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 -