2022/10/14 18:38:23 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.8.13 (default, Mar 28 2022, 11:38:47) [GCC 7.5.0] CUDA available: True numpy_random_seed: 512889092 GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 11.2, V11.2.152 GCC: gcc (GCC) 5.4.0 PyTorch: 1.10.0+cu113 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 11.3 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86 - CuDNN 8.2 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, 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+cu113 OpenCV: 4.6.0 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: 8 ------------------------------------------------------------ 2022/10/14 18:38:23 - mmengine - INFO - Config: model = dict( type='Recognizer3D', backbone=dict( type='C2D', depth=50, pretrained='https://download.pytorch.org/models/resnet50-11ad3fa6.pth', norm_eval=False), cls_head=dict( type='I3DHead', num_classes=400, in_channels=2048, spatial_type='avg', dropout_ratio=0.5, init_std=0.01, 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 = dict( type='EpochBasedTrainLoop', max_epochs=100, val_begin=1, val_interval=1) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') param_scheduler = [ dict( type='MultiStepLR', begin=0, end=100, by_epoch=True, milestones=[40, 80], gamma=0.1) ] optim_wrapper = dict( optimizer=dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001), clip_grad=dict(max_norm=40, norm_type=2)) 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=3, 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/kinetics400/videos_train' data_root_val = 'data/kinetics400/videos_val' ann_file_train = 'data/kinetics400/kinetics400_train_list_videos.txt' ann_file_val = 'data/kinetics400/kinetics400_val_list_videos.txt' file_client_args = dict( io_backend='petrel', path_mapping=dict( {'data/kinetics400': 's3://openmmlab/datasets/action/Kinetics400'})) train_pipeline = [ dict( type='DecordInit', io_backend='petrel', path_mapping=dict( {'data/kinetics400': 's3://openmmlab/datasets/action/Kinetics400'})), dict(type='SampleFrames', clip_len=16, frame_interval=4, num_clips=1), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict( type='MultiScaleCrop', input_size=224, scales=(1, 0.875, 0.75, 0.66), random_crop=False, max_wh_scale_gap=1), 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/kinetics400': 's3://openmmlab/datasets/action/Kinetics400'})), dict( type='SampleFrames', clip_len=16, frame_interval=4, 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/kinetics400': 's3://openmmlab/datasets/action/Kinetics400'})), dict( type='SampleFrames', clip_len=16, frame_interval=4, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 224)), dict(type='ThreeCrop', crop_size=224), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ] train_dataloader = dict( batch_size=32, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='VideoDataset', ann_file='data/kinetics400/kinetics400_train_list_videos.txt', data_prefix=dict(video='data/kinetics400/videos_train'), pipeline=[ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/kinetics400': 's3://openmmlab/datasets/action/Kinetics400' })), dict( type='SampleFrames', clip_len=16, frame_interval=4, num_clips=1), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict( type='MultiScaleCrop', input_size=224, scales=(1, 0.875, 0.75, 0.66), random_crop=False, max_wh_scale_gap=1), 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=32, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='VideoDataset', ann_file='data/kinetics400/kinetics400_val_list_videos.txt', data_prefix=dict(video='data/kinetics400/videos_val'), pipeline=[ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/kinetics400': 's3://openmmlab/datasets/action/Kinetics400' })), dict( type='SampleFrames', clip_len=16, frame_interval=4, 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/kinetics400/kinetics400_val_list_videos.txt', data_prefix=dict(video='data/kinetics400/videos_val'), pipeline=[ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/kinetics400': 's3://openmmlab/datasets/action/Kinetics400' })), dict( type='SampleFrames', clip_len=16, frame_interval=4, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 224)), dict(type='ThreeCrop', crop_size=224), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True)) val_evaluator = dict(type='AccMetric') test_evaluator = dict(type='AccMetric') auto_scale_lr = dict(enable=False, base_batch_size=256) launcher = 'slurm' work_dir = './work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb' 2022/10/14 18:38:25 - mmengine - INFO - These parameters in pretrained checkpoint are not loaded: {'fc.bias', 'fc.weight'} 2022/10/14 18:38:25 - mmengine - INFO - Checkpoints will be saved to /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb. 2022/10/14 18:38:47 - mmengine - INFO - Epoch(train) [1][20/940] lr: 1.0000e-02 eta: 1 day, 5:13:55 time: 1.1198 data_time: 0.5014 memory: 33630 grad_norm: 0.9629 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.9803 loss: 5.9803 2022/10/14 18:38:59 - mmengine - INFO - Epoch(train) [1][40/940] lr: 1.0000e-02 eta: 22:12:54 time: 0.5825 data_time: 0.0341 memory: 33630 grad_norm: 0.9738 top1_acc: 0.0000 top5_acc: 0.0625 loss_cls: 5.9242 loss: 5.9242 2022/10/14 18:39:11 - mmengine - INFO - Epoch(train) [1][60/940] lr: 1.0000e-02 eta: 19:54:43 time: 0.5869 data_time: 0.0424 memory: 33630 grad_norm: 1.2023 top1_acc: 0.0312 top5_acc: 0.0938 loss_cls: 5.8324 loss: 5.8324 2022/10/14 18:39:22 - mmengine - INFO - Epoch(train) [1][80/940] lr: 1.0000e-02 eta: 18:42:21 time: 0.5788 data_time: 0.0331 memory: 33630 grad_norm: 1.4581 top1_acc: 0.0000 top5_acc: 0.0625 loss_cls: 5.6716 loss: 5.6716 2022/10/14 18:39:34 - mmengine - INFO - Epoch(train) [1][100/940] lr: 1.0000e-02 eta: 18:03:47 time: 0.5946 data_time: 0.0421 memory: 33630 grad_norm: 1.7252 top1_acc: 0.0938 top5_acc: 0.2812 loss_cls: 5.4756 loss: 5.4756 2022/10/14 18:39:46 - mmengine - INFO - Epoch(train) [1][120/940] lr: 1.0000e-02 eta: 17:36:36 time: 0.5892 data_time: 0.0305 memory: 33630 grad_norm: 2.0006 top1_acc: 0.0938 top5_acc: 0.1875 loss_cls: 5.1933 loss: 5.1933 2022/10/14 18:39:58 - mmengine - INFO - Epoch(train) [1][140/940] lr: 1.0000e-02 eta: 17:16:15 time: 0.5853 data_time: 0.0419 memory: 33630 grad_norm: 2.2632 top1_acc: 0.1562 top5_acc: 0.3750 loss_cls: 4.7550 loss: 4.7550 2022/10/14 18:40:10 - mmengine - INFO - Epoch(train) [1][160/940] lr: 1.0000e-02 eta: 17:01:14 time: 0.5867 data_time: 0.0315 memory: 33630 grad_norm: 2.4433 top1_acc: 0.1250 top5_acc: 0.2188 loss_cls: 4.6416 loss: 4.6416 2022/10/14 18:40:21 - mmengine - INFO - Epoch(train) [1][180/940] lr: 1.0000e-02 eta: 16:50:11 time: 0.5906 data_time: 0.0330 memory: 33630 grad_norm: 2.5802 top1_acc: 0.1875 top5_acc: 0.5625 loss_cls: 4.3166 loss: 4.3166 2022/10/14 18:40:33 - mmengine - INFO - Epoch(train) [1][200/940] lr: 1.0000e-02 eta: 16:40:03 time: 0.5827 data_time: 0.0335 memory: 33630 grad_norm: 2.6455 top1_acc: 0.1875 top5_acc: 0.3438 loss_cls: 4.2093 loss: 4.2093 2022/10/14 18:40:45 - mmengine - INFO - Epoch(train) [1][220/940] lr: 1.0000e-02 eta: 16:30:28 time: 0.5737 data_time: 0.0373 memory: 33630 grad_norm: 2.7566 top1_acc: 0.2188 top5_acc: 0.5000 loss_cls: 3.9495 loss: 3.9495 2022/10/14 18:40:56 - mmengine - INFO - Epoch(train) [1][240/940] lr: 1.0000e-02 eta: 16:25:36 time: 0.5979 data_time: 0.0303 memory: 33630 grad_norm: 2.8290 top1_acc: 0.2812 top5_acc: 0.5000 loss_cls: 3.9336 loss: 3.9336 2022/10/14 18:41:08 - mmengine - INFO - Epoch(train) [1][260/940] lr: 1.0000e-02 eta: 16:20:42 time: 0.5917 data_time: 0.0359 memory: 33630 grad_norm: 2.8668 top1_acc: 0.3438 top5_acc: 0.5000 loss_cls: 3.8741 loss: 3.8741 2022/10/14 18:41:20 - mmengine - INFO - Epoch(train) [1][280/940] lr: 1.0000e-02 eta: 16:15:30 time: 0.5830 data_time: 0.0310 memory: 33630 grad_norm: 2.8910 top1_acc: 0.2500 top5_acc: 0.4688 loss_cls: 3.7529 loss: 3.7529 2022/10/14 18:41:32 - mmengine - INFO - Epoch(train) [1][300/940] lr: 1.0000e-02 eta: 16:10:19 time: 0.5768 data_time: 0.0387 memory: 33630 grad_norm: 2.9363 top1_acc: 0.1875 top5_acc: 0.4062 loss_cls: 3.6845 loss: 3.6845 2022/10/14 18:41:43 - mmengine - INFO - Epoch(train) [1][320/940] lr: 1.0000e-02 eta: 16:05:59 time: 0.5790 data_time: 0.0433 memory: 33630 grad_norm: 2.9771 top1_acc: 0.1562 top5_acc: 0.2188 loss_cls: 3.6756 loss: 3.6756 2022/10/14 18:41:55 - mmengine - INFO - Epoch(train) [1][340/940] lr: 1.0000e-02 eta: 16:03:59 time: 0.5991 data_time: 0.0307 memory: 33630 grad_norm: 2.9904 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 3.5572 loss: 3.5572 2022/10/14 18:42:07 - mmengine - INFO - Epoch(train) [1][360/940] lr: 1.0000e-02 eta: 16:01:14 time: 0.5883 data_time: 0.0394 memory: 33630 grad_norm: 2.9838 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 3.5151 loss: 3.5151 2022/10/14 18:42:19 - mmengine - INFO - Epoch(train) [1][380/940] lr: 1.0000e-02 eta: 15:58:46 time: 0.5885 data_time: 0.0364 memory: 33630 grad_norm: 3.0028 top1_acc: 0.2500 top5_acc: 0.5312 loss_cls: 3.2213 loss: 3.2213 2022/10/14 18:42:30 - mmengine - INFO - Epoch(train) [1][400/940] lr: 1.0000e-02 eta: 15:56:32 time: 0.5883 data_time: 0.0414 memory: 33630 grad_norm: 3.0280 top1_acc: 0.2188 top5_acc: 0.3750 loss_cls: 3.4488 loss: 3.4488 2022/10/14 18:42:42 - mmengine - INFO - Epoch(train) [1][420/940] lr: 1.0000e-02 eta: 15:54:43 time: 0.5916 data_time: 0.0302 memory: 33630 grad_norm: 3.0471 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.4567 loss: 3.4567 2022/10/14 18:42:54 - mmengine - INFO - Epoch(train) [1][440/940] lr: 1.0000e-02 eta: 15:51:57 time: 0.5760 data_time: 0.0398 memory: 33630 grad_norm: 3.0703 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 3.2980 loss: 3.2980 2022/10/14 18:43:05 - mmengine - INFO - Epoch(train) [1][460/940] lr: 1.0000e-02 eta: 15:49:27 time: 0.5765 data_time: 0.0386 memory: 33630 grad_norm: 3.2183 top1_acc: 0.2500 top5_acc: 0.5312 loss_cls: 3.3258 loss: 3.3258 2022/10/14 18:43:17 - mmengine - INFO - Epoch(train) [1][480/940] lr: 1.0000e-02 eta: 15:47:32 time: 0.5826 data_time: 0.0366 memory: 33630 grad_norm: 3.0611 top1_acc: 0.2188 top5_acc: 0.5312 loss_cls: 3.1984 loss: 3.1984 2022/10/14 18:43:29 - mmengine - INFO - Epoch(train) [1][500/940] lr: 1.0000e-02 eta: 15:45:50 time: 0.5839 data_time: 0.0325 memory: 33630 grad_norm: 3.0901 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 3.1638 loss: 3.1638 2022/10/14 18:43:40 - mmengine - INFO - Epoch(train) [1][520/940] lr: 1.0000e-02 eta: 15:44:20 time: 0.5853 data_time: 0.0326 memory: 33630 grad_norm: 3.0905 top1_acc: 0.2812 top5_acc: 0.6250 loss_cls: 3.1521 loss: 3.1521 2022/10/14 18:43:52 - mmengine - INFO - Epoch(train) [1][540/940] lr: 1.0000e-02 eta: 15:43:05 time: 0.5879 data_time: 0.0395 memory: 33630 grad_norm: 3.0864 top1_acc: 0.3438 top5_acc: 0.5312 loss_cls: 3.2284 loss: 3.2284 2022/10/14 18:44:04 - mmengine - INFO - Epoch(train) [1][560/940] lr: 1.0000e-02 eta: 15:41:28 time: 0.5802 data_time: 0.0388 memory: 33630 grad_norm: 3.0720 top1_acc: 0.3438 top5_acc: 0.6250 loss_cls: 3.2200 loss: 3.2200 2022/10/14 18:44:15 - mmengine - INFO - Epoch(train) [1][580/940] lr: 1.0000e-02 eta: 15:40:16 time: 0.5857 data_time: 0.0440 memory: 33630 grad_norm: 3.1354 top1_acc: 0.1250 top5_acc: 0.4688 loss_cls: 3.1439 loss: 3.1439 2022/10/14 18:44:27 - mmengine - INFO - Epoch(train) [1][600/940] lr: 1.0000e-02 eta: 15:39:19 time: 0.5895 data_time: 0.0447 memory: 33630 grad_norm: 3.0990 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.1522 loss: 3.1522 2022/10/14 18:44:39 - mmengine - INFO - Epoch(train) [1][620/940] lr: 1.0000e-02 eta: 15:37:52 time: 0.5787 data_time: 0.0370 memory: 33630 grad_norm: 3.0837 top1_acc: 0.2812 top5_acc: 0.4375 loss_cls: 3.1717 loss: 3.1717 2022/10/14 18:44:50 - mmengine - INFO - Epoch(train) [1][640/940] lr: 1.0000e-02 eta: 15:36:48 time: 0.5849 data_time: 0.0302 memory: 33630 grad_norm: 3.1383 top1_acc: 0.2188 top5_acc: 0.5625 loss_cls: 3.1275 loss: 3.1275 2022/10/14 18:45:02 - mmengine - INFO - Epoch(train) [1][660/940] lr: 1.0000e-02 eta: 15:35:57 time: 0.5882 data_time: 0.0302 memory: 33630 grad_norm: 3.1201 top1_acc: 0.3438 top5_acc: 0.7812 loss_cls: 3.1138 loss: 3.1138 2022/10/14 18:45:14 - mmengine - INFO - Epoch(train) [1][680/940] lr: 1.0000e-02 eta: 15:35:06 time: 0.5875 data_time: 0.0311 memory: 33630 grad_norm: 3.1438 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 3.0848 loss: 3.0848 2022/10/14 18:45:25 - mmengine - INFO - Epoch(train) [1][700/940] lr: 1.0000e-02 eta: 15:33:44 time: 0.5747 data_time: 0.0315 memory: 33630 grad_norm: 3.1507 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 3.0012 loss: 3.0012 2022/10/14 18:45:37 - mmengine - INFO - Epoch(train) [1][720/940] lr: 1.0000e-02 eta: 15:32:45 time: 0.5826 data_time: 0.0464 memory: 33630 grad_norm: 3.1391 top1_acc: 0.2812 top5_acc: 0.5000 loss_cls: 3.0904 loss: 3.0904 2022/10/14 18:45:49 - mmengine - INFO - Epoch(train) [1][740/940] lr: 1.0000e-02 eta: 15:31:39 time: 0.5783 data_time: 0.0326 memory: 33630 grad_norm: 3.1656 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 3.0080 loss: 3.0080 2022/10/14 18:46:00 - mmengine - INFO - Epoch(train) [1][760/940] lr: 1.0000e-02 eta: 15:30:48 time: 0.5838 data_time: 0.0422 memory: 33630 grad_norm: 3.1286 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 2.9159 loss: 2.9159 2022/10/14 18:46:12 - mmengine - INFO - Epoch(train) [1][780/940] lr: 1.0000e-02 eta: 15:29:57 time: 0.5827 data_time: 0.0350 memory: 33630 grad_norm: 3.1517 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.8614 loss: 2.8614 2022/10/14 18:46:23 - mmengine - INFO - Epoch(train) [1][800/940] lr: 1.0000e-02 eta: 15:28:44 time: 0.5721 data_time: 0.0360 memory: 33630 grad_norm: 3.1685 top1_acc: 0.2812 top5_acc: 0.6250 loss_cls: 2.9325 loss: 2.9325 2022/10/14 18:46:35 - mmengine - INFO - Epoch(train) [1][820/940] lr: 1.0000e-02 eta: 15:27:48 time: 0.5785 data_time: 0.0340 memory: 33630 grad_norm: 3.1416 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.7987 loss: 2.7987 2022/10/14 18:46:47 - mmengine - INFO - Epoch(train) [1][840/940] lr: 1.0000e-02 eta: 15:26:59 time: 0.5807 data_time: 0.0330 memory: 33630 grad_norm: 3.2187 top1_acc: 0.1875 top5_acc: 0.5938 loss_cls: 2.7196 loss: 2.7196 2022/10/14 18:46:58 - mmengine - INFO - Epoch(train) [1][860/940] lr: 1.0000e-02 eta: 15:26:26 time: 0.5875 data_time: 0.0458 memory: 33630 grad_norm: 3.1856 top1_acc: 0.1562 top5_acc: 0.4062 loss_cls: 2.8903 loss: 2.8903 2022/10/14 18:47:10 - mmengine - INFO - Epoch(train) [1][880/940] lr: 1.0000e-02 eta: 15:25:56 time: 0.5883 data_time: 0.0354 memory: 33630 grad_norm: 3.1853 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 3.0460 loss: 3.0460 2022/10/14 18:47:22 - mmengine - INFO - Epoch(train) [1][900/940] lr: 1.0000e-02 eta: 15:25:13 time: 0.5817 data_time: 0.0375 memory: 33630 grad_norm: 3.2206 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 3.0057 loss: 3.0057 2022/10/14 18:47:33 - mmengine - INFO - Epoch(train) [1][920/940] lr: 1.0000e-02 eta: 15:24:30 time: 0.5809 data_time: 0.0337 memory: 33630 grad_norm: 3.1740 top1_acc: 0.3438 top5_acc: 0.6250 loss_cls: 2.7753 loss: 2.7753 2022/10/14 18:47:44 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 18:47:44 - mmengine - INFO - Epoch(train) [1][940/940] lr: 1.0000e-02 eta: 15:22:36 time: 0.5444 data_time: 0.0306 memory: 33630 grad_norm: 3.3518 top1_acc: 0.2857 top5_acc: 0.5714 loss_cls: 3.0349 loss: 3.0349 2022/10/14 18:48:03 - mmengine - INFO - Epoch(val) [1][20/78] eta: 0:00:53 time: 0.9201 data_time: 0.7514 memory: 5967 2022/10/14 18:48:13 - mmengine - INFO - Epoch(val) [1][40/78] eta: 0:00:18 time: 0.4953 data_time: 0.3260 memory: 5967 2022/10/14 18:48:25 - mmengine - INFO - Epoch(val) [1][60/78] eta: 0:00:11 time: 0.6258 data_time: 0.4528 memory: 5967 2022/10/14 18:48:39 - mmengine - INFO - Epoch(val) [1][78/78] acc/top1: 0.4353 acc/top5: 0.7119 acc/mean1: 0.4350 2022/10/14 18:48:39 - mmengine - INFO - The best checkpoint with 0.4353 acc/top1 at 1 epoch is saved to best_acc/top1_epoch_1.pth. 2022/10/14 18:48:55 - mmengine - INFO - Epoch(train) [2][20/940] lr: 1.0000e-02 eta: 15:29:09 time: 0.8038 data_time: 0.2271 memory: 33630 grad_norm: 3.1856 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 3.0748 loss: 3.0748 2022/10/14 18:49:07 - mmengine - INFO - Epoch(train) [2][40/940] lr: 1.0000e-02 eta: 15:28:20 time: 0.5799 data_time: 0.0400 memory: 33630 grad_norm: 3.1606 top1_acc: 0.3125 top5_acc: 0.5000 loss_cls: 2.7817 loss: 2.7817 2022/10/14 18:49:19 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 18:49:19 - mmengine - INFO - Epoch(train) [2][60/940] lr: 1.0000e-02 eta: 15:28:47 time: 0.6196 data_time: 0.0344 memory: 33630 grad_norm: 3.1662 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.7861 loss: 2.7861 2022/10/14 18:49:31 - mmengine - INFO - Epoch(train) [2][80/940] lr: 1.0000e-02 eta: 15:28:12 time: 0.5864 data_time: 0.0337 memory: 33630 grad_norm: 3.2393 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.9395 loss: 2.9395 2022/10/14 18:49:43 - mmengine - INFO - Epoch(train) [2][100/940] lr: 1.0000e-02 eta: 15:27:56 time: 0.5966 data_time: 0.0387 memory: 33630 grad_norm: 3.1937 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 2.8301 loss: 2.8301 2022/10/14 18:49:55 - mmengine - INFO - Epoch(train) [2][120/940] lr: 1.0000e-02 eta: 15:27:16 time: 0.5833 data_time: 0.0315 memory: 33630 grad_norm: 3.2162 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 2.8639 loss: 2.8639 2022/10/14 18:50:07 - mmengine - INFO - Epoch(train) [2][140/940] lr: 1.0000e-02 eta: 15:26:41 time: 0.5852 data_time: 0.0332 memory: 33630 grad_norm: 3.2166 top1_acc: 0.2188 top5_acc: 0.6875 loss_cls: 2.8041 loss: 2.8041 2022/10/14 18:50:18 - mmengine - INFO - Epoch(train) [2][160/940] lr: 1.0000e-02 eta: 15:26:17 time: 0.5910 data_time: 0.0430 memory: 33630 grad_norm: 3.2363 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 2.6334 loss: 2.6334 2022/10/14 18:50:30 - mmengine - INFO - Epoch(train) [2][180/940] lr: 1.0000e-02 eta: 15:25:45 time: 0.5862 data_time: 0.0484 memory: 33630 grad_norm: 3.2469 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 2.8613 loss: 2.8613 2022/10/14 18:50:42 - mmengine - INFO - Epoch(train) [2][200/940] lr: 1.0000e-02 eta: 15:25:35 time: 0.5992 data_time: 0.0358 memory: 33630 grad_norm: 3.2106 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8752 loss: 2.8752 2022/10/14 18:50:54 - mmengine - INFO - Epoch(train) [2][220/940] lr: 1.0000e-02 eta: 15:25:00 time: 0.5840 data_time: 0.0405 memory: 33630 grad_norm: 3.1954 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 2.7177 loss: 2.7177 2022/10/14 18:51:06 - mmengine - INFO - Epoch(train) [2][240/940] lr: 1.0000e-02 eta: 15:24:40 time: 0.5927 data_time: 0.0311 memory: 33630 grad_norm: 3.2507 top1_acc: 0.3125 top5_acc: 0.5312 loss_cls: 2.6542 loss: 2.6542 2022/10/14 18:51:17 - mmengine - INFO - Epoch(train) [2][260/940] lr: 1.0000e-02 eta: 15:23:54 time: 0.5759 data_time: 0.0349 memory: 33630 grad_norm: 3.2426 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.8108 loss: 2.8108 2022/10/14 18:51:29 - mmengine - INFO - Epoch(train) [2][280/940] lr: 1.0000e-02 eta: 15:23:13 time: 0.5781 data_time: 0.0353 memory: 33630 grad_norm: 3.2706 top1_acc: 0.3125 top5_acc: 0.5312 loss_cls: 2.8228 loss: 2.8228 2022/10/14 18:51:40 - mmengine - INFO - Epoch(train) [2][300/940] lr: 1.0000e-02 eta: 15:22:48 time: 0.5883 data_time: 0.0319 memory: 33630 grad_norm: 3.2149 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 2.7799 loss: 2.7799 2022/10/14 18:51:52 - mmengine - INFO - Epoch(train) [2][320/940] lr: 1.0000e-02 eta: 15:22:38 time: 0.5977 data_time: 0.0393 memory: 33630 grad_norm: 3.2663 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.8133 loss: 2.8133 2022/10/14 18:52:04 - mmengine - INFO - Epoch(train) [2][340/940] lr: 1.0000e-02 eta: 15:22:06 time: 0.5832 data_time: 0.0302 memory: 33630 grad_norm: 3.2612 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.7623 loss: 2.7623 2022/10/14 18:52:16 - mmengine - INFO - Epoch(train) [2][360/940] lr: 1.0000e-02 eta: 15:21:43 time: 0.5891 data_time: 0.0328 memory: 33630 grad_norm: 3.2823 top1_acc: 0.2812 top5_acc: 0.5625 loss_cls: 2.8139 loss: 2.8139 2022/10/14 18:52:27 - mmengine - INFO - Epoch(train) [2][380/940] lr: 1.0000e-02 eta: 15:21:02 time: 0.5758 data_time: 0.0373 memory: 33630 grad_norm: 3.2465 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.6772 loss: 2.6772 2022/10/14 18:52:39 - mmengine - INFO - Epoch(train) [2][400/940] lr: 1.0000e-02 eta: 15:20:29 time: 0.5808 data_time: 0.0364 memory: 33630 grad_norm: 3.2955 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 2.5604 loss: 2.5604 2022/10/14 18:52:51 - mmengine - INFO - Epoch(train) [2][420/940] lr: 1.0000e-02 eta: 15:19:57 time: 0.5815 data_time: 0.0366 memory: 33630 grad_norm: 3.2488 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.7704 loss: 2.7704 2022/10/14 18:53:02 - mmengine - INFO - Epoch(train) [2][440/940] lr: 1.0000e-02 eta: 15:19:27 time: 0.5825 data_time: 0.0309 memory: 33630 grad_norm: 3.3228 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.6733 loss: 2.6733 2022/10/14 18:53:14 - mmengine - INFO - Epoch(train) [2][460/940] lr: 1.0000e-02 eta: 15:18:52 time: 0.5784 data_time: 0.0415 memory: 33630 grad_norm: 3.2923 top1_acc: 0.2500 top5_acc: 0.6875 loss_cls: 2.5493 loss: 2.5493 2022/10/14 18:53:25 - mmengine - INFO - Epoch(train) [2][480/940] lr: 1.0000e-02 eta: 15:18:19 time: 0.5789 data_time: 0.0331 memory: 33630 grad_norm: 3.2373 top1_acc: 0.3750 top5_acc: 0.5312 loss_cls: 2.5843 loss: 2.5843 2022/10/14 18:53:37 - mmengine - INFO - Epoch(train) [2][500/940] lr: 1.0000e-02 eta: 15:17:31 time: 0.5669 data_time: 0.0403 memory: 33630 grad_norm: 3.2904 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 2.6494 loss: 2.6494 2022/10/14 18:53:48 - mmengine - INFO - Epoch(train) [2][520/940] lr: 1.0000e-02 eta: 15:17:09 time: 0.5870 data_time: 0.0315 memory: 33630 grad_norm: 3.3109 top1_acc: 0.3125 top5_acc: 0.5312 loss_cls: 2.7666 loss: 2.7666 2022/10/14 18:54:00 - mmengine - INFO - Epoch(train) [2][540/940] lr: 1.0000e-02 eta: 15:16:40 time: 0.5811 data_time: 0.0361 memory: 33630 grad_norm: 3.2630 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 2.6088 loss: 2.6088 2022/10/14 18:54:12 - mmengine - INFO - Epoch(train) [2][560/940] lr: 1.0000e-02 eta: 15:16:09 time: 0.5790 data_time: 0.0423 memory: 33630 grad_norm: 3.2186 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 2.7314 loss: 2.7314 2022/10/14 18:54:23 - mmengine - INFO - Epoch(train) [2][580/940] lr: 1.0000e-02 eta: 15:15:38 time: 0.5782 data_time: 0.0304 memory: 33630 grad_norm: 3.2673 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6138 loss: 2.6138 2022/10/14 18:54:35 - mmengine - INFO - Epoch(train) [2][600/940] lr: 1.0000e-02 eta: 15:15:03 time: 0.5747 data_time: 0.0427 memory: 33630 grad_norm: 3.2928 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.6037 loss: 2.6037 2022/10/14 18:54:46 - mmengine - INFO - Epoch(train) [2][620/940] lr: 1.0000e-02 eta: 15:14:31 time: 0.5771 data_time: 0.0308 memory: 33630 grad_norm: 3.2788 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.6406 loss: 2.6406 2022/10/14 18:54:58 - mmengine - INFO - Epoch(train) [2][640/940] lr: 1.0000e-02 eta: 15:14:09 time: 0.5847 data_time: 0.0355 memory: 33630 grad_norm: 3.2854 top1_acc: 0.3750 top5_acc: 0.5312 loss_cls: 2.7308 loss: 2.7308 2022/10/14 18:55:10 - mmengine - INFO - Epoch(train) [2][660/940] lr: 1.0000e-02 eta: 15:13:56 time: 0.5924 data_time: 0.0421 memory: 33630 grad_norm: 3.3417 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 2.6003 loss: 2.6003 2022/10/14 18:55:22 - mmengine - INFO - Epoch(train) [2][680/940] lr: 1.0000e-02 eta: 15:13:35 time: 0.5856 data_time: 0.0286 memory: 33630 grad_norm: 3.2618 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7191 loss: 2.7191 2022/10/14 18:55:33 - mmengine - INFO - Epoch(train) [2][700/940] lr: 1.0000e-02 eta: 15:13:24 time: 0.5944 data_time: 0.0302 memory: 33630 grad_norm: 3.2730 top1_acc: 0.2812 top5_acc: 0.5625 loss_cls: 2.6145 loss: 2.6145 2022/10/14 18:55:45 - mmengine - INFO - Epoch(train) [2][720/940] lr: 1.0000e-02 eta: 15:13:05 time: 0.5865 data_time: 0.0302 memory: 33630 grad_norm: 3.2790 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5458 loss: 2.5458 2022/10/14 18:55:57 - mmengine - INFO - Epoch(train) [2][740/940] lr: 1.0000e-02 eta: 15:12:39 time: 0.5803 data_time: 0.0437 memory: 33630 grad_norm: 3.2904 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5560 loss: 2.5560 2022/10/14 18:56:08 - mmengine - INFO - Epoch(train) [2][760/940] lr: 1.0000e-02 eta: 15:12:20 time: 0.5869 data_time: 0.0341 memory: 33630 grad_norm: 3.2731 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.5062 loss: 2.5062 2022/10/14 18:56:20 - mmengine - INFO - Epoch(train) [2][780/940] lr: 1.0000e-02 eta: 15:12:00 time: 0.5854 data_time: 0.0391 memory: 33630 grad_norm: 3.2972 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.5691 loss: 2.5691 2022/10/14 18:56:32 - mmengine - INFO - Epoch(train) [2][800/940] lr: 1.0000e-02 eta: 15:11:36 time: 0.5817 data_time: 0.0375 memory: 33630 grad_norm: 3.2637 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.5201 loss: 2.5201 2022/10/14 18:56:43 - mmengine - INFO - Epoch(train) [2][820/940] lr: 1.0000e-02 eta: 15:11:12 time: 0.5809 data_time: 0.0427 memory: 33630 grad_norm: 3.3047 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.5589 loss: 2.5589 2022/10/14 18:56:55 - mmengine - INFO - Epoch(train) [2][840/940] lr: 1.0000e-02 eta: 15:10:36 time: 0.5694 data_time: 0.0395 memory: 33630 grad_norm: 3.2967 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.6799 loss: 2.6799 2022/10/14 18:57:07 - mmengine - INFO - Epoch(train) [2][860/940] lr: 1.0000e-02 eta: 15:10:27 time: 0.5958 data_time: 0.0294 memory: 33630 grad_norm: 3.2853 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.4571 loss: 2.4571 2022/10/14 18:57:18 - mmengine - INFO - Epoch(train) [2][880/940] lr: 1.0000e-02 eta: 15:10:00 time: 0.5768 data_time: 0.0351 memory: 33630 grad_norm: 3.3192 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.5753 loss: 2.5753 2022/10/14 18:57:30 - mmengine - INFO - Epoch(train) [2][900/940] lr: 1.0000e-02 eta: 15:09:43 time: 0.5879 data_time: 0.0379 memory: 33630 grad_norm: 3.3116 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 2.5293 loss: 2.5293 2022/10/14 18:57:42 - mmengine - INFO - Epoch(train) [2][920/940] lr: 1.0000e-02 eta: 15:09:22 time: 0.5830 data_time: 0.0338 memory: 33630 grad_norm: 3.3016 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.5979 loss: 2.5979 2022/10/14 18:57:52 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 18:57:52 - mmengine - INFO - Epoch(train) [2][940/940] lr: 1.0000e-02 eta: 15:08:14 time: 0.5347 data_time: 0.0288 memory: 33630 grad_norm: 3.4641 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 2.4317 loss: 2.4317 2022/10/14 18:58:06 - mmengine - INFO - Epoch(val) [2][20/78] eta: 0:00:39 time: 0.6858 data_time: 0.5141 memory: 5967 2022/10/14 18:58:16 - mmengine - INFO - Epoch(val) [2][40/78] eta: 0:00:19 time: 0.5140 data_time: 0.3438 memory: 5967 2022/10/14 18:58:29 - mmengine - INFO - Epoch(val) [2][60/78] eta: 0:00:11 time: 0.6462 data_time: 0.4771 memory: 5967 2022/10/14 18:58:42 - mmengine - INFO - Epoch(val) [2][78/78] acc/top1: 0.4988 acc/top5: 0.7626 acc/mean1: 0.4986 2022/10/14 18:58:42 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_1.pth is removed 2022/10/14 18:58:42 - mmengine - INFO - The best checkpoint with 0.4988 acc/top1 at 2 epoch is saved to best_acc/top1_epoch_2.pth. 2022/10/14 18:58:59 - mmengine - INFO - Epoch(train) [3][20/940] lr: 1.0000e-02 eta: 15:11:39 time: 0.8156 data_time: 0.2511 memory: 33630 grad_norm: 3.3004 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.5009 loss: 2.5009 2022/10/14 18:59:10 - mmengine - INFO - Epoch(train) [3][40/940] lr: 1.0000e-02 eta: 15:11:28 time: 0.5940 data_time: 0.0449 memory: 33630 grad_norm: 3.3385 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.4718 loss: 2.4718 2022/10/14 18:59:23 - mmengine - INFO - Epoch(train) [3][60/940] lr: 1.0000e-02 eta: 15:11:24 time: 0.6031 data_time: 0.0517 memory: 33630 grad_norm: 3.2985 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5391 loss: 2.5391 2022/10/14 18:59:34 - mmengine - INFO - Epoch(train) [3][80/940] lr: 1.0000e-02 eta: 15:11:11 time: 0.5927 data_time: 0.0300 memory: 33630 grad_norm: 3.3392 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.6821 loss: 2.6821 2022/10/14 18:59:46 - mmengine - INFO - Epoch(train) [3][100/940] lr: 1.0000e-02 eta: 15:10:46 time: 0.5792 data_time: 0.0355 memory: 33630 grad_norm: 3.3436 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5810 loss: 2.5810 2022/10/14 18:59:57 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 18:59:57 - mmengine - INFO - Epoch(train) [3][120/940] lr: 1.0000e-02 eta: 15:10:15 time: 0.5737 data_time: 0.0333 memory: 33630 grad_norm: 3.3005 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.4270 loss: 2.4270 2022/10/14 19:00:09 - mmengine - INFO - Epoch(train) [3][140/940] lr: 1.0000e-02 eta: 15:10:07 time: 0.5974 data_time: 0.0387 memory: 33630 grad_norm: 3.3267 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.5039 loss: 2.5039 2022/10/14 19:00:21 - mmengine - INFO - Epoch(train) [3][160/940] lr: 1.0000e-02 eta: 15:09:41 time: 0.5784 data_time: 0.0350 memory: 33630 grad_norm: 3.2793 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.4410 loss: 2.4410 2022/10/14 19:00:33 - mmengine - INFO - Epoch(train) [3][180/940] lr: 1.0000e-02 eta: 15:09:21 time: 0.5846 data_time: 0.0367 memory: 33630 grad_norm: 3.3238 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4065 loss: 2.4065 2022/10/14 19:00:44 - mmengine - INFO - Epoch(train) [3][200/940] lr: 1.0000e-02 eta: 15:09:00 time: 0.5824 data_time: 0.0331 memory: 33630 grad_norm: 3.3832 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 2.6944 loss: 2.6944 2022/10/14 19:00:56 - mmengine - INFO - Epoch(train) [3][220/940] lr: 1.0000e-02 eta: 15:08:46 time: 0.5909 data_time: 0.0321 memory: 33630 grad_norm: 3.3129 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.3275 loss: 2.3275 2022/10/14 19:01:08 - mmengine - INFO - Epoch(train) [3][240/940] lr: 1.0000e-02 eta: 15:08:21 time: 0.5783 data_time: 0.0332 memory: 33630 grad_norm: 3.3296 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.5188 loss: 2.5188 2022/10/14 19:01:19 - mmengine - INFO - Epoch(train) [3][260/940] lr: 1.0000e-02 eta: 15:07:52 time: 0.5732 data_time: 0.0358 memory: 33630 grad_norm: 3.3106 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.6012 loss: 2.6012 2022/10/14 19:01:31 - mmengine - INFO - Epoch(train) [3][280/940] lr: 1.0000e-02 eta: 15:07:36 time: 0.5884 data_time: 0.0349 memory: 33630 grad_norm: 3.3398 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.5039 loss: 2.5039 2022/10/14 19:01:43 - mmengine - INFO - Epoch(train) [3][300/940] lr: 1.0000e-02 eta: 15:07:19 time: 0.5867 data_time: 0.0302 memory: 33630 grad_norm: 3.3516 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.5372 loss: 2.5372 2022/10/14 19:01:54 - mmengine - INFO - Epoch(train) [3][320/940] lr: 1.0000e-02 eta: 15:07:00 time: 0.5844 data_time: 0.0330 memory: 33630 grad_norm: 3.3247 top1_acc: 0.4688 top5_acc: 0.8750 loss_cls: 2.3831 loss: 2.3831 2022/10/14 19:02:06 - mmengine - INFO - Epoch(train) [3][340/940] lr: 1.0000e-02 eta: 15:06:33 time: 0.5747 data_time: 0.0410 memory: 33630 grad_norm: 3.3249 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.4669 loss: 2.4669 2022/10/14 19:02:17 - mmengine - INFO - Epoch(train) [3][360/940] lr: 1.0000e-02 eta: 15:06:09 time: 0.5774 data_time: 0.0312 memory: 33630 grad_norm: 3.3646 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.4942 loss: 2.4942 2022/10/14 19:02:29 - mmengine - INFO - Epoch(train) [3][380/940] lr: 1.0000e-02 eta: 15:05:48 time: 0.5810 data_time: 0.0360 memory: 33630 grad_norm: 3.3112 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.3834 loss: 2.3834 2022/10/14 19:02:41 - mmengine - INFO - Epoch(train) [3][400/940] lr: 1.0000e-02 eta: 15:05:27 time: 0.5816 data_time: 0.0312 memory: 33630 grad_norm: 3.3049 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.4427 loss: 2.4427 2022/10/14 19:02:52 - mmengine - INFO - Epoch(train) [3][420/940] lr: 1.0000e-02 eta: 15:05:09 time: 0.5842 data_time: 0.0323 memory: 33630 grad_norm: 3.3492 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 2.4782 loss: 2.4782 2022/10/14 19:03:04 - mmengine - INFO - Epoch(train) [3][440/940] lr: 1.0000e-02 eta: 15:04:45 time: 0.5777 data_time: 0.0379 memory: 33630 grad_norm: 3.3871 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.6192 loss: 2.6192 2022/10/14 19:03:15 - mmengine - INFO - Epoch(train) [3][460/940] lr: 1.0000e-02 eta: 15:04:22 time: 0.5768 data_time: 0.0358 memory: 33630 grad_norm: 3.3559 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.4851 loss: 2.4851 2022/10/14 19:03:27 - mmengine - INFO - Epoch(train) [3][480/940] lr: 1.0000e-02 eta: 15:04:09 time: 0.5910 data_time: 0.0309 memory: 33630 grad_norm: 3.3908 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 2.4573 loss: 2.4573 2022/10/14 19:03:39 - mmengine - INFO - Epoch(train) [3][500/940] lr: 1.0000e-02 eta: 15:03:52 time: 0.5853 data_time: 0.0382 memory: 33630 grad_norm: 3.3490 top1_acc: 0.3125 top5_acc: 0.6562 loss_cls: 2.6723 loss: 2.6723 2022/10/14 19:03:51 - mmengine - INFO - Epoch(train) [3][520/940] lr: 1.0000e-02 eta: 15:03:33 time: 0.5829 data_time: 0.0371 memory: 33630 grad_norm: 3.3452 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.5199 loss: 2.5199 2022/10/14 19:04:02 - mmengine - INFO - Epoch(train) [3][540/940] lr: 1.0000e-02 eta: 15:03:15 time: 0.5827 data_time: 0.0372 memory: 33630 grad_norm: 3.3871 top1_acc: 0.3438 top5_acc: 0.7188 loss_cls: 2.4006 loss: 2.4006 2022/10/14 19:04:14 - mmengine - INFO - Epoch(train) [3][560/940] lr: 1.0000e-02 eta: 15:02:40 time: 0.5621 data_time: 0.0313 memory: 33630 grad_norm: 3.3743 top1_acc: 0.3438 top5_acc: 0.6250 loss_cls: 2.4095 loss: 2.4095 2022/10/14 19:04:25 - mmengine - INFO - Epoch(train) [3][580/940] lr: 1.0000e-02 eta: 15:02:17 time: 0.5755 data_time: 0.0376 memory: 33630 grad_norm: 3.3412 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.3342 loss: 2.3342 2022/10/14 19:04:37 - mmengine - INFO - Epoch(train) [3][600/940] lr: 1.0000e-02 eta: 15:02:10 time: 0.5979 data_time: 0.0449 memory: 33630 grad_norm: 3.3616 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.5243 loss: 2.5243 2022/10/14 19:04:48 - mmengine - INFO - Epoch(train) [3][620/940] lr: 1.0000e-02 eta: 15:01:46 time: 0.5755 data_time: 0.0418 memory: 33630 grad_norm: 3.4027 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.6468 loss: 2.6468 2022/10/14 19:05:00 - mmengine - INFO - Epoch(train) [3][640/940] lr: 1.0000e-02 eta: 15:01:33 time: 0.5890 data_time: 0.0313 memory: 33630 grad_norm: 3.3600 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.3014 loss: 2.3014 2022/10/14 19:05:12 - mmengine - INFO - Epoch(train) [3][660/940] lr: 1.0000e-02 eta: 15:01:16 time: 0.5843 data_time: 0.0312 memory: 33630 grad_norm: 3.3423 top1_acc: 0.5000 top5_acc: 0.5938 loss_cls: 2.3265 loss: 2.3265 2022/10/14 19:05:23 - mmengine - INFO - Epoch(train) [3][680/940] lr: 1.0000e-02 eta: 15:00:52 time: 0.5749 data_time: 0.0305 memory: 33630 grad_norm: 3.3665 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.5390 loss: 2.5390 2022/10/14 19:05:35 - mmengine - INFO - Epoch(train) [3][700/940] lr: 1.0000e-02 eta: 15:00:35 time: 0.5835 data_time: 0.0332 memory: 33630 grad_norm: 3.3638 top1_acc: 0.2500 top5_acc: 0.4062 loss_cls: 2.4486 loss: 2.4486 2022/10/14 19:05:47 - mmengine - INFO - Epoch(train) [3][720/940] lr: 1.0000e-02 eta: 15:00:12 time: 0.5755 data_time: 0.0308 memory: 33630 grad_norm: 3.3887 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4905 loss: 2.4905 2022/10/14 19:05:58 - mmengine - INFO - Epoch(train) [3][740/940] lr: 1.0000e-02 eta: 14:59:51 time: 0.5781 data_time: 0.0360 memory: 33630 grad_norm: 3.3745 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 2.3620 loss: 2.3620 2022/10/14 19:06:10 - mmengine - INFO - Epoch(train) [3][760/940] lr: 1.0000e-02 eta: 14:59:37 time: 0.5866 data_time: 0.0318 memory: 33630 grad_norm: 3.3625 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.4953 loss: 2.4953 2022/10/14 19:06:22 - mmengine - INFO - Epoch(train) [3][780/940] lr: 1.0000e-02 eta: 14:59:22 time: 0.5869 data_time: 0.0468 memory: 33630 grad_norm: 3.3388 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 2.2576 loss: 2.2576 2022/10/14 19:06:33 - mmengine - INFO - Epoch(train) [3][800/940] lr: 1.0000e-02 eta: 14:59:05 time: 0.5838 data_time: 0.0355 memory: 33630 grad_norm: 3.3847 top1_acc: 0.2500 top5_acc: 0.5312 loss_cls: 2.4849 loss: 2.4849 2022/10/14 19:06:45 - mmengine - INFO - Epoch(train) [3][820/940] lr: 1.0000e-02 eta: 14:58:54 time: 0.5908 data_time: 0.0324 memory: 33630 grad_norm: 3.3276 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 2.3452 loss: 2.3452 2022/10/14 19:06:57 - mmengine - INFO - Epoch(train) [3][840/940] lr: 1.0000e-02 eta: 14:58:30 time: 0.5731 data_time: 0.0366 memory: 33630 grad_norm: 3.3408 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.5152 loss: 2.5152 2022/10/14 19:07:08 - mmengine - INFO - Epoch(train) [3][860/940] lr: 1.0000e-02 eta: 14:58:14 time: 0.5836 data_time: 0.0400 memory: 33630 grad_norm: 3.3670 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.4206 loss: 2.4206 2022/10/14 19:07:20 - mmengine - INFO - Epoch(train) [3][880/940] lr: 1.0000e-02 eta: 14:57:55 time: 0.5807 data_time: 0.0335 memory: 33630 grad_norm: 3.4295 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5139 loss: 2.5139 2022/10/14 19:07:32 - mmengine - INFO - Epoch(train) [3][900/940] lr: 1.0000e-02 eta: 14:57:38 time: 0.5818 data_time: 0.0317 memory: 33630 grad_norm: 3.3976 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.5290 loss: 2.5290 2022/10/14 19:07:43 - mmengine - INFO - Epoch(train) [3][920/940] lr: 1.0000e-02 eta: 14:57:22 time: 0.5851 data_time: 0.0441 memory: 33630 grad_norm: 3.3559 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.4487 loss: 2.4487 2022/10/14 19:07:54 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 19:07:54 - mmengine - INFO - Epoch(train) [3][940/940] lr: 1.0000e-02 eta: 14:56:42 time: 0.5464 data_time: 0.0266 memory: 33630 grad_norm: 3.5303 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 2.4788 loss: 2.4788 2022/10/14 19:07:54 - mmengine - INFO - Saving checkpoint at 3 epochs 2022/10/14 19:08:10 - mmengine - INFO - Epoch(val) [3][20/78] eta: 0:00:42 time: 0.7249 data_time: 0.5557 memory: 5967 2022/10/14 19:08:20 - mmengine - INFO - Epoch(val) [3][40/78] eta: 0:00:19 time: 0.5220 data_time: 0.3495 memory: 5967 2022/10/14 19:08:33 - mmengine - INFO - Epoch(val) [3][60/78] eta: 0:00:11 time: 0.6631 data_time: 0.4948 memory: 5967 2022/10/14 19:08:44 - mmengine - INFO - Epoch(val) [3][78/78] acc/top1: 0.5390 acc/top5: 0.7896 acc/mean1: 0.5388 2022/10/14 19:08:44 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_2.pth is removed 2022/10/14 19:08:45 - mmengine - INFO - The best checkpoint with 0.5390 acc/top1 at 3 epoch is saved to best_acc/top1_epoch_3.pth. 2022/10/14 19:09:01 - mmengine - INFO - Epoch(train) [4][20/940] lr: 1.0000e-02 eta: 14:58:55 time: 0.8147 data_time: 0.2656 memory: 33630 grad_norm: 3.4056 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 2.3589 loss: 2.3589 2022/10/14 19:09:13 - mmengine - INFO - Epoch(train) [4][40/940] lr: 1.0000e-02 eta: 14:58:42 time: 0.5902 data_time: 0.0352 memory: 33630 grad_norm: 3.3337 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 2.3228 loss: 2.3228 2022/10/14 19:09:25 - mmengine - INFO - Epoch(train) [4][60/940] lr: 1.0000e-02 eta: 14:58:27 time: 0.5863 data_time: 0.0358 memory: 33630 grad_norm: 3.3834 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.4474 loss: 2.4474 2022/10/14 19:09:37 - mmengine - INFO - Epoch(train) [4][80/940] lr: 1.0000e-02 eta: 14:58:18 time: 0.5970 data_time: 0.0340 memory: 33630 grad_norm: 3.4359 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 2.5947 loss: 2.5947 2022/10/14 19:09:49 - mmengine - INFO - Epoch(train) [4][100/940] lr: 1.0000e-02 eta: 14:58:13 time: 0.6020 data_time: 0.0409 memory: 33630 grad_norm: 3.4781 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.2390 loss: 2.2390 2022/10/14 19:10:00 - mmengine - INFO - Epoch(train) [4][120/940] lr: 1.0000e-02 eta: 14:57:57 time: 0.5846 data_time: 0.0357 memory: 33630 grad_norm: 3.4273 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.2705 loss: 2.2705 2022/10/14 19:10:12 - mmengine - INFO - Epoch(train) [4][140/940] lr: 1.0000e-02 eta: 14:57:47 time: 0.5947 data_time: 0.0299 memory: 33630 grad_norm: 3.4339 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.3970 loss: 2.3970 2022/10/14 19:10:24 - mmengine - INFO - Epoch(train) [4][160/940] lr: 1.0000e-02 eta: 14:57:26 time: 0.5779 data_time: 0.0355 memory: 33630 grad_norm: 3.3604 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 2.3500 loss: 2.3500 2022/10/14 19:10:35 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 19:10:35 - mmengine - INFO - Epoch(train) [4][180/940] lr: 1.0000e-02 eta: 14:57:02 time: 0.5717 data_time: 0.0364 memory: 33630 grad_norm: 3.4057 top1_acc: 0.4062 top5_acc: 0.5625 loss_cls: 2.4288 loss: 2.4288 2022/10/14 19:10:47 - mmengine - INFO - Epoch(train) [4][200/940] lr: 1.0000e-02 eta: 14:56:48 time: 0.5877 data_time: 0.0346 memory: 33630 grad_norm: 3.3893 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.3498 loss: 2.3498 2022/10/14 19:10:58 - mmengine - INFO - Epoch(train) [4][220/940] lr: 1.0000e-02 eta: 14:56:26 time: 0.5735 data_time: 0.0283 memory: 33630 grad_norm: 3.3893 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 2.3522 loss: 2.3522 2022/10/14 19:11:10 - mmengine - INFO - Epoch(train) [4][240/940] lr: 1.0000e-02 eta: 14:56:11 time: 0.5858 data_time: 0.0329 memory: 33630 grad_norm: 3.4143 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.2789 loss: 2.2789 2022/10/14 19:11:22 - mmengine - INFO - Epoch(train) [4][260/940] lr: 1.0000e-02 eta: 14:55:47 time: 0.5719 data_time: 0.0335 memory: 33630 grad_norm: 3.3768 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.2295 loss: 2.2295 2022/10/14 19:11:33 - mmengine - INFO - Epoch(train) [4][280/940] lr: 1.0000e-02 eta: 14:55:23 time: 0.5692 data_time: 0.0325 memory: 33630 grad_norm: 3.4043 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.3036 loss: 2.3036 2022/10/14 19:11:45 - mmengine - INFO - Epoch(train) [4][300/940] lr: 1.0000e-02 eta: 14:55:06 time: 0.5820 data_time: 0.0346 memory: 33630 grad_norm: 3.4576 top1_acc: 0.3438 top5_acc: 0.7188 loss_cls: 2.3448 loss: 2.3448 2022/10/14 19:11:56 - mmengine - INFO - Epoch(train) [4][320/940] lr: 1.0000e-02 eta: 14:54:48 time: 0.5817 data_time: 0.0322 memory: 33630 grad_norm: 3.3835 top1_acc: 0.3438 top5_acc: 0.6250 loss_cls: 2.1637 loss: 2.1637 2022/10/14 19:12:08 - mmengine - INFO - Epoch(train) [4][340/940] lr: 1.0000e-02 eta: 14:54:29 time: 0.5774 data_time: 0.0404 memory: 33630 grad_norm: 3.3901 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 2.2505 loss: 2.2505 2022/10/14 19:12:19 - mmengine - INFO - Epoch(train) [4][360/940] lr: 1.0000e-02 eta: 14:54:13 time: 0.5845 data_time: 0.0452 memory: 33630 grad_norm: 3.4783 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.3756 loss: 2.3756 2022/10/14 19:12:31 - mmengine - INFO - Epoch(train) [4][380/940] lr: 1.0000e-02 eta: 14:53:53 time: 0.5763 data_time: 0.0364 memory: 33630 grad_norm: 3.4311 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.2027 loss: 2.2027 2022/10/14 19:12:43 - mmengine - INFO - Epoch(train) [4][400/940] lr: 1.0000e-02 eta: 14:53:41 time: 0.5892 data_time: 0.0372 memory: 33630 grad_norm: 3.4381 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 2.3756 loss: 2.3756 2022/10/14 19:12:55 - mmengine - INFO - Epoch(train) [4][420/940] lr: 1.0000e-02 eta: 14:53:37 time: 0.6047 data_time: 0.0308 memory: 33630 grad_norm: 3.4664 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.3843 loss: 2.3843 2022/10/14 19:13:06 - mmengine - INFO - Epoch(train) [4][440/940] lr: 1.0000e-02 eta: 14:53:20 time: 0.5821 data_time: 0.0319 memory: 33630 grad_norm: 3.4668 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4657 loss: 2.4657 2022/10/14 19:13:18 - mmengine - INFO - Epoch(train) [4][460/940] lr: 1.0000e-02 eta: 14:53:00 time: 0.5749 data_time: 0.0313 memory: 33630 grad_norm: 3.4503 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 2.3430 loss: 2.3430 2022/10/14 19:13:30 - mmengine - INFO - Epoch(train) [4][480/940] lr: 1.0000e-02 eta: 14:52:46 time: 0.5867 data_time: 0.0346 memory: 33630 grad_norm: 3.3874 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3321 loss: 2.3321 2022/10/14 19:13:41 - mmengine - INFO - Epoch(train) [4][500/940] lr: 1.0000e-02 eta: 14:52:31 time: 0.5853 data_time: 0.0346 memory: 33630 grad_norm: 3.4092 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 2.2306 loss: 2.2306 2022/10/14 19:13:53 - mmengine - INFO - Epoch(train) [4][520/940] lr: 1.0000e-02 eta: 14:52:16 time: 0.5852 data_time: 0.0299 memory: 33630 grad_norm: 3.4225 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.2929 loss: 2.2929 2022/10/14 19:14:05 - mmengine - INFO - Epoch(train) [4][540/940] lr: 1.0000e-02 eta: 14:52:04 time: 0.5890 data_time: 0.0296 memory: 33630 grad_norm: 3.4042 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 2.3304 loss: 2.3304 2022/10/14 19:14:17 - mmengine - INFO - Epoch(train) [4][560/940] lr: 1.0000e-02 eta: 14:51:50 time: 0.5881 data_time: 0.0321 memory: 33630 grad_norm: 3.4281 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.2321 loss: 2.2321 2022/10/14 19:14:28 - mmengine - INFO - Epoch(train) [4][580/940] lr: 1.0000e-02 eta: 14:51:30 time: 0.5750 data_time: 0.0313 memory: 33630 grad_norm: 3.4315 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.2565 loss: 2.2565 2022/10/14 19:14:40 - mmengine - INFO - Epoch(train) [4][600/940] lr: 1.0000e-02 eta: 14:51:15 time: 0.5832 data_time: 0.0380 memory: 33630 grad_norm: 3.3571 top1_acc: 0.2812 top5_acc: 0.5625 loss_cls: 2.3214 loss: 2.3214 2022/10/14 19:14:52 - mmengine - INFO - Epoch(train) [4][620/940] lr: 1.0000e-02 eta: 14:51:03 time: 0.5901 data_time: 0.0355 memory: 33630 grad_norm: 3.3810 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.2631 loss: 2.2631 2022/10/14 19:15:03 - mmengine - INFO - Epoch(train) [4][640/940] lr: 1.0000e-02 eta: 14:50:49 time: 0.5856 data_time: 0.0321 memory: 33630 grad_norm: 3.4161 top1_acc: 0.2812 top5_acc: 0.6875 loss_cls: 2.2545 loss: 2.2545 2022/10/14 19:15:15 - mmengine - INFO - Epoch(train) [4][660/940] lr: 1.0000e-02 eta: 14:50:26 time: 0.5702 data_time: 0.0323 memory: 33630 grad_norm: 3.4556 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4035 loss: 2.4035 2022/10/14 19:15:27 - mmengine - INFO - Epoch(train) [4][680/940] lr: 1.0000e-02 eta: 14:50:15 time: 0.5906 data_time: 0.0449 memory: 33630 grad_norm: 3.4434 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3918 loss: 2.3918 2022/10/14 19:15:38 - mmengine - INFO - Epoch(train) [4][700/940] lr: 1.0000e-02 eta: 14:49:58 time: 0.5816 data_time: 0.0411 memory: 33630 grad_norm: 3.4076 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.3258 loss: 2.3258 2022/10/14 19:15:50 - mmengine - INFO - Epoch(train) [4][720/940] lr: 1.0000e-02 eta: 14:49:43 time: 0.5835 data_time: 0.0456 memory: 33630 grad_norm: 3.4041 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.2823 loss: 2.2823 2022/10/14 19:16:01 - mmengine - INFO - Epoch(train) [4][740/940] lr: 1.0000e-02 eta: 14:49:24 time: 0.5762 data_time: 0.0363 memory: 33630 grad_norm: 3.4133 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.3227 loss: 2.3227 2022/10/14 19:16:13 - mmengine - INFO - Epoch(train) [4][760/940] lr: 1.0000e-02 eta: 14:49:06 time: 0.5779 data_time: 0.0319 memory: 33630 grad_norm: 3.4086 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2424 loss: 2.2424 2022/10/14 19:16:25 - mmengine - INFO - Epoch(train) [4][780/940] lr: 1.0000e-02 eta: 14:48:51 time: 0.5830 data_time: 0.0315 memory: 33630 grad_norm: 3.4756 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.3252 loss: 2.3252 2022/10/14 19:16:36 - mmengine - INFO - Epoch(train) [4][800/940] lr: 1.0000e-02 eta: 14:48:42 time: 0.5961 data_time: 0.0405 memory: 33630 grad_norm: 3.4681 top1_acc: 0.3438 top5_acc: 0.7188 loss_cls: 2.5106 loss: 2.5106 2022/10/14 19:16:48 - mmengine - INFO - Epoch(train) [4][820/940] lr: 1.0000e-02 eta: 14:48:26 time: 0.5815 data_time: 0.0371 memory: 33630 grad_norm: 3.3851 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 2.2086 loss: 2.2086 2022/10/14 19:17:00 - mmengine - INFO - Epoch(train) [4][840/940] lr: 1.0000e-02 eta: 14:48:13 time: 0.5868 data_time: 0.0344 memory: 33630 grad_norm: 3.4346 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 2.4335 loss: 2.4335 2022/10/14 19:17:11 - mmengine - INFO - Epoch(train) [4][860/940] lr: 1.0000e-02 eta: 14:47:52 time: 0.5717 data_time: 0.0342 memory: 33630 grad_norm: 3.3917 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.3479 loss: 2.3479 2022/10/14 19:17:23 - mmengine - INFO - Epoch(train) [4][880/940] lr: 1.0000e-02 eta: 14:47:36 time: 0.5807 data_time: 0.0331 memory: 33630 grad_norm: 3.4188 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 2.2004 loss: 2.2004 2022/10/14 19:17:35 - mmengine - INFO - Epoch(train) [4][900/940] lr: 1.0000e-02 eta: 14:47:25 time: 0.5925 data_time: 0.0364 memory: 33630 grad_norm: 3.4184 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.3113 loss: 2.3113 2022/10/14 19:17:46 - mmengine - INFO - Epoch(train) [4][920/940] lr: 1.0000e-02 eta: 14:47:12 time: 0.5867 data_time: 0.0442 memory: 33630 grad_norm: 3.4021 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.2678 loss: 2.2678 2022/10/14 19:17:57 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 19:17:57 - mmengine - INFO - Epoch(train) [4][940/940] lr: 1.0000e-02 eta: 14:46:36 time: 0.5386 data_time: 0.0295 memory: 33630 grad_norm: 3.5551 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 2.3325 loss: 2.3325 2022/10/14 19:18:12 - mmengine - INFO - Epoch(val) [4][20/78] eta: 0:00:42 time: 0.7272 data_time: 0.5559 memory: 5967 2022/10/14 19:18:22 - mmengine - INFO - Epoch(val) [4][40/78] eta: 0:00:19 time: 0.5100 data_time: 0.3425 memory: 5967 2022/10/14 19:18:35 - mmengine - INFO - Epoch(val) [4][60/78] eta: 0:00:11 time: 0.6473 data_time: 0.4787 memory: 5967 2022/10/14 19:18:47 - mmengine - INFO - Epoch(val) [4][78/78] acc/top1: 0.5557 acc/top5: 0.8043 acc/mean1: 0.5554 2022/10/14 19:18:47 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_3.pth is removed 2022/10/14 19:18:47 - mmengine - INFO - The best checkpoint with 0.5557 acc/top1 at 4 epoch is saved to best_acc/top1_epoch_4.pth. 2022/10/14 19:19:05 - mmengine - INFO - Epoch(train) [5][20/940] lr: 1.0000e-02 eta: 14:48:31 time: 0.8548 data_time: 0.3085 memory: 33630 grad_norm: 3.4801 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 2.2350 loss: 2.2350 2022/10/14 19:19:17 - mmengine - INFO - Epoch(train) [5][40/940] lr: 1.0000e-02 eta: 14:48:23 time: 0.5992 data_time: 0.0530 memory: 33630 grad_norm: 3.4535 top1_acc: 0.2500 top5_acc: 0.5938 loss_cls: 2.3478 loss: 2.3478 2022/10/14 19:19:28 - mmengine - INFO - Epoch(train) [5][60/940] lr: 1.0000e-02 eta: 14:48:07 time: 0.5828 data_time: 0.0362 memory: 33630 grad_norm: 3.4073 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 2.2888 loss: 2.2888 2022/10/14 19:19:40 - mmengine - INFO - Epoch(train) [5][80/940] lr: 1.0000e-02 eta: 14:47:48 time: 0.5763 data_time: 0.0309 memory: 33630 grad_norm: 3.4151 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1770 loss: 2.1770 2022/10/14 19:19:51 - mmengine - INFO - Epoch(train) [5][100/940] lr: 1.0000e-02 eta: 14:47:35 time: 0.5872 data_time: 0.0349 memory: 33630 grad_norm: 3.4545 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2632 loss: 2.2632 2022/10/14 19:20:03 - mmengine - INFO - Epoch(train) [5][120/940] lr: 1.0000e-02 eta: 14:47:24 time: 0.5932 data_time: 0.0382 memory: 33630 grad_norm: 3.4297 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2587 loss: 2.2587 2022/10/14 19:20:15 - mmengine - INFO - Epoch(train) [5][140/940] lr: 1.0000e-02 eta: 14:47:07 time: 0.5796 data_time: 0.0377 memory: 33630 grad_norm: 3.4371 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.1054 loss: 2.1054 2022/10/14 19:20:27 - mmengine - INFO - Epoch(train) [5][160/940] lr: 1.0000e-02 eta: 14:46:53 time: 0.5865 data_time: 0.0333 memory: 33630 grad_norm: 3.3648 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 2.1073 loss: 2.1073 2022/10/14 19:20:38 - mmengine - INFO - Epoch(train) [5][180/940] lr: 1.0000e-02 eta: 14:46:35 time: 0.5773 data_time: 0.0407 memory: 33630 grad_norm: 3.4701 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.1555 loss: 2.1555 2022/10/14 19:20:50 - mmengine - INFO - Epoch(train) [5][200/940] lr: 1.0000e-02 eta: 14:46:18 time: 0.5773 data_time: 0.0327 memory: 33630 grad_norm: 3.4109 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 2.1932 loss: 2.1932 2022/10/14 19:21:02 - mmengine - INFO - Epoch(train) [5][220/940] lr: 1.0000e-02 eta: 14:46:08 time: 0.5962 data_time: 0.0348 memory: 33630 grad_norm: 3.4156 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.3777 loss: 2.3777 2022/10/14 19:21:13 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 19:21:13 - mmengine - INFO - Epoch(train) [5][240/940] lr: 1.0000e-02 eta: 14:45:52 time: 0.5805 data_time: 0.0370 memory: 33630 grad_norm: 3.4249 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.1810 loss: 2.1810 2022/10/14 19:21:25 - mmengine - INFO - Epoch(train) [5][260/940] lr: 1.0000e-02 eta: 14:45:39 time: 0.5883 data_time: 0.0459 memory: 33630 grad_norm: 3.4008 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.2146 loss: 2.2146 2022/10/14 19:21:37 - mmengine - INFO - Epoch(train) [5][280/940] lr: 1.0000e-02 eta: 14:45:25 time: 0.5849 data_time: 0.0351 memory: 33630 grad_norm: 3.5057 top1_acc: 0.5000 top5_acc: 0.5938 loss_cls: 2.2539 loss: 2.2539 2022/10/14 19:21:48 - mmengine - INFO - Epoch(train) [5][300/940] lr: 1.0000e-02 eta: 14:45:10 time: 0.5835 data_time: 0.0378 memory: 33630 grad_norm: 3.4745 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.3230 loss: 2.3230 2022/10/14 19:22:00 - mmengine - INFO - Epoch(train) [5][320/940] lr: 1.0000e-02 eta: 14:44:52 time: 0.5768 data_time: 0.0428 memory: 33630 grad_norm: 3.4469 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2291 loss: 2.2291 2022/10/14 19:22:12 - mmengine - INFO - Epoch(train) [5][340/940] lr: 1.0000e-02 eta: 14:44:38 time: 0.5844 data_time: 0.0460 memory: 33630 grad_norm: 3.4091 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.2673 loss: 2.2673 2022/10/14 19:22:23 - mmengine - INFO - Epoch(train) [5][360/940] lr: 1.0000e-02 eta: 14:44:24 time: 0.5862 data_time: 0.0381 memory: 33630 grad_norm: 3.4365 top1_acc: 0.3125 top5_acc: 0.7500 loss_cls: 2.1250 loss: 2.1250 2022/10/14 19:22:35 - mmengine - INFO - Epoch(train) [5][380/940] lr: 1.0000e-02 eta: 14:44:08 time: 0.5811 data_time: 0.0298 memory: 33630 grad_norm: 3.4417 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.1617 loss: 2.1617 2022/10/14 19:22:47 - mmengine - INFO - Epoch(train) [5][400/940] lr: 1.0000e-02 eta: 14:43:53 time: 0.5831 data_time: 0.0403 memory: 33630 grad_norm: 3.4716 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 2.1527 loss: 2.1527 2022/10/14 19:22:58 - mmengine - INFO - Epoch(train) [5][420/940] lr: 1.0000e-02 eta: 14:43:39 time: 0.5859 data_time: 0.0371 memory: 33630 grad_norm: 3.4567 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2180 loss: 2.2180 2022/10/14 19:23:10 - mmengine - INFO - Epoch(train) [5][440/940] lr: 1.0000e-02 eta: 14:43:27 time: 0.5897 data_time: 0.0307 memory: 33630 grad_norm: 3.4144 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 2.2958 loss: 2.2958 2022/10/14 19:23:22 - mmengine - INFO - Epoch(train) [5][460/940] lr: 1.0000e-02 eta: 14:43:09 time: 0.5757 data_time: 0.0322 memory: 33630 grad_norm: 3.4893 top1_acc: 0.4062 top5_acc: 0.5312 loss_cls: 2.3648 loss: 2.3648 2022/10/14 19:23:34 - mmengine - INFO - Epoch(train) [5][480/940] lr: 1.0000e-02 eta: 14:43:00 time: 0.5955 data_time: 0.0373 memory: 33630 grad_norm: 3.4401 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.1655 loss: 2.1655 2022/10/14 19:23:45 - mmengine - INFO - Epoch(train) [5][500/940] lr: 1.0000e-02 eta: 14:42:45 time: 0.5831 data_time: 0.0451 memory: 33630 grad_norm: 3.4070 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.4222 loss: 2.4222 2022/10/14 19:23:57 - mmengine - INFO - Epoch(train) [5][520/940] lr: 1.0000e-02 eta: 14:42:32 time: 0.5873 data_time: 0.0478 memory: 33630 grad_norm: 3.4573 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 2.2484 loss: 2.2484 2022/10/14 19:24:09 - mmengine - INFO - Epoch(train) [5][540/940] lr: 1.0000e-02 eta: 14:42:18 time: 0.5849 data_time: 0.0420 memory: 33630 grad_norm: 3.4738 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2138 loss: 2.2138 2022/10/14 19:24:20 - mmengine - INFO - Epoch(train) [5][560/940] lr: 1.0000e-02 eta: 14:42:05 time: 0.5881 data_time: 0.0441 memory: 33630 grad_norm: 3.4386 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 2.2774 loss: 2.2774 2022/10/14 19:24:32 - mmengine - INFO - Epoch(train) [5][580/940] lr: 1.0000e-02 eta: 14:41:52 time: 0.5861 data_time: 0.0406 memory: 33630 grad_norm: 3.4392 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.1198 loss: 2.1198 2022/10/14 19:24:44 - mmengine - INFO - Epoch(train) [5][600/940] lr: 1.0000e-02 eta: 14:41:35 time: 0.5776 data_time: 0.0310 memory: 33630 grad_norm: 3.4333 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.3156 loss: 2.3156 2022/10/14 19:24:56 - mmengine - INFO - Epoch(train) [5][620/940] lr: 1.0000e-02 eta: 14:41:23 time: 0.5902 data_time: 0.0326 memory: 33630 grad_norm: 3.4604 top1_acc: 0.3750 top5_acc: 0.7812 loss_cls: 2.2062 loss: 2.2062 2022/10/14 19:25:07 - mmengine - INFO - Epoch(train) [5][640/940] lr: 1.0000e-02 eta: 14:41:08 time: 0.5834 data_time: 0.0367 memory: 33630 grad_norm: 3.4647 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.2305 loss: 2.2305 2022/10/14 19:25:19 - mmengine - INFO - Epoch(train) [5][660/940] lr: 1.0000e-02 eta: 14:41:00 time: 0.5981 data_time: 0.0441 memory: 33630 grad_norm: 3.5166 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3557 loss: 2.3557 2022/10/14 19:25:31 - mmengine - INFO - Epoch(train) [5][680/940] lr: 1.0000e-02 eta: 14:40:47 time: 0.5868 data_time: 0.0362 memory: 33630 grad_norm: 3.5363 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.2635 loss: 2.2635 2022/10/14 19:25:43 - mmengine - INFO - Epoch(train) [5][700/940] lr: 1.0000e-02 eta: 14:40:33 time: 0.5858 data_time: 0.0439 memory: 33630 grad_norm: 3.5185 top1_acc: 0.3438 top5_acc: 0.5312 loss_cls: 2.3591 loss: 2.3591 2022/10/14 19:25:54 - mmengine - INFO - Epoch(train) [5][720/940] lr: 1.0000e-02 eta: 14:40:16 time: 0.5767 data_time: 0.0295 memory: 33630 grad_norm: 3.4317 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.2498 loss: 2.2498 2022/10/14 19:26:06 - mmengine - INFO - Epoch(train) [5][740/940] lr: 1.0000e-02 eta: 14:39:56 time: 0.5684 data_time: 0.0306 memory: 33630 grad_norm: 3.4607 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.1760 loss: 2.1760 2022/10/14 19:26:17 - mmengine - INFO - Epoch(train) [5][760/940] lr: 1.0000e-02 eta: 14:39:45 time: 0.5930 data_time: 0.0296 memory: 33630 grad_norm: 3.5165 top1_acc: 0.2812 top5_acc: 0.6562 loss_cls: 2.2831 loss: 2.2831 2022/10/14 19:26:29 - mmengine - INFO - Epoch(train) [5][780/940] lr: 1.0000e-02 eta: 14:39:30 time: 0.5815 data_time: 0.0330 memory: 33630 grad_norm: 3.4483 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 2.2754 loss: 2.2754 2022/10/14 19:26:41 - mmengine - INFO - Epoch(train) [5][800/940] lr: 1.0000e-02 eta: 14:39:18 time: 0.5893 data_time: 0.0326 memory: 33630 grad_norm: 3.5501 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 2.3194 loss: 2.3194 2022/10/14 19:26:52 - mmengine - INFO - Epoch(train) [5][820/940] lr: 1.0000e-02 eta: 14:39:01 time: 0.5776 data_time: 0.0353 memory: 33630 grad_norm: 3.4518 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0947 loss: 2.0947 2022/10/14 19:27:04 - mmengine - INFO - Epoch(train) [5][840/940] lr: 1.0000e-02 eta: 14:38:44 time: 0.5760 data_time: 0.0404 memory: 33630 grad_norm: 3.4812 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2315 loss: 2.2315 2022/10/14 19:27:15 - mmengine - INFO - Epoch(train) [5][860/940] lr: 1.0000e-02 eta: 14:38:29 time: 0.5815 data_time: 0.0427 memory: 33630 grad_norm: 3.4185 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.1083 loss: 2.1083 2022/10/14 19:27:27 - mmengine - INFO - Epoch(train) [5][880/940] lr: 1.0000e-02 eta: 14:38:19 time: 0.5923 data_time: 0.0404 memory: 33630 grad_norm: 3.5076 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 2.1701 loss: 2.1701 2022/10/14 19:27:39 - mmengine - INFO - Epoch(train) [5][900/940] lr: 1.0000e-02 eta: 14:38:10 time: 0.5979 data_time: 0.0375 memory: 33630 grad_norm: 3.4439 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.3217 loss: 2.3217 2022/10/14 19:27:51 - mmengine - INFO - Epoch(train) [5][920/940] lr: 1.0000e-02 eta: 14:37:59 time: 0.5928 data_time: 0.0279 memory: 33630 grad_norm: 3.4757 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.0770 loss: 2.0770 2022/10/14 19:28:02 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 19:28:02 - mmengine - INFO - Epoch(train) [5][940/940] lr: 1.0000e-02 eta: 14:37:31 time: 0.5477 data_time: 0.0312 memory: 33630 grad_norm: 3.6001 top1_acc: 0.1429 top5_acc: 0.4286 loss_cls: 2.1718 loss: 2.1718 2022/10/14 19:28:17 - mmengine - INFO - Epoch(val) [5][20/78] eta: 0:00:43 time: 0.7459 data_time: 0.5720 memory: 5967 2022/10/14 19:28:27 - mmengine - INFO - Epoch(val) [5][40/78] eta: 0:00:19 time: 0.5067 data_time: 0.3383 memory: 5967 2022/10/14 19:28:40 - mmengine - INFO - Epoch(val) [5][60/78] eta: 0:00:11 time: 0.6415 data_time: 0.4727 memory: 5967 2022/10/14 19:28:52 - mmengine - INFO - Epoch(val) [5][78/78] acc/top1: 0.5711 acc/top5: 0.8113 acc/mean1: 0.5708 2022/10/14 19:28:52 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_4.pth is removed 2022/10/14 19:28:53 - mmengine - INFO - The best checkpoint with 0.5711 acc/top1 at 5 epoch is saved to best_acc/top1_epoch_5.pth. 2022/10/14 19:29:09 - mmengine - INFO - Epoch(train) [6][20/940] lr: 1.0000e-02 eta: 14:38:44 time: 0.8117 data_time: 0.2521 memory: 33630 grad_norm: 3.4661 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 2.1872 loss: 2.1872 2022/10/14 19:29:20 - mmengine - INFO - Epoch(train) [6][40/940] lr: 1.0000e-02 eta: 14:38:26 time: 0.5748 data_time: 0.0297 memory: 33630 grad_norm: 3.4652 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.2656 loss: 2.2656 2022/10/14 19:29:32 - mmengine - INFO - Epoch(train) [6][60/940] lr: 1.0000e-02 eta: 14:38:13 time: 0.5874 data_time: 0.0375 memory: 33630 grad_norm: 3.4782 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.2762 loss: 2.2762 2022/10/14 19:29:44 - mmengine - INFO - Epoch(train) [6][80/940] lr: 1.0000e-02 eta: 14:37:55 time: 0.5754 data_time: 0.0305 memory: 33630 grad_norm: 3.3885 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.2199 loss: 2.2199 2022/10/14 19:29:55 - mmengine - INFO - Epoch(train) [6][100/940] lr: 1.0000e-02 eta: 14:37:40 time: 0.5799 data_time: 0.0410 memory: 33630 grad_norm: 3.4615 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.2032 loss: 2.2032 2022/10/14 19:30:07 - mmengine - INFO - Epoch(train) [6][120/940] lr: 1.0000e-02 eta: 14:37:26 time: 0.5862 data_time: 0.0324 memory: 33630 grad_norm: 3.4175 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 2.0677 loss: 2.0677 2022/10/14 19:30:19 - mmengine - INFO - Epoch(train) [6][140/940] lr: 1.0000e-02 eta: 14:37:15 time: 0.5904 data_time: 0.0400 memory: 33630 grad_norm: 3.4144 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0650 loss: 2.0650 2022/10/14 19:30:31 - mmengine - INFO - Epoch(train) [6][160/940] lr: 1.0000e-02 eta: 14:37:04 time: 0.5925 data_time: 0.0299 memory: 33630 grad_norm: 3.4799 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.1587 loss: 2.1587 2022/10/14 19:30:42 - mmengine - INFO - Epoch(train) [6][180/940] lr: 1.0000e-02 eta: 14:36:51 time: 0.5895 data_time: 0.0363 memory: 33630 grad_norm: 3.5436 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.3286 loss: 2.3286 2022/10/14 19:30:54 - mmengine - INFO - Epoch(train) [6][200/940] lr: 1.0000e-02 eta: 14:36:39 time: 0.5880 data_time: 0.0426 memory: 33630 grad_norm: 3.4673 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 2.1454 loss: 2.1454 2022/10/14 19:31:06 - mmengine - INFO - Epoch(train) [6][220/940] lr: 1.0000e-02 eta: 14:36:24 time: 0.5819 data_time: 0.0371 memory: 33630 grad_norm: 3.5072 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.1656 loss: 2.1656 2022/10/14 19:31:18 - mmengine - INFO - Epoch(train) [6][240/940] lr: 1.0000e-02 eta: 14:36:11 time: 0.5862 data_time: 0.0288 memory: 33630 grad_norm: 3.5260 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.4980 loss: 2.4980 2022/10/14 19:31:29 - mmengine - INFO - Epoch(train) [6][260/940] lr: 1.0000e-02 eta: 14:35:55 time: 0.5781 data_time: 0.0399 memory: 33630 grad_norm: 3.4815 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.2824 loss: 2.2824 2022/10/14 19:31:41 - mmengine - INFO - Epoch(train) [6][280/940] lr: 1.0000e-02 eta: 14:35:39 time: 0.5788 data_time: 0.0369 memory: 33630 grad_norm: 3.5262 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.2142 loss: 2.2142 2022/10/14 19:31:52 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 19:31:52 - mmengine - INFO - Epoch(train) [6][300/940] lr: 1.0000e-02 eta: 14:35:22 time: 0.5779 data_time: 0.0361 memory: 33630 grad_norm: 3.4937 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.1403 loss: 2.1403 2022/10/14 19:32:04 - mmengine - INFO - Epoch(train) [6][320/940] lr: 1.0000e-02 eta: 14:35:09 time: 0.5869 data_time: 0.0310 memory: 33630 grad_norm: 3.5348 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.1431 loss: 2.1431 2022/10/14 19:32:16 - mmengine - INFO - Epoch(train) [6][340/940] lr: 1.0000e-02 eta: 14:34:58 time: 0.5902 data_time: 0.0359 memory: 33630 grad_norm: 3.5026 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.1758 loss: 2.1758 2022/10/14 19:32:27 - mmengine - INFO - Epoch(train) [6][360/940] lr: 1.0000e-02 eta: 14:34:41 time: 0.5763 data_time: 0.0331 memory: 33630 grad_norm: 3.5094 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.2433 loss: 2.2433 2022/10/14 19:32:39 - mmengine - INFO - Epoch(train) [6][380/940] lr: 1.0000e-02 eta: 14:34:29 time: 0.5887 data_time: 0.0359 memory: 33630 grad_norm: 3.4555 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0415 loss: 2.0415 2022/10/14 19:32:51 - mmengine - INFO - Epoch(train) [6][400/940] lr: 1.0000e-02 eta: 14:34:17 time: 0.5897 data_time: 0.0391 memory: 33630 grad_norm: 3.5498 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2145 loss: 2.2145 2022/10/14 19:33:02 - mmengine - INFO - Epoch(train) [6][420/940] lr: 1.0000e-02 eta: 14:34:01 time: 0.5786 data_time: 0.0303 memory: 33630 grad_norm: 3.4444 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1230 loss: 2.1230 2022/10/14 19:33:14 - mmengine - INFO - Epoch(train) [6][440/940] lr: 1.0000e-02 eta: 14:33:43 time: 0.5719 data_time: 0.0306 memory: 33630 grad_norm: 3.4922 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2359 loss: 2.2359 2022/10/14 19:33:26 - mmengine - INFO - Epoch(train) [6][460/940] lr: 1.0000e-02 eta: 14:33:33 time: 0.5945 data_time: 0.0403 memory: 33630 grad_norm: 3.4326 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.2627 loss: 2.2627 2022/10/14 19:33:37 - mmengine - INFO - Epoch(train) [6][480/940] lr: 1.0000e-02 eta: 14:33:16 time: 0.5770 data_time: 0.0319 memory: 33630 grad_norm: 3.4651 top1_acc: 0.3438 top5_acc: 0.7500 loss_cls: 2.0603 loss: 2.0603 2022/10/14 19:33:49 - mmengine - INFO - Epoch(train) [6][500/940] lr: 1.0000e-02 eta: 14:33:00 time: 0.5754 data_time: 0.0334 memory: 33630 grad_norm: 3.4922 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 2.1254 loss: 2.1254 2022/10/14 19:34:01 - mmengine - INFO - Epoch(train) [6][520/940] lr: 1.0000e-02 eta: 14:32:47 time: 0.5872 data_time: 0.0378 memory: 33630 grad_norm: 3.4835 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.1963 loss: 2.1963 2022/10/14 19:34:12 - mmengine - INFO - Epoch(train) [6][540/940] lr: 1.0000e-02 eta: 14:32:35 time: 0.5891 data_time: 0.0384 memory: 33630 grad_norm: 3.4607 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.1135 loss: 2.1135 2022/10/14 19:34:24 - mmengine - INFO - Epoch(train) [6][560/940] lr: 1.0000e-02 eta: 14:32:19 time: 0.5783 data_time: 0.0368 memory: 33630 grad_norm: 3.5126 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.1796 loss: 2.1796 2022/10/14 19:34:35 - mmengine - INFO - Epoch(train) [6][580/940] lr: 1.0000e-02 eta: 14:32:04 time: 0.5787 data_time: 0.0337 memory: 33630 grad_norm: 3.5209 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1176 loss: 2.1176 2022/10/14 19:34:47 - mmengine - INFO - Epoch(train) [6][600/940] lr: 1.0000e-02 eta: 14:31:48 time: 0.5784 data_time: 0.0414 memory: 33630 grad_norm: 3.4973 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 2.0419 loss: 2.0419 2022/10/14 19:34:59 - mmengine - INFO - Epoch(train) [6][620/940] lr: 1.0000e-02 eta: 14:31:33 time: 0.5811 data_time: 0.0289 memory: 33630 grad_norm: 3.4741 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2106 loss: 2.2106 2022/10/14 19:35:11 - mmengine - INFO - Epoch(train) [6][640/940] lr: 1.0000e-02 eta: 14:31:23 time: 0.5933 data_time: 0.0473 memory: 33630 grad_norm: 3.5067 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.1654 loss: 2.1654 2022/10/14 19:35:22 - mmengine - INFO - Epoch(train) [6][660/940] lr: 1.0000e-02 eta: 14:31:07 time: 0.5773 data_time: 0.0300 memory: 33630 grad_norm: 3.5287 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.1902 loss: 2.1902 2022/10/14 19:35:34 - mmengine - INFO - Epoch(train) [6][680/940] lr: 1.0000e-02 eta: 14:30:52 time: 0.5814 data_time: 0.0372 memory: 33630 grad_norm: 3.5050 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.1666 loss: 2.1666 2022/10/14 19:35:45 - mmengine - INFO - Epoch(train) [6][700/940] lr: 1.0000e-02 eta: 14:30:39 time: 0.5837 data_time: 0.0369 memory: 33630 grad_norm: 3.4929 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.1271 loss: 2.1271 2022/10/14 19:35:57 - mmengine - INFO - Epoch(train) [6][720/940] lr: 1.0000e-02 eta: 14:30:25 time: 0.5834 data_time: 0.0298 memory: 33630 grad_norm: 3.4850 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.0671 loss: 2.0671 2022/10/14 19:36:09 - mmengine - INFO - Epoch(train) [6][740/940] lr: 1.0000e-02 eta: 14:30:10 time: 0.5788 data_time: 0.0311 memory: 33630 grad_norm: 3.5504 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1788 loss: 2.1788 2022/10/14 19:36:20 - mmengine - INFO - Epoch(train) [6][760/940] lr: 1.0000e-02 eta: 14:29:56 time: 0.5828 data_time: 0.0310 memory: 33630 grad_norm: 3.5541 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.1059 loss: 2.1059 2022/10/14 19:36:32 - mmengine - INFO - Epoch(train) [6][780/940] lr: 1.0000e-02 eta: 14:29:40 time: 0.5783 data_time: 0.0358 memory: 33630 grad_norm: 3.5715 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.3209 loss: 2.3209 2022/10/14 19:36:43 - mmengine - INFO - Epoch(train) [6][800/940] lr: 1.0000e-02 eta: 14:29:25 time: 0.5801 data_time: 0.0323 memory: 33630 grad_norm: 3.5363 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1639 loss: 2.1639 2022/10/14 19:36:55 - mmengine - INFO - Epoch(train) [6][820/940] lr: 1.0000e-02 eta: 14:29:09 time: 0.5745 data_time: 0.0321 memory: 33630 grad_norm: 3.4212 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 2.1587 loss: 2.1587 2022/10/14 19:37:07 - mmengine - INFO - Epoch(train) [6][840/940] lr: 1.0000e-02 eta: 14:28:53 time: 0.5777 data_time: 0.0346 memory: 33630 grad_norm: 3.4458 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 2.2057 loss: 2.2057 2022/10/14 19:37:18 - mmengine - INFO - Epoch(train) [6][860/940] lr: 1.0000e-02 eta: 14:28:39 time: 0.5814 data_time: 0.0390 memory: 33630 grad_norm: 3.5157 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.1830 loss: 2.1830 2022/10/14 19:37:30 - mmengine - INFO - Epoch(train) [6][880/940] lr: 1.0000e-02 eta: 14:28:29 time: 0.5963 data_time: 0.0351 memory: 33630 grad_norm: 3.5049 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.2139 loss: 2.2139 2022/10/14 19:37:42 - mmengine - INFO - Epoch(train) [6][900/940] lr: 1.0000e-02 eta: 14:28:16 time: 0.5844 data_time: 0.0384 memory: 33630 grad_norm: 3.4199 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0620 loss: 2.0620 2022/10/14 19:37:54 - mmengine - INFO - Epoch(train) [6][920/940] lr: 1.0000e-02 eta: 14:28:07 time: 0.5991 data_time: 0.0435 memory: 33630 grad_norm: 3.4878 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 2.1198 loss: 2.1198 2022/10/14 19:38:05 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 19:38:05 - mmengine - INFO - Epoch(train) [6][940/940] lr: 1.0000e-02 eta: 14:27:40 time: 0.5413 data_time: 0.0267 memory: 33630 grad_norm: 3.6659 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 2.1586 loss: 2.1586 2022/10/14 19:38:05 - mmengine - INFO - Saving checkpoint at 6 epochs 2022/10/14 19:38:19 - mmengine - INFO - Epoch(val) [6][20/78] eta: 0:00:40 time: 0.7004 data_time: 0.5299 memory: 5967 2022/10/14 19:38:30 - mmengine - INFO - Epoch(val) [6][40/78] eta: 0:00:19 time: 0.5114 data_time: 0.3441 memory: 5967 2022/10/14 19:38:44 - mmengine - INFO - Epoch(val) [6][60/78] eta: 0:00:12 time: 0.6934 data_time: 0.5226 memory: 5967 2022/10/14 19:38:55 - mmengine - INFO - Epoch(val) [6][78/78] acc/top1: 0.5697 acc/top5: 0.8112 acc/mean1: 0.5694 2022/10/14 19:39:12 - mmengine - INFO - Epoch(train) [7][20/940] lr: 1.0000e-02 eta: 14:28:56 time: 0.8706 data_time: 0.2357 memory: 33630 grad_norm: 3.4924 top1_acc: 0.3438 top5_acc: 0.5312 loss_cls: 2.1176 loss: 2.1176 2022/10/14 19:39:24 - mmengine - INFO - Epoch(train) [7][40/940] lr: 1.0000e-02 eta: 14:28:53 time: 0.6162 data_time: 0.0305 memory: 33630 grad_norm: 3.4774 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9987 loss: 1.9987 2022/10/14 19:39:37 - mmengine - INFO - Epoch(train) [7][60/940] lr: 1.0000e-02 eta: 14:28:45 time: 0.6044 data_time: 0.0395 memory: 33630 grad_norm: 3.4930 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.1450 loss: 2.1450 2022/10/14 19:39:48 - mmengine - INFO - Epoch(train) [7][80/940] lr: 1.0000e-02 eta: 14:28:35 time: 0.5954 data_time: 0.0311 memory: 33630 grad_norm: 3.4972 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.1244 loss: 2.1244 2022/10/14 19:40:00 - mmengine - INFO - Epoch(train) [7][100/940] lr: 1.0000e-02 eta: 14:28:22 time: 0.5862 data_time: 0.0304 memory: 33630 grad_norm: 3.5279 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 2.1950 loss: 2.1950 2022/10/14 19:40:12 - mmengine - INFO - Epoch(train) [7][120/940] lr: 1.0000e-02 eta: 14:28:06 time: 0.5764 data_time: 0.0317 memory: 33630 grad_norm: 3.4805 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.0435 loss: 2.0435 2022/10/14 19:40:23 - mmengine - INFO - Epoch(train) [7][140/940] lr: 1.0000e-02 eta: 14:27:52 time: 0.5823 data_time: 0.0359 memory: 33630 grad_norm: 3.4479 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1334 loss: 2.1334 2022/10/14 19:40:35 - mmengine - INFO - Epoch(train) [7][160/940] lr: 1.0000e-02 eta: 14:27:40 time: 0.5902 data_time: 0.0377 memory: 33630 grad_norm: 3.4820 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.0167 loss: 2.0167 2022/10/14 19:40:47 - mmengine - INFO - Epoch(train) [7][180/940] lr: 1.0000e-02 eta: 14:27:25 time: 0.5807 data_time: 0.0375 memory: 33630 grad_norm: 3.4559 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0657 loss: 2.0657 2022/10/14 19:40:59 - mmengine - INFO - Epoch(train) [7][200/940] lr: 1.0000e-02 eta: 14:27:15 time: 0.5972 data_time: 0.0385 memory: 33630 grad_norm: 3.4315 top1_acc: 0.4375 top5_acc: 0.8438 loss_cls: 2.1344 loss: 2.1344 2022/10/14 19:41:10 - mmengine - INFO - Epoch(train) [7][220/940] lr: 1.0000e-02 eta: 14:27:00 time: 0.5769 data_time: 0.0317 memory: 33630 grad_norm: 3.4824 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.0567 loss: 2.0567 2022/10/14 19:41:22 - mmengine - INFO - Epoch(train) [7][240/940] lr: 1.0000e-02 eta: 14:26:45 time: 0.5793 data_time: 0.0305 memory: 33630 grad_norm: 3.5273 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.1198 loss: 2.1198 2022/10/14 19:41:34 - mmengine - INFO - Epoch(train) [7][260/940] lr: 1.0000e-02 eta: 14:26:32 time: 0.5866 data_time: 0.0324 memory: 33630 grad_norm: 3.5201 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.0654 loss: 2.0654 2022/10/14 19:41:45 - mmengine - INFO - Epoch(train) [7][280/940] lr: 1.0000e-02 eta: 14:26:16 time: 0.5787 data_time: 0.0343 memory: 33630 grad_norm: 3.4454 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.1913 loss: 2.1913 2022/10/14 19:41:57 - mmengine - INFO - Epoch(train) [7][300/940] lr: 1.0000e-02 eta: 14:25:59 time: 0.5714 data_time: 0.0319 memory: 33630 grad_norm: 3.4620 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.0954 loss: 2.0954 2022/10/14 19:42:09 - mmengine - INFO - Epoch(train) [7][320/940] lr: 1.0000e-02 eta: 14:25:49 time: 0.5946 data_time: 0.0334 memory: 33630 grad_norm: 3.4471 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1367 loss: 2.1367 2022/10/14 19:42:20 - mmengine - INFO - Epoch(train) [7][340/940] lr: 1.0000e-02 eta: 14:25:37 time: 0.5913 data_time: 0.0415 memory: 33630 grad_norm: 3.5013 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.1970 loss: 2.1970 2022/10/14 19:42:32 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 19:42:32 - mmengine - INFO - Epoch(train) [7][360/940] lr: 1.0000e-02 eta: 14:25:26 time: 0.5936 data_time: 0.0364 memory: 33630 grad_norm: 3.4598 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9588 loss: 1.9588 2022/10/14 19:42:44 - mmengine - INFO - Epoch(train) [7][380/940] lr: 1.0000e-02 eta: 14:25:16 time: 0.5950 data_time: 0.0347 memory: 33630 grad_norm: 3.5148 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.0577 loss: 2.0577 2022/10/14 19:42:56 - mmengine - INFO - Epoch(train) [7][400/940] lr: 1.0000e-02 eta: 14:25:04 time: 0.5904 data_time: 0.0405 memory: 33630 grad_norm: 3.5223 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0827 loss: 2.0827 2022/10/14 19:43:08 - mmengine - INFO - Epoch(train) [7][420/940] lr: 1.0000e-02 eta: 14:24:52 time: 0.5893 data_time: 0.0418 memory: 33630 grad_norm: 3.5935 top1_acc: 0.4375 top5_acc: 0.8438 loss_cls: 2.2433 loss: 2.2433 2022/10/14 19:43:20 - mmengine - INFO - Epoch(train) [7][440/940] lr: 1.0000e-02 eta: 14:24:41 time: 0.5904 data_time: 0.0382 memory: 33630 grad_norm: 3.5227 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 2.1907 loss: 2.1907 2022/10/14 19:43:31 - mmengine - INFO - Epoch(train) [7][460/940] lr: 1.0000e-02 eta: 14:24:22 time: 0.5668 data_time: 0.0314 memory: 33630 grad_norm: 3.5597 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.1042 loss: 2.1042 2022/10/14 19:43:43 - mmengine - INFO - Epoch(train) [7][480/940] lr: 1.0000e-02 eta: 14:24:09 time: 0.5865 data_time: 0.0314 memory: 33630 grad_norm: 3.5431 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.0751 loss: 2.0751 2022/10/14 19:43:54 - mmengine - INFO - Epoch(train) [7][500/940] lr: 1.0000e-02 eta: 14:23:54 time: 0.5764 data_time: 0.0400 memory: 33630 grad_norm: 3.4487 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1267 loss: 2.1267 2022/10/14 19:44:06 - mmengine - INFO - Epoch(train) [7][520/940] lr: 1.0000e-02 eta: 14:23:36 time: 0.5706 data_time: 0.0282 memory: 33630 grad_norm: 3.4811 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0192 loss: 2.0192 2022/10/14 19:44:17 - mmengine - INFO - Epoch(train) [7][540/940] lr: 1.0000e-02 eta: 14:23:23 time: 0.5842 data_time: 0.0398 memory: 33630 grad_norm: 3.5708 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.9836 loss: 1.9836 2022/10/14 19:44:29 - mmengine - INFO - Epoch(train) [7][560/940] lr: 1.0000e-02 eta: 14:23:09 time: 0.5812 data_time: 0.0320 memory: 33630 grad_norm: 3.5378 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.1414 loss: 2.1414 2022/10/14 19:44:40 - mmengine - INFO - Epoch(train) [7][580/940] lr: 1.0000e-02 eta: 14:22:52 time: 0.5722 data_time: 0.0370 memory: 33630 grad_norm: 3.5603 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1378 loss: 2.1378 2022/10/14 19:44:52 - mmengine - INFO - Epoch(train) [7][600/940] lr: 1.0000e-02 eta: 14:22:35 time: 0.5724 data_time: 0.0335 memory: 33630 grad_norm: 3.5075 top1_acc: 0.4062 top5_acc: 0.5625 loss_cls: 2.1947 loss: 2.1947 2022/10/14 19:45:04 - mmengine - INFO - Epoch(train) [7][620/940] lr: 1.0000e-02 eta: 14:22:24 time: 0.5909 data_time: 0.0337 memory: 33630 grad_norm: 3.5124 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 2.0003 loss: 2.0003 2022/10/14 19:45:15 - mmengine - INFO - Epoch(train) [7][640/940] lr: 1.0000e-02 eta: 14:22:10 time: 0.5832 data_time: 0.0369 memory: 33630 grad_norm: 3.4758 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.9906 loss: 1.9906 2022/10/14 19:45:27 - mmengine - INFO - Epoch(train) [7][660/940] lr: 1.0000e-02 eta: 14:22:01 time: 0.5983 data_time: 0.0338 memory: 33630 grad_norm: 3.4676 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.1558 loss: 2.1558 2022/10/14 19:45:39 - mmengine - INFO - Epoch(train) [7][680/940] lr: 1.0000e-02 eta: 14:21:44 time: 0.5742 data_time: 0.0360 memory: 33630 grad_norm: 3.5891 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 2.0960 loss: 2.0960 2022/10/14 19:45:50 - mmengine - INFO - Epoch(train) [7][700/940] lr: 1.0000e-02 eta: 14:21:31 time: 0.5847 data_time: 0.0371 memory: 33630 grad_norm: 3.4781 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9925 loss: 1.9925 2022/10/14 19:46:02 - mmengine - INFO - Epoch(train) [7][720/940] lr: 1.0000e-02 eta: 14:21:18 time: 0.5837 data_time: 0.0389 memory: 33630 grad_norm: 3.5216 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.1018 loss: 2.1018 2022/10/14 19:46:14 - mmengine - INFO - Epoch(train) [7][740/940] lr: 1.0000e-02 eta: 14:21:07 time: 0.5920 data_time: 0.0475 memory: 33630 grad_norm: 3.4649 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.0596 loss: 2.0596 2022/10/14 19:46:25 - mmengine - INFO - Epoch(train) [7][760/940] lr: 1.0000e-02 eta: 14:20:53 time: 0.5808 data_time: 0.0408 memory: 33630 grad_norm: 3.6091 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1150 loss: 2.1150 2022/10/14 19:46:37 - mmengine - INFO - Epoch(train) [7][780/940] lr: 1.0000e-02 eta: 14:20:38 time: 0.5792 data_time: 0.0345 memory: 33630 grad_norm: 3.5250 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.1759 loss: 2.1759 2022/10/14 19:46:49 - mmengine - INFO - Epoch(train) [7][800/940] lr: 1.0000e-02 eta: 14:20:26 time: 0.5894 data_time: 0.0322 memory: 33630 grad_norm: 3.4775 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.0428 loss: 2.0428 2022/10/14 19:47:01 - mmengine - INFO - Epoch(train) [7][820/940] lr: 1.0000e-02 eta: 14:20:12 time: 0.5831 data_time: 0.0362 memory: 33630 grad_norm: 3.4746 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.9086 loss: 1.9086 2022/10/14 19:47:12 - mmengine - INFO - Epoch(train) [7][840/940] lr: 1.0000e-02 eta: 14:19:57 time: 0.5772 data_time: 0.0360 memory: 33630 grad_norm: 3.5700 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1465 loss: 2.1465 2022/10/14 19:47:24 - mmengine - INFO - Epoch(train) [7][860/940] lr: 1.0000e-02 eta: 14:19:45 time: 0.5885 data_time: 0.0374 memory: 33630 grad_norm: 3.5786 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0922 loss: 2.0922 2022/10/14 19:47:36 - mmengine - INFO - Epoch(train) [7][880/940] lr: 1.0000e-02 eta: 14:19:33 time: 0.5870 data_time: 0.0372 memory: 33630 grad_norm: 3.5270 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0003 loss: 2.0003 2022/10/14 19:47:47 - mmengine - INFO - Epoch(train) [7][900/940] lr: 1.0000e-02 eta: 14:19:17 time: 0.5749 data_time: 0.0295 memory: 33630 grad_norm: 3.5445 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1546 loss: 2.1546 2022/10/14 19:47:59 - mmengine - INFO - Epoch(train) [7][920/940] lr: 1.0000e-02 eta: 14:19:02 time: 0.5786 data_time: 0.0378 memory: 33630 grad_norm: 3.5464 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.9547 loss: 1.9547 2022/10/14 19:48:09 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 19:48:09 - mmengine - INFO - Epoch(train) [7][940/940] lr: 1.0000e-02 eta: 14:18:38 time: 0.5410 data_time: 0.0369 memory: 33630 grad_norm: 3.6878 top1_acc: 0.4286 top5_acc: 0.4286 loss_cls: 2.0516 loss: 2.0516 2022/10/14 19:48:24 - mmengine - INFO - Epoch(val) [7][20/78] eta: 0:00:42 time: 0.7396 data_time: 0.5713 memory: 5967 2022/10/14 19:48:35 - mmengine - INFO - Epoch(val) [7][40/78] eta: 0:00:19 time: 0.5029 data_time: 0.3331 memory: 5967 2022/10/14 19:48:48 - mmengine - INFO - Epoch(val) [7][60/78] eta: 0:00:12 time: 0.6714 data_time: 0.5020 memory: 5967 2022/10/14 19:48:59 - mmengine - INFO - Epoch(val) [7][78/78] acc/top1: 0.5930 acc/top5: 0.8267 acc/mean1: 0.5928 2022/10/14 19:48:59 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_5.pth is removed 2022/10/14 19:49:00 - mmengine - INFO - The best checkpoint with 0.5930 acc/top1 at 7 epoch is saved to best_acc/top1_epoch_7.pth. 2022/10/14 19:49:16 - mmengine - INFO - Epoch(train) [8][20/940] lr: 1.0000e-02 eta: 14:19:22 time: 0.8020 data_time: 0.2198 memory: 33630 grad_norm: 3.5050 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.0909 loss: 2.0909 2022/10/14 19:49:27 - mmengine - INFO - Epoch(train) [8][40/940] lr: 1.0000e-02 eta: 14:19:08 time: 0.5820 data_time: 0.0329 memory: 33630 grad_norm: 3.4712 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.9427 loss: 1.9427 2022/10/14 19:49:39 - mmengine - INFO - Epoch(train) [8][60/940] lr: 1.0000e-02 eta: 14:18:54 time: 0.5806 data_time: 0.0373 memory: 33630 grad_norm: 3.5407 top1_acc: 0.5938 top5_acc: 0.6562 loss_cls: 1.8865 loss: 1.8865 2022/10/14 19:49:51 - mmengine - INFO - Epoch(train) [8][80/940] lr: 1.0000e-02 eta: 14:18:45 time: 0.6001 data_time: 0.0518 memory: 33630 grad_norm: 3.5332 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 2.1419 loss: 2.1419 2022/10/14 19:50:03 - mmengine - INFO - Epoch(train) [8][100/940] lr: 1.0000e-02 eta: 14:18:33 time: 0.5885 data_time: 0.0360 memory: 33630 grad_norm: 3.4925 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 2.1930 loss: 2.1930 2022/10/14 19:50:15 - mmengine - INFO - Epoch(train) [8][120/940] lr: 1.0000e-02 eta: 14:18:21 time: 0.5901 data_time: 0.0310 memory: 33630 grad_norm: 3.4791 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.8962 loss: 1.8962 2022/10/14 19:50:27 - mmengine - INFO - Epoch(train) [8][140/940] lr: 1.0000e-02 eta: 14:18:12 time: 0.5995 data_time: 0.0375 memory: 33630 grad_norm: 3.5259 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0230 loss: 2.0230 2022/10/14 19:50:38 - mmengine - INFO - Epoch(train) [8][160/940] lr: 1.0000e-02 eta: 14:17:57 time: 0.5784 data_time: 0.0325 memory: 33630 grad_norm: 3.5137 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9546 loss: 1.9546 2022/10/14 19:50:50 - mmengine - INFO - Epoch(train) [8][180/940] lr: 1.0000e-02 eta: 14:17:45 time: 0.5895 data_time: 0.0340 memory: 33630 grad_norm: 3.5557 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 2.0721 loss: 2.0721 2022/10/14 19:51:02 - mmengine - INFO - Epoch(train) [8][200/940] lr: 1.0000e-02 eta: 14:17:34 time: 0.5950 data_time: 0.0361 memory: 33630 grad_norm: 3.5460 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.0953 loss: 2.0953 2022/10/14 19:51:14 - mmengine - INFO - Epoch(train) [8][220/940] lr: 1.0000e-02 eta: 14:17:21 time: 0.5853 data_time: 0.0367 memory: 33630 grad_norm: 3.5989 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9942 loss: 1.9942 2022/10/14 19:51:26 - mmengine - INFO - Epoch(train) [8][240/940] lr: 1.0000e-02 eta: 14:17:11 time: 0.5964 data_time: 0.0334 memory: 33630 grad_norm: 3.5522 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0104 loss: 2.0104 2022/10/14 19:51:37 - mmengine - INFO - Epoch(train) [8][260/940] lr: 1.0000e-02 eta: 14:16:57 time: 0.5790 data_time: 0.0312 memory: 33630 grad_norm: 3.5284 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9828 loss: 1.9828 2022/10/14 19:51:49 - mmengine - INFO - Epoch(train) [8][280/940] lr: 1.0000e-02 eta: 14:16:43 time: 0.5816 data_time: 0.0407 memory: 33630 grad_norm: 3.5072 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 1.9900 loss: 1.9900 2022/10/14 19:52:00 - mmengine - INFO - Epoch(train) [8][300/940] lr: 1.0000e-02 eta: 14:16:29 time: 0.5819 data_time: 0.0274 memory: 33630 grad_norm: 3.5496 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.9503 loss: 1.9503 2022/10/14 19:52:12 - mmengine - INFO - Epoch(train) [8][320/940] lr: 1.0000e-02 eta: 14:16:13 time: 0.5714 data_time: 0.0309 memory: 33630 grad_norm: 3.5846 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.1479 loss: 2.1479 2022/10/14 19:52:24 - mmengine - INFO - Epoch(train) [8][340/940] lr: 1.0000e-02 eta: 14:16:01 time: 0.5920 data_time: 0.0417 memory: 33630 grad_norm: 3.5359 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.0583 loss: 2.0583 2022/10/14 19:52:35 - mmengine - INFO - Epoch(train) [8][360/940] lr: 1.0000e-02 eta: 14:15:46 time: 0.5769 data_time: 0.0404 memory: 33630 grad_norm: 3.5810 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2030 loss: 2.2030 2022/10/14 19:52:47 - mmengine - INFO - Epoch(train) [8][380/940] lr: 1.0000e-02 eta: 14:15:34 time: 0.5892 data_time: 0.0408 memory: 33630 grad_norm: 3.5195 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 2.1041 loss: 2.1041 2022/10/14 19:52:59 - mmengine - INFO - Epoch(train) [8][400/940] lr: 1.0000e-02 eta: 14:15:24 time: 0.5949 data_time: 0.0440 memory: 33630 grad_norm: 3.5822 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 2.0467 loss: 2.0467 2022/10/14 19:53:10 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 19:53:10 - mmengine - INFO - Epoch(train) [8][420/940] lr: 1.0000e-02 eta: 14:15:08 time: 0.5748 data_time: 0.0311 memory: 33630 grad_norm: 3.5830 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.0739 loss: 2.0739 2022/10/14 19:53:22 - mmengine - INFO - Epoch(train) [8][440/940] lr: 1.0000e-02 eta: 14:14:56 time: 0.5866 data_time: 0.0331 memory: 33630 grad_norm: 3.5812 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.0703 loss: 2.0703 2022/10/14 19:53:34 - mmengine - INFO - Epoch(train) [8][460/940] lr: 1.0000e-02 eta: 14:14:44 time: 0.5899 data_time: 0.0457 memory: 33630 grad_norm: 3.5611 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0216 loss: 2.0216 2022/10/14 19:53:46 - mmengine - INFO - Epoch(train) [8][480/940] lr: 1.0000e-02 eta: 14:14:31 time: 0.5858 data_time: 0.0327 memory: 33630 grad_norm: 3.5421 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1247 loss: 2.1247 2022/10/14 19:53:57 - mmengine - INFO - Epoch(train) [8][500/940] lr: 1.0000e-02 eta: 14:14:18 time: 0.5846 data_time: 0.0355 memory: 33630 grad_norm: 3.4787 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9882 loss: 1.9882 2022/10/14 19:54:09 - mmengine - INFO - Epoch(train) [8][520/940] lr: 1.0000e-02 eta: 14:14:05 time: 0.5853 data_time: 0.0327 memory: 33630 grad_norm: 3.6054 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.1887 loss: 2.1887 2022/10/14 19:54:21 - mmengine - INFO - Epoch(train) [8][540/940] lr: 1.0000e-02 eta: 14:13:51 time: 0.5792 data_time: 0.0331 memory: 33630 grad_norm: 3.5161 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 2.0406 loss: 2.0406 2022/10/14 19:54:32 - mmengine - INFO - Epoch(train) [8][560/940] lr: 1.0000e-02 eta: 14:13:37 time: 0.5791 data_time: 0.0340 memory: 33630 grad_norm: 3.5636 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.0442 loss: 2.0442 2022/10/14 19:54:44 - mmengine - INFO - Epoch(train) [8][580/940] lr: 1.0000e-02 eta: 14:13:24 time: 0.5874 data_time: 0.0400 memory: 33630 grad_norm: 3.5483 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.9945 loss: 1.9945 2022/10/14 19:54:55 - mmengine - INFO - Epoch(train) [8][600/940] lr: 1.0000e-02 eta: 14:13:09 time: 0.5759 data_time: 0.0415 memory: 33630 grad_norm: 3.4536 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.9833 loss: 1.9833 2022/10/14 19:55:07 - mmengine - INFO - Epoch(train) [8][620/940] lr: 1.0000e-02 eta: 14:12:55 time: 0.5805 data_time: 0.0310 memory: 33630 grad_norm: 3.5124 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.9397 loss: 1.9397 2022/10/14 19:55:19 - mmengine - INFO - Epoch(train) [8][640/940] lr: 1.0000e-02 eta: 14:12:39 time: 0.5722 data_time: 0.0323 memory: 33630 grad_norm: 3.5729 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 2.1019 loss: 2.1019 2022/10/14 19:55:30 - mmengine - INFO - Epoch(train) [8][660/940] lr: 1.0000e-02 eta: 14:12:27 time: 0.5887 data_time: 0.0338 memory: 33630 grad_norm: 3.5197 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 2.0275 loss: 2.0275 2022/10/14 19:55:42 - mmengine - INFO - Epoch(train) [8][680/940] lr: 1.0000e-02 eta: 14:12:16 time: 0.5902 data_time: 0.0396 memory: 33630 grad_norm: 3.5254 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.9358 loss: 1.9358 2022/10/14 19:55:54 - mmengine - INFO - Epoch(train) [8][700/940] lr: 1.0000e-02 eta: 14:12:04 time: 0.5890 data_time: 0.0494 memory: 33630 grad_norm: 3.5771 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.0645 loss: 2.0645 2022/10/14 19:56:05 - mmengine - INFO - Epoch(train) [8][720/940] lr: 1.0000e-02 eta: 14:11:49 time: 0.5784 data_time: 0.0302 memory: 33630 grad_norm: 3.5860 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1756 loss: 2.1756 2022/10/14 19:56:17 - mmengine - INFO - Epoch(train) [8][740/940] lr: 1.0000e-02 eta: 14:11:36 time: 0.5827 data_time: 0.0352 memory: 33630 grad_norm: 3.4701 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9548 loss: 1.9548 2022/10/14 19:56:29 - mmengine - INFO - Epoch(train) [8][760/940] lr: 1.0000e-02 eta: 14:11:27 time: 0.6030 data_time: 0.0453 memory: 33630 grad_norm: 3.5402 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.1008 loss: 2.1008 2022/10/14 19:56:41 - mmengine - INFO - Epoch(train) [8][780/940] lr: 1.0000e-02 eta: 14:11:15 time: 0.5896 data_time: 0.0402 memory: 33630 grad_norm: 3.5793 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1445 loss: 2.1445 2022/10/14 19:56:53 - mmengine - INFO - Epoch(train) [8][800/940] lr: 1.0000e-02 eta: 14:11:03 time: 0.5863 data_time: 0.0348 memory: 33630 grad_norm: 3.5352 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 2.0336 loss: 2.0336 2022/10/14 19:57:05 - mmengine - INFO - Epoch(train) [8][820/940] lr: 1.0000e-02 eta: 14:10:53 time: 0.5986 data_time: 0.0455 memory: 33630 grad_norm: 3.5518 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 2.1127 loss: 2.1127 2022/10/14 19:57:17 - mmengine - INFO - Epoch(train) [8][840/940] lr: 1.0000e-02 eta: 14:10:43 time: 0.5966 data_time: 0.0325 memory: 33630 grad_norm: 3.5490 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.1668 loss: 2.1668 2022/10/14 19:57:28 - mmengine - INFO - Epoch(train) [8][860/940] lr: 1.0000e-02 eta: 14:10:31 time: 0.5875 data_time: 0.0390 memory: 33630 grad_norm: 3.5427 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.2978 loss: 2.2978 2022/10/14 19:57:40 - mmengine - INFO - Epoch(train) [8][880/940] lr: 1.0000e-02 eta: 14:10:18 time: 0.5864 data_time: 0.0356 memory: 33630 grad_norm: 3.5146 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9877 loss: 1.9877 2022/10/14 19:57:52 - mmengine - INFO - Epoch(train) [8][900/940] lr: 1.0000e-02 eta: 14:10:05 time: 0.5852 data_time: 0.0301 memory: 33630 grad_norm: 3.5796 top1_acc: 0.2188 top5_acc: 0.5625 loss_cls: 2.1315 loss: 2.1315 2022/10/14 19:58:03 - mmengine - INFO - Epoch(train) [8][920/940] lr: 1.0000e-02 eta: 14:09:52 time: 0.5823 data_time: 0.0305 memory: 33630 grad_norm: 3.5335 top1_acc: 0.3438 top5_acc: 0.5625 loss_cls: 2.1355 loss: 2.1355 2022/10/14 19:58:14 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 19:58:14 - mmengine - INFO - Epoch(train) [8][940/940] lr: 1.0000e-02 eta: 14:09:30 time: 0.5454 data_time: 0.0316 memory: 33630 grad_norm: 3.7754 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 2.0699 loss: 2.0699 2022/10/14 19:58:29 - mmengine - INFO - Epoch(val) [8][20/78] eta: 0:00:43 time: 0.7510 data_time: 0.5797 memory: 5967 2022/10/14 19:58:39 - mmengine - INFO - Epoch(val) [8][40/78] eta: 0:00:18 time: 0.4867 data_time: 0.3190 memory: 5967 2022/10/14 19:58:52 - mmengine - INFO - Epoch(val) [8][60/78] eta: 0:00:11 time: 0.6629 data_time: 0.4947 memory: 5967 2022/10/14 19:59:04 - mmengine - INFO - Epoch(val) [8][78/78] acc/top1: 0.5917 acc/top5: 0.8244 acc/mean1: 0.5916 2022/10/14 19:59:22 - mmengine - INFO - Epoch(train) [9][20/940] lr: 1.0000e-02 eta: 14:10:21 time: 0.8606 data_time: 0.2526 memory: 33630 grad_norm: 3.5198 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.0584 loss: 2.0584 2022/10/14 19:59:33 - mmengine - INFO - Epoch(train) [9][40/940] lr: 1.0000e-02 eta: 14:10:06 time: 0.5782 data_time: 0.0317 memory: 33630 grad_norm: 3.5586 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 2.0404 loss: 2.0404 2022/10/14 19:59:45 - mmengine - INFO - Epoch(train) [9][60/940] lr: 1.0000e-02 eta: 14:09:59 time: 0.6097 data_time: 0.0390 memory: 33630 grad_norm: 3.5683 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 2.0210 loss: 2.0210 2022/10/14 19:59:57 - mmengine - INFO - Epoch(train) [9][80/940] lr: 1.0000e-02 eta: 14:09:50 time: 0.6027 data_time: 0.0485 memory: 33630 grad_norm: 3.5345 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.1047 loss: 2.1047 2022/10/14 20:00:10 - mmengine - INFO - Epoch(train) [9][100/940] lr: 1.0000e-02 eta: 14:09:43 time: 0.6124 data_time: 0.0453 memory: 33630 grad_norm: 3.5564 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.0476 loss: 2.0476 2022/10/14 20:00:21 - mmengine - INFO - Epoch(train) [9][120/940] lr: 1.0000e-02 eta: 14:09:26 time: 0.5665 data_time: 0.0336 memory: 33630 grad_norm: 3.5495 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.9596 loss: 1.9596 2022/10/14 20:00:33 - mmengine - INFO - Epoch(train) [9][140/940] lr: 1.0000e-02 eta: 14:09:13 time: 0.5863 data_time: 0.0432 memory: 33630 grad_norm: 3.5497 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 2.0296 loss: 2.0296 2022/10/14 20:00:44 - mmengine - INFO - Epoch(train) [9][160/940] lr: 1.0000e-02 eta: 14:09:00 time: 0.5865 data_time: 0.0428 memory: 33630 grad_norm: 3.5429 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.0982 loss: 2.0982 2022/10/14 20:00:56 - mmengine - INFO - Epoch(train) [9][180/940] lr: 1.0000e-02 eta: 14:08:49 time: 0.5896 data_time: 0.0353 memory: 33630 grad_norm: 3.5562 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 2.0554 loss: 2.0554 2022/10/14 20:01:08 - mmengine - INFO - Epoch(train) [9][200/940] lr: 1.0000e-02 eta: 14:08:35 time: 0.5820 data_time: 0.0436 memory: 33630 grad_norm: 3.6061 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0183 loss: 2.0183 2022/10/14 20:01:20 - mmengine - INFO - Epoch(train) [9][220/940] lr: 1.0000e-02 eta: 14:08:22 time: 0.5864 data_time: 0.0340 memory: 33630 grad_norm: 3.5137 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1348 loss: 2.1348 2022/10/14 20:01:31 - mmengine - INFO - Epoch(train) [9][240/940] lr: 1.0000e-02 eta: 14:08:08 time: 0.5796 data_time: 0.0338 memory: 33630 grad_norm: 3.5616 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.0068 loss: 2.0068 2022/10/14 20:01:43 - mmengine - INFO - Epoch(train) [9][260/940] lr: 1.0000e-02 eta: 14:07:54 time: 0.5809 data_time: 0.0308 memory: 33630 grad_norm: 3.4853 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9615 loss: 1.9615 2022/10/14 20:01:54 - mmengine - INFO - Epoch(train) [9][280/940] lr: 1.0000e-02 eta: 14:07:38 time: 0.5698 data_time: 0.0360 memory: 33630 grad_norm: 3.5555 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.0213 loss: 2.0213 2022/10/14 20:02:06 - mmengine - INFO - Epoch(train) [9][300/940] lr: 1.0000e-02 eta: 14:07:27 time: 0.5922 data_time: 0.0322 memory: 33630 grad_norm: 3.4503 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9606 loss: 1.9606 2022/10/14 20:02:18 - mmengine - INFO - Epoch(train) [9][320/940] lr: 1.0000e-02 eta: 14:07:15 time: 0.5905 data_time: 0.0403 memory: 33630 grad_norm: 3.5344 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.0912 loss: 2.0912 2022/10/14 20:02:30 - mmengine - INFO - Epoch(train) [9][340/940] lr: 1.0000e-02 eta: 14:07:04 time: 0.5949 data_time: 0.0326 memory: 33630 grad_norm: 3.5549 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9381 loss: 1.9381 2022/10/14 20:02:42 - mmengine - INFO - Epoch(train) [9][360/940] lr: 1.0000e-02 eta: 14:06:53 time: 0.5919 data_time: 0.0387 memory: 33630 grad_norm: 3.5685 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9931 loss: 1.9931 2022/10/14 20:02:53 - mmengine - INFO - Epoch(train) [9][380/940] lr: 1.0000e-02 eta: 14:06:38 time: 0.5761 data_time: 0.0326 memory: 33630 grad_norm: 3.5882 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.9104 loss: 1.9104 2022/10/14 20:03:05 - mmengine - INFO - Epoch(train) [9][400/940] lr: 1.0000e-02 eta: 14:06:28 time: 0.5958 data_time: 0.0390 memory: 33630 grad_norm: 3.5457 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.9796 loss: 1.9796 2022/10/14 20:03:17 - mmengine - INFO - Epoch(train) [9][420/940] lr: 1.0000e-02 eta: 14:06:14 time: 0.5809 data_time: 0.0456 memory: 33630 grad_norm: 3.5667 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.0067 loss: 2.0067 2022/10/14 20:03:28 - mmengine - INFO - Epoch(train) [9][440/940] lr: 1.0000e-02 eta: 14:05:59 time: 0.5751 data_time: 0.0313 memory: 33630 grad_norm: 3.5477 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9596 loss: 1.9596 2022/10/14 20:03:40 - mmengine - INFO - Epoch(train) [9][460/940] lr: 1.0000e-02 eta: 14:05:48 time: 0.5971 data_time: 0.0460 memory: 33630 grad_norm: 3.5966 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1195 loss: 2.1195 2022/10/14 20:03:52 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 20:03:52 - mmengine - INFO - Epoch(train) [9][480/940] lr: 1.0000e-02 eta: 14:05:38 time: 0.5951 data_time: 0.0382 memory: 33630 grad_norm: 3.5769 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0775 loss: 2.0775 2022/10/14 20:04:04 - mmengine - INFO - Epoch(train) [9][500/940] lr: 1.0000e-02 eta: 14:05:24 time: 0.5788 data_time: 0.0392 memory: 33630 grad_norm: 3.5840 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.1528 loss: 2.1528 2022/10/14 20:04:15 - mmengine - INFO - Epoch(train) [9][520/940] lr: 1.0000e-02 eta: 14:05:09 time: 0.5782 data_time: 0.0357 memory: 33630 grad_norm: 3.5807 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9794 loss: 1.9794 2022/10/14 20:04:27 - mmengine - INFO - Epoch(train) [9][540/940] lr: 1.0000e-02 eta: 14:04:55 time: 0.5803 data_time: 0.0333 memory: 33630 grad_norm: 3.6152 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.0109 loss: 2.0109 2022/10/14 20:04:38 - mmengine - INFO - Epoch(train) [9][560/940] lr: 1.0000e-02 eta: 14:04:42 time: 0.5806 data_time: 0.0309 memory: 33630 grad_norm: 3.5564 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.0261 loss: 2.0261 2022/10/14 20:04:50 - mmengine - INFO - Epoch(train) [9][580/940] lr: 1.0000e-02 eta: 14:04:28 time: 0.5823 data_time: 0.0328 memory: 33630 grad_norm: 3.5972 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 2.0956 loss: 2.0956 2022/10/14 20:05:02 - mmengine - INFO - Epoch(train) [9][600/940] lr: 1.0000e-02 eta: 14:04:18 time: 0.5968 data_time: 0.0376 memory: 33630 grad_norm: 3.5682 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.0526 loss: 2.0526 2022/10/14 20:05:14 - mmengine - INFO - Epoch(train) [9][620/940] lr: 1.0000e-02 eta: 14:04:07 time: 0.5929 data_time: 0.0332 memory: 33630 grad_norm: 3.5802 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9799 loss: 1.9799 2022/10/14 20:05:26 - mmengine - INFO - Epoch(train) [9][640/940] lr: 1.0000e-02 eta: 14:03:55 time: 0.5911 data_time: 0.0499 memory: 33630 grad_norm: 3.6230 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.1943 loss: 2.1943 2022/10/14 20:05:37 - mmengine - INFO - Epoch(train) [9][660/940] lr: 1.0000e-02 eta: 14:03:42 time: 0.5845 data_time: 0.0301 memory: 33630 grad_norm: 3.5697 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 2.0388 loss: 2.0388 2022/10/14 20:05:49 - mmengine - INFO - Epoch(train) [9][680/940] lr: 1.0000e-02 eta: 14:03:32 time: 0.5950 data_time: 0.0469 memory: 33630 grad_norm: 3.5756 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 2.1441 loss: 2.1441 2022/10/14 20:06:01 - mmengine - INFO - Epoch(train) [9][700/940] lr: 1.0000e-02 eta: 14:03:18 time: 0.5818 data_time: 0.0437 memory: 33630 grad_norm: 3.6323 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.8870 loss: 1.8870 2022/10/14 20:06:12 - mmengine - INFO - Epoch(train) [9][720/940] lr: 1.0000e-02 eta: 14:03:04 time: 0.5785 data_time: 0.0361 memory: 33630 grad_norm: 3.5991 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 2.0482 loss: 2.0482 2022/10/14 20:06:24 - mmengine - INFO - Epoch(train) [9][740/940] lr: 1.0000e-02 eta: 14:02:51 time: 0.5827 data_time: 0.0410 memory: 33630 grad_norm: 3.5618 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.0155 loss: 2.0155 2022/10/14 20:06:36 - mmengine - INFO - Epoch(train) [9][760/940] lr: 1.0000e-02 eta: 14:02:38 time: 0.5835 data_time: 0.0352 memory: 33630 grad_norm: 3.5440 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.9704 loss: 1.9704 2022/10/14 20:06:47 - mmengine - INFO - Epoch(train) [9][780/940] lr: 1.0000e-02 eta: 14:02:25 time: 0.5875 data_time: 0.0389 memory: 33630 grad_norm: 3.5933 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.0571 loss: 2.0571 2022/10/14 20:06:59 - mmengine - INFO - Epoch(train) [9][800/940] lr: 1.0000e-02 eta: 14:02:12 time: 0.5817 data_time: 0.0353 memory: 33630 grad_norm: 3.6286 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.0283 loss: 2.0283 2022/10/14 20:07:11 - mmengine - INFO - Epoch(train) [9][820/940] lr: 1.0000e-02 eta: 14:01:58 time: 0.5779 data_time: 0.0317 memory: 33630 grad_norm: 3.6034 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.0587 loss: 2.0587 2022/10/14 20:07:23 - mmengine - INFO - Epoch(train) [9][840/940] lr: 1.0000e-02 eta: 14:01:47 time: 0.5943 data_time: 0.0408 memory: 33630 grad_norm: 3.5411 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.2069 loss: 2.2069 2022/10/14 20:07:34 - mmengine - INFO - Epoch(train) [9][860/940] lr: 1.0000e-02 eta: 14:01:35 time: 0.5888 data_time: 0.0396 memory: 33630 grad_norm: 3.6076 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.9567 loss: 1.9567 2022/10/14 20:07:46 - mmengine - INFO - Epoch(train) [9][880/940] lr: 1.0000e-02 eta: 14:01:22 time: 0.5830 data_time: 0.0308 memory: 33630 grad_norm: 3.6164 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1578 loss: 2.1578 2022/10/14 20:07:58 - mmengine - INFO - Epoch(train) [9][900/940] lr: 1.0000e-02 eta: 14:01:10 time: 0.5901 data_time: 0.0402 memory: 33630 grad_norm: 3.5741 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.9708 loss: 1.9708 2022/10/14 20:08:09 - mmengine - INFO - Epoch(train) [9][920/940] lr: 1.0000e-02 eta: 14:00:57 time: 0.5849 data_time: 0.0256 memory: 33630 grad_norm: 3.5216 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9417 loss: 1.9417 2022/10/14 20:08:20 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 20:08:20 - mmengine - INFO - Epoch(train) [9][940/940] lr: 1.0000e-02 eta: 14:00:36 time: 0.5457 data_time: 0.0342 memory: 33630 grad_norm: 3.6924 top1_acc: 0.2857 top5_acc: 0.7143 loss_cls: 1.9903 loss: 1.9903 2022/10/14 20:08:20 - mmengine - INFO - Saving checkpoint at 9 epochs 2022/10/14 20:08:36 - mmengine - INFO - Epoch(val) [9][20/78] eta: 0:00:41 time: 0.7148 data_time: 0.5455 memory: 5967 2022/10/14 20:08:46 - mmengine - INFO - Epoch(val) [9][40/78] eta: 0:00:19 time: 0.5199 data_time: 0.3514 memory: 5967 2022/10/14 20:08:58 - mmengine - INFO - Epoch(val) [9][60/78] eta: 0:00:11 time: 0.6148 data_time: 0.4466 memory: 5967 2022/10/14 20:09:10 - mmengine - INFO - Epoch(val) [9][78/78] acc/top1: 0.6009 acc/top5: 0.8325 acc/mean1: 0.6008 2022/10/14 20:09:10 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_7.pth is removed 2022/10/14 20:09:11 - mmengine - INFO - The best checkpoint with 0.6009 acc/top1 at 9 epoch is saved to best_acc/top1_epoch_9.pth. 2022/10/14 20:09:28 - mmengine - INFO - Epoch(train) [10][20/940] lr: 1.0000e-02 eta: 14:01:18 time: 0.8547 data_time: 0.2584 memory: 33630 grad_norm: 3.5032 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.0228 loss: 2.0228 2022/10/14 20:09:40 - mmengine - INFO - Epoch(train) [10][40/940] lr: 1.0000e-02 eta: 14:01:03 time: 0.5741 data_time: 0.0312 memory: 33630 grad_norm: 3.5564 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9673 loss: 1.9673 2022/10/14 20:09:51 - mmengine - INFO - Epoch(train) [10][60/940] lr: 1.0000e-02 eta: 14:00:48 time: 0.5736 data_time: 0.0355 memory: 33630 grad_norm: 3.6111 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.9385 loss: 1.9385 2022/10/14 20:10:03 - mmengine - INFO - Epoch(train) [10][80/940] lr: 1.0000e-02 eta: 14:00:35 time: 0.5837 data_time: 0.0396 memory: 33630 grad_norm: 3.5187 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9486 loss: 1.9486 2022/10/14 20:10:15 - mmengine - INFO - Epoch(train) [10][100/940] lr: 1.0000e-02 eta: 14:00:22 time: 0.5865 data_time: 0.0327 memory: 33630 grad_norm: 3.6020 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 1.8693 loss: 1.8693 2022/10/14 20:10:26 - mmengine - INFO - Epoch(train) [10][120/940] lr: 1.0000e-02 eta: 14:00:08 time: 0.5773 data_time: 0.0399 memory: 33630 grad_norm: 3.5936 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 1.9629 loss: 1.9629 2022/10/14 20:10:38 - mmengine - INFO - Epoch(train) [10][140/940] lr: 1.0000e-02 eta: 13:59:57 time: 0.5972 data_time: 0.0399 memory: 33630 grad_norm: 3.5265 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 2.0109 loss: 2.0109 2022/10/14 20:10:50 - mmengine - INFO - Epoch(train) [10][160/940] lr: 1.0000e-02 eta: 13:59:43 time: 0.5748 data_time: 0.0332 memory: 33630 grad_norm: 3.5708 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0126 loss: 2.0126 2022/10/14 20:11:01 - mmengine - INFO - Epoch(train) [10][180/940] lr: 1.0000e-02 eta: 13:59:30 time: 0.5835 data_time: 0.0390 memory: 33630 grad_norm: 3.6168 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9310 loss: 1.9310 2022/10/14 20:11:13 - mmengine - INFO - Epoch(train) [10][200/940] lr: 1.0000e-02 eta: 13:59:15 time: 0.5758 data_time: 0.0365 memory: 33630 grad_norm: 3.5536 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.9420 loss: 1.9420 2022/10/14 20:11:25 - mmengine - INFO - Epoch(train) [10][220/940] lr: 1.0000e-02 eta: 13:59:03 time: 0.5906 data_time: 0.0447 memory: 33630 grad_norm: 3.5732 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0431 loss: 2.0431 2022/10/14 20:11:36 - mmengine - INFO - Epoch(train) [10][240/940] lr: 1.0000e-02 eta: 13:58:49 time: 0.5773 data_time: 0.0348 memory: 33630 grad_norm: 3.5901 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.0032 loss: 2.0032 2022/10/14 20:11:48 - mmengine - INFO - Epoch(train) [10][260/940] lr: 1.0000e-02 eta: 13:58:35 time: 0.5773 data_time: 0.0348 memory: 33630 grad_norm: 3.5609 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9985 loss: 1.9985 2022/10/14 20:11:59 - mmengine - INFO - Epoch(train) [10][280/940] lr: 1.0000e-02 eta: 13:58:21 time: 0.5794 data_time: 0.0455 memory: 33630 grad_norm: 3.6316 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8574 loss: 1.8574 2022/10/14 20:12:11 - mmengine - INFO - Epoch(train) [10][300/940] lr: 1.0000e-02 eta: 13:58:08 time: 0.5846 data_time: 0.0367 memory: 33630 grad_norm: 3.6269 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.9931 loss: 1.9931 2022/10/14 20:12:23 - mmengine - INFO - Epoch(train) [10][320/940] lr: 1.0000e-02 eta: 13:57:55 time: 0.5831 data_time: 0.0334 memory: 33630 grad_norm: 3.6870 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.0064 loss: 2.0064 2022/10/14 20:12:34 - mmengine - INFO - Epoch(train) [10][340/940] lr: 1.0000e-02 eta: 13:57:41 time: 0.5792 data_time: 0.0443 memory: 33630 grad_norm: 3.6304 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9375 loss: 1.9375 2022/10/14 20:12:46 - mmengine - INFO - Epoch(train) [10][360/940] lr: 1.0000e-02 eta: 13:57:28 time: 0.5858 data_time: 0.0384 memory: 33630 grad_norm: 3.5452 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.0913 loss: 2.0913 2022/10/14 20:12:58 - mmengine - INFO - Epoch(train) [10][380/940] lr: 1.0000e-02 eta: 13:57:15 time: 0.5845 data_time: 0.0346 memory: 33630 grad_norm: 3.5627 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8583 loss: 1.8583 2022/10/14 20:13:10 - mmengine - INFO - Epoch(train) [10][400/940] lr: 1.0000e-02 eta: 13:57:04 time: 0.5929 data_time: 0.0304 memory: 33630 grad_norm: 3.6291 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.0766 loss: 2.0766 2022/10/14 20:13:21 - mmengine - INFO - Epoch(train) [10][420/940] lr: 1.0000e-02 eta: 13:56:51 time: 0.5801 data_time: 0.0483 memory: 33630 grad_norm: 3.6488 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0675 loss: 2.0675 2022/10/14 20:13:33 - mmengine - INFO - Epoch(train) [10][440/940] lr: 1.0000e-02 eta: 13:56:38 time: 0.5843 data_time: 0.0396 memory: 33630 grad_norm: 3.6160 top1_acc: 0.5312 top5_acc: 0.6250 loss_cls: 1.9044 loss: 1.9044 2022/10/14 20:13:44 - mmengine - INFO - Epoch(train) [10][460/940] lr: 1.0000e-02 eta: 13:56:24 time: 0.5803 data_time: 0.0341 memory: 33630 grad_norm: 3.5568 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9745 loss: 1.9745 2022/10/14 20:13:56 - mmengine - INFO - Epoch(train) [10][480/940] lr: 1.0000e-02 eta: 13:56:10 time: 0.5783 data_time: 0.0317 memory: 33630 grad_norm: 3.6621 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 2.0466 loss: 2.0466 2022/10/14 20:14:08 - mmengine - INFO - Epoch(train) [10][500/940] lr: 1.0000e-02 eta: 13:55:58 time: 0.5859 data_time: 0.0324 memory: 33630 grad_norm: 3.5952 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9653 loss: 1.9653 2022/10/14 20:14:19 - mmengine - INFO - Epoch(train) [10][520/940] lr: 1.0000e-02 eta: 13:55:46 time: 0.5898 data_time: 0.0303 memory: 33630 grad_norm: 3.5978 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 2.0202 loss: 2.0202 2022/10/14 20:14:31 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 20:14:31 - mmengine - INFO - Epoch(train) [10][540/940] lr: 1.0000e-02 eta: 13:55:32 time: 0.5810 data_time: 0.0396 memory: 33630 grad_norm: 3.5421 top1_acc: 0.3438 top5_acc: 0.7500 loss_cls: 2.0262 loss: 2.0262 2022/10/14 20:14:43 - mmengine - INFO - Epoch(train) [10][560/940] lr: 1.0000e-02 eta: 13:55:20 time: 0.5891 data_time: 0.0380 memory: 33630 grad_norm: 3.5871 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9493 loss: 1.9493 2022/10/14 20:14:55 - mmengine - INFO - Epoch(train) [10][580/940] lr: 1.0000e-02 eta: 13:55:07 time: 0.5835 data_time: 0.0305 memory: 33630 grad_norm: 3.5614 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.9793 loss: 1.9793 2022/10/14 20:15:06 - mmengine - INFO - Epoch(train) [10][600/940] lr: 1.0000e-02 eta: 13:54:56 time: 0.5927 data_time: 0.0376 memory: 33630 grad_norm: 3.5686 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.0815 loss: 2.0815 2022/10/14 20:15:18 - mmengine - INFO - Epoch(train) [10][620/940] lr: 1.0000e-02 eta: 13:54:43 time: 0.5829 data_time: 0.0357 memory: 33630 grad_norm: 3.6367 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 2.1479 loss: 2.1479 2022/10/14 20:15:30 - mmengine - INFO - Epoch(train) [10][640/940] lr: 1.0000e-02 eta: 13:54:31 time: 0.5865 data_time: 0.0362 memory: 33630 grad_norm: 3.6096 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.1215 loss: 2.1215 2022/10/14 20:15:42 - mmengine - INFO - Epoch(train) [10][660/940] lr: 1.0000e-02 eta: 13:54:18 time: 0.5871 data_time: 0.0340 memory: 33630 grad_norm: 3.6229 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.0099 loss: 2.0099 2022/10/14 20:15:53 - mmengine - INFO - Epoch(train) [10][680/940] lr: 1.0000e-02 eta: 13:54:07 time: 0.5919 data_time: 0.0342 memory: 33630 grad_norm: 3.5802 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 2.0403 loss: 2.0403 2022/10/14 20:16:05 - mmengine - INFO - Epoch(train) [10][700/940] lr: 1.0000e-02 eta: 13:53:53 time: 0.5810 data_time: 0.0383 memory: 33630 grad_norm: 3.5605 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.9229 loss: 1.9229 2022/10/14 20:16:17 - mmengine - INFO - Epoch(train) [10][720/940] lr: 1.0000e-02 eta: 13:53:40 time: 0.5819 data_time: 0.0301 memory: 33630 grad_norm: 3.5558 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.9635 loss: 1.9635 2022/10/14 20:16:28 - mmengine - INFO - Epoch(train) [10][740/940] lr: 1.0000e-02 eta: 13:53:28 time: 0.5869 data_time: 0.0336 memory: 33630 grad_norm: 3.6433 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.0775 loss: 2.0775 2022/10/14 20:16:40 - mmengine - INFO - Epoch(train) [10][760/940] lr: 1.0000e-02 eta: 13:53:13 time: 0.5727 data_time: 0.0334 memory: 33630 grad_norm: 3.5899 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0374 loss: 2.0374 2022/10/14 20:16:52 - mmengine - INFO - Epoch(train) [10][780/940] lr: 1.0000e-02 eta: 13:53:03 time: 0.6007 data_time: 0.0368 memory: 33630 grad_norm: 3.5786 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9366 loss: 1.9366 2022/10/14 20:17:04 - mmengine - INFO - Epoch(train) [10][800/940] lr: 1.0000e-02 eta: 13:52:50 time: 0.5832 data_time: 0.0308 memory: 33630 grad_norm: 3.6516 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1211 loss: 2.1211 2022/10/14 20:17:15 - mmengine - INFO - Epoch(train) [10][820/940] lr: 1.0000e-02 eta: 13:52:38 time: 0.5851 data_time: 0.0340 memory: 33630 grad_norm: 3.5750 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 2.0506 loss: 2.0506 2022/10/14 20:17:27 - mmengine - INFO - Epoch(train) [10][840/940] lr: 1.0000e-02 eta: 13:52:23 time: 0.5765 data_time: 0.0377 memory: 33630 grad_norm: 3.6427 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.9227 loss: 1.9227 2022/10/14 20:17:38 - mmengine - INFO - Epoch(train) [10][860/940] lr: 1.0000e-02 eta: 13:52:09 time: 0.5765 data_time: 0.0309 memory: 33630 grad_norm: 3.6662 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9720 loss: 1.9720 2022/10/14 20:17:50 - mmengine - INFO - Epoch(train) [10][880/940] lr: 1.0000e-02 eta: 13:51:58 time: 0.5944 data_time: 0.0405 memory: 33630 grad_norm: 3.5172 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.9129 loss: 1.9129 2022/10/14 20:18:02 - mmengine - INFO - Epoch(train) [10][900/940] lr: 1.0000e-02 eta: 13:51:46 time: 0.5895 data_time: 0.0371 memory: 33630 grad_norm: 3.6105 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 2.0884 loss: 2.0884 2022/10/14 20:18:14 - mmengine - INFO - Epoch(train) [10][920/940] lr: 1.0000e-02 eta: 13:51:33 time: 0.5822 data_time: 0.0424 memory: 33630 grad_norm: 3.6131 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 1.9831 loss: 1.9831 2022/10/14 20:18:24 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 20:18:24 - mmengine - INFO - Epoch(train) [10][940/940] lr: 1.0000e-02 eta: 13:51:12 time: 0.5372 data_time: 0.0439 memory: 33630 grad_norm: 3.7860 top1_acc: 0.4286 top5_acc: 1.0000 loss_cls: 2.0092 loss: 2.0092 2022/10/14 20:18:39 - mmengine - INFO - Epoch(val) [10][20/78] eta: 0:00:42 time: 0.7300 data_time: 0.5586 memory: 5967 2022/10/14 20:18:49 - mmengine - INFO - Epoch(val) [10][40/78] eta: 0:00:19 time: 0.5244 data_time: 0.3564 memory: 5967 2022/10/14 20:19:02 - mmengine - INFO - Epoch(val) [10][60/78] eta: 0:00:11 time: 0.6337 data_time: 0.4663 memory: 5967 2022/10/14 20:19:15 - mmengine - INFO - Epoch(val) [10][78/78] acc/top1: 0.5992 acc/top5: 0.8279 acc/mean1: 0.5990 2022/10/14 20:19:31 - mmengine - INFO - Epoch(train) [11][20/940] lr: 1.0000e-02 eta: 13:51:43 time: 0.8279 data_time: 0.2517 memory: 33630 grad_norm: 3.6488 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.9723 loss: 1.9723 2022/10/14 20:19:43 - mmengine - INFO - Epoch(train) [11][40/940] lr: 1.0000e-02 eta: 13:51:30 time: 0.5828 data_time: 0.0295 memory: 33630 grad_norm: 3.5922 top1_acc: 0.5000 top5_acc: 0.5625 loss_cls: 2.0397 loss: 2.0397 2022/10/14 20:19:55 - mmengine - INFO - Epoch(train) [11][60/940] lr: 1.0000e-02 eta: 13:51:20 time: 0.5972 data_time: 0.0362 memory: 33630 grad_norm: 3.5566 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.0908 loss: 2.0908 2022/10/14 20:20:06 - mmengine - INFO - Epoch(train) [11][80/940] lr: 1.0000e-02 eta: 13:51:07 time: 0.5868 data_time: 0.0316 memory: 33630 grad_norm: 3.5655 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.9628 loss: 1.9628 2022/10/14 20:20:19 - mmengine - INFO - Epoch(train) [11][100/940] lr: 1.0000e-02 eta: 13:50:58 time: 0.6030 data_time: 0.0397 memory: 33630 grad_norm: 3.5747 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.9292 loss: 1.9292 2022/10/14 20:20:30 - mmengine - INFO - Epoch(train) [11][120/940] lr: 1.0000e-02 eta: 13:50:45 time: 0.5880 data_time: 0.0324 memory: 33630 grad_norm: 3.5436 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8990 loss: 1.8990 2022/10/14 20:20:42 - mmengine - INFO - Epoch(train) [11][140/940] lr: 1.0000e-02 eta: 13:50:34 time: 0.5937 data_time: 0.0371 memory: 33630 grad_norm: 3.5934 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.9310 loss: 1.9310 2022/10/14 20:20:54 - mmengine - INFO - Epoch(train) [11][160/940] lr: 1.0000e-02 eta: 13:50:21 time: 0.5834 data_time: 0.0343 memory: 33630 grad_norm: 3.6013 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0088 loss: 2.0088 2022/10/14 20:21:06 - mmengine - INFO - Epoch(train) [11][180/940] lr: 1.0000e-02 eta: 13:50:11 time: 0.5988 data_time: 0.0393 memory: 33630 grad_norm: 3.5697 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8274 loss: 1.8274 2022/10/14 20:21:18 - mmengine - INFO - Epoch(train) [11][200/940] lr: 1.0000e-02 eta: 13:49:59 time: 0.5882 data_time: 0.0290 memory: 33630 grad_norm: 3.6399 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9276 loss: 1.9276 2022/10/14 20:21:29 - mmengine - INFO - Epoch(train) [11][220/940] lr: 1.0000e-02 eta: 13:49:46 time: 0.5849 data_time: 0.0329 memory: 33630 grad_norm: 3.6252 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9943 loss: 1.9943 2022/10/14 20:21:41 - mmengine - INFO - Epoch(train) [11][240/940] lr: 1.0000e-02 eta: 13:49:33 time: 0.5828 data_time: 0.0335 memory: 33630 grad_norm: 3.5408 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 2.0166 loss: 2.0166 2022/10/14 20:21:53 - mmengine - INFO - Epoch(train) [11][260/940] lr: 1.0000e-02 eta: 13:49:22 time: 0.5934 data_time: 0.0432 memory: 33630 grad_norm: 3.5661 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.8626 loss: 1.8626 2022/10/14 20:22:04 - mmengine - INFO - Epoch(train) [11][280/940] lr: 1.0000e-02 eta: 13:49:08 time: 0.5801 data_time: 0.0319 memory: 33630 grad_norm: 3.6347 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.9792 loss: 1.9792 2022/10/14 20:22:16 - mmengine - INFO - Epoch(train) [11][300/940] lr: 1.0000e-02 eta: 13:48:56 time: 0.5839 data_time: 0.0297 memory: 33630 grad_norm: 3.5826 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.9595 loss: 1.9595 2022/10/14 20:22:28 - mmengine - INFO - Epoch(train) [11][320/940] lr: 1.0000e-02 eta: 13:48:42 time: 0.5796 data_time: 0.0415 memory: 33630 grad_norm: 3.6152 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.8366 loss: 1.8366 2022/10/14 20:22:39 - mmengine - INFO - Epoch(train) [11][340/940] lr: 1.0000e-02 eta: 13:48:30 time: 0.5898 data_time: 0.0385 memory: 33630 grad_norm: 3.6306 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.8763 loss: 1.8763 2022/10/14 20:22:51 - mmengine - INFO - Epoch(train) [11][360/940] lr: 1.0000e-02 eta: 13:48:19 time: 0.5914 data_time: 0.0304 memory: 33630 grad_norm: 3.5623 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8760 loss: 1.8760 2022/10/14 20:23:03 - mmengine - INFO - Epoch(train) [11][380/940] lr: 1.0000e-02 eta: 13:48:05 time: 0.5798 data_time: 0.0424 memory: 33630 grad_norm: 3.6579 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.0120 loss: 2.0120 2022/10/14 20:23:14 - mmengine - INFO - Epoch(train) [11][400/940] lr: 1.0000e-02 eta: 13:47:50 time: 0.5722 data_time: 0.0322 memory: 33630 grad_norm: 3.6164 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.9552 loss: 1.9552 2022/10/14 20:23:26 - mmengine - INFO - Epoch(train) [11][420/940] lr: 1.0000e-02 eta: 13:47:40 time: 0.6002 data_time: 0.0441 memory: 33630 grad_norm: 3.6261 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.8740 loss: 1.8740 2022/10/14 20:23:38 - mmengine - INFO - Epoch(train) [11][440/940] lr: 1.0000e-02 eta: 13:47:28 time: 0.5848 data_time: 0.0423 memory: 33630 grad_norm: 3.7037 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.0110 loss: 2.0110 2022/10/14 20:23:50 - mmengine - INFO - Epoch(train) [11][460/940] lr: 1.0000e-02 eta: 13:47:16 time: 0.5895 data_time: 0.0457 memory: 33630 grad_norm: 3.5870 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8911 loss: 1.8911 2022/10/14 20:24:02 - mmengine - INFO - Epoch(train) [11][480/940] lr: 1.0000e-02 eta: 13:47:03 time: 0.5857 data_time: 0.0379 memory: 33630 grad_norm: 3.6574 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.9498 loss: 1.9498 2022/10/14 20:24:13 - mmengine - INFO - Epoch(train) [11][500/940] lr: 1.0000e-02 eta: 13:46:50 time: 0.5835 data_time: 0.0373 memory: 33630 grad_norm: 3.6234 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9991 loss: 1.9991 2022/10/14 20:24:25 - mmengine - INFO - Epoch(train) [11][520/940] lr: 1.0000e-02 eta: 13:46:38 time: 0.5892 data_time: 0.0358 memory: 33630 grad_norm: 3.6596 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.8731 loss: 1.8731 2022/10/14 20:24:37 - mmengine - INFO - Epoch(train) [11][540/940] lr: 1.0000e-02 eta: 13:46:26 time: 0.5889 data_time: 0.0374 memory: 33630 grad_norm: 3.6428 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8735 loss: 1.8735 2022/10/14 20:24:49 - mmengine - INFO - Epoch(train) [11][560/940] lr: 1.0000e-02 eta: 13:46:15 time: 0.5934 data_time: 0.0316 memory: 33630 grad_norm: 3.5976 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 1.9251 loss: 1.9251 2022/10/14 20:25:00 - mmengine - INFO - Epoch(train) [11][580/940] lr: 1.0000e-02 eta: 13:46:03 time: 0.5867 data_time: 0.0365 memory: 33630 grad_norm: 3.6318 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9468 loss: 1.9468 2022/10/14 20:25:12 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 20:25:12 - mmengine - INFO - Epoch(train) [11][600/940] lr: 1.0000e-02 eta: 13:45:48 time: 0.5724 data_time: 0.0380 memory: 33630 grad_norm: 3.5868 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8243 loss: 1.8243 2022/10/14 20:25:23 - mmengine - INFO - Epoch(train) [11][620/940] lr: 1.0000e-02 eta: 13:45:35 time: 0.5822 data_time: 0.0374 memory: 33630 grad_norm: 3.6272 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9192 loss: 1.9192 2022/10/14 20:25:35 - mmengine - INFO - Epoch(train) [11][640/940] lr: 1.0000e-02 eta: 13:45:21 time: 0.5796 data_time: 0.0317 memory: 33630 grad_norm: 3.6304 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9330 loss: 1.9330 2022/10/14 20:25:47 - mmengine - INFO - Epoch(train) [11][660/940] lr: 1.0000e-02 eta: 13:45:08 time: 0.5808 data_time: 0.0362 memory: 33630 grad_norm: 3.5990 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8806 loss: 1.8806 2022/10/14 20:25:58 - mmengine - INFO - Epoch(train) [11][680/940] lr: 1.0000e-02 eta: 13:44:55 time: 0.5841 data_time: 0.0408 memory: 33630 grad_norm: 3.6365 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9446 loss: 1.9446 2022/10/14 20:26:10 - mmengine - INFO - Epoch(train) [11][700/940] lr: 1.0000e-02 eta: 13:44:43 time: 0.5871 data_time: 0.0351 memory: 33630 grad_norm: 3.6609 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9017 loss: 1.9017 2022/10/14 20:26:22 - mmengine - INFO - Epoch(train) [11][720/940] lr: 1.0000e-02 eta: 13:44:30 time: 0.5808 data_time: 0.0303 memory: 33630 grad_norm: 3.5638 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.8286 loss: 1.8286 2022/10/14 20:26:33 - mmengine - INFO - Epoch(train) [11][740/940] lr: 1.0000e-02 eta: 13:44:16 time: 0.5787 data_time: 0.0316 memory: 33630 grad_norm: 3.6006 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.9277 loss: 1.9277 2022/10/14 20:26:45 - mmengine - INFO - Epoch(train) [11][760/940] lr: 1.0000e-02 eta: 13:44:03 time: 0.5834 data_time: 0.0346 memory: 33630 grad_norm: 3.6016 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.0081 loss: 2.0081 2022/10/14 20:26:57 - mmengine - INFO - Epoch(train) [11][780/940] lr: 1.0000e-02 eta: 13:43:53 time: 0.5971 data_time: 0.0373 memory: 33630 grad_norm: 3.5443 top1_acc: 0.3750 top5_acc: 0.5312 loss_cls: 1.9922 loss: 1.9922 2022/10/14 20:27:09 - mmengine - INFO - Epoch(train) [11][800/940] lr: 1.0000e-02 eta: 13:43:41 time: 0.5905 data_time: 0.0355 memory: 33630 grad_norm: 3.6446 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.8369 loss: 1.8369 2022/10/14 20:27:20 - mmengine - INFO - Epoch(train) [11][820/940] lr: 1.0000e-02 eta: 13:43:27 time: 0.5751 data_time: 0.0353 memory: 33630 grad_norm: 3.6114 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9632 loss: 1.9632 2022/10/14 20:27:32 - mmengine - INFO - Epoch(train) [11][840/940] lr: 1.0000e-02 eta: 13:43:14 time: 0.5806 data_time: 0.0395 memory: 33630 grad_norm: 3.6464 top1_acc: 0.4375 top5_acc: 0.9062 loss_cls: 1.9413 loss: 1.9413 2022/10/14 20:27:43 - mmengine - INFO - Epoch(train) [11][860/940] lr: 1.0000e-02 eta: 13:42:59 time: 0.5735 data_time: 0.0343 memory: 33630 grad_norm: 3.5926 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9938 loss: 1.9938 2022/10/14 20:27:55 - mmengine - INFO - Epoch(train) [11][880/940] lr: 1.0000e-02 eta: 13:42:47 time: 0.5847 data_time: 0.0389 memory: 33630 grad_norm: 3.6599 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8115 loss: 1.8115 2022/10/14 20:28:07 - mmengine - INFO - Epoch(train) [11][900/940] lr: 1.0000e-02 eta: 13:42:35 time: 0.5925 data_time: 0.0308 memory: 33630 grad_norm: 3.6187 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9307 loss: 1.9307 2022/10/14 20:28:19 - mmengine - INFO - Epoch(train) [11][920/940] lr: 1.0000e-02 eta: 13:42:23 time: 0.5882 data_time: 0.0316 memory: 33630 grad_norm: 3.6584 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.9536 loss: 1.9536 2022/10/14 20:28:29 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 20:28:29 - mmengine - INFO - Epoch(train) [11][940/940] lr: 1.0000e-02 eta: 13:42:04 time: 0.5424 data_time: 0.0332 memory: 33630 grad_norm: 3.8390 top1_acc: 0.1429 top5_acc: 0.5714 loss_cls: 1.9420 loss: 1.9420 2022/10/14 20:28:45 - mmengine - INFO - Epoch(val) [11][20/78] eta: 0:00:43 time: 0.7534 data_time: 0.5839 memory: 5967 2022/10/14 20:28:54 - mmengine - INFO - Epoch(val) [11][40/78] eta: 0:00:18 time: 0.4989 data_time: 0.3299 memory: 5967 2022/10/14 20:29:08 - mmengine - INFO - Epoch(val) [11][60/78] eta: 0:00:11 time: 0.6605 data_time: 0.4921 memory: 5967 2022/10/14 20:29:20 - mmengine - INFO - Epoch(val) [11][78/78] acc/top1: 0.6077 acc/top5: 0.8316 acc/mean1: 0.6075 2022/10/14 20:29:20 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_9.pth is removed 2022/10/14 20:29:20 - mmengine - INFO - The best checkpoint with 0.6077 acc/top1 at 11 epoch is saved to best_acc/top1_epoch_11.pth. 2022/10/14 20:29:37 - mmengine - INFO - Epoch(train) [12][20/940] lr: 1.0000e-02 eta: 13:42:33 time: 0.8442 data_time: 0.2935 memory: 33630 grad_norm: 3.5893 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.9678 loss: 1.9678 2022/10/14 20:29:49 - mmengine - INFO - Epoch(train) [12][40/940] lr: 1.0000e-02 eta: 13:42:19 time: 0.5734 data_time: 0.0327 memory: 33630 grad_norm: 3.5972 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.9600 loss: 1.9600 2022/10/14 20:30:01 - mmengine - INFO - Epoch(train) [12][60/940] lr: 1.0000e-02 eta: 13:42:12 time: 0.6206 data_time: 0.0725 memory: 33630 grad_norm: 3.5917 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8624 loss: 1.8624 2022/10/14 20:30:13 - mmengine - INFO - Epoch(train) [12][80/940] lr: 1.0000e-02 eta: 13:41:58 time: 0.5778 data_time: 0.0323 memory: 33630 grad_norm: 3.6406 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8277 loss: 1.8277 2022/10/14 20:30:24 - mmengine - INFO - Epoch(train) [12][100/940] lr: 1.0000e-02 eta: 13:41:45 time: 0.5827 data_time: 0.0348 memory: 33630 grad_norm: 3.6446 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8943 loss: 1.8943 2022/10/14 20:30:36 - mmengine - INFO - Epoch(train) [12][120/940] lr: 1.0000e-02 eta: 13:41:32 time: 0.5848 data_time: 0.0349 memory: 33630 grad_norm: 3.5613 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8291 loss: 1.8291 2022/10/14 20:30:48 - mmengine - INFO - Epoch(train) [12][140/940] lr: 1.0000e-02 eta: 13:41:20 time: 0.5885 data_time: 0.0424 memory: 33630 grad_norm: 3.6338 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.7420 loss: 1.7420 2022/10/14 20:31:00 - mmengine - INFO - Epoch(train) [12][160/940] lr: 1.0000e-02 eta: 13:41:09 time: 0.5931 data_time: 0.0463 memory: 33630 grad_norm: 3.5599 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.8810 loss: 1.8810 2022/10/14 20:31:11 - mmengine - INFO - Epoch(train) [12][180/940] lr: 1.0000e-02 eta: 13:40:55 time: 0.5781 data_time: 0.0336 memory: 33630 grad_norm: 3.6001 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.0368 loss: 2.0368 2022/10/14 20:31:23 - mmengine - INFO - Epoch(train) [12][200/940] lr: 1.0000e-02 eta: 13:40:44 time: 0.5902 data_time: 0.0339 memory: 33630 grad_norm: 3.6185 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.9615 loss: 1.9615 2022/10/14 20:31:35 - mmengine - INFO - Epoch(train) [12][220/940] lr: 1.0000e-02 eta: 13:40:30 time: 0.5789 data_time: 0.0352 memory: 33630 grad_norm: 3.5999 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9371 loss: 1.9371 2022/10/14 20:31:47 - mmengine - INFO - Epoch(train) [12][240/940] lr: 1.0000e-02 eta: 13:40:27 time: 0.6433 data_time: 0.0325 memory: 33630 grad_norm: 3.6705 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9213 loss: 1.9213 2022/10/14 20:31:59 - mmengine - INFO - Epoch(train) [12][260/940] lr: 1.0000e-02 eta: 13:40:15 time: 0.5925 data_time: 0.0360 memory: 33630 grad_norm: 3.6277 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.8844 loss: 1.8844 2022/10/14 20:32:11 - mmengine - INFO - Epoch(train) [12][280/940] lr: 1.0000e-02 eta: 13:40:02 time: 0.5824 data_time: 0.0391 memory: 33630 grad_norm: 3.6610 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9407 loss: 1.9407 2022/10/14 20:32:22 - mmengine - INFO - Epoch(train) [12][300/940] lr: 1.0000e-02 eta: 13:39:49 time: 0.5795 data_time: 0.0343 memory: 33630 grad_norm: 3.6656 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.8381 loss: 1.8381 2022/10/14 20:32:34 - mmengine - INFO - Epoch(train) [12][320/940] lr: 1.0000e-02 eta: 13:39:36 time: 0.5846 data_time: 0.0341 memory: 33630 grad_norm: 3.6750 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.9726 loss: 1.9726 2022/10/14 20:32:46 - mmengine - INFO - Epoch(train) [12][340/940] lr: 1.0000e-02 eta: 13:39:22 time: 0.5775 data_time: 0.0319 memory: 33630 grad_norm: 3.6946 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8481 loss: 1.8481 2022/10/14 20:32:57 - mmengine - INFO - Epoch(train) [12][360/940] lr: 1.0000e-02 eta: 13:39:10 time: 0.5842 data_time: 0.0448 memory: 33630 grad_norm: 3.6916 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.9572 loss: 1.9572 2022/10/14 20:33:09 - mmengine - INFO - Epoch(train) [12][380/940] lr: 1.0000e-02 eta: 13:38:56 time: 0.5761 data_time: 0.0319 memory: 33630 grad_norm: 3.6043 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.0160 loss: 2.0160 2022/10/14 20:33:21 - mmengine - INFO - Epoch(train) [12][400/940] lr: 1.0000e-02 eta: 13:38:44 time: 0.5932 data_time: 0.0362 memory: 33630 grad_norm: 3.6650 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.9606 loss: 1.9606 2022/10/14 20:33:32 - mmengine - INFO - Epoch(train) [12][420/940] lr: 1.0000e-02 eta: 13:38:31 time: 0.5829 data_time: 0.0389 memory: 33630 grad_norm: 3.5944 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.9842 loss: 1.9842 2022/10/14 20:33:44 - mmengine - INFO - Epoch(train) [12][440/940] lr: 1.0000e-02 eta: 13:38:17 time: 0.5720 data_time: 0.0313 memory: 33630 grad_norm: 3.6283 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0332 loss: 2.0332 2022/10/14 20:33:55 - mmengine - INFO - Epoch(train) [12][460/940] lr: 1.0000e-02 eta: 13:38:02 time: 0.5736 data_time: 0.0308 memory: 33630 grad_norm: 3.6111 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8886 loss: 1.8886 2022/10/14 20:34:07 - mmengine - INFO - Epoch(train) [12][480/940] lr: 1.0000e-02 eta: 13:37:51 time: 0.5894 data_time: 0.0409 memory: 33630 grad_norm: 3.5811 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.8505 loss: 1.8505 2022/10/14 20:34:19 - mmengine - INFO - Epoch(train) [12][500/940] lr: 1.0000e-02 eta: 13:37:38 time: 0.5852 data_time: 0.0306 memory: 33630 grad_norm: 3.6645 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9316 loss: 1.9316 2022/10/14 20:34:31 - mmengine - INFO - Epoch(train) [12][520/940] lr: 1.0000e-02 eta: 13:37:26 time: 0.5894 data_time: 0.0334 memory: 33630 grad_norm: 3.6513 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 2.1007 loss: 2.1007 2022/10/14 20:34:42 - mmengine - INFO - Epoch(train) [12][540/940] lr: 1.0000e-02 eta: 13:37:14 time: 0.5896 data_time: 0.0356 memory: 33630 grad_norm: 3.6383 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.9235 loss: 1.9235 2022/10/14 20:34:54 - mmengine - INFO - Epoch(train) [12][560/940] lr: 1.0000e-02 eta: 13:37:02 time: 0.5848 data_time: 0.0409 memory: 33630 grad_norm: 3.6959 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8978 loss: 1.8978 2022/10/14 20:35:06 - mmengine - INFO - Epoch(train) [12][580/940] lr: 1.0000e-02 eta: 13:36:49 time: 0.5826 data_time: 0.0417 memory: 33630 grad_norm: 3.6575 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.0011 loss: 2.0011 2022/10/14 20:35:17 - mmengine - INFO - Epoch(train) [12][600/940] lr: 1.0000e-02 eta: 13:36:35 time: 0.5767 data_time: 0.0319 memory: 33630 grad_norm: 3.6452 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.9182 loss: 1.9182 2022/10/14 20:35:29 - mmengine - INFO - Epoch(train) [12][620/940] lr: 1.0000e-02 eta: 13:36:22 time: 0.5800 data_time: 0.0356 memory: 33630 grad_norm: 3.7213 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9832 loss: 1.9832 2022/10/14 20:35:41 - mmengine - INFO - Epoch(train) [12][640/940] lr: 1.0000e-02 eta: 13:36:09 time: 0.5816 data_time: 0.0408 memory: 33630 grad_norm: 3.5837 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8083 loss: 1.8083 2022/10/14 20:35:52 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 20:35:52 - mmengine - INFO - Epoch(train) [12][660/940] lr: 1.0000e-02 eta: 13:35:54 time: 0.5727 data_time: 0.0414 memory: 33630 grad_norm: 3.6371 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0310 loss: 2.0310 2022/10/14 20:36:04 - mmengine - INFO - Epoch(train) [12][680/940] lr: 1.0000e-02 eta: 13:35:44 time: 0.5979 data_time: 0.0405 memory: 33630 grad_norm: 3.6285 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8595 loss: 1.8595 2022/10/14 20:36:16 - mmengine - INFO - Epoch(train) [12][700/940] lr: 1.0000e-02 eta: 13:35:31 time: 0.5857 data_time: 0.0389 memory: 33630 grad_norm: 3.6831 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9672 loss: 1.9672 2022/10/14 20:36:27 - mmengine - INFO - Epoch(train) [12][720/940] lr: 1.0000e-02 eta: 13:35:18 time: 0.5807 data_time: 0.0370 memory: 33630 grad_norm: 3.7135 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.9633 loss: 1.9633 2022/10/14 20:36:39 - mmengine - INFO - Epoch(train) [12][740/940] lr: 1.0000e-02 eta: 13:35:06 time: 0.5871 data_time: 0.0342 memory: 33630 grad_norm: 3.6466 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 2.0013 loss: 2.0013 2022/10/14 20:36:50 - mmengine - INFO - Epoch(train) [12][760/940] lr: 1.0000e-02 eta: 13:34:51 time: 0.5686 data_time: 0.0321 memory: 33630 grad_norm: 3.6181 top1_acc: 0.5312 top5_acc: 0.6250 loss_cls: 1.9640 loss: 1.9640 2022/10/14 20:37:02 - mmengine - INFO - Epoch(train) [12][780/940] lr: 1.0000e-02 eta: 13:34:41 time: 0.6026 data_time: 0.0417 memory: 33630 grad_norm: 3.7267 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.8756 loss: 1.8756 2022/10/14 20:37:14 - mmengine - INFO - Epoch(train) [12][800/940] lr: 1.0000e-02 eta: 13:34:28 time: 0.5783 data_time: 0.0353 memory: 33630 grad_norm: 3.5678 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7843 loss: 1.7843 2022/10/14 20:37:26 - mmengine - INFO - Epoch(train) [12][820/940] lr: 1.0000e-02 eta: 13:34:16 time: 0.5920 data_time: 0.0424 memory: 33630 grad_norm: 3.6577 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.9334 loss: 1.9334 2022/10/14 20:37:38 - mmengine - INFO - Epoch(train) [12][840/940] lr: 1.0000e-02 eta: 13:34:06 time: 0.6001 data_time: 0.0314 memory: 33630 grad_norm: 3.6375 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.9374 loss: 1.9374 2022/10/14 20:37:49 - mmengine - INFO - Epoch(train) [12][860/940] lr: 1.0000e-02 eta: 13:33:52 time: 0.5780 data_time: 0.0306 memory: 33630 grad_norm: 3.6167 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8608 loss: 1.8608 2022/10/14 20:38:01 - mmengine - INFO - Epoch(train) [12][880/940] lr: 1.0000e-02 eta: 13:33:39 time: 0.5817 data_time: 0.0388 memory: 33630 grad_norm: 3.6368 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.7799 loss: 1.7799 2022/10/14 20:38:13 - mmengine - INFO - Epoch(train) [12][900/940] lr: 1.0000e-02 eta: 13:33:26 time: 0.5780 data_time: 0.0370 memory: 33630 grad_norm: 3.6258 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9420 loss: 1.9420 2022/10/14 20:38:24 - mmengine - INFO - Epoch(train) [12][920/940] lr: 1.0000e-02 eta: 13:33:12 time: 0.5759 data_time: 0.0312 memory: 33630 grad_norm: 3.6422 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.9364 loss: 1.9364 2022/10/14 20:38:35 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 20:38:35 - mmengine - INFO - Epoch(train) [12][940/940] lr: 1.0000e-02 eta: 13:32:55 time: 0.5569 data_time: 0.0295 memory: 33630 grad_norm: 3.8128 top1_acc: 0.1429 top5_acc: 0.7143 loss_cls: 1.9876 loss: 1.9876 2022/10/14 20:38:35 - mmengine - INFO - Saving checkpoint at 12 epochs 2022/10/14 20:38:52 - mmengine - INFO - Epoch(val) [12][20/78] eta: 0:00:44 time: 0.7654 data_time: 0.5931 memory: 5967 2022/10/14 20:39:01 - mmengine - INFO - Epoch(val) [12][40/78] eta: 0:00:18 time: 0.4858 data_time: 0.3167 memory: 5967 2022/10/14 20:39:15 - mmengine - INFO - Epoch(val) [12][60/78] eta: 0:00:12 time: 0.6726 data_time: 0.5042 memory: 5967 2022/10/14 20:39:25 - mmengine - INFO - Epoch(val) [12][78/78] acc/top1: 0.6179 acc/top5: 0.8407 acc/mean1: 0.6178 2022/10/14 20:39:25 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_11.pth is removed 2022/10/14 20:39:26 - mmengine - INFO - The best checkpoint with 0.6179 acc/top1 at 12 epoch is saved to best_acc/top1_epoch_12.pth. 2022/10/14 20:39:42 - mmengine - INFO - Epoch(train) [13][20/940] lr: 1.0000e-02 eta: 13:33:15 time: 0.8039 data_time: 0.2346 memory: 33630 grad_norm: 3.5557 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8031 loss: 1.8031 2022/10/14 20:39:54 - mmengine - INFO - Epoch(train) [13][40/940] lr: 1.0000e-02 eta: 13:33:02 time: 0.5825 data_time: 0.0344 memory: 33630 grad_norm: 3.6514 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8387 loss: 1.8387 2022/10/14 20:40:06 - mmengine - INFO - Epoch(train) [13][60/940] lr: 1.0000e-02 eta: 13:32:53 time: 0.6053 data_time: 0.0619 memory: 33630 grad_norm: 3.6453 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8585 loss: 1.8585 2022/10/14 20:40:17 - mmengine - INFO - Epoch(train) [13][80/940] lr: 1.0000e-02 eta: 13:32:39 time: 0.5774 data_time: 0.0322 memory: 33630 grad_norm: 3.5804 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8142 loss: 1.8142 2022/10/14 20:40:30 - mmengine - INFO - Epoch(train) [13][100/940] lr: 1.0000e-02 eta: 13:32:31 time: 0.6149 data_time: 0.0396 memory: 33630 grad_norm: 3.6207 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.9662 loss: 1.9662 2022/10/14 20:40:41 - mmengine - INFO - Epoch(train) [13][120/940] lr: 1.0000e-02 eta: 13:32:18 time: 0.5849 data_time: 0.0309 memory: 33630 grad_norm: 3.6719 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7600 loss: 1.7600 2022/10/14 20:40:53 - mmengine - INFO - Epoch(train) [13][140/940] lr: 1.0000e-02 eta: 13:32:07 time: 0.5919 data_time: 0.0426 memory: 33630 grad_norm: 3.6508 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8090 loss: 1.8090 2022/10/14 20:41:05 - mmengine - INFO - Epoch(train) [13][160/940] lr: 1.0000e-02 eta: 13:31:54 time: 0.5823 data_time: 0.0332 memory: 33630 grad_norm: 3.6019 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.6949 loss: 1.6949 2022/10/14 20:41:16 - mmengine - INFO - Epoch(train) [13][180/940] lr: 1.0000e-02 eta: 13:31:38 time: 0.5662 data_time: 0.0316 memory: 33630 grad_norm: 3.6996 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8462 loss: 1.8462 2022/10/14 20:41:28 - mmengine - INFO - Epoch(train) [13][200/940] lr: 1.0000e-02 eta: 13:31:26 time: 0.5826 data_time: 0.0411 memory: 33630 grad_norm: 3.6202 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9826 loss: 1.9826 2022/10/14 20:41:40 - mmengine - INFO - Epoch(train) [13][220/940] lr: 1.0000e-02 eta: 13:31:15 time: 0.5973 data_time: 0.0329 memory: 33630 grad_norm: 3.6287 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.8759 loss: 1.8759 2022/10/14 20:41:52 - mmengine - INFO - Epoch(train) [13][240/940] lr: 1.0000e-02 eta: 13:31:03 time: 0.5913 data_time: 0.0304 memory: 33630 grad_norm: 3.6906 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 2.0060 loss: 2.0060 2022/10/14 20:42:03 - mmengine - INFO - Epoch(train) [13][260/940] lr: 1.0000e-02 eta: 13:30:51 time: 0.5876 data_time: 0.0404 memory: 33630 grad_norm: 3.5981 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.9438 loss: 1.9438 2022/10/14 20:42:15 - mmengine - INFO - Epoch(train) [13][280/940] lr: 1.0000e-02 eta: 13:30:38 time: 0.5831 data_time: 0.0353 memory: 33630 grad_norm: 3.6497 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.8478 loss: 1.8478 2022/10/14 20:42:26 - mmengine - INFO - Epoch(train) [13][300/940] lr: 1.0000e-02 eta: 13:30:24 time: 0.5746 data_time: 0.0372 memory: 33630 grad_norm: 3.5762 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8736 loss: 1.8736 2022/10/14 20:42:38 - mmengine - INFO - Epoch(train) [13][320/940] lr: 1.0000e-02 eta: 13:30:11 time: 0.5791 data_time: 0.0374 memory: 33630 grad_norm: 3.7021 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.9754 loss: 1.9754 2022/10/14 20:42:50 - mmengine - INFO - Epoch(train) [13][340/940] lr: 1.0000e-02 eta: 13:29:58 time: 0.5798 data_time: 0.0381 memory: 33630 grad_norm: 3.6555 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.0481 loss: 2.0481 2022/10/14 20:43:01 - mmengine - INFO - Epoch(train) [13][360/940] lr: 1.0000e-02 eta: 13:29:44 time: 0.5772 data_time: 0.0317 memory: 33630 grad_norm: 3.6497 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9401 loss: 1.9401 2022/10/14 20:43:13 - mmengine - INFO - Epoch(train) [13][380/940] lr: 1.0000e-02 eta: 13:29:33 time: 0.5968 data_time: 0.0318 memory: 33630 grad_norm: 3.7441 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.8487 loss: 1.8487 2022/10/14 20:43:25 - mmengine - INFO - Epoch(train) [13][400/940] lr: 1.0000e-02 eta: 13:29:20 time: 0.5786 data_time: 0.0466 memory: 33630 grad_norm: 3.6212 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.9529 loss: 1.9529 2022/10/14 20:43:36 - mmengine - INFO - Epoch(train) [13][420/940] lr: 1.0000e-02 eta: 13:29:07 time: 0.5856 data_time: 0.0308 memory: 33630 grad_norm: 3.6897 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.8915 loss: 1.8915 2022/10/14 20:43:48 - mmengine - INFO - Epoch(train) [13][440/940] lr: 1.0000e-02 eta: 13:28:55 time: 0.5863 data_time: 0.0370 memory: 33630 grad_norm: 3.7281 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9133 loss: 1.9133 2022/10/14 20:44:00 - mmengine - INFO - Epoch(train) [13][460/940] lr: 1.0000e-02 eta: 13:28:43 time: 0.5845 data_time: 0.0362 memory: 33630 grad_norm: 3.6229 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.6826 loss: 1.6826 2022/10/14 20:44:11 - mmengine - INFO - Epoch(train) [13][480/940] lr: 1.0000e-02 eta: 13:28:30 time: 0.5809 data_time: 0.0335 memory: 33630 grad_norm: 3.6809 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8685 loss: 1.8685 2022/10/14 20:44:23 - mmengine - INFO - Epoch(train) [13][500/940] lr: 1.0000e-02 eta: 13:28:16 time: 0.5782 data_time: 0.0304 memory: 33630 grad_norm: 3.6012 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.8751 loss: 1.8751 2022/10/14 20:44:35 - mmengine - INFO - Epoch(train) [13][520/940] lr: 1.0000e-02 eta: 13:28:04 time: 0.5843 data_time: 0.0407 memory: 33630 grad_norm: 3.6203 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9024 loss: 1.9024 2022/10/14 20:44:47 - mmengine - INFO - Epoch(train) [13][540/940] lr: 1.0000e-02 eta: 13:27:52 time: 0.5918 data_time: 0.0371 memory: 33630 grad_norm: 3.6465 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9392 loss: 1.9392 2022/10/14 20:44:58 - mmengine - INFO - Epoch(train) [13][560/940] lr: 1.0000e-02 eta: 13:27:40 time: 0.5884 data_time: 0.0434 memory: 33630 grad_norm: 3.6511 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8067 loss: 1.8067 2022/10/14 20:45:10 - mmengine - INFO - Epoch(train) [13][580/940] lr: 1.0000e-02 eta: 13:27:26 time: 0.5733 data_time: 0.0397 memory: 33630 grad_norm: 3.6583 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.9666 loss: 1.9666 2022/10/14 20:45:22 - mmengine - INFO - Epoch(train) [13][600/940] lr: 1.0000e-02 eta: 13:27:15 time: 0.5953 data_time: 0.0484 memory: 33630 grad_norm: 3.6954 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.8769 loss: 1.8769 2022/10/14 20:45:33 - mmengine - INFO - Epoch(train) [13][620/940] lr: 1.0000e-02 eta: 13:27:01 time: 0.5712 data_time: 0.0343 memory: 33630 grad_norm: 3.6870 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8831 loss: 1.8831 2022/10/14 20:45:45 - mmengine - INFO - Epoch(train) [13][640/940] lr: 1.0000e-02 eta: 13:26:48 time: 0.5850 data_time: 0.0412 memory: 33630 grad_norm: 3.7031 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.9052 loss: 1.9052 2022/10/14 20:45:56 - mmengine - INFO - Epoch(train) [13][660/940] lr: 1.0000e-02 eta: 13:26:35 time: 0.5798 data_time: 0.0318 memory: 33630 grad_norm: 3.6399 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.9038 loss: 1.9038 2022/10/14 20:46:08 - mmengine - INFO - Epoch(train) [13][680/940] lr: 1.0000e-02 eta: 13:26:22 time: 0.5817 data_time: 0.0413 memory: 33630 grad_norm: 3.6397 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7617 loss: 1.7617 2022/10/14 20:46:20 - mmengine - INFO - Epoch(train) [13][700/940] lr: 1.0000e-02 eta: 13:26:09 time: 0.5810 data_time: 0.0371 memory: 33630 grad_norm: 3.6900 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 2.0018 loss: 2.0018 2022/10/14 20:46:31 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 20:46:31 - mmengine - INFO - Epoch(train) [13][720/940] lr: 1.0000e-02 eta: 13:25:55 time: 0.5742 data_time: 0.0424 memory: 33630 grad_norm: 3.6704 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8940 loss: 1.8940 2022/10/14 20:46:43 - mmengine - INFO - Epoch(train) [13][740/940] lr: 1.0000e-02 eta: 13:25:41 time: 0.5736 data_time: 0.0390 memory: 33630 grad_norm: 3.6531 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9327 loss: 1.9327 2022/10/14 20:46:54 - mmengine - INFO - Epoch(train) [13][760/940] lr: 1.0000e-02 eta: 13:25:28 time: 0.5797 data_time: 0.0290 memory: 33630 grad_norm: 3.6920 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8893 loss: 1.8893 2022/10/14 20:47:06 - mmengine - INFO - Epoch(train) [13][780/940] lr: 1.0000e-02 eta: 13:25:14 time: 0.5714 data_time: 0.0307 memory: 33630 grad_norm: 3.6754 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0510 loss: 2.0510 2022/10/14 20:47:17 - mmengine - INFO - Epoch(train) [13][800/940] lr: 1.0000e-02 eta: 13:24:59 time: 0.5690 data_time: 0.0367 memory: 33630 grad_norm: 3.6977 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9139 loss: 1.9139 2022/10/14 20:47:29 - mmengine - INFO - Epoch(train) [13][820/940] lr: 1.0000e-02 eta: 13:24:48 time: 0.5969 data_time: 0.0339 memory: 33630 grad_norm: 3.5867 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.9093 loss: 1.9093 2022/10/14 20:47:41 - mmengine - INFO - Epoch(train) [13][840/940] lr: 1.0000e-02 eta: 13:24:35 time: 0.5790 data_time: 0.0324 memory: 33630 grad_norm: 3.6311 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.8251 loss: 1.8251 2022/10/14 20:47:52 - mmengine - INFO - Epoch(train) [13][860/940] lr: 1.0000e-02 eta: 13:24:22 time: 0.5816 data_time: 0.0289 memory: 33630 grad_norm: 3.6862 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9947 loss: 1.9947 2022/10/14 20:48:04 - mmengine - INFO - Epoch(train) [13][880/940] lr: 1.0000e-02 eta: 13:24:08 time: 0.5680 data_time: 0.0322 memory: 33630 grad_norm: 3.7842 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.0656 loss: 2.0656 2022/10/14 20:48:15 - mmengine - INFO - Epoch(train) [13][900/940] lr: 1.0000e-02 eta: 13:23:56 time: 0.5930 data_time: 0.0356 memory: 33630 grad_norm: 3.7408 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8246 loss: 1.8246 2022/10/14 20:48:27 - mmengine - INFO - Epoch(train) [13][920/940] lr: 1.0000e-02 eta: 13:23:43 time: 0.5788 data_time: 0.0311 memory: 33630 grad_norm: 3.6825 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.9960 loss: 1.9960 2022/10/14 20:48:38 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 20:48:38 - mmengine - INFO - Epoch(train) [13][940/940] lr: 1.0000e-02 eta: 13:23:25 time: 0.5435 data_time: 0.0278 memory: 33630 grad_norm: 3.8762 top1_acc: 0.2857 top5_acc: 0.7143 loss_cls: 1.9049 loss: 1.9049 2022/10/14 20:48:52 - mmengine - INFO - Epoch(val) [13][20/78] eta: 0:00:40 time: 0.7022 data_time: 0.5310 memory: 5967 2022/10/14 20:49:02 - mmengine - INFO - Epoch(val) [13][40/78] eta: 0:00:19 time: 0.5217 data_time: 0.3518 memory: 5967 2022/10/14 20:49:14 - mmengine - INFO - Epoch(val) [13][60/78] eta: 0:00:10 time: 0.6030 data_time: 0.4342 memory: 5967 2022/10/14 20:49:28 - mmengine - INFO - Epoch(val) [13][78/78] acc/top1: 0.6181 acc/top5: 0.8399 acc/mean1: 0.6178 2022/10/14 20:49:28 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_12.pth is removed 2022/10/14 20:49:28 - mmengine - INFO - The best checkpoint with 0.6181 acc/top1 at 13 epoch is saved to best_acc/top1_epoch_13.pth. 2022/10/14 20:49:44 - mmengine - INFO - Epoch(train) [14][20/940] lr: 1.0000e-02 eta: 13:23:43 time: 0.8151 data_time: 0.2686 memory: 33630 grad_norm: 3.6448 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.9110 loss: 1.9110 2022/10/14 20:49:56 - mmengine - INFO - Epoch(train) [14][40/940] lr: 1.0000e-02 eta: 13:23:31 time: 0.5826 data_time: 0.0308 memory: 33630 grad_norm: 3.6937 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8307 loss: 1.8307 2022/10/14 20:50:09 - mmengine - INFO - Epoch(train) [14][60/940] lr: 1.0000e-02 eta: 13:23:24 time: 0.6289 data_time: 0.0348 memory: 33630 grad_norm: 3.6761 top1_acc: 0.6875 top5_acc: 0.7188 loss_cls: 1.8304 loss: 1.8304 2022/10/14 20:50:20 - mmengine - INFO - Epoch(train) [14][80/940] lr: 1.0000e-02 eta: 13:23:13 time: 0.5938 data_time: 0.0309 memory: 33630 grad_norm: 3.6386 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9136 loss: 1.9136 2022/10/14 20:50:32 - mmengine - INFO - Epoch(train) [14][100/940] lr: 1.0000e-02 eta: 13:23:01 time: 0.5866 data_time: 0.0330 memory: 33630 grad_norm: 3.7162 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 1.9207 loss: 1.9207 2022/10/14 20:50:44 - mmengine - INFO - Epoch(train) [14][120/940] lr: 1.0000e-02 eta: 13:22:48 time: 0.5820 data_time: 0.0385 memory: 33630 grad_norm: 3.6813 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8713 loss: 1.8713 2022/10/14 20:50:56 - mmengine - INFO - Epoch(train) [14][140/940] lr: 1.0000e-02 eta: 13:22:35 time: 0.5843 data_time: 0.0318 memory: 33630 grad_norm: 3.6890 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.8385 loss: 1.8385 2022/10/14 20:51:07 - mmengine - INFO - Epoch(train) [14][160/940] lr: 1.0000e-02 eta: 13:22:23 time: 0.5892 data_time: 0.0480 memory: 33630 grad_norm: 3.6517 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.8805 loss: 1.8805 2022/10/14 20:51:19 - mmengine - INFO - Epoch(train) [14][180/940] lr: 1.0000e-02 eta: 13:22:11 time: 0.5847 data_time: 0.0335 memory: 33630 grad_norm: 3.6177 top1_acc: 0.3750 top5_acc: 0.8438 loss_cls: 1.9246 loss: 1.9246 2022/10/14 20:51:31 - mmengine - INFO - Epoch(train) [14][200/940] lr: 1.0000e-02 eta: 13:21:59 time: 0.5873 data_time: 0.0377 memory: 33630 grad_norm: 3.7191 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9063 loss: 1.9063 2022/10/14 20:51:43 - mmengine - INFO - Epoch(train) [14][220/940] lr: 1.0000e-02 eta: 13:21:47 time: 0.5939 data_time: 0.0417 memory: 33630 grad_norm: 3.7041 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9974 loss: 1.9974 2022/10/14 20:51:54 - mmengine - INFO - Epoch(train) [14][240/940] lr: 1.0000e-02 eta: 13:21:35 time: 0.5869 data_time: 0.0502 memory: 33630 grad_norm: 3.6321 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.9739 loss: 1.9739 2022/10/14 20:52:06 - mmengine - INFO - Epoch(train) [14][260/940] lr: 1.0000e-02 eta: 13:21:21 time: 0.5751 data_time: 0.0402 memory: 33630 grad_norm: 3.6584 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8407 loss: 1.8407 2022/10/14 20:52:17 - mmengine - INFO - Epoch(train) [14][280/940] lr: 1.0000e-02 eta: 13:21:09 time: 0.5809 data_time: 0.0331 memory: 33630 grad_norm: 3.6637 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.8282 loss: 1.8282 2022/10/14 20:52:30 - mmengine - INFO - Epoch(train) [14][300/940] lr: 1.0000e-02 eta: 13:20:58 time: 0.6011 data_time: 0.0323 memory: 33630 grad_norm: 3.7357 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.8750 loss: 1.8750 2022/10/14 20:52:41 - mmengine - INFO - Epoch(train) [14][320/940] lr: 1.0000e-02 eta: 13:20:46 time: 0.5874 data_time: 0.0347 memory: 33630 grad_norm: 3.7425 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.9230 loss: 1.9230 2022/10/14 20:52:53 - mmengine - INFO - Epoch(train) [14][340/940] lr: 1.0000e-02 eta: 13:20:33 time: 0.5778 data_time: 0.0394 memory: 33630 grad_norm: 3.6638 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8033 loss: 1.8033 2022/10/14 20:53:04 - mmengine - INFO - Epoch(train) [14][360/940] lr: 1.0000e-02 eta: 13:20:20 time: 0.5836 data_time: 0.0327 memory: 33630 grad_norm: 3.7139 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.9227 loss: 1.9227 2022/10/14 20:53:16 - mmengine - INFO - Epoch(train) [14][380/940] lr: 1.0000e-02 eta: 13:20:08 time: 0.5839 data_time: 0.0343 memory: 33630 grad_norm: 3.7577 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8852 loss: 1.8852 2022/10/14 20:53:28 - mmengine - INFO - Epoch(train) [14][400/940] lr: 1.0000e-02 eta: 13:19:55 time: 0.5844 data_time: 0.0361 memory: 33630 grad_norm: 3.7489 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0182 loss: 2.0182 2022/10/14 20:53:40 - mmengine - INFO - Epoch(train) [14][420/940] lr: 1.0000e-02 eta: 13:19:43 time: 0.5893 data_time: 0.0426 memory: 33630 grad_norm: 3.7063 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8221 loss: 1.8221 2022/10/14 20:53:51 - mmengine - INFO - Epoch(train) [14][440/940] lr: 1.0000e-02 eta: 13:19:29 time: 0.5708 data_time: 0.0314 memory: 33630 grad_norm: 3.6667 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9343 loss: 1.9343 2022/10/14 20:54:03 - mmengine - INFO - Epoch(train) [14][460/940] lr: 1.0000e-02 eta: 13:19:18 time: 0.5970 data_time: 0.0366 memory: 33630 grad_norm: 3.7124 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7813 loss: 1.7813 2022/10/14 20:54:15 - mmengine - INFO - Epoch(train) [14][480/940] lr: 1.0000e-02 eta: 13:19:05 time: 0.5833 data_time: 0.0400 memory: 33630 grad_norm: 3.7328 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8693 loss: 1.8693 2022/10/14 20:54:27 - mmengine - INFO - Epoch(train) [14][500/940] lr: 1.0000e-02 eta: 13:18:54 time: 0.5919 data_time: 0.0369 memory: 33630 grad_norm: 3.6490 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.8421 loss: 1.8421 2022/10/14 20:54:38 - mmengine - INFO - Epoch(train) [14][520/940] lr: 1.0000e-02 eta: 13:18:41 time: 0.5799 data_time: 0.0360 memory: 33630 grad_norm: 3.6402 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.9919 loss: 1.9919 2022/10/14 20:54:50 - mmengine - INFO - Epoch(train) [14][540/940] lr: 1.0000e-02 eta: 13:18:28 time: 0.5788 data_time: 0.0336 memory: 33630 grad_norm: 3.6748 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9343 loss: 1.9343 2022/10/14 20:55:02 - mmengine - INFO - Epoch(train) [14][560/940] lr: 1.0000e-02 eta: 13:18:17 time: 0.5944 data_time: 0.0391 memory: 33630 grad_norm: 3.6997 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 1.9516 loss: 1.9516 2022/10/14 20:55:13 - mmengine - INFO - Epoch(train) [14][580/940] lr: 1.0000e-02 eta: 13:18:05 time: 0.5906 data_time: 0.0363 memory: 33630 grad_norm: 3.6488 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8385 loss: 1.8385 2022/10/14 20:55:25 - mmengine - INFO - Epoch(train) [14][600/940] lr: 1.0000e-02 eta: 13:17:53 time: 0.5903 data_time: 0.0510 memory: 33630 grad_norm: 3.7415 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9032 loss: 1.9032 2022/10/14 20:55:37 - mmengine - INFO - Epoch(train) [14][620/940] lr: 1.0000e-02 eta: 13:17:41 time: 0.5911 data_time: 0.0422 memory: 33630 grad_norm: 3.6562 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9286 loss: 1.9286 2022/10/14 20:55:49 - mmengine - INFO - Epoch(train) [14][640/940] lr: 1.0000e-02 eta: 13:17:28 time: 0.5766 data_time: 0.0407 memory: 33630 grad_norm: 3.7220 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8981 loss: 1.8981 2022/10/14 20:56:00 - mmengine - INFO - Epoch(train) [14][660/940] lr: 1.0000e-02 eta: 13:17:16 time: 0.5852 data_time: 0.0339 memory: 33630 grad_norm: 3.6675 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.8067 loss: 1.8067 2022/10/14 20:56:12 - mmengine - INFO - Epoch(train) [14][680/940] lr: 1.0000e-02 eta: 13:17:04 time: 0.5914 data_time: 0.0329 memory: 33630 grad_norm: 3.6830 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.0144 loss: 2.0144 2022/10/14 20:56:24 - mmengine - INFO - Epoch(train) [14][700/940] lr: 1.0000e-02 eta: 13:16:54 time: 0.5995 data_time: 0.0315 memory: 33630 grad_norm: 3.6582 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.9903 loss: 1.9903 2022/10/14 20:56:36 - mmengine - INFO - Epoch(train) [14][720/940] lr: 1.0000e-02 eta: 13:16:40 time: 0.5797 data_time: 0.0416 memory: 33630 grad_norm: 3.6541 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8790 loss: 1.8790 2022/10/14 20:56:48 - mmengine - INFO - Epoch(train) [14][740/940] lr: 1.0000e-02 eta: 13:16:29 time: 0.5936 data_time: 0.0399 memory: 33630 grad_norm: 3.6668 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.8848 loss: 1.8848 2022/10/14 20:56:59 - mmengine - INFO - Epoch(train) [14][760/940] lr: 1.0000e-02 eta: 13:16:16 time: 0.5796 data_time: 0.0353 memory: 33630 grad_norm: 3.6796 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 1.9438 loss: 1.9438 2022/10/14 20:57:11 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 20:57:11 - mmengine - INFO - Epoch(train) [14][780/940] lr: 1.0000e-02 eta: 13:16:03 time: 0.5819 data_time: 0.0315 memory: 33630 grad_norm: 3.7153 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8769 loss: 1.8769 2022/10/14 20:57:22 - mmengine - INFO - Epoch(train) [14][800/940] lr: 1.0000e-02 eta: 13:15:51 time: 0.5851 data_time: 0.0419 memory: 33630 grad_norm: 3.6454 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8301 loss: 1.8301 2022/10/14 20:57:34 - mmengine - INFO - Epoch(train) [14][820/940] lr: 1.0000e-02 eta: 13:15:39 time: 0.5904 data_time: 0.0320 memory: 33630 grad_norm: 3.7022 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.9275 loss: 1.9275 2022/10/14 20:57:46 - mmengine - INFO - Epoch(train) [14][840/940] lr: 1.0000e-02 eta: 13:15:28 time: 0.5914 data_time: 0.0332 memory: 33630 grad_norm: 3.6570 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.8437 loss: 1.8437 2022/10/14 20:57:58 - mmengine - INFO - Epoch(train) [14][860/940] lr: 1.0000e-02 eta: 13:15:16 time: 0.5885 data_time: 0.0309 memory: 33630 grad_norm: 3.7137 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.8546 loss: 1.8546 2022/10/14 20:58:09 - mmengine - INFO - Epoch(train) [14][880/940] lr: 1.0000e-02 eta: 13:15:02 time: 0.5764 data_time: 0.0397 memory: 33630 grad_norm: 3.7012 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.8907 loss: 1.8907 2022/10/14 20:58:21 - mmengine - INFO - Epoch(train) [14][900/940] lr: 1.0000e-02 eta: 13:14:50 time: 0.5865 data_time: 0.0307 memory: 33630 grad_norm: 3.6721 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 2.0091 loss: 2.0091 2022/10/14 20:58:33 - mmengine - INFO - Epoch(train) [14][920/940] lr: 1.0000e-02 eta: 13:14:36 time: 0.5719 data_time: 0.0377 memory: 33630 grad_norm: 3.6242 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8805 loss: 1.8805 2022/10/14 20:58:43 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 20:58:43 - mmengine - INFO - Epoch(train) [14][940/940] lr: 1.0000e-02 eta: 13:14:19 time: 0.5429 data_time: 0.0333 memory: 33630 grad_norm: 3.8981 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 2.0089 loss: 2.0089 2022/10/14 20:58:58 - mmengine - INFO - Epoch(val) [14][20/78] eta: 0:00:41 time: 0.7076 data_time: 0.5357 memory: 5967 2022/10/14 20:59:08 - mmengine - INFO - Epoch(val) [14][40/78] eta: 0:00:20 time: 0.5280 data_time: 0.3590 memory: 5967 2022/10/14 20:59:22 - mmengine - INFO - Epoch(val) [14][60/78] eta: 0:00:12 time: 0.6727 data_time: 0.5045 memory: 5967 2022/10/14 20:59:33 - mmengine - INFO - Epoch(val) [14][78/78] acc/top1: 0.6164 acc/top5: 0.8383 acc/mean1: 0.6164 2022/10/14 20:59:50 - mmengine - INFO - Epoch(train) [15][20/940] lr: 1.0000e-02 eta: 13:14:39 time: 0.8483 data_time: 0.2319 memory: 33630 grad_norm: 3.6273 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.7848 loss: 1.7848 2022/10/14 21:00:02 - mmengine - INFO - Epoch(train) [15][40/940] lr: 1.0000e-02 eta: 13:14:26 time: 0.5837 data_time: 0.0317 memory: 33630 grad_norm: 3.6426 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 1.8890 loss: 1.8890 2022/10/14 21:00:14 - mmengine - INFO - Epoch(train) [15][60/940] lr: 1.0000e-02 eta: 13:14:18 time: 0.6177 data_time: 0.0359 memory: 33630 grad_norm: 3.5873 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8079 loss: 1.8079 2022/10/14 21:00:26 - mmengine - INFO - Epoch(train) [15][80/940] lr: 1.0000e-02 eta: 13:14:06 time: 0.5942 data_time: 0.0362 memory: 33630 grad_norm: 3.6309 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.9826 loss: 1.9826 2022/10/14 21:00:38 - mmengine - INFO - Epoch(train) [15][100/940] lr: 1.0000e-02 eta: 13:13:54 time: 0.5845 data_time: 0.0360 memory: 33630 grad_norm: 3.7354 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.9172 loss: 1.9172 2022/10/14 21:00:50 - mmengine - INFO - Epoch(train) [15][120/940] lr: 1.0000e-02 eta: 13:13:41 time: 0.5780 data_time: 0.0347 memory: 33630 grad_norm: 3.7230 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.9184 loss: 1.9184 2022/10/14 21:01:01 - mmengine - INFO - Epoch(train) [15][140/940] lr: 1.0000e-02 eta: 13:13:26 time: 0.5693 data_time: 0.0465 memory: 33630 grad_norm: 3.6388 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7989 loss: 1.7989 2022/10/14 21:01:13 - mmengine - INFO - Epoch(train) [15][160/940] lr: 1.0000e-02 eta: 13:13:14 time: 0.5872 data_time: 0.0324 memory: 33630 grad_norm: 3.6874 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6970 loss: 1.6970 2022/10/14 21:01:24 - mmengine - INFO - Epoch(train) [15][180/940] lr: 1.0000e-02 eta: 13:13:01 time: 0.5818 data_time: 0.0364 memory: 33630 grad_norm: 3.7918 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.9851 loss: 1.9851 2022/10/14 21:01:36 - mmengine - INFO - Epoch(train) [15][200/940] lr: 1.0000e-02 eta: 13:12:48 time: 0.5783 data_time: 0.0324 memory: 33630 grad_norm: 3.6766 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.8216 loss: 1.8216 2022/10/14 21:01:48 - mmengine - INFO - Epoch(train) [15][220/940] lr: 1.0000e-02 eta: 13:12:37 time: 0.5925 data_time: 0.0467 memory: 33630 grad_norm: 3.6825 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7493 loss: 1.7493 2022/10/14 21:02:00 - mmengine - INFO - Epoch(train) [15][240/940] lr: 1.0000e-02 eta: 13:12:25 time: 0.5874 data_time: 0.0357 memory: 33630 grad_norm: 3.8097 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8408 loss: 1.8408 2022/10/14 21:02:11 - mmengine - INFO - Epoch(train) [15][260/940] lr: 1.0000e-02 eta: 13:12:11 time: 0.5764 data_time: 0.0353 memory: 33630 grad_norm: 3.6687 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8655 loss: 1.8655 2022/10/14 21:02:23 - mmengine - INFO - Epoch(train) [15][280/940] lr: 1.0000e-02 eta: 13:12:00 time: 0.5916 data_time: 0.0380 memory: 33630 grad_norm: 3.6735 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 1.7660 loss: 1.7660 2022/10/14 21:02:34 - mmengine - INFO - Epoch(train) [15][300/940] lr: 1.0000e-02 eta: 13:11:46 time: 0.5758 data_time: 0.0405 memory: 33630 grad_norm: 3.6895 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8871 loss: 1.8871 2022/10/14 21:02:46 - mmengine - INFO - Epoch(train) [15][320/940] lr: 1.0000e-02 eta: 13:11:34 time: 0.5835 data_time: 0.0327 memory: 33630 grad_norm: 3.6529 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8677 loss: 1.8677 2022/10/14 21:02:58 - mmengine - INFO - Epoch(train) [15][340/940] lr: 1.0000e-02 eta: 13:11:21 time: 0.5839 data_time: 0.0352 memory: 33630 grad_norm: 3.7138 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7389 loss: 1.7389 2022/10/14 21:03:09 - mmengine - INFO - Epoch(train) [15][360/940] lr: 1.0000e-02 eta: 13:11:08 time: 0.5779 data_time: 0.0421 memory: 33630 grad_norm: 3.7234 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 1.9887 loss: 1.9887 2022/10/14 21:03:21 - mmengine - INFO - Epoch(train) [15][380/940] lr: 1.0000e-02 eta: 13:10:55 time: 0.5817 data_time: 0.0303 memory: 33630 grad_norm: 3.7685 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8612 loss: 1.8612 2022/10/14 21:03:33 - mmengine - INFO - Epoch(train) [15][400/940] lr: 1.0000e-02 eta: 13:10:44 time: 0.5967 data_time: 0.0386 memory: 33630 grad_norm: 3.7439 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.8217 loss: 1.8217 2022/10/14 21:03:45 - mmengine - INFO - Epoch(train) [15][420/940] lr: 1.0000e-02 eta: 13:10:31 time: 0.5812 data_time: 0.0459 memory: 33630 grad_norm: 3.7295 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6962 loss: 1.6962 2022/10/14 21:03:56 - mmengine - INFO - Epoch(train) [15][440/940] lr: 1.0000e-02 eta: 13:10:19 time: 0.5817 data_time: 0.0321 memory: 33630 grad_norm: 3.7262 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7781 loss: 1.7781 2022/10/14 21:04:08 - mmengine - INFO - Epoch(train) [15][460/940] lr: 1.0000e-02 eta: 13:10:07 time: 0.5880 data_time: 0.0316 memory: 33630 grad_norm: 3.8408 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0225 loss: 2.0225 2022/10/14 21:04:20 - mmengine - INFO - Epoch(train) [15][480/940] lr: 1.0000e-02 eta: 13:09:54 time: 0.5865 data_time: 0.0372 memory: 33630 grad_norm: 3.7006 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7464 loss: 1.7464 2022/10/14 21:04:32 - mmengine - INFO - Epoch(train) [15][500/940] lr: 1.0000e-02 eta: 13:09:43 time: 0.5932 data_time: 0.0344 memory: 33630 grad_norm: 3.7535 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9104 loss: 1.9104 2022/10/14 21:04:43 - mmengine - INFO - Epoch(train) [15][520/940] lr: 1.0000e-02 eta: 13:09:29 time: 0.5702 data_time: 0.0350 memory: 33630 grad_norm: 3.7239 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.9038 loss: 1.9038 2022/10/14 21:04:55 - mmengine - INFO - Epoch(train) [15][540/940] lr: 1.0000e-02 eta: 13:09:16 time: 0.5809 data_time: 0.0375 memory: 33630 grad_norm: 3.7278 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8916 loss: 1.8916 2022/10/14 21:05:06 - mmengine - INFO - Epoch(train) [15][560/940] lr: 1.0000e-02 eta: 13:09:03 time: 0.5796 data_time: 0.0358 memory: 33630 grad_norm: 3.6949 top1_acc: 0.3438 top5_acc: 0.7188 loss_cls: 1.8815 loss: 1.8815 2022/10/14 21:05:18 - mmengine - INFO - Epoch(train) [15][580/940] lr: 1.0000e-02 eta: 13:08:51 time: 0.5889 data_time: 0.0312 memory: 33630 grad_norm: 3.7585 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8024 loss: 1.8024 2022/10/14 21:05:30 - mmengine - INFO - Epoch(train) [15][600/940] lr: 1.0000e-02 eta: 13:08:38 time: 0.5794 data_time: 0.0369 memory: 33630 grad_norm: 3.7856 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 1.9458 loss: 1.9458 2022/10/14 21:05:41 - mmengine - INFO - Epoch(train) [15][620/940] lr: 1.0000e-02 eta: 13:08:26 time: 0.5853 data_time: 0.0387 memory: 33630 grad_norm: 3.6784 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.7389 loss: 1.7389 2022/10/14 21:05:53 - mmengine - INFO - Epoch(train) [15][640/940] lr: 1.0000e-02 eta: 13:08:14 time: 0.5880 data_time: 0.0355 memory: 33630 grad_norm: 3.6692 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.8221 loss: 1.8221 2022/10/14 21:06:05 - mmengine - INFO - Epoch(train) [15][660/940] lr: 1.0000e-02 eta: 13:08:02 time: 0.5860 data_time: 0.0338 memory: 33630 grad_norm: 3.8113 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.8942 loss: 1.8942 2022/10/14 21:06:16 - mmengine - INFO - Epoch(train) [15][680/940] lr: 1.0000e-02 eta: 13:07:50 time: 0.5875 data_time: 0.0396 memory: 33630 grad_norm: 3.7799 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8547 loss: 1.8547 2022/10/14 21:06:28 - mmengine - INFO - Epoch(train) [15][700/940] lr: 1.0000e-02 eta: 13:07:37 time: 0.5856 data_time: 0.0334 memory: 33630 grad_norm: 3.6425 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.8136 loss: 1.8136 2022/10/14 21:06:40 - mmengine - INFO - Epoch(train) [15][720/940] lr: 1.0000e-02 eta: 13:07:25 time: 0.5811 data_time: 0.0352 memory: 33630 grad_norm: 3.6970 top1_acc: 0.5312 top5_acc: 0.6250 loss_cls: 2.0137 loss: 2.0137 2022/10/14 21:06:51 - mmengine - INFO - Epoch(train) [15][740/940] lr: 1.0000e-02 eta: 13:07:11 time: 0.5781 data_time: 0.0333 memory: 33630 grad_norm: 3.6516 top1_acc: 0.4062 top5_acc: 0.5312 loss_cls: 1.8295 loss: 1.8295 2022/10/14 21:07:03 - mmengine - INFO - Epoch(train) [15][760/940] lr: 1.0000e-02 eta: 13:06:59 time: 0.5852 data_time: 0.0410 memory: 33630 grad_norm: 3.6700 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.8597 loss: 1.8597 2022/10/14 21:07:15 - mmengine - INFO - Epoch(train) [15][780/940] lr: 1.0000e-02 eta: 13:06:47 time: 0.5848 data_time: 0.0370 memory: 33630 grad_norm: 3.6373 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7315 loss: 1.7315 2022/10/14 21:07:27 - mmengine - INFO - Epoch(train) [15][800/940] lr: 1.0000e-02 eta: 13:06:35 time: 0.5897 data_time: 0.0387 memory: 33630 grad_norm: 3.6669 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8584 loss: 1.8584 2022/10/14 21:07:38 - mmengine - INFO - Epoch(train) [15][820/940] lr: 1.0000e-02 eta: 13:06:22 time: 0.5822 data_time: 0.0422 memory: 33630 grad_norm: 3.6501 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7447 loss: 1.7447 2022/10/14 21:07:50 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 21:07:50 - mmengine - INFO - Epoch(train) [15][840/940] lr: 1.0000e-02 eta: 13:06:11 time: 0.5918 data_time: 0.0348 memory: 33630 grad_norm: 3.7551 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7834 loss: 1.7834 2022/10/14 21:08:02 - mmengine - INFO - Epoch(train) [15][860/940] lr: 1.0000e-02 eta: 13:05:58 time: 0.5779 data_time: 0.0331 memory: 33630 grad_norm: 3.6871 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8594 loss: 1.8594 2022/10/14 21:08:13 - mmengine - INFO - Epoch(train) [15][880/940] lr: 1.0000e-02 eta: 13:05:45 time: 0.5834 data_time: 0.0315 memory: 33630 grad_norm: 3.6846 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.8558 loss: 1.8558 2022/10/14 21:08:25 - mmengine - INFO - Epoch(train) [15][900/940] lr: 1.0000e-02 eta: 13:05:32 time: 0.5788 data_time: 0.0481 memory: 33630 grad_norm: 3.7066 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8878 loss: 1.8878 2022/10/14 21:08:36 - mmengine - INFO - Epoch(train) [15][920/940] lr: 1.0000e-02 eta: 13:05:19 time: 0.5758 data_time: 0.0377 memory: 33630 grad_norm: 3.6465 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.8916 loss: 1.8916 2022/10/14 21:08:47 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 21:08:47 - mmengine - INFO - Epoch(train) [15][940/940] lr: 1.0000e-02 eta: 13:05:01 time: 0.5401 data_time: 0.0277 memory: 33630 grad_norm: 3.9075 top1_acc: 0.2857 top5_acc: 0.5714 loss_cls: 1.9860 loss: 1.9860 2022/10/14 21:08:47 - mmengine - INFO - Saving checkpoint at 15 epochs 2022/10/14 21:09:02 - mmengine - INFO - Epoch(val) [15][20/78] eta: 0:00:40 time: 0.7050 data_time: 0.5338 memory: 5967 2022/10/14 21:09:13 - mmengine - INFO - Epoch(val) [15][40/78] eta: 0:00:20 time: 0.5363 data_time: 0.3665 memory: 5967 2022/10/14 21:09:27 - mmengine - INFO - Epoch(val) [15][60/78] eta: 0:00:12 time: 0.6956 data_time: 0.5274 memory: 5967 2022/10/14 21:09:37 - mmengine - INFO - Epoch(val) [15][78/78] acc/top1: 0.6237 acc/top5: 0.8443 acc/mean1: 0.6236 2022/10/14 21:09:37 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_13.pth is removed 2022/10/14 21:09:38 - mmengine - INFO - The best checkpoint with 0.6237 acc/top1 at 15 epoch is saved to best_acc/top1_epoch_15.pth. 2022/10/14 21:09:54 - mmengine - INFO - Epoch(train) [16][20/940] lr: 1.0000e-02 eta: 13:05:13 time: 0.7984 data_time: 0.2256 memory: 33630 grad_norm: 3.8028 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.9700 loss: 1.9700 2022/10/14 21:10:05 - mmengine - INFO - Epoch(train) [16][40/940] lr: 1.0000e-02 eta: 13:05:00 time: 0.5758 data_time: 0.0341 memory: 33630 grad_norm: 3.8213 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.9277 loss: 1.9277 2022/10/14 21:10:17 - mmengine - INFO - Epoch(train) [16][60/940] lr: 1.0000e-02 eta: 13:04:51 time: 0.6182 data_time: 0.0362 memory: 33630 grad_norm: 3.7122 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.8145 loss: 1.8145 2022/10/14 21:10:29 - mmengine - INFO - Epoch(train) [16][80/940] lr: 1.0000e-02 eta: 13:04:40 time: 0.5955 data_time: 0.0320 memory: 33630 grad_norm: 3.5828 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.8420 loss: 1.8420 2022/10/14 21:10:41 - mmengine - INFO - Epoch(train) [16][100/940] lr: 1.0000e-02 eta: 13:04:30 time: 0.6049 data_time: 0.0374 memory: 33630 grad_norm: 3.6725 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7227 loss: 1.7227 2022/10/14 21:10:53 - mmengine - INFO - Epoch(train) [16][120/940] lr: 1.0000e-02 eta: 13:04:18 time: 0.5902 data_time: 0.0419 memory: 33630 grad_norm: 3.7041 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7999 loss: 1.7999 2022/10/14 21:11:05 - mmengine - INFO - Epoch(train) [16][140/940] lr: 1.0000e-02 eta: 13:04:06 time: 0.5879 data_time: 0.0371 memory: 33630 grad_norm: 3.7411 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9920 loss: 1.9920 2022/10/14 21:11:17 - mmengine - INFO - Epoch(train) [16][160/940] lr: 1.0000e-02 eta: 13:03:53 time: 0.5780 data_time: 0.0375 memory: 33630 grad_norm: 3.6647 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8275 loss: 1.8275 2022/10/14 21:11:28 - mmengine - INFO - Epoch(train) [16][180/940] lr: 1.0000e-02 eta: 13:03:40 time: 0.5811 data_time: 0.0419 memory: 33630 grad_norm: 3.8015 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8530 loss: 1.8530 2022/10/14 21:11:40 - mmengine - INFO - Epoch(train) [16][200/940] lr: 1.0000e-02 eta: 13:03:28 time: 0.5885 data_time: 0.0319 memory: 33630 grad_norm: 3.6207 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8258 loss: 1.8258 2022/10/14 21:11:52 - mmengine - INFO - Epoch(train) [16][220/940] lr: 1.0000e-02 eta: 13:03:15 time: 0.5792 data_time: 0.0305 memory: 33630 grad_norm: 3.6653 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.8706 loss: 1.8706 2022/10/14 21:12:03 - mmengine - INFO - Epoch(train) [16][240/940] lr: 1.0000e-02 eta: 13:03:02 time: 0.5739 data_time: 0.0401 memory: 33630 grad_norm: 3.6999 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7883 loss: 1.7883 2022/10/14 21:12:15 - mmengine - INFO - Epoch(train) [16][260/940] lr: 1.0000e-02 eta: 13:02:50 time: 0.5884 data_time: 0.0354 memory: 33630 grad_norm: 3.6833 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7597 loss: 1.7597 2022/10/14 21:12:27 - mmengine - INFO - Epoch(train) [16][280/940] lr: 1.0000e-02 eta: 13:02:39 time: 0.5943 data_time: 0.0358 memory: 33630 grad_norm: 3.7085 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7678 loss: 1.7678 2022/10/14 21:12:39 - mmengine - INFO - Epoch(train) [16][300/940] lr: 1.0000e-02 eta: 13:02:27 time: 0.5898 data_time: 0.0330 memory: 33630 grad_norm: 3.7064 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.7627 loss: 1.7627 2022/10/14 21:12:50 - mmengine - INFO - Epoch(train) [16][320/940] lr: 1.0000e-02 eta: 13:02:14 time: 0.5839 data_time: 0.0378 memory: 33630 grad_norm: 3.7626 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7920 loss: 1.7920 2022/10/14 21:13:02 - mmengine - INFO - Epoch(train) [16][340/940] lr: 1.0000e-02 eta: 13:02:02 time: 0.5825 data_time: 0.0317 memory: 33630 grad_norm: 3.7187 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.7072 loss: 1.7072 2022/10/14 21:13:13 - mmengine - INFO - Epoch(train) [16][360/940] lr: 1.0000e-02 eta: 13:01:49 time: 0.5793 data_time: 0.0330 memory: 33630 grad_norm: 3.8258 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8513 loss: 1.8513 2022/10/14 21:13:25 - mmengine - INFO - Epoch(train) [16][380/940] lr: 1.0000e-02 eta: 13:01:37 time: 0.5921 data_time: 0.0351 memory: 33630 grad_norm: 3.7179 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7582 loss: 1.7582 2022/10/14 21:13:37 - mmengine - INFO - Epoch(train) [16][400/940] lr: 1.0000e-02 eta: 13:01:24 time: 0.5770 data_time: 0.0354 memory: 33630 grad_norm: 3.6613 top1_acc: 0.5938 top5_acc: 0.9688 loss_cls: 1.8103 loss: 1.8103 2022/10/14 21:13:49 - mmengine - INFO - Epoch(train) [16][420/940] lr: 1.0000e-02 eta: 13:01:12 time: 0.5878 data_time: 0.0303 memory: 33630 grad_norm: 3.8042 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.8355 loss: 1.8355 2022/10/14 21:14:00 - mmengine - INFO - Epoch(train) [16][440/940] lr: 1.0000e-02 eta: 13:00:58 time: 0.5680 data_time: 0.0311 memory: 33630 grad_norm: 3.7371 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.9086 loss: 1.9086 2022/10/14 21:14:12 - mmengine - INFO - Epoch(train) [16][460/940] lr: 1.0000e-02 eta: 13:00:45 time: 0.5834 data_time: 0.0389 memory: 33630 grad_norm: 3.8068 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7280 loss: 1.7280 2022/10/14 21:14:23 - mmengine - INFO - Epoch(train) [16][480/940] lr: 1.0000e-02 eta: 13:00:33 time: 0.5811 data_time: 0.0361 memory: 33630 grad_norm: 3.7239 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7167 loss: 1.7167 2022/10/14 21:14:35 - mmengine - INFO - Epoch(train) [16][500/940] lr: 1.0000e-02 eta: 13:00:21 time: 0.5916 data_time: 0.0360 memory: 33630 grad_norm: 3.7412 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7213 loss: 1.7213 2022/10/14 21:14:47 - mmengine - INFO - Epoch(train) [16][520/940] lr: 1.0000e-02 eta: 13:00:10 time: 0.5976 data_time: 0.0398 memory: 33630 grad_norm: 3.7811 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.8813 loss: 1.8813 2022/10/14 21:14:59 - mmengine - INFO - Epoch(train) [16][540/940] lr: 1.0000e-02 eta: 12:59:57 time: 0.5777 data_time: 0.0369 memory: 33630 grad_norm: 3.7681 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7466 loss: 1.7466 2022/10/14 21:15:10 - mmengine - INFO - Epoch(train) [16][560/940] lr: 1.0000e-02 eta: 12:59:45 time: 0.5893 data_time: 0.0437 memory: 33630 grad_norm: 3.7030 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7864 loss: 1.7864 2022/10/14 21:15:22 - mmengine - INFO - Epoch(train) [16][580/940] lr: 1.0000e-02 eta: 12:59:33 time: 0.5834 data_time: 0.0370 memory: 33630 grad_norm: 3.7871 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7813 loss: 1.7813 2022/10/14 21:15:34 - mmengine - INFO - Epoch(train) [16][600/940] lr: 1.0000e-02 eta: 12:59:20 time: 0.5791 data_time: 0.0500 memory: 33630 grad_norm: 3.8020 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8414 loss: 1.8414 2022/10/14 21:15:45 - mmengine - INFO - Epoch(train) [16][620/940] lr: 1.0000e-02 eta: 12:59:07 time: 0.5813 data_time: 0.0315 memory: 33630 grad_norm: 3.7462 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8842 loss: 1.8842 2022/10/14 21:15:57 - mmengine - INFO - Epoch(train) [16][640/940] lr: 1.0000e-02 eta: 12:58:55 time: 0.5840 data_time: 0.0399 memory: 33630 grad_norm: 3.7913 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8761 loss: 1.8761 2022/10/14 21:16:09 - mmengine - INFO - Epoch(train) [16][660/940] lr: 1.0000e-02 eta: 12:58:43 time: 0.5879 data_time: 0.0359 memory: 33630 grad_norm: 3.7171 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 1.7738 loss: 1.7738 2022/10/14 21:16:20 - mmengine - INFO - Epoch(train) [16][680/940] lr: 1.0000e-02 eta: 12:58:31 time: 0.5896 data_time: 0.0325 memory: 33630 grad_norm: 3.8072 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 1.9621 loss: 1.9621 2022/10/14 21:16:32 - mmengine - INFO - Epoch(train) [16][700/940] lr: 1.0000e-02 eta: 12:58:19 time: 0.5901 data_time: 0.0324 memory: 33630 grad_norm: 3.7441 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 1.8920 loss: 1.8920 2022/10/14 21:16:44 - mmengine - INFO - Epoch(train) [16][720/940] lr: 1.0000e-02 eta: 12:58:06 time: 0.5766 data_time: 0.0330 memory: 33630 grad_norm: 3.7009 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8503 loss: 1.8503 2022/10/14 21:16:56 - mmengine - INFO - Epoch(train) [16][740/940] lr: 1.0000e-02 eta: 12:57:54 time: 0.5872 data_time: 0.0364 memory: 33630 grad_norm: 3.7250 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.7370 loss: 1.7370 2022/10/14 21:17:07 - mmengine - INFO - Epoch(train) [16][760/940] lr: 1.0000e-02 eta: 12:57:42 time: 0.5881 data_time: 0.0379 memory: 33630 grad_norm: 3.7003 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8856 loss: 1.8856 2022/10/14 21:17:19 - mmengine - INFO - Epoch(train) [16][780/940] lr: 1.0000e-02 eta: 12:57:30 time: 0.5914 data_time: 0.0367 memory: 33630 grad_norm: 3.7734 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 1.9715 loss: 1.9715 2022/10/14 21:17:31 - mmengine - INFO - Epoch(train) [16][800/940] lr: 1.0000e-02 eta: 12:57:18 time: 0.5839 data_time: 0.0373 memory: 33630 grad_norm: 3.7557 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.8689 loss: 1.8689 2022/10/14 21:17:42 - mmengine - INFO - Epoch(train) [16][820/940] lr: 1.0000e-02 eta: 12:57:05 time: 0.5780 data_time: 0.0307 memory: 33630 grad_norm: 3.7062 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8699 loss: 1.8699 2022/10/14 21:17:54 - mmengine - INFO - Epoch(train) [16][840/940] lr: 1.0000e-02 eta: 12:56:54 time: 0.5960 data_time: 0.0326 memory: 33630 grad_norm: 3.6923 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8322 loss: 1.8322 2022/10/14 21:18:06 - mmengine - INFO - Epoch(train) [16][860/940] lr: 1.0000e-02 eta: 12:56:42 time: 0.5911 data_time: 0.0402 memory: 33630 grad_norm: 3.7214 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7261 loss: 1.7261 2022/10/14 21:18:18 - mmengine - INFO - Epoch(train) [16][880/940] lr: 1.0000e-02 eta: 12:56:31 time: 0.5941 data_time: 0.0380 memory: 33630 grad_norm: 3.8237 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 1.8440 loss: 1.8440 2022/10/14 21:18:30 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 21:18:30 - mmengine - INFO - Epoch(train) [16][900/940] lr: 1.0000e-02 eta: 12:56:18 time: 0.5751 data_time: 0.0440 memory: 33630 grad_norm: 3.6634 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.8311 loss: 1.8311 2022/10/14 21:18:41 - mmengine - INFO - Epoch(train) [16][920/940] lr: 1.0000e-02 eta: 12:56:06 time: 0.5894 data_time: 0.0412 memory: 33630 grad_norm: 3.7313 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8192 loss: 1.8192 2022/10/14 21:18:52 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 21:18:52 - mmengine - INFO - Epoch(train) [16][940/940] lr: 1.0000e-02 eta: 12:55:49 time: 0.5389 data_time: 0.0280 memory: 33630 grad_norm: 3.8713 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.8054 loss: 1.8054 2022/10/14 21:19:06 - mmengine - INFO - Epoch(val) [16][20/78] eta: 0:00:41 time: 0.7115 data_time: 0.5424 memory: 5967 2022/10/14 21:19:17 - mmengine - INFO - Epoch(val) [16][40/78] eta: 0:00:20 time: 0.5304 data_time: 0.3586 memory: 5967 2022/10/14 21:19:31 - mmengine - INFO - Epoch(val) [16][60/78] eta: 0:00:12 time: 0.6783 data_time: 0.5097 memory: 5967 2022/10/14 21:19:42 - mmengine - INFO - Epoch(val) [16][78/78] acc/top1: 0.6249 acc/top5: 0.8437 acc/mean1: 0.6248 2022/10/14 21:19:42 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_15.pth is removed 2022/10/14 21:19:43 - mmengine - INFO - The best checkpoint with 0.6249 acc/top1 at 16 epoch is saved to best_acc/top1_epoch_16.pth. 2022/10/14 21:19:59 - mmengine - INFO - Epoch(train) [17][20/940] lr: 1.0000e-02 eta: 12:56:00 time: 0.8101 data_time: 0.2587 memory: 33630 grad_norm: 3.7344 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.8720 loss: 1.8720 2022/10/14 21:20:11 - mmengine - INFO - Epoch(train) [17][40/940] lr: 1.0000e-02 eta: 12:55:48 time: 0.5845 data_time: 0.0314 memory: 33630 grad_norm: 3.6964 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.7495 loss: 1.7495 2022/10/14 21:20:23 - mmengine - INFO - Epoch(train) [17][60/940] lr: 1.0000e-02 eta: 12:55:38 time: 0.6088 data_time: 0.0459 memory: 33630 grad_norm: 3.8068 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.8470 loss: 1.8470 2022/10/14 21:20:35 - mmengine - INFO - Epoch(train) [17][80/940] lr: 1.0000e-02 eta: 12:55:26 time: 0.5917 data_time: 0.0356 memory: 33630 grad_norm: 3.7164 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.7582 loss: 1.7582 2022/10/14 21:20:46 - mmengine - INFO - Epoch(train) [17][100/940] lr: 1.0000e-02 eta: 12:55:14 time: 0.5872 data_time: 0.0299 memory: 33630 grad_norm: 3.6472 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.9383 loss: 1.9383 2022/10/14 21:20:58 - mmengine - INFO - Epoch(train) [17][120/940] lr: 1.0000e-02 eta: 12:55:02 time: 0.5869 data_time: 0.0416 memory: 33630 grad_norm: 3.6714 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.8751 loss: 1.8751 2022/10/14 21:21:10 - mmengine - INFO - Epoch(train) [17][140/940] lr: 1.0000e-02 eta: 12:54:50 time: 0.5851 data_time: 0.0396 memory: 33630 grad_norm: 3.7162 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8586 loss: 1.8586 2022/10/14 21:21:22 - mmengine - INFO - Epoch(train) [17][160/940] lr: 1.0000e-02 eta: 12:54:38 time: 0.5875 data_time: 0.0332 memory: 33630 grad_norm: 3.7862 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6613 loss: 1.6613 2022/10/14 21:21:33 - mmengine - INFO - Epoch(train) [17][180/940] lr: 1.0000e-02 eta: 12:54:25 time: 0.5830 data_time: 0.0316 memory: 33630 grad_norm: 3.7535 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.8961 loss: 1.8961 2022/10/14 21:21:45 - mmengine - INFO - Epoch(train) [17][200/940] lr: 1.0000e-02 eta: 12:54:13 time: 0.5835 data_time: 0.0346 memory: 33630 grad_norm: 3.7753 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8041 loss: 1.8041 2022/10/14 21:21:57 - mmengine - INFO - Epoch(train) [17][220/940] lr: 1.0000e-02 eta: 12:54:01 time: 0.5886 data_time: 0.0424 memory: 33630 grad_norm: 3.7937 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 1.8688 loss: 1.8688 2022/10/14 21:22:08 - mmengine - INFO - Epoch(train) [17][240/940] lr: 1.0000e-02 eta: 12:53:48 time: 0.5770 data_time: 0.0371 memory: 33630 grad_norm: 3.7348 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8692 loss: 1.8692 2022/10/14 21:22:20 - mmengine - INFO - Epoch(train) [17][260/940] lr: 1.0000e-02 eta: 12:53:34 time: 0.5694 data_time: 0.0316 memory: 33630 grad_norm: 3.7542 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.8658 loss: 1.8658 2022/10/14 21:22:31 - mmengine - INFO - Epoch(train) [17][280/940] lr: 1.0000e-02 eta: 12:53:21 time: 0.5760 data_time: 0.0386 memory: 33630 grad_norm: 3.6985 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7218 loss: 1.7218 2022/10/14 21:22:43 - mmengine - INFO - Epoch(train) [17][300/940] lr: 1.0000e-02 eta: 12:53:09 time: 0.5914 data_time: 0.0329 memory: 33630 grad_norm: 3.7600 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7901 loss: 1.7901 2022/10/14 21:22:55 - mmengine - INFO - Epoch(train) [17][320/940] lr: 1.0000e-02 eta: 12:52:57 time: 0.5864 data_time: 0.0389 memory: 33630 grad_norm: 3.8033 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6645 loss: 1.6645 2022/10/14 21:23:06 - mmengine - INFO - Epoch(train) [17][340/940] lr: 1.0000e-02 eta: 12:52:45 time: 0.5894 data_time: 0.0342 memory: 33630 grad_norm: 3.7065 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7688 loss: 1.7688 2022/10/14 21:23:18 - mmengine - INFO - Epoch(train) [17][360/940] lr: 1.0000e-02 eta: 12:52:32 time: 0.5779 data_time: 0.0363 memory: 33630 grad_norm: 3.7500 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.9932 loss: 1.9932 2022/10/14 21:23:30 - mmengine - INFO - Epoch(train) [17][380/940] lr: 1.0000e-02 eta: 12:52:20 time: 0.5873 data_time: 0.0328 memory: 33630 grad_norm: 3.7025 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8979 loss: 1.8979 2022/10/14 21:23:41 - mmengine - INFO - Epoch(train) [17][400/940] lr: 1.0000e-02 eta: 12:52:08 time: 0.5833 data_time: 0.0400 memory: 33630 grad_norm: 3.8275 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7316 loss: 1.7316 2022/10/14 21:23:53 - mmengine - INFO - Epoch(train) [17][420/940] lr: 1.0000e-02 eta: 12:51:56 time: 0.5915 data_time: 0.0341 memory: 33630 grad_norm: 3.7604 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.7357 loss: 1.7357 2022/10/14 21:24:05 - mmengine - INFO - Epoch(train) [17][440/940] lr: 1.0000e-02 eta: 12:51:42 time: 0.5720 data_time: 0.0314 memory: 33630 grad_norm: 3.7128 top1_acc: 0.3750 top5_acc: 0.7812 loss_cls: 1.7432 loss: 1.7432 2022/10/14 21:24:17 - mmengine - INFO - Epoch(train) [17][460/940] lr: 1.0000e-02 eta: 12:51:31 time: 0.5914 data_time: 0.0328 memory: 33630 grad_norm: 3.7888 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.8129 loss: 1.8129 2022/10/14 21:24:28 - mmengine - INFO - Epoch(train) [17][480/940] lr: 1.0000e-02 eta: 12:51:18 time: 0.5806 data_time: 0.0369 memory: 33630 grad_norm: 3.8164 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0323 loss: 2.0323 2022/10/14 21:24:40 - mmengine - INFO - Epoch(train) [17][500/940] lr: 1.0000e-02 eta: 12:51:06 time: 0.5871 data_time: 0.0343 memory: 33630 grad_norm: 3.7723 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8190 loss: 1.8190 2022/10/14 21:24:52 - mmengine - INFO - Epoch(train) [17][520/940] lr: 1.0000e-02 eta: 12:50:55 time: 0.5979 data_time: 0.0333 memory: 33630 grad_norm: 3.7224 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8815 loss: 1.8815 2022/10/14 21:25:04 - mmengine - INFO - Epoch(train) [17][540/940] lr: 1.0000e-02 eta: 12:50:43 time: 0.5858 data_time: 0.0314 memory: 33630 grad_norm: 3.7293 top1_acc: 0.4375 top5_acc: 0.8438 loss_cls: 1.8042 loss: 1.8042 2022/10/14 21:25:15 - mmengine - INFO - Epoch(train) [17][560/940] lr: 1.0000e-02 eta: 12:50:32 time: 0.5960 data_time: 0.0395 memory: 33630 grad_norm: 3.7373 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.8255 loss: 1.8255 2022/10/14 21:25:27 - mmengine - INFO - Epoch(train) [17][580/940] lr: 1.0000e-02 eta: 12:50:19 time: 0.5767 data_time: 0.0366 memory: 33630 grad_norm: 3.7295 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7732 loss: 1.7732 2022/10/14 21:25:39 - mmengine - INFO - Epoch(train) [17][600/940] lr: 1.0000e-02 eta: 12:50:06 time: 0.5808 data_time: 0.0359 memory: 33630 grad_norm: 3.7812 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.7871 loss: 1.7871 2022/10/14 21:25:50 - mmengine - INFO - Epoch(train) [17][620/940] lr: 1.0000e-02 eta: 12:49:53 time: 0.5796 data_time: 0.0353 memory: 33630 grad_norm: 3.8235 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.8885 loss: 1.8885 2022/10/14 21:26:02 - mmengine - INFO - Epoch(train) [17][640/940] lr: 1.0000e-02 eta: 12:49:40 time: 0.5795 data_time: 0.0357 memory: 33630 grad_norm: 3.7672 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.9536 loss: 1.9536 2022/10/14 21:26:13 - mmengine - INFO - Epoch(train) [17][660/940] lr: 1.0000e-02 eta: 12:49:28 time: 0.5814 data_time: 0.0331 memory: 33630 grad_norm: 3.7850 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.7778 loss: 1.7778 2022/10/14 21:26:25 - mmengine - INFO - Epoch(train) [17][680/940] lr: 1.0000e-02 eta: 12:49:15 time: 0.5813 data_time: 0.0388 memory: 33630 grad_norm: 3.7569 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8160 loss: 1.8160 2022/10/14 21:26:37 - mmengine - INFO - Epoch(train) [17][700/940] lr: 1.0000e-02 eta: 12:49:03 time: 0.5883 data_time: 0.0421 memory: 33630 grad_norm: 3.7198 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7665 loss: 1.7665 2022/10/14 21:26:48 - mmengine - INFO - Epoch(train) [17][720/940] lr: 1.0000e-02 eta: 12:48:51 time: 0.5822 data_time: 0.0332 memory: 33630 grad_norm: 3.7938 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 1.8545 loss: 1.8545 2022/10/14 21:27:00 - mmengine - INFO - Epoch(train) [17][740/940] lr: 1.0000e-02 eta: 12:48:38 time: 0.5843 data_time: 0.0312 memory: 33630 grad_norm: 3.7811 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9146 loss: 1.9146 2022/10/14 21:27:12 - mmengine - INFO - Epoch(train) [17][760/940] lr: 1.0000e-02 eta: 12:48:26 time: 0.5892 data_time: 0.0365 memory: 33630 grad_norm: 3.8484 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9680 loss: 1.9680 2022/10/14 21:27:24 - mmengine - INFO - Epoch(train) [17][780/940] lr: 1.0000e-02 eta: 12:48:16 time: 0.5992 data_time: 0.0418 memory: 33630 grad_norm: 3.8423 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.9092 loss: 1.9092 2022/10/14 21:27:36 - mmengine - INFO - Epoch(train) [17][800/940] lr: 1.0000e-02 eta: 12:48:03 time: 0.5842 data_time: 0.0352 memory: 33630 grad_norm: 3.7848 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.8865 loss: 1.8865 2022/10/14 21:27:47 - mmengine - INFO - Epoch(train) [17][820/940] lr: 1.0000e-02 eta: 12:47:50 time: 0.5746 data_time: 0.0323 memory: 33630 grad_norm: 3.7358 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 1.9217 loss: 1.9217 2022/10/14 21:27:59 - mmengine - INFO - Epoch(train) [17][840/940] lr: 1.0000e-02 eta: 12:47:37 time: 0.5811 data_time: 0.0367 memory: 33630 grad_norm: 3.8011 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.8780 loss: 1.8780 2022/10/14 21:28:11 - mmengine - INFO - Epoch(train) [17][860/940] lr: 1.0000e-02 eta: 12:47:26 time: 0.5950 data_time: 0.0407 memory: 33630 grad_norm: 3.7425 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7718 loss: 1.7718 2022/10/14 21:28:22 - mmengine - INFO - Epoch(train) [17][880/940] lr: 1.0000e-02 eta: 12:47:14 time: 0.5884 data_time: 0.0357 memory: 33630 grad_norm: 3.7762 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.7546 loss: 1.7546 2022/10/14 21:28:34 - mmengine - INFO - Epoch(train) [17][900/940] lr: 1.0000e-02 eta: 12:47:02 time: 0.5811 data_time: 0.0290 memory: 33630 grad_norm: 3.7794 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.9064 loss: 1.9064 2022/10/14 21:28:46 - mmengine - INFO - Epoch(train) [17][920/940] lr: 1.0000e-02 eta: 12:46:49 time: 0.5827 data_time: 0.0383 memory: 33630 grad_norm: 3.7544 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8481 loss: 1.8481 2022/10/14 21:28:57 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 21:28:57 - mmengine - INFO - Epoch(train) [17][940/940] lr: 1.0000e-02 eta: 12:46:33 time: 0.5423 data_time: 0.0284 memory: 33630 grad_norm: 4.0382 top1_acc: 0.2857 top5_acc: 0.8571 loss_cls: 1.9655 loss: 1.9655 2022/10/14 21:29:11 - mmengine - INFO - Epoch(val) [17][20/78] eta: 0:00:42 time: 0.7285 data_time: 0.5611 memory: 5967 2022/10/14 21:29:21 - mmengine - INFO - Epoch(val) [17][40/78] eta: 0:00:18 time: 0.4890 data_time: 0.3210 memory: 5967 2022/10/14 21:29:34 - mmengine - INFO - Epoch(val) [17][60/78] eta: 0:00:11 time: 0.6524 data_time: 0.4822 memory: 5967 2022/10/14 21:29:46 - mmengine - INFO - Epoch(val) [17][78/78] acc/top1: 0.6285 acc/top5: 0.8464 acc/mean1: 0.6282 2022/10/14 21:29:46 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_16.pth is removed 2022/10/14 21:29:47 - mmengine - INFO - The best checkpoint with 0.6285 acc/top1 at 17 epoch is saved to best_acc/top1_epoch_17.pth. 2022/10/14 21:30:03 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 21:30:03 - mmengine - INFO - Epoch(train) [18][20/940] lr: 1.0000e-02 eta: 12:46:42 time: 0.8024 data_time: 0.2283 memory: 33630 grad_norm: 3.7376 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.7612 loss: 1.7612 2022/10/14 21:30:14 - mmengine - INFO - Epoch(train) [18][40/940] lr: 1.0000e-02 eta: 12:46:29 time: 0.5768 data_time: 0.0341 memory: 33630 grad_norm: 3.7267 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7116 loss: 1.7116 2022/10/14 21:30:26 - mmengine - INFO - Epoch(train) [18][60/940] lr: 1.0000e-02 eta: 12:46:17 time: 0.5892 data_time: 0.0347 memory: 33630 grad_norm: 3.7429 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.7752 loss: 1.7752 2022/10/14 21:30:38 - mmengine - INFO - Epoch(train) [18][80/940] lr: 1.0000e-02 eta: 12:46:04 time: 0.5837 data_time: 0.0351 memory: 33630 grad_norm: 3.7400 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9575 loss: 1.9575 2022/10/14 21:30:50 - mmengine - INFO - Epoch(train) [18][100/940] lr: 1.0000e-02 eta: 12:45:53 time: 0.5993 data_time: 0.0353 memory: 33630 grad_norm: 3.7332 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8274 loss: 1.8274 2022/10/14 21:31:02 - mmengine - INFO - Epoch(train) [18][120/940] lr: 1.0000e-02 eta: 12:45:42 time: 0.5978 data_time: 0.0330 memory: 33630 grad_norm: 3.7066 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7312 loss: 1.7312 2022/10/14 21:31:14 - mmengine - INFO - Epoch(train) [18][140/940] lr: 1.0000e-02 eta: 12:45:31 time: 0.5883 data_time: 0.0407 memory: 33630 grad_norm: 3.7575 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.7838 loss: 1.7838 2022/10/14 21:31:25 - mmengine - INFO - Epoch(train) [18][160/940] lr: 1.0000e-02 eta: 12:45:18 time: 0.5828 data_time: 0.0344 memory: 33630 grad_norm: 3.7164 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8757 loss: 1.8757 2022/10/14 21:31:37 - mmengine - INFO - Epoch(train) [18][180/940] lr: 1.0000e-02 eta: 12:45:07 time: 0.5935 data_time: 0.0365 memory: 33630 grad_norm: 3.7423 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6920 loss: 1.6920 2022/10/14 21:31:49 - mmengine - INFO - Epoch(train) [18][200/940] lr: 1.0000e-02 eta: 12:44:53 time: 0.5754 data_time: 0.0306 memory: 33630 grad_norm: 3.7528 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.5997 loss: 1.5997 2022/10/14 21:32:00 - mmengine - INFO - Epoch(train) [18][220/940] lr: 1.0000e-02 eta: 12:44:41 time: 0.5874 data_time: 0.0316 memory: 33630 grad_norm: 3.7637 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8162 loss: 1.8162 2022/10/14 21:32:12 - mmengine - INFO - Epoch(train) [18][240/940] lr: 1.0000e-02 eta: 12:44:29 time: 0.5801 data_time: 0.0362 memory: 33630 grad_norm: 3.7398 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7161 loss: 1.7161 2022/10/14 21:32:24 - mmengine - INFO - Epoch(train) [18][260/940] lr: 1.0000e-02 eta: 12:44:16 time: 0.5763 data_time: 0.0342 memory: 33630 grad_norm: 3.7116 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7121 loss: 1.7121 2022/10/14 21:32:35 - mmengine - INFO - Epoch(train) [18][280/940] lr: 1.0000e-02 eta: 12:44:03 time: 0.5819 data_time: 0.0317 memory: 33630 grad_norm: 3.7806 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7146 loss: 1.7146 2022/10/14 21:32:47 - mmengine - INFO - Epoch(train) [18][300/940] lr: 1.0000e-02 eta: 12:43:51 time: 0.5908 data_time: 0.0379 memory: 33630 grad_norm: 3.7574 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8055 loss: 1.8055 2022/10/14 21:32:59 - mmengine - INFO - Epoch(train) [18][320/940] lr: 1.0000e-02 eta: 12:43:40 time: 0.5901 data_time: 0.0328 memory: 33630 grad_norm: 3.8168 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.9275 loss: 1.9275 2022/10/14 21:33:10 - mmengine - INFO - Epoch(train) [18][340/940] lr: 1.0000e-02 eta: 12:43:27 time: 0.5830 data_time: 0.0357 memory: 33630 grad_norm: 3.7742 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.7984 loss: 1.7984 2022/10/14 21:33:22 - mmengine - INFO - Epoch(train) [18][360/940] lr: 1.0000e-02 eta: 12:43:14 time: 0.5794 data_time: 0.0374 memory: 33630 grad_norm: 3.8249 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7396 loss: 1.7396 2022/10/14 21:33:34 - mmengine - INFO - Epoch(train) [18][380/940] lr: 1.0000e-02 eta: 12:43:02 time: 0.5796 data_time: 0.0308 memory: 33630 grad_norm: 3.7646 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8339 loss: 1.8339 2022/10/14 21:33:45 - mmengine - INFO - Epoch(train) [18][400/940] lr: 1.0000e-02 eta: 12:42:49 time: 0.5767 data_time: 0.0385 memory: 33630 grad_norm: 3.7390 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8784 loss: 1.8784 2022/10/14 21:33:57 - mmengine - INFO - Epoch(train) [18][420/940] lr: 1.0000e-02 eta: 12:42:36 time: 0.5832 data_time: 0.0334 memory: 33630 grad_norm: 3.7876 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7433 loss: 1.7433 2022/10/14 21:34:09 - mmengine - INFO - Epoch(train) [18][440/940] lr: 1.0000e-02 eta: 12:42:25 time: 0.5956 data_time: 0.0363 memory: 33630 grad_norm: 3.7238 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.7760 loss: 1.7760 2022/10/14 21:34:20 - mmengine - INFO - Epoch(train) [18][460/940] lr: 1.0000e-02 eta: 12:42:13 time: 0.5867 data_time: 0.0385 memory: 33630 grad_norm: 3.7844 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7586 loss: 1.7586 2022/10/14 21:34:32 - mmengine - INFO - Epoch(train) [18][480/940] lr: 1.0000e-02 eta: 12:42:01 time: 0.5828 data_time: 0.0419 memory: 33630 grad_norm: 3.7723 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7709 loss: 1.7709 2022/10/14 21:34:44 - mmengine - INFO - Epoch(train) [18][500/940] lr: 1.0000e-02 eta: 12:41:47 time: 0.5724 data_time: 0.0400 memory: 33630 grad_norm: 3.8246 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8134 loss: 1.8134 2022/10/14 21:34:55 - mmengine - INFO - Epoch(train) [18][520/940] lr: 1.0000e-02 eta: 12:41:35 time: 0.5872 data_time: 0.0355 memory: 33630 grad_norm: 3.7730 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7529 loss: 1.7529 2022/10/14 21:35:07 - mmengine - INFO - Epoch(train) [18][540/940] lr: 1.0000e-02 eta: 12:41:22 time: 0.5792 data_time: 0.0379 memory: 33630 grad_norm: 3.8138 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8688 loss: 1.8688 2022/10/14 21:35:19 - mmengine - INFO - Epoch(train) [18][560/940] lr: 1.0000e-02 eta: 12:41:12 time: 0.6002 data_time: 0.0331 memory: 33630 grad_norm: 3.8144 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7485 loss: 1.7485 2022/10/14 21:35:30 - mmengine - INFO - Epoch(train) [18][580/940] lr: 1.0000e-02 eta: 12:40:58 time: 0.5722 data_time: 0.0354 memory: 33630 grad_norm: 3.7252 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8627 loss: 1.8627 2022/10/14 21:35:42 - mmengine - INFO - Epoch(train) [18][600/940] lr: 1.0000e-02 eta: 12:40:45 time: 0.5783 data_time: 0.0299 memory: 33630 grad_norm: 3.8066 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8520 loss: 1.8520 2022/10/14 21:35:54 - mmengine - INFO - Epoch(train) [18][620/940] lr: 1.0000e-02 eta: 12:40:33 time: 0.5836 data_time: 0.0398 memory: 33630 grad_norm: 3.8267 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.9134 loss: 1.9134 2022/10/14 21:36:05 - mmengine - INFO - Epoch(train) [18][640/940] lr: 1.0000e-02 eta: 12:40:19 time: 0.5703 data_time: 0.0306 memory: 33630 grad_norm: 3.7618 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7589 loss: 1.7589 2022/10/14 21:36:17 - mmengine - INFO - Epoch(train) [18][660/940] lr: 1.0000e-02 eta: 12:40:08 time: 0.5918 data_time: 0.0325 memory: 33630 grad_norm: 3.8307 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.7836 loss: 1.7836 2022/10/14 21:36:29 - mmengine - INFO - Epoch(train) [18][680/940] lr: 1.0000e-02 eta: 12:39:57 time: 0.5971 data_time: 0.0436 memory: 33630 grad_norm: 3.7255 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 1.8074 loss: 1.8074 2022/10/14 21:36:41 - mmengine - INFO - Epoch(train) [18][700/940] lr: 1.0000e-02 eta: 12:39:45 time: 0.5868 data_time: 0.0336 memory: 33630 grad_norm: 3.8050 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.7591 loss: 1.7591 2022/10/14 21:36:52 - mmengine - INFO - Epoch(train) [18][720/940] lr: 1.0000e-02 eta: 12:39:32 time: 0.5799 data_time: 0.0461 memory: 33630 grad_norm: 3.7899 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7361 loss: 1.7361 2022/10/14 21:37:04 - mmengine - INFO - Epoch(train) [18][740/940] lr: 1.0000e-02 eta: 12:39:20 time: 0.5885 data_time: 0.0340 memory: 33630 grad_norm: 3.7679 top1_acc: 0.4375 top5_acc: 0.5938 loss_cls: 1.9374 loss: 1.9374 2022/10/14 21:37:16 - mmengine - INFO - Epoch(train) [18][760/940] lr: 1.0000e-02 eta: 12:39:08 time: 0.5838 data_time: 0.0397 memory: 33630 grad_norm: 3.8115 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8367 loss: 1.8367 2022/10/14 21:37:27 - mmengine - INFO - Epoch(train) [18][780/940] lr: 1.0000e-02 eta: 12:38:55 time: 0.5745 data_time: 0.0340 memory: 33630 grad_norm: 3.8162 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.9203 loss: 1.9203 2022/10/14 21:37:39 - mmengine - INFO - Epoch(train) [18][800/940] lr: 1.0000e-02 eta: 12:38:43 time: 0.5885 data_time: 0.0363 memory: 33630 grad_norm: 3.7928 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.7697 loss: 1.7697 2022/10/14 21:37:51 - mmengine - INFO - Epoch(train) [18][820/940] lr: 1.0000e-02 eta: 12:38:31 time: 0.5885 data_time: 0.0370 memory: 33630 grad_norm: 3.8183 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.7400 loss: 1.7400 2022/10/14 21:38:02 - mmengine - INFO - Epoch(train) [18][840/940] lr: 1.0000e-02 eta: 12:38:18 time: 0.5754 data_time: 0.0360 memory: 33630 grad_norm: 3.8667 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7549 loss: 1.7549 2022/10/14 21:38:14 - mmengine - INFO - Epoch(train) [18][860/940] lr: 1.0000e-02 eta: 12:38:07 time: 0.5974 data_time: 0.0351 memory: 33630 grad_norm: 3.7799 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7822 loss: 1.7822 2022/10/14 21:38:26 - mmengine - INFO - Epoch(train) [18][880/940] lr: 1.0000e-02 eta: 12:37:54 time: 0.5769 data_time: 0.0385 memory: 33630 grad_norm: 3.8227 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.7195 loss: 1.7195 2022/10/14 21:38:37 - mmengine - INFO - Epoch(train) [18][900/940] lr: 1.0000e-02 eta: 12:37:42 time: 0.5913 data_time: 0.0412 memory: 33630 grad_norm: 3.7892 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8505 loss: 1.8505 2022/10/14 21:38:49 - mmengine - INFO - Epoch(train) [18][920/940] lr: 1.0000e-02 eta: 12:37:29 time: 0.5806 data_time: 0.0327 memory: 33630 grad_norm: 3.8277 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7956 loss: 1.7956 2022/10/14 21:39:00 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 21:39:00 - mmengine - INFO - Epoch(train) [18][940/940] lr: 1.0000e-02 eta: 12:37:14 time: 0.5447 data_time: 0.0306 memory: 33630 grad_norm: 3.8925 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.8196 loss: 1.8196 2022/10/14 21:39:00 - mmengine - INFO - Saving checkpoint at 18 epochs 2022/10/14 21:39:15 - mmengine - INFO - Epoch(val) [18][20/78] eta: 0:00:41 time: 0.7175 data_time: 0.5479 memory: 5967 2022/10/14 21:39:25 - mmengine - INFO - Epoch(val) [18][40/78] eta: 0:00:18 time: 0.4887 data_time: 0.3180 memory: 5967 2022/10/14 21:39:39 - mmengine - INFO - Epoch(val) [18][60/78] eta: 0:00:12 time: 0.6938 data_time: 0.5240 memory: 5967 2022/10/14 21:39:49 - mmengine - INFO - Epoch(val) [18][78/78] acc/top1: 0.6335 acc/top5: 0.8465 acc/mean1: 0.6332 2022/10/14 21:39:49 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_17.pth is removed 2022/10/14 21:39:50 - mmengine - INFO - The best checkpoint with 0.6335 acc/top1 at 18 epoch is saved to best_acc/top1_epoch_18.pth. 2022/10/14 21:40:06 - mmengine - INFO - Epoch(train) [19][20/940] lr: 1.0000e-02 eta: 12:37:21 time: 0.8017 data_time: 0.2384 memory: 33630 grad_norm: 3.7637 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7348 loss: 1.7348 2022/10/14 21:40:17 - mmengine - INFO - Epoch(train) [19][40/940] lr: 1.0000e-02 eta: 12:37:09 time: 0.5886 data_time: 0.0441 memory: 33630 grad_norm: 3.7308 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.8000 loss: 1.8000 2022/10/14 21:40:29 - mmengine - INFO - Epoch(train) [19][60/940] lr: 1.0000e-02 eta: 12:36:59 time: 0.6068 data_time: 0.0391 memory: 33630 grad_norm: 3.7231 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.8386 loss: 1.8386 2022/10/14 21:40:41 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 21:40:41 - mmengine - INFO - Epoch(train) [19][80/940] lr: 1.0000e-02 eta: 12:36:46 time: 0.5742 data_time: 0.0312 memory: 33630 grad_norm: 3.6885 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.7264 loss: 1.7264 2022/10/14 21:40:53 - mmengine - INFO - Epoch(train) [19][100/940] lr: 1.0000e-02 eta: 12:36:35 time: 0.5987 data_time: 0.0372 memory: 33630 grad_norm: 3.7536 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9027 loss: 1.9027 2022/10/14 21:41:05 - mmengine - INFO - Epoch(train) [19][120/940] lr: 1.0000e-02 eta: 12:36:23 time: 0.5866 data_time: 0.0361 memory: 33630 grad_norm: 3.7658 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.6560 loss: 1.6560 2022/10/14 21:41:17 - mmengine - INFO - Epoch(train) [19][140/940] lr: 1.0000e-02 eta: 12:36:11 time: 0.5959 data_time: 0.0393 memory: 33630 grad_norm: 3.8505 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7634 loss: 1.7634 2022/10/14 21:41:28 - mmengine - INFO - Epoch(train) [19][160/940] lr: 1.0000e-02 eta: 12:36:00 time: 0.5912 data_time: 0.0334 memory: 33630 grad_norm: 3.7864 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.8937 loss: 1.8937 2022/10/14 21:41:40 - mmengine - INFO - Epoch(train) [19][180/940] lr: 1.0000e-02 eta: 12:35:48 time: 0.5880 data_time: 0.0380 memory: 33630 grad_norm: 3.7548 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.7587 loss: 1.7587 2022/10/14 21:41:52 - mmengine - INFO - Epoch(train) [19][200/940] lr: 1.0000e-02 eta: 12:35:35 time: 0.5784 data_time: 0.0371 memory: 33630 grad_norm: 3.8238 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7027 loss: 1.7027 2022/10/14 21:42:03 - mmengine - INFO - Epoch(train) [19][220/940] lr: 1.0000e-02 eta: 12:35:22 time: 0.5796 data_time: 0.0341 memory: 33630 grad_norm: 3.7735 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8142 loss: 1.8142 2022/10/14 21:42:15 - mmengine - INFO - Epoch(train) [19][240/940] lr: 1.0000e-02 eta: 12:35:11 time: 0.5975 data_time: 0.0409 memory: 33630 grad_norm: 3.7637 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7448 loss: 1.7448 2022/10/14 21:42:27 - mmengine - INFO - Epoch(train) [19][260/940] lr: 1.0000e-02 eta: 12:34:59 time: 0.5792 data_time: 0.0319 memory: 33630 grad_norm: 3.7391 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7445 loss: 1.7445 2022/10/14 21:42:39 - mmengine - INFO - Epoch(train) [19][280/940] lr: 1.0000e-02 eta: 12:34:46 time: 0.5856 data_time: 0.0325 memory: 33630 grad_norm: 3.8197 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7679 loss: 1.7679 2022/10/14 21:42:50 - mmengine - INFO - Epoch(train) [19][300/940] lr: 1.0000e-02 eta: 12:34:33 time: 0.5703 data_time: 0.0314 memory: 33630 grad_norm: 3.8360 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.9127 loss: 1.9127 2022/10/14 21:43:02 - mmengine - INFO - Epoch(train) [19][320/940] lr: 1.0000e-02 eta: 12:34:21 time: 0.5894 data_time: 0.0358 memory: 33630 grad_norm: 3.7826 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.6378 loss: 1.6378 2022/10/14 21:43:13 - mmengine - INFO - Epoch(train) [19][340/940] lr: 1.0000e-02 eta: 12:34:09 time: 0.5828 data_time: 0.0310 memory: 33630 grad_norm: 3.7513 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6628 loss: 1.6628 2022/10/14 21:43:25 - mmengine - INFO - Epoch(train) [19][360/940] lr: 1.0000e-02 eta: 12:33:56 time: 0.5749 data_time: 0.0399 memory: 33630 grad_norm: 3.8340 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.8719 loss: 1.8719 2022/10/14 21:43:37 - mmengine - INFO - Epoch(train) [19][380/940] lr: 1.0000e-02 eta: 12:33:43 time: 0.5855 data_time: 0.0341 memory: 33630 grad_norm: 3.7858 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7158 loss: 1.7158 2022/10/14 21:43:48 - mmengine - INFO - Epoch(train) [19][400/940] lr: 1.0000e-02 eta: 12:33:31 time: 0.5846 data_time: 0.0396 memory: 33630 grad_norm: 3.7515 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.7459 loss: 1.7459 2022/10/14 21:44:00 - mmengine - INFO - Epoch(train) [19][420/940] lr: 1.0000e-02 eta: 12:33:18 time: 0.5703 data_time: 0.0314 memory: 33630 grad_norm: 3.7682 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8352 loss: 1.8352 2022/10/14 21:44:12 - mmengine - INFO - Epoch(train) [19][440/940] lr: 1.0000e-02 eta: 12:33:06 time: 0.5952 data_time: 0.0344 memory: 33630 grad_norm: 3.8065 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.8199 loss: 1.8199 2022/10/14 21:44:24 - mmengine - INFO - Epoch(train) [19][460/940] lr: 1.0000e-02 eta: 12:32:55 time: 0.5915 data_time: 0.0472 memory: 33630 grad_norm: 3.7968 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7350 loss: 1.7350 2022/10/14 21:44:35 - mmengine - INFO - Epoch(train) [19][480/940] lr: 1.0000e-02 eta: 12:32:43 time: 0.5898 data_time: 0.0496 memory: 33630 grad_norm: 3.8862 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8318 loss: 1.8318 2022/10/14 21:44:47 - mmengine - INFO - Epoch(train) [19][500/940] lr: 1.0000e-02 eta: 12:32:31 time: 0.5929 data_time: 0.0324 memory: 33630 grad_norm: 3.7289 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7587 loss: 1.7587 2022/10/14 21:44:59 - mmengine - INFO - Epoch(train) [19][520/940] lr: 1.0000e-02 eta: 12:32:20 time: 0.5892 data_time: 0.0408 memory: 33630 grad_norm: 3.8505 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.9751 loss: 1.9751 2022/10/14 21:45:11 - mmengine - INFO - Epoch(train) [19][540/940] lr: 1.0000e-02 eta: 12:32:07 time: 0.5858 data_time: 0.0346 memory: 33630 grad_norm: 3.7963 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6615 loss: 1.6615 2022/10/14 21:45:22 - mmengine - INFO - Epoch(train) [19][560/940] lr: 1.0000e-02 eta: 12:31:54 time: 0.5745 data_time: 0.0388 memory: 33630 grad_norm: 3.8715 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.9065 loss: 1.9065 2022/10/14 21:45:34 - mmengine - INFO - Epoch(train) [19][580/940] lr: 1.0000e-02 eta: 12:31:42 time: 0.5862 data_time: 0.0351 memory: 33630 grad_norm: 3.7797 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7842 loss: 1.7842 2022/10/14 21:45:46 - mmengine - INFO - Epoch(train) [19][600/940] lr: 1.0000e-02 eta: 12:31:30 time: 0.5828 data_time: 0.0367 memory: 33630 grad_norm: 3.7944 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7655 loss: 1.7655 2022/10/14 21:45:57 - mmengine - INFO - Epoch(train) [19][620/940] lr: 1.0000e-02 eta: 12:31:18 time: 0.5917 data_time: 0.0535 memory: 33630 grad_norm: 3.8486 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.8426 loss: 1.8426 2022/10/14 21:46:09 - mmengine - INFO - Epoch(train) [19][640/940] lr: 1.0000e-02 eta: 12:31:07 time: 0.5929 data_time: 0.0310 memory: 33630 grad_norm: 3.8218 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8213 loss: 1.8213 2022/10/14 21:46:21 - mmengine - INFO - Epoch(train) [19][660/940] lr: 1.0000e-02 eta: 12:30:54 time: 0.5805 data_time: 0.0363 memory: 33630 grad_norm: 3.8173 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.8563 loss: 1.8563 2022/10/14 21:46:32 - mmengine - INFO - Epoch(train) [19][680/940] lr: 1.0000e-02 eta: 12:30:41 time: 0.5740 data_time: 0.0314 memory: 33630 grad_norm: 3.7629 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7763 loss: 1.7763 2022/10/14 21:46:44 - mmengine - INFO - Epoch(train) [19][700/940] lr: 1.0000e-02 eta: 12:30:28 time: 0.5751 data_time: 0.0378 memory: 33630 grad_norm: 3.8256 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.7752 loss: 1.7752 2022/10/14 21:46:55 - mmengine - INFO - Epoch(train) [19][720/940] lr: 1.0000e-02 eta: 12:30:15 time: 0.5788 data_time: 0.0347 memory: 33630 grad_norm: 3.8136 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.8109 loss: 1.8109 2022/10/14 21:47:07 - mmengine - INFO - Epoch(train) [19][740/940] lr: 1.0000e-02 eta: 12:30:02 time: 0.5753 data_time: 0.0342 memory: 33630 grad_norm: 3.7506 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7389 loss: 1.7389 2022/10/14 21:47:19 - mmengine - INFO - Epoch(train) [19][760/940] lr: 1.0000e-02 eta: 12:29:51 time: 0.5995 data_time: 0.0313 memory: 33630 grad_norm: 3.7562 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 1.8556 loss: 1.8556 2022/10/14 21:47:31 - mmengine - INFO - Epoch(train) [19][780/940] lr: 1.0000e-02 eta: 12:29:39 time: 0.5860 data_time: 0.0316 memory: 33630 grad_norm: 3.8042 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.7605 loss: 1.7605 2022/10/14 21:47:42 - mmengine - INFO - Epoch(train) [19][800/940] lr: 1.0000e-02 eta: 12:29:27 time: 0.5895 data_time: 0.0373 memory: 33630 grad_norm: 3.8163 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7630 loss: 1.7630 2022/10/14 21:47:54 - mmengine - INFO - Epoch(train) [19][820/940] lr: 1.0000e-02 eta: 12:29:15 time: 0.5784 data_time: 0.0405 memory: 33630 grad_norm: 3.7953 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.8343 loss: 1.8343 2022/10/14 21:48:06 - mmengine - INFO - Epoch(train) [19][840/940] lr: 1.0000e-02 eta: 12:29:02 time: 0.5837 data_time: 0.0383 memory: 33630 grad_norm: 3.8722 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8461 loss: 1.8461 2022/10/14 21:48:17 - mmengine - INFO - Epoch(train) [19][860/940] lr: 1.0000e-02 eta: 12:28:51 time: 0.5911 data_time: 0.0408 memory: 33630 grad_norm: 3.7521 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6718 loss: 1.6718 2022/10/14 21:48:29 - mmengine - INFO - Epoch(train) [19][880/940] lr: 1.0000e-02 eta: 12:28:39 time: 0.5909 data_time: 0.0364 memory: 33630 grad_norm: 3.8158 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8144 loss: 1.8144 2022/10/14 21:48:41 - mmengine - INFO - Epoch(train) [19][900/940] lr: 1.0000e-02 eta: 12:28:26 time: 0.5792 data_time: 0.0403 memory: 33630 grad_norm: 3.8289 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7722 loss: 1.7722 2022/10/14 21:48:53 - mmengine - INFO - Epoch(train) [19][920/940] lr: 1.0000e-02 eta: 12:28:15 time: 0.5942 data_time: 0.0361 memory: 33630 grad_norm: 3.8264 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7336 loss: 1.7336 2022/10/14 21:49:04 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 21:49:04 - mmengine - INFO - Epoch(train) [19][940/940] lr: 1.0000e-02 eta: 12:27:59 time: 0.5435 data_time: 0.0384 memory: 33630 grad_norm: 4.0782 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.8464 loss: 1.8464 2022/10/14 21:49:18 - mmengine - INFO - Epoch(val) [19][20/78] eta: 0:00:42 time: 0.7243 data_time: 0.5539 memory: 5967 2022/10/14 21:49:28 - mmengine - INFO - Epoch(val) [19][40/78] eta: 0:00:19 time: 0.5023 data_time: 0.3359 memory: 5967 2022/10/14 21:49:42 - mmengine - INFO - Epoch(val) [19][60/78] eta: 0:00:12 time: 0.6698 data_time: 0.5001 memory: 5967 2022/10/14 21:49:53 - mmengine - INFO - Epoch(val) [19][78/78] acc/top1: 0.6292 acc/top5: 0.8473 acc/mean1: 0.6291 2022/10/14 21:50:10 - mmengine - INFO - Epoch(train) [20][20/940] lr: 1.0000e-02 eta: 12:28:09 time: 0.8410 data_time: 0.2392 memory: 33630 grad_norm: 3.8527 top1_acc: 0.3438 top5_acc: 0.6250 loss_cls: 1.7628 loss: 1.7628 2022/10/14 21:50:22 - mmengine - INFO - Epoch(train) [20][40/940] lr: 1.0000e-02 eta: 12:27:56 time: 0.5800 data_time: 0.0311 memory: 33630 grad_norm: 3.7363 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6618 loss: 1.6618 2022/10/14 21:50:34 - mmengine - INFO - Epoch(train) [20][60/940] lr: 1.0000e-02 eta: 12:27:45 time: 0.5941 data_time: 0.0362 memory: 33630 grad_norm: 3.7238 top1_acc: 0.5000 top5_acc: 0.9062 loss_cls: 1.8356 loss: 1.8356 2022/10/14 21:50:45 - mmengine - INFO - Epoch(train) [20][80/940] lr: 1.0000e-02 eta: 12:27:33 time: 0.5847 data_time: 0.0317 memory: 33630 grad_norm: 3.8280 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7628 loss: 1.7628 2022/10/14 21:50:57 - mmengine - INFO - Epoch(train) [20][100/940] lr: 1.0000e-02 eta: 12:27:21 time: 0.5948 data_time: 0.0373 memory: 33630 grad_norm: 3.7929 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7343 loss: 1.7343 2022/10/14 21:51:09 - mmengine - INFO - Epoch(train) [20][120/940] lr: 1.0000e-02 eta: 12:27:09 time: 0.5779 data_time: 0.0338 memory: 33630 grad_norm: 3.8142 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.7377 loss: 1.7377 2022/10/14 21:51:20 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 21:51:20 - mmengine - INFO - Epoch(train) [20][140/940] lr: 1.0000e-02 eta: 12:26:56 time: 0.5821 data_time: 0.0428 memory: 33630 grad_norm: 3.8100 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7379 loss: 1.7379 2022/10/14 21:51:32 - mmengine - INFO - Epoch(train) [20][160/940] lr: 1.0000e-02 eta: 12:26:43 time: 0.5781 data_time: 0.0317 memory: 33630 grad_norm: 3.7645 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.7255 loss: 1.7255 2022/10/14 21:51:44 - mmengine - INFO - Epoch(train) [20][180/940] lr: 1.0000e-02 eta: 12:26:31 time: 0.5808 data_time: 0.0337 memory: 33630 grad_norm: 3.8095 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8842 loss: 1.8842 2022/10/14 21:51:55 - mmengine - INFO - Epoch(train) [20][200/940] lr: 1.0000e-02 eta: 12:26:18 time: 0.5760 data_time: 0.0353 memory: 33630 grad_norm: 3.7271 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.6753 loss: 1.6753 2022/10/14 21:52:07 - mmengine - INFO - Epoch(train) [20][220/940] lr: 1.0000e-02 eta: 12:26:05 time: 0.5776 data_time: 0.0317 memory: 33630 grad_norm: 3.7656 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7927 loss: 1.7927 2022/10/14 21:52:19 - mmengine - INFO - Epoch(train) [20][240/940] lr: 1.0000e-02 eta: 12:25:54 time: 0.5989 data_time: 0.0363 memory: 33630 grad_norm: 3.7924 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7135 loss: 1.7135 2022/10/14 21:52:30 - mmengine - INFO - Epoch(train) [20][260/940] lr: 1.0000e-02 eta: 12:25:42 time: 0.5843 data_time: 0.0385 memory: 33630 grad_norm: 3.7491 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7943 loss: 1.7943 2022/10/14 21:52:42 - mmengine - INFO - Epoch(train) [20][280/940] lr: 1.0000e-02 eta: 12:25:30 time: 0.5853 data_time: 0.0363 memory: 33630 grad_norm: 3.8281 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6861 loss: 1.6861 2022/10/14 21:52:54 - mmengine - INFO - Epoch(train) [20][300/940] lr: 1.0000e-02 eta: 12:25:17 time: 0.5757 data_time: 0.0410 memory: 33630 grad_norm: 3.7456 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.7852 loss: 1.7852 2022/10/14 21:53:05 - mmengine - INFO - Epoch(train) [20][320/940] lr: 1.0000e-02 eta: 12:25:04 time: 0.5784 data_time: 0.0304 memory: 33630 grad_norm: 3.8477 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7048 loss: 1.7048 2022/10/14 21:53:17 - mmengine - INFO - Epoch(train) [20][340/940] lr: 1.0000e-02 eta: 12:24:51 time: 0.5753 data_time: 0.0429 memory: 33630 grad_norm: 3.9171 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.8620 loss: 1.8620 2022/10/14 21:53:28 - mmengine - INFO - Epoch(train) [20][360/940] lr: 1.0000e-02 eta: 12:24:39 time: 0.5912 data_time: 0.0345 memory: 33630 grad_norm: 3.7513 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6342 loss: 1.6342 2022/10/14 21:53:40 - mmengine - INFO - Epoch(train) [20][380/940] lr: 1.0000e-02 eta: 12:24:27 time: 0.5838 data_time: 0.0336 memory: 33630 grad_norm: 3.8089 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7508 loss: 1.7508 2022/10/14 21:53:52 - mmengine - INFO - Epoch(train) [20][400/940] lr: 1.0000e-02 eta: 12:24:15 time: 0.5841 data_time: 0.0376 memory: 33630 grad_norm: 3.8231 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7247 loss: 1.7247 2022/10/14 21:54:03 - mmengine - INFO - Epoch(train) [20][420/940] lr: 1.0000e-02 eta: 12:24:02 time: 0.5778 data_time: 0.0384 memory: 33630 grad_norm: 3.9003 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7986 loss: 1.7986 2022/10/14 21:54:15 - mmengine - INFO - Epoch(train) [20][440/940] lr: 1.0000e-02 eta: 12:23:50 time: 0.5845 data_time: 0.0425 memory: 33630 grad_norm: 3.8471 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7878 loss: 1.7878 2022/10/14 21:54:27 - mmengine - INFO - Epoch(train) [20][460/940] lr: 1.0000e-02 eta: 12:23:38 time: 0.5839 data_time: 0.0400 memory: 33630 grad_norm: 3.8300 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7462 loss: 1.7462 2022/10/14 21:54:39 - mmengine - INFO - Epoch(train) [20][480/940] lr: 1.0000e-02 eta: 12:23:27 time: 0.5990 data_time: 0.0304 memory: 33630 grad_norm: 3.7409 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7467 loss: 1.7467 2022/10/14 21:54:50 - mmengine - INFO - Epoch(train) [20][500/940] lr: 1.0000e-02 eta: 12:23:14 time: 0.5777 data_time: 0.0326 memory: 33630 grad_norm: 3.7785 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.7385 loss: 1.7385 2022/10/14 21:55:02 - mmengine - INFO - Epoch(train) [20][520/940] lr: 1.0000e-02 eta: 12:23:02 time: 0.5873 data_time: 0.0399 memory: 33630 grad_norm: 3.8271 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6429 loss: 1.6429 2022/10/14 21:55:14 - mmengine - INFO - Epoch(train) [20][540/940] lr: 1.0000e-02 eta: 12:22:49 time: 0.5784 data_time: 0.0323 memory: 33630 grad_norm: 3.9047 top1_acc: 0.4375 top5_acc: 0.5938 loss_cls: 1.7735 loss: 1.7735 2022/10/14 21:55:25 - mmengine - INFO - Epoch(train) [20][560/940] lr: 1.0000e-02 eta: 12:22:36 time: 0.5783 data_time: 0.0354 memory: 33630 grad_norm: 3.9461 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7995 loss: 1.7995 2022/10/14 21:55:37 - mmengine - INFO - Epoch(train) [20][580/940] lr: 1.0000e-02 eta: 12:22:24 time: 0.5776 data_time: 0.0356 memory: 33630 grad_norm: 3.8015 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.7740 loss: 1.7740 2022/10/14 21:55:48 - mmengine - INFO - Epoch(train) [20][600/940] lr: 1.0000e-02 eta: 12:22:12 time: 0.5855 data_time: 0.0322 memory: 33630 grad_norm: 3.9082 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9025 loss: 1.9025 2022/10/14 21:56:00 - mmengine - INFO - Epoch(train) [20][620/940] lr: 1.0000e-02 eta: 12:21:58 time: 0.5732 data_time: 0.0422 memory: 33630 grad_norm: 3.8349 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.9304 loss: 1.9304 2022/10/14 21:56:12 - mmengine - INFO - Epoch(train) [20][640/940] lr: 1.0000e-02 eta: 12:21:46 time: 0.5852 data_time: 0.0356 memory: 33630 grad_norm: 3.8475 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7326 loss: 1.7326 2022/10/14 21:56:23 - mmengine - INFO - Epoch(train) [20][660/940] lr: 1.0000e-02 eta: 12:21:33 time: 0.5766 data_time: 0.0424 memory: 33630 grad_norm: 3.8381 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.8460 loss: 1.8460 2022/10/14 21:56:35 - mmengine - INFO - Epoch(train) [20][680/940] lr: 1.0000e-02 eta: 12:21:21 time: 0.5831 data_time: 0.0336 memory: 33630 grad_norm: 3.7938 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.7603 loss: 1.7603 2022/10/14 21:56:46 - mmengine - INFO - Epoch(train) [20][700/940] lr: 1.0000e-02 eta: 12:21:09 time: 0.5807 data_time: 0.0384 memory: 33630 grad_norm: 3.8310 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.8040 loss: 1.8040 2022/10/14 21:56:58 - mmengine - INFO - Epoch(train) [20][720/940] lr: 1.0000e-02 eta: 12:20:55 time: 0.5694 data_time: 0.0352 memory: 33630 grad_norm: 3.7853 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.8040 loss: 1.8040 2022/10/14 21:57:09 - mmengine - INFO - Epoch(train) [20][740/940] lr: 1.0000e-02 eta: 12:20:43 time: 0.5835 data_time: 0.0379 memory: 33630 grad_norm: 3.7853 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.7477 loss: 1.7477 2022/10/14 21:57:21 - mmengine - INFO - Epoch(train) [20][760/940] lr: 1.0000e-02 eta: 12:20:31 time: 0.5914 data_time: 0.0316 memory: 33630 grad_norm: 3.7795 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.8392 loss: 1.8392 2022/10/14 21:57:33 - mmengine - INFO - Epoch(train) [20][780/940] lr: 1.0000e-02 eta: 12:20:19 time: 0.5834 data_time: 0.0364 memory: 33630 grad_norm: 3.7520 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7003 loss: 1.7003 2022/10/14 21:57:45 - mmengine - INFO - Epoch(train) [20][800/940] lr: 1.0000e-02 eta: 12:20:07 time: 0.5853 data_time: 0.0441 memory: 33630 grad_norm: 3.7812 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7577 loss: 1.7577 2022/10/14 21:57:56 - mmengine - INFO - Epoch(train) [20][820/940] lr: 1.0000e-02 eta: 12:19:55 time: 0.5863 data_time: 0.0343 memory: 33630 grad_norm: 3.7879 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.6712 loss: 1.6712 2022/10/14 21:58:08 - mmengine - INFO - Epoch(train) [20][840/940] lr: 1.0000e-02 eta: 12:19:42 time: 0.5797 data_time: 0.0433 memory: 33630 grad_norm: 3.7408 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.6822 loss: 1.6822 2022/10/14 21:58:19 - mmengine - INFO - Epoch(train) [20][860/940] lr: 1.0000e-02 eta: 12:19:29 time: 0.5768 data_time: 0.0368 memory: 33630 grad_norm: 3.8878 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7468 loss: 1.7468 2022/10/14 21:58:31 - mmengine - INFO - Epoch(train) [20][880/940] lr: 1.0000e-02 eta: 12:19:17 time: 0.5870 data_time: 0.0379 memory: 33630 grad_norm: 3.7627 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8118 loss: 1.8118 2022/10/14 21:58:43 - mmengine - INFO - Epoch(train) [20][900/940] lr: 1.0000e-02 eta: 12:19:05 time: 0.5765 data_time: 0.0422 memory: 33630 grad_norm: 3.8411 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.8418 loss: 1.8418 2022/10/14 21:58:55 - mmengine - INFO - Epoch(train) [20][920/940] lr: 1.0000e-02 eta: 12:18:53 time: 0.5948 data_time: 0.0387 memory: 33630 grad_norm: 3.7775 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7566 loss: 1.7566 2022/10/14 21:59:06 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 21:59:06 - mmengine - INFO - Epoch(train) [20][940/940] lr: 1.0000e-02 eta: 12:18:38 time: 0.5457 data_time: 0.0292 memory: 33630 grad_norm: 3.9871 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.6819 loss: 1.6819 2022/10/14 21:59:20 - mmengine - INFO - Epoch(val) [20][20/78] eta: 0:00:42 time: 0.7247 data_time: 0.5527 memory: 5967 2022/10/14 21:59:30 - mmengine - INFO - Epoch(val) [20][40/78] eta: 0:00:19 time: 0.5030 data_time: 0.3350 memory: 5967 2022/10/14 21:59:44 - mmengine - INFO - Epoch(val) [20][60/78] eta: 0:00:12 time: 0.6875 data_time: 0.5183 memory: 5967 2022/10/14 21:59:55 - mmengine - INFO - Epoch(val) [20][78/78] acc/top1: 0.6356 acc/top5: 0.8508 acc/mean1: 0.6356 2022/10/14 21:59:55 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_18.pth is removed 2022/10/14 21:59:56 - mmengine - INFO - The best checkpoint with 0.6356 acc/top1 at 20 epoch is saved to best_acc/top1_epoch_20.pth. 2022/10/14 22:00:12 - mmengine - INFO - Epoch(train) [21][20/940] lr: 1.0000e-02 eta: 12:18:44 time: 0.8164 data_time: 0.2383 memory: 33630 grad_norm: 3.7885 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7994 loss: 1.7994 2022/10/14 22:00:24 - mmengine - INFO - Epoch(train) [21][40/940] lr: 1.0000e-02 eta: 12:18:32 time: 0.5774 data_time: 0.0332 memory: 33630 grad_norm: 3.7471 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6356 loss: 1.6356 2022/10/14 22:00:36 - mmengine - INFO - Epoch(train) [21][60/940] lr: 1.0000e-02 eta: 12:18:20 time: 0.5939 data_time: 0.0363 memory: 33630 grad_norm: 3.8092 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7575 loss: 1.7575 2022/10/14 22:00:47 - mmengine - INFO - Epoch(train) [21][80/940] lr: 1.0000e-02 eta: 12:18:08 time: 0.5860 data_time: 0.0322 memory: 33630 grad_norm: 3.7679 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.8214 loss: 1.8214 2022/10/14 22:00:59 - mmengine - INFO - Epoch(train) [21][100/940] lr: 1.0000e-02 eta: 12:17:57 time: 0.5951 data_time: 0.0356 memory: 33630 grad_norm: 3.8336 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7746 loss: 1.7746 2022/10/14 22:01:11 - mmengine - INFO - Epoch(train) [21][120/940] lr: 1.0000e-02 eta: 12:17:44 time: 0.5762 data_time: 0.0326 memory: 33630 grad_norm: 3.8344 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 1.6166 loss: 1.6166 2022/10/14 22:01:23 - mmengine - INFO - Epoch(train) [21][140/940] lr: 1.0000e-02 eta: 12:17:33 time: 0.6007 data_time: 0.0405 memory: 33630 grad_norm: 3.7989 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6894 loss: 1.6894 2022/10/14 22:01:34 - mmengine - INFO - Epoch(train) [21][160/940] lr: 1.0000e-02 eta: 12:17:20 time: 0.5714 data_time: 0.0307 memory: 33630 grad_norm: 3.8010 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7230 loss: 1.7230 2022/10/14 22:01:46 - mmengine - INFO - Epoch(train) [21][180/940] lr: 1.0000e-02 eta: 12:17:07 time: 0.5773 data_time: 0.0321 memory: 33630 grad_norm: 3.8025 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 1.7618 loss: 1.7618 2022/10/14 22:01:58 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 22:01:58 - mmengine - INFO - Epoch(train) [21][200/940] lr: 1.0000e-02 eta: 12:16:55 time: 0.5931 data_time: 0.0304 memory: 33630 grad_norm: 3.7582 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.7945 loss: 1.7945 2022/10/14 22:02:09 - mmengine - INFO - Epoch(train) [21][220/940] lr: 1.0000e-02 eta: 12:16:44 time: 0.5933 data_time: 0.0496 memory: 33630 grad_norm: 3.7886 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8768 loss: 1.8768 2022/10/14 22:02:21 - mmengine - INFO - Epoch(train) [21][240/940] lr: 1.0000e-02 eta: 12:16:32 time: 0.5834 data_time: 0.0415 memory: 33630 grad_norm: 3.8159 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7079 loss: 1.7079 2022/10/14 22:02:33 - mmengine - INFO - Epoch(train) [21][260/940] lr: 1.0000e-02 eta: 12:16:19 time: 0.5783 data_time: 0.0376 memory: 33630 grad_norm: 3.8302 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7615 loss: 1.7615 2022/10/14 22:02:44 - mmengine - INFO - Epoch(train) [21][280/940] lr: 1.0000e-02 eta: 12:16:07 time: 0.5846 data_time: 0.0322 memory: 33630 grad_norm: 3.7751 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7593 loss: 1.7593 2022/10/14 22:02:56 - mmengine - INFO - Epoch(train) [21][300/940] lr: 1.0000e-02 eta: 12:15:54 time: 0.5794 data_time: 0.0472 memory: 33630 grad_norm: 3.8627 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.7355 loss: 1.7355 2022/10/14 22:03:08 - mmengine - INFO - Epoch(train) [21][320/940] lr: 1.0000e-02 eta: 12:15:43 time: 0.5922 data_time: 0.0352 memory: 33630 grad_norm: 3.8016 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.6334 loss: 1.6334 2022/10/14 22:03:19 - mmengine - INFO - Epoch(train) [21][340/940] lr: 1.0000e-02 eta: 12:15:30 time: 0.5768 data_time: 0.0352 memory: 33630 grad_norm: 3.8454 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7913 loss: 1.7913 2022/10/14 22:03:31 - mmengine - INFO - Epoch(train) [21][360/940] lr: 1.0000e-02 eta: 12:15:17 time: 0.5783 data_time: 0.0424 memory: 33630 grad_norm: 3.8020 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6708 loss: 1.6708 2022/10/14 22:03:43 - mmengine - INFO - Epoch(train) [21][380/940] lr: 1.0000e-02 eta: 12:15:05 time: 0.5784 data_time: 0.0413 memory: 33630 grad_norm: 3.8848 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.8714 loss: 1.8714 2022/10/14 22:03:54 - mmengine - INFO - Epoch(train) [21][400/940] lr: 1.0000e-02 eta: 12:14:53 time: 0.5977 data_time: 0.0361 memory: 33630 grad_norm: 3.8558 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.7585 loss: 1.7585 2022/10/14 22:04:06 - mmengine - INFO - Epoch(train) [21][420/940] lr: 1.0000e-02 eta: 12:14:42 time: 0.5883 data_time: 0.0350 memory: 33630 grad_norm: 3.8229 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7336 loss: 1.7336 2022/10/14 22:04:18 - mmengine - INFO - Epoch(train) [21][440/940] lr: 1.0000e-02 eta: 12:14:28 time: 0.5725 data_time: 0.0348 memory: 33630 grad_norm: 3.7617 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7254 loss: 1.7254 2022/10/14 22:04:29 - mmengine - INFO - Epoch(train) [21][460/940] lr: 1.0000e-02 eta: 12:14:16 time: 0.5776 data_time: 0.0356 memory: 33630 grad_norm: 3.8294 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7860 loss: 1.7860 2022/10/14 22:04:41 - mmengine - INFO - Epoch(train) [21][480/940] lr: 1.0000e-02 eta: 12:14:04 time: 0.5843 data_time: 0.0360 memory: 33630 grad_norm: 3.9204 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8210 loss: 1.8210 2022/10/14 22:04:53 - mmengine - INFO - Epoch(train) [21][500/940] lr: 1.0000e-02 eta: 12:13:51 time: 0.5855 data_time: 0.0327 memory: 33630 grad_norm: 3.8379 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7530 loss: 1.7530 2022/10/14 22:05:04 - mmengine - INFO - Epoch(train) [21][520/940] lr: 1.0000e-02 eta: 12:13:40 time: 0.5923 data_time: 0.0386 memory: 33630 grad_norm: 3.8532 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.7042 loss: 1.7042 2022/10/14 22:05:16 - mmengine - INFO - Epoch(train) [21][540/940] lr: 1.0000e-02 eta: 12:13:27 time: 0.5786 data_time: 0.0459 memory: 33630 grad_norm: 3.8517 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.8740 loss: 1.8740 2022/10/14 22:05:28 - mmengine - INFO - Epoch(train) [21][560/940] lr: 1.0000e-02 eta: 12:13:15 time: 0.5815 data_time: 0.0369 memory: 33630 grad_norm: 3.8459 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8757 loss: 1.8757 2022/10/14 22:05:39 - mmengine - INFO - Epoch(train) [21][580/940] lr: 1.0000e-02 eta: 12:13:03 time: 0.5856 data_time: 0.0418 memory: 33630 grad_norm: 3.8703 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6801 loss: 1.6801 2022/10/14 22:05:51 - mmengine - INFO - Epoch(train) [21][600/940] lr: 1.0000e-02 eta: 12:12:50 time: 0.5787 data_time: 0.0325 memory: 33630 grad_norm: 3.8087 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7646 loss: 1.7646 2022/10/14 22:06:03 - mmengine - INFO - Epoch(train) [21][620/940] lr: 1.0000e-02 eta: 12:12:38 time: 0.5787 data_time: 0.0352 memory: 33630 grad_norm: 3.8644 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7895 loss: 1.7895 2022/10/14 22:06:14 - mmengine - INFO - Epoch(train) [21][640/940] lr: 1.0000e-02 eta: 12:12:25 time: 0.5826 data_time: 0.0319 memory: 33630 grad_norm: 3.8105 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7873 loss: 1.7873 2022/10/14 22:06:26 - mmengine - INFO - Epoch(train) [21][660/940] lr: 1.0000e-02 eta: 12:12:13 time: 0.5870 data_time: 0.0318 memory: 33630 grad_norm: 3.7741 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.6408 loss: 1.6408 2022/10/14 22:06:37 - mmengine - INFO - Epoch(train) [21][680/940] lr: 1.0000e-02 eta: 12:12:00 time: 0.5761 data_time: 0.0370 memory: 33630 grad_norm: 3.9012 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.7539 loss: 1.7539 2022/10/14 22:06:49 - mmengine - INFO - Epoch(train) [21][700/940] lr: 1.0000e-02 eta: 12:11:49 time: 0.5877 data_time: 0.0318 memory: 33630 grad_norm: 3.8755 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7612 loss: 1.7612 2022/10/14 22:07:01 - mmengine - INFO - Epoch(train) [21][720/940] lr: 1.0000e-02 eta: 12:11:36 time: 0.5858 data_time: 0.0431 memory: 33630 grad_norm: 3.8161 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8155 loss: 1.8155 2022/10/14 22:07:13 - mmengine - INFO - Epoch(train) [21][740/940] lr: 1.0000e-02 eta: 12:11:24 time: 0.5829 data_time: 0.0436 memory: 33630 grad_norm: 3.9175 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9201 loss: 1.9201 2022/10/14 22:07:24 - mmengine - INFO - Epoch(train) [21][760/940] lr: 1.0000e-02 eta: 12:11:12 time: 0.5776 data_time: 0.0328 memory: 33630 grad_norm: 3.8549 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8442 loss: 1.8442 2022/10/14 22:07:36 - mmengine - INFO - Epoch(train) [21][780/940] lr: 1.0000e-02 eta: 12:10:59 time: 0.5810 data_time: 0.0423 memory: 33630 grad_norm: 3.8801 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7507 loss: 1.7507 2022/10/14 22:07:47 - mmengine - INFO - Epoch(train) [21][800/940] lr: 1.0000e-02 eta: 12:10:47 time: 0.5800 data_time: 0.0466 memory: 33630 grad_norm: 3.8997 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.5431 loss: 1.5431 2022/10/14 22:07:59 - mmengine - INFO - Epoch(train) [21][820/940] lr: 1.0000e-02 eta: 12:10:34 time: 0.5740 data_time: 0.0370 memory: 33630 grad_norm: 3.9002 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8283 loss: 1.8283 2022/10/14 22:08:11 - mmengine - INFO - Epoch(train) [21][840/940] lr: 1.0000e-02 eta: 12:10:22 time: 0.5904 data_time: 0.0424 memory: 33630 grad_norm: 3.8777 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8156 loss: 1.8156 2022/10/14 22:08:22 - mmengine - INFO - Epoch(train) [21][860/940] lr: 1.0000e-02 eta: 12:10:09 time: 0.5754 data_time: 0.0329 memory: 33630 grad_norm: 3.7894 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7767 loss: 1.7767 2022/10/14 22:08:34 - mmengine - INFO - Epoch(train) [21][880/940] lr: 1.0000e-02 eta: 12:09:58 time: 0.5931 data_time: 0.0394 memory: 33630 grad_norm: 3.8987 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7318 loss: 1.7318 2022/10/14 22:08:46 - mmengine - INFO - Epoch(train) [21][900/940] lr: 1.0000e-02 eta: 12:09:45 time: 0.5757 data_time: 0.0318 memory: 33630 grad_norm: 3.7979 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.7877 loss: 1.7877 2022/10/14 22:08:57 - mmengine - INFO - Epoch(train) [21][920/940] lr: 1.0000e-02 eta: 12:09:32 time: 0.5812 data_time: 0.0324 memory: 33630 grad_norm: 3.8200 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7424 loss: 1.7424 2022/10/14 22:09:08 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 22:09:08 - mmengine - INFO - Epoch(train) [21][940/940] lr: 1.0000e-02 eta: 12:09:17 time: 0.5380 data_time: 0.0305 memory: 33630 grad_norm: 4.0229 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.9755 loss: 1.9755 2022/10/14 22:09:08 - mmengine - INFO - Saving checkpoint at 21 epochs 2022/10/14 22:09:23 - mmengine - INFO - Epoch(val) [21][20/78] eta: 0:00:41 time: 0.7125 data_time: 0.5409 memory: 5967 2022/10/14 22:09:33 - mmengine - INFO - Epoch(val) [21][40/78] eta: 0:00:19 time: 0.5210 data_time: 0.3535 memory: 5967 2022/10/14 22:09:46 - mmengine - INFO - Epoch(val) [21][60/78] eta: 0:00:11 time: 0.6458 data_time: 0.4774 memory: 5967 2022/10/14 22:09:58 - mmengine - INFO - Epoch(val) [21][78/78] acc/top1: 0.6410 acc/top5: 0.8537 acc/mean1: 0.6409 2022/10/14 22:09:58 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_20.pth is removed 2022/10/14 22:09:59 - mmengine - INFO - The best checkpoint with 0.6410 acc/top1 at 21 epoch is saved to best_acc/top1_epoch_21.pth. 2022/10/14 22:10:15 - mmengine - INFO - Epoch(train) [22][20/940] lr: 1.0000e-02 eta: 12:09:21 time: 0.8080 data_time: 0.2542 memory: 33630 grad_norm: 3.7832 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7695 loss: 1.7695 2022/10/14 22:10:27 - mmengine - INFO - Epoch(train) [22][40/940] lr: 1.0000e-02 eta: 12:09:09 time: 0.5830 data_time: 0.0374 memory: 33630 grad_norm: 3.7953 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8618 loss: 1.8618 2022/10/14 22:10:39 - mmengine - INFO - Epoch(train) [22][60/940] lr: 1.0000e-02 eta: 12:08:58 time: 0.5979 data_time: 0.0368 memory: 33630 grad_norm: 3.7374 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.8103 loss: 1.8103 2022/10/14 22:10:51 - mmengine - INFO - Epoch(train) [22][80/940] lr: 1.0000e-02 eta: 12:08:46 time: 0.5874 data_time: 0.0311 memory: 33630 grad_norm: 3.8090 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6217 loss: 1.6217 2022/10/14 22:11:03 - mmengine - INFO - Epoch(train) [22][100/940] lr: 1.0000e-02 eta: 12:08:36 time: 0.6094 data_time: 0.0391 memory: 33630 grad_norm: 3.8215 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8293 loss: 1.8293 2022/10/14 22:11:15 - mmengine - INFO - Epoch(train) [22][120/940] lr: 1.0000e-02 eta: 12:08:24 time: 0.5883 data_time: 0.0352 memory: 33630 grad_norm: 3.8685 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.8039 loss: 1.8039 2022/10/14 22:11:26 - mmengine - INFO - Epoch(train) [22][140/940] lr: 1.0000e-02 eta: 12:08:11 time: 0.5805 data_time: 0.0360 memory: 33630 grad_norm: 3.8691 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6861 loss: 1.6861 2022/10/14 22:11:38 - mmengine - INFO - Epoch(train) [22][160/940] lr: 1.0000e-02 eta: 12:07:59 time: 0.5807 data_time: 0.0353 memory: 33630 grad_norm: 3.8322 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7304 loss: 1.7304 2022/10/14 22:11:49 - mmengine - INFO - Epoch(train) [22][180/940] lr: 1.0000e-02 eta: 12:07:46 time: 0.5775 data_time: 0.0356 memory: 33630 grad_norm: 3.8205 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8411 loss: 1.8411 2022/10/14 22:12:01 - mmengine - INFO - Epoch(train) [22][200/940] lr: 1.0000e-02 eta: 12:07:35 time: 0.5966 data_time: 0.0349 memory: 33630 grad_norm: 3.8156 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7174 loss: 1.7174 2022/10/14 22:12:13 - mmengine - INFO - Epoch(train) [22][220/940] lr: 1.0000e-02 eta: 12:07:23 time: 0.5841 data_time: 0.0445 memory: 33630 grad_norm: 3.8712 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7198 loss: 1.7198 2022/10/14 22:12:25 - mmengine - INFO - Epoch(train) [22][240/940] lr: 1.0000e-02 eta: 12:07:10 time: 0.5815 data_time: 0.0345 memory: 33630 grad_norm: 3.8306 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6864 loss: 1.6864 2022/10/14 22:12:36 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 22:12:36 - mmengine - INFO - Epoch(train) [22][260/940] lr: 1.0000e-02 eta: 12:06:58 time: 0.5862 data_time: 0.0394 memory: 33630 grad_norm: 3.8507 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.9002 loss: 1.9002 2022/10/14 22:12:48 - mmengine - INFO - Epoch(train) [22][280/940] lr: 1.0000e-02 eta: 12:06:47 time: 0.5891 data_time: 0.0446 memory: 33630 grad_norm: 3.8576 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6766 loss: 1.6766 2022/10/14 22:13:00 - mmengine - INFO - Epoch(train) [22][300/940] lr: 1.0000e-02 eta: 12:06:35 time: 0.5870 data_time: 0.0363 memory: 33630 grad_norm: 3.8040 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8256 loss: 1.8256 2022/10/14 22:13:12 - mmengine - INFO - Epoch(train) [22][320/940] lr: 1.0000e-02 eta: 12:06:23 time: 0.5896 data_time: 0.0374 memory: 33630 grad_norm: 3.8146 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7263 loss: 1.7263 2022/10/14 22:13:23 - mmengine - INFO - Epoch(train) [22][340/940] lr: 1.0000e-02 eta: 12:06:11 time: 0.5884 data_time: 0.0320 memory: 33630 grad_norm: 3.9532 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7948 loss: 1.7948 2022/10/14 22:13:35 - mmengine - INFO - Epoch(train) [22][360/940] lr: 1.0000e-02 eta: 12:05:59 time: 0.5842 data_time: 0.0395 memory: 33630 grad_norm: 3.8272 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6708 loss: 1.6708 2022/10/14 22:13:47 - mmengine - INFO - Epoch(train) [22][380/940] lr: 1.0000e-02 eta: 12:05:46 time: 0.5818 data_time: 0.0307 memory: 33630 grad_norm: 3.8314 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7887 loss: 1.7887 2022/10/14 22:13:58 - mmengine - INFO - Epoch(train) [22][400/940] lr: 1.0000e-02 eta: 12:05:34 time: 0.5848 data_time: 0.0413 memory: 33630 grad_norm: 3.9141 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.8511 loss: 1.8511 2022/10/14 22:14:10 - mmengine - INFO - Epoch(train) [22][420/940] lr: 1.0000e-02 eta: 12:05:22 time: 0.5855 data_time: 0.0310 memory: 33630 grad_norm: 3.8588 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.8151 loss: 1.8151 2022/10/14 22:14:22 - mmengine - INFO - Epoch(train) [22][440/940] lr: 1.0000e-02 eta: 12:05:10 time: 0.5895 data_time: 0.0323 memory: 33630 grad_norm: 3.8146 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9134 loss: 1.9134 2022/10/14 22:14:34 - mmengine - INFO - Epoch(train) [22][460/940] lr: 1.0000e-02 eta: 12:04:59 time: 0.5953 data_time: 0.0360 memory: 33630 grad_norm: 3.8509 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7083 loss: 1.7083 2022/10/14 22:14:45 - mmengine - INFO - Epoch(train) [22][480/940] lr: 1.0000e-02 eta: 12:04:47 time: 0.5831 data_time: 0.0400 memory: 33630 grad_norm: 3.8629 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6625 loss: 1.6625 2022/10/14 22:14:57 - mmengine - INFO - Epoch(train) [22][500/940] lr: 1.0000e-02 eta: 12:04:34 time: 0.5799 data_time: 0.0310 memory: 33630 grad_norm: 3.8542 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.6772 loss: 1.6772 2022/10/14 22:15:09 - mmengine - INFO - Epoch(train) [22][520/940] lr: 1.0000e-02 eta: 12:04:22 time: 0.5787 data_time: 0.0375 memory: 33630 grad_norm: 3.8730 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7889 loss: 1.7889 2022/10/14 22:15:20 - mmengine - INFO - Epoch(train) [22][540/940] lr: 1.0000e-02 eta: 12:04:09 time: 0.5795 data_time: 0.0304 memory: 33630 grad_norm: 3.7762 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.7605 loss: 1.7605 2022/10/14 22:15:32 - mmengine - INFO - Epoch(train) [22][560/940] lr: 1.0000e-02 eta: 12:03:56 time: 0.5714 data_time: 0.0356 memory: 33630 grad_norm: 3.8040 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 1.7302 loss: 1.7302 2022/10/14 22:15:43 - mmengine - INFO - Epoch(train) [22][580/940] lr: 1.0000e-02 eta: 12:03:43 time: 0.5704 data_time: 0.0303 memory: 33630 grad_norm: 3.8683 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7502 loss: 1.7502 2022/10/14 22:15:55 - mmengine - INFO - Epoch(train) [22][600/940] lr: 1.0000e-02 eta: 12:03:31 time: 0.5860 data_time: 0.0307 memory: 33630 grad_norm: 3.8541 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6689 loss: 1.6689 2022/10/14 22:16:06 - mmengine - INFO - Epoch(train) [22][620/940] lr: 1.0000e-02 eta: 12:03:18 time: 0.5765 data_time: 0.0382 memory: 33630 grad_norm: 3.9173 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7288 loss: 1.7288 2022/10/14 22:16:18 - mmengine - INFO - Epoch(train) [22][640/940] lr: 1.0000e-02 eta: 12:03:07 time: 0.5893 data_time: 0.0393 memory: 33630 grad_norm: 3.8666 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.7472 loss: 1.7472 2022/10/14 22:16:30 - mmengine - INFO - Epoch(train) [22][660/940] lr: 1.0000e-02 eta: 12:02:54 time: 0.5857 data_time: 0.0344 memory: 33630 grad_norm: 3.8493 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7598 loss: 1.7598 2022/10/14 22:16:41 - mmengine - INFO - Epoch(train) [22][680/940] lr: 1.0000e-02 eta: 12:02:42 time: 0.5732 data_time: 0.0384 memory: 33630 grad_norm: 3.8448 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.8202 loss: 1.8202 2022/10/14 22:16:53 - mmengine - INFO - Epoch(train) [22][700/940] lr: 1.0000e-02 eta: 12:02:29 time: 0.5758 data_time: 0.0332 memory: 33630 grad_norm: 3.8158 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.7353 loss: 1.7353 2022/10/14 22:17:04 - mmengine - INFO - Epoch(train) [22][720/940] lr: 1.0000e-02 eta: 12:02:16 time: 0.5784 data_time: 0.0356 memory: 33630 grad_norm: 3.8627 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.7436 loss: 1.7436 2022/10/14 22:17:16 - mmengine - INFO - Epoch(train) [22][740/940] lr: 1.0000e-02 eta: 12:02:04 time: 0.5834 data_time: 0.0352 memory: 33630 grad_norm: 3.8390 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8208 loss: 1.8208 2022/10/14 22:17:28 - mmengine - INFO - Epoch(train) [22][760/940] lr: 1.0000e-02 eta: 12:01:53 time: 0.5971 data_time: 0.0360 memory: 33630 grad_norm: 3.7827 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.7108 loss: 1.7108 2022/10/14 22:17:39 - mmengine - INFO - Epoch(train) [22][780/940] lr: 1.0000e-02 eta: 12:01:40 time: 0.5726 data_time: 0.0373 memory: 33630 grad_norm: 3.8925 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5958 loss: 1.5958 2022/10/14 22:17:51 - mmengine - INFO - Epoch(train) [22][800/940] lr: 1.0000e-02 eta: 12:01:27 time: 0.5793 data_time: 0.0318 memory: 33630 grad_norm: 3.8476 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 1.7733 loss: 1.7733 2022/10/14 22:18:02 - mmengine - INFO - Epoch(train) [22][820/940] lr: 1.0000e-02 eta: 12:01:14 time: 0.5721 data_time: 0.0302 memory: 33630 grad_norm: 3.7416 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.5911 loss: 1.5911 2022/10/14 22:18:14 - mmengine - INFO - Epoch(train) [22][840/940] lr: 1.0000e-02 eta: 12:01:02 time: 0.5828 data_time: 0.0333 memory: 33630 grad_norm: 3.9370 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8283 loss: 1.8283 2022/10/14 22:18:26 - mmengine - INFO - Epoch(train) [22][860/940] lr: 1.0000e-02 eta: 12:00:49 time: 0.5745 data_time: 0.0332 memory: 33630 grad_norm: 3.8484 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6787 loss: 1.6787 2022/10/14 22:18:37 - mmengine - INFO - Epoch(train) [22][880/940] lr: 1.0000e-02 eta: 12:00:37 time: 0.5785 data_time: 0.0420 memory: 33630 grad_norm: 3.8449 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7841 loss: 1.7841 2022/10/14 22:18:49 - mmengine - INFO - Epoch(train) [22][900/940] lr: 1.0000e-02 eta: 12:00:25 time: 0.5913 data_time: 0.0381 memory: 33630 grad_norm: 3.9086 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7350 loss: 1.7350 2022/10/14 22:19:01 - mmengine - INFO - Epoch(train) [22][920/940] lr: 1.0000e-02 eta: 12:00:13 time: 0.5929 data_time: 0.0295 memory: 33630 grad_norm: 3.9028 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8115 loss: 1.8115 2022/10/14 22:19:12 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 22:19:12 - mmengine - INFO - Epoch(train) [22][940/940] lr: 1.0000e-02 eta: 11:59:58 time: 0.5307 data_time: 0.0292 memory: 33630 grad_norm: 4.0222 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.7491 loss: 1.7491 2022/10/14 22:19:25 - mmengine - INFO - Epoch(val) [22][20/78] eta: 0:00:39 time: 0.6877 data_time: 0.5153 memory: 5967 2022/10/14 22:19:36 - mmengine - INFO - Epoch(val) [22][40/78] eta: 0:00:19 time: 0.5175 data_time: 0.3505 memory: 5967 2022/10/14 22:19:50 - mmengine - INFO - Epoch(val) [22][60/78] eta: 0:00:12 time: 0.7108 data_time: 0.5427 memory: 5967 2022/10/14 22:20:00 - mmengine - INFO - Epoch(val) [22][78/78] acc/top1: 0.6415 acc/top5: 0.8500 acc/mean1: 0.6415 2022/10/14 22:20:00 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_21.pth is removed 2022/10/14 22:20:01 - mmengine - INFO - The best checkpoint with 0.6415 acc/top1 at 22 epoch is saved to best_acc/top1_epoch_22.pth. 2022/10/14 22:20:17 - mmengine - INFO - Epoch(train) [23][20/940] lr: 1.0000e-02 eta: 12:00:02 time: 0.8195 data_time: 0.2325 memory: 33630 grad_norm: 3.8471 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7274 loss: 1.7274 2022/10/14 22:20:29 - mmengine - INFO - Epoch(train) [23][40/940] lr: 1.0000e-02 eta: 11:59:51 time: 0.5966 data_time: 0.0326 memory: 33630 grad_norm: 3.8312 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6993 loss: 1.6993 2022/10/14 22:20:41 - mmengine - INFO - Epoch(train) [23][60/940] lr: 1.0000e-02 eta: 11:59:40 time: 0.6102 data_time: 0.0343 memory: 33630 grad_norm: 3.9357 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.8202 loss: 1.8202 2022/10/14 22:20:53 - mmengine - INFO - Epoch(train) [23][80/940] lr: 1.0000e-02 eta: 11:59:28 time: 0.5783 data_time: 0.0409 memory: 33630 grad_norm: 3.8397 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6660 loss: 1.6660 2022/10/14 22:21:04 - mmengine - INFO - Epoch(train) [23][100/940] lr: 1.0000e-02 eta: 11:59:15 time: 0.5734 data_time: 0.0326 memory: 33630 grad_norm: 3.9184 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7456 loss: 1.7456 2022/10/14 22:21:16 - mmengine - INFO - Epoch(train) [23][120/940] lr: 1.0000e-02 eta: 11:59:03 time: 0.5807 data_time: 0.0313 memory: 33630 grad_norm: 3.8896 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6849 loss: 1.6849 2022/10/14 22:21:28 - mmengine - INFO - Epoch(train) [23][140/940] lr: 1.0000e-02 eta: 11:58:50 time: 0.5812 data_time: 0.0316 memory: 33630 grad_norm: 3.8896 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6632 loss: 1.6632 2022/10/14 22:21:39 - mmengine - INFO - Epoch(train) [23][160/940] lr: 1.0000e-02 eta: 11:58:38 time: 0.5802 data_time: 0.0408 memory: 33630 grad_norm: 3.8726 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7221 loss: 1.7221 2022/10/14 22:21:51 - mmengine - INFO - Epoch(train) [23][180/940] lr: 1.0000e-02 eta: 11:58:26 time: 0.5827 data_time: 0.0373 memory: 33630 grad_norm: 3.9119 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6860 loss: 1.6860 2022/10/14 22:22:03 - mmengine - INFO - Epoch(train) [23][200/940] lr: 1.0000e-02 eta: 11:58:13 time: 0.5825 data_time: 0.0377 memory: 33630 grad_norm: 3.8761 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.5795 loss: 1.5795 2022/10/14 22:22:14 - mmengine - INFO - Epoch(train) [23][220/940] lr: 1.0000e-02 eta: 11:58:01 time: 0.5785 data_time: 0.0336 memory: 33630 grad_norm: 3.8285 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6878 loss: 1.6878 2022/10/14 22:22:26 - mmengine - INFO - Epoch(train) [23][240/940] lr: 1.0000e-02 eta: 11:57:48 time: 0.5826 data_time: 0.0310 memory: 33630 grad_norm: 3.8842 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.6970 loss: 1.6970 2022/10/14 22:22:38 - mmengine - INFO - Epoch(train) [23][260/940] lr: 1.0000e-02 eta: 11:57:37 time: 0.5925 data_time: 0.0383 memory: 33630 grad_norm: 3.8633 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8351 loss: 1.8351 2022/10/14 22:22:49 - mmengine - INFO - Epoch(train) [23][280/940] lr: 1.0000e-02 eta: 11:57:25 time: 0.5842 data_time: 0.0342 memory: 33630 grad_norm: 3.8493 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8082 loss: 1.8082 2022/10/14 22:23:01 - mmengine - INFO - Epoch(train) [23][300/940] lr: 1.0000e-02 eta: 11:57:12 time: 0.5785 data_time: 0.0310 memory: 33630 grad_norm: 3.8757 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6290 loss: 1.6290 2022/10/14 22:23:13 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 22:23:13 - mmengine - INFO - Epoch(train) [23][320/940] lr: 1.0000e-02 eta: 11:57:00 time: 0.5809 data_time: 0.0373 memory: 33630 grad_norm: 3.8082 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7198 loss: 1.7198 2022/10/14 22:23:24 - mmengine - INFO - Epoch(train) [23][340/940] lr: 1.0000e-02 eta: 11:56:47 time: 0.5739 data_time: 0.0301 memory: 33630 grad_norm: 3.7915 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7331 loss: 1.7331 2022/10/14 22:23:36 - mmengine - INFO - Epoch(train) [23][360/940] lr: 1.0000e-02 eta: 11:56:35 time: 0.5797 data_time: 0.0320 memory: 33630 grad_norm: 3.9117 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 1.7994 loss: 1.7994 2022/10/14 22:23:47 - mmengine - INFO - Epoch(train) [23][380/940] lr: 1.0000e-02 eta: 11:56:22 time: 0.5820 data_time: 0.0341 memory: 33630 grad_norm: 3.9255 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6944 loss: 1.6944 2022/10/14 22:23:59 - mmengine - INFO - Epoch(train) [23][400/940] lr: 1.0000e-02 eta: 11:56:09 time: 0.5719 data_time: 0.0335 memory: 33630 grad_norm: 3.8698 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6715 loss: 1.6715 2022/10/14 22:24:10 - mmengine - INFO - Epoch(train) [23][420/940] lr: 1.0000e-02 eta: 11:55:57 time: 0.5779 data_time: 0.0353 memory: 33630 grad_norm: 3.8827 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7655 loss: 1.7655 2022/10/14 22:24:22 - mmengine - INFO - Epoch(train) [23][440/940] lr: 1.0000e-02 eta: 11:55:44 time: 0.5795 data_time: 0.0363 memory: 33630 grad_norm: 3.8671 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7305 loss: 1.7305 2022/10/14 22:24:33 - mmengine - INFO - Epoch(train) [23][460/940] lr: 1.0000e-02 eta: 11:55:32 time: 0.5765 data_time: 0.0339 memory: 33630 grad_norm: 3.8682 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5898 loss: 1.5898 2022/10/14 22:24:45 - mmengine - INFO - Epoch(train) [23][480/940] lr: 1.0000e-02 eta: 11:55:19 time: 0.5770 data_time: 0.0334 memory: 33630 grad_norm: 3.9274 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6941 loss: 1.6941 2022/10/14 22:24:56 - mmengine - INFO - Epoch(train) [23][500/940] lr: 1.0000e-02 eta: 11:55:06 time: 0.5757 data_time: 0.0333 memory: 33630 grad_norm: 3.8796 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.7554 loss: 1.7554 2022/10/14 22:25:08 - mmengine - INFO - Epoch(train) [23][520/940] lr: 1.0000e-02 eta: 11:54:54 time: 0.5832 data_time: 0.0390 memory: 33630 grad_norm: 3.9119 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.6330 loss: 1.6330 2022/10/14 22:25:20 - mmengine - INFO - Epoch(train) [23][540/940] lr: 1.0000e-02 eta: 11:54:41 time: 0.5779 data_time: 0.0283 memory: 33630 grad_norm: 3.8066 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.8004 loss: 1.8004 2022/10/14 22:25:31 - mmengine - INFO - Epoch(train) [23][560/940] lr: 1.0000e-02 eta: 11:54:29 time: 0.5855 data_time: 0.0350 memory: 33630 grad_norm: 3.7902 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.8728 loss: 1.8728 2022/10/14 22:25:43 - mmengine - INFO - Epoch(train) [23][580/940] lr: 1.0000e-02 eta: 11:54:16 time: 0.5716 data_time: 0.0298 memory: 33630 grad_norm: 3.8482 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7767 loss: 1.7767 2022/10/14 22:25:54 - mmengine - INFO - Epoch(train) [23][600/940] lr: 1.0000e-02 eta: 11:54:04 time: 0.5782 data_time: 0.0333 memory: 33630 grad_norm: 3.8537 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.8154 loss: 1.8154 2022/10/14 22:26:06 - mmengine - INFO - Epoch(train) [23][620/940] lr: 1.0000e-02 eta: 11:53:52 time: 0.5863 data_time: 0.0362 memory: 33630 grad_norm: 3.8064 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6419 loss: 1.6419 2022/10/14 22:26:18 - mmengine - INFO - Epoch(train) [23][640/940] lr: 1.0000e-02 eta: 11:53:40 time: 0.5823 data_time: 0.0481 memory: 33630 grad_norm: 3.8570 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6574 loss: 1.6574 2022/10/14 22:26:29 - mmengine - INFO - Epoch(train) [23][660/940] lr: 1.0000e-02 eta: 11:53:27 time: 0.5696 data_time: 0.0315 memory: 33630 grad_norm: 3.9327 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6943 loss: 1.6943 2022/10/14 22:26:41 - mmengine - INFO - Epoch(train) [23][680/940] lr: 1.0000e-02 eta: 11:53:14 time: 0.5842 data_time: 0.0303 memory: 33630 grad_norm: 3.8755 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.8497 loss: 1.8497 2022/10/14 22:26:53 - mmengine - INFO - Epoch(train) [23][700/940] lr: 1.0000e-02 eta: 11:53:02 time: 0.5867 data_time: 0.0393 memory: 33630 grad_norm: 3.9469 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.7500 loss: 1.7500 2022/10/14 22:27:04 - mmengine - INFO - Epoch(train) [23][720/940] lr: 1.0000e-02 eta: 11:52:49 time: 0.5705 data_time: 0.0363 memory: 33630 grad_norm: 3.9054 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.6807 loss: 1.6807 2022/10/14 22:27:16 - mmengine - INFO - Epoch(train) [23][740/940] lr: 1.0000e-02 eta: 11:52:38 time: 0.5874 data_time: 0.0355 memory: 33630 grad_norm: 3.8206 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.7956 loss: 1.7956 2022/10/14 22:27:28 - mmengine - INFO - Epoch(train) [23][760/940] lr: 1.0000e-02 eta: 11:52:26 time: 0.5905 data_time: 0.0332 memory: 33630 grad_norm: 3.9410 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.5738 loss: 1.5738 2022/10/14 22:27:39 - mmengine - INFO - Epoch(train) [23][780/940] lr: 1.0000e-02 eta: 11:52:14 time: 0.5845 data_time: 0.0412 memory: 33630 grad_norm: 3.8933 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 1.8360 loss: 1.8360 2022/10/14 22:27:51 - mmengine - INFO - Epoch(train) [23][800/940] lr: 1.0000e-02 eta: 11:52:01 time: 0.5752 data_time: 0.0334 memory: 33630 grad_norm: 3.8894 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9269 loss: 1.9269 2022/10/14 22:28:02 - mmengine - INFO - Epoch(train) [23][820/940] lr: 1.0000e-02 eta: 11:51:49 time: 0.5816 data_time: 0.0375 memory: 33630 grad_norm: 3.8494 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7702 loss: 1.7702 2022/10/14 22:28:14 - mmengine - INFO - Epoch(train) [23][840/940] lr: 1.0000e-02 eta: 11:51:37 time: 0.5837 data_time: 0.0326 memory: 33630 grad_norm: 3.8556 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.7494 loss: 1.7494 2022/10/14 22:28:26 - mmengine - INFO - Epoch(train) [23][860/940] lr: 1.0000e-02 eta: 11:51:24 time: 0.5819 data_time: 0.0400 memory: 33630 grad_norm: 3.8431 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5170 loss: 1.5170 2022/10/14 22:28:37 - mmengine - INFO - Epoch(train) [23][880/940] lr: 1.0000e-02 eta: 11:51:12 time: 0.5881 data_time: 0.0393 memory: 33630 grad_norm: 3.8874 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.7002 loss: 1.7002 2022/10/14 22:28:49 - mmengine - INFO - Epoch(train) [23][900/940] lr: 1.0000e-02 eta: 11:51:00 time: 0.5791 data_time: 0.0361 memory: 33630 grad_norm: 3.8071 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6875 loss: 1.6875 2022/10/14 22:29:01 - mmengine - INFO - Epoch(train) [23][920/940] lr: 1.0000e-02 eta: 11:50:48 time: 0.5898 data_time: 0.0366 memory: 33630 grad_norm: 3.8649 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7267 loss: 1.7267 2022/10/14 22:29:12 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 22:29:12 - mmengine - INFO - Epoch(train) [23][940/940] lr: 1.0000e-02 eta: 11:50:33 time: 0.5351 data_time: 0.0276 memory: 33630 grad_norm: 4.0828 top1_acc: 0.2857 top5_acc: 0.5714 loss_cls: 1.7877 loss: 1.7877 2022/10/14 22:29:26 - mmengine - INFO - Epoch(val) [23][20/78] eta: 0:00:41 time: 0.7222 data_time: 0.5524 memory: 5967 2022/10/14 22:29:36 - mmengine - INFO - Epoch(val) [23][40/78] eta: 0:00:19 time: 0.5082 data_time: 0.3390 memory: 5967 2022/10/14 22:29:50 - mmengine - INFO - Epoch(val) [23][60/78] eta: 0:00:12 time: 0.6830 data_time: 0.5151 memory: 5967 2022/10/14 22:30:02 - mmengine - INFO - Epoch(val) [23][78/78] acc/top1: 0.6420 acc/top5: 0.8514 acc/mean1: 0.6418 2022/10/14 22:30:02 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_22.pth is removed 2022/10/14 22:30:02 - mmengine - INFO - The best checkpoint with 0.6420 acc/top1 at 23 epoch is saved to best_acc/top1_epoch_23.pth. 2022/10/14 22:30:19 - mmengine - INFO - Epoch(train) [24][20/940] lr: 1.0000e-02 eta: 11:50:36 time: 0.8137 data_time: 0.2665 memory: 33630 grad_norm: 3.8572 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.7066 loss: 1.7066 2022/10/14 22:30:31 - mmengine - INFO - Epoch(train) [24][40/940] lr: 1.0000e-02 eta: 11:50:26 time: 0.6077 data_time: 0.0610 memory: 33630 grad_norm: 3.8851 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.8013 loss: 1.8013 2022/10/14 22:30:43 - mmengine - INFO - Epoch(train) [24][60/940] lr: 1.0000e-02 eta: 11:50:14 time: 0.5953 data_time: 0.0383 memory: 33630 grad_norm: 3.8619 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.7031 loss: 1.7031 2022/10/14 22:30:55 - mmengine - INFO - Epoch(train) [24][80/940] lr: 1.0000e-02 eta: 11:50:03 time: 0.5925 data_time: 0.0456 memory: 33630 grad_norm: 3.8697 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6575 loss: 1.6575 2022/10/14 22:31:07 - mmengine - INFO - Epoch(train) [24][100/940] lr: 1.0000e-02 eta: 11:49:51 time: 0.5959 data_time: 0.0462 memory: 33630 grad_norm: 3.9577 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.8718 loss: 1.8718 2022/10/14 22:31:18 - mmengine - INFO - Epoch(train) [24][120/940] lr: 1.0000e-02 eta: 11:49:40 time: 0.5986 data_time: 0.0495 memory: 33630 grad_norm: 3.8944 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.7301 loss: 1.7301 2022/10/14 22:31:31 - mmengine - INFO - Epoch(train) [24][140/940] lr: 1.0000e-02 eta: 11:49:29 time: 0.6057 data_time: 0.0509 memory: 33630 grad_norm: 3.8751 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7201 loss: 1.7201 2022/10/14 22:31:42 - mmengine - INFO - Epoch(train) [24][160/940] lr: 1.0000e-02 eta: 11:49:18 time: 0.5922 data_time: 0.0315 memory: 33630 grad_norm: 3.8947 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.6868 loss: 1.6868 2022/10/14 22:31:54 - mmengine - INFO - Epoch(train) [24][180/940] lr: 1.0000e-02 eta: 11:49:05 time: 0.5730 data_time: 0.0379 memory: 33630 grad_norm: 3.7788 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.6642 loss: 1.6642 2022/10/14 22:32:06 - mmengine - INFO - Epoch(train) [24][200/940] lr: 1.0000e-02 eta: 11:48:53 time: 0.5930 data_time: 0.0320 memory: 33630 grad_norm: 3.9003 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.6557 loss: 1.6557 2022/10/14 22:32:17 - mmengine - INFO - Epoch(train) [24][220/940] lr: 1.0000e-02 eta: 11:48:41 time: 0.5775 data_time: 0.0355 memory: 33630 grad_norm: 3.8457 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8272 loss: 1.8272 2022/10/14 22:32:29 - mmengine - INFO - Epoch(train) [24][240/940] lr: 1.0000e-02 eta: 11:48:30 time: 0.5972 data_time: 0.0496 memory: 33630 grad_norm: 3.8903 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7481 loss: 1.7481 2022/10/14 22:32:41 - mmengine - INFO - Epoch(train) [24][260/940] lr: 1.0000e-02 eta: 11:48:17 time: 0.5743 data_time: 0.0363 memory: 33630 grad_norm: 3.8656 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7313 loss: 1.7313 2022/10/14 22:32:52 - mmengine - INFO - Epoch(train) [24][280/940] lr: 1.0000e-02 eta: 11:48:05 time: 0.5815 data_time: 0.0486 memory: 33630 grad_norm: 3.8433 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6479 loss: 1.6479 2022/10/14 22:33:04 - mmengine - INFO - Epoch(train) [24][300/940] lr: 1.0000e-02 eta: 11:47:52 time: 0.5764 data_time: 0.0316 memory: 33630 grad_norm: 3.8700 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9227 loss: 1.9227 2022/10/14 22:33:15 - mmengine - INFO - Epoch(train) [24][320/940] lr: 1.0000e-02 eta: 11:47:39 time: 0.5775 data_time: 0.0355 memory: 33630 grad_norm: 3.9000 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7817 loss: 1.7817 2022/10/14 22:33:27 - mmengine - INFO - Epoch(train) [24][340/940] lr: 1.0000e-02 eta: 11:47:27 time: 0.5735 data_time: 0.0374 memory: 33630 grad_norm: 3.8967 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 1.7300 loss: 1.7300 2022/10/14 22:33:39 - mmengine - INFO - Epoch(train) [24][360/940] lr: 1.0000e-02 eta: 11:47:14 time: 0.5848 data_time: 0.0384 memory: 33630 grad_norm: 3.8354 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.5825 loss: 1.5825 2022/10/14 22:33:50 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 22:33:50 - mmengine - INFO - Epoch(train) [24][380/940] lr: 1.0000e-02 eta: 11:47:02 time: 0.5820 data_time: 0.0395 memory: 33630 grad_norm: 3.8301 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5923 loss: 1.5923 2022/10/14 22:34:02 - mmengine - INFO - Epoch(train) [24][400/940] lr: 1.0000e-02 eta: 11:46:50 time: 0.5772 data_time: 0.0312 memory: 33630 grad_norm: 3.9087 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6957 loss: 1.6957 2022/10/14 22:34:14 - mmengine - INFO - Epoch(train) [24][420/940] lr: 1.0000e-02 eta: 11:46:38 time: 0.5898 data_time: 0.0428 memory: 33630 grad_norm: 3.8406 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6445 loss: 1.6445 2022/10/14 22:34:25 - mmengine - INFO - Epoch(train) [24][440/940] lr: 1.0000e-02 eta: 11:46:26 time: 0.5800 data_time: 0.0383 memory: 33630 grad_norm: 4.0162 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.9119 loss: 1.9119 2022/10/14 22:34:37 - mmengine - INFO - Epoch(train) [24][460/940] lr: 1.0000e-02 eta: 11:46:13 time: 0.5841 data_time: 0.0489 memory: 33630 grad_norm: 3.8733 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6861 loss: 1.6861 2022/10/14 22:34:48 - mmengine - INFO - Epoch(train) [24][480/940] lr: 1.0000e-02 eta: 11:46:01 time: 0.5738 data_time: 0.0328 memory: 33630 grad_norm: 3.8727 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6018 loss: 1.6018 2022/10/14 22:35:00 - mmengine - INFO - Epoch(train) [24][500/940] lr: 1.0000e-02 eta: 11:45:49 time: 0.5838 data_time: 0.0334 memory: 33630 grad_norm: 3.8967 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6123 loss: 1.6123 2022/10/14 22:35:11 - mmengine - INFO - Epoch(train) [24][520/940] lr: 1.0000e-02 eta: 11:45:35 time: 0.5693 data_time: 0.0373 memory: 33630 grad_norm: 3.9064 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7791 loss: 1.7791 2022/10/14 22:35:23 - mmengine - INFO - Epoch(train) [24][540/940] lr: 1.0000e-02 eta: 11:45:23 time: 0.5756 data_time: 0.0335 memory: 33630 grad_norm: 3.9246 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7394 loss: 1.7394 2022/10/14 22:35:35 - mmengine - INFO - Epoch(train) [24][560/940] lr: 1.0000e-02 eta: 11:45:11 time: 0.5851 data_time: 0.0396 memory: 33630 grad_norm: 3.8637 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.7274 loss: 1.7274 2022/10/14 22:35:46 - mmengine - INFO - Epoch(train) [24][580/940] lr: 1.0000e-02 eta: 11:44:59 time: 0.5915 data_time: 0.0354 memory: 33630 grad_norm: 3.8107 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5479 loss: 1.5479 2022/10/14 22:35:58 - mmengine - INFO - Epoch(train) [24][600/940] lr: 1.0000e-02 eta: 11:44:47 time: 0.5843 data_time: 0.0347 memory: 33630 grad_norm: 3.9301 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7924 loss: 1.7924 2022/10/14 22:36:10 - mmengine - INFO - Epoch(train) [24][620/940] lr: 1.0000e-02 eta: 11:44:35 time: 0.5798 data_time: 0.0322 memory: 33630 grad_norm: 3.8919 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6284 loss: 1.6284 2022/10/14 22:36:22 - mmengine - INFO - Epoch(train) [24][640/940] lr: 1.0000e-02 eta: 11:44:23 time: 0.5954 data_time: 0.0386 memory: 33630 grad_norm: 3.9711 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7065 loss: 1.7065 2022/10/14 22:36:34 - mmengine - INFO - Epoch(train) [24][660/940] lr: 1.0000e-02 eta: 11:44:12 time: 0.5907 data_time: 0.0399 memory: 33630 grad_norm: 3.8681 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7015 loss: 1.7015 2022/10/14 22:36:45 - mmengine - INFO - Epoch(train) [24][680/940] lr: 1.0000e-02 eta: 11:44:00 time: 0.5872 data_time: 0.0383 memory: 33630 grad_norm: 3.9414 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6854 loss: 1.6854 2022/10/14 22:36:57 - mmengine - INFO - Epoch(train) [24][700/940] lr: 1.0000e-02 eta: 11:43:47 time: 0.5831 data_time: 0.0352 memory: 33630 grad_norm: 3.8346 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.6678 loss: 1.6678 2022/10/14 22:37:09 - mmengine - INFO - Epoch(train) [24][720/940] lr: 1.0000e-02 eta: 11:43:35 time: 0.5827 data_time: 0.0367 memory: 33630 grad_norm: 4.0007 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5947 loss: 1.5947 2022/10/14 22:37:20 - mmengine - INFO - Epoch(train) [24][740/940] lr: 1.0000e-02 eta: 11:43:23 time: 0.5739 data_time: 0.0359 memory: 33630 grad_norm: 3.9128 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7003 loss: 1.7003 2022/10/14 22:37:32 - mmengine - INFO - Epoch(train) [24][760/940] lr: 1.0000e-02 eta: 11:43:10 time: 0.5741 data_time: 0.0367 memory: 33630 grad_norm: 3.9093 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.8229 loss: 1.8229 2022/10/14 22:37:44 - mmengine - INFO - Epoch(train) [24][780/940] lr: 1.0000e-02 eta: 11:42:59 time: 0.5988 data_time: 0.0371 memory: 33630 grad_norm: 3.8917 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7822 loss: 1.7822 2022/10/14 22:37:55 - mmengine - INFO - Epoch(train) [24][800/940] lr: 1.0000e-02 eta: 11:42:47 time: 0.5933 data_time: 0.0424 memory: 33630 grad_norm: 3.9045 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8630 loss: 1.8630 2022/10/14 22:38:07 - mmengine - INFO - Epoch(train) [24][820/940] lr: 1.0000e-02 eta: 11:42:36 time: 0.5993 data_time: 0.0413 memory: 33630 grad_norm: 3.9915 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7780 loss: 1.7780 2022/10/14 22:38:19 - mmengine - INFO - Epoch(train) [24][840/940] lr: 1.0000e-02 eta: 11:42:24 time: 0.5934 data_time: 0.0348 memory: 33630 grad_norm: 3.9986 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.7554 loss: 1.7554 2022/10/14 22:38:31 - mmengine - INFO - Epoch(train) [24][860/940] lr: 1.0000e-02 eta: 11:42:12 time: 0.5821 data_time: 0.0509 memory: 33630 grad_norm: 3.9330 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.5696 loss: 1.5696 2022/10/14 22:38:43 - mmengine - INFO - Epoch(train) [24][880/940] lr: 1.0000e-02 eta: 11:42:00 time: 0.5855 data_time: 0.0319 memory: 33630 grad_norm: 3.8639 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.7122 loss: 1.7122 2022/10/14 22:38:54 - mmengine - INFO - Epoch(train) [24][900/940] lr: 1.0000e-02 eta: 11:41:49 time: 0.5926 data_time: 0.0363 memory: 33630 grad_norm: 3.9194 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6551 loss: 1.6551 2022/10/14 22:39:06 - mmengine - INFO - Epoch(train) [24][920/940] lr: 1.0000e-02 eta: 11:41:36 time: 0.5787 data_time: 0.0441 memory: 33630 grad_norm: 3.8615 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7558 loss: 1.7558 2022/10/14 22:39:17 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 22:39:17 - mmengine - INFO - Epoch(train) [24][940/940] lr: 1.0000e-02 eta: 11:41:21 time: 0.5357 data_time: 0.0307 memory: 33630 grad_norm: 4.0536 top1_acc: 0.2857 top5_acc: 0.7143 loss_cls: 1.8033 loss: 1.8033 2022/10/14 22:39:17 - mmengine - INFO - Saving checkpoint at 24 epochs 2022/10/14 22:39:32 - mmengine - INFO - Epoch(val) [24][20/78] eta: 0:00:42 time: 0.7357 data_time: 0.5650 memory: 5967 2022/10/14 22:39:43 - mmengine - INFO - Epoch(val) [24][40/78] eta: 0:00:19 time: 0.5117 data_time: 0.3412 memory: 5967 2022/10/14 22:39:55 - mmengine - INFO - Epoch(val) [24][60/78] eta: 0:00:11 time: 0.6452 data_time: 0.4765 memory: 5967 2022/10/14 22:40:07 - mmengine - INFO - Epoch(val) [24][78/78] acc/top1: 0.6419 acc/top5: 0.8537 acc/mean1: 0.6418 2022/10/14 22:40:24 - mmengine - INFO - Epoch(train) [25][20/940] lr: 1.0000e-02 eta: 11:41:25 time: 0.8308 data_time: 0.2342 memory: 33630 grad_norm: 3.9116 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6942 loss: 1.6942 2022/10/14 22:40:36 - mmengine - INFO - Epoch(train) [25][40/940] lr: 1.0000e-02 eta: 11:41:15 time: 0.6210 data_time: 0.0367 memory: 33630 grad_norm: 3.9076 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6403 loss: 1.6403 2022/10/14 22:40:48 - mmengine - INFO - Epoch(train) [25][60/940] lr: 1.0000e-02 eta: 11:41:03 time: 0.5842 data_time: 0.0359 memory: 33630 grad_norm: 3.9800 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.7422 loss: 1.7422 2022/10/14 22:41:00 - mmengine - INFO - Epoch(train) [25][80/940] lr: 1.0000e-02 eta: 11:40:50 time: 0.5793 data_time: 0.0378 memory: 33630 grad_norm: 3.9644 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6600 loss: 1.6600 2022/10/14 22:41:11 - mmengine - INFO - Epoch(train) [25][100/940] lr: 1.0000e-02 eta: 11:40:38 time: 0.5879 data_time: 0.0335 memory: 33630 grad_norm: 3.8878 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7480 loss: 1.7480 2022/10/14 22:41:23 - mmengine - INFO - Epoch(train) [25][120/940] lr: 1.0000e-02 eta: 11:40:26 time: 0.5871 data_time: 0.0319 memory: 33630 grad_norm: 3.7864 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.6907 loss: 1.6907 2022/10/14 22:41:35 - mmengine - INFO - Epoch(train) [25][140/940] lr: 1.0000e-02 eta: 11:40:15 time: 0.5912 data_time: 0.0332 memory: 33630 grad_norm: 3.8261 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7352 loss: 1.7352 2022/10/14 22:41:47 - mmengine - INFO - Epoch(train) [25][160/940] lr: 1.0000e-02 eta: 11:40:02 time: 0.5779 data_time: 0.0361 memory: 33630 grad_norm: 3.8968 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6799 loss: 1.6799 2022/10/14 22:41:58 - mmengine - INFO - Epoch(train) [25][180/940] lr: 1.0000e-02 eta: 11:39:50 time: 0.5825 data_time: 0.0418 memory: 33630 grad_norm: 3.9335 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6277 loss: 1.6277 2022/10/14 22:42:10 - mmengine - INFO - Epoch(train) [25][200/940] lr: 1.0000e-02 eta: 11:39:38 time: 0.5837 data_time: 0.0380 memory: 33630 grad_norm: 3.9411 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6740 loss: 1.6740 2022/10/14 22:42:21 - mmengine - INFO - Epoch(train) [25][220/940] lr: 1.0000e-02 eta: 11:39:25 time: 0.5738 data_time: 0.0392 memory: 33630 grad_norm: 3.9792 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6915 loss: 1.6915 2022/10/14 22:42:33 - mmengine - INFO - Epoch(train) [25][240/940] lr: 1.0000e-02 eta: 11:39:13 time: 0.5854 data_time: 0.0358 memory: 33630 grad_norm: 3.9081 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7186 loss: 1.7186 2022/10/14 22:42:44 - mmengine - INFO - Epoch(train) [25][260/940] lr: 1.0000e-02 eta: 11:39:00 time: 0.5732 data_time: 0.0321 memory: 33630 grad_norm: 3.9529 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6851 loss: 1.6851 2022/10/14 22:42:56 - mmengine - INFO - Epoch(train) [25][280/940] lr: 1.0000e-02 eta: 11:38:48 time: 0.5791 data_time: 0.0363 memory: 33630 grad_norm: 3.9457 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.6721 loss: 1.6721 2022/10/14 22:43:08 - mmengine - INFO - Epoch(train) [25][300/940] lr: 1.0000e-02 eta: 11:38:35 time: 0.5759 data_time: 0.0312 memory: 33630 grad_norm: 3.9107 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.5903 loss: 1.5903 2022/10/14 22:43:19 - mmengine - INFO - Epoch(train) [25][320/940] lr: 1.0000e-02 eta: 11:38:24 time: 0.5896 data_time: 0.0362 memory: 33630 grad_norm: 3.8606 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.6473 loss: 1.6473 2022/10/14 22:43:31 - mmengine - INFO - Epoch(train) [25][340/940] lr: 1.0000e-02 eta: 11:38:12 time: 0.5909 data_time: 0.0416 memory: 33630 grad_norm: 3.7999 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.5953 loss: 1.5953 2022/10/14 22:43:43 - mmengine - INFO - Epoch(train) [25][360/940] lr: 1.0000e-02 eta: 11:37:59 time: 0.5782 data_time: 0.0385 memory: 33630 grad_norm: 3.8277 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6174 loss: 1.6174 2022/10/14 22:43:54 - mmengine - INFO - Epoch(train) [25][380/940] lr: 1.0000e-02 eta: 11:37:47 time: 0.5811 data_time: 0.0516 memory: 33630 grad_norm: 3.9327 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8118 loss: 1.8118 2022/10/14 22:44:06 - mmengine - INFO - Epoch(train) [25][400/940] lr: 1.0000e-02 eta: 11:37:35 time: 0.5859 data_time: 0.0337 memory: 33630 grad_norm: 3.9206 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.7289 loss: 1.7289 2022/10/14 22:44:18 - mmengine - INFO - Epoch(train) [25][420/940] lr: 1.0000e-02 eta: 11:37:24 time: 0.5978 data_time: 0.0403 memory: 33630 grad_norm: 3.9634 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7443 loss: 1.7443 2022/10/14 22:44:30 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 22:44:30 - mmengine - INFO - Epoch(train) [25][440/940] lr: 1.0000e-02 eta: 11:37:11 time: 0.5768 data_time: 0.0312 memory: 33630 grad_norm: 3.9463 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.7353 loss: 1.7353 2022/10/14 22:44:41 - mmengine - INFO - Epoch(train) [25][460/940] lr: 1.0000e-02 eta: 11:36:59 time: 0.5785 data_time: 0.0389 memory: 33630 grad_norm: 3.9656 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7014 loss: 1.7014 2022/10/14 22:44:53 - mmengine - INFO - Epoch(train) [25][480/940] lr: 1.0000e-02 eta: 11:36:47 time: 0.5837 data_time: 0.0351 memory: 33630 grad_norm: 3.9318 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.6171 loss: 1.6171 2022/10/14 22:45:04 - mmengine - INFO - Epoch(train) [25][500/940] lr: 1.0000e-02 eta: 11:36:34 time: 0.5714 data_time: 0.0337 memory: 33630 grad_norm: 3.9510 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.8186 loss: 1.8186 2022/10/14 22:45:16 - mmengine - INFO - Epoch(train) [25][520/940] lr: 1.0000e-02 eta: 11:36:22 time: 0.5897 data_time: 0.0342 memory: 33630 grad_norm: 3.9319 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8141 loss: 1.8141 2022/10/14 22:45:28 - mmengine - INFO - Epoch(train) [25][540/940] lr: 1.0000e-02 eta: 11:36:10 time: 0.5838 data_time: 0.0325 memory: 33630 grad_norm: 3.8748 top1_acc: 0.5625 top5_acc: 0.9688 loss_cls: 1.7134 loss: 1.7134 2022/10/14 22:45:39 - mmengine - INFO - Epoch(train) [25][560/940] lr: 1.0000e-02 eta: 11:35:58 time: 0.5833 data_time: 0.0340 memory: 33630 grad_norm: 3.8973 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.6973 loss: 1.6973 2022/10/14 22:45:51 - mmengine - INFO - Epoch(train) [25][580/940] lr: 1.0000e-02 eta: 11:35:46 time: 0.5796 data_time: 0.0306 memory: 33630 grad_norm: 3.9363 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.7630 loss: 1.7630 2022/10/14 22:46:02 - mmengine - INFO - Epoch(train) [25][600/940] lr: 1.0000e-02 eta: 11:35:33 time: 0.5718 data_time: 0.0466 memory: 33630 grad_norm: 3.9117 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6456 loss: 1.6456 2022/10/14 22:46:14 - mmengine - INFO - Epoch(train) [25][620/940] lr: 1.0000e-02 eta: 11:35:20 time: 0.5677 data_time: 0.0340 memory: 33630 grad_norm: 3.9439 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6971 loss: 1.6971 2022/10/14 22:46:26 - mmengine - INFO - Epoch(train) [25][640/940] lr: 1.0000e-02 eta: 11:35:08 time: 0.5857 data_time: 0.0299 memory: 33630 grad_norm: 3.8822 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7448 loss: 1.7448 2022/10/14 22:46:37 - mmengine - INFO - Epoch(train) [25][660/940] lr: 1.0000e-02 eta: 11:34:55 time: 0.5775 data_time: 0.0349 memory: 33630 grad_norm: 3.9169 top1_acc: 0.6562 top5_acc: 0.6875 loss_cls: 1.6877 loss: 1.6877 2022/10/14 22:46:49 - mmengine - INFO - Epoch(train) [25][680/940] lr: 1.0000e-02 eta: 11:34:43 time: 0.5802 data_time: 0.0362 memory: 33630 grad_norm: 3.9499 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.7660 loss: 1.7660 2022/10/14 22:47:01 - mmengine - INFO - Epoch(train) [25][700/940] lr: 1.0000e-02 eta: 11:34:31 time: 0.5924 data_time: 0.0370 memory: 33630 grad_norm: 4.0004 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8405 loss: 1.8405 2022/10/14 22:47:12 - mmengine - INFO - Epoch(train) [25][720/940] lr: 1.0000e-02 eta: 11:34:19 time: 0.5827 data_time: 0.0402 memory: 33630 grad_norm: 3.9715 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.7270 loss: 1.7270 2022/10/14 22:47:24 - mmengine - INFO - Epoch(train) [25][740/940] lr: 1.0000e-02 eta: 11:34:07 time: 0.5870 data_time: 0.0322 memory: 33630 grad_norm: 3.9368 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.6380 loss: 1.6380 2022/10/14 22:47:36 - mmengine - INFO - Epoch(train) [25][760/940] lr: 1.0000e-02 eta: 11:33:55 time: 0.5814 data_time: 0.0372 memory: 33630 grad_norm: 3.8418 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7365 loss: 1.7365 2022/10/14 22:47:47 - mmengine - INFO - Epoch(train) [25][780/940] lr: 1.0000e-02 eta: 11:33:44 time: 0.5967 data_time: 0.0428 memory: 33630 grad_norm: 3.9402 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.7218 loss: 1.7218 2022/10/14 22:47:59 - mmengine - INFO - Epoch(train) [25][800/940] lr: 1.0000e-02 eta: 11:33:32 time: 0.5884 data_time: 0.0365 memory: 33630 grad_norm: 3.9863 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6125 loss: 1.6125 2022/10/14 22:48:11 - mmengine - INFO - Epoch(train) [25][820/940] lr: 1.0000e-02 eta: 11:33:20 time: 0.5822 data_time: 0.0326 memory: 33630 grad_norm: 3.8775 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5868 loss: 1.5868 2022/10/14 22:48:23 - mmengine - INFO - Epoch(train) [25][840/940] lr: 1.0000e-02 eta: 11:33:08 time: 0.5859 data_time: 0.0415 memory: 33630 grad_norm: 3.8477 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.8006 loss: 1.8006 2022/10/14 22:48:34 - mmengine - INFO - Epoch(train) [25][860/940] lr: 1.0000e-02 eta: 11:32:56 time: 0.5841 data_time: 0.0309 memory: 33630 grad_norm: 3.8649 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.7010 loss: 1.7010 2022/10/14 22:48:46 - mmengine - INFO - Epoch(train) [25][880/940] lr: 1.0000e-02 eta: 11:32:44 time: 0.5854 data_time: 0.0393 memory: 33630 grad_norm: 3.8985 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.6747 loss: 1.6747 2022/10/14 22:48:58 - mmengine - INFO - Epoch(train) [25][900/940] lr: 1.0000e-02 eta: 11:32:32 time: 0.5900 data_time: 0.0347 memory: 33630 grad_norm: 3.8910 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7338 loss: 1.7338 2022/10/14 22:49:09 - mmengine - INFO - Epoch(train) [25][920/940] lr: 1.0000e-02 eta: 11:32:20 time: 0.5798 data_time: 0.0407 memory: 33630 grad_norm: 3.9379 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.7544 loss: 1.7544 2022/10/14 22:49:20 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 22:49:20 - mmengine - INFO - Epoch(train) [25][940/940] lr: 1.0000e-02 eta: 11:32:05 time: 0.5432 data_time: 0.0381 memory: 33630 grad_norm: 4.1324 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.8121 loss: 1.8121 2022/10/14 22:49:34 - mmengine - INFO - Epoch(val) [25][20/78] eta: 0:00:41 time: 0.7088 data_time: 0.5373 memory: 5967 2022/10/14 22:49:46 - mmengine - INFO - Epoch(val) [25][40/78] eta: 0:00:20 time: 0.5516 data_time: 0.3827 memory: 5967 2022/10/14 22:49:58 - mmengine - INFO - Epoch(val) [25][60/78] eta: 0:00:11 time: 0.6295 data_time: 0.4578 memory: 5967 2022/10/14 22:50:10 - mmengine - INFO - Epoch(val) [25][78/78] acc/top1: 0.6426 acc/top5: 0.8524 acc/mean1: 0.6424 2022/10/14 22:50:10 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_23.pth is removed 2022/10/14 22:50:11 - mmengine - INFO - The best checkpoint with 0.6426 acc/top1 at 25 epoch is saved to best_acc/top1_epoch_25.pth. 2022/10/14 22:50:27 - mmengine - INFO - Epoch(train) [26][20/940] lr: 1.0000e-02 eta: 11:32:05 time: 0.7869 data_time: 0.2405 memory: 33630 grad_norm: 3.9121 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6384 loss: 1.6384 2022/10/14 22:50:39 - mmengine - INFO - Epoch(train) [26][40/940] lr: 1.0000e-02 eta: 11:31:54 time: 0.6042 data_time: 0.0328 memory: 33630 grad_norm: 3.8784 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7708 loss: 1.7708 2022/10/14 22:50:51 - mmengine - INFO - Epoch(train) [26][60/940] lr: 1.0000e-02 eta: 11:31:42 time: 0.5874 data_time: 0.0355 memory: 33630 grad_norm: 3.8895 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6400 loss: 1.6400 2022/10/14 22:51:02 - mmengine - INFO - Epoch(train) [26][80/940] lr: 1.0000e-02 eta: 11:31:30 time: 0.5830 data_time: 0.0350 memory: 33630 grad_norm: 3.8882 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6363 loss: 1.6363 2022/10/14 22:51:14 - mmengine - INFO - Epoch(train) [26][100/940] lr: 1.0000e-02 eta: 11:31:18 time: 0.5902 data_time: 0.0360 memory: 33630 grad_norm: 3.9521 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.6409 loss: 1.6409 2022/10/14 22:51:26 - mmengine - INFO - Epoch(train) [26][120/940] lr: 1.0000e-02 eta: 11:31:07 time: 0.5907 data_time: 0.0319 memory: 33630 grad_norm: 3.8268 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7034 loss: 1.7034 2022/10/14 22:51:38 - mmengine - INFO - Epoch(train) [26][140/940] lr: 1.0000e-02 eta: 11:30:55 time: 0.5907 data_time: 0.0312 memory: 33630 grad_norm: 3.9365 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7124 loss: 1.7124 2022/10/14 22:51:49 - mmengine - INFO - Epoch(train) [26][160/940] lr: 1.0000e-02 eta: 11:30:43 time: 0.5802 data_time: 0.0406 memory: 33630 grad_norm: 3.8577 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.6263 loss: 1.6263 2022/10/14 22:52:01 - mmengine - INFO - Epoch(train) [26][180/940] lr: 1.0000e-02 eta: 11:30:31 time: 0.5854 data_time: 0.0331 memory: 33630 grad_norm: 3.9221 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6230 loss: 1.6230 2022/10/14 22:52:13 - mmengine - INFO - Epoch(train) [26][200/940] lr: 1.0000e-02 eta: 11:30:18 time: 0.5774 data_time: 0.0328 memory: 33630 grad_norm: 3.9979 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6695 loss: 1.6695 2022/10/14 22:52:24 - mmengine - INFO - Epoch(train) [26][220/940] lr: 1.0000e-02 eta: 11:30:06 time: 0.5796 data_time: 0.0347 memory: 33630 grad_norm: 3.8025 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6399 loss: 1.6399 2022/10/14 22:52:36 - mmengine - INFO - Epoch(train) [26][240/940] lr: 1.0000e-02 eta: 11:29:53 time: 0.5788 data_time: 0.0422 memory: 33630 grad_norm: 3.8953 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5278 loss: 1.5278 2022/10/14 22:52:47 - mmengine - INFO - Epoch(train) [26][260/940] lr: 1.0000e-02 eta: 11:29:42 time: 0.5886 data_time: 0.0377 memory: 33630 grad_norm: 3.8720 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6372 loss: 1.6372 2022/10/14 22:52:59 - mmengine - INFO - Epoch(train) [26][280/940] lr: 1.0000e-02 eta: 11:29:30 time: 0.5940 data_time: 0.0380 memory: 33630 grad_norm: 3.9880 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.7820 loss: 1.7820 2022/10/14 22:53:11 - mmengine - INFO - Epoch(train) [26][300/940] lr: 1.0000e-02 eta: 11:29:18 time: 0.5817 data_time: 0.0294 memory: 33630 grad_norm: 3.9343 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6467 loss: 1.6467 2022/10/14 22:53:23 - mmengine - INFO - Epoch(train) [26][320/940] lr: 1.0000e-02 eta: 11:29:06 time: 0.5855 data_time: 0.0362 memory: 33630 grad_norm: 3.9132 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5491 loss: 1.5491 2022/10/14 22:53:34 - mmengine - INFO - Epoch(train) [26][340/940] lr: 1.0000e-02 eta: 11:28:53 time: 0.5713 data_time: 0.0337 memory: 33630 grad_norm: 3.8814 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.5823 loss: 1.5823 2022/10/14 22:53:46 - mmengine - INFO - Epoch(train) [26][360/940] lr: 1.0000e-02 eta: 11:28:42 time: 0.5944 data_time: 0.0391 memory: 33630 grad_norm: 3.8684 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7299 loss: 1.7299 2022/10/14 22:53:58 - mmengine - INFO - Epoch(train) [26][380/940] lr: 1.0000e-02 eta: 11:28:29 time: 0.5800 data_time: 0.0354 memory: 33630 grad_norm: 3.9310 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6451 loss: 1.6451 2022/10/14 22:54:09 - mmengine - INFO - Epoch(train) [26][400/940] lr: 1.0000e-02 eta: 11:28:17 time: 0.5849 data_time: 0.0327 memory: 33630 grad_norm: 3.8846 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.6277 loss: 1.6277 2022/10/14 22:54:21 - mmengine - INFO - Epoch(train) [26][420/940] lr: 1.0000e-02 eta: 11:28:05 time: 0.5813 data_time: 0.0337 memory: 33630 grad_norm: 3.9114 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.7159 loss: 1.7159 2022/10/14 22:54:33 - mmengine - INFO - Epoch(train) [26][440/940] lr: 1.0000e-02 eta: 11:27:53 time: 0.5820 data_time: 0.0306 memory: 33630 grad_norm: 3.8843 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7182 loss: 1.7182 2022/10/14 22:54:44 - mmengine - INFO - Epoch(train) [26][460/940] lr: 1.0000e-02 eta: 11:27:41 time: 0.5840 data_time: 0.0307 memory: 33630 grad_norm: 3.9617 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7315 loss: 1.7315 2022/10/14 22:54:56 - mmengine - INFO - Epoch(train) [26][480/940] lr: 1.0000e-02 eta: 11:27:29 time: 0.5852 data_time: 0.0451 memory: 33630 grad_norm: 3.9468 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.7465 loss: 1.7465 2022/10/14 22:55:08 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 22:55:08 - mmengine - INFO - Epoch(train) [26][500/940] lr: 1.0000e-02 eta: 11:27:17 time: 0.5954 data_time: 0.0364 memory: 33630 grad_norm: 3.9896 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6881 loss: 1.6881 2022/10/14 22:55:20 - mmengine - INFO - Epoch(train) [26][520/940] lr: 1.0000e-02 eta: 11:27:05 time: 0.5821 data_time: 0.0355 memory: 33630 grad_norm: 3.9291 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.7155 loss: 1.7155 2022/10/14 22:55:31 - mmengine - INFO - Epoch(train) [26][540/940] lr: 1.0000e-02 eta: 11:26:52 time: 0.5744 data_time: 0.0322 memory: 33630 grad_norm: 4.0437 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7037 loss: 1.7037 2022/10/14 22:55:43 - mmengine - INFO - Epoch(train) [26][560/940] lr: 1.0000e-02 eta: 11:26:40 time: 0.5852 data_time: 0.0413 memory: 33630 grad_norm: 3.9643 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8138 loss: 1.8138 2022/10/14 22:55:54 - mmengine - INFO - Epoch(train) [26][580/940] lr: 1.0000e-02 eta: 11:26:29 time: 0.5884 data_time: 0.0337 memory: 33630 grad_norm: 3.9541 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.8527 loss: 1.8527 2022/10/14 22:56:06 - mmengine - INFO - Epoch(train) [26][600/940] lr: 1.0000e-02 eta: 11:26:17 time: 0.5915 data_time: 0.0397 memory: 33630 grad_norm: 3.9171 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.5205 loss: 1.5205 2022/10/14 22:56:18 - mmengine - INFO - Epoch(train) [26][620/940] lr: 1.0000e-02 eta: 11:26:05 time: 0.5913 data_time: 0.0438 memory: 33630 grad_norm: 4.0012 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7254 loss: 1.7254 2022/10/14 22:56:30 - mmengine - INFO - Epoch(train) [26][640/940] lr: 1.0000e-02 eta: 11:25:53 time: 0.5865 data_time: 0.0329 memory: 33630 grad_norm: 3.9160 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6340 loss: 1.6340 2022/10/14 22:56:42 - mmengine - INFO - Epoch(train) [26][660/940] lr: 1.0000e-02 eta: 11:25:41 time: 0.5852 data_time: 0.0319 memory: 33630 grad_norm: 3.8526 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.6389 loss: 1.6389 2022/10/14 22:56:53 - mmengine - INFO - Epoch(train) [26][680/940] lr: 1.0000e-02 eta: 11:25:29 time: 0.5844 data_time: 0.0380 memory: 33630 grad_norm: 3.9299 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6611 loss: 1.6611 2022/10/14 22:57:05 - mmengine - INFO - Epoch(train) [26][700/940] lr: 1.0000e-02 eta: 11:25:17 time: 0.5808 data_time: 0.0408 memory: 33630 grad_norm: 3.9329 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7624 loss: 1.7624 2022/10/14 22:57:17 - mmengine - INFO - Epoch(train) [26][720/940] lr: 1.0000e-02 eta: 11:25:06 time: 0.5995 data_time: 0.0398 memory: 33630 grad_norm: 3.8666 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.6930 loss: 1.6930 2022/10/14 22:57:28 - mmengine - INFO - Epoch(train) [26][740/940] lr: 1.0000e-02 eta: 11:24:53 time: 0.5771 data_time: 0.0353 memory: 33630 grad_norm: 4.0036 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.7635 loss: 1.7635 2022/10/14 22:57:40 - mmengine - INFO - Epoch(train) [26][760/940] lr: 1.0000e-02 eta: 11:24:42 time: 0.5862 data_time: 0.0376 memory: 33630 grad_norm: 3.8696 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.5592 loss: 1.5592 2022/10/14 22:57:52 - mmengine - INFO - Epoch(train) [26][780/940] lr: 1.0000e-02 eta: 11:24:30 time: 0.5876 data_time: 0.0446 memory: 33630 grad_norm: 3.9566 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.7146 loss: 1.7146 2022/10/14 22:58:04 - mmengine - INFO - Epoch(train) [26][800/940] lr: 1.0000e-02 eta: 11:24:18 time: 0.5832 data_time: 0.0317 memory: 33630 grad_norm: 3.9895 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7839 loss: 1.7839 2022/10/14 22:58:15 - mmengine - INFO - Epoch(train) [26][820/940] lr: 1.0000e-02 eta: 11:24:05 time: 0.5822 data_time: 0.0362 memory: 33630 grad_norm: 3.9645 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7071 loss: 1.7071 2022/10/14 22:58:27 - mmengine - INFO - Epoch(train) [26][840/940] lr: 1.0000e-02 eta: 11:23:53 time: 0.5856 data_time: 0.0392 memory: 33630 grad_norm: 3.9127 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6853 loss: 1.6853 2022/10/14 22:58:39 - mmengine - INFO - Epoch(train) [26][860/940] lr: 1.0000e-02 eta: 11:23:42 time: 0.5892 data_time: 0.0325 memory: 33630 grad_norm: 3.9151 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.8745 loss: 1.8745 2022/10/14 22:58:50 - mmengine - INFO - Epoch(train) [26][880/940] lr: 1.0000e-02 eta: 11:23:30 time: 0.5869 data_time: 0.0379 memory: 33630 grad_norm: 3.8856 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6895 loss: 1.6895 2022/10/14 22:59:02 - mmengine - INFO - Epoch(train) [26][900/940] lr: 1.0000e-02 eta: 11:23:18 time: 0.5914 data_time: 0.0347 memory: 33630 grad_norm: 3.9830 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.7034 loss: 1.7034 2022/10/14 22:59:14 - mmengine - INFO - Epoch(train) [26][920/940] lr: 1.0000e-02 eta: 11:23:06 time: 0.5817 data_time: 0.0316 memory: 33630 grad_norm: 3.9907 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7346 loss: 1.7346 2022/10/14 22:59:25 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 22:59:25 - mmengine - INFO - Epoch(train) [26][940/940] lr: 1.0000e-02 eta: 11:22:51 time: 0.5360 data_time: 0.0288 memory: 33630 grad_norm: 4.1250 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.7673 loss: 1.7673 2022/10/14 22:59:39 - mmengine - INFO - Epoch(val) [26][20/78] eta: 0:00:41 time: 0.7230 data_time: 0.5483 memory: 5967 2022/10/14 22:59:49 - mmengine - INFO - Epoch(val) [26][40/78] eta: 0:00:18 time: 0.4923 data_time: 0.3255 memory: 5967 2022/10/14 23:00:02 - mmengine - INFO - Epoch(val) [26][60/78] eta: 0:00:11 time: 0.6523 data_time: 0.4839 memory: 5967 2022/10/14 23:00:14 - mmengine - INFO - Epoch(val) [26][78/78] acc/top1: 0.6363 acc/top5: 0.8537 acc/mean1: 0.6362 2022/10/14 23:00:31 - mmengine - INFO - Epoch(train) [27][20/940] lr: 1.0000e-02 eta: 11:22:54 time: 0.8426 data_time: 0.2507 memory: 33630 grad_norm: 3.8949 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.6526 loss: 1.6526 2022/10/14 23:00:42 - mmengine - INFO - Epoch(train) [27][40/940] lr: 1.0000e-02 eta: 11:22:41 time: 0.5711 data_time: 0.0290 memory: 33630 grad_norm: 3.8945 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7243 loss: 1.7243 2022/10/14 23:00:54 - mmengine - INFO - Epoch(train) [27][60/940] lr: 1.0000e-02 eta: 11:22:30 time: 0.5999 data_time: 0.0322 memory: 33630 grad_norm: 3.9757 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7369 loss: 1.7369 2022/10/14 23:01:06 - mmengine - INFO - Epoch(train) [27][80/940] lr: 1.0000e-02 eta: 11:22:17 time: 0.5801 data_time: 0.0336 memory: 33630 grad_norm: 3.8947 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6463 loss: 1.6463 2022/10/14 23:01:18 - mmengine - INFO - Epoch(train) [27][100/940] lr: 1.0000e-02 eta: 11:22:06 time: 0.5940 data_time: 0.0351 memory: 33630 grad_norm: 3.9690 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.6263 loss: 1.6263 2022/10/14 23:01:30 - mmengine - INFO - Epoch(train) [27][120/940] lr: 1.0000e-02 eta: 11:21:54 time: 0.5865 data_time: 0.0369 memory: 33630 grad_norm: 3.9472 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7268 loss: 1.7268 2022/10/14 23:01:42 - mmengine - INFO - Epoch(train) [27][140/940] lr: 1.0000e-02 eta: 11:21:43 time: 0.5956 data_time: 0.0318 memory: 33630 grad_norm: 3.8448 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6977 loss: 1.6977 2022/10/14 23:01:54 - mmengine - INFO - Epoch(train) [27][160/940] lr: 1.0000e-02 eta: 11:21:31 time: 0.6014 data_time: 0.0501 memory: 33630 grad_norm: 3.9293 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6527 loss: 1.6527 2022/10/14 23:02:06 - mmengine - INFO - Epoch(train) [27][180/940] lr: 1.0000e-02 eta: 11:21:20 time: 0.6003 data_time: 0.0344 memory: 33630 grad_norm: 3.8672 top1_acc: 0.6562 top5_acc: 0.6875 loss_cls: 1.6164 loss: 1.6164 2022/10/14 23:02:17 - mmengine - INFO - Epoch(train) [27][200/940] lr: 1.0000e-02 eta: 11:21:08 time: 0.5877 data_time: 0.0298 memory: 33630 grad_norm: 3.9667 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6028 loss: 1.6028 2022/10/14 23:02:29 - mmengine - INFO - Epoch(train) [27][220/940] lr: 1.0000e-02 eta: 11:20:56 time: 0.5823 data_time: 0.0365 memory: 33630 grad_norm: 3.9060 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6321 loss: 1.6321 2022/10/14 23:02:41 - mmengine - INFO - Epoch(train) [27][240/940] lr: 1.0000e-02 eta: 11:20:44 time: 0.5781 data_time: 0.0340 memory: 33630 grad_norm: 3.9941 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.7510 loss: 1.7510 2022/10/14 23:02:52 - mmengine - INFO - Epoch(train) [27][260/940] lr: 1.0000e-02 eta: 11:20:32 time: 0.5809 data_time: 0.0413 memory: 33630 grad_norm: 3.9643 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.5710 loss: 1.5710 2022/10/14 23:03:04 - mmengine - INFO - Epoch(train) [27][280/940] lr: 1.0000e-02 eta: 11:20:19 time: 0.5772 data_time: 0.0359 memory: 33630 grad_norm: 3.9075 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7131 loss: 1.7131 2022/10/14 23:03:15 - mmengine - INFO - Epoch(train) [27][300/940] lr: 1.0000e-02 eta: 11:20:07 time: 0.5814 data_time: 0.0316 memory: 33630 grad_norm: 3.9336 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7919 loss: 1.7919 2022/10/14 23:03:27 - mmengine - INFO - Epoch(train) [27][320/940] lr: 1.0000e-02 eta: 11:19:55 time: 0.5942 data_time: 0.0299 memory: 33630 grad_norm: 3.9196 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.6263 loss: 1.6263 2022/10/14 23:03:39 - mmengine - INFO - Epoch(train) [27][340/940] lr: 1.0000e-02 eta: 11:19:43 time: 0.5753 data_time: 0.0334 memory: 33630 grad_norm: 3.9179 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6229 loss: 1.6229 2022/10/14 23:03:51 - mmengine - INFO - Epoch(train) [27][360/940] lr: 1.0000e-02 eta: 11:19:31 time: 0.5912 data_time: 0.0371 memory: 33630 grad_norm: 3.8625 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7918 loss: 1.7918 2022/10/14 23:04:02 - mmengine - INFO - Epoch(train) [27][380/940] lr: 1.0000e-02 eta: 11:19:19 time: 0.5811 data_time: 0.0363 memory: 33630 grad_norm: 3.9446 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6495 loss: 1.6495 2022/10/14 23:04:14 - mmengine - INFO - Epoch(train) [27][400/940] lr: 1.0000e-02 eta: 11:19:07 time: 0.5850 data_time: 0.0388 memory: 33630 grad_norm: 3.9566 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6490 loss: 1.6490 2022/10/14 23:04:26 - mmengine - INFO - Epoch(train) [27][420/940] lr: 1.0000e-02 eta: 11:18:55 time: 0.5952 data_time: 0.0348 memory: 33630 grad_norm: 3.9912 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7043 loss: 1.7043 2022/10/14 23:04:37 - mmengine - INFO - Epoch(train) [27][440/940] lr: 1.0000e-02 eta: 11:18:43 time: 0.5799 data_time: 0.0370 memory: 33630 grad_norm: 3.9137 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.6995 loss: 1.6995 2022/10/14 23:04:49 - mmengine - INFO - Epoch(train) [27][460/940] lr: 1.0000e-02 eta: 11:18:31 time: 0.5784 data_time: 0.0323 memory: 33630 grad_norm: 3.9061 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7960 loss: 1.7960 2022/10/14 23:05:01 - mmengine - INFO - Epoch(train) [27][480/940] lr: 1.0000e-02 eta: 11:18:19 time: 0.5890 data_time: 0.0375 memory: 33630 grad_norm: 4.0151 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6809 loss: 1.6809 2022/10/14 23:05:12 - mmengine - INFO - Epoch(train) [27][500/940] lr: 1.0000e-02 eta: 11:18:07 time: 0.5840 data_time: 0.0335 memory: 33630 grad_norm: 3.8729 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7277 loss: 1.7277 2022/10/14 23:05:24 - mmengine - INFO - Epoch(train) [27][520/940] lr: 1.0000e-02 eta: 11:17:55 time: 0.5856 data_time: 0.0386 memory: 33630 grad_norm: 3.9941 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.7780 loss: 1.7780 2022/10/14 23:05:36 - mmengine - INFO - Epoch(train) [27][540/940] lr: 1.0000e-02 eta: 11:17:43 time: 0.5929 data_time: 0.0506 memory: 33630 grad_norm: 3.9411 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6988 loss: 1.6988 2022/10/14 23:05:48 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 23:05:48 - mmengine - INFO - Epoch(train) [27][560/940] lr: 1.0000e-02 eta: 11:17:31 time: 0.5824 data_time: 0.0336 memory: 33630 grad_norm: 3.8749 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6946 loss: 1.6946 2022/10/14 23:05:59 - mmengine - INFO - Epoch(train) [27][580/940] lr: 1.0000e-02 eta: 11:17:19 time: 0.5856 data_time: 0.0341 memory: 33630 grad_norm: 3.8658 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6444 loss: 1.6444 2022/10/14 23:06:11 - mmengine - INFO - Epoch(train) [27][600/940] lr: 1.0000e-02 eta: 11:17:07 time: 0.5812 data_time: 0.0351 memory: 33630 grad_norm: 3.9678 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6632 loss: 1.6632 2022/10/14 23:06:23 - mmengine - INFO - Epoch(train) [27][620/940] lr: 1.0000e-02 eta: 11:16:55 time: 0.5862 data_time: 0.0342 memory: 33630 grad_norm: 4.0234 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.8280 loss: 1.8280 2022/10/14 23:06:34 - mmengine - INFO - Epoch(train) [27][640/940] lr: 1.0000e-02 eta: 11:16:43 time: 0.5780 data_time: 0.0333 memory: 33630 grad_norm: 3.8876 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5679 loss: 1.5679 2022/10/14 23:06:46 - mmengine - INFO - Epoch(train) [27][660/940] lr: 1.0000e-02 eta: 11:16:31 time: 0.5917 data_time: 0.0344 memory: 33630 grad_norm: 3.9908 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.6149 loss: 1.6149 2022/10/14 23:06:58 - mmengine - INFO - Epoch(train) [27][680/940] lr: 1.0000e-02 eta: 11:16:19 time: 0.5830 data_time: 0.0388 memory: 33630 grad_norm: 3.9899 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7811 loss: 1.7811 2022/10/14 23:07:09 - mmengine - INFO - Epoch(train) [27][700/940] lr: 1.0000e-02 eta: 11:16:07 time: 0.5796 data_time: 0.0345 memory: 33630 grad_norm: 3.9081 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.7205 loss: 1.7205 2022/10/14 23:07:21 - mmengine - INFO - Epoch(train) [27][720/940] lr: 1.0000e-02 eta: 11:15:55 time: 0.5902 data_time: 0.0320 memory: 33630 grad_norm: 4.0625 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.6564 loss: 1.6564 2022/10/14 23:07:33 - mmengine - INFO - Epoch(train) [27][740/940] lr: 1.0000e-02 eta: 11:15:43 time: 0.5819 data_time: 0.0318 memory: 33630 grad_norm: 3.8910 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.7134 loss: 1.7134 2022/10/14 23:07:44 - mmengine - INFO - Epoch(train) [27][760/940] lr: 1.0000e-02 eta: 11:15:31 time: 0.5841 data_time: 0.0313 memory: 33630 grad_norm: 3.8053 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.5631 loss: 1.5631 2022/10/14 23:07:56 - mmengine - INFO - Epoch(train) [27][780/940] lr: 1.0000e-02 eta: 11:15:18 time: 0.5804 data_time: 0.0372 memory: 33630 grad_norm: 4.0152 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7764 loss: 1.7764 2022/10/14 23:08:08 - mmengine - INFO - Epoch(train) [27][800/940] lr: 1.0000e-02 eta: 11:15:07 time: 0.5949 data_time: 0.0309 memory: 33630 grad_norm: 4.0431 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7141 loss: 1.7141 2022/10/14 23:08:20 - mmengine - INFO - Epoch(train) [27][820/940] lr: 1.0000e-02 eta: 11:14:55 time: 0.5837 data_time: 0.0355 memory: 33630 grad_norm: 3.9770 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4774 loss: 1.4774 2022/10/14 23:08:31 - mmengine - INFO - Epoch(train) [27][840/940] lr: 1.0000e-02 eta: 11:14:43 time: 0.5827 data_time: 0.0356 memory: 33630 grad_norm: 4.0118 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.7420 loss: 1.7420 2022/10/14 23:08:43 - mmengine - INFO - Epoch(train) [27][860/940] lr: 1.0000e-02 eta: 11:14:31 time: 0.5898 data_time: 0.0368 memory: 33630 grad_norm: 3.9376 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7111 loss: 1.7111 2022/10/14 23:08:55 - mmengine - INFO - Epoch(train) [27][880/940] lr: 1.0000e-02 eta: 11:14:19 time: 0.5788 data_time: 0.0371 memory: 33630 grad_norm: 4.1079 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.6255 loss: 1.6255 2022/10/14 23:09:06 - mmengine - INFO - Epoch(train) [27][900/940] lr: 1.0000e-02 eta: 11:14:07 time: 0.5836 data_time: 0.0430 memory: 33630 grad_norm: 3.9154 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7125 loss: 1.7125 2022/10/14 23:09:18 - mmengine - INFO - Epoch(train) [27][920/940] lr: 1.0000e-02 eta: 11:13:54 time: 0.5730 data_time: 0.0354 memory: 33630 grad_norm: 3.9294 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6559 loss: 1.6559 2022/10/14 23:09:29 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 23:09:29 - mmengine - INFO - Epoch(train) [27][940/940] lr: 1.0000e-02 eta: 11:13:39 time: 0.5343 data_time: 0.0349 memory: 33630 grad_norm: 4.1989 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.7255 loss: 1.7255 2022/10/14 23:09:29 - mmengine - INFO - Saving checkpoint at 27 epochs 2022/10/14 23:09:44 - mmengine - INFO - Epoch(val) [27][20/78] eta: 0:00:42 time: 0.7352 data_time: 0.5656 memory: 5967 2022/10/14 23:09:54 - mmengine - INFO - Epoch(val) [27][40/78] eta: 0:00:18 time: 0.4862 data_time: 0.3147 memory: 5967 2022/10/14 23:10:09 - mmengine - INFO - Epoch(val) [27][60/78] eta: 0:00:13 time: 0.7620 data_time: 0.5943 memory: 5967 2022/10/14 23:10:20 - mmengine - INFO - Epoch(val) [27][78/78] acc/top1: 0.6402 acc/top5: 0.8515 acc/mean1: 0.6401 2022/10/14 23:10:37 - mmengine - INFO - Epoch(train) [28][20/940] lr: 1.0000e-02 eta: 11:13:42 time: 0.8571 data_time: 0.2999 memory: 33630 grad_norm: 3.9252 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.6569 loss: 1.6569 2022/10/14 23:10:48 - mmengine - INFO - Epoch(train) [28][40/940] lr: 1.0000e-02 eta: 11:13:29 time: 0.5770 data_time: 0.0323 memory: 33630 grad_norm: 3.8563 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7374 loss: 1.7374 2022/10/14 23:11:00 - mmengine - INFO - Epoch(train) [28][60/940] lr: 1.0000e-02 eta: 11:13:18 time: 0.6022 data_time: 0.0395 memory: 33630 grad_norm: 3.8332 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7504 loss: 1.7504 2022/10/14 23:11:12 - mmengine - INFO - Epoch(train) [28][80/940] lr: 1.0000e-02 eta: 11:13:06 time: 0.5865 data_time: 0.0351 memory: 33630 grad_norm: 3.9735 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7338 loss: 1.7338 2022/10/14 23:11:24 - mmengine - INFO - Epoch(train) [28][100/940] lr: 1.0000e-02 eta: 11:12:54 time: 0.5850 data_time: 0.0322 memory: 33630 grad_norm: 3.9244 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.6332 loss: 1.6332 2022/10/14 23:11:35 - mmengine - INFO - Epoch(train) [28][120/940] lr: 1.0000e-02 eta: 11:12:42 time: 0.5845 data_time: 0.0399 memory: 33630 grad_norm: 3.9136 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6143 loss: 1.6143 2022/10/14 23:11:47 - mmengine - INFO - Epoch(train) [28][140/940] lr: 1.0000e-02 eta: 11:12:30 time: 0.5833 data_time: 0.0316 memory: 33630 grad_norm: 3.9173 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5824 loss: 1.5824 2022/10/14 23:11:59 - mmengine - INFO - Epoch(train) [28][160/940] lr: 1.0000e-02 eta: 11:12:18 time: 0.5778 data_time: 0.0417 memory: 33630 grad_norm: 3.9112 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4848 loss: 1.4848 2022/10/14 23:12:11 - mmengine - INFO - Epoch(train) [28][180/940] lr: 1.0000e-02 eta: 11:12:06 time: 0.5922 data_time: 0.0362 memory: 33630 grad_norm: 3.9308 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5642 loss: 1.5642 2022/10/14 23:12:22 - mmengine - INFO - Epoch(train) [28][200/940] lr: 1.0000e-02 eta: 11:11:54 time: 0.5808 data_time: 0.0365 memory: 33630 grad_norm: 3.9592 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6525 loss: 1.6525 2022/10/14 23:12:34 - mmengine - INFO - Epoch(train) [28][220/940] lr: 1.0000e-02 eta: 11:11:42 time: 0.5838 data_time: 0.0332 memory: 33630 grad_norm: 3.9508 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8064 loss: 1.8064 2022/10/14 23:12:46 - mmengine - INFO - Epoch(train) [28][240/940] lr: 1.0000e-02 eta: 11:11:30 time: 0.5864 data_time: 0.0361 memory: 33630 grad_norm: 3.9002 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.6636 loss: 1.6636 2022/10/14 23:12:57 - mmengine - INFO - Epoch(train) [28][260/940] lr: 1.0000e-02 eta: 11:11:18 time: 0.5800 data_time: 0.0326 memory: 33630 grad_norm: 3.8912 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7599 loss: 1.7599 2022/10/14 23:13:09 - mmengine - INFO - Epoch(train) [28][280/940] lr: 1.0000e-02 eta: 11:11:05 time: 0.5726 data_time: 0.0317 memory: 33630 grad_norm: 3.9759 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.5471 loss: 1.5471 2022/10/14 23:13:20 - mmengine - INFO - Epoch(train) [28][300/940] lr: 1.0000e-02 eta: 11:10:53 time: 0.5857 data_time: 0.0475 memory: 33630 grad_norm: 3.9162 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.4788 loss: 1.4788 2022/10/14 23:13:32 - mmengine - INFO - Epoch(train) [28][320/940] lr: 1.0000e-02 eta: 11:10:41 time: 0.5846 data_time: 0.0341 memory: 33630 grad_norm: 3.9533 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6360 loss: 1.6360 2022/10/14 23:13:44 - mmengine - INFO - Epoch(train) [28][340/940] lr: 1.0000e-02 eta: 11:10:30 time: 0.5954 data_time: 0.0352 memory: 33630 grad_norm: 3.8817 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5969 loss: 1.5969 2022/10/14 23:13:55 - mmengine - INFO - Epoch(train) [28][360/940] lr: 1.0000e-02 eta: 11:10:17 time: 0.5682 data_time: 0.0313 memory: 33630 grad_norm: 3.9082 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6902 loss: 1.6902 2022/10/14 23:14:07 - mmengine - INFO - Epoch(train) [28][380/940] lr: 1.0000e-02 eta: 11:10:04 time: 0.5788 data_time: 0.0359 memory: 33630 grad_norm: 3.9201 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.6850 loss: 1.6850 2022/10/14 23:14:19 - mmengine - INFO - Epoch(train) [28][400/940] lr: 1.0000e-02 eta: 11:09:53 time: 0.5945 data_time: 0.0351 memory: 33630 grad_norm: 3.9538 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6355 loss: 1.6355 2022/10/14 23:14:30 - mmengine - INFO - Epoch(train) [28][420/940] lr: 1.0000e-02 eta: 11:09:41 time: 0.5856 data_time: 0.0368 memory: 33630 grad_norm: 3.9206 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.7179 loss: 1.7179 2022/10/14 23:14:42 - mmengine - INFO - Epoch(train) [28][440/940] lr: 1.0000e-02 eta: 11:09:29 time: 0.5794 data_time: 0.0374 memory: 33630 grad_norm: 3.9625 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6689 loss: 1.6689 2022/10/14 23:14:54 - mmengine - INFO - Epoch(train) [28][460/940] lr: 1.0000e-02 eta: 11:09:17 time: 0.5966 data_time: 0.0314 memory: 33630 grad_norm: 3.9370 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.7852 loss: 1.7852 2022/10/14 23:15:06 - mmengine - INFO - Epoch(train) [28][480/940] lr: 1.0000e-02 eta: 11:09:05 time: 0.5894 data_time: 0.0359 memory: 33630 grad_norm: 3.9563 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5917 loss: 1.5917 2022/10/14 23:15:17 - mmengine - INFO - Epoch(train) [28][500/940] lr: 1.0000e-02 eta: 11:08:53 time: 0.5782 data_time: 0.0352 memory: 33630 grad_norm: 3.9601 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.6963 loss: 1.6963 2022/10/14 23:15:29 - mmengine - INFO - Epoch(train) [28][520/940] lr: 1.0000e-02 eta: 11:08:41 time: 0.5808 data_time: 0.0339 memory: 33630 grad_norm: 4.0839 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7576 loss: 1.7576 2022/10/14 23:15:41 - mmengine - INFO - Epoch(train) [28][540/940] lr: 1.0000e-02 eta: 11:08:30 time: 0.6072 data_time: 0.0449 memory: 33630 grad_norm: 3.9721 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6130 loss: 1.6130 2022/10/14 23:15:53 - mmengine - INFO - Epoch(train) [28][560/940] lr: 1.0000e-02 eta: 11:08:18 time: 0.5798 data_time: 0.0343 memory: 33630 grad_norm: 3.9916 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.6555 loss: 1.6555 2022/10/14 23:16:04 - mmengine - INFO - Epoch(train) [28][580/940] lr: 1.0000e-02 eta: 11:08:06 time: 0.5887 data_time: 0.0375 memory: 33630 grad_norm: 3.8808 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7049 loss: 1.7049 2022/10/14 23:16:16 - mmengine - INFO - Epoch(train) [28][600/940] lr: 1.0000e-02 eta: 11:07:53 time: 0.5737 data_time: 0.0412 memory: 33630 grad_norm: 3.9328 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 1.7703 loss: 1.7703 2022/10/14 23:16:28 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 23:16:28 - mmengine - INFO - Epoch(train) [28][620/940] lr: 1.0000e-02 eta: 11:07:41 time: 0.5833 data_time: 0.0390 memory: 33630 grad_norm: 4.0100 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5915 loss: 1.5915 2022/10/14 23:16:39 - mmengine - INFO - Epoch(train) [28][640/940] lr: 1.0000e-02 eta: 11:07:30 time: 0.5916 data_time: 0.0310 memory: 33630 grad_norm: 3.9991 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7241 loss: 1.7241 2022/10/14 23:16:52 - mmengine - INFO - Epoch(train) [28][660/940] lr: 1.0000e-02 eta: 11:07:19 time: 0.6165 data_time: 0.0382 memory: 33630 grad_norm: 3.9986 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5611 loss: 1.5611 2022/10/14 23:17:04 - mmengine - INFO - Epoch(train) [28][680/940] lr: 1.0000e-02 eta: 11:07:09 time: 0.6169 data_time: 0.0351 memory: 33630 grad_norm: 3.9079 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.6135 loss: 1.6135 2022/10/14 23:17:16 - mmengine - INFO - Epoch(train) [28][700/940] lr: 1.0000e-02 eta: 11:06:57 time: 0.5872 data_time: 0.0373 memory: 33630 grad_norm: 3.9133 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6561 loss: 1.6561 2022/10/14 23:17:28 - mmengine - INFO - Epoch(train) [28][720/940] lr: 1.0000e-02 eta: 11:06:45 time: 0.5897 data_time: 0.0352 memory: 33630 grad_norm: 4.0398 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7576 loss: 1.7576 2022/10/14 23:17:39 - mmengine - INFO - Epoch(train) [28][740/940] lr: 1.0000e-02 eta: 11:06:33 time: 0.5830 data_time: 0.0368 memory: 33630 grad_norm: 4.0117 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7991 loss: 1.7991 2022/10/14 23:17:51 - mmengine - INFO - Epoch(train) [28][760/940] lr: 1.0000e-02 eta: 11:06:21 time: 0.5922 data_time: 0.0361 memory: 33630 grad_norm: 4.0119 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6102 loss: 1.6102 2022/10/14 23:18:03 - mmengine - INFO - Epoch(train) [28][780/940] lr: 1.0000e-02 eta: 11:06:09 time: 0.5846 data_time: 0.0327 memory: 33630 grad_norm: 4.0244 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7602 loss: 1.7602 2022/10/14 23:18:14 - mmengine - INFO - Epoch(train) [28][800/940] lr: 1.0000e-02 eta: 11:05:57 time: 0.5778 data_time: 0.0365 memory: 33630 grad_norm: 3.9116 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.7763 loss: 1.7763 2022/10/14 23:18:26 - mmengine - INFO - Epoch(train) [28][820/940] lr: 1.0000e-02 eta: 11:05:45 time: 0.5838 data_time: 0.0327 memory: 33630 grad_norm: 3.9363 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.6080 loss: 1.6080 2022/10/14 23:18:38 - mmengine - INFO - Epoch(train) [28][840/940] lr: 1.0000e-02 eta: 11:05:33 time: 0.5810 data_time: 0.0374 memory: 33630 grad_norm: 3.9513 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.7425 loss: 1.7425 2022/10/14 23:18:49 - mmengine - INFO - Epoch(train) [28][860/940] lr: 1.0000e-02 eta: 11:05:20 time: 0.5744 data_time: 0.0381 memory: 33630 grad_norm: 3.9550 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6390 loss: 1.6390 2022/10/14 23:19:01 - mmengine - INFO - Epoch(train) [28][880/940] lr: 1.0000e-02 eta: 11:05:08 time: 0.5779 data_time: 0.0344 memory: 33630 grad_norm: 4.0001 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.5645 loss: 1.5645 2022/10/14 23:19:13 - mmengine - INFO - Epoch(train) [28][900/940] lr: 1.0000e-02 eta: 11:04:56 time: 0.5883 data_time: 0.0353 memory: 33630 grad_norm: 4.0809 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6343 loss: 1.6343 2022/10/14 23:19:24 - mmengine - INFO - Epoch(train) [28][920/940] lr: 1.0000e-02 eta: 11:04:44 time: 0.5824 data_time: 0.0332 memory: 33630 grad_norm: 3.9826 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5952 loss: 1.5952 2022/10/14 23:19:35 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 23:19:35 - mmengine - INFO - Epoch(train) [28][940/940] lr: 1.0000e-02 eta: 11:04:30 time: 0.5393 data_time: 0.0355 memory: 33630 grad_norm: 4.2321 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.6895 loss: 1.6895 2022/10/14 23:19:49 - mmengine - INFO - Epoch(val) [28][20/78] eta: 0:00:41 time: 0.7180 data_time: 0.5494 memory: 5967 2022/10/14 23:20:00 - mmengine - INFO - Epoch(val) [28][40/78] eta: 0:00:19 time: 0.5084 data_time: 0.3372 memory: 5967 2022/10/14 23:20:12 - mmengine - INFO - Epoch(val) [28][60/78] eta: 0:00:11 time: 0.6385 data_time: 0.4684 memory: 5967 2022/10/14 23:20:24 - mmengine - INFO - Epoch(val) [28][78/78] acc/top1: 0.6445 acc/top5: 0.8545 acc/mean1: 0.6443 2022/10/14 23:20:24 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_25.pth is removed 2022/10/14 23:20:25 - mmengine - INFO - The best checkpoint with 0.6445 acc/top1 at 28 epoch is saved to best_acc/top1_epoch_28.pth. 2022/10/14 23:20:42 - mmengine - INFO - Epoch(train) [29][20/940] lr: 1.0000e-02 eta: 11:04:30 time: 0.8354 data_time: 0.2883 memory: 33630 grad_norm: 3.9340 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6144 loss: 1.6144 2022/10/14 23:20:54 - mmengine - INFO - Epoch(train) [29][40/940] lr: 1.0000e-02 eta: 11:04:19 time: 0.5921 data_time: 0.0301 memory: 33630 grad_norm: 3.9480 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.6248 loss: 1.6248 2022/10/14 23:21:05 - mmengine - INFO - Epoch(train) [29][60/940] lr: 1.0000e-02 eta: 11:04:07 time: 0.5838 data_time: 0.0373 memory: 33630 grad_norm: 3.9820 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.6322 loss: 1.6322 2022/10/14 23:21:17 - mmengine - INFO - Epoch(train) [29][80/940] lr: 1.0000e-02 eta: 11:03:55 time: 0.5941 data_time: 0.0281 memory: 33630 grad_norm: 3.9468 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5493 loss: 1.5493 2022/10/14 23:21:29 - mmengine - INFO - Epoch(train) [29][100/940] lr: 1.0000e-02 eta: 11:03:43 time: 0.5816 data_time: 0.0370 memory: 33630 grad_norm: 3.9394 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.6220 loss: 1.6220 2022/10/14 23:21:40 - mmengine - INFO - Epoch(train) [29][120/940] lr: 1.0000e-02 eta: 11:03:31 time: 0.5796 data_time: 0.0300 memory: 33630 grad_norm: 4.0323 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.6534 loss: 1.6534 2022/10/14 23:21:52 - mmengine - INFO - Epoch(train) [29][140/940] lr: 1.0000e-02 eta: 11:03:19 time: 0.5851 data_time: 0.0365 memory: 33630 grad_norm: 3.9533 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6683 loss: 1.6683 2022/10/14 23:22:04 - mmengine - INFO - Epoch(train) [29][160/940] lr: 1.0000e-02 eta: 11:03:07 time: 0.5921 data_time: 0.0322 memory: 33630 grad_norm: 3.9156 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.6374 loss: 1.6374 2022/10/14 23:22:16 - mmengine - INFO - Epoch(train) [29][180/940] lr: 1.0000e-02 eta: 11:02:55 time: 0.5784 data_time: 0.0361 memory: 33630 grad_norm: 4.0111 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6070 loss: 1.6070 2022/10/14 23:22:27 - mmengine - INFO - Epoch(train) [29][200/940] lr: 1.0000e-02 eta: 11:02:43 time: 0.5865 data_time: 0.0412 memory: 33630 grad_norm: 4.0051 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8530 loss: 1.8530 2022/10/14 23:22:39 - mmengine - INFO - Epoch(train) [29][220/940] lr: 1.0000e-02 eta: 11:02:31 time: 0.5848 data_time: 0.0379 memory: 33630 grad_norm: 4.0017 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5858 loss: 1.5858 2022/10/14 23:22:51 - mmengine - INFO - Epoch(train) [29][240/940] lr: 1.0000e-02 eta: 11:02:19 time: 0.5861 data_time: 0.0383 memory: 33630 grad_norm: 3.8862 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6257 loss: 1.6257 2022/10/14 23:23:03 - mmengine - INFO - Epoch(train) [29][260/940] lr: 1.0000e-02 eta: 11:02:07 time: 0.5891 data_time: 0.0454 memory: 33630 grad_norm: 3.9319 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5975 loss: 1.5975 2022/10/14 23:23:14 - mmengine - INFO - Epoch(train) [29][280/940] lr: 1.0000e-02 eta: 11:01:55 time: 0.5878 data_time: 0.0372 memory: 33630 grad_norm: 4.0190 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6590 loss: 1.6590 2022/10/14 23:23:26 - mmengine - INFO - Epoch(train) [29][300/940] lr: 1.0000e-02 eta: 11:01:43 time: 0.5754 data_time: 0.0377 memory: 33630 grad_norm: 3.9301 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7743 loss: 1.7743 2022/10/14 23:23:38 - mmengine - INFO - Epoch(train) [29][320/940] lr: 1.0000e-02 eta: 11:01:31 time: 0.5900 data_time: 0.0433 memory: 33630 grad_norm: 3.9598 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5980 loss: 1.5980 2022/10/14 23:23:49 - mmengine - INFO - Epoch(train) [29][340/940] lr: 1.0000e-02 eta: 11:01:19 time: 0.5745 data_time: 0.0352 memory: 33630 grad_norm: 3.9780 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.5643 loss: 1.5643 2022/10/14 23:24:01 - mmengine - INFO - Epoch(train) [29][360/940] lr: 1.0000e-02 eta: 11:01:07 time: 0.5877 data_time: 0.0364 memory: 33630 grad_norm: 3.9497 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6198 loss: 1.6198 2022/10/14 23:24:12 - mmengine - INFO - Epoch(train) [29][380/940] lr: 1.0000e-02 eta: 11:00:54 time: 0.5798 data_time: 0.0322 memory: 33630 grad_norm: 3.9937 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4871 loss: 1.4871 2022/10/14 23:24:24 - mmengine - INFO - Epoch(train) [29][400/940] lr: 1.0000e-02 eta: 11:00:42 time: 0.5752 data_time: 0.0378 memory: 33630 grad_norm: 3.9982 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6666 loss: 1.6666 2022/10/14 23:24:35 - mmengine - INFO - Epoch(train) [29][420/940] lr: 1.0000e-02 eta: 11:00:29 time: 0.5772 data_time: 0.0314 memory: 33630 grad_norm: 4.0578 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.6825 loss: 1.6825 2022/10/14 23:24:47 - mmengine - INFO - Epoch(train) [29][440/940] lr: 1.0000e-02 eta: 11:00:17 time: 0.5790 data_time: 0.0385 memory: 33630 grad_norm: 4.0127 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6836 loss: 1.6836 2022/10/14 23:24:59 - mmengine - INFO - Epoch(train) [29][460/940] lr: 1.0000e-02 eta: 11:00:05 time: 0.5868 data_time: 0.0321 memory: 33630 grad_norm: 4.0297 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6815 loss: 1.6815 2022/10/14 23:25:10 - mmengine - INFO - Epoch(train) [29][480/940] lr: 1.0000e-02 eta: 10:59:53 time: 0.5777 data_time: 0.0355 memory: 33630 grad_norm: 4.0078 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 1.7172 loss: 1.7172 2022/10/14 23:25:22 - mmengine - INFO - Epoch(train) [29][500/940] lr: 1.0000e-02 eta: 10:59:42 time: 0.5988 data_time: 0.0364 memory: 33630 grad_norm: 3.9696 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6646 loss: 1.6646 2022/10/14 23:25:34 - mmengine - INFO - Epoch(train) [29][520/940] lr: 1.0000e-02 eta: 10:59:30 time: 0.5890 data_time: 0.0352 memory: 33630 grad_norm: 3.9935 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5704 loss: 1.5704 2022/10/14 23:25:46 - mmengine - INFO - Epoch(train) [29][540/940] lr: 1.0000e-02 eta: 10:59:18 time: 0.5793 data_time: 0.0313 memory: 33630 grad_norm: 4.0079 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6461 loss: 1.6461 2022/10/14 23:25:57 - mmengine - INFO - Epoch(train) [29][560/940] lr: 1.0000e-02 eta: 10:59:06 time: 0.5883 data_time: 0.0420 memory: 33630 grad_norm: 3.9822 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6898 loss: 1.6898 2022/10/14 23:26:09 - mmengine - INFO - Epoch(train) [29][580/940] lr: 1.0000e-02 eta: 10:58:53 time: 0.5775 data_time: 0.0352 memory: 33630 grad_norm: 3.9953 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6922 loss: 1.6922 2022/10/14 23:26:21 - mmengine - INFO - Epoch(train) [29][600/940] lr: 1.0000e-02 eta: 10:58:42 time: 0.5891 data_time: 0.0401 memory: 33630 grad_norm: 3.9804 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7545 loss: 1.7545 2022/10/14 23:26:33 - mmengine - INFO - Epoch(train) [29][620/940] lr: 1.0000e-02 eta: 10:58:30 time: 0.5904 data_time: 0.0406 memory: 33630 grad_norm: 4.0579 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6995 loss: 1.6995 2022/10/14 23:26:44 - mmengine - INFO - Epoch(train) [29][640/940] lr: 1.0000e-02 eta: 10:58:18 time: 0.5864 data_time: 0.0388 memory: 33630 grad_norm: 3.9093 top1_acc: 0.7188 top5_acc: 0.7500 loss_cls: 1.5182 loss: 1.5182 2022/10/14 23:26:56 - mmengine - INFO - Epoch(train) [29][660/940] lr: 1.0000e-02 eta: 10:58:05 time: 0.5735 data_time: 0.0295 memory: 33630 grad_norm: 3.9971 top1_acc: 0.4375 top5_acc: 0.8438 loss_cls: 1.7633 loss: 1.7633 2022/10/14 23:27:07 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 23:27:07 - mmengine - INFO - Epoch(train) [29][680/940] lr: 1.0000e-02 eta: 10:57:53 time: 0.5753 data_time: 0.0361 memory: 33630 grad_norm: 4.0105 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5939 loss: 1.5939 2022/10/14 23:27:19 - mmengine - INFO - Epoch(train) [29][700/940] lr: 1.0000e-02 eta: 10:57:41 time: 0.5824 data_time: 0.0377 memory: 33630 grad_norm: 3.9200 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.7440 loss: 1.7440 2022/10/14 23:27:31 - mmengine - INFO - Epoch(train) [29][720/940] lr: 1.0000e-02 eta: 10:57:29 time: 0.5815 data_time: 0.0403 memory: 33630 grad_norm: 3.9155 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7244 loss: 1.7244 2022/10/14 23:27:42 - mmengine - INFO - Epoch(train) [29][740/940] lr: 1.0000e-02 eta: 10:57:17 time: 0.5864 data_time: 0.0311 memory: 33630 grad_norm: 3.9468 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6122 loss: 1.6122 2022/10/14 23:27:54 - mmengine - INFO - Epoch(train) [29][760/940] lr: 1.0000e-02 eta: 10:57:05 time: 0.5817 data_time: 0.0363 memory: 33630 grad_norm: 3.9423 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.5829 loss: 1.5829 2022/10/14 23:28:06 - mmengine - INFO - Epoch(train) [29][780/940] lr: 1.0000e-02 eta: 10:56:53 time: 0.5923 data_time: 0.0339 memory: 33630 grad_norm: 4.1326 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.7756 loss: 1.7756 2022/10/14 23:28:17 - mmengine - INFO - Epoch(train) [29][800/940] lr: 1.0000e-02 eta: 10:56:41 time: 0.5817 data_time: 0.0363 memory: 33630 grad_norm: 4.0024 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.6547 loss: 1.6547 2022/10/14 23:28:29 - mmengine - INFO - Epoch(train) [29][820/940] lr: 1.0000e-02 eta: 10:56:29 time: 0.5953 data_time: 0.0389 memory: 33630 grad_norm: 4.0510 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7008 loss: 1.7008 2022/10/14 23:28:41 - mmengine - INFO - Epoch(train) [29][840/940] lr: 1.0000e-02 eta: 10:56:18 time: 0.5931 data_time: 0.0344 memory: 33630 grad_norm: 3.9276 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6635 loss: 1.6635 2022/10/14 23:28:53 - mmengine - INFO - Epoch(train) [29][860/940] lr: 1.0000e-02 eta: 10:56:06 time: 0.5935 data_time: 0.0368 memory: 33630 grad_norm: 3.9966 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7270 loss: 1.7270 2022/10/14 23:29:05 - mmengine - INFO - Epoch(train) [29][880/940] lr: 1.0000e-02 eta: 10:55:54 time: 0.5829 data_time: 0.0380 memory: 33630 grad_norm: 4.0564 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.7109 loss: 1.7109 2022/10/14 23:29:17 - mmengine - INFO - Epoch(train) [29][900/940] lr: 1.0000e-02 eta: 10:55:42 time: 0.5907 data_time: 0.0383 memory: 33630 grad_norm: 4.0150 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5402 loss: 1.5402 2022/10/14 23:29:28 - mmengine - INFO - Epoch(train) [29][920/940] lr: 1.0000e-02 eta: 10:55:30 time: 0.5831 data_time: 0.0317 memory: 33630 grad_norm: 3.9243 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.7414 loss: 1.7414 2022/10/14 23:29:39 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 23:29:39 - mmengine - INFO - Epoch(train) [29][940/940] lr: 1.0000e-02 eta: 10:55:16 time: 0.5420 data_time: 0.0351 memory: 33630 grad_norm: 4.3363 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.8597 loss: 1.8597 2022/10/14 23:29:54 - mmengine - INFO - Epoch(val) [29][20/78] eta: 0:00:42 time: 0.7330 data_time: 0.5635 memory: 5967 2022/10/14 23:30:04 - mmengine - INFO - Epoch(val) [29][40/78] eta: 0:00:18 time: 0.5000 data_time: 0.3353 memory: 5967 2022/10/14 23:30:17 - mmengine - INFO - Epoch(val) [29][60/78] eta: 0:00:11 time: 0.6492 data_time: 0.4819 memory: 5967 2022/10/14 23:30:29 - mmengine - INFO - Epoch(val) [29][78/78] acc/top1: 0.6410 acc/top5: 0.8542 acc/mean1: 0.6409 2022/10/14 23:30:46 - mmengine - INFO - Epoch(train) [30][20/940] lr: 1.0000e-02 eta: 10:55:19 time: 0.8786 data_time: 0.2377 memory: 33630 grad_norm: 3.9215 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6520 loss: 1.6520 2022/10/14 23:30:58 - mmengine - INFO - Epoch(train) [30][40/940] lr: 1.0000e-02 eta: 10:55:07 time: 0.5897 data_time: 0.0336 memory: 33630 grad_norm: 3.9649 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6897 loss: 1.6897 2022/10/14 23:31:10 - mmengine - INFO - Epoch(train) [30][60/940] lr: 1.0000e-02 eta: 10:54:55 time: 0.5914 data_time: 0.0423 memory: 33630 grad_norm: 3.9209 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6350 loss: 1.6350 2022/10/14 23:31:21 - mmengine - INFO - Epoch(train) [30][80/940] lr: 1.0000e-02 eta: 10:54:43 time: 0.5804 data_time: 0.0302 memory: 33630 grad_norm: 4.0525 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.6950 loss: 1.6950 2022/10/14 23:31:33 - mmengine - INFO - Epoch(train) [30][100/940] lr: 1.0000e-02 eta: 10:54:31 time: 0.5867 data_time: 0.0397 memory: 33630 grad_norm: 4.0293 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.6827 loss: 1.6827 2022/10/14 23:31:45 - mmengine - INFO - Epoch(train) [30][120/940] lr: 1.0000e-02 eta: 10:54:19 time: 0.5951 data_time: 0.0322 memory: 33630 grad_norm: 3.9938 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6333 loss: 1.6333 2022/10/14 23:31:57 - mmengine - INFO - Epoch(train) [30][140/940] lr: 1.0000e-02 eta: 10:54:07 time: 0.5795 data_time: 0.0346 memory: 33630 grad_norm: 3.9254 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7613 loss: 1.7613 2022/10/14 23:32:08 - mmengine - INFO - Epoch(train) [30][160/940] lr: 1.0000e-02 eta: 10:53:55 time: 0.5804 data_time: 0.0324 memory: 33630 grad_norm: 3.9122 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6059 loss: 1.6059 2022/10/14 23:32:20 - mmengine - INFO - Epoch(train) [30][180/940] lr: 1.0000e-02 eta: 10:53:43 time: 0.5877 data_time: 0.0348 memory: 33630 grad_norm: 3.9650 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.7578 loss: 1.7578 2022/10/14 23:32:32 - mmengine - INFO - Epoch(train) [30][200/940] lr: 1.0000e-02 eta: 10:53:31 time: 0.5827 data_time: 0.0423 memory: 33630 grad_norm: 3.9576 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6538 loss: 1.6538 2022/10/14 23:32:43 - mmengine - INFO - Epoch(train) [30][220/940] lr: 1.0000e-02 eta: 10:53:19 time: 0.5799 data_time: 0.0301 memory: 33630 grad_norm: 3.9516 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.5746 loss: 1.5746 2022/10/14 23:32:55 - mmengine - INFO - Epoch(train) [30][240/940] lr: 1.0000e-02 eta: 10:53:07 time: 0.5864 data_time: 0.0402 memory: 33630 grad_norm: 3.9341 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6775 loss: 1.6775 2022/10/14 23:33:07 - mmengine - INFO - Epoch(train) [30][260/940] lr: 1.0000e-02 eta: 10:52:55 time: 0.5908 data_time: 0.0369 memory: 33630 grad_norm: 4.0013 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6497 loss: 1.6497 2022/10/14 23:33:18 - mmengine - INFO - Epoch(train) [30][280/940] lr: 1.0000e-02 eta: 10:52:43 time: 0.5771 data_time: 0.0327 memory: 33630 grad_norm: 3.9594 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6384 loss: 1.6384 2022/10/14 23:33:30 - mmengine - INFO - Epoch(train) [30][300/940] lr: 1.0000e-02 eta: 10:52:31 time: 0.5838 data_time: 0.0417 memory: 33630 grad_norm: 3.9701 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5712 loss: 1.5712 2022/10/14 23:33:42 - mmengine - INFO - Epoch(train) [30][320/940] lr: 1.0000e-02 eta: 10:52:19 time: 0.5846 data_time: 0.0337 memory: 33630 grad_norm: 4.0033 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.6017 loss: 1.6017 2022/10/14 23:33:53 - mmengine - INFO - Epoch(train) [30][340/940] lr: 1.0000e-02 eta: 10:52:06 time: 0.5716 data_time: 0.0350 memory: 33630 grad_norm: 4.0089 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5144 loss: 1.5144 2022/10/14 23:34:05 - mmengine - INFO - Epoch(train) [30][360/940] lr: 1.0000e-02 eta: 10:51:54 time: 0.5772 data_time: 0.0354 memory: 33630 grad_norm: 4.0855 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6873 loss: 1.6873 2022/10/14 23:34:16 - mmengine - INFO - Epoch(train) [30][380/940] lr: 1.0000e-02 eta: 10:51:41 time: 0.5718 data_time: 0.0322 memory: 33630 grad_norm: 3.8971 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.6378 loss: 1.6378 2022/10/14 23:34:28 - mmengine - INFO - Epoch(train) [30][400/940] lr: 1.0000e-02 eta: 10:51:29 time: 0.5831 data_time: 0.0355 memory: 33630 grad_norm: 4.0587 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7022 loss: 1.7022 2022/10/14 23:34:39 - mmengine - INFO - Epoch(train) [30][420/940] lr: 1.0000e-02 eta: 10:51:17 time: 0.5815 data_time: 0.0364 memory: 33630 grad_norm: 3.9736 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7494 loss: 1.7494 2022/10/14 23:34:51 - mmengine - INFO - Epoch(train) [30][440/940] lr: 1.0000e-02 eta: 10:51:05 time: 0.5795 data_time: 0.0527 memory: 33630 grad_norm: 4.0817 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6842 loss: 1.6842 2022/10/14 23:35:03 - mmengine - INFO - Epoch(train) [30][460/940] lr: 1.0000e-02 eta: 10:50:52 time: 0.5778 data_time: 0.0387 memory: 33630 grad_norm: 3.9883 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.5087 loss: 1.5087 2022/10/14 23:35:14 - mmengine - INFO - Epoch(train) [30][480/940] lr: 1.0000e-02 eta: 10:50:41 time: 0.5907 data_time: 0.0536 memory: 33630 grad_norm: 4.0438 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.7400 loss: 1.7400 2022/10/14 23:35:26 - mmengine - INFO - Epoch(train) [30][500/940] lr: 1.0000e-02 eta: 10:50:28 time: 0.5792 data_time: 0.0324 memory: 33630 grad_norm: 3.9068 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5340 loss: 1.5340 2022/10/14 23:35:38 - mmengine - INFO - Epoch(train) [30][520/940] lr: 1.0000e-02 eta: 10:50:16 time: 0.5790 data_time: 0.0391 memory: 33630 grad_norm: 4.0478 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7615 loss: 1.7615 2022/10/14 23:35:49 - mmengine - INFO - Epoch(train) [30][540/940] lr: 1.0000e-02 eta: 10:50:04 time: 0.5923 data_time: 0.0354 memory: 33630 grad_norm: 3.9838 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7271 loss: 1.7271 2022/10/14 23:36:01 - mmengine - INFO - Epoch(train) [30][560/940] lr: 1.0000e-02 eta: 10:49:52 time: 0.5756 data_time: 0.0327 memory: 33630 grad_norm: 4.0735 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8129 loss: 1.8129 2022/10/14 23:36:12 - mmengine - INFO - Epoch(train) [30][580/940] lr: 1.0000e-02 eta: 10:49:40 time: 0.5789 data_time: 0.0314 memory: 33630 grad_norm: 4.0174 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7924 loss: 1.7924 2022/10/14 23:36:24 - mmengine - INFO - Epoch(train) [30][600/940] lr: 1.0000e-02 eta: 10:49:28 time: 0.5922 data_time: 0.0426 memory: 33630 grad_norm: 4.0182 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.6546 loss: 1.6546 2022/10/14 23:36:36 - mmengine - INFO - Epoch(train) [30][620/940] lr: 1.0000e-02 eta: 10:49:16 time: 0.5819 data_time: 0.0382 memory: 33630 grad_norm: 3.9915 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6713 loss: 1.6713 2022/10/14 23:36:48 - mmengine - INFO - Epoch(train) [30][640/940] lr: 1.0000e-02 eta: 10:49:04 time: 0.5876 data_time: 0.0331 memory: 33630 grad_norm: 3.9299 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 1.6467 loss: 1.6467 2022/10/14 23:36:59 - mmengine - INFO - Epoch(train) [30][660/940] lr: 1.0000e-02 eta: 10:48:52 time: 0.5744 data_time: 0.0383 memory: 33630 grad_norm: 3.9718 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5578 loss: 1.5578 2022/10/14 23:37:11 - mmengine - INFO - Epoch(train) [30][680/940] lr: 1.0000e-02 eta: 10:48:40 time: 0.5938 data_time: 0.0361 memory: 33630 grad_norm: 4.0929 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.7730 loss: 1.7730 2022/10/14 23:37:23 - mmengine - INFO - Epoch(train) [30][700/940] lr: 1.0000e-02 eta: 10:48:28 time: 0.5838 data_time: 0.0405 memory: 33630 grad_norm: 4.0420 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.7411 loss: 1.7411 2022/10/14 23:37:34 - mmengine - INFO - Epoch(train) [30][720/940] lr: 1.0000e-02 eta: 10:48:16 time: 0.5814 data_time: 0.0366 memory: 33630 grad_norm: 3.9599 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6040 loss: 1.6040 2022/10/14 23:37:46 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 23:37:46 - mmengine - INFO - Epoch(train) [30][740/940] lr: 1.0000e-02 eta: 10:48:04 time: 0.5934 data_time: 0.0373 memory: 33630 grad_norm: 4.0499 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.7515 loss: 1.7515 2022/10/14 23:37:58 - mmengine - INFO - Epoch(train) [30][760/940] lr: 1.0000e-02 eta: 10:47:52 time: 0.5837 data_time: 0.0327 memory: 33630 grad_norm: 4.0492 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6851 loss: 1.6851 2022/10/14 23:38:10 - mmengine - INFO - Epoch(train) [30][780/940] lr: 1.0000e-02 eta: 10:47:40 time: 0.5829 data_time: 0.0391 memory: 33630 grad_norm: 3.9859 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5550 loss: 1.5550 2022/10/14 23:38:21 - mmengine - INFO - Epoch(train) [30][800/940] lr: 1.0000e-02 eta: 10:47:27 time: 0.5707 data_time: 0.0350 memory: 33630 grad_norm: 4.0953 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6457 loss: 1.6457 2022/10/14 23:38:33 - mmengine - INFO - Epoch(train) [30][820/940] lr: 1.0000e-02 eta: 10:47:16 time: 0.5872 data_time: 0.0325 memory: 33630 grad_norm: 4.0113 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.5505 loss: 1.5505 2022/10/14 23:38:45 - mmengine - INFO - Epoch(train) [30][840/940] lr: 1.0000e-02 eta: 10:47:04 time: 0.5871 data_time: 0.0318 memory: 33630 grad_norm: 4.0257 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7231 loss: 1.7231 2022/10/14 23:38:56 - mmengine - INFO - Epoch(train) [30][860/940] lr: 1.0000e-02 eta: 10:46:52 time: 0.5901 data_time: 0.0441 memory: 33630 grad_norm: 3.9922 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6236 loss: 1.6236 2022/10/14 23:39:08 - mmengine - INFO - Epoch(train) [30][880/940] lr: 1.0000e-02 eta: 10:46:40 time: 0.5880 data_time: 0.0343 memory: 33630 grad_norm: 4.0901 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.5224 loss: 1.5224 2022/10/14 23:39:20 - mmengine - INFO - Epoch(train) [30][900/940] lr: 1.0000e-02 eta: 10:46:28 time: 0.5861 data_time: 0.0412 memory: 33630 grad_norm: 4.0761 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8334 loss: 1.8334 2022/10/14 23:39:31 - mmengine - INFO - Epoch(train) [30][920/940] lr: 1.0000e-02 eta: 10:46:16 time: 0.5783 data_time: 0.0356 memory: 33630 grad_norm: 4.0505 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.5846 loss: 1.5846 2022/10/14 23:39:42 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 23:39:42 - mmengine - INFO - Epoch(train) [30][940/940] lr: 1.0000e-02 eta: 10:46:02 time: 0.5463 data_time: 0.0397 memory: 33630 grad_norm: 4.2875 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.7013 loss: 1.7013 2022/10/14 23:39:42 - mmengine - INFO - Saving checkpoint at 30 epochs 2022/10/14 23:39:57 - mmengine - INFO - Epoch(val) [30][20/78] eta: 0:00:40 time: 0.7008 data_time: 0.5283 memory: 5967 2022/10/14 23:40:08 - mmengine - INFO - Epoch(val) [30][40/78] eta: 0:00:19 time: 0.5262 data_time: 0.3575 memory: 5967 2022/10/14 23:40:21 - mmengine - INFO - Epoch(val) [30][60/78] eta: 0:00:12 time: 0.6801 data_time: 0.5112 memory: 5967 2022/10/14 23:40:33 - mmengine - INFO - Epoch(val) [30][78/78] acc/top1: 0.6358 acc/top5: 0.8493 acc/mean1: 0.6357 2022/10/14 23:40:50 - mmengine - INFO - Epoch(train) [31][20/940] lr: 1.0000e-02 eta: 10:46:02 time: 0.8477 data_time: 0.2466 memory: 33630 grad_norm: 3.9631 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5823 loss: 1.5823 2022/10/14 23:41:01 - mmengine - INFO - Epoch(train) [31][40/940] lr: 1.0000e-02 eta: 10:45:50 time: 0.5765 data_time: 0.0352 memory: 33630 grad_norm: 4.0026 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5835 loss: 1.5835 2022/10/14 23:41:13 - mmengine - INFO - Epoch(train) [31][60/940] lr: 1.0000e-02 eta: 10:45:40 time: 0.6177 data_time: 0.0363 memory: 33630 grad_norm: 4.0145 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5840 loss: 1.5840 2022/10/14 23:41:25 - mmengine - INFO - Epoch(train) [31][80/940] lr: 1.0000e-02 eta: 10:45:27 time: 0.5801 data_time: 0.0399 memory: 33630 grad_norm: 3.8969 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5942 loss: 1.5942 2022/10/14 23:41:37 - mmengine - INFO - Epoch(train) [31][100/940] lr: 1.0000e-02 eta: 10:45:16 time: 0.5922 data_time: 0.0343 memory: 33630 grad_norm: 3.9319 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6157 loss: 1.6157 2022/10/14 23:41:48 - mmengine - INFO - Epoch(train) [31][120/940] lr: 1.0000e-02 eta: 10:45:03 time: 0.5762 data_time: 0.0371 memory: 33630 grad_norm: 3.9561 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6518 loss: 1.6518 2022/10/14 23:42:00 - mmengine - INFO - Epoch(train) [31][140/940] lr: 1.0000e-02 eta: 10:44:52 time: 0.5946 data_time: 0.0368 memory: 33630 grad_norm: 3.9556 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6160 loss: 1.6160 2022/10/14 23:42:12 - mmengine - INFO - Epoch(train) [31][160/940] lr: 1.0000e-02 eta: 10:44:39 time: 0.5758 data_time: 0.0312 memory: 33630 grad_norm: 3.8922 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5125 loss: 1.5125 2022/10/14 23:42:23 - mmengine - INFO - Epoch(train) [31][180/940] lr: 1.0000e-02 eta: 10:44:27 time: 0.5783 data_time: 0.0395 memory: 33630 grad_norm: 3.9505 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5677 loss: 1.5677 2022/10/14 23:42:35 - mmengine - INFO - Epoch(train) [31][200/940] lr: 1.0000e-02 eta: 10:44:15 time: 0.5884 data_time: 0.0394 memory: 33630 grad_norm: 3.9631 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6536 loss: 1.6536 2022/10/14 23:42:47 - mmengine - INFO - Epoch(train) [31][220/940] lr: 1.0000e-02 eta: 10:44:03 time: 0.5832 data_time: 0.0359 memory: 33630 grad_norm: 3.9586 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5748 loss: 1.5748 2022/10/14 23:42:59 - mmengine - INFO - Epoch(train) [31][240/940] lr: 1.0000e-02 eta: 10:43:51 time: 0.5905 data_time: 0.0310 memory: 33630 grad_norm: 4.0506 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6128 loss: 1.6128 2022/10/14 23:43:10 - mmengine - INFO - Epoch(train) [31][260/940] lr: 1.0000e-02 eta: 10:43:39 time: 0.5820 data_time: 0.0412 memory: 33630 grad_norm: 4.0627 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5365 loss: 1.5365 2022/10/14 23:43:22 - mmengine - INFO - Epoch(train) [31][280/940] lr: 1.0000e-02 eta: 10:43:28 time: 0.5907 data_time: 0.0391 memory: 33630 grad_norm: 3.9799 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6260 loss: 1.6260 2022/10/14 23:43:34 - mmengine - INFO - Epoch(train) [31][300/940] lr: 1.0000e-02 eta: 10:43:16 time: 0.5873 data_time: 0.0305 memory: 33630 grad_norm: 3.9899 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5735 loss: 1.5735 2022/10/14 23:43:46 - mmengine - INFO - Epoch(train) [31][320/940] lr: 1.0000e-02 eta: 10:43:04 time: 0.5819 data_time: 0.0373 memory: 33630 grad_norm: 4.0592 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6476 loss: 1.6476 2022/10/14 23:43:57 - mmengine - INFO - Epoch(train) [31][340/940] lr: 1.0000e-02 eta: 10:42:52 time: 0.5828 data_time: 0.0364 memory: 33630 grad_norm: 4.1044 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.6578 loss: 1.6578 2022/10/14 23:44:09 - mmengine - INFO - Epoch(train) [31][360/940] lr: 1.0000e-02 eta: 10:42:40 time: 0.5900 data_time: 0.0405 memory: 33630 grad_norm: 3.9882 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.5218 loss: 1.5218 2022/10/14 23:44:21 - mmengine - INFO - Epoch(train) [31][380/940] lr: 1.0000e-02 eta: 10:42:28 time: 0.5989 data_time: 0.0371 memory: 33630 grad_norm: 4.0693 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7930 loss: 1.7930 2022/10/14 23:44:33 - mmengine - INFO - Epoch(train) [31][400/940] lr: 1.0000e-02 eta: 10:42:16 time: 0.5822 data_time: 0.0398 memory: 33630 grad_norm: 4.0428 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6527 loss: 1.6527 2022/10/14 23:44:44 - mmengine - INFO - Epoch(train) [31][420/940] lr: 1.0000e-02 eta: 10:42:05 time: 0.5906 data_time: 0.0357 memory: 33630 grad_norm: 4.0547 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7157 loss: 1.7157 2022/10/14 23:44:56 - mmengine - INFO - Epoch(train) [31][440/940] lr: 1.0000e-02 eta: 10:41:53 time: 0.5903 data_time: 0.0420 memory: 33630 grad_norm: 3.9274 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.4724 loss: 1.4724 2022/10/14 23:45:08 - mmengine - INFO - Epoch(train) [31][460/940] lr: 1.0000e-02 eta: 10:41:41 time: 0.5859 data_time: 0.0432 memory: 33630 grad_norm: 4.0551 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.7208 loss: 1.7208 2022/10/14 23:45:19 - mmengine - INFO - Epoch(train) [31][480/940] lr: 1.0000e-02 eta: 10:41:29 time: 0.5758 data_time: 0.0345 memory: 33630 grad_norm: 4.0475 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7525 loss: 1.7525 2022/10/14 23:45:31 - mmengine - INFO - Epoch(train) [31][500/940] lr: 1.0000e-02 eta: 10:41:16 time: 0.5790 data_time: 0.0356 memory: 33630 grad_norm: 4.0747 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.7210 loss: 1.7210 2022/10/14 23:45:43 - mmengine - INFO - Epoch(train) [31][520/940] lr: 1.0000e-02 eta: 10:41:04 time: 0.5775 data_time: 0.0374 memory: 33630 grad_norm: 4.0478 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6094 loss: 1.6094 2022/10/14 23:45:54 - mmengine - INFO - Epoch(train) [31][540/940] lr: 1.0000e-02 eta: 10:40:52 time: 0.5918 data_time: 0.0365 memory: 33630 grad_norm: 4.0400 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8072 loss: 1.8072 2022/10/14 23:46:06 - mmengine - INFO - Epoch(train) [31][560/940] lr: 1.0000e-02 eta: 10:40:40 time: 0.5840 data_time: 0.0396 memory: 33630 grad_norm: 3.8869 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.5710 loss: 1.5710 2022/10/14 23:46:18 - mmengine - INFO - Epoch(train) [31][580/940] lr: 1.0000e-02 eta: 10:40:29 time: 0.5908 data_time: 0.0436 memory: 33630 grad_norm: 4.0299 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5611 loss: 1.5611 2022/10/14 23:46:29 - mmengine - INFO - Epoch(train) [31][600/940] lr: 1.0000e-02 eta: 10:40:16 time: 0.5753 data_time: 0.0343 memory: 33630 grad_norm: 4.0226 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7065 loss: 1.7065 2022/10/14 23:46:41 - mmengine - INFO - Epoch(train) [31][620/940] lr: 1.0000e-02 eta: 10:40:04 time: 0.5802 data_time: 0.0445 memory: 33630 grad_norm: 4.0035 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.7653 loss: 1.7653 2022/10/14 23:46:53 - mmengine - INFO - Epoch(train) [31][640/940] lr: 1.0000e-02 eta: 10:39:52 time: 0.5775 data_time: 0.0297 memory: 33630 grad_norm: 4.0629 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5772 loss: 1.5772 2022/10/14 23:47:04 - mmengine - INFO - Epoch(train) [31][660/940] lr: 1.0000e-02 eta: 10:39:40 time: 0.5809 data_time: 0.0428 memory: 33630 grad_norm: 3.9344 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6271 loss: 1.6271 2022/10/14 23:47:16 - mmengine - INFO - Epoch(train) [31][680/940] lr: 1.0000e-02 eta: 10:39:27 time: 0.5775 data_time: 0.0361 memory: 33630 grad_norm: 4.0132 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6308 loss: 1.6308 2022/10/14 23:47:28 - mmengine - INFO - Epoch(train) [31][700/940] lr: 1.0000e-02 eta: 10:39:16 time: 0.5956 data_time: 0.0321 memory: 33630 grad_norm: 4.0039 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6278 loss: 1.6278 2022/10/14 23:47:39 - mmengine - INFO - Epoch(train) [31][720/940] lr: 1.0000e-02 eta: 10:39:03 time: 0.5765 data_time: 0.0343 memory: 33630 grad_norm: 3.9728 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.6190 loss: 1.6190 2022/10/14 23:47:51 - mmengine - INFO - Epoch(train) [31][740/940] lr: 1.0000e-02 eta: 10:38:52 time: 0.5874 data_time: 0.0457 memory: 33630 grad_norm: 4.0176 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.6743 loss: 1.6743 2022/10/14 23:48:03 - mmengine - INFO - Epoch(train) [31][760/940] lr: 1.0000e-02 eta: 10:38:39 time: 0.5808 data_time: 0.0362 memory: 33630 grad_norm: 4.0607 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.6219 loss: 1.6219 2022/10/14 23:48:14 - mmengine - INFO - Epoch(train) [31][780/940] lr: 1.0000e-02 eta: 10:38:27 time: 0.5827 data_time: 0.0319 memory: 33630 grad_norm: 3.9678 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6299 loss: 1.6299 2022/10/14 23:48:26 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 23:48:26 - mmengine - INFO - Epoch(train) [31][800/940] lr: 1.0000e-02 eta: 10:38:16 time: 0.5905 data_time: 0.0391 memory: 33630 grad_norm: 4.0461 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4420 loss: 1.4420 2022/10/14 23:48:38 - mmengine - INFO - Epoch(train) [31][820/940] lr: 1.0000e-02 eta: 10:38:04 time: 0.5857 data_time: 0.0451 memory: 33630 grad_norm: 4.0933 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5996 loss: 1.5996 2022/10/14 23:48:50 - mmengine - INFO - Epoch(train) [31][840/940] lr: 1.0000e-02 eta: 10:37:52 time: 0.5944 data_time: 0.0368 memory: 33630 grad_norm: 3.9930 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.7758 loss: 1.7758 2022/10/14 23:49:02 - mmengine - INFO - Epoch(train) [31][860/940] lr: 1.0000e-02 eta: 10:37:41 time: 0.5990 data_time: 0.0321 memory: 33630 grad_norm: 4.0922 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.6440 loss: 1.6440 2022/10/14 23:49:13 - mmengine - INFO - Epoch(train) [31][880/940] lr: 1.0000e-02 eta: 10:37:28 time: 0.5781 data_time: 0.0381 memory: 33630 grad_norm: 4.0292 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.6253 loss: 1.6253 2022/10/14 23:49:25 - mmengine - INFO - Epoch(train) [31][900/940] lr: 1.0000e-02 eta: 10:37:16 time: 0.5836 data_time: 0.0432 memory: 33630 grad_norm: 4.0373 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.6000 loss: 1.6000 2022/10/14 23:49:37 - mmengine - INFO - Epoch(train) [31][920/940] lr: 1.0000e-02 eta: 10:37:05 time: 0.5934 data_time: 0.0369 memory: 33630 grad_norm: 4.0393 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5816 loss: 1.5816 2022/10/14 23:49:48 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 23:49:48 - mmengine - INFO - Epoch(train) [31][940/940] lr: 1.0000e-02 eta: 10:36:51 time: 0.5440 data_time: 0.0320 memory: 33630 grad_norm: 4.2922 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.5456 loss: 1.5456 2022/10/14 23:50:02 - mmengine - INFO - Epoch(val) [31][20/78] eta: 0:00:41 time: 0.7175 data_time: 0.5490 memory: 5967 2022/10/14 23:50:13 - mmengine - INFO - Epoch(val) [31][40/78] eta: 0:00:21 time: 0.5685 data_time: 0.4008 memory: 5967 2022/10/14 23:50:28 - mmengine - INFO - Epoch(val) [31][60/78] eta: 0:00:13 time: 0.7525 data_time: 0.5838 memory: 5967 2022/10/14 23:50:38 - mmengine - INFO - Epoch(val) [31][78/78] acc/top1: 0.6408 acc/top5: 0.8505 acc/mean1: 0.6406 2022/10/14 23:50:55 - mmengine - INFO - Epoch(train) [32][20/940] lr: 1.0000e-02 eta: 10:36:50 time: 0.8286 data_time: 0.2372 memory: 33630 grad_norm: 4.0023 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5393 loss: 1.5393 2022/10/14 23:51:07 - mmengine - INFO - Epoch(train) [32][40/940] lr: 1.0000e-02 eta: 10:36:39 time: 0.6095 data_time: 0.0395 memory: 33630 grad_norm: 4.0096 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6090 loss: 1.6090 2022/10/14 23:51:19 - mmengine - INFO - Epoch(train) [32][60/940] lr: 1.0000e-02 eta: 10:36:28 time: 0.5976 data_time: 0.0368 memory: 33630 grad_norm: 3.9339 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5933 loss: 1.5933 2022/10/14 23:51:30 - mmengine - INFO - Epoch(train) [32][80/940] lr: 1.0000e-02 eta: 10:36:16 time: 0.5882 data_time: 0.0332 memory: 33630 grad_norm: 3.9725 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.5798 loss: 1.5798 2022/10/14 23:51:43 - mmengine - INFO - Epoch(train) [32][100/940] lr: 1.0000e-02 eta: 10:36:05 time: 0.6120 data_time: 0.0478 memory: 33630 grad_norm: 4.0442 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6676 loss: 1.6676 2022/10/14 23:51:54 - mmengine - INFO - Epoch(train) [32][120/940] lr: 1.0000e-02 eta: 10:35:53 time: 0.5893 data_time: 0.0373 memory: 33630 grad_norm: 3.9862 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.6204 loss: 1.6204 2022/10/14 23:52:06 - mmengine - INFO - Epoch(train) [32][140/940] lr: 1.0000e-02 eta: 10:35:41 time: 0.5755 data_time: 0.0345 memory: 33630 grad_norm: 4.0319 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6279 loss: 1.6279 2022/10/14 23:52:18 - mmengine - INFO - Epoch(train) [32][160/940] lr: 1.0000e-02 eta: 10:35:29 time: 0.5801 data_time: 0.0301 memory: 33630 grad_norm: 3.9845 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6395 loss: 1.6395 2022/10/14 23:52:29 - mmengine - INFO - Epoch(train) [32][180/940] lr: 1.0000e-02 eta: 10:35:16 time: 0.5725 data_time: 0.0378 memory: 33630 grad_norm: 4.1166 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6768 loss: 1.6768 2022/10/14 23:52:41 - mmengine - INFO - Epoch(train) [32][200/940] lr: 1.0000e-02 eta: 10:35:04 time: 0.5804 data_time: 0.0344 memory: 33630 grad_norm: 4.1126 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.6642 loss: 1.6642 2022/10/14 23:52:52 - mmengine - INFO - Epoch(train) [32][220/940] lr: 1.0000e-02 eta: 10:34:52 time: 0.5919 data_time: 0.0359 memory: 33630 grad_norm: 4.0206 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6473 loss: 1.6473 2022/10/14 23:53:04 - mmengine - INFO - Epoch(train) [32][240/940] lr: 1.0000e-02 eta: 10:34:41 time: 0.5969 data_time: 0.0399 memory: 33630 grad_norm: 4.0142 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.5270 loss: 1.5270 2022/10/14 23:53:16 - mmengine - INFO - Epoch(train) [32][260/940] lr: 1.0000e-02 eta: 10:34:28 time: 0.5752 data_time: 0.0364 memory: 33630 grad_norm: 4.0335 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6771 loss: 1.6771 2022/10/14 23:53:28 - mmengine - INFO - Epoch(train) [32][280/940] lr: 1.0000e-02 eta: 10:34:16 time: 0.5829 data_time: 0.0374 memory: 33630 grad_norm: 4.0420 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6476 loss: 1.6476 2022/10/14 23:53:39 - mmengine - INFO - Epoch(train) [32][300/940] lr: 1.0000e-02 eta: 10:34:04 time: 0.5874 data_time: 0.0365 memory: 33630 grad_norm: 4.0248 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5242 loss: 1.5242 2022/10/14 23:53:51 - mmengine - INFO - Epoch(train) [32][320/940] lr: 1.0000e-02 eta: 10:33:53 time: 0.5872 data_time: 0.0357 memory: 33630 grad_norm: 4.0869 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.5780 loss: 1.5780 2022/10/14 23:54:03 - mmengine - INFO - Epoch(train) [32][340/940] lr: 1.0000e-02 eta: 10:33:41 time: 0.5867 data_time: 0.0338 memory: 33630 grad_norm: 4.0687 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7784 loss: 1.7784 2022/10/14 23:54:14 - mmengine - INFO - Epoch(train) [32][360/940] lr: 1.0000e-02 eta: 10:33:29 time: 0.5835 data_time: 0.0351 memory: 33630 grad_norm: 4.0627 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.7042 loss: 1.7042 2022/10/14 23:54:26 - mmengine - INFO - Epoch(train) [32][380/940] lr: 1.0000e-02 eta: 10:33:17 time: 0.5926 data_time: 0.0399 memory: 33630 grad_norm: 4.0463 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4958 loss: 1.4958 2022/10/14 23:54:38 - mmengine - INFO - Epoch(train) [32][400/940] lr: 1.0000e-02 eta: 10:33:05 time: 0.5897 data_time: 0.0324 memory: 33630 grad_norm: 4.0146 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6959 loss: 1.6959 2022/10/14 23:54:50 - mmengine - INFO - Epoch(train) [32][420/940] lr: 1.0000e-02 eta: 10:32:53 time: 0.5876 data_time: 0.0435 memory: 33630 grad_norm: 3.9028 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5835 loss: 1.5835 2022/10/14 23:55:02 - mmengine - INFO - Epoch(train) [32][440/940] lr: 1.0000e-02 eta: 10:32:41 time: 0.5862 data_time: 0.0355 memory: 33630 grad_norm: 3.9989 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.6988 loss: 1.6988 2022/10/14 23:55:13 - mmengine - INFO - Epoch(train) [32][460/940] lr: 1.0000e-02 eta: 10:32:29 time: 0.5819 data_time: 0.0384 memory: 33630 grad_norm: 4.0083 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6537 loss: 1.6537 2022/10/14 23:55:25 - mmengine - INFO - Epoch(train) [32][480/940] lr: 1.0000e-02 eta: 10:32:17 time: 0.5881 data_time: 0.0412 memory: 33630 grad_norm: 4.0168 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5740 loss: 1.5740 2022/10/14 23:55:37 - mmengine - INFO - Epoch(train) [32][500/940] lr: 1.0000e-02 eta: 10:32:05 time: 0.5805 data_time: 0.0306 memory: 33630 grad_norm: 4.1370 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.6863 loss: 1.6863 2022/10/14 23:55:48 - mmengine - INFO - Epoch(train) [32][520/940] lr: 1.0000e-02 eta: 10:31:54 time: 0.5894 data_time: 0.0398 memory: 33630 grad_norm: 4.0449 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.5977 loss: 1.5977 2022/10/14 23:56:00 - mmengine - INFO - Epoch(train) [32][540/940] lr: 1.0000e-02 eta: 10:31:41 time: 0.5752 data_time: 0.0333 memory: 33630 grad_norm: 4.0090 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5318 loss: 1.5318 2022/10/14 23:56:11 - mmengine - INFO - Epoch(train) [32][560/940] lr: 1.0000e-02 eta: 10:31:28 time: 0.5698 data_time: 0.0374 memory: 33630 grad_norm: 3.9793 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5777 loss: 1.5777 2022/10/14 23:56:23 - mmengine - INFO - Epoch(train) [32][580/940] lr: 1.0000e-02 eta: 10:31:16 time: 0.5817 data_time: 0.0433 memory: 33630 grad_norm: 3.9500 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5602 loss: 1.5602 2022/10/14 23:56:34 - mmengine - INFO - Epoch(train) [32][600/940] lr: 1.0000e-02 eta: 10:31:04 time: 0.5727 data_time: 0.0345 memory: 33630 grad_norm: 3.9781 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5174 loss: 1.5174 2022/10/14 23:56:46 - mmengine - INFO - Epoch(train) [32][620/940] lr: 1.0000e-02 eta: 10:30:52 time: 0.5833 data_time: 0.0370 memory: 33630 grad_norm: 4.0738 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.8255 loss: 1.8255 2022/10/14 23:56:58 - mmengine - INFO - Epoch(train) [32][640/940] lr: 1.0000e-02 eta: 10:30:40 time: 0.5940 data_time: 0.0309 memory: 33630 grad_norm: 4.1594 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6073 loss: 1.6073 2022/10/14 23:57:10 - mmengine - INFO - Epoch(train) [32][660/940] lr: 1.0000e-02 eta: 10:30:28 time: 0.5822 data_time: 0.0315 memory: 33630 grad_norm: 4.0831 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6608 loss: 1.6608 2022/10/14 23:57:21 - mmengine - INFO - Epoch(train) [32][680/940] lr: 1.0000e-02 eta: 10:30:16 time: 0.5910 data_time: 0.0397 memory: 33630 grad_norm: 4.0262 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.5662 loss: 1.5662 2022/10/14 23:57:33 - mmengine - INFO - Epoch(train) [32][700/940] lr: 1.0000e-02 eta: 10:30:04 time: 0.5837 data_time: 0.0361 memory: 33630 grad_norm: 4.0161 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.5739 loss: 1.5739 2022/10/14 23:57:45 - mmengine - INFO - Epoch(train) [32][720/940] lr: 1.0000e-02 eta: 10:29:53 time: 0.5888 data_time: 0.0326 memory: 33630 grad_norm: 4.0841 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7539 loss: 1.7539 2022/10/14 23:57:57 - mmengine - INFO - Epoch(train) [32][740/940] lr: 1.0000e-02 eta: 10:29:41 time: 0.5877 data_time: 0.0406 memory: 33630 grad_norm: 4.1119 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6042 loss: 1.6042 2022/10/14 23:58:08 - mmengine - INFO - Epoch(train) [32][760/940] lr: 1.0000e-02 eta: 10:29:29 time: 0.5819 data_time: 0.0330 memory: 33630 grad_norm: 4.0738 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.6779 loss: 1.6779 2022/10/14 23:58:20 - mmengine - INFO - Epoch(train) [32][780/940] lr: 1.0000e-02 eta: 10:29:17 time: 0.5884 data_time: 0.0420 memory: 33630 grad_norm: 4.0377 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7437 loss: 1.7437 2022/10/14 23:58:32 - mmengine - INFO - Epoch(train) [32][800/940] lr: 1.0000e-02 eta: 10:29:05 time: 0.5939 data_time: 0.0346 memory: 33630 grad_norm: 4.0296 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.5103 loss: 1.5103 2022/10/14 23:58:44 - mmengine - INFO - Epoch(train) [32][820/940] lr: 1.0000e-02 eta: 10:28:53 time: 0.5829 data_time: 0.0388 memory: 33630 grad_norm: 4.1049 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6405 loss: 1.6405 2022/10/14 23:58:55 - mmengine - INFO - Epoch(train) [32][840/940] lr: 1.0000e-02 eta: 10:28:41 time: 0.5906 data_time: 0.0370 memory: 33630 grad_norm: 3.9399 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6340 loss: 1.6340 2022/10/14 23:59:07 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 23:59:07 - mmengine - INFO - Epoch(train) [32][860/940] lr: 1.0000e-02 eta: 10:28:30 time: 0.5855 data_time: 0.0363 memory: 33630 grad_norm: 4.0929 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6924 loss: 1.6924 2022/10/14 23:59:19 - mmengine - INFO - Epoch(train) [32][880/940] lr: 1.0000e-02 eta: 10:28:18 time: 0.5834 data_time: 0.0307 memory: 33630 grad_norm: 4.0363 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5742 loss: 1.5742 2022/10/14 23:59:31 - mmengine - INFO - Epoch(train) [32][900/940] lr: 1.0000e-02 eta: 10:28:06 time: 0.5957 data_time: 0.0471 memory: 33630 grad_norm: 4.0211 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5688 loss: 1.5688 2022/10/14 23:59:42 - mmengine - INFO - Epoch(train) [32][920/940] lr: 1.0000e-02 eta: 10:27:54 time: 0.5848 data_time: 0.0346 memory: 33630 grad_norm: 4.0623 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7107 loss: 1.7107 2022/10/14 23:59:53 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/14 23:59:53 - mmengine - INFO - Epoch(train) [32][940/940] lr: 1.0000e-02 eta: 10:27:40 time: 0.5449 data_time: 0.0357 memory: 33630 grad_norm: 4.2160 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.6136 loss: 1.6136 2022/10/15 00:00:08 - mmengine - INFO - Epoch(val) [32][20/78] eta: 0:00:43 time: 0.7491 data_time: 0.5795 memory: 5967 2022/10/15 00:00:18 - mmengine - INFO - Epoch(val) [32][40/78] eta: 0:00:18 time: 0.4905 data_time: 0.3211 memory: 5967 2022/10/15 00:00:32 - mmengine - INFO - Epoch(val) [32][60/78] eta: 0:00:12 time: 0.6800 data_time: 0.5107 memory: 5967 2022/10/15 00:00:44 - mmengine - INFO - Epoch(val) [32][78/78] acc/top1: 0.6443 acc/top5: 0.8520 acc/mean1: 0.6443 2022/10/15 00:01:01 - mmengine - INFO - Epoch(train) [33][20/940] lr: 1.0000e-02 eta: 10:27:39 time: 0.8240 data_time: 0.2346 memory: 33630 grad_norm: 4.0228 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.6906 loss: 1.6906 2022/10/15 00:01:13 - mmengine - INFO - Epoch(train) [33][40/940] lr: 1.0000e-02 eta: 10:27:27 time: 0.5846 data_time: 0.0322 memory: 33630 grad_norm: 4.0084 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7659 loss: 1.7659 2022/10/15 00:01:25 - mmengine - INFO - Epoch(train) [33][60/940] lr: 1.0000e-02 eta: 10:27:15 time: 0.5988 data_time: 0.0329 memory: 33630 grad_norm: 3.9319 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5651 loss: 1.5651 2022/10/15 00:01:36 - mmengine - INFO - Epoch(train) [33][80/940] lr: 1.0000e-02 eta: 10:27:03 time: 0.5756 data_time: 0.0322 memory: 33630 grad_norm: 4.0326 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6121 loss: 1.6121 2022/10/15 00:01:48 - mmengine - INFO - Epoch(train) [33][100/940] lr: 1.0000e-02 eta: 10:26:51 time: 0.5975 data_time: 0.0357 memory: 33630 grad_norm: 4.0459 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6480 loss: 1.6480 2022/10/15 00:02:00 - mmengine - INFO - Epoch(train) [33][120/940] lr: 1.0000e-02 eta: 10:26:39 time: 0.5842 data_time: 0.0301 memory: 33630 grad_norm: 3.9690 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6185 loss: 1.6185 2022/10/15 00:02:12 - mmengine - INFO - Epoch(train) [33][140/940] lr: 1.0000e-02 eta: 10:26:28 time: 0.5924 data_time: 0.0349 memory: 33630 grad_norm: 3.9515 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.5058 loss: 1.5058 2022/10/15 00:02:23 - mmengine - INFO - Epoch(train) [33][160/940] lr: 1.0000e-02 eta: 10:26:16 time: 0.5943 data_time: 0.0413 memory: 33630 grad_norm: 4.0272 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6700 loss: 1.6700 2022/10/15 00:02:35 - mmengine - INFO - Epoch(train) [33][180/940] lr: 1.0000e-02 eta: 10:26:05 time: 0.5993 data_time: 0.0304 memory: 33630 grad_norm: 4.0754 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6136 loss: 1.6136 2022/10/15 00:02:47 - mmengine - INFO - Epoch(train) [33][200/940] lr: 1.0000e-02 eta: 10:25:52 time: 0.5756 data_time: 0.0361 memory: 33630 grad_norm: 4.0246 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5066 loss: 1.5066 2022/10/15 00:02:59 - mmengine - INFO - Epoch(train) [33][220/940] lr: 1.0000e-02 eta: 10:25:41 time: 0.5994 data_time: 0.0367 memory: 33630 grad_norm: 4.0013 top1_acc: 0.5000 top5_acc: 0.9062 loss_cls: 1.5514 loss: 1.5514 2022/10/15 00:03:11 - mmengine - INFO - Epoch(train) [33][240/940] lr: 1.0000e-02 eta: 10:25:29 time: 0.5838 data_time: 0.0375 memory: 33630 grad_norm: 4.0462 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6392 loss: 1.6392 2022/10/15 00:03:22 - mmengine - INFO - Epoch(train) [33][260/940] lr: 1.0000e-02 eta: 10:25:17 time: 0.5807 data_time: 0.0440 memory: 33630 grad_norm: 4.0750 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.5931 loss: 1.5931 2022/10/15 00:03:34 - mmengine - INFO - Epoch(train) [33][280/940] lr: 1.0000e-02 eta: 10:25:05 time: 0.5944 data_time: 0.0313 memory: 33630 grad_norm: 4.1129 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5590 loss: 1.5590 2022/10/15 00:03:46 - mmengine - INFO - Epoch(train) [33][300/940] lr: 1.0000e-02 eta: 10:24:53 time: 0.5863 data_time: 0.0355 memory: 33630 grad_norm: 4.0332 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5809 loss: 1.5809 2022/10/15 00:03:57 - mmengine - INFO - Epoch(train) [33][320/940] lr: 1.0000e-02 eta: 10:24:41 time: 0.5847 data_time: 0.0354 memory: 33630 grad_norm: 4.0041 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5933 loss: 1.5933 2022/10/15 00:04:09 - mmengine - INFO - Epoch(train) [33][340/940] lr: 1.0000e-02 eta: 10:24:29 time: 0.5856 data_time: 0.0416 memory: 33630 grad_norm: 4.0197 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6152 loss: 1.6152 2022/10/15 00:04:21 - mmengine - INFO - Epoch(train) [33][360/940] lr: 1.0000e-02 eta: 10:24:17 time: 0.5818 data_time: 0.0293 memory: 33630 grad_norm: 3.9830 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3908 loss: 1.3908 2022/10/15 00:04:33 - mmengine - INFO - Epoch(train) [33][380/940] lr: 1.0000e-02 eta: 10:24:06 time: 0.5929 data_time: 0.0433 memory: 33630 grad_norm: 4.0140 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5503 loss: 1.5503 2022/10/15 00:04:44 - mmengine - INFO - Epoch(train) [33][400/940] lr: 1.0000e-02 eta: 10:23:53 time: 0.5792 data_time: 0.0404 memory: 33630 grad_norm: 4.0461 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.6460 loss: 1.6460 2022/10/15 00:04:56 - mmengine - INFO - Epoch(train) [33][420/940] lr: 1.0000e-02 eta: 10:23:42 time: 0.5895 data_time: 0.0356 memory: 33630 grad_norm: 4.1171 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.6495 loss: 1.6495 2022/10/15 00:05:08 - mmengine - INFO - Epoch(train) [33][440/940] lr: 1.0000e-02 eta: 10:23:29 time: 0.5772 data_time: 0.0370 memory: 33630 grad_norm: 4.0899 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.7145 loss: 1.7145 2022/10/15 00:05:19 - mmengine - INFO - Epoch(train) [33][460/940] lr: 1.0000e-02 eta: 10:23:17 time: 0.5847 data_time: 0.0336 memory: 33630 grad_norm: 4.0602 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5707 loss: 1.5707 2022/10/15 00:05:31 - mmengine - INFO - Epoch(train) [33][480/940] lr: 1.0000e-02 eta: 10:23:05 time: 0.5801 data_time: 0.0409 memory: 33630 grad_norm: 4.1606 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7302 loss: 1.7302 2022/10/15 00:05:43 - mmengine - INFO - Epoch(train) [33][500/940] lr: 1.0000e-02 eta: 10:22:53 time: 0.5828 data_time: 0.0362 memory: 33630 grad_norm: 4.0174 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6097 loss: 1.6097 2022/10/15 00:05:54 - mmengine - INFO - Epoch(train) [33][520/940] lr: 1.0000e-02 eta: 10:22:41 time: 0.5885 data_time: 0.0305 memory: 33630 grad_norm: 3.9681 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5790 loss: 1.5790 2022/10/15 00:06:06 - mmengine - INFO - Epoch(train) [33][540/940] lr: 1.0000e-02 eta: 10:22:29 time: 0.5779 data_time: 0.0486 memory: 33630 grad_norm: 4.0211 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6619 loss: 1.6619 2022/10/15 00:06:18 - mmengine - INFO - Epoch(train) [33][560/940] lr: 1.0000e-02 eta: 10:22:17 time: 0.5810 data_time: 0.0349 memory: 33630 grad_norm: 4.1174 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6155 loss: 1.6155 2022/10/15 00:06:29 - mmengine - INFO - Epoch(train) [33][580/940] lr: 1.0000e-02 eta: 10:22:05 time: 0.5849 data_time: 0.0387 memory: 33630 grad_norm: 4.0766 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6817 loss: 1.6817 2022/10/15 00:06:41 - mmengine - INFO - Epoch(train) [33][600/940] lr: 1.0000e-02 eta: 10:21:54 time: 0.5966 data_time: 0.0352 memory: 33630 grad_norm: 4.0621 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.6865 loss: 1.6865 2022/10/15 00:06:53 - mmengine - INFO - Epoch(train) [33][620/940] lr: 1.0000e-02 eta: 10:21:42 time: 0.5828 data_time: 0.0366 memory: 33630 grad_norm: 4.1324 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5685 loss: 1.5685 2022/10/15 00:07:04 - mmengine - INFO - Epoch(train) [33][640/940] lr: 1.0000e-02 eta: 10:21:29 time: 0.5782 data_time: 0.0328 memory: 33630 grad_norm: 4.1055 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7702 loss: 1.7702 2022/10/15 00:07:16 - mmengine - INFO - Epoch(train) [33][660/940] lr: 1.0000e-02 eta: 10:21:18 time: 0.5936 data_time: 0.0404 memory: 33630 grad_norm: 4.0952 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7612 loss: 1.7612 2022/10/15 00:07:28 - mmengine - INFO - Epoch(train) [33][680/940] lr: 1.0000e-02 eta: 10:21:06 time: 0.5943 data_time: 0.0342 memory: 33630 grad_norm: 4.0889 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6215 loss: 1.6215 2022/10/15 00:07:40 - mmengine - INFO - Epoch(train) [33][700/940] lr: 1.0000e-02 eta: 10:20:54 time: 0.5863 data_time: 0.0479 memory: 33630 grad_norm: 4.0524 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.6692 loss: 1.6692 2022/10/15 00:07:52 - mmengine - INFO - Epoch(train) [33][720/940] lr: 1.0000e-02 eta: 10:20:43 time: 0.5969 data_time: 0.0364 memory: 33630 grad_norm: 4.0199 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5514 loss: 1.5514 2022/10/15 00:08:04 - mmengine - INFO - Epoch(train) [33][740/940] lr: 1.0000e-02 eta: 10:20:31 time: 0.5916 data_time: 0.0325 memory: 33630 grad_norm: 4.0298 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5978 loss: 1.5978 2022/10/15 00:08:15 - mmengine - INFO - Epoch(train) [33][760/940] lr: 1.0000e-02 eta: 10:20:19 time: 0.5855 data_time: 0.0394 memory: 33630 grad_norm: 4.0647 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6202 loss: 1.6202 2022/10/15 00:08:27 - mmengine - INFO - Epoch(train) [33][780/940] lr: 1.0000e-02 eta: 10:20:07 time: 0.5869 data_time: 0.0337 memory: 33630 grad_norm: 4.0577 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6775 loss: 1.6775 2022/10/15 00:08:39 - mmengine - INFO - Epoch(train) [33][800/940] lr: 1.0000e-02 eta: 10:19:56 time: 0.5971 data_time: 0.0319 memory: 33630 grad_norm: 4.0394 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5336 loss: 1.5336 2022/10/15 00:08:51 - mmengine - INFO - Epoch(train) [33][820/940] lr: 1.0000e-02 eta: 10:19:44 time: 0.6003 data_time: 0.0339 memory: 33630 grad_norm: 4.1613 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.6469 loss: 1.6469 2022/10/15 00:09:03 - mmengine - INFO - Epoch(train) [33][840/940] lr: 1.0000e-02 eta: 10:19:32 time: 0.5823 data_time: 0.0362 memory: 33630 grad_norm: 4.1667 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6459 loss: 1.6459 2022/10/15 00:09:14 - mmengine - INFO - Epoch(train) [33][860/940] lr: 1.0000e-02 eta: 10:19:20 time: 0.5860 data_time: 0.0311 memory: 33630 grad_norm: 4.0858 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6501 loss: 1.6501 2022/10/15 00:09:26 - mmengine - INFO - Epoch(train) [33][880/940] lr: 1.0000e-02 eta: 10:19:09 time: 0.5885 data_time: 0.0396 memory: 33630 grad_norm: 4.0633 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.6599 loss: 1.6599 2022/10/15 00:09:38 - mmengine - INFO - Epoch(train) [33][900/940] lr: 1.0000e-02 eta: 10:18:56 time: 0.5732 data_time: 0.0353 memory: 33630 grad_norm: 4.2218 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5610 loss: 1.5610 2022/10/15 00:09:49 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 00:09:49 - mmengine - INFO - Epoch(train) [33][920/940] lr: 1.0000e-02 eta: 10:18:44 time: 0.5727 data_time: 0.0434 memory: 33630 grad_norm: 4.0256 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.6124 loss: 1.6124 2022/10/15 00:10:00 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 00:10:00 - mmengine - INFO - Epoch(train) [33][940/940] lr: 1.0000e-02 eta: 10:18:30 time: 0.5508 data_time: 0.0285 memory: 33630 grad_norm: 4.3300 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.6602 loss: 1.6602 2022/10/15 00:10:00 - mmengine - INFO - Saving checkpoint at 33 epochs 2022/10/15 00:10:15 - mmengine - INFO - Epoch(val) [33][20/78] eta: 0:00:42 time: 0.7270 data_time: 0.5550 memory: 5967 2022/10/15 00:10:26 - mmengine - INFO - Epoch(val) [33][40/78] eta: 0:00:19 time: 0.5052 data_time: 0.3369 memory: 5967 2022/10/15 00:10:38 - mmengine - INFO - Epoch(val) [33][60/78] eta: 0:00:10 time: 0.6009 data_time: 0.4297 memory: 5967 2022/10/15 00:10:50 - mmengine - INFO - Epoch(val) [33][78/78] acc/top1: 0.6265 acc/top5: 0.8388 acc/mean1: 0.6263 2022/10/15 00:11:06 - mmengine - INFO - Epoch(train) [34][20/940] lr: 1.0000e-02 eta: 10:18:29 time: 0.8354 data_time: 0.2566 memory: 33630 grad_norm: 4.0908 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6257 loss: 1.6257 2022/10/15 00:11:19 - mmengine - INFO - Epoch(train) [34][40/940] lr: 1.0000e-02 eta: 10:18:18 time: 0.6118 data_time: 0.0358 memory: 33630 grad_norm: 4.0338 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.6369 loss: 1.6369 2022/10/15 00:11:30 - mmengine - INFO - Epoch(train) [34][60/940] lr: 1.0000e-02 eta: 10:18:06 time: 0.5888 data_time: 0.0364 memory: 33630 grad_norm: 3.9879 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6841 loss: 1.6841 2022/10/15 00:11:42 - mmengine - INFO - Epoch(train) [34][80/940] lr: 1.0000e-02 eta: 10:17:54 time: 0.5783 data_time: 0.0310 memory: 33630 grad_norm: 3.9854 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6349 loss: 1.6349 2022/10/15 00:11:54 - mmengine - INFO - Epoch(train) [34][100/940] lr: 1.0000e-02 eta: 10:17:42 time: 0.5905 data_time: 0.0435 memory: 33630 grad_norm: 4.0623 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5659 loss: 1.5659 2022/10/15 00:12:06 - mmengine - INFO - Epoch(train) [34][120/940] lr: 1.0000e-02 eta: 10:17:30 time: 0.5950 data_time: 0.0379 memory: 33630 grad_norm: 4.0020 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5480 loss: 1.5480 2022/10/15 00:12:18 - mmengine - INFO - Epoch(train) [34][140/940] lr: 1.0000e-02 eta: 10:17:19 time: 0.5959 data_time: 0.0397 memory: 33630 grad_norm: 4.0762 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7108 loss: 1.7108 2022/10/15 00:12:29 - mmengine - INFO - Epoch(train) [34][160/940] lr: 1.0000e-02 eta: 10:17:07 time: 0.5809 data_time: 0.0338 memory: 33630 grad_norm: 4.0729 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6966 loss: 1.6966 2022/10/15 00:12:41 - mmengine - INFO - Epoch(train) [34][180/940] lr: 1.0000e-02 eta: 10:16:54 time: 0.5773 data_time: 0.0320 memory: 33630 grad_norm: 4.0290 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 1.5703 loss: 1.5703 2022/10/15 00:12:52 - mmengine - INFO - Epoch(train) [34][200/940] lr: 1.0000e-02 eta: 10:16:42 time: 0.5757 data_time: 0.0349 memory: 33630 grad_norm: 4.0359 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5192 loss: 1.5192 2022/10/15 00:13:04 - mmengine - INFO - Epoch(train) [34][220/940] lr: 1.0000e-02 eta: 10:16:30 time: 0.5825 data_time: 0.0401 memory: 33630 grad_norm: 4.0684 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4664 loss: 1.4664 2022/10/15 00:13:16 - mmengine - INFO - Epoch(train) [34][240/940] lr: 1.0000e-02 eta: 10:16:18 time: 0.5808 data_time: 0.0342 memory: 33630 grad_norm: 4.1253 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5608 loss: 1.5608 2022/10/15 00:13:27 - mmengine - INFO - Epoch(train) [34][260/940] lr: 1.0000e-02 eta: 10:16:06 time: 0.5810 data_time: 0.0396 memory: 33630 grad_norm: 4.1699 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5709 loss: 1.5709 2022/10/15 00:13:39 - mmengine - INFO - Epoch(train) [34][280/940] lr: 1.0000e-02 eta: 10:15:54 time: 0.5875 data_time: 0.0312 memory: 33630 grad_norm: 3.9974 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5578 loss: 1.5578 2022/10/15 00:13:51 - mmengine - INFO - Epoch(train) [34][300/940] lr: 1.0000e-02 eta: 10:15:42 time: 0.5847 data_time: 0.0313 memory: 33630 grad_norm: 3.9797 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6290 loss: 1.6290 2022/10/15 00:14:02 - mmengine - INFO - Epoch(train) [34][320/940] lr: 1.0000e-02 eta: 10:15:30 time: 0.5773 data_time: 0.0321 memory: 33630 grad_norm: 3.9658 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.6194 loss: 1.6194 2022/10/15 00:14:14 - mmengine - INFO - Epoch(train) [34][340/940] lr: 1.0000e-02 eta: 10:15:18 time: 0.6048 data_time: 0.0432 memory: 33630 grad_norm: 4.0479 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.5508 loss: 1.5508 2022/10/15 00:14:26 - mmengine - INFO - Epoch(train) [34][360/940] lr: 1.0000e-02 eta: 10:15:07 time: 0.5988 data_time: 0.0323 memory: 33630 grad_norm: 4.1195 top1_acc: 0.5312 top5_acc: 0.9375 loss_cls: 1.5502 loss: 1.5502 2022/10/15 00:14:39 - mmengine - INFO - Epoch(train) [34][380/940] lr: 1.0000e-02 eta: 10:14:56 time: 0.6173 data_time: 0.0369 memory: 33630 grad_norm: 4.0788 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.5672 loss: 1.5672 2022/10/15 00:14:50 - mmengine - INFO - Epoch(train) [34][400/940] lr: 1.0000e-02 eta: 10:14:44 time: 0.5829 data_time: 0.0317 memory: 33630 grad_norm: 3.9490 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5465 loss: 1.5465 2022/10/15 00:15:02 - mmengine - INFO - Epoch(train) [34][420/940] lr: 1.0000e-02 eta: 10:14:32 time: 0.5864 data_time: 0.0416 memory: 33630 grad_norm: 4.0399 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7798 loss: 1.7798 2022/10/15 00:15:14 - mmengine - INFO - Epoch(train) [34][440/940] lr: 1.0000e-02 eta: 10:14:21 time: 0.5976 data_time: 0.0333 memory: 33630 grad_norm: 3.9765 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4536 loss: 1.4536 2022/10/15 00:15:26 - mmengine - INFO - Epoch(train) [34][460/940] lr: 1.0000e-02 eta: 10:14:09 time: 0.5822 data_time: 0.0467 memory: 33630 grad_norm: 4.0838 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.5988 loss: 1.5988 2022/10/15 00:15:37 - mmengine - INFO - Epoch(train) [34][480/940] lr: 1.0000e-02 eta: 10:13:57 time: 0.5899 data_time: 0.0373 memory: 33630 grad_norm: 4.2160 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8061 loss: 1.8061 2022/10/15 00:15:49 - mmengine - INFO - Epoch(train) [34][500/940] lr: 1.0000e-02 eta: 10:13:45 time: 0.5835 data_time: 0.0332 memory: 33630 grad_norm: 4.1442 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.4942 loss: 1.4942 2022/10/15 00:16:01 - mmengine - INFO - Epoch(train) [34][520/940] lr: 1.0000e-02 eta: 10:13:33 time: 0.5874 data_time: 0.0348 memory: 33630 grad_norm: 4.1323 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6978 loss: 1.6978 2022/10/15 00:16:13 - mmengine - INFO - Epoch(train) [34][540/940] lr: 1.0000e-02 eta: 10:13:21 time: 0.5833 data_time: 0.0328 memory: 33630 grad_norm: 4.0842 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5580 loss: 1.5580 2022/10/15 00:16:24 - mmengine - INFO - Epoch(train) [34][560/940] lr: 1.0000e-02 eta: 10:13:09 time: 0.5816 data_time: 0.0347 memory: 33630 grad_norm: 4.0860 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4998 loss: 1.4998 2022/10/15 00:16:36 - mmengine - INFO - Epoch(train) [34][580/940] lr: 1.0000e-02 eta: 10:12:57 time: 0.5768 data_time: 0.0328 memory: 33630 grad_norm: 4.0650 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.6988 loss: 1.6988 2022/10/15 00:16:47 - mmengine - INFO - Epoch(train) [34][600/940] lr: 1.0000e-02 eta: 10:12:44 time: 0.5766 data_time: 0.0304 memory: 33630 grad_norm: 4.1305 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6286 loss: 1.6286 2022/10/15 00:16:59 - mmengine - INFO - Epoch(train) [34][620/940] lr: 1.0000e-02 eta: 10:12:33 time: 0.5886 data_time: 0.0323 memory: 33630 grad_norm: 4.0853 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7167 loss: 1.7167 2022/10/15 00:17:11 - mmengine - INFO - Epoch(train) [34][640/940] lr: 1.0000e-02 eta: 10:12:21 time: 0.5802 data_time: 0.0339 memory: 33630 grad_norm: 4.1675 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7100 loss: 1.7100 2022/10/15 00:17:22 - mmengine - INFO - Epoch(train) [34][660/940] lr: 1.0000e-02 eta: 10:12:08 time: 0.5782 data_time: 0.0361 memory: 33630 grad_norm: 4.0916 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7139 loss: 1.7139 2022/10/15 00:17:34 - mmengine - INFO - Epoch(train) [34][680/940] lr: 1.0000e-02 eta: 10:11:56 time: 0.5818 data_time: 0.0366 memory: 33630 grad_norm: 4.1135 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5869 loss: 1.5869 2022/10/15 00:17:46 - mmengine - INFO - Epoch(train) [34][700/940] lr: 1.0000e-02 eta: 10:11:44 time: 0.5879 data_time: 0.0375 memory: 33630 grad_norm: 4.0579 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6232 loss: 1.6232 2022/10/15 00:17:57 - mmengine - INFO - Epoch(train) [34][720/940] lr: 1.0000e-02 eta: 10:11:32 time: 0.5772 data_time: 0.0363 memory: 33630 grad_norm: 4.0647 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4894 loss: 1.4894 2022/10/15 00:18:09 - mmengine - INFO - Epoch(train) [34][740/940] lr: 1.0000e-02 eta: 10:11:20 time: 0.5852 data_time: 0.0385 memory: 33630 grad_norm: 4.0949 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7059 loss: 1.7059 2022/10/15 00:18:21 - mmengine - INFO - Epoch(train) [34][760/940] lr: 1.0000e-02 eta: 10:11:09 time: 0.6108 data_time: 0.0314 memory: 33630 grad_norm: 4.1302 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6308 loss: 1.6308 2022/10/15 00:18:33 - mmengine - INFO - Epoch(train) [34][780/940] lr: 1.0000e-02 eta: 10:10:57 time: 0.5753 data_time: 0.0312 memory: 33630 grad_norm: 4.0771 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5854 loss: 1.5854 2022/10/15 00:18:44 - mmengine - INFO - Epoch(train) [34][800/940] lr: 1.0000e-02 eta: 10:10:45 time: 0.5906 data_time: 0.0329 memory: 33630 grad_norm: 4.0999 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7142 loss: 1.7142 2022/10/15 00:18:56 - mmengine - INFO - Epoch(train) [34][820/940] lr: 1.0000e-02 eta: 10:10:34 time: 0.5971 data_time: 0.0427 memory: 33630 grad_norm: 4.0797 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5315 loss: 1.5315 2022/10/15 00:19:08 - mmengine - INFO - Epoch(train) [34][840/940] lr: 1.0000e-02 eta: 10:10:22 time: 0.5829 data_time: 0.0350 memory: 33630 grad_norm: 4.0483 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.6610 loss: 1.6610 2022/10/15 00:19:20 - mmengine - INFO - Epoch(train) [34][860/940] lr: 1.0000e-02 eta: 10:10:10 time: 0.5863 data_time: 0.0365 memory: 33630 grad_norm: 4.0717 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7417 loss: 1.7417 2022/10/15 00:19:32 - mmengine - INFO - Epoch(train) [34][880/940] lr: 1.0000e-02 eta: 10:09:58 time: 0.5920 data_time: 0.0346 memory: 33630 grad_norm: 4.1016 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5671 loss: 1.5671 2022/10/15 00:19:43 - mmengine - INFO - Epoch(train) [34][900/940] lr: 1.0000e-02 eta: 10:09:46 time: 0.5919 data_time: 0.0352 memory: 33630 grad_norm: 4.0281 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6313 loss: 1.6313 2022/10/15 00:19:55 - mmengine - INFO - Epoch(train) [34][920/940] lr: 1.0000e-02 eta: 10:09:34 time: 0.5820 data_time: 0.0359 memory: 33630 grad_norm: 4.1786 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.5758 loss: 1.5758 2022/10/15 00:20:06 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 00:20:06 - mmengine - INFO - Epoch(train) [34][940/940] lr: 1.0000e-02 eta: 10:09:21 time: 0.5421 data_time: 0.0310 memory: 33630 grad_norm: 4.3471 top1_acc: 0.2857 top5_acc: 0.5714 loss_cls: 1.7703 loss: 1.7703 2022/10/15 00:20:21 - mmengine - INFO - Epoch(val) [34][20/78] eta: 0:00:43 time: 0.7434 data_time: 0.5715 memory: 5967 2022/10/15 00:20:31 - mmengine - INFO - Epoch(val) [34][40/78] eta: 0:00:19 time: 0.5214 data_time: 0.3510 memory: 5967 2022/10/15 00:20:46 - mmengine - INFO - Epoch(val) [34][60/78] eta: 0:00:13 time: 0.7264 data_time: 0.5576 memory: 5967 2022/10/15 00:20:56 - mmengine - INFO - Epoch(val) [34][78/78] acc/top1: 0.6426 acc/top5: 0.8499 acc/mean1: 0.6424 2022/10/15 00:21:13 - mmengine - INFO - Epoch(train) [35][20/940] lr: 1.0000e-02 eta: 10:09:19 time: 0.8408 data_time: 0.2263 memory: 33630 grad_norm: 3.9870 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.4061 loss: 1.4061 2022/10/15 00:21:25 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 00:21:25 - mmengine - INFO - Epoch(train) [35][40/940] lr: 1.0000e-02 eta: 10:09:07 time: 0.5984 data_time: 0.0321 memory: 33630 grad_norm: 4.1519 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6260 loss: 1.6260 2022/10/15 00:21:37 - mmengine - INFO - Epoch(train) [35][60/940] lr: 1.0000e-02 eta: 10:08:56 time: 0.5947 data_time: 0.0395 memory: 33630 grad_norm: 4.0248 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.6038 loss: 1.6038 2022/10/15 00:21:49 - mmengine - INFO - Epoch(train) [35][80/940] lr: 1.0000e-02 eta: 10:08:44 time: 0.5946 data_time: 0.0392 memory: 33630 grad_norm: 4.1031 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4693 loss: 1.4693 2022/10/15 00:22:01 - mmengine - INFO - Epoch(train) [35][100/940] lr: 1.0000e-02 eta: 10:08:32 time: 0.5941 data_time: 0.0405 memory: 33630 grad_norm: 4.0440 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5728 loss: 1.5728 2022/10/15 00:22:13 - mmengine - INFO - Epoch(train) [35][120/940] lr: 1.0000e-02 eta: 10:08:21 time: 0.5914 data_time: 0.0350 memory: 33630 grad_norm: 4.1154 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 1.6882 loss: 1.6882 2022/10/15 00:22:25 - mmengine - INFO - Epoch(train) [35][140/940] lr: 1.0000e-02 eta: 10:08:09 time: 0.5958 data_time: 0.0316 memory: 33630 grad_norm: 3.9882 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.6876 loss: 1.6876 2022/10/15 00:22:36 - mmengine - INFO - Epoch(train) [35][160/940] lr: 1.0000e-02 eta: 10:07:57 time: 0.5881 data_time: 0.0386 memory: 33630 grad_norm: 4.0714 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6517 loss: 1.6517 2022/10/15 00:22:48 - mmengine - INFO - Epoch(train) [35][180/940] lr: 1.0000e-02 eta: 10:07:45 time: 0.5775 data_time: 0.0372 memory: 33630 grad_norm: 4.1189 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6361 loss: 1.6361 2022/10/15 00:23:00 - mmengine - INFO - Epoch(train) [35][200/940] lr: 1.0000e-02 eta: 10:07:33 time: 0.5874 data_time: 0.0328 memory: 33630 grad_norm: 4.0436 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5977 loss: 1.5977 2022/10/15 00:23:11 - mmengine - INFO - Epoch(train) [35][220/940] lr: 1.0000e-02 eta: 10:07:21 time: 0.5889 data_time: 0.0331 memory: 33630 grad_norm: 4.0522 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6054 loss: 1.6054 2022/10/15 00:23:23 - mmengine - INFO - Epoch(train) [35][240/940] lr: 1.0000e-02 eta: 10:07:10 time: 0.5924 data_time: 0.0309 memory: 33630 grad_norm: 4.0420 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5581 loss: 1.5581 2022/10/15 00:23:35 - mmengine - INFO - Epoch(train) [35][260/940] lr: 1.0000e-02 eta: 10:06:57 time: 0.5724 data_time: 0.0330 memory: 33630 grad_norm: 4.0510 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6122 loss: 1.6122 2022/10/15 00:23:46 - mmengine - INFO - Epoch(train) [35][280/940] lr: 1.0000e-02 eta: 10:06:45 time: 0.5843 data_time: 0.0351 memory: 33630 grad_norm: 4.0536 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.4310 loss: 1.4310 2022/10/15 00:23:58 - mmengine - INFO - Epoch(train) [35][300/940] lr: 1.0000e-02 eta: 10:06:33 time: 0.5851 data_time: 0.0357 memory: 33630 grad_norm: 4.1317 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5306 loss: 1.5306 2022/10/15 00:24:10 - mmengine - INFO - Epoch(train) [35][320/940] lr: 1.0000e-02 eta: 10:06:21 time: 0.5872 data_time: 0.0355 memory: 33630 grad_norm: 4.0824 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4618 loss: 1.4618 2022/10/15 00:24:21 - mmengine - INFO - Epoch(train) [35][340/940] lr: 1.0000e-02 eta: 10:06:09 time: 0.5784 data_time: 0.0309 memory: 33630 grad_norm: 4.0602 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6814 loss: 1.6814 2022/10/15 00:24:33 - mmengine - INFO - Epoch(train) [35][360/940] lr: 1.0000e-02 eta: 10:05:57 time: 0.5860 data_time: 0.0373 memory: 33630 grad_norm: 4.0523 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.6675 loss: 1.6675 2022/10/15 00:24:45 - mmengine - INFO - Epoch(train) [35][380/940] lr: 1.0000e-02 eta: 10:05:45 time: 0.5813 data_time: 0.0365 memory: 33630 grad_norm: 4.1488 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.5459 loss: 1.5459 2022/10/15 00:24:56 - mmengine - INFO - Epoch(train) [35][400/940] lr: 1.0000e-02 eta: 10:05:32 time: 0.5663 data_time: 0.0328 memory: 33630 grad_norm: 4.0678 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6039 loss: 1.6039 2022/10/15 00:25:08 - mmengine - INFO - Epoch(train) [35][420/940] lr: 1.0000e-02 eta: 10:05:21 time: 0.5872 data_time: 0.0347 memory: 33630 grad_norm: 4.0995 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5990 loss: 1.5990 2022/10/15 00:25:19 - mmengine - INFO - Epoch(train) [35][440/940] lr: 1.0000e-02 eta: 10:05:08 time: 0.5797 data_time: 0.0451 memory: 33630 grad_norm: 4.0460 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6217 loss: 1.6217 2022/10/15 00:25:31 - mmengine - INFO - Epoch(train) [35][460/940] lr: 1.0000e-02 eta: 10:04:57 time: 0.5967 data_time: 0.0331 memory: 33630 grad_norm: 4.0878 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6183 loss: 1.6183 2022/10/15 00:25:43 - mmengine - INFO - Epoch(train) [35][480/940] lr: 1.0000e-02 eta: 10:04:45 time: 0.5742 data_time: 0.0401 memory: 33630 grad_norm: 4.1030 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5538 loss: 1.5538 2022/10/15 00:25:54 - mmengine - INFO - Epoch(train) [35][500/940] lr: 1.0000e-02 eta: 10:04:32 time: 0.5806 data_time: 0.0371 memory: 33630 grad_norm: 4.0936 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6121 loss: 1.6121 2022/10/15 00:26:06 - mmengine - INFO - Epoch(train) [35][520/940] lr: 1.0000e-02 eta: 10:04:20 time: 0.5775 data_time: 0.0380 memory: 33630 grad_norm: 4.1760 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.5087 loss: 1.5087 2022/10/15 00:26:18 - mmengine - INFO - Epoch(train) [35][540/940] lr: 1.0000e-02 eta: 10:04:09 time: 0.5993 data_time: 0.0337 memory: 33630 grad_norm: 4.1211 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.5528 loss: 1.5528 2022/10/15 00:26:30 - mmengine - INFO - Epoch(train) [35][560/940] lr: 1.0000e-02 eta: 10:03:57 time: 0.5864 data_time: 0.0375 memory: 33630 grad_norm: 4.1014 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4739 loss: 1.4739 2022/10/15 00:26:41 - mmengine - INFO - Epoch(train) [35][580/940] lr: 1.0000e-02 eta: 10:03:45 time: 0.5770 data_time: 0.0376 memory: 33630 grad_norm: 4.1977 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7263 loss: 1.7263 2022/10/15 00:26:53 - mmengine - INFO - Epoch(train) [35][600/940] lr: 1.0000e-02 eta: 10:03:33 time: 0.5856 data_time: 0.0291 memory: 33630 grad_norm: 4.0877 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.4918 loss: 1.4918 2022/10/15 00:27:05 - mmengine - INFO - Epoch(train) [35][620/940] lr: 1.0000e-02 eta: 10:03:21 time: 0.5976 data_time: 0.0406 memory: 33630 grad_norm: 4.0961 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.6274 loss: 1.6274 2022/10/15 00:27:17 - mmengine - INFO - Epoch(train) [35][640/940] lr: 1.0000e-02 eta: 10:03:09 time: 0.5796 data_time: 0.0422 memory: 33630 grad_norm: 4.1761 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5813 loss: 1.5813 2022/10/15 00:27:28 - mmengine - INFO - Epoch(train) [35][660/940] lr: 1.0000e-02 eta: 10:02:57 time: 0.5825 data_time: 0.0410 memory: 33630 grad_norm: 4.2030 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.6192 loss: 1.6192 2022/10/15 00:27:40 - mmengine - INFO - Epoch(train) [35][680/940] lr: 1.0000e-02 eta: 10:02:45 time: 0.5795 data_time: 0.0364 memory: 33630 grad_norm: 4.0237 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5126 loss: 1.5126 2022/10/15 00:27:51 - mmengine - INFO - Epoch(train) [35][700/940] lr: 1.0000e-02 eta: 10:02:33 time: 0.5831 data_time: 0.0322 memory: 33630 grad_norm: 4.1378 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6632 loss: 1.6632 2022/10/15 00:28:03 - mmengine - INFO - Epoch(train) [35][720/940] lr: 1.0000e-02 eta: 10:02:21 time: 0.5925 data_time: 0.0443 memory: 33630 grad_norm: 4.1661 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6435 loss: 1.6435 2022/10/15 00:28:15 - mmengine - INFO - Epoch(train) [35][740/940] lr: 1.0000e-02 eta: 10:02:09 time: 0.5782 data_time: 0.0330 memory: 33630 grad_norm: 4.0437 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.5909 loss: 1.5909 2022/10/15 00:28:26 - mmengine - INFO - Epoch(train) [35][760/940] lr: 1.0000e-02 eta: 10:01:57 time: 0.5813 data_time: 0.0398 memory: 33630 grad_norm: 4.0718 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7369 loss: 1.7369 2022/10/15 00:28:38 - mmengine - INFO - Epoch(train) [35][780/940] lr: 1.0000e-02 eta: 10:01:45 time: 0.5980 data_time: 0.0373 memory: 33630 grad_norm: 4.2094 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6692 loss: 1.6692 2022/10/15 00:28:50 - mmengine - INFO - Epoch(train) [35][800/940] lr: 1.0000e-02 eta: 10:01:34 time: 0.5879 data_time: 0.0302 memory: 33630 grad_norm: 4.1495 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6357 loss: 1.6357 2022/10/15 00:29:02 - mmengine - INFO - Epoch(train) [35][820/940] lr: 1.0000e-02 eta: 10:01:22 time: 0.5882 data_time: 0.0310 memory: 33630 grad_norm: 4.0725 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6406 loss: 1.6406 2022/10/15 00:29:14 - mmengine - INFO - Epoch(train) [35][840/940] lr: 1.0000e-02 eta: 10:01:10 time: 0.5882 data_time: 0.0435 memory: 33630 grad_norm: 4.1367 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6358 loss: 1.6358 2022/10/15 00:29:25 - mmengine - INFO - Epoch(train) [35][860/940] lr: 1.0000e-02 eta: 10:00:58 time: 0.5797 data_time: 0.0384 memory: 33630 grad_norm: 4.1474 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6946 loss: 1.6946 2022/10/15 00:29:37 - mmengine - INFO - Epoch(train) [35][880/940] lr: 1.0000e-02 eta: 10:00:46 time: 0.5913 data_time: 0.0317 memory: 33630 grad_norm: 4.1612 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5488 loss: 1.5488 2022/10/15 00:29:49 - mmengine - INFO - Epoch(train) [35][900/940] lr: 1.0000e-02 eta: 10:00:34 time: 0.5707 data_time: 0.0373 memory: 33630 grad_norm: 4.1296 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5105 loss: 1.5105 2022/10/15 00:30:00 - mmengine - INFO - Epoch(train) [35][920/940] lr: 1.0000e-02 eta: 10:00:22 time: 0.5927 data_time: 0.0370 memory: 33630 grad_norm: 4.1707 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6276 loss: 1.6276 2022/10/15 00:30:11 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 00:30:11 - mmengine - INFO - Epoch(train) [35][940/940] lr: 1.0000e-02 eta: 10:00:08 time: 0.5393 data_time: 0.0291 memory: 33630 grad_norm: 4.3711 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.6314 loss: 1.6314 2022/10/15 00:30:25 - mmengine - INFO - Epoch(val) [35][20/78] eta: 0:00:41 time: 0.7104 data_time: 0.5420 memory: 5967 2022/10/15 00:30:35 - mmengine - INFO - Epoch(val) [35][40/78] eta: 0:00:18 time: 0.4948 data_time: 0.3270 memory: 5967 2022/10/15 00:30:50 - mmengine - INFO - Epoch(val) [35][60/78] eta: 0:00:13 time: 0.7491 data_time: 0.5813 memory: 5967 2022/10/15 00:31:01 - mmengine - INFO - Epoch(val) [35][78/78] acc/top1: 0.6348 acc/top5: 0.8484 acc/mean1: 0.6346 2022/10/15 00:31:18 - mmengine - INFO - Epoch(train) [36][20/940] lr: 1.0000e-02 eta: 10:00:05 time: 0.8294 data_time: 0.2198 memory: 33630 grad_norm: 4.0886 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.5365 loss: 1.5365 2022/10/15 00:31:31 - mmengine - INFO - Epoch(train) [36][40/940] lr: 1.0000e-02 eta: 9:59:55 time: 0.6322 data_time: 0.0346 memory: 33630 grad_norm: 3.9724 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4794 loss: 1.4794 2022/10/15 00:31:43 - mmengine - INFO - Epoch(train) [36][60/940] lr: 1.0000e-02 eta: 9:59:44 time: 0.5953 data_time: 0.0310 memory: 33630 grad_norm: 3.9913 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6318 loss: 1.6318 2022/10/15 00:31:56 - mmengine - INFO - Epoch(train) [36][80/940] lr: 1.0000e-02 eta: 9:59:34 time: 0.6418 data_time: 0.0346 memory: 33630 grad_norm: 4.0972 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.5797 loss: 1.5797 2022/10/15 00:32:07 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 00:32:07 - mmengine - INFO - Epoch(train) [36][100/940] lr: 1.0000e-02 eta: 9:59:22 time: 0.5958 data_time: 0.0349 memory: 33630 grad_norm: 4.1329 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6958 loss: 1.6958 2022/10/15 00:32:19 - mmengine - INFO - Epoch(train) [36][120/940] lr: 1.0000e-02 eta: 9:59:10 time: 0.5857 data_time: 0.0401 memory: 33630 grad_norm: 4.1249 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.7080 loss: 1.7080 2022/10/15 00:32:31 - mmengine - INFO - Epoch(train) [36][140/940] lr: 1.0000e-02 eta: 9:58:58 time: 0.5886 data_time: 0.0404 memory: 33630 grad_norm: 4.0305 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5812 loss: 1.5812 2022/10/15 00:32:42 - mmengine - INFO - Epoch(train) [36][160/940] lr: 1.0000e-02 eta: 9:58:46 time: 0.5783 data_time: 0.0309 memory: 33630 grad_norm: 4.1296 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5460 loss: 1.5460 2022/10/15 00:32:54 - mmengine - INFO - Epoch(train) [36][180/940] lr: 1.0000e-02 eta: 9:58:34 time: 0.5799 data_time: 0.0374 memory: 33630 grad_norm: 4.0317 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6740 loss: 1.6740 2022/10/15 00:33:06 - mmengine - INFO - Epoch(train) [36][200/940] lr: 1.0000e-02 eta: 9:58:22 time: 0.5772 data_time: 0.0339 memory: 33630 grad_norm: 4.1627 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.6024 loss: 1.6024 2022/10/15 00:33:17 - mmengine - INFO - Epoch(train) [36][220/940] lr: 1.0000e-02 eta: 9:58:10 time: 0.5833 data_time: 0.0402 memory: 33630 grad_norm: 4.1147 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6064 loss: 1.6064 2022/10/15 00:33:29 - mmengine - INFO - Epoch(train) [36][240/940] lr: 1.0000e-02 eta: 9:57:58 time: 0.5874 data_time: 0.0351 memory: 33630 grad_norm: 4.1496 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6270 loss: 1.6270 2022/10/15 00:33:41 - mmengine - INFO - Epoch(train) [36][260/940] lr: 1.0000e-02 eta: 9:57:46 time: 0.5974 data_time: 0.0323 memory: 33630 grad_norm: 4.2298 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.7374 loss: 1.7374 2022/10/15 00:33:53 - mmengine - INFO - Epoch(train) [36][280/940] lr: 1.0000e-02 eta: 9:57:34 time: 0.5837 data_time: 0.0368 memory: 33630 grad_norm: 4.0418 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4880 loss: 1.4880 2022/10/15 00:34:04 - mmengine - INFO - Epoch(train) [36][300/940] lr: 1.0000e-02 eta: 9:57:23 time: 0.5904 data_time: 0.0353 memory: 33630 grad_norm: 4.0509 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5053 loss: 1.5053 2022/10/15 00:34:16 - mmengine - INFO - Epoch(train) [36][320/940] lr: 1.0000e-02 eta: 9:57:11 time: 0.5821 data_time: 0.0370 memory: 33630 grad_norm: 4.0905 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6487 loss: 1.6487 2022/10/15 00:34:28 - mmengine - INFO - Epoch(train) [36][340/940] lr: 1.0000e-02 eta: 9:56:59 time: 0.5841 data_time: 0.0442 memory: 33630 grad_norm: 4.1355 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.7060 loss: 1.7060 2022/10/15 00:34:39 - mmengine - INFO - Epoch(train) [36][360/940] lr: 1.0000e-02 eta: 9:56:46 time: 0.5750 data_time: 0.0391 memory: 33630 grad_norm: 4.1413 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7063 loss: 1.7063 2022/10/15 00:34:51 - mmengine - INFO - Epoch(train) [36][380/940] lr: 1.0000e-02 eta: 9:56:34 time: 0.5767 data_time: 0.0417 memory: 33630 grad_norm: 4.1133 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6568 loss: 1.6568 2022/10/15 00:35:02 - mmengine - INFO - Epoch(train) [36][400/940] lr: 1.0000e-02 eta: 9:56:22 time: 0.5768 data_time: 0.0304 memory: 33630 grad_norm: 3.9943 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5072 loss: 1.5072 2022/10/15 00:35:14 - mmengine - INFO - Epoch(train) [36][420/940] lr: 1.0000e-02 eta: 9:56:10 time: 0.5876 data_time: 0.0370 memory: 33630 grad_norm: 4.0916 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6001 loss: 1.6001 2022/10/15 00:35:26 - mmengine - INFO - Epoch(train) [36][440/940] lr: 1.0000e-02 eta: 9:55:58 time: 0.5755 data_time: 0.0298 memory: 33630 grad_norm: 4.1098 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5967 loss: 1.5967 2022/10/15 00:35:37 - mmengine - INFO - Epoch(train) [36][460/940] lr: 1.0000e-02 eta: 9:55:46 time: 0.5827 data_time: 0.0387 memory: 33630 grad_norm: 4.0969 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6514 loss: 1.6514 2022/10/15 00:35:49 - mmengine - INFO - Epoch(train) [36][480/940] lr: 1.0000e-02 eta: 9:55:34 time: 0.5862 data_time: 0.0324 memory: 33630 grad_norm: 4.0981 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5036 loss: 1.5036 2022/10/15 00:36:01 - mmengine - INFO - Epoch(train) [36][500/940] lr: 1.0000e-02 eta: 9:55:22 time: 0.5924 data_time: 0.0385 memory: 33630 grad_norm: 4.0057 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.6091 loss: 1.6091 2022/10/15 00:36:12 - mmengine - INFO - Epoch(train) [36][520/940] lr: 1.0000e-02 eta: 9:55:10 time: 0.5772 data_time: 0.0367 memory: 33630 grad_norm: 4.1585 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5168 loss: 1.5168 2022/10/15 00:36:24 - mmengine - INFO - Epoch(train) [36][540/940] lr: 1.0000e-02 eta: 9:54:58 time: 0.5911 data_time: 0.0396 memory: 33630 grad_norm: 4.1399 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6028 loss: 1.6028 2022/10/15 00:36:36 - mmengine - INFO - Epoch(train) [36][560/940] lr: 1.0000e-02 eta: 9:54:46 time: 0.5799 data_time: 0.0303 memory: 33630 grad_norm: 4.0802 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5879 loss: 1.5879 2022/10/15 00:36:47 - mmengine - INFO - Epoch(train) [36][580/940] lr: 1.0000e-02 eta: 9:54:34 time: 0.5817 data_time: 0.0381 memory: 33630 grad_norm: 3.9842 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4349 loss: 1.4349 2022/10/15 00:36:59 - mmengine - INFO - Epoch(train) [36][600/940] lr: 1.0000e-02 eta: 9:54:22 time: 0.5812 data_time: 0.0403 memory: 33630 grad_norm: 4.1121 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4155 loss: 1.4155 2022/10/15 00:37:11 - mmengine - INFO - Epoch(train) [36][620/940] lr: 1.0000e-02 eta: 9:54:10 time: 0.5838 data_time: 0.0373 memory: 33630 grad_norm: 4.1493 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7087 loss: 1.7087 2022/10/15 00:37:23 - mmengine - INFO - Epoch(train) [36][640/940] lr: 1.0000e-02 eta: 9:53:58 time: 0.5936 data_time: 0.0320 memory: 33630 grad_norm: 4.0637 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.5836 loss: 1.5836 2022/10/15 00:37:34 - mmengine - INFO - Epoch(train) [36][660/940] lr: 1.0000e-02 eta: 9:53:46 time: 0.5726 data_time: 0.0395 memory: 33630 grad_norm: 4.1627 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6560 loss: 1.6560 2022/10/15 00:37:46 - mmengine - INFO - Epoch(train) [36][680/940] lr: 1.0000e-02 eta: 9:53:34 time: 0.5868 data_time: 0.0401 memory: 33630 grad_norm: 4.1148 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6316 loss: 1.6316 2022/10/15 00:37:57 - mmengine - INFO - Epoch(train) [36][700/940] lr: 1.0000e-02 eta: 9:53:22 time: 0.5820 data_time: 0.0322 memory: 33630 grad_norm: 4.1899 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6491 loss: 1.6491 2022/10/15 00:38:09 - mmengine - INFO - Epoch(train) [36][720/940] lr: 1.0000e-02 eta: 9:53:09 time: 0.5715 data_time: 0.0389 memory: 33630 grad_norm: 4.1325 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.5038 loss: 1.5038 2022/10/15 00:38:21 - mmengine - INFO - Epoch(train) [36][740/940] lr: 1.0000e-02 eta: 9:52:57 time: 0.5849 data_time: 0.0370 memory: 33630 grad_norm: 4.1584 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.5488 loss: 1.5488 2022/10/15 00:38:32 - mmengine - INFO - Epoch(train) [36][760/940] lr: 1.0000e-02 eta: 9:52:46 time: 0.5895 data_time: 0.0378 memory: 33630 grad_norm: 4.0831 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.5734 loss: 1.5734 2022/10/15 00:38:44 - mmengine - INFO - Epoch(train) [36][780/940] lr: 1.0000e-02 eta: 9:52:34 time: 0.5821 data_time: 0.0369 memory: 33630 grad_norm: 4.0904 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.6293 loss: 1.6293 2022/10/15 00:38:56 - mmengine - INFO - Epoch(train) [36][800/940] lr: 1.0000e-02 eta: 9:52:21 time: 0.5815 data_time: 0.0422 memory: 33630 grad_norm: 4.2048 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6460 loss: 1.6460 2022/10/15 00:39:08 - mmengine - INFO - Epoch(train) [36][820/940] lr: 1.0000e-02 eta: 9:52:10 time: 0.5937 data_time: 0.0332 memory: 33630 grad_norm: 4.1085 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5327 loss: 1.5327 2022/10/15 00:39:19 - mmengine - INFO - Epoch(train) [36][840/940] lr: 1.0000e-02 eta: 9:51:58 time: 0.5840 data_time: 0.0400 memory: 33630 grad_norm: 4.0893 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5373 loss: 1.5373 2022/10/15 00:39:31 - mmengine - INFO - Epoch(train) [36][860/940] lr: 1.0000e-02 eta: 9:51:46 time: 0.5847 data_time: 0.0301 memory: 33630 grad_norm: 4.1128 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5579 loss: 1.5579 2022/10/15 00:39:43 - mmengine - INFO - Epoch(train) [36][880/940] lr: 1.0000e-02 eta: 9:51:34 time: 0.5950 data_time: 0.0377 memory: 33630 grad_norm: 4.1781 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7549 loss: 1.7549 2022/10/15 00:39:55 - mmengine - INFO - Epoch(train) [36][900/940] lr: 1.0000e-02 eta: 9:51:22 time: 0.5883 data_time: 0.0319 memory: 33630 grad_norm: 4.0858 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5945 loss: 1.5945 2022/10/15 00:40:06 - mmengine - INFO - Epoch(train) [36][920/940] lr: 1.0000e-02 eta: 9:51:10 time: 0.5796 data_time: 0.0317 memory: 33630 grad_norm: 4.0622 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6578 loss: 1.6578 2022/10/15 00:40:17 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 00:40:17 - mmengine - INFO - Epoch(train) [36][940/940] lr: 1.0000e-02 eta: 9:50:57 time: 0.5418 data_time: 0.0313 memory: 33630 grad_norm: 4.2742 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.5506 loss: 1.5506 2022/10/15 00:40:17 - mmengine - INFO - Saving checkpoint at 36 epochs 2022/10/15 00:40:32 - mmengine - INFO - Epoch(val) [36][20/78] eta: 0:00:41 time: 0.7231 data_time: 0.5519 memory: 5967 2022/10/15 00:40:42 - mmengine - INFO - Epoch(val) [36][40/78] eta: 0:00:19 time: 0.5048 data_time: 0.3347 memory: 5967 2022/10/15 00:40:56 - mmengine - INFO - Epoch(val) [36][60/78] eta: 0:00:12 time: 0.6758 data_time: 0.5058 memory: 5967 2022/10/15 00:41:06 - mmengine - INFO - Epoch(val) [36][78/78] acc/top1: 0.6479 acc/top5: 0.8568 acc/mean1: 0.6478 2022/10/15 00:41:06 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_28.pth is removed 2022/10/15 00:41:07 - mmengine - INFO - The best checkpoint with 0.6479 acc/top1 at 36 epoch is saved to best_acc/top1_epoch_36.pth. 2022/10/15 00:41:24 - mmengine - INFO - Epoch(train) [37][20/940] lr: 1.0000e-02 eta: 9:50:53 time: 0.8240 data_time: 0.2568 memory: 33630 grad_norm: 3.9757 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.5107 loss: 1.5107 2022/10/15 00:41:35 - mmengine - INFO - Epoch(train) [37][40/940] lr: 1.0000e-02 eta: 9:50:41 time: 0.5843 data_time: 0.0325 memory: 33630 grad_norm: 4.0077 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.4884 loss: 1.4884 2022/10/15 00:41:47 - mmengine - INFO - Epoch(train) [37][60/940] lr: 1.0000e-02 eta: 9:50:30 time: 0.5983 data_time: 0.0430 memory: 33630 grad_norm: 4.1223 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.5615 loss: 1.5615 2022/10/15 00:41:59 - mmengine - INFO - Epoch(train) [37][80/940] lr: 1.0000e-02 eta: 9:50:18 time: 0.5835 data_time: 0.0325 memory: 33630 grad_norm: 4.0924 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.5217 loss: 1.5217 2022/10/15 00:42:11 - mmengine - INFO - Epoch(train) [37][100/940] lr: 1.0000e-02 eta: 9:50:07 time: 0.6067 data_time: 0.0398 memory: 33630 grad_norm: 4.1252 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5762 loss: 1.5762 2022/10/15 00:42:23 - mmengine - INFO - Epoch(train) [37][120/940] lr: 1.0000e-02 eta: 9:49:55 time: 0.5908 data_time: 0.0351 memory: 33630 grad_norm: 4.0708 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5555 loss: 1.5555 2022/10/15 00:42:34 - mmengine - INFO - Epoch(train) [37][140/940] lr: 1.0000e-02 eta: 9:49:43 time: 0.5775 data_time: 0.0388 memory: 33630 grad_norm: 4.0855 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4737 loss: 1.4737 2022/10/15 00:42:46 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 00:42:46 - mmengine - INFO - Epoch(train) [37][160/940] lr: 1.0000e-02 eta: 9:49:31 time: 0.5930 data_time: 0.0325 memory: 33630 grad_norm: 4.0409 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6401 loss: 1.6401 2022/10/15 00:42:58 - mmengine - INFO - Epoch(train) [37][180/940] lr: 1.0000e-02 eta: 9:49:19 time: 0.5862 data_time: 0.0388 memory: 33630 grad_norm: 4.0863 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6074 loss: 1.6074 2022/10/15 00:43:10 - mmengine - INFO - Epoch(train) [37][200/940] lr: 1.0000e-02 eta: 9:49:07 time: 0.5835 data_time: 0.0321 memory: 33630 grad_norm: 4.0445 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.5814 loss: 1.5814 2022/10/15 00:43:21 - mmengine - INFO - Epoch(train) [37][220/940] lr: 1.0000e-02 eta: 9:48:55 time: 0.5814 data_time: 0.0371 memory: 33630 grad_norm: 4.0668 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.5287 loss: 1.5287 2022/10/15 00:43:33 - mmengine - INFO - Epoch(train) [37][240/940] lr: 1.0000e-02 eta: 9:48:43 time: 0.5899 data_time: 0.0333 memory: 33630 grad_norm: 4.1198 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5279 loss: 1.5279 2022/10/15 00:43:45 - mmengine - INFO - Epoch(train) [37][260/940] lr: 1.0000e-02 eta: 9:48:31 time: 0.5710 data_time: 0.0331 memory: 33630 grad_norm: 4.0697 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5646 loss: 1.5646 2022/10/15 00:43:56 - mmengine - INFO - Epoch(train) [37][280/940] lr: 1.0000e-02 eta: 9:48:19 time: 0.5864 data_time: 0.0425 memory: 33630 grad_norm: 4.1307 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5307 loss: 1.5307 2022/10/15 00:44:08 - mmengine - INFO - Epoch(train) [37][300/940] lr: 1.0000e-02 eta: 9:48:07 time: 0.5924 data_time: 0.0327 memory: 33630 grad_norm: 4.1311 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6597 loss: 1.6597 2022/10/15 00:44:20 - mmengine - INFO - Epoch(train) [37][320/940] lr: 1.0000e-02 eta: 9:47:55 time: 0.5787 data_time: 0.0348 memory: 33630 grad_norm: 4.1499 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5828 loss: 1.5828 2022/10/15 00:44:31 - mmengine - INFO - Epoch(train) [37][340/940] lr: 1.0000e-02 eta: 9:47:43 time: 0.5816 data_time: 0.0319 memory: 33630 grad_norm: 4.2615 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6829 loss: 1.6829 2022/10/15 00:44:43 - mmengine - INFO - Epoch(train) [37][360/940] lr: 1.0000e-02 eta: 9:47:31 time: 0.5859 data_time: 0.0371 memory: 33630 grad_norm: 4.1968 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6757 loss: 1.6757 2022/10/15 00:44:55 - mmengine - INFO - Epoch(train) [37][380/940] lr: 1.0000e-02 eta: 9:47:19 time: 0.5935 data_time: 0.0350 memory: 33630 grad_norm: 4.2051 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6537 loss: 1.6537 2022/10/15 00:45:06 - mmengine - INFO - Epoch(train) [37][400/940] lr: 1.0000e-02 eta: 9:47:07 time: 0.5785 data_time: 0.0364 memory: 33630 grad_norm: 4.1012 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5693 loss: 1.5693 2022/10/15 00:45:18 - mmengine - INFO - Epoch(train) [37][420/940] lr: 1.0000e-02 eta: 9:46:55 time: 0.5772 data_time: 0.0399 memory: 33630 grad_norm: 4.2343 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5837 loss: 1.5837 2022/10/15 00:45:30 - mmengine - INFO - Epoch(train) [37][440/940] lr: 1.0000e-02 eta: 9:46:44 time: 0.6039 data_time: 0.0371 memory: 33630 grad_norm: 4.1357 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.5838 loss: 1.5838 2022/10/15 00:45:42 - mmengine - INFO - Epoch(train) [37][460/940] lr: 1.0000e-02 eta: 9:46:32 time: 0.5766 data_time: 0.0309 memory: 33630 grad_norm: 4.1196 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7110 loss: 1.7110 2022/10/15 00:45:53 - mmengine - INFO - Epoch(train) [37][480/940] lr: 1.0000e-02 eta: 9:46:19 time: 0.5760 data_time: 0.0347 memory: 33630 grad_norm: 4.1679 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5441 loss: 1.5441 2022/10/15 00:46:05 - mmengine - INFO - Epoch(train) [37][500/940] lr: 1.0000e-02 eta: 9:46:07 time: 0.5816 data_time: 0.0385 memory: 33630 grad_norm: 4.0554 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5245 loss: 1.5245 2022/10/15 00:46:16 - mmengine - INFO - Epoch(train) [37][520/940] lr: 1.0000e-02 eta: 9:45:55 time: 0.5813 data_time: 0.0370 memory: 33630 grad_norm: 4.1467 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.5893 loss: 1.5893 2022/10/15 00:46:28 - mmengine - INFO - Epoch(train) [37][540/940] lr: 1.0000e-02 eta: 9:45:43 time: 0.5806 data_time: 0.0329 memory: 33630 grad_norm: 4.1279 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5559 loss: 1.5559 2022/10/15 00:46:40 - mmengine - INFO - Epoch(train) [37][560/940] lr: 1.0000e-02 eta: 9:45:31 time: 0.5772 data_time: 0.0319 memory: 33630 grad_norm: 4.1683 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6774 loss: 1.6774 2022/10/15 00:46:51 - mmengine - INFO - Epoch(train) [37][580/940] lr: 1.0000e-02 eta: 9:45:19 time: 0.5891 data_time: 0.0415 memory: 33630 grad_norm: 4.1404 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6077 loss: 1.6077 2022/10/15 00:47:03 - mmengine - INFO - Epoch(train) [37][600/940] lr: 1.0000e-02 eta: 9:45:07 time: 0.5860 data_time: 0.0460 memory: 33630 grad_norm: 4.1272 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.5079 loss: 1.5079 2022/10/15 00:47:15 - mmengine - INFO - Epoch(train) [37][620/940] lr: 1.0000e-02 eta: 9:44:55 time: 0.5871 data_time: 0.0385 memory: 33630 grad_norm: 4.1313 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6480 loss: 1.6480 2022/10/15 00:47:26 - mmengine - INFO - Epoch(train) [37][640/940] lr: 1.0000e-02 eta: 9:44:43 time: 0.5698 data_time: 0.0301 memory: 33630 grad_norm: 4.1717 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.5534 loss: 1.5534 2022/10/15 00:47:38 - mmengine - INFO - Epoch(train) [37][660/940] lr: 1.0000e-02 eta: 9:44:31 time: 0.5946 data_time: 0.0363 memory: 33630 grad_norm: 4.0834 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5825 loss: 1.5825 2022/10/15 00:47:50 - mmengine - INFO - Epoch(train) [37][680/940] lr: 1.0000e-02 eta: 9:44:19 time: 0.5804 data_time: 0.0326 memory: 33630 grad_norm: 4.1475 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6002 loss: 1.6002 2022/10/15 00:48:01 - mmengine - INFO - Epoch(train) [37][700/940] lr: 1.0000e-02 eta: 9:44:07 time: 0.5892 data_time: 0.0314 memory: 33630 grad_norm: 4.1841 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5919 loss: 1.5919 2022/10/15 00:48:13 - mmengine - INFO - Epoch(train) [37][720/940] lr: 1.0000e-02 eta: 9:43:55 time: 0.5761 data_time: 0.0321 memory: 33630 grad_norm: 4.2892 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6414 loss: 1.6414 2022/10/15 00:48:25 - mmengine - INFO - Epoch(train) [37][740/940] lr: 1.0000e-02 eta: 9:43:43 time: 0.5841 data_time: 0.0381 memory: 33630 grad_norm: 4.1664 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5816 loss: 1.5816 2022/10/15 00:48:36 - mmengine - INFO - Epoch(train) [37][760/940] lr: 1.0000e-02 eta: 9:43:31 time: 0.5821 data_time: 0.0388 memory: 33630 grad_norm: 4.1228 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7220 loss: 1.7220 2022/10/15 00:48:48 - mmengine - INFO - Epoch(train) [37][780/940] lr: 1.0000e-02 eta: 9:43:19 time: 0.5887 data_time: 0.0356 memory: 33630 grad_norm: 4.0881 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4911 loss: 1.4911 2022/10/15 00:49:00 - mmengine - INFO - Epoch(train) [37][800/940] lr: 1.0000e-02 eta: 9:43:07 time: 0.5756 data_time: 0.0327 memory: 33630 grad_norm: 4.0806 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.5092 loss: 1.5092 2022/10/15 00:49:11 - mmengine - INFO - Epoch(train) [37][820/940] lr: 1.0000e-02 eta: 9:42:55 time: 0.5822 data_time: 0.0362 memory: 33630 grad_norm: 4.1630 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4327 loss: 1.4327 2022/10/15 00:49:23 - mmengine - INFO - Epoch(train) [37][840/940] lr: 1.0000e-02 eta: 9:42:43 time: 0.5835 data_time: 0.0381 memory: 33630 grad_norm: 4.1600 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.6429 loss: 1.6429 2022/10/15 00:49:35 - mmengine - INFO - Epoch(train) [37][860/940] lr: 1.0000e-02 eta: 9:42:31 time: 0.5924 data_time: 0.0356 memory: 33630 grad_norm: 4.2231 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.7494 loss: 1.7494 2022/10/15 00:49:46 - mmengine - INFO - Epoch(train) [37][880/940] lr: 1.0000e-02 eta: 9:42:19 time: 0.5849 data_time: 0.0336 memory: 33630 grad_norm: 4.1281 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 1.4845 loss: 1.4845 2022/10/15 00:49:58 - mmengine - INFO - Epoch(train) [37][900/940] lr: 1.0000e-02 eta: 9:42:07 time: 0.5850 data_time: 0.0303 memory: 33630 grad_norm: 4.1441 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.5413 loss: 1.5413 2022/10/15 00:50:10 - mmengine - INFO - Epoch(train) [37][920/940] lr: 1.0000e-02 eta: 9:41:55 time: 0.5812 data_time: 0.0332 memory: 33630 grad_norm: 4.1642 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5339 loss: 1.5339 2022/10/15 00:50:21 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 00:50:21 - mmengine - INFO - Epoch(train) [37][940/940] lr: 1.0000e-02 eta: 9:41:42 time: 0.5496 data_time: 0.0289 memory: 33630 grad_norm: 4.4484 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.6463 loss: 1.6463 2022/10/15 00:50:35 - mmengine - INFO - Epoch(val) [37][20/78] eta: 0:00:40 time: 0.7068 data_time: 0.5359 memory: 5967 2022/10/15 00:50:46 - mmengine - INFO - Epoch(val) [37][40/78] eta: 0:00:20 time: 0.5305 data_time: 0.3633 memory: 5967 2022/10/15 00:50:58 - mmengine - INFO - Epoch(val) [37][60/78] eta: 0:00:10 time: 0.6050 data_time: 0.4347 memory: 5967 2022/10/15 00:51:10 - mmengine - INFO - Epoch(val) [37][78/78] acc/top1: 0.6444 acc/top5: 0.8530 acc/mean1: 0.6441 2022/10/15 00:51:27 - mmengine - INFO - Epoch(train) [38][20/940] lr: 1.0000e-02 eta: 9:41:39 time: 0.8302 data_time: 0.2442 memory: 33630 grad_norm: 4.0670 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6417 loss: 1.6417 2022/10/15 00:51:38 - mmengine - INFO - Epoch(train) [38][40/940] lr: 1.0000e-02 eta: 9:41:26 time: 0.5741 data_time: 0.0315 memory: 33630 grad_norm: 4.0588 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6508 loss: 1.6508 2022/10/15 00:51:50 - mmengine - INFO - Epoch(train) [38][60/940] lr: 1.0000e-02 eta: 9:41:14 time: 0.5854 data_time: 0.0393 memory: 33630 grad_norm: 4.0640 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.5734 loss: 1.5734 2022/10/15 00:52:02 - mmengine - INFO - Epoch(train) [38][80/940] lr: 1.0000e-02 eta: 9:41:03 time: 0.5963 data_time: 0.0361 memory: 33630 grad_norm: 4.0059 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4215 loss: 1.4215 2022/10/15 00:52:14 - mmengine - INFO - Epoch(train) [38][100/940] lr: 1.0000e-02 eta: 9:40:51 time: 0.5852 data_time: 0.0362 memory: 33630 grad_norm: 4.1169 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.6381 loss: 1.6381 2022/10/15 00:52:26 - mmengine - INFO - Epoch(train) [38][120/940] lr: 1.0000e-02 eta: 9:40:39 time: 0.5940 data_time: 0.0401 memory: 33630 grad_norm: 4.1278 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.5928 loss: 1.5928 2022/10/15 00:52:37 - mmengine - INFO - Epoch(train) [38][140/940] lr: 1.0000e-02 eta: 9:40:27 time: 0.5833 data_time: 0.0411 memory: 33630 grad_norm: 4.0972 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.4758 loss: 1.4758 2022/10/15 00:52:49 - mmengine - INFO - Epoch(train) [38][160/940] lr: 1.0000e-02 eta: 9:40:15 time: 0.5787 data_time: 0.0356 memory: 33630 grad_norm: 4.0594 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5790 loss: 1.5790 2022/10/15 00:53:01 - mmengine - INFO - Epoch(train) [38][180/940] lr: 1.0000e-02 eta: 9:40:03 time: 0.5845 data_time: 0.0431 memory: 33630 grad_norm: 4.0914 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.5985 loss: 1.5985 2022/10/15 00:53:12 - mmengine - INFO - Epoch(train) [38][200/940] lr: 1.0000e-02 eta: 9:39:51 time: 0.5849 data_time: 0.0329 memory: 33630 grad_norm: 4.0174 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.6313 loss: 1.6313 2022/10/15 00:53:24 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 00:53:24 - mmengine - INFO - Epoch(train) [38][220/940] lr: 1.0000e-02 eta: 9:39:39 time: 0.5861 data_time: 0.0427 memory: 33630 grad_norm: 4.1313 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4546 loss: 1.4546 2022/10/15 00:53:35 - mmengine - INFO - Epoch(train) [38][240/940] lr: 1.0000e-02 eta: 9:39:27 time: 0.5679 data_time: 0.0362 memory: 33630 grad_norm: 4.1144 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6119 loss: 1.6119 2022/10/15 00:53:47 - mmengine - INFO - Epoch(train) [38][260/940] lr: 1.0000e-02 eta: 9:39:14 time: 0.5753 data_time: 0.0349 memory: 33630 grad_norm: 4.1340 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.5979 loss: 1.5979 2022/10/15 00:53:59 - mmengine - INFO - Epoch(train) [38][280/940] lr: 1.0000e-02 eta: 9:39:03 time: 0.5898 data_time: 0.0382 memory: 33630 grad_norm: 4.2109 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5307 loss: 1.5307 2022/10/15 00:54:10 - mmengine - INFO - Epoch(train) [38][300/940] lr: 1.0000e-02 eta: 9:38:51 time: 0.5867 data_time: 0.0342 memory: 33630 grad_norm: 4.1091 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.5809 loss: 1.5809 2022/10/15 00:54:22 - mmengine - INFO - Epoch(train) [38][320/940] lr: 1.0000e-02 eta: 9:38:39 time: 0.5831 data_time: 0.0381 memory: 33630 grad_norm: 4.0935 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5620 loss: 1.5620 2022/10/15 00:54:34 - mmengine - INFO - Epoch(train) [38][340/940] lr: 1.0000e-02 eta: 9:38:27 time: 0.5897 data_time: 0.0344 memory: 33630 grad_norm: 4.0972 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5047 loss: 1.5047 2022/10/15 00:54:46 - mmengine - INFO - Epoch(train) [38][360/940] lr: 1.0000e-02 eta: 9:38:15 time: 0.5971 data_time: 0.0313 memory: 33630 grad_norm: 4.1005 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.5849 loss: 1.5849 2022/10/15 00:54:58 - mmengine - INFO - Epoch(train) [38][380/940] lr: 1.0000e-02 eta: 9:38:04 time: 0.5984 data_time: 0.0367 memory: 33630 grad_norm: 4.1505 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6557 loss: 1.6557 2022/10/15 00:55:09 - mmengine - INFO - Epoch(train) [38][400/940] lr: 1.0000e-02 eta: 9:37:52 time: 0.5780 data_time: 0.0375 memory: 33630 grad_norm: 4.2306 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.6776 loss: 1.6776 2022/10/15 00:55:21 - mmengine - INFO - Epoch(train) [38][420/940] lr: 1.0000e-02 eta: 9:37:40 time: 0.5771 data_time: 0.0318 memory: 33630 grad_norm: 4.1510 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6666 loss: 1.6666 2022/10/15 00:55:33 - mmengine - INFO - Epoch(train) [38][440/940] lr: 1.0000e-02 eta: 9:37:28 time: 0.5924 data_time: 0.0314 memory: 33630 grad_norm: 4.1513 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6013 loss: 1.6013 2022/10/15 00:55:44 - mmengine - INFO - Epoch(train) [38][460/940] lr: 1.0000e-02 eta: 9:37:16 time: 0.5889 data_time: 0.0372 memory: 33630 grad_norm: 4.1527 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.5604 loss: 1.5604 2022/10/15 00:55:56 - mmengine - INFO - Epoch(train) [38][480/940] lr: 1.0000e-02 eta: 9:37:04 time: 0.5935 data_time: 0.0369 memory: 33630 grad_norm: 4.1443 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6373 loss: 1.6373 2022/10/15 00:56:08 - mmengine - INFO - Epoch(train) [38][500/940] lr: 1.0000e-02 eta: 9:36:53 time: 0.5936 data_time: 0.0362 memory: 33630 grad_norm: 4.2662 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5436 loss: 1.5436 2022/10/15 00:56:20 - mmengine - INFO - Epoch(train) [38][520/940] lr: 1.0000e-02 eta: 9:36:41 time: 0.5835 data_time: 0.0463 memory: 33630 grad_norm: 4.1640 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.4492 loss: 1.4492 2022/10/15 00:56:32 - mmengine - INFO - Epoch(train) [38][540/940] lr: 1.0000e-02 eta: 9:36:29 time: 0.5971 data_time: 0.0387 memory: 33630 grad_norm: 4.0566 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5075 loss: 1.5075 2022/10/15 00:56:43 - mmengine - INFO - Epoch(train) [38][560/940] lr: 1.0000e-02 eta: 9:36:17 time: 0.5827 data_time: 0.0329 memory: 33630 grad_norm: 4.0976 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5591 loss: 1.5591 2022/10/15 00:56:55 - mmengine - INFO - Epoch(train) [38][580/940] lr: 1.0000e-02 eta: 9:36:05 time: 0.5750 data_time: 0.0312 memory: 33630 grad_norm: 4.0600 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.4965 loss: 1.4965 2022/10/15 00:57:07 - mmengine - INFO - Epoch(train) [38][600/940] lr: 1.0000e-02 eta: 9:35:53 time: 0.5804 data_time: 0.0384 memory: 33630 grad_norm: 4.1147 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6342 loss: 1.6342 2022/10/15 00:57:18 - mmengine - INFO - Epoch(train) [38][620/940] lr: 1.0000e-02 eta: 9:35:41 time: 0.5929 data_time: 0.0409 memory: 33630 grad_norm: 4.1286 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5483 loss: 1.5483 2022/10/15 00:57:30 - mmengine - INFO - Epoch(train) [38][640/940] lr: 1.0000e-02 eta: 9:35:29 time: 0.5836 data_time: 0.0323 memory: 33630 grad_norm: 4.0170 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5675 loss: 1.5675 2022/10/15 00:57:42 - mmengine - INFO - Epoch(train) [38][660/940] lr: 1.0000e-02 eta: 9:35:17 time: 0.5838 data_time: 0.0400 memory: 33630 grad_norm: 4.1548 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.6440 loss: 1.6440 2022/10/15 00:57:54 - mmengine - INFO - Epoch(train) [38][680/940] lr: 1.0000e-02 eta: 9:35:06 time: 0.6009 data_time: 0.0327 memory: 33630 grad_norm: 4.0943 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6152 loss: 1.6152 2022/10/15 00:58:06 - mmengine - INFO - Epoch(train) [38][700/940] lr: 1.0000e-02 eta: 9:34:54 time: 0.5871 data_time: 0.0417 memory: 33630 grad_norm: 4.1374 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5081 loss: 1.5081 2022/10/15 00:58:17 - mmengine - INFO - Epoch(train) [38][720/940] lr: 1.0000e-02 eta: 9:34:42 time: 0.5909 data_time: 0.0311 memory: 33630 grad_norm: 4.2096 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5593 loss: 1.5593 2022/10/15 00:58:29 - mmengine - INFO - Epoch(train) [38][740/940] lr: 1.0000e-02 eta: 9:34:30 time: 0.5873 data_time: 0.0325 memory: 33630 grad_norm: 4.1446 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.5953 loss: 1.5953 2022/10/15 00:58:41 - mmengine - INFO - Epoch(train) [38][760/940] lr: 1.0000e-02 eta: 9:34:18 time: 0.5820 data_time: 0.0422 memory: 33630 grad_norm: 4.2179 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6083 loss: 1.6083 2022/10/15 00:58:52 - mmengine - INFO - Epoch(train) [38][780/940] lr: 1.0000e-02 eta: 9:34:06 time: 0.5815 data_time: 0.0444 memory: 33630 grad_norm: 4.1443 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6745 loss: 1.6745 2022/10/15 00:59:04 - mmengine - INFO - Epoch(train) [38][800/940] lr: 1.0000e-02 eta: 9:33:55 time: 0.5936 data_time: 0.0344 memory: 33630 grad_norm: 4.2631 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5341 loss: 1.5341 2022/10/15 00:59:16 - mmengine - INFO - Epoch(train) [38][820/940] lr: 1.0000e-02 eta: 9:33:43 time: 0.5837 data_time: 0.0335 memory: 33630 grad_norm: 4.2184 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.5233 loss: 1.5233 2022/10/15 00:59:28 - mmengine - INFO - Epoch(train) [38][840/940] lr: 1.0000e-02 eta: 9:33:31 time: 0.5860 data_time: 0.0379 memory: 33630 grad_norm: 4.2344 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6729 loss: 1.6729 2022/10/15 00:59:39 - mmengine - INFO - Epoch(train) [38][860/940] lr: 1.0000e-02 eta: 9:33:19 time: 0.5778 data_time: 0.0341 memory: 33630 grad_norm: 4.1142 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6328 loss: 1.6328 2022/10/15 00:59:51 - mmengine - INFO - Epoch(train) [38][880/940] lr: 1.0000e-02 eta: 9:33:06 time: 0.5783 data_time: 0.0320 memory: 33630 grad_norm: 4.1593 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5752 loss: 1.5752 2022/10/15 01:00:03 - mmengine - INFO - Epoch(train) [38][900/940] lr: 1.0000e-02 eta: 9:32:55 time: 0.5888 data_time: 0.0330 memory: 33630 grad_norm: 4.1592 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5616 loss: 1.5616 2022/10/15 01:00:14 - mmengine - INFO - Epoch(train) [38][920/940] lr: 1.0000e-02 eta: 9:32:43 time: 0.5818 data_time: 0.0365 memory: 33630 grad_norm: 4.0893 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5326 loss: 1.5326 2022/10/15 01:00:25 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 01:00:25 - mmengine - INFO - Epoch(train) [38][940/940] lr: 1.0000e-02 eta: 9:32:29 time: 0.5404 data_time: 0.0332 memory: 33630 grad_norm: 4.3885 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.6123 loss: 1.6123 2022/10/15 01:00:39 - mmengine - INFO - Epoch(val) [38][20/78] eta: 0:00:40 time: 0.7005 data_time: 0.5315 memory: 5967 2022/10/15 01:00:49 - mmengine - INFO - Epoch(val) [38][40/78] eta: 0:00:19 time: 0.5139 data_time: 0.3453 memory: 5967 2022/10/15 01:01:03 - mmengine - INFO - Epoch(val) [38][60/78] eta: 0:00:12 time: 0.6765 data_time: 0.5073 memory: 5967 2022/10/15 01:01:15 - mmengine - INFO - Epoch(val) [38][78/78] acc/top1: 0.6383 acc/top5: 0.8477 acc/mean1: 0.6380 2022/10/15 01:01:31 - mmengine - INFO - Epoch(train) [39][20/940] lr: 1.0000e-02 eta: 9:32:25 time: 0.8289 data_time: 0.2626 memory: 33630 grad_norm: 4.1199 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5279 loss: 1.5279 2022/10/15 01:01:43 - mmengine - INFO - Epoch(train) [39][40/940] lr: 1.0000e-02 eta: 9:32:13 time: 0.5795 data_time: 0.0334 memory: 33630 grad_norm: 4.1794 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4427 loss: 1.4427 2022/10/15 01:01:55 - mmengine - INFO - Epoch(train) [39][60/940] lr: 1.0000e-02 eta: 9:32:01 time: 0.5914 data_time: 0.0355 memory: 33630 grad_norm: 4.0537 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5279 loss: 1.5279 2022/10/15 01:02:07 - mmengine - INFO - Epoch(train) [39][80/940] lr: 1.0000e-02 eta: 9:31:50 time: 0.5918 data_time: 0.0342 memory: 33630 grad_norm: 4.1108 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.5227 loss: 1.5227 2022/10/15 01:02:18 - mmengine - INFO - Epoch(train) [39][100/940] lr: 1.0000e-02 eta: 9:31:38 time: 0.5803 data_time: 0.0349 memory: 33630 grad_norm: 4.0891 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4816 loss: 1.4816 2022/10/15 01:02:30 - mmengine - INFO - Epoch(train) [39][120/940] lr: 1.0000e-02 eta: 9:31:26 time: 0.5824 data_time: 0.0334 memory: 33630 grad_norm: 4.0530 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5444 loss: 1.5444 2022/10/15 01:02:42 - mmengine - INFO - Epoch(train) [39][140/940] lr: 1.0000e-02 eta: 9:31:14 time: 0.5924 data_time: 0.0407 memory: 33630 grad_norm: 4.0896 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4789 loss: 1.4789 2022/10/15 01:02:53 - mmengine - INFO - Epoch(train) [39][160/940] lr: 1.0000e-02 eta: 9:31:01 time: 0.5703 data_time: 0.0319 memory: 33630 grad_norm: 4.1389 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.6776 loss: 1.6776 2022/10/15 01:03:05 - mmengine - INFO - Epoch(train) [39][180/940] lr: 1.0000e-02 eta: 9:30:50 time: 0.5993 data_time: 0.0377 memory: 33630 grad_norm: 4.1469 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6335 loss: 1.6335 2022/10/15 01:03:17 - mmengine - INFO - Epoch(train) [39][200/940] lr: 1.0000e-02 eta: 9:30:38 time: 0.5815 data_time: 0.0457 memory: 33630 grad_norm: 4.1474 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.5956 loss: 1.5956 2022/10/15 01:03:29 - mmengine - INFO - Epoch(train) [39][220/940] lr: 1.0000e-02 eta: 9:30:26 time: 0.5915 data_time: 0.0415 memory: 33630 grad_norm: 4.1042 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6195 loss: 1.6195 2022/10/15 01:03:40 - mmengine - INFO - Epoch(train) [39][240/940] lr: 1.0000e-02 eta: 9:30:14 time: 0.5787 data_time: 0.0419 memory: 33630 grad_norm: 4.1631 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4840 loss: 1.4840 2022/10/15 01:03:52 - mmengine - INFO - Epoch(train) [39][260/940] lr: 1.0000e-02 eta: 9:30:02 time: 0.5736 data_time: 0.0313 memory: 33630 grad_norm: 4.1717 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5223 loss: 1.5223 2022/10/15 01:04:03 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 01:04:03 - mmengine - INFO - Epoch(train) [39][280/940] lr: 1.0000e-02 eta: 9:29:50 time: 0.5800 data_time: 0.0352 memory: 33630 grad_norm: 4.0627 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5326 loss: 1.5326 2022/10/15 01:04:15 - mmengine - INFO - Epoch(train) [39][300/940] lr: 1.0000e-02 eta: 9:29:38 time: 0.5864 data_time: 0.0344 memory: 33630 grad_norm: 4.1643 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6098 loss: 1.6098 2022/10/15 01:04:27 - mmengine - INFO - Epoch(train) [39][320/940] lr: 1.0000e-02 eta: 9:29:26 time: 0.5800 data_time: 0.0340 memory: 33630 grad_norm: 4.1921 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5531 loss: 1.5531 2022/10/15 01:04:38 - mmengine - INFO - Epoch(train) [39][340/940] lr: 1.0000e-02 eta: 9:29:13 time: 0.5731 data_time: 0.0328 memory: 33630 grad_norm: 4.1606 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4392 loss: 1.4392 2022/10/15 01:04:50 - mmengine - INFO - Epoch(train) [39][360/940] lr: 1.0000e-02 eta: 9:29:01 time: 0.5786 data_time: 0.0436 memory: 33630 grad_norm: 4.1252 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5296 loss: 1.5296 2022/10/15 01:05:01 - mmengine - INFO - Epoch(train) [39][380/940] lr: 1.0000e-02 eta: 9:28:49 time: 0.5897 data_time: 0.0363 memory: 33630 grad_norm: 4.1842 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.5022 loss: 1.5022 2022/10/15 01:05:13 - mmengine - INFO - Epoch(train) [39][400/940] lr: 1.0000e-02 eta: 9:28:37 time: 0.5820 data_time: 0.0313 memory: 33630 grad_norm: 4.1288 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5522 loss: 1.5522 2022/10/15 01:05:25 - mmengine - INFO - Epoch(train) [39][420/940] lr: 1.0000e-02 eta: 9:28:25 time: 0.5807 data_time: 0.0322 memory: 33630 grad_norm: 4.2087 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.4997 loss: 1.4997 2022/10/15 01:05:36 - mmengine - INFO - Epoch(train) [39][440/940] lr: 1.0000e-02 eta: 9:28:13 time: 0.5781 data_time: 0.0319 memory: 33630 grad_norm: 4.1990 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5426 loss: 1.5426 2022/10/15 01:05:48 - mmengine - INFO - Epoch(train) [39][460/940] lr: 1.0000e-02 eta: 9:28:02 time: 0.5944 data_time: 0.0348 memory: 33630 grad_norm: 4.0909 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.6042 loss: 1.6042 2022/10/15 01:06:00 - mmengine - INFO - Epoch(train) [39][480/940] lr: 1.0000e-02 eta: 9:27:49 time: 0.5793 data_time: 0.0310 memory: 33630 grad_norm: 4.1290 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5905 loss: 1.5905 2022/10/15 01:06:11 - mmengine - INFO - Epoch(train) [39][500/940] lr: 1.0000e-02 eta: 9:27:37 time: 0.5768 data_time: 0.0381 memory: 33630 grad_norm: 4.2222 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5826 loss: 1.5826 2022/10/15 01:06:23 - mmengine - INFO - Epoch(train) [39][520/940] lr: 1.0000e-02 eta: 9:27:25 time: 0.5837 data_time: 0.0367 memory: 33630 grad_norm: 4.1604 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5789 loss: 1.5789 2022/10/15 01:06:35 - mmengine - INFO - Epoch(train) [39][540/940] lr: 1.0000e-02 eta: 9:27:14 time: 0.5952 data_time: 0.0352 memory: 33630 grad_norm: 4.0995 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.6076 loss: 1.6076 2022/10/15 01:06:46 - mmengine - INFO - Epoch(train) [39][560/940] lr: 1.0000e-02 eta: 9:27:02 time: 0.5834 data_time: 0.0524 memory: 33630 grad_norm: 4.1136 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6664 loss: 1.6664 2022/10/15 01:06:58 - mmengine - INFO - Epoch(train) [39][580/940] lr: 1.0000e-02 eta: 9:26:50 time: 0.5858 data_time: 0.0344 memory: 33630 grad_norm: 4.1970 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6700 loss: 1.6700 2022/10/15 01:07:10 - mmengine - INFO - Epoch(train) [39][600/940] lr: 1.0000e-02 eta: 9:26:38 time: 0.5885 data_time: 0.0347 memory: 33630 grad_norm: 4.2211 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5835 loss: 1.5835 2022/10/15 01:07:22 - mmengine - INFO - Epoch(train) [39][620/940] lr: 1.0000e-02 eta: 9:26:26 time: 0.5817 data_time: 0.0408 memory: 33630 grad_norm: 4.1588 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6251 loss: 1.6251 2022/10/15 01:07:33 - mmengine - INFO - Epoch(train) [39][640/940] lr: 1.0000e-02 eta: 9:26:13 time: 0.5678 data_time: 0.0402 memory: 33630 grad_norm: 4.1454 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5463 loss: 1.5463 2022/10/15 01:07:44 - mmengine - INFO - Epoch(train) [39][660/940] lr: 1.0000e-02 eta: 9:26:01 time: 0.5756 data_time: 0.0376 memory: 33630 grad_norm: 4.1930 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5227 loss: 1.5227 2022/10/15 01:07:56 - mmengine - INFO - Epoch(train) [39][680/940] lr: 1.0000e-02 eta: 9:25:49 time: 0.5870 data_time: 0.0399 memory: 33630 grad_norm: 4.1097 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5965 loss: 1.5965 2022/10/15 01:08:08 - mmengine - INFO - Epoch(train) [39][700/940] lr: 1.0000e-02 eta: 9:25:37 time: 0.5806 data_time: 0.0304 memory: 33630 grad_norm: 4.1299 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5895 loss: 1.5895 2022/10/15 01:08:19 - mmengine - INFO - Epoch(train) [39][720/940] lr: 1.0000e-02 eta: 9:25:25 time: 0.5796 data_time: 0.0376 memory: 33630 grad_norm: 4.1054 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6094 loss: 1.6094 2022/10/15 01:08:31 - mmengine - INFO - Epoch(train) [39][740/940] lr: 1.0000e-02 eta: 9:25:13 time: 0.5773 data_time: 0.0360 memory: 33630 grad_norm: 4.1486 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6163 loss: 1.6163 2022/10/15 01:08:43 - mmengine - INFO - Epoch(train) [39][760/940] lr: 1.0000e-02 eta: 9:25:01 time: 0.5822 data_time: 0.0389 memory: 33630 grad_norm: 4.1706 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6237 loss: 1.6237 2022/10/15 01:08:55 - mmengine - INFO - Epoch(train) [39][780/940] lr: 1.0000e-02 eta: 9:24:50 time: 0.5984 data_time: 0.0366 memory: 33630 grad_norm: 4.1223 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5024 loss: 1.5024 2022/10/15 01:09:07 - mmengine - INFO - Epoch(train) [39][800/940] lr: 1.0000e-02 eta: 9:24:38 time: 0.5963 data_time: 0.0355 memory: 33630 grad_norm: 4.1244 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6102 loss: 1.6102 2022/10/15 01:09:18 - mmengine - INFO - Epoch(train) [39][820/940] lr: 1.0000e-02 eta: 9:24:26 time: 0.5883 data_time: 0.0336 memory: 33630 grad_norm: 4.1607 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6647 loss: 1.6647 2022/10/15 01:09:30 - mmengine - INFO - Epoch(train) [39][840/940] lr: 1.0000e-02 eta: 9:24:14 time: 0.5763 data_time: 0.0305 memory: 33630 grad_norm: 4.1154 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5075 loss: 1.5075 2022/10/15 01:09:41 - mmengine - INFO - Epoch(train) [39][860/940] lr: 1.0000e-02 eta: 9:24:02 time: 0.5812 data_time: 0.0318 memory: 33630 grad_norm: 4.1885 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4770 loss: 1.4770 2022/10/15 01:09:53 - mmengine - INFO - Epoch(train) [39][880/940] lr: 1.0000e-02 eta: 9:23:50 time: 0.5895 data_time: 0.0363 memory: 33630 grad_norm: 4.1855 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5728 loss: 1.5728 2022/10/15 01:10:05 - mmengine - INFO - Epoch(train) [39][900/940] lr: 1.0000e-02 eta: 9:23:38 time: 0.5881 data_time: 0.0346 memory: 33630 grad_norm: 4.1699 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.5674 loss: 1.5674 2022/10/15 01:10:16 - mmengine - INFO - Epoch(train) [39][920/940] lr: 1.0000e-02 eta: 9:23:26 time: 0.5687 data_time: 0.0405 memory: 33630 grad_norm: 4.1831 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6510 loss: 1.6510 2022/10/15 01:10:27 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 01:10:27 - mmengine - INFO - Epoch(train) [39][940/940] lr: 1.0000e-02 eta: 9:23:12 time: 0.5367 data_time: 0.0294 memory: 33630 grad_norm: 4.5151 top1_acc: 0.4286 top5_acc: 0.5714 loss_cls: 1.7755 loss: 1.7755 2022/10/15 01:10:27 - mmengine - INFO - Saving checkpoint at 39 epochs 2022/10/15 01:10:43 - mmengine - INFO - Epoch(val) [39][20/78] eta: 0:00:43 time: 0.7516 data_time: 0.5818 memory: 5967 2022/10/15 01:10:53 - mmengine - INFO - Epoch(val) [39][40/78] eta: 0:00:18 time: 0.4765 data_time: 0.3087 memory: 5967 2022/10/15 01:11:06 - mmengine - INFO - Epoch(val) [39][60/78] eta: 0:00:12 time: 0.6908 data_time: 0.5201 memory: 5967 2022/10/15 01:11:17 - mmengine - INFO - Epoch(val) [39][78/78] acc/top1: 0.6432 acc/top5: 0.8538 acc/mean1: 0.6431 2022/10/15 01:11:35 - mmengine - INFO - Epoch(train) [40][20/940] lr: 1.0000e-02 eta: 9:23:11 time: 0.9125 data_time: 0.2533 memory: 33630 grad_norm: 4.1049 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3596 loss: 1.3596 2022/10/15 01:11:47 - mmengine - INFO - Epoch(train) [40][40/940] lr: 1.0000e-02 eta: 9:22:59 time: 0.5865 data_time: 0.0367 memory: 33630 grad_norm: 4.1999 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5257 loss: 1.5257 2022/10/15 01:11:59 - mmengine - INFO - Epoch(train) [40][60/940] lr: 1.0000e-02 eta: 9:22:47 time: 0.5899 data_time: 0.0355 memory: 33630 grad_norm: 4.1344 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4101 loss: 1.4101 2022/10/15 01:12:11 - mmengine - INFO - Epoch(train) [40][80/940] lr: 1.0000e-02 eta: 9:22:35 time: 0.5912 data_time: 0.0346 memory: 33630 grad_norm: 4.1207 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5200 loss: 1.5200 2022/10/15 01:12:22 - mmengine - INFO - Epoch(train) [40][100/940] lr: 1.0000e-02 eta: 9:22:24 time: 0.5903 data_time: 0.0384 memory: 33630 grad_norm: 4.1107 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4958 loss: 1.4958 2022/10/15 01:12:34 - mmengine - INFO - Epoch(train) [40][120/940] lr: 1.0000e-02 eta: 9:22:12 time: 0.5847 data_time: 0.0350 memory: 33630 grad_norm: 4.1455 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5189 loss: 1.5189 2022/10/15 01:12:46 - mmengine - INFO - Epoch(train) [40][140/940] lr: 1.0000e-02 eta: 9:22:00 time: 0.5910 data_time: 0.0410 memory: 33630 grad_norm: 4.0757 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.4951 loss: 1.4951 2022/10/15 01:12:58 - mmengine - INFO - Epoch(train) [40][160/940] lr: 1.0000e-02 eta: 9:21:48 time: 0.5932 data_time: 0.0384 memory: 33630 grad_norm: 4.1307 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4340 loss: 1.4340 2022/10/15 01:13:09 - mmengine - INFO - Epoch(train) [40][180/940] lr: 1.0000e-02 eta: 9:21:36 time: 0.5821 data_time: 0.0455 memory: 33630 grad_norm: 4.0467 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5228 loss: 1.5228 2022/10/15 01:13:21 - mmengine - INFO - Epoch(train) [40][200/940] lr: 1.0000e-02 eta: 9:21:24 time: 0.5827 data_time: 0.0363 memory: 33630 grad_norm: 4.1555 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6212 loss: 1.6212 2022/10/15 01:13:33 - mmengine - INFO - Epoch(train) [40][220/940] lr: 1.0000e-02 eta: 9:21:12 time: 0.5858 data_time: 0.0323 memory: 33630 grad_norm: 4.1529 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4734 loss: 1.4734 2022/10/15 01:13:45 - mmengine - INFO - Epoch(train) [40][240/940] lr: 1.0000e-02 eta: 9:21:00 time: 0.5878 data_time: 0.0345 memory: 33630 grad_norm: 4.1350 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6112 loss: 1.6112 2022/10/15 01:13:56 - mmengine - INFO - Epoch(train) [40][260/940] lr: 1.0000e-02 eta: 9:20:48 time: 0.5749 data_time: 0.0357 memory: 33630 grad_norm: 4.1394 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6150 loss: 1.6150 2022/10/15 01:14:08 - mmengine - INFO - Epoch(train) [40][280/940] lr: 1.0000e-02 eta: 9:20:36 time: 0.5853 data_time: 0.0302 memory: 33630 grad_norm: 4.1643 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6460 loss: 1.6460 2022/10/15 01:14:19 - mmengine - INFO - Epoch(train) [40][300/940] lr: 1.0000e-02 eta: 9:20:24 time: 0.5732 data_time: 0.0317 memory: 33630 grad_norm: 4.1957 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5043 loss: 1.5043 2022/10/15 01:14:31 - mmengine - INFO - Epoch(train) [40][320/940] lr: 1.0000e-02 eta: 9:20:12 time: 0.5921 data_time: 0.0370 memory: 33630 grad_norm: 4.2558 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.6544 loss: 1.6544 2022/10/15 01:14:43 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 01:14:43 - mmengine - INFO - Epoch(train) [40][340/940] lr: 1.0000e-02 eta: 9:20:00 time: 0.5827 data_time: 0.0361 memory: 33630 grad_norm: 4.0676 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.5326 loss: 1.5326 2022/10/15 01:14:55 - mmengine - INFO - Epoch(train) [40][360/940] lr: 1.0000e-02 eta: 9:19:49 time: 0.5895 data_time: 0.0426 memory: 33630 grad_norm: 4.1598 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4687 loss: 1.4687 2022/10/15 01:15:06 - mmengine - INFO - Epoch(train) [40][380/940] lr: 1.0000e-02 eta: 9:19:37 time: 0.5953 data_time: 0.0323 memory: 33630 grad_norm: 4.0884 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6075 loss: 1.6075 2022/10/15 01:15:18 - mmengine - INFO - Epoch(train) [40][400/940] lr: 1.0000e-02 eta: 9:19:25 time: 0.5880 data_time: 0.0428 memory: 33630 grad_norm: 4.2353 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.5904 loss: 1.5904 2022/10/15 01:15:30 - mmengine - INFO - Epoch(train) [40][420/940] lr: 1.0000e-02 eta: 9:19:13 time: 0.5932 data_time: 0.0327 memory: 33630 grad_norm: 4.2292 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.5977 loss: 1.5977 2022/10/15 01:15:42 - mmengine - INFO - Epoch(train) [40][440/940] lr: 1.0000e-02 eta: 9:19:01 time: 0.5810 data_time: 0.0328 memory: 33630 grad_norm: 4.1481 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.6835 loss: 1.6835 2022/10/15 01:15:53 - mmengine - INFO - Epoch(train) [40][460/940] lr: 1.0000e-02 eta: 9:18:49 time: 0.5856 data_time: 0.0356 memory: 33630 grad_norm: 4.2190 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.6811 loss: 1.6811 2022/10/15 01:16:05 - mmengine - INFO - Epoch(train) [40][480/940] lr: 1.0000e-02 eta: 9:18:37 time: 0.5737 data_time: 0.0346 memory: 33630 grad_norm: 4.0968 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4683 loss: 1.4683 2022/10/15 01:16:16 - mmengine - INFO - Epoch(train) [40][500/940] lr: 1.0000e-02 eta: 9:18:25 time: 0.5772 data_time: 0.0363 memory: 33630 grad_norm: 4.1419 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6383 loss: 1.6383 2022/10/15 01:16:28 - mmengine - INFO - Epoch(train) [40][520/940] lr: 1.0000e-02 eta: 9:18:13 time: 0.5821 data_time: 0.0321 memory: 33630 grad_norm: 4.1304 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5129 loss: 1.5129 2022/10/15 01:16:40 - mmengine - INFO - Epoch(train) [40][540/940] lr: 1.0000e-02 eta: 9:18:01 time: 0.5796 data_time: 0.0360 memory: 33630 grad_norm: 4.2255 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6273 loss: 1.6273 2022/10/15 01:16:51 - mmengine - INFO - Epoch(train) [40][560/940] lr: 1.0000e-02 eta: 9:17:49 time: 0.5798 data_time: 0.0331 memory: 33630 grad_norm: 4.2067 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.4483 loss: 1.4483 2022/10/15 01:17:03 - mmengine - INFO - Epoch(train) [40][580/940] lr: 1.0000e-02 eta: 9:17:37 time: 0.5963 data_time: 0.0445 memory: 33630 grad_norm: 4.1894 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6172 loss: 1.6172 2022/10/15 01:17:15 - mmengine - INFO - Epoch(train) [40][600/940] lr: 1.0000e-02 eta: 9:17:25 time: 0.5886 data_time: 0.0455 memory: 33630 grad_norm: 4.1835 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.5301 loss: 1.5301 2022/10/15 01:17:27 - mmengine - INFO - Epoch(train) [40][620/940] lr: 1.0000e-02 eta: 9:17:13 time: 0.5801 data_time: 0.0346 memory: 33630 grad_norm: 4.1460 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.5352 loss: 1.5352 2022/10/15 01:17:38 - mmengine - INFO - Epoch(train) [40][640/940] lr: 1.0000e-02 eta: 9:17:01 time: 0.5850 data_time: 0.0342 memory: 33630 grad_norm: 4.1701 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5154 loss: 1.5154 2022/10/15 01:17:50 - mmengine - INFO - Epoch(train) [40][660/940] lr: 1.0000e-02 eta: 9:16:49 time: 0.5792 data_time: 0.0303 memory: 33630 grad_norm: 4.1551 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5936 loss: 1.5936 2022/10/15 01:18:02 - mmengine - INFO - Epoch(train) [40][680/940] lr: 1.0000e-02 eta: 9:16:38 time: 0.5914 data_time: 0.0352 memory: 33630 grad_norm: 4.2153 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4570 loss: 1.4570 2022/10/15 01:18:13 - mmengine - INFO - Epoch(train) [40][700/940] lr: 1.0000e-02 eta: 9:16:26 time: 0.5915 data_time: 0.0297 memory: 33630 grad_norm: 4.1509 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6052 loss: 1.6052 2022/10/15 01:18:25 - mmengine - INFO - Epoch(train) [40][720/940] lr: 1.0000e-02 eta: 9:16:14 time: 0.5822 data_time: 0.0357 memory: 33630 grad_norm: 4.1344 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6190 loss: 1.6190 2022/10/15 01:18:37 - mmengine - INFO - Epoch(train) [40][740/940] lr: 1.0000e-02 eta: 9:16:02 time: 0.5899 data_time: 0.0321 memory: 33630 grad_norm: 4.1962 top1_acc: 0.4062 top5_acc: 0.8750 loss_cls: 1.5965 loss: 1.5965 2022/10/15 01:18:49 - mmengine - INFO - Epoch(train) [40][760/940] lr: 1.0000e-02 eta: 9:15:50 time: 0.5969 data_time: 0.0325 memory: 33630 grad_norm: 4.1524 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6350 loss: 1.6350 2022/10/15 01:19:00 - mmengine - INFO - Epoch(train) [40][780/940] lr: 1.0000e-02 eta: 9:15:38 time: 0.5732 data_time: 0.0385 memory: 33630 grad_norm: 4.0858 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5198 loss: 1.5198 2022/10/15 01:19:12 - mmengine - INFO - Epoch(train) [40][800/940] lr: 1.0000e-02 eta: 9:15:27 time: 0.6023 data_time: 0.0451 memory: 33630 grad_norm: 4.1461 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.5627 loss: 1.5627 2022/10/15 01:19:24 - mmengine - INFO - Epoch(train) [40][820/940] lr: 1.0000e-02 eta: 9:15:15 time: 0.5847 data_time: 0.0395 memory: 33630 grad_norm: 4.2542 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6448 loss: 1.6448 2022/10/15 01:19:36 - mmengine - INFO - Epoch(train) [40][840/940] lr: 1.0000e-02 eta: 9:15:03 time: 0.5825 data_time: 0.0304 memory: 33630 grad_norm: 4.1157 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5149 loss: 1.5149 2022/10/15 01:19:47 - mmengine - INFO - Epoch(train) [40][860/940] lr: 1.0000e-02 eta: 9:14:51 time: 0.5782 data_time: 0.0466 memory: 33630 grad_norm: 4.1846 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5906 loss: 1.5906 2022/10/15 01:19:59 - mmengine - INFO - Epoch(train) [40][880/940] lr: 1.0000e-02 eta: 9:14:39 time: 0.5766 data_time: 0.0342 memory: 33630 grad_norm: 4.1769 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.6177 loss: 1.6177 2022/10/15 01:20:11 - mmengine - INFO - Epoch(train) [40][900/940] lr: 1.0000e-02 eta: 9:14:27 time: 0.5976 data_time: 0.0400 memory: 33630 grad_norm: 4.1715 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5120 loss: 1.5120 2022/10/15 01:20:22 - mmengine - INFO - Epoch(train) [40][920/940] lr: 1.0000e-02 eta: 9:14:15 time: 0.5806 data_time: 0.0328 memory: 33630 grad_norm: 4.2133 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6245 loss: 1.6245 2022/10/15 01:20:33 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 01:20:33 - mmengine - INFO - Epoch(train) [40][940/940] lr: 1.0000e-02 eta: 9:14:02 time: 0.5346 data_time: 0.0284 memory: 33630 grad_norm: 4.4893 top1_acc: 0.2857 top5_acc: 0.7143 loss_cls: 1.5950 loss: 1.5950 2022/10/15 01:20:48 - mmengine - INFO - Epoch(val) [40][20/78] eta: 0:00:43 time: 0.7449 data_time: 0.5754 memory: 5967 2022/10/15 01:20:58 - mmengine - INFO - Epoch(val) [40][40/78] eta: 0:00:19 time: 0.5087 data_time: 0.3403 memory: 5967 2022/10/15 01:21:11 - mmengine - INFO - Epoch(val) [40][60/78] eta: 0:00:11 time: 0.6299 data_time: 0.4612 memory: 5967 2022/10/15 01:21:22 - mmengine - INFO - Epoch(val) [40][78/78] acc/top1: 0.6472 acc/top5: 0.8569 acc/mean1: 0.6471 2022/10/15 01:21:38 - mmengine - INFO - Epoch(train) [41][20/940] lr: 1.0000e-03 eta: 9:13:57 time: 0.8239 data_time: 0.2363 memory: 33630 grad_norm: 4.0223 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4811 loss: 1.4811 2022/10/15 01:21:50 - mmengine - INFO - Epoch(train) [41][40/940] lr: 1.0000e-03 eta: 9:13:45 time: 0.5927 data_time: 0.0316 memory: 33630 grad_norm: 4.0677 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.5356 loss: 1.5356 2022/10/15 01:22:02 - mmengine - INFO - Epoch(train) [41][60/940] lr: 1.0000e-03 eta: 9:13:34 time: 0.6058 data_time: 0.0394 memory: 33630 grad_norm: 4.0601 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5152 loss: 1.5152 2022/10/15 01:22:14 - mmengine - INFO - Epoch(train) [41][80/940] lr: 1.0000e-03 eta: 9:13:22 time: 0.5930 data_time: 0.0315 memory: 33630 grad_norm: 3.9173 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4456 loss: 1.4456 2022/10/15 01:22:26 - mmengine - INFO - Epoch(train) [41][100/940] lr: 1.0000e-03 eta: 9:13:11 time: 0.5958 data_time: 0.0366 memory: 33630 grad_norm: 4.0610 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5536 loss: 1.5536 2022/10/15 01:22:38 - mmengine - INFO - Epoch(train) [41][120/940] lr: 1.0000e-03 eta: 9:12:59 time: 0.5946 data_time: 0.0323 memory: 33630 grad_norm: 3.9014 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.4759 loss: 1.4759 2022/10/15 01:22:50 - mmengine - INFO - Epoch(train) [41][140/940] lr: 1.0000e-03 eta: 9:12:48 time: 0.6037 data_time: 0.0347 memory: 33630 grad_norm: 4.0362 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5779 loss: 1.5779 2022/10/15 01:23:02 - mmengine - INFO - Epoch(train) [41][160/940] lr: 1.0000e-03 eta: 9:12:35 time: 0.5812 data_time: 0.0408 memory: 33630 grad_norm: 4.0093 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4727 loss: 1.4727 2022/10/15 01:23:14 - mmengine - INFO - Epoch(train) [41][180/940] lr: 1.0000e-03 eta: 9:12:24 time: 0.5964 data_time: 0.0372 memory: 33630 grad_norm: 4.0036 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6349 loss: 1.6349 2022/10/15 01:23:25 - mmengine - INFO - Epoch(train) [41][200/940] lr: 1.0000e-03 eta: 9:12:12 time: 0.5842 data_time: 0.0353 memory: 33630 grad_norm: 3.9624 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4663 loss: 1.4663 2022/10/15 01:23:37 - mmengine - INFO - Epoch(train) [41][220/940] lr: 1.0000e-03 eta: 9:12:00 time: 0.5925 data_time: 0.0312 memory: 33630 grad_norm: 3.9406 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.4805 loss: 1.4805 2022/10/15 01:23:49 - mmengine - INFO - Epoch(train) [41][240/940] lr: 1.0000e-03 eta: 9:11:48 time: 0.5729 data_time: 0.0416 memory: 33630 grad_norm: 3.9079 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3123 loss: 1.3123 2022/10/15 01:24:00 - mmengine - INFO - Epoch(train) [41][260/940] lr: 1.0000e-03 eta: 9:11:36 time: 0.5813 data_time: 0.0315 memory: 33630 grad_norm: 3.9849 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5674 loss: 1.5674 2022/10/15 01:24:12 - mmengine - INFO - Epoch(train) [41][280/940] lr: 1.0000e-03 eta: 9:11:24 time: 0.5884 data_time: 0.0363 memory: 33630 grad_norm: 3.9284 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2873 loss: 1.2873 2022/10/15 01:24:24 - mmengine - INFO - Epoch(train) [41][300/940] lr: 1.0000e-03 eta: 9:11:12 time: 0.5920 data_time: 0.0345 memory: 33630 grad_norm: 4.0205 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4739 loss: 1.4739 2022/10/15 01:24:36 - mmengine - INFO - Epoch(train) [41][320/940] lr: 1.0000e-03 eta: 9:11:00 time: 0.5831 data_time: 0.0401 memory: 33630 grad_norm: 3.9268 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4043 loss: 1.4043 2022/10/15 01:24:47 - mmengine - INFO - Epoch(train) [41][340/940] lr: 1.0000e-03 eta: 9:10:48 time: 0.5802 data_time: 0.0385 memory: 33630 grad_norm: 4.0243 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3892 loss: 1.3892 2022/10/15 01:24:59 - mmengine - INFO - Epoch(train) [41][360/940] lr: 1.0000e-03 eta: 9:10:37 time: 0.5891 data_time: 0.0393 memory: 33630 grad_norm: 3.8953 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.3951 loss: 1.3951 2022/10/15 01:25:11 - mmengine - INFO - Epoch(train) [41][380/940] lr: 1.0000e-03 eta: 9:10:24 time: 0.5765 data_time: 0.0330 memory: 33630 grad_norm: 3.9379 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3566 loss: 1.3566 2022/10/15 01:25:22 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 01:25:22 - mmengine - INFO - Epoch(train) [41][400/940] lr: 1.0000e-03 eta: 9:10:13 time: 0.5922 data_time: 0.0376 memory: 33630 grad_norm: 3.8947 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5033 loss: 1.5033 2022/10/15 01:25:34 - mmengine - INFO - Epoch(train) [41][420/940] lr: 1.0000e-03 eta: 9:10:01 time: 0.5844 data_time: 0.0385 memory: 33630 grad_norm: 3.9739 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.5005 loss: 1.5005 2022/10/15 01:25:46 - mmengine - INFO - Epoch(train) [41][440/940] lr: 1.0000e-03 eta: 9:09:49 time: 0.5800 data_time: 0.0441 memory: 33630 grad_norm: 3.8121 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.2887 loss: 1.2887 2022/10/15 01:25:57 - mmengine - INFO - Epoch(train) [41][460/940] lr: 1.0000e-03 eta: 9:09:36 time: 0.5773 data_time: 0.0495 memory: 33630 grad_norm: 3.9455 top1_acc: 0.5938 top5_acc: 0.9688 loss_cls: 1.3511 loss: 1.3511 2022/10/15 01:26:09 - mmengine - INFO - Epoch(train) [41][480/940] lr: 1.0000e-03 eta: 9:09:25 time: 0.5887 data_time: 0.0353 memory: 33630 grad_norm: 3.9793 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4799 loss: 1.4799 2022/10/15 01:26:21 - mmengine - INFO - Epoch(train) [41][500/940] lr: 1.0000e-03 eta: 9:09:13 time: 0.5843 data_time: 0.0309 memory: 33630 grad_norm: 3.9140 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.3499 loss: 1.3499 2022/10/15 01:26:32 - mmengine - INFO - Epoch(train) [41][520/940] lr: 1.0000e-03 eta: 9:09:00 time: 0.5714 data_time: 0.0305 memory: 33630 grad_norm: 3.8702 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5270 loss: 1.5270 2022/10/15 01:26:44 - mmengine - INFO - Epoch(train) [41][540/940] lr: 1.0000e-03 eta: 9:08:48 time: 0.5717 data_time: 0.0371 memory: 33630 grad_norm: 3.9385 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3764 loss: 1.3764 2022/10/15 01:26:55 - mmengine - INFO - Epoch(train) [41][560/940] lr: 1.0000e-03 eta: 9:08:36 time: 0.5904 data_time: 0.0363 memory: 33630 grad_norm: 4.0457 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.5606 loss: 1.5606 2022/10/15 01:27:07 - mmengine - INFO - Epoch(train) [41][580/940] lr: 1.0000e-03 eta: 9:08:24 time: 0.5807 data_time: 0.0381 memory: 33630 grad_norm: 3.9964 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3910 loss: 1.3910 2022/10/15 01:27:19 - mmengine - INFO - Epoch(train) [41][600/940] lr: 1.0000e-03 eta: 9:08:12 time: 0.5824 data_time: 0.0399 memory: 33630 grad_norm: 3.9799 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2939 loss: 1.2939 2022/10/15 01:27:30 - mmengine - INFO - Epoch(train) [41][620/940] lr: 1.0000e-03 eta: 9:08:00 time: 0.5828 data_time: 0.0357 memory: 33630 grad_norm: 3.9224 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3547 loss: 1.3547 2022/10/15 01:27:42 - mmengine - INFO - Epoch(train) [41][640/940] lr: 1.0000e-03 eta: 9:07:48 time: 0.5804 data_time: 0.0426 memory: 33630 grad_norm: 4.0098 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3898 loss: 1.3898 2022/10/15 01:27:54 - mmengine - INFO - Epoch(train) [41][660/940] lr: 1.0000e-03 eta: 9:07:37 time: 0.5934 data_time: 0.0357 memory: 33630 grad_norm: 4.0039 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3459 loss: 1.3459 2022/10/15 01:28:06 - mmengine - INFO - Epoch(train) [41][680/940] lr: 1.0000e-03 eta: 9:07:25 time: 0.5876 data_time: 0.0419 memory: 33630 grad_norm: 3.9200 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5032 loss: 1.5032 2022/10/15 01:28:17 - mmengine - INFO - Epoch(train) [41][700/940] lr: 1.0000e-03 eta: 9:07:13 time: 0.5822 data_time: 0.0296 memory: 33630 grad_norm: 4.0046 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.5111 loss: 1.5111 2022/10/15 01:28:29 - mmengine - INFO - Epoch(train) [41][720/940] lr: 1.0000e-03 eta: 9:07:01 time: 0.5950 data_time: 0.0482 memory: 33630 grad_norm: 3.9198 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3176 loss: 1.3176 2022/10/15 01:28:41 - mmengine - INFO - Epoch(train) [41][740/940] lr: 1.0000e-03 eta: 9:06:49 time: 0.5943 data_time: 0.0407 memory: 33630 grad_norm: 3.8900 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4424 loss: 1.4424 2022/10/15 01:28:53 - mmengine - INFO - Epoch(train) [41][760/940] lr: 1.0000e-03 eta: 9:06:38 time: 0.5943 data_time: 0.0413 memory: 33630 grad_norm: 4.0263 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6321 loss: 1.6321 2022/10/15 01:29:05 - mmengine - INFO - Epoch(train) [41][780/940] lr: 1.0000e-03 eta: 9:06:26 time: 0.5983 data_time: 0.0402 memory: 33630 grad_norm: 3.8981 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3801 loss: 1.3801 2022/10/15 01:29:17 - mmengine - INFO - Epoch(train) [41][800/940] lr: 1.0000e-03 eta: 9:06:14 time: 0.5865 data_time: 0.0378 memory: 33630 grad_norm: 3.9665 top1_acc: 0.5625 top5_acc: 0.9688 loss_cls: 1.3571 loss: 1.3571 2022/10/15 01:29:29 - mmengine - INFO - Epoch(train) [41][820/940] lr: 1.0000e-03 eta: 9:06:03 time: 0.5989 data_time: 0.0366 memory: 33630 grad_norm: 3.9418 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3229 loss: 1.3229 2022/10/15 01:29:40 - mmengine - INFO - Epoch(train) [41][840/940] lr: 1.0000e-03 eta: 9:05:51 time: 0.5833 data_time: 0.0356 memory: 33630 grad_norm: 3.9650 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3813 loss: 1.3813 2022/10/15 01:29:52 - mmengine - INFO - Epoch(train) [41][860/940] lr: 1.0000e-03 eta: 9:05:39 time: 0.5843 data_time: 0.0305 memory: 33630 grad_norm: 4.0388 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4862 loss: 1.4862 2022/10/15 01:30:04 - mmengine - INFO - Epoch(train) [41][880/940] lr: 1.0000e-03 eta: 9:05:27 time: 0.5926 data_time: 0.0412 memory: 33630 grad_norm: 3.9140 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3750 loss: 1.3750 2022/10/15 01:30:15 - mmengine - INFO - Epoch(train) [41][900/940] lr: 1.0000e-03 eta: 9:05:15 time: 0.5792 data_time: 0.0351 memory: 33630 grad_norm: 3.9086 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3559 loss: 1.3559 2022/10/15 01:30:27 - mmengine - INFO - Epoch(train) [41][920/940] lr: 1.0000e-03 eta: 9:05:03 time: 0.5782 data_time: 0.0305 memory: 33630 grad_norm: 3.8865 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4021 loss: 1.4021 2022/10/15 01:30:38 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 01:30:38 - mmengine - INFO - Epoch(train) [41][940/940] lr: 1.0000e-03 eta: 9:04:50 time: 0.5438 data_time: 0.0313 memory: 33630 grad_norm: 4.2501 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.3135 loss: 1.3135 2022/10/15 01:30:52 - mmengine - INFO - Epoch(val) [41][20/78] eta: 0:00:41 time: 0.7127 data_time: 0.5407 memory: 5967 2022/10/15 01:31:03 - mmengine - INFO - Epoch(val) [41][40/78] eta: 0:00:20 time: 0.5466 data_time: 0.3807 memory: 5967 2022/10/15 01:31:14 - mmengine - INFO - Epoch(val) [41][60/78] eta: 0:00:09 time: 0.5506 data_time: 0.3838 memory: 5967 2022/10/15 01:31:28 - mmengine - INFO - Epoch(val) [41][78/78] acc/top1: 0.6763 acc/top5: 0.8734 acc/mean1: 0.6763 2022/10/15 01:31:28 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_36.pth is removed 2022/10/15 01:31:29 - mmengine - INFO - The best checkpoint with 0.6763 acc/top1 at 41 epoch is saved to best_acc/top1_epoch_41.pth. 2022/10/15 01:31:45 - mmengine - INFO - Epoch(train) [42][20/940] lr: 1.0000e-03 eta: 9:04:44 time: 0.8008 data_time: 0.2489 memory: 33630 grad_norm: 3.9747 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3634 loss: 1.3634 2022/10/15 01:31:56 - mmengine - INFO - Epoch(train) [42][40/940] lr: 1.0000e-03 eta: 9:04:32 time: 0.5787 data_time: 0.0326 memory: 33630 grad_norm: 4.0215 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2812 loss: 1.2812 2022/10/15 01:32:08 - mmengine - INFO - Epoch(train) [42][60/940] lr: 1.0000e-03 eta: 9:04:20 time: 0.5809 data_time: 0.0380 memory: 33630 grad_norm: 4.0275 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4807 loss: 1.4807 2022/10/15 01:32:20 - mmengine - INFO - Epoch(train) [42][80/940] lr: 1.0000e-03 eta: 9:04:08 time: 0.5885 data_time: 0.0323 memory: 33630 grad_norm: 3.9620 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3596 loss: 1.3596 2022/10/15 01:32:32 - mmengine - INFO - Epoch(train) [42][100/940] lr: 1.0000e-03 eta: 9:03:57 time: 0.5971 data_time: 0.0387 memory: 33630 grad_norm: 3.9757 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4934 loss: 1.4934 2022/10/15 01:32:44 - mmengine - INFO - Epoch(train) [42][120/940] lr: 1.0000e-03 eta: 9:03:45 time: 0.6026 data_time: 0.0378 memory: 33630 grad_norm: 3.9065 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2548 loss: 1.2548 2022/10/15 01:32:56 - mmengine - INFO - Epoch(train) [42][140/940] lr: 1.0000e-03 eta: 9:03:33 time: 0.5892 data_time: 0.0451 memory: 33630 grad_norm: 3.9592 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3763 loss: 1.3763 2022/10/15 01:33:07 - mmengine - INFO - Epoch(train) [42][160/940] lr: 1.0000e-03 eta: 9:03:21 time: 0.5821 data_time: 0.0381 memory: 33630 grad_norm: 3.9698 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.4185 loss: 1.4185 2022/10/15 01:33:19 - mmengine - INFO - Epoch(train) [42][180/940] lr: 1.0000e-03 eta: 9:03:09 time: 0.5759 data_time: 0.0383 memory: 33630 grad_norm: 4.0728 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3060 loss: 1.3060 2022/10/15 01:33:30 - mmengine - INFO - Epoch(train) [42][200/940] lr: 1.0000e-03 eta: 9:02:57 time: 0.5864 data_time: 0.0456 memory: 33630 grad_norm: 3.9636 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2913 loss: 1.2913 2022/10/15 01:33:42 - mmengine - INFO - Epoch(train) [42][220/940] lr: 1.0000e-03 eta: 9:02:45 time: 0.5780 data_time: 0.0400 memory: 33630 grad_norm: 4.0726 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3680 loss: 1.3680 2022/10/15 01:33:54 - mmengine - INFO - Epoch(train) [42][240/940] lr: 1.0000e-03 eta: 9:02:33 time: 0.5881 data_time: 0.0382 memory: 33630 grad_norm: 3.9709 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5134 loss: 1.5134 2022/10/15 01:34:05 - mmengine - INFO - Epoch(train) [42][260/940] lr: 1.0000e-03 eta: 9:02:21 time: 0.5794 data_time: 0.0314 memory: 33630 grad_norm: 3.9942 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4116 loss: 1.4116 2022/10/15 01:34:17 - mmengine - INFO - Epoch(train) [42][280/940] lr: 1.0000e-03 eta: 9:02:10 time: 0.5905 data_time: 0.0391 memory: 33630 grad_norm: 3.9688 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3311 loss: 1.3311 2022/10/15 01:34:29 - mmengine - INFO - Epoch(train) [42][300/940] lr: 1.0000e-03 eta: 9:01:58 time: 0.5984 data_time: 0.0311 memory: 33630 grad_norm: 4.0333 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3419 loss: 1.3419 2022/10/15 01:34:41 - mmengine - INFO - Epoch(train) [42][320/940] lr: 1.0000e-03 eta: 9:01:46 time: 0.5770 data_time: 0.0404 memory: 33630 grad_norm: 4.0452 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4940 loss: 1.4940 2022/10/15 01:34:52 - mmengine - INFO - Epoch(train) [42][340/940] lr: 1.0000e-03 eta: 9:01:34 time: 0.5891 data_time: 0.0369 memory: 33630 grad_norm: 3.9620 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3474 loss: 1.3474 2022/10/15 01:35:04 - mmengine - INFO - Epoch(train) [42][360/940] lr: 1.0000e-03 eta: 9:01:22 time: 0.5796 data_time: 0.0395 memory: 33630 grad_norm: 4.0476 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3724 loss: 1.3724 2022/10/15 01:35:16 - mmengine - INFO - Epoch(train) [42][380/940] lr: 1.0000e-03 eta: 9:01:10 time: 0.5797 data_time: 0.0392 memory: 33630 grad_norm: 4.0163 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3319 loss: 1.3319 2022/10/15 01:35:27 - mmengine - INFO - Epoch(train) [42][400/940] lr: 1.0000e-03 eta: 9:00:58 time: 0.5713 data_time: 0.0322 memory: 33630 grad_norm: 4.1009 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2777 loss: 1.2777 2022/10/15 01:35:38 - mmengine - INFO - Epoch(train) [42][420/940] lr: 1.0000e-03 eta: 9:00:45 time: 0.5716 data_time: 0.0370 memory: 33630 grad_norm: 4.0588 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4549 loss: 1.4549 2022/10/15 01:35:50 - mmengine - INFO - Epoch(train) [42][440/940] lr: 1.0000e-03 eta: 9:00:34 time: 0.5866 data_time: 0.0369 memory: 33630 grad_norm: 4.0578 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.4988 loss: 1.4988 2022/10/15 01:36:02 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 01:36:02 - mmengine - INFO - Epoch(train) [42][460/940] lr: 1.0000e-03 eta: 9:00:22 time: 0.5903 data_time: 0.0344 memory: 33630 grad_norm: 3.9982 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.4068 loss: 1.4068 2022/10/15 01:36:14 - mmengine - INFO - Epoch(train) [42][480/940] lr: 1.0000e-03 eta: 9:00:10 time: 0.5767 data_time: 0.0356 memory: 33630 grad_norm: 3.9885 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3057 loss: 1.3057 2022/10/15 01:36:25 - mmengine - INFO - Epoch(train) [42][500/940] lr: 1.0000e-03 eta: 8:59:58 time: 0.5833 data_time: 0.0499 memory: 33630 grad_norm: 3.9936 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3021 loss: 1.3021 2022/10/15 01:36:37 - mmengine - INFO - Epoch(train) [42][520/940] lr: 1.0000e-03 eta: 8:59:46 time: 0.5844 data_time: 0.0405 memory: 33630 grad_norm: 3.9238 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4312 loss: 1.4312 2022/10/15 01:36:49 - mmengine - INFO - Epoch(train) [42][540/940] lr: 1.0000e-03 eta: 8:59:34 time: 0.5846 data_time: 0.0310 memory: 33630 grad_norm: 4.0312 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3093 loss: 1.3093 2022/10/15 01:37:00 - mmengine - INFO - Epoch(train) [42][560/940] lr: 1.0000e-03 eta: 8:59:22 time: 0.5733 data_time: 0.0420 memory: 33630 grad_norm: 3.9472 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.3237 loss: 1.3237 2022/10/15 01:37:12 - mmengine - INFO - Epoch(train) [42][580/940] lr: 1.0000e-03 eta: 8:59:10 time: 0.5834 data_time: 0.0495 memory: 33630 grad_norm: 4.0392 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.4106 loss: 1.4106 2022/10/15 01:37:23 - mmengine - INFO - Epoch(train) [42][600/940] lr: 1.0000e-03 eta: 8:58:58 time: 0.5856 data_time: 0.0407 memory: 33630 grad_norm: 4.0197 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4044 loss: 1.4044 2022/10/15 01:37:35 - mmengine - INFO - Epoch(train) [42][620/940] lr: 1.0000e-03 eta: 8:58:46 time: 0.5920 data_time: 0.0342 memory: 33630 grad_norm: 4.0625 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3728 loss: 1.3728 2022/10/15 01:37:47 - mmengine - INFO - Epoch(train) [42][640/940] lr: 1.0000e-03 eta: 8:58:34 time: 0.5818 data_time: 0.0300 memory: 33630 grad_norm: 3.9911 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4056 loss: 1.4056 2022/10/15 01:37:59 - mmengine - INFO - Epoch(train) [42][660/940] lr: 1.0000e-03 eta: 8:58:22 time: 0.5787 data_time: 0.0358 memory: 33630 grad_norm: 4.0014 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3722 loss: 1.3722 2022/10/15 01:38:10 - mmengine - INFO - Epoch(train) [42][680/940] lr: 1.0000e-03 eta: 8:58:10 time: 0.5773 data_time: 0.0360 memory: 33630 grad_norm: 3.9825 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3665 loss: 1.3665 2022/10/15 01:38:22 - mmengine - INFO - Epoch(train) [42][700/940] lr: 1.0000e-03 eta: 8:57:58 time: 0.5867 data_time: 0.0473 memory: 33630 grad_norm: 4.0593 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2634 loss: 1.2634 2022/10/15 01:38:33 - mmengine - INFO - Epoch(train) [42][720/940] lr: 1.0000e-03 eta: 8:57:46 time: 0.5751 data_time: 0.0361 memory: 33630 grad_norm: 4.0140 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4271 loss: 1.4271 2022/10/15 01:38:45 - mmengine - INFO - Epoch(train) [42][740/940] lr: 1.0000e-03 eta: 8:57:34 time: 0.5793 data_time: 0.0295 memory: 33630 grad_norm: 4.0393 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3469 loss: 1.3469 2022/10/15 01:38:57 - mmengine - INFO - Epoch(train) [42][760/940] lr: 1.0000e-03 eta: 8:57:22 time: 0.5975 data_time: 0.0423 memory: 33630 grad_norm: 4.0071 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3506 loss: 1.3506 2022/10/15 01:39:09 - mmengine - INFO - Epoch(train) [42][780/940] lr: 1.0000e-03 eta: 8:57:10 time: 0.5869 data_time: 0.0350 memory: 33630 grad_norm: 4.1483 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4246 loss: 1.4246 2022/10/15 01:39:20 - mmengine - INFO - Epoch(train) [42][800/940] lr: 1.0000e-03 eta: 8:56:58 time: 0.5839 data_time: 0.0320 memory: 33630 grad_norm: 4.0270 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3221 loss: 1.3221 2022/10/15 01:39:32 - mmengine - INFO - Epoch(train) [42][820/940] lr: 1.0000e-03 eta: 8:56:46 time: 0.5756 data_time: 0.0326 memory: 33630 grad_norm: 3.9489 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3796 loss: 1.3796 2022/10/15 01:39:43 - mmengine - INFO - Epoch(train) [42][840/940] lr: 1.0000e-03 eta: 8:56:34 time: 0.5768 data_time: 0.0427 memory: 33630 grad_norm: 4.0375 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5421 loss: 1.5421 2022/10/15 01:39:55 - mmengine - INFO - Epoch(train) [42][860/940] lr: 1.0000e-03 eta: 8:56:22 time: 0.5900 data_time: 0.0408 memory: 33630 grad_norm: 3.9958 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.3084 loss: 1.3084 2022/10/15 01:40:07 - mmengine - INFO - Epoch(train) [42][880/940] lr: 1.0000e-03 eta: 8:56:10 time: 0.5829 data_time: 0.0370 memory: 33630 grad_norm: 4.0603 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.2271 loss: 1.2271 2022/10/15 01:40:18 - mmengine - INFO - Epoch(train) [42][900/940] lr: 1.0000e-03 eta: 8:55:58 time: 0.5816 data_time: 0.0324 memory: 33630 grad_norm: 3.9855 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2717 loss: 1.2717 2022/10/15 01:40:30 - mmengine - INFO - Epoch(train) [42][920/940] lr: 1.0000e-03 eta: 8:55:46 time: 0.5732 data_time: 0.0385 memory: 33630 grad_norm: 4.0933 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3745 loss: 1.3745 2022/10/15 01:40:41 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 01:40:41 - mmengine - INFO - Epoch(train) [42][940/940] lr: 1.0000e-03 eta: 8:55:33 time: 0.5468 data_time: 0.0313 memory: 33630 grad_norm: 4.1406 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.2524 loss: 1.2524 2022/10/15 01:40:41 - mmengine - INFO - Saving checkpoint at 42 epochs 2022/10/15 01:40:56 - mmengine - INFO - Epoch(val) [42][20/78] eta: 0:00:41 time: 0.7229 data_time: 0.5537 memory: 5967 2022/10/15 01:41:06 - mmengine - INFO - Epoch(val) [42][40/78] eta: 0:00:18 time: 0.4854 data_time: 0.3178 memory: 5967 2022/10/15 01:41:20 - mmengine - INFO - Epoch(val) [42][60/78] eta: 0:00:12 time: 0.7083 data_time: 0.5381 memory: 5967 2022/10/15 01:41:31 - mmengine - INFO - Epoch(val) [42][78/78] acc/top1: 0.6796 acc/top5: 0.8748 acc/mean1: 0.6796 2022/10/15 01:41:31 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_41.pth is removed 2022/10/15 01:41:32 - mmengine - INFO - The best checkpoint with 0.6796 acc/top1 at 42 epoch is saved to best_acc/top1_epoch_42.pth. 2022/10/15 01:41:48 - mmengine - INFO - Epoch(train) [43][20/940] lr: 1.0000e-03 eta: 8:55:27 time: 0.8010 data_time: 0.2515 memory: 33630 grad_norm: 3.9951 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4218 loss: 1.4218 2022/10/15 01:42:00 - mmengine - INFO - Epoch(train) [43][40/940] lr: 1.0000e-03 eta: 8:55:15 time: 0.5945 data_time: 0.0305 memory: 33630 grad_norm: 4.0341 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.3612 loss: 1.3612 2022/10/15 01:42:12 - mmengine - INFO - Epoch(train) [43][60/940] lr: 1.0000e-03 eta: 8:55:03 time: 0.5848 data_time: 0.0428 memory: 33630 grad_norm: 3.9901 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.4995 loss: 1.4995 2022/10/15 01:42:23 - mmengine - INFO - Epoch(train) [43][80/940] lr: 1.0000e-03 eta: 8:54:52 time: 0.5858 data_time: 0.0321 memory: 33630 grad_norm: 4.1194 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3637 loss: 1.3637 2022/10/15 01:42:35 - mmengine - INFO - Epoch(train) [43][100/940] lr: 1.0000e-03 eta: 8:54:40 time: 0.5845 data_time: 0.0374 memory: 33630 grad_norm: 4.1250 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3927 loss: 1.3927 2022/10/15 01:42:47 - mmengine - INFO - Epoch(train) [43][120/940] lr: 1.0000e-03 eta: 8:54:28 time: 0.5892 data_time: 0.0316 memory: 33630 grad_norm: 3.9830 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4488 loss: 1.4488 2022/10/15 01:42:59 - mmengine - INFO - Epoch(train) [43][140/940] lr: 1.0000e-03 eta: 8:54:16 time: 0.5778 data_time: 0.0362 memory: 33630 grad_norm: 3.9671 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2943 loss: 1.2943 2022/10/15 01:43:10 - mmengine - INFO - Epoch(train) [43][160/940] lr: 1.0000e-03 eta: 8:54:04 time: 0.5917 data_time: 0.0382 memory: 33630 grad_norm: 3.9175 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2597 loss: 1.2597 2022/10/15 01:43:22 - mmengine - INFO - Epoch(train) [43][180/940] lr: 1.0000e-03 eta: 8:53:52 time: 0.5823 data_time: 0.0359 memory: 33630 grad_norm: 4.0153 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.2708 loss: 1.2708 2022/10/15 01:43:34 - mmengine - INFO - Epoch(train) [43][200/940] lr: 1.0000e-03 eta: 8:53:41 time: 0.5999 data_time: 0.0401 memory: 33630 grad_norm: 4.0437 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3661 loss: 1.3661 2022/10/15 01:43:46 - mmengine - INFO - Epoch(train) [43][220/940] lr: 1.0000e-03 eta: 8:53:28 time: 0.5788 data_time: 0.0361 memory: 33630 grad_norm: 3.9350 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3019 loss: 1.3019 2022/10/15 01:43:57 - mmengine - INFO - Epoch(train) [43][240/940] lr: 1.0000e-03 eta: 8:53:16 time: 0.5758 data_time: 0.0459 memory: 33630 grad_norm: 4.0851 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.4092 loss: 1.4092 2022/10/15 01:44:09 - mmengine - INFO - Epoch(train) [43][260/940] lr: 1.0000e-03 eta: 8:53:05 time: 0.5960 data_time: 0.0420 memory: 33630 grad_norm: 4.0408 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3502 loss: 1.3502 2022/10/15 01:44:21 - mmengine - INFO - Epoch(train) [43][280/940] lr: 1.0000e-03 eta: 8:52:53 time: 0.5806 data_time: 0.0316 memory: 33630 grad_norm: 4.0370 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4029 loss: 1.4029 2022/10/15 01:44:32 - mmengine - INFO - Epoch(train) [43][300/940] lr: 1.0000e-03 eta: 8:52:41 time: 0.5804 data_time: 0.0375 memory: 33630 grad_norm: 4.0149 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.3882 loss: 1.3882 2022/10/15 01:44:44 - mmengine - INFO - Epoch(train) [43][320/940] lr: 1.0000e-03 eta: 8:52:29 time: 0.5895 data_time: 0.0321 memory: 33630 grad_norm: 4.0756 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.3936 loss: 1.3936 2022/10/15 01:44:56 - mmengine - INFO - Epoch(train) [43][340/940] lr: 1.0000e-03 eta: 8:52:17 time: 0.5824 data_time: 0.0354 memory: 33630 grad_norm: 4.0772 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3415 loss: 1.3415 2022/10/15 01:45:07 - mmengine - INFO - Epoch(train) [43][360/940] lr: 1.0000e-03 eta: 8:52:05 time: 0.5865 data_time: 0.0323 memory: 33630 grad_norm: 4.0478 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3297 loss: 1.3297 2022/10/15 01:45:19 - mmengine - INFO - Epoch(train) [43][380/940] lr: 1.0000e-03 eta: 8:51:53 time: 0.5852 data_time: 0.0391 memory: 33630 grad_norm: 3.9980 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3008 loss: 1.3008 2022/10/15 01:45:31 - mmengine - INFO - Epoch(train) [43][400/940] lr: 1.0000e-03 eta: 8:51:41 time: 0.5880 data_time: 0.0402 memory: 33630 grad_norm: 4.1089 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4020 loss: 1.4020 2022/10/15 01:45:43 - mmengine - INFO - Epoch(train) [43][420/940] lr: 1.0000e-03 eta: 8:51:29 time: 0.5879 data_time: 0.0405 memory: 33630 grad_norm: 4.0119 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3902 loss: 1.3902 2022/10/15 01:45:54 - mmengine - INFO - Epoch(train) [43][440/940] lr: 1.0000e-03 eta: 8:51:18 time: 0.5901 data_time: 0.0357 memory: 33630 grad_norm: 4.0113 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2823 loss: 1.2823 2022/10/15 01:46:06 - mmengine - INFO - Epoch(train) [43][460/940] lr: 1.0000e-03 eta: 8:51:05 time: 0.5771 data_time: 0.0333 memory: 33630 grad_norm: 4.1211 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.4001 loss: 1.4001 2022/10/15 01:46:18 - mmengine - INFO - Epoch(train) [43][480/940] lr: 1.0000e-03 eta: 8:50:54 time: 0.5849 data_time: 0.0351 memory: 33630 grad_norm: 4.1008 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2694 loss: 1.2694 2022/10/15 01:46:29 - mmengine - INFO - Epoch(train) [43][500/940] lr: 1.0000e-03 eta: 8:50:42 time: 0.5894 data_time: 0.0329 memory: 33630 grad_norm: 4.0057 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3065 loss: 1.3065 2022/10/15 01:46:41 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 01:46:41 - mmengine - INFO - Epoch(train) [43][520/940] lr: 1.0000e-03 eta: 8:50:30 time: 0.5799 data_time: 0.0370 memory: 33630 grad_norm: 4.0723 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2845 loss: 1.2845 2022/10/15 01:46:53 - mmengine - INFO - Epoch(train) [43][540/940] lr: 1.0000e-03 eta: 8:50:18 time: 0.5729 data_time: 0.0346 memory: 33630 grad_norm: 3.9936 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4212 loss: 1.4212 2022/10/15 01:47:04 - mmengine - INFO - Epoch(train) [43][560/940] lr: 1.0000e-03 eta: 8:50:05 time: 0.5813 data_time: 0.0412 memory: 33630 grad_norm: 4.0338 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2001 loss: 1.2001 2022/10/15 01:47:16 - mmengine - INFO - Epoch(train) [43][580/940] lr: 1.0000e-03 eta: 8:49:54 time: 0.5822 data_time: 0.0402 memory: 33630 grad_norm: 4.0297 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3389 loss: 1.3389 2022/10/15 01:47:27 - mmengine - INFO - Epoch(train) [43][600/940] lr: 1.0000e-03 eta: 8:49:41 time: 0.5796 data_time: 0.0330 memory: 33630 grad_norm: 4.0739 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5048 loss: 1.5048 2022/10/15 01:47:39 - mmengine - INFO - Epoch(train) [43][620/940] lr: 1.0000e-03 eta: 8:49:30 time: 0.5840 data_time: 0.0377 memory: 33630 grad_norm: 4.0979 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3440 loss: 1.3440 2022/10/15 01:47:51 - mmengine - INFO - Epoch(train) [43][640/940] lr: 1.0000e-03 eta: 8:49:17 time: 0.5776 data_time: 0.0408 memory: 33630 grad_norm: 3.9326 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.3511 loss: 1.3511 2022/10/15 01:48:02 - mmengine - INFO - Epoch(train) [43][660/940] lr: 1.0000e-03 eta: 8:49:06 time: 0.5885 data_time: 0.0328 memory: 33630 grad_norm: 4.0775 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3436 loss: 1.3436 2022/10/15 01:48:14 - mmengine - INFO - Epoch(train) [43][680/940] lr: 1.0000e-03 eta: 8:48:54 time: 0.5791 data_time: 0.0388 memory: 33630 grad_norm: 4.1432 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4023 loss: 1.4023 2022/10/15 01:48:26 - mmengine - INFO - Epoch(train) [43][700/940] lr: 1.0000e-03 eta: 8:48:42 time: 0.5818 data_time: 0.0353 memory: 33630 grad_norm: 4.0478 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3737 loss: 1.3737 2022/10/15 01:48:38 - mmengine - INFO - Epoch(train) [43][720/940] lr: 1.0000e-03 eta: 8:48:30 time: 0.5980 data_time: 0.0421 memory: 33630 grad_norm: 4.0134 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3641 loss: 1.3641 2022/10/15 01:48:49 - mmengine - INFO - Epoch(train) [43][740/940] lr: 1.0000e-03 eta: 8:48:18 time: 0.5776 data_time: 0.0363 memory: 33630 grad_norm: 3.9999 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2951 loss: 1.2951 2022/10/15 01:49:01 - mmengine - INFO - Epoch(train) [43][760/940] lr: 1.0000e-03 eta: 8:48:06 time: 0.5759 data_time: 0.0383 memory: 33630 grad_norm: 4.0362 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4901 loss: 1.4901 2022/10/15 01:49:13 - mmengine - INFO - Epoch(train) [43][780/940] lr: 1.0000e-03 eta: 8:47:54 time: 0.6047 data_time: 0.0285 memory: 33630 grad_norm: 4.0759 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3721 loss: 1.3721 2022/10/15 01:49:25 - mmengine - INFO - Epoch(train) [43][800/940] lr: 1.0000e-03 eta: 8:47:43 time: 0.5934 data_time: 0.0380 memory: 33630 grad_norm: 4.0293 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3704 loss: 1.3704 2022/10/15 01:49:36 - mmengine - INFO - Epoch(train) [43][820/940] lr: 1.0000e-03 eta: 8:47:31 time: 0.5800 data_time: 0.0370 memory: 33630 grad_norm: 4.0387 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3686 loss: 1.3686 2022/10/15 01:49:48 - mmengine - INFO - Epoch(train) [43][840/940] lr: 1.0000e-03 eta: 8:47:18 time: 0.5745 data_time: 0.0371 memory: 33630 grad_norm: 3.9979 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2209 loss: 1.2209 2022/10/15 01:49:59 - mmengine - INFO - Epoch(train) [43][860/940] lr: 1.0000e-03 eta: 8:47:06 time: 0.5709 data_time: 0.0425 memory: 33630 grad_norm: 3.9602 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2436 loss: 1.2436 2022/10/15 01:50:11 - mmengine - INFO - Epoch(train) [43][880/940] lr: 1.0000e-03 eta: 8:46:54 time: 0.5810 data_time: 0.0315 memory: 33630 grad_norm: 4.0617 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3050 loss: 1.3050 2022/10/15 01:50:23 - mmengine - INFO - Epoch(train) [43][900/940] lr: 1.0000e-03 eta: 8:46:42 time: 0.5915 data_time: 0.0316 memory: 33630 grad_norm: 3.9803 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3434 loss: 1.3434 2022/10/15 01:50:34 - mmengine - INFO - Epoch(train) [43][920/940] lr: 1.0000e-03 eta: 8:46:31 time: 0.5865 data_time: 0.0336 memory: 33630 grad_norm: 4.1065 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4732 loss: 1.4732 2022/10/15 01:50:45 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 01:50:45 - mmengine - INFO - Epoch(train) [43][940/940] lr: 1.0000e-03 eta: 8:46:17 time: 0.5335 data_time: 0.0279 memory: 33630 grad_norm: 4.3171 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.3772 loss: 1.3772 2022/10/15 01:51:00 - mmengine - INFO - Epoch(val) [43][20/78] eta: 0:00:42 time: 0.7368 data_time: 0.5678 memory: 5967 2022/10/15 01:51:09 - mmengine - INFO - Epoch(val) [43][40/78] eta: 0:00:18 time: 0.4816 data_time: 0.3127 memory: 5967 2022/10/15 01:51:22 - mmengine - INFO - Epoch(val) [43][60/78] eta: 0:00:11 time: 0.6558 data_time: 0.4880 memory: 5967 2022/10/15 01:51:34 - mmengine - INFO - Epoch(val) [43][78/78] acc/top1: 0.6814 acc/top5: 0.8767 acc/mean1: 0.6813 2022/10/15 01:51:34 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_42.pth is removed 2022/10/15 01:51:35 - mmengine - INFO - The best checkpoint with 0.6814 acc/top1 at 43 epoch is saved to best_acc/top1_epoch_43.pth. 2022/10/15 01:51:51 - mmengine - INFO - Epoch(train) [44][20/940] lr: 1.0000e-03 eta: 8:46:11 time: 0.8118 data_time: 0.2610 memory: 33630 grad_norm: 3.9216 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.2224 loss: 1.2224 2022/10/15 01:52:02 - mmengine - INFO - Epoch(train) [44][40/940] lr: 1.0000e-03 eta: 8:45:59 time: 0.5685 data_time: 0.0311 memory: 33630 grad_norm: 4.0858 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3393 loss: 1.3393 2022/10/15 01:52:14 - mmengine - INFO - Epoch(train) [44][60/940] lr: 1.0000e-03 eta: 8:45:47 time: 0.5884 data_time: 0.0402 memory: 33630 grad_norm: 4.0267 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3378 loss: 1.3378 2022/10/15 01:52:26 - mmengine - INFO - Epoch(train) [44][80/940] lr: 1.0000e-03 eta: 8:45:35 time: 0.5879 data_time: 0.0293 memory: 33630 grad_norm: 4.0454 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3365 loss: 1.3365 2022/10/15 01:52:38 - mmengine - INFO - Epoch(train) [44][100/940] lr: 1.0000e-03 eta: 8:45:24 time: 0.5858 data_time: 0.0355 memory: 33630 grad_norm: 3.9628 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2999 loss: 1.2999 2022/10/15 01:52:49 - mmengine - INFO - Epoch(train) [44][120/940] lr: 1.0000e-03 eta: 8:45:12 time: 0.5954 data_time: 0.0320 memory: 33630 grad_norm: 4.1007 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2455 loss: 1.2455 2022/10/15 01:53:01 - mmengine - INFO - Epoch(train) [44][140/940] lr: 1.0000e-03 eta: 8:45:00 time: 0.5849 data_time: 0.0465 memory: 33630 grad_norm: 4.1024 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.3514 loss: 1.3514 2022/10/15 01:53:13 - mmengine - INFO - Epoch(train) [44][160/940] lr: 1.0000e-03 eta: 8:44:48 time: 0.5818 data_time: 0.0344 memory: 33630 grad_norm: 4.0905 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2931 loss: 1.2931 2022/10/15 01:53:24 - mmengine - INFO - Epoch(train) [44][180/940] lr: 1.0000e-03 eta: 8:44:36 time: 0.5816 data_time: 0.0385 memory: 33630 grad_norm: 4.0258 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.2560 loss: 1.2560 2022/10/15 01:53:36 - mmengine - INFO - Epoch(train) [44][200/940] lr: 1.0000e-03 eta: 8:44:24 time: 0.5804 data_time: 0.0396 memory: 33630 grad_norm: 4.0814 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.4404 loss: 1.4404 2022/10/15 01:53:48 - mmengine - INFO - Epoch(train) [44][220/940] lr: 1.0000e-03 eta: 8:44:12 time: 0.5870 data_time: 0.0364 memory: 33630 grad_norm: 4.1332 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4610 loss: 1.4610 2022/10/15 01:54:00 - mmengine - INFO - Epoch(train) [44][240/940] lr: 1.0000e-03 eta: 8:44:00 time: 0.5868 data_time: 0.0501 memory: 33630 grad_norm: 4.0287 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3007 loss: 1.3007 2022/10/15 01:54:11 - mmengine - INFO - Epoch(train) [44][260/940] lr: 1.0000e-03 eta: 8:43:48 time: 0.5889 data_time: 0.0344 memory: 33630 grad_norm: 4.0548 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4266 loss: 1.4266 2022/10/15 01:54:23 - mmengine - INFO - Epoch(train) [44][280/940] lr: 1.0000e-03 eta: 8:43:37 time: 0.5916 data_time: 0.0402 memory: 33630 grad_norm: 3.9615 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3386 loss: 1.3386 2022/10/15 01:54:35 - mmengine - INFO - Epoch(train) [44][300/940] lr: 1.0000e-03 eta: 8:43:25 time: 0.5832 data_time: 0.0416 memory: 33630 grad_norm: 3.9911 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4599 loss: 1.4599 2022/10/15 01:54:46 - mmengine - INFO - Epoch(train) [44][320/940] lr: 1.0000e-03 eta: 8:43:13 time: 0.5714 data_time: 0.0448 memory: 33630 grad_norm: 4.1439 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3988 loss: 1.3988 2022/10/15 01:54:58 - mmengine - INFO - Epoch(train) [44][340/940] lr: 1.0000e-03 eta: 8:43:01 time: 0.5842 data_time: 0.0381 memory: 33630 grad_norm: 4.1029 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3354 loss: 1.3354 2022/10/15 01:55:09 - mmengine - INFO - Epoch(train) [44][360/940] lr: 1.0000e-03 eta: 8:42:48 time: 0.5738 data_time: 0.0313 memory: 33630 grad_norm: 3.9981 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3188 loss: 1.3188 2022/10/15 01:55:21 - mmengine - INFO - Epoch(train) [44][380/940] lr: 1.0000e-03 eta: 8:42:36 time: 0.5847 data_time: 0.0354 memory: 33630 grad_norm: 4.0312 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3625 loss: 1.3625 2022/10/15 01:55:33 - mmengine - INFO - Epoch(train) [44][400/940] lr: 1.0000e-03 eta: 8:42:25 time: 0.5931 data_time: 0.0318 memory: 33630 grad_norm: 4.1540 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3604 loss: 1.3604 2022/10/15 01:55:45 - mmengine - INFO - Epoch(train) [44][420/940] lr: 1.0000e-03 eta: 8:42:13 time: 0.5901 data_time: 0.0435 memory: 33630 grad_norm: 4.0434 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.4388 loss: 1.4388 2022/10/15 01:55:56 - mmengine - INFO - Epoch(train) [44][440/940] lr: 1.0000e-03 eta: 8:42:01 time: 0.5712 data_time: 0.0379 memory: 33630 grad_norm: 4.1097 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3288 loss: 1.3288 2022/10/15 01:56:08 - mmengine - INFO - Epoch(train) [44][460/940] lr: 1.0000e-03 eta: 8:41:49 time: 0.5925 data_time: 0.0356 memory: 33630 grad_norm: 4.0828 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3777 loss: 1.3777 2022/10/15 01:56:20 - mmengine - INFO - Epoch(train) [44][480/940] lr: 1.0000e-03 eta: 8:41:37 time: 0.5820 data_time: 0.0318 memory: 33630 grad_norm: 4.0418 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3060 loss: 1.3060 2022/10/15 01:56:31 - mmengine - INFO - Epoch(train) [44][500/940] lr: 1.0000e-03 eta: 8:41:25 time: 0.5797 data_time: 0.0304 memory: 33630 grad_norm: 4.0616 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3092 loss: 1.3092 2022/10/15 01:56:43 - mmengine - INFO - Epoch(train) [44][520/940] lr: 1.0000e-03 eta: 8:41:13 time: 0.5847 data_time: 0.0307 memory: 33630 grad_norm: 4.2277 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3485 loss: 1.3485 2022/10/15 01:56:55 - mmengine - INFO - Epoch(train) [44][540/940] lr: 1.0000e-03 eta: 8:41:01 time: 0.5820 data_time: 0.0410 memory: 33630 grad_norm: 4.0315 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2203 loss: 1.2203 2022/10/15 01:57:06 - mmengine - INFO - Epoch(train) [44][560/940] lr: 1.0000e-03 eta: 8:40:49 time: 0.5845 data_time: 0.0361 memory: 33630 grad_norm: 4.0565 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3758 loss: 1.3758 2022/10/15 01:57:18 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 01:57:18 - mmengine - INFO - Epoch(train) [44][580/940] lr: 1.0000e-03 eta: 8:40:37 time: 0.5732 data_time: 0.0327 memory: 33630 grad_norm: 4.1577 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4203 loss: 1.4203 2022/10/15 01:57:29 - mmengine - INFO - Epoch(train) [44][600/940] lr: 1.0000e-03 eta: 8:40:25 time: 0.5820 data_time: 0.0380 memory: 33630 grad_norm: 4.0482 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2988 loss: 1.2988 2022/10/15 01:57:41 - mmengine - INFO - Epoch(train) [44][620/940] lr: 1.0000e-03 eta: 8:40:13 time: 0.5845 data_time: 0.0354 memory: 33630 grad_norm: 4.0812 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3584 loss: 1.3584 2022/10/15 01:57:52 - mmengine - INFO - Epoch(train) [44][640/940] lr: 1.0000e-03 eta: 8:40:01 time: 0.5684 data_time: 0.0383 memory: 33630 grad_norm: 4.0189 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2475 loss: 1.2475 2022/10/15 01:58:04 - mmengine - INFO - Epoch(train) [44][660/940] lr: 1.0000e-03 eta: 8:39:49 time: 0.5862 data_time: 0.0336 memory: 33630 grad_norm: 4.0835 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2750 loss: 1.2750 2022/10/15 01:58:16 - mmengine - INFO - Epoch(train) [44][680/940] lr: 1.0000e-03 eta: 8:39:37 time: 0.5868 data_time: 0.0392 memory: 33630 grad_norm: 3.9965 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3896 loss: 1.3896 2022/10/15 01:58:27 - mmengine - INFO - Epoch(train) [44][700/940] lr: 1.0000e-03 eta: 8:39:25 time: 0.5783 data_time: 0.0322 memory: 33630 grad_norm: 4.2011 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3508 loss: 1.3508 2022/10/15 01:58:39 - mmengine - INFO - Epoch(train) [44][720/940] lr: 1.0000e-03 eta: 8:39:13 time: 0.5761 data_time: 0.0320 memory: 33630 grad_norm: 4.1150 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3233 loss: 1.3233 2022/10/15 01:58:51 - mmengine - INFO - Epoch(train) [44][740/940] lr: 1.0000e-03 eta: 8:39:01 time: 0.5752 data_time: 0.0335 memory: 33630 grad_norm: 4.1750 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5052 loss: 1.5052 2022/10/15 01:59:02 - mmengine - INFO - Epoch(train) [44][760/940] lr: 1.0000e-03 eta: 8:38:49 time: 0.5881 data_time: 0.0342 memory: 33630 grad_norm: 4.1179 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2423 loss: 1.2423 2022/10/15 01:59:14 - mmengine - INFO - Epoch(train) [44][780/940] lr: 1.0000e-03 eta: 8:38:37 time: 0.5860 data_time: 0.0356 memory: 33630 grad_norm: 4.1404 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4448 loss: 1.4448 2022/10/15 01:59:26 - mmengine - INFO - Epoch(train) [44][800/940] lr: 1.0000e-03 eta: 8:38:25 time: 0.5823 data_time: 0.0454 memory: 33630 grad_norm: 4.0261 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2678 loss: 1.2678 2022/10/15 01:59:37 - mmengine - INFO - Epoch(train) [44][820/940] lr: 1.0000e-03 eta: 8:38:13 time: 0.5803 data_time: 0.0340 memory: 33630 grad_norm: 3.9492 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2745 loss: 1.2745 2022/10/15 01:59:49 - mmengine - INFO - Epoch(train) [44][840/940] lr: 1.0000e-03 eta: 8:38:01 time: 0.5830 data_time: 0.0292 memory: 33630 grad_norm: 4.1479 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3346 loss: 1.3346 2022/10/15 02:00:01 - mmengine - INFO - Epoch(train) [44][860/940] lr: 1.0000e-03 eta: 8:37:49 time: 0.5890 data_time: 0.0392 memory: 33630 grad_norm: 4.0789 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3370 loss: 1.3370 2022/10/15 02:00:12 - mmengine - INFO - Epoch(train) [44][880/940] lr: 1.0000e-03 eta: 8:37:37 time: 0.5803 data_time: 0.0327 memory: 33630 grad_norm: 4.1613 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3918 loss: 1.3918 2022/10/15 02:00:24 - mmengine - INFO - Epoch(train) [44][900/940] lr: 1.0000e-03 eta: 8:37:25 time: 0.5724 data_time: 0.0369 memory: 33630 grad_norm: 4.0855 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3185 loss: 1.3185 2022/10/15 02:00:35 - mmengine - INFO - Epoch(train) [44][920/940] lr: 1.0000e-03 eta: 8:37:13 time: 0.5752 data_time: 0.0359 memory: 33630 grad_norm: 4.1104 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3258 loss: 1.3258 2022/10/15 02:00:46 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 02:00:46 - mmengine - INFO - Epoch(train) [44][940/940] lr: 1.0000e-03 eta: 8:37:00 time: 0.5400 data_time: 0.0281 memory: 33630 grad_norm: 4.2522 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.3333 loss: 1.3333 2022/10/15 02:01:00 - mmengine - INFO - Epoch(val) [44][20/78] eta: 0:00:41 time: 0.7081 data_time: 0.5398 memory: 5967 2022/10/15 02:01:10 - mmengine - INFO - Epoch(val) [44][40/78] eta: 0:00:18 time: 0.4994 data_time: 0.3303 memory: 5967 2022/10/15 02:01:24 - mmengine - INFO - Epoch(val) [44][60/78] eta: 0:00:12 time: 0.6747 data_time: 0.5073 memory: 5967 2022/10/15 02:01:36 - mmengine - INFO - Epoch(val) [44][78/78] acc/top1: 0.6817 acc/top5: 0.8769 acc/mean1: 0.6816 2022/10/15 02:01:36 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_43.pth is removed 2022/10/15 02:01:36 - mmengine - INFO - The best checkpoint with 0.6817 acc/top1 at 44 epoch is saved to best_acc/top1_epoch_44.pth. 2022/10/15 02:01:52 - mmengine - INFO - Epoch(train) [45][20/940] lr: 1.0000e-03 eta: 8:36:53 time: 0.7992 data_time: 0.2327 memory: 33630 grad_norm: 4.0793 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3438 loss: 1.3438 2022/10/15 02:02:04 - mmengine - INFO - Epoch(train) [45][40/940] lr: 1.0000e-03 eta: 8:36:42 time: 0.5943 data_time: 0.0307 memory: 33630 grad_norm: 4.0193 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3437 loss: 1.3437 2022/10/15 02:02:16 - mmengine - INFO - Epoch(train) [45][60/940] lr: 1.0000e-03 eta: 8:36:30 time: 0.5845 data_time: 0.0382 memory: 33630 grad_norm: 4.0431 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.4232 loss: 1.4232 2022/10/15 02:02:28 - mmengine - INFO - Epoch(train) [45][80/940] lr: 1.0000e-03 eta: 8:36:18 time: 0.5784 data_time: 0.0356 memory: 33630 grad_norm: 4.0959 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2566 loss: 1.2566 2022/10/15 02:02:40 - mmengine - INFO - Epoch(train) [45][100/940] lr: 1.0000e-03 eta: 8:36:07 time: 0.6468 data_time: 0.0997 memory: 33630 grad_norm: 4.0648 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4068 loss: 1.4068 2022/10/15 02:02:52 - mmengine - INFO - Epoch(train) [45][120/940] lr: 1.0000e-03 eta: 8:35:56 time: 0.5938 data_time: 0.0532 memory: 33630 grad_norm: 4.1186 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4233 loss: 1.4233 2022/10/15 02:03:04 - mmengine - INFO - Epoch(train) [45][140/940] lr: 1.0000e-03 eta: 8:35:44 time: 0.5899 data_time: 0.0455 memory: 33630 grad_norm: 4.0251 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3402 loss: 1.3402 2022/10/15 02:03:16 - mmengine - INFO - Epoch(train) [45][160/940] lr: 1.0000e-03 eta: 8:35:32 time: 0.5937 data_time: 0.0317 memory: 33630 grad_norm: 4.0788 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.3572 loss: 1.3572 2022/10/15 02:03:27 - mmengine - INFO - Epoch(train) [45][180/940] lr: 1.0000e-03 eta: 8:35:20 time: 0.5723 data_time: 0.0368 memory: 33630 grad_norm: 4.0597 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3371 loss: 1.3371 2022/10/15 02:03:39 - mmengine - INFO - Epoch(train) [45][200/940] lr: 1.0000e-03 eta: 8:35:08 time: 0.5829 data_time: 0.0322 memory: 33630 grad_norm: 4.1012 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3339 loss: 1.3339 2022/10/15 02:03:51 - mmengine - INFO - Epoch(train) [45][220/940] lr: 1.0000e-03 eta: 8:34:57 time: 0.5957 data_time: 0.0355 memory: 33630 grad_norm: 4.1028 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2894 loss: 1.2894 2022/10/15 02:04:03 - mmengine - INFO - Epoch(train) [45][240/940] lr: 1.0000e-03 eta: 8:34:44 time: 0.5779 data_time: 0.0319 memory: 33630 grad_norm: 4.0929 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4137 loss: 1.4137 2022/10/15 02:04:14 - mmengine - INFO - Epoch(train) [45][260/940] lr: 1.0000e-03 eta: 8:34:32 time: 0.5764 data_time: 0.0364 memory: 33630 grad_norm: 4.1374 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.4389 loss: 1.4389 2022/10/15 02:04:26 - mmengine - INFO - Epoch(train) [45][280/940] lr: 1.0000e-03 eta: 8:34:21 time: 0.5908 data_time: 0.0371 memory: 33630 grad_norm: 4.0549 top1_acc: 0.6875 top5_acc: 0.7188 loss_cls: 1.4348 loss: 1.4348 2022/10/15 02:04:37 - mmengine - INFO - Epoch(train) [45][300/940] lr: 1.0000e-03 eta: 8:34:08 time: 0.5730 data_time: 0.0358 memory: 33630 grad_norm: 4.1777 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4492 loss: 1.4492 2022/10/15 02:04:49 - mmengine - INFO - Epoch(train) [45][320/940] lr: 1.0000e-03 eta: 8:33:56 time: 0.5819 data_time: 0.0338 memory: 33630 grad_norm: 4.0783 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3206 loss: 1.3206 2022/10/15 02:05:01 - mmengine - INFO - Epoch(train) [45][340/940] lr: 1.0000e-03 eta: 8:33:44 time: 0.5745 data_time: 0.0350 memory: 33630 grad_norm: 4.2337 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3493 loss: 1.3493 2022/10/15 02:05:12 - mmengine - INFO - Epoch(train) [45][360/940] lr: 1.0000e-03 eta: 8:33:32 time: 0.5833 data_time: 0.0346 memory: 33630 grad_norm: 4.1503 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3260 loss: 1.3260 2022/10/15 02:05:24 - mmengine - INFO - Epoch(train) [45][380/940] lr: 1.0000e-03 eta: 8:33:20 time: 0.5892 data_time: 0.0436 memory: 33630 grad_norm: 4.1525 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4264 loss: 1.4264 2022/10/15 02:05:36 - mmengine - INFO - Epoch(train) [45][400/940] lr: 1.0000e-03 eta: 8:33:09 time: 0.5891 data_time: 0.0308 memory: 33630 grad_norm: 4.0025 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2726 loss: 1.2726 2022/10/15 02:05:47 - mmengine - INFO - Epoch(train) [45][420/940] lr: 1.0000e-03 eta: 8:32:57 time: 0.5812 data_time: 0.0349 memory: 33630 grad_norm: 4.0535 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3972 loss: 1.3972 2022/10/15 02:05:59 - mmengine - INFO - Epoch(train) [45][440/940] lr: 1.0000e-03 eta: 8:32:45 time: 0.5861 data_time: 0.0383 memory: 33630 grad_norm: 4.0464 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2816 loss: 1.2816 2022/10/15 02:06:11 - mmengine - INFO - Epoch(train) [45][460/940] lr: 1.0000e-03 eta: 8:32:33 time: 0.5757 data_time: 0.0393 memory: 33630 grad_norm: 4.1501 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4377 loss: 1.4377 2022/10/15 02:06:22 - mmengine - INFO - Epoch(train) [45][480/940] lr: 1.0000e-03 eta: 8:32:21 time: 0.5793 data_time: 0.0303 memory: 33630 grad_norm: 4.0497 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4130 loss: 1.4130 2022/10/15 02:06:34 - mmengine - INFO - Epoch(train) [45][500/940] lr: 1.0000e-03 eta: 8:32:09 time: 0.5795 data_time: 0.0354 memory: 33630 grad_norm: 4.0794 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1881 loss: 1.1881 2022/10/15 02:06:45 - mmengine - INFO - Epoch(train) [45][520/940] lr: 1.0000e-03 eta: 8:31:56 time: 0.5726 data_time: 0.0369 memory: 33630 grad_norm: 4.1769 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3635 loss: 1.3635 2022/10/15 02:06:57 - mmengine - INFO - Epoch(train) [45][540/940] lr: 1.0000e-03 eta: 8:31:44 time: 0.5814 data_time: 0.0314 memory: 33630 grad_norm: 4.0918 top1_acc: 0.3750 top5_acc: 0.7812 loss_cls: 1.2954 loss: 1.2954 2022/10/15 02:07:08 - mmengine - INFO - Epoch(train) [45][560/940] lr: 1.0000e-03 eta: 8:31:32 time: 0.5659 data_time: 0.0376 memory: 33630 grad_norm: 4.1421 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4151 loss: 1.4151 2022/10/15 02:07:20 - mmengine - INFO - Epoch(train) [45][580/940] lr: 1.0000e-03 eta: 8:31:20 time: 0.5797 data_time: 0.0341 memory: 33630 grad_norm: 4.1894 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3739 loss: 1.3739 2022/10/15 02:07:32 - mmengine - INFO - Epoch(train) [45][600/940] lr: 1.0000e-03 eta: 8:31:08 time: 0.5952 data_time: 0.0389 memory: 33630 grad_norm: 4.0160 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2956 loss: 1.2956 2022/10/15 02:07:43 - mmengine - INFO - Epoch(train) [45][620/940] lr: 1.0000e-03 eta: 8:30:56 time: 0.5770 data_time: 0.0315 memory: 33630 grad_norm: 4.0308 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3975 loss: 1.3975 2022/10/15 02:07:55 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 02:07:55 - mmengine - INFO - Epoch(train) [45][640/940] lr: 1.0000e-03 eta: 8:30:45 time: 0.5991 data_time: 0.0356 memory: 33630 grad_norm: 4.0927 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2928 loss: 1.2928 2022/10/15 02:08:07 - mmengine - INFO - Epoch(train) [45][660/940] lr: 1.0000e-03 eta: 8:30:33 time: 0.5809 data_time: 0.0382 memory: 33630 grad_norm: 4.0118 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1858 loss: 1.1858 2022/10/15 02:08:18 - mmengine - INFO - Epoch(train) [45][680/940] lr: 1.0000e-03 eta: 8:30:21 time: 0.5716 data_time: 0.0346 memory: 33630 grad_norm: 4.0973 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2779 loss: 1.2779 2022/10/15 02:08:30 - mmengine - INFO - Epoch(train) [45][700/940] lr: 1.0000e-03 eta: 8:30:09 time: 0.5892 data_time: 0.0341 memory: 33630 grad_norm: 4.0725 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2702 loss: 1.2702 2022/10/15 02:08:42 - mmengine - INFO - Epoch(train) [45][720/940] lr: 1.0000e-03 eta: 8:29:57 time: 0.5747 data_time: 0.0323 memory: 33630 grad_norm: 4.0995 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2150 loss: 1.2150 2022/10/15 02:08:53 - mmengine - INFO - Epoch(train) [45][740/940] lr: 1.0000e-03 eta: 8:29:45 time: 0.5948 data_time: 0.0304 memory: 33630 grad_norm: 4.1335 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2532 loss: 1.2532 2022/10/15 02:09:05 - mmengine - INFO - Epoch(train) [45][760/940] lr: 1.0000e-03 eta: 8:29:33 time: 0.5804 data_time: 0.0385 memory: 33630 grad_norm: 4.1129 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2517 loss: 1.2517 2022/10/15 02:09:17 - mmengine - INFO - Epoch(train) [45][780/940] lr: 1.0000e-03 eta: 8:29:21 time: 0.5853 data_time: 0.0366 memory: 33630 grad_norm: 4.2068 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3460 loss: 1.3460 2022/10/15 02:09:28 - mmengine - INFO - Epoch(train) [45][800/940] lr: 1.0000e-03 eta: 8:29:09 time: 0.5858 data_time: 0.0361 memory: 33630 grad_norm: 4.1543 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3795 loss: 1.3795 2022/10/15 02:09:40 - mmengine - INFO - Epoch(train) [45][820/940] lr: 1.0000e-03 eta: 8:28:57 time: 0.5778 data_time: 0.0326 memory: 33630 grad_norm: 4.1384 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2898 loss: 1.2898 2022/10/15 02:09:52 - mmengine - INFO - Epoch(train) [45][840/940] lr: 1.0000e-03 eta: 8:28:45 time: 0.5881 data_time: 0.0345 memory: 33630 grad_norm: 4.2128 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3720 loss: 1.3720 2022/10/15 02:10:04 - mmengine - INFO - Epoch(train) [45][860/940] lr: 1.0000e-03 eta: 8:28:34 time: 0.5902 data_time: 0.0310 memory: 33630 grad_norm: 4.0577 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4233 loss: 1.4233 2022/10/15 02:10:15 - mmengine - INFO - Epoch(train) [45][880/940] lr: 1.0000e-03 eta: 8:28:22 time: 0.5806 data_time: 0.0324 memory: 33630 grad_norm: 4.1481 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4361 loss: 1.4361 2022/10/15 02:10:27 - mmengine - INFO - Epoch(train) [45][900/940] lr: 1.0000e-03 eta: 8:28:09 time: 0.5750 data_time: 0.0332 memory: 33630 grad_norm: 4.0569 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3762 loss: 1.3762 2022/10/15 02:10:39 - mmengine - INFO - Epoch(train) [45][920/940] lr: 1.0000e-03 eta: 8:27:58 time: 0.5904 data_time: 0.0417 memory: 33630 grad_norm: 4.2027 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2938 loss: 1.2938 2022/10/15 02:10:49 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 02:10:49 - mmengine - INFO - Epoch(train) [45][940/940] lr: 1.0000e-03 eta: 8:27:45 time: 0.5356 data_time: 0.0320 memory: 33630 grad_norm: 4.3114 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.2315 loss: 1.2315 2022/10/15 02:10:49 - mmengine - INFO - Saving checkpoint at 45 epochs 2022/10/15 02:11:04 - mmengine - INFO - Epoch(val) [45][20/78] eta: 0:00:40 time: 0.6992 data_time: 0.5285 memory: 5967 2022/10/15 02:11:14 - mmengine - INFO - Epoch(val) [45][40/78] eta: 0:00:19 time: 0.5125 data_time: 0.3450 memory: 5967 2022/10/15 02:11:28 - mmengine - INFO - Epoch(val) [45][60/78] eta: 0:00:11 time: 0.6610 data_time: 0.4932 memory: 5967 2022/10/15 02:11:39 - mmengine - INFO - Epoch(val) [45][78/78] acc/top1: 0.6812 acc/top5: 0.8778 acc/mean1: 0.6811 2022/10/15 02:11:56 - mmengine - INFO - Epoch(train) [46][20/940] lr: 1.0000e-03 eta: 8:27:38 time: 0.8086 data_time: 0.2391 memory: 33630 grad_norm: 4.0678 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3024 loss: 1.3024 2022/10/15 02:12:08 - mmengine - INFO - Epoch(train) [46][40/940] lr: 1.0000e-03 eta: 8:27:27 time: 0.6115 data_time: 0.0321 memory: 33630 grad_norm: 4.0428 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2451 loss: 1.2451 2022/10/15 02:12:20 - mmengine - INFO - Epoch(train) [46][60/940] lr: 1.0000e-03 eta: 8:27:15 time: 0.6039 data_time: 0.0454 memory: 33630 grad_norm: 4.0723 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2447 loss: 1.2447 2022/10/15 02:12:32 - mmengine - INFO - Epoch(train) [46][80/940] lr: 1.0000e-03 eta: 8:27:04 time: 0.5931 data_time: 0.0337 memory: 33630 grad_norm: 4.0495 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2867 loss: 1.2867 2022/10/15 02:12:44 - mmengine - INFO - Epoch(train) [46][100/940] lr: 1.0000e-03 eta: 8:26:52 time: 0.5881 data_time: 0.0350 memory: 33630 grad_norm: 4.1825 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3094 loss: 1.3094 2022/10/15 02:12:55 - mmengine - INFO - Epoch(train) [46][120/940] lr: 1.0000e-03 eta: 8:26:40 time: 0.5777 data_time: 0.0306 memory: 33630 grad_norm: 4.1084 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2322 loss: 1.2322 2022/10/15 02:13:07 - mmengine - INFO - Epoch(train) [46][140/940] lr: 1.0000e-03 eta: 8:26:28 time: 0.5861 data_time: 0.0320 memory: 33630 grad_norm: 4.2326 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3725 loss: 1.3725 2022/10/15 02:13:19 - mmengine - INFO - Epoch(train) [46][160/940] lr: 1.0000e-03 eta: 8:26:16 time: 0.5857 data_time: 0.0417 memory: 33630 grad_norm: 4.1431 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3348 loss: 1.3348 2022/10/15 02:13:31 - mmengine - INFO - Epoch(train) [46][180/940] lr: 1.0000e-03 eta: 8:26:04 time: 0.5957 data_time: 0.0304 memory: 33630 grad_norm: 4.1015 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2801 loss: 1.2801 2022/10/15 02:13:42 - mmengine - INFO - Epoch(train) [46][200/940] lr: 1.0000e-03 eta: 8:25:53 time: 0.5866 data_time: 0.0312 memory: 33630 grad_norm: 4.0879 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4240 loss: 1.4240 2022/10/15 02:13:54 - mmengine - INFO - Epoch(train) [46][220/940] lr: 1.0000e-03 eta: 8:25:40 time: 0.5739 data_time: 0.0378 memory: 33630 grad_norm: 4.2540 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4018 loss: 1.4018 2022/10/15 02:14:06 - mmengine - INFO - Epoch(train) [46][240/940] lr: 1.0000e-03 eta: 8:25:29 time: 0.5898 data_time: 0.0438 memory: 33630 grad_norm: 4.0867 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2757 loss: 1.2757 2022/10/15 02:14:17 - mmengine - INFO - Epoch(train) [46][260/940] lr: 1.0000e-03 eta: 8:25:17 time: 0.5841 data_time: 0.0314 memory: 33630 grad_norm: 4.0783 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2375 loss: 1.2375 2022/10/15 02:14:29 - mmengine - INFO - Epoch(train) [46][280/940] lr: 1.0000e-03 eta: 8:25:05 time: 0.5869 data_time: 0.0391 memory: 33630 grad_norm: 4.1162 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3239 loss: 1.3239 2022/10/15 02:14:40 - mmengine - INFO - Epoch(train) [46][300/940] lr: 1.0000e-03 eta: 8:24:53 time: 0.5706 data_time: 0.0361 memory: 33630 grad_norm: 4.0742 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2531 loss: 1.2531 2022/10/15 02:14:52 - mmengine - INFO - Epoch(train) [46][320/940] lr: 1.0000e-03 eta: 8:24:41 time: 0.5826 data_time: 0.0385 memory: 33630 grad_norm: 4.1166 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.3406 loss: 1.3406 2022/10/15 02:15:04 - mmengine - INFO - Epoch(train) [46][340/940] lr: 1.0000e-03 eta: 8:24:29 time: 0.5788 data_time: 0.0364 memory: 33630 grad_norm: 4.1562 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3091 loss: 1.3091 2022/10/15 02:15:16 - mmengine - INFO - Epoch(train) [46][360/940] lr: 1.0000e-03 eta: 8:24:17 time: 0.5972 data_time: 0.0413 memory: 33630 grad_norm: 4.1628 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4530 loss: 1.4530 2022/10/15 02:15:27 - mmengine - INFO - Epoch(train) [46][380/940] lr: 1.0000e-03 eta: 8:24:05 time: 0.5784 data_time: 0.0353 memory: 33630 grad_norm: 4.0864 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3480 loss: 1.3480 2022/10/15 02:15:39 - mmengine - INFO - Epoch(train) [46][400/940] lr: 1.0000e-03 eta: 8:23:53 time: 0.5829 data_time: 0.0333 memory: 33630 grad_norm: 4.2202 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3428 loss: 1.3428 2022/10/15 02:15:50 - mmengine - INFO - Epoch(train) [46][420/940] lr: 1.0000e-03 eta: 8:23:41 time: 0.5800 data_time: 0.0330 memory: 33630 grad_norm: 4.0748 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1980 loss: 1.1980 2022/10/15 02:16:02 - mmengine - INFO - Epoch(train) [46][440/940] lr: 1.0000e-03 eta: 8:23:29 time: 0.5894 data_time: 0.0361 memory: 33630 grad_norm: 4.1690 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3688 loss: 1.3688 2022/10/15 02:16:14 - mmengine - INFO - Epoch(train) [46][460/940] lr: 1.0000e-03 eta: 8:23:18 time: 0.5904 data_time: 0.0323 memory: 33630 grad_norm: 4.1476 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2194 loss: 1.2194 2022/10/15 02:16:26 - mmengine - INFO - Epoch(train) [46][480/940] lr: 1.0000e-03 eta: 8:23:06 time: 0.5976 data_time: 0.0363 memory: 33630 grad_norm: 4.2026 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3641 loss: 1.3641 2022/10/15 02:16:38 - mmengine - INFO - Epoch(train) [46][500/940] lr: 1.0000e-03 eta: 8:22:54 time: 0.5861 data_time: 0.0324 memory: 33630 grad_norm: 4.1995 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3353 loss: 1.3353 2022/10/15 02:16:49 - mmengine - INFO - Epoch(train) [46][520/940] lr: 1.0000e-03 eta: 8:22:42 time: 0.5868 data_time: 0.0374 memory: 33630 grad_norm: 4.1671 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3780 loss: 1.3780 2022/10/15 02:17:01 - mmengine - INFO - Epoch(train) [46][540/940] lr: 1.0000e-03 eta: 8:22:30 time: 0.5850 data_time: 0.0429 memory: 33630 grad_norm: 3.9744 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2220 loss: 1.2220 2022/10/15 02:17:13 - mmengine - INFO - Epoch(train) [46][560/940] lr: 1.0000e-03 eta: 8:22:18 time: 0.5806 data_time: 0.0390 memory: 33630 grad_norm: 4.1008 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3155 loss: 1.3155 2022/10/15 02:17:24 - mmengine - INFO - Epoch(train) [46][580/940] lr: 1.0000e-03 eta: 8:22:06 time: 0.5793 data_time: 0.0412 memory: 33630 grad_norm: 4.1333 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2506 loss: 1.2506 2022/10/15 02:17:36 - mmengine - INFO - Epoch(train) [46][600/940] lr: 1.0000e-03 eta: 8:21:54 time: 0.5862 data_time: 0.0432 memory: 33630 grad_norm: 4.2204 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4129 loss: 1.4129 2022/10/15 02:17:47 - mmengine - INFO - Epoch(train) [46][620/940] lr: 1.0000e-03 eta: 8:21:42 time: 0.5706 data_time: 0.0393 memory: 33630 grad_norm: 4.0885 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2584 loss: 1.2584 2022/10/15 02:17:59 - mmengine - INFO - Epoch(train) [46][640/940] lr: 1.0000e-03 eta: 8:21:30 time: 0.5867 data_time: 0.0349 memory: 33630 grad_norm: 4.1545 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3109 loss: 1.3109 2022/10/15 02:18:11 - mmengine - INFO - Epoch(train) [46][660/940] lr: 1.0000e-03 eta: 8:21:18 time: 0.5811 data_time: 0.0297 memory: 33630 grad_norm: 4.1747 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2488 loss: 1.2488 2022/10/15 02:18:23 - mmengine - INFO - Epoch(train) [46][680/940] lr: 1.0000e-03 eta: 8:21:07 time: 0.5937 data_time: 0.0417 memory: 33630 grad_norm: 4.1360 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1071 loss: 1.1071 2022/10/15 02:18:34 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 02:18:34 - mmengine - INFO - Epoch(train) [46][700/940] lr: 1.0000e-03 eta: 8:20:55 time: 0.5837 data_time: 0.0393 memory: 33630 grad_norm: 4.1445 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2853 loss: 1.2853 2022/10/15 02:18:46 - mmengine - INFO - Epoch(train) [46][720/940] lr: 1.0000e-03 eta: 8:20:43 time: 0.5793 data_time: 0.0320 memory: 33630 grad_norm: 4.0868 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2951 loss: 1.2951 2022/10/15 02:18:58 - mmengine - INFO - Epoch(train) [46][740/940] lr: 1.0000e-03 eta: 8:20:31 time: 0.5987 data_time: 0.0318 memory: 33630 grad_norm: 4.1634 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.3462 loss: 1.3462 2022/10/15 02:19:10 - mmengine - INFO - Epoch(train) [46][760/940] lr: 1.0000e-03 eta: 8:20:19 time: 0.5832 data_time: 0.0311 memory: 33630 grad_norm: 4.1145 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.4143 loss: 1.4143 2022/10/15 02:19:21 - mmengine - INFO - Epoch(train) [46][780/940] lr: 1.0000e-03 eta: 8:20:07 time: 0.5847 data_time: 0.0383 memory: 33630 grad_norm: 4.0551 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1425 loss: 1.1425 2022/10/15 02:19:33 - mmengine - INFO - Epoch(train) [46][800/940] lr: 1.0000e-03 eta: 8:19:56 time: 0.5929 data_time: 0.0348 memory: 33630 grad_norm: 4.1117 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2541 loss: 1.2541 2022/10/15 02:19:45 - mmengine - INFO - Epoch(train) [46][820/940] lr: 1.0000e-03 eta: 8:19:43 time: 0.5720 data_time: 0.0430 memory: 33630 grad_norm: 4.2041 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3436 loss: 1.3436 2022/10/15 02:19:56 - mmengine - INFO - Epoch(train) [46][840/940] lr: 1.0000e-03 eta: 8:19:32 time: 0.5956 data_time: 0.0358 memory: 33630 grad_norm: 4.1897 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4895 loss: 1.4895 2022/10/15 02:20:08 - mmengine - INFO - Epoch(train) [46][860/940] lr: 1.0000e-03 eta: 8:19:20 time: 0.5817 data_time: 0.0354 memory: 33630 grad_norm: 4.2119 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4799 loss: 1.4799 2022/10/15 02:20:20 - mmengine - INFO - Epoch(train) [46][880/940] lr: 1.0000e-03 eta: 8:19:08 time: 0.5911 data_time: 0.0329 memory: 33630 grad_norm: 4.1604 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.4041 loss: 1.4041 2022/10/15 02:20:32 - mmengine - INFO - Epoch(train) [46][900/940] lr: 1.0000e-03 eta: 8:18:56 time: 0.5890 data_time: 0.0407 memory: 33630 grad_norm: 4.1332 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2349 loss: 1.2349 2022/10/15 02:20:44 - mmengine - INFO - Epoch(train) [46][920/940] lr: 1.0000e-03 eta: 8:18:45 time: 0.5893 data_time: 0.0447 memory: 33630 grad_norm: 4.1398 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3868 loss: 1.3868 2022/10/15 02:20:54 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 02:20:54 - mmengine - INFO - Epoch(train) [46][940/940] lr: 1.0000e-03 eta: 8:18:32 time: 0.5439 data_time: 0.0283 memory: 33630 grad_norm: 4.3617 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.3385 loss: 1.3385 2022/10/15 02:21:09 - mmengine - INFO - Epoch(val) [46][20/78] eta: 0:00:41 time: 0.7151 data_time: 0.5430 memory: 5967 2022/10/15 02:21:19 - mmengine - INFO - Epoch(val) [46][40/78] eta: 0:00:19 time: 0.5013 data_time: 0.3327 memory: 5967 2022/10/15 02:21:33 - mmengine - INFO - Epoch(val) [46][60/78] eta: 0:00:12 time: 0.6996 data_time: 0.5285 memory: 5967 2022/10/15 02:21:44 - mmengine - INFO - Epoch(val) [46][78/78] acc/top1: 0.6828 acc/top5: 0.8755 acc/mean1: 0.6827 2022/10/15 02:21:44 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_44.pth is removed 2022/10/15 02:21:45 - mmengine - INFO - The best checkpoint with 0.6828 acc/top1 at 46 epoch is saved to best_acc/top1_epoch_46.pth. 2022/10/15 02:22:01 - mmengine - INFO - Epoch(train) [47][20/940] lr: 1.0000e-03 eta: 8:18:25 time: 0.8076 data_time: 0.2691 memory: 33630 grad_norm: 4.1530 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2715 loss: 1.2715 2022/10/15 02:22:13 - mmengine - INFO - Epoch(train) [47][40/940] lr: 1.0000e-03 eta: 8:18:14 time: 0.6099 data_time: 0.0705 memory: 33630 grad_norm: 4.1169 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4474 loss: 1.4474 2022/10/15 02:22:25 - mmengine - INFO - Epoch(train) [47][60/940] lr: 1.0000e-03 eta: 8:18:02 time: 0.6018 data_time: 0.0529 memory: 33630 grad_norm: 4.1438 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4445 loss: 1.4445 2022/10/15 02:22:37 - mmengine - INFO - Epoch(train) [47][80/940] lr: 1.0000e-03 eta: 8:17:51 time: 0.5954 data_time: 0.0300 memory: 33630 grad_norm: 4.1255 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3798 loss: 1.3798 2022/10/15 02:22:49 - mmengine - INFO - Epoch(train) [47][100/940] lr: 1.0000e-03 eta: 8:17:39 time: 0.5971 data_time: 0.0420 memory: 33630 grad_norm: 4.1226 top1_acc: 0.5625 top5_acc: 0.9688 loss_cls: 1.2364 loss: 1.2364 2022/10/15 02:23:01 - mmengine - INFO - Epoch(train) [47][120/940] lr: 1.0000e-03 eta: 8:17:27 time: 0.5731 data_time: 0.0309 memory: 33630 grad_norm: 4.0748 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4300 loss: 1.4300 2022/10/15 02:23:12 - mmengine - INFO - Epoch(train) [47][140/940] lr: 1.0000e-03 eta: 8:17:15 time: 0.5877 data_time: 0.0358 memory: 33630 grad_norm: 4.0859 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2834 loss: 1.2834 2022/10/15 02:23:24 - mmengine - INFO - Epoch(train) [47][160/940] lr: 1.0000e-03 eta: 8:17:03 time: 0.5766 data_time: 0.0384 memory: 33630 grad_norm: 4.1551 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3627 loss: 1.3627 2022/10/15 02:23:35 - mmengine - INFO - Epoch(train) [47][180/940] lr: 1.0000e-03 eta: 8:16:51 time: 0.5754 data_time: 0.0301 memory: 33630 grad_norm: 4.1955 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3550 loss: 1.3550 2022/10/15 02:23:47 - mmengine - INFO - Epoch(train) [47][200/940] lr: 1.0000e-03 eta: 8:16:39 time: 0.5889 data_time: 0.0373 memory: 33630 grad_norm: 4.1616 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2236 loss: 1.2236 2022/10/15 02:23:59 - mmengine - INFO - Epoch(train) [47][220/940] lr: 1.0000e-03 eta: 8:16:27 time: 0.5834 data_time: 0.0341 memory: 33630 grad_norm: 4.2450 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.3442 loss: 1.3442 2022/10/15 02:24:11 - mmengine - INFO - Epoch(train) [47][240/940] lr: 1.0000e-03 eta: 8:16:15 time: 0.5815 data_time: 0.0367 memory: 33630 grad_norm: 4.1331 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3231 loss: 1.3231 2022/10/15 02:24:22 - mmengine - INFO - Epoch(train) [47][260/940] lr: 1.0000e-03 eta: 8:16:03 time: 0.5744 data_time: 0.0297 memory: 33630 grad_norm: 4.2228 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3355 loss: 1.3355 2022/10/15 02:24:34 - mmengine - INFO - Epoch(train) [47][280/940] lr: 1.0000e-03 eta: 8:15:51 time: 0.5889 data_time: 0.0447 memory: 33630 grad_norm: 4.1900 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3030 loss: 1.3030 2022/10/15 02:24:45 - mmengine - INFO - Epoch(train) [47][300/940] lr: 1.0000e-03 eta: 8:15:39 time: 0.5792 data_time: 0.0312 memory: 33630 grad_norm: 4.1519 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2407 loss: 1.2407 2022/10/15 02:24:57 - mmengine - INFO - Epoch(train) [47][320/940] lr: 1.0000e-03 eta: 8:15:27 time: 0.5872 data_time: 0.0360 memory: 33630 grad_norm: 4.2036 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3725 loss: 1.3725 2022/10/15 02:25:09 - mmengine - INFO - Epoch(train) [47][340/940] lr: 1.0000e-03 eta: 8:15:15 time: 0.5786 data_time: 0.0396 memory: 33630 grad_norm: 4.1965 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.5133 loss: 1.5133 2022/10/15 02:25:20 - mmengine - INFO - Epoch(train) [47][360/940] lr: 1.0000e-03 eta: 8:15:03 time: 0.5863 data_time: 0.0407 memory: 33630 grad_norm: 4.0926 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3940 loss: 1.3940 2022/10/15 02:25:32 - mmengine - INFO - Epoch(train) [47][380/940] lr: 1.0000e-03 eta: 8:14:52 time: 0.5897 data_time: 0.0365 memory: 33630 grad_norm: 4.1668 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2973 loss: 1.2973 2022/10/15 02:25:44 - mmengine - INFO - Epoch(train) [47][400/940] lr: 1.0000e-03 eta: 8:14:40 time: 0.5807 data_time: 0.0371 memory: 33630 grad_norm: 4.0714 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3164 loss: 1.3164 2022/10/15 02:25:55 - mmengine - INFO - Epoch(train) [47][420/940] lr: 1.0000e-03 eta: 8:14:27 time: 0.5720 data_time: 0.0310 memory: 33630 grad_norm: 4.2866 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4985 loss: 1.4985 2022/10/15 02:26:07 - mmengine - INFO - Epoch(train) [47][440/940] lr: 1.0000e-03 eta: 8:14:16 time: 0.5920 data_time: 0.0348 memory: 33630 grad_norm: 4.1470 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2786 loss: 1.2786 2022/10/15 02:26:19 - mmengine - INFO - Epoch(train) [47][460/940] lr: 1.0000e-03 eta: 8:14:04 time: 0.5884 data_time: 0.0357 memory: 33630 grad_norm: 4.0554 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3629 loss: 1.3629 2022/10/15 02:26:30 - mmengine - INFO - Epoch(train) [47][480/940] lr: 1.0000e-03 eta: 8:13:52 time: 0.5755 data_time: 0.0347 memory: 33630 grad_norm: 4.1866 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2563 loss: 1.2563 2022/10/15 02:26:42 - mmengine - INFO - Epoch(train) [47][500/940] lr: 1.0000e-03 eta: 8:13:40 time: 0.5864 data_time: 0.0339 memory: 33630 grad_norm: 4.1787 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2823 loss: 1.2823 2022/10/15 02:26:54 - mmengine - INFO - Epoch(train) [47][520/940] lr: 1.0000e-03 eta: 8:13:28 time: 0.5812 data_time: 0.0306 memory: 33630 grad_norm: 4.2155 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2652 loss: 1.2652 2022/10/15 02:27:05 - mmengine - INFO - Epoch(train) [47][540/940] lr: 1.0000e-03 eta: 8:13:16 time: 0.5800 data_time: 0.0419 memory: 33630 grad_norm: 4.1678 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2926 loss: 1.2926 2022/10/15 02:27:17 - mmengine - INFO - Epoch(train) [47][560/940] lr: 1.0000e-03 eta: 8:13:04 time: 0.5851 data_time: 0.0423 memory: 33630 grad_norm: 4.2525 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3071 loss: 1.3071 2022/10/15 02:27:29 - mmengine - INFO - Epoch(train) [47][580/940] lr: 1.0000e-03 eta: 8:12:52 time: 0.5941 data_time: 0.0315 memory: 33630 grad_norm: 4.0599 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3109 loss: 1.3109 2022/10/15 02:27:41 - mmengine - INFO - Epoch(train) [47][600/940] lr: 1.0000e-03 eta: 8:12:41 time: 0.5878 data_time: 0.0410 memory: 33630 grad_norm: 4.0466 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2121 loss: 1.2121 2022/10/15 02:27:53 - mmengine - INFO - Epoch(train) [47][620/940] lr: 1.0000e-03 eta: 8:12:29 time: 0.5886 data_time: 0.0332 memory: 33630 grad_norm: 4.1240 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2881 loss: 1.2881 2022/10/15 02:28:04 - mmengine - INFO - Epoch(train) [47][640/940] lr: 1.0000e-03 eta: 8:12:17 time: 0.5789 data_time: 0.0368 memory: 33630 grad_norm: 4.2600 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2698 loss: 1.2698 2022/10/15 02:28:16 - mmengine - INFO - Epoch(train) [47][660/940] lr: 1.0000e-03 eta: 8:12:05 time: 0.5858 data_time: 0.0314 memory: 33630 grad_norm: 4.1824 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2370 loss: 1.2370 2022/10/15 02:28:27 - mmengine - INFO - Epoch(train) [47][680/940] lr: 1.0000e-03 eta: 8:11:53 time: 0.5836 data_time: 0.0326 memory: 33630 grad_norm: 4.1499 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.4731 loss: 1.4731 2022/10/15 02:28:39 - mmengine - INFO - Epoch(train) [47][700/940] lr: 1.0000e-03 eta: 8:11:41 time: 0.5928 data_time: 0.0381 memory: 33630 grad_norm: 4.1986 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.3046 loss: 1.3046 2022/10/15 02:28:51 - mmengine - INFO - Epoch(train) [47][720/940] lr: 1.0000e-03 eta: 8:11:29 time: 0.5819 data_time: 0.0326 memory: 33630 grad_norm: 4.1616 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3827 loss: 1.3827 2022/10/15 02:29:02 - mmengine - INFO - Epoch(train) [47][740/940] lr: 1.0000e-03 eta: 8:11:17 time: 0.5715 data_time: 0.0327 memory: 33630 grad_norm: 4.2508 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2916 loss: 1.2916 2022/10/15 02:29:14 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 02:29:14 - mmengine - INFO - Epoch(train) [47][760/940] lr: 1.0000e-03 eta: 8:11:05 time: 0.5682 data_time: 0.0322 memory: 33630 grad_norm: 4.1870 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2934 loss: 1.2934 2022/10/15 02:29:26 - mmengine - INFO - Epoch(train) [47][780/940] lr: 1.0000e-03 eta: 8:10:53 time: 0.5906 data_time: 0.0315 memory: 33630 grad_norm: 4.1244 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2502 loss: 1.2502 2022/10/15 02:29:37 - mmengine - INFO - Epoch(train) [47][800/940] lr: 1.0000e-03 eta: 8:10:41 time: 0.5782 data_time: 0.0431 memory: 33630 grad_norm: 4.1765 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2034 loss: 1.2034 2022/10/15 02:29:49 - mmengine - INFO - Epoch(train) [47][820/940] lr: 1.0000e-03 eta: 8:10:29 time: 0.5905 data_time: 0.0373 memory: 33630 grad_norm: 4.2395 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4925 loss: 1.4925 2022/10/15 02:30:01 - mmengine - INFO - Epoch(train) [47][840/940] lr: 1.0000e-03 eta: 8:10:18 time: 0.5916 data_time: 0.0420 memory: 33630 grad_norm: 4.2214 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4280 loss: 1.4280 2022/10/15 02:30:12 - mmengine - INFO - Epoch(train) [47][860/940] lr: 1.0000e-03 eta: 8:10:06 time: 0.5780 data_time: 0.0357 memory: 33630 grad_norm: 4.2512 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.2623 loss: 1.2623 2022/10/15 02:30:24 - mmengine - INFO - Epoch(train) [47][880/940] lr: 1.0000e-03 eta: 8:09:53 time: 0.5743 data_time: 0.0307 memory: 33630 grad_norm: 4.1310 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2617 loss: 1.2617 2022/10/15 02:30:36 - mmengine - INFO - Epoch(train) [47][900/940] lr: 1.0000e-03 eta: 8:09:42 time: 0.5906 data_time: 0.0316 memory: 33630 grad_norm: 4.2655 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3245 loss: 1.3245 2022/10/15 02:30:47 - mmengine - INFO - Epoch(train) [47][920/940] lr: 1.0000e-03 eta: 8:09:30 time: 0.5795 data_time: 0.0405 memory: 33630 grad_norm: 4.1860 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3702 loss: 1.3702 2022/10/15 02:30:58 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 02:30:58 - mmengine - INFO - Epoch(train) [47][940/940] lr: 1.0000e-03 eta: 8:09:17 time: 0.5434 data_time: 0.0285 memory: 33630 grad_norm: 4.4336 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.4495 loss: 1.4495 2022/10/15 02:31:13 - mmengine - INFO - Epoch(val) [47][20/78] eta: 0:00:42 time: 0.7254 data_time: 0.5543 memory: 5967 2022/10/15 02:31:23 - mmengine - INFO - Epoch(val) [47][40/78] eta: 0:00:18 time: 0.4961 data_time: 0.3269 memory: 5967 2022/10/15 02:31:37 - mmengine - INFO - Epoch(val) [47][60/78] eta: 0:00:12 time: 0.7031 data_time: 0.5335 memory: 5967 2022/10/15 02:31:48 - mmengine - INFO - Epoch(val) [47][78/78] acc/top1: 0.6856 acc/top5: 0.8753 acc/mean1: 0.6855 2022/10/15 02:31:48 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_46.pth is removed 2022/10/15 02:31:48 - mmengine - INFO - The best checkpoint with 0.6856 acc/top1 at 47 epoch is saved to best_acc/top1_epoch_47.pth. 2022/10/15 02:32:05 - mmengine - INFO - Epoch(train) [48][20/940] lr: 1.0000e-03 eta: 8:09:11 time: 0.8542 data_time: 0.2753 memory: 33630 grad_norm: 4.1621 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3331 loss: 1.3331 2022/10/15 02:32:17 - mmengine - INFO - Epoch(train) [48][40/940] lr: 1.0000e-03 eta: 8:08:59 time: 0.5818 data_time: 0.0312 memory: 33630 grad_norm: 4.2188 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2632 loss: 1.2632 2022/10/15 02:32:29 - mmengine - INFO - Epoch(train) [48][60/940] lr: 1.0000e-03 eta: 8:08:47 time: 0.5872 data_time: 0.0396 memory: 33630 grad_norm: 4.2413 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3529 loss: 1.3529 2022/10/15 02:32:40 - mmengine - INFO - Epoch(train) [48][80/940] lr: 1.0000e-03 eta: 8:08:35 time: 0.5856 data_time: 0.0352 memory: 33630 grad_norm: 4.1961 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3680 loss: 1.3680 2022/10/15 02:32:52 - mmengine - INFO - Epoch(train) [48][100/940] lr: 1.0000e-03 eta: 8:08:24 time: 0.5914 data_time: 0.0433 memory: 33630 grad_norm: 4.1623 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3496 loss: 1.3496 2022/10/15 02:33:04 - mmengine - INFO - Epoch(train) [48][120/940] lr: 1.0000e-03 eta: 8:08:12 time: 0.5839 data_time: 0.0309 memory: 33630 grad_norm: 4.1814 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3948 loss: 1.3948 2022/10/15 02:33:15 - mmengine - INFO - Epoch(train) [48][140/940] lr: 1.0000e-03 eta: 8:08:00 time: 0.5749 data_time: 0.0354 memory: 33630 grad_norm: 4.3049 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3693 loss: 1.3693 2022/10/15 02:33:27 - mmengine - INFO - Epoch(train) [48][160/940] lr: 1.0000e-03 eta: 8:07:48 time: 0.5772 data_time: 0.0313 memory: 33630 grad_norm: 4.1626 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2428 loss: 1.2428 2022/10/15 02:33:39 - mmengine - INFO - Epoch(train) [48][180/940] lr: 1.0000e-03 eta: 8:07:36 time: 0.5812 data_time: 0.0365 memory: 33630 grad_norm: 4.1656 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3227 loss: 1.3227 2022/10/15 02:33:50 - mmengine - INFO - Epoch(train) [48][200/940] lr: 1.0000e-03 eta: 8:07:24 time: 0.5858 data_time: 0.0320 memory: 33630 grad_norm: 4.2818 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5079 loss: 1.5079 2022/10/15 02:34:02 - mmengine - INFO - Epoch(train) [48][220/940] lr: 1.0000e-03 eta: 8:07:12 time: 0.5884 data_time: 0.0324 memory: 33630 grad_norm: 4.1275 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3149 loss: 1.3149 2022/10/15 02:34:14 - mmengine - INFO - Epoch(train) [48][240/940] lr: 1.0000e-03 eta: 8:07:00 time: 0.5751 data_time: 0.0424 memory: 33630 grad_norm: 4.2702 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2324 loss: 1.2324 2022/10/15 02:34:25 - mmengine - INFO - Epoch(train) [48][260/940] lr: 1.0000e-03 eta: 8:06:48 time: 0.5814 data_time: 0.0321 memory: 33630 grad_norm: 4.1607 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2903 loss: 1.2903 2022/10/15 02:34:37 - mmengine - INFO - Epoch(train) [48][280/940] lr: 1.0000e-03 eta: 8:06:36 time: 0.5793 data_time: 0.0323 memory: 33630 grad_norm: 4.1708 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3537 loss: 1.3537 2022/10/15 02:34:49 - mmengine - INFO - Epoch(train) [48][300/940] lr: 1.0000e-03 eta: 8:06:24 time: 0.5924 data_time: 0.0400 memory: 33630 grad_norm: 4.2445 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3654 loss: 1.3654 2022/10/15 02:35:00 - mmengine - INFO - Epoch(train) [48][320/940] lr: 1.0000e-03 eta: 8:06:12 time: 0.5905 data_time: 0.0375 memory: 33630 grad_norm: 4.1744 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3228 loss: 1.3228 2022/10/15 02:35:12 - mmengine - INFO - Epoch(train) [48][340/940] lr: 1.0000e-03 eta: 8:06:00 time: 0.5867 data_time: 0.0365 memory: 33630 grad_norm: 4.2222 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.2863 loss: 1.2863 2022/10/15 02:35:24 - mmengine - INFO - Epoch(train) [48][360/940] lr: 1.0000e-03 eta: 8:05:49 time: 0.5918 data_time: 0.0404 memory: 33630 grad_norm: 4.2173 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2984 loss: 1.2984 2022/10/15 02:35:36 - mmengine - INFO - Epoch(train) [48][380/940] lr: 1.0000e-03 eta: 8:05:37 time: 0.5785 data_time: 0.0376 memory: 33630 grad_norm: 4.2034 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3050 loss: 1.3050 2022/10/15 02:35:47 - mmengine - INFO - Epoch(train) [48][400/940] lr: 1.0000e-03 eta: 8:05:25 time: 0.5829 data_time: 0.0381 memory: 33630 grad_norm: 4.1579 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.1973 loss: 1.1973 2022/10/15 02:35:59 - mmengine - INFO - Epoch(train) [48][420/940] lr: 1.0000e-03 eta: 8:05:13 time: 0.5861 data_time: 0.0380 memory: 33630 grad_norm: 4.2799 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2591 loss: 1.2591 2022/10/15 02:36:11 - mmengine - INFO - Epoch(train) [48][440/940] lr: 1.0000e-03 eta: 8:05:01 time: 0.5824 data_time: 0.0411 memory: 33630 grad_norm: 4.1357 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3251 loss: 1.3251 2022/10/15 02:36:22 - mmengine - INFO - Epoch(train) [48][460/940] lr: 1.0000e-03 eta: 8:04:49 time: 0.5829 data_time: 0.0450 memory: 33630 grad_norm: 4.2372 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2778 loss: 1.2778 2022/10/15 02:36:34 - mmengine - INFO - Epoch(train) [48][480/940] lr: 1.0000e-03 eta: 8:04:37 time: 0.5837 data_time: 0.0384 memory: 33630 grad_norm: 4.2706 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3773 loss: 1.3773 2022/10/15 02:36:46 - mmengine - INFO - Epoch(train) [48][500/940] lr: 1.0000e-03 eta: 8:04:25 time: 0.5892 data_time: 0.0395 memory: 33630 grad_norm: 4.2716 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3591 loss: 1.3591 2022/10/15 02:36:57 - mmengine - INFO - Epoch(train) [48][520/940] lr: 1.0000e-03 eta: 8:04:13 time: 0.5821 data_time: 0.0311 memory: 33630 grad_norm: 4.1912 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3455 loss: 1.3455 2022/10/15 02:37:09 - mmengine - INFO - Epoch(train) [48][540/940] lr: 1.0000e-03 eta: 8:04:01 time: 0.5744 data_time: 0.0326 memory: 33630 grad_norm: 4.2019 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2908 loss: 1.2908 2022/10/15 02:37:21 - mmengine - INFO - Epoch(train) [48][560/940] lr: 1.0000e-03 eta: 8:03:49 time: 0.5890 data_time: 0.0380 memory: 33630 grad_norm: 4.2923 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3071 loss: 1.3071 2022/10/15 02:37:33 - mmengine - INFO - Epoch(train) [48][580/940] lr: 1.0000e-03 eta: 8:03:38 time: 0.5960 data_time: 0.0335 memory: 33630 grad_norm: 4.3030 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2420 loss: 1.2420 2022/10/15 02:37:44 - mmengine - INFO - Epoch(train) [48][600/940] lr: 1.0000e-03 eta: 8:03:26 time: 0.5863 data_time: 0.0395 memory: 33630 grad_norm: 4.1985 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2564 loss: 1.2564 2022/10/15 02:37:56 - mmengine - INFO - Epoch(train) [48][620/940] lr: 1.0000e-03 eta: 8:03:14 time: 0.5881 data_time: 0.0360 memory: 33630 grad_norm: 4.1783 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.4639 loss: 1.4639 2022/10/15 02:38:08 - mmengine - INFO - Epoch(train) [48][640/940] lr: 1.0000e-03 eta: 8:03:02 time: 0.5810 data_time: 0.0321 memory: 33630 grad_norm: 4.2088 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2226 loss: 1.2226 2022/10/15 02:38:19 - mmengine - INFO - Epoch(train) [48][660/940] lr: 1.0000e-03 eta: 8:02:50 time: 0.5807 data_time: 0.0349 memory: 33630 grad_norm: 4.1593 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 1.2748 loss: 1.2748 2022/10/15 02:38:31 - mmengine - INFO - Epoch(train) [48][680/940] lr: 1.0000e-03 eta: 8:02:38 time: 0.5775 data_time: 0.0387 memory: 33630 grad_norm: 4.1253 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2760 loss: 1.2760 2022/10/15 02:38:43 - mmengine - INFO - Epoch(train) [48][700/940] lr: 1.0000e-03 eta: 8:02:26 time: 0.5851 data_time: 0.0365 memory: 33630 grad_norm: 4.2958 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.3810 loss: 1.3810 2022/10/15 02:38:54 - mmengine - INFO - Epoch(train) [48][720/940] lr: 1.0000e-03 eta: 8:02:15 time: 0.5928 data_time: 0.0332 memory: 33630 grad_norm: 4.2248 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3362 loss: 1.3362 2022/10/15 02:39:06 - mmengine - INFO - Epoch(train) [48][740/940] lr: 1.0000e-03 eta: 8:02:03 time: 0.5948 data_time: 0.0370 memory: 33630 grad_norm: 4.2079 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.3478 loss: 1.3478 2022/10/15 02:39:18 - mmengine - INFO - Epoch(train) [48][760/940] lr: 1.0000e-03 eta: 8:01:51 time: 0.5689 data_time: 0.0316 memory: 33630 grad_norm: 4.0498 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1147 loss: 1.1147 2022/10/15 02:39:29 - mmengine - INFO - Epoch(train) [48][780/940] lr: 1.0000e-03 eta: 8:01:39 time: 0.5867 data_time: 0.0404 memory: 33630 grad_norm: 4.1695 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2640 loss: 1.2640 2022/10/15 02:39:41 - mmengine - INFO - Epoch(train) [48][800/940] lr: 1.0000e-03 eta: 8:01:27 time: 0.5832 data_time: 0.0378 memory: 33630 grad_norm: 4.1343 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3277 loss: 1.3277 2022/10/15 02:39:53 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 02:39:53 - mmengine - INFO - Epoch(train) [48][820/940] lr: 1.0000e-03 eta: 8:01:15 time: 0.5824 data_time: 0.0440 memory: 33630 grad_norm: 4.1157 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3644 loss: 1.3644 2022/10/15 02:40:05 - mmengine - INFO - Epoch(train) [48][840/940] lr: 1.0000e-03 eta: 8:01:03 time: 0.5901 data_time: 0.0372 memory: 33630 grad_norm: 4.0993 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2693 loss: 1.2693 2022/10/15 02:40:16 - mmengine - INFO - Epoch(train) [48][860/940] lr: 1.0000e-03 eta: 8:00:51 time: 0.5803 data_time: 0.0370 memory: 33630 grad_norm: 4.2687 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3405 loss: 1.3405 2022/10/15 02:40:28 - mmengine - INFO - Epoch(train) [48][880/940] lr: 1.0000e-03 eta: 8:00:39 time: 0.5844 data_time: 0.0390 memory: 33630 grad_norm: 4.2561 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3985 loss: 1.3985 2022/10/15 02:40:39 - mmengine - INFO - Epoch(train) [48][900/940] lr: 1.0000e-03 eta: 8:00:27 time: 0.5753 data_time: 0.0318 memory: 33630 grad_norm: 4.1391 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1912 loss: 1.1912 2022/10/15 02:40:51 - mmengine - INFO - Epoch(train) [48][920/940] lr: 1.0000e-03 eta: 8:00:15 time: 0.5828 data_time: 0.0327 memory: 33630 grad_norm: 4.1503 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3890 loss: 1.3890 2022/10/15 02:41:02 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 02:41:02 - mmengine - INFO - Epoch(train) [48][940/940] lr: 1.0000e-03 eta: 8:00:03 time: 0.5462 data_time: 0.0285 memory: 33630 grad_norm: 4.4392 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.2177 loss: 1.2177 2022/10/15 02:41:02 - mmengine - INFO - Saving checkpoint at 48 epochs 2022/10/15 02:41:17 - mmengine - INFO - Epoch(val) [48][20/78] eta: 0:00:42 time: 0.7334 data_time: 0.5643 memory: 5967 2022/10/15 02:41:28 - mmengine - INFO - Epoch(val) [48][40/78] eta: 0:00:19 time: 0.5087 data_time: 0.3398 memory: 5967 2022/10/15 02:41:40 - mmengine - INFO - Epoch(val) [48][60/78] eta: 0:00:11 time: 0.6407 data_time: 0.4718 memory: 5967 2022/10/15 02:41:51 - mmengine - INFO - Epoch(val) [48][78/78] acc/top1: 0.6825 acc/top5: 0.8759 acc/mean1: 0.6823 2022/10/15 02:42:08 - mmengine - INFO - Epoch(train) [49][20/940] lr: 1.0000e-03 eta: 7:59:56 time: 0.8141 data_time: 0.2375 memory: 33630 grad_norm: 4.1455 top1_acc: 0.6875 top5_acc: 0.7188 loss_cls: 1.2161 loss: 1.2161 2022/10/15 02:42:19 - mmengine - INFO - Epoch(train) [49][40/940] lr: 1.0000e-03 eta: 7:59:44 time: 0.5795 data_time: 0.0376 memory: 33630 grad_norm: 4.1943 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3249 loss: 1.3249 2022/10/15 02:42:31 - mmengine - INFO - Epoch(train) [49][60/940] lr: 1.0000e-03 eta: 7:59:32 time: 0.5885 data_time: 0.0405 memory: 33630 grad_norm: 4.1527 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2832 loss: 1.2832 2022/10/15 02:42:43 - mmengine - INFO - Epoch(train) [49][80/940] lr: 1.0000e-03 eta: 7:59:20 time: 0.5753 data_time: 0.0311 memory: 33630 grad_norm: 4.2154 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3751 loss: 1.3751 2022/10/15 02:42:54 - mmengine - INFO - Epoch(train) [49][100/940] lr: 1.0000e-03 eta: 7:59:08 time: 0.5829 data_time: 0.0416 memory: 33630 grad_norm: 4.2778 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3340 loss: 1.3340 2022/10/15 02:43:06 - mmengine - INFO - Epoch(train) [49][120/940] lr: 1.0000e-03 eta: 7:58:56 time: 0.5874 data_time: 0.0307 memory: 33630 grad_norm: 4.2246 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3137 loss: 1.3137 2022/10/15 02:43:18 - mmengine - INFO - Epoch(train) [49][140/940] lr: 1.0000e-03 eta: 7:58:45 time: 0.6000 data_time: 0.0405 memory: 33630 grad_norm: 4.2404 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1938 loss: 1.1938 2022/10/15 02:43:30 - mmengine - INFO - Epoch(train) [49][160/940] lr: 1.0000e-03 eta: 7:58:33 time: 0.5800 data_time: 0.0396 memory: 33630 grad_norm: 4.2382 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.3635 loss: 1.3635 2022/10/15 02:43:41 - mmengine - INFO - Epoch(train) [49][180/940] lr: 1.0000e-03 eta: 7:58:21 time: 0.5868 data_time: 0.0473 memory: 33630 grad_norm: 4.1478 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2150 loss: 1.2150 2022/10/15 02:43:53 - mmengine - INFO - Epoch(train) [49][200/940] lr: 1.0000e-03 eta: 7:58:09 time: 0.5831 data_time: 0.0322 memory: 33630 grad_norm: 4.0559 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.2568 loss: 1.2568 2022/10/15 02:44:05 - mmengine - INFO - Epoch(train) [49][220/940] lr: 1.0000e-03 eta: 7:57:57 time: 0.5881 data_time: 0.0323 memory: 33630 grad_norm: 4.2028 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2213 loss: 1.2213 2022/10/15 02:44:17 - mmengine - INFO - Epoch(train) [49][240/940] lr: 1.0000e-03 eta: 7:57:45 time: 0.5965 data_time: 0.0397 memory: 33630 grad_norm: 4.1467 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2687 loss: 1.2687 2022/10/15 02:44:28 - mmengine - INFO - Epoch(train) [49][260/940] lr: 1.0000e-03 eta: 7:57:33 time: 0.5790 data_time: 0.0358 memory: 33630 grad_norm: 4.2392 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3243 loss: 1.3243 2022/10/15 02:44:40 - mmengine - INFO - Epoch(train) [49][280/940] lr: 1.0000e-03 eta: 7:57:22 time: 0.5913 data_time: 0.0391 memory: 33630 grad_norm: 4.2349 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3121 loss: 1.3121 2022/10/15 02:44:52 - mmengine - INFO - Epoch(train) [49][300/940] lr: 1.0000e-03 eta: 7:57:10 time: 0.6057 data_time: 0.0363 memory: 33630 grad_norm: 4.1847 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2698 loss: 1.2698 2022/10/15 02:45:04 - mmengine - INFO - Epoch(train) [49][320/940] lr: 1.0000e-03 eta: 7:56:58 time: 0.5896 data_time: 0.0379 memory: 33630 grad_norm: 4.1880 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.2598 loss: 1.2598 2022/10/15 02:45:16 - mmengine - INFO - Epoch(train) [49][340/940] lr: 1.0000e-03 eta: 7:56:46 time: 0.5870 data_time: 0.0364 memory: 33630 grad_norm: 4.2428 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2521 loss: 1.2521 2022/10/15 02:45:28 - mmengine - INFO - Epoch(train) [49][360/940] lr: 1.0000e-03 eta: 7:56:35 time: 0.5890 data_time: 0.0380 memory: 33630 grad_norm: 4.1551 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2887 loss: 1.2887 2022/10/15 02:45:39 - mmengine - INFO - Epoch(train) [49][380/940] lr: 1.0000e-03 eta: 7:56:23 time: 0.5912 data_time: 0.0355 memory: 33630 grad_norm: 4.3554 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4468 loss: 1.4468 2022/10/15 02:45:51 - mmengine - INFO - Epoch(train) [49][400/940] lr: 1.0000e-03 eta: 7:56:11 time: 0.5905 data_time: 0.0313 memory: 33630 grad_norm: 4.1986 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3791 loss: 1.3791 2022/10/15 02:46:03 - mmengine - INFO - Epoch(train) [49][420/940] lr: 1.0000e-03 eta: 7:55:59 time: 0.5792 data_time: 0.0361 memory: 33630 grad_norm: 4.1888 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4096 loss: 1.4096 2022/10/15 02:46:14 - mmengine - INFO - Epoch(train) [49][440/940] lr: 1.0000e-03 eta: 7:55:47 time: 0.5785 data_time: 0.0404 memory: 33630 grad_norm: 4.2322 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3266 loss: 1.3266 2022/10/15 02:46:26 - mmengine - INFO - Epoch(train) [49][460/940] lr: 1.0000e-03 eta: 7:55:35 time: 0.5915 data_time: 0.0389 memory: 33630 grad_norm: 4.2463 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3518 loss: 1.3518 2022/10/15 02:46:38 - mmengine - INFO - Epoch(train) [49][480/940] lr: 1.0000e-03 eta: 7:55:24 time: 0.5887 data_time: 0.0358 memory: 33630 grad_norm: 4.0871 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2655 loss: 1.2655 2022/10/15 02:46:50 - mmengine - INFO - Epoch(train) [49][500/940] lr: 1.0000e-03 eta: 7:55:12 time: 0.5794 data_time: 0.0425 memory: 33630 grad_norm: 4.2759 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2581 loss: 1.2581 2022/10/15 02:47:01 - mmengine - INFO - Epoch(train) [49][520/940] lr: 1.0000e-03 eta: 7:55:00 time: 0.5882 data_time: 0.0379 memory: 33630 grad_norm: 4.2534 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4289 loss: 1.4289 2022/10/15 02:47:13 - mmengine - INFO - Epoch(train) [49][540/940] lr: 1.0000e-03 eta: 7:54:48 time: 0.5713 data_time: 0.0324 memory: 33630 grad_norm: 4.1818 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3137 loss: 1.3137 2022/10/15 02:47:25 - mmengine - INFO - Epoch(train) [49][560/940] lr: 1.0000e-03 eta: 7:54:36 time: 0.5906 data_time: 0.0354 memory: 33630 grad_norm: 4.1757 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2282 loss: 1.2282 2022/10/15 02:47:36 - mmengine - INFO - Epoch(train) [49][580/940] lr: 1.0000e-03 eta: 7:54:24 time: 0.5901 data_time: 0.0322 memory: 33630 grad_norm: 4.1942 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2860 loss: 1.2860 2022/10/15 02:47:48 - mmengine - INFO - Epoch(train) [49][600/940] lr: 1.0000e-03 eta: 7:54:13 time: 0.5973 data_time: 0.0388 memory: 33630 grad_norm: 4.1693 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2829 loss: 1.2829 2022/10/15 02:48:00 - mmengine - INFO - Epoch(train) [49][620/940] lr: 1.0000e-03 eta: 7:54:01 time: 0.5806 data_time: 0.0363 memory: 33630 grad_norm: 4.2019 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3886 loss: 1.3886 2022/10/15 02:48:12 - mmengine - INFO - Epoch(train) [49][640/940] lr: 1.0000e-03 eta: 7:53:49 time: 0.5860 data_time: 0.0463 memory: 33630 grad_norm: 4.2219 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3322 loss: 1.3322 2022/10/15 02:48:23 - mmengine - INFO - Epoch(train) [49][660/940] lr: 1.0000e-03 eta: 7:53:37 time: 0.5812 data_time: 0.0367 memory: 33630 grad_norm: 4.2166 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2677 loss: 1.2677 2022/10/15 02:48:35 - mmengine - INFO - Epoch(train) [49][680/940] lr: 1.0000e-03 eta: 7:53:25 time: 0.6019 data_time: 0.0361 memory: 33630 grad_norm: 4.2347 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3414 loss: 1.3414 2022/10/15 02:48:47 - mmengine - INFO - Epoch(train) [49][700/940] lr: 1.0000e-03 eta: 7:53:13 time: 0.5839 data_time: 0.0306 memory: 33630 grad_norm: 4.2224 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3821 loss: 1.3821 2022/10/15 02:48:59 - mmengine - INFO - Epoch(train) [49][720/940] lr: 1.0000e-03 eta: 7:53:02 time: 0.5975 data_time: 0.0368 memory: 33630 grad_norm: 4.3456 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3939 loss: 1.3939 2022/10/15 02:49:11 - mmengine - INFO - Epoch(train) [49][740/940] lr: 1.0000e-03 eta: 7:52:50 time: 0.5811 data_time: 0.0400 memory: 33630 grad_norm: 4.3446 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3933 loss: 1.3933 2022/10/15 02:49:22 - mmengine - INFO - Epoch(train) [49][760/940] lr: 1.0000e-03 eta: 7:52:38 time: 0.5898 data_time: 0.0374 memory: 33630 grad_norm: 4.2592 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3602 loss: 1.3602 2022/10/15 02:49:34 - mmengine - INFO - Epoch(train) [49][780/940] lr: 1.0000e-03 eta: 7:52:26 time: 0.5778 data_time: 0.0318 memory: 33630 grad_norm: 4.1400 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1192 loss: 1.1192 2022/10/15 02:49:46 - mmengine - INFO - Epoch(train) [49][800/940] lr: 1.0000e-03 eta: 7:52:14 time: 0.5846 data_time: 0.0326 memory: 33630 grad_norm: 4.1728 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2749 loss: 1.2749 2022/10/15 02:49:57 - mmengine - INFO - Epoch(train) [49][820/940] lr: 1.0000e-03 eta: 7:52:02 time: 0.5788 data_time: 0.0382 memory: 33630 grad_norm: 4.1593 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2926 loss: 1.2926 2022/10/15 02:50:09 - mmengine - INFO - Epoch(train) [49][840/940] lr: 1.0000e-03 eta: 7:51:50 time: 0.5779 data_time: 0.0327 memory: 33630 grad_norm: 4.2998 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3906 loss: 1.3906 2022/10/15 02:50:20 - mmengine - INFO - Epoch(train) [49][860/940] lr: 1.0000e-03 eta: 7:51:38 time: 0.5844 data_time: 0.0323 memory: 33630 grad_norm: 4.2004 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.2711 loss: 1.2711 2022/10/15 02:50:32 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 02:50:32 - mmengine - INFO - Epoch(train) [49][880/940] lr: 1.0000e-03 eta: 7:51:26 time: 0.5841 data_time: 0.0371 memory: 33630 grad_norm: 4.2077 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3192 loss: 1.3192 2022/10/15 02:50:44 - mmengine - INFO - Epoch(train) [49][900/940] lr: 1.0000e-03 eta: 7:51:14 time: 0.5804 data_time: 0.0420 memory: 33630 grad_norm: 4.1778 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2498 loss: 1.2498 2022/10/15 02:50:55 - mmengine - INFO - Epoch(train) [49][920/940] lr: 1.0000e-03 eta: 7:51:02 time: 0.5894 data_time: 0.0369 memory: 33630 grad_norm: 4.1498 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1961 loss: 1.1961 2022/10/15 02:51:06 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 02:51:06 - mmengine - INFO - Epoch(train) [49][940/940] lr: 1.0000e-03 eta: 7:50:50 time: 0.5355 data_time: 0.0308 memory: 33630 grad_norm: 4.3706 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.2461 loss: 1.2461 2022/10/15 02:51:20 - mmengine - INFO - Epoch(val) [49][20/78] eta: 0:00:41 time: 0.7126 data_time: 0.5387 memory: 5967 2022/10/15 02:51:31 - mmengine - INFO - Epoch(val) [49][40/78] eta: 0:00:19 time: 0.5126 data_time: 0.3444 memory: 5967 2022/10/15 02:51:44 - mmengine - INFO - Epoch(val) [49][60/78] eta: 0:00:12 time: 0.6716 data_time: 0.5003 memory: 5967 2022/10/15 02:51:57 - mmengine - INFO - Epoch(val) [49][78/78] acc/top1: 0.6855 acc/top5: 0.8759 acc/mean1: 0.6854 2022/10/15 02:52:13 - mmengine - INFO - Epoch(train) [50][20/940] lr: 1.0000e-03 eta: 7:50:43 time: 0.8362 data_time: 0.2383 memory: 33630 grad_norm: 4.2308 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2157 loss: 1.2157 2022/10/15 02:52:25 - mmengine - INFO - Epoch(train) [50][40/940] lr: 1.0000e-03 eta: 7:50:31 time: 0.5950 data_time: 0.0328 memory: 33630 grad_norm: 4.2530 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3773 loss: 1.3773 2022/10/15 02:52:37 - mmengine - INFO - Epoch(train) [50][60/940] lr: 1.0000e-03 eta: 7:50:20 time: 0.5983 data_time: 0.0439 memory: 33630 grad_norm: 4.2642 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2704 loss: 1.2704 2022/10/15 02:52:49 - mmengine - INFO - Epoch(train) [50][80/940] lr: 1.0000e-03 eta: 7:50:08 time: 0.5845 data_time: 0.0325 memory: 33630 grad_norm: 4.2795 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3679 loss: 1.3679 2022/10/15 02:53:01 - mmengine - INFO - Epoch(train) [50][100/940] lr: 1.0000e-03 eta: 7:49:56 time: 0.5934 data_time: 0.0416 memory: 33630 grad_norm: 4.1067 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2835 loss: 1.2835 2022/10/15 02:53:12 - mmengine - INFO - Epoch(train) [50][120/940] lr: 1.0000e-03 eta: 7:49:44 time: 0.5880 data_time: 0.0343 memory: 33630 grad_norm: 4.2561 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3622 loss: 1.3622 2022/10/15 02:53:24 - mmengine - INFO - Epoch(train) [50][140/940] lr: 1.0000e-03 eta: 7:49:32 time: 0.5851 data_time: 0.0388 memory: 33630 grad_norm: 4.2297 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3948 loss: 1.3948 2022/10/15 02:53:36 - mmengine - INFO - Epoch(train) [50][160/940] lr: 1.0000e-03 eta: 7:49:20 time: 0.5815 data_time: 0.0308 memory: 33630 grad_norm: 4.1672 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3147 loss: 1.3147 2022/10/15 02:53:47 - mmengine - INFO - Epoch(train) [50][180/940] lr: 1.0000e-03 eta: 7:49:09 time: 0.5852 data_time: 0.0372 memory: 33630 grad_norm: 4.1524 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2396 loss: 1.2396 2022/10/15 02:53:59 - mmengine - INFO - Epoch(train) [50][200/940] lr: 1.0000e-03 eta: 7:48:56 time: 0.5757 data_time: 0.0288 memory: 33630 grad_norm: 4.1283 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4449 loss: 1.4449 2022/10/15 02:54:11 - mmengine - INFO - Epoch(train) [50][220/940] lr: 1.0000e-03 eta: 7:48:44 time: 0.5786 data_time: 0.0323 memory: 33630 grad_norm: 4.1539 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1874 loss: 1.1874 2022/10/15 02:54:22 - mmengine - INFO - Epoch(train) [50][240/940] lr: 1.0000e-03 eta: 7:48:32 time: 0.5785 data_time: 0.0343 memory: 33630 grad_norm: 4.2811 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1103 loss: 1.1103 2022/10/15 02:54:34 - mmengine - INFO - Epoch(train) [50][260/940] lr: 1.0000e-03 eta: 7:48:21 time: 0.5876 data_time: 0.0353 memory: 33630 grad_norm: 4.2431 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3350 loss: 1.3350 2022/10/15 02:54:46 - mmengine - INFO - Epoch(train) [50][280/940] lr: 1.0000e-03 eta: 7:48:09 time: 0.5922 data_time: 0.0346 memory: 33630 grad_norm: 4.2153 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2446 loss: 1.2446 2022/10/15 02:54:58 - mmengine - INFO - Epoch(train) [50][300/940] lr: 1.0000e-03 eta: 7:47:57 time: 0.5895 data_time: 0.0320 memory: 33630 grad_norm: 4.2471 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3604 loss: 1.3604 2022/10/15 02:55:09 - mmengine - INFO - Epoch(train) [50][320/940] lr: 1.0000e-03 eta: 7:47:45 time: 0.5926 data_time: 0.0357 memory: 33630 grad_norm: 4.2179 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2956 loss: 1.2956 2022/10/15 02:55:21 - mmengine - INFO - Epoch(train) [50][340/940] lr: 1.0000e-03 eta: 7:47:33 time: 0.5836 data_time: 0.0325 memory: 33630 grad_norm: 4.1903 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3791 loss: 1.3791 2022/10/15 02:55:33 - mmengine - INFO - Epoch(train) [50][360/940] lr: 1.0000e-03 eta: 7:47:22 time: 0.5844 data_time: 0.0305 memory: 33630 grad_norm: 4.2478 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3821 loss: 1.3821 2022/10/15 02:55:44 - mmengine - INFO - Epoch(train) [50][380/940] lr: 1.0000e-03 eta: 7:47:10 time: 0.5835 data_time: 0.0328 memory: 33630 grad_norm: 4.2992 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.3835 loss: 1.3835 2022/10/15 02:55:56 - mmengine - INFO - Epoch(train) [50][400/940] lr: 1.0000e-03 eta: 7:46:58 time: 0.5914 data_time: 0.0397 memory: 33630 grad_norm: 4.2371 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.1338 loss: 1.1338 2022/10/15 02:56:08 - mmengine - INFO - Epoch(train) [50][420/940] lr: 1.0000e-03 eta: 7:46:46 time: 0.5844 data_time: 0.0397 memory: 33630 grad_norm: 4.2488 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3738 loss: 1.3738 2022/10/15 02:56:19 - mmengine - INFO - Epoch(train) [50][440/940] lr: 1.0000e-03 eta: 7:46:34 time: 0.5756 data_time: 0.0385 memory: 33630 grad_norm: 4.1720 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1721 loss: 1.1721 2022/10/15 02:56:31 - mmengine - INFO - Epoch(train) [50][460/940] lr: 1.0000e-03 eta: 7:46:22 time: 0.5861 data_time: 0.0306 memory: 33630 grad_norm: 4.3020 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2985 loss: 1.2985 2022/10/15 02:56:43 - mmengine - INFO - Epoch(train) [50][480/940] lr: 1.0000e-03 eta: 7:46:10 time: 0.5823 data_time: 0.0346 memory: 33630 grad_norm: 4.2311 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3211 loss: 1.3211 2022/10/15 02:56:55 - mmengine - INFO - Epoch(train) [50][500/940] lr: 1.0000e-03 eta: 7:45:58 time: 0.5849 data_time: 0.0401 memory: 33630 grad_norm: 4.2667 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3898 loss: 1.3898 2022/10/15 02:57:06 - mmengine - INFO - Epoch(train) [50][520/940] lr: 1.0000e-03 eta: 7:45:46 time: 0.5812 data_time: 0.0321 memory: 33630 grad_norm: 4.2582 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.1830 loss: 1.1830 2022/10/15 02:57:18 - mmengine - INFO - Epoch(train) [50][540/940] lr: 1.0000e-03 eta: 7:45:34 time: 0.5849 data_time: 0.0369 memory: 33630 grad_norm: 4.2380 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3482 loss: 1.3482 2022/10/15 02:57:30 - mmengine - INFO - Epoch(train) [50][560/940] lr: 1.0000e-03 eta: 7:45:23 time: 0.5903 data_time: 0.0344 memory: 33630 grad_norm: 4.2277 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2224 loss: 1.2224 2022/10/15 02:57:41 - mmengine - INFO - Epoch(train) [50][580/940] lr: 1.0000e-03 eta: 7:45:11 time: 0.5788 data_time: 0.0380 memory: 33630 grad_norm: 4.2728 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3058 loss: 1.3058 2022/10/15 02:57:53 - mmengine - INFO - Epoch(train) [50][600/940] lr: 1.0000e-03 eta: 7:44:59 time: 0.5716 data_time: 0.0367 memory: 33630 grad_norm: 4.2565 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2626 loss: 1.2626 2022/10/15 02:58:04 - mmengine - INFO - Epoch(train) [50][620/940] lr: 1.0000e-03 eta: 7:44:47 time: 0.5847 data_time: 0.0373 memory: 33630 grad_norm: 4.2376 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.3529 loss: 1.3529 2022/10/15 02:58:16 - mmengine - INFO - Epoch(train) [50][640/940] lr: 1.0000e-03 eta: 7:44:35 time: 0.5776 data_time: 0.0375 memory: 33630 grad_norm: 4.2054 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2833 loss: 1.2833 2022/10/15 02:58:28 - mmengine - INFO - Epoch(train) [50][660/940] lr: 1.0000e-03 eta: 7:44:23 time: 0.5792 data_time: 0.0358 memory: 33630 grad_norm: 4.1954 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3315 loss: 1.3315 2022/10/15 02:58:39 - mmengine - INFO - Epoch(train) [50][680/940] lr: 1.0000e-03 eta: 7:44:11 time: 0.5881 data_time: 0.0337 memory: 33630 grad_norm: 4.2221 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3374 loss: 1.3374 2022/10/15 02:58:51 - mmengine - INFO - Epoch(train) [50][700/940] lr: 1.0000e-03 eta: 7:43:59 time: 0.5864 data_time: 0.0380 memory: 33630 grad_norm: 4.3470 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2587 loss: 1.2587 2022/10/15 02:59:03 - mmengine - INFO - Epoch(train) [50][720/940] lr: 1.0000e-03 eta: 7:43:47 time: 0.5870 data_time: 0.0343 memory: 33630 grad_norm: 4.1389 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3153 loss: 1.3153 2022/10/15 02:59:14 - mmengine - INFO - Epoch(train) [50][740/940] lr: 1.0000e-03 eta: 7:43:35 time: 0.5819 data_time: 0.0320 memory: 33630 grad_norm: 4.3263 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.3331 loss: 1.3331 2022/10/15 02:59:26 - mmengine - INFO - Epoch(train) [50][760/940] lr: 1.0000e-03 eta: 7:43:23 time: 0.5826 data_time: 0.0332 memory: 33630 grad_norm: 4.3290 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3222 loss: 1.3222 2022/10/15 02:59:38 - mmengine - INFO - Epoch(train) [50][780/940] lr: 1.0000e-03 eta: 7:43:11 time: 0.5875 data_time: 0.0402 memory: 33630 grad_norm: 4.2710 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3188 loss: 1.3188 2022/10/15 02:59:50 - mmengine - INFO - Epoch(train) [50][800/940] lr: 1.0000e-03 eta: 7:43:00 time: 0.5888 data_time: 0.0308 memory: 33630 grad_norm: 4.2752 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2508 loss: 1.2508 2022/10/15 03:00:01 - mmengine - INFO - Epoch(train) [50][820/940] lr: 1.0000e-03 eta: 7:42:48 time: 0.5848 data_time: 0.0404 memory: 33630 grad_norm: 4.2292 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.1997 loss: 1.1997 2022/10/15 03:00:13 - mmengine - INFO - Epoch(train) [50][840/940] lr: 1.0000e-03 eta: 7:42:36 time: 0.5857 data_time: 0.0428 memory: 33630 grad_norm: 4.2481 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3383 loss: 1.3383 2022/10/15 03:00:25 - mmengine - INFO - Epoch(train) [50][860/940] lr: 1.0000e-03 eta: 7:42:24 time: 0.5916 data_time: 0.0446 memory: 33630 grad_norm: 4.2836 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2763 loss: 1.2763 2022/10/15 03:00:36 - mmengine - INFO - Epoch(train) [50][880/940] lr: 1.0000e-03 eta: 7:42:12 time: 0.5816 data_time: 0.0357 memory: 33630 grad_norm: 4.1210 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1660 loss: 1.1660 2022/10/15 03:00:48 - mmengine - INFO - Epoch(train) [50][900/940] lr: 1.0000e-03 eta: 7:42:00 time: 0.5864 data_time: 0.0351 memory: 33630 grad_norm: 4.2310 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1901 loss: 1.1901 2022/10/15 03:01:00 - mmengine - INFO - Epoch(train) [50][920/940] lr: 1.0000e-03 eta: 7:41:48 time: 0.5793 data_time: 0.0343 memory: 33630 grad_norm: 4.1764 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3664 loss: 1.3664 2022/10/15 03:01:11 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 03:01:11 - mmengine - INFO - Epoch(train) [50][940/940] lr: 1.0000e-03 eta: 7:41:36 time: 0.5367 data_time: 0.0312 memory: 33630 grad_norm: 4.4303 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.2770 loss: 1.2770 2022/10/15 03:01:25 - mmengine - INFO - Epoch(val) [50][20/78] eta: 0:00:40 time: 0.7046 data_time: 0.5332 memory: 5967 2022/10/15 03:01:35 - mmengine - INFO - Epoch(val) [50][40/78] eta: 0:00:20 time: 0.5332 data_time: 0.3645 memory: 5967 2022/10/15 03:01:48 - mmengine - INFO - Epoch(val) [50][60/78] eta: 0:00:11 time: 0.6387 data_time: 0.4680 memory: 5967 2022/10/15 03:02:01 - mmengine - INFO - Epoch(val) [50][78/78] acc/top1: 0.6837 acc/top5: 0.8781 acc/mean1: 0.6836 2022/10/15 03:02:17 - mmengine - INFO - Epoch(train) [51][20/940] lr: 1.0000e-03 eta: 7:41:29 time: 0.8398 data_time: 0.2989 memory: 33630 grad_norm: 4.3229 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1809 loss: 1.1809 2022/10/15 03:02:30 - mmengine - INFO - Epoch(train) [51][40/940] lr: 1.0000e-03 eta: 7:41:17 time: 0.6114 data_time: 0.0708 memory: 33630 grad_norm: 4.2505 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2811 loss: 1.2811 2022/10/15 03:02:42 - mmengine - INFO - Epoch(train) [51][60/940] lr: 1.0000e-03 eta: 7:41:06 time: 0.6030 data_time: 0.0531 memory: 33630 grad_norm: 4.1945 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3159 loss: 1.3159 2022/10/15 03:02:53 - mmengine - INFO - Epoch(train) [51][80/940] lr: 1.0000e-03 eta: 7:40:54 time: 0.5774 data_time: 0.0317 memory: 33630 grad_norm: 4.3391 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1803 loss: 1.1803 2022/10/15 03:03:05 - mmengine - INFO - Epoch(train) [51][100/940] lr: 1.0000e-03 eta: 7:40:42 time: 0.5991 data_time: 0.0417 memory: 33630 grad_norm: 4.2315 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3078 loss: 1.3078 2022/10/15 03:03:17 - mmengine - INFO - Epoch(train) [51][120/940] lr: 1.0000e-03 eta: 7:40:31 time: 0.5899 data_time: 0.0323 memory: 33630 grad_norm: 4.2185 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2952 loss: 1.2952 2022/10/15 03:03:29 - mmengine - INFO - Epoch(train) [51][140/940] lr: 1.0000e-03 eta: 7:40:19 time: 0.6126 data_time: 0.0698 memory: 33630 grad_norm: 4.3158 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.1866 loss: 1.1866 2022/10/15 03:03:41 - mmengine - INFO - Epoch(train) [51][160/940] lr: 1.0000e-03 eta: 7:40:07 time: 0.5716 data_time: 0.0326 memory: 33630 grad_norm: 4.3328 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3345 loss: 1.3345 2022/10/15 03:03:52 - mmengine - INFO - Epoch(train) [51][180/940] lr: 1.0000e-03 eta: 7:39:55 time: 0.5719 data_time: 0.0360 memory: 33630 grad_norm: 4.2185 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2953 loss: 1.2953 2022/10/15 03:04:04 - mmengine - INFO - Epoch(train) [51][200/940] lr: 1.0000e-03 eta: 7:39:43 time: 0.5965 data_time: 0.0325 memory: 33630 grad_norm: 4.1956 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2119 loss: 1.2119 2022/10/15 03:04:16 - mmengine - INFO - Epoch(train) [51][220/940] lr: 1.0000e-03 eta: 7:39:31 time: 0.5821 data_time: 0.0383 memory: 33630 grad_norm: 4.2380 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3709 loss: 1.3709 2022/10/15 03:04:28 - mmengine - INFO - Epoch(train) [51][240/940] lr: 1.0000e-03 eta: 7:39:20 time: 0.5882 data_time: 0.0338 memory: 33630 grad_norm: 4.2050 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2108 loss: 1.2108 2022/10/15 03:04:39 - mmengine - INFO - Epoch(train) [51][260/940] lr: 1.0000e-03 eta: 7:39:08 time: 0.5849 data_time: 0.0364 memory: 33630 grad_norm: 4.2824 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2791 loss: 1.2791 2022/10/15 03:04:51 - mmengine - INFO - Epoch(train) [51][280/940] lr: 1.0000e-03 eta: 7:38:56 time: 0.5839 data_time: 0.0312 memory: 33630 grad_norm: 4.3047 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4162 loss: 1.4162 2022/10/15 03:05:03 - mmengine - INFO - Epoch(train) [51][300/940] lr: 1.0000e-03 eta: 7:38:44 time: 0.5922 data_time: 0.0386 memory: 33630 grad_norm: 4.2822 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2481 loss: 1.2481 2022/10/15 03:05:14 - mmengine - INFO - Epoch(train) [51][320/940] lr: 1.0000e-03 eta: 7:38:32 time: 0.5745 data_time: 0.0413 memory: 33630 grad_norm: 4.2409 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3653 loss: 1.3653 2022/10/15 03:05:26 - mmengine - INFO - Epoch(train) [51][340/940] lr: 1.0000e-03 eta: 7:38:20 time: 0.5939 data_time: 0.0409 memory: 33630 grad_norm: 4.2426 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3694 loss: 1.3694 2022/10/15 03:05:38 - mmengine - INFO - Epoch(train) [51][360/940] lr: 1.0000e-03 eta: 7:38:08 time: 0.5836 data_time: 0.0370 memory: 33630 grad_norm: 4.1352 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2855 loss: 1.2855 2022/10/15 03:05:50 - mmengine - INFO - Epoch(train) [51][380/940] lr: 1.0000e-03 eta: 7:37:57 time: 0.5934 data_time: 0.0452 memory: 33630 grad_norm: 4.2843 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2467 loss: 1.2467 2022/10/15 03:06:01 - mmengine - INFO - Epoch(train) [51][400/940] lr: 1.0000e-03 eta: 7:37:45 time: 0.5771 data_time: 0.0362 memory: 33630 grad_norm: 4.3346 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2793 loss: 1.2793 2022/10/15 03:06:13 - mmengine - INFO - Epoch(train) [51][420/940] lr: 1.0000e-03 eta: 7:37:33 time: 0.5770 data_time: 0.0362 memory: 33630 grad_norm: 4.3205 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.4241 loss: 1.4241 2022/10/15 03:06:25 - mmengine - INFO - Epoch(train) [51][440/940] lr: 1.0000e-03 eta: 7:37:21 time: 0.5906 data_time: 0.0326 memory: 33630 grad_norm: 4.2064 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2687 loss: 1.2687 2022/10/15 03:06:36 - mmengine - INFO - Epoch(train) [51][460/940] lr: 1.0000e-03 eta: 7:37:09 time: 0.5934 data_time: 0.0331 memory: 33630 grad_norm: 4.3344 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1502 loss: 1.1502 2022/10/15 03:06:49 - mmengine - INFO - Epoch(train) [51][480/940] lr: 1.0000e-03 eta: 7:36:58 time: 0.6040 data_time: 0.0369 memory: 33630 grad_norm: 4.2833 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1743 loss: 1.1743 2022/10/15 03:07:00 - mmengine - INFO - Epoch(train) [51][500/940] lr: 1.0000e-03 eta: 7:36:46 time: 0.5744 data_time: 0.0389 memory: 33630 grad_norm: 4.1835 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3341 loss: 1.3341 2022/10/15 03:07:12 - mmengine - INFO - Epoch(train) [51][520/940] lr: 1.0000e-03 eta: 7:36:34 time: 0.5850 data_time: 0.0303 memory: 33630 grad_norm: 4.3822 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2564 loss: 1.2564 2022/10/15 03:07:23 - mmengine - INFO - Epoch(train) [51][540/940] lr: 1.0000e-03 eta: 7:36:22 time: 0.5845 data_time: 0.0420 memory: 33630 grad_norm: 4.3853 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2902 loss: 1.2902 2022/10/15 03:07:35 - mmengine - INFO - Epoch(train) [51][560/940] lr: 1.0000e-03 eta: 7:36:10 time: 0.5930 data_time: 0.0422 memory: 33630 grad_norm: 4.2851 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2138 loss: 1.2138 2022/10/15 03:07:47 - mmengine - INFO - Epoch(train) [51][580/940] lr: 1.0000e-03 eta: 7:35:58 time: 0.5908 data_time: 0.0432 memory: 33630 grad_norm: 4.3425 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3689 loss: 1.3689 2022/10/15 03:07:59 - mmengine - INFO - Epoch(train) [51][600/940] lr: 1.0000e-03 eta: 7:35:46 time: 0.5751 data_time: 0.0385 memory: 33630 grad_norm: 4.2671 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1632 loss: 1.1632 2022/10/15 03:08:10 - mmengine - INFO - Epoch(train) [51][620/940] lr: 1.0000e-03 eta: 7:35:34 time: 0.5789 data_time: 0.0337 memory: 33630 grad_norm: 4.2307 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2694 loss: 1.2694 2022/10/15 03:08:22 - mmengine - INFO - Epoch(train) [51][640/940] lr: 1.0000e-03 eta: 7:35:23 time: 0.5915 data_time: 0.0341 memory: 33630 grad_norm: 4.2572 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1846 loss: 1.1846 2022/10/15 03:08:34 - mmengine - INFO - Epoch(train) [51][660/940] lr: 1.0000e-03 eta: 7:35:11 time: 0.5783 data_time: 0.0348 memory: 33630 grad_norm: 4.2649 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3823 loss: 1.3823 2022/10/15 03:08:45 - mmengine - INFO - Epoch(train) [51][680/940] lr: 1.0000e-03 eta: 7:34:59 time: 0.5793 data_time: 0.0337 memory: 33630 grad_norm: 4.2342 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2122 loss: 1.2122 2022/10/15 03:08:57 - mmengine - INFO - Epoch(train) [51][700/940] lr: 1.0000e-03 eta: 7:34:47 time: 0.5897 data_time: 0.0410 memory: 33630 grad_norm: 4.2338 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3448 loss: 1.3448 2022/10/15 03:09:09 - mmengine - INFO - Epoch(train) [51][720/940] lr: 1.0000e-03 eta: 7:34:35 time: 0.5826 data_time: 0.0386 memory: 33630 grad_norm: 4.3290 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3309 loss: 1.3309 2022/10/15 03:09:20 - mmengine - INFO - Epoch(train) [51][740/940] lr: 1.0000e-03 eta: 7:34:23 time: 0.5809 data_time: 0.0375 memory: 33630 grad_norm: 4.2686 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2901 loss: 1.2901 2022/10/15 03:09:32 - mmengine - INFO - Epoch(train) [51][760/940] lr: 1.0000e-03 eta: 7:34:11 time: 0.5953 data_time: 0.0327 memory: 33630 grad_norm: 4.2840 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2574 loss: 1.2574 2022/10/15 03:09:44 - mmengine - INFO - Epoch(train) [51][780/940] lr: 1.0000e-03 eta: 7:33:59 time: 0.5883 data_time: 0.0361 memory: 33630 grad_norm: 4.2774 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2173 loss: 1.2173 2022/10/15 03:09:55 - mmengine - INFO - Epoch(train) [51][800/940] lr: 1.0000e-03 eta: 7:33:47 time: 0.5679 data_time: 0.0336 memory: 33630 grad_norm: 4.2929 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2630 loss: 1.2630 2022/10/15 03:10:07 - mmengine - INFO - Epoch(train) [51][820/940] lr: 1.0000e-03 eta: 7:33:35 time: 0.5777 data_time: 0.0412 memory: 33630 grad_norm: 4.2804 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2354 loss: 1.2354 2022/10/15 03:10:18 - mmengine - INFO - Epoch(train) [51][840/940] lr: 1.0000e-03 eta: 7:33:23 time: 0.5812 data_time: 0.0324 memory: 33630 grad_norm: 4.2405 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3516 loss: 1.3516 2022/10/15 03:10:30 - mmengine - INFO - Epoch(train) [51][860/940] lr: 1.0000e-03 eta: 7:33:11 time: 0.5805 data_time: 0.0365 memory: 33630 grad_norm: 4.2325 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.1848 loss: 1.1848 2022/10/15 03:10:42 - mmengine - INFO - Epoch(train) [51][880/940] lr: 1.0000e-03 eta: 7:32:59 time: 0.5868 data_time: 0.0363 memory: 33630 grad_norm: 4.4679 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3787 loss: 1.3787 2022/10/15 03:10:54 - mmengine - INFO - Epoch(train) [51][900/940] lr: 1.0000e-03 eta: 7:32:48 time: 0.5923 data_time: 0.0387 memory: 33630 grad_norm: 4.2129 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3670 loss: 1.3670 2022/10/15 03:11:06 - mmengine - INFO - Epoch(train) [51][920/940] lr: 1.0000e-03 eta: 7:32:36 time: 0.5930 data_time: 0.0387 memory: 33630 grad_norm: 4.3113 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3195 loss: 1.3195 2022/10/15 03:11:16 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 03:11:16 - mmengine - INFO - Epoch(train) [51][940/940] lr: 1.0000e-03 eta: 7:32:23 time: 0.5323 data_time: 0.0291 memory: 33630 grad_norm: 4.5802 top1_acc: 0.2857 top5_acc: 0.4286 loss_cls: 1.5206 loss: 1.5206 2022/10/15 03:11:16 - mmengine - INFO - Saving checkpoint at 51 epochs 2022/10/15 03:11:31 - mmengine - INFO - Epoch(val) [51][20/78] eta: 0:00:41 time: 0.7149 data_time: 0.5452 memory: 5967 2022/10/15 03:11:41 - mmengine - INFO - Epoch(val) [51][40/78] eta: 0:00:18 time: 0.4995 data_time: 0.3307 memory: 5967 2022/10/15 03:11:55 - mmengine - INFO - Epoch(val) [51][60/78] eta: 0:00:12 time: 0.7062 data_time: 0.5356 memory: 5967 2022/10/15 03:12:06 - mmengine - INFO - Epoch(val) [51][78/78] acc/top1: 0.6843 acc/top5: 0.8762 acc/mean1: 0.6841 2022/10/15 03:12:23 - mmengine - INFO - Epoch(train) [52][20/940] lr: 1.0000e-03 eta: 7:32:16 time: 0.8150 data_time: 0.2585 memory: 33630 grad_norm: 4.2297 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1722 loss: 1.1722 2022/10/15 03:12:34 - mmengine - INFO - Epoch(train) [52][40/940] lr: 1.0000e-03 eta: 7:32:04 time: 0.5986 data_time: 0.0607 memory: 33630 grad_norm: 4.2830 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2736 loss: 1.2736 2022/10/15 03:12:47 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 03:12:47 - mmengine - INFO - Epoch(train) [52][60/940] lr: 1.0000e-03 eta: 7:31:53 time: 0.6158 data_time: 0.0663 memory: 33630 grad_norm: 4.2959 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2217 loss: 1.2217 2022/10/15 03:12:59 - mmengine - INFO - Epoch(train) [52][80/940] lr: 1.0000e-03 eta: 7:31:41 time: 0.5895 data_time: 0.0321 memory: 33630 grad_norm: 4.1390 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2086 loss: 1.2086 2022/10/15 03:13:10 - mmengine - INFO - Epoch(train) [52][100/940] lr: 1.0000e-03 eta: 7:31:29 time: 0.5781 data_time: 0.0363 memory: 33630 grad_norm: 4.2475 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2213 loss: 1.2213 2022/10/15 03:13:22 - mmengine - INFO - Epoch(train) [52][120/940] lr: 1.0000e-03 eta: 7:31:17 time: 0.5914 data_time: 0.0410 memory: 33630 grad_norm: 4.3304 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2743 loss: 1.2743 2022/10/15 03:13:34 - mmengine - INFO - Epoch(train) [52][140/940] lr: 1.0000e-03 eta: 7:31:05 time: 0.5866 data_time: 0.0359 memory: 33630 grad_norm: 4.2136 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2930 loss: 1.2930 2022/10/15 03:13:45 - mmengine - INFO - Epoch(train) [52][160/940] lr: 1.0000e-03 eta: 7:30:54 time: 0.5854 data_time: 0.0407 memory: 33630 grad_norm: 4.2451 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2232 loss: 1.2232 2022/10/15 03:13:57 - mmengine - INFO - Epoch(train) [52][180/940] lr: 1.0000e-03 eta: 7:30:42 time: 0.5799 data_time: 0.0336 memory: 33630 grad_norm: 4.2523 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3079 loss: 1.3079 2022/10/15 03:14:09 - mmengine - INFO - Epoch(train) [52][200/940] lr: 1.0000e-03 eta: 7:30:30 time: 0.5930 data_time: 0.0454 memory: 33630 grad_norm: 4.3597 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1990 loss: 1.1990 2022/10/15 03:14:21 - mmengine - INFO - Epoch(train) [52][220/940] lr: 1.0000e-03 eta: 7:30:18 time: 0.5884 data_time: 0.0380 memory: 33630 grad_norm: 4.2890 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2596 loss: 1.2596 2022/10/15 03:14:33 - mmengine - INFO - Epoch(train) [52][240/940] lr: 1.0000e-03 eta: 7:30:06 time: 0.5971 data_time: 0.0395 memory: 33630 grad_norm: 4.2616 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3843 loss: 1.3843 2022/10/15 03:14:44 - mmengine - INFO - Epoch(train) [52][260/940] lr: 1.0000e-03 eta: 7:29:55 time: 0.5884 data_time: 0.0393 memory: 33630 grad_norm: 4.1984 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2409 loss: 1.2409 2022/10/15 03:14:56 - mmengine - INFO - Epoch(train) [52][280/940] lr: 1.0000e-03 eta: 7:29:43 time: 0.5857 data_time: 0.0373 memory: 33630 grad_norm: 4.2292 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3201 loss: 1.3201 2022/10/15 03:15:08 - mmengine - INFO - Epoch(train) [52][300/940] lr: 1.0000e-03 eta: 7:29:31 time: 0.5747 data_time: 0.0298 memory: 33630 grad_norm: 4.3005 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1839 loss: 1.1839 2022/10/15 03:15:19 - mmengine - INFO - Epoch(train) [52][320/940] lr: 1.0000e-03 eta: 7:29:19 time: 0.5949 data_time: 0.0360 memory: 33630 grad_norm: 4.2637 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2838 loss: 1.2838 2022/10/15 03:15:31 - mmengine - INFO - Epoch(train) [52][340/940] lr: 1.0000e-03 eta: 7:29:07 time: 0.5932 data_time: 0.0444 memory: 33630 grad_norm: 4.2862 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2930 loss: 1.2930 2022/10/15 03:15:43 - mmengine - INFO - Epoch(train) [52][360/940] lr: 1.0000e-03 eta: 7:28:55 time: 0.5900 data_time: 0.0396 memory: 33630 grad_norm: 4.2703 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2391 loss: 1.2391 2022/10/15 03:15:55 - mmengine - INFO - Epoch(train) [52][380/940] lr: 1.0000e-03 eta: 7:28:44 time: 0.5852 data_time: 0.0334 memory: 33630 grad_norm: 4.3073 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2623 loss: 1.2623 2022/10/15 03:16:07 - mmengine - INFO - Epoch(train) [52][400/940] lr: 1.0000e-03 eta: 7:28:32 time: 0.5849 data_time: 0.0486 memory: 33630 grad_norm: 4.2722 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3367 loss: 1.3367 2022/10/15 03:16:18 - mmengine - INFO - Epoch(train) [52][420/940] lr: 1.0000e-03 eta: 7:28:20 time: 0.5950 data_time: 0.0369 memory: 33630 grad_norm: 4.2118 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2599 loss: 1.2599 2022/10/15 03:16:30 - mmengine - INFO - Epoch(train) [52][440/940] lr: 1.0000e-03 eta: 7:28:08 time: 0.5769 data_time: 0.0464 memory: 33630 grad_norm: 4.2654 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3763 loss: 1.3763 2022/10/15 03:16:42 - mmengine - INFO - Epoch(train) [52][460/940] lr: 1.0000e-03 eta: 7:27:56 time: 0.5907 data_time: 0.0357 memory: 33630 grad_norm: 4.3346 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4047 loss: 1.4047 2022/10/15 03:16:54 - mmengine - INFO - Epoch(train) [52][480/940] lr: 1.0000e-03 eta: 7:27:44 time: 0.5877 data_time: 0.0298 memory: 33630 grad_norm: 4.3753 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3638 loss: 1.3638 2022/10/15 03:17:05 - mmengine - INFO - Epoch(train) [52][500/940] lr: 1.0000e-03 eta: 7:27:32 time: 0.5751 data_time: 0.0360 memory: 33630 grad_norm: 4.3719 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2850 loss: 1.2850 2022/10/15 03:17:17 - mmengine - INFO - Epoch(train) [52][520/940] lr: 1.0000e-03 eta: 7:27:20 time: 0.5782 data_time: 0.0328 memory: 33630 grad_norm: 4.3827 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3340 loss: 1.3340 2022/10/15 03:17:28 - mmengine - INFO - Epoch(train) [52][540/940] lr: 1.0000e-03 eta: 7:27:08 time: 0.5813 data_time: 0.0337 memory: 33630 grad_norm: 4.2364 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3313 loss: 1.3313 2022/10/15 03:17:40 - mmengine - INFO - Epoch(train) [52][560/940] lr: 1.0000e-03 eta: 7:26:56 time: 0.5789 data_time: 0.0354 memory: 33630 grad_norm: 4.3545 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.3552 loss: 1.3552 2022/10/15 03:17:51 - mmengine - INFO - Epoch(train) [52][580/940] lr: 1.0000e-03 eta: 7:26:44 time: 0.5759 data_time: 0.0364 memory: 33630 grad_norm: 4.2490 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2229 loss: 1.2229 2022/10/15 03:18:03 - mmengine - INFO - Epoch(train) [52][600/940] lr: 1.0000e-03 eta: 7:26:33 time: 0.5851 data_time: 0.0488 memory: 33630 grad_norm: 4.2169 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3108 loss: 1.3108 2022/10/15 03:18:15 - mmengine - INFO - Epoch(train) [52][620/940] lr: 1.0000e-03 eta: 7:26:21 time: 0.5833 data_time: 0.0410 memory: 33630 grad_norm: 4.3288 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4313 loss: 1.4313 2022/10/15 03:18:26 - mmengine - INFO - Epoch(train) [52][640/940] lr: 1.0000e-03 eta: 7:26:09 time: 0.5823 data_time: 0.0312 memory: 33630 grad_norm: 4.3425 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3336 loss: 1.3336 2022/10/15 03:18:38 - mmengine - INFO - Epoch(train) [52][660/940] lr: 1.0000e-03 eta: 7:25:57 time: 0.5880 data_time: 0.0405 memory: 33630 grad_norm: 4.3026 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3222 loss: 1.3222 2022/10/15 03:18:50 - mmengine - INFO - Epoch(train) [52][680/940] lr: 1.0000e-03 eta: 7:25:45 time: 0.5777 data_time: 0.0358 memory: 33630 grad_norm: 4.3131 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.3598 loss: 1.3598 2022/10/15 03:19:01 - mmengine - INFO - Epoch(train) [52][700/940] lr: 1.0000e-03 eta: 7:25:33 time: 0.5643 data_time: 0.0333 memory: 33630 grad_norm: 4.3384 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2916 loss: 1.2916 2022/10/15 03:19:13 - mmengine - INFO - Epoch(train) [52][720/940] lr: 1.0000e-03 eta: 7:25:21 time: 0.5845 data_time: 0.0356 memory: 33630 grad_norm: 4.2389 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2844 loss: 1.2844 2022/10/15 03:19:24 - mmengine - INFO - Epoch(train) [52][740/940] lr: 1.0000e-03 eta: 7:25:09 time: 0.5824 data_time: 0.0345 memory: 33630 grad_norm: 4.2315 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2758 loss: 1.2758 2022/10/15 03:19:36 - mmengine - INFO - Epoch(train) [52][760/940] lr: 1.0000e-03 eta: 7:24:57 time: 0.5794 data_time: 0.0354 memory: 33630 grad_norm: 4.2784 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3206 loss: 1.3206 2022/10/15 03:19:48 - mmengine - INFO - Epoch(train) [52][780/940] lr: 1.0000e-03 eta: 7:24:45 time: 0.5915 data_time: 0.0496 memory: 33630 grad_norm: 4.2894 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3226 loss: 1.3226 2022/10/15 03:19:59 - mmengine - INFO - Epoch(train) [52][800/940] lr: 1.0000e-03 eta: 7:24:33 time: 0.5826 data_time: 0.0409 memory: 33630 grad_norm: 4.2993 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1610 loss: 1.1610 2022/10/15 03:20:11 - mmengine - INFO - Epoch(train) [52][820/940] lr: 1.0000e-03 eta: 7:24:21 time: 0.5876 data_time: 0.0328 memory: 33630 grad_norm: 4.3052 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2944 loss: 1.2944 2022/10/15 03:20:23 - mmengine - INFO - Epoch(train) [52][840/940] lr: 1.0000e-03 eta: 7:24:09 time: 0.5803 data_time: 0.0352 memory: 33630 grad_norm: 4.3353 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1279 loss: 1.1279 2022/10/15 03:20:34 - mmengine - INFO - Epoch(train) [52][860/940] lr: 1.0000e-03 eta: 7:23:58 time: 0.5861 data_time: 0.0347 memory: 33630 grad_norm: 4.3363 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2995 loss: 1.2995 2022/10/15 03:20:46 - mmengine - INFO - Epoch(train) [52][880/940] lr: 1.0000e-03 eta: 7:23:46 time: 0.5806 data_time: 0.0307 memory: 33630 grad_norm: 4.2731 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.1669 loss: 1.1669 2022/10/15 03:20:58 - mmengine - INFO - Epoch(train) [52][900/940] lr: 1.0000e-03 eta: 7:23:34 time: 0.5956 data_time: 0.0385 memory: 33630 grad_norm: 4.3437 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1471 loss: 1.1471 2022/10/15 03:21:10 - mmengine - INFO - Epoch(train) [52][920/940] lr: 1.0000e-03 eta: 7:23:22 time: 0.5811 data_time: 0.0374 memory: 33630 grad_norm: 4.4151 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2630 loss: 1.2630 2022/10/15 03:21:21 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 03:21:21 - mmengine - INFO - Epoch(train) [52][940/940] lr: 1.0000e-03 eta: 7:23:10 time: 0.5477 data_time: 0.0355 memory: 33630 grad_norm: 4.7063 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.4462 loss: 1.4462 2022/10/15 03:21:36 - mmengine - INFO - Epoch(val) [52][20/78] eta: 0:00:43 time: 0.7458 data_time: 0.5753 memory: 5967 2022/10/15 03:21:46 - mmengine - INFO - Epoch(val) [52][40/78] eta: 0:00:19 time: 0.5202 data_time: 0.3508 memory: 5967 2022/10/15 03:21:59 - mmengine - INFO - Epoch(val) [52][60/78] eta: 0:00:11 time: 0.6362 data_time: 0.4672 memory: 5967 2022/10/15 03:22:10 - mmengine - INFO - Epoch(val) [52][78/78] acc/top1: 0.6829 acc/top5: 0.8760 acc/mean1: 0.6828 2022/10/15 03:22:27 - mmengine - INFO - Epoch(train) [53][20/940] lr: 1.0000e-03 eta: 7:23:02 time: 0.8270 data_time: 0.2280 memory: 33630 grad_norm: 4.3271 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2782 loss: 1.2782 2022/10/15 03:22:38 - mmengine - INFO - Epoch(train) [53][40/940] lr: 1.0000e-03 eta: 7:22:50 time: 0.5875 data_time: 0.0308 memory: 33630 grad_norm: 4.3046 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3132 loss: 1.3132 2022/10/15 03:22:50 - mmengine - INFO - Epoch(train) [53][60/940] lr: 1.0000e-03 eta: 7:22:39 time: 0.6042 data_time: 0.0376 memory: 33630 grad_norm: 4.2719 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2955 loss: 1.2955 2022/10/15 03:23:02 - mmengine - INFO - Epoch(train) [53][80/940] lr: 1.0000e-03 eta: 7:22:27 time: 0.5865 data_time: 0.0294 memory: 33630 grad_norm: 4.2470 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2861 loss: 1.2861 2022/10/15 03:23:14 - mmengine - INFO - Epoch(train) [53][100/940] lr: 1.0000e-03 eta: 7:22:15 time: 0.5977 data_time: 0.0468 memory: 33630 grad_norm: 4.2523 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2014 loss: 1.2014 2022/10/15 03:23:26 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 03:23:26 - mmengine - INFO - Epoch(train) [53][120/940] lr: 1.0000e-03 eta: 7:22:04 time: 0.5996 data_time: 0.0320 memory: 33630 grad_norm: 4.1876 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2124 loss: 1.2124 2022/10/15 03:23:38 - mmengine - INFO - Epoch(train) [53][140/940] lr: 1.0000e-03 eta: 7:21:52 time: 0.6021 data_time: 0.0396 memory: 33630 grad_norm: 4.2528 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2507 loss: 1.2507 2022/10/15 03:23:50 - mmengine - INFO - Epoch(train) [53][160/940] lr: 1.0000e-03 eta: 7:21:40 time: 0.5927 data_time: 0.0327 memory: 33630 grad_norm: 4.3564 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3287 loss: 1.3287 2022/10/15 03:24:02 - mmengine - INFO - Epoch(train) [53][180/940] lr: 1.0000e-03 eta: 7:21:29 time: 0.5876 data_time: 0.0371 memory: 33630 grad_norm: 4.3219 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2805 loss: 1.2805 2022/10/15 03:24:13 - mmengine - INFO - Epoch(train) [53][200/940] lr: 1.0000e-03 eta: 7:21:17 time: 0.5797 data_time: 0.0317 memory: 33630 grad_norm: 4.3448 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4069 loss: 1.4069 2022/10/15 03:24:25 - mmengine - INFO - Epoch(train) [53][220/940] lr: 1.0000e-03 eta: 7:21:05 time: 0.5880 data_time: 0.0391 memory: 33630 grad_norm: 4.2735 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2830 loss: 1.2830 2022/10/15 03:24:37 - mmengine - INFO - Epoch(train) [53][240/940] lr: 1.0000e-03 eta: 7:20:53 time: 0.5977 data_time: 0.0299 memory: 33630 grad_norm: 4.3230 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3586 loss: 1.3586 2022/10/15 03:24:49 - mmengine - INFO - Epoch(train) [53][260/940] lr: 1.0000e-03 eta: 7:20:41 time: 0.5765 data_time: 0.0442 memory: 33630 grad_norm: 4.2758 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2676 loss: 1.2676 2022/10/15 03:25:00 - mmengine - INFO - Epoch(train) [53][280/940] lr: 1.0000e-03 eta: 7:20:29 time: 0.5765 data_time: 0.0436 memory: 33630 grad_norm: 4.3562 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2088 loss: 1.2088 2022/10/15 03:25:12 - mmengine - INFO - Epoch(train) [53][300/940] lr: 1.0000e-03 eta: 7:20:17 time: 0.5790 data_time: 0.0350 memory: 33630 grad_norm: 4.4154 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2285 loss: 1.2285 2022/10/15 03:25:24 - mmengine - INFO - Epoch(train) [53][320/940] lr: 1.0000e-03 eta: 7:20:05 time: 0.5918 data_time: 0.0319 memory: 33630 grad_norm: 4.2262 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2542 loss: 1.2542 2022/10/15 03:25:35 - mmengine - INFO - Epoch(train) [53][340/940] lr: 1.0000e-03 eta: 7:19:53 time: 0.5730 data_time: 0.0376 memory: 33630 grad_norm: 4.1792 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1970 loss: 1.1970 2022/10/15 03:25:47 - mmengine - INFO - Epoch(train) [53][360/940] lr: 1.0000e-03 eta: 7:19:41 time: 0.5773 data_time: 0.0323 memory: 33630 grad_norm: 4.3411 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3703 loss: 1.3703 2022/10/15 03:25:58 - mmengine - INFO - Epoch(train) [53][380/940] lr: 1.0000e-03 eta: 7:19:29 time: 0.5775 data_time: 0.0344 memory: 33630 grad_norm: 4.2846 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2783 loss: 1.2783 2022/10/15 03:26:10 - mmengine - INFO - Epoch(train) [53][400/940] lr: 1.0000e-03 eta: 7:19:17 time: 0.5876 data_time: 0.0428 memory: 33630 grad_norm: 4.2217 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2297 loss: 1.2297 2022/10/15 03:26:21 - mmengine - INFO - Epoch(train) [53][420/940] lr: 1.0000e-03 eta: 7:19:05 time: 0.5769 data_time: 0.0373 memory: 33630 grad_norm: 4.2664 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2996 loss: 1.2996 2022/10/15 03:26:33 - mmengine - INFO - Epoch(train) [53][440/940] lr: 1.0000e-03 eta: 7:18:53 time: 0.5778 data_time: 0.0447 memory: 33630 grad_norm: 4.3615 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2584 loss: 1.2584 2022/10/15 03:26:45 - mmengine - INFO - Epoch(train) [53][460/940] lr: 1.0000e-03 eta: 7:18:42 time: 0.5970 data_time: 0.0358 memory: 33630 grad_norm: 4.1752 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.3612 loss: 1.3612 2022/10/15 03:26:57 - mmengine - INFO - Epoch(train) [53][480/940] lr: 1.0000e-03 eta: 7:18:30 time: 0.5827 data_time: 0.0366 memory: 33630 grad_norm: 4.3801 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2185 loss: 1.2185 2022/10/15 03:27:08 - mmengine - INFO - Epoch(train) [53][500/940] lr: 1.0000e-03 eta: 7:18:18 time: 0.5812 data_time: 0.0337 memory: 33630 grad_norm: 4.3016 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.2119 loss: 1.2119 2022/10/15 03:27:20 - mmengine - INFO - Epoch(train) [53][520/940] lr: 1.0000e-03 eta: 7:18:06 time: 0.5976 data_time: 0.0414 memory: 33630 grad_norm: 4.3037 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4446 loss: 1.4446 2022/10/15 03:27:32 - mmengine - INFO - Epoch(train) [53][540/940] lr: 1.0000e-03 eta: 7:17:54 time: 0.5799 data_time: 0.0309 memory: 33630 grad_norm: 4.2681 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2545 loss: 1.2545 2022/10/15 03:27:44 - mmengine - INFO - Epoch(train) [53][560/940] lr: 1.0000e-03 eta: 7:17:43 time: 0.5911 data_time: 0.0438 memory: 33630 grad_norm: 4.3718 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3911 loss: 1.3911 2022/10/15 03:27:55 - mmengine - INFO - Epoch(train) [53][580/940] lr: 1.0000e-03 eta: 7:17:31 time: 0.5898 data_time: 0.0310 memory: 33630 grad_norm: 4.2395 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2958 loss: 1.2958 2022/10/15 03:28:07 - mmengine - INFO - Epoch(train) [53][600/940] lr: 1.0000e-03 eta: 7:17:19 time: 0.5881 data_time: 0.0414 memory: 33630 grad_norm: 4.3312 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3077 loss: 1.3077 2022/10/15 03:28:19 - mmengine - INFO - Epoch(train) [53][620/940] lr: 1.0000e-03 eta: 7:17:07 time: 0.5829 data_time: 0.0344 memory: 33630 grad_norm: 4.3196 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1557 loss: 1.1557 2022/10/15 03:28:31 - mmengine - INFO - Epoch(train) [53][640/940] lr: 1.0000e-03 eta: 7:16:55 time: 0.5881 data_time: 0.0407 memory: 33630 grad_norm: 4.2979 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3340 loss: 1.3340 2022/10/15 03:28:42 - mmengine - INFO - Epoch(train) [53][660/940] lr: 1.0000e-03 eta: 7:16:43 time: 0.5764 data_time: 0.0348 memory: 33630 grad_norm: 4.2540 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4020 loss: 1.4020 2022/10/15 03:28:54 - mmengine - INFO - Epoch(train) [53][680/940] lr: 1.0000e-03 eta: 7:16:31 time: 0.5805 data_time: 0.0384 memory: 33630 grad_norm: 4.2925 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4783 loss: 1.4783 2022/10/15 03:29:06 - mmengine - INFO - Epoch(train) [53][700/940] lr: 1.0000e-03 eta: 7:16:20 time: 0.5961 data_time: 0.0305 memory: 33630 grad_norm: 4.3292 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2705 loss: 1.2705 2022/10/15 03:29:18 - mmengine - INFO - Epoch(train) [53][720/940] lr: 1.0000e-03 eta: 7:16:08 time: 0.5926 data_time: 0.0349 memory: 33630 grad_norm: 4.2241 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1744 loss: 1.1744 2022/10/15 03:29:29 - mmengine - INFO - Epoch(train) [53][740/940] lr: 1.0000e-03 eta: 7:15:56 time: 0.5941 data_time: 0.0360 memory: 33630 grad_norm: 4.2400 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1606 loss: 1.1606 2022/10/15 03:29:41 - mmengine - INFO - Epoch(train) [53][760/940] lr: 1.0000e-03 eta: 7:15:45 time: 0.5929 data_time: 0.0397 memory: 33630 grad_norm: 4.3065 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2350 loss: 1.2350 2022/10/15 03:29:53 - mmengine - INFO - Epoch(train) [53][780/940] lr: 1.0000e-03 eta: 7:15:33 time: 0.5869 data_time: 0.0443 memory: 33630 grad_norm: 4.2955 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2056 loss: 1.2056 2022/10/15 03:30:05 - mmengine - INFO - Epoch(train) [53][800/940] lr: 1.0000e-03 eta: 7:15:21 time: 0.5866 data_time: 0.0387 memory: 33630 grad_norm: 4.3516 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2820 loss: 1.2820 2022/10/15 03:30:16 - mmengine - INFO - Epoch(train) [53][820/940] lr: 1.0000e-03 eta: 7:15:09 time: 0.5756 data_time: 0.0427 memory: 33630 grad_norm: 4.2949 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3408 loss: 1.3408 2022/10/15 03:30:28 - mmengine - INFO - Epoch(train) [53][840/940] lr: 1.0000e-03 eta: 7:14:57 time: 0.5737 data_time: 0.0421 memory: 33630 grad_norm: 4.2814 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.2927 loss: 1.2927 2022/10/15 03:30:39 - mmengine - INFO - Epoch(train) [53][860/940] lr: 1.0000e-03 eta: 7:14:45 time: 0.5890 data_time: 0.0336 memory: 33630 grad_norm: 4.3760 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3952 loss: 1.3952 2022/10/15 03:30:51 - mmengine - INFO - Epoch(train) [53][880/940] lr: 1.0000e-03 eta: 7:14:33 time: 0.5857 data_time: 0.0330 memory: 33630 grad_norm: 4.3246 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2926 loss: 1.2926 2022/10/15 03:31:03 - mmengine - INFO - Epoch(train) [53][900/940] lr: 1.0000e-03 eta: 7:14:21 time: 0.5883 data_time: 0.0311 memory: 33630 grad_norm: 4.2995 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2015 loss: 1.2015 2022/10/15 03:31:15 - mmengine - INFO - Epoch(train) [53][920/940] lr: 1.0000e-03 eta: 7:14:10 time: 0.5932 data_time: 0.0404 memory: 33630 grad_norm: 4.2476 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2749 loss: 1.2749 2022/10/15 03:31:26 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 03:31:26 - mmengine - INFO - Epoch(train) [53][940/940] lr: 1.0000e-03 eta: 7:13:57 time: 0.5420 data_time: 0.0310 memory: 33630 grad_norm: 4.5814 top1_acc: 0.4286 top5_acc: 0.4286 loss_cls: 1.3899 loss: 1.3899 2022/10/15 03:31:40 - mmengine - INFO - Epoch(val) [53][20/78] eta: 0:00:41 time: 0.7112 data_time: 0.5406 memory: 5967 2022/10/15 03:31:50 - mmengine - INFO - Epoch(val) [53][40/78] eta: 0:00:18 time: 0.4836 data_time: 0.3156 memory: 5967 2022/10/15 03:32:02 - mmengine - INFO - Epoch(val) [53][60/78] eta: 0:00:11 time: 0.6204 data_time: 0.4496 memory: 5967 2022/10/15 03:32:15 - mmengine - INFO - Epoch(val) [53][78/78] acc/top1: 0.6877 acc/top5: 0.8777 acc/mean1: 0.6876 2022/10/15 03:32:15 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_47.pth is removed 2022/10/15 03:32:15 - mmengine - INFO - The best checkpoint with 0.6877 acc/top1 at 53 epoch is saved to best_acc/top1_epoch_53.pth. 2022/10/15 03:32:32 - mmengine - INFO - Epoch(train) [54][20/940] lr: 1.0000e-03 eta: 7:13:50 time: 0.8553 data_time: 0.3244 memory: 33630 grad_norm: 4.3165 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1791 loss: 1.1791 2022/10/15 03:32:44 - mmengine - INFO - Epoch(train) [54][40/940] lr: 1.0000e-03 eta: 7:13:38 time: 0.5806 data_time: 0.0401 memory: 33630 grad_norm: 4.3099 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2893 loss: 1.2893 2022/10/15 03:32:57 - mmengine - INFO - Epoch(train) [54][60/940] lr: 1.0000e-03 eta: 7:13:27 time: 0.6372 data_time: 0.0935 memory: 33630 grad_norm: 4.2831 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1719 loss: 1.1719 2022/10/15 03:33:08 - mmengine - INFO - Epoch(train) [54][80/940] lr: 1.0000e-03 eta: 7:13:15 time: 0.5786 data_time: 0.0318 memory: 33630 grad_norm: 4.3611 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3711 loss: 1.3711 2022/10/15 03:33:20 - mmengine - INFO - Epoch(train) [54][100/940] lr: 1.0000e-03 eta: 7:13:03 time: 0.5816 data_time: 0.0437 memory: 33630 grad_norm: 4.3428 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3600 loss: 1.3600 2022/10/15 03:33:31 - mmengine - INFO - Epoch(train) [54][120/940] lr: 1.0000e-03 eta: 7:12:51 time: 0.5756 data_time: 0.0321 memory: 33630 grad_norm: 4.3165 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2138 loss: 1.2138 2022/10/15 03:33:43 - mmengine - INFO - Epoch(train) [54][140/940] lr: 1.0000e-03 eta: 7:12:39 time: 0.5824 data_time: 0.0395 memory: 33630 grad_norm: 4.4046 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3770 loss: 1.3770 2022/10/15 03:33:55 - mmengine - INFO - Epoch(train) [54][160/940] lr: 1.0000e-03 eta: 7:12:27 time: 0.5856 data_time: 0.0334 memory: 33630 grad_norm: 4.2607 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.2008 loss: 1.2008 2022/10/15 03:34:06 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 03:34:06 - mmengine - INFO - Epoch(train) [54][180/940] lr: 1.0000e-03 eta: 7:12:15 time: 0.5817 data_time: 0.0368 memory: 33630 grad_norm: 4.3102 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2968 loss: 1.2968 2022/10/15 03:34:18 - mmengine - INFO - Epoch(train) [54][200/940] lr: 1.0000e-03 eta: 7:12:04 time: 0.5911 data_time: 0.0453 memory: 33630 grad_norm: 4.2378 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2501 loss: 1.2501 2022/10/15 03:34:30 - mmengine - INFO - Epoch(train) [54][220/940] lr: 1.0000e-03 eta: 7:11:52 time: 0.5952 data_time: 0.0342 memory: 33630 grad_norm: 4.3568 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.1848 loss: 1.1848 2022/10/15 03:34:42 - mmengine - INFO - Epoch(train) [54][240/940] lr: 1.0000e-03 eta: 7:11:40 time: 0.5856 data_time: 0.0390 memory: 33630 grad_norm: 4.3643 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3412 loss: 1.3412 2022/10/15 03:34:54 - mmengine - INFO - Epoch(train) [54][260/940] lr: 1.0000e-03 eta: 7:11:28 time: 0.5863 data_time: 0.0389 memory: 33630 grad_norm: 4.3072 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3364 loss: 1.3364 2022/10/15 03:35:05 - mmengine - INFO - Epoch(train) [54][280/940] lr: 1.0000e-03 eta: 7:11:16 time: 0.5708 data_time: 0.0385 memory: 33630 grad_norm: 4.3194 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.3200 loss: 1.3200 2022/10/15 03:35:17 - mmengine - INFO - Epoch(train) [54][300/940] lr: 1.0000e-03 eta: 7:11:04 time: 0.5833 data_time: 0.0373 memory: 33630 grad_norm: 4.2395 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1163 loss: 1.1163 2022/10/15 03:35:29 - mmengine - INFO - Epoch(train) [54][320/940] lr: 1.0000e-03 eta: 7:10:52 time: 0.5898 data_time: 0.0339 memory: 33630 grad_norm: 4.2801 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3728 loss: 1.3728 2022/10/15 03:35:40 - mmengine - INFO - Epoch(train) [54][340/940] lr: 1.0000e-03 eta: 7:10:41 time: 0.5839 data_time: 0.0373 memory: 33630 grad_norm: 4.2677 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3356 loss: 1.3356 2022/10/15 03:35:52 - mmengine - INFO - Epoch(train) [54][360/940] lr: 1.0000e-03 eta: 7:10:29 time: 0.5922 data_time: 0.0401 memory: 33630 grad_norm: 4.3065 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2310 loss: 1.2310 2022/10/15 03:36:04 - mmengine - INFO - Epoch(train) [54][380/940] lr: 1.0000e-03 eta: 7:10:17 time: 0.5846 data_time: 0.0317 memory: 33630 grad_norm: 4.3034 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2329 loss: 1.2329 2022/10/15 03:36:15 - mmengine - INFO - Epoch(train) [54][400/940] lr: 1.0000e-03 eta: 7:10:05 time: 0.5792 data_time: 0.0353 memory: 33630 grad_norm: 4.3108 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3043 loss: 1.3043 2022/10/15 03:36:27 - mmengine - INFO - Epoch(train) [54][420/940] lr: 1.0000e-03 eta: 7:09:53 time: 0.5798 data_time: 0.0367 memory: 33630 grad_norm: 4.2774 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2467 loss: 1.2467 2022/10/15 03:36:39 - mmengine - INFO - Epoch(train) [54][440/940] lr: 1.0000e-03 eta: 7:09:41 time: 0.5847 data_time: 0.0383 memory: 33630 grad_norm: 4.3321 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2883 loss: 1.2883 2022/10/15 03:36:50 - mmengine - INFO - Epoch(train) [54][460/940] lr: 1.0000e-03 eta: 7:09:29 time: 0.5756 data_time: 0.0329 memory: 33630 grad_norm: 4.2754 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.2752 loss: 1.2752 2022/10/15 03:37:02 - mmengine - INFO - Epoch(train) [54][480/940] lr: 1.0000e-03 eta: 7:09:17 time: 0.5805 data_time: 0.0371 memory: 33630 grad_norm: 4.2484 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1957 loss: 1.1957 2022/10/15 03:37:13 - mmengine - INFO - Epoch(train) [54][500/940] lr: 1.0000e-03 eta: 7:09:05 time: 0.5844 data_time: 0.0403 memory: 33630 grad_norm: 4.2978 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3923 loss: 1.3923 2022/10/15 03:37:25 - mmengine - INFO - Epoch(train) [54][520/940] lr: 1.0000e-03 eta: 7:08:54 time: 0.5926 data_time: 0.0342 memory: 33630 grad_norm: 4.2681 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3490 loss: 1.3490 2022/10/15 03:37:37 - mmengine - INFO - Epoch(train) [54][540/940] lr: 1.0000e-03 eta: 7:08:41 time: 0.5725 data_time: 0.0342 memory: 33630 grad_norm: 4.3031 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.3187 loss: 1.3187 2022/10/15 03:37:48 - mmengine - INFO - Epoch(train) [54][560/940] lr: 1.0000e-03 eta: 7:08:30 time: 0.5846 data_time: 0.0433 memory: 33630 grad_norm: 4.2913 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2596 loss: 1.2596 2022/10/15 03:38:00 - mmengine - INFO - Epoch(train) [54][580/940] lr: 1.0000e-03 eta: 7:08:18 time: 0.5801 data_time: 0.0320 memory: 33630 grad_norm: 4.2741 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2606 loss: 1.2606 2022/10/15 03:38:12 - mmengine - INFO - Epoch(train) [54][600/940] lr: 1.0000e-03 eta: 7:08:06 time: 0.5927 data_time: 0.0327 memory: 33630 grad_norm: 4.3529 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2044 loss: 1.2044 2022/10/15 03:38:23 - mmengine - INFO - Epoch(train) [54][620/940] lr: 1.0000e-03 eta: 7:07:54 time: 0.5803 data_time: 0.0507 memory: 33630 grad_norm: 4.2536 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2176 loss: 1.2176 2022/10/15 03:38:35 - mmengine - INFO - Epoch(train) [54][640/940] lr: 1.0000e-03 eta: 7:07:42 time: 0.5952 data_time: 0.0449 memory: 33630 grad_norm: 4.3424 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3007 loss: 1.3007 2022/10/15 03:38:47 - mmengine - INFO - Epoch(train) [54][660/940] lr: 1.0000e-03 eta: 7:07:30 time: 0.5821 data_time: 0.0420 memory: 33630 grad_norm: 4.4033 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4492 loss: 1.4492 2022/10/15 03:38:59 - mmengine - INFO - Epoch(train) [54][680/940] lr: 1.0000e-03 eta: 7:07:19 time: 0.5911 data_time: 0.0348 memory: 33630 grad_norm: 4.3284 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3045 loss: 1.3045 2022/10/15 03:39:11 - mmengine - INFO - Epoch(train) [54][700/940] lr: 1.0000e-03 eta: 7:07:07 time: 0.5849 data_time: 0.0422 memory: 33630 grad_norm: 4.2857 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2860 loss: 1.2860 2022/10/15 03:39:22 - mmengine - INFO - Epoch(train) [54][720/940] lr: 1.0000e-03 eta: 7:06:55 time: 0.5856 data_time: 0.0313 memory: 33630 grad_norm: 4.2195 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2753 loss: 1.2753 2022/10/15 03:39:34 - mmengine - INFO - Epoch(train) [54][740/940] lr: 1.0000e-03 eta: 7:06:43 time: 0.5800 data_time: 0.0410 memory: 33630 grad_norm: 4.2851 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.1821 loss: 1.1821 2022/10/15 03:39:46 - mmengine - INFO - Epoch(train) [54][760/940] lr: 1.0000e-03 eta: 7:06:31 time: 0.5871 data_time: 0.0366 memory: 33630 grad_norm: 4.3409 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3406 loss: 1.3406 2022/10/15 03:39:57 - mmengine - INFO - Epoch(train) [54][780/940] lr: 1.0000e-03 eta: 7:06:19 time: 0.5771 data_time: 0.0391 memory: 33630 grad_norm: 4.3145 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3090 loss: 1.3090 2022/10/15 03:40:09 - mmengine - INFO - Epoch(train) [54][800/940] lr: 1.0000e-03 eta: 7:06:07 time: 0.5766 data_time: 0.0408 memory: 33630 grad_norm: 4.3636 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1778 loss: 1.1778 2022/10/15 03:40:20 - mmengine - INFO - Epoch(train) [54][820/940] lr: 1.0000e-03 eta: 7:05:55 time: 0.5877 data_time: 0.0380 memory: 33630 grad_norm: 4.3242 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.1953 loss: 1.1953 2022/10/15 03:40:32 - mmengine - INFO - Epoch(train) [54][840/940] lr: 1.0000e-03 eta: 7:05:43 time: 0.5902 data_time: 0.0345 memory: 33630 grad_norm: 4.3122 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4332 loss: 1.4332 2022/10/15 03:40:44 - mmengine - INFO - Epoch(train) [54][860/940] lr: 1.0000e-03 eta: 7:05:32 time: 0.5886 data_time: 0.0331 memory: 33630 grad_norm: 4.3340 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2144 loss: 1.2144 2022/10/15 03:40:56 - mmengine - INFO - Epoch(train) [54][880/940] lr: 1.0000e-03 eta: 7:05:20 time: 0.5883 data_time: 0.0331 memory: 33630 grad_norm: 4.2942 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3919 loss: 1.3919 2022/10/15 03:41:07 - mmengine - INFO - Epoch(train) [54][900/940] lr: 1.0000e-03 eta: 7:05:08 time: 0.5815 data_time: 0.0309 memory: 33630 grad_norm: 4.2223 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1749 loss: 1.1749 2022/10/15 03:41:19 - mmengine - INFO - Epoch(train) [54][920/940] lr: 1.0000e-03 eta: 7:04:56 time: 0.5724 data_time: 0.0414 memory: 33630 grad_norm: 4.3065 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.3327 loss: 1.3327 2022/10/15 03:41:30 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 03:41:30 - mmengine - INFO - Epoch(train) [54][940/940] lr: 1.0000e-03 eta: 7:04:43 time: 0.5444 data_time: 0.0342 memory: 33630 grad_norm: 4.8018 top1_acc: 0.2857 top5_acc: 0.7143 loss_cls: 1.3543 loss: 1.3543 2022/10/15 03:41:30 - mmengine - INFO - Saving checkpoint at 54 epochs 2022/10/15 03:41:45 - mmengine - INFO - Epoch(val) [54][20/78] eta: 0:00:40 time: 0.6919 data_time: 0.5207 memory: 5967 2022/10/15 03:41:55 - mmengine - INFO - Epoch(val) [54][40/78] eta: 0:00:19 time: 0.5053 data_time: 0.3369 memory: 5967 2022/10/15 03:42:08 - mmengine - INFO - Epoch(val) [54][60/78] eta: 0:00:11 time: 0.6591 data_time: 0.4902 memory: 5967 2022/10/15 03:42:20 - mmengine - INFO - Epoch(val) [54][78/78] acc/top1: 0.6849 acc/top5: 0.8768 acc/mean1: 0.6848 2022/10/15 03:42:37 - mmengine - INFO - Epoch(train) [55][20/940] lr: 1.0000e-03 eta: 7:04:36 time: 0.8333 data_time: 0.2309 memory: 33630 grad_norm: 4.2904 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.1798 loss: 1.1798 2022/10/15 03:42:48 - mmengine - INFO - Epoch(train) [55][40/940] lr: 1.0000e-03 eta: 7:04:24 time: 0.5901 data_time: 0.0359 memory: 33630 grad_norm: 4.2979 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2468 loss: 1.2468 2022/10/15 03:43:00 - mmengine - INFO - Epoch(train) [55][60/940] lr: 1.0000e-03 eta: 7:04:12 time: 0.5739 data_time: 0.0394 memory: 33630 grad_norm: 4.2282 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3041 loss: 1.3041 2022/10/15 03:43:12 - mmengine - INFO - Epoch(train) [55][80/940] lr: 1.0000e-03 eta: 7:04:00 time: 0.5955 data_time: 0.0353 memory: 33630 grad_norm: 4.3263 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.2075 loss: 1.2075 2022/10/15 03:43:23 - mmengine - INFO - Epoch(train) [55][100/940] lr: 1.0000e-03 eta: 7:03:48 time: 0.5779 data_time: 0.0423 memory: 33630 grad_norm: 4.4683 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2957 loss: 1.2957 2022/10/15 03:43:36 - mmengine - INFO - Epoch(train) [55][120/940] lr: 1.0000e-03 eta: 7:03:37 time: 0.6212 data_time: 0.0349 memory: 33630 grad_norm: 4.3316 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2780 loss: 1.2780 2022/10/15 03:43:48 - mmengine - INFO - Epoch(train) [55][140/940] lr: 1.0000e-03 eta: 7:03:25 time: 0.5856 data_time: 0.0330 memory: 33630 grad_norm: 4.3536 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4167 loss: 1.4167 2022/10/15 03:44:00 - mmengine - INFO - Epoch(train) [55][160/940] lr: 1.0000e-03 eta: 7:03:13 time: 0.5993 data_time: 0.0416 memory: 33630 grad_norm: 4.3658 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3472 loss: 1.3472 2022/10/15 03:44:12 - mmengine - INFO - Epoch(train) [55][180/940] lr: 1.0000e-03 eta: 7:03:02 time: 0.6118 data_time: 0.0344 memory: 33630 grad_norm: 4.3512 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2015 loss: 1.2015 2022/10/15 03:44:24 - mmengine - INFO - Epoch(train) [55][200/940] lr: 1.0000e-03 eta: 7:02:50 time: 0.5966 data_time: 0.0375 memory: 33630 grad_norm: 4.3563 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2241 loss: 1.2241 2022/10/15 03:44:35 - mmengine - INFO - Epoch(train) [55][220/940] lr: 1.0000e-03 eta: 7:02:39 time: 0.5868 data_time: 0.0366 memory: 33630 grad_norm: 4.3220 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.1806 loss: 1.1806 2022/10/15 03:44:47 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 03:44:47 - mmengine - INFO - Epoch(train) [55][240/940] lr: 1.0000e-03 eta: 7:02:27 time: 0.5847 data_time: 0.0387 memory: 33630 grad_norm: 4.3030 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2549 loss: 1.2549 2022/10/15 03:44:59 - mmengine - INFO - Epoch(train) [55][260/940] lr: 1.0000e-03 eta: 7:02:15 time: 0.5914 data_time: 0.0381 memory: 33630 grad_norm: 4.3273 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2811 loss: 1.2811 2022/10/15 03:45:11 - mmengine - INFO - Epoch(train) [55][280/940] lr: 1.0000e-03 eta: 7:02:03 time: 0.5872 data_time: 0.0352 memory: 33630 grad_norm: 4.4772 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3305 loss: 1.3305 2022/10/15 03:45:22 - mmengine - INFO - Epoch(train) [55][300/940] lr: 1.0000e-03 eta: 7:01:51 time: 0.5778 data_time: 0.0429 memory: 33630 grad_norm: 4.4637 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2983 loss: 1.2983 2022/10/15 03:45:34 - mmengine - INFO - Epoch(train) [55][320/940] lr: 1.0000e-03 eta: 7:01:39 time: 0.5884 data_time: 0.0407 memory: 33630 grad_norm: 4.2303 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2182 loss: 1.2182 2022/10/15 03:45:46 - mmengine - INFO - Epoch(train) [55][340/940] lr: 1.0000e-03 eta: 7:01:28 time: 0.5913 data_time: 0.0410 memory: 33630 grad_norm: 4.3433 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2806 loss: 1.2806 2022/10/15 03:45:57 - mmengine - INFO - Epoch(train) [55][360/940] lr: 1.0000e-03 eta: 7:01:16 time: 0.5758 data_time: 0.0327 memory: 33630 grad_norm: 4.3919 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2522 loss: 1.2522 2022/10/15 03:46:09 - mmengine - INFO - Epoch(train) [55][380/940] lr: 1.0000e-03 eta: 7:01:04 time: 0.5822 data_time: 0.0332 memory: 33630 grad_norm: 4.3683 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.1974 loss: 1.1974 2022/10/15 03:46:21 - mmengine - INFO - Epoch(train) [55][400/940] lr: 1.0000e-03 eta: 7:00:52 time: 0.5850 data_time: 0.0438 memory: 33630 grad_norm: 4.3130 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3506 loss: 1.3506 2022/10/15 03:46:33 - mmengine - INFO - Epoch(train) [55][420/940] lr: 1.0000e-03 eta: 7:00:40 time: 0.5903 data_time: 0.0382 memory: 33630 grad_norm: 4.3636 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2470 loss: 1.2470 2022/10/15 03:46:44 - mmengine - INFO - Epoch(train) [55][440/940] lr: 1.0000e-03 eta: 7:00:28 time: 0.5708 data_time: 0.0360 memory: 33630 grad_norm: 4.3200 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1555 loss: 1.1555 2022/10/15 03:46:56 - mmengine - INFO - Epoch(train) [55][460/940] lr: 1.0000e-03 eta: 7:00:16 time: 0.5918 data_time: 0.0387 memory: 33630 grad_norm: 4.3504 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2063 loss: 1.2063 2022/10/15 03:47:08 - mmengine - INFO - Epoch(train) [55][480/940] lr: 1.0000e-03 eta: 7:00:05 time: 0.6012 data_time: 0.0400 memory: 33630 grad_norm: 4.4034 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2385 loss: 1.2385 2022/10/15 03:47:20 - mmengine - INFO - Epoch(train) [55][500/940] lr: 1.0000e-03 eta: 6:59:53 time: 0.5927 data_time: 0.0359 memory: 33630 grad_norm: 4.3327 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4047 loss: 1.4047 2022/10/15 03:47:31 - mmengine - INFO - Epoch(train) [55][520/940] lr: 1.0000e-03 eta: 6:59:41 time: 0.5815 data_time: 0.0340 memory: 33630 grad_norm: 4.3010 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3217 loss: 1.3217 2022/10/15 03:47:43 - mmengine - INFO - Epoch(train) [55][540/940] lr: 1.0000e-03 eta: 6:59:29 time: 0.5752 data_time: 0.0368 memory: 33630 grad_norm: 4.3723 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1259 loss: 1.1259 2022/10/15 03:47:54 - mmengine - INFO - Epoch(train) [55][560/940] lr: 1.0000e-03 eta: 6:59:17 time: 0.5768 data_time: 0.0363 memory: 33630 grad_norm: 4.3184 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2957 loss: 1.2957 2022/10/15 03:48:06 - mmengine - INFO - Epoch(train) [55][580/940] lr: 1.0000e-03 eta: 6:59:05 time: 0.5959 data_time: 0.0406 memory: 33630 grad_norm: 4.4021 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2440 loss: 1.2440 2022/10/15 03:48:18 - mmengine - INFO - Epoch(train) [55][600/940] lr: 1.0000e-03 eta: 6:58:53 time: 0.5817 data_time: 0.0377 memory: 33630 grad_norm: 4.2545 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3078 loss: 1.3078 2022/10/15 03:48:29 - mmengine - INFO - Epoch(train) [55][620/940] lr: 1.0000e-03 eta: 6:58:41 time: 0.5771 data_time: 0.0332 memory: 33630 grad_norm: 4.3042 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1838 loss: 1.1838 2022/10/15 03:48:41 - mmengine - INFO - Epoch(train) [55][640/940] lr: 1.0000e-03 eta: 6:58:29 time: 0.5839 data_time: 0.0347 memory: 33630 grad_norm: 4.3605 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1434 loss: 1.1434 2022/10/15 03:48:53 - mmengine - INFO - Epoch(train) [55][660/940] lr: 1.0000e-03 eta: 6:58:17 time: 0.5793 data_time: 0.0295 memory: 33630 grad_norm: 4.3568 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3558 loss: 1.3558 2022/10/15 03:49:04 - mmengine - INFO - Epoch(train) [55][680/940] lr: 1.0000e-03 eta: 6:58:05 time: 0.5777 data_time: 0.0359 memory: 33630 grad_norm: 4.3241 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2240 loss: 1.2240 2022/10/15 03:49:16 - mmengine - INFO - Epoch(train) [55][700/940] lr: 1.0000e-03 eta: 6:57:54 time: 0.5868 data_time: 0.0356 memory: 33630 grad_norm: 4.3261 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2922 loss: 1.2922 2022/10/15 03:49:28 - mmengine - INFO - Epoch(train) [55][720/940] lr: 1.0000e-03 eta: 6:57:42 time: 0.5871 data_time: 0.0390 memory: 33630 grad_norm: 4.2699 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2936 loss: 1.2936 2022/10/15 03:49:39 - mmengine - INFO - Epoch(train) [55][740/940] lr: 1.0000e-03 eta: 6:57:30 time: 0.5851 data_time: 0.0446 memory: 33630 grad_norm: 4.4312 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3726 loss: 1.3726 2022/10/15 03:49:51 - mmengine - INFO - Epoch(train) [55][760/940] lr: 1.0000e-03 eta: 6:57:18 time: 0.5819 data_time: 0.0321 memory: 33630 grad_norm: 4.3302 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1356 loss: 1.1356 2022/10/15 03:50:03 - mmengine - INFO - Epoch(train) [55][780/940] lr: 1.0000e-03 eta: 6:57:06 time: 0.5755 data_time: 0.0335 memory: 33630 grad_norm: 4.2967 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3122 loss: 1.3122 2022/10/15 03:50:14 - mmengine - INFO - Epoch(train) [55][800/940] lr: 1.0000e-03 eta: 6:56:54 time: 0.5879 data_time: 0.0454 memory: 33630 grad_norm: 4.4201 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2544 loss: 1.2544 2022/10/15 03:50:26 - mmengine - INFO - Epoch(train) [55][820/940] lr: 1.0000e-03 eta: 6:56:42 time: 0.5885 data_time: 0.0460 memory: 33630 grad_norm: 4.4287 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3669 loss: 1.3669 2022/10/15 03:50:38 - mmengine - INFO - Epoch(train) [55][840/940] lr: 1.0000e-03 eta: 6:56:30 time: 0.5764 data_time: 0.0327 memory: 33630 grad_norm: 4.3433 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2846 loss: 1.2846 2022/10/15 03:50:49 - mmengine - INFO - Epoch(train) [55][860/940] lr: 1.0000e-03 eta: 6:56:18 time: 0.5825 data_time: 0.0385 memory: 33630 grad_norm: 4.3690 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3622 loss: 1.3622 2022/10/15 03:51:01 - mmengine - INFO - Epoch(train) [55][880/940] lr: 1.0000e-03 eta: 6:56:07 time: 0.5903 data_time: 0.0358 memory: 33630 grad_norm: 4.5095 top1_acc: 0.5938 top5_acc: 0.9688 loss_cls: 1.2433 loss: 1.2433 2022/10/15 03:51:13 - mmengine - INFO - Epoch(train) [55][900/940] lr: 1.0000e-03 eta: 6:55:55 time: 0.5818 data_time: 0.0355 memory: 33630 grad_norm: 4.4091 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3801 loss: 1.3801 2022/10/15 03:51:24 - mmengine - INFO - Epoch(train) [55][920/940] lr: 1.0000e-03 eta: 6:55:43 time: 0.5813 data_time: 0.0448 memory: 33630 grad_norm: 4.3083 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2900 loss: 1.2900 2022/10/15 03:51:35 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 03:51:35 - mmengine - INFO - Epoch(train) [55][940/940] lr: 1.0000e-03 eta: 6:55:30 time: 0.5418 data_time: 0.0301 memory: 33630 grad_norm: 4.6121 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.2464 loss: 1.2464 2022/10/15 03:51:50 - mmengine - INFO - Epoch(val) [55][20/78] eta: 0:00:41 time: 0.7128 data_time: 0.5408 memory: 5967 2022/10/15 03:52:00 - mmengine - INFO - Epoch(val) [55][40/78] eta: 0:00:19 time: 0.5035 data_time: 0.3347 memory: 5967 2022/10/15 03:52:13 - mmengine - INFO - Epoch(val) [55][60/78] eta: 0:00:12 time: 0.6741 data_time: 0.5048 memory: 5967 2022/10/15 03:52:24 - mmengine - INFO - Epoch(val) [55][78/78] acc/top1: 0.6852 acc/top5: 0.8767 acc/mean1: 0.6850 2022/10/15 03:52:40 - mmengine - INFO - Epoch(train) [56][20/940] lr: 1.0000e-03 eta: 6:55:22 time: 0.8243 data_time: 0.2512 memory: 33630 grad_norm: 4.4162 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1850 loss: 1.1850 2022/10/15 03:52:52 - mmengine - INFO - Epoch(train) [56][40/940] lr: 1.0000e-03 eta: 6:55:10 time: 0.5773 data_time: 0.0315 memory: 33630 grad_norm: 4.3679 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3313 loss: 1.3313 2022/10/15 03:53:04 - mmengine - INFO - Epoch(train) [56][60/940] lr: 1.0000e-03 eta: 6:54:59 time: 0.6038 data_time: 0.0393 memory: 33630 grad_norm: 4.3028 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2393 loss: 1.2393 2022/10/15 03:53:15 - mmengine - INFO - Epoch(train) [56][80/940] lr: 1.0000e-03 eta: 6:54:47 time: 0.5770 data_time: 0.0321 memory: 33630 grad_norm: 4.2848 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2787 loss: 1.2787 2022/10/15 03:53:27 - mmengine - INFO - Epoch(train) [56][100/940] lr: 1.0000e-03 eta: 6:54:35 time: 0.5809 data_time: 0.0326 memory: 33630 grad_norm: 4.3396 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1558 loss: 1.1558 2022/10/15 03:53:39 - mmengine - INFO - Epoch(train) [56][120/940] lr: 1.0000e-03 eta: 6:54:23 time: 0.5913 data_time: 0.0372 memory: 33630 grad_norm: 4.3896 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3661 loss: 1.3661 2022/10/15 03:53:51 - mmengine - INFO - Epoch(train) [56][140/940] lr: 1.0000e-03 eta: 6:54:11 time: 0.5867 data_time: 0.0377 memory: 33630 grad_norm: 4.3263 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2959 loss: 1.2959 2022/10/15 03:54:02 - mmengine - INFO - Epoch(train) [56][160/940] lr: 1.0000e-03 eta: 6:54:00 time: 0.5922 data_time: 0.0451 memory: 33630 grad_norm: 4.2928 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.2264 loss: 1.2264 2022/10/15 03:54:14 - mmengine - INFO - Epoch(train) [56][180/940] lr: 1.0000e-03 eta: 6:53:48 time: 0.5896 data_time: 0.0384 memory: 33630 grad_norm: 4.4163 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2404 loss: 1.2404 2022/10/15 03:54:26 - mmengine - INFO - Epoch(train) [56][200/940] lr: 1.0000e-03 eta: 6:53:36 time: 0.5795 data_time: 0.0392 memory: 33630 grad_norm: 4.3525 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3308 loss: 1.3308 2022/10/15 03:54:38 - mmengine - INFO - Epoch(train) [56][220/940] lr: 1.0000e-03 eta: 6:53:24 time: 0.5903 data_time: 0.0373 memory: 33630 grad_norm: 4.3053 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.3271 loss: 1.3271 2022/10/15 03:54:49 - mmengine - INFO - Epoch(train) [56][240/940] lr: 1.0000e-03 eta: 6:53:12 time: 0.5829 data_time: 0.0438 memory: 33630 grad_norm: 4.3970 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1893 loss: 1.1893 2022/10/15 03:55:01 - mmengine - INFO - Epoch(train) [56][260/940] lr: 1.0000e-03 eta: 6:53:00 time: 0.5824 data_time: 0.0380 memory: 33630 grad_norm: 4.3084 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2308 loss: 1.2308 2022/10/15 03:55:13 - mmengine - INFO - Epoch(train) [56][280/940] lr: 1.0000e-03 eta: 6:52:48 time: 0.5891 data_time: 0.0399 memory: 33630 grad_norm: 4.2752 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2934 loss: 1.2934 2022/10/15 03:55:25 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 03:55:25 - mmengine - INFO - Epoch(train) [56][300/940] lr: 1.0000e-03 eta: 6:52:37 time: 0.5884 data_time: 0.0343 memory: 33630 grad_norm: 4.4111 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2772 loss: 1.2772 2022/10/15 03:55:36 - mmengine - INFO - Epoch(train) [56][320/940] lr: 1.0000e-03 eta: 6:52:25 time: 0.5935 data_time: 0.0341 memory: 33630 grad_norm: 4.4213 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2899 loss: 1.2899 2022/10/15 03:55:48 - mmengine - INFO - Epoch(train) [56][340/940] lr: 1.0000e-03 eta: 6:52:13 time: 0.5839 data_time: 0.0348 memory: 33630 grad_norm: 4.3629 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3231 loss: 1.3231 2022/10/15 03:56:00 - mmengine - INFO - Epoch(train) [56][360/940] lr: 1.0000e-03 eta: 6:52:01 time: 0.5909 data_time: 0.0389 memory: 33630 grad_norm: 4.3721 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2275 loss: 1.2275 2022/10/15 03:56:12 - mmengine - INFO - Epoch(train) [56][380/940] lr: 1.0000e-03 eta: 6:51:49 time: 0.5847 data_time: 0.0466 memory: 33630 grad_norm: 4.3034 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2554 loss: 1.2554 2022/10/15 03:56:23 - mmengine - INFO - Epoch(train) [56][400/940] lr: 1.0000e-03 eta: 6:51:38 time: 0.5915 data_time: 0.0363 memory: 33630 grad_norm: 4.3338 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3661 loss: 1.3661 2022/10/15 03:56:35 - mmengine - INFO - Epoch(train) [56][420/940] lr: 1.0000e-03 eta: 6:51:26 time: 0.5775 data_time: 0.0470 memory: 33630 grad_norm: 4.3655 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2460 loss: 1.2460 2022/10/15 03:56:47 - mmengine - INFO - Epoch(train) [56][440/940] lr: 1.0000e-03 eta: 6:51:14 time: 0.5818 data_time: 0.0389 memory: 33630 grad_norm: 4.2814 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2898 loss: 1.2898 2022/10/15 03:56:58 - mmengine - INFO - Epoch(train) [56][460/940] lr: 1.0000e-03 eta: 6:51:02 time: 0.5808 data_time: 0.0369 memory: 33630 grad_norm: 4.3215 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3508 loss: 1.3508 2022/10/15 03:57:10 - mmengine - INFO - Epoch(train) [56][480/940] lr: 1.0000e-03 eta: 6:50:50 time: 0.5715 data_time: 0.0341 memory: 33630 grad_norm: 4.4098 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1856 loss: 1.1856 2022/10/15 03:57:21 - mmengine - INFO - Epoch(train) [56][500/940] lr: 1.0000e-03 eta: 6:50:38 time: 0.5901 data_time: 0.0330 memory: 33630 grad_norm: 4.4355 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3009 loss: 1.3009 2022/10/15 03:57:33 - mmengine - INFO - Epoch(train) [56][520/940] lr: 1.0000e-03 eta: 6:50:26 time: 0.5893 data_time: 0.0363 memory: 33630 grad_norm: 4.3676 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2598 loss: 1.2598 2022/10/15 03:57:45 - mmengine - INFO - Epoch(train) [56][540/940] lr: 1.0000e-03 eta: 6:50:15 time: 0.5975 data_time: 0.0388 memory: 33630 grad_norm: 4.5165 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3612 loss: 1.3612 2022/10/15 03:57:57 - mmengine - INFO - Epoch(train) [56][560/940] lr: 1.0000e-03 eta: 6:50:03 time: 0.5858 data_time: 0.0396 memory: 33630 grad_norm: 4.4769 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4561 loss: 1.4561 2022/10/15 03:58:09 - mmengine - INFO - Epoch(train) [56][580/940] lr: 1.0000e-03 eta: 6:49:51 time: 0.5840 data_time: 0.0352 memory: 33630 grad_norm: 4.3802 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3064 loss: 1.3064 2022/10/15 03:58:20 - mmengine - INFO - Epoch(train) [56][600/940] lr: 1.0000e-03 eta: 6:49:39 time: 0.5718 data_time: 0.0354 memory: 33630 grad_norm: 4.3629 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2649 loss: 1.2649 2022/10/15 03:58:32 - mmengine - INFO - Epoch(train) [56][620/940] lr: 1.0000e-03 eta: 6:49:27 time: 0.5831 data_time: 0.0314 memory: 33630 grad_norm: 4.2916 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2759 loss: 1.2759 2022/10/15 03:58:43 - mmengine - INFO - Epoch(train) [56][640/940] lr: 1.0000e-03 eta: 6:49:15 time: 0.5790 data_time: 0.0357 memory: 33630 grad_norm: 4.4314 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2499 loss: 1.2499 2022/10/15 03:58:55 - mmengine - INFO - Epoch(train) [56][660/940] lr: 1.0000e-03 eta: 6:49:03 time: 0.5873 data_time: 0.0413 memory: 33630 grad_norm: 4.3737 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3406 loss: 1.3406 2022/10/15 03:59:06 - mmengine - INFO - Epoch(train) [56][680/940] lr: 1.0000e-03 eta: 6:48:51 time: 0.5724 data_time: 0.0319 memory: 33630 grad_norm: 4.3955 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2497 loss: 1.2497 2022/10/15 03:59:18 - mmengine - INFO - Epoch(train) [56][700/940] lr: 1.0000e-03 eta: 6:48:39 time: 0.5959 data_time: 0.0398 memory: 33630 grad_norm: 4.3403 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2433 loss: 1.2433 2022/10/15 03:59:30 - mmengine - INFO - Epoch(train) [56][720/940] lr: 1.0000e-03 eta: 6:48:28 time: 0.5933 data_time: 0.0409 memory: 33630 grad_norm: 4.4649 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2538 loss: 1.2538 2022/10/15 03:59:42 - mmengine - INFO - Epoch(train) [56][740/940] lr: 1.0000e-03 eta: 6:48:16 time: 0.5909 data_time: 0.0426 memory: 33630 grad_norm: 4.3261 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4329 loss: 1.4329 2022/10/15 03:59:54 - mmengine - INFO - Epoch(train) [56][760/940] lr: 1.0000e-03 eta: 6:48:04 time: 0.5842 data_time: 0.0309 memory: 33630 grad_norm: 4.3123 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3491 loss: 1.3491 2022/10/15 04:00:05 - mmengine - INFO - Epoch(train) [56][780/940] lr: 1.0000e-03 eta: 6:47:52 time: 0.5782 data_time: 0.0435 memory: 33630 grad_norm: 4.4065 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2887 loss: 1.2887 2022/10/15 04:00:17 - mmengine - INFO - Epoch(train) [56][800/940] lr: 1.0000e-03 eta: 6:47:40 time: 0.5801 data_time: 0.0400 memory: 33630 grad_norm: 4.2540 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1913 loss: 1.1913 2022/10/15 04:00:29 - mmengine - INFO - Epoch(train) [56][820/940] lr: 1.0000e-03 eta: 6:47:28 time: 0.5777 data_time: 0.0315 memory: 33630 grad_norm: 4.4498 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3231 loss: 1.3231 2022/10/15 04:00:40 - mmengine - INFO - Epoch(train) [56][840/940] lr: 1.0000e-03 eta: 6:47:16 time: 0.5918 data_time: 0.0351 memory: 33630 grad_norm: 4.3793 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3480 loss: 1.3480 2022/10/15 04:00:52 - mmengine - INFO - Epoch(train) [56][860/940] lr: 1.0000e-03 eta: 6:47:04 time: 0.5794 data_time: 0.0332 memory: 33630 grad_norm: 4.4308 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2636 loss: 1.2636 2022/10/15 04:01:04 - mmengine - INFO - Epoch(train) [56][880/940] lr: 1.0000e-03 eta: 6:46:52 time: 0.5790 data_time: 0.0386 memory: 33630 grad_norm: 4.3324 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3216 loss: 1.3216 2022/10/15 04:01:15 - mmengine - INFO - Epoch(train) [56][900/940] lr: 1.0000e-03 eta: 6:46:40 time: 0.5738 data_time: 0.0362 memory: 33630 grad_norm: 4.3286 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.2649 loss: 1.2649 2022/10/15 04:01:27 - mmengine - INFO - Epoch(train) [56][920/940] lr: 1.0000e-03 eta: 6:46:29 time: 0.5954 data_time: 0.0475 memory: 33630 grad_norm: 4.3545 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2576 loss: 1.2576 2022/10/15 04:01:38 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 04:01:38 - mmengine - INFO - Epoch(train) [56][940/940] lr: 1.0000e-03 eta: 6:46:16 time: 0.5439 data_time: 0.0389 memory: 33630 grad_norm: 4.7440 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.4549 loss: 1.4549 2022/10/15 04:01:52 - mmengine - INFO - Epoch(val) [56][20/78] eta: 0:00:41 time: 0.7227 data_time: 0.5532 memory: 5967 2022/10/15 04:02:03 - mmengine - INFO - Epoch(val) [56][40/78] eta: 0:00:19 time: 0.5237 data_time: 0.3545 memory: 5967 2022/10/15 04:02:16 - mmengine - INFO - Epoch(val) [56][60/78] eta: 0:00:11 time: 0.6508 data_time: 0.4811 memory: 5967 2022/10/15 04:02:28 - mmengine - INFO - Epoch(val) [56][78/78] acc/top1: 0.6894 acc/top5: 0.8779 acc/mean1: 0.6893 2022/10/15 04:02:28 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_53.pth is removed 2022/10/15 04:02:28 - mmengine - INFO - The best checkpoint with 0.6894 acc/top1 at 56 epoch is saved to best_acc/top1_epoch_56.pth. 2022/10/15 04:02:45 - mmengine - INFO - Epoch(train) [57][20/940] lr: 1.0000e-03 eta: 6:46:08 time: 0.8287 data_time: 0.2751 memory: 33630 grad_norm: 4.4094 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3408 loss: 1.3408 2022/10/15 04:02:57 - mmengine - INFO - Epoch(train) [57][40/940] lr: 1.0000e-03 eta: 6:45:56 time: 0.5885 data_time: 0.0322 memory: 33630 grad_norm: 4.2477 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2999 loss: 1.2999 2022/10/15 04:03:09 - mmengine - INFO - Epoch(train) [57][60/940] lr: 1.0000e-03 eta: 6:45:45 time: 0.5948 data_time: 0.0398 memory: 33630 grad_norm: 4.3645 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2168 loss: 1.2168 2022/10/15 04:03:20 - mmengine - INFO - Epoch(train) [57][80/940] lr: 1.0000e-03 eta: 6:45:33 time: 0.5760 data_time: 0.0312 memory: 33630 grad_norm: 4.4065 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3104 loss: 1.3104 2022/10/15 04:03:32 - mmengine - INFO - Epoch(train) [57][100/940] lr: 1.0000e-03 eta: 6:45:21 time: 0.5990 data_time: 0.0389 memory: 33630 grad_norm: 4.4683 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2223 loss: 1.2223 2022/10/15 04:03:44 - mmengine - INFO - Epoch(train) [57][120/940] lr: 1.0000e-03 eta: 6:45:09 time: 0.5893 data_time: 0.0403 memory: 33630 grad_norm: 4.2678 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2319 loss: 1.2319 2022/10/15 04:03:56 - mmengine - INFO - Epoch(train) [57][140/940] lr: 1.0000e-03 eta: 6:44:57 time: 0.5898 data_time: 0.0322 memory: 33630 grad_norm: 4.2692 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2469 loss: 1.2469 2022/10/15 04:04:07 - mmengine - INFO - Epoch(train) [57][160/940] lr: 1.0000e-03 eta: 6:44:46 time: 0.5821 data_time: 0.0331 memory: 33630 grad_norm: 4.3502 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1681 loss: 1.1681 2022/10/15 04:04:19 - mmengine - INFO - Epoch(train) [57][180/940] lr: 1.0000e-03 eta: 6:44:34 time: 0.6073 data_time: 0.0495 memory: 33630 grad_norm: 4.2476 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2556 loss: 1.2556 2022/10/15 04:04:31 - mmengine - INFO - Epoch(train) [57][200/940] lr: 1.0000e-03 eta: 6:44:22 time: 0.5856 data_time: 0.0357 memory: 33630 grad_norm: 4.2754 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1427 loss: 1.1427 2022/10/15 04:04:43 - mmengine - INFO - Epoch(train) [57][220/940] lr: 1.0000e-03 eta: 6:44:10 time: 0.5949 data_time: 0.0383 memory: 33630 grad_norm: 4.4347 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2675 loss: 1.2675 2022/10/15 04:04:55 - mmengine - INFO - Epoch(train) [57][240/940] lr: 1.0000e-03 eta: 6:43:58 time: 0.5783 data_time: 0.0337 memory: 33630 grad_norm: 4.2600 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3603 loss: 1.3603 2022/10/15 04:05:06 - mmengine - INFO - Epoch(train) [57][260/940] lr: 1.0000e-03 eta: 6:43:46 time: 0.5725 data_time: 0.0334 memory: 33630 grad_norm: 4.3892 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3923 loss: 1.3923 2022/10/15 04:05:18 - mmengine - INFO - Epoch(train) [57][280/940] lr: 1.0000e-03 eta: 6:43:34 time: 0.5792 data_time: 0.0354 memory: 33630 grad_norm: 4.3833 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3175 loss: 1.3175 2022/10/15 04:05:29 - mmengine - INFO - Epoch(train) [57][300/940] lr: 1.0000e-03 eta: 6:43:23 time: 0.5839 data_time: 0.0435 memory: 33630 grad_norm: 4.3667 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2394 loss: 1.2394 2022/10/15 04:05:41 - mmengine - INFO - Epoch(train) [57][320/940] lr: 1.0000e-03 eta: 6:43:11 time: 0.5826 data_time: 0.0331 memory: 33630 grad_norm: 4.3397 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1421 loss: 1.1421 2022/10/15 04:05:53 - mmengine - INFO - Epoch(train) [57][340/940] lr: 1.0000e-03 eta: 6:42:59 time: 0.5900 data_time: 0.0393 memory: 33630 grad_norm: 4.3694 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2411 loss: 1.2411 2022/10/15 04:06:04 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 04:06:04 - mmengine - INFO - Epoch(train) [57][360/940] lr: 1.0000e-03 eta: 6:42:47 time: 0.5800 data_time: 0.0311 memory: 33630 grad_norm: 4.3747 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1960 loss: 1.1960 2022/10/15 04:06:16 - mmengine - INFO - Epoch(train) [57][380/940] lr: 1.0000e-03 eta: 6:42:35 time: 0.5918 data_time: 0.0451 memory: 33630 grad_norm: 4.3088 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2721 loss: 1.2721 2022/10/15 04:06:28 - mmengine - INFO - Epoch(train) [57][400/940] lr: 1.0000e-03 eta: 6:42:23 time: 0.5748 data_time: 0.0357 memory: 33630 grad_norm: 4.3242 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3109 loss: 1.3109 2022/10/15 04:06:40 - mmengine - INFO - Epoch(train) [57][420/940] lr: 1.0000e-03 eta: 6:42:12 time: 0.5925 data_time: 0.0361 memory: 33630 grad_norm: 4.3597 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2394 loss: 1.2394 2022/10/15 04:06:51 - mmengine - INFO - Epoch(train) [57][440/940] lr: 1.0000e-03 eta: 6:42:00 time: 0.5869 data_time: 0.0388 memory: 33630 grad_norm: 4.3155 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2789 loss: 1.2789 2022/10/15 04:07:03 - mmengine - INFO - Epoch(train) [57][460/940] lr: 1.0000e-03 eta: 6:41:48 time: 0.5852 data_time: 0.0346 memory: 33630 grad_norm: 4.4051 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2433 loss: 1.2433 2022/10/15 04:07:15 - mmengine - INFO - Epoch(train) [57][480/940] lr: 1.0000e-03 eta: 6:41:36 time: 0.5820 data_time: 0.0349 memory: 33630 grad_norm: 4.4037 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2367 loss: 1.2367 2022/10/15 04:07:26 - mmengine - INFO - Epoch(train) [57][500/940] lr: 1.0000e-03 eta: 6:41:24 time: 0.5801 data_time: 0.0317 memory: 33630 grad_norm: 4.5262 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2346 loss: 1.2346 2022/10/15 04:07:38 - mmengine - INFO - Epoch(train) [57][520/940] lr: 1.0000e-03 eta: 6:41:12 time: 0.5918 data_time: 0.0359 memory: 33630 grad_norm: 4.4768 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3095 loss: 1.3095 2022/10/15 04:07:50 - mmengine - INFO - Epoch(train) [57][540/940] lr: 1.0000e-03 eta: 6:41:00 time: 0.5881 data_time: 0.0355 memory: 33630 grad_norm: 4.4457 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3490 loss: 1.3490 2022/10/15 04:08:02 - mmengine - INFO - Epoch(train) [57][560/940] lr: 1.0000e-03 eta: 6:40:49 time: 0.5848 data_time: 0.0320 memory: 33630 grad_norm: 4.3712 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3089 loss: 1.3089 2022/10/15 04:08:13 - mmengine - INFO - Epoch(train) [57][580/940] lr: 1.0000e-03 eta: 6:40:37 time: 0.5785 data_time: 0.0315 memory: 33630 grad_norm: 4.4448 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2101 loss: 1.2101 2022/10/15 04:08:25 - mmengine - INFO - Epoch(train) [57][600/940] lr: 1.0000e-03 eta: 6:40:25 time: 0.5931 data_time: 0.0336 memory: 33630 grad_norm: 4.4275 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3266 loss: 1.3266 2022/10/15 04:08:37 - mmengine - INFO - Epoch(train) [57][620/940] lr: 1.0000e-03 eta: 6:40:13 time: 0.5824 data_time: 0.0396 memory: 33630 grad_norm: 4.3773 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0924 loss: 1.0924 2022/10/15 04:08:48 - mmengine - INFO - Epoch(train) [57][640/940] lr: 1.0000e-03 eta: 6:40:01 time: 0.5850 data_time: 0.0318 memory: 33630 grad_norm: 4.5011 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2609 loss: 1.2609 2022/10/15 04:09:00 - mmengine - INFO - Epoch(train) [57][660/940] lr: 1.0000e-03 eta: 6:39:49 time: 0.5747 data_time: 0.0373 memory: 33630 grad_norm: 4.4627 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2181 loss: 1.2181 2022/10/15 04:09:12 - mmengine - INFO - Epoch(train) [57][680/940] lr: 1.0000e-03 eta: 6:39:37 time: 0.5960 data_time: 0.0371 memory: 33630 grad_norm: 4.3614 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1945 loss: 1.1945 2022/10/15 04:09:23 - mmengine - INFO - Epoch(train) [57][700/940] lr: 1.0000e-03 eta: 6:39:26 time: 0.5851 data_time: 0.0498 memory: 33630 grad_norm: 4.3772 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3008 loss: 1.3008 2022/10/15 04:09:35 - mmengine - INFO - Epoch(train) [57][720/940] lr: 1.0000e-03 eta: 6:39:14 time: 0.5813 data_time: 0.0323 memory: 33630 grad_norm: 4.4094 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3031 loss: 1.3031 2022/10/15 04:09:47 - mmengine - INFO - Epoch(train) [57][740/940] lr: 1.0000e-03 eta: 6:39:02 time: 0.5884 data_time: 0.0328 memory: 33630 grad_norm: 4.3089 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2713 loss: 1.2713 2022/10/15 04:09:58 - mmengine - INFO - Epoch(train) [57][760/940] lr: 1.0000e-03 eta: 6:38:50 time: 0.5766 data_time: 0.0411 memory: 33630 grad_norm: 4.3966 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3013 loss: 1.3013 2022/10/15 04:10:10 - mmengine - INFO - Epoch(train) [57][780/940] lr: 1.0000e-03 eta: 6:38:38 time: 0.5887 data_time: 0.0309 memory: 33630 grad_norm: 4.4041 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.2875 loss: 1.2875 2022/10/15 04:10:22 - mmengine - INFO - Epoch(train) [57][800/940] lr: 1.0000e-03 eta: 6:38:26 time: 0.5858 data_time: 0.0319 memory: 33630 grad_norm: 4.4414 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2770 loss: 1.2770 2022/10/15 04:10:34 - mmengine - INFO - Epoch(train) [57][820/940] lr: 1.0000e-03 eta: 6:38:14 time: 0.5838 data_time: 0.0374 memory: 33630 grad_norm: 4.4200 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.3597 loss: 1.3597 2022/10/15 04:10:45 - mmengine - INFO - Epoch(train) [57][840/940] lr: 1.0000e-03 eta: 6:38:02 time: 0.5787 data_time: 0.0338 memory: 33630 grad_norm: 4.4063 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3593 loss: 1.3593 2022/10/15 04:10:57 - mmengine - INFO - Epoch(train) [57][860/940] lr: 1.0000e-03 eta: 6:37:50 time: 0.5817 data_time: 0.0339 memory: 33630 grad_norm: 4.4466 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3333 loss: 1.3333 2022/10/15 04:11:08 - mmengine - INFO - Epoch(train) [57][880/940] lr: 1.0000e-03 eta: 6:37:38 time: 0.5717 data_time: 0.0328 memory: 33630 grad_norm: 4.4158 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3249 loss: 1.3249 2022/10/15 04:11:20 - mmengine - INFO - Epoch(train) [57][900/940] lr: 1.0000e-03 eta: 6:37:27 time: 0.5832 data_time: 0.0399 memory: 33630 grad_norm: 4.4117 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2952 loss: 1.2952 2022/10/15 04:11:31 - mmengine - INFO - Epoch(train) [57][920/940] lr: 1.0000e-03 eta: 6:37:15 time: 0.5732 data_time: 0.0326 memory: 33630 grad_norm: 4.2723 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2621 loss: 1.2621 2022/10/15 04:11:42 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 04:11:42 - mmengine - INFO - Epoch(train) [57][940/940] lr: 1.0000e-03 eta: 6:37:02 time: 0.5340 data_time: 0.0302 memory: 33630 grad_norm: 4.7098 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.2287 loss: 1.2287 2022/10/15 04:11:42 - mmengine - INFO - Saving checkpoint at 57 epochs 2022/10/15 04:11:57 - mmengine - INFO - Epoch(val) [57][20/78] eta: 0:00:40 time: 0.7042 data_time: 0.5327 memory: 5967 2022/10/15 04:12:07 - mmengine - INFO - Epoch(val) [57][40/78] eta: 0:00:20 time: 0.5281 data_time: 0.3608 memory: 5967 2022/10/15 04:12:20 - mmengine - INFO - Epoch(val) [57][60/78] eta: 0:00:11 time: 0.6118 data_time: 0.4422 memory: 5967 2022/10/15 04:12:33 - mmengine - INFO - Epoch(val) [57][78/78] acc/top1: 0.6869 acc/top5: 0.8785 acc/mean1: 0.6868 2022/10/15 04:12:50 - mmengine - INFO - Epoch(train) [58][20/940] lr: 1.0000e-03 eta: 6:36:54 time: 0.8756 data_time: 0.2274 memory: 33630 grad_norm: 4.4229 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3042 loss: 1.3042 2022/10/15 04:13:02 - mmengine - INFO - Epoch(train) [58][40/940] lr: 1.0000e-03 eta: 6:36:43 time: 0.5859 data_time: 0.0348 memory: 33630 grad_norm: 4.2955 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.2418 loss: 1.2418 2022/10/15 04:13:14 - mmengine - INFO - Epoch(train) [58][60/940] lr: 1.0000e-03 eta: 6:36:31 time: 0.5970 data_time: 0.0330 memory: 33630 grad_norm: 4.4232 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1086 loss: 1.1086 2022/10/15 04:13:26 - mmengine - INFO - Epoch(train) [58][80/940] lr: 1.0000e-03 eta: 6:36:19 time: 0.5789 data_time: 0.0368 memory: 33630 grad_norm: 4.3783 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3801 loss: 1.3801 2022/10/15 04:13:37 - mmengine - INFO - Epoch(train) [58][100/940] lr: 1.0000e-03 eta: 6:36:07 time: 0.5856 data_time: 0.0335 memory: 33630 grad_norm: 4.4366 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2734 loss: 1.2734 2022/10/15 04:13:49 - mmengine - INFO - Epoch(train) [58][120/940] lr: 1.0000e-03 eta: 6:35:55 time: 0.5838 data_time: 0.0369 memory: 33630 grad_norm: 4.4487 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4164 loss: 1.4164 2022/10/15 04:14:01 - mmengine - INFO - Epoch(train) [58][140/940] lr: 1.0000e-03 eta: 6:35:43 time: 0.5827 data_time: 0.0385 memory: 33630 grad_norm: 4.4926 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2637 loss: 1.2637 2022/10/15 04:14:13 - mmengine - INFO - Epoch(train) [58][160/940] lr: 1.0000e-03 eta: 6:35:32 time: 0.5954 data_time: 0.0400 memory: 33630 grad_norm: 4.4162 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2117 loss: 1.2117 2022/10/15 04:14:24 - mmengine - INFO - Epoch(train) [58][180/940] lr: 1.0000e-03 eta: 6:35:20 time: 0.5799 data_time: 0.0318 memory: 33630 grad_norm: 4.4067 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2049 loss: 1.2049 2022/10/15 04:14:36 - mmengine - INFO - Epoch(train) [58][200/940] lr: 1.0000e-03 eta: 6:35:08 time: 0.5915 data_time: 0.0464 memory: 33630 grad_norm: 4.4163 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2382 loss: 1.2382 2022/10/15 04:14:48 - mmengine - INFO - Epoch(train) [58][220/940] lr: 1.0000e-03 eta: 6:34:56 time: 0.5803 data_time: 0.0337 memory: 33630 grad_norm: 4.3894 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.2175 loss: 1.2175 2022/10/15 04:14:59 - mmengine - INFO - Epoch(train) [58][240/940] lr: 1.0000e-03 eta: 6:34:44 time: 0.5833 data_time: 0.0390 memory: 33630 grad_norm: 4.4494 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3608 loss: 1.3608 2022/10/15 04:15:11 - mmengine - INFO - Epoch(train) [58][260/940] lr: 1.0000e-03 eta: 6:34:32 time: 0.5842 data_time: 0.0408 memory: 33630 grad_norm: 4.3808 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1083 loss: 1.1083 2022/10/15 04:15:23 - mmengine - INFO - Epoch(train) [58][280/940] lr: 1.0000e-03 eta: 6:34:20 time: 0.5810 data_time: 0.0336 memory: 33630 grad_norm: 4.4279 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3034 loss: 1.3034 2022/10/15 04:15:34 - mmengine - INFO - Epoch(train) [58][300/940] lr: 1.0000e-03 eta: 6:34:09 time: 0.5853 data_time: 0.0341 memory: 33630 grad_norm: 4.3701 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2056 loss: 1.2056 2022/10/15 04:15:46 - mmengine - INFO - Epoch(train) [58][320/940] lr: 1.0000e-03 eta: 6:33:56 time: 0.5695 data_time: 0.0384 memory: 33630 grad_norm: 4.4007 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3091 loss: 1.3091 2022/10/15 04:15:57 - mmengine - INFO - Epoch(train) [58][340/940] lr: 1.0000e-03 eta: 6:33:44 time: 0.5773 data_time: 0.0315 memory: 33630 grad_norm: 4.3777 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.1264 loss: 1.1264 2022/10/15 04:16:09 - mmengine - INFO - Epoch(train) [58][360/940] lr: 1.0000e-03 eta: 6:33:32 time: 0.5706 data_time: 0.0339 memory: 33630 grad_norm: 4.4297 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2203 loss: 1.2203 2022/10/15 04:16:21 - mmengine - INFO - Epoch(train) [58][380/940] lr: 1.0000e-03 eta: 6:33:21 time: 0.5946 data_time: 0.0408 memory: 33630 grad_norm: 4.3988 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2373 loss: 1.2373 2022/10/15 04:16:32 - mmengine - INFO - Epoch(train) [58][400/940] lr: 1.0000e-03 eta: 6:33:09 time: 0.5869 data_time: 0.0311 memory: 33630 grad_norm: 4.4258 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1841 loss: 1.1841 2022/10/15 04:16:44 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 04:16:44 - mmengine - INFO - Epoch(train) [58][420/940] lr: 1.0000e-03 eta: 6:32:57 time: 0.5844 data_time: 0.0322 memory: 33630 grad_norm: 4.3995 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.3154 loss: 1.3154 2022/10/15 04:16:56 - mmengine - INFO - Epoch(train) [58][440/940] lr: 1.0000e-03 eta: 6:32:45 time: 0.5876 data_time: 0.0354 memory: 33630 grad_norm: 4.3959 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3483 loss: 1.3483 2022/10/15 04:17:08 - mmengine - INFO - Epoch(train) [58][460/940] lr: 1.0000e-03 eta: 6:32:33 time: 0.5908 data_time: 0.0342 memory: 33630 grad_norm: 4.4216 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2749 loss: 1.2749 2022/10/15 04:17:19 - mmengine - INFO - Epoch(train) [58][480/940] lr: 1.0000e-03 eta: 6:32:22 time: 0.5883 data_time: 0.0382 memory: 33630 grad_norm: 4.3736 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2853 loss: 1.2853 2022/10/15 04:17:31 - mmengine - INFO - Epoch(train) [58][500/940] lr: 1.0000e-03 eta: 6:32:10 time: 0.5939 data_time: 0.0430 memory: 33630 grad_norm: 4.3023 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1901 loss: 1.1901 2022/10/15 04:17:43 - mmengine - INFO - Epoch(train) [58][520/940] lr: 1.0000e-03 eta: 6:31:58 time: 0.5886 data_time: 0.0342 memory: 33630 grad_norm: 4.5173 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.3547 loss: 1.3547 2022/10/15 04:17:55 - mmengine - INFO - Epoch(train) [58][540/940] lr: 1.0000e-03 eta: 6:31:46 time: 0.5824 data_time: 0.0341 memory: 33630 grad_norm: 4.2871 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2103 loss: 1.2103 2022/10/15 04:18:06 - mmengine - INFO - Epoch(train) [58][560/940] lr: 1.0000e-03 eta: 6:31:34 time: 0.5722 data_time: 0.0412 memory: 33630 grad_norm: 4.5053 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3534 loss: 1.3534 2022/10/15 04:18:18 - mmengine - INFO - Epoch(train) [58][580/940] lr: 1.0000e-03 eta: 6:31:22 time: 0.5835 data_time: 0.0393 memory: 33630 grad_norm: 4.3903 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2819 loss: 1.2819 2022/10/15 04:18:29 - mmengine - INFO - Epoch(train) [58][600/940] lr: 1.0000e-03 eta: 6:31:10 time: 0.5759 data_time: 0.0335 memory: 33630 grad_norm: 4.5167 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3042 loss: 1.3042 2022/10/15 04:18:41 - mmengine - INFO - Epoch(train) [58][620/940] lr: 1.0000e-03 eta: 6:30:58 time: 0.5824 data_time: 0.0345 memory: 33630 grad_norm: 4.3542 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3135 loss: 1.3135 2022/10/15 04:18:53 - mmengine - INFO - Epoch(train) [58][640/940] lr: 1.0000e-03 eta: 6:30:47 time: 0.5867 data_time: 0.0492 memory: 33630 grad_norm: 4.4929 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3234 loss: 1.3234 2022/10/15 04:19:04 - mmengine - INFO - Epoch(train) [58][660/940] lr: 1.0000e-03 eta: 6:30:35 time: 0.5793 data_time: 0.0322 memory: 33630 grad_norm: 4.4557 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2602 loss: 1.2602 2022/10/15 04:19:16 - mmengine - INFO - Epoch(train) [58][680/940] lr: 1.0000e-03 eta: 6:30:23 time: 0.5735 data_time: 0.0300 memory: 33630 grad_norm: 4.4709 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2708 loss: 1.2708 2022/10/15 04:19:28 - mmengine - INFO - Epoch(train) [58][700/940] lr: 1.0000e-03 eta: 6:30:11 time: 0.5916 data_time: 0.0395 memory: 33630 grad_norm: 4.3561 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2912 loss: 1.2912 2022/10/15 04:19:39 - mmengine - INFO - Epoch(train) [58][720/940] lr: 1.0000e-03 eta: 6:29:59 time: 0.5826 data_time: 0.0365 memory: 33630 grad_norm: 4.4181 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4775 loss: 1.4775 2022/10/15 04:19:51 - mmengine - INFO - Epoch(train) [58][740/940] lr: 1.0000e-03 eta: 6:29:47 time: 0.5857 data_time: 0.0334 memory: 33630 grad_norm: 4.3711 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.3096 loss: 1.3096 2022/10/15 04:20:03 - mmengine - INFO - Epoch(train) [58][760/940] lr: 1.0000e-03 eta: 6:29:35 time: 0.5855 data_time: 0.0405 memory: 33630 grad_norm: 4.3822 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2180 loss: 1.2180 2022/10/15 04:20:14 - mmengine - INFO - Epoch(train) [58][780/940] lr: 1.0000e-03 eta: 6:29:23 time: 0.5787 data_time: 0.0395 memory: 33630 grad_norm: 4.3615 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2756 loss: 1.2756 2022/10/15 04:20:26 - mmengine - INFO - Epoch(train) [58][800/940] lr: 1.0000e-03 eta: 6:29:11 time: 0.5842 data_time: 0.0464 memory: 33630 grad_norm: 4.3917 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2415 loss: 1.2415 2022/10/15 04:20:38 - mmengine - INFO - Epoch(train) [58][820/940] lr: 1.0000e-03 eta: 6:29:00 time: 0.5882 data_time: 0.0412 memory: 33630 grad_norm: 4.4016 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2990 loss: 1.2990 2022/10/15 04:20:49 - mmengine - INFO - Epoch(train) [58][840/940] lr: 1.0000e-03 eta: 6:28:48 time: 0.5814 data_time: 0.0321 memory: 33630 grad_norm: 4.4658 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3601 loss: 1.3601 2022/10/15 04:21:01 - mmengine - INFO - Epoch(train) [58][860/940] lr: 1.0000e-03 eta: 6:28:36 time: 0.5784 data_time: 0.0463 memory: 33630 grad_norm: 4.3875 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.3096 loss: 1.3096 2022/10/15 04:21:13 - mmengine - INFO - Epoch(train) [58][880/940] lr: 1.0000e-03 eta: 6:28:24 time: 0.5916 data_time: 0.0405 memory: 33630 grad_norm: 4.4367 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0358 loss: 1.0358 2022/10/15 04:21:24 - mmengine - INFO - Epoch(train) [58][900/940] lr: 1.0000e-03 eta: 6:28:12 time: 0.5820 data_time: 0.0376 memory: 33630 grad_norm: 4.3748 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2851 loss: 1.2851 2022/10/15 04:21:36 - mmengine - INFO - Epoch(train) [58][920/940] lr: 1.0000e-03 eta: 6:28:00 time: 0.5790 data_time: 0.0302 memory: 33630 grad_norm: 4.4368 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2167 loss: 1.2167 2022/10/15 04:21:47 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 04:21:47 - mmengine - INFO - Epoch(train) [58][940/940] lr: 1.0000e-03 eta: 6:27:48 time: 0.5406 data_time: 0.0329 memory: 33630 grad_norm: 4.6632 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1180 loss: 1.1180 2022/10/15 04:22:01 - mmengine - INFO - Epoch(val) [58][20/78] eta: 0:00:42 time: 0.7257 data_time: 0.5555 memory: 5967 2022/10/15 04:22:11 - mmengine - INFO - Epoch(val) [58][40/78] eta: 0:00:18 time: 0.4909 data_time: 0.3239 memory: 5967 2022/10/15 04:22:24 - mmengine - INFO - Epoch(val) [58][60/78] eta: 0:00:11 time: 0.6579 data_time: 0.4860 memory: 5967 2022/10/15 04:22:36 - mmengine - INFO - Epoch(val) [58][78/78] acc/top1: 0.6854 acc/top5: 0.8778 acc/mean1: 0.6854 2022/10/15 04:22:53 - mmengine - INFO - Epoch(train) [59][20/940] lr: 1.0000e-03 eta: 6:27:40 time: 0.8480 data_time: 0.2473 memory: 33630 grad_norm: 4.3802 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2003 loss: 1.2003 2022/10/15 04:23:05 - mmengine - INFO - Epoch(train) [59][40/940] lr: 1.0000e-03 eta: 6:27:28 time: 0.5788 data_time: 0.0307 memory: 33630 grad_norm: 4.3241 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3077 loss: 1.3077 2022/10/15 04:23:17 - mmengine - INFO - Epoch(train) [59][60/940] lr: 1.0000e-03 eta: 6:27:16 time: 0.5892 data_time: 0.0372 memory: 33630 grad_norm: 4.4041 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1807 loss: 1.1807 2022/10/15 04:23:28 - mmengine - INFO - Epoch(train) [59][80/940] lr: 1.0000e-03 eta: 6:27:04 time: 0.5964 data_time: 0.0303 memory: 33630 grad_norm: 4.3178 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2316 loss: 1.2316 2022/10/15 04:23:40 - mmengine - INFO - Epoch(train) [59][100/940] lr: 1.0000e-03 eta: 6:26:52 time: 0.5905 data_time: 0.0390 memory: 33630 grad_norm: 4.4395 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2922 loss: 1.2922 2022/10/15 04:23:52 - mmengine - INFO - Epoch(train) [59][120/940] lr: 1.0000e-03 eta: 6:26:41 time: 0.5902 data_time: 0.0293 memory: 33630 grad_norm: 4.4696 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3557 loss: 1.3557 2022/10/15 04:24:04 - mmengine - INFO - Epoch(train) [59][140/940] lr: 1.0000e-03 eta: 6:26:29 time: 0.5796 data_time: 0.0370 memory: 33630 grad_norm: 4.4925 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1616 loss: 1.1616 2022/10/15 04:24:15 - mmengine - INFO - Epoch(train) [59][160/940] lr: 1.0000e-03 eta: 6:26:17 time: 0.5829 data_time: 0.0377 memory: 33630 grad_norm: 4.4144 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3453 loss: 1.3453 2022/10/15 04:24:27 - mmengine - INFO - Epoch(train) [59][180/940] lr: 1.0000e-03 eta: 6:26:05 time: 0.5855 data_time: 0.0362 memory: 33630 grad_norm: 4.4019 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3236 loss: 1.3236 2022/10/15 04:24:39 - mmengine - INFO - Epoch(train) [59][200/940] lr: 1.0000e-03 eta: 6:25:53 time: 0.5780 data_time: 0.0303 memory: 33630 grad_norm: 4.4158 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2474 loss: 1.2474 2022/10/15 04:24:50 - mmengine - INFO - Epoch(train) [59][220/940] lr: 1.0000e-03 eta: 6:25:41 time: 0.5913 data_time: 0.0377 memory: 33630 grad_norm: 4.3170 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2397 loss: 1.2397 2022/10/15 04:25:02 - mmengine - INFO - Epoch(train) [59][240/940] lr: 1.0000e-03 eta: 6:25:30 time: 0.5994 data_time: 0.0461 memory: 33630 grad_norm: 4.3939 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2082 loss: 1.2082 2022/10/15 04:25:14 - mmengine - INFO - Epoch(train) [59][260/940] lr: 1.0000e-03 eta: 6:25:18 time: 0.5756 data_time: 0.0348 memory: 33630 grad_norm: 4.4900 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3258 loss: 1.3258 2022/10/15 04:25:26 - mmengine - INFO - Epoch(train) [59][280/940] lr: 1.0000e-03 eta: 6:25:06 time: 0.5906 data_time: 0.0398 memory: 33630 grad_norm: 4.4012 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3327 loss: 1.3327 2022/10/15 04:25:37 - mmengine - INFO - Epoch(train) [59][300/940] lr: 1.0000e-03 eta: 6:24:54 time: 0.5694 data_time: 0.0331 memory: 33630 grad_norm: 4.4011 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2875 loss: 1.2875 2022/10/15 04:25:49 - mmengine - INFO - Epoch(train) [59][320/940] lr: 1.0000e-03 eta: 6:24:42 time: 0.5811 data_time: 0.0360 memory: 33630 grad_norm: 4.4272 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3080 loss: 1.3080 2022/10/15 04:26:00 - mmengine - INFO - Epoch(train) [59][340/940] lr: 1.0000e-03 eta: 6:24:30 time: 0.5839 data_time: 0.0445 memory: 33630 grad_norm: 4.3632 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3738 loss: 1.3738 2022/10/15 04:26:12 - mmengine - INFO - Epoch(train) [59][360/940] lr: 1.0000e-03 eta: 6:24:18 time: 0.5701 data_time: 0.0355 memory: 33630 grad_norm: 4.4347 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3413 loss: 1.3413 2022/10/15 04:26:24 - mmengine - INFO - Epoch(train) [59][380/940] lr: 1.0000e-03 eta: 6:24:06 time: 0.5888 data_time: 0.0334 memory: 33630 grad_norm: 4.4329 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1788 loss: 1.1788 2022/10/15 04:26:36 - mmengine - INFO - Epoch(train) [59][400/940] lr: 1.0000e-03 eta: 6:23:55 time: 0.5981 data_time: 0.0316 memory: 33630 grad_norm: 4.4032 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1782 loss: 1.1782 2022/10/15 04:26:47 - mmengine - INFO - Epoch(train) [59][420/940] lr: 1.0000e-03 eta: 6:23:43 time: 0.5774 data_time: 0.0369 memory: 33630 grad_norm: 4.3136 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3230 loss: 1.3230 2022/10/15 04:26:59 - mmengine - INFO - Epoch(train) [59][440/940] lr: 1.0000e-03 eta: 6:23:31 time: 0.5773 data_time: 0.0331 memory: 33630 grad_norm: 4.5114 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1357 loss: 1.1357 2022/10/15 04:27:10 - mmengine - INFO - Epoch(train) [59][460/940] lr: 1.0000e-03 eta: 6:23:19 time: 0.5871 data_time: 0.0344 memory: 33630 grad_norm: 4.5211 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1962 loss: 1.1962 2022/10/15 04:27:22 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 04:27:22 - mmengine - INFO - Epoch(train) [59][480/940] lr: 1.0000e-03 eta: 6:23:07 time: 0.5770 data_time: 0.0337 memory: 33630 grad_norm: 4.5214 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2774 loss: 1.2774 2022/10/15 04:27:34 - mmengine - INFO - Epoch(train) [59][500/940] lr: 1.0000e-03 eta: 6:22:55 time: 0.5963 data_time: 0.0477 memory: 33630 grad_norm: 4.4386 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2979 loss: 1.2979 2022/10/15 04:27:46 - mmengine - INFO - Epoch(train) [59][520/940] lr: 1.0000e-03 eta: 6:22:43 time: 0.5883 data_time: 0.0356 memory: 33630 grad_norm: 4.3384 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1656 loss: 1.1656 2022/10/15 04:27:57 - mmengine - INFO - Epoch(train) [59][540/940] lr: 1.0000e-03 eta: 6:22:31 time: 0.5830 data_time: 0.0348 memory: 33630 grad_norm: 4.4765 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.3378 loss: 1.3378 2022/10/15 04:28:09 - mmengine - INFO - Epoch(train) [59][560/940] lr: 1.0000e-03 eta: 6:22:20 time: 0.5839 data_time: 0.0405 memory: 33630 grad_norm: 4.4825 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1905 loss: 1.1905 2022/10/15 04:28:21 - mmengine - INFO - Epoch(train) [59][580/940] lr: 1.0000e-03 eta: 6:22:08 time: 0.5741 data_time: 0.0308 memory: 33630 grad_norm: 4.4848 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2164 loss: 1.2164 2022/10/15 04:28:32 - mmengine - INFO - Epoch(train) [59][600/940] lr: 1.0000e-03 eta: 6:21:56 time: 0.5739 data_time: 0.0323 memory: 33630 grad_norm: 4.5392 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2589 loss: 1.2589 2022/10/15 04:28:44 - mmengine - INFO - Epoch(train) [59][620/940] lr: 1.0000e-03 eta: 6:21:44 time: 0.5969 data_time: 0.0521 memory: 33630 grad_norm: 4.4437 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3237 loss: 1.3237 2022/10/15 04:28:55 - mmengine - INFO - Epoch(train) [59][640/940] lr: 1.0000e-03 eta: 6:21:32 time: 0.5707 data_time: 0.0310 memory: 33630 grad_norm: 4.4380 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1844 loss: 1.1844 2022/10/15 04:29:07 - mmengine - INFO - Epoch(train) [59][660/940] lr: 1.0000e-03 eta: 6:21:20 time: 0.5846 data_time: 0.0314 memory: 33630 grad_norm: 4.3954 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3608 loss: 1.3608 2022/10/15 04:29:19 - mmengine - INFO - Epoch(train) [59][680/940] lr: 1.0000e-03 eta: 6:21:08 time: 0.5863 data_time: 0.0325 memory: 33630 grad_norm: 4.4058 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2012 loss: 1.2012 2022/10/15 04:29:30 - mmengine - INFO - Epoch(train) [59][700/940] lr: 1.0000e-03 eta: 6:20:56 time: 0.5836 data_time: 0.0351 memory: 33630 grad_norm: 4.5341 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2089 loss: 1.2089 2022/10/15 04:29:42 - mmengine - INFO - Epoch(train) [59][720/940] lr: 1.0000e-03 eta: 6:20:45 time: 0.5901 data_time: 0.0414 memory: 33630 grad_norm: 4.4582 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3300 loss: 1.3300 2022/10/15 04:29:54 - mmengine - INFO - Epoch(train) [59][740/940] lr: 1.0000e-03 eta: 6:20:33 time: 0.5907 data_time: 0.0393 memory: 33630 grad_norm: 4.4383 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2230 loss: 1.2230 2022/10/15 04:30:06 - mmengine - INFO - Epoch(train) [59][760/940] lr: 1.0000e-03 eta: 6:20:21 time: 0.5822 data_time: 0.0401 memory: 33630 grad_norm: 4.4520 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3465 loss: 1.3465 2022/10/15 04:30:18 - mmengine - INFO - Epoch(train) [59][780/940] lr: 1.0000e-03 eta: 6:20:09 time: 0.5892 data_time: 0.0327 memory: 33630 grad_norm: 4.3780 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1467 loss: 1.1467 2022/10/15 04:30:29 - mmengine - INFO - Epoch(train) [59][800/940] lr: 1.0000e-03 eta: 6:19:57 time: 0.5788 data_time: 0.0367 memory: 33630 grad_norm: 4.4757 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2848 loss: 1.2848 2022/10/15 04:30:41 - mmengine - INFO - Epoch(train) [59][820/940] lr: 1.0000e-03 eta: 6:19:45 time: 0.5719 data_time: 0.0319 memory: 33630 grad_norm: 4.3879 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1024 loss: 1.1024 2022/10/15 04:30:52 - mmengine - INFO - Epoch(train) [59][840/940] lr: 1.0000e-03 eta: 6:19:33 time: 0.5836 data_time: 0.0375 memory: 33630 grad_norm: 4.5258 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2646 loss: 1.2646 2022/10/15 04:31:04 - mmengine - INFO - Epoch(train) [59][860/940] lr: 1.0000e-03 eta: 6:19:21 time: 0.5942 data_time: 0.0344 memory: 33630 grad_norm: 4.4493 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2800 loss: 1.2800 2022/10/15 04:31:16 - mmengine - INFO - Epoch(train) [59][880/940] lr: 1.0000e-03 eta: 6:19:10 time: 0.5852 data_time: 0.0349 memory: 33630 grad_norm: 4.5793 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3975 loss: 1.3975 2022/10/15 04:31:28 - mmengine - INFO - Epoch(train) [59][900/940] lr: 1.0000e-03 eta: 6:18:58 time: 0.5873 data_time: 0.0306 memory: 33630 grad_norm: 4.3856 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.1299 loss: 1.1299 2022/10/15 04:31:39 - mmengine - INFO - Epoch(train) [59][920/940] lr: 1.0000e-03 eta: 6:18:46 time: 0.5774 data_time: 0.0387 memory: 33630 grad_norm: 4.5025 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3231 loss: 1.3231 2022/10/15 04:31:50 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 04:31:50 - mmengine - INFO - Epoch(train) [59][940/940] lr: 1.0000e-03 eta: 6:18:33 time: 0.5382 data_time: 0.0297 memory: 33630 grad_norm: 4.8354 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.2925 loss: 1.2925 2022/10/15 04:32:05 - mmengine - INFO - Epoch(val) [59][20/78] eta: 0:00:42 time: 0.7359 data_time: 0.5666 memory: 5967 2022/10/15 04:32:14 - mmengine - INFO - Epoch(val) [59][40/78] eta: 0:00:18 time: 0.4920 data_time: 0.3239 memory: 5967 2022/10/15 04:32:28 - mmengine - INFO - Epoch(val) [59][60/78] eta: 0:00:11 time: 0.6650 data_time: 0.4974 memory: 5967 2022/10/15 04:32:42 - mmengine - INFO - Epoch(val) [59][78/78] acc/top1: 0.6870 acc/top5: 0.8778 acc/mean1: 0.6869 2022/10/15 04:32:58 - mmengine - INFO - Epoch(train) [60][20/940] lr: 1.0000e-03 eta: 6:18:25 time: 0.8409 data_time: 0.2757 memory: 33630 grad_norm: 4.3388 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3234 loss: 1.3234 2022/10/15 04:33:10 - mmengine - INFO - Epoch(train) [60][40/940] lr: 1.0000e-03 eta: 6:18:13 time: 0.5761 data_time: 0.0326 memory: 33630 grad_norm: 4.3833 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3096 loss: 1.3096 2022/10/15 04:33:22 - mmengine - INFO - Epoch(train) [60][60/940] lr: 1.0000e-03 eta: 6:18:01 time: 0.5869 data_time: 0.0363 memory: 33630 grad_norm: 4.3925 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.2516 loss: 1.2516 2022/10/15 04:33:33 - mmengine - INFO - Epoch(train) [60][80/940] lr: 1.0000e-03 eta: 6:17:49 time: 0.5831 data_time: 0.0344 memory: 33630 grad_norm: 4.3536 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1773 loss: 1.1773 2022/10/15 04:33:45 - mmengine - INFO - Epoch(train) [60][100/940] lr: 1.0000e-03 eta: 6:17:38 time: 0.5878 data_time: 0.0345 memory: 33630 grad_norm: 4.4781 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1548 loss: 1.1548 2022/10/15 04:33:57 - mmengine - INFO - Epoch(train) [60][120/940] lr: 1.0000e-03 eta: 6:17:26 time: 0.5882 data_time: 0.0307 memory: 33630 grad_norm: 4.3661 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.1529 loss: 1.1529 2022/10/15 04:34:08 - mmengine - INFO - Epoch(train) [60][140/940] lr: 1.0000e-03 eta: 6:17:14 time: 0.5794 data_time: 0.0344 memory: 33630 grad_norm: 4.3750 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1915 loss: 1.1915 2022/10/15 04:34:20 - mmengine - INFO - Epoch(train) [60][160/940] lr: 1.0000e-03 eta: 6:17:02 time: 0.5867 data_time: 0.0339 memory: 33630 grad_norm: 4.4246 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2248 loss: 1.2248 2022/10/15 04:34:32 - mmengine - INFO - Epoch(train) [60][180/940] lr: 1.0000e-03 eta: 6:16:50 time: 0.5809 data_time: 0.0311 memory: 33630 grad_norm: 4.3543 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2702 loss: 1.2702 2022/10/15 04:34:43 - mmengine - INFO - Epoch(train) [60][200/940] lr: 1.0000e-03 eta: 6:16:38 time: 0.5781 data_time: 0.0328 memory: 33630 grad_norm: 4.4396 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2281 loss: 1.2281 2022/10/15 04:34:55 - mmengine - INFO - Epoch(train) [60][220/940] lr: 1.0000e-03 eta: 6:16:26 time: 0.5803 data_time: 0.0414 memory: 33630 grad_norm: 4.4316 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3103 loss: 1.3103 2022/10/15 04:35:07 - mmengine - INFO - Epoch(train) [60][240/940] lr: 1.0000e-03 eta: 6:16:14 time: 0.5890 data_time: 0.0421 memory: 33630 grad_norm: 4.4505 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3121 loss: 1.3121 2022/10/15 04:35:19 - mmengine - INFO - Epoch(train) [60][260/940] lr: 1.0000e-03 eta: 6:16:03 time: 0.5881 data_time: 0.0367 memory: 33630 grad_norm: 4.4850 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2185 loss: 1.2185 2022/10/15 04:35:30 - mmengine - INFO - Epoch(train) [60][280/940] lr: 1.0000e-03 eta: 6:15:51 time: 0.5776 data_time: 0.0366 memory: 33630 grad_norm: 4.4690 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2645 loss: 1.2645 2022/10/15 04:35:42 - mmengine - INFO - Epoch(train) [60][300/940] lr: 1.0000e-03 eta: 6:15:39 time: 0.5971 data_time: 0.0368 memory: 33630 grad_norm: 4.5063 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1370 loss: 1.1370 2022/10/15 04:35:54 - mmengine - INFO - Epoch(train) [60][320/940] lr: 1.0000e-03 eta: 6:15:27 time: 0.5790 data_time: 0.0418 memory: 33630 grad_norm: 4.5198 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3524 loss: 1.3524 2022/10/15 04:36:05 - mmengine - INFO - Epoch(train) [60][340/940] lr: 1.0000e-03 eta: 6:15:15 time: 0.5856 data_time: 0.0377 memory: 33630 grad_norm: 4.4178 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2072 loss: 1.2072 2022/10/15 04:36:17 - mmengine - INFO - Epoch(train) [60][360/940] lr: 1.0000e-03 eta: 6:15:03 time: 0.5815 data_time: 0.0331 memory: 33630 grad_norm: 4.3358 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2143 loss: 1.2143 2022/10/15 04:36:29 - mmengine - INFO - Epoch(train) [60][380/940] lr: 1.0000e-03 eta: 6:14:52 time: 0.5908 data_time: 0.0402 memory: 33630 grad_norm: 4.5144 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3155 loss: 1.3155 2022/10/15 04:36:40 - mmengine - INFO - Epoch(train) [60][400/940] lr: 1.0000e-03 eta: 6:14:40 time: 0.5766 data_time: 0.0416 memory: 33630 grad_norm: 4.3940 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2318 loss: 1.2318 2022/10/15 04:36:52 - mmengine - INFO - Epoch(train) [60][420/940] lr: 1.0000e-03 eta: 6:14:28 time: 0.5851 data_time: 0.0312 memory: 33630 grad_norm: 4.4286 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2016 loss: 1.2016 2022/10/15 04:37:04 - mmengine - INFO - Epoch(train) [60][440/940] lr: 1.0000e-03 eta: 6:14:16 time: 0.5734 data_time: 0.0352 memory: 33630 grad_norm: 4.3970 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1607 loss: 1.1607 2022/10/15 04:37:15 - mmengine - INFO - Epoch(train) [60][460/940] lr: 1.0000e-03 eta: 6:14:04 time: 0.5760 data_time: 0.0332 memory: 33630 grad_norm: 4.4372 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1716 loss: 1.1716 2022/10/15 04:37:27 - mmengine - INFO - Epoch(train) [60][480/940] lr: 1.0000e-03 eta: 6:13:52 time: 0.5816 data_time: 0.0441 memory: 33630 grad_norm: 4.4379 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1217 loss: 1.1217 2022/10/15 04:37:38 - mmengine - INFO - Epoch(train) [60][500/940] lr: 1.0000e-03 eta: 6:13:40 time: 0.5816 data_time: 0.0324 memory: 33630 grad_norm: 4.4923 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1954 loss: 1.1954 2022/10/15 04:37:50 - mmengine - INFO - Epoch(train) [60][520/940] lr: 1.0000e-03 eta: 6:13:28 time: 0.5931 data_time: 0.0330 memory: 33630 grad_norm: 4.3464 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0961 loss: 1.0961 2022/10/15 04:38:02 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 04:38:02 - mmengine - INFO - Epoch(train) [60][540/940] lr: 1.0000e-03 eta: 6:13:16 time: 0.5857 data_time: 0.0338 memory: 33630 grad_norm: 4.4630 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.0974 loss: 1.0974 2022/10/15 04:38:14 - mmengine - INFO - Epoch(train) [60][560/940] lr: 1.0000e-03 eta: 6:13:05 time: 0.5903 data_time: 0.0390 memory: 33630 grad_norm: 4.4321 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2917 loss: 1.2917 2022/10/15 04:38:25 - mmengine - INFO - Epoch(train) [60][580/940] lr: 1.0000e-03 eta: 6:12:53 time: 0.5792 data_time: 0.0361 memory: 33630 grad_norm: 4.5320 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2586 loss: 1.2586 2022/10/15 04:38:37 - mmengine - INFO - Epoch(train) [60][600/940] lr: 1.0000e-03 eta: 6:12:41 time: 0.5811 data_time: 0.0373 memory: 33630 grad_norm: 4.4940 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.3602 loss: 1.3602 2022/10/15 04:38:48 - mmengine - INFO - Epoch(train) [60][620/940] lr: 1.0000e-03 eta: 6:12:29 time: 0.5789 data_time: 0.0348 memory: 33630 grad_norm: 4.4157 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2431 loss: 1.2431 2022/10/15 04:39:00 - mmengine - INFO - Epoch(train) [60][640/940] lr: 1.0000e-03 eta: 6:12:17 time: 0.5772 data_time: 0.0316 memory: 33630 grad_norm: 4.5347 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4207 loss: 1.4207 2022/10/15 04:39:12 - mmengine - INFO - Epoch(train) [60][660/940] lr: 1.0000e-03 eta: 6:12:05 time: 0.5883 data_time: 0.0377 memory: 33630 grad_norm: 4.4916 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2681 loss: 1.2681 2022/10/15 04:39:23 - mmengine - INFO - Epoch(train) [60][680/940] lr: 1.0000e-03 eta: 6:11:53 time: 0.5791 data_time: 0.0319 memory: 33630 grad_norm: 4.4114 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2282 loss: 1.2282 2022/10/15 04:39:35 - mmengine - INFO - Epoch(train) [60][700/940] lr: 1.0000e-03 eta: 6:11:41 time: 0.5822 data_time: 0.0415 memory: 33630 grad_norm: 4.5063 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.2794 loss: 1.2794 2022/10/15 04:39:47 - mmengine - INFO - Epoch(train) [60][720/940] lr: 1.0000e-03 eta: 6:11:29 time: 0.5758 data_time: 0.0317 memory: 33630 grad_norm: 4.5188 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1573 loss: 1.1573 2022/10/15 04:39:58 - mmengine - INFO - Epoch(train) [60][740/940] lr: 1.0000e-03 eta: 6:11:17 time: 0.5722 data_time: 0.0346 memory: 33630 grad_norm: 4.3270 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1248 loss: 1.1248 2022/10/15 04:40:09 - mmengine - INFO - Epoch(train) [60][760/940] lr: 1.0000e-03 eta: 6:11:05 time: 0.5759 data_time: 0.0315 memory: 33630 grad_norm: 4.4515 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3238 loss: 1.3238 2022/10/15 04:40:21 - mmengine - INFO - Epoch(train) [60][780/940] lr: 1.0000e-03 eta: 6:10:53 time: 0.5792 data_time: 0.0329 memory: 33630 grad_norm: 4.4683 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2173 loss: 1.2173 2022/10/15 04:40:33 - mmengine - INFO - Epoch(train) [60][800/940] lr: 1.0000e-03 eta: 6:10:42 time: 0.5777 data_time: 0.0370 memory: 33630 grad_norm: 4.4545 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3306 loss: 1.3306 2022/10/15 04:40:44 - mmengine - INFO - Epoch(train) [60][820/940] lr: 1.0000e-03 eta: 6:10:29 time: 0.5707 data_time: 0.0347 memory: 33630 grad_norm: 4.4804 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2650 loss: 1.2650 2022/10/15 04:40:56 - mmengine - INFO - Epoch(train) [60][840/940] lr: 1.0000e-03 eta: 6:10:18 time: 0.5813 data_time: 0.0363 memory: 33630 grad_norm: 4.5031 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2502 loss: 1.2502 2022/10/15 04:41:07 - mmengine - INFO - Epoch(train) [60][860/940] lr: 1.0000e-03 eta: 6:10:06 time: 0.5805 data_time: 0.0366 memory: 33630 grad_norm: 4.5119 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3010 loss: 1.3010 2022/10/15 04:41:19 - mmengine - INFO - Epoch(train) [60][880/940] lr: 1.0000e-03 eta: 6:09:54 time: 0.5849 data_time: 0.0403 memory: 33630 grad_norm: 4.4603 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1658 loss: 1.1658 2022/10/15 04:41:31 - mmengine - INFO - Epoch(train) [60][900/940] lr: 1.0000e-03 eta: 6:09:42 time: 0.5863 data_time: 0.0387 memory: 33630 grad_norm: 4.5360 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2416 loss: 1.2416 2022/10/15 04:41:43 - mmengine - INFO - Epoch(train) [60][920/940] lr: 1.0000e-03 eta: 6:09:30 time: 0.6010 data_time: 0.0346 memory: 33630 grad_norm: 4.5361 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2575 loss: 1.2575 2022/10/15 04:41:54 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 04:41:54 - mmengine - INFO - Epoch(train) [60][940/940] lr: 1.0000e-03 eta: 6:09:18 time: 0.5494 data_time: 0.0334 memory: 33630 grad_norm: 4.7581 top1_acc: 0.4286 top5_acc: 0.4286 loss_cls: 1.3037 loss: 1.3037 2022/10/15 04:41:54 - mmengine - INFO - Saving checkpoint at 60 epochs 2022/10/15 04:42:09 - mmengine - INFO - Epoch(val) [60][20/78] eta: 0:00:42 time: 0.7357 data_time: 0.5682 memory: 5967 2022/10/15 04:42:20 - mmengine - INFO - Epoch(val) [60][40/78] eta: 0:00:20 time: 0.5304 data_time: 0.3578 memory: 5967 2022/10/15 04:42:33 - mmengine - INFO - Epoch(val) [60][60/78] eta: 0:00:11 time: 0.6503 data_time: 0.4795 memory: 5967 2022/10/15 04:42:44 - mmengine - INFO - Epoch(val) [60][78/78] acc/top1: 0.6884 acc/top5: 0.8781 acc/mean1: 0.6883 2022/10/15 04:43:00 - mmengine - INFO - Epoch(train) [61][20/940] lr: 1.0000e-03 eta: 6:09:09 time: 0.8195 data_time: 0.2460 memory: 33630 grad_norm: 4.3915 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1455 loss: 1.1455 2022/10/15 04:43:12 - mmengine - INFO - Epoch(train) [61][40/940] lr: 1.0000e-03 eta: 6:08:58 time: 0.5890 data_time: 0.0323 memory: 33630 grad_norm: 4.4471 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2648 loss: 1.2648 2022/10/15 04:43:24 - mmengine - INFO - Epoch(train) [61][60/940] lr: 1.0000e-03 eta: 6:08:46 time: 0.5999 data_time: 0.0372 memory: 33630 grad_norm: 4.3546 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2217 loss: 1.2217 2022/10/15 04:43:36 - mmengine - INFO - Epoch(train) [61][80/940] lr: 1.0000e-03 eta: 6:08:34 time: 0.5833 data_time: 0.0332 memory: 33630 grad_norm: 4.4254 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2234 loss: 1.2234 2022/10/15 04:43:48 - mmengine - INFO - Epoch(train) [61][100/940] lr: 1.0000e-03 eta: 6:08:22 time: 0.5967 data_time: 0.0460 memory: 33630 grad_norm: 4.3851 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2863 loss: 1.2863 2022/10/15 04:43:59 - mmengine - INFO - Epoch(train) [61][120/940] lr: 1.0000e-03 eta: 6:08:10 time: 0.5712 data_time: 0.0388 memory: 33630 grad_norm: 4.6032 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.3985 loss: 1.3985 2022/10/15 04:44:11 - mmengine - INFO - Epoch(train) [61][140/940] lr: 1.0000e-03 eta: 6:07:58 time: 0.5755 data_time: 0.0320 memory: 33630 grad_norm: 4.4911 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2651 loss: 1.2651 2022/10/15 04:44:23 - mmengine - INFO - Epoch(train) [61][160/940] lr: 1.0000e-03 eta: 6:07:47 time: 0.5905 data_time: 0.0333 memory: 33630 grad_norm: 4.4812 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1240 loss: 1.1240 2022/10/15 04:44:34 - mmengine - INFO - Epoch(train) [61][180/940] lr: 1.0000e-03 eta: 6:07:35 time: 0.5802 data_time: 0.0353 memory: 33630 grad_norm: 4.3560 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3068 loss: 1.3068 2022/10/15 04:44:46 - mmengine - INFO - Epoch(train) [61][200/940] lr: 1.0000e-03 eta: 6:07:23 time: 0.5801 data_time: 0.0371 memory: 33630 grad_norm: 4.3651 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1798 loss: 1.1798 2022/10/15 04:44:57 - mmengine - INFO - Epoch(train) [61][220/940] lr: 1.0000e-03 eta: 6:07:11 time: 0.5810 data_time: 0.0340 memory: 33630 grad_norm: 4.4348 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3021 loss: 1.3021 2022/10/15 04:45:09 - mmengine - INFO - Epoch(train) [61][240/940] lr: 1.0000e-03 eta: 6:06:59 time: 0.5737 data_time: 0.0369 memory: 33630 grad_norm: 4.5542 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2111 loss: 1.2111 2022/10/15 04:45:21 - mmengine - INFO - Epoch(train) [61][260/940] lr: 1.0000e-03 eta: 6:06:47 time: 0.5835 data_time: 0.0346 memory: 33630 grad_norm: 4.4839 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2849 loss: 1.2849 2022/10/15 04:45:32 - mmengine - INFO - Epoch(train) [61][280/940] lr: 1.0000e-03 eta: 6:06:35 time: 0.5737 data_time: 0.0319 memory: 33630 grad_norm: 4.3890 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2083 loss: 1.2083 2022/10/15 04:45:44 - mmengine - INFO - Epoch(train) [61][300/940] lr: 1.0000e-03 eta: 6:06:23 time: 0.5900 data_time: 0.0395 memory: 33630 grad_norm: 4.4272 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2702 loss: 1.2702 2022/10/15 04:45:56 - mmengine - INFO - Epoch(train) [61][320/940] lr: 1.0000e-03 eta: 6:06:11 time: 0.5869 data_time: 0.0353 memory: 33630 grad_norm: 4.4673 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.1944 loss: 1.1944 2022/10/15 04:46:07 - mmengine - INFO - Epoch(train) [61][340/940] lr: 1.0000e-03 eta: 6:06:00 time: 0.5845 data_time: 0.0322 memory: 33630 grad_norm: 4.4226 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2595 loss: 1.2595 2022/10/15 04:46:19 - mmengine - INFO - Epoch(train) [61][360/940] lr: 1.0000e-03 eta: 6:05:48 time: 0.5953 data_time: 0.0466 memory: 33630 grad_norm: 4.5303 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2709 loss: 1.2709 2022/10/15 04:46:31 - mmengine - INFO - Epoch(train) [61][380/940] lr: 1.0000e-03 eta: 6:05:36 time: 0.5801 data_time: 0.0366 memory: 33630 grad_norm: 4.4356 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2648 loss: 1.2648 2022/10/15 04:46:42 - mmengine - INFO - Epoch(train) [61][400/940] lr: 1.0000e-03 eta: 6:05:24 time: 0.5820 data_time: 0.0382 memory: 33630 grad_norm: 4.4445 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3193 loss: 1.3193 2022/10/15 04:46:54 - mmengine - INFO - Epoch(train) [61][420/940] lr: 1.0000e-03 eta: 6:05:12 time: 0.5819 data_time: 0.0385 memory: 33630 grad_norm: 4.4611 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1380 loss: 1.1380 2022/10/15 04:47:06 - mmengine - INFO - Epoch(train) [61][440/940] lr: 1.0000e-03 eta: 6:05:00 time: 0.5820 data_time: 0.0351 memory: 33630 grad_norm: 4.4629 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3161 loss: 1.3161 2022/10/15 04:47:17 - mmengine - INFO - Epoch(train) [61][460/940] lr: 1.0000e-03 eta: 6:04:48 time: 0.5835 data_time: 0.0425 memory: 33630 grad_norm: 4.4490 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2501 loss: 1.2501 2022/10/15 04:47:29 - mmengine - INFO - Epoch(train) [61][480/940] lr: 1.0000e-03 eta: 6:04:37 time: 0.5956 data_time: 0.0344 memory: 33630 grad_norm: 4.4659 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1880 loss: 1.1880 2022/10/15 04:47:41 - mmengine - INFO - Epoch(train) [61][500/940] lr: 1.0000e-03 eta: 6:04:25 time: 0.5730 data_time: 0.0336 memory: 33630 grad_norm: 4.4766 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2968 loss: 1.2968 2022/10/15 04:47:52 - mmengine - INFO - Epoch(train) [61][520/940] lr: 1.0000e-03 eta: 6:04:13 time: 0.5798 data_time: 0.0348 memory: 33630 grad_norm: 4.5010 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2116 loss: 1.2116 2022/10/15 04:48:04 - mmengine - INFO - Epoch(train) [61][540/940] lr: 1.0000e-03 eta: 6:04:01 time: 0.5804 data_time: 0.0374 memory: 33630 grad_norm: 4.5038 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2531 loss: 1.2531 2022/10/15 04:48:15 - mmengine - INFO - Epoch(train) [61][560/940] lr: 1.0000e-03 eta: 6:03:49 time: 0.5781 data_time: 0.0323 memory: 33630 grad_norm: 4.5286 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2275 loss: 1.2275 2022/10/15 04:48:27 - mmengine - INFO - Epoch(train) [61][580/940] lr: 1.0000e-03 eta: 6:03:37 time: 0.5796 data_time: 0.0355 memory: 33630 grad_norm: 4.5947 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1910 loss: 1.1910 2022/10/15 04:48:39 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 04:48:39 - mmengine - INFO - Epoch(train) [61][600/940] lr: 1.0000e-03 eta: 6:03:25 time: 0.5775 data_time: 0.0426 memory: 33630 grad_norm: 4.5014 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.2003 loss: 1.2003 2022/10/15 04:48:50 - mmengine - INFO - Epoch(train) [61][620/940] lr: 1.0000e-03 eta: 6:03:13 time: 0.5731 data_time: 0.0375 memory: 33630 grad_norm: 4.4191 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1396 loss: 1.1396 2022/10/15 04:49:02 - mmengine - INFO - Epoch(train) [61][640/940] lr: 1.0000e-03 eta: 6:03:01 time: 0.5841 data_time: 0.0328 memory: 33630 grad_norm: 4.3879 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.2488 loss: 1.2488 2022/10/15 04:49:13 - mmengine - INFO - Epoch(train) [61][660/940] lr: 1.0000e-03 eta: 6:02:49 time: 0.5760 data_time: 0.0362 memory: 33630 grad_norm: 4.3891 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2444 loss: 1.2444 2022/10/15 04:49:25 - mmengine - INFO - Epoch(train) [61][680/940] lr: 1.0000e-03 eta: 6:02:37 time: 0.5816 data_time: 0.0385 memory: 33630 grad_norm: 4.4033 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2269 loss: 1.2269 2022/10/15 04:49:37 - mmengine - INFO - Epoch(train) [61][700/940] lr: 1.0000e-03 eta: 6:02:26 time: 0.5821 data_time: 0.0414 memory: 33630 grad_norm: 4.3573 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2200 loss: 1.2200 2022/10/15 04:49:48 - mmengine - INFO - Epoch(train) [61][720/940] lr: 1.0000e-03 eta: 6:02:14 time: 0.5853 data_time: 0.0394 memory: 33630 grad_norm: 4.4552 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2497 loss: 1.2497 2022/10/15 04:50:00 - mmengine - INFO - Epoch(train) [61][740/940] lr: 1.0000e-03 eta: 6:02:02 time: 0.5940 data_time: 0.0373 memory: 33630 grad_norm: 4.4721 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2284 loss: 1.2284 2022/10/15 04:50:12 - mmengine - INFO - Epoch(train) [61][760/940] lr: 1.0000e-03 eta: 6:01:50 time: 0.5836 data_time: 0.0335 memory: 33630 grad_norm: 4.3808 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1641 loss: 1.1641 2022/10/15 04:50:23 - mmengine - INFO - Epoch(train) [61][780/940] lr: 1.0000e-03 eta: 6:01:38 time: 0.5731 data_time: 0.0330 memory: 33630 grad_norm: 4.4605 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.1933 loss: 1.1933 2022/10/15 04:50:35 - mmengine - INFO - Epoch(train) [61][800/940] lr: 1.0000e-03 eta: 6:01:26 time: 0.5834 data_time: 0.0414 memory: 33630 grad_norm: 4.4650 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2385 loss: 1.2385 2022/10/15 04:50:47 - mmengine - INFO - Epoch(train) [61][820/940] lr: 1.0000e-03 eta: 6:01:14 time: 0.5880 data_time: 0.0379 memory: 33630 grad_norm: 4.5505 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2238 loss: 1.2238 2022/10/15 04:50:58 - mmengine - INFO - Epoch(train) [61][840/940] lr: 1.0000e-03 eta: 6:01:03 time: 0.5838 data_time: 0.0410 memory: 33630 grad_norm: 4.4682 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1389 loss: 1.1389 2022/10/15 04:51:10 - mmengine - INFO - Epoch(train) [61][860/940] lr: 1.0000e-03 eta: 6:00:51 time: 0.5764 data_time: 0.0341 memory: 33630 grad_norm: 4.5053 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3338 loss: 1.3338 2022/10/15 04:51:22 - mmengine - INFO - Epoch(train) [61][880/940] lr: 1.0000e-03 eta: 6:00:39 time: 0.5865 data_time: 0.0415 memory: 33630 grad_norm: 4.4808 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1575 loss: 1.1575 2022/10/15 04:51:33 - mmengine - INFO - Epoch(train) [61][900/940] lr: 1.0000e-03 eta: 6:00:27 time: 0.5908 data_time: 0.0343 memory: 33630 grad_norm: 4.4622 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2498 loss: 1.2498 2022/10/15 04:51:45 - mmengine - INFO - Epoch(train) [61][920/940] lr: 1.0000e-03 eta: 6:00:15 time: 0.5894 data_time: 0.0368 memory: 33630 grad_norm: 4.4589 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2161 loss: 1.2161 2022/10/15 04:51:56 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 04:51:56 - mmengine - INFO - Epoch(train) [61][940/940] lr: 1.0000e-03 eta: 6:00:03 time: 0.5413 data_time: 0.0352 memory: 33630 grad_norm: 4.7367 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.1291 loss: 1.1291 2022/10/15 04:52:10 - mmengine - INFO - Epoch(val) [61][20/78] eta: 0:00:41 time: 0.7179 data_time: 0.5473 memory: 5967 2022/10/15 04:52:20 - mmengine - INFO - Epoch(val) [61][40/78] eta: 0:00:18 time: 0.4842 data_time: 0.3162 memory: 5967 2022/10/15 04:52:33 - mmengine - INFO - Epoch(val) [61][60/78] eta: 0:00:11 time: 0.6405 data_time: 0.4716 memory: 5967 2022/10/15 04:52:46 - mmengine - INFO - Epoch(val) [61][78/78] acc/top1: 0.6895 acc/top5: 0.8792 acc/mean1: 0.6894 2022/10/15 04:52:46 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_56.pth is removed 2022/10/15 04:52:47 - mmengine - INFO - The best checkpoint with 0.6895 acc/top1 at 61 epoch is saved to best_acc/top1_epoch_61.pth. 2022/10/15 04:53:03 - mmengine - INFO - Epoch(train) [62][20/940] lr: 1.0000e-03 eta: 5:59:54 time: 0.8136 data_time: 0.2491 memory: 33630 grad_norm: 4.4786 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2609 loss: 1.2609 2022/10/15 04:53:15 - mmengine - INFO - Epoch(train) [62][40/940] lr: 1.0000e-03 eta: 5:59:42 time: 0.5816 data_time: 0.0334 memory: 33630 grad_norm: 4.4600 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1669 loss: 1.1669 2022/10/15 04:53:27 - mmengine - INFO - Epoch(train) [62][60/940] lr: 1.0000e-03 eta: 5:59:30 time: 0.5908 data_time: 0.0390 memory: 33630 grad_norm: 4.3572 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2214 loss: 1.2214 2022/10/15 04:53:38 - mmengine - INFO - Epoch(train) [62][80/940] lr: 1.0000e-03 eta: 5:59:18 time: 0.5807 data_time: 0.0353 memory: 33630 grad_norm: 4.4571 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1594 loss: 1.1594 2022/10/15 04:53:50 - mmengine - INFO - Epoch(train) [62][100/940] lr: 1.0000e-03 eta: 5:59:07 time: 0.5831 data_time: 0.0408 memory: 33630 grad_norm: 4.4368 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2797 loss: 1.2797 2022/10/15 04:54:01 - mmengine - INFO - Epoch(train) [62][120/940] lr: 1.0000e-03 eta: 5:58:54 time: 0.5698 data_time: 0.0325 memory: 33630 grad_norm: 4.3965 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3361 loss: 1.3361 2022/10/15 04:54:13 - mmengine - INFO - Epoch(train) [62][140/940] lr: 1.0000e-03 eta: 5:58:43 time: 0.5974 data_time: 0.0462 memory: 33630 grad_norm: 4.3681 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2147 loss: 1.2147 2022/10/15 04:54:25 - mmengine - INFO - Epoch(train) [62][160/940] lr: 1.0000e-03 eta: 5:58:31 time: 0.5791 data_time: 0.0377 memory: 33630 grad_norm: 4.4933 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2528 loss: 1.2528 2022/10/15 04:54:36 - mmengine - INFO - Epoch(train) [62][180/940] lr: 1.0000e-03 eta: 5:58:19 time: 0.5834 data_time: 0.0398 memory: 33630 grad_norm: 4.5064 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2466 loss: 1.2466 2022/10/15 04:54:48 - mmengine - INFO - Epoch(train) [62][200/940] lr: 1.0000e-03 eta: 5:58:07 time: 0.5819 data_time: 0.0319 memory: 33630 grad_norm: 4.5376 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1788 loss: 1.1788 2022/10/15 04:55:00 - mmengine - INFO - Epoch(train) [62][220/940] lr: 1.0000e-03 eta: 5:57:55 time: 0.5894 data_time: 0.0336 memory: 33630 grad_norm: 4.5395 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3518 loss: 1.3518 2022/10/15 04:55:11 - mmengine - INFO - Epoch(train) [62][240/940] lr: 1.0000e-03 eta: 5:57:43 time: 0.5800 data_time: 0.0366 memory: 33630 grad_norm: 4.4435 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2505 loss: 1.2505 2022/10/15 04:55:23 - mmengine - INFO - Epoch(train) [62][260/940] lr: 1.0000e-03 eta: 5:57:32 time: 0.5765 data_time: 0.0438 memory: 33630 grad_norm: 4.5248 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1747 loss: 1.1747 2022/10/15 04:55:35 - mmengine - INFO - Epoch(train) [62][280/940] lr: 1.0000e-03 eta: 5:57:20 time: 0.5802 data_time: 0.0300 memory: 33630 grad_norm: 4.4153 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1161 loss: 1.1161 2022/10/15 04:55:46 - mmengine - INFO - Epoch(train) [62][300/940] lr: 1.0000e-03 eta: 5:57:08 time: 0.5902 data_time: 0.0386 memory: 33630 grad_norm: 4.4487 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1852 loss: 1.1852 2022/10/15 04:55:58 - mmengine - INFO - Epoch(train) [62][320/940] lr: 1.0000e-03 eta: 5:56:56 time: 0.5693 data_time: 0.0366 memory: 33630 grad_norm: 4.5099 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0941 loss: 1.0941 2022/10/15 04:56:10 - mmengine - INFO - Epoch(train) [62][340/940] lr: 1.0000e-03 eta: 5:56:44 time: 0.5955 data_time: 0.0373 memory: 33630 grad_norm: 4.4722 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.2726 loss: 1.2726 2022/10/15 04:56:21 - mmengine - INFO - Epoch(train) [62][360/940] lr: 1.0000e-03 eta: 5:56:32 time: 0.5854 data_time: 0.0356 memory: 33630 grad_norm: 4.5398 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2828 loss: 1.2828 2022/10/15 04:56:33 - mmengine - INFO - Epoch(train) [62][380/940] lr: 1.0000e-03 eta: 5:56:20 time: 0.5848 data_time: 0.0331 memory: 33630 grad_norm: 4.6010 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1722 loss: 1.1722 2022/10/15 04:56:45 - mmengine - INFO - Epoch(train) [62][400/940] lr: 1.0000e-03 eta: 5:56:08 time: 0.5724 data_time: 0.0368 memory: 33630 grad_norm: 4.5061 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2908 loss: 1.2908 2022/10/15 04:56:56 - mmengine - INFO - Epoch(train) [62][420/940] lr: 1.0000e-03 eta: 5:55:57 time: 0.5857 data_time: 0.0372 memory: 33630 grad_norm: 4.5592 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4001 loss: 1.4001 2022/10/15 04:57:08 - mmengine - INFO - Epoch(train) [62][440/940] lr: 1.0000e-03 eta: 5:55:45 time: 0.5801 data_time: 0.0321 memory: 33630 grad_norm: 4.4462 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2149 loss: 1.2149 2022/10/15 04:57:20 - mmengine - INFO - Epoch(train) [62][460/940] lr: 1.0000e-03 eta: 5:55:33 time: 0.5809 data_time: 0.0415 memory: 33630 grad_norm: 4.5618 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2108 loss: 1.2108 2022/10/15 04:57:31 - mmengine - INFO - Epoch(train) [62][480/940] lr: 1.0000e-03 eta: 5:55:21 time: 0.5788 data_time: 0.0381 memory: 33630 grad_norm: 4.5219 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1993 loss: 1.1993 2022/10/15 04:57:43 - mmengine - INFO - Epoch(train) [62][500/940] lr: 1.0000e-03 eta: 5:55:09 time: 0.5763 data_time: 0.0326 memory: 33630 grad_norm: 4.4712 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2710 loss: 1.2710 2022/10/15 04:57:54 - mmengine - INFO - Epoch(train) [62][520/940] lr: 1.0000e-03 eta: 5:54:57 time: 0.5902 data_time: 0.0395 memory: 33630 grad_norm: 4.5944 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3016 loss: 1.3016 2022/10/15 04:58:06 - mmengine - INFO - Epoch(train) [62][540/940] lr: 1.0000e-03 eta: 5:54:45 time: 0.5751 data_time: 0.0427 memory: 33630 grad_norm: 4.4196 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3256 loss: 1.3256 2022/10/15 04:58:18 - mmengine - INFO - Epoch(train) [62][560/940] lr: 1.0000e-03 eta: 5:54:33 time: 0.5819 data_time: 0.0441 memory: 33630 grad_norm: 4.4277 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1452 loss: 1.1452 2022/10/15 04:58:29 - mmengine - INFO - Epoch(train) [62][580/940] lr: 1.0000e-03 eta: 5:54:21 time: 0.5829 data_time: 0.0325 memory: 33630 grad_norm: 4.4789 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1119 loss: 1.1119 2022/10/15 04:58:41 - mmengine - INFO - Epoch(train) [62][600/940] lr: 1.0000e-03 eta: 5:54:10 time: 0.5811 data_time: 0.0337 memory: 33630 grad_norm: 4.4040 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1671 loss: 1.1671 2022/10/15 04:58:52 - mmengine - INFO - Epoch(train) [62][620/940] lr: 1.0000e-03 eta: 5:53:58 time: 0.5786 data_time: 0.0324 memory: 33630 grad_norm: 4.5676 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1625 loss: 1.1625 2022/10/15 04:59:04 - mmengine - INFO - Epoch(train) [62][640/940] lr: 1.0000e-03 eta: 5:53:46 time: 0.5771 data_time: 0.0403 memory: 33630 grad_norm: 4.4401 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1561 loss: 1.1561 2022/10/15 04:59:16 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 04:59:16 - mmengine - INFO - Epoch(train) [62][660/940] lr: 1.0000e-03 eta: 5:53:34 time: 0.5839 data_time: 0.0313 memory: 33630 grad_norm: 4.5427 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2163 loss: 1.2163 2022/10/15 04:59:27 - mmengine - INFO - Epoch(train) [62][680/940] lr: 1.0000e-03 eta: 5:53:22 time: 0.5864 data_time: 0.0366 memory: 33630 grad_norm: 4.4833 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1497 loss: 1.1497 2022/10/15 04:59:39 - mmengine - INFO - Epoch(train) [62][700/940] lr: 1.0000e-03 eta: 5:53:10 time: 0.5811 data_time: 0.0365 memory: 33630 grad_norm: 4.5062 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1703 loss: 1.1703 2022/10/15 04:59:50 - mmengine - INFO - Epoch(train) [62][720/940] lr: 1.0000e-03 eta: 5:52:58 time: 0.5726 data_time: 0.0319 memory: 33630 grad_norm: 4.4590 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3176 loss: 1.3176 2022/10/15 05:00:02 - mmengine - INFO - Epoch(train) [62][740/940] lr: 1.0000e-03 eta: 5:52:46 time: 0.5725 data_time: 0.0363 memory: 33630 grad_norm: 4.4638 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.3648 loss: 1.3648 2022/10/15 05:00:14 - mmengine - INFO - Epoch(train) [62][760/940] lr: 1.0000e-03 eta: 5:52:34 time: 0.5935 data_time: 0.0492 memory: 33630 grad_norm: 4.5439 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.3187 loss: 1.3187 2022/10/15 05:00:26 - mmengine - INFO - Epoch(train) [62][780/940] lr: 1.0000e-03 eta: 5:52:23 time: 0.5906 data_time: 0.0306 memory: 33630 grad_norm: 4.5575 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1826 loss: 1.1826 2022/10/15 05:00:37 - mmengine - INFO - Epoch(train) [62][800/940] lr: 1.0000e-03 eta: 5:52:11 time: 0.5938 data_time: 0.0407 memory: 33630 grad_norm: 4.5095 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1772 loss: 1.1772 2022/10/15 05:00:49 - mmengine - INFO - Epoch(train) [62][820/940] lr: 1.0000e-03 eta: 5:51:59 time: 0.5905 data_time: 0.0423 memory: 33630 grad_norm: 4.5503 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2230 loss: 1.2230 2022/10/15 05:01:01 - mmengine - INFO - Epoch(train) [62][840/940] lr: 1.0000e-03 eta: 5:51:47 time: 0.5778 data_time: 0.0354 memory: 33630 grad_norm: 4.3929 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3537 loss: 1.3537 2022/10/15 05:01:12 - mmengine - INFO - Epoch(train) [62][860/940] lr: 1.0000e-03 eta: 5:51:35 time: 0.5727 data_time: 0.0324 memory: 33630 grad_norm: 4.5608 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2728 loss: 1.2728 2022/10/15 05:01:24 - mmengine - INFO - Epoch(train) [62][880/940] lr: 1.0000e-03 eta: 5:51:23 time: 0.5802 data_time: 0.0416 memory: 33630 grad_norm: 4.4617 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1712 loss: 1.1712 2022/10/15 05:01:36 - mmengine - INFO - Epoch(train) [62][900/940] lr: 1.0000e-03 eta: 5:51:12 time: 0.5936 data_time: 0.0430 memory: 33630 grad_norm: 4.5348 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2571 loss: 1.2571 2022/10/15 05:01:48 - mmengine - INFO - Epoch(train) [62][920/940] lr: 1.0000e-03 eta: 5:51:00 time: 0.5879 data_time: 0.0453 memory: 33630 grad_norm: 4.5833 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4382 loss: 1.4382 2022/10/15 05:01:58 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 05:01:58 - mmengine - INFO - Epoch(train) [62][940/940] lr: 1.0000e-03 eta: 5:50:47 time: 0.5408 data_time: 0.0287 memory: 33630 grad_norm: 4.7026 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.1377 loss: 1.1377 2022/10/15 05:02:12 - mmengine - INFO - Epoch(val) [62][20/78] eta: 0:00:40 time: 0.6965 data_time: 0.5262 memory: 5967 2022/10/15 05:02:22 - mmengine - INFO - Epoch(val) [62][40/78] eta: 0:00:19 time: 0.5056 data_time: 0.3359 memory: 5967 2022/10/15 05:02:36 - mmengine - INFO - Epoch(val) [62][60/78] eta: 0:00:11 time: 0.6628 data_time: 0.4930 memory: 5967 2022/10/15 05:02:47 - mmengine - INFO - Epoch(val) [62][78/78] acc/top1: 0.6871 acc/top5: 0.8790 acc/mean1: 0.6869 2022/10/15 05:03:04 - mmengine - INFO - Epoch(train) [63][20/940] lr: 1.0000e-03 eta: 5:50:38 time: 0.8155 data_time: 0.2186 memory: 33630 grad_norm: 4.5145 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2155 loss: 1.2155 2022/10/15 05:03:15 - mmengine - INFO - Epoch(train) [63][40/940] lr: 1.0000e-03 eta: 5:50:26 time: 0.5737 data_time: 0.0353 memory: 33630 grad_norm: 4.4137 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2568 loss: 1.2568 2022/10/15 05:03:27 - mmengine - INFO - Epoch(train) [63][60/940] lr: 1.0000e-03 eta: 5:50:15 time: 0.6049 data_time: 0.0399 memory: 33630 grad_norm: 4.4255 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2975 loss: 1.2975 2022/10/15 05:03:39 - mmengine - INFO - Epoch(train) [63][80/940] lr: 1.0000e-03 eta: 5:50:03 time: 0.5789 data_time: 0.0330 memory: 33630 grad_norm: 4.5194 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2417 loss: 1.2417 2022/10/15 05:03:51 - mmengine - INFO - Epoch(train) [63][100/940] lr: 1.0000e-03 eta: 5:49:51 time: 0.5932 data_time: 0.0367 memory: 33630 grad_norm: 4.6101 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1841 loss: 1.1841 2022/10/15 05:04:03 - mmengine - INFO - Epoch(train) [63][120/940] lr: 1.0000e-03 eta: 5:49:39 time: 0.5993 data_time: 0.0354 memory: 33630 grad_norm: 4.3763 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0690 loss: 1.0690 2022/10/15 05:04:14 - mmengine - INFO - Epoch(train) [63][140/940] lr: 1.0000e-03 eta: 5:49:28 time: 0.5857 data_time: 0.0324 memory: 33630 grad_norm: 4.6180 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1604 loss: 1.1604 2022/10/15 05:04:26 - mmengine - INFO - Epoch(train) [63][160/940] lr: 1.0000e-03 eta: 5:49:16 time: 0.5932 data_time: 0.0376 memory: 33630 grad_norm: 4.5984 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4088 loss: 1.4088 2022/10/15 05:04:38 - mmengine - INFO - Epoch(train) [63][180/940] lr: 1.0000e-03 eta: 5:49:04 time: 0.5828 data_time: 0.0401 memory: 33630 grad_norm: 4.4674 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1713 loss: 1.1713 2022/10/15 05:04:49 - mmengine - INFO - Epoch(train) [63][200/940] lr: 1.0000e-03 eta: 5:48:52 time: 0.5819 data_time: 0.0422 memory: 33630 grad_norm: 4.5052 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1631 loss: 1.1631 2022/10/15 05:05:01 - mmengine - INFO - Epoch(train) [63][220/940] lr: 1.0000e-03 eta: 5:48:40 time: 0.5848 data_time: 0.0435 memory: 33630 grad_norm: 4.4544 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3019 loss: 1.3019 2022/10/15 05:05:12 - mmengine - INFO - Epoch(train) [63][240/940] lr: 1.0000e-03 eta: 5:48:28 time: 0.5651 data_time: 0.0332 memory: 33630 grad_norm: 4.4883 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2382 loss: 1.2382 2022/10/15 05:05:24 - mmengine - INFO - Epoch(train) [63][260/940] lr: 1.0000e-03 eta: 5:48:16 time: 0.5766 data_time: 0.0330 memory: 33630 grad_norm: 4.5110 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3548 loss: 1.3548 2022/10/15 05:05:36 - mmengine - INFO - Epoch(train) [63][280/940] lr: 1.0000e-03 eta: 5:48:05 time: 0.5935 data_time: 0.0375 memory: 33630 grad_norm: 4.5479 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2472 loss: 1.2472 2022/10/15 05:05:47 - mmengine - INFO - Epoch(train) [63][300/940] lr: 1.0000e-03 eta: 5:47:53 time: 0.5761 data_time: 0.0422 memory: 33630 grad_norm: 4.4780 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1667 loss: 1.1667 2022/10/15 05:05:59 - mmengine - INFO - Epoch(train) [63][320/940] lr: 1.0000e-03 eta: 5:47:41 time: 0.5862 data_time: 0.0315 memory: 33630 grad_norm: 4.4998 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2572 loss: 1.2572 2022/10/15 05:06:11 - mmengine - INFO - Epoch(train) [63][340/940] lr: 1.0000e-03 eta: 5:47:29 time: 0.5858 data_time: 0.0334 memory: 33630 grad_norm: 4.5414 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1767 loss: 1.1767 2022/10/15 05:06:23 - mmengine - INFO - Epoch(train) [63][360/940] lr: 1.0000e-03 eta: 5:47:17 time: 0.5867 data_time: 0.0374 memory: 33630 grad_norm: 4.4168 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2109 loss: 1.2109 2022/10/15 05:06:34 - mmengine - INFO - Epoch(train) [63][380/940] lr: 1.0000e-03 eta: 5:47:05 time: 0.5898 data_time: 0.0400 memory: 33630 grad_norm: 4.4721 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2888 loss: 1.2888 2022/10/15 05:06:46 - mmengine - INFO - Epoch(train) [63][400/940] lr: 1.0000e-03 eta: 5:46:53 time: 0.5754 data_time: 0.0309 memory: 33630 grad_norm: 4.4465 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2972 loss: 1.2972 2022/10/15 05:06:57 - mmengine - INFO - Epoch(train) [63][420/940] lr: 1.0000e-03 eta: 5:46:42 time: 0.5768 data_time: 0.0330 memory: 33630 grad_norm: 4.6444 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3560 loss: 1.3560 2022/10/15 05:07:09 - mmengine - INFO - Epoch(train) [63][440/940] lr: 1.0000e-03 eta: 5:46:30 time: 0.5933 data_time: 0.0338 memory: 33630 grad_norm: 4.3559 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1043 loss: 1.1043 2022/10/15 05:07:21 - mmengine - INFO - Epoch(train) [63][460/940] lr: 1.0000e-03 eta: 5:46:18 time: 0.5788 data_time: 0.0356 memory: 33630 grad_norm: 4.5719 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1966 loss: 1.1966 2022/10/15 05:07:32 - mmengine - INFO - Epoch(train) [63][480/940] lr: 1.0000e-03 eta: 5:46:06 time: 0.5789 data_time: 0.0360 memory: 33630 grad_norm: 4.4873 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1835 loss: 1.1835 2022/10/15 05:07:44 - mmengine - INFO - Epoch(train) [63][500/940] lr: 1.0000e-03 eta: 5:45:54 time: 0.5858 data_time: 0.0351 memory: 33630 grad_norm: 4.5802 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2930 loss: 1.2930 2022/10/15 05:07:56 - mmengine - INFO - Epoch(train) [63][520/940] lr: 1.0000e-03 eta: 5:45:42 time: 0.5851 data_time: 0.0309 memory: 33630 grad_norm: 4.4578 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.1919 loss: 1.1919 2022/10/15 05:08:08 - mmengine - INFO - Epoch(train) [63][540/940] lr: 1.0000e-03 eta: 5:45:31 time: 0.5914 data_time: 0.0458 memory: 33630 grad_norm: 4.5727 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2867 loss: 1.2867 2022/10/15 05:08:19 - mmengine - INFO - Epoch(train) [63][560/940] lr: 1.0000e-03 eta: 5:45:19 time: 0.5828 data_time: 0.0314 memory: 33630 grad_norm: 4.5203 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2092 loss: 1.2092 2022/10/15 05:08:31 - mmengine - INFO - Epoch(train) [63][580/940] lr: 1.0000e-03 eta: 5:45:07 time: 0.5811 data_time: 0.0538 memory: 33630 grad_norm: 4.4714 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0700 loss: 1.0700 2022/10/15 05:08:43 - mmengine - INFO - Epoch(train) [63][600/940] lr: 1.0000e-03 eta: 5:44:55 time: 0.5796 data_time: 0.0440 memory: 33630 grad_norm: 4.4573 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2833 loss: 1.2833 2022/10/15 05:08:54 - mmengine - INFO - Epoch(train) [63][620/940] lr: 1.0000e-03 eta: 5:44:43 time: 0.5796 data_time: 0.0360 memory: 33630 grad_norm: 4.5058 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1578 loss: 1.1578 2022/10/15 05:09:06 - mmengine - INFO - Epoch(train) [63][640/940] lr: 1.0000e-03 eta: 5:44:31 time: 0.5872 data_time: 0.0372 memory: 33630 grad_norm: 4.4161 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2028 loss: 1.2028 2022/10/15 05:09:18 - mmengine - INFO - Epoch(train) [63][660/940] lr: 1.0000e-03 eta: 5:44:19 time: 0.5816 data_time: 0.0378 memory: 33630 grad_norm: 4.5340 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2000 loss: 1.2000 2022/10/15 05:09:29 - mmengine - INFO - Epoch(train) [63][680/940] lr: 1.0000e-03 eta: 5:44:07 time: 0.5828 data_time: 0.0414 memory: 33630 grad_norm: 4.3887 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2019 loss: 1.2019 2022/10/15 05:09:41 - mmengine - INFO - Epoch(train) [63][700/940] lr: 1.0000e-03 eta: 5:43:56 time: 0.5842 data_time: 0.0332 memory: 33630 grad_norm: 4.5424 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2828 loss: 1.2828 2022/10/15 05:09:52 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 05:09:52 - mmengine - INFO - Epoch(train) [63][720/940] lr: 1.0000e-03 eta: 5:43:44 time: 0.5804 data_time: 0.0405 memory: 33630 grad_norm: 4.4744 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2734 loss: 1.2734 2022/10/15 05:10:04 - mmengine - INFO - Epoch(train) [63][740/940] lr: 1.0000e-03 eta: 5:43:32 time: 0.5828 data_time: 0.0405 memory: 33630 grad_norm: 4.4897 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3107 loss: 1.3107 2022/10/15 05:10:16 - mmengine - INFO - Epoch(train) [63][760/940] lr: 1.0000e-03 eta: 5:43:20 time: 0.5973 data_time: 0.0416 memory: 33630 grad_norm: 4.5193 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2594 loss: 1.2594 2022/10/15 05:10:28 - mmengine - INFO - Epoch(train) [63][780/940] lr: 1.0000e-03 eta: 5:43:08 time: 0.5813 data_time: 0.0356 memory: 33630 grad_norm: 4.4642 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3663 loss: 1.3663 2022/10/15 05:10:39 - mmengine - INFO - Epoch(train) [63][800/940] lr: 1.0000e-03 eta: 5:42:56 time: 0.5883 data_time: 0.0421 memory: 33630 grad_norm: 4.5262 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3247 loss: 1.3247 2022/10/15 05:10:51 - mmengine - INFO - Epoch(train) [63][820/940] lr: 1.0000e-03 eta: 5:42:45 time: 0.5811 data_time: 0.0400 memory: 33630 grad_norm: 4.5693 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.1910 loss: 1.1910 2022/10/15 05:11:03 - mmengine - INFO - Epoch(train) [63][840/940] lr: 1.0000e-03 eta: 5:42:33 time: 0.5870 data_time: 0.0376 memory: 33630 grad_norm: 4.5995 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2372 loss: 1.2372 2022/10/15 05:11:15 - mmengine - INFO - Epoch(train) [63][860/940] lr: 1.0000e-03 eta: 5:42:21 time: 0.5855 data_time: 0.0330 memory: 33630 grad_norm: 4.5217 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0800 loss: 1.0800 2022/10/15 05:11:26 - mmengine - INFO - Epoch(train) [63][880/940] lr: 1.0000e-03 eta: 5:42:09 time: 0.5751 data_time: 0.0307 memory: 33630 grad_norm: 4.6418 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3504 loss: 1.3504 2022/10/15 05:11:38 - mmengine - INFO - Epoch(train) [63][900/940] lr: 1.0000e-03 eta: 5:41:57 time: 0.5905 data_time: 0.0379 memory: 33630 grad_norm: 4.5715 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1371 loss: 1.1371 2022/10/15 05:11:49 - mmengine - INFO - Epoch(train) [63][920/940] lr: 1.0000e-03 eta: 5:41:45 time: 0.5798 data_time: 0.0341 memory: 33630 grad_norm: 4.5822 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.2411 loss: 1.2411 2022/10/15 05:12:00 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 05:12:00 - mmengine - INFO - Epoch(train) [63][940/940] lr: 1.0000e-03 eta: 5:41:33 time: 0.5437 data_time: 0.0343 memory: 33630 grad_norm: 4.7196 top1_acc: 0.5714 top5_acc: 1.0000 loss_cls: 1.2875 loss: 1.2875 2022/10/15 05:12:00 - mmengine - INFO - Saving checkpoint at 63 epochs 2022/10/15 05:12:16 - mmengine - INFO - Epoch(val) [63][20/78] eta: 0:00:41 time: 0.7163 data_time: 0.5460 memory: 5967 2022/10/15 05:12:26 - mmengine - INFO - Epoch(val) [63][40/78] eta: 0:00:19 time: 0.5023 data_time: 0.3329 memory: 5967 2022/10/15 05:12:39 - mmengine - INFO - Epoch(val) [63][60/78] eta: 0:00:12 time: 0.6728 data_time: 0.5021 memory: 5967 2022/10/15 05:12:50 - mmengine - INFO - Epoch(val) [63][78/78] acc/top1: 0.6871 acc/top5: 0.8776 acc/mean1: 0.6869 2022/10/15 05:13:07 - mmengine - INFO - Epoch(train) [64][20/940] lr: 1.0000e-03 eta: 5:41:24 time: 0.8402 data_time: 0.2316 memory: 33630 grad_norm: 4.3821 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2666 loss: 1.2666 2022/10/15 05:13:19 - mmengine - INFO - Epoch(train) [64][40/940] lr: 1.0000e-03 eta: 5:41:12 time: 0.5893 data_time: 0.0363 memory: 33630 grad_norm: 4.5679 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3510 loss: 1.3510 2022/10/15 05:13:31 - mmengine - INFO - Epoch(train) [64][60/940] lr: 1.0000e-03 eta: 5:41:01 time: 0.6015 data_time: 0.0411 memory: 33630 grad_norm: 4.4200 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0715 loss: 1.0715 2022/10/15 05:13:42 - mmengine - INFO - Epoch(train) [64][80/940] lr: 1.0000e-03 eta: 5:40:49 time: 0.5836 data_time: 0.0344 memory: 33630 grad_norm: 4.4752 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2502 loss: 1.2502 2022/10/15 05:13:54 - mmengine - INFO - Epoch(train) [64][100/940] lr: 1.0000e-03 eta: 5:40:37 time: 0.5948 data_time: 0.0410 memory: 33630 grad_norm: 4.4509 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2541 loss: 1.2541 2022/10/15 05:14:06 - mmengine - INFO - Epoch(train) [64][120/940] lr: 1.0000e-03 eta: 5:40:25 time: 0.5793 data_time: 0.0397 memory: 33630 grad_norm: 4.4640 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1972 loss: 1.1972 2022/10/15 05:14:18 - mmengine - INFO - Epoch(train) [64][140/940] lr: 1.0000e-03 eta: 5:40:13 time: 0.5866 data_time: 0.0386 memory: 33630 grad_norm: 4.5009 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2222 loss: 1.2222 2022/10/15 05:14:29 - mmengine - INFO - Epoch(train) [64][160/940] lr: 1.0000e-03 eta: 5:40:02 time: 0.5848 data_time: 0.0429 memory: 33630 grad_norm: 4.5737 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.2933 loss: 1.2933 2022/10/15 05:14:41 - mmengine - INFO - Epoch(train) [64][180/940] lr: 1.0000e-03 eta: 5:39:50 time: 0.5844 data_time: 0.0323 memory: 33630 grad_norm: 4.4662 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2134 loss: 1.2134 2022/10/15 05:14:53 - mmengine - INFO - Epoch(train) [64][200/940] lr: 1.0000e-03 eta: 5:39:38 time: 0.5827 data_time: 0.0324 memory: 33630 grad_norm: 4.4610 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2583 loss: 1.2583 2022/10/15 05:15:04 - mmengine - INFO - Epoch(train) [64][220/940] lr: 1.0000e-03 eta: 5:39:26 time: 0.5854 data_time: 0.0354 memory: 33630 grad_norm: 4.5882 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3832 loss: 1.3832 2022/10/15 05:15:16 - mmengine - INFO - Epoch(train) [64][240/940] lr: 1.0000e-03 eta: 5:39:14 time: 0.5835 data_time: 0.0441 memory: 33630 grad_norm: 4.5290 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2761 loss: 1.2761 2022/10/15 05:15:28 - mmengine - INFO - Epoch(train) [64][260/940] lr: 1.0000e-03 eta: 5:39:02 time: 0.5861 data_time: 0.0384 memory: 33630 grad_norm: 4.4890 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3232 loss: 1.3232 2022/10/15 05:15:39 - mmengine - INFO - Epoch(train) [64][280/940] lr: 1.0000e-03 eta: 5:38:50 time: 0.5770 data_time: 0.0373 memory: 33630 grad_norm: 4.4997 top1_acc: 0.5312 top5_acc: 0.9688 loss_cls: 1.0998 loss: 1.0998 2022/10/15 05:15:51 - mmengine - INFO - Epoch(train) [64][300/940] lr: 1.0000e-03 eta: 5:38:39 time: 0.5769 data_time: 0.0328 memory: 33630 grad_norm: 4.4364 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.1466 loss: 1.1466 2022/10/15 05:16:02 - mmengine - INFO - Epoch(train) [64][320/940] lr: 1.0000e-03 eta: 5:38:27 time: 0.5832 data_time: 0.0318 memory: 33630 grad_norm: 4.5448 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.3573 loss: 1.3573 2022/10/15 05:16:14 - mmengine - INFO - Epoch(train) [64][340/940] lr: 1.0000e-03 eta: 5:38:15 time: 0.5826 data_time: 0.0341 memory: 33630 grad_norm: 4.4842 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2465 loss: 1.2465 2022/10/15 05:16:26 - mmengine - INFO - Epoch(train) [64][360/940] lr: 1.0000e-03 eta: 5:38:03 time: 0.5867 data_time: 0.0364 memory: 33630 grad_norm: 4.5136 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1259 loss: 1.1259 2022/10/15 05:16:37 - mmengine - INFO - Epoch(train) [64][380/940] lr: 1.0000e-03 eta: 5:37:51 time: 0.5804 data_time: 0.0331 memory: 33630 grad_norm: 4.4707 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1766 loss: 1.1766 2022/10/15 05:16:49 - mmengine - INFO - Epoch(train) [64][400/940] lr: 1.0000e-03 eta: 5:37:39 time: 0.5755 data_time: 0.0350 memory: 33630 grad_norm: 4.5374 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1370 loss: 1.1370 2022/10/15 05:17:01 - mmengine - INFO - Epoch(train) [64][420/940] lr: 1.0000e-03 eta: 5:37:27 time: 0.5811 data_time: 0.0344 memory: 33630 grad_norm: 4.4809 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.2710 loss: 1.2710 2022/10/15 05:17:12 - mmengine - INFO - Epoch(train) [64][440/940] lr: 1.0000e-03 eta: 5:37:15 time: 0.5744 data_time: 0.0393 memory: 33630 grad_norm: 4.5258 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2396 loss: 1.2396 2022/10/15 05:17:24 - mmengine - INFO - Epoch(train) [64][460/940] lr: 1.0000e-03 eta: 5:37:03 time: 0.5846 data_time: 0.0407 memory: 33630 grad_norm: 4.5730 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1702 loss: 1.1702 2022/10/15 05:17:35 - mmengine - INFO - Epoch(train) [64][480/940] lr: 1.0000e-03 eta: 5:36:52 time: 0.5810 data_time: 0.0366 memory: 33630 grad_norm: 4.4216 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2991 loss: 1.2991 2022/10/15 05:17:47 - mmengine - INFO - Epoch(train) [64][500/940] lr: 1.0000e-03 eta: 5:36:40 time: 0.5755 data_time: 0.0316 memory: 33630 grad_norm: 4.5665 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1372 loss: 1.1372 2022/10/15 05:17:58 - mmengine - INFO - Epoch(train) [64][520/940] lr: 1.0000e-03 eta: 5:36:28 time: 0.5766 data_time: 0.0376 memory: 33630 grad_norm: 4.5284 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2704 loss: 1.2704 2022/10/15 05:18:10 - mmengine - INFO - Epoch(train) [64][540/940] lr: 1.0000e-03 eta: 5:36:16 time: 0.5737 data_time: 0.0309 memory: 33630 grad_norm: 4.6264 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3348 loss: 1.3348 2022/10/15 05:18:21 - mmengine - INFO - Epoch(train) [64][560/940] lr: 1.0000e-03 eta: 5:36:04 time: 0.5781 data_time: 0.0397 memory: 33630 grad_norm: 4.4832 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1143 loss: 1.1143 2022/10/15 05:18:33 - mmengine - INFO - Epoch(train) [64][580/940] lr: 1.0000e-03 eta: 5:35:52 time: 0.5728 data_time: 0.0357 memory: 33630 grad_norm: 4.5190 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1386 loss: 1.1386 2022/10/15 05:18:45 - mmengine - INFO - Epoch(train) [64][600/940] lr: 1.0000e-03 eta: 5:35:40 time: 0.5825 data_time: 0.0349 memory: 33630 grad_norm: 4.5635 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1943 loss: 1.1943 2022/10/15 05:18:56 - mmengine - INFO - Epoch(train) [64][620/940] lr: 1.0000e-03 eta: 5:35:28 time: 0.5823 data_time: 0.0356 memory: 33630 grad_norm: 4.5975 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2748 loss: 1.2748 2022/10/15 05:19:08 - mmengine - INFO - Epoch(train) [64][640/940] lr: 1.0000e-03 eta: 5:35:16 time: 0.5975 data_time: 0.0352 memory: 33630 grad_norm: 4.5682 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2002 loss: 1.2002 2022/10/15 05:19:20 - mmengine - INFO - Epoch(train) [64][660/940] lr: 1.0000e-03 eta: 5:35:04 time: 0.5750 data_time: 0.0318 memory: 33630 grad_norm: 4.5179 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2785 loss: 1.2785 2022/10/15 05:19:31 - mmengine - INFO - Epoch(train) [64][680/940] lr: 1.0000e-03 eta: 5:34:53 time: 0.5799 data_time: 0.0361 memory: 33630 grad_norm: 4.5393 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2173 loss: 1.2173 2022/10/15 05:19:43 - mmengine - INFO - Epoch(train) [64][700/940] lr: 1.0000e-03 eta: 5:34:41 time: 0.5866 data_time: 0.0351 memory: 33630 grad_norm: 4.6326 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4273 loss: 1.4273 2022/10/15 05:19:55 - mmengine - INFO - Epoch(train) [64][720/940] lr: 1.0000e-03 eta: 5:34:29 time: 0.5767 data_time: 0.0387 memory: 33630 grad_norm: 4.5381 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1899 loss: 1.1899 2022/10/15 05:20:06 - mmengine - INFO - Epoch(train) [64][740/940] lr: 1.0000e-03 eta: 5:34:17 time: 0.5832 data_time: 0.0359 memory: 33630 grad_norm: 4.5752 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2325 loss: 1.2325 2022/10/15 05:20:18 - mmengine - INFO - Epoch(train) [64][760/940] lr: 1.0000e-03 eta: 5:34:05 time: 0.5761 data_time: 0.0403 memory: 33630 grad_norm: 4.5920 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1403 loss: 1.1403 2022/10/15 05:20:29 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 05:20:29 - mmengine - INFO - Epoch(train) [64][780/940] lr: 1.0000e-03 eta: 5:33:53 time: 0.5803 data_time: 0.0352 memory: 33630 grad_norm: 4.5027 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3289 loss: 1.3289 2022/10/15 05:20:41 - mmengine - INFO - Epoch(train) [64][800/940] lr: 1.0000e-03 eta: 5:33:41 time: 0.5917 data_time: 0.0472 memory: 33630 grad_norm: 4.6530 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3061 loss: 1.3061 2022/10/15 05:20:53 - mmengine - INFO - Epoch(train) [64][820/940] lr: 1.0000e-03 eta: 5:33:30 time: 0.5804 data_time: 0.0394 memory: 33630 grad_norm: 4.4582 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3574 loss: 1.3574 2022/10/15 05:21:04 - mmengine - INFO - Epoch(train) [64][840/940] lr: 1.0000e-03 eta: 5:33:18 time: 0.5826 data_time: 0.0375 memory: 33630 grad_norm: 4.6110 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3090 loss: 1.3090 2022/10/15 05:21:16 - mmengine - INFO - Epoch(train) [64][860/940] lr: 1.0000e-03 eta: 5:33:06 time: 0.5805 data_time: 0.0296 memory: 33630 grad_norm: 4.5118 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2885 loss: 1.2885 2022/10/15 05:21:28 - mmengine - INFO - Epoch(train) [64][880/940] lr: 1.0000e-03 eta: 5:32:54 time: 0.5768 data_time: 0.0449 memory: 33630 grad_norm: 4.5791 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2620 loss: 1.2620 2022/10/15 05:21:39 - mmengine - INFO - Epoch(train) [64][900/940] lr: 1.0000e-03 eta: 5:32:42 time: 0.5739 data_time: 0.0338 memory: 33630 grad_norm: 4.4831 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1922 loss: 1.1922 2022/10/15 05:21:51 - mmengine - INFO - Epoch(train) [64][920/940] lr: 1.0000e-03 eta: 5:32:30 time: 0.5818 data_time: 0.0418 memory: 33630 grad_norm: 4.5319 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1799 loss: 1.1799 2022/10/15 05:22:02 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 05:22:02 - mmengine - INFO - Epoch(train) [64][940/940] lr: 1.0000e-03 eta: 5:32:18 time: 0.5448 data_time: 0.0354 memory: 33630 grad_norm: 4.7514 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.2464 loss: 1.2464 2022/10/15 05:22:16 - mmengine - INFO - Epoch(val) [64][20/78] eta: 0:00:42 time: 0.7322 data_time: 0.5608 memory: 5967 2022/10/15 05:22:26 - mmengine - INFO - Epoch(val) [64][40/78] eta: 0:00:18 time: 0.4972 data_time: 0.3275 memory: 5967 2022/10/15 05:22:40 - mmengine - INFO - Epoch(val) [64][60/78] eta: 0:00:12 time: 0.6705 data_time: 0.5002 memory: 5967 2022/10/15 05:22:50 - mmengine - INFO - Epoch(val) [64][78/78] acc/top1: 0.6828 acc/top5: 0.8778 acc/mean1: 0.6826 2022/10/15 05:23:07 - mmengine - INFO - Epoch(train) [65][20/940] lr: 1.0000e-03 eta: 5:32:09 time: 0.8566 data_time: 0.2311 memory: 33630 grad_norm: 4.5567 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1948 loss: 1.1948 2022/10/15 05:23:19 - mmengine - INFO - Epoch(train) [65][40/940] lr: 1.0000e-03 eta: 5:31:57 time: 0.5799 data_time: 0.0323 memory: 33630 grad_norm: 4.5861 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3074 loss: 1.3074 2022/10/15 05:23:31 - mmengine - INFO - Epoch(train) [65][60/940] lr: 1.0000e-03 eta: 5:31:45 time: 0.5885 data_time: 0.0350 memory: 33630 grad_norm: 4.5888 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2938 loss: 1.2938 2022/10/15 05:23:42 - mmengine - INFO - Epoch(train) [65][80/940] lr: 1.0000e-03 eta: 5:31:33 time: 0.5800 data_time: 0.0417 memory: 33630 grad_norm: 4.5679 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2110 loss: 1.2110 2022/10/15 05:23:54 - mmengine - INFO - Epoch(train) [65][100/940] lr: 1.0000e-03 eta: 5:31:22 time: 0.6085 data_time: 0.0411 memory: 33630 grad_norm: 4.4628 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2270 loss: 1.2270 2022/10/15 05:24:06 - mmengine - INFO - Epoch(train) [65][120/940] lr: 1.0000e-03 eta: 5:31:10 time: 0.5944 data_time: 0.0408 memory: 33630 grad_norm: 4.4433 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0794 loss: 1.0794 2022/10/15 05:24:18 - mmengine - INFO - Epoch(train) [65][140/940] lr: 1.0000e-03 eta: 5:30:58 time: 0.5934 data_time: 0.0290 memory: 33630 grad_norm: 4.5012 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2142 loss: 1.2142 2022/10/15 05:24:30 - mmengine - INFO - Epoch(train) [65][160/940] lr: 1.0000e-03 eta: 5:30:47 time: 0.5866 data_time: 0.0369 memory: 33630 grad_norm: 4.5322 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1616 loss: 1.1616 2022/10/15 05:24:42 - mmengine - INFO - Epoch(train) [65][180/940] lr: 1.0000e-03 eta: 5:30:35 time: 0.5923 data_time: 0.0373 memory: 33630 grad_norm: 4.5030 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3268 loss: 1.3268 2022/10/15 05:24:53 - mmengine - INFO - Epoch(train) [65][200/940] lr: 1.0000e-03 eta: 5:30:23 time: 0.5749 data_time: 0.0324 memory: 33630 grad_norm: 4.4354 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.3023 loss: 1.3023 2022/10/15 05:25:05 - mmengine - INFO - Epoch(train) [65][220/940] lr: 1.0000e-03 eta: 5:30:11 time: 0.5866 data_time: 0.0326 memory: 33630 grad_norm: 4.6204 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2467 loss: 1.2467 2022/10/15 05:25:17 - mmengine - INFO - Epoch(train) [65][240/940] lr: 1.0000e-03 eta: 5:29:59 time: 0.5748 data_time: 0.0344 memory: 33630 grad_norm: 4.5563 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1799 loss: 1.1799 2022/10/15 05:25:28 - mmengine - INFO - Epoch(train) [65][260/940] lr: 1.0000e-03 eta: 5:29:47 time: 0.5829 data_time: 0.0387 memory: 33630 grad_norm: 4.5741 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2500 loss: 1.2500 2022/10/15 05:25:40 - mmengine - INFO - Epoch(train) [65][280/940] lr: 1.0000e-03 eta: 5:29:35 time: 0.5795 data_time: 0.0382 memory: 33630 grad_norm: 4.5117 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.3014 loss: 1.3014 2022/10/15 05:25:51 - mmengine - INFO - Epoch(train) [65][300/940] lr: 1.0000e-03 eta: 5:29:24 time: 0.5829 data_time: 0.0353 memory: 33630 grad_norm: 4.5170 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2316 loss: 1.2316 2022/10/15 05:26:03 - mmengine - INFO - Epoch(train) [65][320/940] lr: 1.0000e-03 eta: 5:29:12 time: 0.5773 data_time: 0.0376 memory: 33630 grad_norm: 4.4759 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1770 loss: 1.1770 2022/10/15 05:26:15 - mmengine - INFO - Epoch(train) [65][340/940] lr: 1.0000e-03 eta: 5:29:00 time: 0.5932 data_time: 0.0467 memory: 33630 grad_norm: 4.5423 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2356 loss: 1.2356 2022/10/15 05:26:26 - mmengine - INFO - Epoch(train) [65][360/940] lr: 1.0000e-03 eta: 5:28:48 time: 0.5790 data_time: 0.0377 memory: 33630 grad_norm: 4.4419 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1264 loss: 1.1264 2022/10/15 05:26:38 - mmengine - INFO - Epoch(train) [65][380/940] lr: 1.0000e-03 eta: 5:28:36 time: 0.5910 data_time: 0.0323 memory: 33630 grad_norm: 4.5397 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2425 loss: 1.2425 2022/10/15 05:26:50 - mmengine - INFO - Epoch(train) [65][400/940] lr: 1.0000e-03 eta: 5:28:24 time: 0.5802 data_time: 0.0325 memory: 33630 grad_norm: 4.5461 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.2647 loss: 1.2647 2022/10/15 05:27:01 - mmengine - INFO - Epoch(train) [65][420/940] lr: 1.0000e-03 eta: 5:28:12 time: 0.5779 data_time: 0.0301 memory: 33630 grad_norm: 4.5390 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2128 loss: 1.2128 2022/10/15 05:27:13 - mmengine - INFO - Epoch(train) [65][440/940] lr: 1.0000e-03 eta: 5:28:01 time: 0.5823 data_time: 0.0334 memory: 33630 grad_norm: 4.5883 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.2098 loss: 1.2098 2022/10/15 05:27:25 - mmengine - INFO - Epoch(train) [65][460/940] lr: 1.0000e-03 eta: 5:27:49 time: 0.5851 data_time: 0.0328 memory: 33630 grad_norm: 4.5157 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1324 loss: 1.1324 2022/10/15 05:27:36 - mmengine - INFO - Epoch(train) [65][480/940] lr: 1.0000e-03 eta: 5:27:37 time: 0.5728 data_time: 0.0376 memory: 33630 grad_norm: 4.5644 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1992 loss: 1.1992 2022/10/15 05:27:48 - mmengine - INFO - Epoch(train) [65][500/940] lr: 1.0000e-03 eta: 5:27:25 time: 0.5884 data_time: 0.0450 memory: 33630 grad_norm: 4.5214 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3414 loss: 1.3414 2022/10/15 05:28:00 - mmengine - INFO - Epoch(train) [65][520/940] lr: 1.0000e-03 eta: 5:27:13 time: 0.5921 data_time: 0.0318 memory: 33630 grad_norm: 4.5477 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2064 loss: 1.2064 2022/10/15 05:28:11 - mmengine - INFO - Epoch(train) [65][540/940] lr: 1.0000e-03 eta: 5:27:01 time: 0.5791 data_time: 0.0406 memory: 33630 grad_norm: 4.6076 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2357 loss: 1.2357 2022/10/15 05:28:23 - mmengine - INFO - Epoch(train) [65][560/940] lr: 1.0000e-03 eta: 5:26:49 time: 0.5729 data_time: 0.0411 memory: 33630 grad_norm: 4.5259 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2810 loss: 1.2810 2022/10/15 05:28:35 - mmengine - INFO - Epoch(train) [65][580/940] lr: 1.0000e-03 eta: 5:26:38 time: 0.5926 data_time: 0.0326 memory: 33630 grad_norm: 4.5499 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2007 loss: 1.2007 2022/10/15 05:28:46 - mmengine - INFO - Epoch(train) [65][600/940] lr: 1.0000e-03 eta: 5:26:26 time: 0.5828 data_time: 0.0319 memory: 33630 grad_norm: 4.6037 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3079 loss: 1.3079 2022/10/15 05:28:58 - mmengine - INFO - Epoch(train) [65][620/940] lr: 1.0000e-03 eta: 5:26:14 time: 0.5726 data_time: 0.0427 memory: 33630 grad_norm: 4.6334 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3864 loss: 1.3864 2022/10/15 05:29:09 - mmengine - INFO - Epoch(train) [65][640/940] lr: 1.0000e-03 eta: 5:26:02 time: 0.5735 data_time: 0.0302 memory: 33630 grad_norm: 4.5150 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2256 loss: 1.2256 2022/10/15 05:29:21 - mmengine - INFO - Epoch(train) [65][660/940] lr: 1.0000e-03 eta: 5:25:50 time: 0.5856 data_time: 0.0392 memory: 33630 grad_norm: 4.6053 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2012 loss: 1.2012 2022/10/15 05:29:33 - mmengine - INFO - Epoch(train) [65][680/940] lr: 1.0000e-03 eta: 5:25:38 time: 0.5820 data_time: 0.0401 memory: 33630 grad_norm: 4.6525 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2365 loss: 1.2365 2022/10/15 05:29:45 - mmengine - INFO - Epoch(train) [65][700/940] lr: 1.0000e-03 eta: 5:25:26 time: 0.5909 data_time: 0.0379 memory: 33630 grad_norm: 4.6199 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2957 loss: 1.2957 2022/10/15 05:29:56 - mmengine - INFO - Epoch(train) [65][720/940] lr: 1.0000e-03 eta: 5:25:14 time: 0.5830 data_time: 0.0341 memory: 33630 grad_norm: 4.5872 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3835 loss: 1.3835 2022/10/15 05:30:08 - mmengine - INFO - Epoch(train) [65][740/940] lr: 1.0000e-03 eta: 5:25:03 time: 0.5779 data_time: 0.0401 memory: 33630 grad_norm: 4.6219 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2481 loss: 1.2481 2022/10/15 05:30:19 - mmengine - INFO - Epoch(train) [65][760/940] lr: 1.0000e-03 eta: 5:24:51 time: 0.5810 data_time: 0.0321 memory: 33630 grad_norm: 4.6588 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2848 loss: 1.2848 2022/10/15 05:30:31 - mmengine - INFO - Epoch(train) [65][780/940] lr: 1.0000e-03 eta: 5:24:39 time: 0.5838 data_time: 0.0350 memory: 33630 grad_norm: 4.6170 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2504 loss: 1.2504 2022/10/15 05:30:43 - mmengine - INFO - Epoch(train) [65][800/940] lr: 1.0000e-03 eta: 5:24:27 time: 0.5775 data_time: 0.0404 memory: 33630 grad_norm: 4.5693 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0780 loss: 1.0780 2022/10/15 05:30:54 - mmengine - INFO - Epoch(train) [65][820/940] lr: 1.0000e-03 eta: 5:24:15 time: 0.5872 data_time: 0.0383 memory: 33630 grad_norm: 4.4900 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3406 loss: 1.3406 2022/10/15 05:31:06 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 05:31:06 - mmengine - INFO - Epoch(train) [65][840/940] lr: 1.0000e-03 eta: 5:24:03 time: 0.5868 data_time: 0.0361 memory: 33630 grad_norm: 4.5646 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2216 loss: 1.2216 2022/10/15 05:31:18 - mmengine - INFO - Epoch(train) [65][860/940] lr: 1.0000e-03 eta: 5:23:51 time: 0.5788 data_time: 0.0367 memory: 33630 grad_norm: 4.5705 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2846 loss: 1.2846 2022/10/15 05:31:29 - mmengine - INFO - Epoch(train) [65][880/940] lr: 1.0000e-03 eta: 5:23:40 time: 0.5807 data_time: 0.0363 memory: 33630 grad_norm: 4.5789 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3531 loss: 1.3531 2022/10/15 05:31:41 - mmengine - INFO - Epoch(train) [65][900/940] lr: 1.0000e-03 eta: 5:23:28 time: 0.5891 data_time: 0.0386 memory: 33630 grad_norm: 4.4406 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1760 loss: 1.1760 2022/10/15 05:31:53 - mmengine - INFO - Epoch(train) [65][920/940] lr: 1.0000e-03 eta: 5:23:16 time: 0.5820 data_time: 0.0375 memory: 33630 grad_norm: 4.6793 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1677 loss: 1.1677 2022/10/15 05:32:04 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 05:32:04 - mmengine - INFO - Epoch(train) [65][940/940] lr: 1.0000e-03 eta: 5:23:04 time: 0.5498 data_time: 0.0348 memory: 33630 grad_norm: 4.8983 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.4963 loss: 1.4963 2022/10/15 05:32:18 - mmengine - INFO - Epoch(val) [65][20/78] eta: 0:00:42 time: 0.7244 data_time: 0.5521 memory: 5967 2022/10/15 05:32:28 - mmengine - INFO - Epoch(val) [65][40/78] eta: 0:00:18 time: 0.4981 data_time: 0.3289 memory: 5967 2022/10/15 05:32:41 - mmengine - INFO - Epoch(val) [65][60/78] eta: 0:00:11 time: 0.6517 data_time: 0.4814 memory: 5967 2022/10/15 05:32:53 - mmengine - INFO - Epoch(val) [65][78/78] acc/top1: 0.6879 acc/top5: 0.8784 acc/mean1: 0.6877 2022/10/15 05:33:09 - mmengine - INFO - Epoch(train) [66][20/940] lr: 1.0000e-03 eta: 5:22:54 time: 0.8150 data_time: 0.2053 memory: 33630 grad_norm: 4.5296 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2142 loss: 1.2142 2022/10/15 05:33:21 - mmengine - INFO - Epoch(train) [66][40/940] lr: 1.0000e-03 eta: 5:22:42 time: 0.5816 data_time: 0.0309 memory: 33630 grad_norm: 4.6019 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2669 loss: 1.2669 2022/10/15 05:33:33 - mmengine - INFO - Epoch(train) [66][60/940] lr: 1.0000e-03 eta: 5:22:31 time: 0.5944 data_time: 0.0359 memory: 33630 grad_norm: 4.5121 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1400 loss: 1.1400 2022/10/15 05:33:45 - mmengine - INFO - Epoch(train) [66][80/940] lr: 1.0000e-03 eta: 5:22:19 time: 0.5845 data_time: 0.0376 memory: 33630 grad_norm: 4.6100 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0938 loss: 1.0938 2022/10/15 05:33:56 - mmengine - INFO - Epoch(train) [66][100/940] lr: 1.0000e-03 eta: 5:22:07 time: 0.5864 data_time: 0.0379 memory: 33630 grad_norm: 4.5646 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1638 loss: 1.1638 2022/10/15 05:34:08 - mmengine - INFO - Epoch(train) [66][120/940] lr: 1.0000e-03 eta: 5:21:55 time: 0.5990 data_time: 0.0377 memory: 33630 grad_norm: 4.5405 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1804 loss: 1.1804 2022/10/15 05:34:20 - mmengine - INFO - Epoch(train) [66][140/940] lr: 1.0000e-03 eta: 5:21:44 time: 0.5858 data_time: 0.0376 memory: 33630 grad_norm: 4.5604 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2943 loss: 1.2943 2022/10/15 05:34:32 - mmengine - INFO - Epoch(train) [66][160/940] lr: 1.0000e-03 eta: 5:21:32 time: 0.5817 data_time: 0.0369 memory: 33630 grad_norm: 4.5651 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1918 loss: 1.1918 2022/10/15 05:34:43 - mmengine - INFO - Epoch(train) [66][180/940] lr: 1.0000e-03 eta: 5:21:20 time: 0.5834 data_time: 0.0443 memory: 33630 grad_norm: 4.5754 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1640 loss: 1.1640 2022/10/15 05:34:55 - mmengine - INFO - Epoch(train) [66][200/940] lr: 1.0000e-03 eta: 5:21:08 time: 0.5809 data_time: 0.0456 memory: 33630 grad_norm: 4.5094 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2603 loss: 1.2603 2022/10/15 05:35:07 - mmengine - INFO - Epoch(train) [66][220/940] lr: 1.0000e-03 eta: 5:20:56 time: 0.5839 data_time: 0.0322 memory: 33630 grad_norm: 4.6616 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1984 loss: 1.1984 2022/10/15 05:35:18 - mmengine - INFO - Epoch(train) [66][240/940] lr: 1.0000e-03 eta: 5:20:44 time: 0.5933 data_time: 0.0323 memory: 33630 grad_norm: 4.5361 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2659 loss: 1.2659 2022/10/15 05:35:30 - mmengine - INFO - Epoch(train) [66][260/940] lr: 1.0000e-03 eta: 5:20:33 time: 0.5948 data_time: 0.0436 memory: 33630 grad_norm: 4.5624 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.1792 loss: 1.1792 2022/10/15 05:35:42 - mmengine - INFO - Epoch(train) [66][280/940] lr: 1.0000e-03 eta: 5:20:21 time: 0.5874 data_time: 0.0402 memory: 33630 grad_norm: 4.5592 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.1382 loss: 1.1382 2022/10/15 05:35:54 - mmengine - INFO - Epoch(train) [66][300/940] lr: 1.0000e-03 eta: 5:20:09 time: 0.5869 data_time: 0.0369 memory: 33630 grad_norm: 4.6237 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1839 loss: 1.1839 2022/10/15 05:36:05 - mmengine - INFO - Epoch(train) [66][320/940] lr: 1.0000e-03 eta: 5:19:57 time: 0.5813 data_time: 0.0433 memory: 33630 grad_norm: 4.5873 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3140 loss: 1.3140 2022/10/15 05:36:17 - mmengine - INFO - Epoch(train) [66][340/940] lr: 1.0000e-03 eta: 5:19:45 time: 0.5819 data_time: 0.0323 memory: 33630 grad_norm: 4.5444 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2895 loss: 1.2895 2022/10/15 05:36:29 - mmengine - INFO - Epoch(train) [66][360/940] lr: 1.0000e-03 eta: 5:19:34 time: 0.5883 data_time: 0.0398 memory: 33630 grad_norm: 4.5444 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.1472 loss: 1.1472 2022/10/15 05:36:40 - mmengine - INFO - Epoch(train) [66][380/940] lr: 1.0000e-03 eta: 5:19:22 time: 0.5727 data_time: 0.0324 memory: 33630 grad_norm: 4.5746 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2564 loss: 1.2564 2022/10/15 05:36:52 - mmengine - INFO - Epoch(train) [66][400/940] lr: 1.0000e-03 eta: 5:19:10 time: 0.5865 data_time: 0.0336 memory: 33630 grad_norm: 4.5299 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2199 loss: 1.2199 2022/10/15 05:37:04 - mmengine - INFO - Epoch(train) [66][420/940] lr: 1.0000e-03 eta: 5:18:58 time: 0.5835 data_time: 0.0464 memory: 33630 grad_norm: 4.5080 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1008 loss: 1.1008 2022/10/15 05:37:15 - mmengine - INFO - Epoch(train) [66][440/940] lr: 1.0000e-03 eta: 5:18:46 time: 0.5875 data_time: 0.0487 memory: 33630 grad_norm: 4.6744 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2783 loss: 1.2783 2022/10/15 05:37:27 - mmengine - INFO - Epoch(train) [66][460/940] lr: 1.0000e-03 eta: 5:18:34 time: 0.5854 data_time: 0.0306 memory: 33630 grad_norm: 4.5096 top1_acc: 0.6875 top5_acc: 0.7188 loss_cls: 1.2537 loss: 1.2537 2022/10/15 05:37:39 - mmengine - INFO - Epoch(train) [66][480/940] lr: 1.0000e-03 eta: 5:18:22 time: 0.5811 data_time: 0.0425 memory: 33630 grad_norm: 4.4790 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2117 loss: 1.2117 2022/10/15 05:37:51 - mmengine - INFO - Epoch(train) [66][500/940] lr: 1.0000e-03 eta: 5:18:11 time: 0.5861 data_time: 0.0367 memory: 33630 grad_norm: 4.5391 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3088 loss: 1.3088 2022/10/15 05:38:02 - mmengine - INFO - Epoch(train) [66][520/940] lr: 1.0000e-03 eta: 5:17:59 time: 0.5860 data_time: 0.0303 memory: 33630 grad_norm: 4.6435 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1425 loss: 1.1425 2022/10/15 05:38:14 - mmengine - INFO - Epoch(train) [66][540/940] lr: 1.0000e-03 eta: 5:17:47 time: 0.5765 data_time: 0.0399 memory: 33630 grad_norm: 4.5947 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3938 loss: 1.3938 2022/10/15 05:38:25 - mmengine - INFO - Epoch(train) [66][560/940] lr: 1.0000e-03 eta: 5:17:35 time: 0.5731 data_time: 0.0317 memory: 33630 grad_norm: 4.5507 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1792 loss: 1.1792 2022/10/15 05:38:37 - mmengine - INFO - Epoch(train) [66][580/940] lr: 1.0000e-03 eta: 5:17:23 time: 0.5677 data_time: 0.0345 memory: 33630 grad_norm: 4.6684 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.2956 loss: 1.2956 2022/10/15 05:38:48 - mmengine - INFO - Epoch(train) [66][600/940] lr: 1.0000e-03 eta: 5:17:11 time: 0.5836 data_time: 0.0408 memory: 33630 grad_norm: 4.5997 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4019 loss: 1.4019 2022/10/15 05:39:00 - mmengine - INFO - Epoch(train) [66][620/940] lr: 1.0000e-03 eta: 5:16:59 time: 0.5833 data_time: 0.0313 memory: 33630 grad_norm: 4.6149 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2464 loss: 1.2464 2022/10/15 05:39:12 - mmengine - INFO - Epoch(train) [66][640/940] lr: 1.0000e-03 eta: 5:16:47 time: 0.5915 data_time: 0.0363 memory: 33630 grad_norm: 4.5493 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1944 loss: 1.1944 2022/10/15 05:39:23 - mmengine - INFO - Epoch(train) [66][660/940] lr: 1.0000e-03 eta: 5:16:36 time: 0.5853 data_time: 0.0354 memory: 33630 grad_norm: 4.5506 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2648 loss: 1.2648 2022/10/15 05:39:35 - mmengine - INFO - Epoch(train) [66][680/940] lr: 1.0000e-03 eta: 5:16:24 time: 0.5799 data_time: 0.0362 memory: 33630 grad_norm: 4.6190 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2191 loss: 1.2191 2022/10/15 05:39:47 - mmengine - INFO - Epoch(train) [66][700/940] lr: 1.0000e-03 eta: 5:16:12 time: 0.5848 data_time: 0.0423 memory: 33630 grad_norm: 4.5760 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1754 loss: 1.1754 2022/10/15 05:39:58 - mmengine - INFO - Epoch(train) [66][720/940] lr: 1.0000e-03 eta: 5:16:00 time: 0.5781 data_time: 0.0376 memory: 33630 grad_norm: 4.6558 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2715 loss: 1.2715 2022/10/15 05:40:10 - mmengine - INFO - Epoch(train) [66][740/940] lr: 1.0000e-03 eta: 5:15:48 time: 0.5807 data_time: 0.0408 memory: 33630 grad_norm: 4.4800 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1675 loss: 1.1675 2022/10/15 05:40:22 - mmengine - INFO - Epoch(train) [66][760/940] lr: 1.0000e-03 eta: 5:15:36 time: 0.5783 data_time: 0.0337 memory: 33630 grad_norm: 4.5210 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2131 loss: 1.2131 2022/10/15 05:40:33 - mmengine - INFO - Epoch(train) [66][780/940] lr: 1.0000e-03 eta: 5:15:24 time: 0.5867 data_time: 0.0329 memory: 33630 grad_norm: 4.5172 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1557 loss: 1.1557 2022/10/15 05:40:45 - mmengine - INFO - Epoch(train) [66][800/940] lr: 1.0000e-03 eta: 5:15:13 time: 0.5765 data_time: 0.0316 memory: 33630 grad_norm: 4.4627 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2056 loss: 1.2056 2022/10/15 05:40:56 - mmengine - INFO - Epoch(train) [66][820/940] lr: 1.0000e-03 eta: 5:15:01 time: 0.5726 data_time: 0.0324 memory: 33630 grad_norm: 4.4986 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3273 loss: 1.3273 2022/10/15 05:41:08 - mmengine - INFO - Epoch(train) [66][840/940] lr: 1.0000e-03 eta: 5:14:49 time: 0.5874 data_time: 0.0313 memory: 33630 grad_norm: 4.5907 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4007 loss: 1.4007 2022/10/15 05:41:20 - mmengine - INFO - Epoch(train) [66][860/940] lr: 1.0000e-03 eta: 5:14:37 time: 0.5792 data_time: 0.0388 memory: 33630 grad_norm: 4.4357 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.2301 loss: 1.2301 2022/10/15 05:41:31 - mmengine - INFO - Epoch(train) [66][880/940] lr: 1.0000e-03 eta: 5:14:25 time: 0.5909 data_time: 0.0303 memory: 33630 grad_norm: 4.5004 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.2402 loss: 1.2402 2022/10/15 05:41:43 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 05:41:43 - mmengine - INFO - Epoch(train) [66][900/940] lr: 1.0000e-03 eta: 5:14:13 time: 0.5729 data_time: 0.0374 memory: 33630 grad_norm: 4.6534 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2825 loss: 1.2825 2022/10/15 05:41:54 - mmengine - INFO - Epoch(train) [66][920/940] lr: 1.0000e-03 eta: 5:14:01 time: 0.5769 data_time: 0.0403 memory: 33630 grad_norm: 4.6160 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2473 loss: 1.2473 2022/10/15 05:42:05 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 05:42:05 - mmengine - INFO - Epoch(train) [66][940/940] lr: 1.0000e-03 eta: 5:13:49 time: 0.5514 data_time: 0.0308 memory: 33630 grad_norm: 4.8439 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.1725 loss: 1.1725 2022/10/15 05:42:05 - mmengine - INFO - Saving checkpoint at 66 epochs 2022/10/15 05:42:20 - mmengine - INFO - Epoch(val) [66][20/78] eta: 0:00:39 time: 0.6894 data_time: 0.5171 memory: 5967 2022/10/15 05:42:31 - mmengine - INFO - Epoch(val) [66][40/78] eta: 0:00:20 time: 0.5296 data_time: 0.3614 memory: 5967 2022/10/15 05:42:44 - mmengine - INFO - Epoch(val) [66][60/78] eta: 0:00:11 time: 0.6469 data_time: 0.4751 memory: 5967 2022/10/15 05:42:55 - mmengine - INFO - Epoch(val) [66][78/78] acc/top1: 0.6848 acc/top5: 0.8769 acc/mean1: 0.6848 2022/10/15 05:43:11 - mmengine - INFO - Epoch(train) [67][20/940] lr: 1.0000e-03 eta: 5:13:40 time: 0.8323 data_time: 0.2241 memory: 33630 grad_norm: 4.4883 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2362 loss: 1.2362 2022/10/15 05:43:23 - mmengine - INFO - Epoch(train) [67][40/940] lr: 1.0000e-03 eta: 5:13:28 time: 0.5924 data_time: 0.0322 memory: 33630 grad_norm: 4.5469 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1499 loss: 1.1499 2022/10/15 05:43:35 - mmengine - INFO - Epoch(train) [67][60/940] lr: 1.0000e-03 eta: 5:13:17 time: 0.6172 data_time: 0.0375 memory: 33630 grad_norm: 4.6014 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1736 loss: 1.1736 2022/10/15 05:43:47 - mmengine - INFO - Epoch(train) [67][80/940] lr: 1.0000e-03 eta: 5:13:05 time: 0.5748 data_time: 0.0392 memory: 33630 grad_norm: 4.6304 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1171 loss: 1.1171 2022/10/15 05:43:59 - mmengine - INFO - Epoch(train) [67][100/940] lr: 1.0000e-03 eta: 5:12:53 time: 0.5972 data_time: 0.0410 memory: 33630 grad_norm: 4.4983 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2925 loss: 1.2925 2022/10/15 05:44:10 - mmengine - INFO - Epoch(train) [67][120/940] lr: 1.0000e-03 eta: 5:12:41 time: 0.5741 data_time: 0.0349 memory: 33630 grad_norm: 4.5382 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1526 loss: 1.1526 2022/10/15 05:44:22 - mmengine - INFO - Epoch(train) [67][140/940] lr: 1.0000e-03 eta: 5:12:29 time: 0.5821 data_time: 0.0388 memory: 33630 grad_norm: 4.5436 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1481 loss: 1.1481 2022/10/15 05:44:34 - mmengine - INFO - Epoch(train) [67][160/940] lr: 1.0000e-03 eta: 5:12:17 time: 0.5878 data_time: 0.0446 memory: 33630 grad_norm: 4.5981 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2907 loss: 1.2907 2022/10/15 05:44:45 - mmengine - INFO - Epoch(train) [67][180/940] lr: 1.0000e-03 eta: 5:12:05 time: 0.5796 data_time: 0.0341 memory: 33630 grad_norm: 4.5255 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.3164 loss: 1.3164 2022/10/15 05:44:57 - mmengine - INFO - Epoch(train) [67][200/940] lr: 1.0000e-03 eta: 5:11:54 time: 0.5800 data_time: 0.0341 memory: 33630 grad_norm: 4.5620 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1520 loss: 1.1520 2022/10/15 05:45:09 - mmengine - INFO - Epoch(train) [67][220/940] lr: 1.0000e-03 eta: 5:11:42 time: 0.6092 data_time: 0.0594 memory: 33630 grad_norm: 4.5883 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2264 loss: 1.2264 2022/10/15 05:45:21 - mmengine - INFO - Epoch(train) [67][240/940] lr: 1.0000e-03 eta: 5:11:30 time: 0.5985 data_time: 0.0581 memory: 33630 grad_norm: 4.5766 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0758 loss: 1.0758 2022/10/15 05:45:33 - mmengine - INFO - Epoch(train) [67][260/940] lr: 1.0000e-03 eta: 5:11:19 time: 0.5961 data_time: 0.0385 memory: 33630 grad_norm: 4.5564 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2109 loss: 1.2109 2022/10/15 05:45:45 - mmengine - INFO - Epoch(train) [67][280/940] lr: 1.0000e-03 eta: 5:11:07 time: 0.5857 data_time: 0.0304 memory: 33630 grad_norm: 4.6187 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2352 loss: 1.2352 2022/10/15 05:45:57 - mmengine - INFO - Epoch(train) [67][300/940] lr: 1.0000e-03 eta: 5:10:55 time: 0.5852 data_time: 0.0401 memory: 33630 grad_norm: 4.6855 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1018 loss: 1.1018 2022/10/15 05:46:08 - mmengine - INFO - Epoch(train) [67][320/940] lr: 1.0000e-03 eta: 5:10:43 time: 0.5797 data_time: 0.0325 memory: 33630 grad_norm: 4.6289 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2886 loss: 1.2886 2022/10/15 05:46:20 - mmengine - INFO - Epoch(train) [67][340/940] lr: 1.0000e-03 eta: 5:10:31 time: 0.5838 data_time: 0.0399 memory: 33630 grad_norm: 4.6162 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3156 loss: 1.3156 2022/10/15 05:46:31 - mmengine - INFO - Epoch(train) [67][360/940] lr: 1.0000e-03 eta: 5:10:19 time: 0.5815 data_time: 0.0321 memory: 33630 grad_norm: 4.5454 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2543 loss: 1.2543 2022/10/15 05:46:43 - mmengine - INFO - Epoch(train) [67][380/940] lr: 1.0000e-03 eta: 5:10:08 time: 0.5921 data_time: 0.0409 memory: 33630 grad_norm: 4.6546 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.3649 loss: 1.3649 2022/10/15 05:46:55 - mmengine - INFO - Epoch(train) [67][400/940] lr: 1.0000e-03 eta: 5:09:56 time: 0.5835 data_time: 0.0466 memory: 33630 grad_norm: 4.5820 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3276 loss: 1.3276 2022/10/15 05:47:07 - mmengine - INFO - Epoch(train) [67][420/940] lr: 1.0000e-03 eta: 5:09:44 time: 0.5826 data_time: 0.0442 memory: 33630 grad_norm: 4.6972 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2025 loss: 1.2025 2022/10/15 05:47:18 - mmengine - INFO - Epoch(train) [67][440/940] lr: 1.0000e-03 eta: 5:09:32 time: 0.5748 data_time: 0.0465 memory: 33630 grad_norm: 4.4679 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2639 loss: 1.2639 2022/10/15 05:47:30 - mmengine - INFO - Epoch(train) [67][460/940] lr: 1.0000e-03 eta: 5:09:20 time: 0.5840 data_time: 0.0321 memory: 33630 grad_norm: 4.5848 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2102 loss: 1.2102 2022/10/15 05:47:41 - mmengine - INFO - Epoch(train) [67][480/940] lr: 1.0000e-03 eta: 5:09:08 time: 0.5792 data_time: 0.0370 memory: 33630 grad_norm: 4.6618 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2144 loss: 1.2144 2022/10/15 05:47:53 - mmengine - INFO - Epoch(train) [67][500/940] lr: 1.0000e-03 eta: 5:08:56 time: 0.5778 data_time: 0.0316 memory: 33630 grad_norm: 4.5401 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2093 loss: 1.2093 2022/10/15 05:48:06 - mmengine - INFO - Epoch(train) [67][520/940] lr: 1.0000e-03 eta: 5:08:45 time: 0.6602 data_time: 0.0393 memory: 33630 grad_norm: 4.5694 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1578 loss: 1.1578 2022/10/15 05:48:18 - mmengine - INFO - Epoch(train) [67][540/940] lr: 1.0000e-03 eta: 5:08:33 time: 0.5795 data_time: 0.0351 memory: 33630 grad_norm: 4.6561 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3154 loss: 1.3154 2022/10/15 05:48:30 - mmengine - INFO - Epoch(train) [67][560/940] lr: 1.0000e-03 eta: 5:08:22 time: 0.6216 data_time: 0.0320 memory: 33630 grad_norm: 4.5241 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1390 loss: 1.1390 2022/10/15 05:48:42 - mmengine - INFO - Epoch(train) [67][580/940] lr: 1.0000e-03 eta: 5:08:10 time: 0.5868 data_time: 0.0326 memory: 33630 grad_norm: 4.6078 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3244 loss: 1.3244 2022/10/15 05:48:53 - mmengine - INFO - Epoch(train) [67][600/940] lr: 1.0000e-03 eta: 5:07:58 time: 0.5808 data_time: 0.0373 memory: 33630 grad_norm: 4.5299 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1572 loss: 1.1572 2022/10/15 05:49:05 - mmengine - INFO - Epoch(train) [67][620/940] lr: 1.0000e-03 eta: 5:07:46 time: 0.5873 data_time: 0.0444 memory: 33630 grad_norm: 4.6684 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.4144 loss: 1.4144 2022/10/15 05:49:17 - mmengine - INFO - Epoch(train) [67][640/940] lr: 1.0000e-03 eta: 5:07:35 time: 0.5740 data_time: 0.0354 memory: 33630 grad_norm: 4.5687 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2676 loss: 1.2676 2022/10/15 05:49:28 - mmengine - INFO - Epoch(train) [67][660/940] lr: 1.0000e-03 eta: 5:07:23 time: 0.5841 data_time: 0.0444 memory: 33630 grad_norm: 4.6798 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2669 loss: 1.2669 2022/10/15 05:49:40 - mmengine - INFO - Epoch(train) [67][680/940] lr: 1.0000e-03 eta: 5:07:11 time: 0.5983 data_time: 0.0346 memory: 33630 grad_norm: 4.6972 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2275 loss: 1.2275 2022/10/15 05:49:52 - mmengine - INFO - Epoch(train) [67][700/940] lr: 1.0000e-03 eta: 5:06:59 time: 0.5773 data_time: 0.0360 memory: 33630 grad_norm: 4.5829 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2889 loss: 1.2889 2022/10/15 05:50:04 - mmengine - INFO - Epoch(train) [67][720/940] lr: 1.0000e-03 eta: 5:06:47 time: 0.5823 data_time: 0.0376 memory: 33630 grad_norm: 4.5665 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1743 loss: 1.1743 2022/10/15 05:50:15 - mmengine - INFO - Epoch(train) [67][740/940] lr: 1.0000e-03 eta: 5:06:35 time: 0.5877 data_time: 0.0356 memory: 33630 grad_norm: 4.6397 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2137 loss: 1.2137 2022/10/15 05:50:27 - mmengine - INFO - Epoch(train) [67][760/940] lr: 1.0000e-03 eta: 5:06:24 time: 0.5849 data_time: 0.0399 memory: 33630 grad_norm: 4.5064 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1439 loss: 1.1439 2022/10/15 05:50:39 - mmengine - INFO - Epoch(train) [67][780/940] lr: 1.0000e-03 eta: 5:06:12 time: 0.5926 data_time: 0.0397 memory: 33630 grad_norm: 4.5248 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.2377 loss: 1.2377 2022/10/15 05:50:51 - mmengine - INFO - Epoch(train) [67][800/940] lr: 1.0000e-03 eta: 5:06:00 time: 0.5840 data_time: 0.0404 memory: 33630 grad_norm: 4.6713 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1942 loss: 1.1942 2022/10/15 05:51:02 - mmengine - INFO - Epoch(train) [67][820/940] lr: 1.0000e-03 eta: 5:05:48 time: 0.5845 data_time: 0.0442 memory: 33630 grad_norm: 4.5517 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1811 loss: 1.1811 2022/10/15 05:51:14 - mmengine - INFO - Epoch(train) [67][840/940] lr: 1.0000e-03 eta: 5:05:36 time: 0.5871 data_time: 0.0375 memory: 33630 grad_norm: 4.7065 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2771 loss: 1.2771 2022/10/15 05:51:26 - mmengine - INFO - Epoch(train) [67][860/940] lr: 1.0000e-03 eta: 5:05:25 time: 0.5966 data_time: 0.0430 memory: 33630 grad_norm: 4.6611 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2285 loss: 1.2285 2022/10/15 05:51:38 - mmengine - INFO - Epoch(train) [67][880/940] lr: 1.0000e-03 eta: 5:05:13 time: 0.5878 data_time: 0.0360 memory: 33630 grad_norm: 4.6204 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2557 loss: 1.2557 2022/10/15 05:51:49 - mmengine - INFO - Epoch(train) [67][900/940] lr: 1.0000e-03 eta: 5:05:01 time: 0.5743 data_time: 0.0378 memory: 33630 grad_norm: 4.5890 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2373 loss: 1.2373 2022/10/15 05:52:01 - mmengine - INFO - Epoch(train) [67][920/940] lr: 1.0000e-03 eta: 5:04:49 time: 0.5912 data_time: 0.0354 memory: 33630 grad_norm: 4.7546 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3023 loss: 1.3023 2022/10/15 05:52:12 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 05:52:12 - mmengine - INFO - Epoch(train) [67][940/940] lr: 1.0000e-03 eta: 5:04:37 time: 0.5377 data_time: 0.0292 memory: 33630 grad_norm: 4.8596 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.2860 loss: 1.2860 2022/10/15 05:52:26 - mmengine - INFO - Epoch(val) [67][20/78] eta: 0:00:42 time: 0.7266 data_time: 0.5536 memory: 5967 2022/10/15 05:52:37 - mmengine - INFO - Epoch(val) [67][40/78] eta: 0:00:19 time: 0.5163 data_time: 0.3459 memory: 5967 2022/10/15 05:52:50 - mmengine - INFO - Epoch(val) [67][60/78] eta: 0:00:12 time: 0.6741 data_time: 0.5056 memory: 5967 2022/10/15 05:53:01 - mmengine - INFO - Epoch(val) [67][78/78] acc/top1: 0.6858 acc/top5: 0.8789 acc/mean1: 0.6857 2022/10/15 05:53:17 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 05:53:17 - mmengine - INFO - Epoch(train) [68][20/940] lr: 1.0000e-03 eta: 5:04:27 time: 0.7929 data_time: 0.2251 memory: 33630 grad_norm: 4.6342 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.3558 loss: 1.3558 2022/10/15 05:53:29 - mmengine - INFO - Epoch(train) [68][40/940] lr: 1.0000e-03 eta: 5:04:15 time: 0.6041 data_time: 0.0519 memory: 33630 grad_norm: 4.5488 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2069 loss: 1.2069 2022/10/15 05:53:41 - mmengine - INFO - Epoch(train) [68][60/940] lr: 1.0000e-03 eta: 5:04:04 time: 0.6155 data_time: 0.0611 memory: 33630 grad_norm: 4.6235 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2424 loss: 1.2424 2022/10/15 05:53:53 - mmengine - INFO - Epoch(train) [68][80/940] lr: 1.0000e-03 eta: 5:03:52 time: 0.5896 data_time: 0.0379 memory: 33630 grad_norm: 4.6208 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2313 loss: 1.2313 2022/10/15 05:54:05 - mmengine - INFO - Epoch(train) [68][100/940] lr: 1.0000e-03 eta: 5:03:40 time: 0.5989 data_time: 0.0428 memory: 33630 grad_norm: 4.5724 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2648 loss: 1.2648 2022/10/15 05:54:17 - mmengine - INFO - Epoch(train) [68][120/940] lr: 1.0000e-03 eta: 5:03:29 time: 0.5897 data_time: 0.0308 memory: 33630 grad_norm: 4.5954 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2599 loss: 1.2599 2022/10/15 05:54:29 - mmengine - INFO - Epoch(train) [68][140/940] lr: 1.0000e-03 eta: 5:03:17 time: 0.5763 data_time: 0.0405 memory: 33630 grad_norm: 4.6195 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2016 loss: 1.2016 2022/10/15 05:54:40 - mmengine - INFO - Epoch(train) [68][160/940] lr: 1.0000e-03 eta: 5:03:05 time: 0.5837 data_time: 0.0331 memory: 33630 grad_norm: 4.5561 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2476 loss: 1.2476 2022/10/15 05:54:52 - mmengine - INFO - Epoch(train) [68][180/940] lr: 1.0000e-03 eta: 5:02:53 time: 0.5807 data_time: 0.0390 memory: 33630 grad_norm: 4.6257 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3069 loss: 1.3069 2022/10/15 05:55:04 - mmengine - INFO - Epoch(train) [68][200/940] lr: 1.0000e-03 eta: 5:02:41 time: 0.5837 data_time: 0.0380 memory: 33630 grad_norm: 4.6333 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1750 loss: 1.1750 2022/10/15 05:55:15 - mmengine - INFO - Epoch(train) [68][220/940] lr: 1.0000e-03 eta: 5:02:29 time: 0.5731 data_time: 0.0389 memory: 33630 grad_norm: 4.5976 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2765 loss: 1.2765 2022/10/15 05:55:27 - mmengine - INFO - Epoch(train) [68][240/940] lr: 1.0000e-03 eta: 5:02:17 time: 0.5797 data_time: 0.0424 memory: 33630 grad_norm: 4.6836 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2327 loss: 1.2327 2022/10/15 05:55:38 - mmengine - INFO - Epoch(train) [68][260/940] lr: 1.0000e-03 eta: 5:02:06 time: 0.5806 data_time: 0.0323 memory: 33630 grad_norm: 4.6489 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2611 loss: 1.2611 2022/10/15 05:55:50 - mmengine - INFO - Epoch(train) [68][280/940] lr: 1.0000e-03 eta: 5:01:54 time: 0.5779 data_time: 0.0353 memory: 33630 grad_norm: 4.6505 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1918 loss: 1.1918 2022/10/15 05:56:01 - mmengine - INFO - Epoch(train) [68][300/940] lr: 1.0000e-03 eta: 5:01:42 time: 0.5761 data_time: 0.0407 memory: 33630 grad_norm: 4.7201 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3134 loss: 1.3134 2022/10/15 05:56:13 - mmengine - INFO - Epoch(train) [68][320/940] lr: 1.0000e-03 eta: 5:01:30 time: 0.5843 data_time: 0.0464 memory: 33630 grad_norm: 4.6625 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2186 loss: 1.2186 2022/10/15 05:56:25 - mmengine - INFO - Epoch(train) [68][340/940] lr: 1.0000e-03 eta: 5:01:18 time: 0.5836 data_time: 0.0337 memory: 33630 grad_norm: 4.5586 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1386 loss: 1.1386 2022/10/15 05:56:36 - mmengine - INFO - Epoch(train) [68][360/940] lr: 1.0000e-03 eta: 5:01:06 time: 0.5831 data_time: 0.0400 memory: 33630 grad_norm: 4.7181 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3201 loss: 1.3201 2022/10/15 05:56:48 - mmengine - INFO - Epoch(train) [68][380/940] lr: 1.0000e-03 eta: 5:00:54 time: 0.5826 data_time: 0.0349 memory: 33630 grad_norm: 4.5672 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1376 loss: 1.1376 2022/10/15 05:57:00 - mmengine - INFO - Epoch(train) [68][400/940] lr: 1.0000e-03 eta: 5:00:42 time: 0.5784 data_time: 0.0390 memory: 33630 grad_norm: 4.5167 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3281 loss: 1.3281 2022/10/15 05:57:11 - mmengine - INFO - Epoch(train) [68][420/940] lr: 1.0000e-03 eta: 5:00:31 time: 0.5749 data_time: 0.0341 memory: 33630 grad_norm: 4.7224 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.3521 loss: 1.3521 2022/10/15 05:57:23 - mmengine - INFO - Epoch(train) [68][440/940] lr: 1.0000e-03 eta: 5:00:19 time: 0.5860 data_time: 0.0447 memory: 33630 grad_norm: 4.7136 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2256 loss: 1.2256 2022/10/15 05:57:35 - mmengine - INFO - Epoch(train) [68][460/940] lr: 1.0000e-03 eta: 5:00:07 time: 0.5927 data_time: 0.0347 memory: 33630 grad_norm: 4.5174 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1397 loss: 1.1397 2022/10/15 05:57:46 - mmengine - INFO - Epoch(train) [68][480/940] lr: 1.0000e-03 eta: 4:59:55 time: 0.5886 data_time: 0.0402 memory: 33630 grad_norm: 4.5018 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2134 loss: 1.2134 2022/10/15 05:57:58 - mmengine - INFO - Epoch(train) [68][500/940] lr: 1.0000e-03 eta: 4:59:43 time: 0.5788 data_time: 0.0371 memory: 33630 grad_norm: 4.6309 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2179 loss: 1.2179 2022/10/15 05:58:10 - mmengine - INFO - Epoch(train) [68][520/940] lr: 1.0000e-03 eta: 4:59:31 time: 0.5834 data_time: 0.0430 memory: 33630 grad_norm: 4.6757 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2386 loss: 1.2386 2022/10/15 05:58:21 - mmengine - INFO - Epoch(train) [68][540/940] lr: 1.0000e-03 eta: 4:59:20 time: 0.5820 data_time: 0.0378 memory: 33630 grad_norm: 4.5886 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1420 loss: 1.1420 2022/10/15 05:58:33 - mmengine - INFO - Epoch(train) [68][560/940] lr: 1.0000e-03 eta: 4:59:08 time: 0.5807 data_time: 0.0331 memory: 33630 grad_norm: 4.6614 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2413 loss: 1.2413 2022/10/15 05:58:44 - mmengine - INFO - Epoch(train) [68][580/940] lr: 1.0000e-03 eta: 4:58:56 time: 0.5781 data_time: 0.0339 memory: 33630 grad_norm: 4.5753 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2686 loss: 1.2686 2022/10/15 05:58:56 - mmengine - INFO - Epoch(train) [68][600/940] lr: 1.0000e-03 eta: 4:58:44 time: 0.5856 data_time: 0.0350 memory: 33630 grad_norm: 4.6617 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2136 loss: 1.2136 2022/10/15 05:59:08 - mmengine - INFO - Epoch(train) [68][620/940] lr: 1.0000e-03 eta: 4:58:32 time: 0.5871 data_time: 0.0383 memory: 33630 grad_norm: 4.6515 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2129 loss: 1.2129 2022/10/15 05:59:19 - mmengine - INFO - Epoch(train) [68][640/940] lr: 1.0000e-03 eta: 4:58:20 time: 0.5758 data_time: 0.0391 memory: 33630 grad_norm: 4.6766 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1484 loss: 1.1484 2022/10/15 05:59:31 - mmengine - INFO - Epoch(train) [68][660/940] lr: 1.0000e-03 eta: 4:58:08 time: 0.5777 data_time: 0.0350 memory: 33630 grad_norm: 4.5792 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2448 loss: 1.2448 2022/10/15 05:59:42 - mmengine - INFO - Epoch(train) [68][680/940] lr: 1.0000e-03 eta: 4:57:56 time: 0.5675 data_time: 0.0321 memory: 33630 grad_norm: 4.5310 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4072 loss: 1.4072 2022/10/15 05:59:54 - mmengine - INFO - Epoch(train) [68][700/940] lr: 1.0000e-03 eta: 4:57:45 time: 0.5834 data_time: 0.0379 memory: 33630 grad_norm: 4.6489 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.2588 loss: 1.2588 2022/10/15 06:00:05 - mmengine - INFO - Epoch(train) [68][720/940] lr: 1.0000e-03 eta: 4:57:33 time: 0.5733 data_time: 0.0361 memory: 33630 grad_norm: 4.5693 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2366 loss: 1.2366 2022/10/15 06:00:17 - mmengine - INFO - Epoch(train) [68][740/940] lr: 1.0000e-03 eta: 4:57:21 time: 0.5878 data_time: 0.0337 memory: 33630 grad_norm: 4.5759 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2248 loss: 1.2248 2022/10/15 06:00:29 - mmengine - INFO - Epoch(train) [68][760/940] lr: 1.0000e-03 eta: 4:57:09 time: 0.5783 data_time: 0.0356 memory: 33630 grad_norm: 4.5716 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1665 loss: 1.1665 2022/10/15 06:00:40 - mmengine - INFO - Epoch(train) [68][780/940] lr: 1.0000e-03 eta: 4:56:57 time: 0.5811 data_time: 0.0309 memory: 33630 grad_norm: 4.6341 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1233 loss: 1.1233 2022/10/15 06:00:52 - mmengine - INFO - Epoch(train) [68][800/940] lr: 1.0000e-03 eta: 4:56:45 time: 0.5839 data_time: 0.0325 memory: 33630 grad_norm: 4.5757 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2150 loss: 1.2150 2022/10/15 06:01:04 - mmengine - INFO - Epoch(train) [68][820/940] lr: 1.0000e-03 eta: 4:56:34 time: 0.5977 data_time: 0.0347 memory: 33630 grad_norm: 4.5462 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3164 loss: 1.3164 2022/10/15 06:01:15 - mmengine - INFO - Epoch(train) [68][840/940] lr: 1.0000e-03 eta: 4:56:22 time: 0.5728 data_time: 0.0327 memory: 33630 grad_norm: 4.5566 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2404 loss: 1.2404 2022/10/15 06:01:27 - mmengine - INFO - Epoch(train) [68][860/940] lr: 1.0000e-03 eta: 4:56:10 time: 0.5970 data_time: 0.0390 memory: 33630 grad_norm: 4.5681 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.0762 loss: 1.0762 2022/10/15 06:01:39 - mmengine - INFO - Epoch(train) [68][880/940] lr: 1.0000e-03 eta: 4:55:58 time: 0.5845 data_time: 0.0356 memory: 33630 grad_norm: 4.7378 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.3342 loss: 1.3342 2022/10/15 06:01:51 - mmengine - INFO - Epoch(train) [68][900/940] lr: 1.0000e-03 eta: 4:55:46 time: 0.5860 data_time: 0.0459 memory: 33630 grad_norm: 4.6186 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3474 loss: 1.3474 2022/10/15 06:02:03 - mmengine - INFO - Epoch(train) [68][920/940] lr: 1.0000e-03 eta: 4:55:34 time: 0.5831 data_time: 0.0299 memory: 33630 grad_norm: 4.4822 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0803 loss: 1.0803 2022/10/15 06:02:13 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 06:02:13 - mmengine - INFO - Epoch(train) [68][940/940] lr: 1.0000e-03 eta: 4:55:22 time: 0.5414 data_time: 0.0302 memory: 33630 grad_norm: 5.0025 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.3246 loss: 1.3246 2022/10/15 06:02:28 - mmengine - INFO - Epoch(val) [68][20/78] eta: 0:00:42 time: 0.7362 data_time: 0.5664 memory: 5967 2022/10/15 06:02:39 - mmengine - INFO - Epoch(val) [68][40/78] eta: 0:00:20 time: 0.5292 data_time: 0.3597 memory: 5967 2022/10/15 06:02:51 - mmengine - INFO - Epoch(val) [68][60/78] eta: 0:00:11 time: 0.6197 data_time: 0.4488 memory: 5967 2022/10/15 06:03:03 - mmengine - INFO - Epoch(val) [68][78/78] acc/top1: 0.6873 acc/top5: 0.8794 acc/mean1: 0.6871 2022/10/15 06:03:20 - mmengine - INFO - Epoch(train) [69][20/940] lr: 1.0000e-03 eta: 4:55:13 time: 0.8389 data_time: 0.2671 memory: 33630 grad_norm: 4.6136 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2793 loss: 1.2793 2022/10/15 06:03:31 - mmengine - INFO - Epoch(train) [69][40/940] lr: 1.0000e-03 eta: 4:55:01 time: 0.5778 data_time: 0.0327 memory: 33630 grad_norm: 4.5983 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2229 loss: 1.2229 2022/10/15 06:03:43 - mmengine - INFO - Epoch(train) [69][60/940] lr: 1.0000e-03 eta: 4:54:49 time: 0.5874 data_time: 0.0342 memory: 33630 grad_norm: 4.5238 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1766 loss: 1.1766 2022/10/15 06:03:55 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 06:03:55 - mmengine - INFO - Epoch(train) [69][80/940] lr: 1.0000e-03 eta: 4:54:37 time: 0.5971 data_time: 0.0354 memory: 33630 grad_norm: 4.7430 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2948 loss: 1.2948 2022/10/15 06:04:07 - mmengine - INFO - Epoch(train) [69][100/940] lr: 1.0000e-03 eta: 4:54:26 time: 0.5966 data_time: 0.0307 memory: 33630 grad_norm: 4.5576 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1986 loss: 1.1986 2022/10/15 06:04:19 - mmengine - INFO - Epoch(train) [69][120/940] lr: 1.0000e-03 eta: 4:54:14 time: 0.5772 data_time: 0.0392 memory: 33630 grad_norm: 4.4502 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1410 loss: 1.1410 2022/10/15 06:04:30 - mmengine - INFO - Epoch(train) [69][140/940] lr: 1.0000e-03 eta: 4:54:02 time: 0.5757 data_time: 0.0340 memory: 33630 grad_norm: 4.5608 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1414 loss: 1.1414 2022/10/15 06:04:42 - mmengine - INFO - Epoch(train) [69][160/940] lr: 1.0000e-03 eta: 4:53:50 time: 0.5921 data_time: 0.0460 memory: 33630 grad_norm: 4.5462 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1770 loss: 1.1770 2022/10/15 06:04:54 - mmengine - INFO - Epoch(train) [69][180/940] lr: 1.0000e-03 eta: 4:53:38 time: 0.5844 data_time: 0.0369 memory: 33630 grad_norm: 4.5937 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1529 loss: 1.1529 2022/10/15 06:05:05 - mmengine - INFO - Epoch(train) [69][200/940] lr: 1.0000e-03 eta: 4:53:26 time: 0.5782 data_time: 0.0435 memory: 33630 grad_norm: 4.6417 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2285 loss: 1.2285 2022/10/15 06:05:17 - mmengine - INFO - Epoch(train) [69][220/940] lr: 1.0000e-03 eta: 4:53:15 time: 0.5867 data_time: 0.0381 memory: 33630 grad_norm: 4.6729 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1641 loss: 1.1641 2022/10/15 06:05:28 - mmengine - INFO - Epoch(train) [69][240/940] lr: 1.0000e-03 eta: 4:53:03 time: 0.5743 data_time: 0.0363 memory: 33630 grad_norm: 4.5629 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.2739 loss: 1.2739 2022/10/15 06:05:40 - mmengine - INFO - Epoch(train) [69][260/940] lr: 1.0000e-03 eta: 4:52:51 time: 0.5824 data_time: 0.0512 memory: 33630 grad_norm: 4.6090 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2553 loss: 1.2553 2022/10/15 06:05:52 - mmengine - INFO - Epoch(train) [69][280/940] lr: 1.0000e-03 eta: 4:52:39 time: 0.5837 data_time: 0.0327 memory: 33630 grad_norm: 4.5629 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1074 loss: 1.1074 2022/10/15 06:06:04 - mmengine - INFO - Epoch(train) [69][300/940] lr: 1.0000e-03 eta: 4:52:27 time: 0.5902 data_time: 0.0436 memory: 33630 grad_norm: 4.6258 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0815 loss: 1.0815 2022/10/15 06:06:15 - mmengine - INFO - Epoch(train) [69][320/940] lr: 1.0000e-03 eta: 4:52:15 time: 0.5912 data_time: 0.0418 memory: 33630 grad_norm: 4.7032 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3391 loss: 1.3391 2022/10/15 06:06:27 - mmengine - INFO - Epoch(train) [69][340/940] lr: 1.0000e-03 eta: 4:52:04 time: 0.5883 data_time: 0.0404 memory: 33630 grad_norm: 4.6357 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2763 loss: 1.2763 2022/10/15 06:06:39 - mmengine - INFO - Epoch(train) [69][360/940] lr: 1.0000e-03 eta: 4:51:52 time: 0.5811 data_time: 0.0406 memory: 33630 grad_norm: 4.5443 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2594 loss: 1.2594 2022/10/15 06:06:51 - mmengine - INFO - Epoch(train) [69][380/940] lr: 1.0000e-03 eta: 4:51:40 time: 0.5961 data_time: 0.0387 memory: 33630 grad_norm: 4.5813 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1353 loss: 1.1353 2022/10/15 06:07:02 - mmengine - INFO - Epoch(train) [69][400/940] lr: 1.0000e-03 eta: 4:51:28 time: 0.5783 data_time: 0.0390 memory: 33630 grad_norm: 4.6746 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1755 loss: 1.1755 2022/10/15 06:07:14 - mmengine - INFO - Epoch(train) [69][420/940] lr: 1.0000e-03 eta: 4:51:16 time: 0.5800 data_time: 0.0440 memory: 33630 grad_norm: 4.6651 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1706 loss: 1.1706 2022/10/15 06:07:26 - mmengine - INFO - Epoch(train) [69][440/940] lr: 1.0000e-03 eta: 4:51:04 time: 0.5822 data_time: 0.0369 memory: 33630 grad_norm: 4.6191 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1497 loss: 1.1497 2022/10/15 06:07:37 - mmengine - INFO - Epoch(train) [69][460/940] lr: 1.0000e-03 eta: 4:50:53 time: 0.5841 data_time: 0.0329 memory: 33630 grad_norm: 4.6611 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2242 loss: 1.2242 2022/10/15 06:07:49 - mmengine - INFO - Epoch(train) [69][480/940] lr: 1.0000e-03 eta: 4:50:41 time: 0.5790 data_time: 0.0432 memory: 33630 grad_norm: 4.8016 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2021 loss: 1.2021 2022/10/15 06:08:00 - mmengine - INFO - Epoch(train) [69][500/940] lr: 1.0000e-03 eta: 4:50:29 time: 0.5802 data_time: 0.0449 memory: 33630 grad_norm: 4.6190 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3060 loss: 1.3060 2022/10/15 06:08:12 - mmengine - INFO - Epoch(train) [69][520/940] lr: 1.0000e-03 eta: 4:50:17 time: 0.5900 data_time: 0.0375 memory: 33630 grad_norm: 4.5830 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3114 loss: 1.3114 2022/10/15 06:08:24 - mmengine - INFO - Epoch(train) [69][540/940] lr: 1.0000e-03 eta: 4:50:05 time: 0.5739 data_time: 0.0340 memory: 33630 grad_norm: 4.6012 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2670 loss: 1.2670 2022/10/15 06:08:35 - mmengine - INFO - Epoch(train) [69][560/940] lr: 1.0000e-03 eta: 4:49:53 time: 0.5859 data_time: 0.0447 memory: 33630 grad_norm: 4.7186 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1309 loss: 1.1309 2022/10/15 06:08:47 - mmengine - INFO - Epoch(train) [69][580/940] lr: 1.0000e-03 eta: 4:49:41 time: 0.5845 data_time: 0.0412 memory: 33630 grad_norm: 4.5276 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2550 loss: 1.2550 2022/10/15 06:08:59 - mmengine - INFO - Epoch(train) [69][600/940] lr: 1.0000e-03 eta: 4:49:30 time: 0.5810 data_time: 0.0314 memory: 33630 grad_norm: 4.6240 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2983 loss: 1.2983 2022/10/15 06:09:10 - mmengine - INFO - Epoch(train) [69][620/940] lr: 1.0000e-03 eta: 4:49:18 time: 0.5885 data_time: 0.0367 memory: 33630 grad_norm: 4.5801 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1209 loss: 1.1209 2022/10/15 06:09:22 - mmengine - INFO - Epoch(train) [69][640/940] lr: 1.0000e-03 eta: 4:49:06 time: 0.5915 data_time: 0.0319 memory: 33630 grad_norm: 4.6411 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.1644 loss: 1.1644 2022/10/15 06:09:34 - mmengine - INFO - Epoch(train) [69][660/940] lr: 1.0000e-03 eta: 4:48:54 time: 0.5831 data_time: 0.0435 memory: 33630 grad_norm: 4.6372 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2748 loss: 1.2748 2022/10/15 06:09:46 - mmengine - INFO - Epoch(train) [69][680/940] lr: 1.0000e-03 eta: 4:48:42 time: 0.5871 data_time: 0.0344 memory: 33630 grad_norm: 4.5706 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1425 loss: 1.1425 2022/10/15 06:09:57 - mmengine - INFO - Epoch(train) [69][700/940] lr: 1.0000e-03 eta: 4:48:31 time: 0.5846 data_time: 0.0368 memory: 33630 grad_norm: 4.7278 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2241 loss: 1.2241 2022/10/15 06:10:09 - mmengine - INFO - Epoch(train) [69][720/940] lr: 1.0000e-03 eta: 4:48:19 time: 0.5781 data_time: 0.0318 memory: 33630 grad_norm: 4.6449 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2547 loss: 1.2547 2022/10/15 06:10:21 - mmengine - INFO - Epoch(train) [69][740/940] lr: 1.0000e-03 eta: 4:48:07 time: 0.5818 data_time: 0.0403 memory: 33630 grad_norm: 4.7092 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1967 loss: 1.1967 2022/10/15 06:10:32 - mmengine - INFO - Epoch(train) [69][760/940] lr: 1.0000e-03 eta: 4:47:55 time: 0.5893 data_time: 0.0446 memory: 33630 grad_norm: 4.6289 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2643 loss: 1.2643 2022/10/15 06:10:44 - mmengine - INFO - Epoch(train) [69][780/940] lr: 1.0000e-03 eta: 4:47:43 time: 0.5834 data_time: 0.0456 memory: 33630 grad_norm: 4.6650 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2640 loss: 1.2640 2022/10/15 06:10:56 - mmengine - INFO - Epoch(train) [69][800/940] lr: 1.0000e-03 eta: 4:47:31 time: 0.5834 data_time: 0.0331 memory: 33630 grad_norm: 4.6065 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1984 loss: 1.1984 2022/10/15 06:11:08 - mmengine - INFO - Epoch(train) [69][820/940] lr: 1.0000e-03 eta: 4:47:20 time: 0.5901 data_time: 0.0411 memory: 33630 grad_norm: 4.7025 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2246 loss: 1.2246 2022/10/15 06:11:19 - mmengine - INFO - Epoch(train) [69][840/940] lr: 1.0000e-03 eta: 4:47:08 time: 0.5886 data_time: 0.0395 memory: 33630 grad_norm: 4.5730 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.1660 loss: 1.1660 2022/10/15 06:11:31 - mmengine - INFO - Epoch(train) [69][860/940] lr: 1.0000e-03 eta: 4:46:56 time: 0.5771 data_time: 0.0386 memory: 33630 grad_norm: 4.6365 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1553 loss: 1.1553 2022/10/15 06:11:42 - mmengine - INFO - Epoch(train) [69][880/940] lr: 1.0000e-03 eta: 4:46:44 time: 0.5687 data_time: 0.0352 memory: 33630 grad_norm: 4.6781 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2457 loss: 1.2457 2022/10/15 06:11:54 - mmengine - INFO - Epoch(train) [69][900/940] lr: 1.0000e-03 eta: 4:46:32 time: 0.5809 data_time: 0.0431 memory: 33630 grad_norm: 4.5881 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1890 loss: 1.1890 2022/10/15 06:12:05 - mmengine - INFO - Epoch(train) [69][920/940] lr: 1.0000e-03 eta: 4:46:20 time: 0.5704 data_time: 0.0332 memory: 33630 grad_norm: 4.6964 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1661 loss: 1.1661 2022/10/15 06:12:16 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 06:12:16 - mmengine - INFO - Epoch(train) [69][940/940] lr: 1.0000e-03 eta: 4:46:08 time: 0.5387 data_time: 0.0305 memory: 33630 grad_norm: 4.8601 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.3257 loss: 1.3257 2022/10/15 06:12:16 - mmengine - INFO - Saving checkpoint at 69 epochs 2022/10/15 06:12:31 - mmengine - INFO - Epoch(val) [69][20/78] eta: 0:00:41 time: 0.7134 data_time: 0.5440 memory: 5967 2022/10/15 06:12:41 - mmengine - INFO - Epoch(val) [69][40/78] eta: 0:00:18 time: 0.4962 data_time: 0.3281 memory: 5967 2022/10/15 06:12:54 - mmengine - INFO - Epoch(val) [69][60/78] eta: 0:00:11 time: 0.6399 data_time: 0.4691 memory: 5967 2022/10/15 06:13:05 - mmengine - INFO - Epoch(val) [69][78/78] acc/top1: 0.6868 acc/top5: 0.8789 acc/mean1: 0.6866 2022/10/15 06:13:21 - mmengine - INFO - Epoch(train) [70][20/940] lr: 1.0000e-03 eta: 4:45:58 time: 0.8171 data_time: 0.2193 memory: 33630 grad_norm: 4.5350 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1640 loss: 1.1640 2022/10/15 06:13:33 - mmengine - INFO - Epoch(train) [70][40/940] lr: 1.0000e-03 eta: 4:45:46 time: 0.5983 data_time: 0.0330 memory: 33630 grad_norm: 4.5179 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0555 loss: 1.0555 2022/10/15 06:13:45 - mmengine - INFO - Epoch(train) [70][60/940] lr: 1.0000e-03 eta: 4:45:35 time: 0.5922 data_time: 0.0400 memory: 33630 grad_norm: 4.5714 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1131 loss: 1.1131 2022/10/15 06:13:57 - mmengine - INFO - Epoch(train) [70][80/940] lr: 1.0000e-03 eta: 4:45:23 time: 0.5772 data_time: 0.0355 memory: 33630 grad_norm: 4.4937 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2496 loss: 1.2496 2022/10/15 06:14:09 - mmengine - INFO - Epoch(train) [70][100/940] lr: 1.0000e-03 eta: 4:45:11 time: 0.5994 data_time: 0.0358 memory: 33630 grad_norm: 4.6151 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3579 loss: 1.3579 2022/10/15 06:14:21 - mmengine - INFO - Epoch(train) [70][120/940] lr: 1.0000e-03 eta: 4:44:59 time: 0.5971 data_time: 0.0339 memory: 33630 grad_norm: 4.4984 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1605 loss: 1.1605 2022/10/15 06:14:33 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 06:14:33 - mmengine - INFO - Epoch(train) [70][140/940] lr: 1.0000e-03 eta: 4:44:48 time: 0.5959 data_time: 0.0384 memory: 33630 grad_norm: 4.6174 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1644 loss: 1.1644 2022/10/15 06:14:44 - mmengine - INFO - Epoch(train) [70][160/940] lr: 1.0000e-03 eta: 4:44:36 time: 0.5799 data_time: 0.0416 memory: 33630 grad_norm: 4.6976 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.2412 loss: 1.2412 2022/10/15 06:14:56 - mmengine - INFO - Epoch(train) [70][180/940] lr: 1.0000e-03 eta: 4:44:24 time: 0.5834 data_time: 0.0321 memory: 33630 grad_norm: 4.6247 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2677 loss: 1.2677 2022/10/15 06:15:07 - mmengine - INFO - Epoch(train) [70][200/940] lr: 1.0000e-03 eta: 4:44:12 time: 0.5779 data_time: 0.0389 memory: 33630 grad_norm: 4.6470 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2010 loss: 1.2010 2022/10/15 06:15:19 - mmengine - INFO - Epoch(train) [70][220/940] lr: 1.0000e-03 eta: 4:44:00 time: 0.5835 data_time: 0.0453 memory: 33630 grad_norm: 4.5800 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1706 loss: 1.1706 2022/10/15 06:15:31 - mmengine - INFO - Epoch(train) [70][240/940] lr: 1.0000e-03 eta: 4:43:48 time: 0.5784 data_time: 0.0360 memory: 33630 grad_norm: 4.6061 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1723 loss: 1.1723 2022/10/15 06:15:42 - mmengine - INFO - Epoch(train) [70][260/940] lr: 1.0000e-03 eta: 4:43:36 time: 0.5757 data_time: 0.0325 memory: 33630 grad_norm: 4.6215 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2799 loss: 1.2799 2022/10/15 06:15:54 - mmengine - INFO - Epoch(train) [70][280/940] lr: 1.0000e-03 eta: 4:43:25 time: 0.5848 data_time: 0.0453 memory: 33630 grad_norm: 4.5708 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2406 loss: 1.2406 2022/10/15 06:16:06 - mmengine - INFO - Epoch(train) [70][300/940] lr: 1.0000e-03 eta: 4:43:13 time: 0.5923 data_time: 0.0325 memory: 33630 grad_norm: 4.6272 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2110 loss: 1.2110 2022/10/15 06:16:18 - mmengine - INFO - Epoch(train) [70][320/940] lr: 1.0000e-03 eta: 4:43:01 time: 0.5871 data_time: 0.0388 memory: 33630 grad_norm: 4.6313 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2254 loss: 1.2254 2022/10/15 06:16:29 - mmengine - INFO - Epoch(train) [70][340/940] lr: 1.0000e-03 eta: 4:42:49 time: 0.5734 data_time: 0.0402 memory: 33630 grad_norm: 4.5634 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2833 loss: 1.2833 2022/10/15 06:16:41 - mmengine - INFO - Epoch(train) [70][360/940] lr: 1.0000e-03 eta: 4:42:37 time: 0.5908 data_time: 0.0377 memory: 33630 grad_norm: 4.6849 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2280 loss: 1.2280 2022/10/15 06:16:53 - mmengine - INFO - Epoch(train) [70][380/940] lr: 1.0000e-03 eta: 4:42:26 time: 0.5853 data_time: 0.0365 memory: 33630 grad_norm: 4.6390 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.1942 loss: 1.1942 2022/10/15 06:17:04 - mmengine - INFO - Epoch(train) [70][400/940] lr: 1.0000e-03 eta: 4:42:14 time: 0.5862 data_time: 0.0349 memory: 33630 grad_norm: 4.5999 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2381 loss: 1.2381 2022/10/15 06:17:16 - mmengine - INFO - Epoch(train) [70][420/940] lr: 1.0000e-03 eta: 4:42:02 time: 0.5765 data_time: 0.0320 memory: 33630 grad_norm: 4.7173 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1906 loss: 1.1906 2022/10/15 06:17:28 - mmengine - INFO - Epoch(train) [70][440/940] lr: 1.0000e-03 eta: 4:41:50 time: 0.5878 data_time: 0.0318 memory: 33630 grad_norm: 4.7440 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2708 loss: 1.2708 2022/10/15 06:17:39 - mmengine - INFO - Epoch(train) [70][460/940] lr: 1.0000e-03 eta: 4:41:38 time: 0.5811 data_time: 0.0337 memory: 33630 grad_norm: 4.5297 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2394 loss: 1.2394 2022/10/15 06:17:51 - mmengine - INFO - Epoch(train) [70][480/940] lr: 1.0000e-03 eta: 4:41:26 time: 0.5810 data_time: 0.0547 memory: 33630 grad_norm: 4.5944 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1182 loss: 1.1182 2022/10/15 06:18:02 - mmengine - INFO - Epoch(train) [70][500/940] lr: 1.0000e-03 eta: 4:41:14 time: 0.5734 data_time: 0.0350 memory: 33630 grad_norm: 4.6500 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2604 loss: 1.2604 2022/10/15 06:18:14 - mmengine - INFO - Epoch(train) [70][520/940] lr: 1.0000e-03 eta: 4:41:03 time: 0.5911 data_time: 0.0387 memory: 33630 grad_norm: 4.6932 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1361 loss: 1.1361 2022/10/15 06:18:26 - mmengine - INFO - Epoch(train) [70][540/940] lr: 1.0000e-03 eta: 4:40:51 time: 0.5895 data_time: 0.0367 memory: 33630 grad_norm: 4.6716 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2677 loss: 1.2677 2022/10/15 06:18:37 - mmengine - INFO - Epoch(train) [70][560/940] lr: 1.0000e-03 eta: 4:40:39 time: 0.5790 data_time: 0.0337 memory: 33630 grad_norm: 4.6096 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3637 loss: 1.3637 2022/10/15 06:18:49 - mmengine - INFO - Epoch(train) [70][580/940] lr: 1.0000e-03 eta: 4:40:27 time: 0.5879 data_time: 0.0434 memory: 33630 grad_norm: 4.7126 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2036 loss: 1.2036 2022/10/15 06:19:01 - mmengine - INFO - Epoch(train) [70][600/940] lr: 1.0000e-03 eta: 4:40:15 time: 0.5902 data_time: 0.0375 memory: 33630 grad_norm: 4.7210 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2097 loss: 1.2097 2022/10/15 06:19:13 - mmengine - INFO - Epoch(train) [70][620/940] lr: 1.0000e-03 eta: 4:40:04 time: 0.5821 data_time: 0.0445 memory: 33630 grad_norm: 4.7477 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.4633 loss: 1.4633 2022/10/15 06:19:24 - mmengine - INFO - Epoch(train) [70][640/940] lr: 1.0000e-03 eta: 4:39:52 time: 0.5742 data_time: 0.0339 memory: 33630 grad_norm: 4.6029 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1432 loss: 1.1432 2022/10/15 06:19:36 - mmengine - INFO - Epoch(train) [70][660/940] lr: 1.0000e-03 eta: 4:39:40 time: 0.5864 data_time: 0.0361 memory: 33630 grad_norm: 4.7021 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1886 loss: 1.1886 2022/10/15 06:19:48 - mmengine - INFO - Epoch(train) [70][680/940] lr: 1.0000e-03 eta: 4:39:28 time: 0.5889 data_time: 0.0320 memory: 33630 grad_norm: 4.6309 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2701 loss: 1.2701 2022/10/15 06:19:59 - mmengine - INFO - Epoch(train) [70][700/940] lr: 1.0000e-03 eta: 4:39:16 time: 0.5731 data_time: 0.0327 memory: 33630 grad_norm: 4.5727 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2132 loss: 1.2132 2022/10/15 06:20:11 - mmengine - INFO - Epoch(train) [70][720/940] lr: 1.0000e-03 eta: 4:39:04 time: 0.5862 data_time: 0.0372 memory: 33630 grad_norm: 4.6216 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2517 loss: 1.2517 2022/10/15 06:20:23 - mmengine - INFO - Epoch(train) [70][740/940] lr: 1.0000e-03 eta: 4:38:53 time: 0.5825 data_time: 0.0339 memory: 33630 grad_norm: 4.6588 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1393 loss: 1.1393 2022/10/15 06:20:34 - mmengine - INFO - Epoch(train) [70][760/940] lr: 1.0000e-03 eta: 4:38:41 time: 0.5855 data_time: 0.0398 memory: 33630 grad_norm: 4.5807 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1560 loss: 1.1560 2022/10/15 06:20:46 - mmengine - INFO - Epoch(train) [70][780/940] lr: 1.0000e-03 eta: 4:38:29 time: 0.5865 data_time: 0.0333 memory: 33630 grad_norm: 4.7357 top1_acc: 0.5000 top5_acc: 0.9062 loss_cls: 1.3277 loss: 1.3277 2022/10/15 06:20:58 - mmengine - INFO - Epoch(train) [70][800/940] lr: 1.0000e-03 eta: 4:38:17 time: 0.5843 data_time: 0.0310 memory: 33630 grad_norm: 4.6560 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2231 loss: 1.2231 2022/10/15 06:21:09 - mmengine - INFO - Epoch(train) [70][820/940] lr: 1.0000e-03 eta: 4:38:05 time: 0.5779 data_time: 0.0356 memory: 33630 grad_norm: 4.6613 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1650 loss: 1.1650 2022/10/15 06:21:21 - mmengine - INFO - Epoch(train) [70][840/940] lr: 1.0000e-03 eta: 4:37:53 time: 0.5844 data_time: 0.0427 memory: 33630 grad_norm: 4.5432 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1520 loss: 1.1520 2022/10/15 06:21:33 - mmengine - INFO - Epoch(train) [70][860/940] lr: 1.0000e-03 eta: 4:37:42 time: 0.5839 data_time: 0.0405 memory: 33630 grad_norm: 4.6553 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1927 loss: 1.1927 2022/10/15 06:21:44 - mmengine - INFO - Epoch(train) [70][880/940] lr: 1.0000e-03 eta: 4:37:30 time: 0.5893 data_time: 0.0417 memory: 33630 grad_norm: 4.6363 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1487 loss: 1.1487 2022/10/15 06:21:56 - mmengine - INFO - Epoch(train) [70][900/940] lr: 1.0000e-03 eta: 4:37:18 time: 0.5778 data_time: 0.0411 memory: 33630 grad_norm: 4.6212 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.1923 loss: 1.1923 2022/10/15 06:22:08 - mmengine - INFO - Epoch(train) [70][920/940] lr: 1.0000e-03 eta: 4:37:06 time: 0.5866 data_time: 0.0356 memory: 33630 grad_norm: 4.6517 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2920 loss: 1.2920 2022/10/15 06:22:18 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 06:22:18 - mmengine - INFO - Epoch(train) [70][940/940] lr: 1.0000e-03 eta: 4:36:54 time: 0.5425 data_time: 0.0401 memory: 33630 grad_norm: 4.9205 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.2679 loss: 1.2679 2022/10/15 06:22:32 - mmengine - INFO - Epoch(val) [70][20/78] eta: 0:00:40 time: 0.6925 data_time: 0.5219 memory: 5967 2022/10/15 06:22:43 - mmengine - INFO - Epoch(val) [70][40/78] eta: 0:00:20 time: 0.5418 data_time: 0.3723 memory: 5967 2022/10/15 06:22:56 - mmengine - INFO - Epoch(val) [70][60/78] eta: 0:00:11 time: 0.6265 data_time: 0.4576 memory: 5967 2022/10/15 06:23:08 - mmengine - INFO - Epoch(val) [70][78/78] acc/top1: 0.6857 acc/top5: 0.8784 acc/mean1: 0.6856 2022/10/15 06:23:25 - mmengine - INFO - Epoch(train) [71][20/940] lr: 1.0000e-03 eta: 4:36:44 time: 0.8106 data_time: 0.2346 memory: 33630 grad_norm: 4.7211 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2270 loss: 1.2270 2022/10/15 06:23:36 - mmengine - INFO - Epoch(train) [71][40/940] lr: 1.0000e-03 eta: 4:36:32 time: 0.5792 data_time: 0.0320 memory: 33630 grad_norm: 4.6455 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0870 loss: 1.0870 2022/10/15 06:23:48 - mmengine - INFO - Epoch(train) [71][60/940] lr: 1.0000e-03 eta: 4:36:20 time: 0.6039 data_time: 0.0545 memory: 33630 grad_norm: 4.5749 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2003 loss: 1.2003 2022/10/15 06:24:00 - mmengine - INFO - Epoch(train) [71][80/940] lr: 1.0000e-03 eta: 4:36:09 time: 0.5867 data_time: 0.0336 memory: 33630 grad_norm: 4.6663 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2852 loss: 1.2852 2022/10/15 06:24:12 - mmengine - INFO - Epoch(train) [71][100/940] lr: 1.0000e-03 eta: 4:35:57 time: 0.5975 data_time: 0.0416 memory: 33630 grad_norm: 4.6238 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2028 loss: 1.2028 2022/10/15 06:24:24 - mmengine - INFO - Epoch(train) [71][120/940] lr: 1.0000e-03 eta: 4:35:45 time: 0.5806 data_time: 0.0313 memory: 33630 grad_norm: 4.6136 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1838 loss: 1.1838 2022/10/15 06:24:35 - mmengine - INFO - Epoch(train) [71][140/940] lr: 1.0000e-03 eta: 4:35:33 time: 0.5786 data_time: 0.0333 memory: 33630 grad_norm: 4.7724 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1929 loss: 1.1929 2022/10/15 06:24:47 - mmengine - INFO - Epoch(train) [71][160/940] lr: 1.0000e-03 eta: 4:35:21 time: 0.5857 data_time: 0.0341 memory: 33630 grad_norm: 4.6829 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1596 loss: 1.1596 2022/10/15 06:24:59 - mmengine - INFO - Epoch(train) [71][180/940] lr: 1.0000e-03 eta: 4:35:10 time: 0.5811 data_time: 0.0410 memory: 33630 grad_norm: 4.5808 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1578 loss: 1.1578 2022/10/15 06:25:10 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 06:25:10 - mmengine - INFO - Epoch(train) [71][200/940] lr: 1.0000e-03 eta: 4:34:58 time: 0.5781 data_time: 0.0335 memory: 33630 grad_norm: 4.7308 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1769 loss: 1.1769 2022/10/15 06:25:22 - mmengine - INFO - Epoch(train) [71][220/940] lr: 1.0000e-03 eta: 4:34:46 time: 0.5844 data_time: 0.0301 memory: 33630 grad_norm: 4.6417 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3323 loss: 1.3323 2022/10/15 06:25:34 - mmengine - INFO - Epoch(train) [71][240/940] lr: 1.0000e-03 eta: 4:34:34 time: 0.5867 data_time: 0.0373 memory: 33630 grad_norm: 4.6341 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2535 loss: 1.2535 2022/10/15 06:25:45 - mmengine - INFO - Epoch(train) [71][260/940] lr: 1.0000e-03 eta: 4:34:22 time: 0.5784 data_time: 0.0325 memory: 33630 grad_norm: 4.6410 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2375 loss: 1.2375 2022/10/15 06:25:57 - mmengine - INFO - Epoch(train) [71][280/940] lr: 1.0000e-03 eta: 4:34:10 time: 0.5838 data_time: 0.0407 memory: 33630 grad_norm: 4.7292 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1569 loss: 1.1569 2022/10/15 06:26:08 - mmengine - INFO - Epoch(train) [71][300/940] lr: 1.0000e-03 eta: 4:33:58 time: 0.5784 data_time: 0.0358 memory: 33630 grad_norm: 4.8019 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1702 loss: 1.1702 2022/10/15 06:26:20 - mmengine - INFO - Epoch(train) [71][320/940] lr: 1.0000e-03 eta: 4:33:47 time: 0.5725 data_time: 0.0467 memory: 33630 grad_norm: 4.7999 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1969 loss: 1.1969 2022/10/15 06:26:32 - mmengine - INFO - Epoch(train) [71][340/940] lr: 1.0000e-03 eta: 4:33:35 time: 0.5887 data_time: 0.0374 memory: 33630 grad_norm: 4.6968 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1369 loss: 1.1369 2022/10/15 06:26:43 - mmengine - INFO - Epoch(train) [71][360/940] lr: 1.0000e-03 eta: 4:33:23 time: 0.5751 data_time: 0.0421 memory: 33630 grad_norm: 4.5220 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.0689 loss: 1.0689 2022/10/15 06:26:55 - mmengine - INFO - Epoch(train) [71][380/940] lr: 1.0000e-03 eta: 4:33:11 time: 0.5738 data_time: 0.0316 memory: 33630 grad_norm: 4.7376 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.1439 loss: 1.1439 2022/10/15 06:27:06 - mmengine - INFO - Epoch(train) [71][400/940] lr: 1.0000e-03 eta: 4:32:59 time: 0.5783 data_time: 0.0349 memory: 33630 grad_norm: 4.6470 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1660 loss: 1.1660 2022/10/15 06:27:18 - mmengine - INFO - Epoch(train) [71][420/940] lr: 1.0000e-03 eta: 4:32:47 time: 0.5801 data_time: 0.0389 memory: 33630 grad_norm: 4.6610 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1287 loss: 1.1287 2022/10/15 06:27:29 - mmengine - INFO - Epoch(train) [71][440/940] lr: 1.0000e-03 eta: 4:32:35 time: 0.5813 data_time: 0.0388 memory: 33630 grad_norm: 4.7072 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2766 loss: 1.2766 2022/10/15 06:27:41 - mmengine - INFO - Epoch(train) [71][460/940] lr: 1.0000e-03 eta: 4:32:23 time: 0.5824 data_time: 0.0334 memory: 33630 grad_norm: 4.6966 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.1674 loss: 1.1674 2022/10/15 06:27:53 - mmengine - INFO - Epoch(train) [71][480/940] lr: 1.0000e-03 eta: 4:32:12 time: 0.5918 data_time: 0.0419 memory: 33630 grad_norm: 4.5629 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0841 loss: 1.0841 2022/10/15 06:28:04 - mmengine - INFO - Epoch(train) [71][500/940] lr: 1.0000e-03 eta: 4:32:00 time: 0.5763 data_time: 0.0354 memory: 33630 grad_norm: 4.6229 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1830 loss: 1.1830 2022/10/15 06:28:16 - mmengine - INFO - Epoch(train) [71][520/940] lr: 1.0000e-03 eta: 4:31:48 time: 0.5838 data_time: 0.0347 memory: 33630 grad_norm: 4.6716 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1562 loss: 1.1562 2022/10/15 06:28:28 - mmengine - INFO - Epoch(train) [71][540/940] lr: 1.0000e-03 eta: 4:31:36 time: 0.5773 data_time: 0.0329 memory: 33630 grad_norm: 4.8113 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2285 loss: 1.2285 2022/10/15 06:28:39 - mmengine - INFO - Epoch(train) [71][560/940] lr: 1.0000e-03 eta: 4:31:24 time: 0.5762 data_time: 0.0348 memory: 33630 grad_norm: 4.6777 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2567 loss: 1.2567 2022/10/15 06:28:51 - mmengine - INFO - Epoch(train) [71][580/940] lr: 1.0000e-03 eta: 4:31:12 time: 0.5821 data_time: 0.0349 memory: 33630 grad_norm: 4.7419 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2808 loss: 1.2808 2022/10/15 06:29:03 - mmengine - INFO - Epoch(train) [71][600/940] lr: 1.0000e-03 eta: 4:31:01 time: 0.5910 data_time: 0.0378 memory: 33630 grad_norm: 4.6387 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2699 loss: 1.2699 2022/10/15 06:29:15 - mmengine - INFO - Epoch(train) [71][620/940] lr: 1.0000e-03 eta: 4:30:49 time: 0.5935 data_time: 0.0359 memory: 33630 grad_norm: 4.7996 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1969 loss: 1.1969 2022/10/15 06:29:26 - mmengine - INFO - Epoch(train) [71][640/940] lr: 1.0000e-03 eta: 4:30:37 time: 0.5874 data_time: 0.0328 memory: 33630 grad_norm: 4.6625 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1642 loss: 1.1642 2022/10/15 06:29:38 - mmengine - INFO - Epoch(train) [71][660/940] lr: 1.0000e-03 eta: 4:30:25 time: 0.5761 data_time: 0.0544 memory: 33630 grad_norm: 4.6492 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2340 loss: 1.2340 2022/10/15 06:29:49 - mmengine - INFO - Epoch(train) [71][680/940] lr: 1.0000e-03 eta: 4:30:13 time: 0.5805 data_time: 0.0387 memory: 33630 grad_norm: 4.6241 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2115 loss: 1.2115 2022/10/15 06:30:01 - mmengine - INFO - Epoch(train) [71][700/940] lr: 1.0000e-03 eta: 4:30:01 time: 0.5831 data_time: 0.0388 memory: 33630 grad_norm: 4.7519 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1698 loss: 1.1698 2022/10/15 06:30:13 - mmengine - INFO - Epoch(train) [71][720/940] lr: 1.0000e-03 eta: 4:29:50 time: 0.5846 data_time: 0.0334 memory: 33630 grad_norm: 4.6496 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1232 loss: 1.1232 2022/10/15 06:30:25 - mmengine - INFO - Epoch(train) [71][740/940] lr: 1.0000e-03 eta: 4:29:38 time: 0.5884 data_time: 0.0374 memory: 33630 grad_norm: 4.7038 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3407 loss: 1.3407 2022/10/15 06:30:36 - mmengine - INFO - Epoch(train) [71][760/940] lr: 1.0000e-03 eta: 4:29:26 time: 0.5782 data_time: 0.0323 memory: 33630 grad_norm: 4.4824 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.1357 loss: 1.1357 2022/10/15 06:30:48 - mmengine - INFO - Epoch(train) [71][780/940] lr: 1.0000e-03 eta: 4:29:14 time: 0.5859 data_time: 0.0333 memory: 33630 grad_norm: 4.6487 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2784 loss: 1.2784 2022/10/15 06:30:59 - mmengine - INFO - Epoch(train) [71][800/940] lr: 1.0000e-03 eta: 4:29:02 time: 0.5821 data_time: 0.0423 memory: 33630 grad_norm: 4.7114 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2943 loss: 1.2943 2022/10/15 06:31:11 - mmengine - INFO - Epoch(train) [71][820/940] lr: 1.0000e-03 eta: 4:28:50 time: 0.5793 data_time: 0.0321 memory: 33630 grad_norm: 4.7551 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1942 loss: 1.1942 2022/10/15 06:31:23 - mmengine - INFO - Epoch(train) [71][840/940] lr: 1.0000e-03 eta: 4:28:39 time: 0.5810 data_time: 0.0354 memory: 33630 grad_norm: 4.6702 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2950 loss: 1.2950 2022/10/15 06:31:34 - mmengine - INFO - Epoch(train) [71][860/940] lr: 1.0000e-03 eta: 4:28:27 time: 0.5844 data_time: 0.0336 memory: 33630 grad_norm: 4.7052 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2485 loss: 1.2485 2022/10/15 06:31:46 - mmengine - INFO - Epoch(train) [71][880/940] lr: 1.0000e-03 eta: 4:28:15 time: 0.5844 data_time: 0.0398 memory: 33630 grad_norm: 4.6818 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1445 loss: 1.1445 2022/10/15 06:31:58 - mmengine - INFO - Epoch(train) [71][900/940] lr: 1.0000e-03 eta: 4:28:03 time: 0.5782 data_time: 0.0323 memory: 33630 grad_norm: 4.6723 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3022 loss: 1.3022 2022/10/15 06:32:09 - mmengine - INFO - Epoch(train) [71][920/940] lr: 1.0000e-03 eta: 4:27:51 time: 0.5804 data_time: 0.0330 memory: 33630 grad_norm: 4.6312 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2230 loss: 1.2230 2022/10/15 06:32:20 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 06:32:20 - mmengine - INFO - Epoch(train) [71][940/940] lr: 1.0000e-03 eta: 4:27:39 time: 0.5402 data_time: 0.0317 memory: 33630 grad_norm: 4.8124 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2130 loss: 1.2130 2022/10/15 06:32:35 - mmengine - INFO - Epoch(val) [71][20/78] eta: 0:00:42 time: 0.7273 data_time: 0.5560 memory: 5967 2022/10/15 06:32:45 - mmengine - INFO - Epoch(val) [71][40/78] eta: 0:00:19 time: 0.5024 data_time: 0.3342 memory: 5967 2022/10/15 06:32:58 - mmengine - INFO - Epoch(val) [71][60/78] eta: 0:00:12 time: 0.6776 data_time: 0.5077 memory: 5967 2022/10/15 06:33:09 - mmengine - INFO - Epoch(val) [71][78/78] acc/top1: 0.6864 acc/top5: 0.8784 acc/mean1: 0.6863 2022/10/15 06:33:26 - mmengine - INFO - Epoch(train) [72][20/940] lr: 1.0000e-03 eta: 4:27:29 time: 0.8247 data_time: 0.2624 memory: 33630 grad_norm: 4.6153 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1290 loss: 1.1290 2022/10/15 06:33:37 - mmengine - INFO - Epoch(train) [72][40/940] lr: 1.0000e-03 eta: 4:27:17 time: 0.5835 data_time: 0.0335 memory: 33630 grad_norm: 4.6758 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1619 loss: 1.1619 2022/10/15 06:33:49 - mmengine - INFO - Epoch(train) [72][60/940] lr: 1.0000e-03 eta: 4:27:06 time: 0.5809 data_time: 0.0415 memory: 33630 grad_norm: 4.6534 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1446 loss: 1.1446 2022/10/15 06:34:01 - mmengine - INFO - Epoch(train) [72][80/940] lr: 1.0000e-03 eta: 4:26:54 time: 0.5918 data_time: 0.0326 memory: 33630 grad_norm: 4.6272 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2024 loss: 1.2024 2022/10/15 06:34:13 - mmengine - INFO - Epoch(train) [72][100/940] lr: 1.0000e-03 eta: 4:26:42 time: 0.6159 data_time: 0.0364 memory: 33630 grad_norm: 4.6256 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2113 loss: 1.2113 2022/10/15 06:34:25 - mmengine - INFO - Epoch(train) [72][120/940] lr: 1.0000e-03 eta: 4:26:30 time: 0.5818 data_time: 0.0328 memory: 33630 grad_norm: 4.5821 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2533 loss: 1.2533 2022/10/15 06:34:37 - mmengine - INFO - Epoch(train) [72][140/940] lr: 1.0000e-03 eta: 4:26:19 time: 0.5915 data_time: 0.0515 memory: 33630 grad_norm: 4.7021 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.2113 loss: 1.2113 2022/10/15 06:34:49 - mmengine - INFO - Epoch(train) [72][160/940] lr: 1.0000e-03 eta: 4:26:07 time: 0.5941 data_time: 0.0358 memory: 33630 grad_norm: 4.6383 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3189 loss: 1.3189 2022/10/15 06:35:00 - mmengine - INFO - Epoch(train) [72][180/940] lr: 1.0000e-03 eta: 4:25:55 time: 0.5732 data_time: 0.0355 memory: 33630 grad_norm: 4.7572 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2425 loss: 1.2425 2022/10/15 06:35:12 - mmengine - INFO - Epoch(train) [72][200/940] lr: 1.0000e-03 eta: 4:25:43 time: 0.5772 data_time: 0.0372 memory: 33630 grad_norm: 4.7309 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2898 loss: 1.2898 2022/10/15 06:35:23 - mmengine - INFO - Epoch(train) [72][220/940] lr: 1.0000e-03 eta: 4:25:31 time: 0.5837 data_time: 0.0424 memory: 33630 grad_norm: 4.6151 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2544 loss: 1.2544 2022/10/15 06:35:35 - mmengine - INFO - Epoch(train) [72][240/940] lr: 1.0000e-03 eta: 4:25:19 time: 0.5887 data_time: 0.0484 memory: 33630 grad_norm: 4.6409 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1844 loss: 1.1844 2022/10/15 06:35:47 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 06:35:47 - mmengine - INFO - Epoch(train) [72][260/940] lr: 1.0000e-03 eta: 4:25:08 time: 0.5802 data_time: 0.0365 memory: 33630 grad_norm: 4.7411 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1312 loss: 1.1312 2022/10/15 06:35:58 - mmengine - INFO - Epoch(train) [72][280/940] lr: 1.0000e-03 eta: 4:24:56 time: 0.5794 data_time: 0.0473 memory: 33630 grad_norm: 4.7273 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1688 loss: 1.1688 2022/10/15 06:36:10 - mmengine - INFO - Epoch(train) [72][300/940] lr: 1.0000e-03 eta: 4:24:44 time: 0.5762 data_time: 0.0419 memory: 33630 grad_norm: 4.6918 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2001 loss: 1.2001 2022/10/15 06:36:22 - mmengine - INFO - Epoch(train) [72][320/940] lr: 1.0000e-03 eta: 4:24:32 time: 0.5872 data_time: 0.0356 memory: 33630 grad_norm: 4.6300 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1082 loss: 1.1082 2022/10/15 06:36:33 - mmengine - INFO - Epoch(train) [72][340/940] lr: 1.0000e-03 eta: 4:24:20 time: 0.5743 data_time: 0.0375 memory: 33630 grad_norm: 4.6600 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1948 loss: 1.1948 2022/10/15 06:36:45 - mmengine - INFO - Epoch(train) [72][360/940] lr: 1.0000e-03 eta: 4:24:08 time: 0.5897 data_time: 0.0301 memory: 33630 grad_norm: 4.7570 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2120 loss: 1.2120 2022/10/15 06:36:56 - mmengine - INFO - Epoch(train) [72][380/940] lr: 1.0000e-03 eta: 4:23:57 time: 0.5831 data_time: 0.0463 memory: 33630 grad_norm: 4.7099 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2598 loss: 1.2598 2022/10/15 06:37:08 - mmengine - INFO - Epoch(train) [72][400/940] lr: 1.0000e-03 eta: 4:23:45 time: 0.5800 data_time: 0.0343 memory: 33630 grad_norm: 4.6246 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1998 loss: 1.1998 2022/10/15 06:37:20 - mmengine - INFO - Epoch(train) [72][420/940] lr: 1.0000e-03 eta: 4:23:33 time: 0.5816 data_time: 0.0317 memory: 33630 grad_norm: 4.6871 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1349 loss: 1.1349 2022/10/15 06:37:31 - mmengine - INFO - Epoch(train) [72][440/940] lr: 1.0000e-03 eta: 4:23:21 time: 0.5751 data_time: 0.0378 memory: 33630 grad_norm: 4.7135 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2558 loss: 1.2558 2022/10/15 06:37:43 - mmengine - INFO - Epoch(train) [72][460/940] lr: 1.0000e-03 eta: 4:23:09 time: 0.5832 data_time: 0.0400 memory: 33630 grad_norm: 4.7512 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1927 loss: 1.1927 2022/10/15 06:37:55 - mmengine - INFO - Epoch(train) [72][480/940] lr: 1.0000e-03 eta: 4:22:57 time: 0.5840 data_time: 0.0310 memory: 33630 grad_norm: 4.6744 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.2483 loss: 1.2483 2022/10/15 06:38:06 - mmengine - INFO - Epoch(train) [72][500/940] lr: 1.0000e-03 eta: 4:22:46 time: 0.5919 data_time: 0.0317 memory: 33630 grad_norm: 4.6449 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3886 loss: 1.3886 2022/10/15 06:38:18 - mmengine - INFO - Epoch(train) [72][520/940] lr: 1.0000e-03 eta: 4:22:34 time: 0.5837 data_time: 0.0380 memory: 33630 grad_norm: 4.7461 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1161 loss: 1.1161 2022/10/15 06:38:30 - mmengine - INFO - Epoch(train) [72][540/940] lr: 1.0000e-03 eta: 4:22:22 time: 0.5772 data_time: 0.0373 memory: 33630 grad_norm: 4.6001 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1313 loss: 1.1313 2022/10/15 06:38:41 - mmengine - INFO - Epoch(train) [72][560/940] lr: 1.0000e-03 eta: 4:22:10 time: 0.5875 data_time: 0.0446 memory: 33630 grad_norm: 4.7305 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2116 loss: 1.2116 2022/10/15 06:38:53 - mmengine - INFO - Epoch(train) [72][580/940] lr: 1.0000e-03 eta: 4:21:58 time: 0.5834 data_time: 0.0391 memory: 33630 grad_norm: 4.7248 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0977 loss: 1.0977 2022/10/15 06:39:05 - mmengine - INFO - Epoch(train) [72][600/940] lr: 1.0000e-03 eta: 4:21:46 time: 0.5782 data_time: 0.0368 memory: 33630 grad_norm: 4.7317 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2154 loss: 1.2154 2022/10/15 06:39:16 - mmengine - INFO - Epoch(train) [72][620/940] lr: 1.0000e-03 eta: 4:21:34 time: 0.5772 data_time: 0.0400 memory: 33630 grad_norm: 4.6815 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3326 loss: 1.3326 2022/10/15 06:39:28 - mmengine - INFO - Epoch(train) [72][640/940] lr: 1.0000e-03 eta: 4:21:23 time: 0.5705 data_time: 0.0358 memory: 33630 grad_norm: 4.7266 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2620 loss: 1.2620 2022/10/15 06:39:39 - mmengine - INFO - Epoch(train) [72][660/940] lr: 1.0000e-03 eta: 4:21:11 time: 0.5857 data_time: 0.0309 memory: 33630 grad_norm: 4.6318 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1870 loss: 1.1870 2022/10/15 06:39:51 - mmengine - INFO - Epoch(train) [72][680/940] lr: 1.0000e-03 eta: 4:20:59 time: 0.5781 data_time: 0.0433 memory: 33630 grad_norm: 4.7628 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.2452 loss: 1.2452 2022/10/15 06:40:03 - mmengine - INFO - Epoch(train) [72][700/940] lr: 1.0000e-03 eta: 4:20:47 time: 0.5915 data_time: 0.0477 memory: 33630 grad_norm: 4.5832 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0542 loss: 1.0542 2022/10/15 06:40:14 - mmengine - INFO - Epoch(train) [72][720/940] lr: 1.0000e-03 eta: 4:20:35 time: 0.5679 data_time: 0.0333 memory: 33630 grad_norm: 4.6698 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2644 loss: 1.2644 2022/10/15 06:40:26 - mmengine - INFO - Epoch(train) [72][740/940] lr: 1.0000e-03 eta: 4:20:23 time: 0.5906 data_time: 0.0358 memory: 33630 grad_norm: 4.5529 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2129 loss: 1.2129 2022/10/15 06:40:37 - mmengine - INFO - Epoch(train) [72][760/940] lr: 1.0000e-03 eta: 4:20:11 time: 0.5752 data_time: 0.0320 memory: 33630 grad_norm: 4.7129 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1850 loss: 1.1850 2022/10/15 06:40:49 - mmengine - INFO - Epoch(train) [72][780/940] lr: 1.0000e-03 eta: 4:20:00 time: 0.5759 data_time: 0.0380 memory: 33630 grad_norm: 4.6764 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1974 loss: 1.1974 2022/10/15 06:41:00 - mmengine - INFO - Epoch(train) [72][800/940] lr: 1.0000e-03 eta: 4:19:48 time: 0.5787 data_time: 0.0334 memory: 33630 grad_norm: 4.7159 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2959 loss: 1.2959 2022/10/15 06:41:12 - mmengine - INFO - Epoch(train) [72][820/940] lr: 1.0000e-03 eta: 4:19:36 time: 0.5808 data_time: 0.0348 memory: 33630 grad_norm: 4.7037 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1226 loss: 1.1226 2022/10/15 06:41:24 - mmengine - INFO - Epoch(train) [72][840/940] lr: 1.0000e-03 eta: 4:19:24 time: 0.5789 data_time: 0.0337 memory: 33630 grad_norm: 4.6162 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0825 loss: 1.0825 2022/10/15 06:41:35 - mmengine - INFO - Epoch(train) [72][860/940] lr: 1.0000e-03 eta: 4:19:12 time: 0.5885 data_time: 0.0347 memory: 33630 grad_norm: 4.6782 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3648 loss: 1.3648 2022/10/15 06:41:47 - mmengine - INFO - Epoch(train) [72][880/940] lr: 1.0000e-03 eta: 4:19:00 time: 0.5947 data_time: 0.0325 memory: 33630 grad_norm: 4.7434 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2458 loss: 1.2458 2022/10/15 06:41:59 - mmengine - INFO - Epoch(train) [72][900/940] lr: 1.0000e-03 eta: 4:18:49 time: 0.5779 data_time: 0.0383 memory: 33630 grad_norm: 4.6065 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1632 loss: 1.1632 2022/10/15 06:42:11 - mmengine - INFO - Epoch(train) [72][920/940] lr: 1.0000e-03 eta: 4:18:37 time: 0.5920 data_time: 0.0370 memory: 33630 grad_norm: 4.7528 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2378 loss: 1.2378 2022/10/15 06:42:22 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 06:42:22 - mmengine - INFO - Epoch(train) [72][940/940] lr: 1.0000e-03 eta: 4:18:25 time: 0.5390 data_time: 0.0294 memory: 33630 grad_norm: 4.8292 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.1969 loss: 1.1969 2022/10/15 06:42:22 - mmengine - INFO - Saving checkpoint at 72 epochs 2022/10/15 06:42:37 - mmengine - INFO - Epoch(val) [72][20/78] eta: 0:00:42 time: 0.7293 data_time: 0.5591 memory: 5967 2022/10/15 06:42:47 - mmengine - INFO - Epoch(val) [72][40/78] eta: 0:00:18 time: 0.4928 data_time: 0.3250 memory: 5967 2022/10/15 06:42:59 - mmengine - INFO - Epoch(val) [72][60/78] eta: 0:00:11 time: 0.6335 data_time: 0.4648 memory: 5967 2022/10/15 06:43:10 - mmengine - INFO - Epoch(val) [72][78/78] acc/top1: 0.6849 acc/top5: 0.8801 acc/mean1: 0.6848 2022/10/15 06:43:26 - mmengine - INFO - Epoch(train) [73][20/940] lr: 1.0000e-03 eta: 4:18:15 time: 0.8108 data_time: 0.2476 memory: 33630 grad_norm: 4.7834 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.2184 loss: 1.2184 2022/10/15 06:43:38 - mmengine - INFO - Epoch(train) [73][40/940] lr: 1.0000e-03 eta: 4:18:03 time: 0.5787 data_time: 0.0365 memory: 33630 grad_norm: 4.6125 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1998 loss: 1.1998 2022/10/15 06:43:50 - mmengine - INFO - Epoch(train) [73][60/940] lr: 1.0000e-03 eta: 4:17:51 time: 0.5928 data_time: 0.0366 memory: 33630 grad_norm: 4.6808 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1842 loss: 1.1842 2022/10/15 06:44:02 - mmengine - INFO - Epoch(train) [73][80/940] lr: 1.0000e-03 eta: 4:17:39 time: 0.5842 data_time: 0.0355 memory: 33630 grad_norm: 4.9077 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1949 loss: 1.1949 2022/10/15 06:44:13 - mmengine - INFO - Epoch(train) [73][100/940] lr: 1.0000e-03 eta: 4:17:27 time: 0.5915 data_time: 0.0359 memory: 33630 grad_norm: 4.5791 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0893 loss: 1.0893 2022/10/15 06:44:25 - mmengine - INFO - Epoch(train) [73][120/940] lr: 1.0000e-03 eta: 4:17:16 time: 0.5935 data_time: 0.0371 memory: 33630 grad_norm: 4.7401 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2918 loss: 1.2918 2022/10/15 06:44:37 - mmengine - INFO - Epoch(train) [73][140/940] lr: 1.0000e-03 eta: 4:17:04 time: 0.5799 data_time: 0.0349 memory: 33630 grad_norm: 4.7531 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.1837 loss: 1.1837 2022/10/15 06:44:49 - mmengine - INFO - Epoch(train) [73][160/940] lr: 1.0000e-03 eta: 4:16:52 time: 0.5871 data_time: 0.0363 memory: 33630 grad_norm: 4.7438 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1616 loss: 1.1616 2022/10/15 06:45:00 - mmengine - INFO - Epoch(train) [73][180/940] lr: 1.0000e-03 eta: 4:16:40 time: 0.5913 data_time: 0.0366 memory: 33630 grad_norm: 4.7601 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2366 loss: 1.2366 2022/10/15 06:45:12 - mmengine - INFO - Epoch(train) [73][200/940] lr: 1.0000e-03 eta: 4:16:28 time: 0.5940 data_time: 0.0422 memory: 33630 grad_norm: 4.6986 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2053 loss: 1.2053 2022/10/15 06:45:24 - mmengine - INFO - Epoch(train) [73][220/940] lr: 1.0000e-03 eta: 4:16:17 time: 0.5833 data_time: 0.0470 memory: 33630 grad_norm: 4.8019 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.1831 loss: 1.1831 2022/10/15 06:45:36 - mmengine - INFO - Epoch(train) [73][240/940] lr: 1.0000e-03 eta: 4:16:05 time: 0.5839 data_time: 0.0345 memory: 33630 grad_norm: 4.7032 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1854 loss: 1.1854 2022/10/15 06:45:47 - mmengine - INFO - Epoch(train) [73][260/940] lr: 1.0000e-03 eta: 4:15:53 time: 0.5739 data_time: 0.0386 memory: 33630 grad_norm: 4.6452 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1743 loss: 1.1743 2022/10/15 06:45:59 - mmengine - INFO - Epoch(train) [73][280/940] lr: 1.0000e-03 eta: 4:15:41 time: 0.5743 data_time: 0.0471 memory: 33630 grad_norm: 4.6635 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2355 loss: 1.2355 2022/10/15 06:46:10 - mmengine - INFO - Epoch(train) [73][300/940] lr: 1.0000e-03 eta: 4:15:29 time: 0.5804 data_time: 0.0327 memory: 33630 grad_norm: 4.7448 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.2402 loss: 1.2402 2022/10/15 06:46:22 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 06:46:22 - mmengine - INFO - Epoch(train) [73][320/940] lr: 1.0000e-03 eta: 4:15:17 time: 0.5859 data_time: 0.0395 memory: 33630 grad_norm: 4.7941 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1497 loss: 1.1497 2022/10/15 06:46:34 - mmengine - INFO - Epoch(train) [73][340/940] lr: 1.0000e-03 eta: 4:15:06 time: 0.5888 data_time: 0.0519 memory: 33630 grad_norm: 4.6348 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1815 loss: 1.1815 2022/10/15 06:46:45 - mmengine - INFO - Epoch(train) [73][360/940] lr: 1.0000e-03 eta: 4:14:54 time: 0.5786 data_time: 0.0350 memory: 33630 grad_norm: 4.6708 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1131 loss: 1.1131 2022/10/15 06:46:57 - mmengine - INFO - Epoch(train) [73][380/940] lr: 1.0000e-03 eta: 4:14:42 time: 0.5758 data_time: 0.0346 memory: 33630 grad_norm: 4.5909 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2251 loss: 1.2251 2022/10/15 06:47:09 - mmengine - INFO - Epoch(train) [73][400/940] lr: 1.0000e-03 eta: 4:14:30 time: 0.5995 data_time: 0.0359 memory: 33630 grad_norm: 4.6778 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1924 loss: 1.1924 2022/10/15 06:47:20 - mmengine - INFO - Epoch(train) [73][420/940] lr: 1.0000e-03 eta: 4:14:18 time: 0.5817 data_time: 0.0363 memory: 33630 grad_norm: 4.6066 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1316 loss: 1.1316 2022/10/15 06:47:32 - mmengine - INFO - Epoch(train) [73][440/940] lr: 1.0000e-03 eta: 4:14:06 time: 0.5849 data_time: 0.0392 memory: 33630 grad_norm: 4.6912 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0852 loss: 1.0852 2022/10/15 06:47:44 - mmengine - INFO - Epoch(train) [73][460/940] lr: 1.0000e-03 eta: 4:13:55 time: 0.5768 data_time: 0.0356 memory: 33630 grad_norm: 4.7294 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2372 loss: 1.2372 2022/10/15 06:47:56 - mmengine - INFO - Epoch(train) [73][480/940] lr: 1.0000e-03 eta: 4:13:43 time: 0.6024 data_time: 0.0394 memory: 33630 grad_norm: 4.6609 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1387 loss: 1.1387 2022/10/15 06:48:07 - mmengine - INFO - Epoch(train) [73][500/940] lr: 1.0000e-03 eta: 4:13:31 time: 0.5810 data_time: 0.0347 memory: 33630 grad_norm: 4.7448 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.2085 loss: 1.2085 2022/10/15 06:48:19 - mmengine - INFO - Epoch(train) [73][520/940] lr: 1.0000e-03 eta: 4:13:19 time: 0.5760 data_time: 0.0344 memory: 33630 grad_norm: 4.7518 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2542 loss: 1.2542 2022/10/15 06:48:30 - mmengine - INFO - Epoch(train) [73][540/940] lr: 1.0000e-03 eta: 4:13:07 time: 0.5719 data_time: 0.0339 memory: 33630 grad_norm: 4.8695 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1909 loss: 1.1909 2022/10/15 06:48:42 - mmengine - INFO - Epoch(train) [73][560/940] lr: 1.0000e-03 eta: 4:12:55 time: 0.5749 data_time: 0.0365 memory: 33630 grad_norm: 4.6300 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0854 loss: 1.0854 2022/10/15 06:48:53 - mmengine - INFO - Epoch(train) [73][580/940] lr: 1.0000e-03 eta: 4:12:44 time: 0.5821 data_time: 0.0364 memory: 33630 grad_norm: 4.6728 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2043 loss: 1.2043 2022/10/15 06:49:05 - mmengine - INFO - Epoch(train) [73][600/940] lr: 1.0000e-03 eta: 4:12:32 time: 0.5842 data_time: 0.0426 memory: 33630 grad_norm: 4.6709 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1580 loss: 1.1580 2022/10/15 06:49:17 - mmengine - INFO - Epoch(train) [73][620/940] lr: 1.0000e-03 eta: 4:12:20 time: 0.5789 data_time: 0.0365 memory: 33630 grad_norm: 4.7190 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2451 loss: 1.2451 2022/10/15 06:49:28 - mmengine - INFO - Epoch(train) [73][640/940] lr: 1.0000e-03 eta: 4:12:08 time: 0.5738 data_time: 0.0366 memory: 33630 grad_norm: 4.7707 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2683 loss: 1.2683 2022/10/15 06:49:40 - mmengine - INFO - Epoch(train) [73][660/940] lr: 1.0000e-03 eta: 4:11:56 time: 0.5917 data_time: 0.0414 memory: 33630 grad_norm: 4.6919 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1385 loss: 1.1385 2022/10/15 06:49:52 - mmengine - INFO - Epoch(train) [73][680/940] lr: 1.0000e-03 eta: 4:11:44 time: 0.5791 data_time: 0.0367 memory: 33630 grad_norm: 4.8546 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3748 loss: 1.3748 2022/10/15 06:50:03 - mmengine - INFO - Epoch(train) [73][700/940] lr: 1.0000e-03 eta: 4:11:33 time: 0.5898 data_time: 0.0408 memory: 33630 grad_norm: 4.7556 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2619 loss: 1.2619 2022/10/15 06:50:15 - mmengine - INFO - Epoch(train) [73][720/940] lr: 1.0000e-03 eta: 4:11:21 time: 0.5788 data_time: 0.0316 memory: 33630 grad_norm: 4.7113 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2507 loss: 1.2507 2022/10/15 06:50:27 - mmengine - INFO - Epoch(train) [73][740/940] lr: 1.0000e-03 eta: 4:11:09 time: 0.5829 data_time: 0.0326 memory: 33630 grad_norm: 4.7345 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1728 loss: 1.1728 2022/10/15 06:50:38 - mmengine - INFO - Epoch(train) [73][760/940] lr: 1.0000e-03 eta: 4:10:57 time: 0.5685 data_time: 0.0384 memory: 33630 grad_norm: 4.7332 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2634 loss: 1.2634 2022/10/15 06:50:50 - mmengine - INFO - Epoch(train) [73][780/940] lr: 1.0000e-03 eta: 4:10:45 time: 0.5779 data_time: 0.0360 memory: 33630 grad_norm: 4.7820 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1573 loss: 1.1573 2022/10/15 06:51:01 - mmengine - INFO - Epoch(train) [73][800/940] lr: 1.0000e-03 eta: 4:10:33 time: 0.5961 data_time: 0.0385 memory: 33630 grad_norm: 4.7032 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1197 loss: 1.1197 2022/10/15 06:51:13 - mmengine - INFO - Epoch(train) [73][820/940] lr: 1.0000e-03 eta: 4:10:21 time: 0.5753 data_time: 0.0360 memory: 33630 grad_norm: 4.7081 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2022 loss: 1.2022 2022/10/15 06:51:25 - mmengine - INFO - Epoch(train) [73][840/940] lr: 1.0000e-03 eta: 4:10:10 time: 0.5932 data_time: 0.0403 memory: 33630 grad_norm: 4.7598 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1964 loss: 1.1964 2022/10/15 06:51:36 - mmengine - INFO - Epoch(train) [73][860/940] lr: 1.0000e-03 eta: 4:09:58 time: 0.5804 data_time: 0.0315 memory: 33630 grad_norm: 4.7459 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2375 loss: 1.2375 2022/10/15 06:51:48 - mmengine - INFO - Epoch(train) [73][880/940] lr: 1.0000e-03 eta: 4:09:46 time: 0.5768 data_time: 0.0329 memory: 33630 grad_norm: 4.7379 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.1262 loss: 1.1262 2022/10/15 06:52:00 - mmengine - INFO - Epoch(train) [73][900/940] lr: 1.0000e-03 eta: 4:09:34 time: 0.5891 data_time: 0.0415 memory: 33630 grad_norm: 4.7721 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2386 loss: 1.2386 2022/10/15 06:52:11 - mmengine - INFO - Epoch(train) [73][920/940] lr: 1.0000e-03 eta: 4:09:22 time: 0.5837 data_time: 0.0515 memory: 33630 grad_norm: 4.8161 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.1654 loss: 1.1654 2022/10/15 06:52:22 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 06:52:22 - mmengine - INFO - Epoch(train) [73][940/940] lr: 1.0000e-03 eta: 4:09:10 time: 0.5477 data_time: 0.0318 memory: 33630 grad_norm: 5.4541 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.1516 loss: 1.1516 2022/10/15 06:52:37 - mmengine - INFO - Epoch(val) [73][20/78] eta: 0:00:41 time: 0.7136 data_time: 0.5454 memory: 5967 2022/10/15 06:52:46 - mmengine - INFO - Epoch(val) [73][40/78] eta: 0:00:18 time: 0.4762 data_time: 0.3088 memory: 5967 2022/10/15 06:52:59 - mmengine - INFO - Epoch(val) [73][60/78] eta: 0:00:11 time: 0.6307 data_time: 0.4596 memory: 5967 2022/10/15 06:53:11 - mmengine - INFO - Epoch(val) [73][78/78] acc/top1: 0.6865 acc/top5: 0.8803 acc/mean1: 0.6863 2022/10/15 06:53:27 - mmengine - INFO - Epoch(train) [74][20/940] lr: 1.0000e-03 eta: 4:09:00 time: 0.8261 data_time: 0.2525 memory: 33630 grad_norm: 4.6780 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1567 loss: 1.1567 2022/10/15 06:53:39 - mmengine - INFO - Epoch(train) [74][40/940] lr: 1.0000e-03 eta: 4:08:49 time: 0.6043 data_time: 0.0387 memory: 33630 grad_norm: 4.7067 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1856 loss: 1.1856 2022/10/15 06:53:51 - mmengine - INFO - Epoch(train) [74][60/940] lr: 1.0000e-03 eta: 4:08:37 time: 0.5885 data_time: 0.0360 memory: 33630 grad_norm: 4.6292 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1041 loss: 1.1041 2022/10/15 06:54:03 - mmengine - INFO - Epoch(train) [74][80/940] lr: 1.0000e-03 eta: 4:08:25 time: 0.5817 data_time: 0.0349 memory: 33630 grad_norm: 4.7236 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1863 loss: 1.1863 2022/10/15 06:54:14 - mmengine - INFO - Epoch(train) [74][100/940] lr: 1.0000e-03 eta: 4:08:13 time: 0.5881 data_time: 0.0448 memory: 33630 grad_norm: 4.7523 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1790 loss: 1.1790 2022/10/15 06:54:26 - mmengine - INFO - Epoch(train) [74][120/940] lr: 1.0000e-03 eta: 4:08:01 time: 0.5848 data_time: 0.0319 memory: 33630 grad_norm: 4.7739 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1212 loss: 1.1212 2022/10/15 06:54:38 - mmengine - INFO - Epoch(train) [74][140/940] lr: 1.0000e-03 eta: 4:07:50 time: 0.5776 data_time: 0.0330 memory: 33630 grad_norm: 4.6177 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.0846 loss: 1.0846 2022/10/15 06:54:49 - mmengine - INFO - Epoch(train) [74][160/940] lr: 1.0000e-03 eta: 4:07:38 time: 0.5789 data_time: 0.0378 memory: 33630 grad_norm: 4.6456 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.2377 loss: 1.2377 2022/10/15 06:55:01 - mmengine - INFO - Epoch(train) [74][180/940] lr: 1.0000e-03 eta: 4:07:26 time: 0.5824 data_time: 0.0417 memory: 33630 grad_norm: 4.7729 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3556 loss: 1.3556 2022/10/15 06:55:13 - mmengine - INFO - Epoch(train) [74][200/940] lr: 1.0000e-03 eta: 4:07:14 time: 0.5858 data_time: 0.0312 memory: 33630 grad_norm: 4.6412 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1533 loss: 1.1533 2022/10/15 06:55:24 - mmengine - INFO - Epoch(train) [74][220/940] lr: 1.0000e-03 eta: 4:07:02 time: 0.5841 data_time: 0.0391 memory: 33630 grad_norm: 4.6571 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.1342 loss: 1.1342 2022/10/15 06:55:36 - mmengine - INFO - Epoch(train) [74][240/940] lr: 1.0000e-03 eta: 4:06:50 time: 0.5724 data_time: 0.0348 memory: 33630 grad_norm: 4.6880 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0949 loss: 1.0949 2022/10/15 06:55:47 - mmengine - INFO - Epoch(train) [74][260/940] lr: 1.0000e-03 eta: 4:06:38 time: 0.5798 data_time: 0.0428 memory: 33630 grad_norm: 4.7381 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3250 loss: 1.3250 2022/10/15 06:55:59 - mmengine - INFO - Epoch(train) [74][280/940] lr: 1.0000e-03 eta: 4:06:27 time: 0.5738 data_time: 0.0326 memory: 33630 grad_norm: 4.8256 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2608 loss: 1.2608 2022/10/15 06:56:11 - mmengine - INFO - Epoch(train) [74][300/940] lr: 1.0000e-03 eta: 4:06:15 time: 0.5991 data_time: 0.0427 memory: 33630 grad_norm: 4.7323 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2470 loss: 1.2470 2022/10/15 06:56:22 - mmengine - INFO - Epoch(train) [74][320/940] lr: 1.0000e-03 eta: 4:06:03 time: 0.5825 data_time: 0.0318 memory: 33630 grad_norm: 4.7578 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2045 loss: 1.2045 2022/10/15 06:56:34 - mmengine - INFO - Epoch(train) [74][340/940] lr: 1.0000e-03 eta: 4:05:51 time: 0.5791 data_time: 0.0440 memory: 33630 grad_norm: 4.6432 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2556 loss: 1.2556 2022/10/15 06:56:46 - mmengine - INFO - Epoch(train) [74][360/940] lr: 1.0000e-03 eta: 4:05:39 time: 0.5815 data_time: 0.0404 memory: 33630 grad_norm: 4.7059 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2941 loss: 1.2941 2022/10/15 06:56:57 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 06:56:57 - mmengine - INFO - Epoch(train) [74][380/940] lr: 1.0000e-03 eta: 4:05:27 time: 0.5790 data_time: 0.0398 memory: 33630 grad_norm: 4.5461 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0976 loss: 1.0976 2022/10/15 06:57:09 - mmengine - INFO - Epoch(train) [74][400/940] lr: 1.0000e-03 eta: 4:05:16 time: 0.5807 data_time: 0.0326 memory: 33630 grad_norm: 4.7261 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2919 loss: 1.2919 2022/10/15 06:57:21 - mmengine - INFO - Epoch(train) [74][420/940] lr: 1.0000e-03 eta: 4:05:04 time: 0.5857 data_time: 0.0439 memory: 33630 grad_norm: 4.7483 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.3059 loss: 1.3059 2022/10/15 06:57:32 - mmengine - INFO - Epoch(train) [74][440/940] lr: 1.0000e-03 eta: 4:04:52 time: 0.5803 data_time: 0.0325 memory: 33630 grad_norm: 4.7887 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2268 loss: 1.2268 2022/10/15 06:57:44 - mmengine - INFO - Epoch(train) [74][460/940] lr: 1.0000e-03 eta: 4:04:40 time: 0.5843 data_time: 0.0366 memory: 33630 grad_norm: 4.6865 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1881 loss: 1.1881 2022/10/15 06:57:56 - mmengine - INFO - Epoch(train) [74][480/940] lr: 1.0000e-03 eta: 4:04:28 time: 0.5857 data_time: 0.0308 memory: 33630 grad_norm: 4.8190 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1618 loss: 1.1618 2022/10/15 06:58:07 - mmengine - INFO - Epoch(train) [74][500/940] lr: 1.0000e-03 eta: 4:04:17 time: 0.5828 data_time: 0.0332 memory: 33630 grad_norm: 4.6654 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1972 loss: 1.1972 2022/10/15 06:58:19 - mmengine - INFO - Epoch(train) [74][520/940] lr: 1.0000e-03 eta: 4:04:05 time: 0.5810 data_time: 0.0394 memory: 33630 grad_norm: 4.8409 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3033 loss: 1.3033 2022/10/15 06:58:31 - mmengine - INFO - Epoch(train) [74][540/940] lr: 1.0000e-03 eta: 4:03:53 time: 0.5799 data_time: 0.0334 memory: 33630 grad_norm: 4.6901 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1722 loss: 1.1722 2022/10/15 06:58:42 - mmengine - INFO - Epoch(train) [74][560/940] lr: 1.0000e-03 eta: 4:03:41 time: 0.5775 data_time: 0.0348 memory: 33630 grad_norm: 4.6312 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1511 loss: 1.1511 2022/10/15 06:58:54 - mmengine - INFO - Epoch(train) [74][580/940] lr: 1.0000e-03 eta: 4:03:29 time: 0.5798 data_time: 0.0328 memory: 33630 grad_norm: 4.7240 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3966 loss: 1.3966 2022/10/15 06:59:05 - mmengine - INFO - Epoch(train) [74][600/940] lr: 1.0000e-03 eta: 4:03:17 time: 0.5762 data_time: 0.0341 memory: 33630 grad_norm: 4.8610 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2128 loss: 1.2128 2022/10/15 06:59:17 - mmengine - INFO - Epoch(train) [74][620/940] lr: 1.0000e-03 eta: 4:03:05 time: 0.5760 data_time: 0.0340 memory: 33630 grad_norm: 4.8266 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1880 loss: 1.1880 2022/10/15 06:59:29 - mmengine - INFO - Epoch(train) [74][640/940] lr: 1.0000e-03 eta: 4:02:54 time: 0.5893 data_time: 0.0425 memory: 33630 grad_norm: 4.8058 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3176 loss: 1.3176 2022/10/15 06:59:40 - mmengine - INFO - Epoch(train) [74][660/940] lr: 1.0000e-03 eta: 4:02:42 time: 0.5821 data_time: 0.0365 memory: 33630 grad_norm: 4.6865 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1654 loss: 1.1654 2022/10/15 06:59:52 - mmengine - INFO - Epoch(train) [74][680/940] lr: 1.0000e-03 eta: 4:02:30 time: 0.5813 data_time: 0.0419 memory: 33630 grad_norm: 4.7719 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3071 loss: 1.3071 2022/10/15 07:00:04 - mmengine - INFO - Epoch(train) [74][700/940] lr: 1.0000e-03 eta: 4:02:18 time: 0.5868 data_time: 0.0346 memory: 33630 grad_norm: 4.7279 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1657 loss: 1.1657 2022/10/15 07:00:15 - mmengine - INFO - Epoch(train) [74][720/940] lr: 1.0000e-03 eta: 4:02:06 time: 0.5956 data_time: 0.0377 memory: 33630 grad_norm: 4.7276 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3173 loss: 1.3173 2022/10/15 07:00:27 - mmengine - INFO - Epoch(train) [74][740/940] lr: 1.0000e-03 eta: 4:01:55 time: 0.5781 data_time: 0.0399 memory: 33630 grad_norm: 4.7066 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3260 loss: 1.3260 2022/10/15 07:00:39 - mmengine - INFO - Epoch(train) [74][760/940] lr: 1.0000e-03 eta: 4:01:43 time: 0.5788 data_time: 0.0410 memory: 33630 grad_norm: 4.7916 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1173 loss: 1.1173 2022/10/15 07:00:50 - mmengine - INFO - Epoch(train) [74][780/940] lr: 1.0000e-03 eta: 4:01:31 time: 0.5916 data_time: 0.0329 memory: 33630 grad_norm: 4.7153 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2338 loss: 1.2338 2022/10/15 07:01:02 - mmengine - INFO - Epoch(train) [74][800/940] lr: 1.0000e-03 eta: 4:01:19 time: 0.5752 data_time: 0.0452 memory: 33630 grad_norm: 4.7298 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2417 loss: 1.2417 2022/10/15 07:01:14 - mmengine - INFO - Epoch(train) [74][820/940] lr: 1.0000e-03 eta: 4:01:07 time: 0.5825 data_time: 0.0462 memory: 33630 grad_norm: 4.6747 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2156 loss: 1.2156 2022/10/15 07:01:25 - mmengine - INFO - Epoch(train) [74][840/940] lr: 1.0000e-03 eta: 4:00:55 time: 0.5796 data_time: 0.0407 memory: 33630 grad_norm: 4.7738 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2146 loss: 1.2146 2022/10/15 07:01:37 - mmengine - INFO - Epoch(train) [74][860/940] lr: 1.0000e-03 eta: 4:00:43 time: 0.5792 data_time: 0.0326 memory: 33630 grad_norm: 4.7364 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2100 loss: 1.2100 2022/10/15 07:01:48 - mmengine - INFO - Epoch(train) [74][880/940] lr: 1.0000e-03 eta: 4:00:32 time: 0.5758 data_time: 0.0365 memory: 33630 grad_norm: 4.7504 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2057 loss: 1.2057 2022/10/15 07:02:00 - mmengine - INFO - Epoch(train) [74][900/940] lr: 1.0000e-03 eta: 4:00:20 time: 0.5952 data_time: 0.0375 memory: 33630 grad_norm: 4.7046 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1426 loss: 1.1426 2022/10/15 07:02:12 - mmengine - INFO - Epoch(train) [74][920/940] lr: 1.0000e-03 eta: 4:00:08 time: 0.5774 data_time: 0.0374 memory: 33630 grad_norm: 4.7106 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1787 loss: 1.1787 2022/10/15 07:02:23 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 07:02:23 - mmengine - INFO - Epoch(train) [74][940/940] lr: 1.0000e-03 eta: 3:59:56 time: 0.5390 data_time: 0.0395 memory: 33630 grad_norm: 5.0062 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.1942 loss: 1.1942 2022/10/15 07:02:37 - mmengine - INFO - Epoch(val) [74][20/78] eta: 0:00:41 time: 0.7166 data_time: 0.5425 memory: 5967 2022/10/15 07:02:47 - mmengine - INFO - Epoch(val) [74][40/78] eta: 0:00:19 time: 0.5083 data_time: 0.3400 memory: 5967 2022/10/15 07:03:01 - mmengine - INFO - Epoch(val) [74][60/78] eta: 0:00:12 time: 0.6836 data_time: 0.5140 memory: 5967 2022/10/15 07:03:12 - mmengine - INFO - Epoch(val) [74][78/78] acc/top1: 0.6863 acc/top5: 0.8773 acc/mean1: 0.6861 2022/10/15 07:03:29 - mmengine - INFO - Epoch(train) [75][20/940] lr: 1.0000e-03 eta: 3:59:46 time: 0.8313 data_time: 0.2595 memory: 33630 grad_norm: 4.7756 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2146 loss: 1.2146 2022/10/15 07:03:41 - mmengine - INFO - Epoch(train) [75][40/940] lr: 1.0000e-03 eta: 3:59:34 time: 0.5946 data_time: 0.0329 memory: 33630 grad_norm: 4.7678 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1773 loss: 1.1773 2022/10/15 07:03:53 - mmengine - INFO - Epoch(train) [75][60/940] lr: 1.0000e-03 eta: 3:59:22 time: 0.5990 data_time: 0.0424 memory: 33630 grad_norm: 4.6766 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1211 loss: 1.1211 2022/10/15 07:04:04 - mmengine - INFO - Epoch(train) [75][80/940] lr: 1.0000e-03 eta: 3:59:11 time: 0.5869 data_time: 0.0410 memory: 33630 grad_norm: 4.7113 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2831 loss: 1.2831 2022/10/15 07:04:16 - mmengine - INFO - Epoch(train) [75][100/940] lr: 1.0000e-03 eta: 3:58:59 time: 0.5940 data_time: 0.0334 memory: 33630 grad_norm: 4.6217 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2480 loss: 1.2480 2022/10/15 07:04:28 - mmengine - INFO - Epoch(train) [75][120/940] lr: 1.0000e-03 eta: 3:58:47 time: 0.5712 data_time: 0.0343 memory: 33630 grad_norm: 4.7590 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2303 loss: 1.2303 2022/10/15 07:04:39 - mmengine - INFO - Epoch(train) [75][140/940] lr: 1.0000e-03 eta: 3:58:35 time: 0.5791 data_time: 0.0358 memory: 33630 grad_norm: 4.7691 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0791 loss: 1.0791 2022/10/15 07:04:51 - mmengine - INFO - Epoch(train) [75][160/940] lr: 1.0000e-03 eta: 3:58:23 time: 0.5853 data_time: 0.0324 memory: 33630 grad_norm: 4.7133 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1811 loss: 1.1811 2022/10/15 07:05:03 - mmengine - INFO - Epoch(train) [75][180/940] lr: 1.0000e-03 eta: 3:58:11 time: 0.5953 data_time: 0.0397 memory: 33630 grad_norm: 4.8462 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2133 loss: 1.2133 2022/10/15 07:05:14 - mmengine - INFO - Epoch(train) [75][200/940] lr: 1.0000e-03 eta: 3:58:00 time: 0.5780 data_time: 0.0308 memory: 33630 grad_norm: 4.7218 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2996 loss: 1.2996 2022/10/15 07:05:26 - mmengine - INFO - Epoch(train) [75][220/940] lr: 1.0000e-03 eta: 3:57:48 time: 0.5780 data_time: 0.0370 memory: 33630 grad_norm: 4.8088 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1548 loss: 1.1548 2022/10/15 07:05:38 - mmengine - INFO - Epoch(train) [75][240/940] lr: 1.0000e-03 eta: 3:57:36 time: 0.5851 data_time: 0.0367 memory: 33630 grad_norm: 4.7201 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2322 loss: 1.2322 2022/10/15 07:05:49 - mmengine - INFO - Epoch(train) [75][260/940] lr: 1.0000e-03 eta: 3:57:24 time: 0.5868 data_time: 0.0357 memory: 33630 grad_norm: 4.6848 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1404 loss: 1.1404 2022/10/15 07:06:01 - mmengine - INFO - Epoch(train) [75][280/940] lr: 1.0000e-03 eta: 3:57:12 time: 0.5872 data_time: 0.0377 memory: 33630 grad_norm: 4.8146 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2721 loss: 1.2721 2022/10/15 07:06:13 - mmengine - INFO - Epoch(train) [75][300/940] lr: 1.0000e-03 eta: 3:57:00 time: 0.5761 data_time: 0.0381 memory: 33630 grad_norm: 4.7288 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1387 loss: 1.1387 2022/10/15 07:06:24 - mmengine - INFO - Epoch(train) [75][320/940] lr: 1.0000e-03 eta: 3:56:49 time: 0.5862 data_time: 0.0346 memory: 33630 grad_norm: 4.8141 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1682 loss: 1.1682 2022/10/15 07:06:36 - mmengine - INFO - Epoch(train) [75][340/940] lr: 1.0000e-03 eta: 3:56:37 time: 0.5743 data_time: 0.0362 memory: 33630 grad_norm: 4.7192 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1789 loss: 1.1789 2022/10/15 07:06:48 - mmengine - INFO - Epoch(train) [75][360/940] lr: 1.0000e-03 eta: 3:56:25 time: 0.5918 data_time: 0.0325 memory: 33630 grad_norm: 4.6030 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2449 loss: 1.2449 2022/10/15 07:06:59 - mmengine - INFO - Epoch(train) [75][380/940] lr: 1.0000e-03 eta: 3:56:13 time: 0.5802 data_time: 0.0307 memory: 33630 grad_norm: 4.6843 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1498 loss: 1.1498 2022/10/15 07:07:11 - mmengine - INFO - Epoch(train) [75][400/940] lr: 1.0000e-03 eta: 3:56:01 time: 0.5920 data_time: 0.0337 memory: 33630 grad_norm: 4.8001 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2754 loss: 1.2754 2022/10/15 07:07:23 - mmengine - INFO - Epoch(train) [75][420/940] lr: 1.0000e-03 eta: 3:55:50 time: 0.6031 data_time: 0.0488 memory: 33630 grad_norm: 4.7064 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1709 loss: 1.1709 2022/10/15 07:07:35 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 07:07:35 - mmengine - INFO - Epoch(train) [75][440/940] lr: 1.0000e-03 eta: 3:55:38 time: 0.5810 data_time: 0.0414 memory: 33630 grad_norm: 4.7510 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3103 loss: 1.3103 2022/10/15 07:07:46 - mmengine - INFO - Epoch(train) [75][460/940] lr: 1.0000e-03 eta: 3:55:26 time: 0.5780 data_time: 0.0436 memory: 33630 grad_norm: 4.6738 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2079 loss: 1.2079 2022/10/15 07:07:58 - mmengine - INFO - Epoch(train) [75][480/940] lr: 1.0000e-03 eta: 3:55:14 time: 0.5748 data_time: 0.0406 memory: 33630 grad_norm: 4.6210 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1249 loss: 1.1249 2022/10/15 07:08:09 - mmengine - INFO - Epoch(train) [75][500/940] lr: 1.0000e-03 eta: 3:55:02 time: 0.5702 data_time: 0.0304 memory: 33630 grad_norm: 4.7666 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2974 loss: 1.2974 2022/10/15 07:08:21 - mmengine - INFO - Epoch(train) [75][520/940] lr: 1.0000e-03 eta: 3:54:50 time: 0.5791 data_time: 0.0347 memory: 33630 grad_norm: 4.7101 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2518 loss: 1.2518 2022/10/15 07:08:33 - mmengine - INFO - Epoch(train) [75][540/940] lr: 1.0000e-03 eta: 3:54:39 time: 0.5804 data_time: 0.0340 memory: 33630 grad_norm: 4.6923 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2059 loss: 1.2059 2022/10/15 07:08:44 - mmengine - INFO - Epoch(train) [75][560/940] lr: 1.0000e-03 eta: 3:54:27 time: 0.5740 data_time: 0.0370 memory: 33630 grad_norm: 4.8877 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2018 loss: 1.2018 2022/10/15 07:08:56 - mmengine - INFO - Epoch(train) [75][580/940] lr: 1.0000e-03 eta: 3:54:15 time: 0.5806 data_time: 0.0368 memory: 33630 grad_norm: 4.6819 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2645 loss: 1.2645 2022/10/15 07:09:07 - mmengine - INFO - Epoch(train) [75][600/940] lr: 1.0000e-03 eta: 3:54:03 time: 0.5895 data_time: 0.0351 memory: 33630 grad_norm: 4.7864 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.1262 loss: 1.1262 2022/10/15 07:09:19 - mmengine - INFO - Epoch(train) [75][620/940] lr: 1.0000e-03 eta: 3:53:51 time: 0.5828 data_time: 0.0373 memory: 33630 grad_norm: 4.8107 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2797 loss: 1.2797 2022/10/15 07:09:31 - mmengine - INFO - Epoch(train) [75][640/940] lr: 1.0000e-03 eta: 3:53:39 time: 0.5834 data_time: 0.0314 memory: 33630 grad_norm: 4.8491 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2192 loss: 1.2192 2022/10/15 07:09:42 - mmengine - INFO - Epoch(train) [75][660/940] lr: 1.0000e-03 eta: 3:53:28 time: 0.5780 data_time: 0.0348 memory: 33630 grad_norm: 4.7581 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1265 loss: 1.1265 2022/10/15 07:09:54 - mmengine - INFO - Epoch(train) [75][680/940] lr: 1.0000e-03 eta: 3:53:16 time: 0.5816 data_time: 0.0356 memory: 33630 grad_norm: 4.6838 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1517 loss: 1.1517 2022/10/15 07:10:05 - mmengine - INFO - Epoch(train) [75][700/940] lr: 1.0000e-03 eta: 3:53:04 time: 0.5745 data_time: 0.0310 memory: 33630 grad_norm: 4.7991 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1731 loss: 1.1731 2022/10/15 07:10:17 - mmengine - INFO - Epoch(train) [75][720/940] lr: 1.0000e-03 eta: 3:52:52 time: 0.5837 data_time: 0.0378 memory: 33630 grad_norm: 4.7450 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.2107 loss: 1.2107 2022/10/15 07:10:29 - mmengine - INFO - Epoch(train) [75][740/940] lr: 1.0000e-03 eta: 3:52:40 time: 0.5750 data_time: 0.0333 memory: 33630 grad_norm: 4.8211 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1674 loss: 1.1674 2022/10/15 07:10:40 - mmengine - INFO - Epoch(train) [75][760/940] lr: 1.0000e-03 eta: 3:52:28 time: 0.5894 data_time: 0.0327 memory: 33630 grad_norm: 4.7901 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1992 loss: 1.1992 2022/10/15 07:10:52 - mmengine - INFO - Epoch(train) [75][780/940] lr: 1.0000e-03 eta: 3:52:17 time: 0.5840 data_time: 0.0327 memory: 33630 grad_norm: 4.6976 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1992 loss: 1.1992 2022/10/15 07:11:04 - mmengine - INFO - Epoch(train) [75][800/940] lr: 1.0000e-03 eta: 3:52:05 time: 0.5729 data_time: 0.0375 memory: 33630 grad_norm: 4.8807 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1373 loss: 1.1373 2022/10/15 07:11:15 - mmengine - INFO - Epoch(train) [75][820/940] lr: 1.0000e-03 eta: 3:51:53 time: 0.5906 data_time: 0.0485 memory: 33630 grad_norm: 4.7325 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1378 loss: 1.1378 2022/10/15 07:11:27 - mmengine - INFO - Epoch(train) [75][840/940] lr: 1.0000e-03 eta: 3:51:41 time: 0.5684 data_time: 0.0355 memory: 33630 grad_norm: 4.7470 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2436 loss: 1.2436 2022/10/15 07:11:39 - mmengine - INFO - Epoch(train) [75][860/940] lr: 1.0000e-03 eta: 3:51:29 time: 0.5893 data_time: 0.0340 memory: 33630 grad_norm: 4.6867 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2252 loss: 1.2252 2022/10/15 07:11:50 - mmengine - INFO - Epoch(train) [75][880/940] lr: 1.0000e-03 eta: 3:51:17 time: 0.5765 data_time: 0.0390 memory: 33630 grad_norm: 4.6862 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2089 loss: 1.2089 2022/10/15 07:12:02 - mmengine - INFO - Epoch(train) [75][900/940] lr: 1.0000e-03 eta: 3:51:06 time: 0.5846 data_time: 0.0422 memory: 33630 grad_norm: 4.8552 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2503 loss: 1.2503 2022/10/15 07:12:13 - mmengine - INFO - Epoch(train) [75][920/940] lr: 1.0000e-03 eta: 3:50:54 time: 0.5777 data_time: 0.0382 memory: 33630 grad_norm: 4.8446 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1374 loss: 1.1374 2022/10/15 07:12:24 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 07:12:24 - mmengine - INFO - Epoch(train) [75][940/940] lr: 1.0000e-03 eta: 3:50:42 time: 0.5378 data_time: 0.0296 memory: 33630 grad_norm: 5.1933 top1_acc: 0.4286 top5_acc: 1.0000 loss_cls: 1.3985 loss: 1.3985 2022/10/15 07:12:24 - mmengine - INFO - Saving checkpoint at 75 epochs 2022/10/15 07:12:40 - mmengine - INFO - Epoch(val) [75][20/78] eta: 0:00:44 time: 0.7755 data_time: 0.6070 memory: 5967 2022/10/15 07:12:50 - mmengine - INFO - Epoch(val) [75][40/78] eta: 0:00:18 time: 0.4762 data_time: 0.3088 memory: 5967 2022/10/15 07:13:03 - mmengine - INFO - Epoch(val) [75][60/78] eta: 0:00:11 time: 0.6436 data_time: 0.4733 memory: 5967 2022/10/15 07:13:13 - mmengine - INFO - Epoch(val) [75][78/78] acc/top1: 0.6867 acc/top5: 0.8784 acc/mean1: 0.6866 2022/10/15 07:13:29 - mmengine - INFO - Epoch(train) [76][20/940] lr: 1.0000e-03 eta: 3:50:31 time: 0.8023 data_time: 0.2619 memory: 33630 grad_norm: 4.7645 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2399 loss: 1.2399 2022/10/15 07:13:40 - mmengine - INFO - Epoch(train) [76][40/940] lr: 1.0000e-03 eta: 3:50:19 time: 0.5796 data_time: 0.0356 memory: 33630 grad_norm: 4.7790 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1675 loss: 1.1675 2022/10/15 07:13:52 - mmengine - INFO - Epoch(train) [76][60/940] lr: 1.0000e-03 eta: 3:50:08 time: 0.5886 data_time: 0.0355 memory: 33630 grad_norm: 4.6673 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2717 loss: 1.2717 2022/10/15 07:14:04 - mmengine - INFO - Epoch(train) [76][80/940] lr: 1.0000e-03 eta: 3:49:56 time: 0.5961 data_time: 0.0362 memory: 33630 grad_norm: 4.6904 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1896 loss: 1.1896 2022/10/15 07:14:16 - mmengine - INFO - Epoch(train) [76][100/940] lr: 1.0000e-03 eta: 3:49:44 time: 0.5911 data_time: 0.0392 memory: 33630 grad_norm: 4.6413 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1253 loss: 1.1253 2022/10/15 07:14:28 - mmengine - INFO - Epoch(train) [76][120/940] lr: 1.0000e-03 eta: 3:49:32 time: 0.5859 data_time: 0.0346 memory: 33630 grad_norm: 4.7275 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2376 loss: 1.2376 2022/10/15 07:14:40 - mmengine - INFO - Epoch(train) [76][140/940] lr: 1.0000e-03 eta: 3:49:21 time: 0.5949 data_time: 0.0376 memory: 33630 grad_norm: 4.5768 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1527 loss: 1.1527 2022/10/15 07:14:51 - mmengine - INFO - Epoch(train) [76][160/940] lr: 1.0000e-03 eta: 3:49:09 time: 0.5731 data_time: 0.0304 memory: 33630 grad_norm: 4.7772 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0899 loss: 1.0899 2022/10/15 07:15:03 - mmengine - INFO - Epoch(train) [76][180/940] lr: 1.0000e-03 eta: 3:48:57 time: 0.5897 data_time: 0.0429 memory: 33630 grad_norm: 4.7106 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1279 loss: 1.1279 2022/10/15 07:15:14 - mmengine - INFO - Epoch(train) [76][200/940] lr: 1.0000e-03 eta: 3:48:45 time: 0.5719 data_time: 0.0322 memory: 33630 grad_norm: 4.8450 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1820 loss: 1.1820 2022/10/15 07:15:26 - mmengine - INFO - Epoch(train) [76][220/940] lr: 1.0000e-03 eta: 3:48:33 time: 0.5851 data_time: 0.0389 memory: 33630 grad_norm: 4.7744 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.1752 loss: 1.1752 2022/10/15 07:15:37 - mmengine - INFO - Epoch(train) [76][240/940] lr: 1.0000e-03 eta: 3:48:21 time: 0.5731 data_time: 0.0320 memory: 33630 grad_norm: 4.7579 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2005 loss: 1.2005 2022/10/15 07:15:49 - mmengine - INFO - Epoch(train) [76][260/940] lr: 1.0000e-03 eta: 3:48:09 time: 0.5765 data_time: 0.0352 memory: 33630 grad_norm: 4.6955 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1475 loss: 1.1475 2022/10/15 07:16:01 - mmengine - INFO - Epoch(train) [76][280/940] lr: 1.0000e-03 eta: 3:47:58 time: 0.5867 data_time: 0.0382 memory: 33630 grad_norm: 4.7049 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1887 loss: 1.1887 2022/10/15 07:16:12 - mmengine - INFO - Epoch(train) [76][300/940] lr: 1.0000e-03 eta: 3:47:46 time: 0.5853 data_time: 0.0375 memory: 33630 grad_norm: 4.7548 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1857 loss: 1.1857 2022/10/15 07:16:24 - mmengine - INFO - Epoch(train) [76][320/940] lr: 1.0000e-03 eta: 3:47:34 time: 0.5827 data_time: 0.0307 memory: 33630 grad_norm: 4.7647 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2153 loss: 1.2153 2022/10/15 07:16:36 - mmengine - INFO - Epoch(train) [76][340/940] lr: 1.0000e-03 eta: 3:47:22 time: 0.5800 data_time: 0.0373 memory: 33630 grad_norm: 4.7993 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2319 loss: 1.2319 2022/10/15 07:16:47 - mmengine - INFO - Epoch(train) [76][360/940] lr: 1.0000e-03 eta: 3:47:10 time: 0.5685 data_time: 0.0330 memory: 33630 grad_norm: 4.8457 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2488 loss: 1.2488 2022/10/15 07:16:59 - mmengine - INFO - Epoch(train) [76][380/940] lr: 1.0000e-03 eta: 3:46:58 time: 0.5818 data_time: 0.0366 memory: 33630 grad_norm: 4.6331 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1489 loss: 1.1489 2022/10/15 07:17:10 - mmengine - INFO - Epoch(train) [76][400/940] lr: 1.0000e-03 eta: 3:46:47 time: 0.5743 data_time: 0.0334 memory: 33630 grad_norm: 4.7980 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.2535 loss: 1.2535 2022/10/15 07:17:22 - mmengine - INFO - Epoch(train) [76][420/940] lr: 1.0000e-03 eta: 3:46:35 time: 0.5883 data_time: 0.0412 memory: 33630 grad_norm: 4.7032 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2972 loss: 1.2972 2022/10/15 07:17:33 - mmengine - INFO - Epoch(train) [76][440/940] lr: 1.0000e-03 eta: 3:46:23 time: 0.5759 data_time: 0.0418 memory: 33630 grad_norm: 4.6935 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1546 loss: 1.1546 2022/10/15 07:17:45 - mmengine - INFO - Epoch(train) [76][460/940] lr: 1.0000e-03 eta: 3:46:11 time: 0.5826 data_time: 0.0369 memory: 33630 grad_norm: 4.7087 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1689 loss: 1.1689 2022/10/15 07:17:57 - mmengine - INFO - Epoch(train) [76][480/940] lr: 1.0000e-03 eta: 3:45:59 time: 0.5706 data_time: 0.0354 memory: 33630 grad_norm: 4.8833 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2090 loss: 1.2090 2022/10/15 07:18:08 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 07:18:08 - mmengine - INFO - Epoch(train) [76][500/940] lr: 1.0000e-03 eta: 3:45:47 time: 0.5854 data_time: 0.0377 memory: 33630 grad_norm: 4.5988 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1927 loss: 1.1927 2022/10/15 07:18:20 - mmengine - INFO - Epoch(train) [76][520/940] lr: 1.0000e-03 eta: 3:45:36 time: 0.5886 data_time: 0.0342 memory: 33630 grad_norm: 4.6879 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1112 loss: 1.1112 2022/10/15 07:18:32 - mmengine - INFO - Epoch(train) [76][540/940] lr: 1.0000e-03 eta: 3:45:24 time: 0.5845 data_time: 0.0394 memory: 33630 grad_norm: 4.7770 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1962 loss: 1.1962 2022/10/15 07:18:43 - mmengine - INFO - Epoch(train) [76][560/940] lr: 1.0000e-03 eta: 3:45:12 time: 0.5876 data_time: 0.0384 memory: 33630 grad_norm: 4.8506 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0914 loss: 1.0914 2022/10/15 07:18:55 - mmengine - INFO - Epoch(train) [76][580/940] lr: 1.0000e-03 eta: 3:45:00 time: 0.5766 data_time: 0.0412 memory: 33630 grad_norm: 4.7498 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.1999 loss: 1.1999 2022/10/15 07:19:07 - mmengine - INFO - Epoch(train) [76][600/940] lr: 1.0000e-03 eta: 3:44:48 time: 0.5792 data_time: 0.0359 memory: 33630 grad_norm: 4.7978 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2453 loss: 1.2453 2022/10/15 07:19:18 - mmengine - INFO - Epoch(train) [76][620/940] lr: 1.0000e-03 eta: 3:44:36 time: 0.5896 data_time: 0.0317 memory: 33630 grad_norm: 4.7485 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2228 loss: 1.2228 2022/10/15 07:19:30 - mmengine - INFO - Epoch(train) [76][640/940] lr: 1.0000e-03 eta: 3:44:25 time: 0.5812 data_time: 0.0379 memory: 33630 grad_norm: 4.6822 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2012 loss: 1.2012 2022/10/15 07:19:42 - mmengine - INFO - Epoch(train) [76][660/940] lr: 1.0000e-03 eta: 3:44:13 time: 0.5809 data_time: 0.0356 memory: 33630 grad_norm: 4.8102 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2096 loss: 1.2096 2022/10/15 07:19:53 - mmengine - INFO - Epoch(train) [76][680/940] lr: 1.0000e-03 eta: 3:44:01 time: 0.5871 data_time: 0.0379 memory: 33630 grad_norm: 4.8008 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3044 loss: 1.3044 2022/10/15 07:20:05 - mmengine - INFO - Epoch(train) [76][700/940] lr: 1.0000e-03 eta: 3:43:49 time: 0.5854 data_time: 0.0371 memory: 33630 grad_norm: 4.7918 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.1499 loss: 1.1499 2022/10/15 07:20:16 - mmengine - INFO - Epoch(train) [76][720/940] lr: 1.0000e-03 eta: 3:43:37 time: 0.5680 data_time: 0.0343 memory: 33630 grad_norm: 4.8205 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1156 loss: 1.1156 2022/10/15 07:20:28 - mmengine - INFO - Epoch(train) [76][740/940] lr: 1.0000e-03 eta: 3:43:25 time: 0.5821 data_time: 0.0328 memory: 33630 grad_norm: 4.8135 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1563 loss: 1.1563 2022/10/15 07:20:40 - mmengine - INFO - Epoch(train) [76][760/940] lr: 1.0000e-03 eta: 3:43:14 time: 0.5804 data_time: 0.0366 memory: 33630 grad_norm: 4.7699 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2298 loss: 1.2298 2022/10/15 07:20:51 - mmengine - INFO - Epoch(train) [76][780/940] lr: 1.0000e-03 eta: 3:43:02 time: 0.5685 data_time: 0.0368 memory: 33630 grad_norm: 4.6854 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1524 loss: 1.1524 2022/10/15 07:21:03 - mmengine - INFO - Epoch(train) [76][800/940] lr: 1.0000e-03 eta: 3:42:50 time: 0.5831 data_time: 0.0472 memory: 33630 grad_norm: 4.7126 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2775 loss: 1.2775 2022/10/15 07:21:14 - mmengine - INFO - Epoch(train) [76][820/940] lr: 1.0000e-03 eta: 3:42:38 time: 0.5730 data_time: 0.0329 memory: 33630 grad_norm: 4.7760 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0924 loss: 1.0924 2022/10/15 07:21:26 - mmengine - INFO - Epoch(train) [76][840/940] lr: 1.0000e-03 eta: 3:42:26 time: 0.5881 data_time: 0.0341 memory: 33630 grad_norm: 4.7642 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1968 loss: 1.1968 2022/10/15 07:21:37 - mmengine - INFO - Epoch(train) [76][860/940] lr: 1.0000e-03 eta: 3:42:14 time: 0.5690 data_time: 0.0329 memory: 33630 grad_norm: 4.7837 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2326 loss: 1.2326 2022/10/15 07:21:49 - mmengine - INFO - Epoch(train) [76][880/940] lr: 1.0000e-03 eta: 3:42:03 time: 0.5824 data_time: 0.0368 memory: 33630 grad_norm: 4.8077 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2020 loss: 1.2020 2022/10/15 07:22:01 - mmengine - INFO - Epoch(train) [76][900/940] lr: 1.0000e-03 eta: 3:41:51 time: 0.5785 data_time: 0.0381 memory: 33630 grad_norm: 4.7408 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.1542 loss: 1.1542 2022/10/15 07:22:12 - mmengine - INFO - Epoch(train) [76][920/940] lr: 1.0000e-03 eta: 3:41:39 time: 0.5848 data_time: 0.0323 memory: 33630 grad_norm: 4.7390 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1493 loss: 1.1493 2022/10/15 07:22:23 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 07:22:23 - mmengine - INFO - Epoch(train) [76][940/940] lr: 1.0000e-03 eta: 3:41:27 time: 0.5338 data_time: 0.0347 memory: 33630 grad_norm: 5.3419 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.2645 loss: 1.2645 2022/10/15 07:22:37 - mmengine - INFO - Epoch(val) [76][20/78] eta: 0:00:41 time: 0.7224 data_time: 0.5523 memory: 5967 2022/10/15 07:22:48 - mmengine - INFO - Epoch(val) [76][40/78] eta: 0:00:19 time: 0.5181 data_time: 0.3471 memory: 5967 2022/10/15 07:23:01 - mmengine - INFO - Epoch(val) [76][60/78] eta: 0:00:11 time: 0.6447 data_time: 0.4742 memory: 5967 2022/10/15 07:23:12 - mmengine - INFO - Epoch(val) [76][78/78] acc/top1: 0.6854 acc/top5: 0.8785 acc/mean1: 0.6852 2022/10/15 07:23:28 - mmengine - INFO - Epoch(train) [77][20/940] lr: 1.0000e-03 eta: 3:41:16 time: 0.8151 data_time: 0.2551 memory: 33630 grad_norm: 4.7671 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.1121 loss: 1.1121 2022/10/15 07:23:40 - mmengine - INFO - Epoch(train) [77][40/940] lr: 1.0000e-03 eta: 3:41:05 time: 0.5760 data_time: 0.0331 memory: 33630 grad_norm: 4.8220 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2934 loss: 1.2934 2022/10/15 07:23:51 - mmengine - INFO - Epoch(train) [77][60/940] lr: 1.0000e-03 eta: 3:40:53 time: 0.5857 data_time: 0.0380 memory: 33630 grad_norm: 4.7416 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2288 loss: 1.2288 2022/10/15 07:24:03 - mmengine - INFO - Epoch(train) [77][80/940] lr: 1.0000e-03 eta: 3:40:41 time: 0.5754 data_time: 0.0343 memory: 33630 grad_norm: 4.7483 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1865 loss: 1.1865 2022/10/15 07:24:15 - mmengine - INFO - Epoch(train) [77][100/940] lr: 1.0000e-03 eta: 3:40:29 time: 0.5855 data_time: 0.0400 memory: 33630 grad_norm: 4.8499 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2738 loss: 1.2738 2022/10/15 07:24:26 - mmengine - INFO - Epoch(train) [77][120/940] lr: 1.0000e-03 eta: 3:40:17 time: 0.5786 data_time: 0.0342 memory: 33630 grad_norm: 4.6962 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1672 loss: 1.1672 2022/10/15 07:24:38 - mmengine - INFO - Epoch(train) [77][140/940] lr: 1.0000e-03 eta: 3:40:05 time: 0.5777 data_time: 0.0374 memory: 33630 grad_norm: 4.7310 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2172 loss: 1.2172 2022/10/15 07:24:50 - mmengine - INFO - Epoch(train) [77][160/940] lr: 1.0000e-03 eta: 3:39:54 time: 0.5948 data_time: 0.0311 memory: 33630 grad_norm: 4.7092 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1051 loss: 1.1051 2022/10/15 07:25:01 - mmengine - INFO - Epoch(train) [77][180/940] lr: 1.0000e-03 eta: 3:39:42 time: 0.5839 data_time: 0.0478 memory: 33630 grad_norm: 4.7529 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3566 loss: 1.3566 2022/10/15 07:25:13 - mmengine - INFO - Epoch(train) [77][200/940] lr: 1.0000e-03 eta: 3:39:30 time: 0.5733 data_time: 0.0350 memory: 33630 grad_norm: 4.6725 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3244 loss: 1.3244 2022/10/15 07:25:25 - mmengine - INFO - Epoch(train) [77][220/940] lr: 1.0000e-03 eta: 3:39:18 time: 0.5882 data_time: 0.0331 memory: 33630 grad_norm: 4.7805 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0709 loss: 1.0709 2022/10/15 07:25:36 - mmengine - INFO - Epoch(train) [77][240/940] lr: 1.0000e-03 eta: 3:39:06 time: 0.5876 data_time: 0.0380 memory: 33630 grad_norm: 4.7740 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2362 loss: 1.2362 2022/10/15 07:25:48 - mmengine - INFO - Epoch(train) [77][260/940] lr: 1.0000e-03 eta: 3:38:55 time: 0.5808 data_time: 0.0389 memory: 33630 grad_norm: 4.7324 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1436 loss: 1.1436 2022/10/15 07:25:59 - mmengine - INFO - Epoch(train) [77][280/940] lr: 1.0000e-03 eta: 3:38:43 time: 0.5778 data_time: 0.0462 memory: 33630 grad_norm: 4.6844 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1428 loss: 1.1428 2022/10/15 07:26:11 - mmengine - INFO - Epoch(train) [77][300/940] lr: 1.0000e-03 eta: 3:38:31 time: 0.5869 data_time: 0.0367 memory: 33630 grad_norm: 4.7670 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1516 loss: 1.1516 2022/10/15 07:26:23 - mmengine - INFO - Epoch(train) [77][320/940] lr: 1.0000e-03 eta: 3:38:19 time: 0.5758 data_time: 0.0471 memory: 33630 grad_norm: 4.7107 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1456 loss: 1.1456 2022/10/15 07:26:34 - mmengine - INFO - Epoch(train) [77][340/940] lr: 1.0000e-03 eta: 3:38:07 time: 0.5793 data_time: 0.0376 memory: 33630 grad_norm: 4.7452 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.1716 loss: 1.1716 2022/10/15 07:26:46 - mmengine - INFO - Epoch(train) [77][360/940] lr: 1.0000e-03 eta: 3:37:55 time: 0.5904 data_time: 0.0460 memory: 33630 grad_norm: 4.6668 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1311 loss: 1.1311 2022/10/15 07:26:58 - mmengine - INFO - Epoch(train) [77][380/940] lr: 1.0000e-03 eta: 3:37:44 time: 0.5748 data_time: 0.0341 memory: 33630 grad_norm: 4.6380 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1422 loss: 1.1422 2022/10/15 07:27:09 - mmengine - INFO - Epoch(train) [77][400/940] lr: 1.0000e-03 eta: 3:37:32 time: 0.5803 data_time: 0.0362 memory: 33630 grad_norm: 4.7830 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1073 loss: 1.1073 2022/10/15 07:27:21 - mmengine - INFO - Epoch(train) [77][420/940] lr: 1.0000e-03 eta: 3:37:20 time: 0.5763 data_time: 0.0316 memory: 33630 grad_norm: 4.8415 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2341 loss: 1.2341 2022/10/15 07:27:32 - mmengine - INFO - Epoch(train) [77][440/940] lr: 1.0000e-03 eta: 3:37:08 time: 0.5812 data_time: 0.0366 memory: 33630 grad_norm: 4.7552 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3032 loss: 1.3032 2022/10/15 07:27:44 - mmengine - INFO - Epoch(train) [77][460/940] lr: 1.0000e-03 eta: 3:36:56 time: 0.5881 data_time: 0.0418 memory: 33630 grad_norm: 4.7064 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2005 loss: 1.2005 2022/10/15 07:27:56 - mmengine - INFO - Epoch(train) [77][480/940] lr: 1.0000e-03 eta: 3:36:44 time: 0.5741 data_time: 0.0401 memory: 33630 grad_norm: 4.8097 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1505 loss: 1.1505 2022/10/15 07:28:07 - mmengine - INFO - Epoch(train) [77][500/940] lr: 1.0000e-03 eta: 3:36:33 time: 0.5806 data_time: 0.0374 memory: 33630 grad_norm: 4.8193 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1853 loss: 1.1853 2022/10/15 07:28:19 - mmengine - INFO - Epoch(train) [77][520/940] lr: 1.0000e-03 eta: 3:36:21 time: 0.5784 data_time: 0.0373 memory: 33630 grad_norm: 4.7558 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0586 loss: 1.0586 2022/10/15 07:28:31 - mmengine - INFO - Epoch(train) [77][540/940] lr: 1.0000e-03 eta: 3:36:09 time: 0.5853 data_time: 0.0383 memory: 33630 grad_norm: 4.7612 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0110 loss: 1.0110 2022/10/15 07:28:42 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 07:28:42 - mmengine - INFO - Epoch(train) [77][560/940] lr: 1.0000e-03 eta: 3:35:57 time: 0.5734 data_time: 0.0316 memory: 33630 grad_norm: 4.6910 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0698 loss: 1.0698 2022/10/15 07:28:54 - mmengine - INFO - Epoch(train) [77][580/940] lr: 1.0000e-03 eta: 3:35:45 time: 0.5833 data_time: 0.0303 memory: 33630 grad_norm: 4.6680 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3218 loss: 1.3218 2022/10/15 07:29:05 - mmengine - INFO - Epoch(train) [77][600/940] lr: 1.0000e-03 eta: 3:35:33 time: 0.5830 data_time: 0.0318 memory: 33630 grad_norm: 4.7733 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1622 loss: 1.1622 2022/10/15 07:29:17 - mmengine - INFO - Epoch(train) [77][620/940] lr: 1.0000e-03 eta: 3:35:22 time: 0.5762 data_time: 0.0364 memory: 33630 grad_norm: 4.7303 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.1358 loss: 1.1358 2022/10/15 07:29:29 - mmengine - INFO - Epoch(train) [77][640/940] lr: 1.0000e-03 eta: 3:35:10 time: 0.5832 data_time: 0.0327 memory: 33630 grad_norm: 4.8252 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1251 loss: 1.1251 2022/10/15 07:29:40 - mmengine - INFO - Epoch(train) [77][660/940] lr: 1.0000e-03 eta: 3:34:58 time: 0.5797 data_time: 0.0384 memory: 33630 grad_norm: 4.8401 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2203 loss: 1.2203 2022/10/15 07:29:52 - mmengine - INFO - Epoch(train) [77][680/940] lr: 1.0000e-03 eta: 3:34:46 time: 0.5728 data_time: 0.0387 memory: 33630 grad_norm: 4.7278 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1827 loss: 1.1827 2022/10/15 07:30:03 - mmengine - INFO - Epoch(train) [77][700/940] lr: 1.0000e-03 eta: 3:34:34 time: 0.5904 data_time: 0.0326 memory: 33630 grad_norm: 4.8698 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3150 loss: 1.3150 2022/10/15 07:30:15 - mmengine - INFO - Epoch(train) [77][720/940] lr: 1.0000e-03 eta: 3:34:22 time: 0.5758 data_time: 0.0369 memory: 33630 grad_norm: 4.8442 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1905 loss: 1.1905 2022/10/15 07:30:27 - mmengine - INFO - Epoch(train) [77][740/940] lr: 1.0000e-03 eta: 3:34:11 time: 0.5858 data_time: 0.0379 memory: 33630 grad_norm: 4.9179 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2196 loss: 1.2196 2022/10/15 07:30:38 - mmengine - INFO - Epoch(train) [77][760/940] lr: 1.0000e-03 eta: 3:33:59 time: 0.5827 data_time: 0.0315 memory: 33630 grad_norm: 4.7253 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2654 loss: 1.2654 2022/10/15 07:30:50 - mmengine - INFO - Epoch(train) [77][780/940] lr: 1.0000e-03 eta: 3:33:47 time: 0.5801 data_time: 0.0325 memory: 33630 grad_norm: 4.7763 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0915 loss: 1.0915 2022/10/15 07:31:02 - mmengine - INFO - Epoch(train) [77][800/940] lr: 1.0000e-03 eta: 3:33:35 time: 0.5796 data_time: 0.0397 memory: 33630 grad_norm: 4.7084 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.1349 loss: 1.1349 2022/10/15 07:31:13 - mmengine - INFO - Epoch(train) [77][820/940] lr: 1.0000e-03 eta: 3:33:23 time: 0.5912 data_time: 0.0394 memory: 33630 grad_norm: 4.7843 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1769 loss: 1.1769 2022/10/15 07:31:25 - mmengine - INFO - Epoch(train) [77][840/940] lr: 1.0000e-03 eta: 3:33:11 time: 0.5817 data_time: 0.0312 memory: 33630 grad_norm: 4.7554 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2492 loss: 1.2492 2022/10/15 07:31:36 - mmengine - INFO - Epoch(train) [77][860/940] lr: 1.0000e-03 eta: 3:33:00 time: 0.5741 data_time: 0.0331 memory: 33630 grad_norm: 4.9044 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1831 loss: 1.1831 2022/10/15 07:31:48 - mmengine - INFO - Epoch(train) [77][880/940] lr: 1.0000e-03 eta: 3:32:48 time: 0.5819 data_time: 0.0387 memory: 33630 grad_norm: 4.7613 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1739 loss: 1.1739 2022/10/15 07:32:00 - mmengine - INFO - Epoch(train) [77][900/940] lr: 1.0000e-03 eta: 3:32:36 time: 0.5796 data_time: 0.0350 memory: 33630 grad_norm: 4.8164 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1082 loss: 1.1082 2022/10/15 07:32:11 - mmengine - INFO - Epoch(train) [77][920/940] lr: 1.0000e-03 eta: 3:32:24 time: 0.5835 data_time: 0.0406 memory: 33630 grad_norm: 4.8264 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2088 loss: 1.2088 2022/10/15 07:32:22 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 07:32:22 - mmengine - INFO - Epoch(train) [77][940/940] lr: 1.0000e-03 eta: 3:32:12 time: 0.5411 data_time: 0.0307 memory: 33630 grad_norm: 5.1167 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.3021 loss: 1.3021 2022/10/15 07:32:37 - mmengine - INFO - Epoch(val) [77][20/78] eta: 0:00:42 time: 0.7384 data_time: 0.5662 memory: 5967 2022/10/15 07:32:47 - mmengine - INFO - Epoch(val) [77][40/78] eta: 0:00:18 time: 0.4938 data_time: 0.3248 memory: 5967 2022/10/15 07:33:00 - mmengine - INFO - Epoch(val) [77][60/78] eta: 0:00:11 time: 0.6495 data_time: 0.4773 memory: 5967 2022/10/15 07:33:12 - mmengine - INFO - Epoch(val) [77][78/78] acc/top1: 0.6866 acc/top5: 0.8786 acc/mean1: 0.6865 2022/10/15 07:33:28 - mmengine - INFO - Epoch(train) [78][20/940] lr: 1.0000e-03 eta: 3:32:02 time: 0.8140 data_time: 0.2607 memory: 33630 grad_norm: 4.7478 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3424 loss: 1.3424 2022/10/15 07:33:40 - mmengine - INFO - Epoch(train) [78][40/940] lr: 1.0000e-03 eta: 3:31:50 time: 0.5842 data_time: 0.0368 memory: 33630 grad_norm: 4.7373 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2042 loss: 1.2042 2022/10/15 07:33:51 - mmengine - INFO - Epoch(train) [78][60/940] lr: 1.0000e-03 eta: 3:31:38 time: 0.5885 data_time: 0.0389 memory: 33630 grad_norm: 4.8190 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2787 loss: 1.2787 2022/10/15 07:34:03 - mmengine - INFO - Epoch(train) [78][80/940] lr: 1.0000e-03 eta: 3:31:26 time: 0.6040 data_time: 0.0341 memory: 33630 grad_norm: 4.7341 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1525 loss: 1.1525 2022/10/15 07:34:15 - mmengine - INFO - Epoch(train) [78][100/940] lr: 1.0000e-03 eta: 3:31:15 time: 0.5856 data_time: 0.0349 memory: 33630 grad_norm: 4.7546 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2153 loss: 1.2153 2022/10/15 07:34:27 - mmengine - INFO - Epoch(train) [78][120/940] lr: 1.0000e-03 eta: 3:31:03 time: 0.5861 data_time: 0.0344 memory: 33630 grad_norm: 4.7850 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2563 loss: 1.2563 2022/10/15 07:34:39 - mmengine - INFO - Epoch(train) [78][140/940] lr: 1.0000e-03 eta: 3:30:51 time: 0.5902 data_time: 0.0395 memory: 33630 grad_norm: 4.7993 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2867 loss: 1.2867 2022/10/15 07:34:50 - mmengine - INFO - Epoch(train) [78][160/940] lr: 1.0000e-03 eta: 3:30:39 time: 0.5879 data_time: 0.0316 memory: 33630 grad_norm: 4.7233 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1232 loss: 1.1232 2022/10/15 07:35:02 - mmengine - INFO - Epoch(train) [78][180/940] lr: 1.0000e-03 eta: 3:30:27 time: 0.5814 data_time: 0.0360 memory: 33630 grad_norm: 4.8762 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3018 loss: 1.3018 2022/10/15 07:35:14 - mmengine - INFO - Epoch(train) [78][200/940] lr: 1.0000e-03 eta: 3:30:16 time: 0.5841 data_time: 0.0300 memory: 33630 grad_norm: 4.7604 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2025 loss: 1.2025 2022/10/15 07:35:25 - mmengine - INFO - Epoch(train) [78][220/940] lr: 1.0000e-03 eta: 3:30:04 time: 0.5760 data_time: 0.0358 memory: 33630 grad_norm: 4.7812 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0550 loss: 1.0550 2022/10/15 07:35:37 - mmengine - INFO - Epoch(train) [78][240/940] lr: 1.0000e-03 eta: 3:29:52 time: 0.5743 data_time: 0.0329 memory: 33630 grad_norm: 4.7743 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0807 loss: 1.0807 2022/10/15 07:35:48 - mmengine - INFO - Epoch(train) [78][260/940] lr: 1.0000e-03 eta: 3:29:40 time: 0.5803 data_time: 0.0316 memory: 33630 grad_norm: 4.8152 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2175 loss: 1.2175 2022/10/15 07:36:00 - mmengine - INFO - Epoch(train) [78][280/940] lr: 1.0000e-03 eta: 3:29:28 time: 0.5712 data_time: 0.0312 memory: 33630 grad_norm: 4.7439 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1291 loss: 1.1291 2022/10/15 07:36:11 - mmengine - INFO - Epoch(train) [78][300/940] lr: 1.0000e-03 eta: 3:29:16 time: 0.5834 data_time: 0.0354 memory: 33630 grad_norm: 4.8523 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2001 loss: 1.2001 2022/10/15 07:36:23 - mmengine - INFO - Epoch(train) [78][320/940] lr: 1.0000e-03 eta: 3:29:04 time: 0.5785 data_time: 0.0366 memory: 33630 grad_norm: 4.7899 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.1848 loss: 1.1848 2022/10/15 07:36:35 - mmengine - INFO - Epoch(train) [78][340/940] lr: 1.0000e-03 eta: 3:28:53 time: 0.5776 data_time: 0.0414 memory: 33630 grad_norm: 4.7334 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2058 loss: 1.2058 2022/10/15 07:36:46 - mmengine - INFO - Epoch(train) [78][360/940] lr: 1.0000e-03 eta: 3:28:41 time: 0.5881 data_time: 0.0361 memory: 33630 grad_norm: 4.6727 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1971 loss: 1.1971 2022/10/15 07:36:58 - mmengine - INFO - Epoch(train) [78][380/940] lr: 1.0000e-03 eta: 3:28:29 time: 0.5875 data_time: 0.0336 memory: 33630 grad_norm: 4.8135 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1573 loss: 1.1573 2022/10/15 07:37:10 - mmengine - INFO - Epoch(train) [78][400/940] lr: 1.0000e-03 eta: 3:28:17 time: 0.5778 data_time: 0.0363 memory: 33630 grad_norm: 4.7837 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3188 loss: 1.3188 2022/10/15 07:37:21 - mmengine - INFO - Epoch(train) [78][420/940] lr: 1.0000e-03 eta: 3:28:05 time: 0.5830 data_time: 0.0406 memory: 33630 grad_norm: 4.7859 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1260 loss: 1.1260 2022/10/15 07:37:33 - mmengine - INFO - Epoch(train) [78][440/940] lr: 1.0000e-03 eta: 3:27:54 time: 0.5775 data_time: 0.0424 memory: 33630 grad_norm: 4.7030 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.0649 loss: 1.0649 2022/10/15 07:37:45 - mmengine - INFO - Epoch(train) [78][460/940] lr: 1.0000e-03 eta: 3:27:42 time: 0.5856 data_time: 0.0423 memory: 33630 grad_norm: 4.6825 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.1616 loss: 1.1616 2022/10/15 07:37:57 - mmengine - INFO - Epoch(train) [78][480/940] lr: 1.0000e-03 eta: 3:27:30 time: 0.5976 data_time: 0.0311 memory: 33630 grad_norm: 4.8516 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0890 loss: 1.0890 2022/10/15 07:38:08 - mmengine - INFO - Epoch(train) [78][500/940] lr: 1.0000e-03 eta: 3:27:18 time: 0.5856 data_time: 0.0407 memory: 33630 grad_norm: 4.8413 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2134 loss: 1.2134 2022/10/15 07:38:20 - mmengine - INFO - Epoch(train) [78][520/940] lr: 1.0000e-03 eta: 3:27:06 time: 0.5747 data_time: 0.0315 memory: 33630 grad_norm: 4.8005 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.1958 loss: 1.1958 2022/10/15 07:38:31 - mmengine - INFO - Epoch(train) [78][540/940] lr: 1.0000e-03 eta: 3:26:55 time: 0.5737 data_time: 0.0332 memory: 33630 grad_norm: 4.7573 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2473 loss: 1.2473 2022/10/15 07:38:43 - mmengine - INFO - Epoch(train) [78][560/940] lr: 1.0000e-03 eta: 3:26:43 time: 0.5762 data_time: 0.0378 memory: 33630 grad_norm: 4.7104 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0740 loss: 1.0740 2022/10/15 07:38:54 - mmengine - INFO - Epoch(train) [78][580/940] lr: 1.0000e-03 eta: 3:26:31 time: 0.5847 data_time: 0.0429 memory: 33630 grad_norm: 4.7305 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2771 loss: 1.2771 2022/10/15 07:39:06 - mmengine - INFO - Epoch(train) [78][600/940] lr: 1.0000e-03 eta: 3:26:19 time: 0.5878 data_time: 0.0376 memory: 33630 grad_norm: 4.7656 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.2251 loss: 1.2251 2022/10/15 07:39:18 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 07:39:18 - mmengine - INFO - Epoch(train) [78][620/940] lr: 1.0000e-03 eta: 3:26:07 time: 0.5864 data_time: 0.0319 memory: 33630 grad_norm: 4.8389 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2274 loss: 1.2274 2022/10/15 07:39:30 - mmengine - INFO - Epoch(train) [78][640/940] lr: 1.0000e-03 eta: 3:25:55 time: 0.5793 data_time: 0.0326 memory: 33630 grad_norm: 4.7754 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2641 loss: 1.2641 2022/10/15 07:39:41 - mmengine - INFO - Epoch(train) [78][660/940] lr: 1.0000e-03 eta: 3:25:44 time: 0.5823 data_time: 0.0353 memory: 33630 grad_norm: 4.8095 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1332 loss: 1.1332 2022/10/15 07:39:53 - mmengine - INFO - Epoch(train) [78][680/940] lr: 1.0000e-03 eta: 3:25:32 time: 0.5715 data_time: 0.0378 memory: 33630 grad_norm: 4.7809 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2372 loss: 1.2372 2022/10/15 07:40:04 - mmengine - INFO - Epoch(train) [78][700/940] lr: 1.0000e-03 eta: 3:25:20 time: 0.5711 data_time: 0.0332 memory: 33630 grad_norm: 4.7826 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2055 loss: 1.2055 2022/10/15 07:40:16 - mmengine - INFO - Epoch(train) [78][720/940] lr: 1.0000e-03 eta: 3:25:08 time: 0.5927 data_time: 0.0363 memory: 33630 grad_norm: 4.8183 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2833 loss: 1.2833 2022/10/15 07:40:28 - mmengine - INFO - Epoch(train) [78][740/940] lr: 1.0000e-03 eta: 3:24:56 time: 0.5809 data_time: 0.0332 memory: 33630 grad_norm: 4.6711 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1029 loss: 1.1029 2022/10/15 07:40:39 - mmengine - INFO - Epoch(train) [78][760/940] lr: 1.0000e-03 eta: 3:24:44 time: 0.5828 data_time: 0.0398 memory: 33630 grad_norm: 4.8828 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2976 loss: 1.2976 2022/10/15 07:40:51 - mmengine - INFO - Epoch(train) [78][780/940] lr: 1.0000e-03 eta: 3:24:33 time: 0.5784 data_time: 0.0403 memory: 33630 grad_norm: 4.7817 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1436 loss: 1.1436 2022/10/15 07:41:03 - mmengine - INFO - Epoch(train) [78][800/940] lr: 1.0000e-03 eta: 3:24:21 time: 0.5923 data_time: 0.0419 memory: 33630 grad_norm: 4.7695 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0916 loss: 1.0916 2022/10/15 07:41:14 - mmengine - INFO - Epoch(train) [78][820/940] lr: 1.0000e-03 eta: 3:24:09 time: 0.5801 data_time: 0.0372 memory: 33630 grad_norm: 4.7656 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.0871 loss: 1.0871 2022/10/15 07:41:26 - mmengine - INFO - Epoch(train) [78][840/940] lr: 1.0000e-03 eta: 3:23:57 time: 0.5894 data_time: 0.0376 memory: 33630 grad_norm: 4.7712 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1327 loss: 1.1327 2022/10/15 07:41:38 - mmengine - INFO - Epoch(train) [78][860/940] lr: 1.0000e-03 eta: 3:23:45 time: 0.5825 data_time: 0.0354 memory: 33630 grad_norm: 4.8195 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1413 loss: 1.1413 2022/10/15 07:41:49 - mmengine - INFO - Epoch(train) [78][880/940] lr: 1.0000e-03 eta: 3:23:34 time: 0.5817 data_time: 0.0366 memory: 33630 grad_norm: 4.7674 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2378 loss: 1.2378 2022/10/15 07:42:01 - mmengine - INFO - Epoch(train) [78][900/940] lr: 1.0000e-03 eta: 3:23:22 time: 0.5780 data_time: 0.0413 memory: 33630 grad_norm: 4.8136 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2650 loss: 1.2650 2022/10/15 07:42:13 - mmengine - INFO - Epoch(train) [78][920/940] lr: 1.0000e-03 eta: 3:23:10 time: 0.5866 data_time: 0.0371 memory: 33630 grad_norm: 4.8293 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2913 loss: 1.2913 2022/10/15 07:42:23 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 07:42:23 - mmengine - INFO - Epoch(train) [78][940/940] lr: 1.0000e-03 eta: 3:22:58 time: 0.5420 data_time: 0.0346 memory: 33630 grad_norm: 5.1014 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.2306 loss: 1.2306 2022/10/15 07:42:24 - mmengine - INFO - Saving checkpoint at 78 epochs 2022/10/15 07:42:39 - mmengine - INFO - Epoch(val) [78][20/78] eta: 0:00:41 time: 0.7116 data_time: 0.5404 memory: 5967 2022/10/15 07:42:49 - mmengine - INFO - Epoch(val) [78][40/78] eta: 0:00:19 time: 0.5009 data_time: 0.3308 memory: 5967 2022/10/15 07:43:02 - mmengine - INFO - Epoch(val) [78][60/78] eta: 0:00:12 time: 0.6732 data_time: 0.5016 memory: 5967 2022/10/15 07:43:13 - mmengine - INFO - Epoch(val) [78][78/78] acc/top1: 0.6852 acc/top5: 0.8774 acc/mean1: 0.6851 2022/10/15 07:43:30 - mmengine - INFO - Epoch(train) [79][20/940] lr: 1.0000e-03 eta: 3:22:48 time: 0.8458 data_time: 0.2328 memory: 33630 grad_norm: 4.8622 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2316 loss: 1.2316 2022/10/15 07:43:41 - mmengine - INFO - Epoch(train) [79][40/940] lr: 1.0000e-03 eta: 3:22:36 time: 0.5814 data_time: 0.0331 memory: 33630 grad_norm: 4.7510 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1548 loss: 1.1548 2022/10/15 07:43:53 - mmengine - INFO - Epoch(train) [79][60/940] lr: 1.0000e-03 eta: 3:22:24 time: 0.5987 data_time: 0.0351 memory: 33630 grad_norm: 4.7610 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1991 loss: 1.1991 2022/10/15 07:44:05 - mmengine - INFO - Epoch(train) [79][80/940] lr: 1.0000e-03 eta: 3:22:12 time: 0.5898 data_time: 0.0331 memory: 33630 grad_norm: 4.7286 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1663 loss: 1.1663 2022/10/15 07:44:17 - mmengine - INFO - Epoch(train) [79][100/940] lr: 1.0000e-03 eta: 3:22:01 time: 0.5906 data_time: 0.0374 memory: 33630 grad_norm: 4.8581 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1996 loss: 1.1996 2022/10/15 07:44:29 - mmengine - INFO - Epoch(train) [79][120/940] lr: 1.0000e-03 eta: 3:21:49 time: 0.5886 data_time: 0.0337 memory: 33630 grad_norm: 4.7806 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1149 loss: 1.1149 2022/10/15 07:44:40 - mmengine - INFO - Epoch(train) [79][140/940] lr: 1.0000e-03 eta: 3:21:37 time: 0.5833 data_time: 0.0381 memory: 33630 grad_norm: 4.8467 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1603 loss: 1.1603 2022/10/15 07:44:52 - mmengine - INFO - Epoch(train) [79][160/940] lr: 1.0000e-03 eta: 3:21:25 time: 0.5848 data_time: 0.0365 memory: 33630 grad_norm: 4.7654 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.1728 loss: 1.1728 2022/10/15 07:45:04 - mmengine - INFO - Epoch(train) [79][180/940] lr: 1.0000e-03 eta: 3:21:13 time: 0.5889 data_time: 0.0395 memory: 33630 grad_norm: 4.7974 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1525 loss: 1.1525 2022/10/15 07:45:16 - mmengine - INFO - Epoch(train) [79][200/940] lr: 1.0000e-03 eta: 3:21:02 time: 0.5842 data_time: 0.0384 memory: 33630 grad_norm: 4.8083 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1378 loss: 1.1378 2022/10/15 07:45:27 - mmengine - INFO - Epoch(train) [79][220/940] lr: 1.0000e-03 eta: 3:20:50 time: 0.5788 data_time: 0.0325 memory: 33630 grad_norm: 4.7404 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2019 loss: 1.2019 2022/10/15 07:45:39 - mmengine - INFO - Epoch(train) [79][240/940] lr: 1.0000e-03 eta: 3:20:38 time: 0.5769 data_time: 0.0347 memory: 33630 grad_norm: 4.8024 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1727 loss: 1.1727 2022/10/15 07:45:50 - mmengine - INFO - Epoch(train) [79][260/940] lr: 1.0000e-03 eta: 3:20:26 time: 0.5853 data_time: 0.0340 memory: 33630 grad_norm: 4.8334 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1493 loss: 1.1493 2022/10/15 07:46:02 - mmengine - INFO - Epoch(train) [79][280/940] lr: 1.0000e-03 eta: 3:20:14 time: 0.5804 data_time: 0.0331 memory: 33630 grad_norm: 4.8825 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2712 loss: 1.2712 2022/10/15 07:46:13 - mmengine - INFO - Epoch(train) [79][300/940] lr: 1.0000e-03 eta: 3:20:02 time: 0.5764 data_time: 0.0370 memory: 33630 grad_norm: 4.7670 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1571 loss: 1.1571 2022/10/15 07:46:25 - mmengine - INFO - Epoch(train) [79][320/940] lr: 1.0000e-03 eta: 3:19:51 time: 0.5751 data_time: 0.0388 memory: 33630 grad_norm: 4.8298 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.1305 loss: 1.1305 2022/10/15 07:46:37 - mmengine - INFO - Epoch(train) [79][340/940] lr: 1.0000e-03 eta: 3:19:39 time: 0.5793 data_time: 0.0383 memory: 33630 grad_norm: 4.8331 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.1458 loss: 1.1458 2022/10/15 07:46:48 - mmengine - INFO - Epoch(train) [79][360/940] lr: 1.0000e-03 eta: 3:19:27 time: 0.5808 data_time: 0.0320 memory: 33630 grad_norm: 4.8201 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1656 loss: 1.1656 2022/10/15 07:47:00 - mmengine - INFO - Epoch(train) [79][380/940] lr: 1.0000e-03 eta: 3:19:15 time: 0.5776 data_time: 0.0379 memory: 33630 grad_norm: 4.7376 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1787 loss: 1.1787 2022/10/15 07:47:11 - mmengine - INFO - Epoch(train) [79][400/940] lr: 1.0000e-03 eta: 3:19:03 time: 0.5865 data_time: 0.0353 memory: 33630 grad_norm: 4.8733 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.1420 loss: 1.1420 2022/10/15 07:47:23 - mmengine - INFO - Epoch(train) [79][420/940] lr: 1.0000e-03 eta: 3:18:51 time: 0.5890 data_time: 0.0326 memory: 33630 grad_norm: 4.8323 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3004 loss: 1.3004 2022/10/15 07:47:35 - mmengine - INFO - Epoch(train) [79][440/940] lr: 1.0000e-03 eta: 3:18:40 time: 0.5733 data_time: 0.0421 memory: 33630 grad_norm: 4.8009 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2229 loss: 1.2229 2022/10/15 07:47:46 - mmengine - INFO - Epoch(train) [79][460/940] lr: 1.0000e-03 eta: 3:18:28 time: 0.5790 data_time: 0.0343 memory: 33630 grad_norm: 4.7060 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0692 loss: 1.0692 2022/10/15 07:47:58 - mmengine - INFO - Epoch(train) [79][480/940] lr: 1.0000e-03 eta: 3:18:16 time: 0.5888 data_time: 0.0393 memory: 33630 grad_norm: 4.8774 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2177 loss: 1.2177 2022/10/15 07:48:10 - mmengine - INFO - Epoch(train) [79][500/940] lr: 1.0000e-03 eta: 3:18:04 time: 0.5866 data_time: 0.0348 memory: 33630 grad_norm: 4.9115 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2245 loss: 1.2245 2022/10/15 07:48:21 - mmengine - INFO - Epoch(train) [79][520/940] lr: 1.0000e-03 eta: 3:17:52 time: 0.5760 data_time: 0.0331 memory: 33630 grad_norm: 4.8086 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2218 loss: 1.2218 2022/10/15 07:48:33 - mmengine - INFO - Epoch(train) [79][540/940] lr: 1.0000e-03 eta: 3:17:41 time: 0.5920 data_time: 0.0351 memory: 33630 grad_norm: 4.8159 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2526 loss: 1.2526 2022/10/15 07:48:45 - mmengine - INFO - Epoch(train) [79][560/940] lr: 1.0000e-03 eta: 3:17:29 time: 0.5834 data_time: 0.0380 memory: 33630 grad_norm: 4.7909 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1645 loss: 1.1645 2022/10/15 07:48:57 - mmengine - INFO - Epoch(train) [79][580/940] lr: 1.0000e-03 eta: 3:17:17 time: 0.5935 data_time: 0.0493 memory: 33630 grad_norm: 4.7377 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3270 loss: 1.3270 2022/10/15 07:49:08 - mmengine - INFO - Epoch(train) [79][600/940] lr: 1.0000e-03 eta: 3:17:05 time: 0.5743 data_time: 0.0369 memory: 33630 grad_norm: 4.6618 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2524 loss: 1.2524 2022/10/15 07:49:20 - mmengine - INFO - Epoch(train) [79][620/940] lr: 1.0000e-03 eta: 3:16:53 time: 0.5774 data_time: 0.0364 memory: 33630 grad_norm: 4.8637 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.2201 loss: 1.2201 2022/10/15 07:49:31 - mmengine - INFO - Epoch(train) [79][640/940] lr: 1.0000e-03 eta: 3:16:41 time: 0.5793 data_time: 0.0359 memory: 33630 grad_norm: 4.8431 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1918 loss: 1.1918 2022/10/15 07:49:43 - mmengine - INFO - Epoch(train) [79][660/940] lr: 1.0000e-03 eta: 3:16:30 time: 0.5819 data_time: 0.0370 memory: 33630 grad_norm: 4.8327 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2612 loss: 1.2612 2022/10/15 07:49:55 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 07:49:55 - mmengine - INFO - Epoch(train) [79][680/940] lr: 1.0000e-03 eta: 3:16:18 time: 0.5891 data_time: 0.0374 memory: 33630 grad_norm: 4.7013 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0800 loss: 1.0800 2022/10/15 07:50:06 - mmengine - INFO - Epoch(train) [79][700/940] lr: 1.0000e-03 eta: 3:16:06 time: 0.5795 data_time: 0.0338 memory: 33630 grad_norm: 4.7836 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2015 loss: 1.2015 2022/10/15 07:50:18 - mmengine - INFO - Epoch(train) [79][720/940] lr: 1.0000e-03 eta: 3:15:54 time: 0.5882 data_time: 0.0430 memory: 33630 grad_norm: 4.8569 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1492 loss: 1.1492 2022/10/15 07:50:30 - mmengine - INFO - Epoch(train) [79][740/940] lr: 1.0000e-03 eta: 3:15:42 time: 0.5821 data_time: 0.0377 memory: 33630 grad_norm: 4.8925 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2487 loss: 1.2487 2022/10/15 07:50:42 - mmengine - INFO - Epoch(train) [79][760/940] lr: 1.0000e-03 eta: 3:15:31 time: 0.5902 data_time: 0.0317 memory: 33630 grad_norm: 4.8226 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2573 loss: 1.2573 2022/10/15 07:50:53 - mmengine - INFO - Epoch(train) [79][780/940] lr: 1.0000e-03 eta: 3:15:19 time: 0.5774 data_time: 0.0510 memory: 33630 grad_norm: 4.8797 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.1065 loss: 1.1065 2022/10/15 07:51:05 - mmengine - INFO - Epoch(train) [79][800/940] lr: 1.0000e-03 eta: 3:15:07 time: 0.5839 data_time: 0.0424 memory: 33630 grad_norm: 4.7505 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1402 loss: 1.1402 2022/10/15 07:51:16 - mmengine - INFO - Epoch(train) [79][820/940] lr: 1.0000e-03 eta: 3:14:55 time: 0.5833 data_time: 0.0422 memory: 33630 grad_norm: 4.9308 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3072 loss: 1.3072 2022/10/15 07:51:28 - mmengine - INFO - Epoch(train) [79][840/940] lr: 1.0000e-03 eta: 3:14:43 time: 0.5904 data_time: 0.0443 memory: 33630 grad_norm: 4.7743 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1610 loss: 1.1610 2022/10/15 07:51:40 - mmengine - INFO - Epoch(train) [79][860/940] lr: 1.0000e-03 eta: 3:14:32 time: 0.5808 data_time: 0.0409 memory: 33630 grad_norm: 4.8229 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1856 loss: 1.1856 2022/10/15 07:51:52 - mmengine - INFO - Epoch(train) [79][880/940] lr: 1.0000e-03 eta: 3:14:20 time: 0.5836 data_time: 0.0403 memory: 33630 grad_norm: 4.6892 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1601 loss: 1.1601 2022/10/15 07:52:03 - mmengine - INFO - Epoch(train) [79][900/940] lr: 1.0000e-03 eta: 3:14:08 time: 0.5892 data_time: 0.0383 memory: 33630 grad_norm: 4.6650 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1909 loss: 1.1909 2022/10/15 07:52:15 - mmengine - INFO - Epoch(train) [79][920/940] lr: 1.0000e-03 eta: 3:13:56 time: 0.5800 data_time: 0.0464 memory: 33630 grad_norm: 4.9292 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.1838 loss: 1.1838 2022/10/15 07:52:26 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 07:52:26 - mmengine - INFO - Epoch(train) [79][940/940] lr: 1.0000e-03 eta: 3:13:44 time: 0.5452 data_time: 0.0309 memory: 33630 grad_norm: 5.0562 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.2123 loss: 1.2123 2022/10/15 07:52:40 - mmengine - INFO - Epoch(val) [79][20/78] eta: 0:00:40 time: 0.7067 data_time: 0.5371 memory: 5967 2022/10/15 07:52:50 - mmengine - INFO - Epoch(val) [79][40/78] eta: 0:00:19 time: 0.5038 data_time: 0.3364 memory: 5967 2022/10/15 07:53:03 - mmengine - INFO - Epoch(val) [79][60/78] eta: 0:00:11 time: 0.6503 data_time: 0.4807 memory: 5967 2022/10/15 07:53:15 - mmengine - INFO - Epoch(val) [79][78/78] acc/top1: 0.6869 acc/top5: 0.8760 acc/mean1: 0.6867 2022/10/15 07:53:31 - mmengine - INFO - Epoch(train) [80][20/940] lr: 1.0000e-03 eta: 3:13:34 time: 0.8169 data_time: 0.2347 memory: 33630 grad_norm: 4.7653 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2500 loss: 1.2500 2022/10/15 07:53:43 - mmengine - INFO - Epoch(train) [80][40/940] lr: 1.0000e-03 eta: 3:13:22 time: 0.5806 data_time: 0.0382 memory: 33630 grad_norm: 4.8798 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.0990 loss: 1.0990 2022/10/15 07:53:55 - mmengine - INFO - Epoch(train) [80][60/940] lr: 1.0000e-03 eta: 3:13:10 time: 0.5877 data_time: 0.0376 memory: 33630 grad_norm: 4.9363 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1384 loss: 1.1384 2022/10/15 07:54:07 - mmengine - INFO - Epoch(train) [80][80/940] lr: 1.0000e-03 eta: 3:12:58 time: 0.5913 data_time: 0.0322 memory: 33630 grad_norm: 4.7941 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.2857 loss: 1.2857 2022/10/15 07:54:18 - mmengine - INFO - Epoch(train) [80][100/940] lr: 1.0000e-03 eta: 3:12:47 time: 0.5885 data_time: 0.0369 memory: 33630 grad_norm: 4.7852 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1176 loss: 1.1176 2022/10/15 07:54:30 - mmengine - INFO - Epoch(train) [80][120/940] lr: 1.0000e-03 eta: 3:12:35 time: 0.5768 data_time: 0.0413 memory: 33630 grad_norm: 4.8428 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2378 loss: 1.2378 2022/10/15 07:54:41 - mmengine - INFO - Epoch(train) [80][140/940] lr: 1.0000e-03 eta: 3:12:23 time: 0.5775 data_time: 0.0307 memory: 33630 grad_norm: 4.7119 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1544 loss: 1.1544 2022/10/15 07:54:53 - mmengine - INFO - Epoch(train) [80][160/940] lr: 1.0000e-03 eta: 3:12:11 time: 0.5779 data_time: 0.0396 memory: 33630 grad_norm: 4.8118 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1608 loss: 1.1608 2022/10/15 07:55:05 - mmengine - INFO - Epoch(train) [80][180/940] lr: 1.0000e-03 eta: 3:11:59 time: 0.5820 data_time: 0.0405 memory: 33630 grad_norm: 4.9175 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.1354 loss: 1.1354 2022/10/15 07:55:16 - mmengine - INFO - Epoch(train) [80][200/940] lr: 1.0000e-03 eta: 3:11:47 time: 0.5724 data_time: 0.0367 memory: 33630 grad_norm: 4.7574 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1740 loss: 1.1740 2022/10/15 07:55:28 - mmengine - INFO - Epoch(train) [80][220/940] lr: 1.0000e-03 eta: 3:11:36 time: 0.5838 data_time: 0.0560 memory: 33630 grad_norm: 4.7937 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2201 loss: 1.2201 2022/10/15 07:55:39 - mmengine - INFO - Epoch(train) [80][240/940] lr: 1.0000e-03 eta: 3:11:24 time: 0.5784 data_time: 0.0362 memory: 33630 grad_norm: 4.7846 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1625 loss: 1.1625 2022/10/15 07:55:51 - mmengine - INFO - Epoch(train) [80][260/940] lr: 1.0000e-03 eta: 3:11:12 time: 0.5843 data_time: 0.0365 memory: 33630 grad_norm: 4.8357 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2286 loss: 1.2286 2022/10/15 07:56:03 - mmengine - INFO - Epoch(train) [80][280/940] lr: 1.0000e-03 eta: 3:11:00 time: 0.5858 data_time: 0.0315 memory: 33630 grad_norm: 4.8174 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1794 loss: 1.1794 2022/10/15 07:56:14 - mmengine - INFO - Epoch(train) [80][300/940] lr: 1.0000e-03 eta: 3:10:48 time: 0.5829 data_time: 0.0315 memory: 33630 grad_norm: 4.8530 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1395 loss: 1.1395 2022/10/15 07:56:26 - mmengine - INFO - Epoch(train) [80][320/940] lr: 1.0000e-03 eta: 3:10:36 time: 0.5859 data_time: 0.0349 memory: 33630 grad_norm: 4.8385 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.2480 loss: 1.2480 2022/10/15 07:56:38 - mmengine - INFO - Epoch(train) [80][340/940] lr: 1.0000e-03 eta: 3:10:25 time: 0.5875 data_time: 0.0402 memory: 33630 grad_norm: 4.8587 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1482 loss: 1.1482 2022/10/15 07:56:50 - mmengine - INFO - Epoch(train) [80][360/940] lr: 1.0000e-03 eta: 3:10:13 time: 0.5888 data_time: 0.0331 memory: 33630 grad_norm: 4.7419 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2845 loss: 1.2845 2022/10/15 07:57:01 - mmengine - INFO - Epoch(train) [80][380/940] lr: 1.0000e-03 eta: 3:10:01 time: 0.5779 data_time: 0.0374 memory: 33630 grad_norm: 4.8263 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2257 loss: 1.2257 2022/10/15 07:57:13 - mmengine - INFO - Epoch(train) [80][400/940] lr: 1.0000e-03 eta: 3:09:49 time: 0.5857 data_time: 0.0429 memory: 33630 grad_norm: 4.8894 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.1116 loss: 1.1116 2022/10/15 07:57:25 - mmengine - INFO - Epoch(train) [80][420/940] lr: 1.0000e-03 eta: 3:09:37 time: 0.5797 data_time: 0.0372 memory: 33630 grad_norm: 4.7906 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0460 loss: 1.0460 2022/10/15 07:57:36 - mmengine - INFO - Epoch(train) [80][440/940] lr: 1.0000e-03 eta: 3:09:26 time: 0.5880 data_time: 0.0391 memory: 33630 grad_norm: 4.9076 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1883 loss: 1.1883 2022/10/15 07:57:48 - mmengine - INFO - Epoch(train) [80][460/940] lr: 1.0000e-03 eta: 3:09:14 time: 0.5829 data_time: 0.0356 memory: 33630 grad_norm: 4.9089 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2895 loss: 1.2895 2022/10/15 07:58:00 - mmengine - INFO - Epoch(train) [80][480/940] lr: 1.0000e-03 eta: 3:09:02 time: 0.5919 data_time: 0.0375 memory: 33630 grad_norm: 4.7145 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0798 loss: 1.0798 2022/10/15 07:58:12 - mmengine - INFO - Epoch(train) [80][500/940] lr: 1.0000e-03 eta: 3:08:50 time: 0.5876 data_time: 0.0428 memory: 33630 grad_norm: 4.9489 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3585 loss: 1.3585 2022/10/15 07:58:23 - mmengine - INFO - Epoch(train) [80][520/940] lr: 1.0000e-03 eta: 3:08:39 time: 0.5872 data_time: 0.0390 memory: 33630 grad_norm: 4.8722 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2074 loss: 1.2074 2022/10/15 07:58:35 - mmengine - INFO - Epoch(train) [80][540/940] lr: 1.0000e-03 eta: 3:08:27 time: 0.5754 data_time: 0.0378 memory: 33630 grad_norm: 4.9335 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.2771 loss: 1.2771 2022/10/15 07:58:47 - mmengine - INFO - Epoch(train) [80][560/940] lr: 1.0000e-03 eta: 3:08:15 time: 0.5876 data_time: 0.0322 memory: 33630 grad_norm: 4.8134 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.1891 loss: 1.1891 2022/10/15 07:58:58 - mmengine - INFO - Epoch(train) [80][580/940] lr: 1.0000e-03 eta: 3:08:03 time: 0.5860 data_time: 0.0360 memory: 33630 grad_norm: 4.8245 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.1633 loss: 1.1633 2022/10/15 07:59:10 - mmengine - INFO - Epoch(train) [80][600/940] lr: 1.0000e-03 eta: 3:07:51 time: 0.5896 data_time: 0.0322 memory: 33630 grad_norm: 4.9122 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1565 loss: 1.1565 2022/10/15 07:59:22 - mmengine - INFO - Epoch(train) [80][620/940] lr: 1.0000e-03 eta: 3:07:39 time: 0.5749 data_time: 0.0338 memory: 33630 grad_norm: 4.7975 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1380 loss: 1.1380 2022/10/15 07:59:33 - mmengine - INFO - Epoch(train) [80][640/940] lr: 1.0000e-03 eta: 3:07:28 time: 0.5765 data_time: 0.0320 memory: 33630 grad_norm: 4.8305 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1401 loss: 1.1401 2022/10/15 07:59:45 - mmengine - INFO - Epoch(train) [80][660/940] lr: 1.0000e-03 eta: 3:07:16 time: 0.5951 data_time: 0.0369 memory: 33630 grad_norm: 4.7759 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2069 loss: 1.2069 2022/10/15 07:59:57 - mmengine - INFO - Epoch(train) [80][680/940] lr: 1.0000e-03 eta: 3:07:04 time: 0.5833 data_time: 0.0395 memory: 33630 grad_norm: 4.8255 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3643 loss: 1.3643 2022/10/15 08:00:09 - mmengine - INFO - Epoch(train) [80][700/940] lr: 1.0000e-03 eta: 3:06:52 time: 0.5940 data_time: 0.0409 memory: 33630 grad_norm: 4.8039 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1158 loss: 1.1158 2022/10/15 08:00:20 - mmengine - INFO - Epoch(train) [80][720/940] lr: 1.0000e-03 eta: 3:06:41 time: 0.5848 data_time: 0.0380 memory: 33630 grad_norm: 4.7909 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2060 loss: 1.2060 2022/10/15 08:00:32 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 08:00:32 - mmengine - INFO - Epoch(train) [80][740/940] lr: 1.0000e-03 eta: 3:06:29 time: 0.5803 data_time: 0.0338 memory: 33630 grad_norm: 4.8167 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1386 loss: 1.1386 2022/10/15 08:00:44 - mmengine - INFO - Epoch(train) [80][760/940] lr: 1.0000e-03 eta: 3:06:17 time: 0.5830 data_time: 0.0436 memory: 33630 grad_norm: 4.7574 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0669 loss: 1.0669 2022/10/15 08:00:55 - mmengine - INFO - Epoch(train) [80][780/940] lr: 1.0000e-03 eta: 3:06:05 time: 0.5824 data_time: 0.0359 memory: 33630 grad_norm: 4.8823 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1467 loss: 1.1467 2022/10/15 08:01:07 - mmengine - INFO - Epoch(train) [80][800/940] lr: 1.0000e-03 eta: 3:05:53 time: 0.5716 data_time: 0.0392 memory: 33630 grad_norm: 4.8619 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1648 loss: 1.1648 2022/10/15 08:01:18 - mmengine - INFO - Epoch(train) [80][820/940] lr: 1.0000e-03 eta: 3:05:41 time: 0.5762 data_time: 0.0372 memory: 33630 grad_norm: 4.7967 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1927 loss: 1.1927 2022/10/15 08:01:30 - mmengine - INFO - Epoch(train) [80][840/940] lr: 1.0000e-03 eta: 3:05:30 time: 0.5880 data_time: 0.0351 memory: 33630 grad_norm: 4.8872 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1803 loss: 1.1803 2022/10/15 08:01:42 - mmengine - INFO - Epoch(train) [80][860/940] lr: 1.0000e-03 eta: 3:05:18 time: 0.5810 data_time: 0.0395 memory: 33630 grad_norm: 4.7849 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1779 loss: 1.1779 2022/10/15 08:01:53 - mmengine - INFO - Epoch(train) [80][880/940] lr: 1.0000e-03 eta: 3:05:06 time: 0.5697 data_time: 0.0340 memory: 33630 grad_norm: 4.8271 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2708 loss: 1.2708 2022/10/15 08:02:04 - mmengine - INFO - Epoch(train) [80][900/940] lr: 1.0000e-03 eta: 3:04:54 time: 0.5735 data_time: 0.0324 memory: 33630 grad_norm: 4.7570 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2515 loss: 1.2515 2022/10/15 08:02:16 - mmengine - INFO - Epoch(train) [80][920/940] lr: 1.0000e-03 eta: 3:04:42 time: 0.5828 data_time: 0.0396 memory: 33630 grad_norm: 4.8559 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2711 loss: 1.2711 2022/10/15 08:02:27 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 08:02:27 - mmengine - INFO - Epoch(train) [80][940/940] lr: 1.0000e-03 eta: 3:04:30 time: 0.5401 data_time: 0.0274 memory: 33630 grad_norm: 5.1655 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.1388 loss: 1.1388 2022/10/15 08:02:41 - mmengine - INFO - Epoch(val) [80][20/78] eta: 0:00:42 time: 0.7278 data_time: 0.5576 memory: 5967 2022/10/15 08:02:51 - mmengine - INFO - Epoch(val) [80][40/78] eta: 0:00:18 time: 0.4953 data_time: 0.3263 memory: 5967 2022/10/15 08:03:04 - mmengine - INFO - Epoch(val) [80][60/78] eta: 0:00:11 time: 0.6404 data_time: 0.4707 memory: 5967 2022/10/15 08:03:16 - mmengine - INFO - Epoch(val) [80][78/78] acc/top1: 0.6853 acc/top5: 0.8771 acc/mean1: 0.6852 2022/10/15 08:03:32 - mmengine - INFO - Epoch(train) [81][20/940] lr: 1.0000e-04 eta: 3:04:20 time: 0.8170 data_time: 0.2510 memory: 33630 grad_norm: 4.8614 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1906 loss: 1.1906 2022/10/15 08:03:44 - mmengine - INFO - Epoch(train) [81][40/940] lr: 1.0000e-04 eta: 3:04:08 time: 0.5738 data_time: 0.0330 memory: 33630 grad_norm: 4.8570 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0673 loss: 1.0673 2022/10/15 08:03:56 - mmengine - INFO - Epoch(train) [81][60/940] lr: 1.0000e-04 eta: 3:03:56 time: 0.6252 data_time: 0.0786 memory: 33630 grad_norm: 4.8725 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1916 loss: 1.1916 2022/10/15 08:04:08 - mmengine - INFO - Epoch(train) [81][80/940] lr: 1.0000e-04 eta: 3:03:44 time: 0.5909 data_time: 0.0318 memory: 33630 grad_norm: 4.8135 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1393 loss: 1.1393 2022/10/15 08:04:20 - mmengine - INFO - Epoch(train) [81][100/940] lr: 1.0000e-04 eta: 3:03:33 time: 0.5882 data_time: 0.0338 memory: 33630 grad_norm: 4.8342 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1777 loss: 1.1777 2022/10/15 08:04:32 - mmengine - INFO - Epoch(train) [81][120/940] lr: 1.0000e-04 eta: 3:03:21 time: 0.5813 data_time: 0.0374 memory: 33630 grad_norm: 4.7923 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1003 loss: 1.1003 2022/10/15 08:04:43 - mmengine - INFO - Epoch(train) [81][140/940] lr: 1.0000e-04 eta: 3:03:09 time: 0.5808 data_time: 0.0507 memory: 33630 grad_norm: 4.7476 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1975 loss: 1.1975 2022/10/15 08:04:55 - mmengine - INFO - Epoch(train) [81][160/940] lr: 1.0000e-04 eta: 3:02:57 time: 0.5793 data_time: 0.0327 memory: 33630 grad_norm: 4.8079 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.1885 loss: 1.1885 2022/10/15 08:05:07 - mmengine - INFO - Epoch(train) [81][180/940] lr: 1.0000e-04 eta: 3:02:45 time: 0.5897 data_time: 0.0465 memory: 33630 grad_norm: 4.7987 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2871 loss: 1.2871 2022/10/15 08:05:18 - mmengine - INFO - Epoch(train) [81][200/940] lr: 1.0000e-04 eta: 3:02:33 time: 0.5747 data_time: 0.0383 memory: 33630 grad_norm: 4.7585 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.2923 loss: 1.2923 2022/10/15 08:05:30 - mmengine - INFO - Epoch(train) [81][220/940] lr: 1.0000e-04 eta: 3:02:22 time: 0.5727 data_time: 0.0403 memory: 33630 grad_norm: 4.6510 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1113 loss: 1.1113 2022/10/15 08:05:41 - mmengine - INFO - Epoch(train) [81][240/940] lr: 1.0000e-04 eta: 3:02:10 time: 0.5898 data_time: 0.0375 memory: 33630 grad_norm: 4.7347 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1068 loss: 1.1068 2022/10/15 08:05:53 - mmengine - INFO - Epoch(train) [81][260/940] lr: 1.0000e-04 eta: 3:01:58 time: 0.5771 data_time: 0.0426 memory: 33630 grad_norm: 4.9063 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2428 loss: 1.2428 2022/10/15 08:06:05 - mmengine - INFO - Epoch(train) [81][280/940] lr: 1.0000e-04 eta: 3:01:46 time: 0.5892 data_time: 0.0495 memory: 33630 grad_norm: 4.8244 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2320 loss: 1.2320 2022/10/15 08:06:16 - mmengine - INFO - Epoch(train) [81][300/940] lr: 1.0000e-04 eta: 3:01:34 time: 0.5759 data_time: 0.0366 memory: 33630 grad_norm: 4.7817 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.2919 loss: 1.2919 2022/10/15 08:06:28 - mmengine - INFO - Epoch(train) [81][320/940] lr: 1.0000e-04 eta: 3:01:23 time: 0.5894 data_time: 0.0400 memory: 33630 grad_norm: 4.7122 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2188 loss: 1.2188 2022/10/15 08:06:40 - mmengine - INFO - Epoch(train) [81][340/940] lr: 1.0000e-04 eta: 3:01:11 time: 0.5815 data_time: 0.0430 memory: 33630 grad_norm: 4.8881 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1327 loss: 1.1327 2022/10/15 08:06:51 - mmengine - INFO - Epoch(train) [81][360/940] lr: 1.0000e-04 eta: 3:00:59 time: 0.5852 data_time: 0.0380 memory: 33630 grad_norm: 4.6980 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1651 loss: 1.1651 2022/10/15 08:07:03 - mmengine - INFO - Epoch(train) [81][380/940] lr: 1.0000e-04 eta: 3:00:47 time: 0.5755 data_time: 0.0360 memory: 33630 grad_norm: 4.8339 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2970 loss: 1.2970 2022/10/15 08:07:15 - mmengine - INFO - Epoch(train) [81][400/940] lr: 1.0000e-04 eta: 3:00:35 time: 0.5832 data_time: 0.0444 memory: 33630 grad_norm: 4.8302 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2516 loss: 1.2516 2022/10/15 08:07:26 - mmengine - INFO - Epoch(train) [81][420/940] lr: 1.0000e-04 eta: 3:00:23 time: 0.5698 data_time: 0.0331 memory: 33630 grad_norm: 4.7920 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.2226 loss: 1.2226 2022/10/15 08:07:38 - mmengine - INFO - Epoch(train) [81][440/940] lr: 1.0000e-04 eta: 3:00:12 time: 0.5861 data_time: 0.0345 memory: 33630 grad_norm: 4.7624 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1566 loss: 1.1566 2022/10/15 08:07:49 - mmengine - INFO - Epoch(train) [81][460/940] lr: 1.0000e-04 eta: 3:00:00 time: 0.5830 data_time: 0.0444 memory: 33630 grad_norm: 4.8183 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2917 loss: 1.2917 2022/10/15 08:08:01 - mmengine - INFO - Epoch(train) [81][480/940] lr: 1.0000e-04 eta: 2:59:48 time: 0.5860 data_time: 0.0441 memory: 33630 grad_norm: 4.8101 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.1014 loss: 1.1014 2022/10/15 08:08:13 - mmengine - INFO - Epoch(train) [81][500/940] lr: 1.0000e-04 eta: 2:59:36 time: 0.5851 data_time: 0.0412 memory: 33630 grad_norm: 4.8691 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2697 loss: 1.2697 2022/10/15 08:08:24 - mmengine - INFO - Epoch(train) [81][520/940] lr: 1.0000e-04 eta: 2:59:24 time: 0.5818 data_time: 0.0534 memory: 33630 grad_norm: 4.6750 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2474 loss: 1.2474 2022/10/15 08:08:36 - mmengine - INFO - Epoch(train) [81][540/940] lr: 1.0000e-04 eta: 2:59:13 time: 0.5818 data_time: 0.0361 memory: 33630 grad_norm: 4.8233 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2227 loss: 1.2227 2022/10/15 08:08:48 - mmengine - INFO - Epoch(train) [81][560/940] lr: 1.0000e-04 eta: 2:59:01 time: 0.5863 data_time: 0.0423 memory: 33630 grad_norm: 4.7237 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1806 loss: 1.1806 2022/10/15 08:08:59 - mmengine - INFO - Epoch(train) [81][580/940] lr: 1.0000e-04 eta: 2:58:49 time: 0.5798 data_time: 0.0348 memory: 33630 grad_norm: 4.6960 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1428 loss: 1.1428 2022/10/15 08:09:11 - mmengine - INFO - Epoch(train) [81][600/940] lr: 1.0000e-04 eta: 2:58:37 time: 0.5773 data_time: 0.0410 memory: 33630 grad_norm: 4.7822 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1820 loss: 1.1820 2022/10/15 08:09:22 - mmengine - INFO - Epoch(train) [81][620/940] lr: 1.0000e-04 eta: 2:58:25 time: 0.5731 data_time: 0.0331 memory: 33630 grad_norm: 4.8046 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1365 loss: 1.1365 2022/10/15 08:09:34 - mmengine - INFO - Epoch(train) [81][640/940] lr: 1.0000e-04 eta: 2:58:14 time: 0.5716 data_time: 0.0425 memory: 33630 grad_norm: 4.7011 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1844 loss: 1.1844 2022/10/15 08:09:45 - mmengine - INFO - Epoch(train) [81][660/940] lr: 1.0000e-04 eta: 2:58:02 time: 0.5829 data_time: 0.0399 memory: 33630 grad_norm: 4.7724 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2266 loss: 1.2266 2022/10/15 08:09:57 - mmengine - INFO - Epoch(train) [81][680/940] lr: 1.0000e-04 eta: 2:57:50 time: 0.5820 data_time: 0.0318 memory: 33630 grad_norm: 4.6923 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.1905 loss: 1.1905 2022/10/15 08:10:09 - mmengine - INFO - Epoch(train) [81][700/940] lr: 1.0000e-04 eta: 2:57:38 time: 0.5943 data_time: 0.0401 memory: 33630 grad_norm: 4.7712 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.0568 loss: 1.0568 2022/10/15 08:10:20 - mmengine - INFO - Epoch(train) [81][720/940] lr: 1.0000e-04 eta: 2:57:26 time: 0.5709 data_time: 0.0319 memory: 33630 grad_norm: 4.8303 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2178 loss: 1.2178 2022/10/15 08:10:32 - mmengine - INFO - Epoch(train) [81][740/940] lr: 1.0000e-04 eta: 2:57:14 time: 0.5791 data_time: 0.0346 memory: 33630 grad_norm: 4.8026 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2552 loss: 1.2552 2022/10/15 08:10:44 - mmengine - INFO - Epoch(train) [81][760/940] lr: 1.0000e-04 eta: 2:57:03 time: 0.5813 data_time: 0.0389 memory: 33630 grad_norm: 4.7918 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.1494 loss: 1.1494 2022/10/15 08:10:55 - mmengine - INFO - Epoch(train) [81][780/940] lr: 1.0000e-04 eta: 2:56:51 time: 0.5856 data_time: 0.0368 memory: 33630 grad_norm: 4.7746 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.0544 loss: 1.0544 2022/10/15 08:11:07 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 08:11:07 - mmengine - INFO - Epoch(train) [81][800/940] lr: 1.0000e-04 eta: 2:56:39 time: 0.5763 data_time: 0.0360 memory: 33630 grad_norm: 4.6182 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2111 loss: 1.2111 2022/10/15 08:11:19 - mmengine - INFO - Epoch(train) [81][820/940] lr: 1.0000e-04 eta: 2:56:27 time: 0.5869 data_time: 0.0338 memory: 33630 grad_norm: 4.8693 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2507 loss: 1.2507 2022/10/15 08:11:30 - mmengine - INFO - Epoch(train) [81][840/940] lr: 1.0000e-04 eta: 2:56:15 time: 0.5812 data_time: 0.0388 memory: 33630 grad_norm: 4.7248 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1070 loss: 1.1070 2022/10/15 08:11:42 - mmengine - INFO - Epoch(train) [81][860/940] lr: 1.0000e-04 eta: 2:56:04 time: 0.5904 data_time: 0.0339 memory: 33630 grad_norm: 4.7091 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0984 loss: 1.0984 2022/10/15 08:11:54 - mmengine - INFO - Epoch(train) [81][880/940] lr: 1.0000e-04 eta: 2:55:52 time: 0.5789 data_time: 0.0372 memory: 33630 grad_norm: 4.7543 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1102 loss: 1.1102 2022/10/15 08:12:05 - mmengine - INFO - Epoch(train) [81][900/940] lr: 1.0000e-04 eta: 2:55:40 time: 0.5768 data_time: 0.0375 memory: 33630 grad_norm: 4.7831 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.1620 loss: 1.1620 2022/10/15 08:12:17 - mmengine - INFO - Epoch(train) [81][920/940] lr: 1.0000e-04 eta: 2:55:28 time: 0.5824 data_time: 0.0324 memory: 33630 grad_norm: 4.8630 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1192 loss: 1.1192 2022/10/15 08:12:28 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 08:12:28 - mmengine - INFO - Epoch(train) [81][940/940] lr: 1.0000e-04 eta: 2:55:16 time: 0.5418 data_time: 0.0290 memory: 33630 grad_norm: 6.4549 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.2613 loss: 1.2613 2022/10/15 08:12:28 - mmengine - INFO - Saving checkpoint at 81 epochs 2022/10/15 08:12:43 - mmengine - INFO - Epoch(val) [81][20/78] eta: 0:00:40 time: 0.6980 data_time: 0.5279 memory: 5967 2022/10/15 08:12:53 - mmengine - INFO - Epoch(val) [81][40/78] eta: 0:00:18 time: 0.4980 data_time: 0.3316 memory: 5967 2022/10/15 08:13:05 - mmengine - INFO - Epoch(val) [81][60/78] eta: 0:00:11 time: 0.6196 data_time: 0.4491 memory: 5967 2022/10/15 08:13:16 - mmengine - INFO - Epoch(val) [81][78/78] acc/top1: 0.6887 acc/top5: 0.8787 acc/mean1: 0.6886 2022/10/15 08:13:33 - mmengine - INFO - Epoch(train) [82][20/940] lr: 1.0000e-04 eta: 2:55:05 time: 0.8139 data_time: 0.2457 memory: 33630 grad_norm: 4.8391 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1651 loss: 1.1651 2022/10/15 08:13:44 - mmengine - INFO - Epoch(train) [82][40/940] lr: 1.0000e-04 eta: 2:54:54 time: 0.5762 data_time: 0.0327 memory: 33630 grad_norm: 4.7537 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1822 loss: 1.1822 2022/10/15 08:13:56 - mmengine - INFO - Epoch(train) [82][60/940] lr: 1.0000e-04 eta: 2:54:42 time: 0.5907 data_time: 0.0402 memory: 33630 grad_norm: 4.7331 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0832 loss: 1.0832 2022/10/15 08:14:08 - mmengine - INFO - Epoch(train) [82][80/940] lr: 1.0000e-04 eta: 2:54:30 time: 0.5857 data_time: 0.0330 memory: 33630 grad_norm: 4.7485 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1188 loss: 1.1188 2022/10/15 08:14:20 - mmengine - INFO - Epoch(train) [82][100/940] lr: 1.0000e-04 eta: 2:54:18 time: 0.5913 data_time: 0.0417 memory: 33630 grad_norm: 4.8609 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2479 loss: 1.2479 2022/10/15 08:14:31 - mmengine - INFO - Epoch(train) [82][120/940] lr: 1.0000e-04 eta: 2:54:06 time: 0.5817 data_time: 0.0366 memory: 33630 grad_norm: 4.7113 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1936 loss: 1.1936 2022/10/15 08:14:43 - mmengine - INFO - Epoch(train) [82][140/940] lr: 1.0000e-04 eta: 2:53:55 time: 0.5804 data_time: 0.0446 memory: 33630 grad_norm: 4.7810 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2331 loss: 1.2331 2022/10/15 08:14:54 - mmengine - INFO - Epoch(train) [82][160/940] lr: 1.0000e-04 eta: 2:53:43 time: 0.5819 data_time: 0.0326 memory: 33630 grad_norm: 4.6927 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0972 loss: 1.0972 2022/10/15 08:15:06 - mmengine - INFO - Epoch(train) [82][180/940] lr: 1.0000e-04 eta: 2:53:31 time: 0.5909 data_time: 0.0363 memory: 33630 grad_norm: 4.9023 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1716 loss: 1.1716 2022/10/15 08:15:18 - mmengine - INFO - Epoch(train) [82][200/940] lr: 1.0000e-04 eta: 2:53:19 time: 0.5799 data_time: 0.0429 memory: 33630 grad_norm: 4.9076 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2883 loss: 1.2883 2022/10/15 08:15:30 - mmengine - INFO - Epoch(train) [82][220/940] lr: 1.0000e-04 eta: 2:53:07 time: 0.5846 data_time: 0.0371 memory: 33630 grad_norm: 4.7615 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2042 loss: 1.2042 2022/10/15 08:15:41 - mmengine - INFO - Epoch(train) [82][240/940] lr: 1.0000e-04 eta: 2:52:56 time: 0.5856 data_time: 0.0330 memory: 33630 grad_norm: 4.7623 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1627 loss: 1.1627 2022/10/15 08:15:53 - mmengine - INFO - Epoch(train) [82][260/940] lr: 1.0000e-04 eta: 2:52:44 time: 0.5793 data_time: 0.0437 memory: 33630 grad_norm: 4.8129 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1481 loss: 1.1481 2022/10/15 08:16:04 - mmengine - INFO - Epoch(train) [82][280/940] lr: 1.0000e-04 eta: 2:52:32 time: 0.5822 data_time: 0.0357 memory: 33630 grad_norm: 4.7261 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1884 loss: 1.1884 2022/10/15 08:16:16 - mmengine - INFO - Epoch(train) [82][300/940] lr: 1.0000e-04 eta: 2:52:20 time: 0.5753 data_time: 0.0386 memory: 33630 grad_norm: 4.8646 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1218 loss: 1.1218 2022/10/15 08:16:28 - mmengine - INFO - Epoch(train) [82][320/940] lr: 1.0000e-04 eta: 2:52:08 time: 0.5822 data_time: 0.0374 memory: 33630 grad_norm: 4.7472 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1367 loss: 1.1367 2022/10/15 08:16:39 - mmengine - INFO - Epoch(train) [82][340/940] lr: 1.0000e-04 eta: 2:51:57 time: 0.5802 data_time: 0.0406 memory: 33630 grad_norm: 4.7983 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1638 loss: 1.1638 2022/10/15 08:16:51 - mmengine - INFO - Epoch(train) [82][360/940] lr: 1.0000e-04 eta: 2:51:45 time: 0.5902 data_time: 0.0512 memory: 33630 grad_norm: 4.7891 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1668 loss: 1.1668 2022/10/15 08:17:03 - mmengine - INFO - Epoch(train) [82][380/940] lr: 1.0000e-04 eta: 2:51:33 time: 0.5850 data_time: 0.0346 memory: 33630 grad_norm: 4.7412 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1656 loss: 1.1656 2022/10/15 08:17:14 - mmengine - INFO - Epoch(train) [82][400/940] lr: 1.0000e-04 eta: 2:51:21 time: 0.5864 data_time: 0.0370 memory: 33630 grad_norm: 4.8432 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2352 loss: 1.2352 2022/10/15 08:17:26 - mmengine - INFO - Epoch(train) [82][420/940] lr: 1.0000e-04 eta: 2:51:09 time: 0.5906 data_time: 0.0454 memory: 33630 grad_norm: 4.7349 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2023 loss: 1.2023 2022/10/15 08:17:38 - mmengine - INFO - Epoch(train) [82][440/940] lr: 1.0000e-04 eta: 2:50:58 time: 0.5814 data_time: 0.0351 memory: 33630 grad_norm: 4.8623 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1742 loss: 1.1742 2022/10/15 08:17:49 - mmengine - INFO - Epoch(train) [82][460/940] lr: 1.0000e-04 eta: 2:50:46 time: 0.5714 data_time: 0.0320 memory: 33630 grad_norm: 4.7856 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1963 loss: 1.1963 2022/10/15 08:18:01 - mmengine - INFO - Epoch(train) [82][480/940] lr: 1.0000e-04 eta: 2:50:34 time: 0.5837 data_time: 0.0387 memory: 33630 grad_norm: 4.6735 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1019 loss: 1.1019 2022/10/15 08:18:13 - mmengine - INFO - Epoch(train) [82][500/940] lr: 1.0000e-04 eta: 2:50:22 time: 0.5858 data_time: 0.0315 memory: 33630 grad_norm: 4.7412 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.0916 loss: 1.0916 2022/10/15 08:18:25 - mmengine - INFO - Epoch(train) [82][520/940] lr: 1.0000e-04 eta: 2:50:10 time: 0.5906 data_time: 0.0330 memory: 33630 grad_norm: 4.8579 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1794 loss: 1.1794 2022/10/15 08:18:36 - mmengine - INFO - Epoch(train) [82][540/940] lr: 1.0000e-04 eta: 2:49:59 time: 0.5785 data_time: 0.0367 memory: 33630 grad_norm: 4.6759 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1683 loss: 1.1683 2022/10/15 08:18:48 - mmengine - INFO - Epoch(train) [82][560/940] lr: 1.0000e-04 eta: 2:49:47 time: 0.5927 data_time: 0.0528 memory: 33630 grad_norm: 4.7362 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1718 loss: 1.1718 2022/10/15 08:19:00 - mmengine - INFO - Epoch(train) [82][580/940] lr: 1.0000e-04 eta: 2:49:35 time: 0.5812 data_time: 0.0373 memory: 33630 grad_norm: 4.8696 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.1611 loss: 1.1611 2022/10/15 08:19:11 - mmengine - INFO - Epoch(train) [82][600/940] lr: 1.0000e-04 eta: 2:49:23 time: 0.5928 data_time: 0.0373 memory: 33630 grad_norm: 4.7747 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0785 loss: 1.0785 2022/10/15 08:19:23 - mmengine - INFO - Epoch(train) [82][620/940] lr: 1.0000e-04 eta: 2:49:11 time: 0.5847 data_time: 0.0450 memory: 33630 grad_norm: 4.7894 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1868 loss: 1.1868 2022/10/15 08:19:35 - mmengine - INFO - Epoch(train) [82][640/940] lr: 1.0000e-04 eta: 2:49:00 time: 0.5799 data_time: 0.0406 memory: 33630 grad_norm: 4.7741 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1224 loss: 1.1224 2022/10/15 08:19:46 - mmengine - INFO - Epoch(train) [82][660/940] lr: 1.0000e-04 eta: 2:48:48 time: 0.5762 data_time: 0.0339 memory: 33630 grad_norm: 4.8115 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1732 loss: 1.1732 2022/10/15 08:19:58 - mmengine - INFO - Epoch(train) [82][680/940] lr: 1.0000e-04 eta: 2:48:36 time: 0.5810 data_time: 0.0303 memory: 33630 grad_norm: 4.7650 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0899 loss: 1.0899 2022/10/15 08:20:09 - mmengine - INFO - Epoch(train) [82][700/940] lr: 1.0000e-04 eta: 2:48:24 time: 0.5774 data_time: 0.0333 memory: 33630 grad_norm: 4.7611 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0863 loss: 1.0863 2022/10/15 08:20:21 - mmengine - INFO - Epoch(train) [82][720/940] lr: 1.0000e-04 eta: 2:48:12 time: 0.5826 data_time: 0.0332 memory: 33630 grad_norm: 4.7174 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1547 loss: 1.1547 2022/10/15 08:20:33 - mmengine - INFO - Epoch(train) [82][740/940] lr: 1.0000e-04 eta: 2:48:01 time: 0.5843 data_time: 0.0463 memory: 33630 grad_norm: 4.7834 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1883 loss: 1.1883 2022/10/15 08:20:45 - mmengine - INFO - Epoch(train) [82][760/940] lr: 1.0000e-04 eta: 2:47:49 time: 0.5959 data_time: 0.0367 memory: 33630 grad_norm: 4.7694 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2346 loss: 1.2346 2022/10/15 08:20:57 - mmengine - INFO - Epoch(train) [82][780/940] lr: 1.0000e-04 eta: 2:47:37 time: 0.5886 data_time: 0.0400 memory: 33630 grad_norm: 4.7952 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1560 loss: 1.1560 2022/10/15 08:21:08 - mmengine - INFO - Epoch(train) [82][800/940] lr: 1.0000e-04 eta: 2:47:25 time: 0.5827 data_time: 0.0314 memory: 33630 grad_norm: 4.6943 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.2164 loss: 1.2164 2022/10/15 08:21:20 - mmengine - INFO - Epoch(train) [82][820/940] lr: 1.0000e-04 eta: 2:47:13 time: 0.5866 data_time: 0.0440 memory: 33630 grad_norm: 4.6645 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0919 loss: 1.0919 2022/10/15 08:21:32 - mmengine - INFO - Epoch(train) [82][840/940] lr: 1.0000e-04 eta: 2:47:02 time: 0.5846 data_time: 0.0341 memory: 33630 grad_norm: 4.8500 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1162 loss: 1.1162 2022/10/15 08:21:43 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 08:21:43 - mmengine - INFO - Epoch(train) [82][860/940] lr: 1.0000e-04 eta: 2:46:50 time: 0.5880 data_time: 0.0377 memory: 33630 grad_norm: 4.7593 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0785 loss: 1.0785 2022/10/15 08:21:55 - mmengine - INFO - Epoch(train) [82][880/940] lr: 1.0000e-04 eta: 2:46:38 time: 0.5763 data_time: 0.0381 memory: 33630 grad_norm: 4.7748 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2732 loss: 1.2732 2022/10/15 08:22:07 - mmengine - INFO - Epoch(train) [82][900/940] lr: 1.0000e-04 eta: 2:46:26 time: 0.5860 data_time: 0.0371 memory: 33630 grad_norm: 4.7181 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1926 loss: 1.1926 2022/10/15 08:22:18 - mmengine - INFO - Epoch(train) [82][920/940] lr: 1.0000e-04 eta: 2:46:14 time: 0.5881 data_time: 0.0541 memory: 33630 grad_norm: 4.7558 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1294 loss: 1.1294 2022/10/15 08:22:29 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 08:22:29 - mmengine - INFO - Epoch(train) [82][940/940] lr: 1.0000e-04 eta: 2:46:03 time: 0.5397 data_time: 0.0341 memory: 33630 grad_norm: 5.0087 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.0725 loss: 1.0725 2022/10/15 08:22:43 - mmengine - INFO - Epoch(val) [82][20/78] eta: 0:00:40 time: 0.6958 data_time: 0.5249 memory: 5967 2022/10/15 08:22:54 - mmengine - INFO - Epoch(val) [82][40/78] eta: 0:00:20 time: 0.5362 data_time: 0.3695 memory: 5967 2022/10/15 08:23:07 - mmengine - INFO - Epoch(val) [82][60/78] eta: 0:00:11 time: 0.6646 data_time: 0.4950 memory: 5967 2022/10/15 08:23:19 - mmengine - INFO - Epoch(val) [82][78/78] acc/top1: 0.6867 acc/top5: 0.8791 acc/mean1: 0.6866 2022/10/15 08:23:35 - mmengine - INFO - Epoch(train) [83][20/940] lr: 1.0000e-04 eta: 2:45:52 time: 0.8236 data_time: 0.2652 memory: 33630 grad_norm: 4.7545 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2824 loss: 1.2824 2022/10/15 08:23:47 - mmengine - INFO - Epoch(train) [83][40/940] lr: 1.0000e-04 eta: 2:45:40 time: 0.5765 data_time: 0.0328 memory: 33630 grad_norm: 4.8638 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2929 loss: 1.2929 2022/10/15 08:23:59 - mmengine - INFO - Epoch(train) [83][60/940] lr: 1.0000e-04 eta: 2:45:28 time: 0.6063 data_time: 0.0401 memory: 33630 grad_norm: 4.8210 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0897 loss: 1.0897 2022/10/15 08:24:11 - mmengine - INFO - Epoch(train) [83][80/940] lr: 1.0000e-04 eta: 2:45:16 time: 0.5875 data_time: 0.0343 memory: 33630 grad_norm: 4.8068 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0688 loss: 1.0688 2022/10/15 08:24:22 - mmengine - INFO - Epoch(train) [83][100/940] lr: 1.0000e-04 eta: 2:45:05 time: 0.5992 data_time: 0.0383 memory: 33630 grad_norm: 4.8348 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.2130 loss: 1.2130 2022/10/15 08:24:34 - mmengine - INFO - Epoch(train) [83][120/940] lr: 1.0000e-04 eta: 2:44:53 time: 0.5792 data_time: 0.0312 memory: 33630 grad_norm: 4.8096 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2155 loss: 1.2155 2022/10/15 08:24:46 - mmengine - INFO - Epoch(train) [83][140/940] lr: 1.0000e-04 eta: 2:44:41 time: 0.5823 data_time: 0.0329 memory: 33630 grad_norm: 4.8727 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2981 loss: 1.2981 2022/10/15 08:24:57 - mmengine - INFO - Epoch(train) [83][160/940] lr: 1.0000e-04 eta: 2:44:29 time: 0.5766 data_time: 0.0339 memory: 33630 grad_norm: 4.7803 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2557 loss: 1.2557 2022/10/15 08:25:09 - mmengine - INFO - Epoch(train) [83][180/940] lr: 1.0000e-04 eta: 2:44:17 time: 0.5858 data_time: 0.0325 memory: 33630 grad_norm: 4.8345 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2221 loss: 1.2221 2022/10/15 08:25:21 - mmengine - INFO - Epoch(train) [83][200/940] lr: 1.0000e-04 eta: 2:44:06 time: 0.5865 data_time: 0.0367 memory: 33630 grad_norm: 4.8140 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.2222 loss: 1.2222 2022/10/15 08:25:33 - mmengine - INFO - Epoch(train) [83][220/940] lr: 1.0000e-04 eta: 2:43:54 time: 0.5972 data_time: 0.0334 memory: 33630 grad_norm: 4.7720 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2115 loss: 1.2115 2022/10/15 08:25:44 - mmengine - INFO - Epoch(train) [83][240/940] lr: 1.0000e-04 eta: 2:43:42 time: 0.5752 data_time: 0.0424 memory: 33630 grad_norm: 4.7057 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0514 loss: 1.0514 2022/10/15 08:25:56 - mmengine - INFO - Epoch(train) [83][260/940] lr: 1.0000e-04 eta: 2:43:30 time: 0.5724 data_time: 0.0329 memory: 33630 grad_norm: 4.9503 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1300 loss: 1.1300 2022/10/15 08:26:07 - mmengine - INFO - Epoch(train) [83][280/940] lr: 1.0000e-04 eta: 2:43:18 time: 0.5749 data_time: 0.0374 memory: 33630 grad_norm: 4.6547 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2048 loss: 1.2048 2022/10/15 08:26:19 - mmengine - INFO - Epoch(train) [83][300/940] lr: 1.0000e-04 eta: 2:43:07 time: 0.5879 data_time: 0.0390 memory: 33630 grad_norm: 4.8024 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2120 loss: 1.2120 2022/10/15 08:26:31 - mmengine - INFO - Epoch(train) [83][320/940] lr: 1.0000e-04 eta: 2:42:55 time: 0.5890 data_time: 0.0433 memory: 33630 grad_norm: 4.7728 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0652 loss: 1.0652 2022/10/15 08:26:42 - mmengine - INFO - Epoch(train) [83][340/940] lr: 1.0000e-04 eta: 2:42:43 time: 0.5817 data_time: 0.0321 memory: 33630 grad_norm: 4.7903 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2152 loss: 1.2152 2022/10/15 08:26:54 - mmengine - INFO - Epoch(train) [83][360/940] lr: 1.0000e-04 eta: 2:42:31 time: 0.5845 data_time: 0.0336 memory: 33630 grad_norm: 4.8663 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.1318 loss: 1.1318 2022/10/15 08:27:06 - mmengine - INFO - Epoch(train) [83][380/940] lr: 1.0000e-04 eta: 2:42:19 time: 0.5776 data_time: 0.0371 memory: 33630 grad_norm: 4.8182 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1916 loss: 1.1916 2022/10/15 08:27:17 - mmengine - INFO - Epoch(train) [83][400/940] lr: 1.0000e-04 eta: 2:42:08 time: 0.5811 data_time: 0.0377 memory: 33630 grad_norm: 4.7495 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1784 loss: 1.1784 2022/10/15 08:27:29 - mmengine - INFO - Epoch(train) [83][420/940] lr: 1.0000e-04 eta: 2:41:56 time: 0.5828 data_time: 0.0315 memory: 33630 grad_norm: 4.9266 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1227 loss: 1.1227 2022/10/15 08:27:40 - mmengine - INFO - Epoch(train) [83][440/940] lr: 1.0000e-04 eta: 2:41:44 time: 0.5777 data_time: 0.0311 memory: 33630 grad_norm: 4.7830 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.2571 loss: 1.2571 2022/10/15 08:27:52 - mmengine - INFO - Epoch(train) [83][460/940] lr: 1.0000e-04 eta: 2:41:32 time: 0.5746 data_time: 0.0429 memory: 33630 grad_norm: 4.7978 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1492 loss: 1.1492 2022/10/15 08:28:04 - mmengine - INFO - Epoch(train) [83][480/940] lr: 1.0000e-04 eta: 2:41:20 time: 0.5828 data_time: 0.0436 memory: 33630 grad_norm: 4.8288 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.2502 loss: 1.2502 2022/10/15 08:28:15 - mmengine - INFO - Epoch(train) [83][500/940] lr: 1.0000e-04 eta: 2:41:09 time: 0.5858 data_time: 0.0394 memory: 33630 grad_norm: 4.8457 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1821 loss: 1.1821 2022/10/15 08:28:27 - mmengine - INFO - Epoch(train) [83][520/940] lr: 1.0000e-04 eta: 2:40:57 time: 0.5856 data_time: 0.0415 memory: 33630 grad_norm: 4.7139 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1530 loss: 1.1530 2022/10/15 08:28:39 - mmengine - INFO - Epoch(train) [83][540/940] lr: 1.0000e-04 eta: 2:40:45 time: 0.5805 data_time: 0.0347 memory: 33630 grad_norm: 4.8112 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2400 loss: 1.2400 2022/10/15 08:28:50 - mmengine - INFO - Epoch(train) [83][560/940] lr: 1.0000e-04 eta: 2:40:33 time: 0.5708 data_time: 0.0353 memory: 33630 grad_norm: 4.7755 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2477 loss: 1.2477 2022/10/15 08:29:02 - mmengine - INFO - Epoch(train) [83][580/940] lr: 1.0000e-04 eta: 2:40:21 time: 0.5877 data_time: 0.0381 memory: 33630 grad_norm: 4.9253 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2729 loss: 1.2729 2022/10/15 08:29:13 - mmengine - INFO - Epoch(train) [83][600/940] lr: 1.0000e-04 eta: 2:40:09 time: 0.5811 data_time: 0.0393 memory: 33630 grad_norm: 4.7985 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1232 loss: 1.1232 2022/10/15 08:29:25 - mmengine - INFO - Epoch(train) [83][620/940] lr: 1.0000e-04 eta: 2:39:58 time: 0.5765 data_time: 0.0314 memory: 33630 grad_norm: 4.7105 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2405 loss: 1.2405 2022/10/15 08:29:37 - mmengine - INFO - Epoch(train) [83][640/940] lr: 1.0000e-04 eta: 2:39:46 time: 0.5866 data_time: 0.0433 memory: 33630 grad_norm: 4.8130 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1762 loss: 1.1762 2022/10/15 08:29:48 - mmengine - INFO - Epoch(train) [83][660/940] lr: 1.0000e-04 eta: 2:39:34 time: 0.5878 data_time: 0.0364 memory: 33630 grad_norm: 4.7198 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1741 loss: 1.1741 2022/10/15 08:30:00 - mmengine - INFO - Epoch(train) [83][680/940] lr: 1.0000e-04 eta: 2:39:22 time: 0.5754 data_time: 0.0370 memory: 33630 grad_norm: 4.7262 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1264 loss: 1.1264 2022/10/15 08:30:11 - mmengine - INFO - Epoch(train) [83][700/940] lr: 1.0000e-04 eta: 2:39:10 time: 0.5700 data_time: 0.0416 memory: 33630 grad_norm: 4.7614 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1133 loss: 1.1133 2022/10/15 08:30:23 - mmengine - INFO - Epoch(train) [83][720/940] lr: 1.0000e-04 eta: 2:38:59 time: 0.5748 data_time: 0.0413 memory: 33630 grad_norm: 4.7436 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0826 loss: 1.0826 2022/10/15 08:30:34 - mmengine - INFO - Epoch(train) [83][740/940] lr: 1.0000e-04 eta: 2:38:47 time: 0.5820 data_time: 0.0388 memory: 33630 grad_norm: 4.8095 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1692 loss: 1.1692 2022/10/15 08:30:46 - mmengine - INFO - Epoch(train) [83][760/940] lr: 1.0000e-04 eta: 2:38:35 time: 0.5752 data_time: 0.0315 memory: 33630 grad_norm: 4.7888 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3069 loss: 1.3069 2022/10/15 08:30:58 - mmengine - INFO - Epoch(train) [83][780/940] lr: 1.0000e-04 eta: 2:38:23 time: 0.5809 data_time: 0.0302 memory: 33630 grad_norm: 4.8585 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0070 loss: 1.0070 2022/10/15 08:31:09 - mmengine - INFO - Epoch(train) [83][800/940] lr: 1.0000e-04 eta: 2:38:11 time: 0.5794 data_time: 0.0322 memory: 33630 grad_norm: 4.8051 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.0727 loss: 1.0727 2022/10/15 08:31:21 - mmengine - INFO - Epoch(train) [83][820/940] lr: 1.0000e-04 eta: 2:37:59 time: 0.5783 data_time: 0.0441 memory: 33630 grad_norm: 4.7911 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.1213 loss: 1.1213 2022/10/15 08:31:32 - mmengine - INFO - Epoch(train) [83][840/940] lr: 1.0000e-04 eta: 2:37:48 time: 0.5844 data_time: 0.0339 memory: 33630 grad_norm: 4.8044 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1941 loss: 1.1941 2022/10/15 08:31:44 - mmengine - INFO - Epoch(train) [83][860/940] lr: 1.0000e-04 eta: 2:37:36 time: 0.5842 data_time: 0.0366 memory: 33630 grad_norm: 4.7296 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1605 loss: 1.1605 2022/10/15 08:31:56 - mmengine - INFO - Epoch(train) [83][880/940] lr: 1.0000e-04 eta: 2:37:24 time: 0.5874 data_time: 0.0344 memory: 33630 grad_norm: 4.7602 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2674 loss: 1.2674 2022/10/15 08:32:08 - mmengine - INFO - Epoch(train) [83][900/940] lr: 1.0000e-04 eta: 2:37:12 time: 0.5824 data_time: 0.0331 memory: 33630 grad_norm: 4.8223 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2917 loss: 1.2917 2022/10/15 08:32:19 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 08:32:19 - mmengine - INFO - Epoch(train) [83][920/940] lr: 1.0000e-04 eta: 2:37:00 time: 0.5732 data_time: 0.0356 memory: 33630 grad_norm: 4.7740 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1206 loss: 1.1206 2022/10/15 08:32:30 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 08:32:30 - mmengine - INFO - Epoch(train) [83][940/940] lr: 1.0000e-04 eta: 2:36:49 time: 0.5447 data_time: 0.0260 memory: 33630 grad_norm: 5.1199 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.2567 loss: 1.2567 2022/10/15 08:32:44 - mmengine - INFO - Epoch(val) [83][20/78] eta: 0:00:41 time: 0.7146 data_time: 0.5454 memory: 5967 2022/10/15 08:32:54 - mmengine - INFO - Epoch(val) [83][40/78] eta: 0:00:19 time: 0.5119 data_time: 0.3422 memory: 5967 2022/10/15 08:33:08 - mmengine - INFO - Epoch(val) [83][60/78] eta: 0:00:11 time: 0.6588 data_time: 0.4905 memory: 5967 2022/10/15 08:33:20 - mmengine - INFO - Epoch(val) [83][78/78] acc/top1: 0.6876 acc/top5: 0.8791 acc/mean1: 0.6874 2022/10/15 08:33:37 - mmengine - INFO - Epoch(train) [84][20/940] lr: 1.0000e-04 eta: 2:36:38 time: 0.8635 data_time: 0.2470 memory: 33630 grad_norm: 4.7890 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1919 loss: 1.1919 2022/10/15 08:33:49 - mmengine - INFO - Epoch(train) [84][40/940] lr: 1.0000e-04 eta: 2:36:26 time: 0.5846 data_time: 0.0329 memory: 33630 grad_norm: 4.8804 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.1604 loss: 1.1604 2022/10/15 08:34:01 - mmengine - INFO - Epoch(train) [84][60/940] lr: 1.0000e-04 eta: 2:36:14 time: 0.5921 data_time: 0.0391 memory: 33630 grad_norm: 4.8681 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2192 loss: 1.2192 2022/10/15 08:34:12 - mmengine - INFO - Epoch(train) [84][80/940] lr: 1.0000e-04 eta: 2:36:02 time: 0.5793 data_time: 0.0316 memory: 33630 grad_norm: 4.7190 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1188 loss: 1.1188 2022/10/15 08:34:25 - mmengine - INFO - Epoch(train) [84][100/940] lr: 1.0000e-04 eta: 2:35:51 time: 0.6555 data_time: 0.1073 memory: 33630 grad_norm: 4.6675 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1584 loss: 1.1584 2022/10/15 08:34:37 - mmengine - INFO - Epoch(train) [84][120/940] lr: 1.0000e-04 eta: 2:35:39 time: 0.5890 data_time: 0.0297 memory: 33630 grad_norm: 4.7171 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1558 loss: 1.1558 2022/10/15 08:34:49 - mmengine - INFO - Epoch(train) [84][140/940] lr: 1.0000e-04 eta: 2:35:27 time: 0.5855 data_time: 0.0355 memory: 33630 grad_norm: 4.8856 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0703 loss: 1.0703 2022/10/15 08:35:00 - mmengine - INFO - Epoch(train) [84][160/940] lr: 1.0000e-04 eta: 2:35:16 time: 0.5830 data_time: 0.0349 memory: 33630 grad_norm: 4.9147 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1941 loss: 1.1941 2022/10/15 08:35:12 - mmengine - INFO - Epoch(train) [84][180/940] lr: 1.0000e-04 eta: 2:35:04 time: 0.5847 data_time: 0.0296 memory: 33630 grad_norm: 4.7406 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2486 loss: 1.2486 2022/10/15 08:35:24 - mmengine - INFO - Epoch(train) [84][200/940] lr: 1.0000e-04 eta: 2:34:52 time: 0.5848 data_time: 0.0379 memory: 33630 grad_norm: 4.7605 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1537 loss: 1.1537 2022/10/15 08:35:35 - mmengine - INFO - Epoch(train) [84][220/940] lr: 1.0000e-04 eta: 2:34:40 time: 0.5821 data_time: 0.0411 memory: 33630 grad_norm: 4.8998 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1480 loss: 1.1480 2022/10/15 08:35:47 - mmengine - INFO - Epoch(train) [84][240/940] lr: 1.0000e-04 eta: 2:34:28 time: 0.5875 data_time: 0.0388 memory: 33630 grad_norm: 4.8431 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1241 loss: 1.1241 2022/10/15 08:35:59 - mmengine - INFO - Epoch(train) [84][260/940] lr: 1.0000e-04 eta: 2:34:17 time: 0.5788 data_time: 0.0413 memory: 33630 grad_norm: 4.7714 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1068 loss: 1.1068 2022/10/15 08:36:10 - mmengine - INFO - Epoch(train) [84][280/940] lr: 1.0000e-04 eta: 2:34:05 time: 0.5811 data_time: 0.0415 memory: 33630 grad_norm: 4.7847 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1977 loss: 1.1977 2022/10/15 08:36:22 - mmengine - INFO - Epoch(train) [84][300/940] lr: 1.0000e-04 eta: 2:33:53 time: 0.5851 data_time: 0.0466 memory: 33630 grad_norm: 4.7618 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.1765 loss: 1.1765 2022/10/15 08:36:34 - mmengine - INFO - Epoch(train) [84][320/940] lr: 1.0000e-04 eta: 2:33:41 time: 0.5836 data_time: 0.0411 memory: 33630 grad_norm: 4.7077 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2020 loss: 1.2020 2022/10/15 08:36:45 - mmengine - INFO - Epoch(train) [84][340/940] lr: 1.0000e-04 eta: 2:33:29 time: 0.5805 data_time: 0.0407 memory: 33630 grad_norm: 4.7467 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1284 loss: 1.1284 2022/10/15 08:36:57 - mmengine - INFO - Epoch(train) [84][360/940] lr: 1.0000e-04 eta: 2:33:18 time: 0.5814 data_time: 0.0327 memory: 33630 grad_norm: 4.9345 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1513 loss: 1.1513 2022/10/15 08:37:09 - mmengine - INFO - Epoch(train) [84][380/940] lr: 1.0000e-04 eta: 2:33:06 time: 0.5827 data_time: 0.0439 memory: 33630 grad_norm: 4.8596 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0882 loss: 1.0882 2022/10/15 08:37:20 - mmengine - INFO - Epoch(train) [84][400/940] lr: 1.0000e-04 eta: 2:32:54 time: 0.5771 data_time: 0.0336 memory: 33630 grad_norm: 4.8923 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1802 loss: 1.1802 2022/10/15 08:37:32 - mmengine - INFO - Epoch(train) [84][420/940] lr: 1.0000e-04 eta: 2:32:42 time: 0.5724 data_time: 0.0327 memory: 33630 grad_norm: 4.7942 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1930 loss: 1.1930 2022/10/15 08:37:43 - mmengine - INFO - Epoch(train) [84][440/940] lr: 1.0000e-04 eta: 2:32:30 time: 0.5796 data_time: 0.0350 memory: 33630 grad_norm: 4.8407 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.0552 loss: 1.0552 2022/10/15 08:37:55 - mmengine - INFO - Epoch(train) [84][460/940] lr: 1.0000e-04 eta: 2:32:19 time: 0.5927 data_time: 0.0398 memory: 33630 grad_norm: 4.7261 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2306 loss: 1.2306 2022/10/15 08:38:07 - mmengine - INFO - Epoch(train) [84][480/940] lr: 1.0000e-04 eta: 2:32:07 time: 0.5750 data_time: 0.0464 memory: 33630 grad_norm: 4.6611 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1586 loss: 1.1586 2022/10/15 08:38:18 - mmengine - INFO - Epoch(train) [84][500/940] lr: 1.0000e-04 eta: 2:31:55 time: 0.5897 data_time: 0.0411 memory: 33630 grad_norm: 4.6884 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.1694 loss: 1.1694 2022/10/15 08:38:30 - mmengine - INFO - Epoch(train) [84][520/940] lr: 1.0000e-04 eta: 2:31:43 time: 0.5933 data_time: 0.0358 memory: 33630 grad_norm: 4.7467 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2072 loss: 1.2072 2022/10/15 08:38:42 - mmengine - INFO - Epoch(train) [84][540/940] lr: 1.0000e-04 eta: 2:31:31 time: 0.5705 data_time: 0.0305 memory: 33630 grad_norm: 4.6861 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1538 loss: 1.1538 2022/10/15 08:38:53 - mmengine - INFO - Epoch(train) [84][560/940] lr: 1.0000e-04 eta: 2:31:20 time: 0.5747 data_time: 0.0315 memory: 33630 grad_norm: 4.8299 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.1961 loss: 1.1961 2022/10/15 08:39:05 - mmengine - INFO - Epoch(train) [84][580/940] lr: 1.0000e-04 eta: 2:31:08 time: 0.5778 data_time: 0.0337 memory: 33630 grad_norm: 4.8544 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0903 loss: 1.0903 2022/10/15 08:39:16 - mmengine - INFO - Epoch(train) [84][600/940] lr: 1.0000e-04 eta: 2:30:56 time: 0.5840 data_time: 0.0349 memory: 33630 grad_norm: 4.7913 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1551 loss: 1.1551 2022/10/15 08:39:28 - mmengine - INFO - Epoch(train) [84][620/940] lr: 1.0000e-04 eta: 2:30:44 time: 0.5817 data_time: 0.0374 memory: 33630 grad_norm: 4.8576 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1882 loss: 1.1882 2022/10/15 08:39:40 - mmengine - INFO - Epoch(train) [84][640/940] lr: 1.0000e-04 eta: 2:30:32 time: 0.5759 data_time: 0.0458 memory: 33630 grad_norm: 4.7753 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1765 loss: 1.1765 2022/10/15 08:39:51 - mmengine - INFO - Epoch(train) [84][660/940] lr: 1.0000e-04 eta: 2:30:20 time: 0.5889 data_time: 0.0344 memory: 33630 grad_norm: 4.8396 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2465 loss: 1.2465 2022/10/15 08:40:03 - mmengine - INFO - Epoch(train) [84][680/940] lr: 1.0000e-04 eta: 2:30:09 time: 0.5861 data_time: 0.0379 memory: 33630 grad_norm: 4.7995 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0816 loss: 1.0816 2022/10/15 08:40:15 - mmengine - INFO - Epoch(train) [84][700/940] lr: 1.0000e-04 eta: 2:29:57 time: 0.5806 data_time: 0.0352 memory: 33630 grad_norm: 4.7213 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2011 loss: 1.2011 2022/10/15 08:40:26 - mmengine - INFO - Epoch(train) [84][720/940] lr: 1.0000e-04 eta: 2:29:45 time: 0.5766 data_time: 0.0487 memory: 33630 grad_norm: 4.7043 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1134 loss: 1.1134 2022/10/15 08:40:38 - mmengine - INFO - Epoch(train) [84][740/940] lr: 1.0000e-04 eta: 2:29:33 time: 0.5876 data_time: 0.0386 memory: 33630 grad_norm: 4.8957 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.1381 loss: 1.1381 2022/10/15 08:40:50 - mmengine - INFO - Epoch(train) [84][760/940] lr: 1.0000e-04 eta: 2:29:21 time: 0.5764 data_time: 0.0345 memory: 33630 grad_norm: 4.7090 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1906 loss: 1.1906 2022/10/15 08:41:01 - mmengine - INFO - Epoch(train) [84][780/940] lr: 1.0000e-04 eta: 2:29:10 time: 0.5812 data_time: 0.0323 memory: 33630 grad_norm: 4.7315 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1222 loss: 1.1222 2022/10/15 08:41:13 - mmengine - INFO - Epoch(train) [84][800/940] lr: 1.0000e-04 eta: 2:28:58 time: 0.5826 data_time: 0.0348 memory: 33630 grad_norm: 4.9150 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1287 loss: 1.1287 2022/10/15 08:41:24 - mmengine - INFO - Epoch(train) [84][820/940] lr: 1.0000e-04 eta: 2:28:46 time: 0.5665 data_time: 0.0328 memory: 33630 grad_norm: 4.8751 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0857 loss: 1.0857 2022/10/15 08:41:36 - mmengine - INFO - Epoch(train) [84][840/940] lr: 1.0000e-04 eta: 2:28:34 time: 0.5793 data_time: 0.0338 memory: 33630 grad_norm: 4.8537 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1757 loss: 1.1757 2022/10/15 08:41:47 - mmengine - INFO - Epoch(train) [84][860/940] lr: 1.0000e-04 eta: 2:28:22 time: 0.5794 data_time: 0.0371 memory: 33630 grad_norm: 4.8089 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1256 loss: 1.1256 2022/10/15 08:41:59 - mmengine - INFO - Epoch(train) [84][880/940] lr: 1.0000e-04 eta: 2:28:11 time: 0.5762 data_time: 0.0369 memory: 33630 grad_norm: 4.8154 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2136 loss: 1.2136 2022/10/15 08:42:11 - mmengine - INFO - Epoch(train) [84][900/940] lr: 1.0000e-04 eta: 2:27:59 time: 0.5898 data_time: 0.0370 memory: 33630 grad_norm: 4.7270 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1373 loss: 1.1373 2022/10/15 08:42:22 - mmengine - INFO - Epoch(train) [84][920/940] lr: 1.0000e-04 eta: 2:27:47 time: 0.5815 data_time: 0.0387 memory: 33630 grad_norm: 4.8187 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.2271 loss: 1.2271 2022/10/15 08:42:33 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 08:42:33 - mmengine - INFO - Epoch(train) [84][940/940] lr: 1.0000e-04 eta: 2:27:35 time: 0.5370 data_time: 0.0394 memory: 33630 grad_norm: 5.0966 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.2404 loss: 1.2404 2022/10/15 08:42:33 - mmengine - INFO - Saving checkpoint at 84 epochs 2022/10/15 08:42:48 - mmengine - INFO - Epoch(val) [84][20/78] eta: 0:00:41 time: 0.7109 data_time: 0.5378 memory: 5967 2022/10/15 08:42:58 - mmengine - INFO - Epoch(val) [84][40/78] eta: 0:00:19 time: 0.5010 data_time: 0.3311 memory: 5967 2022/10/15 08:43:12 - mmengine - INFO - Epoch(val) [84][60/78] eta: 0:00:11 time: 0.6666 data_time: 0.4955 memory: 5967 2022/10/15 08:43:22 - mmengine - INFO - Epoch(val) [84][78/78] acc/top1: 0.6870 acc/top5: 0.8784 acc/mean1: 0.6869 2022/10/15 08:43:39 - mmengine - INFO - Epoch(train) [85][20/940] lr: 1.0000e-04 eta: 2:27:24 time: 0.8272 data_time: 0.2494 memory: 33630 grad_norm: 4.8083 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2981 loss: 1.2981 2022/10/15 08:43:50 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 08:43:50 - mmengine - INFO - Epoch(train) [85][40/940] lr: 1.0000e-04 eta: 2:27:12 time: 0.5907 data_time: 0.0343 memory: 33630 grad_norm: 4.7977 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2280 loss: 1.2280 2022/10/15 08:44:03 - mmengine - INFO - Epoch(train) [85][60/940] lr: 1.0000e-04 eta: 2:27:01 time: 0.6389 data_time: 0.0390 memory: 33630 grad_norm: 4.7909 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1800 loss: 1.1800 2022/10/15 08:44:15 - mmengine - INFO - Epoch(train) [85][80/940] lr: 1.0000e-04 eta: 2:26:49 time: 0.5918 data_time: 0.0332 memory: 33630 grad_norm: 4.8228 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1173 loss: 1.1173 2022/10/15 08:44:27 - mmengine - INFO - Epoch(train) [85][100/940] lr: 1.0000e-04 eta: 2:26:37 time: 0.6082 data_time: 0.0352 memory: 33630 grad_norm: 4.7353 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0300 loss: 1.0300 2022/10/15 08:44:39 - mmengine - INFO - Epoch(train) [85][120/940] lr: 1.0000e-04 eta: 2:26:25 time: 0.5769 data_time: 0.0382 memory: 33630 grad_norm: 4.8756 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1962 loss: 1.1962 2022/10/15 08:44:50 - mmengine - INFO - Epoch(train) [85][140/940] lr: 1.0000e-04 eta: 2:26:14 time: 0.5816 data_time: 0.0380 memory: 33630 grad_norm: 4.8611 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1219 loss: 1.1219 2022/10/15 08:45:02 - mmengine - INFO - Epoch(train) [85][160/940] lr: 1.0000e-04 eta: 2:26:02 time: 0.5928 data_time: 0.0348 memory: 33630 grad_norm: 4.7841 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2673 loss: 1.2673 2022/10/15 08:45:14 - mmengine - INFO - Epoch(train) [85][180/940] lr: 1.0000e-04 eta: 2:25:50 time: 0.5824 data_time: 0.0468 memory: 33630 grad_norm: 4.9236 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2798 loss: 1.2798 2022/10/15 08:45:26 - mmengine - INFO - Epoch(train) [85][200/940] lr: 1.0000e-04 eta: 2:25:38 time: 0.5858 data_time: 0.0330 memory: 33630 grad_norm: 4.7196 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0819 loss: 1.0819 2022/10/15 08:45:37 - mmengine - INFO - Epoch(train) [85][220/940] lr: 1.0000e-04 eta: 2:25:26 time: 0.5777 data_time: 0.0362 memory: 33630 grad_norm: 4.7884 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2454 loss: 1.2454 2022/10/15 08:45:49 - mmengine - INFO - Epoch(train) [85][240/940] lr: 1.0000e-04 eta: 2:25:15 time: 0.5867 data_time: 0.0319 memory: 33630 grad_norm: 4.8106 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0123 loss: 1.0123 2022/10/15 08:46:01 - mmengine - INFO - Epoch(train) [85][260/940] lr: 1.0000e-04 eta: 2:25:03 time: 0.5857 data_time: 0.0481 memory: 33630 grad_norm: 4.7407 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0780 loss: 1.0780 2022/10/15 08:46:12 - mmengine - INFO - Epoch(train) [85][280/940] lr: 1.0000e-04 eta: 2:24:51 time: 0.5741 data_time: 0.0369 memory: 33630 grad_norm: 4.8044 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2534 loss: 1.2534 2022/10/15 08:46:24 - mmengine - INFO - Epoch(train) [85][300/940] lr: 1.0000e-04 eta: 2:24:39 time: 0.5775 data_time: 0.0333 memory: 33630 grad_norm: 4.8674 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2597 loss: 1.2597 2022/10/15 08:46:35 - mmengine - INFO - Epoch(train) [85][320/940] lr: 1.0000e-04 eta: 2:24:27 time: 0.5706 data_time: 0.0333 memory: 33630 grad_norm: 4.7716 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1236 loss: 1.1236 2022/10/15 08:46:47 - mmengine - INFO - Epoch(train) [85][340/940] lr: 1.0000e-04 eta: 2:24:16 time: 0.5808 data_time: 0.0421 memory: 33630 grad_norm: 4.6616 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.1902 loss: 1.1902 2022/10/15 08:46:58 - mmengine - INFO - Epoch(train) [85][360/940] lr: 1.0000e-04 eta: 2:24:04 time: 0.5760 data_time: 0.0414 memory: 33630 grad_norm: 4.9006 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1700 loss: 1.1700 2022/10/15 08:47:10 - mmengine - INFO - Epoch(train) [85][380/940] lr: 1.0000e-04 eta: 2:23:52 time: 0.5836 data_time: 0.0342 memory: 33630 grad_norm: 4.8169 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2219 loss: 1.2219 2022/10/15 08:47:21 - mmengine - INFO - Epoch(train) [85][400/940] lr: 1.0000e-04 eta: 2:23:40 time: 0.5776 data_time: 0.0374 memory: 33630 grad_norm: 4.7740 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2224 loss: 1.2224 2022/10/15 08:47:33 - mmengine - INFO - Epoch(train) [85][420/940] lr: 1.0000e-04 eta: 2:23:28 time: 0.5709 data_time: 0.0314 memory: 33630 grad_norm: 4.8467 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1597 loss: 1.1597 2022/10/15 08:47:45 - mmengine - INFO - Epoch(train) [85][440/940] lr: 1.0000e-04 eta: 2:23:17 time: 0.5919 data_time: 0.0589 memory: 33630 grad_norm: 4.8324 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2765 loss: 1.2765 2022/10/15 08:47:56 - mmengine - INFO - Epoch(train) [85][460/940] lr: 1.0000e-04 eta: 2:23:05 time: 0.5826 data_time: 0.0325 memory: 33630 grad_norm: 4.8091 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1129 loss: 1.1129 2022/10/15 08:48:08 - mmengine - INFO - Epoch(train) [85][480/940] lr: 1.0000e-04 eta: 2:22:53 time: 0.5907 data_time: 0.0324 memory: 33630 grad_norm: 4.8313 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1122 loss: 1.1122 2022/10/15 08:48:20 - mmengine - INFO - Epoch(train) [85][500/940] lr: 1.0000e-04 eta: 2:22:41 time: 0.5838 data_time: 0.0465 memory: 33630 grad_norm: 4.7934 top1_acc: 0.8438 top5_acc: 0.8438 loss_cls: 1.1237 loss: 1.1237 2022/10/15 08:48:31 - mmengine - INFO - Epoch(train) [85][520/940] lr: 1.0000e-04 eta: 2:22:29 time: 0.5829 data_time: 0.0354 memory: 33630 grad_norm: 4.8168 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.2392 loss: 1.2392 2022/10/15 08:48:43 - mmengine - INFO - Epoch(train) [85][540/940] lr: 1.0000e-04 eta: 2:22:18 time: 0.5792 data_time: 0.0429 memory: 33630 grad_norm: 4.8114 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2244 loss: 1.2244 2022/10/15 08:48:55 - mmengine - INFO - Epoch(train) [85][560/940] lr: 1.0000e-04 eta: 2:22:06 time: 0.5727 data_time: 0.0331 memory: 33630 grad_norm: 4.8623 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2737 loss: 1.2737 2022/10/15 08:49:06 - mmengine - INFO - Epoch(train) [85][580/940] lr: 1.0000e-04 eta: 2:21:54 time: 0.5817 data_time: 0.0378 memory: 33630 grad_norm: 4.7304 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1328 loss: 1.1328 2022/10/15 08:49:18 - mmengine - INFO - Epoch(train) [85][600/940] lr: 1.0000e-04 eta: 2:21:42 time: 0.5818 data_time: 0.0335 memory: 33630 grad_norm: 4.6776 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.2084 loss: 1.2084 2022/10/15 08:49:29 - mmengine - INFO - Epoch(train) [85][620/940] lr: 1.0000e-04 eta: 2:21:30 time: 0.5762 data_time: 0.0357 memory: 33630 grad_norm: 4.8138 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0975 loss: 1.0975 2022/10/15 08:49:41 - mmengine - INFO - Epoch(train) [85][640/940] lr: 1.0000e-04 eta: 2:21:19 time: 0.5834 data_time: 0.0326 memory: 33630 grad_norm: 4.8088 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2669 loss: 1.2669 2022/10/15 08:49:53 - mmengine - INFO - Epoch(train) [85][660/940] lr: 1.0000e-04 eta: 2:21:07 time: 0.5796 data_time: 0.0402 memory: 33630 grad_norm: 4.8175 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2194 loss: 1.2194 2022/10/15 08:50:04 - mmengine - INFO - Epoch(train) [85][680/940] lr: 1.0000e-04 eta: 2:20:55 time: 0.5862 data_time: 0.0345 memory: 33630 grad_norm: 4.7255 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0888 loss: 1.0888 2022/10/15 08:50:16 - mmengine - INFO - Epoch(train) [85][700/940] lr: 1.0000e-04 eta: 2:20:43 time: 0.5776 data_time: 0.0435 memory: 33630 grad_norm: 4.7815 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1537 loss: 1.1537 2022/10/15 08:50:27 - mmengine - INFO - Epoch(train) [85][720/940] lr: 1.0000e-04 eta: 2:20:31 time: 0.5749 data_time: 0.0358 memory: 33630 grad_norm: 4.7006 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.0920 loss: 1.0920 2022/10/15 08:50:39 - mmengine - INFO - Epoch(train) [85][740/940] lr: 1.0000e-04 eta: 2:20:19 time: 0.5825 data_time: 0.0381 memory: 33630 grad_norm: 4.8759 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1678 loss: 1.1678 2022/10/15 08:50:50 - mmengine - INFO - Epoch(train) [85][760/940] lr: 1.0000e-04 eta: 2:20:08 time: 0.5705 data_time: 0.0353 memory: 33630 grad_norm: 4.7673 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0967 loss: 1.0967 2022/10/15 08:51:02 - mmengine - INFO - Epoch(train) [85][780/940] lr: 1.0000e-04 eta: 2:19:56 time: 0.5764 data_time: 0.0301 memory: 33630 grad_norm: 4.6970 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1433 loss: 1.1433 2022/10/15 08:51:14 - mmengine - INFO - Epoch(train) [85][800/940] lr: 1.0000e-04 eta: 2:19:44 time: 0.5823 data_time: 0.0357 memory: 33630 grad_norm: 4.6819 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1477 loss: 1.1477 2022/10/15 08:51:25 - mmengine - INFO - Epoch(train) [85][820/940] lr: 1.0000e-04 eta: 2:19:32 time: 0.5862 data_time: 0.0365 memory: 33630 grad_norm: 4.7791 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1536 loss: 1.1536 2022/10/15 08:51:37 - mmengine - INFO - Epoch(train) [85][840/940] lr: 1.0000e-04 eta: 2:19:20 time: 0.5740 data_time: 0.0336 memory: 33630 grad_norm: 4.7800 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2332 loss: 1.2332 2022/10/15 08:51:48 - mmengine - INFO - Epoch(train) [85][860/940] lr: 1.0000e-04 eta: 2:19:09 time: 0.5816 data_time: 0.0394 memory: 33630 grad_norm: 4.8417 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1372 loss: 1.1372 2022/10/15 08:52:00 - mmengine - INFO - Epoch(train) [85][880/940] lr: 1.0000e-04 eta: 2:18:57 time: 0.5812 data_time: 0.0322 memory: 33630 grad_norm: 4.7304 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.0914 loss: 1.0914 2022/10/15 08:52:12 - mmengine - INFO - Epoch(train) [85][900/940] lr: 1.0000e-04 eta: 2:18:45 time: 0.5772 data_time: 0.0384 memory: 33630 grad_norm: 4.9524 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2194 loss: 1.2194 2022/10/15 08:52:23 - mmengine - INFO - Epoch(train) [85][920/940] lr: 1.0000e-04 eta: 2:18:33 time: 0.5781 data_time: 0.0391 memory: 33630 grad_norm: 4.8173 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0481 loss: 1.0481 2022/10/15 08:52:34 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 08:52:34 - mmengine - INFO - Epoch(train) [85][940/940] lr: 1.0000e-04 eta: 2:18:21 time: 0.5347 data_time: 0.0276 memory: 33630 grad_norm: 5.0286 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.1690 loss: 1.1690 2022/10/15 08:52:48 - mmengine - INFO - Epoch(val) [85][20/78] eta: 0:00:41 time: 0.7071 data_time: 0.5354 memory: 5967 2022/10/15 08:52:58 - mmengine - INFO - Epoch(val) [85][40/78] eta: 0:00:18 time: 0.5000 data_time: 0.3325 memory: 5967 2022/10/15 08:53:11 - mmengine - INFO - Epoch(val) [85][60/78] eta: 0:00:11 time: 0.6238 data_time: 0.4545 memory: 5967 2022/10/15 08:53:23 - mmengine - INFO - Epoch(val) [85][78/78] acc/top1: 0.6890 acc/top5: 0.8792 acc/mean1: 0.6889 2022/10/15 08:53:39 - mmengine - INFO - Epoch(train) [86][20/940] lr: 1.0000e-04 eta: 2:18:10 time: 0.8272 data_time: 0.2606 memory: 33630 grad_norm: 4.8223 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1986 loss: 1.1986 2022/10/15 08:53:51 - mmengine - INFO - Epoch(train) [86][40/940] lr: 1.0000e-04 eta: 2:17:58 time: 0.5791 data_time: 0.0334 memory: 33630 grad_norm: 4.8680 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.1411 loss: 1.1411 2022/10/15 08:54:03 - mmengine - INFO - Epoch(train) [86][60/940] lr: 1.0000e-04 eta: 2:17:47 time: 0.5891 data_time: 0.0385 memory: 33630 grad_norm: 4.8458 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1830 loss: 1.1830 2022/10/15 08:54:14 - mmengine - INFO - Epoch(train) [86][80/940] lr: 1.0000e-04 eta: 2:17:35 time: 0.5864 data_time: 0.0367 memory: 33630 grad_norm: 4.7746 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0790 loss: 1.0790 2022/10/15 08:54:26 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 08:54:26 - mmengine - INFO - Epoch(train) [86][100/940] lr: 1.0000e-04 eta: 2:17:23 time: 0.5922 data_time: 0.0364 memory: 33630 grad_norm: 4.8464 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1925 loss: 1.1925 2022/10/15 08:54:38 - mmengine - INFO - Epoch(train) [86][120/940] lr: 1.0000e-04 eta: 2:17:11 time: 0.5802 data_time: 0.0333 memory: 33630 grad_norm: 4.8706 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1442 loss: 1.1442 2022/10/15 08:54:49 - mmengine - INFO - Epoch(train) [86][140/940] lr: 1.0000e-04 eta: 2:17:00 time: 0.5868 data_time: 0.0356 memory: 33630 grad_norm: 4.8106 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1525 loss: 1.1525 2022/10/15 08:55:01 - mmengine - INFO - Epoch(train) [86][160/940] lr: 1.0000e-04 eta: 2:16:48 time: 0.5880 data_time: 0.0335 memory: 33630 grad_norm: 4.7296 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1013 loss: 1.1013 2022/10/15 08:55:13 - mmengine - INFO - Epoch(train) [86][180/940] lr: 1.0000e-04 eta: 2:16:36 time: 0.5755 data_time: 0.0356 memory: 33630 grad_norm: 4.8677 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1382 loss: 1.1382 2022/10/15 08:55:25 - mmengine - INFO - Epoch(train) [86][200/940] lr: 1.0000e-04 eta: 2:16:24 time: 0.5872 data_time: 0.0356 memory: 33630 grad_norm: 4.7876 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1666 loss: 1.1666 2022/10/15 08:55:36 - mmengine - INFO - Epoch(train) [86][220/940] lr: 1.0000e-04 eta: 2:16:12 time: 0.5802 data_time: 0.0318 memory: 33630 grad_norm: 4.8367 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2355 loss: 1.2355 2022/10/15 08:55:48 - mmengine - INFO - Epoch(train) [86][240/940] lr: 1.0000e-04 eta: 2:16:01 time: 0.5880 data_time: 0.0406 memory: 33630 grad_norm: 4.7449 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.1232 loss: 1.1232 2022/10/15 08:55:59 - mmengine - INFO - Epoch(train) [86][260/940] lr: 1.0000e-04 eta: 2:15:49 time: 0.5770 data_time: 0.0388 memory: 33630 grad_norm: 4.8594 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1386 loss: 1.1386 2022/10/15 08:56:11 - mmengine - INFO - Epoch(train) [86][280/940] lr: 1.0000e-04 eta: 2:15:37 time: 0.5828 data_time: 0.0310 memory: 33630 grad_norm: 4.8035 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1375 loss: 1.1375 2022/10/15 08:56:23 - mmengine - INFO - Epoch(train) [86][300/940] lr: 1.0000e-04 eta: 2:15:25 time: 0.5761 data_time: 0.0365 memory: 33630 grad_norm: 4.9857 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2486 loss: 1.2486 2022/10/15 08:56:34 - mmengine - INFO - Epoch(train) [86][320/940] lr: 1.0000e-04 eta: 2:15:13 time: 0.5864 data_time: 0.0320 memory: 33630 grad_norm: 4.6893 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1790 loss: 1.1790 2022/10/15 08:56:46 - mmengine - INFO - Epoch(train) [86][340/940] lr: 1.0000e-04 eta: 2:15:02 time: 0.5745 data_time: 0.0366 memory: 33630 grad_norm: 4.8298 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1387 loss: 1.1387 2022/10/15 08:56:58 - mmengine - INFO - Epoch(train) [86][360/940] lr: 1.0000e-04 eta: 2:14:50 time: 0.5854 data_time: 0.0402 memory: 33630 grad_norm: 4.7910 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1408 loss: 1.1408 2022/10/15 08:57:09 - mmengine - INFO - Epoch(train) [86][380/940] lr: 1.0000e-04 eta: 2:14:38 time: 0.5767 data_time: 0.0372 memory: 33630 grad_norm: 4.8142 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2130 loss: 1.2130 2022/10/15 08:57:21 - mmengine - INFO - Epoch(train) [86][400/940] lr: 1.0000e-04 eta: 2:14:26 time: 0.5772 data_time: 0.0319 memory: 33630 grad_norm: 4.7996 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1107 loss: 1.1107 2022/10/15 08:57:32 - mmengine - INFO - Epoch(train) [86][420/940] lr: 1.0000e-04 eta: 2:14:14 time: 0.5781 data_time: 0.0394 memory: 33630 grad_norm: 4.8403 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2040 loss: 1.2040 2022/10/15 08:57:44 - mmengine - INFO - Epoch(train) [86][440/940] lr: 1.0000e-04 eta: 2:14:03 time: 0.5869 data_time: 0.0462 memory: 33630 grad_norm: 4.8168 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1632 loss: 1.1632 2022/10/15 08:57:56 - mmengine - INFO - Epoch(train) [86][460/940] lr: 1.0000e-04 eta: 2:13:51 time: 0.5831 data_time: 0.0382 memory: 33630 grad_norm: 4.7702 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0616 loss: 1.0616 2022/10/15 08:58:07 - mmengine - INFO - Epoch(train) [86][480/940] lr: 1.0000e-04 eta: 2:13:39 time: 0.5852 data_time: 0.0366 memory: 33630 grad_norm: 4.7449 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1826 loss: 1.1826 2022/10/15 08:58:19 - mmengine - INFO - Epoch(train) [86][500/940] lr: 1.0000e-04 eta: 2:13:27 time: 0.5805 data_time: 0.0338 memory: 33630 grad_norm: 4.7996 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2435 loss: 1.2435 2022/10/15 08:58:30 - mmengine - INFO - Epoch(train) [86][520/940] lr: 1.0000e-04 eta: 2:13:15 time: 0.5744 data_time: 0.0346 memory: 33630 grad_norm: 4.7832 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1547 loss: 1.1547 2022/10/15 08:58:42 - mmengine - INFO - Epoch(train) [86][540/940] lr: 1.0000e-04 eta: 2:13:04 time: 0.5822 data_time: 0.0317 memory: 33630 grad_norm: 4.7738 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2368 loss: 1.2368 2022/10/15 08:58:54 - mmengine - INFO - Epoch(train) [86][560/940] lr: 1.0000e-04 eta: 2:12:52 time: 0.5828 data_time: 0.0524 memory: 33630 grad_norm: 4.7122 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1291 loss: 1.1291 2022/10/15 08:59:05 - mmengine - INFO - Epoch(train) [86][580/940] lr: 1.0000e-04 eta: 2:12:40 time: 0.5816 data_time: 0.0338 memory: 33630 grad_norm: 4.8044 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1882 loss: 1.1882 2022/10/15 08:59:17 - mmengine - INFO - Epoch(train) [86][600/940] lr: 1.0000e-04 eta: 2:12:28 time: 0.5821 data_time: 0.0335 memory: 33630 grad_norm: 4.8376 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0650 loss: 1.0650 2022/10/15 08:59:29 - mmengine - INFO - Epoch(train) [86][620/940] lr: 1.0000e-04 eta: 2:12:16 time: 0.5871 data_time: 0.0405 memory: 33630 grad_norm: 4.7190 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.0865 loss: 1.0865 2022/10/15 08:59:40 - mmengine - INFO - Epoch(train) [86][640/940] lr: 1.0000e-04 eta: 2:12:05 time: 0.5819 data_time: 0.0377 memory: 33630 grad_norm: 4.8368 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2318 loss: 1.2318 2022/10/15 08:59:52 - mmengine - INFO - Epoch(train) [86][660/940] lr: 1.0000e-04 eta: 2:11:53 time: 0.5812 data_time: 0.0363 memory: 33630 grad_norm: 4.7143 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1306 loss: 1.1306 2022/10/15 09:00:04 - mmengine - INFO - Epoch(train) [86][680/940] lr: 1.0000e-04 eta: 2:11:41 time: 0.5791 data_time: 0.0416 memory: 33630 grad_norm: 4.8095 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1896 loss: 1.1896 2022/10/15 09:00:15 - mmengine - INFO - Epoch(train) [86][700/940] lr: 1.0000e-04 eta: 2:11:29 time: 0.5733 data_time: 0.0422 memory: 33630 grad_norm: 4.8482 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0912 loss: 1.0912 2022/10/15 09:00:27 - mmengine - INFO - Epoch(train) [86][720/940] lr: 1.0000e-04 eta: 2:11:17 time: 0.5847 data_time: 0.0506 memory: 33630 grad_norm: 4.7608 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1669 loss: 1.1669 2022/10/15 09:00:38 - mmengine - INFO - Epoch(train) [86][740/940] lr: 1.0000e-04 eta: 2:11:05 time: 0.5749 data_time: 0.0414 memory: 33630 grad_norm: 4.8584 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.1282 loss: 1.1282 2022/10/15 09:00:50 - mmengine - INFO - Epoch(train) [86][760/940] lr: 1.0000e-04 eta: 2:10:54 time: 0.5937 data_time: 0.0461 memory: 33630 grad_norm: 4.7710 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1336 loss: 1.1336 2022/10/15 09:01:02 - mmengine - INFO - Epoch(train) [86][780/940] lr: 1.0000e-04 eta: 2:10:42 time: 0.5758 data_time: 0.0342 memory: 33630 grad_norm: 4.8433 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2067 loss: 1.2067 2022/10/15 09:01:13 - mmengine - INFO - Epoch(train) [86][800/940] lr: 1.0000e-04 eta: 2:10:30 time: 0.5896 data_time: 0.0410 memory: 33630 grad_norm: 4.8092 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1833 loss: 1.1833 2022/10/15 09:01:25 - mmengine - INFO - Epoch(train) [86][820/940] lr: 1.0000e-04 eta: 2:10:18 time: 0.5780 data_time: 0.0396 memory: 33630 grad_norm: 4.7675 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1545 loss: 1.1545 2022/10/15 09:01:37 - mmengine - INFO - Epoch(train) [86][840/940] lr: 1.0000e-04 eta: 2:10:07 time: 0.5790 data_time: 0.0431 memory: 33630 grad_norm: 4.8639 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1852 loss: 1.1852 2022/10/15 09:01:48 - mmengine - INFO - Epoch(train) [86][860/940] lr: 1.0000e-04 eta: 2:09:55 time: 0.5912 data_time: 0.0382 memory: 33630 grad_norm: 4.8768 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2370 loss: 1.2370 2022/10/15 09:02:00 - mmengine - INFO - Epoch(train) [86][880/940] lr: 1.0000e-04 eta: 2:09:43 time: 0.5812 data_time: 0.0320 memory: 33630 grad_norm: 4.7732 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0617 loss: 1.0617 2022/10/15 09:02:12 - mmengine - INFO - Epoch(train) [86][900/940] lr: 1.0000e-04 eta: 2:09:31 time: 0.5829 data_time: 0.0423 memory: 33630 grad_norm: 4.7759 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1530 loss: 1.1530 2022/10/15 09:02:23 - mmengine - INFO - Epoch(train) [86][920/940] lr: 1.0000e-04 eta: 2:09:19 time: 0.5793 data_time: 0.0373 memory: 33630 grad_norm: 4.8177 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2634 loss: 1.2634 2022/10/15 09:02:34 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 09:02:34 - mmengine - INFO - Epoch(train) [86][940/940] lr: 1.0000e-04 eta: 2:09:07 time: 0.5443 data_time: 0.0289 memory: 33630 grad_norm: 5.0887 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.0579 loss: 1.0579 2022/10/15 09:02:49 - mmengine - INFO - Epoch(val) [86][20/78] eta: 0:00:41 time: 0.7161 data_time: 0.5448 memory: 5967 2022/10/15 09:02:58 - mmengine - INFO - Epoch(val) [86][40/78] eta: 0:00:18 time: 0.4891 data_time: 0.3217 memory: 5967 2022/10/15 09:03:12 - mmengine - INFO - Epoch(val) [86][60/78] eta: 0:00:12 time: 0.6974 data_time: 0.5278 memory: 5967 2022/10/15 09:03:23 - mmengine - INFO - Epoch(val) [86][78/78] acc/top1: 0.6898 acc/top5: 0.8801 acc/mean1: 0.6897 2022/10/15 09:03:23 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_61.pth is removed 2022/10/15 09:03:24 - mmengine - INFO - The best checkpoint with 0.6898 acc/top1 at 86 epoch is saved to best_acc/top1_epoch_86.pth. 2022/10/15 09:03:41 - mmengine - INFO - Epoch(train) [87][20/940] lr: 1.0000e-04 eta: 2:08:56 time: 0.8461 data_time: 0.3091 memory: 33630 grad_norm: 4.6798 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0721 loss: 1.0721 2022/10/15 09:03:52 - mmengine - INFO - Epoch(train) [87][40/940] lr: 1.0000e-04 eta: 2:08:45 time: 0.5769 data_time: 0.0309 memory: 33630 grad_norm: 4.7721 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.0004 loss: 1.0004 2022/10/15 09:04:04 - mmengine - INFO - Epoch(train) [87][60/940] lr: 1.0000e-04 eta: 2:08:33 time: 0.5828 data_time: 0.0377 memory: 33630 grad_norm: 4.8294 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.1318 loss: 1.1318 2022/10/15 09:04:16 - mmengine - INFO - Epoch(train) [87][80/940] lr: 1.0000e-04 eta: 2:08:21 time: 0.5897 data_time: 0.0336 memory: 33630 grad_norm: 4.7537 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.0446 loss: 1.0446 2022/10/15 09:04:28 - mmengine - INFO - Epoch(train) [87][100/940] lr: 1.0000e-04 eta: 2:08:09 time: 0.5938 data_time: 0.0379 memory: 33630 grad_norm: 4.8596 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2589 loss: 1.2589 2022/10/15 09:04:39 - mmengine - INFO - Epoch(train) [87][120/940] lr: 1.0000e-04 eta: 2:07:58 time: 0.5782 data_time: 0.0363 memory: 33630 grad_norm: 4.8383 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2015 loss: 1.2015 2022/10/15 09:04:51 - mmengine - INFO - Epoch(train) [87][140/940] lr: 1.0000e-04 eta: 2:07:46 time: 0.5863 data_time: 0.0373 memory: 33630 grad_norm: 4.7796 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0861 loss: 1.0861 2022/10/15 09:05:02 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 09:05:02 - mmengine - INFO - Epoch(train) [87][160/940] lr: 1.0000e-04 eta: 2:07:34 time: 0.5827 data_time: 0.0380 memory: 33630 grad_norm: 4.7814 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1479 loss: 1.1479 2022/10/15 09:05:14 - mmengine - INFO - Epoch(train) [87][180/940] lr: 1.0000e-04 eta: 2:07:22 time: 0.5772 data_time: 0.0321 memory: 33630 grad_norm: 4.8041 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1558 loss: 1.1558 2022/10/15 09:05:26 - mmengine - INFO - Epoch(train) [87][200/940] lr: 1.0000e-04 eta: 2:07:10 time: 0.5888 data_time: 0.0358 memory: 33630 grad_norm: 4.7441 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0939 loss: 1.0939 2022/10/15 09:05:38 - mmengine - INFO - Epoch(train) [87][220/940] lr: 1.0000e-04 eta: 2:06:59 time: 0.5941 data_time: 0.0448 memory: 33630 grad_norm: 4.8862 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2414 loss: 1.2414 2022/10/15 09:05:49 - mmengine - INFO - Epoch(train) [87][240/940] lr: 1.0000e-04 eta: 2:06:47 time: 0.5779 data_time: 0.0350 memory: 33630 grad_norm: 4.6738 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2097 loss: 1.2097 2022/10/15 09:06:01 - mmengine - INFO - Epoch(train) [87][260/940] lr: 1.0000e-04 eta: 2:06:35 time: 0.5800 data_time: 0.0412 memory: 33630 grad_norm: 4.7480 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1119 loss: 1.1119 2022/10/15 09:06:13 - mmengine - INFO - Epoch(train) [87][280/940] lr: 1.0000e-04 eta: 2:06:23 time: 0.5874 data_time: 0.0396 memory: 33630 grad_norm: 4.6299 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0362 loss: 1.0362 2022/10/15 09:06:24 - mmengine - INFO - Epoch(train) [87][300/940] lr: 1.0000e-04 eta: 2:06:11 time: 0.5825 data_time: 0.0363 memory: 33630 grad_norm: 4.8810 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1509 loss: 1.1509 2022/10/15 09:06:36 - mmengine - INFO - Epoch(train) [87][320/940] lr: 1.0000e-04 eta: 2:06:00 time: 0.5845 data_time: 0.0413 memory: 33630 grad_norm: 4.7853 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3243 loss: 1.3243 2022/10/15 09:06:47 - mmengine - INFO - Epoch(train) [87][340/940] lr: 1.0000e-04 eta: 2:05:48 time: 0.5741 data_time: 0.0328 memory: 33630 grad_norm: 4.7277 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1342 loss: 1.1342 2022/10/15 09:06:59 - mmengine - INFO - Epoch(train) [87][360/940] lr: 1.0000e-04 eta: 2:05:36 time: 0.5798 data_time: 0.0326 memory: 33630 grad_norm: 4.9615 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1835 loss: 1.1835 2022/10/15 09:07:11 - mmengine - INFO - Epoch(train) [87][380/940] lr: 1.0000e-04 eta: 2:05:24 time: 0.5927 data_time: 0.0408 memory: 33630 grad_norm: 4.6890 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1999 loss: 1.1999 2022/10/15 09:07:22 - mmengine - INFO - Epoch(train) [87][400/940] lr: 1.0000e-04 eta: 2:05:12 time: 0.5796 data_time: 0.0320 memory: 33630 grad_norm: 4.7284 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0932 loss: 1.0932 2022/10/15 09:07:34 - mmengine - INFO - Epoch(train) [87][420/940] lr: 1.0000e-04 eta: 2:05:01 time: 0.5769 data_time: 0.0405 memory: 33630 grad_norm: 4.7761 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1805 loss: 1.1805 2022/10/15 09:07:46 - mmengine - INFO - Epoch(train) [87][440/940] lr: 1.0000e-04 eta: 2:04:49 time: 0.5894 data_time: 0.0393 memory: 33630 grad_norm: 4.7107 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1323 loss: 1.1323 2022/10/15 09:07:57 - mmengine - INFO - Epoch(train) [87][460/940] lr: 1.0000e-04 eta: 2:04:37 time: 0.5806 data_time: 0.0417 memory: 33630 grad_norm: 4.7148 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.2010 loss: 1.2010 2022/10/15 09:08:09 - mmengine - INFO - Epoch(train) [87][480/940] lr: 1.0000e-04 eta: 2:04:25 time: 0.5940 data_time: 0.0368 memory: 33630 grad_norm: 4.8137 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1383 loss: 1.1383 2022/10/15 09:08:21 - mmengine - INFO - Epoch(train) [87][500/940] lr: 1.0000e-04 eta: 2:04:14 time: 0.5918 data_time: 0.0333 memory: 33630 grad_norm: 4.8436 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.1338 loss: 1.1338 2022/10/15 09:08:33 - mmengine - INFO - Epoch(train) [87][520/940] lr: 1.0000e-04 eta: 2:04:02 time: 0.5832 data_time: 0.0463 memory: 33630 grad_norm: 4.7973 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.1424 loss: 1.1424 2022/10/15 09:08:44 - mmengine - INFO - Epoch(train) [87][540/940] lr: 1.0000e-04 eta: 2:03:50 time: 0.5733 data_time: 0.0370 memory: 33630 grad_norm: 4.8069 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 1.0624 loss: 1.0624 2022/10/15 09:08:56 - mmengine - INFO - Epoch(train) [87][560/940] lr: 1.0000e-04 eta: 2:03:38 time: 0.5862 data_time: 0.0313 memory: 33630 grad_norm: 4.8130 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1895 loss: 1.1895 2022/10/15 09:09:07 - mmengine - INFO - Epoch(train) [87][580/940] lr: 1.0000e-04 eta: 2:03:26 time: 0.5744 data_time: 0.0321 memory: 33630 grad_norm: 4.8620 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2290 loss: 1.2290 2022/10/15 09:09:19 - mmengine - INFO - Epoch(train) [87][600/940] lr: 1.0000e-04 eta: 2:03:14 time: 0.5672 data_time: 0.0324 memory: 33630 grad_norm: 4.7662 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2534 loss: 1.2534 2022/10/15 09:09:31 - mmengine - INFO - Epoch(train) [87][620/940] lr: 1.0000e-04 eta: 2:03:03 time: 0.5925 data_time: 0.0466 memory: 33630 grad_norm: 4.8164 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1643 loss: 1.1643 2022/10/15 09:09:42 - mmengine - INFO - Epoch(train) [87][640/940] lr: 1.0000e-04 eta: 2:02:51 time: 0.5874 data_time: 0.0459 memory: 33630 grad_norm: 4.8247 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.1856 loss: 1.1856 2022/10/15 09:09:54 - mmengine - INFO - Epoch(train) [87][660/940] lr: 1.0000e-04 eta: 2:02:39 time: 0.5921 data_time: 0.0479 memory: 33630 grad_norm: 4.7503 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2332 loss: 1.2332 2022/10/15 09:10:06 - mmengine - INFO - Epoch(train) [87][680/940] lr: 1.0000e-04 eta: 2:02:27 time: 0.5928 data_time: 0.0363 memory: 33630 grad_norm: 4.7386 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1383 loss: 1.1383 2022/10/15 09:10:18 - mmengine - INFO - Epoch(train) [87][700/940] lr: 1.0000e-04 eta: 2:02:16 time: 0.5799 data_time: 0.0393 memory: 33630 grad_norm: 4.8028 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0709 loss: 1.0709 2022/10/15 09:10:30 - mmengine - INFO - Epoch(train) [87][720/940] lr: 1.0000e-04 eta: 2:02:04 time: 0.5893 data_time: 0.0457 memory: 33630 grad_norm: 4.7026 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2523 loss: 1.2523 2022/10/15 09:10:41 - mmengine - INFO - Epoch(train) [87][740/940] lr: 1.0000e-04 eta: 2:01:52 time: 0.5716 data_time: 0.0338 memory: 33630 grad_norm: 4.8758 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1819 loss: 1.1819 2022/10/15 09:10:53 - mmengine - INFO - Epoch(train) [87][760/940] lr: 1.0000e-04 eta: 2:01:40 time: 0.5776 data_time: 0.0442 memory: 33630 grad_norm: 4.8969 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0879 loss: 1.0879 2022/10/15 09:11:04 - mmengine - INFO - Epoch(train) [87][780/940] lr: 1.0000e-04 eta: 2:01:28 time: 0.5911 data_time: 0.0415 memory: 33630 grad_norm: 4.7259 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1679 loss: 1.1679 2022/10/15 09:11:16 - mmengine - INFO - Epoch(train) [87][800/940] lr: 1.0000e-04 eta: 2:01:17 time: 0.5813 data_time: 0.0346 memory: 33630 grad_norm: 4.9044 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2112 loss: 1.2112 2022/10/15 09:11:28 - mmengine - INFO - Epoch(train) [87][820/940] lr: 1.0000e-04 eta: 2:01:05 time: 0.5820 data_time: 0.0393 memory: 33630 grad_norm: 4.8090 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0319 loss: 1.0319 2022/10/15 09:11:39 - mmengine - INFO - Epoch(train) [87][840/940] lr: 1.0000e-04 eta: 2:00:53 time: 0.5909 data_time: 0.0386 memory: 33630 grad_norm: 4.8438 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1136 loss: 1.1136 2022/10/15 09:11:51 - mmengine - INFO - Epoch(train) [87][860/940] lr: 1.0000e-04 eta: 2:00:41 time: 0.5750 data_time: 0.0323 memory: 33630 grad_norm: 4.7576 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0748 loss: 1.0748 2022/10/15 09:12:02 - mmengine - INFO - Epoch(train) [87][880/940] lr: 1.0000e-04 eta: 2:00:29 time: 0.5721 data_time: 0.0330 memory: 33630 grad_norm: 4.8212 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2415 loss: 1.2415 2022/10/15 09:12:14 - mmengine - INFO - Epoch(train) [87][900/940] lr: 1.0000e-04 eta: 2:00:18 time: 0.5830 data_time: 0.0368 memory: 33630 grad_norm: 4.8580 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.1490 loss: 1.1490 2022/10/15 09:12:26 - mmengine - INFO - Epoch(train) [87][920/940] lr: 1.0000e-04 eta: 2:00:06 time: 0.5854 data_time: 0.0362 memory: 33630 grad_norm: 4.8449 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3258 loss: 1.3258 2022/10/15 09:12:37 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 09:12:37 - mmengine - INFO - Epoch(train) [87][940/940] lr: 1.0000e-04 eta: 1:59:54 time: 0.5445 data_time: 0.0287 memory: 33630 grad_norm: 4.9925 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.3270 loss: 1.3270 2022/10/15 09:12:37 - mmengine - INFO - Saving checkpoint at 87 epochs 2022/10/15 09:12:52 - mmengine - INFO - Epoch(val) [87][20/78] eta: 0:00:41 time: 0.7218 data_time: 0.5530 memory: 5967 2022/10/15 09:13:02 - mmengine - INFO - Epoch(val) [87][40/78] eta: 0:00:18 time: 0.4829 data_time: 0.3093 memory: 5967 2022/10/15 09:13:15 - mmengine - INFO - Epoch(val) [87][60/78] eta: 0:00:12 time: 0.6730 data_time: 0.5053 memory: 5967 2022/10/15 09:13:25 - mmengine - INFO - Epoch(val) [87][78/78] acc/top1: 0.6877 acc/top5: 0.8795 acc/mean1: 0.6876 2022/10/15 09:13:42 - mmengine - INFO - Epoch(train) [88][20/940] lr: 1.0000e-04 eta: 1:59:43 time: 0.8242 data_time: 0.2412 memory: 33630 grad_norm: 4.7503 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2129 loss: 1.2129 2022/10/15 09:13:54 - mmengine - INFO - Epoch(train) [88][40/940] lr: 1.0000e-04 eta: 1:59:31 time: 0.5807 data_time: 0.0347 memory: 33630 grad_norm: 4.7830 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1474 loss: 1.1474 2022/10/15 09:14:05 - mmengine - INFO - Epoch(train) [88][60/940] lr: 1.0000e-04 eta: 1:59:19 time: 0.5923 data_time: 0.0416 memory: 33630 grad_norm: 4.7686 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2187 loss: 1.2187 2022/10/15 09:14:17 - mmengine - INFO - Epoch(train) [88][80/940] lr: 1.0000e-04 eta: 1:59:08 time: 0.5930 data_time: 0.0320 memory: 33630 grad_norm: 4.8647 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2596 loss: 1.2596 2022/10/15 09:14:29 - mmengine - INFO - Epoch(train) [88][100/940] lr: 1.0000e-04 eta: 1:58:56 time: 0.5910 data_time: 0.0326 memory: 33630 grad_norm: 4.7160 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1190 loss: 1.1190 2022/10/15 09:14:41 - mmengine - INFO - Epoch(train) [88][120/940] lr: 1.0000e-04 eta: 1:58:44 time: 0.5839 data_time: 0.0438 memory: 33630 grad_norm: 4.7809 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1220 loss: 1.1220 2022/10/15 09:14:53 - mmengine - INFO - Epoch(train) [88][140/940] lr: 1.0000e-04 eta: 1:58:32 time: 0.5878 data_time: 0.0323 memory: 33630 grad_norm: 4.8417 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1255 loss: 1.1255 2022/10/15 09:15:04 - mmengine - INFO - Epoch(train) [88][160/940] lr: 1.0000e-04 eta: 1:58:20 time: 0.5823 data_time: 0.0396 memory: 33630 grad_norm: 4.7951 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0754 loss: 1.0754 2022/10/15 09:15:16 - mmengine - INFO - Epoch(train) [88][180/940] lr: 1.0000e-04 eta: 1:58:09 time: 0.5743 data_time: 0.0403 memory: 33630 grad_norm: 4.7150 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0564 loss: 1.0564 2022/10/15 09:15:27 - mmengine - INFO - Epoch(train) [88][200/940] lr: 1.0000e-04 eta: 1:57:57 time: 0.5879 data_time: 0.0358 memory: 33630 grad_norm: 4.7824 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1827 loss: 1.1827 2022/10/15 09:15:39 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 09:15:39 - mmengine - INFO - Epoch(train) [88][220/940] lr: 1.0000e-04 eta: 1:57:45 time: 0.5797 data_time: 0.0439 memory: 33630 grad_norm: 4.7994 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.0234 loss: 1.0234 2022/10/15 09:15:51 - mmengine - INFO - Epoch(train) [88][240/940] lr: 1.0000e-04 eta: 1:57:33 time: 0.5807 data_time: 0.0316 memory: 33630 grad_norm: 4.8453 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2055 loss: 1.2055 2022/10/15 09:16:02 - mmengine - INFO - Epoch(train) [88][260/940] lr: 1.0000e-04 eta: 1:57:21 time: 0.5841 data_time: 0.0339 memory: 33630 grad_norm: 4.6626 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0998 loss: 1.0998 2022/10/15 09:16:14 - mmengine - INFO - Epoch(train) [88][280/940] lr: 1.0000e-04 eta: 1:57:10 time: 0.5864 data_time: 0.0333 memory: 33630 grad_norm: 4.7964 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1501 loss: 1.1501 2022/10/15 09:16:26 - mmengine - INFO - Epoch(train) [88][300/940] lr: 1.0000e-04 eta: 1:56:58 time: 0.5740 data_time: 0.0350 memory: 33630 grad_norm: 4.8105 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0246 loss: 1.0246 2022/10/15 09:16:37 - mmengine - INFO - Epoch(train) [88][320/940] lr: 1.0000e-04 eta: 1:56:46 time: 0.5824 data_time: 0.0353 memory: 33630 grad_norm: 4.8496 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2653 loss: 1.2653 2022/10/15 09:16:49 - mmengine - INFO - Epoch(train) [88][340/940] lr: 1.0000e-04 eta: 1:56:34 time: 0.5770 data_time: 0.0375 memory: 33630 grad_norm: 4.7667 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.0708 loss: 1.0708 2022/10/15 09:17:00 - mmengine - INFO - Epoch(train) [88][360/940] lr: 1.0000e-04 eta: 1:56:22 time: 0.5800 data_time: 0.0322 memory: 33630 grad_norm: 4.7099 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1181 loss: 1.1181 2022/10/15 09:17:12 - mmengine - INFO - Epoch(train) [88][380/940] lr: 1.0000e-04 eta: 1:56:11 time: 0.5666 data_time: 0.0394 memory: 33630 grad_norm: 4.8300 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.2356 loss: 1.2356 2022/10/15 09:17:23 - mmengine - INFO - Epoch(train) [88][400/940] lr: 1.0000e-04 eta: 1:55:59 time: 0.5805 data_time: 0.0375 memory: 33630 grad_norm: 4.8265 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0495 loss: 1.0495 2022/10/15 09:17:35 - mmengine - INFO - Epoch(train) [88][420/940] lr: 1.0000e-04 eta: 1:55:47 time: 0.5762 data_time: 0.0321 memory: 33630 grad_norm: 4.9092 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2406 loss: 1.2406 2022/10/15 09:17:47 - mmengine - INFO - Epoch(train) [88][440/940] lr: 1.0000e-04 eta: 1:55:35 time: 0.5859 data_time: 0.0437 memory: 33630 grad_norm: 4.8264 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1114 loss: 1.1114 2022/10/15 09:17:58 - mmengine - INFO - Epoch(train) [88][460/940] lr: 1.0000e-04 eta: 1:55:23 time: 0.5835 data_time: 0.0362 memory: 33630 grad_norm: 4.7808 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.0827 loss: 1.0827 2022/10/15 09:18:10 - mmengine - INFO - Epoch(train) [88][480/940] lr: 1.0000e-04 eta: 1:55:12 time: 0.5874 data_time: 0.0378 memory: 33630 grad_norm: 4.8258 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.3093 loss: 1.3093 2022/10/15 09:18:22 - mmengine - INFO - Epoch(train) [88][500/940] lr: 1.0000e-04 eta: 1:55:00 time: 0.5792 data_time: 0.0392 memory: 33630 grad_norm: 4.8498 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0863 loss: 1.0863 2022/10/15 09:18:33 - mmengine - INFO - Epoch(train) [88][520/940] lr: 1.0000e-04 eta: 1:54:48 time: 0.5826 data_time: 0.0329 memory: 33630 grad_norm: 4.6668 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1723 loss: 1.1723 2022/10/15 09:18:45 - mmengine - INFO - Epoch(train) [88][540/940] lr: 1.0000e-04 eta: 1:54:36 time: 0.5809 data_time: 0.0372 memory: 33630 grad_norm: 4.8989 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1668 loss: 1.1668 2022/10/15 09:18:57 - mmengine - INFO - Epoch(train) [88][560/940] lr: 1.0000e-04 eta: 1:54:24 time: 0.5876 data_time: 0.0465 memory: 33630 grad_norm: 4.8588 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2850 loss: 1.2850 2022/10/15 09:19:08 - mmengine - INFO - Epoch(train) [88][580/940] lr: 1.0000e-04 eta: 1:54:13 time: 0.5812 data_time: 0.0396 memory: 33630 grad_norm: 4.7264 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3449 loss: 1.3449 2022/10/15 09:19:20 - mmengine - INFO - Epoch(train) [88][600/940] lr: 1.0000e-04 eta: 1:54:01 time: 0.5783 data_time: 0.0411 memory: 33630 grad_norm: 4.7766 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1933 loss: 1.1933 2022/10/15 09:19:32 - mmengine - INFO - Epoch(train) [88][620/940] lr: 1.0000e-04 eta: 1:53:49 time: 0.5849 data_time: 0.0377 memory: 33630 grad_norm: 4.8132 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.2021 loss: 1.2021 2022/10/15 09:19:43 - mmengine - INFO - Epoch(train) [88][640/940] lr: 1.0000e-04 eta: 1:53:37 time: 0.5837 data_time: 0.0444 memory: 33630 grad_norm: 4.8323 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1588 loss: 1.1588 2022/10/15 09:19:55 - mmengine - INFO - Epoch(train) [88][660/940] lr: 1.0000e-04 eta: 1:53:25 time: 0.5953 data_time: 0.0417 memory: 33630 grad_norm: 4.7464 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1616 loss: 1.1616 2022/10/15 09:20:07 - mmengine - INFO - Epoch(train) [88][680/940] lr: 1.0000e-04 eta: 1:53:14 time: 0.5767 data_time: 0.0304 memory: 33630 grad_norm: 4.8730 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1938 loss: 1.1938 2022/10/15 09:20:18 - mmengine - INFO - Epoch(train) [88][700/940] lr: 1.0000e-04 eta: 1:53:02 time: 0.5753 data_time: 0.0352 memory: 33630 grad_norm: 4.6797 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0608 loss: 1.0608 2022/10/15 09:20:30 - mmengine - INFO - Epoch(train) [88][720/940] lr: 1.0000e-04 eta: 1:52:50 time: 0.5741 data_time: 0.0330 memory: 33630 grad_norm: 4.8373 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2582 loss: 1.2582 2022/10/15 09:20:42 - mmengine - INFO - Epoch(train) [88][740/940] lr: 1.0000e-04 eta: 1:52:38 time: 0.5944 data_time: 0.0387 memory: 33630 grad_norm: 4.8185 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.0805 loss: 1.0805 2022/10/15 09:20:53 - mmengine - INFO - Epoch(train) [88][760/940] lr: 1.0000e-04 eta: 1:52:26 time: 0.5704 data_time: 0.0358 memory: 33630 grad_norm: 4.8287 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1181 loss: 1.1181 2022/10/15 09:21:05 - mmengine - INFO - Epoch(train) [88][780/940] lr: 1.0000e-04 eta: 1:52:15 time: 0.5884 data_time: 0.0319 memory: 33630 grad_norm: 4.9198 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1481 loss: 1.1481 2022/10/15 09:21:17 - mmengine - INFO - Epoch(train) [88][800/940] lr: 1.0000e-04 eta: 1:52:03 time: 0.5909 data_time: 0.0399 memory: 33630 grad_norm: 4.7233 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0225 loss: 1.0225 2022/10/15 09:21:28 - mmengine - INFO - Epoch(train) [88][820/940] lr: 1.0000e-04 eta: 1:51:51 time: 0.5758 data_time: 0.0356 memory: 33630 grad_norm: 4.7922 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.1278 loss: 1.1278 2022/10/15 09:21:40 - mmengine - INFO - Epoch(train) [88][840/940] lr: 1.0000e-04 eta: 1:51:39 time: 0.5808 data_time: 0.0366 memory: 33630 grad_norm: 4.8384 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1488 loss: 1.1488 2022/10/15 09:21:51 - mmengine - INFO - Epoch(train) [88][860/940] lr: 1.0000e-04 eta: 1:51:28 time: 0.5869 data_time: 0.0334 memory: 33630 grad_norm: 4.8485 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2216 loss: 1.2216 2022/10/15 09:22:03 - mmengine - INFO - Epoch(train) [88][880/940] lr: 1.0000e-04 eta: 1:51:16 time: 0.5770 data_time: 0.0353 memory: 33630 grad_norm: 4.8628 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1384 loss: 1.1384 2022/10/15 09:22:15 - mmengine - INFO - Epoch(train) [88][900/940] lr: 1.0000e-04 eta: 1:51:04 time: 0.5824 data_time: 0.0345 memory: 33630 grad_norm: 4.7525 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1091 loss: 1.1091 2022/10/15 09:22:26 - mmengine - INFO - Epoch(train) [88][920/940] lr: 1.0000e-04 eta: 1:50:52 time: 0.5727 data_time: 0.0387 memory: 33630 grad_norm: 4.8115 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0928 loss: 1.0928 2022/10/15 09:22:37 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 09:22:37 - mmengine - INFO - Epoch(train) [88][940/940] lr: 1.0000e-04 eta: 1:50:40 time: 0.5380 data_time: 0.0297 memory: 33630 grad_norm: 5.1800 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.1805 loss: 1.1805 2022/10/15 09:22:51 - mmengine - INFO - Epoch(val) [88][20/78] eta: 0:00:41 time: 0.7161 data_time: 0.5469 memory: 5967 2022/10/15 09:23:01 - mmengine - INFO - Epoch(val) [88][40/78] eta: 0:00:19 time: 0.5010 data_time: 0.3314 memory: 5967 2022/10/15 09:23:14 - mmengine - INFO - Epoch(val) [88][60/78] eta: 0:00:11 time: 0.6555 data_time: 0.4844 memory: 5967 2022/10/15 09:23:25 - mmengine - INFO - Epoch(val) [88][78/78] acc/top1: 0.6880 acc/top5: 0.8788 acc/mean1: 0.6879 2022/10/15 09:23:42 - mmengine - INFO - Epoch(train) [89][20/940] lr: 1.0000e-04 eta: 1:50:29 time: 0.8148 data_time: 0.2490 memory: 33630 grad_norm: 4.8228 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1663 loss: 1.1663 2022/10/15 09:23:53 - mmengine - INFO - Epoch(train) [89][40/940] lr: 1.0000e-04 eta: 1:50:17 time: 0.5808 data_time: 0.0374 memory: 33630 grad_norm: 4.8231 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1227 loss: 1.1227 2022/10/15 09:24:05 - mmengine - INFO - Epoch(train) [89][60/940] lr: 1.0000e-04 eta: 1:50:06 time: 0.6111 data_time: 0.0373 memory: 33630 grad_norm: 4.7686 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1611 loss: 1.1611 2022/10/15 09:24:17 - mmengine - INFO - Epoch(train) [89][80/940] lr: 1.0000e-04 eta: 1:49:54 time: 0.5770 data_time: 0.0427 memory: 33630 grad_norm: 4.7665 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1931 loss: 1.1931 2022/10/15 09:24:29 - mmengine - INFO - Epoch(train) [89][100/940] lr: 1.0000e-04 eta: 1:49:42 time: 0.5967 data_time: 0.0431 memory: 33630 grad_norm: 4.7820 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1682 loss: 1.1682 2022/10/15 09:24:41 - mmengine - INFO - Epoch(train) [89][120/940] lr: 1.0000e-04 eta: 1:49:30 time: 0.5900 data_time: 0.0342 memory: 33630 grad_norm: 4.8844 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2370 loss: 1.2370 2022/10/15 09:24:52 - mmengine - INFO - Epoch(train) [89][140/940] lr: 1.0000e-04 eta: 1:49:18 time: 0.5855 data_time: 0.0365 memory: 33630 grad_norm: 4.7832 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2378 loss: 1.2378 2022/10/15 09:25:04 - mmengine - INFO - Epoch(train) [89][160/940] lr: 1.0000e-04 eta: 1:49:07 time: 0.5886 data_time: 0.0453 memory: 33630 grad_norm: 4.8337 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1960 loss: 1.1960 2022/10/15 09:25:16 - mmengine - INFO - Epoch(train) [89][180/940] lr: 1.0000e-04 eta: 1:48:55 time: 0.5937 data_time: 0.0406 memory: 33630 grad_norm: 4.7141 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.1775 loss: 1.1775 2022/10/15 09:25:28 - mmengine - INFO - Epoch(train) [89][200/940] lr: 1.0000e-04 eta: 1:48:43 time: 0.5734 data_time: 0.0312 memory: 33630 grad_norm: 4.9104 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2106 loss: 1.2106 2022/10/15 09:25:39 - mmengine - INFO - Epoch(train) [89][220/940] lr: 1.0000e-04 eta: 1:48:31 time: 0.5758 data_time: 0.0339 memory: 33630 grad_norm: 5.0029 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1898 loss: 1.1898 2022/10/15 09:25:51 - mmengine - INFO - Epoch(train) [89][240/940] lr: 1.0000e-04 eta: 1:48:19 time: 0.5898 data_time: 0.0384 memory: 33630 grad_norm: 4.7204 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0978 loss: 1.0978 2022/10/15 09:26:03 - mmengine - INFO - Epoch(train) [89][260/940] lr: 1.0000e-04 eta: 1:48:08 time: 0.5866 data_time: 0.0427 memory: 33630 grad_norm: 4.7971 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0498 loss: 1.0498 2022/10/15 09:26:15 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 09:26:15 - mmengine - INFO - Epoch(train) [89][280/940] lr: 1.0000e-04 eta: 1:47:56 time: 0.6014 data_time: 0.0304 memory: 33630 grad_norm: 4.7798 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1447 loss: 1.1447 2022/10/15 09:26:26 - mmengine - INFO - Epoch(train) [89][300/940] lr: 1.0000e-04 eta: 1:47:44 time: 0.5767 data_time: 0.0387 memory: 33630 grad_norm: 4.8344 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1677 loss: 1.1677 2022/10/15 09:26:38 - mmengine - INFO - Epoch(train) [89][320/940] lr: 1.0000e-04 eta: 1:47:32 time: 0.5842 data_time: 0.0314 memory: 33630 grad_norm: 4.6846 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1423 loss: 1.1423 2022/10/15 09:26:49 - mmengine - INFO - Epoch(train) [89][340/940] lr: 1.0000e-04 eta: 1:47:21 time: 0.5740 data_time: 0.0352 memory: 33630 grad_norm: 4.8539 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1981 loss: 1.1981 2022/10/15 09:27:01 - mmengine - INFO - Epoch(train) [89][360/940] lr: 1.0000e-04 eta: 1:47:09 time: 0.5860 data_time: 0.0402 memory: 33630 grad_norm: 4.9115 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1989 loss: 1.1989 2022/10/15 09:27:13 - mmengine - INFO - Epoch(train) [89][380/940] lr: 1.0000e-04 eta: 1:46:57 time: 0.5750 data_time: 0.0410 memory: 33630 grad_norm: 4.8786 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0843 loss: 1.0843 2022/10/15 09:27:24 - mmengine - INFO - Epoch(train) [89][400/940] lr: 1.0000e-04 eta: 1:46:45 time: 0.5833 data_time: 0.0336 memory: 33630 grad_norm: 4.7861 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2422 loss: 1.2422 2022/10/15 09:27:36 - mmengine - INFO - Epoch(train) [89][420/940] lr: 1.0000e-04 eta: 1:46:33 time: 0.5824 data_time: 0.0380 memory: 33630 grad_norm: 4.7703 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1899 loss: 1.1899 2022/10/15 09:27:48 - mmengine - INFO - Epoch(train) [89][440/940] lr: 1.0000e-04 eta: 1:46:22 time: 0.5825 data_time: 0.0429 memory: 33630 grad_norm: 4.7278 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1049 loss: 1.1049 2022/10/15 09:27:59 - mmengine - INFO - Epoch(train) [89][460/940] lr: 1.0000e-04 eta: 1:46:10 time: 0.5749 data_time: 0.0332 memory: 33630 grad_norm: 4.7679 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1406 loss: 1.1406 2022/10/15 09:28:11 - mmengine - INFO - Epoch(train) [89][480/940] lr: 1.0000e-04 eta: 1:45:58 time: 0.5859 data_time: 0.0339 memory: 33630 grad_norm: 4.9224 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1532 loss: 1.1532 2022/10/15 09:28:23 - mmengine - INFO - Epoch(train) [89][500/940] lr: 1.0000e-04 eta: 1:45:46 time: 0.5902 data_time: 0.0375 memory: 33630 grad_norm: 4.9312 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2963 loss: 1.2963 2022/10/15 09:28:34 - mmengine - INFO - Epoch(train) [89][520/940] lr: 1.0000e-04 eta: 1:45:34 time: 0.5769 data_time: 0.0378 memory: 33630 grad_norm: 4.8525 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2428 loss: 1.2428 2022/10/15 09:28:46 - mmengine - INFO - Epoch(train) [89][540/940] lr: 1.0000e-04 eta: 1:45:23 time: 0.5798 data_time: 0.0341 memory: 33630 grad_norm: 4.8429 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1762 loss: 1.1762 2022/10/15 09:28:57 - mmengine - INFO - Epoch(train) [89][560/940] lr: 1.0000e-04 eta: 1:45:11 time: 0.5868 data_time: 0.0401 memory: 33630 grad_norm: 4.8398 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3335 loss: 1.3335 2022/10/15 09:29:09 - mmengine - INFO - Epoch(train) [89][580/940] lr: 1.0000e-04 eta: 1:44:59 time: 0.5725 data_time: 0.0357 memory: 33630 grad_norm: 4.7939 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0940 loss: 1.0940 2022/10/15 09:29:21 - mmengine - INFO - Epoch(train) [89][600/940] lr: 1.0000e-04 eta: 1:44:47 time: 0.5813 data_time: 0.0467 memory: 33630 grad_norm: 4.7239 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1369 loss: 1.1369 2022/10/15 09:29:32 - mmengine - INFO - Epoch(train) [89][620/940] lr: 1.0000e-04 eta: 1:44:35 time: 0.5690 data_time: 0.0360 memory: 33630 grad_norm: 4.8660 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.0744 loss: 1.0744 2022/10/15 09:29:44 - mmengine - INFO - Epoch(train) [89][640/940] lr: 1.0000e-04 eta: 1:44:24 time: 0.5842 data_time: 0.0406 memory: 33630 grad_norm: 4.8435 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.0895 loss: 1.0895 2022/10/15 09:29:55 - mmengine - INFO - Epoch(train) [89][660/940] lr: 1.0000e-04 eta: 1:44:12 time: 0.5710 data_time: 0.0331 memory: 33630 grad_norm: 4.9120 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2662 loss: 1.2662 2022/10/15 09:30:07 - mmengine - INFO - Epoch(train) [89][680/940] lr: 1.0000e-04 eta: 1:44:00 time: 0.5772 data_time: 0.0406 memory: 33630 grad_norm: 4.7427 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1620 loss: 1.1620 2022/10/15 09:30:18 - mmengine - INFO - Epoch(train) [89][700/940] lr: 1.0000e-04 eta: 1:43:48 time: 0.5859 data_time: 0.0344 memory: 33630 grad_norm: 4.7949 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1766 loss: 1.1766 2022/10/15 09:30:30 - mmengine - INFO - Epoch(train) [89][720/940] lr: 1.0000e-04 eta: 1:43:36 time: 0.5914 data_time: 0.0392 memory: 33630 grad_norm: 4.8806 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0759 loss: 1.0759 2022/10/15 09:30:42 - mmengine - INFO - Epoch(train) [89][740/940] lr: 1.0000e-04 eta: 1:43:25 time: 0.5731 data_time: 0.0354 memory: 33630 grad_norm: 4.8803 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2218 loss: 1.2218 2022/10/15 09:30:53 - mmengine - INFO - Epoch(train) [89][760/940] lr: 1.0000e-04 eta: 1:43:13 time: 0.5887 data_time: 0.0369 memory: 33630 grad_norm: 4.9074 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1528 loss: 1.1528 2022/10/15 09:31:05 - mmengine - INFO - Epoch(train) [89][780/940] lr: 1.0000e-04 eta: 1:43:01 time: 0.5687 data_time: 0.0384 memory: 33630 grad_norm: 4.8325 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1001 loss: 1.1001 2022/10/15 09:31:16 - mmengine - INFO - Epoch(train) [89][800/940] lr: 1.0000e-04 eta: 1:42:49 time: 0.5853 data_time: 0.0306 memory: 33630 grad_norm: 4.7246 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0898 loss: 1.0898 2022/10/15 09:31:28 - mmengine - INFO - Epoch(train) [89][820/940] lr: 1.0000e-04 eta: 1:42:37 time: 0.5896 data_time: 0.0362 memory: 33630 grad_norm: 4.7882 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1203 loss: 1.1203 2022/10/15 09:31:40 - mmengine - INFO - Epoch(train) [89][840/940] lr: 1.0000e-04 eta: 1:42:26 time: 0.5764 data_time: 0.0339 memory: 33630 grad_norm: 4.8248 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2319 loss: 1.2319 2022/10/15 09:31:51 - mmengine - INFO - Epoch(train) [89][860/940] lr: 1.0000e-04 eta: 1:42:14 time: 0.5792 data_time: 0.0423 memory: 33630 grad_norm: 4.7979 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2288 loss: 1.2288 2022/10/15 09:32:03 - mmengine - INFO - Epoch(train) [89][880/940] lr: 1.0000e-04 eta: 1:42:02 time: 0.5845 data_time: 0.0345 memory: 33630 grad_norm: 4.8242 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2019 loss: 1.2019 2022/10/15 09:32:15 - mmengine - INFO - Epoch(train) [89][900/940] lr: 1.0000e-04 eta: 1:41:50 time: 0.5926 data_time: 0.0346 memory: 33630 grad_norm: 4.8617 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1748 loss: 1.1748 2022/10/15 09:32:27 - mmengine - INFO - Epoch(train) [89][920/940] lr: 1.0000e-04 eta: 1:41:39 time: 0.5923 data_time: 0.0405 memory: 33630 grad_norm: 4.8009 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0353 loss: 1.0353 2022/10/15 09:32:38 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 09:32:38 - mmengine - INFO - Epoch(train) [89][940/940] lr: 1.0000e-04 eta: 1:41:27 time: 0.5457 data_time: 0.0371 memory: 33630 grad_norm: 5.0555 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.0729 loss: 1.0729 2022/10/15 09:32:52 - mmengine - INFO - Epoch(val) [89][20/78] eta: 0:00:41 time: 0.7163 data_time: 0.5449 memory: 5967 2022/10/15 09:33:02 - mmengine - INFO - Epoch(val) [89][40/78] eta: 0:00:18 time: 0.4804 data_time: 0.3125 memory: 5967 2022/10/15 09:33:15 - mmengine - INFO - Epoch(val) [89][60/78] eta: 0:00:11 time: 0.6453 data_time: 0.4758 memory: 5967 2022/10/15 09:33:26 - mmengine - INFO - Epoch(val) [89][78/78] acc/top1: 0.6884 acc/top5: 0.8785 acc/mean1: 0.6883 2022/10/15 09:33:43 - mmengine - INFO - Epoch(train) [90][20/940] lr: 1.0000e-04 eta: 1:41:16 time: 0.8415 data_time: 0.2499 memory: 33630 grad_norm: 4.8007 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0882 loss: 1.0882 2022/10/15 09:33:54 - mmengine - INFO - Epoch(train) [90][40/940] lr: 1.0000e-04 eta: 1:41:04 time: 0.5745 data_time: 0.0377 memory: 33630 grad_norm: 4.8776 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2707 loss: 1.2707 2022/10/15 09:34:06 - mmengine - INFO - Epoch(train) [90][60/940] lr: 1.0000e-04 eta: 1:40:52 time: 0.5959 data_time: 0.0420 memory: 33630 grad_norm: 4.7815 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.1458 loss: 1.1458 2022/10/15 09:34:18 - mmengine - INFO - Epoch(train) [90][80/940] lr: 1.0000e-04 eta: 1:40:40 time: 0.5749 data_time: 0.0332 memory: 33630 grad_norm: 4.8640 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.0865 loss: 1.0865 2022/10/15 09:34:30 - mmengine - INFO - Epoch(train) [90][100/940] lr: 1.0000e-04 eta: 1:40:28 time: 0.5808 data_time: 0.0366 memory: 33630 grad_norm: 4.8461 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1041 loss: 1.1041 2022/10/15 09:34:41 - mmengine - INFO - Epoch(train) [90][120/940] lr: 1.0000e-04 eta: 1:40:17 time: 0.5855 data_time: 0.0330 memory: 33630 grad_norm: 4.7471 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.0770 loss: 1.0770 2022/10/15 09:34:53 - mmengine - INFO - Epoch(train) [90][140/940] lr: 1.0000e-04 eta: 1:40:05 time: 0.5782 data_time: 0.0371 memory: 33630 grad_norm: 4.8290 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1579 loss: 1.1579 2022/10/15 09:35:04 - mmengine - INFO - Epoch(train) [90][160/940] lr: 1.0000e-04 eta: 1:39:53 time: 0.5765 data_time: 0.0342 memory: 33630 grad_norm: 4.7758 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0508 loss: 1.0508 2022/10/15 09:35:16 - mmengine - INFO - Epoch(train) [90][180/940] lr: 1.0000e-04 eta: 1:39:41 time: 0.5810 data_time: 0.0351 memory: 33630 grad_norm: 4.7792 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0454 loss: 1.0454 2022/10/15 09:35:27 - mmengine - INFO - Epoch(train) [90][200/940] lr: 1.0000e-04 eta: 1:39:29 time: 0.5714 data_time: 0.0340 memory: 33630 grad_norm: 4.8179 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2303 loss: 1.2303 2022/10/15 09:35:39 - mmengine - INFO - Epoch(train) [90][220/940] lr: 1.0000e-04 eta: 1:39:18 time: 0.5848 data_time: 0.0320 memory: 33630 grad_norm: 4.7056 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0437 loss: 1.0437 2022/10/15 09:35:51 - mmengine - INFO - Epoch(train) [90][240/940] lr: 1.0000e-04 eta: 1:39:06 time: 0.5964 data_time: 0.0349 memory: 33630 grad_norm: 4.8316 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2813 loss: 1.2813 2022/10/15 09:36:03 - mmengine - INFO - Epoch(train) [90][260/940] lr: 1.0000e-04 eta: 1:38:54 time: 0.5864 data_time: 0.0348 memory: 33630 grad_norm: 4.7368 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1648 loss: 1.1648 2022/10/15 09:36:14 - mmengine - INFO - Epoch(train) [90][280/940] lr: 1.0000e-04 eta: 1:38:42 time: 0.5840 data_time: 0.0322 memory: 33630 grad_norm: 4.8284 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2665 loss: 1.2665 2022/10/15 09:36:26 - mmengine - INFO - Epoch(train) [90][300/940] lr: 1.0000e-04 eta: 1:38:30 time: 0.5819 data_time: 0.0370 memory: 33630 grad_norm: 4.8684 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1533 loss: 1.1533 2022/10/15 09:36:38 - mmengine - INFO - Epoch(train) [90][320/940] lr: 1.0000e-04 eta: 1:38:19 time: 0.5941 data_time: 0.0542 memory: 33630 grad_norm: 4.8878 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0831 loss: 1.0831 2022/10/15 09:36:50 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 09:36:50 - mmengine - INFO - Epoch(train) [90][340/940] lr: 1.0000e-04 eta: 1:38:07 time: 0.5846 data_time: 0.0462 memory: 33630 grad_norm: 4.7812 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2338 loss: 1.2338 2022/10/15 09:37:01 - mmengine - INFO - Epoch(train) [90][360/940] lr: 1.0000e-04 eta: 1:37:55 time: 0.5775 data_time: 0.0370 memory: 33630 grad_norm: 4.7994 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1671 loss: 1.1671 2022/10/15 09:37:13 - mmengine - INFO - Epoch(train) [90][380/940] lr: 1.0000e-04 eta: 1:37:43 time: 0.5787 data_time: 0.0406 memory: 33630 grad_norm: 4.8112 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1554 loss: 1.1554 2022/10/15 09:37:24 - mmengine - INFO - Epoch(train) [90][400/940] lr: 1.0000e-04 eta: 1:37:32 time: 0.5790 data_time: 0.0324 memory: 33630 grad_norm: 4.7361 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2017 loss: 1.2017 2022/10/15 09:37:36 - mmengine - INFO - Epoch(train) [90][420/940] lr: 1.0000e-04 eta: 1:37:20 time: 0.5750 data_time: 0.0349 memory: 33630 grad_norm: 4.8687 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.0028 loss: 1.0028 2022/10/15 09:37:48 - mmengine - INFO - Epoch(train) [90][440/940] lr: 1.0000e-04 eta: 1:37:08 time: 0.5894 data_time: 0.0417 memory: 33630 grad_norm: 4.8102 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1360 loss: 1.1360 2022/10/15 09:37:59 - mmengine - INFO - Epoch(train) [90][460/940] lr: 1.0000e-04 eta: 1:36:56 time: 0.5798 data_time: 0.0402 memory: 33630 grad_norm: 4.8860 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2125 loss: 1.2125 2022/10/15 09:38:11 - mmengine - INFO - Epoch(train) [90][480/940] lr: 1.0000e-04 eta: 1:36:44 time: 0.5856 data_time: 0.0359 memory: 33630 grad_norm: 4.9019 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3844 loss: 1.3844 2022/10/15 09:38:23 - mmengine - INFO - Epoch(train) [90][500/940] lr: 1.0000e-04 eta: 1:36:33 time: 0.5852 data_time: 0.0416 memory: 33630 grad_norm: 4.8263 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1543 loss: 1.1543 2022/10/15 09:38:34 - mmengine - INFO - Epoch(train) [90][520/940] lr: 1.0000e-04 eta: 1:36:21 time: 0.5803 data_time: 0.0330 memory: 33630 grad_norm: 4.9465 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.2140 loss: 1.2140 2022/10/15 09:38:46 - mmengine - INFO - Epoch(train) [90][540/940] lr: 1.0000e-04 eta: 1:36:09 time: 0.5875 data_time: 0.0350 memory: 33630 grad_norm: 4.8120 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.1744 loss: 1.1744 2022/10/15 09:38:58 - mmengine - INFO - Epoch(train) [90][560/940] lr: 1.0000e-04 eta: 1:35:57 time: 0.5892 data_time: 0.0363 memory: 33630 grad_norm: 4.7948 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1341 loss: 1.1341 2022/10/15 09:39:10 - mmengine - INFO - Epoch(train) [90][580/940] lr: 1.0000e-04 eta: 1:35:45 time: 0.5856 data_time: 0.0317 memory: 33630 grad_norm: 4.8908 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2312 loss: 1.2312 2022/10/15 09:39:21 - mmengine - INFO - Epoch(train) [90][600/940] lr: 1.0000e-04 eta: 1:35:34 time: 0.5724 data_time: 0.0374 memory: 33630 grad_norm: 4.8489 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.1701 loss: 1.1701 2022/10/15 09:39:33 - mmengine - INFO - Epoch(train) [90][620/940] lr: 1.0000e-04 eta: 1:35:22 time: 0.5909 data_time: 0.0372 memory: 33630 grad_norm: 4.8037 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1280 loss: 1.1280 2022/10/15 09:39:44 - mmengine - INFO - Epoch(train) [90][640/940] lr: 1.0000e-04 eta: 1:35:10 time: 0.5834 data_time: 0.0311 memory: 33630 grad_norm: 4.8909 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2065 loss: 1.2065 2022/10/15 09:39:56 - mmengine - INFO - Epoch(train) [90][660/940] lr: 1.0000e-04 eta: 1:34:58 time: 0.5687 data_time: 0.0359 memory: 33630 grad_norm: 4.8883 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2318 loss: 1.2318 2022/10/15 09:40:07 - mmengine - INFO - Epoch(train) [90][680/940] lr: 1.0000e-04 eta: 1:34:46 time: 0.5793 data_time: 0.0323 memory: 33630 grad_norm: 4.8279 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2594 loss: 1.2594 2022/10/15 09:40:19 - mmengine - INFO - Epoch(train) [90][700/940] lr: 1.0000e-04 eta: 1:34:35 time: 0.5847 data_time: 0.0449 memory: 33630 grad_norm: 4.8017 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2146 loss: 1.2146 2022/10/15 09:40:31 - mmengine - INFO - Epoch(train) [90][720/940] lr: 1.0000e-04 eta: 1:34:23 time: 0.5773 data_time: 0.0397 memory: 33630 grad_norm: 4.8916 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1816 loss: 1.1816 2022/10/15 09:40:42 - mmengine - INFO - Epoch(train) [90][740/940] lr: 1.0000e-04 eta: 1:34:11 time: 0.5838 data_time: 0.0426 memory: 33630 grad_norm: 4.7495 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2083 loss: 1.2083 2022/10/15 09:40:54 - mmengine - INFO - Epoch(train) [90][760/940] lr: 1.0000e-04 eta: 1:33:59 time: 0.5866 data_time: 0.0328 memory: 33630 grad_norm: 4.8810 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1109 loss: 1.1109 2022/10/15 09:41:06 - mmengine - INFO - Epoch(train) [90][780/940] lr: 1.0000e-04 eta: 1:33:48 time: 0.5964 data_time: 0.0503 memory: 33630 grad_norm: 4.7557 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2427 loss: 1.2427 2022/10/15 09:41:18 - mmengine - INFO - Epoch(train) [90][800/940] lr: 1.0000e-04 eta: 1:33:36 time: 0.5782 data_time: 0.0412 memory: 33630 grad_norm: 4.8769 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1319 loss: 1.1319 2022/10/15 09:41:29 - mmengine - INFO - Epoch(train) [90][820/940] lr: 1.0000e-04 eta: 1:33:24 time: 0.5839 data_time: 0.0383 memory: 33630 grad_norm: 4.7895 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1010 loss: 1.1010 2022/10/15 09:41:41 - mmengine - INFO - Epoch(train) [90][840/940] lr: 1.0000e-04 eta: 1:33:12 time: 0.5807 data_time: 0.0374 memory: 33630 grad_norm: 4.9390 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.1259 loss: 1.1259 2022/10/15 09:41:53 - mmengine - INFO - Epoch(train) [90][860/940] lr: 1.0000e-04 eta: 1:33:00 time: 0.5859 data_time: 0.0378 memory: 33630 grad_norm: 4.7434 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.0890 loss: 1.0890 2022/10/15 09:42:04 - mmengine - INFO - Epoch(train) [90][880/940] lr: 1.0000e-04 eta: 1:32:49 time: 0.5797 data_time: 0.0376 memory: 33630 grad_norm: 4.6975 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1994 loss: 1.1994 2022/10/15 09:42:16 - mmengine - INFO - Epoch(train) [90][900/940] lr: 1.0000e-04 eta: 1:32:37 time: 0.5762 data_time: 0.0343 memory: 33630 grad_norm: 4.8600 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 0.9974 loss: 0.9974 2022/10/15 09:42:27 - mmengine - INFO - Epoch(train) [90][920/940] lr: 1.0000e-04 eta: 1:32:25 time: 0.5829 data_time: 0.0295 memory: 33630 grad_norm: 4.8193 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1775 loss: 1.1775 2022/10/15 09:42:38 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 09:42:38 - mmengine - INFO - Epoch(train) [90][940/940] lr: 1.0000e-04 eta: 1:32:13 time: 0.5364 data_time: 0.0331 memory: 33630 grad_norm: 5.1788 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.1372 loss: 1.1372 2022/10/15 09:42:38 - mmengine - INFO - Saving checkpoint at 90 epochs 2022/10/15 09:42:53 - mmengine - INFO - Epoch(val) [90][20/78] eta: 0:00:42 time: 0.7256 data_time: 0.5566 memory: 5967 2022/10/15 09:43:03 - mmengine - INFO - Epoch(val) [90][40/78] eta: 0:00:18 time: 0.4782 data_time: 0.3110 memory: 5967 2022/10/15 09:43:16 - mmengine - INFO - Epoch(val) [90][60/78] eta: 0:00:12 time: 0.6691 data_time: 0.4964 memory: 5967 2022/10/15 09:43:27 - mmengine - INFO - Epoch(val) [90][78/78] acc/top1: 0.6880 acc/top5: 0.8789 acc/mean1: 0.6879 2022/10/15 09:43:44 - mmengine - INFO - Epoch(train) [91][20/940] lr: 1.0000e-04 eta: 1:32:02 time: 0.8632 data_time: 0.2423 memory: 33630 grad_norm: 4.7542 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2798 loss: 1.2798 2022/10/15 09:43:56 - mmengine - INFO - Epoch(train) [91][40/940] lr: 1.0000e-04 eta: 1:31:50 time: 0.5871 data_time: 0.0434 memory: 33630 grad_norm: 4.7710 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0047 loss: 1.0047 2022/10/15 09:44:08 - mmengine - INFO - Epoch(train) [91][60/940] lr: 1.0000e-04 eta: 1:31:38 time: 0.5913 data_time: 0.0402 memory: 33630 grad_norm: 4.9355 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3255 loss: 1.3255 2022/10/15 09:44:20 - mmengine - INFO - Epoch(train) [91][80/940] lr: 1.0000e-04 eta: 1:31:27 time: 0.5899 data_time: 0.0327 memory: 33630 grad_norm: 4.7651 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1916 loss: 1.1916 2022/10/15 09:44:32 - mmengine - INFO - Epoch(train) [91][100/940] lr: 1.0000e-04 eta: 1:31:15 time: 0.6012 data_time: 0.0420 memory: 33630 grad_norm: 4.9044 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2456 loss: 1.2456 2022/10/15 09:44:44 - mmengine - INFO - Epoch(train) [91][120/940] lr: 1.0000e-04 eta: 1:31:03 time: 0.5865 data_time: 0.0314 memory: 33630 grad_norm: 4.8222 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0950 loss: 1.0950 2022/10/15 09:44:55 - mmengine - INFO - Epoch(train) [91][140/940] lr: 1.0000e-04 eta: 1:30:51 time: 0.5871 data_time: 0.0330 memory: 33630 grad_norm: 4.8336 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2029 loss: 1.2029 2022/10/15 09:45:07 - mmengine - INFO - Epoch(train) [91][160/940] lr: 1.0000e-04 eta: 1:30:40 time: 0.5812 data_time: 0.0466 memory: 33630 grad_norm: 4.7918 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2132 loss: 1.2132 2022/10/15 09:45:19 - mmengine - INFO - Epoch(train) [91][180/940] lr: 1.0000e-04 eta: 1:30:28 time: 0.5928 data_time: 0.0380 memory: 33630 grad_norm: 4.8520 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.0444 loss: 1.0444 2022/10/15 09:45:31 - mmengine - INFO - Epoch(train) [91][200/940] lr: 1.0000e-04 eta: 1:30:16 time: 0.5887 data_time: 0.0308 memory: 33630 grad_norm: 4.7850 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1535 loss: 1.1535 2022/10/15 09:45:42 - mmengine - INFO - Epoch(train) [91][220/940] lr: 1.0000e-04 eta: 1:30:04 time: 0.5926 data_time: 0.0327 memory: 33630 grad_norm: 4.8785 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2098 loss: 1.2098 2022/10/15 09:45:54 - mmengine - INFO - Epoch(train) [91][240/940] lr: 1.0000e-04 eta: 1:29:52 time: 0.5791 data_time: 0.0374 memory: 33630 grad_norm: 4.7463 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1058 loss: 1.1058 2022/10/15 09:46:06 - mmengine - INFO - Epoch(train) [91][260/940] lr: 1.0000e-04 eta: 1:29:41 time: 0.5777 data_time: 0.0378 memory: 33630 grad_norm: 4.7644 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0441 loss: 1.0441 2022/10/15 09:46:17 - mmengine - INFO - Epoch(train) [91][280/940] lr: 1.0000e-04 eta: 1:29:29 time: 0.5785 data_time: 0.0397 memory: 33630 grad_norm: 4.8504 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1227 loss: 1.1227 2022/10/15 09:46:29 - mmengine - INFO - Epoch(train) [91][300/940] lr: 1.0000e-04 eta: 1:29:17 time: 0.5781 data_time: 0.0300 memory: 33630 grad_norm: 4.7562 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2627 loss: 1.2627 2022/10/15 09:46:40 - mmengine - INFO - Epoch(train) [91][320/940] lr: 1.0000e-04 eta: 1:29:05 time: 0.5780 data_time: 0.0318 memory: 33630 grad_norm: 4.7323 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2407 loss: 1.2407 2022/10/15 09:46:52 - mmengine - INFO - Epoch(train) [91][340/940] lr: 1.0000e-04 eta: 1:28:54 time: 0.6052 data_time: 0.0395 memory: 33630 grad_norm: 4.7563 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1294 loss: 1.1294 2022/10/15 09:47:04 - mmengine - INFO - Epoch(train) [91][360/940] lr: 1.0000e-04 eta: 1:28:42 time: 0.5799 data_time: 0.0350 memory: 33630 grad_norm: 4.7656 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.1862 loss: 1.1862 2022/10/15 09:47:16 - mmengine - INFO - Epoch(train) [91][380/940] lr: 1.0000e-04 eta: 1:28:30 time: 0.5877 data_time: 0.0429 memory: 33630 grad_norm: 4.8027 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0104 loss: 1.0104 2022/10/15 09:47:27 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 09:47:27 - mmengine - INFO - Epoch(train) [91][400/940] lr: 1.0000e-04 eta: 1:28:18 time: 0.5799 data_time: 0.0335 memory: 33630 grad_norm: 4.8014 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1968 loss: 1.1968 2022/10/15 09:47:39 - mmengine - INFO - Epoch(train) [91][420/940] lr: 1.0000e-04 eta: 1:28:06 time: 0.5779 data_time: 0.0456 memory: 33630 grad_norm: 4.9082 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1112 loss: 1.1112 2022/10/15 09:47:50 - mmengine - INFO - Epoch(train) [91][440/940] lr: 1.0000e-04 eta: 1:27:55 time: 0.5736 data_time: 0.0332 memory: 33630 grad_norm: 4.9150 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1031 loss: 1.1031 2022/10/15 09:48:02 - mmengine - INFO - Epoch(train) [91][460/940] lr: 1.0000e-04 eta: 1:27:43 time: 0.5763 data_time: 0.0302 memory: 33630 grad_norm: 4.7965 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.0809 loss: 1.0809 2022/10/15 09:48:14 - mmengine - INFO - Epoch(train) [91][480/940] lr: 1.0000e-04 eta: 1:27:31 time: 0.5832 data_time: 0.0414 memory: 33630 grad_norm: 4.7276 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.0522 loss: 1.0522 2022/10/15 09:48:25 - mmengine - INFO - Epoch(train) [91][500/940] lr: 1.0000e-04 eta: 1:27:19 time: 0.5762 data_time: 0.0386 memory: 33630 grad_norm: 4.9663 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2265 loss: 1.2265 2022/10/15 09:48:37 - mmengine - INFO - Epoch(train) [91][520/940] lr: 1.0000e-04 eta: 1:27:07 time: 0.5803 data_time: 0.0367 memory: 33630 grad_norm: 4.7302 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1204 loss: 1.1204 2022/10/15 09:48:48 - mmengine - INFO - Epoch(train) [91][540/940] lr: 1.0000e-04 eta: 1:26:56 time: 0.5755 data_time: 0.0322 memory: 33630 grad_norm: 4.8158 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1535 loss: 1.1535 2022/10/15 09:49:00 - mmengine - INFO - Epoch(train) [91][560/940] lr: 1.0000e-04 eta: 1:26:44 time: 0.5931 data_time: 0.0365 memory: 33630 grad_norm: 4.7760 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1157 loss: 1.1157 2022/10/15 09:49:12 - mmengine - INFO - Epoch(train) [91][580/940] lr: 1.0000e-04 eta: 1:26:32 time: 0.5890 data_time: 0.0434 memory: 33630 grad_norm: 4.8004 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1428 loss: 1.1428 2022/10/15 09:49:24 - mmengine - INFO - Epoch(train) [91][600/940] lr: 1.0000e-04 eta: 1:26:20 time: 0.5829 data_time: 0.0333 memory: 33630 grad_norm: 4.8422 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2950 loss: 1.2950 2022/10/15 09:49:35 - mmengine - INFO - Epoch(train) [91][620/940] lr: 1.0000e-04 eta: 1:26:08 time: 0.5813 data_time: 0.0334 memory: 33630 grad_norm: 4.7444 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1699 loss: 1.1699 2022/10/15 09:49:47 - mmengine - INFO - Epoch(train) [91][640/940] lr: 1.0000e-04 eta: 1:25:57 time: 0.5874 data_time: 0.0425 memory: 33630 grad_norm: 4.8695 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1920 loss: 1.1920 2022/10/15 09:49:59 - mmengine - INFO - Epoch(train) [91][660/940] lr: 1.0000e-04 eta: 1:25:45 time: 0.5799 data_time: 0.0445 memory: 33630 grad_norm: 4.8260 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0525 loss: 1.0525 2022/10/15 09:50:10 - mmengine - INFO - Epoch(train) [91][680/940] lr: 1.0000e-04 eta: 1:25:33 time: 0.5747 data_time: 0.0376 memory: 33630 grad_norm: 4.7740 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1859 loss: 1.1859 2022/10/15 09:50:22 - mmengine - INFO - Epoch(train) [91][700/940] lr: 1.0000e-04 eta: 1:25:21 time: 0.5741 data_time: 0.0325 memory: 33630 grad_norm: 4.8821 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0768 loss: 1.0768 2022/10/15 09:50:33 - mmengine - INFO - Epoch(train) [91][720/940] lr: 1.0000e-04 eta: 1:25:09 time: 0.5775 data_time: 0.0401 memory: 33630 grad_norm: 4.8407 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1723 loss: 1.1723 2022/10/15 09:50:45 - mmengine - INFO - Epoch(train) [91][740/940] lr: 1.0000e-04 eta: 1:24:58 time: 0.5730 data_time: 0.0351 memory: 33630 grad_norm: 4.7679 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1099 loss: 1.1099 2022/10/15 09:50:56 - mmengine - INFO - Epoch(train) [91][760/940] lr: 1.0000e-04 eta: 1:24:46 time: 0.5806 data_time: 0.0393 memory: 33630 grad_norm: 4.8433 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.0843 loss: 1.0843 2022/10/15 09:51:08 - mmengine - INFO - Epoch(train) [91][780/940] lr: 1.0000e-04 eta: 1:24:34 time: 0.5847 data_time: 0.0442 memory: 33630 grad_norm: 4.8239 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2036 loss: 1.2036 2022/10/15 09:51:19 - mmengine - INFO - Epoch(train) [91][800/940] lr: 1.0000e-04 eta: 1:24:22 time: 0.5771 data_time: 0.0371 memory: 33630 grad_norm: 4.7785 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0963 loss: 1.0963 2022/10/15 09:51:31 - mmengine - INFO - Epoch(train) [91][820/940] lr: 1.0000e-04 eta: 1:24:10 time: 0.5802 data_time: 0.0378 memory: 33630 grad_norm: 4.9592 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1330 loss: 1.1330 2022/10/15 09:51:43 - mmengine - INFO - Epoch(train) [91][840/940] lr: 1.0000e-04 eta: 1:23:59 time: 0.5766 data_time: 0.0349 memory: 33630 grad_norm: 4.8465 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.0758 loss: 1.0758 2022/10/15 09:51:54 - mmengine - INFO - Epoch(train) [91][860/940] lr: 1.0000e-04 eta: 1:23:47 time: 0.5768 data_time: 0.0381 memory: 33630 grad_norm: 4.8613 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0667 loss: 1.0667 2022/10/15 09:52:06 - mmengine - INFO - Epoch(train) [91][880/940] lr: 1.0000e-04 eta: 1:23:35 time: 0.5792 data_time: 0.0374 memory: 33630 grad_norm: 4.8486 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2160 loss: 1.2160 2022/10/15 09:52:17 - mmengine - INFO - Epoch(train) [91][900/940] lr: 1.0000e-04 eta: 1:23:23 time: 0.5803 data_time: 0.0402 memory: 33630 grad_norm: 4.8005 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1535 loss: 1.1535 2022/10/15 09:52:29 - mmengine - INFO - Epoch(train) [91][920/940] lr: 1.0000e-04 eta: 1:23:12 time: 0.5850 data_time: 0.0350 memory: 33630 grad_norm: 4.8711 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0464 loss: 1.0464 2022/10/15 09:52:40 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 09:52:40 - mmengine - INFO - Epoch(train) [91][940/940] lr: 1.0000e-04 eta: 1:23:00 time: 0.5448 data_time: 0.0292 memory: 33630 grad_norm: 5.1646 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.2059 loss: 1.2059 2022/10/15 09:52:54 - mmengine - INFO - Epoch(val) [91][20/78] eta: 0:00:40 time: 0.7032 data_time: 0.5320 memory: 5967 2022/10/15 09:53:04 - mmengine - INFO - Epoch(val) [91][40/78] eta: 0:00:18 time: 0.4880 data_time: 0.3200 memory: 5967 2022/10/15 09:53:17 - mmengine - INFO - Epoch(val) [91][60/78] eta: 0:00:12 time: 0.6781 data_time: 0.5100 memory: 5967 2022/10/15 09:53:29 - mmengine - INFO - Epoch(val) [91][78/78] acc/top1: 0.6899 acc/top5: 0.8802 acc/mean1: 0.6898 2022/10/15 09:53:29 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb/best_acc/top1_epoch_86.pth is removed 2022/10/15 09:53:29 - mmengine - INFO - The best checkpoint with 0.6899 acc/top1 at 91 epoch is saved to best_acc/top1_epoch_91.pth. 2022/10/15 09:53:45 - mmengine - INFO - Epoch(train) [92][20/940] lr: 1.0000e-04 eta: 1:22:48 time: 0.7997 data_time: 0.2548 memory: 33630 grad_norm: 4.8390 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1313 loss: 1.1313 2022/10/15 09:53:57 - mmengine - INFO - Epoch(train) [92][40/940] lr: 1.0000e-04 eta: 1:22:37 time: 0.5872 data_time: 0.0317 memory: 33630 grad_norm: 4.8293 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1060 loss: 1.1060 2022/10/15 09:54:09 - mmengine - INFO - Epoch(train) [92][60/940] lr: 1.0000e-04 eta: 1:22:25 time: 0.5920 data_time: 0.0405 memory: 33630 grad_norm: 4.8918 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1315 loss: 1.1315 2022/10/15 09:54:21 - mmengine - INFO - Epoch(train) [92][80/940] lr: 1.0000e-04 eta: 1:22:13 time: 0.5903 data_time: 0.0325 memory: 33630 grad_norm: 4.8206 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.2006 loss: 1.2006 2022/10/15 09:54:32 - mmengine - INFO - Epoch(train) [92][100/940] lr: 1.0000e-04 eta: 1:22:01 time: 0.5890 data_time: 0.0389 memory: 33630 grad_norm: 4.8340 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0645 loss: 1.0645 2022/10/15 09:54:44 - mmengine - INFO - Epoch(train) [92][120/940] lr: 1.0000e-04 eta: 1:21:49 time: 0.5807 data_time: 0.0279 memory: 33630 grad_norm: 4.8271 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1393 loss: 1.1393 2022/10/15 09:54:56 - mmengine - INFO - Epoch(train) [92][140/940] lr: 1.0000e-04 eta: 1:21:38 time: 0.5801 data_time: 0.0388 memory: 33630 grad_norm: 4.7743 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2158 loss: 1.2158 2022/10/15 09:55:07 - mmengine - INFO - Epoch(train) [92][160/940] lr: 1.0000e-04 eta: 1:21:26 time: 0.5885 data_time: 0.0377 memory: 33630 grad_norm: 4.8296 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1479 loss: 1.1479 2022/10/15 09:55:19 - mmengine - INFO - Epoch(train) [92][180/940] lr: 1.0000e-04 eta: 1:21:14 time: 0.5877 data_time: 0.0469 memory: 33630 grad_norm: 4.9543 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3465 loss: 1.3465 2022/10/15 09:55:31 - mmengine - INFO - Epoch(train) [92][200/940] lr: 1.0000e-04 eta: 1:21:02 time: 0.5832 data_time: 0.0373 memory: 33630 grad_norm: 4.8502 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1262 loss: 1.1262 2022/10/15 09:55:42 - mmengine - INFO - Epoch(train) [92][220/940] lr: 1.0000e-04 eta: 1:20:51 time: 0.5787 data_time: 0.0392 memory: 33630 grad_norm: 4.8124 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.0619 loss: 1.0619 2022/10/15 09:55:54 - mmengine - INFO - Epoch(train) [92][240/940] lr: 1.0000e-04 eta: 1:20:39 time: 0.5828 data_time: 0.0419 memory: 33630 grad_norm: 5.0216 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1487 loss: 1.1487 2022/10/15 09:56:06 - mmengine - INFO - Epoch(train) [92][260/940] lr: 1.0000e-04 eta: 1:20:27 time: 0.5757 data_time: 0.0342 memory: 33630 grad_norm: 4.8365 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1638 loss: 1.1638 2022/10/15 09:56:17 - mmengine - INFO - Epoch(train) [92][280/940] lr: 1.0000e-04 eta: 1:20:15 time: 0.5818 data_time: 0.0429 memory: 33630 grad_norm: 4.8359 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2303 loss: 1.2303 2022/10/15 09:56:29 - mmengine - INFO - Epoch(train) [92][300/940] lr: 1.0000e-04 eta: 1:20:03 time: 0.5909 data_time: 0.0313 memory: 33630 grad_norm: 4.8794 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1360 loss: 1.1360 2022/10/15 09:56:41 - mmengine - INFO - Epoch(train) [92][320/940] lr: 1.0000e-04 eta: 1:19:52 time: 0.5798 data_time: 0.0366 memory: 33630 grad_norm: 4.8470 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.0429 loss: 1.0429 2022/10/15 09:56:52 - mmengine - INFO - Epoch(train) [92][340/940] lr: 1.0000e-04 eta: 1:19:40 time: 0.5828 data_time: 0.0485 memory: 33630 grad_norm: 4.7550 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1327 loss: 1.1327 2022/10/15 09:57:04 - mmengine - INFO - Epoch(train) [92][360/940] lr: 1.0000e-04 eta: 1:19:28 time: 0.5819 data_time: 0.0379 memory: 33630 grad_norm: 4.7426 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1114 loss: 1.1114 2022/10/15 09:57:16 - mmengine - INFO - Epoch(train) [92][380/940] lr: 1.0000e-04 eta: 1:19:16 time: 0.5884 data_time: 0.0449 memory: 33630 grad_norm: 4.9553 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2039 loss: 1.2039 2022/10/15 09:57:27 - mmengine - INFO - Epoch(train) [92][400/940] lr: 1.0000e-04 eta: 1:19:04 time: 0.5878 data_time: 0.0330 memory: 33630 grad_norm: 4.9575 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1807 loss: 1.1807 2022/10/15 09:57:39 - mmengine - INFO - Epoch(train) [92][420/940] lr: 1.0000e-04 eta: 1:18:53 time: 0.5720 data_time: 0.0444 memory: 33630 grad_norm: 4.7647 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1356 loss: 1.1356 2022/10/15 09:57:51 - mmengine - INFO - Epoch(train) [92][440/940] lr: 1.0000e-04 eta: 1:18:41 time: 0.5897 data_time: 0.0365 memory: 33630 grad_norm: 4.8999 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1714 loss: 1.1714 2022/10/15 09:58:03 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 09:58:03 - mmengine - INFO - Epoch(train) [92][460/940] lr: 1.0000e-04 eta: 1:18:29 time: 0.5897 data_time: 0.0406 memory: 33630 grad_norm: 4.8408 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.2132 loss: 1.2132 2022/10/15 09:58:14 - mmengine - INFO - Epoch(train) [92][480/940] lr: 1.0000e-04 eta: 1:18:17 time: 0.5876 data_time: 0.0311 memory: 33630 grad_norm: 4.8884 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.1966 loss: 1.1966 2022/10/15 09:58:26 - mmengine - INFO - Epoch(train) [92][500/940] lr: 1.0000e-04 eta: 1:18:06 time: 0.5841 data_time: 0.0425 memory: 33630 grad_norm: 4.8859 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1835 loss: 1.1835 2022/10/15 09:58:38 - mmengine - INFO - Epoch(train) [92][520/940] lr: 1.0000e-04 eta: 1:17:54 time: 0.5922 data_time: 0.0318 memory: 33630 grad_norm: 4.8656 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1150 loss: 1.1150 2022/10/15 09:58:49 - mmengine - INFO - Epoch(train) [92][540/940] lr: 1.0000e-04 eta: 1:17:42 time: 0.5799 data_time: 0.0411 memory: 33630 grad_norm: 4.8008 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2161 loss: 1.2161 2022/10/15 09:59:01 - mmengine - INFO - Epoch(train) [92][560/940] lr: 1.0000e-04 eta: 1:17:30 time: 0.5772 data_time: 0.0385 memory: 33630 grad_norm: 4.5744 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1225 loss: 1.1225 2022/10/15 09:59:13 - mmengine - INFO - Epoch(train) [92][580/940] lr: 1.0000e-04 eta: 1:17:18 time: 0.5815 data_time: 0.0450 memory: 33630 grad_norm: 4.8021 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1656 loss: 1.1656 2022/10/15 09:59:24 - mmengine - INFO - Epoch(train) [92][600/940] lr: 1.0000e-04 eta: 1:17:07 time: 0.5868 data_time: 0.0393 memory: 33630 grad_norm: 4.9169 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.1950 loss: 1.1950 2022/10/15 09:59:36 - mmengine - INFO - Epoch(train) [92][620/940] lr: 1.0000e-04 eta: 1:16:55 time: 0.5743 data_time: 0.0420 memory: 33630 grad_norm: 4.8001 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0523 loss: 1.0523 2022/10/15 09:59:47 - mmengine - INFO - Epoch(train) [92][640/940] lr: 1.0000e-04 eta: 1:16:43 time: 0.5763 data_time: 0.0361 memory: 33630 grad_norm: 4.8575 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0696 loss: 1.0696 2022/10/15 09:59:59 - mmengine - INFO - Epoch(train) [92][660/940] lr: 1.0000e-04 eta: 1:16:31 time: 0.5839 data_time: 0.0464 memory: 33630 grad_norm: 4.7659 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1461 loss: 1.1461 2022/10/15 10:00:11 - mmengine - INFO - Epoch(train) [92][680/940] lr: 1.0000e-04 eta: 1:16:19 time: 0.5940 data_time: 0.0439 memory: 33630 grad_norm: 4.7540 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1709 loss: 1.1709 2022/10/15 10:00:23 - mmengine - INFO - Epoch(train) [92][700/940] lr: 1.0000e-04 eta: 1:16:08 time: 0.5934 data_time: 0.0444 memory: 33630 grad_norm: 4.7473 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0862 loss: 1.0862 2022/10/15 10:00:34 - mmengine - INFO - Epoch(train) [92][720/940] lr: 1.0000e-04 eta: 1:15:56 time: 0.5783 data_time: 0.0329 memory: 33630 grad_norm: 4.9643 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2183 loss: 1.2183 2022/10/15 10:00:46 - mmengine - INFO - Epoch(train) [92][740/940] lr: 1.0000e-04 eta: 1:15:44 time: 0.5763 data_time: 0.0341 memory: 33630 grad_norm: 4.7842 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1519 loss: 1.1519 2022/10/15 10:00:57 - mmengine - INFO - Epoch(train) [92][760/940] lr: 1.0000e-04 eta: 1:15:32 time: 0.5746 data_time: 0.0348 memory: 33630 grad_norm: 4.7906 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2323 loss: 1.2323 2022/10/15 10:01:09 - mmengine - INFO - Epoch(train) [92][780/940] lr: 1.0000e-04 eta: 1:15:21 time: 0.5734 data_time: 0.0340 memory: 33630 grad_norm: 4.7540 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1007 loss: 1.1007 2022/10/15 10:01:21 - mmengine - INFO - Epoch(train) [92][800/940] lr: 1.0000e-04 eta: 1:15:09 time: 0.5889 data_time: 0.0358 memory: 33630 grad_norm: 4.6210 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2437 loss: 1.2437 2022/10/15 10:01:32 - mmengine - INFO - Epoch(train) [92][820/940] lr: 1.0000e-04 eta: 1:14:57 time: 0.5848 data_time: 0.0342 memory: 33630 grad_norm: 4.7750 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0771 loss: 1.0771 2022/10/15 10:01:44 - mmengine - INFO - Epoch(train) [92][840/940] lr: 1.0000e-04 eta: 1:14:45 time: 0.5768 data_time: 0.0346 memory: 33630 grad_norm: 4.8568 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.1763 loss: 1.1763 2022/10/15 10:01:56 - mmengine - INFO - Epoch(train) [92][860/940] lr: 1.0000e-04 eta: 1:14:33 time: 0.5882 data_time: 0.0445 memory: 33630 grad_norm: 4.8509 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0791 loss: 1.0791 2022/10/15 10:02:07 - mmengine - INFO - Epoch(train) [92][880/940] lr: 1.0000e-04 eta: 1:14:22 time: 0.5743 data_time: 0.0444 memory: 33630 grad_norm: 4.7828 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.0822 loss: 1.0822 2022/10/15 10:02:19 - mmengine - INFO - Epoch(train) [92][900/940] lr: 1.0000e-04 eta: 1:14:10 time: 0.5860 data_time: 0.0392 memory: 33630 grad_norm: 4.8713 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1490 loss: 1.1490 2022/10/15 10:02:31 - mmengine - INFO - Epoch(train) [92][920/940] lr: 1.0000e-04 eta: 1:13:58 time: 0.5830 data_time: 0.0384 memory: 33630 grad_norm: 4.8284 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2041 loss: 1.2041 2022/10/15 10:02:41 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 10:02:41 - mmengine - INFO - Epoch(train) [92][940/940] lr: 1.0000e-04 eta: 1:13:46 time: 0.5445 data_time: 0.0382 memory: 33630 grad_norm: 5.1646 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.2172 loss: 1.2172 2022/10/15 10:02:56 - mmengine - INFO - Epoch(val) [92][20/78] eta: 0:00:43 time: 0.7450 data_time: 0.5733 memory: 5967 2022/10/15 10:03:07 - mmengine - INFO - Epoch(val) [92][40/78] eta: 0:00:19 time: 0.5099 data_time: 0.3401 memory: 5967 2022/10/15 10:03:19 - mmengine - INFO - Epoch(val) [92][60/78] eta: 0:00:11 time: 0.6460 data_time: 0.4757 memory: 5967 2022/10/15 10:03:30 - mmengine - INFO - Epoch(val) [92][78/78] acc/top1: 0.6899 acc/top5: 0.8803 acc/mean1: 0.6897 2022/10/15 10:03:47 - mmengine - INFO - Epoch(train) [93][20/940] lr: 1.0000e-04 eta: 1:13:35 time: 0.8494 data_time: 0.2376 memory: 33630 grad_norm: 4.7753 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.1575 loss: 1.1575 2022/10/15 10:03:59 - mmengine - INFO - Epoch(train) [93][40/940] lr: 1.0000e-04 eta: 1:13:23 time: 0.5973 data_time: 0.0357 memory: 33630 grad_norm: 4.8410 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2562 loss: 1.2562 2022/10/15 10:04:11 - mmengine - INFO - Epoch(train) [93][60/940] lr: 1.0000e-04 eta: 1:13:11 time: 0.5923 data_time: 0.0382 memory: 33630 grad_norm: 4.8968 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1042 loss: 1.1042 2022/10/15 10:04:23 - mmengine - INFO - Epoch(train) [93][80/940] lr: 1.0000e-04 eta: 1:13:00 time: 0.6093 data_time: 0.0369 memory: 33630 grad_norm: 4.6376 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0069 loss: 1.0069 2022/10/15 10:04:35 - mmengine - INFO - Epoch(train) [93][100/940] lr: 1.0000e-04 eta: 1:12:48 time: 0.5913 data_time: 0.0343 memory: 33630 grad_norm: 4.8178 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.0513 loss: 1.0513 2022/10/15 10:04:46 - mmengine - INFO - Epoch(train) [93][120/940] lr: 1.0000e-04 eta: 1:12:36 time: 0.5903 data_time: 0.0363 memory: 33630 grad_norm: 4.6868 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0834 loss: 1.0834 2022/10/15 10:04:58 - mmengine - INFO - Epoch(train) [93][140/940] lr: 1.0000e-04 eta: 1:12:24 time: 0.5811 data_time: 0.0354 memory: 33630 grad_norm: 4.8361 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0662 loss: 1.0662 2022/10/15 10:05:10 - mmengine - INFO - Epoch(train) [93][160/940] lr: 1.0000e-04 eta: 1:12:13 time: 0.5816 data_time: 0.0350 memory: 33630 grad_norm: 4.8154 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1564 loss: 1.1564 2022/10/15 10:05:21 - mmengine - INFO - Epoch(train) [93][180/940] lr: 1.0000e-04 eta: 1:12:01 time: 0.5730 data_time: 0.0319 memory: 33630 grad_norm: 4.8041 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1789 loss: 1.1789 2022/10/15 10:05:33 - mmengine - INFO - Epoch(train) [93][200/940] lr: 1.0000e-04 eta: 1:11:49 time: 0.5789 data_time: 0.0359 memory: 33630 grad_norm: 4.7842 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1268 loss: 1.1268 2022/10/15 10:05:44 - mmengine - INFO - Epoch(train) [93][220/940] lr: 1.0000e-04 eta: 1:11:37 time: 0.5739 data_time: 0.0431 memory: 33630 grad_norm: 4.8265 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1872 loss: 1.1872 2022/10/15 10:05:56 - mmengine - INFO - Epoch(train) [93][240/940] lr: 1.0000e-04 eta: 1:11:25 time: 0.5827 data_time: 0.0328 memory: 33630 grad_norm: 4.8975 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.2162 loss: 1.2162 2022/10/15 10:06:08 - mmengine - INFO - Epoch(train) [93][260/940] lr: 1.0000e-04 eta: 1:11:14 time: 0.5812 data_time: 0.0335 memory: 33630 grad_norm: 4.7530 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.0893 loss: 1.0893 2022/10/15 10:06:19 - mmengine - INFO - Epoch(train) [93][280/940] lr: 1.0000e-04 eta: 1:11:02 time: 0.5759 data_time: 0.0369 memory: 33630 grad_norm: 4.9148 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0424 loss: 1.0424 2022/10/15 10:06:31 - mmengine - INFO - Epoch(train) [93][300/940] lr: 1.0000e-04 eta: 1:10:50 time: 0.5869 data_time: 0.0360 memory: 33630 grad_norm: 4.6973 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.0976 loss: 1.0976 2022/10/15 10:06:42 - mmengine - INFO - Epoch(train) [93][320/940] lr: 1.0000e-04 eta: 1:10:38 time: 0.5844 data_time: 0.0334 memory: 33630 grad_norm: 4.9396 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1462 loss: 1.1462 2022/10/15 10:06:54 - mmengine - INFO - Epoch(train) [93][340/940] lr: 1.0000e-04 eta: 1:10:26 time: 0.5762 data_time: 0.0408 memory: 33630 grad_norm: 4.8390 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.1510 loss: 1.1510 2022/10/15 10:07:06 - mmengine - INFO - Epoch(train) [93][360/940] lr: 1.0000e-04 eta: 1:10:15 time: 0.5829 data_time: 0.0402 memory: 33630 grad_norm: 4.8120 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0711 loss: 1.0711 2022/10/15 10:07:17 - mmengine - INFO - Epoch(train) [93][380/940] lr: 1.0000e-04 eta: 1:10:03 time: 0.5844 data_time: 0.0430 memory: 33630 grad_norm: 4.8666 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1786 loss: 1.1786 2022/10/15 10:07:29 - mmengine - INFO - Epoch(train) [93][400/940] lr: 1.0000e-04 eta: 1:09:51 time: 0.5791 data_time: 0.0371 memory: 33630 grad_norm: 4.8792 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1245 loss: 1.1245 2022/10/15 10:07:40 - mmengine - INFO - Epoch(train) [93][420/940] lr: 1.0000e-04 eta: 1:09:39 time: 0.5766 data_time: 0.0362 memory: 33630 grad_norm: 4.7951 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2059 loss: 1.2059 2022/10/15 10:07:52 - mmengine - INFO - Epoch(train) [93][440/940] lr: 1.0000e-04 eta: 1:09:27 time: 0.5794 data_time: 0.0387 memory: 33630 grad_norm: 4.7659 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2458 loss: 1.2458 2022/10/15 10:08:04 - mmengine - INFO - Epoch(train) [93][460/940] lr: 1.0000e-04 eta: 1:09:16 time: 0.5758 data_time: 0.0342 memory: 33630 grad_norm: 4.8253 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1334 loss: 1.1334 2022/10/15 10:08:15 - mmengine - INFO - Epoch(train) [93][480/940] lr: 1.0000e-04 eta: 1:09:04 time: 0.5771 data_time: 0.0362 memory: 33630 grad_norm: 4.8925 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1263 loss: 1.1263 2022/10/15 10:08:27 - mmengine - INFO - Epoch(train) [93][500/940] lr: 1.0000e-04 eta: 1:08:52 time: 0.5785 data_time: 0.0341 memory: 33630 grad_norm: 4.7863 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.0531 loss: 1.0531 2022/10/15 10:08:38 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 10:08:38 - mmengine - INFO - Epoch(train) [93][520/940] lr: 1.0000e-04 eta: 1:08:40 time: 0.5762 data_time: 0.0391 memory: 33630 grad_norm: 4.7635 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.1193 loss: 1.1193 2022/10/15 10:08:50 - mmengine - INFO - Epoch(train) [93][540/940] lr: 1.0000e-04 eta: 1:08:29 time: 0.5865 data_time: 0.0420 memory: 33630 grad_norm: 4.8176 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0714 loss: 1.0714 2022/10/15 10:09:02 - mmengine - INFO - Epoch(train) [93][560/940] lr: 1.0000e-04 eta: 1:08:17 time: 0.5777 data_time: 0.0364 memory: 33630 grad_norm: 4.8919 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1975 loss: 1.1975 2022/10/15 10:09:13 - mmengine - INFO - Epoch(train) [93][580/940] lr: 1.0000e-04 eta: 1:08:05 time: 0.5837 data_time: 0.0343 memory: 33630 grad_norm: 4.8524 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2110 loss: 1.2110 2022/10/15 10:09:25 - mmengine - INFO - Epoch(train) [93][600/940] lr: 1.0000e-04 eta: 1:07:53 time: 0.5808 data_time: 0.0387 memory: 33630 grad_norm: 4.7720 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0969 loss: 1.0969 2022/10/15 10:09:36 - mmengine - INFO - Epoch(train) [93][620/940] lr: 1.0000e-04 eta: 1:07:41 time: 0.5793 data_time: 0.0385 memory: 33630 grad_norm: 4.9477 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2145 loss: 1.2145 2022/10/15 10:09:48 - mmengine - INFO - Epoch(train) [93][640/940] lr: 1.0000e-04 eta: 1:07:30 time: 0.5738 data_time: 0.0352 memory: 33630 grad_norm: 4.8808 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1272 loss: 1.1272 2022/10/15 10:10:00 - mmengine - INFO - Epoch(train) [93][660/940] lr: 1.0000e-04 eta: 1:07:18 time: 0.5842 data_time: 0.0324 memory: 33630 grad_norm: 4.8535 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.1064 loss: 1.1064 2022/10/15 10:10:11 - mmengine - INFO - Epoch(train) [93][680/940] lr: 1.0000e-04 eta: 1:07:06 time: 0.5730 data_time: 0.0343 memory: 33630 grad_norm: 4.7930 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.1712 loss: 1.1712 2022/10/15 10:10:23 - mmengine - INFO - Epoch(train) [93][700/940] lr: 1.0000e-04 eta: 1:06:54 time: 0.5748 data_time: 0.0367 memory: 33630 grad_norm: 4.8680 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1918 loss: 1.1918 2022/10/15 10:10:34 - mmengine - INFO - Epoch(train) [93][720/940] lr: 1.0000e-04 eta: 1:06:42 time: 0.5679 data_time: 0.0317 memory: 33630 grad_norm: 4.7839 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.0894 loss: 1.0894 2022/10/15 10:10:45 - mmengine - INFO - Epoch(train) [93][740/940] lr: 1.0000e-04 eta: 1:06:31 time: 0.5769 data_time: 0.0383 memory: 33630 grad_norm: 4.8158 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.1669 loss: 1.1669 2022/10/15 10:10:57 - mmengine - INFO - Epoch(train) [93][760/940] lr: 1.0000e-04 eta: 1:06:19 time: 0.5781 data_time: 0.0373 memory: 33630 grad_norm: 4.8412 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1680 loss: 1.1680 2022/10/15 10:11:08 - mmengine - INFO - Epoch(train) [93][780/940] lr: 1.0000e-04 eta: 1:06:07 time: 0.5721 data_time: 0.0452 memory: 33630 grad_norm: 4.7389 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1918 loss: 1.1918 2022/10/15 10:11:20 - mmengine - INFO - Epoch(train) [93][800/940] lr: 1.0000e-04 eta: 1:05:55 time: 0.5931 data_time: 0.0380 memory: 33630 grad_norm: 4.9405 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2241 loss: 1.2241 2022/10/15 10:11:32 - mmengine - INFO - Epoch(train) [93][820/940] lr: 1.0000e-04 eta: 1:05:43 time: 0.5783 data_time: 0.0354 memory: 33630 grad_norm: 4.8018 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.0763 loss: 1.0763 2022/10/15 10:11:43 - mmengine - INFO - Epoch(train) [93][840/940] lr: 1.0000e-04 eta: 1:05:32 time: 0.5741 data_time: 0.0344 memory: 33630 grad_norm: 4.7963 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1440 loss: 1.1440 2022/10/15 10:11:55 - mmengine - INFO - Epoch(train) [93][860/940] lr: 1.0000e-04 eta: 1:05:20 time: 0.5868 data_time: 0.0350 memory: 33630 grad_norm: 4.9383 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.2005 loss: 1.2005 2022/10/15 10:12:07 - mmengine - INFO - Epoch(train) [93][880/940] lr: 1.0000e-04 eta: 1:05:08 time: 0.5805 data_time: 0.0570 memory: 33630 grad_norm: 4.8334 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2568 loss: 1.2568 2022/10/15 10:12:19 - mmengine - INFO - Epoch(train) [93][900/940] lr: 1.0000e-04 eta: 1:04:56 time: 0.5949 data_time: 0.0416 memory: 33630 grad_norm: 4.7827 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.1702 loss: 1.1702 2022/10/15 10:12:30 - mmengine - INFO - Epoch(train) [93][920/940] lr: 1.0000e-04 eta: 1:04:45 time: 0.5783 data_time: 0.0364 memory: 33630 grad_norm: 4.8876 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1340 loss: 1.1340 2022/10/15 10:12:41 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 10:12:41 - mmengine - INFO - Epoch(train) [93][940/940] lr: 1.0000e-04 eta: 1:04:33 time: 0.5465 data_time: 0.0306 memory: 33630 grad_norm: 5.1213 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.2027 loss: 1.2027 2022/10/15 10:12:41 - mmengine - INFO - Saving checkpoint at 93 epochs 2022/10/15 10:12:57 - mmengine - INFO - Epoch(val) [93][20/78] eta: 0:00:42 time: 0.7245 data_time: 0.5531 memory: 5967 2022/10/15 10:13:06 - mmengine - INFO - Epoch(val) [93][40/78] eta: 0:00:18 time: 0.4853 data_time: 0.3180 memory: 5967 2022/10/15 10:13:19 - mmengine - INFO - Epoch(val) [93][60/78] eta: 0:00:11 time: 0.6411 data_time: 0.4696 memory: 5967 2022/10/15 10:13:30 - mmengine - INFO - Epoch(val) [93][78/78] acc/top1: 0.6885 acc/top5: 0.8794 acc/mean1: 0.6884 2022/10/15 10:13:46 - mmengine - INFO - Epoch(train) [94][20/940] lr: 1.0000e-04 eta: 1:04:21 time: 0.8105 data_time: 0.2323 memory: 33630 grad_norm: 4.9606 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1516 loss: 1.1516 2022/10/15 10:13:58 - mmengine - INFO - Epoch(train) [94][40/940] lr: 1.0000e-04 eta: 1:04:09 time: 0.5867 data_time: 0.0556 memory: 33630 grad_norm: 4.9525 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1234 loss: 1.1234 2022/10/15 10:14:10 - mmengine - INFO - Epoch(train) [94][60/940] lr: 1.0000e-04 eta: 1:03:58 time: 0.6194 data_time: 0.0652 memory: 33630 grad_norm: 4.8252 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1161 loss: 1.1161 2022/10/15 10:14:22 - mmengine - INFO - Epoch(train) [94][80/940] lr: 1.0000e-04 eta: 1:03:46 time: 0.5853 data_time: 0.0326 memory: 33630 grad_norm: 4.8588 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1587 loss: 1.1587 2022/10/15 10:14:34 - mmengine - INFO - Epoch(train) [94][100/940] lr: 1.0000e-04 eta: 1:03:34 time: 0.5860 data_time: 0.0361 memory: 33630 grad_norm: 4.7542 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2057 loss: 1.2057 2022/10/15 10:14:45 - mmengine - INFO - Epoch(train) [94][120/940] lr: 1.0000e-04 eta: 1:03:22 time: 0.5825 data_time: 0.0343 memory: 33630 grad_norm: 4.8111 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0104 loss: 1.0104 2022/10/15 10:14:57 - mmengine - INFO - Epoch(train) [94][140/940] lr: 1.0000e-04 eta: 1:03:11 time: 0.5784 data_time: 0.0366 memory: 33630 grad_norm: 4.8071 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1077 loss: 1.1077 2022/10/15 10:15:09 - mmengine - INFO - Epoch(train) [94][160/940] lr: 1.0000e-04 eta: 1:02:59 time: 0.5809 data_time: 0.0437 memory: 33630 grad_norm: 4.8171 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0940 loss: 1.0940 2022/10/15 10:15:20 - mmengine - INFO - Epoch(train) [94][180/940] lr: 1.0000e-04 eta: 1:02:47 time: 0.5788 data_time: 0.0387 memory: 33630 grad_norm: 4.8619 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2426 loss: 1.2426 2022/10/15 10:15:32 - mmengine - INFO - Epoch(train) [94][200/940] lr: 1.0000e-04 eta: 1:02:35 time: 0.5817 data_time: 0.0354 memory: 33630 grad_norm: 4.8570 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2651 loss: 1.2651 2022/10/15 10:15:43 - mmengine - INFO - Epoch(train) [94][220/940] lr: 1.0000e-04 eta: 1:02:23 time: 0.5773 data_time: 0.0371 memory: 33630 grad_norm: 4.8259 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0916 loss: 1.0916 2022/10/15 10:15:55 - mmengine - INFO - Epoch(train) [94][240/940] lr: 1.0000e-04 eta: 1:02:12 time: 0.5854 data_time: 0.0348 memory: 33630 grad_norm: 4.8034 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1889 loss: 1.1889 2022/10/15 10:16:07 - mmengine - INFO - Epoch(train) [94][260/940] lr: 1.0000e-04 eta: 1:02:00 time: 0.5869 data_time: 0.0445 memory: 33630 grad_norm: 4.7574 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1994 loss: 1.1994 2022/10/15 10:16:18 - mmengine - INFO - Epoch(train) [94][280/940] lr: 1.0000e-04 eta: 1:01:48 time: 0.5822 data_time: 0.0443 memory: 33630 grad_norm: 4.8340 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1425 loss: 1.1425 2022/10/15 10:16:30 - mmengine - INFO - Epoch(train) [94][300/940] lr: 1.0000e-04 eta: 1:01:36 time: 0.5848 data_time: 0.0477 memory: 33630 grad_norm: 4.7731 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0308 loss: 1.0308 2022/10/15 10:16:42 - mmengine - INFO - Epoch(train) [94][320/940] lr: 1.0000e-04 eta: 1:01:25 time: 0.5787 data_time: 0.0326 memory: 33630 grad_norm: 4.7357 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0513 loss: 1.0513 2022/10/15 10:16:53 - mmengine - INFO - Epoch(train) [94][340/940] lr: 1.0000e-04 eta: 1:01:13 time: 0.5826 data_time: 0.0373 memory: 33630 grad_norm: 4.7868 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1798 loss: 1.1798 2022/10/15 10:17:05 - mmengine - INFO - Epoch(train) [94][360/940] lr: 1.0000e-04 eta: 1:01:01 time: 0.5863 data_time: 0.0355 memory: 33630 grad_norm: 4.7462 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.0945 loss: 1.0945 2022/10/15 10:17:17 - mmengine - INFO - Epoch(train) [94][380/940] lr: 1.0000e-04 eta: 1:00:49 time: 0.5807 data_time: 0.0340 memory: 33630 grad_norm: 4.8325 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1796 loss: 1.1796 2022/10/15 10:17:28 - mmengine - INFO - Epoch(train) [94][400/940] lr: 1.0000e-04 eta: 1:00:37 time: 0.5801 data_time: 0.0375 memory: 33630 grad_norm: 4.8876 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2473 loss: 1.2473 2022/10/15 10:17:40 - mmengine - INFO - Epoch(train) [94][420/940] lr: 1.0000e-04 eta: 1:00:26 time: 0.5805 data_time: 0.0338 memory: 33630 grad_norm: 4.8526 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1326 loss: 1.1326 2022/10/15 10:17:52 - mmengine - INFO - Epoch(train) [94][440/940] lr: 1.0000e-04 eta: 1:00:14 time: 0.5834 data_time: 0.0359 memory: 33630 grad_norm: 4.8473 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0928 loss: 1.0928 2022/10/15 10:18:03 - mmengine - INFO - Epoch(train) [94][460/940] lr: 1.0000e-04 eta: 1:00:02 time: 0.5737 data_time: 0.0331 memory: 33630 grad_norm: 4.7449 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0907 loss: 1.0907 2022/10/15 10:18:15 - mmengine - INFO - Epoch(train) [94][480/940] lr: 1.0000e-04 eta: 0:59:50 time: 0.5893 data_time: 0.0401 memory: 33630 grad_norm: 4.8534 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0600 loss: 1.0600 2022/10/15 10:18:27 - mmengine - INFO - Epoch(train) [94][500/940] lr: 1.0000e-04 eta: 0:59:39 time: 0.5871 data_time: 0.0495 memory: 33630 grad_norm: 4.7819 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0842 loss: 1.0842 2022/10/15 10:18:38 - mmengine - INFO - Epoch(train) [94][520/940] lr: 1.0000e-04 eta: 0:59:27 time: 0.5912 data_time: 0.0473 memory: 33630 grad_norm: 4.8544 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1976 loss: 1.1976 2022/10/15 10:18:50 - mmengine - INFO - Epoch(train) [94][540/940] lr: 1.0000e-04 eta: 0:59:15 time: 0.5822 data_time: 0.0321 memory: 33630 grad_norm: 4.9372 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2578 loss: 1.2578 2022/10/15 10:19:02 - mmengine - INFO - Epoch(train) [94][560/940] lr: 1.0000e-04 eta: 0:59:03 time: 0.5837 data_time: 0.0424 memory: 33630 grad_norm: 4.8074 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.0585 loss: 1.0585 2022/10/15 10:19:13 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 10:19:13 - mmengine - INFO - Epoch(train) [94][580/940] lr: 1.0000e-04 eta: 0:58:51 time: 0.5741 data_time: 0.0358 memory: 33630 grad_norm: 4.7201 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0547 loss: 1.0547 2022/10/15 10:19:25 - mmengine - INFO - Epoch(train) [94][600/940] lr: 1.0000e-04 eta: 0:58:40 time: 0.5886 data_time: 0.0340 memory: 33630 grad_norm: 4.8665 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0655 loss: 1.0655 2022/10/15 10:19:37 - mmengine - INFO - Epoch(train) [94][620/940] lr: 1.0000e-04 eta: 0:58:28 time: 0.5764 data_time: 0.0311 memory: 33630 grad_norm: 4.7272 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.1054 loss: 1.1054 2022/10/15 10:19:48 - mmengine - INFO - Epoch(train) [94][640/940] lr: 1.0000e-04 eta: 0:58:16 time: 0.5777 data_time: 0.0380 memory: 33630 grad_norm: 4.9045 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.1576 loss: 1.1576 2022/10/15 10:20:00 - mmengine - INFO - Epoch(train) [94][660/940] lr: 1.0000e-04 eta: 0:58:04 time: 0.5794 data_time: 0.0311 memory: 33630 grad_norm: 4.8513 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1726 loss: 1.1726 2022/10/15 10:20:11 - mmengine - INFO - Epoch(train) [94][680/940] lr: 1.0000e-04 eta: 0:57:53 time: 0.5833 data_time: 0.0312 memory: 33630 grad_norm: 4.8120 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1783 loss: 1.1783 2022/10/15 10:20:23 - mmengine - INFO - Epoch(train) [94][700/940] lr: 1.0000e-04 eta: 0:57:41 time: 0.5941 data_time: 0.0527 memory: 33630 grad_norm: 4.8435 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1474 loss: 1.1474 2022/10/15 10:20:35 - mmengine - INFO - Epoch(train) [94][720/940] lr: 1.0000e-04 eta: 0:57:29 time: 0.5750 data_time: 0.0340 memory: 33630 grad_norm: 4.9099 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2342 loss: 1.2342 2022/10/15 10:20:46 - mmengine - INFO - Epoch(train) [94][740/940] lr: 1.0000e-04 eta: 0:57:17 time: 0.5816 data_time: 0.0356 memory: 33630 grad_norm: 4.7470 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2212 loss: 1.2212 2022/10/15 10:20:58 - mmengine - INFO - Epoch(train) [94][760/940] lr: 1.0000e-04 eta: 0:57:05 time: 0.5836 data_time: 0.0351 memory: 33630 grad_norm: 4.7726 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.0436 loss: 1.0436 2022/10/15 10:21:10 - mmengine - INFO - Epoch(train) [94][780/940] lr: 1.0000e-04 eta: 0:56:54 time: 0.5862 data_time: 0.0361 memory: 33630 grad_norm: 4.8346 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0119 loss: 1.0119 2022/10/15 10:21:22 - mmengine - INFO - Epoch(train) [94][800/940] lr: 1.0000e-04 eta: 0:56:42 time: 0.5910 data_time: 0.0347 memory: 33630 grad_norm: 4.8142 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.2117 loss: 1.2117 2022/10/15 10:21:33 - mmengine - INFO - Epoch(train) [94][820/940] lr: 1.0000e-04 eta: 0:56:30 time: 0.5737 data_time: 0.0344 memory: 33630 grad_norm: 4.7081 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1633 loss: 1.1633 2022/10/15 10:21:45 - mmengine - INFO - Epoch(train) [94][840/940] lr: 1.0000e-04 eta: 0:56:18 time: 0.5707 data_time: 0.0335 memory: 33630 grad_norm: 4.7133 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1499 loss: 1.1499 2022/10/15 10:21:56 - mmengine - INFO - Epoch(train) [94][860/940] lr: 1.0000e-04 eta: 0:56:06 time: 0.5855 data_time: 0.0474 memory: 33630 grad_norm: 4.7419 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1546 loss: 1.1546 2022/10/15 10:22:08 - mmengine - INFO - Epoch(train) [94][880/940] lr: 1.0000e-04 eta: 0:55:55 time: 0.5751 data_time: 0.0374 memory: 33630 grad_norm: 4.8223 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1316 loss: 1.1316 2022/10/15 10:22:19 - mmengine - INFO - Epoch(train) [94][900/940] lr: 1.0000e-04 eta: 0:55:43 time: 0.5797 data_time: 0.0381 memory: 33630 grad_norm: 4.8705 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2369 loss: 1.2369 2022/10/15 10:22:31 - mmengine - INFO - Epoch(train) [94][920/940] lr: 1.0000e-04 eta: 0:55:31 time: 0.5855 data_time: 0.0396 memory: 33630 grad_norm: 4.9102 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1859 loss: 1.1859 2022/10/15 10:22:42 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 10:22:42 - mmengine - INFO - Epoch(train) [94][940/940] lr: 1.0000e-04 eta: 0:55:19 time: 0.5390 data_time: 0.0338 memory: 33630 grad_norm: 5.2075 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.4323 loss: 1.4323 2022/10/15 10:22:56 - mmengine - INFO - Epoch(val) [94][20/78] eta: 0:00:39 time: 0.6882 data_time: 0.5188 memory: 5967 2022/10/15 10:23:05 - mmengine - INFO - Epoch(val) [94][40/78] eta: 0:00:18 time: 0.4863 data_time: 0.3190 memory: 5967 2022/10/15 10:23:19 - mmengine - INFO - Epoch(val) [94][60/78] eta: 0:00:12 time: 0.6739 data_time: 0.5059 memory: 5967 2022/10/15 10:23:31 - mmengine - INFO - Epoch(val) [94][78/78] acc/top1: 0.6896 acc/top5: 0.8800 acc/mean1: 0.6895 2022/10/15 10:23:47 - mmengine - INFO - Epoch(train) [95][20/940] lr: 1.0000e-04 eta: 0:55:08 time: 0.8135 data_time: 0.2280 memory: 33630 grad_norm: 4.7723 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0676 loss: 1.0676 2022/10/15 10:23:59 - mmengine - INFO - Epoch(train) [95][40/940] lr: 1.0000e-04 eta: 0:54:56 time: 0.5773 data_time: 0.0324 memory: 33630 grad_norm: 4.8551 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1702 loss: 1.1702 2022/10/15 10:24:11 - mmengine - INFO - Epoch(train) [95][60/940] lr: 1.0000e-04 eta: 0:54:44 time: 0.5980 data_time: 0.0369 memory: 33630 grad_norm: 4.7678 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2726 loss: 1.2726 2022/10/15 10:24:22 - mmengine - INFO - Epoch(train) [95][80/940] lr: 1.0000e-04 eta: 0:54:32 time: 0.5788 data_time: 0.0305 memory: 33630 grad_norm: 4.8149 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1234 loss: 1.1234 2022/10/15 10:24:34 - mmengine - INFO - Epoch(train) [95][100/940] lr: 1.0000e-04 eta: 0:54:21 time: 0.5802 data_time: 0.0326 memory: 33630 grad_norm: 4.7307 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 1.2186 loss: 1.2186 2022/10/15 10:24:46 - mmengine - INFO - Epoch(train) [95][120/940] lr: 1.0000e-04 eta: 0:54:09 time: 0.5800 data_time: 0.0403 memory: 33630 grad_norm: 4.8653 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2127 loss: 1.2127 2022/10/15 10:24:57 - mmengine - INFO - Epoch(train) [95][140/940] lr: 1.0000e-04 eta: 0:53:57 time: 0.5946 data_time: 0.0372 memory: 33630 grad_norm: 4.8422 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.1412 loss: 1.1412 2022/10/15 10:25:09 - mmengine - INFO - Epoch(train) [95][160/940] lr: 1.0000e-04 eta: 0:53:45 time: 0.5792 data_time: 0.0386 memory: 33630 grad_norm: 4.7874 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.0524 loss: 1.0524 2022/10/15 10:25:21 - mmengine - INFO - Epoch(train) [95][180/940] lr: 1.0000e-04 eta: 0:53:34 time: 0.5824 data_time: 0.0439 memory: 33630 grad_norm: 4.8553 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1058 loss: 1.1058 2022/10/15 10:25:32 - mmengine - INFO - Epoch(train) [95][200/940] lr: 1.0000e-04 eta: 0:53:22 time: 0.5773 data_time: 0.0392 memory: 33630 grad_norm: 4.7470 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1852 loss: 1.1852 2022/10/15 10:25:44 - mmengine - INFO - Epoch(train) [95][220/940] lr: 1.0000e-04 eta: 0:53:10 time: 0.5833 data_time: 0.0354 memory: 33630 grad_norm: 4.8802 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2561 loss: 1.2561 2022/10/15 10:25:56 - mmengine - INFO - Epoch(train) [95][240/940] lr: 1.0000e-04 eta: 0:52:58 time: 0.5850 data_time: 0.0451 memory: 33630 grad_norm: 4.8813 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0816 loss: 1.0816 2022/10/15 10:26:07 - mmengine - INFO - Epoch(train) [95][260/940] lr: 1.0000e-04 eta: 0:52:46 time: 0.5771 data_time: 0.0417 memory: 33630 grad_norm: 4.8270 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.0742 loss: 1.0742 2022/10/15 10:26:19 - mmengine - INFO - Epoch(train) [95][280/940] lr: 1.0000e-04 eta: 0:52:35 time: 0.5750 data_time: 0.0386 memory: 33630 grad_norm: 4.9200 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1824 loss: 1.1824 2022/10/15 10:26:30 - mmengine - INFO - Epoch(train) [95][300/940] lr: 1.0000e-04 eta: 0:52:23 time: 0.5781 data_time: 0.0331 memory: 33630 grad_norm: 4.8224 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1783 loss: 1.1783 2022/10/15 10:26:42 - mmengine - INFO - Epoch(train) [95][320/940] lr: 1.0000e-04 eta: 0:52:11 time: 0.5781 data_time: 0.0340 memory: 33630 grad_norm: 4.9255 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1908 loss: 1.1908 2022/10/15 10:26:53 - mmengine - INFO - Epoch(train) [95][340/940] lr: 1.0000e-04 eta: 0:51:59 time: 0.5819 data_time: 0.0408 memory: 33630 grad_norm: 4.7686 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.1450 loss: 1.1450 2022/10/15 10:27:05 - mmengine - INFO - Epoch(train) [95][360/940] lr: 1.0000e-04 eta: 0:51:48 time: 0.5796 data_time: 0.0339 memory: 33630 grad_norm: 4.8403 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1665 loss: 1.1665 2022/10/15 10:27:17 - mmengine - INFO - Epoch(train) [95][380/940] lr: 1.0000e-04 eta: 0:51:36 time: 0.5822 data_time: 0.0413 memory: 33630 grad_norm: 4.9417 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2763 loss: 1.2763 2022/10/15 10:27:28 - mmengine - INFO - Epoch(train) [95][400/940] lr: 1.0000e-04 eta: 0:51:24 time: 0.5914 data_time: 0.0458 memory: 33630 grad_norm: 4.8419 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2715 loss: 1.2715 2022/10/15 10:27:40 - mmengine - INFO - Epoch(train) [95][420/940] lr: 1.0000e-04 eta: 0:51:12 time: 0.5713 data_time: 0.0316 memory: 33630 grad_norm: 4.8681 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2758 loss: 1.2758 2022/10/15 10:27:51 - mmengine - INFO - Epoch(train) [95][440/940] lr: 1.0000e-04 eta: 0:51:00 time: 0.5774 data_time: 0.0337 memory: 33630 grad_norm: 4.8696 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1881 loss: 1.1881 2022/10/15 10:28:03 - mmengine - INFO - Epoch(train) [95][460/940] lr: 1.0000e-04 eta: 0:50:49 time: 0.5768 data_time: 0.0362 memory: 33630 grad_norm: 4.8694 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1257 loss: 1.1257 2022/10/15 10:28:15 - mmengine - INFO - Epoch(train) [95][480/940] lr: 1.0000e-04 eta: 0:50:37 time: 0.5795 data_time: 0.0317 memory: 33630 grad_norm: 4.8019 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2364 loss: 1.2364 2022/10/15 10:28:27 - mmengine - INFO - Epoch(train) [95][500/940] lr: 1.0000e-04 eta: 0:50:25 time: 0.5953 data_time: 0.0477 memory: 33630 grad_norm: 4.9332 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2249 loss: 1.2249 2022/10/15 10:28:38 - mmengine - INFO - Epoch(train) [95][520/940] lr: 1.0000e-04 eta: 0:50:13 time: 0.5755 data_time: 0.0341 memory: 33630 grad_norm: 4.8410 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2451 loss: 1.2451 2022/10/15 10:28:50 - mmengine - INFO - Epoch(train) [95][540/940] lr: 1.0000e-04 eta: 0:50:01 time: 0.5784 data_time: 0.0313 memory: 33630 grad_norm: 4.8127 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2450 loss: 1.2450 2022/10/15 10:29:01 - mmengine - INFO - Epoch(train) [95][560/940] lr: 1.0000e-04 eta: 0:49:50 time: 0.5908 data_time: 0.0331 memory: 33630 grad_norm: 4.8491 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0673 loss: 1.0673 2022/10/15 10:29:13 - mmengine - INFO - Epoch(train) [95][580/940] lr: 1.0000e-04 eta: 0:49:38 time: 0.5741 data_time: 0.0350 memory: 33630 grad_norm: 4.8238 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.1691 loss: 1.1691 2022/10/15 10:29:25 - mmengine - INFO - Epoch(train) [95][600/940] lr: 1.0000e-04 eta: 0:49:26 time: 0.5870 data_time: 0.0357 memory: 33630 grad_norm: 4.9156 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1803 loss: 1.1803 2022/10/15 10:29:36 - mmengine - INFO - Epoch(train) [95][620/940] lr: 1.0000e-04 eta: 0:49:14 time: 0.5738 data_time: 0.0340 memory: 33630 grad_norm: 4.8521 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2601 loss: 1.2601 2022/10/15 10:29:48 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 10:29:48 - mmengine - INFO - Epoch(train) [95][640/940] lr: 1.0000e-04 eta: 0:49:03 time: 0.5802 data_time: 0.0330 memory: 33630 grad_norm: 4.6926 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 0.9791 loss: 0.9791 2022/10/15 10:29:59 - mmengine - INFO - Epoch(train) [95][660/940] lr: 1.0000e-04 eta: 0:48:51 time: 0.5873 data_time: 0.0382 memory: 33630 grad_norm: 4.7454 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0716 loss: 1.0716 2022/10/15 10:30:11 - mmengine - INFO - Epoch(train) [95][680/940] lr: 1.0000e-04 eta: 0:48:39 time: 0.5828 data_time: 0.0367 memory: 33630 grad_norm: 4.8573 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1751 loss: 1.1751 2022/10/15 10:30:23 - mmengine - INFO - Epoch(train) [95][700/940] lr: 1.0000e-04 eta: 0:48:27 time: 0.5767 data_time: 0.0397 memory: 33630 grad_norm: 4.8842 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2056 loss: 1.2056 2022/10/15 10:30:34 - mmengine - INFO - Epoch(train) [95][720/940] lr: 1.0000e-04 eta: 0:48:15 time: 0.5839 data_time: 0.0416 memory: 33630 grad_norm: 4.8748 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1514 loss: 1.1514 2022/10/15 10:30:46 - mmengine - INFO - Epoch(train) [95][740/940] lr: 1.0000e-04 eta: 0:48:04 time: 0.5924 data_time: 0.0358 memory: 33630 grad_norm: 4.8810 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1613 loss: 1.1613 2022/10/15 10:30:58 - mmengine - INFO - Epoch(train) [95][760/940] lr: 1.0000e-04 eta: 0:47:52 time: 0.5828 data_time: 0.0384 memory: 33630 grad_norm: 4.8277 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2424 loss: 1.2424 2022/10/15 10:31:10 - mmengine - INFO - Epoch(train) [95][780/940] lr: 1.0000e-04 eta: 0:47:40 time: 0.5966 data_time: 0.0426 memory: 33630 grad_norm: 4.8361 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0166 loss: 1.0166 2022/10/15 10:31:22 - mmengine - INFO - Epoch(train) [95][800/940] lr: 1.0000e-04 eta: 0:47:28 time: 0.5910 data_time: 0.0395 memory: 33630 grad_norm: 4.7177 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1613 loss: 1.1613 2022/10/15 10:31:33 - mmengine - INFO - Epoch(train) [95][820/940] lr: 1.0000e-04 eta: 0:47:17 time: 0.5835 data_time: 0.0379 memory: 33630 grad_norm: 4.9077 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2337 loss: 1.2337 2022/10/15 10:31:45 - mmengine - INFO - Epoch(train) [95][840/940] lr: 1.0000e-04 eta: 0:47:05 time: 0.5786 data_time: 0.0416 memory: 33630 grad_norm: 4.8867 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1400 loss: 1.1400 2022/10/15 10:31:56 - mmengine - INFO - Epoch(train) [95][860/940] lr: 1.0000e-04 eta: 0:46:53 time: 0.5799 data_time: 0.0394 memory: 33630 grad_norm: 4.7269 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1277 loss: 1.1277 2022/10/15 10:32:08 - mmengine - INFO - Epoch(train) [95][880/940] lr: 1.0000e-04 eta: 0:46:41 time: 0.5712 data_time: 0.0339 memory: 33630 grad_norm: 4.6773 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 0.9860 loss: 0.9860 2022/10/15 10:32:19 - mmengine - INFO - Epoch(train) [95][900/940] lr: 1.0000e-04 eta: 0:46:29 time: 0.5751 data_time: 0.0403 memory: 33630 grad_norm: 4.8431 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1486 loss: 1.1486 2022/10/15 10:32:31 - mmengine - INFO - Epoch(train) [95][920/940] lr: 1.0000e-04 eta: 0:46:18 time: 0.5851 data_time: 0.0350 memory: 33630 grad_norm: 4.8436 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1850 loss: 1.1850 2022/10/15 10:32:42 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 10:32:42 - mmengine - INFO - Epoch(train) [95][940/940] lr: 1.0000e-04 eta: 0:46:06 time: 0.5399 data_time: 0.0317 memory: 33630 grad_norm: 5.0839 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.0752 loss: 1.0752 2022/10/15 10:32:56 - mmengine - INFO - Epoch(val) [95][20/78] eta: 0:00:41 time: 0.7200 data_time: 0.5505 memory: 5967 2022/10/15 10:33:06 - mmengine - INFO - Epoch(val) [95][40/78] eta: 0:00:18 time: 0.4918 data_time: 0.3219 memory: 5967 2022/10/15 10:33:19 - mmengine - INFO - Epoch(val) [95][60/78] eta: 0:00:11 time: 0.6620 data_time: 0.4933 memory: 5967 2022/10/15 10:33:31 - mmengine - INFO - Epoch(val) [95][78/78] acc/top1: 0.6874 acc/top5: 0.8794 acc/mean1: 0.6873 2022/10/15 10:33:48 - mmengine - INFO - Epoch(train) [96][20/940] lr: 1.0000e-04 eta: 0:45:54 time: 0.8477 data_time: 0.2499 memory: 33630 grad_norm: 4.9958 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1689 loss: 1.1689 2022/10/15 10:34:00 - mmengine - INFO - Epoch(train) [96][40/940] lr: 1.0000e-04 eta: 0:45:43 time: 0.5841 data_time: 0.0332 memory: 33630 grad_norm: 4.9344 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2714 loss: 1.2714 2022/10/15 10:34:11 - mmengine - INFO - Epoch(train) [96][60/940] lr: 1.0000e-04 eta: 0:45:31 time: 0.5861 data_time: 0.0393 memory: 33630 grad_norm: 4.7051 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0573 loss: 1.0573 2022/10/15 10:34:23 - mmengine - INFO - Epoch(train) [96][80/940] lr: 1.0000e-04 eta: 0:45:19 time: 0.5919 data_time: 0.0432 memory: 33630 grad_norm: 4.8606 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1431 loss: 1.1431 2022/10/15 10:34:35 - mmengine - INFO - Epoch(train) [96][100/940] lr: 1.0000e-04 eta: 0:45:07 time: 0.5910 data_time: 0.0364 memory: 33630 grad_norm: 4.8349 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1341 loss: 1.1341 2022/10/15 10:34:47 - mmengine - INFO - Epoch(train) [96][120/940] lr: 1.0000e-04 eta: 0:44:55 time: 0.5836 data_time: 0.0368 memory: 33630 grad_norm: 4.9033 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2268 loss: 1.2268 2022/10/15 10:34:58 - mmengine - INFO - Epoch(train) [96][140/940] lr: 1.0000e-04 eta: 0:44:44 time: 0.5797 data_time: 0.0363 memory: 33630 grad_norm: 4.8550 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.2700 loss: 1.2700 2022/10/15 10:35:10 - mmengine - INFO - Epoch(train) [96][160/940] lr: 1.0000e-04 eta: 0:44:32 time: 0.5794 data_time: 0.0378 memory: 33630 grad_norm: 4.8541 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1863 loss: 1.1863 2022/10/15 10:35:21 - mmengine - INFO - Epoch(train) [96][180/940] lr: 1.0000e-04 eta: 0:44:20 time: 0.5780 data_time: 0.0356 memory: 33630 grad_norm: 4.8091 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3259 loss: 1.3259 2022/10/15 10:35:33 - mmengine - INFO - Epoch(train) [96][200/940] lr: 1.0000e-04 eta: 0:44:08 time: 0.5856 data_time: 0.0430 memory: 33630 grad_norm: 4.8442 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.0837 loss: 1.0837 2022/10/15 10:35:45 - mmengine - INFO - Epoch(train) [96][220/940] lr: 1.0000e-04 eta: 0:43:57 time: 0.5901 data_time: 0.0409 memory: 33630 grad_norm: 4.7916 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1448 loss: 1.1448 2022/10/15 10:35:56 - mmengine - INFO - Epoch(train) [96][240/940] lr: 1.0000e-04 eta: 0:43:45 time: 0.5739 data_time: 0.0334 memory: 33630 grad_norm: 4.7795 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.1955 loss: 1.1955 2022/10/15 10:36:08 - mmengine - INFO - Epoch(train) [96][260/940] lr: 1.0000e-04 eta: 0:43:33 time: 0.5931 data_time: 0.0394 memory: 33630 grad_norm: 4.8199 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1168 loss: 1.1168 2022/10/15 10:36:20 - mmengine - INFO - Epoch(train) [96][280/940] lr: 1.0000e-04 eta: 0:43:21 time: 0.5853 data_time: 0.0393 memory: 33630 grad_norm: 4.8386 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1175 loss: 1.1175 2022/10/15 10:36:31 - mmengine - INFO - Epoch(train) [96][300/940] lr: 1.0000e-04 eta: 0:43:09 time: 0.5742 data_time: 0.0347 memory: 33630 grad_norm: 4.7588 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2083 loss: 1.2083 2022/10/15 10:36:43 - mmengine - INFO - Epoch(train) [96][320/940] lr: 1.0000e-04 eta: 0:42:58 time: 0.5723 data_time: 0.0339 memory: 33630 grad_norm: 4.9440 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2565 loss: 1.2565 2022/10/15 10:36:55 - mmengine - INFO - Epoch(train) [96][340/940] lr: 1.0000e-04 eta: 0:42:46 time: 0.5861 data_time: 0.0331 memory: 33630 grad_norm: 4.9277 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1209 loss: 1.1209 2022/10/15 10:37:06 - mmengine - INFO - Epoch(train) [96][360/940] lr: 1.0000e-04 eta: 0:42:34 time: 0.5870 data_time: 0.0385 memory: 33630 grad_norm: 4.7298 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0642 loss: 1.0642 2022/10/15 10:37:18 - mmengine - INFO - Epoch(train) [96][380/940] lr: 1.0000e-04 eta: 0:42:22 time: 0.5719 data_time: 0.0383 memory: 33630 grad_norm: 4.8259 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1760 loss: 1.1760 2022/10/15 10:37:30 - mmengine - INFO - Epoch(train) [96][400/940] lr: 1.0000e-04 eta: 0:42:11 time: 0.5910 data_time: 0.0510 memory: 33630 grad_norm: 4.8384 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1280 loss: 1.1280 2022/10/15 10:37:41 - mmengine - INFO - Epoch(train) [96][420/940] lr: 1.0000e-04 eta: 0:41:59 time: 0.5768 data_time: 0.0370 memory: 33630 grad_norm: 4.9064 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1067 loss: 1.1067 2022/10/15 10:37:53 - mmengine - INFO - Epoch(train) [96][440/940] lr: 1.0000e-04 eta: 0:41:47 time: 0.5998 data_time: 0.0373 memory: 33630 grad_norm: 4.7831 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0592 loss: 1.0592 2022/10/15 10:38:05 - mmengine - INFO - Epoch(train) [96][460/940] lr: 1.0000e-04 eta: 0:41:35 time: 0.5759 data_time: 0.0383 memory: 33630 grad_norm: 4.7999 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2666 loss: 1.2666 2022/10/15 10:38:16 - mmengine - INFO - Epoch(train) [96][480/940] lr: 1.0000e-04 eta: 0:41:23 time: 0.5724 data_time: 0.0349 memory: 33630 grad_norm: 4.8957 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1778 loss: 1.1778 2022/10/15 10:38:28 - mmengine - INFO - Epoch(train) [96][500/940] lr: 1.0000e-04 eta: 0:41:12 time: 0.5754 data_time: 0.0325 memory: 33630 grad_norm: 4.7405 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.1078 loss: 1.1078 2022/10/15 10:38:39 - mmengine - INFO - Epoch(train) [96][520/940] lr: 1.0000e-04 eta: 0:41:00 time: 0.5746 data_time: 0.0356 memory: 33630 grad_norm: 4.8904 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.1883 loss: 1.1883 2022/10/15 10:38:51 - mmengine - INFO - Epoch(train) [96][540/940] lr: 1.0000e-04 eta: 0:40:48 time: 0.5754 data_time: 0.0418 memory: 33630 grad_norm: 4.8133 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.0190 loss: 1.0190 2022/10/15 10:39:02 - mmengine - INFO - Epoch(train) [96][560/940] lr: 1.0000e-04 eta: 0:40:36 time: 0.5908 data_time: 0.0329 memory: 33630 grad_norm: 4.8951 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.1599 loss: 1.1599 2022/10/15 10:39:14 - mmengine - INFO - Epoch(train) [96][580/940] lr: 1.0000e-04 eta: 0:40:25 time: 0.5756 data_time: 0.0353 memory: 33630 grad_norm: 4.7886 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0477 loss: 1.0477 2022/10/15 10:39:25 - mmengine - INFO - Epoch(train) [96][600/940] lr: 1.0000e-04 eta: 0:40:13 time: 0.5750 data_time: 0.0369 memory: 33630 grad_norm: 4.6875 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.2436 loss: 1.2436 2022/10/15 10:39:37 - mmengine - INFO - Epoch(train) [96][620/940] lr: 1.0000e-04 eta: 0:40:01 time: 0.5776 data_time: 0.0318 memory: 33630 grad_norm: 4.7298 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2297 loss: 1.2297 2022/10/15 10:39:49 - mmengine - INFO - Epoch(train) [96][640/940] lr: 1.0000e-04 eta: 0:39:49 time: 0.5849 data_time: 0.0322 memory: 33630 grad_norm: 4.8053 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0728 loss: 1.0728 2022/10/15 10:40:00 - mmengine - INFO - Epoch(train) [96][660/940] lr: 1.0000e-04 eta: 0:39:37 time: 0.5851 data_time: 0.0355 memory: 33630 grad_norm: 4.8833 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.2991 loss: 1.2991 2022/10/15 10:40:12 - mmengine - INFO - Epoch(train) [96][680/940] lr: 1.0000e-04 eta: 0:39:26 time: 0.5889 data_time: 0.0380 memory: 33630 grad_norm: 4.8636 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1682 loss: 1.1682 2022/10/15 10:40:24 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 10:40:24 - mmengine - INFO - Epoch(train) [96][700/940] lr: 1.0000e-04 eta: 0:39:14 time: 0.5798 data_time: 0.0360 memory: 33630 grad_norm: 4.9013 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1499 loss: 1.1499 2022/10/15 10:40:35 - mmengine - INFO - Epoch(train) [96][720/940] lr: 1.0000e-04 eta: 0:39:02 time: 0.5773 data_time: 0.0341 memory: 33630 grad_norm: 4.7762 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1548 loss: 1.1548 2022/10/15 10:40:47 - mmengine - INFO - Epoch(train) [96][740/940] lr: 1.0000e-04 eta: 0:38:50 time: 0.5740 data_time: 0.0341 memory: 33630 grad_norm: 4.9036 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0919 loss: 1.0919 2022/10/15 10:40:58 - mmengine - INFO - Epoch(train) [96][760/940] lr: 1.0000e-04 eta: 0:38:39 time: 0.5827 data_time: 0.0308 memory: 33630 grad_norm: 4.8453 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1595 loss: 1.1595 2022/10/15 10:41:10 - mmengine - INFO - Epoch(train) [96][780/940] lr: 1.0000e-04 eta: 0:38:27 time: 0.5835 data_time: 0.0375 memory: 33630 grad_norm: 4.8740 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0541 loss: 1.0541 2022/10/15 10:41:22 - mmengine - INFO - Epoch(train) [96][800/940] lr: 1.0000e-04 eta: 0:38:15 time: 0.5876 data_time: 0.0387 memory: 33630 grad_norm: 4.8811 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1464 loss: 1.1464 2022/10/15 10:41:33 - mmengine - INFO - Epoch(train) [96][820/940] lr: 1.0000e-04 eta: 0:38:03 time: 0.5713 data_time: 0.0341 memory: 33630 grad_norm: 4.7660 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1407 loss: 1.1407 2022/10/15 10:41:45 - mmengine - INFO - Epoch(train) [96][840/940] lr: 1.0000e-04 eta: 0:37:51 time: 0.5834 data_time: 0.0417 memory: 33630 grad_norm: 4.7548 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0034 loss: 1.0034 2022/10/15 10:41:57 - mmengine - INFO - Epoch(train) [96][860/940] lr: 1.0000e-04 eta: 0:37:40 time: 0.5786 data_time: 0.0346 memory: 33630 grad_norm: 4.8497 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2972 loss: 1.2972 2022/10/15 10:42:08 - mmengine - INFO - Epoch(train) [96][880/940] lr: 1.0000e-04 eta: 0:37:28 time: 0.5856 data_time: 0.0347 memory: 33630 grad_norm: 4.9262 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1651 loss: 1.1651 2022/10/15 10:42:20 - mmengine - INFO - Epoch(train) [96][900/940] lr: 1.0000e-04 eta: 0:37:16 time: 0.5752 data_time: 0.0380 memory: 33630 grad_norm: 4.8834 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1892 loss: 1.1892 2022/10/15 10:42:31 - mmengine - INFO - Epoch(train) [96][920/940] lr: 1.0000e-04 eta: 0:37:04 time: 0.5757 data_time: 0.0339 memory: 33630 grad_norm: 4.8181 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1336 loss: 1.1336 2022/10/15 10:42:42 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 10:42:42 - mmengine - INFO - Epoch(train) [96][940/940] lr: 1.0000e-04 eta: 0:36:52 time: 0.5380 data_time: 0.0294 memory: 33630 grad_norm: 5.0682 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.1642 loss: 1.1642 2022/10/15 10:42:42 - mmengine - INFO - Saving checkpoint at 96 epochs 2022/10/15 10:42:58 - mmengine - INFO - Epoch(val) [96][20/78] eta: 0:00:42 time: 0.7280 data_time: 0.5574 memory: 5967 2022/10/15 10:43:08 - mmengine - INFO - Epoch(val) [96][40/78] eta: 0:00:19 time: 0.5169 data_time: 0.3485 memory: 5967 2022/10/15 10:43:21 - mmengine - INFO - Epoch(val) [96][60/78] eta: 0:00:11 time: 0.6488 data_time: 0.4803 memory: 5967 2022/10/15 10:43:31 - mmengine - INFO - Epoch(val) [96][78/78] acc/top1: 0.6886 acc/top5: 0.8794 acc/mean1: 0.6885 2022/10/15 10:43:48 - mmengine - INFO - Epoch(train) [97][20/940] lr: 1.0000e-04 eta: 0:36:41 time: 0.8576 data_time: 0.2422 memory: 33630 grad_norm: 4.8228 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1402 loss: 1.1402 2022/10/15 10:44:00 - mmengine - INFO - Epoch(train) [97][40/940] lr: 1.0000e-04 eta: 0:36:29 time: 0.5896 data_time: 0.0565 memory: 33630 grad_norm: 4.7856 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1921 loss: 1.1921 2022/10/15 10:44:12 - mmengine - INFO - Epoch(train) [97][60/940] lr: 1.0000e-04 eta: 0:36:17 time: 0.5967 data_time: 0.0371 memory: 33630 grad_norm: 4.9419 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1061 loss: 1.1061 2022/10/15 10:44:24 - mmengine - INFO - Epoch(train) [97][80/940] lr: 1.0000e-04 eta: 0:36:06 time: 0.5922 data_time: 0.0324 memory: 33630 grad_norm: 4.9055 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1012 loss: 1.1012 2022/10/15 10:44:35 - mmengine - INFO - Epoch(train) [97][100/940] lr: 1.0000e-04 eta: 0:35:54 time: 0.5902 data_time: 0.0353 memory: 33630 grad_norm: 4.8092 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1769 loss: 1.1769 2022/10/15 10:44:47 - mmengine - INFO - Epoch(train) [97][120/940] lr: 1.0000e-04 eta: 0:35:42 time: 0.5873 data_time: 0.0389 memory: 33630 grad_norm: 4.7662 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1444 loss: 1.1444 2022/10/15 10:44:59 - mmengine - INFO - Epoch(train) [97][140/940] lr: 1.0000e-04 eta: 0:35:30 time: 0.5859 data_time: 0.0322 memory: 33630 grad_norm: 4.8455 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1853 loss: 1.1853 2022/10/15 10:45:11 - mmengine - INFO - Epoch(train) [97][160/940] lr: 1.0000e-04 eta: 0:35:19 time: 0.5840 data_time: 0.0360 memory: 33630 grad_norm: 4.7680 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1285 loss: 1.1285 2022/10/15 10:45:22 - mmengine - INFO - Epoch(train) [97][180/940] lr: 1.0000e-04 eta: 0:35:07 time: 0.5800 data_time: 0.0379 memory: 33630 grad_norm: 4.8914 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1370 loss: 1.1370 2022/10/15 10:45:34 - mmengine - INFO - Epoch(train) [97][200/940] lr: 1.0000e-04 eta: 0:34:55 time: 0.5811 data_time: 0.0344 memory: 33630 grad_norm: 4.8793 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1357 loss: 1.1357 2022/10/15 10:45:46 - mmengine - INFO - Epoch(train) [97][220/940] lr: 1.0000e-04 eta: 0:34:43 time: 0.5834 data_time: 0.0337 memory: 33630 grad_norm: 4.8871 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2062 loss: 1.2062 2022/10/15 10:45:57 - mmengine - INFO - Epoch(train) [97][240/940] lr: 1.0000e-04 eta: 0:34:31 time: 0.5830 data_time: 0.0397 memory: 33630 grad_norm: 4.7763 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.0727 loss: 1.0727 2022/10/15 10:46:09 - mmengine - INFO - Epoch(train) [97][260/940] lr: 1.0000e-04 eta: 0:34:20 time: 0.5904 data_time: 0.0367 memory: 33630 grad_norm: 4.9114 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2004 loss: 1.2004 2022/10/15 10:46:21 - mmengine - INFO - Epoch(train) [97][280/940] lr: 1.0000e-04 eta: 0:34:08 time: 0.5775 data_time: 0.0387 memory: 33630 grad_norm: 4.8654 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1622 loss: 1.1622 2022/10/15 10:46:32 - mmengine - INFO - Epoch(train) [97][300/940] lr: 1.0000e-04 eta: 0:33:56 time: 0.5770 data_time: 0.0330 memory: 33630 grad_norm: 4.8466 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1718 loss: 1.1718 2022/10/15 10:46:44 - mmengine - INFO - Epoch(train) [97][320/940] lr: 1.0000e-04 eta: 0:33:44 time: 0.5870 data_time: 0.0325 memory: 33630 grad_norm: 4.8008 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1179 loss: 1.1179 2022/10/15 10:46:56 - mmengine - INFO - Epoch(train) [97][340/940] lr: 1.0000e-04 eta: 0:33:33 time: 0.5839 data_time: 0.0469 memory: 33630 grad_norm: 4.8916 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1948 loss: 1.1948 2022/10/15 10:47:07 - mmengine - INFO - Epoch(train) [97][360/940] lr: 1.0000e-04 eta: 0:33:21 time: 0.5755 data_time: 0.0372 memory: 33630 grad_norm: 4.8257 top1_acc: 0.5938 top5_acc: 1.0000 loss_cls: 1.1897 loss: 1.1897 2022/10/15 10:47:19 - mmengine - INFO - Epoch(train) [97][380/940] lr: 1.0000e-04 eta: 0:33:09 time: 0.5743 data_time: 0.0388 memory: 33630 grad_norm: 4.7273 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1655 loss: 1.1655 2022/10/15 10:47:30 - mmengine - INFO - Epoch(train) [97][400/940] lr: 1.0000e-04 eta: 0:32:57 time: 0.5905 data_time: 0.0358 memory: 33630 grad_norm: 4.8615 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0332 loss: 1.0332 2022/10/15 10:47:42 - mmengine - INFO - Epoch(train) [97][420/940] lr: 1.0000e-04 eta: 0:32:45 time: 0.5839 data_time: 0.0397 memory: 33630 grad_norm: 4.7930 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1126 loss: 1.1126 2022/10/15 10:47:54 - mmengine - INFO - Epoch(train) [97][440/940] lr: 1.0000e-04 eta: 0:32:34 time: 0.5775 data_time: 0.0401 memory: 33630 grad_norm: 4.7466 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0064 loss: 1.0064 2022/10/15 10:48:05 - mmengine - INFO - Epoch(train) [97][460/940] lr: 1.0000e-04 eta: 0:32:22 time: 0.5747 data_time: 0.0336 memory: 33630 grad_norm: 4.8014 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0894 loss: 1.0894 2022/10/15 10:48:17 - mmengine - INFO - Epoch(train) [97][480/940] lr: 1.0000e-04 eta: 0:32:10 time: 0.5867 data_time: 0.0394 memory: 33630 grad_norm: 4.8381 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1527 loss: 1.1527 2022/10/15 10:48:29 - mmengine - INFO - Epoch(train) [97][500/940] lr: 1.0000e-04 eta: 0:31:58 time: 0.5856 data_time: 0.0419 memory: 33630 grad_norm: 4.8223 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.1271 loss: 1.1271 2022/10/15 10:48:40 - mmengine - INFO - Epoch(train) [97][520/940] lr: 1.0000e-04 eta: 0:31:47 time: 0.5910 data_time: 0.0361 memory: 33630 grad_norm: 4.7636 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0904 loss: 1.0904 2022/10/15 10:48:52 - mmengine - INFO - Epoch(train) [97][540/940] lr: 1.0000e-04 eta: 0:31:35 time: 0.5843 data_time: 0.0328 memory: 33630 grad_norm: 4.8610 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1531 loss: 1.1531 2022/10/15 10:49:04 - mmengine - INFO - Epoch(train) [97][560/940] lr: 1.0000e-04 eta: 0:31:23 time: 0.5898 data_time: 0.0382 memory: 33630 grad_norm: 4.8479 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1892 loss: 1.1892 2022/10/15 10:49:15 - mmengine - INFO - Epoch(train) [97][580/940] lr: 1.0000e-04 eta: 0:31:11 time: 0.5805 data_time: 0.0379 memory: 33630 grad_norm: 4.8090 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1245 loss: 1.1245 2022/10/15 10:49:27 - mmengine - INFO - Epoch(train) [97][600/940] lr: 1.0000e-04 eta: 0:30:59 time: 0.5834 data_time: 0.0395 memory: 33630 grad_norm: 4.8896 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0917 loss: 1.0917 2022/10/15 10:49:39 - mmengine - INFO - Epoch(train) [97][620/940] lr: 1.0000e-04 eta: 0:30:48 time: 0.5893 data_time: 0.0451 memory: 33630 grad_norm: 4.8447 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2228 loss: 1.2228 2022/10/15 10:49:50 - mmengine - INFO - Epoch(train) [97][640/940] lr: 1.0000e-04 eta: 0:30:36 time: 0.5743 data_time: 0.0364 memory: 33630 grad_norm: 4.8297 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1595 loss: 1.1595 2022/10/15 10:50:02 - mmengine - INFO - Epoch(train) [97][660/940] lr: 1.0000e-04 eta: 0:30:24 time: 0.5797 data_time: 0.0383 memory: 33630 grad_norm: 4.7968 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1464 loss: 1.1464 2022/10/15 10:50:14 - mmengine - INFO - Epoch(train) [97][680/940] lr: 1.0000e-04 eta: 0:30:12 time: 0.5794 data_time: 0.0364 memory: 33630 grad_norm: 4.9147 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2948 loss: 1.2948 2022/10/15 10:50:25 - mmengine - INFO - Epoch(train) [97][700/940] lr: 1.0000e-04 eta: 0:30:01 time: 0.5807 data_time: 0.0393 memory: 33630 grad_norm: 4.8337 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.1117 loss: 1.1117 2022/10/15 10:50:37 - mmengine - INFO - Epoch(train) [97][720/940] lr: 1.0000e-04 eta: 0:29:49 time: 0.5845 data_time: 0.0351 memory: 33630 grad_norm: 4.8351 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1179 loss: 1.1179 2022/10/15 10:50:49 - mmengine - INFO - Epoch(train) [97][740/940] lr: 1.0000e-04 eta: 0:29:37 time: 0.5818 data_time: 0.0333 memory: 33630 grad_norm: 4.8609 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1970 loss: 1.1970 2022/10/15 10:51:00 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 10:51:00 - mmengine - INFO - Epoch(train) [97][760/940] lr: 1.0000e-04 eta: 0:29:25 time: 0.5762 data_time: 0.0383 memory: 33630 grad_norm: 4.7896 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.0760 loss: 1.0760 2022/10/15 10:51:12 - mmengine - INFO - Epoch(train) [97][780/940] lr: 1.0000e-04 eta: 0:29:13 time: 0.5764 data_time: 0.0322 memory: 33630 grad_norm: 4.9038 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1789 loss: 1.1789 2022/10/15 10:51:23 - mmengine - INFO - Epoch(train) [97][800/940] lr: 1.0000e-04 eta: 0:29:02 time: 0.5868 data_time: 0.0395 memory: 33630 grad_norm: 4.8953 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2757 loss: 1.2757 2022/10/15 10:51:35 - mmengine - INFO - Epoch(train) [97][820/940] lr: 1.0000e-04 eta: 0:28:50 time: 0.5807 data_time: 0.0366 memory: 33630 grad_norm: 4.9019 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0871 loss: 1.0871 2022/10/15 10:51:47 - mmengine - INFO - Epoch(train) [97][840/940] lr: 1.0000e-04 eta: 0:28:38 time: 0.5831 data_time: 0.0346 memory: 33630 grad_norm: 4.8326 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1905 loss: 1.1905 2022/10/15 10:51:58 - mmengine - INFO - Epoch(train) [97][860/940] lr: 1.0000e-04 eta: 0:28:26 time: 0.5788 data_time: 0.0391 memory: 33630 grad_norm: 4.8424 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.0951 loss: 1.0951 2022/10/15 10:52:10 - mmengine - INFO - Epoch(train) [97][880/940] lr: 1.0000e-04 eta: 0:28:15 time: 0.5771 data_time: 0.0358 memory: 33630 grad_norm: 4.8086 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2929 loss: 1.2929 2022/10/15 10:52:21 - mmengine - INFO - Epoch(train) [97][900/940] lr: 1.0000e-04 eta: 0:28:03 time: 0.5821 data_time: 0.0339 memory: 33630 grad_norm: 4.8371 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1257 loss: 1.1257 2022/10/15 10:52:33 - mmengine - INFO - Epoch(train) [97][920/940] lr: 1.0000e-04 eta: 0:27:51 time: 0.5839 data_time: 0.0400 memory: 33630 grad_norm: 4.8915 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2171 loss: 1.2171 2022/10/15 10:52:44 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 10:52:44 - mmengine - INFO - Epoch(train) [97][940/940] lr: 1.0000e-04 eta: 0:27:39 time: 0.5358 data_time: 0.0306 memory: 33630 grad_norm: 5.2142 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.1864 loss: 1.1864 2022/10/15 10:52:58 - mmengine - INFO - Epoch(val) [97][20/78] eta: 0:00:40 time: 0.7058 data_time: 0.5363 memory: 5967 2022/10/15 10:53:08 - mmengine - INFO - Epoch(val) [97][40/78] eta: 0:00:18 time: 0.4856 data_time: 0.3163 memory: 5967 2022/10/15 10:53:21 - mmengine - INFO - Epoch(val) [97][60/78] eta: 0:00:11 time: 0.6581 data_time: 0.4865 memory: 5967 2022/10/15 10:53:33 - mmengine - INFO - Epoch(val) [97][78/78] acc/top1: 0.6881 acc/top5: 0.8795 acc/mean1: 0.6880 2022/10/15 10:53:49 - mmengine - INFO - Epoch(train) [98][20/940] lr: 1.0000e-04 eta: 0:27:28 time: 0.8115 data_time: 0.2472 memory: 33630 grad_norm: 4.8155 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2321 loss: 1.2321 2022/10/15 10:54:01 - mmengine - INFO - Epoch(train) [98][40/940] lr: 1.0000e-04 eta: 0:27:16 time: 0.5751 data_time: 0.0340 memory: 33630 grad_norm: 4.8102 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2336 loss: 1.2336 2022/10/15 10:54:13 - mmengine - INFO - Epoch(train) [98][60/940] lr: 1.0000e-04 eta: 0:27:04 time: 0.5911 data_time: 0.0384 memory: 33630 grad_norm: 4.8708 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2008 loss: 1.2008 2022/10/15 10:54:24 - mmengine - INFO - Epoch(train) [98][80/940] lr: 1.0000e-04 eta: 0:26:52 time: 0.5755 data_time: 0.0381 memory: 33630 grad_norm: 4.8524 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2662 loss: 1.2662 2022/10/15 10:54:36 - mmengine - INFO - Epoch(train) [98][100/940] lr: 1.0000e-04 eta: 0:26:40 time: 0.5982 data_time: 0.0340 memory: 33630 grad_norm: 4.8563 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2051 loss: 1.2051 2022/10/15 10:54:48 - mmengine - INFO - Epoch(train) [98][120/940] lr: 1.0000e-04 eta: 0:26:29 time: 0.5870 data_time: 0.0463 memory: 33630 grad_norm: 4.8602 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1834 loss: 1.1834 2022/10/15 10:54:59 - mmengine - INFO - Epoch(train) [98][140/940] lr: 1.0000e-04 eta: 0:26:17 time: 0.5870 data_time: 0.0353 memory: 33630 grad_norm: 4.9329 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0810 loss: 1.0810 2022/10/15 10:55:11 - mmengine - INFO - Epoch(train) [98][160/940] lr: 1.0000e-04 eta: 0:26:05 time: 0.5805 data_time: 0.0337 memory: 33630 grad_norm: 4.9256 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2010 loss: 1.2010 2022/10/15 10:55:23 - mmengine - INFO - Epoch(train) [98][180/940] lr: 1.0000e-04 eta: 0:25:53 time: 0.5878 data_time: 0.0405 memory: 33630 grad_norm: 4.8571 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.0900 loss: 1.0900 2022/10/15 10:55:35 - mmengine - INFO - Epoch(train) [98][200/940] lr: 1.0000e-04 eta: 0:25:42 time: 0.5865 data_time: 0.0314 memory: 33630 grad_norm: 4.8315 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1670 loss: 1.1670 2022/10/15 10:55:46 - mmengine - INFO - Epoch(train) [98][220/940] lr: 1.0000e-04 eta: 0:25:30 time: 0.5836 data_time: 0.0433 memory: 33630 grad_norm: 4.8598 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1666 loss: 1.1666 2022/10/15 10:55:58 - mmengine - INFO - Epoch(train) [98][240/940] lr: 1.0000e-04 eta: 0:25:18 time: 0.5823 data_time: 0.0398 memory: 33630 grad_norm: 4.8602 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1888 loss: 1.1888 2022/10/15 10:56:10 - mmengine - INFO - Epoch(train) [98][260/940] lr: 1.0000e-04 eta: 0:25:06 time: 0.5857 data_time: 0.0363 memory: 33630 grad_norm: 4.7745 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1662 loss: 1.1662 2022/10/15 10:56:21 - mmengine - INFO - Epoch(train) [98][280/940] lr: 1.0000e-04 eta: 0:24:55 time: 0.5775 data_time: 0.0356 memory: 33630 grad_norm: 4.8444 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1001 loss: 1.1001 2022/10/15 10:56:33 - mmengine - INFO - Epoch(train) [98][300/940] lr: 1.0000e-04 eta: 0:24:43 time: 0.5709 data_time: 0.0316 memory: 33630 grad_norm: 4.8529 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1799 loss: 1.1799 2022/10/15 10:56:44 - mmengine - INFO - Epoch(train) [98][320/940] lr: 1.0000e-04 eta: 0:24:31 time: 0.5777 data_time: 0.0354 memory: 33630 grad_norm: 4.8875 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1520 loss: 1.1520 2022/10/15 10:56:56 - mmengine - INFO - Epoch(train) [98][340/940] lr: 1.0000e-04 eta: 0:24:19 time: 0.5872 data_time: 0.0366 memory: 33630 grad_norm: 4.8563 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.0047 loss: 1.0047 2022/10/15 10:57:08 - mmengine - INFO - Epoch(train) [98][360/940] lr: 1.0000e-04 eta: 0:24:07 time: 0.5894 data_time: 0.0469 memory: 33630 grad_norm: 4.7559 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2196 loss: 1.2196 2022/10/15 10:57:19 - mmengine - INFO - Epoch(train) [98][380/940] lr: 1.0000e-04 eta: 0:23:56 time: 0.5778 data_time: 0.0316 memory: 33630 grad_norm: 4.8819 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2108 loss: 1.2108 2022/10/15 10:57:31 - mmengine - INFO - Epoch(train) [98][400/940] lr: 1.0000e-04 eta: 0:23:44 time: 0.5791 data_time: 0.0384 memory: 33630 grad_norm: 4.9015 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2144 loss: 1.2144 2022/10/15 10:57:42 - mmengine - INFO - Epoch(train) [98][420/940] lr: 1.0000e-04 eta: 0:23:32 time: 0.5797 data_time: 0.0379 memory: 33630 grad_norm: 4.8428 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1447 loss: 1.1447 2022/10/15 10:57:54 - mmengine - INFO - Epoch(train) [98][440/940] lr: 1.0000e-04 eta: 0:23:20 time: 0.5789 data_time: 0.0390 memory: 33630 grad_norm: 4.8541 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2484 loss: 1.2484 2022/10/15 10:58:06 - mmengine - INFO - Epoch(train) [98][460/940] lr: 1.0000e-04 eta: 0:23:09 time: 0.5785 data_time: 0.0324 memory: 33630 grad_norm: 4.8602 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1745 loss: 1.1745 2022/10/15 10:58:17 - mmengine - INFO - Epoch(train) [98][480/940] lr: 1.0000e-04 eta: 0:22:57 time: 0.5763 data_time: 0.0374 memory: 33630 grad_norm: 4.9155 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1138 loss: 1.1138 2022/10/15 10:58:29 - mmengine - INFO - Epoch(train) [98][500/940] lr: 1.0000e-04 eta: 0:22:45 time: 0.5820 data_time: 0.0382 memory: 33630 grad_norm: 4.8079 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2352 loss: 1.2352 2022/10/15 10:58:40 - mmengine - INFO - Epoch(train) [98][520/940] lr: 1.0000e-04 eta: 0:22:33 time: 0.5788 data_time: 0.0355 memory: 33630 grad_norm: 4.8828 top1_acc: 0.6875 top5_acc: 0.7188 loss_cls: 1.2617 loss: 1.2617 2022/10/15 10:58:52 - mmengine - INFO - Epoch(train) [98][540/940] lr: 1.0000e-04 eta: 0:22:21 time: 0.5774 data_time: 0.0385 memory: 33630 grad_norm: 4.8646 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.0544 loss: 1.0544 2022/10/15 10:59:04 - mmengine - INFO - Epoch(train) [98][560/940] lr: 1.0000e-04 eta: 0:22:10 time: 0.5816 data_time: 0.0398 memory: 33630 grad_norm: 4.9304 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1538 loss: 1.1538 2022/10/15 10:59:15 - mmengine - INFO - Epoch(train) [98][580/940] lr: 1.0000e-04 eta: 0:21:58 time: 0.5830 data_time: 0.0339 memory: 33630 grad_norm: 4.7948 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1303 loss: 1.1303 2022/10/15 10:59:27 - mmengine - INFO - Epoch(train) [98][600/940] lr: 1.0000e-04 eta: 0:21:46 time: 0.5800 data_time: 0.0348 memory: 33630 grad_norm: 4.7604 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.0759 loss: 1.0759 2022/10/15 10:59:38 - mmengine - INFO - Epoch(train) [98][620/940] lr: 1.0000e-04 eta: 0:21:34 time: 0.5842 data_time: 0.0354 memory: 33630 grad_norm: 4.8488 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.0660 loss: 1.0660 2022/10/15 10:59:50 - mmengine - INFO - Epoch(train) [98][640/940] lr: 1.0000e-04 eta: 0:21:23 time: 0.5900 data_time: 0.0321 memory: 33630 grad_norm: 4.9627 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2212 loss: 1.2212 2022/10/15 11:00:02 - mmengine - INFO - Epoch(train) [98][660/940] lr: 1.0000e-04 eta: 0:21:11 time: 0.5875 data_time: 0.0409 memory: 33630 grad_norm: 4.9204 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3429 loss: 1.3429 2022/10/15 11:00:14 - mmengine - INFO - Epoch(train) [98][680/940] lr: 1.0000e-04 eta: 0:20:59 time: 0.5773 data_time: 0.0534 memory: 33630 grad_norm: 4.9226 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1459 loss: 1.1459 2022/10/15 11:00:25 - mmengine - INFO - Epoch(train) [98][700/940] lr: 1.0000e-04 eta: 0:20:47 time: 0.5956 data_time: 0.0303 memory: 33630 grad_norm: 4.8750 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.1128 loss: 1.1128 2022/10/15 11:00:37 - mmengine - INFO - Epoch(train) [98][720/940] lr: 1.0000e-04 eta: 0:20:35 time: 0.5725 data_time: 0.0320 memory: 33630 grad_norm: 4.8771 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2132 loss: 1.2132 2022/10/15 11:00:49 - mmengine - INFO - Epoch(train) [98][740/940] lr: 1.0000e-04 eta: 0:20:24 time: 0.5799 data_time: 0.0338 memory: 33630 grad_norm: 4.8976 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1540 loss: 1.1540 2022/10/15 11:01:00 - mmengine - INFO - Epoch(train) [98][760/940] lr: 1.0000e-04 eta: 0:20:12 time: 0.5819 data_time: 0.0358 memory: 33630 grad_norm: 4.8179 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1211 loss: 1.1211 2022/10/15 11:01:12 - mmengine - INFO - Epoch(train) [98][780/940] lr: 1.0000e-04 eta: 0:20:00 time: 0.5826 data_time: 0.0404 memory: 33630 grad_norm: 4.9587 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2301 loss: 1.2301 2022/10/15 11:01:24 - mmengine - INFO - Epoch(train) [98][800/940] lr: 1.0000e-04 eta: 0:19:48 time: 0.5892 data_time: 0.0449 memory: 33630 grad_norm: 4.9583 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1858 loss: 1.1858 2022/10/15 11:01:35 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 11:01:35 - mmengine - INFO - Epoch(train) [98][820/940] lr: 1.0000e-04 eta: 0:19:37 time: 0.5852 data_time: 0.0371 memory: 33630 grad_norm: 4.7228 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1090 loss: 1.1090 2022/10/15 11:01:47 - mmengine - INFO - Epoch(train) [98][840/940] lr: 1.0000e-04 eta: 0:19:25 time: 0.5904 data_time: 0.0338 memory: 33630 grad_norm: 4.9103 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2146 loss: 1.2146 2022/10/15 11:01:59 - mmengine - INFO - Epoch(train) [98][860/940] lr: 1.0000e-04 eta: 0:19:13 time: 0.5692 data_time: 0.0386 memory: 33630 grad_norm: 4.8602 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2186 loss: 1.2186 2022/10/15 11:02:10 - mmengine - INFO - Epoch(train) [98][880/940] lr: 1.0000e-04 eta: 0:19:01 time: 0.5883 data_time: 0.0461 memory: 33630 grad_norm: 4.8574 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1727 loss: 1.1727 2022/10/15 11:02:22 - mmengine - INFO - Epoch(train) [98][900/940] lr: 1.0000e-04 eta: 0:18:50 time: 0.5880 data_time: 0.0380 memory: 33630 grad_norm: 4.9604 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2456 loss: 1.2456 2022/10/15 11:02:34 - mmengine - INFO - Epoch(train) [98][920/940] lr: 1.0000e-04 eta: 0:18:38 time: 0.5855 data_time: 0.0401 memory: 33630 grad_norm: 4.8354 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1780 loss: 1.1780 2022/10/15 11:02:44 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 11:02:44 - mmengine - INFO - Epoch(train) [98][940/940] lr: 1.0000e-04 eta: 0:18:26 time: 0.5333 data_time: 0.0288 memory: 33630 grad_norm: 5.0510 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1058 loss: 1.1058 2022/10/15 11:02:58 - mmengine - INFO - Epoch(val) [98][20/78] eta: 0:00:40 time: 0.7013 data_time: 0.5302 memory: 5967 2022/10/15 11:03:09 - mmengine - INFO - Epoch(val) [98][40/78] eta: 0:00:19 time: 0.5184 data_time: 0.3503 memory: 5967 2022/10/15 11:03:24 - mmengine - INFO - Epoch(val) [98][60/78] eta: 0:00:13 time: 0.7334 data_time: 0.5643 memory: 5967 2022/10/15 11:03:33 - mmengine - INFO - Epoch(val) [98][78/78] acc/top1: 0.6878 acc/top5: 0.8795 acc/mean1: 0.6876 2022/10/15 11:03:50 - mmengine - INFO - Epoch(train) [99][20/940] lr: 1.0000e-04 eta: 0:18:14 time: 0.8381 data_time: 0.2630 memory: 33630 grad_norm: 4.8552 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2076 loss: 1.2076 2022/10/15 11:04:02 - mmengine - INFO - Epoch(train) [99][40/940] lr: 1.0000e-04 eta: 0:18:03 time: 0.6046 data_time: 0.0308 memory: 33630 grad_norm: 4.8316 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1329 loss: 1.1329 2022/10/15 11:04:15 - mmengine - INFO - Epoch(train) [99][60/940] lr: 1.0000e-04 eta: 0:17:51 time: 0.6152 data_time: 0.0348 memory: 33630 grad_norm: 4.8292 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1106 loss: 1.1106 2022/10/15 11:04:26 - mmengine - INFO - Epoch(train) [99][80/940] lr: 1.0000e-04 eta: 0:17:39 time: 0.5977 data_time: 0.0325 memory: 33630 grad_norm: 4.8053 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1778 loss: 1.1778 2022/10/15 11:04:38 - mmengine - INFO - Epoch(train) [99][100/940] lr: 1.0000e-04 eta: 0:17:27 time: 0.5946 data_time: 0.0410 memory: 33630 grad_norm: 4.8617 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1601 loss: 1.1601 2022/10/15 11:04:50 - mmengine - INFO - Epoch(train) [99][120/940] lr: 1.0000e-04 eta: 0:17:15 time: 0.5945 data_time: 0.0392 memory: 33630 grad_norm: 5.0084 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1491 loss: 1.1491 2022/10/15 11:05:02 - mmengine - INFO - Epoch(train) [99][140/940] lr: 1.0000e-04 eta: 0:17:04 time: 0.5900 data_time: 0.0480 memory: 33630 grad_norm: 4.8248 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0723 loss: 1.0723 2022/10/15 11:05:14 - mmengine - INFO - Epoch(train) [99][160/940] lr: 1.0000e-04 eta: 0:16:52 time: 0.5801 data_time: 0.0367 memory: 33630 grad_norm: 4.8618 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.1657 loss: 1.1657 2022/10/15 11:05:25 - mmengine - INFO - Epoch(train) [99][180/940] lr: 1.0000e-04 eta: 0:16:40 time: 0.5781 data_time: 0.0329 memory: 33630 grad_norm: 4.8012 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2297 loss: 1.2297 2022/10/15 11:05:37 - mmengine - INFO - Epoch(train) [99][200/940] lr: 1.0000e-04 eta: 0:16:28 time: 0.5857 data_time: 0.0345 memory: 33630 grad_norm: 4.7236 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0650 loss: 1.0650 2022/10/15 11:05:48 - mmengine - INFO - Epoch(train) [99][220/940] lr: 1.0000e-04 eta: 0:16:17 time: 0.5763 data_time: 0.0301 memory: 33630 grad_norm: 4.8704 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2381 loss: 1.2381 2022/10/15 11:06:00 - mmengine - INFO - Epoch(train) [99][240/940] lr: 1.0000e-04 eta: 0:16:05 time: 0.5828 data_time: 0.0315 memory: 33630 grad_norm: 4.8207 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.1406 loss: 1.1406 2022/10/15 11:06:12 - mmengine - INFO - Epoch(train) [99][260/940] lr: 1.0000e-04 eta: 0:15:53 time: 0.5796 data_time: 0.0358 memory: 33630 grad_norm: 4.8955 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1057 loss: 1.1057 2022/10/15 11:06:23 - mmengine - INFO - Epoch(train) [99][280/940] lr: 1.0000e-04 eta: 0:15:41 time: 0.5851 data_time: 0.0329 memory: 33630 grad_norm: 4.8816 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1186 loss: 1.1186 2022/10/15 11:06:35 - mmengine - INFO - Epoch(train) [99][300/940] lr: 1.0000e-04 eta: 0:15:29 time: 0.5719 data_time: 0.0329 memory: 33630 grad_norm: 4.8370 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1038 loss: 1.1038 2022/10/15 11:06:47 - mmengine - INFO - Epoch(train) [99][320/940] lr: 1.0000e-04 eta: 0:15:18 time: 0.5897 data_time: 0.0379 memory: 33630 grad_norm: 4.8004 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.0746 loss: 1.0746 2022/10/15 11:06:58 - mmengine - INFO - Epoch(train) [99][340/940] lr: 1.0000e-04 eta: 0:15:06 time: 0.5869 data_time: 0.0410 memory: 33630 grad_norm: 4.8579 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0170 loss: 1.0170 2022/10/15 11:07:10 - mmengine - INFO - Epoch(train) [99][360/940] lr: 1.0000e-04 eta: 0:14:54 time: 0.5779 data_time: 0.0379 memory: 33630 grad_norm: 4.7467 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.0846 loss: 1.0846 2022/10/15 11:07:22 - mmengine - INFO - Epoch(train) [99][380/940] lr: 1.0000e-04 eta: 0:14:42 time: 0.5872 data_time: 0.0427 memory: 33630 grad_norm: 4.8938 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.2200 loss: 1.2200 2022/10/15 11:07:33 - mmengine - INFO - Epoch(train) [99][400/940] lr: 1.0000e-04 eta: 0:14:31 time: 0.5756 data_time: 0.0421 memory: 33630 grad_norm: 4.8750 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.1636 loss: 1.1636 2022/10/15 11:07:45 - mmengine - INFO - Epoch(train) [99][420/940] lr: 1.0000e-04 eta: 0:14:19 time: 0.5772 data_time: 0.0351 memory: 33630 grad_norm: 4.7106 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.0569 loss: 1.0569 2022/10/15 11:07:56 - mmengine - INFO - Epoch(train) [99][440/940] lr: 1.0000e-04 eta: 0:14:07 time: 0.5787 data_time: 0.0424 memory: 33630 grad_norm: 4.8377 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1046 loss: 1.1046 2022/10/15 11:08:08 - mmengine - INFO - Epoch(train) [99][460/940] lr: 1.0000e-04 eta: 0:13:55 time: 0.5962 data_time: 0.0414 memory: 33630 grad_norm: 4.8407 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1657 loss: 1.1657 2022/10/15 11:08:20 - mmengine - INFO - Epoch(train) [99][480/940] lr: 1.0000e-04 eta: 0:13:44 time: 0.5828 data_time: 0.0345 memory: 33630 grad_norm: 4.8129 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2149 loss: 1.2149 2022/10/15 11:08:32 - mmengine - INFO - Epoch(train) [99][500/940] lr: 1.0000e-04 eta: 0:13:32 time: 0.5883 data_time: 0.0468 memory: 33630 grad_norm: 4.8992 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.0640 loss: 1.0640 2022/10/15 11:08:43 - mmengine - INFO - Epoch(train) [99][520/940] lr: 1.0000e-04 eta: 0:13:20 time: 0.5789 data_time: 0.0343 memory: 33630 grad_norm: 4.9089 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.0821 loss: 1.0821 2022/10/15 11:08:55 - mmengine - INFO - Epoch(train) [99][540/940] lr: 1.0000e-04 eta: 0:13:08 time: 0.5787 data_time: 0.0450 memory: 33630 grad_norm: 4.7368 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1391 loss: 1.1391 2022/10/15 11:09:07 - mmengine - INFO - Epoch(train) [99][560/940] lr: 1.0000e-04 eta: 0:12:56 time: 0.5847 data_time: 0.0332 memory: 33630 grad_norm: 4.7156 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1605 loss: 1.1605 2022/10/15 11:09:18 - mmengine - INFO - Epoch(train) [99][580/940] lr: 1.0000e-04 eta: 0:12:45 time: 0.5770 data_time: 0.0428 memory: 33630 grad_norm: 4.8479 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1614 loss: 1.1614 2022/10/15 11:09:30 - mmengine - INFO - Epoch(train) [99][600/940] lr: 1.0000e-04 eta: 0:12:33 time: 0.5874 data_time: 0.0424 memory: 33630 grad_norm: 4.9292 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3296 loss: 1.3296 2022/10/15 11:09:41 - mmengine - INFO - Epoch(train) [99][620/940] lr: 1.0000e-04 eta: 0:12:21 time: 0.5754 data_time: 0.0352 memory: 33630 grad_norm: 4.7640 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 0.9132 loss: 0.9132 2022/10/15 11:09:53 - mmengine - INFO - Epoch(train) [99][640/940] lr: 1.0000e-04 eta: 0:12:09 time: 0.5801 data_time: 0.0401 memory: 33630 grad_norm: 4.8264 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.1564 loss: 1.1564 2022/10/15 11:10:05 - mmengine - INFO - Epoch(train) [99][660/940] lr: 1.0000e-04 eta: 0:11:58 time: 0.5844 data_time: 0.0350 memory: 33630 grad_norm: 4.6636 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.0669 loss: 1.0669 2022/10/15 11:10:16 - mmengine - INFO - Epoch(train) [99][680/940] lr: 1.0000e-04 eta: 0:11:46 time: 0.5850 data_time: 0.0332 memory: 33630 grad_norm: 4.8896 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2200 loss: 1.2200 2022/10/15 11:10:28 - mmengine - INFO - Epoch(train) [99][700/940] lr: 1.0000e-04 eta: 0:11:34 time: 0.5812 data_time: 0.0413 memory: 33630 grad_norm: 4.8427 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2306 loss: 1.2306 2022/10/15 11:10:40 - mmengine - INFO - Epoch(train) [99][720/940] lr: 1.0000e-04 eta: 0:11:22 time: 0.5805 data_time: 0.0355 memory: 33630 grad_norm: 4.8523 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2255 loss: 1.2255 2022/10/15 11:10:51 - mmengine - INFO - Epoch(train) [99][740/940] lr: 1.0000e-04 eta: 0:11:10 time: 0.5855 data_time: 0.0391 memory: 33630 grad_norm: 4.7433 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2659 loss: 1.2659 2022/10/15 11:11:03 - mmengine - INFO - Epoch(train) [99][760/940] lr: 1.0000e-04 eta: 0:10:59 time: 0.5686 data_time: 0.0359 memory: 33630 grad_norm: 4.9100 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1369 loss: 1.1369 2022/10/15 11:11:14 - mmengine - INFO - Epoch(train) [99][780/940] lr: 1.0000e-04 eta: 0:10:47 time: 0.5790 data_time: 0.0321 memory: 33630 grad_norm: 4.8356 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1473 loss: 1.1473 2022/10/15 11:11:26 - mmengine - INFO - Epoch(train) [99][800/940] lr: 1.0000e-04 eta: 0:10:35 time: 0.5982 data_time: 0.0397 memory: 33630 grad_norm: 4.9090 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2989 loss: 1.2989 2022/10/15 11:11:38 - mmengine - INFO - Epoch(train) [99][820/940] lr: 1.0000e-04 eta: 0:10:23 time: 0.5717 data_time: 0.0417 memory: 33630 grad_norm: 4.8084 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1389 loss: 1.1389 2022/10/15 11:11:49 - mmengine - INFO - Epoch(train) [99][840/940] lr: 1.0000e-04 eta: 0:10:12 time: 0.5815 data_time: 0.0500 memory: 33630 grad_norm: 4.7100 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1626 loss: 1.1626 2022/10/15 11:12:01 - mmengine - INFO - Epoch(train) [99][860/940] lr: 1.0000e-04 eta: 0:10:00 time: 0.5808 data_time: 0.0389 memory: 33630 grad_norm: 4.7903 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1392 loss: 1.1392 2022/10/15 11:12:13 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 11:12:13 - mmengine - INFO - Epoch(train) [99][880/940] lr: 1.0000e-04 eta: 0:09:48 time: 0.5779 data_time: 0.0433 memory: 33630 grad_norm: 4.7420 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0178 loss: 1.0178 2022/10/15 11:12:24 - mmengine - INFO - Epoch(train) [99][900/940] lr: 1.0000e-04 eta: 0:09:36 time: 0.5820 data_time: 0.0403 memory: 33630 grad_norm: 4.7936 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1340 loss: 1.1340 2022/10/15 11:12:36 - mmengine - INFO - Epoch(train) [99][920/940] lr: 1.0000e-04 eta: 0:09:25 time: 0.5936 data_time: 0.0313 memory: 33630 grad_norm: 4.7730 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.1867 loss: 1.1867 2022/10/15 11:12:47 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 11:12:47 - mmengine - INFO - Epoch(train) [99][940/940] lr: 1.0000e-04 eta: 0:09:13 time: 0.5434 data_time: 0.0294 memory: 33630 grad_norm: 5.1534 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.0669 loss: 1.0669 2022/10/15 11:12:47 - mmengine - INFO - Saving checkpoint at 99 epochs 2022/10/15 11:13:02 - mmengine - INFO - Epoch(val) [99][20/78] eta: 0:00:42 time: 0.7270 data_time: 0.5568 memory: 5967 2022/10/15 11:13:13 - mmengine - INFO - Epoch(val) [99][40/78] eta: 0:00:19 time: 0.5233 data_time: 0.3527 memory: 5967 2022/10/15 11:13:26 - mmengine - INFO - Epoch(val) [99][60/78] eta: 0:00:11 time: 0.6541 data_time: 0.4870 memory: 5967 2022/10/15 11:13:36 - mmengine - INFO - Epoch(val) [99][78/78] acc/top1: 0.6884 acc/top5: 0.8800 acc/mean1: 0.6883 2022/10/15 11:13:54 - mmengine - INFO - Epoch(train) [100][20/940] lr: 1.0000e-04 eta: 0:09:01 time: 0.8783 data_time: 0.2648 memory: 33630 grad_norm: 4.8034 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1600 loss: 1.1600 2022/10/15 11:14:05 - mmengine - INFO - Epoch(train) [100][40/940] lr: 1.0000e-04 eta: 0:08:49 time: 0.5989 data_time: 0.0441 memory: 33630 grad_norm: 4.8501 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0789 loss: 1.0789 2022/10/15 11:14:18 - mmengine - INFO - Epoch(train) [100][60/940] lr: 1.0000e-04 eta: 0:08:37 time: 0.6050 data_time: 0.0373 memory: 33630 grad_norm: 4.8901 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.1849 loss: 1.1849 2022/10/15 11:14:29 - mmengine - INFO - Epoch(train) [100][80/940] lr: 1.0000e-04 eta: 0:08:26 time: 0.5781 data_time: 0.0335 memory: 33630 grad_norm: 4.8386 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1783 loss: 1.1783 2022/10/15 11:14:41 - mmengine - INFO - Epoch(train) [100][100/940] lr: 1.0000e-04 eta: 0:08:14 time: 0.5787 data_time: 0.0337 memory: 33630 grad_norm: 4.7776 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.0516 loss: 1.0516 2022/10/15 11:14:53 - mmengine - INFO - Epoch(train) [100][120/940] lr: 1.0000e-04 eta: 0:08:02 time: 0.5887 data_time: 0.0327 memory: 33630 grad_norm: 4.7691 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1710 loss: 1.1710 2022/10/15 11:15:04 - mmengine - INFO - Epoch(train) [100][140/940] lr: 1.0000e-04 eta: 0:07:50 time: 0.5763 data_time: 0.0378 memory: 33630 grad_norm: 4.8256 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2127 loss: 1.2127 2022/10/15 11:15:16 - mmengine - INFO - Epoch(train) [100][160/940] lr: 1.0000e-04 eta: 0:07:39 time: 0.5805 data_time: 0.0321 memory: 33630 grad_norm: 4.8573 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2507 loss: 1.2507 2022/10/15 11:15:27 - mmengine - INFO - Epoch(train) [100][180/940] lr: 1.0000e-04 eta: 0:07:27 time: 0.5812 data_time: 0.0422 memory: 33630 grad_norm: 4.8409 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2135 loss: 1.2135 2022/10/15 11:15:39 - mmengine - INFO - Epoch(train) [100][200/940] lr: 1.0000e-04 eta: 0:07:15 time: 0.5821 data_time: 0.0323 memory: 33630 grad_norm: 4.8717 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.0687 loss: 1.0687 2022/10/15 11:15:51 - mmengine - INFO - Epoch(train) [100][220/940] lr: 1.0000e-04 eta: 0:07:03 time: 0.5842 data_time: 0.0432 memory: 33630 grad_norm: 4.8505 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2090 loss: 1.2090 2022/10/15 11:16:02 - mmengine - INFO - Epoch(train) [100][240/940] lr: 1.0000e-04 eta: 0:06:52 time: 0.5725 data_time: 0.0368 memory: 33630 grad_norm: 4.9951 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2633 loss: 1.2633 2022/10/15 11:16:14 - mmengine - INFO - Epoch(train) [100][260/940] lr: 1.0000e-04 eta: 0:06:40 time: 0.5765 data_time: 0.0386 memory: 33630 grad_norm: 4.7898 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3510 loss: 1.3510 2022/10/15 11:16:25 - mmengine - INFO - Epoch(train) [100][280/940] lr: 1.0000e-04 eta: 0:06:28 time: 0.5837 data_time: 0.0315 memory: 33630 grad_norm: 4.7737 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1093 loss: 1.1093 2022/10/15 11:16:37 - mmengine - INFO - Epoch(train) [100][300/940] lr: 1.0000e-04 eta: 0:06:16 time: 0.5800 data_time: 0.0328 memory: 33630 grad_norm: 4.8913 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.1346 loss: 1.1346 2022/10/15 11:16:48 - mmengine - INFO - Epoch(train) [100][320/940] lr: 1.0000e-04 eta: 0:06:04 time: 0.5775 data_time: 0.0392 memory: 33630 grad_norm: 4.8210 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0753 loss: 1.0753 2022/10/15 11:17:00 - mmengine - INFO - Epoch(train) [100][340/940] lr: 1.0000e-04 eta: 0:05:53 time: 0.5770 data_time: 0.0414 memory: 33630 grad_norm: 4.7908 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.0929 loss: 1.0929 2022/10/15 11:17:12 - mmengine - INFO - Epoch(train) [100][360/940] lr: 1.0000e-04 eta: 0:05:41 time: 0.5841 data_time: 0.0394 memory: 33630 grad_norm: 4.8770 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1774 loss: 1.1774 2022/10/15 11:17:23 - mmengine - INFO - Epoch(train) [100][380/940] lr: 1.0000e-04 eta: 0:05:29 time: 0.5858 data_time: 0.0332 memory: 33630 grad_norm: 4.9002 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1655 loss: 1.1655 2022/10/15 11:17:35 - mmengine - INFO - Epoch(train) [100][400/940] lr: 1.0000e-04 eta: 0:05:17 time: 0.5786 data_time: 0.0396 memory: 33630 grad_norm: 4.8192 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.2938 loss: 1.2938 2022/10/15 11:17:47 - mmengine - INFO - Epoch(train) [100][420/940] lr: 1.0000e-04 eta: 0:05:06 time: 0.5832 data_time: 0.0345 memory: 33630 grad_norm: 4.8837 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.1531 loss: 1.1531 2022/10/15 11:17:58 - mmengine - INFO - Epoch(train) [100][440/940] lr: 1.0000e-04 eta: 0:04:54 time: 0.5784 data_time: 0.0419 memory: 33630 grad_norm: 4.8638 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1610 loss: 1.1610 2022/10/15 11:18:10 - mmengine - INFO - Epoch(train) [100][460/940] lr: 1.0000e-04 eta: 0:04:42 time: 0.5865 data_time: 0.0419 memory: 33630 grad_norm: 4.8746 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.1141 loss: 1.1141 2022/10/15 11:18:22 - mmengine - INFO - Epoch(train) [100][480/940] lr: 1.0000e-04 eta: 0:04:30 time: 0.5874 data_time: 0.0328 memory: 33630 grad_norm: 4.8512 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.1571 loss: 1.1571 2022/10/15 11:18:33 - mmengine - INFO - Epoch(train) [100][500/940] lr: 1.0000e-04 eta: 0:04:18 time: 0.5777 data_time: 0.0455 memory: 33630 grad_norm: 4.8789 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1502 loss: 1.1502 2022/10/15 11:18:45 - mmengine - INFO - Epoch(train) [100][520/940] lr: 1.0000e-04 eta: 0:04:07 time: 0.5755 data_time: 0.0391 memory: 33630 grad_norm: 4.8648 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1802 loss: 1.1802 2022/10/15 11:18:56 - mmengine - INFO - Epoch(train) [100][540/940] lr: 1.0000e-04 eta: 0:03:55 time: 0.5783 data_time: 0.0343 memory: 33630 grad_norm: 4.9114 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1064 loss: 1.1064 2022/10/15 11:19:08 - mmengine - INFO - Epoch(train) [100][560/940] lr: 1.0000e-04 eta: 0:03:43 time: 0.5869 data_time: 0.0351 memory: 33630 grad_norm: 4.8093 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.0768 loss: 1.0768 2022/10/15 11:19:20 - mmengine - INFO - Epoch(train) [100][580/940] lr: 1.0000e-04 eta: 0:03:31 time: 0.5893 data_time: 0.0347 memory: 33630 grad_norm: 4.7406 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1253 loss: 1.1253 2022/10/15 11:19:31 - mmengine - INFO - Epoch(train) [100][600/940] lr: 1.0000e-04 eta: 0:03:20 time: 0.5778 data_time: 0.0326 memory: 33630 grad_norm: 4.8316 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1892 loss: 1.1892 2022/10/15 11:19:43 - mmengine - INFO - Epoch(train) [100][620/940] lr: 1.0000e-04 eta: 0:03:08 time: 0.5776 data_time: 0.0315 memory: 33630 grad_norm: 4.8087 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1325 loss: 1.1325 2022/10/15 11:19:55 - mmengine - INFO - Epoch(train) [100][640/940] lr: 1.0000e-04 eta: 0:02:56 time: 0.5817 data_time: 0.0346 memory: 33630 grad_norm: 4.8497 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1620 loss: 1.1620 2022/10/15 11:20:06 - mmengine - INFO - Epoch(train) [100][660/940] lr: 1.0000e-04 eta: 0:02:44 time: 0.5865 data_time: 0.0332 memory: 33630 grad_norm: 4.7556 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0137 loss: 1.0137 2022/10/15 11:20:18 - mmengine - INFO - Epoch(train) [100][680/940] lr: 1.0000e-04 eta: 0:02:33 time: 0.5926 data_time: 0.0357 memory: 33630 grad_norm: 4.7347 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.0550 loss: 1.0550 2022/10/15 11:20:30 - mmengine - INFO - Epoch(train) [100][700/940] lr: 1.0000e-04 eta: 0:02:21 time: 0.5853 data_time: 0.0335 memory: 33630 grad_norm: 4.7657 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.1507 loss: 1.1507 2022/10/15 11:20:41 - mmengine - INFO - Epoch(train) [100][720/940] lr: 1.0000e-04 eta: 0:02:09 time: 0.5768 data_time: 0.0462 memory: 33630 grad_norm: 4.8375 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1699 loss: 1.1699 2022/10/15 11:20:53 - mmengine - INFO - Epoch(train) [100][740/940] lr: 1.0000e-04 eta: 0:01:57 time: 0.5823 data_time: 0.0345 memory: 33630 grad_norm: 4.8612 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2484 loss: 1.2484 2022/10/15 11:21:04 - mmengine - INFO - Epoch(train) [100][760/940] lr: 1.0000e-04 eta: 0:01:45 time: 0.5704 data_time: 0.0325 memory: 33630 grad_norm: 4.8122 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.0894 loss: 1.0894 2022/10/15 11:21:16 - mmengine - INFO - Epoch(train) [100][780/940] lr: 1.0000e-04 eta: 0:01:34 time: 0.5843 data_time: 0.0367 memory: 33630 grad_norm: 4.7183 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1154 loss: 1.1154 2022/10/15 11:21:28 - mmengine - INFO - Epoch(train) [100][800/940] lr: 1.0000e-04 eta: 0:01:22 time: 0.5795 data_time: 0.0406 memory: 33630 grad_norm: 4.8352 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.0138 loss: 1.0138 2022/10/15 11:21:39 - mmengine - INFO - Epoch(train) [100][820/940] lr: 1.0000e-04 eta: 0:01:10 time: 0.5754 data_time: 0.0362 memory: 33630 grad_norm: 4.9131 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.0318 loss: 1.0318 2022/10/15 11:21:51 - mmengine - INFO - Epoch(train) [100][840/940] lr: 1.0000e-04 eta: 0:00:58 time: 0.5869 data_time: 0.0398 memory: 33630 grad_norm: 4.8397 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1862 loss: 1.1862 2022/10/15 11:22:03 - mmengine - INFO - Epoch(train) [100][860/940] lr: 1.0000e-04 eta: 0:00:47 time: 0.5881 data_time: 0.0385 memory: 33630 grad_norm: 4.8478 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0607 loss: 1.0607 2022/10/15 11:22:14 - mmengine - INFO - Epoch(train) [100][880/940] lr: 1.0000e-04 eta: 0:00:35 time: 0.5802 data_time: 0.0488 memory: 33630 grad_norm: 4.9008 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1634 loss: 1.1634 2022/10/15 11:22:26 - mmengine - INFO - Epoch(train) [100][900/940] lr: 1.0000e-04 eta: 0:00:23 time: 0.5775 data_time: 0.0448 memory: 33630 grad_norm: 4.8558 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2712 loss: 1.2712 2022/10/15 11:22:38 - mmengine - INFO - Epoch(train) [100][920/940] lr: 1.0000e-04 eta: 0:00:11 time: 0.5825 data_time: 0.0422 memory: 33630 grad_norm: 4.7949 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.0935 loss: 1.0935 2022/10/15 11:22:48 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-16x4x1-100e_kinetics400-rgb_20221014_183809 2022/10/15 11:22:48 - mmengine - INFO - Epoch(train) [100][940/940] lr: 1.0000e-04 eta: 0:00:00 time: 0.5370 data_time: 0.0294 memory: 33630 grad_norm: 5.0033 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.1719 loss: 1.1719 2022/10/15 11:22:48 - mmengine - INFO - Saving checkpoint at 100 epochs 2022/10/15 11:23:04 - mmengine - INFO - Epoch(val) [100][20/78] eta: 0:00:41 time: 0.7204 data_time: 0.5483 memory: 5967 2022/10/15 11:23:14 - mmengine - INFO - Epoch(val) [100][40/78] eta: 0:00:18 time: 0.4989 data_time: 0.3311 memory: 5967 2022/10/15 11:23:28 - mmengine - INFO - Epoch(val) [100][60/78] eta: 0:00:12 time: 0.6970 data_time: 0.5254 memory: 5967 2022/10/15 11:23:38 - mmengine - INFO - Epoch(val) [100][78/78] acc/top1: 0.6874 acc/top5: 0.8793 acc/mean1: 0.6873