 05:19:52 - mmengine - INFO - Epoch(train) [105][20/2119] lr: 4.0000e-03 eta: 9:23:50 time: 0.4495 data_time: 0.2173 memory: 5826 grad_norm: 3.4491 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0131 loss: 2.0131 2022/10/08 05:19:59 - mmengine - INFO - Epoch(train) [105][40/2119] lr: 4.0000e-03 eta: 9:23:42 time: 0.3071 data_time: 0.0771 memory: 5826 grad_norm: 3.5123 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.1506 loss: 2.1506 2022/10/08 05:20:06 - mmengine - INFO - Epoch(train) [105][60/2119] lr: 4.0000e-03 eta: 9:23:36 time: 0.3529 data_time: 0.0578 memory: 5826 grad_norm: 3.4499 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9479 loss: 1.9479 2022/10/08 05:20:13 - mmengine - INFO - Epoch(train) [105][80/2119] lr: 4.0000e-03 eta: 9:23:29 time: 0.3561 data_time: 0.0185 memory: 5826 grad_norm: 3.4650 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0066 loss: 2.0066 2022/10/08 05:20:20 - mmengine - INFO - Epoch(train) [105][100/2119] lr: 4.0000e-03 eta: 9:23:22 time: 0.3524 data_time: 0.0207 memory: 5826 grad_norm: 3.5063 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0116 loss: 2.0116 2022/10/08 05:20:27 - mmengine - INFO - Epoch(train) [105][120/2119] lr: 4.0000e-03 eta: 9:23:15 time: 0.3373 data_time: 0.0289 memory: 5826 grad_norm: 3.5430 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0223 loss: 2.0223 2022/10/08 05:20:34 - mmengine - INFO - Epoch(train) [105][140/2119] lr: 4.0000e-03 eta: 9:23:08 time: 0.3767 data_time: 0.0219 memory: 5826 grad_norm: 3.4886 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.2218 loss: 2.2218 2022/10/08 05:20:41 - mmengine - INFO - Epoch(train) [105][160/2119] lr: 4.0000e-03 eta: 9:23:01 time: 0.3358 data_time: 0.0237 memory: 5826 grad_norm: 3.5357 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.3073 loss: 2.3073 2022/10/08 05:20:48 - mmengine - INFO - Epoch(train) [105][180/2119] lr: 4.0000e-03 eta: 9:22:54 time: 0.3603 data_time: 0.0263 memory: 5826 grad_norm: 3.4642 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0795 loss: 2.0795 2022/10/08 05:20:55 - mmengine - INFO - Epoch(train) [105][200/2119] lr: 4.0000e-03 eta: 9:22:47 time: 0.3434 data_time: 0.0219 memory: 5826 grad_norm: 3.5389 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.3022 loss: 2.3022 2022/10/08 05:21:02 - mmengine - INFO - Epoch(train) [105][220/2119] lr: 4.0000e-03 eta: 9:22:40 time: 0.3679 data_time: 0.0172 memory: 5826 grad_norm: 3.4744 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2422 loss: 2.2422 2022/10/08 05:21:09 - mmengine - INFO - Epoch(train) [105][240/2119] lr: 4.0000e-03 eta: 9:22:34 time: 0.3498 data_time: 0.0211 memory: 5826 grad_norm: 3.4690 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0421 loss: 2.0421 2022/10/08 05:21:16 - mmengine - INFO - Epoch(train) [105][260/2119] lr: 4.0000e-03 eta: 9:22:27 time: 0.3440 data_time: 0.0233 memory: 5826 grad_norm: 3.4934 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.3293 loss: 2.3293 2022/10/08 05:21:23 - mmengine - INFO - Epoch(train) [105][280/2119] lr: 4.0000e-03 eta: 9:22:19 time: 0.3181 data_time: 0.0227 memory: 5826 grad_norm: 3.4776 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1620 loss: 2.1620 2022/10/08 05:21:29 - mmengine - INFO - Epoch(train) [105][300/2119] lr: 4.0000e-03 eta: 9:22:12 time: 0.3368 data_time: 0.0182 memory: 5826 grad_norm: 3.4921 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8235 loss: 1.8235 2022/10/08 05:21:37 - mmengine - INFO - Epoch(train) [105][320/2119] lr: 4.0000e-03 eta: 9:22:06 time: 0.3757 data_time: 0.0245 memory: 5826 grad_norm: 3.4844 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9698 loss: 1.9698 2022/10/08 05:21:44 - mmengine - INFO - Epoch(train) [105][340/2119] lr: 4.0000e-03 eta: 9:21:59 time: 0.3478 data_time: 0.0238 memory: 5826 grad_norm: 3.4552 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 2.1791 loss: 2.1791 2022/10/08 05:21:51 - mmengine - INFO - Epoch(train) [105][360/2119] lr: 4.0000e-03 eta: 9:21:52 time: 0.3666 data_time: 0.0193 memory: 5826 grad_norm: 3.5499 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.3000 loss: 2.3000 2022/10/08 05:21:58 - mmengine - INFO - Epoch(train) [105][380/2119] lr: 4.0000e-03 eta: 9:21:45 time: 0.3589 data_time: 0.0190 memory: 5826 grad_norm: 3.5227 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9106 loss: 1.9106 2022/10/08 05:22:06 - mmengine - INFO - Epoch(train) [105][400/2119] lr: 4.0000e-03 eta: 9:21:39 time: 0.3893 data_time: 0.0241 memory: 5826 grad_norm: 3.4612 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1431 loss: 2.1431 2022/10/08 05:22:13 - mmengine - INFO - Epoch(train) [105][420/2119] lr: 4.0000e-03 eta: 9:21:32 time: 0.3664 data_time: 0.0198 memory: 5826 grad_norm: 3.5531 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.1025 loss: 2.1025 2022/10/08 05:22:20 - mmengine - INFO - Epoch(train) [105][440/2119] lr: 4.0000e-03 eta: 9:21:25 time: 0.3342 data_time: 0.0229 memory: 5826 grad_norm: 3.4650 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9720 loss: 1.9720 2022/10/08 05:22:28 - mmengine - INFO - Epoch(train) [105][460/2119] lr: 4.0000e-03 eta: 9:21:18 time: 0.4063 data_time: 0.0232 memory: 5826 grad_norm: 3.5334 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2021 loss: 2.2021 2022/10/08 05:22:35 - mmengine - INFO - Epoch(train) [105][480/2119] lr: 4.0000e-03 eta: 9:21:11 time: 0.3284 data_time: 0.0243 memory: 5826 grad_norm: 3.4704 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.2476 loss: 2.2476 2022/10/08 05:22:42 - mmengine - INFO - Epoch(train) [105][500/2119] lr: 4.0000e-03 eta: 9:21:04 time: 0.3463 data_time: 0.0266 memory: 5826 grad_norm: 3.4779 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1522 loss: 2.1522 2022/10/08 05:22:49 - mmengine - INFO - Epoch(train) [105][520/2119] lr: 4.0000e-03 eta: 9:20:57 time: 0.3632 data_time: 0.0198 memory: 5826 grad_norm: 3.5306 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2470 loss: 2.2470 2022/10/08 05:22:57 - mmengine - INFO - Epoch(train) [105][540/2119] lr: 4.0000e-03 eta: 9:20:51 time: 0.3789 data_time: 0.0221 memory: 5826 grad_norm: 3.4739 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1733 loss: 2.1733 2022/10/08 05:23:04 - mmengine - INFO - Epoch(train) [105][560/2119] lr: 4.0000e-03 eta: 9:20:44 time: 0.3448 data_time: 0.0213 memory: 5826 grad_norm: 3.4934 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.1681 loss: 2.1681 2022/10/08 05:23:11 - mmengine - INFO - Epoch(train) [105][580/2119] lr: 4.0000e-03 eta: 9:20:37 time: 0.3608 data_time: 0.0203 memory: 5826 grad_norm: 3.4173 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9211 loss: 1.9211 2022/10/08 05:23:18 - mmengine - INFO - Epoch(train) [105][600/2119] lr: 4.0000e-03 eta: 9:20:30 time: 0.3572 data_time: 0.0192 memory: 5826 grad_norm: 3.5144 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1190 loss: 2.1190 2022/10/08 05:23:25 - mmengine - INFO - Epoch(train) [105][620/2119] lr: 4.0000e-03 eta: 9:20:23 time: 0.3321 data_time: 0.0218 memory: 5826 grad_norm: 3.5425 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0777 loss: 2.0777 2022/10/08 05:23:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 05:23:31 - mmengine - INFO - Epoch(train) [105][640/2119] lr: 4.0000e-03 eta: 9:20:16 time: 0.3229 data_time: 0.0260 memory: 5826 grad_norm: 3.5030 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0931 loss: 2.0931 2022/10/08 05:23:39 - mmengine - INFO - Epoch(train) [105][660/2119] lr: 4.0000e-03 eta: 9:20:09 time: 0.3977 data_time: 0.0199 memory: 5826 grad_norm: 3.5387 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.1345 loss: 2.1345 2022/10/08 05:23:46 - mmengine - INFO - Epoch(train) [105][680/2119] lr: 4.0000e-03 eta: 9:20:02 time: 0.3403 data_time: 0.0239 memory: 5826 grad_norm: 3.4932 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9750 loss: 1.9750 2022/10/08 05:23:54 - mmengine - INFO - Epoch(train) [105][700/2119] lr: 4.0000e-03 eta: 9:19:56 time: 0.3850 data_time: 0.0225 memory: 5826 grad_norm: 3.5357 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1877 loss: 2.1877 2022/10/08 05:24:00 - mmengine - INFO - Epoch(train) [105][720/2119] lr: 4.0000e-03 eta: 9:19:48 time: 0.3125 data_time: 0.0223 memory: 5826 grad_norm: 3.5173 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.0022 loss: 2.0022 2022/10/08 05:24:08 - mmengine - INFO - Epoch(train) [105][740/2119] lr: 4.0000e-03 eta: 9:19:42 time: 0.3966 data_time: 0.0199 memory: 5826 grad_norm: 3.5144 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3406 loss: 2.3406 2022/10/08 05:24:15 - mmengine - INFO - Epoch(train) [105][760/2119] lr: 4.0000e-03 eta: 9:19:35 time: 0.3433 data_time: 0.0199 memory: 5826 grad_norm: 3.5025 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9988 loss: 1.9988 2022/10/08 05:24:22 - mmengine - INFO - Epoch(train) [105][780/2119] lr: 4.0000e-03 eta: 9:19:28 time: 0.3731 data_time: 0.0186 memory: 5826 grad_norm: 3.5404 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1033 loss: 2.1033 2022/10/08 05:24:29 - mmengine - INFO - Epoch(train) [105][800/2119] lr: 4.0000e-03 eta: 9:19:21 time: 0.3287 data_time: 0.0248 memory: 5826 grad_norm: 3.5231 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1624 loss: 2.1624 2022/10/08 05:24:37 - mmengine - INFO - Epoch(train) [105][820/2119] lr: 4.0000e-03 eta: 9:19:15 time: 0.4307 data_time: 0.0272 memory: 5826 grad_norm: 3.5041 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.3159 loss: 2.3159 2022/10/08 05:24:43 - mmengine - INFO - Epoch(train) [105][840/2119] lr: 4.0000e-03 eta: 9:19:07 time: 0.2853 data_time: 0.0260 memory: 5826 grad_norm: 3.4935 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2605 loss: 2.2605 2022/10/08 05:24:50 - mmengine - INFO - Epoch(train) [105][860/2119] lr: 4.0000e-03 eta: 9:19:01 time: 0.3440 data_time: 0.0215 memory: 5826 grad_norm: 3.4635 top1_acc: 0.5625 top5_acc: 1.0000 loss_cls: 2.1297 loss: 2.1297 2022/10/08 05:24:56 - mmengine - INFO - Epoch(train) [105][880/2119] lr: 4.0000e-03 eta: 9:18:53 time: 0.3184 data_time: 0.0315 memory: 5826 grad_norm: 3.5283 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.2780 loss: 2.2780 2022/10/08 05:25:04 - mmengine - INFO - Epoch(train) [105][900/2119] lr: 4.0000e-03 eta: 9:18:47 time: 0.3865 data_time: 0.0242 memory: 5826 grad_norm: 3.5541 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.3077 loss: 2.3077 2022/10/08 05:25:11 - mmengine - INFO - Epoch(train) [105][920/2119] lr: 4.0000e-03 eta: 9:18:40 time: 0.3591 data_time: 0.0253 memory: 5826 grad_norm: 3.5875 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.1056 loss: 2.1056 2022/10/08 05:25:19 - mmengine - INFO - Epoch(train) [105][940/2119] lr: 4.0000e-03 eta: 9:18:33 time: 0.3688 data_time: 0.0190 memory: 5826 grad_norm: 3.5100 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9001 loss: 1.9001 2022/10/08 05:25:25 - mmengine - INFO - Epoch(train) [105][960/2119] lr: 4.0000e-03 eta: 9:18:26 time: 0.3301 data_time: 0.0251 memory: 5826 grad_norm: 3.4922 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1441 loss: 2.1441 2022/10/08 05:25:32 - mmengine - INFO - Epoch(train) [105][980/2119] lr: 4.0000e-03 eta: 9:18:19 time: 0.3562 data_time: 0.0159 memory: 5826 grad_norm: 3.5878 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1608 loss: 2.1608 2022/10/08 05:25:39 - mmengine - INFO - Epoch(train) [105][1000/2119] lr: 4.0000e-03 eta: 9:18:12 time: 0.3409 data_time: 0.0264 memory: 5826 grad_norm: 3.5510 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2084 loss: 2.2084 2022/10/08 05:25:46 - mmengine - INFO - Epoch(train) [105][1020/2119] lr: 4.0000e-03 eta: 9:18:05 time: 0.3471 data_time: 0.0219 memory: 5826 grad_norm: 3.5557 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0072 loss: 2.0072 2022/10/08 05:25:53 - mmengine - INFO - Epoch(train) [105][1040/2119] lr: 4.0000e-03 eta: 9:17:58 time: 0.3626 data_time: 0.0197 memory: 5826 grad_norm: 3.5520 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3490 loss: 2.3490 2022/10/08 05:26:00 - mmengine - INFO - Epoch(train) [105][1060/2119] lr: 4.0000e-03 eta: 9:17:51 time: 0.3389 data_time: 0.0309 memory: 5826 grad_norm: 3.5377 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1965 loss: 2.1965 2022/10/08 05:26:08 - mmengine - INFO - Epoch(train) [105][1080/2119] lr: 4.0000e-03 eta: 9:17:45 time: 0.3807 data_time: 0.0219 memory: 5826 grad_norm: 3.5982 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1305 loss: 2.1305 2022/10/08 05:26:16 - mmengine - INFO - Epoch(train) [105][1100/2119] lr: 4.0000e-03 eta: 9:17:38 time: 0.3948 data_time: 0.0233 memory: 5826 grad_norm: 3.4746 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.2447 loss: 2.2447 2022/10/08 05:26:22 - mmengine - INFO - Epoch(train) [105][1120/2119] lr: 4.0000e-03 eta: 9:17:31 time: 0.3217 data_time: 0.0233 memory: 5826 grad_norm: 3.5344 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3937 loss: 2.3937 2022/10/08 05:26:30 - mmengine - INFO - Epoch(train) [105][1140/2119] lr: 4.0000e-03 eta: 9:17:25 time: 0.4124 data_time: 0.0197 memory: 5826 grad_norm: 3.4720 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.1021 loss: 2.1021 2022/10/08 05:26:37 - mmengine - INFO - Epoch(train) [105][1160/2119] lr: 4.0000e-03 eta: 9:17:17 time: 0.3192 data_time: 0.0228 memory: 5826 grad_norm: 3.5188 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0612 loss: 2.0612 2022/10/08 05:26:44 - mmengine - INFO - Epoch(train) [105][1180/2119] lr: 4.0000e-03 eta: 9:17:11 time: 0.3877 data_time: 0.0208 memory: 5826 grad_norm: 3.4324 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0475 loss: 2.0475 2022/10/08 05:26:51 - mmengine - INFO - Epoch(train) [105][1200/2119] lr: 4.0000e-03 eta: 9:17:04 time: 0.3345 data_time: 0.0238 memory: 5826 grad_norm: 3.4378 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0045 loss: 2.0045 2022/10/08 05:26:59 - mmengine - INFO - Epoch(train) [105][1220/2119] lr: 4.0000e-03 eta: 9:16:57 time: 0.4139 data_time: 0.0306 memory: 5826 grad_norm: 3.4998 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1819 loss: 2.1819 2022/10/08 05:27:06 - mmengine - INFO - Epoch(train) [105][1240/2119] lr: 4.0000e-03 eta: 9:16:50 time: 0.3328 data_time: 0.0266 memory: 5826 grad_norm: 3.5439 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.1589 loss: 2.1589 2022/10/08 05:27:14 - mmengine - INFO - Epoch(train) [105][1260/2119] lr: 4.0000e-03 eta: 9:16:44 time: 0.3907 data_time: 0.0197 memory: 5826 grad_norm: 3.5856 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2690 loss: 2.2690 2022/10/08 05:27:21 - mmengine - INFO - Epoch(train) [105][1280/2119] lr: 4.0000e-03 eta: 9:16:37 time: 0.3311 data_time: 0.0214 memory: 5826 grad_norm: 3.5785 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1846 loss: 2.1846 2022/10/08 05:27:28 - mmengine - INFO - Epoch(train) [105][1300/2119] lr: 4.0000e-03 eta: 9:16:30 time: 0.3708 data_time: 0.0242 memory: 5826 grad_norm: 3.5526 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0617 loss: 2.0617 2022/10/08 05:27:35 - mmengine - INFO - Epoch(train) [105][1320/2119] lr: 4.0000e-03 eta: 9:16:23 time: 0.3611 data_time: 0.0248 memory: 5826 grad_norm: 3.5176 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.0474 loss: 2.0474 2022/10/08 05:27:42 - mmengine - INFO - Epoch(train) [105][1340/2119] lr: 4.0000e-03 eta: 9:16:16 time: 0.3282 data_time: 0.0228 memory: 5826 grad_norm: 3.5282 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1197 loss: 2.1197 2022/10/08 05:27:49 - mmengine - INFO - Epoch(train) [105][1360/2119] lr: 4.0000e-03 eta: 9:16:09 time: 0.3372 data_time: 0.0209 memory: 5826 grad_norm: 3.4896 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1825 loss: 2.1825 2022/10/08 05:27:57 - mmengine - INFO - Epoch(train) [105][1380/2119] lr: 4.0000e-03 eta: 9:16:03 time: 0.4181 data_time: 0.0253 memory: 5826 grad_norm: 3.5432 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2451 loss: 2.2451 2022/10/08 05:28:03 - mmengine - INFO - Epoch(train) [105][1400/2119] lr: 4.0000e-03 eta: 9:15:55 time: 0.3055 data_time: 0.0233 memory: 5826 grad_norm: 3.5285 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9936 loss: 1.9936 2022/10/08 05:28:11 - mmengine - INFO - Epoch(train) [105][1420/2119] lr: 4.0000e-03 eta: 9:15:49 time: 0.4072 data_time: 0.0153 memory: 5826 grad_norm: 3.5628 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1657 loss: 2.1657 2022/10/08 05:28:18 - mmengine - INFO - Epoch(train) [105][1440/2119] lr: 4.0000e-03 eta: 9:15:42 time: 0.3400 data_time: 0.0236 memory: 5826 grad_norm: 3.6159 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2521 loss: 2.2521 2022/10/08 05:28:25 - mmengine - INFO - Epoch(train) [105][1460/2119] lr: 4.0000e-03 eta: 9:15:35 time: 0.3507 data_time: 0.0233 memory: 5826 grad_norm: 3.5929 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.1231 loss: 2.1231 2022/10/08 05:28:32 - mmengine - INFO - Epoch(train) [105][1480/2119] lr: 4.0000e-03 eta: 9:15:28 time: 0.3601 data_time: 0.0207 memory: 5826 grad_norm: 3.5408 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.2125 loss: 2.2125 2022/10/08 05:28:40 - mmengine - INFO - Epoch(train) [105][1500/2119] lr: 4.0000e-03 eta: 9:15:22 time: 0.3818 data_time: 0.0257 memory: 5826 grad_norm: 3.5494 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1427 loss: 2.1427 2022/10/08 05:28:47 - mmengine - INFO - Epoch(train) [105][1520/2119] lr: 4.0000e-03 eta: 9:15:15 time: 0.3492 data_time: 0.0213 memory: 5826 grad_norm: 3.6135 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1051 loss: 2.1051 2022/10/08 05:28:53 - mmengine - INFO - Epoch(train) [105][1540/2119] lr: 4.0000e-03 eta: 9:15:08 time: 0.3239 data_time: 0.0206 memory: 5826 grad_norm: 3.5451 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.2449 loss: 2.2449 2022/10/08 05:29:01 - mmengine - INFO - Epoch(train) [105][1560/2119] lr: 4.0000e-03 eta: 9:15:01 time: 0.3955 data_time: 0.0248 memory: 5826 grad_norm: 3.5970 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.2014 loss: 2.2014 2022/10/08 05:29:08 - mmengine - INFO - Epoch(train) [105][1580/2119] lr: 4.0000e-03 eta: 9:14:54 time: 0.3421 data_time: 0.0226 memory: 5826 grad_norm: 3.5759 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1329 loss: 2.1329 2022/10/08 05:29:15 - mmengine - INFO - Epoch(train) [105][1600/2119] lr: 4.0000e-03 eta: 9:14:47 time: 0.3328 data_time: 0.0262 memory: 5826 grad_norm: 3.5636 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.1537 loss: 2.1537 2022/10/08 05:29:22 - mmengine - INFO - Epoch(train) [105][1620/2119] lr: 4.0000e-03 eta: 9:14:40 time: 0.3507 data_time: 0.0219 memory: 5826 grad_norm: 3.5087 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0682 loss: 2.0682 2022/10/08 05:29:23 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 05:29:29 - mmengine - INFO - Epoch(train) [105][1640/2119] lr: 4.0000e-03 eta: 9:14:33 time: 0.3780 data_time: 0.0260 memory: 5826 grad_norm: 3.5553 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.0085 loss: 2.0085 2022/10/08 05:29:36 - mmengine - INFO - Epoch(train) [105][1660/2119] lr: 4.0000e-03 eta: 9:14:26 time: 0.3106 data_time: 0.0170 memory: 5826 grad_norm: 3.5483 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9584 loss: 1.9584 2022/10/08 05:29:43 - mmengine - INFO - Epoch(train) [105][1680/2119] lr: 4.0000e-03 eta: 9:14:19 time: 0.3689 data_time: 0.0338 memory: 5826 grad_norm: 3.5107 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3440 loss: 2.3440 2022/10/08 05:29:50 - mmengine - INFO - Epoch(train) [105][1700/2119] lr: 4.0000e-03 eta: 9:14:12 time: 0.3395 data_time: 0.0220 memory: 5826 grad_norm: 3.5253 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.3143 loss: 2.3143 2022/10/08 05:29:57 - mmengine - INFO - Epoch(train) [105][1720/2119] lr: 4.0000e-03 eta: 9:14:06 time: 0.3772 data_time: 0.0232 memory: 5826 grad_norm: 3.5666 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1091 loss: 2.1091 2022/10/08 05:30:04 - mmengine - INFO - Epoch(train) [105][1740/2119] lr: 4.0000e-03 eta: 9:13:59 time: 0.3234 data_time: 0.0266 memory: 5826 grad_norm: 3.5692 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1348 loss: 2.1348 2022/10/08 05:30:11 - mmengine - INFO - Epoch(train) [105][1760/2119] lr: 4.0000e-03 eta: 9:13:52 time: 0.3461 data_time: 0.0228 memory: 5826 grad_norm: 3.5120 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.2548 loss: 2.2548 2022/10/08 05:30:18 - mmengine - INFO - Epoch(train) [105][1780/2119] lr: 4.0000e-03 eta: 9:13:45 time: 0.3695 data_time: 0.0239 memory: 5826 grad_norm: 3.5656 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0742 loss: 2.0742 2022/10/08 05:30:26 - mmengine - INFO - Epoch(train) [105][1800/2119] lr: 4.0000e-03 eta: 9:13:38 time: 0.3951 data_time: 0.0208 memory: 5826 grad_norm: 3.4804 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.1546 loss: 2.1546 2022/10/08 05:30:32 - mmengine - INFO - Epoch(train) [105][1820/2119] lr: 4.0000e-03 eta: 9:13:31 time: 0.2853 data_time: 0.0197 memory: 5826 grad_norm: 3.5191 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.2095 loss: 2.2095 2022/10/08 05:30:39 - mmengine - INFO - Epoch(train) [105][1840/2119] lr: 4.0000e-03 eta: 9:13:24 time: 0.3383 data_time: 0.0275 memory: 5826 grad_norm: 3.5334 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1050 loss: 2.1050 2022/10/08 05:30:46 - mmengine - INFO - Epoch(train) [105][1860/2119] lr: 4.0000e-03 eta: 9:13:17 time: 0.3686 data_time: 0.0207 memory: 5826 grad_norm: 3.5322 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.2877 loss: 2.2877 2022/10/08 05:30:53 - mmengine - INFO - Epoch(train) [105][1880/2119] lr: 4.0000e-03 eta: 9:13:10 time: 0.3434 data_time: 0.0237 memory: 5826 grad_norm: 3.5502 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.2160 loss: 2.2160 2022/10/08 05:31:00 - mmengine - INFO - Epoch(train) [105][1900/2119] lr: 4.0000e-03 eta: 9:13:03 time: 0.3816 data_time: 0.0247 memory: 5826 grad_norm: 3.5346 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.2605 loss: 2.2605 2022/10/08 05:31:07 - mmengine - INFO - Epoch(train) [105][1920/2119] lr: 4.0000e-03 eta: 9:12:56 time: 0.3445 data_time: 0.0217 memory: 5826 grad_norm: 3.5777 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.2117 loss: 2.2117 2022/10/08 05:31:15 - mmengine - INFO - Epoch(train) [105][1940/2119] lr: 4.0000e-03 eta: 9:12:50 time: 0.3829 data_time: 0.0214 memory: 5826 grad_norm: 3.5463 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1395 loss: 2.1395 2022/10/08 05:31:21 - mmengine - INFO - Epoch(train) [105][1960/2119] lr: 4.0000e-03 eta: 9:12:43 time: 0.3206 data_time: 0.0305 memory: 5826 grad_norm: 3.6214 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1153 loss: 2.1153 2022/10/08 05:31:29 - mmengine - INFO - Epoch(train) [105][1980/2119] lr: 4.0000e-03 eta: 9:12:36 time: 0.3979 data_time: 0.0207 memory: 5826 grad_norm: 3.5511 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3947 loss: 2.3947 2022/10/08 05:31:36 - mmengine - INFO - Epoch(train) [105][2000/2119] lr: 4.0000e-03 eta: 9:12:29 time: 0.3414 data_time: 0.0230 memory: 5826 grad_norm: 3.5891 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.0037 loss: 2.0037 2022/10/08 05:31:44 - mmengine - INFO - Epoch(train) [105][2020/2119] lr: 4.0000e-03 eta: 9:12:22 time: 0.3821 data_time: 0.0210 memory: 5826 grad_norm: 3.6068 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1254 loss: 2.1254 2022/10/08 05:31:51 - mmengine - INFO - Epoch(train) [105][2040/2119] lr: 4.0000e-03 eta: 9:12:16 time: 0.3693 data_time: 0.0214 memory: 5826 grad_norm: 3.5334 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9961 loss: 1.9961 2022/10/08 05:31:59 - mmengine - INFO - Epoch(train) [105][2060/2119] lr: 4.0000e-03 eta: 9:12:09 time: 0.3797 data_time: 0.0269 memory: 5826 grad_norm: 3.5916 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.2450 loss: 2.2450 2022/10/08 05:32:05 - mmengine - INFO - Epoch(train) [105][2080/2119] lr: 4.0000e-03 eta: 9:12:02 time: 0.3151 data_time: 0.0219 memory: 5826 grad_norm: 3.5409 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9644 loss: 1.9644 2022/10/08 05:32:12 - mmengine - INFO - Epoch(train) [105][2100/2119] lr: 4.0000e-03 eta: 9:11:55 time: 0.3584 data_time: 0.0191 memory: 5826 grad_norm: 3.4841 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1554 loss: 2.1554 2022/10/08 05:32:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 05:32:18 - mmengine - INFO - Epoch(train) [105][2119/2119] lr: 4.0000e-03 eta: 9:11:55 time: 0.3010 data_time: 0.0195 memory: 5826 grad_norm: 3.5525 top1_acc: 0.7000 top5_acc: 0.8000 loss_cls: 2.1520 loss: 2.1520 2022/10/08 05:32:27 - mmengine - INFO - Epoch(val) [105][20/137] eta: 0:00:54 time: 0.4621 data_time: 0.3848 memory: 1241 2022/10/08 05:32:33 - mmengine - INFO - Epoch(val) [105][40/137] eta: 0:00:27 time: 0.2831 data_time: 0.2181 memory: 1241 2022/10/08 05:32:41 - mmengine - INFO - Epoch(val) [105][60/137] eta: 0:00:29 time: 0.3775 data_time: 0.3117 memory: 1241 2022/10/08 05:32:46 - mmengine - INFO - Epoch(val) [105][80/137] eta: 0:00:15 time: 0.2730 data_time: 0.2059 memory: 1241 2022/10/08 05:32:52 - mmengine - INFO - Epoch(val) [105][100/137] eta: 0:00:11 time: 0.3115 data_time: 0.2459 memory: 1241 2022/10/08 05:32:57 - mmengine - INFO - Epoch(val) [105][120/137] eta: 0:00:04 time: 0.2434 data_time: 0.1764 memory: 1241 2022/10/08 05:33:10 - mmengine - INFO - Epoch(val) [105][137/137] acc/top1: 0.5300 acc/top5: 0.7571 acc/mean1: 0.5299 2022/10/08 05:33:10 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb/best_acc/top1_epoch_90.pth is removed 2022/10/08 05:33:12 - mmengine - INFO - The best checkpoint with 0.5300 acc/top1 at 105 epoch is saved to best_acc/top1_epoch_105.pth. 2022/10/08 05:33:21 - mmengine - INFO - Epoch(train) [106][20/2119] lr: 4.0000e-03 eta: 9:11:39 time: 0.4200 data_time: 0.2048 memory: 5826 grad_norm: 3.5342 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1868 loss: 2.1868 2022/10/08 05:33:28 - mmengine - INFO - Epoch(train) [106][40/2119] lr: 4.0000e-03 eta: 9:11:32 time: 0.3613 data_time: 0.1255 memory: 5826 grad_norm: 3.5217 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2449 loss: 2.2449 2022/10/08 05:33:35 - mmengine - INFO - Epoch(train) [106][60/2119] lr: 4.0000e-03 eta: 9:11:25 time: 0.3402 data_time: 0.0217 memory: 5826 grad_norm: 3.5927 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1715 loss: 2.1715 2022/10/08 05:33:41 - mmengine - INFO - Epoch(train) [106][80/2119] lr: 4.0000e-03 eta: 9:11:18 time: 0.3318 data_time: 0.0213 memory: 5826 grad_norm: 3.5312 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.3073 loss: 2.3073 2022/10/08 05:33:49 - mmengine - INFO - Epoch(train) [106][100/2119] lr: 4.0000e-03 eta: 9:11:12 time: 0.3872 data_time: 0.0208 memory: 5826 grad_norm: 3.5113 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9447 loss: 1.9447 2022/10/08 05:33:56 - mmengine - INFO - Epoch(train) [106][120/2119] lr: 4.0000e-03 eta: 9:11:05 time: 0.3313 data_time: 0.0236 memory: 5826 grad_norm: 3.5683 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1226 loss: 2.1226 2022/10/08 05:34:03 - mmengine - INFO - Epoch(train) [106][140/2119] lr: 4.0000e-03 eta: 9:10:58 time: 0.3605 data_time: 0.0200 memory: 5826 grad_norm: 3.5673 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.2920 loss: 2.2920 2022/10/08 05:34:10 - mmengine - INFO - Epoch(train) [106][160/2119] lr: 4.0000e-03 eta: 9:10:51 time: 0.3469 data_time: 0.0225 memory: 5826 grad_norm: 3.6094 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1588 loss: 2.1588 2022/10/08 05:34:17 - mmengine - INFO - Epoch(train) [106][180/2119] lr: 4.0000e-03 eta: 9:10:44 time: 0.3389 data_time: 0.0209 memory: 5826 grad_norm: 3.5238 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1846 loss: 2.1846 2022/10/08 05:34:24 - mmengine - INFO - Epoch(train) [106][200/2119] lr: 4.0000e-03 eta: 9:10:37 time: 0.3732 data_time: 0.0236 memory: 5826 grad_norm: 3.5358 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.4263 loss: 2.4263 2022/10/08 05:34:32 - mmengine - INFO - Epoch(train) [106][220/2119] lr: 4.0000e-03 eta: 9:10:30 time: 0.3756 data_time: 0.0206 memory: 5826 grad_norm: 3.5042 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0941 loss: 2.0941 2022/10/08 05:34:39 - mmengine - INFO - Epoch(train) [106][240/2119] lr: 4.0000e-03 eta: 9:10:23 time: 0.3482 data_time: 0.0208 memory: 5826 grad_norm: 3.5767 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1876 loss: 2.1876 2022/10/08 05:34:46 - mmengine - INFO - Epoch(train) [106][260/2119] lr: 4.0000e-03 eta: 9:10:17 time: 0.3567 data_time: 0.0226 memory: 5826 grad_norm: 3.5223 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1072 loss: 2.1072 2022/10/08 05:34:52 - mmengine - INFO - Epoch(train) [106][280/2119] lr: 4.0000e-03 eta: 9:10:10 time: 0.3268 data_time: 0.0217 memory: 5826 grad_norm: 3.5513 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.1459 loss: 2.1459 2022/10/08 05:35:00 - mmengine - INFO - Epoch(train) [106][300/2119] lr: 4.0000e-03 eta: 9:10:03 time: 0.3840 data_time: 0.0193 memory: 5826 grad_norm: 3.5649 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.2980 loss: 2.2980 2022/10/08 05:35:07 - mmengine - INFO - Epoch(train) [106][320/2119] lr: 4.0000e-03 eta: 9:09:56 time: 0.3449 data_time: 0.0284 memory: 5826 grad_norm: 3.5367 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.0256 loss: 2.0256 2022/10/08 05:35:15 - mmengine - INFO - Epoch(train) [106][340/2119] lr: 4.0000e-03 eta: 9:09:49 time: 0.4011 data_time: 0.0197 memory: 5826 grad_norm: 3.5567 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1941 loss: 2.1941 2022/10/08 05:35:22 - mmengine - INFO - Epoch(train) [106][360/2119] lr: 4.0000e-03 eta: 9:09:42 time: 0.3457 data_time: 0.0222 memory: 5826 grad_norm: 3.5606 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9156 loss: 1.9156 2022/10/08 05:35:29 - mmengine - INFO - Epoch(train) [106][380/2119] lr: 4.0000e-03 eta: 9:09:36 time: 0.3473 data_time: 0.0219 memory: 5826 grad_norm: 3.6151 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1927 loss: 2.1927 2022/10/08 05:35:35 - mmengine - INFO - Epoch(train) [106][400/2119] lr: 4.0000e-03 eta: 9:09:28 time: 0.3142 data_time: 0.0259 memory: 5826 grad_norm: 3.5676 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.2723 loss: 2.2723 2022/10/08 05:35:42 - mmengine - INFO - Epoch(train) [106][420/2119] lr: 4.0000e-03 eta: 9:09:22 time: 0.3638 data_time: 0.0298 memory: 5826 grad_norm: 3.6105 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.2158 loss: 2.2158 2022/10/08 05:35:49 - mmengine - INFO - Epoch(train) [106][440/2119] lr: 4.0000e-03 eta: 9:09:15 time: 0.3402 data_time: 0.0240 memory: 5826 grad_norm: 3.5896 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0452 loss: 2.0452 2022/10/08 05:35:57 - mmengine - INFO - Epoch(train) [106][460/2119] lr: 4.0000e-03 eta: 9:09:08 time: 0.4059 data_time: 0.0200 memory: 5826 grad_norm: 3.5825 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0964 loss: 2.0964 2022/10/08 05:36:04 - mmengine - INFO - Epoch(train) [106][480/2119] lr: 4.0000e-03 eta: 9:09:01 time: 0.3304 data_time: 0.0210 memory: 5826 grad_norm: 3.6445 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1134 loss: 2.1134 2022/10/08 05:36:11 - mmengine - INFO - Epoch(train) [106][500/2119] lr: 4.0000e-03 eta: 9:08:54 time: 0.3709 data_time: 0.0220 memory: 5826 grad_norm: 3.5851 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2308 loss: 2.2308 2022/10/08 05:36:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 05:36:18 - mmengine - INFO - Epoch(train) [106][520/2119] lr: 4.0000e-03 eta: 9:08:47 time: 0.3385 data_time: 0.0245 memory: 5826 grad_norm: 3.5965 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9341 loss: 1.9341 2022/10/08 05:36:25 - mmengine - INFO - Epoch(train) [106][540/2119] lr: 4.0000e-03 eta: 9:08:40 time: 0.3422 data_time: 0.0223 memory: 5826 grad_norm: 3.5830 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0931 loss: 2.0931 2022/10/08 05:36:31 - mmengine - INFO - Epoch(train) [106][560/2119] lr: 4.0000e-03 eta: 9:08:33 time: 0.3254 data_time: 0.0235 memory: 5826 grad_norm: 3.5869 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0809 loss: 2.0809 2022/10/08 05:36:39 - mmengine - INFO - Epoch(train) [106][580/2119] lr: 4.0000e-03 eta: 9:08:26 time: 0.3793 data_time: 0.0254 memory: 5826 grad_norm: 3.5956 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0275 loss: 2.0275 2022/10/08 05:36:46 - mmengine - INFO - Epoch(train) [106][600/2119] lr: 4.0000e-03 eta: 9:08:19 time: 0.3401 data_time: 0.0229 memory: 5826 grad_norm: 3.6075 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9421 loss: 1.9421 2022/10/08 05:36:53 - mmengine - INFO - Epoch(train) [106][620/2119] lr: 4.0000e-03 eta: 9:08:13 time: 0.3610 data_time: 0.0257 memory: 5826 grad_norm: 3.5468 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1138 loss: 2.1138 2022/10/08 05:37:01 - mmengine - INFO - Epoch(train) [106][640/2119] lr: 4.0000e-03 eta: 9:08:06 time: 0.3822 data_time: 0.0188 memory: 5826 grad_norm: 3.5484 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2694 loss: 2.2694 2022/10/08 05:37:08 - mmengine - INFO - Epoch(train) [106][660/2119] lr: 4.0000e-03 eta: 9:07:59 time: 0.3581 data_time: 0.0243 memory: 5826 grad_norm: 3.5714 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0834 loss: 2.0834 2022/10/08 05:37:15 - mmengine - INFO - Epoch(train) [106][680/2119] lr: 4.0000e-03 eta: 9:07:52 time: 0.3325 data_time: 0.0274 memory: 5826 grad_norm: 3.5943 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9810 loss: 1.9810 2022/10/08 05:37:22 - mmengine - INFO - Epoch(train) [106][700/2119] lr: 4.0000e-03 eta: 9:07:45 time: 0.3884 data_time: 0.0230 memory: 5826 grad_norm: 3.5363 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1155 loss: 2.1155 2022/10/08 05:37:30 - mmengine - INFO - Epoch(train) [106][720/2119] lr: 4.0000e-03 eta: 9:07:39 time: 0.3853 data_time: 0.0215 memory: 5826 grad_norm: 3.5877 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0735 loss: 2.0735 2022/10/08 05:37:38 - mmengine - INFO - Epoch(train) [106][740/2119] lr: 4.0000e-03 eta: 9:07:32 time: 0.3766 data_time: 0.0211 memory: 5826 grad_norm: 3.5582 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0734 loss: 2.0734 2022/10/08 05:37:44 - mmengine - INFO - Epoch(train) [106][760/2119] lr: 4.0000e-03 eta: 9:07:25 time: 0.3070 data_time: 0.0210 memory: 5826 grad_norm: 3.6203 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0433 loss: 2.0433 2022/10/08 05:37:51 - mmengine - INFO - Epoch(train) [106][780/2119] lr: 4.0000e-03 eta: 9:07:18 time: 0.3765 data_time: 0.0233 memory: 5826 grad_norm: 3.5657 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1597 loss: 2.1597 2022/10/08 05:37:58 - mmengine - INFO - Epoch(train) [106][800/2119] lr: 4.0000e-03 eta: 9:07:11 time: 0.3463 data_time: 0.0205 memory: 5826 grad_norm: 3.6188 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0684 loss: 2.0684 2022/10/08 05:38:05 - mmengine - INFO - Epoch(train) [106][820/2119] lr: 4.0000e-03 eta: 9:07:04 time: 0.3361 data_time: 0.0212 memory: 5826 grad_norm: 3.5997 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1095 loss: 2.1095 2022/10/08 05:38:11 - mmengine - INFO - Epoch(train) [106][840/2119] lr: 4.0000e-03 eta: 9:06:57 time: 0.3159 data_time: 0.0221 memory: 5826 grad_norm: 3.6821 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0633 loss: 2.0633 2022/10/08 05:38:19 - mmengine - INFO - Epoch(train) [106][860/2119] lr: 4.0000e-03 eta: 9:06:50 time: 0.3660 data_time: 0.0228 memory: 5826 grad_norm: 3.6236 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.3755 loss: 2.3755 2022/10/08 05:38:25 - mmengine - INFO - Epoch(train) [106][880/2119] lr: 4.0000e-03 eta: 9:06:43 time: 0.3421 data_time: 0.0228 memory: 5826 grad_norm: 3.5842 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.2891 loss: 2.2891 2022/10/08 05:38:33 - mmengine - INFO - Epoch(train) [106][900/2119] lr: 4.0000e-03 eta: 9:06:36 time: 0.3717 data_time: 0.0190 memory: 5826 grad_norm: 3.5683 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9816 loss: 1.9816 2022/10/08 05:38:40 - mmengine - INFO - Epoch(train) [106][920/2119] lr: 4.0000e-03 eta: 9:06:30 time: 0.3644 data_time: 0.0201 memory: 5826 grad_norm: 3.5938 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 2.1452 loss: 2.1452 2022/10/08 05:38:48 - mmengine - INFO - Epoch(train) [106][940/2119] lr: 4.0000e-03 eta: 9:06:23 time: 0.4080 data_time: 0.0229 memory: 5826 grad_norm: 3.6010 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0646 loss: 2.0646 2022/10/08 05:38:55 - mmengine - INFO - Epoch(train) [106][960/2119] lr: 4.0000e-03 eta: 9:06:16 time: 0.3084 data_time: 0.0252 memory: 5826 grad_norm: 3.6533 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1887 loss: 2.1887 2022/10/08 05:39:03 - mmengine - INFO - Epoch(train) [106][980/2119] lr: 4.0000e-03 eta: 9:06:09 time: 0.4060 data_time: 0.0192 memory: 5826 grad_norm: 3.6405 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0855 loss: 2.0855 2022/10/08 05:39:09 - mmengine - INFO - Epoch(train) [106][1000/2119] lr: 4.0000e-03 eta: 9:06:02 time: 0.3250 data_time: 0.0209 memory: 5826 grad_norm: 3.5648 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0014 loss: 2.0014 2022/10/08 05:39:17 - mmengine - INFO - Epoch(train) [106][1020/2119] lr: 4.0000e-03 eta: 9:05:56 time: 0.3702 data_time: 0.0230 memory: 5826 grad_norm: 3.6128 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2619 loss: 2.2619 2022/10/08 05:39:24 - mmengine - INFO - Epoch(train) [106][1040/2119] lr: 4.0000e-03 eta: 9:05:49 time: 0.3651 data_time: 0.0195 memory: 5826 grad_norm: 3.6414 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.2074 loss: 2.2074 2022/10/08 05:39:32 - mmengine - INFO - Epoch(train) [106][1060/2119] lr: 4.0000e-03 eta: 9:05:42 time: 0.3837 data_time: 0.0225 memory: 5826 grad_norm: 3.6508 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1150 loss: 2.1150 2022/10/08 05:39:38 - mmengine - INFO - Epoch(train) [106][1080/2119] lr: 4.0000e-03 eta: 9:05:35 time: 0.3366 data_time: 0.0199 memory: 5826 grad_norm: 3.5992 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2416 loss: 2.2416 2022/10/08 05:39:46 - mmengine - INFO - Epoch(train) [106][1100/2119] lr: 4.0000e-03 eta: 9:05:29 time: 0.3916 data_time: 0.0213 memory: 5826 grad_norm: 3.5203 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3764 loss: 2.3764 2022/10/08 05:39:53 - mmengine - INFO - Epoch(train) [106][1120/2119] lr: 4.0000e-03 eta: 9:05:22 time: 0.3468 data_time: 0.0171 memory: 5826 grad_norm: 3.5605 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.1619 loss: 2.1619 2022/10/08 05:40:01 - mmengine - INFO - Epoch(train) [106][1140/2119] lr: 4.0000e-03 eta: 9:05:15 time: 0.3997 data_time: 0.0232 memory: 5826 grad_norm: 3.6346 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0441 loss: 2.0441 2022/10/08 05:40:08 - mmengine - INFO - Epoch(train) [106][1160/2119] lr: 4.0000e-03 eta: 9:05:08 time: 0.3526 data_time: 0.0189 memory: 5826 grad_norm: 3.5943 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1394 loss: 2.1394 2022/10/08 05:40:15 - mmengine - INFO - Epoch(train) [106][1180/2119] lr: 4.0000e-03 eta: 9:05:01 time: 0.3225 data_time: 0.0230 memory: 5826 grad_norm: 3.5889 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0218 loss: 2.0218 2022/10/08 05:40:22 - mmengine - INFO - Epoch(train) [106][1200/2119] lr: 4.0000e-03 eta: 9:04:54 time: 0.3551 data_time: 0.0225 memory: 5826 grad_norm: 3.5515 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9570 loss: 1.9570 2022/10/08 05:40:29 - mmengine - INFO - Epoch(train) [106][1220/2119] lr: 4.0000e-03 eta: 9:04:47 time: 0.3720 data_time: 0.0203 memory: 5826 grad_norm: 3.6125 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0869 loss: 2.0869 2022/10/08 05:40:36 - mmengine - INFO - Epoch(train) [106][1240/2119] lr: 4.0000e-03 eta: 9:04:40 time: 0.3408 data_time: 0.0225 memory: 5826 grad_norm: 3.5867 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.3620 loss: 2.3620 2022/10/08 05:40:43 - mmengine - INFO - Epoch(train) [106][1260/2119] lr: 4.0000e-03 eta: 9:04:34 time: 0.3577 data_time: 0.0212 memory: 5826 grad_norm: 3.5539 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9973 loss: 1.9973 2022/10/08 05:40:49 - mmengine - INFO - Epoch(train) [106][1280/2119] lr: 4.0000e-03 eta: 9:04:26 time: 0.3099 data_time: 0.0224 memory: 5826 grad_norm: 3.5554 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9299 loss: 1.9299 2022/10/08 05:40:58 - mmengine - INFO - Epoch(train) [106][1300/2119] lr: 4.0000e-03 eta: 9:04:20 time: 0.4350 data_time: 0.0228 memory: 5826 grad_norm: 3.5967 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9022 loss: 1.9022 2022/10/08 05:41:04 - mmengine - INFO - Epoch(train) [106][1320/2119] lr: 4.0000e-03 eta: 9:04:13 time: 0.3195 data_time: 0.0194 memory: 5826 grad_norm: 3.5250 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0840 loss: 2.0840 2022/10/08 05:41:12 - mmengine - INFO - Epoch(train) [106][1340/2119] lr: 4.0000e-03 eta: 9:04:06 time: 0.3919 data_time: 0.0209 memory: 5826 grad_norm: 3.5990 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.1656 loss: 2.1656 2022/10/08 05:41:19 - mmengine - INFO - Epoch(train) [106][1360/2119] lr: 4.0000e-03 eta: 9:03:59 time: 0.3471 data_time: 0.0265 memory: 5826 grad_norm: 3.6349 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4225 loss: 2.4225 2022/10/08 05:41:26 - mmengine - INFO - Epoch(train) [106][1380/2119] lr: 4.0000e-03 eta: 9:03:53 time: 0.3524 data_time: 0.0233 memory: 5826 grad_norm: 3.6131 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0695 loss: 2.0695 2022/10/08 05:41:34 - mmengine - INFO - Epoch(train) [106][1400/2119] lr: 4.0000e-03 eta: 9:03:46 time: 0.3608 data_time: 0.0225 memory: 5826 grad_norm: 3.6122 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.2556 loss: 2.2556 2022/10/08 05:41:40 - mmengine - INFO - Epoch(train) [106][1420/2119] lr: 4.0000e-03 eta: 9:03:39 time: 0.3365 data_time: 0.0214 memory: 5826 grad_norm: 3.5579 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0106 loss: 2.0106 2022/10/08 05:41:47 - mmengine - INFO - Epoch(train) [106][1440/2119] lr: 4.0000e-03 eta: 9:03:32 time: 0.3514 data_time: 0.0194 memory: 5826 grad_norm: 3.6048 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2328 loss: 2.2328 2022/10/08 05:41:55 - mmengine - INFO - Epoch(train) [106][1460/2119] lr: 4.0000e-03 eta: 9:03:25 time: 0.4060 data_time: 0.0210 memory: 5826 grad_norm: 3.6491 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8844 loss: 1.8844 2022/10/08 05:42:02 - mmengine - INFO - Epoch(train) [106][1480/2119] lr: 4.0000e-03 eta: 9:03:18 time: 0.3088 data_time: 0.0198 memory: 5826 grad_norm: 3.5898 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2854 loss: 2.2854 2022/10/08 05:42:09 - mmengine - INFO - Epoch(train) [106][1500/2119] lr: 4.0000e-03 eta: 9:03:11 time: 0.3778 data_time: 0.0247 memory: 5826 grad_norm: 3.6273 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1143 loss: 2.1143 2022/10/08 05:42:10 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 05:42:15 - mmengine - INFO - Epoch(train) [106][1520/2119] lr: 4.0000e-03 eta: 9:03:04 time: 0.2967 data_time: 0.0283 memory: 5826 grad_norm: 3.6143 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0951 loss: 2.0951 2022/10/08 05:42:23 - mmengine - INFO - Epoch(train) [106][1540/2119] lr: 4.0000e-03 eta: 9:02:58 time: 0.4184 data_time: 0.0209 memory: 5826 grad_norm: 3.6567 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9222 loss: 1.9222 2022/10/08 05:42:30 - mmengine - INFO - Epoch(train) [106][1560/2119] lr: 4.0000e-03 eta: 9:02:50 time: 0.3109 data_time: 0.0225 memory: 5826 grad_norm: 3.5623 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1804 loss: 2.1804 2022/10/08 05:42:37 - mmengine - INFO - Epoch(train) [106][1580/2119] lr: 4.0000e-03 eta: 9:02:44 time: 0.3865 data_time: 0.0210 memory: 5826 grad_norm: 3.6274 top1_acc: 0.2500 top5_acc: 0.8125 loss_cls: 2.0545 loss: 2.0545 2022/10/08 05:42:44 - mmengine - INFO - Epoch(train) [106][1600/2119] lr: 4.0000e-03 eta: 9:02:37 time: 0.3388 data_time: 0.0216 memory: 5826 grad_norm: 3.5875 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2119 loss: 2.2119 2022/10/08 05:42:51 - mmengine - INFO - Epoch(train) [106][1620/2119] lr: 4.0000e-03 eta: 9:02:30 time: 0.3616 data_time: 0.0247 memory: 5826 grad_norm: 3.6117 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2443 loss: 2.2443 2022/10/08 05:42:58 - mmengine - INFO - Epoch(train) [106][1640/2119] lr: 4.0000e-03 eta: 9:02:23 time: 0.3249 data_time: 0.0253 memory: 5826 grad_norm: 3.5819 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0609 loss: 2.0609 2022/10/08 05:43:05 - mmengine - INFO - Epoch(train) [106][1660/2119] lr: 4.0000e-03 eta: 9:02:16 time: 0.3558 data_time: 0.0221 memory: 5826 grad_norm: 3.6158 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.1190 loss: 2.1190 2022/10/08 05:43:12 - mmengine - INFO - Epoch(train) [106][1680/2119] lr: 4.0000e-03 eta: 9:02:09 time: 0.3239 data_time: 0.0208 memory: 5826 grad_norm: 3.6286 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0809 loss: 2.0809 2022/10/08 05:43:19 - mmengine - INFO - Epoch(train) [106][1700/2119] lr: 4.0000e-03 eta: 9:02:02 time: 0.3475 data_time: 0.0213 memory: 5826 grad_norm: 3.5748 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.1456 loss: 2.1456 2022/10/08 05:43:26 - mmengine - INFO - Epoch(train) [106][1720/2119] lr: 4.0000e-03 eta: 9:01:55 time: 0.3559 data_time: 0.0238 memory: 5826 grad_norm: 3.5912 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5944 loss: 2.5944 2022/10/08 05:43:33 - mmengine - INFO - Epoch(train) [106][1740/2119] lr: 4.0000e-03 eta: 9:01:48 time: 0.3781 data_time: 0.0199 memory: 5826 grad_norm: 3.6034 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.2210 loss: 2.2210 2022/10/08 05:43:41 - mmengine - INFO - Epoch(train) [106][1760/2119] lr: 4.0000e-03 eta: 9:01:41 time: 0.3641 data_time: 0.0236 memory: 5826 grad_norm: 3.6490 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0843 loss: 2.0843 2022/10/08 05:43:48 - mmengine - INFO - Epoch(train) [106][1780/2119] lr: 4.0000e-03 eta: 9:01:35 time: 0.3786 data_time: 0.0202 memory: 5826 grad_norm: 3.6204 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.2356 loss: 2.2356 2022/10/08 05:43:55 - mmengine - INFO - Epoch(train) [106][1800/2119] lr: 4.0000e-03 eta: 9:01:28 time: 0.3204 data_time: 0.0227 memory: 5826 grad_norm: 3.5571 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.0408 loss: 2.0408 2022/10/08 05:44:03 - mmengine - INFO - Epoch(train) [106][1820/2119] lr: 4.0000e-03 eta: 9:01:21 time: 0.4144 data_time: 0.0246 memory: 5826 grad_norm: 3.6420 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1420 loss: 2.1420 2022/10/08 05:44:09 - mmengine - INFO - Epoch(train) [106][1840/2119] lr: 4.0000e-03 eta: 9:01:14 time: 0.3058 data_time: 0.0228 memory: 5826 grad_norm: 3.5676 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2754 loss: 2.2754 2022/10/08 05:44:16 - mmengine - INFO - Epoch(train) [106][1860/2119] lr: 4.0000e-03 eta: 9:01:07 time: 0.3567 data_time: 0.0192 memory: 5826 grad_norm: 3.6222 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1407 loss: 2.1407 2022/10/08 05:44:23 - mmengine - INFO - Epoch(train) [106][1880/2119] lr: 4.0000e-03 eta: 9:01:00 time: 0.3519 data_time: 0.0231 memory: 5826 grad_norm: 3.6088 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0348 loss: 2.0348 2022/10/08 05:44:31 - mmengine - INFO - Epoch(train) [106][1900/2119] lr: 4.0000e-03 eta: 9:00:54 time: 0.3925 data_time: 0.0220 memory: 5826 grad_norm: 3.6296 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1936 loss: 2.1936 2022/10/08 05:44:37 - mmengine - INFO - Epoch(train) [106][1920/2119] lr: 4.0000e-03 eta: 9:00:46 time: 0.3118 data_time: 0.0253 memory: 5826 grad_norm: 3.6010 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.2808 loss: 2.2808 2022/10/08 05:44:45 - mmengine - INFO - Epoch(train) [106][1940/2119] lr: 4.0000e-03 eta: 9:00:40 time: 0.3785 data_time: 0.0182 memory: 5826 grad_norm: 3.6241 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 1.9630 loss: 1.9630 2022/10/08 05:44:52 - mmengine - INFO - Epoch(train) [106][1960/2119] lr: 4.0000e-03 eta: 9:00:33 time: 0.3358 data_time: 0.0218 memory: 5826 grad_norm: 3.6145 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.3003 loss: 2.3003 2022/10/08 05:44:59 - mmengine - INFO - Epoch(train) [106][1980/2119] lr: 4.0000e-03 eta: 9:00:26 time: 0.3826 data_time: 0.0201 memory: 5826 grad_norm: 3.6404 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1852 loss: 2.1852 2022/10/08 05:45:05 - mmengine - INFO - Epoch(train) [106][2000/2119] lr: 4.0000e-03 eta: 9:00:19 time: 0.3119 data_time: 0.0220 memory: 5826 grad_norm: 3.5681 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9524 loss: 1.9524 2022/10/08 05:45:13 - mmengine - INFO - Epoch(train) [106][2020/2119] lr: 4.0000e-03 eta: 9:00:12 time: 0.3607 data_time: 0.0288 memory: 5826 grad_norm: 3.6176 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2491 loss: 2.2491 2022/10/08 05:45:20 - mmengine - INFO - Epoch(train) [106][2040/2119] lr: 4.0000e-03 eta: 9:00:05 time: 0.3490 data_time: 0.0235 memory: 5826 grad_norm: 3.6259 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8382 loss: 1.8382 2022/10/08 05:45:27 - mmengine - INFO - Epoch(train) [106][2060/2119] lr: 4.0000e-03 eta: 8:59:58 time: 0.3553 data_time: 0.0194 memory: 5826 grad_norm: 3.6935 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1007 loss: 2.1007 2022/10/08 05:45:33 - mmengine - INFO - Epoch(train) [106][2080/2119] lr: 4.0000e-03 eta: 8:59:51 time: 0.3261 data_time: 0.0219 memory: 5826 grad_norm: 3.6809 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.2722 loss: 2.2722 2022/10/08 05:45:40 - mmengine - INFO - Epoch(train) [106][2100/2119] lr: 4.0000e-03 eta: 8:59:44 time: 0.3593 data_time: 0.0226 memory: 5826 grad_norm: 3.6709 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.1591 loss: 2.1591 2022/10/08 05:45:47 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 05:45:47 - mmengine - INFO - Epoch(train) [106][2119/2119] lr: 4.0000e-03 eta: 8:59:44 time: 0.3162 data_time: 0.0212 memory: 5826 grad_norm: 3.7059 top1_acc: 0.5000 top5_acc: 0.9000 loss_cls: 1.9217 loss: 1.9217 2022/10/08 05:45:56 - mmengine - INFO - Epoch(train) [107][20/2119] lr: 4.0000e-03 eta: 8:59:29 time: 0.4691 data_time: 0.1476 memory: 5826 grad_norm: 3.5698 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0742 loss: 2.0742 2022/10/08 05:46:03 - mmengine - INFO - Epoch(train) [107][40/2119] lr: 4.0000e-03 eta: 8:59:22 time: 0.3332 data_time: 0.0265 memory: 5826 grad_norm: 3.6430 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0803 loss: 2.0803 2022/10/08 05:46:10 - mmengine - INFO - Epoch(train) [107][60/2119] lr: 4.0000e-03 eta: 8:59:15 time: 0.3683 data_time: 0.0223 memory: 5826 grad_norm: 3.6448 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9648 loss: 1.9648 2022/10/08 05:46:17 - mmengine - INFO - Epoch(train) [107][80/2119] lr: 4.0000e-03 eta: 8:59:08 time: 0.3467 data_time: 0.0258 memory: 5826 grad_norm: 3.6372 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1673 loss: 2.1673 2022/10/08 05:46:25 - mmengine - INFO - Epoch(train) [107][100/2119] lr: 4.0000e-03 eta: 8:59:02 time: 0.4173 data_time: 0.0195 memory: 5826 grad_norm: 3.5802 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9905 loss: 1.9905 2022/10/08 05:46:32 - mmengine - INFO - Epoch(train) [107][120/2119] lr: 4.0000e-03 eta: 8:58:55 time: 0.3436 data_time: 0.0218 memory: 5826 grad_norm: 3.6665 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1245 loss: 2.1245 2022/10/08 05:46:39 - mmengine - INFO - Epoch(train) [107][140/2119] lr: 4.0000e-03 eta: 8:58:48 time: 0.3410 data_time: 0.0230 memory: 5826 grad_norm: 3.6744 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0649 loss: 2.0649 2022/10/08 05:46:45 - mmengine - INFO - Epoch(train) [107][160/2119] lr: 4.0000e-03 eta: 8:58:40 time: 0.3085 data_time: 0.0271 memory: 5826 grad_norm: 3.6701 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9264 loss: 1.9264 2022/10/08 05:46:53 - mmengine - INFO - Epoch(train) [107][180/2119] lr: 4.0000e-03 eta: 8:58:34 time: 0.3724 data_time: 0.0169 memory: 5826 grad_norm: 3.5833 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.0785 loss: 2.0785 2022/10/08 05:46:59 - mmengine - INFO - Epoch(train) [107][200/2119] lr: 4.0000e-03 eta: 8:58:27 time: 0.3223 data_time: 0.0239 memory: 5826 grad_norm: 3.6719 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2684 loss: 2.2684 2022/10/08 05:47:07 - mmengine - INFO - Epoch(train) [107][220/2119] lr: 4.0000e-03 eta: 8:58:20 time: 0.3684 data_time: 0.0193 memory: 5826 grad_norm: 3.5906 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.1884 loss: 2.1884 2022/10/08 05:47:13 - mmengine - INFO - Epoch(train) [107][240/2119] lr: 4.0000e-03 eta: 8:58:13 time: 0.3193 data_time: 0.0282 memory: 5826 grad_norm: 3.6378 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1848 loss: 2.1848 2022/10/08 05:47:21 - mmengine - INFO - Epoch(train) [107][260/2119] lr: 4.0000e-03 eta: 8:58:06 time: 0.4047 data_time: 0.0256 memory: 5826 grad_norm: 3.6357 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.1522 loss: 2.1522 2022/10/08 05:47:29 - mmengine - INFO - Epoch(train) [107][280/2119] lr: 4.0000e-03 eta: 8:57:59 time: 0.3693 data_time: 0.0219 memory: 5826 grad_norm: 3.6608 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.3290 loss: 2.3290 2022/10/08 05:47:36 - mmengine - INFO - Epoch(train) [107][300/2119] lr: 4.0000e-03 eta: 8:57:52 time: 0.3533 data_time: 0.0191 memory: 5826 grad_norm: 3.6249 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 2.1660 loss: 2.1660 2022/10/08 05:47:42 - mmengine - INFO - Epoch(train) [107][320/2119] lr: 4.0000e-03 eta: 8:57:46 time: 0.3425 data_time: 0.0196 memory: 5826 grad_norm: 3.5711 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.1835 loss: 2.1835 2022/10/08 05:47:50 - mmengine - INFO - Epoch(train) [107][340/2119] lr: 4.0000e-03 eta: 8:57:39 time: 0.3883 data_time: 0.0206 memory: 5826 grad_norm: 3.6008 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1009 loss: 2.1009 2022/10/08 05:47:57 - mmengine - INFO - Epoch(train) [107][360/2119] lr: 4.0000e-03 eta: 8:57:32 time: 0.3577 data_time: 0.0214 memory: 5826 grad_norm: 3.6626 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.3629 loss: 2.3629 2022/10/08 05:48:06 - mmengine - INFO - Epoch(train) [107][380/2119] lr: 4.0000e-03 eta: 8:57:26 time: 0.4087 data_time: 0.0234 memory: 5826 grad_norm: 3.6932 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.3190 loss: 2.3190 2022/10/08 05:48:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 05:48:11 - mmengine - INFO - Epoch(train) [107][400/2119] lr: 4.0000e-03 eta: 8:57:18 time: 0.2805 data_time: 0.0268 memory: 5826 grad_norm: 3.6272 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0517 loss: 2.0517 2022/10/08 05:48:19 - mmengine - INFO - Epoch(train) [107][420/2119] lr: 4.0000e-03 eta: 8:57:12 time: 0.3982 data_time: 0.0286 memory: 5826 grad_norm: 3.6228 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1323 loss: 2.1323 2022/10/08 05:48:25 - mmengine - INFO - Epoch(train) [107][440/2119] lr: 4.0000e-03 eta: 8:57:04 time: 0.3032 data_time: 0.0213 memory: 5826 grad_norm: 3.6305 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0356 loss: 2.0356 2022/10/08 05:48:33 - mmengine - INFO - Epoch(train) [107][460/2119] lr: 4.0000e-03 eta: 8:56:58 time: 0.4058 data_time: 0.0214 memory: 5826 grad_norm: 3.6218 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2086 loss: 2.2086 2022/10/08 05:48:41 - mmengine - INFO - Epoch(train) [107][480/2119] lr: 4.0000e-03 eta: 8:56:51 time: 0.3690 data_time: 0.0220 memory: 5826 grad_norm: 3.5666 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.2033 loss: 2.2033 2022/10/08 05:48:48 - mmengine - INFO - Epoch(train) [107][500/2119] lr: 4.0000e-03 eta: 8:56:44 time: 0.3501 data_time: 0.0220 memory: 5826 grad_norm: 3.6172 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.2274 loss: 2.2274 2022/10/08 05:48:54 - mmengine - INFO - Epoch(train) [107][520/2119] lr: 4.0000e-03 eta: 8:56:37 time: 0.3233 data_time: 0.0260 memory: 5826 grad_norm: 3.6269 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0906 loss: 2.0906 2022/10/08 05:49:02 - mmengine - INFO - Epoch(train) [107][540/2119] lr: 4.0000e-03 eta: 8:56:30 time: 0.3780 data_time: 0.0176 memory: 5826 grad_norm: 3.6770 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2383 loss: 2.2383 2022/10/08 05:49:09 - mmengine - INFO - Epoch(train) [107][560/2119] lr: 4.0000e-03 eta: 8:56:23 time: 0.3397 data_time: 0.0253 memory: 5826 grad_norm: 3.5807 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1703 loss: 2.1703 2022/10/08 05:49:16 - mmengine - INFO - Epoch(train) [107][580/2119] lr: 4.0000e-03 eta: 8:56:16 time: 0.3674 data_time: 0.0176 memory: 5826 grad_norm: 3.6110 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0176 loss: 2.0176 2022/10/08 05:49:23 - mmengine - INFO - Epoch(train) [107][600/2119] lr: 4.0000e-03 eta: 8:56:10 time: 0.3576 data_time: 0.0220 memory: 5826 grad_norm: 3.6384 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9854 loss: 1.9854 2022/10/08 05:49:31 - mmengine - INFO - Epoch(train) [107][620/2119] lr: 4.0000e-03 eta: 8:56:03 time: 0.3808 data_time: 0.0193 memory: 5826 grad_norm: 3.5834 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9345 loss: 1.9345 2022/10/08 05:49:38 - mmengine - INFO - Epoch(train) [107][640/2119] lr: 4.0000e-03 eta: 8:55:56 time: 0.3427 data_time: 0.0218 memory: 5826 grad_norm: 3.6200 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9460 loss: 1.9460 2022/10/08 05:49:47 - mmengine - INFO - Epoch(train) [107][660/2119] lr: 4.0000e-03 eta: 8:55:50 time: 0.4494 data_time: 0.0184 memory: 5826 grad_norm: 3.5957 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.2121 loss: 2.2121 2022/10/08 05:49:53 - mmengine - INFO - Epoch(train) [107][680/2119] lr: 4.0000e-03 eta: 8:55:43 time: 0.3361 data_time: 0.0301 memory: 5826 grad_norm: 3.5558 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0007 loss: 2.0007 2022/10/08 05:50:00 - mmengine - INFO - Epoch(train) [107][700/2119] lr: 4.0000e-03 eta: 8:55:36 time: 0.3322 data_time: 0.0225 memory: 5826 grad_norm: 3.6362 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3347 loss: 2.3347 2022/10/08 05:50:07 - mmengine - INFO - Epoch(train) [107][720/2119] lr: 4.0000e-03 eta: 8:55:29 time: 0.3441 data_time: 0.0289 memory: 5826 grad_norm: 3.6317 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0989 loss: 2.0989 2022/10/08 05:50:14 - mmengine - INFO - Epoch(train) [107][740/2119] lr: 4.0000e-03 eta: 8:55:22 time: 0.3507 data_time: 0.0162 memory: 5826 grad_norm: 3.6841 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.2352 loss: 2.2352 2022/10/08 05:50:20 - mmengine - INFO - Epoch(train) [107][760/2119] lr: 4.0000e-03 eta: 8:55:15 time: 0.3049 data_time: 0.0245 memory: 5826 grad_norm: 3.6494 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1272 loss: 2.1272 2022/10/08 05:50:28 - mmengine - INFO - Epoch(train) [107][780/2119] lr: 4.0000e-03 eta: 8:55:08 time: 0.4124 data_time: 0.0202 memory: 5826 grad_norm: 3.7078 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1156 loss: 2.1156 2022/10/08 05:50:34 - mmengine - INFO - Epoch(train) [107][800/2119] lr: 4.0000e-03 eta: 8:55:01 time: 0.2839 data_time: 0.0257 memory: 5826 grad_norm: 3.6609 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.9775 loss: 1.9775 2022/10/08 05:50:42 - mmengine - INFO - Epoch(train) [107][820/2119] lr: 4.0000e-03 eta: 8:54:54 time: 0.3897 data_time: 0.0221 memory: 5826 grad_norm: 3.6403 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.0368 loss: 2.0368 2022/10/08 05:50:49 - mmengine - INFO - Epoch(train) [107][840/2119] lr: 4.0000e-03 eta: 8:54:47 time: 0.3532 data_time: 0.0271 memory: 5826 grad_norm: 3.6508 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0450 loss: 2.0450 2022/10/08 05:50:55 - mmengine - INFO - Epoch(train) [107][860/2119] lr: 4.0000e-03 eta: 8:54:40 time: 0.3285 data_time: 0.0201 memory: 5826 grad_norm: 3.6060 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.3013 loss: 2.3013 2022/10/08 05:51:02 - mmengine - INFO - Epoch(train) [107][880/2119] lr: 4.0000e-03 eta: 8:54:33 time: 0.3321 data_time: 0.0295 memory: 5826 grad_norm: 3.6909 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.0124 loss: 2.0124 2022/10/08 05:51:09 - mmengine - INFO - Epoch(train) [107][900/2119] lr: 4.0000e-03 eta: 8:54:26 time: 0.3696 data_time: 0.0181 memory: 5826 grad_norm: 3.6448 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0215 loss: 2.0215 2022/10/08 05:51:16 - mmengine - INFO - Epoch(train) [107][920/2119] lr: 4.0000e-03 eta: 8:54:19 time: 0.3330 data_time: 0.0215 memory: 5826 grad_norm: 3.6344 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1417 loss: 2.1417 2022/10/08 05:51:23 - mmengine - INFO - Epoch(train) [107][940/2119] lr: 4.0000e-03 eta: 8:54:12 time: 0.3458 data_time: 0.0254 memory: 5826 grad_norm: 3.7003 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1009 loss: 2.1009 2022/10/08 05:51:30 - mmengine - INFO - Epoch(train) [107][960/2119] lr: 4.0000e-03 eta: 8:54:05 time: 0.3493 data_time: 0.0243 memory: 5826 grad_norm: 3.7180 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.4763 loss: 2.4763 2022/10/08 05:51:37 - mmengine - INFO - Epoch(train) [107][980/2119] lr: 4.0000e-03 eta: 8:53:58 time: 0.3333 data_time: 0.0224 memory: 5826 grad_norm: 3.6998 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1330 loss: 2.1330 2022/10/08 05:51:44 - mmengine - INFO - Epoch(train) [107][1000/2119] lr: 4.0000e-03 eta: 8:53:51 time: 0.3481 data_time: 0.0237 memory: 5826 grad_norm: 3.6100 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.0289 loss: 2.0289 2022/10/08 05:51:51 - mmengine - INFO - Epoch(train) [107][1020/2119] lr: 4.0000e-03 eta: 8:53:45 time: 0.3663 data_time: 0.0251 memory: 5826 grad_norm: 3.6344 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.1386 loss: 2.1386 2022/10/08 05:51:57 - mmengine - INFO - Epoch(train) [107][1040/2119] lr: 4.0000e-03 eta: 8:53:37 time: 0.3147 data_time: 0.0234 memory: 5826 grad_norm: 3.7091 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.2876 loss: 2.2876 2022/10/08 05:52:05 - mmengine - INFO - Epoch(train) [107][1060/2119] lr: 4.0000e-03 eta: 8:53:31 time: 0.3863 data_time: 0.0478 memory: 5826 grad_norm: 3.5888 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1595 loss: 2.1595 2022/10/08 05:52:12 - mmengine - INFO - Epoch(train) [107][1080/2119] lr: 4.0000e-03 eta: 8:53:24 time: 0.3343 data_time: 0.0263 memory: 5826 grad_norm: 3.6053 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1629 loss: 2.1629 2022/10/08 05:52:19 - mmengine - INFO - Epoch(train) [107][1100/2119] lr: 4.0000e-03 eta: 8:53:17 time: 0.3597 data_time: 0.0237 memory: 5826 grad_norm: 3.5762 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.5042 loss: 2.5042 2022/10/08 05:52:26 - mmengine - INFO - Epoch(train) [107][1120/2119] lr: 4.0000e-03 eta: 8:53:10 time: 0.3344 data_time: 0.0214 memory: 5826 grad_norm: 3.6559 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0871 loss: 2.0871 2022/10/08 05:52:33 - mmengine - INFO - Epoch(train) [107][1140/2119] lr: 4.0000e-03 eta: 8:53:03 time: 0.3756 data_time: 0.0178 memory: 5826 grad_norm: 3.6592 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1136 loss: 2.1136 2022/10/08 05:52:40 - mmengine - INFO - Epoch(train) [107][1160/2119] lr: 4.0000e-03 eta: 8:52:56 time: 0.3477 data_time: 0.0202 memory: 5826 grad_norm: 3.6413 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1766 loss: 2.1766 2022/10/08 05:52:47 - mmengine - INFO - Epoch(train) [107][1180/2119] lr: 4.0000e-03 eta: 8:52:49 time: 0.3410 data_time: 0.0214 memory: 5826 grad_norm: 3.6426 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2057 loss: 2.2057 2022/10/08 05:52:54 - mmengine - INFO - Epoch(train) [107][1200/2119] lr: 4.0000e-03 eta: 8:52:42 time: 0.3530 data_time: 0.0204 memory: 5826 grad_norm: 3.6176 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0530 loss: 2.0530 2022/10/08 05:53:01 - mmengine - INFO - Epoch(train) [107][1220/2119] lr: 4.0000e-03 eta: 8:52:35 time: 0.3754 data_time: 0.0202 memory: 5826 grad_norm: 3.6580 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0499 loss: 2.0499 2022/10/08 05:53:08 - mmengine - INFO - Epoch(train) [107][1240/2119] lr: 4.0000e-03 eta: 8:52:28 time: 0.3254 data_time: 0.0249 memory: 5826 grad_norm: 3.6087 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.2003 loss: 2.2003 2022/10/08 05:53:16 - mmengine - INFO - Epoch(train) [107][1260/2119] lr: 4.0000e-03 eta: 8:52:22 time: 0.3787 data_time: 0.0194 memory: 5826 grad_norm: 3.6088 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.2821 loss: 2.2821 2022/10/08 05:53:22 - mmengine - INFO - Epoch(train) [107][1280/2119] lr: 4.0000e-03 eta: 8:52:15 time: 0.3339 data_time: 0.0222 memory: 5826 grad_norm: 3.6540 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.3034 loss: 2.3034 2022/10/08 05:53:30 - mmengine - INFO - Epoch(train) [107][1300/2119] lr: 4.0000e-03 eta: 8:52:08 time: 0.3738 data_time: 0.0226 memory: 5826 grad_norm: 3.6532 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.2436 loss: 2.2436 2022/10/08 05:53:37 - mmengine - INFO - Epoch(train) [107][1320/2119] lr: 4.0000e-03 eta: 8:52:01 time: 0.3476 data_time: 0.0218 memory: 5826 grad_norm: 3.6414 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.0227 loss: 2.0227 2022/10/08 05:53:43 - mmengine - INFO - Epoch(train) [107][1340/2119] lr: 4.0000e-03 eta: 8:51:54 time: 0.3333 data_time: 0.0236 memory: 5826 grad_norm: 3.6968 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.3201 loss: 2.3201 2022/10/08 05:53:50 - mmengine - INFO - Epoch(train) [107][1360/2119] lr: 4.0000e-03 eta: 8:51:47 time: 0.3387 data_time: 0.0199 memory: 5826 grad_norm: 3.7357 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1751 loss: 2.1751 2022/10/08 05:53:59 - mmengine - INFO - Epoch(train) [107][1380/2119] lr: 4.0000e-03 eta: 8:51:40 time: 0.4154 data_time: 0.0191 memory: 5826 grad_norm: 3.6890 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0597 loss: 2.0597 2022/10/08 05:54:00 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 05:54:06 - mmengine - INFO - Epoch(train) [107][1400/2119] lr: 4.0000e-03 eta: 8:51:34 time: 0.3527 data_time: 0.0237 memory: 5826 grad_norm: 3.6464 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.3538 loss: 2.3538 2022/10/08 05:54:13 - mmengine - INFO - Epoch(train) [107][1420/2119] lr: 4.0000e-03 eta: 8:51:27 time: 0.3813 data_time: 0.0239 memory: 5826 grad_norm: 3.5887 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1920 loss: 2.1920 2022/10/08 05:54:19 - mmengine - INFO - Epoch(train) [107][1440/2119] lr: 4.0000e-03 eta: 8:51:20 time: 0.3057 data_time: 0.0259 memory: 5826 grad_norm: 3.6489 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1181 loss: 2.1181 2022/10/08 05:54:26 - mmengine - INFO - Epoch(train) [107][1460/2119] lr: 4.0000e-03 eta: 8:51:12 time: 0.3251 data_time: 0.0225 memory: 5826 grad_norm: 3.7361 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9934 loss: 1.9934 2022/10/08 05:54:32 - mmengine - INFO - Epoch(train) [107][1480/2119] lr: 4.0000e-03 eta: 8:51:05 time: 0.3337 data_time: 0.0249 memory: 5826 grad_norm: 3.6112 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9302 loss: 1.9302 2022/10/08 05:54:41 - mmengine - INFO - Epoch(train) [107][1500/2119] lr: 4.0000e-03 eta: 8:50:59 time: 0.4038 data_time: 0.0207 memory: 5826 grad_norm: 3.6508 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.9723 loss: 1.9723 2022/10/08 05:54:47 - mmengine - INFO - Epoch(train) [107][1520/2119] lr: 4.0000e-03 eta: 8:50:52 time: 0.2995 data_time: 0.0198 memory: 5826 grad_norm: 3.6654 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0091 loss: 2.0091 2022/10/08 05:54:54 - mmengine - INFO - Epoch(train) [107][1540/2119] lr: 4.0000e-03 eta: 8:50:45 time: 0.3569 data_time: 0.0212 memory: 5826 grad_norm: 3.6992 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.2041 loss: 2.2041 2022/10/08 05:55:01 - mmengine - INFO - Epoch(train) [107][1560/2119] lr: 4.0000e-03 eta: 8:50:38 time: 0.3610 data_time: 0.0211 memory: 5826 grad_norm: 3.6791 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2301 loss: 2.2301 2022/10/08 05:55:08 - mmengine - INFO - Epoch(train) [107][1580/2119] lr: 4.0000e-03 eta: 8:50:31 time: 0.3457 data_time: 0.0284 memory: 5826 grad_norm: 3.6081 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.2684 loss: 2.2684 2022/10/08 05:55:15 - mmengine - INFO - Epoch(train) [107][1600/2119] lr: 4.0000e-03 eta: 8:50:24 time: 0.3631 data_time: 0.0246 memory: 5826 grad_norm: 3.6191 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1257 loss: 2.1257 2022/10/08 05:55:22 - mmengine - INFO - Epoch(train) [107][1620/2119] lr: 4.0000e-03 eta: 8:50:17 time: 0.3534 data_time: 0.0176 memory: 5826 grad_norm: 3.6670 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1663 loss: 2.1663 2022/10/08 05:55:29 - mmengine - INFO - Epoch(train) [107][1640/2119] lr: 4.0000e-03 eta: 8:50:10 time: 0.3460 data_time: 0.0260 memory: 5826 grad_norm: 3.6286 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9549 loss: 1.9549 2022/10/08 05:55:37 - mmengine - INFO - Epoch(train) [107][1660/2119] lr: 4.0000e-03 eta: 8:50:04 time: 0.3819 data_time: 0.0196 memory: 5826 grad_norm: 3.6379 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.2461 loss: 2.2461 2022/10/08 05:55:44 - mmengine - INFO - Epoch(train) [107][1680/2119] lr: 4.0000e-03 eta: 8:49:57 time: 0.3543 data_time: 0.0214 memory: 5826 grad_norm: 3.6741 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.2192 loss: 2.2192 2022/10/08 05:55:51 - mmengine - INFO - Epoch(train) [107][1700/2119] lr: 4.0000e-03 eta: 8:49:50 time: 0.3563 data_time: 0.0249 memory: 5826 grad_norm: 3.7003 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1748 loss: 2.1748 2022/10/08 05:55:58 - mmengine - INFO - Epoch(train) [107][1720/2119] lr: 4.0000e-03 eta: 8:49:43 time: 0.3722 data_time: 0.0185 memory: 5826 grad_norm: 3.6986 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.1671 loss: 2.1671 2022/10/08 05:56:06 - mmengine - INFO - Epoch(train) [107][1740/2119] lr: 4.0000e-03 eta: 8:49:36 time: 0.3543 data_time: 0.0223 memory: 5826 grad_norm: 3.6837 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0253 loss: 2.0253 2022/10/08 05:56:12 - mmengine - INFO - Epoch(train) [107][1760/2119] lr: 4.0000e-03 eta: 8:49:29 time: 0.3044 data_time: 0.0239 memory: 5826 grad_norm: 3.6577 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9601 loss: 1.9601 2022/10/08 05:56:19 - mmengine - INFO - Epoch(train) [107][1780/2119] lr: 4.0000e-03 eta: 8:49:22 time: 0.3696 data_time: 0.0242 memory: 5826 grad_norm: 3.7391 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1953 loss: 2.1953 2022/10/08 05:56:25 - mmengine - INFO - Epoch(train) [107][1800/2119] lr: 4.0000e-03 eta: 8:49:15 time: 0.3159 data_time: 0.0220 memory: 5826 grad_norm: 3.7370 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2556 loss: 2.2556 2022/10/08 05:56:32 - mmengine - INFO - Epoch(train) [107][1820/2119] lr: 4.0000e-03 eta: 8:49:08 time: 0.3502 data_time: 0.0205 memory: 5826 grad_norm: 3.7270 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.2823 loss: 2.2823 2022/10/08 05:56:39 - mmengine - INFO - Epoch(train) [107][1840/2119] lr: 4.0000e-03 eta: 8:49:01 time: 0.3506 data_time: 0.0343 memory: 5826 grad_norm: 3.5984 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0855 loss: 2.0855 2022/10/08 05:56:47 - mmengine - INFO - Epoch(train) [107][1860/2119] lr: 4.0000e-03 eta: 8:48:54 time: 0.3752 data_time: 0.0223 memory: 5826 grad_norm: 3.6882 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1376 loss: 2.1376 2022/10/08 05:56:54 - mmengine - INFO - Epoch(train) [107][1880/2119] lr: 4.0000e-03 eta: 8:48:48 time: 0.3555 data_time: 0.0262 memory: 5826 grad_norm: 3.6257 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1090 loss: 2.1090 2022/10/08 05:57:01 - mmengine - INFO - Epoch(train) [107][1900/2119] lr: 4.0000e-03 eta: 8:48:41 time: 0.3724 data_time: 0.0272 memory: 5826 grad_norm: 3.6420 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2957 loss: 2.2957 2022/10/08 05:57:09 - mmengine - INFO - Epoch(train) [107][1920/2119] lr: 4.0000e-03 eta: 8:48:34 time: 0.3693 data_time: 0.0217 memory: 5826 grad_norm: 3.6639 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0456 loss: 2.0456 2022/10/08 05:57:16 - mmengine - INFO - Epoch(train) [107][1940/2119] lr: 4.0000e-03 eta: 8:48:27 time: 0.3604 data_time: 0.0199 memory: 5826 grad_norm: 3.6500 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.1217 loss: 2.1217 2022/10/08 05:57:23 - mmengine - INFO - Epoch(train) [107][1960/2119] lr: 4.0000e-03 eta: 8:48:20 time: 0.3524 data_time: 0.0209 memory: 5826 grad_norm: 3.7020 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2331 loss: 2.2331 2022/10/08 05:57:30 - mmengine - INFO - Epoch(train) [107][1980/2119] lr: 4.0000e-03 eta: 8:48:13 time: 0.3670 data_time: 0.0242 memory: 5826 grad_norm: 3.6929 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.2194 loss: 2.2194 2022/10/08 05:57:38 - mmengine - INFO - Epoch(train) [107][2000/2119] lr: 4.0000e-03 eta: 8:48:07 time: 0.3743 data_time: 0.0177 memory: 5826 grad_norm: 3.6753 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.0817 loss: 2.0817 2022/10/08 05:57:45 - mmengine - INFO - Epoch(train) [107][2020/2119] lr: 4.0000e-03 eta: 8:48:00 time: 0.3580 data_time: 0.0248 memory: 5826 grad_norm: 3.6732 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1356 loss: 2.1356 2022/10/08 05:57:52 - mmengine - INFO - Epoch(train) [107][2040/2119] lr: 4.0000e-03 eta: 8:47:53 time: 0.3182 data_time: 0.0290 memory: 5826 grad_norm: 3.7275 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1008 loss: 2.1008 2022/10/08 05:57:58 - mmengine - INFO - Epoch(train) [107][2060/2119] lr: 4.0000e-03 eta: 8:47:46 time: 0.3376 data_time: 0.0173 memory: 5826 grad_norm: 3.6424 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0506 loss: 2.0506 2022/10/08 05:58:06 - mmengine - INFO - Epoch(train) [107][2080/2119] lr: 4.0000e-03 eta: 8:47:39 time: 0.3691 data_time: 0.0253 memory: 5826 grad_norm: 3.6739 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9789 loss: 1.9789 2022/10/08 05:58:13 - mmengine - INFO - Epoch(train) [107][2100/2119] lr: 4.0000e-03 eta: 8:47:32 time: 0.3781 data_time: 0.0195 memory: 5826 grad_norm: 3.7327 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0562 loss: 2.0562 2022/10/08 05:58:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 05:58:19 - mmengine - INFO - Epoch(train) [107][2119/2119] lr: 4.0000e-03 eta: 8:47:32 time: 0.3311 data_time: 0.0192 memory: 5826 grad_norm: 3.7262 top1_acc: 0.8000 top5_acc: 0.9000 loss_cls: 1.8677 loss: 1.8677 2022/10/08 05:58:29 - mmengine - INFO - Epoch(train) [108][20/2119] lr: 4.0000e-03 eta: 8:47:17 time: 0.4992 data_time: 0.1644 memory: 5826 grad_norm: 3.7628 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1869 loss: 2.1869 2022/10/08 05:58:36 - mmengine - INFO - Epoch(train) [108][40/2119] lr: 4.0000e-03 eta: 8:47:10 time: 0.3409 data_time: 0.0215 memory: 5826 grad_norm: 3.6438 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0613 loss: 2.0613 2022/10/08 05:58:44 - mmengine - INFO - Epoch(train) [108][60/2119] lr: 4.0000e-03 eta: 8:47:04 time: 0.3973 data_time: 0.0219 memory: 5826 grad_norm: 3.5865 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.1821 loss: 2.1821 2022/10/08 05:58:51 - mmengine - INFO - Epoch(train) [108][80/2119] lr: 4.0000e-03 eta: 8:46:57 time: 0.3602 data_time: 0.0229 memory: 5826 grad_norm: 3.6719 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2370 loss: 2.2370 2022/10/08 05:58:59 - mmengine - INFO - Epoch(train) [108][100/2119] lr: 4.0000e-03 eta: 8:46:50 time: 0.3770 data_time: 0.0206 memory: 5826 grad_norm: 3.6990 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1498 loss: 2.1498 2022/10/08 05:59:05 - mmengine - INFO - Epoch(train) [108][120/2119] lr: 4.0000e-03 eta: 8:46:43 time: 0.3185 data_time: 0.0261 memory: 5826 grad_norm: 3.6245 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9984 loss: 1.9984 2022/10/08 05:59:13 - mmengine - INFO - Epoch(train) [108][140/2119] lr: 4.0000e-03 eta: 8:46:36 time: 0.3675 data_time: 0.0213 memory: 5826 grad_norm: 3.6906 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1684 loss: 2.1684 2022/10/08 05:59:20 - mmengine - INFO - Epoch(train) [108][160/2119] lr: 4.0000e-03 eta: 8:46:29 time: 0.3438 data_time: 0.0220 memory: 5826 grad_norm: 3.6735 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.1766 loss: 2.1766 2022/10/08 05:59:28 - mmengine - INFO - Epoch(train) [108][180/2119] lr: 4.0000e-03 eta: 8:46:23 time: 0.4014 data_time: 0.0240 memory: 5826 grad_norm: 3.7114 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0750 loss: 2.0750 2022/10/08 05:59:34 - mmengine - INFO - Epoch(train) [108][200/2119] lr: 4.0000e-03 eta: 8:46:16 time: 0.3197 data_time: 0.0248 memory: 5826 grad_norm: 3.6858 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0771 loss: 2.0771 2022/10/08 05:59:42 - mmengine - INFO - Epoch(train) [108][220/2119] lr: 4.0000e-03 eta: 8:46:09 time: 0.4164 data_time: 0.0192 memory: 5826 grad_norm: 3.7368 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0279 loss: 2.0279 2022/10/08 05:59:49 - mmengine - INFO - Epoch(train) [108][240/2119] lr: 4.0000e-03 eta: 8:46:02 time: 0.3383 data_time: 0.0261 memory: 5826 grad_norm: 3.7569 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8632 loss: 1.8632 2022/10/08 05:59:56 - mmengine - INFO - Epoch(train) [108][260/2119] lr: 4.0000e-03 eta: 8:45:55 time: 0.3392 data_time: 0.0250 memory: 5826 grad_norm: 3.7438 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.1046 loss: 2.1046 2022/10/08 05:59:59 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 06:00:05 - mmengine - INFO - Epoch(train) [108][280/2119] lr: 4.0000e-03 eta: 8:45:49 time: 0.4535 data_time: 0.0237 memory: 5826 grad_norm: 3.7130 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.1199 loss: 2.1199 2022/10/08 06:00:11 - mmengine - INFO - Epoch(train) [108][300/2119] lr: 4.0000e-03 eta: 8:45:42 time: 0.3179 data_time: 0.0318 memory: 5826 grad_norm: 3.6398 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9633 loss: 1.9633 2022/10/08 06:00:18 - mmengine - INFO - Epoch(train) [108][320/2119] lr: 4.0000e-03 eta: 8:45:35 time: 0.3277 data_time: 0.0195 memory: 5826 grad_norm: 3.7085 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9925 loss: 1.9925 2022/10/08 06:00:25 - mmengine - INFO - Epoch(train) [108][340/2119] lr: 4.0000e-03 eta: 8:45:28 time: 0.3637 data_time: 0.0229 memory: 5826 grad_norm: 3.7307 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1878 loss: 2.1878 2022/10/08 06:00:32 - mmengine - INFO - Epoch(train) [108][360/2119] lr: 4.0000e-03 eta: 8:45:21 time: 0.3605 data_time: 0.0170 memory: 5826 grad_norm: 3.6921 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1942 loss: 2.1942 2022/10/08 06:00:39 - mmengine - INFO - Epoch(train) [108][380/2119] lr: 4.0000e-03 eta: 8:45:14 time: 0.3459 data_time: 0.0227 memory: 5826 grad_norm: 3.7539 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0092 loss: 2.0092 2022/10/08 06:00:47 - mmengine - INFO - Epoch(train) [108][400/2119] lr: 4.0000e-03 eta: 8:45:07 time: 0.3760 data_time: 0.0350 memory: 5826 grad_norm: 3.7566 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0507 loss: 2.0507 2022/10/08 06:00:53 - mmengine - INFO - Epoch(train) [108][420/2119] lr: 4.0000e-03 eta: 8:45:00 time: 0.3232 data_time: 0.0264 memory: 5826 grad_norm: 3.7208 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.1630 loss: 2.1630 2022/10/08 06:01:01 - mmengine - INFO - Epoch(train) [108][440/2119] lr: 4.0000e-03 eta: 8:44:54 time: 0.3925 data_time: 0.0166 memory: 5826 grad_norm: 3.6637 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.0608 loss: 2.0608 2022/10/08 06:01:07 - mmengine - INFO - Epoch(train) [108][460/2119] lr: 4.0000e-03 eta: 8:44:46 time: 0.3157 data_time: 0.0200 memory: 5826 grad_norm: 3.6940 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2054 loss: 2.2054 2022/10/08 06:01:14 - mmengine - INFO - Epoch(train) [108][480/2119] lr: 4.0000e-03 eta: 8:44:40 time: 0.3487 data_time: 0.0191 memory: 5826 grad_norm: 3.7536 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.0599 loss: 2.0599 2022/10/08 06:01:22 - mmengine - INFO - Epoch(train) [108][500/2119] lr: 4.0000e-03 eta: 8:44:33 time: 0.3673 data_time: 0.0224 memory: 5826 grad_norm: 3.7577 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1294 loss: 2.1294 2022/10/08 06:01:28 - mmengine - INFO - Epoch(train) [108][520/2119] lr: 4.0000e-03 eta: 8:44:26 time: 0.3300 data_time: 0.0216 memory: 5826 grad_norm: 3.7348 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.4191 loss: 2.4191 2022/10/08 06:01:36 - mmengine - INFO - Epoch(train) [108][540/2119] lr: 4.0000e-03 eta: 8:44:19 time: 0.3949 data_time: 0.0207 memory: 5826 grad_norm: 3.7136 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9655 loss: 1.9655 2022/10/08 06:01:44 - mmengine - INFO - Epoch(train) [108][560/2119] lr: 4.0000e-03 eta: 8:44:12 time: 0.3619 data_time: 0.0357 memory: 5826 grad_norm: 3.7171 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.9468 loss: 1.9468 2022/10/08 06:01:50 - mmengine - INFO - Epoch(train) [108][580/2119] lr: 4.0000e-03 eta: 8:44:05 time: 0.3327 data_time: 0.0218 memory: 5826 grad_norm: 3.7503 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0691 loss: 2.0691 2022/10/08 06:01:57 - mmengine - INFO - Epoch(train) [108][600/2119] lr: 4.0000e-03 eta: 8:43:58 time: 0.3433 data_time: 0.0219 memory: 5826 grad_norm: 3.7590 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9974 loss: 1.9974 2022/10/08 06:02:04 - mmengine - INFO - Epoch(train) [108][620/2119] lr: 4.0000e-03 eta: 8:43:51 time: 0.3338 data_time: 0.0268 memory: 5826 grad_norm: 3.7179 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.3474 loss: 2.3474 2022/10/08 06:02:11 - mmengine - INFO - Epoch(train) [108][640/2119] lr: 4.0000e-03 eta: 8:43:44 time: 0.3688 data_time: 0.0198 memory: 5826 grad_norm: 3.7257 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2048 loss: 2.2048 2022/10/08 06:02:20 - mmengine - INFO - Epoch(train) [108][660/2119] lr: 4.0000e-03 eta: 8:43:38 time: 0.4187 data_time: 0.0270 memory: 5826 grad_norm: 3.7495 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1849 loss: 2.1849 2022/10/08 06:02:26 - mmengine - INFO - Epoch(train) [108][680/2119] lr: 4.0000e-03 eta: 8:43:31 time: 0.3048 data_time: 0.0168 memory: 5826 grad_norm: 3.6376 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6484 loss: 1.6484 2022/10/08 06:02:33 - mmengine - INFO - Epoch(train) [108][700/2119] lr: 4.0000e-03 eta: 8:43:24 time: 0.3871 data_time: 0.0245 memory: 5826 grad_norm: 3.7267 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0773 loss: 2.0773 2022/10/08 06:02:40 - mmengine - INFO - Epoch(train) [108][720/2119] lr: 4.0000e-03 eta: 8:43:17 time: 0.3471 data_time: 0.0298 memory: 5826 grad_norm: 3.6794 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1679 loss: 2.1679 2022/10/08 06:02:47 - mmengine - INFO - Epoch(train) [108][740/2119] lr: 4.0000e-03 eta: 8:43:10 time: 0.3329 data_time: 0.0212 memory: 5826 grad_norm: 3.7104 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9738 loss: 1.9738 2022/10/08 06:02:54 - mmengine - INFO - Epoch(train) [108][760/2119] lr: 4.0000e-03 eta: 8:43:03 time: 0.3573 data_time: 0.0208 memory: 5826 grad_norm: 3.6360 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1465 loss: 2.1465 2022/10/08 06:03:02 - mmengine - INFO - Epoch(train) [108][780/2119] lr: 4.0000e-03 eta: 8:42:56 time: 0.3703 data_time: 0.0232 memory: 5826 grad_norm: 3.7292 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1392 loss: 2.1392 2022/10/08 06:03:09 - mmengine - INFO - Epoch(train) [108][800/2119] lr: 4.0000e-03 eta: 8:42:50 time: 0.3639 data_time: 0.0201 memory: 5826 grad_norm: 3.6773 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.2853 loss: 2.2853 2022/10/08 06:03:16 - mmengine - INFO - Epoch(train) [108][820/2119] lr: 4.0000e-03 eta: 8:42:43 time: 0.3625 data_time: 0.0167 memory: 5826 grad_norm: 3.6775 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0900 loss: 2.0900 2022/10/08 06:03:23 - mmengine - INFO - Epoch(train) [108][840/2119] lr: 4.0000e-03 eta: 8:42:36 time: 0.3223 data_time: 0.0180 memory: 5826 grad_norm: 3.6598 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1169 loss: 2.1169 2022/10/08 06:03:29 - mmengine - INFO - Epoch(train) [108][860/2119] lr: 4.0000e-03 eta: 8:42:29 time: 0.3434 data_time: 0.0231 memory: 5826 grad_norm: 3.7347 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.2589 loss: 2.2589 2022/10/08 06:03:37 - mmengine - INFO - Epoch(train) [108][880/2119] lr: 4.0000e-03 eta: 8:42:22 time: 0.3765 data_time: 0.0229 memory: 5826 grad_norm: 3.7653 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0297 loss: 2.0297 2022/10/08 06:03:45 - mmengine - INFO - Epoch(train) [108][900/2119] lr: 4.0000e-03 eta: 8:42:15 time: 0.3839 data_time: 0.0224 memory: 5826 grad_norm: 3.7365 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9797 loss: 1.9797 2022/10/08 06:03:52 - mmengine - INFO - Epoch(train) [108][920/2119] lr: 4.0000e-03 eta: 8:42:08 time: 0.3492 data_time: 0.0228 memory: 5826 grad_norm: 3.6764 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1023 loss: 2.1023 2022/10/08 06:03:59 - mmengine - INFO - Epoch(train) [108][940/2119] lr: 4.0000e-03 eta: 8:42:02 time: 0.3768 data_time: 0.0238 memory: 5826 grad_norm: 3.6978 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0685 loss: 2.0685 2022/10/08 06:04:06 - mmengine - INFO - Epoch(train) [108][960/2119] lr: 4.0000e-03 eta: 8:41:55 time: 0.3455 data_time: 0.0212 memory: 5826 grad_norm: 3.6907 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9047 loss: 1.9047 2022/10/08 06:04:14 - mmengine - INFO - Epoch(train) [108][980/2119] lr: 4.0000e-03 eta: 8:41:48 time: 0.3880 data_time: 0.0205 memory: 5826 grad_norm: 3.7326 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0321 loss: 2.0321 2022/10/08 06:04:22 - mmengine - INFO - Epoch(train) [108][1000/2119] lr: 4.0000e-03 eta: 8:41:42 time: 0.4047 data_time: 0.0196 memory: 5826 grad_norm: 3.6575 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0951 loss: 2.0951 2022/10/08 06:04:28 - mmengine - INFO - Epoch(train) [108][1020/2119] lr: 4.0000e-03 eta: 8:41:34 time: 0.2977 data_time: 0.0224 memory: 5826 grad_norm: 3.7191 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0913 loss: 2.0913 2022/10/08 06:04:35 - mmengine - INFO - Epoch(train) [108][1040/2119] lr: 4.0000e-03 eta: 8:41:27 time: 0.3630 data_time: 0.0229 memory: 5826 grad_norm: 3.6710 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0066 loss: 2.0066 2022/10/08 06:04:43 - mmengine - INFO - Epoch(train) [108][1060/2119] lr: 4.0000e-03 eta: 8:41:21 time: 0.3708 data_time: 0.0229 memory: 5826 grad_norm: 3.6634 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.7861 loss: 1.7861 2022/10/08 06:04:49 - mmengine - INFO - Epoch(train) [108][1080/2119] lr: 4.0000e-03 eta: 8:41:13 time: 0.3083 data_time: 0.0219 memory: 5826 grad_norm: 3.6974 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9608 loss: 1.9608 2022/10/08 06:04:56 - mmengine - INFO - Epoch(train) [108][1100/2119] lr: 4.0000e-03 eta: 8:41:07 time: 0.3751 data_time: 0.0231 memory: 5826 grad_norm: 3.7706 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0495 loss: 2.0495 2022/10/08 06:05:03 - mmengine - INFO - Epoch(train) [108][1120/2119] lr: 4.0000e-03 eta: 8:41:00 time: 0.3450 data_time: 0.0209 memory: 5826 grad_norm: 3.7080 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.1833 loss: 2.1833 2022/10/08 06:05:10 - mmengine - INFO - Epoch(train) [108][1140/2119] lr: 4.0000e-03 eta: 8:40:53 time: 0.3342 data_time: 0.0216 memory: 5826 grad_norm: 3.6980 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.0131 loss: 2.0131 2022/10/08 06:05:18 - mmengine - INFO - Epoch(train) [108][1160/2119] lr: 4.0000e-03 eta: 8:40:46 time: 0.3936 data_time: 0.0182 memory: 5826 grad_norm: 3.7086 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1439 loss: 2.1439 2022/10/08 06:05:25 - mmengine - INFO - Epoch(train) [108][1180/2119] lr: 4.0000e-03 eta: 8:40:39 time: 0.3438 data_time: 0.0222 memory: 5826 grad_norm: 3.7070 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2851 loss: 2.2851 2022/10/08 06:05:32 - mmengine - INFO - Epoch(train) [108][1200/2119] lr: 4.0000e-03 eta: 8:40:32 time: 0.3851 data_time: 0.0209 memory: 5826 grad_norm: 3.7277 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.1497 loss: 2.1497 2022/10/08 06:05:39 - mmengine - INFO - Epoch(train) [108][1220/2119] lr: 4.0000e-03 eta: 8:40:26 time: 0.3490 data_time: 0.0226 memory: 5826 grad_norm: 3.7273 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0601 loss: 2.0601 2022/10/08 06:05:46 - mmengine - INFO - Epoch(train) [108][1240/2119] lr: 4.0000e-03 eta: 8:40:18 time: 0.3077 data_time: 0.0246 memory: 5826 grad_norm: 3.7294 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.0006 loss: 2.0006 2022/10/08 06:05:53 - mmengine - INFO - Epoch(train) [108][1260/2119] lr: 4.0000e-03 eta: 8:40:12 time: 0.3901 data_time: 0.0261 memory: 5826 grad_norm: 3.6550 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0770 loss: 2.0770 2022/10/08 06:05:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 06:06:00 - mmengine - INFO - Epoch(train) [108][1280/2119] lr: 4.0000e-03 eta: 8:40:05 time: 0.3255 data_time: 0.0209 memory: 5826 grad_norm: 3.6573 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1566 loss: 2.1566 2022/10/08 06:06:07 - mmengine - INFO - Epoch(train) [108][1300/2119] lr: 4.0000e-03 eta: 8:39:58 time: 0.3513 data_time: 0.0242 memory: 5826 grad_norm: 3.6910 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8331 loss: 1.8331 2022/10/08 06:06:13 - mmengine - INFO - Epoch(train) [108][1320/2119] lr: 4.0000e-03 eta: 8:39:50 time: 0.3216 data_time: 0.0208 memory: 5826 grad_norm: 3.6879 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.3869 loss: 2.3869 2022/10/08 06:06:20 - mmengine - INFO - Epoch(train) [108][1340/2119] lr: 4.0000e-03 eta: 8:39:44 time: 0.3567 data_time: 0.0256 memory: 5826 grad_norm: 3.7245 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 1.9724 loss: 1.9724 2022/10/08 06:06:28 - mmengine - INFO - Epoch(train) [108][1360/2119] lr: 4.0000e-03 eta: 8:39:37 time: 0.3779 data_time: 0.0240 memory: 5826 grad_norm: 3.7090 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.1541 loss: 2.1541 2022/10/08 06:06:35 - mmengine - INFO - Epoch(train) [108][1380/2119] lr: 4.0000e-03 eta: 8:39:30 time: 0.3253 data_time: 0.0173 memory: 5826 grad_norm: 3.7510 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8340 loss: 1.8340 2022/10/08 06:06:42 - mmengine - INFO - Epoch(train) [108][1400/2119] lr: 4.0000e-03 eta: 8:39:23 time: 0.3555 data_time: 0.0278 memory: 5826 grad_norm: 3.7503 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 2.1407 loss: 2.1407 2022/10/08 06:06:48 - mmengine - INFO - Epoch(train) [108][1420/2119] lr: 4.0000e-03 eta: 8:39:16 time: 0.3400 data_time: 0.0229 memory: 5826 grad_norm: 3.7096 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0043 loss: 2.0043 2022/10/08 06:06:56 - mmengine - INFO - Epoch(train) [108][1440/2119] lr: 4.0000e-03 eta: 8:39:09 time: 0.3655 data_time: 0.0191 memory: 5826 grad_norm: 3.7441 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0301 loss: 2.0301 2022/10/08 06:07:04 - mmengine - INFO - Epoch(train) [108][1460/2119] lr: 4.0000e-03 eta: 8:39:03 time: 0.4096 data_time: 0.0192 memory: 5826 grad_norm: 3.6953 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8914 loss: 1.8914 2022/10/08 06:07:11 - mmengine - INFO - Epoch(train) [108][1480/2119] lr: 4.0000e-03 eta: 8:38:56 time: 0.3436 data_time: 0.0234 memory: 5826 grad_norm: 3.6984 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.0168 loss: 2.0168 2022/10/08 06:07:18 - mmengine - INFO - Epoch(train) [108][1500/2119] lr: 4.0000e-03 eta: 8:38:49 time: 0.3607 data_time: 0.0202 memory: 5826 grad_norm: 3.8037 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.2000 loss: 2.2000 2022/10/08 06:07:25 - mmengine - INFO - Epoch(train) [108][1520/2119] lr: 4.0000e-03 eta: 8:38:42 time: 0.3354 data_time: 0.0209 memory: 5826 grad_norm: 3.7218 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.0390 loss: 2.0390 2022/10/08 06:07:32 - mmengine - INFO - Epoch(train) [108][1540/2119] lr: 4.0000e-03 eta: 8:38:35 time: 0.3642 data_time: 0.0216 memory: 5826 grad_norm: 3.8066 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2644 loss: 2.2644 2022/10/08 06:07:39 - mmengine - INFO - Epoch(train) [108][1560/2119] lr: 4.0000e-03 eta: 8:38:28 time: 0.3531 data_time: 0.0176 memory: 5826 grad_norm: 3.7362 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1947 loss: 2.1947 2022/10/08 06:07:47 - mmengine - INFO - Epoch(train) [108][1580/2119] lr: 4.0000e-03 eta: 8:38:21 time: 0.3702 data_time: 0.0188 memory: 5826 grad_norm: 3.7638 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.3344 loss: 2.3344 2022/10/08 06:07:53 - mmengine - INFO - Epoch(train) [108][1600/2119] lr: 4.0000e-03 eta: 8:38:14 time: 0.3400 data_time: 0.0204 memory: 5826 grad_norm: 3.6932 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0038 loss: 2.0038 2022/10/08 06:08:02 - mmengine - INFO - Epoch(train) [108][1620/2119] lr: 4.0000e-03 eta: 8:38:08 time: 0.4238 data_time: 0.0214 memory: 5826 grad_norm: 3.7441 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1724 loss: 2.1724 2022/10/08 06:08:09 - mmengine - INFO - Epoch(train) [108][1640/2119] lr: 4.0000e-03 eta: 8:38:01 time: 0.3419 data_time: 0.0191 memory: 5826 grad_norm: 3.7239 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0931 loss: 2.0931 2022/10/08 06:08:16 - mmengine - INFO - Epoch(train) [108][1660/2119] lr: 4.0000e-03 eta: 8:37:54 time: 0.3780 data_time: 0.0235 memory: 5826 grad_norm: 3.7454 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.2016 loss: 2.2016 2022/10/08 06:08:24 - mmengine - INFO - Epoch(train) [108][1680/2119] lr: 4.0000e-03 eta: 8:37:47 time: 0.3607 data_time: 0.0195 memory: 5826 grad_norm: 3.6876 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1116 loss: 2.1116 2022/10/08 06:08:32 - mmengine - INFO - Epoch(train) [108][1700/2119] lr: 4.0000e-03 eta: 8:37:41 time: 0.4056 data_time: 0.0238 memory: 5826 grad_norm: 3.7154 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0560 loss: 2.0560 2022/10/08 06:08:37 - mmengine - INFO - Epoch(train) [108][1720/2119] lr: 4.0000e-03 eta: 8:37:34 time: 0.2906 data_time: 0.0256 memory: 5826 grad_norm: 3.7396 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.0698 loss: 2.0698 2022/10/08 06:08:46 - mmengine - INFO - Epoch(train) [108][1740/2119] lr: 4.0000e-03 eta: 8:37:27 time: 0.4024 data_time: 0.0225 memory: 5826 grad_norm: 3.7303 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9931 loss: 1.9931 2022/10/08 06:08:52 - mmengine - INFO - Epoch(train) [108][1760/2119] lr: 4.0000e-03 eta: 8:37:20 time: 0.3156 data_time: 0.0196 memory: 5826 grad_norm: 3.8299 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0612 loss: 2.0612 2022/10/08 06:08:59 - mmengine - INFO - Epoch(train) [108][1780/2119] lr: 4.0000e-03 eta: 8:37:13 time: 0.3697 data_time: 0.0232 memory: 5826 grad_norm: 3.7570 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0826 loss: 2.0826 2022/10/08 06:09:06 - mmengine - INFO - Epoch(train) [108][1800/2119] lr: 4.0000e-03 eta: 8:37:06 time: 0.3560 data_time: 0.0182 memory: 5826 grad_norm: 3.7598 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0385 loss: 2.0385 2022/10/08 06:09:14 - mmengine - INFO - Epoch(train) [108][1820/2119] lr: 4.0000e-03 eta: 8:36:59 time: 0.3687 data_time: 0.0238 memory: 5826 grad_norm: 3.7353 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0943 loss: 2.0943 2022/10/08 06:09:21 - mmengine - INFO - Epoch(train) [108][1840/2119] lr: 4.0000e-03 eta: 8:36:53 time: 0.3752 data_time: 0.0232 memory: 5826 grad_norm: 3.7899 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0692 loss: 2.0692 2022/10/08 06:09:28 - mmengine - INFO - Epoch(train) [108][1860/2119] lr: 4.0000e-03 eta: 8:36:46 time: 0.3545 data_time: 0.0226 memory: 5826 grad_norm: 3.6842 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0804 loss: 2.0804 2022/10/08 06:09:35 - mmengine - INFO - Epoch(train) [108][1880/2119] lr: 4.0000e-03 eta: 8:36:39 time: 0.3467 data_time: 0.0212 memory: 5826 grad_norm: 3.7407 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1125 loss: 2.1125 2022/10/08 06:09:43 - mmengine - INFO - Epoch(train) [108][1900/2119] lr: 4.0000e-03 eta: 8:36:32 time: 0.3827 data_time: 0.0314 memory: 5826 grad_norm: 3.7315 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.1111 loss: 2.1111 2022/10/08 06:09:50 - mmengine - INFO - Epoch(train) [108][1920/2119] lr: 4.0000e-03 eta: 8:36:25 time: 0.3392 data_time: 0.0197 memory: 5826 grad_norm: 3.7423 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0605 loss: 2.0605 2022/10/08 06:09:57 - mmengine - INFO - Epoch(train) [108][1940/2119] lr: 4.0000e-03 eta: 8:36:18 time: 0.3671 data_time: 0.0229 memory: 5826 grad_norm: 3.7313 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.1769 loss: 2.1769 2022/10/08 06:10:04 - mmengine - INFO - Epoch(train) [108][1960/2119] lr: 4.0000e-03 eta: 8:36:11 time: 0.3453 data_time: 0.0262 memory: 5826 grad_norm: 3.7325 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0937 loss: 2.0937 2022/10/08 06:10:11 - mmengine - INFO - Epoch(train) [108][1980/2119] lr: 4.0000e-03 eta: 8:36:04 time: 0.3577 data_time: 0.0235 memory: 5826 grad_norm: 3.7043 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8576 loss: 1.8576 2022/10/08 06:10:18 - mmengine - INFO - Epoch(train) [108][2000/2119] lr: 4.0000e-03 eta: 8:35:57 time: 0.3318 data_time: 0.0211 memory: 5826 grad_norm: 3.8146 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2257 loss: 2.2257 2022/10/08 06:10:25 - mmengine - INFO - Epoch(train) [108][2020/2119] lr: 4.0000e-03 eta: 8:35:51 time: 0.3819 data_time: 0.0212 memory: 5826 grad_norm: 3.7364 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9075 loss: 1.9075 2022/10/08 06:10:32 - mmengine - INFO - Epoch(train) [108][2040/2119] lr: 4.0000e-03 eta: 8:35:44 time: 0.3235 data_time: 0.0205 memory: 5826 grad_norm: 3.7868 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9396 loss: 1.9396 2022/10/08 06:10:39 - mmengine - INFO - Epoch(train) [108][2060/2119] lr: 4.0000e-03 eta: 8:35:37 time: 0.3475 data_time: 0.0214 memory: 5826 grad_norm: 3.7690 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0926 loss: 2.0926 2022/10/08 06:10:47 - mmengine - INFO - Epoch(train) [108][2080/2119] lr: 4.0000e-03 eta: 8:35:30 time: 0.3847 data_time: 0.0253 memory: 5826 grad_norm: 3.7951 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.0871 loss: 2.0871 2022/10/08 06:10:54 - mmengine - INFO - Epoch(train) [108][2100/2119] lr: 4.0000e-03 eta: 8:35:23 time: 0.3554 data_time: 0.0254 memory: 5826 grad_norm: 3.8287 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.1525 loss: 2.1525 2022/10/08 06:11:01 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 06:11:01 - mmengine - INFO - Epoch(train) [108][2119/2119] lr: 4.0000e-03 eta: 8:35:23 time: 0.3727 data_time: 0.0284 memory: 5826 grad_norm: 3.8210 top1_acc: 0.7000 top5_acc: 0.9000 loss_cls: 2.1054 loss: 2.1054 2022/10/08 06:11:01 - mmengine - INFO - Saving checkpoint at 108 epochs 2022/10/08 06:11:12 - mmengine - INFO - Epoch(train) [109][20/2119] lr: 4.0000e-03 eta: 8:35:08 time: 0.4615 data_time: 0.2361 memory: 5826 grad_norm: 3.7637 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.8510 loss: 1.8510 2022/10/08 06:11:18 - mmengine - INFO - Epoch(train) [109][40/2119] lr: 4.0000e-03 eta: 8:35:01 time: 0.3145 data_time: 0.0358 memory: 5826 grad_norm: 3.6969 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9396 loss: 1.9396 2022/10/08 06:11:26 - mmengine - INFO - Epoch(train) [109][60/2119] lr: 4.0000e-03 eta: 8:34:54 time: 0.4255 data_time: 0.0192 memory: 5826 grad_norm: 3.6886 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.0318 loss: 2.0318 2022/10/08 06:11:33 - mmengine - INFO - Epoch(train) [109][80/2119] lr: 4.0000e-03 eta: 8:34:47 time: 0.3233 data_time: 0.0205 memory: 5826 grad_norm: 3.7410 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1420 loss: 2.1420 2022/10/08 06:11:40 - mmengine - INFO - Epoch(train) [109][100/2119] lr: 4.0000e-03 eta: 8:34:40 time: 0.3695 data_time: 0.0214 memory: 5826 grad_norm: 3.7348 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0223 loss: 2.0223 2022/10/08 06:11:47 - mmengine - INFO - Epoch(train) [109][120/2119] lr: 4.0000e-03 eta: 8:34:33 time: 0.3099 data_time: 0.0182 memory: 5826 grad_norm: 3.8045 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0562 loss: 2.0562 2022/10/08 06:11:54 - mmengine - INFO - Epoch(train) [109][140/2119] lr: 4.0000e-03 eta: 8:34:26 time: 0.3564 data_time: 0.0198 memory: 5826 grad_norm: 3.7592 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1542 loss: 2.1542 2022/10/08 06:11:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 06:12:02 - mmengine - INFO - Epoch(train) [109][160/2119] lr: 4.0000e-03 eta: 8:34:20 time: 0.4056 data_time: 0.0196 memory: 5826 grad_norm: 3.7399 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9220 loss: 1.9220 2022/10/08 06:12:08 - mmengine - INFO - Epoch(train) [109][180/2119] lr: 4.0000e-03 eta: 8:34:13 time: 0.3138 data_time: 0.0196 memory: 5826 grad_norm: 3.7020 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8738 loss: 1.8738 2022/10/08 06:12:16 - mmengine - INFO - Epoch(train) [109][200/2119] lr: 4.0000e-03 eta: 8:34:06 time: 0.4160 data_time: 0.0204 memory: 5826 grad_norm: 3.8209 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1063 loss: 2.1063 2022/10/08 06:12:23 - mmengine - INFO - Epoch(train) [109][220/2119] lr: 4.0000e-03 eta: 8:33:59 time: 0.3280 data_time: 0.0195 memory: 5826 grad_norm: 3.8046 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2339 loss: 2.2339 2022/10/08 06:12:30 - mmengine - INFO - Epoch(train) [109][240/2119] lr: 4.0000e-03 eta: 8:33:52 time: 0.3413 data_time: 0.0211 memory: 5826 grad_norm: 3.7410 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 1.9915 loss: 1.9915 2022/10/08 06:12:37 - mmengine - INFO - Epoch(train) [109][260/2119] lr: 4.0000e-03 eta: 8:33:45 time: 0.3655 data_time: 0.0224 memory: 5826 grad_norm: 3.6905 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2227 loss: 2.2227 2022/10/08 06:12:45 - mmengine - INFO - Epoch(train) [109][280/2119] lr: 4.0000e-03 eta: 8:33:39 time: 0.3918 data_time: 0.0249 memory: 5826 grad_norm: 3.7866 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0743 loss: 2.0743 2022/10/08 06:12:53 - mmengine - INFO - Epoch(train) [109][300/2119] lr: 4.0000e-03 eta: 8:33:32 time: 0.3770 data_time: 0.0196 memory: 5826 grad_norm: 3.7664 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.1066 loss: 2.1066 2022/10/08 06:12:59 - mmengine - INFO - Epoch(train) [109][320/2119] lr: 4.0000e-03 eta: 8:33:25 time: 0.3398 data_time: 0.0202 memory: 5826 grad_norm: 3.7593 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9272 loss: 1.9272 2022/10/08 06:13:07 - mmengine - INFO - Epoch(train) [109][340/2119] lr: 4.0000e-03 eta: 8:33:18 time: 0.3993 data_time: 0.0264 memory: 5826 grad_norm: 3.7358 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.9406 loss: 1.9406 2022/10/08 06:13:15 - mmengine - INFO - Epoch(train) [109][360/2119] lr: 4.0000e-03 eta: 8:33:12 time: 0.3753 data_time: 0.0211 memory: 5826 grad_norm: 3.7352 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9643 loss: 1.9643 2022/10/08 06:13:23 - mmengine - INFO - Epoch(train) [109][380/2119] lr: 4.0000e-03 eta: 8:33:05 time: 0.3840 data_time: 0.0198 memory: 5826 grad_norm: 3.7779 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.2388 loss: 2.2388 2022/10/08 06:13:29 - mmengine - INFO - Epoch(train) [109][400/2119] lr: 4.0000e-03 eta: 8:32:58 time: 0.3100 data_time: 0.0175 memory: 5826 grad_norm: 3.7488 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0506 loss: 2.0506 2022/10/08 06:13:36 - mmengine - INFO - Epoch(train) [109][420/2119] lr: 4.0000e-03 eta: 8:32:51 time: 0.3772 data_time: 0.0227 memory: 5826 grad_norm: 3.7067 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.2107 loss: 2.2107 2022/10/08 06:13:43 - mmengine - INFO - Epoch(train) [109][440/2119] lr: 4.0000e-03 eta: 8:32:44 time: 0.3530 data_time: 0.0247 memory: 5826 grad_norm: 3.7728 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2289 loss: 2.2289 2022/10/08 06:13:51 - mmengine - INFO - Epoch(train) [109][460/2119] lr: 4.0000e-03 eta: 8:32:38 time: 0.3849 data_time: 0.0239 memory: 5826 grad_norm: 3.7299 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0201 loss: 2.0201 2022/10/08 06:13:58 - mmengine - INFO - Epoch(train) [109][480/2119] lr: 4.0000e-03 eta: 8:32:30 time: 0.3325 data_time: 0.0245 memory: 5826 grad_norm: 3.7575 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1665 loss: 2.1665 2022/10/08 06:14:05 - mmengine - INFO - Epoch(train) [109][500/2119] lr: 4.0000e-03 eta: 8:32:24 time: 0.3693 data_time: 0.0213 memory: 5826 grad_norm: 3.7943 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0139 loss: 2.0139 2022/10/08 06:14:12 - mmengine - INFO - Epoch(train) [109][520/2119] lr: 4.0000e-03 eta: 8:32:17 time: 0.3643 data_time: 0.0214 memory: 5826 grad_norm: 3.7267 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.0906 loss: 2.0906 2022/10/08 06:14:20 - mmengine - INFO - Epoch(train) [109][540/2119] lr: 4.0000e-03 eta: 8:32:10 time: 0.3584 data_time: 0.0201 memory: 5826 grad_norm: 3.7486 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1206 loss: 2.1206 2022/10/08 06:14:26 - mmengine - INFO - Epoch(train) [109][560/2119] lr: 4.0000e-03 eta: 8:32:03 time: 0.3301 data_time: 0.0203 memory: 5826 grad_norm: 3.7219 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2642 loss: 2.2642 2022/10/08 06:14:34 - mmengine - INFO - Epoch(train) [109][580/2119] lr: 4.0000e-03 eta: 8:31:56 time: 0.3988 data_time: 0.0238 memory: 5826 grad_norm: 3.7783 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1129 loss: 2.1129 2022/10/08 06:14:41 - mmengine - INFO - Epoch(train) [109][600/2119] lr: 4.0000e-03 eta: 8:31:50 time: 0.3615 data_time: 0.0200 memory: 5826 grad_norm: 3.8334 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0066 loss: 2.0066 2022/10/08 06:14:49 - mmengine - INFO - Epoch(train) [109][620/2119] lr: 4.0000e-03 eta: 8:31:43 time: 0.3555 data_time: 0.0268 memory: 5826 grad_norm: 3.7950 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9269 loss: 1.9269 2022/10/08 06:14:55 - mmengine - INFO - Epoch(train) [109][640/2119] lr: 4.0000e-03 eta: 8:31:36 time: 0.3332 data_time: 0.0227 memory: 5826 grad_norm: 3.7575 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9710 loss: 1.9710 2022/10/08 06:15:02 - mmengine - INFO - Epoch(train) [109][660/2119] lr: 4.0000e-03 eta: 8:31:29 time: 0.3590 data_time: 0.0228 memory: 5826 grad_norm: 3.7025 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0344 loss: 2.0344 2022/10/08 06:15:09 - mmengine - INFO - Epoch(train) [109][680/2119] lr: 4.0000e-03 eta: 8:31:22 time: 0.3232 data_time: 0.0208 memory: 5826 grad_norm: 3.7923 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.0326 loss: 2.0326 2022/10/08 06:15:16 - mmengine - INFO - Epoch(train) [109][700/2119] lr: 4.0000e-03 eta: 8:31:15 time: 0.3508 data_time: 0.0243 memory: 5826 grad_norm: 3.7089 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9132 loss: 1.9132 2022/10/08 06:15:23 - mmengine - INFO - Epoch(train) [109][720/2119] lr: 4.0000e-03 eta: 8:31:08 time: 0.3520 data_time: 0.0203 memory: 5826 grad_norm: 3.7571 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.2093 loss: 2.2093 2022/10/08 06:15:31 - mmengine - INFO - Epoch(train) [109][740/2119] lr: 4.0000e-03 eta: 8:31:01 time: 0.4139 data_time: 0.0223 memory: 5826 grad_norm: 3.7141 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8955 loss: 1.8955 2022/10/08 06:15:38 - mmengine - INFO - Epoch(train) [109][760/2119] lr: 4.0000e-03 eta: 8:30:54 time: 0.3270 data_time: 0.0211 memory: 5826 grad_norm: 3.7116 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1095 loss: 2.1095 2022/10/08 06:15:45 - mmengine - INFO - Epoch(train) [109][780/2119] lr: 4.0000e-03 eta: 8:30:47 time: 0.3553 data_time: 0.0230 memory: 5826 grad_norm: 3.7637 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0707 loss: 2.0707 2022/10/08 06:15:52 - mmengine - INFO - Epoch(train) [109][800/2119] lr: 4.0000e-03 eta: 8:30:41 time: 0.3745 data_time: 0.0289 memory: 5826 grad_norm: 3.7692 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1405 loss: 2.1405 2022/10/08 06:15:59 - mmengine - INFO - Epoch(train) [109][820/2119] lr: 4.0000e-03 eta: 8:30:33 time: 0.3147 data_time: 0.0209 memory: 5826 grad_norm: 3.7905 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0717 loss: 2.0717 2022/10/08 06:16:06 - mmengine - INFO - Epoch(train) [109][840/2119] lr: 4.0000e-03 eta: 8:30:26 time: 0.3473 data_time: 0.0226 memory: 5826 grad_norm: 3.7528 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.0243 loss: 2.0243 2022/10/08 06:16:13 - mmengine - INFO - Epoch(train) [109][860/2119] lr: 4.0000e-03 eta: 8:30:20 time: 0.3590 data_time: 0.0264 memory: 5826 grad_norm: 3.7449 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9440 loss: 1.9440 2022/10/08 06:16:21 - mmengine - INFO - Epoch(train) [109][880/2119] lr: 4.0000e-03 eta: 8:30:13 time: 0.4136 data_time: 0.0209 memory: 5826 grad_norm: 3.7648 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0679 loss: 2.0679 2022/10/08 06:16:28 - mmengine - INFO - Epoch(train) [109][900/2119] lr: 4.0000e-03 eta: 8:30:06 time: 0.3399 data_time: 0.0237 memory: 5826 grad_norm: 3.7519 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9955 loss: 1.9955 2022/10/08 06:16:35 - mmengine - INFO - Epoch(train) [109][920/2119] lr: 4.0000e-03 eta: 8:29:59 time: 0.3336 data_time: 0.0241 memory: 5826 grad_norm: 3.8006 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1387 loss: 2.1387 2022/10/08 06:16:42 - mmengine - INFO - Epoch(train) [109][940/2119] lr: 4.0000e-03 eta: 8:29:52 time: 0.3655 data_time: 0.0229 memory: 5826 grad_norm: 3.7563 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9843 loss: 1.9843 2022/10/08 06:16:48 - mmengine - INFO - Epoch(train) [109][960/2119] lr: 4.0000e-03 eta: 8:29:45 time: 0.3061 data_time: 0.0258 memory: 5826 grad_norm: 3.8509 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 2.0578 loss: 2.0578 2022/10/08 06:16:56 - mmengine - INFO - Epoch(train) [109][980/2119] lr: 4.0000e-03 eta: 8:29:38 time: 0.3787 data_time: 0.0242 memory: 5826 grad_norm: 3.8116 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.1294 loss: 2.1294 2022/10/08 06:17:03 - mmengine - INFO - Epoch(train) [109][1000/2119] lr: 4.0000e-03 eta: 8:29:31 time: 0.3520 data_time: 0.0222 memory: 5826 grad_norm: 3.7552 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1619 loss: 2.1619 2022/10/08 06:17:10 - mmengine - INFO - Epoch(train) [109][1020/2119] lr: 4.0000e-03 eta: 8:29:24 time: 0.3574 data_time: 0.0224 memory: 5826 grad_norm: 3.7502 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 1.9713 loss: 1.9713 2022/10/08 06:17:17 - mmengine - INFO - Epoch(train) [109][1040/2119] lr: 4.0000e-03 eta: 8:29:18 time: 0.3628 data_time: 0.0242 memory: 5826 grad_norm: 3.8098 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0815 loss: 2.0815 2022/10/08 06:17:24 - mmengine - INFO - Epoch(train) [109][1060/2119] lr: 4.0000e-03 eta: 8:29:11 time: 0.3353 data_time: 0.0201 memory: 5826 grad_norm: 3.8041 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4011 loss: 2.4011 2022/10/08 06:17:31 - mmengine - INFO - Epoch(train) [109][1080/2119] lr: 4.0000e-03 eta: 8:29:04 time: 0.3786 data_time: 0.0244 memory: 5826 grad_norm: 3.8141 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.2587 loss: 2.2587 2022/10/08 06:17:37 - mmengine - INFO - Epoch(train) [109][1100/2119] lr: 4.0000e-03 eta: 8:28:57 time: 0.2904 data_time: 0.0242 memory: 5826 grad_norm: 3.8013 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2491 loss: 2.2491 2022/10/08 06:17:45 - mmengine - INFO - Epoch(train) [109][1120/2119] lr: 4.0000e-03 eta: 8:28:50 time: 0.3904 data_time: 0.0193 memory: 5826 grad_norm: 3.7839 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1418 loss: 2.1418 2022/10/08 06:17:52 - mmengine - INFO - Epoch(train) [109][1140/2119] lr: 4.0000e-03 eta: 8:28:43 time: 0.3618 data_time: 0.0308 memory: 5826 grad_norm: 3.7877 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 1.9412 loss: 1.9412 2022/10/08 06:17:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 06:17:59 - mmengine - INFO - Epoch(train) [109][1160/2119] lr: 4.0000e-03 eta: 8:28:36 time: 0.3502 data_time: 0.0217 memory: 5826 grad_norm: 3.8525 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.2820 loss: 2.2820 2022/10/08 06:18:06 - mmengine - INFO - Epoch(train) [109][1180/2119] lr: 4.0000e-03 eta: 8:28:29 time: 0.3166 data_time: 0.0205 memory: 5826 grad_norm: 3.7706 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8752 loss: 1.8752 2022/10/08 06:18:13 - mmengine - INFO - Epoch(train) [109][1200/2119] lr: 4.0000e-03 eta: 8:28:22 time: 0.3583 data_time: 0.0191 memory: 5826 grad_norm: 3.8100 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2413 loss: 2.2413 2022/10/08 06:18:19 - mmengine - INFO - Epoch(train) [109][1220/2119] lr: 4.0000e-03 eta: 8:28:15 time: 0.3348 data_time: 0.0225 memory: 5826 grad_norm: 3.7101 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.9563 loss: 1.9563 2022/10/08 06:18:27 - mmengine - INFO - Epoch(train) [109][1240/2119] lr: 4.0000e-03 eta: 8:28:08 time: 0.3866 data_time: 0.0181 memory: 5826 grad_norm: 3.7269 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1569 loss: 2.1569 2022/10/08 06:18:34 - mmengine - INFO - Epoch(train) [109][1260/2119] lr: 4.0000e-03 eta: 8:28:01 time: 0.3399 data_time: 0.0171 memory: 5826 grad_norm: 3.7849 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0058 loss: 2.0058 2022/10/08 06:18:43 - mmengine - INFO - Epoch(train) [109][1280/2119] lr: 4.0000e-03 eta: 8:27:55 time: 0.4241 data_time: 0.0221 memory: 5826 grad_norm: 3.7426 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1362 loss: 2.1362 2022/10/08 06:18:49 - mmengine - INFO - Epoch(train) [109][1300/2119] lr: 4.0000e-03 eta: 8:27:48 time: 0.3161 data_time: 0.0201 memory: 5826 grad_norm: 3.7892 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1414 loss: 2.1414 2022/10/08 06:18:56 - mmengine - INFO - Epoch(train) [109][1320/2119] lr: 4.0000e-03 eta: 8:27:41 time: 0.3594 data_time: 0.0193 memory: 5826 grad_norm: 3.8502 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.2130 loss: 2.2130 2022/10/08 06:19:03 - mmengine - INFO - Epoch(train) [109][1340/2119] lr: 4.0000e-03 eta: 8:27:34 time: 0.3355 data_time: 0.0236 memory: 5826 grad_norm: 3.8440 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9501 loss: 1.9501 2022/10/08 06:19:10 - mmengine - INFO - Epoch(train) [109][1360/2119] lr: 4.0000e-03 eta: 8:27:27 time: 0.3687 data_time: 0.0217 memory: 5826 grad_norm: 3.8379 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.1515 loss: 2.1515 2022/10/08 06:19:17 - mmengine - INFO - Epoch(train) [109][1380/2119] lr: 4.0000e-03 eta: 8:27:20 time: 0.3314 data_time: 0.0207 memory: 5826 grad_norm: 3.8168 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0541 loss: 2.0541 2022/10/08 06:19:24 - mmengine - INFO - Epoch(train) [109][1400/2119] lr: 4.0000e-03 eta: 8:27:13 time: 0.3825 data_time: 0.0244 memory: 5826 grad_norm: 3.8327 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1926 loss: 2.1926 2022/10/08 06:19:31 - mmengine - INFO - Epoch(train) [109][1420/2119] lr: 4.0000e-03 eta: 8:27:06 time: 0.3218 data_time: 0.0215 memory: 5826 grad_norm: 3.7924 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0049 loss: 2.0049 2022/10/08 06:19:38 - mmengine - INFO - Epoch(train) [109][1440/2119] lr: 4.0000e-03 eta: 8:26:59 time: 0.3570 data_time: 0.0208 memory: 5826 grad_norm: 3.7989 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.1236 loss: 2.1236 2022/10/08 06:19:45 - mmengine - INFO - Epoch(train) [109][1460/2119] lr: 4.0000e-03 eta: 8:26:52 time: 0.3486 data_time: 0.0201 memory: 5826 grad_norm: 3.8229 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9716 loss: 1.9716 2022/10/08 06:19:52 - mmengine - INFO - Epoch(train) [109][1480/2119] lr: 4.0000e-03 eta: 8:26:46 time: 0.3725 data_time: 0.0168 memory: 5826 grad_norm: 3.8026 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.2291 loss: 2.2291 2022/10/08 06:19:59 - mmengine - INFO - Epoch(train) [109][1500/2119] lr: 4.0000e-03 eta: 8:26:38 time: 0.3102 data_time: 0.0245 memory: 5826 grad_norm: 3.7977 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.2584 loss: 2.2584 2022/10/08 06:20:06 - mmengine - INFO - Epoch(train) [109][1520/2119] lr: 4.0000e-03 eta: 8:26:32 time: 0.3861 data_time: 0.0209 memory: 5826 grad_norm: 3.7563 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0098 loss: 2.0098 2022/10/08 06:20:13 - mmengine - INFO - Epoch(train) [109][1540/2119] lr: 4.0000e-03 eta: 8:26:25 time: 0.3223 data_time: 0.0204 memory: 5826 grad_norm: 3.7335 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9220 loss: 1.9220 2022/10/08 06:20:19 - mmengine - INFO - Epoch(train) [109][1560/2119] lr: 4.0000e-03 eta: 8:26:18 time: 0.3301 data_time: 0.0255 memory: 5826 grad_norm: 3.7552 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9598 loss: 1.9598 2022/10/08 06:20:27 - mmengine - INFO - Epoch(train) [109][1580/2119] lr: 4.0000e-03 eta: 8:26:11 time: 0.3546 data_time: 0.0240 memory: 5826 grad_norm: 3.7668 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.0844 loss: 2.0844 2022/10/08 06:20:34 - mmengine - INFO - Epoch(train) [109][1600/2119] lr: 4.0000e-03 eta: 8:26:04 time: 0.3588 data_time: 0.0191 memory: 5826 grad_norm: 3.7705 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9893 loss: 1.9893 2022/10/08 06:20:40 - mmengine - INFO - Epoch(train) [109][1620/2119] lr: 4.0000e-03 eta: 8:25:57 time: 0.3203 data_time: 0.0204 memory: 5826 grad_norm: 3.8194 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2976 loss: 2.2976 2022/10/08 06:20:47 - mmengine - INFO - Epoch(train) [109][1640/2119] lr: 4.0000e-03 eta: 8:25:50 time: 0.3535 data_time: 0.0229 memory: 5826 grad_norm: 3.7757 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0519 loss: 2.0519 2022/10/08 06:20:54 - mmengine - INFO - Epoch(train) [109][1660/2119] lr: 4.0000e-03 eta: 8:25:43 time: 0.3560 data_time: 0.0226 memory: 5826 grad_norm: 3.7741 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9552 loss: 1.9552 2022/10/08 06:21:02 - mmengine - INFO - Epoch(train) [109][1680/2119] lr: 4.0000e-03 eta: 8:25:36 time: 0.3728 data_time: 0.0242 memory: 5826 grad_norm: 3.8035 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8359 loss: 1.8359 2022/10/08 06:21:08 - mmengine - INFO - Epoch(train) [109][1700/2119] lr: 4.0000e-03 eta: 8:25:29 time: 0.3173 data_time: 0.0182 memory: 5826 grad_norm: 3.8190 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0662 loss: 2.0662 2022/10/08 06:21:15 - mmengine - INFO - Epoch(train) [109][1720/2119] lr: 4.0000e-03 eta: 8:25:22 time: 0.3639 data_time: 0.0231 memory: 5826 grad_norm: 3.7833 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1778 loss: 2.1778 2022/10/08 06:21:23 - mmengine - INFO - Epoch(train) [109][1740/2119] lr: 4.0000e-03 eta: 8:25:16 time: 0.3909 data_time: 0.0236 memory: 5826 grad_norm: 3.8358 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.3001 loss: 2.3001 2022/10/08 06:21:30 - mmengine - INFO - Epoch(train) [109][1760/2119] lr: 4.0000e-03 eta: 8:25:08 time: 0.3257 data_time: 0.0212 memory: 5826 grad_norm: 3.8424 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.9816 loss: 1.9816 2022/10/08 06:21:36 - mmengine - INFO - Epoch(train) [109][1780/2119] lr: 4.0000e-03 eta: 8:25:01 time: 0.3278 data_time: 0.0201 memory: 5826 grad_norm: 3.8175 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1984 loss: 2.1984 2022/10/08 06:21:44 - mmengine - INFO - Epoch(train) [109][1800/2119] lr: 4.0000e-03 eta: 8:24:55 time: 0.3961 data_time: 0.0185 memory: 5826 grad_norm: 3.8786 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8815 loss: 1.8815 2022/10/08 06:21:51 - mmengine - INFO - Epoch(train) [109][1820/2119] lr: 4.0000e-03 eta: 8:24:48 time: 0.3232 data_time: 0.0203 memory: 5826 grad_norm: 3.7824 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1398 loss: 2.1398 2022/10/08 06:21:59 - mmengine - INFO - Epoch(train) [109][1840/2119] lr: 4.0000e-03 eta: 8:24:41 time: 0.3950 data_time: 0.0200 memory: 5826 grad_norm: 3.8085 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.0751 loss: 2.0751 2022/10/08 06:22:05 - mmengine - INFO - Epoch(train) [109][1860/2119] lr: 4.0000e-03 eta: 8:24:34 time: 0.3172 data_time: 0.0211 memory: 5826 grad_norm: 3.8000 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0911 loss: 2.0911 2022/10/08 06:22:13 - mmengine - INFO - Epoch(train) [109][1880/2119] lr: 4.0000e-03 eta: 8:24:27 time: 0.3807 data_time: 0.0226 memory: 5826 grad_norm: 3.8377 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1627 loss: 2.1627 2022/10/08 06:22:19 - mmengine - INFO - Epoch(train) [109][1900/2119] lr: 4.0000e-03 eta: 8:24:20 time: 0.3370 data_time: 0.0184 memory: 5826 grad_norm: 3.8646 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0075 loss: 2.0075 2022/10/08 06:22:26 - mmengine - INFO - Epoch(train) [109][1920/2119] lr: 4.0000e-03 eta: 8:24:13 time: 0.3425 data_time: 0.0233 memory: 5826 grad_norm: 3.7596 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.9495 loss: 1.9495 2022/10/08 06:22:33 - mmengine - INFO - Epoch(train) [109][1940/2119] lr: 4.0000e-03 eta: 8:24:06 time: 0.3439 data_time: 0.0215 memory: 5826 grad_norm: 3.8190 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.3523 loss: 2.3523 2022/10/08 06:22:41 - mmengine - INFO - Epoch(train) [109][1960/2119] lr: 4.0000e-03 eta: 8:23:59 time: 0.3772 data_time: 0.0250 memory: 5826 grad_norm: 3.8746 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2180 loss: 2.2180 2022/10/08 06:22:48 - mmengine - INFO - Epoch(train) [109][1980/2119] lr: 4.0000e-03 eta: 8:23:53 time: 0.3565 data_time: 0.0207 memory: 5826 grad_norm: 3.8739 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9940 loss: 1.9940 2022/10/08 06:22:55 - mmengine - INFO - Epoch(train) [109][2000/2119] lr: 4.0000e-03 eta: 8:23:46 time: 0.3418 data_time: 0.0191 memory: 5826 grad_norm: 3.8047 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1321 loss: 2.1321 2022/10/08 06:23:02 - mmengine - INFO - Epoch(train) [109][2020/2119] lr: 4.0000e-03 eta: 8:23:39 time: 0.3549 data_time: 0.0229 memory: 5826 grad_norm: 3.8515 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1357 loss: 2.1357 2022/10/08 06:23:09 - mmengine - INFO - Epoch(train) [109][2040/2119] lr: 4.0000e-03 eta: 8:23:32 time: 0.3653 data_time: 0.0220 memory: 5826 grad_norm: 3.8565 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2089 loss: 2.2089 2022/10/08 06:23:16 - mmengine - INFO - Epoch(train) [109][2060/2119] lr: 4.0000e-03 eta: 8:23:25 time: 0.3674 data_time: 0.0198 memory: 5826 grad_norm: 3.7960 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9492 loss: 1.9492 2022/10/08 06:23:23 - mmengine - INFO - Epoch(train) [109][2080/2119] lr: 4.0000e-03 eta: 8:23:18 time: 0.3520 data_time: 0.0313 memory: 5826 grad_norm: 3.7700 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.1732 loss: 2.1732 2022/10/08 06:23:31 - mmengine - INFO - Epoch(train) [109][2100/2119] lr: 4.0000e-03 eta: 8:23:11 time: 0.3768 data_time: 0.0226 memory: 5826 grad_norm: 3.7816 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9726 loss: 1.9726 2022/10/08 06:23:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 06:23:38 - mmengine - INFO - Epoch(train) [109][2119/2119] lr: 4.0000e-03 eta: 8:23:11 time: 0.3790 data_time: 0.0145 memory: 5826 grad_norm: 3.8406 top1_acc: 0.8000 top5_acc: 0.9000 loss_cls: 2.2109 loss: 2.2109 2022/10/08 06:23:48 - mmengine - INFO - Epoch(train) [110][20/2119] lr: 4.0000e-03 eta: 8:22:56 time: 0.4846 data_time: 0.1313 memory: 5826 grad_norm: 3.7616 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8023 loss: 1.8023 2022/10/08 06:23:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 06:23:55 - mmengine - INFO - Epoch(train) [110][40/2119] lr: 4.0000e-03 eta: 8:22:49 time: 0.3480 data_time: 0.0242 memory: 5826 grad_norm: 3.7517 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0495 loss: 2.0495 2022/10/08 06:24:03 - mmengine - INFO - Epoch(train) [110][60/2119] lr: 4.0000e-03 eta: 8:22:43 time: 0.3900 data_time: 0.0245 memory: 5826 grad_norm: 3.8478 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.2502 loss: 2.2502 2022/10/08 06:24:09 - mmengine - INFO - Epoch(train) [110][80/2119] lr: 4.0000e-03 eta: 8:22:36 time: 0.3169 data_time: 0.0185 memory: 5826 grad_norm: 3.7868 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1382 loss: 2.1382 2022/10/08 06:24:17 - mmengine - INFO - Epoch(train) [110][100/2119] lr: 4.0000e-03 eta: 8:22:29 time: 0.3636 data_time: 0.0209 memory: 5826 grad_norm: 3.8133 top1_acc: 0.3125 top5_acc: 0.3125 loss_cls: 2.2218 loss: 2.2218 2022/10/08 06:24:25 - mmengine - INFO - Epoch(train) [110][120/2119] lr: 4.0000e-03 eta: 8:22:23 time: 0.4342 data_time: 0.0135 memory: 5826 grad_norm: 3.8279 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.2014 loss: 2.2014 2022/10/08 06:24:32 - mmengine - INFO - Epoch(train) [110][140/2119] lr: 4.0000e-03 eta: 8:22:15 time: 0.3261 data_time: 0.0282 memory: 5826 grad_norm: 3.7841 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.1961 loss: 2.1961 2022/10/08 06:24:39 - mmengine - INFO - Epoch(train) [110][160/2119] lr: 4.0000e-03 eta: 8:22:09 time: 0.3759 data_time: 0.0192 memory: 5826 grad_norm: 3.7590 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0221 loss: 2.0221 2022/10/08 06:24:46 - mmengine - INFO - Epoch(train) [110][180/2119] lr: 4.0000e-03 eta: 8:22:02 time: 0.3445 data_time: 0.0201 memory: 5826 grad_norm: 3.7436 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1043 loss: 2.1043 2022/10/08 06:24:53 - mmengine - INFO - Epoch(train) [110][200/2119] lr: 4.0000e-03 eta: 8:21:55 time: 0.3361 data_time: 0.0246 memory: 5826 grad_norm: 3.8283 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0415 loss: 2.0415 2022/10/08 06:25:00 - mmengine - INFO - Epoch(train) [110][220/2119] lr: 4.0000e-03 eta: 8:21:48 time: 0.3306 data_time: 0.0267 memory: 5826 grad_norm: 3.8597 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1146 loss: 2.1146 2022/10/08 06:25:08 - mmengine - INFO - Epoch(train) [110][240/2119] lr: 4.0000e-03 eta: 8:21:41 time: 0.4021 data_time: 0.0270 memory: 5826 grad_norm: 3.7990 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9897 loss: 1.9897 2022/10/08 06:25:14 - mmengine - INFO - Epoch(train) [110][260/2119] lr: 4.0000e-03 eta: 8:21:34 time: 0.3158 data_time: 0.0235 memory: 5826 grad_norm: 3.8278 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2959 loss: 2.2959 2022/10/08 06:25:22 - mmengine - INFO - Epoch(train) [110][280/2119] lr: 4.0000e-03 eta: 8:21:27 time: 0.3928 data_time: 0.0264 memory: 5826 grad_norm: 3.7571 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9866 loss: 1.9866 2022/10/08 06:25:29 - mmengine - INFO - Epoch(train) [110][300/2119] lr: 4.0000e-03 eta: 8:21:20 time: 0.3657 data_time: 0.0201 memory: 5826 grad_norm: 3.8629 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1281 loss: 2.1281 2022/10/08 06:25:36 - mmengine - INFO - Epoch(train) [110][320/2119] lr: 4.0000e-03 eta: 8:21:13 time: 0.3294 data_time: 0.0188 memory: 5826 grad_norm: 3.8776 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9535 loss: 1.9535 2022/10/08 06:25:43 - mmengine - INFO - Epoch(train) [110][340/2119] lr: 4.0000e-03 eta: 8:21:07 time: 0.3673 data_time: 0.0266 memory: 5826 grad_norm: 3.7898 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1430 loss: 2.1430 2022/10/08 06:25:51 - mmengine - INFO - Epoch(train) [110][360/2119] lr: 4.0000e-03 eta: 8:21:00 time: 0.3811 data_time: 0.0187 memory: 5826 grad_norm: 3.8606 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.1257 loss: 2.1257 2022/10/08 06:25:57 - mmengine - INFO - Epoch(train) [110][380/2119] lr: 4.0000e-03 eta: 8:20:53 time: 0.3096 data_time: 0.0206 memory: 5826 grad_norm: 3.7736 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.1869 loss: 2.1869 2022/10/08 06:26:05 - mmengine - INFO - Epoch(train) [110][400/2119] lr: 4.0000e-03 eta: 8:20:46 time: 0.3791 data_time: 0.0227 memory: 5826 grad_norm: 3.7946 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9127 loss: 1.9127 2022/10/08 06:26:10 - mmengine - INFO - Epoch(train) [110][420/2119] lr: 4.0000e-03 eta: 8:20:38 time: 0.2817 data_time: 0.0253 memory: 5826 grad_norm: 3.8371 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1938 loss: 2.1938 2022/10/08 06:26:18 - mmengine - INFO - Epoch(train) [110][440/2119] lr: 4.0000e-03 eta: 8:20:32 time: 0.3798 data_time: 0.0229 memory: 5826 grad_norm: 3.7692 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0842 loss: 2.0842 2022/10/08 06:26:25 - mmengine - INFO - Epoch(train) [110][460/2119] lr: 4.0000e-03 eta: 8:20:25 time: 0.3525 data_time: 0.0276 memory: 5826 grad_norm: 3.7264 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0187 loss: 2.0187 2022/10/08 06:26:32 - mmengine - INFO - Epoch(train) [110][480/2119] lr: 4.0000e-03 eta: 8:20:18 time: 0.3666 data_time: 0.0204 memory: 5826 grad_norm: 3.7996 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0883 loss: 2.0883 2022/10/08 06:26:39 - mmengine - INFO - Epoch(train) [110][500/2119] lr: 4.0000e-03 eta: 8:20:11 time: 0.3359 data_time: 0.0221 memory: 5826 grad_norm: 3.7149 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.0551 loss: 2.0551 2022/10/08 06:26:47 - mmengine - INFO - Epoch(train) [110][520/2119] lr: 4.0000e-03 eta: 8:20:05 time: 0.4126 data_time: 0.0236 memory: 5826 grad_norm: 3.8603 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9786 loss: 1.9786 2022/10/08 06:26:54 - mmengine - INFO - Epoch(train) [110][540/2119] lr: 4.0000e-03 eta: 8:19:58 time: 0.3577 data_time: 0.0167 memory: 5826 grad_norm: 3.7803 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.7543 loss: 1.7543 2022/10/08 06:27:02 - mmengine - INFO - Epoch(train) [110][560/2119] lr: 4.0000e-03 eta: 8:19:51 time: 0.3933 data_time: 0.0274 memory: 5826 grad_norm: 3.8017 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0826 loss: 2.0826 2022/10/08 06:27:08 - mmengine - INFO - Epoch(train) [110][580/2119] lr: 4.0000e-03 eta: 8:19:44 time: 0.3100 data_time: 0.0207 memory: 5826 grad_norm: 3.8024 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.1649 loss: 2.1649 2022/10/08 06:27:16 - mmengine - INFO - Epoch(train) [110][600/2119] lr: 4.0000e-03 eta: 8:19:37 time: 0.3625 data_time: 0.0182 memory: 5826 grad_norm: 3.7457 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.0823 loss: 2.0823 2022/10/08 06:27:23 - mmengine - INFO - Epoch(train) [110][620/2119] lr: 4.0000e-03 eta: 8:19:30 time: 0.3629 data_time: 0.0216 memory: 5826 grad_norm: 3.7638 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8661 loss: 1.8661 2022/10/08 06:27:30 - mmengine - INFO - Epoch(train) [110][640/2119] lr: 4.0000e-03 eta: 8:19:23 time: 0.3344 data_time: 0.0242 memory: 5826 grad_norm: 3.7919 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.0326 loss: 2.0326 2022/10/08 06:27:37 - mmengine - INFO - Epoch(train) [110][660/2119] lr: 4.0000e-03 eta: 8:19:16 time: 0.3509 data_time: 0.0215 memory: 5826 grad_norm: 3.8110 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9382 loss: 1.9382 2022/10/08 06:27:44 - mmengine - INFO - Epoch(train) [110][680/2119] lr: 4.0000e-03 eta: 8:19:09 time: 0.3756 data_time: 0.0224 memory: 5826 grad_norm: 3.8555 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1951 loss: 2.1951 2022/10/08 06:27:52 - mmengine - INFO - Epoch(train) [110][700/2119] lr: 4.0000e-03 eta: 8:19:03 time: 0.3651 data_time: 0.0190 memory: 5826 grad_norm: 3.8328 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0697 loss: 2.0697 2022/10/08 06:27:59 - mmengine - INFO - Epoch(train) [110][720/2119] lr: 4.0000e-03 eta: 8:18:56 time: 0.3707 data_time: 0.0197 memory: 5826 grad_norm: 3.8358 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1585 loss: 2.1585 2022/10/08 06:28:06 - mmengine - INFO - Epoch(train) [110][740/2119] lr: 4.0000e-03 eta: 8:18:49 time: 0.3493 data_time: 0.0200 memory: 5826 grad_norm: 3.8634 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.8954 loss: 1.8954 2022/10/08 06:28:14 - mmengine - INFO - Epoch(train) [110][760/2119] lr: 4.0000e-03 eta: 8:18:42 time: 0.3832 data_time: 0.0194 memory: 5826 grad_norm: 3.8185 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1052 loss: 2.1052 2022/10/08 06:28:20 - mmengine - INFO - Epoch(train) [110][780/2119] lr: 4.0000e-03 eta: 8:18:35 time: 0.3443 data_time: 0.0217 memory: 5826 grad_norm: 3.8892 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9950 loss: 1.9950 2022/10/08 06:28:29 - mmengine - INFO - Epoch(train) [110][800/2119] lr: 4.0000e-03 eta: 8:18:29 time: 0.4099 data_time: 0.0257 memory: 5826 grad_norm: 3.9101 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0817 loss: 2.0817 2022/10/08 06:28:35 - mmengine - INFO - Epoch(train) [110][820/2119] lr: 4.0000e-03 eta: 8:18:22 time: 0.3209 data_time: 0.0215 memory: 5826 grad_norm: 3.8113 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9408 loss: 1.9408 2022/10/08 06:28:43 - mmengine - INFO - Epoch(train) [110][840/2119] lr: 4.0000e-03 eta: 8:18:15 time: 0.4039 data_time: 0.0261 memory: 5826 grad_norm: 3.9087 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0274 loss: 2.0274 2022/10/08 06:28:50 - mmengine - INFO - Epoch(train) [110][860/2119] lr: 4.0000e-03 eta: 8:18:08 time: 0.3254 data_time: 0.0218 memory: 5826 grad_norm: 3.8858 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9960 loss: 1.9960 2022/10/08 06:28:57 - mmengine - INFO - Epoch(train) [110][880/2119] lr: 4.0000e-03 eta: 8:18:01 time: 0.3798 data_time: 0.0290 memory: 5826 grad_norm: 3.8344 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2956 loss: 2.2956 2022/10/08 06:29:04 - mmengine - INFO - Epoch(train) [110][900/2119] lr: 4.0000e-03 eta: 8:17:54 time: 0.3487 data_time: 0.0220 memory: 5826 grad_norm: 3.8588 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0939 loss: 2.0939 2022/10/08 06:29:11 - mmengine - INFO - Epoch(train) [110][920/2119] lr: 4.0000e-03 eta: 8:17:47 time: 0.3339 data_time: 0.0231 memory: 5826 grad_norm: 3.8199 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 1.9651 loss: 1.9651 2022/10/08 06:29:17 - mmengine - INFO - Epoch(train) [110][940/2119] lr: 4.0000e-03 eta: 8:17:40 time: 0.3245 data_time: 0.0201 memory: 5826 grad_norm: 3.8178 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1871 loss: 2.1871 2022/10/08 06:29:25 - mmengine - INFO - Epoch(train) [110][960/2119] lr: 4.0000e-03 eta: 8:17:34 time: 0.3885 data_time: 0.0251 memory: 5826 grad_norm: 3.8630 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1196 loss: 2.1196 2022/10/08 06:29:32 - mmengine - INFO - Epoch(train) [110][980/2119] lr: 4.0000e-03 eta: 8:17:27 time: 0.3349 data_time: 0.0233 memory: 5826 grad_norm: 3.9114 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.1125 loss: 2.1125 2022/10/08 06:29:39 - mmengine - INFO - Epoch(train) [110][1000/2119] lr: 4.0000e-03 eta: 8:17:20 time: 0.3475 data_time: 0.0255 memory: 5826 grad_norm: 3.8127 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1797 loss: 2.1797 2022/10/08 06:29:46 - mmengine - INFO - Epoch(train) [110][1020/2119] lr: 4.0000e-03 eta: 8:17:13 time: 0.3546 data_time: 0.0249 memory: 5826 grad_norm: 3.7719 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1305 loss: 2.1305 2022/10/08 06:29:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 06:29:54 - mmengine - INFO - Epoch(train) [110][1040/2119] lr: 4.0000e-03 eta: 8:17:06 time: 0.3739 data_time: 0.0213 memory: 5826 grad_norm: 3.9352 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1372 loss: 2.1372 2022/10/08 06:30:00 - mmengine - INFO - Epoch(train) [110][1060/2119] lr: 4.0000e-03 eta: 8:16:59 time: 0.3206 data_time: 0.0230 memory: 5826 grad_norm: 3.8238 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8842 loss: 1.8842 2022/10/08 06:30:07 - mmengine - INFO - Epoch(train) [110][1080/2119] lr: 4.0000e-03 eta: 8:16:52 time: 0.3770 data_time: 0.0218 memory: 5826 grad_norm: 3.8561 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.8935 loss: 1.8935 2022/10/08 06:30:14 - mmengine - INFO - Epoch(train) [110][1100/2119] lr: 4.0000e-03 eta: 8:16:45 time: 0.3224 data_time: 0.0206 memory: 5826 grad_norm: 3.8317 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9146 loss: 1.9146 2022/10/08 06:30:23 - mmengine - INFO - Epoch(train) [110][1120/2119] lr: 4.0000e-03 eta: 8:16:39 time: 0.4555 data_time: 0.0258 memory: 5826 grad_norm: 3.8842 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.2175 loss: 2.2175 2022/10/08 06:30:29 - mmengine - INFO - Epoch(train) [110][1140/2119] lr: 4.0000e-03 eta: 8:16:31 time: 0.2953 data_time: 0.0225 memory: 5826 grad_norm: 3.8573 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.1714 loss: 2.1714 2022/10/08 06:30:38 - mmengine - INFO - Epoch(train) [110][1160/2119] lr: 4.0000e-03 eta: 8:16:25 time: 0.4334 data_time: 0.0234 memory: 5826 grad_norm: 3.7700 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.8932 loss: 1.8932 2022/10/08 06:30:44 - mmengine - INFO - Epoch(train) [110][1180/2119] lr: 4.0000e-03 eta: 8:16:18 time: 0.3124 data_time: 0.0168 memory: 5826 grad_norm: 3.8025 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9731 loss: 1.9731 2022/10/08 06:30:51 - mmengine - INFO - Epoch(train) [110][1200/2119] lr: 4.0000e-03 eta: 8:16:11 time: 0.3774 data_time: 0.0226 memory: 5826 grad_norm: 3.7484 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.0386 loss: 2.0386 2022/10/08 06:30:57 - mmengine - INFO - Epoch(train) [110][1220/2119] lr: 4.0000e-03 eta: 8:16:04 time: 0.2907 data_time: 0.0230 memory: 5826 grad_norm: 3.8293 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0724 loss: 2.0724 2022/10/08 06:31:05 - mmengine - INFO - Epoch(train) [110][1240/2119] lr: 4.0000e-03 eta: 8:15:57 time: 0.3903 data_time: 0.0244 memory: 5826 grad_norm: 3.8248 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0511 loss: 2.0511 2022/10/08 06:31:11 - mmengine - INFO - Epoch(train) [110][1260/2119] lr: 4.0000e-03 eta: 8:15:50 time: 0.2979 data_time: 0.0211 memory: 5826 grad_norm: 3.8522 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.2079 loss: 2.2079 2022/10/08 06:31:18 - mmengine - INFO - Epoch(train) [110][1280/2119] lr: 4.0000e-03 eta: 8:15:43 time: 0.3536 data_time: 0.0221 memory: 5826 grad_norm: 3.8132 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.1706 loss: 2.1706 2022/10/08 06:31:26 - mmengine - INFO - Epoch(train) [110][1300/2119] lr: 4.0000e-03 eta: 8:15:36 time: 0.3779 data_time: 0.0226 memory: 5826 grad_norm: 3.8493 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.1853 loss: 2.1853 2022/10/08 06:31:33 - mmengine - INFO - Epoch(train) [110][1320/2119] lr: 4.0000e-03 eta: 8:15:29 time: 0.3613 data_time: 0.0211 memory: 5826 grad_norm: 3.8445 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.2050 loss: 2.2050 2022/10/08 06:31:40 - mmengine - INFO - Epoch(train) [110][1340/2119] lr: 4.0000e-03 eta: 8:15:23 time: 0.3637 data_time: 0.0227 memory: 5826 grad_norm: 3.8259 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.0541 loss: 2.0541 2022/10/08 06:31:47 - mmengine - INFO - Epoch(train) [110][1360/2119] lr: 4.0000e-03 eta: 8:15:16 time: 0.3491 data_time: 0.0234 memory: 5826 grad_norm: 3.8044 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9646 loss: 1.9646 2022/10/08 06:31:54 - mmengine - INFO - Epoch(train) [110][1380/2119] lr: 4.0000e-03 eta: 8:15:09 time: 0.3420 data_time: 0.0247 memory: 5826 grad_norm: 3.8118 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9066 loss: 1.9066 2022/10/08 06:32:02 - mmengine - INFO - Epoch(train) [110][1400/2119] lr: 4.0000e-03 eta: 8:15:02 time: 0.3930 data_time: 0.0186 memory: 5826 grad_norm: 3.8687 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0739 loss: 2.0739 2022/10/08 06:32:09 - mmengine - INFO - Epoch(train) [110][1420/2119] lr: 4.0000e-03 eta: 8:14:55 time: 0.3430 data_time: 0.0236 memory: 5826 grad_norm: 3.8324 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.2168 loss: 2.2168 2022/10/08 06:32:17 - mmengine - INFO - Epoch(train) [110][1440/2119] lr: 4.0000e-03 eta: 8:14:48 time: 0.3983 data_time: 0.0236 memory: 5826 grad_norm: 3.8634 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9374 loss: 1.9374 2022/10/08 06:32:23 - mmengine - INFO - Epoch(train) [110][1460/2119] lr: 4.0000e-03 eta: 8:14:41 time: 0.3139 data_time: 0.0200 memory: 5826 grad_norm: 3.8440 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1719 loss: 2.1719 2022/10/08 06:32:31 - mmengine - INFO - Epoch(train) [110][1480/2119] lr: 4.0000e-03 eta: 8:14:35 time: 0.3768 data_time: 0.0251 memory: 5826 grad_norm: 3.7517 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.1354 loss: 2.1354 2022/10/08 06:32:36 - mmengine - INFO - Epoch(train) [110][1500/2119] lr: 4.0000e-03 eta: 8:14:27 time: 0.2942 data_time: 0.0246 memory: 5826 grad_norm: 3.8227 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1393 loss: 2.1393 2022/10/08 06:32:44 - mmengine - INFO - Epoch(train) [110][1520/2119] lr: 4.0000e-03 eta: 8:14:20 time: 0.3736 data_time: 0.0188 memory: 5826 grad_norm: 3.8418 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9595 loss: 1.9595 2022/10/08 06:32:51 - mmengine - INFO - Epoch(train) [110][1540/2119] lr: 4.0000e-03 eta: 8:14:14 time: 0.3632 data_time: 0.0209 memory: 5826 grad_norm: 3.8264 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0215 loss: 2.0215 2022/10/08 06:32:58 - mmengine - INFO - Epoch(train) [110][1560/2119] lr: 4.0000e-03 eta: 8:14:07 time: 0.3623 data_time: 0.0250 memory: 5826 grad_norm: 3.8519 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1972 loss: 2.1972 2022/10/08 06:33:05 - mmengine - INFO - Epoch(train) [110][1580/2119] lr: 4.0000e-03 eta: 8:14:00 time: 0.3403 data_time: 0.0153 memory: 5826 grad_norm: 3.8509 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9864 loss: 1.9864 2022/10/08 06:33:13 - mmengine - INFO - Epoch(train) [110][1600/2119] lr: 4.0000e-03 eta: 8:13:53 time: 0.3745 data_time: 0.0255 memory: 5826 grad_norm: 3.8951 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.1655 loss: 2.1655 2022/10/08 06:33:19 - mmengine - INFO - Epoch(train) [110][1620/2119] lr: 4.0000e-03 eta: 8:13:46 time: 0.3297 data_time: 0.0268 memory: 5826 grad_norm: 3.8673 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0543 loss: 2.0543 2022/10/08 06:33:27 - mmengine - INFO - Epoch(train) [110][1640/2119] lr: 4.0000e-03 eta: 8:13:39 time: 0.3658 data_time: 0.0252 memory: 5826 grad_norm: 3.9254 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0334 loss: 2.0334 2022/10/08 06:33:34 - mmengine - INFO - Epoch(train) [110][1660/2119] lr: 4.0000e-03 eta: 8:13:32 time: 0.3820 data_time: 0.0216 memory: 5826 grad_norm: 3.9266 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0084 loss: 2.0084 2022/10/08 06:33:42 - mmengine - INFO - Epoch(train) [110][1680/2119] lr: 4.0000e-03 eta: 8:13:26 time: 0.3689 data_time: 0.0260 memory: 5826 grad_norm: 3.8799 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0779 loss: 2.0779 2022/10/08 06:33:48 - mmengine - INFO - Epoch(train) [110][1700/2119] lr: 4.0000e-03 eta: 8:13:19 time: 0.3360 data_time: 0.0179 memory: 5826 grad_norm: 3.8637 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9899 loss: 1.9899 2022/10/08 06:33:56 - mmengine - INFO - Epoch(train) [110][1720/2119] lr: 4.0000e-03 eta: 8:13:12 time: 0.3842 data_time: 0.0275 memory: 5826 grad_norm: 3.7992 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0472 loss: 2.0472 2022/10/08 06:34:03 - mmengine - INFO - Epoch(train) [110][1740/2119] lr: 4.0000e-03 eta: 8:13:05 time: 0.3376 data_time: 0.0207 memory: 5826 grad_norm: 3.8219 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9424 loss: 1.9424 2022/10/08 06:34:11 - mmengine - INFO - Epoch(train) [110][1760/2119] lr: 4.0000e-03 eta: 8:12:58 time: 0.3853 data_time: 0.0234 memory: 5826 grad_norm: 3.8628 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7291 loss: 1.7291 2022/10/08 06:34:17 - mmengine - INFO - Epoch(train) [110][1780/2119] lr: 4.0000e-03 eta: 8:12:51 time: 0.3256 data_time: 0.0238 memory: 5826 grad_norm: 3.9191 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.2053 loss: 2.2053 2022/10/08 06:34:24 - mmengine - INFO - Epoch(train) [110][1800/2119] lr: 4.0000e-03 eta: 8:12:44 time: 0.3424 data_time: 0.0241 memory: 5826 grad_norm: 3.8174 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.0461 loss: 2.0461 2022/10/08 06:34:31 - mmengine - INFO - Epoch(train) [110][1820/2119] lr: 4.0000e-03 eta: 8:12:37 time: 0.3524 data_time: 0.0265 memory: 5826 grad_norm: 3.8834 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0769 loss: 2.0769 2022/10/08 06:34:38 - mmengine - INFO - Epoch(train) [110][1840/2119] lr: 4.0000e-03 eta: 8:12:30 time: 0.3612 data_time: 0.0275 memory: 5826 grad_norm: 3.8397 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9849 loss: 1.9849 2022/10/08 06:34:45 - mmengine - INFO - Epoch(train) [110][1860/2119] lr: 4.0000e-03 eta: 8:12:23 time: 0.3495 data_time: 0.0212 memory: 5826 grad_norm: 3.9292 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.3083 loss: 2.3083 2022/10/08 06:34:54 - mmengine - INFO - Epoch(train) [110][1880/2119] lr: 4.0000e-03 eta: 8:12:17 time: 0.4219 data_time: 0.0257 memory: 5826 grad_norm: 3.8592 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9321 loss: 1.9321 2022/10/08 06:35:00 - mmengine - INFO - Epoch(train) [110][1900/2119] lr: 4.0000e-03 eta: 8:12:10 time: 0.3186 data_time: 0.0216 memory: 5826 grad_norm: 3.8280 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0923 loss: 2.0923 2022/10/08 06:35:08 - mmengine - INFO - Epoch(train) [110][1920/2119] lr: 4.0000e-03 eta: 8:12:03 time: 0.3838 data_time: 0.0223 memory: 5826 grad_norm: 3.8856 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.0019 loss: 2.0019 2022/10/08 06:35:15 - mmengine - INFO - Epoch(train) [110][1940/2119] lr: 4.0000e-03 eta: 8:11:56 time: 0.3709 data_time: 0.0206 memory: 5826 grad_norm: 3.8624 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2050 loss: 2.2050 2022/10/08 06:35:22 - mmengine - INFO - Epoch(train) [110][1960/2119] lr: 4.0000e-03 eta: 8:11:49 time: 0.3549 data_time: 0.0267 memory: 5826 grad_norm: 3.8372 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1388 loss: 2.1388 2022/10/08 06:35:30 - mmengine - INFO - Epoch(train) [110][1980/2119] lr: 4.0000e-03 eta: 8:11:43 time: 0.3635 data_time: 0.0211 memory: 5826 grad_norm: 3.8811 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2299 loss: 2.2299 2022/10/08 06:35:37 - mmengine - INFO - Epoch(train) [110][2000/2119] lr: 4.0000e-03 eta: 8:11:36 time: 0.3884 data_time: 0.0225 memory: 5826 grad_norm: 3.8467 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0853 loss: 2.0853 2022/10/08 06:35:44 - mmengine - INFO - Epoch(train) [110][2020/2119] lr: 4.0000e-03 eta: 8:11:29 time: 0.3334 data_time: 0.0226 memory: 5826 grad_norm: 3.7612 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9086 loss: 1.9086 2022/10/08 06:35:48 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 06:35:51 - mmengine - INFO - Epoch(train) [110][2040/2119] lr: 4.0000e-03 eta: 8:11:22 time: 0.3683 data_time: 0.0189 memory: 5826 grad_norm: 3.8574 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.3094 loss: 2.3094 2022/10/08 06:35:59 - mmengine - INFO - Epoch(train) [110][2060/2119] lr: 4.0000e-03 eta: 8:11:15 time: 0.3639 data_time: 0.0236 memory: 5826 grad_norm: 3.8658 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.1248 loss: 2.1248 2022/10/08 06:36:06 - mmengine - INFO - Epoch(train) [110][2080/2119] lr: 4.0000e-03 eta: 8:11:08 time: 0.3456 data_time: 0.0254 memory: 5826 grad_norm: 3.9182 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1140 loss: 2.1140 2022/10/08 06:36:13 - mmengine - INFO - Epoch(train) [110][2100/2119] lr: 4.0000e-03 eta: 8:11:01 time: 0.3541 data_time: 0.0221 memory: 5826 grad_norm: 3.8702 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3530 loss: 2.3530 2022/10/08 06:36:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 06:36:20 - mmengine - INFO - Epoch(train) [110][2119/2119] lr: 4.0000e-03 eta: 8:11:01 time: 0.3644 data_time: 0.0194 memory: 5826 grad_norm: 3.9013 top1_acc: 0.5000 top5_acc: 0.7000 loss_cls: 2.0392 loss: 2.0392 2022/10/08 06:36:28 - mmengine - INFO - Epoch(val) [110][20/137] eta: 0:00:49 time: 0.4273 data_time: 0.3578 memory: 1241 2022/10/08 06:36:34 - mmengine - INFO - Epoch(val) [110][40/137] eta: 0:00:29 time: 0.3054 data_time: 0.2385 memory: 1241 2022/10/08 06:36:42 - mmengine - INFO - Epoch(val) [110][60/137] eta: 0:00:29 time: 0.3822 data_time: 0.3150 memory: 1241 2022/10/08 06:36:47 - mmengine - INFO - Epoch(val) [110][80/137] eta: 0:00:15 time: 0.2664 data_time: 0.1965 memory: 1241 2022/10/08 06:36:54 - mmengine - INFO - Epoch(val) [110][100/137] eta: 0:00:12 time: 0.3473 data_time: 0.2768 memory: 1241 2022/10/08 06:37:00 - mmengine - INFO - Epoch(val) [110][120/137] eta: 0:00:04 time: 0.2739 data_time: 0.2079 memory: 1241 2022/10/08 06:37:12 - mmengine - INFO - Epoch(val) [110][137/137] acc/top1: 0.5343 acc/top5: 0.7613 acc/mean1: 0.5342 2022/10/08 06:37:12 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb/best_acc/top1_epoch_105.pth is removed 2022/10/08 06:37:14 - mmengine - INFO - The best checkpoint with 0.5343 acc/top1 at 110 epoch is saved to best_acc/top1_epoch_110.pth. 2022/10/08 06:37:23 - mmengine - INFO - Epoch(train) [111][20/2119] lr: 4.0000e-03 eta: 8:10:46 time: 0.4336 data_time: 0.1785 memory: 5826 grad_norm: 3.8570 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9003 loss: 1.9003 2022/10/08 06:37:30 - mmengine - INFO - Epoch(train) [111][40/2119] lr: 4.0000e-03 eta: 8:10:39 time: 0.3436 data_time: 0.0244 memory: 5826 grad_norm: 3.8368 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1861 loss: 2.1861 2022/10/08 06:37:36 - mmengine - INFO - Epoch(train) [111][60/2119] lr: 4.0000e-03 eta: 8:10:32 time: 0.3440 data_time: 0.0272 memory: 5826 grad_norm: 3.8879 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0820 loss: 2.0820 2022/10/08 06:37:44 - mmengine - INFO - Epoch(train) [111][80/2119] lr: 4.0000e-03 eta: 8:10:25 time: 0.3623 data_time: 0.0165 memory: 5826 grad_norm: 3.9394 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.1542 loss: 2.1542 2022/10/08 06:37:51 - mmengine - INFO - Epoch(train) [111][100/2119] lr: 4.0000e-03 eta: 8:10:19 time: 0.3823 data_time: 0.0189 memory: 5826 grad_norm: 3.8454 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.9215 loss: 1.9215 2022/10/08 06:37:58 - mmengine - INFO - Epoch(train) [111][120/2119] lr: 4.0000e-03 eta: 8:10:11 time: 0.3122 data_time: 0.0179 memory: 5826 grad_norm: 3.8980 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8995 loss: 1.8995 2022/10/08 06:38:05 - mmengine - INFO - Epoch(train) [111][140/2119] lr: 4.0000e-03 eta: 8:10:05 time: 0.3953 data_time: 0.0245 memory: 5826 grad_norm: 3.8836 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0724 loss: 2.0724 2022/10/08 06:38:13 - mmengine - INFO - Epoch(train) [111][160/2119] lr: 4.0000e-03 eta: 8:09:58 time: 0.3562 data_time: 0.0224 memory: 5826 grad_norm: 3.9844 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0669 loss: 2.0669 2022/10/08 06:38:19 - mmengine - INFO - Epoch(train) [111][180/2119] lr: 4.0000e-03 eta: 8:09:51 time: 0.3397 data_time: 0.0190 memory: 5826 grad_norm: 3.8712 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1476 loss: 2.1476 2022/10/08 06:38:26 - mmengine - INFO - Epoch(train) [111][200/2119] lr: 4.0000e-03 eta: 8:09:44 time: 0.3475 data_time: 0.0226 memory: 5826 grad_norm: 3.8581 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0400 loss: 2.0400 2022/10/08 06:38:35 - mmengine - INFO - Epoch(train) [111][220/2119] lr: 4.0000e-03 eta: 8:09:38 time: 0.4226 data_time: 0.0256 memory: 5826 grad_norm: 3.8826 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.0231 loss: 2.0231 2022/10/08 06:38:40 - mmengine - INFO - Epoch(train) [111][240/2119] lr: 4.0000e-03 eta: 8:09:30 time: 0.2809 data_time: 0.0226 memory: 5826 grad_norm: 3.8596 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9910 loss: 1.9910 2022/10/08 06:38:48 - mmengine - INFO - Epoch(train) [111][260/2119] lr: 4.0000e-03 eta: 8:09:23 time: 0.3678 data_time: 0.0220 memory: 5826 grad_norm: 3.8468 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8930 loss: 1.8930 2022/10/08 06:38:55 - mmengine - INFO - Epoch(train) [111][280/2119] lr: 4.0000e-03 eta: 8:09:16 time: 0.3607 data_time: 0.0231 memory: 5826 grad_norm: 3.8568 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0579 loss: 2.0579 2022/10/08 06:39:02 - mmengine - INFO - Epoch(train) [111][300/2119] lr: 4.0000e-03 eta: 8:09:10 time: 0.3637 data_time: 0.0202 memory: 5826 grad_norm: 3.8889 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1426 loss: 2.1426 2022/10/08 06:39:09 - mmengine - INFO - Epoch(train) [111][320/2119] lr: 4.0000e-03 eta: 8:09:03 time: 0.3380 data_time: 0.0266 memory: 5826 grad_norm: 3.8799 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8929 loss: 1.8929 2022/10/08 06:39:16 - mmengine - INFO - Epoch(train) [111][340/2119] lr: 4.0000e-03 eta: 8:08:56 time: 0.3339 data_time: 0.0228 memory: 5826 grad_norm: 3.8976 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0871 loss: 2.0871 2022/10/08 06:39:24 - mmengine - INFO - Epoch(train) [111][360/2119] lr: 4.0000e-03 eta: 8:08:49 time: 0.3975 data_time: 0.0350 memory: 5826 grad_norm: 3.9476 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.0514 loss: 2.0514 2022/10/08 06:39:30 - mmengine - INFO - Epoch(train) [111][380/2119] lr: 4.0000e-03 eta: 8:08:42 time: 0.3313 data_time: 0.0227 memory: 5826 grad_norm: 3.8533 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9276 loss: 1.9276 2022/10/08 06:39:38 - mmengine - INFO - Epoch(train) [111][400/2119] lr: 4.0000e-03 eta: 8:08:35 time: 0.3718 data_time: 0.0216 memory: 5826 grad_norm: 3.8619 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9948 loss: 1.9948 2022/10/08 06:39:44 - mmengine - INFO - Epoch(train) [111][420/2119] lr: 4.0000e-03 eta: 8:08:28 time: 0.3332 data_time: 0.0229 memory: 5826 grad_norm: 3.9290 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1919 loss: 2.1919 2022/10/08 06:39:53 - mmengine - INFO - Epoch(train) [111][440/2119] lr: 4.0000e-03 eta: 8:08:22 time: 0.4468 data_time: 0.0237 memory: 5826 grad_norm: 3.8832 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0190 loss: 2.0190 2022/10/08 06:40:00 - mmengine - INFO - Epoch(train) [111][460/2119] lr: 4.0000e-03 eta: 8:08:15 time: 0.3402 data_time: 0.0227 memory: 5826 grad_norm: 3.8909 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9341 loss: 1.9341 2022/10/08 06:40:08 - mmengine - INFO - Epoch(train) [111][480/2119] lr: 4.0000e-03 eta: 8:08:08 time: 0.3707 data_time: 0.0161 memory: 5826 grad_norm: 3.9143 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2672 loss: 2.2672 2022/10/08 06:40:15 - mmengine - INFO - Epoch(train) [111][500/2119] lr: 4.0000e-03 eta: 8:08:01 time: 0.3418 data_time: 0.0235 memory: 5826 grad_norm: 3.8977 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.1969 loss: 2.1969 2022/10/08 06:40:22 - mmengine - INFO - Epoch(train) [111][520/2119] lr: 4.0000e-03 eta: 8:07:54 time: 0.3624 data_time: 0.0197 memory: 5826 grad_norm: 3.9071 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0509 loss: 2.0509 2022/10/08 06:40:29 - mmengine - INFO - Epoch(train) [111][540/2119] lr: 4.0000e-03 eta: 8:07:47 time: 0.3423 data_time: 0.0208 memory: 5826 grad_norm: 3.9901 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9050 loss: 1.9050 2022/10/08 06:40:36 - mmengine - INFO - Epoch(train) [111][560/2119] lr: 4.0000e-03 eta: 8:07:41 time: 0.3793 data_time: 0.0195 memory: 5826 grad_norm: 3.9134 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1301 loss: 2.1301 2022/10/08 06:40:45 - mmengine - INFO - Epoch(train) [111][580/2119] lr: 4.0000e-03 eta: 8:07:34 time: 0.4147 data_time: 0.0246 memory: 5826 grad_norm: 3.8965 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1463 loss: 2.1463 2022/10/08 06:40:51 - mmengine - INFO - Epoch(train) [111][600/2119] lr: 4.0000e-03 eta: 8:07:27 time: 0.3279 data_time: 0.0253 memory: 5826 grad_norm: 3.9946 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0944 loss: 2.0944 2022/10/08 06:40:58 - mmengine - INFO - Epoch(train) [111][620/2119] lr: 4.0000e-03 eta: 8:07:20 time: 0.3354 data_time: 0.0217 memory: 5826 grad_norm: 3.8493 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9813 loss: 1.9813 2022/10/08 06:41:05 - mmengine - INFO - Epoch(train) [111][640/2119] lr: 4.0000e-03 eta: 8:07:13 time: 0.3623 data_time: 0.0238 memory: 5826 grad_norm: 3.9696 top1_acc: 0.1875 top5_acc: 0.3750 loss_cls: 2.0293 loss: 2.0293 2022/10/08 06:41:12 - mmengine - INFO - Epoch(train) [111][660/2119] lr: 4.0000e-03 eta: 8:07:06 time: 0.3261 data_time: 0.0179 memory: 5826 grad_norm: 3.9706 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.7860 loss: 1.7860 2022/10/08 06:41:19 - mmengine - INFO - Epoch(train) [111][680/2119] lr: 4.0000e-03 eta: 8:06:59 time: 0.3825 data_time: 0.0215 memory: 5826 grad_norm: 3.8851 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9847 loss: 1.9847 2022/10/08 06:41:26 - mmengine - INFO - Epoch(train) [111][700/2119] lr: 4.0000e-03 eta: 8:06:52 time: 0.3473 data_time: 0.0349 memory: 5826 grad_norm: 3.9056 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.2720 loss: 2.2720 2022/10/08 06:41:33 - mmengine - INFO - Epoch(train) [111][720/2119] lr: 4.0000e-03 eta: 8:06:45 time: 0.3602 data_time: 0.0212 memory: 5826 grad_norm: 3.8821 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1087 loss: 2.1087 2022/10/08 06:41:40 - mmengine - INFO - Epoch(train) [111][740/2119] lr: 4.0000e-03 eta: 8:06:38 time: 0.3132 data_time: 0.0245 memory: 5826 grad_norm: 3.8748 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0336 loss: 2.0336 2022/10/08 06:41:47 - mmengine - INFO - Epoch(train) [111][760/2119] lr: 4.0000e-03 eta: 8:06:32 time: 0.3838 data_time: 0.0209 memory: 5826 grad_norm: 3.8646 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7576 loss: 1.7576 2022/10/08 06:41:53 - mmengine - INFO - Epoch(train) [111][780/2119] lr: 4.0000e-03 eta: 8:06:24 time: 0.3031 data_time: 0.0210 memory: 5826 grad_norm: 3.8872 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1188 loss: 2.1188 2022/10/08 06:42:02 - mmengine - INFO - Epoch(train) [111][800/2119] lr: 4.0000e-03 eta: 8:06:18 time: 0.4098 data_time: 0.0205 memory: 5826 grad_norm: 3.9483 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2033 loss: 2.2033 2022/10/08 06:42:09 - mmengine - INFO - Epoch(train) [111][820/2119] lr: 4.0000e-03 eta: 8:06:11 time: 0.3457 data_time: 0.0180 memory: 5826 grad_norm: 3.8993 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.1710 loss: 2.1710 2022/10/08 06:42:15 - mmengine - INFO - Epoch(train) [111][840/2119] lr: 4.0000e-03 eta: 8:06:04 time: 0.3387 data_time: 0.0233 memory: 5826 grad_norm: 3.8960 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1343 loss: 2.1343 2022/10/08 06:42:22 - mmengine - INFO - Epoch(train) [111][860/2119] lr: 4.0000e-03 eta: 8:05:57 time: 0.3150 data_time: 0.0269 memory: 5826 grad_norm: 3.8366 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8689 loss: 1.8689 2022/10/08 06:42:30 - mmengine - INFO - Epoch(train) [111][880/2119] lr: 4.0000e-03 eta: 8:05:50 time: 0.4379 data_time: 0.0217 memory: 5826 grad_norm: 3.9064 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2389 loss: 2.2389 2022/10/08 06:42:37 - mmengine - INFO - Epoch(train) [111][900/2119] lr: 4.0000e-03 eta: 8:05:43 time: 0.3381 data_time: 0.0247 memory: 5826 grad_norm: 3.8577 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2435 loss: 2.2435 2022/10/08 06:42:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 06:42:45 - mmengine - INFO - Epoch(train) [111][920/2119] lr: 4.0000e-03 eta: 8:05:37 time: 0.3906 data_time: 0.0228 memory: 5826 grad_norm: 3.8506 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2548 loss: 2.2548 2022/10/08 06:42:51 - mmengine - INFO - Epoch(train) [111][940/2119] lr: 4.0000e-03 eta: 8:05:30 time: 0.3214 data_time: 0.0199 memory: 5826 grad_norm: 3.8502 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.9144 loss: 1.9144 2022/10/08 06:42:59 - mmengine - INFO - Epoch(train) [111][960/2119] lr: 4.0000e-03 eta: 8:05:23 time: 0.3867 data_time: 0.0211 memory: 5826 grad_norm: 3.9785 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1024 loss: 2.1024 2022/10/08 06:43:06 - mmengine - INFO - Epoch(train) [111][980/2119] lr: 4.0000e-03 eta: 8:05:16 time: 0.3170 data_time: 0.0257 memory: 5826 grad_norm: 3.8780 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.0549 loss: 2.0549 2022/10/08 06:43:13 - mmengine - INFO - Epoch(train) [111][1000/2119] lr: 4.0000e-03 eta: 8:05:09 time: 0.3704 data_time: 0.0236 memory: 5826 grad_norm: 3.9025 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0329 loss: 2.0329 2022/10/08 06:43:20 - mmengine - INFO - Epoch(train) [111][1020/2119] lr: 4.0000e-03 eta: 8:05:02 time: 0.3388 data_time: 0.0251 memory: 5826 grad_norm: 3.8970 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1080 loss: 2.1080 2022/10/08 06:43:27 - mmengine - INFO - Epoch(train) [111][1040/2119] lr: 4.0000e-03 eta: 8:04:55 time: 0.3854 data_time: 0.0201 memory: 5826 grad_norm: 3.9232 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9061 loss: 1.9061 2022/10/08 06:43:34 - mmengine - INFO - Epoch(train) [111][1060/2119] lr: 4.0000e-03 eta: 8:04:48 time: 0.3504 data_time: 0.0299 memory: 5826 grad_norm: 3.8850 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8732 loss: 1.8732 2022/10/08 06:43:42 - mmengine - INFO - Epoch(train) [111][1080/2119] lr: 4.0000e-03 eta: 8:04:41 time: 0.3624 data_time: 0.0198 memory: 5826 grad_norm: 3.8728 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8513 loss: 1.8513 2022/10/08 06:43:49 - mmengine - INFO - Epoch(train) [111][1100/2119] lr: 4.0000e-03 eta: 8:04:35 time: 0.3650 data_time: 0.0238 memory: 5826 grad_norm: 3.8483 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.0155 loss: 2.0155 2022/10/08 06:43:57 - mmengine - INFO - Epoch(train) [111][1120/2119] lr: 4.0000e-03 eta: 8:04:28 time: 0.3776 data_time: 0.0181 memory: 5826 grad_norm: 3.9443 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0198 loss: 2.0198 2022/10/08 06:44:03 - mmengine - INFO - Epoch(train) [111][1140/2119] lr: 4.0000e-03 eta: 8:04:21 time: 0.3387 data_time: 0.0211 memory: 5826 grad_norm: 3.9640 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.1460 loss: 2.1460 2022/10/08 06:44:10 - mmengine - INFO - Epoch(train) [111][1160/2119] lr: 4.0000e-03 eta: 8:04:14 time: 0.3543 data_time: 0.0254 memory: 5826 grad_norm: 3.9046 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9952 loss: 1.9952 2022/10/08 06:44:18 - mmengine - INFO - Epoch(train) [111][1180/2119] lr: 4.0000e-03 eta: 8:04:07 time: 0.3597 data_time: 0.0239 memory: 5826 grad_norm: 3.8784 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0199 loss: 2.0199 2022/10/08 06:44:25 - mmengine - INFO - Epoch(train) [111][1200/2119] lr: 4.0000e-03 eta: 8:04:00 time: 0.3493 data_time: 0.0241 memory: 5826 grad_norm: 3.8831 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.9123 loss: 1.9123 2022/10/08 06:44:31 - mmengine - INFO - Epoch(train) [111][1220/2119] lr: 4.0000e-03 eta: 8:03:53 time: 0.3066 data_time: 0.0320 memory: 5826 grad_norm: 3.8689 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.1782 loss: 2.1782 2022/10/08 06:44:39 - mmengine - INFO - Epoch(train) [111][1240/2119] lr: 4.0000e-03 eta: 8:03:46 time: 0.3959 data_time: 0.0190 memory: 5826 grad_norm: 3.8914 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0998 loss: 2.0998 2022/10/08 06:44:46 - mmengine - INFO - Epoch(train) [111][1260/2119] lr: 4.0000e-03 eta: 8:03:39 time: 0.3466 data_time: 0.0229 memory: 5826 grad_norm: 3.8605 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0496 loss: 2.0496 2022/10/08 06:44:53 - mmengine - INFO - Epoch(train) [111][1280/2119] lr: 4.0000e-03 eta: 8:03:33 time: 0.3804 data_time: 0.0186 memory: 5826 grad_norm: 3.8638 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.9231 loss: 1.9231 2022/10/08 06:45:00 - mmengine - INFO - Epoch(train) [111][1300/2119] lr: 4.0000e-03 eta: 8:03:26 time: 0.3365 data_time: 0.0228 memory: 5826 grad_norm: 3.8805 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0218 loss: 2.0218 2022/10/08 06:45:08 - mmengine - INFO - Epoch(train) [111][1320/2119] lr: 4.0000e-03 eta: 8:03:19 time: 0.3893 data_time: 0.0239 memory: 5826 grad_norm: 3.9050 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9365 loss: 1.9365 2022/10/08 06:45:14 - mmengine - INFO - Epoch(train) [111][1340/2119] lr: 4.0000e-03 eta: 8:03:12 time: 0.3006 data_time: 0.0215 memory: 5826 grad_norm: 3.9108 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.0648 loss: 2.0648 2022/10/08 06:45:21 - mmengine - INFO - Epoch(train) [111][1360/2119] lr: 4.0000e-03 eta: 8:03:05 time: 0.3356 data_time: 0.0217 memory: 5826 grad_norm: 3.8483 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.2236 loss: 2.2236 2022/10/08 06:45:28 - mmengine - INFO - Epoch(train) [111][1380/2119] lr: 4.0000e-03 eta: 8:02:58 time: 0.3676 data_time: 0.0272 memory: 5826 grad_norm: 3.8979 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1932 loss: 2.1932 2022/10/08 06:45:36 - mmengine - INFO - Epoch(train) [111][1400/2119] lr: 4.0000e-03 eta: 8:02:51 time: 0.3862 data_time: 0.0187 memory: 5826 grad_norm: 3.9260 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9489 loss: 1.9489 2022/10/08 06:45:42 - mmengine - INFO - Epoch(train) [111][1420/2119] lr: 4.0000e-03 eta: 8:02:44 time: 0.3244 data_time: 0.0249 memory: 5826 grad_norm: 3.8906 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1749 loss: 2.1749 2022/10/08 06:45:50 - mmengine - INFO - Epoch(train) [111][1440/2119] lr: 4.0000e-03 eta: 8:02:37 time: 0.3928 data_time: 0.0218 memory: 5826 grad_norm: 3.9324 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0884 loss: 2.0884 2022/10/08 06:45:56 - mmengine - INFO - Epoch(train) [111][1460/2119] lr: 4.0000e-03 eta: 8:02:30 time: 0.2911 data_time: 0.0213 memory: 5826 grad_norm: 3.9006 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.1188 loss: 2.1188 2022/10/08 06:46:04 - mmengine - INFO - Epoch(train) [111][1480/2119] lr: 4.0000e-03 eta: 8:02:23 time: 0.3977 data_time: 0.0222 memory: 5826 grad_norm: 3.9335 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1722 loss: 2.1722 2022/10/08 06:46:10 - mmengine - INFO - Epoch(train) [111][1500/2119] lr: 4.0000e-03 eta: 8:02:16 time: 0.3200 data_time: 0.0238 memory: 5826 grad_norm: 3.9005 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0852 loss: 2.0852 2022/10/08 06:46:17 - mmengine - INFO - Epoch(train) [111][1520/2119] lr: 4.0000e-03 eta: 8:02:09 time: 0.3539 data_time: 0.0216 memory: 5826 grad_norm: 3.8947 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.0260 loss: 2.0260 2022/10/08 06:46:24 - mmengine - INFO - Epoch(train) [111][1540/2119] lr: 4.0000e-03 eta: 8:02:02 time: 0.3286 data_time: 0.0267 memory: 5826 grad_norm: 3.9482 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8899 loss: 1.8899 2022/10/08 06:46:31 - mmengine - INFO - Epoch(train) [111][1560/2119] lr: 4.0000e-03 eta: 8:01:55 time: 0.3572 data_time: 0.0190 memory: 5826 grad_norm: 3.9016 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9350 loss: 1.9350 2022/10/08 06:46:38 - mmengine - INFO - Epoch(train) [111][1580/2119] lr: 4.0000e-03 eta: 8:01:48 time: 0.3277 data_time: 0.0184 memory: 5826 grad_norm: 3.8428 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.1158 loss: 2.1158 2022/10/08 06:46:45 - mmengine - INFO - Epoch(train) [111][1600/2119] lr: 4.0000e-03 eta: 8:01:42 time: 0.3653 data_time: 0.0247 memory: 5826 grad_norm: 3.8916 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.1749 loss: 2.1749 2022/10/08 06:46:51 - mmengine - INFO - Epoch(train) [111][1620/2119] lr: 4.0000e-03 eta: 8:01:34 time: 0.2897 data_time: 0.0177 memory: 5826 grad_norm: 3.9271 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.8736 loss: 1.8736 2022/10/08 06:46:58 - mmengine - INFO - Epoch(train) [111][1640/2119] lr: 4.0000e-03 eta: 8:01:27 time: 0.3536 data_time: 0.0242 memory: 5826 grad_norm: 3.8408 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1447 loss: 2.1447 2022/10/08 06:47:05 - mmengine - INFO - Epoch(train) [111][1660/2119] lr: 4.0000e-03 eta: 8:01:20 time: 0.3685 data_time: 0.0174 memory: 5826 grad_norm: 3.8873 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.3068 loss: 2.3068 2022/10/08 06:47:12 - mmengine - INFO - Epoch(train) [111][1680/2119] lr: 4.0000e-03 eta: 8:01:14 time: 0.3663 data_time: 0.0208 memory: 5826 grad_norm: 3.8558 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.1446 loss: 2.1446 2022/10/08 06:47:19 - mmengine - INFO - Epoch(train) [111][1700/2119] lr: 4.0000e-03 eta: 8:01:07 time: 0.3403 data_time: 0.0246 memory: 5826 grad_norm: 3.8584 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8534 loss: 1.8534 2022/10/08 06:47:26 - mmengine - INFO - Epoch(train) [111][1720/2119] lr: 4.0000e-03 eta: 8:01:00 time: 0.3511 data_time: 0.0220 memory: 5826 grad_norm: 3.9628 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.3489 loss: 2.3489 2022/10/08 06:47:33 - mmengine - INFO - Epoch(train) [111][1740/2119] lr: 4.0000e-03 eta: 8:00:53 time: 0.3598 data_time: 0.0245 memory: 5826 grad_norm: 3.8967 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8128 loss: 1.8128 2022/10/08 06:47:40 - mmengine - INFO - Epoch(train) [111][1760/2119] lr: 4.0000e-03 eta: 8:00:46 time: 0.3354 data_time: 0.0231 memory: 5826 grad_norm: 3.8731 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9032 loss: 1.9032 2022/10/08 06:47:47 - mmengine - INFO - Epoch(train) [111][1780/2119] lr: 4.0000e-03 eta: 8:00:39 time: 0.3450 data_time: 0.0209 memory: 5826 grad_norm: 3.9519 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 2.0139 loss: 2.0139 2022/10/08 06:47:55 - mmengine - INFO - Epoch(train) [111][1800/2119] lr: 4.0000e-03 eta: 8:00:32 time: 0.3972 data_time: 0.0393 memory: 5826 grad_norm: 3.9806 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.3851 loss: 2.3851 2022/10/08 06:48:01 - mmengine - INFO - Epoch(train) [111][1820/2119] lr: 4.0000e-03 eta: 8:00:25 time: 0.2894 data_time: 0.0235 memory: 5826 grad_norm: 3.8952 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.1159 loss: 2.1159 2022/10/08 06:48:08 - mmengine - INFO - Epoch(train) [111][1840/2119] lr: 4.0000e-03 eta: 8:00:18 time: 0.3538 data_time: 0.0281 memory: 5826 grad_norm: 3.8524 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.0402 loss: 2.0402 2022/10/08 06:48:15 - mmengine - INFO - Epoch(train) [111][1860/2119] lr: 4.0000e-03 eta: 8:00:11 time: 0.3696 data_time: 0.0212 memory: 5826 grad_norm: 3.9261 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2362 loss: 2.2362 2022/10/08 06:48:22 - mmengine - INFO - Epoch(train) [111][1880/2119] lr: 4.0000e-03 eta: 8:00:04 time: 0.3454 data_time: 0.0298 memory: 5826 grad_norm: 3.9845 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9288 loss: 1.9288 2022/10/08 06:48:29 - mmengine - INFO - Epoch(train) [111][1900/2119] lr: 4.0000e-03 eta: 7:59:57 time: 0.3300 data_time: 0.0240 memory: 5826 grad_norm: 3.9240 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0473 loss: 2.0473 2022/10/08 06:48:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 06:48:36 - mmengine - INFO - Epoch(train) [111][1920/2119] lr: 4.0000e-03 eta: 7:59:50 time: 0.3717 data_time: 0.0176 memory: 5826 grad_norm: 3.9578 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1674 loss: 2.1674 2022/10/08 06:48:43 - mmengine - INFO - Epoch(train) [111][1940/2119] lr: 4.0000e-03 eta: 7:59:43 time: 0.3257 data_time: 0.0276 memory: 5826 grad_norm: 3.8946 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.2343 loss: 2.2343 2022/10/08 06:48:49 - mmengine - INFO - Epoch(train) [111][1960/2119] lr: 4.0000e-03 eta: 7:59:36 time: 0.3260 data_time: 0.0246 memory: 5826 grad_norm: 3.8984 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1644 loss: 2.1644 2022/10/08 06:48:56 - mmengine - INFO - Epoch(train) [111][1980/2119] lr: 4.0000e-03 eta: 7:59:29 time: 0.3530 data_time: 0.0294 memory: 5826 grad_norm: 3.9687 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0250 loss: 2.0250 2022/10/08 06:49:04 - mmengine - INFO - Epoch(train) [111][2000/2119] lr: 4.0000e-03 eta: 7:59:22 time: 0.3624 data_time: 0.0214 memory: 5826 grad_norm: 3.9165 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0585 loss: 2.0585 2022/10/08 06:49:10 - mmengine - INFO - Epoch(train) [111][2020/2119] lr: 4.0000e-03 eta: 7:59:15 time: 0.3278 data_time: 0.0226 memory: 5826 grad_norm: 3.9791 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9768 loss: 1.9768 2022/10/08 06:49:17 - mmengine - INFO - Epoch(train) [111][2040/2119] lr: 4.0000e-03 eta: 7:59:08 time: 0.3506 data_time: 0.0281 memory: 5826 grad_norm: 3.9313 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2449 loss: 2.2449 2022/10/08 06:49:24 - mmengine - INFO - Epoch(train) [111][2060/2119] lr: 4.0000e-03 eta: 7:59:01 time: 0.3331 data_time: 0.0245 memory: 5826 grad_norm: 3.9153 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9032 loss: 1.9032 2022/10/08 06:49:31 - mmengine - INFO - Epoch(train) [111][2080/2119] lr: 4.0000e-03 eta: 7:58:54 time: 0.3491 data_time: 0.0224 memory: 5826 grad_norm: 4.0262 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.2064 loss: 2.2064 2022/10/08 06:49:38 - mmengine - INFO - Epoch(train) [111][2100/2119] lr: 4.0000e-03 eta: 7:58:48 time: 0.3630 data_time: 0.0240 memory: 5826 grad_norm: 4.0310 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1537 loss: 2.1537 2022/10/08 06:49:45 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 06:49:45 - mmengine - INFO - Epoch(train) [111][2119/2119] lr: 4.0000e-03 eta: 7:58:48 time: 0.3780 data_time: 0.0240 memory: 5826 grad_norm: 3.8647 top1_acc: 0.8000 top5_acc: 0.9000 loss_cls: 1.8180 loss: 1.8180 2022/10/08 06:49:56 - mmengine - INFO - Epoch(train) [112][20/2119] lr: 4.0000e-03 eta: 7:58:33 time: 0.5261 data_time: 0.1538 memory: 5826 grad_norm: 3.8277 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0558 loss: 2.0558 2022/10/08 06:50:02 - mmengine - INFO - Epoch(train) [112][40/2119] lr: 4.0000e-03 eta: 7:58:26 time: 0.3004 data_time: 0.0257 memory: 5826 grad_norm: 3.8622 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.0457 loss: 2.0457 2022/10/08 06:50:09 - mmengine - INFO - Epoch(train) [112][60/2119] lr: 4.0000e-03 eta: 7:58:19 time: 0.3699 data_time: 0.0213 memory: 5826 grad_norm: 3.9517 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9662 loss: 1.9662 2022/10/08 06:50:16 - mmengine - INFO - Epoch(train) [112][80/2119] lr: 4.0000e-03 eta: 7:58:12 time: 0.3565 data_time: 0.0320 memory: 5826 grad_norm: 3.9169 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9489 loss: 1.9489 2022/10/08 06:50:23 - mmengine - INFO - Epoch(train) [112][100/2119] lr: 4.0000e-03 eta: 7:58:05 time: 0.3388 data_time: 0.0166 memory: 5826 grad_norm: 3.9336 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9060 loss: 1.9060 2022/10/08 06:50:30 - mmengine - INFO - Epoch(train) [112][120/2119] lr: 4.0000e-03 eta: 7:57:58 time: 0.3216 data_time: 0.0174 memory: 5826 grad_norm: 3.9633 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0486 loss: 2.0486 2022/10/08 06:50:37 - mmengine - INFO - Epoch(train) [112][140/2119] lr: 4.0000e-03 eta: 7:57:51 time: 0.3883 data_time: 0.0172 memory: 5826 grad_norm: 3.9401 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0070 loss: 2.0070 2022/10/08 06:50:44 - mmengine - INFO - Epoch(train) [112][160/2119] lr: 4.0000e-03 eta: 7:57:44 time: 0.3288 data_time: 0.0247 memory: 5826 grad_norm: 3.8925 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9419 loss: 1.9419 2022/10/08 06:50:52 - mmengine - INFO - Epoch(train) [112][180/2119] lr: 4.0000e-03 eta: 7:57:37 time: 0.3814 data_time: 0.0221 memory: 5826 grad_norm: 3.9511 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.0181 loss: 2.0181 2022/10/08 06:50:58 - mmengine - INFO - Epoch(train) [112][200/2119] lr: 4.0000e-03 eta: 7:57:30 time: 0.3369 data_time: 0.0209 memory: 5826 grad_norm: 3.9491 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0191 loss: 2.0191 2022/10/08 06:51:07 - mmengine - INFO - Epoch(train) [112][220/2119] lr: 4.0000e-03 eta: 7:57:24 time: 0.4270 data_time: 0.0273 memory: 5826 grad_norm: 3.8970 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0773 loss: 2.0773 2022/10/08 06:51:13 - mmengine - INFO - Epoch(train) [112][240/2119] lr: 4.0000e-03 eta: 7:57:17 time: 0.3087 data_time: 0.0195 memory: 5826 grad_norm: 3.9946 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1017 loss: 2.1017 2022/10/08 06:51:21 - mmengine - INFO - Epoch(train) [112][260/2119] lr: 4.0000e-03 eta: 7:57:10 time: 0.3657 data_time: 0.0255 memory: 5826 grad_norm: 3.9474 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0462 loss: 2.0462 2022/10/08 06:51:27 - mmengine - INFO - Epoch(train) [112][280/2119] lr: 4.0000e-03 eta: 7:57:03 time: 0.3309 data_time: 0.0228 memory: 5826 grad_norm: 3.9535 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8765 loss: 1.8765 2022/10/08 06:51:35 - mmengine - INFO - Epoch(train) [112][300/2119] lr: 4.0000e-03 eta: 7:56:56 time: 0.3703 data_time: 0.0257 memory: 5826 grad_norm: 3.8586 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9459 loss: 1.9459 2022/10/08 06:51:41 - mmengine - INFO - Epoch(train) [112][320/2119] lr: 4.0000e-03 eta: 7:56:49 time: 0.3243 data_time: 0.0335 memory: 5826 grad_norm: 3.8958 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3561 loss: 2.3561 2022/10/08 06:51:48 - mmengine - INFO - Epoch(train) [112][340/2119] lr: 4.0000e-03 eta: 7:56:42 time: 0.3671 data_time: 0.0184 memory: 5826 grad_norm: 3.9404 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9190 loss: 1.9190 2022/10/08 06:51:55 - mmengine - INFO - Epoch(train) [112][360/2119] lr: 4.0000e-03 eta: 7:56:35 time: 0.3265 data_time: 0.0246 memory: 5826 grad_norm: 3.8347 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.1383 loss: 2.1383 2022/10/08 06:52:03 - mmengine - INFO - Epoch(train) [112][380/2119] lr: 4.0000e-03 eta: 7:56:28 time: 0.3974 data_time: 0.0192 memory: 5826 grad_norm: 3.9557 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1517 loss: 2.1517 2022/10/08 06:52:09 - mmengine - INFO - Epoch(train) [112][400/2119] lr: 4.0000e-03 eta: 7:56:21 time: 0.3140 data_time: 0.0218 memory: 5826 grad_norm: 4.0406 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1338 loss: 2.1338 2022/10/08 06:52:17 - mmengine - INFO - Epoch(train) [112][420/2119] lr: 4.0000e-03 eta: 7:56:15 time: 0.3905 data_time: 0.0289 memory: 5826 grad_norm: 3.9256 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9201 loss: 1.9201 2022/10/08 06:52:24 - mmengine - INFO - Epoch(train) [112][440/2119] lr: 4.0000e-03 eta: 7:56:08 time: 0.3491 data_time: 0.0236 memory: 5826 grad_norm: 3.8970 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9689 loss: 1.9689 2022/10/08 06:52:31 - mmengine - INFO - Epoch(train) [112][460/2119] lr: 4.0000e-03 eta: 7:56:01 time: 0.3436 data_time: 0.0208 memory: 5826 grad_norm: 3.9683 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0397 loss: 2.0397 2022/10/08 06:52:38 - mmengine - INFO - Epoch(train) [112][480/2119] lr: 4.0000e-03 eta: 7:55:54 time: 0.3745 data_time: 0.0250 memory: 5826 grad_norm: 3.9031 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 1.8734 loss: 1.8734 2022/10/08 06:52:46 - mmengine - INFO - Epoch(train) [112][500/2119] lr: 4.0000e-03 eta: 7:55:47 time: 0.3696 data_time: 0.0234 memory: 5826 grad_norm: 3.9051 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9257 loss: 1.9257 2022/10/08 06:52:52 - mmengine - INFO - Epoch(train) [112][520/2119] lr: 4.0000e-03 eta: 7:55:40 time: 0.3306 data_time: 0.0184 memory: 5826 grad_norm: 3.8485 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.2310 loss: 2.2310 2022/10/08 06:53:00 - mmengine - INFO - Epoch(train) [112][540/2119] lr: 4.0000e-03 eta: 7:55:33 time: 0.3574 data_time: 0.0205 memory: 5826 grad_norm: 3.9229 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9782 loss: 1.9782 2022/10/08 06:53:06 - mmengine - INFO - Epoch(train) [112][560/2119] lr: 4.0000e-03 eta: 7:55:26 time: 0.3116 data_time: 0.0237 memory: 5826 grad_norm: 3.9799 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1800 loss: 2.1800 2022/10/08 06:53:13 - mmengine - INFO - Epoch(train) [112][580/2119] lr: 4.0000e-03 eta: 7:55:19 time: 0.3808 data_time: 0.0218 memory: 5826 grad_norm: 3.9197 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9232 loss: 1.9232 2022/10/08 06:53:19 - mmengine - INFO - Epoch(train) [112][600/2119] lr: 4.0000e-03 eta: 7:55:12 time: 0.2924 data_time: 0.0234 memory: 5826 grad_norm: 3.8616 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0829 loss: 2.0829 2022/10/08 06:53:28 - mmengine - INFO - Epoch(train) [112][620/2119] lr: 4.0000e-03 eta: 7:55:05 time: 0.4156 data_time: 0.0246 memory: 5826 grad_norm: 3.9169 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0295 loss: 2.0295 2022/10/08 06:53:34 - mmengine - INFO - Epoch(train) [112][640/2119] lr: 4.0000e-03 eta: 7:54:58 time: 0.3401 data_time: 0.0214 memory: 5826 grad_norm: 3.9998 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0888 loss: 2.0888 2022/10/08 06:53:41 - mmengine - INFO - Epoch(train) [112][660/2119] lr: 4.0000e-03 eta: 7:54:51 time: 0.3405 data_time: 0.0188 memory: 5826 grad_norm: 3.9473 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1947 loss: 2.1947 2022/10/08 06:53:48 - mmengine - INFO - Epoch(train) [112][680/2119] lr: 4.0000e-03 eta: 7:54:44 time: 0.3495 data_time: 0.0222 memory: 5826 grad_norm: 3.9609 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.2638 loss: 2.2638 2022/10/08 06:53:55 - mmengine - INFO - Epoch(train) [112][700/2119] lr: 4.0000e-03 eta: 7:54:37 time: 0.3345 data_time: 0.0239 memory: 5826 grad_norm: 3.9673 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.1091 loss: 2.1091 2022/10/08 06:54:02 - mmengine - INFO - Epoch(train) [112][720/2119] lr: 4.0000e-03 eta: 7:54:30 time: 0.3408 data_time: 0.0243 memory: 5826 grad_norm: 4.0070 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0442 loss: 2.0442 2022/10/08 06:54:08 - mmengine - INFO - Epoch(train) [112][740/2119] lr: 4.0000e-03 eta: 7:54:23 time: 0.3359 data_time: 0.0225 memory: 5826 grad_norm: 3.9862 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0972 loss: 2.0972 2022/10/08 06:54:16 - mmengine - INFO - Epoch(train) [112][760/2119] lr: 4.0000e-03 eta: 7:54:17 time: 0.3852 data_time: 0.0241 memory: 5826 grad_norm: 4.0130 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0930 loss: 2.0930 2022/10/08 06:54:23 - mmengine - INFO - Epoch(train) [112][780/2119] lr: 4.0000e-03 eta: 7:54:10 time: 0.3425 data_time: 0.0195 memory: 5826 grad_norm: 3.9955 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0338 loss: 2.0338 2022/10/08 06:54:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 06:54:31 - mmengine - INFO - Epoch(train) [112][800/2119] lr: 4.0000e-03 eta: 7:54:03 time: 0.3755 data_time: 0.0263 memory: 5826 grad_norm: 3.9017 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9601 loss: 1.9601 2022/10/08 06:54:37 - mmengine - INFO - Epoch(train) [112][820/2119] lr: 4.0000e-03 eta: 7:53:56 time: 0.3272 data_time: 0.0269 memory: 5826 grad_norm: 3.9258 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9881 loss: 1.9881 2022/10/08 06:54:44 - mmengine - INFO - Epoch(train) [112][840/2119] lr: 4.0000e-03 eta: 7:53:49 time: 0.3559 data_time: 0.0214 memory: 5826 grad_norm: 3.9206 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0341 loss: 2.0341 2022/10/08 06:54:50 - mmengine - INFO - Epoch(train) [112][860/2119] lr: 4.0000e-03 eta: 7:53:42 time: 0.3091 data_time: 0.0232 memory: 5826 grad_norm: 3.9804 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1031 loss: 2.1031 2022/10/08 06:54:58 - mmengine - INFO - Epoch(train) [112][880/2119] lr: 4.0000e-03 eta: 7:53:35 time: 0.3665 data_time: 0.0296 memory: 5826 grad_norm: 3.9271 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9545 loss: 1.9545 2022/10/08 06:55:05 - mmengine - INFO - Epoch(train) [112][900/2119] lr: 4.0000e-03 eta: 7:53:28 time: 0.3748 data_time: 0.0227 memory: 5826 grad_norm: 3.9685 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.0692 loss: 2.0692 2022/10/08 06:55:12 - mmengine - INFO - Epoch(train) [112][920/2119] lr: 4.0000e-03 eta: 7:53:21 time: 0.3456 data_time: 0.0223 memory: 5826 grad_norm: 3.9419 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.1800 loss: 2.1800 2022/10/08 06:55:19 - mmengine - INFO - Epoch(train) [112][940/2119] lr: 4.0000e-03 eta: 7:53:14 time: 0.3532 data_time: 0.0231 memory: 5826 grad_norm: 4.0018 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.9187 loss: 1.9187 2022/10/08 06:55:26 - mmengine - INFO - Epoch(train) [112][960/2119] lr: 4.0000e-03 eta: 7:53:07 time: 0.3392 data_time: 0.0249 memory: 5826 grad_norm: 3.9177 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9246 loss: 1.9246 2022/10/08 06:55:33 - mmengine - INFO - Epoch(train) [112][980/2119] lr: 4.0000e-03 eta: 7:53:00 time: 0.3297 data_time: 0.0207 memory: 5826 grad_norm: 4.0208 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9972 loss: 1.9972 2022/10/08 06:55:40 - mmengine - INFO - Epoch(train) [112][1000/2119] lr: 4.0000e-03 eta: 7:52:54 time: 0.3859 data_time: 0.0266 memory: 5826 grad_norm: 3.9818 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.1929 loss: 2.1929 2022/10/08 06:55:46 - mmengine - INFO - Epoch(train) [112][1020/2119] lr: 4.0000e-03 eta: 7:52:46 time: 0.3023 data_time: 0.0175 memory: 5826 grad_norm: 3.9036 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1039 loss: 2.1039 2022/10/08 06:55:56 - mmengine - INFO - Epoch(train) [112][1040/2119] lr: 4.0000e-03 eta: 7:52:40 time: 0.4563 data_time: 0.0258 memory: 5826 grad_norm: 4.0019 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0338 loss: 2.0338 2022/10/08 06:56:02 - mmengine - INFO - Epoch(train) [112][1060/2119] lr: 4.0000e-03 eta: 7:52:33 time: 0.3147 data_time: 0.0234 memory: 5826 grad_norm: 3.8983 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8841 loss: 1.8841 2022/10/08 06:56:09 - mmengine - INFO - Epoch(train) [112][1080/2119] lr: 4.0000e-03 eta: 7:52:26 time: 0.3746 data_time: 0.0264 memory: 5826 grad_norm: 3.9130 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.2407 loss: 2.2407 2022/10/08 06:56:16 - mmengine - INFO - Epoch(train) [112][1100/2119] lr: 4.0000e-03 eta: 7:52:19 time: 0.3373 data_time: 0.0170 memory: 5826 grad_norm: 3.8790 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7229 loss: 1.7229 2022/10/08 06:56:23 - mmengine - INFO - Epoch(train) [112][1120/2119] lr: 4.0000e-03 eta: 7:52:12 time: 0.3674 data_time: 0.0234 memory: 5826 grad_norm: 3.9994 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0989 loss: 2.0989 2022/10/08 06:56:31 - mmengine - INFO - Epoch(train) [112][1140/2119] lr: 4.0000e-03 eta: 7:52:05 time: 0.3560 data_time: 0.0203 memory: 5826 grad_norm: 4.0055 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1230 loss: 2.1230 2022/10/08 06:56:38 - mmengine - INFO - Epoch(train) [112][1160/2119] lr: 4.0000e-03 eta: 7:51:59 time: 0.3612 data_time: 0.0311 memory: 5826 grad_norm: 3.9650 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9347 loss: 1.9347 2022/10/08 06:56:45 - mmengine - INFO - Epoch(train) [112][1180/2119] lr: 4.0000e-03 eta: 7:51:52 time: 0.3550 data_time: 0.0199 memory: 5826 grad_norm: 3.9515 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9825 loss: 1.9825 2022/10/08 06:56:52 - mmengine - INFO - Epoch(train) [112][1200/2119] lr: 4.0000e-03 eta: 7:51:45 time: 0.3730 data_time: 0.0228 memory: 5826 grad_norm: 4.0491 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9021 loss: 1.9021 2022/10/08 06:56:59 - mmengine - INFO - Epoch(train) [112][1220/2119] lr: 4.0000e-03 eta: 7:51:38 time: 0.3407 data_time: 0.0269 memory: 5826 grad_norm: 3.9797 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.0645 loss: 2.0645 2022/10/08 06:57:07 - mmengine - INFO - Epoch(train) [112][1240/2119] lr: 4.0000e-03 eta: 7:51:31 time: 0.3746 data_time: 0.0214 memory: 5826 grad_norm: 4.0246 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9462 loss: 1.9462 2022/10/08 06:57:13 - mmengine - INFO - Epoch(train) [112][1260/2119] lr: 4.0000e-03 eta: 7:51:24 time: 0.3371 data_time: 0.0220 memory: 5826 grad_norm: 3.9509 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.1621 loss: 2.1621 2022/10/08 06:57:21 - mmengine - INFO - Epoch(train) [112][1280/2119] lr: 4.0000e-03 eta: 7:51:17 time: 0.3742 data_time: 0.0225 memory: 5826 grad_norm: 3.9651 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0973 loss: 2.0973 2022/10/08 06:57:28 - mmengine - INFO - Epoch(train) [112][1300/2119] lr: 4.0000e-03 eta: 7:51:10 time: 0.3372 data_time: 0.0231 memory: 5826 grad_norm: 3.9682 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1627 loss: 2.1627 2022/10/08 06:57:35 - mmengine - INFO - Epoch(train) [112][1320/2119] lr: 4.0000e-03 eta: 7:51:03 time: 0.3508 data_time: 0.0215 memory: 5826 grad_norm: 3.9742 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9995 loss: 1.9995 2022/10/08 06:57:41 - mmengine - INFO - Epoch(train) [112][1340/2119] lr: 4.0000e-03 eta: 7:50:56 time: 0.3084 data_time: 0.0258 memory: 5826 grad_norm: 3.9874 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.9599 loss: 1.9599 2022/10/08 06:57:49 - mmengine - INFO - Epoch(train) [112][1360/2119] lr: 4.0000e-03 eta: 7:50:50 time: 0.4122 data_time: 0.0230 memory: 5826 grad_norm: 4.0109 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9474 loss: 1.9474 2022/10/08 06:57:56 - mmengine - INFO - Epoch(train) [112][1380/2119] lr: 4.0000e-03 eta: 7:50:43 time: 0.3432 data_time: 0.0222 memory: 5826 grad_norm: 3.9622 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0673 loss: 2.0673 2022/10/08 06:58:04 - mmengine - INFO - Epoch(train) [112][1400/2119] lr: 4.0000e-03 eta: 7:50:36 time: 0.3992 data_time: 0.0235 memory: 5826 grad_norm: 4.0064 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.1074 loss: 2.1074 2022/10/08 06:58:11 - mmengine - INFO - Epoch(train) [112][1420/2119] lr: 4.0000e-03 eta: 7:50:29 time: 0.3287 data_time: 0.0272 memory: 5826 grad_norm: 3.9595 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9575 loss: 1.9575 2022/10/08 06:58:18 - mmengine - INFO - Epoch(train) [112][1440/2119] lr: 4.0000e-03 eta: 7:50:22 time: 0.3589 data_time: 0.0216 memory: 5826 grad_norm: 3.8652 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1032 loss: 2.1032 2022/10/08 06:58:25 - mmengine - INFO - Epoch(train) [112][1460/2119] lr: 4.0000e-03 eta: 7:50:15 time: 0.3415 data_time: 0.0297 memory: 5826 grad_norm: 4.0086 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1578 loss: 2.1578 2022/10/08 06:58:32 - mmengine - INFO - Epoch(train) [112][1480/2119] lr: 4.0000e-03 eta: 7:50:08 time: 0.3713 data_time: 0.0184 memory: 5826 grad_norm: 3.9586 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1916 loss: 2.1916 2022/10/08 06:58:39 - mmengine - INFO - Epoch(train) [112][1500/2119] lr: 4.0000e-03 eta: 7:50:01 time: 0.3263 data_time: 0.0233 memory: 5826 grad_norm: 3.9957 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0469 loss: 2.0469 2022/10/08 06:58:47 - mmengine - INFO - Epoch(train) [112][1520/2119] lr: 4.0000e-03 eta: 7:49:55 time: 0.4041 data_time: 0.0225 memory: 5826 grad_norm: 3.9458 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9567 loss: 1.9567 2022/10/08 06:58:53 - mmengine - INFO - Epoch(train) [112][1540/2119] lr: 4.0000e-03 eta: 7:49:47 time: 0.3057 data_time: 0.0177 memory: 5826 grad_norm: 3.9626 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.1809 loss: 2.1809 2022/10/08 06:59:01 - mmengine - INFO - Epoch(train) [112][1560/2119] lr: 4.0000e-03 eta: 7:49:41 time: 0.4064 data_time: 0.0251 memory: 5826 grad_norm: 3.9504 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0407 loss: 2.0407 2022/10/08 06:59:08 - mmengine - INFO - Epoch(train) [112][1580/2119] lr: 4.0000e-03 eta: 7:49:34 time: 0.3771 data_time: 0.0248 memory: 5826 grad_norm: 3.8822 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9600 loss: 1.9600 2022/10/08 06:59:15 - mmengine - INFO - Epoch(train) [112][1600/2119] lr: 4.0000e-03 eta: 7:49:27 time: 0.3274 data_time: 0.0259 memory: 5826 grad_norm: 3.9273 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.2633 loss: 2.2633 2022/10/08 06:59:22 - mmengine - INFO - Epoch(train) [112][1620/2119] lr: 4.0000e-03 eta: 7:49:20 time: 0.3315 data_time: 0.0246 memory: 5826 grad_norm: 3.9073 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.2204 loss: 2.2204 2022/10/08 06:59:29 - mmengine - INFO - Epoch(train) [112][1640/2119] lr: 4.0000e-03 eta: 7:49:13 time: 0.3492 data_time: 0.0241 memory: 5826 grad_norm: 3.9951 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.1538 loss: 2.1538 2022/10/08 06:59:35 - mmengine - INFO - Epoch(train) [112][1660/2119] lr: 4.0000e-03 eta: 7:49:06 time: 0.3346 data_time: 0.0281 memory: 5826 grad_norm: 3.9992 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0656 loss: 2.0656 2022/10/08 06:59:42 - mmengine - INFO - Epoch(train) [112][1680/2119] lr: 4.0000e-03 eta: 7:48:59 time: 0.3514 data_time: 0.0231 memory: 5826 grad_norm: 3.9800 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9387 loss: 1.9387 2022/10/08 06:59:49 - mmengine - INFO - Epoch(train) [112][1700/2119] lr: 4.0000e-03 eta: 7:48:52 time: 0.3280 data_time: 0.0249 memory: 5826 grad_norm: 4.0124 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1171 loss: 2.1171 2022/10/08 06:59:56 - mmengine - INFO - Epoch(train) [112][1720/2119] lr: 4.0000e-03 eta: 7:48:45 time: 0.3379 data_time: 0.0250 memory: 5826 grad_norm: 3.9467 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.0519 loss: 2.0519 2022/10/08 07:00:04 - mmengine - INFO - Epoch(train) [112][1740/2119] lr: 4.0000e-03 eta: 7:48:38 time: 0.4056 data_time: 0.0242 memory: 5826 grad_norm: 3.9733 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.0874 loss: 2.0874 2022/10/08 07:00:10 - mmengine - INFO - Epoch(train) [112][1760/2119] lr: 4.0000e-03 eta: 7:48:31 time: 0.3288 data_time: 0.0193 memory: 5826 grad_norm: 3.9350 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0819 loss: 2.0819 2022/10/08 07:00:18 - mmengine - INFO - Epoch(train) [112][1780/2119] lr: 4.0000e-03 eta: 7:48:25 time: 0.3859 data_time: 0.0222 memory: 5826 grad_norm: 3.9204 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.1379 loss: 2.1379 2022/10/08 07:00:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 07:00:25 - mmengine - INFO - Epoch(train) [112][1800/2119] lr: 4.0000e-03 eta: 7:48:18 time: 0.3242 data_time: 0.0249 memory: 5826 grad_norm: 3.9381 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0802 loss: 2.0802 2022/10/08 07:00:32 - mmengine - INFO - Epoch(train) [112][1820/2119] lr: 4.0000e-03 eta: 7:48:11 time: 0.3618 data_time: 0.0228 memory: 5826 grad_norm: 4.0010 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1854 loss: 2.1854 2022/10/08 07:00:40 - mmengine - INFO - Epoch(train) [112][1840/2119] lr: 4.0000e-03 eta: 7:48:04 time: 0.3850 data_time: 0.0218 memory: 5826 grad_norm: 3.9779 top1_acc: 0.3125 top5_acc: 0.8750 loss_cls: 2.0204 loss: 2.0204 2022/10/08 07:00:46 - mmengine - INFO - Epoch(train) [112][1860/2119] lr: 4.0000e-03 eta: 7:47:57 time: 0.3395 data_time: 0.0195 memory: 5826 grad_norm: 4.0490 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1147 loss: 2.1147 2022/10/08 07:00:54 - mmengine - INFO - Epoch(train) [112][1880/2119] lr: 4.0000e-03 eta: 7:47:50 time: 0.4048 data_time: 0.0274 memory: 5826 grad_norm: 3.9740 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0125 loss: 2.0125 2022/10/08 07:01:01 - mmengine - INFO - Epoch(train) [112][1900/2119] lr: 4.0000e-03 eta: 7:47:43 time: 0.3298 data_time: 0.0217 memory: 5826 grad_norm: 4.0079 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.2380 loss: 2.2380 2022/10/08 07:01:09 - mmengine - INFO - Epoch(train) [112][1920/2119] lr: 4.0000e-03 eta: 7:47:37 time: 0.4007 data_time: 0.0188 memory: 5826 grad_norm: 3.9336 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9423 loss: 1.9423 2022/10/08 07:01:17 - mmengine - INFO - Epoch(train) [112][1940/2119] lr: 4.0000e-03 eta: 7:47:30 time: 0.3891 data_time: 0.0208 memory: 5826 grad_norm: 4.0118 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1226 loss: 2.1226 2022/10/08 07:01:23 - mmengine - INFO - Epoch(train) [112][1960/2119] lr: 4.0000e-03 eta: 7:47:23 time: 0.3031 data_time: 0.0226 memory: 5826 grad_norm: 3.9222 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0950 loss: 2.0950 2022/10/08 07:01:30 - mmengine - INFO - Epoch(train) [112][1980/2119] lr: 4.0000e-03 eta: 7:47:16 time: 0.3285 data_time: 0.0225 memory: 5826 grad_norm: 3.9637 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.2049 loss: 2.2049 2022/10/08 07:01:37 - mmengine - INFO - Epoch(train) [112][2000/2119] lr: 4.0000e-03 eta: 7:47:09 time: 0.3748 data_time: 0.0236 memory: 5826 grad_norm: 3.9573 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.0470 loss: 2.0470 2022/10/08 07:01:44 - mmengine - INFO - Epoch(train) [112][2020/2119] lr: 4.0000e-03 eta: 7:47:02 time: 0.3444 data_time: 0.0227 memory: 5826 grad_norm: 3.9797 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0351 loss: 2.0351 2022/10/08 07:01:51 - mmengine - INFO - Epoch(train) [112][2040/2119] lr: 4.0000e-03 eta: 7:46:55 time: 0.3737 data_time: 0.0283 memory: 5826 grad_norm: 3.9813 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0487 loss: 2.0487 2022/10/08 07:01:59 - mmengine - INFO - Epoch(train) [112][2060/2119] lr: 4.0000e-03 eta: 7:46:48 time: 0.3578 data_time: 0.0247 memory: 5826 grad_norm: 3.9312 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1863 loss: 2.1863 2022/10/08 07:02:05 - mmengine - INFO - Epoch(train) [112][2080/2119] lr: 4.0000e-03 eta: 7:46:41 time: 0.3383 data_time: 0.0199 memory: 5826 grad_norm: 3.9856 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0297 loss: 2.0297 2022/10/08 07:02:12 - mmengine - INFO - Epoch(train) [112][2100/2119] lr: 4.0000e-03 eta: 7:46:34 time: 0.3384 data_time: 0.0230 memory: 5826 grad_norm: 3.9995 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0985 loss: 2.0985 2022/10/08 07:02:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 07:02:18 - mmengine - INFO - Epoch(train) [112][2119/2119] lr: 4.0000e-03 eta: 7:46:34 time: 0.2916 data_time: 0.0210 memory: 5826 grad_norm: 4.0026 top1_acc: 0.8000 top5_acc: 0.8000 loss_cls: 2.0017 loss: 2.0017 2022/10/08 07:02:18 - mmengine - INFO - Saving checkpoint at 112 epochs 2022/10/08 07:02:38 - mmengine - INFO - Epoch(train) [113][20/2119] lr: 4.0000e-03 eta: 7:46:19 time: 0.4250 data_time: 0.1735 memory: 5826 grad_norm: 3.9916 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.1451 loss: 2.1451 2022/10/08 07:02:44 - mmengine - INFO - Epoch(train) [113][40/2119] lr: 4.0000e-03 eta: 7:46:12 time: 0.3308 data_time: 0.1099 memory: 5826 grad_norm: 3.9830 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.0300 loss: 2.0300 2022/10/08 07:02:51 - mmengine - INFO - Epoch(train) [113][60/2119] lr: 4.0000e-03 eta: 7:46:05 time: 0.3353 data_time: 0.1009 memory: 5826 grad_norm: 4.0414 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1490 loss: 2.1490 2022/10/08 07:02:58 - mmengine - INFO - Epoch(train) [113][80/2119] lr: 4.0000e-03 eta: 7:45:58 time: 0.3459 data_time: 0.0805 memory: 5826 grad_norm: 4.0334 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.3087 loss: 2.3087 2022/10/08 07:03:05 - mmengine - INFO - Epoch(train) [113][100/2119] lr: 4.0000e-03 eta: 7:45:51 time: 0.3577 data_time: 0.0186 memory: 5826 grad_norm: 4.0567 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1794 loss: 2.1794 2022/10/08 07:03:11 - mmengine - INFO - Epoch(train) [113][120/2119] lr: 4.0000e-03 eta: 7:45:44 time: 0.3162 data_time: 0.0235 memory: 5826 grad_norm: 4.0020 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0628 loss: 2.0628 2022/10/08 07:03:19 - mmengine - INFO - Epoch(train) [113][140/2119] lr: 4.0000e-03 eta: 7:45:37 time: 0.4023 data_time: 0.0229 memory: 5826 grad_norm: 3.9983 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9181 loss: 1.9181 2022/10/08 07:03:26 - mmengine - INFO - Epoch(train) [113][160/2119] lr: 4.0000e-03 eta: 7:45:30 time: 0.3513 data_time: 0.0239 memory: 5826 grad_norm: 3.9534 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9579 loss: 1.9579 2022/10/08 07:03:34 - mmengine - INFO - Epoch(train) [113][180/2119] lr: 4.0000e-03 eta: 7:45:24 time: 0.3569 data_time: 0.0244 memory: 5826 grad_norm: 4.0087 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9916 loss: 1.9916 2022/10/08 07:03:40 - mmengine - INFO - Epoch(train) [113][200/2119] lr: 4.0000e-03 eta: 7:45:16 time: 0.3190 data_time: 0.0219 memory: 5826 grad_norm: 4.0086 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1779 loss: 2.1779 2022/10/08 07:03:47 - mmengine - INFO - Epoch(train) [113][220/2119] lr: 4.0000e-03 eta: 7:45:10 time: 0.3678 data_time: 0.0251 memory: 5826 grad_norm: 4.0158 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9866 loss: 1.9866 2022/10/08 07:03:54 - mmengine - INFO - Epoch(train) [113][240/2119] lr: 4.0000e-03 eta: 7:45:03 time: 0.3573 data_time: 0.0216 memory: 5826 grad_norm: 3.9997 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9846 loss: 1.9846 2022/10/08 07:04:01 - mmengine - INFO - Epoch(train) [113][260/2119] lr: 4.0000e-03 eta: 7:44:56 time: 0.3405 data_time: 0.0254 memory: 5826 grad_norm: 4.0068 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.8957 loss: 1.8957 2022/10/08 07:04:09 - mmengine - INFO - Epoch(train) [113][280/2119] lr: 4.0000e-03 eta: 7:44:49 time: 0.4004 data_time: 0.0207 memory: 5826 grad_norm: 3.9621 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9753 loss: 1.9753 2022/10/08 07:04:17 - mmengine - INFO - Epoch(train) [113][300/2119] lr: 4.0000e-03 eta: 7:44:42 time: 0.3869 data_time: 0.0200 memory: 5826 grad_norm: 4.0086 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9826 loss: 1.9826 2022/10/08 07:04:24 - mmengine - INFO - Epoch(train) [113][320/2119] lr: 4.0000e-03 eta: 7:44:35 time: 0.3316 data_time: 0.0202 memory: 5826 grad_norm: 4.0339 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0700 loss: 2.0700 2022/10/08 07:04:32 - mmengine - INFO - Epoch(train) [113][340/2119] lr: 4.0000e-03 eta: 7:44:29 time: 0.4022 data_time: 0.0244 memory: 5826 grad_norm: 3.9233 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9839 loss: 1.9839 2022/10/08 07:04:39 - mmengine - INFO - Epoch(train) [113][360/2119] lr: 4.0000e-03 eta: 7:44:22 time: 0.3522 data_time: 0.0236 memory: 5826 grad_norm: 3.9941 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1298 loss: 2.1298 2022/10/08 07:04:45 - mmengine - INFO - Epoch(train) [113][380/2119] lr: 4.0000e-03 eta: 7:44:15 time: 0.3108 data_time: 0.0244 memory: 5826 grad_norm: 4.0184 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0486 loss: 2.0486 2022/10/08 07:04:52 - mmengine - INFO - Epoch(train) [113][400/2119] lr: 4.0000e-03 eta: 7:44:08 time: 0.3485 data_time: 0.0254 memory: 5826 grad_norm: 3.9935 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9663 loss: 1.9663 2022/10/08 07:04:59 - mmengine - INFO - Epoch(train) [113][420/2119] lr: 4.0000e-03 eta: 7:44:01 time: 0.3680 data_time: 0.0226 memory: 5826 grad_norm: 4.0607 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9701 loss: 1.9701 2022/10/08 07:05:06 - mmengine - INFO - Epoch(train) [113][440/2119] lr: 4.0000e-03 eta: 7:43:54 time: 0.3524 data_time: 0.0223 memory: 5826 grad_norm: 3.9714 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8926 loss: 1.8926 2022/10/08 07:05:13 - mmengine - INFO - Epoch(train) [113][460/2119] lr: 4.0000e-03 eta: 7:43:47 time: 0.3565 data_time: 0.0230 memory: 5826 grad_norm: 3.8703 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0403 loss: 2.0403 2022/10/08 07:05:21 - mmengine - INFO - Epoch(train) [113][480/2119] lr: 4.0000e-03 eta: 7:43:40 time: 0.3884 data_time: 0.0197 memory: 5826 grad_norm: 4.0453 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9095 loss: 1.9095 2022/10/08 07:05:28 - mmengine - INFO - Epoch(train) [113][500/2119] lr: 4.0000e-03 eta: 7:43:33 time: 0.3372 data_time: 0.0190 memory: 5826 grad_norm: 3.9724 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2719 loss: 2.2719 2022/10/08 07:05:35 - mmengine - INFO - Epoch(train) [113][520/2119] lr: 4.0000e-03 eta: 7:43:26 time: 0.3453 data_time: 0.0236 memory: 5826 grad_norm: 3.9692 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2069 loss: 2.2069 2022/10/08 07:05:42 - mmengine - INFO - Epoch(train) [113][540/2119] lr: 4.0000e-03 eta: 7:43:19 time: 0.3536 data_time: 0.0274 memory: 5826 grad_norm: 4.0254 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0628 loss: 2.0628 2022/10/08 07:05:49 - mmengine - INFO - Epoch(train) [113][560/2119] lr: 4.0000e-03 eta: 7:43:13 time: 0.3504 data_time: 0.0212 memory: 5826 grad_norm: 4.0109 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9552 loss: 1.9552 2022/10/08 07:05:56 - mmengine - INFO - Epoch(train) [113][580/2119] lr: 4.0000e-03 eta: 7:43:06 time: 0.3548 data_time: 0.0171 memory: 5826 grad_norm: 3.9328 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.1077 loss: 2.1077 2022/10/08 07:06:03 - mmengine - INFO - Epoch(train) [113][600/2119] lr: 4.0000e-03 eta: 7:42:59 time: 0.3382 data_time: 0.0223 memory: 5826 grad_norm: 4.0379 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0180 loss: 2.0180 2022/10/08 07:06:10 - mmengine - INFO - Epoch(train) [113][620/2119] lr: 4.0000e-03 eta: 7:42:52 time: 0.3353 data_time: 0.0155 memory: 5826 grad_norm: 3.9810 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8367 loss: 1.8367 2022/10/08 07:06:17 - mmengine - INFO - Epoch(train) [113][640/2119] lr: 4.0000e-03 eta: 7:42:45 time: 0.3900 data_time: 0.0203 memory: 5826 grad_norm: 4.0771 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9753 loss: 1.9753 2022/10/08 07:06:23 - mmengine - INFO - Epoch(train) [113][660/2119] lr: 4.0000e-03 eta: 7:42:38 time: 0.3011 data_time: 0.0247 memory: 5826 grad_norm: 4.0162 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9683 loss: 1.9683 2022/10/08 07:06:28 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 07:06:31 - mmengine - INFO - Epoch(train) [113][680/2119] lr: 4.0000e-03 eta: 7:42:31 time: 0.3538 data_time: 0.0211 memory: 5826 grad_norm: 4.0694 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.0410 loss: 2.0410 2022/10/08 07:06:39 - mmengine - INFO - Epoch(train) [113][700/2119] lr: 4.0000e-03 eta: 7:42:24 time: 0.4194 data_time: 0.0260 memory: 5826 grad_norm: 3.9642 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1638 loss: 2.1638 2022/10/08 07:06:45 - mmengine - INFO - Epoch(train) [113][720/2119] lr: 4.0000e-03 eta: 7:42:17 time: 0.3095 data_time: 0.0231 memory: 5826 grad_norm: 4.0487 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.0755 loss: 2.0755 2022/10/08 07:06:52 - mmengine - INFO - Epoch(train) [113][740/2119] lr: 4.0000e-03 eta: 7:42:10 time: 0.3432 data_time: 0.0236 memory: 5826 grad_norm: 4.0649 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1016 loss: 2.1016 2022/10/08 07:07:00 - mmengine - INFO - Epoch(train) [113][760/2119] lr: 4.0000e-03 eta: 7:42:04 time: 0.4165 data_time: 0.0187 memory: 5826 grad_norm: 4.0601 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9106 loss: 1.9106 2022/10/08 07:07:07 - mmengine - INFO - Epoch(train) [113][780/2119] lr: 4.0000e-03 eta: 7:41:57 time: 0.3236 data_time: 0.0244 memory: 5826 grad_norm: 4.0327 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0616 loss: 2.0616 2022/10/08 07:07:14 - mmengine - INFO - Epoch(train) [113][800/2119] lr: 4.0000e-03 eta: 7:41:50 time: 0.3520 data_time: 0.0210 memory: 5826 grad_norm: 4.0888 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9647 loss: 1.9647 2022/10/08 07:07:20 - mmengine - INFO - Epoch(train) [113][820/2119] lr: 4.0000e-03 eta: 7:41:43 time: 0.3297 data_time: 0.0225 memory: 5826 grad_norm: 4.0215 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.2493 loss: 2.2493 2022/10/08 07:07:27 - mmengine - INFO - Epoch(train) [113][840/2119] lr: 4.0000e-03 eta: 7:41:36 time: 0.3389 data_time: 0.0217 memory: 5826 grad_norm: 3.9935 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.3427 loss: 2.3427 2022/10/08 07:07:35 - mmengine - INFO - Epoch(train) [113][860/2119] lr: 4.0000e-03 eta: 7:41:29 time: 0.3636 data_time: 0.0259 memory: 5826 grad_norm: 3.9564 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0067 loss: 2.0067 2022/10/08 07:07:43 - mmengine - INFO - Epoch(train) [113][880/2119] lr: 4.0000e-03 eta: 7:41:22 time: 0.4046 data_time: 0.0200 memory: 5826 grad_norm: 4.0000 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9547 loss: 1.9547 2022/10/08 07:07:50 - mmengine - INFO - Epoch(train) [113][900/2119] lr: 4.0000e-03 eta: 7:41:15 time: 0.3809 data_time: 0.0246 memory: 5826 grad_norm: 4.0971 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0094 loss: 2.0094 2022/10/08 07:07:57 - mmengine - INFO - Epoch(train) [113][920/2119] lr: 4.0000e-03 eta: 7:41:08 time: 0.3452 data_time: 0.0203 memory: 5826 grad_norm: 4.0150 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.2779 loss: 2.2779 2022/10/08 07:08:03 - mmengine - INFO - Epoch(train) [113][940/2119] lr: 4.0000e-03 eta: 7:41:01 time: 0.3152 data_time: 0.0208 memory: 5826 grad_norm: 4.0298 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.1419 loss: 2.1419 2022/10/08 07:08:10 - mmengine - INFO - Epoch(train) [113][960/2119] lr: 4.0000e-03 eta: 7:40:54 time: 0.3265 data_time: 0.0233 memory: 5826 grad_norm: 4.0081 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0808 loss: 2.0808 2022/10/08 07:08:18 - mmengine - INFO - Epoch(train) [113][980/2119] lr: 4.0000e-03 eta: 7:40:48 time: 0.4136 data_time: 0.0210 memory: 5826 grad_norm: 4.0248 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0315 loss: 2.0315 2022/10/08 07:08:25 - mmengine - INFO - Epoch(train) [113][1000/2119] lr: 4.0000e-03 eta: 7:40:40 time: 0.3214 data_time: 0.0278 memory: 5826 grad_norm: 4.0258 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9780 loss: 1.9780 2022/10/08 07:08:32 - mmengine - INFO - Epoch(train) [113][1020/2119] lr: 4.0000e-03 eta: 7:40:34 time: 0.3834 data_time: 0.0251 memory: 5826 grad_norm: 4.1032 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1158 loss: 2.1158 2022/10/08 07:08:39 - mmengine - INFO - Epoch(train) [113][1040/2119] lr: 4.0000e-03 eta: 7:40:27 time: 0.3388 data_time: 0.0203 memory: 5826 grad_norm: 4.0954 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1581 loss: 2.1581 2022/10/08 07:08:47 - mmengine - INFO - Epoch(train) [113][1060/2119] lr: 4.0000e-03 eta: 7:40:20 time: 0.3748 data_time: 0.0270 memory: 5826 grad_norm: 4.0611 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9924 loss: 1.9924 2022/10/08 07:08:53 - mmengine - INFO - Epoch(train) [113][1080/2119] lr: 4.0000e-03 eta: 7:40:13 time: 0.3369 data_time: 0.0215 memory: 5826 grad_norm: 3.9705 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.2170 loss: 2.2170 2022/10/08 07:09:01 - mmengine - INFO - Epoch(train) [113][1100/2119] lr: 4.0000e-03 eta: 7:40:06 time: 0.3567 data_time: 0.0239 memory: 5826 grad_norm: 4.0355 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9150 loss: 1.9150 2022/10/08 07:09:08 - mmengine - INFO - Epoch(train) [113][1120/2119] lr: 4.0000e-03 eta: 7:39:59 time: 0.3695 data_time: 0.0233 memory: 5826 grad_norm: 4.0715 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.9786 loss: 1.9786 2022/10/08 07:09:16 - mmengine - INFO - Epoch(train) [113][1140/2119] lr: 4.0000e-03 eta: 7:39:53 time: 0.3949 data_time: 0.0205 memory: 5826 grad_norm: 4.0413 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.0494 loss: 2.0494 2022/10/08 07:09:22 - mmengine - INFO - Epoch(train) [113][1160/2119] lr: 4.0000e-03 eta: 7:39:46 time: 0.3196 data_time: 0.0235 memory: 5826 grad_norm: 4.0028 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9532 loss: 1.9532 2022/10/08 07:09:30 - mmengine - INFO - Epoch(train) [113][1180/2119] lr: 4.0000e-03 eta: 7:39:39 time: 0.3829 data_time: 0.0220 memory: 5826 grad_norm: 3.9919 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0612 loss: 2.0612 2022/10/08 07:09:37 - mmengine - INFO - Epoch(train) [113][1200/2119] lr: 4.0000e-03 eta: 7:39:32 time: 0.3511 data_time: 0.0277 memory: 5826 grad_norm: 4.0608 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0368 loss: 2.0368 2022/10/08 07:09:44 - mmengine - INFO - Epoch(train) [113][1220/2119] lr: 4.0000e-03 eta: 7:39:25 time: 0.3321 data_time: 0.0199 memory: 5826 grad_norm: 3.9104 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9724 loss: 1.9724 2022/10/08 07:09:51 - mmengine - INFO - Epoch(train) [113][1240/2119] lr: 4.0000e-03 eta: 7:39:18 time: 0.3545 data_time: 0.0304 memory: 5826 grad_norm: 3.9768 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9084 loss: 1.9084 2022/10/08 07:09:59 - mmengine - INFO - Epoch(train) [113][1260/2119] lr: 4.0000e-03 eta: 7:39:11 time: 0.4097 data_time: 0.0264 memory: 5826 grad_norm: 4.0511 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9904 loss: 1.9904 2022/10/08 07:10:07 - mmengine - INFO - Epoch(train) [113][1280/2119] lr: 4.0000e-03 eta: 7:39:05 time: 0.4004 data_time: 0.0222 memory: 5826 grad_norm: 4.0003 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0142 loss: 2.0142 2022/10/08 07:10:13 - mmengine - INFO - Epoch(train) [113][1300/2119] lr: 4.0000e-03 eta: 7:38:57 time: 0.2802 data_time: 0.0205 memory: 5826 grad_norm: 4.0007 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.1475 loss: 2.1475 2022/10/08 07:10:20 - mmengine - INFO - Epoch(train) [113][1320/2119] lr: 4.0000e-03 eta: 7:38:51 time: 0.3839 data_time: 0.0362 memory: 5826 grad_norm: 4.1073 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1093 loss: 2.1093 2022/10/08 07:10:27 - mmengine - INFO - Epoch(train) [113][1340/2119] lr: 4.0000e-03 eta: 7:38:44 time: 0.3354 data_time: 0.0229 memory: 5826 grad_norm: 4.0950 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2718 loss: 2.2718 2022/10/08 07:10:34 - mmengine - INFO - Epoch(train) [113][1360/2119] lr: 4.0000e-03 eta: 7:38:37 time: 0.3537 data_time: 0.0274 memory: 5826 grad_norm: 4.0112 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.8775 loss: 1.8775 2022/10/08 07:10:41 - mmengine - INFO - Epoch(train) [113][1380/2119] lr: 4.0000e-03 eta: 7:38:30 time: 0.3365 data_time: 0.0220 memory: 5826 grad_norm: 3.9899 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0068 loss: 2.0068 2022/10/08 07:10:48 - mmengine - INFO - Epoch(train) [113][1400/2119] lr: 4.0000e-03 eta: 7:38:23 time: 0.3833 data_time: 0.0195 memory: 5826 grad_norm: 4.0440 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.2390 loss: 2.2390 2022/10/08 07:10:56 - mmengine - INFO - Epoch(train) [113][1420/2119] lr: 4.0000e-03 eta: 7:38:16 time: 0.3572 data_time: 0.0255 memory: 5826 grad_norm: 4.0492 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7223 loss: 1.7223 2022/10/08 07:11:03 - mmengine - INFO - Epoch(train) [113][1440/2119] lr: 4.0000e-03 eta: 7:38:09 time: 0.3545 data_time: 0.0185 memory: 5826 grad_norm: 3.9918 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0944 loss: 2.0944 2022/10/08 07:11:10 - mmengine - INFO - Epoch(train) [113][1460/2119] lr: 4.0000e-03 eta: 7:38:02 time: 0.3405 data_time: 0.0264 memory: 5826 grad_norm: 4.0134 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9104 loss: 1.9104 2022/10/08 07:11:17 - mmengine - INFO - Epoch(train) [113][1480/2119] lr: 4.0000e-03 eta: 7:37:55 time: 0.3686 data_time: 0.0243 memory: 5826 grad_norm: 4.0188 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0699 loss: 2.0699 2022/10/08 07:11:24 - mmengine - INFO - Epoch(train) [113][1500/2119] lr: 4.0000e-03 eta: 7:37:48 time: 0.3378 data_time: 0.0254 memory: 5826 grad_norm: 4.0320 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9825 loss: 1.9825 2022/10/08 07:11:31 - mmengine - INFO - Epoch(train) [113][1520/2119] lr: 4.0000e-03 eta: 7:37:41 time: 0.3586 data_time: 0.0223 memory: 5826 grad_norm: 4.0436 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0423 loss: 2.0423 2022/10/08 07:11:38 - mmengine - INFO - Epoch(train) [113][1540/2119] lr: 4.0000e-03 eta: 7:37:35 time: 0.3745 data_time: 0.0269 memory: 5826 grad_norm: 4.0851 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2689 loss: 2.2689 2022/10/08 07:11:45 - mmengine - INFO - Epoch(train) [113][1560/2119] lr: 4.0000e-03 eta: 7:37:28 time: 0.3235 data_time: 0.0199 memory: 5826 grad_norm: 4.0272 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9802 loss: 1.9802 2022/10/08 07:11:52 - mmengine - INFO - Epoch(train) [113][1580/2119] lr: 4.0000e-03 eta: 7:37:21 time: 0.3546 data_time: 0.0208 memory: 5826 grad_norm: 4.0604 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.1405 loss: 2.1405 2022/10/08 07:11:59 - mmengine - INFO - Epoch(train) [113][1600/2119] lr: 4.0000e-03 eta: 7:37:14 time: 0.3563 data_time: 0.0209 memory: 5826 grad_norm: 4.1387 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3204 loss: 2.3204 2022/10/08 07:12:05 - mmengine - INFO - Epoch(train) [113][1620/2119] lr: 4.0000e-03 eta: 7:37:07 time: 0.3218 data_time: 0.0276 memory: 5826 grad_norm: 4.0824 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.2757 loss: 2.2757 2022/10/08 07:12:12 - mmengine - INFO - Epoch(train) [113][1640/2119] lr: 4.0000e-03 eta: 7:37:00 time: 0.3473 data_time: 0.0265 memory: 5826 grad_norm: 4.0888 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1728 loss: 2.1728 2022/10/08 07:12:20 - mmengine - INFO - Epoch(train) [113][1660/2119] lr: 4.0000e-03 eta: 7:36:53 time: 0.3617 data_time: 0.0218 memory: 5826 grad_norm: 4.0283 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9817 loss: 1.9817 2022/10/08 07:12:25 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 07:12:28 - mmengine - INFO - Epoch(train) [113][1680/2119] lr: 4.0000e-03 eta: 7:36:46 time: 0.3954 data_time: 0.0235 memory: 5826 grad_norm: 4.0391 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0751 loss: 2.0751 2022/10/08 07:12:34 - mmengine - INFO - Epoch(train) [113][1700/2119] lr: 4.0000e-03 eta: 7:36:39 time: 0.3257 data_time: 0.0217 memory: 5826 grad_norm: 4.0951 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9375 loss: 1.9375 2022/10/08 07:12:42 - mmengine - INFO - Epoch(train) [113][1720/2119] lr: 4.0000e-03 eta: 7:36:32 time: 0.3765 data_time: 0.0231 memory: 5826 grad_norm: 4.1680 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0592 loss: 2.0592 2022/10/08 07:12:48 - mmengine - INFO - Epoch(train) [113][1740/2119] lr: 4.0000e-03 eta: 7:36:25 time: 0.3393 data_time: 0.0206 memory: 5826 grad_norm: 4.0691 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0162 loss: 2.0162 2022/10/08 07:12:55 - mmengine - INFO - Epoch(train) [113][1760/2119] lr: 4.0000e-03 eta: 7:36:18 time: 0.3481 data_time: 0.0289 memory: 5826 grad_norm: 4.0250 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.1692 loss: 2.1692 2022/10/08 07:13:02 - mmengine - INFO - Epoch(train) [113][1780/2119] lr: 4.0000e-03 eta: 7:36:11 time: 0.3258 data_time: 0.0218 memory: 5826 grad_norm: 4.1070 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1305 loss: 2.1305 2022/10/08 07:13:10 - mmengine - INFO - Epoch(train) [113][1800/2119] lr: 4.0000e-03 eta: 7:36:05 time: 0.3893 data_time: 0.0244 memory: 5826 grad_norm: 4.0680 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2199 loss: 2.2199 2022/10/08 07:13:17 - mmengine - INFO - Epoch(train) [113][1820/2119] lr: 4.0000e-03 eta: 7:35:58 time: 0.3557 data_time: 0.0255 memory: 5826 grad_norm: 3.9502 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1505 loss: 2.1505 2022/10/08 07:13:24 - mmengine - INFO - Epoch(train) [113][1840/2119] lr: 4.0000e-03 eta: 7:35:51 time: 0.3493 data_time: 0.0187 memory: 5826 grad_norm: 3.9804 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1386 loss: 2.1386 2022/10/08 07:13:31 - mmengine - INFO - Epoch(train) [113][1860/2119] lr: 4.0000e-03 eta: 7:35:44 time: 0.3533 data_time: 0.0210 memory: 5826 grad_norm: 3.9666 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1346 loss: 2.1346 2022/10/08 07:13:38 - mmengine - INFO - Epoch(train) [113][1880/2119] lr: 4.0000e-03 eta: 7:35:37 time: 0.3438 data_time: 0.0231 memory: 5826 grad_norm: 4.0241 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 1.9905 loss: 1.9905 2022/10/08 07:13:45 - mmengine - INFO - Epoch(train) [113][1900/2119] lr: 4.0000e-03 eta: 7:35:30 time: 0.3682 data_time: 0.0188 memory: 5826 grad_norm: 3.9631 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8273 loss: 1.8273 2022/10/08 07:13:52 - mmengine - INFO - Epoch(train) [113][1920/2119] lr: 4.0000e-03 eta: 7:35:23 time: 0.3321 data_time: 0.0177 memory: 5826 grad_norm: 4.0834 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8517 loss: 1.8517 2022/10/08 07:13:59 - mmengine - INFO - Epoch(train) [113][1940/2119] lr: 4.0000e-03 eta: 7:35:16 time: 0.3786 data_time: 0.0214 memory: 5826 grad_norm: 4.1314 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9940 loss: 1.9940 2022/10/08 07:14:07 - mmengine - INFO - Epoch(train) [113][1960/2119] lr: 4.0000e-03 eta: 7:35:09 time: 0.3554 data_time: 0.0276 memory: 5826 grad_norm: 4.0720 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0775 loss: 2.0775 2022/10/08 07:14:14 - mmengine - INFO - Epoch(train) [113][1980/2119] lr: 4.0000e-03 eta: 7:35:03 time: 0.3959 data_time: 0.0198 memory: 5826 grad_norm: 4.0526 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 2.0502 loss: 2.0502 2022/10/08 07:14:22 - mmengine - INFO - Epoch(train) [113][2000/2119] lr: 4.0000e-03 eta: 7:34:56 time: 0.3521 data_time: 0.0239 memory: 5826 grad_norm: 4.0472 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0449 loss: 2.0449 2022/10/08 07:14:29 - mmengine - INFO - Epoch(train) [113][2020/2119] lr: 4.0000e-03 eta: 7:34:49 time: 0.3966 data_time: 0.0219 memory: 5826 grad_norm: 3.9651 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0464 loss: 2.0464 2022/10/08 07:14:36 - mmengine - INFO - Epoch(train) [113][2040/2119] lr: 4.0000e-03 eta: 7:34:42 time: 0.3415 data_time: 0.0160 memory: 5826 grad_norm: 4.0892 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1128 loss: 2.1128 2022/10/08 07:14:43 - mmengine - INFO - Epoch(train) [113][2060/2119] lr: 4.0000e-03 eta: 7:34:35 time: 0.3469 data_time: 0.0217 memory: 5826 grad_norm: 4.0559 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.1204 loss: 2.1204 2022/10/08 07:14:50 - mmengine - INFO - Epoch(train) [113][2080/2119] lr: 4.0000e-03 eta: 7:34:28 time: 0.3307 data_time: 0.0241 memory: 5826 grad_norm: 4.0084 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9599 loss: 1.9599 2022/10/08 07:14:58 - mmengine - INFO - Epoch(train) [113][2100/2119] lr: 4.0000e-03 eta: 7:34:21 time: 0.3838 data_time: 0.0226 memory: 5826 grad_norm: 4.0185 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8939 loss: 1.8939 2022/10/08 07:15:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 07:15:03 - mmengine - INFO - Epoch(train) [113][2119/2119] lr: 4.0000e-03 eta: 7:34:21 time: 0.2950 data_time: 0.0182 memory: 5826 grad_norm: 4.0707 top1_acc: 0.6000 top5_acc: 0.7000 loss_cls: 2.0785 loss: 2.0785 2022/10/08 07:15:13 - mmengine - INFO - Epoch(train) [114][20/2119] lr: 4.0000e-03 eta: 7:34:07 time: 0.4723 data_time: 0.1420 memory: 5826 grad_norm: 4.1241 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9718 loss: 1.9718 2022/10/08 07:15:20 - mmengine - INFO - Epoch(train) [114][40/2119] lr: 4.0000e-03 eta: 7:34:00 time: 0.3572 data_time: 0.0172 memory: 5826 grad_norm: 4.1111 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 2.1444 loss: 2.1444 2022/10/08 07:15:28 - mmengine - INFO - Epoch(train) [114][60/2119] lr: 4.0000e-03 eta: 7:33:53 time: 0.4028 data_time: 0.0250 memory: 5826 grad_norm: 4.0960 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0893 loss: 2.0893 2022/10/08 07:15:34 - mmengine - INFO - Epoch(train) [114][80/2119] lr: 4.0000e-03 eta: 7:33:46 time: 0.3101 data_time: 0.0184 memory: 5826 grad_norm: 4.0941 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.4027 loss: 2.4027 2022/10/08 07:15:42 - mmengine - INFO - Epoch(train) [114][100/2119] lr: 4.0000e-03 eta: 7:33:39 time: 0.3856 data_time: 0.0254 memory: 5826 grad_norm: 4.0114 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2000 loss: 2.2000 2022/10/08 07:15:48 - mmengine - INFO - Epoch(train) [114][120/2119] lr: 4.0000e-03 eta: 7:33:32 time: 0.3222 data_time: 0.0208 memory: 5826 grad_norm: 4.0481 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.9306 loss: 1.9306 2022/10/08 07:15:57 - mmengine - INFO - Epoch(train) [114][140/2119] lr: 4.0000e-03 eta: 7:33:26 time: 0.4523 data_time: 0.0200 memory: 5826 grad_norm: 4.0143 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9989 loss: 1.9989 2022/10/08 07:16:03 - mmengine - INFO - Epoch(train) [114][160/2119] lr: 4.0000e-03 eta: 7:33:19 time: 0.3054 data_time: 0.0218 memory: 5826 grad_norm: 4.0352 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0493 loss: 2.0493 2022/10/08 07:16:11 - mmengine - INFO - Epoch(train) [114][180/2119] lr: 4.0000e-03 eta: 7:33:12 time: 0.3664 data_time: 0.0227 memory: 5826 grad_norm: 4.0106 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0992 loss: 2.0992 2022/10/08 07:16:19 - mmengine - INFO - Epoch(train) [114][200/2119] lr: 4.0000e-03 eta: 7:33:05 time: 0.4053 data_time: 0.0176 memory: 5826 grad_norm: 4.0332 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0265 loss: 2.0265 2022/10/08 07:16:26 - mmengine - INFO - Epoch(train) [114][220/2119] lr: 4.0000e-03 eta: 7:32:58 time: 0.3505 data_time: 0.0192 memory: 5826 grad_norm: 3.9835 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9097 loss: 1.9097 2022/10/08 07:16:32 - mmengine - INFO - Epoch(train) [114][240/2119] lr: 4.0000e-03 eta: 7:32:51 time: 0.2894 data_time: 0.0201 memory: 5826 grad_norm: 4.0554 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1008 loss: 2.1008 2022/10/08 07:16:40 - mmengine - INFO - Epoch(train) [114][260/2119] lr: 4.0000e-03 eta: 7:32:44 time: 0.3967 data_time: 0.0221 memory: 5826 grad_norm: 4.0619 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0403 loss: 2.0403 2022/10/08 07:16:47 - mmengine - INFO - Epoch(train) [114][280/2119] lr: 4.0000e-03 eta: 7:32:37 time: 0.3411 data_time: 0.0210 memory: 5826 grad_norm: 4.0478 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1625 loss: 2.1625 2022/10/08 07:16:54 - mmengine - INFO - Epoch(train) [114][300/2119] lr: 4.0000e-03 eta: 7:32:30 time: 0.3680 data_time: 0.0193 memory: 5826 grad_norm: 4.0533 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.9838 loss: 1.9838 2022/10/08 07:17:01 - mmengine - INFO - Epoch(train) [114][320/2119] lr: 4.0000e-03 eta: 7:32:23 time: 0.3526 data_time: 0.0201 memory: 5826 grad_norm: 4.0742 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7725 loss: 1.7725 2022/10/08 07:17:08 - mmengine - INFO - Epoch(train) [114][340/2119] lr: 4.0000e-03 eta: 7:32:17 time: 0.3571 data_time: 0.0214 memory: 5826 grad_norm: 4.0483 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.0287 loss: 2.0287 2022/10/08 07:17:15 - mmengine - INFO - Epoch(train) [114][360/2119] lr: 4.0000e-03 eta: 7:32:09 time: 0.3226 data_time: 0.0237 memory: 5826 grad_norm: 4.0888 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8971 loss: 1.8971 2022/10/08 07:17:22 - mmengine - INFO - Epoch(train) [114][380/2119] lr: 4.0000e-03 eta: 7:32:03 time: 0.3763 data_time: 0.0269 memory: 5826 grad_norm: 4.0818 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9180 loss: 1.9180 2022/10/08 07:17:29 - mmengine - INFO - Epoch(train) [114][400/2119] lr: 4.0000e-03 eta: 7:31:56 time: 0.3481 data_time: 0.0196 memory: 5826 grad_norm: 4.0631 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.2822 loss: 2.2822 2022/10/08 07:17:37 - mmengine - INFO - Epoch(train) [114][420/2119] lr: 4.0000e-03 eta: 7:31:49 time: 0.3822 data_time: 0.0308 memory: 5826 grad_norm: 4.0656 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.2029 loss: 2.2029 2022/10/08 07:17:44 - mmengine - INFO - Epoch(train) [114][440/2119] lr: 4.0000e-03 eta: 7:31:42 time: 0.3511 data_time: 0.0236 memory: 5826 grad_norm: 4.0491 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.1927 loss: 2.1927 2022/10/08 07:17:51 - mmengine - INFO - Epoch(train) [114][460/2119] lr: 4.0000e-03 eta: 7:31:35 time: 0.3723 data_time: 0.0224 memory: 5826 grad_norm: 4.1055 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1133 loss: 2.1133 2022/10/08 07:17:58 - mmengine - INFO - Epoch(train) [114][480/2119] lr: 4.0000e-03 eta: 7:31:28 time: 0.3151 data_time: 0.0263 memory: 5826 grad_norm: 4.0882 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9823 loss: 1.9823 2022/10/08 07:18:05 - mmengine - INFO - Epoch(train) [114][500/2119] lr: 4.0000e-03 eta: 7:31:21 time: 0.3641 data_time: 0.0276 memory: 5826 grad_norm: 4.1244 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.3392 loss: 2.3392 2022/10/08 07:18:11 - mmengine - INFO - Epoch(train) [114][520/2119] lr: 4.0000e-03 eta: 7:31:14 time: 0.3075 data_time: 0.0170 memory: 5826 grad_norm: 4.0472 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2033 loss: 2.2033 2022/10/08 07:18:19 - mmengine - INFO - Epoch(train) [114][540/2119] lr: 4.0000e-03 eta: 7:31:08 time: 0.4139 data_time: 0.0259 memory: 5826 grad_norm: 4.0891 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9407 loss: 1.9407 2022/10/08 07:18:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 07:18:26 - mmengine - INFO - Epoch(train) [114][560/2119] lr: 4.0000e-03 eta: 7:31:00 time: 0.3280 data_time: 0.0229 memory: 5826 grad_norm: 4.0371 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8216 loss: 1.8216 2022/10/08 07:18:33 - mmengine - INFO - Epoch(train) [114][580/2119] lr: 4.0000e-03 eta: 7:30:54 time: 0.3681 data_time: 0.0249 memory: 5826 grad_norm: 4.0532 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0848 loss: 2.0848 2022/10/08 07:18:40 - mmengine - INFO - Epoch(train) [114][600/2119] lr: 4.0000e-03 eta: 7:30:47 time: 0.3488 data_time: 0.0191 memory: 5826 grad_norm: 4.0145 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.8530 loss: 1.8530 2022/10/08 07:18:47 - mmengine - INFO - Epoch(train) [114][620/2119] lr: 4.0000e-03 eta: 7:30:40 time: 0.3451 data_time: 0.0304 memory: 5826 grad_norm: 4.0578 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2595 loss: 2.2595 2022/10/08 07:18:53 - mmengine - INFO - Epoch(train) [114][640/2119] lr: 4.0000e-03 eta: 7:30:33 time: 0.3201 data_time: 0.0244 memory: 5826 grad_norm: 4.0826 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0361 loss: 2.0361 2022/10/08 07:19:01 - mmengine - INFO - Epoch(train) [114][660/2119] lr: 4.0000e-03 eta: 7:30:26 time: 0.3726 data_time: 0.0232 memory: 5826 grad_norm: 4.0498 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0708 loss: 2.0708 2022/10/08 07:19:08 - mmengine - INFO - Epoch(train) [114][680/2119] lr: 4.0000e-03 eta: 7:30:19 time: 0.3647 data_time: 0.0241 memory: 5826 grad_norm: 4.0122 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0473 loss: 2.0473 2022/10/08 07:19:17 - mmengine - INFO - Epoch(train) [114][700/2119] lr: 4.0000e-03 eta: 7:30:13 time: 0.4386 data_time: 0.0209 memory: 5826 grad_norm: 3.9678 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.2264 loss: 2.2264 2022/10/08 07:19:23 - mmengine - INFO - Epoch(train) [114][720/2119] lr: 4.0000e-03 eta: 7:30:05 time: 0.2978 data_time: 0.0270 memory: 5826 grad_norm: 4.0824 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9207 loss: 1.9207 2022/10/08 07:19:30 - mmengine - INFO - Epoch(train) [114][740/2119] lr: 4.0000e-03 eta: 7:29:58 time: 0.3607 data_time: 0.0272 memory: 5826 grad_norm: 4.1188 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9835 loss: 1.9835 2022/10/08 07:19:37 - mmengine - INFO - Epoch(train) [114][760/2119] lr: 4.0000e-03 eta: 7:29:51 time: 0.3225 data_time: 0.0198 memory: 5826 grad_norm: 4.0451 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.6884 loss: 1.6884 2022/10/08 07:19:44 - mmengine - INFO - Epoch(train) [114][780/2119] lr: 4.0000e-03 eta: 7:29:45 time: 0.3777 data_time: 0.0200 memory: 5826 grad_norm: 4.0735 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9682 loss: 1.9682 2022/10/08 07:19:51 - mmengine - INFO - Epoch(train) [114][800/2119] lr: 4.0000e-03 eta: 7:29:38 time: 0.3426 data_time: 0.0209 memory: 5826 grad_norm: 4.0641 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9903 loss: 1.9903 2022/10/08 07:19:59 - mmengine - INFO - Epoch(train) [114][820/2119] lr: 4.0000e-03 eta: 7:29:31 time: 0.3982 data_time: 0.0241 memory: 5826 grad_norm: 4.0186 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0330 loss: 2.0330 2022/10/08 07:20:06 - mmengine - INFO - Epoch(train) [114][840/2119] lr: 4.0000e-03 eta: 7:29:24 time: 0.3551 data_time: 0.0197 memory: 5826 grad_norm: 4.0810 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0969 loss: 2.0969 2022/10/08 07:20:14 - mmengine - INFO - Epoch(train) [114][860/2119] lr: 4.0000e-03 eta: 7:29:17 time: 0.3756 data_time: 0.0242 memory: 5826 grad_norm: 4.1294 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9870 loss: 1.9870 2022/10/08 07:20:21 - mmengine - INFO - Epoch(train) [114][880/2119] lr: 4.0000e-03 eta: 7:29:11 time: 0.3779 data_time: 0.0221 memory: 5826 grad_norm: 4.0348 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0260 loss: 2.0260 2022/10/08 07:20:29 - mmengine - INFO - Epoch(train) [114][900/2119] lr: 4.0000e-03 eta: 7:29:04 time: 0.3725 data_time: 0.0192 memory: 5826 grad_norm: 4.1512 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.1640 loss: 2.1640 2022/10/08 07:20:35 - mmengine - INFO - Epoch(train) [114][920/2119] lr: 4.0000e-03 eta: 7:28:57 time: 0.3348 data_time: 0.0200 memory: 5826 grad_norm: 4.0733 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0619 loss: 2.0619 2022/10/08 07:20:43 - mmengine - INFO - Epoch(train) [114][940/2119] lr: 4.0000e-03 eta: 7:28:50 time: 0.3735 data_time: 0.0241 memory: 5826 grad_norm: 4.0701 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8266 loss: 1.8266 2022/10/08 07:20:49 - mmengine - INFO - Epoch(train) [114][960/2119] lr: 4.0000e-03 eta: 7:28:43 time: 0.3211 data_time: 0.0210 memory: 5826 grad_norm: 4.0968 top1_acc: 0.3750 top5_acc: 0.9375 loss_cls: 1.9756 loss: 1.9756 2022/10/08 07:20:58 - mmengine - INFO - Epoch(train) [114][980/2119] lr: 4.0000e-03 eta: 7:28:36 time: 0.4237 data_time: 0.0271 memory: 5826 grad_norm: 3.9908 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9618 loss: 1.9618 2022/10/08 07:21:03 - mmengine - INFO - Epoch(train) [114][1000/2119] lr: 4.0000e-03 eta: 7:28:29 time: 0.2742 data_time: 0.0262 memory: 5826 grad_norm: 4.0778 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0347 loss: 2.0347 2022/10/08 07:21:11 - mmengine - INFO - Epoch(train) [114][1020/2119] lr: 4.0000e-03 eta: 7:28:22 time: 0.3706 data_time: 0.0290 memory: 5826 grad_norm: 4.0458 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.1243 loss: 2.1243 2022/10/08 07:21:19 - mmengine - INFO - Epoch(train) [114][1040/2119] lr: 4.0000e-03 eta: 7:28:16 time: 0.4026 data_time: 0.0249 memory: 5826 grad_norm: 4.0625 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9668 loss: 1.9668 2022/10/08 07:21:26 - mmengine - INFO - Epoch(train) [114][1060/2119] lr: 4.0000e-03 eta: 7:28:09 time: 0.3649 data_time: 0.0190 memory: 5826 grad_norm: 4.0731 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0162 loss: 2.0162 2022/10/08 07:21:32 - mmengine - INFO - Epoch(train) [114][1080/2119] lr: 4.0000e-03 eta: 7:28:02 time: 0.3147 data_time: 0.0229 memory: 5826 grad_norm: 3.9424 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9207 loss: 1.9207 2022/10/08 07:21:41 - mmengine - INFO - Epoch(train) [114][1100/2119] lr: 4.0000e-03 eta: 7:27:55 time: 0.4249 data_time: 0.0260 memory: 5826 grad_norm: 4.0737 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9137 loss: 1.9137 2022/10/08 07:21:47 - mmengine - INFO - Epoch(train) [114][1120/2119] lr: 4.0000e-03 eta: 7:27:48 time: 0.3221 data_time: 0.0199 memory: 5826 grad_norm: 4.0981 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9889 loss: 1.9889 2022/10/08 07:21:55 - mmengine - INFO - Epoch(train) [114][1140/2119] lr: 4.0000e-03 eta: 7:27:41 time: 0.3692 data_time: 0.0224 memory: 5826 grad_norm: 4.0146 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1522 loss: 2.1522 2022/10/08 07:22:02 - mmengine - INFO - Epoch(train) [114][1160/2119] lr: 4.0000e-03 eta: 7:27:34 time: 0.3659 data_time: 0.0209 memory: 5826 grad_norm: 4.0802 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0523 loss: 2.0523 2022/10/08 07:22:08 - mmengine - INFO - Epoch(train) [114][1180/2119] lr: 4.0000e-03 eta: 7:27:27 time: 0.3108 data_time: 0.0239 memory: 5826 grad_norm: 4.0290 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9472 loss: 1.9472 2022/10/08 07:22:16 - mmengine - INFO - Epoch(train) [114][1200/2119] lr: 4.0000e-03 eta: 7:27:20 time: 0.3643 data_time: 0.0201 memory: 5826 grad_norm: 4.0586 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0432 loss: 2.0432 2022/10/08 07:22:23 - mmengine - INFO - Epoch(train) [114][1220/2119] lr: 4.0000e-03 eta: 7:27:13 time: 0.3640 data_time: 0.0211 memory: 5826 grad_norm: 4.1530 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.3140 loss: 2.3140 2022/10/08 07:22:29 - mmengine - INFO - Epoch(train) [114][1240/2119] lr: 4.0000e-03 eta: 7:27:06 time: 0.3304 data_time: 0.0284 memory: 5826 grad_norm: 4.0422 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0537 loss: 2.0537 2022/10/08 07:22:38 - mmengine - INFO - Epoch(train) [114][1260/2119] lr: 4.0000e-03 eta: 7:27:00 time: 0.4125 data_time: 0.0213 memory: 5826 grad_norm: 4.1537 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1394 loss: 2.1394 2022/10/08 07:22:44 - mmengine - INFO - Epoch(train) [114][1280/2119] lr: 4.0000e-03 eta: 7:26:53 time: 0.3057 data_time: 0.0210 memory: 5826 grad_norm: 4.1475 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.9686 loss: 1.9686 2022/10/08 07:22:51 - mmengine - INFO - Epoch(train) [114][1300/2119] lr: 4.0000e-03 eta: 7:26:46 time: 0.3540 data_time: 0.0210 memory: 5826 grad_norm: 3.9843 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8890 loss: 1.8890 2022/10/08 07:22:57 - mmengine - INFO - Epoch(train) [114][1320/2119] lr: 4.0000e-03 eta: 7:26:39 time: 0.3230 data_time: 0.0268 memory: 5826 grad_norm: 4.1530 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.3754 loss: 2.3754 2022/10/08 07:23:05 - mmengine - INFO - Epoch(train) [114][1340/2119] lr: 4.0000e-03 eta: 7:26:32 time: 0.3699 data_time: 0.0223 memory: 5826 grad_norm: 4.0835 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0755 loss: 2.0755 2022/10/08 07:23:12 - mmengine - INFO - Epoch(train) [114][1360/2119] lr: 4.0000e-03 eta: 7:26:25 time: 0.3398 data_time: 0.0173 memory: 5826 grad_norm: 3.9722 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9083 loss: 1.9083 2022/10/08 07:23:20 - mmengine - INFO - Epoch(train) [114][1380/2119] lr: 4.0000e-03 eta: 7:26:18 time: 0.3953 data_time: 0.0241 memory: 5826 grad_norm: 4.0888 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1263 loss: 2.1263 2022/10/08 07:23:26 - mmengine - INFO - Epoch(train) [114][1400/2119] lr: 4.0000e-03 eta: 7:26:11 time: 0.3304 data_time: 0.0230 memory: 5826 grad_norm: 4.0236 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0090 loss: 2.0090 2022/10/08 07:23:33 - mmengine - INFO - Epoch(train) [114][1420/2119] lr: 4.0000e-03 eta: 7:26:04 time: 0.3279 data_time: 0.0205 memory: 5826 grad_norm: 4.0694 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9523 loss: 1.9523 2022/10/08 07:23:40 - mmengine - INFO - Epoch(train) [114][1440/2119] lr: 4.0000e-03 eta: 7:25:57 time: 0.3465 data_time: 0.0285 memory: 5826 grad_norm: 4.0874 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0703 loss: 2.0703 2022/10/08 07:23:47 - mmengine - INFO - Epoch(train) [114][1460/2119] lr: 4.0000e-03 eta: 7:25:50 time: 0.3689 data_time: 0.0245 memory: 5826 grad_norm: 4.0735 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9848 loss: 1.9848 2022/10/08 07:23:54 - mmengine - INFO - Epoch(train) [114][1480/2119] lr: 4.0000e-03 eta: 7:25:43 time: 0.3250 data_time: 0.0220 memory: 5826 grad_norm: 4.0556 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8646 loss: 1.8646 2022/10/08 07:24:01 - mmengine - INFO - Epoch(train) [114][1500/2119] lr: 4.0000e-03 eta: 7:25:36 time: 0.3733 data_time: 0.0279 memory: 5826 grad_norm: 4.1133 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0192 loss: 2.0192 2022/10/08 07:24:07 - mmengine - INFO - Epoch(train) [114][1520/2119] lr: 4.0000e-03 eta: 7:25:29 time: 0.3175 data_time: 0.0200 memory: 5826 grad_norm: 4.0314 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9069 loss: 1.9069 2022/10/08 07:24:15 - mmengine - INFO - Epoch(train) [114][1540/2119] lr: 4.0000e-03 eta: 7:25:23 time: 0.3955 data_time: 0.0196 memory: 5826 grad_norm: 4.0327 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9945 loss: 1.9945 2022/10/08 07:24:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 07:24:22 - mmengine - INFO - Epoch(train) [114][1560/2119] lr: 4.0000e-03 eta: 7:25:15 time: 0.3268 data_time: 0.0263 memory: 5826 grad_norm: 4.0666 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0423 loss: 2.0423 2022/10/08 07:24:29 - mmengine - INFO - Epoch(train) [114][1580/2119] lr: 4.0000e-03 eta: 7:25:09 time: 0.3690 data_time: 0.0209 memory: 5826 grad_norm: 4.1185 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9344 loss: 1.9344 2022/10/08 07:24:36 - mmengine - INFO - Epoch(train) [114][1600/2119] lr: 4.0000e-03 eta: 7:25:02 time: 0.3424 data_time: 0.0202 memory: 5826 grad_norm: 4.0630 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0679 loss: 2.0679 2022/10/08 07:24:44 - mmengine - INFO - Epoch(train) [114][1620/2119] lr: 4.0000e-03 eta: 7:24:55 time: 0.3818 data_time: 0.0209 memory: 5826 grad_norm: 4.0862 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 1.8745 loss: 1.8745 2022/10/08 07:24:50 - mmengine - INFO - Epoch(train) [114][1640/2119] lr: 4.0000e-03 eta: 7:24:48 time: 0.3183 data_time: 0.0204 memory: 5826 grad_norm: 4.1629 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0988 loss: 2.0988 2022/10/08 07:24:58 - mmengine - INFO - Epoch(train) [114][1660/2119] lr: 4.0000e-03 eta: 7:24:41 time: 0.4053 data_time: 0.0242 memory: 5826 grad_norm: 4.0563 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2340 loss: 2.2340 2022/10/08 07:25:04 - mmengine - INFO - Epoch(train) [114][1680/2119] lr: 4.0000e-03 eta: 7:24:34 time: 0.2790 data_time: 0.0244 memory: 5826 grad_norm: 4.0901 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8958 loss: 1.8958 2022/10/08 07:25:11 - mmengine - INFO - Epoch(train) [114][1700/2119] lr: 4.0000e-03 eta: 7:24:27 time: 0.3737 data_time: 0.0238 memory: 5826 grad_norm: 4.1941 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2351 loss: 2.2351 2022/10/08 07:25:18 - mmengine - INFO - Epoch(train) [114][1720/2119] lr: 4.0000e-03 eta: 7:24:20 time: 0.3282 data_time: 0.0246 memory: 5826 grad_norm: 4.0489 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1451 loss: 2.1451 2022/10/08 07:25:26 - mmengine - INFO - Epoch(train) [114][1740/2119] lr: 4.0000e-03 eta: 7:24:13 time: 0.3975 data_time: 0.0212 memory: 5826 grad_norm: 4.0785 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0702 loss: 2.0702 2022/10/08 07:25:33 - mmengine - INFO - Epoch(train) [114][1760/2119] lr: 4.0000e-03 eta: 7:24:06 time: 0.3469 data_time: 0.0225 memory: 5826 grad_norm: 4.0144 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9611 loss: 1.9611 2022/10/08 07:25:40 - mmengine - INFO - Epoch(train) [114][1780/2119] lr: 4.0000e-03 eta: 7:24:00 time: 0.3741 data_time: 0.0212 memory: 5826 grad_norm: 4.0730 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1427 loss: 2.1427 2022/10/08 07:25:47 - mmengine - INFO - Epoch(train) [114][1800/2119] lr: 4.0000e-03 eta: 7:23:53 time: 0.3398 data_time: 0.0216 memory: 5826 grad_norm: 4.1155 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.2468 loss: 2.2468 2022/10/08 07:25:54 - mmengine - INFO - Epoch(train) [114][1820/2119] lr: 4.0000e-03 eta: 7:23:46 time: 0.3529 data_time: 0.0226 memory: 5826 grad_norm: 3.9932 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0320 loss: 2.0320 2022/10/08 07:26:01 - mmengine - INFO - Epoch(train) [114][1840/2119] lr: 4.0000e-03 eta: 7:23:39 time: 0.3271 data_time: 0.0249 memory: 5826 grad_norm: 4.1540 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9952 loss: 1.9952 2022/10/08 07:26:08 - mmengine - INFO - Epoch(train) [114][1860/2119] lr: 4.0000e-03 eta: 7:23:32 time: 0.3858 data_time: 0.0193 memory: 5826 grad_norm: 4.0438 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9722 loss: 1.9722 2022/10/08 07:26:16 - mmengine - INFO - Epoch(train) [114][1880/2119] lr: 4.0000e-03 eta: 7:23:25 time: 0.3631 data_time: 0.0240 memory: 5826 grad_norm: 4.0798 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0244 loss: 2.0244 2022/10/08 07:26:23 - mmengine - INFO - Epoch(train) [114][1900/2119] lr: 4.0000e-03 eta: 7:23:18 time: 0.3487 data_time: 0.0220 memory: 5826 grad_norm: 4.1289 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1381 loss: 2.1381 2022/10/08 07:26:29 - mmengine - INFO - Epoch(train) [114][1920/2119] lr: 4.0000e-03 eta: 7:23:11 time: 0.3379 data_time: 0.0359 memory: 5826 grad_norm: 4.1283 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1050 loss: 2.1050 2022/10/08 07:26:37 - mmengine - INFO - Epoch(train) [114][1940/2119] lr: 4.0000e-03 eta: 7:23:04 time: 0.3611 data_time: 0.0202 memory: 5826 grad_norm: 4.1299 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1914 loss: 2.1914 2022/10/08 07:26:44 - mmengine - INFO - Epoch(train) [114][1960/2119] lr: 4.0000e-03 eta: 7:22:57 time: 0.3839 data_time: 0.0210 memory: 5826 grad_norm: 4.1392 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.8439 loss: 1.8439 2022/10/08 07:26:51 - mmengine - INFO - Epoch(train) [114][1980/2119] lr: 4.0000e-03 eta: 7:22:50 time: 0.3264 data_time: 0.0234 memory: 5826 grad_norm: 4.0398 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6436 loss: 1.6436 2022/10/08 07:26:58 - mmengine - INFO - Epoch(train) [114][2000/2119] lr: 4.0000e-03 eta: 7:22:43 time: 0.3555 data_time: 0.0203 memory: 5826 grad_norm: 4.1562 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 2.0336 loss: 2.0336 2022/10/08 07:27:05 - mmengine - INFO - Epoch(train) [114][2020/2119] lr: 4.0000e-03 eta: 7:22:36 time: 0.3572 data_time: 0.0253 memory: 5826 grad_norm: 4.0315 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0469 loss: 2.0469 2022/10/08 07:27:12 - mmengine - INFO - Epoch(train) [114][2040/2119] lr: 4.0000e-03 eta: 7:22:29 time: 0.3382 data_time: 0.0234 memory: 5826 grad_norm: 4.1213 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0549 loss: 2.0549 2022/10/08 07:27:19 - mmengine - INFO - Epoch(train) [114][2060/2119] lr: 4.0000e-03 eta: 7:22:23 time: 0.3775 data_time: 0.0223 memory: 5826 grad_norm: 4.1055 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9378 loss: 1.9378 2022/10/08 07:27:26 - mmengine - INFO - Epoch(train) [114][2080/2119] lr: 4.0000e-03 eta: 7:22:16 time: 0.3336 data_time: 0.0237 memory: 5826 grad_norm: 4.0556 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8944 loss: 1.8944 2022/10/08 07:27:33 - mmengine - INFO - Epoch(train) [114][2100/2119] lr: 4.0000e-03 eta: 7:22:09 time: 0.3468 data_time: 0.0254 memory: 5826 grad_norm: 4.0954 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2363 loss: 2.2363 2022/10/08 07:27:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 07:27:40 - mmengine - INFO - Epoch(train) [114][2119/2119] lr: 4.0000e-03 eta: 7:22:09 time: 0.3438 data_time: 0.0233 memory: 5826 grad_norm: 4.1457 top1_acc: 0.5000 top5_acc: 0.8000 loss_cls: 2.0558 loss: 2.0558 2022/10/08 07:27:50 - mmengine - INFO - Epoch(train) [115][20/2119] lr: 4.0000e-03 eta: 7:21:54 time: 0.4893 data_time: 0.1158 memory: 5826 grad_norm: 4.1342 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0401 loss: 2.0401 2022/10/08 07:27:56 - mmengine - INFO - Epoch(train) [115][40/2119] lr: 4.0000e-03 eta: 7:21:47 time: 0.3267 data_time: 0.0231 memory: 5826 grad_norm: 4.0698 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9758 loss: 1.9758 2022/10/08 07:28:04 - mmengine - INFO - Epoch(train) [115][60/2119] lr: 4.0000e-03 eta: 7:21:40 time: 0.3890 data_time: 0.0192 memory: 5826 grad_norm: 4.0683 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9625 loss: 1.9625 2022/10/08 07:28:10 - mmengine - INFO - Epoch(train) [115][80/2119] lr: 4.0000e-03 eta: 7:21:33 time: 0.3285 data_time: 0.0249 memory: 5826 grad_norm: 4.1952 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1187 loss: 2.1187 2022/10/08 07:28:18 - mmengine - INFO - Epoch(train) [115][100/2119] lr: 4.0000e-03 eta: 7:21:26 time: 0.3818 data_time: 0.0233 memory: 5826 grad_norm: 4.1523 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0386 loss: 2.0386 2022/10/08 07:28:25 - mmengine - INFO - Epoch(train) [115][120/2119] lr: 4.0000e-03 eta: 7:21:19 time: 0.3324 data_time: 0.0259 memory: 5826 grad_norm: 4.1336 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.1361 loss: 2.1361 2022/10/08 07:28:32 - mmengine - INFO - Epoch(train) [115][140/2119] lr: 4.0000e-03 eta: 7:21:13 time: 0.3797 data_time: 0.0191 memory: 5826 grad_norm: 3.9997 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8105 loss: 1.8105 2022/10/08 07:28:39 - mmengine - INFO - Epoch(train) [115][160/2119] lr: 4.0000e-03 eta: 7:21:06 time: 0.3519 data_time: 0.0223 memory: 5826 grad_norm: 4.1517 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7589 loss: 1.7589 2022/10/08 07:28:47 - mmengine - INFO - Epoch(train) [115][180/2119] lr: 4.0000e-03 eta: 7:20:59 time: 0.3652 data_time: 0.0257 memory: 5826 grad_norm: 4.1530 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0739 loss: 2.0739 2022/10/08 07:28:53 - mmengine - INFO - Epoch(train) [115][200/2119] lr: 4.0000e-03 eta: 7:20:52 time: 0.3264 data_time: 0.0215 memory: 5826 grad_norm: 4.0523 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1810 loss: 2.1810 2022/10/08 07:29:00 - mmengine - INFO - Epoch(train) [115][220/2119] lr: 4.0000e-03 eta: 7:20:45 time: 0.3600 data_time: 0.0293 memory: 5826 grad_norm: 4.1856 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8744 loss: 1.8744 2022/10/08 07:29:08 - mmengine - INFO - Epoch(train) [115][240/2119] lr: 4.0000e-03 eta: 7:20:38 time: 0.3634 data_time: 0.0220 memory: 5826 grad_norm: 4.1410 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9646 loss: 1.9646 2022/10/08 07:29:15 - mmengine - INFO - Epoch(train) [115][260/2119] lr: 4.0000e-03 eta: 7:20:31 time: 0.3818 data_time: 0.0207 memory: 5826 grad_norm: 4.0498 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8890 loss: 1.8890 2022/10/08 07:29:22 - mmengine - INFO - Epoch(train) [115][280/2119] lr: 4.0000e-03 eta: 7:20:24 time: 0.3384 data_time: 0.0254 memory: 5826 grad_norm: 4.1036 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.3221 loss: 2.3221 2022/10/08 07:29:29 - mmengine - INFO - Epoch(train) [115][300/2119] lr: 4.0000e-03 eta: 7:20:17 time: 0.3664 data_time: 0.0215 memory: 5826 grad_norm: 4.0227 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 1.7533 loss: 1.7533 2022/10/08 07:29:36 - mmengine - INFO - Epoch(train) [115][320/2119] lr: 4.0000e-03 eta: 7:20:10 time: 0.3151 data_time: 0.0195 memory: 5826 grad_norm: 4.0010 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9732 loss: 1.9732 2022/10/08 07:29:44 - mmengine - INFO - Epoch(train) [115][340/2119] lr: 4.0000e-03 eta: 7:20:04 time: 0.3972 data_time: 0.0231 memory: 5826 grad_norm: 4.0583 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0148 loss: 2.0148 2022/10/08 07:29:50 - mmengine - INFO - Epoch(train) [115][360/2119] lr: 4.0000e-03 eta: 7:19:56 time: 0.3209 data_time: 0.0211 memory: 5826 grad_norm: 4.0322 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.7421 loss: 1.7421 2022/10/08 07:29:59 - mmengine - INFO - Epoch(train) [115][380/2119] lr: 4.0000e-03 eta: 7:19:50 time: 0.4431 data_time: 0.0220 memory: 5826 grad_norm: 4.0417 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9361 loss: 1.9361 2022/10/08 07:30:06 - mmengine - INFO - Epoch(train) [115][400/2119] lr: 4.0000e-03 eta: 7:19:43 time: 0.3548 data_time: 0.0195 memory: 5826 grad_norm: 4.0401 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0299 loss: 2.0299 2022/10/08 07:30:14 - mmengine - INFO - Epoch(train) [115][420/2119] lr: 4.0000e-03 eta: 7:19:36 time: 0.3684 data_time: 0.0180 memory: 5826 grad_norm: 4.1161 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.2345 loss: 2.2345 2022/10/08 07:30:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 07:30:21 - mmengine - INFO - Epoch(train) [115][440/2119] lr: 4.0000e-03 eta: 7:19:29 time: 0.3485 data_time: 0.0241 memory: 5826 grad_norm: 4.1793 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1594 loss: 2.1594 2022/10/08 07:30:28 - mmengine - INFO - Epoch(train) [115][460/2119] lr: 4.0000e-03 eta: 7:19:23 time: 0.3514 data_time: 0.0221 memory: 5826 grad_norm: 4.1117 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0201 loss: 2.0201 2022/10/08 07:30:35 - mmengine - INFO - Epoch(train) [115][480/2119] lr: 4.0000e-03 eta: 7:19:16 time: 0.3570 data_time: 0.0204 memory: 5826 grad_norm: 4.0909 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1844 loss: 2.1844 2022/10/08 07:30:43 - mmengine - INFO - Epoch(train) [115][500/2119] lr: 4.0000e-03 eta: 7:19:09 time: 0.3926 data_time: 0.0267 memory: 5826 grad_norm: 4.1785 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.2531 loss: 2.2531 2022/10/08 07:30:50 - mmengine - INFO - Epoch(train) [115][520/2119] lr: 4.0000e-03 eta: 7:19:02 time: 0.3651 data_time: 0.0216 memory: 5826 grad_norm: 4.1314 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.2838 loss: 2.2838 2022/10/08 07:30:56 - mmengine - INFO - Epoch(train) [115][540/2119] lr: 4.0000e-03 eta: 7:18:55 time: 0.3269 data_time: 0.0224 memory: 5826 grad_norm: 4.0692 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 1.9459 loss: 1.9459 2022/10/08 07:31:03 - mmengine - INFO - Epoch(train) [115][560/2119] lr: 4.0000e-03 eta: 7:18:48 time: 0.3367 data_time: 0.0244 memory: 5826 grad_norm: 4.1436 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9264 loss: 1.9264 2022/10/08 07:31:11 - mmengine - INFO - Epoch(train) [115][580/2119] lr: 4.0000e-03 eta: 7:18:41 time: 0.3836 data_time: 0.0254 memory: 5826 grad_norm: 4.0749 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0445 loss: 2.0445 2022/10/08 07:31:18 - mmengine - INFO - Epoch(train) [115][600/2119] lr: 4.0000e-03 eta: 7:18:34 time: 0.3553 data_time: 0.0227 memory: 5826 grad_norm: 4.1521 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2944 loss: 2.2944 2022/10/08 07:31:26 - mmengine - INFO - Epoch(train) [115][620/2119] lr: 4.0000e-03 eta: 7:18:28 time: 0.3810 data_time: 0.0239 memory: 5826 grad_norm: 4.1287 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1364 loss: 2.1364 2022/10/08 07:31:32 - mmengine - INFO - Epoch(train) [115][640/2119] lr: 4.0000e-03 eta: 7:18:20 time: 0.3187 data_time: 0.0233 memory: 5826 grad_norm: 4.1319 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9865 loss: 1.9865 2022/10/08 07:31:39 - mmengine - INFO - Epoch(train) [115][660/2119] lr: 4.0000e-03 eta: 7:18:14 time: 0.3620 data_time: 0.0260 memory: 5826 grad_norm: 4.0846 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9877 loss: 1.9877 2022/10/08 07:31:46 - mmengine - INFO - Epoch(train) [115][680/2119] lr: 4.0000e-03 eta: 7:18:07 time: 0.3585 data_time: 0.0257 memory: 5826 grad_norm: 4.1024 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8530 loss: 1.8530 2022/10/08 07:31:54 - mmengine - INFO - Epoch(train) [115][700/2119] lr: 4.0000e-03 eta: 7:18:00 time: 0.3794 data_time: 0.0255 memory: 5826 grad_norm: 4.1537 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1162 loss: 2.1162 2022/10/08 07:32:00 - mmengine - INFO - Epoch(train) [115][720/2119] lr: 4.0000e-03 eta: 7:17:53 time: 0.3057 data_time: 0.0231 memory: 5826 grad_norm: 4.0886 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9096 loss: 1.9096 2022/10/08 07:32:08 - mmengine - INFO - Epoch(train) [115][740/2119] lr: 4.0000e-03 eta: 7:17:46 time: 0.4000 data_time: 0.0252 memory: 5826 grad_norm: 4.1699 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.8821 loss: 1.8821 2022/10/08 07:32:14 - mmengine - INFO - Epoch(train) [115][760/2119] lr: 4.0000e-03 eta: 7:17:39 time: 0.2906 data_time: 0.0226 memory: 5826 grad_norm: 4.1681 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0268 loss: 2.0268 2022/10/08 07:32:22 - mmengine - INFO - Epoch(train) [115][780/2119] lr: 4.0000e-03 eta: 7:17:32 time: 0.4010 data_time: 0.0232 memory: 5826 grad_norm: 4.2074 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0861 loss: 2.0861 2022/10/08 07:32:29 - mmengine - INFO - Epoch(train) [115][800/2119] lr: 4.0000e-03 eta: 7:17:25 time: 0.3482 data_time: 0.0184 memory: 5826 grad_norm: 4.0960 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9886 loss: 1.9886 2022/10/08 07:32:37 - mmengine - INFO - Epoch(train) [115][820/2119] lr: 4.0000e-03 eta: 7:17:19 time: 0.4020 data_time: 0.0223 memory: 5826 grad_norm: 4.1188 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1198 loss: 2.1198 2022/10/08 07:32:44 - mmengine - INFO - Epoch(train) [115][840/2119] lr: 4.0000e-03 eta: 7:17:12 time: 0.3280 data_time: 0.0256 memory: 5826 grad_norm: 4.1307 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8262 loss: 1.8262 2022/10/08 07:32:51 - mmengine - INFO - Epoch(train) [115][860/2119] lr: 4.0000e-03 eta: 7:17:05 time: 0.3765 data_time: 0.0221 memory: 5826 grad_norm: 4.0662 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0460 loss: 2.0460 2022/10/08 07:32:59 - mmengine - INFO - Epoch(train) [115][880/2119] lr: 4.0000e-03 eta: 7:16:58 time: 0.3828 data_time: 0.0222 memory: 5826 grad_norm: 4.1105 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.0198 loss: 2.0198 2022/10/08 07:33:06 - mmengine - INFO - Epoch(train) [115][900/2119] lr: 4.0000e-03 eta: 7:16:51 time: 0.3539 data_time: 0.0269 memory: 5826 grad_norm: 4.0679 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0513 loss: 2.0513 2022/10/08 07:33:13 - mmengine - INFO - Epoch(train) [115][920/2119] lr: 4.0000e-03 eta: 7:16:44 time: 0.3450 data_time: 0.0204 memory: 5826 grad_norm: 4.0343 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0521 loss: 2.0521 2022/10/08 07:33:20 - mmengine - INFO - Epoch(train) [115][940/2119] lr: 4.0000e-03 eta: 7:16:37 time: 0.3479 data_time: 0.0198 memory: 5826 grad_norm: 4.0548 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2129 loss: 2.2129 2022/10/08 07:33:27 - mmengine - INFO - Epoch(train) [115][960/2119] lr: 4.0000e-03 eta: 7:16:30 time: 0.3674 data_time: 0.0269 memory: 5826 grad_norm: 4.1594 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0527 loss: 2.0527 2022/10/08 07:33:35 - mmengine - INFO - Epoch(train) [115][980/2119] lr: 4.0000e-03 eta: 7:16:24 time: 0.3828 data_time: 0.0261 memory: 5826 grad_norm: 4.1432 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2129 loss: 2.2129 2022/10/08 07:33:42 - mmengine - INFO - Epoch(train) [115][1000/2119] lr: 4.0000e-03 eta: 7:16:17 time: 0.3628 data_time: 0.0263 memory: 5826 grad_norm: 4.1447 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.1311 loss: 2.1311 2022/10/08 07:33:50 - mmengine - INFO - Epoch(train) [115][1020/2119] lr: 4.0000e-03 eta: 7:16:10 time: 0.3808 data_time: 0.0231 memory: 5826 grad_norm: 4.0700 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8978 loss: 1.8978 2022/10/08 07:33:56 - mmengine - INFO - Epoch(train) [115][1040/2119] lr: 4.0000e-03 eta: 7:16:03 time: 0.3227 data_time: 0.0223 memory: 5826 grad_norm: 4.1262 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9642 loss: 1.9642 2022/10/08 07:34:04 - mmengine - INFO - Epoch(train) [115][1060/2119] lr: 4.0000e-03 eta: 7:15:56 time: 0.3746 data_time: 0.0240 memory: 5826 grad_norm: 4.0856 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8740 loss: 1.8740 2022/10/08 07:34:10 - mmengine - INFO - Epoch(train) [115][1080/2119] lr: 4.0000e-03 eta: 7:15:49 time: 0.3110 data_time: 0.0229 memory: 5826 grad_norm: 4.2026 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.9235 loss: 1.9235 2022/10/08 07:34:16 - mmengine - INFO - Epoch(train) [115][1100/2119] lr: 4.0000e-03 eta: 7:15:42 time: 0.3288 data_time: 0.0251 memory: 5826 grad_norm: 4.1861 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3231 loss: 2.3231 2022/10/08 07:34:24 - mmengine - INFO - Epoch(train) [115][1120/2119] lr: 4.0000e-03 eta: 7:15:35 time: 0.3748 data_time: 0.0265 memory: 5826 grad_norm: 4.1219 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.1544 loss: 2.1544 2022/10/08 07:34:31 - mmengine - INFO - Epoch(train) [115][1140/2119] lr: 4.0000e-03 eta: 7:15:28 time: 0.3756 data_time: 0.0207 memory: 5826 grad_norm: 4.1297 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.2509 loss: 2.2509 2022/10/08 07:34:38 - mmengine - INFO - Epoch(train) [115][1160/2119] lr: 4.0000e-03 eta: 7:15:21 time: 0.3205 data_time: 0.0219 memory: 5826 grad_norm: 4.1119 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.0017 loss: 2.0017 2022/10/08 07:34:45 - mmengine - INFO - Epoch(train) [115][1180/2119] lr: 4.0000e-03 eta: 7:15:14 time: 0.3651 data_time: 0.0199 memory: 5826 grad_norm: 4.1599 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0436 loss: 2.0436 2022/10/08 07:34:52 - mmengine - INFO - Epoch(train) [115][1200/2119] lr: 4.0000e-03 eta: 7:15:07 time: 0.3338 data_time: 0.0252 memory: 5826 grad_norm: 4.1950 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0042 loss: 2.0042 2022/10/08 07:35:00 - mmengine - INFO - Epoch(train) [115][1220/2119] lr: 4.0000e-03 eta: 7:15:01 time: 0.4194 data_time: 0.0245 memory: 5826 grad_norm: 4.1305 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 1.9758 loss: 1.9758 2022/10/08 07:35:06 - mmengine - INFO - Epoch(train) [115][1240/2119] lr: 4.0000e-03 eta: 7:14:54 time: 0.3085 data_time: 0.0233 memory: 5826 grad_norm: 4.1759 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9235 loss: 1.9235 2022/10/08 07:35:14 - mmengine - INFO - Epoch(train) [115][1260/2119] lr: 4.0000e-03 eta: 7:14:47 time: 0.3875 data_time: 0.0169 memory: 5826 grad_norm: 4.2325 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.1606 loss: 2.1606 2022/10/08 07:35:21 - mmengine - INFO - Epoch(train) [115][1280/2119] lr: 4.0000e-03 eta: 7:14:40 time: 0.3377 data_time: 0.0237 memory: 5826 grad_norm: 4.0853 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0531 loss: 2.0531 2022/10/08 07:35:29 - mmengine - INFO - Epoch(train) [115][1300/2119] lr: 4.0000e-03 eta: 7:14:33 time: 0.4004 data_time: 0.0195 memory: 5826 grad_norm: 4.1799 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0554 loss: 2.0554 2022/10/08 07:35:36 - mmengine - INFO - Epoch(train) [115][1320/2119] lr: 4.0000e-03 eta: 7:14:26 time: 0.3326 data_time: 0.0225 memory: 5826 grad_norm: 4.1001 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1756 loss: 2.1756 2022/10/08 07:35:44 - mmengine - INFO - Epoch(train) [115][1340/2119] lr: 4.0000e-03 eta: 7:14:20 time: 0.4052 data_time: 0.0210 memory: 5826 grad_norm: 4.1728 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8886 loss: 1.8886 2022/10/08 07:35:51 - mmengine - INFO - Epoch(train) [115][1360/2119] lr: 4.0000e-03 eta: 7:14:13 time: 0.3548 data_time: 0.0241 memory: 5826 grad_norm: 4.1820 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9543 loss: 1.9543 2022/10/08 07:35:59 - mmengine - INFO - Epoch(train) [115][1380/2119] lr: 4.0000e-03 eta: 7:14:06 time: 0.3969 data_time: 0.0230 memory: 5826 grad_norm: 4.1176 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0696 loss: 2.0696 2022/10/08 07:36:05 - mmengine - INFO - Epoch(train) [115][1400/2119] lr: 4.0000e-03 eta: 7:13:59 time: 0.3117 data_time: 0.0185 memory: 5826 grad_norm: 4.1489 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8517 loss: 1.8517 2022/10/08 07:36:13 - mmengine - INFO - Epoch(train) [115][1420/2119] lr: 4.0000e-03 eta: 7:13:52 time: 0.3764 data_time: 0.0291 memory: 5826 grad_norm: 4.1831 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0604 loss: 2.0604 2022/10/08 07:36:17 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 07:36:20 - mmengine - INFO - Epoch(train) [115][1440/2119] lr: 4.0000e-03 eta: 7:13:45 time: 0.3512 data_time: 0.0248 memory: 5826 grad_norm: 4.1423 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9281 loss: 1.9281 2022/10/08 07:36:27 - mmengine - INFO - Epoch(train) [115][1460/2119] lr: 4.0000e-03 eta: 7:13:38 time: 0.3780 data_time: 0.0221 memory: 5826 grad_norm: 4.1640 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0805 loss: 2.0805 2022/10/08 07:36:33 - mmengine - INFO - Epoch(train) [115][1480/2119] lr: 4.0000e-03 eta: 7:13:31 time: 0.3071 data_time: 0.0222 memory: 5826 grad_norm: 4.0720 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0332 loss: 2.0332 2022/10/08 07:36:41 - mmengine - INFO - Epoch(train) [115][1500/2119] lr: 4.0000e-03 eta: 7:13:24 time: 0.3768 data_time: 0.0235 memory: 5826 grad_norm: 4.1247 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9495 loss: 1.9495 2022/10/08 07:36:49 - mmengine - INFO - Epoch(train) [115][1520/2119] lr: 4.0000e-03 eta: 7:13:18 time: 0.4132 data_time: 0.0256 memory: 5826 grad_norm: 4.1806 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.2400 loss: 2.2400 2022/10/08 07:36:55 - mmengine - INFO - Epoch(train) [115][1540/2119] lr: 4.0000e-03 eta: 7:13:11 time: 0.3099 data_time: 0.0250 memory: 5826 grad_norm: 4.0838 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.1794 loss: 2.1794 2022/10/08 07:37:03 - mmengine - INFO - Epoch(train) [115][1560/2119] lr: 4.0000e-03 eta: 7:13:04 time: 0.3885 data_time: 0.0222 memory: 5826 grad_norm: 4.1126 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1468 loss: 2.1468 2022/10/08 07:37:10 - mmengine - INFO - Epoch(train) [115][1580/2119] lr: 4.0000e-03 eta: 7:12:57 time: 0.3522 data_time: 0.0266 memory: 5826 grad_norm: 4.1263 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.1836 loss: 2.1836 2022/10/08 07:37:18 - mmengine - INFO - Epoch(train) [115][1600/2119] lr: 4.0000e-03 eta: 7:12:50 time: 0.3850 data_time: 0.0205 memory: 5826 grad_norm: 4.1053 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.0852 loss: 2.0852 2022/10/08 07:37:25 - mmengine - INFO - Epoch(train) [115][1620/2119] lr: 4.0000e-03 eta: 7:12:43 time: 0.3452 data_time: 0.0248 memory: 5826 grad_norm: 4.1294 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.3068 loss: 2.3068 2022/10/08 07:37:33 - mmengine - INFO - Epoch(train) [115][1640/2119] lr: 4.0000e-03 eta: 7:12:37 time: 0.3901 data_time: 0.0269 memory: 5826 grad_norm: 4.1738 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1291 loss: 2.1291 2022/10/08 07:37:39 - mmengine - INFO - Epoch(train) [115][1660/2119] lr: 4.0000e-03 eta: 7:12:30 time: 0.3271 data_time: 0.0202 memory: 5826 grad_norm: 4.1631 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.1231 loss: 2.1231 2022/10/08 07:37:47 - mmengine - INFO - Epoch(train) [115][1680/2119] lr: 4.0000e-03 eta: 7:12:23 time: 0.3702 data_time: 0.0249 memory: 5826 grad_norm: 4.1787 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0112 loss: 2.0112 2022/10/08 07:37:53 - mmengine - INFO - Epoch(train) [115][1700/2119] lr: 4.0000e-03 eta: 7:12:16 time: 0.3120 data_time: 0.0255 memory: 5826 grad_norm: 4.1372 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8712 loss: 1.8712 2022/10/08 07:38:01 - mmengine - INFO - Epoch(train) [115][1720/2119] lr: 4.0000e-03 eta: 7:12:09 time: 0.4183 data_time: 0.0210 memory: 5826 grad_norm: 4.1772 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1131 loss: 2.1131 2022/10/08 07:38:07 - mmengine - INFO - Epoch(train) [115][1740/2119] lr: 4.0000e-03 eta: 7:12:02 time: 0.3177 data_time: 0.0226 memory: 5826 grad_norm: 4.0620 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9451 loss: 1.9451 2022/10/08 07:38:15 - mmengine - INFO - Epoch(train) [115][1760/2119] lr: 4.0000e-03 eta: 7:11:55 time: 0.3857 data_time: 0.0219 memory: 5826 grad_norm: 4.1623 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9332 loss: 1.9332 2022/10/08 07:38:21 - mmengine - INFO - Epoch(train) [115][1780/2119] lr: 4.0000e-03 eta: 7:11:48 time: 0.3134 data_time: 0.0230 memory: 5826 grad_norm: 4.1545 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9380 loss: 1.9380 2022/10/08 07:38:30 - mmengine - INFO - Epoch(train) [115][1800/2119] lr: 4.0000e-03 eta: 7:11:41 time: 0.4015 data_time: 0.0240 memory: 5826 grad_norm: 4.1569 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.1030 loss: 2.1030 2022/10/08 07:38:35 - mmengine - INFO - Epoch(train) [115][1820/2119] lr: 4.0000e-03 eta: 7:11:34 time: 0.2878 data_time: 0.0276 memory: 5826 grad_norm: 4.2396 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.2509 loss: 2.2509 2022/10/08 07:38:44 - mmengine - INFO - Epoch(train) [115][1840/2119] lr: 4.0000e-03 eta: 7:11:28 time: 0.4202 data_time: 0.0240 memory: 5826 grad_norm: 4.1922 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0410 loss: 2.0410 2022/10/08 07:38:50 - mmengine - INFO - Epoch(train) [115][1860/2119] lr: 4.0000e-03 eta: 7:11:20 time: 0.3283 data_time: 0.0254 memory: 5826 grad_norm: 4.1330 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9465 loss: 1.9465 2022/10/08 07:38:57 - mmengine - INFO - Epoch(train) [115][1880/2119] lr: 4.0000e-03 eta: 7:11:14 time: 0.3512 data_time: 0.0239 memory: 5826 grad_norm: 4.1150 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9748 loss: 1.9748 2022/10/08 07:39:06 - mmengine - INFO - Epoch(train) [115][1900/2119] lr: 4.0000e-03 eta: 7:11:07 time: 0.4177 data_time: 0.0260 memory: 5826 grad_norm: 4.1210 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0985 loss: 2.0985 2022/10/08 07:39:12 - mmengine - INFO - Epoch(train) [115][1920/2119] lr: 4.0000e-03 eta: 7:11:00 time: 0.3306 data_time: 0.0223 memory: 5826 grad_norm: 4.1473 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9491 loss: 1.9491 2022/10/08 07:39:19 - mmengine - INFO - Epoch(train) [115][1940/2119] lr: 4.0000e-03 eta: 7:10:53 time: 0.3361 data_time: 0.0208 memory: 5826 grad_norm: 4.1340 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.8764 loss: 1.8764 2022/10/08 07:39:26 - mmengine - INFO - Epoch(train) [115][1960/2119] lr: 4.0000e-03 eta: 7:10:46 time: 0.3412 data_time: 0.0235 memory: 5826 grad_norm: 4.1755 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.1276 loss: 2.1276 2022/10/08 07:39:34 - mmengine - INFO - Epoch(train) [115][1980/2119] lr: 4.0000e-03 eta: 7:10:39 time: 0.3866 data_time: 0.0204 memory: 5826 grad_norm: 4.1669 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9952 loss: 1.9952 2022/10/08 07:39:41 - mmengine - INFO - Epoch(train) [115][2000/2119] lr: 4.0000e-03 eta: 7:10:32 time: 0.3509 data_time: 0.0264 memory: 5826 grad_norm: 4.1286 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.8828 loss: 1.8828 2022/10/08 07:39:48 - mmengine - INFO - Epoch(train) [115][2020/2119] lr: 4.0000e-03 eta: 7:10:25 time: 0.3532 data_time: 0.0181 memory: 5826 grad_norm: 4.1748 top1_acc: 0.5625 top5_acc: 1.0000 loss_cls: 1.8630 loss: 1.8630 2022/10/08 07:39:54 - mmengine - INFO - Epoch(train) [115][2040/2119] lr: 4.0000e-03 eta: 7:10:18 time: 0.3361 data_time: 0.0250 memory: 5826 grad_norm: 4.1785 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2576 loss: 2.2576 2022/10/08 07:40:02 - mmengine - INFO - Epoch(train) [115][2060/2119] lr: 4.0000e-03 eta: 7:10:12 time: 0.3967 data_time: 0.0257 memory: 5826 grad_norm: 4.1777 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 1.8686 loss: 1.8686 2022/10/08 07:40:09 - mmengine - INFO - Epoch(train) [115][2080/2119] lr: 4.0000e-03 eta: 7:10:05 time: 0.3457 data_time: 0.0238 memory: 5826 grad_norm: 4.1061 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8380 loss: 1.8380 2022/10/08 07:40:17 - mmengine - INFO - Epoch(train) [115][2100/2119] lr: 4.0000e-03 eta: 7:09:58 time: 0.3631 data_time: 0.0218 memory: 5826 grad_norm: 4.1264 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2154 loss: 2.2154 2022/10/08 07:40:23 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 07:40:23 - mmengine - INFO - Epoch(train) [115][2119/2119] lr: 4.0000e-03 eta: 7:09:58 time: 0.3992 data_time: 0.0183 memory: 5826 grad_norm: 4.1524 top1_acc: 0.7000 top5_acc: 0.9000 loss_cls: 1.8180 loss: 1.8180 2022/10/08 07:40:31 - mmengine - INFO - Epoch(val) [115][20/137] eta: 0:00:44 time: 0.3842 data_time: 0.3183 memory: 1241 2022/10/08 07:40:37 - mmengine - INFO - Epoch(val) [115][40/137] eta: 0:00:28 time: 0.2924 data_time: 0.2259 memory: 1241 2022/10/08 07:40:44 - mmengine - INFO - Epoch(val) [115][60/137] eta: 0:00:27 time: 0.3543 data_time: 0.2862 memory: 1241 2022/10/08 07:40:50 - mmengine - INFO - Epoch(val) [115][80/137] eta: 0:00:16 time: 0.2978 data_time: 0.2335 memory: 1241 2022/10/08 07:40:58 - mmengine - INFO - Epoch(val) [115][100/137] eta: 0:00:13 time: 0.3716 data_time: 0.3036 memory: 1241 2022/10/08 07:41:03 - mmengine - INFO - Epoch(val) [115][120/137] eta: 0:00:04 time: 0.2530 data_time: 0.1759 memory: 1241 2022/10/08 07:41:15 - mmengine - INFO - Epoch(val) [115][137/137] acc/top1: 0.5393 acc/top5: 0.7655 acc/mean1: 0.5392 2022/10/08 07:41:15 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb/best_acc/top1_epoch_110.pth is removed 2022/10/08 07:41:16 - mmengine - INFO - The best checkpoint with 0.5393 acc/top1 at 115 epoch is saved to best_acc/top1_epoch_115.pth. 2022/10/08 07:41:25 - mmengine - INFO - Epoch(train) [116][20/2119] lr: 4.0000e-03 eta: 7:09:43 time: 0.4525 data_time: 0.2109 memory: 5826 grad_norm: 4.1002 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 1.7743 loss: 1.7743 2022/10/08 07:41:32 - mmengine - INFO - Epoch(train) [116][40/2119] lr: 4.0000e-03 eta: 7:09:36 time: 0.3322 data_time: 0.0999 memory: 5826 grad_norm: 4.1621 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9107 loss: 1.9107 2022/10/08 07:41:39 - mmengine - INFO - Epoch(train) [116][60/2119] lr: 4.0000e-03 eta: 7:09:29 time: 0.3388 data_time: 0.0628 memory: 5826 grad_norm: 4.2048 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8661 loss: 1.8661 2022/10/08 07:41:45 - mmengine - INFO - Epoch(train) [116][80/2119] lr: 4.0000e-03 eta: 7:09:22 time: 0.3217 data_time: 0.0621 memory: 5826 grad_norm: 4.1614 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0618 loss: 2.0618 2022/10/08 07:41:53 - mmengine - INFO - Epoch(train) [116][100/2119] lr: 4.0000e-03 eta: 7:09:15 time: 0.3885 data_time: 0.0659 memory: 5826 grad_norm: 4.1285 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.1065 loss: 2.1065 2022/10/08 07:42:00 - mmengine - INFO - Epoch(train) [116][120/2119] lr: 4.0000e-03 eta: 7:09:08 time: 0.3444 data_time: 0.0183 memory: 5826 grad_norm: 4.1468 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8841 loss: 1.8841 2022/10/08 07:42:06 - mmengine - INFO - Epoch(train) [116][140/2119] lr: 4.0000e-03 eta: 7:09:01 time: 0.3386 data_time: 0.0227 memory: 5826 grad_norm: 4.1755 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9933 loss: 1.9933 2022/10/08 07:42:13 - mmengine - INFO - Epoch(train) [116][160/2119] lr: 4.0000e-03 eta: 7:08:54 time: 0.3517 data_time: 0.0213 memory: 5826 grad_norm: 4.1596 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0450 loss: 2.0450 2022/10/08 07:42:20 - mmengine - INFO - Epoch(train) [116][180/2119] lr: 4.0000e-03 eta: 7:08:47 time: 0.3359 data_time: 0.0227 memory: 5826 grad_norm: 4.1943 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0168 loss: 2.0168 2022/10/08 07:42:27 - mmengine - INFO - Epoch(train) [116][200/2119] lr: 4.0000e-03 eta: 7:08:40 time: 0.3232 data_time: 0.0228 memory: 5826 grad_norm: 4.1289 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0312 loss: 2.0312 2022/10/08 07:42:35 - mmengine - INFO - Epoch(train) [116][220/2119] lr: 4.0000e-03 eta: 7:08:33 time: 0.4047 data_time: 0.0333 memory: 5826 grad_norm: 4.1800 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9372 loss: 1.9372 2022/10/08 07:42:41 - mmengine - INFO - Epoch(train) [116][240/2119] lr: 4.0000e-03 eta: 7:08:26 time: 0.3007 data_time: 0.0260 memory: 5826 grad_norm: 4.2556 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0584 loss: 2.0584 2022/10/08 07:42:48 - mmengine - INFO - Epoch(train) [116][260/2119] lr: 4.0000e-03 eta: 7:08:19 time: 0.3781 data_time: 0.0217 memory: 5826 grad_norm: 4.2459 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0627 loss: 2.0627 2022/10/08 07:42:55 - mmengine - INFO - Epoch(train) [116][280/2119] lr: 4.0000e-03 eta: 7:08:12 time: 0.3476 data_time: 0.0294 memory: 5826 grad_norm: 4.1690 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1382 loss: 2.1382 2022/10/08 07:43:02 - mmengine - INFO - Epoch(train) [116][300/2119] lr: 4.0000e-03 eta: 7:08:05 time: 0.3313 data_time: 0.0269 memory: 5826 grad_norm: 4.0986 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8541 loss: 1.8541 2022/10/08 07:43:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 07:43:09 - mmengine - INFO - Epoch(train) [116][320/2119] lr: 4.0000e-03 eta: 7:07:58 time: 0.3542 data_time: 0.0212 memory: 5826 grad_norm: 4.0817 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0300 loss: 2.0300 2022/10/08 07:43:16 - mmengine - INFO - Epoch(train) [116][340/2119] lr: 4.0000e-03 eta: 7:07:51 time: 0.3484 data_time: 0.0275 memory: 5826 grad_norm: 4.1233 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.1061 loss: 2.1061 2022/10/08 07:43:23 - mmengine - INFO - Epoch(train) [116][360/2119] lr: 4.0000e-03 eta: 7:07:45 time: 0.3536 data_time: 0.0245 memory: 5826 grad_norm: 4.1261 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0585 loss: 2.0585 2022/10/08 07:43:31 - mmengine - INFO - Epoch(train) [116][380/2119] lr: 4.0000e-03 eta: 7:07:38 time: 0.3930 data_time: 0.0232 memory: 5826 grad_norm: 4.1926 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9726 loss: 1.9726 2022/10/08 07:43:37 - mmengine - INFO - Epoch(train) [116][400/2119] lr: 4.0000e-03 eta: 7:07:31 time: 0.3114 data_time: 0.0227 memory: 5826 grad_norm: 4.2056 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 1.8871 loss: 1.8871 2022/10/08 07:43:45 - mmengine - INFO - Epoch(train) [116][420/2119] lr: 4.0000e-03 eta: 7:07:24 time: 0.3841 data_time: 0.0229 memory: 5826 grad_norm: 4.1142 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0304 loss: 2.0304 2022/10/08 07:43:52 - mmengine - INFO - Epoch(train) [116][440/2119] lr: 4.0000e-03 eta: 7:07:17 time: 0.3506 data_time: 0.0193 memory: 5826 grad_norm: 4.2080 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.0764 loss: 2.0764 2022/10/08 07:43:59 - mmengine - INFO - Epoch(train) [116][460/2119] lr: 4.0000e-03 eta: 7:07:10 time: 0.3550 data_time: 0.0243 memory: 5826 grad_norm: 4.1133 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9885 loss: 1.9885 2022/10/08 07:44:05 - mmengine - INFO - Epoch(train) [116][480/2119] lr: 4.0000e-03 eta: 7:07:03 time: 0.3124 data_time: 0.0196 memory: 5826 grad_norm: 4.0869 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0566 loss: 2.0566 2022/10/08 07:44:13 - mmengine - INFO - Epoch(train) [116][500/2119] lr: 4.0000e-03 eta: 7:06:56 time: 0.3726 data_time: 0.0228 memory: 5826 grad_norm: 4.1798 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9989 loss: 1.9989 2022/10/08 07:44:19 - mmengine - INFO - Epoch(train) [116][520/2119] lr: 4.0000e-03 eta: 7:06:49 time: 0.3140 data_time: 0.0214 memory: 5826 grad_norm: 4.2524 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.0114 loss: 2.0114 2022/10/08 07:44:27 - mmengine - INFO - Epoch(train) [116][540/2119] lr: 4.0000e-03 eta: 7:06:42 time: 0.3932 data_time: 0.0156 memory: 5826 grad_norm: 4.1923 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0663 loss: 2.0663 2022/10/08 07:44:34 - mmengine - INFO - Epoch(train) [116][560/2119] lr: 4.0000e-03 eta: 7:06:35 time: 0.3467 data_time: 0.0213 memory: 5826 grad_norm: 4.1390 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9552 loss: 1.9552 2022/10/08 07:44:41 - mmengine - INFO - Epoch(train) [116][580/2119] lr: 4.0000e-03 eta: 7:06:29 time: 0.3788 data_time: 0.0284 memory: 5826 grad_norm: 4.1664 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0700 loss: 2.0700 2022/10/08 07:44:47 - mmengine - INFO - Epoch(train) [116][600/2119] lr: 4.0000e-03 eta: 7:06:21 time: 0.2988 data_time: 0.0217 memory: 5826 grad_norm: 4.1648 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0275 loss: 2.0275 2022/10/08 07:44:55 - mmengine - INFO - Epoch(train) [116][620/2119] lr: 4.0000e-03 eta: 7:06:15 time: 0.4012 data_time: 0.0228 memory: 5826 grad_norm: 4.2252 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0602 loss: 2.0602 2022/10/08 07:45:02 - mmengine - INFO - Epoch(train) [116][640/2119] lr: 4.0000e-03 eta: 7:06:08 time: 0.3353 data_time: 0.0335 memory: 5826 grad_norm: 4.1563 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.2526 loss: 2.2526 2022/10/08 07:45:10 - mmengine - INFO - Epoch(train) [116][660/2119] lr: 4.0000e-03 eta: 7:06:01 time: 0.3950 data_time: 0.0221 memory: 5826 grad_norm: 4.1012 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7794 loss: 1.7794 2022/10/08 07:45:17 - mmengine - INFO - Epoch(train) [116][680/2119] lr: 4.0000e-03 eta: 7:05:54 time: 0.3226 data_time: 0.0210 memory: 5826 grad_norm: 4.1713 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8884 loss: 1.8884 2022/10/08 07:45:24 - mmengine - INFO - Epoch(train) [116][700/2119] lr: 4.0000e-03 eta: 7:05:47 time: 0.3741 data_time: 0.0277 memory: 5826 grad_norm: 4.1350 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0863 loss: 2.0863 2022/10/08 07:45:31 - mmengine - INFO - Epoch(train) [116][720/2119] lr: 4.0000e-03 eta: 7:05:40 time: 0.3576 data_time: 0.0199 memory: 5826 grad_norm: 4.2170 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0496 loss: 2.0496 2022/10/08 07:45:40 - mmengine - INFO - Epoch(train) [116][740/2119] lr: 4.0000e-03 eta: 7:05:34 time: 0.4190 data_time: 0.0239 memory: 5826 grad_norm: 4.1787 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0842 loss: 2.0842 2022/10/08 07:45:46 - mmengine - INFO - Epoch(train) [116][760/2119] lr: 4.0000e-03 eta: 7:05:27 time: 0.3185 data_time: 0.0237 memory: 5826 grad_norm: 4.1037 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.2321 loss: 2.2321 2022/10/08 07:45:53 - mmengine - INFO - Epoch(train) [116][780/2119] lr: 4.0000e-03 eta: 7:05:20 time: 0.3775 data_time: 0.0244 memory: 5826 grad_norm: 4.1351 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0963 loss: 2.0963 2022/10/08 07:46:00 - mmengine - INFO - Epoch(train) [116][800/2119] lr: 4.0000e-03 eta: 7:05:13 time: 0.3425 data_time: 0.0247 memory: 5826 grad_norm: 4.1479 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.8646 loss: 1.8646 2022/10/08 07:46:08 - mmengine - INFO - Epoch(train) [116][820/2119] lr: 4.0000e-03 eta: 7:05:06 time: 0.3590 data_time: 0.0241 memory: 5826 grad_norm: 4.1506 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1424 loss: 2.1424 2022/10/08 07:46:14 - mmengine - INFO - Epoch(train) [116][840/2119] lr: 4.0000e-03 eta: 7:04:59 time: 0.3382 data_time: 0.0190 memory: 5826 grad_norm: 4.2718 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.1457 loss: 2.1457 2022/10/08 07:46:22 - mmengine - INFO - Epoch(train) [116][860/2119] lr: 4.0000e-03 eta: 7:04:52 time: 0.3920 data_time: 0.0228 memory: 5826 grad_norm: 4.2618 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0556 loss: 2.0556 2022/10/08 07:46:29 - mmengine - INFO - Epoch(train) [116][880/2119] lr: 4.0000e-03 eta: 7:04:45 time: 0.3320 data_time: 0.0238 memory: 5826 grad_norm: 4.2139 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1248 loss: 2.1248 2022/10/08 07:46:37 - mmengine - INFO - Epoch(train) [116][900/2119] lr: 4.0000e-03 eta: 7:04:38 time: 0.3853 data_time: 0.0218 memory: 5826 grad_norm: 4.1400 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 1.9548 loss: 1.9548 2022/10/08 07:46:44 - mmengine - INFO - Epoch(train) [116][920/2119] lr: 4.0000e-03 eta: 7:04:32 time: 0.3666 data_time: 0.0200 memory: 5826 grad_norm: 4.1468 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.9632 loss: 1.9632 2022/10/08 07:46:51 - mmengine - INFO - Epoch(train) [116][940/2119] lr: 4.0000e-03 eta: 7:04:25 time: 0.3598 data_time: 0.0249 memory: 5826 grad_norm: 4.2526 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9552 loss: 1.9552 2022/10/08 07:46:57 - mmengine - INFO - Epoch(train) [116][960/2119] lr: 4.0000e-03 eta: 7:04:18 time: 0.3186 data_time: 0.0214 memory: 5826 grad_norm: 4.1809 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8621 loss: 1.8621 2022/10/08 07:47:05 - mmengine - INFO - Epoch(train) [116][980/2119] lr: 4.0000e-03 eta: 7:04:11 time: 0.3579 data_time: 0.0229 memory: 5826 grad_norm: 4.1742 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.1905 loss: 2.1905 2022/10/08 07:47:11 - mmengine - INFO - Epoch(train) [116][1000/2119] lr: 4.0000e-03 eta: 7:04:04 time: 0.3266 data_time: 0.0351 memory: 5826 grad_norm: 4.2202 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.2897 loss: 2.2897 2022/10/08 07:47:19 - mmengine - INFO - Epoch(train) [116][1020/2119] lr: 4.0000e-03 eta: 7:03:57 time: 0.3770 data_time: 0.0203 memory: 5826 grad_norm: 4.1785 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1010 loss: 2.1010 2022/10/08 07:47:26 - mmengine - INFO - Epoch(train) [116][1040/2119] lr: 4.0000e-03 eta: 7:03:50 time: 0.3644 data_time: 0.0225 memory: 5826 grad_norm: 4.1719 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0993 loss: 2.0993 2022/10/08 07:47:34 - mmengine - INFO - Epoch(train) [116][1060/2119] lr: 4.0000e-03 eta: 7:03:43 time: 0.3912 data_time: 0.0273 memory: 5826 grad_norm: 4.3212 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.1354 loss: 2.1354 2022/10/08 07:47:41 - mmengine - INFO - Epoch(train) [116][1080/2119] lr: 4.0000e-03 eta: 7:03:36 time: 0.3511 data_time: 0.0205 memory: 5826 grad_norm: 4.1602 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.1060 loss: 2.1060 2022/10/08 07:47:48 - mmengine - INFO - Epoch(train) [116][1100/2119] lr: 4.0000e-03 eta: 7:03:29 time: 0.3396 data_time: 0.0205 memory: 5826 grad_norm: 4.1515 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9463 loss: 1.9463 2022/10/08 07:47:55 - mmengine - INFO - Epoch(train) [116][1120/2119] lr: 4.0000e-03 eta: 7:03:22 time: 0.3623 data_time: 0.0235 memory: 5826 grad_norm: 4.1924 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2204 loss: 2.2204 2022/10/08 07:48:02 - mmengine - INFO - Epoch(train) [116][1140/2119] lr: 4.0000e-03 eta: 7:03:16 time: 0.3718 data_time: 0.0179 memory: 5826 grad_norm: 4.1502 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0538 loss: 2.0538 2022/10/08 07:48:10 - mmengine - INFO - Epoch(train) [116][1160/2119] lr: 4.0000e-03 eta: 7:03:09 time: 0.4062 data_time: 0.0219 memory: 5826 grad_norm: 4.1657 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9677 loss: 1.9677 2022/10/08 07:48:16 - mmengine - INFO - Epoch(train) [116][1180/2119] lr: 4.0000e-03 eta: 7:03:02 time: 0.2743 data_time: 0.0220 memory: 5826 grad_norm: 4.2278 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0912 loss: 2.0912 2022/10/08 07:48:24 - mmengine - INFO - Epoch(train) [116][1200/2119] lr: 4.0000e-03 eta: 7:02:55 time: 0.3842 data_time: 0.0207 memory: 5826 grad_norm: 4.3154 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1095 loss: 2.1095 2022/10/08 07:48:30 - mmengine - INFO - Epoch(train) [116][1220/2119] lr: 4.0000e-03 eta: 7:02:48 time: 0.3351 data_time: 0.0216 memory: 5826 grad_norm: 4.1969 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8477 loss: 1.8477 2022/10/08 07:48:38 - mmengine - INFO - Epoch(train) [116][1240/2119] lr: 4.0000e-03 eta: 7:02:41 time: 0.3692 data_time: 0.0254 memory: 5826 grad_norm: 4.1903 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0135 loss: 2.0135 2022/10/08 07:48:44 - mmengine - INFO - Epoch(train) [116][1260/2119] lr: 4.0000e-03 eta: 7:02:34 time: 0.3276 data_time: 0.0169 memory: 5826 grad_norm: 4.2308 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0806 loss: 2.0806 2022/10/08 07:48:52 - mmengine - INFO - Epoch(train) [116][1280/2119] lr: 4.0000e-03 eta: 7:02:27 time: 0.4080 data_time: 0.0227 memory: 5826 grad_norm: 4.1178 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9729 loss: 1.9729 2022/10/08 07:48:59 - mmengine - INFO - Epoch(train) [116][1300/2119] lr: 4.0000e-03 eta: 7:02:20 time: 0.3227 data_time: 0.0246 memory: 5826 grad_norm: 4.1926 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.1125 loss: 2.1125 2022/10/08 07:49:05 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 07:49:06 - mmengine - INFO - Epoch(train) [116][1320/2119] lr: 4.0000e-03 eta: 7:02:13 time: 0.3766 data_time: 0.0173 memory: 5826 grad_norm: 4.2189 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.2790 loss: 2.2790 2022/10/08 07:49:13 - mmengine - INFO - Epoch(train) [116][1340/2119] lr: 4.0000e-03 eta: 7:02:06 time: 0.3303 data_time: 0.0239 memory: 5826 grad_norm: 4.1594 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.1291 loss: 2.1291 2022/10/08 07:49:20 - mmengine - INFO - Epoch(train) [116][1360/2119] lr: 4.0000e-03 eta: 7:02:00 time: 0.3592 data_time: 0.0226 memory: 5826 grad_norm: 4.1439 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9542 loss: 1.9542 2022/10/08 07:49:27 - mmengine - INFO - Epoch(train) [116][1380/2119] lr: 4.0000e-03 eta: 7:01:53 time: 0.3534 data_time: 0.0210 memory: 5826 grad_norm: 4.2243 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0589 loss: 2.0589 2022/10/08 07:49:34 - mmengine - INFO - Epoch(train) [116][1400/2119] lr: 4.0000e-03 eta: 7:01:46 time: 0.3503 data_time: 0.0191 memory: 5826 grad_norm: 4.2108 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9062 loss: 1.9062 2022/10/08 07:49:41 - mmengine - INFO - Epoch(train) [116][1420/2119] lr: 4.0000e-03 eta: 7:01:39 time: 0.3469 data_time: 0.0257 memory: 5826 grad_norm: 4.2203 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.0910 loss: 2.0910 2022/10/08 07:49:48 - mmengine - INFO - Epoch(train) [116][1440/2119] lr: 4.0000e-03 eta: 7:01:32 time: 0.3217 data_time: 0.0218 memory: 5826 grad_norm: 4.1876 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.8792 loss: 1.8792 2022/10/08 07:49:55 - mmengine - INFO - Epoch(train) [116][1460/2119] lr: 4.0000e-03 eta: 7:01:25 time: 0.3485 data_time: 0.0236 memory: 5826 grad_norm: 4.1822 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0994 loss: 2.0994 2022/10/08 07:50:03 - mmengine - INFO - Epoch(train) [116][1480/2119] lr: 4.0000e-03 eta: 7:01:18 time: 0.3903 data_time: 0.0201 memory: 5826 grad_norm: 4.1723 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8719 loss: 1.8719 2022/10/08 07:50:09 - mmengine - INFO - Epoch(train) [116][1500/2119] lr: 4.0000e-03 eta: 7:01:11 time: 0.3283 data_time: 0.0237 memory: 5826 grad_norm: 4.1697 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9959 loss: 1.9959 2022/10/08 07:50:16 - mmengine - INFO - Epoch(train) [116][1520/2119] lr: 4.0000e-03 eta: 7:01:04 time: 0.3614 data_time: 0.0263 memory: 5826 grad_norm: 4.3013 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1295 loss: 2.1295 2022/10/08 07:50:23 - mmengine - INFO - Epoch(train) [116][1540/2119] lr: 4.0000e-03 eta: 7:00:57 time: 0.3384 data_time: 0.0190 memory: 5826 grad_norm: 4.2051 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9818 loss: 1.9818 2022/10/08 07:50:30 - mmengine - INFO - Epoch(train) [116][1560/2119] lr: 4.0000e-03 eta: 7:00:50 time: 0.3400 data_time: 0.0207 memory: 5826 grad_norm: 4.1933 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 2.0608 loss: 2.0608 2022/10/08 07:50:36 - mmengine - INFO - Epoch(train) [116][1580/2119] lr: 4.0000e-03 eta: 7:00:43 time: 0.3169 data_time: 0.0221 memory: 5826 grad_norm: 4.1177 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1125 loss: 2.1125 2022/10/08 07:50:44 - mmengine - INFO - Epoch(train) [116][1600/2119] lr: 4.0000e-03 eta: 7:00:36 time: 0.3909 data_time: 0.0216 memory: 5826 grad_norm: 4.1826 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9783 loss: 1.9783 2022/10/08 07:50:51 - mmengine - INFO - Epoch(train) [116][1620/2119] lr: 4.0000e-03 eta: 7:00:29 time: 0.3449 data_time: 0.0234 memory: 5826 grad_norm: 4.2280 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1299 loss: 2.1299 2022/10/08 07:50:59 - mmengine - INFO - Epoch(train) [116][1640/2119] lr: 4.0000e-03 eta: 7:00:22 time: 0.3766 data_time: 0.0212 memory: 5826 grad_norm: 4.2178 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0091 loss: 2.0091 2022/10/08 07:51:06 - mmengine - INFO - Epoch(train) [116][1660/2119] lr: 4.0000e-03 eta: 7:00:15 time: 0.3496 data_time: 0.0284 memory: 5826 grad_norm: 4.1239 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.2084 loss: 2.2084 2022/10/08 07:51:14 - mmengine - INFO - Epoch(train) [116][1680/2119] lr: 4.0000e-03 eta: 7:00:09 time: 0.4018 data_time: 0.0192 memory: 5826 grad_norm: 4.2433 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0248 loss: 2.0248 2022/10/08 07:51:20 - mmengine - INFO - Epoch(train) [116][1700/2119] lr: 4.0000e-03 eta: 7:00:02 time: 0.3267 data_time: 0.0224 memory: 5826 grad_norm: 4.1010 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1353 loss: 2.1353 2022/10/08 07:51:27 - mmengine - INFO - Epoch(train) [116][1720/2119] lr: 4.0000e-03 eta: 6:59:55 time: 0.3428 data_time: 0.0176 memory: 5826 grad_norm: 4.2897 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0050 loss: 2.0050 2022/10/08 07:51:35 - mmengine - INFO - Epoch(train) [116][1740/2119] lr: 4.0000e-03 eta: 6:59:48 time: 0.4001 data_time: 0.0231 memory: 5826 grad_norm: 4.1766 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1633 loss: 2.1633 2022/10/08 07:51:42 - mmengine - INFO - Epoch(train) [116][1760/2119] lr: 4.0000e-03 eta: 6:59:41 time: 0.3687 data_time: 0.0249 memory: 5826 grad_norm: 4.2066 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9896 loss: 1.9896 2022/10/08 07:51:48 - mmengine - INFO - Epoch(train) [116][1780/2119] lr: 4.0000e-03 eta: 6:59:34 time: 0.2942 data_time: 0.0249 memory: 5826 grad_norm: 4.2784 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0013 loss: 2.0013 2022/10/08 07:51:55 - mmengine - INFO - Epoch(train) [116][1800/2119] lr: 4.0000e-03 eta: 6:59:27 time: 0.3377 data_time: 0.0176 memory: 5826 grad_norm: 4.1814 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0234 loss: 2.0234 2022/10/08 07:52:02 - mmengine - INFO - Epoch(train) [116][1820/2119] lr: 4.0000e-03 eta: 6:59:20 time: 0.3613 data_time: 0.0275 memory: 5826 grad_norm: 4.2396 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9952 loss: 1.9952 2022/10/08 07:52:09 - mmengine - INFO - Epoch(train) [116][1840/2119] lr: 4.0000e-03 eta: 6:59:13 time: 0.3314 data_time: 0.0216 memory: 5826 grad_norm: 4.1556 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0063 loss: 2.0063 2022/10/08 07:52:16 - mmengine - INFO - Epoch(train) [116][1860/2119] lr: 4.0000e-03 eta: 6:59:06 time: 0.3416 data_time: 0.0212 memory: 5826 grad_norm: 4.2076 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2801 loss: 2.2801 2022/10/08 07:52:23 - mmengine - INFO - Epoch(train) [116][1880/2119] lr: 4.0000e-03 eta: 6:58:59 time: 0.3653 data_time: 0.0234 memory: 5826 grad_norm: 4.1928 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8241 loss: 1.8241 2022/10/08 07:52:30 - mmengine - INFO - Epoch(train) [116][1900/2119] lr: 4.0000e-03 eta: 6:58:52 time: 0.3599 data_time: 0.0224 memory: 5826 grad_norm: 4.2422 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9958 loss: 1.9958 2022/10/08 07:52:37 - mmengine - INFO - Epoch(train) [116][1920/2119] lr: 4.0000e-03 eta: 6:58:45 time: 0.3574 data_time: 0.0243 memory: 5826 grad_norm: 4.2048 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0731 loss: 2.0731 2022/10/08 07:52:44 - mmengine - INFO - Epoch(train) [116][1940/2119] lr: 4.0000e-03 eta: 6:58:38 time: 0.3222 data_time: 0.0217 memory: 5826 grad_norm: 4.2247 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1732 loss: 2.1732 2022/10/08 07:52:51 - mmengine - INFO - Epoch(train) [116][1960/2119] lr: 4.0000e-03 eta: 6:58:31 time: 0.3556 data_time: 0.0225 memory: 5826 grad_norm: 4.2072 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9723 loss: 1.9723 2022/10/08 07:52:58 - mmengine - INFO - Epoch(train) [116][1980/2119] lr: 4.0000e-03 eta: 6:58:24 time: 0.3306 data_time: 0.0265 memory: 5826 grad_norm: 4.2310 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.2103 loss: 2.2103 2022/10/08 07:53:06 - mmengine - INFO - Epoch(train) [116][2000/2119] lr: 4.0000e-03 eta: 6:58:18 time: 0.4036 data_time: 0.0190 memory: 5826 grad_norm: 4.2113 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0931 loss: 2.0931 2022/10/08 07:53:13 - mmengine - INFO - Epoch(train) [116][2020/2119] lr: 4.0000e-03 eta: 6:58:11 time: 0.3545 data_time: 0.0210 memory: 5826 grad_norm: 4.2856 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.1700 loss: 2.1700 2022/10/08 07:53:21 - mmengine - INFO - Epoch(train) [116][2040/2119] lr: 4.0000e-03 eta: 6:58:04 time: 0.3910 data_time: 0.0204 memory: 5826 grad_norm: 4.1608 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.1126 loss: 2.1126 2022/10/08 07:53:27 - mmengine - INFO - Epoch(train) [116][2060/2119] lr: 4.0000e-03 eta: 6:57:57 time: 0.3377 data_time: 0.0238 memory: 5826 grad_norm: 4.2256 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9959 loss: 1.9959 2022/10/08 07:53:35 - mmengine - INFO - Epoch(train) [116][2080/2119] lr: 4.0000e-03 eta: 6:57:50 time: 0.3795 data_time: 0.0217 memory: 5826 grad_norm: 4.2330 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1386 loss: 2.1386 2022/10/08 07:53:41 - mmengine - INFO - Epoch(train) [116][2100/2119] lr: 4.0000e-03 eta: 6:57:43 time: 0.2887 data_time: 0.0193 memory: 5826 grad_norm: 4.2921 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0626 loss: 2.0626 2022/10/08 07:53:47 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 07:53:47 - mmengine - INFO - Epoch(train) [116][2119/2119] lr: 4.0000e-03 eta: 6:57:43 time: 0.3036 data_time: 0.0183 memory: 5826 grad_norm: 4.2511 top1_acc: 0.8000 top5_acc: 1.0000 loss_cls: 1.9205 loss: 1.9205 2022/10/08 07:53:47 - mmengine - INFO - Saving checkpoint at 116 epochs 2022/10/08 07:54:09 - mmengine - INFO - Epoch(train) [117][20/2119] lr: 4.0000e-03 eta: 6:57:28 time: 0.4472 data_time: 0.2051 memory: 5826 grad_norm: 4.1465 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1718 loss: 2.1718 2022/10/08 07:54:14 - mmengine - INFO - Epoch(train) [117][40/2119] lr: 4.0000e-03 eta: 6:57:21 time: 0.2786 data_time: 0.0556 memory: 5826 grad_norm: 4.1463 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.0705 loss: 2.0705 2022/10/08 07:54:21 - mmengine - INFO - Epoch(train) [117][60/2119] lr: 4.0000e-03 eta: 6:57:14 time: 0.3704 data_time: 0.0366 memory: 5826 grad_norm: 4.1321 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8575 loss: 1.8575 2022/10/08 07:54:28 - mmengine - INFO - Epoch(train) [117][80/2119] lr: 4.0000e-03 eta: 6:57:07 time: 0.3292 data_time: 0.0183 memory: 5826 grad_norm: 4.2126 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9229 loss: 1.9229 2022/10/08 07:54:35 - mmengine - INFO - Epoch(train) [117][100/2119] lr: 4.0000e-03 eta: 6:57:00 time: 0.3609 data_time: 0.0222 memory: 5826 grad_norm: 4.2332 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7294 loss: 1.7294 2022/10/08 07:54:42 - mmengine - INFO - Epoch(train) [117][120/2119] lr: 4.0000e-03 eta: 6:56:53 time: 0.3569 data_time: 0.0245 memory: 5826 grad_norm: 4.1723 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9815 loss: 1.9815 2022/10/08 07:54:49 - mmengine - INFO - Epoch(train) [117][140/2119] lr: 4.0000e-03 eta: 6:56:46 time: 0.3497 data_time: 0.0223 memory: 5826 grad_norm: 4.2438 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8936 loss: 1.8936 2022/10/08 07:54:56 - mmengine - INFO - Epoch(train) [117][160/2119] lr: 4.0000e-03 eta: 6:56:39 time: 0.3250 data_time: 0.0216 memory: 5826 grad_norm: 4.1854 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.0266 loss: 2.0266 2022/10/08 07:55:04 - mmengine - INFO - Epoch(train) [117][180/2119] lr: 4.0000e-03 eta: 6:56:32 time: 0.3952 data_time: 0.0228 memory: 5826 grad_norm: 4.2675 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0192 loss: 2.0192 2022/10/08 07:55:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 07:55:10 - mmengine - INFO - Epoch(train) [117][200/2119] lr: 4.0000e-03 eta: 6:56:25 time: 0.3074 data_time: 0.0256 memory: 5826 grad_norm: 4.2136 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2179 loss: 2.2179 2022/10/08 07:55:18 - mmengine - INFO - Epoch(train) [117][220/2119] lr: 4.0000e-03 eta: 6:56:19 time: 0.4058 data_time: 0.0240 memory: 5826 grad_norm: 4.2380 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 1.9912 loss: 1.9912 2022/10/08 07:55:24 - mmengine - INFO - Epoch(train) [117][240/2119] lr: 4.0000e-03 eta: 6:56:11 time: 0.2957 data_time: 0.0252 memory: 5826 grad_norm: 4.2162 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1054 loss: 2.1054 2022/10/08 07:55:32 - mmengine - INFO - Epoch(train) [117][260/2119] lr: 4.0000e-03 eta: 6:56:04 time: 0.3731 data_time: 0.0220 memory: 5826 grad_norm: 4.2586 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9590 loss: 1.9590 2022/10/08 07:55:37 - mmengine - INFO - Epoch(train) [117][280/2119] lr: 4.0000e-03 eta: 6:55:57 time: 0.2819 data_time: 0.0174 memory: 5826 grad_norm: 4.2958 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.3060 loss: 2.3060 2022/10/08 07:55:46 - mmengine - INFO - Epoch(train) [117][300/2119] lr: 4.0000e-03 eta: 6:55:51 time: 0.4181 data_time: 0.0181 memory: 5826 grad_norm: 4.3397 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9674 loss: 1.9674 2022/10/08 07:55:52 - mmengine - INFO - Epoch(train) [117][320/2119] lr: 4.0000e-03 eta: 6:55:44 time: 0.3285 data_time: 0.0204 memory: 5826 grad_norm: 4.2561 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0298 loss: 2.0298 2022/10/08 07:56:00 - mmengine - INFO - Epoch(train) [117][340/2119] lr: 4.0000e-03 eta: 6:55:37 time: 0.4120 data_time: 0.0201 memory: 5826 grad_norm: 4.2260 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8090 loss: 1.8090 2022/10/08 07:56:06 - mmengine - INFO - Epoch(train) [117][360/2119] lr: 4.0000e-03 eta: 6:55:30 time: 0.3005 data_time: 0.0217 memory: 5826 grad_norm: 4.3112 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.1007 loss: 2.1007 2022/10/08 07:56:14 - mmengine - INFO - Epoch(train) [117][380/2119] lr: 4.0000e-03 eta: 6:55:23 time: 0.4026 data_time: 0.0275 memory: 5826 grad_norm: 4.2933 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 1.8442 loss: 1.8442 2022/10/08 07:56:21 - mmengine - INFO - Epoch(train) [117][400/2119] lr: 4.0000e-03 eta: 6:55:16 time: 0.3312 data_time: 0.0183 memory: 5826 grad_norm: 4.2764 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9458 loss: 1.9458 2022/10/08 07:56:28 - mmengine - INFO - Epoch(train) [117][420/2119] lr: 4.0000e-03 eta: 6:55:09 time: 0.3439 data_time: 0.0234 memory: 5826 grad_norm: 4.2326 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7834 loss: 1.7834 2022/10/08 07:56:35 - mmengine - INFO - Epoch(train) [117][440/2119] lr: 4.0000e-03 eta: 6:55:02 time: 0.3447 data_time: 0.0171 memory: 5826 grad_norm: 4.1499 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0548 loss: 2.0548 2022/10/08 07:56:42 - mmengine - INFO - Epoch(train) [117][460/2119] lr: 4.0000e-03 eta: 6:54:55 time: 0.3650 data_time: 0.0268 memory: 5826 grad_norm: 4.1330 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.9724 loss: 1.9724 2022/10/08 07:56:49 - mmengine - INFO - Epoch(train) [117][480/2119] lr: 4.0000e-03 eta: 6:54:48 time: 0.3314 data_time: 0.0185 memory: 5826 grad_norm: 4.2157 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6465 loss: 1.6465 2022/10/08 07:56:56 - mmengine - INFO - Epoch(train) [117][500/2119] lr: 4.0000e-03 eta: 6:54:41 time: 0.3635 data_time: 0.0221 memory: 5826 grad_norm: 4.3277 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0672 loss: 2.0672 2022/10/08 07:57:03 - mmengine - INFO - Epoch(train) [117][520/2119] lr: 4.0000e-03 eta: 6:54:34 time: 0.3200 data_time: 0.0218 memory: 5826 grad_norm: 4.2286 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1103 loss: 2.1103 2022/10/08 07:57:10 - mmengine - INFO - Epoch(train) [117][540/2119] lr: 4.0000e-03 eta: 6:54:27 time: 0.3781 data_time: 0.0209 memory: 5826 grad_norm: 4.1595 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0956 loss: 2.0956 2022/10/08 07:57:16 - mmengine - INFO - Epoch(train) [117][560/2119] lr: 4.0000e-03 eta: 6:54:20 time: 0.2962 data_time: 0.0245 memory: 5826 grad_norm: 4.2640 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0890 loss: 2.0890 2022/10/08 07:57:23 - mmengine - INFO - Epoch(train) [117][580/2119] lr: 4.0000e-03 eta: 6:54:13 time: 0.3597 data_time: 0.0261 memory: 5826 grad_norm: 4.1788 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0401 loss: 2.0401 2022/10/08 07:57:29 - mmengine - INFO - Epoch(train) [117][600/2119] lr: 4.0000e-03 eta: 6:54:06 time: 0.3103 data_time: 0.0198 memory: 5826 grad_norm: 4.2399 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.0170 loss: 2.0170 2022/10/08 07:57:37 - mmengine - INFO - Epoch(train) [117][620/2119] lr: 4.0000e-03 eta: 6:53:59 time: 0.3663 data_time: 0.0193 memory: 5826 grad_norm: 4.2853 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1186 loss: 2.1186 2022/10/08 07:57:44 - mmengine - INFO - Epoch(train) [117][640/2119] lr: 4.0000e-03 eta: 6:53:52 time: 0.3580 data_time: 0.0249 memory: 5826 grad_norm: 4.2500 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0697 loss: 2.0697 2022/10/08 07:57:50 - mmengine - INFO - Epoch(train) [117][660/2119] lr: 4.0000e-03 eta: 6:53:45 time: 0.3265 data_time: 0.0198 memory: 5826 grad_norm: 4.1926 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9795 loss: 1.9795 2022/10/08 07:57:57 - mmengine - INFO - Epoch(train) [117][680/2119] lr: 4.0000e-03 eta: 6:53:38 time: 0.3323 data_time: 0.0234 memory: 5826 grad_norm: 4.1796 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.2580 loss: 2.2580 2022/10/08 07:58:04 - mmengine - INFO - Epoch(train) [117][700/2119] lr: 4.0000e-03 eta: 6:53:31 time: 0.3489 data_time: 0.0269 memory: 5826 grad_norm: 4.2378 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9797 loss: 1.9797 2022/10/08 07:58:12 - mmengine - INFO - Epoch(train) [117][720/2119] lr: 4.0000e-03 eta: 6:53:24 time: 0.3754 data_time: 0.0222 memory: 5826 grad_norm: 4.1889 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.8912 loss: 1.8912 2022/10/08 07:58:18 - mmengine - INFO - Epoch(train) [117][740/2119] lr: 4.0000e-03 eta: 6:53:17 time: 0.3409 data_time: 0.0208 memory: 5826 grad_norm: 4.1800 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.9003 loss: 1.9003 2022/10/08 07:58:26 - mmengine - INFO - Epoch(train) [117][760/2119] lr: 4.0000e-03 eta: 6:53:11 time: 0.3677 data_time: 0.0221 memory: 5826 grad_norm: 4.3247 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2100 loss: 2.2100 2022/10/08 07:58:32 - mmengine - INFO - Epoch(train) [117][780/2119] lr: 4.0000e-03 eta: 6:53:04 time: 0.3323 data_time: 0.0211 memory: 5826 grad_norm: 4.2724 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9481 loss: 1.9481 2022/10/08 07:58:40 - mmengine - INFO - Epoch(train) [117][800/2119] lr: 4.0000e-03 eta: 6:52:57 time: 0.3676 data_time: 0.0224 memory: 5826 grad_norm: 4.2276 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9576 loss: 1.9576 2022/10/08 07:58:46 - mmengine - INFO - Epoch(train) [117][820/2119] lr: 4.0000e-03 eta: 6:52:50 time: 0.2985 data_time: 0.0265 memory: 5826 grad_norm: 4.2474 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1394 loss: 2.1394 2022/10/08 07:58:53 - mmengine - INFO - Epoch(train) [117][840/2119] lr: 4.0000e-03 eta: 6:52:43 time: 0.3554 data_time: 0.0259 memory: 5826 grad_norm: 4.2126 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8860 loss: 1.8860 2022/10/08 07:59:00 - mmengine - INFO - Epoch(train) [117][860/2119] lr: 4.0000e-03 eta: 6:52:36 time: 0.3418 data_time: 0.0237 memory: 5826 grad_norm: 4.2212 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9477 loss: 1.9477 2022/10/08 07:59:07 - mmengine - INFO - Epoch(train) [117][880/2119] lr: 4.0000e-03 eta: 6:52:29 time: 0.3573 data_time: 0.0199 memory: 5826 grad_norm: 4.2268 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9206 loss: 1.9206 2022/10/08 07:59:14 - mmengine - INFO - Epoch(train) [117][900/2119] lr: 4.0000e-03 eta: 6:52:22 time: 0.3541 data_time: 0.0207 memory: 5826 grad_norm: 4.2335 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9105 loss: 1.9105 2022/10/08 07:59:22 - mmengine - INFO - Epoch(train) [117][920/2119] lr: 4.0000e-03 eta: 6:52:15 time: 0.4193 data_time: 0.0224 memory: 5826 grad_norm: 4.1995 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0852 loss: 2.0852 2022/10/08 07:59:29 - mmengine - INFO - Epoch(train) [117][940/2119] lr: 4.0000e-03 eta: 6:52:08 time: 0.3109 data_time: 0.0213 memory: 5826 grad_norm: 4.2242 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0239 loss: 2.0239 2022/10/08 07:59:35 - mmengine - INFO - Epoch(train) [117][960/2119] lr: 4.0000e-03 eta: 6:52:01 time: 0.3364 data_time: 0.0202 memory: 5826 grad_norm: 4.2403 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.1476 loss: 2.1476 2022/10/08 07:59:42 - mmengine - INFO - Epoch(train) [117][980/2119] lr: 4.0000e-03 eta: 6:51:54 time: 0.3336 data_time: 0.0257 memory: 5826 grad_norm: 4.1857 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8788 loss: 1.8788 2022/10/08 07:59:49 - mmengine - INFO - Epoch(train) [117][1000/2119] lr: 4.0000e-03 eta: 6:51:47 time: 0.3647 data_time: 0.0162 memory: 5826 grad_norm: 4.1096 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.9897 loss: 1.9897 2022/10/08 07:59:56 - mmengine - INFO - Epoch(train) [117][1020/2119] lr: 4.0000e-03 eta: 6:51:40 time: 0.3232 data_time: 0.0204 memory: 5826 grad_norm: 4.1852 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2508 loss: 2.2508 2022/10/08 08:00:03 - mmengine - INFO - Epoch(train) [117][1040/2119] lr: 4.0000e-03 eta: 6:51:33 time: 0.3744 data_time: 0.0229 memory: 5826 grad_norm: 4.2252 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0073 loss: 2.0073 2022/10/08 08:00:10 - mmengine - INFO - Epoch(train) [117][1060/2119] lr: 4.0000e-03 eta: 6:51:26 time: 0.3191 data_time: 0.0213 memory: 5826 grad_norm: 4.1951 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0121 loss: 2.0121 2022/10/08 08:00:17 - mmengine - INFO - Epoch(train) [117][1080/2119] lr: 4.0000e-03 eta: 6:51:19 time: 0.3842 data_time: 0.0240 memory: 5826 grad_norm: 4.2329 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1060 loss: 2.1060 2022/10/08 08:00:24 - mmengine - INFO - Epoch(train) [117][1100/2119] lr: 4.0000e-03 eta: 6:51:12 time: 0.3290 data_time: 0.0250 memory: 5826 grad_norm: 4.2650 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9885 loss: 1.9885 2022/10/08 08:00:32 - mmengine - INFO - Epoch(train) [117][1120/2119] lr: 4.0000e-03 eta: 6:51:06 time: 0.3902 data_time: 0.0235 memory: 5826 grad_norm: 4.2372 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.8002 loss: 1.8002 2022/10/08 08:00:37 - mmengine - INFO - Epoch(train) [117][1140/2119] lr: 4.0000e-03 eta: 6:50:58 time: 0.2835 data_time: 0.0204 memory: 5826 grad_norm: 4.2184 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0582 loss: 2.0582 2022/10/08 08:00:44 - mmengine - INFO - Epoch(train) [117][1160/2119] lr: 4.0000e-03 eta: 6:50:51 time: 0.3225 data_time: 0.0237 memory: 5826 grad_norm: 4.2467 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0199 loss: 2.0199 2022/10/08 08:00:51 - mmengine - INFO - Epoch(train) [117][1180/2119] lr: 4.0000e-03 eta: 6:50:44 time: 0.3683 data_time: 0.0241 memory: 5826 grad_norm: 4.3163 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9446 loss: 1.9446 2022/10/08 08:00:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 08:00:58 - mmengine - INFO - Epoch(train) [117][1200/2119] lr: 4.0000e-03 eta: 6:50:37 time: 0.3424 data_time: 0.0228 memory: 5826 grad_norm: 4.2312 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9460 loss: 1.9460 2022/10/08 08:01:06 - mmengine - INFO - Epoch(train) [117][1220/2119] lr: 4.0000e-03 eta: 6:50:31 time: 0.3680 data_time: 0.0224 memory: 5826 grad_norm: 4.2396 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0536 loss: 2.0536 2022/10/08 08:01:12 - mmengine - INFO - Epoch(train) [117][1240/2119] lr: 4.0000e-03 eta: 6:50:24 time: 0.3449 data_time: 0.0203 memory: 5826 grad_norm: 4.2237 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 1.9605 loss: 1.9605 2022/10/08 08:01:19 - mmengine - INFO - Epoch(train) [117][1260/2119] lr: 4.0000e-03 eta: 6:50:17 time: 0.3476 data_time: 0.0282 memory: 5826 grad_norm: 4.1668 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1561 loss: 2.1561 2022/10/08 08:01:27 - mmengine - INFO - Epoch(train) [117][1280/2119] lr: 4.0000e-03 eta: 6:50:10 time: 0.3613 data_time: 0.0236 memory: 5826 grad_norm: 4.2718 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 1.9274 loss: 1.9274 2022/10/08 08:01:34 - mmengine - INFO - Epoch(train) [117][1300/2119] lr: 4.0000e-03 eta: 6:50:03 time: 0.3553 data_time: 0.0220 memory: 5826 grad_norm: 4.2539 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0795 loss: 2.0795 2022/10/08 08:01:41 - mmengine - INFO - Epoch(train) [117][1320/2119] lr: 4.0000e-03 eta: 6:49:56 time: 0.3502 data_time: 0.0247 memory: 5826 grad_norm: 4.2735 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.1407 loss: 2.1407 2022/10/08 08:01:48 - mmengine - INFO - Epoch(train) [117][1340/2119] lr: 4.0000e-03 eta: 6:49:49 time: 0.3588 data_time: 0.0212 memory: 5826 grad_norm: 4.3392 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.2868 loss: 2.2868 2022/10/08 08:01:54 - mmengine - INFO - Epoch(train) [117][1360/2119] lr: 4.0000e-03 eta: 6:49:42 time: 0.3219 data_time: 0.0267 memory: 5826 grad_norm: 4.3216 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0393 loss: 2.0393 2022/10/08 08:02:02 - mmengine - INFO - Epoch(train) [117][1380/2119] lr: 4.0000e-03 eta: 6:49:35 time: 0.4017 data_time: 0.0219 memory: 5826 grad_norm: 4.2065 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1487 loss: 2.1487 2022/10/08 08:02:09 - mmengine - INFO - Epoch(train) [117][1400/2119] lr: 4.0000e-03 eta: 6:49:28 time: 0.3038 data_time: 0.0224 memory: 5826 grad_norm: 4.1861 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.1285 loss: 2.1285 2022/10/08 08:02:16 - mmengine - INFO - Epoch(train) [117][1420/2119] lr: 4.0000e-03 eta: 6:49:21 time: 0.3643 data_time: 0.0259 memory: 5826 grad_norm: 4.2505 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1248 loss: 2.1248 2022/10/08 08:02:23 - mmengine - INFO - Epoch(train) [117][1440/2119] lr: 4.0000e-03 eta: 6:49:14 time: 0.3527 data_time: 0.0225 memory: 5826 grad_norm: 4.1720 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 1.8478 loss: 1.8478 2022/10/08 08:02:30 - mmengine - INFO - Epoch(train) [117][1460/2119] lr: 4.0000e-03 eta: 6:49:07 time: 0.3474 data_time: 0.0218 memory: 5826 grad_norm: 4.2836 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0547 loss: 2.0547 2022/10/08 08:02:37 - mmengine - INFO - Epoch(train) [117][1480/2119] lr: 4.0000e-03 eta: 6:49:00 time: 0.3589 data_time: 0.0225 memory: 5826 grad_norm: 4.1867 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0798 loss: 2.0798 2022/10/08 08:02:44 - mmengine - INFO - Epoch(train) [117][1500/2119] lr: 4.0000e-03 eta: 6:48:53 time: 0.3426 data_time: 0.0213 memory: 5826 grad_norm: 4.2691 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1889 loss: 2.1889 2022/10/08 08:02:51 - mmengine - INFO - Epoch(train) [117][1520/2119] lr: 4.0000e-03 eta: 6:48:46 time: 0.3418 data_time: 0.0227 memory: 5826 grad_norm: 4.2103 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9090 loss: 1.9090 2022/10/08 08:02:58 - mmengine - INFO - Epoch(train) [117][1540/2119] lr: 4.0000e-03 eta: 6:48:40 time: 0.3619 data_time: 0.0242 memory: 5826 grad_norm: 4.2870 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0459 loss: 2.0459 2022/10/08 08:03:05 - mmengine - INFO - Epoch(train) [117][1560/2119] lr: 4.0000e-03 eta: 6:48:33 time: 0.3495 data_time: 0.0236 memory: 5826 grad_norm: 4.2552 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9696 loss: 1.9696 2022/10/08 08:03:11 - mmengine - INFO - Epoch(train) [117][1580/2119] lr: 4.0000e-03 eta: 6:48:25 time: 0.3076 data_time: 0.0254 memory: 5826 grad_norm: 4.2631 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9393 loss: 1.9393 2022/10/08 08:03:18 - mmengine - INFO - Epoch(train) [117][1600/2119] lr: 4.0000e-03 eta: 6:48:18 time: 0.3472 data_time: 0.0217 memory: 5826 grad_norm: 4.2197 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0879 loss: 2.0879 2022/10/08 08:03:26 - mmengine - INFO - Epoch(train) [117][1620/2119] lr: 4.0000e-03 eta: 6:48:12 time: 0.3942 data_time: 0.0215 memory: 5826 grad_norm: 4.1970 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 2.2162 loss: 2.2162 2022/10/08 08:03:33 - mmengine - INFO - Epoch(train) [117][1640/2119] lr: 4.0000e-03 eta: 6:48:05 time: 0.3521 data_time: 0.0240 memory: 5826 grad_norm: 4.2966 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0212 loss: 2.0212 2022/10/08 08:03:41 - mmengine - INFO - Epoch(train) [117][1660/2119] lr: 4.0000e-03 eta: 6:47:58 time: 0.3848 data_time: 0.0189 memory: 5826 grad_norm: 4.2303 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 2.1103 loss: 2.1103 2022/10/08 08:03:47 - mmengine - INFO - Epoch(train) [117][1680/2119] lr: 4.0000e-03 eta: 6:47:51 time: 0.3333 data_time: 0.0211 memory: 5826 grad_norm: 4.2871 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1593 loss: 2.1593 2022/10/08 08:03:55 - mmengine - INFO - Epoch(train) [117][1700/2119] lr: 4.0000e-03 eta: 6:47:44 time: 0.3728 data_time: 0.0199 memory: 5826 grad_norm: 4.1711 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0540 loss: 2.0540 2022/10/08 08:04:01 - mmengine - INFO - Epoch(train) [117][1720/2119] lr: 4.0000e-03 eta: 6:47:37 time: 0.3290 data_time: 0.0244 memory: 5826 grad_norm: 4.2083 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0020 loss: 2.0020 2022/10/08 08:04:09 - mmengine - INFO - Epoch(train) [117][1740/2119] lr: 4.0000e-03 eta: 6:47:30 time: 0.3714 data_time: 0.0210 memory: 5826 grad_norm: 4.3132 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9855 loss: 1.9855 2022/10/08 08:04:15 - mmengine - INFO - Epoch(train) [117][1760/2119] lr: 4.0000e-03 eta: 6:47:23 time: 0.2994 data_time: 0.0217 memory: 5826 grad_norm: 4.2451 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0074 loss: 2.0074 2022/10/08 08:04:22 - mmengine - INFO - Epoch(train) [117][1780/2119] lr: 4.0000e-03 eta: 6:47:16 time: 0.3307 data_time: 0.0241 memory: 5826 grad_norm: 4.2316 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9568 loss: 1.9568 2022/10/08 08:04:29 - mmengine - INFO - Epoch(train) [117][1800/2119] lr: 4.0000e-03 eta: 6:47:09 time: 0.3537 data_time: 0.0205 memory: 5826 grad_norm: 4.1959 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9866 loss: 1.9866 2022/10/08 08:04:36 - mmengine - INFO - Epoch(train) [117][1820/2119] lr: 4.0000e-03 eta: 6:47:02 time: 0.3779 data_time: 0.0256 memory: 5826 grad_norm: 4.2496 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8092 loss: 1.8092 2022/10/08 08:04:42 - mmengine - INFO - Epoch(train) [117][1840/2119] lr: 4.0000e-03 eta: 6:46:55 time: 0.3086 data_time: 0.0209 memory: 5826 grad_norm: 4.2717 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9658 loss: 1.9658 2022/10/08 08:04:50 - mmengine - INFO - Epoch(train) [117][1860/2119] lr: 4.0000e-03 eta: 6:46:48 time: 0.3753 data_time: 0.0217 memory: 5826 grad_norm: 4.2035 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.0248 loss: 2.0248 2022/10/08 08:04:57 - mmengine - INFO - Epoch(train) [117][1880/2119] lr: 4.0000e-03 eta: 6:46:41 time: 0.3432 data_time: 0.0198 memory: 5826 grad_norm: 4.1986 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7890 loss: 1.7890 2022/10/08 08:05:04 - mmengine - INFO - Epoch(train) [117][1900/2119] lr: 4.0000e-03 eta: 6:46:35 time: 0.3747 data_time: 0.0232 memory: 5826 grad_norm: 4.2816 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0209 loss: 2.0209 2022/10/08 08:05:11 - mmengine - INFO - Epoch(train) [117][1920/2119] lr: 4.0000e-03 eta: 6:46:28 time: 0.3243 data_time: 0.0271 memory: 5826 grad_norm: 4.2350 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0038 loss: 2.0038 2022/10/08 08:05:18 - mmengine - INFO - Epoch(train) [117][1940/2119] lr: 4.0000e-03 eta: 6:46:21 time: 0.3607 data_time: 0.0213 memory: 5826 grad_norm: 4.2598 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.1301 loss: 2.1301 2022/10/08 08:05:25 - mmengine - INFO - Epoch(train) [117][1960/2119] lr: 4.0000e-03 eta: 6:46:14 time: 0.3428 data_time: 0.0218 memory: 5826 grad_norm: 4.2244 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9817 loss: 1.9817 2022/10/08 08:05:32 - mmengine - INFO - Epoch(train) [117][1980/2119] lr: 4.0000e-03 eta: 6:46:07 time: 0.3747 data_time: 0.0233 memory: 5826 grad_norm: 4.2664 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9855 loss: 1.9855 2022/10/08 08:05:39 - mmengine - INFO - Epoch(train) [117][2000/2119] lr: 4.0000e-03 eta: 6:46:00 time: 0.3326 data_time: 0.0317 memory: 5826 grad_norm: 4.2968 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8994 loss: 1.8994 2022/10/08 08:05:46 - mmengine - INFO - Epoch(train) [117][2020/2119] lr: 4.0000e-03 eta: 6:45:53 time: 0.3518 data_time: 0.0199 memory: 5826 grad_norm: 4.2390 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9213 loss: 1.9213 2022/10/08 08:05:52 - mmengine - INFO - Epoch(train) [117][2040/2119] lr: 4.0000e-03 eta: 6:45:46 time: 0.3233 data_time: 0.0202 memory: 5826 grad_norm: 4.1235 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9863 loss: 1.9863 2022/10/08 08:06:00 - mmengine - INFO - Epoch(train) [117][2060/2119] lr: 4.0000e-03 eta: 6:45:39 time: 0.3641 data_time: 0.0244 memory: 5826 grad_norm: 4.2895 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1279 loss: 2.1279 2022/10/08 08:06:06 - mmengine - INFO - Epoch(train) [117][2080/2119] lr: 4.0000e-03 eta: 6:45:32 time: 0.3084 data_time: 0.0215 memory: 5826 grad_norm: 4.2328 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0764 loss: 2.0764 2022/10/08 08:06:14 - mmengine - INFO - Epoch(train) [117][2100/2119] lr: 4.0000e-03 eta: 6:45:25 time: 0.3873 data_time: 0.0266 memory: 5826 grad_norm: 4.3011 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0237 loss: 2.0237 2022/10/08 08:06:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 08:06:19 - mmengine - INFO - Epoch(train) [117][2119/2119] lr: 4.0000e-03 eta: 6:45:25 time: 0.2786 data_time: 0.0242 memory: 5826 grad_norm: 4.3292 top1_acc: 0.6000 top5_acc: 0.7000 loss_cls: 2.0214 loss: 2.0214 2022/10/08 08:06:29 - mmengine - INFO - Epoch(train) [118][20/2119] lr: 4.0000e-03 eta: 6:45:10 time: 0.4964 data_time: 0.1397 memory: 5826 grad_norm: 4.2485 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9385 loss: 1.9385 2022/10/08 08:06:36 - mmengine - INFO - Epoch(train) [118][40/2119] lr: 4.0000e-03 eta: 6:45:03 time: 0.3408 data_time: 0.0195 memory: 5826 grad_norm: 4.2211 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7187 loss: 1.7187 2022/10/08 08:06:44 - mmengine - INFO - Epoch(train) [118][60/2119] lr: 4.0000e-03 eta: 6:44:57 time: 0.3877 data_time: 0.0259 memory: 5826 grad_norm: 4.3615 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1050 loss: 2.1050 2022/10/08 08:06:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 08:06:50 - mmengine - INFO - Epoch(train) [118][80/2119] lr: 4.0000e-03 eta: 6:44:50 time: 0.3248 data_time: 0.0288 memory: 5826 grad_norm: 4.3058 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9036 loss: 1.9036 2022/10/08 08:06:58 - mmengine - INFO - Epoch(train) [118][100/2119] lr: 4.0000e-03 eta: 6:44:43 time: 0.4096 data_time: 0.0222 memory: 5826 grad_norm: 4.2740 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0745 loss: 2.0745 2022/10/08 08:07:05 - mmengine - INFO - Epoch(train) [118][120/2119] lr: 4.0000e-03 eta: 6:44:36 time: 0.3233 data_time: 0.0236 memory: 5826 grad_norm: 4.1508 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7929 loss: 1.7929 2022/10/08 08:07:12 - mmengine - INFO - Epoch(train) [118][140/2119] lr: 4.0000e-03 eta: 6:44:29 time: 0.3812 data_time: 0.0164 memory: 5826 grad_norm: 4.1771 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0324 loss: 2.0324 2022/10/08 08:07:19 - mmengine - INFO - Epoch(train) [118][160/2119] lr: 4.0000e-03 eta: 6:44:22 time: 0.3127 data_time: 0.0198 memory: 5826 grad_norm: 4.2727 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0847 loss: 2.0847 2022/10/08 08:07:26 - mmengine - INFO - Epoch(train) [118][180/2119] lr: 4.0000e-03 eta: 6:44:15 time: 0.3785 data_time: 0.0246 memory: 5826 grad_norm: 4.2651 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0388 loss: 2.0388 2022/10/08 08:07:33 - mmengine - INFO - Epoch(train) [118][200/2119] lr: 4.0000e-03 eta: 6:44:08 time: 0.3567 data_time: 0.0234 memory: 5826 grad_norm: 4.2942 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9782 loss: 1.9782 2022/10/08 08:07:40 - mmengine - INFO - Epoch(train) [118][220/2119] lr: 4.0000e-03 eta: 6:44:01 time: 0.3523 data_time: 0.0209 memory: 5826 grad_norm: 4.3333 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0753 loss: 2.0753 2022/10/08 08:07:47 - mmengine - INFO - Epoch(train) [118][240/2119] lr: 4.0000e-03 eta: 6:43:54 time: 0.3235 data_time: 0.0248 memory: 5826 grad_norm: 4.2953 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9396 loss: 1.9396 2022/10/08 08:07:54 - mmengine - INFO - Epoch(train) [118][260/2119] lr: 4.0000e-03 eta: 6:43:47 time: 0.3756 data_time: 0.0175 memory: 5826 grad_norm: 4.3515 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1960 loss: 2.1960 2022/10/08 08:08:01 - mmengine - INFO - Epoch(train) [118][280/2119] lr: 4.0000e-03 eta: 6:43:40 time: 0.3390 data_time: 0.0226 memory: 5826 grad_norm: 4.1794 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9866 loss: 1.9866 2022/10/08 08:08:08 - mmengine - INFO - Epoch(train) [118][300/2119] lr: 4.0000e-03 eta: 6:43:33 time: 0.3449 data_time: 0.0185 memory: 5826 grad_norm: 4.2835 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.7437 loss: 1.7437 2022/10/08 08:08:15 - mmengine - INFO - Epoch(train) [118][320/2119] lr: 4.0000e-03 eta: 6:43:26 time: 0.3389 data_time: 0.0292 memory: 5826 grad_norm: 4.2571 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0499 loss: 2.0499 2022/10/08 08:08:22 - mmengine - INFO - Epoch(train) [118][340/2119] lr: 4.0000e-03 eta: 6:43:20 time: 0.3554 data_time: 0.0237 memory: 5826 grad_norm: 4.2779 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1771 loss: 2.1771 2022/10/08 08:08:29 - mmengine - INFO - Epoch(train) [118][360/2119] lr: 4.0000e-03 eta: 6:43:13 time: 0.3308 data_time: 0.0226 memory: 5826 grad_norm: 4.2644 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0866 loss: 2.0866 2022/10/08 08:08:36 - mmengine - INFO - Epoch(train) [118][380/2119] lr: 4.0000e-03 eta: 6:43:06 time: 0.3773 data_time: 0.0265 memory: 5826 grad_norm: 4.2640 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9314 loss: 1.9314 2022/10/08 08:08:43 - mmengine - INFO - Epoch(train) [118][400/2119] lr: 4.0000e-03 eta: 6:42:59 time: 0.3246 data_time: 0.0228 memory: 5826 grad_norm: 4.2681 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0342 loss: 2.0342 2022/10/08 08:08:50 - mmengine - INFO - Epoch(train) [118][420/2119] lr: 4.0000e-03 eta: 6:42:52 time: 0.3613 data_time: 0.0240 memory: 5826 grad_norm: 4.2756 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6946 loss: 1.6946 2022/10/08 08:08:57 - mmengine - INFO - Epoch(train) [118][440/2119] lr: 4.0000e-03 eta: 6:42:45 time: 0.3414 data_time: 0.0193 memory: 5826 grad_norm: 4.1987 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 2.0286 loss: 2.0286 2022/10/08 08:09:04 - mmengine - INFO - Epoch(train) [118][460/2119] lr: 4.0000e-03 eta: 6:42:38 time: 0.3772 data_time: 0.0215 memory: 5826 grad_norm: 4.2348 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0584 loss: 2.0584 2022/10/08 08:09:11 - mmengine - INFO - Epoch(train) [118][480/2119] lr: 4.0000e-03 eta: 6:42:31 time: 0.3432 data_time: 0.0207 memory: 5826 grad_norm: 4.2535 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2172 loss: 2.2172 2022/10/08 08:09:18 - mmengine - INFO - Epoch(train) [118][500/2119] lr: 4.0000e-03 eta: 6:42:24 time: 0.3596 data_time: 0.0197 memory: 5826 grad_norm: 4.1693 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8678 loss: 1.8678 2022/10/08 08:09:26 - mmengine - INFO - Epoch(train) [118][520/2119] lr: 4.0000e-03 eta: 6:42:17 time: 0.3699 data_time: 0.0184 memory: 5826 grad_norm: 4.3792 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0502 loss: 2.0502 2022/10/08 08:09:33 - mmengine - INFO - Epoch(train) [118][540/2119] lr: 4.0000e-03 eta: 6:42:10 time: 0.3761 data_time: 0.0245 memory: 5826 grad_norm: 4.3379 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0284 loss: 2.0284 2022/10/08 08:09:40 - mmengine - INFO - Epoch(train) [118][560/2119] lr: 4.0000e-03 eta: 6:42:03 time: 0.3259 data_time: 0.0220 memory: 5826 grad_norm: 4.2639 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0436 loss: 2.0436 2022/10/08 08:09:47 - mmengine - INFO - Epoch(train) [118][580/2119] lr: 4.0000e-03 eta: 6:41:56 time: 0.3472 data_time: 0.0178 memory: 5826 grad_norm: 4.2935 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9664 loss: 1.9664 2022/10/08 08:09:53 - mmengine - INFO - Epoch(train) [118][600/2119] lr: 4.0000e-03 eta: 6:41:49 time: 0.3238 data_time: 0.0269 memory: 5826 grad_norm: 4.3993 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.1500 loss: 2.1500 2022/10/08 08:10:00 - mmengine - INFO - Epoch(train) [118][620/2119] lr: 4.0000e-03 eta: 6:41:42 time: 0.3194 data_time: 0.0223 memory: 5826 grad_norm: 4.2289 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9251 loss: 1.9251 2022/10/08 08:10:08 - mmengine - INFO - Epoch(train) [118][640/2119] lr: 4.0000e-03 eta: 6:41:36 time: 0.4043 data_time: 0.0266 memory: 5826 grad_norm: 4.3287 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0756 loss: 2.0756 2022/10/08 08:10:14 - mmengine - INFO - Epoch(train) [118][660/2119] lr: 4.0000e-03 eta: 6:41:28 time: 0.3119 data_time: 0.0225 memory: 5826 grad_norm: 4.3933 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1961 loss: 2.1961 2022/10/08 08:10:21 - mmengine - INFO - Epoch(train) [118][680/2119] lr: 4.0000e-03 eta: 6:41:21 time: 0.3374 data_time: 0.0182 memory: 5826 grad_norm: 4.3545 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 2.0249 loss: 2.0249 2022/10/08 08:10:28 - mmengine - INFO - Epoch(train) [118][700/2119] lr: 4.0000e-03 eta: 6:41:15 time: 0.3725 data_time: 0.0180 memory: 5826 grad_norm: 4.2831 top1_acc: 0.3750 top5_acc: 0.9375 loss_cls: 1.8387 loss: 1.8387 2022/10/08 08:10:35 - mmengine - INFO - Epoch(train) [118][720/2119] lr: 4.0000e-03 eta: 6:41:08 time: 0.3287 data_time: 0.0229 memory: 5826 grad_norm: 4.2346 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0919 loss: 2.0919 2022/10/08 08:10:42 - mmengine - INFO - Epoch(train) [118][740/2119] lr: 4.0000e-03 eta: 6:41:01 time: 0.3768 data_time: 0.0228 memory: 5826 grad_norm: 4.2163 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9492 loss: 1.9492 2022/10/08 08:10:49 - mmengine - INFO - Epoch(train) [118][760/2119] lr: 4.0000e-03 eta: 6:40:54 time: 0.3178 data_time: 0.0238 memory: 5826 grad_norm: 4.3286 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.2468 loss: 2.2468 2022/10/08 08:10:56 - mmengine - INFO - Epoch(train) [118][780/2119] lr: 4.0000e-03 eta: 6:40:47 time: 0.3482 data_time: 0.0247 memory: 5826 grad_norm: 4.2555 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0426 loss: 2.0426 2022/10/08 08:11:04 - mmengine - INFO - Epoch(train) [118][800/2119] lr: 4.0000e-03 eta: 6:40:40 time: 0.3995 data_time: 0.0222 memory: 5826 grad_norm: 4.2633 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1236 loss: 2.1236 2022/10/08 08:11:10 - mmengine - INFO - Epoch(train) [118][820/2119] lr: 4.0000e-03 eta: 6:40:33 time: 0.3273 data_time: 0.0198 memory: 5826 grad_norm: 4.2535 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7039 loss: 1.7039 2022/10/08 08:11:17 - mmengine - INFO - Epoch(train) [118][840/2119] lr: 4.0000e-03 eta: 6:40:26 time: 0.3272 data_time: 0.0253 memory: 5826 grad_norm: 4.6854 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0570 loss: 2.0570 2022/10/08 08:11:24 - mmengine - INFO - Epoch(train) [118][860/2119] lr: 4.0000e-03 eta: 6:40:19 time: 0.3714 data_time: 0.0262 memory: 5826 grad_norm: 4.3767 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0582 loss: 2.0582 2022/10/08 08:11:31 - mmengine - INFO - Epoch(train) [118][880/2119] lr: 4.0000e-03 eta: 6:40:12 time: 0.3172 data_time: 0.0257 memory: 5826 grad_norm: 4.3552 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9489 loss: 1.9489 2022/10/08 08:11:38 - mmengine - INFO - Epoch(train) [118][900/2119] lr: 4.0000e-03 eta: 6:40:05 time: 0.3514 data_time: 0.0222 memory: 5826 grad_norm: 4.3632 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9962 loss: 1.9962 2022/10/08 08:11:45 - mmengine - INFO - Epoch(train) [118][920/2119] lr: 4.0000e-03 eta: 6:39:58 time: 0.3882 data_time: 0.0212 memory: 5826 grad_norm: 4.2831 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0127 loss: 2.0127 2022/10/08 08:11:53 - mmengine - INFO - Epoch(train) [118][940/2119] lr: 4.0000e-03 eta: 6:39:52 time: 0.3965 data_time: 0.0225 memory: 5826 grad_norm: 4.2598 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8605 loss: 1.8605 2022/10/08 08:12:01 - mmengine - INFO - Epoch(train) [118][960/2119] lr: 4.0000e-03 eta: 6:39:45 time: 0.3725 data_time: 0.0257 memory: 5826 grad_norm: 4.2268 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0452 loss: 2.0452 2022/10/08 08:12:07 - mmengine - INFO - Epoch(train) [118][980/2119] lr: 4.0000e-03 eta: 6:39:38 time: 0.3134 data_time: 0.0258 memory: 5826 grad_norm: 4.2745 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9537 loss: 1.9537 2022/10/08 08:12:15 - mmengine - INFO - Epoch(train) [118][1000/2119] lr: 4.0000e-03 eta: 6:39:31 time: 0.3984 data_time: 0.0228 memory: 5826 grad_norm: 4.2560 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9765 loss: 1.9765 2022/10/08 08:12:21 - mmengine - INFO - Epoch(train) [118][1020/2119] lr: 4.0000e-03 eta: 6:39:24 time: 0.2953 data_time: 0.0202 memory: 5826 grad_norm: 4.2922 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0626 loss: 2.0626 2022/10/08 08:12:28 - mmengine - INFO - Epoch(train) [118][1040/2119] lr: 4.0000e-03 eta: 6:39:17 time: 0.3738 data_time: 0.0186 memory: 5826 grad_norm: 4.2915 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1616 loss: 2.1616 2022/10/08 08:12:35 - mmengine - INFO - Epoch(train) [118][1060/2119] lr: 4.0000e-03 eta: 6:39:10 time: 0.3209 data_time: 0.0308 memory: 5826 grad_norm: 4.2934 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0533 loss: 2.0533 2022/10/08 08:12:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 08:12:43 - mmengine - INFO - Epoch(train) [118][1080/2119] lr: 4.0000e-03 eta: 6:39:03 time: 0.3912 data_time: 0.0235 memory: 5826 grad_norm: 4.3294 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8572 loss: 1.8572 2022/10/08 08:12:49 - mmengine - INFO - Epoch(train) [118][1100/2119] lr: 4.0000e-03 eta: 6:38:56 time: 0.3272 data_time: 0.0213 memory: 5826 grad_norm: 4.3313 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8482 loss: 1.8482 2022/10/08 08:12:57 - mmengine - INFO - Epoch(train) [118][1120/2119] lr: 4.0000e-03 eta: 6:38:49 time: 0.3805 data_time: 0.0190 memory: 5826 grad_norm: 4.3100 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9100 loss: 1.9100 2022/10/08 08:13:04 - mmengine - INFO - Epoch(train) [118][1140/2119] lr: 4.0000e-03 eta: 6:38:42 time: 0.3530 data_time: 0.0213 memory: 5826 grad_norm: 4.2891 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9864 loss: 1.9864 2022/10/08 08:13:12 - mmengine - INFO - Epoch(train) [118][1160/2119] lr: 4.0000e-03 eta: 6:38:36 time: 0.3870 data_time: 0.0219 memory: 5826 grad_norm: 4.2723 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.8520 loss: 1.8520 2022/10/08 08:13:18 - mmengine - INFO - Epoch(train) [118][1180/2119] lr: 4.0000e-03 eta: 6:38:28 time: 0.3233 data_time: 0.0290 memory: 5826 grad_norm: 4.3019 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1622 loss: 2.1622 2022/10/08 08:13:25 - mmengine - INFO - Epoch(train) [118][1200/2119] lr: 4.0000e-03 eta: 6:38:22 time: 0.3668 data_time: 0.0275 memory: 5826 grad_norm: 4.3286 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.0145 loss: 2.0145 2022/10/08 08:13:33 - mmengine - INFO - Epoch(train) [118][1220/2119] lr: 4.0000e-03 eta: 6:38:15 time: 0.3547 data_time: 0.0215 memory: 5826 grad_norm: 4.3614 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.2730 loss: 2.2730 2022/10/08 08:13:40 - mmengine - INFO - Epoch(train) [118][1240/2119] lr: 4.0000e-03 eta: 6:38:08 time: 0.3549 data_time: 0.0271 memory: 5826 grad_norm: 4.3159 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8643 loss: 1.8643 2022/10/08 08:13:46 - mmengine - INFO - Epoch(train) [118][1260/2119] lr: 4.0000e-03 eta: 6:38:01 time: 0.3273 data_time: 0.0269 memory: 5826 grad_norm: 4.3519 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0854 loss: 2.0854 2022/10/08 08:13:53 - mmengine - INFO - Epoch(train) [118][1280/2119] lr: 4.0000e-03 eta: 6:37:54 time: 0.3464 data_time: 0.0233 memory: 5826 grad_norm: 4.3557 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8773 loss: 1.8773 2022/10/08 08:13:59 - mmengine - INFO - Epoch(train) [118][1300/2119] lr: 4.0000e-03 eta: 6:37:47 time: 0.3085 data_time: 0.0251 memory: 5826 grad_norm: 4.2525 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9557 loss: 1.9557 2022/10/08 08:14:08 - mmengine - INFO - Epoch(train) [118][1320/2119] lr: 4.0000e-03 eta: 6:37:40 time: 0.4098 data_time: 0.0283 memory: 5826 grad_norm: 4.3106 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 1.9611 loss: 1.9611 2022/10/08 08:14:14 - mmengine - INFO - Epoch(train) [118][1340/2119] lr: 4.0000e-03 eta: 6:37:33 time: 0.3136 data_time: 0.0237 memory: 5826 grad_norm: 4.3283 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0441 loss: 2.0441 2022/10/08 08:14:22 - mmengine - INFO - Epoch(train) [118][1360/2119] lr: 4.0000e-03 eta: 6:37:26 time: 0.4179 data_time: 0.0268 memory: 5826 grad_norm: 4.3200 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3395 loss: 2.3395 2022/10/08 08:14:29 - mmengine - INFO - Epoch(train) [118][1380/2119] lr: 4.0000e-03 eta: 6:37:19 time: 0.3239 data_time: 0.0193 memory: 5826 grad_norm: 4.2940 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1784 loss: 2.1784 2022/10/08 08:14:36 - mmengine - INFO - Epoch(train) [118][1400/2119] lr: 4.0000e-03 eta: 6:37:12 time: 0.3539 data_time: 0.0212 memory: 5826 grad_norm: 4.3906 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0094 loss: 2.0094 2022/10/08 08:14:42 - mmengine - INFO - Epoch(train) [118][1420/2119] lr: 4.0000e-03 eta: 6:37:05 time: 0.3212 data_time: 0.0220 memory: 5826 grad_norm: 4.3202 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7604 loss: 1.7604 2022/10/08 08:14:49 - mmengine - INFO - Epoch(train) [118][1440/2119] lr: 4.0000e-03 eta: 6:36:58 time: 0.3577 data_time: 0.0289 memory: 5826 grad_norm: 4.3894 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7537 loss: 1.7537 2022/10/08 08:14:56 - mmengine - INFO - Epoch(train) [118][1460/2119] lr: 4.0000e-03 eta: 6:36:51 time: 0.3521 data_time: 0.0246 memory: 5826 grad_norm: 4.2749 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0806 loss: 2.0806 2022/10/08 08:15:03 - mmengine - INFO - Epoch(train) [118][1480/2119] lr: 4.0000e-03 eta: 6:36:44 time: 0.3115 data_time: 0.0233 memory: 5826 grad_norm: 4.3486 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 1.9974 loss: 1.9974 2022/10/08 08:15:10 - mmengine - INFO - Epoch(train) [118][1500/2119] lr: 4.0000e-03 eta: 6:36:37 time: 0.3631 data_time: 0.0267 memory: 5826 grad_norm: 4.2851 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.0511 loss: 2.0511 2022/10/08 08:15:17 - mmengine - INFO - Epoch(train) [118][1520/2119] lr: 4.0000e-03 eta: 6:36:30 time: 0.3438 data_time: 0.0226 memory: 5826 grad_norm: 4.3577 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0605 loss: 2.0605 2022/10/08 08:15:25 - mmengine - INFO - Epoch(train) [118][1540/2119] lr: 4.0000e-03 eta: 6:36:24 time: 0.3846 data_time: 0.0242 memory: 5826 grad_norm: 4.3178 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8937 loss: 1.8937 2022/10/08 08:15:32 - mmengine - INFO - Epoch(train) [118][1560/2119] lr: 4.0000e-03 eta: 6:36:17 time: 0.3529 data_time: 0.0223 memory: 5826 grad_norm: 4.3012 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.8684 loss: 1.8684 2022/10/08 08:15:39 - mmengine - INFO - Epoch(train) [118][1580/2119] lr: 4.0000e-03 eta: 6:36:10 time: 0.3706 data_time: 0.0234 memory: 5826 grad_norm: 4.2828 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0306 loss: 2.0306 2022/10/08 08:15:46 - mmengine - INFO - Epoch(train) [118][1600/2119] lr: 4.0000e-03 eta: 6:36:03 time: 0.3689 data_time: 0.0214 memory: 5826 grad_norm: 4.2839 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0376 loss: 2.0376 2022/10/08 08:15:54 - mmengine - INFO - Epoch(train) [118][1620/2119] lr: 4.0000e-03 eta: 6:35:56 time: 0.3600 data_time: 0.0261 memory: 5826 grad_norm: 4.2520 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1155 loss: 2.1155 2022/10/08 08:16:00 - mmengine - INFO - Epoch(train) [118][1640/2119] lr: 4.0000e-03 eta: 6:35:49 time: 0.3043 data_time: 0.0207 memory: 5826 grad_norm: 4.2218 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7005 loss: 1.7005 2022/10/08 08:16:07 - mmengine - INFO - Epoch(train) [118][1660/2119] lr: 4.0000e-03 eta: 6:35:42 time: 0.3848 data_time: 0.0241 memory: 5826 grad_norm: 4.3164 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.9533 loss: 1.9533 2022/10/08 08:16:15 - mmengine - INFO - Epoch(train) [118][1680/2119] lr: 4.0000e-03 eta: 6:35:35 time: 0.3622 data_time: 0.0223 memory: 5826 grad_norm: 4.2581 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1313 loss: 2.1313 2022/10/08 08:16:22 - mmengine - INFO - Epoch(train) [118][1700/2119] lr: 4.0000e-03 eta: 6:35:28 time: 0.3509 data_time: 0.0213 memory: 5826 grad_norm: 4.2557 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.9715 loss: 1.9715 2022/10/08 08:16:28 - mmengine - INFO - Epoch(train) [118][1720/2119] lr: 4.0000e-03 eta: 6:35:21 time: 0.3240 data_time: 0.0226 memory: 5826 grad_norm: 4.2342 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1912 loss: 2.1912 2022/10/08 08:16:35 - mmengine - INFO - Epoch(train) [118][1740/2119] lr: 4.0000e-03 eta: 6:35:14 time: 0.3476 data_time: 0.0249 memory: 5826 grad_norm: 4.2573 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0733 loss: 2.0733 2022/10/08 08:16:42 - mmengine - INFO - Epoch(train) [118][1760/2119] lr: 4.0000e-03 eta: 6:35:07 time: 0.3335 data_time: 0.0222 memory: 5826 grad_norm: 4.3069 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0377 loss: 2.0377 2022/10/08 08:16:49 - mmengine - INFO - Epoch(train) [118][1780/2119] lr: 4.0000e-03 eta: 6:35:00 time: 0.3732 data_time: 0.0199 memory: 5826 grad_norm: 4.3163 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8347 loss: 1.8347 2022/10/08 08:16:56 - mmengine - INFO - Epoch(train) [118][1800/2119] lr: 4.0000e-03 eta: 6:34:53 time: 0.3242 data_time: 0.0225 memory: 5826 grad_norm: 4.3421 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8915 loss: 1.8915 2022/10/08 08:17:02 - mmengine - INFO - Epoch(train) [118][1820/2119] lr: 4.0000e-03 eta: 6:34:46 time: 0.3355 data_time: 0.0265 memory: 5826 grad_norm: 4.3096 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7728 loss: 1.7728 2022/10/08 08:17:10 - mmengine - INFO - Epoch(train) [118][1840/2119] lr: 4.0000e-03 eta: 6:34:39 time: 0.3577 data_time: 0.0194 memory: 5826 grad_norm: 4.3039 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0754 loss: 2.0754 2022/10/08 08:17:16 - mmengine - INFO - Epoch(train) [118][1860/2119] lr: 4.0000e-03 eta: 6:34:32 time: 0.3376 data_time: 0.0218 memory: 5826 grad_norm: 4.3735 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.8445 loss: 1.8445 2022/10/08 08:17:24 - mmengine - INFO - Epoch(train) [118][1880/2119] lr: 4.0000e-03 eta: 6:34:26 time: 0.3851 data_time: 0.0188 memory: 5826 grad_norm: 4.2720 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1924 loss: 2.1924 2022/10/08 08:17:30 - mmengine - INFO - Epoch(train) [118][1900/2119] lr: 4.0000e-03 eta: 6:34:18 time: 0.3098 data_time: 0.0216 memory: 5826 grad_norm: 4.3089 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9484 loss: 1.9484 2022/10/08 08:17:37 - mmengine - INFO - Epoch(train) [118][1920/2119] lr: 4.0000e-03 eta: 6:34:11 time: 0.3354 data_time: 0.0254 memory: 5826 grad_norm: 4.3167 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9410 loss: 1.9410 2022/10/08 08:17:45 - mmengine - INFO - Epoch(train) [118][1940/2119] lr: 4.0000e-03 eta: 6:34:05 time: 0.3975 data_time: 0.0229 memory: 5826 grad_norm: 4.3717 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0540 loss: 2.0540 2022/10/08 08:17:51 - mmengine - INFO - Epoch(train) [118][1960/2119] lr: 4.0000e-03 eta: 6:33:58 time: 0.3008 data_time: 0.0227 memory: 5826 grad_norm: 4.2918 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7761 loss: 1.7761 2022/10/08 08:17:59 - mmengine - INFO - Epoch(train) [118][1980/2119] lr: 4.0000e-03 eta: 6:33:51 time: 0.3985 data_time: 0.0202 memory: 5826 grad_norm: 4.3145 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.9861 loss: 1.9861 2022/10/08 08:18:06 - mmengine - INFO - Epoch(train) [118][2000/2119] lr: 4.0000e-03 eta: 6:33:44 time: 0.3278 data_time: 0.0192 memory: 5826 grad_norm: 4.2404 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9403 loss: 1.9403 2022/10/08 08:18:12 - mmengine - INFO - Epoch(train) [118][2020/2119] lr: 4.0000e-03 eta: 6:33:37 time: 0.3279 data_time: 0.0200 memory: 5826 grad_norm: 4.3997 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 1.8792 loss: 1.8792 2022/10/08 08:18:19 - mmengine - INFO - Epoch(train) [118][2040/2119] lr: 4.0000e-03 eta: 6:33:30 time: 0.3345 data_time: 0.0185 memory: 5826 grad_norm: 4.3884 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0089 loss: 2.0089 2022/10/08 08:18:26 - mmengine - INFO - Epoch(train) [118][2060/2119] lr: 4.0000e-03 eta: 6:33:23 time: 0.3570 data_time: 0.0196 memory: 5826 grad_norm: 4.2871 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8930 loss: 1.8930 2022/10/08 08:18:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 08:18:33 - mmengine - INFO - Epoch(train) [118][2080/2119] lr: 4.0000e-03 eta: 6:33:16 time: 0.3483 data_time: 0.0171 memory: 5826 grad_norm: 4.3745 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0894 loss: 2.0894 2022/10/08 08:18:40 - mmengine - INFO - Epoch(train) [118][2100/2119] lr: 4.0000e-03 eta: 6:33:09 time: 0.3492 data_time: 0.0178 memory: 5826 grad_norm: 4.3623 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.2073 loss: 2.2073 2022/10/08 08:18:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 08:18:46 - mmengine - INFO - Epoch(train) [118][2119/2119] lr: 4.0000e-03 eta: 6:33:09 time: 0.3309 data_time: 0.0214 memory: 5826 grad_norm: 4.3799 top1_acc: 0.6000 top5_acc: 1.0000 loss_cls: 2.0302 loss: 2.0302 2022/10/08 08:18:56 - mmengine - INFO - Epoch(train) [119][20/2119] lr: 4.0000e-03 eta: 6:32:54 time: 0.4729 data_time: 0.1145 memory: 5826 grad_norm: 4.2890 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.0369 loss: 2.0369 2022/10/08 08:19:03 - mmengine - INFO - Epoch(train) [119][40/2119] lr: 4.0000e-03 eta: 6:32:47 time: 0.3565 data_time: 0.0203 memory: 5826 grad_norm: 4.2635 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.2268 loss: 2.2268 2022/10/08 08:19:10 - mmengine - INFO - Epoch(train) [119][60/2119] lr: 4.0000e-03 eta: 6:32:40 time: 0.3614 data_time: 0.0378 memory: 5826 grad_norm: 4.2973 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 1.8948 loss: 1.8948 2022/10/08 08:19:17 - mmengine - INFO - Epoch(train) [119][80/2119] lr: 4.0000e-03 eta: 6:32:33 time: 0.3333 data_time: 0.0179 memory: 5826 grad_norm: 4.3782 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0828 loss: 2.0828 2022/10/08 08:19:24 - mmengine - INFO - Epoch(train) [119][100/2119] lr: 4.0000e-03 eta: 6:32:26 time: 0.3464 data_time: 0.0259 memory: 5826 grad_norm: 4.3322 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1598 loss: 2.1598 2022/10/08 08:19:30 - mmengine - INFO - Epoch(train) [119][120/2119] lr: 4.0000e-03 eta: 6:32:19 time: 0.3265 data_time: 0.0210 memory: 5826 grad_norm: 4.3374 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9738 loss: 1.9738 2022/10/08 08:19:37 - mmengine - INFO - Epoch(train) [119][140/2119] lr: 4.0000e-03 eta: 6:32:12 time: 0.3519 data_time: 0.0239 memory: 5826 grad_norm: 4.3959 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.2386 loss: 2.2386 2022/10/08 08:19:45 - mmengine - INFO - Epoch(train) [119][160/2119] lr: 4.0000e-03 eta: 6:32:06 time: 0.3936 data_time: 0.0209 memory: 5826 grad_norm: 4.3082 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.7935 loss: 1.7935 2022/10/08 08:19:51 - mmengine - INFO - Epoch(train) [119][180/2119] lr: 4.0000e-03 eta: 6:31:58 time: 0.2851 data_time: 0.0232 memory: 5826 grad_norm: 4.3667 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.9725 loss: 1.9725 2022/10/08 08:19:58 - mmengine - INFO - Epoch(train) [119][200/2119] lr: 4.0000e-03 eta: 6:31:52 time: 0.3565 data_time: 0.0228 memory: 5826 grad_norm: 4.4228 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0014 loss: 2.0014 2022/10/08 08:20:06 - mmengine - INFO - Epoch(train) [119][220/2119] lr: 4.0000e-03 eta: 6:31:45 time: 0.3912 data_time: 0.0215 memory: 5826 grad_norm: 4.3377 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.9226 loss: 1.9226 2022/10/08 08:20:13 - mmengine - INFO - Epoch(train) [119][240/2119] lr: 4.0000e-03 eta: 6:31:38 time: 0.3676 data_time: 0.0337 memory: 5826 grad_norm: 4.3169 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0359 loss: 2.0359 2022/10/08 08:20:20 - mmengine - INFO - Epoch(train) [119][260/2119] lr: 4.0000e-03 eta: 6:31:31 time: 0.3212 data_time: 0.0208 memory: 5826 grad_norm: 4.3904 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0388 loss: 2.0388 2022/10/08 08:20:27 - mmengine - INFO - Epoch(train) [119][280/2119] lr: 4.0000e-03 eta: 6:31:24 time: 0.3366 data_time: 0.0253 memory: 5826 grad_norm: 4.2850 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0652 loss: 2.0652 2022/10/08 08:20:34 - mmengine - INFO - Epoch(train) [119][300/2119] lr: 4.0000e-03 eta: 6:31:17 time: 0.3646 data_time: 0.0274 memory: 5826 grad_norm: 4.3393 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9269 loss: 1.9269 2022/10/08 08:20:40 - mmengine - INFO - Epoch(train) [119][320/2119] lr: 4.0000e-03 eta: 6:31:10 time: 0.3162 data_time: 0.0177 memory: 5826 grad_norm: 4.3106 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8184 loss: 1.8184 2022/10/08 08:20:47 - mmengine - INFO - Epoch(train) [119][340/2119] lr: 4.0000e-03 eta: 6:31:03 time: 0.3417 data_time: 0.0236 memory: 5826 grad_norm: 4.3242 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.7392 loss: 1.7392 2022/10/08 08:20:54 - mmengine - INFO - Epoch(train) [119][360/2119] lr: 4.0000e-03 eta: 6:30:56 time: 0.3609 data_time: 0.0264 memory: 5826 grad_norm: 4.3547 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8653 loss: 1.8653 2022/10/08 08:21:01 - mmengine - INFO - Epoch(train) [119][380/2119] lr: 4.0000e-03 eta: 6:30:49 time: 0.3461 data_time: 0.0234 memory: 5826 grad_norm: 4.3544 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9602 loss: 1.9602 2022/10/08 08:21:08 - mmengine - INFO - Epoch(train) [119][400/2119] lr: 4.0000e-03 eta: 6:30:42 time: 0.3560 data_time: 0.0234 memory: 5826 grad_norm: 4.3105 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9817 loss: 1.9817 2022/10/08 08:21:15 - mmengine - INFO - Epoch(train) [119][420/2119] lr: 4.0000e-03 eta: 6:30:35 time: 0.3217 data_time: 0.0230 memory: 5826 grad_norm: 4.3748 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0942 loss: 2.0942 2022/10/08 08:21:22 - mmengine - INFO - Epoch(train) [119][440/2119] lr: 4.0000e-03 eta: 6:30:28 time: 0.3594 data_time: 0.0199 memory: 5826 grad_norm: 4.4388 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1040 loss: 2.1040 2022/10/08 08:21:29 - mmengine - INFO - Epoch(train) [119][460/2119] lr: 4.0000e-03 eta: 6:30:21 time: 0.3472 data_time: 0.0201 memory: 5826 grad_norm: 4.3042 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9734 loss: 1.9734 2022/10/08 08:21:36 - mmengine - INFO - Epoch(train) [119][480/2119] lr: 4.0000e-03 eta: 6:30:14 time: 0.3788 data_time: 0.0206 memory: 5826 grad_norm: 4.2579 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0584 loss: 2.0584 2022/10/08 08:21:43 - mmengine - INFO - Epoch(train) [119][500/2119] lr: 4.0000e-03 eta: 6:30:07 time: 0.3349 data_time: 0.0226 memory: 5826 grad_norm: 4.3488 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.7658 loss: 1.7658 2022/10/08 08:21:51 - mmengine - INFO - Epoch(train) [119][520/2119] lr: 4.0000e-03 eta: 6:30:01 time: 0.3936 data_time: 0.0215 memory: 5826 grad_norm: 4.3119 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0105 loss: 2.0105 2022/10/08 08:21:58 - mmengine - INFO - Epoch(train) [119][540/2119] lr: 4.0000e-03 eta: 6:29:54 time: 0.3241 data_time: 0.0257 memory: 5826 grad_norm: 4.3115 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.2845 loss: 2.2845 2022/10/08 08:22:05 - mmengine - INFO - Epoch(train) [119][560/2119] lr: 4.0000e-03 eta: 6:29:47 time: 0.3705 data_time: 0.0240 memory: 5826 grad_norm: 4.2807 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0123 loss: 2.0123 2022/10/08 08:22:11 - mmengine - INFO - Epoch(train) [119][580/2119] lr: 4.0000e-03 eta: 6:29:40 time: 0.3109 data_time: 0.0237 memory: 5826 grad_norm: 4.3183 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0744 loss: 2.0744 2022/10/08 08:22:19 - mmengine - INFO - Epoch(train) [119][600/2119] lr: 4.0000e-03 eta: 6:29:33 time: 0.3662 data_time: 0.0285 memory: 5826 grad_norm: 4.3425 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1314 loss: 2.1314 2022/10/08 08:22:25 - mmengine - INFO - Epoch(train) [119][620/2119] lr: 4.0000e-03 eta: 6:29:26 time: 0.3351 data_time: 0.0261 memory: 5826 grad_norm: 4.3714 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9291 loss: 1.9291 2022/10/08 08:22:33 - mmengine - INFO - Epoch(train) [119][640/2119] lr: 4.0000e-03 eta: 6:29:19 time: 0.3644 data_time: 0.0218 memory: 5826 grad_norm: 4.3621 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.9210 loss: 1.9210 2022/10/08 08:22:40 - mmengine - INFO - Epoch(train) [119][660/2119] lr: 4.0000e-03 eta: 6:29:12 time: 0.3497 data_time: 0.0242 memory: 5826 grad_norm: 4.3962 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.0612 loss: 2.0612 2022/10/08 08:22:48 - mmengine - INFO - Epoch(train) [119][680/2119] lr: 4.0000e-03 eta: 6:29:05 time: 0.4050 data_time: 0.0198 memory: 5826 grad_norm: 4.3969 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8973 loss: 1.8973 2022/10/08 08:22:54 - mmengine - INFO - Epoch(train) [119][700/2119] lr: 4.0000e-03 eta: 6:28:58 time: 0.3214 data_time: 0.0257 memory: 5826 grad_norm: 4.3209 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9648 loss: 1.9648 2022/10/08 08:23:01 - mmengine - INFO - Epoch(train) [119][720/2119] lr: 4.0000e-03 eta: 6:28:51 time: 0.3459 data_time: 0.0187 memory: 5826 grad_norm: 4.3402 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8071 loss: 1.8071 2022/10/08 08:23:08 - mmengine - INFO - Epoch(train) [119][740/2119] lr: 4.0000e-03 eta: 6:28:44 time: 0.3481 data_time: 0.0232 memory: 5826 grad_norm: 4.3407 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9157 loss: 1.9157 2022/10/08 08:23:15 - mmengine - INFO - Epoch(train) [119][760/2119] lr: 4.0000e-03 eta: 6:28:37 time: 0.3572 data_time: 0.0194 memory: 5826 grad_norm: 4.4064 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1670 loss: 2.1670 2022/10/08 08:23:22 - mmengine - INFO - Epoch(train) [119][780/2119] lr: 4.0000e-03 eta: 6:28:30 time: 0.3220 data_time: 0.0204 memory: 5826 grad_norm: 4.3172 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9955 loss: 1.9955 2022/10/08 08:23:30 - mmengine - INFO - Epoch(train) [119][800/2119] lr: 4.0000e-03 eta: 6:28:24 time: 0.4007 data_time: 0.0199 memory: 5826 grad_norm: 4.3172 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9424 loss: 1.9424 2022/10/08 08:23:36 - mmengine - INFO - Epoch(train) [119][820/2119] lr: 4.0000e-03 eta: 6:28:16 time: 0.3183 data_time: 0.0228 memory: 5826 grad_norm: 4.3425 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.8894 loss: 1.8894 2022/10/08 08:23:43 - mmengine - INFO - Epoch(train) [119][840/2119] lr: 4.0000e-03 eta: 6:28:10 time: 0.3666 data_time: 0.0263 memory: 5826 grad_norm: 4.2989 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.1059 loss: 2.1059 2022/10/08 08:23:49 - mmengine - INFO - Epoch(train) [119][860/2119] lr: 4.0000e-03 eta: 6:28:02 time: 0.3079 data_time: 0.0257 memory: 5826 grad_norm: 4.2689 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2242 loss: 2.2242 2022/10/08 08:23:57 - mmengine - INFO - Epoch(train) [119][880/2119] lr: 4.0000e-03 eta: 6:27:56 time: 0.3962 data_time: 0.0187 memory: 5826 grad_norm: 4.3041 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0739 loss: 2.0739 2022/10/08 08:24:04 - mmengine - INFO - Epoch(train) [119][900/2119] lr: 4.0000e-03 eta: 6:27:49 time: 0.3207 data_time: 0.0234 memory: 5826 grad_norm: 4.3534 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1721 loss: 2.1721 2022/10/08 08:24:11 - mmengine - INFO - Epoch(train) [119][920/2119] lr: 4.0000e-03 eta: 6:27:42 time: 0.3388 data_time: 0.0246 memory: 5826 grad_norm: 4.3634 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.9880 loss: 1.9880 2022/10/08 08:24:17 - mmengine - INFO - Epoch(train) [119][940/2119] lr: 4.0000e-03 eta: 6:27:35 time: 0.3239 data_time: 0.0234 memory: 5826 grad_norm: 4.2815 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7399 loss: 1.7399 2022/10/08 08:24:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 08:24:25 - mmengine - INFO - Epoch(train) [119][960/2119] lr: 4.0000e-03 eta: 6:27:28 time: 0.4115 data_time: 0.0237 memory: 5826 grad_norm: 4.2993 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.1454 loss: 2.1454 2022/10/08 08:24:31 - mmengine - INFO - Epoch(train) [119][980/2119] lr: 4.0000e-03 eta: 6:27:21 time: 0.2884 data_time: 0.0232 memory: 5826 grad_norm: 4.3271 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1321 loss: 2.1321 2022/10/08 08:24:38 - mmengine - INFO - Epoch(train) [119][1000/2119] lr: 4.0000e-03 eta: 6:27:14 time: 0.3642 data_time: 0.0221 memory: 5826 grad_norm: 4.2954 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9430 loss: 1.9430 2022/10/08 08:24:45 - mmengine - INFO - Epoch(train) [119][1020/2119] lr: 4.0000e-03 eta: 6:27:07 time: 0.3174 data_time: 0.0245 memory: 5826 grad_norm: 4.4483 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.7795 loss: 1.7795 2022/10/08 08:24:52 - mmengine - INFO - Epoch(train) [119][1040/2119] lr: 4.0000e-03 eta: 6:27:00 time: 0.3570 data_time: 0.0208 memory: 5826 grad_norm: 4.3894 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9482 loss: 1.9482 2022/10/08 08:24:59 - mmengine - INFO - Epoch(train) [119][1060/2119] lr: 4.0000e-03 eta: 6:26:53 time: 0.3461 data_time: 0.0225 memory: 5826 grad_norm: 4.3759 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2032 loss: 2.2032 2022/10/08 08:25:07 - mmengine - INFO - Epoch(train) [119][1080/2119] lr: 4.0000e-03 eta: 6:26:46 time: 0.4059 data_time: 0.0216 memory: 5826 grad_norm: 4.3717 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0023 loss: 2.0023 2022/10/08 08:25:14 - mmengine - INFO - Epoch(train) [119][1100/2119] lr: 4.0000e-03 eta: 6:26:39 time: 0.3624 data_time: 0.0207 memory: 5826 grad_norm: 4.3044 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.1785 loss: 2.1785 2022/10/08 08:25:21 - mmengine - INFO - Epoch(train) [119][1120/2119] lr: 4.0000e-03 eta: 6:26:32 time: 0.3372 data_time: 0.0245 memory: 5826 grad_norm: 4.3578 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1552 loss: 2.1552 2022/10/08 08:25:27 - mmengine - INFO - Epoch(train) [119][1140/2119] lr: 4.0000e-03 eta: 6:26:25 time: 0.3178 data_time: 0.0226 memory: 5826 grad_norm: 4.4237 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2164 loss: 2.2164 2022/10/08 08:25:35 - mmengine - INFO - Epoch(train) [119][1160/2119] lr: 4.0000e-03 eta: 6:26:18 time: 0.3777 data_time: 0.0306 memory: 5826 grad_norm: 4.3650 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9754 loss: 1.9754 2022/10/08 08:25:42 - mmengine - INFO - Epoch(train) [119][1180/2119] lr: 4.0000e-03 eta: 6:26:11 time: 0.3568 data_time: 0.0215 memory: 5826 grad_norm: 4.3326 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.0638 loss: 2.0638 2022/10/08 08:25:49 - mmengine - INFO - Epoch(train) [119][1200/2119] lr: 4.0000e-03 eta: 6:26:04 time: 0.3402 data_time: 0.0208 memory: 5826 grad_norm: 4.2525 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1126 loss: 2.1126 2022/10/08 08:25:56 - mmengine - INFO - Epoch(train) [119][1220/2119] lr: 4.0000e-03 eta: 6:25:57 time: 0.3377 data_time: 0.0235 memory: 5826 grad_norm: 4.3778 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2031 loss: 2.2031 2022/10/08 08:26:03 - mmengine - INFO - Epoch(train) [119][1240/2119] lr: 4.0000e-03 eta: 6:25:51 time: 0.3627 data_time: 0.0224 memory: 5826 grad_norm: 4.3401 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1709 loss: 2.1709 2022/10/08 08:26:09 - mmengine - INFO - Epoch(train) [119][1260/2119] lr: 4.0000e-03 eta: 6:25:43 time: 0.3238 data_time: 0.0208 memory: 5826 grad_norm: 4.3199 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9354 loss: 1.9354 2022/10/08 08:26:18 - mmengine - INFO - Epoch(train) [119][1280/2119] lr: 4.0000e-03 eta: 6:25:37 time: 0.4119 data_time: 0.0232 memory: 5826 grad_norm: 4.3155 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9376 loss: 1.9376 2022/10/08 08:26:24 - mmengine - INFO - Epoch(train) [119][1300/2119] lr: 4.0000e-03 eta: 6:25:30 time: 0.3251 data_time: 0.0233 memory: 5826 grad_norm: 4.4587 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7980 loss: 1.7980 2022/10/08 08:26:31 - mmengine - INFO - Epoch(train) [119][1320/2119] lr: 4.0000e-03 eta: 6:25:23 time: 0.3210 data_time: 0.0284 memory: 5826 grad_norm: 4.4575 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1926 loss: 2.1926 2022/10/08 08:26:37 - mmengine - INFO - Epoch(train) [119][1340/2119] lr: 4.0000e-03 eta: 6:25:16 time: 0.3317 data_time: 0.0216 memory: 5826 grad_norm: 4.3026 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8161 loss: 1.8161 2022/10/08 08:26:44 - mmengine - INFO - Epoch(train) [119][1360/2119] lr: 4.0000e-03 eta: 6:25:09 time: 0.3579 data_time: 0.0238 memory: 5826 grad_norm: 4.3036 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9492 loss: 1.9492 2022/10/08 08:26:51 - mmengine - INFO - Epoch(train) [119][1380/2119] lr: 4.0000e-03 eta: 6:25:02 time: 0.3545 data_time: 0.0207 memory: 5826 grad_norm: 4.3103 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9867 loss: 1.9867 2022/10/08 08:26:59 - mmengine - INFO - Epoch(train) [119][1400/2119] lr: 4.0000e-03 eta: 6:24:55 time: 0.3773 data_time: 0.0239 memory: 5826 grad_norm: 4.3315 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1379 loss: 2.1379 2022/10/08 08:27:05 - mmengine - INFO - Epoch(train) [119][1420/2119] lr: 4.0000e-03 eta: 6:24:48 time: 0.3188 data_time: 0.0232 memory: 5826 grad_norm: 4.4023 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2627 loss: 2.2627 2022/10/08 08:27:14 - mmengine - INFO - Epoch(train) [119][1440/2119] lr: 4.0000e-03 eta: 6:24:41 time: 0.4158 data_time: 0.0348 memory: 5826 grad_norm: 4.3254 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.8885 loss: 1.8885 2022/10/08 08:27:19 - mmengine - INFO - Epoch(train) [119][1460/2119] lr: 4.0000e-03 eta: 6:24:34 time: 0.2853 data_time: 0.0218 memory: 5826 grad_norm: 4.3246 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9347 loss: 1.9347 2022/10/08 08:27:27 - mmengine - INFO - Epoch(train) [119][1480/2119] lr: 4.0000e-03 eta: 6:24:27 time: 0.3914 data_time: 0.0218 memory: 5826 grad_norm: 4.3455 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1405 loss: 2.1405 2022/10/08 08:27:33 - mmengine - INFO - Epoch(train) [119][1500/2119] lr: 4.0000e-03 eta: 6:24:20 time: 0.2916 data_time: 0.0215 memory: 5826 grad_norm: 4.3821 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0312 loss: 2.0312 2022/10/08 08:27:41 - mmengine - INFO - Epoch(train) [119][1520/2119] lr: 4.0000e-03 eta: 6:24:13 time: 0.3892 data_time: 0.0231 memory: 5826 grad_norm: 4.4391 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7895 loss: 1.7895 2022/10/08 08:27:47 - mmengine - INFO - Epoch(train) [119][1540/2119] lr: 4.0000e-03 eta: 6:24:06 time: 0.3073 data_time: 0.0225 memory: 5826 grad_norm: 4.3536 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1319 loss: 2.1319 2022/10/08 08:27:55 - mmengine - INFO - Epoch(train) [119][1560/2119] lr: 4.0000e-03 eta: 6:23:59 time: 0.3850 data_time: 0.0216 memory: 5826 grad_norm: 4.3209 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.1671 loss: 2.1671 2022/10/08 08:28:01 - mmengine - INFO - Epoch(train) [119][1580/2119] lr: 4.0000e-03 eta: 6:23:52 time: 0.3325 data_time: 0.0234 memory: 5826 grad_norm: 4.3477 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8320 loss: 1.8320 2022/10/08 08:28:08 - mmengine - INFO - Epoch(train) [119][1600/2119] lr: 4.0000e-03 eta: 6:23:45 time: 0.3093 data_time: 0.0269 memory: 5826 grad_norm: 4.3789 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0283 loss: 2.0283 2022/10/08 08:28:15 - mmengine - INFO - Epoch(train) [119][1620/2119] lr: 4.0000e-03 eta: 6:23:38 time: 0.3784 data_time: 0.0203 memory: 5826 grad_norm: 4.3484 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9863 loss: 1.9863 2022/10/08 08:28:21 - mmengine - INFO - Epoch(train) [119][1640/2119] lr: 4.0000e-03 eta: 6:23:31 time: 0.3090 data_time: 0.0270 memory: 5826 grad_norm: 4.3701 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0083 loss: 2.0083 2022/10/08 08:28:29 - mmengine - INFO - Epoch(train) [119][1660/2119] lr: 4.0000e-03 eta: 6:23:24 time: 0.3725 data_time: 0.0192 memory: 5826 grad_norm: 4.3248 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0708 loss: 2.0708 2022/10/08 08:28:36 - mmengine - INFO - Epoch(train) [119][1680/2119] lr: 4.0000e-03 eta: 6:23:17 time: 0.3426 data_time: 0.0247 memory: 5826 grad_norm: 4.4268 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2097 loss: 2.2097 2022/10/08 08:28:43 - mmengine - INFO - Epoch(train) [119][1700/2119] lr: 4.0000e-03 eta: 6:23:10 time: 0.3545 data_time: 0.0217 memory: 5826 grad_norm: 4.3886 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8527 loss: 1.8527 2022/10/08 08:28:50 - mmengine - INFO - Epoch(train) [119][1720/2119] lr: 4.0000e-03 eta: 6:23:04 time: 0.3542 data_time: 0.0260 memory: 5826 grad_norm: 4.3589 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8658 loss: 1.8658 2022/10/08 08:28:57 - mmengine - INFO - Epoch(train) [119][1740/2119] lr: 4.0000e-03 eta: 6:22:57 time: 0.3415 data_time: 0.0248 memory: 5826 grad_norm: 4.3172 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8489 loss: 1.8489 2022/10/08 08:29:04 - mmengine - INFO - Epoch(train) [119][1760/2119] lr: 4.0000e-03 eta: 6:22:50 time: 0.3687 data_time: 0.0224 memory: 5826 grad_norm: 4.3970 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0346 loss: 2.0346 2022/10/08 08:29:11 - mmengine - INFO - Epoch(train) [119][1780/2119] lr: 4.0000e-03 eta: 6:22:43 time: 0.3324 data_time: 0.0229 memory: 5826 grad_norm: 4.3391 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0595 loss: 2.0595 2022/10/08 08:29:19 - mmengine - INFO - Epoch(train) [119][1800/2119] lr: 4.0000e-03 eta: 6:22:36 time: 0.3944 data_time: 0.0217 memory: 5826 grad_norm: 4.4352 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8321 loss: 1.8321 2022/10/08 08:29:26 - mmengine - INFO - Epoch(train) [119][1820/2119] lr: 4.0000e-03 eta: 6:22:29 time: 0.3549 data_time: 0.0225 memory: 5826 grad_norm: 4.3467 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0360 loss: 2.0360 2022/10/08 08:29:34 - mmengine - INFO - Epoch(train) [119][1840/2119] lr: 4.0000e-03 eta: 6:22:22 time: 0.3938 data_time: 0.0229 memory: 5826 grad_norm: 4.3492 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1423 loss: 2.1423 2022/10/08 08:29:40 - mmengine - INFO - Epoch(train) [119][1860/2119] lr: 4.0000e-03 eta: 6:22:15 time: 0.3280 data_time: 0.0238 memory: 5826 grad_norm: 4.4420 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1576 loss: 2.1576 2022/10/08 08:29:47 - mmengine - INFO - Epoch(train) [119][1880/2119] lr: 4.0000e-03 eta: 6:22:08 time: 0.3559 data_time: 0.0221 memory: 5826 grad_norm: 4.3787 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.1636 loss: 2.1636 2022/10/08 08:29:53 - mmengine - INFO - Epoch(train) [119][1900/2119] lr: 4.0000e-03 eta: 6:22:01 time: 0.2997 data_time: 0.0277 memory: 5826 grad_norm: 4.2847 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2165 loss: 2.2165 2022/10/08 08:29:59 - mmengine - INFO - Epoch(train) [119][1920/2119] lr: 4.0000e-03 eta: 6:21:54 time: 0.2915 data_time: 0.0276 memory: 5826 grad_norm: 4.3837 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.2697 loss: 2.2697 2022/10/08 08:30:06 - mmengine - INFO - Epoch(train) [119][1940/2119] lr: 4.0000e-03 eta: 6:21:47 time: 0.3585 data_time: 0.0224 memory: 5826 grad_norm: 4.3260 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1514 loss: 2.1514 2022/10/08 08:30:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 08:30:14 - mmengine - INFO - Epoch(train) [119][1960/2119] lr: 4.0000e-03 eta: 6:21:40 time: 0.3725 data_time: 0.0174 memory: 5826 grad_norm: 4.3962 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0121 loss: 2.0121 2022/10/08 08:30:21 - mmengine - INFO - Epoch(train) [119][1980/2119] lr: 4.0000e-03 eta: 6:21:33 time: 0.3571 data_time: 0.0194 memory: 5826 grad_norm: 4.3198 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0740 loss: 2.0740 2022/10/08 08:30:27 - mmengine - INFO - Epoch(train) [119][2000/2119] lr: 4.0000e-03 eta: 6:21:26 time: 0.3221 data_time: 0.0217 memory: 5826 grad_norm: 4.3428 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0024 loss: 2.0024 2022/10/08 08:30:35 - mmengine - INFO - Epoch(train) [119][2020/2119] lr: 4.0000e-03 eta: 6:21:19 time: 0.3932 data_time: 0.0270 memory: 5826 grad_norm: 4.4041 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.1024 loss: 2.1024 2022/10/08 08:30:42 - mmengine - INFO - Epoch(train) [119][2040/2119] lr: 4.0000e-03 eta: 6:21:12 time: 0.3354 data_time: 0.0193 memory: 5826 grad_norm: 4.3632 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.3546 loss: 2.3546 2022/10/08 08:30:50 - mmengine - INFO - Epoch(train) [119][2060/2119] lr: 4.0000e-03 eta: 6:21:06 time: 0.3951 data_time: 0.0190 memory: 5826 grad_norm: 4.3620 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.2783 loss: 2.2783 2022/10/08 08:30:56 - mmengine - INFO - Epoch(train) [119][2080/2119] lr: 4.0000e-03 eta: 6:20:59 time: 0.3042 data_time: 0.0285 memory: 5826 grad_norm: 4.4554 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2050 loss: 2.2050 2022/10/08 08:31:03 - mmengine - INFO - Epoch(train) [119][2100/2119] lr: 4.0000e-03 eta: 6:20:52 time: 0.3378 data_time: 0.0238 memory: 5826 grad_norm: 4.2920 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9722 loss: 1.9722 2022/10/08 08:31:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 08:31:09 - mmengine - INFO - Epoch(train) [119][2119/2119] lr: 4.0000e-03 eta: 6:20:52 time: 0.3035 data_time: 0.0231 memory: 5826 grad_norm: 4.4301 top1_acc: 0.6000 top5_acc: 1.0000 loss_cls: 2.1520 loss: 2.1520 2022/10/08 08:31:18 - mmengine - INFO - Epoch(train) [120][20/2119] lr: 4.0000e-03 eta: 6:20:37 time: 0.4753 data_time: 0.1473 memory: 5826 grad_norm: 4.3892 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0158 loss: 2.0158 2022/10/08 08:31:25 - mmengine - INFO - Epoch(train) [120][40/2119] lr: 4.0000e-03 eta: 6:20:30 time: 0.3328 data_time: 0.0221 memory: 5826 grad_norm: 4.3918 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9395 loss: 1.9395 2022/10/08 08:31:33 - mmengine - INFO - Epoch(train) [120][60/2119] lr: 4.0000e-03 eta: 6:20:23 time: 0.3947 data_time: 0.0214 memory: 5826 grad_norm: 4.4093 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.7048 loss: 1.7048 2022/10/08 08:31:39 - mmengine - INFO - Epoch(train) [120][80/2119] lr: 4.0000e-03 eta: 6:20:16 time: 0.3188 data_time: 0.0250 memory: 5826 grad_norm: 4.2557 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.9668 loss: 1.9668 2022/10/08 08:31:47 - mmengine - INFO - Epoch(train) [120][100/2119] lr: 4.0000e-03 eta: 6:20:09 time: 0.3845 data_time: 0.0204 memory: 5826 grad_norm: 4.3449 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0657 loss: 2.0657 2022/10/08 08:31:54 - mmengine - INFO - Epoch(train) [120][120/2119] lr: 4.0000e-03 eta: 6:20:02 time: 0.3465 data_time: 0.0247 memory: 5826 grad_norm: 4.3637 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.9128 loss: 1.9128 2022/10/08 08:32:01 - mmengine - INFO - Epoch(train) [120][140/2119] lr: 4.0000e-03 eta: 6:19:56 time: 0.3884 data_time: 0.0227 memory: 5826 grad_norm: 4.3380 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7165 loss: 1.7165 2022/10/08 08:32:08 - mmengine - INFO - Epoch(train) [120][160/2119] lr: 4.0000e-03 eta: 6:19:49 time: 0.3249 data_time: 0.0225 memory: 5826 grad_norm: 4.4524 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.1808 loss: 2.1808 2022/10/08 08:32:15 - mmengine - INFO - Epoch(train) [120][180/2119] lr: 4.0000e-03 eta: 6:19:42 time: 0.3686 data_time: 0.0212 memory: 5826 grad_norm: 4.3542 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.1164 loss: 2.1164 2022/10/08 08:32:22 - mmengine - INFO - Epoch(train) [120][200/2119] lr: 4.0000e-03 eta: 6:19:35 time: 0.3196 data_time: 0.0265 memory: 5826 grad_norm: 4.4264 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8617 loss: 1.8617 2022/10/08 08:32:29 - mmengine - INFO - Epoch(train) [120][220/2119] lr: 4.0000e-03 eta: 6:19:28 time: 0.3553 data_time: 0.0211 memory: 5826 grad_norm: 4.3788 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8759 loss: 1.8759 2022/10/08 08:32:36 - mmengine - INFO - Epoch(train) [120][240/2119] lr: 4.0000e-03 eta: 6:19:21 time: 0.3517 data_time: 0.0214 memory: 5826 grad_norm: 4.3592 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.7210 loss: 1.7210 2022/10/08 08:32:43 - mmengine - INFO - Epoch(train) [120][260/2119] lr: 4.0000e-03 eta: 6:19:14 time: 0.3718 data_time: 0.0230 memory: 5826 grad_norm: 4.3425 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8689 loss: 1.8689 2022/10/08 08:32:50 - mmengine - INFO - Epoch(train) [120][280/2119] lr: 4.0000e-03 eta: 6:19:07 time: 0.3352 data_time: 0.0264 memory: 5826 grad_norm: 4.3824 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1458 loss: 2.1458 2022/10/08 08:32:57 - mmengine - INFO - Epoch(train) [120][300/2119] lr: 4.0000e-03 eta: 6:19:00 time: 0.3632 data_time: 0.0229 memory: 5826 grad_norm: 4.4503 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7973 loss: 1.7973 2022/10/08 08:33:04 - mmengine - INFO - Epoch(train) [120][320/2119] lr: 4.0000e-03 eta: 6:18:53 time: 0.3362 data_time: 0.0243 memory: 5826 grad_norm: 4.4284 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1497 loss: 2.1497 2022/10/08 08:33:11 - mmengine - INFO - Epoch(train) [120][340/2119] lr: 4.0000e-03 eta: 6:18:46 time: 0.3632 data_time: 0.0229 memory: 5826 grad_norm: 4.3664 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9432 loss: 1.9432 2022/10/08 08:33:18 - mmengine - INFO - Epoch(train) [120][360/2119] lr: 4.0000e-03 eta: 6:18:39 time: 0.3555 data_time: 0.0239 memory: 5826 grad_norm: 4.3657 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8104 loss: 1.8104 2022/10/08 08:33:26 - mmengine - INFO - Epoch(train) [120][380/2119] lr: 4.0000e-03 eta: 6:18:32 time: 0.3923 data_time: 0.0208 memory: 5826 grad_norm: 4.3944 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.1199 loss: 2.1199 2022/10/08 08:33:32 - mmengine - INFO - Epoch(train) [120][400/2119] lr: 4.0000e-03 eta: 6:18:25 time: 0.3076 data_time: 0.0246 memory: 5826 grad_norm: 4.4032 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9206 loss: 1.9206 2022/10/08 08:33:41 - mmengine - INFO - Epoch(train) [120][420/2119] lr: 4.0000e-03 eta: 6:18:19 time: 0.4202 data_time: 0.0239 memory: 5826 grad_norm: 4.3482 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8915 loss: 1.8915 2022/10/08 08:33:48 - mmengine - INFO - Epoch(train) [120][440/2119] lr: 4.0000e-03 eta: 6:18:12 time: 0.3515 data_time: 0.0228 memory: 5826 grad_norm: 4.3166 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4446 loss: 2.4446 2022/10/08 08:33:56 - mmengine - INFO - Epoch(train) [120][460/2119] lr: 4.0000e-03 eta: 6:18:05 time: 0.4222 data_time: 0.0198 memory: 5826 grad_norm: 4.4074 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2463 loss: 2.2463 2022/10/08 08:34:02 - mmengine - INFO - Epoch(train) [120][480/2119] lr: 4.0000e-03 eta: 6:17:58 time: 0.3006 data_time: 0.0242 memory: 5826 grad_norm: 4.3982 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8751 loss: 1.8751 2022/10/08 08:34:09 - mmengine - INFO - Epoch(train) [120][500/2119] lr: 4.0000e-03 eta: 6:17:51 time: 0.3526 data_time: 0.0247 memory: 5826 grad_norm: 4.3142 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9135 loss: 1.9135 2022/10/08 08:34:17 - mmengine - INFO - Epoch(train) [120][520/2119] lr: 4.0000e-03 eta: 6:17:44 time: 0.3526 data_time: 0.0251 memory: 5826 grad_norm: 4.3902 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8046 loss: 1.8046 2022/10/08 08:34:23 - mmengine - INFO - Epoch(train) [120][540/2119] lr: 4.0000e-03 eta: 6:17:37 time: 0.3381 data_time: 0.0237 memory: 5826 grad_norm: 4.3609 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9926 loss: 1.9926 2022/10/08 08:34:30 - mmengine - INFO - Epoch(train) [120][560/2119] lr: 4.0000e-03 eta: 6:17:30 time: 0.3347 data_time: 0.0253 memory: 5826 grad_norm: 4.4183 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0778 loss: 2.0778 2022/10/08 08:34:37 - mmengine - INFO - Epoch(train) [120][580/2119] lr: 4.0000e-03 eta: 6:17:23 time: 0.3733 data_time: 0.0258 memory: 5826 grad_norm: 4.4530 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8773 loss: 1.8773 2022/10/08 08:34:44 - mmengine - INFO - Epoch(train) [120][600/2119] lr: 4.0000e-03 eta: 6:17:16 time: 0.3056 data_time: 0.0208 memory: 5826 grad_norm: 4.4265 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0096 loss: 2.0096 2022/10/08 08:34:52 - mmengine - INFO - Epoch(train) [120][620/2119] lr: 4.0000e-03 eta: 6:17:10 time: 0.4145 data_time: 0.0223 memory: 5826 grad_norm: 4.3538 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.0899 loss: 2.0899 2022/10/08 08:34:58 - mmengine - INFO - Epoch(train) [120][640/2119] lr: 4.0000e-03 eta: 6:17:02 time: 0.3173 data_time: 0.0283 memory: 5826 grad_norm: 4.3667 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1447 loss: 2.1447 2022/10/08 08:35:06 - mmengine - INFO - Epoch(train) [120][660/2119] lr: 4.0000e-03 eta: 6:16:56 time: 0.3705 data_time: 0.0199 memory: 5826 grad_norm: 4.3451 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9457 loss: 1.9457 2022/10/08 08:35:13 - mmengine - INFO - Epoch(train) [120][680/2119] lr: 4.0000e-03 eta: 6:16:49 time: 0.3578 data_time: 0.0235 memory: 5826 grad_norm: 4.4313 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2892 loss: 2.2892 2022/10/08 08:35:21 - mmengine - INFO - Epoch(train) [120][700/2119] lr: 4.0000e-03 eta: 6:16:42 time: 0.4093 data_time: 0.0203 memory: 5826 grad_norm: 4.4281 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7981 loss: 1.7981 2022/10/08 08:35:27 - mmengine - INFO - Epoch(train) [120][720/2119] lr: 4.0000e-03 eta: 6:16:35 time: 0.3089 data_time: 0.0251 memory: 5826 grad_norm: 4.3701 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8203 loss: 1.8203 2022/10/08 08:35:35 - mmengine - INFO - Epoch(train) [120][740/2119] lr: 4.0000e-03 eta: 6:16:28 time: 0.4024 data_time: 0.0262 memory: 5826 grad_norm: 4.3507 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.8032 loss: 1.8032 2022/10/08 08:35:41 - mmengine - INFO - Epoch(train) [120][760/2119] lr: 4.0000e-03 eta: 6:16:21 time: 0.3028 data_time: 0.0240 memory: 5826 grad_norm: 4.4428 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.1565 loss: 2.1565 2022/10/08 08:35:49 - mmengine - INFO - Epoch(train) [120][780/2119] lr: 4.0000e-03 eta: 6:16:14 time: 0.3713 data_time: 0.0201 memory: 5826 grad_norm: 4.3841 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.9608 loss: 1.9608 2022/10/08 08:35:57 - mmengine - INFO - Epoch(train) [120][800/2119] lr: 4.0000e-03 eta: 6:16:08 time: 0.4222 data_time: 0.0275 memory: 5826 grad_norm: 4.4001 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1666 loss: 2.1666 2022/10/08 08:36:04 - mmengine - INFO - Epoch(train) [120][820/2119] lr: 4.0000e-03 eta: 6:16:01 time: 0.3599 data_time: 0.0218 memory: 5826 grad_norm: 4.3811 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1716 loss: 2.1716 2022/10/08 08:36:11 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 08:36:11 - mmengine - INFO - Epoch(train) [120][840/2119] lr: 4.0000e-03 eta: 6:15:54 time: 0.3250 data_time: 0.0200 memory: 5826 grad_norm: 4.4046 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9801 loss: 1.9801 2022/10/08 08:36:19 - mmengine - INFO - Epoch(train) [120][860/2119] lr: 4.0000e-03 eta: 6:15:47 time: 0.4167 data_time: 0.0191 memory: 5826 grad_norm: 4.4158 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8938 loss: 1.8938 2022/10/08 08:36:25 - mmengine - INFO - Epoch(train) [120][880/2119] lr: 4.0000e-03 eta: 6:15:40 time: 0.3110 data_time: 0.0238 memory: 5826 grad_norm: 4.3711 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1319 loss: 2.1319 2022/10/08 08:36:33 - mmengine - INFO - Epoch(train) [120][900/2119] lr: 4.0000e-03 eta: 6:15:33 time: 0.3658 data_time: 0.0283 memory: 5826 grad_norm: 4.4042 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.1801 loss: 2.1801 2022/10/08 08:36:40 - mmengine - INFO - Epoch(train) [120][920/2119] lr: 4.0000e-03 eta: 6:15:26 time: 0.3715 data_time: 0.0237 memory: 5826 grad_norm: 4.3329 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.0472 loss: 2.0472 2022/10/08 08:36:46 - mmengine - INFO - Epoch(train) [120][940/2119] lr: 4.0000e-03 eta: 6:15:19 time: 0.3064 data_time: 0.0180 memory: 5826 grad_norm: 4.5029 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9723 loss: 1.9723 2022/10/08 08:36:54 - mmengine - INFO - Epoch(train) [120][960/2119] lr: 4.0000e-03 eta: 6:15:12 time: 0.3899 data_time: 0.0225 memory: 5826 grad_norm: 4.3723 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9777 loss: 1.9777 2022/10/08 08:37:02 - mmengine - INFO - Epoch(train) [120][980/2119] lr: 4.0000e-03 eta: 6:15:06 time: 0.4084 data_time: 0.0225 memory: 5826 grad_norm: 4.4101 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9995 loss: 1.9995 2022/10/08 08:37:09 - mmengine - INFO - Epoch(train) [120][1000/2119] lr: 4.0000e-03 eta: 6:14:59 time: 0.3441 data_time: 0.0238 memory: 5826 grad_norm: 4.3752 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9766 loss: 1.9766 2022/10/08 08:37:17 - mmengine - INFO - Epoch(train) [120][1020/2119] lr: 4.0000e-03 eta: 6:14:52 time: 0.3888 data_time: 0.0191 memory: 5826 grad_norm: 4.4187 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9584 loss: 1.9584 2022/10/08 08:37:23 - mmengine - INFO - Epoch(train) [120][1040/2119] lr: 4.0000e-03 eta: 6:14:45 time: 0.3100 data_time: 0.0221 memory: 5826 grad_norm: 4.4644 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0459 loss: 2.0459 2022/10/08 08:37:30 - mmengine - INFO - Epoch(train) [120][1060/2119] lr: 4.0000e-03 eta: 6:14:38 time: 0.3445 data_time: 0.0216 memory: 5826 grad_norm: 4.5314 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8842 loss: 1.8842 2022/10/08 08:37:37 - mmengine - INFO - Epoch(train) [120][1080/2119] lr: 4.0000e-03 eta: 6:14:31 time: 0.3528 data_time: 0.0240 memory: 5826 grad_norm: 4.4294 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0499 loss: 2.0499 2022/10/08 08:37:45 - mmengine - INFO - Epoch(train) [120][1100/2119] lr: 4.0000e-03 eta: 6:14:24 time: 0.3659 data_time: 0.0190 memory: 5826 grad_norm: 4.3475 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9666 loss: 1.9666 2022/10/08 08:37:51 - mmengine - INFO - Epoch(train) [120][1120/2119] lr: 4.0000e-03 eta: 6:14:17 time: 0.3033 data_time: 0.0238 memory: 5826 grad_norm: 4.4207 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8981 loss: 1.8981 2022/10/08 08:37:58 - mmengine - INFO - Epoch(train) [120][1140/2119] lr: 4.0000e-03 eta: 6:14:10 time: 0.3896 data_time: 0.0228 memory: 5826 grad_norm: 4.4873 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.9443 loss: 1.9443 2022/10/08 08:38:05 - mmengine - INFO - Epoch(train) [120][1160/2119] lr: 4.0000e-03 eta: 6:14:03 time: 0.3109 data_time: 0.0248 memory: 5826 grad_norm: 4.3597 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0975 loss: 2.0975 2022/10/08 08:38:12 - mmengine - INFO - Epoch(train) [120][1180/2119] lr: 4.0000e-03 eta: 6:13:56 time: 0.3598 data_time: 0.0206 memory: 5826 grad_norm: 4.3087 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0317 loss: 2.0317 2022/10/08 08:38:19 - mmengine - INFO - Epoch(train) [120][1200/2119] lr: 4.0000e-03 eta: 6:13:49 time: 0.3645 data_time: 0.0232 memory: 5826 grad_norm: 4.4271 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.1249 loss: 2.1249 2022/10/08 08:38:27 - mmengine - INFO - Epoch(train) [120][1220/2119] lr: 4.0000e-03 eta: 6:13:42 time: 0.3875 data_time: 0.0179 memory: 5826 grad_norm: 4.4013 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.3495 loss: 2.3495 2022/10/08 08:38:33 - mmengine - INFO - Epoch(train) [120][1240/2119] lr: 4.0000e-03 eta: 6:13:35 time: 0.3035 data_time: 0.0181 memory: 5826 grad_norm: 4.4114 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.9655 loss: 1.9655 2022/10/08 08:38:41 - mmengine - INFO - Epoch(train) [120][1260/2119] lr: 4.0000e-03 eta: 6:13:28 time: 0.3807 data_time: 0.0251 memory: 5826 grad_norm: 4.4590 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1413 loss: 2.1413 2022/10/08 08:38:47 - mmengine - INFO - Epoch(train) [120][1280/2119] lr: 4.0000e-03 eta: 6:13:21 time: 0.3167 data_time: 0.0240 memory: 5826 grad_norm: 4.3742 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1887 loss: 2.1887 2022/10/08 08:38:54 - mmengine - INFO - Epoch(train) [120][1300/2119] lr: 4.0000e-03 eta: 6:13:14 time: 0.3390 data_time: 0.0234 memory: 5826 grad_norm: 4.4029 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.8461 loss: 1.8461 2022/10/08 08:39:00 - mmengine - INFO - Epoch(train) [120][1320/2119] lr: 4.0000e-03 eta: 6:13:07 time: 0.3366 data_time: 0.0216 memory: 5826 grad_norm: 4.3739 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1862 loss: 2.1862 2022/10/08 08:39:08 - mmengine - INFO - Epoch(train) [120][1340/2119] lr: 4.0000e-03 eta: 6:13:01 time: 0.4013 data_time: 0.0197 memory: 5826 grad_norm: 4.3685 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.2920 loss: 2.2920 2022/10/08 08:39:15 - mmengine - INFO - Epoch(train) [120][1360/2119] lr: 4.0000e-03 eta: 6:12:54 time: 0.3258 data_time: 0.0245 memory: 5826 grad_norm: 4.4066 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0738 loss: 2.0738 2022/10/08 08:39:22 - mmengine - INFO - Epoch(train) [120][1380/2119] lr: 4.0000e-03 eta: 6:12:47 time: 0.3563 data_time: 0.0170 memory: 5826 grad_norm: 4.4244 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.8682 loss: 1.8682 2022/10/08 08:39:29 - mmengine - INFO - Epoch(train) [120][1400/2119] lr: 4.0000e-03 eta: 6:12:40 time: 0.3477 data_time: 0.0251 memory: 5826 grad_norm: 4.4039 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9904 loss: 1.9904 2022/10/08 08:39:36 - mmengine - INFO - Epoch(train) [120][1420/2119] lr: 4.0000e-03 eta: 6:12:33 time: 0.3577 data_time: 0.0233 memory: 5826 grad_norm: 4.4563 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9905 loss: 1.9905 2022/10/08 08:39:43 - mmengine - INFO - Epoch(train) [120][1440/2119] lr: 4.0000e-03 eta: 6:12:26 time: 0.3245 data_time: 0.0201 memory: 5826 grad_norm: 4.4113 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9533 loss: 1.9533 2022/10/08 08:39:51 - mmengine - INFO - Epoch(train) [120][1460/2119] lr: 4.0000e-03 eta: 6:12:19 time: 0.3863 data_time: 0.0229 memory: 5826 grad_norm: 4.4469 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9215 loss: 1.9215 2022/10/08 08:39:57 - mmengine - INFO - Epoch(train) [120][1480/2119] lr: 4.0000e-03 eta: 6:12:12 time: 0.3246 data_time: 0.0232 memory: 5826 grad_norm: 4.4083 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8847 loss: 1.8847 2022/10/08 08:40:04 - mmengine - INFO - Epoch(train) [120][1500/2119] lr: 4.0000e-03 eta: 6:12:05 time: 0.3671 data_time: 0.0204 memory: 5826 grad_norm: 4.4034 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9439 loss: 1.9439 2022/10/08 08:40:11 - mmengine - INFO - Epoch(train) [120][1520/2119] lr: 4.0000e-03 eta: 6:11:58 time: 0.3256 data_time: 0.0290 memory: 5826 grad_norm: 4.4714 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9346 loss: 1.9346 2022/10/08 08:40:18 - mmengine - INFO - Epoch(train) [120][1540/2119] lr: 4.0000e-03 eta: 6:11:51 time: 0.3665 data_time: 0.0207 memory: 5826 grad_norm: 4.4725 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9210 loss: 1.9210 2022/10/08 08:40:26 - mmengine - INFO - Epoch(train) [120][1560/2119] lr: 4.0000e-03 eta: 6:11:44 time: 0.3705 data_time: 0.0224 memory: 5826 grad_norm: 4.4566 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1459 loss: 2.1459 2022/10/08 08:40:32 - mmengine - INFO - Epoch(train) [120][1580/2119] lr: 4.0000e-03 eta: 6:11:37 time: 0.3339 data_time: 0.0186 memory: 5826 grad_norm: 4.4541 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0977 loss: 2.0977 2022/10/08 08:40:39 - mmengine - INFO - Epoch(train) [120][1600/2119] lr: 4.0000e-03 eta: 6:11:30 time: 0.3377 data_time: 0.0228 memory: 5826 grad_norm: 4.5250 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1363 loss: 2.1363 2022/10/08 08:40:46 - mmengine - INFO - Epoch(train) [120][1620/2119] lr: 4.0000e-03 eta: 6:11:23 time: 0.3284 data_time: 0.0233 memory: 5826 grad_norm: 4.3815 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0758 loss: 2.0758 2022/10/08 08:40:53 - mmengine - INFO - Epoch(train) [120][1640/2119] lr: 4.0000e-03 eta: 6:11:16 time: 0.3499 data_time: 0.0245 memory: 5826 grad_norm: 4.4156 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0649 loss: 2.0649 2022/10/08 08:41:00 - mmengine - INFO - Epoch(train) [120][1660/2119] lr: 4.0000e-03 eta: 6:11:09 time: 0.3550 data_time: 0.0182 memory: 5826 grad_norm: 4.4193 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1815 loss: 2.1815 2022/10/08 08:41:07 - mmengine - INFO - Epoch(train) [120][1680/2119] lr: 4.0000e-03 eta: 6:11:02 time: 0.3746 data_time: 0.0221 memory: 5826 grad_norm: 4.4033 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6207 loss: 1.6207 2022/10/08 08:41:14 - mmengine - INFO - Epoch(train) [120][1700/2119] lr: 4.0000e-03 eta: 6:10:55 time: 0.3112 data_time: 0.0260 memory: 5826 grad_norm: 4.3400 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8345 loss: 1.8345 2022/10/08 08:41:21 - mmengine - INFO - Epoch(train) [120][1720/2119] lr: 4.0000e-03 eta: 6:10:49 time: 0.3788 data_time: 0.0223 memory: 5826 grad_norm: 4.3830 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0227 loss: 2.0227 2022/10/08 08:41:28 - mmengine - INFO - Epoch(train) [120][1740/2119] lr: 4.0000e-03 eta: 6:10:42 time: 0.3377 data_time: 0.0225 memory: 5826 grad_norm: 4.3418 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.1709 loss: 2.1709 2022/10/08 08:41:35 - mmengine - INFO - Epoch(train) [120][1760/2119] lr: 4.0000e-03 eta: 6:10:35 time: 0.3747 data_time: 0.0216 memory: 5826 grad_norm: 4.3455 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0196 loss: 2.0196 2022/10/08 08:41:42 - mmengine - INFO - Epoch(train) [120][1780/2119] lr: 4.0000e-03 eta: 6:10:28 time: 0.3180 data_time: 0.0211 memory: 5826 grad_norm: 4.4294 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.7681 loss: 1.7681 2022/10/08 08:41:50 - mmengine - INFO - Epoch(train) [120][1800/2119] lr: 4.0000e-03 eta: 6:10:21 time: 0.3908 data_time: 0.0282 memory: 5826 grad_norm: 4.4632 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0689 loss: 2.0689 2022/10/08 08:41:57 - mmengine - INFO - Epoch(train) [120][1820/2119] lr: 4.0000e-03 eta: 6:10:14 time: 0.3541 data_time: 0.0166 memory: 5826 grad_norm: 4.4465 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1562 loss: 2.1562 2022/10/08 08:42:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 08:42:04 - mmengine - INFO - Epoch(train) [120][1840/2119] lr: 4.0000e-03 eta: 6:10:07 time: 0.3622 data_time: 0.0242 memory: 5826 grad_norm: 4.5346 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9464 loss: 1.9464 2022/10/08 08:42:10 - mmengine - INFO - Epoch(train) [120][1860/2119] lr: 4.0000e-03 eta: 6:10:00 time: 0.3202 data_time: 0.0225 memory: 5826 grad_norm: 4.5054 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9304 loss: 1.9304 2022/10/08 08:42:18 - mmengine - INFO - Epoch(train) [120][1880/2119] lr: 4.0000e-03 eta: 6:09:53 time: 0.3733 data_time: 0.0215 memory: 5826 grad_norm: 4.4300 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.1027 loss: 2.1027 2022/10/08 08:42:24 - mmengine - INFO - Epoch(train) [120][1900/2119] lr: 4.0000e-03 eta: 6:09:46 time: 0.3171 data_time: 0.0202 memory: 5826 grad_norm: 4.4017 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.0878 loss: 2.0878 2022/10/08 08:42:31 - mmengine - INFO - Epoch(train) [120][1920/2119] lr: 4.0000e-03 eta: 6:09:39 time: 0.3624 data_time: 0.0201 memory: 5826 grad_norm: 4.4214 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9279 loss: 1.9279 2022/10/08 08:42:38 - mmengine - INFO - Epoch(train) [120][1940/2119] lr: 4.0000e-03 eta: 6:09:32 time: 0.3434 data_time: 0.0210 memory: 5826 grad_norm: 4.4165 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0705 loss: 2.0705 2022/10/08 08:42:45 - mmengine - INFO - Epoch(train) [120][1960/2119] lr: 4.0000e-03 eta: 6:09:25 time: 0.3523 data_time: 0.0211 memory: 5826 grad_norm: 4.4320 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.2565 loss: 2.2565 2022/10/08 08:42:53 - mmengine - INFO - Epoch(train) [120][1980/2119] lr: 4.0000e-03 eta: 6:09:19 time: 0.4011 data_time: 0.0243 memory: 5826 grad_norm: 4.4166 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9701 loss: 1.9701 2022/10/08 08:43:01 - mmengine - INFO - Epoch(train) [120][2000/2119] lr: 4.0000e-03 eta: 6:09:12 time: 0.3722 data_time: 0.0195 memory: 5826 grad_norm: 4.3598 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9804 loss: 1.9804 2022/10/08 08:43:07 - mmengine - INFO - Epoch(train) [120][2020/2119] lr: 4.0000e-03 eta: 6:09:05 time: 0.3295 data_time: 0.0263 memory: 5826 grad_norm: 4.4279 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6802 loss: 1.6802 2022/10/08 08:43:14 - mmengine - INFO - Epoch(train) [120][2040/2119] lr: 4.0000e-03 eta: 6:08:58 time: 0.3250 data_time: 0.0228 memory: 5826 grad_norm: 4.4490 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.2254 loss: 2.2254 2022/10/08 08:43:21 - mmengine - INFO - Epoch(train) [120][2060/2119] lr: 4.0000e-03 eta: 6:08:51 time: 0.3571 data_time: 0.0220 memory: 5826 grad_norm: 4.3995 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.3236 loss: 2.3236 2022/10/08 08:43:28 - mmengine - INFO - Epoch(train) [120][2080/2119] lr: 4.0000e-03 eta: 6:08:44 time: 0.3527 data_time: 0.0216 memory: 5826 grad_norm: 4.4574 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0584 loss: 2.0584 2022/10/08 08:43:37 - mmengine - INFO - Epoch(train) [120][2100/2119] lr: 4.0000e-03 eta: 6:08:37 time: 0.4282 data_time: 0.0209 memory: 5826 grad_norm: 4.4286 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1720 loss: 2.1720 2022/10/08 08:43:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 08:43:42 - mmengine - INFO - Epoch(train) [120][2119/2119] lr: 4.0000e-03 eta: 6:08:37 time: 0.2965 data_time: 0.0228 memory: 5826 grad_norm: 4.4566 top1_acc: 0.4000 top5_acc: 0.8000 loss_cls: 2.2156 loss: 2.2156 2022/10/08 08:43:42 - mmengine - INFO - Saving checkpoint at 120 epochs 2022/10/08 08:43:52 - mmengine - INFO - Epoch(val) [120][20/137] eta: 0:00:49 time: 0.4243 data_time: 0.3565 memory: 1241 2022/10/08 08:43:58 - mmengine - INFO - Epoch(val) [120][40/137] eta: 0:00:29 time: 0.3035 data_time: 0.2383 memory: 1241 2022/10/08 08:44:05 - mmengine - INFO - Epoch(val) [120][60/137] eta: 0:00:23 time: 0.3024 data_time: 0.2364 memory: 1241 2022/10/08 08:44:10 - mmengine - INFO - Epoch(val) [120][80/137] eta: 0:00:15 time: 0.2641 data_time: 0.1974 memory: 1241 2022/10/08 08:44:17 - mmengine - INFO - Epoch(val) [120][100/137] eta: 0:00:13 time: 0.3550 data_time: 0.2841 memory: 1241 2022/10/08 08:44:22 - mmengine - INFO - Epoch(val) [120][120/137] eta: 0:00:04 time: 0.2631 data_time: 0.1984 memory: 1241 2022/10/08 08:44:33 - mmengine - INFO - Epoch(val) [120][137/137] acc/top1: 0.5420 acc/top5: 0.7688 acc/mean1: 0.5420 2022/10/08 08:44:33 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb/best_acc/top1_epoch_115.pth is removed 2022/10/08 08:44:35 - mmengine - INFO - The best checkpoint with 0.5420 acc/top1 at 120 epoch is saved to best_acc/top1_epoch_120.pth. 2022/10/08 08:44:43 - mmengine - INFO - Epoch(train) [121][20/2119] lr: 4.0000e-03 eta: 6:08:22 time: 0.3925 data_time: 0.1694 memory: 5826 grad_norm: 4.4097 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0597 loss: 2.0597 2022/10/08 08:44:49 - mmengine - INFO - Epoch(train) [121][40/2119] lr: 4.0000e-03 eta: 6:08:15 time: 0.3297 data_time: 0.0633 memory: 5826 grad_norm: 4.4140 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7962 loss: 1.7962 2022/10/08 08:44:57 - mmengine - INFO - Epoch(train) [121][60/2119] lr: 4.0000e-03 eta: 6:08:08 time: 0.3832 data_time: 0.0278 memory: 5826 grad_norm: 4.4148 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.1072 loss: 2.1072 2022/10/08 08:45:04 - mmengine - INFO - Epoch(train) [121][80/2119] lr: 4.0000e-03 eta: 6:08:01 time: 0.3629 data_time: 0.0216 memory: 5826 grad_norm: 4.4374 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1420 loss: 2.1420 2022/10/08 08:45:12 - mmengine - INFO - Epoch(train) [121][100/2119] lr: 4.0000e-03 eta: 6:07:55 time: 0.3921 data_time: 0.0174 memory: 5826 grad_norm: 4.3911 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0485 loss: 2.0485 2022/10/08 08:45:19 - mmengine - INFO - Epoch(train) [121][120/2119] lr: 4.0000e-03 eta: 6:07:48 time: 0.3146 data_time: 0.0241 memory: 5826 grad_norm: 4.3301 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0059 loss: 2.0059 2022/10/08 08:45:27 - mmengine - INFO - Epoch(train) [121][140/2119] lr: 4.0000e-03 eta: 6:07:41 time: 0.3984 data_time: 0.0207 memory: 5826 grad_norm: 4.3798 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0041 loss: 2.0041 2022/10/08 08:45:32 - mmengine - INFO - Epoch(train) [121][160/2119] lr: 4.0000e-03 eta: 6:07:34 time: 0.2950 data_time: 0.0183 memory: 5826 grad_norm: 4.4455 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1443 loss: 2.1443 2022/10/08 08:45:41 - mmengine - INFO - Epoch(train) [121][180/2119] lr: 4.0000e-03 eta: 6:07:27 time: 0.4080 data_time: 0.0226 memory: 5826 grad_norm: 4.4137 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8117 loss: 1.8117 2022/10/08 08:45:47 - mmengine - INFO - Epoch(train) [121][200/2119] lr: 4.0000e-03 eta: 6:07:20 time: 0.3064 data_time: 0.0278 memory: 5826 grad_norm: 4.4268 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9852 loss: 1.9852 2022/10/08 08:45:55 - mmengine - INFO - Epoch(train) [121][220/2119] lr: 4.0000e-03 eta: 6:07:13 time: 0.4356 data_time: 0.0231 memory: 5826 grad_norm: 4.4425 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8491 loss: 1.8491 2022/10/08 08:46:01 - mmengine - INFO - Epoch(train) [121][240/2119] lr: 4.0000e-03 eta: 6:07:06 time: 0.2921 data_time: 0.0223 memory: 5826 grad_norm: 4.3924 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9052 loss: 1.9052 2022/10/08 08:46:10 - mmengine - INFO - Epoch(train) [121][260/2119] lr: 4.0000e-03 eta: 6:07:00 time: 0.4159 data_time: 0.0203 memory: 5826 grad_norm: 4.3954 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9149 loss: 1.9149 2022/10/08 08:46:17 - mmengine - INFO - Epoch(train) [121][280/2119] lr: 4.0000e-03 eta: 6:06:53 time: 0.3641 data_time: 0.0205 memory: 5826 grad_norm: 4.4873 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1873 loss: 2.1873 2022/10/08 08:46:24 - mmengine - INFO - Epoch(train) [121][300/2119] lr: 4.0000e-03 eta: 6:06:46 time: 0.3648 data_time: 0.0255 memory: 5826 grad_norm: 4.5123 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8609 loss: 1.8609 2022/10/08 08:46:31 - mmengine - INFO - Epoch(train) [121][320/2119] lr: 4.0000e-03 eta: 6:06:39 time: 0.3512 data_time: 0.0198 memory: 5826 grad_norm: 4.4160 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8507 loss: 1.8507 2022/10/08 08:46:38 - mmengine - INFO - Epoch(train) [121][340/2119] lr: 4.0000e-03 eta: 6:06:32 time: 0.3574 data_time: 0.0255 memory: 5826 grad_norm: 4.3922 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9000 loss: 1.9000 2022/10/08 08:46:45 - mmengine - INFO - Epoch(train) [121][360/2119] lr: 4.0000e-03 eta: 6:06:25 time: 0.3346 data_time: 0.0222 memory: 5826 grad_norm: 4.4447 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9485 loss: 1.9485 2022/10/08 08:46:53 - mmengine - INFO - Epoch(train) [121][380/2119] lr: 4.0000e-03 eta: 6:06:18 time: 0.3900 data_time: 0.0220 memory: 5826 grad_norm: 4.4332 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9450 loss: 1.9450 2022/10/08 08:46:59 - mmengine - INFO - Epoch(train) [121][400/2119] lr: 4.0000e-03 eta: 6:06:11 time: 0.3094 data_time: 0.0281 memory: 5826 grad_norm: 4.4255 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9863 loss: 1.9863 2022/10/08 08:47:07 - mmengine - INFO - Epoch(train) [121][420/2119] lr: 4.0000e-03 eta: 6:06:04 time: 0.3930 data_time: 0.0224 memory: 5826 grad_norm: 4.3794 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1122 loss: 2.1122 2022/10/08 08:47:13 - mmengine - INFO - Epoch(train) [121][440/2119] lr: 4.0000e-03 eta: 6:05:57 time: 0.3240 data_time: 0.0240 memory: 5826 grad_norm: 4.3841 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.7982 loss: 1.7982 2022/10/08 08:47:20 - mmengine - INFO - Epoch(train) [121][460/2119] lr: 4.0000e-03 eta: 6:05:50 time: 0.3345 data_time: 0.0228 memory: 5826 grad_norm: 4.4393 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.2181 loss: 2.2181 2022/10/08 08:47:27 - mmengine - INFO - Epoch(train) [121][480/2119] lr: 4.0000e-03 eta: 6:05:43 time: 0.3334 data_time: 0.0254 memory: 5826 grad_norm: 4.4461 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8250 loss: 1.8250 2022/10/08 08:47:34 - mmengine - INFO - Epoch(train) [121][500/2119] lr: 4.0000e-03 eta: 6:05:36 time: 0.3384 data_time: 0.0179 memory: 5826 grad_norm: 4.3898 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.9628 loss: 1.9628 2022/10/08 08:47:40 - mmengine - INFO - Epoch(train) [121][520/2119] lr: 4.0000e-03 eta: 6:05:29 time: 0.3201 data_time: 0.0243 memory: 5826 grad_norm: 4.4576 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9092 loss: 1.9092 2022/10/08 08:47:48 - mmengine - INFO - Epoch(train) [121][540/2119] lr: 4.0000e-03 eta: 6:05:22 time: 0.3911 data_time: 0.0177 memory: 5826 grad_norm: 4.4649 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.9440 loss: 1.9440 2022/10/08 08:47:55 - mmengine - INFO - Epoch(train) [121][560/2119] lr: 4.0000e-03 eta: 6:05:15 time: 0.3682 data_time: 0.0308 memory: 5826 grad_norm: 4.3452 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9430 loss: 1.9430 2022/10/08 08:48:02 - mmengine - INFO - Epoch(train) [121][580/2119] lr: 4.0000e-03 eta: 6:05:08 time: 0.3276 data_time: 0.0218 memory: 5826 grad_norm: 4.4177 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 1.9555 loss: 1.9555 2022/10/08 08:48:08 - mmengine - INFO - Epoch(train) [121][600/2119] lr: 4.0000e-03 eta: 6:05:01 time: 0.3246 data_time: 0.0235 memory: 5826 grad_norm: 4.5079 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 2.1055 loss: 2.1055 2022/10/08 08:48:16 - mmengine - INFO - Epoch(train) [121][620/2119] lr: 4.0000e-03 eta: 6:04:55 time: 0.3888 data_time: 0.0204 memory: 5826 grad_norm: 4.4039 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8663 loss: 1.8663 2022/10/08 08:48:23 - mmengine - INFO - Epoch(train) [121][640/2119] lr: 4.0000e-03 eta: 6:04:48 time: 0.3544 data_time: 0.0202 memory: 5826 grad_norm: 4.4104 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9185 loss: 1.9185 2022/10/08 08:48:31 - mmengine - INFO - Epoch(train) [121][660/2119] lr: 4.0000e-03 eta: 6:04:41 time: 0.3723 data_time: 0.0263 memory: 5826 grad_norm: 4.4757 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9889 loss: 1.9889 2022/10/08 08:48:37 - mmengine - INFO - Epoch(train) [121][680/2119] lr: 4.0000e-03 eta: 6:04:34 time: 0.3299 data_time: 0.0259 memory: 5826 grad_norm: 4.4407 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.9309 loss: 1.9309 2022/10/08 08:48:46 - mmengine - INFO - Epoch(train) [121][700/2119] lr: 4.0000e-03 eta: 6:04:27 time: 0.4352 data_time: 0.0208 memory: 5826 grad_norm: 4.4288 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0061 loss: 2.0061 2022/10/08 08:48:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 08:48:52 - mmengine - INFO - Epoch(train) [121][720/2119] lr: 4.0000e-03 eta: 6:04:20 time: 0.3086 data_time: 0.0182 memory: 5826 grad_norm: 4.4012 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9067 loss: 1.9067 2022/10/08 08:48:59 - mmengine - INFO - Epoch(train) [121][740/2119] lr: 4.0000e-03 eta: 6:04:13 time: 0.3453 data_time: 0.0190 memory: 5826 grad_norm: 4.5244 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.0476 loss: 2.0476 2022/10/08 08:49:07 - mmengine - INFO - Epoch(train) [121][760/2119] lr: 4.0000e-03 eta: 6:04:07 time: 0.4166 data_time: 0.0274 memory: 5826 grad_norm: 4.4427 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9976 loss: 1.9976 2022/10/08 08:49:15 - mmengine - INFO - Epoch(train) [121][780/2119] lr: 4.0000e-03 eta: 6:04:00 time: 0.3556 data_time: 0.0173 memory: 5826 grad_norm: 4.4218 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6799 loss: 1.6799 2022/10/08 08:49:21 - mmengine - INFO - Epoch(train) [121][800/2119] lr: 4.0000e-03 eta: 6:03:53 time: 0.3251 data_time: 0.0233 memory: 5826 grad_norm: 4.3924 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9470 loss: 1.9470 2022/10/08 08:49:30 - mmengine - INFO - Epoch(train) [121][820/2119] lr: 4.0000e-03 eta: 6:03:46 time: 0.4290 data_time: 0.0214 memory: 5826 grad_norm: 4.5124 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0371 loss: 2.0371 2022/10/08 08:49:36 - mmengine - INFO - Epoch(train) [121][840/2119] lr: 4.0000e-03 eta: 6:03:39 time: 0.3133 data_time: 0.0234 memory: 5826 grad_norm: 4.4342 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9521 loss: 1.9521 2022/10/08 08:49:43 - mmengine - INFO - Epoch(train) [121][860/2119] lr: 4.0000e-03 eta: 6:03:32 time: 0.3752 data_time: 0.0188 memory: 5826 grad_norm: 4.5258 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0584 loss: 2.0584 2022/10/08 08:49:50 - mmengine - INFO - Epoch(train) [121][880/2119] lr: 4.0000e-03 eta: 6:03:25 time: 0.3067 data_time: 0.0250 memory: 5826 grad_norm: 4.4555 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0897 loss: 2.0897 2022/10/08 08:49:57 - mmengine - INFO - Epoch(train) [121][900/2119] lr: 4.0000e-03 eta: 6:03:18 time: 0.3655 data_time: 0.0211 memory: 5826 grad_norm: 4.4817 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0804 loss: 2.0804 2022/10/08 08:50:04 - mmengine - INFO - Epoch(train) [121][920/2119] lr: 4.0000e-03 eta: 6:03:11 time: 0.3552 data_time: 0.0233 memory: 5826 grad_norm: 4.4207 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.0038 loss: 2.0038 2022/10/08 08:50:11 - mmengine - INFO - Epoch(train) [121][940/2119] lr: 4.0000e-03 eta: 6:03:04 time: 0.3269 data_time: 0.0185 memory: 5826 grad_norm: 4.3509 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9611 loss: 1.9611 2022/10/08 08:50:19 - mmengine - INFO - Epoch(train) [121][960/2119] lr: 4.0000e-03 eta: 6:02:57 time: 0.4035 data_time: 0.0201 memory: 5826 grad_norm: 4.4277 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1382 loss: 2.1382 2022/10/08 08:50:24 - mmengine - INFO - Epoch(train) [121][980/2119] lr: 4.0000e-03 eta: 6:02:50 time: 0.2936 data_time: 0.0188 memory: 5826 grad_norm: 4.4152 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8086 loss: 1.8086 2022/10/08 08:50:31 - mmengine - INFO - Epoch(train) [121][1000/2119] lr: 4.0000e-03 eta: 6:02:43 time: 0.3492 data_time: 0.0234 memory: 5826 grad_norm: 4.4050 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8375 loss: 1.8375 2022/10/08 08:50:39 - mmengine - INFO - Epoch(train) [121][1020/2119] lr: 4.0000e-03 eta: 6:02:36 time: 0.3657 data_time: 0.0273 memory: 5826 grad_norm: 4.5041 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9015 loss: 1.9015 2022/10/08 08:50:46 - mmengine - INFO - Epoch(train) [121][1040/2119] lr: 4.0000e-03 eta: 6:02:29 time: 0.3532 data_time: 0.0266 memory: 5826 grad_norm: 4.5021 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9135 loss: 1.9135 2022/10/08 08:50:53 - mmengine - INFO - Epoch(train) [121][1060/2119] lr: 4.0000e-03 eta: 6:02:23 time: 0.3727 data_time: 0.0209 memory: 5826 grad_norm: 4.3704 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9002 loss: 1.9002 2022/10/08 08:51:00 - mmengine - INFO - Epoch(train) [121][1080/2119] lr: 4.0000e-03 eta: 6:02:15 time: 0.3255 data_time: 0.0174 memory: 5826 grad_norm: 4.3616 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1553 loss: 2.1553 2022/10/08 08:51:07 - mmengine - INFO - Epoch(train) [121][1100/2119] lr: 4.0000e-03 eta: 6:02:09 time: 0.3557 data_time: 0.0192 memory: 5826 grad_norm: 4.4831 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.1981 loss: 2.1981 2022/10/08 08:51:13 - mmengine - INFO - Epoch(train) [121][1120/2119] lr: 4.0000e-03 eta: 6:02:01 time: 0.3251 data_time: 0.0213 memory: 5826 grad_norm: 4.3741 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8278 loss: 1.8278 2022/10/08 08:51:21 - mmengine - INFO - Epoch(train) [121][1140/2119] lr: 4.0000e-03 eta: 6:01:55 time: 0.3924 data_time: 0.0220 memory: 5826 grad_norm: 4.5181 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0108 loss: 2.0108 2022/10/08 08:51:28 - mmengine - INFO - Epoch(train) [121][1160/2119] lr: 4.0000e-03 eta: 6:01:48 time: 0.3362 data_time: 0.0198 memory: 5826 grad_norm: 4.4342 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8684 loss: 1.8684 2022/10/08 08:51:35 - mmengine - INFO - Epoch(train) [121][1180/2119] lr: 4.0000e-03 eta: 6:01:41 time: 0.3570 data_time: 0.0258 memory: 5826 grad_norm: 4.4682 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0982 loss: 2.0982 2022/10/08 08:51:42 - mmengine - INFO - Epoch(train) [121][1200/2119] lr: 4.0000e-03 eta: 6:01:34 time: 0.3410 data_time: 0.0256 memory: 5826 grad_norm: 4.4813 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.7460 loss: 1.7460 2022/10/08 08:51:49 - mmengine - INFO - Epoch(train) [121][1220/2119] lr: 4.0000e-03 eta: 6:01:27 time: 0.3646 data_time: 0.0213 memory: 5826 grad_norm: 4.4422 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1811 loss: 2.1811 2022/10/08 08:51:56 - mmengine - INFO - Epoch(train) [121][1240/2119] lr: 4.0000e-03 eta: 6:01:20 time: 0.3400 data_time: 0.0159 memory: 5826 grad_norm: 4.4813 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0584 loss: 2.0584 2022/10/08 08:52:04 - mmengine - INFO - Epoch(train) [121][1260/2119] lr: 4.0000e-03 eta: 6:01:13 time: 0.3810 data_time: 0.0231 memory: 5826 grad_norm: 4.3992 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9368 loss: 1.9368 2022/10/08 08:52:10 - mmengine - INFO - Epoch(train) [121][1280/2119] lr: 4.0000e-03 eta: 6:01:06 time: 0.3302 data_time: 0.0196 memory: 5826 grad_norm: 4.4985 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9208 loss: 1.9208 2022/10/08 08:52:17 - mmengine - INFO - Epoch(train) [121][1300/2119] lr: 4.0000e-03 eta: 6:00:59 time: 0.3527 data_time: 0.0200 memory: 5826 grad_norm: 4.5038 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.0446 loss: 2.0446 2022/10/08 08:52:24 - mmengine - INFO - Epoch(train) [121][1320/2119] lr: 4.0000e-03 eta: 6:00:52 time: 0.3162 data_time: 0.0214 memory: 5826 grad_norm: 4.4222 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9621 loss: 1.9621 2022/10/08 08:52:31 - mmengine - INFO - Epoch(train) [121][1340/2119] lr: 4.0000e-03 eta: 6:00:45 time: 0.3757 data_time: 0.0247 memory: 5826 grad_norm: 4.5377 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.1530 loss: 2.1530 2022/10/08 08:52:39 - mmengine - INFO - Epoch(train) [121][1360/2119] lr: 4.0000e-03 eta: 6:00:38 time: 0.3755 data_time: 0.0221 memory: 5826 grad_norm: 4.4893 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9611 loss: 1.9611 2022/10/08 08:52:47 - mmengine - INFO - Epoch(train) [121][1380/2119] lr: 4.0000e-03 eta: 6:00:32 time: 0.3855 data_time: 0.0229 memory: 5826 grad_norm: 4.5088 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.1296 loss: 2.1296 2022/10/08 08:52:53 - mmengine - INFO - Epoch(train) [121][1400/2119] lr: 4.0000e-03 eta: 6:00:25 time: 0.3350 data_time: 0.0226 memory: 5826 grad_norm: 4.5030 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0174 loss: 2.0174 2022/10/08 08:53:01 - mmengine - INFO - Epoch(train) [121][1420/2119] lr: 4.0000e-03 eta: 6:00:18 time: 0.3795 data_time: 0.0174 memory: 5826 grad_norm: 4.3983 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9127 loss: 1.9127 2022/10/08 08:53:07 - mmengine - INFO - Epoch(train) [121][1440/2119] lr: 4.0000e-03 eta: 6:00:11 time: 0.3079 data_time: 0.0262 memory: 5826 grad_norm: 4.4383 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9698 loss: 1.9698 2022/10/08 08:53:15 - mmengine - INFO - Epoch(train) [121][1460/2119] lr: 4.0000e-03 eta: 6:00:04 time: 0.4196 data_time: 0.0198 memory: 5826 grad_norm: 4.3844 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0604 loss: 2.0604 2022/10/08 08:53:22 - mmengine - INFO - Epoch(train) [121][1480/2119] lr: 4.0000e-03 eta: 5:59:57 time: 0.3274 data_time: 0.0206 memory: 5826 grad_norm: 4.4372 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7648 loss: 1.7648 2022/10/08 08:53:30 - mmengine - INFO - Epoch(train) [121][1500/2119] lr: 4.0000e-03 eta: 5:59:50 time: 0.3758 data_time: 0.0264 memory: 5826 grad_norm: 4.5167 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0562 loss: 2.0562 2022/10/08 08:53:37 - mmengine - INFO - Epoch(train) [121][1520/2119] lr: 4.0000e-03 eta: 5:59:43 time: 0.3648 data_time: 0.0266 memory: 5826 grad_norm: 4.4390 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8512 loss: 1.8512 2022/10/08 08:53:44 - mmengine - INFO - Epoch(train) [121][1540/2119] lr: 4.0000e-03 eta: 5:59:36 time: 0.3657 data_time: 0.0230 memory: 5826 grad_norm: 4.3784 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9647 loss: 1.9647 2022/10/08 08:53:50 - mmengine - INFO - Epoch(train) [121][1560/2119] lr: 4.0000e-03 eta: 5:59:29 time: 0.3100 data_time: 0.0217 memory: 5826 grad_norm: 4.4173 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0365 loss: 2.0365 2022/10/08 08:53:58 - mmengine - INFO - Epoch(train) [121][1580/2119] lr: 4.0000e-03 eta: 5:59:23 time: 0.3834 data_time: 0.0253 memory: 5826 grad_norm: 4.4207 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.0916 loss: 2.0916 2022/10/08 08:54:04 - mmengine - INFO - Epoch(train) [121][1600/2119] lr: 4.0000e-03 eta: 5:59:15 time: 0.3159 data_time: 0.0205 memory: 5826 grad_norm: 4.4155 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0300 loss: 2.0300 2022/10/08 08:54:11 - mmengine - INFO - Epoch(train) [121][1620/2119] lr: 4.0000e-03 eta: 5:59:08 time: 0.3437 data_time: 0.0222 memory: 5826 grad_norm: 4.4258 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8090 loss: 1.8090 2022/10/08 08:54:18 - mmengine - INFO - Epoch(train) [121][1640/2119] lr: 4.0000e-03 eta: 5:59:01 time: 0.3477 data_time: 0.0189 memory: 5826 grad_norm: 4.4010 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.7284 loss: 1.7284 2022/10/08 08:54:25 - mmengine - INFO - Epoch(train) [121][1660/2119] lr: 4.0000e-03 eta: 5:58:55 time: 0.3559 data_time: 0.0242 memory: 5826 grad_norm: 4.4414 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0463 loss: 2.0463 2022/10/08 08:54:32 - mmengine - INFO - Epoch(train) [121][1680/2119] lr: 4.0000e-03 eta: 5:58:48 time: 0.3457 data_time: 0.0207 memory: 5826 grad_norm: 4.4192 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.9362 loss: 1.9362 2022/10/08 08:54:39 - mmengine - INFO - Epoch(train) [121][1700/2119] lr: 4.0000e-03 eta: 5:58:41 time: 0.3512 data_time: 0.0227 memory: 5826 grad_norm: 4.4901 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0616 loss: 2.0616 2022/10/08 08:54:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 08:54:46 - mmengine - INFO - Epoch(train) [121][1720/2119] lr: 4.0000e-03 eta: 5:58:34 time: 0.3484 data_time: 0.0212 memory: 5826 grad_norm: 4.4086 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9792 loss: 1.9792 2022/10/08 08:54:53 - mmengine - INFO - Epoch(train) [121][1740/2119] lr: 4.0000e-03 eta: 5:58:27 time: 0.3274 data_time: 0.0227 memory: 5826 grad_norm: 4.3925 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9323 loss: 1.9323 2022/10/08 08:55:00 - mmengine - INFO - Epoch(train) [121][1760/2119] lr: 4.0000e-03 eta: 5:58:20 time: 0.3614 data_time: 0.0277 memory: 5826 grad_norm: 4.4193 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0212 loss: 2.0212 2022/10/08 08:55:07 - mmengine - INFO - Epoch(train) [121][1780/2119] lr: 4.0000e-03 eta: 5:58:13 time: 0.3405 data_time: 0.0221 memory: 5826 grad_norm: 4.5380 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9578 loss: 1.9578 2022/10/08 08:55:13 - mmengine - INFO - Epoch(train) [121][1800/2119] lr: 4.0000e-03 eta: 5:58:06 time: 0.3296 data_time: 0.0247 memory: 5826 grad_norm: 4.4503 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8373 loss: 1.8373 2022/10/08 08:55:21 - mmengine - INFO - Epoch(train) [121][1820/2119] lr: 4.0000e-03 eta: 5:57:59 time: 0.3785 data_time: 0.0229 memory: 5826 grad_norm: 4.4556 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0961 loss: 2.0961 2022/10/08 08:55:27 - mmengine - INFO - Epoch(train) [121][1840/2119] lr: 4.0000e-03 eta: 5:57:52 time: 0.2873 data_time: 0.0213 memory: 5826 grad_norm: 4.5302 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0188 loss: 2.0188 2022/10/08 08:55:35 - mmengine - INFO - Epoch(train) [121][1860/2119] lr: 4.0000e-03 eta: 5:57:45 time: 0.3878 data_time: 0.0237 memory: 5826 grad_norm: 4.6029 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0480 loss: 2.0480 2022/10/08 08:55:42 - mmengine - INFO - Epoch(train) [121][1880/2119] lr: 4.0000e-03 eta: 5:57:38 time: 0.3726 data_time: 0.0175 memory: 5826 grad_norm: 4.4778 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8296 loss: 1.8296 2022/10/08 08:55:49 - mmengine - INFO - Epoch(train) [121][1900/2119] lr: 4.0000e-03 eta: 5:57:31 time: 0.3733 data_time: 0.0226 memory: 5826 grad_norm: 4.5260 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.1897 loss: 2.1897 2022/10/08 08:55:56 - mmengine - INFO - Epoch(train) [121][1920/2119] lr: 4.0000e-03 eta: 5:57:24 time: 0.3194 data_time: 0.0226 memory: 5826 grad_norm: 4.5629 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0896 loss: 2.0896 2022/10/08 08:56:03 - mmengine - INFO - Epoch(train) [121][1940/2119] lr: 4.0000e-03 eta: 5:57:17 time: 0.3666 data_time: 0.0280 memory: 5826 grad_norm: 4.3634 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8552 loss: 1.8552 2022/10/08 08:56:10 - mmengine - INFO - Epoch(train) [121][1960/2119] lr: 4.0000e-03 eta: 5:57:10 time: 0.3310 data_time: 0.0206 memory: 5826 grad_norm: 4.4812 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8844 loss: 1.8844 2022/10/08 08:56:17 - mmengine - INFO - Epoch(train) [121][1980/2119] lr: 4.0000e-03 eta: 5:57:03 time: 0.3562 data_time: 0.0185 memory: 5826 grad_norm: 4.4520 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7716 loss: 1.7716 2022/10/08 08:56:24 - mmengine - INFO - Epoch(train) [121][2000/2119] lr: 4.0000e-03 eta: 5:56:56 time: 0.3466 data_time: 0.0248 memory: 5826 grad_norm: 4.5210 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9759 loss: 1.9759 2022/10/08 08:56:31 - mmengine - INFO - Epoch(train) [121][2020/2119] lr: 4.0000e-03 eta: 5:56:49 time: 0.3585 data_time: 0.0242 memory: 5826 grad_norm: 4.3930 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.8890 loss: 1.8890 2022/10/08 08:56:38 - mmengine - INFO - Epoch(train) [121][2040/2119] lr: 4.0000e-03 eta: 5:56:43 time: 0.3561 data_time: 0.0232 memory: 5826 grad_norm: 4.5314 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9411 loss: 1.9411 2022/10/08 08:56:46 - mmengine - INFO - Epoch(train) [121][2060/2119] lr: 4.0000e-03 eta: 5:56:36 time: 0.3795 data_time: 0.0217 memory: 5826 grad_norm: 4.5822 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.8737 loss: 1.8737 2022/10/08 08:56:53 - mmengine - INFO - Epoch(train) [121][2080/2119] lr: 4.0000e-03 eta: 5:56:29 time: 0.3364 data_time: 0.0207 memory: 5826 grad_norm: 4.5253 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9130 loss: 1.9130 2022/10/08 08:57:01 - mmengine - INFO - Epoch(train) [121][2100/2119] lr: 4.0000e-03 eta: 5:56:22 time: 0.4017 data_time: 0.0186 memory: 5826 grad_norm: 4.5036 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9693 loss: 1.9693 2022/10/08 08:57:06 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 08:57:06 - mmengine - INFO - Epoch(train) [121][2119/2119] lr: 4.0000e-03 eta: 5:56:22 time: 0.2676 data_time: 0.0173 memory: 5826 grad_norm: 4.5877 top1_acc: 0.6000 top5_acc: 0.6000 loss_cls: 2.1324 loss: 2.1324 2022/10/08 08:57:15 - mmengine - INFO - Epoch(train) [122][20/2119] lr: 4.0000e-03 eta: 5:56:07 time: 0.4709 data_time: 0.1698 memory: 5826 grad_norm: 4.4843 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8946 loss: 1.8946 2022/10/08 08:57:22 - mmengine - INFO - Epoch(train) [122][40/2119] lr: 4.0000e-03 eta: 5:56:00 time: 0.3476 data_time: 0.0176 memory: 5826 grad_norm: 4.5096 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.1376 loss: 2.1376 2022/10/08 08:57:30 - mmengine - INFO - Epoch(train) [122][60/2119] lr: 4.0000e-03 eta: 5:55:54 time: 0.3911 data_time: 0.0220 memory: 5826 grad_norm: 4.4471 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0671 loss: 2.0671 2022/10/08 08:57:38 - mmengine - INFO - Epoch(train) [122][80/2119] lr: 4.0000e-03 eta: 5:55:47 time: 0.3790 data_time: 0.0253 memory: 5826 grad_norm: 4.4962 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9818 loss: 1.9818 2022/10/08 08:57:45 - mmengine - INFO - Epoch(train) [122][100/2119] lr: 4.0000e-03 eta: 5:55:40 time: 0.3479 data_time: 0.0191 memory: 5826 grad_norm: 4.5004 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.8703 loss: 1.8703 2022/10/08 08:57:51 - mmengine - INFO - Epoch(train) [122][120/2119] lr: 4.0000e-03 eta: 5:55:33 time: 0.3460 data_time: 0.0242 memory: 5826 grad_norm: 4.5224 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8835 loss: 1.8835 2022/10/08 08:58:00 - mmengine - INFO - Epoch(train) [122][140/2119] lr: 4.0000e-03 eta: 5:55:26 time: 0.4266 data_time: 0.0200 memory: 5826 grad_norm: 4.4535 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8359 loss: 1.8359 2022/10/08 08:58:07 - mmengine - INFO - Epoch(train) [122][160/2119] lr: 4.0000e-03 eta: 5:55:19 time: 0.3345 data_time: 0.0261 memory: 5826 grad_norm: 4.4381 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6736 loss: 1.6736 2022/10/08 08:58:15 - mmengine - INFO - Epoch(train) [122][180/2119] lr: 4.0000e-03 eta: 5:55:13 time: 0.4159 data_time: 0.0233 memory: 5826 grad_norm: 4.5333 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8311 loss: 1.8311 2022/10/08 08:58:21 - mmengine - INFO - Epoch(train) [122][200/2119] lr: 4.0000e-03 eta: 5:55:06 time: 0.3065 data_time: 0.0243 memory: 5826 grad_norm: 4.4092 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1231 loss: 2.1231 2022/10/08 08:58:28 - mmengine - INFO - Epoch(train) [122][220/2119] lr: 4.0000e-03 eta: 5:54:59 time: 0.3499 data_time: 0.0210 memory: 5826 grad_norm: 4.5212 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.1109 loss: 2.1109 2022/10/08 08:58:35 - mmengine - INFO - Epoch(train) [122][240/2119] lr: 4.0000e-03 eta: 5:54:52 time: 0.3508 data_time: 0.0261 memory: 5826 grad_norm: 4.5094 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0563 loss: 2.0563 2022/10/08 08:58:43 - mmengine - INFO - Epoch(train) [122][260/2119] lr: 4.0000e-03 eta: 5:54:45 time: 0.3840 data_time: 0.0185 memory: 5826 grad_norm: 4.5156 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0564 loss: 2.0564 2022/10/08 08:58:49 - mmengine - INFO - Epoch(train) [122][280/2119] lr: 4.0000e-03 eta: 5:54:38 time: 0.3280 data_time: 0.0275 memory: 5826 grad_norm: 4.4310 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9846 loss: 1.9846 2022/10/08 08:58:58 - mmengine - INFO - Epoch(train) [122][300/2119] lr: 4.0000e-03 eta: 5:54:31 time: 0.4177 data_time: 0.0235 memory: 5826 grad_norm: 4.4449 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.1563 loss: 2.1563 2022/10/08 08:59:04 - mmengine - INFO - Epoch(train) [122][320/2119] lr: 4.0000e-03 eta: 5:54:24 time: 0.3186 data_time: 0.0241 memory: 5826 grad_norm: 4.4075 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9574 loss: 1.9574 2022/10/08 08:59:11 - mmengine - INFO - Epoch(train) [122][340/2119] lr: 4.0000e-03 eta: 5:54:17 time: 0.3590 data_time: 0.0213 memory: 5826 grad_norm: 4.5718 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0902 loss: 2.0902 2022/10/08 08:59:18 - mmengine - INFO - Epoch(train) [122][360/2119] lr: 4.0000e-03 eta: 5:54:10 time: 0.3230 data_time: 0.0229 memory: 5826 grad_norm: 4.4545 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.0699 loss: 2.0699 2022/10/08 08:59:25 - mmengine - INFO - Epoch(train) [122][380/2119] lr: 4.0000e-03 eta: 5:54:03 time: 0.3468 data_time: 0.0228 memory: 5826 grad_norm: 4.4450 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 1.7837 loss: 1.7837 2022/10/08 08:59:31 - mmengine - INFO - Epoch(train) [122][400/2119] lr: 4.0000e-03 eta: 5:53:56 time: 0.3278 data_time: 0.0263 memory: 5826 grad_norm: 4.4423 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9080 loss: 1.9080 2022/10/08 08:59:39 - mmengine - INFO - Epoch(train) [122][420/2119] lr: 4.0000e-03 eta: 5:53:49 time: 0.3805 data_time: 0.0229 memory: 5826 grad_norm: 4.4991 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9842 loss: 1.9842 2022/10/08 08:59:46 - mmengine - INFO - Epoch(train) [122][440/2119] lr: 4.0000e-03 eta: 5:53:42 time: 0.3292 data_time: 0.0225 memory: 5826 grad_norm: 4.5088 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1171 loss: 2.1171 2022/10/08 08:59:53 - mmengine - INFO - Epoch(train) [122][460/2119] lr: 4.0000e-03 eta: 5:53:36 time: 0.3930 data_time: 0.0204 memory: 5826 grad_norm: 4.4962 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8014 loss: 1.8014 2022/10/08 09:00:00 - mmengine - INFO - Epoch(train) [122][480/2119] lr: 4.0000e-03 eta: 5:53:29 time: 0.3278 data_time: 0.0256 memory: 5826 grad_norm: 4.5441 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.0003 loss: 2.0003 2022/10/08 09:00:07 - mmengine - INFO - Epoch(train) [122][500/2119] lr: 4.0000e-03 eta: 5:53:22 time: 0.3590 data_time: 0.0165 memory: 5826 grad_norm: 4.5098 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0332 loss: 2.0332 2022/10/08 09:00:13 - mmengine - INFO - Epoch(train) [122][520/2119] lr: 4.0000e-03 eta: 5:53:14 time: 0.3043 data_time: 0.0247 memory: 5826 grad_norm: 4.4869 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0533 loss: 2.0533 2022/10/08 09:00:21 - mmengine - INFO - Epoch(train) [122][540/2119] lr: 4.0000e-03 eta: 5:53:08 time: 0.3922 data_time: 0.0205 memory: 5826 grad_norm: 4.4645 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9866 loss: 1.9866 2022/10/08 09:00:28 - mmengine - INFO - Epoch(train) [122][560/2119] lr: 4.0000e-03 eta: 5:53:01 time: 0.3467 data_time: 0.0227 memory: 5826 grad_norm: 4.5193 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1423 loss: 2.1423 2022/10/08 09:00:36 - mmengine - INFO - Epoch(train) [122][580/2119] lr: 4.0000e-03 eta: 5:52:54 time: 0.4155 data_time: 0.0248 memory: 5826 grad_norm: 4.5782 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1099 loss: 2.1099 2022/10/08 09:00:43 - mmengine - INFO - Epoch(train) [122][600/2119] lr: 4.0000e-03 eta: 5:52:47 time: 0.3321 data_time: 0.0216 memory: 5826 grad_norm: 4.4683 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1368 loss: 2.1368 2022/10/08 09:00:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 09:00:51 - mmengine - INFO - Epoch(train) [122][620/2119] lr: 4.0000e-03 eta: 5:52:40 time: 0.3751 data_time: 0.0191 memory: 5826 grad_norm: 4.4151 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9310 loss: 1.9310 2022/10/08 09:00:58 - mmengine - INFO - Epoch(train) [122][640/2119] lr: 4.0000e-03 eta: 5:52:33 time: 0.3536 data_time: 0.0264 memory: 5826 grad_norm: 4.6228 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8777 loss: 1.8777 2022/10/08 09:01:04 - mmengine - INFO - Epoch(train) [122][660/2119] lr: 4.0000e-03 eta: 5:52:26 time: 0.3405 data_time: 0.0195 memory: 5826 grad_norm: 4.4806 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.9882 loss: 1.9882 2022/10/08 09:01:12 - mmengine - INFO - Epoch(train) [122][680/2119] lr: 4.0000e-03 eta: 5:52:19 time: 0.3596 data_time: 0.0171 memory: 5826 grad_norm: 4.5206 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0860 loss: 2.0860 2022/10/08 09:01:19 - mmengine - INFO - Epoch(train) [122][700/2119] lr: 4.0000e-03 eta: 5:52:13 time: 0.3862 data_time: 0.0190 memory: 5826 grad_norm: 4.5048 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9645 loss: 1.9645 2022/10/08 09:01:27 - mmengine - INFO - Epoch(train) [122][720/2119] lr: 4.0000e-03 eta: 5:52:06 time: 0.3582 data_time: 0.0218 memory: 5826 grad_norm: 4.4707 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0440 loss: 2.0440 2022/10/08 09:01:34 - mmengine - INFO - Epoch(train) [122][740/2119] lr: 4.0000e-03 eta: 5:51:59 time: 0.3729 data_time: 0.0223 memory: 5826 grad_norm: 4.4639 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8533 loss: 1.8533 2022/10/08 09:01:40 - mmengine - INFO - Epoch(train) [122][760/2119] lr: 4.0000e-03 eta: 5:51:52 time: 0.3174 data_time: 0.0194 memory: 5826 grad_norm: 4.4905 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0032 loss: 2.0032 2022/10/08 09:01:48 - mmengine - INFO - Epoch(train) [122][780/2119] lr: 4.0000e-03 eta: 5:51:45 time: 0.3734 data_time: 0.0264 memory: 5826 grad_norm: 4.4953 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.1438 loss: 2.1438 2022/10/08 09:01:55 - mmengine - INFO - Epoch(train) [122][800/2119] lr: 4.0000e-03 eta: 5:51:38 time: 0.3373 data_time: 0.0264 memory: 5826 grad_norm: 4.3849 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.0312 loss: 2.0312 2022/10/08 09:02:03 - mmengine - INFO - Epoch(train) [122][820/2119] lr: 4.0000e-03 eta: 5:51:31 time: 0.3967 data_time: 0.0212 memory: 5826 grad_norm: 4.5574 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0324 loss: 2.0324 2022/10/08 09:02:09 - mmengine - INFO - Epoch(train) [122][840/2119] lr: 4.0000e-03 eta: 5:51:24 time: 0.3010 data_time: 0.0225 memory: 5826 grad_norm: 4.5465 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9813 loss: 1.9813 2022/10/08 09:02:17 - mmengine - INFO - Epoch(train) [122][860/2119] lr: 4.0000e-03 eta: 5:51:17 time: 0.4207 data_time: 0.0235 memory: 5826 grad_norm: 4.4689 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.0089 loss: 2.0089 2022/10/08 09:02:23 - mmengine - INFO - Epoch(train) [122][880/2119] lr: 4.0000e-03 eta: 5:51:10 time: 0.3168 data_time: 0.0203 memory: 5826 grad_norm: 4.5601 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9772 loss: 1.9772 2022/10/08 09:02:30 - mmengine - INFO - Epoch(train) [122][900/2119] lr: 4.0000e-03 eta: 5:51:03 time: 0.3542 data_time: 0.0185 memory: 5826 grad_norm: 4.5709 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9841 loss: 1.9841 2022/10/08 09:02:38 - mmengine - INFO - Epoch(train) [122][920/2119] lr: 4.0000e-03 eta: 5:50:57 time: 0.3638 data_time: 0.0245 memory: 5826 grad_norm: 4.5290 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9942 loss: 1.9942 2022/10/08 09:02:45 - mmengine - INFO - Epoch(train) [122][940/2119] lr: 4.0000e-03 eta: 5:50:50 time: 0.3744 data_time: 0.0196 memory: 5826 grad_norm: 4.5292 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9157 loss: 1.9157 2022/10/08 09:02:51 - mmengine - INFO - Epoch(train) [122][960/2119] lr: 4.0000e-03 eta: 5:50:43 time: 0.3082 data_time: 0.0306 memory: 5826 grad_norm: 4.4321 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8510 loss: 1.8510 2022/10/08 09:02:58 - mmengine - INFO - Epoch(train) [122][980/2119] lr: 4.0000e-03 eta: 5:50:36 time: 0.3468 data_time: 0.0280 memory: 5826 grad_norm: 4.5336 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9642 loss: 1.9642 2022/10/08 09:03:05 - mmengine - INFO - Epoch(train) [122][1000/2119] lr: 4.0000e-03 eta: 5:50:29 time: 0.3506 data_time: 0.0226 memory: 5826 grad_norm: 4.7384 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7465 loss: 1.7465 2022/10/08 09:03:13 - mmengine - INFO - Epoch(train) [122][1020/2119] lr: 4.0000e-03 eta: 5:50:22 time: 0.4029 data_time: 0.0230 memory: 5826 grad_norm: 4.5162 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9757 loss: 1.9757 2022/10/08 09:03:21 - mmengine - INFO - Epoch(train) [122][1040/2119] lr: 4.0000e-03 eta: 5:50:15 time: 0.3631 data_time: 0.0195 memory: 5826 grad_norm: 4.5699 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1899 loss: 2.1899 2022/10/08 09:03:28 - mmengine - INFO - Epoch(train) [122][1060/2119] lr: 4.0000e-03 eta: 5:50:08 time: 0.3644 data_time: 0.0253 memory: 5826 grad_norm: 4.5257 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.1216 loss: 2.1216 2022/10/08 09:03:35 - mmengine - INFO - Epoch(train) [122][1080/2119] lr: 4.0000e-03 eta: 5:50:01 time: 0.3484 data_time: 0.0191 memory: 5826 grad_norm: 4.4941 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.8114 loss: 1.8114 2022/10/08 09:03:42 - mmengine - INFO - Epoch(train) [122][1100/2119] lr: 4.0000e-03 eta: 5:49:54 time: 0.3598 data_time: 0.0218 memory: 5826 grad_norm: 4.5348 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0667 loss: 2.0667 2022/10/08 09:03:49 - mmengine - INFO - Epoch(train) [122][1120/2119] lr: 4.0000e-03 eta: 5:49:47 time: 0.3350 data_time: 0.0243 memory: 5826 grad_norm: 4.4972 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0635 loss: 2.0635 2022/10/08 09:03:56 - mmengine - INFO - Epoch(train) [122][1140/2119] lr: 4.0000e-03 eta: 5:49:40 time: 0.3449 data_time: 0.0175 memory: 5826 grad_norm: 4.4993 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0290 loss: 2.0290 2022/10/08 09:04:02 - mmengine - INFO - Epoch(train) [122][1160/2119] lr: 4.0000e-03 eta: 5:49:33 time: 0.3257 data_time: 0.0255 memory: 5826 grad_norm: 4.4754 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.8935 loss: 1.8935 2022/10/08 09:04:09 - mmengine - INFO - Epoch(train) [122][1180/2119] lr: 4.0000e-03 eta: 5:49:26 time: 0.3542 data_time: 0.0231 memory: 5826 grad_norm: 4.4610 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9614 loss: 1.9614 2022/10/08 09:04:16 - mmengine - INFO - Epoch(train) [122][1200/2119] lr: 4.0000e-03 eta: 5:49:19 time: 0.3397 data_time: 0.0231 memory: 5826 grad_norm: 4.5673 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.2292 loss: 2.2292 2022/10/08 09:04:24 - mmengine - INFO - Epoch(train) [122][1220/2119] lr: 4.0000e-03 eta: 5:49:13 time: 0.4017 data_time: 0.0223 memory: 5826 grad_norm: 4.5377 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.1294 loss: 2.1294 2022/10/08 09:04:30 - mmengine - INFO - Epoch(train) [122][1240/2119] lr: 4.0000e-03 eta: 5:49:05 time: 0.2944 data_time: 0.0210 memory: 5826 grad_norm: 4.4962 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9184 loss: 1.9184 2022/10/08 09:04:38 - mmengine - INFO - Epoch(train) [122][1260/2119] lr: 4.0000e-03 eta: 5:48:59 time: 0.4076 data_time: 0.0249 memory: 5826 grad_norm: 4.5772 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9707 loss: 1.9707 2022/10/08 09:04:44 - mmengine - INFO - Epoch(train) [122][1280/2119] lr: 4.0000e-03 eta: 5:48:52 time: 0.2950 data_time: 0.0258 memory: 5826 grad_norm: 4.6548 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0727 loss: 2.0727 2022/10/08 09:04:53 - mmengine - INFO - Epoch(train) [122][1300/2119] lr: 4.0000e-03 eta: 5:48:45 time: 0.4177 data_time: 0.0230 memory: 5826 grad_norm: 4.5671 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0402 loss: 2.0402 2022/10/08 09:05:00 - mmengine - INFO - Epoch(train) [122][1320/2119] lr: 4.0000e-03 eta: 5:48:38 time: 0.3905 data_time: 0.0227 memory: 5826 grad_norm: 4.5521 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.0646 loss: 2.0646 2022/10/08 09:05:08 - mmengine - INFO - Epoch(train) [122][1340/2119] lr: 4.0000e-03 eta: 5:48:31 time: 0.3648 data_time: 0.0189 memory: 5826 grad_norm: 4.4877 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0710 loss: 2.0710 2022/10/08 09:05:14 - mmengine - INFO - Epoch(train) [122][1360/2119] lr: 4.0000e-03 eta: 5:48:24 time: 0.3203 data_time: 0.0214 memory: 5826 grad_norm: 4.4767 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9156 loss: 1.9156 2022/10/08 09:05:21 - mmengine - INFO - Epoch(train) [122][1380/2119] lr: 4.0000e-03 eta: 5:48:17 time: 0.3661 data_time: 0.0253 memory: 5826 grad_norm: 4.4959 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0008 loss: 2.0008 2022/10/08 09:05:28 - mmengine - INFO - Epoch(train) [122][1400/2119] lr: 4.0000e-03 eta: 5:48:10 time: 0.3196 data_time: 0.0243 memory: 5826 grad_norm: 4.5090 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8456 loss: 1.8456 2022/10/08 09:05:35 - mmengine - INFO - Epoch(train) [122][1420/2119] lr: 4.0000e-03 eta: 5:48:03 time: 0.3569 data_time: 0.0236 memory: 5826 grad_norm: 4.3933 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9460 loss: 1.9460 2022/10/08 09:05:41 - mmengine - INFO - Epoch(train) [122][1440/2119] lr: 4.0000e-03 eta: 5:47:56 time: 0.3202 data_time: 0.0214 memory: 5826 grad_norm: 4.4969 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9136 loss: 1.9136 2022/10/08 09:05:49 - mmengine - INFO - Epoch(train) [122][1460/2119] lr: 4.0000e-03 eta: 5:47:50 time: 0.4005 data_time: 0.0243 memory: 5826 grad_norm: 4.5666 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8555 loss: 1.8555 2022/10/08 09:05:56 - mmengine - INFO - Epoch(train) [122][1480/2119] lr: 4.0000e-03 eta: 5:47:42 time: 0.3082 data_time: 0.0248 memory: 5826 grad_norm: 4.5230 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9174 loss: 1.9174 2022/10/08 09:06:03 - mmengine - INFO - Epoch(train) [122][1500/2119] lr: 4.0000e-03 eta: 5:47:36 time: 0.3830 data_time: 0.0246 memory: 5826 grad_norm: 4.5586 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9988 loss: 1.9988 2022/10/08 09:06:09 - mmengine - INFO - Epoch(train) [122][1520/2119] lr: 4.0000e-03 eta: 5:47:28 time: 0.2998 data_time: 0.0231 memory: 5826 grad_norm: 4.5530 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0446 loss: 2.0446 2022/10/08 09:06:17 - mmengine - INFO - Epoch(train) [122][1540/2119] lr: 4.0000e-03 eta: 5:47:22 time: 0.3714 data_time: 0.0191 memory: 5826 grad_norm: 4.5698 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1799 loss: 2.1799 2022/10/08 09:06:22 - mmengine - INFO - Epoch(train) [122][1560/2119] lr: 4.0000e-03 eta: 5:47:14 time: 0.2833 data_time: 0.0258 memory: 5826 grad_norm: 4.5253 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0727 loss: 2.0727 2022/10/08 09:06:30 - mmengine - INFO - Epoch(train) [122][1580/2119] lr: 4.0000e-03 eta: 5:47:07 time: 0.3713 data_time: 0.0199 memory: 5826 grad_norm: 4.4810 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.1052 loss: 2.1052 2022/10/08 09:06:36 - mmengine - INFO - Epoch(train) [122][1600/2119] lr: 4.0000e-03 eta: 5:47:00 time: 0.3170 data_time: 0.0233 memory: 5826 grad_norm: 4.5427 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9889 loss: 1.9889 2022/10/08 09:06:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 09:06:44 - mmengine - INFO - Epoch(train) [122][1620/2119] lr: 4.0000e-03 eta: 5:46:54 time: 0.3989 data_time: 0.0237 memory: 5826 grad_norm: 4.5659 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9343 loss: 1.9343 2022/10/08 09:06:50 - mmengine - INFO - Epoch(train) [122][1640/2119] lr: 4.0000e-03 eta: 5:46:47 time: 0.3154 data_time: 0.0240 memory: 5826 grad_norm: 4.4477 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.0211 loss: 2.0211 2022/10/08 09:06:59 - mmengine - INFO - Epoch(train) [122][1660/2119] lr: 4.0000e-03 eta: 5:46:40 time: 0.4075 data_time: 0.0242 memory: 5826 grad_norm: 4.5024 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9911 loss: 1.9911 2022/10/08 09:07:05 - mmengine - INFO - Epoch(train) [122][1680/2119] lr: 4.0000e-03 eta: 5:46:33 time: 0.3127 data_time: 0.0207 memory: 5826 grad_norm: 4.5011 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0177 loss: 2.0177 2022/10/08 09:07:13 - mmengine - INFO - Epoch(train) [122][1700/2119] lr: 4.0000e-03 eta: 5:46:26 time: 0.3826 data_time: 0.0228 memory: 5826 grad_norm: 4.5150 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0352 loss: 2.0352 2022/10/08 09:07:20 - mmengine - INFO - Epoch(train) [122][1720/2119] lr: 4.0000e-03 eta: 5:46:19 time: 0.3891 data_time: 0.0231 memory: 5826 grad_norm: 4.5430 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1971 loss: 2.1971 2022/10/08 09:07:28 - mmengine - INFO - Epoch(train) [122][1740/2119] lr: 4.0000e-03 eta: 5:46:12 time: 0.3699 data_time: 0.0288 memory: 5826 grad_norm: 4.4513 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0115 loss: 2.0115 2022/10/08 09:07:34 - mmengine - INFO - Epoch(train) [122][1760/2119] lr: 4.0000e-03 eta: 5:46:05 time: 0.3302 data_time: 0.0202 memory: 5826 grad_norm: 4.5073 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.9337 loss: 1.9337 2022/10/08 09:07:42 - mmengine - INFO - Epoch(train) [122][1780/2119] lr: 4.0000e-03 eta: 5:45:58 time: 0.3675 data_time: 0.0245 memory: 5826 grad_norm: 4.4799 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9673 loss: 1.9673 2022/10/08 09:07:48 - mmengine - INFO - Epoch(train) [122][1800/2119] lr: 4.0000e-03 eta: 5:45:51 time: 0.3314 data_time: 0.0216 memory: 5826 grad_norm: 4.4902 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 1.9078 loss: 1.9078 2022/10/08 09:07:56 - mmengine - INFO - Epoch(train) [122][1820/2119] lr: 4.0000e-03 eta: 5:45:45 time: 0.3846 data_time: 0.0205 memory: 5826 grad_norm: 4.5450 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0993 loss: 2.0993 2022/10/08 09:08:02 - mmengine - INFO - Epoch(train) [122][1840/2119] lr: 4.0000e-03 eta: 5:45:37 time: 0.3143 data_time: 0.0217 memory: 5826 grad_norm: 4.5112 top1_acc: 0.3125 top5_acc: 0.8750 loss_cls: 2.0566 loss: 2.0566 2022/10/08 09:08:10 - mmengine - INFO - Epoch(train) [122][1860/2119] lr: 4.0000e-03 eta: 5:45:31 time: 0.4059 data_time: 0.0307 memory: 5826 grad_norm: 4.4902 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0000 loss: 2.0000 2022/10/08 09:08:17 - mmengine - INFO - Epoch(train) [122][1880/2119] lr: 4.0000e-03 eta: 5:45:24 time: 0.3375 data_time: 0.0239 memory: 5826 grad_norm: 4.4607 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0907 loss: 2.0907 2022/10/08 09:08:24 - mmengine - INFO - Epoch(train) [122][1900/2119] lr: 4.0000e-03 eta: 5:45:17 time: 0.3379 data_time: 0.0234 memory: 5826 grad_norm: 4.5376 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.0371 loss: 2.0371 2022/10/08 09:08:31 - mmengine - INFO - Epoch(train) [122][1920/2119] lr: 4.0000e-03 eta: 5:45:10 time: 0.3335 data_time: 0.0229 memory: 5826 grad_norm: 4.5235 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9122 loss: 1.9122 2022/10/08 09:08:38 - mmengine - INFO - Epoch(train) [122][1940/2119] lr: 4.0000e-03 eta: 5:45:03 time: 0.3812 data_time: 0.0198 memory: 5826 grad_norm: 4.5351 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9548 loss: 1.9548 2022/10/08 09:08:45 - mmengine - INFO - Epoch(train) [122][1960/2119] lr: 4.0000e-03 eta: 5:44:56 time: 0.3385 data_time: 0.0339 memory: 5826 grad_norm: 4.5842 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9014 loss: 1.9014 2022/10/08 09:08:52 - mmengine - INFO - Epoch(train) [122][1980/2119] lr: 4.0000e-03 eta: 5:44:49 time: 0.3472 data_time: 0.0220 memory: 5826 grad_norm: 4.4399 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.1026 loss: 2.1026 2022/10/08 09:08:59 - mmengine - INFO - Epoch(train) [122][2000/2119] lr: 4.0000e-03 eta: 5:44:42 time: 0.3604 data_time: 0.0256 memory: 5826 grad_norm: 4.5661 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1951 loss: 2.1951 2022/10/08 09:09:06 - mmengine - INFO - Epoch(train) [122][2020/2119] lr: 4.0000e-03 eta: 5:44:35 time: 0.3354 data_time: 0.0212 memory: 5826 grad_norm: 4.5023 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.4276 loss: 2.4276 2022/10/08 09:09:13 - mmengine - INFO - Epoch(train) [122][2040/2119] lr: 4.0000e-03 eta: 5:44:28 time: 0.3436 data_time: 0.0205 memory: 5826 grad_norm: 4.6063 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.7959 loss: 1.7959 2022/10/08 09:09:21 - mmengine - INFO - Epoch(train) [122][2060/2119] lr: 4.0000e-03 eta: 5:44:21 time: 0.4116 data_time: 0.0191 memory: 5826 grad_norm: 4.5649 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8227 loss: 1.8227 2022/10/08 09:09:27 - mmengine - INFO - Epoch(train) [122][2080/2119] lr: 4.0000e-03 eta: 5:44:14 time: 0.3126 data_time: 0.0243 memory: 5826 grad_norm: 4.4938 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4067 loss: 2.4067 2022/10/08 09:09:36 - mmengine - INFO - Epoch(train) [122][2100/2119] lr: 4.0000e-03 eta: 5:44:08 time: 0.4161 data_time: 0.0206 memory: 5826 grad_norm: 4.5219 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8284 loss: 1.8284 2022/10/08 09:09:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 09:09:41 - mmengine - INFO - Epoch(train) [122][2119/2119] lr: 4.0000e-03 eta: 5:44:08 time: 0.2921 data_time: 0.0204 memory: 5826 grad_norm: 4.7146 top1_acc: 0.4000 top5_acc: 0.5000 loss_cls: 2.1751 loss: 2.1751 2022/10/08 09:09:51 - mmengine - INFO - Epoch(train) [123][20/2119] lr: 4.0000e-03 eta: 5:43:53 time: 0.4918 data_time: 0.1226 memory: 5826 grad_norm: 4.4459 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8042 loss: 1.8042 2022/10/08 09:09:58 - mmengine - INFO - Epoch(train) [123][40/2119] lr: 4.0000e-03 eta: 5:43:46 time: 0.3384 data_time: 0.0223 memory: 5826 grad_norm: 4.5585 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1154 loss: 2.1154 2022/10/08 09:10:05 - mmengine - INFO - Epoch(train) [123][60/2119] lr: 4.0000e-03 eta: 5:43:39 time: 0.3678 data_time: 0.0209 memory: 5826 grad_norm: 4.5720 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8102 loss: 1.8102 2022/10/08 09:10:12 - mmengine - INFO - Epoch(train) [123][80/2119] lr: 4.0000e-03 eta: 5:43:32 time: 0.3371 data_time: 0.0232 memory: 5826 grad_norm: 4.5380 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0104 loss: 2.0104 2022/10/08 09:10:20 - mmengine - INFO - Epoch(train) [123][100/2119] lr: 4.0000e-03 eta: 5:43:26 time: 0.3827 data_time: 0.0228 memory: 5826 grad_norm: 4.5479 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8865 loss: 1.8865 2022/10/08 09:10:27 - mmengine - INFO - Epoch(train) [123][120/2119] lr: 4.0000e-03 eta: 5:43:19 time: 0.3455 data_time: 0.0220 memory: 5826 grad_norm: 4.5731 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7396 loss: 1.7396 2022/10/08 09:10:34 - mmengine - INFO - Epoch(train) [123][140/2119] lr: 4.0000e-03 eta: 5:43:12 time: 0.3648 data_time: 0.0202 memory: 5826 grad_norm: 4.5130 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9145 loss: 1.9145 2022/10/08 09:10:41 - mmengine - INFO - Epoch(train) [123][160/2119] lr: 4.0000e-03 eta: 5:43:05 time: 0.3306 data_time: 0.0239 memory: 5826 grad_norm: 4.5548 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9721 loss: 1.9721 2022/10/08 09:10:48 - mmengine - INFO - Epoch(train) [123][180/2119] lr: 4.0000e-03 eta: 5:42:58 time: 0.3811 data_time: 0.0245 memory: 5826 grad_norm: 4.5893 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9903 loss: 1.9903 2022/10/08 09:10:54 - mmengine - INFO - Epoch(train) [123][200/2119] lr: 4.0000e-03 eta: 5:42:51 time: 0.2913 data_time: 0.0228 memory: 5826 grad_norm: 4.5597 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.0872 loss: 2.0872 2022/10/08 09:11:03 - mmengine - INFO - Epoch(train) [123][220/2119] lr: 4.0000e-03 eta: 5:42:44 time: 0.4411 data_time: 0.0164 memory: 5826 grad_norm: 4.4698 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9719 loss: 1.9719 2022/10/08 09:11:09 - mmengine - INFO - Epoch(train) [123][240/2119] lr: 4.0000e-03 eta: 5:42:37 time: 0.3093 data_time: 0.0227 memory: 5826 grad_norm: 4.5946 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.9778 loss: 1.9778 2022/10/08 09:11:16 - mmengine - INFO - Epoch(train) [123][260/2119] lr: 4.0000e-03 eta: 5:42:30 time: 0.3432 data_time: 0.0249 memory: 5826 grad_norm: 4.5702 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0226 loss: 2.0226 2022/10/08 09:11:23 - mmengine - INFO - Epoch(train) [123][280/2119] lr: 4.0000e-03 eta: 5:42:23 time: 0.3359 data_time: 0.0185 memory: 5826 grad_norm: 4.5163 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7483 loss: 1.7483 2022/10/08 09:11:30 - mmengine - INFO - Epoch(train) [123][300/2119] lr: 4.0000e-03 eta: 5:42:16 time: 0.3785 data_time: 0.0215 memory: 5826 grad_norm: 4.5294 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9012 loss: 1.9012 2022/10/08 09:11:36 - mmengine - INFO - Epoch(train) [123][320/2119] lr: 4.0000e-03 eta: 5:42:09 time: 0.3072 data_time: 0.0207 memory: 5826 grad_norm: 4.4963 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.8682 loss: 1.8682 2022/10/08 09:11:43 - mmengine - INFO - Epoch(train) [123][340/2119] lr: 4.0000e-03 eta: 5:42:02 time: 0.3382 data_time: 0.0204 memory: 5826 grad_norm: 4.5532 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9748 loss: 1.9748 2022/10/08 09:11:50 - mmengine - INFO - Epoch(train) [123][360/2119] lr: 4.0000e-03 eta: 5:41:55 time: 0.3589 data_time: 0.0274 memory: 5826 grad_norm: 4.5068 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9526 loss: 1.9526 2022/10/08 09:11:58 - mmengine - INFO - Epoch(train) [123][380/2119] lr: 4.0000e-03 eta: 5:41:48 time: 0.3668 data_time: 0.0233 memory: 5826 grad_norm: 4.5205 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2341 loss: 2.2341 2022/10/08 09:12:04 - mmengine - INFO - Epoch(train) [123][400/2119] lr: 4.0000e-03 eta: 5:41:41 time: 0.3392 data_time: 0.0220 memory: 5826 grad_norm: 4.5346 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0190 loss: 2.0190 2022/10/08 09:12:12 - mmengine - INFO - Epoch(train) [123][420/2119] lr: 4.0000e-03 eta: 5:41:34 time: 0.3593 data_time: 0.0215 memory: 5826 grad_norm: 4.5599 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1171 loss: 2.1171 2022/10/08 09:12:19 - mmengine - INFO - Epoch(train) [123][440/2119] lr: 4.0000e-03 eta: 5:41:27 time: 0.3383 data_time: 0.0262 memory: 5826 grad_norm: 4.5488 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7154 loss: 1.7154 2022/10/08 09:12:26 - mmengine - INFO - Epoch(train) [123][460/2119] lr: 4.0000e-03 eta: 5:41:21 time: 0.3792 data_time: 0.0283 memory: 5826 grad_norm: 4.5279 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0003 loss: 2.0003 2022/10/08 09:12:33 - mmengine - INFO - Epoch(train) [123][480/2119] lr: 4.0000e-03 eta: 5:41:13 time: 0.3225 data_time: 0.0245 memory: 5826 grad_norm: 4.5012 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9741 loss: 1.9741 2022/10/08 09:12:33 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 09:12:40 - mmengine - INFO - Epoch(train) [123][500/2119] lr: 4.0000e-03 eta: 5:41:07 time: 0.3798 data_time: 0.0210 memory: 5826 grad_norm: 4.5530 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.0642 loss: 2.0642 2022/10/08 09:12:46 - mmengine - INFO - Epoch(train) [123][520/2119] lr: 4.0000e-03 eta: 5:40:59 time: 0.3029 data_time: 0.0254 memory: 5826 grad_norm: 4.5494 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.2564 loss: 2.2564 2022/10/08 09:12:54 - mmengine - INFO - Epoch(train) [123][540/2119] lr: 4.0000e-03 eta: 5:40:53 time: 0.3908 data_time: 0.0226 memory: 5826 grad_norm: 4.5530 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8497 loss: 1.8497 2022/10/08 09:13:01 - mmengine - INFO - Epoch(train) [123][560/2119] lr: 4.0000e-03 eta: 5:40:46 time: 0.3593 data_time: 0.0205 memory: 5826 grad_norm: 4.5927 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1576 loss: 2.1576 2022/10/08 09:13:09 - mmengine - INFO - Epoch(train) [123][580/2119] lr: 4.0000e-03 eta: 5:40:39 time: 0.3742 data_time: 0.0192 memory: 5826 grad_norm: 5.1254 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9083 loss: 1.9083 2022/10/08 09:13:16 - mmengine - INFO - Epoch(train) [123][600/2119] lr: 4.0000e-03 eta: 5:40:32 time: 0.3460 data_time: 0.0167 memory: 5826 grad_norm: 4.5465 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0474 loss: 2.0474 2022/10/08 09:13:24 - mmengine - INFO - Epoch(train) [123][620/2119] lr: 4.0000e-03 eta: 5:40:25 time: 0.3966 data_time: 0.0195 memory: 5826 grad_norm: 4.4097 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8202 loss: 1.8202 2022/10/08 09:13:30 - mmengine - INFO - Epoch(train) [123][640/2119] lr: 4.0000e-03 eta: 5:40:18 time: 0.3158 data_time: 0.0227 memory: 5826 grad_norm: 4.5131 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1579 loss: 2.1579 2022/10/08 09:13:39 - mmengine - INFO - Epoch(train) [123][660/2119] lr: 4.0000e-03 eta: 5:40:12 time: 0.4401 data_time: 0.0205 memory: 5826 grad_norm: 4.6340 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.2273 loss: 2.2273 2022/10/08 09:13:44 - mmengine - INFO - Epoch(train) [123][680/2119] lr: 4.0000e-03 eta: 5:40:04 time: 0.2853 data_time: 0.0232 memory: 5826 grad_norm: 4.5602 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0532 loss: 2.0532 2022/10/08 09:13:52 - mmengine - INFO - Epoch(train) [123][700/2119] lr: 4.0000e-03 eta: 5:39:58 time: 0.3923 data_time: 0.0217 memory: 5826 grad_norm: 4.4309 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9505 loss: 1.9505 2022/10/08 09:13:59 - mmengine - INFO - Epoch(train) [123][720/2119] lr: 4.0000e-03 eta: 5:39:51 time: 0.3396 data_time: 0.0239 memory: 5826 grad_norm: 4.5798 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1703 loss: 2.1703 2022/10/08 09:14:06 - mmengine - INFO - Epoch(train) [123][740/2119] lr: 4.0000e-03 eta: 5:39:44 time: 0.3458 data_time: 0.0203 memory: 5826 grad_norm: 4.5063 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9286 loss: 1.9286 2022/10/08 09:14:13 - mmengine - INFO - Epoch(train) [123][760/2119] lr: 4.0000e-03 eta: 5:39:37 time: 0.3422 data_time: 0.0316 memory: 5826 grad_norm: 4.4388 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.6966 loss: 1.6966 2022/10/08 09:14:20 - mmengine - INFO - Epoch(train) [123][780/2119] lr: 4.0000e-03 eta: 5:39:30 time: 0.3760 data_time: 0.0216 memory: 5826 grad_norm: 4.5153 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0587 loss: 2.0587 2022/10/08 09:14:27 - mmengine - INFO - Epoch(train) [123][800/2119] lr: 4.0000e-03 eta: 5:39:23 time: 0.3481 data_time: 0.0268 memory: 5826 grad_norm: 4.4534 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1797 loss: 2.1797 2022/10/08 09:14:35 - mmengine - INFO - Epoch(train) [123][820/2119] lr: 4.0000e-03 eta: 5:39:16 time: 0.3670 data_time: 0.0221 memory: 5826 grad_norm: 4.5498 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0816 loss: 2.0816 2022/10/08 09:14:42 - mmengine - INFO - Epoch(train) [123][840/2119] lr: 4.0000e-03 eta: 5:39:09 time: 0.3597 data_time: 0.0360 memory: 5826 grad_norm: 4.5785 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.0793 loss: 2.0793 2022/10/08 09:14:50 - mmengine - INFO - Epoch(train) [123][860/2119] lr: 4.0000e-03 eta: 5:39:02 time: 0.4043 data_time: 0.0149 memory: 5826 grad_norm: 4.6172 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9680 loss: 1.9680 2022/10/08 09:14:57 - mmengine - INFO - Epoch(train) [123][880/2119] lr: 4.0000e-03 eta: 5:38:55 time: 0.3507 data_time: 0.0233 memory: 5826 grad_norm: 4.5540 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9521 loss: 1.9521 2022/10/08 09:15:04 - mmengine - INFO - Epoch(train) [123][900/2119] lr: 4.0000e-03 eta: 5:38:48 time: 0.3471 data_time: 0.0221 memory: 5826 grad_norm: 4.6506 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9672 loss: 1.9672 2022/10/08 09:15:11 - mmengine - INFO - Epoch(train) [123][920/2119] lr: 4.0000e-03 eta: 5:38:42 time: 0.3760 data_time: 0.0225 memory: 5826 grad_norm: 4.5715 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9223 loss: 1.9223 2022/10/08 09:15:19 - mmengine - INFO - Epoch(train) [123][940/2119] lr: 4.0000e-03 eta: 5:38:35 time: 0.3850 data_time: 0.0217 memory: 5826 grad_norm: 4.4874 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0554 loss: 2.0554 2022/10/08 09:15:27 - mmengine - INFO - Epoch(train) [123][960/2119] lr: 4.0000e-03 eta: 5:38:28 time: 0.3754 data_time: 0.0244 memory: 5826 grad_norm: 4.5733 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0113 loss: 2.0113 2022/10/08 09:15:34 - mmengine - INFO - Epoch(train) [123][980/2119] lr: 4.0000e-03 eta: 5:38:21 time: 0.3478 data_time: 0.0234 memory: 5826 grad_norm: 4.5303 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8964 loss: 1.8964 2022/10/08 09:15:41 - mmengine - INFO - Epoch(train) [123][1000/2119] lr: 4.0000e-03 eta: 5:38:14 time: 0.3770 data_time: 0.0244 memory: 5826 grad_norm: 4.4839 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.9243 loss: 1.9243 2022/10/08 09:15:49 - mmengine - INFO - Epoch(train) [123][1020/2119] lr: 4.0000e-03 eta: 5:38:07 time: 0.3627 data_time: 0.0190 memory: 5826 grad_norm: 4.5575 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9416 loss: 1.9416 2022/10/08 09:15:55 - mmengine - INFO - Epoch(train) [123][1040/2119] lr: 4.0000e-03 eta: 5:38:00 time: 0.3003 data_time: 0.0283 memory: 5826 grad_norm: 4.5725 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0397 loss: 2.0397 2022/10/08 09:16:03 - mmengine - INFO - Epoch(train) [123][1060/2119] lr: 4.0000e-03 eta: 5:37:54 time: 0.4204 data_time: 0.0170 memory: 5826 grad_norm: 4.5990 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9709 loss: 1.9709 2022/10/08 09:16:09 - mmengine - INFO - Epoch(train) [123][1080/2119] lr: 4.0000e-03 eta: 5:37:46 time: 0.3198 data_time: 0.0252 memory: 5826 grad_norm: 4.5733 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9689 loss: 1.9689 2022/10/08 09:16:16 - mmengine - INFO - Epoch(train) [123][1100/2119] lr: 4.0000e-03 eta: 5:37:40 time: 0.3560 data_time: 0.0280 memory: 5826 grad_norm: 4.6089 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.8734 loss: 1.8734 2022/10/08 09:16:23 - mmengine - INFO - Epoch(train) [123][1120/2119] lr: 4.0000e-03 eta: 5:37:32 time: 0.3148 data_time: 0.0209 memory: 5826 grad_norm: 4.6083 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9100 loss: 1.9100 2022/10/08 09:16:30 - mmengine - INFO - Epoch(train) [123][1140/2119] lr: 4.0000e-03 eta: 5:37:26 time: 0.3677 data_time: 0.0220 memory: 5826 grad_norm: 4.5978 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0157 loss: 2.0157 2022/10/08 09:16:37 - mmengine - INFO - Epoch(train) [123][1160/2119] lr: 4.0000e-03 eta: 5:37:19 time: 0.3309 data_time: 0.0202 memory: 5826 grad_norm: 4.5803 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1590 loss: 2.1590 2022/10/08 09:16:44 - mmengine - INFO - Epoch(train) [123][1180/2119] lr: 4.0000e-03 eta: 5:37:12 time: 0.3439 data_time: 0.0231 memory: 5826 grad_norm: 4.5667 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.8882 loss: 1.8882 2022/10/08 09:16:50 - mmengine - INFO - Epoch(train) [123][1200/2119] lr: 4.0000e-03 eta: 5:37:05 time: 0.3319 data_time: 0.0251 memory: 5826 grad_norm: 4.5700 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.9986 loss: 1.9986 2022/10/08 09:16:58 - mmengine - INFO - Epoch(train) [123][1220/2119] lr: 4.0000e-03 eta: 5:36:58 time: 0.3911 data_time: 0.0232 memory: 5826 grad_norm: 4.5806 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7603 loss: 1.7603 2022/10/08 09:17:05 - mmengine - INFO - Epoch(train) [123][1240/2119] lr: 4.0000e-03 eta: 5:36:51 time: 0.3528 data_time: 0.0183 memory: 5826 grad_norm: 4.6413 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8170 loss: 1.8170 2022/10/08 09:17:12 - mmengine - INFO - Epoch(train) [123][1260/2119] lr: 4.0000e-03 eta: 5:36:44 time: 0.3464 data_time: 0.0231 memory: 5826 grad_norm: 4.6236 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2113 loss: 2.2113 2022/10/08 09:17:20 - mmengine - INFO - Epoch(train) [123][1280/2119] lr: 4.0000e-03 eta: 5:36:37 time: 0.3853 data_time: 0.0238 memory: 5826 grad_norm: 4.6359 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1801 loss: 2.1801 2022/10/08 09:17:27 - mmengine - INFO - Epoch(train) [123][1300/2119] lr: 4.0000e-03 eta: 5:36:30 time: 0.3392 data_time: 0.0203 memory: 5826 grad_norm: 4.5767 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.7370 loss: 1.7370 2022/10/08 09:17:33 - mmengine - INFO - Epoch(train) [123][1320/2119] lr: 4.0000e-03 eta: 5:36:23 time: 0.3193 data_time: 0.0276 memory: 5826 grad_norm: 4.4856 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0460 loss: 2.0460 2022/10/08 09:17:39 - mmengine - INFO - Epoch(train) [123][1340/2119] lr: 4.0000e-03 eta: 5:36:16 time: 0.3216 data_time: 0.0228 memory: 5826 grad_norm: 4.4932 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8408 loss: 1.8408 2022/10/08 09:17:46 - mmengine - INFO - Epoch(train) [123][1360/2119] lr: 4.0000e-03 eta: 5:36:09 time: 0.3381 data_time: 0.0236 memory: 5826 grad_norm: 4.4989 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0461 loss: 2.0461 2022/10/08 09:17:53 - mmengine - INFO - Epoch(train) [123][1380/2119] lr: 4.0000e-03 eta: 5:36:02 time: 0.3464 data_time: 0.0211 memory: 5826 grad_norm: 4.5345 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9189 loss: 1.9189 2022/10/08 09:18:01 - mmengine - INFO - Epoch(train) [123][1400/2119] lr: 4.0000e-03 eta: 5:35:55 time: 0.3713 data_time: 0.0273 memory: 5826 grad_norm: 4.5522 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.3565 loss: 2.3565 2022/10/08 09:18:08 - mmengine - INFO - Epoch(train) [123][1420/2119] lr: 4.0000e-03 eta: 5:35:48 time: 0.3859 data_time: 0.0180 memory: 5826 grad_norm: 4.5401 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8696 loss: 1.8696 2022/10/08 09:18:14 - mmengine - INFO - Epoch(train) [123][1440/2119] lr: 4.0000e-03 eta: 5:35:41 time: 0.2933 data_time: 0.0201 memory: 5826 grad_norm: 4.5946 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.3574 loss: 2.3574 2022/10/08 09:18:22 - mmengine - INFO - Epoch(train) [123][1460/2119] lr: 4.0000e-03 eta: 5:35:34 time: 0.3910 data_time: 0.0197 memory: 5826 grad_norm: 4.6167 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9659 loss: 1.9659 2022/10/08 09:18:29 - mmengine - INFO - Epoch(train) [123][1480/2119] lr: 4.0000e-03 eta: 5:35:27 time: 0.3728 data_time: 0.0238 memory: 5826 grad_norm: 4.6272 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0765 loss: 2.0765 2022/10/08 09:18:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 09:18:36 - mmengine - INFO - Epoch(train) [123][1500/2119] lr: 4.0000e-03 eta: 5:35:20 time: 0.3191 data_time: 0.0227 memory: 5826 grad_norm: 4.5661 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0246 loss: 2.0246 2022/10/08 09:18:42 - mmengine - INFO - Epoch(train) [123][1520/2119] lr: 4.0000e-03 eta: 5:35:13 time: 0.3206 data_time: 0.0217 memory: 5826 grad_norm: 4.6028 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0417 loss: 2.0417 2022/10/08 09:18:50 - mmengine - INFO - Epoch(train) [123][1540/2119] lr: 4.0000e-03 eta: 5:35:07 time: 0.3801 data_time: 0.0238 memory: 5826 grad_norm: 4.6318 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1105 loss: 2.1105 2022/10/08 09:18:56 - mmengine - INFO - Epoch(train) [123][1560/2119] lr: 4.0000e-03 eta: 5:34:59 time: 0.3016 data_time: 0.0245 memory: 5826 grad_norm: 4.7027 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0495 loss: 2.0495 2022/10/08 09:19:04 - mmengine - INFO - Epoch(train) [123][1580/2119] lr: 4.0000e-03 eta: 5:34:53 time: 0.3954 data_time: 0.0211 memory: 5826 grad_norm: 4.4507 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1049 loss: 2.1049 2022/10/08 09:19:11 - mmengine - INFO - Epoch(train) [123][1600/2119] lr: 4.0000e-03 eta: 5:34:46 time: 0.3628 data_time: 0.0243 memory: 5826 grad_norm: 4.5522 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0154 loss: 2.0154 2022/10/08 09:19:19 - mmengine - INFO - Epoch(train) [123][1620/2119] lr: 4.0000e-03 eta: 5:34:39 time: 0.4071 data_time: 0.0157 memory: 5826 grad_norm: 4.4519 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8942 loss: 1.8942 2022/10/08 09:19:26 - mmengine - INFO - Epoch(train) [123][1640/2119] lr: 4.0000e-03 eta: 5:34:32 time: 0.3308 data_time: 0.0178 memory: 5826 grad_norm: 4.6712 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.0794 loss: 2.0794 2022/10/08 09:19:32 - mmengine - INFO - Epoch(train) [123][1660/2119] lr: 4.0000e-03 eta: 5:34:25 time: 0.3253 data_time: 0.0243 memory: 5826 grad_norm: 4.5720 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.7357 loss: 1.7357 2022/10/08 09:19:39 - mmengine - INFO - Epoch(train) [123][1680/2119] lr: 4.0000e-03 eta: 5:34:18 time: 0.3529 data_time: 0.0292 memory: 5826 grad_norm: 4.5903 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0040 loss: 2.0040 2022/10/08 09:19:47 - mmengine - INFO - Epoch(train) [123][1700/2119] lr: 4.0000e-03 eta: 5:34:11 time: 0.3757 data_time: 0.0198 memory: 5826 grad_norm: 4.5805 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.1584 loss: 2.1584 2022/10/08 09:19:53 - mmengine - INFO - Epoch(train) [123][1720/2119] lr: 4.0000e-03 eta: 5:34:04 time: 0.3135 data_time: 0.0265 memory: 5826 grad_norm: 4.6100 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9972 loss: 1.9972 2022/10/08 09:20:01 - mmengine - INFO - Epoch(train) [123][1740/2119] lr: 4.0000e-03 eta: 5:33:57 time: 0.3925 data_time: 0.0234 memory: 5826 grad_norm: 4.5677 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0443 loss: 2.0443 2022/10/08 09:20:08 - mmengine - INFO - Epoch(train) [123][1760/2119] lr: 4.0000e-03 eta: 5:33:50 time: 0.3336 data_time: 0.0235 memory: 5826 grad_norm: 4.5276 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1450 loss: 2.1450 2022/10/08 09:20:15 - mmengine - INFO - Epoch(train) [123][1780/2119] lr: 4.0000e-03 eta: 5:33:43 time: 0.3363 data_time: 0.0180 memory: 5826 grad_norm: 4.5216 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9214 loss: 1.9214 2022/10/08 09:20:22 - mmengine - INFO - Epoch(train) [123][1800/2119] lr: 4.0000e-03 eta: 5:33:36 time: 0.3838 data_time: 0.0279 memory: 5826 grad_norm: 4.5730 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1465 loss: 2.1465 2022/10/08 09:20:29 - mmengine - INFO - Epoch(train) [123][1820/2119] lr: 4.0000e-03 eta: 5:33:29 time: 0.3166 data_time: 0.0210 memory: 5826 grad_norm: 4.6080 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9882 loss: 1.9882 2022/10/08 09:20:35 - mmengine - INFO - Epoch(train) [123][1840/2119] lr: 4.0000e-03 eta: 5:33:22 time: 0.3397 data_time: 0.0206 memory: 5826 grad_norm: 4.6077 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8700 loss: 1.8700 2022/10/08 09:20:42 - mmengine - INFO - Epoch(train) [123][1860/2119] lr: 4.0000e-03 eta: 5:33:15 time: 0.3531 data_time: 0.0185 memory: 5826 grad_norm: 4.5937 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8363 loss: 1.8363 2022/10/08 09:20:49 - mmengine - INFO - Epoch(train) [123][1880/2119] lr: 4.0000e-03 eta: 5:33:08 time: 0.3330 data_time: 0.0293 memory: 5826 grad_norm: 4.4989 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8559 loss: 1.8559 2022/10/08 09:20:56 - mmengine - INFO - Epoch(train) [123][1900/2119] lr: 4.0000e-03 eta: 5:33:01 time: 0.3475 data_time: 0.0187 memory: 5826 grad_norm: 4.4922 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8652 loss: 1.8652 2022/10/08 09:21:03 - mmengine - INFO - Epoch(train) [123][1920/2119] lr: 4.0000e-03 eta: 5:32:54 time: 0.3444 data_time: 0.0223 memory: 5826 grad_norm: 4.5845 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9434 loss: 1.9434 2022/10/08 09:21:10 - mmengine - INFO - Epoch(train) [123][1940/2119] lr: 4.0000e-03 eta: 5:32:48 time: 0.3633 data_time: 0.0250 memory: 5826 grad_norm: 4.6360 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9805 loss: 1.9805 2022/10/08 09:21:16 - mmengine - INFO - Epoch(train) [123][1960/2119] lr: 4.0000e-03 eta: 5:32:40 time: 0.2998 data_time: 0.0241 memory: 5826 grad_norm: 4.5672 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9480 loss: 1.9480 2022/10/08 09:21:25 - mmengine - INFO - Epoch(train) [123][1980/2119] lr: 4.0000e-03 eta: 5:32:34 time: 0.4191 data_time: 0.0259 memory: 5826 grad_norm: 4.6346 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1999 loss: 2.1999 2022/10/08 09:21:31 - mmengine - INFO - Epoch(train) [123][2000/2119] lr: 4.0000e-03 eta: 5:32:27 time: 0.3322 data_time: 0.0220 memory: 5826 grad_norm: 4.5448 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8386 loss: 1.8386 2022/10/08 09:21:39 - mmengine - INFO - Epoch(train) [123][2020/2119] lr: 4.0000e-03 eta: 5:32:20 time: 0.3909 data_time: 0.0202 memory: 5826 grad_norm: 4.7228 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9680 loss: 1.9680 2022/10/08 09:21:45 - mmengine - INFO - Epoch(train) [123][2040/2119] lr: 4.0000e-03 eta: 5:32:13 time: 0.3112 data_time: 0.0199 memory: 5826 grad_norm: 4.4871 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7770 loss: 1.7770 2022/10/08 09:21:53 - mmengine - INFO - Epoch(train) [123][2060/2119] lr: 4.0000e-03 eta: 5:32:06 time: 0.3770 data_time: 0.0307 memory: 5826 grad_norm: 4.6264 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0726 loss: 2.0726 2022/10/08 09:22:01 - mmengine - INFO - Epoch(train) [123][2080/2119] lr: 4.0000e-03 eta: 5:31:59 time: 0.3835 data_time: 0.0230 memory: 5826 grad_norm: 4.6352 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.1355 loss: 2.1355 2022/10/08 09:22:09 - mmengine - INFO - Epoch(train) [123][2100/2119] lr: 4.0000e-03 eta: 5:31:52 time: 0.3955 data_time: 0.0211 memory: 5826 grad_norm: 4.6404 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0643 loss: 2.0643 2022/10/08 09:22:14 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 09:22:14 - mmengine - INFO - Epoch(train) [123][2119/2119] lr: 4.0000e-03 eta: 5:31:52 time: 0.3211 data_time: 0.0188 memory: 5826 grad_norm: 4.6391 top1_acc: 0.7000 top5_acc: 0.7000 loss_cls: 2.0693 loss: 2.0693 2022/10/08 09:22:24 - mmengine - INFO - Epoch(train) [124][20/2119] lr: 4.0000e-03 eta: 5:31:38 time: 0.4787 data_time: 0.1857 memory: 5826 grad_norm: 4.5226 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 1.9045 loss: 1.9045 2022/10/08 09:22:31 - mmengine - INFO - Epoch(train) [124][40/2119] lr: 4.0000e-03 eta: 5:31:31 time: 0.3565 data_time: 0.0270 memory: 5826 grad_norm: 4.6054 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1135 loss: 2.1135 2022/10/08 09:22:38 - mmengine - INFO - Epoch(train) [124][60/2119] lr: 4.0000e-03 eta: 5:31:24 time: 0.3405 data_time: 0.0244 memory: 5826 grad_norm: 4.5581 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0209 loss: 2.0209 2022/10/08 09:22:45 - mmengine - INFO - Epoch(train) [124][80/2119] lr: 4.0000e-03 eta: 5:31:17 time: 0.3512 data_time: 0.0200 memory: 5826 grad_norm: 4.4325 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9261 loss: 1.9261 2022/10/08 09:22:52 - mmengine - INFO - Epoch(train) [124][100/2119] lr: 4.0000e-03 eta: 5:31:10 time: 0.3699 data_time: 0.0212 memory: 5826 grad_norm: 4.5736 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8751 loss: 1.8751 2022/10/08 09:22:59 - mmengine - INFO - Epoch(train) [124][120/2119] lr: 4.0000e-03 eta: 5:31:03 time: 0.3264 data_time: 0.0261 memory: 5826 grad_norm: 4.5008 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0190 loss: 2.0190 2022/10/08 09:23:05 - mmengine - INFO - Epoch(train) [124][140/2119] lr: 4.0000e-03 eta: 5:30:56 time: 0.3296 data_time: 0.0235 memory: 5826 grad_norm: 4.5857 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 1.9857 loss: 1.9857 2022/10/08 09:23:13 - mmengine - INFO - Epoch(train) [124][160/2119] lr: 4.0000e-03 eta: 5:30:49 time: 0.4050 data_time: 0.0215 memory: 5826 grad_norm: 4.6756 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.0100 loss: 2.0100 2022/10/08 09:23:21 - mmengine - INFO - Epoch(train) [124][180/2119] lr: 4.0000e-03 eta: 5:30:43 time: 0.3849 data_time: 0.0178 memory: 5826 grad_norm: 4.5952 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9761 loss: 1.9761 2022/10/08 09:23:28 - mmengine - INFO - Epoch(train) [124][200/2119] lr: 4.0000e-03 eta: 5:30:36 time: 0.3614 data_time: 0.0188 memory: 5826 grad_norm: 4.5663 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0615 loss: 2.0615 2022/10/08 09:23:34 - mmengine - INFO - Epoch(train) [124][220/2119] lr: 4.0000e-03 eta: 5:30:29 time: 0.3128 data_time: 0.0231 memory: 5826 grad_norm: 4.5447 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.1084 loss: 2.1084 2022/10/08 09:23:42 - mmengine - INFO - Epoch(train) [124][240/2119] lr: 4.0000e-03 eta: 5:30:22 time: 0.3899 data_time: 0.0227 memory: 5826 grad_norm: 4.5824 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9044 loss: 1.9044 2022/10/08 09:23:49 - mmengine - INFO - Epoch(train) [124][260/2119] lr: 4.0000e-03 eta: 5:30:15 time: 0.3380 data_time: 0.0219 memory: 5826 grad_norm: 4.6203 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9744 loss: 1.9744 2022/10/08 09:23:56 - mmengine - INFO - Epoch(train) [124][280/2119] lr: 4.0000e-03 eta: 5:30:08 time: 0.3563 data_time: 0.0244 memory: 5826 grad_norm: 4.4893 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.7877 loss: 1.7877 2022/10/08 09:24:03 - mmengine - INFO - Epoch(train) [124][300/2119] lr: 4.0000e-03 eta: 5:30:01 time: 0.3501 data_time: 0.0225 memory: 5826 grad_norm: 4.6332 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1691 loss: 2.1691 2022/10/08 09:24:10 - mmengine - INFO - Epoch(train) [124][320/2119] lr: 4.0000e-03 eta: 5:29:54 time: 0.3245 data_time: 0.0263 memory: 5826 grad_norm: 4.6447 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.9944 loss: 1.9944 2022/10/08 09:24:17 - mmengine - INFO - Epoch(train) [124][340/2119] lr: 4.0000e-03 eta: 5:29:47 time: 0.3588 data_time: 0.0231 memory: 5826 grad_norm: 4.5443 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8570 loss: 1.8570 2022/10/08 09:24:24 - mmengine - INFO - Epoch(train) [124][360/2119] lr: 4.0000e-03 eta: 5:29:40 time: 0.3515 data_time: 0.0212 memory: 5826 grad_norm: 4.4418 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9352 loss: 1.9352 2022/10/08 09:24:25 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 09:24:31 - mmengine - INFO - Epoch(train) [124][380/2119] lr: 4.0000e-03 eta: 5:29:33 time: 0.3794 data_time: 0.0234 memory: 5826 grad_norm: 4.4705 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0257 loss: 2.0257 2022/10/08 09:24:38 - mmengine - INFO - Epoch(train) [124][400/2119] lr: 4.0000e-03 eta: 5:29:26 time: 0.3393 data_time: 0.0228 memory: 5826 grad_norm: 4.5833 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9448 loss: 1.9448 2022/10/08 09:24:45 - mmengine - INFO - Epoch(train) [124][420/2119] lr: 4.0000e-03 eta: 5:29:19 time: 0.3432 data_time: 0.0174 memory: 5826 grad_norm: 4.6116 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.1694 loss: 2.1694 2022/10/08 09:24:53 - mmengine - INFO - Epoch(train) [124][440/2119] lr: 4.0000e-03 eta: 5:29:12 time: 0.3787 data_time: 0.0230 memory: 5826 grad_norm: 4.5973 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.1559 loss: 2.1559 2022/10/08 09:25:00 - mmengine - INFO - Epoch(train) [124][460/2119] lr: 4.0000e-03 eta: 5:29:06 time: 0.3592 data_time: 0.0187 memory: 5826 grad_norm: 4.5705 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9512 loss: 1.9512 2022/10/08 09:25:08 - mmengine - INFO - Epoch(train) [124][480/2119] lr: 4.0000e-03 eta: 5:28:59 time: 0.3838 data_time: 0.0193 memory: 5826 grad_norm: 4.5781 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1342 loss: 2.1342 2022/10/08 09:25:14 - mmengine - INFO - Epoch(train) [124][500/2119] lr: 4.0000e-03 eta: 5:28:52 time: 0.3207 data_time: 0.0260 memory: 5826 grad_norm: 4.6170 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0584 loss: 2.0584 2022/10/08 09:25:22 - mmengine - INFO - Epoch(train) [124][520/2119] lr: 4.0000e-03 eta: 5:28:45 time: 0.3827 data_time: 0.0221 memory: 5826 grad_norm: 4.6509 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9136 loss: 1.9136 2022/10/08 09:25:29 - mmengine - INFO - Epoch(train) [124][540/2119] lr: 4.0000e-03 eta: 5:28:38 time: 0.3798 data_time: 0.0191 memory: 5826 grad_norm: 4.5689 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8984 loss: 1.8984 2022/10/08 09:25:36 - mmengine - INFO - Epoch(train) [124][560/2119] lr: 4.0000e-03 eta: 5:28:31 time: 0.3558 data_time: 0.0229 memory: 5826 grad_norm: 4.6454 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.0088 loss: 2.0088 2022/10/08 09:25:44 - mmengine - INFO - Epoch(train) [124][580/2119] lr: 4.0000e-03 eta: 5:28:24 time: 0.4036 data_time: 0.0266 memory: 5826 grad_norm: 4.6088 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.8650 loss: 1.8650 2022/10/08 09:25:52 - mmengine - INFO - Epoch(train) [124][600/2119] lr: 4.0000e-03 eta: 5:28:18 time: 0.3560 data_time: 0.0203 memory: 5826 grad_norm: 4.5177 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9953 loss: 1.9953 2022/10/08 09:25:58 - mmengine - INFO - Epoch(train) [124][620/2119] lr: 4.0000e-03 eta: 5:28:10 time: 0.3264 data_time: 0.0242 memory: 5826 grad_norm: 4.5107 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0889 loss: 2.0889 2022/10/08 09:26:06 - mmengine - INFO - Epoch(train) [124][640/2119] lr: 4.0000e-03 eta: 5:28:04 time: 0.3681 data_time: 0.0195 memory: 5826 grad_norm: 4.6806 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1030 loss: 2.1030 2022/10/08 09:26:13 - mmengine - INFO - Epoch(train) [124][660/2119] lr: 4.0000e-03 eta: 5:27:57 time: 0.3649 data_time: 0.0201 memory: 5826 grad_norm: 4.7111 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.2560 loss: 2.2560 2022/10/08 09:26:20 - mmengine - INFO - Epoch(train) [124][680/2119] lr: 4.0000e-03 eta: 5:27:50 time: 0.3479 data_time: 0.0212 memory: 5826 grad_norm: 4.6181 top1_acc: 0.1250 top5_acc: 0.6875 loss_cls: 2.2703 loss: 2.2703 2022/10/08 09:26:26 - mmengine - INFO - Epoch(train) [124][700/2119] lr: 4.0000e-03 eta: 5:27:43 time: 0.3012 data_time: 0.0265 memory: 5826 grad_norm: 4.5478 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9030 loss: 1.9030 2022/10/08 09:26:34 - mmengine - INFO - Epoch(train) [124][720/2119] lr: 4.0000e-03 eta: 5:27:36 time: 0.4085 data_time: 0.0177 memory: 5826 grad_norm: 4.5775 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0334 loss: 2.0334 2022/10/08 09:26:42 - mmengine - INFO - Epoch(train) [124][740/2119] lr: 4.0000e-03 eta: 5:27:29 time: 0.4026 data_time: 0.0274 memory: 5826 grad_norm: 4.5655 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8734 loss: 1.8734 2022/10/08 09:26:49 - mmengine - INFO - Epoch(train) [124][760/2119] lr: 4.0000e-03 eta: 5:27:22 time: 0.3594 data_time: 0.0218 memory: 5826 grad_norm: 4.6200 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.8949 loss: 1.8949 2022/10/08 09:26:55 - mmengine - INFO - Epoch(train) [124][780/2119] lr: 4.0000e-03 eta: 5:27:15 time: 0.3078 data_time: 0.0217 memory: 5826 grad_norm: 4.6147 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9061 loss: 1.9061 2022/10/08 09:27:03 - mmengine - INFO - Epoch(train) [124][800/2119] lr: 4.0000e-03 eta: 5:27:08 time: 0.3998 data_time: 0.0228 memory: 5826 grad_norm: 4.5569 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9895 loss: 1.9895 2022/10/08 09:27:10 - mmengine - INFO - Epoch(train) [124][820/2119] lr: 4.0000e-03 eta: 5:27:01 time: 0.3220 data_time: 0.0211 memory: 5826 grad_norm: 4.6068 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9929 loss: 1.9929 2022/10/08 09:27:18 - mmengine - INFO - Epoch(train) [124][840/2119] lr: 4.0000e-03 eta: 5:26:55 time: 0.4020 data_time: 0.0218 memory: 5826 grad_norm: 4.5074 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9058 loss: 1.9058 2022/10/08 09:27:25 - mmengine - INFO - Epoch(train) [124][860/2119] lr: 4.0000e-03 eta: 5:26:48 time: 0.3774 data_time: 0.0191 memory: 5826 grad_norm: 4.6178 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0923 loss: 2.0923 2022/10/08 09:27:33 - mmengine - INFO - Epoch(train) [124][880/2119] lr: 4.0000e-03 eta: 5:26:41 time: 0.3613 data_time: 0.0211 memory: 5826 grad_norm: 4.5618 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9853 loss: 1.9853 2022/10/08 09:27:40 - mmengine - INFO - Epoch(train) [124][900/2119] lr: 4.0000e-03 eta: 5:26:34 time: 0.3428 data_time: 0.0227 memory: 5826 grad_norm: 4.6690 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9529 loss: 1.9529 2022/10/08 09:27:47 - mmengine - INFO - Epoch(train) [124][920/2119] lr: 4.0000e-03 eta: 5:26:27 time: 0.3848 data_time: 0.0247 memory: 5826 grad_norm: 4.6171 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 1.8974 loss: 1.8974 2022/10/08 09:27:53 - mmengine - INFO - Epoch(train) [124][940/2119] lr: 4.0000e-03 eta: 5:26:20 time: 0.2973 data_time: 0.0232 memory: 5826 grad_norm: 4.5706 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.8060 loss: 1.8060 2022/10/08 09:28:01 - mmengine - INFO - Epoch(train) [124][960/2119] lr: 4.0000e-03 eta: 5:26:13 time: 0.4127 data_time: 0.0256 memory: 5826 grad_norm: 4.6573 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0322 loss: 2.0322 2022/10/08 09:28:09 - mmengine - INFO - Epoch(train) [124][980/2119] lr: 4.0000e-03 eta: 5:26:06 time: 0.3624 data_time: 0.0193 memory: 5826 grad_norm: 4.6275 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2681 loss: 2.2681 2022/10/08 09:28:17 - mmengine - INFO - Epoch(train) [124][1000/2119] lr: 4.0000e-03 eta: 5:26:00 time: 0.4034 data_time: 0.0170 memory: 5826 grad_norm: 4.5568 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8705 loss: 1.8705 2022/10/08 09:28:24 - mmengine - INFO - Epoch(train) [124][1020/2119] lr: 4.0000e-03 eta: 5:25:53 time: 0.3565 data_time: 0.0249 memory: 5826 grad_norm: 4.6420 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7941 loss: 1.7941 2022/10/08 09:28:32 - mmengine - INFO - Epoch(train) [124][1040/2119] lr: 4.0000e-03 eta: 5:25:46 time: 0.3869 data_time: 0.0205 memory: 5826 grad_norm: 4.6108 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0770 loss: 2.0770 2022/10/08 09:28:38 - mmengine - INFO - Epoch(train) [124][1060/2119] lr: 4.0000e-03 eta: 5:25:39 time: 0.3265 data_time: 0.0193 memory: 5826 grad_norm: 4.6432 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9316 loss: 1.9316 2022/10/08 09:28:45 - mmengine - INFO - Epoch(train) [124][1080/2119] lr: 4.0000e-03 eta: 5:25:32 time: 0.3195 data_time: 0.0261 memory: 5826 grad_norm: 4.5954 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9555 loss: 1.9555 2022/10/08 09:28:52 - mmengine - INFO - Epoch(train) [124][1100/2119] lr: 4.0000e-03 eta: 5:25:25 time: 0.3459 data_time: 0.0252 memory: 5826 grad_norm: 4.6163 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9793 loss: 1.9793 2022/10/08 09:28:59 - mmengine - INFO - Epoch(train) [124][1120/2119] lr: 4.0000e-03 eta: 5:25:18 time: 0.3736 data_time: 0.0181 memory: 5826 grad_norm: 4.5813 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9409 loss: 1.9409 2022/10/08 09:29:07 - mmengine - INFO - Epoch(train) [124][1140/2119] lr: 4.0000e-03 eta: 5:25:11 time: 0.3879 data_time: 0.0212 memory: 5826 grad_norm: 4.6163 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2087 loss: 2.2087 2022/10/08 09:29:13 - mmengine - INFO - Epoch(train) [124][1160/2119] lr: 4.0000e-03 eta: 5:25:04 time: 0.3227 data_time: 0.0212 memory: 5826 grad_norm: 4.5807 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7154 loss: 1.7154 2022/10/08 09:29:21 - mmengine - INFO - Epoch(train) [124][1180/2119] lr: 4.0000e-03 eta: 5:24:57 time: 0.3614 data_time: 0.0275 memory: 5826 grad_norm: 4.6280 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.0995 loss: 2.0995 2022/10/08 09:29:27 - mmengine - INFO - Epoch(train) [124][1200/2119] lr: 4.0000e-03 eta: 5:24:50 time: 0.3266 data_time: 0.0238 memory: 5826 grad_norm: 4.6303 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0053 loss: 2.0053 2022/10/08 09:29:34 - mmengine - INFO - Epoch(train) [124][1220/2119] lr: 4.0000e-03 eta: 5:24:43 time: 0.3572 data_time: 0.0210 memory: 5826 grad_norm: 4.6394 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9930 loss: 1.9930 2022/10/08 09:29:42 - mmengine - INFO - Epoch(train) [124][1240/2119] lr: 4.0000e-03 eta: 5:24:36 time: 0.4050 data_time: 0.0233 memory: 5826 grad_norm: 4.6083 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9979 loss: 1.9979 2022/10/08 09:29:50 - mmengine - INFO - Epoch(train) [124][1260/2119] lr: 4.0000e-03 eta: 5:24:30 time: 0.3664 data_time: 0.0267 memory: 5826 grad_norm: 4.6262 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8556 loss: 1.8556 2022/10/08 09:29:57 - mmengine - INFO - Epoch(train) [124][1280/2119] lr: 4.0000e-03 eta: 5:24:23 time: 0.3767 data_time: 0.0210 memory: 5826 grad_norm: 4.6133 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9640 loss: 1.9640 2022/10/08 09:30:04 - mmengine - INFO - Epoch(train) [124][1300/2119] lr: 4.0000e-03 eta: 5:24:16 time: 0.3269 data_time: 0.0238 memory: 5826 grad_norm: 4.5593 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0969 loss: 2.0969 2022/10/08 09:30:11 - mmengine - INFO - Epoch(train) [124][1320/2119] lr: 4.0000e-03 eta: 5:24:09 time: 0.3469 data_time: 0.0232 memory: 5826 grad_norm: 4.5401 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9279 loss: 1.9279 2022/10/08 09:30:17 - mmengine - INFO - Epoch(train) [124][1340/2119] lr: 4.0000e-03 eta: 5:24:02 time: 0.3364 data_time: 0.0230 memory: 5826 grad_norm: 4.6099 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0482 loss: 2.0482 2022/10/08 09:30:25 - mmengine - INFO - Epoch(train) [124][1360/2119] lr: 4.0000e-03 eta: 5:23:55 time: 0.3881 data_time: 0.0218 memory: 5826 grad_norm: 4.6387 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1184 loss: 2.1184 2022/10/08 09:30:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 09:30:32 - mmengine - INFO - Epoch(train) [124][1380/2119] lr: 4.0000e-03 eta: 5:23:48 time: 0.3489 data_time: 0.0239 memory: 5826 grad_norm: 4.6165 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8489 loss: 1.8489 2022/10/08 09:30:39 - mmengine - INFO - Epoch(train) [124][1400/2119] lr: 4.0000e-03 eta: 5:23:41 time: 0.3549 data_time: 0.0227 memory: 5826 grad_norm: 4.6157 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0241 loss: 2.0241 2022/10/08 09:30:46 - mmengine - INFO - Epoch(train) [124][1420/2119] lr: 4.0000e-03 eta: 5:23:34 time: 0.3214 data_time: 0.0204 memory: 5826 grad_norm: 4.4887 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1538 loss: 2.1538 2022/10/08 09:30:53 - mmengine - INFO - Epoch(train) [124][1440/2119] lr: 4.0000e-03 eta: 5:23:27 time: 0.3814 data_time: 0.0265 memory: 5826 grad_norm: 4.6434 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0634 loss: 2.0634 2022/10/08 09:31:00 - mmengine - INFO - Epoch(train) [124][1460/2119] lr: 4.0000e-03 eta: 5:23:20 time: 0.3242 data_time: 0.0228 memory: 5826 grad_norm: 4.6582 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7820 loss: 1.7820 2022/10/08 09:31:07 - mmengine - INFO - Epoch(train) [124][1480/2119] lr: 4.0000e-03 eta: 5:23:13 time: 0.3690 data_time: 0.0193 memory: 5826 grad_norm: 4.6326 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.1524 loss: 2.1524 2022/10/08 09:31:14 - mmengine - INFO - Epoch(train) [124][1500/2119] lr: 4.0000e-03 eta: 5:23:06 time: 0.3227 data_time: 0.0191 memory: 5826 grad_norm: 4.6044 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.7340 loss: 1.7340 2022/10/08 09:31:21 - mmengine - INFO - Epoch(train) [124][1520/2119] lr: 4.0000e-03 eta: 5:22:59 time: 0.3725 data_time: 0.0208 memory: 5826 grad_norm: 4.5604 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9729 loss: 1.9729 2022/10/08 09:31:28 - mmengine - INFO - Epoch(train) [124][1540/2119] lr: 4.0000e-03 eta: 5:22:52 time: 0.3312 data_time: 0.0193 memory: 5826 grad_norm: 4.5219 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7586 loss: 1.7586 2022/10/08 09:31:36 - mmengine - INFO - Epoch(train) [124][1560/2119] lr: 4.0000e-03 eta: 5:22:46 time: 0.3974 data_time: 0.0258 memory: 5826 grad_norm: 4.6716 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9801 loss: 1.9801 2022/10/08 09:31:43 - mmengine - INFO - Epoch(train) [124][1580/2119] lr: 4.0000e-03 eta: 5:22:39 time: 0.3474 data_time: 0.0219 memory: 5826 grad_norm: 4.5881 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1528 loss: 2.1528 2022/10/08 09:31:50 - mmengine - INFO - Epoch(train) [124][1600/2119] lr: 4.0000e-03 eta: 5:22:32 time: 0.3840 data_time: 0.0227 memory: 5826 grad_norm: 4.6393 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0606 loss: 2.0606 2022/10/08 09:31:57 - mmengine - INFO - Epoch(train) [124][1620/2119] lr: 4.0000e-03 eta: 5:22:25 time: 0.3193 data_time: 0.0239 memory: 5826 grad_norm: 4.6264 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8384 loss: 1.8384 2022/10/08 09:32:05 - mmengine - INFO - Epoch(train) [124][1640/2119] lr: 4.0000e-03 eta: 5:22:18 time: 0.4336 data_time: 0.0217 memory: 5826 grad_norm: 4.6607 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9992 loss: 1.9992 2022/10/08 09:32:13 - mmengine - INFO - Epoch(train) [124][1660/2119] lr: 4.0000e-03 eta: 5:22:11 time: 0.3586 data_time: 0.0220 memory: 5826 grad_norm: 4.6341 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6708 loss: 1.6708 2022/10/08 09:32:20 - mmengine - INFO - Epoch(train) [124][1680/2119] lr: 4.0000e-03 eta: 5:22:04 time: 0.3738 data_time: 0.0163 memory: 5826 grad_norm: 4.5911 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9018 loss: 1.9018 2022/10/08 09:32:26 - mmengine - INFO - Epoch(train) [124][1700/2119] lr: 4.0000e-03 eta: 5:21:57 time: 0.3009 data_time: 0.0209 memory: 5826 grad_norm: 4.6465 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9274 loss: 1.9274 2022/10/08 09:32:34 - mmengine - INFO - Epoch(train) [124][1720/2119] lr: 4.0000e-03 eta: 5:21:50 time: 0.3963 data_time: 0.0248 memory: 5826 grad_norm: 4.7382 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9325 loss: 1.9325 2022/10/08 09:32:40 - mmengine - INFO - Epoch(train) [124][1740/2119] lr: 4.0000e-03 eta: 5:21:43 time: 0.3025 data_time: 0.0201 memory: 5826 grad_norm: 4.7086 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9300 loss: 1.9300 2022/10/08 09:32:48 - mmengine - INFO - Epoch(train) [124][1760/2119] lr: 4.0000e-03 eta: 5:21:36 time: 0.3670 data_time: 0.0226 memory: 5826 grad_norm: 4.6689 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0533 loss: 2.0533 2022/10/08 09:32:54 - mmengine - INFO - Epoch(train) [124][1780/2119] lr: 4.0000e-03 eta: 5:21:29 time: 0.3423 data_time: 0.0232 memory: 5826 grad_norm: 4.6196 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1060 loss: 2.1060 2022/10/08 09:33:02 - mmengine - INFO - Epoch(train) [124][1800/2119] lr: 4.0000e-03 eta: 5:21:23 time: 0.3840 data_time: 0.0254 memory: 5826 grad_norm: 4.6742 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7421 loss: 1.7421 2022/10/08 09:33:09 - mmengine - INFO - Epoch(train) [124][1820/2119] lr: 4.0000e-03 eta: 5:21:16 time: 0.3653 data_time: 0.0255 memory: 5826 grad_norm: 4.7008 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9133 loss: 1.9133 2022/10/08 09:33:16 - mmengine - INFO - Epoch(train) [124][1840/2119] lr: 4.0000e-03 eta: 5:21:09 time: 0.3457 data_time: 0.0245 memory: 5826 grad_norm: 4.5990 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.1712 loss: 2.1712 2022/10/08 09:33:23 - mmengine - INFO - Epoch(train) [124][1860/2119] lr: 4.0000e-03 eta: 5:21:02 time: 0.3402 data_time: 0.0187 memory: 5826 grad_norm: 4.6078 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9306 loss: 1.9306 2022/10/08 09:33:31 - mmengine - INFO - Epoch(train) [124][1880/2119] lr: 4.0000e-03 eta: 5:20:55 time: 0.3867 data_time: 0.0206 memory: 5826 grad_norm: 4.5792 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0570 loss: 2.0570 2022/10/08 09:33:37 - mmengine - INFO - Epoch(train) [124][1900/2119] lr: 4.0000e-03 eta: 5:20:48 time: 0.2939 data_time: 0.0226 memory: 5826 grad_norm: 4.6050 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1992 loss: 2.1992 2022/10/08 09:33:44 - mmengine - INFO - Epoch(train) [124][1920/2119] lr: 4.0000e-03 eta: 5:20:41 time: 0.3875 data_time: 0.0202 memory: 5826 grad_norm: 4.5364 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.9488 loss: 1.9488 2022/10/08 09:33:51 - mmengine - INFO - Epoch(train) [124][1940/2119] lr: 4.0000e-03 eta: 5:20:34 time: 0.3482 data_time: 0.0215 memory: 5826 grad_norm: 4.6240 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8545 loss: 1.8545 2022/10/08 09:33:59 - mmengine - INFO - Epoch(train) [124][1960/2119] lr: 4.0000e-03 eta: 5:20:27 time: 0.3759 data_time: 0.0258 memory: 5826 grad_norm: 4.6656 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1505 loss: 2.1505 2022/10/08 09:34:05 - mmengine - INFO - Epoch(train) [124][1980/2119] lr: 4.0000e-03 eta: 5:20:20 time: 0.3135 data_time: 0.0184 memory: 5826 grad_norm: 4.6963 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1775 loss: 2.1775 2022/10/08 09:34:13 - mmengine - INFO - Epoch(train) [124][2000/2119] lr: 4.0000e-03 eta: 5:20:13 time: 0.3871 data_time: 0.0212 memory: 5826 grad_norm: 4.6371 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.1278 loss: 2.1278 2022/10/08 09:34:20 - mmengine - INFO - Epoch(train) [124][2020/2119] lr: 4.0000e-03 eta: 5:20:06 time: 0.3255 data_time: 0.0198 memory: 5826 grad_norm: 4.6680 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.0128 loss: 2.0128 2022/10/08 09:34:27 - mmengine - INFO - Epoch(train) [124][2040/2119] lr: 4.0000e-03 eta: 5:19:59 time: 0.3601 data_time: 0.0197 memory: 5826 grad_norm: 4.6484 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1947 loss: 2.1947 2022/10/08 09:34:33 - mmengine - INFO - Epoch(train) [124][2060/2119] lr: 4.0000e-03 eta: 5:19:52 time: 0.3353 data_time: 0.0227 memory: 5826 grad_norm: 4.6237 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.0497 loss: 2.0497 2022/10/08 09:34:41 - mmengine - INFO - Epoch(train) [124][2080/2119] lr: 4.0000e-03 eta: 5:19:46 time: 0.4017 data_time: 0.0211 memory: 5826 grad_norm: 4.7687 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9799 loss: 1.9799 2022/10/08 09:34:48 - mmengine - INFO - Epoch(train) [124][2100/2119] lr: 4.0000e-03 eta: 5:19:39 time: 0.3288 data_time: 0.0212 memory: 5826 grad_norm: 4.6604 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.2384 loss: 2.2384 2022/10/08 09:34:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 09:34:56 - mmengine - INFO - Epoch(train) [124][2119/2119] lr: 4.0000e-03 eta: 5:19:39 time: 0.3978 data_time: 0.0183 memory: 5826 grad_norm: 4.6159 top1_acc: 0.4000 top5_acc: 0.8000 loss_cls: 2.1595 loss: 2.1595 2022/10/08 09:34:56 - mmengine - INFO - Saving checkpoint at 124 epochs 2022/10/08 09:35:08 - mmengine - INFO - Epoch(train) [125][20/2119] lr: 4.0000e-03 eta: 5:19:24 time: 0.4853 data_time: 0.2720 memory: 5826 grad_norm: 4.6949 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9572 loss: 1.9572 2022/10/08 09:35:15 - mmengine - INFO - Epoch(train) [125][40/2119] lr: 4.0000e-03 eta: 5:19:17 time: 0.3134 data_time: 0.0884 memory: 5826 grad_norm: 4.5836 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8590 loss: 1.8590 2022/10/08 09:35:22 - mmengine - INFO - Epoch(train) [125][60/2119] lr: 4.0000e-03 eta: 5:19:10 time: 0.3814 data_time: 0.1470 memory: 5826 grad_norm: 4.6241 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.1393 loss: 2.1393 2022/10/08 09:35:29 - mmengine - INFO - Epoch(train) [125][80/2119] lr: 4.0000e-03 eta: 5:19:03 time: 0.3251 data_time: 0.0977 memory: 5826 grad_norm: 4.6161 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9606 loss: 1.9606 2022/10/08 09:35:36 - mmengine - INFO - Epoch(train) [125][100/2119] lr: 4.0000e-03 eta: 5:18:56 time: 0.3813 data_time: 0.1483 memory: 5826 grad_norm: 4.6857 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0496 loss: 2.0496 2022/10/08 09:35:43 - mmengine - INFO - Epoch(train) [125][120/2119] lr: 4.0000e-03 eta: 5:18:49 time: 0.3077 data_time: 0.0552 memory: 5826 grad_norm: 4.6315 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8445 loss: 1.8445 2022/10/08 09:35:50 - mmengine - INFO - Epoch(train) [125][140/2119] lr: 4.0000e-03 eta: 5:18:42 time: 0.3645 data_time: 0.1338 memory: 5826 grad_norm: 4.7010 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9422 loss: 1.9422 2022/10/08 09:35:57 - mmengine - INFO - Epoch(train) [125][160/2119] lr: 4.0000e-03 eta: 5:18:35 time: 0.3421 data_time: 0.1052 memory: 5826 grad_norm: 4.6481 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9772 loss: 1.9772 2022/10/08 09:36:03 - mmengine - INFO - Epoch(train) [125][180/2119] lr: 4.0000e-03 eta: 5:18:28 time: 0.3352 data_time: 0.0432 memory: 5826 grad_norm: 4.6415 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9754 loss: 1.9754 2022/10/08 09:36:10 - mmengine - INFO - Epoch(train) [125][200/2119] lr: 4.0000e-03 eta: 5:18:21 time: 0.3453 data_time: 0.0164 memory: 5826 grad_norm: 4.6151 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9695 loss: 1.9695 2022/10/08 09:36:18 - mmengine - INFO - Epoch(train) [125][220/2119] lr: 4.0000e-03 eta: 5:18:14 time: 0.3593 data_time: 0.0201 memory: 5826 grad_norm: 4.6942 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0272 loss: 2.0272 2022/10/08 09:36:25 - mmengine - INFO - Epoch(train) [125][240/2119] lr: 4.0000e-03 eta: 5:18:07 time: 0.3518 data_time: 0.0210 memory: 5826 grad_norm: 4.7441 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8346 loss: 1.8346 2022/10/08 09:36:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 09:36:32 - mmengine - INFO - Epoch(train) [125][260/2119] lr: 4.0000e-03 eta: 5:18:01 time: 0.3786 data_time: 0.0248 memory: 5826 grad_norm: 4.6225 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7845 loss: 1.7845 2022/10/08 09:36:41 - mmengine - INFO - Epoch(train) [125][280/2119] lr: 4.0000e-03 eta: 5:17:54 time: 0.4238 data_time: 0.0259 memory: 5826 grad_norm: 4.6986 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0548 loss: 2.0548 2022/10/08 09:36:46 - mmengine - INFO - Epoch(train) [125][300/2119] lr: 4.0000e-03 eta: 5:17:47 time: 0.2619 data_time: 0.0232 memory: 5826 grad_norm: 4.6270 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0170 loss: 2.0170 2022/10/08 09:36:53 - mmengine - INFO - Epoch(train) [125][320/2119] lr: 4.0000e-03 eta: 5:17:40 time: 0.3748 data_time: 0.0236 memory: 5826 grad_norm: 4.5385 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1065 loss: 2.1065 2022/10/08 09:37:00 - mmengine - INFO - Epoch(train) [125][340/2119] lr: 4.0000e-03 eta: 5:17:33 time: 0.3464 data_time: 0.0229 memory: 5826 grad_norm: 4.6027 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8041 loss: 1.8041 2022/10/08 09:37:08 - mmengine - INFO - Epoch(train) [125][360/2119] lr: 4.0000e-03 eta: 5:17:26 time: 0.3695 data_time: 0.0234 memory: 5826 grad_norm: 4.5419 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9387 loss: 1.9387 2022/10/08 09:37:15 - mmengine - INFO - Epoch(train) [125][380/2119] lr: 4.0000e-03 eta: 5:17:19 time: 0.3655 data_time: 0.0198 memory: 5826 grad_norm: 4.6194 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8522 loss: 1.8522 2022/10/08 09:37:22 - mmengine - INFO - Epoch(train) [125][400/2119] lr: 4.0000e-03 eta: 5:17:12 time: 0.3552 data_time: 0.0254 memory: 5826 grad_norm: 4.6115 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9795 loss: 1.9795 2022/10/08 09:37:30 - mmengine - INFO - Epoch(train) [125][420/2119] lr: 4.0000e-03 eta: 5:17:05 time: 0.3747 data_time: 0.0208 memory: 5826 grad_norm: 4.5106 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9323 loss: 1.9323 2022/10/08 09:37:36 - mmengine - INFO - Epoch(train) [125][440/2119] lr: 4.0000e-03 eta: 5:16:58 time: 0.3215 data_time: 0.0322 memory: 5826 grad_norm: 4.6355 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0283 loss: 2.0283 2022/10/08 09:37:43 - mmengine - INFO - Epoch(train) [125][460/2119] lr: 4.0000e-03 eta: 5:16:51 time: 0.3460 data_time: 0.0219 memory: 5826 grad_norm: 4.6455 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9261 loss: 1.9261 2022/10/08 09:37:52 - mmengine - INFO - Epoch(train) [125][480/2119] lr: 4.0000e-03 eta: 5:16:45 time: 0.4626 data_time: 0.0200 memory: 5826 grad_norm: 4.6404 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9743 loss: 1.9743 2022/10/08 09:37:58 - mmengine - INFO - Epoch(train) [125][500/2119] lr: 4.0000e-03 eta: 5:16:38 time: 0.3038 data_time: 0.0195 memory: 5826 grad_norm: 4.6467 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.9935 loss: 1.9935 2022/10/08 09:38:06 - mmengine - INFO - Epoch(train) [125][520/2119] lr: 4.0000e-03 eta: 5:16:31 time: 0.3928 data_time: 0.0252 memory: 5826 grad_norm: 4.6789 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1471 loss: 2.1471 2022/10/08 09:38:13 - mmengine - INFO - Epoch(train) [125][540/2119] lr: 4.0000e-03 eta: 5:16:24 time: 0.3201 data_time: 0.0224 memory: 5826 grad_norm: 4.6333 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1285 loss: 2.1285 2022/10/08 09:38:19 - mmengine - INFO - Epoch(train) [125][560/2119] lr: 4.0000e-03 eta: 5:16:17 time: 0.3119 data_time: 0.0219 memory: 5826 grad_norm: 4.6442 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0171 loss: 2.0171 2022/10/08 09:38:26 - mmengine - INFO - Epoch(train) [125][580/2119] lr: 4.0000e-03 eta: 5:16:10 time: 0.3359 data_time: 0.0210 memory: 5826 grad_norm: 4.6335 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8070 loss: 1.8070 2022/10/08 09:38:33 - mmengine - INFO - Epoch(train) [125][600/2119] lr: 4.0000e-03 eta: 5:16:03 time: 0.3798 data_time: 0.0222 memory: 5826 grad_norm: 4.7031 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8869 loss: 1.8869 2022/10/08 09:38:40 - mmengine - INFO - Epoch(train) [125][620/2119] lr: 4.0000e-03 eta: 5:15:56 time: 0.3214 data_time: 0.0259 memory: 5826 grad_norm: 4.6659 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9788 loss: 1.9788 2022/10/08 09:38:48 - mmengine - INFO - Epoch(train) [125][640/2119] lr: 4.0000e-03 eta: 5:15:49 time: 0.4349 data_time: 0.0174 memory: 5826 grad_norm: 4.7020 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8984 loss: 1.8984 2022/10/08 09:38:55 - mmengine - INFO - Epoch(train) [125][660/2119] lr: 4.0000e-03 eta: 5:15:42 time: 0.3170 data_time: 0.0217 memory: 5826 grad_norm: 4.6752 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0453 loss: 2.0453 2022/10/08 09:39:03 - mmengine - INFO - Epoch(train) [125][680/2119] lr: 4.0000e-03 eta: 5:15:35 time: 0.3889 data_time: 0.0282 memory: 5826 grad_norm: 4.6744 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.8104 loss: 1.8104 2022/10/08 09:39:09 - mmengine - INFO - Epoch(train) [125][700/2119] lr: 4.0000e-03 eta: 5:15:28 time: 0.3462 data_time: 0.0223 memory: 5826 grad_norm: 4.7730 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1237 loss: 2.1237 2022/10/08 09:39:17 - mmengine - INFO - Epoch(train) [125][720/2119] lr: 4.0000e-03 eta: 5:15:22 time: 0.3716 data_time: 0.0192 memory: 5826 grad_norm: 4.8037 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.9819 loss: 1.9819 2022/10/08 09:39:24 - mmengine - INFO - Epoch(train) [125][740/2119] lr: 4.0000e-03 eta: 5:15:15 time: 0.3548 data_time: 0.0194 memory: 5826 grad_norm: 4.6689 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.0393 loss: 2.0393 2022/10/08 09:39:32 - mmengine - INFO - Epoch(train) [125][760/2119] lr: 4.0000e-03 eta: 5:15:08 time: 0.3998 data_time: 0.0232 memory: 5826 grad_norm: 4.6262 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.9118 loss: 1.9118 2022/10/08 09:39:38 - mmengine - INFO - Epoch(train) [125][780/2119] lr: 4.0000e-03 eta: 5:15:01 time: 0.3155 data_time: 0.0252 memory: 5826 grad_norm: 4.7462 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0393 loss: 2.0393 2022/10/08 09:39:45 - mmengine - INFO - Epoch(train) [125][800/2119] lr: 4.0000e-03 eta: 5:14:54 time: 0.3383 data_time: 0.0362 memory: 5826 grad_norm: 4.6860 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.8982 loss: 1.8982 2022/10/08 09:39:52 - mmengine - INFO - Epoch(train) [125][820/2119] lr: 4.0000e-03 eta: 5:14:47 time: 0.3509 data_time: 0.0219 memory: 5826 grad_norm: 4.7186 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8091 loss: 1.8091 2022/10/08 09:39:59 - mmengine - INFO - Epoch(train) [125][840/2119] lr: 4.0000e-03 eta: 5:14:40 time: 0.3490 data_time: 0.0221 memory: 5826 grad_norm: 4.6523 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0825 loss: 2.0825 2022/10/08 09:40:05 - mmengine - INFO - Epoch(train) [125][860/2119] lr: 4.0000e-03 eta: 5:14:33 time: 0.3170 data_time: 0.0240 memory: 5826 grad_norm: 4.6210 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9024 loss: 1.9024 2022/10/08 09:40:14 - mmengine - INFO - Epoch(train) [125][880/2119] lr: 4.0000e-03 eta: 5:14:26 time: 0.4041 data_time: 0.0200 memory: 5826 grad_norm: 4.5800 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8598 loss: 1.8598 2022/10/08 09:40:20 - mmengine - INFO - Epoch(train) [125][900/2119] lr: 4.0000e-03 eta: 5:14:19 time: 0.3118 data_time: 0.0267 memory: 5826 grad_norm: 4.6231 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0287 loss: 2.0287 2022/10/08 09:40:27 - mmengine - INFO - Epoch(train) [125][920/2119] lr: 4.0000e-03 eta: 5:14:12 time: 0.3661 data_time: 0.0201 memory: 5826 grad_norm: 4.6212 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9517 loss: 1.9517 2022/10/08 09:40:34 - mmengine - INFO - Epoch(train) [125][940/2119] lr: 4.0000e-03 eta: 5:14:05 time: 0.3592 data_time: 0.0215 memory: 5826 grad_norm: 4.6525 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.1548 loss: 2.1548 2022/10/08 09:40:41 - mmengine - INFO - Epoch(train) [125][960/2119] lr: 4.0000e-03 eta: 5:13:58 time: 0.3530 data_time: 0.0233 memory: 5826 grad_norm: 4.6010 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8409 loss: 1.8409 2022/10/08 09:40:48 - mmengine - INFO - Epoch(train) [125][980/2119] lr: 4.0000e-03 eta: 5:13:51 time: 0.3329 data_time: 0.0233 memory: 5826 grad_norm: 4.6551 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0280 loss: 2.0280 2022/10/08 09:40:56 - mmengine - INFO - Epoch(train) [125][1000/2119] lr: 4.0000e-03 eta: 5:13:44 time: 0.3866 data_time: 0.0226 memory: 5826 grad_norm: 4.6004 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8760 loss: 1.8760 2022/10/08 09:41:03 - mmengine - INFO - Epoch(train) [125][1020/2119] lr: 4.0000e-03 eta: 5:13:37 time: 0.3642 data_time: 0.0222 memory: 5826 grad_norm: 4.7236 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0259 loss: 2.0259 2022/10/08 09:41:11 - mmengine - INFO - Epoch(train) [125][1040/2119] lr: 4.0000e-03 eta: 5:13:31 time: 0.3697 data_time: 0.0172 memory: 5826 grad_norm: 4.8046 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0663 loss: 2.0663 2022/10/08 09:41:17 - mmengine - INFO - Epoch(train) [125][1060/2119] lr: 4.0000e-03 eta: 5:13:23 time: 0.3087 data_time: 0.0226 memory: 5826 grad_norm: 4.5888 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8840 loss: 1.8840 2022/10/08 09:41:24 - mmengine - INFO - Epoch(train) [125][1080/2119] lr: 4.0000e-03 eta: 5:13:17 time: 0.3813 data_time: 0.0227 memory: 5826 grad_norm: 4.5935 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9055 loss: 1.9055 2022/10/08 09:41:31 - mmengine - INFO - Epoch(train) [125][1100/2119] lr: 4.0000e-03 eta: 5:13:10 time: 0.3321 data_time: 0.0262 memory: 5826 grad_norm: 4.6279 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1943 loss: 2.1943 2022/10/08 09:41:38 - mmengine - INFO - Epoch(train) [125][1120/2119] lr: 4.0000e-03 eta: 5:13:03 time: 0.3286 data_time: 0.0279 memory: 5826 grad_norm: 4.6701 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.1707 loss: 2.1707 2022/10/08 09:41:46 - mmengine - INFO - Epoch(train) [125][1140/2119] lr: 4.0000e-03 eta: 5:12:56 time: 0.4096 data_time: 0.0190 memory: 5826 grad_norm: 4.7066 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1008 loss: 2.1008 2022/10/08 09:41:53 - mmengine - INFO - Epoch(train) [125][1160/2119] lr: 4.0000e-03 eta: 5:12:49 time: 0.3389 data_time: 0.0234 memory: 5826 grad_norm: 4.6787 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9900 loss: 1.9900 2022/10/08 09:42:00 - mmengine - INFO - Epoch(train) [125][1180/2119] lr: 4.0000e-03 eta: 5:12:42 time: 0.3772 data_time: 0.0208 memory: 5826 grad_norm: 4.6231 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.0849 loss: 2.0849 2022/10/08 09:42:07 - mmengine - INFO - Epoch(train) [125][1200/2119] lr: 4.0000e-03 eta: 5:12:35 time: 0.3255 data_time: 0.0173 memory: 5826 grad_norm: 4.6341 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9085 loss: 1.9085 2022/10/08 09:42:13 - mmengine - INFO - Epoch(train) [125][1220/2119] lr: 4.0000e-03 eta: 5:12:28 time: 0.3152 data_time: 0.0212 memory: 5826 grad_norm: 4.6445 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2493 loss: 2.2493 2022/10/08 09:42:20 - mmengine - INFO - Epoch(train) [125][1240/2119] lr: 4.0000e-03 eta: 5:12:21 time: 0.3564 data_time: 0.0479 memory: 5826 grad_norm: 4.6873 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9004 loss: 1.9004 2022/10/08 09:42:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 09:42:28 - mmengine - INFO - Epoch(train) [125][1260/2119] lr: 4.0000e-03 eta: 5:12:14 time: 0.3796 data_time: 0.0296 memory: 5826 grad_norm: 4.6392 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.9345 loss: 1.9345 2022/10/08 09:42:34 - mmengine - INFO - Epoch(train) [125][1280/2119] lr: 4.0000e-03 eta: 5:12:07 time: 0.3353 data_time: 0.0167 memory: 5826 grad_norm: 4.7606 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1106 loss: 2.1106 2022/10/08 09:42:41 - mmengine - INFO - Epoch(train) [125][1300/2119] lr: 4.0000e-03 eta: 5:12:00 time: 0.3218 data_time: 0.0192 memory: 5826 grad_norm: 4.5715 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0740 loss: 2.0740 2022/10/08 09:42:48 - mmengine - INFO - Epoch(train) [125][1320/2119] lr: 4.0000e-03 eta: 5:11:53 time: 0.3645 data_time: 0.0219 memory: 5826 grad_norm: 4.5931 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1809 loss: 2.1809 2022/10/08 09:42:56 - mmengine - INFO - Epoch(train) [125][1340/2119] lr: 4.0000e-03 eta: 5:11:46 time: 0.3775 data_time: 0.0260 memory: 5826 grad_norm: 4.6634 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.9749 loss: 1.9749 2022/10/08 09:43:04 - mmengine - INFO - Epoch(train) [125][1360/2119] lr: 4.0000e-03 eta: 5:11:40 time: 0.4143 data_time: 0.0252 memory: 5826 grad_norm: 4.6325 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8998 loss: 1.8998 2022/10/08 09:43:10 - mmengine - INFO - Epoch(train) [125][1380/2119] lr: 4.0000e-03 eta: 5:11:32 time: 0.3073 data_time: 0.0217 memory: 5826 grad_norm: 4.6370 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.1710 loss: 2.1710 2022/10/08 09:43:19 - mmengine - INFO - Epoch(train) [125][1400/2119] lr: 4.0000e-03 eta: 5:11:26 time: 0.4294 data_time: 0.0228 memory: 5826 grad_norm: 4.7169 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1797 loss: 2.1797 2022/10/08 09:43:26 - mmengine - INFO - Epoch(train) [125][1420/2119] lr: 4.0000e-03 eta: 5:11:19 time: 0.3776 data_time: 0.0207 memory: 5826 grad_norm: 4.6643 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9537 loss: 1.9537 2022/10/08 09:43:34 - mmengine - INFO - Epoch(train) [125][1440/2119] lr: 4.0000e-03 eta: 5:11:12 time: 0.3811 data_time: 0.0242 memory: 5826 grad_norm: 4.6029 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0136 loss: 2.0136 2022/10/08 09:43:40 - mmengine - INFO - Epoch(train) [125][1460/2119] lr: 4.0000e-03 eta: 5:11:05 time: 0.2856 data_time: 0.0192 memory: 5826 grad_norm: 4.7099 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.0110 loss: 2.0110 2022/10/08 09:43:49 - mmengine - INFO - Epoch(train) [125][1480/2119] lr: 4.0000e-03 eta: 5:10:58 time: 0.4479 data_time: 0.0207 memory: 5826 grad_norm: 4.7235 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1310 loss: 2.1310 2022/10/08 09:43:55 - mmengine - INFO - Epoch(train) [125][1500/2119] lr: 4.0000e-03 eta: 5:10:51 time: 0.3419 data_time: 0.0226 memory: 5826 grad_norm: 4.6607 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.0145 loss: 2.0145 2022/10/08 09:44:03 - mmengine - INFO - Epoch(train) [125][1520/2119] lr: 4.0000e-03 eta: 5:10:45 time: 0.3810 data_time: 0.0204 memory: 5826 grad_norm: 4.7966 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1691 loss: 2.1691 2022/10/08 09:44:10 - mmengine - INFO - Epoch(train) [125][1540/2119] lr: 4.0000e-03 eta: 5:10:38 time: 0.3515 data_time: 0.0196 memory: 5826 grad_norm: 4.6670 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9872 loss: 1.9872 2022/10/08 09:44:16 - mmengine - INFO - Epoch(train) [125][1560/2119] lr: 4.0000e-03 eta: 5:10:31 time: 0.3075 data_time: 0.0260 memory: 5826 grad_norm: 4.7156 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9823 loss: 1.9823 2022/10/08 09:44:24 - mmengine - INFO - Epoch(train) [125][1580/2119] lr: 4.0000e-03 eta: 5:10:24 time: 0.3744 data_time: 0.0210 memory: 5826 grad_norm: 4.6184 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9986 loss: 1.9986 2022/10/08 09:44:32 - mmengine - INFO - Epoch(train) [125][1600/2119] lr: 4.0000e-03 eta: 5:10:17 time: 0.3895 data_time: 0.0213 memory: 5826 grad_norm: 4.6418 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0088 loss: 2.0088 2022/10/08 09:44:38 - mmengine - INFO - Epoch(train) [125][1620/2119] lr: 4.0000e-03 eta: 5:10:10 time: 0.3388 data_time: 0.0246 memory: 5826 grad_norm: 4.6713 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0943 loss: 2.0943 2022/10/08 09:44:45 - mmengine - INFO - Epoch(train) [125][1640/2119] lr: 4.0000e-03 eta: 5:10:03 time: 0.3551 data_time: 0.0212 memory: 5826 grad_norm: 4.7345 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0611 loss: 2.0611 2022/10/08 09:44:52 - mmengine - INFO - Epoch(train) [125][1660/2119] lr: 4.0000e-03 eta: 5:09:56 time: 0.3242 data_time: 0.0229 memory: 5826 grad_norm: 4.5912 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8992 loss: 1.8992 2022/10/08 09:44:59 - mmengine - INFO - Epoch(train) [125][1680/2119] lr: 4.0000e-03 eta: 5:09:49 time: 0.3507 data_time: 0.0226 memory: 5826 grad_norm: 4.7843 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.7292 loss: 1.7292 2022/10/08 09:45:06 - mmengine - INFO - Epoch(train) [125][1700/2119] lr: 4.0000e-03 eta: 5:09:42 time: 0.3313 data_time: 0.0213 memory: 5826 grad_norm: 4.7371 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 2.0366 loss: 2.0366 2022/10/08 09:45:13 - mmengine - INFO - Epoch(train) [125][1720/2119] lr: 4.0000e-03 eta: 5:09:35 time: 0.3694 data_time: 0.0222 memory: 5826 grad_norm: 4.6623 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.1443 loss: 2.1443 2022/10/08 09:45:20 - mmengine - INFO - Epoch(train) [125][1740/2119] lr: 4.0000e-03 eta: 5:09:28 time: 0.3285 data_time: 0.0197 memory: 5826 grad_norm: 4.6138 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8373 loss: 1.8373 2022/10/08 09:45:26 - mmengine - INFO - Epoch(train) [125][1760/2119] lr: 4.0000e-03 eta: 5:09:21 time: 0.3432 data_time: 0.0204 memory: 5826 grad_norm: 4.6435 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8864 loss: 1.8864 2022/10/08 09:45:33 - mmengine - INFO - Epoch(train) [125][1780/2119] lr: 4.0000e-03 eta: 5:09:14 time: 0.3455 data_time: 0.0183 memory: 5826 grad_norm: 4.7138 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0290 loss: 2.0290 2022/10/08 09:45:41 - mmengine - INFO - Epoch(train) [125][1800/2119] lr: 4.0000e-03 eta: 5:09:07 time: 0.3878 data_time: 0.0181 memory: 5826 grad_norm: 4.6234 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0149 loss: 2.0149 2022/10/08 09:45:48 - mmengine - INFO - Epoch(train) [125][1820/2119] lr: 4.0000e-03 eta: 5:09:00 time: 0.3361 data_time: 0.0208 memory: 5826 grad_norm: 4.6147 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9567 loss: 1.9567 2022/10/08 09:45:56 - mmengine - INFO - Epoch(train) [125][1840/2119] lr: 4.0000e-03 eta: 5:08:53 time: 0.3825 data_time: 0.0183 memory: 5826 grad_norm: 4.6536 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.1834 loss: 2.1834 2022/10/08 09:46:03 - mmengine - INFO - Epoch(train) [125][1860/2119] lr: 4.0000e-03 eta: 5:08:46 time: 0.3532 data_time: 0.0213 memory: 5826 grad_norm: 4.6384 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8692 loss: 1.8692 2022/10/08 09:46:09 - mmengine - INFO - Epoch(train) [125][1880/2119] lr: 4.0000e-03 eta: 5:08:40 time: 0.3413 data_time: 0.0266 memory: 5826 grad_norm: 4.7064 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9542 loss: 1.9542 2022/10/08 09:46:16 - mmengine - INFO - Epoch(train) [125][1900/2119] lr: 4.0000e-03 eta: 5:08:32 time: 0.3058 data_time: 0.0228 memory: 5826 grad_norm: 4.7600 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1282 loss: 2.1282 2022/10/08 09:46:23 - mmengine - INFO - Epoch(train) [125][1920/2119] lr: 4.0000e-03 eta: 5:08:26 time: 0.3791 data_time: 0.0196 memory: 5826 grad_norm: 4.6783 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0244 loss: 2.0244 2022/10/08 09:46:30 - mmengine - INFO - Epoch(train) [125][1940/2119] lr: 4.0000e-03 eta: 5:08:18 time: 0.3204 data_time: 0.0211 memory: 5826 grad_norm: 4.7039 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8794 loss: 1.8794 2022/10/08 09:46:37 - mmengine - INFO - Epoch(train) [125][1960/2119] lr: 4.0000e-03 eta: 5:08:12 time: 0.3745 data_time: 0.0215 memory: 5826 grad_norm: 4.6123 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9753 loss: 1.9753 2022/10/08 09:46:44 - mmengine - INFO - Epoch(train) [125][1980/2119] lr: 4.0000e-03 eta: 5:08:05 time: 0.3401 data_time: 0.0202 memory: 5826 grad_norm: 4.7348 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0471 loss: 2.0471 2022/10/08 09:46:52 - mmengine - INFO - Epoch(train) [125][2000/2119] lr: 4.0000e-03 eta: 5:07:58 time: 0.3947 data_time: 0.0230 memory: 5826 grad_norm: 4.6516 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9985 loss: 1.9985 2022/10/08 09:46:58 - mmengine - INFO - Epoch(train) [125][2020/2119] lr: 4.0000e-03 eta: 5:07:51 time: 0.3343 data_time: 0.0252 memory: 5826 grad_norm: 4.6356 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.6796 loss: 1.6796 2022/10/08 09:47:06 - mmengine - INFO - Epoch(train) [125][2040/2119] lr: 4.0000e-03 eta: 5:07:44 time: 0.3642 data_time: 0.0301 memory: 5826 grad_norm: 4.7186 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.9309 loss: 1.9309 2022/10/08 09:47:13 - mmengine - INFO - Epoch(train) [125][2060/2119] lr: 4.0000e-03 eta: 5:07:37 time: 0.3468 data_time: 0.0218 memory: 5826 grad_norm: 4.6181 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.0652 loss: 2.0652 2022/10/08 09:47:19 - mmengine - INFO - Epoch(train) [125][2080/2119] lr: 4.0000e-03 eta: 5:07:30 time: 0.2928 data_time: 0.0206 memory: 5826 grad_norm: 4.6674 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8885 loss: 1.8885 2022/10/08 09:47:25 - mmengine - INFO - Epoch(train) [125][2100/2119] lr: 4.0000e-03 eta: 5:07:23 time: 0.3350 data_time: 0.0221 memory: 5826 grad_norm: 4.6712 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.1021 loss: 2.1021 2022/10/08 09:47:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 09:47:32 - mmengine - INFO - Epoch(train) [125][2119/2119] lr: 4.0000e-03 eta: 5:07:23 time: 0.3255 data_time: 0.0209 memory: 5826 grad_norm: 4.7933 top1_acc: 0.5000 top5_acc: 0.8000 loss_cls: 1.6878 loss: 1.6878 2022/10/08 09:47:40 - mmengine - INFO - Epoch(val) [125][20/137] eta: 0:00:49 time: 0.4273 data_time: 0.3594 memory: 1241 2022/10/08 09:47:46 - mmengine - INFO - Epoch(val) [125][40/137] eta: 0:00:28 time: 0.2891 data_time: 0.2231 memory: 1241 2022/10/08 09:47:53 - mmengine - INFO - Epoch(val) [125][60/137] eta: 0:00:28 time: 0.3689 data_time: 0.3011 memory: 1241 2022/10/08 09:47:59 - mmengine - INFO - Epoch(val) [125][80/137] eta: 0:00:16 time: 0.2897 data_time: 0.2243 memory: 1241 2022/10/08 09:48:07 - mmengine - INFO - Epoch(val) [125][100/137] eta: 0:00:14 time: 0.3820 data_time: 0.3162 memory: 1241 2022/10/08 09:48:12 - mmengine - INFO - Epoch(val) [125][120/137] eta: 0:00:04 time: 0.2635 data_time: 0.1975 memory: 1241 2022/10/08 09:48:24 - mmengine - INFO - Epoch(val) [125][137/137] acc/top1: 0.5434 acc/top5: 0.7678 acc/mean1: 0.5433 2022/10/08 09:48:24 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb/best_acc/top1_epoch_120.pth is removed 2022/10/08 09:48:32 - mmengine - INFO - The best checkpoint with 0.5434 acc/top1 at 125 epoch is saved to best_acc/top1_epoch_125.pth. 2022/10/08 09:48:40 - mmengine - INFO - Epoch(train) [126][20/2119] lr: 4.0000e-03 eta: 5:07:08 time: 0.4087 data_time: 0.2004 memory: 5826 grad_norm: 4.7342 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8340 loss: 1.8340 2022/10/08 09:48:46 - mmengine - INFO - Epoch(train) [126][40/2119] lr: 4.0000e-03 eta: 5:07:01 time: 0.3043 data_time: 0.0755 memory: 5826 grad_norm: 4.6702 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.8292 loss: 1.8292 2022/10/08 09:48:54 - mmengine - INFO - Epoch(train) [126][60/2119] lr: 4.0000e-03 eta: 5:06:54 time: 0.3954 data_time: 0.1620 memory: 5826 grad_norm: 4.7380 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9508 loss: 1.9508 2022/10/08 09:49:00 - mmengine - INFO - Epoch(train) [126][80/2119] lr: 4.0000e-03 eta: 5:06:47 time: 0.3033 data_time: 0.0654 memory: 5826 grad_norm: 4.7072 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8707 loss: 1.8707 2022/10/08 09:49:07 - mmengine - INFO - Epoch(train) [126][100/2119] lr: 4.0000e-03 eta: 5:06:40 time: 0.3651 data_time: 0.1345 memory: 5826 grad_norm: 4.7149 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9345 loss: 1.9345 2022/10/08 09:49:14 - mmengine - INFO - Epoch(train) [126][120/2119] lr: 4.0000e-03 eta: 5:06:33 time: 0.3277 data_time: 0.0550 memory: 5826 grad_norm: 4.7187 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.0107 loss: 2.0107 2022/10/08 09:49:15 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 09:49:21 - mmengine - INFO - Epoch(train) [126][140/2119] lr: 4.0000e-03 eta: 5:06:26 time: 0.3747 data_time: 0.0221 memory: 5826 grad_norm: 4.7565 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9784 loss: 1.9784 2022/10/08 09:49:29 - mmengine - INFO - Epoch(train) [126][160/2119] lr: 4.0000e-03 eta: 5:06:20 time: 0.3885 data_time: 0.0166 memory: 5826 grad_norm: 4.7208 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9443 loss: 1.9443 2022/10/08 09:49:35 - mmengine - INFO - Epoch(train) [126][180/2119] lr: 4.0000e-03 eta: 5:06:12 time: 0.3054 data_time: 0.0194 memory: 5826 grad_norm: 4.6755 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9957 loss: 1.9957 2022/10/08 09:49:43 - mmengine - INFO - Epoch(train) [126][200/2119] lr: 4.0000e-03 eta: 5:06:06 time: 0.4027 data_time: 0.0191 memory: 5826 grad_norm: 4.7036 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8600 loss: 1.8600 2022/10/08 09:49:50 - mmengine - INFO - Epoch(train) [126][220/2119] lr: 4.0000e-03 eta: 5:05:59 time: 0.3197 data_time: 0.0252 memory: 5826 grad_norm: 4.7064 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0884 loss: 2.0884 2022/10/08 09:49:57 - mmengine - INFO - Epoch(train) [126][240/2119] lr: 4.0000e-03 eta: 5:05:52 time: 0.3347 data_time: 0.0209 memory: 5826 grad_norm: 4.8096 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0174 loss: 2.0174 2022/10/08 09:50:04 - mmengine - INFO - Epoch(train) [126][260/2119] lr: 4.0000e-03 eta: 5:05:45 time: 0.3467 data_time: 0.0221 memory: 5826 grad_norm: 4.7967 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1632 loss: 2.1632 2022/10/08 09:50:12 - mmengine - INFO - Epoch(train) [126][280/2119] lr: 4.0000e-03 eta: 5:05:38 time: 0.4292 data_time: 0.0205 memory: 5826 grad_norm: 4.7083 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0464 loss: 2.0464 2022/10/08 09:50:18 - mmengine - INFO - Epoch(train) [126][300/2119] lr: 4.0000e-03 eta: 5:05:31 time: 0.3094 data_time: 0.0258 memory: 5826 grad_norm: 4.7349 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1362 loss: 2.1362 2022/10/08 09:50:27 - mmengine - INFO - Epoch(train) [126][320/2119] lr: 4.0000e-03 eta: 5:05:24 time: 0.4132 data_time: 0.0159 memory: 5826 grad_norm: 4.6961 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0684 loss: 2.0684 2022/10/08 09:50:34 - mmengine - INFO - Epoch(train) [126][340/2119] lr: 4.0000e-03 eta: 5:05:17 time: 0.3587 data_time: 0.0212 memory: 5826 grad_norm: 4.6344 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9002 loss: 1.9002 2022/10/08 09:50:41 - mmengine - INFO - Epoch(train) [126][360/2119] lr: 4.0000e-03 eta: 5:05:10 time: 0.3857 data_time: 0.0212 memory: 5826 grad_norm: 4.6916 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9833 loss: 1.9833 2022/10/08 09:50:48 - mmengine - INFO - Epoch(train) [126][380/2119] lr: 4.0000e-03 eta: 5:05:03 time: 0.3091 data_time: 0.0200 memory: 5826 grad_norm: 4.5911 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1024 loss: 2.1024 2022/10/08 09:50:55 - mmengine - INFO - Epoch(train) [126][400/2119] lr: 4.0000e-03 eta: 5:04:56 time: 0.3630 data_time: 0.0189 memory: 5826 grad_norm: 4.7275 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0806 loss: 2.0806 2022/10/08 09:51:02 - mmengine - INFO - Epoch(train) [126][420/2119] lr: 4.0000e-03 eta: 5:04:49 time: 0.3580 data_time: 0.0199 memory: 5826 grad_norm: 4.7103 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0183 loss: 2.0183 2022/10/08 09:51:10 - mmengine - INFO - Epoch(train) [126][440/2119] lr: 4.0000e-03 eta: 5:04:43 time: 0.3702 data_time: 0.0155 memory: 5826 grad_norm: 4.6625 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.9832 loss: 1.9832 2022/10/08 09:51:16 - mmengine - INFO - Epoch(train) [126][460/2119] lr: 4.0000e-03 eta: 5:04:36 time: 0.3459 data_time: 0.0229 memory: 5826 grad_norm: 4.7160 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9314 loss: 1.9314 2022/10/08 09:51:23 - mmengine - INFO - Epoch(train) [126][480/2119] lr: 4.0000e-03 eta: 5:04:29 time: 0.3411 data_time: 0.0189 memory: 5826 grad_norm: 4.6784 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9317 loss: 1.9317 2022/10/08 09:51:30 - mmengine - INFO - Epoch(train) [126][500/2119] lr: 4.0000e-03 eta: 5:04:22 time: 0.3329 data_time: 0.0239 memory: 5826 grad_norm: 4.7213 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9931 loss: 1.9931 2022/10/08 09:51:38 - mmengine - INFO - Epoch(train) [126][520/2119] lr: 4.0000e-03 eta: 5:04:15 time: 0.3850 data_time: 0.0188 memory: 5826 grad_norm: 4.7291 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0827 loss: 2.0827 2022/10/08 09:51:44 - mmengine - INFO - Epoch(train) [126][540/2119] lr: 4.0000e-03 eta: 5:04:08 time: 0.3165 data_time: 0.0240 memory: 5826 grad_norm: 4.6287 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.7565 loss: 1.7565 2022/10/08 09:51:53 - mmengine - INFO - Epoch(train) [126][560/2119] lr: 4.0000e-03 eta: 5:04:01 time: 0.4392 data_time: 0.0210 memory: 5826 grad_norm: 4.6160 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.8148 loss: 1.8148 2022/10/08 09:51:58 - mmengine - INFO - Epoch(train) [126][580/2119] lr: 4.0000e-03 eta: 5:03:54 time: 0.2711 data_time: 0.0182 memory: 5826 grad_norm: 4.7021 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.8149 loss: 1.8149 2022/10/08 09:52:06 - mmengine - INFO - Epoch(train) [126][600/2119] lr: 4.0000e-03 eta: 5:03:47 time: 0.3864 data_time: 0.0237 memory: 5826 grad_norm: 4.6648 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9991 loss: 1.9991 2022/10/08 09:52:13 - mmengine - INFO - Epoch(train) [126][620/2119] lr: 4.0000e-03 eta: 5:03:40 time: 0.3568 data_time: 0.0185 memory: 5826 grad_norm: 4.6901 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0011 loss: 2.0011 2022/10/08 09:52:20 - mmengine - INFO - Epoch(train) [126][640/2119] lr: 4.0000e-03 eta: 5:03:33 time: 0.3210 data_time: 0.0236 memory: 5826 grad_norm: 4.7353 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0381 loss: 2.0381 2022/10/08 09:52:26 - mmengine - INFO - Epoch(train) [126][660/2119] lr: 4.0000e-03 eta: 5:03:26 time: 0.3385 data_time: 0.0300 memory: 5826 grad_norm: 4.6577 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0270 loss: 2.0270 2022/10/08 09:52:33 - mmengine - INFO - Epoch(train) [126][680/2119] lr: 4.0000e-03 eta: 5:03:19 time: 0.3425 data_time: 0.0250 memory: 5826 grad_norm: 4.7511 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 2.0494 loss: 2.0494 2022/10/08 09:52:40 - mmengine - INFO - Epoch(train) [126][700/2119] lr: 4.0000e-03 eta: 5:03:12 time: 0.3532 data_time: 0.0214 memory: 5826 grad_norm: 4.6938 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.2021 loss: 2.2021 2022/10/08 09:52:47 - mmengine - INFO - Epoch(train) [126][720/2119] lr: 4.0000e-03 eta: 5:03:05 time: 0.3466 data_time: 0.0214 memory: 5826 grad_norm: 4.7607 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.8798 loss: 1.8798 2022/10/08 09:52:55 - mmengine - INFO - Epoch(train) [126][740/2119] lr: 4.0000e-03 eta: 5:02:58 time: 0.3737 data_time: 0.0273 memory: 5826 grad_norm: 4.6708 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9113 loss: 1.9113 2022/10/08 09:53:02 - mmengine - INFO - Epoch(train) [126][760/2119] lr: 4.0000e-03 eta: 5:02:51 time: 0.3455 data_time: 0.0283 memory: 5826 grad_norm: 4.7371 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0747 loss: 2.0747 2022/10/08 09:53:09 - mmengine - INFO - Epoch(train) [126][780/2119] lr: 4.0000e-03 eta: 5:02:44 time: 0.3581 data_time: 0.0237 memory: 5826 grad_norm: 4.7083 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0198 loss: 2.0198 2022/10/08 09:53:16 - mmengine - INFO - Epoch(train) [126][800/2119] lr: 4.0000e-03 eta: 5:02:37 time: 0.3526 data_time: 0.0202 memory: 5826 grad_norm: 4.6619 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8406 loss: 1.8406 2022/10/08 09:53:24 - mmengine - INFO - Epoch(train) [126][820/2119] lr: 4.0000e-03 eta: 5:02:31 time: 0.4111 data_time: 0.0179 memory: 5826 grad_norm: 4.7317 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0523 loss: 2.0523 2022/10/08 09:53:31 - mmengine - INFO - Epoch(train) [126][840/2119] lr: 4.0000e-03 eta: 5:02:24 time: 0.3365 data_time: 0.0252 memory: 5826 grad_norm: 4.6938 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9633 loss: 1.9633 2022/10/08 09:53:39 - mmengine - INFO - Epoch(train) [126][860/2119] lr: 4.0000e-03 eta: 5:02:17 time: 0.4175 data_time: 0.0199 memory: 5826 grad_norm: 4.6250 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.0162 loss: 2.0162 2022/10/08 09:53:46 - mmengine - INFO - Epoch(train) [126][880/2119] lr: 4.0000e-03 eta: 5:02:10 time: 0.3407 data_time: 0.0292 memory: 5826 grad_norm: 4.6342 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0175 loss: 2.0175 2022/10/08 09:53:53 - mmengine - INFO - Epoch(train) [126][900/2119] lr: 4.0000e-03 eta: 5:02:03 time: 0.3700 data_time: 0.0265 memory: 5826 grad_norm: 4.8079 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0674 loss: 2.0674 2022/10/08 09:54:00 - mmengine - INFO - Epoch(train) [126][920/2119] lr: 4.0000e-03 eta: 5:01:56 time: 0.3279 data_time: 0.0221 memory: 5826 grad_norm: 4.8539 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9762 loss: 1.9762 2022/10/08 09:54:07 - mmengine - INFO - Epoch(train) [126][940/2119] lr: 4.0000e-03 eta: 5:01:49 time: 0.3739 data_time: 0.0194 memory: 5826 grad_norm: 4.7538 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.7795 loss: 1.7795 2022/10/08 09:54:14 - mmengine - INFO - Epoch(train) [126][960/2119] lr: 4.0000e-03 eta: 5:01:42 time: 0.3227 data_time: 0.0237 memory: 5826 grad_norm: 4.6144 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9453 loss: 1.9453 2022/10/08 09:54:22 - mmengine - INFO - Epoch(train) [126][980/2119] lr: 4.0000e-03 eta: 5:01:35 time: 0.3968 data_time: 0.0213 memory: 5826 grad_norm: 4.6641 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9363 loss: 1.9363 2022/10/08 09:54:29 - mmengine - INFO - Epoch(train) [126][1000/2119] lr: 4.0000e-03 eta: 5:01:28 time: 0.3436 data_time: 0.0238 memory: 5826 grad_norm: 4.7588 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9533 loss: 1.9533 2022/10/08 09:54:35 - mmengine - INFO - Epoch(train) [126][1020/2119] lr: 4.0000e-03 eta: 5:01:21 time: 0.3092 data_time: 0.0245 memory: 5826 grad_norm: 4.7964 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0132 loss: 2.0132 2022/10/08 09:54:42 - mmengine - INFO - Epoch(train) [126][1040/2119] lr: 4.0000e-03 eta: 5:01:14 time: 0.3553 data_time: 0.0292 memory: 5826 grad_norm: 4.8256 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9707 loss: 1.9707 2022/10/08 09:54:49 - mmengine - INFO - Epoch(train) [126][1060/2119] lr: 4.0000e-03 eta: 5:01:08 time: 0.3659 data_time: 0.0228 memory: 5826 grad_norm: 4.7724 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0252 loss: 2.0252 2022/10/08 09:54:57 - mmengine - INFO - Epoch(train) [126][1080/2119] lr: 4.0000e-03 eta: 5:01:01 time: 0.3611 data_time: 0.0230 memory: 5826 grad_norm: 4.7743 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7972 loss: 1.7972 2022/10/08 09:55:04 - mmengine - INFO - Epoch(train) [126][1100/2119] lr: 4.0000e-03 eta: 5:00:54 time: 0.3643 data_time: 0.0240 memory: 5826 grad_norm: 4.7106 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0685 loss: 2.0685 2022/10/08 09:55:12 - mmengine - INFO - Epoch(train) [126][1120/2119] lr: 4.0000e-03 eta: 5:00:47 time: 0.4144 data_time: 0.0239 memory: 5826 grad_norm: 4.7081 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6891 loss: 1.6891 2022/10/08 09:55:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 09:55:18 - mmengine - INFO - Epoch(train) [126][1140/2119] lr: 4.0000e-03 eta: 5:00:40 time: 0.3032 data_time: 0.0237 memory: 5826 grad_norm: 4.6814 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9121 loss: 1.9121 2022/10/08 09:55:26 - mmengine - INFO - Epoch(train) [126][1160/2119] lr: 4.0000e-03 eta: 5:00:33 time: 0.3724 data_time: 0.0221 memory: 5826 grad_norm: 4.6768 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8421 loss: 1.8421 2022/10/08 09:55:33 - mmengine - INFO - Epoch(train) [126][1180/2119] lr: 4.0000e-03 eta: 5:00:26 time: 0.3643 data_time: 0.0255 memory: 5826 grad_norm: 4.6404 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9449 loss: 1.9449 2022/10/08 09:55:39 - mmengine - INFO - Epoch(train) [126][1200/2119] lr: 4.0000e-03 eta: 5:00:19 time: 0.3232 data_time: 0.0178 memory: 5826 grad_norm: 4.7190 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9919 loss: 1.9919 2022/10/08 09:55:47 - mmengine - INFO - Epoch(train) [126][1220/2119] lr: 4.0000e-03 eta: 5:00:12 time: 0.3547 data_time: 0.0233 memory: 5826 grad_norm: 4.7742 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1455 loss: 2.1455 2022/10/08 09:55:55 - mmengine - INFO - Epoch(train) [126][1240/2119] lr: 4.0000e-03 eta: 5:00:05 time: 0.4045 data_time: 0.0258 memory: 5826 grad_norm: 4.7027 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9612 loss: 1.9612 2022/10/08 09:56:01 - mmengine - INFO - Epoch(train) [126][1260/2119] lr: 4.0000e-03 eta: 4:59:58 time: 0.3305 data_time: 0.0237 memory: 5826 grad_norm: 4.6755 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.0250 loss: 2.0250 2022/10/08 09:56:09 - mmengine - INFO - Epoch(train) [126][1280/2119] lr: 4.0000e-03 eta: 4:59:52 time: 0.3762 data_time: 0.0209 memory: 5826 grad_norm: 4.6835 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8912 loss: 1.8912 2022/10/08 09:56:16 - mmengine - INFO - Epoch(train) [126][1300/2119] lr: 4.0000e-03 eta: 4:59:45 time: 0.3522 data_time: 0.0230 memory: 5826 grad_norm: 4.6559 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7971 loss: 1.7971 2022/10/08 09:56:23 - mmengine - INFO - Epoch(train) [126][1320/2119] lr: 4.0000e-03 eta: 4:59:38 time: 0.3697 data_time: 0.0242 memory: 5826 grad_norm: 4.7140 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7812 loss: 1.7812 2022/10/08 09:56:30 - mmengine - INFO - Epoch(train) [126][1340/2119] lr: 4.0000e-03 eta: 4:59:31 time: 0.3231 data_time: 0.0246 memory: 5826 grad_norm: 4.7288 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8304 loss: 1.8304 2022/10/08 09:56:37 - mmengine - INFO - Epoch(train) [126][1360/2119] lr: 4.0000e-03 eta: 4:59:24 time: 0.3614 data_time: 0.0175 memory: 5826 grad_norm: 4.6937 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8848 loss: 1.8848 2022/10/08 09:56:44 - mmengine - INFO - Epoch(train) [126][1380/2119] lr: 4.0000e-03 eta: 4:59:17 time: 0.3467 data_time: 0.0185 memory: 5826 grad_norm: 4.6256 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.9993 loss: 1.9993 2022/10/08 09:56:51 - mmengine - INFO - Epoch(train) [126][1400/2119] lr: 4.0000e-03 eta: 4:59:10 time: 0.3507 data_time: 0.0213 memory: 5826 grad_norm: 4.6098 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1464 loss: 2.1464 2022/10/08 09:56:58 - mmengine - INFO - Epoch(train) [126][1420/2119] lr: 4.0000e-03 eta: 4:59:03 time: 0.3586 data_time: 0.0224 memory: 5826 grad_norm: 4.6914 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9091 loss: 1.9091 2022/10/08 09:57:06 - mmengine - INFO - Epoch(train) [126][1440/2119] lr: 4.0000e-03 eta: 4:58:56 time: 0.3828 data_time: 0.0238 memory: 5826 grad_norm: 4.5147 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6227 loss: 1.6227 2022/10/08 09:57:12 - mmengine - INFO - Epoch(train) [126][1460/2119] lr: 4.0000e-03 eta: 4:58:49 time: 0.3348 data_time: 0.0220 memory: 5826 grad_norm: 4.6953 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7397 loss: 1.7397 2022/10/08 09:57:20 - mmengine - INFO - Epoch(train) [126][1480/2119] lr: 4.0000e-03 eta: 4:58:42 time: 0.3511 data_time: 0.0215 memory: 5826 grad_norm: 4.6859 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8915 loss: 1.8915 2022/10/08 09:57:26 - mmengine - INFO - Epoch(train) [126][1500/2119] lr: 4.0000e-03 eta: 4:58:35 time: 0.3005 data_time: 0.0232 memory: 5826 grad_norm: 4.6337 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9965 loss: 1.9965 2022/10/08 09:57:33 - mmengine - INFO - Epoch(train) [126][1520/2119] lr: 4.0000e-03 eta: 4:58:28 time: 0.3701 data_time: 0.0271 memory: 5826 grad_norm: 4.7701 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9821 loss: 1.9821 2022/10/08 09:57:40 - mmengine - INFO - Epoch(train) [126][1540/2119] lr: 4.0000e-03 eta: 4:58:21 time: 0.3317 data_time: 0.0206 memory: 5826 grad_norm: 4.7847 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 2.0324 loss: 2.0324 2022/10/08 09:57:47 - mmengine - INFO - Epoch(train) [126][1560/2119] lr: 4.0000e-03 eta: 4:58:14 time: 0.3668 data_time: 0.0257 memory: 5826 grad_norm: 4.7028 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8818 loss: 1.8818 2022/10/08 09:57:54 - mmengine - INFO - Epoch(train) [126][1580/2119] lr: 4.0000e-03 eta: 4:58:07 time: 0.3478 data_time: 0.0218 memory: 5826 grad_norm: 4.7591 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.8294 loss: 1.8294 2022/10/08 09:58:02 - mmengine - INFO - Epoch(train) [126][1600/2119] lr: 4.0000e-03 eta: 4:58:01 time: 0.4172 data_time: 0.0245 memory: 5826 grad_norm: 4.7312 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9482 loss: 1.9482 2022/10/08 09:58:09 - mmengine - INFO - Epoch(train) [126][1620/2119] lr: 4.0000e-03 eta: 4:57:53 time: 0.3192 data_time: 0.0156 memory: 5826 grad_norm: 4.7198 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1114 loss: 2.1114 2022/10/08 09:58:16 - mmengine - INFO - Epoch(train) [126][1640/2119] lr: 4.0000e-03 eta: 4:57:47 time: 0.3509 data_time: 0.0231 memory: 5826 grad_norm: 4.6707 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9127 loss: 1.9127 2022/10/08 09:58:22 - mmengine - INFO - Epoch(train) [126][1660/2119] lr: 4.0000e-03 eta: 4:57:40 time: 0.3374 data_time: 0.0228 memory: 5826 grad_norm: 4.6846 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9908 loss: 1.9908 2022/10/08 09:58:29 - mmengine - INFO - Epoch(train) [126][1680/2119] lr: 4.0000e-03 eta: 4:57:33 time: 0.3369 data_time: 0.0193 memory: 5826 grad_norm: 4.7424 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9548 loss: 1.9548 2022/10/08 09:58:36 - mmengine - INFO - Epoch(train) [126][1700/2119] lr: 4.0000e-03 eta: 4:57:26 time: 0.3625 data_time: 0.0248 memory: 5826 grad_norm: 4.7373 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1629 loss: 2.1629 2022/10/08 09:58:43 - mmengine - INFO - Epoch(train) [126][1720/2119] lr: 4.0000e-03 eta: 4:57:19 time: 0.3432 data_time: 0.0168 memory: 5826 grad_norm: 4.7862 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9257 loss: 1.9257 2022/10/08 09:58:50 - mmengine - INFO - Epoch(train) [126][1740/2119] lr: 4.0000e-03 eta: 4:57:12 time: 0.3439 data_time: 0.0264 memory: 5826 grad_norm: 4.7921 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0536 loss: 2.0536 2022/10/08 09:58:58 - mmengine - INFO - Epoch(train) [126][1760/2119] lr: 4.0000e-03 eta: 4:57:05 time: 0.3686 data_time: 0.0190 memory: 5826 grad_norm: 4.7204 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.9855 loss: 1.9855 2022/10/08 09:59:04 - mmengine - INFO - Epoch(train) [126][1780/2119] lr: 4.0000e-03 eta: 4:56:58 time: 0.3449 data_time: 0.0229 memory: 5826 grad_norm: 4.7226 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.0599 loss: 2.0599 2022/10/08 09:59:11 - mmengine - INFO - Epoch(train) [126][1800/2119] lr: 4.0000e-03 eta: 4:56:51 time: 0.3342 data_time: 0.0270 memory: 5826 grad_norm: 4.8386 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0481 loss: 2.0481 2022/10/08 09:59:19 - mmengine - INFO - Epoch(train) [126][1820/2119] lr: 4.0000e-03 eta: 4:56:44 time: 0.3714 data_time: 0.0208 memory: 5826 grad_norm: 4.8098 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9073 loss: 1.9073 2022/10/08 09:59:26 - mmengine - INFO - Epoch(train) [126][1840/2119] lr: 4.0000e-03 eta: 4:56:37 time: 0.3769 data_time: 0.0267 memory: 5826 grad_norm: 4.7528 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0988 loss: 2.0988 2022/10/08 09:59:32 - mmengine - INFO - Epoch(train) [126][1860/2119] lr: 4.0000e-03 eta: 4:56:30 time: 0.3084 data_time: 0.0229 memory: 5826 grad_norm: 4.7879 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.0763 loss: 2.0763 2022/10/08 09:59:39 - mmengine - INFO - Epoch(train) [126][1880/2119] lr: 4.0000e-03 eta: 4:56:23 time: 0.3486 data_time: 0.0285 memory: 5826 grad_norm: 4.7734 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9043 loss: 1.9043 2022/10/08 09:59:46 - mmengine - INFO - Epoch(train) [126][1900/2119] lr: 4.0000e-03 eta: 4:56:16 time: 0.3445 data_time: 0.0248 memory: 5826 grad_norm: 4.7075 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0929 loss: 2.0929 2022/10/08 09:59:53 - mmengine - INFO - Epoch(train) [126][1920/2119] lr: 4.0000e-03 eta: 4:56:09 time: 0.3318 data_time: 0.0266 memory: 5826 grad_norm: 4.6108 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9438 loss: 1.9438 2022/10/08 10:00:01 - mmengine - INFO - Epoch(train) [126][1940/2119] lr: 4.0000e-03 eta: 4:56:02 time: 0.3859 data_time: 0.0237 memory: 5826 grad_norm: 4.6894 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9117 loss: 1.9117 2022/10/08 10:00:08 - mmengine - INFO - Epoch(train) [126][1960/2119] lr: 4.0000e-03 eta: 4:55:55 time: 0.3756 data_time: 0.0218 memory: 5826 grad_norm: 4.6546 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0487 loss: 2.0487 2022/10/08 10:00:15 - mmengine - INFO - Epoch(train) [126][1980/2119] lr: 4.0000e-03 eta: 4:55:48 time: 0.3341 data_time: 0.0251 memory: 5826 grad_norm: 4.6546 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9055 loss: 1.9055 2022/10/08 10:00:22 - mmengine - INFO - Epoch(train) [126][2000/2119] lr: 4.0000e-03 eta: 4:55:41 time: 0.3682 data_time: 0.0226 memory: 5826 grad_norm: 4.7648 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8460 loss: 1.8460 2022/10/08 10:00:29 - mmengine - INFO - Epoch(train) [126][2020/2119] lr: 4.0000e-03 eta: 4:55:34 time: 0.3380 data_time: 0.0204 memory: 5826 grad_norm: 4.7733 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0424 loss: 2.0424 2022/10/08 10:00:36 - mmengine - INFO - Epoch(train) [126][2040/2119] lr: 4.0000e-03 eta: 4:55:27 time: 0.3535 data_time: 0.0325 memory: 5826 grad_norm: 4.8271 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2206 loss: 2.2206 2022/10/08 10:00:44 - mmengine - INFO - Epoch(train) [126][2060/2119] lr: 4.0000e-03 eta: 4:55:21 time: 0.3859 data_time: 0.0185 memory: 5826 grad_norm: 4.7504 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9099 loss: 1.9099 2022/10/08 10:00:51 - mmengine - INFO - Epoch(train) [126][2080/2119] lr: 4.0000e-03 eta: 4:55:14 time: 0.3563 data_time: 0.0261 memory: 5826 grad_norm: 4.8153 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9036 loss: 1.9036 2022/10/08 10:00:58 - mmengine - INFO - Epoch(train) [126][2100/2119] lr: 4.0000e-03 eta: 4:55:07 time: 0.3315 data_time: 0.0239 memory: 5826 grad_norm: 4.8655 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9055 loss: 1.9055 2022/10/08 10:01:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 10:01:03 - mmengine - INFO - Epoch(train) [126][2119/2119] lr: 4.0000e-03 eta: 4:55:07 time: 0.3085 data_time: 0.0212 memory: 5826 grad_norm: 4.8218 top1_acc: 0.7000 top5_acc: 0.9000 loss_cls: 1.8344 loss: 1.8344 2022/10/08 10:01:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 10:01:13 - mmengine - INFO - Epoch(train) [127][20/2119] lr: 4.0000e-03 eta: 4:54:52 time: 0.4795 data_time: 0.1414 memory: 5826 grad_norm: 4.6435 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0067 loss: 2.0067 2022/10/08 10:01:20 - mmengine - INFO - Epoch(train) [127][40/2119] lr: 4.0000e-03 eta: 4:54:45 time: 0.3374 data_time: 0.0200 memory: 5826 grad_norm: 4.7389 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9760 loss: 1.9760 2022/10/08 10:01:28 - mmengine - INFO - Epoch(train) [127][60/2119] lr: 4.0000e-03 eta: 4:54:39 time: 0.3920 data_time: 0.0213 memory: 5826 grad_norm: 4.7646 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9998 loss: 1.9998 2022/10/08 10:01:34 - mmengine - INFO - Epoch(train) [127][80/2119] lr: 4.0000e-03 eta: 4:54:31 time: 0.3140 data_time: 0.0191 memory: 5826 grad_norm: 4.6686 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 1.9982 loss: 1.9982 2022/10/08 10:01:41 - mmengine - INFO - Epoch(train) [127][100/2119] lr: 4.0000e-03 eta: 4:54:25 time: 0.3666 data_time: 0.0227 memory: 5826 grad_norm: 4.7192 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.7896 loss: 1.7896 2022/10/08 10:01:48 - mmengine - INFO - Epoch(train) [127][120/2119] lr: 4.0000e-03 eta: 4:54:18 time: 0.3494 data_time: 0.0194 memory: 5826 grad_norm: 4.7370 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9805 loss: 1.9805 2022/10/08 10:01:55 - mmengine - INFO - Epoch(train) [127][140/2119] lr: 4.0000e-03 eta: 4:54:11 time: 0.3430 data_time: 0.0218 memory: 5826 grad_norm: 4.8056 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0889 loss: 2.0889 2022/10/08 10:02:03 - mmengine - INFO - Epoch(train) [127][160/2119] lr: 4.0000e-03 eta: 4:54:04 time: 0.3857 data_time: 0.0218 memory: 5826 grad_norm: 4.6760 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8431 loss: 1.8431 2022/10/08 10:02:10 - mmengine - INFO - Epoch(train) [127][180/2119] lr: 4.0000e-03 eta: 4:53:57 time: 0.3367 data_time: 0.0200 memory: 5826 grad_norm: 4.7483 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9338 loss: 1.9338 2022/10/08 10:02:16 - mmengine - INFO - Epoch(train) [127][200/2119] lr: 4.0000e-03 eta: 4:53:50 time: 0.3363 data_time: 0.0259 memory: 5826 grad_norm: 4.7179 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0323 loss: 2.0323 2022/10/08 10:02:24 - mmengine - INFO - Epoch(train) [127][220/2119] lr: 4.0000e-03 eta: 4:53:43 time: 0.3845 data_time: 0.0249 memory: 5826 grad_norm: 4.7097 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9347 loss: 1.9347 2022/10/08 10:02:31 - mmengine - INFO - Epoch(train) [127][240/2119] lr: 4.0000e-03 eta: 4:53:36 time: 0.3542 data_time: 0.0239 memory: 5826 grad_norm: 4.7710 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8136 loss: 1.8136 2022/10/08 10:02:39 - mmengine - INFO - Epoch(train) [127][260/2119] lr: 4.0000e-03 eta: 4:53:29 time: 0.3690 data_time: 0.0199 memory: 5826 grad_norm: 4.7407 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9624 loss: 1.9624 2022/10/08 10:02:46 - mmengine - INFO - Epoch(train) [127][280/2119] lr: 4.0000e-03 eta: 4:53:22 time: 0.3910 data_time: 0.0228 memory: 5826 grad_norm: 4.8446 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9662 loss: 1.9662 2022/10/08 10:02:53 - mmengine - INFO - Epoch(train) [127][300/2119] lr: 4.0000e-03 eta: 4:53:15 time: 0.3448 data_time: 0.0248 memory: 5826 grad_norm: 4.7133 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.9060 loss: 1.9060 2022/10/08 10:03:01 - mmengine - INFO - Epoch(train) [127][320/2119] lr: 4.0000e-03 eta: 4:53:09 time: 0.3589 data_time: 0.0182 memory: 5826 grad_norm: 4.7296 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8819 loss: 1.8819 2022/10/08 10:03:08 - mmengine - INFO - Epoch(train) [127][340/2119] lr: 4.0000e-03 eta: 4:53:02 time: 0.3556 data_time: 0.0206 memory: 5826 grad_norm: 4.7138 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9577 loss: 1.9577 2022/10/08 10:03:15 - mmengine - INFO - Epoch(train) [127][360/2119] lr: 4.0000e-03 eta: 4:52:55 time: 0.3821 data_time: 0.0190 memory: 5826 grad_norm: 4.7268 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8343 loss: 1.8343 2022/10/08 10:03:22 - mmengine - INFO - Epoch(train) [127][380/2119] lr: 4.0000e-03 eta: 4:52:48 time: 0.3236 data_time: 0.0223 memory: 5826 grad_norm: 4.7129 top1_acc: 0.5625 top5_acc: 1.0000 loss_cls: 1.8876 loss: 1.8876 2022/10/08 10:03:29 - mmengine - INFO - Epoch(train) [127][400/2119] lr: 4.0000e-03 eta: 4:52:41 time: 0.3698 data_time: 0.0168 memory: 5826 grad_norm: 4.7708 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8305 loss: 1.8305 2022/10/08 10:03:35 - mmengine - INFO - Epoch(train) [127][420/2119] lr: 4.0000e-03 eta: 4:52:34 time: 0.2912 data_time: 0.0234 memory: 5826 grad_norm: 4.8507 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7767 loss: 1.7767 2022/10/08 10:03:42 - mmengine - INFO - Epoch(train) [127][440/2119] lr: 4.0000e-03 eta: 4:52:27 time: 0.3717 data_time: 0.0228 memory: 5826 grad_norm: 4.7189 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9749 loss: 1.9749 2022/10/08 10:03:50 - mmengine - INFO - Epoch(train) [127][460/2119] lr: 4.0000e-03 eta: 4:52:20 time: 0.3541 data_time: 0.0225 memory: 5826 grad_norm: 4.7604 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8425 loss: 1.8425 2022/10/08 10:03:58 - mmengine - INFO - Epoch(train) [127][480/2119] lr: 4.0000e-03 eta: 4:52:13 time: 0.4018 data_time: 0.0233 memory: 5826 grad_norm: 4.7061 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0751 loss: 2.0751 2022/10/08 10:04:04 - mmengine - INFO - Epoch(train) [127][500/2119] lr: 4.0000e-03 eta: 4:52:06 time: 0.3225 data_time: 0.0239 memory: 5826 grad_norm: 4.7201 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1366 loss: 2.1366 2022/10/08 10:04:11 - mmengine - INFO - Epoch(train) [127][520/2119] lr: 4.0000e-03 eta: 4:51:59 time: 0.3644 data_time: 0.0246 memory: 5826 grad_norm: 4.7154 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9389 loss: 1.9389 2022/10/08 10:04:20 - mmengine - INFO - Epoch(train) [127][540/2119] lr: 4.0000e-03 eta: 4:51:53 time: 0.4510 data_time: 0.0222 memory: 5826 grad_norm: 4.7494 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0241 loss: 2.0241 2022/10/08 10:04:27 - mmengine - INFO - Epoch(train) [127][560/2119] lr: 4.0000e-03 eta: 4:51:46 time: 0.3437 data_time: 0.0230 memory: 5826 grad_norm: 4.6706 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.9099 loss: 1.9099 2022/10/08 10:04:34 - mmengine - INFO - Epoch(train) [127][580/2119] lr: 4.0000e-03 eta: 4:51:39 time: 0.3486 data_time: 0.0228 memory: 5826 grad_norm: 4.6668 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9133 loss: 1.9133 2022/10/08 10:04:41 - mmengine - INFO - Epoch(train) [127][600/2119] lr: 4.0000e-03 eta: 4:51:32 time: 0.3488 data_time: 0.0240 memory: 5826 grad_norm: 4.7840 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9124 loss: 1.9124 2022/10/08 10:04:47 - mmengine - INFO - Epoch(train) [127][620/2119] lr: 4.0000e-03 eta: 4:51:25 time: 0.3114 data_time: 0.0280 memory: 5826 grad_norm: 4.7879 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0223 loss: 2.0223 2022/10/08 10:04:55 - mmengine - INFO - Epoch(train) [127][640/2119] lr: 4.0000e-03 eta: 4:51:18 time: 0.3677 data_time: 0.0201 memory: 5826 grad_norm: 4.8373 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1002 loss: 2.1002 2022/10/08 10:05:03 - mmengine - INFO - Epoch(train) [127][660/2119] lr: 4.0000e-03 eta: 4:51:11 time: 0.4152 data_time: 0.0220 memory: 5826 grad_norm: 4.7461 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.2285 loss: 2.2285 2022/10/08 10:05:09 - mmengine - INFO - Epoch(train) [127][680/2119] lr: 4.0000e-03 eta: 4:51:04 time: 0.3135 data_time: 0.0174 memory: 5826 grad_norm: 4.7025 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8148 loss: 1.8148 2022/10/08 10:05:17 - mmengine - INFO - Epoch(train) [127][700/2119] lr: 4.0000e-03 eta: 4:50:57 time: 0.3735 data_time: 0.0220 memory: 5826 grad_norm: 4.8335 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0970 loss: 2.0970 2022/10/08 10:05:23 - mmengine - INFO - Epoch(train) [127][720/2119] lr: 4.0000e-03 eta: 4:50:50 time: 0.3239 data_time: 0.0202 memory: 5826 grad_norm: 4.7274 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.9641 loss: 1.9641 2022/10/08 10:05:32 - mmengine - INFO - Epoch(train) [127][740/2119] lr: 4.0000e-03 eta: 4:50:43 time: 0.4179 data_time: 0.0174 memory: 5826 grad_norm: 4.7142 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9135 loss: 1.9135 2022/10/08 10:05:38 - mmengine - INFO - Epoch(train) [127][760/2119] lr: 4.0000e-03 eta: 4:50:36 time: 0.3342 data_time: 0.0309 memory: 5826 grad_norm: 4.6955 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0153 loss: 2.0153 2022/10/08 10:05:45 - mmengine - INFO - Epoch(train) [127][780/2119] lr: 4.0000e-03 eta: 4:50:29 time: 0.3333 data_time: 0.0182 memory: 5826 grad_norm: 4.7630 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0293 loss: 2.0293 2022/10/08 10:05:52 - mmengine - INFO - Epoch(train) [127][800/2119] lr: 4.0000e-03 eta: 4:50:22 time: 0.3226 data_time: 0.0255 memory: 5826 grad_norm: 4.7830 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9881 loss: 1.9881 2022/10/08 10:05:58 - mmengine - INFO - Epoch(train) [127][820/2119] lr: 4.0000e-03 eta: 4:50:15 time: 0.3269 data_time: 0.0232 memory: 5826 grad_norm: 4.7631 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.8880 loss: 1.8880 2022/10/08 10:06:05 - mmengine - INFO - Epoch(train) [127][840/2119] lr: 4.0000e-03 eta: 4:50:08 time: 0.3367 data_time: 0.0199 memory: 5826 grad_norm: 4.7847 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9081 loss: 1.9081 2022/10/08 10:06:12 - mmengine - INFO - Epoch(train) [127][860/2119] lr: 4.0000e-03 eta: 4:50:01 time: 0.3611 data_time: 0.0228 memory: 5826 grad_norm: 4.6143 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7226 loss: 1.7226 2022/10/08 10:06:19 - mmengine - INFO - Epoch(train) [127][880/2119] lr: 4.0000e-03 eta: 4:49:54 time: 0.3318 data_time: 0.0280 memory: 5826 grad_norm: 4.7041 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1530 loss: 2.1530 2022/10/08 10:06:26 - mmengine - INFO - Epoch(train) [127][900/2119] lr: 4.0000e-03 eta: 4:49:47 time: 0.3711 data_time: 0.0752 memory: 5826 grad_norm: 4.8352 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0946 loss: 2.0946 2022/10/08 10:06:34 - mmengine - INFO - Epoch(train) [127][920/2119] lr: 4.0000e-03 eta: 4:49:40 time: 0.3673 data_time: 0.0231 memory: 5826 grad_norm: 4.8429 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 2.0368 loss: 2.0368 2022/10/08 10:06:41 - mmengine - INFO - Epoch(train) [127][940/2119] lr: 4.0000e-03 eta: 4:49:33 time: 0.3609 data_time: 0.0197 memory: 5826 grad_norm: 4.6586 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0274 loss: 2.0274 2022/10/08 10:06:48 - mmengine - INFO - Epoch(train) [127][960/2119] lr: 4.0000e-03 eta: 4:49:27 time: 0.3597 data_time: 0.0174 memory: 5826 grad_norm: 4.7260 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7954 loss: 1.7954 2022/10/08 10:06:55 - mmengine - INFO - Epoch(train) [127][980/2119] lr: 4.0000e-03 eta: 4:49:20 time: 0.3515 data_time: 0.0227 memory: 5826 grad_norm: 4.7624 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0506 loss: 2.0506 2022/10/08 10:07:02 - mmengine - INFO - Epoch(train) [127][1000/2119] lr: 4.0000e-03 eta: 4:49:13 time: 0.3388 data_time: 0.0456 memory: 5826 grad_norm: 4.7963 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0923 loss: 2.0923 2022/10/08 10:07:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 10:07:08 - mmengine - INFO - Epoch(train) [127][1020/2119] lr: 4.0000e-03 eta: 4:49:06 time: 0.3162 data_time: 0.0481 memory: 5826 grad_norm: 4.8318 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8818 loss: 1.8818 2022/10/08 10:07:15 - mmengine - INFO - Epoch(train) [127][1040/2119] lr: 4.0000e-03 eta: 4:48:59 time: 0.3487 data_time: 0.0360 memory: 5826 grad_norm: 4.7148 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8436 loss: 1.8436 2022/10/08 10:07:23 - mmengine - INFO - Epoch(train) [127][1060/2119] lr: 4.0000e-03 eta: 4:48:52 time: 0.3713 data_time: 0.1021 memory: 5826 grad_norm: 4.8037 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1156 loss: 2.1156 2022/10/08 10:07:29 - mmengine - INFO - Epoch(train) [127][1080/2119] lr: 4.0000e-03 eta: 4:48:45 time: 0.3272 data_time: 0.0666 memory: 5826 grad_norm: 4.7031 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1782 loss: 2.1782 2022/10/08 10:07:36 - mmengine - INFO - Epoch(train) [127][1100/2119] lr: 4.0000e-03 eta: 4:48:38 time: 0.3463 data_time: 0.0466 memory: 5826 grad_norm: 4.8490 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0422 loss: 2.0422 2022/10/08 10:07:43 - mmengine - INFO - Epoch(train) [127][1120/2119] lr: 4.0000e-03 eta: 4:48:31 time: 0.3677 data_time: 0.0278 memory: 5826 grad_norm: 4.7712 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9560 loss: 1.9560 2022/10/08 10:07:50 - mmengine - INFO - Epoch(train) [127][1140/2119] lr: 4.0000e-03 eta: 4:48:24 time: 0.3364 data_time: 0.0431 memory: 5826 grad_norm: 4.6997 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9804 loss: 1.9804 2022/10/08 10:07:58 - mmengine - INFO - Epoch(train) [127][1160/2119] lr: 4.0000e-03 eta: 4:48:17 time: 0.3885 data_time: 0.0227 memory: 5826 grad_norm: 4.7427 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0428 loss: 2.0428 2022/10/08 10:08:05 - mmengine - INFO - Epoch(train) [127][1180/2119] lr: 4.0000e-03 eta: 4:48:10 time: 0.3690 data_time: 0.0252 memory: 5826 grad_norm: 4.8671 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9372 loss: 1.9372 2022/10/08 10:08:14 - mmengine - INFO - Epoch(train) [127][1200/2119] lr: 4.0000e-03 eta: 4:48:03 time: 0.4276 data_time: 0.0161 memory: 5826 grad_norm: 4.7420 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9778 loss: 1.9778 2022/10/08 10:08:20 - mmengine - INFO - Epoch(train) [127][1220/2119] lr: 4.0000e-03 eta: 4:47:56 time: 0.2850 data_time: 0.0226 memory: 5826 grad_norm: 4.7187 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0100 loss: 2.0100 2022/10/08 10:08:27 - mmengine - INFO - Epoch(train) [127][1240/2119] lr: 4.0000e-03 eta: 4:47:49 time: 0.3848 data_time: 0.0205 memory: 5826 grad_norm: 4.7222 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1147 loss: 2.1147 2022/10/08 10:08:34 - mmengine - INFO - Epoch(train) [127][1260/2119] lr: 4.0000e-03 eta: 4:47:42 time: 0.3482 data_time: 0.0222 memory: 5826 grad_norm: 4.7696 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.9878 loss: 1.9878 2022/10/08 10:08:41 - mmengine - INFO - Epoch(train) [127][1280/2119] lr: 4.0000e-03 eta: 4:47:35 time: 0.3215 data_time: 0.0230 memory: 5826 grad_norm: 4.8136 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8908 loss: 1.8908 2022/10/08 10:08:48 - mmengine - INFO - Epoch(train) [127][1300/2119] lr: 4.0000e-03 eta: 4:47:29 time: 0.3647 data_time: 0.0215 memory: 5826 grad_norm: 4.7313 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0910 loss: 2.0910 2022/10/08 10:08:55 - mmengine - INFO - Epoch(train) [127][1320/2119] lr: 4.0000e-03 eta: 4:47:21 time: 0.3282 data_time: 0.0304 memory: 5826 grad_norm: 4.7392 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8501 loss: 1.8501 2022/10/08 10:09:01 - mmengine - INFO - Epoch(train) [127][1340/2119] lr: 4.0000e-03 eta: 4:47:14 time: 0.3201 data_time: 0.0226 memory: 5826 grad_norm: 4.7709 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.6629 loss: 1.6629 2022/10/08 10:09:08 - mmengine - INFO - Epoch(train) [127][1360/2119] lr: 4.0000e-03 eta: 4:47:07 time: 0.3622 data_time: 0.0258 memory: 5826 grad_norm: 4.7469 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9543 loss: 1.9543 2022/10/08 10:09:16 - mmengine - INFO - Epoch(train) [127][1380/2119] lr: 4.0000e-03 eta: 4:47:01 time: 0.3853 data_time: 0.0238 memory: 5826 grad_norm: 4.9102 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.7868 loss: 1.7868 2022/10/08 10:09:23 - mmengine - INFO - Epoch(train) [127][1400/2119] lr: 4.0000e-03 eta: 4:46:54 time: 0.3577 data_time: 0.0298 memory: 5826 grad_norm: 4.8212 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8305 loss: 1.8305 2022/10/08 10:09:29 - mmengine - INFO - Epoch(train) [127][1420/2119] lr: 4.0000e-03 eta: 4:46:47 time: 0.2965 data_time: 0.0214 memory: 5826 grad_norm: 4.8216 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9639 loss: 1.9639 2022/10/08 10:09:36 - mmengine - INFO - Epoch(train) [127][1440/2119] lr: 4.0000e-03 eta: 4:46:40 time: 0.3614 data_time: 0.0199 memory: 5826 grad_norm: 4.7903 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9589 loss: 1.9589 2022/10/08 10:09:44 - mmengine - INFO - Epoch(train) [127][1460/2119] lr: 4.0000e-03 eta: 4:46:33 time: 0.3965 data_time: 0.0241 memory: 5826 grad_norm: 4.7797 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.1253 loss: 2.1253 2022/10/08 10:09:51 - mmengine - INFO - Epoch(train) [127][1480/2119] lr: 4.0000e-03 eta: 4:46:26 time: 0.3232 data_time: 0.0226 memory: 5826 grad_norm: 4.7730 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0576 loss: 2.0576 2022/10/08 10:09:58 - mmengine - INFO - Epoch(train) [127][1500/2119] lr: 4.0000e-03 eta: 4:46:19 time: 0.3573 data_time: 0.0259 memory: 5826 grad_norm: 4.8107 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9643 loss: 1.9643 2022/10/08 10:10:05 - mmengine - INFO - Epoch(train) [127][1520/2119] lr: 4.0000e-03 eta: 4:46:12 time: 0.3568 data_time: 0.0262 memory: 5826 grad_norm: 4.6801 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0581 loss: 2.0581 2022/10/08 10:10:12 - mmengine - INFO - Epoch(train) [127][1540/2119] lr: 4.0000e-03 eta: 4:46:05 time: 0.3674 data_time: 0.0222 memory: 5826 grad_norm: 4.7718 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0627 loss: 2.0627 2022/10/08 10:10:19 - mmengine - INFO - Epoch(train) [127][1560/2119] lr: 4.0000e-03 eta: 4:45:58 time: 0.3502 data_time: 0.0302 memory: 5826 grad_norm: 4.8359 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0588 loss: 2.0588 2022/10/08 10:10:26 - mmengine - INFO - Epoch(train) [127][1580/2119] lr: 4.0000e-03 eta: 4:45:51 time: 0.3313 data_time: 0.0247 memory: 5826 grad_norm: 4.8042 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0318 loss: 2.0318 2022/10/08 10:10:32 - mmengine - INFO - Epoch(train) [127][1600/2119] lr: 4.0000e-03 eta: 4:45:44 time: 0.2995 data_time: 0.0268 memory: 5826 grad_norm: 4.7447 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0605 loss: 2.0605 2022/10/08 10:10:39 - mmengine - INFO - Epoch(train) [127][1620/2119] lr: 4.0000e-03 eta: 4:45:37 time: 0.3568 data_time: 0.0244 memory: 5826 grad_norm: 4.7154 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0699 loss: 2.0699 2022/10/08 10:10:46 - mmengine - INFO - Epoch(train) [127][1640/2119] lr: 4.0000e-03 eta: 4:45:30 time: 0.3599 data_time: 0.0154 memory: 5826 grad_norm: 4.7061 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.9994 loss: 1.9994 2022/10/08 10:10:53 - mmengine - INFO - Epoch(train) [127][1660/2119] lr: 4.0000e-03 eta: 4:45:23 time: 0.3578 data_time: 0.0218 memory: 5826 grad_norm: 4.7870 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0780 loss: 2.0780 2022/10/08 10:11:01 - mmengine - INFO - Epoch(train) [127][1680/2119] lr: 4.0000e-03 eta: 4:45:16 time: 0.3689 data_time: 0.0310 memory: 5826 grad_norm: 4.7335 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9551 loss: 1.9551 2022/10/08 10:11:08 - mmengine - INFO - Epoch(train) [127][1700/2119] lr: 4.0000e-03 eta: 4:45:09 time: 0.3411 data_time: 0.0197 memory: 5826 grad_norm: 4.8591 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8472 loss: 1.8472 2022/10/08 10:11:15 - mmengine - INFO - Epoch(train) [127][1720/2119] lr: 4.0000e-03 eta: 4:45:02 time: 0.3608 data_time: 0.0178 memory: 5826 grad_norm: 4.8119 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8896 loss: 1.8896 2022/10/08 10:11:21 - mmengine - INFO - Epoch(train) [127][1740/2119] lr: 4.0000e-03 eta: 4:44:55 time: 0.3181 data_time: 0.0258 memory: 5826 grad_norm: 4.8178 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0096 loss: 2.0096 2022/10/08 10:11:29 - mmengine - INFO - Epoch(train) [127][1760/2119] lr: 4.0000e-03 eta: 4:44:49 time: 0.3884 data_time: 0.0240 memory: 5826 grad_norm: 4.7762 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9819 loss: 1.9819 2022/10/08 10:11:35 - mmengine - INFO - Epoch(train) [127][1780/2119] lr: 4.0000e-03 eta: 4:44:41 time: 0.3179 data_time: 0.0209 memory: 5826 grad_norm: 4.7957 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9635 loss: 1.9635 2022/10/08 10:11:42 - mmengine - INFO - Epoch(train) [127][1800/2119] lr: 4.0000e-03 eta: 4:44:34 time: 0.3417 data_time: 0.0228 memory: 5826 grad_norm: 4.7463 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0012 loss: 2.0012 2022/10/08 10:11:49 - mmengine - INFO - Epoch(train) [127][1820/2119] lr: 4.0000e-03 eta: 4:44:27 time: 0.3378 data_time: 0.0253 memory: 5826 grad_norm: 4.7808 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0183 loss: 2.0183 2022/10/08 10:11:56 - mmengine - INFO - Epoch(train) [127][1840/2119] lr: 4.0000e-03 eta: 4:44:20 time: 0.3326 data_time: 0.0176 memory: 5826 grad_norm: 4.6931 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8489 loss: 1.8489 2022/10/08 10:12:04 - mmengine - INFO - Epoch(train) [127][1860/2119] lr: 4.0000e-03 eta: 4:44:14 time: 0.4006 data_time: 0.0234 memory: 5826 grad_norm: 4.7600 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8795 loss: 1.8795 2022/10/08 10:12:10 - mmengine - INFO - Epoch(train) [127][1880/2119] lr: 4.0000e-03 eta: 4:44:07 time: 0.3112 data_time: 0.0250 memory: 5826 grad_norm: 4.6702 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7372 loss: 1.7372 2022/10/08 10:12:17 - mmengine - INFO - Epoch(train) [127][1900/2119] lr: 4.0000e-03 eta: 4:44:00 time: 0.3393 data_time: 0.0209 memory: 5826 grad_norm: 4.7768 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0338 loss: 2.0338 2022/10/08 10:12:23 - mmengine - INFO - Epoch(train) [127][1920/2119] lr: 4.0000e-03 eta: 4:43:53 time: 0.3369 data_time: 0.0220 memory: 5826 grad_norm: 4.7677 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9350 loss: 1.9350 2022/10/08 10:12:31 - mmengine - INFO - Epoch(train) [127][1940/2119] lr: 4.0000e-03 eta: 4:43:46 time: 0.3625 data_time: 0.0236 memory: 5826 grad_norm: 4.6563 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0615 loss: 2.0615 2022/10/08 10:12:38 - mmengine - INFO - Epoch(train) [127][1960/2119] lr: 4.0000e-03 eta: 4:43:39 time: 0.3806 data_time: 0.0228 memory: 5826 grad_norm: 4.7170 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8715 loss: 1.8715 2022/10/08 10:12:46 - mmengine - INFO - Epoch(train) [127][1980/2119] lr: 4.0000e-03 eta: 4:43:32 time: 0.3763 data_time: 0.0178 memory: 5826 grad_norm: 4.8376 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0102 loss: 2.0102 2022/10/08 10:12:53 - mmengine - INFO - Epoch(train) [127][2000/2119] lr: 4.0000e-03 eta: 4:43:25 time: 0.3724 data_time: 0.0245 memory: 5826 grad_norm: 4.7801 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0600 loss: 2.0600 2022/10/08 10:12:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 10:13:01 - mmengine - INFO - Epoch(train) [127][2020/2119] lr: 4.0000e-03 eta: 4:43:18 time: 0.3665 data_time: 0.0229 memory: 5826 grad_norm: 4.7081 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0600 loss: 2.0600 2022/10/08 10:13:07 - mmengine - INFO - Epoch(train) [127][2040/2119] lr: 4.0000e-03 eta: 4:43:11 time: 0.3216 data_time: 0.0250 memory: 5826 grad_norm: 4.7737 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.0084 loss: 2.0084 2022/10/08 10:13:15 - mmengine - INFO - Epoch(train) [127][2060/2119] lr: 4.0000e-03 eta: 4:43:04 time: 0.4142 data_time: 0.0222 memory: 5826 grad_norm: 4.7921 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.0256 loss: 2.0256 2022/10/08 10:13:22 - mmengine - INFO - Epoch(train) [127][2080/2119] lr: 4.0000e-03 eta: 4:42:57 time: 0.3216 data_time: 0.0260 memory: 5826 grad_norm: 4.7454 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0946 loss: 2.0946 2022/10/08 10:13:29 - mmengine - INFO - Epoch(train) [127][2100/2119] lr: 4.0000e-03 eta: 4:42:50 time: 0.3536 data_time: 0.0184 memory: 5826 grad_norm: 4.8290 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7408 loss: 1.7408 2022/10/08 10:13:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 10:13:35 - mmengine - INFO - Epoch(train) [127][2119/2119] lr: 4.0000e-03 eta: 4:42:50 time: 0.3714 data_time: 0.0217 memory: 5826 grad_norm: 4.7950 top1_acc: 0.5000 top5_acc: 0.8000 loss_cls: 1.8317 loss: 1.8317 2022/10/08 10:13:46 - mmengine - INFO - Epoch(train) [128][20/2119] lr: 4.0000e-03 eta: 4:42:36 time: 0.5086 data_time: 0.1654 memory: 5826 grad_norm: 4.6960 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8309 loss: 1.8309 2022/10/08 10:13:53 - mmengine - INFO - Epoch(train) [128][40/2119] lr: 4.0000e-03 eta: 4:42:29 time: 0.3413 data_time: 0.0261 memory: 5826 grad_norm: 4.7325 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.2078 loss: 2.2078 2022/10/08 10:14:00 - mmengine - INFO - Epoch(train) [128][60/2119] lr: 4.0000e-03 eta: 4:42:22 time: 0.3773 data_time: 0.0248 memory: 5826 grad_norm: 4.8278 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.0920 loss: 2.0920 2022/10/08 10:14:07 - mmengine - INFO - Epoch(train) [128][80/2119] lr: 4.0000e-03 eta: 4:42:15 time: 0.3260 data_time: 0.0216 memory: 5826 grad_norm: 4.7453 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8952 loss: 1.8952 2022/10/08 10:14:15 - mmengine - INFO - Epoch(train) [128][100/2119] lr: 4.0000e-03 eta: 4:42:09 time: 0.3967 data_time: 0.0216 memory: 5826 grad_norm: 4.7079 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8910 loss: 1.8910 2022/10/08 10:14:21 - mmengine - INFO - Epoch(train) [128][120/2119] lr: 4.0000e-03 eta: 4:42:01 time: 0.3057 data_time: 0.0313 memory: 5826 grad_norm: 4.8073 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0738 loss: 2.0738 2022/10/08 10:14:28 - mmengine - INFO - Epoch(train) [128][140/2119] lr: 4.0000e-03 eta: 4:41:55 time: 0.3480 data_time: 0.0246 memory: 5826 grad_norm: 4.8312 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9982 loss: 1.9982 2022/10/08 10:14:35 - mmengine - INFO - Epoch(train) [128][160/2119] lr: 4.0000e-03 eta: 4:41:48 time: 0.3488 data_time: 0.0242 memory: 5826 grad_norm: 4.8457 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9765 loss: 1.9765 2022/10/08 10:14:42 - mmengine - INFO - Epoch(train) [128][180/2119] lr: 4.0000e-03 eta: 4:41:41 time: 0.3443 data_time: 0.0248 memory: 5826 grad_norm: 4.8405 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9954 loss: 1.9954 2022/10/08 10:14:49 - mmengine - INFO - Epoch(train) [128][200/2119] lr: 4.0000e-03 eta: 4:41:34 time: 0.3759 data_time: 0.0264 memory: 5826 grad_norm: 4.7717 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0194 loss: 2.0194 2022/10/08 10:14:56 - mmengine - INFO - Epoch(train) [128][220/2119] lr: 4.0000e-03 eta: 4:41:27 time: 0.3645 data_time: 0.0222 memory: 5826 grad_norm: 4.7697 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9667 loss: 1.9667 2022/10/08 10:15:03 - mmengine - INFO - Epoch(train) [128][240/2119] lr: 4.0000e-03 eta: 4:41:20 time: 0.3476 data_time: 0.0210 memory: 5826 grad_norm: 4.7885 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0750 loss: 2.0750 2022/10/08 10:15:11 - mmengine - INFO - Epoch(train) [128][260/2119] lr: 4.0000e-03 eta: 4:41:13 time: 0.3633 data_time: 0.0205 memory: 5826 grad_norm: 4.7894 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0552 loss: 2.0552 2022/10/08 10:15:19 - mmengine - INFO - Epoch(train) [128][280/2119] lr: 4.0000e-03 eta: 4:41:06 time: 0.3989 data_time: 0.0228 memory: 5826 grad_norm: 4.7387 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9276 loss: 1.9276 2022/10/08 10:15:25 - mmengine - INFO - Epoch(train) [128][300/2119] lr: 4.0000e-03 eta: 4:40:59 time: 0.3391 data_time: 0.0200 memory: 5826 grad_norm: 4.8062 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.3019 loss: 2.3019 2022/10/08 10:15:32 - mmengine - INFO - Epoch(train) [128][320/2119] lr: 4.0000e-03 eta: 4:40:52 time: 0.3515 data_time: 0.0231 memory: 5826 grad_norm: 4.7700 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.8842 loss: 1.8842 2022/10/08 10:15:39 - mmengine - INFO - Epoch(train) [128][340/2119] lr: 4.0000e-03 eta: 4:40:45 time: 0.3300 data_time: 0.0238 memory: 5826 grad_norm: 4.6387 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.9961 loss: 1.9961 2022/10/08 10:15:46 - mmengine - INFO - Epoch(train) [128][360/2119] lr: 4.0000e-03 eta: 4:40:38 time: 0.3613 data_time: 0.0272 memory: 5826 grad_norm: 4.8061 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8740 loss: 1.8740 2022/10/08 10:15:54 - mmengine - INFO - Epoch(train) [128][380/2119] lr: 4.0000e-03 eta: 4:40:31 time: 0.3773 data_time: 0.0208 memory: 5826 grad_norm: 4.8174 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9828 loss: 1.9828 2022/10/08 10:16:00 - mmengine - INFO - Epoch(train) [128][400/2119] lr: 4.0000e-03 eta: 4:40:24 time: 0.3166 data_time: 0.0220 memory: 5826 grad_norm: 4.8321 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 2.1430 loss: 2.1430 2022/10/08 10:16:07 - mmengine - INFO - Epoch(train) [128][420/2119] lr: 4.0000e-03 eta: 4:40:17 time: 0.3390 data_time: 0.0206 memory: 5826 grad_norm: 4.8190 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8516 loss: 1.8516 2022/10/08 10:16:15 - mmengine - INFO - Epoch(train) [128][440/2119] lr: 4.0000e-03 eta: 4:40:11 time: 0.4186 data_time: 0.0235 memory: 5826 grad_norm: 4.8428 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8647 loss: 1.8647 2022/10/08 10:16:21 - mmengine - INFO - Epoch(train) [128][460/2119] lr: 4.0000e-03 eta: 4:40:03 time: 0.2773 data_time: 0.0209 memory: 5826 grad_norm: 4.8130 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7564 loss: 1.7564 2022/10/08 10:16:29 - mmengine - INFO - Epoch(train) [128][480/2119] lr: 4.0000e-03 eta: 4:39:57 time: 0.3920 data_time: 0.0202 memory: 5826 grad_norm: 4.8491 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 1.7936 loss: 1.7936 2022/10/08 10:16:36 - mmengine - INFO - Epoch(train) [128][500/2119] lr: 4.0000e-03 eta: 4:39:50 time: 0.3784 data_time: 0.0196 memory: 5826 grad_norm: 4.7077 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8575 loss: 1.8575 2022/10/08 10:16:43 - mmengine - INFO - Epoch(train) [128][520/2119] lr: 4.0000e-03 eta: 4:39:43 time: 0.3294 data_time: 0.0273 memory: 5826 grad_norm: 4.7039 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7933 loss: 1.7933 2022/10/08 10:16:49 - mmengine - INFO - Epoch(train) [128][540/2119] lr: 4.0000e-03 eta: 4:39:36 time: 0.3248 data_time: 0.0187 memory: 5826 grad_norm: 4.7683 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9725 loss: 1.9725 2022/10/08 10:16:57 - mmengine - INFO - Epoch(train) [128][560/2119] lr: 4.0000e-03 eta: 4:39:29 time: 0.3611 data_time: 0.0242 memory: 5826 grad_norm: 4.8287 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9876 loss: 1.9876 2022/10/08 10:17:03 - mmengine - INFO - Epoch(train) [128][580/2119] lr: 4.0000e-03 eta: 4:39:22 time: 0.3432 data_time: 0.0207 memory: 5826 grad_norm: 4.7780 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9232 loss: 1.9232 2022/10/08 10:17:10 - mmengine - INFO - Epoch(train) [128][600/2119] lr: 4.0000e-03 eta: 4:39:15 time: 0.3446 data_time: 0.0222 memory: 5826 grad_norm: 4.8227 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.8845 loss: 1.8845 2022/10/08 10:17:17 - mmengine - INFO - Epoch(train) [128][620/2119] lr: 4.0000e-03 eta: 4:39:08 time: 0.3346 data_time: 0.0202 memory: 5826 grad_norm: 4.7026 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9272 loss: 1.9272 2022/10/08 10:17:24 - mmengine - INFO - Epoch(train) [128][640/2119] lr: 4.0000e-03 eta: 4:39:01 time: 0.3592 data_time: 0.0328 memory: 5826 grad_norm: 4.8388 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0608 loss: 2.0608 2022/10/08 10:17:31 - mmengine - INFO - Epoch(train) [128][660/2119] lr: 4.0000e-03 eta: 4:38:54 time: 0.3524 data_time: 0.0180 memory: 5826 grad_norm: 4.8621 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9427 loss: 1.9427 2022/10/08 10:17:39 - mmengine - INFO - Epoch(train) [128][680/2119] lr: 4.0000e-03 eta: 4:38:47 time: 0.3822 data_time: 0.0242 memory: 5826 grad_norm: 4.7406 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.0261 loss: 2.0261 2022/10/08 10:17:45 - mmengine - INFO - Epoch(train) [128][700/2119] lr: 4.0000e-03 eta: 4:38:40 time: 0.3193 data_time: 0.0211 memory: 5826 grad_norm: 4.7875 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8931 loss: 1.8931 2022/10/08 10:17:53 - mmengine - INFO - Epoch(train) [128][720/2119] lr: 4.0000e-03 eta: 4:38:33 time: 0.3854 data_time: 0.0217 memory: 5826 grad_norm: 4.7711 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0797 loss: 2.0797 2022/10/08 10:18:00 - mmengine - INFO - Epoch(train) [128][740/2119] lr: 4.0000e-03 eta: 4:38:26 time: 0.3316 data_time: 0.0216 memory: 5826 grad_norm: 4.8138 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.8924 loss: 1.8924 2022/10/08 10:18:07 - mmengine - INFO - Epoch(train) [128][760/2119] lr: 4.0000e-03 eta: 4:38:19 time: 0.3434 data_time: 0.0240 memory: 5826 grad_norm: 4.8868 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2001 loss: 2.2001 2022/10/08 10:18:14 - mmengine - INFO - Epoch(train) [128][780/2119] lr: 4.0000e-03 eta: 4:38:12 time: 0.3467 data_time: 0.0264 memory: 5826 grad_norm: 4.7922 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0513 loss: 2.0513 2022/10/08 10:18:21 - mmengine - INFO - Epoch(train) [128][800/2119] lr: 4.0000e-03 eta: 4:38:05 time: 0.3520 data_time: 0.0206 memory: 5826 grad_norm: 4.8628 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.2621 loss: 2.2621 2022/10/08 10:18:28 - mmengine - INFO - Epoch(train) [128][820/2119] lr: 4.0000e-03 eta: 4:37:58 time: 0.3443 data_time: 0.0187 memory: 5826 grad_norm: 4.7923 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7909 loss: 1.7909 2022/10/08 10:18:35 - mmengine - INFO - Epoch(train) [128][840/2119] lr: 4.0000e-03 eta: 4:37:52 time: 0.3931 data_time: 0.0226 memory: 5826 grad_norm: 4.7243 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0369 loss: 2.0369 2022/10/08 10:18:42 - mmengine - INFO - Epoch(train) [128][860/2119] lr: 4.0000e-03 eta: 4:37:45 time: 0.3337 data_time: 0.0220 memory: 5826 grad_norm: 4.7279 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.9053 loss: 1.9053 2022/10/08 10:18:50 - mmengine - INFO - Epoch(train) [128][880/2119] lr: 4.0000e-03 eta: 4:37:38 time: 0.3923 data_time: 0.0228 memory: 5826 grad_norm: 4.8306 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0726 loss: 2.0726 2022/10/08 10:18:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 10:18:56 - mmengine - INFO - Epoch(train) [128][900/2119] lr: 4.0000e-03 eta: 4:37:31 time: 0.3061 data_time: 0.0180 memory: 5826 grad_norm: 4.7200 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 1.8705 loss: 1.8705 2022/10/08 10:19:03 - mmengine - INFO - Epoch(train) [128][920/2119] lr: 4.0000e-03 eta: 4:37:24 time: 0.3354 data_time: 0.0225 memory: 5826 grad_norm: 4.8724 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.8768 loss: 1.8768 2022/10/08 10:19:10 - mmengine - INFO - Epoch(train) [128][940/2119] lr: 4.0000e-03 eta: 4:37:17 time: 0.3676 data_time: 0.0186 memory: 5826 grad_norm: 4.8612 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9055 loss: 1.9055 2022/10/08 10:19:17 - mmengine - INFO - Epoch(train) [128][960/2119] lr: 4.0000e-03 eta: 4:37:10 time: 0.3596 data_time: 0.0188 memory: 5826 grad_norm: 4.7473 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8947 loss: 1.8947 2022/10/08 10:19:25 - mmengine - INFO - Epoch(train) [128][980/2119] lr: 4.0000e-03 eta: 4:37:03 time: 0.4037 data_time: 0.0203 memory: 5826 grad_norm: 4.7036 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1913 loss: 2.1913 2022/10/08 10:19:31 - mmengine - INFO - Epoch(train) [128][1000/2119] lr: 4.0000e-03 eta: 4:36:56 time: 0.2901 data_time: 0.0249 memory: 5826 grad_norm: 4.8106 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0964 loss: 2.0964 2022/10/08 10:19:39 - mmengine - INFO - Epoch(train) [128][1020/2119] lr: 4.0000e-03 eta: 4:36:49 time: 0.3760 data_time: 0.0220 memory: 5826 grad_norm: 4.7441 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0391 loss: 2.0391 2022/10/08 10:19:47 - mmengine - INFO - Epoch(train) [128][1040/2119] lr: 4.0000e-03 eta: 4:36:42 time: 0.4185 data_time: 0.0201 memory: 5826 grad_norm: 4.7398 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8577 loss: 1.8577 2022/10/08 10:19:54 - mmengine - INFO - Epoch(train) [128][1060/2119] lr: 4.0000e-03 eta: 4:36:35 time: 0.3693 data_time: 0.0258 memory: 5826 grad_norm: 4.9422 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9741 loss: 1.9741 2022/10/08 10:20:01 - mmengine - INFO - Epoch(train) [128][1080/2119] lr: 4.0000e-03 eta: 4:36:28 time: 0.3459 data_time: 0.0210 memory: 5826 grad_norm: 4.7396 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8902 loss: 1.8902 2022/10/08 10:20:08 - mmengine - INFO - Epoch(train) [128][1100/2119] lr: 4.0000e-03 eta: 4:36:21 time: 0.3179 data_time: 0.0242 memory: 5826 grad_norm: 4.8911 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.8432 loss: 1.8432 2022/10/08 10:20:15 - mmengine - INFO - Epoch(train) [128][1120/2119] lr: 4.0000e-03 eta: 4:36:14 time: 0.3759 data_time: 0.0272 memory: 5826 grad_norm: 4.8635 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0313 loss: 2.0313 2022/10/08 10:20:22 - mmengine - INFO - Epoch(train) [128][1140/2119] lr: 4.0000e-03 eta: 4:36:07 time: 0.3309 data_time: 0.0202 memory: 5826 grad_norm: 4.8380 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9207 loss: 1.9207 2022/10/08 10:20:29 - mmengine - INFO - Epoch(train) [128][1160/2119] lr: 4.0000e-03 eta: 4:36:01 time: 0.3549 data_time: 0.0266 memory: 5826 grad_norm: 4.7074 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8445 loss: 1.8445 2022/10/08 10:20:36 - mmengine - INFO - Epoch(train) [128][1180/2119] lr: 4.0000e-03 eta: 4:35:53 time: 0.3272 data_time: 0.0209 memory: 5826 grad_norm: 4.7469 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9061 loss: 1.9061 2022/10/08 10:20:42 - mmengine - INFO - Epoch(train) [128][1200/2119] lr: 4.0000e-03 eta: 4:35:46 time: 0.3282 data_time: 0.0231 memory: 5826 grad_norm: 4.8446 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0451 loss: 2.0451 2022/10/08 10:20:50 - mmengine - INFO - Epoch(train) [128][1220/2119] lr: 4.0000e-03 eta: 4:35:40 time: 0.4041 data_time: 0.0228 memory: 5826 grad_norm: 4.6877 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9326 loss: 1.9326 2022/10/08 10:20:57 - mmengine - INFO - Epoch(train) [128][1240/2119] lr: 4.0000e-03 eta: 4:35:33 time: 0.3308 data_time: 0.0225 memory: 5826 grad_norm: 4.8333 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0030 loss: 2.0030 2022/10/08 10:21:05 - mmengine - INFO - Epoch(train) [128][1260/2119] lr: 4.0000e-03 eta: 4:35:26 time: 0.4202 data_time: 0.0239 memory: 5826 grad_norm: 4.7798 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1202 loss: 2.1202 2022/10/08 10:21:11 - mmengine - INFO - Epoch(train) [128][1280/2119] lr: 4.0000e-03 eta: 4:35:19 time: 0.2791 data_time: 0.0228 memory: 5826 grad_norm: 4.7527 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9698 loss: 1.9698 2022/10/08 10:21:18 - mmengine - INFO - Epoch(train) [128][1300/2119] lr: 4.0000e-03 eta: 4:35:12 time: 0.3558 data_time: 0.0225 memory: 5826 grad_norm: 4.8379 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0581 loss: 2.0581 2022/10/08 10:21:25 - mmengine - INFO - Epoch(train) [128][1320/2119] lr: 4.0000e-03 eta: 4:35:05 time: 0.3367 data_time: 0.0271 memory: 5826 grad_norm: 4.7942 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9407 loss: 1.9407 2022/10/08 10:21:32 - mmengine - INFO - Epoch(train) [128][1340/2119] lr: 4.0000e-03 eta: 4:34:58 time: 0.3565 data_time: 0.0222 memory: 5826 grad_norm: 4.8766 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8061 loss: 1.8061 2022/10/08 10:21:39 - mmengine - INFO - Epoch(train) [128][1360/2119] lr: 4.0000e-03 eta: 4:34:51 time: 0.3597 data_time: 0.0184 memory: 5826 grad_norm: 4.8166 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0129 loss: 2.0129 2022/10/08 10:21:46 - mmengine - INFO - Epoch(train) [128][1380/2119] lr: 4.0000e-03 eta: 4:34:44 time: 0.3483 data_time: 0.0260 memory: 5826 grad_norm: 4.8851 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9905 loss: 1.9905 2022/10/08 10:21:52 - mmengine - INFO - Epoch(train) [128][1400/2119] lr: 4.0000e-03 eta: 4:34:37 time: 0.3175 data_time: 0.0273 memory: 5826 grad_norm: 4.7962 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0866 loss: 2.0866 2022/10/08 10:22:01 - mmengine - INFO - Epoch(train) [128][1420/2119] lr: 4.0000e-03 eta: 4:34:30 time: 0.4111 data_time: 0.0164 memory: 5826 grad_norm: 4.8308 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9704 loss: 1.9704 2022/10/08 10:22:08 - mmengine - INFO - Epoch(train) [128][1440/2119] lr: 4.0000e-03 eta: 4:34:23 time: 0.3690 data_time: 0.0222 memory: 5826 grad_norm: 4.8114 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9606 loss: 1.9606 2022/10/08 10:22:15 - mmengine - INFO - Epoch(train) [128][1460/2119] lr: 4.0000e-03 eta: 4:34:16 time: 0.3626 data_time: 0.0242 memory: 5826 grad_norm: 4.8434 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7967 loss: 1.7967 2022/10/08 10:22:22 - mmengine - INFO - Epoch(train) [128][1480/2119] lr: 4.0000e-03 eta: 4:34:09 time: 0.3100 data_time: 0.0222 memory: 5826 grad_norm: 4.7949 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1459 loss: 2.1459 2022/10/08 10:22:29 - mmengine - INFO - Epoch(train) [128][1500/2119] lr: 4.0000e-03 eta: 4:34:02 time: 0.3785 data_time: 0.0222 memory: 5826 grad_norm: 4.8210 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9529 loss: 1.9529 2022/10/08 10:22:36 - mmengine - INFO - Epoch(train) [128][1520/2119] lr: 4.0000e-03 eta: 4:33:55 time: 0.3460 data_time: 0.0207 memory: 5826 grad_norm: 4.7930 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0941 loss: 2.0941 2022/10/08 10:22:44 - mmengine - INFO - Epoch(train) [128][1540/2119] lr: 4.0000e-03 eta: 4:33:49 time: 0.4029 data_time: 0.0207 memory: 5826 grad_norm: 4.7899 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0728 loss: 2.0728 2022/10/08 10:22:50 - mmengine - INFO - Epoch(train) [128][1560/2119] lr: 4.0000e-03 eta: 4:33:42 time: 0.3080 data_time: 0.0278 memory: 5826 grad_norm: 4.8224 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9834 loss: 1.9834 2022/10/08 10:22:58 - mmengine - INFO - Epoch(train) [128][1580/2119] lr: 4.0000e-03 eta: 4:33:35 time: 0.4032 data_time: 0.0179 memory: 5826 grad_norm: 4.8217 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9762 loss: 1.9762 2022/10/08 10:23:05 - mmengine - INFO - Epoch(train) [128][1600/2119] lr: 4.0000e-03 eta: 4:33:28 time: 0.3148 data_time: 0.0215 memory: 5826 grad_norm: 4.8138 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.0777 loss: 2.0777 2022/10/08 10:23:12 - mmengine - INFO - Epoch(train) [128][1620/2119] lr: 4.0000e-03 eta: 4:33:21 time: 0.3639 data_time: 0.0204 memory: 5826 grad_norm: 4.8866 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8558 loss: 1.8558 2022/10/08 10:23:18 - mmengine - INFO - Epoch(train) [128][1640/2119] lr: 4.0000e-03 eta: 4:33:14 time: 0.2970 data_time: 0.0298 memory: 5826 grad_norm: 4.8480 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0719 loss: 2.0719 2022/10/08 10:23:26 - mmengine - INFO - Epoch(train) [128][1660/2119] lr: 4.0000e-03 eta: 4:33:07 time: 0.3835 data_time: 0.0294 memory: 5826 grad_norm: 4.9093 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 1.9848 loss: 1.9848 2022/10/08 10:23:32 - mmengine - INFO - Epoch(train) [128][1680/2119] lr: 4.0000e-03 eta: 4:33:00 time: 0.3326 data_time: 0.0222 memory: 5826 grad_norm: 4.8473 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.7533 loss: 1.7533 2022/10/08 10:23:39 - mmengine - INFO - Epoch(train) [128][1700/2119] lr: 4.0000e-03 eta: 4:32:53 time: 0.3553 data_time: 0.0230 memory: 5826 grad_norm: 4.8272 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9234 loss: 1.9234 2022/10/08 10:23:46 - mmengine - INFO - Epoch(train) [128][1720/2119] lr: 4.0000e-03 eta: 4:32:46 time: 0.3298 data_time: 0.0245 memory: 5826 grad_norm: 4.8532 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9536 loss: 1.9536 2022/10/08 10:23:53 - mmengine - INFO - Epoch(train) [128][1740/2119] lr: 4.0000e-03 eta: 4:32:39 time: 0.3486 data_time: 0.0224 memory: 5826 grad_norm: 4.8655 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8625 loss: 1.8625 2022/10/08 10:24:00 - mmengine - INFO - Epoch(train) [128][1760/2119] lr: 4.0000e-03 eta: 4:32:32 time: 0.3310 data_time: 0.0222 memory: 5826 grad_norm: 4.7667 top1_acc: 0.5625 top5_acc: 1.0000 loss_cls: 1.9109 loss: 1.9109 2022/10/08 10:24:06 - mmengine - INFO - Epoch(train) [128][1780/2119] lr: 4.0000e-03 eta: 4:32:25 time: 0.3391 data_time: 0.0191 memory: 5826 grad_norm: 4.7027 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9885 loss: 1.9885 2022/10/08 10:24:13 - mmengine - INFO - Epoch(train) [128][1800/2119] lr: 4.0000e-03 eta: 4:32:18 time: 0.3534 data_time: 0.0258 memory: 5826 grad_norm: 4.7296 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9027 loss: 1.9027 2022/10/08 10:24:21 - mmengine - INFO - Epoch(train) [128][1820/2119] lr: 4.0000e-03 eta: 4:32:11 time: 0.3809 data_time: 0.0210 memory: 5826 grad_norm: 4.7826 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.2212 loss: 2.2212 2022/10/08 10:24:27 - mmengine - INFO - Epoch(train) [128][1840/2119] lr: 4.0000e-03 eta: 4:32:04 time: 0.3050 data_time: 0.0223 memory: 5826 grad_norm: 4.7906 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0762 loss: 2.0762 2022/10/08 10:24:35 - mmengine - INFO - Epoch(train) [128][1860/2119] lr: 4.0000e-03 eta: 4:31:57 time: 0.4114 data_time: 0.0246 memory: 5826 grad_norm: 4.8130 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0898 loss: 2.0898 2022/10/08 10:24:42 - mmengine - INFO - Epoch(train) [128][1880/2119] lr: 4.0000e-03 eta: 4:31:50 time: 0.3271 data_time: 0.0255 memory: 5826 grad_norm: 4.7350 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8325 loss: 1.8325 2022/10/08 10:24:45 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 10:24:49 - mmengine - INFO - Epoch(train) [128][1900/2119] lr: 4.0000e-03 eta: 4:31:43 time: 0.3726 data_time: 0.0181 memory: 5826 grad_norm: 4.7528 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0824 loss: 2.0824 2022/10/08 10:24:56 - mmengine - INFO - Epoch(train) [128][1920/2119] lr: 4.0000e-03 eta: 4:31:36 time: 0.3498 data_time: 0.0239 memory: 5826 grad_norm: 4.7665 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7871 loss: 1.7871 2022/10/08 10:25:05 - mmengine - INFO - Epoch(train) [128][1940/2119] lr: 4.0000e-03 eta: 4:31:30 time: 0.4174 data_time: 0.0224 memory: 5826 grad_norm: 4.8385 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1209 loss: 2.1209 2022/10/08 10:25:11 - mmengine - INFO - Epoch(train) [128][1960/2119] lr: 4.0000e-03 eta: 4:31:23 time: 0.3335 data_time: 0.0238 memory: 5826 grad_norm: 4.8242 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1595 loss: 2.1595 2022/10/08 10:25:18 - mmengine - INFO - Epoch(train) [128][1980/2119] lr: 4.0000e-03 eta: 4:31:16 time: 0.3320 data_time: 0.0214 memory: 5826 grad_norm: 4.8256 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9483 loss: 1.9483 2022/10/08 10:25:25 - mmengine - INFO - Epoch(train) [128][2000/2119] lr: 4.0000e-03 eta: 4:31:09 time: 0.3394 data_time: 0.0249 memory: 5826 grad_norm: 4.8737 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9246 loss: 1.9246 2022/10/08 10:25:32 - mmengine - INFO - Epoch(train) [128][2020/2119] lr: 4.0000e-03 eta: 4:31:02 time: 0.3599 data_time: 0.0197 memory: 5826 grad_norm: 4.8228 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8556 loss: 1.8556 2022/10/08 10:25:39 - mmengine - INFO - Epoch(train) [128][2040/2119] lr: 4.0000e-03 eta: 4:30:55 time: 0.3441 data_time: 0.0213 memory: 5826 grad_norm: 4.7756 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8995 loss: 1.8995 2022/10/08 10:25:47 - mmengine - INFO - Epoch(train) [128][2060/2119] lr: 4.0000e-03 eta: 4:30:48 time: 0.3870 data_time: 0.0238 memory: 5826 grad_norm: 4.7944 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8897 loss: 1.8897 2022/10/08 10:25:53 - mmengine - INFO - Epoch(train) [128][2080/2119] lr: 4.0000e-03 eta: 4:30:41 time: 0.3316 data_time: 0.0204 memory: 5826 grad_norm: 4.9029 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9744 loss: 1.9744 2022/10/08 10:26:02 - mmengine - INFO - Epoch(train) [128][2100/2119] lr: 4.0000e-03 eta: 4:30:34 time: 0.4471 data_time: 0.0234 memory: 5826 grad_norm: 4.8441 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0121 loss: 2.0121 2022/10/08 10:26:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 10:26:08 - mmengine - INFO - Epoch(train) [128][2119/2119] lr: 4.0000e-03 eta: 4:30:34 time: 0.2707 data_time: 0.0209 memory: 5826 grad_norm: 4.8415 top1_acc: 0.5000 top5_acc: 0.6000 loss_cls: 1.7369 loss: 1.7369 2022/10/08 10:26:08 - mmengine - INFO - Saving checkpoint at 128 epochs 2022/10/08 10:26:29 - mmengine - INFO - Epoch(train) [129][20/2119] lr: 4.0000e-03 eta: 4:30:20 time: 0.4440 data_time: 0.1935 memory: 5826 grad_norm: 4.6424 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8518 loss: 1.8518 2022/10/08 10:26:36 - mmengine - INFO - Epoch(train) [129][40/2119] lr: 4.0000e-03 eta: 4:30:13 time: 0.3373 data_time: 0.1001 memory: 5826 grad_norm: 4.8759 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6987 loss: 1.6987 2022/10/08 10:26:43 - mmengine - INFO - Epoch(train) [129][60/2119] lr: 4.0000e-03 eta: 4:30:06 time: 0.3575 data_time: 0.1260 memory: 5826 grad_norm: 4.8759 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9315 loss: 1.9315 2022/10/08 10:26:49 - mmengine - INFO - Epoch(train) [129][80/2119] lr: 4.0000e-03 eta: 4:29:59 time: 0.3166 data_time: 0.0646 memory: 5826 grad_norm: 4.8087 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8455 loss: 1.8455 2022/10/08 10:26:56 - mmengine - INFO - Epoch(train) [129][100/2119] lr: 4.0000e-03 eta: 4:29:52 time: 0.3320 data_time: 0.0587 memory: 5826 grad_norm: 4.8356 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 2.2014 loss: 2.2014 2022/10/08 10:27:03 - mmengine - INFO - Epoch(train) [129][120/2119] lr: 4.0000e-03 eta: 4:29:45 time: 0.3572 data_time: 0.0205 memory: 5826 grad_norm: 4.8244 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0275 loss: 2.0275 2022/10/08 10:27:10 - mmengine - INFO - Epoch(train) [129][140/2119] lr: 4.0000e-03 eta: 4:29:38 time: 0.3380 data_time: 0.0256 memory: 5826 grad_norm: 4.9242 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0526 loss: 2.0526 2022/10/08 10:27:17 - mmengine - INFO - Epoch(train) [129][160/2119] lr: 4.0000e-03 eta: 4:29:31 time: 0.3531 data_time: 0.0160 memory: 5826 grad_norm: 4.8507 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9715 loss: 1.9715 2022/10/08 10:27:24 - mmengine - INFO - Epoch(train) [129][180/2119] lr: 4.0000e-03 eta: 4:29:24 time: 0.3453 data_time: 0.0225 memory: 5826 grad_norm: 4.8443 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.8165 loss: 1.8165 2022/10/08 10:27:32 - mmengine - INFO - Epoch(train) [129][200/2119] lr: 4.0000e-03 eta: 4:29:17 time: 0.4029 data_time: 0.0279 memory: 5826 grad_norm: 4.9300 top1_acc: 0.3125 top5_acc: 0.8750 loss_cls: 1.9607 loss: 1.9607 2022/10/08 10:27:40 - mmengine - INFO - Epoch(train) [129][220/2119] lr: 4.0000e-03 eta: 4:29:10 time: 0.3897 data_time: 0.0266 memory: 5826 grad_norm: 4.8684 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0099 loss: 2.0099 2022/10/08 10:27:47 - mmengine - INFO - Epoch(train) [129][240/2119] lr: 4.0000e-03 eta: 4:29:04 time: 0.3683 data_time: 0.0268 memory: 5826 grad_norm: 4.8232 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.0262 loss: 2.0262 2022/10/08 10:27:53 - mmengine - INFO - Epoch(train) [129][260/2119] lr: 4.0000e-03 eta: 4:28:56 time: 0.3133 data_time: 0.0205 memory: 5826 grad_norm: 4.8587 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9593 loss: 1.9593 2022/10/08 10:27:59 - mmengine - INFO - Epoch(train) [129][280/2119] lr: 4.0000e-03 eta: 4:28:49 time: 0.3065 data_time: 0.0220 memory: 5826 grad_norm: 4.7797 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9792 loss: 1.9792 2022/10/08 10:28:07 - mmengine - INFO - Epoch(train) [129][300/2119] lr: 4.0000e-03 eta: 4:28:42 time: 0.3521 data_time: 0.0274 memory: 5826 grad_norm: 4.8390 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.0573 loss: 2.0573 2022/10/08 10:28:13 - mmengine - INFO - Epoch(train) [129][320/2119] lr: 4.0000e-03 eta: 4:28:35 time: 0.3357 data_time: 0.0241 memory: 5826 grad_norm: 4.9004 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.1880 loss: 2.1880 2022/10/08 10:28:20 - mmengine - INFO - Epoch(train) [129][340/2119] lr: 4.0000e-03 eta: 4:28:28 time: 0.3465 data_time: 0.0198 memory: 5826 grad_norm: 4.8533 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8915 loss: 1.8915 2022/10/08 10:28:28 - mmengine - INFO - Epoch(train) [129][360/2119] lr: 4.0000e-03 eta: 4:28:22 time: 0.3819 data_time: 0.0284 memory: 5826 grad_norm: 4.8616 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1007 loss: 2.1007 2022/10/08 10:28:34 - mmengine - INFO - Epoch(train) [129][380/2119] lr: 4.0000e-03 eta: 4:28:15 time: 0.3116 data_time: 0.0209 memory: 5826 grad_norm: 4.8130 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9810 loss: 1.9810 2022/10/08 10:28:42 - mmengine - INFO - Epoch(train) [129][400/2119] lr: 4.0000e-03 eta: 4:28:08 time: 0.3935 data_time: 0.0289 memory: 5826 grad_norm: 4.7720 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9304 loss: 1.9304 2022/10/08 10:28:48 - mmengine - INFO - Epoch(train) [129][420/2119] lr: 4.0000e-03 eta: 4:28:01 time: 0.3178 data_time: 0.0239 memory: 5826 grad_norm: 4.8311 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8785 loss: 1.8785 2022/10/08 10:28:56 - mmengine - INFO - Epoch(train) [129][440/2119] lr: 4.0000e-03 eta: 4:27:54 time: 0.3870 data_time: 0.0229 memory: 5826 grad_norm: 4.9436 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1851 loss: 2.1851 2022/10/08 10:29:02 - mmengine - INFO - Epoch(train) [129][460/2119] lr: 4.0000e-03 eta: 4:27:47 time: 0.2914 data_time: 0.0191 memory: 5826 grad_norm: 4.8108 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.7332 loss: 1.7332 2022/10/08 10:29:09 - mmengine - INFO - Epoch(train) [129][480/2119] lr: 4.0000e-03 eta: 4:27:40 time: 0.3549 data_time: 0.0282 memory: 5826 grad_norm: 4.8699 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8856 loss: 1.8856 2022/10/08 10:29:17 - mmengine - INFO - Epoch(train) [129][500/2119] lr: 4.0000e-03 eta: 4:27:33 time: 0.3906 data_time: 0.0218 memory: 5826 grad_norm: 4.8126 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 1.9321 loss: 1.9321 2022/10/08 10:29:23 - mmengine - INFO - Epoch(train) [129][520/2119] lr: 4.0000e-03 eta: 4:27:26 time: 0.3106 data_time: 0.0185 memory: 5826 grad_norm: 4.9044 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.7401 loss: 1.7401 2022/10/08 10:29:31 - mmengine - INFO - Epoch(train) [129][540/2119] lr: 4.0000e-03 eta: 4:27:19 time: 0.3752 data_time: 0.0214 memory: 5826 grad_norm: 4.9432 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9043 loss: 1.9043 2022/10/08 10:29:37 - mmengine - INFO - Epoch(train) [129][560/2119] lr: 4.0000e-03 eta: 4:27:12 time: 0.3413 data_time: 0.0264 memory: 5826 grad_norm: 4.9349 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8333 loss: 1.8333 2022/10/08 10:29:44 - mmengine - INFO - Epoch(train) [129][580/2119] lr: 4.0000e-03 eta: 4:27:05 time: 0.3517 data_time: 0.0243 memory: 5826 grad_norm: 4.8407 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9896 loss: 1.9896 2022/10/08 10:29:51 - mmengine - INFO - Epoch(train) [129][600/2119] lr: 4.0000e-03 eta: 4:26:58 time: 0.3148 data_time: 0.0343 memory: 5826 grad_norm: 4.9657 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9823 loss: 1.9823 2022/10/08 10:29:59 - mmengine - INFO - Epoch(train) [129][620/2119] lr: 4.0000e-03 eta: 4:26:51 time: 0.3915 data_time: 0.0249 memory: 5826 grad_norm: 4.8575 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0231 loss: 2.0231 2022/10/08 10:30:06 - mmengine - INFO - Epoch(train) [129][640/2119] lr: 4.0000e-03 eta: 4:26:44 time: 0.3746 data_time: 0.0211 memory: 5826 grad_norm: 4.8394 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9304 loss: 1.9304 2022/10/08 10:30:13 - mmengine - INFO - Epoch(train) [129][660/2119] lr: 4.0000e-03 eta: 4:26:37 time: 0.3565 data_time: 0.0234 memory: 5826 grad_norm: 4.8127 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0755 loss: 2.0755 2022/10/08 10:30:20 - mmengine - INFO - Epoch(train) [129][680/2119] lr: 4.0000e-03 eta: 4:26:30 time: 0.3141 data_time: 0.0259 memory: 5826 grad_norm: 4.8093 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0763 loss: 2.0763 2022/10/08 10:30:28 - mmengine - INFO - Epoch(train) [129][700/2119] lr: 4.0000e-03 eta: 4:26:24 time: 0.4311 data_time: 0.0225 memory: 5826 grad_norm: 4.8703 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9854 loss: 1.9854 2022/10/08 10:30:34 - mmengine - INFO - Epoch(train) [129][720/2119] lr: 4.0000e-03 eta: 4:26:16 time: 0.2794 data_time: 0.0200 memory: 5826 grad_norm: 4.8199 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0342 loss: 2.0342 2022/10/08 10:30:42 - mmengine - INFO - Epoch(train) [129][740/2119] lr: 4.0000e-03 eta: 4:26:10 time: 0.4090 data_time: 0.0230 memory: 5826 grad_norm: 4.8679 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9231 loss: 1.9231 2022/10/08 10:30:49 - mmengine - INFO - Epoch(train) [129][760/2119] lr: 4.0000e-03 eta: 4:26:03 time: 0.3396 data_time: 0.0276 memory: 5826 grad_norm: 4.7898 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0729 loss: 2.0729 2022/10/08 10:30:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 10:30:56 - mmengine - INFO - Epoch(train) [129][780/2119] lr: 4.0000e-03 eta: 4:25:56 time: 0.3800 data_time: 0.0241 memory: 5826 grad_norm: 4.8430 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8158 loss: 1.8158 2022/10/08 10:31:02 - mmengine - INFO - Epoch(train) [129][800/2119] lr: 4.0000e-03 eta: 4:25:49 time: 0.2934 data_time: 0.0224 memory: 5826 grad_norm: 4.9220 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1535 loss: 2.1535 2022/10/08 10:31:10 - mmengine - INFO - Epoch(train) [129][820/2119] lr: 4.0000e-03 eta: 4:25:42 time: 0.4090 data_time: 0.0234 memory: 5826 grad_norm: 4.7931 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2435 loss: 2.2435 2022/10/08 10:31:17 - mmengine - INFO - Epoch(train) [129][840/2119] lr: 4.0000e-03 eta: 4:25:35 time: 0.3472 data_time: 0.0221 memory: 5826 grad_norm: 4.9164 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1723 loss: 2.1723 2022/10/08 10:31:25 - mmengine - INFO - Epoch(train) [129][860/2119] lr: 4.0000e-03 eta: 4:25:28 time: 0.3967 data_time: 0.0248 memory: 5826 grad_norm: 4.8356 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9225 loss: 1.9225 2022/10/08 10:31:32 - mmengine - INFO - Epoch(train) [129][880/2119] lr: 4.0000e-03 eta: 4:25:21 time: 0.3291 data_time: 0.0175 memory: 5826 grad_norm: 4.8797 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0077 loss: 2.0077 2022/10/08 10:31:40 - mmengine - INFO - Epoch(train) [129][900/2119] lr: 4.0000e-03 eta: 4:25:14 time: 0.4124 data_time: 0.0199 memory: 5826 grad_norm: 4.8433 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8746 loss: 1.8746 2022/10/08 10:31:47 - mmengine - INFO - Epoch(train) [129][920/2119] lr: 4.0000e-03 eta: 4:25:07 time: 0.3430 data_time: 0.0251 memory: 5826 grad_norm: 4.7865 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8001 loss: 1.8001 2022/10/08 10:31:55 - mmengine - INFO - Epoch(train) [129][940/2119] lr: 4.0000e-03 eta: 4:25:01 time: 0.3842 data_time: 0.0208 memory: 5826 grad_norm: 4.8218 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9467 loss: 1.9467 2022/10/08 10:32:01 - mmengine - INFO - Epoch(train) [129][960/2119] lr: 4.0000e-03 eta: 4:24:54 time: 0.3310 data_time: 0.0279 memory: 5826 grad_norm: 4.8654 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7105 loss: 1.7105 2022/10/08 10:32:09 - mmengine - INFO - Epoch(train) [129][980/2119] lr: 4.0000e-03 eta: 4:24:47 time: 0.3791 data_time: 0.0225 memory: 5826 grad_norm: 4.8213 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0189 loss: 2.0189 2022/10/08 10:32:16 - mmengine - INFO - Epoch(train) [129][1000/2119] lr: 4.0000e-03 eta: 4:24:40 time: 0.3398 data_time: 0.0266 memory: 5826 grad_norm: 4.9350 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 1.9898 loss: 1.9898 2022/10/08 10:32:24 - mmengine - INFO - Epoch(train) [129][1020/2119] lr: 4.0000e-03 eta: 4:24:33 time: 0.3939 data_time: 0.0189 memory: 5826 grad_norm: 4.9197 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9266 loss: 1.9266 2022/10/08 10:32:30 - mmengine - INFO - Epoch(train) [129][1040/2119] lr: 4.0000e-03 eta: 4:24:26 time: 0.3404 data_time: 0.0195 memory: 5826 grad_norm: 4.9246 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0987 loss: 2.0987 2022/10/08 10:32:39 - mmengine - INFO - Epoch(train) [129][1060/2119] lr: 4.0000e-03 eta: 4:24:19 time: 0.4116 data_time: 0.0218 memory: 5826 grad_norm: 4.8665 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.7727 loss: 1.7727 2022/10/08 10:32:45 - mmengine - INFO - Epoch(train) [129][1080/2119] lr: 4.0000e-03 eta: 4:24:12 time: 0.3178 data_time: 0.0232 memory: 5826 grad_norm: 4.8783 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0428 loss: 2.0428 2022/10/08 10:32:53 - mmengine - INFO - Epoch(train) [129][1100/2119] lr: 4.0000e-03 eta: 4:24:05 time: 0.3815 data_time: 0.0255 memory: 5826 grad_norm: 4.9095 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9797 loss: 1.9797 2022/10/08 10:32:59 - mmengine - INFO - Epoch(train) [129][1120/2119] lr: 4.0000e-03 eta: 4:23:58 time: 0.3194 data_time: 0.0212 memory: 5826 grad_norm: 4.9422 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0929 loss: 2.0929 2022/10/08 10:33:06 - mmengine - INFO - Epoch(train) [129][1140/2119] lr: 4.0000e-03 eta: 4:23:51 time: 0.3481 data_time: 0.0236 memory: 5826 grad_norm: 4.8861 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9822 loss: 1.9822 2022/10/08 10:33:13 - mmengine - INFO - Epoch(train) [129][1160/2119] lr: 4.0000e-03 eta: 4:23:44 time: 0.3231 data_time: 0.0236 memory: 5826 grad_norm: 4.9110 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9782 loss: 1.9782 2022/10/08 10:33:21 - mmengine - INFO - Epoch(train) [129][1180/2119] lr: 4.0000e-03 eta: 4:23:37 time: 0.4078 data_time: 0.0182 memory: 5826 grad_norm: 4.8963 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0075 loss: 2.0075 2022/10/08 10:33:27 - mmengine - INFO - Epoch(train) [129][1200/2119] lr: 4.0000e-03 eta: 4:23:30 time: 0.2928 data_time: 0.0248 memory: 5826 grad_norm: 4.8888 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8471 loss: 1.8471 2022/10/08 10:33:35 - mmengine - INFO - Epoch(train) [129][1220/2119] lr: 4.0000e-03 eta: 4:23:24 time: 0.4298 data_time: 0.0196 memory: 5826 grad_norm: 4.8674 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8324 loss: 1.8324 2022/10/08 10:33:41 - mmengine - INFO - Epoch(train) [129][1240/2119] lr: 4.0000e-03 eta: 4:23:16 time: 0.3154 data_time: 0.0218 memory: 5826 grad_norm: 4.9964 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0426 loss: 2.0426 2022/10/08 10:33:48 - mmengine - INFO - Epoch(train) [129][1260/2119] lr: 4.0000e-03 eta: 4:23:09 time: 0.3426 data_time: 0.0262 memory: 5826 grad_norm: 4.9433 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9738 loss: 1.9738 2022/10/08 10:33:55 - mmengine - INFO - Epoch(train) [129][1280/2119] lr: 4.0000e-03 eta: 4:23:02 time: 0.3126 data_time: 0.0322 memory: 5826 grad_norm: 4.7875 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2294 loss: 2.2294 2022/10/08 10:34:03 - mmengine - INFO - Epoch(train) [129][1300/2119] lr: 4.0000e-03 eta: 4:22:56 time: 0.4379 data_time: 0.0193 memory: 5826 grad_norm: 4.7920 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9051 loss: 1.9051 2022/10/08 10:34:10 - mmengine - INFO - Epoch(train) [129][1320/2119] lr: 4.0000e-03 eta: 4:22:49 time: 0.3102 data_time: 0.0208 memory: 5826 grad_norm: 4.8805 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8650 loss: 1.8650 2022/10/08 10:34:16 - mmengine - INFO - Epoch(train) [129][1340/2119] lr: 4.0000e-03 eta: 4:22:42 time: 0.3199 data_time: 0.0215 memory: 5826 grad_norm: 4.8471 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.7830 loss: 1.7830 2022/10/08 10:34:23 - mmengine - INFO - Epoch(train) [129][1360/2119] lr: 4.0000e-03 eta: 4:22:35 time: 0.3383 data_time: 0.0219 memory: 5826 grad_norm: 4.9317 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0667 loss: 2.0667 2022/10/08 10:34:30 - mmengine - INFO - Epoch(train) [129][1380/2119] lr: 4.0000e-03 eta: 4:22:28 time: 0.3670 data_time: 0.0158 memory: 5826 grad_norm: 4.9296 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0295 loss: 2.0295 2022/10/08 10:34:38 - mmengine - INFO - Epoch(train) [129][1400/2119] lr: 4.0000e-03 eta: 4:22:21 time: 0.3700 data_time: 0.0312 memory: 5826 grad_norm: 4.9819 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0309 loss: 2.0309 2022/10/08 10:34:44 - mmengine - INFO - Epoch(train) [129][1420/2119] lr: 4.0000e-03 eta: 4:22:14 time: 0.3178 data_time: 0.0254 memory: 5826 grad_norm: 5.0102 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.1361 loss: 2.1361 2022/10/08 10:34:51 - mmengine - INFO - Epoch(train) [129][1440/2119] lr: 4.0000e-03 eta: 4:22:07 time: 0.3608 data_time: 0.0238 memory: 5826 grad_norm: 4.8455 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.9684 loss: 1.9684 2022/10/08 10:34:59 - mmengine - INFO - Epoch(train) [129][1460/2119] lr: 4.0000e-03 eta: 4:22:00 time: 0.3857 data_time: 0.0176 memory: 5826 grad_norm: 4.9089 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2018 loss: 2.2018 2022/10/08 10:35:05 - mmengine - INFO - Epoch(train) [129][1480/2119] lr: 4.0000e-03 eta: 4:21:53 time: 0.3147 data_time: 0.0270 memory: 5826 grad_norm: 4.9221 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0628 loss: 2.0628 2022/10/08 10:35:12 - mmengine - INFO - Epoch(train) [129][1500/2119] lr: 4.0000e-03 eta: 4:21:46 time: 0.3461 data_time: 0.0257 memory: 5826 grad_norm: 4.8512 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.7788 loss: 1.7788 2022/10/08 10:35:19 - mmengine - INFO - Epoch(train) [129][1520/2119] lr: 4.0000e-03 eta: 4:21:39 time: 0.3479 data_time: 0.0229 memory: 5826 grad_norm: 4.9160 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9593 loss: 1.9593 2022/10/08 10:35:26 - mmengine - INFO - Epoch(train) [129][1540/2119] lr: 4.0000e-03 eta: 4:21:32 time: 0.3614 data_time: 0.0285 memory: 5826 grad_norm: 4.8523 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0697 loss: 2.0697 2022/10/08 10:35:33 - mmengine - INFO - Epoch(train) [129][1560/2119] lr: 4.0000e-03 eta: 4:21:25 time: 0.3451 data_time: 0.0229 memory: 5826 grad_norm: 4.9457 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0158 loss: 2.0158 2022/10/08 10:35:40 - mmengine - INFO - Epoch(train) [129][1580/2119] lr: 4.0000e-03 eta: 4:21:18 time: 0.3345 data_time: 0.0284 memory: 5826 grad_norm: 4.8664 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0278 loss: 2.0278 2022/10/08 10:35:47 - mmengine - INFO - Epoch(train) [129][1600/2119] lr: 4.0000e-03 eta: 4:21:11 time: 0.3479 data_time: 0.0204 memory: 5826 grad_norm: 4.8927 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.1287 loss: 2.1287 2022/10/08 10:35:54 - mmengine - INFO - Epoch(train) [129][1620/2119] lr: 4.0000e-03 eta: 4:21:04 time: 0.3709 data_time: 0.0232 memory: 5826 grad_norm: 4.8661 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 1.8878 loss: 1.8878 2022/10/08 10:36:01 - mmengine - INFO - Epoch(train) [129][1640/2119] lr: 4.0000e-03 eta: 4:20:57 time: 0.3159 data_time: 0.0214 memory: 5826 grad_norm: 4.8581 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.9112 loss: 1.9112 2022/10/08 10:36:08 - mmengine - INFO - Epoch(train) [129][1660/2119] lr: 4.0000e-03 eta: 4:20:50 time: 0.3753 data_time: 0.0189 memory: 5826 grad_norm: 4.8698 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8732 loss: 1.8732 2022/10/08 10:36:15 - mmengine - INFO - Epoch(train) [129][1680/2119] lr: 4.0000e-03 eta: 4:20:43 time: 0.3211 data_time: 0.0211 memory: 5826 grad_norm: 4.8435 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.0605 loss: 2.0605 2022/10/08 10:36:22 - mmengine - INFO - Epoch(train) [129][1700/2119] lr: 4.0000e-03 eta: 4:20:36 time: 0.3833 data_time: 0.0254 memory: 5826 grad_norm: 4.8079 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0466 loss: 2.0466 2022/10/08 10:36:28 - mmengine - INFO - Epoch(train) [129][1720/2119] lr: 4.0000e-03 eta: 4:20:29 time: 0.3083 data_time: 0.0265 memory: 5826 grad_norm: 4.8373 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.7632 loss: 1.7632 2022/10/08 10:36:37 - mmengine - INFO - Epoch(train) [129][1740/2119] lr: 4.0000e-03 eta: 4:20:23 time: 0.4058 data_time: 0.0239 memory: 5826 grad_norm: 4.9579 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.0993 loss: 2.0993 2022/10/08 10:36:43 - mmengine - INFO - Epoch(train) [129][1760/2119] lr: 4.0000e-03 eta: 4:20:16 time: 0.3445 data_time: 0.0240 memory: 5826 grad_norm: 4.8340 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7860 loss: 1.7860 2022/10/08 10:36:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 10:36:51 - mmengine - INFO - Epoch(train) [129][1780/2119] lr: 4.0000e-03 eta: 4:20:09 time: 0.3673 data_time: 0.0214 memory: 5826 grad_norm: 4.7997 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7773 loss: 1.7773 2022/10/08 10:36:57 - mmengine - INFO - Epoch(train) [129][1800/2119] lr: 4.0000e-03 eta: 4:20:02 time: 0.3243 data_time: 0.0281 memory: 5826 grad_norm: 4.7653 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9055 loss: 1.9055 2022/10/08 10:37:05 - mmengine - INFO - Epoch(train) [129][1820/2119] lr: 4.0000e-03 eta: 4:19:55 time: 0.3652 data_time: 0.0211 memory: 5826 grad_norm: 4.8207 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0580 loss: 2.0580 2022/10/08 10:37:11 - mmengine - INFO - Epoch(train) [129][1840/2119] lr: 4.0000e-03 eta: 4:19:48 time: 0.3258 data_time: 0.0219 memory: 5826 grad_norm: 4.8703 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8397 loss: 1.8397 2022/10/08 10:37:19 - mmengine - INFO - Epoch(train) [129][1860/2119] lr: 4.0000e-03 eta: 4:19:41 time: 0.3732 data_time: 0.0265 memory: 5826 grad_norm: 4.8072 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9384 loss: 1.9384 2022/10/08 10:37:27 - mmengine - INFO - Epoch(train) [129][1880/2119] lr: 4.0000e-03 eta: 4:19:34 time: 0.3970 data_time: 0.0218 memory: 5826 grad_norm: 4.9285 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8724 loss: 1.8724 2022/10/08 10:37:33 - mmengine - INFO - Epoch(train) [129][1900/2119] lr: 4.0000e-03 eta: 4:19:27 time: 0.2995 data_time: 0.0221 memory: 5826 grad_norm: 4.9634 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 1.9702 loss: 1.9702 2022/10/08 10:37:40 - mmengine - INFO - Epoch(train) [129][1920/2119] lr: 4.0000e-03 eta: 4:19:20 time: 0.3655 data_time: 0.0178 memory: 5826 grad_norm: 4.8553 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8883 loss: 1.8883 2022/10/08 10:37:46 - mmengine - INFO - Epoch(train) [129][1940/2119] lr: 4.0000e-03 eta: 4:19:13 time: 0.3317 data_time: 0.0257 memory: 5826 grad_norm: 4.7987 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1096 loss: 2.1096 2022/10/08 10:37:53 - mmengine - INFO - Epoch(train) [129][1960/2119] lr: 4.0000e-03 eta: 4:19:06 time: 0.3467 data_time: 0.0245 memory: 5826 grad_norm: 4.8110 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8668 loss: 1.8668 2022/10/08 10:38:01 - mmengine - INFO - Epoch(train) [129][1980/2119] lr: 4.0000e-03 eta: 4:18:59 time: 0.3588 data_time: 0.0182 memory: 5826 grad_norm: 4.8375 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.8152 loss: 1.8152 2022/10/08 10:38:08 - mmengine - INFO - Epoch(train) [129][2000/2119] lr: 4.0000e-03 eta: 4:18:52 time: 0.3641 data_time: 0.0233 memory: 5826 grad_norm: 4.9042 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.1159 loss: 2.1159 2022/10/08 10:38:16 - mmengine - INFO - Epoch(train) [129][2020/2119] lr: 4.0000e-03 eta: 4:18:45 time: 0.4033 data_time: 0.0177 memory: 5826 grad_norm: 4.9813 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 1.9315 loss: 1.9315 2022/10/08 10:38:23 - mmengine - INFO - Epoch(train) [129][2040/2119] lr: 4.0000e-03 eta: 4:18:38 time: 0.3325 data_time: 0.0200 memory: 5826 grad_norm: 4.8398 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0703 loss: 2.0703 2022/10/08 10:38:31 - mmengine - INFO - Epoch(train) [129][2060/2119] lr: 4.0000e-03 eta: 4:18:32 time: 0.4140 data_time: 0.0191 memory: 5826 grad_norm: 4.8390 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.9583 loss: 1.9583 2022/10/08 10:38:37 - mmengine - INFO - Epoch(train) [129][2080/2119] lr: 4.0000e-03 eta: 4:18:24 time: 0.3002 data_time: 0.0218 memory: 5826 grad_norm: 4.9104 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9322 loss: 1.9322 2022/10/08 10:38:43 - mmengine - INFO - Epoch(train) [129][2100/2119] lr: 4.0000e-03 eta: 4:18:17 time: 0.3224 data_time: 0.0207 memory: 5826 grad_norm: 4.8600 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0313 loss: 2.0313 2022/10/08 10:38:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 10:38:50 - mmengine - INFO - Epoch(train) [129][2119/2119] lr: 4.0000e-03 eta: 4:18:17 time: 0.3389 data_time: 0.0202 memory: 5826 grad_norm: 4.8705 top1_acc: 0.7000 top5_acc: 0.7000 loss_cls: 1.7054 loss: 1.7054 2022/10/08 10:39:00 - mmengine - INFO - Epoch(train) [130][20/2119] lr: 4.0000e-03 eta: 4:18:03 time: 0.4776 data_time: 0.2091 memory: 5826 grad_norm: 4.8437 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.8108 loss: 1.8108 2022/10/08 10:39:06 - mmengine - INFO - Epoch(train) [130][40/2119] lr: 4.0000e-03 eta: 4:17:56 time: 0.3428 data_time: 0.0169 memory: 5826 grad_norm: 4.8977 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.1282 loss: 2.1282 2022/10/08 10:39:14 - mmengine - INFO - Epoch(train) [130][60/2119] lr: 4.0000e-03 eta: 4:17:49 time: 0.3693 data_time: 0.0266 memory: 5826 grad_norm: 4.8339 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8722 loss: 1.8722 2022/10/08 10:39:21 - mmengine - INFO - Epoch(train) [130][80/2119] lr: 4.0000e-03 eta: 4:17:42 time: 0.3737 data_time: 0.0205 memory: 5826 grad_norm: 4.9180 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0878 loss: 2.0878 2022/10/08 10:39:29 - mmengine - INFO - Epoch(train) [130][100/2119] lr: 4.0000e-03 eta: 4:17:36 time: 0.3782 data_time: 0.0288 memory: 5826 grad_norm: 4.8935 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9460 loss: 1.9460 2022/10/08 10:39:35 - mmengine - INFO - Epoch(train) [130][120/2119] lr: 4.0000e-03 eta: 4:17:29 time: 0.3275 data_time: 0.0220 memory: 5826 grad_norm: 4.8455 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.9663 loss: 1.9663 2022/10/08 10:39:44 - mmengine - INFO - Epoch(train) [130][140/2119] lr: 4.0000e-03 eta: 4:17:22 time: 0.4058 data_time: 0.0198 memory: 5826 grad_norm: 4.8078 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0720 loss: 2.0720 2022/10/08 10:39:49 - mmengine - INFO - Epoch(train) [130][160/2119] lr: 4.0000e-03 eta: 4:17:15 time: 0.2605 data_time: 0.0263 memory: 5826 grad_norm: 4.8970 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9008 loss: 1.9008 2022/10/08 10:39:57 - mmengine - INFO - Epoch(train) [130][180/2119] lr: 4.0000e-03 eta: 4:17:08 time: 0.3890 data_time: 0.0263 memory: 5826 grad_norm: 4.9138 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1168 loss: 2.1168 2022/10/08 10:40:03 - mmengine - INFO - Epoch(train) [130][200/2119] lr: 4.0000e-03 eta: 4:17:01 time: 0.3217 data_time: 0.0351 memory: 5826 grad_norm: 4.9074 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9729 loss: 1.9729 2022/10/08 10:40:10 - mmengine - INFO - Epoch(train) [130][220/2119] lr: 4.0000e-03 eta: 4:16:54 time: 0.3531 data_time: 0.0277 memory: 5826 grad_norm: 4.9573 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8788 loss: 1.8788 2022/10/08 10:40:17 - mmengine - INFO - Epoch(train) [130][240/2119] lr: 4.0000e-03 eta: 4:16:47 time: 0.3398 data_time: 0.0216 memory: 5826 grad_norm: 4.8436 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.0227 loss: 2.0227 2022/10/08 10:40:24 - mmengine - INFO - Epoch(train) [130][260/2119] lr: 4.0000e-03 eta: 4:16:40 time: 0.3593 data_time: 0.0263 memory: 5826 grad_norm: 4.9665 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9332 loss: 1.9332 2022/10/08 10:40:31 - mmengine - INFO - Epoch(train) [130][280/2119] lr: 4.0000e-03 eta: 4:16:33 time: 0.3400 data_time: 0.0183 memory: 5826 grad_norm: 4.8162 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 2.0888 loss: 2.0888 2022/10/08 10:40:38 - mmengine - INFO - Epoch(train) [130][300/2119] lr: 4.0000e-03 eta: 4:16:26 time: 0.3550 data_time: 0.0253 memory: 5826 grad_norm: 4.8246 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9297 loss: 1.9297 2022/10/08 10:40:45 - mmengine - INFO - Epoch(train) [130][320/2119] lr: 4.0000e-03 eta: 4:16:19 time: 0.3601 data_time: 0.0232 memory: 5826 grad_norm: 4.7937 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9892 loss: 1.9892 2022/10/08 10:40:53 - mmengine - INFO - Epoch(train) [130][340/2119] lr: 4.0000e-03 eta: 4:16:12 time: 0.3924 data_time: 0.0194 memory: 5826 grad_norm: 4.8004 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9818 loss: 1.9818 2022/10/08 10:40:59 - mmengine - INFO - Epoch(train) [130][360/2119] lr: 4.0000e-03 eta: 4:16:05 time: 0.2996 data_time: 0.0207 memory: 5826 grad_norm: 4.8532 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9197 loss: 1.9197 2022/10/08 10:41:07 - mmengine - INFO - Epoch(train) [130][380/2119] lr: 4.0000e-03 eta: 4:15:58 time: 0.4120 data_time: 0.0204 memory: 5826 grad_norm: 4.8021 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8795 loss: 1.8795 2022/10/08 10:41:14 - mmengine - INFO - Epoch(train) [130][400/2119] lr: 4.0000e-03 eta: 4:15:51 time: 0.3389 data_time: 0.0198 memory: 5826 grad_norm: 4.8806 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0429 loss: 2.0429 2022/10/08 10:41:21 - mmengine - INFO - Epoch(train) [130][420/2119] lr: 4.0000e-03 eta: 4:15:44 time: 0.3604 data_time: 0.0222 memory: 5826 grad_norm: 4.9007 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7046 loss: 1.7046 2022/10/08 10:41:28 - mmengine - INFO - Epoch(train) [130][440/2119] lr: 4.0000e-03 eta: 4:15:37 time: 0.3594 data_time: 0.0225 memory: 5826 grad_norm: 4.8619 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8827 loss: 1.8827 2022/10/08 10:41:36 - mmengine - INFO - Epoch(train) [130][460/2119] lr: 4.0000e-03 eta: 4:15:31 time: 0.3871 data_time: 0.0213 memory: 5826 grad_norm: 4.8484 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9753 loss: 1.9753 2022/10/08 10:41:43 - mmengine - INFO - Epoch(train) [130][480/2119] lr: 4.0000e-03 eta: 4:15:24 time: 0.3433 data_time: 0.0235 memory: 5826 grad_norm: 4.8514 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.1248 loss: 2.1248 2022/10/08 10:41:51 - mmengine - INFO - Epoch(train) [130][500/2119] lr: 4.0000e-03 eta: 4:15:17 time: 0.3757 data_time: 0.0227 memory: 5826 grad_norm: 4.8652 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0202 loss: 2.0202 2022/10/08 10:41:57 - mmengine - INFO - Epoch(train) [130][520/2119] lr: 4.0000e-03 eta: 4:15:10 time: 0.2980 data_time: 0.0195 memory: 5826 grad_norm: 4.8253 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8897 loss: 1.8897 2022/10/08 10:42:04 - mmengine - INFO - Epoch(train) [130][540/2119] lr: 4.0000e-03 eta: 4:15:03 time: 0.3529 data_time: 0.0261 memory: 5826 grad_norm: 4.9138 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9594 loss: 1.9594 2022/10/08 10:42:11 - mmengine - INFO - Epoch(train) [130][560/2119] lr: 4.0000e-03 eta: 4:14:56 time: 0.3556 data_time: 0.0219 memory: 5826 grad_norm: 4.9574 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.8323 loss: 1.8323 2022/10/08 10:42:18 - mmengine - INFO - Epoch(train) [130][580/2119] lr: 4.0000e-03 eta: 4:14:49 time: 0.3724 data_time: 0.0191 memory: 5826 grad_norm: 4.9547 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8951 loss: 1.8951 2022/10/08 10:42:24 - mmengine - INFO - Epoch(train) [130][600/2119] lr: 4.0000e-03 eta: 4:14:42 time: 0.2874 data_time: 0.0204 memory: 5826 grad_norm: 4.8926 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7536 loss: 1.7536 2022/10/08 10:42:31 - mmengine - INFO - Epoch(train) [130][620/2119] lr: 4.0000e-03 eta: 4:14:35 time: 0.3712 data_time: 0.0220 memory: 5826 grad_norm: 4.9436 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9466 loss: 1.9466 2022/10/08 10:42:38 - mmengine - INFO - Epoch(train) [130][640/2119] lr: 4.0000e-03 eta: 4:14:28 time: 0.3470 data_time: 0.0234 memory: 5826 grad_norm: 5.0120 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9823 loss: 1.9823 2022/10/08 10:42:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 10:42:45 - mmengine - INFO - Epoch(train) [130][660/2119] lr: 4.0000e-03 eta: 4:14:21 time: 0.3523 data_time: 0.0196 memory: 5826 grad_norm: 4.8729 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0515 loss: 2.0515 2022/10/08 10:42:53 - mmengine - INFO - Epoch(train) [130][680/2119] lr: 4.0000e-03 eta: 4:14:14 time: 0.3775 data_time: 0.0198 memory: 5826 grad_norm: 4.9562 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9928 loss: 1.9928 2022/10/08 10:43:01 - mmengine - INFO - Epoch(train) [130][700/2119] lr: 4.0000e-03 eta: 4:14:07 time: 0.3798 data_time: 0.0202 memory: 5826 grad_norm: 4.9090 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.0554 loss: 2.0554 2022/10/08 10:43:07 - mmengine - INFO - Epoch(train) [130][720/2119] lr: 4.0000e-03 eta: 4:14:00 time: 0.3261 data_time: 0.0173 memory: 5826 grad_norm: 4.8194 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8741 loss: 1.8741 2022/10/08 10:43:14 - mmengine - INFO - Epoch(train) [130][740/2119] lr: 4.0000e-03 eta: 4:13:53 time: 0.3222 data_time: 0.0239 memory: 5826 grad_norm: 4.9118 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9731 loss: 1.9731 2022/10/08 10:43:20 - mmengine - INFO - Epoch(train) [130][760/2119] lr: 4.0000e-03 eta: 4:13:46 time: 0.3333 data_time: 0.0231 memory: 5826 grad_norm: 4.9468 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.0501 loss: 2.0501 2022/10/08 10:43:29 - mmengine - INFO - Epoch(train) [130][780/2119] lr: 4.0000e-03 eta: 4:13:39 time: 0.4181 data_time: 0.0247 memory: 5826 grad_norm: 4.8049 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8742 loss: 1.8742 2022/10/08 10:43:35 - mmengine - INFO - Epoch(train) [130][800/2119] lr: 4.0000e-03 eta: 4:13:32 time: 0.3200 data_time: 0.0181 memory: 5826 grad_norm: 4.8380 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8951 loss: 1.8951 2022/10/08 10:43:43 - mmengine - INFO - Epoch(train) [130][820/2119] lr: 4.0000e-03 eta: 4:13:25 time: 0.3751 data_time: 0.0226 memory: 5826 grad_norm: 4.8396 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9651 loss: 1.9651 2022/10/08 10:43:49 - mmengine - INFO - Epoch(train) [130][840/2119] lr: 4.0000e-03 eta: 4:13:18 time: 0.3347 data_time: 0.0268 memory: 5826 grad_norm: 4.8665 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0527 loss: 2.0527 2022/10/08 10:43:57 - mmengine - INFO - Epoch(train) [130][860/2119] lr: 4.0000e-03 eta: 4:13:11 time: 0.3660 data_time: 0.0252 memory: 5826 grad_norm: 4.9228 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8466 loss: 1.8466 2022/10/08 10:44:02 - mmengine - INFO - Epoch(train) [130][880/2119] lr: 4.0000e-03 eta: 4:13:04 time: 0.2910 data_time: 0.0201 memory: 5826 grad_norm: 4.8836 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0448 loss: 2.0448 2022/10/08 10:44:10 - mmengine - INFO - Epoch(train) [130][900/2119] lr: 4.0000e-03 eta: 4:12:57 time: 0.3868 data_time: 0.0219 memory: 5826 grad_norm: 4.8751 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0118 loss: 2.0118 2022/10/08 10:44:16 - mmengine - INFO - Epoch(train) [130][920/2119] lr: 4.0000e-03 eta: 4:12:50 time: 0.3110 data_time: 0.0198 memory: 5826 grad_norm: 4.9520 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.1045 loss: 2.1045 2022/10/08 10:44:23 - mmengine - INFO - Epoch(train) [130][940/2119] lr: 4.0000e-03 eta: 4:12:43 time: 0.3433 data_time: 0.0239 memory: 5826 grad_norm: 4.9616 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8967 loss: 1.8967 2022/10/08 10:44:30 - mmengine - INFO - Epoch(train) [130][960/2119] lr: 4.0000e-03 eta: 4:12:36 time: 0.3503 data_time: 0.0224 memory: 5826 grad_norm: 4.8819 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9678 loss: 1.9678 2022/10/08 10:44:37 - mmengine - INFO - Epoch(train) [130][980/2119] lr: 4.0000e-03 eta: 4:12:30 time: 0.3590 data_time: 0.0242 memory: 5826 grad_norm: 4.8450 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.8350 loss: 1.8350 2022/10/08 10:44:44 - mmengine - INFO - Epoch(train) [130][1000/2119] lr: 4.0000e-03 eta: 4:12:22 time: 0.3250 data_time: 0.0265 memory: 5826 grad_norm: 4.8689 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.0466 loss: 2.0466 2022/10/08 10:44:51 - mmengine - INFO - Epoch(train) [130][1020/2119] lr: 4.0000e-03 eta: 4:12:16 time: 0.3590 data_time: 0.0219 memory: 5826 grad_norm: 4.9874 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8984 loss: 1.8984 2022/10/08 10:44:57 - mmengine - INFO - Epoch(train) [130][1040/2119] lr: 4.0000e-03 eta: 4:12:08 time: 0.3007 data_time: 0.0248 memory: 5826 grad_norm: 4.9585 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.8803 loss: 1.8803 2022/10/08 10:45:05 - mmengine - INFO - Epoch(train) [130][1060/2119] lr: 4.0000e-03 eta: 4:12:02 time: 0.3838 data_time: 0.0281 memory: 5826 grad_norm: 4.9612 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9018 loss: 1.9018 2022/10/08 10:45:11 - mmengine - INFO - Epoch(train) [130][1080/2119] lr: 4.0000e-03 eta: 4:11:55 time: 0.3283 data_time: 0.0228 memory: 5826 grad_norm: 5.0244 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.9311 loss: 1.9311 2022/10/08 10:45:19 - mmengine - INFO - Epoch(train) [130][1100/2119] lr: 4.0000e-03 eta: 4:11:48 time: 0.4020 data_time: 0.0240 memory: 5826 grad_norm: 4.8579 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0361 loss: 2.0361 2022/10/08 10:45:25 - mmengine - INFO - Epoch(train) [130][1120/2119] lr: 4.0000e-03 eta: 4:11:41 time: 0.2900 data_time: 0.0241 memory: 5826 grad_norm: 4.9315 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9561 loss: 1.9561 2022/10/08 10:45:33 - mmengine - INFO - Epoch(train) [130][1140/2119] lr: 4.0000e-03 eta: 4:11:34 time: 0.3778 data_time: 0.0193 memory: 5826 grad_norm: 4.8396 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9747 loss: 1.9747 2022/10/08 10:45:40 - mmengine - INFO - Epoch(train) [130][1160/2119] lr: 4.0000e-03 eta: 4:11:27 time: 0.3364 data_time: 0.0227 memory: 5826 grad_norm: 4.9729 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0519 loss: 2.0519 2022/10/08 10:45:47 - mmengine - INFO - Epoch(train) [130][1180/2119] lr: 4.0000e-03 eta: 4:11:20 time: 0.3756 data_time: 0.0216 memory: 5826 grad_norm: 4.9372 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9264 loss: 1.9264 2022/10/08 10:45:53 - mmengine - INFO - Epoch(train) [130][1200/2119] lr: 4.0000e-03 eta: 4:11:13 time: 0.3038 data_time: 0.0211 memory: 5826 grad_norm: 4.8609 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8664 loss: 1.8664 2022/10/08 10:46:00 - mmengine - INFO - Epoch(train) [130][1220/2119] lr: 4.0000e-03 eta: 4:11:06 time: 0.3500 data_time: 0.0236 memory: 5826 grad_norm: 4.9359 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0293 loss: 2.0293 2022/10/08 10:46:07 - mmengine - INFO - Epoch(train) [130][1240/2119] lr: 4.0000e-03 eta: 4:10:59 time: 0.3396 data_time: 0.0260 memory: 5826 grad_norm: 4.8919 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8960 loss: 1.8960 2022/10/08 10:46:13 - mmengine - INFO - Epoch(train) [130][1260/2119] lr: 4.0000e-03 eta: 4:10:52 time: 0.3168 data_time: 0.0247 memory: 5826 grad_norm: 4.9615 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8830 loss: 1.8830 2022/10/08 10:46:20 - mmengine - INFO - Epoch(train) [130][1280/2119] lr: 4.0000e-03 eta: 4:10:45 time: 0.3275 data_time: 0.0206 memory: 5826 grad_norm: 4.8692 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9420 loss: 1.9420 2022/10/08 10:46:28 - mmengine - INFO - Epoch(train) [130][1300/2119] lr: 4.0000e-03 eta: 4:10:38 time: 0.3940 data_time: 0.0232 memory: 5826 grad_norm: 4.8839 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 1.8963 loss: 1.8963 2022/10/08 10:46:35 - mmengine - INFO - Epoch(train) [130][1320/2119] lr: 4.0000e-03 eta: 4:10:31 time: 0.3426 data_time: 0.0152 memory: 5826 grad_norm: 4.8429 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.9501 loss: 1.9501 2022/10/08 10:46:42 - mmengine - INFO - Epoch(train) [130][1340/2119] lr: 4.0000e-03 eta: 4:10:24 time: 0.3759 data_time: 0.0220 memory: 5826 grad_norm: 5.0149 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.1190 loss: 2.1190 2022/10/08 10:46:49 - mmengine - INFO - Epoch(train) [130][1360/2119] lr: 4.0000e-03 eta: 4:10:17 time: 0.3267 data_time: 0.0217 memory: 5826 grad_norm: 4.9713 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.2176 loss: 2.2176 2022/10/08 10:46:56 - mmengine - INFO - Epoch(train) [130][1380/2119] lr: 4.0000e-03 eta: 4:10:10 time: 0.3835 data_time: 0.0226 memory: 5826 grad_norm: 4.9055 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 1.9309 loss: 1.9309 2022/10/08 10:47:03 - mmengine - INFO - Epoch(train) [130][1400/2119] lr: 4.0000e-03 eta: 4:10:03 time: 0.3515 data_time: 0.0170 memory: 5826 grad_norm: 4.8999 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9689 loss: 1.9689 2022/10/08 10:47:11 - mmengine - INFO - Epoch(train) [130][1420/2119] lr: 4.0000e-03 eta: 4:09:56 time: 0.3822 data_time: 0.0203 memory: 5826 grad_norm: 5.0356 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0061 loss: 2.0061 2022/10/08 10:47:18 - mmengine - INFO - Epoch(train) [130][1440/2119] lr: 4.0000e-03 eta: 4:09:49 time: 0.3213 data_time: 0.0250 memory: 5826 grad_norm: 4.8795 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8655 loss: 1.8655 2022/10/08 10:47:25 - mmengine - INFO - Epoch(train) [130][1460/2119] lr: 4.0000e-03 eta: 4:09:42 time: 0.3619 data_time: 0.0256 memory: 5826 grad_norm: 4.9603 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 2.1808 loss: 2.1808 2022/10/08 10:47:32 - mmengine - INFO - Epoch(train) [130][1480/2119] lr: 4.0000e-03 eta: 4:09:35 time: 0.3554 data_time: 0.0186 memory: 5826 grad_norm: 4.8401 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7109 loss: 1.7109 2022/10/08 10:47:39 - mmengine - INFO - Epoch(train) [130][1500/2119] lr: 4.0000e-03 eta: 4:09:29 time: 0.3670 data_time: 0.0254 memory: 5826 grad_norm: 4.8587 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0302 loss: 2.0302 2022/10/08 10:47:48 - mmengine - INFO - Epoch(train) [130][1520/2119] lr: 4.0000e-03 eta: 4:09:22 time: 0.4232 data_time: 0.0222 memory: 5826 grad_norm: 4.8576 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.9302 loss: 1.9302 2022/10/08 10:47:54 - mmengine - INFO - Epoch(train) [130][1540/2119] lr: 4.0000e-03 eta: 4:09:15 time: 0.3054 data_time: 0.0227 memory: 5826 grad_norm: 5.0101 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9611 loss: 1.9611 2022/10/08 10:48:00 - mmengine - INFO - Epoch(train) [130][1560/2119] lr: 4.0000e-03 eta: 4:09:08 time: 0.3197 data_time: 0.0210 memory: 5826 grad_norm: 4.7920 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9205 loss: 1.9205 2022/10/08 10:48:07 - mmengine - INFO - Epoch(train) [130][1580/2119] lr: 4.0000e-03 eta: 4:09:01 time: 0.3437 data_time: 0.0265 memory: 5826 grad_norm: 4.8592 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8543 loss: 1.8543 2022/10/08 10:48:13 - mmengine - INFO - Epoch(train) [130][1600/2119] lr: 4.0000e-03 eta: 4:08:54 time: 0.3169 data_time: 0.0215 memory: 5826 grad_norm: 4.9311 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7117 loss: 1.7117 2022/10/08 10:48:21 - mmengine - INFO - Epoch(train) [130][1620/2119] lr: 4.0000e-03 eta: 4:08:47 time: 0.3930 data_time: 0.0207 memory: 5826 grad_norm: 4.8739 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.1583 loss: 2.1583 2022/10/08 10:48:28 - mmengine - INFO - Epoch(train) [130][1640/2119] lr: 4.0000e-03 eta: 4:08:40 time: 0.3188 data_time: 0.0243 memory: 5826 grad_norm: 4.9205 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0245 loss: 2.0245 2022/10/08 10:48:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 10:48:35 - mmengine - INFO - Epoch(train) [130][1660/2119] lr: 4.0000e-03 eta: 4:08:33 time: 0.3432 data_time: 0.0228 memory: 5826 grad_norm: 4.8992 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9361 loss: 1.9361 2022/10/08 10:48:42 - mmengine - INFO - Epoch(train) [130][1680/2119] lr: 4.0000e-03 eta: 4:08:26 time: 0.3730 data_time: 0.0227 memory: 5826 grad_norm: 4.9674 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0931 loss: 2.0931 2022/10/08 10:48:49 - mmengine - INFO - Epoch(train) [130][1700/2119] lr: 4.0000e-03 eta: 4:08:19 time: 0.3318 data_time: 0.0248 memory: 5826 grad_norm: 5.0155 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.1738 loss: 2.1738 2022/10/08 10:48:55 - mmengine - INFO - Epoch(train) [130][1720/2119] lr: 4.0000e-03 eta: 4:08:12 time: 0.3181 data_time: 0.0201 memory: 5826 grad_norm: 4.9321 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.8109 loss: 1.8109 2022/10/08 10:49:03 - mmengine - INFO - Epoch(train) [130][1740/2119] lr: 4.0000e-03 eta: 4:08:05 time: 0.4191 data_time: 0.0223 memory: 5826 grad_norm: 4.9849 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8872 loss: 1.8872 2022/10/08 10:49:29 - mmengine - INFO - Epoch(train) [130][1760/2119] lr: 4.0000e-03 eta: 4:08:01 time: 1.2698 data_time: 0.0327 memory: 5826 grad_norm: 4.9516 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 1.9215 loss: 1.9215 2022/10/08 10:49:35 - mmengine - INFO - Epoch(train) [130][1780/2119] lr: 4.0000e-03 eta: 4:07:54 time: 0.3018 data_time: 0.0296 memory: 5826 grad_norm: 5.0140 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2306 loss: 2.2306 2022/10/08 10:49:42 - mmengine - INFO - Epoch(train) [130][1800/2119] lr: 4.0000e-03 eta: 4:07:47 time: 0.3407 data_time: 0.0239 memory: 5826 grad_norm: 4.8813 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8111 loss: 1.8111 2022/10/08 10:49:50 - mmengine - INFO - Epoch(train) [130][1820/2119] lr: 4.0000e-03 eta: 4:07:40 time: 0.4071 data_time: 0.0300 memory: 5826 grad_norm: 4.9844 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8941 loss: 1.8941 2022/10/08 10:49:56 - mmengine - INFO - Epoch(train) [130][1840/2119] lr: 4.0000e-03 eta: 4:07:33 time: 0.2987 data_time: 0.0253 memory: 5826 grad_norm: 4.8655 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.1670 loss: 2.1670 2022/10/08 10:50:03 - mmengine - INFO - Epoch(train) [130][1860/2119] lr: 4.0000e-03 eta: 4:07:26 time: 0.3772 data_time: 0.0211 memory: 5826 grad_norm: 4.9215 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0099 loss: 2.0099 2022/10/08 10:50:14 - mmengine - INFO - Epoch(train) [130][1880/2119] lr: 4.0000e-03 eta: 4:07:20 time: 0.5511 data_time: 0.0269 memory: 5826 grad_norm: 4.9820 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1161 loss: 2.1161 2022/10/08 10:50:21 - mmengine - INFO - Epoch(train) [130][1900/2119] lr: 4.0000e-03 eta: 4:07:13 time: 0.3071 data_time: 0.0241 memory: 5826 grad_norm: 4.8774 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.8606 loss: 1.8606 2022/10/08 10:50:28 - mmengine - INFO - Epoch(train) [130][1920/2119] lr: 4.0000e-03 eta: 4:07:06 time: 0.3529 data_time: 0.0212 memory: 5826 grad_norm: 4.8621 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0767 loss: 2.0767 2022/10/08 10:50:33 - mmengine - INFO - Epoch(train) [130][1940/2119] lr: 4.0000e-03 eta: 4:06:59 time: 0.2639 data_time: 0.0273 memory: 5826 grad_norm: 4.9769 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0732 loss: 2.0732 2022/10/08 10:50:41 - mmengine - INFO - Epoch(train) [130][1960/2119] lr: 4.0000e-03 eta: 4:06:52 time: 0.3948 data_time: 0.0215 memory: 5826 grad_norm: 4.9261 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.9186 loss: 1.9186 2022/10/08 10:50:48 - mmengine - INFO - Epoch(train) [130][1980/2119] lr: 4.0000e-03 eta: 4:06:45 time: 0.3761 data_time: 0.0221 memory: 5826 grad_norm: 4.9174 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9399 loss: 1.9399 2022/10/08 10:50:55 - mmengine - INFO - Epoch(train) [130][2000/2119] lr: 4.0000e-03 eta: 4:06:38 time: 0.3267 data_time: 0.0199 memory: 5826 grad_norm: 5.0425 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0375 loss: 2.0375 2022/10/08 10:51:02 - mmengine - INFO - Epoch(train) [130][2020/2119] lr: 4.0000e-03 eta: 4:06:31 time: 0.3497 data_time: 0.0220 memory: 5826 grad_norm: 4.9550 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0598 loss: 2.0598 2022/10/08 10:51:09 - mmengine - INFO - Epoch(train) [130][2040/2119] lr: 4.0000e-03 eta: 4:06:24 time: 0.3531 data_time: 0.0245 memory: 5826 grad_norm: 4.9550 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8374 loss: 1.8374 2022/10/08 10:51:16 - mmengine - INFO - Epoch(train) [130][2060/2119] lr: 4.0000e-03 eta: 4:06:17 time: 0.3489 data_time: 0.0227 memory: 5826 grad_norm: 4.9892 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0040 loss: 2.0040 2022/10/08 10:51:23 - mmengine - INFO - Epoch(train) [130][2080/2119] lr: 4.0000e-03 eta: 4:06:10 time: 0.3604 data_time: 0.0208 memory: 5826 grad_norm: 4.9531 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9831 loss: 1.9831 2022/10/08 10:51:30 - mmengine - INFO - Epoch(train) [130][2100/2119] lr: 4.0000e-03 eta: 4:06:03 time: 0.3157 data_time: 0.0247 memory: 5826 grad_norm: 4.9405 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0343 loss: 2.0343 2022/10/08 10:51:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 10:51:36 - mmengine - INFO - Epoch(train) [130][2119/2119] lr: 4.0000e-03 eta: 4:06:03 time: 0.3227 data_time: 0.0203 memory: 5826 grad_norm: 4.9635 top1_acc: 0.3000 top5_acc: 0.6000 loss_cls: 1.8630 loss: 1.8630 2022/10/08 10:51:44 - mmengine - INFO - Epoch(val) [130][20/137] eta: 0:00:50 time: 0.4334 data_time: 0.3631 memory: 1241 2022/10/08 10:51:51 - mmengine - INFO - Epoch(val) [130][40/137] eta: 0:00:32 time: 0.3304 data_time: 0.2641 memory: 1241 2022/10/08 10:51:58 - mmengine - INFO - Epoch(val) [130][60/137] eta: 0:00:26 time: 0.3386 data_time: 0.2731 memory: 1241 2022/10/08 10:52:03 - mmengine - INFO - Epoch(val) [130][80/137] eta: 0:00:14 time: 0.2592 data_time: 0.1917 memory: 1241 2022/10/08 10:52:11 - mmengine - INFO - Epoch(val) [130][100/137] eta: 0:00:13 time: 0.3738 data_time: 0.3079 memory: 1241 2022/10/08 10:52:15 - mmengine - INFO - Epoch(val) [130][120/137] eta: 0:00:04 time: 0.2459 data_time: 0.1801 memory: 1241 2022/10/08 10:52:26 - mmengine - INFO - Epoch(val) [130][137/137] acc/top1: 0.5404 acc/top5: 0.7684 acc/mean1: 0.5403 2022/10/08 10:52:35 - mmengine - INFO - Epoch(train) [131][20/2119] lr: 4.0000e-03 eta: 4:05:49 time: 0.4530 data_time: 0.1220 memory: 5826 grad_norm: 4.8852 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9115 loss: 1.9115 2022/10/08 10:52:42 - mmengine - INFO - Epoch(train) [131][40/2119] lr: 4.0000e-03 eta: 4:05:42 time: 0.3391 data_time: 0.0176 memory: 5826 grad_norm: 4.9792 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9148 loss: 1.9148 2022/10/08 10:52:49 - mmengine - INFO - Epoch(train) [131][60/2119] lr: 4.0000e-03 eta: 4:05:35 time: 0.3274 data_time: 0.0229 memory: 5826 grad_norm: 4.8755 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9718 loss: 1.9718 2022/10/08 10:52:56 - mmengine - INFO - Epoch(train) [131][80/2119] lr: 4.0000e-03 eta: 4:05:28 time: 0.3511 data_time: 0.0232 memory: 5826 grad_norm: 4.9724 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8827 loss: 1.8827 2022/10/08 10:53:03 - mmengine - INFO - Epoch(train) [131][100/2119] lr: 4.0000e-03 eta: 4:05:21 time: 0.3500 data_time: 0.0247 memory: 5826 grad_norm: 4.9211 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8016 loss: 1.8016 2022/10/08 10:53:10 - mmengine - INFO - Epoch(train) [131][120/2119] lr: 4.0000e-03 eta: 4:05:14 time: 0.3488 data_time: 0.0203 memory: 5826 grad_norm: 4.8698 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7623 loss: 1.7623 2022/10/08 10:53:16 - mmengine - INFO - Epoch(train) [131][140/2119] lr: 4.0000e-03 eta: 4:05:07 time: 0.3305 data_time: 0.0268 memory: 5826 grad_norm: 4.9095 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8356 loss: 1.8356 2022/10/08 10:53:24 - mmengine - INFO - Epoch(train) [131][160/2119] lr: 4.0000e-03 eta: 4:05:00 time: 0.4029 data_time: 0.0239 memory: 5826 grad_norm: 4.9620 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.8416 loss: 1.8416 2022/10/08 10:53:31 - mmengine - INFO - Epoch(train) [131][180/2119] lr: 4.0000e-03 eta: 4:04:53 time: 0.3217 data_time: 0.0231 memory: 5826 grad_norm: 4.8990 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9971 loss: 1.9971 2022/10/08 10:53:38 - mmengine - INFO - Epoch(train) [131][200/2119] lr: 4.0000e-03 eta: 4:04:46 time: 0.3394 data_time: 0.0267 memory: 5826 grad_norm: 4.8710 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0790 loss: 2.0790 2022/10/08 10:53:44 - mmengine - INFO - Epoch(train) [131][220/2119] lr: 4.0000e-03 eta: 4:04:39 time: 0.3465 data_time: 0.0216 memory: 5826 grad_norm: 4.7900 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8899 loss: 1.8899 2022/10/08 10:53:51 - mmengine - INFO - Epoch(train) [131][240/2119] lr: 4.0000e-03 eta: 4:04:32 time: 0.3228 data_time: 0.0191 memory: 5826 grad_norm: 4.9129 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.7920 loss: 1.7920 2022/10/08 10:53:58 - mmengine - INFO - Epoch(train) [131][260/2119] lr: 4.0000e-03 eta: 4:04:25 time: 0.3599 data_time: 0.0222 memory: 5826 grad_norm: 4.9268 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0184 loss: 2.0184 2022/10/08 10:54:05 - mmengine - INFO - Epoch(train) [131][280/2119] lr: 4.0000e-03 eta: 4:04:18 time: 0.3608 data_time: 0.0210 memory: 5826 grad_norm: 4.9303 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9096 loss: 1.9096 2022/10/08 10:54:12 - mmengine - INFO - Epoch(train) [131][300/2119] lr: 4.0000e-03 eta: 4:04:11 time: 0.3378 data_time: 0.0211 memory: 5826 grad_norm: 4.9067 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8804 loss: 1.8804 2022/10/08 10:54:19 - mmengine - INFO - Epoch(train) [131][320/2119] lr: 4.0000e-03 eta: 4:04:04 time: 0.3601 data_time: 0.0260 memory: 5826 grad_norm: 4.8745 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8186 loss: 1.8186 2022/10/08 10:54:26 - mmengine - INFO - Epoch(train) [131][340/2119] lr: 4.0000e-03 eta: 4:03:57 time: 0.3291 data_time: 0.0206 memory: 5826 grad_norm: 4.9403 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7607 loss: 1.7607 2022/10/08 10:54:33 - mmengine - INFO - Epoch(train) [131][360/2119] lr: 4.0000e-03 eta: 4:03:50 time: 0.3504 data_time: 0.0248 memory: 5826 grad_norm: 4.9088 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8216 loss: 1.8216 2022/10/08 10:54:39 - mmengine - INFO - Epoch(train) [131][380/2119] lr: 4.0000e-03 eta: 4:03:43 time: 0.3144 data_time: 0.0259 memory: 5826 grad_norm: 5.0240 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8829 loss: 1.8829 2022/10/08 10:54:46 - mmengine - INFO - Epoch(train) [131][400/2119] lr: 4.0000e-03 eta: 4:03:36 time: 0.3595 data_time: 0.0211 memory: 5826 grad_norm: 4.8799 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8443 loss: 1.8443 2022/10/08 10:54:53 - mmengine - INFO - Epoch(train) [131][420/2119] lr: 4.0000e-03 eta: 4:03:29 time: 0.3382 data_time: 0.0175 memory: 5826 grad_norm: 4.9140 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9764 loss: 1.9764 2022/10/08 10:55:00 - mmengine - INFO - Epoch(train) [131][440/2119] lr: 4.0000e-03 eta: 4:03:22 time: 0.3343 data_time: 0.0271 memory: 5826 grad_norm: 4.9004 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0802 loss: 2.0802 2022/10/08 10:55:06 - mmengine - INFO - Epoch(train) [131][460/2119] lr: 4.0000e-03 eta: 4:03:15 time: 0.3263 data_time: 0.0207 memory: 5826 grad_norm: 4.8239 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7832 loss: 1.7832 2022/10/08 10:55:14 - mmengine - INFO - Epoch(train) [131][480/2119] lr: 4.0000e-03 eta: 4:03:08 time: 0.3837 data_time: 0.0180 memory: 5826 grad_norm: 4.8449 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9256 loss: 1.9256 2022/10/08 10:55:21 - mmengine - INFO - Epoch(train) [131][500/2119] lr: 4.0000e-03 eta: 4:03:01 time: 0.3422 data_time: 0.0276 memory: 5826 grad_norm: 4.8242 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9085 loss: 1.9085 2022/10/08 10:55:28 - mmengine - INFO - Epoch(train) [131][520/2119] lr: 4.0000e-03 eta: 4:02:54 time: 0.3735 data_time: 0.0239 memory: 5826 grad_norm: 4.9039 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9082 loss: 1.9082 2022/10/08 10:55:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 10:55:34 - mmengine - INFO - Epoch(train) [131][540/2119] lr: 4.0000e-03 eta: 4:02:47 time: 0.2868 data_time: 0.0240 memory: 5826 grad_norm: 5.0055 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0814 loss: 2.0814 2022/10/08 10:55:43 - mmengine - INFO - Epoch(train) [131][560/2119] lr: 4.0000e-03 eta: 4:02:41 time: 0.4150 data_time: 0.0244 memory: 5826 grad_norm: 4.9260 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0166 loss: 2.0166 2022/10/08 10:55:49 - mmengine - INFO - Epoch(train) [131][580/2119] lr: 4.0000e-03 eta: 4:02:33 time: 0.3105 data_time: 0.0199 memory: 5826 grad_norm: 5.0036 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 1.9626 loss: 1.9626 2022/10/08 10:55:55 - mmengine - INFO - Epoch(train) [131][600/2119] lr: 4.0000e-03 eta: 4:02:26 time: 0.3284 data_time: 0.0220 memory: 5826 grad_norm: 4.9161 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1862 loss: 2.1862 2022/10/08 10:56:02 - mmengine - INFO - Epoch(train) [131][620/2119] lr: 4.0000e-03 eta: 4:02:19 time: 0.3406 data_time: 0.0246 memory: 5826 grad_norm: 4.9010 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8943 loss: 1.8943 2022/10/08 10:56:10 - mmengine - INFO - Epoch(train) [131][640/2119] lr: 4.0000e-03 eta: 4:02:13 time: 0.3793 data_time: 0.0205 memory: 5826 grad_norm: 4.8777 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8944 loss: 1.8944 2022/10/08 10:56:16 - mmengine - INFO - Epoch(train) [131][660/2119] lr: 4.0000e-03 eta: 4:02:05 time: 0.2922 data_time: 0.0253 memory: 5826 grad_norm: 4.9046 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9805 loss: 1.9805 2022/10/08 10:56:24 - mmengine - INFO - Epoch(train) [131][680/2119] lr: 4.0000e-03 eta: 4:01:59 time: 0.4111 data_time: 0.0226 memory: 5826 grad_norm: 4.9387 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0771 loss: 2.0771 2022/10/08 10:56:31 - mmengine - INFO - Epoch(train) [131][700/2119] lr: 4.0000e-03 eta: 4:01:52 time: 0.3349 data_time: 0.0211 memory: 5826 grad_norm: 4.9927 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8788 loss: 1.8788 2022/10/08 10:56:38 - mmengine - INFO - Epoch(train) [131][720/2119] lr: 4.0000e-03 eta: 4:01:45 time: 0.3757 data_time: 0.0228 memory: 5826 grad_norm: 4.9251 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9836 loss: 1.9836 2022/10/08 10:56:43 - mmengine - INFO - Epoch(train) [131][740/2119] lr: 4.0000e-03 eta: 4:01:38 time: 0.2643 data_time: 0.0220 memory: 5826 grad_norm: 4.8377 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7631 loss: 1.7631 2022/10/08 10:56:50 - mmengine - INFO - Epoch(train) [131][760/2119] lr: 4.0000e-03 eta: 4:01:31 time: 0.3329 data_time: 0.0198 memory: 5826 grad_norm: 4.9480 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7707 loss: 1.7707 2022/10/08 10:56:56 - mmengine - INFO - Epoch(train) [131][780/2119] lr: 4.0000e-03 eta: 4:01:24 time: 0.3185 data_time: 0.0254 memory: 5826 grad_norm: 5.1663 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1759 loss: 2.1759 2022/10/08 10:57:05 - mmengine - INFO - Epoch(train) [131][800/2119] lr: 4.0000e-03 eta: 4:01:17 time: 0.4086 data_time: 0.0217 memory: 5826 grad_norm: 4.9803 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0281 loss: 2.0281 2022/10/08 10:57:11 - mmengine - INFO - Epoch(train) [131][820/2119] lr: 4.0000e-03 eta: 4:01:10 time: 0.3201 data_time: 0.0241 memory: 5826 grad_norm: 4.9331 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.7574 loss: 1.7574 2022/10/08 10:57:18 - mmengine - INFO - Epoch(train) [131][840/2119] lr: 4.0000e-03 eta: 4:01:03 time: 0.3339 data_time: 0.0222 memory: 5826 grad_norm: 5.0272 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8518 loss: 1.8518 2022/10/08 10:57:25 - mmengine - INFO - Epoch(train) [131][860/2119] lr: 4.0000e-03 eta: 4:00:56 time: 0.3548 data_time: 0.0254 memory: 5826 grad_norm: 4.8809 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7860 loss: 1.7860 2022/10/08 10:57:32 - mmengine - INFO - Epoch(train) [131][880/2119] lr: 4.0000e-03 eta: 4:00:49 time: 0.3601 data_time: 0.0182 memory: 5826 grad_norm: 4.9565 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0535 loss: 2.0535 2022/10/08 10:57:38 - mmengine - INFO - Epoch(train) [131][900/2119] lr: 4.0000e-03 eta: 4:00:42 time: 0.3023 data_time: 0.0307 memory: 5826 grad_norm: 4.9676 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1966 loss: 2.1966 2022/10/08 10:57:45 - mmengine - INFO - Epoch(train) [131][920/2119] lr: 4.0000e-03 eta: 4:00:35 time: 0.3431 data_time: 0.0249 memory: 5826 grad_norm: 4.8107 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9147 loss: 1.9147 2022/10/08 10:57:53 - mmengine - INFO - Epoch(train) [131][940/2119] lr: 4.0000e-03 eta: 4:00:28 time: 0.3854 data_time: 0.0273 memory: 5826 grad_norm: 4.9516 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.0252 loss: 2.0252 2022/10/08 10:58:00 - mmengine - INFO - Epoch(train) [131][960/2119] lr: 4.0000e-03 eta: 4:00:21 time: 0.3623 data_time: 0.0218 memory: 5826 grad_norm: 4.9991 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9064 loss: 1.9064 2022/10/08 10:58:07 - mmengine - INFO - Epoch(train) [131][980/2119] lr: 4.0000e-03 eta: 4:00:14 time: 0.3534 data_time: 0.0195 memory: 5826 grad_norm: 4.9039 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.8558 loss: 1.8558 2022/10/08 10:58:14 - mmengine - INFO - Epoch(train) [131][1000/2119] lr: 4.0000e-03 eta: 4:00:07 time: 0.3499 data_time: 0.0229 memory: 5826 grad_norm: 4.9189 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9678 loss: 1.9678 2022/10/08 10:58:21 - mmengine - INFO - Epoch(train) [131][1020/2119] lr: 4.0000e-03 eta: 4:00:00 time: 0.3531 data_time: 0.0215 memory: 5826 grad_norm: 4.9750 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9605 loss: 1.9605 2022/10/08 10:58:28 - mmengine - INFO - Epoch(train) [131][1040/2119] lr: 4.0000e-03 eta: 3:59:53 time: 0.3350 data_time: 0.0201 memory: 5826 grad_norm: 4.8411 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7788 loss: 1.7788 2022/10/08 10:58:34 - mmengine - INFO - Epoch(train) [131][1060/2119] lr: 4.0000e-03 eta: 3:59:46 time: 0.3139 data_time: 0.0261 memory: 5826 grad_norm: 4.9788 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9164 loss: 1.9164 2022/10/08 10:58:41 - mmengine - INFO - Epoch(train) [131][1080/2119] lr: 4.0000e-03 eta: 3:59:39 time: 0.3720 data_time: 0.0165 memory: 5826 grad_norm: 4.9185 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8471 loss: 1.8471 2022/10/08 10:58:47 - mmengine - INFO - Epoch(train) [131][1100/2119] lr: 4.0000e-03 eta: 3:59:32 time: 0.2797 data_time: 0.0225 memory: 5826 grad_norm: 5.0000 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9892 loss: 1.9892 2022/10/08 10:58:54 - mmengine - INFO - Epoch(train) [131][1120/2119] lr: 4.0000e-03 eta: 3:59:25 time: 0.3640 data_time: 0.0242 memory: 5826 grad_norm: 4.9848 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0135 loss: 2.0135 2022/10/08 10:59:01 - mmengine - INFO - Epoch(train) [131][1140/2119] lr: 4.0000e-03 eta: 3:59:18 time: 0.3380 data_time: 0.0235 memory: 5826 grad_norm: 4.9062 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.9605 loss: 1.9605 2022/10/08 10:59:09 - mmengine - INFO - Epoch(train) [131][1160/2119] lr: 4.0000e-03 eta: 3:59:11 time: 0.3772 data_time: 0.0188 memory: 5826 grad_norm: 4.9704 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1093 loss: 2.1093 2022/10/08 10:59:15 - mmengine - INFO - Epoch(train) [131][1180/2119] lr: 4.0000e-03 eta: 3:59:04 time: 0.3130 data_time: 0.0214 memory: 5826 grad_norm: 4.8754 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9297 loss: 1.9297 2022/10/08 10:59:23 - mmengine - INFO - Epoch(train) [131][1200/2119] lr: 4.0000e-03 eta: 3:58:57 time: 0.3965 data_time: 0.0175 memory: 5826 grad_norm: 4.9521 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.8187 loss: 1.8187 2022/10/08 10:59:29 - mmengine - INFO - Epoch(train) [131][1220/2119] lr: 4.0000e-03 eta: 3:58:50 time: 0.3181 data_time: 0.0243 memory: 5826 grad_norm: 5.0215 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0388 loss: 2.0388 2022/10/08 10:59:37 - mmengine - INFO - Epoch(train) [131][1240/2119] lr: 4.0000e-03 eta: 3:58:43 time: 0.3700 data_time: 0.0277 memory: 5826 grad_norm: 4.9604 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0074 loss: 2.0074 2022/10/08 10:59:44 - mmengine - INFO - Epoch(train) [131][1260/2119] lr: 4.0000e-03 eta: 3:58:36 time: 0.3420 data_time: 0.0271 memory: 5826 grad_norm: 4.9876 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9014 loss: 1.9014 2022/10/08 10:59:51 - mmengine - INFO - Epoch(train) [131][1280/2119] lr: 4.0000e-03 eta: 3:58:29 time: 0.3600 data_time: 0.0198 memory: 5826 grad_norm: 5.0216 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0304 loss: 2.0304 2022/10/08 10:59:57 - mmengine - INFO - Epoch(train) [131][1300/2119] lr: 4.0000e-03 eta: 3:58:22 time: 0.3139 data_time: 0.0238 memory: 5826 grad_norm: 5.0232 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.0697 loss: 2.0697 2022/10/08 11:00:05 - mmengine - INFO - Epoch(train) [131][1320/2119] lr: 4.0000e-03 eta: 3:58:16 time: 0.4022 data_time: 0.0210 memory: 5826 grad_norm: 4.9067 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9349 loss: 1.9349 2022/10/08 11:00:11 - mmengine - INFO - Epoch(train) [131][1340/2119] lr: 4.0000e-03 eta: 3:58:08 time: 0.3131 data_time: 0.0229 memory: 5826 grad_norm: 5.0901 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.8467 loss: 1.8467 2022/10/08 11:00:20 - mmengine - INFO - Epoch(train) [131][1360/2119] lr: 4.0000e-03 eta: 3:58:02 time: 0.4180 data_time: 0.0219 memory: 5826 grad_norm: 5.0149 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9839 loss: 1.9839 2022/10/08 11:00:26 - mmengine - INFO - Epoch(train) [131][1380/2119] lr: 4.0000e-03 eta: 3:57:55 time: 0.3143 data_time: 0.0205 memory: 5826 grad_norm: 4.9896 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8726 loss: 1.8726 2022/10/08 11:00:34 - mmengine - INFO - Epoch(train) [131][1400/2119] lr: 4.0000e-03 eta: 3:57:48 time: 0.3980 data_time: 0.0180 memory: 5826 grad_norm: 4.9472 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.2069 loss: 2.2069 2022/10/08 11:00:40 - mmengine - INFO - Epoch(train) [131][1420/2119] lr: 4.0000e-03 eta: 3:57:41 time: 0.2997 data_time: 0.0270 memory: 5826 grad_norm: 4.9536 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1180 loss: 2.1180 2022/10/08 11:00:48 - mmengine - INFO - Epoch(train) [131][1440/2119] lr: 4.0000e-03 eta: 3:57:34 time: 0.3964 data_time: 0.0198 memory: 5826 grad_norm: 4.8765 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2234 loss: 2.2234 2022/10/08 11:00:54 - mmengine - INFO - Epoch(train) [131][1460/2119] lr: 4.0000e-03 eta: 3:57:27 time: 0.2940 data_time: 0.0244 memory: 5826 grad_norm: 4.9147 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8958 loss: 1.8958 2022/10/08 11:01:01 - mmengine - INFO - Epoch(train) [131][1480/2119] lr: 4.0000e-03 eta: 3:57:20 time: 0.3600 data_time: 0.0200 memory: 5826 grad_norm: 5.0620 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.0674 loss: 2.0674 2022/10/08 11:01:08 - mmengine - INFO - Epoch(train) [131][1500/2119] lr: 4.0000e-03 eta: 3:57:13 time: 0.3457 data_time: 0.0245 memory: 5826 grad_norm: 4.9043 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7456 loss: 1.7456 2022/10/08 11:01:16 - mmengine - INFO - Epoch(train) [131][1520/2119] lr: 4.0000e-03 eta: 3:57:06 time: 0.3797 data_time: 0.0226 memory: 5826 grad_norm: 4.9575 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2031 loss: 2.2031 2022/10/08 11:01:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 11:01:22 - mmengine - INFO - Epoch(train) [131][1540/2119] lr: 4.0000e-03 eta: 3:56:59 time: 0.3126 data_time: 0.0271 memory: 5826 grad_norm: 4.9998 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8818 loss: 1.8818 2022/10/08 11:01:29 - mmengine - INFO - Epoch(train) [131][1560/2119] lr: 4.0000e-03 eta: 3:56:52 time: 0.3410 data_time: 0.0200 memory: 5826 grad_norm: 5.0027 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1293 loss: 2.1293 2022/10/08 11:01:35 - mmengine - INFO - Epoch(train) [131][1580/2119] lr: 4.0000e-03 eta: 3:56:45 time: 0.3240 data_time: 0.0230 memory: 5826 grad_norm: 4.9524 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0624 loss: 2.0624 2022/10/08 11:01:43 - mmengine - INFO - Epoch(train) [131][1600/2119] lr: 4.0000e-03 eta: 3:56:38 time: 0.3768 data_time: 0.0247 memory: 5826 grad_norm: 5.0236 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0728 loss: 2.0728 2022/10/08 11:01:49 - mmengine - INFO - Epoch(train) [131][1620/2119] lr: 4.0000e-03 eta: 3:56:31 time: 0.3192 data_time: 0.0216 memory: 5826 grad_norm: 4.9202 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1954 loss: 2.1954 2022/10/08 11:01:57 - mmengine - INFO - Epoch(train) [131][1640/2119] lr: 4.0000e-03 eta: 3:56:24 time: 0.3782 data_time: 0.0222 memory: 5826 grad_norm: 4.9288 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8101 loss: 1.8101 2022/10/08 11:02:04 - mmengine - INFO - Epoch(train) [131][1660/2119] lr: 4.0000e-03 eta: 3:56:17 time: 0.3481 data_time: 0.0228 memory: 5826 grad_norm: 4.9532 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.9845 loss: 1.9845 2022/10/08 11:02:10 - mmengine - INFO - Epoch(train) [131][1680/2119] lr: 4.0000e-03 eta: 3:56:10 time: 0.3434 data_time: 0.0172 memory: 5826 grad_norm: 4.9461 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0310 loss: 2.0310 2022/10/08 11:02:17 - mmengine - INFO - Epoch(train) [131][1700/2119] lr: 4.0000e-03 eta: 3:56:03 time: 0.3102 data_time: 0.0268 memory: 5826 grad_norm: 5.0519 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9977 loss: 1.9977 2022/10/08 11:02:25 - mmengine - INFO - Epoch(train) [131][1720/2119] lr: 4.0000e-03 eta: 3:55:56 time: 0.4331 data_time: 0.0250 memory: 5826 grad_norm: 4.9559 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9339 loss: 1.9339 2022/10/08 11:02:32 - mmengine - INFO - Epoch(train) [131][1740/2119] lr: 4.0000e-03 eta: 3:55:49 time: 0.3108 data_time: 0.0203 memory: 5826 grad_norm: 4.9496 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.7757 loss: 1.7757 2022/10/08 11:02:38 - mmengine - INFO - Epoch(train) [131][1760/2119] lr: 4.0000e-03 eta: 3:55:42 time: 0.3451 data_time: 0.0227 memory: 5826 grad_norm: 4.9888 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9209 loss: 1.9209 2022/10/08 11:02:45 - mmengine - INFO - Epoch(train) [131][1780/2119] lr: 4.0000e-03 eta: 3:55:35 time: 0.3264 data_time: 0.0212 memory: 5826 grad_norm: 5.0104 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1132 loss: 2.1132 2022/10/08 11:02:52 - mmengine - INFO - Epoch(train) [131][1800/2119] lr: 4.0000e-03 eta: 3:55:28 time: 0.3397 data_time: 0.0202 memory: 5826 grad_norm: 5.0079 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9025 loss: 1.9025 2022/10/08 11:02:58 - mmengine - INFO - Epoch(train) [131][1820/2119] lr: 4.0000e-03 eta: 3:55:21 time: 0.3280 data_time: 0.0219 memory: 5826 grad_norm: 5.0379 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0643 loss: 2.0643 2022/10/08 11:03:05 - mmengine - INFO - Epoch(train) [131][1840/2119] lr: 4.0000e-03 eta: 3:55:14 time: 0.3446 data_time: 0.0224 memory: 5826 grad_norm: 5.0068 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8860 loss: 1.8860 2022/10/08 11:03:11 - mmengine - INFO - Epoch(train) [131][1860/2119] lr: 4.0000e-03 eta: 3:55:07 time: 0.3003 data_time: 0.0299 memory: 5826 grad_norm: 4.9476 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0498 loss: 2.0498 2022/10/08 11:03:18 - mmengine - INFO - Epoch(train) [131][1880/2119] lr: 4.0000e-03 eta: 3:55:00 time: 0.3392 data_time: 0.0193 memory: 5826 grad_norm: 4.9364 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0799 loss: 2.0799 2022/10/08 11:03:25 - mmengine - INFO - Epoch(train) [131][1900/2119] lr: 4.0000e-03 eta: 3:54:53 time: 0.3634 data_time: 0.0210 memory: 5826 grad_norm: 4.9245 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9313 loss: 1.9313 2022/10/08 11:03:32 - mmengine - INFO - Epoch(train) [131][1920/2119] lr: 4.0000e-03 eta: 3:54:46 time: 0.3453 data_time: 0.0227 memory: 5826 grad_norm: 5.0233 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7701 loss: 1.7701 2022/10/08 11:03:40 - mmengine - INFO - Epoch(train) [131][1940/2119] lr: 4.0000e-03 eta: 3:54:39 time: 0.3602 data_time: 0.0239 memory: 5826 grad_norm: 5.0333 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.8086 loss: 1.8086 2022/10/08 11:03:47 - mmengine - INFO - Epoch(train) [131][1960/2119] lr: 4.0000e-03 eta: 3:54:33 time: 0.3605 data_time: 0.0226 memory: 5826 grad_norm: 5.0017 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9320 loss: 1.9320 2022/10/08 11:03:54 - mmengine - INFO - Epoch(train) [131][1980/2119] lr: 4.0000e-03 eta: 3:54:26 time: 0.3415 data_time: 0.0197 memory: 5826 grad_norm: 4.9051 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9613 loss: 1.9613 2022/10/08 11:04:01 - mmengine - INFO - Epoch(train) [131][2000/2119] lr: 4.0000e-03 eta: 3:54:19 time: 0.3710 data_time: 0.0214 memory: 5826 grad_norm: 5.0282 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1317 loss: 2.1317 2022/10/08 11:04:07 - mmengine - INFO - Epoch(train) [131][2020/2119] lr: 4.0000e-03 eta: 3:54:12 time: 0.3132 data_time: 0.0225 memory: 5826 grad_norm: 5.0793 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0072 loss: 2.0072 2022/10/08 11:04:16 - mmengine - INFO - Epoch(train) [131][2040/2119] lr: 4.0000e-03 eta: 3:54:05 time: 0.4115 data_time: 0.0167 memory: 5826 grad_norm: 5.0439 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9887 loss: 1.9887 2022/10/08 11:04:22 - mmengine - INFO - Epoch(train) [131][2060/2119] lr: 4.0000e-03 eta: 3:53:58 time: 0.3205 data_time: 0.0264 memory: 5826 grad_norm: 5.0244 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 1.8659 loss: 1.8659 2022/10/08 11:04:29 - mmengine - INFO - Epoch(train) [131][2080/2119] lr: 4.0000e-03 eta: 3:53:51 time: 0.3517 data_time: 0.0230 memory: 5826 grad_norm: 4.9905 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8962 loss: 1.8962 2022/10/08 11:04:35 - mmengine - INFO - Epoch(train) [131][2100/2119] lr: 4.0000e-03 eta: 3:53:44 time: 0.3086 data_time: 0.0266 memory: 5826 grad_norm: 4.9403 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0998 loss: 2.0998 2022/10/08 11:04:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 11:04:41 - mmengine - INFO - Epoch(train) [131][2119/2119] lr: 4.0000e-03 eta: 3:53:44 time: 0.3004 data_time: 0.0197 memory: 5826 grad_norm: 5.1728 top1_acc: 0.4000 top5_acc: 0.9000 loss_cls: 2.2293 loss: 2.2293 2022/10/08 11:04:50 - mmengine - INFO - Epoch(train) [132][20/2119] lr: 4.0000e-03 eta: 3:53:30 time: 0.4634 data_time: 0.1817 memory: 5826 grad_norm: 4.9413 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.8343 loss: 1.8343 2022/10/08 11:04:57 - mmengine - INFO - Epoch(train) [132][40/2119] lr: 4.0000e-03 eta: 3:53:23 time: 0.3483 data_time: 0.0164 memory: 5826 grad_norm: 4.9107 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9287 loss: 1.9287 2022/10/08 11:05:05 - mmengine - INFO - Epoch(train) [132][60/2119] lr: 4.0000e-03 eta: 3:53:16 time: 0.3692 data_time: 0.0237 memory: 5826 grad_norm: 5.0987 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9551 loss: 1.9551 2022/10/08 11:05:11 - mmengine - INFO - Epoch(train) [132][80/2119] lr: 4.0000e-03 eta: 3:53:09 time: 0.3115 data_time: 0.0249 memory: 5826 grad_norm: 4.9863 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9171 loss: 1.9171 2022/10/08 11:05:18 - mmengine - INFO - Epoch(train) [132][100/2119] lr: 4.0000e-03 eta: 3:53:02 time: 0.3375 data_time: 0.0227 memory: 5826 grad_norm: 4.9346 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9682 loss: 1.9682 2022/10/08 11:05:25 - mmengine - INFO - Epoch(train) [132][120/2119] lr: 4.0000e-03 eta: 3:52:55 time: 0.3517 data_time: 0.0177 memory: 5826 grad_norm: 4.9882 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8310 loss: 1.8310 2022/10/08 11:05:32 - mmengine - INFO - Epoch(train) [132][140/2119] lr: 4.0000e-03 eta: 3:52:48 time: 0.3569 data_time: 0.0275 memory: 5826 grad_norm: 4.9644 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8881 loss: 1.8881 2022/10/08 11:05:38 - mmengine - INFO - Epoch(train) [132][160/2119] lr: 4.0000e-03 eta: 3:52:41 time: 0.3082 data_time: 0.0221 memory: 5826 grad_norm: 4.8779 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0556 loss: 2.0556 2022/10/08 11:05:46 - mmengine - INFO - Epoch(train) [132][180/2119] lr: 4.0000e-03 eta: 3:52:34 time: 0.3842 data_time: 0.0222 memory: 5826 grad_norm: 4.9772 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0580 loss: 2.0580 2022/10/08 11:05:52 - mmengine - INFO - Epoch(train) [132][200/2119] lr: 4.0000e-03 eta: 3:52:27 time: 0.3106 data_time: 0.0266 memory: 5826 grad_norm: 5.0231 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1330 loss: 2.1330 2022/10/08 11:06:00 - mmengine - INFO - Epoch(train) [132][220/2119] lr: 4.0000e-03 eta: 3:52:20 time: 0.4045 data_time: 0.0194 memory: 5826 grad_norm: 5.0230 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8097 loss: 1.8097 2022/10/08 11:06:07 - mmengine - INFO - Epoch(train) [132][240/2119] lr: 4.0000e-03 eta: 3:52:13 time: 0.3263 data_time: 0.0186 memory: 5826 grad_norm: 5.0248 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9881 loss: 1.9881 2022/10/08 11:06:13 - mmengine - INFO - Epoch(train) [132][260/2119] lr: 4.0000e-03 eta: 3:52:06 time: 0.3035 data_time: 0.0244 memory: 5826 grad_norm: 5.0220 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9051 loss: 1.9051 2022/10/08 11:06:19 - mmengine - INFO - Epoch(train) [132][280/2119] lr: 4.0000e-03 eta: 3:51:59 time: 0.3355 data_time: 0.0215 memory: 5826 grad_norm: 5.0511 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0606 loss: 2.0606 2022/10/08 11:06:26 - mmengine - INFO - Epoch(train) [132][300/2119] lr: 4.0000e-03 eta: 3:51:52 time: 0.3364 data_time: 0.0284 memory: 5826 grad_norm: 5.0772 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.0230 loss: 2.0230 2022/10/08 11:06:33 - mmengine - INFO - Epoch(train) [132][320/2119] lr: 4.0000e-03 eta: 3:51:45 time: 0.3440 data_time: 0.0181 memory: 5826 grad_norm: 5.0708 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9419 loss: 1.9419 2022/10/08 11:06:40 - mmengine - INFO - Epoch(train) [132][340/2119] lr: 4.0000e-03 eta: 3:51:38 time: 0.3535 data_time: 0.0212 memory: 5826 grad_norm: 5.0373 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8401 loss: 1.8401 2022/10/08 11:06:47 - mmengine - INFO - Epoch(train) [132][360/2119] lr: 4.0000e-03 eta: 3:51:31 time: 0.3646 data_time: 0.0178 memory: 5826 grad_norm: 4.9384 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7198 loss: 1.7198 2022/10/08 11:06:53 - mmengine - INFO - Epoch(train) [132][380/2119] lr: 4.0000e-03 eta: 3:51:24 time: 0.2966 data_time: 0.0271 memory: 5826 grad_norm: 4.9911 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.9700 loss: 1.9700 2022/10/08 11:07:01 - mmengine - INFO - Epoch(train) [132][400/2119] lr: 4.0000e-03 eta: 3:51:17 time: 0.3599 data_time: 0.0179 memory: 5826 grad_norm: 5.0454 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0559 loss: 2.0559 2022/10/08 11:07:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 11:07:07 - mmengine - INFO - Epoch(train) [132][420/2119] lr: 4.0000e-03 eta: 3:51:10 time: 0.3371 data_time: 0.0218 memory: 5826 grad_norm: 4.9733 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.0050 loss: 2.0050 2022/10/08 11:07:15 - mmengine - INFO - Epoch(train) [132][440/2119] lr: 4.0000e-03 eta: 3:51:03 time: 0.3642 data_time: 0.0184 memory: 5826 grad_norm: 5.0948 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0338 loss: 2.0338 2022/10/08 11:07:22 - mmengine - INFO - Epoch(train) [132][460/2119] lr: 4.0000e-03 eta: 3:50:56 time: 0.3768 data_time: 0.0189 memory: 5826 grad_norm: 5.0168 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.0798 loss: 2.0798 2022/10/08 11:07:29 - mmengine - INFO - Epoch(train) [132][480/2119] lr: 4.0000e-03 eta: 3:50:49 time: 0.3562 data_time: 0.0192 memory: 5826 grad_norm: 5.0152 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8326 loss: 1.8326 2022/10/08 11:07:36 - mmengine - INFO - Epoch(train) [132][500/2119] lr: 4.0000e-03 eta: 3:50:42 time: 0.3230 data_time: 0.0260 memory: 5826 grad_norm: 4.9631 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.8340 loss: 1.8340 2022/10/08 11:07:44 - mmengine - INFO - Epoch(train) [132][520/2119] lr: 4.0000e-03 eta: 3:50:35 time: 0.3909 data_time: 0.0207 memory: 5826 grad_norm: 4.9287 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9428 loss: 1.9428 2022/10/08 11:07:50 - mmengine - INFO - Epoch(train) [132][540/2119] lr: 4.0000e-03 eta: 3:50:28 time: 0.3067 data_time: 0.0265 memory: 5826 grad_norm: 4.9498 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.7946 loss: 1.7946 2022/10/08 11:07:56 - mmengine - INFO - Epoch(train) [132][560/2119] lr: 4.0000e-03 eta: 3:50:21 time: 0.3101 data_time: 0.0200 memory: 5826 grad_norm: 4.9450 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8593 loss: 1.8593 2022/10/08 11:08:03 - mmengine - INFO - Epoch(train) [132][580/2119] lr: 4.0000e-03 eta: 3:50:14 time: 0.3317 data_time: 0.0258 memory: 5826 grad_norm: 4.9108 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.9127 loss: 1.9127 2022/10/08 11:08:10 - mmengine - INFO - Epoch(train) [132][600/2119] lr: 4.0000e-03 eta: 3:50:07 time: 0.3478 data_time: 0.0178 memory: 5826 grad_norm: 5.0311 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0043 loss: 2.0043 2022/10/08 11:08:16 - mmengine - INFO - Epoch(train) [132][620/2119] lr: 4.0000e-03 eta: 3:50:00 time: 0.3122 data_time: 0.0273 memory: 5826 grad_norm: 4.9590 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.8201 loss: 1.8201 2022/10/08 11:08:23 - mmengine - INFO - Epoch(train) [132][640/2119] lr: 4.0000e-03 eta: 3:49:53 time: 0.3684 data_time: 0.0194 memory: 5826 grad_norm: 5.1155 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0825 loss: 2.0825 2022/10/08 11:08:31 - mmengine - INFO - Epoch(train) [132][660/2119] lr: 4.0000e-03 eta: 3:49:46 time: 0.3791 data_time: 0.0242 memory: 5826 grad_norm: 4.9658 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.8758 loss: 1.8758 2022/10/08 11:08:37 - mmengine - INFO - Epoch(train) [132][680/2119] lr: 4.0000e-03 eta: 3:49:39 time: 0.3348 data_time: 0.0222 memory: 5826 grad_norm: 4.9814 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9612 loss: 1.9612 2022/10/08 11:08:44 - mmengine - INFO - Epoch(train) [132][700/2119] lr: 4.0000e-03 eta: 3:49:32 time: 0.3405 data_time: 0.0228 memory: 5826 grad_norm: 4.9551 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1459 loss: 2.1459 2022/10/08 11:08:51 - mmengine - INFO - Epoch(train) [132][720/2119] lr: 4.0000e-03 eta: 3:49:25 time: 0.3574 data_time: 0.0218 memory: 5826 grad_norm: 5.0401 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.7868 loss: 1.7868 2022/10/08 11:08:58 - mmengine - INFO - Epoch(train) [132][740/2119] lr: 4.0000e-03 eta: 3:49:18 time: 0.3257 data_time: 0.0168 memory: 5826 grad_norm: 4.9444 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 1.9650 loss: 1.9650 2022/10/08 11:09:06 - mmengine - INFO - Epoch(train) [132][760/2119] lr: 4.0000e-03 eta: 3:49:12 time: 0.3939 data_time: 0.0191 memory: 5826 grad_norm: 4.9647 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9709 loss: 1.9709 2022/10/08 11:09:12 - mmengine - INFO - Epoch(train) [132][780/2119] lr: 4.0000e-03 eta: 3:49:04 time: 0.3062 data_time: 0.0234 memory: 5826 grad_norm: 4.9905 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1260 loss: 2.1260 2022/10/08 11:09:19 - mmengine - INFO - Epoch(train) [132][800/2119] lr: 4.0000e-03 eta: 3:48:57 time: 0.3448 data_time: 0.0214 memory: 5826 grad_norm: 4.9995 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.7021 loss: 1.7021 2022/10/08 11:09:26 - mmengine - INFO - Epoch(train) [132][820/2119] lr: 4.0000e-03 eta: 3:48:50 time: 0.3331 data_time: 0.0224 memory: 5826 grad_norm: 4.9390 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9844 loss: 1.9844 2022/10/08 11:09:33 - mmengine - INFO - Epoch(train) [132][840/2119] lr: 4.0000e-03 eta: 3:48:44 time: 0.3809 data_time: 0.0187 memory: 5826 grad_norm: 5.0083 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8764 loss: 1.8764 2022/10/08 11:09:40 - mmengine - INFO - Epoch(train) [132][860/2119] lr: 4.0000e-03 eta: 3:48:37 time: 0.3496 data_time: 0.0223 memory: 5826 grad_norm: 4.9319 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0561 loss: 2.0561 2022/10/08 11:09:47 - mmengine - INFO - Epoch(train) [132][880/2119] lr: 4.0000e-03 eta: 3:48:30 time: 0.3516 data_time: 0.0159 memory: 5826 grad_norm: 4.9387 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.8793 loss: 1.8793 2022/10/08 11:09:54 - mmengine - INFO - Epoch(train) [132][900/2119] lr: 4.0000e-03 eta: 3:48:23 time: 0.3248 data_time: 0.0254 memory: 5826 grad_norm: 4.9428 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 2.0327 loss: 2.0327 2022/10/08 11:10:01 - mmengine - INFO - Epoch(train) [132][920/2119] lr: 4.0000e-03 eta: 3:48:16 time: 0.3579 data_time: 0.0150 memory: 5826 grad_norm: 4.9993 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0483 loss: 2.0483 2022/10/08 11:10:07 - mmengine - INFO - Epoch(train) [132][940/2119] lr: 4.0000e-03 eta: 3:48:09 time: 0.2851 data_time: 0.0271 memory: 5826 grad_norm: 5.0628 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.9323 loss: 1.9323 2022/10/08 11:10:14 - mmengine - INFO - Epoch(train) [132][960/2119] lr: 4.0000e-03 eta: 3:48:02 time: 0.3805 data_time: 0.0218 memory: 5826 grad_norm: 5.0581 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8471 loss: 1.8471 2022/10/08 11:10:22 - mmengine - INFO - Epoch(train) [132][980/2119] lr: 4.0000e-03 eta: 3:47:55 time: 0.3839 data_time: 0.0226 memory: 5826 grad_norm: 5.0457 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1864 loss: 2.1864 2022/10/08 11:10:29 - mmengine - INFO - Epoch(train) [132][1000/2119] lr: 4.0000e-03 eta: 3:47:48 time: 0.3665 data_time: 0.0216 memory: 5826 grad_norm: 5.0110 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8765 loss: 1.8765 2022/10/08 11:10:36 - mmengine - INFO - Epoch(train) [132][1020/2119] lr: 4.0000e-03 eta: 3:47:41 time: 0.3116 data_time: 0.0206 memory: 5826 grad_norm: 4.9949 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9241 loss: 1.9241 2022/10/08 11:10:43 - mmengine - INFO - Epoch(train) [132][1040/2119] lr: 4.0000e-03 eta: 3:47:34 time: 0.3682 data_time: 0.0233 memory: 5826 grad_norm: 4.9698 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9447 loss: 1.9447 2022/10/08 11:10:49 - mmengine - INFO - Epoch(train) [132][1060/2119] lr: 4.0000e-03 eta: 3:47:27 time: 0.3187 data_time: 0.0261 memory: 5826 grad_norm: 4.9519 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0070 loss: 2.0070 2022/10/08 11:10:56 - mmengine - INFO - Epoch(train) [132][1080/2119] lr: 4.0000e-03 eta: 3:47:20 time: 0.3610 data_time: 0.0206 memory: 5826 grad_norm: 4.8929 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8702 loss: 1.8702 2022/10/08 11:11:03 - mmengine - INFO - Epoch(train) [132][1100/2119] lr: 4.0000e-03 eta: 3:47:13 time: 0.3247 data_time: 0.0275 memory: 5826 grad_norm: 4.9693 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 1.8843 loss: 1.8843 2022/10/08 11:11:10 - mmengine - INFO - Epoch(train) [132][1120/2119] lr: 4.0000e-03 eta: 3:47:06 time: 0.3319 data_time: 0.0192 memory: 5826 grad_norm: 4.9385 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0194 loss: 2.0194 2022/10/08 11:11:16 - mmengine - INFO - Epoch(train) [132][1140/2119] lr: 4.0000e-03 eta: 3:46:59 time: 0.3323 data_time: 0.0283 memory: 5826 grad_norm: 5.0516 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8499 loss: 1.8499 2022/10/08 11:11:24 - mmengine - INFO - Epoch(train) [132][1160/2119] lr: 4.0000e-03 eta: 3:46:52 time: 0.3704 data_time: 0.0203 memory: 5826 grad_norm: 5.1492 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8444 loss: 1.8444 2022/10/08 11:11:29 - mmengine - INFO - Epoch(train) [132][1180/2119] lr: 4.0000e-03 eta: 3:46:45 time: 0.2777 data_time: 0.0261 memory: 5826 grad_norm: 5.0091 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0882 loss: 2.0882 2022/10/08 11:11:37 - mmengine - INFO - Epoch(train) [132][1200/2119] lr: 4.0000e-03 eta: 3:46:38 time: 0.3744 data_time: 0.0179 memory: 5826 grad_norm: 4.9989 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.8582 loss: 1.8582 2022/10/08 11:11:43 - mmengine - INFO - Epoch(train) [132][1220/2119] lr: 4.0000e-03 eta: 3:46:31 time: 0.3281 data_time: 0.0249 memory: 5826 grad_norm: 4.9954 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9844 loss: 1.9844 2022/10/08 11:11:50 - mmengine - INFO - Epoch(train) [132][1240/2119] lr: 4.0000e-03 eta: 3:46:24 time: 0.3571 data_time: 0.0205 memory: 5826 grad_norm: 4.9755 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 2.1469 loss: 2.1469 2022/10/08 11:11:57 - mmengine - INFO - Epoch(train) [132][1260/2119] lr: 4.0000e-03 eta: 3:46:17 time: 0.3050 data_time: 0.0234 memory: 5826 grad_norm: 5.0542 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9552 loss: 1.9552 2022/10/08 11:12:04 - mmengine - INFO - Epoch(train) [132][1280/2119] lr: 4.0000e-03 eta: 3:46:10 time: 0.3747 data_time: 0.0203 memory: 5826 grad_norm: 5.0431 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8359 loss: 1.8359 2022/10/08 11:12:10 - mmengine - INFO - Epoch(train) [132][1300/2119] lr: 4.0000e-03 eta: 3:46:03 time: 0.2949 data_time: 0.0224 memory: 5826 grad_norm: 5.0500 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8103 loss: 1.8103 2022/10/08 11:12:16 - mmengine - INFO - Epoch(train) [132][1320/2119] lr: 4.0000e-03 eta: 3:45:56 time: 0.3173 data_time: 0.0215 memory: 5826 grad_norm: 5.0751 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1511 loss: 2.1511 2022/10/08 11:12:23 - mmengine - INFO - Epoch(train) [132][1340/2119] lr: 4.0000e-03 eta: 3:45:49 time: 0.3267 data_time: 0.0285 memory: 5826 grad_norm: 5.0874 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8975 loss: 1.8975 2022/10/08 11:12:30 - mmengine - INFO - Epoch(train) [132][1360/2119] lr: 4.0000e-03 eta: 3:45:42 time: 0.3392 data_time: 0.0182 memory: 5826 grad_norm: 4.9116 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7421 loss: 1.7421 2022/10/08 11:12:36 - mmengine - INFO - Epoch(train) [132][1380/2119] lr: 4.0000e-03 eta: 3:45:35 time: 0.3264 data_time: 0.0231 memory: 5826 grad_norm: 4.9637 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8220 loss: 1.8220 2022/10/08 11:12:44 - mmengine - INFO - Epoch(train) [132][1400/2119] lr: 4.0000e-03 eta: 3:45:28 time: 0.3874 data_time: 0.0180 memory: 5826 grad_norm: 4.9976 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0100 loss: 2.0100 2022/10/08 11:12:48 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 11:12:50 - mmengine - INFO - Epoch(train) [132][1420/2119] lr: 4.0000e-03 eta: 3:45:21 time: 0.3064 data_time: 0.0223 memory: 5826 grad_norm: 4.9938 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9732 loss: 1.9732 2022/10/08 11:12:57 - mmengine - INFO - Epoch(train) [132][1440/2119] lr: 4.0000e-03 eta: 3:45:14 time: 0.3359 data_time: 0.0186 memory: 5826 grad_norm: 5.0986 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9827 loss: 1.9827 2022/10/08 11:13:04 - mmengine - INFO - Epoch(train) [132][1460/2119] lr: 4.0000e-03 eta: 3:45:07 time: 0.3354 data_time: 0.0242 memory: 5826 grad_norm: 4.9865 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.8360 loss: 1.8360 2022/10/08 11:13:11 - mmengine - INFO - Epoch(train) [132][1480/2119] lr: 4.0000e-03 eta: 3:45:00 time: 0.3500 data_time: 0.0197 memory: 5826 grad_norm: 4.9852 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8953 loss: 1.8953 2022/10/08 11:13:17 - mmengine - INFO - Epoch(train) [132][1500/2119] lr: 4.0000e-03 eta: 3:44:53 time: 0.3059 data_time: 0.0245 memory: 5826 grad_norm: 5.0122 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9917 loss: 1.9917 2022/10/08 11:13:24 - mmengine - INFO - Epoch(train) [132][1520/2119] lr: 4.0000e-03 eta: 3:44:46 time: 0.3587 data_time: 0.0246 memory: 5826 grad_norm: 5.0408 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.8536 loss: 1.8536 2022/10/08 11:13:30 - mmengine - INFO - Epoch(train) [132][1540/2119] lr: 4.0000e-03 eta: 3:44:39 time: 0.3190 data_time: 0.0240 memory: 5826 grad_norm: 5.0217 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1836 loss: 2.1836 2022/10/08 11:13:38 - mmengine - INFO - Epoch(train) [132][1560/2119] lr: 4.0000e-03 eta: 3:44:32 time: 0.3607 data_time: 0.0223 memory: 5826 grad_norm: 5.1155 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 2.0350 loss: 2.0350 2022/10/08 11:13:44 - mmengine - INFO - Epoch(train) [132][1580/2119] lr: 4.0000e-03 eta: 3:44:25 time: 0.3334 data_time: 0.0201 memory: 5826 grad_norm: 4.9888 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9999 loss: 1.9999 2022/10/08 11:13:51 - mmengine - INFO - Epoch(train) [132][1600/2119] lr: 4.0000e-03 eta: 3:44:18 time: 0.3258 data_time: 0.0242 memory: 5826 grad_norm: 4.9331 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6888 loss: 1.6888 2022/10/08 11:13:57 - mmengine - INFO - Epoch(train) [132][1620/2119] lr: 4.0000e-03 eta: 3:44:11 time: 0.3119 data_time: 0.0289 memory: 5826 grad_norm: 5.0433 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0253 loss: 2.0253 2022/10/08 11:14:04 - mmengine - INFO - Epoch(train) [132][1640/2119] lr: 4.0000e-03 eta: 3:44:04 time: 0.3632 data_time: 0.0218 memory: 5826 grad_norm: 4.9727 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1567 loss: 2.1567 2022/10/08 11:14:11 - mmengine - INFO - Epoch(train) [132][1660/2119] lr: 4.0000e-03 eta: 3:43:57 time: 0.3232 data_time: 0.0286 memory: 5826 grad_norm: 4.9896 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.0309 loss: 2.0309 2022/10/08 11:14:17 - mmengine - INFO - Epoch(train) [132][1680/2119] lr: 4.0000e-03 eta: 3:43:50 time: 0.3253 data_time: 0.0215 memory: 5826 grad_norm: 4.8624 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.9227 loss: 1.9227 2022/10/08 11:14:23 - mmengine - INFO - Epoch(train) [132][1700/2119] lr: 4.0000e-03 eta: 3:43:43 time: 0.2997 data_time: 0.0195 memory: 5826 grad_norm: 4.8649 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8403 loss: 1.8403 2022/10/08 11:14:30 - mmengine - INFO - Epoch(train) [132][1720/2119] lr: 4.0000e-03 eta: 3:43:36 time: 0.3505 data_time: 0.0210 memory: 5826 grad_norm: 5.1000 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.0245 loss: 2.0245 2022/10/08 11:14:37 - mmengine - INFO - Epoch(train) [132][1740/2119] lr: 4.0000e-03 eta: 3:43:29 time: 0.3412 data_time: 0.0369 memory: 5826 grad_norm: 5.0025 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.8834 loss: 1.8834 2022/10/08 11:14:44 - mmengine - INFO - Epoch(train) [132][1760/2119] lr: 4.0000e-03 eta: 3:43:22 time: 0.3575 data_time: 0.0223 memory: 5826 grad_norm: 4.9819 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9191 loss: 1.9191 2022/10/08 11:14:51 - mmengine - INFO - Epoch(train) [132][1780/2119] lr: 4.0000e-03 eta: 3:43:15 time: 0.3419 data_time: 0.0218 memory: 5826 grad_norm: 4.9315 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9566 loss: 1.9566 2022/10/08 11:14:58 - mmengine - INFO - Epoch(train) [132][1800/2119] lr: 4.0000e-03 eta: 3:43:08 time: 0.3329 data_time: 0.0188 memory: 5826 grad_norm: 5.0307 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0965 loss: 2.0965 2022/10/08 11:15:05 - mmengine - INFO - Epoch(train) [132][1820/2119] lr: 4.0000e-03 eta: 3:43:01 time: 0.3450 data_time: 0.0215 memory: 5826 grad_norm: 5.0503 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9690 loss: 1.9690 2022/10/08 11:15:12 - mmengine - INFO - Epoch(train) [132][1840/2119] lr: 4.0000e-03 eta: 3:42:54 time: 0.3619 data_time: 0.0214 memory: 5826 grad_norm: 5.0178 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.7503 loss: 1.7503 2022/10/08 11:15:19 - mmengine - INFO - Epoch(train) [132][1860/2119] lr: 4.0000e-03 eta: 3:42:47 time: 0.3344 data_time: 0.0252 memory: 5826 grad_norm: 5.0679 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8925 loss: 1.8925 2022/10/08 11:15:25 - mmengine - INFO - Epoch(train) [132][1880/2119] lr: 4.0000e-03 eta: 3:42:40 time: 0.3410 data_time: 0.0169 memory: 5826 grad_norm: 5.0839 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9716 loss: 1.9716 2022/10/08 11:15:32 - mmengine - INFO - Epoch(train) [132][1900/2119] lr: 4.0000e-03 eta: 3:42:33 time: 0.3308 data_time: 0.0245 memory: 5826 grad_norm: 5.0833 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8852 loss: 1.8852 2022/10/08 11:15:39 - mmengine - INFO - Epoch(train) [132][1920/2119] lr: 4.0000e-03 eta: 3:42:26 time: 0.3592 data_time: 0.0167 memory: 5826 grad_norm: 5.1591 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5712 loss: 1.5712 2022/10/08 11:15:45 - mmengine - INFO - Epoch(train) [132][1940/2119] lr: 4.0000e-03 eta: 3:42:19 time: 0.3062 data_time: 0.0238 memory: 5826 grad_norm: 5.0973 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.0170 loss: 2.0170 2022/10/08 11:15:52 - mmengine - INFO - Epoch(train) [132][1960/2119] lr: 4.0000e-03 eta: 3:42:12 time: 0.3546 data_time: 0.0195 memory: 5826 grad_norm: 4.9898 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0021 loss: 2.0021 2022/10/08 11:15:58 - mmengine - INFO - Epoch(train) [132][1980/2119] lr: 4.0000e-03 eta: 3:42:05 time: 0.2880 data_time: 0.0209 memory: 5826 grad_norm: 5.0608 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.8998 loss: 1.8998 2022/10/08 11:16:06 - mmengine - INFO - Epoch(train) [132][2000/2119] lr: 4.0000e-03 eta: 3:41:58 time: 0.3831 data_time: 0.0205 memory: 5826 grad_norm: 5.0826 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.8619 loss: 1.8619 2022/10/08 11:16:12 - mmengine - INFO - Epoch(train) [132][2020/2119] lr: 4.0000e-03 eta: 3:41:51 time: 0.3056 data_time: 0.0214 memory: 5826 grad_norm: 5.0276 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9812 loss: 1.9812 2022/10/08 11:16:19 - mmengine - INFO - Epoch(train) [132][2040/2119] lr: 4.0000e-03 eta: 3:41:44 time: 0.3454 data_time: 0.0230 memory: 5826 grad_norm: 4.9635 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0165 loss: 2.0165 2022/10/08 11:16:25 - mmengine - INFO - Epoch(train) [132][2060/2119] lr: 4.0000e-03 eta: 3:41:37 time: 0.3061 data_time: 0.0232 memory: 5826 grad_norm: 5.0718 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0970 loss: 2.0970 2022/10/08 11:16:32 - mmengine - INFO - Epoch(train) [132][2080/2119] lr: 4.0000e-03 eta: 3:41:30 time: 0.3282 data_time: 0.0228 memory: 5826 grad_norm: 5.1827 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9863 loss: 1.9863 2022/10/08 11:16:38 - mmengine - INFO - Epoch(train) [132][2100/2119] lr: 4.0000e-03 eta: 3:41:23 time: 0.3185 data_time: 0.0274 memory: 5826 grad_norm: 4.9896 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9496 loss: 1.9496 2022/10/08 11:16:44 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221007_073256 2022/10/08 11:16:44 - mmengine - INFO - Epoch(train) [132][2119/2119] lr: 4.0000e-03 eta: 3:41:23 time: 0.2880 data_time: 0.0230 memory: 5826 grad_norm: 5.0852 top1_acc: 0.3000 top5_acc: 0.6000 loss_cls: 1.8862 loss: 1.8862 2022/10/08 11:16:44 - mmengine - INFO - Saving checkpoint at 132 epochs 2022/10/08 13:43:49 - mmengine - INFO - Epoch(train) [133][20/2119] lr: 4.0000e-03 eta: 1 day, 22:50:18 time: 4.4231 data_time: 4.0870 memory: 5821 grad_norm: 4.9856 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.7462 loss: 1.7462 2022/10/08 13:43:55 - mmengine - INFO - Epoch(train) [133][40/2119] lr: 4.0000e-03 eta: 1 day, 0:51:29 time: 0.2742 data_time: 0.0224 memory: 5821 grad_norm: 5.0134 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8699 loss: 1.8699 2022/10/08 13:44:01 - mmengine - INFO - Epoch(train) [133][60/2119] lr: 4.0000e-03 eta: 17:36:09 time: 0.2947 data_time: 0.0228 memory: 5821 grad_norm: 5.0446 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8717 loss: 1.8717 2022/10/08 13:44:07 - mmengine - INFO - Epoch(train) [133][80/2119] lr: 4.0000e-03 eta: 14:00:38 time: 0.3086 data_time: 0.0171 memory: 5821 grad_norm: 5.0293 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.9265 loss: 1.9265 2022/10/08 13:44:13 - mmengine - INFO - Epoch(train) [133][100/2119] lr: 4.0000e-03 eta: 11:49:28 time: 0.2944 data_time: 0.0178 memory: 5821 grad_norm: 5.0259 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9225 loss: 1.9225 2022/10/08 13:44:18 - mmengine - INFO - Epoch(train) [133][120/2119] lr: 4.0000e-03 eta: 10:20:52 time: 0.2836 data_time: 0.0251 memory: 5821 grad_norm: 5.0908 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9601 loss: 1.9601 2022/10/08 13:44:24 - mmengine - INFO - Epoch(train) [133][140/2119] lr: 4.0000e-03 eta: 9:18:46 time: 0.2970 data_time: 0.0179 memory: 5821 grad_norm: 5.0404 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7119 loss: 1.7119 2022/10/08 13:44:30 - mmengine - INFO - Epoch(train) [133][160/2119] lr: 4.0000e-03 eta: 8:30:52 time: 0.2806 data_time: 0.0182 memory: 5821 grad_norm: 4.9512 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1657 loss: 2.1657 2022/10/08 13:44:36 - mmengine - INFO - Epoch(train) [133][180/2119] lr: 4.0000e-03 eta: 7:53:51 time: 0.2844 data_time: 0.0161 memory: 5821 grad_norm: 5.0611 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.9050 loss: 1.9050 2022/10/08 13:44:42 - mmengine - INFO - Epoch(train) [133][200/2119] lr: 4.0000e-03 eta: 7:25:49 time: 0.3095 data_time: 0.0195 memory: 5821 grad_norm: 5.0425 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8594 loss: 1.8594 2022/10/08 13:44:48 - mmengine - INFO - Epoch(train) [133][220/2119] lr: 4.0000e-03 eta: 7:01:54 time: 0.2929 data_time: 0.0179 memory: 5821 grad_norm: 4.9626 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7855 loss: 1.7855 2022/10/08 13:44:54 - mmengine - INFO - Epoch(train) [133][240/2119] lr: 4.0000e-03 eta: 6:41:53 time: 0.2915 data_time: 0.0213 memory: 5821 grad_norm: 5.0122 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8643 loss: 1.8643 2022/10/08 13:45:00 - mmengine - INFO - Epoch(train) [133][260/2119] lr: 4.0000e-03 eta: 6:26:08 time: 0.3162 data_time: 0.0199 memory: 5821 grad_norm: 5.0398 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8726 loss: 1.8726 2022/10/08 13:45:06 - mmengine - INFO - Epoch(train) [133][280/2119] lr: 4.0000e-03 eta: 6:11:54 time: 0.3004 data_time: 0.0204 memory: 5821 grad_norm: 4.9708 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9025 loss: 1.9025 2022/10/08 13:45:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 13:45:12 - mmengine - INFO - Epoch(train) [133][300/2119] lr: 4.0000e-03 eta: 5:59:36 time: 0.3015 data_time: 0.0197 memory: 5821 grad_norm: 4.9561 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7566 loss: 1.7566 2022/10/08 13:45:18 - mmengine - INFO - Epoch(train) [133][320/2119] lr: 4.0000e-03 eta: 5:48:54 time: 0.3035 data_time: 0.0177 memory: 5821 grad_norm: 5.0138 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8398 loss: 1.8398 2022/10/08 13:45:24 - mmengine - INFO - Epoch(train) [133][340/2119] lr: 4.0000e-03 eta: 5:39:00 time: 0.2911 data_time: 0.0169 memory: 5821 grad_norm: 5.0180 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8597 loss: 1.8597 2022/10/08 13:45:29 - mmengine - INFO - Epoch(train) [133][360/2119] lr: 4.0000e-03 eta: 5:29:22 time: 0.2678 data_time: 0.0220 memory: 5821 grad_norm: 5.0285 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8986 loss: 1.8986 2022/10/08 13:45:36 - mmengine - INFO - Epoch(train) [133][380/2119] lr: 4.0000e-03 eta: 5:23:46 time: 0.3594 data_time: 0.0236 memory: 5821 grad_norm: 5.0554 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0542 loss: 2.0542 2022/10/08 13:45:42 - mmengine - INFO - Epoch(train) [133][400/2119] lr: 4.0000e-03 eta: 5:15:30 time: 0.2574 data_time: 0.0224 memory: 5821 grad_norm: 4.9855 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0094 loss: 2.0094 2022/10/08 13:45:48 - mmengine - INFO - Epoch(train) [133][420/2119] lr: 4.0000e-03 eta: 5:09:18 time: 0.3000 data_time: 0.0217 memory: 5821 grad_norm: 5.0132 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8772 loss: 1.8772 2022/10/08 13:45:53 - mmengine - INFO - Epoch(train) [133][440/2119] lr: 4.0000e-03 eta: 5:02:26 time: 0.2569 data_time: 0.0218 memory: 5821 grad_norm: 5.0897 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7304 loss: 1.7304 2022/10/08 13:45:59 - mmengine - INFO - Epoch(train) [133][460/2119] lr: 4.0000e-03 eta: 4:58:09 time: 0.3306 data_time: 0.0171 memory: 5821 grad_norm: 5.0816 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0028 loss: 2.0028 2022/10/08 13:46:05 - mmengine - INFO - Epoch(train) [133][480/2119] lr: 4.0000e-03 eta: 4:53:04 time: 0.2863 data_time: 0.0212 memory: 5821 grad_norm: 5.0345 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9489 loss: 1.9489 2022/10/08 13:46:11 - mmengine - INFO - Epoch(train) [133][500/2119] lr: 4.0000e-03 eta: 4:49:00 time: 0.3111 data_time: 0.0140 memory: 5821 grad_norm: 5.0394 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1246 loss: 2.1246 2022/10/08 13:46:17 - mmengine - INFO - Epoch(train) [133][520/2119] lr: 4.0000e-03 eta: 4:44:30 time: 0.2807 data_time: 0.0165 memory: 5821 grad_norm: 5.0289 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8965 loss: 1.8965 2022/10/08 13:46:23 - mmengine - INFO - Epoch(train) [133][540/2119] lr: 4.0000e-03 eta: 4:40:47 time: 0.2998 data_time: 0.0171 memory: 5821 grad_norm: 5.1069 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0654 loss: 2.0654 2022/10/08 13:46:29 - mmengine - INFO - Epoch(train) [133][560/2119] lr: 4.0000e-03 eta: 4:37:28 time: 0.3068 data_time: 0.0238 memory: 5821 grad_norm: 5.0068 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8807 loss: 1.8807 2022/10/08 13:46:35 - mmengine - INFO - Epoch(train) [133][580/2119] lr: 4.0000e-03 eta: 4:34:20 time: 0.3043 data_time: 0.0207 memory: 5821 grad_norm: 5.0503 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 1.8207 loss: 1.8207 2022/10/08 13:46:41 - mmengine - INFO - Epoch(train) [133][600/2119] lr: 4.0000e-03 eta: 4:30:57 time: 0.2833 data_time: 0.0181 memory: 5821 grad_norm: 5.1604 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8417 loss: 1.8417 2022/10/08 13:46:47 - mmengine - INFO - Epoch(train) [133][620/2119] lr: 4.0000e-03 eta: 4:28:39 time: 0.3264 data_time: 0.0184 memory: 5821 grad_norm: 5.0541 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8934 loss: 1.8934 2022/10/08 13:46:53 - mmengine - INFO - Epoch(train) [133][640/2119] lr: 4.0000e-03 eta: 4:25:28 time: 0.2735 data_time: 0.0206 memory: 5821 grad_norm: 4.9797 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 1.9721 loss: 1.9721 2022/10/08 13:46:59 - mmengine - INFO - Epoch(train) [133][660/2119] lr: 4.0000e-03 eta: 4:23:26 time: 0.3253 data_time: 0.0196 memory: 5821 grad_norm: 5.0116 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8413 loss: 1.8413 2022/10/08 13:47:05 - mmengine - INFO - Epoch(train) [133][680/2119] lr: 4.0000e-03 eta: 4:20:54 time: 0.2915 data_time: 0.0181 memory: 5821 grad_norm: 5.0754 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.7856 loss: 1.7856 2022/10/08 13:47:11 - mmengine - INFO - Epoch(train) [133][700/2119] lr: 4.0000e-03 eta: 4:18:28 time: 0.2890 data_time: 0.0162 memory: 5821 grad_norm: 5.0494 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2085 loss: 2.2085 2022/10/08 13:47:16 - mmengine - INFO - Epoch(train) [133][720/2119] lr: 4.0000e-03 eta: 4:15:36 time: 0.2570 data_time: 0.0206 memory: 5821 grad_norm: 5.0910 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1301 loss: 2.1301 2022/10/08 13:47:23 - mmengine - INFO - Epoch(train) [133][740/2119] lr: 4.0000e-03 eta: 4:14:08 time: 0.3305 data_time: 0.0182 memory: 5821 grad_norm: 4.9770 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0331 loss: 2.0331 2022/10/08 13:47:28 - mmengine - INFO - Epoch(train) [133][760/2119] lr: 4.0000e-03 eta: 4:11:56 time: 0.2816 data_time: 0.0169 memory: 5821 grad_norm: 5.0688 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9671 loss: 1.9671 2022/10/08 13:47:34 - mmengine - INFO - Epoch(train) [133][780/2119] lr: 4.0000e-03 eta: 4:09:57 time: 0.2887 data_time: 0.0153 memory: 5821 grad_norm: 5.0575 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9784 loss: 1.9784 2022/10/08 13:47:41 - mmengine - INFO - Epoch(train) [133][800/2119] lr: 4.0000e-03 eta: 4:09:02 time: 0.3513 data_time: 0.0192 memory: 5821 grad_norm: 5.0642 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9510 loss: 1.9510 2022/10/08 13:47:47 - mmengine - INFO - Epoch(train) [133][820/2119] lr: 4.0000e-03 eta: 4:07:05 time: 0.2800 data_time: 0.0192 memory: 5821 grad_norm: 5.1371 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1840 loss: 2.1840 2022/10/08 13:47:53 - mmengine - INFO - Epoch(train) [133][840/2119] lr: 4.0000e-03 eta: 4:05:51 time: 0.3227 data_time: 0.0151 memory: 5821 grad_norm: 5.0650 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7524 loss: 1.7524 2022/10/08 13:47:59 - mmengine - INFO - Epoch(train) [133][860/2119] lr: 4.0000e-03 eta: 4:04:20 time: 0.2995 data_time: 0.0163 memory: 5821 grad_norm: 5.1223 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1000 loss: 2.1000 2022/10/08 13:48:05 - mmengine - INFO - Epoch(train) [133][880/2119] lr: 4.0000e-03 eta: 4:02:52 time: 0.2993 data_time: 0.0203 memory: 5821 grad_norm: 5.0071 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9230 loss: 1.9230 2022/10/08 13:48:12 - mmengine - INFO - Epoch(train) [133][900/2119] lr: 4.0000e-03 eta: 4:01:38 time: 0.3109 data_time: 0.0126 memory: 5821 grad_norm: 5.0162 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0068 loss: 2.0068 2022/10/08 13:48:17 - mmengine - INFO - Epoch(train) [133][920/2119] lr: 4.0000e-03 eta: 3:59:53 time: 0.2696 data_time: 0.0224 memory: 5821 grad_norm: 5.0418 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8992 loss: 1.8992 2022/10/08 13:48:23 - mmengine - INFO - Epoch(train) [133][940/2119] lr: 4.0000e-03 eta: 3:58:35 time: 0.2981 data_time: 0.0266 memory: 5821 grad_norm: 5.0284 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.8964 loss: 1.8964 2022/10/08 13:48:29 - mmengine - INFO - Epoch(train) [133][960/2119] lr: 4.0000e-03 eta: 3:57:13 time: 0.2887 data_time: 0.0188 memory: 5821 grad_norm: 4.9989 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8368 loss: 1.8368 2022/10/08 13:48:34 - mmengine - INFO - Epoch(train) [133][980/2119] lr: 4.0000e-03 eta: 3:55:43 time: 0.2736 data_time: 0.0151 memory: 5821 grad_norm: 5.1458 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8629 loss: 1.8629 2022/10/08 13:48:41 - mmengine - INFO - Epoch(train) [133][1000/2119] lr: 4.0000e-03 eta: 3:54:47 time: 0.3159 data_time: 0.0235 memory: 5821 grad_norm: 5.0631 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8747 loss: 1.8747 2022/10/08 13:48:47 - mmengine - INFO - Epoch(train) [133][1020/2119] lr: 4.0000e-03 eta: 3:54:00 time: 0.3246 data_time: 0.0203 memory: 5821 grad_norm: 5.0281 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9009 loss: 1.9009 2022/10/08 13:48:53 - mmengine - INFO - Epoch(train) [133][1040/2119] lr: 4.0000e-03 eta: 3:52:47 time: 0.2872 data_time: 0.0178 memory: 5821 grad_norm: 5.0472 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.0991 loss: 2.0991 2022/10/08 13:48:59 - mmengine - INFO - Epoch(train) [133][1060/2119] lr: 4.0000e-03 eta: 3:51:56 time: 0.3140 data_time: 0.0212 memory: 5821 grad_norm: 5.0853 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.8816 loss: 1.8816 2022/10/08 13:49:05 - mmengine - INFO - Epoch(train) [133][1080/2119] lr: 4.0000e-03 eta: 3:50:40 time: 0.2757 data_time: 0.0185 memory: 5821 grad_norm: 5.0256 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9072 loss: 1.9072 2022/10/08 13:49:10 - mmengine - INFO - Epoch(train) [133][1100/2119] lr: 4.0000e-03 eta: 3:49:37 time: 0.2907 data_time: 0.0176 memory: 5821 grad_norm: 5.0925 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0952 loss: 2.0952 2022/10/08 13:49:16 - mmengine - INFO - Epoch(train) [133][1120/2119] lr: 4.0000e-03 eta: 3:48:24 time: 0.2728 data_time: 0.0207 memory: 5821 grad_norm: 5.0508 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9996 loss: 1.9996 2022/10/08 13:49:22 - mmengine - INFO - Epoch(train) [133][1140/2119] lr: 4.0000e-03 eta: 3:47:25 time: 0.2905 data_time: 0.0178 memory: 5821 grad_norm: 5.2012 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1141 loss: 2.1141 2022/10/08 13:49:28 - mmengine - INFO - Epoch(train) [133][1160/2119] lr: 4.0000e-03 eta: 3:46:45 time: 0.3176 data_time: 0.0168 memory: 5821 grad_norm: 5.0513 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 1.9625 loss: 1.9625 2022/10/08 13:49:34 - mmengine - INFO - Epoch(train) [133][1180/2119] lr: 4.0000e-03 eta: 3:45:48 time: 0.2886 data_time: 0.0176 memory: 5821 grad_norm: 4.9570 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9190 loss: 1.9190 2022/10/08 13:49:40 - mmengine - INFO - Epoch(train) [133][1200/2119] lr: 4.0000e-03 eta: 3:45:04 time: 0.3076 data_time: 0.0152 memory: 5821 grad_norm: 5.0638 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7009 loss: 1.7009 2022/10/08 13:49:46 - mmengine - INFO - Epoch(train) [133][1220/2119] lr: 4.0000e-03 eta: 3:44:18 time: 0.3012 data_time: 0.0217 memory: 5821 grad_norm: 5.0191 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9803 loss: 1.9803 2022/10/08 13:49:52 - mmengine - INFO - Epoch(train) [133][1240/2119] lr: 4.0000e-03 eta: 3:43:28 time: 0.2934 data_time: 0.0243 memory: 5821 grad_norm: 5.0834 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.7907 loss: 1.7907 2022/10/08 13:49:58 - mmengine - INFO - Epoch(train) [133][1260/2119] lr: 4.0000e-03 eta: 3:42:41 time: 0.2946 data_time: 0.0237 memory: 5821 grad_norm: 5.0592 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9727 loss: 1.9727 2022/10/08 13:50:03 - mmengine - INFO - Epoch(train) [133][1280/2119] lr: 4.0000e-03 eta: 3:41:39 time: 0.2676 data_time: 0.0189 memory: 5821 grad_norm: 5.0432 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9544 loss: 1.9544 2022/10/08 13:50:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 13:50:09 - mmengine - INFO - Epoch(train) [133][1300/2119] lr: 4.0000e-03 eta: 3:41:04 time: 0.3123 data_time: 0.0168 memory: 5821 grad_norm: 5.0069 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8517 loss: 1.8517 2022/10/08 13:50:16 - mmengine - INFO - Epoch(train) [133][1320/2119] lr: 4.0000e-03 eta: 3:40:33 time: 0.3174 data_time: 0.0192 memory: 5821 grad_norm: 5.0435 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.0556 loss: 2.0556 2022/10/08 13:50:21 - mmengine - INFO - Epoch(train) [133][1340/2119] lr: 4.0000e-03 eta: 3:39:42 time: 0.2796 data_time: 0.0195 memory: 5821 grad_norm: 5.0650 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9808 loss: 1.9808 2022/10/08 13:50:28 - mmengine - INFO - Epoch(train) [133][1360/2119] lr: 4.0000e-03 eta: 3:39:09 time: 0.3090 data_time: 0.0175 memory: 5821 grad_norm: 5.0119 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8539 loss: 1.8539 2022/10/08 13:50:33 - mmengine - INFO - Epoch(train) [133][1380/2119] lr: 4.0000e-03 eta: 3:38:27 time: 0.2935 data_time: 0.0185 memory: 5821 grad_norm: 5.0852 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6904 loss: 1.6904 2022/10/08 13:50:40 - mmengine - INFO - Epoch(train) [133][1400/2119] lr: 4.0000e-03 eta: 3:38:05 time: 0.3268 data_time: 0.0141 memory: 5821 grad_norm: 5.0299 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9234 loss: 1.9234 2022/10/08 13:50:46 - mmengine - INFO - Epoch(train) [133][1420/2119] lr: 4.0000e-03 eta: 3:37:19 time: 0.2814 data_time: 0.0170 memory: 5821 grad_norm: 4.9946 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0959 loss: 2.0959 2022/10/08 13:50:52 - mmengine - INFO - Epoch(train) [133][1440/2119] lr: 4.0000e-03 eta: 3:36:51 time: 0.3151 data_time: 0.0172 memory: 5821 grad_norm: 5.0200 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 1.9130 loss: 1.9130 2022/10/08 13:50:57 - mmengine - INFO - Epoch(train) [133][1460/2119] lr: 4.0000e-03 eta: 3:36:05 time: 0.2760 data_time: 0.0145 memory: 5821 grad_norm: 5.0049 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9510 loss: 1.9510 2022/10/08 13:51:04 - mmengine - INFO - Epoch(train) [133][1480/2119] lr: 4.0000e-03 eta: 3:35:33 time: 0.3036 data_time: 0.0203 memory: 5821 grad_norm: 4.9202 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9094 loss: 1.9094 2022/10/08 13:51:09 - mmengine - INFO - Epoch(train) [133][1500/2119] lr: 4.0000e-03 eta: 3:34:56 time: 0.2926 data_time: 0.0209 memory: 5821 grad_norm: 5.1582 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9122 loss: 1.9122 2022/10/08 13:51:15 - mmengine - INFO - Epoch(train) [133][1520/2119] lr: 4.0000e-03 eta: 3:34:26 time: 0.3026 data_time: 0.0173 memory: 5821 grad_norm: 5.0554 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8599 loss: 1.8599 2022/10/08 13:51:22 - mmengine - INFO - Epoch(train) [133][1540/2119] lr: 4.0000e-03 eta: 3:33:59 time: 0.3104 data_time: 0.0161 memory: 5821 grad_norm: 5.0469 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.1258 loss: 2.1258 2022/10/08 13:51:28 - mmengine - INFO - Epoch(train) [133][1560/2119] lr: 4.0000e-03 eta: 3:33:29 time: 0.3018 data_time: 0.0149 memory: 5821 grad_norm: 5.1155 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2557 loss: 2.2557 2022/10/08 13:51:34 - mmengine - INFO - Epoch(train) [133][1580/2119] lr: 4.0000e-03 eta: 3:32:54 time: 0.2904 data_time: 0.0316 memory: 5821 grad_norm: 5.1442 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0533 loss: 2.0533 2022/10/08 13:51:40 - mmengine - INFO - Epoch(train) [133][1600/2119] lr: 4.0000e-03 eta: 3:32:29 time: 0.3097 data_time: 0.0236 memory: 5821 grad_norm: 4.9932 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9372 loss: 1.9372 2022/10/08 13:51:45 - mmengine - INFO - Epoch(train) [133][1620/2119] lr: 4.0000e-03 eta: 3:31:49 time: 0.2741 data_time: 0.0138 memory: 5821 grad_norm: 5.1385 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0264 loss: 2.0264 2022/10/08 13:51:52 - mmengine - INFO - Epoch(train) [133][1640/2119] lr: 4.0000e-03 eta: 3:31:32 time: 0.3258 data_time: 0.0248 memory: 5821 grad_norm: 5.1458 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9228 loss: 1.9228 2022/10/08 13:51:58 - mmengine - INFO - Epoch(train) [133][1660/2119] lr: 4.0000e-03 eta: 3:31:17 time: 0.3302 data_time: 0.0153 memory: 5821 grad_norm: 4.9897 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8565 loss: 1.8565 2022/10/08 13:52:04 - mmengine - INFO - Epoch(train) [133][1680/2119] lr: 4.0000e-03 eta: 3:30:37 time: 0.2706 data_time: 0.0184 memory: 5821 grad_norm: 4.9809 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8716 loss: 1.8716 2022/10/08 13:52:10 - mmengine - INFO - Epoch(train) [133][1700/2119] lr: 4.0000e-03 eta: 3:30:23 time: 0.3298 data_time: 0.0157 memory: 5821 grad_norm: 5.0880 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8012 loss: 1.8012 2022/10/08 13:52:17 - mmengine - INFO - Epoch(train) [133][1720/2119] lr: 4.0000e-03 eta: 3:30:17 time: 0.3484 data_time: 0.0214 memory: 5821 grad_norm: 5.0611 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.0392 loss: 2.0392 2022/10/08 13:52:23 - mmengine - INFO - Epoch(train) [133][1740/2119] lr: 4.0000e-03 eta: 3:29:40 time: 0.2762 data_time: 0.0194 memory: 5821 grad_norm: 5.1834 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0166 loss: 2.0166 2022/10/08 13:52:29 - mmengine - INFO - Epoch(train) [133][1760/2119] lr: 4.0000e-03 eta: 3:29:22 time: 0.3183 data_time: 0.0240 memory: 5821 grad_norm: 5.0767 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9228 loss: 1.9228 2022/10/08 13:52:34 - mmengine - INFO - Epoch(train) [133][1780/2119] lr: 4.0000e-03 eta: 3:28:39 time: 0.2574 data_time: 0.0195 memory: 5821 grad_norm: 5.0106 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9080 loss: 1.9080 2022/10/08 13:52:40 - mmengine - INFO - Epoch(train) [133][1800/2119] lr: 4.0000e-03 eta: 3:28:08 time: 0.2847 data_time: 0.0171 memory: 5821 grad_norm: 5.0858 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.1964 loss: 2.1964 2022/10/08 13:52:46 - mmengine - INFO - Epoch(train) [133][1820/2119] lr: 4.0000e-03 eta: 3:27:44 time: 0.3010 data_time: 0.0178 memory: 5821 grad_norm: 5.0952 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1581 loss: 2.1581 2022/10/08 13:52:52 - mmengine - INFO - Epoch(train) [133][1840/2119] lr: 4.0000e-03 eta: 3:27:25 time: 0.3106 data_time: 0.0195 memory: 5821 grad_norm: 5.1574 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2079 loss: 2.2079 2022/10/08 13:52:58 - mmengine - INFO - Epoch(train) [133][1860/2119] lr: 4.0000e-03 eta: 3:26:55 time: 0.2842 data_time: 0.0182 memory: 5821 grad_norm: 5.1680 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9051 loss: 1.9051 2022/10/08 13:53:04 - mmengine - INFO - Epoch(train) [133][1880/2119] lr: 4.0000e-03 eta: 3:26:36 time: 0.3096 data_time: 0.0205 memory: 5821 grad_norm: 5.0377 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1346 loss: 2.1346 2022/10/08 13:53:11 - mmengine - INFO - Epoch(train) [133][1900/2119] lr: 4.0000e-03 eta: 3:26:24 time: 0.3300 data_time: 0.0199 memory: 5821 grad_norm: 5.0521 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.2067 loss: 2.2067 2022/10/08 13:53:16 - mmengine - INFO - Epoch(train) [133][1920/2119] lr: 4.0000e-03 eta: 3:25:47 time: 0.2611 data_time: 0.0229 memory: 5821 grad_norm: 5.0162 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9741 loss: 1.9741 2022/10/08 13:53:23 - mmengine - INFO - Epoch(train) [133][1940/2119] lr: 4.0000e-03 eta: 3:25:34 time: 0.3231 data_time: 0.0239 memory: 5821 grad_norm: 4.9927 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9570 loss: 1.9570 2022/10/08 13:53:30 - mmengine - INFO - Epoch(train) [133][1960/2119] lr: 4.0000e-03 eta: 3:25:30 time: 0.3494 data_time: 0.0233 memory: 5821 grad_norm: 5.0331 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.1393 loss: 2.1393 2022/10/08 13:53:35 - mmengine - INFO - Epoch(train) [133][1980/2119] lr: 4.0000e-03 eta: 3:24:49 time: 0.2475 data_time: 0.0191 memory: 5821 grad_norm: 5.0617 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1312 loss: 2.1312 2022/10/08 13:53:41 - mmengine - INFO - Epoch(train) [133][2000/2119] lr: 4.0000e-03 eta: 3:24:30 time: 0.3072 data_time: 0.0164 memory: 5821 grad_norm: 5.0716 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9293 loss: 1.9293 2022/10/08 13:53:46 - mmengine - INFO - Epoch(train) [133][2020/2119] lr: 4.0000e-03 eta: 3:24:01 time: 0.2752 data_time: 0.0227 memory: 5821 grad_norm: 5.0478 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9108 loss: 1.9108 2022/10/08 13:53:52 - mmengine - INFO - Epoch(train) [133][2040/2119] lr: 4.0000e-03 eta: 3:23:43 time: 0.3068 data_time: 0.0262 memory: 5821 grad_norm: 5.0363 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9323 loss: 1.9323 2022/10/08 13:53:58 - mmengine - INFO - Epoch(train) [133][2060/2119] lr: 4.0000e-03 eta: 3:23:18 time: 0.2868 data_time: 0.0187 memory: 5821 grad_norm: 5.0698 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9341 loss: 1.9341 2022/10/08 13:54:04 - mmengine - INFO - Epoch(train) [133][2080/2119] lr: 4.0000e-03 eta: 3:22:59 time: 0.3052 data_time: 0.0175 memory: 5821 grad_norm: 5.0400 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0223 loss: 2.0223 2022/10/08 13:54:10 - mmengine - INFO - Epoch(train) [133][2100/2119] lr: 4.0000e-03 eta: 3:22:41 time: 0.3037 data_time: 0.0179 memory: 5821 grad_norm: 5.1029 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.2009 loss: 2.2009 2022/10/08 13:54:15 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 13:54:15 - mmengine - INFO - Epoch(train) [133][2119/2119] lr: 4.0000e-03 eta: 3:22:41 time: 0.2611 data_time: 0.0199 memory: 5821 grad_norm: 5.1098 top1_acc: 0.4000 top5_acc: 0.7000 loss_cls: 2.0396 loss: 2.0396 2022/10/08 13:54:25 - mmengine - INFO - Epoch(train) [134][20/2119] lr: 4.0000e-03 eta: 3:21:27 time: 0.4775 data_time: 0.0886 memory: 5821 grad_norm: 5.0758 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7473 loss: 1.7473 2022/10/08 13:54:33 - mmengine - INFO - Epoch(train) [134][40/2119] lr: 4.0000e-03 eta: 3:21:37 time: 0.3871 data_time: 0.0184 memory: 5821 grad_norm: 5.0713 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.9734 loss: 1.9734 2022/10/08 13:54:38 - mmengine - INFO - Epoch(train) [134][60/2119] lr: 4.0000e-03 eta: 3:21:05 time: 0.2572 data_time: 0.0166 memory: 5821 grad_norm: 5.0707 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8428 loss: 1.8428 2022/10/08 13:54:44 - mmengine - INFO - Epoch(train) [134][80/2119] lr: 4.0000e-03 eta: 3:20:45 time: 0.2956 data_time: 0.0196 memory: 5821 grad_norm: 5.0807 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9505 loss: 1.9505 2022/10/08 13:54:52 - mmengine - INFO - Epoch(train) [134][100/2119] lr: 4.0000e-03 eta: 3:21:04 time: 0.4146 data_time: 0.1186 memory: 5821 grad_norm: 5.1260 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0135 loss: 2.0135 2022/10/08 13:54:57 - mmengine - INFO - Epoch(train) [134][120/2119] lr: 4.0000e-03 eta: 3:20:31 time: 0.2556 data_time: 0.0188 memory: 5821 grad_norm: 5.0959 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.7252 loss: 1.7252 2022/10/08 13:55:02 - mmengine - INFO - Epoch(train) [134][140/2119] lr: 4.0000e-03 eta: 3:19:59 time: 0.2533 data_time: 0.0226 memory: 5821 grad_norm: 5.0489 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0151 loss: 2.0151 2022/10/08 13:55:08 - mmengine - INFO - Epoch(train) [134][160/2119] lr: 4.0000e-03 eta: 3:19:41 time: 0.2990 data_time: 0.0217 memory: 5821 grad_norm: 5.0342 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0713 loss: 2.0713 2022/10/08 13:55:12 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 13:55:14 - mmengine - INFO - Epoch(train) [134][180/2119] lr: 4.0000e-03 eta: 3:19:26 time: 0.3082 data_time: 0.0114 memory: 5821 grad_norm: 5.0320 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9494 loss: 1.9494 2022/10/08 13:55:21 - mmengine - INFO - Epoch(train) [134][200/2119] lr: 4.0000e-03 eta: 3:19:15 time: 0.3184 data_time: 0.0198 memory: 5821 grad_norm: 5.0869 top1_acc: 0.3125 top5_acc: 0.8125 loss_cls: 1.7931 loss: 1.7931 2022/10/08 13:55:26 - mmengine - INFO - Epoch(train) [134][220/2119] lr: 4.0000e-03 eta: 3:18:54 time: 0.2876 data_time: 0.0332 memory: 5821 grad_norm: 5.0483 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0082 loss: 2.0082 2022/10/08 13:55:32 - mmengine - INFO - Epoch(train) [134][240/2119] lr: 4.0000e-03 eta: 3:18:38 time: 0.3024 data_time: 0.0203 memory: 5821 grad_norm: 5.0576 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.0955 loss: 2.0955 2022/10/08 13:55:38 - mmengine - INFO - Epoch(train) [134][260/2119] lr: 4.0000e-03 eta: 3:18:10 time: 0.2626 data_time: 0.0203 memory: 5821 grad_norm: 5.0929 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.9542 loss: 1.9542 2022/10/08 13:55:44 - mmengine - INFO - Epoch(train) [134][280/2119] lr: 4.0000e-03 eta: 3:17:55 time: 0.3048 data_time: 0.0197 memory: 5821 grad_norm: 5.0160 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.7827 loss: 1.7827 2022/10/08 13:55:49 - mmengine - INFO - Epoch(train) [134][300/2119] lr: 4.0000e-03 eta: 3:17:33 time: 0.2790 data_time: 0.0164 memory: 5821 grad_norm: 5.0900 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8410 loss: 1.8410 2022/10/08 13:55:56 - mmengine - INFO - Epoch(train) [134][320/2119] lr: 4.0000e-03 eta: 3:17:20 time: 0.3090 data_time: 0.0222 memory: 5821 grad_norm: 4.8936 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0409 loss: 2.0409 2022/10/08 13:56:01 - mmengine - INFO - Epoch(train) [134][340/2119] lr: 4.0000e-03 eta: 3:16:54 time: 0.2657 data_time: 0.0191 memory: 5821 grad_norm: 5.0541 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0212 loss: 2.0212 2022/10/08 13:56:07 - mmengine - INFO - Epoch(train) [134][360/2119] lr: 4.0000e-03 eta: 3:16:41 time: 0.3083 data_time: 0.0194 memory: 5821 grad_norm: 5.0185 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8267 loss: 1.8267 2022/10/08 13:56:13 - mmengine - INFO - Epoch(train) [134][380/2119] lr: 4.0000e-03 eta: 3:16:20 time: 0.2811 data_time: 0.0154 memory: 5821 grad_norm: 5.0593 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9572 loss: 1.9572 2022/10/08 13:56:19 - mmengine - INFO - Epoch(train) [134][400/2119] lr: 4.0000e-03 eta: 3:16:02 time: 0.2902 data_time: 0.0190 memory: 5821 grad_norm: 4.9898 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9650 loss: 1.9650 2022/10/08 13:56:24 - mmengine - INFO - Epoch(train) [134][420/2119] lr: 4.0000e-03 eta: 3:15:39 time: 0.2718 data_time: 0.0167 memory: 5821 grad_norm: 4.9775 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.7908 loss: 1.7908 2022/10/08 13:56:30 - mmengine - INFO - Epoch(train) [134][440/2119] lr: 4.0000e-03 eta: 3:15:23 time: 0.2974 data_time: 0.0182 memory: 5821 grad_norm: 5.0214 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9625 loss: 1.9625 2022/10/08 13:56:35 - mmengine - INFO - Epoch(train) [134][460/2119] lr: 4.0000e-03 eta: 3:14:57 time: 0.2579 data_time: 0.0229 memory: 5821 grad_norm: 5.1317 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 2.0445 loss: 2.0445 2022/10/08 13:56:41 - mmengine - INFO - Epoch(train) [134][480/2119] lr: 4.0000e-03 eta: 3:14:39 time: 0.2860 data_time: 0.0184 memory: 5821 grad_norm: 5.0380 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.1235 loss: 2.1235 2022/10/08 13:56:47 - mmengine - INFO - Epoch(train) [134][500/2119] lr: 4.0000e-03 eta: 3:14:21 time: 0.2891 data_time: 0.0187 memory: 5821 grad_norm: 5.0257 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1180 loss: 2.1180 2022/10/08 13:56:52 - mmengine - INFO - Epoch(train) [134][520/2119] lr: 4.0000e-03 eta: 3:14:01 time: 0.2764 data_time: 0.0181 memory: 5821 grad_norm: 5.0764 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 1.9187 loss: 1.9187 2022/10/08 13:56:59 - mmengine - INFO - Epoch(train) [134][540/2119] lr: 4.0000e-03 eta: 3:13:50 time: 0.3134 data_time: 0.0172 memory: 5821 grad_norm: 5.1469 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7656 loss: 1.7656 2022/10/08 13:57:04 - mmengine - INFO - Epoch(train) [134][560/2119] lr: 4.0000e-03 eta: 3:13:28 time: 0.2692 data_time: 0.0288 memory: 5821 grad_norm: 5.0575 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8493 loss: 1.8493 2022/10/08 13:57:10 - mmengine - INFO - Epoch(train) [134][580/2119] lr: 4.0000e-03 eta: 3:13:16 time: 0.3042 data_time: 0.0191 memory: 5821 grad_norm: 5.0939 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9921 loss: 1.9921 2022/10/08 13:57:16 - mmengine - INFO - Epoch(train) [134][600/2119] lr: 4.0000e-03 eta: 3:13:04 time: 0.3072 data_time: 0.0171 memory: 5821 grad_norm: 5.0673 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.9076 loss: 1.9076 2022/10/08 13:57:22 - mmengine - INFO - Epoch(train) [134][620/2119] lr: 4.0000e-03 eta: 3:12:43 time: 0.2734 data_time: 0.0183 memory: 5821 grad_norm: 5.0413 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1777 loss: 2.1777 2022/10/08 13:57:27 - mmengine - INFO - Epoch(train) [134][640/2119] lr: 4.0000e-03 eta: 3:12:21 time: 0.2631 data_time: 0.0305 memory: 5821 grad_norm: 5.0962 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.1560 loss: 2.1560 2022/10/08 13:57:32 - mmengine - INFO - Epoch(train) [134][660/2119] lr: 4.0000e-03 eta: 3:11:59 time: 0.2686 data_time: 0.0228 memory: 5821 grad_norm: 5.0968 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0630 loss: 2.0630 2022/10/08 13:57:39 - mmengine - INFO - Epoch(train) [134][680/2119] lr: 4.0000e-03 eta: 3:11:54 time: 0.3307 data_time: 0.0235 memory: 5821 grad_norm: 5.1297 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9157 loss: 1.9157 2022/10/08 13:57:45 - mmengine - INFO - Epoch(train) [134][700/2119] lr: 4.0000e-03 eta: 3:11:38 time: 0.2887 data_time: 0.0175 memory: 5821 grad_norm: 5.2162 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9298 loss: 1.9298 2022/10/08 13:57:50 - mmengine - INFO - Epoch(train) [134][720/2119] lr: 4.0000e-03 eta: 3:11:17 time: 0.2643 data_time: 0.0196 memory: 5821 grad_norm: 5.1577 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8719 loss: 1.8719 2022/10/08 13:57:56 - mmengine - INFO - Epoch(train) [134][740/2119] lr: 4.0000e-03 eta: 3:11:04 time: 0.2997 data_time: 0.0239 memory: 5821 grad_norm: 5.0989 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1184 loss: 2.1184 2022/10/08 13:58:02 - mmengine - INFO - Epoch(train) [134][760/2119] lr: 4.0000e-03 eta: 3:10:48 time: 0.2869 data_time: 0.0162 memory: 5821 grad_norm: 5.0415 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7654 loss: 1.7654 2022/10/08 13:58:07 - mmengine - INFO - Epoch(train) [134][780/2119] lr: 4.0000e-03 eta: 3:10:29 time: 0.2719 data_time: 0.0196 memory: 5821 grad_norm: 5.0563 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8486 loss: 1.8486 2022/10/08 13:58:20 - mmengine - INFO - Epoch(train) [134][800/2119] lr: 4.0000e-03 eta: 3:11:36 time: 0.6318 data_time: 0.3918 memory: 5821 grad_norm: 5.0767 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8388 loss: 1.8388 2022/10/08 13:58:25 - mmengine - INFO - Epoch(train) [134][820/2119] lr: 4.0000e-03 eta: 3:11:12 time: 0.2524 data_time: 0.0209 memory: 5821 grad_norm: 5.0702 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5556 loss: 1.5556 2022/10/08 13:58:30 - mmengine - INFO - Epoch(train) [134][840/2119] lr: 4.0000e-03 eta: 3:10:55 time: 0.2821 data_time: 0.0179 memory: 5821 grad_norm: 5.0348 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9756 loss: 1.9756 2022/10/08 13:58:36 - mmengine - INFO - Epoch(train) [134][860/2119] lr: 4.0000e-03 eta: 3:10:40 time: 0.2889 data_time: 0.0195 memory: 5821 grad_norm: 5.0897 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8208 loss: 1.8208 2022/10/08 13:58:42 - mmengine - INFO - Epoch(train) [134][880/2119] lr: 4.0000e-03 eta: 3:10:19 time: 0.2652 data_time: 0.0236 memory: 5821 grad_norm: 5.1216 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8557 loss: 1.8557 2022/10/08 13:58:47 - mmengine - INFO - Epoch(train) [134][900/2119] lr: 4.0000e-03 eta: 3:10:02 time: 0.2768 data_time: 0.0232 memory: 5821 grad_norm: 5.0822 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0584 loss: 2.0584 2022/10/08 13:58:53 - mmengine - INFO - Epoch(train) [134][920/2119] lr: 4.0000e-03 eta: 3:09:48 time: 0.2931 data_time: 0.0189 memory: 5821 grad_norm: 5.0065 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8740 loss: 1.8740 2022/10/08 13:58:59 - mmengine - INFO - Epoch(train) [134][940/2119] lr: 4.0000e-03 eta: 3:09:35 time: 0.2958 data_time: 0.0211 memory: 5821 grad_norm: 5.1191 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1881 loss: 2.1881 2022/10/08 13:59:05 - mmengine - INFO - Epoch(train) [134][960/2119] lr: 4.0000e-03 eta: 3:09:18 time: 0.2800 data_time: 0.0210 memory: 5821 grad_norm: 5.0903 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8192 loss: 1.8192 2022/10/08 13:59:11 - mmengine - INFO - Epoch(train) [134][980/2119] lr: 4.0000e-03 eta: 3:09:09 time: 0.3097 data_time: 0.0204 memory: 5821 grad_norm: 5.1411 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.0161 loss: 2.0161 2022/10/08 13:59:17 - mmengine - INFO - Epoch(train) [134][1000/2119] lr: 4.0000e-03 eta: 3:09:00 time: 0.3122 data_time: 0.0154 memory: 5821 grad_norm: 5.1322 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9595 loss: 1.9595 2022/10/08 13:59:23 - mmengine - INFO - Epoch(train) [134][1020/2119] lr: 4.0000e-03 eta: 3:08:43 time: 0.2768 data_time: 0.0181 memory: 5821 grad_norm: 5.1422 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8568 loss: 1.8568 2022/10/08 13:59:28 - mmengine - INFO - Epoch(train) [134][1040/2119] lr: 4.0000e-03 eta: 3:08:23 time: 0.2632 data_time: 0.0201 memory: 5821 grad_norm: 4.9865 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7159 loss: 1.7159 2022/10/08 13:59:34 - mmengine - INFO - Epoch(train) [134][1060/2119] lr: 4.0000e-03 eta: 3:08:09 time: 0.2879 data_time: 0.0178 memory: 5821 grad_norm: 5.0111 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9145 loss: 1.9145 2022/10/08 13:59:39 - mmengine - INFO - Epoch(train) [134][1080/2119] lr: 4.0000e-03 eta: 3:07:55 time: 0.2897 data_time: 0.0198 memory: 5821 grad_norm: 5.0943 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8878 loss: 1.8878 2022/10/08 13:59:45 - mmengine - INFO - Epoch(train) [134][1100/2119] lr: 4.0000e-03 eta: 3:07:37 time: 0.2695 data_time: 0.0181 memory: 5821 grad_norm: 5.0250 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8239 loss: 1.8239 2022/10/08 13:59:51 - mmengine - INFO - Epoch(train) [134][1120/2119] lr: 4.0000e-03 eta: 3:07:26 time: 0.3003 data_time: 0.0210 memory: 5821 grad_norm: 5.1662 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9327 loss: 1.9327 2022/10/08 13:59:56 - mmengine - INFO - Epoch(train) [134][1140/2119] lr: 4.0000e-03 eta: 3:07:06 time: 0.2620 data_time: 0.0190 memory: 5821 grad_norm: 5.0988 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0730 loss: 2.0730 2022/10/08 14:00:02 - mmengine - INFO - Epoch(train) [134][1160/2119] lr: 4.0000e-03 eta: 3:06:58 time: 0.3114 data_time: 0.0169 memory: 5821 grad_norm: 5.0897 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8940 loss: 1.8940 2022/10/08 14:00:06 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:00:08 - mmengine - INFO - Epoch(train) [134][1180/2119] lr: 4.0000e-03 eta: 3:06:47 time: 0.3005 data_time: 0.0251 memory: 5821 grad_norm: 4.9596 top1_acc: 0.3125 top5_acc: 0.3750 loss_cls: 1.9204 loss: 1.9204 2022/10/08 14:00:14 - mmengine - INFO - Epoch(train) [134][1200/2119] lr: 4.0000e-03 eta: 3:06:29 time: 0.2696 data_time: 0.0155 memory: 5821 grad_norm: 5.1525 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9360 loss: 1.9360 2022/10/08 14:00:19 - mmengine - INFO - Epoch(train) [134][1220/2119] lr: 4.0000e-03 eta: 3:06:14 time: 0.2762 data_time: 0.0223 memory: 5821 grad_norm: 5.1486 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9905 loss: 1.9905 2022/10/08 14:00:25 - mmengine - INFO - Epoch(train) [134][1240/2119] lr: 4.0000e-03 eta: 3:06:03 time: 0.2994 data_time: 0.0198 memory: 5821 grad_norm: 5.1488 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9858 loss: 1.9858 2022/10/08 14:00:31 - mmengine - INFO - Epoch(train) [134][1260/2119] lr: 4.0000e-03 eta: 3:05:47 time: 0.2775 data_time: 0.0229 memory: 5821 grad_norm: 5.0730 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7184 loss: 1.7184 2022/10/08 14:00:37 - mmengine - INFO - Epoch(train) [134][1280/2119] lr: 4.0000e-03 eta: 3:05:42 time: 0.3258 data_time: 0.0181 memory: 5821 grad_norm: 5.1080 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3919 loss: 2.3919 2022/10/08 14:00:43 - mmengine - INFO - Epoch(train) [134][1300/2119] lr: 4.0000e-03 eta: 3:05:23 time: 0.2599 data_time: 0.0237 memory: 5821 grad_norm: 5.0272 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9271 loss: 1.9271 2022/10/08 14:00:48 - mmengine - INFO - Epoch(train) [134][1320/2119] lr: 4.0000e-03 eta: 3:05:07 time: 0.2717 data_time: 0.0177 memory: 5821 grad_norm: 5.0896 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9176 loss: 1.9176 2022/10/08 14:00:54 - mmengine - INFO - Epoch(train) [134][1340/2119] lr: 4.0000e-03 eta: 3:04:55 time: 0.2940 data_time: 0.0208 memory: 5821 grad_norm: 5.0089 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.7317 loss: 1.7317 2022/10/08 14:01:00 - mmengine - INFO - Epoch(train) [134][1360/2119] lr: 4.0000e-03 eta: 3:04:46 time: 0.3047 data_time: 0.0160 memory: 5821 grad_norm: 5.1860 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8673 loss: 1.8673 2022/10/08 14:01:06 - mmengine - INFO - Epoch(train) [134][1380/2119] lr: 4.0000e-03 eta: 3:04:34 time: 0.2906 data_time: 0.0171 memory: 5821 grad_norm: 5.0962 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7445 loss: 1.7445 2022/10/08 14:01:12 - mmengine - INFO - Epoch(train) [134][1400/2119] lr: 4.0000e-03 eta: 3:04:24 time: 0.3026 data_time: 0.0178 memory: 5821 grad_norm: 5.0984 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.9440 loss: 1.9440 2022/10/08 14:01:17 - mmengine - INFO - Epoch(train) [134][1420/2119] lr: 4.0000e-03 eta: 3:04:09 time: 0.2744 data_time: 0.0142 memory: 5821 grad_norm: 5.1201 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1100 loss: 2.1100 2022/10/08 14:01:24 - mmengine - INFO - Epoch(train) [134][1440/2119] lr: 4.0000e-03 eta: 3:03:58 time: 0.2967 data_time: 0.0232 memory: 5821 grad_norm: 4.9931 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9634 loss: 1.9634 2022/10/08 14:01:29 - mmengine - INFO - Epoch(train) [134][1460/2119] lr: 4.0000e-03 eta: 3:03:47 time: 0.2966 data_time: 0.0325 memory: 5821 grad_norm: 4.9963 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9038 loss: 1.9038 2022/10/08 14:01:34 - mmengine - INFO - Epoch(train) [134][1480/2119] lr: 4.0000e-03 eta: 3:03:30 time: 0.2607 data_time: 0.0212 memory: 5821 grad_norm: 5.2429 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0161 loss: 2.0161 2022/10/08 14:01:41 - mmengine - INFO - Epoch(train) [134][1500/2119] lr: 4.0000e-03 eta: 3:03:22 time: 0.3144 data_time: 0.0215 memory: 5821 grad_norm: 5.0133 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1329 loss: 2.1329 2022/10/08 14:01:47 - mmengine - INFO - Epoch(train) [134][1520/2119] lr: 4.0000e-03 eta: 3:03:11 time: 0.2921 data_time: 0.0186 memory: 5821 grad_norm: 5.0731 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8168 loss: 1.8168 2022/10/08 14:01:52 - mmengine - INFO - Epoch(train) [134][1540/2119] lr: 4.0000e-03 eta: 3:02:58 time: 0.2831 data_time: 0.0162 memory: 5821 grad_norm: 5.1752 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.8774 loss: 1.8774 2022/10/08 14:01:58 - mmengine - INFO - Epoch(train) [134][1560/2119] lr: 4.0000e-03 eta: 3:02:42 time: 0.2656 data_time: 0.0180 memory: 5821 grad_norm: 5.0506 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9243 loss: 1.9243 2022/10/08 14:02:04 - mmengine - INFO - Epoch(train) [134][1580/2119] lr: 4.0000e-03 eta: 3:02:32 time: 0.3018 data_time: 0.0234 memory: 5821 grad_norm: 5.0570 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8068 loss: 1.8068 2022/10/08 14:02:09 - mmengine - INFO - Epoch(train) [134][1600/2119] lr: 4.0000e-03 eta: 3:02:18 time: 0.2738 data_time: 0.0193 memory: 5821 grad_norm: 5.0607 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8892 loss: 1.8892 2022/10/08 14:02:15 - mmengine - INFO - Epoch(train) [134][1620/2119] lr: 4.0000e-03 eta: 3:02:05 time: 0.2835 data_time: 0.0164 memory: 5821 grad_norm: 5.2040 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.1222 loss: 2.1222 2022/10/08 14:02:21 - mmengine - INFO - Epoch(train) [134][1640/2119] lr: 4.0000e-03 eta: 3:01:53 time: 0.2882 data_time: 0.0206 memory: 5821 grad_norm: 5.1049 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.7637 loss: 1.7637 2022/10/08 14:02:27 - mmengine - INFO - Epoch(train) [134][1660/2119] lr: 4.0000e-03 eta: 3:01:46 time: 0.3121 data_time: 0.0170 memory: 5821 grad_norm: 5.1978 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9730 loss: 1.9730 2022/10/08 14:02:32 - mmengine - INFO - Epoch(train) [134][1680/2119] lr: 4.0000e-03 eta: 3:01:32 time: 0.2743 data_time: 0.0193 memory: 5821 grad_norm: 5.0316 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9290 loss: 1.9290 2022/10/08 14:02:38 - mmengine - INFO - Epoch(train) [134][1700/2119] lr: 4.0000e-03 eta: 3:01:22 time: 0.2990 data_time: 0.0187 memory: 5821 grad_norm: 5.0999 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.0165 loss: 2.0165 2022/10/08 14:02:44 - mmengine - INFO - Epoch(train) [134][1720/2119] lr: 4.0000e-03 eta: 3:01:06 time: 0.2638 data_time: 0.0168 memory: 5821 grad_norm: 5.0915 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8188 loss: 1.8188 2022/10/08 14:02:50 - mmengine - INFO - Epoch(train) [134][1740/2119] lr: 4.0000e-03 eta: 3:00:59 time: 0.3128 data_time: 0.0201 memory: 5821 grad_norm: 5.0295 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 2.0198 loss: 2.0198 2022/10/08 14:02:55 - mmengine - INFO - Epoch(train) [134][1760/2119] lr: 4.0000e-03 eta: 3:00:45 time: 0.2699 data_time: 0.0193 memory: 5821 grad_norm: 5.0359 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9157 loss: 1.9157 2022/10/08 14:03:01 - mmengine - INFO - Epoch(train) [134][1780/2119] lr: 4.0000e-03 eta: 3:00:31 time: 0.2741 data_time: 0.0216 memory: 5821 grad_norm: 5.1443 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.8201 loss: 1.8201 2022/10/08 14:03:06 - mmengine - INFO - Epoch(train) [134][1800/2119] lr: 4.0000e-03 eta: 3:00:18 time: 0.2809 data_time: 0.0179 memory: 5821 grad_norm: 5.1071 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0404 loss: 2.0404 2022/10/08 14:03:12 - mmengine - INFO - Epoch(train) [134][1820/2119] lr: 4.0000e-03 eta: 3:00:04 time: 0.2688 data_time: 0.0316 memory: 5821 grad_norm: 5.0560 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0277 loss: 2.0277 2022/10/08 14:03:18 - mmengine - INFO - Epoch(train) [134][1840/2119] lr: 4.0000e-03 eta: 2:59:56 time: 0.3093 data_time: 0.0191 memory: 5821 grad_norm: 5.0075 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9581 loss: 1.9581 2022/10/08 14:03:24 - mmengine - INFO - Epoch(train) [134][1860/2119] lr: 4.0000e-03 eta: 2:59:50 time: 0.3136 data_time: 0.0210 memory: 5821 grad_norm: 5.1153 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0462 loss: 2.0462 2022/10/08 14:03:30 - mmengine - INFO - Epoch(train) [134][1880/2119] lr: 4.0000e-03 eta: 2:59:36 time: 0.2702 data_time: 0.0217 memory: 5821 grad_norm: 5.0710 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8882 loss: 1.8882 2022/10/08 14:03:35 - mmengine - INFO - Epoch(train) [134][1900/2119] lr: 4.0000e-03 eta: 2:59:23 time: 0.2810 data_time: 0.0187 memory: 5821 grad_norm: 5.0234 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9161 loss: 1.9161 2022/10/08 14:03:41 - mmengine - INFO - Epoch(train) [134][1920/2119] lr: 4.0000e-03 eta: 2:59:10 time: 0.2707 data_time: 0.0178 memory: 5821 grad_norm: 5.0621 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9749 loss: 1.9749 2022/10/08 14:03:46 - mmengine - INFO - Epoch(train) [134][1940/2119] lr: 4.0000e-03 eta: 2:58:58 time: 0.2849 data_time: 0.0199 memory: 5821 grad_norm: 5.1483 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8147 loss: 1.8147 2022/10/08 14:03:52 - mmengine - INFO - Epoch(train) [134][1960/2119] lr: 4.0000e-03 eta: 2:58:49 time: 0.3006 data_time: 0.0182 memory: 5821 grad_norm: 5.0366 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.1660 loss: 2.1660 2022/10/08 14:03:58 - mmengine - INFO - Epoch(train) [134][1980/2119] lr: 4.0000e-03 eta: 2:58:41 time: 0.3009 data_time: 0.0178 memory: 5821 grad_norm: 5.1133 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9535 loss: 1.9535 2022/10/08 14:04:04 - mmengine - INFO - Epoch(train) [134][2000/2119] lr: 4.0000e-03 eta: 2:58:30 time: 0.2886 data_time: 0.0176 memory: 5821 grad_norm: 5.0977 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8621 loss: 1.8621 2022/10/08 14:04:10 - mmengine - INFO - Epoch(train) [134][2020/2119] lr: 4.0000e-03 eta: 2:58:23 time: 0.3101 data_time: 0.0204 memory: 5821 grad_norm: 5.1273 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9485 loss: 1.9485 2022/10/08 14:04:16 - mmengine - INFO - Epoch(train) [134][2040/2119] lr: 4.0000e-03 eta: 2:58:07 time: 0.2560 data_time: 0.0172 memory: 5821 grad_norm: 5.1423 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9314 loss: 1.9314 2022/10/08 14:04:21 - mmengine - INFO - Epoch(train) [134][2060/2119] lr: 4.0000e-03 eta: 2:57:56 time: 0.2845 data_time: 0.0178 memory: 5821 grad_norm: 5.2400 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8902 loss: 1.8902 2022/10/08 14:04:27 - mmengine - INFO - Epoch(train) [134][2080/2119] lr: 4.0000e-03 eta: 2:57:43 time: 0.2702 data_time: 0.0179 memory: 5821 grad_norm: 5.0570 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.5703 loss: 1.5703 2022/10/08 14:04:32 - mmengine - INFO - Epoch(train) [134][2100/2119] lr: 4.0000e-03 eta: 2:57:32 time: 0.2877 data_time: 0.0283 memory: 5821 grad_norm: 5.0889 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.1533 loss: 2.1533 2022/10/08 14:04:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:04:38 - mmengine - INFO - Epoch(train) [134][2119/2119] lr: 4.0000e-03 eta: 2:57:32 time: 0.2664 data_time: 0.0136 memory: 5821 grad_norm: 5.1916 top1_acc: 0.1000 top5_acc: 0.7000 loss_cls: 2.0278 loss: 2.0278 2022/10/08 14:04:46 - mmengine - INFO - Epoch(train) [135][20/2119] lr: 4.0000e-03 eta: 2:56:47 time: 0.4029 data_time: 0.1335 memory: 5821 grad_norm: 5.0712 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9381 loss: 1.9381 2022/10/08 14:04:52 - mmengine - INFO - Epoch(train) [135][40/2119] lr: 4.0000e-03 eta: 2:56:38 time: 0.2977 data_time: 0.0146 memory: 5821 grad_norm: 5.1793 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8939 loss: 1.8939 2022/10/08 14:04:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:04:58 - mmengine - INFO - Epoch(train) [135][60/2119] lr: 4.0000e-03 eta: 2:56:29 time: 0.2948 data_time: 0.0200 memory: 5821 grad_norm: 5.2048 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7185 loss: 1.7185 2022/10/08 14:05:03 - mmengine - INFO - Epoch(train) [135][80/2119] lr: 4.0000e-03 eta: 2:56:17 time: 0.2796 data_time: 0.0168 memory: 5821 grad_norm: 5.0763 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8997 loss: 1.8997 2022/10/08 14:05:09 - mmengine - INFO - Epoch(train) [135][100/2119] lr: 4.0000e-03 eta: 2:56:11 time: 0.3113 data_time: 0.0170 memory: 5821 grad_norm: 5.1093 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0080 loss: 2.0080 2022/10/08 14:05:15 - mmengine - INFO - Epoch(train) [135][120/2119] lr: 4.0000e-03 eta: 2:55:59 time: 0.2760 data_time: 0.0142 memory: 5821 grad_norm: 5.0368 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0116 loss: 2.0116 2022/10/08 14:05:21 - mmengine - INFO - Epoch(train) [135][140/2119] lr: 4.0000e-03 eta: 2:55:51 time: 0.3019 data_time: 0.0269 memory: 5821 grad_norm: 5.1015 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8550 loss: 1.8550 2022/10/08 14:05:26 - mmengine - INFO - Epoch(train) [135][160/2119] lr: 4.0000e-03 eta: 2:55:36 time: 0.2542 data_time: 0.0215 memory: 5821 grad_norm: 5.0428 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7606 loss: 1.7606 2022/10/08 14:05:32 - mmengine - INFO - Epoch(train) [135][180/2119] lr: 4.0000e-03 eta: 2:55:26 time: 0.2921 data_time: 0.0225 memory: 5821 grad_norm: 5.0522 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7128 loss: 1.7128 2022/10/08 14:05:38 - mmengine - INFO - Epoch(train) [135][200/2119] lr: 4.0000e-03 eta: 2:55:18 time: 0.2953 data_time: 0.0165 memory: 5821 grad_norm: 5.1227 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0231 loss: 2.0231 2022/10/08 14:05:43 - mmengine - INFO - Epoch(train) [135][220/2119] lr: 4.0000e-03 eta: 2:55:07 time: 0.2812 data_time: 0.0224 memory: 5821 grad_norm: 5.1537 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.6611 loss: 1.6611 2022/10/08 14:05:50 - mmengine - INFO - Epoch(train) [135][240/2119] lr: 4.0000e-03 eta: 2:55:02 time: 0.3207 data_time: 0.0244 memory: 5821 grad_norm: 5.1435 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9684 loss: 1.9684 2022/10/08 14:05:55 - mmengine - INFO - Epoch(train) [135][260/2119] lr: 4.0000e-03 eta: 2:54:47 time: 0.2563 data_time: 0.0188 memory: 5821 grad_norm: 5.0404 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.6745 loss: 1.6745 2022/10/08 14:06:01 - mmengine - INFO - Epoch(train) [135][280/2119] lr: 4.0000e-03 eta: 2:54:35 time: 0.2750 data_time: 0.0183 memory: 5821 grad_norm: 5.1611 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9375 loss: 1.9375 2022/10/08 14:06:06 - mmengine - INFO - Epoch(train) [135][300/2119] lr: 4.0000e-03 eta: 2:54:27 time: 0.2975 data_time: 0.0194 memory: 5821 grad_norm: 5.1398 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0351 loss: 2.0351 2022/10/08 14:06:13 - mmengine - INFO - Epoch(train) [135][320/2119] lr: 4.0000e-03 eta: 2:54:21 time: 0.3121 data_time: 0.0206 memory: 5821 grad_norm: 5.0409 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1329 loss: 2.1329 2022/10/08 14:06:18 - mmengine - INFO - Epoch(train) [135][340/2119] lr: 4.0000e-03 eta: 2:54:07 time: 0.2598 data_time: 0.0212 memory: 5821 grad_norm: 5.0838 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8612 loss: 1.8612 2022/10/08 14:06:23 - mmengine - INFO - Epoch(train) [135][360/2119] lr: 4.0000e-03 eta: 2:53:54 time: 0.2627 data_time: 0.0209 memory: 5821 grad_norm: 5.1076 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8180 loss: 1.8180 2022/10/08 14:06:29 - mmengine - INFO - Epoch(train) [135][380/2119] lr: 4.0000e-03 eta: 2:53:44 time: 0.2888 data_time: 0.0188 memory: 5821 grad_norm: 5.1602 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8256 loss: 1.8256 2022/10/08 14:06:35 - mmengine - INFO - Epoch(train) [135][400/2119] lr: 4.0000e-03 eta: 2:53:39 time: 0.3165 data_time: 0.0174 memory: 5821 grad_norm: 5.0888 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 1.7974 loss: 1.7974 2022/10/08 14:06:41 - mmengine - INFO - Epoch(train) [135][420/2119] lr: 4.0000e-03 eta: 2:53:30 time: 0.2909 data_time: 0.0257 memory: 5821 grad_norm: 5.1836 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9730 loss: 1.9730 2022/10/08 14:06:47 - mmengine - INFO - Epoch(train) [135][440/2119] lr: 4.0000e-03 eta: 2:53:20 time: 0.2853 data_time: 0.0166 memory: 5821 grad_norm: 5.0900 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7687 loss: 1.7687 2022/10/08 14:06:53 - mmengine - INFO - Epoch(train) [135][460/2119] lr: 4.0000e-03 eta: 2:53:12 time: 0.2947 data_time: 0.0218 memory: 5821 grad_norm: 5.1544 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.7861 loss: 1.7861 2022/10/08 14:06:59 - mmengine - INFO - Epoch(train) [135][480/2119] lr: 4.0000e-03 eta: 2:53:03 time: 0.2961 data_time: 0.0184 memory: 5821 grad_norm: 5.0815 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.9715 loss: 1.9715 2022/10/08 14:07:04 - mmengine - INFO - Epoch(train) [135][500/2119] lr: 4.0000e-03 eta: 2:52:50 time: 0.2603 data_time: 0.0198 memory: 5821 grad_norm: 5.0468 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.9523 loss: 1.9523 2022/10/08 14:07:09 - mmengine - INFO - Epoch(train) [135][520/2119] lr: 4.0000e-03 eta: 2:52:37 time: 0.2616 data_time: 0.0193 memory: 5821 grad_norm: 5.0107 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9125 loss: 1.9125 2022/10/08 14:07:15 - mmengine - INFO - Epoch(train) [135][540/2119] lr: 4.0000e-03 eta: 2:52:29 time: 0.3002 data_time: 0.0194 memory: 5821 grad_norm: 5.1732 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9868 loss: 1.9868 2022/10/08 14:07:21 - mmengine - INFO - Epoch(train) [135][560/2119] lr: 4.0000e-03 eta: 2:52:21 time: 0.2982 data_time: 0.0181 memory: 5821 grad_norm: 5.1724 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9523 loss: 1.9523 2022/10/08 14:07:27 - mmengine - INFO - Epoch(train) [135][580/2119] lr: 4.0000e-03 eta: 2:52:11 time: 0.2822 data_time: 0.0206 memory: 5821 grad_norm: 5.0472 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.8694 loss: 1.8694 2022/10/08 14:07:33 - mmengine - INFO - Epoch(train) [135][600/2119] lr: 4.0000e-03 eta: 2:52:03 time: 0.2935 data_time: 0.0176 memory: 5821 grad_norm: 5.3186 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 2.0286 loss: 2.0286 2022/10/08 14:07:38 - mmengine - INFO - Epoch(train) [135][620/2119] lr: 4.0000e-03 eta: 2:51:51 time: 0.2669 data_time: 0.0198 memory: 5821 grad_norm: 5.0605 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7207 loss: 1.7207 2022/10/08 14:07:45 - mmengine - INFO - Epoch(train) [135][640/2119] lr: 4.0000e-03 eta: 2:51:47 time: 0.3280 data_time: 0.0273 memory: 5821 grad_norm: 5.0253 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.0800 loss: 2.0800 2022/10/08 14:07:50 - mmengine - INFO - Epoch(train) [135][660/2119] lr: 4.0000e-03 eta: 2:51:36 time: 0.2769 data_time: 0.0188 memory: 5821 grad_norm: 5.1115 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7566 loss: 1.7566 2022/10/08 14:07:55 - mmengine - INFO - Epoch(train) [135][680/2119] lr: 4.0000e-03 eta: 2:51:23 time: 0.2591 data_time: 0.0205 memory: 5821 grad_norm: 5.1162 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0095 loss: 2.0095 2022/10/08 14:08:01 - mmengine - INFO - Epoch(train) [135][700/2119] lr: 4.0000e-03 eta: 2:51:16 time: 0.3033 data_time: 0.0184 memory: 5821 grad_norm: 5.1091 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9327 loss: 1.9327 2022/10/08 14:08:07 - mmengine - INFO - Epoch(train) [135][720/2119] lr: 4.0000e-03 eta: 2:51:07 time: 0.2852 data_time: 0.0166 memory: 5821 grad_norm: 4.9866 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1396 loss: 2.1396 2022/10/08 14:08:13 - mmengine - INFO - Epoch(train) [135][740/2119] lr: 4.0000e-03 eta: 2:50:57 time: 0.2843 data_time: 0.0230 memory: 5821 grad_norm: 5.0996 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0037 loss: 2.0037 2022/10/08 14:08:18 - mmengine - INFO - Epoch(train) [135][760/2119] lr: 4.0000e-03 eta: 2:50:45 time: 0.2631 data_time: 0.0217 memory: 5821 grad_norm: 5.1386 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0101 loss: 2.0101 2022/10/08 14:08:24 - mmengine - INFO - Epoch(train) [135][780/2119] lr: 4.0000e-03 eta: 2:50:38 time: 0.3040 data_time: 0.0182 memory: 5821 grad_norm: 5.1150 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7572 loss: 1.7572 2022/10/08 14:08:30 - mmengine - INFO - Epoch(train) [135][800/2119] lr: 4.0000e-03 eta: 2:50:33 time: 0.3160 data_time: 0.0296 memory: 5821 grad_norm: 5.1676 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.9098 loss: 1.9098 2022/10/08 14:08:36 - mmengine - INFO - Epoch(train) [135][820/2119] lr: 4.0000e-03 eta: 2:50:22 time: 0.2708 data_time: 0.0174 memory: 5821 grad_norm: 5.1533 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 2.0008 loss: 2.0008 2022/10/08 14:08:41 - mmengine - INFO - Epoch(train) [135][840/2119] lr: 4.0000e-03 eta: 2:50:11 time: 0.2728 data_time: 0.0183 memory: 5821 grad_norm: 5.1529 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0738 loss: 2.0738 2022/10/08 14:08:47 - mmengine - INFO - Epoch(train) [135][860/2119] lr: 4.0000e-03 eta: 2:50:03 time: 0.2973 data_time: 0.0183 memory: 5821 grad_norm: 5.1440 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8518 loss: 1.8518 2022/10/08 14:08:53 - mmengine - INFO - Epoch(train) [135][880/2119] lr: 4.0000e-03 eta: 2:49:52 time: 0.2698 data_time: 0.0163 memory: 5821 grad_norm: 5.0862 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.1683 loss: 2.1683 2022/10/08 14:08:59 - mmengine - INFO - Epoch(train) [135][900/2119] lr: 4.0000e-03 eta: 2:49:45 time: 0.2993 data_time: 0.0261 memory: 5821 grad_norm: 5.0810 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9091 loss: 1.9091 2022/10/08 14:09:05 - mmengine - INFO - Epoch(train) [135][920/2119] lr: 4.0000e-03 eta: 2:49:37 time: 0.3010 data_time: 0.0166 memory: 5821 grad_norm: 5.0953 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.8746 loss: 1.8746 2022/10/08 14:09:11 - mmengine - INFO - Epoch(train) [135][940/2119] lr: 4.0000e-03 eta: 2:49:34 time: 0.3325 data_time: 0.0185 memory: 5821 grad_norm: 5.1449 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0802 loss: 2.0802 2022/10/08 14:09:17 - mmengine - INFO - Epoch(train) [135][960/2119] lr: 4.0000e-03 eta: 2:49:22 time: 0.2609 data_time: 0.0179 memory: 5821 grad_norm: 5.2080 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9446 loss: 1.9446 2022/10/08 14:09:22 - mmengine - INFO - Epoch(train) [135][980/2119] lr: 4.0000e-03 eta: 2:49:13 time: 0.2845 data_time: 0.0208 memory: 5821 grad_norm: 5.1478 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0073 loss: 2.0073 2022/10/08 14:09:28 - mmengine - INFO - Epoch(train) [135][1000/2119] lr: 4.0000e-03 eta: 2:49:02 time: 0.2739 data_time: 0.0228 memory: 5821 grad_norm: 5.0947 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8840 loss: 1.8840 2022/10/08 14:09:34 - mmengine - INFO - Epoch(train) [135][1020/2119] lr: 4.0000e-03 eta: 2:48:54 time: 0.2902 data_time: 0.0181 memory: 5821 grad_norm: 5.1699 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9626 loss: 1.9626 2022/10/08 14:09:39 - mmengine - INFO - Epoch(train) [135][1040/2119] lr: 4.0000e-03 eta: 2:48:45 time: 0.2835 data_time: 0.0172 memory: 5821 grad_norm: 5.1120 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9591 loss: 1.9591 2022/10/08 14:09:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:09:45 - mmengine - INFO - Epoch(train) [135][1060/2119] lr: 4.0000e-03 eta: 2:48:35 time: 0.2817 data_time: 0.0199 memory: 5821 grad_norm: 5.1282 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8935 loss: 1.8935 2022/10/08 14:09:51 - mmengine - INFO - Epoch(train) [135][1080/2119] lr: 4.0000e-03 eta: 2:48:28 time: 0.2957 data_time: 0.0218 memory: 5821 grad_norm: 5.0154 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.8902 loss: 1.8902 2022/10/08 14:09:57 - mmengine - INFO - Epoch(train) [135][1100/2119] lr: 4.0000e-03 eta: 2:48:19 time: 0.2872 data_time: 0.0192 memory: 5821 grad_norm: 5.1108 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9918 loss: 1.9918 2022/10/08 14:10:02 - mmengine - INFO - Epoch(train) [135][1120/2119] lr: 4.0000e-03 eta: 2:48:11 time: 0.2903 data_time: 0.0214 memory: 5821 grad_norm: 5.1059 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6848 loss: 1.6848 2022/10/08 14:10:08 - mmengine - INFO - Epoch(train) [135][1140/2119] lr: 4.0000e-03 eta: 2:48:00 time: 0.2718 data_time: 0.0153 memory: 5821 grad_norm: 5.1124 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1715 loss: 2.1715 2022/10/08 14:10:14 - mmengine - INFO - Epoch(train) [135][1160/2119] lr: 4.0000e-03 eta: 2:47:53 time: 0.3010 data_time: 0.0159 memory: 5821 grad_norm: 5.2856 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9941 loss: 1.9941 2022/10/08 14:10:20 - mmengine - INFO - Epoch(train) [135][1180/2119] lr: 4.0000e-03 eta: 2:47:44 time: 0.2862 data_time: 0.0215 memory: 5821 grad_norm: 5.2896 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1415 loss: 2.1415 2022/10/08 14:10:25 - mmengine - INFO - Epoch(train) [135][1200/2119] lr: 4.0000e-03 eta: 2:47:34 time: 0.2740 data_time: 0.0136 memory: 5821 grad_norm: 5.2190 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9053 loss: 1.9053 2022/10/08 14:10:31 - mmengine - INFO - Epoch(train) [135][1220/2119] lr: 4.0000e-03 eta: 2:47:26 time: 0.2937 data_time: 0.0235 memory: 5821 grad_norm: 5.1372 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9667 loss: 1.9667 2022/10/08 14:10:37 - mmengine - INFO - Epoch(train) [135][1240/2119] lr: 4.0000e-03 eta: 2:47:21 time: 0.3103 data_time: 0.0182 memory: 5821 grad_norm: 5.0779 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.7986 loss: 1.7986 2022/10/08 14:10:43 - mmengine - INFO - Epoch(train) [135][1260/2119] lr: 4.0000e-03 eta: 2:47:12 time: 0.2856 data_time: 0.0170 memory: 5821 grad_norm: 5.0990 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8699 loss: 1.8699 2022/10/08 14:10:49 - mmengine - INFO - Epoch(train) [135][1280/2119] lr: 4.0000e-03 eta: 2:47:04 time: 0.2976 data_time: 0.0197 memory: 5821 grad_norm: 5.2894 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8819 loss: 1.8819 2022/10/08 14:10:55 - mmengine - INFO - Epoch(train) [135][1300/2119] lr: 4.0000e-03 eta: 2:46:57 time: 0.2920 data_time: 0.0187 memory: 5821 grad_norm: 5.1710 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9031 loss: 1.9031 2022/10/08 14:11:00 - mmengine - INFO - Epoch(train) [135][1320/2119] lr: 4.0000e-03 eta: 2:46:47 time: 0.2755 data_time: 0.0210 memory: 5821 grad_norm: 5.1487 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9826 loss: 1.9826 2022/10/08 14:11:07 - mmengine - INFO - Epoch(train) [135][1340/2119] lr: 4.0000e-03 eta: 2:46:44 time: 0.3379 data_time: 0.0179 memory: 5821 grad_norm: 5.0529 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9946 loss: 1.9946 2022/10/08 14:11:12 - mmengine - INFO - Epoch(train) [135][1360/2119] lr: 4.0000e-03 eta: 2:46:33 time: 0.2641 data_time: 0.0223 memory: 5821 grad_norm: 5.1876 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.0653 loss: 2.0653 2022/10/08 14:11:18 - mmengine - INFO - Epoch(train) [135][1380/2119] lr: 4.0000e-03 eta: 2:46:22 time: 0.2650 data_time: 0.0229 memory: 5821 grad_norm: 5.1341 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8996 loss: 1.8996 2022/10/08 14:11:23 - mmengine - INFO - Epoch(train) [135][1400/2119] lr: 4.0000e-03 eta: 2:46:12 time: 0.2766 data_time: 0.0163 memory: 5821 grad_norm: 5.1528 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0943 loss: 2.0943 2022/10/08 14:11:29 - mmengine - INFO - Epoch(train) [135][1420/2119] lr: 4.0000e-03 eta: 2:46:05 time: 0.2965 data_time: 0.0236 memory: 5821 grad_norm: 5.1996 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8233 loss: 1.8233 2022/10/08 14:11:35 - mmengine - INFO - Epoch(train) [135][1440/2119] lr: 4.0000e-03 eta: 2:45:56 time: 0.2785 data_time: 0.0187 memory: 5821 grad_norm: 5.1084 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1955 loss: 2.1955 2022/10/08 14:11:40 - mmengine - INFO - Epoch(train) [135][1460/2119] lr: 4.0000e-03 eta: 2:45:47 time: 0.2843 data_time: 0.0169 memory: 5821 grad_norm: 5.0074 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9176 loss: 1.9176 2022/10/08 14:11:46 - mmengine - INFO - Epoch(train) [135][1480/2119] lr: 4.0000e-03 eta: 2:45:39 time: 0.2897 data_time: 0.0209 memory: 5821 grad_norm: 5.2250 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 1.9722 loss: 1.9722 2022/10/08 14:11:52 - mmengine - INFO - Epoch(train) [135][1500/2119] lr: 4.0000e-03 eta: 2:45:33 time: 0.3086 data_time: 0.0211 memory: 5821 grad_norm: 5.2289 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0142 loss: 2.0142 2022/10/08 14:11:58 - mmengine - INFO - Epoch(train) [135][1520/2119] lr: 4.0000e-03 eta: 2:45:24 time: 0.2778 data_time: 0.0197 memory: 5821 grad_norm: 5.2611 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0255 loss: 2.0255 2022/10/08 14:12:04 - mmengine - INFO - Epoch(train) [135][1540/2119] lr: 4.0000e-03 eta: 2:45:15 time: 0.2807 data_time: 0.0179 memory: 5821 grad_norm: 5.2020 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1683 loss: 2.1683 2022/10/08 14:12:10 - mmengine - INFO - Epoch(train) [135][1560/2119] lr: 4.0000e-03 eta: 2:45:07 time: 0.2971 data_time: 0.0188 memory: 5821 grad_norm: 5.1525 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.0348 loss: 2.0348 2022/10/08 14:12:15 - mmengine - INFO - Epoch(train) [135][1580/2119] lr: 4.0000e-03 eta: 2:45:00 time: 0.2939 data_time: 0.0305 memory: 5821 grad_norm: 5.2377 top1_acc: 0.1875 top5_acc: 0.6250 loss_cls: 2.1388 loss: 2.1388 2022/10/08 14:12:21 - mmengine - INFO - Epoch(train) [135][1600/2119] lr: 4.0000e-03 eta: 2:44:51 time: 0.2773 data_time: 0.0224 memory: 5821 grad_norm: 5.2913 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0051 loss: 2.0051 2022/10/08 14:12:27 - mmengine - INFO - Epoch(train) [135][1620/2119] lr: 4.0000e-03 eta: 2:44:41 time: 0.2743 data_time: 0.0253 memory: 5821 grad_norm: 5.2330 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1834 loss: 2.1834 2022/10/08 14:12:33 - mmengine - INFO - Epoch(train) [135][1640/2119] lr: 4.0000e-03 eta: 2:44:36 time: 0.3137 data_time: 0.0203 memory: 5821 grad_norm: 5.1111 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7223 loss: 1.7223 2022/10/08 14:12:39 - mmengine - INFO - Epoch(train) [135][1660/2119] lr: 4.0000e-03 eta: 2:44:29 time: 0.3001 data_time: 0.0179 memory: 5821 grad_norm: 5.1949 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6800 loss: 1.6800 2022/10/08 14:12:45 - mmengine - INFO - Epoch(train) [135][1680/2119] lr: 4.0000e-03 eta: 2:44:18 time: 0.2603 data_time: 0.0209 memory: 5821 grad_norm: 5.3185 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0723 loss: 2.0723 2022/10/08 14:12:52 - mmengine - INFO - Epoch(train) [135][1700/2119] lr: 4.0000e-03 eta: 2:44:20 time: 0.3836 data_time: 0.0525 memory: 5821 grad_norm: 5.1738 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0074 loss: 2.0074 2022/10/08 14:12:57 - mmengine - INFO - Epoch(train) [135][1720/2119] lr: 4.0000e-03 eta: 2:44:08 time: 0.2476 data_time: 0.0166 memory: 5821 grad_norm: 5.1733 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0505 loss: 2.0505 2022/10/08 14:13:02 - mmengine - INFO - Epoch(train) [135][1740/2119] lr: 4.0000e-03 eta: 2:43:56 time: 0.2590 data_time: 0.0211 memory: 5821 grad_norm: 5.1279 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9944 loss: 1.9944 2022/10/08 14:13:08 - mmengine - INFO - Epoch(train) [135][1760/2119] lr: 4.0000e-03 eta: 2:43:48 time: 0.2864 data_time: 0.0146 memory: 5821 grad_norm: 5.1672 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7753 loss: 1.7753 2022/10/08 14:13:14 - mmengine - INFO - Epoch(train) [135][1780/2119] lr: 4.0000e-03 eta: 2:43:42 time: 0.3056 data_time: 0.0245 memory: 5821 grad_norm: 5.1437 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9954 loss: 1.9954 2022/10/08 14:13:19 - mmengine - INFO - Epoch(train) [135][1800/2119] lr: 4.0000e-03 eta: 2:43:34 time: 0.2844 data_time: 0.0188 memory: 5821 grad_norm: 5.0354 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9549 loss: 1.9549 2022/10/08 14:13:25 - mmengine - INFO - Epoch(train) [135][1820/2119] lr: 4.0000e-03 eta: 2:43:27 time: 0.3018 data_time: 0.0216 memory: 5821 grad_norm: 5.0664 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.8412 loss: 1.8412 2022/10/08 14:13:31 - mmengine - INFO - Epoch(train) [135][1840/2119] lr: 4.0000e-03 eta: 2:43:19 time: 0.2894 data_time: 0.0154 memory: 5821 grad_norm: 5.1932 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0205 loss: 2.0205 2022/10/08 14:13:37 - mmengine - INFO - Epoch(train) [135][1860/2119] lr: 4.0000e-03 eta: 2:43:10 time: 0.2753 data_time: 0.0213 memory: 5821 grad_norm: 5.2176 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1377 loss: 2.1377 2022/10/08 14:13:42 - mmengine - INFO - Epoch(train) [135][1880/2119] lr: 4.0000e-03 eta: 2:43:00 time: 0.2716 data_time: 0.0234 memory: 5821 grad_norm: 5.1801 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8464 loss: 1.8464 2022/10/08 14:13:48 - mmengine - INFO - Epoch(train) [135][1900/2119] lr: 4.0000e-03 eta: 2:42:55 time: 0.3076 data_time: 0.0192 memory: 5821 grad_norm: 5.1584 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2015 loss: 2.2015 2022/10/08 14:13:54 - mmengine - INFO - Epoch(train) [135][1920/2119] lr: 4.0000e-03 eta: 2:42:45 time: 0.2686 data_time: 0.0163 memory: 5821 grad_norm: 5.1902 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8512 loss: 1.8512 2022/10/08 14:13:59 - mmengine - INFO - Epoch(train) [135][1940/2119] lr: 4.0000e-03 eta: 2:42:37 time: 0.2862 data_time: 0.0172 memory: 5821 grad_norm: 5.2265 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8001 loss: 1.8001 2022/10/08 14:14:05 - mmengine - INFO - Epoch(train) [135][1960/2119] lr: 4.0000e-03 eta: 2:42:29 time: 0.2942 data_time: 0.0176 memory: 5821 grad_norm: 5.2011 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.2967 loss: 2.2967 2022/10/08 14:14:12 - mmengine - INFO - Epoch(train) [135][1980/2119] lr: 4.0000e-03 eta: 2:42:26 time: 0.3371 data_time: 0.0221 memory: 5821 grad_norm: 5.0882 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.9247 loss: 1.9247 2022/10/08 14:14:17 - mmengine - INFO - Epoch(train) [135][2000/2119] lr: 4.0000e-03 eta: 2:42:15 time: 0.2565 data_time: 0.0181 memory: 5821 grad_norm: 5.1090 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2866 loss: 2.2866 2022/10/08 14:14:23 - mmengine - INFO - Epoch(train) [135][2020/2119] lr: 4.0000e-03 eta: 2:42:05 time: 0.2628 data_time: 0.0172 memory: 5821 grad_norm: 5.1371 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9966 loss: 1.9966 2022/10/08 14:14:28 - mmengine - INFO - Epoch(train) [135][2040/2119] lr: 4.0000e-03 eta: 2:41:57 time: 0.2866 data_time: 0.0295 memory: 5821 grad_norm: 5.0699 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9239 loss: 1.9239 2022/10/08 14:14:33 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:14:34 - mmengine - INFO - Epoch(train) [135][2060/2119] lr: 4.0000e-03 eta: 2:41:50 time: 0.2914 data_time: 0.0189 memory: 5821 grad_norm: 5.0631 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8751 loss: 1.8751 2022/10/08 14:14:40 - mmengine - INFO - Epoch(train) [135][2080/2119] lr: 4.0000e-03 eta: 2:41:44 time: 0.3073 data_time: 0.0254 memory: 5821 grad_norm: 5.1497 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0769 loss: 2.0769 2022/10/08 14:14:46 - mmengine - INFO - Epoch(train) [135][2100/2119] lr: 4.0000e-03 eta: 2:41:34 time: 0.2729 data_time: 0.0194 memory: 5821 grad_norm: 5.1296 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9021 loss: 1.9021 2022/10/08 14:14:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:14:51 - mmengine - INFO - Epoch(train) [135][2119/2119] lr: 4.0000e-03 eta: 2:41:34 time: 0.2629 data_time: 0.0135 memory: 5821 grad_norm: 5.2746 top1_acc: 0.6000 top5_acc: 0.8000 loss_cls: 2.1002 loss: 2.1002 2022/10/08 14:16:31 - mmengine - INFO - Epoch(val) [135][20/137] eta: 0:09:44 time: 4.9970 data_time: 4.9054 memory: 1236 2022/10/08 14:16:35 - mmengine - INFO - Epoch(val) [135][40/137] eta: 0:00:20 time: 0.2160 data_time: 0.1481 memory: 1236 2022/10/08 14:16:41 - mmengine - INFO - Epoch(val) [135][60/137] eta: 0:00:23 time: 0.3033 data_time: 0.2376 memory: 1236 2022/10/08 14:16:45 - mmengine - INFO - Epoch(val) [135][80/137] eta: 0:00:12 time: 0.2120 data_time: 0.1494 memory: 1236 2022/10/08 14:16:51 - mmengine - INFO - Epoch(val) [135][100/137] eta: 0:00:10 time: 0.2909 data_time: 0.2265 memory: 1236 2022/10/08 14:16:55 - mmengine - INFO - Epoch(val) [135][120/137] eta: 0:00:03 time: 0.1993 data_time: 0.1342 memory: 1236 2022/10/08 14:17:04 - mmengine - INFO - Epoch(val) [135][137/137] acc/top1: 0.5419 acc/top5: 0.7698 acc/mean1: 0.5418 2022/10/08 14:17:12 - mmengine - INFO - Epoch(train) [136][20/2119] lr: 4.0000e-03 eta: 2:41:06 time: 0.4314 data_time: 0.1249 memory: 5821 grad_norm: 5.1089 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0876 loss: 2.0876 2022/10/08 14:17:18 - mmengine - INFO - Epoch(train) [136][40/2119] lr: 4.0000e-03 eta: 2:40:57 time: 0.2686 data_time: 0.0207 memory: 5821 grad_norm: 5.1648 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9006 loss: 1.9006 2022/10/08 14:17:24 - mmengine - INFO - Epoch(train) [136][60/2119] lr: 4.0000e-03 eta: 2:40:49 time: 0.2904 data_time: 0.0187 memory: 5821 grad_norm: 5.1658 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8346 loss: 1.8346 2022/10/08 14:17:29 - mmengine - INFO - Epoch(train) [136][80/2119] lr: 4.0000e-03 eta: 2:40:40 time: 0.2748 data_time: 0.0164 memory: 5821 grad_norm: 5.1001 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0670 loss: 2.0670 2022/10/08 14:17:35 - mmengine - INFO - Epoch(train) [136][100/2119] lr: 4.0000e-03 eta: 2:40:35 time: 0.3113 data_time: 0.0207 memory: 5821 grad_norm: 5.1779 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9734 loss: 1.9734 2022/10/08 14:17:42 - mmengine - INFO - Epoch(train) [136][120/2119] lr: 4.0000e-03 eta: 2:40:29 time: 0.3111 data_time: 0.0229 memory: 5821 grad_norm: 5.1244 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9402 loss: 1.9402 2022/10/08 14:17:47 - mmengine - INFO - Epoch(train) [136][140/2119] lr: 4.0000e-03 eta: 2:40:20 time: 0.2696 data_time: 0.0201 memory: 5821 grad_norm: 5.1932 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7722 loss: 1.7722 2022/10/08 14:17:52 - mmengine - INFO - Epoch(train) [136][160/2119] lr: 4.0000e-03 eta: 2:40:10 time: 0.2691 data_time: 0.0186 memory: 5821 grad_norm: 5.2387 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.0414 loss: 2.0414 2022/10/08 14:17:58 - mmengine - INFO - Epoch(train) [136][180/2119] lr: 4.0000e-03 eta: 2:40:02 time: 0.2836 data_time: 0.0188 memory: 5821 grad_norm: 5.2589 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9476 loss: 1.9476 2022/10/08 14:18:04 - mmengine - INFO - Epoch(train) [136][200/2119] lr: 4.0000e-03 eta: 2:39:55 time: 0.2892 data_time: 0.0205 memory: 5821 grad_norm: 5.1872 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5791 loss: 1.5791 2022/10/08 14:18:09 - mmengine - INFO - Epoch(train) [136][220/2119] lr: 4.0000e-03 eta: 2:39:45 time: 0.2656 data_time: 0.0205 memory: 5821 grad_norm: 5.2062 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9010 loss: 1.9010 2022/10/08 14:18:15 - mmengine - INFO - Epoch(train) [136][240/2119] lr: 4.0000e-03 eta: 2:39:38 time: 0.2900 data_time: 0.0189 memory: 5821 grad_norm: 5.2095 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0808 loss: 2.0808 2022/10/08 14:18:21 - mmengine - INFO - Epoch(train) [136][260/2119] lr: 4.0000e-03 eta: 2:39:32 time: 0.3040 data_time: 0.0244 memory: 5821 grad_norm: 5.2625 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9670 loss: 1.9670 2022/10/08 14:18:26 - mmengine - INFO - Epoch(train) [136][280/2119] lr: 4.0000e-03 eta: 2:39:22 time: 0.2605 data_time: 0.0271 memory: 5821 grad_norm: 5.1609 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.8041 loss: 1.8041 2022/10/08 14:18:32 - mmengine - INFO - Epoch(train) [136][300/2119] lr: 4.0000e-03 eta: 2:39:13 time: 0.2786 data_time: 0.0230 memory: 5821 grad_norm: 5.2025 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9296 loss: 1.9296 2022/10/08 14:18:38 - mmengine - INFO - Epoch(train) [136][320/2119] lr: 4.0000e-03 eta: 2:39:06 time: 0.2963 data_time: 0.0181 memory: 5821 grad_norm: 5.2411 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9909 loss: 1.9909 2022/10/08 14:18:44 - mmengine - INFO - Epoch(train) [136][340/2119] lr: 4.0000e-03 eta: 2:39:02 time: 0.3159 data_time: 0.0222 memory: 5821 grad_norm: 5.0558 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8555 loss: 1.8555 2022/10/08 14:18:49 - mmengine - INFO - Epoch(train) [136][360/2119] lr: 4.0000e-03 eta: 2:38:52 time: 0.2622 data_time: 0.0195 memory: 5821 grad_norm: 5.1394 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8154 loss: 1.8154 2022/10/08 14:18:55 - mmengine - INFO - Epoch(train) [136][380/2119] lr: 4.0000e-03 eta: 2:38:45 time: 0.2954 data_time: 0.0219 memory: 5821 grad_norm: 5.2106 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0436 loss: 2.0436 2022/10/08 14:19:02 - mmengine - INFO - Epoch(train) [136][400/2119] lr: 4.0000e-03 eta: 2:38:41 time: 0.3258 data_time: 0.0227 memory: 5821 grad_norm: 5.1057 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8228 loss: 1.8228 2022/10/08 14:19:07 - mmengine - INFO - Epoch(train) [136][420/2119] lr: 4.0000e-03 eta: 2:38:33 time: 0.2794 data_time: 0.0243 memory: 5821 grad_norm: 5.2339 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8672 loss: 1.8672 2022/10/08 14:19:13 - mmengine - INFO - Epoch(train) [136][440/2119] lr: 4.0000e-03 eta: 2:38:23 time: 0.2690 data_time: 0.0218 memory: 5821 grad_norm: 5.1277 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1772 loss: 2.1772 2022/10/08 14:19:18 - mmengine - INFO - Epoch(train) [136][460/2119] lr: 4.0000e-03 eta: 2:38:15 time: 0.2788 data_time: 0.0204 memory: 5821 grad_norm: 5.2446 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8661 loss: 1.8661 2022/10/08 14:19:24 - mmengine - INFO - Epoch(train) [136][480/2119] lr: 4.0000e-03 eta: 2:38:08 time: 0.2936 data_time: 0.0195 memory: 5821 grad_norm: 5.2911 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9967 loss: 1.9967 2022/10/08 14:19:30 - mmengine - INFO - Epoch(train) [136][500/2119] lr: 4.0000e-03 eta: 2:37:59 time: 0.2723 data_time: 0.0238 memory: 5821 grad_norm: 5.1703 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8662 loss: 1.8662 2022/10/08 14:19:36 - mmengine - INFO - Epoch(train) [136][520/2119] lr: 4.0000e-03 eta: 2:37:52 time: 0.2883 data_time: 0.0185 memory: 5821 grad_norm: 5.2360 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9921 loss: 1.9921 2022/10/08 14:19:42 - mmengine - INFO - Epoch(train) [136][540/2119] lr: 4.0000e-03 eta: 2:37:45 time: 0.2970 data_time: 0.0292 memory: 5821 grad_norm: 5.1367 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7742 loss: 1.7742 2022/10/08 14:19:47 - mmengine - INFO - Epoch(train) [136][560/2119] lr: 4.0000e-03 eta: 2:37:35 time: 0.2607 data_time: 0.0210 memory: 5821 grad_norm: 5.1781 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 1.7373 loss: 1.7373 2022/10/08 14:19:53 - mmengine - INFO - Epoch(train) [136][580/2119] lr: 4.0000e-03 eta: 2:37:29 time: 0.3034 data_time: 0.0203 memory: 5821 grad_norm: 5.1957 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6801 loss: 1.6801 2022/10/08 14:19:58 - mmengine - INFO - Epoch(train) [136][600/2119] lr: 4.0000e-03 eta: 2:37:21 time: 0.2770 data_time: 0.0231 memory: 5821 grad_norm: 5.1400 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9081 loss: 1.9081 2022/10/08 14:20:04 - mmengine - INFO - Epoch(train) [136][620/2119] lr: 4.0000e-03 eta: 2:37:14 time: 0.2897 data_time: 0.0191 memory: 5821 grad_norm: 5.1191 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1105 loss: 2.1105 2022/10/08 14:20:10 - mmengine - INFO - Epoch(train) [136][640/2119] lr: 4.0000e-03 eta: 2:37:08 time: 0.3027 data_time: 0.0147 memory: 5821 grad_norm: 5.2821 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1223 loss: 2.1223 2022/10/08 14:20:16 - mmengine - INFO - Epoch(train) [136][660/2119] lr: 4.0000e-03 eta: 2:36:58 time: 0.2655 data_time: 0.0218 memory: 5821 grad_norm: 5.1860 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.2043 loss: 2.2043 2022/10/08 14:20:22 - mmengine - INFO - Epoch(train) [136][680/2119] lr: 4.0000e-03 eta: 2:36:54 time: 0.3174 data_time: 0.0185 memory: 5821 grad_norm: 5.1618 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9177 loss: 1.9177 2022/10/08 14:20:27 - mmengine - INFO - Epoch(train) [136][700/2119] lr: 4.0000e-03 eta: 2:36:43 time: 0.2518 data_time: 0.0245 memory: 5821 grad_norm: 5.1366 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7924 loss: 1.7924 2022/10/08 14:20:33 - mmengine - INFO - Epoch(train) [136][720/2119] lr: 4.0000e-03 eta: 2:36:38 time: 0.3189 data_time: 0.0231 memory: 5821 grad_norm: 5.1770 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8940 loss: 1.8940 2022/10/08 14:20:39 - mmengine - INFO - Epoch(train) [136][740/2119] lr: 4.0000e-03 eta: 2:36:30 time: 0.2793 data_time: 0.0193 memory: 5821 grad_norm: 5.2325 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8283 loss: 1.8283 2022/10/08 14:20:45 - mmengine - INFO - Epoch(train) [136][760/2119] lr: 4.0000e-03 eta: 2:36:22 time: 0.2797 data_time: 0.0174 memory: 5821 grad_norm: 5.2010 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8448 loss: 1.8448 2022/10/08 14:20:50 - mmengine - INFO - Epoch(train) [136][780/2119] lr: 4.0000e-03 eta: 2:36:15 time: 0.2874 data_time: 0.0214 memory: 5821 grad_norm: 5.2075 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8177 loss: 1.8177 2022/10/08 14:20:56 - mmengine - INFO - Epoch(train) [136][800/2119] lr: 4.0000e-03 eta: 2:36:07 time: 0.2859 data_time: 0.0194 memory: 5821 grad_norm: 5.1576 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7617 loss: 1.7617 2022/10/08 14:21:02 - mmengine - INFO - Epoch(train) [136][820/2119] lr: 4.0000e-03 eta: 2:36:01 time: 0.2989 data_time: 0.0239 memory: 5821 grad_norm: 5.0778 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8034 loss: 1.8034 2022/10/08 14:21:08 - mmengine - INFO - Epoch(train) [136][840/2119] lr: 4.0000e-03 eta: 2:35:55 time: 0.2973 data_time: 0.0171 memory: 5821 grad_norm: 5.1623 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0121 loss: 2.0121 2022/10/08 14:21:13 - mmengine - INFO - Epoch(train) [136][860/2119] lr: 4.0000e-03 eta: 2:35:45 time: 0.2624 data_time: 0.0204 memory: 5821 grad_norm: 5.1599 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9015 loss: 1.9015 2022/10/08 14:21:20 - mmengine - INFO - Epoch(train) [136][880/2119] lr: 4.0000e-03 eta: 2:35:42 time: 0.3309 data_time: 0.0204 memory: 5821 grad_norm: 5.1723 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0491 loss: 2.0491 2022/10/08 14:21:25 - mmengine - INFO - Epoch(train) [136][900/2119] lr: 4.0000e-03 eta: 2:35:33 time: 0.2739 data_time: 0.0245 memory: 5821 grad_norm: 5.0556 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 1.9884 loss: 1.9884 2022/10/08 14:21:31 - mmengine - INFO - Epoch(train) [136][920/2119] lr: 4.0000e-03 eta: 2:35:26 time: 0.2908 data_time: 0.0235 memory: 5821 grad_norm: 5.2257 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2650 loss: 2.2650 2022/10/08 14:21:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:21:37 - mmengine - INFO - Epoch(train) [136][940/2119] lr: 4.0000e-03 eta: 2:35:20 time: 0.2993 data_time: 0.0284 memory: 5821 grad_norm: 5.1604 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0038 loss: 2.0038 2022/10/08 14:21:43 - mmengine - INFO - Epoch(train) [136][960/2119] lr: 4.0000e-03 eta: 2:35:12 time: 0.2757 data_time: 0.0177 memory: 5821 grad_norm: 5.2745 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9839 loss: 1.9839 2022/10/08 14:21:48 - mmengine - INFO - Epoch(train) [136][980/2119] lr: 4.0000e-03 eta: 2:35:03 time: 0.2752 data_time: 0.0276 memory: 5821 grad_norm: 5.2056 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9934 loss: 1.9934 2022/10/08 14:21:54 - mmengine - INFO - Epoch(train) [136][1000/2119] lr: 4.0000e-03 eta: 2:34:57 time: 0.2977 data_time: 0.0210 memory: 5821 grad_norm: 5.1609 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0508 loss: 2.0508 2022/10/08 14:22:00 - mmengine - INFO - Epoch(train) [136][1020/2119] lr: 4.0000e-03 eta: 2:34:51 time: 0.2991 data_time: 0.0189 memory: 5821 grad_norm: 5.1913 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.7471 loss: 1.7471 2022/10/08 14:22:06 - mmengine - INFO - Epoch(train) [136][1040/2119] lr: 4.0000e-03 eta: 2:34:44 time: 0.2950 data_time: 0.0189 memory: 5821 grad_norm: 5.1105 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.9399 loss: 1.9399 2022/10/08 14:22:12 - mmengine - INFO - Epoch(train) [136][1060/2119] lr: 4.0000e-03 eta: 2:34:35 time: 0.2712 data_time: 0.0217 memory: 5821 grad_norm: 5.2392 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0309 loss: 2.0309 2022/10/08 14:22:17 - mmengine - INFO - Epoch(train) [136][1080/2119] lr: 4.0000e-03 eta: 2:34:26 time: 0.2636 data_time: 0.0204 memory: 5821 grad_norm: 5.1419 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.8932 loss: 1.8932 2022/10/08 14:22:23 - mmengine - INFO - Epoch(train) [136][1100/2119] lr: 4.0000e-03 eta: 2:34:19 time: 0.2882 data_time: 0.0182 memory: 5821 grad_norm: 5.2220 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9295 loss: 1.9295 2022/10/08 14:22:28 - mmengine - INFO - Epoch(train) [136][1120/2119] lr: 4.0000e-03 eta: 2:34:11 time: 0.2790 data_time: 0.0204 memory: 5821 grad_norm: 5.2115 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8552 loss: 1.8552 2022/10/08 14:22:34 - mmengine - INFO - Epoch(train) [136][1140/2119] lr: 4.0000e-03 eta: 2:34:05 time: 0.3060 data_time: 0.0236 memory: 5821 grad_norm: 5.1549 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0019 loss: 2.0019 2022/10/08 14:22:40 - mmengine - INFO - Epoch(train) [136][1160/2119] lr: 4.0000e-03 eta: 2:33:57 time: 0.2673 data_time: 0.0244 memory: 5821 grad_norm: 5.1623 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.9094 loss: 1.9094 2022/10/08 14:22:45 - mmengine - INFO - Epoch(train) [136][1180/2119] lr: 4.0000e-03 eta: 2:33:50 time: 0.2930 data_time: 0.0214 memory: 5821 grad_norm: 5.1501 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9898 loss: 1.9898 2022/10/08 14:22:52 - mmengine - INFO - Epoch(train) [136][1200/2119] lr: 4.0000e-03 eta: 2:33:47 time: 0.3389 data_time: 0.0204 memory: 5821 grad_norm: 5.2943 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9572 loss: 1.9572 2022/10/08 14:22:58 - mmengine - INFO - Epoch(train) [136][1220/2119] lr: 4.0000e-03 eta: 2:33:38 time: 0.2729 data_time: 0.0234 memory: 5821 grad_norm: 5.1137 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.9900 loss: 1.9900 2022/10/08 14:23:04 - mmengine - INFO - Epoch(train) [136][1240/2119] lr: 4.0000e-03 eta: 2:33:31 time: 0.2894 data_time: 0.0161 memory: 5821 grad_norm: 5.1245 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9116 loss: 1.9116 2022/10/08 14:23:10 - mmengine - INFO - Epoch(train) [136][1260/2119] lr: 4.0000e-03 eta: 2:33:26 time: 0.3039 data_time: 0.0210 memory: 5821 grad_norm: 5.2130 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9651 loss: 1.9651 2022/10/08 14:23:22 - mmengine - INFO - Epoch(train) [136][1280/2119] lr: 4.0000e-03 eta: 2:33:45 time: 0.6145 data_time: 0.2988 memory: 5821 grad_norm: 5.1583 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6656 loss: 1.6656 2022/10/08 14:23:27 - mmengine - INFO - Epoch(train) [136][1300/2119] lr: 4.0000e-03 eta: 2:33:34 time: 0.2500 data_time: 0.0165 memory: 5821 grad_norm: 5.1713 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0250 loss: 2.0250 2022/10/08 14:23:32 - mmengine - INFO - Epoch(train) [136][1320/2119] lr: 4.0000e-03 eta: 2:33:26 time: 0.2756 data_time: 0.0212 memory: 5821 grad_norm: 5.2083 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.2860 loss: 2.2860 2022/10/08 14:23:38 - mmengine - INFO - Epoch(train) [136][1340/2119] lr: 4.0000e-03 eta: 2:33:19 time: 0.2901 data_time: 0.0229 memory: 5821 grad_norm: 5.0734 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.8478 loss: 1.8478 2022/10/08 14:23:44 - mmengine - INFO - Epoch(train) [136][1360/2119] lr: 4.0000e-03 eta: 2:33:12 time: 0.2858 data_time: 0.0191 memory: 5821 grad_norm: 5.1695 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.9585 loss: 1.9585 2022/10/08 14:23:50 - mmengine - INFO - Epoch(train) [136][1380/2119] lr: 4.0000e-03 eta: 2:33:06 time: 0.2993 data_time: 0.0294 memory: 5821 grad_norm: 5.1596 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0526 loss: 2.0526 2022/10/08 14:23:56 - mmengine - INFO - Epoch(train) [136][1400/2119] lr: 4.0000e-03 eta: 2:32:58 time: 0.2877 data_time: 0.0210 memory: 5821 grad_norm: 5.1412 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.9985 loss: 1.9985 2022/10/08 14:24:01 - mmengine - INFO - Epoch(train) [136][1420/2119] lr: 4.0000e-03 eta: 2:32:50 time: 0.2738 data_time: 0.0188 memory: 5821 grad_norm: 5.1361 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9230 loss: 1.9230 2022/10/08 14:24:07 - mmengine - INFO - Epoch(train) [136][1440/2119] lr: 4.0000e-03 eta: 2:32:42 time: 0.2721 data_time: 0.0201 memory: 5821 grad_norm: 5.1784 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.9373 loss: 1.9373 2022/10/08 14:24:12 - mmengine - INFO - Epoch(train) [136][1460/2119] lr: 4.0000e-03 eta: 2:32:34 time: 0.2846 data_time: 0.0243 memory: 5821 grad_norm: 5.1509 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0003 loss: 2.0003 2022/10/08 14:24:19 - mmengine - INFO - Epoch(train) [136][1480/2119] lr: 4.0000e-03 eta: 2:32:29 time: 0.3053 data_time: 0.0187 memory: 5821 grad_norm: 5.1966 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0878 loss: 2.0878 2022/10/08 14:24:24 - mmengine - INFO - Epoch(train) [136][1500/2119] lr: 4.0000e-03 eta: 2:32:20 time: 0.2707 data_time: 0.0192 memory: 5821 grad_norm: 5.3156 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0717 loss: 2.0717 2022/10/08 14:24:30 - mmengine - INFO - Epoch(train) [136][1520/2119] lr: 4.0000e-03 eta: 2:32:14 time: 0.2940 data_time: 0.0250 memory: 5821 grad_norm: 5.2348 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.8516 loss: 1.8516 2022/10/08 14:24:35 - mmengine - INFO - Epoch(train) [136][1540/2119] lr: 4.0000e-03 eta: 2:32:04 time: 0.2620 data_time: 0.0191 memory: 5821 grad_norm: 5.3328 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8895 loss: 1.8895 2022/10/08 14:24:41 - mmengine - INFO - Epoch(train) [136][1560/2119] lr: 4.0000e-03 eta: 2:31:57 time: 0.2799 data_time: 0.0167 memory: 5821 grad_norm: 5.2429 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8179 loss: 1.8179 2022/10/08 14:24:46 - mmengine - INFO - Epoch(train) [136][1580/2119] lr: 4.0000e-03 eta: 2:31:49 time: 0.2799 data_time: 0.0204 memory: 5821 grad_norm: 5.2163 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.0942 loss: 2.0942 2022/10/08 14:24:53 - mmengine - INFO - Epoch(train) [136][1600/2119] lr: 4.0000e-03 eta: 2:31:44 time: 0.3130 data_time: 0.0216 memory: 5821 grad_norm: 5.1614 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.0196 loss: 2.0196 2022/10/08 14:24:59 - mmengine - INFO - Epoch(train) [136][1620/2119] lr: 4.0000e-03 eta: 2:31:37 time: 0.2943 data_time: 0.0176 memory: 5821 grad_norm: 5.1735 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0243 loss: 2.0243 2022/10/08 14:25:10 - mmengine - INFO - Epoch(train) [136][1640/2119] lr: 4.0000e-03 eta: 2:31:51 time: 0.5687 data_time: 0.3333 memory: 5821 grad_norm: 5.1186 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7187 loss: 1.7187 2022/10/08 14:25:15 - mmengine - INFO - Epoch(train) [136][1660/2119] lr: 4.0000e-03 eta: 2:31:42 time: 0.2522 data_time: 0.0188 memory: 5821 grad_norm: 5.2264 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0180 loss: 2.0180 2022/10/08 14:25:20 - mmengine - INFO - Epoch(train) [136][1680/2119] lr: 4.0000e-03 eta: 2:31:33 time: 0.2705 data_time: 0.0174 memory: 5821 grad_norm: 5.1585 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.7894 loss: 1.7894 2022/10/08 14:25:27 - mmengine - INFO - Epoch(train) [136][1700/2119] lr: 4.0000e-03 eta: 2:31:29 time: 0.3207 data_time: 0.0193 memory: 5821 grad_norm: 5.1975 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0857 loss: 2.0857 2022/10/08 14:25:33 - mmengine - INFO - Epoch(train) [136][1720/2119] lr: 4.0000e-03 eta: 2:31:22 time: 0.2938 data_time: 0.0152 memory: 5821 grad_norm: 5.0901 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0235 loss: 2.0235 2022/10/08 14:25:38 - mmengine - INFO - Epoch(train) [136][1740/2119] lr: 4.0000e-03 eta: 2:31:14 time: 0.2813 data_time: 0.0325 memory: 5821 grad_norm: 5.1888 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1692 loss: 2.1692 2022/10/08 14:25:44 - mmengine - INFO - Epoch(train) [136][1760/2119] lr: 4.0000e-03 eta: 2:31:06 time: 0.2718 data_time: 0.0241 memory: 5821 grad_norm: 5.1609 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8298 loss: 1.8298 2022/10/08 14:25:49 - mmengine - INFO - Epoch(train) [136][1780/2119] lr: 4.0000e-03 eta: 2:30:58 time: 0.2791 data_time: 0.0224 memory: 5821 grad_norm: 5.2196 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2725 loss: 2.2725 2022/10/08 14:25:55 - mmengine - INFO - Epoch(train) [136][1800/2119] lr: 4.0000e-03 eta: 2:30:52 time: 0.2968 data_time: 0.0179 memory: 5821 grad_norm: 5.1939 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1540 loss: 2.1540 2022/10/08 14:26:02 - mmengine - INFO - Epoch(train) [136][1820/2119] lr: 4.0000e-03 eta: 2:30:49 time: 0.3380 data_time: 0.0166 memory: 5821 grad_norm: 5.2330 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8502 loss: 1.8502 2022/10/08 14:26:08 - mmengine - INFO - Epoch(train) [136][1840/2119] lr: 4.0000e-03 eta: 2:30:42 time: 0.2924 data_time: 0.0154 memory: 5821 grad_norm: 5.1253 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7516 loss: 1.7516 2022/10/08 14:26:13 - mmengine - INFO - Epoch(train) [136][1860/2119] lr: 4.0000e-03 eta: 2:30:33 time: 0.2585 data_time: 0.0202 memory: 5821 grad_norm: 5.1069 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9441 loss: 1.9441 2022/10/08 14:26:19 - mmengine - INFO - Epoch(train) [136][1880/2119] lr: 4.0000e-03 eta: 2:30:25 time: 0.2797 data_time: 0.0153 memory: 5821 grad_norm: 5.2561 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0433 loss: 2.0433 2022/10/08 14:26:25 - mmengine - INFO - Epoch(train) [136][1900/2119] lr: 4.0000e-03 eta: 2:30:19 time: 0.2979 data_time: 0.0200 memory: 5821 grad_norm: 5.1614 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6598 loss: 1.6598 2022/10/08 14:26:30 - mmengine - INFO - Epoch(train) [136][1920/2119] lr: 4.0000e-03 eta: 2:30:11 time: 0.2862 data_time: 0.0213 memory: 5821 grad_norm: 5.2244 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.8459 loss: 1.8459 2022/10/08 14:26:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:26:36 - mmengine - INFO - Epoch(train) [136][1940/2119] lr: 4.0000e-03 eta: 2:30:05 time: 0.2932 data_time: 0.0153 memory: 5821 grad_norm: 5.2178 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0074 loss: 2.0074 2022/10/08 14:26:43 - mmengine - INFO - Epoch(train) [136][1960/2119] lr: 4.0000e-03 eta: 2:30:01 time: 0.3371 data_time: 0.0230 memory: 5821 grad_norm: 5.1717 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0989 loss: 2.0989 2022/10/08 14:26:48 - mmengine - INFO - Epoch(train) [136][1980/2119] lr: 4.0000e-03 eta: 2:29:51 time: 0.2490 data_time: 0.0160 memory: 5821 grad_norm: 5.1878 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 2.0704 loss: 2.0704 2022/10/08 14:26:53 - mmengine - INFO - Epoch(train) [136][2000/2119] lr: 4.0000e-03 eta: 2:29:43 time: 0.2699 data_time: 0.0282 memory: 5821 grad_norm: 5.2301 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9330 loss: 1.9330 2022/10/08 14:26:59 - mmengine - INFO - Epoch(train) [136][2020/2119] lr: 4.0000e-03 eta: 2:29:35 time: 0.2664 data_time: 0.0211 memory: 5821 grad_norm: 5.1765 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8027 loss: 1.8027 2022/10/08 14:27:05 - mmengine - INFO - Epoch(train) [136][2040/2119] lr: 4.0000e-03 eta: 2:29:31 time: 0.3296 data_time: 0.0195 memory: 5821 grad_norm: 5.1813 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9950 loss: 1.9950 2022/10/08 14:27:11 - mmengine - INFO - Epoch(train) [136][2060/2119] lr: 4.0000e-03 eta: 2:29:23 time: 0.2850 data_time: 0.0155 memory: 5821 grad_norm: 5.1692 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9606 loss: 1.9606 2022/10/08 14:27:17 - mmengine - INFO - Epoch(train) [136][2080/2119] lr: 4.0000e-03 eta: 2:29:17 time: 0.2939 data_time: 0.0230 memory: 5821 grad_norm: 5.2235 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0321 loss: 2.0321 2022/10/08 14:27:23 - mmengine - INFO - Epoch(train) [136][2100/2119] lr: 4.0000e-03 eta: 2:29:11 time: 0.3002 data_time: 0.0179 memory: 5821 grad_norm: 5.1838 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9385 loss: 1.9385 2022/10/08 14:27:28 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:27:28 - mmengine - INFO - Epoch(train) [136][2119/2119] lr: 4.0000e-03 eta: 2:29:11 time: 0.2528 data_time: 0.0121 memory: 5821 grad_norm: 5.2927 top1_acc: 0.6000 top5_acc: 0.6000 loss_cls: 2.0360 loss: 2.0360 2022/10/08 14:27:28 - mmengine - INFO - Saving checkpoint at 136 epochs 2022/10/08 14:27:36 - mmengine - INFO - Epoch(train) [137][20/2119] lr: 4.0000e-03 eta: 2:28:42 time: 0.3510 data_time: 0.1273 memory: 5821 grad_norm: 5.1958 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.6802 loss: 1.6802 2022/10/08 14:27:42 - mmengine - INFO - Epoch(train) [137][40/2119] lr: 4.0000e-03 eta: 2:28:34 time: 0.2727 data_time: 0.0165 memory: 5821 grad_norm: 5.0942 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 1.9194 loss: 1.9194 2022/10/08 14:27:48 - mmengine - INFO - Epoch(train) [137][60/2119] lr: 4.0000e-03 eta: 2:28:28 time: 0.2999 data_time: 0.0282 memory: 5821 grad_norm: 5.0989 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9119 loss: 1.9119 2022/10/08 14:27:53 - mmengine - INFO - Epoch(train) [137][80/2119] lr: 4.0000e-03 eta: 2:28:21 time: 0.2773 data_time: 0.0193 memory: 5821 grad_norm: 5.2267 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9331 loss: 1.9331 2022/10/08 14:28:00 - mmengine - INFO - Epoch(train) [137][100/2119] lr: 4.0000e-03 eta: 2:28:16 time: 0.3206 data_time: 0.0215 memory: 5821 grad_norm: 5.1997 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9401 loss: 1.9401 2022/10/08 14:28:06 - mmengine - INFO - Epoch(train) [137][120/2119] lr: 4.0000e-03 eta: 2:28:10 time: 0.2939 data_time: 0.0192 memory: 5821 grad_norm: 5.2690 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9133 loss: 1.9133 2022/10/08 14:28:11 - mmengine - INFO - Epoch(train) [137][140/2119] lr: 4.0000e-03 eta: 2:28:01 time: 0.2584 data_time: 0.0271 memory: 5821 grad_norm: 5.1584 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8301 loss: 1.8301 2022/10/08 14:28:16 - mmengine - INFO - Epoch(train) [137][160/2119] lr: 4.0000e-03 eta: 2:27:52 time: 0.2643 data_time: 0.0233 memory: 5821 grad_norm: 5.3166 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9893 loss: 1.9893 2022/10/08 14:28:23 - mmengine - INFO - Epoch(train) [137][180/2119] lr: 4.0000e-03 eta: 2:27:47 time: 0.3149 data_time: 0.0204 memory: 5821 grad_norm: 5.2992 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9376 loss: 1.9376 2022/10/08 14:28:29 - mmengine - INFO - Epoch(train) [137][200/2119] lr: 4.0000e-03 eta: 2:27:41 time: 0.3013 data_time: 0.0154 memory: 5821 grad_norm: 5.2871 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7542 loss: 1.7542 2022/10/08 14:28:34 - mmengine - INFO - Epoch(train) [137][220/2119] lr: 4.0000e-03 eta: 2:27:33 time: 0.2642 data_time: 0.0213 memory: 5821 grad_norm: 5.2208 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8991 loss: 1.8991 2022/10/08 14:28:40 - mmengine - INFO - Epoch(train) [137][240/2119] lr: 4.0000e-03 eta: 2:27:28 time: 0.3175 data_time: 0.0202 memory: 5821 grad_norm: 5.1241 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0577 loss: 2.0577 2022/10/08 14:28:46 - mmengine - INFO - Epoch(train) [137][260/2119] lr: 4.0000e-03 eta: 2:27:20 time: 0.2785 data_time: 0.0207 memory: 5821 grad_norm: 5.2541 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2135 loss: 2.2135 2022/10/08 14:28:52 - mmengine - INFO - Epoch(train) [137][280/2119] lr: 4.0000e-03 eta: 2:27:14 time: 0.3006 data_time: 0.0213 memory: 5821 grad_norm: 5.2409 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9942 loss: 1.9942 2022/10/08 14:28:57 - mmengine - INFO - Epoch(train) [137][300/2119] lr: 4.0000e-03 eta: 2:27:05 time: 0.2607 data_time: 0.0171 memory: 5821 grad_norm: 5.1589 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8830 loss: 1.8830 2022/10/08 14:29:03 - mmengine - INFO - Epoch(train) [137][320/2119] lr: 4.0000e-03 eta: 2:26:58 time: 0.2816 data_time: 0.0183 memory: 5821 grad_norm: 5.2152 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8756 loss: 1.8756 2022/10/08 14:29:09 - mmengine - INFO - Epoch(train) [137][340/2119] lr: 4.0000e-03 eta: 2:26:52 time: 0.2984 data_time: 0.0170 memory: 5821 grad_norm: 5.1772 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8976 loss: 1.8976 2022/10/08 14:29:14 - mmengine - INFO - Epoch(train) [137][360/2119] lr: 4.0000e-03 eta: 2:26:44 time: 0.2682 data_time: 0.0173 memory: 5821 grad_norm: 5.2566 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9998 loss: 1.9998 2022/10/08 14:29:21 - mmengine - INFO - Epoch(train) [137][380/2119] lr: 4.0000e-03 eta: 2:26:39 time: 0.3246 data_time: 0.0187 memory: 5821 grad_norm: 5.1893 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9420 loss: 1.9420 2022/10/08 14:29:26 - mmengine - INFO - Epoch(train) [137][400/2119] lr: 4.0000e-03 eta: 2:26:31 time: 0.2681 data_time: 0.0200 memory: 5821 grad_norm: 5.2327 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8366 loss: 1.8366 2022/10/08 14:29:31 - mmengine - INFO - Epoch(train) [137][420/2119] lr: 4.0000e-03 eta: 2:26:23 time: 0.2695 data_time: 0.0226 memory: 5821 grad_norm: 5.3247 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.8970 loss: 1.8970 2022/10/08 14:29:37 - mmengine - INFO - Epoch(train) [137][440/2119] lr: 4.0000e-03 eta: 2:26:17 time: 0.2973 data_time: 0.0182 memory: 5821 grad_norm: 5.2150 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8505 loss: 1.8505 2022/10/08 14:29:43 - mmengine - INFO - Epoch(train) [137][460/2119] lr: 4.0000e-03 eta: 2:26:11 time: 0.2972 data_time: 0.0215 memory: 5821 grad_norm: 5.1904 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.9907 loss: 1.9907 2022/10/08 14:29:49 - mmengine - INFO - Epoch(train) [137][480/2119] lr: 4.0000e-03 eta: 2:26:03 time: 0.2768 data_time: 0.0162 memory: 5821 grad_norm: 5.1602 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.1821 loss: 2.1821 2022/10/08 14:29:55 - mmengine - INFO - Epoch(train) [137][500/2119] lr: 4.0000e-03 eta: 2:25:59 time: 0.3189 data_time: 0.0204 memory: 5821 grad_norm: 5.1728 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.0022 loss: 2.0022 2022/10/08 14:30:00 - mmengine - INFO - Epoch(train) [137][520/2119] lr: 4.0000e-03 eta: 2:25:49 time: 0.2534 data_time: 0.0278 memory: 5821 grad_norm: 5.2386 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9061 loss: 1.9061 2022/10/08 14:30:06 - mmengine - INFO - Epoch(train) [137][540/2119] lr: 4.0000e-03 eta: 2:25:43 time: 0.2967 data_time: 0.0246 memory: 5821 grad_norm: 5.1451 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 1.8965 loss: 1.8965 2022/10/08 14:30:12 - mmengine - INFO - Epoch(train) [137][560/2119] lr: 4.0000e-03 eta: 2:25:36 time: 0.2879 data_time: 0.0164 memory: 5821 grad_norm: 5.1329 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8806 loss: 1.8806 2022/10/08 14:30:18 - mmengine - INFO - Epoch(train) [137][580/2119] lr: 4.0000e-03 eta: 2:25:30 time: 0.2972 data_time: 0.0198 memory: 5821 grad_norm: 5.3177 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9667 loss: 1.9667 2022/10/08 14:30:24 - mmengine - INFO - Epoch(train) [137][600/2119] lr: 4.0000e-03 eta: 2:25:25 time: 0.3141 data_time: 0.0185 memory: 5821 grad_norm: 5.3034 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.8679 loss: 1.8679 2022/10/08 14:30:29 - mmengine - INFO - Epoch(train) [137][620/2119] lr: 4.0000e-03 eta: 2:25:16 time: 0.2573 data_time: 0.0236 memory: 5821 grad_norm: 5.2693 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 1.9615 loss: 1.9615 2022/10/08 14:30:35 - mmengine - INFO - Epoch(train) [137][640/2119] lr: 4.0000e-03 eta: 2:25:10 time: 0.2999 data_time: 0.0223 memory: 5821 grad_norm: 5.1918 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8093 loss: 1.8093 2022/10/08 14:30:42 - mmengine - INFO - Epoch(train) [137][660/2119] lr: 4.0000e-03 eta: 2:25:05 time: 0.3130 data_time: 0.0194 memory: 5821 grad_norm: 5.1784 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8975 loss: 1.8975 2022/10/08 14:30:47 - mmengine - INFO - Epoch(train) [137][680/2119] lr: 4.0000e-03 eta: 2:24:58 time: 0.2834 data_time: 0.0144 memory: 5821 grad_norm: 5.2159 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8977 loss: 1.8977 2022/10/08 14:30:54 - mmengine - INFO - Epoch(train) [137][700/2119] lr: 4.0000e-03 eta: 2:24:53 time: 0.3134 data_time: 0.0213 memory: 5821 grad_norm: 5.2117 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9040 loss: 1.9040 2022/10/08 14:30:59 - mmengine - INFO - Epoch(train) [137][720/2119] lr: 4.0000e-03 eta: 2:24:45 time: 0.2615 data_time: 0.0258 memory: 5821 grad_norm: 5.1734 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.2998 loss: 2.2998 2022/10/08 14:31:05 - mmengine - INFO - Epoch(train) [137][740/2119] lr: 4.0000e-03 eta: 2:24:38 time: 0.2936 data_time: 0.0250 memory: 5821 grad_norm: 5.2007 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0407 loss: 2.0407 2022/10/08 14:31:10 - mmengine - INFO - Epoch(train) [137][760/2119] lr: 4.0000e-03 eta: 2:24:30 time: 0.2646 data_time: 0.0189 memory: 5821 grad_norm: 5.1501 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8835 loss: 1.8835 2022/10/08 14:31:16 - mmengine - INFO - Epoch(train) [137][780/2119] lr: 4.0000e-03 eta: 2:24:23 time: 0.2928 data_time: 0.0154 memory: 5821 grad_norm: 5.1999 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.9009 loss: 1.9009 2022/10/08 14:31:22 - mmengine - INFO - Epoch(train) [137][800/2119] lr: 4.0000e-03 eta: 2:24:19 time: 0.3175 data_time: 0.0158 memory: 5821 grad_norm: 5.2010 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.8859 loss: 1.8859 2022/10/08 14:31:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:31:28 - mmengine - INFO - Epoch(train) [137][820/2119] lr: 4.0000e-03 eta: 2:24:11 time: 0.2779 data_time: 0.0191 memory: 5821 grad_norm: 5.2370 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9446 loss: 1.9446 2022/10/08 14:31:34 - mmengine - INFO - Epoch(train) [137][840/2119] lr: 4.0000e-03 eta: 2:24:05 time: 0.2951 data_time: 0.0187 memory: 5821 grad_norm: 5.0933 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8413 loss: 1.8413 2022/10/08 14:31:39 - mmengine - INFO - Epoch(train) [137][860/2119] lr: 4.0000e-03 eta: 2:23:57 time: 0.2714 data_time: 0.0215 memory: 5821 grad_norm: 5.2054 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9588 loss: 1.9588 2022/10/08 14:31:45 - mmengine - INFO - Epoch(train) [137][880/2119] lr: 4.0000e-03 eta: 2:23:52 time: 0.3054 data_time: 0.0204 memory: 5821 grad_norm: 5.2289 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9165 loss: 1.9165 2022/10/08 14:31:51 - mmengine - INFO - Epoch(train) [137][900/2119] lr: 4.0000e-03 eta: 2:23:45 time: 0.2963 data_time: 0.0178 memory: 5821 grad_norm: 5.1405 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9690 loss: 1.9690 2022/10/08 14:31:56 - mmengine - INFO - Epoch(train) [137][920/2119] lr: 4.0000e-03 eta: 2:23:37 time: 0.2614 data_time: 0.0180 memory: 5821 grad_norm: 5.2313 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9066 loss: 1.9066 2022/10/08 14:32:02 - mmengine - INFO - Epoch(train) [137][940/2119] lr: 4.0000e-03 eta: 2:23:30 time: 0.2807 data_time: 0.0212 memory: 5821 grad_norm: 5.2809 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.1859 loss: 2.1859 2022/10/08 14:32:08 - mmengine - INFO - Epoch(train) [137][960/2119] lr: 4.0000e-03 eta: 2:23:23 time: 0.2794 data_time: 0.0220 memory: 5821 grad_norm: 5.1803 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 1.8725 loss: 1.8725 2022/10/08 14:32:14 - mmengine - INFO - Epoch(train) [137][980/2119] lr: 4.0000e-03 eta: 2:23:17 time: 0.2992 data_time: 0.0196 memory: 5821 grad_norm: 5.0937 top1_acc: 0.5625 top5_acc: 1.0000 loss_cls: 1.9534 loss: 1.9534 2022/10/08 14:32:19 - mmengine - INFO - Epoch(train) [137][1000/2119] lr: 4.0000e-03 eta: 2:23:10 time: 0.2892 data_time: 0.0183 memory: 5821 grad_norm: 5.3032 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9305 loss: 1.9305 2022/10/08 14:32:25 - mmengine - INFO - Epoch(train) [137][1020/2119] lr: 4.0000e-03 eta: 2:23:04 time: 0.3014 data_time: 0.0228 memory: 5821 grad_norm: 5.1877 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2053 loss: 2.2053 2022/10/08 14:32:31 - mmengine - INFO - Epoch(train) [137][1040/2119] lr: 4.0000e-03 eta: 2:22:57 time: 0.2831 data_time: 0.0166 memory: 5821 grad_norm: 5.2908 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9988 loss: 1.9988 2022/10/08 14:32:37 - mmengine - INFO - Epoch(train) [137][1060/2119] lr: 4.0000e-03 eta: 2:22:49 time: 0.2704 data_time: 0.0214 memory: 5821 grad_norm: 5.2601 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9667 loss: 1.9667 2022/10/08 14:32:42 - mmengine - INFO - Epoch(train) [137][1080/2119] lr: 4.0000e-03 eta: 2:22:42 time: 0.2707 data_time: 0.0148 memory: 5821 grad_norm: 5.2366 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0247 loss: 2.0247 2022/10/08 14:32:48 - mmengine - INFO - Epoch(train) [137][1100/2119] lr: 4.0000e-03 eta: 2:22:36 time: 0.3031 data_time: 0.0197 memory: 5821 grad_norm: 5.0994 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 1.9050 loss: 1.9050 2022/10/08 14:32:54 - mmengine - INFO - Epoch(train) [137][1120/2119] lr: 4.0000e-03 eta: 2:22:30 time: 0.3066 data_time: 0.0195 memory: 5821 grad_norm: 5.1474 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9050 loss: 1.9050 2022/10/08 14:33:00 - mmengine - INFO - Epoch(train) [137][1140/2119] lr: 4.0000e-03 eta: 2:22:24 time: 0.3039 data_time: 0.0187 memory: 5821 grad_norm: 5.1386 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8626 loss: 1.8626 2022/10/08 14:33:06 - mmengine - INFO - Epoch(train) [137][1160/2119] lr: 4.0000e-03 eta: 2:22:17 time: 0.2693 data_time: 0.0153 memory: 5821 grad_norm: 5.1774 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.2604 loss: 2.2604 2022/10/08 14:33:11 - mmengine - INFO - Epoch(train) [137][1180/2119] lr: 4.0000e-03 eta: 2:22:08 time: 0.2594 data_time: 0.0148 memory: 5821 grad_norm: 5.1761 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8581 loss: 1.8581 2022/10/08 14:33:16 - mmengine - INFO - Epoch(train) [137][1200/2119] lr: 4.0000e-03 eta: 2:22:01 time: 0.2790 data_time: 0.0204 memory: 5821 grad_norm: 5.1998 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0643 loss: 2.0643 2022/10/08 14:33:23 - mmengine - INFO - Epoch(train) [137][1220/2119] lr: 4.0000e-03 eta: 2:21:56 time: 0.3211 data_time: 0.0213 memory: 5821 grad_norm: 5.2439 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9930 loss: 1.9930 2022/10/08 14:33:28 - mmengine - INFO - Epoch(train) [137][1240/2119] lr: 4.0000e-03 eta: 2:21:49 time: 0.2782 data_time: 0.0209 memory: 5821 grad_norm: 5.1773 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9313 loss: 1.9313 2022/10/08 14:33:35 - mmengine - INFO - Epoch(train) [137][1260/2119] lr: 4.0000e-03 eta: 2:21:43 time: 0.3038 data_time: 0.0231 memory: 5821 grad_norm: 5.2404 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8157 loss: 1.8157 2022/10/08 14:33:40 - mmengine - INFO - Epoch(train) [137][1280/2119] lr: 4.0000e-03 eta: 2:21:36 time: 0.2753 data_time: 0.0155 memory: 5821 grad_norm: 5.2603 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7225 loss: 1.7225 2022/10/08 14:33:45 - mmengine - INFO - Epoch(train) [137][1300/2119] lr: 4.0000e-03 eta: 2:21:28 time: 0.2559 data_time: 0.0195 memory: 5821 grad_norm: 5.2365 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.7111 loss: 1.7111 2022/10/08 14:33:51 - mmengine - INFO - Epoch(train) [137][1320/2119] lr: 4.0000e-03 eta: 2:21:22 time: 0.3012 data_time: 0.0171 memory: 5821 grad_norm: 5.1899 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8708 loss: 1.8708 2022/10/08 14:33:57 - mmengine - INFO - Epoch(train) [137][1340/2119] lr: 4.0000e-03 eta: 2:21:16 time: 0.2956 data_time: 0.0199 memory: 5821 grad_norm: 5.2863 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.0735 loss: 2.0735 2022/10/08 14:34:03 - mmengine - INFO - Epoch(train) [137][1360/2119] lr: 4.0000e-03 eta: 2:21:09 time: 0.2858 data_time: 0.0207 memory: 5821 grad_norm: 5.1515 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0225 loss: 2.0225 2022/10/08 14:34:09 - mmengine - INFO - Epoch(train) [137][1380/2119] lr: 4.0000e-03 eta: 2:21:02 time: 0.2907 data_time: 0.0513 memory: 5821 grad_norm: 5.1475 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 1.8652 loss: 1.8652 2022/10/08 14:34:14 - mmengine - INFO - Epoch(train) [137][1400/2119] lr: 4.0000e-03 eta: 2:20:54 time: 0.2639 data_time: 0.0186 memory: 5821 grad_norm: 5.1785 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.0408 loss: 2.0408 2022/10/08 14:34:19 - mmengine - INFO - Epoch(train) [137][1420/2119] lr: 4.0000e-03 eta: 2:20:47 time: 0.2743 data_time: 0.0239 memory: 5821 grad_norm: 5.2763 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9306 loss: 1.9306 2022/10/08 14:34:26 - mmengine - INFO - Epoch(train) [137][1440/2119] lr: 4.0000e-03 eta: 2:20:41 time: 0.3034 data_time: 0.0223 memory: 5821 grad_norm: 5.1902 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.9171 loss: 1.9171 2022/10/08 14:34:31 - mmengine - INFO - Epoch(train) [137][1460/2119] lr: 4.0000e-03 eta: 2:20:34 time: 0.2787 data_time: 0.0159 memory: 5821 grad_norm: 5.2092 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8213 loss: 1.8213 2022/10/08 14:34:37 - mmengine - INFO - Epoch(train) [137][1480/2119] lr: 4.0000e-03 eta: 2:20:28 time: 0.2941 data_time: 0.0186 memory: 5821 grad_norm: 5.1727 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0931 loss: 2.0931 2022/10/08 14:34:43 - mmengine - INFO - Epoch(train) [137][1500/2119] lr: 4.0000e-03 eta: 2:20:21 time: 0.2910 data_time: 0.0232 memory: 5821 grad_norm: 5.1744 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1104 loss: 2.1104 2022/10/08 14:34:48 - mmengine - INFO - Epoch(train) [137][1520/2119] lr: 4.0000e-03 eta: 2:20:14 time: 0.2726 data_time: 0.0222 memory: 5821 grad_norm: 5.3189 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9652 loss: 1.9652 2022/10/08 14:34:54 - mmengine - INFO - Epoch(train) [137][1540/2119] lr: 4.0000e-03 eta: 2:20:08 time: 0.3005 data_time: 0.0233 memory: 5821 grad_norm: 5.2773 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0452 loss: 2.0452 2022/10/08 14:35:00 - mmengine - INFO - Epoch(train) [137][1560/2119] lr: 4.0000e-03 eta: 2:20:01 time: 0.2830 data_time: 0.0284 memory: 5821 grad_norm: 5.1886 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8069 loss: 1.8069 2022/10/08 14:35:05 - mmengine - INFO - Epoch(train) [137][1580/2119] lr: 4.0000e-03 eta: 2:19:53 time: 0.2622 data_time: 0.0248 memory: 5821 grad_norm: 5.1348 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9407 loss: 1.9407 2022/10/08 14:35:11 - mmengine - INFO - Epoch(train) [137][1600/2119] lr: 4.0000e-03 eta: 2:19:46 time: 0.2720 data_time: 0.0184 memory: 5821 grad_norm: 5.2572 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9578 loss: 1.9578 2022/10/08 14:35:17 - mmengine - INFO - Epoch(train) [137][1620/2119] lr: 4.0000e-03 eta: 2:19:40 time: 0.3051 data_time: 0.0199 memory: 5821 grad_norm: 5.2819 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7075 loss: 1.7075 2022/10/08 14:35:23 - mmengine - INFO - Epoch(train) [137][1640/2119] lr: 4.0000e-03 eta: 2:19:34 time: 0.3046 data_time: 0.0154 memory: 5821 grad_norm: 5.3322 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1942 loss: 2.1942 2022/10/08 14:35:28 - mmengine - INFO - Epoch(train) [137][1660/2119] lr: 4.0000e-03 eta: 2:19:27 time: 0.2722 data_time: 0.0227 memory: 5821 grad_norm: 5.2306 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7574 loss: 1.7574 2022/10/08 14:35:34 - mmengine - INFO - Epoch(train) [137][1680/2119] lr: 4.0000e-03 eta: 2:19:21 time: 0.3020 data_time: 0.0220 memory: 5821 grad_norm: 5.2575 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8612 loss: 1.8612 2022/10/08 14:35:40 - mmengine - INFO - Epoch(train) [137][1700/2119] lr: 4.0000e-03 eta: 2:19:14 time: 0.2820 data_time: 0.0169 memory: 5821 grad_norm: 5.2275 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7852 loss: 1.7852 2022/10/08 14:35:46 - mmengine - INFO - Epoch(train) [137][1720/2119] lr: 4.0000e-03 eta: 2:19:08 time: 0.2954 data_time: 0.0164 memory: 5821 grad_norm: 5.1408 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0800 loss: 2.0800 2022/10/08 14:35:52 - mmengine - INFO - Epoch(train) [137][1740/2119] lr: 4.0000e-03 eta: 2:19:03 time: 0.3170 data_time: 0.0200 memory: 5821 grad_norm: 5.2709 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8861 loss: 1.8861 2022/10/08 14:35:58 - mmengine - INFO - Epoch(train) [137][1760/2119] lr: 4.0000e-03 eta: 2:18:56 time: 0.2735 data_time: 0.0178 memory: 5821 grad_norm: 5.2494 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7365 loss: 1.7365 2022/10/08 14:36:03 - mmengine - INFO - Epoch(train) [137][1780/2119] lr: 4.0000e-03 eta: 2:18:48 time: 0.2710 data_time: 0.0232 memory: 5821 grad_norm: 5.2690 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0618 loss: 2.0618 2022/10/08 14:36:09 - mmengine - INFO - Epoch(train) [137][1800/2119] lr: 4.0000e-03 eta: 2:18:40 time: 0.2658 data_time: 0.0253 memory: 5821 grad_norm: 5.3224 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0589 loss: 2.0589 2022/10/08 14:36:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:36:15 - mmengine - INFO - Epoch(train) [137][1820/2119] lr: 4.0000e-03 eta: 2:18:35 time: 0.3144 data_time: 0.0165 memory: 5821 grad_norm: 5.2621 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1089 loss: 2.1089 2022/10/08 14:36:21 - mmengine - INFO - Epoch(train) [137][1840/2119] lr: 4.0000e-03 eta: 2:18:30 time: 0.3040 data_time: 0.0166 memory: 5821 grad_norm: 5.2131 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.7830 loss: 1.7830 2022/10/08 14:36:26 - mmengine - INFO - Epoch(train) [137][1860/2119] lr: 4.0000e-03 eta: 2:18:22 time: 0.2700 data_time: 0.0266 memory: 5821 grad_norm: 5.2913 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9569 loss: 1.9569 2022/10/08 14:36:32 - mmengine - INFO - Epoch(train) [137][1880/2119] lr: 4.0000e-03 eta: 2:18:15 time: 0.2838 data_time: 0.0177 memory: 5821 grad_norm: 5.2947 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1019 loss: 2.1019 2022/10/08 14:36:38 - mmengine - INFO - Epoch(train) [137][1900/2119] lr: 4.0000e-03 eta: 2:18:10 time: 0.3086 data_time: 0.0196 memory: 5821 grad_norm: 5.2370 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8660 loss: 1.8660 2022/10/08 14:36:44 - mmengine - INFO - Epoch(train) [137][1920/2119] lr: 4.0000e-03 eta: 2:18:03 time: 0.2721 data_time: 0.0210 memory: 5821 grad_norm: 5.1569 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7766 loss: 1.7766 2022/10/08 14:36:50 - mmengine - INFO - Epoch(train) [137][1940/2119] lr: 4.0000e-03 eta: 2:17:57 time: 0.3002 data_time: 0.0164 memory: 5821 grad_norm: 5.1232 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0044 loss: 2.0044 2022/10/08 14:36:55 - mmengine - INFO - Epoch(train) [137][1960/2119] lr: 4.0000e-03 eta: 2:17:50 time: 0.2789 data_time: 0.0158 memory: 5821 grad_norm: 5.1728 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1027 loss: 2.1027 2022/10/08 14:37:02 - mmengine - INFO - Epoch(train) [137][1980/2119] lr: 4.0000e-03 eta: 2:17:45 time: 0.3146 data_time: 0.0148 memory: 5821 grad_norm: 5.1442 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0465 loss: 2.0465 2022/10/08 14:37:07 - mmengine - INFO - Epoch(train) [137][2000/2119] lr: 4.0000e-03 eta: 2:17:37 time: 0.2608 data_time: 0.0207 memory: 5821 grad_norm: 5.4910 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8947 loss: 1.8947 2022/10/08 14:37:12 - mmengine - INFO - Epoch(train) [137][2020/2119] lr: 4.0000e-03 eta: 2:17:30 time: 0.2793 data_time: 0.0211 memory: 5821 grad_norm: 5.2676 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9218 loss: 1.9218 2022/10/08 14:37:19 - mmengine - INFO - Epoch(train) [137][2040/2119] lr: 4.0000e-03 eta: 2:17:24 time: 0.3100 data_time: 0.0193 memory: 5821 grad_norm: 5.1908 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9417 loss: 1.9417 2022/10/08 14:37:24 - mmengine - INFO - Epoch(train) [137][2060/2119] lr: 4.0000e-03 eta: 2:17:16 time: 0.2583 data_time: 0.0203 memory: 5821 grad_norm: 5.1737 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1017 loss: 2.1017 2022/10/08 14:37:30 - mmengine - INFO - Epoch(train) [137][2080/2119] lr: 4.0000e-03 eta: 2:17:10 time: 0.2968 data_time: 0.0204 memory: 5821 grad_norm: 5.2304 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.8765 loss: 1.8765 2022/10/08 14:37:35 - mmengine - INFO - Epoch(train) [137][2100/2119] lr: 4.0000e-03 eta: 2:17:02 time: 0.2655 data_time: 0.0258 memory: 5821 grad_norm: 5.2070 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9662 loss: 1.9662 2022/10/08 14:37:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:37:40 - mmengine - INFO - Epoch(train) [137][2119/2119] lr: 4.0000e-03 eta: 2:17:02 time: 0.2701 data_time: 0.0165 memory: 5821 grad_norm: 5.2599 top1_acc: 0.6000 top5_acc: 0.7000 loss_cls: 1.8112 loss: 1.8112 2022/10/08 14:37:48 - mmengine - INFO - Epoch(train) [138][20/2119] lr: 4.0000e-03 eta: 2:16:42 time: 0.4034 data_time: 0.1093 memory: 5821 grad_norm: 5.2384 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9616 loss: 1.9616 2022/10/08 14:37:54 - mmengine - INFO - Epoch(train) [138][40/2119] lr: 4.0000e-03 eta: 2:16:35 time: 0.2779 data_time: 0.0181 memory: 5821 grad_norm: 5.1760 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.0307 loss: 2.0307 2022/10/08 14:38:00 - mmengine - INFO - Epoch(train) [138][60/2119] lr: 4.0000e-03 eta: 2:16:28 time: 0.2926 data_time: 0.0294 memory: 5821 grad_norm: 5.2249 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8360 loss: 1.8360 2022/10/08 14:38:06 - mmengine - INFO - Epoch(train) [138][80/2119] lr: 4.0000e-03 eta: 2:16:22 time: 0.2933 data_time: 0.0212 memory: 5821 grad_norm: 5.2210 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9783 loss: 1.9783 2022/10/08 14:38:11 - mmengine - INFO - Epoch(train) [138][100/2119] lr: 4.0000e-03 eta: 2:16:15 time: 0.2805 data_time: 0.0196 memory: 5821 grad_norm: 5.2012 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.0415 loss: 2.0415 2022/10/08 14:38:17 - mmengine - INFO - Epoch(train) [138][120/2119] lr: 4.0000e-03 eta: 2:16:08 time: 0.2779 data_time: 0.0193 memory: 5821 grad_norm: 5.2255 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.7131 loss: 1.7131 2022/10/08 14:38:23 - mmengine - INFO - Epoch(train) [138][140/2119] lr: 4.0000e-03 eta: 2:16:02 time: 0.2941 data_time: 0.0260 memory: 5821 grad_norm: 5.3292 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0080 loss: 2.0080 2022/10/08 14:38:28 - mmengine - INFO - Epoch(train) [138][160/2119] lr: 4.0000e-03 eta: 2:15:55 time: 0.2738 data_time: 0.0256 memory: 5821 grad_norm: 5.1974 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9385 loss: 1.9385 2022/10/08 14:38:34 - mmengine - INFO - Epoch(train) [138][180/2119] lr: 4.0000e-03 eta: 2:15:48 time: 0.2761 data_time: 0.0217 memory: 5821 grad_norm: 5.1165 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.7760 loss: 1.7760 2022/10/08 14:38:40 - mmengine - INFO - Epoch(train) [138][200/2119] lr: 4.0000e-03 eta: 2:15:42 time: 0.3030 data_time: 0.0180 memory: 5821 grad_norm: 5.2296 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9212 loss: 1.9212 2022/10/08 14:38:46 - mmengine - INFO - Epoch(train) [138][220/2119] lr: 4.0000e-03 eta: 2:15:35 time: 0.2819 data_time: 0.0205 memory: 5821 grad_norm: 5.1894 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7409 loss: 1.7409 2022/10/08 14:38:51 - mmengine - INFO - Epoch(train) [138][240/2119] lr: 4.0000e-03 eta: 2:15:29 time: 0.2922 data_time: 0.0184 memory: 5821 grad_norm: 5.2491 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7813 loss: 1.7813 2022/10/08 14:38:57 - mmengine - INFO - Epoch(train) [138][260/2119] lr: 4.0000e-03 eta: 2:15:23 time: 0.2880 data_time: 0.0178 memory: 5821 grad_norm: 5.2792 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9646 loss: 1.9646 2022/10/08 14:39:03 - mmengine - INFO - Epoch(train) [138][280/2119] lr: 4.0000e-03 eta: 2:15:16 time: 0.2842 data_time: 0.0156 memory: 5821 grad_norm: 5.2026 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.0231 loss: 2.0231 2022/10/08 14:39:09 - mmengine - INFO - Epoch(train) [138][300/2119] lr: 4.0000e-03 eta: 2:15:10 time: 0.2985 data_time: 0.0167 memory: 5821 grad_norm: 5.2527 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0022 loss: 2.0022 2022/10/08 14:39:15 - mmengine - INFO - Epoch(train) [138][320/2119] lr: 4.0000e-03 eta: 2:15:04 time: 0.2962 data_time: 0.0209 memory: 5821 grad_norm: 5.2134 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5633 loss: 1.5633 2022/10/08 14:39:20 - mmengine - INFO - Epoch(train) [138][340/2119] lr: 4.0000e-03 eta: 2:14:56 time: 0.2579 data_time: 0.0244 memory: 5821 grad_norm: 5.2510 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7672 loss: 1.7672 2022/10/08 14:39:25 - mmengine - INFO - Epoch(train) [138][360/2119] lr: 4.0000e-03 eta: 2:14:49 time: 0.2759 data_time: 0.0170 memory: 5821 grad_norm: 5.2525 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0252 loss: 2.0252 2022/10/08 14:39:31 - mmengine - INFO - Epoch(train) [138][380/2119] lr: 4.0000e-03 eta: 2:14:43 time: 0.2871 data_time: 0.0175 memory: 5821 grad_norm: 5.2435 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8079 loss: 1.8079 2022/10/08 14:39:37 - mmengine - INFO - Epoch(train) [138][400/2119] lr: 4.0000e-03 eta: 2:14:37 time: 0.3105 data_time: 0.0174 memory: 5821 grad_norm: 5.2443 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 1.8597 loss: 1.8597 2022/10/08 14:39:43 - mmengine - INFO - Epoch(train) [138][420/2119] lr: 4.0000e-03 eta: 2:14:31 time: 0.2944 data_time: 0.0198 memory: 5821 grad_norm: 5.2889 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9403 loss: 1.9403 2022/10/08 14:39:49 - mmengine - INFO - Epoch(train) [138][440/2119] lr: 4.0000e-03 eta: 2:14:25 time: 0.2802 data_time: 0.0153 memory: 5821 grad_norm: 5.2435 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7461 loss: 1.7461 2022/10/08 14:39:54 - mmengine - INFO - Epoch(train) [138][460/2119] lr: 4.0000e-03 eta: 2:14:18 time: 0.2762 data_time: 0.0258 memory: 5821 grad_norm: 5.2384 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8853 loss: 1.8853 2022/10/08 14:40:00 - mmengine - INFO - Epoch(train) [138][480/2119] lr: 4.0000e-03 eta: 2:14:11 time: 0.2912 data_time: 0.0165 memory: 5821 grad_norm: 5.1777 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7749 loss: 1.7749 2022/10/08 14:40:06 - mmengine - INFO - Epoch(train) [138][500/2119] lr: 4.0000e-03 eta: 2:14:04 time: 0.2720 data_time: 0.0224 memory: 5821 grad_norm: 5.2482 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8923 loss: 1.8923 2022/10/08 14:40:12 - mmengine - INFO - Epoch(train) [138][520/2119] lr: 4.0000e-03 eta: 2:13:58 time: 0.2988 data_time: 0.0205 memory: 5821 grad_norm: 5.1961 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8910 loss: 1.8910 2022/10/08 14:40:18 - mmengine - INFO - Epoch(train) [138][540/2119] lr: 4.0000e-03 eta: 2:13:52 time: 0.2971 data_time: 0.0223 memory: 5821 grad_norm: 5.2942 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0411 loss: 2.0411 2022/10/08 14:40:23 - mmengine - INFO - Epoch(train) [138][560/2119] lr: 4.0000e-03 eta: 2:13:46 time: 0.2861 data_time: 0.0160 memory: 5821 grad_norm: 5.2264 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.1829 loss: 2.1829 2022/10/08 14:40:30 - mmengine - INFO - Epoch(train) [138][580/2119] lr: 4.0000e-03 eta: 2:13:41 time: 0.3244 data_time: 0.0156 memory: 5821 grad_norm: 5.2226 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.0616 loss: 2.0616 2022/10/08 14:40:35 - mmengine - INFO - Epoch(train) [138][600/2119] lr: 4.0000e-03 eta: 2:13:33 time: 0.2572 data_time: 0.0228 memory: 5821 grad_norm: 5.1840 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9001 loss: 1.9001 2022/10/08 14:40:42 - mmengine - INFO - Epoch(train) [138][620/2119] lr: 4.0000e-03 eta: 2:13:29 time: 0.3408 data_time: 0.0188 memory: 5821 grad_norm: 5.0887 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9443 loss: 1.9443 2022/10/08 14:40:48 - mmengine - INFO - Epoch(train) [138][640/2119] lr: 4.0000e-03 eta: 2:13:23 time: 0.2918 data_time: 0.0184 memory: 5821 grad_norm: 5.2865 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.8883 loss: 1.8883 2022/10/08 14:40:53 - mmengine - INFO - Epoch(train) [138][660/2119] lr: 4.0000e-03 eta: 2:13:16 time: 0.2760 data_time: 0.0386 memory: 5821 grad_norm: 5.3322 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9297 loss: 1.9297 2022/10/08 14:40:59 - mmengine - INFO - Epoch(train) [138][680/2119] lr: 4.0000e-03 eta: 2:13:10 time: 0.2875 data_time: 0.0242 memory: 5821 grad_norm: 5.3040 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6164 loss: 1.6164 2022/10/08 14:41:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:41:05 - mmengine - INFO - Epoch(train) [138][700/2119] lr: 4.0000e-03 eta: 2:13:04 time: 0.2934 data_time: 0.0215 memory: 5821 grad_norm: 5.3182 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.8506 loss: 1.8506 2022/10/08 14:41:10 - mmengine - INFO - Epoch(train) [138][720/2119] lr: 4.0000e-03 eta: 2:12:56 time: 0.2661 data_time: 0.0225 memory: 5821 grad_norm: 5.3336 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8454 loss: 1.8454 2022/10/08 14:41:16 - mmengine - INFO - Epoch(train) [138][740/2119] lr: 4.0000e-03 eta: 2:12:49 time: 0.2794 data_time: 0.0263 memory: 5821 grad_norm: 5.2497 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9420 loss: 1.9420 2022/10/08 14:41:22 - mmengine - INFO - Epoch(train) [138][760/2119] lr: 4.0000e-03 eta: 2:12:44 time: 0.3103 data_time: 0.0170 memory: 5821 grad_norm: 5.1675 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7737 loss: 1.7737 2022/10/08 14:41:28 - mmengine - INFO - Epoch(train) [138][780/2119] lr: 4.0000e-03 eta: 2:12:38 time: 0.3004 data_time: 0.0255 memory: 5821 grad_norm: 5.3166 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9414 loss: 1.9414 2022/10/08 14:41:34 - mmengine - INFO - Epoch(train) [138][800/2119] lr: 4.0000e-03 eta: 2:12:32 time: 0.2951 data_time: 0.0189 memory: 5821 grad_norm: 5.2599 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0549 loss: 2.0549 2022/10/08 14:41:40 - mmengine - INFO - Epoch(train) [138][820/2119] lr: 4.0000e-03 eta: 2:12:26 time: 0.2993 data_time: 0.0182 memory: 5821 grad_norm: 5.2073 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9579 loss: 1.9579 2022/10/08 14:41:46 - mmengine - INFO - Epoch(train) [138][840/2119] lr: 4.0000e-03 eta: 2:12:20 time: 0.2946 data_time: 0.0192 memory: 5821 grad_norm: 5.2322 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.7423 loss: 1.7423 2022/10/08 14:41:52 - mmengine - INFO - Epoch(train) [138][860/2119] lr: 4.0000e-03 eta: 2:12:14 time: 0.2853 data_time: 0.0182 memory: 5821 grad_norm: 5.1862 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9738 loss: 1.9738 2022/10/08 14:41:58 - mmengine - INFO - Epoch(train) [138][880/2119] lr: 4.0000e-03 eta: 2:12:08 time: 0.2960 data_time: 0.0225 memory: 5821 grad_norm: 5.2630 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0581 loss: 2.0581 2022/10/08 14:42:03 - mmengine - INFO - Epoch(train) [138][900/2119] lr: 4.0000e-03 eta: 2:12:01 time: 0.2760 data_time: 0.0180 memory: 5821 grad_norm: 5.2616 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9335 loss: 1.9335 2022/10/08 14:42:09 - mmengine - INFO - Epoch(train) [138][920/2119] lr: 4.0000e-03 eta: 2:11:54 time: 0.2877 data_time: 0.0170 memory: 5821 grad_norm: 5.2669 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9612 loss: 1.9612 2022/10/08 14:42:16 - mmengine - INFO - Epoch(train) [138][940/2119] lr: 4.0000e-03 eta: 2:11:52 time: 0.3705 data_time: 0.1134 memory: 5821 grad_norm: 5.2804 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9398 loss: 1.9398 2022/10/08 14:42:21 - mmengine - INFO - Epoch(train) [138][960/2119] lr: 4.0000e-03 eta: 2:11:44 time: 0.2522 data_time: 0.0180 memory: 5821 grad_norm: 5.3023 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1066 loss: 2.1066 2022/10/08 14:42:27 - mmengine - INFO - Epoch(train) [138][980/2119] lr: 4.0000e-03 eta: 2:11:37 time: 0.2703 data_time: 0.0186 memory: 5821 grad_norm: 5.2578 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.1450 loss: 2.1450 2022/10/08 14:42:33 - mmengine - INFO - Epoch(train) [138][1000/2119] lr: 4.0000e-03 eta: 2:11:31 time: 0.2980 data_time: 0.0211 memory: 5821 grad_norm: 5.2393 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.6967 loss: 1.6967 2022/10/08 14:42:39 - mmengine - INFO - Epoch(train) [138][1020/2119] lr: 4.0000e-03 eta: 2:11:25 time: 0.2961 data_time: 0.0199 memory: 5821 grad_norm: 5.2257 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0995 loss: 2.0995 2022/10/08 14:42:44 - mmengine - INFO - Epoch(train) [138][1040/2119] lr: 4.0000e-03 eta: 2:11:18 time: 0.2884 data_time: 0.0221 memory: 5821 grad_norm: 5.3211 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8248 loss: 1.8248 2022/10/08 14:42:50 - mmengine - INFO - Epoch(train) [138][1060/2119] lr: 4.0000e-03 eta: 2:11:12 time: 0.2895 data_time: 0.0230 memory: 5821 grad_norm: 5.2962 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9383 loss: 1.9383 2022/10/08 14:42:57 - mmengine - INFO - Epoch(train) [138][1080/2119] lr: 4.0000e-03 eta: 2:11:08 time: 0.3345 data_time: 0.0200 memory: 5821 grad_norm: 5.2063 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7502 loss: 1.7502 2022/10/08 14:43:02 - mmengine - INFO - Epoch(train) [138][1100/2119] lr: 4.0000e-03 eta: 2:11:00 time: 0.2627 data_time: 0.0175 memory: 5821 grad_norm: 5.2181 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8497 loss: 1.8497 2022/10/08 14:43:08 - mmengine - INFO - Epoch(train) [138][1120/2119] lr: 4.0000e-03 eta: 2:10:54 time: 0.2928 data_time: 0.0229 memory: 5821 grad_norm: 5.2674 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8945 loss: 1.8945 2022/10/08 14:43:14 - mmengine - INFO - Epoch(train) [138][1140/2119] lr: 4.0000e-03 eta: 2:10:48 time: 0.2867 data_time: 0.0226 memory: 5821 grad_norm: 5.2148 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7372 loss: 1.7372 2022/10/08 14:43:19 - mmengine - INFO - Epoch(train) [138][1160/2119] lr: 4.0000e-03 eta: 2:10:41 time: 0.2770 data_time: 0.0134 memory: 5821 grad_norm: 5.2564 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9885 loss: 1.9885 2022/10/08 14:43:25 - mmengine - INFO - Epoch(train) [138][1180/2119] lr: 4.0000e-03 eta: 2:10:34 time: 0.2799 data_time: 0.0189 memory: 5821 grad_norm: 5.2857 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0836 loss: 2.0836 2022/10/08 14:43:31 - mmengine - INFO - Epoch(train) [138][1200/2119] lr: 4.0000e-03 eta: 2:10:28 time: 0.2960 data_time: 0.0240 memory: 5821 grad_norm: 5.3326 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8507 loss: 1.8507 2022/10/08 14:43:37 - mmengine - INFO - Epoch(train) [138][1220/2119] lr: 4.0000e-03 eta: 2:10:22 time: 0.2904 data_time: 0.0181 memory: 5821 grad_norm: 5.1344 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8948 loss: 1.8948 2022/10/08 14:43:43 - mmengine - INFO - Epoch(train) [138][1240/2119] lr: 4.0000e-03 eta: 2:10:16 time: 0.3040 data_time: 0.0158 memory: 5821 grad_norm: 5.3154 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9467 loss: 1.9467 2022/10/08 14:43:49 - mmengine - INFO - Epoch(train) [138][1260/2119] lr: 4.0000e-03 eta: 2:10:11 time: 0.3069 data_time: 0.0174 memory: 5821 grad_norm: 5.2992 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0022 loss: 2.0022 2022/10/08 14:43:54 - mmengine - INFO - Epoch(train) [138][1280/2119] lr: 4.0000e-03 eta: 2:10:04 time: 0.2739 data_time: 0.0186 memory: 5821 grad_norm: 5.2879 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.9366 loss: 1.9366 2022/10/08 14:44:00 - mmengine - INFO - Epoch(train) [138][1300/2119] lr: 4.0000e-03 eta: 2:09:57 time: 0.2807 data_time: 0.0233 memory: 5821 grad_norm: 5.2578 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9442 loss: 1.9442 2022/10/08 14:44:06 - mmengine - INFO - Epoch(train) [138][1320/2119] lr: 4.0000e-03 eta: 2:09:50 time: 0.2787 data_time: 0.0184 memory: 5821 grad_norm: 5.3830 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9944 loss: 1.9944 2022/10/08 14:44:11 - mmengine - INFO - Epoch(train) [138][1340/2119] lr: 4.0000e-03 eta: 2:09:43 time: 0.2707 data_time: 0.0203 memory: 5821 grad_norm: 5.2276 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8843 loss: 1.8843 2022/10/08 14:44:17 - mmengine - INFO - Epoch(train) [138][1360/2119] lr: 4.0000e-03 eta: 2:09:37 time: 0.2784 data_time: 0.0244 memory: 5821 grad_norm: 5.3471 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.8257 loss: 1.8257 2022/10/08 14:44:22 - mmengine - INFO - Epoch(train) [138][1380/2119] lr: 4.0000e-03 eta: 2:09:30 time: 0.2857 data_time: 0.0183 memory: 5821 grad_norm: 5.3887 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9328 loss: 1.9328 2022/10/08 14:44:28 - mmengine - INFO - Epoch(train) [138][1400/2119] lr: 4.0000e-03 eta: 2:09:24 time: 0.2870 data_time: 0.0245 memory: 5821 grad_norm: 5.3084 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7844 loss: 1.7844 2022/10/08 14:44:34 - mmengine - INFO - Epoch(train) [138][1420/2119] lr: 4.0000e-03 eta: 2:09:18 time: 0.2952 data_time: 0.0329 memory: 5821 grad_norm: 5.3115 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0636 loss: 2.0636 2022/10/08 14:44:40 - mmengine - INFO - Epoch(train) [138][1440/2119] lr: 4.0000e-03 eta: 2:09:11 time: 0.2805 data_time: 0.0142 memory: 5821 grad_norm: 5.3838 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1621 loss: 2.1621 2022/10/08 14:44:46 - mmengine - INFO - Epoch(train) [138][1460/2119] lr: 4.0000e-03 eta: 2:09:06 time: 0.3061 data_time: 0.0254 memory: 5821 grad_norm: 5.3929 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0157 loss: 2.0157 2022/10/08 14:44:52 - mmengine - INFO - Epoch(train) [138][1480/2119] lr: 4.0000e-03 eta: 2:08:59 time: 0.2915 data_time: 0.0182 memory: 5821 grad_norm: 5.2612 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7527 loss: 1.7527 2022/10/08 14:44:57 - mmengine - INFO - Epoch(train) [138][1500/2119] lr: 4.0000e-03 eta: 2:08:53 time: 0.2907 data_time: 0.0187 memory: 5821 grad_norm: 5.2779 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7196 loss: 1.7196 2022/10/08 14:45:04 - mmengine - INFO - Epoch(train) [138][1520/2119] lr: 4.0000e-03 eta: 2:08:48 time: 0.3077 data_time: 0.0220 memory: 5821 grad_norm: 5.3499 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9784 loss: 1.9784 2022/10/08 14:45:09 - mmengine - INFO - Epoch(train) [138][1540/2119] lr: 4.0000e-03 eta: 2:08:41 time: 0.2676 data_time: 0.0199 memory: 5821 grad_norm: 5.3183 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8943 loss: 1.8943 2022/10/08 14:45:15 - mmengine - INFO - Epoch(train) [138][1560/2119] lr: 4.0000e-03 eta: 2:08:34 time: 0.2880 data_time: 0.0227 memory: 5821 grad_norm: 5.2490 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0066 loss: 2.0066 2022/10/08 14:45:21 - mmengine - INFO - Epoch(train) [138][1580/2119] lr: 4.0000e-03 eta: 2:08:28 time: 0.2907 data_time: 0.0219 memory: 5821 grad_norm: 5.3277 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.0190 loss: 2.0190 2022/10/08 14:45:26 - mmengine - INFO - Epoch(train) [138][1600/2119] lr: 4.0000e-03 eta: 2:08:21 time: 0.2779 data_time: 0.0167 memory: 5821 grad_norm: 5.2701 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8943 loss: 1.8943 2022/10/08 14:45:32 - mmengine - INFO - Epoch(train) [138][1620/2119] lr: 4.0000e-03 eta: 2:08:15 time: 0.2871 data_time: 0.0190 memory: 5821 grad_norm: 5.2351 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9364 loss: 1.9364 2022/10/08 14:45:38 - mmengine - INFO - Epoch(train) [138][1640/2119] lr: 4.0000e-03 eta: 2:08:09 time: 0.2934 data_time: 0.0223 memory: 5821 grad_norm: 5.3752 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8075 loss: 1.8075 2022/10/08 14:45:43 - mmengine - INFO - Epoch(train) [138][1660/2119] lr: 4.0000e-03 eta: 2:08:02 time: 0.2781 data_time: 0.0254 memory: 5821 grad_norm: 5.2578 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1148 loss: 2.1148 2022/10/08 14:45:49 - mmengine - INFO - Epoch(train) [138][1680/2119] lr: 4.0000e-03 eta: 2:07:55 time: 0.2627 data_time: 0.0229 memory: 5821 grad_norm: 5.3260 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7045 loss: 1.7045 2022/10/08 14:45:53 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:45:54 - mmengine - INFO - Epoch(train) [138][1700/2119] lr: 4.0000e-03 eta: 2:07:48 time: 0.2787 data_time: 0.0265 memory: 5821 grad_norm: 5.3207 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.0164 loss: 2.0164 2022/10/08 14:46:01 - mmengine - INFO - Epoch(train) [138][1720/2119] lr: 4.0000e-03 eta: 2:07:43 time: 0.3247 data_time: 0.0176 memory: 5821 grad_norm: 5.2299 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9976 loss: 1.9976 2022/10/08 14:46:06 - mmengine - INFO - Epoch(train) [138][1740/2119] lr: 4.0000e-03 eta: 2:07:36 time: 0.2764 data_time: 0.0238 memory: 5821 grad_norm: 5.1757 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8236 loss: 1.8236 2022/10/08 14:46:12 - mmengine - INFO - Epoch(train) [138][1760/2119] lr: 4.0000e-03 eta: 2:07:31 time: 0.3121 data_time: 0.0201 memory: 5821 grad_norm: 5.2265 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.0820 loss: 2.0820 2022/10/08 14:46:18 - mmengine - INFO - Epoch(train) [138][1780/2119] lr: 4.0000e-03 eta: 2:07:25 time: 0.2796 data_time: 0.0206 memory: 5821 grad_norm: 5.2886 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1537 loss: 2.1537 2022/10/08 14:46:23 - mmengine - INFO - Epoch(train) [138][1800/2119] lr: 4.0000e-03 eta: 2:07:18 time: 0.2702 data_time: 0.0187 memory: 5821 grad_norm: 5.3048 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0605 loss: 2.0605 2022/10/08 14:46:29 - mmengine - INFO - Epoch(train) [138][1820/2119] lr: 4.0000e-03 eta: 2:07:10 time: 0.2586 data_time: 0.0227 memory: 5821 grad_norm: 5.2855 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9955 loss: 1.9955 2022/10/08 14:46:35 - mmengine - INFO - Epoch(train) [138][1840/2119] lr: 4.0000e-03 eta: 2:07:05 time: 0.3130 data_time: 0.0186 memory: 5821 grad_norm: 5.3352 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.9983 loss: 1.9983 2022/10/08 14:46:40 - mmengine - INFO - Epoch(train) [138][1860/2119] lr: 4.0000e-03 eta: 2:06:58 time: 0.2717 data_time: 0.0216 memory: 5821 grad_norm: 5.2338 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8132 loss: 1.8132 2022/10/08 14:46:46 - mmengine - INFO - Epoch(train) [138][1880/2119] lr: 4.0000e-03 eta: 2:06:51 time: 0.2835 data_time: 0.0191 memory: 5821 grad_norm: 5.2528 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1185 loss: 2.1185 2022/10/08 14:46:52 - mmengine - INFO - Epoch(train) [138][1900/2119] lr: 4.0000e-03 eta: 2:06:45 time: 0.2954 data_time: 0.0233 memory: 5821 grad_norm: 5.2590 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7840 loss: 1.7840 2022/10/08 14:46:58 - mmengine - INFO - Epoch(train) [138][1920/2119] lr: 4.0000e-03 eta: 2:06:40 time: 0.3123 data_time: 0.0265 memory: 5821 grad_norm: 5.3081 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1223 loss: 2.1223 2022/10/08 14:47:03 - mmengine - INFO - Epoch(train) [138][1940/2119] lr: 4.0000e-03 eta: 2:06:33 time: 0.2574 data_time: 0.0174 memory: 5821 grad_norm: 5.3849 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8740 loss: 1.8740 2022/10/08 14:47:09 - mmengine - INFO - Epoch(train) [138][1960/2119] lr: 4.0000e-03 eta: 2:06:27 time: 0.3039 data_time: 0.0182 memory: 5821 grad_norm: 5.3114 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8804 loss: 1.8804 2022/10/08 14:47:15 - mmengine - INFO - Epoch(train) [138][1980/2119] lr: 4.0000e-03 eta: 2:06:21 time: 0.2973 data_time: 0.0242 memory: 5821 grad_norm: 5.2012 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7914 loss: 1.7914 2022/10/08 14:47:21 - mmengine - INFO - Epoch(train) [138][2000/2119] lr: 4.0000e-03 eta: 2:06:14 time: 0.2715 data_time: 0.0195 memory: 5821 grad_norm: 5.3055 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8938 loss: 1.8938 2022/10/08 14:47:26 - mmengine - INFO - Epoch(train) [138][2020/2119] lr: 4.0000e-03 eta: 2:06:07 time: 0.2716 data_time: 0.0245 memory: 5821 grad_norm: 5.3356 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0498 loss: 2.0498 2022/10/08 14:47:33 - mmengine - INFO - Epoch(train) [138][2040/2119] lr: 4.0000e-03 eta: 2:06:02 time: 0.3170 data_time: 0.0235 memory: 5821 grad_norm: 5.2114 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7677 loss: 1.7677 2022/10/08 14:47:39 - mmengine - INFO - Epoch(train) [138][2060/2119] lr: 4.0000e-03 eta: 2:05:57 time: 0.3098 data_time: 0.0190 memory: 5821 grad_norm: 5.2937 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0291 loss: 2.0291 2022/10/08 14:47:45 - mmengine - INFO - Epoch(train) [138][2080/2119] lr: 4.0000e-03 eta: 2:05:51 time: 0.3093 data_time: 0.0185 memory: 5821 grad_norm: 5.3551 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 1.9440 loss: 1.9440 2022/10/08 14:47:50 - mmengine - INFO - Epoch(train) [138][2100/2119] lr: 4.0000e-03 eta: 2:05:44 time: 0.2529 data_time: 0.0233 memory: 5821 grad_norm: 5.2376 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.8389 loss: 1.8389 2022/10/08 14:47:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:47:55 - mmengine - INFO - Epoch(train) [138][2119/2119] lr: 4.0000e-03 eta: 2:05:44 time: 0.2482 data_time: 0.0163 memory: 5821 grad_norm: 5.3045 top1_acc: 0.2000 top5_acc: 0.8000 loss_cls: 2.0332 loss: 2.0332 2022/10/08 14:48:03 - mmengine - INFO - Epoch(train) [139][20/2119] lr: 4.0000e-03 eta: 2:05:25 time: 0.4118 data_time: 0.1171 memory: 5821 grad_norm: 5.2245 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0508 loss: 2.0508 2022/10/08 14:48:09 - mmengine - INFO - Epoch(train) [139][40/2119] lr: 4.0000e-03 eta: 2:05:19 time: 0.2984 data_time: 0.0167 memory: 5821 grad_norm: 5.1702 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0131 loss: 2.0131 2022/10/08 14:48:15 - mmengine - INFO - Epoch(train) [139][60/2119] lr: 4.0000e-03 eta: 2:05:13 time: 0.2911 data_time: 0.0272 memory: 5821 grad_norm: 5.2609 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0855 loss: 2.0855 2022/10/08 14:48:20 - mmengine - INFO - Epoch(train) [139][80/2119] lr: 4.0000e-03 eta: 2:05:06 time: 0.2674 data_time: 0.0235 memory: 5821 grad_norm: 5.3103 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.8102 loss: 1.8102 2022/10/08 14:48:26 - mmengine - INFO - Epoch(train) [139][100/2119] lr: 4.0000e-03 eta: 2:04:59 time: 0.2727 data_time: 0.0199 memory: 5821 grad_norm: 5.2708 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 1.9589 loss: 1.9589 2022/10/08 14:48:32 - mmengine - INFO - Epoch(train) [139][120/2119] lr: 4.0000e-03 eta: 2:04:54 time: 0.3054 data_time: 0.0216 memory: 5821 grad_norm: 5.2995 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8078 loss: 1.8078 2022/10/08 14:48:38 - mmengine - INFO - Epoch(train) [139][140/2119] lr: 4.0000e-03 eta: 2:04:48 time: 0.2856 data_time: 0.0267 memory: 5821 grad_norm: 5.3049 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.2159 loss: 2.2159 2022/10/08 14:48:43 - mmengine - INFO - Epoch(train) [139][160/2119] lr: 4.0000e-03 eta: 2:04:41 time: 0.2879 data_time: 0.0210 memory: 5821 grad_norm: 5.2775 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9516 loss: 1.9516 2022/10/08 14:48:49 - mmengine - INFO - Epoch(train) [139][180/2119] lr: 4.0000e-03 eta: 2:04:35 time: 0.2951 data_time: 0.0151 memory: 5821 grad_norm: 5.3098 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0941 loss: 2.0941 2022/10/08 14:48:56 - mmengine - INFO - Epoch(train) [139][200/2119] lr: 4.0000e-03 eta: 2:04:30 time: 0.3121 data_time: 0.0194 memory: 5821 grad_norm: 5.2438 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7376 loss: 1.7376 2022/10/08 14:49:01 - mmengine - INFO - Epoch(train) [139][220/2119] lr: 4.0000e-03 eta: 2:04:24 time: 0.2816 data_time: 0.0158 memory: 5821 grad_norm: 5.2333 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0368 loss: 2.0368 2022/10/08 14:49:07 - mmengine - INFO - Epoch(train) [139][240/2119] lr: 4.0000e-03 eta: 2:04:18 time: 0.3086 data_time: 0.0211 memory: 5821 grad_norm: 5.2260 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6772 loss: 1.6772 2022/10/08 14:49:13 - mmengine - INFO - Epoch(train) [139][260/2119] lr: 4.0000e-03 eta: 2:04:11 time: 0.2769 data_time: 0.0144 memory: 5821 grad_norm: 5.4089 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9037 loss: 1.9037 2022/10/08 14:49:19 - mmengine - INFO - Epoch(train) [139][280/2119] lr: 4.0000e-03 eta: 2:04:06 time: 0.3029 data_time: 0.0195 memory: 5821 grad_norm: 5.2318 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9646 loss: 1.9646 2022/10/08 14:49:25 - mmengine - INFO - Epoch(train) [139][300/2119] lr: 4.0000e-03 eta: 2:03:59 time: 0.2753 data_time: 0.0184 memory: 5821 grad_norm: 5.2478 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.8368 loss: 1.8368 2022/10/08 14:49:31 - mmengine - INFO - Epoch(train) [139][320/2119] lr: 4.0000e-03 eta: 2:03:54 time: 0.3114 data_time: 0.0210 memory: 5821 grad_norm: 5.3156 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8683 loss: 1.8683 2022/10/08 14:49:36 - mmengine - INFO - Epoch(train) [139][340/2119] lr: 4.0000e-03 eta: 2:03:47 time: 0.2763 data_time: 0.0147 memory: 5821 grad_norm: 5.2877 top1_acc: 0.3750 top5_acc: 0.9375 loss_cls: 2.0251 loss: 2.0251 2022/10/08 14:49:42 - mmengine - INFO - Epoch(train) [139][360/2119] lr: 4.0000e-03 eta: 2:03:41 time: 0.2937 data_time: 0.0185 memory: 5821 grad_norm: 5.2805 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9562 loss: 1.9562 2022/10/08 14:49:48 - mmengine - INFO - Epoch(train) [139][380/2119] lr: 4.0000e-03 eta: 2:03:34 time: 0.2720 data_time: 0.0269 memory: 5821 grad_norm: 5.4159 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8644 loss: 1.8644 2022/10/08 14:49:54 - mmengine - INFO - Epoch(train) [139][400/2119] lr: 4.0000e-03 eta: 2:03:29 time: 0.3043 data_time: 0.0183 memory: 5821 grad_norm: 5.3014 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 1.9148 loss: 1.9148 2022/10/08 14:49:59 - mmengine - INFO - Epoch(train) [139][420/2119] lr: 4.0000e-03 eta: 2:03:22 time: 0.2832 data_time: 0.0208 memory: 5821 grad_norm: 5.3566 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.9985 loss: 1.9985 2022/10/08 14:50:06 - mmengine - INFO - Epoch(train) [139][440/2119] lr: 4.0000e-03 eta: 2:03:17 time: 0.3187 data_time: 0.0225 memory: 5821 grad_norm: 5.2382 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8673 loss: 1.8673 2022/10/08 14:50:11 - mmengine - INFO - Epoch(train) [139][460/2119] lr: 4.0000e-03 eta: 2:03:10 time: 0.2522 data_time: 0.0174 memory: 5821 grad_norm: 5.3032 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0198 loss: 2.0198 2022/10/08 14:50:16 - mmengine - INFO - Epoch(train) [139][480/2119] lr: 4.0000e-03 eta: 2:03:02 time: 0.2631 data_time: 0.0183 memory: 5821 grad_norm: 5.3087 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8526 loss: 1.8526 2022/10/08 14:50:22 - mmengine - INFO - Epoch(train) [139][500/2119] lr: 4.0000e-03 eta: 2:02:57 time: 0.3106 data_time: 0.0241 memory: 5821 grad_norm: 5.3596 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0537 loss: 2.0537 2022/10/08 14:50:28 - mmengine - INFO - Epoch(train) [139][520/2119] lr: 4.0000e-03 eta: 2:02:51 time: 0.2836 data_time: 0.0209 memory: 5821 grad_norm: 5.3713 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.8593 loss: 1.8593 2022/10/08 14:50:34 - mmengine - INFO - Epoch(train) [139][540/2119] lr: 4.0000e-03 eta: 2:02:44 time: 0.2808 data_time: 0.0225 memory: 5821 grad_norm: 5.2776 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8846 loss: 1.8846 2022/10/08 14:50:40 - mmengine - INFO - Epoch(train) [139][560/2119] lr: 4.0000e-03 eta: 2:02:38 time: 0.2950 data_time: 0.0204 memory: 5821 grad_norm: 5.3631 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8647 loss: 1.8647 2022/10/08 14:50:45 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:50:45 - mmengine - INFO - Epoch(train) [139][580/2119] lr: 4.0000e-03 eta: 2:02:32 time: 0.2932 data_time: 0.0149 memory: 5821 grad_norm: 5.2478 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7783 loss: 1.7783 2022/10/08 14:50:51 - mmengine - INFO - Epoch(train) [139][600/2119] lr: 4.0000e-03 eta: 2:02:25 time: 0.2738 data_time: 0.0212 memory: 5821 grad_norm: 5.5265 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8672 loss: 1.8672 2022/10/08 14:50:56 - mmengine - INFO - Epoch(train) [139][620/2119] lr: 4.0000e-03 eta: 2:02:19 time: 0.2746 data_time: 0.0212 memory: 5821 grad_norm: 5.3360 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.7941 loss: 1.7941 2022/10/08 14:51:02 - mmengine - INFO - Epoch(train) [139][640/2119] lr: 4.0000e-03 eta: 2:02:12 time: 0.2751 data_time: 0.0179 memory: 5821 grad_norm: 5.2996 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9024 loss: 1.9024 2022/10/08 14:51:07 - mmengine - INFO - Epoch(train) [139][660/2119] lr: 4.0000e-03 eta: 2:02:06 time: 0.2795 data_time: 0.0220 memory: 5821 grad_norm: 5.3118 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.9020 loss: 1.9020 2022/10/08 14:51:13 - mmengine - INFO - Epoch(train) [139][680/2119] lr: 4.0000e-03 eta: 2:01:59 time: 0.2892 data_time: 0.0193 memory: 5821 grad_norm: 5.3591 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9277 loss: 1.9277 2022/10/08 14:51:24 - mmengine - INFO - Epoch(train) [139][700/2119] lr: 4.0000e-03 eta: 2:02:03 time: 0.5468 data_time: 0.2964 memory: 5821 grad_norm: 5.2378 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8636 loss: 1.8636 2022/10/08 14:51:29 - mmengine - INFO - Epoch(train) [139][720/2119] lr: 4.0000e-03 eta: 2:01:55 time: 0.2522 data_time: 0.0204 memory: 5821 grad_norm: 5.2683 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9143 loss: 1.9143 2022/10/08 14:51:35 - mmengine - INFO - Epoch(train) [139][740/2119] lr: 4.0000e-03 eta: 2:01:50 time: 0.3040 data_time: 0.0268 memory: 5821 grad_norm: 5.3388 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0786 loss: 2.0786 2022/10/08 14:51:41 - mmengine - INFO - Epoch(train) [139][760/2119] lr: 4.0000e-03 eta: 2:01:43 time: 0.2680 data_time: 0.0159 memory: 5821 grad_norm: 5.3392 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.8128 loss: 1.8128 2022/10/08 14:51:47 - mmengine - INFO - Epoch(train) [139][780/2119] lr: 4.0000e-03 eta: 2:01:37 time: 0.3097 data_time: 0.0230 memory: 5821 grad_norm: 5.4342 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0200 loss: 2.0200 2022/10/08 14:51:52 - mmengine - INFO - Epoch(train) [139][800/2119] lr: 4.0000e-03 eta: 2:01:31 time: 0.2762 data_time: 0.0341 memory: 5821 grad_norm: 5.3742 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 2.1965 loss: 2.1965 2022/10/08 14:51:58 - mmengine - INFO - Epoch(train) [139][820/2119] lr: 4.0000e-03 eta: 2:01:24 time: 0.2810 data_time: 0.0263 memory: 5821 grad_norm: 5.3554 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8947 loss: 1.8947 2022/10/08 14:52:07 - mmengine - INFO - Epoch(train) [139][840/2119] lr: 4.0000e-03 eta: 2:01:24 time: 0.4562 data_time: 0.0262 memory: 5821 grad_norm: 5.3622 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9375 loss: 1.9375 2022/10/08 14:52:13 - mmengine - INFO - Epoch(train) [139][860/2119] lr: 4.0000e-03 eta: 2:01:17 time: 0.2691 data_time: 0.0209 memory: 5821 grad_norm: 5.2153 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9054 loss: 1.9054 2022/10/08 14:52:18 - mmengine - INFO - Epoch(train) [139][880/2119] lr: 4.0000e-03 eta: 2:01:10 time: 0.2785 data_time: 0.0262 memory: 5821 grad_norm: 5.3534 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9202 loss: 1.9202 2022/10/08 14:52:24 - mmengine - INFO - Epoch(train) [139][900/2119] lr: 4.0000e-03 eta: 2:01:04 time: 0.2849 data_time: 0.0193 memory: 5821 grad_norm: 5.3937 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0309 loss: 2.0309 2022/10/08 14:52:30 - mmengine - INFO - Epoch(train) [139][920/2119] lr: 4.0000e-03 eta: 2:00:58 time: 0.2866 data_time: 0.0239 memory: 5821 grad_norm: 5.4353 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0700 loss: 2.0700 2022/10/08 14:52:36 - mmengine - INFO - Epoch(train) [139][940/2119] lr: 4.0000e-03 eta: 2:00:52 time: 0.2955 data_time: 0.0189 memory: 5821 grad_norm: 5.2314 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.9089 loss: 1.9089 2022/10/08 14:52:41 - mmengine - INFO - Epoch(train) [139][960/2119] lr: 4.0000e-03 eta: 2:00:45 time: 0.2787 data_time: 0.0207 memory: 5821 grad_norm: 5.1914 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7230 loss: 1.7230 2022/10/08 14:52:47 - mmengine - INFO - Epoch(train) [139][980/2119] lr: 4.0000e-03 eta: 2:00:39 time: 0.2953 data_time: 0.0199 memory: 5821 grad_norm: 5.2916 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8570 loss: 1.8570 2022/10/08 14:52:52 - mmengine - INFO - Epoch(train) [139][1000/2119] lr: 4.0000e-03 eta: 2:00:32 time: 0.2611 data_time: 0.0156 memory: 5821 grad_norm: 5.3145 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0120 loss: 2.0120 2022/10/08 14:52:58 - mmengine - INFO - Epoch(train) [139][1020/2119] lr: 4.0000e-03 eta: 2:00:26 time: 0.2781 data_time: 0.0172 memory: 5821 grad_norm: 5.3067 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9062 loss: 1.9062 2022/10/08 14:53:04 - mmengine - INFO - Epoch(train) [139][1040/2119] lr: 4.0000e-03 eta: 2:00:21 time: 0.3215 data_time: 0.0347 memory: 5821 grad_norm: 5.3553 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.0067 loss: 2.0067 2022/10/08 14:53:10 - mmengine - INFO - Epoch(train) [139][1060/2119] lr: 4.0000e-03 eta: 2:00:13 time: 0.2594 data_time: 0.0179 memory: 5821 grad_norm: 5.3213 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0853 loss: 2.0853 2022/10/08 14:53:15 - mmengine - INFO - Epoch(train) [139][1080/2119] lr: 4.0000e-03 eta: 2:00:07 time: 0.2846 data_time: 0.0201 memory: 5821 grad_norm: 5.3493 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8100 loss: 1.8100 2022/10/08 14:53:22 - mmengine - INFO - Epoch(train) [139][1100/2119] lr: 4.0000e-03 eta: 2:00:02 time: 0.3246 data_time: 0.0182 memory: 5821 grad_norm: 5.2786 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8042 loss: 1.8042 2022/10/08 14:53:27 - mmengine - INFO - Epoch(train) [139][1120/2119] lr: 4.0000e-03 eta: 1:59:55 time: 0.2669 data_time: 0.0190 memory: 5821 grad_norm: 5.3041 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0333 loss: 2.0333 2022/10/08 14:53:33 - mmengine - INFO - Epoch(train) [139][1140/2119] lr: 4.0000e-03 eta: 1:59:49 time: 0.2861 data_time: 0.0166 memory: 5821 grad_norm: 5.3687 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2237 loss: 2.2237 2022/10/08 14:53:38 - mmengine - INFO - Epoch(train) [139][1160/2119] lr: 4.0000e-03 eta: 1:59:42 time: 0.2797 data_time: 0.0227 memory: 5821 grad_norm: 5.3106 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6778 loss: 1.6778 2022/10/08 14:53:44 - mmengine - INFO - Epoch(train) [139][1180/2119] lr: 4.0000e-03 eta: 1:59:37 time: 0.2982 data_time: 0.0203 memory: 5821 grad_norm: 5.2970 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.1867 loss: 2.1867 2022/10/08 14:53:49 - mmengine - INFO - Epoch(train) [139][1200/2119] lr: 4.0000e-03 eta: 1:59:29 time: 0.2532 data_time: 0.0166 memory: 5821 grad_norm: 5.2842 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8974 loss: 1.8974 2022/10/08 14:53:56 - mmengine - INFO - Epoch(train) [139][1220/2119] lr: 4.0000e-03 eta: 1:59:24 time: 0.3192 data_time: 0.0169 memory: 5821 grad_norm: 5.3151 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8297 loss: 1.8297 2022/10/08 14:54:01 - mmengine - INFO - Epoch(train) [139][1240/2119] lr: 4.0000e-03 eta: 1:59:18 time: 0.2761 data_time: 0.0206 memory: 5821 grad_norm: 5.3230 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0371 loss: 2.0371 2022/10/08 14:54:07 - mmengine - INFO - Epoch(train) [139][1260/2119] lr: 4.0000e-03 eta: 1:59:11 time: 0.2865 data_time: 0.0208 memory: 5821 grad_norm: 5.2801 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8701 loss: 1.8701 2022/10/08 14:54:13 - mmengine - INFO - Epoch(train) [139][1280/2119] lr: 4.0000e-03 eta: 1:59:06 time: 0.3037 data_time: 0.0206 memory: 5821 grad_norm: 5.2180 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8649 loss: 1.8649 2022/10/08 14:54:19 - mmengine - INFO - Epoch(train) [139][1300/2119] lr: 4.0000e-03 eta: 1:58:59 time: 0.2746 data_time: 0.0248 memory: 5821 grad_norm: 5.3012 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.8368 loss: 1.8368 2022/10/08 14:54:25 - mmengine - INFO - Epoch(train) [139][1320/2119] lr: 4.0000e-03 eta: 1:58:53 time: 0.2934 data_time: 0.0184 memory: 5821 grad_norm: 5.2730 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9646 loss: 1.9646 2022/10/08 14:54:30 - mmengine - INFO - Epoch(train) [139][1340/2119] lr: 4.0000e-03 eta: 1:58:47 time: 0.2827 data_time: 0.0163 memory: 5821 grad_norm: 5.2327 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.9154 loss: 1.9154 2022/10/08 14:54:36 - mmengine - INFO - Epoch(train) [139][1360/2119] lr: 4.0000e-03 eta: 1:58:40 time: 0.2858 data_time: 0.0253 memory: 5821 grad_norm: 5.4345 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.9418 loss: 1.9418 2022/10/08 14:54:42 - mmengine - INFO - Epoch(train) [139][1380/2119] lr: 4.0000e-03 eta: 1:58:35 time: 0.2984 data_time: 0.0161 memory: 5821 grad_norm: 5.3448 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9309 loss: 1.9309 2022/10/08 14:54:48 - mmengine - INFO - Epoch(train) [139][1400/2119] lr: 4.0000e-03 eta: 1:58:29 time: 0.2956 data_time: 0.0198 memory: 5821 grad_norm: 5.3764 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0152 loss: 2.0152 2022/10/08 14:54:54 - mmengine - INFO - Epoch(train) [139][1420/2119] lr: 4.0000e-03 eta: 1:58:23 time: 0.3119 data_time: 0.0148 memory: 5821 grad_norm: 5.3784 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.9887 loss: 1.9887 2022/10/08 14:55:00 - mmengine - INFO - Epoch(train) [139][1440/2119] lr: 4.0000e-03 eta: 1:58:17 time: 0.2787 data_time: 0.0176 memory: 5821 grad_norm: 5.3599 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8460 loss: 1.8460 2022/10/08 14:55:05 - mmengine - INFO - Epoch(train) [139][1460/2119] lr: 4.0000e-03 eta: 1:58:10 time: 0.2740 data_time: 0.0205 memory: 5821 grad_norm: 5.3155 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1329 loss: 2.1329 2022/10/08 14:55:11 - mmengine - INFO - Epoch(train) [139][1480/2119] lr: 4.0000e-03 eta: 1:58:03 time: 0.2768 data_time: 0.0172 memory: 5821 grad_norm: 5.3220 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.0939 loss: 2.0939 2022/10/08 14:55:16 - mmengine - INFO - Epoch(train) [139][1500/2119] lr: 4.0000e-03 eta: 1:57:57 time: 0.2701 data_time: 0.0269 memory: 5821 grad_norm: 5.4210 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9364 loss: 1.9364 2022/10/08 14:55:23 - mmengine - INFO - Epoch(train) [139][1520/2119] lr: 4.0000e-03 eta: 1:57:52 time: 0.3398 data_time: 0.0179 memory: 5821 grad_norm: 5.3047 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9429 loss: 1.9429 2022/10/08 14:55:28 - mmengine - INFO - Epoch(train) [139][1540/2119] lr: 4.0000e-03 eta: 1:57:45 time: 0.2602 data_time: 0.0185 memory: 5821 grad_norm: 5.3584 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1086 loss: 2.1086 2022/10/08 14:55:34 - mmengine - INFO - Epoch(train) [139][1560/2119] lr: 4.0000e-03 eta: 1:57:39 time: 0.2824 data_time: 0.0191 memory: 5821 grad_norm: 5.2856 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8973 loss: 1.8973 2022/10/08 14:55:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:55:40 - mmengine - INFO - Epoch(train) [139][1580/2119] lr: 4.0000e-03 eta: 1:57:33 time: 0.3002 data_time: 0.0199 memory: 5821 grad_norm: 5.4540 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9750 loss: 1.9750 2022/10/08 14:55:46 - mmengine - INFO - Epoch(train) [139][1600/2119] lr: 4.0000e-03 eta: 1:57:27 time: 0.3057 data_time: 0.0188 memory: 5821 grad_norm: 5.3652 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7387 loss: 1.7387 2022/10/08 14:55:51 - mmengine - INFO - Epoch(train) [139][1620/2119] lr: 4.0000e-03 eta: 1:57:21 time: 0.2686 data_time: 0.0225 memory: 5821 grad_norm: 5.3717 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0781 loss: 2.0781 2022/10/08 14:55:57 - mmengine - INFO - Epoch(train) [139][1640/2119] lr: 4.0000e-03 eta: 1:57:14 time: 0.2803 data_time: 0.0198 memory: 5821 grad_norm: 5.3243 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0720 loss: 2.0720 2022/10/08 14:56:03 - mmengine - INFO - Epoch(train) [139][1660/2119] lr: 4.0000e-03 eta: 1:57:08 time: 0.2958 data_time: 0.0174 memory: 5821 grad_norm: 5.3326 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7922 loss: 1.7922 2022/10/08 14:56:08 - mmengine - INFO - Epoch(train) [139][1680/2119] lr: 4.0000e-03 eta: 1:57:02 time: 0.2732 data_time: 0.0168 memory: 5821 grad_norm: 5.3722 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.0822 loss: 2.0822 2022/10/08 14:56:14 - mmengine - INFO - Epoch(train) [139][1700/2119] lr: 4.0000e-03 eta: 1:56:55 time: 0.2843 data_time: 0.0191 memory: 5821 grad_norm: 5.4397 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8919 loss: 1.8919 2022/10/08 14:56:19 - mmengine - INFO - Epoch(train) [139][1720/2119] lr: 4.0000e-03 eta: 1:56:48 time: 0.2644 data_time: 0.0188 memory: 5821 grad_norm: 5.2539 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.6822 loss: 1.6822 2022/10/08 14:56:26 - mmengine - INFO - Epoch(train) [139][1740/2119] lr: 4.0000e-03 eta: 1:56:43 time: 0.3170 data_time: 0.0187 memory: 5821 grad_norm: 5.3083 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7773 loss: 1.7773 2022/10/08 14:56:32 - mmengine - INFO - Epoch(train) [139][1760/2119] lr: 4.0000e-03 eta: 1:56:37 time: 0.2923 data_time: 0.0161 memory: 5821 grad_norm: 5.2672 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0920 loss: 2.0920 2022/10/08 14:56:38 - mmengine - INFO - Epoch(train) [139][1780/2119] lr: 4.0000e-03 eta: 1:56:31 time: 0.2982 data_time: 0.0154 memory: 5821 grad_norm: 5.4413 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0907 loss: 2.0907 2022/10/08 14:56:43 - mmengine - INFO - Epoch(train) [139][1800/2119] lr: 4.0000e-03 eta: 1:56:24 time: 0.2666 data_time: 0.0190 memory: 5821 grad_norm: 5.3651 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0316 loss: 2.0316 2022/10/08 14:56:49 - mmengine - INFO - Epoch(train) [139][1820/2119] lr: 4.0000e-03 eta: 1:56:19 time: 0.2980 data_time: 0.0170 memory: 5821 grad_norm: 5.4339 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9231 loss: 1.9231 2022/10/08 14:56:54 - mmengine - INFO - Epoch(train) [139][1840/2119] lr: 4.0000e-03 eta: 1:56:12 time: 0.2597 data_time: 0.0217 memory: 5821 grad_norm: 5.3433 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.8563 loss: 1.8563 2022/10/08 14:57:00 - mmengine - INFO - Epoch(train) [139][1860/2119] lr: 4.0000e-03 eta: 1:56:05 time: 0.2906 data_time: 0.0276 memory: 5821 grad_norm: 5.3660 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9140 loss: 1.9140 2022/10/08 14:57:07 - mmengine - INFO - Epoch(train) [139][1880/2119] lr: 4.0000e-03 eta: 1:56:01 time: 0.3347 data_time: 0.0202 memory: 5821 grad_norm: 5.3904 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9386 loss: 1.9386 2022/10/08 14:57:12 - mmengine - INFO - Epoch(train) [139][1900/2119] lr: 4.0000e-03 eta: 1:55:55 time: 0.2846 data_time: 0.0261 memory: 5821 grad_norm: 5.3650 top1_acc: 0.3125 top5_acc: 0.4375 loss_cls: 1.7762 loss: 1.7762 2022/10/08 14:57:18 - mmengine - INFO - Epoch(train) [139][1920/2119] lr: 4.0000e-03 eta: 1:55:48 time: 0.2861 data_time: 0.0186 memory: 5821 grad_norm: 5.3794 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9266 loss: 1.9266 2022/10/08 14:57:24 - mmengine - INFO - Epoch(train) [139][1940/2119] lr: 4.0000e-03 eta: 1:55:42 time: 0.2753 data_time: 0.0208 memory: 5821 grad_norm: 5.3933 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7366 loss: 1.7366 2022/10/08 14:57:29 - mmengine - INFO - Epoch(train) [139][1960/2119] lr: 4.0000e-03 eta: 1:55:36 time: 0.2914 data_time: 0.0192 memory: 5821 grad_norm: 5.3184 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1547 loss: 2.1547 2022/10/08 14:57:35 - mmengine - INFO - Epoch(train) [139][1980/2119] lr: 4.0000e-03 eta: 1:55:30 time: 0.2863 data_time: 0.0179 memory: 5821 grad_norm: 5.3731 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0687 loss: 2.0687 2022/10/08 14:57:41 - mmengine - INFO - Epoch(train) [139][2000/2119] lr: 4.0000e-03 eta: 1:55:24 time: 0.3106 data_time: 0.0164 memory: 5821 grad_norm: 5.3285 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9375 loss: 1.9375 2022/10/08 14:57:47 - mmengine - INFO - Epoch(train) [139][2020/2119] lr: 4.0000e-03 eta: 1:55:18 time: 0.2937 data_time: 0.0217 memory: 5821 grad_norm: 5.4077 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.9320 loss: 1.9320 2022/10/08 14:57:53 - mmengine - INFO - Epoch(train) [139][2040/2119] lr: 4.0000e-03 eta: 1:55:13 time: 0.3074 data_time: 0.0228 memory: 5821 grad_norm: 5.2620 top1_acc: 0.4375 top5_acc: 0.4375 loss_cls: 1.9514 loss: 1.9514 2022/10/08 14:57:59 - mmengine - INFO - Epoch(train) [139][2060/2119] lr: 4.0000e-03 eta: 1:55:06 time: 0.2677 data_time: 0.0185 memory: 5821 grad_norm: 5.2470 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1229 loss: 2.1229 2022/10/08 14:58:05 - mmengine - INFO - Epoch(train) [139][2080/2119] lr: 4.0000e-03 eta: 1:55:01 time: 0.3335 data_time: 0.0273 memory: 5821 grad_norm: 5.3032 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.9197 loss: 1.9197 2022/10/08 14:58:11 - mmengine - INFO - Epoch(train) [139][2100/2119] lr: 4.0000e-03 eta: 1:54:54 time: 0.2543 data_time: 0.0199 memory: 5821 grad_norm: 5.3699 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0476 loss: 2.0476 2022/10/08 14:58:15 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 14:58:15 - mmengine - INFO - Epoch(train) [139][2119/2119] lr: 4.0000e-03 eta: 1:54:54 time: 0.2372 data_time: 0.0145 memory: 5821 grad_norm: 5.3649 top1_acc: 0.5000 top5_acc: 0.7000 loss_cls: 1.8419 loss: 1.8419 2022/10/08 14:58:23 - mmengine - INFO - Epoch(train) [140][20/2119] lr: 4.0000e-03 eta: 1:54:37 time: 0.4129 data_time: 0.1391 memory: 5821 grad_norm: 5.2547 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8130 loss: 1.8130 2022/10/08 14:58:29 - mmengine - INFO - Epoch(train) [140][40/2119] lr: 4.0000e-03 eta: 1:54:31 time: 0.2768 data_time: 0.0272 memory: 5821 grad_norm: 5.2645 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7538 loss: 1.7538 2022/10/08 14:58:36 - mmengine - INFO - Epoch(train) [140][60/2119] lr: 4.0000e-03 eta: 1:54:26 time: 0.3299 data_time: 0.0220 memory: 5821 grad_norm: 5.2784 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7128 loss: 1.7128 2022/10/08 14:58:41 - mmengine - INFO - Epoch(train) [140][80/2119] lr: 4.0000e-03 eta: 1:54:19 time: 0.2587 data_time: 0.0223 memory: 5821 grad_norm: 5.2546 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.7654 loss: 1.7654 2022/10/08 14:58:47 - mmengine - INFO - Epoch(train) [140][100/2119] lr: 4.0000e-03 eta: 1:54:14 time: 0.3185 data_time: 0.0158 memory: 5821 grad_norm: 5.2354 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9935 loss: 1.9935 2022/10/08 14:58:52 - mmengine - INFO - Epoch(train) [140][120/2119] lr: 4.0000e-03 eta: 1:54:07 time: 0.2647 data_time: 0.0191 memory: 5821 grad_norm: 5.3311 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.8265 loss: 1.8265 2022/10/08 14:58:59 - mmengine - INFO - Epoch(train) [140][140/2119] lr: 4.0000e-03 eta: 1:54:02 time: 0.3148 data_time: 0.0214 memory: 5821 grad_norm: 5.4839 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0560 loss: 2.0560 2022/10/08 14:59:04 - mmengine - INFO - Epoch(train) [140][160/2119] lr: 4.0000e-03 eta: 1:53:55 time: 0.2604 data_time: 0.0205 memory: 5821 grad_norm: 5.4632 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8759 loss: 1.8759 2022/10/08 14:59:09 - mmengine - INFO - Epoch(train) [140][180/2119] lr: 4.0000e-03 eta: 1:53:48 time: 0.2731 data_time: 0.0220 memory: 5821 grad_norm: 5.3122 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.7506 loss: 1.7506 2022/10/08 14:59:16 - mmengine - INFO - Epoch(train) [140][200/2119] lr: 4.0000e-03 eta: 1:53:43 time: 0.3294 data_time: 0.0168 memory: 5821 grad_norm: 5.4495 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0019 loss: 2.0019 2022/10/08 14:59:21 - mmengine - INFO - Epoch(train) [140][220/2119] lr: 4.0000e-03 eta: 1:53:36 time: 0.2565 data_time: 0.0187 memory: 5821 grad_norm: 5.2814 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8943 loss: 1.8943 2022/10/08 14:59:30 - mmengine - INFO - Epoch(train) [140][240/2119] lr: 4.0000e-03 eta: 1:53:34 time: 0.4299 data_time: 0.1917 memory: 5821 grad_norm: 5.1819 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0243 loss: 2.0243 2022/10/08 14:59:35 - mmengine - INFO - Epoch(train) [140][260/2119] lr: 4.0000e-03 eta: 1:53:27 time: 0.2605 data_time: 0.0194 memory: 5821 grad_norm: 5.4707 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0430 loss: 2.0430 2022/10/08 14:59:40 - mmengine - INFO - Epoch(train) [140][280/2119] lr: 4.0000e-03 eta: 1:53:21 time: 0.2708 data_time: 0.0250 memory: 5821 grad_norm: 5.3861 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9907 loss: 1.9907 2022/10/08 14:59:46 - mmengine - INFO - Epoch(train) [140][300/2119] lr: 4.0000e-03 eta: 1:53:15 time: 0.2892 data_time: 0.0147 memory: 5821 grad_norm: 5.4007 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0606 loss: 2.0606 2022/10/08 14:59:52 - mmengine - INFO - Epoch(train) [140][320/2119] lr: 4.0000e-03 eta: 1:53:08 time: 0.2867 data_time: 0.0231 memory: 5821 grad_norm: 5.3709 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1363 loss: 2.1363 2022/10/08 14:59:58 - mmengine - INFO - Epoch(train) [140][340/2119] lr: 4.0000e-03 eta: 1:53:03 time: 0.3063 data_time: 0.0186 memory: 5821 grad_norm: 5.2570 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8511 loss: 1.8511 2022/10/08 15:00:04 - mmengine - INFO - Epoch(train) [140][360/2119] lr: 4.0000e-03 eta: 1:52:57 time: 0.3003 data_time: 0.0147 memory: 5821 grad_norm: 5.3341 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6663 loss: 1.6663 2022/10/08 15:00:14 - mmengine - INFO - Epoch(train) [140][380/2119] lr: 4.0000e-03 eta: 1:52:57 time: 0.4893 data_time: 0.2496 memory: 5821 grad_norm: 5.2930 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9750 loss: 1.9750 2022/10/08 15:00:19 - mmengine - INFO - Epoch(train) [140][400/2119] lr: 4.0000e-03 eta: 1:52:50 time: 0.2549 data_time: 0.0201 memory: 5821 grad_norm: 5.3420 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 1.9326 loss: 1.9326 2022/10/08 15:00:25 - mmengine - INFO - Epoch(train) [140][420/2119] lr: 4.0000e-03 eta: 1:52:44 time: 0.2971 data_time: 0.0242 memory: 5821 grad_norm: 5.3135 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9490 loss: 1.9490 2022/10/08 15:00:30 - mmengine - INFO - Epoch(train) [140][440/2119] lr: 4.0000e-03 eta: 1:52:37 time: 0.2679 data_time: 0.0220 memory: 5821 grad_norm: 5.3264 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.8748 loss: 1.8748 2022/10/08 15:00:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 15:00:37 - mmengine - INFO - Epoch(train) [140][460/2119] lr: 4.0000e-03 eta: 1:52:32 time: 0.3221 data_time: 0.0217 memory: 5821 grad_norm: 5.4115 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9934 loss: 1.9934 2022/10/08 15:00:42 - mmengine - INFO - Epoch(train) [140][480/2119] lr: 4.0000e-03 eta: 1:52:26 time: 0.2786 data_time: 0.0187 memory: 5821 grad_norm: 5.3506 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0709 loss: 2.0709 2022/10/08 15:00:48 - mmengine - INFO - Epoch(train) [140][500/2119] lr: 4.0000e-03 eta: 1:52:20 time: 0.2904 data_time: 0.0139 memory: 5821 grad_norm: 5.3785 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7625 loss: 1.7625 2022/10/08 15:00:53 - mmengine - INFO - Epoch(train) [140][520/2119] lr: 4.0000e-03 eta: 1:52:13 time: 0.2619 data_time: 0.0201 memory: 5821 grad_norm: 5.3577 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7771 loss: 1.7771 2022/10/08 15:00:59 - mmengine - INFO - Epoch(train) [140][540/2119] lr: 4.0000e-03 eta: 1:52:06 time: 0.2828 data_time: 0.0195 memory: 5821 grad_norm: 5.2212 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0370 loss: 2.0370 2022/10/08 15:01:05 - mmengine - INFO - Epoch(train) [140][560/2119] lr: 4.0000e-03 eta: 1:52:00 time: 0.2944 data_time: 0.0174 memory: 5821 grad_norm: 5.2942 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7896 loss: 1.7896 2022/10/08 15:01:11 - mmengine - INFO - Epoch(train) [140][580/2119] lr: 4.0000e-03 eta: 1:51:55 time: 0.2993 data_time: 0.0164 memory: 5821 grad_norm: 5.2563 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9503 loss: 1.9503 2022/10/08 15:01:17 - mmengine - INFO - Epoch(train) [140][600/2119] lr: 4.0000e-03 eta: 1:51:49 time: 0.3046 data_time: 0.0175 memory: 5821 grad_norm: 5.3567 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.1237 loss: 2.1237 2022/10/08 15:01:22 - mmengine - INFO - Epoch(train) [140][620/2119] lr: 4.0000e-03 eta: 1:51:42 time: 0.2528 data_time: 0.0187 memory: 5821 grad_norm: 5.3618 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7465 loss: 1.7465 2022/10/08 15:01:27 - mmengine - INFO - Epoch(train) [140][640/2119] lr: 4.0000e-03 eta: 1:51:35 time: 0.2619 data_time: 0.0217 memory: 5821 grad_norm: 5.3300 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7312 loss: 1.7312 2022/10/08 15:01:34 - mmengine - INFO - Epoch(train) [140][660/2119] lr: 4.0000e-03 eta: 1:51:30 time: 0.3243 data_time: 0.0213 memory: 5821 grad_norm: 5.3199 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8233 loss: 1.8233 2022/10/08 15:01:39 - mmengine - INFO - Epoch(train) [140][680/2119] lr: 4.0000e-03 eta: 1:51:24 time: 0.2786 data_time: 0.0204 memory: 5821 grad_norm: 5.3359 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7334 loss: 1.7334 2022/10/08 15:01:45 - mmengine - INFO - Epoch(train) [140][700/2119] lr: 4.0000e-03 eta: 1:51:17 time: 0.2876 data_time: 0.0248 memory: 5821 grad_norm: 5.3266 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8885 loss: 1.8885 2022/10/08 15:01:51 - mmengine - INFO - Epoch(train) [140][720/2119] lr: 4.0000e-03 eta: 1:51:12 time: 0.3058 data_time: 0.0180 memory: 5821 grad_norm: 5.2854 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 2.0048 loss: 2.0048 2022/10/08 15:01:57 - mmengine - INFO - Epoch(train) [140][740/2119] lr: 4.0000e-03 eta: 1:51:06 time: 0.2847 data_time: 0.0189 memory: 5821 grad_norm: 5.4463 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0192 loss: 2.0192 2022/10/08 15:02:02 - mmengine - INFO - Epoch(train) [140][760/2119] lr: 4.0000e-03 eta: 1:50:59 time: 0.2728 data_time: 0.0240 memory: 5821 grad_norm: 5.3944 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0073 loss: 2.0073 2022/10/08 15:02:08 - mmengine - INFO - Epoch(train) [140][780/2119] lr: 4.0000e-03 eta: 1:50:53 time: 0.2966 data_time: 0.0204 memory: 5821 grad_norm: 5.3923 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0364 loss: 2.0364 2022/10/08 15:02:14 - mmengine - INFO - Epoch(train) [140][800/2119] lr: 4.0000e-03 eta: 1:50:47 time: 0.2755 data_time: 0.0238 memory: 5821 grad_norm: 5.3710 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7991 loss: 1.7991 2022/10/08 15:02:20 - mmengine - INFO - Epoch(train) [140][820/2119] lr: 4.0000e-03 eta: 1:50:40 time: 0.2814 data_time: 0.0209 memory: 5821 grad_norm: 5.4190 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8073 loss: 1.8073 2022/10/08 15:02:26 - mmengine - INFO - Epoch(train) [140][840/2119] lr: 4.0000e-03 eta: 1:50:34 time: 0.2965 data_time: 0.0216 memory: 5821 grad_norm: 5.3575 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7030 loss: 1.7030 2022/10/08 15:02:31 - mmengine - INFO - Epoch(train) [140][860/2119] lr: 4.0000e-03 eta: 1:50:28 time: 0.2834 data_time: 0.0185 memory: 5821 grad_norm: 5.4442 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0775 loss: 2.0775 2022/10/08 15:02:38 - mmengine - INFO - Epoch(train) [140][880/2119] lr: 4.0000e-03 eta: 1:50:23 time: 0.3306 data_time: 0.0184 memory: 5821 grad_norm: 5.4318 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0578 loss: 2.0578 2022/10/08 15:02:43 - mmengine - INFO - Epoch(train) [140][900/2119] lr: 4.0000e-03 eta: 1:50:17 time: 0.2741 data_time: 0.0140 memory: 5821 grad_norm: 5.4503 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0768 loss: 2.0768 2022/10/08 15:02:49 - mmengine - INFO - Epoch(train) [140][920/2119] lr: 4.0000e-03 eta: 1:50:10 time: 0.2700 data_time: 0.0207 memory: 5821 grad_norm: 5.3545 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.8346 loss: 1.8346 2022/10/08 15:02:55 - mmengine - INFO - Epoch(train) [140][940/2119] lr: 4.0000e-03 eta: 1:50:05 time: 0.3068 data_time: 0.0202 memory: 5821 grad_norm: 5.4398 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8598 loss: 1.8598 2022/10/08 15:03:00 - mmengine - INFO - Epoch(train) [140][960/2119] lr: 4.0000e-03 eta: 1:49:58 time: 0.2645 data_time: 0.0242 memory: 5821 grad_norm: 5.3792 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 2.0653 loss: 2.0653 2022/10/08 15:03:06 - mmengine - INFO - Epoch(train) [140][980/2119] lr: 4.0000e-03 eta: 1:49:52 time: 0.3127 data_time: 0.0204 memory: 5821 grad_norm: 5.3691 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7012 loss: 1.7012 2022/10/08 15:03:12 - mmengine - INFO - Epoch(train) [140][1000/2119] lr: 4.0000e-03 eta: 1:49:46 time: 0.2601 data_time: 0.0204 memory: 5821 grad_norm: 5.3138 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9570 loss: 1.9570 2022/10/08 15:03:17 - mmengine - INFO - Epoch(train) [140][1020/2119] lr: 4.0000e-03 eta: 1:49:39 time: 0.2899 data_time: 0.0162 memory: 5821 grad_norm: 5.4295 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9183 loss: 1.9183 2022/10/08 15:03:24 - mmengine - INFO - Epoch(train) [140][1040/2119] lr: 4.0000e-03 eta: 1:49:34 time: 0.3102 data_time: 0.0200 memory: 5821 grad_norm: 5.2760 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8263 loss: 1.8263 2022/10/08 15:03:29 - mmengine - INFO - Epoch(train) [140][1060/2119] lr: 4.0000e-03 eta: 1:49:27 time: 0.2626 data_time: 0.0181 memory: 5821 grad_norm: 5.2765 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8872 loss: 1.8872 2022/10/08 15:03:34 - mmengine - INFO - Epoch(train) [140][1080/2119] lr: 4.0000e-03 eta: 1:49:21 time: 0.2729 data_time: 0.0196 memory: 5821 grad_norm: 5.4331 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.8479 loss: 1.8479 2022/10/08 15:03:40 - mmengine - INFO - Epoch(train) [140][1100/2119] lr: 4.0000e-03 eta: 1:49:15 time: 0.2914 data_time: 0.0152 memory: 5821 grad_norm: 5.3273 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0070 loss: 2.0070 2022/10/08 15:03:47 - mmengine - INFO - Epoch(train) [140][1120/2119] lr: 4.0000e-03 eta: 1:49:09 time: 0.3120 data_time: 0.0211 memory: 5821 grad_norm: 5.4130 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8861 loss: 1.8861 2022/10/08 15:03:52 - mmengine - INFO - Epoch(train) [140][1140/2119] lr: 4.0000e-03 eta: 1:49:03 time: 0.2668 data_time: 0.0200 memory: 5821 grad_norm: 5.3736 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9934 loss: 1.9934 2022/10/08 15:03:57 - mmengine - INFO - Epoch(train) [140][1160/2119] lr: 4.0000e-03 eta: 1:48:56 time: 0.2796 data_time: 0.0166 memory: 5821 grad_norm: 5.3730 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.2240 loss: 2.2240 2022/10/08 15:04:03 - mmengine - INFO - Epoch(train) [140][1180/2119] lr: 4.0000e-03 eta: 1:48:50 time: 0.3004 data_time: 0.0170 memory: 5821 grad_norm: 5.3749 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9622 loss: 1.9622 2022/10/08 15:04:10 - mmengine - INFO - Epoch(train) [140][1200/2119] lr: 4.0000e-03 eta: 1:48:45 time: 0.3103 data_time: 0.0232 memory: 5821 grad_norm: 5.3303 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.9167 loss: 1.9167 2022/10/08 15:04:16 - mmengine - INFO - Epoch(train) [140][1220/2119] lr: 4.0000e-03 eta: 1:48:39 time: 0.2869 data_time: 0.0189 memory: 5821 grad_norm: 5.2434 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.9652 loss: 1.9652 2022/10/08 15:04:21 - mmengine - INFO - Epoch(train) [140][1240/2119] lr: 4.0000e-03 eta: 1:48:33 time: 0.2922 data_time: 0.0255 memory: 5821 grad_norm: 5.3083 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8376 loss: 1.8376 2022/10/08 15:04:27 - mmengine - INFO - Epoch(train) [140][1260/2119] lr: 4.0000e-03 eta: 1:48:27 time: 0.3003 data_time: 0.0268 memory: 5821 grad_norm: 5.4559 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.6621 loss: 1.6621 2022/10/08 15:04:33 - mmengine - INFO - Epoch(train) [140][1280/2119] lr: 4.0000e-03 eta: 1:48:21 time: 0.2916 data_time: 0.0224 memory: 5821 grad_norm: 5.3225 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.1995 loss: 2.1995 2022/10/08 15:04:38 - mmengine - INFO - Epoch(train) [140][1300/2119] lr: 4.0000e-03 eta: 1:48:14 time: 0.2582 data_time: 0.0190 memory: 5821 grad_norm: 5.2653 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7898 loss: 1.7898 2022/10/08 15:04:45 - mmengine - INFO - Epoch(train) [140][1320/2119] lr: 4.0000e-03 eta: 1:48:09 time: 0.3096 data_time: 0.0212 memory: 5821 grad_norm: 5.3919 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.1870 loss: 2.1870 2022/10/08 15:04:50 - mmengine - INFO - Epoch(train) [140][1340/2119] lr: 4.0000e-03 eta: 1:48:02 time: 0.2682 data_time: 0.0193 memory: 5821 grad_norm: 5.3816 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8670 loss: 1.8670 2022/10/08 15:04:56 - mmengine - INFO - Epoch(train) [140][1360/2119] lr: 4.0000e-03 eta: 1:47:57 time: 0.3214 data_time: 0.0175 memory: 5821 grad_norm: 5.4099 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9545 loss: 1.9545 2022/10/08 15:05:02 - mmengine - INFO - Epoch(train) [140][1380/2119] lr: 4.0000e-03 eta: 1:47:50 time: 0.2650 data_time: 0.0216 memory: 5821 grad_norm: 5.3018 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.1111 loss: 2.1111 2022/10/08 15:05:07 - mmengine - INFO - Epoch(train) [140][1400/2119] lr: 4.0000e-03 eta: 1:47:44 time: 0.2850 data_time: 0.0192 memory: 5821 grad_norm: 5.3449 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7740 loss: 1.7740 2022/10/08 15:05:13 - mmengine - INFO - Epoch(train) [140][1420/2119] lr: 4.0000e-03 eta: 1:47:38 time: 0.2773 data_time: 0.0255 memory: 5821 grad_norm: 5.3342 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8292 loss: 1.8292 2022/10/08 15:05:19 - mmengine - INFO - Epoch(train) [140][1440/2119] lr: 4.0000e-03 eta: 1:47:32 time: 0.3056 data_time: 0.0159 memory: 5821 grad_norm: 5.4536 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0680 loss: 2.0680 2022/10/08 15:05:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 15:05:24 - mmengine - INFO - Epoch(train) [140][1460/2119] lr: 4.0000e-03 eta: 1:47:25 time: 0.2683 data_time: 0.0216 memory: 5821 grad_norm: 5.3344 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8035 loss: 1.8035 2022/10/08 15:05:30 - mmengine - INFO - Epoch(train) [140][1480/2119] lr: 4.0000e-03 eta: 1:47:20 time: 0.3022 data_time: 0.0223 memory: 5821 grad_norm: 5.3411 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.0559 loss: 2.0559 2022/10/08 15:05:36 - mmengine - INFO - Epoch(train) [140][1500/2119] lr: 4.0000e-03 eta: 1:47:13 time: 0.2755 data_time: 0.0282 memory: 5821 grad_norm: 5.3766 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6498 loss: 1.6498 2022/10/08 15:05:42 - mmengine - INFO - Epoch(train) [140][1520/2119] lr: 4.0000e-03 eta: 1:47:07 time: 0.2772 data_time: 0.0276 memory: 5821 grad_norm: 5.3671 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8962 loss: 1.8962 2022/10/08 15:05:47 - mmengine - INFO - Epoch(train) [140][1540/2119] lr: 4.0000e-03 eta: 1:47:01 time: 0.2967 data_time: 0.0248 memory: 5821 grad_norm: 5.3836 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7381 loss: 1.7381 2022/10/08 15:05:53 - mmengine - INFO - Epoch(train) [140][1560/2119] lr: 4.0000e-03 eta: 1:46:55 time: 0.2923 data_time: 0.0193 memory: 5821 grad_norm: 5.3713 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0375 loss: 2.0375 2022/10/08 15:05:59 - mmengine - INFO - Epoch(train) [140][1580/2119] lr: 4.0000e-03 eta: 1:46:49 time: 0.2933 data_time: 0.0166 memory: 5821 grad_norm: 5.3577 top1_acc: 0.3750 top5_acc: 0.4375 loss_cls: 2.0619 loss: 2.0619 2022/10/08 15:06:05 - mmengine - INFO - Epoch(train) [140][1600/2119] lr: 4.0000e-03 eta: 1:46:43 time: 0.2713 data_time: 0.0228 memory: 5821 grad_norm: 5.2457 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9206 loss: 1.9206 2022/10/08 15:06:10 - mmengine - INFO - Epoch(train) [140][1620/2119] lr: 4.0000e-03 eta: 1:46:36 time: 0.2852 data_time: 0.0211 memory: 5821 grad_norm: 5.3732 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8631 loss: 1.8631 2022/10/08 15:06:16 - mmengine - INFO - Epoch(train) [140][1640/2119] lr: 4.0000e-03 eta: 1:46:30 time: 0.2748 data_time: 0.0214 memory: 5821 grad_norm: 5.3939 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7348 loss: 1.7348 2022/10/08 15:06:22 - mmengine - INFO - Epoch(train) [140][1660/2119] lr: 4.0000e-03 eta: 1:46:24 time: 0.2856 data_time: 0.0172 memory: 5821 grad_norm: 5.3413 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9183 loss: 1.9183 2022/10/08 15:06:39 - mmengine - INFO - Epoch(train) [140][1680/2119] lr: 4.0000e-03 eta: 1:46:33 time: 0.8847 data_time: 0.5755 memory: 5821 grad_norm: 5.5283 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8240 loss: 1.8240 2022/10/08 15:06:44 - mmengine - INFO - Epoch(train) [140][1700/2119] lr: 4.0000e-03 eta: 1:46:26 time: 0.2499 data_time: 0.0169 memory: 5821 grad_norm: 5.4848 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9965 loss: 1.9965 2022/10/08 15:06:50 - mmengine - INFO - Epoch(train) [140][1720/2119] lr: 4.0000e-03 eta: 1:46:20 time: 0.2801 data_time: 0.0191 memory: 5821 grad_norm: 5.3582 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 1.9525 loss: 1.9525 2022/10/08 15:06:56 - mmengine - INFO - Epoch(train) [140][1740/2119] lr: 4.0000e-03 eta: 1:46:14 time: 0.3081 data_time: 0.0187 memory: 5821 grad_norm: 5.4444 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.8071 loss: 1.8071 2022/10/08 15:07:02 - mmengine - INFO - Epoch(train) [140][1760/2119] lr: 4.0000e-03 eta: 1:46:08 time: 0.2794 data_time: 0.0183 memory: 5821 grad_norm: 5.3821 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1844 loss: 2.1844 2022/10/08 15:07:08 - mmengine - INFO - Epoch(train) [140][1780/2119] lr: 4.0000e-03 eta: 1:46:02 time: 0.2917 data_time: 0.0171 memory: 5821 grad_norm: 5.3745 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9572 loss: 1.9572 2022/10/08 15:07:13 - mmengine - INFO - Epoch(train) [140][1800/2119] lr: 4.0000e-03 eta: 1:45:55 time: 0.2656 data_time: 0.0177 memory: 5821 grad_norm: 5.2753 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8791 loss: 1.8791 2022/10/08 15:07:19 - mmengine - INFO - Epoch(train) [140][1820/2119] lr: 4.0000e-03 eta: 1:45:50 time: 0.3259 data_time: 0.0187 memory: 5821 grad_norm: 5.3632 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 2.1472 loss: 2.1472 2022/10/08 15:07:25 - mmengine - INFO - Epoch(train) [140][1840/2119] lr: 4.0000e-03 eta: 1:45:43 time: 0.2571 data_time: 0.0176 memory: 5821 grad_norm: 5.3936 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9264 loss: 1.9264 2022/10/08 15:07:30 - mmengine - INFO - Epoch(train) [140][1860/2119] lr: 4.0000e-03 eta: 1:45:37 time: 0.2840 data_time: 0.0227 memory: 5821 grad_norm: 5.4931 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0386 loss: 2.0386 2022/10/08 15:07:36 - mmengine - INFO - Epoch(train) [140][1880/2119] lr: 4.0000e-03 eta: 1:45:32 time: 0.3128 data_time: 0.0174 memory: 5821 grad_norm: 5.3388 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0642 loss: 2.0642 2022/10/08 15:07:42 - mmengine - INFO - Epoch(train) [140][1900/2119] lr: 4.0000e-03 eta: 1:45:25 time: 0.2747 data_time: 0.0299 memory: 5821 grad_norm: 5.2205 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8214 loss: 1.8214 2022/10/08 15:07:48 - mmengine - INFO - Epoch(train) [140][1920/2119] lr: 4.0000e-03 eta: 1:45:19 time: 0.2965 data_time: 0.0206 memory: 5821 grad_norm: 5.4382 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1129 loss: 2.1129 2022/10/08 15:07:53 - mmengine - INFO - Epoch(train) [140][1940/2119] lr: 4.0000e-03 eta: 1:45:13 time: 0.2720 data_time: 0.0175 memory: 5821 grad_norm: 5.3870 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1560 loss: 2.1560 2022/10/08 15:07:59 - mmengine - INFO - Epoch(train) [140][1960/2119] lr: 4.0000e-03 eta: 1:45:06 time: 0.2762 data_time: 0.0169 memory: 5821 grad_norm: 5.4190 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 2.1428 loss: 2.1428 2022/10/08 15:08:06 - mmengine - INFO - Epoch(train) [140][1980/2119] lr: 4.0000e-03 eta: 1:45:02 time: 0.3364 data_time: 0.0204 memory: 5821 grad_norm: 5.4083 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 2.0271 loss: 2.0271 2022/10/08 15:08:11 - mmengine - INFO - Epoch(train) [140][2000/2119] lr: 4.0000e-03 eta: 1:44:55 time: 0.2577 data_time: 0.0257 memory: 5821 grad_norm: 5.2917 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.8179 loss: 1.8179 2022/10/08 15:08:17 - mmengine - INFO - Epoch(train) [140][2020/2119] lr: 4.0000e-03 eta: 1:44:49 time: 0.2937 data_time: 0.0258 memory: 5821 grad_norm: 5.3234 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7725 loss: 1.7725 2022/10/08 15:08:22 - mmengine - INFO - Epoch(train) [140][2040/2119] lr: 4.0000e-03 eta: 1:44:42 time: 0.2801 data_time: 0.0187 memory: 5821 grad_norm: 5.3802 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8602 loss: 1.8602 2022/10/08 15:08:28 - mmengine - INFO - Epoch(train) [140][2060/2119] lr: 4.0000e-03 eta: 1:44:37 time: 0.3007 data_time: 0.0209 memory: 5821 grad_norm: 5.3684 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0905 loss: 2.0905 2022/10/08 15:08:34 - mmengine - INFO - Epoch(train) [140][2080/2119] lr: 4.0000e-03 eta: 1:44:30 time: 0.2603 data_time: 0.0175 memory: 5821 grad_norm: 5.4629 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2282 loss: 2.2282 2022/10/08 15:08:40 - mmengine - INFO - Epoch(train) [140][2100/2119] lr: 4.0000e-03 eta: 1:44:24 time: 0.3170 data_time: 0.0203 memory: 5821 grad_norm: 5.3278 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8732 loss: 1.8732 2022/10/08 15:08:44 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 15:08:44 - mmengine - INFO - Epoch(train) [140][2119/2119] lr: 4.0000e-03 eta: 1:44:24 time: 0.2316 data_time: 0.0139 memory: 5821 grad_norm: 5.3290 top1_acc: 0.7000 top5_acc: 0.8000 loss_cls: 1.7150 loss: 1.7150 2022/10/08 15:08:44 - mmengine - INFO - Saving checkpoint at 140 epochs 2022/10/08 15:08:52 - mmengine - INFO - Epoch(val) [140][20/137] eta: 0:00:35 time: 0.3076 data_time: 0.2422 memory: 1236 2022/10/08 15:08:57 - mmengine - INFO - Epoch(val) [140][40/137] eta: 0:00:24 time: 0.2498 data_time: 0.1794 memory: 1236 2022/10/08 15:09:02 - mmengine - INFO - Epoch(val) [140][60/137] eta: 0:00:20 time: 0.2655 data_time: 0.2007 memory: 1236 2022/10/08 15:09:07 - mmengine - INFO - Epoch(val) [140][80/137] eta: 0:00:13 time: 0.2300 data_time: 0.1567 memory: 1236 2022/10/08 15:09:12 - mmengine - INFO - Epoch(val) [140][100/137] eta: 0:00:09 time: 0.2619 data_time: 0.1947 memory: 1236 2022/10/08 15:09:16 - mmengine - INFO - Epoch(val) [140][120/137] eta: 0:00:03 time: 0.2112 data_time: 0.1459 memory: 1236 2022/10/08 15:09:27 - mmengine - INFO - Epoch(val) [140][137/137] acc/top1: 0.5437 acc/top5: 0.7688 acc/mean1: 0.5436 2022/10/08 15:09:27 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb/best_acc/top1_epoch_125.pth is removed 2022/10/08 15:09:28 - mmengine - INFO - The best checkpoint with 0.5437 acc/top1 at 140 epoch is saved to best_acc/top1_epoch_140.pth. 2022/10/08 15:09:36 - mmengine - INFO - Epoch(train) [141][20/2119] lr: 4.0000e-04 eta: 1:44:08 time: 0.3816 data_time: 0.1358 memory: 5821 grad_norm: 5.3892 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7312 loss: 1.7312 2022/10/08 15:09:41 - mmengine - INFO - Epoch(train) [141][40/2119] lr: 4.0000e-04 eta: 1:44:01 time: 0.2622 data_time: 0.0198 memory: 5821 grad_norm: 5.3360 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9502 loss: 1.9502 2022/10/08 15:09:48 - mmengine - INFO - Epoch(train) [141][60/2119] lr: 4.0000e-04 eta: 1:43:57 time: 0.3430 data_time: 0.0208 memory: 5821 grad_norm: 5.2600 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8382 loss: 1.8382 2022/10/08 15:09:53 - mmengine - INFO - Epoch(train) [141][80/2119] lr: 4.0000e-04 eta: 1:43:50 time: 0.2652 data_time: 0.0227 memory: 5821 grad_norm: 5.3481 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1171 loss: 2.1171 2022/10/08 15:09:59 - mmengine - INFO - Epoch(train) [141][100/2119] lr: 4.0000e-04 eta: 1:43:44 time: 0.2934 data_time: 0.0192 memory: 5821 grad_norm: 5.1745 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8585 loss: 1.8585 2022/10/08 15:10:05 - mmengine - INFO - Epoch(train) [141][120/2119] lr: 4.0000e-04 eta: 1:43:38 time: 0.2795 data_time: 0.0163 memory: 5821 grad_norm: 5.1809 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9266 loss: 1.9266 2022/10/08 15:10:10 - mmengine - INFO - Epoch(train) [141][140/2119] lr: 4.0000e-04 eta: 1:43:31 time: 0.2763 data_time: 0.0233 memory: 5821 grad_norm: 5.3423 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9027 loss: 1.9027 2022/10/08 15:10:16 - mmengine - INFO - Epoch(train) [141][160/2119] lr: 4.0000e-04 eta: 1:43:26 time: 0.3078 data_time: 0.0218 memory: 5821 grad_norm: 5.2896 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9836 loss: 1.9836 2022/10/08 15:10:22 - mmengine - INFO - Epoch(train) [141][180/2119] lr: 4.0000e-04 eta: 1:43:20 time: 0.2910 data_time: 0.0149 memory: 5821 grad_norm: 5.1738 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5867 loss: 1.5867 2022/10/08 15:10:28 - mmengine - INFO - Epoch(train) [141][200/2119] lr: 4.0000e-04 eta: 1:43:13 time: 0.2686 data_time: 0.0146 memory: 5821 grad_norm: 5.2259 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7779 loss: 1.7779 2022/10/08 15:10:33 - mmengine - INFO - Epoch(train) [141][220/2119] lr: 4.0000e-04 eta: 1:43:07 time: 0.2680 data_time: 0.0226 memory: 5821 grad_norm: 5.1997 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8932 loss: 1.8932 2022/10/08 15:10:39 - mmengine - INFO - Epoch(train) [141][240/2119] lr: 4.0000e-04 eta: 1:43:01 time: 0.2979 data_time: 0.0159 memory: 5821 grad_norm: 5.3427 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8442 loss: 1.8442 2022/10/08 15:10:45 - mmengine - INFO - Epoch(train) [141][260/2119] lr: 4.0000e-04 eta: 1:42:55 time: 0.3075 data_time: 0.0157 memory: 5821 grad_norm: 5.2913 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.9420 loss: 1.9420 2022/10/08 15:10:51 - mmengine - INFO - Epoch(train) [141][280/2119] lr: 4.0000e-04 eta: 1:42:49 time: 0.2824 data_time: 0.0214 memory: 5821 grad_norm: 5.2083 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9904 loss: 1.9904 2022/10/08 15:10:56 - mmengine - INFO - Epoch(train) [141][300/2119] lr: 4.0000e-04 eta: 1:42:42 time: 0.2639 data_time: 0.0255 memory: 5821 grad_norm: 5.2976 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9908 loss: 1.9908 2022/10/08 15:11:02 - mmengine - INFO - Epoch(train) [141][320/2119] lr: 4.0000e-04 eta: 1:42:36 time: 0.2750 data_time: 0.0192 memory: 5821 grad_norm: 5.2685 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8143 loss: 1.8143 2022/10/08 15:11:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 15:11:08 - mmengine - INFO - Epoch(train) [141][340/2119] lr: 4.0000e-04 eta: 1:42:31 time: 0.3141 data_time: 0.0161 memory: 5821 grad_norm: 5.1683 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8493 loss: 1.8493 2022/10/08 15:11:13 - mmengine - INFO - Epoch(train) [141][360/2119] lr: 4.0000e-04 eta: 1:42:24 time: 0.2781 data_time: 0.0230 memory: 5821 grad_norm: 5.3312 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8202 loss: 1.8202 2022/10/08 15:11:19 - mmengine - INFO - Epoch(train) [141][380/2119] lr: 4.0000e-04 eta: 1:42:18 time: 0.2700 data_time: 0.0231 memory: 5821 grad_norm: 5.2425 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9309 loss: 1.9309 2022/10/08 15:11:24 - mmengine - INFO - Epoch(train) [141][400/2119] lr: 4.0000e-04 eta: 1:42:11 time: 0.2759 data_time: 0.0198 memory: 5821 grad_norm: 5.3044 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6757 loss: 1.6757 2022/10/08 15:11:30 - mmengine - INFO - Epoch(train) [141][420/2119] lr: 4.0000e-04 eta: 1:42:05 time: 0.2867 data_time: 0.0203 memory: 5821 grad_norm: 5.2728 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9353 loss: 1.9353 2022/10/08 15:11:36 - mmengine - INFO - Epoch(train) [141][440/2119] lr: 4.0000e-04 eta: 1:41:59 time: 0.2932 data_time: 0.0166 memory: 5821 grad_norm: 5.3327 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7727 loss: 1.7727 2022/10/08 15:11:42 - mmengine - INFO - Epoch(train) [141][460/2119] lr: 4.0000e-04 eta: 1:41:54 time: 0.3023 data_time: 0.0254 memory: 5821 grad_norm: 5.2988 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9351 loss: 1.9351 2022/10/08 15:11:48 - mmengine - INFO - Epoch(train) [141][480/2119] lr: 4.0000e-04 eta: 1:41:48 time: 0.2903 data_time: 0.0266 memory: 5821 grad_norm: 5.1696 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.7199 loss: 1.7199 2022/10/08 15:11:54 - mmengine - INFO - Epoch(train) [141][500/2119] lr: 4.0000e-04 eta: 1:41:42 time: 0.3234 data_time: 0.0154 memory: 5821 grad_norm: 5.3086 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9445 loss: 1.9445 2022/10/08 15:11:59 - mmengine - INFO - Epoch(train) [141][520/2119] lr: 4.0000e-04 eta: 1:41:36 time: 0.2547 data_time: 0.0220 memory: 5821 grad_norm: 5.2400 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8857 loss: 1.8857 2022/10/08 15:12:05 - mmengine - INFO - Epoch(train) [141][540/2119] lr: 4.0000e-04 eta: 1:41:30 time: 0.2978 data_time: 0.0195 memory: 5821 grad_norm: 5.2133 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9893 loss: 1.9893 2022/10/08 15:12:11 - mmengine - INFO - Epoch(train) [141][560/2119] lr: 4.0000e-04 eta: 1:41:24 time: 0.2938 data_time: 0.0206 memory: 5821 grad_norm: 5.2691 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9156 loss: 1.9156 2022/10/08 15:12:17 - mmengine - INFO - Epoch(train) [141][580/2119] lr: 4.0000e-04 eta: 1:41:18 time: 0.2767 data_time: 0.0235 memory: 5821 grad_norm: 5.2561 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 1.9729 loss: 1.9729 2022/10/08 15:12:23 - mmengine - INFO - Epoch(train) [141][600/2119] lr: 4.0000e-04 eta: 1:41:11 time: 0.2875 data_time: 0.0150 memory: 5821 grad_norm: 5.2742 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9496 loss: 1.9496 2022/10/08 15:12:28 - mmengine - INFO - Epoch(train) [141][620/2119] lr: 4.0000e-04 eta: 1:41:05 time: 0.2857 data_time: 0.0363 memory: 5821 grad_norm: 5.2638 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8201 loss: 1.8201 2022/10/08 15:12:34 - mmengine - INFO - Epoch(train) [141][640/2119] lr: 4.0000e-04 eta: 1:41:00 time: 0.3007 data_time: 0.0190 memory: 5821 grad_norm: 5.2687 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9985 loss: 1.9985 2022/10/08 15:12:40 - mmengine - INFO - Epoch(train) [141][660/2119] lr: 4.0000e-04 eta: 1:40:54 time: 0.3013 data_time: 0.0187 memory: 5821 grad_norm: 5.2649 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0833 loss: 2.0833 2022/10/08 15:12:46 - mmengine - INFO - Epoch(train) [141][680/2119] lr: 4.0000e-04 eta: 1:40:47 time: 0.2699 data_time: 0.0174 memory: 5821 grad_norm: 5.2344 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7004 loss: 1.7004 2022/10/08 15:12:51 - mmengine - INFO - Epoch(train) [141][700/2119] lr: 4.0000e-04 eta: 1:40:41 time: 0.2655 data_time: 0.0233 memory: 5821 grad_norm: 5.4514 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9593 loss: 1.9593 2022/10/08 15:12:57 - mmengine - INFO - Epoch(train) [141][720/2119] lr: 4.0000e-04 eta: 1:40:35 time: 0.2927 data_time: 0.0190 memory: 5821 grad_norm: 5.2683 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8481 loss: 1.8481 2022/10/08 15:13:03 - mmengine - INFO - Epoch(train) [141][740/2119] lr: 4.0000e-04 eta: 1:40:29 time: 0.3071 data_time: 0.0209 memory: 5821 grad_norm: 5.3096 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.8650 loss: 1.8650 2022/10/08 15:13:09 - mmengine - INFO - Epoch(train) [141][760/2119] lr: 4.0000e-04 eta: 1:40:23 time: 0.2743 data_time: 0.0131 memory: 5821 grad_norm: 5.3270 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8374 loss: 1.8374 2022/10/08 15:13:14 - mmengine - INFO - Epoch(train) [141][780/2119] lr: 4.0000e-04 eta: 1:40:17 time: 0.2896 data_time: 0.0242 memory: 5821 grad_norm: 5.3077 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8131 loss: 1.8131 2022/10/08 15:13:20 - mmengine - INFO - Epoch(train) [141][800/2119] lr: 4.0000e-04 eta: 1:40:10 time: 0.2760 data_time: 0.0161 memory: 5821 grad_norm: 5.2666 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7542 loss: 1.7542 2022/10/08 15:13:26 - mmengine - INFO - Epoch(train) [141][820/2119] lr: 4.0000e-04 eta: 1:40:04 time: 0.2881 data_time: 0.0184 memory: 5821 grad_norm: 5.4318 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 1.9390 loss: 1.9390 2022/10/08 15:13:44 - mmengine - INFO - Epoch(train) [141][840/2119] lr: 4.0000e-04 eta: 1:40:12 time: 0.8962 data_time: 0.6115 memory: 5821 grad_norm: 5.3063 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5927 loss: 1.5927 2022/10/08 15:13:49 - mmengine - INFO - Epoch(train) [141][860/2119] lr: 4.0000e-04 eta: 1:40:06 time: 0.2619 data_time: 0.0325 memory: 5821 grad_norm: 5.2581 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8954 loss: 1.8954 2022/10/08 15:13:55 - mmengine - INFO - Epoch(train) [141][880/2119] lr: 4.0000e-04 eta: 1:40:00 time: 0.3023 data_time: 0.0147 memory: 5821 grad_norm: 5.3313 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7522 loss: 1.7522 2022/10/08 15:14:00 - mmengine - INFO - Epoch(train) [141][900/2119] lr: 4.0000e-04 eta: 1:39:53 time: 0.2597 data_time: 0.0179 memory: 5821 grad_norm: 5.4546 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6015 loss: 1.6015 2022/10/08 15:14:06 - mmengine - INFO - Epoch(train) [141][920/2119] lr: 4.0000e-04 eta: 1:39:48 time: 0.3080 data_time: 0.0157 memory: 5821 grad_norm: 5.2362 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8365 loss: 1.8365 2022/10/08 15:14:12 - mmengine - INFO - Epoch(train) [141][940/2119] lr: 4.0000e-04 eta: 1:39:41 time: 0.2859 data_time: 0.0178 memory: 5821 grad_norm: 5.3637 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9317 loss: 1.9317 2022/10/08 15:14:18 - mmengine - INFO - Epoch(train) [141][960/2119] lr: 4.0000e-04 eta: 1:39:36 time: 0.3072 data_time: 0.0212 memory: 5821 grad_norm: 5.2940 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9070 loss: 1.9070 2022/10/08 15:14:25 - mmengine - INFO - Epoch(train) [141][980/2119] lr: 4.0000e-04 eta: 1:39:31 time: 0.3322 data_time: 0.0206 memory: 5821 grad_norm: 5.2752 top1_acc: 0.4375 top5_acc: 1.0000 loss_cls: 1.7958 loss: 1.7958 2022/10/08 15:14:30 - mmengine - INFO - Epoch(train) [141][1000/2119] lr: 4.0000e-04 eta: 1:39:24 time: 0.2640 data_time: 0.0192 memory: 5821 grad_norm: 5.2892 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0814 loss: 2.0814 2022/10/08 15:14:35 - mmengine - INFO - Epoch(train) [141][1020/2119] lr: 4.0000e-04 eta: 1:39:17 time: 0.2646 data_time: 0.0196 memory: 5821 grad_norm: 5.2605 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.9397 loss: 1.9397 2022/10/08 15:14:41 - mmengine - INFO - Epoch(train) [141][1040/2119] lr: 4.0000e-04 eta: 1:39:11 time: 0.2723 data_time: 0.0216 memory: 5821 grad_norm: 5.3303 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 1.6322 loss: 1.6322 2022/10/08 15:14:47 - mmengine - INFO - Epoch(train) [141][1060/2119] lr: 4.0000e-04 eta: 1:39:05 time: 0.3093 data_time: 0.0196 memory: 5821 grad_norm: 5.3442 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7991 loss: 1.7991 2022/10/08 15:14:53 - mmengine - INFO - Epoch(train) [141][1080/2119] lr: 4.0000e-04 eta: 1:39:00 time: 0.2994 data_time: 0.0164 memory: 5821 grad_norm: 5.2447 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0016 loss: 2.0016 2022/10/08 15:14:59 - mmengine - INFO - Epoch(train) [141][1100/2119] lr: 4.0000e-04 eta: 1:38:54 time: 0.2867 data_time: 0.0294 memory: 5821 grad_norm: 5.3604 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9349 loss: 1.9349 2022/10/08 15:15:04 - mmengine - INFO - Epoch(train) [141][1120/2119] lr: 4.0000e-04 eta: 1:38:47 time: 0.2702 data_time: 0.0144 memory: 5821 grad_norm: 5.4334 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.7831 loss: 1.7831 2022/10/08 15:15:10 - mmengine - INFO - Epoch(train) [141][1140/2119] lr: 4.0000e-04 eta: 1:38:41 time: 0.2991 data_time: 0.0155 memory: 5821 grad_norm: 5.3813 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8604 loss: 1.8604 2022/10/08 15:15:17 - mmengine - INFO - Epoch(train) [141][1160/2119] lr: 4.0000e-04 eta: 1:38:36 time: 0.3252 data_time: 0.0177 memory: 5821 grad_norm: 5.2988 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.8122 loss: 1.8122 2022/10/08 15:15:22 - mmengine - INFO - Epoch(train) [141][1180/2119] lr: 4.0000e-04 eta: 1:38:30 time: 0.2729 data_time: 0.0246 memory: 5821 grad_norm: 5.4120 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6920 loss: 1.6920 2022/10/08 15:15:27 - mmengine - INFO - Epoch(train) [141][1200/2119] lr: 4.0000e-04 eta: 1:38:23 time: 0.2590 data_time: 0.0257 memory: 5821 grad_norm: 5.2699 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9165 loss: 1.9165 2022/10/08 15:15:34 - mmengine - INFO - Epoch(train) [141][1220/2119] lr: 4.0000e-04 eta: 1:38:17 time: 0.3079 data_time: 0.0211 memory: 5821 grad_norm: 5.3607 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8867 loss: 1.8867 2022/10/08 15:15:39 - mmengine - INFO - Epoch(train) [141][1240/2119] lr: 4.0000e-04 eta: 1:38:11 time: 0.2929 data_time: 0.0207 memory: 5821 grad_norm: 5.3250 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8310 loss: 1.8310 2022/10/08 15:15:46 - mmengine - INFO - Epoch(train) [141][1260/2119] lr: 4.0000e-04 eta: 1:38:06 time: 0.3071 data_time: 0.0181 memory: 5821 grad_norm: 5.3420 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6943 loss: 1.6943 2022/10/08 15:15:51 - mmengine - INFO - Epoch(train) [141][1280/2119] lr: 4.0000e-04 eta: 1:37:59 time: 0.2803 data_time: 0.0219 memory: 5821 grad_norm: 5.4356 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6825 loss: 1.6825 2022/10/08 15:15:57 - mmengine - INFO - Epoch(train) [141][1300/2119] lr: 4.0000e-04 eta: 1:37:54 time: 0.2966 data_time: 0.0266 memory: 5821 grad_norm: 5.2558 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.6957 loss: 1.6957 2022/10/08 15:16:03 - mmengine - INFO - Epoch(train) [141][1320/2119] lr: 4.0000e-04 eta: 1:37:47 time: 0.2685 data_time: 0.0228 memory: 5821 grad_norm: 5.3198 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7558 loss: 1.7558 2022/10/08 15:16:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 15:16:08 - mmengine - INFO - Epoch(train) [141][1340/2119] lr: 4.0000e-04 eta: 1:37:41 time: 0.2699 data_time: 0.0193 memory: 5821 grad_norm: 5.4095 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8808 loss: 1.8808 2022/10/08 15:16:14 - mmengine - INFO - Epoch(train) [141][1360/2119] lr: 4.0000e-04 eta: 1:37:34 time: 0.2862 data_time: 0.0233 memory: 5821 grad_norm: 5.4265 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 1.9440 loss: 1.9440 2022/10/08 15:16:20 - mmengine - INFO - Epoch(train) [141][1380/2119] lr: 4.0000e-04 eta: 1:37:29 time: 0.3084 data_time: 0.0235 memory: 5821 grad_norm: 5.3175 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9924 loss: 1.9924 2022/10/08 15:16:25 - mmengine - INFO - Epoch(train) [141][1400/2119] lr: 4.0000e-04 eta: 1:37:22 time: 0.2644 data_time: 0.0170 memory: 5821 grad_norm: 5.3708 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9242 loss: 1.9242 2022/10/08 15:16:32 - mmengine - INFO - Epoch(train) [141][1420/2119] lr: 4.0000e-04 eta: 1:37:17 time: 0.3239 data_time: 0.0164 memory: 5821 grad_norm: 5.2492 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8261 loss: 1.8261 2022/10/08 15:16:37 - mmengine - INFO - Epoch(train) [141][1440/2119] lr: 4.0000e-04 eta: 1:37:10 time: 0.2631 data_time: 0.0242 memory: 5821 grad_norm: 5.3240 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.7858 loss: 1.7858 2022/10/08 15:16:43 - mmengine - INFO - Epoch(train) [141][1460/2119] lr: 4.0000e-04 eta: 1:37:05 time: 0.3244 data_time: 0.0194 memory: 5821 grad_norm: 5.3675 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.8362 loss: 1.8362 2022/10/08 15:16:49 - mmengine - INFO - Epoch(train) [141][1480/2119] lr: 4.0000e-04 eta: 1:36:59 time: 0.2657 data_time: 0.0121 memory: 5821 grad_norm: 5.3216 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8838 loss: 1.8838 2022/10/08 15:16:54 - mmengine - INFO - Epoch(train) [141][1500/2119] lr: 4.0000e-04 eta: 1:36:52 time: 0.2835 data_time: 0.0230 memory: 5821 grad_norm: 5.4153 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7763 loss: 1.7763 2022/10/08 15:17:00 - mmengine - INFO - Epoch(train) [141][1520/2119] lr: 4.0000e-04 eta: 1:36:46 time: 0.2841 data_time: 0.0206 memory: 5821 grad_norm: 5.3051 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9019 loss: 1.9019 2022/10/08 15:17:06 - mmengine - INFO - Epoch(train) [141][1540/2119] lr: 4.0000e-04 eta: 1:36:41 time: 0.3029 data_time: 0.0188 memory: 5821 grad_norm: 5.2825 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8256 loss: 1.8256 2022/10/08 15:17:12 - mmengine - INFO - Epoch(train) [141][1560/2119] lr: 4.0000e-04 eta: 1:36:35 time: 0.2907 data_time: 0.0173 memory: 5821 grad_norm: 5.2800 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.7101 loss: 1.7101 2022/10/08 15:17:18 - mmengine - INFO - Epoch(train) [141][1580/2119] lr: 4.0000e-04 eta: 1:36:29 time: 0.2921 data_time: 0.0184 memory: 5821 grad_norm: 5.3328 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8852 loss: 1.8852 2022/10/08 15:17:24 - mmengine - INFO - Epoch(train) [141][1600/2119] lr: 4.0000e-04 eta: 1:36:22 time: 0.2832 data_time: 0.0228 memory: 5821 grad_norm: 5.3284 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.9233 loss: 1.9233 2022/10/08 15:17:29 - mmengine - INFO - Epoch(train) [141][1620/2119] lr: 4.0000e-04 eta: 1:36:16 time: 0.2852 data_time: 0.0184 memory: 5821 grad_norm: 5.2832 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6836 loss: 1.6836 2022/10/08 15:17:35 - mmengine - INFO - Epoch(train) [141][1640/2119] lr: 4.0000e-04 eta: 1:36:10 time: 0.2743 data_time: 0.0158 memory: 5821 grad_norm: 5.3218 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.7284 loss: 1.7284 2022/10/08 15:17:41 - mmengine - INFO - Epoch(train) [141][1660/2119] lr: 4.0000e-04 eta: 1:36:05 time: 0.3257 data_time: 0.0289 memory: 5821 grad_norm: 5.3463 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.6185 loss: 1.6185 2022/10/08 15:17:47 - mmengine - INFO - Epoch(train) [141][1680/2119] lr: 4.0000e-04 eta: 1:35:59 time: 0.2854 data_time: 0.0150 memory: 5821 grad_norm: 5.3160 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9560 loss: 1.9560 2022/10/08 15:17:53 - mmengine - INFO - Epoch(train) [141][1700/2119] lr: 4.0000e-04 eta: 1:35:52 time: 0.2806 data_time: 0.0189 memory: 5821 grad_norm: 5.3352 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9065 loss: 1.9065 2022/10/08 15:17:58 - mmengine - INFO - Epoch(train) [141][1720/2119] lr: 4.0000e-04 eta: 1:35:46 time: 0.2795 data_time: 0.0193 memory: 5821 grad_norm: 5.1867 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.7881 loss: 1.7881 2022/10/08 15:18:05 - mmengine - INFO - Epoch(train) [141][1740/2119] lr: 4.0000e-04 eta: 1:35:41 time: 0.3254 data_time: 0.0220 memory: 5821 grad_norm: 5.3388 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9739 loss: 1.9739 2022/10/08 15:18:10 - mmengine - INFO - Epoch(train) [141][1760/2119] lr: 4.0000e-04 eta: 1:35:35 time: 0.2852 data_time: 0.0193 memory: 5821 grad_norm: 5.2984 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7376 loss: 1.7376 2022/10/08 15:18:16 - mmengine - INFO - Epoch(train) [141][1780/2119] lr: 4.0000e-04 eta: 1:35:29 time: 0.2856 data_time: 0.0294 memory: 5821 grad_norm: 5.3212 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9460 loss: 1.9460 2022/10/08 15:18:22 - mmengine - INFO - Epoch(train) [141][1800/2119] lr: 4.0000e-04 eta: 1:35:22 time: 0.2727 data_time: 0.0150 memory: 5821 grad_norm: 5.3051 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7292 loss: 1.7292 2022/10/08 15:18:27 - mmengine - INFO - Epoch(train) [141][1820/2119] lr: 4.0000e-04 eta: 1:35:16 time: 0.2901 data_time: 0.0249 memory: 5821 grad_norm: 5.3941 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9901 loss: 1.9901 2022/10/08 15:18:33 - mmengine - INFO - Epoch(train) [141][1840/2119] lr: 4.0000e-04 eta: 1:35:10 time: 0.2818 data_time: 0.0218 memory: 5821 grad_norm: 5.3318 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9526 loss: 1.9526 2022/10/08 15:18:39 - mmengine - INFO - Epoch(train) [141][1860/2119] lr: 4.0000e-04 eta: 1:35:04 time: 0.3040 data_time: 0.0452 memory: 5821 grad_norm: 5.3551 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9180 loss: 1.9180 2022/10/08 15:18:45 - mmengine - INFO - Epoch(train) [141][1880/2119] lr: 4.0000e-04 eta: 1:34:58 time: 0.2747 data_time: 0.0167 memory: 5821 grad_norm: 5.3625 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9535 loss: 1.9535 2022/10/08 15:18:50 - mmengine - INFO - Epoch(train) [141][1900/2119] lr: 4.0000e-04 eta: 1:34:52 time: 0.2813 data_time: 0.0192 memory: 5821 grad_norm: 5.4315 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1343 loss: 2.1343 2022/10/08 15:18:59 - mmengine - INFO - Epoch(train) [141][1920/2119] lr: 4.0000e-04 eta: 1:34:49 time: 0.4306 data_time: 0.0175 memory: 5821 grad_norm: 5.3406 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7874 loss: 1.7874 2022/10/08 15:19:07 - mmengine - INFO - Epoch(train) [141][1940/2119] lr: 4.0000e-04 eta: 1:34:45 time: 0.3804 data_time: 0.1523 memory: 5821 grad_norm: 5.3781 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0301 loss: 2.0301 2022/10/08 15:19:12 - mmengine - INFO - Epoch(train) [141][1960/2119] lr: 4.0000e-04 eta: 1:34:38 time: 0.2537 data_time: 0.0228 memory: 5821 grad_norm: 5.3229 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.0652 loss: 2.0652 2022/10/08 15:19:18 - mmengine - INFO - Epoch(train) [141][1980/2119] lr: 4.0000e-04 eta: 1:34:32 time: 0.3063 data_time: 0.0163 memory: 5821 grad_norm: 5.2833 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6096 loss: 1.6096 2022/10/08 15:19:23 - mmengine - INFO - Epoch(train) [141][2000/2119] lr: 4.0000e-04 eta: 1:34:26 time: 0.2840 data_time: 0.0194 memory: 5821 grad_norm: 5.3205 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.8163 loss: 1.8163 2022/10/08 15:19:29 - mmengine - INFO - Epoch(train) [141][2020/2119] lr: 4.0000e-04 eta: 1:34:20 time: 0.2987 data_time: 0.0151 memory: 5821 grad_norm: 5.2898 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6744 loss: 1.6744 2022/10/08 15:19:35 - mmengine - INFO - Epoch(train) [141][2040/2119] lr: 4.0000e-04 eta: 1:34:14 time: 0.2856 data_time: 0.0151 memory: 5821 grad_norm: 5.3610 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7418 loss: 1.7418 2022/10/08 15:19:41 - mmengine - INFO - Epoch(train) [141][2060/2119] lr: 4.0000e-04 eta: 1:34:08 time: 0.2763 data_time: 0.0170 memory: 5821 grad_norm: 5.2934 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7635 loss: 1.7635 2022/10/08 15:19:47 - mmengine - INFO - Epoch(train) [141][2080/2119] lr: 4.0000e-04 eta: 1:34:02 time: 0.3080 data_time: 0.0182 memory: 5821 grad_norm: 5.3911 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.1801 loss: 2.1801 2022/10/08 15:19:52 - mmengine - INFO - Epoch(train) [141][2100/2119] lr: 4.0000e-04 eta: 1:33:56 time: 0.2705 data_time: 0.0201 memory: 5821 grad_norm: 5.3451 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9096 loss: 1.9096 2022/10/08 15:19:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 15:19:58 - mmengine - INFO - Epoch(train) [141][2119/2119] lr: 4.0000e-04 eta: 1:33:56 time: 0.3182 data_time: 0.0198 memory: 5821 grad_norm: 5.4207 top1_acc: 0.6000 top5_acc: 0.9000 loss_cls: 1.8508 loss: 1.8508 2022/10/08 15:20:07 - mmengine - INFO - Epoch(train) [142][20/2119] lr: 4.0000e-04 eta: 1:33:42 time: 0.4478 data_time: 0.1344 memory: 5821 grad_norm: 5.2897 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7167 loss: 1.7167 2022/10/08 15:20:13 - mmengine - INFO - Epoch(train) [142][40/2119] lr: 4.0000e-04 eta: 1:33:35 time: 0.2708 data_time: 0.0163 memory: 5821 grad_norm: 5.3208 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9131 loss: 1.9131 2022/10/08 15:20:19 - mmengine - INFO - Epoch(train) [142][60/2119] lr: 4.0000e-04 eta: 1:33:30 time: 0.3142 data_time: 0.0184 memory: 5821 grad_norm: 5.3224 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6999 loss: 1.6999 2022/10/08 15:20:24 - mmengine - INFO - Epoch(train) [142][80/2119] lr: 4.0000e-04 eta: 1:33:23 time: 0.2565 data_time: 0.0159 memory: 5821 grad_norm: 5.3921 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9653 loss: 1.9653 2022/10/08 15:20:30 - mmengine - INFO - Epoch(train) [142][100/2119] lr: 4.0000e-04 eta: 1:33:17 time: 0.2977 data_time: 0.0196 memory: 5821 grad_norm: 5.3261 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7541 loss: 1.7541 2022/10/08 15:20:36 - mmengine - INFO - Epoch(train) [142][120/2119] lr: 4.0000e-04 eta: 1:33:11 time: 0.2983 data_time: 0.0125 memory: 5821 grad_norm: 5.3070 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8823 loss: 1.8823 2022/10/08 15:20:42 - mmengine - INFO - Epoch(train) [142][140/2119] lr: 4.0000e-04 eta: 1:33:05 time: 0.2824 data_time: 0.0192 memory: 5821 grad_norm: 5.3204 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8203 loss: 1.8203 2022/10/08 15:20:47 - mmengine - INFO - Epoch(train) [142][160/2119] lr: 4.0000e-04 eta: 1:32:59 time: 0.2688 data_time: 0.0207 memory: 5821 grad_norm: 5.3195 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8106 loss: 1.8106 2022/10/08 15:20:53 - mmengine - INFO - Epoch(train) [142][180/2119] lr: 4.0000e-04 eta: 1:32:53 time: 0.2894 data_time: 0.0217 memory: 5821 grad_norm: 5.3931 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8327 loss: 1.8327 2022/10/08 15:20:59 - mmengine - INFO - Epoch(train) [142][200/2119] lr: 4.0000e-04 eta: 1:32:47 time: 0.3109 data_time: 0.0182 memory: 5821 grad_norm: 5.4231 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7810 loss: 1.7810 2022/10/08 15:21:05 - mmengine - INFO - Epoch(train) [142][220/2119] lr: 4.0000e-04 eta: 1:32:41 time: 0.2820 data_time: 0.0256 memory: 5821 grad_norm: 5.3739 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9611 loss: 1.9611 2022/10/08 15:21:05 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 15:21:11 - mmengine - INFO - Epoch(train) [142][240/2119] lr: 4.0000e-04 eta: 1:32:35 time: 0.2762 data_time: 0.0186 memory: 5821 grad_norm: 5.4246 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1838 loss: 2.1838 2022/10/08 15:21:17 - mmengine - INFO - Epoch(train) [142][260/2119] lr: 4.0000e-04 eta: 1:32:29 time: 0.2987 data_time: 0.0132 memory: 5821 grad_norm: 5.3037 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8507 loss: 1.8507 2022/10/08 15:21:22 - mmengine - INFO - Epoch(train) [142][280/2119] lr: 4.0000e-04 eta: 1:32:23 time: 0.2769 data_time: 0.0373 memory: 5821 grad_norm: 5.3162 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9223 loss: 1.9223 2022/10/08 15:21:28 - mmengine - INFO - Epoch(train) [142][300/2119] lr: 4.0000e-04 eta: 1:32:17 time: 0.2970 data_time: 0.0234 memory: 5821 grad_norm: 5.3319 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8456 loss: 1.8456 2022/10/08 15:21:34 - mmengine - INFO - Epoch(train) [142][320/2119] lr: 4.0000e-04 eta: 1:32:11 time: 0.2833 data_time: 0.0228 memory: 5821 grad_norm: 5.3079 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8550 loss: 1.8550 2022/10/08 15:21:39 - mmengine - INFO - Epoch(train) [142][340/2119] lr: 4.0000e-04 eta: 1:32:04 time: 0.2751 data_time: 0.0224 memory: 5821 grad_norm: 5.3287 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6126 loss: 1.6126 2022/10/08 15:21:45 - mmengine - INFO - Epoch(train) [142][360/2119] lr: 4.0000e-04 eta: 1:31:58 time: 0.2686 data_time: 0.0220 memory: 5821 grad_norm: 5.3221 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8793 loss: 1.8793 2022/10/08 15:21:51 - mmengine - INFO - Epoch(train) [142][380/2119] lr: 4.0000e-04 eta: 1:31:52 time: 0.2959 data_time: 0.0187 memory: 5821 grad_norm: 5.3521 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.6573 loss: 1.6573 2022/10/08 15:22:09 - mmengine - INFO - Epoch(train) [142][400/2119] lr: 4.0000e-04 eta: 1:31:59 time: 0.9369 data_time: 0.0142 memory: 5821 grad_norm: 5.3904 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.6536 loss: 1.6536 2022/10/08 15:22:15 - mmengine - INFO - Epoch(train) [142][420/2119] lr: 4.0000e-04 eta: 1:31:52 time: 0.2629 data_time: 0.0279 memory: 5821 grad_norm: 5.5670 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8212 loss: 1.8212 2022/10/08 15:22:20 - mmengine - INFO - Epoch(train) [142][440/2119] lr: 4.0000e-04 eta: 1:31:45 time: 0.2542 data_time: 0.0212 memory: 5821 grad_norm: 5.3509 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7283 loss: 1.7283 2022/10/08 15:22:25 - mmengine - INFO - Epoch(train) [142][460/2119] lr: 4.0000e-04 eta: 1:31:39 time: 0.2885 data_time: 0.0213 memory: 5821 grad_norm: 5.3713 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8457 loss: 1.8457 2022/10/08 15:22:32 - mmengine - INFO - Epoch(train) [142][480/2119] lr: 4.0000e-04 eta: 1:31:34 time: 0.3046 data_time: 0.0163 memory: 5821 grad_norm: 5.2472 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.8405 loss: 1.8405 2022/10/08 15:22:38 - mmengine - INFO - Epoch(train) [142][500/2119] lr: 4.0000e-04 eta: 1:31:28 time: 0.3207 data_time: 0.0212 memory: 5821 grad_norm: 5.4309 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7954 loss: 1.7954 2022/10/08 15:22:43 - mmengine - INFO - Epoch(train) [142][520/2119] lr: 4.0000e-04 eta: 1:31:22 time: 0.2606 data_time: 0.0177 memory: 5821 grad_norm: 5.4053 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.8341 loss: 1.8341 2022/10/08 15:22:49 - mmengine - INFO - Epoch(train) [142][540/2119] lr: 4.0000e-04 eta: 1:31:16 time: 0.3051 data_time: 0.0361 memory: 5821 grad_norm: 5.5099 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9594 loss: 1.9594 2022/10/08 15:22:55 - mmengine - INFO - Epoch(train) [142][560/2119] lr: 4.0000e-04 eta: 1:31:10 time: 0.2809 data_time: 0.0265 memory: 5821 grad_norm: 5.4693 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7477 loss: 1.7477 2022/10/08 15:23:01 - mmengine - INFO - Epoch(train) [142][580/2119] lr: 4.0000e-04 eta: 1:31:04 time: 0.2945 data_time: 0.0328 memory: 5821 grad_norm: 5.5141 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6978 loss: 1.6978 2022/10/08 15:23:06 - mmengine - INFO - Epoch(train) [142][600/2119] lr: 4.0000e-04 eta: 1:30:57 time: 0.2572 data_time: 0.0166 memory: 5821 grad_norm: 5.3461 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5363 loss: 1.5363 2022/10/08 15:23:12 - mmengine - INFO - Epoch(train) [142][620/2119] lr: 4.0000e-04 eta: 1:30:51 time: 0.2958 data_time: 0.0263 memory: 5821 grad_norm: 5.4793 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9029 loss: 1.9029 2022/10/08 15:23:18 - mmengine - INFO - Epoch(train) [142][640/2119] lr: 4.0000e-04 eta: 1:30:45 time: 0.2946 data_time: 0.0207 memory: 5821 grad_norm: 5.4327 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9605 loss: 1.9605 2022/10/08 15:23:23 - mmengine - INFO - Epoch(train) [142][660/2119] lr: 4.0000e-04 eta: 1:30:39 time: 0.2681 data_time: 0.0223 memory: 5821 grad_norm: 5.2924 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8537 loss: 1.8537 2022/10/08 15:23:30 - mmengine - INFO - Epoch(train) [142][680/2119] lr: 4.0000e-04 eta: 1:30:34 time: 0.3310 data_time: 0.0180 memory: 5821 grad_norm: 5.2601 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9973 loss: 1.9973 2022/10/08 15:23:35 - mmengine - INFO - Epoch(train) [142][700/2119] lr: 4.0000e-04 eta: 1:30:27 time: 0.2545 data_time: 0.0202 memory: 5821 grad_norm: 5.4332 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9046 loss: 1.9046 2022/10/08 15:23:41 - mmengine - INFO - Epoch(train) [142][720/2119] lr: 4.0000e-04 eta: 1:30:21 time: 0.3058 data_time: 0.0193 memory: 5821 grad_norm: 5.4214 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0077 loss: 2.0077 2022/10/08 15:23:47 - mmengine - INFO - Epoch(train) [142][740/2119] lr: 4.0000e-04 eta: 1:30:15 time: 0.2992 data_time: 0.0159 memory: 5821 grad_norm: 5.4356 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6523 loss: 1.6523 2022/10/08 15:23:52 - mmengine - INFO - Epoch(train) [142][760/2119] lr: 4.0000e-04 eta: 1:30:09 time: 0.2631 data_time: 0.0246 memory: 5821 grad_norm: 5.3632 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6484 loss: 1.6484 2022/10/08 15:23:58 - mmengine - INFO - Epoch(train) [142][780/2119] lr: 4.0000e-04 eta: 1:30:03 time: 0.2848 data_time: 0.0179 memory: 5821 grad_norm: 5.3594 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0502 loss: 2.0502 2022/10/08 15:24:04 - mmengine - INFO - Epoch(train) [142][800/2119] lr: 4.0000e-04 eta: 1:29:57 time: 0.3185 data_time: 0.0151 memory: 5821 grad_norm: 5.2979 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5996 loss: 1.5996 2022/10/08 15:24:10 - mmengine - INFO - Epoch(train) [142][820/2119] lr: 4.0000e-04 eta: 1:29:51 time: 0.2818 data_time: 0.0274 memory: 5821 grad_norm: 5.5207 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 1.9396 loss: 1.9396 2022/10/08 15:24:15 - mmengine - INFO - Epoch(train) [142][840/2119] lr: 4.0000e-04 eta: 1:29:45 time: 0.2654 data_time: 0.0233 memory: 5821 grad_norm: 5.3842 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8152 loss: 1.8152 2022/10/08 15:24:21 - mmengine - INFO - Epoch(train) [142][860/2119] lr: 4.0000e-04 eta: 1:29:39 time: 0.2886 data_time: 0.0184 memory: 5821 grad_norm: 5.3142 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7207 loss: 1.7207 2022/10/08 15:24:27 - mmengine - INFO - Epoch(train) [142][880/2119] lr: 4.0000e-04 eta: 1:29:33 time: 0.3047 data_time: 0.0167 memory: 5821 grad_norm: 5.3923 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.6597 loss: 1.6597 2022/10/08 15:24:33 - mmengine - INFO - Epoch(train) [142][900/2119] lr: 4.0000e-04 eta: 1:29:27 time: 0.2702 data_time: 0.0191 memory: 5821 grad_norm: 5.3983 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8346 loss: 1.8346 2022/10/08 15:24:38 - mmengine - INFO - Epoch(train) [142][920/2119] lr: 4.0000e-04 eta: 1:29:20 time: 0.2890 data_time: 0.0175 memory: 5821 grad_norm: 5.3625 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9505 loss: 1.9505 2022/10/08 15:24:44 - mmengine - INFO - Epoch(train) [142][940/2119] lr: 4.0000e-04 eta: 1:29:14 time: 0.2684 data_time: 0.0205 memory: 5821 grad_norm: 5.3953 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6513 loss: 1.6513 2022/10/08 15:24:50 - mmengine - INFO - Epoch(train) [142][960/2119] lr: 4.0000e-04 eta: 1:29:08 time: 0.2870 data_time: 0.0179 memory: 5821 grad_norm: 5.3300 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 1.9730 loss: 1.9730 2022/10/08 15:24:56 - mmengine - INFO - Epoch(train) [142][980/2119] lr: 4.0000e-04 eta: 1:29:02 time: 0.3026 data_time: 0.0213 memory: 5821 grad_norm: 5.3715 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9061 loss: 1.9061 2022/10/08 15:25:01 - mmengine - INFO - Epoch(train) [142][1000/2119] lr: 4.0000e-04 eta: 1:28:56 time: 0.2861 data_time: 0.0245 memory: 5821 grad_norm: 5.3942 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7872 loss: 1.7872 2022/10/08 15:25:07 - mmengine - INFO - Epoch(train) [142][1020/2119] lr: 4.0000e-04 eta: 1:28:50 time: 0.2943 data_time: 0.0173 memory: 5821 grad_norm: 5.3124 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7219 loss: 1.7219 2022/10/08 15:25:13 - mmengine - INFO - Epoch(train) [142][1040/2119] lr: 4.0000e-04 eta: 1:28:44 time: 0.2829 data_time: 0.0219 memory: 5821 grad_norm: 5.4017 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9239 loss: 1.9239 2022/10/08 15:25:19 - mmengine - INFO - Epoch(train) [142][1060/2119] lr: 4.0000e-04 eta: 1:28:38 time: 0.2818 data_time: 0.0155 memory: 5821 grad_norm: 5.3749 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8602 loss: 1.8602 2022/10/08 15:25:25 - mmengine - INFO - Epoch(train) [142][1080/2119] lr: 4.0000e-04 eta: 1:28:32 time: 0.3017 data_time: 0.0173 memory: 5821 grad_norm: 5.4128 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7573 loss: 1.7573 2022/10/08 15:25:31 - mmengine - INFO - Epoch(train) [142][1100/2119] lr: 4.0000e-04 eta: 1:28:26 time: 0.2990 data_time: 0.0255 memory: 5821 grad_norm: 5.3923 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9860 loss: 1.9860 2022/10/08 15:25:36 - mmengine - INFO - Epoch(train) [142][1120/2119] lr: 4.0000e-04 eta: 1:28:20 time: 0.2805 data_time: 0.0143 memory: 5821 grad_norm: 5.3403 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9892 loss: 1.9892 2022/10/08 15:25:42 - mmengine - INFO - Epoch(train) [142][1140/2119] lr: 4.0000e-04 eta: 1:28:14 time: 0.2677 data_time: 0.0193 memory: 5821 grad_norm: 5.3926 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.6315 loss: 1.6315 2022/10/08 15:25:48 - mmengine - INFO - Epoch(train) [142][1160/2119] lr: 4.0000e-04 eta: 1:28:08 time: 0.3181 data_time: 0.0197 memory: 5821 grad_norm: 5.4097 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8411 loss: 1.8411 2022/10/08 15:25:53 - mmengine - INFO - Epoch(train) [142][1180/2119] lr: 4.0000e-04 eta: 1:28:02 time: 0.2675 data_time: 0.0179 memory: 5821 grad_norm: 5.3979 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.7734 loss: 1.7734 2022/10/08 15:25:59 - mmengine - INFO - Epoch(train) [142][1200/2119] lr: 4.0000e-04 eta: 1:27:56 time: 0.2813 data_time: 0.0147 memory: 5821 grad_norm: 5.4810 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6660 loss: 1.6660 2022/10/08 15:26:05 - mmengine - INFO - Epoch(train) [142][1220/2119] lr: 4.0000e-04 eta: 1:27:50 time: 0.3197 data_time: 0.0221 memory: 5821 grad_norm: 5.3976 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0124 loss: 2.0124 2022/10/08 15:26:06 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 15:26:11 - mmengine - INFO - Epoch(train) [142][1240/2119] lr: 4.0000e-04 eta: 1:27:44 time: 0.2659 data_time: 0.0153 memory: 5821 grad_norm: 5.3974 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 1.7026 loss: 1.7026 2022/10/08 15:26:17 - mmengine - INFO - Epoch(train) [142][1260/2119] lr: 4.0000e-04 eta: 1:27:38 time: 0.2977 data_time: 0.0159 memory: 5821 grad_norm: 5.5259 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8884 loss: 1.8884 2022/10/08 15:26:22 - mmengine - INFO - Epoch(train) [142][1280/2119] lr: 4.0000e-04 eta: 1:27:32 time: 0.2848 data_time: 0.0179 memory: 5821 grad_norm: 5.3344 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7357 loss: 1.7357 2022/10/08 15:26:28 - mmengine - INFO - Epoch(train) [142][1300/2119] lr: 4.0000e-04 eta: 1:27:26 time: 0.2982 data_time: 0.0235 memory: 5821 grad_norm: 5.4259 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7628 loss: 1.7628 2022/10/08 15:26:33 - mmengine - INFO - Epoch(train) [142][1320/2119] lr: 4.0000e-04 eta: 1:27:20 time: 0.2581 data_time: 0.0176 memory: 5821 grad_norm: 5.4853 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.8191 loss: 1.8191 2022/10/08 15:26:40 - mmengine - INFO - Epoch(train) [142][1340/2119] lr: 4.0000e-04 eta: 1:27:14 time: 0.3055 data_time: 0.0189 memory: 5821 grad_norm: 5.4098 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8992 loss: 1.8992 2022/10/08 15:26:46 - mmengine - INFO - Epoch(train) [142][1360/2119] lr: 4.0000e-04 eta: 1:27:08 time: 0.3120 data_time: 0.0157 memory: 5821 grad_norm: 5.2947 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0207 loss: 2.0207 2022/10/08 15:26:52 - mmengine - INFO - Epoch(train) [142][1380/2119] lr: 4.0000e-04 eta: 1:27:02 time: 0.2881 data_time: 0.0272 memory: 5821 grad_norm: 5.4371 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8566 loss: 1.8566 2022/10/08 15:26:58 - mmengine - INFO - Epoch(train) [142][1400/2119] lr: 4.0000e-04 eta: 1:26:56 time: 0.3097 data_time: 0.0237 memory: 5821 grad_norm: 5.3203 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7042 loss: 1.7042 2022/10/08 15:27:03 - mmengine - INFO - Epoch(train) [142][1420/2119] lr: 4.0000e-04 eta: 1:26:50 time: 0.2688 data_time: 0.0171 memory: 5821 grad_norm: 5.3792 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7105 loss: 1.7105 2022/10/08 15:27:09 - mmengine - INFO - Epoch(train) [142][1440/2119] lr: 4.0000e-04 eta: 1:26:44 time: 0.2825 data_time: 0.0195 memory: 5821 grad_norm: 5.4101 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8379 loss: 1.8379 2022/10/08 15:27:14 - mmengine - INFO - Epoch(train) [142][1460/2119] lr: 4.0000e-04 eta: 1:26:38 time: 0.2742 data_time: 0.0184 memory: 5821 grad_norm: 5.4604 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7030 loss: 1.7030 2022/10/08 15:27:21 - mmengine - INFO - Epoch(train) [142][1480/2119] lr: 4.0000e-04 eta: 1:26:32 time: 0.3213 data_time: 0.0144 memory: 5821 grad_norm: 5.3937 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.7861 loss: 1.7861 2022/10/08 15:27:26 - mmengine - INFO - Epoch(train) [142][1500/2119] lr: 4.0000e-04 eta: 1:26:26 time: 0.2679 data_time: 0.0258 memory: 5821 grad_norm: 5.2778 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0737 loss: 2.0737 2022/10/08 15:27:32 - mmengine - INFO - Epoch(train) [142][1520/2119] lr: 4.0000e-04 eta: 1:26:20 time: 0.2819 data_time: 0.0173 memory: 5821 grad_norm: 5.4352 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.6644 loss: 1.6644 2022/10/08 15:27:38 - mmengine - INFO - Epoch(train) [142][1540/2119] lr: 4.0000e-04 eta: 1:26:14 time: 0.2903 data_time: 0.0191 memory: 5821 grad_norm: 5.4262 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9252 loss: 1.9252 2022/10/08 15:27:44 - mmengine - INFO - Epoch(train) [142][1560/2119] lr: 4.0000e-04 eta: 1:26:08 time: 0.2986 data_time: 0.0169 memory: 5821 grad_norm: 5.3372 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7887 loss: 1.7887 2022/10/08 15:27:49 - mmengine - INFO - Epoch(train) [142][1580/2119] lr: 4.0000e-04 eta: 1:26:02 time: 0.2740 data_time: 0.0205 memory: 5821 grad_norm: 5.4674 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.8410 loss: 1.8410 2022/10/08 15:27:55 - mmengine - INFO - Epoch(train) [142][1600/2119] lr: 4.0000e-04 eta: 1:25:56 time: 0.2849 data_time: 0.0205 memory: 5821 grad_norm: 5.3724 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.6538 loss: 1.6538 2022/10/08 15:28:01 - mmengine - INFO - Epoch(train) [142][1620/2119] lr: 4.0000e-04 eta: 1:25:50 time: 0.3044 data_time: 0.0168 memory: 5821 grad_norm: 5.4033 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7090 loss: 1.7090 2022/10/08 15:28:07 - mmengine - INFO - Epoch(train) [142][1640/2119] lr: 4.0000e-04 eta: 1:25:44 time: 0.3020 data_time: 0.0174 memory: 5821 grad_norm: 5.3745 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5957 loss: 1.5957 2022/10/08 15:28:12 - mmengine - INFO - Epoch(train) [142][1660/2119] lr: 4.0000e-04 eta: 1:25:38 time: 0.2747 data_time: 0.0180 memory: 5821 grad_norm: 5.5553 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1571 loss: 2.1571 2022/10/08 15:28:18 - mmengine - INFO - Epoch(train) [142][1680/2119] lr: 4.0000e-04 eta: 1:25:32 time: 0.2840 data_time: 0.0185 memory: 5821 grad_norm: 5.4191 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9462 loss: 1.9462 2022/10/08 15:28:24 - mmengine - INFO - Epoch(train) [142][1700/2119] lr: 4.0000e-04 eta: 1:25:26 time: 0.3051 data_time: 0.0173 memory: 5821 grad_norm: 5.3136 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0101 loss: 2.0101 2022/10/08 15:28:30 - mmengine - INFO - Epoch(train) [142][1720/2119] lr: 4.0000e-04 eta: 1:25:20 time: 0.2973 data_time: 0.0176 memory: 5821 grad_norm: 5.4333 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7302 loss: 1.7302 2022/10/08 15:28:35 - mmengine - INFO - Epoch(train) [142][1740/2119] lr: 4.0000e-04 eta: 1:25:14 time: 0.2572 data_time: 0.0173 memory: 5821 grad_norm: 5.4263 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1464 loss: 2.1464 2022/10/08 15:28:41 - mmengine - INFO - Epoch(train) [142][1760/2119] lr: 4.0000e-04 eta: 1:25:07 time: 0.2806 data_time: 0.0215 memory: 5821 grad_norm: 5.4422 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9248 loss: 1.9248 2022/10/08 15:28:47 - mmengine - INFO - Epoch(train) [142][1780/2119] lr: 4.0000e-04 eta: 1:25:02 time: 0.2916 data_time: 0.0205 memory: 5821 grad_norm: 5.3666 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8889 loss: 1.8889 2022/10/08 15:28:53 - mmengine - INFO - Epoch(train) [142][1800/2119] lr: 4.0000e-04 eta: 1:24:55 time: 0.2861 data_time: 0.0210 memory: 5821 grad_norm: 5.4664 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8595 loss: 1.8595 2022/10/08 15:28:58 - mmengine - INFO - Epoch(train) [142][1820/2119] lr: 4.0000e-04 eta: 1:24:50 time: 0.2927 data_time: 0.0192 memory: 5821 grad_norm: 5.4660 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8086 loss: 1.8086 2022/10/08 15:29:04 - mmengine - INFO - Epoch(train) [142][1840/2119] lr: 4.0000e-04 eta: 1:24:44 time: 0.2881 data_time: 0.0233 memory: 5821 grad_norm: 5.4449 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6953 loss: 1.6953 2022/10/08 15:29:10 - mmengine - INFO - Epoch(train) [142][1860/2119] lr: 4.0000e-04 eta: 1:24:38 time: 0.3003 data_time: 0.0200 memory: 5821 grad_norm: 5.3491 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.9008 loss: 1.9008 2022/10/08 15:29:16 - mmengine - INFO - Epoch(train) [142][1880/2119] lr: 4.0000e-04 eta: 1:24:31 time: 0.2731 data_time: 0.0168 memory: 5821 grad_norm: 5.4094 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 1.9902 loss: 1.9902 2022/10/08 15:29:22 - mmengine - INFO - Epoch(train) [142][1900/2119] lr: 4.0000e-04 eta: 1:24:26 time: 0.2964 data_time: 0.0240 memory: 5821 grad_norm: 5.4108 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7185 loss: 1.7185 2022/10/08 15:29:28 - mmengine - INFO - Epoch(train) [142][1920/2119] lr: 4.0000e-04 eta: 1:24:20 time: 0.3260 data_time: 0.0152 memory: 5821 grad_norm: 5.4044 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8188 loss: 1.8188 2022/10/08 15:29:33 - mmengine - INFO - Epoch(train) [142][1940/2119] lr: 4.0000e-04 eta: 1:24:13 time: 0.2481 data_time: 0.0263 memory: 5821 grad_norm: 5.4701 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7808 loss: 1.7808 2022/10/08 15:29:38 - mmengine - INFO - Epoch(train) [142][1960/2119] lr: 4.0000e-04 eta: 1:24:07 time: 0.2580 data_time: 0.0332 memory: 5821 grad_norm: 5.4590 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0288 loss: 2.0288 2022/10/08 15:29:44 - mmengine - INFO - Epoch(train) [142][1980/2119] lr: 4.0000e-04 eta: 1:24:01 time: 0.3061 data_time: 0.0205 memory: 5821 grad_norm: 5.4701 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8068 loss: 1.8068 2022/10/08 15:29:50 - mmengine - INFO - Epoch(train) [142][2000/2119] lr: 4.0000e-04 eta: 1:23:55 time: 0.2856 data_time: 0.0203 memory: 5821 grad_norm: 5.3716 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8608 loss: 1.8608 2022/10/08 15:29:56 - mmengine - INFO - Epoch(train) [142][2020/2119] lr: 4.0000e-04 eta: 1:23:49 time: 0.2870 data_time: 0.0242 memory: 5821 grad_norm: 5.4594 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7945 loss: 1.7945 2022/10/08 15:30:01 - mmengine - INFO - Epoch(train) [142][2040/2119] lr: 4.0000e-04 eta: 1:23:43 time: 0.2751 data_time: 0.0256 memory: 5821 grad_norm: 5.4202 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.7429 loss: 1.7429 2022/10/08 15:30:08 - mmengine - INFO - Epoch(train) [142][2060/2119] lr: 4.0000e-04 eta: 1:23:38 time: 0.3324 data_time: 0.0213 memory: 5821 grad_norm: 5.4527 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8441 loss: 1.8441 2022/10/08 15:30:13 - mmengine - INFO - Epoch(train) [142][2080/2119] lr: 4.0000e-04 eta: 1:23:31 time: 0.2575 data_time: 0.0269 memory: 5821 grad_norm: 5.3968 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0214 loss: 2.0214 2022/10/08 15:30:19 - mmengine - INFO - Epoch(train) [142][2100/2119] lr: 4.0000e-04 eta: 1:23:26 time: 0.3105 data_time: 0.0179 memory: 5821 grad_norm: 5.3465 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4462 loss: 1.4462 2022/10/08 15:30:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 15:30:24 - mmengine - INFO - Epoch(train) [142][2119/2119] lr: 4.0000e-04 eta: 1:23:26 time: 0.2355 data_time: 0.0174 memory: 5821 grad_norm: 5.4889 top1_acc: 0.6000 top5_acc: 0.8000 loss_cls: 1.7590 loss: 1.7590 2022/10/08 15:30:32 - mmengine - INFO - Epoch(train) [143][20/2119] lr: 4.0000e-04 eta: 1:23:11 time: 0.4060 data_time: 0.1088 memory: 5821 grad_norm: 5.3552 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9068 loss: 1.9068 2022/10/08 15:30:38 - mmengine - INFO - Epoch(train) [143][40/2119] lr: 4.0000e-04 eta: 1:23:05 time: 0.2920 data_time: 0.0189 memory: 5821 grad_norm: 5.3870 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8382 loss: 1.8382 2022/10/08 15:30:44 - mmengine - INFO - Epoch(train) [143][60/2119] lr: 4.0000e-04 eta: 1:22:59 time: 0.2955 data_time: 0.0190 memory: 5821 grad_norm: 5.4316 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8597 loss: 1.8597 2022/10/08 15:30:49 - mmengine - INFO - Epoch(train) [143][80/2119] lr: 4.0000e-04 eta: 1:22:53 time: 0.2745 data_time: 0.0204 memory: 5821 grad_norm: 5.4626 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8368 loss: 1.8368 2022/10/08 15:30:56 - mmengine - INFO - Epoch(train) [143][100/2119] lr: 4.0000e-04 eta: 1:22:48 time: 0.3069 data_time: 0.0165 memory: 5821 grad_norm: 5.3445 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.6486 loss: 1.6486 2022/10/08 15:30:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 15:31:01 - mmengine - INFO - Epoch(train) [143][120/2119] lr: 4.0000e-04 eta: 1:22:41 time: 0.2590 data_time: 0.0181 memory: 5821 grad_norm: 5.3110 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9138 loss: 1.9138 2022/10/08 15:31:06 - mmengine - INFO - Epoch(train) [143][140/2119] lr: 4.0000e-04 eta: 1:22:35 time: 0.2697 data_time: 0.0265 memory: 5821 grad_norm: 5.4200 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8258 loss: 1.8258 2022/10/08 15:31:12 - mmengine - INFO - Epoch(train) [143][160/2119] lr: 4.0000e-04 eta: 1:22:29 time: 0.2955 data_time: 0.0162 memory: 5821 grad_norm: 5.3480 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8293 loss: 1.8293 2022/10/08 15:31:19 - mmengine - INFO - Epoch(train) [143][180/2119] lr: 4.0000e-04 eta: 1:22:24 time: 0.3253 data_time: 0.0215 memory: 5821 grad_norm: 5.3716 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.8120 loss: 1.8120 2022/10/08 15:31:24 - mmengine - INFO - Epoch(train) [143][200/2119] lr: 4.0000e-04 eta: 1:22:17 time: 0.2687 data_time: 0.0162 memory: 5821 grad_norm: 5.4141 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9522 loss: 1.9522 2022/10/08 15:31:31 - mmengine - INFO - Epoch(train) [143][220/2119] lr: 4.0000e-04 eta: 1:22:12 time: 0.3331 data_time: 0.0253 memory: 5821 grad_norm: 5.3543 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7168 loss: 1.7168 2022/10/08 15:31:36 - mmengine - INFO - Epoch(train) [143][240/2119] lr: 4.0000e-04 eta: 1:22:05 time: 0.2515 data_time: 0.0196 memory: 5821 grad_norm: 5.4307 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9310 loss: 1.9310 2022/10/08 15:31:42 - mmengine - INFO - Epoch(train) [143][260/2119] lr: 4.0000e-04 eta: 1:22:00 time: 0.3021 data_time: 0.0235 memory: 5821 grad_norm: 5.4028 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8046 loss: 1.8046 2022/10/08 15:31:47 - mmengine - INFO - Epoch(train) [143][280/2119] lr: 4.0000e-04 eta: 1:21:53 time: 0.2797 data_time: 0.0196 memory: 5821 grad_norm: 5.3352 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7668 loss: 1.7668 2022/10/08 15:31:53 - mmengine - INFO - Epoch(train) [143][300/2119] lr: 4.0000e-04 eta: 1:21:47 time: 0.2652 data_time: 0.0269 memory: 5821 grad_norm: 5.4184 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8722 loss: 1.8722 2022/10/08 15:31:59 - mmengine - INFO - Epoch(train) [143][320/2119] lr: 4.0000e-04 eta: 1:21:42 time: 0.3212 data_time: 0.0134 memory: 5821 grad_norm: 5.4180 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.9706 loss: 1.9706 2022/10/08 15:32:05 - mmengine - INFO - Epoch(train) [143][340/2119] lr: 4.0000e-04 eta: 1:21:36 time: 0.2866 data_time: 0.0222 memory: 5821 grad_norm: 5.5460 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8959 loss: 1.8959 2022/10/08 15:32:11 - mmengine - INFO - Epoch(train) [143][360/2119] lr: 4.0000e-04 eta: 1:21:30 time: 0.2969 data_time: 0.0239 memory: 5821 grad_norm: 5.2961 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0078 loss: 2.0078 2022/10/08 15:32:17 - mmengine - INFO - Epoch(train) [143][380/2119] lr: 4.0000e-04 eta: 1:21:24 time: 0.2937 data_time: 0.0216 memory: 5821 grad_norm: 5.4320 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.5722 loss: 1.5722 2022/10/08 15:32:22 - mmengine - INFO - Epoch(train) [143][400/2119] lr: 4.0000e-04 eta: 1:21:17 time: 0.2677 data_time: 0.0215 memory: 5821 grad_norm: 5.4337 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8629 loss: 1.8629 2022/10/08 15:32:28 - mmengine - INFO - Epoch(train) [143][420/2119] lr: 4.0000e-04 eta: 1:21:12 time: 0.3118 data_time: 0.0211 memory: 5821 grad_norm: 5.4239 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.6787 loss: 1.6787 2022/10/08 15:32:33 - mmengine - INFO - Epoch(train) [143][440/2119] lr: 4.0000e-04 eta: 1:21:05 time: 0.2560 data_time: 0.0246 memory: 5821 grad_norm: 5.5454 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.6766 loss: 1.6766 2022/10/08 15:32:40 - mmengine - INFO - Epoch(train) [143][460/2119] lr: 4.0000e-04 eta: 1:21:00 time: 0.3196 data_time: 0.0207 memory: 5821 grad_norm: 5.4349 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9835 loss: 1.9835 2022/10/08 15:32:46 - mmengine - INFO - Epoch(train) [143][480/2119] lr: 4.0000e-04 eta: 1:20:54 time: 0.2901 data_time: 0.0183 memory: 5821 grad_norm: 5.3907 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8220 loss: 1.8220 2022/10/08 15:32:51 - mmengine - INFO - Epoch(train) [143][500/2119] lr: 4.0000e-04 eta: 1:20:48 time: 0.2777 data_time: 0.0174 memory: 5821 grad_norm: 5.4745 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6114 loss: 1.6114 2022/10/08 15:32:57 - mmengine - INFO - Epoch(train) [143][520/2119] lr: 4.0000e-04 eta: 1:20:42 time: 0.2776 data_time: 0.0129 memory: 5821 grad_norm: 5.4662 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.8046 loss: 1.8046 2022/10/08 15:33:02 - mmengine - INFO - Epoch(train) [143][540/2119] lr: 4.0000e-04 eta: 1:20:36 time: 0.2828 data_time: 0.0160 memory: 5821 grad_norm: 5.4138 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7560 loss: 1.7560 2022/10/08 15:33:09 - mmengine - INFO - Epoch(train) [143][560/2119] lr: 4.0000e-04 eta: 1:20:30 time: 0.3177 data_time: 0.0207 memory: 5821 grad_norm: 5.5109 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0576 loss: 2.0576 2022/10/08 15:33:14 - mmengine - INFO - Epoch(train) [143][580/2119] lr: 4.0000e-04 eta: 1:20:24 time: 0.2674 data_time: 0.0226 memory: 5821 grad_norm: 5.4460 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9933 loss: 1.9933 2022/10/08 15:33:20 - mmengine - INFO - Epoch(train) [143][600/2119] lr: 4.0000e-04 eta: 1:20:17 time: 0.2758 data_time: 0.0180 memory: 5821 grad_norm: 5.4220 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.6155 loss: 1.6155 2022/10/08 15:33:26 - mmengine - INFO - Epoch(train) [143][620/2119] lr: 4.0000e-04 eta: 1:20:12 time: 0.2899 data_time: 0.0200 memory: 5821 grad_norm: 5.4821 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9364 loss: 1.9364 2022/10/08 15:33:37 - mmengine - INFO - Epoch(train) [143][640/2119] lr: 4.0000e-04 eta: 1:20:10 time: 0.5809 data_time: 0.3031 memory: 5821 grad_norm: 5.4326 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6430 loss: 1.6430 2022/10/08 15:33:42 - mmengine - INFO - Epoch(train) [143][660/2119] lr: 4.0000e-04 eta: 1:20:03 time: 0.2581 data_time: 0.0216 memory: 5821 grad_norm: 5.4083 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9260 loss: 1.9260 2022/10/08 15:33:49 - mmengine - INFO - Epoch(train) [143][680/2119] lr: 4.0000e-04 eta: 1:19:58 time: 0.3241 data_time: 0.0251 memory: 5821 grad_norm: 5.4268 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7255 loss: 1.7255 2022/10/08 15:33:54 - mmengine - INFO - Epoch(train) [143][700/2119] lr: 4.0000e-04 eta: 1:19:51 time: 0.2511 data_time: 0.0177 memory: 5821 grad_norm: 5.4048 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7257 loss: 1.7257 2022/10/08 15:34:00 - mmengine - INFO - Epoch(train) [143][720/2119] lr: 4.0000e-04 eta: 1:19:46 time: 0.2925 data_time: 0.0226 memory: 5821 grad_norm: 5.4082 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.7990 loss: 1.7990 2022/10/08 15:34:06 - mmengine - INFO - Epoch(train) [143][740/2119] lr: 4.0000e-04 eta: 1:19:40 time: 0.2938 data_time: 0.0162 memory: 5821 grad_norm: 5.3934 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8911 loss: 1.8911 2022/10/08 15:34:12 - mmengine - INFO - Epoch(train) [143][760/2119] lr: 4.0000e-04 eta: 1:19:34 time: 0.3035 data_time: 0.0143 memory: 5821 grad_norm: 5.4206 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7990 loss: 1.7990 2022/10/08 15:34:17 - mmengine - INFO - Epoch(train) [143][780/2119] lr: 4.0000e-04 eta: 1:19:28 time: 0.2688 data_time: 0.0261 memory: 5821 grad_norm: 5.2761 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.8809 loss: 1.8809 2022/10/08 15:34:23 - mmengine - INFO - Epoch(train) [143][800/2119] lr: 4.0000e-04 eta: 1:19:22 time: 0.2961 data_time: 0.0215 memory: 5821 grad_norm: 5.3862 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8525 loss: 1.8525 2022/10/08 15:34:29 - mmengine - INFO - Epoch(train) [143][820/2119] lr: 4.0000e-04 eta: 1:19:16 time: 0.2969 data_time: 0.0194 memory: 5821 grad_norm: 5.4238 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9840 loss: 1.9840 2022/10/08 15:34:34 - mmengine - INFO - Epoch(train) [143][840/2119] lr: 4.0000e-04 eta: 1:19:09 time: 0.2612 data_time: 0.0184 memory: 5821 grad_norm: 5.3966 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8008 loss: 1.8008 2022/10/08 15:34:40 - mmengine - INFO - Epoch(train) [143][860/2119] lr: 4.0000e-04 eta: 1:19:03 time: 0.2804 data_time: 0.0195 memory: 5821 grad_norm: 5.4324 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8673 loss: 1.8673 2022/10/08 15:34:46 - mmengine - INFO - Epoch(train) [143][880/2119] lr: 4.0000e-04 eta: 1:18:57 time: 0.2942 data_time: 0.0268 memory: 5821 grad_norm: 5.3978 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.8524 loss: 1.8524 2022/10/08 15:34:52 - mmengine - INFO - Epoch(train) [143][900/2119] lr: 4.0000e-04 eta: 1:18:52 time: 0.2964 data_time: 0.0196 memory: 5821 grad_norm: 5.5524 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9006 loss: 1.9006 2022/10/08 15:34:57 - mmengine - INFO - Epoch(train) [143][920/2119] lr: 4.0000e-04 eta: 1:18:46 time: 0.2915 data_time: 0.0239 memory: 5821 grad_norm: 5.4755 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7106 loss: 1.7106 2022/10/08 15:35:03 - mmengine - INFO - Epoch(train) [143][940/2119] lr: 4.0000e-04 eta: 1:18:40 time: 0.2862 data_time: 0.0169 memory: 5821 grad_norm: 5.5265 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8529 loss: 1.8529 2022/10/08 15:35:09 - mmengine - INFO - Epoch(train) [143][960/2119] lr: 4.0000e-04 eta: 1:18:34 time: 0.3015 data_time: 0.0147 memory: 5821 grad_norm: 5.4410 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8168 loss: 1.8168 2022/10/08 15:35:14 - mmengine - INFO - Epoch(train) [143][980/2119] lr: 4.0000e-04 eta: 1:18:27 time: 0.2543 data_time: 0.0244 memory: 5821 grad_norm: 5.4426 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.7531 loss: 1.7531 2022/10/08 15:35:20 - mmengine - INFO - Epoch(train) [143][1000/2119] lr: 4.0000e-04 eta: 1:18:21 time: 0.2935 data_time: 0.0291 memory: 5821 grad_norm: 5.4255 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8160 loss: 1.8160 2022/10/08 15:35:26 - mmengine - INFO - Epoch(train) [143][1020/2119] lr: 4.0000e-04 eta: 1:18:15 time: 0.2715 data_time: 0.0210 memory: 5821 grad_norm: 5.3908 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9573 loss: 1.9573 2022/10/08 15:35:31 - mmengine - INFO - Epoch(train) [143][1040/2119] lr: 4.0000e-04 eta: 1:18:09 time: 0.2782 data_time: 0.0182 memory: 5821 grad_norm: 5.3868 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8867 loss: 1.8867 2022/10/08 15:35:38 - mmengine - INFO - Epoch(train) [143][1060/2119] lr: 4.0000e-04 eta: 1:18:03 time: 0.3178 data_time: 0.0176 memory: 5821 grad_norm: 5.4898 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.8243 loss: 1.8243 2022/10/08 15:35:43 - mmengine - INFO - Epoch(train) [143][1080/2119] lr: 4.0000e-04 eta: 1:17:57 time: 0.2647 data_time: 0.0178 memory: 5821 grad_norm: 5.3873 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5345 loss: 1.5345 2022/10/08 15:35:50 - mmengine - INFO - Epoch(train) [143][1100/2119] lr: 4.0000e-04 eta: 1:17:52 time: 0.3306 data_time: 0.0231 memory: 5821 grad_norm: 5.4548 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7586 loss: 1.7586 2022/10/08 15:35:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 15:35:55 - mmengine - INFO - Epoch(train) [143][1120/2119] lr: 4.0000e-04 eta: 1:17:45 time: 0.2529 data_time: 0.0173 memory: 5821 grad_norm: 5.4172 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8390 loss: 1.8390 2022/10/08 15:36:00 - mmengine - INFO - Epoch(train) [143][1140/2119] lr: 4.0000e-04 eta: 1:17:39 time: 0.2855 data_time: 0.0192 memory: 5821 grad_norm: 5.4077 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.5947 loss: 1.5947 2022/10/08 15:36:06 - mmengine - INFO - Epoch(train) [143][1160/2119] lr: 4.0000e-04 eta: 1:17:33 time: 0.2862 data_time: 0.0182 memory: 5821 grad_norm: 5.4721 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8917 loss: 1.8917 2022/10/08 15:36:11 - mmengine - INFO - Epoch(train) [143][1180/2119] lr: 4.0000e-04 eta: 1:17:27 time: 0.2722 data_time: 0.0185 memory: 5821 grad_norm: 5.4207 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9344 loss: 1.9344 2022/10/08 15:36:18 - mmengine - INFO - Epoch(train) [143][1200/2119] lr: 4.0000e-04 eta: 1:17:21 time: 0.3129 data_time: 0.0191 memory: 5821 grad_norm: 5.3661 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8494 loss: 1.8494 2022/10/08 15:36:24 - mmengine - INFO - Epoch(train) [143][1220/2119] lr: 4.0000e-04 eta: 1:17:16 time: 0.3060 data_time: 0.0191 memory: 5821 grad_norm: 5.4364 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7943 loss: 1.7943 2022/10/08 15:36:30 - mmengine - INFO - Epoch(train) [143][1240/2119] lr: 4.0000e-04 eta: 1:17:10 time: 0.3096 data_time: 0.0198 memory: 5821 grad_norm: 5.4238 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.7944 loss: 1.7944 2022/10/08 15:36:36 - mmengine - INFO - Epoch(train) [143][1260/2119] lr: 4.0000e-04 eta: 1:17:04 time: 0.2777 data_time: 0.0179 memory: 5821 grad_norm: 5.5404 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6905 loss: 1.6905 2022/10/08 15:36:42 - mmengine - INFO - Epoch(train) [143][1280/2119] lr: 4.0000e-04 eta: 1:16:58 time: 0.3283 data_time: 0.0155 memory: 5821 grad_norm: 5.5178 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6572 loss: 1.6572 2022/10/08 15:36:48 - mmengine - INFO - Epoch(train) [143][1300/2119] lr: 4.0000e-04 eta: 1:16:52 time: 0.2691 data_time: 0.0195 memory: 5821 grad_norm: 5.4148 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8243 loss: 1.8243 2022/10/08 15:36:53 - mmengine - INFO - Epoch(train) [143][1320/2119] lr: 4.0000e-04 eta: 1:16:46 time: 0.2864 data_time: 0.0253 memory: 5821 grad_norm: 5.4134 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9001 loss: 1.9001 2022/10/08 15:36:59 - mmengine - INFO - Epoch(train) [143][1340/2119] lr: 4.0000e-04 eta: 1:16:40 time: 0.2739 data_time: 0.0172 memory: 5821 grad_norm: 5.4493 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7295 loss: 1.7295 2022/10/08 15:37:05 - mmengine - INFO - Epoch(train) [143][1360/2119] lr: 4.0000e-04 eta: 1:16:34 time: 0.2921 data_time: 0.0240 memory: 5821 grad_norm: 5.3848 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8328 loss: 1.8328 2022/10/08 15:37:10 - mmengine - INFO - Epoch(train) [143][1380/2119] lr: 4.0000e-04 eta: 1:16:28 time: 0.2838 data_time: 0.0188 memory: 5821 grad_norm: 5.4305 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.6184 loss: 1.6184 2022/10/08 15:37:17 - mmengine - INFO - Epoch(train) [143][1400/2119] lr: 4.0000e-04 eta: 1:16:23 time: 0.3521 data_time: 0.0218 memory: 5821 grad_norm: 5.4911 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7741 loss: 1.7741 2022/10/08 15:37:23 - mmengine - INFO - Epoch(train) [143][1420/2119] lr: 4.0000e-04 eta: 1:16:17 time: 0.3002 data_time: 0.0239 memory: 5821 grad_norm: 5.4171 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9350 loss: 1.9350 2022/10/08 15:37:29 - mmengine - INFO - Epoch(train) [143][1440/2119] lr: 4.0000e-04 eta: 1:16:11 time: 0.2852 data_time: 0.0207 memory: 5821 grad_norm: 5.4523 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6045 loss: 1.6045 2022/10/08 15:37:35 - mmengine - INFO - Epoch(train) [143][1460/2119] lr: 4.0000e-04 eta: 1:16:05 time: 0.3002 data_time: 0.0229 memory: 5821 grad_norm: 5.6074 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8627 loss: 1.8627 2022/10/08 15:37:41 - mmengine - INFO - Epoch(train) [143][1480/2119] lr: 4.0000e-04 eta: 1:15:59 time: 0.2705 data_time: 0.0214 memory: 5821 grad_norm: 5.4347 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6075 loss: 1.6075 2022/10/08 15:37:46 - mmengine - INFO - Epoch(train) [143][1500/2119] lr: 4.0000e-04 eta: 1:15:53 time: 0.2931 data_time: 0.0191 memory: 5821 grad_norm: 5.4028 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9992 loss: 1.9992 2022/10/08 15:37:53 - mmengine - INFO - Epoch(train) [143][1520/2119] lr: 4.0000e-04 eta: 1:15:47 time: 0.3051 data_time: 0.0186 memory: 5821 grad_norm: 5.4574 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9042 loss: 1.9042 2022/10/08 15:37:59 - mmengine - INFO - Epoch(train) [143][1540/2119] lr: 4.0000e-04 eta: 1:15:42 time: 0.3020 data_time: 0.0203 memory: 5821 grad_norm: 5.4360 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7919 loss: 1.7919 2022/10/08 15:38:05 - mmengine - INFO - Epoch(train) [143][1560/2119] lr: 4.0000e-04 eta: 1:15:36 time: 0.2974 data_time: 0.0170 memory: 5821 grad_norm: 5.5235 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7486 loss: 1.7486 2022/10/08 15:38:11 - mmengine - INFO - Epoch(train) [143][1580/2119] lr: 4.0000e-04 eta: 1:15:30 time: 0.2993 data_time: 0.0224 memory: 5821 grad_norm: 5.4403 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7320 loss: 1.7320 2022/10/08 15:38:16 - mmengine - INFO - Epoch(train) [143][1600/2119] lr: 4.0000e-04 eta: 1:15:24 time: 0.2718 data_time: 0.0147 memory: 5821 grad_norm: 5.3981 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 1.8514 loss: 1.8514 2022/10/08 15:38:21 - mmengine - INFO - Epoch(train) [143][1620/2119] lr: 4.0000e-04 eta: 1:15:17 time: 0.2683 data_time: 0.0238 memory: 5821 grad_norm: 5.5085 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0140 loss: 2.0140 2022/10/08 15:38:27 - mmengine - INFO - Epoch(train) [143][1640/2119] lr: 4.0000e-04 eta: 1:15:11 time: 0.2918 data_time: 0.0161 memory: 5821 grad_norm: 5.4795 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9252 loss: 1.9252 2022/10/08 15:38:33 - mmengine - INFO - Epoch(train) [143][1660/2119] lr: 4.0000e-04 eta: 1:15:05 time: 0.2859 data_time: 0.0190 memory: 5821 grad_norm: 5.4717 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8261 loss: 1.8261 2022/10/08 15:38:39 - mmengine - INFO - Epoch(train) [143][1680/2119] lr: 4.0000e-04 eta: 1:15:00 time: 0.3218 data_time: 0.0222 memory: 5821 grad_norm: 5.5139 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.7016 loss: 1.7016 2022/10/08 15:38:45 - mmengine - INFO - Epoch(train) [143][1700/2119] lr: 4.0000e-04 eta: 1:14:54 time: 0.2713 data_time: 0.0215 memory: 5821 grad_norm: 5.4421 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6954 loss: 1.6954 2022/10/08 15:38:51 - mmengine - INFO - Epoch(train) [143][1720/2119] lr: 4.0000e-04 eta: 1:14:48 time: 0.2848 data_time: 0.0211 memory: 5821 grad_norm: 5.4646 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7173 loss: 1.7173 2022/10/08 15:38:56 - mmengine - INFO - Epoch(train) [143][1740/2119] lr: 4.0000e-04 eta: 1:14:41 time: 0.2695 data_time: 0.0180 memory: 5821 grad_norm: 5.3854 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.5557 loss: 1.5557 2022/10/08 15:39:03 - mmengine - INFO - Epoch(train) [143][1760/2119] lr: 4.0000e-04 eta: 1:14:36 time: 0.3321 data_time: 0.0196 memory: 5821 grad_norm: 5.5135 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9167 loss: 1.9167 2022/10/08 15:39:08 - mmengine - INFO - Epoch(train) [143][1780/2119] lr: 4.0000e-04 eta: 1:14:30 time: 0.2580 data_time: 0.0199 memory: 5821 grad_norm: 5.4861 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8784 loss: 1.8784 2022/10/08 15:39:14 - mmengine - INFO - Epoch(train) [143][1800/2119] lr: 4.0000e-04 eta: 1:14:24 time: 0.3227 data_time: 0.0180 memory: 5821 grad_norm: 5.5486 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9804 loss: 1.9804 2022/10/08 15:39:20 - mmengine - INFO - Epoch(train) [143][1820/2119] lr: 4.0000e-04 eta: 1:14:18 time: 0.2798 data_time: 0.0176 memory: 5821 grad_norm: 5.4169 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.6678 loss: 1.6678 2022/10/08 15:39:25 - mmengine - INFO - Epoch(train) [143][1840/2119] lr: 4.0000e-04 eta: 1:14:12 time: 0.2605 data_time: 0.0198 memory: 5821 grad_norm: 5.4265 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8724 loss: 1.8724 2022/10/08 15:39:31 - mmengine - INFO - Epoch(train) [143][1860/2119] lr: 4.0000e-04 eta: 1:14:06 time: 0.2817 data_time: 0.0245 memory: 5821 grad_norm: 5.4277 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5069 loss: 1.5069 2022/10/08 15:39:37 - mmengine - INFO - Epoch(train) [143][1880/2119] lr: 4.0000e-04 eta: 1:14:00 time: 0.3019 data_time: 0.0198 memory: 5821 grad_norm: 5.5459 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8640 loss: 1.8640 2022/10/08 15:39:43 - mmengine - INFO - Epoch(train) [143][1900/2119] lr: 4.0000e-04 eta: 1:13:54 time: 0.3013 data_time: 0.0189 memory: 5821 grad_norm: 5.4343 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4982 loss: 1.4982 2022/10/08 15:39:49 - mmengine - INFO - Epoch(train) [143][1920/2119] lr: 4.0000e-04 eta: 1:13:48 time: 0.2907 data_time: 0.0182 memory: 5821 grad_norm: 5.3626 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.9294 loss: 1.9294 2022/10/08 15:39:54 - mmengine - INFO - Epoch(train) [143][1940/2119] lr: 4.0000e-04 eta: 1:13:42 time: 0.2689 data_time: 0.0184 memory: 5821 grad_norm: 5.4327 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7313 loss: 1.7313 2022/10/08 15:40:00 - mmengine - INFO - Epoch(train) [143][1960/2119] lr: 4.0000e-04 eta: 1:13:36 time: 0.3052 data_time: 0.0172 memory: 5821 grad_norm: 5.4654 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9325 loss: 1.9325 2022/10/08 15:40:06 - mmengine - INFO - Epoch(train) [143][1980/2119] lr: 4.0000e-04 eta: 1:13:30 time: 0.2868 data_time: 0.0253 memory: 5821 grad_norm: 5.5571 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7597 loss: 1.7597 2022/10/08 15:40:12 - mmengine - INFO - Epoch(train) [143][2000/2119] lr: 4.0000e-04 eta: 1:13:24 time: 0.2921 data_time: 0.0169 memory: 5821 grad_norm: 5.4678 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9477 loss: 1.9477 2022/10/08 15:40:18 - mmengine - INFO - Epoch(train) [143][2020/2119] lr: 4.0000e-04 eta: 1:13:18 time: 0.2887 data_time: 0.0178 memory: 5821 grad_norm: 5.4550 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 1.9120 loss: 1.9120 2022/10/08 15:40:23 - mmengine - INFO - Epoch(train) [143][2040/2119] lr: 4.0000e-04 eta: 1:13:12 time: 0.2961 data_time: 0.0187 memory: 5821 grad_norm: 5.5998 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8102 loss: 1.8102 2022/10/08 15:40:29 - mmengine - INFO - Epoch(train) [143][2060/2119] lr: 4.0000e-04 eta: 1:13:06 time: 0.2751 data_time: 0.0221 memory: 5821 grad_norm: 5.5526 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9767 loss: 1.9767 2022/10/08 15:40:35 - mmengine - INFO - Epoch(train) [143][2080/2119] lr: 4.0000e-04 eta: 1:13:00 time: 0.2951 data_time: 0.0159 memory: 5821 grad_norm: 5.4454 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 1.7192 loss: 1.7192 2022/10/08 15:40:41 - mmengine - INFO - Epoch(train) [143][2100/2119] lr: 4.0000e-04 eta: 1:12:54 time: 0.2858 data_time: 0.0305 memory: 5821 grad_norm: 5.5158 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8060 loss: 1.8060 2022/10/08 15:40:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 15:40:45 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 15:40:45 - mmengine - INFO - Epoch(train) [143][2119/2119] lr: 4.0000e-04 eta: 1:12:54 time: 0.2409 data_time: 0.0142 memory: 5821 grad_norm: 5.4880 top1_acc: 0.9000 top5_acc: 1.0000 loss_cls: 1.8594 loss: 1.8594 2022/10/08 15:40:54 - mmengine - INFO - Epoch(train) [144][20/2119] lr: 4.0000e-04 eta: 1:12:41 time: 0.4309 data_time: 0.1380 memory: 5821 grad_norm: 5.3248 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.7614 loss: 1.7614 2022/10/08 15:41:00 - mmengine - INFO - Epoch(train) [144][40/2119] lr: 4.0000e-04 eta: 1:12:35 time: 0.2938 data_time: 0.0148 memory: 5821 grad_norm: 5.4595 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9736 loss: 1.9736 2022/10/08 15:41:06 - mmengine - INFO - Epoch(train) [144][60/2119] lr: 4.0000e-04 eta: 1:12:29 time: 0.2897 data_time: 0.0208 memory: 5821 grad_norm: 5.5294 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.5030 loss: 1.5030 2022/10/08 15:41:11 - mmengine - INFO - Epoch(train) [144][80/2119] lr: 4.0000e-04 eta: 1:12:23 time: 0.2797 data_time: 0.0183 memory: 5821 grad_norm: 5.4416 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8233 loss: 1.8233 2022/10/08 15:41:17 - mmengine - INFO - Epoch(train) [144][100/2119] lr: 4.0000e-04 eta: 1:12:17 time: 0.2878 data_time: 0.0163 memory: 5821 grad_norm: 5.3615 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8192 loss: 1.8192 2022/10/08 15:41:22 - mmengine - INFO - Epoch(train) [144][120/2119] lr: 4.0000e-04 eta: 1:12:11 time: 0.2742 data_time: 0.0191 memory: 5821 grad_norm: 5.5256 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9438 loss: 1.9438 2022/10/08 15:41:29 - mmengine - INFO - Epoch(train) [144][140/2119] lr: 4.0000e-04 eta: 1:12:05 time: 0.3209 data_time: 0.0169 memory: 5821 grad_norm: 5.4065 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7404 loss: 1.7404 2022/10/08 15:41:35 - mmengine - INFO - Epoch(train) [144][160/2119] lr: 4.0000e-04 eta: 1:11:59 time: 0.2818 data_time: 0.0206 memory: 5821 grad_norm: 5.3846 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7388 loss: 1.7388 2022/10/08 15:41:40 - mmengine - INFO - Epoch(train) [144][180/2119] lr: 4.0000e-04 eta: 1:11:54 time: 0.2930 data_time: 0.0198 memory: 5821 grad_norm: 5.4303 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8030 loss: 1.8030 2022/10/08 15:41:46 - mmengine - INFO - Epoch(train) [144][200/2119] lr: 4.0000e-04 eta: 1:11:47 time: 0.2681 data_time: 0.0160 memory: 5821 grad_norm: 5.5121 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8132 loss: 1.8132 2022/10/08 15:41:52 - mmengine - INFO - Epoch(train) [144][220/2119] lr: 4.0000e-04 eta: 1:11:41 time: 0.2984 data_time: 0.0237 memory: 5821 grad_norm: 5.5901 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8113 loss: 1.8113 2022/10/08 15:41:58 - mmengine - INFO - Epoch(train) [144][240/2119] lr: 4.0000e-04 eta: 1:11:36 time: 0.3087 data_time: 0.0237 memory: 5821 grad_norm: 5.5535 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.8791 loss: 1.8791 2022/10/08 15:42:04 - mmengine - INFO - Epoch(train) [144][260/2119] lr: 4.0000e-04 eta: 1:11:30 time: 0.2803 data_time: 0.0156 memory: 5821 grad_norm: 5.4357 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7139 loss: 1.7139 2022/10/08 15:42:11 - mmengine - INFO - Epoch(train) [144][280/2119] lr: 4.0000e-04 eta: 1:11:25 time: 0.3877 data_time: 0.0940 memory: 5821 grad_norm: 5.3832 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8328 loss: 1.8328 2022/10/08 15:42:16 - mmengine - INFO - Epoch(train) [144][300/2119] lr: 4.0000e-04 eta: 1:11:18 time: 0.2473 data_time: 0.0174 memory: 5821 grad_norm: 5.4391 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7794 loss: 1.7794 2022/10/08 15:42:22 - mmengine - INFO - Epoch(train) [144][320/2119] lr: 4.0000e-04 eta: 1:11:12 time: 0.2682 data_time: 0.0286 memory: 5821 grad_norm: 5.4880 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7645 loss: 1.7645 2022/10/08 15:42:27 - mmengine - INFO - Epoch(train) [144][340/2119] lr: 4.0000e-04 eta: 1:11:06 time: 0.2834 data_time: 0.0200 memory: 5821 grad_norm: 5.4063 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9052 loss: 1.9052 2022/10/08 15:42:33 - mmengine - INFO - Epoch(train) [144][360/2119] lr: 4.0000e-04 eta: 1:11:00 time: 0.3023 data_time: 0.0219 memory: 5821 grad_norm: 5.5136 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.6433 loss: 1.6433 2022/10/08 15:42:39 - mmengine - INFO - Epoch(train) [144][380/2119] lr: 4.0000e-04 eta: 1:10:55 time: 0.2911 data_time: 0.0244 memory: 5821 grad_norm: 5.4894 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7577 loss: 1.7577 2022/10/08 15:42:45 - mmengine - INFO - Epoch(train) [144][400/2119] lr: 4.0000e-04 eta: 1:10:48 time: 0.2718 data_time: 0.0185 memory: 5821 grad_norm: 5.4475 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8531 loss: 1.8531 2022/10/08 15:42:51 - mmengine - INFO - Epoch(train) [144][420/2119] lr: 4.0000e-04 eta: 1:10:43 time: 0.3106 data_time: 0.0163 memory: 5821 grad_norm: 5.4182 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.8721 loss: 1.8721 2022/10/08 15:42:57 - mmengine - INFO - Epoch(train) [144][440/2119] lr: 4.0000e-04 eta: 1:10:37 time: 0.2996 data_time: 0.0193 memory: 5821 grad_norm: 5.4353 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.6494 loss: 1.6494 2022/10/08 15:43:03 - mmengine - INFO - Epoch(train) [144][460/2119] lr: 4.0000e-04 eta: 1:10:31 time: 0.2854 data_time: 0.0179 memory: 5821 grad_norm: 5.3553 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6110 loss: 1.6110 2022/10/08 15:43:08 - mmengine - INFO - Epoch(train) [144][480/2119] lr: 4.0000e-04 eta: 1:10:25 time: 0.2802 data_time: 0.0166 memory: 5821 grad_norm: 5.5111 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5333 loss: 1.5333 2022/10/08 15:43:14 - mmengine - INFO - Epoch(train) [144][500/2119] lr: 4.0000e-04 eta: 1:10:19 time: 0.2895 data_time: 0.0225 memory: 5821 grad_norm: 5.4883 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9701 loss: 1.9701 2022/10/08 15:43:20 - mmengine - INFO - Epoch(train) [144][520/2119] lr: 4.0000e-04 eta: 1:10:13 time: 0.2850 data_time: 0.0185 memory: 5821 grad_norm: 5.5997 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.8366 loss: 1.8366 2022/10/08 15:43:26 - mmengine - INFO - Epoch(train) [144][540/2119] lr: 4.0000e-04 eta: 1:10:07 time: 0.2900 data_time: 0.0201 memory: 5821 grad_norm: 5.5361 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4829 loss: 1.4829 2022/10/08 15:43:32 - mmengine - INFO - Epoch(train) [144][560/2119] lr: 4.0000e-04 eta: 1:10:01 time: 0.3012 data_time: 0.0174 memory: 5821 grad_norm: 5.4152 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9494 loss: 1.9494 2022/10/08 15:43:37 - mmengine - INFO - Epoch(train) [144][580/2119] lr: 4.0000e-04 eta: 1:09:55 time: 0.2845 data_time: 0.0208 memory: 5821 grad_norm: 5.5524 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.7514 loss: 1.7514 2022/10/08 15:43:43 - mmengine - INFO - Epoch(train) [144][600/2119] lr: 4.0000e-04 eta: 1:09:49 time: 0.2881 data_time: 0.0163 memory: 5821 grad_norm: 5.5362 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.8211 loss: 1.8211 2022/10/08 15:43:50 - mmengine - INFO - Epoch(train) [144][620/2119] lr: 4.0000e-04 eta: 1:09:44 time: 0.3253 data_time: 0.0234 memory: 5821 grad_norm: 5.5212 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.7918 loss: 1.7918 2022/10/08 15:43:55 - mmengine - INFO - Epoch(train) [144][640/2119] lr: 4.0000e-04 eta: 1:09:37 time: 0.2527 data_time: 0.0172 memory: 5821 grad_norm: 5.6213 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.6861 loss: 1.6861 2022/10/08 15:44:00 - mmengine - INFO - Epoch(train) [144][660/2119] lr: 4.0000e-04 eta: 1:09:31 time: 0.2648 data_time: 0.0236 memory: 5821 grad_norm: 5.6117 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9438 loss: 1.9438 2022/10/08 15:44:06 - mmengine - INFO - Epoch(train) [144][680/2119] lr: 4.0000e-04 eta: 1:09:25 time: 0.3102 data_time: 0.0206 memory: 5821 grad_norm: 5.4319 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8512 loss: 1.8512 2022/10/08 15:44:12 - mmengine - INFO - Epoch(train) [144][700/2119] lr: 4.0000e-04 eta: 1:09:19 time: 0.2941 data_time: 0.0163 memory: 5821 grad_norm: 5.4239 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7292 loss: 1.7292 2022/10/08 15:44:18 - mmengine - INFO - Epoch(train) [144][720/2119] lr: 4.0000e-04 eta: 1:09:14 time: 0.2943 data_time: 0.0151 memory: 5821 grad_norm: 5.4640 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.5505 loss: 1.5505 2022/10/08 15:44:24 - mmengine - INFO - Epoch(train) [144][740/2119] lr: 4.0000e-04 eta: 1:09:08 time: 0.3029 data_time: 0.0158 memory: 5821 grad_norm: 5.5489 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.6462 loss: 1.6462 2022/10/08 15:44:30 - mmengine - INFO - Epoch(train) [144][760/2119] lr: 4.0000e-04 eta: 1:09:02 time: 0.2809 data_time: 0.0151 memory: 5821 grad_norm: 5.4276 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7452 loss: 1.7452 2022/10/08 15:44:35 - mmengine - INFO - Epoch(train) [144][780/2119] lr: 4.0000e-04 eta: 1:08:55 time: 0.2531 data_time: 0.0154 memory: 5821 grad_norm: 5.5789 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8042 loss: 1.8042 2022/10/08 15:44:41 - mmengine - INFO - Epoch(train) [144][800/2119] lr: 4.0000e-04 eta: 1:08:50 time: 0.3012 data_time: 0.0215 memory: 5821 grad_norm: 5.3296 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6565 loss: 1.6565 2022/10/08 15:44:46 - mmengine - INFO - Epoch(train) [144][820/2119] lr: 4.0000e-04 eta: 1:08:44 time: 0.2875 data_time: 0.0196 memory: 5821 grad_norm: 5.5207 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8805 loss: 1.8805 2022/10/08 15:44:52 - mmengine - INFO - Epoch(train) [144][840/2119] lr: 4.0000e-04 eta: 1:08:38 time: 0.2950 data_time: 0.0162 memory: 5821 grad_norm: 5.4713 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 1.7186 loss: 1.7186 2022/10/08 15:44:58 - mmengine - INFO - Epoch(train) [144][860/2119] lr: 4.0000e-04 eta: 1:08:32 time: 0.2835 data_time: 0.0194 memory: 5821 grad_norm: 5.4464 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7486 loss: 1.7486 2022/10/08 15:45:04 - mmengine - INFO - Epoch(train) [144][880/2119] lr: 4.0000e-04 eta: 1:08:26 time: 0.2851 data_time: 0.0219 memory: 5821 grad_norm: 5.4677 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8951 loss: 1.8951 2022/10/08 15:45:09 - mmengine - INFO - Epoch(train) [144][900/2119] lr: 4.0000e-04 eta: 1:08:20 time: 0.2717 data_time: 0.0250 memory: 5821 grad_norm: 5.4076 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.5869 loss: 1.5869 2022/10/08 15:45:14 - mmengine - INFO - Epoch(train) [144][920/2119] lr: 4.0000e-04 eta: 1:08:13 time: 0.2600 data_time: 0.0168 memory: 5821 grad_norm: 5.5508 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7263 loss: 1.7263 2022/10/08 15:45:21 - mmengine - INFO - Epoch(train) [144][940/2119] lr: 4.0000e-04 eta: 1:08:08 time: 0.3364 data_time: 0.0224 memory: 5821 grad_norm: 5.5387 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5538 loss: 1.5538 2022/10/08 15:45:27 - mmengine - INFO - Epoch(train) [144][960/2119] lr: 4.0000e-04 eta: 1:08:02 time: 0.2872 data_time: 0.0138 memory: 5821 grad_norm: 5.6291 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9966 loss: 1.9966 2022/10/08 15:45:32 - mmengine - INFO - Epoch(train) [144][980/2119] lr: 4.0000e-04 eta: 1:07:56 time: 0.2779 data_time: 0.0182 memory: 5821 grad_norm: 5.4926 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7955 loss: 1.7955 2022/10/08 15:45:34 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 15:45:39 - mmengine - INFO - Epoch(train) [144][1000/2119] lr: 4.0000e-04 eta: 1:07:50 time: 0.3187 data_time: 0.0138 memory: 5821 grad_norm: 5.4882 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.9662 loss: 1.9662 2022/10/08 15:45:44 - mmengine - INFO - Epoch(train) [144][1020/2119] lr: 4.0000e-04 eta: 1:07:44 time: 0.2683 data_time: 0.0285 memory: 5821 grad_norm: 5.4254 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9548 loss: 1.9548 2022/10/08 15:45:50 - mmengine - INFO - Epoch(train) [144][1040/2119] lr: 4.0000e-04 eta: 1:07:38 time: 0.2773 data_time: 0.0208 memory: 5821 grad_norm: 5.5359 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8296 loss: 1.8296 2022/10/08 15:45:55 - mmengine - INFO - Epoch(train) [144][1060/2119] lr: 4.0000e-04 eta: 1:07:32 time: 0.2655 data_time: 0.0197 memory: 5821 grad_norm: 5.4778 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.7003 loss: 1.7003 2022/10/08 15:46:03 - mmengine - INFO - Epoch(train) [144][1080/2119] lr: 4.0000e-04 eta: 1:07:27 time: 0.3810 data_time: 0.0984 memory: 5821 grad_norm: 5.4936 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.8494 loss: 1.8494 2022/10/08 15:46:08 - mmengine - INFO - Epoch(train) [144][1100/2119] lr: 4.0000e-04 eta: 1:07:21 time: 0.2704 data_time: 0.0211 memory: 5821 grad_norm: 5.4837 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8936 loss: 1.8936 2022/10/08 15:46:13 - mmengine - INFO - Epoch(train) [144][1120/2119] lr: 4.0000e-04 eta: 1:07:14 time: 0.2514 data_time: 0.0200 memory: 5821 grad_norm: 5.4608 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0112 loss: 2.0112 2022/10/08 15:46:20 - mmengine - INFO - Epoch(train) [144][1140/2119] lr: 4.0000e-04 eta: 1:07:09 time: 0.3396 data_time: 0.0248 memory: 5821 grad_norm: 5.5720 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9207 loss: 1.9207 2022/10/08 15:46:25 - mmengine - INFO - Epoch(train) [144][1160/2119] lr: 4.0000e-04 eta: 1:07:03 time: 0.2546 data_time: 0.0230 memory: 5821 grad_norm: 5.4993 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.8419 loss: 1.8419 2022/10/08 15:46:30 - mmengine - INFO - Epoch(train) [144][1180/2119] lr: 4.0000e-04 eta: 1:06:56 time: 0.2660 data_time: 0.0206 memory: 5821 grad_norm: 5.5057 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5960 loss: 1.5960 2022/10/08 15:46:36 - mmengine - INFO - Epoch(train) [144][1200/2119] lr: 4.0000e-04 eta: 1:06:50 time: 0.2815 data_time: 0.0214 memory: 5821 grad_norm: 5.5688 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7849 loss: 1.7849 2022/10/08 15:46:43 - mmengine - INFO - Epoch(train) [144][1220/2119] lr: 4.0000e-04 eta: 1:06:45 time: 0.3259 data_time: 0.0234 memory: 5821 grad_norm: 5.5186 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6178 loss: 1.6178 2022/10/08 15:46:48 - mmengine - INFO - Epoch(train) [144][1240/2119] lr: 4.0000e-04 eta: 1:06:39 time: 0.2866 data_time: 0.0159 memory: 5821 grad_norm: 5.5232 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8948 loss: 1.8948 2022/10/08 15:46:54 - mmengine - INFO - Epoch(train) [144][1260/2119] lr: 4.0000e-04 eta: 1:06:33 time: 0.2862 data_time: 0.0160 memory: 5821 grad_norm: 5.5751 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6744 loss: 1.6744 2022/10/08 15:47:00 - mmengine - INFO - Epoch(train) [144][1280/2119] lr: 4.0000e-04 eta: 1:06:27 time: 0.3025 data_time: 0.0190 memory: 5821 grad_norm: 5.4893 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7933 loss: 1.7933 2022/10/08 15:47:06 - mmengine - INFO - Epoch(train) [144][1300/2119] lr: 4.0000e-04 eta: 1:06:21 time: 0.2752 data_time: 0.0195 memory: 5821 grad_norm: 5.5131 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.8088 loss: 1.8088 2022/10/08 15:47:11 - mmengine - INFO - Epoch(train) [144][1320/2119] lr: 4.0000e-04 eta: 1:06:15 time: 0.2908 data_time: 0.0197 memory: 5821 grad_norm: 5.5946 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.7307 loss: 1.7307 2022/10/08 15:47:17 - mmengine - INFO - Epoch(train) [144][1340/2119] lr: 4.0000e-04 eta: 1:06:09 time: 0.2824 data_time: 0.0222 memory: 5821 grad_norm: 5.4233 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8162 loss: 1.8162 2022/10/08 15:47:23 - mmengine - INFO - Epoch(train) [144][1360/2119] lr: 4.0000e-04 eta: 1:06:03 time: 0.2977 data_time: 0.0203 memory: 5821 grad_norm: 5.5434 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.7404 loss: 1.7404 2022/10/08 15:47:29 - mmengine - INFO - Epoch(train) [144][1380/2119] lr: 4.0000e-04 eta: 1:05:57 time: 0.2838 data_time: 0.0204 memory: 5821 grad_norm: 5.6449 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9804 loss: 1.9804 2022/10/08 15:47:34 - mmengine - INFO - Epoch(train) [144][1400/2119] lr: 4.0000e-04 eta: 1:05:51 time: 0.2590 data_time: 0.0201 memory: 5821 grad_norm: 5.4692 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8422 loss: 1.8422 2022/10/08 15:47:40 - mmengine - INFO - Epoch(train) [144][1420/2119] lr: 4.0000e-04 eta: 1:05:45 time: 0.3006 data_time: 0.0241 memory: 5821 grad_norm: 5.4922 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8454 loss: 1.8454 2022/10/08 15:47:45 - mmengine - INFO - Epoch(train) [144][1440/2119] lr: 4.0000e-04 eta: 1:05:39 time: 0.2648 data_time: 0.0205 memory: 5821 grad_norm: 5.3928 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7620 loss: 1.7620 2022/10/08 15:47:51 - mmengine - INFO - Epoch(train) [144][1460/2119] lr: 4.0000e-04 eta: 1:05:33 time: 0.2991 data_time: 0.0144 memory: 5821 grad_norm: 5.4754 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0450 loss: 2.0450 2022/10/08 15:47:58 - mmengine - INFO - Epoch(train) [144][1480/2119] lr: 4.0000e-04 eta: 1:05:27 time: 0.3108 data_time: 0.0195 memory: 5821 grad_norm: 5.4568 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7253 loss: 1.7253 2022/10/08 15:48:03 - mmengine - INFO - Epoch(train) [144][1500/2119] lr: 4.0000e-04 eta: 1:05:22 time: 0.2945 data_time: 0.0233 memory: 5821 grad_norm: 5.5028 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7940 loss: 1.7940 2022/10/08 15:48:09 - mmengine - INFO - Epoch(train) [144][1520/2119] lr: 4.0000e-04 eta: 1:05:15 time: 0.2787 data_time: 0.0225 memory: 5821 grad_norm: 5.5150 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0469 loss: 2.0469 2022/10/08 15:48:15 - mmengine - INFO - Epoch(train) [144][1540/2119] lr: 4.0000e-04 eta: 1:05:10 time: 0.2909 data_time: 0.0223 memory: 5821 grad_norm: 5.4887 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0871 loss: 2.0871 2022/10/08 15:48:22 - mmengine - INFO - Epoch(train) [144][1560/2119] lr: 4.0000e-04 eta: 1:05:04 time: 0.3325 data_time: 0.0204 memory: 5821 grad_norm: 5.3343 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7803 loss: 1.7803 2022/10/08 15:48:27 - mmengine - INFO - Epoch(train) [144][1580/2119] lr: 4.0000e-04 eta: 1:04:58 time: 0.2744 data_time: 0.0217 memory: 5821 grad_norm: 5.5238 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9959 loss: 1.9959 2022/10/08 15:48:32 - mmengine - INFO - Epoch(train) [144][1600/2119] lr: 4.0000e-04 eta: 1:04:52 time: 0.2534 data_time: 0.0183 memory: 5821 grad_norm: 5.4538 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8103 loss: 1.8103 2022/10/08 15:48:38 - mmengine - INFO - Epoch(train) [144][1620/2119] lr: 4.0000e-04 eta: 1:04:46 time: 0.2979 data_time: 0.0226 memory: 5821 grad_norm: 5.4898 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.7600 loss: 1.7600 2022/10/08 15:48:44 - mmengine - INFO - Epoch(train) [144][1640/2119] lr: 4.0000e-04 eta: 1:04:40 time: 0.2825 data_time: 0.0206 memory: 5821 grad_norm: 5.5574 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8170 loss: 1.8170 2022/10/08 15:48:49 - mmengine - INFO - Epoch(train) [144][1660/2119] lr: 4.0000e-04 eta: 1:04:34 time: 0.2851 data_time: 0.0211 memory: 5821 grad_norm: 5.5944 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6512 loss: 1.6512 2022/10/08 15:48:56 - mmengine - INFO - Epoch(train) [144][1680/2119] lr: 4.0000e-04 eta: 1:04:28 time: 0.3274 data_time: 0.0176 memory: 5821 grad_norm: 5.5047 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7113 loss: 1.7113 2022/10/08 15:49:02 - mmengine - INFO - Epoch(train) [144][1700/2119] lr: 4.0000e-04 eta: 1:04:22 time: 0.2817 data_time: 0.0330 memory: 5821 grad_norm: 5.3239 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7987 loss: 1.7987 2022/10/08 15:49:07 - mmengine - INFO - Epoch(train) [144][1720/2119] lr: 4.0000e-04 eta: 1:04:16 time: 0.2826 data_time: 0.0199 memory: 5821 grad_norm: 5.5475 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9357 loss: 1.9357 2022/10/08 15:49:13 - mmengine - INFO - Epoch(train) [144][1740/2119] lr: 4.0000e-04 eta: 1:04:10 time: 0.2687 data_time: 0.0194 memory: 5821 grad_norm: 5.6214 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8443 loss: 1.8443 2022/10/08 15:49:19 - mmengine - INFO - Epoch(train) [144][1760/2119] lr: 4.0000e-04 eta: 1:04:04 time: 0.2914 data_time: 0.0166 memory: 5821 grad_norm: 5.5657 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.6861 loss: 1.6861 2022/10/08 15:49:24 - mmengine - INFO - Epoch(train) [144][1780/2119] lr: 4.0000e-04 eta: 1:03:58 time: 0.2960 data_time: 0.0274 memory: 5821 grad_norm: 5.5005 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6847 loss: 1.6847 2022/10/08 15:49:30 - mmengine - INFO - Epoch(train) [144][1800/2119] lr: 4.0000e-04 eta: 1:03:52 time: 0.2616 data_time: 0.0168 memory: 5821 grad_norm: 5.5326 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7713 loss: 1.7713 2022/10/08 15:49:35 - mmengine - INFO - Epoch(train) [144][1820/2119] lr: 4.0000e-04 eta: 1:03:46 time: 0.2891 data_time: 0.0217 memory: 5821 grad_norm: 5.5419 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9189 loss: 1.9189 2022/10/08 15:49:42 - mmengine - INFO - Epoch(train) [144][1840/2119] lr: 4.0000e-04 eta: 1:03:41 time: 0.3185 data_time: 0.0168 memory: 5821 grad_norm: 5.4792 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6496 loss: 1.6496 2022/10/08 15:49:48 - mmengine - INFO - Epoch(train) [144][1860/2119] lr: 4.0000e-04 eta: 1:03:35 time: 0.2821 data_time: 0.0170 memory: 5821 grad_norm: 5.4231 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.6975 loss: 1.6975 2022/10/08 15:49:53 - mmengine - INFO - Epoch(train) [144][1880/2119] lr: 4.0000e-04 eta: 1:03:28 time: 0.2561 data_time: 0.0168 memory: 5821 grad_norm: 5.5171 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8840 loss: 1.8840 2022/10/08 15:49:59 - mmengine - INFO - Epoch(train) [144][1900/2119] lr: 4.0000e-04 eta: 1:03:23 time: 0.3294 data_time: 0.0236 memory: 5821 grad_norm: 5.4608 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.6070 loss: 1.6070 2022/10/08 15:50:05 - mmengine - INFO - Epoch(train) [144][1920/2119] lr: 4.0000e-04 eta: 1:03:17 time: 0.2781 data_time: 0.0232 memory: 5821 grad_norm: 5.4706 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0041 loss: 2.0041 2022/10/08 15:50:11 - mmengine - INFO - Epoch(train) [144][1940/2119] lr: 4.0000e-04 eta: 1:03:11 time: 0.3050 data_time: 0.0211 memory: 5821 grad_norm: 5.5898 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.8387 loss: 1.8387 2022/10/08 15:50:17 - mmengine - INFO - Epoch(train) [144][1960/2119] lr: 4.0000e-04 eta: 1:03:05 time: 0.2806 data_time: 0.0174 memory: 5821 grad_norm: 5.4998 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6325 loss: 1.6325 2022/10/08 15:50:23 - mmengine - INFO - Epoch(train) [144][1980/2119] lr: 4.0000e-04 eta: 1:02:59 time: 0.3171 data_time: 0.0188 memory: 5821 grad_norm: 5.4662 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.5586 loss: 1.5586 2022/10/08 15:50:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 15:50:29 - mmengine - INFO - Epoch(train) [144][2000/2119] lr: 4.0000e-04 eta: 1:02:53 time: 0.2817 data_time: 0.0195 memory: 5821 grad_norm: 5.5621 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7974 loss: 1.7974 2022/10/08 15:50:34 - mmengine - INFO - Epoch(train) [144][2020/2119] lr: 4.0000e-04 eta: 1:02:47 time: 0.2746 data_time: 0.0184 memory: 5821 grad_norm: 5.5297 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.7891 loss: 1.7891 2022/10/08 15:50:40 - mmengine - INFO - Epoch(train) [144][2040/2119] lr: 4.0000e-04 eta: 1:02:41 time: 0.3047 data_time: 0.0219 memory: 5821 grad_norm: 5.4472 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6231 loss: 1.6231 2022/10/08 15:50:46 - mmengine - INFO - Epoch(train) [144][2060/2119] lr: 4.0000e-04 eta: 1:02:36 time: 0.2929 data_time: 0.0167 memory: 5821 grad_norm: 5.4934 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6444 loss: 1.6444 2022/10/08 15:50:52 - mmengine - INFO - Epoch(train) [144][2080/2119] lr: 4.0000e-04 eta: 1:02:30 time: 0.2796 data_time: 0.0196 memory: 5821 grad_norm: 5.4927 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7883 loss: 1.7883 2022/10/08 15:50:57 - mmengine - INFO - Epoch(train) [144][2100/2119] lr: 4.0000e-04 eta: 1:02:23 time: 0.2688 data_time: 0.0199 memory: 5821 grad_norm: 5.5260 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8058 loss: 1.8058 2022/10/08 15:51:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 15:51:02 - mmengine - INFO - Epoch(train) [144][2119/2119] lr: 4.0000e-04 eta: 1:02:23 time: 0.2541 data_time: 0.0169 memory: 5821 grad_norm: 5.6496 top1_acc: 0.3000 top5_acc: 0.5000 loss_cls: 1.9925 loss: 1.9925 2022/10/08 15:51:02 - mmengine - INFO - Saving checkpoint at 144 epochs 2022/10/08 15:51:10 - mmengine - INFO - Epoch(train) [145][20/2119] lr: 4.0000e-04 eta: 1:02:10 time: 0.3482 data_time: 0.1142 memory: 5821 grad_norm: 5.4787 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7072 loss: 1.7072 2022/10/08 15:51:16 - mmengine - INFO - Epoch(train) [145][40/2119] lr: 4.0000e-04 eta: 1:02:04 time: 0.2663 data_time: 0.0162 memory: 5821 grad_norm: 5.5061 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7569 loss: 1.7569 2022/10/08 15:51:22 - mmengine - INFO - Epoch(train) [145][60/2119] lr: 4.0000e-04 eta: 1:01:58 time: 0.3299 data_time: 0.0302 memory: 5821 grad_norm: 5.5715 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9943 loss: 1.9943 2022/10/08 15:51:28 - mmengine - INFO - Epoch(train) [145][80/2119] lr: 4.0000e-04 eta: 1:01:52 time: 0.2607 data_time: 0.0160 memory: 5821 grad_norm: 5.5401 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.7278 loss: 1.7278 2022/10/08 15:51:34 - mmengine - INFO - Epoch(train) [145][100/2119] lr: 4.0000e-04 eta: 1:01:46 time: 0.2965 data_time: 0.0187 memory: 5821 grad_norm: 5.5678 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.6032 loss: 1.6032 2022/10/08 15:51:39 - mmengine - INFO - Epoch(train) [145][120/2119] lr: 4.0000e-04 eta: 1:01:40 time: 0.2852 data_time: 0.0244 memory: 5821 grad_norm: 5.5511 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8829 loss: 1.8829 2022/10/08 15:51:45 - mmengine - INFO - Epoch(train) [145][140/2119] lr: 4.0000e-04 eta: 1:01:34 time: 0.2901 data_time: 0.0166 memory: 5821 grad_norm: 5.5961 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.7564 loss: 1.7564 2022/10/08 15:51:51 - mmengine - INFO - Epoch(train) [145][160/2119] lr: 4.0000e-04 eta: 1:01:28 time: 0.2954 data_time: 0.0159 memory: 5821 grad_norm: 5.6236 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.8261 loss: 1.8261 2022/10/08 15:51:56 - mmengine - INFO - Epoch(train) [145][180/2119] lr: 4.0000e-04 eta: 1:01:22 time: 0.2628 data_time: 0.0211 memory: 5821 grad_norm: 5.5098 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5639 loss: 1.5639 2022/10/08 15:52:07 - mmengine - INFO - Epoch(train) [145][200/2119] lr: 4.0000e-04 eta: 1:01:18 time: 0.5191 data_time: 0.0161 memory: 5821 grad_norm: 5.5685 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7717 loss: 1.7717 2022/10/08 15:52:12 - mmengine - INFO - Epoch(train) [145][220/2119] lr: 4.0000e-04 eta: 1:01:12 time: 0.2774 data_time: 0.0265 memory: 5821 grad_norm: 5.4308 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0379 loss: 2.0379 2022/10/08 15:52:19 - mmengine - INFO - Epoch(train) [145][240/2119] lr: 4.0000e-04 eta: 1:01:07 time: 0.3204 data_time: 0.0197 memory: 5821 grad_norm: 5.4937 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8118 loss: 1.8118 2022/10/08 15:52:24 - mmengine - INFO - Epoch(train) [145][260/2119] lr: 4.0000e-04 eta: 1:01:01 time: 0.2751 data_time: 0.0229 memory: 5821 grad_norm: 5.5083 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7090 loss: 1.7090 2022/10/08 15:52:30 - mmengine - INFO - Epoch(train) [145][280/2119] lr: 4.0000e-04 eta: 1:00:55 time: 0.2750 data_time: 0.0219 memory: 5821 grad_norm: 5.4551 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.8032 loss: 1.8032 2022/10/08 15:52:36 - mmengine - INFO - Epoch(train) [145][300/2119] lr: 4.0000e-04 eta: 1:00:49 time: 0.3038 data_time: 0.0176 memory: 5821 grad_norm: 5.6202 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9284 loss: 1.9284 2022/10/08 15:52:41 - mmengine - INFO - Epoch(train) [145][320/2119] lr: 4.0000e-04 eta: 1:00:43 time: 0.2727 data_time: 0.0203 memory: 5821 grad_norm: 5.4529 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5731 loss: 1.5731 2022/10/08 15:52:47 - mmengine - INFO - Epoch(train) [145][340/2119] lr: 4.0000e-04 eta: 1:00:37 time: 0.2648 data_time: 0.0204 memory: 5821 grad_norm: 5.5452 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 1.7601 loss: 1.7601 2022/10/08 15:52:52 - mmengine - INFO - Epoch(train) [145][360/2119] lr: 4.0000e-04 eta: 1:00:31 time: 0.2920 data_time: 0.0200 memory: 5821 grad_norm: 5.6125 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9794 loss: 1.9794 2022/10/08 15:52:59 - mmengine - INFO - Epoch(train) [145][380/2119] lr: 4.0000e-04 eta: 1:00:25 time: 0.3132 data_time: 0.0179 memory: 5821 grad_norm: 5.5144 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8084 loss: 1.8084 2022/10/08 15:53:05 - mmengine - INFO - Epoch(train) [145][400/2119] lr: 4.0000e-04 eta: 1:00:19 time: 0.3204 data_time: 0.0193 memory: 5821 grad_norm: 5.5698 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6902 loss: 1.6902 2022/10/08 15:53:10 - mmengine - INFO - Epoch(train) [145][420/2119] lr: 4.0000e-04 eta: 1:00:13 time: 0.2607 data_time: 0.0254 memory: 5821 grad_norm: 5.5271 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8767 loss: 1.8767 2022/10/08 15:53:16 - mmengine - INFO - Epoch(train) [145][440/2119] lr: 4.0000e-04 eta: 1:00:07 time: 0.2965 data_time: 0.0176 memory: 5821 grad_norm: 5.4828 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7220 loss: 1.7220 2022/10/08 15:53:22 - mmengine - INFO - Epoch(train) [145][460/2119] lr: 4.0000e-04 eta: 1:00:01 time: 0.2950 data_time: 0.0259 memory: 5821 grad_norm: 5.5336 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.6351 loss: 1.6351 2022/10/08 15:53:28 - mmengine - INFO - Epoch(train) [145][480/2119] lr: 4.0000e-04 eta: 0:59:55 time: 0.2696 data_time: 0.0266 memory: 5821 grad_norm: 5.4704 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8675 loss: 1.8675 2022/10/08 15:53:33 - mmengine - INFO - Epoch(train) [145][500/2119] lr: 4.0000e-04 eta: 0:59:49 time: 0.2884 data_time: 0.0148 memory: 5821 grad_norm: 5.5254 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6979 loss: 1.6979 2022/10/08 15:53:39 - mmengine - INFO - Epoch(train) [145][520/2119] lr: 4.0000e-04 eta: 0:59:44 time: 0.2962 data_time: 0.0169 memory: 5821 grad_norm: 5.4628 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6996 loss: 1.6996 2022/10/08 15:53:45 - mmengine - INFO - Epoch(train) [145][540/2119] lr: 4.0000e-04 eta: 0:59:38 time: 0.2829 data_time: 0.0232 memory: 5821 grad_norm: 5.4328 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7504 loss: 1.7504 2022/10/08 15:53:51 - mmengine - INFO - Epoch(train) [145][560/2119] lr: 4.0000e-04 eta: 0:59:32 time: 0.2972 data_time: 0.0181 memory: 5821 grad_norm: 5.4652 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7356 loss: 1.7356 2022/10/08 15:53:56 - mmengine - INFO - Epoch(train) [145][580/2119] lr: 4.0000e-04 eta: 0:59:26 time: 0.2700 data_time: 0.0168 memory: 5821 grad_norm: 5.5097 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6882 loss: 1.6882 2022/10/08 15:54:02 - mmengine - INFO - Epoch(train) [145][600/2119] lr: 4.0000e-04 eta: 0:59:20 time: 0.2942 data_time: 0.0150 memory: 5821 grad_norm: 5.4579 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8691 loss: 1.8691 2022/10/08 15:54:08 - mmengine - INFO - Epoch(train) [145][620/2119] lr: 4.0000e-04 eta: 0:59:14 time: 0.2736 data_time: 0.0206 memory: 5821 grad_norm: 5.4426 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.6824 loss: 1.6824 2022/10/08 15:54:14 - mmengine - INFO - Epoch(train) [145][640/2119] lr: 4.0000e-04 eta: 0:59:08 time: 0.2913 data_time: 0.0180 memory: 5821 grad_norm: 5.5047 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7515 loss: 1.7515 2022/10/08 15:54:33 - mmengine - INFO - Epoch(train) [145][660/2119] lr: 4.0000e-04 eta: 0:59:08 time: 0.9687 data_time: 0.0228 memory: 5821 grad_norm: 5.5971 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7542 loss: 1.7542 2022/10/08 15:54:38 - mmengine - INFO - Epoch(train) [145][680/2119] lr: 4.0000e-04 eta: 0:59:02 time: 0.2547 data_time: 0.0307 memory: 5821 grad_norm: 5.4627 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7328 loss: 1.7328 2022/10/08 15:54:43 - mmengine - INFO - Epoch(train) [145][700/2119] lr: 4.0000e-04 eta: 0:58:56 time: 0.2712 data_time: 0.0233 memory: 5821 grad_norm: 5.4401 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.7586 loss: 1.7586 2022/10/08 15:54:50 - mmengine - INFO - Epoch(train) [145][720/2119] lr: 4.0000e-04 eta: 0:58:50 time: 0.3375 data_time: 0.0186 memory: 5821 grad_norm: 5.5259 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0737 loss: 2.0737 2022/10/08 15:54:56 - mmengine - INFO - Epoch(train) [145][740/2119] lr: 4.0000e-04 eta: 0:58:44 time: 0.2668 data_time: 0.0202 memory: 5821 grad_norm: 5.4886 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8034 loss: 1.8034 2022/10/08 15:55:01 - mmengine - INFO - Epoch(train) [145][760/2119] lr: 4.0000e-04 eta: 0:58:38 time: 0.2799 data_time: 0.0196 memory: 5821 grad_norm: 5.3524 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.5744 loss: 1.5744 2022/10/08 15:55:08 - mmengine - INFO - Epoch(train) [145][780/2119] lr: 4.0000e-04 eta: 0:58:33 time: 0.3229 data_time: 0.0198 memory: 5821 grad_norm: 5.5025 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.7118 loss: 1.7118 2022/10/08 15:55:13 - mmengine - INFO - Epoch(train) [145][800/2119] lr: 4.0000e-04 eta: 0:58:27 time: 0.2822 data_time: 0.0274 memory: 5821 grad_norm: 5.5269 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8323 loss: 1.8323 2022/10/08 15:55:19 - mmengine - INFO - Epoch(train) [145][820/2119] lr: 4.0000e-04 eta: 0:58:20 time: 0.2709 data_time: 0.0170 memory: 5821 grad_norm: 5.4782 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8197 loss: 1.8197 2022/10/08 15:55:24 - mmengine - INFO - Epoch(train) [145][840/2119] lr: 4.0000e-04 eta: 0:58:14 time: 0.2734 data_time: 0.0180 memory: 5821 grad_norm: 5.5979 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7771 loss: 1.7771 2022/10/08 15:55:30 - mmengine - INFO - Epoch(train) [145][860/2119] lr: 4.0000e-04 eta: 0:58:08 time: 0.2797 data_time: 0.0169 memory: 5821 grad_norm: 5.4455 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.7466 loss: 1.7466 2022/10/08 15:55:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 15:55:36 - mmengine - INFO - Epoch(train) [145][880/2119] lr: 4.0000e-04 eta: 0:58:02 time: 0.2894 data_time: 0.0280 memory: 5821 grad_norm: 5.4442 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7145 loss: 1.7145 2022/10/08 15:55:42 - mmengine - INFO - Epoch(train) [145][900/2119] lr: 4.0000e-04 eta: 0:57:57 time: 0.3013 data_time: 0.0156 memory: 5821 grad_norm: 5.5915 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7530 loss: 1.7530 2022/10/08 15:55:47 - mmengine - INFO - Epoch(train) [145][920/2119] lr: 4.0000e-04 eta: 0:57:51 time: 0.2877 data_time: 0.0231 memory: 5821 grad_norm: 5.5081 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7263 loss: 1.7263 2022/10/08 15:55:54 - mmengine - INFO - Epoch(train) [145][940/2119] lr: 4.0000e-04 eta: 0:57:45 time: 0.3159 data_time: 0.0233 memory: 5821 grad_norm: 5.6214 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.9883 loss: 1.9883 2022/10/08 15:55:59 - mmengine - INFO - Epoch(train) [145][960/2119] lr: 4.0000e-04 eta: 0:57:39 time: 0.2593 data_time: 0.0216 memory: 5821 grad_norm: 5.6299 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6703 loss: 1.6703 2022/10/08 15:56:05 - mmengine - INFO - Epoch(train) [145][980/2119] lr: 4.0000e-04 eta: 0:57:33 time: 0.2810 data_time: 0.0235 memory: 5821 grad_norm: 5.5524 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9264 loss: 1.9264 2022/10/08 15:56:11 - mmengine - INFO - Epoch(train) [145][1000/2119] lr: 4.0000e-04 eta: 0:57:27 time: 0.3049 data_time: 0.0204 memory: 5821 grad_norm: 5.4630 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6895 loss: 1.6895 2022/10/08 15:56:16 - mmengine - INFO - Epoch(train) [145][1020/2119] lr: 4.0000e-04 eta: 0:57:21 time: 0.2655 data_time: 0.0185 memory: 5821 grad_norm: 5.5431 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5990 loss: 1.5990 2022/10/08 15:56:22 - mmengine - INFO - Epoch(train) [145][1040/2119] lr: 4.0000e-04 eta: 0:57:15 time: 0.2943 data_time: 0.0231 memory: 5821 grad_norm: 5.4807 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5979 loss: 1.5979 2022/10/08 15:56:27 - mmengine - INFO - Epoch(train) [145][1060/2119] lr: 4.0000e-04 eta: 0:57:09 time: 0.2775 data_time: 0.0223 memory: 5821 grad_norm: 5.5139 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6609 loss: 1.6609 2022/10/08 15:56:33 - mmengine - INFO - Epoch(train) [145][1080/2119] lr: 4.0000e-04 eta: 0:57:03 time: 0.2938 data_time: 0.0247 memory: 5821 grad_norm: 5.5788 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7906 loss: 1.7906 2022/10/08 15:56:39 - mmengine - INFO - Epoch(train) [145][1100/2119] lr: 4.0000e-04 eta: 0:56:57 time: 0.2842 data_time: 0.0201 memory: 5821 grad_norm: 5.6585 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8854 loss: 1.8854 2022/10/08 15:56:45 - mmengine - INFO - Epoch(train) [145][1120/2119] lr: 4.0000e-04 eta: 0:56:51 time: 0.2980 data_time: 0.0181 memory: 5821 grad_norm: 5.4449 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.6003 loss: 1.6003 2022/10/08 15:56:51 - mmengine - INFO - Epoch(train) [145][1140/2119] lr: 4.0000e-04 eta: 0:56:45 time: 0.3037 data_time: 0.0205 memory: 5821 grad_norm: 5.5784 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6854 loss: 1.6854 2022/10/08 15:56:57 - mmengine - INFO - Epoch(train) [145][1160/2119] lr: 4.0000e-04 eta: 0:56:39 time: 0.2765 data_time: 0.0220 memory: 5821 grad_norm: 5.5631 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9335 loss: 1.9335 2022/10/08 15:57:03 - mmengine - INFO - Epoch(train) [145][1180/2119] lr: 4.0000e-04 eta: 0:56:34 time: 0.3098 data_time: 0.0201 memory: 5821 grad_norm: 5.5000 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.5872 loss: 1.5872 2022/10/08 15:57:09 - mmengine - INFO - Epoch(train) [145][1200/2119] lr: 4.0000e-04 eta: 0:56:28 time: 0.3088 data_time: 0.0200 memory: 5821 grad_norm: 5.5982 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8259 loss: 1.8259 2022/10/08 15:57:15 - mmengine - INFO - Epoch(train) [145][1220/2119] lr: 4.0000e-04 eta: 0:56:22 time: 0.2905 data_time: 0.0197 memory: 5821 grad_norm: 5.5442 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7940 loss: 1.7940 2022/10/08 15:57:21 - mmengine - INFO - Epoch(train) [145][1240/2119] lr: 4.0000e-04 eta: 0:56:16 time: 0.3026 data_time: 0.0204 memory: 5821 grad_norm: 5.5553 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8016 loss: 1.8016 2022/10/08 15:57:26 - mmengine - INFO - Epoch(train) [145][1260/2119] lr: 4.0000e-04 eta: 0:56:10 time: 0.2670 data_time: 0.0214 memory: 5821 grad_norm: 5.5023 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9211 loss: 1.9211 2022/10/08 15:57:32 - mmengine - INFO - Epoch(train) [145][1280/2119] lr: 4.0000e-04 eta: 0:56:04 time: 0.3059 data_time: 0.0175 memory: 5821 grad_norm: 5.4571 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7272 loss: 1.7272 2022/10/08 15:57:38 - mmengine - INFO - Epoch(train) [145][1300/2119] lr: 4.0000e-04 eta: 0:55:58 time: 0.2698 data_time: 0.0155 memory: 5821 grad_norm: 5.4695 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6293 loss: 1.6293 2022/10/08 15:57:44 - mmengine - INFO - Epoch(train) [145][1320/2119] lr: 4.0000e-04 eta: 0:55:52 time: 0.3083 data_time: 0.0180 memory: 5821 grad_norm: 5.5959 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9926 loss: 1.9926 2022/10/08 15:57:49 - mmengine - INFO - Epoch(train) [145][1340/2119] lr: 4.0000e-04 eta: 0:55:46 time: 0.2752 data_time: 0.0182 memory: 5821 grad_norm: 5.5699 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 1.8918 loss: 1.8918 2022/10/08 15:57:55 - mmengine - INFO - Epoch(train) [145][1360/2119] lr: 4.0000e-04 eta: 0:55:40 time: 0.2729 data_time: 0.0252 memory: 5821 grad_norm: 5.5170 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9846 loss: 1.9846 2022/10/08 15:58:01 - mmengine - INFO - Epoch(train) [145][1380/2119] lr: 4.0000e-04 eta: 0:55:34 time: 0.3130 data_time: 0.0207 memory: 5821 grad_norm: 5.5831 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8781 loss: 1.8781 2022/10/08 15:58:07 - mmengine - INFO - Epoch(train) [145][1400/2119] lr: 4.0000e-04 eta: 0:55:28 time: 0.2683 data_time: 0.0201 memory: 5821 grad_norm: 5.5561 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.7968 loss: 1.7968 2022/10/08 15:58:12 - mmengine - INFO - Epoch(train) [145][1420/2119] lr: 4.0000e-04 eta: 0:55:22 time: 0.2905 data_time: 0.0220 memory: 5821 grad_norm: 5.5204 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8744 loss: 1.8744 2022/10/08 15:58:18 - mmengine - INFO - Epoch(train) [145][1440/2119] lr: 4.0000e-04 eta: 0:55:16 time: 0.2859 data_time: 0.0164 memory: 5821 grad_norm: 5.4469 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5775 loss: 1.5775 2022/10/08 15:58:24 - mmengine - INFO - Epoch(train) [145][1460/2119] lr: 4.0000e-04 eta: 0:55:11 time: 0.2846 data_time: 0.0151 memory: 5821 grad_norm: 5.5994 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8062 loss: 1.8062 2022/10/08 15:58:30 - mmengine - INFO - Epoch(train) [145][1480/2119] lr: 4.0000e-04 eta: 0:55:05 time: 0.2962 data_time: 0.0193 memory: 5821 grad_norm: 5.6182 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.7180 loss: 1.7180 2022/10/08 15:58:36 - mmengine - INFO - Epoch(train) [145][1500/2119] lr: 4.0000e-04 eta: 0:54:59 time: 0.2919 data_time: 0.0171 memory: 5821 grad_norm: 5.6075 top1_acc: 0.5625 top5_acc: 0.5625 loss_cls: 1.8377 loss: 1.8377 2022/10/08 15:58:41 - mmengine - INFO - Epoch(train) [145][1520/2119] lr: 4.0000e-04 eta: 0:54:53 time: 0.2891 data_time: 0.0170 memory: 5821 grad_norm: 5.4417 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7242 loss: 1.7242 2022/10/08 15:58:47 - mmengine - INFO - Epoch(train) [145][1540/2119] lr: 4.0000e-04 eta: 0:54:47 time: 0.2693 data_time: 0.0255 memory: 5821 grad_norm: 5.4542 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.8955 loss: 1.8955 2022/10/08 15:58:53 - mmengine - INFO - Epoch(train) [145][1560/2119] lr: 4.0000e-04 eta: 0:54:41 time: 0.2863 data_time: 0.0200 memory: 5821 grad_norm: 5.5961 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.7291 loss: 1.7291 2022/10/08 15:58:59 - mmengine - INFO - Epoch(train) [145][1580/2119] lr: 4.0000e-04 eta: 0:54:35 time: 0.2985 data_time: 0.0183 memory: 5821 grad_norm: 5.6844 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8835 loss: 1.8835 2022/10/08 15:59:04 - mmengine - INFO - Epoch(train) [145][1600/2119] lr: 4.0000e-04 eta: 0:54:29 time: 0.2829 data_time: 0.0186 memory: 5821 grad_norm: 5.6039 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5743 loss: 1.5743 2022/10/08 15:59:10 - mmengine - INFO - Epoch(train) [145][1620/2119] lr: 4.0000e-04 eta: 0:54:23 time: 0.2698 data_time: 0.0194 memory: 5821 grad_norm: 5.5856 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.6319 loss: 1.6319 2022/10/08 15:59:15 - mmengine - INFO - Epoch(train) [145][1640/2119] lr: 4.0000e-04 eta: 0:54:17 time: 0.2822 data_time: 0.0211 memory: 5821 grad_norm: 5.5231 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6600 loss: 1.6600 2022/10/08 15:59:21 - mmengine - INFO - Epoch(train) [145][1660/2119] lr: 4.0000e-04 eta: 0:54:11 time: 0.2950 data_time: 0.0166 memory: 5821 grad_norm: 5.5422 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8123 loss: 1.8123 2022/10/08 15:59:27 - mmengine - INFO - Epoch(train) [145][1680/2119] lr: 4.0000e-04 eta: 0:54:05 time: 0.2961 data_time: 0.0201 memory: 5821 grad_norm: 5.6566 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8419 loss: 1.8419 2022/10/08 15:59:33 - mmengine - INFO - Epoch(train) [145][1700/2119] lr: 4.0000e-04 eta: 0:53:59 time: 0.2978 data_time: 0.0190 memory: 5821 grad_norm: 5.5307 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9992 loss: 1.9992 2022/10/08 15:59:39 - mmengine - INFO - Epoch(train) [145][1720/2119] lr: 4.0000e-04 eta: 0:53:53 time: 0.2779 data_time: 0.0182 memory: 5821 grad_norm: 5.6504 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0116 loss: 2.0116 2022/10/08 15:59:45 - mmengine - INFO - Epoch(train) [145][1740/2119] lr: 4.0000e-04 eta: 0:53:47 time: 0.2977 data_time: 0.0184 memory: 5821 grad_norm: 5.6180 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 1.9139 loss: 1.9139 2022/10/08 15:59:51 - mmengine - INFO - Epoch(train) [145][1760/2119] lr: 4.0000e-04 eta: 0:53:42 time: 0.2947 data_time: 0.0183 memory: 5821 grad_norm: 5.5853 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9631 loss: 1.9631 2022/10/08 15:59:56 - mmengine - INFO - Epoch(train) [145][1780/2119] lr: 4.0000e-04 eta: 0:53:35 time: 0.2611 data_time: 0.0253 memory: 5821 grad_norm: 5.5939 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 1.7970 loss: 1.7970 2022/10/08 16:00:02 - mmengine - INFO - Epoch(train) [145][1800/2119] lr: 4.0000e-04 eta: 0:53:30 time: 0.3074 data_time: 0.0186 memory: 5821 grad_norm: 5.5257 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9319 loss: 1.9319 2022/10/08 16:00:08 - mmengine - INFO - Epoch(train) [145][1820/2119] lr: 4.0000e-04 eta: 0:53:24 time: 0.2939 data_time: 0.0153 memory: 5821 grad_norm: 5.5576 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9059 loss: 1.9059 2022/10/08 16:00:13 - mmengine - INFO - Epoch(train) [145][1840/2119] lr: 4.0000e-04 eta: 0:53:18 time: 0.2776 data_time: 0.0213 memory: 5821 grad_norm: 5.5884 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7438 loss: 1.7438 2022/10/08 16:00:19 - mmengine - INFO - Epoch(train) [145][1860/2119] lr: 4.0000e-04 eta: 0:53:12 time: 0.2877 data_time: 0.0178 memory: 5821 grad_norm: 5.5990 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8401 loss: 1.8401 2022/10/08 16:00:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 16:00:25 - mmengine - INFO - Epoch(train) [145][1880/2119] lr: 4.0000e-04 eta: 0:53:06 time: 0.2791 data_time: 0.0232 memory: 5821 grad_norm: 5.4288 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6664 loss: 1.6664 2022/10/08 16:00:32 - mmengine - INFO - Epoch(train) [145][1900/2119] lr: 4.0000e-04 eta: 0:53:01 time: 0.3741 data_time: 0.0188 memory: 5821 grad_norm: 5.4941 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.8373 loss: 1.8373 2022/10/08 16:00:39 - mmengine - INFO - Epoch(train) [145][1920/2119] lr: 4.0000e-04 eta: 0:52:55 time: 0.3243 data_time: 0.0145 memory: 5821 grad_norm: 5.6059 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.7675 loss: 1.7675 2022/10/08 16:00:44 - mmengine - INFO - Epoch(train) [145][1940/2119] lr: 4.0000e-04 eta: 0:52:49 time: 0.2772 data_time: 0.0211 memory: 5821 grad_norm: 5.5764 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5195 loss: 1.5195 2022/10/08 16:00:50 - mmengine - INFO - Epoch(train) [145][1960/2119] lr: 4.0000e-04 eta: 0:52:43 time: 0.2869 data_time: 0.0273 memory: 5821 grad_norm: 5.5935 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8695 loss: 1.8695 2022/10/08 16:00:56 - mmengine - INFO - Epoch(train) [145][1980/2119] lr: 4.0000e-04 eta: 0:52:37 time: 0.2940 data_time: 0.0225 memory: 5821 grad_norm: 5.5473 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6961 loss: 1.6961 2022/10/08 16:01:01 - mmengine - INFO - Epoch(train) [145][2000/2119] lr: 4.0000e-04 eta: 0:52:31 time: 0.2799 data_time: 0.0194 memory: 5821 grad_norm: 5.5777 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6961 loss: 1.6961 2022/10/08 16:01:07 - mmengine - INFO - Epoch(train) [145][2020/2119] lr: 4.0000e-04 eta: 0:52:25 time: 0.2761 data_time: 0.0172 memory: 5821 grad_norm: 5.6637 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.7415 loss: 1.7415 2022/10/08 16:01:13 - mmengine - INFO - Epoch(train) [145][2040/2119] lr: 4.0000e-04 eta: 0:52:19 time: 0.2759 data_time: 0.0217 memory: 5821 grad_norm: 5.5475 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8261 loss: 1.8261 2022/10/08 16:01:18 - mmengine - INFO - Epoch(train) [145][2060/2119] lr: 4.0000e-04 eta: 0:52:13 time: 0.2914 data_time: 0.0142 memory: 5821 grad_norm: 5.6117 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8611 loss: 1.8611 2022/10/08 16:01:25 - mmengine - INFO - Epoch(train) [145][2080/2119] lr: 4.0000e-04 eta: 0:52:07 time: 0.3081 data_time: 0.0195 memory: 5821 grad_norm: 5.6279 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9634 loss: 1.9634 2022/10/08 16:01:30 - mmengine - INFO - Epoch(train) [145][2100/2119] lr: 4.0000e-04 eta: 0:52:01 time: 0.2788 data_time: 0.0210 memory: 5821 grad_norm: 5.5209 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.6517 loss: 1.6517 2022/10/08 16:01:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 16:01:35 - mmengine - INFO - Epoch(train) [145][2119/2119] lr: 4.0000e-04 eta: 0:52:01 time: 0.2450 data_time: 0.0150 memory: 5821 grad_norm: 5.4596 top1_acc: 0.7000 top5_acc: 0.8000 loss_cls: 1.7759 loss: 1.7759 2022/10/08 16:01:41 - mmengine - INFO - Epoch(val) [145][20/137] eta: 0:00:38 time: 0.3296 data_time: 0.2620 memory: 1236 2022/10/08 16:01:46 - mmengine - INFO - Epoch(val) [145][40/137] eta: 0:00:22 time: 0.2286 data_time: 0.1627 memory: 1236 2022/10/08 16:01:52 - mmengine - INFO - Epoch(val) [145][60/137] eta: 0:00:21 time: 0.2829 data_time: 0.2184 memory: 1236 2022/10/08 16:01:56 - mmengine - INFO - Epoch(val) [145][80/137] eta: 0:00:11 time: 0.2087 data_time: 0.1448 memory: 1236 2022/10/08 16:02:01 - mmengine - INFO - Epoch(val) [145][100/137] eta: 0:00:09 time: 0.2665 data_time: 0.2009 memory: 1236 2022/10/08 16:02:05 - mmengine - INFO - Epoch(val) [145][120/137] eta: 0:00:03 time: 0.1874 data_time: 0.1212 memory: 1236 2022/10/08 16:02:18 - mmengine - INFO - Epoch(val) [145][137/137] acc/top1: 0.5613 acc/top5: 0.7822 acc/mean1: 0.5612 2022/10/08 16:02:18 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb/best_acc/top1_epoch_140.pth is removed 2022/10/08 16:02:19 - mmengine - INFO - The best checkpoint with 0.5613 acc/top1 at 145 epoch is saved to best_acc/top1_epoch_145.pth. 2022/10/08 16:02:27 - mmengine - INFO - Epoch(train) [146][20/2119] lr: 4.0000e-04 eta: 0:51:48 time: 0.3585 data_time: 0.1056 memory: 5821 grad_norm: 5.4906 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 1.8106 loss: 1.8106 2022/10/08 16:02:32 - mmengine - INFO - Epoch(train) [146][40/2119] lr: 4.0000e-04 eta: 0:51:42 time: 0.2550 data_time: 0.0135 memory: 5821 grad_norm: 5.5291 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7549 loss: 1.7549 2022/10/08 16:02:38 - mmengine - INFO - Epoch(train) [146][60/2119] lr: 4.0000e-04 eta: 0:51:36 time: 0.3371 data_time: 0.0196 memory: 5821 grad_norm: 5.5154 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8550 loss: 1.8550 2022/10/08 16:02:44 - mmengine - INFO - Epoch(train) [146][80/2119] lr: 4.0000e-04 eta: 0:51:30 time: 0.2722 data_time: 0.0259 memory: 5821 grad_norm: 5.5306 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7531 loss: 1.7531 2022/10/08 16:02:50 - mmengine - INFO - Epoch(train) [146][100/2119] lr: 4.0000e-04 eta: 0:51:25 time: 0.3009 data_time: 0.0232 memory: 5821 grad_norm: 5.5370 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.5768 loss: 1.5768 2022/10/08 16:02:56 - mmengine - INFO - Epoch(train) [146][120/2119] lr: 4.0000e-04 eta: 0:51:19 time: 0.2952 data_time: 0.0221 memory: 5821 grad_norm: 5.4875 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8293 loss: 1.8293 2022/10/08 16:03:01 - mmengine - INFO - Epoch(train) [146][140/2119] lr: 4.0000e-04 eta: 0:51:13 time: 0.2618 data_time: 0.0164 memory: 5821 grad_norm: 5.5003 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7612 loss: 1.7612 2022/10/08 16:03:06 - mmengine - INFO - Epoch(train) [146][160/2119] lr: 4.0000e-04 eta: 0:51:07 time: 0.2682 data_time: 0.0222 memory: 5821 grad_norm: 5.5607 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8924 loss: 1.8924 2022/10/08 16:03:12 - mmengine - INFO - Epoch(train) [146][180/2119] lr: 4.0000e-04 eta: 0:51:01 time: 0.2773 data_time: 0.0188 memory: 5821 grad_norm: 5.5541 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7998 loss: 1.7998 2022/10/08 16:03:18 - mmengine - INFO - Epoch(train) [146][200/2119] lr: 4.0000e-04 eta: 0:50:55 time: 0.2840 data_time: 0.0188 memory: 5821 grad_norm: 5.5369 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8691 loss: 1.8691 2022/10/08 16:03:24 - mmengine - INFO - Epoch(train) [146][220/2119] lr: 4.0000e-04 eta: 0:50:49 time: 0.3096 data_time: 0.0176 memory: 5821 grad_norm: 5.6001 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6973 loss: 1.6973 2022/10/08 16:03:30 - mmengine - INFO - Epoch(train) [146][240/2119] lr: 4.0000e-04 eta: 0:50:43 time: 0.2849 data_time: 0.0194 memory: 5821 grad_norm: 5.6194 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8661 loss: 1.8661 2022/10/08 16:03:36 - mmengine - INFO - Epoch(train) [146][260/2119] lr: 4.0000e-04 eta: 0:50:37 time: 0.3114 data_time: 0.0190 memory: 5821 grad_norm: 5.5291 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8115 loss: 1.8115 2022/10/08 16:03:42 - mmengine - INFO - Epoch(train) [146][280/2119] lr: 4.0000e-04 eta: 0:50:31 time: 0.2881 data_time: 0.0197 memory: 5821 grad_norm: 5.5533 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6664 loss: 1.6664 2022/10/08 16:03:47 - mmengine - INFO - Epoch(train) [146][300/2119] lr: 4.0000e-04 eta: 0:50:25 time: 0.2810 data_time: 0.0211 memory: 5821 grad_norm: 5.6487 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1314 loss: 2.1314 2022/10/08 16:03:53 - mmengine - INFO - Epoch(train) [146][320/2119] lr: 4.0000e-04 eta: 0:50:19 time: 0.3105 data_time: 0.0189 memory: 5821 grad_norm: 5.5329 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7558 loss: 1.7558 2022/10/08 16:03:59 - mmengine - INFO - Epoch(train) [146][340/2119] lr: 4.0000e-04 eta: 0:50:13 time: 0.2594 data_time: 0.0182 memory: 5821 grad_norm: 5.5119 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5111 loss: 1.5111 2022/10/08 16:04:05 - mmengine - INFO - Epoch(train) [146][360/2119] lr: 4.0000e-04 eta: 0:50:08 time: 0.2964 data_time: 0.0161 memory: 5821 grad_norm: 5.5489 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.6725 loss: 1.6725 2022/10/08 16:04:11 - mmengine - INFO - Epoch(train) [146][380/2119] lr: 4.0000e-04 eta: 0:50:02 time: 0.3166 data_time: 0.0184 memory: 5821 grad_norm: 5.5492 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8646 loss: 1.8646 2022/10/08 16:04:17 - mmengine - INFO - Epoch(train) [146][400/2119] lr: 4.0000e-04 eta: 0:49:56 time: 0.2842 data_time: 0.0193 memory: 5821 grad_norm: 5.6235 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7824 loss: 1.7824 2022/10/08 16:04:22 - mmengine - INFO - Epoch(train) [146][420/2119] lr: 4.0000e-04 eta: 0:49:50 time: 0.2605 data_time: 0.0191 memory: 5821 grad_norm: 5.4964 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.7929 loss: 1.7929 2022/10/08 16:04:27 - mmengine - INFO - Epoch(train) [146][440/2119] lr: 4.0000e-04 eta: 0:49:44 time: 0.2770 data_time: 0.0156 memory: 5821 grad_norm: 5.5487 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8346 loss: 1.8346 2022/10/08 16:04:34 - mmengine - INFO - Epoch(train) [146][460/2119] lr: 4.0000e-04 eta: 0:49:38 time: 0.3266 data_time: 0.0213 memory: 5821 grad_norm: 5.5942 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.8405 loss: 1.8405 2022/10/08 16:04:39 - mmengine - INFO - Epoch(train) [146][480/2119] lr: 4.0000e-04 eta: 0:49:32 time: 0.2669 data_time: 0.0241 memory: 5821 grad_norm: 5.5276 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9807 loss: 1.9807 2022/10/08 16:04:45 - mmengine - INFO - Epoch(train) [146][500/2119] lr: 4.0000e-04 eta: 0:49:26 time: 0.2736 data_time: 0.0199 memory: 5821 grad_norm: 5.4825 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.5689 loss: 1.5689 2022/10/08 16:04:50 - mmengine - INFO - Epoch(train) [146][520/2119] lr: 4.0000e-04 eta: 0:49:20 time: 0.2872 data_time: 0.0205 memory: 5821 grad_norm: 5.5245 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7362 loss: 1.7362 2022/10/08 16:04:57 - mmengine - INFO - Epoch(train) [146][540/2119] lr: 4.0000e-04 eta: 0:49:14 time: 0.2999 data_time: 0.0231 memory: 5821 grad_norm: 5.5873 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8518 loss: 1.8518 2022/10/08 16:05:02 - mmengine - INFO - Epoch(train) [146][560/2119] lr: 4.0000e-04 eta: 0:49:08 time: 0.2965 data_time: 0.0184 memory: 5821 grad_norm: 5.5279 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.6221 loss: 1.6221 2022/10/08 16:05:08 - mmengine - INFO - Epoch(train) [146][580/2119] lr: 4.0000e-04 eta: 0:49:02 time: 0.2820 data_time: 0.0264 memory: 5821 grad_norm: 5.5536 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7825 loss: 1.7825 2022/10/08 16:05:14 - mmengine - INFO - Epoch(train) [146][600/2119] lr: 4.0000e-04 eta: 0:48:56 time: 0.2743 data_time: 0.0163 memory: 5821 grad_norm: 5.6313 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9096 loss: 1.9096 2022/10/08 16:05:20 - mmengine - INFO - Epoch(train) [146][620/2119] lr: 4.0000e-04 eta: 0:48:51 time: 0.3076 data_time: 0.0221 memory: 5821 grad_norm: 5.5059 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9345 loss: 1.9345 2022/10/08 16:05:26 - mmengine - INFO - Epoch(train) [146][640/2119] lr: 4.0000e-04 eta: 0:48:45 time: 0.2967 data_time: 0.0174 memory: 5821 grad_norm: 5.5406 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.1270 loss: 2.1270 2022/10/08 16:05:31 - mmengine - INFO - Epoch(train) [146][660/2119] lr: 4.0000e-04 eta: 0:48:39 time: 0.2889 data_time: 0.0187 memory: 5821 grad_norm: 5.5953 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8988 loss: 1.8988 2022/10/08 16:05:37 - mmengine - INFO - Epoch(train) [146][680/2119] lr: 4.0000e-04 eta: 0:48:33 time: 0.2661 data_time: 0.0221 memory: 5821 grad_norm: 5.6359 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9024 loss: 1.9024 2022/10/08 16:05:42 - mmengine - INFO - Epoch(train) [146][700/2119] lr: 4.0000e-04 eta: 0:48:27 time: 0.2658 data_time: 0.0202 memory: 5821 grad_norm: 5.5390 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.7754 loss: 1.7754 2022/10/08 16:05:48 - mmengine - INFO - Epoch(train) [146][720/2119] lr: 4.0000e-04 eta: 0:48:21 time: 0.2983 data_time: 0.0167 memory: 5821 grad_norm: 5.6515 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8455 loss: 1.8455 2022/10/08 16:05:54 - mmengine - INFO - Epoch(train) [146][740/2119] lr: 4.0000e-04 eta: 0:48:15 time: 0.3050 data_time: 0.0218 memory: 5821 grad_norm: 5.4999 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.6607 loss: 1.6607 2022/10/08 16:05:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 16:06:00 - mmengine - INFO - Epoch(train) [146][760/2119] lr: 4.0000e-04 eta: 0:48:09 time: 0.2756 data_time: 0.0200 memory: 5821 grad_norm: 5.4669 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6791 loss: 1.6791 2022/10/08 16:06:06 - mmengine - INFO - Epoch(train) [146][780/2119] lr: 4.0000e-04 eta: 0:48:03 time: 0.2923 data_time: 0.0163 memory: 5821 grad_norm: 5.4953 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7891 loss: 1.7891 2022/10/08 16:06:12 - mmengine - INFO - Epoch(train) [146][800/2119] lr: 4.0000e-04 eta: 0:47:58 time: 0.3432 data_time: 0.0224 memory: 5821 grad_norm: 5.5448 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6085 loss: 1.6085 2022/10/08 16:06:18 - mmengine - INFO - Epoch(train) [146][820/2119] lr: 4.0000e-04 eta: 0:47:51 time: 0.2516 data_time: 0.0160 memory: 5821 grad_norm: 5.5827 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9023 loss: 1.9023 2022/10/08 16:06:23 - mmengine - INFO - Epoch(train) [146][840/2119] lr: 4.0000e-04 eta: 0:47:46 time: 0.2902 data_time: 0.0184 memory: 5821 grad_norm: 5.4341 top1_acc: 0.5000 top5_acc: 0.9375 loss_cls: 1.7885 loss: 1.7885 2022/10/08 16:06:29 - mmengine - INFO - Epoch(train) [146][860/2119] lr: 4.0000e-04 eta: 0:47:40 time: 0.2781 data_time: 0.0197 memory: 5821 grad_norm: 5.4212 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8128 loss: 1.8128 2022/10/08 16:06:34 - mmengine - INFO - Epoch(train) [146][880/2119] lr: 4.0000e-04 eta: 0:47:34 time: 0.2732 data_time: 0.0199 memory: 5821 grad_norm: 5.4394 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.8188 loss: 1.8188 2022/10/08 16:06:40 - mmengine - INFO - Epoch(train) [146][900/2119] lr: 4.0000e-04 eta: 0:47:28 time: 0.2934 data_time: 0.0251 memory: 5821 grad_norm: 5.5898 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8404 loss: 1.8404 2022/10/08 16:06:46 - mmengine - INFO - Epoch(train) [146][920/2119] lr: 4.0000e-04 eta: 0:47:22 time: 0.2950 data_time: 0.0161 memory: 5821 grad_norm: 5.6254 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7486 loss: 1.7486 2022/10/08 16:06:52 - mmengine - INFO - Epoch(train) [146][940/2119] lr: 4.0000e-04 eta: 0:47:16 time: 0.2699 data_time: 0.0232 memory: 5821 grad_norm: 5.5262 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8676 loss: 1.8676 2022/10/08 16:06:57 - mmengine - INFO - Epoch(train) [146][960/2119] lr: 4.0000e-04 eta: 0:47:10 time: 0.2773 data_time: 0.0159 memory: 5821 grad_norm: 5.5258 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7928 loss: 1.7928 2022/10/08 16:07:03 - mmengine - INFO - Epoch(train) [146][980/2119] lr: 4.0000e-04 eta: 0:47:04 time: 0.2934 data_time: 0.0152 memory: 5821 grad_norm: 5.4906 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6912 loss: 1.6912 2022/10/08 16:07:09 - mmengine - INFO - Epoch(train) [146][1000/2119] lr: 4.0000e-04 eta: 0:46:58 time: 0.3034 data_time: 0.0182 memory: 5821 grad_norm: 5.6149 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6181 loss: 1.6181 2022/10/08 16:07:14 - mmengine - INFO - Epoch(train) [146][1020/2119] lr: 4.0000e-04 eta: 0:46:52 time: 0.2685 data_time: 0.0217 memory: 5821 grad_norm: 5.5397 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9242 loss: 1.9242 2022/10/08 16:07:20 - mmengine - INFO - Epoch(train) [146][1040/2119] lr: 4.0000e-04 eta: 0:46:46 time: 0.2853 data_time: 0.0194 memory: 5821 grad_norm: 5.5948 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9478 loss: 1.9478 2022/10/08 16:07:26 - mmengine - INFO - Epoch(train) [146][1060/2119] lr: 4.0000e-04 eta: 0:46:40 time: 0.3046 data_time: 0.0190 memory: 5821 grad_norm: 5.4900 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 1.6486 loss: 1.6486 2022/10/08 16:07:32 - mmengine - INFO - Epoch(train) [146][1080/2119] lr: 4.0000e-04 eta: 0:46:34 time: 0.2677 data_time: 0.0221 memory: 5821 grad_norm: 5.5818 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8862 loss: 1.8862 2022/10/08 16:07:37 - mmengine - INFO - Epoch(train) [146][1100/2119] lr: 4.0000e-04 eta: 0:46:28 time: 0.2784 data_time: 0.0174 memory: 5821 grad_norm: 5.5527 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8197 loss: 1.8197 2022/10/08 16:07:44 - mmengine - INFO - Epoch(train) [146][1120/2119] lr: 4.0000e-04 eta: 0:46:23 time: 0.3139 data_time: 0.0224 memory: 5821 grad_norm: 5.5197 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7275 loss: 1.7275 2022/10/08 16:07:49 - mmengine - INFO - Epoch(train) [146][1140/2119] lr: 4.0000e-04 eta: 0:46:17 time: 0.2793 data_time: 0.0167 memory: 5821 grad_norm: 5.4706 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8247 loss: 1.8247 2022/10/08 16:07:59 - mmengine - INFO - Epoch(train) [146][1160/2119] lr: 4.0000e-04 eta: 0:46:12 time: 0.5063 data_time: 0.0582 memory: 5821 grad_norm: 5.6077 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7335 loss: 1.7335 2022/10/08 16:08:05 - mmengine - INFO - Epoch(train) [146][1180/2119] lr: 4.0000e-04 eta: 0:46:06 time: 0.2923 data_time: 0.0261 memory: 5821 grad_norm: 5.6144 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7828 loss: 1.7828 2022/10/08 16:08:11 - mmengine - INFO - Epoch(train) [146][1200/2119] lr: 4.0000e-04 eta: 0:46:00 time: 0.2710 data_time: 0.0223 memory: 5821 grad_norm: 5.6122 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8531 loss: 1.8531 2022/10/08 16:08:20 - mmengine - INFO - Epoch(train) [146][1220/2119] lr: 4.0000e-04 eta: 0:45:55 time: 0.4617 data_time: 0.0215 memory: 5821 grad_norm: 5.5187 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8620 loss: 1.8620 2022/10/08 16:08:25 - mmengine - INFO - Epoch(train) [146][1240/2119] lr: 4.0000e-04 eta: 0:45:49 time: 0.2557 data_time: 0.0198 memory: 5821 grad_norm: 5.5821 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9110 loss: 1.9110 2022/10/08 16:08:30 - mmengine - INFO - Epoch(train) [146][1260/2119] lr: 4.0000e-04 eta: 0:45:43 time: 0.2723 data_time: 0.0215 memory: 5821 grad_norm: 5.5623 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.8550 loss: 1.8550 2022/10/08 16:08:37 - mmengine - INFO - Epoch(train) [146][1280/2119] lr: 4.0000e-04 eta: 0:45:38 time: 0.3135 data_time: 0.0212 memory: 5821 grad_norm: 5.5831 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9612 loss: 1.9612 2022/10/08 16:08:43 - mmengine - INFO - Epoch(train) [146][1300/2119] lr: 4.0000e-04 eta: 0:45:32 time: 0.3046 data_time: 0.0179 memory: 5821 grad_norm: 5.6730 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7961 loss: 1.7961 2022/10/08 16:08:49 - mmengine - INFO - Epoch(train) [146][1320/2119] lr: 4.0000e-04 eta: 0:45:26 time: 0.3095 data_time: 0.0180 memory: 5821 grad_norm: 5.5344 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9290 loss: 1.9290 2022/10/08 16:08:54 - mmengine - INFO - Epoch(train) [146][1340/2119] lr: 4.0000e-04 eta: 0:45:20 time: 0.2527 data_time: 0.0208 memory: 5821 grad_norm: 5.5689 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8380 loss: 1.8380 2022/10/08 16:08:59 - mmengine - INFO - Epoch(train) [146][1360/2119] lr: 4.0000e-04 eta: 0:45:14 time: 0.2614 data_time: 0.0189 memory: 5821 grad_norm: 5.5180 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7655 loss: 1.7655 2022/10/08 16:09:05 - mmengine - INFO - Epoch(train) [146][1380/2119] lr: 4.0000e-04 eta: 0:45:08 time: 0.3081 data_time: 0.0228 memory: 5821 grad_norm: 5.5856 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7464 loss: 1.7464 2022/10/08 16:09:11 - mmengine - INFO - Epoch(train) [146][1400/2119] lr: 4.0000e-04 eta: 0:45:02 time: 0.2748 data_time: 0.0198 memory: 5821 grad_norm: 5.4992 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6892 loss: 1.6892 2022/10/08 16:09:16 - mmengine - INFO - Epoch(train) [146][1420/2119] lr: 4.0000e-04 eta: 0:44:56 time: 0.2654 data_time: 0.0183 memory: 5821 grad_norm: 5.6153 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8727 loss: 1.8727 2022/10/08 16:09:23 - mmengine - INFO - Epoch(train) [146][1440/2119] lr: 4.0000e-04 eta: 0:44:50 time: 0.3229 data_time: 0.0206 memory: 5821 grad_norm: 5.4764 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5081 loss: 1.5081 2022/10/08 16:09:29 - mmengine - INFO - Epoch(train) [146][1460/2119] lr: 4.0000e-04 eta: 0:44:44 time: 0.2899 data_time: 0.0206 memory: 5821 grad_norm: 5.4701 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.8571 loss: 1.8571 2022/10/08 16:09:34 - mmengine - INFO - Epoch(train) [146][1480/2119] lr: 4.0000e-04 eta: 0:44:38 time: 0.2808 data_time: 0.0134 memory: 5821 grad_norm: 5.5949 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8022 loss: 1.8022 2022/10/08 16:09:40 - mmengine - INFO - Epoch(train) [146][1500/2119] lr: 4.0000e-04 eta: 0:44:32 time: 0.2962 data_time: 0.0255 memory: 5821 grad_norm: 5.6524 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.7475 loss: 1.7475 2022/10/08 16:09:46 - mmengine - INFO - Epoch(train) [146][1520/2119] lr: 4.0000e-04 eta: 0:44:27 time: 0.2907 data_time: 0.0227 memory: 5821 grad_norm: 5.6082 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7587 loss: 1.7587 2022/10/08 16:09:52 - mmengine - INFO - Epoch(train) [146][1540/2119] lr: 4.0000e-04 eta: 0:44:21 time: 0.2861 data_time: 0.0193 memory: 5821 grad_norm: 5.5723 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.6996 loss: 1.6996 2022/10/08 16:09:57 - mmengine - INFO - Epoch(train) [146][1560/2119] lr: 4.0000e-04 eta: 0:44:15 time: 0.2630 data_time: 0.0171 memory: 5821 grad_norm: 5.5709 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0374 loss: 2.0374 2022/10/08 16:10:03 - mmengine - INFO - Epoch(train) [146][1580/2119] lr: 4.0000e-04 eta: 0:44:09 time: 0.3093 data_time: 0.0168 memory: 5821 grad_norm: 5.5285 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7552 loss: 1.7552 2022/10/08 16:10:09 - mmengine - INFO - Epoch(train) [146][1600/2119] lr: 4.0000e-04 eta: 0:44:03 time: 0.2760 data_time: 0.0187 memory: 5821 grad_norm: 5.5901 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9315 loss: 1.9315 2022/10/08 16:10:15 - mmengine - INFO - Epoch(train) [146][1620/2119] lr: 4.0000e-04 eta: 0:43:57 time: 0.3084 data_time: 0.0173 memory: 5821 grad_norm: 5.5665 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.6723 loss: 1.6723 2022/10/08 16:10:20 - mmengine - INFO - Epoch(train) [146][1640/2119] lr: 4.0000e-04 eta: 0:43:51 time: 0.2638 data_time: 0.0211 memory: 5821 grad_norm: 5.6430 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8428 loss: 1.8428 2022/10/08 16:10:27 - mmengine - INFO - Epoch(train) [146][1660/2119] lr: 4.0000e-04 eta: 0:43:45 time: 0.3196 data_time: 0.0260 memory: 5821 grad_norm: 5.5730 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9658 loss: 1.9658 2022/10/08 16:10:32 - mmengine - INFO - Epoch(train) [146][1680/2119] lr: 4.0000e-04 eta: 0:43:39 time: 0.2731 data_time: 0.0165 memory: 5821 grad_norm: 5.5231 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8393 loss: 1.8393 2022/10/08 16:10:37 - mmengine - INFO - Epoch(train) [146][1700/2119] lr: 4.0000e-04 eta: 0:43:33 time: 0.2634 data_time: 0.0168 memory: 5821 grad_norm: 5.5547 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.7674 loss: 1.7674 2022/10/08 16:10:44 - mmengine - INFO - Epoch(train) [146][1720/2119] lr: 4.0000e-04 eta: 0:43:27 time: 0.3187 data_time: 0.0239 memory: 5821 grad_norm: 5.5693 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7764 loss: 1.7764 2022/10/08 16:10:49 - mmengine - INFO - Epoch(train) [146][1740/2119] lr: 4.0000e-04 eta: 0:43:21 time: 0.2780 data_time: 0.0181 memory: 5821 grad_norm: 5.5933 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6364 loss: 1.6364 2022/10/08 16:10:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 16:10:55 - mmengine - INFO - Epoch(train) [146][1760/2119] lr: 4.0000e-04 eta: 0:43:16 time: 0.2871 data_time: 0.0185 memory: 5821 grad_norm: 5.5879 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8005 loss: 1.8005 2022/10/08 16:11:00 - mmengine - INFO - Epoch(train) [146][1780/2119] lr: 4.0000e-04 eta: 0:43:10 time: 0.2745 data_time: 0.0178 memory: 5821 grad_norm: 5.6462 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.8050 loss: 1.8050 2022/10/08 16:11:07 - mmengine - INFO - Epoch(train) [146][1800/2119] lr: 4.0000e-04 eta: 0:43:04 time: 0.3157 data_time: 0.0186 memory: 5821 grad_norm: 5.4069 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7080 loss: 1.7080 2022/10/08 16:11:12 - mmengine - INFO - Epoch(train) [146][1820/2119] lr: 4.0000e-04 eta: 0:42:58 time: 0.2749 data_time: 0.0175 memory: 5821 grad_norm: 5.5334 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8638 loss: 1.8638 2022/10/08 16:11:18 - mmengine - INFO - Epoch(train) [146][1840/2119] lr: 4.0000e-04 eta: 0:42:52 time: 0.2693 data_time: 0.0160 memory: 5821 grad_norm: 5.5197 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8193 loss: 1.8193 2022/10/08 16:11:24 - mmengine - INFO - Epoch(train) [146][1860/2119] lr: 4.0000e-04 eta: 0:42:46 time: 0.2965 data_time: 0.0252 memory: 5821 grad_norm: 5.6951 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9314 loss: 1.9314 2022/10/08 16:11:29 - mmengine - INFO - Epoch(train) [146][1880/2119] lr: 4.0000e-04 eta: 0:42:40 time: 0.2866 data_time: 0.0162 memory: 5821 grad_norm: 5.5663 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7546 loss: 1.7546 2022/10/08 16:11:35 - mmengine - INFO - Epoch(train) [146][1900/2119] lr: 4.0000e-04 eta: 0:42:34 time: 0.2769 data_time: 0.0156 memory: 5821 grad_norm: 5.5730 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6615 loss: 1.6615 2022/10/08 16:11:41 - mmengine - INFO - Epoch(train) [146][1920/2119] lr: 4.0000e-04 eta: 0:42:28 time: 0.3020 data_time: 0.0190 memory: 5821 grad_norm: 5.5713 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.6109 loss: 1.6109 2022/10/08 16:11:47 - mmengine - INFO - Epoch(train) [146][1940/2119] lr: 4.0000e-04 eta: 0:42:22 time: 0.2893 data_time: 0.0239 memory: 5821 grad_norm: 5.6283 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7346 loss: 1.7346 2022/10/08 16:11:53 - mmengine - INFO - Epoch(train) [146][1960/2119] lr: 4.0000e-04 eta: 0:42:16 time: 0.2964 data_time: 0.0199 memory: 5821 grad_norm: 5.5899 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9387 loss: 1.9387 2022/10/08 16:11:59 - mmengine - INFO - Epoch(train) [146][1980/2119] lr: 4.0000e-04 eta: 0:42:11 time: 0.3010 data_time: 0.0225 memory: 5821 grad_norm: 5.6272 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.6832 loss: 1.6832 2022/10/08 16:12:05 - mmengine - INFO - Epoch(train) [146][2000/2119] lr: 4.0000e-04 eta: 0:42:05 time: 0.3093 data_time: 0.0203 memory: 5821 grad_norm: 5.6111 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8018 loss: 1.8018 2022/10/08 16:12:10 - mmengine - INFO - Epoch(train) [146][2020/2119] lr: 4.0000e-04 eta: 0:41:59 time: 0.2508 data_time: 0.0186 memory: 5821 grad_norm: 5.6697 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8186 loss: 1.8186 2022/10/08 16:12:16 - mmengine - INFO - Epoch(train) [146][2040/2119] lr: 4.0000e-04 eta: 0:41:53 time: 0.3017 data_time: 0.0193 memory: 5821 grad_norm: 5.5333 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7842 loss: 1.7842 2022/10/08 16:12:21 - mmengine - INFO - Epoch(train) [146][2060/2119] lr: 4.0000e-04 eta: 0:41:47 time: 0.2665 data_time: 0.0191 memory: 5821 grad_norm: 5.4994 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.4981 loss: 1.4981 2022/10/08 16:12:27 - mmengine - INFO - Epoch(train) [146][2080/2119] lr: 4.0000e-04 eta: 0:41:41 time: 0.2982 data_time: 0.0188 memory: 5821 grad_norm: 5.5201 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8762 loss: 1.8762 2022/10/08 16:12:33 - mmengine - INFO - Epoch(train) [146][2100/2119] lr: 4.0000e-04 eta: 0:41:35 time: 0.2656 data_time: 0.0165 memory: 5821 grad_norm: 5.7083 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.5954 loss: 1.5954 2022/10/08 16:12:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 16:12:38 - mmengine - INFO - Epoch(train) [146][2119/2119] lr: 4.0000e-04 eta: 0:41:35 time: 0.2627 data_time: 0.0143 memory: 5821 grad_norm: 5.6547 top1_acc: 0.5000 top5_acc: 0.7000 loss_cls: 1.8573 loss: 1.8573 2022/10/08 16:12:46 - mmengine - INFO - Epoch(train) [147][20/2119] lr: 4.0000e-04 eta: 0:41:23 time: 0.4123 data_time: 0.1006 memory: 5821 grad_norm: 5.5375 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8781 loss: 1.8781 2022/10/08 16:12:52 - mmengine - INFO - Epoch(train) [147][40/2119] lr: 4.0000e-04 eta: 0:41:17 time: 0.3121 data_time: 0.0209 memory: 5821 grad_norm: 5.4980 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.4170 loss: 1.4170 2022/10/08 16:12:58 - mmengine - INFO - Epoch(train) [147][60/2119] lr: 4.0000e-04 eta: 0:41:11 time: 0.2876 data_time: 0.0249 memory: 5821 grad_norm: 5.4830 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8686 loss: 1.8686 2022/10/08 16:13:04 - mmengine - INFO - Epoch(train) [147][80/2119] lr: 4.0000e-04 eta: 0:41:05 time: 0.3067 data_time: 0.0227 memory: 5821 grad_norm: 5.5281 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8506 loss: 1.8506 2022/10/08 16:13:09 - mmengine - INFO - Epoch(train) [147][100/2119] lr: 4.0000e-04 eta: 0:40:59 time: 0.2573 data_time: 0.0170 memory: 5821 grad_norm: 5.5299 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.7370 loss: 1.7370 2022/10/08 16:13:15 - mmengine - INFO - Epoch(train) [147][120/2119] lr: 4.0000e-04 eta: 0:40:53 time: 0.3021 data_time: 0.0186 memory: 5821 grad_norm: 5.5173 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7557 loss: 1.7557 2022/10/08 16:13:21 - mmengine - INFO - Epoch(train) [147][140/2119] lr: 4.0000e-04 eta: 0:40:47 time: 0.3021 data_time: 0.0209 memory: 5821 grad_norm: 5.5508 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8345 loss: 1.8345 2022/10/08 16:13:27 - mmengine - INFO - Epoch(train) [147][160/2119] lr: 4.0000e-04 eta: 0:40:41 time: 0.2806 data_time: 0.0247 memory: 5821 grad_norm: 5.6107 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8470 loss: 1.8470 2022/10/08 16:13:33 - mmengine - INFO - Epoch(train) [147][180/2119] lr: 4.0000e-04 eta: 0:40:35 time: 0.2826 data_time: 0.0258 memory: 5821 grad_norm: 5.5959 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.9100 loss: 1.9100 2022/10/08 16:13:38 - mmengine - INFO - Epoch(train) [147][200/2119] lr: 4.0000e-04 eta: 0:40:30 time: 0.2787 data_time: 0.0197 memory: 5821 grad_norm: 5.6345 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7836 loss: 1.7836 2022/10/08 16:13:44 - mmengine - INFO - Epoch(train) [147][220/2119] lr: 4.0000e-04 eta: 0:40:24 time: 0.2850 data_time: 0.0250 memory: 5821 grad_norm: 5.6570 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7294 loss: 1.7294 2022/10/08 16:13:50 - mmengine - INFO - Epoch(train) [147][240/2119] lr: 4.0000e-04 eta: 0:40:18 time: 0.2794 data_time: 0.0194 memory: 5821 grad_norm: 5.5317 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.8346 loss: 1.8346 2022/10/08 16:13:56 - mmengine - INFO - Epoch(train) [147][260/2119] lr: 4.0000e-04 eta: 0:40:12 time: 0.3005 data_time: 0.0169 memory: 5821 grad_norm: 5.4266 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5626 loss: 1.5626 2022/10/08 16:14:01 - mmengine - INFO - Epoch(train) [147][280/2119] lr: 4.0000e-04 eta: 0:40:06 time: 0.2832 data_time: 0.0151 memory: 5821 grad_norm: 5.5940 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 1.7476 loss: 1.7476 2022/10/08 16:14:07 - mmengine - INFO - Epoch(train) [147][300/2119] lr: 4.0000e-04 eta: 0:40:00 time: 0.2835 data_time: 0.0239 memory: 5821 grad_norm: 5.6283 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6647 loss: 1.6647 2022/10/08 16:14:13 - mmengine - INFO - Epoch(train) [147][320/2119] lr: 4.0000e-04 eta: 0:39:54 time: 0.2932 data_time: 0.0245 memory: 5821 grad_norm: 5.4508 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6645 loss: 1.6645 2022/10/08 16:14:19 - mmengine - INFO - Epoch(train) [147][340/2119] lr: 4.0000e-04 eta: 0:39:48 time: 0.2972 data_time: 0.0151 memory: 5821 grad_norm: 5.4950 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 1.6334 loss: 1.6334 2022/10/08 16:14:24 - mmengine - INFO - Epoch(train) [147][360/2119] lr: 4.0000e-04 eta: 0:39:42 time: 0.2735 data_time: 0.0227 memory: 5821 grad_norm: 5.5920 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6857 loss: 1.6857 2022/10/08 16:14:30 - mmengine - INFO - Epoch(train) [147][380/2119] lr: 4.0000e-04 eta: 0:39:36 time: 0.2927 data_time: 0.0232 memory: 5821 grad_norm: 5.5592 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8097 loss: 1.8097 2022/10/08 16:14:35 - mmengine - INFO - Epoch(train) [147][400/2119] lr: 4.0000e-04 eta: 0:39:30 time: 0.2651 data_time: 0.0184 memory: 5821 grad_norm: 5.7244 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7932 loss: 1.7932 2022/10/08 16:14:41 - mmengine - INFO - Epoch(train) [147][420/2119] lr: 4.0000e-04 eta: 0:39:24 time: 0.2903 data_time: 0.0307 memory: 5821 grad_norm: 5.4859 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6409 loss: 1.6409 2022/10/08 16:14:47 - mmengine - INFO - Epoch(train) [147][440/2119] lr: 4.0000e-04 eta: 0:39:19 time: 0.2939 data_time: 0.0169 memory: 5821 grad_norm: 5.4353 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.6105 loss: 1.6105 2022/10/08 16:14:54 - mmengine - INFO - Epoch(train) [147][460/2119] lr: 4.0000e-04 eta: 0:39:13 time: 0.3632 data_time: 0.0197 memory: 5821 grad_norm: 5.4921 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.6269 loss: 1.6269 2022/10/08 16:15:00 - mmengine - INFO - Epoch(train) [147][480/2119] lr: 4.0000e-04 eta: 0:39:07 time: 0.2626 data_time: 0.0152 memory: 5821 grad_norm: 5.5987 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1205 loss: 2.1205 2022/10/08 16:15:05 - mmengine - INFO - Epoch(train) [147][500/2119] lr: 4.0000e-04 eta: 0:39:01 time: 0.2593 data_time: 0.0219 memory: 5821 grad_norm: 5.6148 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7658 loss: 1.7658 2022/10/08 16:15:11 - mmengine - INFO - Epoch(train) [147][520/2119] lr: 4.0000e-04 eta: 0:38:55 time: 0.3037 data_time: 0.0190 memory: 5821 grad_norm: 5.4529 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7958 loss: 1.7958 2022/10/08 16:15:17 - mmengine - INFO - Epoch(train) [147][540/2119] lr: 4.0000e-04 eta: 0:38:49 time: 0.2819 data_time: 0.0314 memory: 5821 grad_norm: 5.5843 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7878 loss: 1.7878 2022/10/08 16:15:22 - mmengine - INFO - Epoch(train) [147][560/2119] lr: 4.0000e-04 eta: 0:38:43 time: 0.2866 data_time: 0.0218 memory: 5821 grad_norm: 5.5825 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.8101 loss: 1.8101 2022/10/08 16:15:28 - mmengine - INFO - Epoch(train) [147][580/2119] lr: 4.0000e-04 eta: 0:38:37 time: 0.2844 data_time: 0.0201 memory: 5821 grad_norm: 5.4471 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7136 loss: 1.7136 2022/10/08 16:15:35 - mmengine - INFO - Epoch(train) [147][600/2119] lr: 4.0000e-04 eta: 0:38:32 time: 0.3527 data_time: 0.0417 memory: 5821 grad_norm: 5.6025 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6804 loss: 1.6804 2022/10/08 16:15:42 - mmengine - INFO - Epoch(train) [147][620/2119] lr: 4.0000e-04 eta: 0:38:26 time: 0.3230 data_time: 0.0274 memory: 5821 grad_norm: 5.6196 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7053 loss: 1.7053 2022/10/08 16:15:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 16:15:47 - mmengine - INFO - Epoch(train) [147][640/2119] lr: 4.0000e-04 eta: 0:38:20 time: 0.2578 data_time: 0.0155 memory: 5821 grad_norm: 5.5660 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9657 loss: 1.9657 2022/10/08 16:15:53 - mmengine - INFO - Epoch(train) [147][660/2119] lr: 4.0000e-04 eta: 0:38:14 time: 0.3278 data_time: 0.0288 memory: 5821 grad_norm: 5.5869 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8213 loss: 1.8213 2022/10/08 16:15:59 - mmengine - INFO - Epoch(train) [147][680/2119] lr: 4.0000e-04 eta: 0:38:09 time: 0.3036 data_time: 0.0169 memory: 5821 grad_norm: 5.6191 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8656 loss: 1.8656 2022/10/08 16:16:06 - mmengine - INFO - Epoch(train) [147][700/2119] lr: 4.0000e-04 eta: 0:38:03 time: 0.3066 data_time: 0.0474 memory: 5821 grad_norm: 5.5829 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6840 loss: 1.6840 2022/10/08 16:16:11 - mmengine - INFO - Epoch(train) [147][720/2119] lr: 4.0000e-04 eta: 0:37:57 time: 0.2562 data_time: 0.0194 memory: 5821 grad_norm: 5.4804 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6820 loss: 1.6820 2022/10/08 16:16:16 - mmengine - INFO - Epoch(train) [147][740/2119] lr: 4.0000e-04 eta: 0:37:51 time: 0.2723 data_time: 0.0229 memory: 5821 grad_norm: 5.5787 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.7737 loss: 1.7737 2022/10/08 16:16:22 - mmengine - INFO - Epoch(train) [147][760/2119] lr: 4.0000e-04 eta: 0:37:45 time: 0.3106 data_time: 0.0197 memory: 5821 grad_norm: 5.5417 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9553 loss: 1.9553 2022/10/08 16:16:28 - mmengine - INFO - Epoch(train) [147][780/2119] lr: 4.0000e-04 eta: 0:37:39 time: 0.2854 data_time: 0.0189 memory: 5821 grad_norm: 5.6727 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8734 loss: 1.8734 2022/10/08 16:16:35 - mmengine - INFO - Epoch(train) [147][800/2119] lr: 4.0000e-04 eta: 0:37:33 time: 0.3320 data_time: 0.0236 memory: 5821 grad_norm: 5.4906 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7581 loss: 1.7581 2022/10/08 16:16:40 - mmengine - INFO - Epoch(train) [147][820/2119] lr: 4.0000e-04 eta: 0:37:27 time: 0.2737 data_time: 0.0209 memory: 5821 grad_norm: 5.5808 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7362 loss: 1.7362 2022/10/08 16:16:45 - mmengine - INFO - Epoch(train) [147][840/2119] lr: 4.0000e-04 eta: 0:37:21 time: 0.2579 data_time: 0.0160 memory: 5821 grad_norm: 5.6448 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9276 loss: 1.9276 2022/10/08 16:16:51 - mmengine - INFO - Epoch(train) [147][860/2119] lr: 4.0000e-04 eta: 0:37:15 time: 0.3041 data_time: 0.0244 memory: 5821 grad_norm: 5.6739 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.5168 loss: 1.5168 2022/10/08 16:17:00 - mmengine - INFO - Epoch(train) [147][880/2119] lr: 4.0000e-04 eta: 0:37:10 time: 0.4242 data_time: 0.0202 memory: 5821 grad_norm: 5.5358 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9783 loss: 1.9783 2022/10/08 16:17:05 - mmengine - INFO - Epoch(train) [147][900/2119] lr: 4.0000e-04 eta: 0:37:04 time: 0.2530 data_time: 0.0209 memory: 5821 grad_norm: 5.6681 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6768 loss: 1.6768 2022/10/08 16:17:16 - mmengine - INFO - Epoch(train) [147][920/2119] lr: 4.0000e-04 eta: 0:36:59 time: 0.4910 data_time: 0.0181 memory: 5821 grad_norm: 5.5877 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9114 loss: 1.9114 2022/10/08 16:17:21 - mmengine - INFO - Epoch(train) [147][940/2119] lr: 4.0000e-04 eta: 0:36:54 time: 0.3282 data_time: 0.0775 memory: 5821 grad_norm: 5.4978 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7476 loss: 1.7476 2022/10/08 16:17:27 - mmengine - INFO - Epoch(train) [147][960/2119] lr: 4.0000e-04 eta: 0:36:48 time: 0.2523 data_time: 0.0165 memory: 5821 grad_norm: 5.5633 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8600 loss: 1.8600 2022/10/08 16:17:33 - mmengine - INFO - Epoch(train) [147][980/2119] lr: 4.0000e-04 eta: 0:36:42 time: 0.3162 data_time: 0.0217 memory: 5821 grad_norm: 5.6071 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.6494 loss: 1.6494 2022/10/08 16:17:38 - mmengine - INFO - Epoch(train) [147][1000/2119] lr: 4.0000e-04 eta: 0:36:36 time: 0.2586 data_time: 0.0212 memory: 5821 grad_norm: 5.6287 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9617 loss: 1.9617 2022/10/08 16:17:44 - mmengine - INFO - Epoch(train) [147][1020/2119] lr: 4.0000e-04 eta: 0:36:30 time: 0.2828 data_time: 0.0192 memory: 5821 grad_norm: 5.6218 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8492 loss: 1.8492 2022/10/08 16:17:50 - mmengine - INFO - Epoch(train) [147][1040/2119] lr: 4.0000e-04 eta: 0:36:24 time: 0.2916 data_time: 0.0185 memory: 5821 grad_norm: 5.6608 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8077 loss: 1.8077 2022/10/08 16:17:56 - mmengine - INFO - Epoch(train) [147][1060/2119] lr: 4.0000e-04 eta: 0:36:18 time: 0.3116 data_time: 0.0193 memory: 5821 grad_norm: 5.6475 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.6227 loss: 1.6227 2022/10/08 16:18:01 - mmengine - INFO - Epoch(train) [147][1080/2119] lr: 4.0000e-04 eta: 0:36:12 time: 0.2567 data_time: 0.0179 memory: 5821 grad_norm: 5.5746 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8595 loss: 1.8595 2022/10/08 16:18:07 - mmengine - INFO - Epoch(train) [147][1100/2119] lr: 4.0000e-04 eta: 0:36:06 time: 0.3049 data_time: 0.0190 memory: 5821 grad_norm: 5.5558 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.7698 loss: 1.7698 2022/10/08 16:18:13 - mmengine - INFO - Epoch(train) [147][1120/2119] lr: 4.0000e-04 eta: 0:36:00 time: 0.2770 data_time: 0.0165 memory: 5821 grad_norm: 5.5656 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6388 loss: 1.6388 2022/10/08 16:18:19 - mmengine - INFO - Epoch(train) [147][1140/2119] lr: 4.0000e-04 eta: 0:35:54 time: 0.2971 data_time: 0.0184 memory: 5821 grad_norm: 5.5457 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7439 loss: 1.7439 2022/10/08 16:18:24 - mmengine - INFO - Epoch(train) [147][1160/2119] lr: 4.0000e-04 eta: 0:35:48 time: 0.2840 data_time: 0.0246 memory: 5821 grad_norm: 5.6477 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 1.8499 loss: 1.8499 2022/10/08 16:18:30 - mmengine - INFO - Epoch(train) [147][1180/2119] lr: 4.0000e-04 eta: 0:35:43 time: 0.2837 data_time: 0.0175 memory: 5821 grad_norm: 5.5606 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6674 loss: 1.6674 2022/10/08 16:18:36 - mmengine - INFO - Epoch(train) [147][1200/2119] lr: 4.0000e-04 eta: 0:35:37 time: 0.3001 data_time: 0.0210 memory: 5821 grad_norm: 5.6200 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7867 loss: 1.7867 2022/10/08 16:18:42 - mmengine - INFO - Epoch(train) [147][1220/2119] lr: 4.0000e-04 eta: 0:35:31 time: 0.2988 data_time: 0.0152 memory: 5821 grad_norm: 5.6746 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1035 loss: 2.1035 2022/10/08 16:18:48 - mmengine - INFO - Epoch(train) [147][1240/2119] lr: 4.0000e-04 eta: 0:35:25 time: 0.2818 data_time: 0.0187 memory: 5821 grad_norm: 5.6495 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9339 loss: 1.9339 2022/10/08 16:18:54 - mmengine - INFO - Epoch(train) [147][1260/2119] lr: 4.0000e-04 eta: 0:35:19 time: 0.2962 data_time: 0.0227 memory: 5821 grad_norm: 5.6077 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8068 loss: 1.8068 2022/10/08 16:18:59 - mmengine - INFO - Epoch(train) [147][1280/2119] lr: 4.0000e-04 eta: 0:35:13 time: 0.2523 data_time: 0.0235 memory: 5821 grad_norm: 5.4219 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8065 loss: 1.8065 2022/10/08 16:19:05 - mmengine - INFO - Epoch(train) [147][1300/2119] lr: 4.0000e-04 eta: 0:35:07 time: 0.3092 data_time: 0.0224 memory: 5821 grad_norm: 5.5434 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7551 loss: 1.7551 2022/10/08 16:19:10 - mmengine - INFO - Epoch(train) [147][1320/2119] lr: 4.0000e-04 eta: 0:35:01 time: 0.2860 data_time: 0.0198 memory: 5821 grad_norm: 5.6273 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9581 loss: 1.9581 2022/10/08 16:19:16 - mmengine - INFO - Epoch(train) [147][1340/2119] lr: 4.0000e-04 eta: 0:34:55 time: 0.2975 data_time: 0.0237 memory: 5821 grad_norm: 5.6563 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7129 loss: 1.7129 2022/10/08 16:19:23 - mmengine - INFO - Epoch(train) [147][1360/2119] lr: 4.0000e-04 eta: 0:34:50 time: 0.3174 data_time: 0.0271 memory: 5821 grad_norm: 5.5767 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6354 loss: 1.6354 2022/10/08 16:19:28 - mmengine - INFO - Epoch(train) [147][1380/2119] lr: 4.0000e-04 eta: 0:34:44 time: 0.2574 data_time: 0.0233 memory: 5821 grad_norm: 5.6199 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9320 loss: 1.9320 2022/10/08 16:19:33 - mmengine - INFO - Epoch(train) [147][1400/2119] lr: 4.0000e-04 eta: 0:34:38 time: 0.2602 data_time: 0.0200 memory: 5821 grad_norm: 5.6973 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9900 loss: 1.9900 2022/10/08 16:19:40 - mmengine - INFO - Epoch(train) [147][1420/2119] lr: 4.0000e-04 eta: 0:34:32 time: 0.3243 data_time: 0.0209 memory: 5821 grad_norm: 5.6059 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8922 loss: 1.8922 2022/10/08 16:19:45 - mmengine - INFO - Epoch(train) [147][1440/2119] lr: 4.0000e-04 eta: 0:34:26 time: 0.2858 data_time: 0.0187 memory: 5821 grad_norm: 5.4667 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6971 loss: 1.6971 2022/10/08 16:19:52 - mmengine - INFO - Epoch(train) [147][1460/2119] lr: 4.0000e-04 eta: 0:34:20 time: 0.3073 data_time: 0.0184 memory: 5821 grad_norm: 5.5471 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7083 loss: 1.7083 2022/10/08 16:19:57 - mmengine - INFO - Epoch(train) [147][1480/2119] lr: 4.0000e-04 eta: 0:34:14 time: 0.2828 data_time: 0.0222 memory: 5821 grad_norm: 5.5139 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7065 loss: 1.7065 2022/10/08 16:20:04 - mmengine - INFO - Epoch(train) [147][1500/2119] lr: 4.0000e-04 eta: 0:34:08 time: 0.3187 data_time: 0.0213 memory: 5821 grad_norm: 5.6767 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6905 loss: 1.6905 2022/10/08 16:20:09 - mmengine - INFO - Epoch(train) [147][1520/2119] lr: 4.0000e-04 eta: 0:34:03 time: 0.2819 data_time: 0.0234 memory: 5821 grad_norm: 5.4908 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5501 loss: 1.5501 2022/10/08 16:20:15 - mmengine - INFO - Epoch(train) [147][1540/2119] lr: 4.0000e-04 eta: 0:33:57 time: 0.2748 data_time: 0.0219 memory: 5821 grad_norm: 5.6782 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0257 loss: 2.0257 2022/10/08 16:20:20 - mmengine - INFO - Epoch(train) [147][1560/2119] lr: 4.0000e-04 eta: 0:33:51 time: 0.2710 data_time: 0.0165 memory: 5821 grad_norm: 5.5314 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.6120 loss: 1.6120 2022/10/08 16:20:26 - mmengine - INFO - Epoch(train) [147][1580/2119] lr: 4.0000e-04 eta: 0:33:45 time: 0.3016 data_time: 0.0254 memory: 5821 grad_norm: 5.6014 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7807 loss: 1.7807 2022/10/08 16:20:32 - mmengine - INFO - Epoch(train) [147][1600/2119] lr: 4.0000e-04 eta: 0:33:39 time: 0.2846 data_time: 0.0153 memory: 5821 grad_norm: 5.5185 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.7725 loss: 1.7725 2022/10/08 16:20:37 - mmengine - INFO - Epoch(train) [147][1620/2119] lr: 4.0000e-04 eta: 0:33:33 time: 0.2620 data_time: 0.0206 memory: 5821 grad_norm: 5.6178 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7219 loss: 1.7219 2022/10/08 16:20:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 16:20:43 - mmengine - INFO - Epoch(train) [147][1640/2119] lr: 4.0000e-04 eta: 0:33:27 time: 0.2894 data_time: 0.0206 memory: 5821 grad_norm: 5.6850 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.8446 loss: 1.8446 2022/10/08 16:20:49 - mmengine - INFO - Epoch(train) [147][1660/2119] lr: 4.0000e-04 eta: 0:33:21 time: 0.2896 data_time: 0.0249 memory: 5821 grad_norm: 5.5796 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9112 loss: 1.9112 2022/10/08 16:20:55 - mmengine - INFO - Epoch(train) [147][1680/2119] lr: 4.0000e-04 eta: 0:33:15 time: 0.3077 data_time: 0.0188 memory: 5821 grad_norm: 5.5700 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7869 loss: 1.7869 2022/10/08 16:21:01 - mmengine - INFO - Epoch(train) [147][1700/2119] lr: 4.0000e-04 eta: 0:33:09 time: 0.2943 data_time: 0.0178 memory: 5821 grad_norm: 5.6096 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.5177 loss: 1.5177 2022/10/08 16:21:07 - mmengine - INFO - Epoch(train) [147][1720/2119] lr: 4.0000e-04 eta: 0:33:03 time: 0.2892 data_time: 0.0231 memory: 5821 grad_norm: 5.6544 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6335 loss: 1.6335 2022/10/08 16:21:12 - mmengine - INFO - Epoch(train) [147][1740/2119] lr: 4.0000e-04 eta: 0:32:58 time: 0.2801 data_time: 0.0185 memory: 5821 grad_norm: 5.5385 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.7943 loss: 1.7943 2022/10/08 16:21:18 - mmengine - INFO - Epoch(train) [147][1760/2119] lr: 4.0000e-04 eta: 0:32:52 time: 0.2817 data_time: 0.0264 memory: 5821 grad_norm: 5.6305 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.5985 loss: 1.5985 2022/10/08 16:21:24 - mmengine - INFO - Epoch(train) [147][1780/2119] lr: 4.0000e-04 eta: 0:32:46 time: 0.3184 data_time: 0.0186 memory: 5821 grad_norm: 5.6474 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.7314 loss: 1.7314 2022/10/08 16:21:30 - mmengine - INFO - Epoch(train) [147][1800/2119] lr: 4.0000e-04 eta: 0:32:40 time: 0.2813 data_time: 0.0212 memory: 5821 grad_norm: 5.6794 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8679 loss: 1.8679 2022/10/08 16:21:36 - mmengine - INFO - Epoch(train) [147][1820/2119] lr: 4.0000e-04 eta: 0:32:34 time: 0.2801 data_time: 0.0179 memory: 5821 grad_norm: 5.5593 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.7765 loss: 1.7765 2022/10/08 16:21:41 - mmengine - INFO - Epoch(train) [147][1840/2119] lr: 4.0000e-04 eta: 0:32:28 time: 0.2763 data_time: 0.0235 memory: 5821 grad_norm: 5.7165 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7949 loss: 1.7949 2022/10/08 16:21:47 - mmengine - INFO - Epoch(train) [147][1860/2119] lr: 4.0000e-04 eta: 0:32:22 time: 0.2783 data_time: 0.0187 memory: 5821 grad_norm: 5.5896 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9111 loss: 1.9111 2022/10/08 16:21:53 - mmengine - INFO - Epoch(train) [147][1880/2119] lr: 4.0000e-04 eta: 0:32:16 time: 0.3272 data_time: 0.0185 memory: 5821 grad_norm: 5.6620 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8983 loss: 1.8983 2022/10/08 16:21:59 - mmengine - INFO - Epoch(train) [147][1900/2119] lr: 4.0000e-04 eta: 0:32:10 time: 0.2768 data_time: 0.0189 memory: 5821 grad_norm: 5.5877 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.6898 loss: 1.6898 2022/10/08 16:22:05 - mmengine - INFO - Epoch(train) [147][1920/2119] lr: 4.0000e-04 eta: 0:32:05 time: 0.2947 data_time: 0.0170 memory: 5821 grad_norm: 5.6910 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0770 loss: 2.0770 2022/10/08 16:22:11 - mmengine - INFO - Epoch(train) [147][1940/2119] lr: 4.0000e-04 eta: 0:31:59 time: 0.2978 data_time: 0.0204 memory: 5821 grad_norm: 5.6866 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7265 loss: 1.7265 2022/10/08 16:22:16 - mmengine - INFO - Epoch(train) [147][1960/2119] lr: 4.0000e-04 eta: 0:31:53 time: 0.2631 data_time: 0.0205 memory: 5821 grad_norm: 5.6278 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.7117 loss: 1.7117 2022/10/08 16:22:22 - mmengine - INFO - Epoch(train) [147][1980/2119] lr: 4.0000e-04 eta: 0:31:47 time: 0.2883 data_time: 0.0185 memory: 5821 grad_norm: 5.7526 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9900 loss: 1.9900 2022/10/08 16:22:27 - mmengine - INFO - Epoch(train) [147][2000/2119] lr: 4.0000e-04 eta: 0:31:41 time: 0.2834 data_time: 0.0206 memory: 5821 grad_norm: 5.5710 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.7834 loss: 1.7834 2022/10/08 16:22:33 - mmengine - INFO - Epoch(train) [147][2020/2119] lr: 4.0000e-04 eta: 0:31:35 time: 0.2956 data_time: 0.0239 memory: 5821 grad_norm: 5.5357 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6689 loss: 1.6689 2022/10/08 16:22:39 - mmengine - INFO - Epoch(train) [147][2040/2119] lr: 4.0000e-04 eta: 0:31:29 time: 0.3007 data_time: 0.0162 memory: 5821 grad_norm: 5.5578 top1_acc: 0.4375 top5_acc: 0.9375 loss_cls: 1.6639 loss: 1.6639 2022/10/08 16:22:46 - mmengine - INFO - Epoch(train) [147][2060/2119] lr: 4.0000e-04 eta: 0:31:23 time: 0.3172 data_time: 0.0199 memory: 5821 grad_norm: 5.5514 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.7669 loss: 1.7669 2022/10/08 16:22:51 - mmengine - INFO - Epoch(train) [147][2080/2119] lr: 4.0000e-04 eta: 0:31:18 time: 0.2865 data_time: 0.0144 memory: 5821 grad_norm: 5.6547 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5158 loss: 1.5158 2022/10/08 16:22:57 - mmengine - INFO - Epoch(train) [147][2100/2119] lr: 4.0000e-04 eta: 0:31:12 time: 0.2809 data_time: 0.0215 memory: 5821 grad_norm: 5.6786 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9460 loss: 1.9460 2022/10/08 16:23:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 16:23:02 - mmengine - INFO - Epoch(train) [147][2119/2119] lr: 4.0000e-04 eta: 0:31:12 time: 0.2603 data_time: 0.0136 memory: 5821 grad_norm: 5.7096 top1_acc: 0.4000 top5_acc: 0.7000 loss_cls: 1.9379 loss: 1.9379 2022/10/08 16:23:10 - mmengine - INFO - Epoch(train) [148][20/2119] lr: 4.0000e-04 eta: 0:30:59 time: 0.3789 data_time: 0.1170 memory: 5821 grad_norm: 5.5575 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0261 loss: 2.0261 2022/10/08 16:23:16 - mmengine - INFO - Epoch(train) [148][40/2119] lr: 4.0000e-04 eta: 0:30:54 time: 0.3079 data_time: 0.0186 memory: 5821 grad_norm: 5.5214 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6444 loss: 1.6444 2022/10/08 16:23:22 - mmengine - INFO - Epoch(train) [148][60/2119] lr: 4.0000e-04 eta: 0:30:48 time: 0.2981 data_time: 0.0226 memory: 5821 grad_norm: 5.6281 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8134 loss: 1.8134 2022/10/08 16:23:28 - mmengine - INFO - Epoch(train) [148][80/2119] lr: 4.0000e-04 eta: 0:30:42 time: 0.2944 data_time: 0.0185 memory: 5821 grad_norm: 5.5401 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9302 loss: 1.9302 2022/10/08 16:23:34 - mmengine - INFO - Epoch(train) [148][100/2119] lr: 4.0000e-04 eta: 0:30:36 time: 0.3119 data_time: 0.0210 memory: 5821 grad_norm: 5.5755 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8577 loss: 1.8577 2022/10/08 16:23:39 - mmengine - INFO - Epoch(train) [148][120/2119] lr: 4.0000e-04 eta: 0:30:30 time: 0.2565 data_time: 0.0179 memory: 5821 grad_norm: 5.6163 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7012 loss: 1.7012 2022/10/08 16:23:45 - mmengine - INFO - Epoch(train) [148][140/2119] lr: 4.0000e-04 eta: 0:30:24 time: 0.3000 data_time: 0.0200 memory: 5821 grad_norm: 5.5293 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8434 loss: 1.8434 2022/10/08 16:23:51 - mmengine - INFO - Epoch(train) [148][160/2119] lr: 4.0000e-04 eta: 0:30:18 time: 0.2742 data_time: 0.0174 memory: 5821 grad_norm: 5.6800 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8277 loss: 1.8277 2022/10/08 16:23:56 - mmengine - INFO - Epoch(train) [148][180/2119] lr: 4.0000e-04 eta: 0:30:12 time: 0.2853 data_time: 0.0182 memory: 5821 grad_norm: 5.6572 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1493 loss: 2.1493 2022/10/08 16:24:02 - mmengine - INFO - Epoch(train) [148][200/2119] lr: 4.0000e-04 eta: 0:30:06 time: 0.2815 data_time: 0.0217 memory: 5821 grad_norm: 5.6409 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.6468 loss: 1.6468 2022/10/08 16:24:08 - mmengine - INFO - Epoch(train) [148][220/2119] lr: 4.0000e-04 eta: 0:30:01 time: 0.3107 data_time: 0.0237 memory: 5821 grad_norm: 5.5606 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8147 loss: 1.8147 2022/10/08 16:24:14 - mmengine - INFO - Epoch(train) [148][240/2119] lr: 4.0000e-04 eta: 0:29:55 time: 0.2955 data_time: 0.0153 memory: 5821 grad_norm: 5.5990 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7914 loss: 1.7914 2022/10/08 16:24:20 - mmengine - INFO - Epoch(train) [148][260/2119] lr: 4.0000e-04 eta: 0:29:49 time: 0.2799 data_time: 0.0238 memory: 5821 grad_norm: 5.5879 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5922 loss: 1.5922 2022/10/08 16:24:38 - mmengine - INFO - Epoch(train) [148][280/2119] lr: 4.0000e-04 eta: 0:29:45 time: 0.9368 data_time: 0.6881 memory: 5821 grad_norm: 5.5900 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7152 loss: 1.7152 2022/10/08 16:24:44 - mmengine - INFO - Epoch(train) [148][300/2119] lr: 4.0000e-04 eta: 0:29:39 time: 0.2523 data_time: 0.0226 memory: 5821 grad_norm: 5.5755 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.8613 loss: 1.8613 2022/10/08 16:24:49 - mmengine - INFO - Epoch(train) [148][320/2119] lr: 4.0000e-04 eta: 0:29:33 time: 0.2841 data_time: 0.0220 memory: 5821 grad_norm: 5.5398 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9846 loss: 1.9846 2022/10/08 16:24:55 - mmengine - INFO - Epoch(train) [148][340/2119] lr: 4.0000e-04 eta: 0:29:28 time: 0.3017 data_time: 0.0191 memory: 5821 grad_norm: 5.5795 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7713 loss: 1.7713 2022/10/08 16:25:01 - mmengine - INFO - Epoch(train) [148][360/2119] lr: 4.0000e-04 eta: 0:29:22 time: 0.2974 data_time: 0.0167 memory: 5821 grad_norm: 5.5207 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.6985 loss: 1.6985 2022/10/08 16:25:07 - mmengine - INFO - Epoch(train) [148][380/2119] lr: 4.0000e-04 eta: 0:29:16 time: 0.2941 data_time: 0.0169 memory: 5821 grad_norm: 5.6487 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.6691 loss: 1.6691 2022/10/08 16:25:13 - mmengine - INFO - Epoch(train) [148][400/2119] lr: 4.0000e-04 eta: 0:29:10 time: 0.2756 data_time: 0.0161 memory: 5821 grad_norm: 5.5809 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9627 loss: 1.9627 2022/10/08 16:25:18 - mmengine - INFO - Epoch(train) [148][420/2119] lr: 4.0000e-04 eta: 0:29:04 time: 0.2907 data_time: 0.0313 memory: 5821 grad_norm: 5.7055 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7728 loss: 1.7728 2022/10/08 16:25:24 - mmengine - INFO - Epoch(train) [148][440/2119] lr: 4.0000e-04 eta: 0:28:58 time: 0.2968 data_time: 0.0174 memory: 5821 grad_norm: 5.5762 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 1.9996 loss: 1.9996 2022/10/08 16:25:30 - mmengine - INFO - Epoch(train) [148][460/2119] lr: 4.0000e-04 eta: 0:28:52 time: 0.2874 data_time: 0.0190 memory: 5821 grad_norm: 5.5977 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7913 loss: 1.7913 2022/10/08 16:25:35 - mmengine - INFO - Epoch(train) [148][480/2119] lr: 4.0000e-04 eta: 0:28:46 time: 0.2638 data_time: 0.0227 memory: 5821 grad_norm: 5.5935 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8882 loss: 1.8882 2022/10/08 16:25:42 - mmengine - INFO - Epoch(train) [148][500/2119] lr: 4.0000e-04 eta: 0:28:40 time: 0.3066 data_time: 0.0239 memory: 5821 grad_norm: 5.5440 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8059 loss: 1.8059 2022/10/08 16:25:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 16:25:47 - mmengine - INFO - Epoch(train) [148][520/2119] lr: 4.0000e-04 eta: 0:28:35 time: 0.2735 data_time: 0.0183 memory: 5821 grad_norm: 5.6613 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8249 loss: 1.8249 2022/10/08 16:25:52 - mmengine - INFO - Epoch(train) [148][540/2119] lr: 4.0000e-04 eta: 0:28:29 time: 0.2681 data_time: 0.0189 memory: 5821 grad_norm: 5.5439 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.6244 loss: 1.6244 2022/10/08 16:25:59 - mmengine - INFO - Epoch(train) [148][560/2119] lr: 4.0000e-04 eta: 0:28:23 time: 0.3322 data_time: 0.0223 memory: 5821 grad_norm: 5.6809 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9609 loss: 1.9609 2022/10/08 16:26:05 - mmengine - INFO - Epoch(train) [148][580/2119] lr: 4.0000e-04 eta: 0:28:17 time: 0.2863 data_time: 0.0160 memory: 5821 grad_norm: 5.6032 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5371 loss: 1.5371 2022/10/08 16:26:11 - mmengine - INFO - Epoch(train) [148][600/2119] lr: 4.0000e-04 eta: 0:28:11 time: 0.3035 data_time: 0.0175 memory: 5821 grad_norm: 5.4978 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.8658 loss: 1.8658 2022/10/08 16:26:16 - mmengine - INFO - Epoch(train) [148][620/2119] lr: 4.0000e-04 eta: 0:28:05 time: 0.2669 data_time: 0.0190 memory: 5821 grad_norm: 5.5611 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6979 loss: 1.6979 2022/10/08 16:26:22 - mmengine - INFO - Epoch(train) [148][640/2119] lr: 4.0000e-04 eta: 0:27:59 time: 0.3052 data_time: 0.0156 memory: 5821 grad_norm: 5.6670 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7405 loss: 1.7405 2022/10/08 16:26:28 - mmengine - INFO - Epoch(train) [148][660/2119] lr: 4.0000e-04 eta: 0:27:53 time: 0.2828 data_time: 0.0196 memory: 5821 grad_norm: 5.6122 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.7917 loss: 1.7917 2022/10/08 16:26:34 - mmengine - INFO - Epoch(train) [148][680/2119] lr: 4.0000e-04 eta: 0:27:47 time: 0.2821 data_time: 0.0181 memory: 5821 grad_norm: 5.5633 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.6029 loss: 1.6029 2022/10/08 16:26:39 - mmengine - INFO - Epoch(train) [148][700/2119] lr: 4.0000e-04 eta: 0:27:41 time: 0.2761 data_time: 0.0196 memory: 5821 grad_norm: 5.7742 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7788 loss: 1.7788 2022/10/08 16:26:45 - mmengine - INFO - Epoch(train) [148][720/2119] lr: 4.0000e-04 eta: 0:27:36 time: 0.2996 data_time: 0.0176 memory: 5821 grad_norm: 5.6816 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7815 loss: 1.7815 2022/10/08 16:26:51 - mmengine - INFO - Epoch(train) [148][740/2119] lr: 4.0000e-04 eta: 0:27:30 time: 0.2741 data_time: 0.0212 memory: 5821 grad_norm: 5.6394 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7891 loss: 1.7891 2022/10/08 16:26:57 - mmengine - INFO - Epoch(train) [148][760/2119] lr: 4.0000e-04 eta: 0:27:24 time: 0.2872 data_time: 0.0209 memory: 5821 grad_norm: 5.5188 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5223 loss: 1.5223 2022/10/08 16:27:02 - mmengine - INFO - Epoch(train) [148][780/2119] lr: 4.0000e-04 eta: 0:27:18 time: 0.2878 data_time: 0.0180 memory: 5821 grad_norm: 5.7020 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7801 loss: 1.7801 2022/10/08 16:27:08 - mmengine - INFO - Epoch(train) [148][800/2119] lr: 4.0000e-04 eta: 0:27:12 time: 0.2697 data_time: 0.0149 memory: 5821 grad_norm: 5.5106 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5810 loss: 1.5810 2022/10/08 16:27:14 - mmengine - INFO - Epoch(train) [148][820/2119] lr: 4.0000e-04 eta: 0:27:06 time: 0.3054 data_time: 0.0182 memory: 5821 grad_norm: 5.5934 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.8721 loss: 1.8721 2022/10/08 16:27:20 - mmengine - INFO - Epoch(train) [148][840/2119] lr: 4.0000e-04 eta: 0:27:00 time: 0.2954 data_time: 0.0200 memory: 5821 grad_norm: 5.5433 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5844 loss: 1.5844 2022/10/08 16:27:25 - mmengine - INFO - Epoch(train) [148][860/2119] lr: 4.0000e-04 eta: 0:26:54 time: 0.2701 data_time: 0.0196 memory: 5821 grad_norm: 5.6335 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7592 loss: 1.7592 2022/10/08 16:27:30 - mmengine - INFO - Epoch(train) [148][880/2119] lr: 4.0000e-04 eta: 0:26:48 time: 0.2571 data_time: 0.0178 memory: 5821 grad_norm: 5.6029 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9925 loss: 1.9925 2022/10/08 16:27:36 - mmengine - INFO - Epoch(train) [148][900/2119] lr: 4.0000e-04 eta: 0:26:42 time: 0.3021 data_time: 0.0247 memory: 5821 grad_norm: 5.6290 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8700 loss: 1.8700 2022/10/08 16:27:42 - mmengine - INFO - Epoch(train) [148][920/2119] lr: 4.0000e-04 eta: 0:26:37 time: 0.2891 data_time: 0.0210 memory: 5821 grad_norm: 5.5666 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7933 loss: 1.7933 2022/10/08 16:27:48 - mmengine - INFO - Epoch(train) [148][940/2119] lr: 4.0000e-04 eta: 0:26:31 time: 0.2792 data_time: 0.0188 memory: 5821 grad_norm: 5.6658 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7168 loss: 1.7168 2022/10/08 16:27:54 - mmengine - INFO - Epoch(train) [148][960/2119] lr: 4.0000e-04 eta: 0:26:25 time: 0.2888 data_time: 0.0211 memory: 5821 grad_norm: 5.6704 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.6964 loss: 1.6964 2022/10/08 16:27:59 - mmengine - INFO - Epoch(train) [148][980/2119] lr: 4.0000e-04 eta: 0:26:19 time: 0.2874 data_time: 0.0157 memory: 5821 grad_norm: 5.5118 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5950 loss: 1.5950 2022/10/08 16:28:05 - mmengine - INFO - Epoch(train) [148][1000/2119] lr: 4.0000e-04 eta: 0:26:13 time: 0.2798 data_time: 0.0153 memory: 5821 grad_norm: 5.6585 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.8551 loss: 1.8551 2022/10/08 16:28:11 - mmengine - INFO - Epoch(train) [148][1020/2119] lr: 4.0000e-04 eta: 0:26:07 time: 0.2997 data_time: 0.0184 memory: 5821 grad_norm: 5.5655 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8326 loss: 1.8326 2022/10/08 16:28:17 - mmengine - INFO - Epoch(train) [148][1040/2119] lr: 4.0000e-04 eta: 0:26:01 time: 0.2867 data_time: 0.0160 memory: 5821 grad_norm: 5.6945 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7583 loss: 1.7583 2022/10/08 16:28:22 - mmengine - INFO - Epoch(train) [148][1060/2119] lr: 4.0000e-04 eta: 0:25:55 time: 0.2737 data_time: 0.0155 memory: 5821 grad_norm: 5.6184 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6811 loss: 1.6811 2022/10/08 16:28:28 - mmengine - INFO - Epoch(train) [148][1080/2119] lr: 4.0000e-04 eta: 0:25:49 time: 0.3015 data_time: 0.0151 memory: 5821 grad_norm: 5.6225 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7036 loss: 1.7036 2022/10/08 16:28:35 - mmengine - INFO - Epoch(train) [148][1100/2119] lr: 4.0000e-04 eta: 0:25:44 time: 0.3195 data_time: 0.0204 memory: 5821 grad_norm: 5.6717 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7216 loss: 1.7216 2022/10/08 16:28:40 - mmengine - INFO - Epoch(train) [148][1120/2119] lr: 4.0000e-04 eta: 0:25:38 time: 0.2529 data_time: 0.0164 memory: 5821 grad_norm: 5.6501 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.9260 loss: 1.9260 2022/10/08 16:28:45 - mmengine - INFO - Epoch(train) [148][1140/2119] lr: 4.0000e-04 eta: 0:25:32 time: 0.2710 data_time: 0.0242 memory: 5821 grad_norm: 5.6017 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6733 loss: 1.6733 2022/10/08 16:28:51 - mmengine - INFO - Epoch(train) [148][1160/2119] lr: 4.0000e-04 eta: 0:25:26 time: 0.2776 data_time: 0.0135 memory: 5821 grad_norm: 5.5948 top1_acc: 0.4375 top5_acc: 0.5000 loss_cls: 1.8065 loss: 1.8065 2022/10/08 16:28:57 - mmengine - INFO - Epoch(train) [148][1180/2119] lr: 4.0000e-04 eta: 0:25:20 time: 0.3026 data_time: 0.0203 memory: 5821 grad_norm: 5.6006 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8814 loss: 1.8814 2022/10/08 16:29:03 - mmengine - INFO - Epoch(train) [148][1200/2119] lr: 4.0000e-04 eta: 0:25:14 time: 0.3060 data_time: 0.0192 memory: 5821 grad_norm: 5.6023 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6898 loss: 1.6898 2022/10/08 16:29:08 - mmengine - INFO - Epoch(train) [148][1220/2119] lr: 4.0000e-04 eta: 0:25:08 time: 0.2736 data_time: 0.0178 memory: 5821 grad_norm: 5.7353 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.9049 loss: 1.9049 2022/10/08 16:29:14 - mmengine - INFO - Epoch(train) [148][1240/2119] lr: 4.0000e-04 eta: 0:25:02 time: 0.3035 data_time: 0.0152 memory: 5821 grad_norm: 5.6042 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8877 loss: 1.8877 2022/10/08 16:29:20 - mmengine - INFO - Epoch(train) [148][1260/2119] lr: 4.0000e-04 eta: 0:24:56 time: 0.2805 data_time: 0.0195 memory: 5821 grad_norm: 5.5909 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.5705 loss: 1.5705 2022/10/08 16:29:26 - mmengine - INFO - Epoch(train) [148][1280/2119] lr: 4.0000e-04 eta: 0:24:50 time: 0.2964 data_time: 0.0275 memory: 5821 grad_norm: 5.6434 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6152 loss: 1.6152 2022/10/08 16:29:31 - mmengine - INFO - Epoch(train) [148][1300/2119] lr: 4.0000e-04 eta: 0:24:45 time: 0.2658 data_time: 0.0249 memory: 5821 grad_norm: 5.6048 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.6287 loss: 1.6287 2022/10/08 16:29:37 - mmengine - INFO - Epoch(train) [148][1320/2119] lr: 4.0000e-04 eta: 0:24:39 time: 0.2632 data_time: 0.0148 memory: 5821 grad_norm: 5.6908 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.7061 loss: 1.7061 2022/10/08 16:29:42 - mmengine - INFO - Epoch(train) [148][1340/2119] lr: 4.0000e-04 eta: 0:24:33 time: 0.2877 data_time: 0.0187 memory: 5821 grad_norm: 5.5577 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7523 loss: 1.7523 2022/10/08 16:29:48 - mmengine - INFO - Epoch(train) [148][1360/2119] lr: 4.0000e-04 eta: 0:24:27 time: 0.2767 data_time: 0.0173 memory: 5821 grad_norm: 5.5032 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7844 loss: 1.7844 2022/10/08 16:29:54 - mmengine - INFO - Epoch(train) [148][1380/2119] lr: 4.0000e-04 eta: 0:24:21 time: 0.2859 data_time: 0.0234 memory: 5821 grad_norm: 5.7687 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0294 loss: 2.0294 2022/10/08 16:29:59 - mmengine - INFO - Epoch(train) [148][1400/2119] lr: 4.0000e-04 eta: 0:24:15 time: 0.2829 data_time: 0.0189 memory: 5821 grad_norm: 5.6738 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9919 loss: 1.9919 2022/10/08 16:30:06 - mmengine - INFO - Epoch(train) [148][1420/2119] lr: 4.0000e-04 eta: 0:24:09 time: 0.3375 data_time: 0.0186 memory: 5821 grad_norm: 5.5352 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7347 loss: 1.7347 2022/10/08 16:30:11 - mmengine - INFO - Epoch(train) [148][1440/2119] lr: 4.0000e-04 eta: 0:24:03 time: 0.2515 data_time: 0.0154 memory: 5821 grad_norm: 5.5858 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6402 loss: 1.6402 2022/10/08 16:30:16 - mmengine - INFO - Epoch(train) [148][1460/2119] lr: 4.0000e-04 eta: 0:23:57 time: 0.2609 data_time: 0.0249 memory: 5821 grad_norm: 5.5763 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.9585 loss: 1.9585 2022/10/08 16:30:22 - mmengine - INFO - Epoch(train) [148][1480/2119] lr: 4.0000e-04 eta: 0:23:51 time: 0.2920 data_time: 0.0226 memory: 5821 grad_norm: 5.7202 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6675 loss: 1.6675 2022/10/08 16:30:28 - mmengine - INFO - Epoch(train) [148][1500/2119] lr: 4.0000e-04 eta: 0:23:46 time: 0.3070 data_time: 0.0149 memory: 5821 grad_norm: 5.6075 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7034 loss: 1.7034 2022/10/08 16:30:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 16:30:34 - mmengine - INFO - Epoch(train) [148][1520/2119] lr: 4.0000e-04 eta: 0:23:40 time: 0.3057 data_time: 0.0142 memory: 5821 grad_norm: 5.6055 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7566 loss: 1.7566 2022/10/08 16:30:41 - mmengine - INFO - Epoch(train) [148][1540/2119] lr: 4.0000e-04 eta: 0:23:34 time: 0.3179 data_time: 0.0181 memory: 5821 grad_norm: 5.6763 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0570 loss: 2.0570 2022/10/08 16:30:47 - mmengine - INFO - Epoch(train) [148][1560/2119] lr: 4.0000e-04 eta: 0:23:28 time: 0.2978 data_time: 0.0161 memory: 5821 grad_norm: 5.6719 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7458 loss: 1.7458 2022/10/08 16:30:52 - mmengine - INFO - Epoch(train) [148][1580/2119] lr: 4.0000e-04 eta: 0:23:22 time: 0.2587 data_time: 0.0214 memory: 5821 grad_norm: 5.5710 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.7300 loss: 1.7300 2022/10/08 16:30:57 - mmengine - INFO - Epoch(train) [148][1600/2119] lr: 4.0000e-04 eta: 0:23:16 time: 0.2788 data_time: 0.0204 memory: 5821 grad_norm: 5.7410 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.7701 loss: 1.7701 2022/10/08 16:31:04 - mmengine - INFO - Epoch(train) [148][1620/2119] lr: 4.0000e-04 eta: 0:23:10 time: 0.3111 data_time: 0.0249 memory: 5821 grad_norm: 5.6639 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8021 loss: 1.8021 2022/10/08 16:31:10 - mmengine - INFO - Epoch(train) [148][1640/2119] lr: 4.0000e-04 eta: 0:23:04 time: 0.2970 data_time: 0.0201 memory: 5821 grad_norm: 5.6756 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9993 loss: 1.9993 2022/10/08 16:31:16 - mmengine - INFO - Epoch(train) [148][1660/2119] lr: 4.0000e-04 eta: 0:22:59 time: 0.2922 data_time: 0.0218 memory: 5821 grad_norm: 5.6122 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.7367 loss: 1.7367 2022/10/08 16:31:21 - mmengine - INFO - Epoch(train) [148][1680/2119] lr: 4.0000e-04 eta: 0:22:53 time: 0.2656 data_time: 0.0171 memory: 5821 grad_norm: 5.6993 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6402 loss: 1.6402 2022/10/08 16:31:27 - mmengine - INFO - Epoch(train) [148][1700/2119] lr: 4.0000e-04 eta: 0:22:47 time: 0.3113 data_time: 0.0240 memory: 5821 grad_norm: 5.6383 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7422 loss: 1.7422 2022/10/08 16:31:33 - mmengine - INFO - Epoch(train) [148][1720/2119] lr: 4.0000e-04 eta: 0:22:41 time: 0.2750 data_time: 0.0187 memory: 5821 grad_norm: 5.6730 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7326 loss: 1.7326 2022/10/08 16:31:38 - mmengine - INFO - Epoch(train) [148][1740/2119] lr: 4.0000e-04 eta: 0:22:35 time: 0.2790 data_time: 0.0244 memory: 5821 grad_norm: 5.5707 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7911 loss: 1.7911 2022/10/08 16:31:44 - mmengine - INFO - Epoch(train) [148][1760/2119] lr: 4.0000e-04 eta: 0:22:29 time: 0.3092 data_time: 0.0174 memory: 5821 grad_norm: 5.6058 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6635 loss: 1.6635 2022/10/08 16:31:50 - mmengine - INFO - Epoch(train) [148][1780/2119] lr: 4.0000e-04 eta: 0:22:23 time: 0.2643 data_time: 0.0205 memory: 5821 grad_norm: 5.6756 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0394 loss: 2.0394 2022/10/08 16:31:55 - mmengine - INFO - Epoch(train) [148][1800/2119] lr: 4.0000e-04 eta: 0:22:17 time: 0.2898 data_time: 0.0165 memory: 5821 grad_norm: 5.4969 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7466 loss: 1.7466 2022/10/08 16:32:01 - mmengine - INFO - Epoch(train) [148][1820/2119] lr: 4.0000e-04 eta: 0:22:11 time: 0.2996 data_time: 0.0176 memory: 5821 grad_norm: 5.6731 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.4977 loss: 1.4977 2022/10/08 16:32:07 - mmengine - INFO - Epoch(train) [148][1840/2119] lr: 4.0000e-04 eta: 0:22:06 time: 0.2768 data_time: 0.0152 memory: 5821 grad_norm: 5.6562 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7768 loss: 1.7768 2022/10/08 16:32:13 - mmengine - INFO - Epoch(train) [148][1860/2119] lr: 4.0000e-04 eta: 0:22:00 time: 0.2979 data_time: 0.0190 memory: 5821 grad_norm: 5.5155 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9401 loss: 1.9401 2022/10/08 16:32:18 - mmengine - INFO - Epoch(train) [148][1880/2119] lr: 4.0000e-04 eta: 0:21:54 time: 0.2666 data_time: 0.0234 memory: 5821 grad_norm: 5.6231 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.8543 loss: 1.8543 2022/10/08 16:32:24 - mmengine - INFO - Epoch(train) [148][1900/2119] lr: 4.0000e-04 eta: 0:21:48 time: 0.2847 data_time: 0.0219 memory: 5821 grad_norm: 5.6903 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7403 loss: 1.7403 2022/10/08 16:32:30 - mmengine - INFO - Epoch(train) [148][1920/2119] lr: 4.0000e-04 eta: 0:21:42 time: 0.2746 data_time: 0.0185 memory: 5821 grad_norm: 5.6247 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8334 loss: 1.8334 2022/10/08 16:32:35 - mmengine - INFO - Epoch(train) [148][1940/2119] lr: 4.0000e-04 eta: 0:21:36 time: 0.2816 data_time: 0.0213 memory: 5821 grad_norm: 5.5457 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9706 loss: 1.9706 2022/10/08 16:32:41 - mmengine - INFO - Epoch(train) [148][1960/2119] lr: 4.0000e-04 eta: 0:21:30 time: 0.2875 data_time: 0.0200 memory: 5821 grad_norm: 5.6231 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7134 loss: 1.7134 2022/10/08 16:32:47 - mmengine - INFO - Epoch(train) [148][1980/2119] lr: 4.0000e-04 eta: 0:21:24 time: 0.3091 data_time: 0.0211 memory: 5821 grad_norm: 5.6393 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9629 loss: 1.9629 2022/10/08 16:32:53 - mmengine - INFO - Epoch(train) [148][2000/2119] lr: 4.0000e-04 eta: 0:21:18 time: 0.2943 data_time: 0.0142 memory: 5821 grad_norm: 5.6817 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9888 loss: 1.9888 2022/10/08 16:32:59 - mmengine - INFO - Epoch(train) [148][2020/2119] lr: 4.0000e-04 eta: 0:21:13 time: 0.2872 data_time: 0.0208 memory: 5821 grad_norm: 5.6426 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7728 loss: 1.7728 2022/10/08 16:33:05 - mmengine - INFO - Epoch(train) [148][2040/2119] lr: 4.0000e-04 eta: 0:21:07 time: 0.3117 data_time: 0.0194 memory: 5821 grad_norm: 5.7170 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0220 loss: 2.0220 2022/10/08 16:33:10 - mmengine - INFO - Epoch(train) [148][2060/2119] lr: 4.0000e-04 eta: 0:21:01 time: 0.2559 data_time: 0.0197 memory: 5821 grad_norm: 5.6565 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8893 loss: 1.8893 2022/10/08 16:33:16 - mmengine - INFO - Epoch(train) [148][2080/2119] lr: 4.0000e-04 eta: 0:20:55 time: 0.2871 data_time: 0.0193 memory: 5821 grad_norm: 5.6923 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.7208 loss: 1.7208 2022/10/08 16:33:22 - mmengine - INFO - Epoch(train) [148][2100/2119] lr: 4.0000e-04 eta: 0:20:49 time: 0.3109 data_time: 0.0196 memory: 5821 grad_norm: 5.5747 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6864 loss: 1.6864 2022/10/08 16:33:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 16:33:27 - mmengine - INFO - Epoch(train) [148][2119/2119] lr: 4.0000e-04 eta: 0:20:49 time: 0.2737 data_time: 0.0147 memory: 5821 grad_norm: 5.6545 top1_acc: 0.6000 top5_acc: 0.7000 loss_cls: 1.6565 loss: 1.6565 2022/10/08 16:33:27 - mmengine - INFO - Saving checkpoint at 148 epochs 2022/10/08 16:33:36 - mmengine - INFO - Epoch(train) [149][20/2119] lr: 4.0000e-04 eta: 0:20:37 time: 0.3458 data_time: 0.1179 memory: 5821 grad_norm: 5.6453 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7987 loss: 1.7987 2022/10/08 16:33:41 - mmengine - INFO - Epoch(train) [149][40/2119] lr: 4.0000e-04 eta: 0:20:31 time: 0.2671 data_time: 0.0152 memory: 5821 grad_norm: 5.6541 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7124 loss: 1.7124 2022/10/08 16:33:47 - mmengine - INFO - Epoch(train) [149][60/2119] lr: 4.0000e-04 eta: 0:20:25 time: 0.3003 data_time: 0.0188 memory: 5821 grad_norm: 5.6165 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7938 loss: 1.7938 2022/10/08 16:33:53 - mmengine - INFO - Epoch(train) [149][80/2119] lr: 4.0000e-04 eta: 0:20:19 time: 0.2840 data_time: 0.0221 memory: 5821 grad_norm: 5.6973 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.7537 loss: 1.7537 2022/10/08 16:33:59 - mmengine - INFO - Epoch(train) [149][100/2119] lr: 4.0000e-04 eta: 0:20:13 time: 0.2919 data_time: 0.0213 memory: 5821 grad_norm: 5.6425 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8370 loss: 1.8370 2022/10/08 16:34:05 - mmengine - INFO - Epoch(train) [149][120/2119] lr: 4.0000e-04 eta: 0:20:08 time: 0.2946 data_time: 0.0178 memory: 5821 grad_norm: 5.6925 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7451 loss: 1.7451 2022/10/08 16:34:10 - mmengine - INFO - Epoch(train) [149][140/2119] lr: 4.0000e-04 eta: 0:20:02 time: 0.2738 data_time: 0.0220 memory: 5821 grad_norm: 5.6343 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7424 loss: 1.7424 2022/10/08 16:34:16 - mmengine - INFO - Epoch(train) [149][160/2119] lr: 4.0000e-04 eta: 0:19:56 time: 0.2965 data_time: 0.0181 memory: 5821 grad_norm: 5.6806 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 2.0340 loss: 2.0340 2022/10/08 16:34:22 - mmengine - INFO - Epoch(train) [149][180/2119] lr: 4.0000e-04 eta: 0:19:50 time: 0.3018 data_time: 0.0230 memory: 5821 grad_norm: 5.5946 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8581 loss: 1.8581 2022/10/08 16:34:28 - mmengine - INFO - Epoch(train) [149][200/2119] lr: 4.0000e-04 eta: 0:19:44 time: 0.2800 data_time: 0.0230 memory: 5821 grad_norm: 5.6453 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6919 loss: 1.6919 2022/10/08 16:34:33 - mmengine - INFO - Epoch(train) [149][220/2119] lr: 4.0000e-04 eta: 0:19:38 time: 0.2665 data_time: 0.0227 memory: 5821 grad_norm: 5.6346 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8233 loss: 1.8233 2022/10/08 16:34:39 - mmengine - INFO - Epoch(train) [149][240/2119] lr: 4.0000e-04 eta: 0:19:32 time: 0.2769 data_time: 0.0211 memory: 5821 grad_norm: 5.6592 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6293 loss: 1.6293 2022/10/08 16:34:45 - mmengine - INFO - Epoch(train) [149][260/2119] lr: 4.0000e-04 eta: 0:19:26 time: 0.3217 data_time: 0.0291 memory: 5821 grad_norm: 5.5392 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.6392 loss: 1.6392 2022/10/08 16:34:50 - mmengine - INFO - Epoch(train) [149][280/2119] lr: 4.0000e-04 eta: 0:19:20 time: 0.2577 data_time: 0.0236 memory: 5821 grad_norm: 5.6106 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9811 loss: 1.9811 2022/10/08 16:34:56 - mmengine - INFO - Epoch(train) [149][300/2119] lr: 4.0000e-04 eta: 0:19:15 time: 0.2732 data_time: 0.0172 memory: 5821 grad_norm: 5.6990 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.5770 loss: 1.5770 2022/10/08 16:35:03 - mmengine - INFO - Epoch(train) [149][320/2119] lr: 4.0000e-04 eta: 0:19:09 time: 0.3403 data_time: 0.0179 memory: 5821 grad_norm: 5.5843 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7892 loss: 1.7892 2022/10/08 16:35:08 - mmengine - INFO - Epoch(train) [149][340/2119] lr: 4.0000e-04 eta: 0:19:03 time: 0.2739 data_time: 0.0204 memory: 5821 grad_norm: 5.5620 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7488 loss: 1.7488 2022/10/08 16:35:14 - mmengine - INFO - Epoch(train) [149][360/2119] lr: 4.0000e-04 eta: 0:18:57 time: 0.2728 data_time: 0.0169 memory: 5821 grad_norm: 5.6685 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8233 loss: 1.8233 2022/10/08 16:35:19 - mmengine - INFO - Epoch(train) [149][380/2119] lr: 4.0000e-04 eta: 0:18:51 time: 0.2867 data_time: 0.0217 memory: 5821 grad_norm: 5.6958 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1962 loss: 2.1962 2022/10/08 16:35:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 16:35:26 - mmengine - INFO - Epoch(train) [149][400/2119] lr: 4.0000e-04 eta: 0:18:45 time: 0.3200 data_time: 0.0165 memory: 5821 grad_norm: 5.6128 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7676 loss: 1.7676 2022/10/08 16:35:31 - mmengine - INFO - Epoch(train) [149][420/2119] lr: 4.0000e-04 eta: 0:18:39 time: 0.2666 data_time: 0.0194 memory: 5821 grad_norm: 5.5229 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7182 loss: 1.7182 2022/10/08 16:35:38 - mmengine - INFO - Epoch(train) [149][440/2119] lr: 4.0000e-04 eta: 0:18:34 time: 0.3216 data_time: 0.0159 memory: 5821 grad_norm: 5.6092 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.7352 loss: 1.7352 2022/10/08 16:35:43 - mmengine - INFO - Epoch(train) [149][460/2119] lr: 4.0000e-04 eta: 0:18:28 time: 0.2765 data_time: 0.0216 memory: 5821 grad_norm: 5.6982 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.7355 loss: 1.7355 2022/10/08 16:35:49 - mmengine - INFO - Epoch(train) [149][480/2119] lr: 4.0000e-04 eta: 0:18:22 time: 0.2958 data_time: 0.0282 memory: 5821 grad_norm: 5.6569 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9744 loss: 1.9744 2022/10/08 16:35:55 - mmengine - INFO - Epoch(train) [149][500/2119] lr: 4.0000e-04 eta: 0:18:16 time: 0.2799 data_time: 0.0266 memory: 5821 grad_norm: 5.5976 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6975 loss: 1.6975 2022/10/08 16:36:00 - mmengine - INFO - Epoch(train) [149][520/2119] lr: 4.0000e-04 eta: 0:18:10 time: 0.2734 data_time: 0.0197 memory: 5821 grad_norm: 5.6222 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.9289 loss: 1.9289 2022/10/08 16:36:06 - mmengine - INFO - Epoch(train) [149][540/2119] lr: 4.0000e-04 eta: 0:18:04 time: 0.3133 data_time: 0.0201 memory: 5821 grad_norm: 5.6614 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.7165 loss: 1.7165 2022/10/08 16:36:12 - mmengine - INFO - Epoch(train) [149][560/2119] lr: 4.0000e-04 eta: 0:17:58 time: 0.2968 data_time: 0.0154 memory: 5821 grad_norm: 5.6555 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8256 loss: 1.8256 2022/10/08 16:36:18 - mmengine - INFO - Epoch(train) [149][580/2119] lr: 4.0000e-04 eta: 0:17:52 time: 0.2992 data_time: 0.0167 memory: 5821 grad_norm: 6.4532 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8324 loss: 1.8324 2022/10/08 16:36:25 - mmengine - INFO - Epoch(train) [149][600/2119] lr: 4.0000e-04 eta: 0:17:47 time: 0.3325 data_time: 0.0194 memory: 5821 grad_norm: 5.6726 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.9650 loss: 1.9650 2022/10/08 16:36:30 - mmengine - INFO - Epoch(train) [149][620/2119] lr: 4.0000e-04 eta: 0:17:41 time: 0.2498 data_time: 0.0184 memory: 5821 grad_norm: 5.5851 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.6496 loss: 1.6496 2022/10/08 16:36:35 - mmengine - INFO - Epoch(train) [149][640/2119] lr: 4.0000e-04 eta: 0:17:35 time: 0.2699 data_time: 0.0174 memory: 5821 grad_norm: 5.8063 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8229 loss: 1.8229 2022/10/08 16:36:42 - mmengine - INFO - Epoch(train) [149][660/2119] lr: 4.0000e-04 eta: 0:17:29 time: 0.3158 data_time: 0.0222 memory: 5821 grad_norm: 5.6545 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8790 loss: 1.8790 2022/10/08 16:36:48 - mmengine - INFO - Epoch(train) [149][680/2119] lr: 4.0000e-04 eta: 0:17:23 time: 0.2970 data_time: 0.0180 memory: 5821 grad_norm: 5.6686 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7344 loss: 1.7344 2022/10/08 16:36:53 - mmengine - INFO - Epoch(train) [149][700/2119] lr: 4.0000e-04 eta: 0:17:17 time: 0.2622 data_time: 0.0282 memory: 5821 grad_norm: 5.5993 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5410 loss: 1.5410 2022/10/08 16:36:59 - mmengine - INFO - Epoch(train) [149][720/2119] lr: 4.0000e-04 eta: 0:17:11 time: 0.2869 data_time: 0.0221 memory: 5821 grad_norm: 5.6594 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9612 loss: 1.9612 2022/10/08 16:37:04 - mmengine - INFO - Epoch(train) [149][740/2119] lr: 4.0000e-04 eta: 0:17:05 time: 0.2788 data_time: 0.0218 memory: 5821 grad_norm: 5.6465 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7155 loss: 1.7155 2022/10/08 16:37:10 - mmengine - INFO - Epoch(train) [149][760/2119] lr: 4.0000e-04 eta: 0:17:00 time: 0.2900 data_time: 0.0196 memory: 5821 grad_norm: 5.5964 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.6956 loss: 1.6956 2022/10/08 16:37:16 - mmengine - INFO - Epoch(train) [149][780/2119] lr: 4.0000e-04 eta: 0:16:54 time: 0.2947 data_time: 0.0219 memory: 5821 grad_norm: 5.6447 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8479 loss: 1.8479 2022/10/08 16:37:22 - mmengine - INFO - Epoch(train) [149][800/2119] lr: 4.0000e-04 eta: 0:16:48 time: 0.3038 data_time: 0.0205 memory: 5821 grad_norm: 5.5686 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.6127 loss: 1.6127 2022/10/08 16:37:28 - mmengine - INFO - Epoch(train) [149][820/2119] lr: 4.0000e-04 eta: 0:16:42 time: 0.2962 data_time: 0.0224 memory: 5821 grad_norm: 5.5217 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6269 loss: 1.6269 2022/10/08 16:37:34 - mmengine - INFO - Epoch(train) [149][840/2119] lr: 4.0000e-04 eta: 0:16:36 time: 0.2941 data_time: 0.0212 memory: 5821 grad_norm: 5.6387 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8844 loss: 1.8844 2022/10/08 16:37:40 - mmengine - INFO - Epoch(train) [149][860/2119] lr: 4.0000e-04 eta: 0:16:30 time: 0.3017 data_time: 0.0198 memory: 5821 grad_norm: 5.6851 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7183 loss: 1.7183 2022/10/08 16:37:46 - mmengine - INFO - Epoch(train) [149][880/2119] lr: 4.0000e-04 eta: 0:16:24 time: 0.2849 data_time: 0.0180 memory: 5821 grad_norm: 5.6665 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.6883 loss: 1.6883 2022/10/08 16:37:51 - mmengine - INFO - Epoch(train) [149][900/2119] lr: 4.0000e-04 eta: 0:16:18 time: 0.2596 data_time: 0.0226 memory: 5821 grad_norm: 5.5750 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7812 loss: 1.7812 2022/10/08 16:37:57 - mmengine - INFO - Epoch(train) [149][920/2119] lr: 4.0000e-04 eta: 0:16:13 time: 0.2949 data_time: 0.0191 memory: 5821 grad_norm: 5.5831 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7129 loss: 1.7129 2022/10/08 16:38:03 - mmengine - INFO - Epoch(train) [149][940/2119] lr: 4.0000e-04 eta: 0:16:07 time: 0.2915 data_time: 0.0181 memory: 5821 grad_norm: 5.5908 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.0883 loss: 2.0883 2022/10/08 16:38:08 - mmengine - INFO - Epoch(train) [149][960/2119] lr: 4.0000e-04 eta: 0:16:01 time: 0.2835 data_time: 0.0208 memory: 5821 grad_norm: 5.6724 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6844 loss: 1.6844 2022/10/08 16:38:15 - mmengine - INFO - Epoch(train) [149][980/2119] lr: 4.0000e-04 eta: 0:15:55 time: 0.3163 data_time: 0.0231 memory: 5821 grad_norm: 5.5838 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7010 loss: 1.7010 2022/10/08 16:38:20 - mmengine - INFO - Epoch(train) [149][1000/2119] lr: 4.0000e-04 eta: 0:15:49 time: 0.2610 data_time: 0.0209 memory: 5821 grad_norm: 5.6492 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.7449 loss: 1.7449 2022/10/08 16:38:26 - mmengine - INFO - Epoch(train) [149][1020/2119] lr: 4.0000e-04 eta: 0:15:43 time: 0.2858 data_time: 0.0293 memory: 5821 grad_norm: 5.5912 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7771 loss: 1.7771 2022/10/08 16:38:32 - mmengine - INFO - Epoch(train) [149][1040/2119] lr: 4.0000e-04 eta: 0:15:37 time: 0.2950 data_time: 0.0210 memory: 5821 grad_norm: 5.6099 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7761 loss: 1.7761 2022/10/08 16:38:38 - mmengine - INFO - Epoch(train) [149][1060/2119] lr: 4.0000e-04 eta: 0:15:32 time: 0.3229 data_time: 0.0183 memory: 5821 grad_norm: 5.6113 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8955 loss: 1.8955 2022/10/08 16:38:44 - mmengine - INFO - Epoch(train) [149][1080/2119] lr: 4.0000e-04 eta: 0:15:26 time: 0.2833 data_time: 0.0157 memory: 5821 grad_norm: 5.7189 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8248 loss: 1.8248 2022/10/08 16:38:50 - mmengine - INFO - Epoch(train) [149][1100/2119] lr: 4.0000e-04 eta: 0:15:20 time: 0.2901 data_time: 0.0204 memory: 5821 grad_norm: 5.5757 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6001 loss: 1.6001 2022/10/08 16:38:55 - mmengine - INFO - Epoch(train) [149][1120/2119] lr: 4.0000e-04 eta: 0:15:14 time: 0.2620 data_time: 0.0185 memory: 5821 grad_norm: 5.6160 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8933 loss: 1.8933 2022/10/08 16:39:01 - mmengine - INFO - Epoch(train) [149][1140/2119] lr: 4.0000e-04 eta: 0:15:08 time: 0.2864 data_time: 0.0210 memory: 5821 grad_norm: 5.6518 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7129 loss: 1.7129 2022/10/08 16:39:07 - mmengine - INFO - Epoch(train) [149][1160/2119] lr: 4.0000e-04 eta: 0:15:02 time: 0.3213 data_time: 0.0183 memory: 5821 grad_norm: 5.5755 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8267 loss: 1.8267 2022/10/08 16:39:13 - mmengine - INFO - Epoch(train) [149][1180/2119] lr: 4.0000e-04 eta: 0:14:56 time: 0.3238 data_time: 0.0182 memory: 5821 grad_norm: 5.6292 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.6851 loss: 1.6851 2022/10/08 16:39:19 - mmengine - INFO - Epoch(train) [149][1200/2119] lr: 4.0000e-04 eta: 0:14:50 time: 0.2798 data_time: 0.0244 memory: 5821 grad_norm: 5.6747 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7211 loss: 1.7211 2022/10/08 16:39:25 - mmengine - INFO - Epoch(train) [149][1220/2119] lr: 4.0000e-04 eta: 0:14:45 time: 0.2967 data_time: 0.0199 memory: 5821 grad_norm: 5.7699 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8532 loss: 1.8532 2022/10/08 16:39:31 - mmengine - INFO - Epoch(train) [149][1240/2119] lr: 4.0000e-04 eta: 0:14:39 time: 0.2816 data_time: 0.0195 memory: 5821 grad_norm: 5.6627 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8476 loss: 1.8476 2022/10/08 16:39:37 - mmengine - INFO - Epoch(train) [149][1260/2119] lr: 4.0000e-04 eta: 0:14:33 time: 0.2991 data_time: 0.0185 memory: 5821 grad_norm: 5.5877 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 1.7433 loss: 1.7433 2022/10/08 16:39:42 - mmengine - INFO - Epoch(train) [149][1280/2119] lr: 4.0000e-04 eta: 0:14:27 time: 0.2644 data_time: 0.0241 memory: 5821 grad_norm: 5.6354 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.6231 loss: 1.6231 2022/10/08 16:39:48 - mmengine - INFO - Epoch(train) [149][1300/2119] lr: 4.0000e-04 eta: 0:14:21 time: 0.2868 data_time: 0.0196 memory: 5821 grad_norm: 5.8133 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9214 loss: 1.9214 2022/10/08 16:39:53 - mmengine - INFO - Epoch(train) [149][1320/2119] lr: 4.0000e-04 eta: 0:14:15 time: 0.2741 data_time: 0.0186 memory: 5821 grad_norm: 5.5929 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.5560 loss: 1.5560 2022/10/08 16:39:59 - mmengine - INFO - Epoch(train) [149][1340/2119] lr: 4.0000e-04 eta: 0:14:09 time: 0.2916 data_time: 0.0203 memory: 5821 grad_norm: 5.6540 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8896 loss: 1.8896 2022/10/08 16:40:05 - mmengine - INFO - Epoch(train) [149][1360/2119] lr: 4.0000e-04 eta: 0:14:03 time: 0.3006 data_time: 0.0209 memory: 5821 grad_norm: 5.7945 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8836 loss: 1.8836 2022/10/08 16:40:10 - mmengine - INFO - Epoch(train) [149][1380/2119] lr: 4.0000e-04 eta: 0:13:58 time: 0.2603 data_time: 0.0165 memory: 5821 grad_norm: 5.5524 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.6432 loss: 1.6432 2022/10/08 16:40:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 16:40:16 - mmengine - INFO - Epoch(train) [149][1400/2119] lr: 4.0000e-04 eta: 0:13:52 time: 0.2993 data_time: 0.0191 memory: 5821 grad_norm: 5.6666 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8944 loss: 1.8944 2022/10/08 16:40:22 - mmengine - INFO - Epoch(train) [149][1420/2119] lr: 4.0000e-04 eta: 0:13:46 time: 0.2839 data_time: 0.0195 memory: 5821 grad_norm: 5.6066 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7949 loss: 1.7949 2022/10/08 16:40:28 - mmengine - INFO - Epoch(train) [149][1440/2119] lr: 4.0000e-04 eta: 0:13:40 time: 0.3058 data_time: 0.0173 memory: 5821 grad_norm: 5.6085 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7040 loss: 1.7040 2022/10/08 16:40:33 - mmengine - INFO - Epoch(train) [149][1460/2119] lr: 4.0000e-04 eta: 0:13:34 time: 0.2691 data_time: 0.0378 memory: 5821 grad_norm: 5.6230 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7278 loss: 1.7278 2022/10/08 16:40:39 - mmengine - INFO - Epoch(train) [149][1480/2119] lr: 4.0000e-04 eta: 0:13:28 time: 0.2659 data_time: 0.0247 memory: 5821 grad_norm: 5.6499 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6244 loss: 1.6244 2022/10/08 16:40:45 - mmengine - INFO - Epoch(train) [149][1500/2119] lr: 4.0000e-04 eta: 0:13:22 time: 0.3117 data_time: 0.0229 memory: 5821 grad_norm: 5.7055 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9099 loss: 1.9099 2022/10/08 16:40:51 - mmengine - INFO - Epoch(train) [149][1520/2119] lr: 4.0000e-04 eta: 0:13:16 time: 0.2888 data_time: 0.0210 memory: 5821 grad_norm: 5.6566 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7494 loss: 1.7494 2022/10/08 16:40:56 - mmengine - INFO - Epoch(train) [149][1540/2119] lr: 4.0000e-04 eta: 0:13:11 time: 0.2741 data_time: 0.0163 memory: 5821 grad_norm: 5.6096 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8868 loss: 1.8868 2022/10/08 16:41:02 - mmengine - INFO - Epoch(train) [149][1560/2119] lr: 4.0000e-04 eta: 0:13:05 time: 0.2938 data_time: 0.0190 memory: 5821 grad_norm: 5.6033 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9026 loss: 1.9026 2022/10/08 16:41:09 - mmengine - INFO - Epoch(train) [149][1580/2119] lr: 4.0000e-04 eta: 0:12:59 time: 0.3188 data_time: 0.0269 memory: 5821 grad_norm: 5.5692 top1_acc: 0.5625 top5_acc: 1.0000 loss_cls: 1.8217 loss: 1.8217 2022/10/08 16:41:14 - mmengine - INFO - Epoch(train) [149][1600/2119] lr: 4.0000e-04 eta: 0:12:53 time: 0.2745 data_time: 0.0185 memory: 5821 grad_norm: 5.6830 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9333 loss: 1.9333 2022/10/08 16:41:20 - mmengine - INFO - Epoch(train) [149][1620/2119] lr: 4.0000e-04 eta: 0:12:47 time: 0.2921 data_time: 0.0199 memory: 5821 grad_norm: 5.6881 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7366 loss: 1.7366 2022/10/08 16:41:26 - mmengine - INFO - Epoch(train) [149][1640/2119] lr: 4.0000e-04 eta: 0:12:41 time: 0.3066 data_time: 0.0261 memory: 5821 grad_norm: 5.6976 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6910 loss: 1.6910 2022/10/08 16:41:31 - mmengine - INFO - Epoch(train) [149][1660/2119] lr: 4.0000e-04 eta: 0:12:35 time: 0.2632 data_time: 0.0186 memory: 5821 grad_norm: 5.6714 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7385 loss: 1.7385 2022/10/08 16:41:37 - mmengine - INFO - Epoch(train) [149][1680/2119] lr: 4.0000e-04 eta: 0:12:29 time: 0.2649 data_time: 0.0184 memory: 5821 grad_norm: 5.5512 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 1.7224 loss: 1.7224 2022/10/08 16:41:44 - mmengine - INFO - Epoch(train) [149][1700/2119] lr: 4.0000e-04 eta: 0:12:24 time: 0.3792 data_time: 0.0222 memory: 5821 grad_norm: 5.7609 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.0115 loss: 2.0115 2022/10/08 16:41:50 - mmengine - INFO - Epoch(train) [149][1720/2119] lr: 4.0000e-04 eta: 0:12:18 time: 0.2738 data_time: 0.0225 memory: 5821 grad_norm: 5.6886 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7088 loss: 1.7088 2022/10/08 16:41:55 - mmengine - INFO - Epoch(train) [149][1740/2119] lr: 4.0000e-04 eta: 0:12:12 time: 0.2747 data_time: 0.0193 memory: 5821 grad_norm: 5.6108 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9106 loss: 1.9106 2022/10/08 16:42:01 - mmengine - INFO - Epoch(train) [149][1760/2119] lr: 4.0000e-04 eta: 0:12:06 time: 0.2984 data_time: 0.0200 memory: 5821 grad_norm: 5.6645 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7226 loss: 1.7226 2022/10/08 16:42:07 - mmengine - INFO - Epoch(train) [149][1780/2119] lr: 4.0000e-04 eta: 0:12:00 time: 0.2938 data_time: 0.0179 memory: 5821 grad_norm: 5.6480 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1670 loss: 2.1670 2022/10/08 16:42:12 - mmengine - INFO - Epoch(train) [149][1800/2119] lr: 4.0000e-04 eta: 0:11:54 time: 0.2654 data_time: 0.0196 memory: 5821 grad_norm: 5.6294 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7817 loss: 1.7817 2022/10/08 16:42:19 - mmengine - INFO - Epoch(train) [149][1820/2119] lr: 4.0000e-04 eta: 0:11:48 time: 0.3128 data_time: 0.0237 memory: 5821 grad_norm: 5.6535 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7060 loss: 1.7060 2022/10/08 16:42:24 - mmengine - INFO - Epoch(train) [149][1840/2119] lr: 4.0000e-04 eta: 0:11:43 time: 0.2763 data_time: 0.0177 memory: 5821 grad_norm: 5.6229 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6934 loss: 1.6934 2022/10/08 16:42:30 - mmengine - INFO - Epoch(train) [149][1860/2119] lr: 4.0000e-04 eta: 0:11:37 time: 0.3065 data_time: 0.0217 memory: 5821 grad_norm: 5.5510 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9274 loss: 1.9274 2022/10/08 16:42:36 - mmengine - INFO - Epoch(train) [149][1880/2119] lr: 4.0000e-04 eta: 0:11:31 time: 0.2688 data_time: 0.0234 memory: 5821 grad_norm: 5.6220 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7077 loss: 1.7077 2022/10/08 16:42:42 - mmengine - INFO - Epoch(train) [149][1900/2119] lr: 4.0000e-04 eta: 0:11:25 time: 0.2967 data_time: 0.0184 memory: 5821 grad_norm: 5.6348 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8256 loss: 1.8256 2022/10/08 16:42:47 - mmengine - INFO - Epoch(train) [149][1920/2119] lr: 4.0000e-04 eta: 0:11:19 time: 0.2806 data_time: 0.0160 memory: 5821 grad_norm: 5.6262 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.9269 loss: 1.9269 2022/10/08 16:42:53 - mmengine - INFO - Epoch(train) [149][1940/2119] lr: 4.0000e-04 eta: 0:11:13 time: 0.2681 data_time: 0.0161 memory: 5821 grad_norm: 5.6883 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8300 loss: 1.8300 2022/10/08 16:42:58 - mmengine - INFO - Epoch(train) [149][1960/2119] lr: 4.0000e-04 eta: 0:11:07 time: 0.2790 data_time: 0.0183 memory: 5821 grad_norm: 5.6666 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.8267 loss: 1.8267 2022/10/08 16:43:04 - mmengine - INFO - Epoch(train) [149][1980/2119] lr: 4.0000e-04 eta: 0:11:01 time: 0.2938 data_time: 0.0191 memory: 5821 grad_norm: 5.6738 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.7845 loss: 1.7845 2022/10/08 16:43:10 - mmengine - INFO - Epoch(train) [149][2000/2119] lr: 4.0000e-04 eta: 0:10:56 time: 0.2817 data_time: 0.0191 memory: 5821 grad_norm: 5.5724 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6120 loss: 1.6120 2022/10/08 16:43:16 - mmengine - INFO - Epoch(train) [149][2020/2119] lr: 4.0000e-04 eta: 0:10:50 time: 0.3137 data_time: 0.0255 memory: 5821 grad_norm: 5.5584 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6937 loss: 1.6937 2022/10/08 16:43:22 - mmengine - INFO - Epoch(train) [149][2040/2119] lr: 4.0000e-04 eta: 0:10:44 time: 0.2804 data_time: 0.0191 memory: 5821 grad_norm: 5.6317 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9044 loss: 1.9044 2022/10/08 16:43:27 - mmengine - INFO - Epoch(train) [149][2060/2119] lr: 4.0000e-04 eta: 0:10:38 time: 0.2843 data_time: 0.0199 memory: 5821 grad_norm: 5.6784 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.7510 loss: 1.7510 2022/10/08 16:43:33 - mmengine - INFO - Epoch(train) [149][2080/2119] lr: 4.0000e-04 eta: 0:10:32 time: 0.2944 data_time: 0.0196 memory: 5821 grad_norm: 5.6410 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7384 loss: 1.7384 2022/10/08 16:43:39 - mmengine - INFO - Epoch(train) [149][2100/2119] lr: 4.0000e-04 eta: 0:10:26 time: 0.2790 data_time: 0.0186 memory: 5821 grad_norm: 5.6190 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6875 loss: 1.6875 2022/10/08 16:43:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 16:43:43 - mmengine - INFO - Epoch(train) [149][2119/2119] lr: 4.0000e-04 eta: 0:10:26 time: 0.2399 data_time: 0.0122 memory: 5821 grad_norm: 5.7281 top1_acc: 0.4000 top5_acc: 0.8000 loss_cls: 1.8012 loss: 1.8012 2022/10/08 16:43:51 - mmengine - INFO - Epoch(train) [150][20/2119] lr: 4.0000e-04 eta: 0:10:15 time: 0.3828 data_time: 0.1149 memory: 5821 grad_norm: 5.6055 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7760 loss: 1.7760 2022/10/08 16:43:57 - mmengine - INFO - Epoch(train) [150][40/2119] lr: 4.0000e-04 eta: 0:10:09 time: 0.3038 data_time: 0.0180 memory: 5821 grad_norm: 5.5997 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6696 loss: 1.6696 2022/10/08 16:44:03 - mmengine - INFO - Epoch(train) [150][60/2119] lr: 4.0000e-04 eta: 0:10:03 time: 0.3030 data_time: 0.0192 memory: 5821 grad_norm: 5.6250 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7043 loss: 1.7043 2022/10/08 16:44:09 - mmengine - INFO - Epoch(train) [150][80/2119] lr: 4.0000e-04 eta: 0:09:57 time: 0.2798 data_time: 0.0211 memory: 5821 grad_norm: 5.6786 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7834 loss: 1.7834 2022/10/08 16:44:15 - mmengine - INFO - Epoch(train) [150][100/2119] lr: 4.0000e-04 eta: 0:09:51 time: 0.3164 data_time: 0.0176 memory: 5821 grad_norm: 5.8078 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7396 loss: 1.7396 2022/10/08 16:44:21 - mmengine - INFO - Epoch(train) [150][120/2119] lr: 4.0000e-04 eta: 0:09:45 time: 0.2790 data_time: 0.0184 memory: 5821 grad_norm: 5.7179 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9188 loss: 1.9188 2022/10/08 16:44:27 - mmengine - INFO - Epoch(train) [150][140/2119] lr: 4.0000e-04 eta: 0:09:39 time: 0.3116 data_time: 0.0205 memory: 5821 grad_norm: 5.6735 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7453 loss: 1.7453 2022/10/08 16:44:33 - mmengine - INFO - Epoch(train) [150][160/2119] lr: 4.0000e-04 eta: 0:09:34 time: 0.2763 data_time: 0.0171 memory: 5821 grad_norm: 5.5302 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6582 loss: 1.6582 2022/10/08 16:44:38 - mmengine - INFO - Epoch(train) [150][180/2119] lr: 4.0000e-04 eta: 0:09:28 time: 0.2521 data_time: 0.0201 memory: 5821 grad_norm: 5.7259 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8257 loss: 1.8257 2022/10/08 16:44:44 - mmengine - INFO - Epoch(train) [150][200/2119] lr: 4.0000e-04 eta: 0:09:22 time: 0.3142 data_time: 0.0232 memory: 5821 grad_norm: 5.6856 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.7674 loss: 1.7674 2022/10/08 16:44:50 - mmengine - INFO - Epoch(train) [150][220/2119] lr: 4.0000e-04 eta: 0:09:16 time: 0.2929 data_time: 0.0219 memory: 5821 grad_norm: 5.7464 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7216 loss: 1.7216 2022/10/08 16:44:56 - mmengine - INFO - Epoch(train) [150][240/2119] lr: 4.0000e-04 eta: 0:09:10 time: 0.2976 data_time: 0.0192 memory: 5821 grad_norm: 5.6384 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7324 loss: 1.7324 2022/10/08 16:45:02 - mmengine - INFO - Epoch(train) [150][260/2119] lr: 4.0000e-04 eta: 0:09:04 time: 0.3041 data_time: 0.0194 memory: 5821 grad_norm: 5.6458 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7519 loss: 1.7519 2022/10/08 16:45:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 16:45:08 - mmengine - INFO - Epoch(train) [150][280/2119] lr: 4.0000e-04 eta: 0:08:58 time: 0.2858 data_time: 0.0224 memory: 5821 grad_norm: 5.5632 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7944 loss: 1.7944 2022/10/08 16:45:13 - mmengine - INFO - Epoch(train) [150][300/2119] lr: 4.0000e-04 eta: 0:08:53 time: 0.2557 data_time: 0.0201 memory: 5821 grad_norm: 5.7118 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6492 loss: 1.6492 2022/10/08 16:45:19 - mmengine - INFO - Epoch(train) [150][320/2119] lr: 4.0000e-04 eta: 0:08:47 time: 0.3015 data_time: 0.0219 memory: 5821 grad_norm: 5.6726 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5263 loss: 1.5263 2022/10/08 16:45:24 - mmengine - INFO - Epoch(train) [150][340/2119] lr: 4.0000e-04 eta: 0:08:41 time: 0.2703 data_time: 0.0279 memory: 5821 grad_norm: 5.6323 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.7888 loss: 1.7888 2022/10/08 16:45:30 - mmengine - INFO - Epoch(train) [150][360/2119] lr: 4.0000e-04 eta: 0:08:35 time: 0.2850 data_time: 0.0147 memory: 5821 grad_norm: 5.7432 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7632 loss: 1.7632 2022/10/08 16:45:36 - mmengine - INFO - Epoch(train) [150][380/2119] lr: 4.0000e-04 eta: 0:08:29 time: 0.2831 data_time: 0.0250 memory: 5821 grad_norm: 5.6563 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0769 loss: 2.0769 2022/10/08 16:45:41 - mmengine - INFO - Epoch(train) [150][400/2119] lr: 4.0000e-04 eta: 0:08:23 time: 0.2832 data_time: 0.0217 memory: 5821 grad_norm: 5.5968 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9644 loss: 1.9644 2022/10/08 16:45:47 - mmengine - INFO - Epoch(train) [150][420/2119] lr: 4.0000e-04 eta: 0:08:17 time: 0.3022 data_time: 0.0229 memory: 5821 grad_norm: 5.6253 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.6776 loss: 1.6776 2022/10/08 16:45:53 - mmengine - INFO - Epoch(train) [150][440/2119] lr: 4.0000e-04 eta: 0:08:11 time: 0.2791 data_time: 0.0237 memory: 5821 grad_norm: 5.6416 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5988 loss: 1.5988 2022/10/08 16:45:59 - mmengine - INFO - Epoch(train) [150][460/2119] lr: 4.0000e-04 eta: 0:08:06 time: 0.2779 data_time: 0.0240 memory: 5821 grad_norm: 5.5866 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6842 loss: 1.6842 2022/10/08 16:46:05 - mmengine - INFO - Epoch(train) [150][480/2119] lr: 4.0000e-04 eta: 0:08:00 time: 0.3011 data_time: 0.0229 memory: 5821 grad_norm: 5.7096 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8677 loss: 1.8677 2022/10/08 16:46:10 - mmengine - INFO - Epoch(train) [150][500/2119] lr: 4.0000e-04 eta: 0:07:54 time: 0.2767 data_time: 0.0176 memory: 5821 grad_norm: 5.6625 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7593 loss: 1.7593 2022/10/08 16:46:16 - mmengine - INFO - Epoch(train) [150][520/2119] lr: 4.0000e-04 eta: 0:07:48 time: 0.2881 data_time: 0.0198 memory: 5821 grad_norm: 5.6993 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8681 loss: 1.8681 2022/10/08 16:46:22 - mmengine - INFO - Epoch(train) [150][540/2119] lr: 4.0000e-04 eta: 0:07:42 time: 0.2835 data_time: 0.0230 memory: 5821 grad_norm: 5.6379 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8887 loss: 1.8887 2022/10/08 16:46:27 - mmengine - INFO - Epoch(train) [150][560/2119] lr: 4.0000e-04 eta: 0:07:36 time: 0.2852 data_time: 0.0183 memory: 5821 grad_norm: 5.6159 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6930 loss: 1.6930 2022/10/08 16:46:33 - mmengine - INFO - Epoch(train) [150][580/2119] lr: 4.0000e-04 eta: 0:07:30 time: 0.2820 data_time: 0.0187 memory: 5821 grad_norm: 5.8442 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.0892 loss: 2.0892 2022/10/08 16:46:39 - mmengine - INFO - Epoch(train) [150][600/2119] lr: 4.0000e-04 eta: 0:07:25 time: 0.2834 data_time: 0.0197 memory: 5821 grad_norm: 5.5924 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8273 loss: 1.8273 2022/10/08 16:46:44 - mmengine - INFO - Epoch(train) [150][620/2119] lr: 4.0000e-04 eta: 0:07:19 time: 0.2803 data_time: 0.0178 memory: 5821 grad_norm: 5.6748 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7624 loss: 1.7624 2022/10/08 16:46:50 - mmengine - INFO - Epoch(train) [150][640/2119] lr: 4.0000e-04 eta: 0:07:13 time: 0.2899 data_time: 0.0169 memory: 5821 grad_norm: 5.6557 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7705 loss: 1.7705 2022/10/08 16:46:56 - mmengine - INFO - Epoch(train) [150][660/2119] lr: 4.0000e-04 eta: 0:07:07 time: 0.2981 data_time: 0.0185 memory: 5821 grad_norm: 5.7190 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7389 loss: 1.7389 2022/10/08 16:47:01 - mmengine - INFO - Epoch(train) [150][680/2119] lr: 4.0000e-04 eta: 0:07:01 time: 0.2651 data_time: 0.0238 memory: 5821 grad_norm: 5.6814 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9464 loss: 1.9464 2022/10/08 16:47:07 - mmengine - INFO - Epoch(train) [150][700/2119] lr: 4.0000e-04 eta: 0:06:55 time: 0.2884 data_time: 0.0217 memory: 5821 grad_norm: 5.6260 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7234 loss: 1.7234 2022/10/08 16:47:13 - mmengine - INFO - Epoch(train) [150][720/2119] lr: 4.0000e-04 eta: 0:06:49 time: 0.3040 data_time: 0.0165 memory: 5821 grad_norm: 5.6267 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.6725 loss: 1.6725 2022/10/08 16:47:19 - mmengine - INFO - Epoch(train) [150][740/2119] lr: 4.0000e-04 eta: 0:06:43 time: 0.2844 data_time: 0.0219 memory: 5821 grad_norm: 5.7523 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.7368 loss: 1.7368 2022/10/08 16:47:25 - mmengine - INFO - Epoch(train) [150][760/2119] lr: 4.0000e-04 eta: 0:06:38 time: 0.2827 data_time: 0.0135 memory: 5821 grad_norm: 5.7141 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9053 loss: 1.9053 2022/10/08 16:47:30 - mmengine - INFO - Epoch(train) [150][780/2119] lr: 4.0000e-04 eta: 0:06:32 time: 0.2917 data_time: 0.0191 memory: 5821 grad_norm: 5.6929 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.6132 loss: 1.6132 2022/10/08 16:47:36 - mmengine - INFO - Epoch(train) [150][800/2119] lr: 4.0000e-04 eta: 0:06:26 time: 0.2727 data_time: 0.0176 memory: 5821 grad_norm: 5.7690 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7918 loss: 1.7918 2022/10/08 16:47:42 - mmengine - INFO - Epoch(train) [150][820/2119] lr: 4.0000e-04 eta: 0:06:20 time: 0.2967 data_time: 0.0201 memory: 5821 grad_norm: 5.6652 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7249 loss: 1.7249 2022/10/08 16:47:48 - mmengine - INFO - Epoch(train) [150][840/2119] lr: 4.0000e-04 eta: 0:06:14 time: 0.3047 data_time: 0.0161 memory: 5821 grad_norm: 5.6929 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7387 loss: 1.7387 2022/10/08 16:47:54 - mmengine - INFO - Epoch(train) [150][860/2119] lr: 4.0000e-04 eta: 0:06:08 time: 0.2859 data_time: 0.0221 memory: 5821 grad_norm: 5.7838 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.9117 loss: 1.9117 2022/10/08 16:47:59 - mmengine - INFO - Epoch(train) [150][880/2119] lr: 4.0000e-04 eta: 0:06:02 time: 0.2820 data_time: 0.0155 memory: 5821 grad_norm: 5.7189 top1_acc: 0.6875 top5_acc: 0.6875 loss_cls: 1.7734 loss: 1.7734 2022/10/08 16:48:05 - mmengine - INFO - Epoch(train) [150][900/2119] lr: 4.0000e-04 eta: 0:05:57 time: 0.3058 data_time: 0.0264 memory: 5821 grad_norm: 5.7635 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6659 loss: 1.6659 2022/10/08 16:48:11 - mmengine - INFO - Epoch(train) [150][920/2119] lr: 4.0000e-04 eta: 0:05:51 time: 0.2567 data_time: 0.0145 memory: 5821 grad_norm: 5.5364 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7791 loss: 1.7791 2022/10/08 16:48:17 - mmengine - INFO - Epoch(train) [150][940/2119] lr: 4.0000e-04 eta: 0:05:45 time: 0.3011 data_time: 0.0221 memory: 5821 grad_norm: 5.7120 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7904 loss: 1.7904 2022/10/08 16:48:22 - mmengine - INFO - Epoch(train) [150][960/2119] lr: 4.0000e-04 eta: 0:05:39 time: 0.2837 data_time: 0.0144 memory: 5821 grad_norm: 5.6480 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8340 loss: 1.8340 2022/10/08 16:48:28 - mmengine - INFO - Epoch(train) [150][980/2119] lr: 4.0000e-04 eta: 0:05:33 time: 0.2791 data_time: 0.0200 memory: 5821 grad_norm: 5.6106 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5141 loss: 1.5141 2022/10/08 16:48:33 - mmengine - INFO - Epoch(train) [150][1000/2119] lr: 4.0000e-04 eta: 0:05:27 time: 0.2670 data_time: 0.0264 memory: 5821 grad_norm: 5.6763 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8109 loss: 1.8109 2022/10/08 16:48:39 - mmengine - INFO - Epoch(train) [150][1020/2119] lr: 4.0000e-04 eta: 0:05:21 time: 0.3034 data_time: 0.0197 memory: 5821 grad_norm: 5.6766 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9228 loss: 1.9228 2022/10/08 16:48:45 - mmengine - INFO - Epoch(train) [150][1040/2119] lr: 4.0000e-04 eta: 0:05:16 time: 0.2967 data_time: 0.0238 memory: 5821 grad_norm: 5.6525 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6665 loss: 1.6665 2022/10/08 16:48:51 - mmengine - INFO - Epoch(train) [150][1060/2119] lr: 4.0000e-04 eta: 0:05:10 time: 0.2737 data_time: 0.0203 memory: 5821 grad_norm: 5.6497 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7776 loss: 1.7776 2022/10/08 16:48:57 - mmengine - INFO - Epoch(train) [150][1080/2119] lr: 4.0000e-04 eta: 0:05:04 time: 0.2926 data_time: 0.0161 memory: 5821 grad_norm: 5.7680 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7455 loss: 1.7455 2022/10/08 16:49:03 - mmengine - INFO - Epoch(train) [150][1100/2119] lr: 4.0000e-04 eta: 0:04:58 time: 0.2995 data_time: 0.0255 memory: 5821 grad_norm: 5.6650 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7063 loss: 1.7063 2022/10/08 16:49:09 - mmengine - INFO - Epoch(train) [150][1120/2119] lr: 4.0000e-04 eta: 0:04:52 time: 0.2964 data_time: 0.0140 memory: 5821 grad_norm: 5.6305 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6858 loss: 1.6858 2022/10/08 16:49:14 - mmengine - INFO - Epoch(train) [150][1140/2119] lr: 4.0000e-04 eta: 0:04:46 time: 0.2672 data_time: 0.0227 memory: 5821 grad_norm: 5.6859 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5365 loss: 1.5365 2022/10/08 16:49:20 - mmengine - INFO - Epoch(train) [150][1160/2119] lr: 4.0000e-04 eta: 0:04:40 time: 0.2963 data_time: 0.0237 memory: 5821 grad_norm: 5.6409 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8092 loss: 1.8092 2022/10/08 16:49:26 - mmengine - INFO - Epoch(train) [150][1180/2119] lr: 4.0000e-04 eta: 0:04:35 time: 0.2872 data_time: 0.0248 memory: 5821 grad_norm: 5.6585 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6827 loss: 1.6827 2022/10/08 16:49:31 - mmengine - INFO - Epoch(train) [150][1200/2119] lr: 4.0000e-04 eta: 0:04:29 time: 0.2964 data_time: 0.0263 memory: 5821 grad_norm: 5.6031 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7399 loss: 1.7399 2022/10/08 16:49:37 - mmengine - INFO - Epoch(train) [150][1220/2119] lr: 4.0000e-04 eta: 0:04:23 time: 0.2829 data_time: 0.0161 memory: 5821 grad_norm: 5.6794 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.7652 loss: 1.7652 2022/10/08 16:49:43 - mmengine - INFO - Epoch(train) [150][1240/2119] lr: 4.0000e-04 eta: 0:04:17 time: 0.2984 data_time: 0.0238 memory: 5821 grad_norm: 5.7140 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0192 loss: 2.0192 2022/10/08 16:49:49 - mmengine - INFO - Epoch(train) [150][1260/2119] lr: 4.0000e-04 eta: 0:04:11 time: 0.2797 data_time: 0.0217 memory: 5821 grad_norm: 5.6866 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5916 loss: 1.5916 2022/10/08 16:49:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 16:49:54 - mmengine - INFO - Epoch(train) [150][1280/2119] lr: 4.0000e-04 eta: 0:04:05 time: 0.2683 data_time: 0.0284 memory: 5821 grad_norm: 5.6711 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9124 loss: 1.9124 2022/10/08 16:50:00 - mmengine - INFO - Epoch(train) [150][1300/2119] lr: 4.0000e-04 eta: 0:03:59 time: 0.2792 data_time: 0.0190 memory: 5821 grad_norm: 5.5848 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9543 loss: 1.9543 2022/10/08 16:50:07 - mmengine - INFO - Epoch(train) [150][1320/2119] lr: 4.0000e-04 eta: 0:03:54 time: 0.3495 data_time: 0.0301 memory: 5821 grad_norm: 5.6564 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8038 loss: 1.8038 2022/10/08 16:50:12 - mmengine - INFO - Epoch(train) [150][1340/2119] lr: 4.0000e-04 eta: 0:03:48 time: 0.2466 data_time: 0.0171 memory: 5821 grad_norm: 5.7288 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8014 loss: 1.8014 2022/10/08 16:50:17 - mmengine - INFO - Epoch(train) [150][1360/2119] lr: 4.0000e-04 eta: 0:03:42 time: 0.2866 data_time: 0.0308 memory: 5821 grad_norm: 5.6833 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6816 loss: 1.6816 2022/10/08 16:50:23 - mmengine - INFO - Epoch(train) [150][1380/2119] lr: 4.0000e-04 eta: 0:03:36 time: 0.2939 data_time: 0.0220 memory: 5821 grad_norm: 5.6003 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7582 loss: 1.7582 2022/10/08 16:50:29 - mmengine - INFO - Epoch(train) [150][1400/2119] lr: 4.0000e-04 eta: 0:03:30 time: 0.2726 data_time: 0.0210 memory: 5821 grad_norm: 5.6256 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8090 loss: 1.8090 2022/10/08 16:50:35 - mmengine - INFO - Epoch(train) [150][1420/2119] lr: 4.0000e-04 eta: 0:03:24 time: 0.3052 data_time: 0.0172 memory: 5821 grad_norm: 5.7202 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.7242 loss: 1.7242 2022/10/08 16:50:41 - mmengine - INFO - Epoch(train) [150][1440/2119] lr: 4.0000e-04 eta: 0:03:18 time: 0.2916 data_time: 0.0178 memory: 5821 grad_norm: 5.8128 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9634 loss: 1.9634 2022/10/08 16:50:47 - mmengine - INFO - Epoch(train) [150][1460/2119] lr: 4.0000e-04 eta: 0:03:12 time: 0.3028 data_time: 0.0185 memory: 5821 grad_norm: 5.6688 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0859 loss: 2.0859 2022/10/08 16:50:52 - mmengine - INFO - Epoch(train) [150][1480/2119] lr: 4.0000e-04 eta: 0:03:07 time: 0.2625 data_time: 0.0179 memory: 5821 grad_norm: 5.8128 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.8999 loss: 1.8999 2022/10/08 16:50:58 - mmengine - INFO - Epoch(train) [150][1500/2119] lr: 4.0000e-04 eta: 0:03:01 time: 0.2798 data_time: 0.0275 memory: 5821 grad_norm: 5.5649 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7179 loss: 1.7179 2022/10/08 16:51:04 - mmengine - INFO - Epoch(train) [150][1520/2119] lr: 4.0000e-04 eta: 0:02:55 time: 0.3096 data_time: 0.0231 memory: 5821 grad_norm: 5.6020 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.9752 loss: 1.9752 2022/10/08 16:51:10 - mmengine - INFO - Epoch(train) [150][1540/2119] lr: 4.0000e-04 eta: 0:02:49 time: 0.3132 data_time: 0.0262 memory: 5821 grad_norm: 5.6021 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8633 loss: 1.8633 2022/10/08 16:51:15 - mmengine - INFO - Epoch(train) [150][1560/2119] lr: 4.0000e-04 eta: 0:02:43 time: 0.2518 data_time: 0.0309 memory: 5821 grad_norm: 5.6195 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.7052 loss: 1.7052 2022/10/08 16:51:21 - mmengine - INFO - Epoch(train) [150][1580/2119] lr: 4.0000e-04 eta: 0:02:37 time: 0.3043 data_time: 0.0361 memory: 5821 grad_norm: 5.7946 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7714 loss: 1.7714 2022/10/08 16:51:27 - mmengine - INFO - Epoch(train) [150][1600/2119] lr: 4.0000e-04 eta: 0:02:31 time: 0.3048 data_time: 0.0254 memory: 5821 grad_norm: 5.7447 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7583 loss: 1.7583 2022/10/08 16:51:33 - mmengine - INFO - Epoch(train) [150][1620/2119] lr: 4.0000e-04 eta: 0:02:26 time: 0.2568 data_time: 0.0306 memory: 5821 grad_norm: 5.6898 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9650 loss: 1.9650 2022/10/08 16:51:38 - mmengine - INFO - Epoch(train) [150][1640/2119] lr: 4.0000e-04 eta: 0:02:20 time: 0.2913 data_time: 0.0326 memory: 5821 grad_norm: 5.7274 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9641 loss: 1.9641 2022/10/08 16:51:44 - mmengine - INFO - Epoch(train) [150][1660/2119] lr: 4.0000e-04 eta: 0:02:14 time: 0.3049 data_time: 0.0272 memory: 5821 grad_norm: 5.5910 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.0543 loss: 2.0543 2022/10/08 16:51:50 - mmengine - INFO - Epoch(train) [150][1680/2119] lr: 4.0000e-04 eta: 0:02:08 time: 0.2886 data_time: 0.0265 memory: 5821 grad_norm: 5.6465 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8692 loss: 1.8692 2022/10/08 16:51:56 - mmengine - INFO - Epoch(train) [150][1700/2119] lr: 4.0000e-04 eta: 0:02:02 time: 0.2651 data_time: 0.0262 memory: 5821 grad_norm: 5.5947 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5528 loss: 1.5528 2022/10/08 16:52:01 - mmengine - INFO - Epoch(train) [150][1720/2119] lr: 4.0000e-04 eta: 0:01:56 time: 0.2694 data_time: 0.0327 memory: 5821 grad_norm: 5.6802 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.6443 loss: 1.6443 2022/10/08 16:52:08 - mmengine - INFO - Epoch(train) [150][1740/2119] lr: 4.0000e-04 eta: 0:01:50 time: 0.3289 data_time: 0.0254 memory: 5821 grad_norm: 5.6437 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7370 loss: 1.7370 2022/10/08 16:52:13 - mmengine - INFO - Epoch(train) [150][1760/2119] lr: 4.0000e-04 eta: 0:01:45 time: 0.2569 data_time: 0.0284 memory: 5821 grad_norm: 5.6984 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6970 loss: 1.6970 2022/10/08 16:52:19 - mmengine - INFO - Epoch(train) [150][1780/2119] lr: 4.0000e-04 eta: 0:01:39 time: 0.3103 data_time: 0.0312 memory: 5821 grad_norm: 5.6707 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8814 loss: 1.8814 2022/10/08 16:52:25 - mmengine - INFO - Epoch(train) [150][1800/2119] lr: 4.0000e-04 eta: 0:01:33 time: 0.2888 data_time: 0.0285 memory: 5821 grad_norm: 5.7471 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6612 loss: 1.6612 2022/10/08 16:52:30 - mmengine - INFO - Epoch(train) [150][1820/2119] lr: 4.0000e-04 eta: 0:01:27 time: 0.2696 data_time: 0.0251 memory: 5821 grad_norm: 5.7110 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8452 loss: 1.8452 2022/10/08 16:52:36 - mmengine - INFO - Epoch(train) [150][1840/2119] lr: 4.0000e-04 eta: 0:01:21 time: 0.2746 data_time: 0.0369 memory: 5821 grad_norm: 5.6559 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.8035 loss: 1.8035 2022/10/08 16:52:42 - mmengine - INFO - Epoch(train) [150][1860/2119] lr: 4.0000e-04 eta: 0:01:15 time: 0.3147 data_time: 0.0292 memory: 5821 grad_norm: 5.6712 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8378 loss: 1.8378 2022/10/08 16:52:49 - mmengine - INFO - Epoch(train) [150][1880/2119] lr: 4.0000e-04 eta: 0:01:09 time: 0.3426 data_time: 0.0271 memory: 5821 grad_norm: 5.6126 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5671 loss: 1.5671 2022/10/08 16:52:54 - mmengine - INFO - Epoch(train) [150][1900/2119] lr: 4.0000e-04 eta: 0:01:04 time: 0.2692 data_time: 0.0374 memory: 5821 grad_norm: 5.5794 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.6282 loss: 1.6282 2022/10/08 16:53:00 - mmengine - INFO - Epoch(train) [150][1920/2119] lr: 4.0000e-04 eta: 0:00:58 time: 0.2668 data_time: 0.0300 memory: 5821 grad_norm: 5.7528 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9271 loss: 1.9271 2022/10/08 16:53:06 - mmengine - INFO - Epoch(train) [150][1940/2119] lr: 4.0000e-04 eta: 0:00:52 time: 0.3069 data_time: 0.0280 memory: 5821 grad_norm: 5.7196 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6458 loss: 1.6458 2022/10/08 16:53:11 - mmengine - INFO - Epoch(train) [150][1960/2119] lr: 4.0000e-04 eta: 0:00:46 time: 0.2769 data_time: 0.0305 memory: 5821 grad_norm: 5.7627 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8081 loss: 1.8081 2022/10/08 16:53:17 - mmengine - INFO - Epoch(train) [150][1980/2119] lr: 4.0000e-04 eta: 0:00:40 time: 0.3121 data_time: 0.0285 memory: 5821 grad_norm: 5.7584 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.9484 loss: 1.9484 2022/10/08 16:53:23 - mmengine - INFO - Epoch(train) [150][2000/2119] lr: 4.0000e-04 eta: 0:00:34 time: 0.2763 data_time: 0.0321 memory: 5821 grad_norm: 5.7282 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9426 loss: 1.9426 2022/10/08 16:53:29 - mmengine - INFO - Epoch(train) [150][2020/2119] lr: 4.0000e-04 eta: 0:00:28 time: 0.3053 data_time: 0.0306 memory: 5821 grad_norm: 5.7340 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.5996 loss: 1.5996 2022/10/08 16:53:35 - mmengine - INFO - Epoch(train) [150][2040/2119] lr: 4.0000e-04 eta: 0:00:23 time: 0.3134 data_time: 0.0345 memory: 5821 grad_norm: 5.6708 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7270 loss: 1.7270 2022/10/08 16:53:41 - mmengine - INFO - Epoch(train) [150][2060/2119] lr: 4.0000e-04 eta: 0:00:17 time: 0.2610 data_time: 0.0278 memory: 5821 grad_norm: 5.7753 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8345 loss: 1.8345 2022/10/08 16:53:46 - mmengine - INFO - Epoch(train) [150][2080/2119] lr: 4.0000e-04 eta: 0:00:11 time: 0.2852 data_time: 0.0320 memory: 5821 grad_norm: 5.7176 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8041 loss: 1.8041 2022/10/08 16:53:52 - mmengine - INFO - Epoch(train) [150][2100/2119] lr: 4.0000e-04 eta: 0:00:05 time: 0.2592 data_time: 0.0286 memory: 5821 grad_norm: 5.6295 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.5993 loss: 1.5993 2022/10/08 16:53:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb_20221008_134159 2022/10/08 16:53:57 - mmengine - INFO - Epoch(train) [150][2119/2119] lr: 4.0000e-04 eta: 0:00:05 time: 0.2819 data_time: 0.0206 memory: 5821 grad_norm: 5.7011 top1_acc: 0.7000 top5_acc: 1.0000 loss_cls: 1.5714 loss: 1.5714 2022/10/08 16:53:57 - mmengine - INFO - Saving checkpoint at 150 epochs 2022/10/08 16:54:05 - mmengine - INFO - Epoch(val) [150][20/137] eta: 0:00:36 time: 0.3147 data_time: 0.2495 memory: 1236 2022/10/08 16:54:09 - mmengine - INFO - Epoch(val) [150][40/137] eta: 0:00:21 time: 0.2229 data_time: 0.1566 memory: 1236 2022/10/08 16:54:15 - mmengine - INFO - Epoch(val) [150][60/137] eta: 0:00:21 time: 0.2761 data_time: 0.2083 memory: 1236 2022/10/08 16:54:20 - mmengine - INFO - Epoch(val) [150][80/137] eta: 0:00:13 time: 0.2386 data_time: 0.1698 memory: 1236 2022/10/08 16:54:25 - mmengine - INFO - Epoch(val) [150][100/137] eta: 0:00:09 time: 0.2636 data_time: 0.1987 memory: 1236 2022/10/08 16:54:29 - mmengine - INFO - Epoch(val) [150][120/137] eta: 0:00:03 time: 0.1946 data_time: 0.1299 memory: 1236 2022/10/08 16:54:39 - mmengine - INFO - Epoch(val) [150][137/137] acc/top1: 0.5631 acc/top5: 0.7842 acc/mean1: 0.5630 2022/10/08 16:54:39 - mmengine - INFO - The previous best checkpoint /mnt/lustre/hukai/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-4x16x1-steplr-150e_kinetics700-rgb/best_acc/top1_epoch_145.pth is removed 2022/10/08 16:54:41 - mmengine - INFO - The best checkpoint with 0.5631 acc/top1 at 150 epoch is saved to best_acc/top1_epoch_150.pth.