2022/10/12 22:31:29 - 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: 177911072 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 ------------------------------------------------------------ 2022/10/12 22:31:29 - 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=8, frame_interval=8, 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=8, frame_interval=8, num_clips=1, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ] test_pipeline = [ dict( type='DecordInit', io_backend='petrel', path_mapping=dict( {'data/kinetics400': 's3://openmmlab/datasets/action/Kinetics400'})), dict( type='SampleFrames', clip_len=8, frame_interval=8, 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=8, frame_interval=8, 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=8, frame_interval=8, num_clips=1, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True)) test_dataloader = dict( batch_size=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=8, frame_interval=8, 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_8xb32-8x8x1-100e_kinetics400-rgb' 2022/10/12 22:31:31 - mmengine - INFO - These parameters in pretrained checkpoint are not loaded: {'fc.weight', 'fc.bias'} 2022/10/12 22:31:31 - mmengine - INFO - Checkpoints will be saved to /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb. 2022/10/12 22:31:52 - mmengine - INFO - Epoch(train) [1][20/940] lr: 1.0000e-02 eta: 1 day, 2:57:13 time: 1.0325 data_time: 0.6321 memory: 17006 grad_norm: 1.0214 top1_acc: 0.0000 top5_acc: 0.0312 loss_cls: 5.9779 loss: 5.9779 2022/10/12 22:32:03 - mmengine - INFO - Epoch(train) [1][40/940] lr: 1.0000e-02 eta: 20:51:54 time: 0.5664 data_time: 0.2393 memory: 17006 grad_norm: 1.0972 top1_acc: 0.0000 top5_acc: 0.0938 loss_cls: 5.9189 loss: 5.9189 2022/10/12 22:32:13 - mmengine - INFO - Epoch(train) [1][60/940] lr: 1.0000e-02 eta: 18:13:35 time: 0.4966 data_time: 0.1012 memory: 17006 grad_norm: 1.3417 top1_acc: 0.0938 top5_acc: 0.1875 loss_cls: 5.8066 loss: 5.8066 2022/10/12 22:32:24 - mmengine - INFO - Epoch(train) [1][80/940] lr: 1.0000e-02 eta: 17:15:39 time: 0.5510 data_time: 0.0678 memory: 17006 grad_norm: 1.5916 top1_acc: 0.0312 top5_acc: 0.1562 loss_cls: 5.6358 loss: 5.6358 2022/10/12 22:32:35 - mmengine - INFO - Epoch(train) [1][100/940] lr: 1.0000e-02 eta: 16:39:11 time: 0.5458 data_time: 0.0300 memory: 17006 grad_norm: 1.8740 top1_acc: 0.1562 top5_acc: 0.3750 loss_cls: 5.3661 loss: 5.3661 2022/10/12 22:32:44 - mmengine - INFO - Epoch(train) [1][120/940] lr: 1.0000e-02 eta: 15:48:23 time: 0.4445 data_time: 0.0404 memory: 17006 grad_norm: 2.1552 top1_acc: 0.0625 top5_acc: 0.2500 loss_cls: 5.1241 loss: 5.1241 2022/10/12 22:32:55 - mmengine - INFO - Epoch(train) [1][140/940] lr: 1.0000e-02 eta: 15:28:40 time: 0.5188 data_time: 0.0289 memory: 17006 grad_norm: 2.3733 top1_acc: 0.0312 top5_acc: 0.2500 loss_cls: 4.6948 loss: 4.6948 2022/10/12 22:33:05 - mmengine - INFO - Epoch(train) [1][160/940] lr: 1.0000e-02 eta: 15:09:53 time: 0.4986 data_time: 0.0381 memory: 17006 grad_norm: 2.5521 top1_acc: 0.1562 top5_acc: 0.3125 loss_cls: 4.5970 loss: 4.5970 2022/10/12 22:33:15 - mmengine - INFO - Epoch(train) [1][180/940] lr: 1.0000e-02 eta: 15:01:08 time: 0.5326 data_time: 0.0338 memory: 17006 grad_norm: 2.6701 top1_acc: 0.1875 top5_acc: 0.4062 loss_cls: 4.3131 loss: 4.3131 2022/10/12 22:33:25 - mmengine - INFO - Epoch(train) [1][200/940] lr: 1.0000e-02 eta: 14:49:16 time: 0.5016 data_time: 0.0545 memory: 17006 grad_norm: 2.7718 top1_acc: 0.2500 top5_acc: 0.4375 loss_cls: 4.1431 loss: 4.1431 2022/10/12 22:33:37 - mmengine - INFO - Epoch(train) [1][220/940] lr: 1.0000e-02 eta: 14:48:57 time: 0.5678 data_time: 0.0886 memory: 17006 grad_norm: 2.8736 top1_acc: 0.1562 top5_acc: 0.5000 loss_cls: 4.1044 loss: 4.1044 2022/10/12 22:33:46 - mmengine - INFO - Epoch(train) [1][240/940] lr: 1.0000e-02 eta: 14:35:52 time: 0.4698 data_time: 0.1140 memory: 17006 grad_norm: 2.9099 top1_acc: 0.1562 top5_acc: 0.4688 loss_cls: 3.8557 loss: 3.8557 2022/10/12 22:33:58 - mmengine - INFO - Epoch(train) [1][260/940] lr: 1.0000e-02 eta: 14:38:12 time: 0.5816 data_time: 0.0842 memory: 17006 grad_norm: 2.9457 top1_acc: 0.1875 top5_acc: 0.4062 loss_cls: 3.8465 loss: 3.8465 2022/10/12 22:34:07 - mmengine - INFO - Epoch(train) [1][280/940] lr: 1.0000e-02 eta: 14:29:01 time: 0.4815 data_time: 0.0256 memory: 17006 grad_norm: 2.9891 top1_acc: 0.2812 top5_acc: 0.5312 loss_cls: 3.7059 loss: 3.7059 2022/10/12 22:34:18 - mmengine - INFO - Epoch(train) [1][300/940] lr: 1.0000e-02 eta: 14:26:19 time: 0.5322 data_time: 0.0880 memory: 17006 grad_norm: 3.0254 top1_acc: 0.2188 top5_acc: 0.3750 loss_cls: 3.6738 loss: 3.6738 2022/10/12 22:34:27 - mmengine - INFO - Epoch(train) [1][320/940] lr: 1.0000e-02 eta: 14:18:35 time: 0.4774 data_time: 0.0351 memory: 17006 grad_norm: 3.0907 top1_acc: 0.2812 top5_acc: 0.4688 loss_cls: 3.6628 loss: 3.6628 2022/10/12 22:34:39 - mmengine - INFO - Epoch(train) [1][340/940] lr: 1.0000e-02 eta: 14:22:02 time: 0.5893 data_time: 0.2059 memory: 17006 grad_norm: 3.0676 top1_acc: 0.2188 top5_acc: 0.5625 loss_cls: 3.5648 loss: 3.5648 2022/10/12 22:34:49 - mmengine - INFO - Epoch(train) [1][360/940] lr: 1.0000e-02 eta: 14:17:13 time: 0.4990 data_time: 0.1641 memory: 17006 grad_norm: 3.2281 top1_acc: 0.2500 top5_acc: 0.4688 loss_cls: 3.5750 loss: 3.5750 2022/10/12 22:35:00 - mmengine - INFO - Epoch(train) [1][380/940] lr: 1.0000e-02 eta: 14:15:24 time: 0.5293 data_time: 0.2058 memory: 17006 grad_norm: 3.0977 top1_acc: 0.2812 top5_acc: 0.5625 loss_cls: 3.3574 loss: 3.3574 2022/10/12 22:35:09 - mmengine - INFO - Epoch(train) [1][400/940] lr: 1.0000e-02 eta: 14:10:06 time: 0.4827 data_time: 0.1481 memory: 17006 grad_norm: 3.1380 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 3.5074 loss: 3.5074 2022/10/12 22:35:21 - mmengine - INFO - Epoch(train) [1][420/940] lr: 1.0000e-02 eta: 14:12:29 time: 0.5795 data_time: 0.2487 memory: 17006 grad_norm: 3.1555 top1_acc: 0.2812 top5_acc: 0.5312 loss_cls: 3.3965 loss: 3.3965 2022/10/12 22:35:30 - mmengine - INFO - Epoch(train) [1][440/940] lr: 1.0000e-02 eta: 14:06:49 time: 0.4690 data_time: 0.1386 memory: 17006 grad_norm: 3.1407 top1_acc: 0.2812 top5_acc: 0.5312 loss_cls: 3.5091 loss: 3.5091 2022/10/12 22:35:42 - mmengine - INFO - Epoch(train) [1][460/940] lr: 1.0000e-02 eta: 14:10:44 time: 0.6035 data_time: 0.2685 memory: 17006 grad_norm: 3.1715 top1_acc: 0.1875 top5_acc: 0.6562 loss_cls: 3.3749 loss: 3.3749 2022/10/12 22:35:51 - mmengine - INFO - Epoch(train) [1][480/940] lr: 1.0000e-02 eta: 14:03:46 time: 0.4414 data_time: 0.1077 memory: 17006 grad_norm: 3.1456 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 3.2400 loss: 3.2400 2022/10/12 22:36:03 - mmengine - INFO - Epoch(train) [1][500/940] lr: 1.0000e-02 eta: 14:05:31 time: 0.5721 data_time: 0.2462 memory: 17006 grad_norm: 3.1937 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 3.0942 loss: 3.0942 2022/10/12 22:36:12 - mmengine - INFO - Epoch(train) [1][520/940] lr: 1.0000e-02 eta: 14:00:43 time: 0.4656 data_time: 0.1280 memory: 17006 grad_norm: 3.2379 top1_acc: 0.3438 top5_acc: 0.7188 loss_cls: 3.2195 loss: 3.2195 2022/10/12 22:36:24 - mmengine - INFO - Epoch(train) [1][540/940] lr: 1.0000e-02 eta: 14:02:32 time: 0.5742 data_time: 0.2439 memory: 17006 grad_norm: 3.1988 top1_acc: 0.2188 top5_acc: 0.5938 loss_cls: 3.3086 loss: 3.3086 2022/10/12 22:36:33 - mmengine - INFO - Epoch(train) [1][560/940] lr: 1.0000e-02 eta: 13:58:04 time: 0.4638 data_time: 0.1312 memory: 17006 grad_norm: 3.2332 top1_acc: 0.2812 top5_acc: 0.6562 loss_cls: 3.1650 loss: 3.1650 2022/10/12 22:36:43 - mmengine - INFO - Epoch(train) [1][580/940] lr: 1.0000e-02 eta: 13:57:00 time: 0.5218 data_time: 0.1935 memory: 17006 grad_norm: 3.2642 top1_acc: 0.1875 top5_acc: 0.4375 loss_cls: 3.2409 loss: 3.2409 2022/10/12 22:36:53 - mmengine - INFO - Epoch(train) [1][600/940] lr: 1.0000e-02 eta: 13:55:17 time: 0.5079 data_time: 0.1843 memory: 17006 grad_norm: 3.2504 top1_acc: 0.1250 top5_acc: 0.3438 loss_cls: 3.2843 loss: 3.2843 2022/10/12 22:37:04 - mmengine - INFO - Epoch(train) [1][620/940] lr: 1.0000e-02 eta: 13:55:55 time: 0.5526 data_time: 0.2211 memory: 17006 grad_norm: 3.2805 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 3.1481 loss: 3.1481 2022/10/12 22:37:14 - mmengine - INFO - Epoch(train) [1][640/940] lr: 1.0000e-02 eta: 13:52:45 time: 0.4760 data_time: 0.1456 memory: 17006 grad_norm: 3.2689 top1_acc: 0.2188 top5_acc: 0.6875 loss_cls: 3.0196 loss: 3.0196 2022/10/12 22:37:26 - mmengine - INFO - Epoch(train) [1][660/940] lr: 1.0000e-02 eta: 13:56:00 time: 0.6079 data_time: 0.2856 memory: 17006 grad_norm: 3.2597 top1_acc: 0.2188 top5_acc: 0.6250 loss_cls: 3.0827 loss: 3.0827 2022/10/12 22:37:35 - mmengine - INFO - Epoch(train) [1][680/940] lr: 1.0000e-02 eta: 13:50:58 time: 0.4310 data_time: 0.1046 memory: 17006 grad_norm: 3.2766 top1_acc: 0.2188 top5_acc: 0.4062 loss_cls: 3.0840 loss: 3.0840 2022/10/12 22:37:46 - mmengine - INFO - Epoch(train) [1][700/940] lr: 1.0000e-02 eta: 13:51:34 time: 0.5520 data_time: 0.2228 memory: 17006 grad_norm: 3.3062 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0687 loss: 3.0687 2022/10/12 22:37:55 - mmengine - INFO - Epoch(train) [1][720/940] lr: 1.0000e-02 eta: 13:49:03 time: 0.4806 data_time: 0.1476 memory: 17006 grad_norm: 3.2796 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 3.0246 loss: 3.0246 2022/10/12 22:38:07 - mmengine - INFO - Epoch(train) [1][740/940] lr: 1.0000e-02 eta: 13:50:00 time: 0.5601 data_time: 0.2308 memory: 17006 grad_norm: 3.3068 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 3.0309 loss: 3.0309 2022/10/12 22:38:16 - mmengine - INFO - Epoch(train) [1][760/940] lr: 1.0000e-02 eta: 13:47:35 time: 0.4794 data_time: 0.1411 memory: 17006 grad_norm: 3.2785 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 2.9880 loss: 2.9880 2022/10/12 22:38:26 - mmengine - INFO - Epoch(train) [1][780/940] lr: 1.0000e-02 eta: 13:46:16 time: 0.5038 data_time: 0.1604 memory: 17006 grad_norm: 3.3445 top1_acc: 0.2500 top5_acc: 0.5312 loss_cls: 3.0867 loss: 3.0867 2022/10/12 22:38:36 - mmengine - INFO - Epoch(train) [1][800/940] lr: 1.0000e-02 eta: 13:44:51 time: 0.4998 data_time: 0.0647 memory: 17006 grad_norm: 3.3257 top1_acc: 0.2188 top5_acc: 0.6250 loss_cls: 3.0595 loss: 3.0595 2022/10/12 22:38:48 - mmengine - INFO - Epoch(train) [1][820/940] lr: 1.0000e-02 eta: 13:46:24 time: 0.5768 data_time: 0.0342 memory: 17006 grad_norm: 3.3247 top1_acc: 0.2812 top5_acc: 0.4062 loss_cls: 3.0740 loss: 3.0740 2022/10/12 22:38:58 - mmengine - INFO - Epoch(train) [1][840/940] lr: 1.0000e-02 eta: 13:44:48 time: 0.4938 data_time: 0.0366 memory: 17006 grad_norm: 3.3394 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0150 loss: 3.0150 2022/10/12 22:39:08 - mmengine - INFO - Epoch(train) [1][860/940] lr: 1.0000e-02 eta: 13:44:42 time: 0.5332 data_time: 0.0512 memory: 17006 grad_norm: 3.3441 top1_acc: 0.2812 top5_acc: 0.6875 loss_cls: 3.0071 loss: 3.0071 2022/10/12 22:39:19 - mmengine - INFO - Epoch(train) [1][880/940] lr: 1.0000e-02 eta: 13:43:45 time: 0.5096 data_time: 0.0280 memory: 17006 grad_norm: 3.3994 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 2.9058 loss: 2.9058 2022/10/12 22:39:30 - mmengine - INFO - Epoch(train) [1][900/940] lr: 1.0000e-02 eta: 13:45:08 time: 0.5757 data_time: 0.0292 memory: 17006 grad_norm: 3.3580 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 2.9282 loss: 2.9282 2022/10/12 22:39:40 - mmengine - INFO - Epoch(train) [1][920/940] lr: 1.0000e-02 eta: 13:44:10 time: 0.5086 data_time: 0.0324 memory: 17006 grad_norm: 3.3942 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 2.9288 loss: 2.9288 2022/10/12 22:39:49 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 22:39:49 - mmengine - INFO - Epoch(train) [1][940/940] lr: 1.0000e-02 eta: 13:41:24 time: 0.4525 data_time: 0.0245 memory: 17006 grad_norm: 3.5095 top1_acc: 0.1429 top5_acc: 0.2857 loss_cls: 3.0178 loss: 3.0178 2022/10/12 22:40:07 - mmengine - INFO - Epoch(val) [1][20/78] eta: 0:00:51 time: 0.8964 data_time: 0.8042 memory: 3172 2022/10/12 22:40:16 - mmengine - INFO - Epoch(val) [1][40/78] eta: 0:00:16 time: 0.4370 data_time: 0.3473 memory: 3172 2022/10/12 22:40:28 - mmengine - INFO - Epoch(val) [1][60/78] eta: 0:00:10 time: 0.6016 data_time: 0.5107 memory: 3172 2022/10/12 22:40:40 - mmengine - INFO - Epoch(val) [1][78/78] acc/top1: 0.4262 acc/top5: 0.7046 acc/mean1: 0.4259 2022/10/12 22:40:40 - mmengine - INFO - The best checkpoint with 0.4262 acc/top1 at 1 epoch is saved to best_acc/top1_epoch_1.pth. 2022/10/12 22:40:55 - mmengine - INFO - Epoch(train) [2][20/940] lr: 1.0000e-02 eta: 13:47:22 time: 0.7202 data_time: 0.2112 memory: 17006 grad_norm: 3.3347 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.7568 loss: 2.7568 2022/10/12 22:41:04 - mmengine - INFO - Epoch(train) [2][40/940] lr: 1.0000e-02 eta: 13:44:38 time: 0.4527 data_time: 0.0301 memory: 17006 grad_norm: 3.4129 top1_acc: 0.2500 top5_acc: 0.4688 loss_cls: 2.9304 loss: 2.9304 2022/10/12 22:41:15 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 22:41:15 - mmengine - INFO - Epoch(train) [2][60/940] lr: 1.0000e-02 eta: 13:45:00 time: 0.5497 data_time: 0.0314 memory: 17006 grad_norm: 3.3341 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.9760 loss: 2.9760 2022/10/12 22:41:24 - mmengine - INFO - Epoch(train) [2][80/940] lr: 1.0000e-02 eta: 13:43:17 time: 0.4814 data_time: 0.0250 memory: 17006 grad_norm: 3.3507 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 2.8929 loss: 2.8929 2022/10/12 22:41:36 - mmengine - INFO - Epoch(train) [2][100/940] lr: 1.0000e-02 eta: 13:44:29 time: 0.5777 data_time: 0.0379 memory: 17006 grad_norm: 3.4174 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 3.0991 loss: 3.0991 2022/10/12 22:41:45 - mmengine - INFO - Epoch(train) [2][120/940] lr: 1.0000e-02 eta: 13:42:22 time: 0.4654 data_time: 0.0302 memory: 17006 grad_norm: 3.3744 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.9671 loss: 2.9671 2022/10/12 22:41:56 - mmengine - INFO - Epoch(train) [2][140/940] lr: 1.0000e-02 eta: 13:42:38 time: 0.5465 data_time: 0.0393 memory: 17006 grad_norm: 3.3843 top1_acc: 0.3438 top5_acc: 0.7812 loss_cls: 2.7222 loss: 2.7222 2022/10/12 22:42:05 - mmengine - INFO - Epoch(train) [2][160/940] lr: 1.0000e-02 eta: 13:40:11 time: 0.4507 data_time: 0.0280 memory: 17006 grad_norm: 3.4108 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.7401 loss: 2.7401 2022/10/12 22:42:17 - mmengine - INFO - Epoch(train) [2][180/940] lr: 1.0000e-02 eta: 13:41:29 time: 0.5831 data_time: 0.0314 memory: 17006 grad_norm: 3.4307 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.8763 loss: 2.8763 2022/10/12 22:42:27 - mmengine - INFO - Epoch(train) [2][200/940] lr: 1.0000e-02 eta: 13:40:15 time: 0.4917 data_time: 0.0270 memory: 17006 grad_norm: 3.3827 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.7339 loss: 2.7339 2022/10/12 22:42:39 - mmengine - INFO - Epoch(train) [2][220/940] lr: 1.0000e-02 eta: 13:42:53 time: 0.6353 data_time: 0.0359 memory: 17006 grad_norm: 3.4141 top1_acc: 0.1875 top5_acc: 0.5000 loss_cls: 2.7610 loss: 2.7610 2022/10/12 22:42:49 - mmengine - INFO - Epoch(train) [2][240/940] lr: 1.0000e-02 eta: 13:41:19 time: 0.4790 data_time: 0.0232 memory: 17006 grad_norm: 3.4316 top1_acc: 0.3438 top5_acc: 0.5625 loss_cls: 2.8164 loss: 2.8164 2022/10/12 22:42:59 - mmengine - INFO - Epoch(train) [2][260/940] lr: 1.0000e-02 eta: 13:40:09 time: 0.4925 data_time: 0.0394 memory: 17006 grad_norm: 3.4035 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.7812 loss: 2.7812 2022/10/12 22:43:09 - mmengine - INFO - Epoch(train) [2][280/940] lr: 1.0000e-02 eta: 13:39:32 time: 0.5129 data_time: 0.0331 memory: 17006 grad_norm: 3.4299 top1_acc: 0.4375 top5_acc: 0.5938 loss_cls: 2.9310 loss: 2.9310 2022/10/12 22:43:19 - mmengine - INFO - Epoch(train) [2][300/940] lr: 1.0000e-02 eta: 13:39:16 time: 0.5262 data_time: 0.0331 memory: 17006 grad_norm: 3.4259 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 2.7541 loss: 2.7541 2022/10/12 22:43:30 - mmengine - INFO - Epoch(train) [2][320/940] lr: 1.0000e-02 eta: 13:38:42 time: 0.5142 data_time: 0.0323 memory: 17006 grad_norm: 3.4071 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7109 loss: 2.7109 2022/10/12 22:43:41 - mmengine - INFO - Epoch(train) [2][340/940] lr: 1.0000e-02 eta: 13:39:26 time: 0.5671 data_time: 0.0276 memory: 17006 grad_norm: 3.3952 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 2.8552 loss: 2.8552 2022/10/12 22:43:51 - mmengine - INFO - Epoch(train) [2][360/940] lr: 1.0000e-02 eta: 13:38:13 time: 0.4870 data_time: 0.0354 memory: 17006 grad_norm: 3.4130 top1_acc: 0.4062 top5_acc: 0.5000 loss_cls: 2.8271 loss: 2.8271 2022/10/12 22:44:02 - mmengine - INFO - Epoch(train) [2][380/940] lr: 1.0000e-02 eta: 13:38:13 time: 0.5370 data_time: 0.0307 memory: 17006 grad_norm: 3.4247 top1_acc: 0.2812 top5_acc: 0.4688 loss_cls: 2.9562 loss: 2.9562 2022/10/12 22:44:12 - mmengine - INFO - Epoch(train) [2][400/940] lr: 1.0000e-02 eta: 13:37:52 time: 0.5220 data_time: 0.0294 memory: 17006 grad_norm: 3.4215 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 2.7259 loss: 2.7259 2022/10/12 22:44:23 - mmengine - INFO - Epoch(train) [2][420/940] lr: 1.0000e-02 eta: 13:37:59 time: 0.5427 data_time: 0.0314 memory: 17006 grad_norm: 3.4142 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6942 loss: 2.6942 2022/10/12 22:44:33 - mmengine - INFO - Epoch(train) [2][440/940] lr: 1.0000e-02 eta: 13:37:22 time: 0.5103 data_time: 0.0284 memory: 17006 grad_norm: 3.4602 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.7677 loss: 2.7677 2022/10/12 22:44:44 - mmengine - INFO - Epoch(train) [2][460/940] lr: 1.0000e-02 eta: 13:37:18 time: 0.5338 data_time: 0.0339 memory: 17006 grad_norm: 3.4042 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.6663 loss: 2.6663 2022/10/12 22:44:54 - mmengine - INFO - Epoch(train) [2][480/940] lr: 1.0000e-02 eta: 13:36:16 time: 0.4903 data_time: 0.0422 memory: 17006 grad_norm: 3.4617 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.6610 loss: 2.6610 2022/10/12 22:45:05 - mmengine - INFO - Epoch(train) [2][500/940] lr: 1.0000e-02 eta: 13:36:30 time: 0.5483 data_time: 0.0298 memory: 17006 grad_norm: 3.4295 top1_acc: 0.2812 top5_acc: 0.6250 loss_cls: 2.6635 loss: 2.6635 2022/10/12 22:45:14 - mmengine - INFO - Epoch(train) [2][520/940] lr: 1.0000e-02 eta: 13:35:09 time: 0.4735 data_time: 0.0312 memory: 17006 grad_norm: 3.4625 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.6832 loss: 2.6832 2022/10/12 22:45:25 - mmengine - INFO - Epoch(train) [2][540/940] lr: 1.0000e-02 eta: 13:35:43 time: 0.5646 data_time: 0.0342 memory: 17006 grad_norm: 3.4368 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.8196 loss: 2.8196 2022/10/12 22:45:35 - mmengine - INFO - Epoch(train) [2][560/940] lr: 1.0000e-02 eta: 13:34:40 time: 0.4863 data_time: 0.0416 memory: 17006 grad_norm: 3.4693 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.7813 loss: 2.7813 2022/10/12 22:45:46 - mmengine - INFO - Epoch(train) [2][580/940] lr: 1.0000e-02 eta: 13:34:52 time: 0.5472 data_time: 0.0271 memory: 17006 grad_norm: 3.4327 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.5872 loss: 2.5872 2022/10/12 22:45:57 - mmengine - INFO - Epoch(train) [2][600/940] lr: 1.0000e-02 eta: 13:35:39 time: 0.5760 data_time: 0.0302 memory: 17006 grad_norm: 3.5140 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 2.7018 loss: 2.7018 2022/10/12 22:46:08 - mmengine - INFO - Epoch(train) [2][620/940] lr: 1.0000e-02 eta: 13:35:33 time: 0.5336 data_time: 0.0345 memory: 17006 grad_norm: 3.4489 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.5770 loss: 2.5770 2022/10/12 22:46:19 - mmengine - INFO - Epoch(train) [2][640/940] lr: 1.0000e-02 eta: 13:35:09 time: 0.5176 data_time: 0.0354 memory: 17006 grad_norm: 3.4990 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.5938 loss: 2.5938 2022/10/12 22:46:30 - mmengine - INFO - Epoch(train) [2][660/940] lr: 1.0000e-02 eta: 13:35:43 time: 0.5683 data_time: 0.0293 memory: 17006 grad_norm: 3.4848 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.6210 loss: 2.6210 2022/10/12 22:46:40 - mmengine - INFO - Epoch(train) [2][680/940] lr: 1.0000e-02 eta: 13:35:06 time: 0.5059 data_time: 0.0383 memory: 17006 grad_norm: 3.4762 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 2.7111 loss: 2.7111 2022/10/12 22:46:50 - mmengine - INFO - Epoch(train) [2][700/940] lr: 1.0000e-02 eta: 13:34:47 time: 0.5227 data_time: 0.0284 memory: 17006 grad_norm: 3.4900 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.6477 loss: 2.6477 2022/10/12 22:47:01 - mmengine - INFO - Epoch(train) [2][720/940] lr: 1.0000e-02 eta: 13:34:29 time: 0.5221 data_time: 0.0352 memory: 17006 grad_norm: 3.5109 top1_acc: 0.3438 top5_acc: 0.6250 loss_cls: 2.7706 loss: 2.7706 2022/10/12 22:47:12 - mmengine - INFO - Epoch(train) [2][740/940] lr: 1.0000e-02 eta: 13:34:27 time: 0.5371 data_time: 0.0314 memory: 17006 grad_norm: 3.4473 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.7038 loss: 2.7038 2022/10/12 22:47:21 - mmengine - INFO - Epoch(train) [2][760/940] lr: 1.0000e-02 eta: 13:33:20 time: 0.4779 data_time: 0.0368 memory: 17006 grad_norm: 3.4341 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.6723 loss: 2.6723 2022/10/12 22:47:32 - mmengine - INFO - Epoch(train) [2][780/940] lr: 1.0000e-02 eta: 13:33:33 time: 0.5500 data_time: 0.0290 memory: 17006 grad_norm: 3.5248 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.6582 loss: 2.6582 2022/10/12 22:47:42 - mmengine - INFO - Epoch(train) [2][800/940] lr: 1.0000e-02 eta: 13:33:03 time: 0.5115 data_time: 0.0342 memory: 17006 grad_norm: 3.4994 top1_acc: 0.3750 top5_acc: 0.7812 loss_cls: 2.6730 loss: 2.6730 2022/10/12 22:47:53 - mmengine - INFO - Epoch(train) [2][820/940] lr: 1.0000e-02 eta: 13:32:40 time: 0.5165 data_time: 0.0399 memory: 17006 grad_norm: 3.4680 top1_acc: 0.3438 top5_acc: 0.7188 loss_cls: 2.6077 loss: 2.6077 2022/10/12 22:48:02 - mmengine - INFO - Epoch(train) [2][840/940] lr: 1.0000e-02 eta: 13:31:38 time: 0.4794 data_time: 0.0352 memory: 17006 grad_norm: 3.4768 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.6154 loss: 2.6154 2022/10/12 22:48:13 - mmengine - INFO - Epoch(train) [2][860/940] lr: 1.0000e-02 eta: 13:31:43 time: 0.5429 data_time: 0.0374 memory: 17006 grad_norm: 3.4844 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.7392 loss: 2.7392 2022/10/12 22:48:23 - mmengine - INFO - Epoch(train) [2][880/940] lr: 1.0000e-02 eta: 13:30:59 time: 0.4954 data_time: 0.0380 memory: 17006 grad_norm: 3.4689 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.6253 loss: 2.6253 2022/10/12 22:48:35 - mmengine - INFO - Epoch(train) [2][900/940] lr: 1.0000e-02 eta: 13:31:36 time: 0.5750 data_time: 0.0284 memory: 17006 grad_norm: 3.4852 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5455 loss: 2.5455 2022/10/12 22:48:43 - mmengine - INFO - Epoch(train) [2][920/940] lr: 1.0000e-02 eta: 13:30:01 time: 0.4432 data_time: 0.0352 memory: 17006 grad_norm: 3.4997 top1_acc: 0.4062 top5_acc: 0.8438 loss_cls: 2.5135 loss: 2.5135 2022/10/12 22:48:53 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 22:48:53 - mmengine - INFO - Epoch(train) [2][940/940] lr: 1.0000e-02 eta: 13:28:52 time: 0.4684 data_time: 0.0284 memory: 17006 grad_norm: 3.6902 top1_acc: 0.2857 top5_acc: 0.4286 loss_cls: 2.7706 loss: 2.7706 2022/10/12 22:49:06 - mmengine - INFO - Epoch(val) [2][20/78] eta: 0:00:36 time: 0.6369 data_time: 0.5445 memory: 3172 2022/10/12 22:49:15 - mmengine - INFO - Epoch(val) [2][40/78] eta: 0:00:18 time: 0.4765 data_time: 0.3871 memory: 3172 2022/10/12 22:49:26 - mmengine - INFO - Epoch(val) [2][60/78] eta: 0:00:09 time: 0.5444 data_time: 0.4550 memory: 3172 2022/10/12 22:49:38 - mmengine - INFO - Epoch(val) [2][78/78] acc/top1: 0.4920 acc/top5: 0.7538 acc/mean1: 0.4918 2022/10/12 22:49:38 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_1.pth is removed 2022/10/12 22:49:38 - mmengine - INFO - The best checkpoint with 0.4920 acc/top1 at 2 epoch is saved to best_acc/top1_epoch_2.pth. 2022/10/12 22:49:53 - mmengine - INFO - Epoch(train) [3][20/940] lr: 1.0000e-02 eta: 13:32:36 time: 0.7683 data_time: 0.2752 memory: 17006 grad_norm: 3.4782 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.7242 loss: 2.7242 2022/10/12 22:50:03 - mmengine - INFO - Epoch(train) [3][40/940] lr: 1.0000e-02 eta: 13:31:21 time: 0.4621 data_time: 0.0277 memory: 17006 grad_norm: 3.4832 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.5173 loss: 2.5173 2022/10/12 22:50:14 - mmengine - INFO - Epoch(train) [3][60/940] lr: 1.0000e-02 eta: 13:31:48 time: 0.5690 data_time: 0.0356 memory: 17006 grad_norm: 3.5098 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 2.6125 loss: 2.6125 2022/10/12 22:50:24 - mmengine - INFO - Epoch(train) [3][80/940] lr: 1.0000e-02 eta: 13:31:24 time: 0.5142 data_time: 0.0309 memory: 17006 grad_norm: 3.4880 top1_acc: 0.3438 top5_acc: 0.8125 loss_cls: 2.7276 loss: 2.7276 2022/10/12 22:50:36 - mmengine - INFO - Epoch(train) [3][100/940] lr: 1.0000e-02 eta: 13:31:53 time: 0.5719 data_time: 0.0345 memory: 17006 grad_norm: 3.4552 top1_acc: 0.1875 top5_acc: 0.5312 loss_cls: 2.4746 loss: 2.4746 2022/10/12 22:50:45 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 22:50:45 - mmengine - INFO - Epoch(train) [3][120/940] lr: 1.0000e-02 eta: 13:30:34 time: 0.4553 data_time: 0.0309 memory: 17006 grad_norm: 3.4624 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 2.6756 loss: 2.6756 2022/10/12 22:50:56 - mmengine - INFO - Epoch(train) [3][140/940] lr: 1.0000e-02 eta: 13:30:45 time: 0.5521 data_time: 0.0303 memory: 17006 grad_norm: 3.4479 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.5166 loss: 2.5166 2022/10/12 22:51:06 - mmengine - INFO - Epoch(train) [3][160/940] lr: 1.0000e-02 eta: 13:29:52 time: 0.4815 data_time: 0.0368 memory: 17006 grad_norm: 3.4706 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4408 loss: 2.4408 2022/10/12 22:51:16 - mmengine - INFO - Epoch(train) [3][180/940] lr: 1.0000e-02 eta: 13:29:56 time: 0.5445 data_time: 0.0345 memory: 17006 grad_norm: 3.4728 top1_acc: 0.1875 top5_acc: 0.5312 loss_cls: 2.6140 loss: 2.6140 2022/10/12 22:51:25 - mmengine - INFO - Epoch(train) [3][200/940] lr: 1.0000e-02 eta: 13:28:37 time: 0.4516 data_time: 0.0331 memory: 17006 grad_norm: 3.4864 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.6286 loss: 2.6286 2022/10/12 22:51:37 - mmengine - INFO - Epoch(train) [3][220/940] lr: 1.0000e-02 eta: 13:29:19 time: 0.5872 data_time: 0.0300 memory: 17006 grad_norm: 3.5145 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.5355 loss: 2.5355 2022/10/12 22:51:47 - mmengine - INFO - Epoch(train) [3][240/940] lr: 1.0000e-02 eta: 13:28:14 time: 0.4664 data_time: 0.0382 memory: 17006 grad_norm: 3.5084 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.4428 loss: 2.4428 2022/10/12 22:51:58 - mmengine - INFO - Epoch(train) [3][260/940] lr: 1.0000e-02 eta: 13:28:35 time: 0.5647 data_time: 0.0303 memory: 17006 grad_norm: 3.5188 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 2.5677 loss: 2.5677 2022/10/12 22:52:07 - mmengine - INFO - Epoch(train) [3][280/940] lr: 1.0000e-02 eta: 13:27:13 time: 0.4432 data_time: 0.0339 memory: 17006 grad_norm: 3.5549 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.5771 loss: 2.5771 2022/10/12 22:52:18 - mmengine - INFO - Epoch(train) [3][300/940] lr: 1.0000e-02 eta: 13:27:14 time: 0.5412 data_time: 0.0330 memory: 17006 grad_norm: 3.4748 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.4244 loss: 2.4244 2022/10/12 22:52:28 - mmengine - INFO - Epoch(train) [3][320/940] lr: 1.0000e-02 eta: 13:26:45 time: 0.5059 data_time: 0.0343 memory: 17006 grad_norm: 3.5178 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5393 loss: 2.5393 2022/10/12 22:52:38 - mmengine - INFO - Epoch(train) [3][340/940] lr: 1.0000e-02 eta: 13:26:20 time: 0.5095 data_time: 0.0345 memory: 17006 grad_norm: 3.5095 top1_acc: 0.2812 top5_acc: 0.5938 loss_cls: 2.5337 loss: 2.5337 2022/10/12 22:52:49 - mmengine - INFO - Epoch(train) [3][360/940] lr: 1.0000e-02 eta: 13:26:19 time: 0.5394 data_time: 0.0372 memory: 17006 grad_norm: 3.5592 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.4373 loss: 2.4373 2022/10/12 22:52:59 - mmengine - INFO - Epoch(train) [3][380/940] lr: 1.0000e-02 eta: 13:25:55 time: 0.5100 data_time: 0.0347 memory: 17006 grad_norm: 3.4709 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 2.5778 loss: 2.5778 2022/10/12 22:53:10 - mmengine - INFO - Epoch(train) [3][400/940] lr: 1.0000e-02 eta: 13:26:04 time: 0.5518 data_time: 0.0324 memory: 17006 grad_norm: 3.5147 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.5074 loss: 2.5074 2022/10/12 22:53:21 - mmengine - INFO - Epoch(train) [3][420/940] lr: 1.0000e-02 eta: 13:25:58 time: 0.5332 data_time: 0.0363 memory: 17006 grad_norm: 3.5314 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.5224 loss: 2.5224 2022/10/12 22:53:31 - mmengine - INFO - Epoch(train) [3][440/940] lr: 1.0000e-02 eta: 13:25:39 time: 0.5166 data_time: 0.0294 memory: 17006 grad_norm: 3.5586 top1_acc: 0.2812 top5_acc: 0.5625 loss_cls: 2.5741 loss: 2.5741 2022/10/12 22:53:42 - mmengine - INFO - Epoch(train) [3][460/940] lr: 1.0000e-02 eta: 13:25:36 time: 0.5359 data_time: 0.0330 memory: 17006 grad_norm: 3.4977 top1_acc: 0.3750 top5_acc: 0.5312 loss_cls: 2.4661 loss: 2.4661 2022/10/12 22:53:52 - mmengine - INFO - Epoch(train) [3][480/940] lr: 1.0000e-02 eta: 13:25:36 time: 0.5417 data_time: 0.0281 memory: 17006 grad_norm: 3.5262 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.6510 loss: 2.6510 2022/10/12 22:54:02 - mmengine - INFO - Epoch(train) [3][500/940] lr: 1.0000e-02 eta: 13:25:06 time: 0.5017 data_time: 0.0337 memory: 17006 grad_norm: 3.5125 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.5550 loss: 2.5550 2022/10/12 22:54:13 - mmengine - INFO - Epoch(train) [3][520/940] lr: 1.0000e-02 eta: 13:24:40 time: 0.5077 data_time: 0.0317 memory: 17006 grad_norm: 3.5982 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 2.5689 loss: 2.5689 2022/10/12 22:54:22 - mmengine - INFO - Epoch(train) [3][540/940] lr: 1.0000e-02 eta: 13:24:05 time: 0.4938 data_time: 0.0333 memory: 17006 grad_norm: 3.4969 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 2.4041 loss: 2.4041 2022/10/12 22:54:33 - mmengine - INFO - Epoch(train) [3][560/940] lr: 1.0000e-02 eta: 13:23:40 time: 0.5076 data_time: 0.0371 memory: 17006 grad_norm: 3.5432 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4555 loss: 2.4555 2022/10/12 22:54:42 - mmengine - INFO - Epoch(train) [3][580/940] lr: 1.0000e-02 eta: 13:22:39 time: 0.4594 data_time: 0.0312 memory: 17006 grad_norm: 3.5909 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.5072 loss: 2.5072 2022/10/12 22:54:52 - mmengine - INFO - Epoch(train) [3][600/940] lr: 1.0000e-02 eta: 13:22:33 time: 0.5322 data_time: 0.0301 memory: 17006 grad_norm: 3.5393 top1_acc: 0.2812 top5_acc: 0.7188 loss_cls: 2.5102 loss: 2.5102 2022/10/12 22:55:02 - mmengine - INFO - Epoch(train) [3][620/940] lr: 1.0000e-02 eta: 13:21:55 time: 0.4882 data_time: 0.0308 memory: 17006 grad_norm: 3.5343 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 2.5167 loss: 2.5167 2022/10/12 22:55:14 - mmengine - INFO - Epoch(train) [3][640/940] lr: 1.0000e-02 eta: 13:22:15 time: 0.5679 data_time: 0.0403 memory: 17006 grad_norm: 3.5296 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 2.6297 loss: 2.6297 2022/10/12 22:55:24 - mmengine - INFO - Epoch(train) [3][660/940] lr: 1.0000e-02 eta: 13:21:51 time: 0.5077 data_time: 0.0362 memory: 17006 grad_norm: 3.5206 top1_acc: 0.3125 top5_acc: 0.6562 loss_cls: 2.5677 loss: 2.5677 2022/10/12 22:55:34 - mmengine - INFO - Epoch(train) [3][680/940] lr: 1.0000e-02 eta: 13:21:41 time: 0.5275 data_time: 0.0307 memory: 17006 grad_norm: 3.5616 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.4829 loss: 2.4829 2022/10/12 22:55:44 - mmengine - INFO - Epoch(train) [3][700/940] lr: 1.0000e-02 eta: 13:21:07 time: 0.4929 data_time: 0.0345 memory: 17006 grad_norm: 3.5601 top1_acc: 0.4375 top5_acc: 0.5625 loss_cls: 2.4964 loss: 2.4964 2022/10/12 22:55:55 - mmengine - INFO - Epoch(train) [3][720/940] lr: 1.0000e-02 eta: 13:21:04 time: 0.5357 data_time: 0.0396 memory: 17006 grad_norm: 3.5999 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 2.6133 loss: 2.6133 2022/10/12 22:56:05 - mmengine - INFO - Epoch(train) [3][740/940] lr: 1.0000e-02 eta: 13:20:41 time: 0.5079 data_time: 0.0288 memory: 17006 grad_norm: 3.5205 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.4750 loss: 2.4750 2022/10/12 22:56:16 - mmengine - INFO - Epoch(train) [3][760/940] lr: 1.0000e-02 eta: 13:20:43 time: 0.5441 data_time: 0.0301 memory: 17006 grad_norm: 3.6007 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.4504 loss: 2.4504 2022/10/12 22:56:25 - mmengine - INFO - Epoch(train) [3][780/940] lr: 1.0000e-02 eta: 13:19:56 time: 0.4724 data_time: 0.0328 memory: 17006 grad_norm: 3.5389 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.3794 loss: 2.3794 2022/10/12 22:56:36 - mmengine - INFO - Epoch(train) [3][800/940] lr: 1.0000e-02 eta: 13:19:41 time: 0.5196 data_time: 0.0302 memory: 17006 grad_norm: 3.5742 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.5907 loss: 2.5907 2022/10/12 22:56:45 - mmengine - INFO - Epoch(train) [3][820/940] lr: 1.0000e-02 eta: 13:18:56 time: 0.4745 data_time: 0.0319 memory: 17006 grad_norm: 3.5775 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5403 loss: 2.5403 2022/10/12 22:56:55 - mmengine - INFO - Epoch(train) [3][840/940] lr: 1.0000e-02 eta: 13:18:34 time: 0.5075 data_time: 0.0306 memory: 17006 grad_norm: 3.5916 top1_acc: 0.4375 top5_acc: 0.5938 loss_cls: 2.4698 loss: 2.4698 2022/10/12 22:57:05 - mmengine - INFO - Epoch(train) [3][860/940] lr: 1.0000e-02 eta: 13:18:04 time: 0.4956 data_time: 0.0328 memory: 17006 grad_norm: 3.5243 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.5008 loss: 2.5008 2022/10/12 22:57:16 - mmengine - INFO - Epoch(train) [3][880/940] lr: 1.0000e-02 eta: 13:18:12 time: 0.5523 data_time: 0.0300 memory: 17006 grad_norm: 3.5613 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.5215 loss: 2.5215 2022/10/12 22:57:26 - mmengine - INFO - Epoch(train) [3][900/940] lr: 1.0000e-02 eta: 13:17:21 time: 0.4640 data_time: 0.0319 memory: 17006 grad_norm: 3.5230 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5745 loss: 2.5745 2022/10/12 22:57:38 - mmengine - INFO - Epoch(train) [3][920/940] lr: 1.0000e-02 eta: 13:17:58 time: 0.5974 data_time: 0.0318 memory: 17006 grad_norm: 3.5599 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 2.3105 loss: 2.3105 2022/10/12 22:57:45 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 22:57:45 - mmengine - INFO - Epoch(train) [3][940/940] lr: 1.0000e-02 eta: 13:16:19 time: 0.3872 data_time: 0.0290 memory: 17006 grad_norm: 3.7265 top1_acc: 0.4286 top5_acc: 0.5714 loss_cls: 2.5010 loss: 2.5010 2022/10/12 22:57:45 - mmengine - INFO - Saving checkpoint at 3 epochs 2022/10/12 22:57:59 - mmengine - INFO - Epoch(val) [3][20/78] eta: 0:00:36 time: 0.6290 data_time: 0.5396 memory: 3172 2022/10/12 22:58:07 - mmengine - INFO - Epoch(val) [3][40/78] eta: 0:00:16 time: 0.4309 data_time: 0.3403 memory: 3172 2022/10/12 22:58:19 - mmengine - INFO - Epoch(val) [3][60/78] eta: 0:00:10 time: 0.5681 data_time: 0.4772 memory: 3172 2022/10/12 22:58:28 - mmengine - INFO - Epoch(val) [3][78/78] acc/top1: 0.5190 acc/top5: 0.7773 acc/mean1: 0.5189 2022/10/12 22:58:28 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_2.pth is removed 2022/10/12 22:58:29 - mmengine - INFO - The best checkpoint with 0.5190 acc/top1 at 3 epoch is saved to best_acc/top1_epoch_3.pth. 2022/10/12 22:58:42 - mmengine - INFO - Epoch(train) [4][20/940] lr: 1.0000e-02 eta: 13:17:38 time: 0.6633 data_time: 0.3372 memory: 17006 grad_norm: 3.5574 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 2.4255 loss: 2.4255 2022/10/12 22:58:52 - mmengine - INFO - Epoch(train) [4][40/940] lr: 1.0000e-02 eta: 13:17:09 time: 0.4964 data_time: 0.1482 memory: 17006 grad_norm: 3.5392 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4410 loss: 2.4410 2022/10/12 22:59:03 - mmengine - INFO - Epoch(train) [4][60/940] lr: 1.0000e-02 eta: 13:17:15 time: 0.5513 data_time: 0.0510 memory: 17006 grad_norm: 3.5692 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.3567 loss: 2.3567 2022/10/12 22:59:12 - mmengine - INFO - Epoch(train) [4][80/940] lr: 1.0000e-02 eta: 13:16:32 time: 0.4734 data_time: 0.0324 memory: 17006 grad_norm: 3.5790 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.3695 loss: 2.3695 2022/10/12 22:59:24 - mmengine - INFO - Epoch(train) [4][100/940] lr: 1.0000e-02 eta: 13:17:03 time: 0.5912 data_time: 0.0313 memory: 17006 grad_norm: 3.6149 top1_acc: 0.2812 top5_acc: 0.5938 loss_cls: 2.4104 loss: 2.4104 2022/10/12 22:59:34 - mmengine - INFO - Epoch(train) [4][120/940] lr: 1.0000e-02 eta: 13:16:44 time: 0.5113 data_time: 0.0273 memory: 17006 grad_norm: 3.5208 top1_acc: 0.2812 top5_acc: 0.5625 loss_cls: 2.4238 loss: 2.4238 2022/10/12 22:59:45 - mmengine - INFO - Epoch(train) [4][140/940] lr: 1.0000e-02 eta: 13:16:47 time: 0.5463 data_time: 0.0359 memory: 17006 grad_norm: 3.5762 top1_acc: 0.2812 top5_acc: 0.5625 loss_cls: 2.5337 loss: 2.5337 2022/10/12 22:59:55 - mmengine - INFO - Epoch(train) [4][160/940] lr: 1.0000e-02 eta: 13:16:09 time: 0.4811 data_time: 0.0308 memory: 17006 grad_norm: 3.5675 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 2.5314 loss: 2.5314 2022/10/12 23:00:05 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 23:00:05 - mmengine - INFO - Epoch(train) [4][180/940] lr: 1.0000e-02 eta: 13:15:51 time: 0.5112 data_time: 0.0279 memory: 17006 grad_norm: 3.5482 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.4696 loss: 2.4696 2022/10/12 23:00:14 - mmengine - INFO - Epoch(train) [4][200/940] lr: 1.0000e-02 eta: 13:14:56 time: 0.4513 data_time: 0.0336 memory: 17006 grad_norm: 3.5055 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 2.4106 loss: 2.4106 2022/10/12 23:00:25 - mmengine - INFO - Epoch(train) [4][220/940] lr: 1.0000e-02 eta: 13:14:51 time: 0.5342 data_time: 0.0277 memory: 17006 grad_norm: 3.5638 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 2.3903 loss: 2.3903 2022/10/12 23:00:34 - mmengine - INFO - Epoch(train) [4][240/940] lr: 1.0000e-02 eta: 13:14:01 time: 0.4580 data_time: 0.0336 memory: 17006 grad_norm: 3.5850 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.3623 loss: 2.3623 2022/10/12 23:00:46 - mmengine - INFO - Epoch(train) [4][260/940] lr: 1.0000e-02 eta: 13:14:26 time: 0.5830 data_time: 0.0309 memory: 17006 grad_norm: 3.5729 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.4686 loss: 2.4686 2022/10/12 23:00:55 - mmengine - INFO - Epoch(train) [4][280/940] lr: 1.0000e-02 eta: 13:13:56 time: 0.4918 data_time: 0.0346 memory: 17006 grad_norm: 3.5913 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.3074 loss: 2.3074 2022/10/12 23:01:07 - mmengine - INFO - Epoch(train) [4][300/940] lr: 1.0000e-02 eta: 13:14:19 time: 0.5803 data_time: 0.0313 memory: 17006 grad_norm: 3.5282 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 2.3304 loss: 2.3304 2022/10/12 23:01:17 - mmengine - INFO - Epoch(train) [4][320/940] lr: 1.0000e-02 eta: 13:13:49 time: 0.4915 data_time: 0.0347 memory: 17006 grad_norm: 3.5947 top1_acc: 0.2812 top5_acc: 0.5000 loss_cls: 2.4847 loss: 2.4847 2022/10/12 23:01:27 - mmengine - INFO - Epoch(train) [4][340/940] lr: 1.0000e-02 eta: 13:13:36 time: 0.5202 data_time: 0.0362 memory: 17006 grad_norm: 3.5766 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 2.5241 loss: 2.5241 2022/10/12 23:01:37 - mmengine - INFO - Epoch(train) [4][360/940] lr: 1.0000e-02 eta: 13:13:11 time: 0.4979 data_time: 0.0378 memory: 17006 grad_norm: 3.6058 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.6136 loss: 2.6136 2022/10/12 23:01:47 - mmengine - INFO - Epoch(train) [4][380/940] lr: 1.0000e-02 eta: 13:12:41 time: 0.4906 data_time: 0.0273 memory: 17006 grad_norm: 3.5067 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.3548 loss: 2.3548 2022/10/12 23:01:57 - mmengine - INFO - Epoch(train) [4][400/940] lr: 1.0000e-02 eta: 13:12:06 time: 0.4787 data_time: 0.0347 memory: 17006 grad_norm: 3.5829 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.4921 loss: 2.4921 2022/10/12 23:02:08 - mmengine - INFO - Epoch(train) [4][420/940] lr: 1.0000e-02 eta: 13:12:09 time: 0.5484 data_time: 0.0366 memory: 17006 grad_norm: 3.5654 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 2.3369 loss: 2.3369 2022/10/12 23:02:18 - mmengine - INFO - Epoch(train) [4][440/940] lr: 1.0000e-02 eta: 13:11:47 time: 0.5024 data_time: 0.0333 memory: 17006 grad_norm: 3.5517 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 2.2411 loss: 2.2411 2022/10/12 23:02:27 - mmengine - INFO - Epoch(train) [4][460/940] lr: 1.0000e-02 eta: 13:11:11 time: 0.4773 data_time: 0.0309 memory: 17006 grad_norm: 3.6151 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 2.4186 loss: 2.4186 2022/10/12 23:02:37 - mmengine - INFO - Epoch(train) [4][480/940] lr: 1.0000e-02 eta: 13:10:55 time: 0.5140 data_time: 0.0373 memory: 17006 grad_norm: 3.6391 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.4269 loss: 2.4269 2022/10/12 23:02:48 - mmengine - INFO - Epoch(train) [4][500/940] lr: 1.0000e-02 eta: 13:10:46 time: 0.5250 data_time: 0.0300 memory: 17006 grad_norm: 3.5675 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 2.4201 loss: 2.4201 2022/10/12 23:02:58 - mmengine - INFO - Epoch(train) [4][520/940] lr: 1.0000e-02 eta: 13:10:11 time: 0.4784 data_time: 0.0361 memory: 17006 grad_norm: 3.6384 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.3342 loss: 2.3342 2022/10/12 23:03:08 - mmengine - INFO - Epoch(train) [4][540/940] lr: 1.0000e-02 eta: 13:09:58 time: 0.5194 data_time: 0.0340 memory: 17006 grad_norm: 3.5283 top1_acc: 0.3438 top5_acc: 0.5312 loss_cls: 2.5467 loss: 2.5467 2022/10/12 23:03:18 - mmengine - INFO - Epoch(train) [4][560/940] lr: 1.0000e-02 eta: 13:09:31 time: 0.4914 data_time: 0.0328 memory: 17006 grad_norm: 3.5212 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 2.4679 loss: 2.4679 2022/10/12 23:03:28 - mmengine - INFO - Epoch(train) [4][580/940] lr: 1.0000e-02 eta: 13:09:08 time: 0.4997 data_time: 0.0398 memory: 17006 grad_norm: 3.5636 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 2.4053 loss: 2.4053 2022/10/12 23:03:37 - mmengine - INFO - Epoch(train) [4][600/940] lr: 1.0000e-02 eta: 13:08:29 time: 0.4677 data_time: 0.0302 memory: 17006 grad_norm: 3.6591 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 2.3663 loss: 2.3663 2022/10/12 23:03:48 - mmengine - INFO - Epoch(train) [4][620/940] lr: 1.0000e-02 eta: 13:08:39 time: 0.5624 data_time: 0.0324 memory: 17006 grad_norm: 3.5603 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.3982 loss: 2.3982 2022/10/12 23:03:58 - mmengine - INFO - Epoch(train) [4][640/940] lr: 1.0000e-02 eta: 13:07:56 time: 0.4591 data_time: 0.0314 memory: 17006 grad_norm: 3.5982 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.3361 loss: 2.3361 2022/10/12 23:04:09 - mmengine - INFO - Epoch(train) [4][660/940] lr: 1.0000e-02 eta: 13:08:16 time: 0.5815 data_time: 0.0299 memory: 17006 grad_norm: 3.6364 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.5054 loss: 2.5054 2022/10/12 23:04:18 - mmengine - INFO - Epoch(train) [4][680/940] lr: 1.0000e-02 eta: 13:07:37 time: 0.4666 data_time: 0.0321 memory: 17006 grad_norm: 3.5738 top1_acc: 0.3438 top5_acc: 0.5625 loss_cls: 2.3707 loss: 2.3707 2022/10/12 23:04:30 - mmengine - INFO - Epoch(train) [4][700/940] lr: 1.0000e-02 eta: 13:07:49 time: 0.5665 data_time: 0.0348 memory: 17006 grad_norm: 3.6108 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4128 loss: 2.4128 2022/10/12 23:04:39 - mmengine - INFO - Epoch(train) [4][720/940] lr: 1.0000e-02 eta: 13:07:06 time: 0.4589 data_time: 0.0374 memory: 17006 grad_norm: 3.6046 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.3657 loss: 2.3657 2022/10/12 23:04:49 - mmengine - INFO - Epoch(train) [4][740/940] lr: 1.0000e-02 eta: 13:06:47 time: 0.5039 data_time: 0.0364 memory: 17006 grad_norm: 3.6860 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.4438 loss: 2.4438 2022/10/12 23:04:59 - mmengine - INFO - Epoch(train) [4][760/940] lr: 1.0000e-02 eta: 13:06:22 time: 0.4942 data_time: 0.0359 memory: 17006 grad_norm: 3.5237 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.4011 loss: 2.4011 2022/10/12 23:05:09 - mmengine - INFO - Epoch(train) [4][780/940] lr: 1.0000e-02 eta: 13:05:55 time: 0.4889 data_time: 0.0279 memory: 17006 grad_norm: 3.6102 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.4731 loss: 2.4731 2022/10/12 23:05:19 - mmengine - INFO - Epoch(train) [4][800/940] lr: 1.0000e-02 eta: 13:05:34 time: 0.4990 data_time: 0.0367 memory: 17006 grad_norm: 3.6477 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.3802 loss: 2.3802 2022/10/12 23:05:29 - mmengine - INFO - Epoch(train) [4][820/940] lr: 1.0000e-02 eta: 13:05:29 time: 0.5328 data_time: 0.0372 memory: 17006 grad_norm: 3.6035 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.3662 loss: 2.3662 2022/10/12 23:05:40 - mmengine - INFO - Epoch(train) [4][840/940] lr: 1.0000e-02 eta: 13:05:25 time: 0.5353 data_time: 0.0282 memory: 17006 grad_norm: 3.5652 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2175 loss: 2.2175 2022/10/12 23:05:50 - mmengine - INFO - Epoch(train) [4][860/940] lr: 1.0000e-02 eta: 13:05:10 time: 0.5127 data_time: 0.0262 memory: 17006 grad_norm: 3.6198 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.3456 loss: 2.3456 2022/10/12 23:05:59 - mmengine - INFO - Epoch(train) [4][880/940] lr: 1.0000e-02 eta: 13:04:29 time: 0.4584 data_time: 0.0374 memory: 17006 grad_norm: 3.6366 top1_acc: 0.3750 top5_acc: 0.7812 loss_cls: 2.2686 loss: 2.2686 2022/10/12 23:06:10 - mmengine - INFO - Epoch(train) [4][900/940] lr: 1.0000e-02 eta: 13:04:19 time: 0.5219 data_time: 0.0357 memory: 17006 grad_norm: 3.6335 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.5101 loss: 2.5101 2022/10/12 23:06:20 - mmengine - INFO - Epoch(train) [4][920/940] lr: 1.0000e-02 eta: 13:03:59 time: 0.5020 data_time: 0.0293 memory: 17006 grad_norm: 3.5695 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3819 loss: 2.3819 2022/10/12 23:06:29 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 23:06:29 - mmengine - INFO - Epoch(train) [4][940/940] lr: 1.0000e-02 eta: 13:03:22 time: 0.4654 data_time: 0.0255 memory: 17006 grad_norm: 3.7881 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 2.4912 loss: 2.4912 2022/10/12 23:06:42 - mmengine - INFO - Epoch(val) [4][20/78] eta: 0:00:36 time: 0.6251 data_time: 0.5304 memory: 3172 2022/10/12 23:06:50 - mmengine - INFO - Epoch(val) [4][40/78] eta: 0:00:16 time: 0.4310 data_time: 0.3385 memory: 3172 2022/10/12 23:07:02 - mmengine - INFO - Epoch(val) [4][60/78] eta: 0:00:10 time: 0.5773 data_time: 0.4873 memory: 3172 2022/10/12 23:07:12 - mmengine - INFO - Epoch(val) [4][78/78] acc/top1: 0.5388 acc/top5: 0.7848 acc/mean1: 0.5386 2022/10/12 23:07:12 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_3.pth is removed 2022/10/12 23:07:13 - mmengine - INFO - The best checkpoint with 0.5388 acc/top1 at 4 epoch is saved to best_acc/top1_epoch_4.pth. 2022/10/12 23:07:27 - mmengine - INFO - Epoch(train) [5][20/940] lr: 1.0000e-02 eta: 13:04:38 time: 0.7019 data_time: 0.3530 memory: 17006 grad_norm: 3.5790 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.3059 loss: 2.3059 2022/10/12 23:07:36 - mmengine - INFO - Epoch(train) [5][40/940] lr: 1.0000e-02 eta: 13:03:55 time: 0.4537 data_time: 0.0904 memory: 17006 grad_norm: 3.5080 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.3508 loss: 2.3508 2022/10/12 23:07:48 - mmengine - INFO - Epoch(train) [5][60/940] lr: 1.0000e-02 eta: 13:04:23 time: 0.6028 data_time: 0.0721 memory: 17006 grad_norm: 3.5953 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.2832 loss: 2.2832 2022/10/12 23:07:58 - mmengine - INFO - Epoch(train) [5][80/940] lr: 1.0000e-02 eta: 13:04:01 time: 0.4975 data_time: 0.0258 memory: 17006 grad_norm: 3.5893 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2898 loss: 2.2898 2022/10/12 23:08:09 - mmengine - INFO - Epoch(train) [5][100/940] lr: 1.0000e-02 eta: 13:04:00 time: 0.5413 data_time: 0.0301 memory: 17006 grad_norm: 3.5800 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3992 loss: 2.3992 2022/10/12 23:08:18 - mmengine - INFO - Epoch(train) [5][120/940] lr: 1.0000e-02 eta: 13:03:32 time: 0.4834 data_time: 0.0310 memory: 17006 grad_norm: 3.6407 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.5384 loss: 2.5384 2022/10/12 23:08:29 - mmengine - INFO - Epoch(train) [5][140/940] lr: 1.0000e-02 eta: 13:03:34 time: 0.5491 data_time: 0.0331 memory: 17006 grad_norm: 3.6036 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.2603 loss: 2.2603 2022/10/12 23:08:39 - mmengine - INFO - Epoch(train) [5][160/940] lr: 1.0000e-02 eta: 13:03:09 time: 0.4897 data_time: 0.0378 memory: 17006 grad_norm: 3.5968 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 2.2704 loss: 2.2704 2022/10/12 23:08:49 - mmengine - INFO - Epoch(train) [5][180/940] lr: 1.0000e-02 eta: 13:02:57 time: 0.5187 data_time: 0.0309 memory: 17006 grad_norm: 3.6909 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 2.3502 loss: 2.3502 2022/10/12 23:08:58 - mmengine - INFO - Epoch(train) [5][200/940] lr: 1.0000e-02 eta: 13:02:14 time: 0.4501 data_time: 0.0327 memory: 17006 grad_norm: 3.6164 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1984 loss: 2.1984 2022/10/12 23:09:09 - mmengine - INFO - Epoch(train) [5][220/940] lr: 1.0000e-02 eta: 13:02:07 time: 0.5297 data_time: 0.0371 memory: 17006 grad_norm: 3.6327 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.3134 loss: 2.3134 2022/10/12 23:09:19 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 23:09:19 - mmengine - INFO - Epoch(train) [5][240/940] lr: 1.0000e-02 eta: 13:01:45 time: 0.4956 data_time: 0.0316 memory: 17006 grad_norm: 3.5785 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 2.3751 loss: 2.3751 2022/10/12 23:09:30 - mmengine - INFO - Epoch(train) [5][260/940] lr: 1.0000e-02 eta: 13:01:43 time: 0.5405 data_time: 0.0378 memory: 17006 grad_norm: 3.6082 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.3146 loss: 2.3146 2022/10/12 23:09:39 - mmengine - INFO - Epoch(train) [5][280/940] lr: 1.0000e-02 eta: 13:01:08 time: 0.4646 data_time: 0.0355 memory: 17006 grad_norm: 3.6127 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2143 loss: 2.2143 2022/10/12 23:09:49 - mmengine - INFO - Epoch(train) [5][300/940] lr: 1.0000e-02 eta: 13:00:56 time: 0.5173 data_time: 0.0345 memory: 17006 grad_norm: 3.5991 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.2345 loss: 2.2345 2022/10/12 23:09:59 - mmengine - INFO - Epoch(train) [5][320/940] lr: 1.0000e-02 eta: 13:00:35 time: 0.4976 data_time: 0.0285 memory: 17006 grad_norm: 3.5800 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.2128 loss: 2.2128 2022/10/12 23:10:10 - mmengine - INFO - Epoch(train) [5][340/940] lr: 1.0000e-02 eta: 13:00:26 time: 0.5244 data_time: 0.0327 memory: 17006 grad_norm: 3.6135 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2199 loss: 2.2199 2022/10/12 23:10:20 - mmengine - INFO - Epoch(train) [5][360/940] lr: 1.0000e-02 eta: 13:00:19 time: 0.5293 data_time: 0.0351 memory: 17006 grad_norm: 3.5560 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 2.2327 loss: 2.2327 2022/10/12 23:10:31 - mmengine - INFO - Epoch(train) [5][380/940] lr: 1.0000e-02 eta: 13:00:02 time: 0.5058 data_time: 0.0374 memory: 17006 grad_norm: 3.6338 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.2650 loss: 2.2650 2022/10/12 23:10:40 - mmengine - INFO - Epoch(train) [5][400/940] lr: 1.0000e-02 eta: 12:59:36 time: 0.4838 data_time: 0.0296 memory: 17006 grad_norm: 3.6170 top1_acc: 0.3438 top5_acc: 0.7812 loss_cls: 2.3838 loss: 2.3838 2022/10/12 23:10:51 - mmengine - INFO - Epoch(train) [5][420/940] lr: 1.0000e-02 eta: 12:59:26 time: 0.5214 data_time: 0.0336 memory: 17006 grad_norm: 3.5977 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.3148 loss: 2.3148 2022/10/12 23:11:01 - mmengine - INFO - Epoch(train) [5][440/940] lr: 1.0000e-02 eta: 12:59:22 time: 0.5369 data_time: 0.0286 memory: 17006 grad_norm: 3.6190 top1_acc: 0.3438 top5_acc: 0.7812 loss_cls: 2.3165 loss: 2.3165 2022/10/12 23:11:11 - mmengine - INFO - Epoch(train) [5][460/940] lr: 1.0000e-02 eta: 12:58:47 time: 0.4611 data_time: 0.0335 memory: 17006 grad_norm: 3.6756 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.3625 loss: 2.3625 2022/10/12 23:11:21 - mmengine - INFO - Epoch(train) [5][480/940] lr: 1.0000e-02 eta: 12:58:30 time: 0.5063 data_time: 0.0616 memory: 17006 grad_norm: 3.6266 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 2.4676 loss: 2.4676 2022/10/12 23:11:31 - mmengine - INFO - Epoch(train) [5][500/940] lr: 1.0000e-02 eta: 12:58:24 time: 0.5299 data_time: 0.0328 memory: 17006 grad_norm: 3.6159 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 2.2078 loss: 2.2078 2022/10/12 23:11:42 - mmengine - INFO - Epoch(train) [5][520/940] lr: 1.0000e-02 eta: 12:58:07 time: 0.5057 data_time: 0.0390 memory: 17006 grad_norm: 3.6419 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.2751 loss: 2.2751 2022/10/12 23:11:52 - mmengine - INFO - Epoch(train) [5][540/940] lr: 1.0000e-02 eta: 12:58:07 time: 0.5458 data_time: 0.0427 memory: 17006 grad_norm: 3.6091 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.3207 loss: 2.3207 2022/10/12 23:12:02 - mmengine - INFO - Epoch(train) [5][560/940] lr: 1.0000e-02 eta: 12:57:44 time: 0.4895 data_time: 0.0260 memory: 17006 grad_norm: 3.6381 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.3667 loss: 2.3667 2022/10/12 23:12:13 - mmengine - INFO - Epoch(train) [5][580/940] lr: 1.0000e-02 eta: 12:57:37 time: 0.5269 data_time: 0.0331 memory: 17006 grad_norm: 3.5822 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.3806 loss: 2.3806 2022/10/12 23:12:23 - mmengine - INFO - Epoch(train) [5][600/940] lr: 1.0000e-02 eta: 12:57:25 time: 0.5185 data_time: 0.0299 memory: 17006 grad_norm: 3.6258 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.4010 loss: 2.4010 2022/10/12 23:12:33 - mmengine - INFO - Epoch(train) [5][620/940] lr: 1.0000e-02 eta: 12:57:12 time: 0.5140 data_time: 0.0295 memory: 17006 grad_norm: 3.6017 top1_acc: 0.3750 top5_acc: 0.5625 loss_cls: 2.2401 loss: 2.2401 2022/10/12 23:12:44 - mmengine - INFO - Epoch(train) [5][640/940] lr: 1.0000e-02 eta: 12:57:15 time: 0.5533 data_time: 0.0352 memory: 17006 grad_norm: 3.6406 top1_acc: 0.4375 top5_acc: 0.5938 loss_cls: 2.3147 loss: 2.3147 2022/10/12 23:12:53 - mmengine - INFO - Epoch(train) [5][660/940] lr: 1.0000e-02 eta: 12:56:32 time: 0.4396 data_time: 0.0363 memory: 17006 grad_norm: 3.6625 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 2.3640 loss: 2.3640 2022/10/12 23:13:04 - mmengine - INFO - Epoch(train) [5][680/940] lr: 1.0000e-02 eta: 12:56:36 time: 0.5543 data_time: 0.0305 memory: 17006 grad_norm: 3.6195 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.1904 loss: 2.1904 2022/10/12 23:13:14 - mmengine - INFO - Epoch(train) [5][700/940] lr: 1.0000e-02 eta: 12:56:15 time: 0.4951 data_time: 0.0369 memory: 17006 grad_norm: 3.6841 top1_acc: 0.3125 top5_acc: 0.6875 loss_cls: 2.3776 loss: 2.3776 2022/10/12 23:13:24 - mmengine - INFO - Epoch(train) [5][720/940] lr: 1.0000e-02 eta: 12:55:57 time: 0.5000 data_time: 0.0270 memory: 17006 grad_norm: 3.6808 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.3519 loss: 2.3519 2022/10/12 23:13:34 - mmengine - INFO - Epoch(train) [5][740/940] lr: 1.0000e-02 eta: 12:55:39 time: 0.5021 data_time: 0.0321 memory: 17006 grad_norm: 3.6539 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3079 loss: 2.3079 2022/10/12 23:13:45 - mmengine - INFO - Epoch(train) [5][760/940] lr: 1.0000e-02 eta: 12:55:29 time: 0.5220 data_time: 0.0274 memory: 17006 grad_norm: 3.6547 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 2.2009 loss: 2.2009 2022/10/12 23:13:54 - mmengine - INFO - Epoch(train) [5][780/940] lr: 1.0000e-02 eta: 12:55:03 time: 0.4805 data_time: 0.0282 memory: 17006 grad_norm: 3.6111 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.2861 loss: 2.2861 2022/10/12 23:14:05 - mmengine - INFO - Epoch(train) [5][800/940] lr: 1.0000e-02 eta: 12:54:58 time: 0.5315 data_time: 0.0301 memory: 17006 grad_norm: 3.6695 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3375 loss: 2.3375 2022/10/12 23:14:15 - mmengine - INFO - Epoch(train) [5][820/940] lr: 1.0000e-02 eta: 12:54:40 time: 0.5003 data_time: 0.0281 memory: 17006 grad_norm: 3.6537 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.4649 loss: 2.4649 2022/10/12 23:14:26 - mmengine - INFO - Epoch(train) [5][840/940] lr: 1.0000e-02 eta: 12:54:45 time: 0.5606 data_time: 0.0300 memory: 17006 grad_norm: 3.6220 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 2.4761 loss: 2.4761 2022/10/12 23:14:36 - mmengine - INFO - Epoch(train) [5][860/940] lr: 1.0000e-02 eta: 12:54:14 time: 0.4657 data_time: 0.0340 memory: 17006 grad_norm: 3.6846 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 2.4564 loss: 2.4564 2022/10/12 23:14:45 - mmengine - INFO - Epoch(train) [5][880/940] lr: 1.0000e-02 eta: 12:53:55 time: 0.4987 data_time: 0.0312 memory: 17006 grad_norm: 3.6735 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.4101 loss: 2.4101 2022/10/12 23:14:56 - mmengine - INFO - Epoch(train) [5][900/940] lr: 1.0000e-02 eta: 12:53:45 time: 0.5211 data_time: 0.0330 memory: 17006 grad_norm: 3.5900 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.1664 loss: 2.1664 2022/10/12 23:15:07 - mmengine - INFO - Epoch(train) [5][920/940] lr: 1.0000e-02 eta: 12:53:49 time: 0.5570 data_time: 0.0342 memory: 17006 grad_norm: 3.6619 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.4462 loss: 2.4462 2022/10/12 23:15:14 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 23:15:14 - mmengine - INFO - Epoch(train) [5][940/940] lr: 1.0000e-02 eta: 12:52:40 time: 0.3650 data_time: 0.0258 memory: 17006 grad_norm: 3.8548 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 2.3402 loss: 2.3402 2022/10/12 23:15:27 - mmengine - INFO - Epoch(val) [5][20/78] eta: 0:00:36 time: 0.6338 data_time: 0.5400 memory: 3172 2022/10/12 23:15:36 - mmengine - INFO - Epoch(val) [5][40/78] eta: 0:00:16 time: 0.4255 data_time: 0.3356 memory: 3172 2022/10/12 23:15:47 - mmengine - INFO - Epoch(val) [5][60/78] eta: 0:00:10 time: 0.5742 data_time: 0.4811 memory: 3172 2022/10/12 23:15:57 - mmengine - INFO - Epoch(val) [5][78/78] acc/top1: 0.5506 acc/top5: 0.8010 acc/mean1: 0.5503 2022/10/12 23:15:57 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_4.pth is removed 2022/10/12 23:15:58 - mmengine - INFO - The best checkpoint with 0.5506 acc/top1 at 5 epoch is saved to best_acc/top1_epoch_5.pth. 2022/10/12 23:16:12 - mmengine - INFO - Epoch(train) [6][20/940] lr: 1.0000e-02 eta: 12:53:41 time: 0.7078 data_time: 0.2350 memory: 17006 grad_norm: 3.6009 top1_acc: 0.2500 top5_acc: 0.5625 loss_cls: 2.3148 loss: 2.3148 2022/10/12 23:16:21 - mmengine - INFO - Epoch(train) [6][40/940] lr: 1.0000e-02 eta: 12:53:07 time: 0.4566 data_time: 0.0347 memory: 17006 grad_norm: 3.5956 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 2.3299 loss: 2.3299 2022/10/12 23:16:31 - mmengine - INFO - Epoch(train) [6][60/940] lr: 1.0000e-02 eta: 12:52:58 time: 0.5232 data_time: 0.0347 memory: 17006 grad_norm: 3.5698 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 2.3044 loss: 2.3044 2022/10/12 23:16:41 - mmengine - INFO - Epoch(train) [6][80/940] lr: 1.0000e-02 eta: 12:52:32 time: 0.4802 data_time: 0.0280 memory: 17006 grad_norm: 3.5917 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3683 loss: 2.3683 2022/10/12 23:16:52 - mmengine - INFO - Epoch(train) [6][100/940] lr: 1.0000e-02 eta: 12:52:34 time: 0.5524 data_time: 0.0355 memory: 17006 grad_norm: 3.6300 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 2.2655 loss: 2.2655 2022/10/12 23:17:02 - mmengine - INFO - Epoch(train) [6][120/940] lr: 1.0000e-02 eta: 12:52:13 time: 0.4903 data_time: 0.0274 memory: 17006 grad_norm: 3.5630 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.1893 loss: 2.1893 2022/10/12 23:17:12 - mmengine - INFO - Epoch(train) [6][140/940] lr: 1.0000e-02 eta: 12:51:58 time: 0.5061 data_time: 0.0311 memory: 17006 grad_norm: 3.6462 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.2586 loss: 2.2586 2022/10/12 23:17:21 - mmengine - INFO - Epoch(train) [6][160/940] lr: 1.0000e-02 eta: 12:51:33 time: 0.4793 data_time: 0.0419 memory: 17006 grad_norm: 3.6259 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.2502 loss: 2.2502 2022/10/12 23:17:32 - mmengine - INFO - Epoch(train) [6][180/940] lr: 1.0000e-02 eta: 12:51:25 time: 0.5281 data_time: 0.0338 memory: 17006 grad_norm: 3.6020 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.2196 loss: 2.2196 2022/10/12 23:17:42 - mmengine - INFO - Epoch(train) [6][200/940] lr: 1.0000e-02 eta: 12:51:15 time: 0.5184 data_time: 0.0275 memory: 17006 grad_norm: 3.6067 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.1607 loss: 2.1607 2022/10/12 23:17:52 - mmengine - INFO - Epoch(train) [6][220/940] lr: 1.0000e-02 eta: 12:50:56 time: 0.4958 data_time: 0.0328 memory: 17006 grad_norm: 3.7029 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2994 loss: 2.2994 2022/10/12 23:18:03 - mmengine - INFO - Epoch(train) [6][240/940] lr: 1.0000e-02 eta: 12:50:49 time: 0.5297 data_time: 0.0338 memory: 17006 grad_norm: 3.6137 top1_acc: 0.2812 top5_acc: 0.5312 loss_cls: 2.4081 loss: 2.4081 2022/10/12 23:18:14 - mmengine - INFO - Epoch(train) [6][260/940] lr: 1.0000e-02 eta: 12:50:45 time: 0.5362 data_time: 0.0306 memory: 17006 grad_norm: 3.5834 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.1943 loss: 2.1943 2022/10/12 23:18:23 - mmengine - INFO - Epoch(train) [6][280/940] lr: 1.0000e-02 eta: 12:50:18 time: 0.4747 data_time: 0.0360 memory: 17006 grad_norm: 3.6675 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.2537 loss: 2.2537 2022/10/12 23:18:34 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 23:18:34 - mmengine - INFO - Epoch(train) [6][300/940] lr: 1.0000e-02 eta: 12:50:18 time: 0.5464 data_time: 0.0291 memory: 17006 grad_norm: 3.6587 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 2.1469 loss: 2.1469 2022/10/12 23:18:44 - mmengine - INFO - Epoch(train) [6][320/940] lr: 1.0000e-02 eta: 12:50:01 time: 0.5012 data_time: 0.0320 memory: 17006 grad_norm: 3.6250 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.2457 loss: 2.2457 2022/10/12 23:18:54 - mmengine - INFO - Epoch(train) [6][340/940] lr: 1.0000e-02 eta: 12:49:43 time: 0.4979 data_time: 0.0337 memory: 17006 grad_norm: 3.6893 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.3162 loss: 2.3162 2022/10/12 23:19:04 - mmengine - INFO - Epoch(train) [6][360/940] lr: 1.0000e-02 eta: 12:49:21 time: 0.4868 data_time: 0.0290 memory: 17006 grad_norm: 3.6612 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.9699 loss: 1.9699 2022/10/12 23:19:15 - mmengine - INFO - Epoch(train) [6][380/940] lr: 1.0000e-02 eta: 12:49:28 time: 0.5683 data_time: 0.0268 memory: 17006 grad_norm: 3.6576 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 2.1561 loss: 2.1561 2022/10/12 23:19:25 - mmengine - INFO - Epoch(train) [6][400/940] lr: 1.0000e-02 eta: 12:49:04 time: 0.4814 data_time: 0.0407 memory: 17006 grad_norm: 3.6978 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4176 loss: 2.4176 2022/10/12 23:19:35 - mmengine - INFO - Epoch(train) [6][420/940] lr: 1.0000e-02 eta: 12:48:53 time: 0.5157 data_time: 0.0294 memory: 17006 grad_norm: 3.6698 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 2.4438 loss: 2.4438 2022/10/12 23:19:45 - mmengine - INFO - Epoch(train) [6][440/940] lr: 1.0000e-02 eta: 12:48:35 time: 0.4984 data_time: 0.0317 memory: 17006 grad_norm: 3.6950 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.3291 loss: 2.3291 2022/10/12 23:19:56 - mmengine - INFO - Epoch(train) [6][460/940] lr: 1.0000e-02 eta: 12:48:43 time: 0.5720 data_time: 0.0351 memory: 17006 grad_norm: 3.6269 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 2.2593 loss: 2.2593 2022/10/12 23:20:06 - mmengine - INFO - Epoch(train) [6][480/940] lr: 1.0000e-02 eta: 12:48:19 time: 0.4773 data_time: 0.0325 memory: 17006 grad_norm: 3.6727 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.3367 loss: 2.3367 2022/10/12 23:20:16 - mmengine - INFO - Epoch(train) [6][500/940] lr: 1.0000e-02 eta: 12:48:05 time: 0.5088 data_time: 0.0368 memory: 17006 grad_norm: 3.7516 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.3276 loss: 2.3276 2022/10/12 23:20:26 - mmengine - INFO - Epoch(train) [6][520/940] lr: 1.0000e-02 eta: 12:47:38 time: 0.4698 data_time: 0.0361 memory: 17006 grad_norm: 3.6514 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.3399 loss: 2.3399 2022/10/12 23:20:36 - mmengine - INFO - Epoch(train) [6][540/940] lr: 1.0000e-02 eta: 12:47:20 time: 0.4983 data_time: 0.0293 memory: 17006 grad_norm: 3.6485 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 2.2553 loss: 2.2553 2022/10/12 23:20:45 - mmengine - INFO - Epoch(train) [6][560/940] lr: 1.0000e-02 eta: 12:46:56 time: 0.4774 data_time: 0.0394 memory: 17006 grad_norm: 3.6872 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 2.3948 loss: 2.3948 2022/10/12 23:20:56 - mmengine - INFO - Epoch(train) [6][580/940] lr: 1.0000e-02 eta: 12:46:49 time: 0.5292 data_time: 0.0303 memory: 17006 grad_norm: 3.6926 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 2.3380 loss: 2.3380 2022/10/12 23:21:06 - mmengine - INFO - Epoch(train) [6][600/940] lr: 1.0000e-02 eta: 12:46:29 time: 0.4905 data_time: 0.0707 memory: 17006 grad_norm: 3.6373 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2737 loss: 2.2737 2022/10/12 23:21:16 - mmengine - INFO - Epoch(train) [6][620/940] lr: 1.0000e-02 eta: 12:46:26 time: 0.5406 data_time: 0.1066 memory: 17006 grad_norm: 3.6827 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.2983 loss: 2.2983 2022/10/12 23:21:28 - mmengine - INFO - Epoch(train) [6][640/940] lr: 1.0000e-02 eta: 12:46:31 time: 0.5643 data_time: 0.2332 memory: 17006 grad_norm: 3.6945 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 2.3218 loss: 2.3218 2022/10/12 23:21:37 - mmengine - INFO - Epoch(train) [6][660/940] lr: 1.0000e-02 eta: 12:46:06 time: 0.4746 data_time: 0.1499 memory: 17006 grad_norm: 3.6023 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.2379 loss: 2.2379 2022/10/12 23:21:48 - mmengine - INFO - Epoch(train) [6][680/940] lr: 1.0000e-02 eta: 12:46:07 time: 0.5512 data_time: 0.2182 memory: 17006 grad_norm: 3.6528 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 2.1472 loss: 2.1472 2022/10/12 23:21:57 - mmengine - INFO - Epoch(train) [6][700/940] lr: 1.0000e-02 eta: 12:45:39 time: 0.4668 data_time: 0.1374 memory: 17006 grad_norm: 3.7320 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 2.2057 loss: 2.2057 2022/10/12 23:22:08 - mmengine - INFO - Epoch(train) [6][720/940] lr: 1.0000e-02 eta: 12:45:34 time: 0.5334 data_time: 0.2129 memory: 17006 grad_norm: 3.6822 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0272 loss: 2.0272 2022/10/12 23:22:18 - mmengine - INFO - Epoch(train) [6][740/940] lr: 1.0000e-02 eta: 12:45:18 time: 0.5032 data_time: 0.1724 memory: 17006 grad_norm: 3.7220 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4653 loss: 2.4653 2022/10/12 23:22:29 - mmengine - INFO - Epoch(train) [6][760/940] lr: 1.0000e-02 eta: 12:45:11 time: 0.5280 data_time: 0.1899 memory: 17006 grad_norm: 3.6604 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1997 loss: 2.1997 2022/10/12 23:22:39 - mmengine - INFO - Epoch(train) [6][780/940] lr: 1.0000e-02 eta: 12:44:51 time: 0.4879 data_time: 0.1581 memory: 17006 grad_norm: 3.6995 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 2.1186 loss: 2.1186 2022/10/12 23:22:49 - mmengine - INFO - Epoch(train) [6][800/940] lr: 1.0000e-02 eta: 12:44:43 time: 0.5269 data_time: 0.1960 memory: 17006 grad_norm: 3.6245 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 2.1558 loss: 2.1558 2022/10/12 23:22:59 - mmengine - INFO - Epoch(train) [6][820/940] lr: 1.0000e-02 eta: 12:44:19 time: 0.4763 data_time: 0.1455 memory: 17006 grad_norm: 3.6179 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.3360 loss: 2.3360 2022/10/12 23:23:09 - mmengine - INFO - Epoch(train) [6][840/940] lr: 1.0000e-02 eta: 12:44:12 time: 0.5274 data_time: 0.2013 memory: 17006 grad_norm: 3.6806 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.2751 loss: 2.2751 2022/10/12 23:23:19 - mmengine - INFO - Epoch(train) [6][860/940] lr: 1.0000e-02 eta: 12:43:55 time: 0.4975 data_time: 0.1538 memory: 17006 grad_norm: 3.6900 top1_acc: 0.3750 top5_acc: 0.5312 loss_cls: 2.3076 loss: 2.3076 2022/10/12 23:23:29 - mmengine - INFO - Epoch(train) [6][880/940] lr: 1.0000e-02 eta: 12:43:43 time: 0.5144 data_time: 0.1680 memory: 17006 grad_norm: 3.6244 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 2.2107 loss: 2.2107 2022/10/12 23:23:39 - mmengine - INFO - Epoch(train) [6][900/940] lr: 1.0000e-02 eta: 12:43:19 time: 0.4743 data_time: 0.1161 memory: 17006 grad_norm: 3.6523 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.2403 loss: 2.2403 2022/10/12 23:23:49 - mmengine - INFO - Epoch(train) [6][920/940] lr: 1.0000e-02 eta: 12:43:10 time: 0.5239 data_time: 0.1886 memory: 17006 grad_norm: 3.6646 top1_acc: 0.3438 top5_acc: 0.6250 loss_cls: 2.2515 loss: 2.2515 2022/10/12 23:23:58 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 23:23:58 - mmengine - INFO - Epoch(train) [6][940/940] lr: 1.0000e-02 eta: 12:42:41 time: 0.4575 data_time: 0.1395 memory: 17006 grad_norm: 3.7792 top1_acc: 0.4286 top5_acc: 0.5714 loss_cls: 2.3689 loss: 2.3689 2022/10/12 23:23:58 - mmengine - INFO - Saving checkpoint at 6 epochs 2022/10/12 23:24:12 - mmengine - INFO - Epoch(val) [6][20/78] eta: 0:00:36 time: 0.6211 data_time: 0.5305 memory: 3172 2022/10/12 23:24:20 - mmengine - INFO - Epoch(val) [6][40/78] eta: 0:00:16 time: 0.4296 data_time: 0.3394 memory: 3172 2022/10/12 23:24:32 - mmengine - INFO - Epoch(val) [6][60/78] eta: 0:00:10 time: 0.5802 data_time: 0.4893 memory: 3172 2022/10/12 23:24:41 - mmengine - INFO - Epoch(val) [6][78/78] acc/top1: 0.5649 acc/top5: 0.8038 acc/mean1: 0.5647 2022/10/12 23:24:41 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_5.pth is removed 2022/10/12 23:24:42 - mmengine - INFO - The best checkpoint with 0.5649 acc/top1 at 6 epoch is saved to best_acc/top1_epoch_6.pth. 2022/10/12 23:24:55 - mmengine - INFO - Epoch(train) [7][20/940] lr: 1.0000e-02 eta: 12:43:21 time: 0.6777 data_time: 0.2260 memory: 17006 grad_norm: 3.6496 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2461 loss: 2.2461 2022/10/12 23:25:05 - mmengine - INFO - Epoch(train) [7][40/940] lr: 1.0000e-02 eta: 12:42:58 time: 0.4792 data_time: 0.0369 memory: 17006 grad_norm: 3.6727 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.1720 loss: 2.1720 2022/10/12 23:25:17 - mmengine - INFO - Epoch(train) [7][60/940] lr: 1.0000e-02 eta: 12:43:17 time: 0.6135 data_time: 0.0355 memory: 17006 grad_norm: 3.6199 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.1669 loss: 2.1669 2022/10/12 23:25:28 - mmengine - INFO - Epoch(train) [7][80/940] lr: 1.0000e-02 eta: 12:43:11 time: 0.5327 data_time: 0.0291 memory: 17006 grad_norm: 3.6297 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.2672 loss: 2.2672 2022/10/12 23:25:39 - mmengine - INFO - Epoch(train) [7][100/940] lr: 1.0000e-02 eta: 12:43:12 time: 0.5549 data_time: 0.0297 memory: 17006 grad_norm: 3.6463 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.1580 loss: 2.1580 2022/10/12 23:25:48 - mmengine - INFO - Epoch(train) [7][120/940] lr: 1.0000e-02 eta: 12:42:41 time: 0.4519 data_time: 0.0405 memory: 17006 grad_norm: 3.6628 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.3515 loss: 2.3515 2022/10/12 23:25:59 - mmengine - INFO - Epoch(train) [7][140/940] lr: 1.0000e-02 eta: 12:42:40 time: 0.5490 data_time: 0.0366 memory: 17006 grad_norm: 3.6559 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1557 loss: 2.1557 2022/10/12 23:26:08 - mmengine - INFO - Epoch(train) [7][160/940] lr: 1.0000e-02 eta: 12:42:04 time: 0.4336 data_time: 0.0317 memory: 17006 grad_norm: 3.6760 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 2.3092 loss: 2.3092 2022/10/12 23:26:18 - mmengine - INFO - Epoch(train) [7][180/940] lr: 1.0000e-02 eta: 12:41:55 time: 0.5254 data_time: 0.0320 memory: 17006 grad_norm: 3.6551 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.2645 loss: 2.2645 2022/10/12 23:26:28 - mmengine - INFO - Epoch(train) [7][200/940] lr: 1.0000e-02 eta: 12:41:37 time: 0.4906 data_time: 0.0364 memory: 17006 grad_norm: 3.5976 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.0773 loss: 2.0773 2022/10/12 23:26:38 - mmengine - INFO - Epoch(train) [7][220/940] lr: 1.0000e-02 eta: 12:41:27 time: 0.5223 data_time: 0.0362 memory: 17006 grad_norm: 3.6493 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.1147 loss: 2.1147 2022/10/12 23:26:48 - mmengine - INFO - Epoch(train) [7][240/940] lr: 1.0000e-02 eta: 12:41:05 time: 0.4786 data_time: 0.0397 memory: 17006 grad_norm: 3.6856 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.1775 loss: 2.1775 2022/10/12 23:26:59 - mmengine - INFO - Epoch(train) [7][260/940] lr: 1.0000e-02 eta: 12:41:06 time: 0.5545 data_time: 0.0497 memory: 17006 grad_norm: 3.6331 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.2409 loss: 2.2409 2022/10/12 23:27:08 - mmengine - INFO - Epoch(train) [7][280/940] lr: 1.0000e-02 eta: 12:40:34 time: 0.4479 data_time: 0.0370 memory: 17006 grad_norm: 3.7427 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.1509 loss: 2.1509 2022/10/12 23:27:19 - mmengine - INFO - Epoch(train) [7][300/940] lr: 1.0000e-02 eta: 12:40:26 time: 0.5260 data_time: 0.0375 memory: 17006 grad_norm: 3.6598 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1884 loss: 2.1884 2022/10/12 23:27:29 - mmengine - INFO - Epoch(train) [7][320/940] lr: 1.0000e-02 eta: 12:40:18 time: 0.5252 data_time: 0.0279 memory: 17006 grad_norm: 3.6767 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 2.2953 loss: 2.2953 2022/10/12 23:27:39 - mmengine - INFO - Epoch(train) [7][340/940] lr: 1.0000e-02 eta: 12:39:58 time: 0.4871 data_time: 0.0345 memory: 17006 grad_norm: 3.7441 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2468 loss: 2.2468 2022/10/12 23:27:49 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 23:27:49 - mmengine - INFO - Epoch(train) [7][360/940] lr: 1.0000e-02 eta: 12:39:46 time: 0.5123 data_time: 0.0304 memory: 17006 grad_norm: 3.6294 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.1718 loss: 2.1718 2022/10/12 23:27:59 - mmengine - INFO - Epoch(train) [7][380/940] lr: 1.0000e-02 eta: 12:39:34 time: 0.5108 data_time: 0.0329 memory: 17006 grad_norm: 3.6480 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.1629 loss: 2.1629 2022/10/12 23:28:09 - mmengine - INFO - Epoch(train) [7][400/940] lr: 1.0000e-02 eta: 12:39:17 time: 0.4952 data_time: 0.0400 memory: 17006 grad_norm: 3.7014 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.1045 loss: 2.1045 2022/10/12 23:28:20 - mmengine - INFO - Epoch(train) [7][420/940] lr: 1.0000e-02 eta: 12:39:09 time: 0.5253 data_time: 0.0338 memory: 17006 grad_norm: 3.6297 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.4268 loss: 2.4268 2022/10/12 23:28:30 - mmengine - INFO - Epoch(train) [7][440/940] lr: 1.0000e-02 eta: 12:39:04 time: 0.5388 data_time: 0.0352 memory: 17006 grad_norm: 3.6596 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2743 loss: 2.2743 2022/10/12 23:28:41 - mmengine - INFO - Epoch(train) [7][460/940] lr: 1.0000e-02 eta: 12:38:53 time: 0.5156 data_time: 0.0315 memory: 17006 grad_norm: 3.5910 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2982 loss: 2.2982 2022/10/12 23:28:52 - mmengine - INFO - Epoch(train) [7][480/940] lr: 1.0000e-02 eta: 12:38:49 time: 0.5389 data_time: 0.0305 memory: 17006 grad_norm: 3.6580 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.1146 loss: 2.1146 2022/10/12 23:29:02 - mmengine - INFO - Epoch(train) [7][500/940] lr: 1.0000e-02 eta: 12:38:37 time: 0.5110 data_time: 0.0347 memory: 17006 grad_norm: 3.6433 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.1831 loss: 2.1831 2022/10/12 23:29:13 - mmengine - INFO - Epoch(train) [7][520/940] lr: 1.0000e-02 eta: 12:38:38 time: 0.5597 data_time: 0.0328 memory: 17006 grad_norm: 3.7325 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.2029 loss: 2.2029 2022/10/12 23:29:22 - mmengine - INFO - Epoch(train) [7][540/940] lr: 1.0000e-02 eta: 12:38:04 time: 0.4336 data_time: 0.0360 memory: 17006 grad_norm: 3.6535 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.1859 loss: 2.1859 2022/10/12 23:29:33 - mmengine - INFO - Epoch(train) [7][560/940] lr: 1.0000e-02 eta: 12:38:02 time: 0.5480 data_time: 0.0284 memory: 17006 grad_norm: 3.6993 top1_acc: 0.3438 top5_acc: 0.5625 loss_cls: 2.2276 loss: 2.2276 2022/10/12 23:29:42 - mmengine - INFO - Epoch(train) [7][580/940] lr: 1.0000e-02 eta: 12:37:35 time: 0.4593 data_time: 0.0359 memory: 17006 grad_norm: 3.6803 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 2.2868 loss: 2.2868 2022/10/12 23:29:53 - mmengine - INFO - Epoch(train) [7][600/940] lr: 1.0000e-02 eta: 12:37:32 time: 0.5426 data_time: 0.0337 memory: 17006 grad_norm: 3.7270 top1_acc: 0.3750 top5_acc: 0.7812 loss_cls: 2.2346 loss: 2.2346 2022/10/12 23:30:02 - mmengine - INFO - Epoch(train) [7][620/940] lr: 1.0000e-02 eta: 12:37:08 time: 0.4699 data_time: 0.0323 memory: 17006 grad_norm: 3.6627 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0633 loss: 2.0633 2022/10/12 23:30:13 - mmengine - INFO - Epoch(train) [7][640/940] lr: 1.0000e-02 eta: 12:37:12 time: 0.5696 data_time: 0.0274 memory: 17006 grad_norm: 3.6440 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.1151 loss: 2.1151 2022/10/12 23:30:23 - mmengine - INFO - Epoch(train) [7][660/940] lr: 1.0000e-02 eta: 12:36:44 time: 0.4566 data_time: 0.0342 memory: 17006 grad_norm: 3.6126 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.2454 loss: 2.2454 2022/10/12 23:30:33 - mmengine - INFO - Epoch(train) [7][680/940] lr: 1.0000e-02 eta: 12:36:31 time: 0.5076 data_time: 0.0319 memory: 17006 grad_norm: 3.7075 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 2.2028 loss: 2.2028 2022/10/12 23:30:42 - mmengine - INFO - Epoch(train) [7][700/940] lr: 1.0000e-02 eta: 12:36:08 time: 0.4696 data_time: 0.0317 memory: 17006 grad_norm: 3.6956 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.4099 loss: 2.4099 2022/10/12 23:30:53 - mmengine - INFO - Epoch(train) [7][720/940] lr: 1.0000e-02 eta: 12:36:01 time: 0.5305 data_time: 0.0323 memory: 17006 grad_norm: 3.7037 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 2.1002 loss: 2.1002 2022/10/12 23:31:03 - mmengine - INFO - Epoch(train) [7][740/940] lr: 1.0000e-02 eta: 12:35:46 time: 0.5005 data_time: 0.0334 memory: 17006 grad_norm: 3.7138 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 2.3623 loss: 2.3623 2022/10/12 23:31:12 - mmengine - INFO - Epoch(train) [7][760/940] lr: 1.0000e-02 eta: 12:35:28 time: 0.4905 data_time: 0.0300 memory: 17006 grad_norm: 3.6862 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.3137 loss: 2.3137 2022/10/12 23:31:23 - mmengine - INFO - Epoch(train) [7][780/940] lr: 1.0000e-02 eta: 12:35:23 time: 0.5368 data_time: 0.0339 memory: 17006 grad_norm: 3.6679 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.1921 loss: 2.1921 2022/10/12 23:31:34 - mmengine - INFO - Epoch(train) [7][800/940] lr: 1.0000e-02 eta: 12:35:17 time: 0.5335 data_time: 0.0295 memory: 17006 grad_norm: 3.6505 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.1820 loss: 2.1820 2022/10/12 23:31:45 - mmengine - INFO - Epoch(train) [7][820/940] lr: 1.0000e-02 eta: 12:35:14 time: 0.5450 data_time: 0.0367 memory: 17006 grad_norm: 3.6869 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.1509 loss: 2.1509 2022/10/12 23:31:54 - mmengine - INFO - Epoch(train) [7][840/940] lr: 1.0000e-02 eta: 12:34:49 time: 0.4643 data_time: 0.0326 memory: 17006 grad_norm: 3.6923 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 2.2210 loss: 2.2210 2022/10/12 23:32:04 - mmengine - INFO - Epoch(train) [7][860/940] lr: 1.0000e-02 eta: 12:34:38 time: 0.5158 data_time: 0.0305 memory: 17006 grad_norm: 3.6082 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.1775 loss: 2.1775 2022/10/12 23:32:15 - mmengine - INFO - Epoch(train) [7][880/940] lr: 1.0000e-02 eta: 12:34:36 time: 0.5468 data_time: 0.0324 memory: 17006 grad_norm: 3.6810 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.1042 loss: 2.1042 2022/10/12 23:32:26 - mmengine - INFO - Epoch(train) [7][900/940] lr: 1.0000e-02 eta: 12:34:36 time: 0.5577 data_time: 0.0373 memory: 17006 grad_norm: 3.6464 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.2365 loss: 2.2365 2022/10/12 23:32:36 - mmengine - INFO - Epoch(train) [7][920/940] lr: 1.0000e-02 eta: 12:34:18 time: 0.4881 data_time: 0.0376 memory: 17006 grad_norm: 3.7175 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.2881 loss: 2.2881 2022/10/12 23:32:47 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 23:32:47 - mmengine - INFO - Epoch(train) [7][940/940] lr: 1.0000e-02 eta: 12:34:19 time: 0.5601 data_time: 0.0241 memory: 17006 grad_norm: 3.8183 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 2.1952 loss: 2.1952 2022/10/12 23:33:00 - mmengine - INFO - Epoch(val) [7][20/78] eta: 0:00:36 time: 0.6255 data_time: 0.5336 memory: 3172 2022/10/12 23:33:09 - mmengine - INFO - Epoch(val) [7][40/78] eta: 0:00:16 time: 0.4298 data_time: 0.3378 memory: 3172 2022/10/12 23:33:20 - mmengine - INFO - Epoch(val) [7][60/78] eta: 0:00:10 time: 0.5672 data_time: 0.4771 memory: 3172 2022/10/12 23:33:30 - mmengine - INFO - Epoch(val) [7][78/78] acc/top1: 0.5683 acc/top5: 0.8106 acc/mean1: 0.5681 2022/10/12 23:33:30 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_6.pth is removed 2022/10/12 23:33:31 - mmengine - INFO - The best checkpoint with 0.5683 acc/top1 at 7 epoch is saved to best_acc/top1_epoch_7.pth. 2022/10/12 23:33:44 - mmengine - INFO - Epoch(train) [8][20/940] lr: 1.0000e-02 eta: 12:34:52 time: 0.6806 data_time: 0.2508 memory: 17006 grad_norm: 3.6551 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 2.2323 loss: 2.2323 2022/10/12 23:33:53 - mmengine - INFO - Epoch(train) [8][40/940] lr: 1.0000e-02 eta: 12:34:27 time: 0.4642 data_time: 0.0265 memory: 17006 grad_norm: 3.6535 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0757 loss: 2.0757 2022/10/12 23:34:05 - mmengine - INFO - Epoch(train) [8][60/940] lr: 1.0000e-02 eta: 12:34:31 time: 0.5738 data_time: 0.0401 memory: 17006 grad_norm: 3.7345 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1200 loss: 2.1200 2022/10/12 23:34:14 - mmengine - INFO - Epoch(train) [8][80/940] lr: 1.0000e-02 eta: 12:34:00 time: 0.4375 data_time: 0.0367 memory: 17006 grad_norm: 3.6786 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 2.0881 loss: 2.0881 2022/10/12 23:34:25 - mmengine - INFO - Epoch(train) [8][100/940] lr: 1.0000e-02 eta: 12:34:00 time: 0.5593 data_time: 0.0316 memory: 17006 grad_norm: 3.6696 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 2.0595 loss: 2.0595 2022/10/12 23:34:34 - mmengine - INFO - Epoch(train) [8][120/940] lr: 1.0000e-02 eta: 12:33:31 time: 0.4461 data_time: 0.0351 memory: 17006 grad_norm: 3.7304 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.2633 loss: 2.2633 2022/10/12 23:34:45 - mmengine - INFO - Epoch(train) [8][140/940] lr: 1.0000e-02 eta: 12:33:30 time: 0.5527 data_time: 0.0349 memory: 17006 grad_norm: 3.6657 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 2.0486 loss: 2.0486 2022/10/12 23:34:54 - mmengine - INFO - Epoch(train) [8][160/940] lr: 1.0000e-02 eta: 12:33:06 time: 0.4666 data_time: 0.0333 memory: 17006 grad_norm: 3.6984 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.2070 loss: 2.2070 2022/10/12 23:35:06 - mmengine - INFO - Epoch(train) [8][180/940] lr: 1.0000e-02 eta: 12:33:09 time: 0.5685 data_time: 0.0310 memory: 17006 grad_norm: 3.6544 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 2.0813 loss: 2.0813 2022/10/12 23:35:15 - mmengine - INFO - Epoch(train) [8][200/940] lr: 1.0000e-02 eta: 12:32:45 time: 0.4642 data_time: 0.0344 memory: 17006 grad_norm: 3.7583 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.1145 loss: 2.1145 2022/10/12 23:35:25 - mmengine - INFO - Epoch(train) [8][220/940] lr: 1.0000e-02 eta: 12:32:37 time: 0.5271 data_time: 0.0345 memory: 17006 grad_norm: 3.7022 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0863 loss: 2.0863 2022/10/12 23:35:35 - mmengine - INFO - Epoch(train) [8][240/940] lr: 1.0000e-02 eta: 12:32:16 time: 0.4761 data_time: 0.0337 memory: 17006 grad_norm: 3.6991 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.0901 loss: 2.0901 2022/10/12 23:35:46 - mmengine - INFO - Epoch(train) [8][260/940] lr: 1.0000e-02 eta: 12:32:14 time: 0.5528 data_time: 0.0413 memory: 17006 grad_norm: 3.6652 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1465 loss: 2.1465 2022/10/12 23:35:56 - mmengine - INFO - Epoch(train) [8][280/940] lr: 1.0000e-02 eta: 12:32:01 time: 0.5052 data_time: 0.0288 memory: 17006 grad_norm: 3.7200 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.1524 loss: 2.1524 2022/10/12 23:36:07 - mmengine - INFO - Epoch(train) [8][300/940] lr: 1.0000e-02 eta: 12:32:01 time: 0.5591 data_time: 0.0331 memory: 17006 grad_norm: 3.7203 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.9990 loss: 1.9990 2022/10/12 23:36:17 - mmengine - INFO - Epoch(train) [8][320/940] lr: 1.0000e-02 eta: 12:31:47 time: 0.5051 data_time: 0.0295 memory: 17006 grad_norm: 3.7215 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 2.2007 loss: 2.2007 2022/10/12 23:36:28 - mmengine - INFO - Epoch(train) [8][340/940] lr: 1.0000e-02 eta: 12:31:45 time: 0.5500 data_time: 0.0375 memory: 17006 grad_norm: 3.7145 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 2.2382 loss: 2.2382 2022/10/12 23:36:37 - mmengine - INFO - Epoch(train) [8][360/940] lr: 1.0000e-02 eta: 12:31:18 time: 0.4495 data_time: 0.0353 memory: 17006 grad_norm: 3.6849 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.1834 loss: 2.1834 2022/10/12 23:36:48 - mmengine - INFO - Epoch(train) [8][380/940] lr: 1.0000e-02 eta: 12:31:12 time: 0.5390 data_time: 0.0360 memory: 17006 grad_norm: 3.8076 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.1178 loss: 2.1178 2022/10/12 23:36:58 - mmengine - INFO - Epoch(train) [8][400/940] lr: 1.0000e-02 eta: 12:30:58 time: 0.4996 data_time: 0.0340 memory: 17006 grad_norm: 3.8316 top1_acc: 0.4688 top5_acc: 0.5938 loss_cls: 2.1431 loss: 2.1431 2022/10/12 23:37:08 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 23:37:08 - mmengine - INFO - Epoch(train) [8][420/940] lr: 1.0000e-02 eta: 12:30:47 time: 0.5155 data_time: 0.0436 memory: 17006 grad_norm: 3.7264 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 2.1702 loss: 2.1702 2022/10/12 23:37:18 - mmengine - INFO - Epoch(train) [8][440/940] lr: 1.0000e-02 eta: 12:30:24 time: 0.4699 data_time: 0.0375 memory: 17006 grad_norm: 3.7646 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.2505 loss: 2.2505 2022/10/12 23:37:29 - mmengine - INFO - Epoch(train) [8][460/940] lr: 1.0000e-02 eta: 12:30:19 time: 0.5382 data_time: 0.0338 memory: 17006 grad_norm: 3.6655 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 2.1711 loss: 2.1711 2022/10/12 23:37:38 - mmengine - INFO - Epoch(train) [8][480/940] lr: 1.0000e-02 eta: 12:30:02 time: 0.4901 data_time: 0.0316 memory: 17006 grad_norm: 3.7245 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.1214 loss: 2.1214 2022/10/12 23:37:49 - mmengine - INFO - Epoch(train) [8][500/940] lr: 1.0000e-02 eta: 12:29:58 time: 0.5438 data_time: 0.0294 memory: 17006 grad_norm: 3.7218 top1_acc: 0.1875 top5_acc: 0.6562 loss_cls: 2.2676 loss: 2.2676 2022/10/12 23:37:59 - mmengine - INFO - Epoch(train) [8][520/940] lr: 1.0000e-02 eta: 12:29:42 time: 0.4947 data_time: 0.0340 memory: 17006 grad_norm: 3.6371 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.0473 loss: 2.0473 2022/10/12 23:38:10 - mmengine - INFO - Epoch(train) [8][540/940] lr: 1.0000e-02 eta: 12:29:43 time: 0.5654 data_time: 0.0286 memory: 17006 grad_norm: 3.6209 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0197 loss: 2.0197 2022/10/12 23:38:20 - mmengine - INFO - Epoch(train) [8][560/940] lr: 1.0000e-02 eta: 12:29:25 time: 0.4854 data_time: 0.0359 memory: 17006 grad_norm: 3.7015 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.1328 loss: 2.1328 2022/10/12 23:38:31 - mmengine - INFO - Epoch(train) [8][580/940] lr: 1.0000e-02 eta: 12:29:21 time: 0.5419 data_time: 0.0338 memory: 17006 grad_norm: 3.7404 top1_acc: 0.3438 top5_acc: 0.6250 loss_cls: 2.0883 loss: 2.0883 2022/10/12 23:38:41 - mmengine - INFO - Epoch(train) [8][600/940] lr: 1.0000e-02 eta: 12:29:04 time: 0.4931 data_time: 0.0354 memory: 17006 grad_norm: 3.7678 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 2.2683 loss: 2.2683 2022/10/12 23:38:52 - mmengine - INFO - Epoch(train) [8][620/940] lr: 1.0000e-02 eta: 12:29:01 time: 0.5449 data_time: 0.0338 memory: 17006 grad_norm: 3.6810 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.1228 loss: 2.1228 2022/10/12 23:39:01 - mmengine - INFO - Epoch(train) [8][640/940] lr: 1.0000e-02 eta: 12:28:36 time: 0.4604 data_time: 0.0341 memory: 17006 grad_norm: 3.7198 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.2670 loss: 2.2670 2022/10/12 23:39:12 - mmengine - INFO - Epoch(train) [8][660/940] lr: 1.0000e-02 eta: 12:28:30 time: 0.5330 data_time: 0.0286 memory: 17006 grad_norm: 3.7111 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.3305 loss: 2.3305 2022/10/12 23:39:21 - mmengine - INFO - Epoch(train) [8][680/940] lr: 1.0000e-02 eta: 12:28:09 time: 0.4723 data_time: 0.0339 memory: 17006 grad_norm: 3.7053 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.2226 loss: 2.2226 2022/10/12 23:39:32 - mmengine - INFO - Epoch(train) [8][700/940] lr: 1.0000e-02 eta: 12:28:02 time: 0.5345 data_time: 0.0268 memory: 17006 grad_norm: 3.6928 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.1962 loss: 2.1962 2022/10/12 23:39:41 - mmengine - INFO - Epoch(train) [8][720/940] lr: 1.0000e-02 eta: 12:27:41 time: 0.4726 data_time: 0.0296 memory: 17006 grad_norm: 3.6954 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 2.0435 loss: 2.0435 2022/10/12 23:39:53 - mmengine - INFO - Epoch(train) [8][740/940] lr: 1.0000e-02 eta: 12:27:42 time: 0.5628 data_time: 0.0331 memory: 17006 grad_norm: 3.6776 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 2.1914 loss: 2.1914 2022/10/12 23:40:02 - mmengine - INFO - Epoch(train) [8][760/940] lr: 1.0000e-02 eta: 12:27:18 time: 0.4632 data_time: 0.0403 memory: 17006 grad_norm: 3.7280 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.2404 loss: 2.2404 2022/10/12 23:40:13 - mmengine - INFO - Epoch(train) [8][780/940] lr: 1.0000e-02 eta: 12:27:18 time: 0.5591 data_time: 0.0298 memory: 17006 grad_norm: 3.6944 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.2477 loss: 2.2477 2022/10/12 23:40:23 - mmengine - INFO - Epoch(train) [8][800/940] lr: 1.0000e-02 eta: 12:27:04 time: 0.5021 data_time: 0.0336 memory: 17006 grad_norm: 3.7227 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0623 loss: 2.0623 2022/10/12 23:40:34 - mmengine - INFO - Epoch(train) [8][820/940] lr: 1.0000e-02 eta: 12:27:00 time: 0.5462 data_time: 0.0278 memory: 17006 grad_norm: 3.7444 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 2.1260 loss: 2.1260 2022/10/12 23:40:43 - mmengine - INFO - Epoch(train) [8][840/940] lr: 1.0000e-02 eta: 12:26:40 time: 0.4769 data_time: 0.0384 memory: 17006 grad_norm: 3.7498 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.1978 loss: 2.1978 2022/10/12 23:40:54 - mmengine - INFO - Epoch(train) [8][860/940] lr: 1.0000e-02 eta: 12:26:33 time: 0.5321 data_time: 0.0363 memory: 17006 grad_norm: 3.7704 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1583 loss: 2.1583 2022/10/12 23:41:04 - mmengine - INFO - Epoch(train) [8][880/940] lr: 1.0000e-02 eta: 12:26:21 time: 0.5096 data_time: 0.0381 memory: 17006 grad_norm: 3.7198 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 2.2356 loss: 2.2356 2022/10/12 23:41:15 - mmengine - INFO - Epoch(train) [8][900/940] lr: 1.0000e-02 eta: 12:26:13 time: 0.5249 data_time: 0.0291 memory: 17006 grad_norm: 3.7421 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 2.0341 loss: 2.0341 2022/10/12 23:41:25 - mmengine - INFO - Epoch(train) [8][920/940] lr: 1.0000e-02 eta: 12:25:59 time: 0.5028 data_time: 0.0346 memory: 17006 grad_norm: 3.6755 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.2242 loss: 2.2242 2022/10/12 23:41:35 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 23:41:35 - mmengine - INFO - Epoch(train) [8][940/940] lr: 1.0000e-02 eta: 12:25:41 time: 0.4828 data_time: 0.0327 memory: 17006 grad_norm: 3.8548 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 2.2305 loss: 2.2305 2022/10/12 23:41:47 - mmengine - INFO - Epoch(val) [8][20/78] eta: 0:00:36 time: 0.6286 data_time: 0.5347 memory: 3172 2022/10/12 23:41:56 - mmengine - INFO - Epoch(val) [8][40/78] eta: 0:00:16 time: 0.4269 data_time: 0.3350 memory: 3172 2022/10/12 23:42:07 - mmengine - INFO - Epoch(val) [8][60/78] eta: 0:00:10 time: 0.5835 data_time: 0.4894 memory: 3172 2022/10/12 23:42:17 - mmengine - INFO - Epoch(val) [8][78/78] acc/top1: 0.5728 acc/top5: 0.8117 acc/mean1: 0.5726 2022/10/12 23:42:17 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_7.pth is removed 2022/10/12 23:42:18 - mmengine - INFO - The best checkpoint with 0.5728 acc/top1 at 8 epoch is saved to best_acc/top1_epoch_8.pth. 2022/10/12 23:42:31 - mmengine - INFO - Epoch(train) [9][20/940] lr: 1.0000e-02 eta: 12:26:07 time: 0.6780 data_time: 0.3530 memory: 17006 grad_norm: 3.7402 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.0426 loss: 2.0426 2022/10/12 23:42:41 - mmengine - INFO - Epoch(train) [9][40/940] lr: 1.0000e-02 eta: 12:25:50 time: 0.4903 data_time: 0.1759 memory: 17006 grad_norm: 3.6644 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.0274 loss: 2.0274 2022/10/12 23:42:52 - mmengine - INFO - Epoch(train) [9][60/940] lr: 1.0000e-02 eta: 12:25:42 time: 0.5273 data_time: 0.1961 memory: 17006 grad_norm: 3.7578 top1_acc: 0.2812 top5_acc: 0.5625 loss_cls: 2.2580 loss: 2.2580 2022/10/12 23:43:03 - mmengine - INFO - Epoch(train) [9][80/940] lr: 1.0000e-02 eta: 12:25:39 time: 0.5488 data_time: 0.0803 memory: 17006 grad_norm: 3.6968 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0115 loss: 2.0115 2022/10/12 23:43:12 - mmengine - INFO - Epoch(train) [9][100/940] lr: 1.0000e-02 eta: 12:25:22 time: 0.4879 data_time: 0.0338 memory: 17006 grad_norm: 3.6937 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.0725 loss: 2.0725 2022/10/12 23:43:22 - mmengine - INFO - Epoch(train) [9][120/940] lr: 1.0000e-02 eta: 12:25:00 time: 0.4665 data_time: 0.1264 memory: 17006 grad_norm: 3.6804 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.1381 loss: 2.1381 2022/10/12 23:43:32 - mmengine - INFO - Epoch(train) [9][140/940] lr: 1.0000e-02 eta: 12:24:54 time: 0.5356 data_time: 0.1986 memory: 17006 grad_norm: 3.6506 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.9969 loss: 1.9969 2022/10/12 23:43:42 - mmengine - INFO - Epoch(train) [9][160/940] lr: 1.0000e-02 eta: 12:24:33 time: 0.4718 data_time: 0.1469 memory: 17006 grad_norm: 3.7312 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.0553 loss: 2.0553 2022/10/12 23:43:53 - mmengine - INFO - Epoch(train) [9][180/940] lr: 1.0000e-02 eta: 12:24:33 time: 0.5641 data_time: 0.2281 memory: 17006 grad_norm: 3.7854 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0769 loss: 2.0769 2022/10/12 23:44:03 - mmengine - INFO - Epoch(train) [9][200/940] lr: 1.0000e-02 eta: 12:24:14 time: 0.4783 data_time: 0.1541 memory: 17006 grad_norm: 3.7098 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.1615 loss: 2.1615 2022/10/12 23:44:13 - mmengine - INFO - Epoch(train) [9][220/940] lr: 1.0000e-02 eta: 12:24:06 time: 0.5269 data_time: 0.1939 memory: 17006 grad_norm: 3.6622 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9466 loss: 1.9466 2022/10/12 23:44:23 - mmengine - INFO - Epoch(train) [9][240/940] lr: 1.0000e-02 eta: 12:23:46 time: 0.4757 data_time: 0.1516 memory: 17006 grad_norm: 3.6973 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.9894 loss: 1.9894 2022/10/12 23:44:34 - mmengine - INFO - Epoch(train) [9][260/940] lr: 1.0000e-02 eta: 12:23:44 time: 0.5549 data_time: 0.2280 memory: 17006 grad_norm: 3.7271 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 2.2121 loss: 2.2121 2022/10/12 23:44:43 - mmengine - INFO - Epoch(train) [9][280/940] lr: 1.0000e-02 eta: 12:23:24 time: 0.4719 data_time: 0.1395 memory: 17006 grad_norm: 3.7217 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 2.3105 loss: 2.3105 2022/10/12 23:44:55 - mmengine - INFO - Epoch(train) [9][300/940] lr: 1.0000e-02 eta: 12:23:24 time: 0.5661 data_time: 0.2314 memory: 17006 grad_norm: 3.7022 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.0232 loss: 2.0232 2022/10/12 23:45:03 - mmengine - INFO - Epoch(train) [9][320/940] lr: 1.0000e-02 eta: 12:22:53 time: 0.4235 data_time: 0.0988 memory: 17006 grad_norm: 3.7732 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.2945 loss: 2.2945 2022/10/12 23:45:13 - mmengine - INFO - Epoch(train) [9][340/940] lr: 1.0000e-02 eta: 12:22:39 time: 0.5009 data_time: 0.1710 memory: 17006 grad_norm: 3.7733 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.1189 loss: 2.1189 2022/10/12 23:45:23 - mmengine - INFO - Epoch(train) [9][360/940] lr: 1.0000e-02 eta: 12:22:21 time: 0.4842 data_time: 0.0796 memory: 17006 grad_norm: 3.7860 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.1685 loss: 2.1685 2022/10/12 23:45:34 - mmengine - INFO - Epoch(train) [9][380/940] lr: 1.0000e-02 eta: 12:22:23 time: 0.5721 data_time: 0.1932 memory: 17006 grad_norm: 3.7170 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.2180 loss: 2.2180 2022/10/12 23:45:44 - mmengine - INFO - Epoch(train) [9][400/940] lr: 1.0000e-02 eta: 12:22:07 time: 0.4897 data_time: 0.1224 memory: 17006 grad_norm: 3.7375 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0623 loss: 2.0623 2022/10/12 23:45:56 - mmengine - INFO - Epoch(train) [9][420/940] lr: 1.0000e-02 eta: 12:22:09 time: 0.5744 data_time: 0.2166 memory: 17006 grad_norm: 3.7221 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.0882 loss: 2.0882 2022/10/12 23:46:05 - mmengine - INFO - Epoch(train) [9][440/940] lr: 1.0000e-02 eta: 12:21:50 time: 0.4787 data_time: 0.1062 memory: 17006 grad_norm: 3.7422 top1_acc: 0.3438 top5_acc: 0.7188 loss_cls: 2.1408 loss: 2.1408 2022/10/12 23:46:16 - mmengine - INFO - Epoch(train) [9][460/940] lr: 1.0000e-02 eta: 12:21:42 time: 0.5308 data_time: 0.1785 memory: 17006 grad_norm: 3.7642 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 2.1805 loss: 2.1805 2022/10/12 23:46:25 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 23:46:25 - mmengine - INFO - Epoch(train) [9][480/940] lr: 1.0000e-02 eta: 12:21:26 time: 0.4879 data_time: 0.1527 memory: 17006 grad_norm: 3.6978 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.0801 loss: 2.0801 2022/10/12 23:46:37 - mmengine - INFO - Epoch(train) [9][500/940] lr: 1.0000e-02 eta: 12:21:24 time: 0.5590 data_time: 0.2158 memory: 17006 grad_norm: 3.6724 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 2.0708 loss: 2.0708 2022/10/12 23:46:46 - mmengine - INFO - Epoch(train) [9][520/940] lr: 1.0000e-02 eta: 12:20:59 time: 0.4488 data_time: 0.1224 memory: 17006 grad_norm: 3.6729 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 2.0073 loss: 2.0073 2022/10/12 23:46:56 - mmengine - INFO - Epoch(train) [9][540/940] lr: 1.0000e-02 eta: 12:20:44 time: 0.4954 data_time: 0.1575 memory: 17006 grad_norm: 3.6857 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.0455 loss: 2.0455 2022/10/12 23:47:06 - mmengine - INFO - Epoch(train) [9][560/940] lr: 1.0000e-02 eta: 12:20:31 time: 0.5008 data_time: 0.1571 memory: 17006 grad_norm: 3.7910 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.0921 loss: 2.0921 2022/10/12 23:47:17 - mmengine - INFO - Epoch(train) [9][580/940] lr: 1.0000e-02 eta: 12:20:29 time: 0.5590 data_time: 0.2166 memory: 17006 grad_norm: 3.6671 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.0763 loss: 2.0763 2022/10/12 23:47:26 - mmengine - INFO - Epoch(train) [9][600/940] lr: 1.0000e-02 eta: 12:20:12 time: 0.4829 data_time: 0.1478 memory: 17006 grad_norm: 3.7486 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.2277 loss: 2.2277 2022/10/12 23:47:36 - mmengine - INFO - Epoch(train) [9][620/940] lr: 1.0000e-02 eta: 12:19:57 time: 0.4990 data_time: 0.1792 memory: 17006 grad_norm: 3.7562 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 2.0652 loss: 2.0652 2022/10/12 23:47:46 - mmengine - INFO - Epoch(train) [9][640/940] lr: 1.0000e-02 eta: 12:19:39 time: 0.4811 data_time: 0.1507 memory: 17006 grad_norm: 3.7017 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 2.1441 loss: 2.1441 2022/10/12 23:47:57 - mmengine - INFO - Epoch(train) [9][660/940] lr: 1.0000e-02 eta: 12:19:31 time: 0.5280 data_time: 0.1999 memory: 17006 grad_norm: 3.7648 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.1728 loss: 2.1728 2022/10/12 23:48:07 - mmengine - INFO - Epoch(train) [9][680/940] lr: 1.0000e-02 eta: 12:19:20 time: 0.5111 data_time: 0.1674 memory: 17006 grad_norm: 3.7277 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.0759 loss: 2.0759 2022/10/12 23:48:18 - mmengine - INFO - Epoch(train) [9][700/940] lr: 1.0000e-02 eta: 12:19:17 time: 0.5527 data_time: 0.2202 memory: 17006 grad_norm: 3.6672 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 2.0702 loss: 2.0702 2022/10/12 23:48:28 - mmengine - INFO - Epoch(train) [9][720/940] lr: 1.0000e-02 eta: 12:19:03 time: 0.5018 data_time: 0.1735 memory: 17006 grad_norm: 3.7153 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1630 loss: 2.1630 2022/10/12 23:48:39 - mmengine - INFO - Epoch(train) [9][740/940] lr: 1.0000e-02 eta: 12:19:03 time: 0.5656 data_time: 0.2429 memory: 17006 grad_norm: 3.7299 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.0047 loss: 2.0047 2022/10/12 23:48:49 - mmengine - INFO - Epoch(train) [9][760/940] lr: 1.0000e-02 eta: 12:18:42 time: 0.4663 data_time: 0.1330 memory: 17006 grad_norm: 3.8310 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 2.0959 loss: 2.0959 2022/10/12 23:48:59 - mmengine - INFO - Epoch(train) [9][780/940] lr: 1.0000e-02 eta: 12:18:35 time: 0.5307 data_time: 0.2015 memory: 17006 grad_norm: 3.7561 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.9995 loss: 1.9995 2022/10/12 23:49:08 - mmengine - INFO - Epoch(train) [9][800/940] lr: 1.0000e-02 eta: 12:18:13 time: 0.4636 data_time: 0.1305 memory: 17006 grad_norm: 3.7583 top1_acc: 0.5000 top5_acc: 0.5938 loss_cls: 2.0926 loss: 2.0926 2022/10/12 23:49:19 - mmengine - INFO - Epoch(train) [9][820/940] lr: 1.0000e-02 eta: 12:18:07 time: 0.5382 data_time: 0.2033 memory: 17006 grad_norm: 3.7726 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 2.0721 loss: 2.0721 2022/10/12 23:49:30 - mmengine - INFO - Epoch(train) [9][840/940] lr: 1.0000e-02 eta: 12:18:00 time: 0.5306 data_time: 0.1933 memory: 17006 grad_norm: 3.7694 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.1435 loss: 2.1435 2022/10/12 23:49:40 - mmengine - INFO - Epoch(train) [9][860/940] lr: 1.0000e-02 eta: 12:17:53 time: 0.5346 data_time: 0.2088 memory: 17006 grad_norm: 3.7725 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.1149 loss: 2.1149 2022/10/12 23:49:50 - mmengine - INFO - Epoch(train) [9][880/940] lr: 1.0000e-02 eta: 12:17:35 time: 0.4770 data_time: 0.1451 memory: 17006 grad_norm: 3.7591 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9976 loss: 1.9976 2022/10/12 23:50:01 - mmengine - INFO - Epoch(train) [9][900/940] lr: 1.0000e-02 eta: 12:17:27 time: 0.5326 data_time: 0.2006 memory: 17006 grad_norm: 3.7042 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.1550 loss: 2.1550 2022/10/12 23:50:11 - mmengine - INFO - Epoch(train) [9][920/940] lr: 1.0000e-02 eta: 12:17:12 time: 0.4941 data_time: 0.1604 memory: 17006 grad_norm: 3.7008 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0268 loss: 2.0268 2022/10/12 23:50:21 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 23:50:21 - mmengine - INFO - Epoch(train) [9][940/940] lr: 1.0000e-02 eta: 12:17:05 time: 0.5297 data_time: 0.2284 memory: 17006 grad_norm: 3.9732 top1_acc: 0.2857 top5_acc: 0.5714 loss_cls: 2.2295 loss: 2.2295 2022/10/12 23:50:21 - mmengine - INFO - Saving checkpoint at 9 epochs 2022/10/12 23:50:35 - mmengine - INFO - Epoch(val) [9][20/78] eta: 0:00:36 time: 0.6339 data_time: 0.5420 memory: 3172 2022/10/12 23:50:43 - mmengine - INFO - Epoch(val) [9][40/78] eta: 0:00:16 time: 0.4382 data_time: 0.3462 memory: 3172 2022/10/12 23:50:55 - mmengine - INFO - Epoch(val) [9][60/78] eta: 0:00:10 time: 0.5614 data_time: 0.4698 memory: 3172 2022/10/12 23:51:04 - mmengine - INFO - Epoch(val) [9][78/78] acc/top1: 0.5792 acc/top5: 0.8159 acc/mean1: 0.5790 2022/10/12 23:51:04 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_8.pth is removed 2022/10/12 23:51:04 - mmengine - INFO - The best checkpoint with 0.5792 acc/top1 at 9 epoch is saved to best_acc/top1_epoch_9.pth. 2022/10/12 23:51:18 - mmengine - INFO - Epoch(train) [10][20/940] lr: 1.0000e-02 eta: 12:17:25 time: 0.6714 data_time: 0.2419 memory: 17006 grad_norm: 3.7768 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.0851 loss: 2.0851 2022/10/12 23:51:28 - mmengine - INFO - Epoch(train) [10][40/940] lr: 1.0000e-02 eta: 12:17:15 time: 0.5147 data_time: 0.0401 memory: 17006 grad_norm: 3.7015 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.0588 loss: 2.0588 2022/10/12 23:51:40 - mmengine - INFO - Epoch(train) [10][60/940] lr: 1.0000e-02 eta: 12:17:15 time: 0.5729 data_time: 0.0356 memory: 17006 grad_norm: 3.7053 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0833 loss: 2.0833 2022/10/12 23:51:49 - mmengine - INFO - Epoch(train) [10][80/940] lr: 1.0000e-02 eta: 12:16:53 time: 0.4596 data_time: 0.0362 memory: 17006 grad_norm: 3.7022 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.0275 loss: 2.0275 2022/10/12 23:51:59 - mmengine - INFO - Epoch(train) [10][100/940] lr: 1.0000e-02 eta: 12:16:45 time: 0.5276 data_time: 0.0304 memory: 17006 grad_norm: 3.7565 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.0204 loss: 2.0204 2022/10/12 23:52:08 - mmengine - INFO - Epoch(train) [10][120/940] lr: 1.0000e-02 eta: 12:16:16 time: 0.4239 data_time: 0.0375 memory: 17006 grad_norm: 3.7462 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1005 loss: 2.1005 2022/10/12 23:52:19 - mmengine - INFO - Epoch(train) [10][140/940] lr: 1.0000e-02 eta: 12:16:14 time: 0.5595 data_time: 0.0330 memory: 17006 grad_norm: 3.7709 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 2.0265 loss: 2.0265 2022/10/12 23:52:28 - mmengine - INFO - Epoch(train) [10][160/940] lr: 1.0000e-02 eta: 12:15:53 time: 0.4622 data_time: 0.0352 memory: 17006 grad_norm: 3.7247 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.1447 loss: 2.1447 2022/10/12 23:52:39 - mmengine - INFO - Epoch(train) [10][180/940] lr: 1.0000e-02 eta: 12:15:48 time: 0.5465 data_time: 0.0298 memory: 17006 grad_norm: 3.7436 top1_acc: 0.3750 top5_acc: 0.8438 loss_cls: 2.0463 loss: 2.0463 2022/10/12 23:52:49 - mmengine - INFO - Epoch(train) [10][200/940] lr: 1.0000e-02 eta: 12:15:33 time: 0.4930 data_time: 0.0387 memory: 17006 grad_norm: 3.7606 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 2.0544 loss: 2.0544 2022/10/12 23:53:00 - mmengine - INFO - Epoch(train) [10][220/940] lr: 1.0000e-02 eta: 12:15:29 time: 0.5479 data_time: 0.0337 memory: 17006 grad_norm: 3.8619 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 2.1116 loss: 2.1116 2022/10/12 23:53:09 - mmengine - INFO - Epoch(train) [10][240/940] lr: 1.0000e-02 eta: 12:15:04 time: 0.4427 data_time: 0.0338 memory: 17006 grad_norm: 3.7335 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 2.0257 loss: 2.0257 2022/10/12 23:53:19 - mmengine - INFO - Epoch(train) [10][260/940] lr: 1.0000e-02 eta: 12:14:56 time: 0.5273 data_time: 0.0356 memory: 17006 grad_norm: 3.7954 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.2802 loss: 2.2802 2022/10/12 23:53:29 - mmengine - INFO - Epoch(train) [10][280/940] lr: 1.0000e-02 eta: 12:14:39 time: 0.4829 data_time: 0.0340 memory: 17006 grad_norm: 3.7306 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1094 loss: 2.1094 2022/10/12 23:53:40 - mmengine - INFO - Epoch(train) [10][300/940] lr: 1.0000e-02 eta: 12:14:32 time: 0.5341 data_time: 0.0344 memory: 17006 grad_norm: 3.6894 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.0615 loss: 2.0615 2022/10/12 23:53:50 - mmengine - INFO - Epoch(train) [10][320/940] lr: 1.0000e-02 eta: 12:14:19 time: 0.5071 data_time: 0.0337 memory: 17006 grad_norm: 3.7682 top1_acc: 0.3125 top5_acc: 0.5938 loss_cls: 2.0336 loss: 2.0336 2022/10/12 23:54:00 - mmengine - INFO - Epoch(train) [10][340/940] lr: 1.0000e-02 eta: 12:14:11 time: 0.5295 data_time: 0.0290 memory: 17006 grad_norm: 3.7650 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9957 loss: 1.9957 2022/10/12 23:54:10 - mmengine - INFO - Epoch(train) [10][360/940] lr: 1.0000e-02 eta: 12:13:57 time: 0.4976 data_time: 0.0380 memory: 17006 grad_norm: 3.7419 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0252 loss: 2.0252 2022/10/12 23:54:22 - mmengine - INFO - Epoch(train) [10][380/940] lr: 1.0000e-02 eta: 12:13:57 time: 0.5664 data_time: 0.0345 memory: 17006 grad_norm: 3.8107 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0066 loss: 2.0066 2022/10/12 23:54:31 - mmengine - INFO - Epoch(train) [10][400/940] lr: 1.0000e-02 eta: 12:13:39 time: 0.4784 data_time: 0.0322 memory: 17006 grad_norm: 3.7564 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.0015 loss: 2.0015 2022/10/12 23:54:42 - mmengine - INFO - Epoch(train) [10][420/940] lr: 1.0000e-02 eta: 12:13:32 time: 0.5368 data_time: 0.0320 memory: 17006 grad_norm: 3.7451 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 2.1244 loss: 2.1244 2022/10/12 23:54:51 - mmengine - INFO - Epoch(train) [10][440/940] lr: 1.0000e-02 eta: 12:13:09 time: 0.4508 data_time: 0.0364 memory: 17006 grad_norm: 3.7522 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0429 loss: 2.0429 2022/10/12 23:55:02 - mmengine - INFO - Epoch(train) [10][460/940] lr: 1.0000e-02 eta: 12:13:05 time: 0.5490 data_time: 0.0329 memory: 17006 grad_norm: 3.7378 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1603 loss: 2.1603 2022/10/12 23:55:11 - mmengine - INFO - Epoch(train) [10][480/940] lr: 1.0000e-02 eta: 12:12:46 time: 0.4712 data_time: 0.0326 memory: 17006 grad_norm: 3.7685 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.2261 loss: 2.2261 2022/10/12 23:55:21 - mmengine - INFO - Epoch(train) [10][500/940] lr: 1.0000e-02 eta: 12:12:31 time: 0.4923 data_time: 0.0313 memory: 17006 grad_norm: 3.7247 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.9686 loss: 1.9686 2022/10/12 23:55:31 - mmengine - INFO - Epoch(train) [10][520/940] lr: 1.0000e-02 eta: 12:12:10 time: 0.4616 data_time: 0.0344 memory: 17006 grad_norm: 3.7018 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.9858 loss: 1.9858 2022/10/12 23:55:42 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 23:55:42 - mmengine - INFO - Epoch(train) [10][540/940] lr: 1.0000e-02 eta: 12:12:08 time: 0.5620 data_time: 0.0341 memory: 17006 grad_norm: 3.7874 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.1085 loss: 2.1085 2022/10/12 23:55:52 - mmengine - INFO - Epoch(train) [10][560/940] lr: 1.0000e-02 eta: 12:11:53 time: 0.4876 data_time: 0.0353 memory: 17006 grad_norm: 3.7458 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.1228 loss: 2.1228 2022/10/12 23:56:02 - mmengine - INFO - Epoch(train) [10][580/940] lr: 1.0000e-02 eta: 12:11:45 time: 0.5326 data_time: 0.0327 memory: 17006 grad_norm: 3.7088 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.0881 loss: 2.0881 2022/10/12 23:56:12 - mmengine - INFO - Epoch(train) [10][600/940] lr: 1.0000e-02 eta: 12:11:28 time: 0.4785 data_time: 0.0358 memory: 17006 grad_norm: 3.7737 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1391 loss: 2.1391 2022/10/12 23:56:23 - mmengine - INFO - Epoch(train) [10][620/940] lr: 1.0000e-02 eta: 12:11:24 time: 0.5529 data_time: 0.0340 memory: 17006 grad_norm: 3.6965 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.1142 loss: 2.1142 2022/10/12 23:56:32 - mmengine - INFO - Epoch(train) [10][640/940] lr: 1.0000e-02 eta: 12:11:07 time: 0.4787 data_time: 0.0311 memory: 17006 grad_norm: 3.7489 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 2.1021 loss: 2.1021 2022/10/12 23:56:43 - mmengine - INFO - Epoch(train) [10][660/940] lr: 1.0000e-02 eta: 12:10:58 time: 0.5264 data_time: 0.0335 memory: 17006 grad_norm: 3.7338 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.0205 loss: 2.0205 2022/10/12 23:56:53 - mmengine - INFO - Epoch(train) [10][680/940] lr: 1.0000e-02 eta: 12:10:42 time: 0.4869 data_time: 0.0361 memory: 17006 grad_norm: 3.7163 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1101 loss: 2.1101 2022/10/12 23:57:04 - mmengine - INFO - Epoch(train) [10][700/940] lr: 1.0000e-02 eta: 12:10:41 time: 0.5674 data_time: 0.0362 memory: 17006 grad_norm: 3.7701 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.1157 loss: 2.1157 2022/10/12 23:57:14 - mmengine - INFO - Epoch(train) [10][720/940] lr: 1.0000e-02 eta: 12:10:25 time: 0.4850 data_time: 0.0329 memory: 17006 grad_norm: 3.6977 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.9227 loss: 1.9227 2022/10/12 23:57:24 - mmengine - INFO - Epoch(train) [10][740/940] lr: 1.0000e-02 eta: 12:10:19 time: 0.5368 data_time: 0.0343 memory: 17006 grad_norm: 3.7354 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 2.0718 loss: 2.0718 2022/10/12 23:57:34 - mmengine - INFO - Epoch(train) [10][760/940] lr: 1.0000e-02 eta: 12:10:01 time: 0.4793 data_time: 0.0343 memory: 17006 grad_norm: 3.7578 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0314 loss: 2.0314 2022/10/12 23:57:45 - mmengine - INFO - Epoch(train) [10][780/940] lr: 1.0000e-02 eta: 12:09:57 time: 0.5516 data_time: 0.0365 memory: 17006 grad_norm: 3.7112 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0844 loss: 2.0844 2022/10/12 23:57:55 - mmengine - INFO - Epoch(train) [10][800/940] lr: 1.0000e-02 eta: 12:09:39 time: 0.4731 data_time: 0.0402 memory: 17006 grad_norm: 3.6881 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9866 loss: 1.9866 2022/10/12 23:58:04 - mmengine - INFO - Epoch(train) [10][820/940] lr: 1.0000e-02 eta: 12:09:25 time: 0.4936 data_time: 0.0432 memory: 17006 grad_norm: 3.7264 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.9219 loss: 1.9219 2022/10/12 23:58:15 - mmengine - INFO - Epoch(train) [10][840/940] lr: 1.0000e-02 eta: 12:09:13 time: 0.5125 data_time: 0.0337 memory: 17006 grad_norm: 3.8024 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.0838 loss: 2.0838 2022/10/12 23:58:25 - mmengine - INFO - Epoch(train) [10][860/940] lr: 1.0000e-02 eta: 12:09:06 time: 0.5334 data_time: 0.0339 memory: 17006 grad_norm: 3.7016 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0044 loss: 2.0044 2022/10/12 23:58:34 - mmengine - INFO - Epoch(train) [10][880/940] lr: 1.0000e-02 eta: 12:08:44 time: 0.4498 data_time: 0.0344 memory: 17006 grad_norm: 3.6603 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.9456 loss: 1.9456 2022/10/12 23:58:45 - mmengine - INFO - Epoch(train) [10][900/940] lr: 1.0000e-02 eta: 12:08:36 time: 0.5311 data_time: 0.0344 memory: 17006 grad_norm: 3.7637 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0703 loss: 2.0703 2022/10/12 23:58:55 - mmengine - INFO - Epoch(train) [10][920/940] lr: 1.0000e-02 eta: 12:08:27 time: 0.5232 data_time: 0.0339 memory: 17006 grad_norm: 3.7617 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0092 loss: 2.0092 2022/10/12 23:59:05 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/12 23:59:05 - mmengine - INFO - Epoch(train) [10][940/940] lr: 1.0000e-02 eta: 12:08:14 time: 0.5014 data_time: 0.0295 memory: 17006 grad_norm: 3.9868 top1_acc: 0.4286 top5_acc: 0.4286 loss_cls: 2.1610 loss: 2.1610 2022/10/12 23:59:18 - mmengine - INFO - Epoch(val) [10][20/78] eta: 0:00:36 time: 0.6349 data_time: 0.5405 memory: 3172 2022/10/12 23:59:27 - mmengine - INFO - Epoch(val) [10][40/78] eta: 0:00:16 time: 0.4308 data_time: 0.3382 memory: 3172 2022/10/12 23:59:38 - mmengine - INFO - Epoch(val) [10][60/78] eta: 0:00:10 time: 0.5682 data_time: 0.4755 memory: 3172 2022/10/12 23:59:48 - mmengine - INFO - Epoch(val) [10][78/78] acc/top1: 0.5914 acc/top5: 0.8225 acc/mean1: 0.5912 2022/10/12 23:59:48 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_9.pth is removed 2022/10/12 23:59:49 - mmengine - INFO - The best checkpoint with 0.5914 acc/top1 at 10 epoch is saved to best_acc/top1_epoch_10.pth. 2022/10/13 00:00:02 - mmengine - INFO - Epoch(train) [11][20/940] lr: 1.0000e-02 eta: 12:08:34 time: 0.6857 data_time: 0.2879 memory: 17006 grad_norm: 3.7847 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.0000 loss: 2.0000 2022/10/13 00:00:13 - mmengine - INFO - Epoch(train) [11][40/940] lr: 1.0000e-02 eta: 12:08:24 time: 0.5207 data_time: 0.0752 memory: 17006 grad_norm: 3.7124 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.8234 loss: 1.8234 2022/10/13 00:00:23 - mmengine - INFO - Epoch(train) [11][60/940] lr: 1.0000e-02 eta: 12:08:14 time: 0.5169 data_time: 0.0308 memory: 17006 grad_norm: 3.7762 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.1131 loss: 2.1131 2022/10/13 00:00:33 - mmengine - INFO - Epoch(train) [11][80/940] lr: 1.0000e-02 eta: 12:07:56 time: 0.4755 data_time: 0.0355 memory: 17006 grad_norm: 3.7168 top1_acc: 0.3438 top5_acc: 0.6250 loss_cls: 2.0346 loss: 2.0346 2022/10/13 00:00:43 - mmengine - INFO - Epoch(train) [11][100/940] lr: 1.0000e-02 eta: 12:07:50 time: 0.5397 data_time: 0.0355 memory: 17006 grad_norm: 3.6846 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 2.0335 loss: 2.0335 2022/10/13 00:00:53 - mmengine - INFO - Epoch(train) [11][120/940] lr: 1.0000e-02 eta: 12:07:35 time: 0.4906 data_time: 0.0325 memory: 17006 grad_norm: 3.7555 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 2.0306 loss: 2.0306 2022/10/13 00:01:05 - mmengine - INFO - Epoch(train) [11][140/940] lr: 1.0000e-02 eta: 12:07:38 time: 0.5897 data_time: 0.0334 memory: 17006 grad_norm: 3.7315 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 2.1497 loss: 2.1497 2022/10/13 00:01:14 - mmengine - INFO - Epoch(train) [11][160/940] lr: 1.0000e-02 eta: 12:07:12 time: 0.4325 data_time: 0.0334 memory: 17006 grad_norm: 3.8121 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.1550 loss: 2.1550 2022/10/13 00:01:25 - mmengine - INFO - Epoch(train) [11][180/940] lr: 1.0000e-02 eta: 12:07:09 time: 0.5542 data_time: 0.0337 memory: 17006 grad_norm: 3.7210 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0703 loss: 2.0703 2022/10/13 00:01:34 - mmengine - INFO - Epoch(train) [11][200/940] lr: 1.0000e-02 eta: 12:06:50 time: 0.4715 data_time: 0.0335 memory: 17006 grad_norm: 3.7889 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.0296 loss: 2.0296 2022/10/13 00:01:45 - mmengine - INFO - Epoch(train) [11][220/940] lr: 1.0000e-02 eta: 12:06:49 time: 0.5707 data_time: 0.0324 memory: 17006 grad_norm: 3.7387 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.0090 loss: 2.0090 2022/10/13 00:01:56 - mmengine - INFO - Epoch(train) [11][240/940] lr: 1.0000e-02 eta: 12:06:37 time: 0.5021 data_time: 0.0305 memory: 17006 grad_norm: 3.7542 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 2.0415 loss: 2.0415 2022/10/13 00:02:06 - mmengine - INFO - Epoch(train) [11][260/940] lr: 1.0000e-02 eta: 12:06:26 time: 0.5143 data_time: 0.0405 memory: 17006 grad_norm: 3.7616 top1_acc: 0.5000 top5_acc: 0.5938 loss_cls: 2.1442 loss: 2.1442 2022/10/13 00:02:15 - mmengine - INFO - Epoch(train) [11][280/940] lr: 1.0000e-02 eta: 12:06:09 time: 0.4789 data_time: 0.0297 memory: 17006 grad_norm: 3.7722 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 2.1096 loss: 2.1096 2022/10/13 00:02:26 - mmengine - INFO - Epoch(train) [11][300/940] lr: 1.0000e-02 eta: 12:05:58 time: 0.5149 data_time: 0.0368 memory: 17006 grad_norm: 3.7479 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.9559 loss: 1.9559 2022/10/13 00:02:35 - mmengine - INFO - Epoch(train) [11][320/940] lr: 1.0000e-02 eta: 12:05:41 time: 0.4783 data_time: 0.0416 memory: 17006 grad_norm: 3.8084 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.0506 loss: 2.0506 2022/10/13 00:02:45 - mmengine - INFO - Epoch(train) [11][340/940] lr: 1.0000e-02 eta: 12:05:27 time: 0.4963 data_time: 0.0329 memory: 17006 grad_norm: 3.8009 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 2.0513 loss: 2.0513 2022/10/13 00:02:56 - mmengine - INFO - Epoch(train) [11][360/940] lr: 1.0000e-02 eta: 12:05:20 time: 0.5328 data_time: 0.0346 memory: 17006 grad_norm: 3.8028 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 2.0702 loss: 2.0702 2022/10/13 00:03:06 - mmengine - INFO - Epoch(train) [11][380/940] lr: 1.0000e-02 eta: 12:05:05 time: 0.4903 data_time: 0.0302 memory: 17006 grad_norm: 3.7493 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9313 loss: 1.9313 2022/10/13 00:03:16 - mmengine - INFO - Epoch(train) [11][400/940] lr: 1.0000e-02 eta: 12:04:53 time: 0.5051 data_time: 0.0322 memory: 17006 grad_norm: 3.8270 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.9900 loss: 1.9900 2022/10/13 00:03:26 - mmengine - INFO - Epoch(train) [11][420/940] lr: 1.0000e-02 eta: 12:04:46 time: 0.5367 data_time: 0.0270 memory: 17006 grad_norm: 3.8143 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.0804 loss: 2.0804 2022/10/13 00:03:37 - mmengine - INFO - Epoch(train) [11][440/940] lr: 1.0000e-02 eta: 12:04:33 time: 0.5019 data_time: 0.0303 memory: 17006 grad_norm: 3.7776 top1_acc: 0.4062 top5_acc: 0.5625 loss_cls: 2.1551 loss: 2.1551 2022/10/13 00:03:48 - mmengine - INFO - Epoch(train) [11][460/940] lr: 1.0000e-02 eta: 12:04:35 time: 0.5921 data_time: 0.0366 memory: 17006 grad_norm: 3.7592 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 2.0638 loss: 2.0638 2022/10/13 00:03:57 - mmengine - INFO - Epoch(train) [11][480/940] lr: 1.0000e-02 eta: 12:04:11 time: 0.4312 data_time: 0.0280 memory: 17006 grad_norm: 3.8407 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.0175 loss: 2.0175 2022/10/13 00:04:07 - mmengine - INFO - Epoch(train) [11][500/940] lr: 1.0000e-02 eta: 12:03:57 time: 0.5000 data_time: 0.0372 memory: 17006 grad_norm: 3.7576 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 1.9839 loss: 1.9839 2022/10/13 00:04:17 - mmengine - INFO - Epoch(train) [11][520/940] lr: 1.0000e-02 eta: 12:03:44 time: 0.4987 data_time: 0.0273 memory: 17006 grad_norm: 3.7546 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.9967 loss: 1.9967 2022/10/13 00:04:29 - mmengine - INFO - Epoch(train) [11][540/940] lr: 1.0000e-02 eta: 12:03:51 time: 0.6174 data_time: 0.0288 memory: 17006 grad_norm: 3.8015 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 2.1394 loss: 2.1394 2022/10/13 00:04:39 - mmengine - INFO - Epoch(train) [11][560/940] lr: 1.0000e-02 eta: 12:03:35 time: 0.4836 data_time: 0.0342 memory: 17006 grad_norm: 3.8210 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.9707 loss: 1.9707 2022/10/13 00:04:49 - mmengine - INFO - Epoch(train) [11][580/940] lr: 1.0000e-02 eta: 12:03:24 time: 0.5110 data_time: 0.0387 memory: 17006 grad_norm: 3.7925 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.9762 loss: 1.9762 2022/10/13 00:04:58 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 00:04:58 - mmengine - INFO - Epoch(train) [11][600/940] lr: 1.0000e-02 eta: 12:03:02 time: 0.4465 data_time: 0.0333 memory: 17006 grad_norm: 3.7738 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.9867 loss: 1.9867 2022/10/13 00:05:08 - mmengine - INFO - Epoch(train) [11][620/940] lr: 1.0000e-02 eta: 12:02:49 time: 0.5036 data_time: 0.0380 memory: 17006 grad_norm: 3.7797 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.0868 loss: 2.0868 2022/10/13 00:05:18 - mmengine - INFO - Epoch(train) [11][640/940] lr: 1.0000e-02 eta: 12:02:37 time: 0.5071 data_time: 0.0368 memory: 17006 grad_norm: 3.7408 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 1.9528 loss: 1.9528 2022/10/13 00:05:28 - mmengine - INFO - Epoch(train) [11][660/940] lr: 1.0000e-02 eta: 12:02:18 time: 0.4649 data_time: 0.0341 memory: 17006 grad_norm: 3.8092 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1240 loss: 2.1240 2022/10/13 00:05:37 - mmengine - INFO - Epoch(train) [11][680/940] lr: 1.0000e-02 eta: 12:02:04 time: 0.4923 data_time: 0.0286 memory: 17006 grad_norm: 3.8187 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 2.0271 loss: 2.0271 2022/10/13 00:05:48 - mmengine - INFO - Epoch(train) [11][700/940] lr: 1.0000e-02 eta: 12:01:58 time: 0.5444 data_time: 0.0303 memory: 17006 grad_norm: 3.7327 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9653 loss: 1.9653 2022/10/13 00:05:58 - mmengine - INFO - Epoch(train) [11][720/940] lr: 1.0000e-02 eta: 12:01:43 time: 0.4882 data_time: 0.0368 memory: 17006 grad_norm: 3.7668 top1_acc: 0.3438 top5_acc: 0.5625 loss_cls: 2.0785 loss: 2.0785 2022/10/13 00:06:08 - mmengine - INFO - Epoch(train) [11][740/940] lr: 1.0000e-02 eta: 12:01:33 time: 0.5150 data_time: 0.0314 memory: 17006 grad_norm: 3.8525 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.1169 loss: 2.1169 2022/10/13 00:06:18 - mmengine - INFO - Epoch(train) [11][760/940] lr: 1.0000e-02 eta: 12:01:19 time: 0.4982 data_time: 0.0415 memory: 17006 grad_norm: 3.7372 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 2.0269 loss: 2.0269 2022/10/13 00:06:29 - mmengine - INFO - Epoch(train) [11][780/940] lr: 1.0000e-02 eta: 12:01:07 time: 0.5061 data_time: 0.0392 memory: 17006 grad_norm: 3.7644 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 2.0470 loss: 2.0470 2022/10/13 00:06:38 - mmengine - INFO - Epoch(train) [11][800/940] lr: 1.0000e-02 eta: 12:00:52 time: 0.4824 data_time: 0.0511 memory: 17006 grad_norm: 3.8501 top1_acc: 0.3125 top5_acc: 0.6250 loss_cls: 2.1693 loss: 2.1693 2022/10/13 00:06:48 - mmengine - INFO - Epoch(train) [11][820/940] lr: 1.0000e-02 eta: 12:00:40 time: 0.5106 data_time: 0.0494 memory: 17006 grad_norm: 3.7529 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.0186 loss: 2.0186 2022/10/13 00:06:59 - mmengine - INFO - Epoch(train) [11][840/940] lr: 1.0000e-02 eta: 12:00:28 time: 0.5055 data_time: 0.0368 memory: 17006 grad_norm: 3.7673 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0039 loss: 2.0039 2022/10/13 00:07:10 - mmengine - INFO - Epoch(train) [11][860/940] lr: 1.0000e-02 eta: 12:00:30 time: 0.5900 data_time: 0.0291 memory: 17006 grad_norm: 3.7120 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9759 loss: 1.9759 2022/10/13 00:07:20 - mmengine - INFO - Epoch(train) [11][880/940] lr: 1.0000e-02 eta: 12:00:13 time: 0.4751 data_time: 0.0422 memory: 17006 grad_norm: 3.7938 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.0782 loss: 2.0782 2022/10/13 00:07:30 - mmengine - INFO - Epoch(train) [11][900/940] lr: 1.0000e-02 eta: 12:00:01 time: 0.5051 data_time: 0.0321 memory: 17006 grad_norm: 3.8057 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.0586 loss: 2.0586 2022/10/13 00:07:39 - mmengine - INFO - Epoch(train) [11][920/940] lr: 1.0000e-02 eta: 11:59:43 time: 0.4721 data_time: 0.0298 memory: 17006 grad_norm: 3.7575 top1_acc: 0.4688 top5_acc: 0.5938 loss_cls: 2.0051 loss: 2.0051 2022/10/13 00:07:49 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 00:07:49 - mmengine - INFO - Epoch(train) [11][940/940] lr: 1.0000e-02 eta: 11:59:24 time: 0.4598 data_time: 0.0251 memory: 17006 grad_norm: 3.9489 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 2.0092 loss: 2.0092 2022/10/13 00:08:01 - mmengine - INFO - Epoch(val) [11][20/78] eta: 0:00:36 time: 0.6288 data_time: 0.5353 memory: 3172 2022/10/13 00:08:10 - mmengine - INFO - Epoch(val) [11][40/78] eta: 0:00:16 time: 0.4240 data_time: 0.3331 memory: 3172 2022/10/13 00:08:21 - mmengine - INFO - Epoch(val) [11][60/78] eta: 0:00:10 time: 0.5706 data_time: 0.4772 memory: 3172 2022/10/13 00:08:31 - mmengine - INFO - Epoch(val) [11][78/78] acc/top1: 0.5969 acc/top5: 0.8277 acc/mean1: 0.5968 2022/10/13 00:08:31 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_10.pth is removed 2022/10/13 00:08:32 - mmengine - INFO - The best checkpoint with 0.5969 acc/top1 at 11 epoch is saved to best_acc/top1_epoch_11.pth. 2022/10/13 00:08:45 - mmengine - INFO - Epoch(train) [12][20/940] lr: 1.0000e-02 eta: 11:59:40 time: 0.6817 data_time: 0.3238 memory: 17006 grad_norm: 3.7673 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 2.1205 loss: 2.1205 2022/10/13 00:08:55 - mmengine - INFO - Epoch(train) [12][40/940] lr: 1.0000e-02 eta: 11:59:21 time: 0.4587 data_time: 0.0554 memory: 17006 grad_norm: 3.7778 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.0895 loss: 2.0895 2022/10/13 00:09:06 - mmengine - INFO - Epoch(train) [12][60/940] lr: 1.0000e-02 eta: 11:59:20 time: 0.5781 data_time: 0.0592 memory: 17006 grad_norm: 3.7289 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8628 loss: 1.8628 2022/10/13 00:09:15 - mmengine - INFO - Epoch(train) [12][80/940] lr: 1.0000e-02 eta: 11:58:58 time: 0.4389 data_time: 0.0349 memory: 17006 grad_norm: 3.7430 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.0469 loss: 2.0469 2022/10/13 00:09:25 - mmengine - INFO - Epoch(train) [12][100/940] lr: 1.0000e-02 eta: 11:58:48 time: 0.5187 data_time: 0.0346 memory: 17006 grad_norm: 3.7853 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.0478 loss: 2.0478 2022/10/13 00:09:36 - mmengine - INFO - Epoch(train) [12][120/940] lr: 1.0000e-02 eta: 11:58:38 time: 0.5223 data_time: 0.0532 memory: 17006 grad_norm: 3.7829 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.9071 loss: 1.9071 2022/10/13 00:09:46 - mmengine - INFO - Epoch(train) [12][140/940] lr: 1.0000e-02 eta: 11:58:26 time: 0.5020 data_time: 0.0631 memory: 17006 grad_norm: 3.6563 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8034 loss: 1.8034 2022/10/13 00:09:56 - mmengine - INFO - Epoch(train) [12][160/940] lr: 1.0000e-02 eta: 11:58:15 time: 0.5113 data_time: 0.0243 memory: 17006 grad_norm: 3.7599 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0298 loss: 2.0298 2022/10/13 00:10:06 - mmengine - INFO - Epoch(train) [12][180/940] lr: 1.0000e-02 eta: 11:58:05 time: 0.5216 data_time: 0.0346 memory: 17006 grad_norm: 3.8136 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0896 loss: 2.0896 2022/10/13 00:10:16 - mmengine - INFO - Epoch(train) [12][200/940] lr: 1.0000e-02 eta: 11:57:48 time: 0.4689 data_time: 0.0275 memory: 17006 grad_norm: 3.8115 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.9857 loss: 1.9857 2022/10/13 00:10:27 - mmengine - INFO - Epoch(train) [12][220/940] lr: 1.0000e-02 eta: 11:57:45 time: 0.5666 data_time: 0.0363 memory: 17006 grad_norm: 3.7707 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8750 loss: 1.8750 2022/10/13 00:10:36 - mmengine - INFO - Epoch(train) [12][240/940] lr: 1.0000e-02 eta: 11:57:27 time: 0.4655 data_time: 0.0317 memory: 17006 grad_norm: 3.7765 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.9900 loss: 1.9900 2022/10/13 00:10:47 - mmengine - INFO - Epoch(train) [12][260/940] lr: 1.0000e-02 eta: 11:57:16 time: 0.5115 data_time: 0.0359 memory: 17006 grad_norm: 3.7800 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.0521 loss: 2.0521 2022/10/13 00:10:57 - mmengine - INFO - Epoch(train) [12][280/940] lr: 1.0000e-02 eta: 11:57:06 time: 0.5158 data_time: 0.0351 memory: 17006 grad_norm: 3.8378 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0616 loss: 2.0616 2022/10/13 00:11:07 - mmengine - INFO - Epoch(train) [12][300/940] lr: 1.0000e-02 eta: 11:56:54 time: 0.5100 data_time: 0.0293 memory: 17006 grad_norm: 3.7740 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.1168 loss: 2.1168 2022/10/13 00:11:17 - mmengine - INFO - Epoch(train) [12][320/940] lr: 1.0000e-02 eta: 11:56:40 time: 0.4908 data_time: 0.0356 memory: 17006 grad_norm: 3.7071 top1_acc: 0.3438 top5_acc: 0.7188 loss_cls: 2.1097 loss: 2.1097 2022/10/13 00:11:28 - mmengine - INFO - Epoch(train) [12][340/940] lr: 1.0000e-02 eta: 11:56:32 time: 0.5322 data_time: 0.0314 memory: 17006 grad_norm: 3.8293 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 2.0549 loss: 2.0549 2022/10/13 00:11:38 - mmengine - INFO - Epoch(train) [12][360/940] lr: 1.0000e-02 eta: 11:56:22 time: 0.5175 data_time: 0.0273 memory: 17006 grad_norm: 3.7867 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.9258 loss: 1.9258 2022/10/13 00:11:48 - mmengine - INFO - Epoch(train) [12][380/940] lr: 1.0000e-02 eta: 11:56:12 time: 0.5145 data_time: 0.0432 memory: 17006 grad_norm: 3.7833 top1_acc: 0.4062 top5_acc: 0.5938 loss_cls: 2.1391 loss: 2.1391 2022/10/13 00:11:59 - mmengine - INFO - Epoch(train) [12][400/940] lr: 1.0000e-02 eta: 11:56:05 time: 0.5369 data_time: 0.0335 memory: 17006 grad_norm: 3.7935 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9059 loss: 1.9059 2022/10/13 00:12:08 - mmengine - INFO - Epoch(train) [12][420/940] lr: 1.0000e-02 eta: 11:55:47 time: 0.4674 data_time: 0.0344 memory: 17006 grad_norm: 3.8259 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9513 loss: 1.9513 2022/10/13 00:12:19 - mmengine - INFO - Epoch(train) [12][440/940] lr: 1.0000e-02 eta: 11:55:42 time: 0.5535 data_time: 0.0349 memory: 17006 grad_norm: 3.7922 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 2.0993 loss: 2.0993 2022/10/13 00:12:29 - mmengine - INFO - Epoch(train) [12][460/940] lr: 1.0000e-02 eta: 11:55:24 time: 0.4646 data_time: 0.0259 memory: 17006 grad_norm: 3.7740 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 2.0541 loss: 2.0541 2022/10/13 00:12:39 - mmengine - INFO - Epoch(train) [12][480/940] lr: 1.0000e-02 eta: 11:55:12 time: 0.5032 data_time: 0.0304 memory: 17006 grad_norm: 3.8190 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 2.0814 loss: 2.0814 2022/10/13 00:12:49 - mmengine - INFO - Epoch(train) [12][500/940] lr: 1.0000e-02 eta: 11:54:58 time: 0.4961 data_time: 0.0311 memory: 17006 grad_norm: 3.8820 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.2291 loss: 2.2291 2022/10/13 00:12:59 - mmengine - INFO - Epoch(train) [12][520/940] lr: 1.0000e-02 eta: 11:54:46 time: 0.5024 data_time: 0.0365 memory: 17006 grad_norm: 3.7696 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.1132 loss: 2.1132 2022/10/13 00:13:08 - mmengine - INFO - Epoch(train) [12][540/940] lr: 1.0000e-02 eta: 11:54:30 time: 0.4795 data_time: 0.0321 memory: 17006 grad_norm: 3.8311 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.0167 loss: 2.0167 2022/10/13 00:13:18 - mmengine - INFO - Epoch(train) [12][560/940] lr: 1.0000e-02 eta: 11:54:18 time: 0.5036 data_time: 0.0316 memory: 17006 grad_norm: 3.7718 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9456 loss: 1.9456 2022/10/13 00:13:29 - mmengine - INFO - Epoch(train) [12][580/940] lr: 1.0000e-02 eta: 11:54:10 time: 0.5307 data_time: 0.0341 memory: 17006 grad_norm: 3.7925 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0053 loss: 2.0053 2022/10/13 00:13:39 - mmengine - INFO - Epoch(train) [12][600/940] lr: 1.0000e-02 eta: 11:53:56 time: 0.4914 data_time: 0.0364 memory: 17006 grad_norm: 3.8133 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 2.0398 loss: 2.0398 2022/10/13 00:13:50 - mmengine - INFO - Epoch(train) [12][620/940] lr: 1.0000e-02 eta: 11:53:50 time: 0.5443 data_time: 0.0303 memory: 17006 grad_norm: 3.7849 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0235 loss: 2.0235 2022/10/13 00:14:00 - mmengine - INFO - Epoch(train) [12][640/940] lr: 1.0000e-02 eta: 11:53:37 time: 0.4998 data_time: 0.0343 memory: 17006 grad_norm: 3.7963 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.9465 loss: 1.9465 2022/10/13 00:14:10 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 00:14:10 - mmengine - INFO - Epoch(train) [12][660/940] lr: 1.0000e-02 eta: 11:53:24 time: 0.4980 data_time: 0.0350 memory: 17006 grad_norm: 3.8220 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.9370 loss: 1.9370 2022/10/13 00:14:20 - mmengine - INFO - Epoch(train) [12][680/940] lr: 1.0000e-02 eta: 11:53:11 time: 0.4982 data_time: 0.0324 memory: 17006 grad_norm: 3.7649 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.8640 loss: 1.8640 2022/10/13 00:14:30 - mmengine - INFO - Epoch(train) [12][700/940] lr: 1.0000e-02 eta: 11:52:58 time: 0.4958 data_time: 0.0303 memory: 17006 grad_norm: 3.7914 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0819 loss: 2.0819 2022/10/13 00:14:40 - mmengine - INFO - Epoch(train) [12][720/940] lr: 1.0000e-02 eta: 11:52:46 time: 0.5053 data_time: 0.0346 memory: 17006 grad_norm: 3.8180 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.8994 loss: 1.8994 2022/10/13 00:14:50 - mmengine - INFO - Epoch(train) [12][740/940] lr: 1.0000e-02 eta: 11:52:37 time: 0.5230 data_time: 0.0342 memory: 17006 grad_norm: 3.7773 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 2.0078 loss: 2.0078 2022/10/13 00:15:00 - mmengine - INFO - Epoch(train) [12][760/940] lr: 1.0000e-02 eta: 11:52:25 time: 0.5062 data_time: 0.0390 memory: 17006 grad_norm: 3.8374 top1_acc: 0.3750 top5_acc: 0.5312 loss_cls: 2.0118 loss: 2.0118 2022/10/13 00:15:10 - mmengine - INFO - Epoch(train) [12][780/940] lr: 1.0000e-02 eta: 11:52:12 time: 0.4968 data_time: 0.0329 memory: 17006 grad_norm: 3.7603 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.0416 loss: 2.0416 2022/10/13 00:15:20 - mmengine - INFO - Epoch(train) [12][800/940] lr: 1.0000e-02 eta: 11:51:58 time: 0.4921 data_time: 0.0317 memory: 17006 grad_norm: 3.7697 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9115 loss: 1.9115 2022/10/13 00:15:30 - mmengine - INFO - Epoch(train) [12][820/940] lr: 1.0000e-02 eta: 11:51:49 time: 0.5216 data_time: 0.0319 memory: 17006 grad_norm: 3.8431 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.1907 loss: 2.1907 2022/10/13 00:15:40 - mmengine - INFO - Epoch(train) [12][840/940] lr: 1.0000e-02 eta: 11:51:33 time: 0.4816 data_time: 0.0281 memory: 17006 grad_norm: 3.8668 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 2.1132 loss: 2.1132 2022/10/13 00:15:51 - mmengine - INFO - Epoch(train) [12][860/940] lr: 1.0000e-02 eta: 11:51:30 time: 0.5628 data_time: 0.0311 memory: 17006 grad_norm: 3.8317 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.0747 loss: 2.0747 2022/10/13 00:16:01 - mmengine - INFO - Epoch(train) [12][880/940] lr: 1.0000e-02 eta: 11:51:16 time: 0.4894 data_time: 0.0335 memory: 17006 grad_norm: 3.7979 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.9590 loss: 1.9590 2022/10/13 00:16:12 - mmengine - INFO - Epoch(train) [12][900/940] lr: 1.0000e-02 eta: 11:51:08 time: 0.5303 data_time: 0.0305 memory: 17006 grad_norm: 3.8247 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 2.2039 loss: 2.2039 2022/10/13 00:16:22 - mmengine - INFO - Epoch(train) [12][920/940] lr: 1.0000e-02 eta: 11:50:54 time: 0.4910 data_time: 0.0357 memory: 17006 grad_norm: 3.8170 top1_acc: 0.5312 top5_acc: 0.6250 loss_cls: 2.0639 loss: 2.0639 2022/10/13 00:16:32 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 00:16:32 - mmengine - INFO - Epoch(train) [12][940/940] lr: 1.0000e-02 eta: 11:50:44 time: 0.5162 data_time: 0.0287 memory: 17006 grad_norm: 3.9904 top1_acc: 0.4286 top5_acc: 0.4286 loss_cls: 2.0970 loss: 2.0970 2022/10/13 00:16:32 - mmengine - INFO - Saving checkpoint at 12 epochs 2022/10/13 00:16:45 - mmengine - INFO - Epoch(val) [12][20/78] eta: 0:00:36 time: 0.6278 data_time: 0.5364 memory: 3172 2022/10/13 00:16:54 - mmengine - INFO - Epoch(val) [12][40/78] eta: 0:00:16 time: 0.4288 data_time: 0.3396 memory: 3172 2022/10/13 00:17:06 - mmengine - INFO - Epoch(val) [12][60/78] eta: 0:00:10 time: 0.5798 data_time: 0.4897 memory: 3172 2022/10/13 00:17:15 - mmengine - INFO - Epoch(val) [12][78/78] acc/top1: 0.5843 acc/top5: 0.8183 acc/mean1: 0.5841 2022/10/13 00:17:29 - mmengine - INFO - Epoch(train) [13][20/940] lr: 1.0000e-02 eta: 11:51:02 time: 0.7095 data_time: 0.3537 memory: 17006 grad_norm: 3.7202 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.0531 loss: 2.0531 2022/10/13 00:17:39 - mmengine - INFO - Epoch(train) [13][40/940] lr: 1.0000e-02 eta: 11:50:49 time: 0.4974 data_time: 0.0383 memory: 17006 grad_norm: 3.8255 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0860 loss: 2.0860 2022/10/13 00:17:50 - mmengine - INFO - Epoch(train) [13][60/940] lr: 1.0000e-02 eta: 11:50:44 time: 0.5520 data_time: 0.0394 memory: 17006 grad_norm: 3.7189 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.0056 loss: 2.0056 2022/10/13 00:18:00 - mmengine - INFO - Epoch(train) [13][80/940] lr: 1.0000e-02 eta: 11:50:28 time: 0.4810 data_time: 0.0259 memory: 17006 grad_norm: 3.7502 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.9441 loss: 1.9441 2022/10/13 00:18:11 - mmengine - INFO - Epoch(train) [13][100/940] lr: 1.0000e-02 eta: 11:50:25 time: 0.5656 data_time: 0.0335 memory: 17006 grad_norm: 3.7352 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9934 loss: 1.9934 2022/10/13 00:18:21 - mmengine - INFO - Epoch(train) [13][120/940] lr: 1.0000e-02 eta: 11:50:11 time: 0.4924 data_time: 0.0367 memory: 17006 grad_norm: 3.7963 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0614 loss: 2.0614 2022/10/13 00:18:31 - mmengine - INFO - Epoch(train) [13][140/940] lr: 1.0000e-02 eta: 11:50:03 time: 0.5269 data_time: 0.0293 memory: 17006 grad_norm: 3.7811 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.8562 loss: 1.8562 2022/10/13 00:18:41 - mmengine - INFO - Epoch(train) [13][160/940] lr: 1.0000e-02 eta: 11:49:48 time: 0.4869 data_time: 0.0328 memory: 17006 grad_norm: 3.8086 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9942 loss: 1.9942 2022/10/13 00:18:52 - mmengine - INFO - Epoch(train) [13][180/940] lr: 1.0000e-02 eta: 11:49:39 time: 0.5265 data_time: 0.0297 memory: 17006 grad_norm: 3.8546 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9358 loss: 1.9358 2022/10/13 00:19:01 - mmengine - INFO - Epoch(train) [13][200/940] lr: 1.0000e-02 eta: 11:49:22 time: 0.4658 data_time: 0.0334 memory: 17006 grad_norm: 3.8268 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 2.0627 loss: 2.0627 2022/10/13 00:19:13 - mmengine - INFO - Epoch(train) [13][220/940] lr: 1.0000e-02 eta: 11:49:23 time: 0.5965 data_time: 0.0315 memory: 17006 grad_norm: 3.8313 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.0628 loss: 2.0628 2022/10/13 00:19:22 - mmengine - INFO - Epoch(train) [13][240/940] lr: 1.0000e-02 eta: 11:49:05 time: 0.4610 data_time: 0.0350 memory: 17006 grad_norm: 3.8035 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.9726 loss: 1.9726 2022/10/13 00:19:33 - mmengine - INFO - Epoch(train) [13][260/940] lr: 1.0000e-02 eta: 11:49:01 time: 0.5590 data_time: 0.0293 memory: 17006 grad_norm: 3.8079 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8749 loss: 1.8749 2022/10/13 00:19:42 - mmengine - INFO - Epoch(train) [13][280/940] lr: 1.0000e-02 eta: 11:48:42 time: 0.4538 data_time: 0.0296 memory: 17006 grad_norm: 3.7702 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.9396 loss: 1.9396 2022/10/13 00:19:54 - mmengine - INFO - Epoch(train) [13][300/940] lr: 1.0000e-02 eta: 11:48:41 time: 0.5807 data_time: 0.0370 memory: 17006 grad_norm: 3.7832 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.9615 loss: 1.9615 2022/10/13 00:20:03 - mmengine - INFO - Epoch(train) [13][320/940] lr: 1.0000e-02 eta: 11:48:21 time: 0.4537 data_time: 0.0331 memory: 17006 grad_norm: 3.8586 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9106 loss: 1.9106 2022/10/13 00:20:14 - mmengine - INFO - Epoch(train) [13][340/940] lr: 1.0000e-02 eta: 11:48:11 time: 0.5180 data_time: 0.0311 memory: 17006 grad_norm: 3.7620 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9536 loss: 1.9536 2022/10/13 00:20:23 - mmengine - INFO - Epoch(train) [13][360/940] lr: 1.0000e-02 eta: 11:47:52 time: 0.4503 data_time: 0.0296 memory: 17006 grad_norm: 3.8289 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.0396 loss: 2.0396 2022/10/13 00:20:33 - mmengine - INFO - Epoch(train) [13][380/940] lr: 1.0000e-02 eta: 11:47:40 time: 0.5081 data_time: 0.0387 memory: 17006 grad_norm: 3.8132 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.0524 loss: 2.0524 2022/10/13 00:20:43 - mmengine - INFO - Epoch(train) [13][400/940] lr: 1.0000e-02 eta: 11:47:27 time: 0.4960 data_time: 0.0360 memory: 17006 grad_norm: 3.8557 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9119 loss: 1.9119 2022/10/13 00:20:54 - mmengine - INFO - Epoch(train) [13][420/940] lr: 1.0000e-02 eta: 11:47:23 time: 0.5575 data_time: 0.0317 memory: 17006 grad_norm: 3.7870 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.0311 loss: 2.0311 2022/10/13 00:21:04 - mmengine - INFO - Epoch(train) [13][440/940] lr: 1.0000e-02 eta: 11:47:13 time: 0.5157 data_time: 0.0363 memory: 17006 grad_norm: 3.8249 top1_acc: 0.4375 top5_acc: 0.5938 loss_cls: 1.9408 loss: 1.9408 2022/10/13 00:21:15 - mmengine - INFO - Epoch(train) [13][460/940] lr: 1.0000e-02 eta: 11:47:04 time: 0.5286 data_time: 0.0338 memory: 17006 grad_norm: 3.8146 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.1483 loss: 2.1483 2022/10/13 00:21:24 - mmengine - INFO - Epoch(train) [13][480/940] lr: 1.0000e-02 eta: 11:46:47 time: 0.4638 data_time: 0.0245 memory: 17006 grad_norm: 3.8554 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9286 loss: 1.9286 2022/10/13 00:21:35 - mmengine - INFO - Epoch(train) [13][500/940] lr: 1.0000e-02 eta: 11:46:43 time: 0.5648 data_time: 0.0387 memory: 17006 grad_norm: 3.7724 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9190 loss: 1.9190 2022/10/13 00:21:44 - mmengine - INFO - Epoch(train) [13][520/940] lr: 1.0000e-02 eta: 11:46:23 time: 0.4466 data_time: 0.0341 memory: 17006 grad_norm: 3.8414 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.9971 loss: 1.9971 2022/10/13 00:21:55 - mmengine - INFO - Epoch(train) [13][540/940] lr: 1.0000e-02 eta: 11:46:17 time: 0.5466 data_time: 0.0322 memory: 17006 grad_norm: 3.8215 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.9959 loss: 1.9959 2022/10/13 00:22:04 - mmengine - INFO - Epoch(train) [13][560/940] lr: 1.0000e-02 eta: 11:45:57 time: 0.4427 data_time: 0.0356 memory: 17006 grad_norm: 3.8515 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.0686 loss: 2.0686 2022/10/13 00:22:14 - mmengine - INFO - Epoch(train) [13][580/940] lr: 1.0000e-02 eta: 11:45:43 time: 0.4931 data_time: 0.0343 memory: 17006 grad_norm: 3.8994 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 2.0507 loss: 2.0507 2022/10/13 00:22:23 - mmengine - INFO - Epoch(train) [13][600/940] lr: 1.0000e-02 eta: 11:45:26 time: 0.4656 data_time: 0.0312 memory: 17006 grad_norm: 3.8150 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9720 loss: 1.9720 2022/10/13 00:22:34 - mmengine - INFO - Epoch(train) [13][620/940] lr: 1.0000e-02 eta: 11:45:18 time: 0.5313 data_time: 0.0517 memory: 17006 grad_norm: 3.8222 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 2.0563 loss: 2.0563 2022/10/13 00:22:43 - mmengine - INFO - Epoch(train) [13][640/940] lr: 1.0000e-02 eta: 11:45:03 time: 0.4785 data_time: 0.0322 memory: 17006 grad_norm: 3.7850 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.9559 loss: 1.9559 2022/10/13 00:22:55 - mmengine - INFO - Epoch(train) [13][660/940] lr: 1.0000e-02 eta: 11:44:59 time: 0.5629 data_time: 0.0304 memory: 17006 grad_norm: 3.7758 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9844 loss: 1.9844 2022/10/13 00:23:04 - mmengine - INFO - Epoch(train) [13][680/940] lr: 1.0000e-02 eta: 11:44:43 time: 0.4732 data_time: 0.0344 memory: 17006 grad_norm: 3.8293 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 2.0169 loss: 2.0169 2022/10/13 00:23:15 - mmengine - INFO - Epoch(train) [13][700/940] lr: 1.0000e-02 eta: 11:44:38 time: 0.5595 data_time: 0.0345 memory: 17006 grad_norm: 3.8968 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0107 loss: 2.0107 2022/10/13 00:23:24 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 00:23:24 - mmengine - INFO - Epoch(train) [13][720/940] lr: 1.0000e-02 eta: 11:44:21 time: 0.4625 data_time: 0.0291 memory: 17006 grad_norm: 3.8968 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 2.0054 loss: 2.0054 2022/10/13 00:23:35 - mmengine - INFO - Epoch(train) [13][740/940] lr: 1.0000e-02 eta: 11:44:11 time: 0.5216 data_time: 0.0309 memory: 17006 grad_norm: 3.8369 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 2.0014 loss: 2.0014 2022/10/13 00:23:44 - mmengine - INFO - Epoch(train) [13][760/940] lr: 1.0000e-02 eta: 11:43:55 time: 0.4714 data_time: 0.0312 memory: 17006 grad_norm: 3.9219 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.1233 loss: 2.1233 2022/10/13 00:23:55 - mmengine - INFO - Epoch(train) [13][780/940] lr: 1.0000e-02 eta: 11:43:45 time: 0.5193 data_time: 0.0337 memory: 17006 grad_norm: 3.8386 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.8412 loss: 1.8412 2022/10/13 00:24:05 - mmengine - INFO - Epoch(train) [13][800/940] lr: 1.0000e-02 eta: 11:43:33 time: 0.5012 data_time: 0.0359 memory: 17006 grad_norm: 3.8905 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0384 loss: 2.0384 2022/10/13 00:24:16 - mmengine - INFO - Epoch(train) [13][820/940] lr: 1.0000e-02 eta: 11:43:28 time: 0.5566 data_time: 0.0363 memory: 17006 grad_norm: 3.7857 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.9214 loss: 1.9214 2022/10/13 00:24:25 - mmengine - INFO - Epoch(train) [13][840/940] lr: 1.0000e-02 eta: 11:43:11 time: 0.4595 data_time: 0.0283 memory: 17006 grad_norm: 3.8242 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9815 loss: 1.9815 2022/10/13 00:24:36 - mmengine - INFO - Epoch(train) [13][860/940] lr: 1.0000e-02 eta: 11:43:01 time: 0.5228 data_time: 0.0338 memory: 17006 grad_norm: 3.8406 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.0706 loss: 2.0706 2022/10/13 00:24:46 - mmengine - INFO - Epoch(train) [13][880/940] lr: 1.0000e-02 eta: 11:42:51 time: 0.5145 data_time: 0.0327 memory: 17006 grad_norm: 3.8173 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 2.0567 loss: 2.0567 2022/10/13 00:24:56 - mmengine - INFO - Epoch(train) [13][900/940] lr: 1.0000e-02 eta: 11:42:41 time: 0.5194 data_time: 0.0261 memory: 17006 grad_norm: 3.8004 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9269 loss: 1.9269 2022/10/13 00:25:06 - mmengine - INFO - Epoch(train) [13][920/940] lr: 1.0000e-02 eta: 11:42:30 time: 0.5093 data_time: 0.0299 memory: 17006 grad_norm: 3.7802 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 2.0896 loss: 2.0896 2022/10/13 00:25:16 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 00:25:16 - mmengine - INFO - Epoch(train) [13][940/940] lr: 1.0000e-02 eta: 11:42:18 time: 0.5001 data_time: 0.0241 memory: 17006 grad_norm: 4.0806 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.9625 loss: 1.9625 2022/10/13 00:25:29 - mmengine - INFO - Epoch(val) [13][20/78] eta: 0:00:36 time: 0.6306 data_time: 0.5353 memory: 3172 2022/10/13 00:25:38 - mmengine - INFO - Epoch(val) [13][40/78] eta: 0:00:16 time: 0.4242 data_time: 0.3328 memory: 3172 2022/10/13 00:25:49 - mmengine - INFO - Epoch(val) [13][60/78] eta: 0:00:10 time: 0.5774 data_time: 0.4852 memory: 3172 2022/10/13 00:25:59 - mmengine - INFO - Epoch(val) [13][78/78] acc/top1: 0.5998 acc/top5: 0.8288 acc/mean1: 0.5997 2022/10/13 00:25:59 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_11.pth is removed 2022/10/13 00:25:59 - mmengine - INFO - The best checkpoint with 0.5998 acc/top1 at 13 epoch is saved to best_acc/top1_epoch_13.pth. 2022/10/13 00:26:13 - mmengine - INFO - Epoch(train) [14][20/940] lr: 1.0000e-02 eta: 11:42:32 time: 0.6966 data_time: 0.3002 memory: 17006 grad_norm: 3.8801 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.9687 loss: 1.9687 2022/10/13 00:26:23 - mmengine - INFO - Epoch(train) [14][40/940] lr: 1.0000e-02 eta: 11:42:19 time: 0.5022 data_time: 0.0567 memory: 17006 grad_norm: 3.7833 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.8734 loss: 1.8734 2022/10/13 00:26:34 - mmengine - INFO - Epoch(train) [14][60/940] lr: 1.0000e-02 eta: 11:42:08 time: 0.5066 data_time: 0.0475 memory: 17006 grad_norm: 3.8236 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9512 loss: 1.9512 2022/10/13 00:26:43 - mmengine - INFO - Epoch(train) [14][80/940] lr: 1.0000e-02 eta: 11:41:55 time: 0.4939 data_time: 0.0323 memory: 17006 grad_norm: 3.8004 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.0551 loss: 2.0551 2022/10/13 00:26:54 - mmengine - INFO - Epoch(train) [14][100/940] lr: 1.0000e-02 eta: 11:41:46 time: 0.5269 data_time: 0.0355 memory: 17006 grad_norm: 3.8641 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0165 loss: 2.0165 2022/10/13 00:27:03 - mmengine - INFO - Epoch(train) [14][120/940] lr: 1.0000e-02 eta: 11:41:26 time: 0.4389 data_time: 0.0348 memory: 17006 grad_norm: 3.8061 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.0425 loss: 2.0425 2022/10/13 00:27:13 - mmengine - INFO - Epoch(train) [14][140/940] lr: 1.0000e-02 eta: 11:41:18 time: 0.5356 data_time: 0.0315 memory: 17006 grad_norm: 3.8096 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.9960 loss: 1.9960 2022/10/13 00:27:23 - mmengine - INFO - Epoch(train) [14][160/940] lr: 1.0000e-02 eta: 11:41:05 time: 0.4972 data_time: 0.0383 memory: 17006 grad_norm: 3.8294 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.9023 loss: 1.9023 2022/10/13 00:27:34 - mmengine - INFO - Epoch(train) [14][180/940] lr: 1.0000e-02 eta: 11:40:54 time: 0.5118 data_time: 0.0306 memory: 17006 grad_norm: 3.8121 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9423 loss: 1.9423 2022/10/13 00:27:44 - mmengine - INFO - Epoch(train) [14][200/940] lr: 1.0000e-02 eta: 11:40:43 time: 0.5098 data_time: 0.0359 memory: 17006 grad_norm: 3.8562 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 2.0333 loss: 2.0333 2022/10/13 00:27:54 - mmengine - INFO - Epoch(train) [14][220/940] lr: 1.0000e-02 eta: 11:40:31 time: 0.5003 data_time: 0.0296 memory: 17006 grad_norm: 3.8764 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 2.0909 loss: 2.0909 2022/10/13 00:28:04 - mmengine - INFO - Epoch(train) [14][240/940] lr: 1.0000e-02 eta: 11:40:18 time: 0.4950 data_time: 0.0301 memory: 17006 grad_norm: 3.8689 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.0242 loss: 2.0242 2022/10/13 00:28:14 - mmengine - INFO - Epoch(train) [14][260/940] lr: 1.0000e-02 eta: 11:40:09 time: 0.5207 data_time: 0.0315 memory: 17006 grad_norm: 3.7912 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9509 loss: 1.9509 2022/10/13 00:28:24 - mmengine - INFO - Epoch(train) [14][280/940] lr: 1.0000e-02 eta: 11:39:55 time: 0.4886 data_time: 0.0337 memory: 17006 grad_norm: 3.8657 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 2.0682 loss: 2.0682 2022/10/13 00:28:34 - mmengine - INFO - Epoch(train) [14][300/940] lr: 1.0000e-02 eta: 11:39:42 time: 0.4985 data_time: 0.0296 memory: 17006 grad_norm: 3.8914 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9845 loss: 1.9845 2022/10/13 00:28:44 - mmengine - INFO - Epoch(train) [14][320/940] lr: 1.0000e-02 eta: 11:39:29 time: 0.4935 data_time: 0.0342 memory: 17006 grad_norm: 3.8736 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.8620 loss: 1.8620 2022/10/13 00:28:54 - mmengine - INFO - Epoch(train) [14][340/940] lr: 1.0000e-02 eta: 11:39:21 time: 0.5296 data_time: 0.0313 memory: 17006 grad_norm: 3.8642 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.8607 loss: 1.8607 2022/10/13 00:29:05 - mmengine - INFO - Epoch(train) [14][360/940] lr: 1.0000e-02 eta: 11:39:10 time: 0.5111 data_time: 0.0306 memory: 17006 grad_norm: 3.9073 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.0671 loss: 2.0671 2022/10/13 00:29:15 - mmengine - INFO - Epoch(train) [14][380/940] lr: 1.0000e-02 eta: 11:39:01 time: 0.5234 data_time: 0.0290 memory: 17006 grad_norm: 3.8119 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.9209 loss: 1.9209 2022/10/13 00:29:24 - mmengine - INFO - Epoch(train) [14][400/940] lr: 1.0000e-02 eta: 11:38:44 time: 0.4672 data_time: 0.0336 memory: 17006 grad_norm: 3.7353 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9874 loss: 1.9874 2022/10/13 00:29:35 - mmengine - INFO - Epoch(train) [14][420/940] lr: 1.0000e-02 eta: 11:38:39 time: 0.5524 data_time: 0.0352 memory: 17006 grad_norm: 3.8539 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 2.0346 loss: 2.0346 2022/10/13 00:29:45 - mmengine - INFO - Epoch(train) [14][440/940] lr: 1.0000e-02 eta: 11:38:24 time: 0.4811 data_time: 0.0384 memory: 17006 grad_norm: 3.8378 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9256 loss: 1.9256 2022/10/13 00:29:56 - mmengine - INFO - Epoch(train) [14][460/940] lr: 1.0000e-02 eta: 11:38:18 time: 0.5482 data_time: 0.0344 memory: 17006 grad_norm: 3.8901 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9938 loss: 1.9938 2022/10/13 00:30:06 - mmengine - INFO - Epoch(train) [14][480/940] lr: 1.0000e-02 eta: 11:38:03 time: 0.4801 data_time: 0.0368 memory: 17006 grad_norm: 3.7564 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.1942 loss: 2.1942 2022/10/13 00:30:16 - mmengine - INFO - Epoch(train) [14][500/940] lr: 1.0000e-02 eta: 11:37:51 time: 0.5035 data_time: 0.0355 memory: 17006 grad_norm: 3.8062 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 2.0156 loss: 2.0156 2022/10/13 00:30:25 - mmengine - INFO - Epoch(train) [14][520/940] lr: 1.0000e-02 eta: 11:37:37 time: 0.4812 data_time: 0.0393 memory: 17006 grad_norm: 3.8382 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.9072 loss: 1.9072 2022/10/13 00:30:36 - mmengine - INFO - Epoch(train) [14][540/940] lr: 1.0000e-02 eta: 11:37:29 time: 0.5352 data_time: 0.0309 memory: 17006 grad_norm: 3.8412 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9469 loss: 1.9469 2022/10/13 00:30:46 - mmengine - INFO - Epoch(train) [14][560/940] lr: 1.0000e-02 eta: 11:37:18 time: 0.5139 data_time: 0.0318 memory: 17006 grad_norm: 3.8277 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 2.0643 loss: 2.0643 2022/10/13 00:30:56 - mmengine - INFO - Epoch(train) [14][580/940] lr: 1.0000e-02 eta: 11:37:02 time: 0.4670 data_time: 0.0284 memory: 17006 grad_norm: 3.8168 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 2.1035 loss: 2.1035 2022/10/13 00:31:06 - mmengine - INFO - Epoch(train) [14][600/940] lr: 1.0000e-02 eta: 11:36:52 time: 0.5153 data_time: 0.0371 memory: 17006 grad_norm: 3.8017 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.8386 loss: 1.8386 2022/10/13 00:31:16 - mmengine - INFO - Epoch(train) [14][620/940] lr: 1.0000e-02 eta: 11:36:42 time: 0.5171 data_time: 0.0311 memory: 17006 grad_norm: 3.8527 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.9446 loss: 1.9446 2022/10/13 00:31:27 - mmengine - INFO - Epoch(train) [14][640/940] lr: 1.0000e-02 eta: 11:36:34 time: 0.5394 data_time: 0.0409 memory: 17006 grad_norm: 3.8283 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 2.0900 loss: 2.0900 2022/10/13 00:31:37 - mmengine - INFO - Epoch(train) [14][660/940] lr: 1.0000e-02 eta: 11:36:22 time: 0.4985 data_time: 0.0282 memory: 17006 grad_norm: 3.8751 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9880 loss: 1.9880 2022/10/13 00:31:47 - mmengine - INFO - Epoch(train) [14][680/940] lr: 1.0000e-02 eta: 11:36:06 time: 0.4705 data_time: 0.0368 memory: 17006 grad_norm: 3.8843 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 2.0778 loss: 2.0778 2022/10/13 00:31:56 - mmengine - INFO - Epoch(train) [14][700/940] lr: 1.0000e-02 eta: 11:35:50 time: 0.4652 data_time: 0.0341 memory: 17006 grad_norm: 3.8581 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9954 loss: 1.9954 2022/10/13 00:32:06 - mmengine - INFO - Epoch(train) [14][720/940] lr: 1.0000e-02 eta: 11:35:41 time: 0.5323 data_time: 0.0349 memory: 17006 grad_norm: 3.9183 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.1479 loss: 2.1479 2022/10/13 00:32:16 - mmengine - INFO - Epoch(train) [14][740/940] lr: 1.0000e-02 eta: 11:35:27 time: 0.4792 data_time: 0.0343 memory: 17006 grad_norm: 3.8821 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.0068 loss: 2.0068 2022/10/13 00:32:26 - mmengine - INFO - Epoch(train) [14][760/940] lr: 1.0000e-02 eta: 11:35:17 time: 0.5186 data_time: 0.0332 memory: 17006 grad_norm: 3.8665 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8456 loss: 1.8456 2022/10/13 00:32:38 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 00:32:38 - mmengine - INFO - Epoch(train) [14][780/940] lr: 1.0000e-02 eta: 11:35:12 time: 0.5573 data_time: 0.0328 memory: 17006 grad_norm: 3.8209 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9195 loss: 1.9195 2022/10/13 00:32:47 - mmengine - INFO - Epoch(train) [14][800/940] lr: 1.0000e-02 eta: 11:34:59 time: 0.4955 data_time: 0.0299 memory: 17006 grad_norm: 3.8638 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9160 loss: 1.9160 2022/10/13 00:32:58 - mmengine - INFO - Epoch(train) [14][820/940] lr: 1.0000e-02 eta: 11:34:49 time: 0.5125 data_time: 0.0347 memory: 17006 grad_norm: 3.9306 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.1459 loss: 2.1459 2022/10/13 00:33:08 - mmengine - INFO - Epoch(train) [14][840/940] lr: 1.0000e-02 eta: 11:34:37 time: 0.5083 data_time: 0.0306 memory: 17006 grad_norm: 3.8256 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9380 loss: 1.9380 2022/10/13 00:33:17 - mmengine - INFO - Epoch(train) [14][860/940] lr: 1.0000e-02 eta: 11:34:20 time: 0.4554 data_time: 0.0303 memory: 17006 grad_norm: 3.8134 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.8793 loss: 1.8793 2022/10/13 00:33:28 - mmengine - INFO - Epoch(train) [14][880/940] lr: 1.0000e-02 eta: 11:34:15 time: 0.5630 data_time: 0.0351 memory: 17006 grad_norm: 3.8634 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.9812 loss: 1.9812 2022/10/13 00:33:38 - mmengine - INFO - Epoch(train) [14][900/940] lr: 1.0000e-02 eta: 11:33:59 time: 0.4626 data_time: 0.0303 memory: 17006 grad_norm: 3.9074 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9479 loss: 1.9479 2022/10/13 00:33:48 - mmengine - INFO - Epoch(train) [14][920/940] lr: 1.0000e-02 eta: 11:33:50 time: 0.5295 data_time: 0.0341 memory: 17006 grad_norm: 3.8526 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.9377 loss: 1.9377 2022/10/13 00:33:57 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 00:33:57 - mmengine - INFO - Epoch(train) [14][940/940] lr: 1.0000e-02 eta: 11:33:29 time: 0.4305 data_time: 0.0268 memory: 17006 grad_norm: 4.0500 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.9274 loss: 1.9274 2022/10/13 00:34:09 - mmengine - INFO - Epoch(val) [14][20/78] eta: 0:00:36 time: 0.6307 data_time: 0.5366 memory: 3172 2022/10/13 00:34:18 - mmengine - INFO - Epoch(val) [14][40/78] eta: 0:00:16 time: 0.4330 data_time: 0.3422 memory: 3172 2022/10/13 00:34:30 - mmengine - INFO - Epoch(val) [14][60/78] eta: 0:00:10 time: 0.5770 data_time: 0.4854 memory: 3172 2022/10/13 00:34:39 - mmengine - INFO - Epoch(val) [14][78/78] acc/top1: 0.6028 acc/top5: 0.8261 acc/mean1: 0.6027 2022/10/13 00:34:39 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_13.pth is removed 2022/10/13 00:34:40 - mmengine - INFO - The best checkpoint with 0.6028 acc/top1 at 14 epoch is saved to best_acc/top1_epoch_14.pth. 2022/10/13 00:34:53 - mmengine - INFO - Epoch(train) [15][20/940] lr: 1.0000e-02 eta: 11:33:40 time: 0.6862 data_time: 0.3053 memory: 17006 grad_norm: 3.8844 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.9644 loss: 1.9644 2022/10/13 00:35:03 - mmengine - INFO - Epoch(train) [15][40/940] lr: 1.0000e-02 eta: 11:33:24 time: 0.4704 data_time: 0.1040 memory: 17006 grad_norm: 3.8460 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8428 loss: 1.8428 2022/10/13 00:35:14 - mmengine - INFO - Epoch(train) [15][60/940] lr: 1.0000e-02 eta: 11:33:18 time: 0.5481 data_time: 0.2000 memory: 17006 grad_norm: 3.8586 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.9179 loss: 1.9179 2022/10/13 00:35:23 - mmengine - INFO - Epoch(train) [15][80/940] lr: 1.0000e-02 eta: 11:33:02 time: 0.4632 data_time: 0.1187 memory: 17006 grad_norm: 3.8506 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.9782 loss: 1.9782 2022/10/13 00:35:34 - mmengine - INFO - Epoch(train) [15][100/940] lr: 1.0000e-02 eta: 11:32:54 time: 0.5334 data_time: 0.1520 memory: 17006 grad_norm: 3.8192 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.9844 loss: 1.9844 2022/10/13 00:35:43 - mmengine - INFO - Epoch(train) [15][120/940] lr: 1.0000e-02 eta: 11:32:38 time: 0.4739 data_time: 0.1127 memory: 17006 grad_norm: 3.8270 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.9027 loss: 1.9027 2022/10/13 00:35:54 - mmengine - INFO - Epoch(train) [15][140/940] lr: 1.0000e-02 eta: 11:32:32 time: 0.5466 data_time: 0.0281 memory: 17006 grad_norm: 3.8671 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9351 loss: 1.9351 2022/10/13 00:36:04 - mmengine - INFO - Epoch(train) [15][160/940] lr: 1.0000e-02 eta: 11:32:18 time: 0.4833 data_time: 0.0302 memory: 17006 grad_norm: 3.8336 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.9691 loss: 1.9691 2022/10/13 00:36:15 - mmengine - INFO - Epoch(train) [15][180/940] lr: 1.0000e-02 eta: 11:32:13 time: 0.5629 data_time: 0.0353 memory: 17006 grad_norm: 3.8123 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8870 loss: 1.8870 2022/10/13 00:36:24 - mmengine - INFO - Epoch(train) [15][200/940] lr: 1.0000e-02 eta: 11:31:57 time: 0.4624 data_time: 0.0310 memory: 17006 grad_norm: 3.8611 top1_acc: 0.4688 top5_acc: 0.9062 loss_cls: 2.0786 loss: 2.0786 2022/10/13 00:36:35 - mmengine - INFO - Epoch(train) [15][220/940] lr: 1.0000e-02 eta: 11:31:48 time: 0.5299 data_time: 0.0319 memory: 17006 grad_norm: 3.8098 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 2.0608 loss: 2.0608 2022/10/13 00:36:45 - mmengine - INFO - Epoch(train) [15][240/940] lr: 1.0000e-02 eta: 11:31:38 time: 0.5164 data_time: 0.0328 memory: 17006 grad_norm: 3.8574 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.9771 loss: 1.9771 2022/10/13 00:36:55 - mmengine - INFO - Epoch(train) [15][260/940] lr: 1.0000e-02 eta: 11:31:24 time: 0.4810 data_time: 0.0304 memory: 17006 grad_norm: 3.8757 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.0873 loss: 2.0873 2022/10/13 00:37:05 - mmengine - INFO - Epoch(train) [15][280/940] lr: 1.0000e-02 eta: 11:31:12 time: 0.5016 data_time: 0.0302 memory: 17006 grad_norm: 3.8351 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8003 loss: 1.8003 2022/10/13 00:37:14 - mmengine - INFO - Epoch(train) [15][300/940] lr: 1.0000e-02 eta: 11:30:57 time: 0.4742 data_time: 0.0385 memory: 17006 grad_norm: 3.8209 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9422 loss: 1.9422 2022/10/13 00:37:25 - mmengine - INFO - Epoch(train) [15][320/940] lr: 1.0000e-02 eta: 11:30:48 time: 0.5279 data_time: 0.0332 memory: 17006 grad_norm: 3.7957 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9692 loss: 1.9692 2022/10/13 00:37:35 - mmengine - INFO - Epoch(train) [15][340/940] lr: 1.0000e-02 eta: 11:30:33 time: 0.4772 data_time: 0.0303 memory: 17006 grad_norm: 3.8796 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.9342 loss: 1.9342 2022/10/13 00:37:45 - mmengine - INFO - Epoch(train) [15][360/940] lr: 1.0000e-02 eta: 11:30:25 time: 0.5366 data_time: 0.0323 memory: 17006 grad_norm: 3.9041 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9179 loss: 1.9179 2022/10/13 00:37:55 - mmengine - INFO - Epoch(train) [15][380/940] lr: 1.0000e-02 eta: 11:30:11 time: 0.4768 data_time: 0.0327 memory: 17006 grad_norm: 3.8582 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.9353 loss: 1.9353 2022/10/13 00:38:05 - mmengine - INFO - Epoch(train) [15][400/940] lr: 1.0000e-02 eta: 11:30:03 time: 0.5339 data_time: 0.0377 memory: 17006 grad_norm: 3.8572 top1_acc: 0.3750 top5_acc: 0.5938 loss_cls: 1.9519 loss: 1.9519 2022/10/13 00:38:16 - mmengine - INFO - Epoch(train) [15][420/940] lr: 1.0000e-02 eta: 11:29:57 time: 0.5520 data_time: 0.0319 memory: 17006 grad_norm: 3.8419 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9609 loss: 1.9609 2022/10/13 00:38:25 - mmengine - INFO - Epoch(train) [15][440/940] lr: 1.0000e-02 eta: 11:29:37 time: 0.4349 data_time: 0.0350 memory: 17006 grad_norm: 3.7963 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.9856 loss: 1.9856 2022/10/13 00:38:36 - mmengine - INFO - Epoch(train) [15][460/940] lr: 1.0000e-02 eta: 11:29:31 time: 0.5525 data_time: 0.0345 memory: 17006 grad_norm: 3.8158 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.9579 loss: 1.9579 2022/10/13 00:38:46 - mmengine - INFO - Epoch(train) [15][480/940] lr: 1.0000e-02 eta: 11:29:19 time: 0.4956 data_time: 0.0312 memory: 17006 grad_norm: 3.9001 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 2.0074 loss: 2.0074 2022/10/13 00:38:58 - mmengine - INFO - Epoch(train) [15][500/940] lr: 1.0000e-02 eta: 11:29:16 time: 0.5803 data_time: 0.0279 memory: 17006 grad_norm: 3.8786 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9949 loss: 1.9949 2022/10/13 00:39:08 - mmengine - INFO - Epoch(train) [15][520/940] lr: 1.0000e-02 eta: 11:29:03 time: 0.4880 data_time: 0.0311 memory: 17006 grad_norm: 3.8003 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8959 loss: 1.8959 2022/10/13 00:39:17 - mmengine - INFO - Epoch(train) [15][540/940] lr: 1.0000e-02 eta: 11:28:49 time: 0.4854 data_time: 0.0346 memory: 17006 grad_norm: 3.9426 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.7485 loss: 1.7485 2022/10/13 00:39:26 - mmengine - INFO - Epoch(train) [15][560/940] lr: 1.0000e-02 eta: 11:28:32 time: 0.4571 data_time: 0.0289 memory: 17006 grad_norm: 3.8744 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9821 loss: 1.9821 2022/10/13 00:39:37 - mmengine - INFO - Epoch(train) [15][580/940] lr: 1.0000e-02 eta: 11:28:24 time: 0.5321 data_time: 0.0285 memory: 17006 grad_norm: 3.8836 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.0327 loss: 2.0327 2022/10/13 00:39:47 - mmengine - INFO - Epoch(train) [15][600/940] lr: 1.0000e-02 eta: 11:28:13 time: 0.5115 data_time: 0.0345 memory: 17006 grad_norm: 3.8691 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.0001 loss: 2.0001 2022/10/13 00:39:58 - mmengine - INFO - Epoch(train) [15][620/940] lr: 1.0000e-02 eta: 11:28:06 time: 0.5437 data_time: 0.0314 memory: 17006 grad_norm: 3.8487 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.9930 loss: 1.9930 2022/10/13 00:40:08 - mmengine - INFO - Epoch(train) [15][640/940] lr: 1.0000e-02 eta: 11:27:53 time: 0.4891 data_time: 0.0382 memory: 17006 grad_norm: 3.8985 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8568 loss: 1.8568 2022/10/13 00:40:19 - mmengine - INFO - Epoch(train) [15][660/940] lr: 1.0000e-02 eta: 11:27:47 time: 0.5571 data_time: 0.0367 memory: 17006 grad_norm: 3.8693 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9362 loss: 1.9362 2022/10/13 00:40:28 - mmengine - INFO - Epoch(train) [15][680/940] lr: 1.0000e-02 eta: 11:27:30 time: 0.4538 data_time: 0.0406 memory: 17006 grad_norm: 3.8995 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8199 loss: 1.8199 2022/10/13 00:40:39 - mmengine - INFO - Epoch(train) [15][700/940] lr: 1.0000e-02 eta: 11:27:25 time: 0.5633 data_time: 0.0398 memory: 17006 grad_norm: 3.8944 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 2.0866 loss: 2.0866 2022/10/13 00:40:48 - mmengine - INFO - Epoch(train) [15][720/940] lr: 1.0000e-02 eta: 11:27:08 time: 0.4501 data_time: 0.0281 memory: 17006 grad_norm: 3.9067 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.9772 loss: 1.9772 2022/10/13 00:40:59 - mmengine - INFO - Epoch(train) [15][740/940] lr: 1.0000e-02 eta: 11:26:58 time: 0.5173 data_time: 0.0345 memory: 17006 grad_norm: 3.8733 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9365 loss: 1.9365 2022/10/13 00:41:08 - mmengine - INFO - Epoch(train) [15][760/940] lr: 1.0000e-02 eta: 11:26:44 time: 0.4825 data_time: 0.0309 memory: 17006 grad_norm: 3.8450 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.8554 loss: 1.8554 2022/10/13 00:41:20 - mmengine - INFO - Epoch(train) [15][780/940] lr: 1.0000e-02 eta: 11:26:39 time: 0.5643 data_time: 0.0313 memory: 17006 grad_norm: 3.8762 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 2.1774 loss: 2.1774 2022/10/13 00:41:30 - mmengine - INFO - Epoch(train) [15][800/940] lr: 1.0000e-02 eta: 11:26:26 time: 0.4913 data_time: 0.0306 memory: 17006 grad_norm: 3.9009 top1_acc: 0.3438 top5_acc: 0.5625 loss_cls: 2.0745 loss: 2.0745 2022/10/13 00:41:40 - mmengine - INFO - Epoch(train) [15][820/940] lr: 1.0000e-02 eta: 11:26:14 time: 0.5014 data_time: 0.0308 memory: 17006 grad_norm: 3.8495 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0086 loss: 2.0086 2022/10/13 00:41:51 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 00:41:51 - mmengine - INFO - Epoch(train) [15][840/940] lr: 1.0000e-02 eta: 11:26:10 time: 0.5641 data_time: 0.0319 memory: 17006 grad_norm: 3.8619 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.0454 loss: 2.0454 2022/10/13 00:42:00 - mmengine - INFO - Epoch(train) [15][860/940] lr: 1.0000e-02 eta: 11:25:56 time: 0.4829 data_time: 0.0309 memory: 17006 grad_norm: 3.9662 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0750 loss: 2.0750 2022/10/13 00:42:12 - mmengine - INFO - Epoch(train) [15][880/940] lr: 1.0000e-02 eta: 11:25:50 time: 0.5523 data_time: 0.0285 memory: 17006 grad_norm: 3.8883 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.9947 loss: 1.9947 2022/10/13 00:42:21 - mmengine - INFO - Epoch(train) [15][900/940] lr: 1.0000e-02 eta: 11:25:34 time: 0.4698 data_time: 0.0253 memory: 17006 grad_norm: 3.8627 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7974 loss: 1.7974 2022/10/13 00:42:31 - mmengine - INFO - Epoch(train) [15][920/940] lr: 1.0000e-02 eta: 11:25:25 time: 0.5218 data_time: 0.0370 memory: 17006 grad_norm: 3.8537 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.8976 loss: 1.8976 2022/10/13 00:42:41 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 00:42:41 - mmengine - INFO - Epoch(train) [15][940/940] lr: 1.0000e-02 eta: 11:25:12 time: 0.4943 data_time: 0.0277 memory: 17006 grad_norm: 4.0137 top1_acc: 0.4286 top5_acc: 0.4286 loss_cls: 1.9602 loss: 1.9602 2022/10/13 00:42:41 - mmengine - INFO - Saving checkpoint at 15 epochs 2022/10/13 00:42:55 - mmengine - INFO - Epoch(val) [15][20/78] eta: 0:00:36 time: 0.6288 data_time: 0.5374 memory: 3172 2022/10/13 00:43:03 - mmengine - INFO - Epoch(val) [15][40/78] eta: 0:00:16 time: 0.4275 data_time: 0.3372 memory: 3172 2022/10/13 00:43:15 - mmengine - INFO - Epoch(val) [15][60/78] eta: 0:00:10 time: 0.5800 data_time: 0.4892 memory: 3172 2022/10/13 00:43:24 - mmengine - INFO - Epoch(val) [15][78/78] acc/top1: 0.6084 acc/top5: 0.8336 acc/mean1: 0.6083 2022/10/13 00:43:24 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_14.pth is removed 2022/10/13 00:43:25 - mmengine - INFO - The best checkpoint with 0.6084 acc/top1 at 15 epoch is saved to best_acc/top1_epoch_15.pth. 2022/10/13 00:43:38 - mmengine - INFO - Epoch(train) [16][20/940] lr: 1.0000e-02 eta: 11:25:20 time: 0.6762 data_time: 0.3027 memory: 17006 grad_norm: 3.7818 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.8408 loss: 1.8408 2022/10/13 00:43:48 - mmengine - INFO - Epoch(train) [16][40/940] lr: 1.0000e-02 eta: 11:25:06 time: 0.4763 data_time: 0.0954 memory: 17006 grad_norm: 3.8421 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8936 loss: 1.8936 2022/10/13 00:43:59 - mmengine - INFO - Epoch(train) [16][60/940] lr: 1.0000e-02 eta: 11:25:03 time: 0.5805 data_time: 0.2591 memory: 17006 grad_norm: 3.8335 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0423 loss: 2.0423 2022/10/13 00:44:08 - mmengine - INFO - Epoch(train) [16][80/940] lr: 1.0000e-02 eta: 11:24:44 time: 0.4396 data_time: 0.1032 memory: 17006 grad_norm: 3.8691 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8704 loss: 1.8704 2022/10/13 00:44:18 - mmengine - INFO - Epoch(train) [16][100/940] lr: 1.0000e-02 eta: 11:24:34 time: 0.5147 data_time: 0.1938 memory: 17006 grad_norm: 3.8317 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.8151 loss: 1.8151 2022/10/13 00:44:29 - mmengine - INFO - Epoch(train) [16][120/940] lr: 1.0000e-02 eta: 11:24:22 time: 0.5008 data_time: 0.1295 memory: 17006 grad_norm: 3.7904 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9353 loss: 1.9353 2022/10/13 00:44:40 - mmengine - INFO - Epoch(train) [16][140/940] lr: 1.0000e-02 eta: 11:24:19 time: 0.5818 data_time: 0.0335 memory: 17006 grad_norm: 3.8916 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.9913 loss: 1.9913 2022/10/13 00:44:50 - mmengine - INFO - Epoch(train) [16][160/940] lr: 1.0000e-02 eta: 11:24:06 time: 0.4852 data_time: 0.0252 memory: 17006 grad_norm: 3.9189 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.9208 loss: 1.9208 2022/10/13 00:45:00 - mmengine - INFO - Epoch(train) [16][180/940] lr: 1.0000e-02 eta: 11:23:54 time: 0.5013 data_time: 0.0344 memory: 17006 grad_norm: 3.8576 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9413 loss: 1.9413 2022/10/13 00:45:10 - mmengine - INFO - Epoch(train) [16][200/940] lr: 1.0000e-02 eta: 11:23:40 time: 0.4815 data_time: 0.0263 memory: 17006 grad_norm: 3.9035 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.9957 loss: 1.9957 2022/10/13 00:45:20 - mmengine - INFO - Epoch(train) [16][220/940] lr: 1.0000e-02 eta: 11:23:30 time: 0.5240 data_time: 0.0337 memory: 17006 grad_norm: 3.8782 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 2.0092 loss: 2.0092 2022/10/13 00:45:29 - mmengine - INFO - Epoch(train) [16][240/940] lr: 1.0000e-02 eta: 11:23:13 time: 0.4504 data_time: 0.0295 memory: 17006 grad_norm: 3.8576 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9650 loss: 1.9650 2022/10/13 00:45:40 - mmengine - INFO - Epoch(train) [16][260/940] lr: 1.0000e-02 eta: 11:23:06 time: 0.5441 data_time: 0.0329 memory: 17006 grad_norm: 3.8489 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7863 loss: 1.7863 2022/10/13 00:45:49 - mmengine - INFO - Epoch(train) [16][280/940] lr: 1.0000e-02 eta: 11:22:50 time: 0.4666 data_time: 0.0341 memory: 17006 grad_norm: 3.8870 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.0031 loss: 2.0031 2022/10/13 00:46:00 - mmengine - INFO - Epoch(train) [16][300/940] lr: 1.0000e-02 eta: 11:22:43 time: 0.5439 data_time: 0.0358 memory: 17006 grad_norm: 3.9198 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 1.9589 loss: 1.9589 2022/10/13 00:46:09 - mmengine - INFO - Epoch(train) [16][320/940] lr: 1.0000e-02 eta: 11:22:27 time: 0.4622 data_time: 0.0333 memory: 17006 grad_norm: 3.9684 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 2.0829 loss: 2.0829 2022/10/13 00:46:22 - mmengine - INFO - Epoch(train) [16][340/940] lr: 1.0000e-02 eta: 11:22:27 time: 0.6097 data_time: 0.0263 memory: 17006 grad_norm: 3.8288 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8633 loss: 1.8633 2022/10/13 00:46:31 - mmengine - INFO - Epoch(train) [16][360/940] lr: 1.0000e-02 eta: 11:22:13 time: 0.4726 data_time: 0.0334 memory: 17006 grad_norm: 3.8582 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 2.0600 loss: 2.0600 2022/10/13 00:46:42 - mmengine - INFO - Epoch(train) [16][380/940] lr: 1.0000e-02 eta: 11:22:05 time: 0.5356 data_time: 0.0332 memory: 17006 grad_norm: 3.9038 top1_acc: 0.6875 top5_acc: 0.7188 loss_cls: 1.8295 loss: 1.8295 2022/10/13 00:46:52 - mmengine - INFO - Epoch(train) [16][400/940] lr: 1.0000e-02 eta: 11:21:52 time: 0.4943 data_time: 0.0337 memory: 17006 grad_norm: 3.8599 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9839 loss: 1.9839 2022/10/13 00:47:02 - mmengine - INFO - Epoch(train) [16][420/940] lr: 1.0000e-02 eta: 11:21:41 time: 0.5067 data_time: 0.0341 memory: 17006 grad_norm: 3.8120 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 2.0297 loss: 2.0297 2022/10/13 00:47:11 - mmengine - INFO - Epoch(train) [16][440/940] lr: 1.0000e-02 eta: 11:21:27 time: 0.4796 data_time: 0.0300 memory: 17006 grad_norm: 3.8332 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8581 loss: 1.8581 2022/10/13 00:47:22 - mmengine - INFO - Epoch(train) [16][460/940] lr: 1.0000e-02 eta: 11:21:17 time: 0.5170 data_time: 0.0293 memory: 17006 grad_norm: 3.8697 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 1.9262 loss: 1.9262 2022/10/13 00:47:31 - mmengine - INFO - Epoch(train) [16][480/940] lr: 1.0000e-02 eta: 11:21:04 time: 0.4884 data_time: 0.0407 memory: 17006 grad_norm: 3.9174 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9915 loss: 1.9915 2022/10/13 00:47:42 - mmengine - INFO - Epoch(train) [16][500/940] lr: 1.0000e-02 eta: 11:20:57 time: 0.5474 data_time: 0.0357 memory: 17006 grad_norm: 3.8926 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.0131 loss: 2.0131 2022/10/13 00:47:52 - mmengine - INFO - Epoch(train) [16][520/940] lr: 1.0000e-02 eta: 11:20:42 time: 0.4721 data_time: 0.0311 memory: 17006 grad_norm: 3.8831 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.8220 loss: 1.8220 2022/10/13 00:48:01 - mmengine - INFO - Epoch(train) [16][540/940] lr: 1.0000e-02 eta: 11:20:27 time: 0.4705 data_time: 0.0303 memory: 17006 grad_norm: 3.8533 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.9497 loss: 1.9497 2022/10/13 00:48:11 - mmengine - INFO - Epoch(train) [16][560/940] lr: 1.0000e-02 eta: 11:20:14 time: 0.4908 data_time: 0.0319 memory: 17006 grad_norm: 3.8701 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9899 loss: 1.9899 2022/10/13 00:48:22 - mmengine - INFO - Epoch(train) [16][580/940] lr: 1.0000e-02 eta: 11:20:07 time: 0.5409 data_time: 0.0283 memory: 17006 grad_norm: 3.8365 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.9794 loss: 1.9794 2022/10/13 00:48:32 - mmengine - INFO - Epoch(train) [16][600/940] lr: 1.0000e-02 eta: 11:19:54 time: 0.4932 data_time: 0.0340 memory: 17006 grad_norm: 3.8591 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9652 loss: 1.9652 2022/10/13 00:48:42 - mmengine - INFO - Epoch(train) [16][620/940] lr: 1.0000e-02 eta: 11:19:45 time: 0.5228 data_time: 0.0292 memory: 17006 grad_norm: 3.9765 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9109 loss: 1.9109 2022/10/13 00:48:52 - mmengine - INFO - Epoch(train) [16][640/940] lr: 1.0000e-02 eta: 11:19:33 time: 0.5033 data_time: 0.0329 memory: 17006 grad_norm: 3.9077 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.9969 loss: 1.9969 2022/10/13 00:49:03 - mmengine - INFO - Epoch(train) [16][660/940] lr: 1.0000e-02 eta: 11:19:26 time: 0.5461 data_time: 0.0330 memory: 17006 grad_norm: 3.8306 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8516 loss: 1.8516 2022/10/13 00:49:13 - mmengine - INFO - Epoch(train) [16][680/940] lr: 1.0000e-02 eta: 11:19:13 time: 0.4834 data_time: 0.0375 memory: 17006 grad_norm: 3.8472 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9168 loss: 1.9168 2022/10/13 00:49:24 - mmengine - INFO - Epoch(train) [16][700/940] lr: 1.0000e-02 eta: 11:19:06 time: 0.5488 data_time: 0.0300 memory: 17006 grad_norm: 3.8595 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.9199 loss: 1.9199 2022/10/13 00:49:33 - mmengine - INFO - Epoch(train) [16][720/940] lr: 1.0000e-02 eta: 11:18:49 time: 0.4488 data_time: 0.0306 memory: 17006 grad_norm: 3.9084 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8160 loss: 1.8160 2022/10/13 00:49:43 - mmengine - INFO - Epoch(train) [16][740/940] lr: 1.0000e-02 eta: 11:18:38 time: 0.5085 data_time: 0.0310 memory: 17006 grad_norm: 3.8131 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.0020 loss: 2.0020 2022/10/13 00:49:53 - mmengine - INFO - Epoch(train) [16][760/940] lr: 1.0000e-02 eta: 11:18:28 time: 0.5141 data_time: 0.0284 memory: 17006 grad_norm: 3.8806 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.8769 loss: 1.8769 2022/10/13 00:50:04 - mmengine - INFO - Epoch(train) [16][780/940] lr: 1.0000e-02 eta: 11:18:19 time: 0.5317 data_time: 0.0316 memory: 17006 grad_norm: 3.9255 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8250 loss: 1.8250 2022/10/13 00:50:14 - mmengine - INFO - Epoch(train) [16][800/940] lr: 1.0000e-02 eta: 11:18:08 time: 0.5057 data_time: 0.0270 memory: 17006 grad_norm: 3.9265 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9783 loss: 1.9783 2022/10/13 00:50:25 - mmengine - INFO - Epoch(train) [16][820/940] lr: 1.0000e-02 eta: 11:17:59 time: 0.5321 data_time: 0.0355 memory: 17006 grad_norm: 3.8956 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.0278 loss: 2.0278 2022/10/13 00:50:35 - mmengine - INFO - Epoch(train) [16][840/940] lr: 1.0000e-02 eta: 11:17:47 time: 0.4941 data_time: 0.0343 memory: 17006 grad_norm: 3.9161 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7917 loss: 1.7917 2022/10/13 00:50:45 - mmengine - INFO - Epoch(train) [16][860/940] lr: 1.0000e-02 eta: 11:17:39 time: 0.5382 data_time: 0.0245 memory: 17006 grad_norm: 3.8896 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9263 loss: 1.9263 2022/10/13 00:50:55 - mmengine - INFO - Epoch(train) [16][880/940] lr: 1.0000e-02 eta: 11:17:29 time: 0.5107 data_time: 0.0356 memory: 17006 grad_norm: 3.9497 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.9098 loss: 1.9098 2022/10/13 00:51:06 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 00:51:06 - mmengine - INFO - Epoch(train) [16][900/940] lr: 1.0000e-02 eta: 11:17:20 time: 0.5269 data_time: 0.0255 memory: 17006 grad_norm: 3.9758 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7698 loss: 1.7698 2022/10/13 00:51:16 - mmengine - INFO - Epoch(train) [16][920/940] lr: 1.0000e-02 eta: 11:17:09 time: 0.5076 data_time: 0.0298 memory: 17006 grad_norm: 3.9182 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8525 loss: 1.8525 2022/10/13 00:51:26 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 00:51:26 - mmengine - INFO - Epoch(train) [16][940/940] lr: 1.0000e-02 eta: 11:16:58 time: 0.5074 data_time: 0.0256 memory: 17006 grad_norm: 4.1573 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 2.0115 loss: 2.0115 2022/10/13 00:51:39 - mmengine - INFO - Epoch(val) [16][20/78] eta: 0:00:36 time: 0.6292 data_time: 0.5346 memory: 3172 2022/10/13 00:51:48 - mmengine - INFO - Epoch(val) [16][40/78] eta: 0:00:16 time: 0.4346 data_time: 0.3416 memory: 3172 2022/10/13 00:51:59 - mmengine - INFO - Epoch(val) [16][60/78] eta: 0:00:10 time: 0.5732 data_time: 0.4806 memory: 3172 2022/10/13 00:52:09 - mmengine - INFO - Epoch(val) [16][78/78] acc/top1: 0.6095 acc/top5: 0.8339 acc/mean1: 0.6092 2022/10/13 00:52:09 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_15.pth is removed 2022/10/13 00:52:09 - mmengine - INFO - The best checkpoint with 0.6095 acc/top1 at 16 epoch is saved to best_acc/top1_epoch_16.pth. 2022/10/13 00:52:23 - mmengine - INFO - Epoch(train) [17][20/940] lr: 1.0000e-02 eta: 11:17:06 time: 0.6893 data_time: 0.3019 memory: 17006 grad_norm: 3.8114 top1_acc: 0.5625 top5_acc: 0.6250 loss_cls: 1.9360 loss: 1.9360 2022/10/13 00:52:33 - mmengine - INFO - Epoch(train) [17][40/940] lr: 1.0000e-02 eta: 11:16:52 time: 0.4814 data_time: 0.0329 memory: 17006 grad_norm: 3.8029 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.8817 loss: 1.8817 2022/10/13 00:52:44 - mmengine - INFO - Epoch(train) [17][60/940] lr: 1.0000e-02 eta: 11:16:46 time: 0.5560 data_time: 0.0328 memory: 17006 grad_norm: 3.8762 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.9270 loss: 1.9270 2022/10/13 00:52:54 - mmengine - INFO - Epoch(train) [17][80/940] lr: 1.0000e-02 eta: 11:16:32 time: 0.4836 data_time: 0.0339 memory: 17006 grad_norm: 3.8984 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 2.1024 loss: 2.1024 2022/10/13 00:53:04 - mmengine - INFO - Epoch(train) [17][100/940] lr: 1.0000e-02 eta: 11:16:24 time: 0.5376 data_time: 0.0347 memory: 17006 grad_norm: 3.9242 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 2.0060 loss: 2.0060 2022/10/13 00:53:14 - mmengine - INFO - Epoch(train) [17][120/940] lr: 1.0000e-02 eta: 11:16:11 time: 0.4809 data_time: 0.0300 memory: 17006 grad_norm: 3.8759 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.9587 loss: 1.9587 2022/10/13 00:53:25 - mmengine - INFO - Epoch(train) [17][140/940] lr: 1.0000e-02 eta: 11:16:04 time: 0.5523 data_time: 0.0326 memory: 17006 grad_norm: 3.9208 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9053 loss: 1.9053 2022/10/13 00:53:35 - mmengine - INFO - Epoch(train) [17][160/940] lr: 1.0000e-02 eta: 11:15:50 time: 0.4737 data_time: 0.0282 memory: 17006 grad_norm: 3.8563 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.9574 loss: 1.9574 2022/10/13 00:53:46 - mmengine - INFO - Epoch(train) [17][180/940] lr: 1.0000e-02 eta: 11:15:44 time: 0.5582 data_time: 0.0320 memory: 17006 grad_norm: 3.9318 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9749 loss: 1.9749 2022/10/13 00:53:55 - mmengine - INFO - Epoch(train) [17][200/940] lr: 1.0000e-02 eta: 11:15:26 time: 0.4412 data_time: 0.0318 memory: 17006 grad_norm: 3.8615 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 1.8715 loss: 1.8715 2022/10/13 00:54:05 - mmengine - INFO - Epoch(train) [17][220/940] lr: 1.0000e-02 eta: 11:15:18 time: 0.5339 data_time: 0.0349 memory: 17006 grad_norm: 3.8711 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7667 loss: 1.7667 2022/10/13 00:54:15 - mmengine - INFO - Epoch(train) [17][240/940] lr: 1.0000e-02 eta: 11:15:04 time: 0.4788 data_time: 0.0358 memory: 17006 grad_norm: 3.9519 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 2.2135 loss: 2.2135 2022/10/13 00:54:26 - mmengine - INFO - Epoch(train) [17][260/940] lr: 1.0000e-02 eta: 11:14:58 time: 0.5587 data_time: 0.0303 memory: 17006 grad_norm: 3.9125 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.8251 loss: 1.8251 2022/10/13 00:54:35 - mmengine - INFO - Epoch(train) [17][280/940] lr: 1.0000e-02 eta: 11:14:41 time: 0.4539 data_time: 0.0295 memory: 17006 grad_norm: 3.8851 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.9705 loss: 1.9705 2022/10/13 00:54:46 - mmengine - INFO - Epoch(train) [17][300/940] lr: 1.0000e-02 eta: 11:14:36 time: 0.5642 data_time: 0.0298 memory: 17006 grad_norm: 3.8967 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7798 loss: 1.7798 2022/10/13 00:54:56 - mmengine - INFO - Epoch(train) [17][320/940] lr: 1.0000e-02 eta: 11:14:21 time: 0.4658 data_time: 0.0352 memory: 17006 grad_norm: 3.8458 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8775 loss: 1.8775 2022/10/13 00:55:06 - mmengine - INFO - Epoch(train) [17][340/940] lr: 1.0000e-02 eta: 11:14:11 time: 0.5217 data_time: 0.0286 memory: 17006 grad_norm: 3.9548 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8720 loss: 1.8720 2022/10/13 00:55:15 - mmengine - INFO - Epoch(train) [17][360/940] lr: 1.0000e-02 eta: 11:13:56 time: 0.4640 data_time: 0.0359 memory: 17006 grad_norm: 3.8715 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8392 loss: 1.8392 2022/10/13 00:55:27 - mmengine - INFO - Epoch(train) [17][380/940] lr: 1.0000e-02 eta: 11:13:53 time: 0.5861 data_time: 0.0324 memory: 17006 grad_norm: 3.9161 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8144 loss: 1.8144 2022/10/13 00:55:36 - mmengine - INFO - Epoch(train) [17][400/940] lr: 1.0000e-02 eta: 11:13:35 time: 0.4346 data_time: 0.0372 memory: 17006 grad_norm: 3.8299 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.8114 loss: 1.8114 2022/10/13 00:55:46 - mmengine - INFO - Epoch(train) [17][420/940] lr: 1.0000e-02 eta: 11:13:25 time: 0.5230 data_time: 0.0308 memory: 17006 grad_norm: 3.9607 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.9220 loss: 1.9220 2022/10/13 00:55:55 - mmengine - INFO - Epoch(train) [17][440/940] lr: 1.0000e-02 eta: 11:13:09 time: 0.4597 data_time: 0.0352 memory: 17006 grad_norm: 3.8777 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7683 loss: 1.7683 2022/10/13 00:56:07 - mmengine - INFO - Epoch(train) [17][460/940] lr: 1.0000e-02 eta: 11:13:06 time: 0.5824 data_time: 0.0340 memory: 17006 grad_norm: 3.9167 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.9011 loss: 1.9011 2022/10/13 00:56:16 - mmengine - INFO - Epoch(train) [17][480/940] lr: 1.0000e-02 eta: 11:12:50 time: 0.4608 data_time: 0.0357 memory: 17006 grad_norm: 3.9717 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.8421 loss: 1.8421 2022/10/13 00:56:27 - mmengine - INFO - Epoch(train) [17][500/940] lr: 1.0000e-02 eta: 11:12:43 time: 0.5463 data_time: 0.0252 memory: 17006 grad_norm: 3.9083 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9734 loss: 1.9734 2022/10/13 00:56:37 - mmengine - INFO - Epoch(train) [17][520/940] lr: 1.0000e-02 eta: 11:12:30 time: 0.4835 data_time: 0.0306 memory: 17006 grad_norm: 3.9290 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.9321 loss: 1.9321 2022/10/13 00:56:48 - mmengine - INFO - Epoch(train) [17][540/940] lr: 1.0000e-02 eta: 11:12:22 time: 0.5394 data_time: 0.0364 memory: 17006 grad_norm: 3.9082 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.9044 loss: 1.9044 2022/10/13 00:56:58 - mmengine - INFO - Epoch(train) [17][560/940] lr: 1.0000e-02 eta: 11:12:11 time: 0.5056 data_time: 0.0291 memory: 17006 grad_norm: 3.8904 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8436 loss: 1.8436 2022/10/13 00:57:09 - mmengine - INFO - Epoch(train) [17][580/940] lr: 1.0000e-02 eta: 11:12:03 time: 0.5399 data_time: 0.0310 memory: 17006 grad_norm: 3.9100 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.9039 loss: 1.9039 2022/10/13 00:57:18 - mmengine - INFO - Epoch(train) [17][600/940] lr: 1.0000e-02 eta: 11:11:50 time: 0.4888 data_time: 0.0346 memory: 17006 grad_norm: 3.8638 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 2.0634 loss: 2.0634 2022/10/13 00:57:29 - mmengine - INFO - Epoch(train) [17][620/940] lr: 1.0000e-02 eta: 11:11:43 time: 0.5480 data_time: 0.0310 memory: 17006 grad_norm: 3.8799 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.9750 loss: 1.9750 2022/10/13 00:57:38 - mmengine - INFO - Epoch(train) [17][640/940] lr: 1.0000e-02 eta: 11:11:27 time: 0.4544 data_time: 0.0299 memory: 17006 grad_norm: 3.9157 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.9557 loss: 1.9557 2022/10/13 00:57:49 - mmengine - INFO - Epoch(train) [17][660/940] lr: 1.0000e-02 eta: 11:11:16 time: 0.5126 data_time: 0.0326 memory: 17006 grad_norm: 3.9496 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8640 loss: 1.8640 2022/10/13 00:58:00 - mmengine - INFO - Epoch(train) [17][680/940] lr: 1.0000e-02 eta: 11:11:10 time: 0.5534 data_time: 0.0308 memory: 17006 grad_norm: 3.9914 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.9592 loss: 1.9592 2022/10/13 00:58:09 - mmengine - INFO - Epoch(train) [17][700/940] lr: 1.0000e-02 eta: 11:10:54 time: 0.4573 data_time: 0.0330 memory: 17006 grad_norm: 3.9778 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8488 loss: 1.8488 2022/10/13 00:58:19 - mmengine - INFO - Epoch(train) [17][720/940] lr: 1.0000e-02 eta: 11:10:41 time: 0.4906 data_time: 0.0317 memory: 17006 grad_norm: 3.9190 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7505 loss: 1.7505 2022/10/13 00:58:29 - mmengine - INFO - Epoch(train) [17][740/940] lr: 1.0000e-02 eta: 11:10:32 time: 0.5182 data_time: 0.0357 memory: 17006 grad_norm: 3.9046 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8431 loss: 1.8431 2022/10/13 00:58:40 - mmengine - INFO - Epoch(train) [17][760/940] lr: 1.0000e-02 eta: 11:10:23 time: 0.5334 data_time: 0.0363 memory: 17006 grad_norm: 3.9356 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9760 loss: 1.9760 2022/10/13 00:58:50 - mmengine - INFO - Epoch(train) [17][780/940] lr: 1.0000e-02 eta: 11:10:13 time: 0.5199 data_time: 0.0296 memory: 17006 grad_norm: 3.8995 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7985 loss: 1.7985 2022/10/13 00:59:00 - mmengine - INFO - Epoch(train) [17][800/940] lr: 1.0000e-02 eta: 11:09:59 time: 0.4770 data_time: 0.0297 memory: 17006 grad_norm: 3.9202 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9582 loss: 1.9582 2022/10/13 00:59:10 - mmengine - INFO - Epoch(train) [17][820/940] lr: 1.0000e-02 eta: 11:09:51 time: 0.5369 data_time: 0.0355 memory: 17006 grad_norm: 3.9358 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.9471 loss: 1.9471 2022/10/13 00:59:20 - mmengine - INFO - Epoch(train) [17][840/940] lr: 1.0000e-02 eta: 11:09:37 time: 0.4744 data_time: 0.0329 memory: 17006 grad_norm: 4.0110 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8600 loss: 1.8600 2022/10/13 00:59:30 - mmengine - INFO - Epoch(train) [17][860/940] lr: 1.0000e-02 eta: 11:09:25 time: 0.4982 data_time: 0.0361 memory: 17006 grad_norm: 3.9140 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8877 loss: 1.8877 2022/10/13 00:59:39 - mmengine - INFO - Epoch(train) [17][880/940] lr: 1.0000e-02 eta: 11:09:10 time: 0.4591 data_time: 0.0269 memory: 17006 grad_norm: 3.8826 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.9458 loss: 1.9458 2022/10/13 00:59:50 - mmengine - INFO - Epoch(train) [17][900/940] lr: 1.0000e-02 eta: 11:09:01 time: 0.5292 data_time: 0.0312 memory: 17006 grad_norm: 3.9717 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.8335 loss: 1.8335 2022/10/13 01:00:00 - mmengine - INFO - Epoch(train) [17][920/940] lr: 1.0000e-02 eta: 11:08:53 time: 0.5378 data_time: 0.0380 memory: 17006 grad_norm: 3.9433 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 2.0493 loss: 2.0493 2022/10/13 01:00:09 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 01:00:09 - mmengine - INFO - Epoch(train) [17][940/940] lr: 1.0000e-02 eta: 11:08:34 time: 0.4319 data_time: 0.0299 memory: 17006 grad_norm: 4.1526 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.7373 loss: 1.7373 2022/10/13 01:00:22 - mmengine - INFO - Epoch(val) [17][20/78] eta: 0:00:36 time: 0.6299 data_time: 0.5356 memory: 3172 2022/10/13 01:00:30 - mmengine - INFO - Epoch(val) [17][40/78] eta: 0:00:16 time: 0.4313 data_time: 0.3388 memory: 3172 2022/10/13 01:00:42 - mmengine - INFO - Epoch(val) [17][60/78] eta: 0:00:10 time: 0.5759 data_time: 0.4847 memory: 3172 2022/10/13 01:00:51 - mmengine - INFO - Epoch(val) [17][78/78] acc/top1: 0.6069 acc/top5: 0.8327 acc/mean1: 0.6068 2022/10/13 01:01:05 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 01:01:05 - mmengine - INFO - Epoch(train) [18][20/940] lr: 1.0000e-02 eta: 11:08:39 time: 0.6621 data_time: 0.2785 memory: 17006 grad_norm: 3.8617 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9234 loss: 1.9234 2022/10/13 01:01:14 - mmengine - INFO - Epoch(train) [18][40/940] lr: 1.0000e-02 eta: 11:08:25 time: 0.4798 data_time: 0.0448 memory: 17006 grad_norm: 3.9821 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.8904 loss: 1.8904 2022/10/13 01:01:25 - mmengine - INFO - Epoch(train) [18][60/940] lr: 1.0000e-02 eta: 11:08:17 time: 0.5360 data_time: 0.1874 memory: 17006 grad_norm: 3.8522 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8840 loss: 1.8840 2022/10/13 01:01:35 - mmengine - INFO - Epoch(train) [18][80/940] lr: 1.0000e-02 eta: 11:08:04 time: 0.4875 data_time: 0.1248 memory: 17006 grad_norm: 3.9420 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7113 loss: 1.7113 2022/10/13 01:01:45 - mmengine - INFO - Epoch(train) [18][100/940] lr: 1.0000e-02 eta: 11:07:55 time: 0.5327 data_time: 0.1992 memory: 17006 grad_norm: 3.8924 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8187 loss: 1.8187 2022/10/13 01:01:55 - mmengine - INFO - Epoch(train) [18][120/940] lr: 1.0000e-02 eta: 11:07:43 time: 0.4880 data_time: 0.0972 memory: 17006 grad_norm: 3.9033 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.9518 loss: 1.9518 2022/10/13 01:02:06 - mmengine - INFO - Epoch(train) [18][140/940] lr: 1.0000e-02 eta: 11:07:35 time: 0.5391 data_time: 0.0505 memory: 17006 grad_norm: 3.8596 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.9685 loss: 1.9685 2022/10/13 01:02:17 - mmengine - INFO - Epoch(train) [18][160/940] lr: 1.0000e-02 eta: 11:07:26 time: 0.5309 data_time: 0.0304 memory: 17006 grad_norm: 3.9053 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8275 loss: 1.8275 2022/10/13 01:02:26 - mmengine - INFO - Epoch(train) [18][180/940] lr: 1.0000e-02 eta: 11:07:13 time: 0.4889 data_time: 0.0321 memory: 17006 grad_norm: 4.0397 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.9037 loss: 1.9037 2022/10/13 01:02:37 - mmengine - INFO - Epoch(train) [18][200/940] lr: 1.0000e-02 eta: 11:07:05 time: 0.5358 data_time: 0.0303 memory: 17006 grad_norm: 3.8793 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8417 loss: 1.8417 2022/10/13 01:02:47 - mmengine - INFO - Epoch(train) [18][220/940] lr: 1.0000e-02 eta: 11:06:54 time: 0.5029 data_time: 0.0336 memory: 17006 grad_norm: 3.9950 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.9612 loss: 1.9612 2022/10/13 01:02:56 - mmengine - INFO - Epoch(train) [18][240/940] lr: 1.0000e-02 eta: 11:06:38 time: 0.4624 data_time: 0.0252 memory: 17006 grad_norm: 3.9053 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7701 loss: 1.7701 2022/10/13 01:03:08 - mmengine - INFO - Epoch(train) [18][260/940] lr: 1.0000e-02 eta: 11:06:33 time: 0.5619 data_time: 0.0309 memory: 17006 grad_norm: 3.9164 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.9089 loss: 1.9089 2022/10/13 01:03:17 - mmengine - INFO - Epoch(train) [18][280/940] lr: 1.0000e-02 eta: 11:06:19 time: 0.4794 data_time: 0.0337 memory: 17006 grad_norm: 3.9059 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8482 loss: 1.8482 2022/10/13 01:03:28 - mmengine - INFO - Epoch(train) [18][300/940] lr: 1.0000e-02 eta: 11:06:11 time: 0.5426 data_time: 0.0364 memory: 17006 grad_norm: 3.9609 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8345 loss: 1.8345 2022/10/13 01:03:38 - mmengine - INFO - Epoch(train) [18][320/940] lr: 1.0000e-02 eta: 11:06:00 time: 0.5007 data_time: 0.0269 memory: 17006 grad_norm: 3.9544 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8730 loss: 1.8730 2022/10/13 01:03:48 - mmengine - INFO - Epoch(train) [18][340/940] lr: 1.0000e-02 eta: 11:05:50 time: 0.5178 data_time: 0.0289 memory: 17006 grad_norm: 3.8999 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 1.9411 loss: 1.9411 2022/10/13 01:03:58 - mmengine - INFO - Epoch(train) [18][360/940] lr: 1.0000e-02 eta: 11:05:36 time: 0.4776 data_time: 0.0338 memory: 17006 grad_norm: 3.9053 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.7585 loss: 1.7585 2022/10/13 01:04:09 - mmengine - INFO - Epoch(train) [18][380/940] lr: 1.0000e-02 eta: 11:05:28 time: 0.5365 data_time: 0.0272 memory: 17006 grad_norm: 3.9280 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7891 loss: 1.7891 2022/10/13 01:04:18 - mmengine - INFO - Epoch(train) [18][400/940] lr: 1.0000e-02 eta: 11:05:12 time: 0.4592 data_time: 0.0333 memory: 17006 grad_norm: 3.9068 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.8297 loss: 1.8297 2022/10/13 01:04:29 - mmengine - INFO - Epoch(train) [18][420/940] lr: 1.0000e-02 eta: 11:05:07 time: 0.5690 data_time: 0.0361 memory: 17006 grad_norm: 3.9334 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9557 loss: 1.9557 2022/10/13 01:04:38 - mmengine - INFO - Epoch(train) [18][440/940] lr: 1.0000e-02 eta: 11:04:49 time: 0.4313 data_time: 0.0339 memory: 17006 grad_norm: 3.9422 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7881 loss: 1.7881 2022/10/13 01:04:49 - mmengine - INFO - Epoch(train) [18][460/940] lr: 1.0000e-02 eta: 11:04:43 time: 0.5558 data_time: 0.0318 memory: 17006 grad_norm: 4.0504 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9236 loss: 1.9236 2022/10/13 01:04:58 - mmengine - INFO - Epoch(train) [18][480/940] lr: 1.0000e-02 eta: 11:04:27 time: 0.4535 data_time: 0.0287 memory: 17006 grad_norm: 3.9072 top1_acc: 0.4375 top5_acc: 0.8750 loss_cls: 1.6888 loss: 1.6888 2022/10/13 01:05:09 - mmengine - INFO - Epoch(train) [18][500/940] lr: 1.0000e-02 eta: 11:04:20 time: 0.5523 data_time: 0.0343 memory: 17006 grad_norm: 3.8422 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 2.0114 loss: 2.0114 2022/10/13 01:05:19 - mmengine - INFO - Epoch(train) [18][520/940] lr: 1.0000e-02 eta: 11:04:09 time: 0.5072 data_time: 0.0358 memory: 17006 grad_norm: 3.9002 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.7783 loss: 1.7783 2022/10/13 01:05:31 - mmengine - INFO - Epoch(train) [18][540/940] lr: 1.0000e-02 eta: 11:04:05 time: 0.5758 data_time: 0.0319 memory: 17006 grad_norm: 3.9391 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9947 loss: 1.9947 2022/10/13 01:05:40 - mmengine - INFO - Epoch(train) [18][560/940] lr: 1.0000e-02 eta: 11:03:49 time: 0.4586 data_time: 0.0361 memory: 17006 grad_norm: 3.9367 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9554 loss: 1.9554 2022/10/13 01:05:51 - mmengine - INFO - Epoch(train) [18][580/940] lr: 1.0000e-02 eta: 11:03:43 time: 0.5629 data_time: 0.0265 memory: 17006 grad_norm: 3.9039 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8509 loss: 1.8509 2022/10/13 01:06:01 - mmengine - INFO - Epoch(train) [18][600/940] lr: 1.0000e-02 eta: 11:03:30 time: 0.4753 data_time: 0.0286 memory: 17006 grad_norm: 3.9300 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.9961 loss: 1.9961 2022/10/13 01:06:12 - mmengine - INFO - Epoch(train) [18][620/940] lr: 1.0000e-02 eta: 11:03:22 time: 0.5420 data_time: 0.0347 memory: 17006 grad_norm: 3.9665 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.8931 loss: 1.8931 2022/10/13 01:06:21 - mmengine - INFO - Epoch(train) [18][640/940] lr: 1.0000e-02 eta: 11:03:09 time: 0.4869 data_time: 0.0332 memory: 17006 grad_norm: 3.9261 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.8525 loss: 1.8525 2022/10/13 01:06:33 - mmengine - INFO - Epoch(train) [18][660/940] lr: 1.0000e-02 eta: 11:03:03 time: 0.5570 data_time: 0.0357 memory: 17006 grad_norm: 3.9042 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8878 loss: 1.8878 2022/10/13 01:06:43 - mmengine - INFO - Epoch(train) [18][680/940] lr: 1.0000e-02 eta: 11:02:51 time: 0.5002 data_time: 0.0303 memory: 17006 grad_norm: 3.8751 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8216 loss: 1.8216 2022/10/13 01:06:53 - mmengine - INFO - Epoch(train) [18][700/940] lr: 1.0000e-02 eta: 11:02:42 time: 0.5214 data_time: 0.0296 memory: 17006 grad_norm: 3.8828 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 1.9041 loss: 1.9041 2022/10/13 01:07:02 - mmengine - INFO - Epoch(train) [18][720/940] lr: 1.0000e-02 eta: 11:02:25 time: 0.4501 data_time: 0.0296 memory: 17006 grad_norm: 3.9361 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9280 loss: 1.9280 2022/10/13 01:07:12 - mmengine - INFO - Epoch(train) [18][740/940] lr: 1.0000e-02 eta: 11:02:16 time: 0.5255 data_time: 0.0350 memory: 17006 grad_norm: 3.9259 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.8990 loss: 1.8990 2022/10/13 01:07:22 - mmengine - INFO - Epoch(train) [18][760/940] lr: 1.0000e-02 eta: 11:02:02 time: 0.4717 data_time: 0.0318 memory: 17006 grad_norm: 3.8978 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9700 loss: 1.9700 2022/10/13 01:07:32 - mmengine - INFO - Epoch(train) [18][780/940] lr: 1.0000e-02 eta: 11:01:52 time: 0.5149 data_time: 0.0314 memory: 17006 grad_norm: 3.8560 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9156 loss: 1.9156 2022/10/13 01:07:42 - mmengine - INFO - Epoch(train) [18][800/940] lr: 1.0000e-02 eta: 11:01:39 time: 0.4833 data_time: 0.0338 memory: 17006 grad_norm: 3.8988 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.8796 loss: 1.8796 2022/10/13 01:07:52 - mmengine - INFO - Epoch(train) [18][820/940] lr: 1.0000e-02 eta: 11:01:26 time: 0.4868 data_time: 0.0376 memory: 17006 grad_norm: 3.9275 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7654 loss: 1.7654 2022/10/13 01:08:03 - mmengine - INFO - Epoch(train) [18][840/940] lr: 1.0000e-02 eta: 11:01:18 time: 0.5465 data_time: 0.0307 memory: 17006 grad_norm: 3.8913 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.0087 loss: 2.0087 2022/10/13 01:08:13 - mmengine - INFO - Epoch(train) [18][860/940] lr: 1.0000e-02 eta: 11:01:07 time: 0.4996 data_time: 0.0386 memory: 17006 grad_norm: 3.9956 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7438 loss: 1.7438 2022/10/13 01:08:23 - mmengine - INFO - Epoch(train) [18][880/940] lr: 1.0000e-02 eta: 11:00:56 time: 0.5090 data_time: 0.0313 memory: 17006 grad_norm: 3.9632 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.9752 loss: 1.9752 2022/10/13 01:08:33 - mmengine - INFO - Epoch(train) [18][900/940] lr: 1.0000e-02 eta: 11:00:45 time: 0.5071 data_time: 0.0288 memory: 17006 grad_norm: 3.8925 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9152 loss: 1.9152 2022/10/13 01:08:42 - mmengine - INFO - Epoch(train) [18][920/940] lr: 1.0000e-02 eta: 11:00:32 time: 0.4810 data_time: 0.0277 memory: 17006 grad_norm: 3.9889 top1_acc: 0.6875 top5_acc: 0.7188 loss_cls: 1.9480 loss: 1.9480 2022/10/13 01:08:53 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 01:08:53 - mmengine - INFO - Epoch(train) [18][940/940] lr: 1.0000e-02 eta: 11:00:23 time: 0.5248 data_time: 0.0298 memory: 17006 grad_norm: 4.1476 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.8729 loss: 1.8729 2022/10/13 01:08:53 - mmengine - INFO - Saving checkpoint at 18 epochs 2022/10/13 01:09:06 - mmengine - INFO - Epoch(val) [18][20/78] eta: 0:00:36 time: 0.6235 data_time: 0.5323 memory: 3172 2022/10/13 01:09:15 - mmengine - INFO - Epoch(val) [18][40/78] eta: 0:00:16 time: 0.4304 data_time: 0.3406 memory: 3172 2022/10/13 01:09:27 - mmengine - INFO - Epoch(val) [18][60/78] eta: 0:00:10 time: 0.5874 data_time: 0.4972 memory: 3172 2022/10/13 01:09:36 - mmengine - INFO - Epoch(val) [18][78/78] acc/top1: 0.6142 acc/top5: 0.8357 acc/mean1: 0.6140 2022/10/13 01:09:36 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_16.pth is removed 2022/10/13 01:09:36 - mmengine - INFO - The best checkpoint with 0.6142 acc/top1 at 18 epoch is saved to best_acc/top1_epoch_18.pth. 2022/10/13 01:09:49 - mmengine - INFO - Epoch(train) [19][20/940] lr: 1.0000e-02 eta: 11:00:26 time: 0.6632 data_time: 0.3380 memory: 17006 grad_norm: 3.8518 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8029 loss: 1.8029 2022/10/13 01:10:00 - mmengine - INFO - Epoch(train) [19][40/940] lr: 1.0000e-02 eta: 11:00:15 time: 0.5096 data_time: 0.1132 memory: 17006 grad_norm: 3.9193 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9505 loss: 1.9505 2022/10/13 01:10:11 - mmengine - INFO - Epoch(train) [19][60/940] lr: 1.0000e-02 eta: 11:00:10 time: 0.5692 data_time: 0.0292 memory: 17006 grad_norm: 3.8198 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9106 loss: 1.9106 2022/10/13 01:10:20 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 01:10:20 - mmengine - INFO - Epoch(train) [19][80/940] lr: 1.0000e-02 eta: 10:59:55 time: 0.4657 data_time: 0.0295 memory: 17006 grad_norm: 3.9808 top1_acc: 0.2812 top5_acc: 0.5625 loss_cls: 2.0232 loss: 2.0232 2022/10/13 01:10:32 - mmengine - INFO - Epoch(train) [19][100/940] lr: 1.0000e-02 eta: 10:59:49 time: 0.5573 data_time: 0.0316 memory: 17006 grad_norm: 3.9527 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8793 loss: 1.8793 2022/10/13 01:10:41 - mmengine - INFO - Epoch(train) [19][120/940] lr: 1.0000e-02 eta: 10:59:37 time: 0.4995 data_time: 0.0313 memory: 17006 grad_norm: 3.9404 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 2.0286 loss: 2.0286 2022/10/13 01:10:52 - mmengine - INFO - Epoch(train) [19][140/940] lr: 1.0000e-02 eta: 10:59:27 time: 0.5169 data_time: 0.0336 memory: 17006 grad_norm: 3.8834 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 1.8147 loss: 1.8147 2022/10/13 01:11:01 - mmengine - INFO - Epoch(train) [19][160/940] lr: 1.0000e-02 eta: 10:59:14 time: 0.4824 data_time: 0.0290 memory: 17006 grad_norm: 3.9372 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8820 loss: 1.8820 2022/10/13 01:11:13 - mmengine - INFO - Epoch(train) [19][180/940] lr: 1.0000e-02 eta: 10:59:08 time: 0.5575 data_time: 0.0356 memory: 17006 grad_norm: 3.9276 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8174 loss: 1.8174 2022/10/13 01:11:22 - mmengine - INFO - Epoch(train) [19][200/940] lr: 1.0000e-02 eta: 10:58:53 time: 0.4618 data_time: 0.0353 memory: 17006 grad_norm: 3.9762 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8648 loss: 1.8648 2022/10/13 01:11:32 - mmengine - INFO - Epoch(train) [19][220/940] lr: 1.0000e-02 eta: 10:58:42 time: 0.5129 data_time: 0.0326 memory: 17006 grad_norm: 3.9155 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9398 loss: 1.9398 2022/10/13 01:11:41 - mmengine - INFO - Epoch(train) [19][240/940] lr: 1.0000e-02 eta: 10:58:27 time: 0.4646 data_time: 0.0307 memory: 17006 grad_norm: 3.9639 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.9318 loss: 1.9318 2022/10/13 01:11:51 - mmengine - INFO - Epoch(train) [19][260/940] lr: 1.0000e-02 eta: 10:58:16 time: 0.4981 data_time: 0.0330 memory: 17006 grad_norm: 3.9434 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.8649 loss: 1.8649 2022/10/13 01:12:01 - mmengine - INFO - Epoch(train) [19][280/940] lr: 1.0000e-02 eta: 10:58:03 time: 0.4859 data_time: 0.0389 memory: 17006 grad_norm: 3.9318 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9284 loss: 1.9284 2022/10/13 01:12:12 - mmengine - INFO - Epoch(train) [19][300/940] lr: 1.0000e-02 eta: 10:57:56 time: 0.5494 data_time: 0.0342 memory: 17006 grad_norm: 3.9869 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7165 loss: 1.7165 2022/10/13 01:12:22 - mmengine - INFO - Epoch(train) [19][320/940] lr: 1.0000e-02 eta: 10:57:43 time: 0.4913 data_time: 0.0319 memory: 17006 grad_norm: 3.9368 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8326 loss: 1.8326 2022/10/13 01:12:33 - mmengine - INFO - Epoch(train) [19][340/940] lr: 1.0000e-02 eta: 10:57:35 time: 0.5317 data_time: 0.0342 memory: 17006 grad_norm: 3.9437 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 2.0076 loss: 2.0076 2022/10/13 01:12:42 - mmengine - INFO - Epoch(train) [19][360/940] lr: 1.0000e-02 eta: 10:57:21 time: 0.4703 data_time: 0.0291 memory: 17006 grad_norm: 3.9312 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7626 loss: 1.7626 2022/10/13 01:12:53 - mmengine - INFO - Epoch(train) [19][380/940] lr: 1.0000e-02 eta: 10:57:12 time: 0.5356 data_time: 0.0299 memory: 17006 grad_norm: 4.0044 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.7681 loss: 1.7681 2022/10/13 01:13:02 - mmengine - INFO - Epoch(train) [19][400/940] lr: 1.0000e-02 eta: 10:56:59 time: 0.4819 data_time: 0.0385 memory: 17006 grad_norm: 3.9236 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.9070 loss: 1.9070 2022/10/13 01:13:13 - mmengine - INFO - Epoch(train) [19][420/940] lr: 1.0000e-02 eta: 10:56:49 time: 0.5224 data_time: 0.0274 memory: 17006 grad_norm: 3.9422 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9967 loss: 1.9967 2022/10/13 01:13:22 - mmengine - INFO - Epoch(train) [19][440/940] lr: 1.0000e-02 eta: 10:56:36 time: 0.4824 data_time: 0.0313 memory: 17006 grad_norm: 3.9351 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8883 loss: 1.8883 2022/10/13 01:13:33 - mmengine - INFO - Epoch(train) [19][460/940] lr: 1.0000e-02 eta: 10:56:27 time: 0.5281 data_time: 0.0321 memory: 17006 grad_norm: 3.9318 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 2.0070 loss: 2.0070 2022/10/13 01:13:43 - mmengine - INFO - Epoch(train) [19][480/940] lr: 1.0000e-02 eta: 10:56:16 time: 0.5040 data_time: 0.0396 memory: 17006 grad_norm: 3.9552 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.8541 loss: 1.8541 2022/10/13 01:13:54 - mmengine - INFO - Epoch(train) [19][500/940] lr: 1.0000e-02 eta: 10:56:08 time: 0.5391 data_time: 0.0283 memory: 17006 grad_norm: 3.9316 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9408 loss: 1.9408 2022/10/13 01:14:03 - mmengine - INFO - Epoch(train) [19][520/940] lr: 1.0000e-02 eta: 10:55:53 time: 0.4604 data_time: 0.0309 memory: 17006 grad_norm: 3.9539 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.9506 loss: 1.9506 2022/10/13 01:14:14 - mmengine - INFO - Epoch(train) [19][540/940] lr: 1.0000e-02 eta: 10:55:44 time: 0.5232 data_time: 0.0313 memory: 17006 grad_norm: 3.9864 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.9221 loss: 1.9221 2022/10/13 01:14:23 - mmengine - INFO - Epoch(train) [19][560/940] lr: 1.0000e-02 eta: 10:55:30 time: 0.4781 data_time: 0.0368 memory: 17006 grad_norm: 3.9840 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7727 loss: 1.7727 2022/10/13 01:14:34 - mmengine - INFO - Epoch(train) [19][580/940] lr: 1.0000e-02 eta: 10:55:24 time: 0.5616 data_time: 0.0309 memory: 17006 grad_norm: 3.9157 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.0366 loss: 2.0366 2022/10/13 01:14:44 - mmengine - INFO - Epoch(train) [19][600/940] lr: 1.0000e-02 eta: 10:55:10 time: 0.4680 data_time: 0.0318 memory: 17006 grad_norm: 3.9536 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8993 loss: 1.8993 2022/10/13 01:14:54 - mmengine - INFO - Epoch(train) [19][620/940] lr: 1.0000e-02 eta: 10:55:00 time: 0.5170 data_time: 0.0421 memory: 17006 grad_norm: 3.9131 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8378 loss: 1.8378 2022/10/13 01:15:04 - mmengine - INFO - Epoch(train) [19][640/940] lr: 1.0000e-02 eta: 10:54:46 time: 0.4787 data_time: 0.0355 memory: 17006 grad_norm: 3.8181 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8786 loss: 1.8786 2022/10/13 01:15:15 - mmengine - INFO - Epoch(train) [19][660/940] lr: 1.0000e-02 eta: 10:54:42 time: 0.5765 data_time: 0.0445 memory: 17006 grad_norm: 3.9755 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.8547 loss: 1.8547 2022/10/13 01:15:24 - mmengine - INFO - Epoch(train) [19][680/940] lr: 1.0000e-02 eta: 10:54:27 time: 0.4652 data_time: 0.0360 memory: 17006 grad_norm: 3.9573 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 2.0089 loss: 2.0089 2022/10/13 01:15:35 - mmengine - INFO - Epoch(train) [19][700/940] lr: 1.0000e-02 eta: 10:54:17 time: 0.5174 data_time: 0.0326 memory: 17006 grad_norm: 3.9184 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9074 loss: 1.9074 2022/10/13 01:15:44 - mmengine - INFO - Epoch(train) [19][720/940] lr: 1.0000e-02 eta: 10:54:03 time: 0.4683 data_time: 0.0342 memory: 17006 grad_norm: 3.9747 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7331 loss: 1.7331 2022/10/13 01:15:55 - mmengine - INFO - Epoch(train) [19][740/940] lr: 1.0000e-02 eta: 10:53:56 time: 0.5558 data_time: 0.0371 memory: 17006 grad_norm: 3.9202 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.8765 loss: 1.8765 2022/10/13 01:16:05 - mmengine - INFO - Epoch(train) [19][760/940] lr: 1.0000e-02 eta: 10:53:42 time: 0.4657 data_time: 0.0304 memory: 17006 grad_norm: 3.9299 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.9000 loss: 1.9000 2022/10/13 01:16:16 - mmengine - INFO - Epoch(train) [19][780/940] lr: 1.0000e-02 eta: 10:53:36 time: 0.5720 data_time: 0.0344 memory: 17006 grad_norm: 3.9370 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.9044 loss: 1.9044 2022/10/13 01:16:25 - mmengine - INFO - Epoch(train) [19][800/940] lr: 1.0000e-02 eta: 10:53:22 time: 0.4615 data_time: 0.0311 memory: 17006 grad_norm: 3.9198 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.8351 loss: 1.8351 2022/10/13 01:16:36 - mmengine - INFO - Epoch(train) [19][820/940] lr: 1.0000e-02 eta: 10:53:15 time: 0.5579 data_time: 0.0305 memory: 17006 grad_norm: 3.9426 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7716 loss: 1.7716 2022/10/13 01:16:46 - mmengine - INFO - Epoch(train) [19][840/940] lr: 1.0000e-02 eta: 10:53:04 time: 0.5001 data_time: 0.0401 memory: 17006 grad_norm: 3.9729 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8160 loss: 1.8160 2022/10/13 01:16:57 - mmengine - INFO - Epoch(train) [19][860/940] lr: 1.0000e-02 eta: 10:52:55 time: 0.5376 data_time: 0.0392 memory: 17006 grad_norm: 3.9242 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.9159 loss: 1.9159 2022/10/13 01:17:07 - mmengine - INFO - Epoch(train) [19][880/940] lr: 1.0000e-02 eta: 10:52:42 time: 0.4763 data_time: 0.0309 memory: 17006 grad_norm: 3.9193 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.9308 loss: 1.9308 2022/10/13 01:17:18 - mmengine - INFO - Epoch(train) [19][900/940] lr: 1.0000e-02 eta: 10:52:35 time: 0.5589 data_time: 0.0431 memory: 17006 grad_norm: 3.9428 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.9400 loss: 1.9400 2022/10/13 01:17:27 - mmengine - INFO - Epoch(train) [19][920/940] lr: 1.0000e-02 eta: 10:52:18 time: 0.4333 data_time: 0.0318 memory: 17006 grad_norm: 3.9285 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.8334 loss: 1.8334 2022/10/13 01:17:36 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 01:17:36 - mmengine - INFO - Epoch(train) [19][940/940] lr: 1.0000e-02 eta: 10:52:03 time: 0.4588 data_time: 0.0243 memory: 17006 grad_norm: 4.2085 top1_acc: 0.5714 top5_acc: 1.0000 loss_cls: 1.7807 loss: 1.7807 2022/10/13 01:17:48 - mmengine - INFO - Epoch(val) [19][20/78] eta: 0:00:36 time: 0.6238 data_time: 0.5296 memory: 3172 2022/10/13 01:17:57 - mmengine - INFO - Epoch(val) [19][40/78] eta: 0:00:16 time: 0.4275 data_time: 0.3358 memory: 3172 2022/10/13 01:18:08 - mmengine - INFO - Epoch(val) [19][60/78] eta: 0:00:10 time: 0.5779 data_time: 0.4851 memory: 3172 2022/10/13 01:18:18 - mmengine - INFO - Epoch(val) [19][78/78] acc/top1: 0.6064 acc/top5: 0.8298 acc/mean1: 0.6062 2022/10/13 01:18:33 - mmengine - INFO - Epoch(train) [20][20/940] lr: 1.0000e-02 eta: 10:52:10 time: 0.7117 data_time: 0.2746 memory: 17006 grad_norm: 3.9585 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8850 loss: 1.8850 2022/10/13 01:18:42 - mmengine - INFO - Epoch(train) [20][40/940] lr: 1.0000e-02 eta: 10:51:57 time: 0.4812 data_time: 0.0280 memory: 17006 grad_norm: 3.9795 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8537 loss: 1.8537 2022/10/13 01:18:54 - mmengine - INFO - Epoch(train) [20][60/940] lr: 1.0000e-02 eta: 10:51:51 time: 0.5665 data_time: 0.0320 memory: 17006 grad_norm: 3.9529 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.9005 loss: 1.9005 2022/10/13 01:19:03 - mmengine - INFO - Epoch(train) [20][80/940] lr: 1.0000e-02 eta: 10:51:36 time: 0.4540 data_time: 0.0259 memory: 17006 grad_norm: 4.0294 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.9213 loss: 1.9213 2022/10/13 01:19:13 - mmengine - INFO - Epoch(train) [20][100/940] lr: 1.0000e-02 eta: 10:51:25 time: 0.5101 data_time: 0.0284 memory: 17006 grad_norm: 3.9157 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.8154 loss: 1.8154 2022/10/13 01:19:22 - mmengine - INFO - Epoch(train) [20][120/940] lr: 1.0000e-02 eta: 10:51:12 time: 0.4788 data_time: 0.0417 memory: 17006 grad_norm: 3.9649 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8326 loss: 1.8326 2022/10/13 01:19:33 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 01:19:33 - mmengine - INFO - Epoch(train) [20][140/940] lr: 1.0000e-02 eta: 10:51:04 time: 0.5420 data_time: 0.0317 memory: 17006 grad_norm: 3.8759 top1_acc: 0.3750 top5_acc: 0.7812 loss_cls: 1.8494 loss: 1.8494 2022/10/13 01:19:43 - mmengine - INFO - Epoch(train) [20][160/940] lr: 1.0000e-02 eta: 10:50:51 time: 0.4873 data_time: 0.0328 memory: 17006 grad_norm: 3.9202 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 2.0589 loss: 2.0589 2022/10/13 01:19:54 - mmengine - INFO - Epoch(train) [20][180/940] lr: 1.0000e-02 eta: 10:50:45 time: 0.5589 data_time: 0.0277 memory: 17006 grad_norm: 3.9534 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.7584 loss: 1.7584 2022/10/13 01:20:04 - mmengine - INFO - Epoch(train) [20][200/940] lr: 1.0000e-02 eta: 10:50:33 time: 0.5008 data_time: 0.0405 memory: 17006 grad_norm: 3.9386 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8535 loss: 1.8535 2022/10/13 01:20:16 - mmengine - INFO - Epoch(train) [20][220/940] lr: 1.0000e-02 eta: 10:50:29 time: 0.5791 data_time: 0.0372 memory: 17006 grad_norm: 4.0063 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.8783 loss: 1.8783 2022/10/13 01:20:26 - mmengine - INFO - Epoch(train) [20][240/940] lr: 1.0000e-02 eta: 10:50:16 time: 0.4852 data_time: 0.0301 memory: 17006 grad_norm: 3.9262 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.9402 loss: 1.9402 2022/10/13 01:20:36 - mmengine - INFO - Epoch(train) [20][260/940] lr: 1.0000e-02 eta: 10:50:07 time: 0.5315 data_time: 0.0291 memory: 17006 grad_norm: 4.0200 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.7078 loss: 1.7078 2022/10/13 01:20:45 - mmengine - INFO - Epoch(train) [20][280/940] lr: 1.0000e-02 eta: 10:49:50 time: 0.4352 data_time: 0.0387 memory: 17006 grad_norm: 3.9249 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7815 loss: 1.7815 2022/10/13 01:20:55 - mmengine - INFO - Epoch(train) [20][300/940] lr: 1.0000e-02 eta: 10:49:41 time: 0.5287 data_time: 0.0347 memory: 17006 grad_norm: 3.9024 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9160 loss: 1.9160 2022/10/13 01:21:05 - mmengine - INFO - Epoch(train) [20][320/940] lr: 1.0000e-02 eta: 10:49:27 time: 0.4703 data_time: 0.0366 memory: 17006 grad_norm: 4.0625 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.7740 loss: 1.7740 2022/10/13 01:21:15 - mmengine - INFO - Epoch(train) [20][340/940] lr: 1.0000e-02 eta: 10:49:19 time: 0.5330 data_time: 0.0349 memory: 17006 grad_norm: 3.9327 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8162 loss: 1.8162 2022/10/13 01:21:25 - mmengine - INFO - Epoch(train) [20][360/940] lr: 1.0000e-02 eta: 10:49:06 time: 0.4867 data_time: 0.0365 memory: 17006 grad_norm: 3.9035 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.8593 loss: 1.8593 2022/10/13 01:21:35 - mmengine - INFO - Epoch(train) [20][380/940] lr: 1.0000e-02 eta: 10:48:55 time: 0.4999 data_time: 0.0312 memory: 17006 grad_norm: 3.9663 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.8014 loss: 1.8014 2022/10/13 01:21:44 - mmengine - INFO - Epoch(train) [20][400/940] lr: 1.0000e-02 eta: 10:48:39 time: 0.4555 data_time: 0.0402 memory: 17006 grad_norm: 3.9776 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.8479 loss: 1.8479 2022/10/13 01:21:55 - mmengine - INFO - Epoch(train) [20][420/940] lr: 1.0000e-02 eta: 10:48:32 time: 0.5434 data_time: 0.0370 memory: 17006 grad_norm: 3.9356 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7773 loss: 1.7773 2022/10/13 01:22:05 - mmengine - INFO - Epoch(train) [20][440/940] lr: 1.0000e-02 eta: 10:48:21 time: 0.5074 data_time: 0.0284 memory: 17006 grad_norm: 3.9394 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8002 loss: 1.8002 2022/10/13 01:22:15 - mmengine - INFO - Epoch(train) [20][460/940] lr: 1.0000e-02 eta: 10:48:09 time: 0.5014 data_time: 0.0339 memory: 17006 grad_norm: 4.0255 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 2.0248 loss: 2.0248 2022/10/13 01:22:26 - mmengine - INFO - Epoch(train) [20][480/940] lr: 1.0000e-02 eta: 10:48:00 time: 0.5217 data_time: 0.0364 memory: 17006 grad_norm: 3.9871 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8242 loss: 1.8242 2022/10/13 01:22:36 - mmengine - INFO - Epoch(train) [20][500/940] lr: 1.0000e-02 eta: 10:47:49 time: 0.5129 data_time: 0.0364 memory: 17006 grad_norm: 3.8720 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7730 loss: 1.7730 2022/10/13 01:22:45 - mmengine - INFO - Epoch(train) [20][520/940] lr: 1.0000e-02 eta: 10:47:36 time: 0.4709 data_time: 0.0333 memory: 17006 grad_norm: 4.0261 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 2.1723 loss: 2.1723 2022/10/13 01:22:57 - mmengine - INFO - Epoch(train) [20][540/940] lr: 1.0000e-02 eta: 10:47:28 time: 0.5512 data_time: 0.0408 memory: 17006 grad_norm: 3.9401 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 1.7593 loss: 1.7593 2022/10/13 01:23:06 - mmengine - INFO - Epoch(train) [20][560/940] lr: 1.0000e-02 eta: 10:47:14 time: 0.4584 data_time: 0.0302 memory: 17006 grad_norm: 3.9960 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.8515 loss: 1.8515 2022/10/13 01:23:16 - mmengine - INFO - Epoch(train) [20][580/940] lr: 1.0000e-02 eta: 10:47:05 time: 0.5309 data_time: 0.0382 memory: 17006 grad_norm: 3.8917 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8907 loss: 1.8907 2022/10/13 01:23:27 - mmengine - INFO - Epoch(train) [20][600/940] lr: 1.0000e-02 eta: 10:46:56 time: 0.5275 data_time: 0.0241 memory: 17006 grad_norm: 4.0543 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9022 loss: 1.9022 2022/10/13 01:23:37 - mmengine - INFO - Epoch(train) [20][620/940] lr: 1.0000e-02 eta: 10:46:46 time: 0.5253 data_time: 0.0348 memory: 17006 grad_norm: 3.9373 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.7894 loss: 1.7894 2022/10/13 01:23:48 - mmengine - INFO - Epoch(train) [20][640/940] lr: 1.0000e-02 eta: 10:46:38 time: 0.5397 data_time: 0.0270 memory: 17006 grad_norm: 3.9808 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8420 loss: 1.8420 2022/10/13 01:23:58 - mmengine - INFO - Epoch(train) [20][660/940] lr: 1.0000e-02 eta: 10:46:27 time: 0.5064 data_time: 0.0293 memory: 17006 grad_norm: 3.9485 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7732 loss: 1.7732 2022/10/13 01:24:08 - mmengine - INFO - Epoch(train) [20][680/940] lr: 1.0000e-02 eta: 10:46:16 time: 0.5074 data_time: 0.0324 memory: 17006 grad_norm: 3.9507 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7707 loss: 1.7707 2022/10/13 01:24:18 - mmengine - INFO - Epoch(train) [20][700/940] lr: 1.0000e-02 eta: 10:46:03 time: 0.4777 data_time: 0.0297 memory: 17006 grad_norm: 4.0084 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.9583 loss: 1.9583 2022/10/13 01:24:29 - mmengine - INFO - Epoch(train) [20][720/940] lr: 1.0000e-02 eta: 10:45:55 time: 0.5341 data_time: 0.0290 memory: 17006 grad_norm: 3.8608 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7008 loss: 1.7008 2022/10/13 01:24:38 - mmengine - INFO - Epoch(train) [20][740/940] lr: 1.0000e-02 eta: 10:45:42 time: 0.4903 data_time: 0.0294 memory: 17006 grad_norm: 3.9944 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.8337 loss: 1.8337 2022/10/13 01:24:50 - mmengine - INFO - Epoch(train) [20][760/940] lr: 1.0000e-02 eta: 10:45:37 time: 0.5697 data_time: 0.0294 memory: 17006 grad_norm: 3.9907 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9109 loss: 1.9109 2022/10/13 01:24:59 - mmengine - INFO - Epoch(train) [20][780/940] lr: 1.0000e-02 eta: 10:45:20 time: 0.4345 data_time: 0.0295 memory: 17006 grad_norm: 3.9710 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8842 loss: 1.8842 2022/10/13 01:25:10 - mmengine - INFO - Epoch(train) [20][800/940] lr: 1.0000e-02 eta: 10:45:15 time: 0.5841 data_time: 0.0378 memory: 17006 grad_norm: 4.0205 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.8496 loss: 1.8496 2022/10/13 01:25:19 - mmengine - INFO - Epoch(train) [20][820/940] lr: 1.0000e-02 eta: 10:44:59 time: 0.4441 data_time: 0.0317 memory: 17006 grad_norm: 3.9699 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.8729 loss: 1.8729 2022/10/13 01:25:29 - mmengine - INFO - Epoch(train) [20][840/940] lr: 1.0000e-02 eta: 10:44:48 time: 0.5027 data_time: 0.0299 memory: 17006 grad_norm: 3.9800 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.9886 loss: 1.9886 2022/10/13 01:25:39 - mmengine - INFO - Epoch(train) [20][860/940] lr: 1.0000e-02 eta: 10:44:36 time: 0.4950 data_time: 0.0347 memory: 17006 grad_norm: 3.9313 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8361 loss: 1.8361 2022/10/13 01:25:49 - mmengine - INFO - Epoch(train) [20][880/940] lr: 1.0000e-02 eta: 10:44:26 time: 0.5179 data_time: 0.0327 memory: 17006 grad_norm: 3.9094 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9456 loss: 1.9456 2022/10/13 01:25:59 - mmengine - INFO - Epoch(train) [20][900/940] lr: 1.0000e-02 eta: 10:44:12 time: 0.4612 data_time: 0.0384 memory: 17006 grad_norm: 4.0110 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7841 loss: 1.7841 2022/10/13 01:26:09 - mmengine - INFO - Epoch(train) [20][920/940] lr: 1.0000e-02 eta: 10:44:01 time: 0.5055 data_time: 0.0551 memory: 17006 grad_norm: 3.9916 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8663 loss: 1.8663 2022/10/13 01:26:18 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 01:26:18 - mmengine - INFO - Epoch(train) [20][940/940] lr: 1.0000e-02 eta: 10:43:45 time: 0.4436 data_time: 0.0323 memory: 17006 grad_norm: 4.1973 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 2.1247 loss: 2.1247 2022/10/13 01:26:30 - mmengine - INFO - Epoch(val) [20][20/78] eta: 0:00:36 time: 0.6332 data_time: 0.5396 memory: 3172 2022/10/13 01:26:39 - mmengine - INFO - Epoch(val) [20][40/78] eta: 0:00:16 time: 0.4265 data_time: 0.3359 memory: 3172 2022/10/13 01:26:50 - mmengine - INFO - Epoch(val) [20][60/78] eta: 0:00:10 time: 0.5754 data_time: 0.4824 memory: 3172 2022/10/13 01:27:00 - mmengine - INFO - Epoch(val) [20][78/78] acc/top1: 0.6161 acc/top5: 0.8407 acc/mean1: 0.6160 2022/10/13 01:27:00 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_18.pth is removed 2022/10/13 01:27:01 - mmengine - INFO - The best checkpoint with 0.6161 acc/top1 at 20 epoch is saved to best_acc/top1_epoch_20.pth. 2022/10/13 01:27:14 - mmengine - INFO - Epoch(train) [21][20/940] lr: 1.0000e-02 eta: 10:43:47 time: 0.6645 data_time: 0.3401 memory: 17006 grad_norm: 3.9814 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7392 loss: 1.7392 2022/10/13 01:27:24 - mmengine - INFO - Epoch(train) [21][40/940] lr: 1.0000e-02 eta: 10:43:36 time: 0.5062 data_time: 0.0981 memory: 17006 grad_norm: 3.8705 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.9486 loss: 1.9486 2022/10/13 01:27:35 - mmengine - INFO - Epoch(train) [21][60/940] lr: 1.0000e-02 eta: 10:43:26 time: 0.5220 data_time: 0.0554 memory: 17006 grad_norm: 3.9054 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.9231 loss: 1.9231 2022/10/13 01:27:44 - mmengine - INFO - Epoch(train) [21][80/940] lr: 1.0000e-02 eta: 10:43:13 time: 0.4790 data_time: 0.1042 memory: 17006 grad_norm: 3.8898 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.8171 loss: 1.8171 2022/10/13 01:27:55 - mmengine - INFO - Epoch(train) [21][100/940] lr: 1.0000e-02 eta: 10:43:04 time: 0.5214 data_time: 0.1299 memory: 17006 grad_norm: 3.9919 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.9259 loss: 1.9259 2022/10/13 01:28:05 - mmengine - INFO - Epoch(train) [21][120/940] lr: 1.0000e-02 eta: 10:42:52 time: 0.4962 data_time: 0.0405 memory: 17006 grad_norm: 3.9956 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8203 loss: 1.8203 2022/10/13 01:28:15 - mmengine - INFO - Epoch(train) [21][140/940] lr: 1.0000e-02 eta: 10:42:43 time: 0.5294 data_time: 0.0329 memory: 17006 grad_norm: 3.9996 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.7928 loss: 1.7928 2022/10/13 01:28:25 - mmengine - INFO - Epoch(train) [21][160/940] lr: 1.0000e-02 eta: 10:42:30 time: 0.4794 data_time: 0.0264 memory: 17006 grad_norm: 4.0350 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7949 loss: 1.7949 2022/10/13 01:28:36 - mmengine - INFO - Epoch(train) [21][180/940] lr: 1.0000e-02 eta: 10:42:23 time: 0.5496 data_time: 0.0320 memory: 17006 grad_norm: 3.9747 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8691 loss: 1.8691 2022/10/13 01:28:45 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 01:28:45 - mmengine - INFO - Epoch(train) [21][200/940] lr: 1.0000e-02 eta: 10:42:09 time: 0.4761 data_time: 0.0302 memory: 17006 grad_norm: 4.0181 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7521 loss: 1.7521 2022/10/13 01:28:56 - mmengine - INFO - Epoch(train) [21][220/940] lr: 1.0000e-02 eta: 10:42:01 time: 0.5410 data_time: 0.0305 memory: 17006 grad_norm: 3.9670 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.8215 loss: 1.8215 2022/10/13 01:29:06 - mmengine - INFO - Epoch(train) [21][240/940] lr: 1.0000e-02 eta: 10:41:49 time: 0.4903 data_time: 0.0378 memory: 17006 grad_norm: 3.9079 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.7132 loss: 1.7132 2022/10/13 01:29:16 - mmengine - INFO - Epoch(train) [21][260/940] lr: 1.0000e-02 eta: 10:41:39 time: 0.5127 data_time: 0.0334 memory: 17006 grad_norm: 3.9363 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 1.8201 loss: 1.8201 2022/10/13 01:29:26 - mmengine - INFO - Epoch(train) [21][280/940] lr: 1.0000e-02 eta: 10:41:27 time: 0.4953 data_time: 0.0320 memory: 17006 grad_norm: 3.9325 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 1.8043 loss: 1.8043 2022/10/13 01:29:37 - mmengine - INFO - Epoch(train) [21][300/940] lr: 1.0000e-02 eta: 10:41:19 time: 0.5389 data_time: 0.0379 memory: 17006 grad_norm: 3.9335 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8029 loss: 1.8029 2022/10/13 01:29:47 - mmengine - INFO - Epoch(train) [21][320/940] lr: 1.0000e-02 eta: 10:41:06 time: 0.4844 data_time: 0.0339 memory: 17006 grad_norm: 4.0530 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.9056 loss: 1.9056 2022/10/13 01:29:58 - mmengine - INFO - Epoch(train) [21][340/940] lr: 1.0000e-02 eta: 10:40:59 time: 0.5543 data_time: 0.0375 memory: 17006 grad_norm: 3.9790 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7823 loss: 1.7823 2022/10/13 01:30:07 - mmengine - INFO - Epoch(train) [21][360/940] lr: 1.0000e-02 eta: 10:40:43 time: 0.4458 data_time: 0.0333 memory: 17006 grad_norm: 3.9493 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8639 loss: 1.8639 2022/10/13 01:30:17 - mmengine - INFO - Epoch(train) [21][380/940] lr: 1.0000e-02 eta: 10:40:35 time: 0.5385 data_time: 0.0341 memory: 17006 grad_norm: 3.9937 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 2.1189 loss: 2.1189 2022/10/13 01:30:26 - mmengine - INFO - Epoch(train) [21][400/940] lr: 1.0000e-02 eta: 10:40:20 time: 0.4568 data_time: 0.0261 memory: 17006 grad_norm: 3.9198 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7634 loss: 1.7634 2022/10/13 01:30:38 - mmengine - INFO - Epoch(train) [21][420/940] lr: 1.0000e-02 eta: 10:40:14 time: 0.5657 data_time: 0.0316 memory: 17006 grad_norm: 3.9959 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.9108 loss: 1.9108 2022/10/13 01:30:47 - mmengine - INFO - Epoch(train) [21][440/940] lr: 1.0000e-02 eta: 10:39:59 time: 0.4560 data_time: 0.0249 memory: 17006 grad_norm: 3.9532 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.8956 loss: 1.8956 2022/10/13 01:30:57 - mmengine - INFO - Epoch(train) [21][460/940] lr: 1.0000e-02 eta: 10:39:50 time: 0.5206 data_time: 0.0317 memory: 17006 grad_norm: 3.9572 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.8153 loss: 1.8153 2022/10/13 01:31:08 - mmengine - INFO - Epoch(train) [21][480/940] lr: 1.0000e-02 eta: 10:39:41 time: 0.5378 data_time: 0.0356 memory: 17006 grad_norm: 3.9653 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.9489 loss: 1.9489 2022/10/13 01:31:19 - mmengine - INFO - Epoch(train) [21][500/940] lr: 1.0000e-02 eta: 10:39:34 time: 0.5511 data_time: 0.0342 memory: 17006 grad_norm: 3.8905 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8573 loss: 1.8573 2022/10/13 01:31:29 - mmengine - INFO - Epoch(train) [21][520/940] lr: 1.0000e-02 eta: 10:39:22 time: 0.4880 data_time: 0.0274 memory: 17006 grad_norm: 4.0619 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.8715 loss: 1.8715 2022/10/13 01:31:40 - mmengine - INFO - Epoch(train) [21][540/940] lr: 1.0000e-02 eta: 10:39:14 time: 0.5408 data_time: 0.0371 memory: 17006 grad_norm: 4.0177 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.9486 loss: 1.9486 2022/10/13 01:31:48 - mmengine - INFO - Epoch(train) [21][560/940] lr: 1.0000e-02 eta: 10:38:57 time: 0.4314 data_time: 0.0387 memory: 17006 grad_norm: 4.0677 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7576 loss: 1.7576 2022/10/13 01:31:59 - mmengine - INFO - Epoch(train) [21][580/940] lr: 1.0000e-02 eta: 10:38:47 time: 0.5224 data_time: 0.0266 memory: 17006 grad_norm: 4.0375 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8776 loss: 1.8776 2022/10/13 01:32:09 - mmengine - INFO - Epoch(train) [21][600/940] lr: 1.0000e-02 eta: 10:38:36 time: 0.4966 data_time: 0.0354 memory: 17006 grad_norm: 3.9682 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.9266 loss: 1.9266 2022/10/13 01:32:19 - mmengine - INFO - Epoch(train) [21][620/940] lr: 1.0000e-02 eta: 10:38:25 time: 0.5072 data_time: 0.0309 memory: 17006 grad_norm: 3.9829 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7860 loss: 1.7860 2022/10/13 01:32:28 - mmengine - INFO - Epoch(train) [21][640/940] lr: 1.0000e-02 eta: 10:38:12 time: 0.4740 data_time: 0.0330 memory: 17006 grad_norm: 3.9985 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.0338 loss: 2.0338 2022/10/13 01:32:39 - mmengine - INFO - Epoch(train) [21][660/940] lr: 1.0000e-02 eta: 10:38:02 time: 0.5245 data_time: 0.0311 memory: 17006 grad_norm: 4.0533 top1_acc: 0.5000 top5_acc: 0.9062 loss_cls: 1.8406 loss: 1.8406 2022/10/13 01:32:49 - mmengine - INFO - Epoch(train) [21][680/940] lr: 1.0000e-02 eta: 10:37:51 time: 0.4956 data_time: 0.0346 memory: 17006 grad_norm: 3.9195 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7897 loss: 1.7897 2022/10/13 01:32:59 - mmengine - INFO - Epoch(train) [21][700/940] lr: 1.0000e-02 eta: 10:37:42 time: 0.5375 data_time: 0.0314 memory: 17006 grad_norm: 3.9101 top1_acc: 0.4375 top5_acc: 0.8438 loss_cls: 1.9171 loss: 1.9171 2022/10/13 01:33:09 - mmengine - INFO - Epoch(train) [21][720/940] lr: 1.0000e-02 eta: 10:37:29 time: 0.4760 data_time: 0.0394 memory: 17006 grad_norm: 3.9850 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.8385 loss: 1.8385 2022/10/13 01:33:20 - mmengine - INFO - Epoch(train) [21][740/940] lr: 1.0000e-02 eta: 10:37:20 time: 0.5294 data_time: 0.0332 memory: 17006 grad_norm: 4.0033 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6449 loss: 1.6449 2022/10/13 01:33:29 - mmengine - INFO - Epoch(train) [21][760/940] lr: 1.0000e-02 eta: 10:37:07 time: 0.4854 data_time: 0.0346 memory: 17006 grad_norm: 3.9338 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7566 loss: 1.7566 2022/10/13 01:33:40 - mmengine - INFO - Epoch(train) [21][780/940] lr: 1.0000e-02 eta: 10:36:59 time: 0.5384 data_time: 0.0322 memory: 17006 grad_norm: 4.0348 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8677 loss: 1.8677 2022/10/13 01:33:49 - mmengine - INFO - Epoch(train) [21][800/940] lr: 1.0000e-02 eta: 10:36:45 time: 0.4612 data_time: 0.0320 memory: 17006 grad_norm: 3.9710 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7571 loss: 1.7571 2022/10/13 01:34:00 - mmengine - INFO - Epoch(train) [21][820/940] lr: 1.0000e-02 eta: 10:36:37 time: 0.5512 data_time: 0.0312 memory: 17006 grad_norm: 3.9794 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.8114 loss: 1.8114 2022/10/13 01:34:10 - mmengine - INFO - Epoch(train) [21][840/940] lr: 1.0000e-02 eta: 10:36:24 time: 0.4719 data_time: 0.0299 memory: 17006 grad_norm: 3.9710 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8181 loss: 1.8181 2022/10/13 01:34:21 - mmengine - INFO - Epoch(train) [21][860/940] lr: 1.0000e-02 eta: 10:36:17 time: 0.5536 data_time: 0.0324 memory: 17006 grad_norm: 3.9474 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.8982 loss: 1.8982 2022/10/13 01:34:30 - mmengine - INFO - Epoch(train) [21][880/940] lr: 1.0000e-02 eta: 10:36:04 time: 0.4825 data_time: 0.0343 memory: 17006 grad_norm: 4.0106 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8529 loss: 1.8529 2022/10/13 01:34:42 - mmengine - INFO - Epoch(train) [21][900/940] lr: 1.0000e-02 eta: 10:35:58 time: 0.5702 data_time: 0.0307 memory: 17006 grad_norm: 3.9453 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.9998 loss: 1.9998 2022/10/13 01:34:51 - mmengine - INFO - Epoch(train) [21][920/940] lr: 1.0000e-02 eta: 10:35:45 time: 0.4807 data_time: 0.0254 memory: 17006 grad_norm: 3.9344 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.9207 loss: 1.9207 2022/10/13 01:35:01 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 01:35:01 - mmengine - INFO - Epoch(train) [21][940/940] lr: 1.0000e-02 eta: 10:35:33 time: 0.4792 data_time: 0.0276 memory: 17006 grad_norm: 4.2232 top1_acc: 0.2857 top5_acc: 0.2857 loss_cls: 2.0710 loss: 2.0710 2022/10/13 01:35:01 - mmengine - INFO - Saving checkpoint at 21 epochs 2022/10/13 01:35:15 - mmengine - INFO - Epoch(val) [21][20/78] eta: 0:00:36 time: 0.6312 data_time: 0.5404 memory: 3172 2022/10/13 01:35:23 - mmengine - INFO - Epoch(val) [21][40/78] eta: 0:00:16 time: 0.4260 data_time: 0.3352 memory: 3172 2022/10/13 01:35:35 - mmengine - INFO - Epoch(val) [21][60/78] eta: 0:00:10 time: 0.5778 data_time: 0.4876 memory: 3172 2022/10/13 01:35:44 - mmengine - INFO - Epoch(val) [21][78/78] acc/top1: 0.6187 acc/top5: 0.8359 acc/mean1: 0.6187 2022/10/13 01:35:44 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_20.pth is removed 2022/10/13 01:35:44 - mmengine - INFO - The best checkpoint with 0.6187 acc/top1 at 21 epoch is saved to best_acc/top1_epoch_21.pth. 2022/10/13 01:35:58 - mmengine - INFO - Epoch(train) [22][20/940] lr: 1.0000e-02 eta: 10:35:35 time: 0.6773 data_time: 0.3647 memory: 17006 grad_norm: 3.9295 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.8440 loss: 1.8440 2022/10/13 01:36:07 - mmengine - INFO - Epoch(train) [22][40/940] lr: 1.0000e-02 eta: 10:35:20 time: 0.4591 data_time: 0.1130 memory: 17006 grad_norm: 3.9389 top1_acc: 0.3750 top5_acc: 0.7812 loss_cls: 1.8347 loss: 1.8347 2022/10/13 01:36:19 - mmengine - INFO - Epoch(train) [22][60/940] lr: 1.0000e-02 eta: 10:35:17 time: 0.6024 data_time: 0.0952 memory: 17006 grad_norm: 3.9449 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.9494 loss: 1.9494 2022/10/13 01:36:28 - mmengine - INFO - Epoch(train) [22][80/940] lr: 1.0000e-02 eta: 10:35:02 time: 0.4519 data_time: 0.0252 memory: 17006 grad_norm: 3.9234 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.7626 loss: 1.7626 2022/10/13 01:36:39 - mmengine - INFO - Epoch(train) [22][100/940] lr: 1.0000e-02 eta: 10:34:55 time: 0.5590 data_time: 0.0415 memory: 17006 grad_norm: 3.9351 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.8147 loss: 1.8147 2022/10/13 01:36:49 - mmengine - INFO - Epoch(train) [22][120/940] lr: 1.0000e-02 eta: 10:34:41 time: 0.4684 data_time: 0.0260 memory: 17006 grad_norm: 4.0398 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9860 loss: 1.9860 2022/10/13 01:37:00 - mmengine - INFO - Epoch(train) [22][140/940] lr: 1.0000e-02 eta: 10:34:34 time: 0.5516 data_time: 0.0540 memory: 17006 grad_norm: 4.0954 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8283 loss: 1.8283 2022/10/13 01:37:09 - mmengine - INFO - Epoch(train) [22][160/940] lr: 1.0000e-02 eta: 10:34:20 time: 0.4660 data_time: 0.0668 memory: 17006 grad_norm: 3.9747 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7222 loss: 1.7222 2022/10/13 01:37:21 - mmengine - INFO - Epoch(train) [22][180/940] lr: 1.0000e-02 eta: 10:34:14 time: 0.5684 data_time: 0.0703 memory: 17006 grad_norm: 4.0055 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.9131 loss: 1.9131 2022/10/13 01:37:30 - mmengine - INFO - Epoch(train) [22][200/940] lr: 1.0000e-02 eta: 10:34:02 time: 0.4897 data_time: 0.0273 memory: 17006 grad_norm: 3.8750 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.8886 loss: 1.8886 2022/10/13 01:37:41 - mmengine - INFO - Epoch(train) [22][220/940] lr: 1.0000e-02 eta: 10:33:53 time: 0.5297 data_time: 0.0371 memory: 17006 grad_norm: 4.0113 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.7956 loss: 1.7956 2022/10/13 01:37:51 - mmengine - INFO - Epoch(train) [22][240/940] lr: 1.0000e-02 eta: 10:33:40 time: 0.4886 data_time: 0.0261 memory: 17006 grad_norm: 4.0081 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.7763 loss: 1.7763 2022/10/13 01:38:00 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 01:38:00 - mmengine - INFO - Epoch(train) [22][260/940] lr: 1.0000e-02 eta: 10:33:27 time: 0.4735 data_time: 0.0353 memory: 17006 grad_norm: 4.0171 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7811 loss: 1.7811 2022/10/13 01:38:10 - mmengine - INFO - Epoch(train) [22][280/940] lr: 1.0000e-02 eta: 10:33:14 time: 0.4715 data_time: 0.0294 memory: 17006 grad_norm: 3.9526 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.8495 loss: 1.8495 2022/10/13 01:38:21 - mmengine - INFO - Epoch(train) [22][300/940] lr: 1.0000e-02 eta: 10:33:06 time: 0.5497 data_time: 0.0381 memory: 17006 grad_norm: 4.0890 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6698 loss: 1.6698 2022/10/13 01:38:30 - mmengine - INFO - Epoch(train) [22][320/940] lr: 1.0000e-02 eta: 10:32:54 time: 0.4912 data_time: 0.0259 memory: 17006 grad_norm: 4.0293 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7599 loss: 1.7599 2022/10/13 01:38:42 - mmengine - INFO - Epoch(train) [22][340/940] lr: 1.0000e-02 eta: 10:32:49 time: 0.5786 data_time: 0.0363 memory: 17006 grad_norm: 3.9942 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8708 loss: 1.8708 2022/10/13 01:38:52 - mmengine - INFO - Epoch(train) [22][360/940] lr: 1.0000e-02 eta: 10:32:36 time: 0.4775 data_time: 0.0297 memory: 17006 grad_norm: 3.9461 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8359 loss: 1.8359 2022/10/13 01:39:01 - mmengine - INFO - Epoch(train) [22][380/940] lr: 1.0000e-02 eta: 10:32:23 time: 0.4810 data_time: 0.0288 memory: 17006 grad_norm: 4.0131 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7898 loss: 1.7898 2022/10/13 01:39:11 - mmengine - INFO - Epoch(train) [22][400/940] lr: 1.0000e-02 eta: 10:32:10 time: 0.4718 data_time: 0.0406 memory: 17006 grad_norm: 3.9972 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8682 loss: 1.8682 2022/10/13 01:39:22 - mmengine - INFO - Epoch(train) [22][420/940] lr: 1.0000e-02 eta: 10:32:05 time: 0.5816 data_time: 0.0303 memory: 17006 grad_norm: 4.0721 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6590 loss: 1.6590 2022/10/13 01:39:31 - mmengine - INFO - Epoch(train) [22][440/940] lr: 1.0000e-02 eta: 10:31:49 time: 0.4399 data_time: 0.0305 memory: 17006 grad_norm: 3.9591 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.8720 loss: 1.8720 2022/10/13 01:39:42 - mmengine - INFO - Epoch(train) [22][460/940] lr: 1.0000e-02 eta: 10:31:41 time: 0.5516 data_time: 0.0329 memory: 17006 grad_norm: 3.9638 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8434 loss: 1.8434 2022/10/13 01:39:52 - mmengine - INFO - Epoch(train) [22][480/940] lr: 1.0000e-02 eta: 10:31:29 time: 0.4810 data_time: 0.0335 memory: 17006 grad_norm: 4.0259 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.7494 loss: 1.7494 2022/10/13 01:40:02 - mmengine - INFO - Epoch(train) [22][500/940] lr: 1.0000e-02 eta: 10:31:20 time: 0.5286 data_time: 0.0273 memory: 17006 grad_norm: 3.9534 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8626 loss: 1.8626 2022/10/13 01:40:12 - mmengine - INFO - Epoch(train) [22][520/940] lr: 1.0000e-02 eta: 10:31:06 time: 0.4679 data_time: 0.0314 memory: 17006 grad_norm: 4.0564 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8051 loss: 1.8051 2022/10/13 01:40:22 - mmengine - INFO - Epoch(train) [22][540/940] lr: 1.0000e-02 eta: 10:30:57 time: 0.5344 data_time: 0.0310 memory: 17006 grad_norm: 4.0206 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8453 loss: 1.8453 2022/10/13 01:40:32 - mmengine - INFO - Epoch(train) [22][560/940] lr: 1.0000e-02 eta: 10:30:45 time: 0.4802 data_time: 0.0320 memory: 17006 grad_norm: 4.0869 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.9938 loss: 1.9938 2022/10/13 01:40:43 - mmengine - INFO - Epoch(train) [22][580/940] lr: 1.0000e-02 eta: 10:30:36 time: 0.5349 data_time: 0.0330 memory: 17006 grad_norm: 3.9940 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8855 loss: 1.8855 2022/10/13 01:40:52 - mmengine - INFO - Epoch(train) [22][600/940] lr: 1.0000e-02 eta: 10:30:23 time: 0.4727 data_time: 0.0337 memory: 17006 grad_norm: 4.0109 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.8258 loss: 1.8258 2022/10/13 01:41:03 - mmengine - INFO - Epoch(train) [22][620/940] lr: 1.0000e-02 eta: 10:30:15 time: 0.5564 data_time: 0.0368 memory: 17006 grad_norm: 4.0196 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7804 loss: 1.7804 2022/10/13 01:41:13 - mmengine - INFO - Epoch(train) [22][640/940] lr: 1.0000e-02 eta: 10:30:02 time: 0.4740 data_time: 0.0351 memory: 17006 grad_norm: 4.0278 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 2.0147 loss: 2.0147 2022/10/13 01:41:23 - mmengine - INFO - Epoch(train) [22][660/940] lr: 1.0000e-02 eta: 10:29:54 time: 0.5361 data_time: 0.0314 memory: 17006 grad_norm: 4.0382 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.8107 loss: 1.8107 2022/10/13 01:41:33 - mmengine - INFO - Epoch(train) [22][680/940] lr: 1.0000e-02 eta: 10:29:41 time: 0.4737 data_time: 0.0356 memory: 17006 grad_norm: 4.0307 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7792 loss: 1.7792 2022/10/13 01:41:44 - mmengine - INFO - Epoch(train) [22][700/940] lr: 1.0000e-02 eta: 10:29:32 time: 0.5439 data_time: 0.0296 memory: 17006 grad_norm: 3.9889 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 2.0835 loss: 2.0835 2022/10/13 01:41:53 - mmengine - INFO - Epoch(train) [22][720/940] lr: 1.0000e-02 eta: 10:29:20 time: 0.4848 data_time: 0.0323 memory: 17006 grad_norm: 3.9976 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.9117 loss: 1.9117 2022/10/13 01:42:04 - mmengine - INFO - Epoch(train) [22][740/940] lr: 1.0000e-02 eta: 10:29:11 time: 0.5359 data_time: 0.0256 memory: 17006 grad_norm: 4.0819 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8804 loss: 1.8804 2022/10/13 01:42:14 - mmengine - INFO - Epoch(train) [22][760/940] lr: 1.0000e-02 eta: 10:29:00 time: 0.5015 data_time: 0.0323 memory: 17006 grad_norm: 4.0792 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.7585 loss: 1.7585 2022/10/13 01:42:24 - mmengine - INFO - Epoch(train) [22][780/940] lr: 1.0000e-02 eta: 10:28:49 time: 0.5043 data_time: 0.0292 memory: 17006 grad_norm: 4.0221 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8483 loss: 1.8483 2022/10/13 01:42:34 - mmengine - INFO - Epoch(train) [22][800/940] lr: 1.0000e-02 eta: 10:28:38 time: 0.4926 data_time: 0.0348 memory: 17006 grad_norm: 4.0573 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.7203 loss: 1.7203 2022/10/13 01:42:45 - mmengine - INFO - Epoch(train) [22][820/940] lr: 1.0000e-02 eta: 10:28:30 time: 0.5562 data_time: 0.0324 memory: 17006 grad_norm: 4.0091 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.9159 loss: 1.9159 2022/10/13 01:42:54 - mmengine - INFO - Epoch(train) [22][840/940] lr: 1.0000e-02 eta: 10:28:16 time: 0.4532 data_time: 0.0327 memory: 17006 grad_norm: 4.0190 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9154 loss: 1.9154 2022/10/13 01:43:05 - mmengine - INFO - Epoch(train) [22][860/940] lr: 1.0000e-02 eta: 10:28:09 time: 0.5586 data_time: 0.0287 memory: 17006 grad_norm: 4.0179 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.8686 loss: 1.8686 2022/10/13 01:43:15 - mmengine - INFO - Epoch(train) [22][880/940] lr: 1.0000e-02 eta: 10:27:55 time: 0.4622 data_time: 0.0375 memory: 17006 grad_norm: 3.9786 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8598 loss: 1.8598 2022/10/13 01:43:25 - mmengine - INFO - Epoch(train) [22][900/940] lr: 1.0000e-02 eta: 10:27:44 time: 0.5057 data_time: 0.0313 memory: 17006 grad_norm: 4.0393 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.7747 loss: 1.7747 2022/10/13 01:43:34 - mmengine - INFO - Epoch(train) [22][920/940] lr: 1.0000e-02 eta: 10:27:31 time: 0.4750 data_time: 0.0335 memory: 17006 grad_norm: 4.0367 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8879 loss: 1.8879 2022/10/13 01:43:44 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 01:43:44 - mmengine - INFO - Epoch(train) [22][940/940] lr: 1.0000e-02 eta: 10:27:20 time: 0.4977 data_time: 0.0333 memory: 17006 grad_norm: 4.2962 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.8570 loss: 1.8570 2022/10/13 01:43:57 - mmengine - INFO - Epoch(val) [22][20/78] eta: 0:00:36 time: 0.6352 data_time: 0.5398 memory: 3172 2022/10/13 01:44:06 - mmengine - INFO - Epoch(val) [22][40/78] eta: 0:00:16 time: 0.4273 data_time: 0.3338 memory: 3172 2022/10/13 01:44:17 - mmengine - INFO - Epoch(val) [22][60/78] eta: 0:00:10 time: 0.5790 data_time: 0.4879 memory: 3172 2022/10/13 01:44:27 - mmengine - INFO - Epoch(val) [22][78/78] acc/top1: 0.6203 acc/top5: 0.8414 acc/mean1: 0.6201 2022/10/13 01:44:27 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_21.pth is removed 2022/10/13 01:44:27 - mmengine - INFO - The best checkpoint with 0.6203 acc/top1 at 22 epoch is saved to best_acc/top1_epoch_22.pth. 2022/10/13 01:44:40 - mmengine - INFO - Epoch(train) [23][20/940] lr: 1.0000e-02 eta: 10:27:19 time: 0.6470 data_time: 0.3035 memory: 17006 grad_norm: 4.0446 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7590 loss: 1.7590 2022/10/13 01:44:50 - mmengine - INFO - Epoch(train) [23][40/940] lr: 1.0000e-02 eta: 10:27:06 time: 0.4768 data_time: 0.0734 memory: 17006 grad_norm: 4.0154 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8419 loss: 1.8419 2022/10/13 01:45:01 - mmengine - INFO - Epoch(train) [23][60/940] lr: 1.0000e-02 eta: 10:26:59 time: 0.5615 data_time: 0.1071 memory: 17006 grad_norm: 3.9360 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7946 loss: 1.7946 2022/10/13 01:45:11 - mmengine - INFO - Epoch(train) [23][80/940] lr: 1.0000e-02 eta: 10:26:48 time: 0.4949 data_time: 0.0700 memory: 17006 grad_norm: 3.9676 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.8043 loss: 1.8043 2022/10/13 01:45:22 - mmengine - INFO - Epoch(train) [23][100/940] lr: 1.0000e-02 eta: 10:26:39 time: 0.5415 data_time: 0.1452 memory: 17006 grad_norm: 4.0722 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8022 loss: 1.8022 2022/10/13 01:45:32 - mmengine - INFO - Epoch(train) [23][120/940] lr: 1.0000e-02 eta: 10:26:30 time: 0.5224 data_time: 0.1756 memory: 17006 grad_norm: 4.0358 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.7315 loss: 1.7315 2022/10/13 01:45:44 - mmengine - INFO - Epoch(train) [23][140/940] lr: 1.0000e-02 eta: 10:26:23 time: 0.5660 data_time: 0.2450 memory: 17006 grad_norm: 3.9770 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6755 loss: 1.6755 2022/10/13 01:45:52 - mmengine - INFO - Epoch(train) [23][160/940] lr: 1.0000e-02 eta: 10:26:08 time: 0.4412 data_time: 0.1093 memory: 17006 grad_norm: 3.9935 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7319 loss: 1.7319 2022/10/13 01:46:03 - mmengine - INFO - Epoch(train) [23][180/940] lr: 1.0000e-02 eta: 10:25:57 time: 0.5127 data_time: 0.1912 memory: 17006 grad_norm: 3.9924 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.9661 loss: 1.9661 2022/10/13 01:46:12 - mmengine - INFO - Epoch(train) [23][200/940] lr: 1.0000e-02 eta: 10:25:44 time: 0.4648 data_time: 0.1277 memory: 17006 grad_norm: 3.9120 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.7060 loss: 1.7060 2022/10/13 01:46:22 - mmengine - INFO - Epoch(train) [23][220/940] lr: 1.0000e-02 eta: 10:25:33 time: 0.5138 data_time: 0.0704 memory: 17006 grad_norm: 4.0371 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.9216 loss: 1.9216 2022/10/13 01:46:33 - mmengine - INFO - Epoch(train) [23][240/940] lr: 1.0000e-02 eta: 10:25:24 time: 0.5277 data_time: 0.0233 memory: 17006 grad_norm: 3.9897 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8913 loss: 1.8913 2022/10/13 01:46:42 - mmengine - INFO - Epoch(train) [23][260/940] lr: 1.0000e-02 eta: 10:25:11 time: 0.4760 data_time: 0.0377 memory: 17006 grad_norm: 3.9743 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7583 loss: 1.7583 2022/10/13 01:46:53 - mmengine - INFO - Epoch(train) [23][280/940] lr: 1.0000e-02 eta: 10:25:03 time: 0.5360 data_time: 0.0319 memory: 17006 grad_norm: 3.9230 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8240 loss: 1.8240 2022/10/13 01:47:03 - mmengine - INFO - Epoch(train) [23][300/940] lr: 1.0000e-02 eta: 10:24:50 time: 0.4776 data_time: 0.0296 memory: 17006 grad_norm: 3.9546 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.6256 loss: 1.6256 2022/10/13 01:47:13 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 01:47:13 - mmengine - INFO - Epoch(train) [23][320/940] lr: 1.0000e-02 eta: 10:24:42 time: 0.5416 data_time: 0.0309 memory: 17006 grad_norm: 3.9800 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8752 loss: 1.8752 2022/10/13 01:47:24 - mmengine - INFO - Epoch(train) [23][340/940] lr: 1.0000e-02 eta: 10:24:31 time: 0.5078 data_time: 0.0314 memory: 17006 grad_norm: 4.0699 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.8796 loss: 1.8796 2022/10/13 01:47:34 - mmengine - INFO - Epoch(train) [23][360/940] lr: 1.0000e-02 eta: 10:24:23 time: 0.5425 data_time: 0.0257 memory: 17006 grad_norm: 4.0490 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.8673 loss: 1.8673 2022/10/13 01:47:44 - mmengine - INFO - Epoch(train) [23][380/940] lr: 1.0000e-02 eta: 10:24:10 time: 0.4729 data_time: 0.0296 memory: 17006 grad_norm: 4.0890 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7850 loss: 1.7850 2022/10/13 01:47:55 - mmengine - INFO - Epoch(train) [23][400/940] lr: 1.0000e-02 eta: 10:24:00 time: 0.5301 data_time: 0.0337 memory: 17006 grad_norm: 3.9659 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6473 loss: 1.6473 2022/10/13 01:48:05 - mmengine - INFO - Epoch(train) [23][420/940] lr: 1.0000e-02 eta: 10:23:51 time: 0.5294 data_time: 0.0353 memory: 17006 grad_norm: 3.9539 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.8802 loss: 1.8802 2022/10/13 01:48:15 - mmengine - INFO - Epoch(train) [23][440/940] lr: 1.0000e-02 eta: 10:23:38 time: 0.4687 data_time: 0.0369 memory: 17006 grad_norm: 4.0247 top1_acc: 0.3438 top5_acc: 0.7500 loss_cls: 1.8313 loss: 1.8313 2022/10/13 01:48:26 - mmengine - INFO - Epoch(train) [23][460/940] lr: 1.0000e-02 eta: 10:23:32 time: 0.5716 data_time: 0.0327 memory: 17006 grad_norm: 4.0424 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.8655 loss: 1.8655 2022/10/13 01:48:35 - mmengine - INFO - Epoch(train) [23][480/940] lr: 1.0000e-02 eta: 10:23:19 time: 0.4765 data_time: 0.0304 memory: 17006 grad_norm: 4.0150 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7201 loss: 1.7201 2022/10/13 01:48:46 - mmengine - INFO - Epoch(train) [23][500/940] lr: 1.0000e-02 eta: 10:23:08 time: 0.5051 data_time: 0.0343 memory: 17006 grad_norm: 3.9895 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8081 loss: 1.8081 2022/10/13 01:48:54 - mmengine - INFO - Epoch(train) [23][520/940] lr: 1.0000e-02 eta: 10:22:53 time: 0.4380 data_time: 0.0294 memory: 17006 grad_norm: 4.0386 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8369 loss: 1.8369 2022/10/13 01:49:04 - mmengine - INFO - Epoch(train) [23][540/940] lr: 1.0000e-02 eta: 10:22:40 time: 0.4872 data_time: 0.0264 memory: 17006 grad_norm: 4.0875 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.8660 loss: 1.8660 2022/10/13 01:49:14 - mmengine - INFO - Epoch(train) [23][560/940] lr: 1.0000e-02 eta: 10:22:28 time: 0.4886 data_time: 0.0322 memory: 17006 grad_norm: 3.9953 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7545 loss: 1.7545 2022/10/13 01:49:25 - mmengine - INFO - Epoch(train) [23][580/940] lr: 1.0000e-02 eta: 10:22:21 time: 0.5574 data_time: 0.0347 memory: 17006 grad_norm: 3.9802 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8336 loss: 1.8336 2022/10/13 01:49:35 - mmengine - INFO - Epoch(train) [23][600/940] lr: 1.0000e-02 eta: 10:22:11 time: 0.5078 data_time: 0.0386 memory: 17006 grad_norm: 4.0257 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.8685 loss: 1.8685 2022/10/13 01:49:45 - mmengine - INFO - Epoch(train) [23][620/940] lr: 1.0000e-02 eta: 10:22:00 time: 0.5085 data_time: 0.0309 memory: 17006 grad_norm: 3.9539 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.8432 loss: 1.8432 2022/10/13 01:49:56 - mmengine - INFO - Epoch(train) [23][640/940] lr: 1.0000e-02 eta: 10:21:50 time: 0.5127 data_time: 0.0305 memory: 17006 grad_norm: 4.0564 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.9169 loss: 1.9169 2022/10/13 01:50:05 - mmengine - INFO - Epoch(train) [23][660/940] lr: 1.0000e-02 eta: 10:21:36 time: 0.4674 data_time: 0.0286 memory: 17006 grad_norm: 4.0107 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7962 loss: 1.7962 2022/10/13 01:50:16 - mmengine - INFO - Epoch(train) [23][680/940] lr: 1.0000e-02 eta: 10:21:28 time: 0.5366 data_time: 0.0263 memory: 17006 grad_norm: 4.0531 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7651 loss: 1.7651 2022/10/13 01:50:25 - mmengine - INFO - Epoch(train) [23][700/940] lr: 1.0000e-02 eta: 10:21:14 time: 0.4633 data_time: 0.0291 memory: 17006 grad_norm: 4.1055 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.9291 loss: 1.9291 2022/10/13 01:50:35 - mmengine - INFO - Epoch(train) [23][720/940] lr: 1.0000e-02 eta: 10:21:04 time: 0.5224 data_time: 0.0321 memory: 17006 grad_norm: 4.0716 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7848 loss: 1.7848 2022/10/13 01:50:45 - mmengine - INFO - Epoch(train) [23][740/940] lr: 1.0000e-02 eta: 10:20:52 time: 0.4867 data_time: 0.0307 memory: 17006 grad_norm: 4.0045 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8887 loss: 1.8887 2022/10/13 01:50:56 - mmengine - INFO - Epoch(train) [23][760/940] lr: 1.0000e-02 eta: 10:20:44 time: 0.5372 data_time: 0.0278 memory: 17006 grad_norm: 3.9877 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.9529 loss: 1.9529 2022/10/13 01:51:06 - mmengine - INFO - Epoch(train) [23][780/940] lr: 1.0000e-02 eta: 10:20:31 time: 0.4823 data_time: 0.0290 memory: 17006 grad_norm: 4.0910 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9198 loss: 1.9198 2022/10/13 01:51:16 - mmengine - INFO - Epoch(train) [23][800/940] lr: 1.0000e-02 eta: 10:20:21 time: 0.5080 data_time: 0.0286 memory: 17006 grad_norm: 3.9836 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7697 loss: 1.7697 2022/10/13 01:51:25 - mmengine - INFO - Epoch(train) [23][820/940] lr: 1.0000e-02 eta: 10:20:07 time: 0.4682 data_time: 0.0342 memory: 17006 grad_norm: 3.9341 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7976 loss: 1.7976 2022/10/13 01:51:35 - mmengine - INFO - Epoch(train) [23][840/940] lr: 1.0000e-02 eta: 10:19:57 time: 0.5191 data_time: 0.0304 memory: 17006 grad_norm: 4.0515 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7348 loss: 1.7348 2022/10/13 01:51:45 - mmengine - INFO - Epoch(train) [23][860/940] lr: 1.0000e-02 eta: 10:19:45 time: 0.4854 data_time: 0.0288 memory: 17006 grad_norm: 4.1323 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8351 loss: 1.8351 2022/10/13 01:51:56 - mmengine - INFO - Epoch(train) [23][880/940] lr: 1.0000e-02 eta: 10:19:36 time: 0.5246 data_time: 0.0337 memory: 17006 grad_norm: 3.9939 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8789 loss: 1.8789 2022/10/13 01:52:07 - mmengine - INFO - Epoch(train) [23][900/940] lr: 1.0000e-02 eta: 10:19:28 time: 0.5492 data_time: 0.0295 memory: 17006 grad_norm: 4.0652 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.9389 loss: 1.9389 2022/10/13 01:52:16 - mmengine - INFO - Epoch(train) [23][920/940] lr: 1.0000e-02 eta: 10:19:15 time: 0.4724 data_time: 0.0309 memory: 17006 grad_norm: 4.0352 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.7999 loss: 1.7999 2022/10/13 01:52:26 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 01:52:26 - mmengine - INFO - Epoch(train) [23][940/940] lr: 1.0000e-02 eta: 10:19:03 time: 0.4886 data_time: 0.0261 memory: 17006 grad_norm: 4.2560 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.8360 loss: 1.8360 2022/10/13 01:52:38 - mmengine - INFO - Epoch(val) [23][20/78] eta: 0:00:36 time: 0.6288 data_time: 0.5345 memory: 3172 2022/10/13 01:52:47 - mmengine - INFO - Epoch(val) [23][40/78] eta: 0:00:16 time: 0.4255 data_time: 0.3363 memory: 3172 2022/10/13 01:52:59 - mmengine - INFO - Epoch(val) [23][60/78] eta: 0:00:10 time: 0.5897 data_time: 0.4983 memory: 3172 2022/10/13 01:53:08 - mmengine - INFO - Epoch(val) [23][78/78] acc/top1: 0.6120 acc/top5: 0.8324 acc/mean1: 0.6119 2022/10/13 01:53:22 - mmengine - INFO - Epoch(train) [24][20/940] lr: 1.0000e-02 eta: 10:19:05 time: 0.6998 data_time: 0.3246 memory: 17006 grad_norm: 3.9605 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7771 loss: 1.7771 2022/10/13 01:53:32 - mmengine - INFO - Epoch(train) [24][40/940] lr: 1.0000e-02 eta: 10:18:51 time: 0.4585 data_time: 0.1217 memory: 17006 grad_norm: 4.0520 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.7177 loss: 1.7177 2022/10/13 01:53:43 - mmengine - INFO - Epoch(train) [24][60/940] lr: 1.0000e-02 eta: 10:18:44 time: 0.5635 data_time: 0.2048 memory: 17006 grad_norm: 3.9889 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7448 loss: 1.7448 2022/10/13 01:53:53 - mmengine - INFO - Epoch(train) [24][80/940] lr: 1.0000e-02 eta: 10:18:33 time: 0.5008 data_time: 0.1920 memory: 17006 grad_norm: 4.0389 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.7815 loss: 1.7815 2022/10/13 01:54:04 - mmengine - INFO - Epoch(train) [24][100/940] lr: 1.0000e-02 eta: 10:18:26 time: 0.5651 data_time: 0.2450 memory: 17006 grad_norm: 4.0286 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 1.7827 loss: 1.7827 2022/10/13 01:54:14 - mmengine - INFO - Epoch(train) [24][120/940] lr: 1.0000e-02 eta: 10:18:15 time: 0.4883 data_time: 0.0778 memory: 17006 grad_norm: 3.9347 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.8333 loss: 1.8333 2022/10/13 01:54:26 - mmengine - INFO - Epoch(train) [24][140/940] lr: 1.0000e-02 eta: 10:18:09 time: 0.5821 data_time: 0.0312 memory: 17006 grad_norm: 4.0641 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 2.0138 loss: 2.0138 2022/10/13 01:54:35 - mmengine - INFO - Epoch(train) [24][160/940] lr: 1.0000e-02 eta: 10:17:54 time: 0.4454 data_time: 0.0324 memory: 17006 grad_norm: 4.0183 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.9359 loss: 1.9359 2022/10/13 01:54:44 - mmengine - INFO - Epoch(train) [24][180/940] lr: 1.0000e-02 eta: 10:17:43 time: 0.4939 data_time: 0.0392 memory: 17006 grad_norm: 3.9894 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6847 loss: 1.6847 2022/10/13 01:54:54 - mmengine - INFO - Epoch(train) [24][200/940] lr: 1.0000e-02 eta: 10:17:32 time: 0.5023 data_time: 0.0279 memory: 17006 grad_norm: 4.0456 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6886 loss: 1.6886 2022/10/13 01:55:05 - mmengine - INFO - Epoch(train) [24][220/940] lr: 1.0000e-02 eta: 10:17:23 time: 0.5472 data_time: 0.0390 memory: 17006 grad_norm: 4.0048 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.8115 loss: 1.8115 2022/10/13 01:55:14 - mmengine - INFO - Epoch(train) [24][240/940] lr: 1.0000e-02 eta: 10:17:09 time: 0.4526 data_time: 0.0282 memory: 17006 grad_norm: 4.0653 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8466 loss: 1.8466 2022/10/13 01:55:25 - mmengine - INFO - Epoch(train) [24][260/940] lr: 1.0000e-02 eta: 10:17:00 time: 0.5364 data_time: 0.0352 memory: 17006 grad_norm: 4.0606 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7308 loss: 1.7308 2022/10/13 01:55:35 - mmengine - INFO - Epoch(train) [24][280/940] lr: 1.0000e-02 eta: 10:16:48 time: 0.4752 data_time: 0.0348 memory: 17006 grad_norm: 4.0134 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.7438 loss: 1.7438 2022/10/13 01:55:45 - mmengine - INFO - Epoch(train) [24][300/940] lr: 1.0000e-02 eta: 10:16:37 time: 0.5068 data_time: 0.0328 memory: 17006 grad_norm: 4.0507 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.8000 loss: 1.8000 2022/10/13 01:55:55 - mmengine - INFO - Epoch(train) [24][320/940] lr: 1.0000e-02 eta: 10:16:25 time: 0.4928 data_time: 0.0339 memory: 17006 grad_norm: 4.1650 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8346 loss: 1.8346 2022/10/13 01:56:05 - mmengine - INFO - Epoch(train) [24][340/940] lr: 1.0000e-02 eta: 10:16:15 time: 0.5116 data_time: 0.0361 memory: 17006 grad_norm: 4.0273 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.8450 loss: 1.8450 2022/10/13 01:56:15 - mmengine - INFO - Epoch(train) [24][360/940] lr: 1.0000e-02 eta: 10:16:05 time: 0.5106 data_time: 0.0308 memory: 17006 grad_norm: 3.9772 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.7270 loss: 1.7270 2022/10/13 01:56:26 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 01:56:26 - mmengine - INFO - Epoch(train) [24][380/940] lr: 1.0000e-02 eta: 10:15:57 time: 0.5579 data_time: 0.0339 memory: 17006 grad_norm: 3.9321 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.7814 loss: 1.7814 2022/10/13 01:56:36 - mmengine - INFO - Epoch(train) [24][400/940] lr: 1.0000e-02 eta: 10:15:47 time: 0.5076 data_time: 0.0292 memory: 17006 grad_norm: 4.0257 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8421 loss: 1.8421 2022/10/13 01:56:47 - mmengine - INFO - Epoch(train) [24][420/940] lr: 1.0000e-02 eta: 10:15:36 time: 0.5156 data_time: 0.0357 memory: 17006 grad_norm: 3.9217 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.7025 loss: 1.7025 2022/10/13 01:56:57 - mmengine - INFO - Epoch(train) [24][440/940] lr: 1.0000e-02 eta: 10:15:25 time: 0.4932 data_time: 0.0256 memory: 17006 grad_norm: 4.0005 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6774 loss: 1.6774 2022/10/13 01:57:08 - mmengine - INFO - Epoch(train) [24][460/940] lr: 1.0000e-02 eta: 10:15:17 time: 0.5547 data_time: 0.0408 memory: 17006 grad_norm: 4.0495 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6555 loss: 1.6555 2022/10/13 01:57:18 - mmengine - INFO - Epoch(train) [24][480/940] lr: 1.0000e-02 eta: 10:15:07 time: 0.5158 data_time: 0.0343 memory: 17006 grad_norm: 4.0509 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8473 loss: 1.8473 2022/10/13 01:57:29 - mmengine - INFO - Epoch(train) [24][500/940] lr: 1.0000e-02 eta: 10:14:58 time: 0.5352 data_time: 0.0357 memory: 17006 grad_norm: 4.0630 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.8138 loss: 1.8138 2022/10/13 01:57:38 - mmengine - INFO - Epoch(train) [24][520/940] lr: 1.0000e-02 eta: 10:14:46 time: 0.4819 data_time: 0.0353 memory: 17006 grad_norm: 4.0791 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.8122 loss: 1.8122 2022/10/13 01:57:48 - mmengine - INFO - Epoch(train) [24][540/940] lr: 1.0000e-02 eta: 10:14:35 time: 0.5004 data_time: 0.0318 memory: 17006 grad_norm: 4.0754 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8774 loss: 1.8774 2022/10/13 01:57:58 - mmengine - INFO - Epoch(train) [24][560/940] lr: 1.0000e-02 eta: 10:14:21 time: 0.4616 data_time: 0.0285 memory: 17006 grad_norm: 4.0701 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.7701 loss: 1.7701 2022/10/13 01:58:09 - mmengine - INFO - Epoch(train) [24][580/940] lr: 1.0000e-02 eta: 10:14:16 time: 0.5856 data_time: 0.0400 memory: 17006 grad_norm: 4.0116 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7300 loss: 1.7300 2022/10/13 01:58:19 - mmengine - INFO - Epoch(train) [24][600/940] lr: 1.0000e-02 eta: 10:14:04 time: 0.4870 data_time: 0.0328 memory: 17006 grad_norm: 4.0401 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8266 loss: 1.8266 2022/10/13 01:58:30 - mmengine - INFO - Epoch(train) [24][620/940] lr: 1.0000e-02 eta: 10:13:55 time: 0.5295 data_time: 0.0396 memory: 17006 grad_norm: 4.0984 top1_acc: 0.3750 top5_acc: 0.8125 loss_cls: 1.8721 loss: 1.8721 2022/10/13 01:58:39 - mmengine - INFO - Epoch(train) [24][640/940] lr: 1.0000e-02 eta: 10:13:40 time: 0.4533 data_time: 0.0316 memory: 17006 grad_norm: 4.0339 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7350 loss: 1.7350 2022/10/13 01:58:49 - mmengine - INFO - Epoch(train) [24][660/940] lr: 1.0000e-02 eta: 10:13:30 time: 0.5097 data_time: 0.0305 memory: 17006 grad_norm: 4.0886 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7986 loss: 1.7986 2022/10/13 01:58:58 - mmengine - INFO - Epoch(train) [24][680/940] lr: 1.0000e-02 eta: 10:13:17 time: 0.4686 data_time: 0.0328 memory: 17006 grad_norm: 4.0099 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8439 loss: 1.8439 2022/10/13 01:59:09 - mmengine - INFO - Epoch(train) [24][700/940] lr: 1.0000e-02 eta: 10:13:07 time: 0.5183 data_time: 0.0312 memory: 17006 grad_norm: 4.0097 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8642 loss: 1.8642 2022/10/13 01:59:19 - mmengine - INFO - Epoch(train) [24][720/940] lr: 1.0000e-02 eta: 10:12:55 time: 0.4942 data_time: 0.0305 memory: 17006 grad_norm: 4.0691 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7553 loss: 1.7553 2022/10/13 01:59:29 - mmengine - INFO - Epoch(train) [24][740/940] lr: 1.0000e-02 eta: 10:12:45 time: 0.5042 data_time: 0.0377 memory: 17006 grad_norm: 4.0026 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.9417 loss: 1.9417 2022/10/13 01:59:39 - mmengine - INFO - Epoch(train) [24][760/940] lr: 1.0000e-02 eta: 10:12:35 time: 0.5223 data_time: 0.0343 memory: 17006 grad_norm: 4.0068 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7007 loss: 1.7007 2022/10/13 01:59:49 - mmengine - INFO - Epoch(train) [24][780/940] lr: 1.0000e-02 eta: 10:12:24 time: 0.5020 data_time: 0.0292 memory: 17006 grad_norm: 4.0554 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7066 loss: 1.7066 2022/10/13 01:59:59 - mmengine - INFO - Epoch(train) [24][800/940] lr: 1.0000e-02 eta: 10:12:12 time: 0.4893 data_time: 0.0325 memory: 17006 grad_norm: 4.0659 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.7589 loss: 1.7589 2022/10/13 02:00:10 - mmengine - INFO - Epoch(train) [24][820/940] lr: 1.0000e-02 eta: 10:12:03 time: 0.5367 data_time: 0.0247 memory: 17006 grad_norm: 4.0119 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6927 loss: 1.6927 2022/10/13 02:00:20 - mmengine - INFO - Epoch(train) [24][840/940] lr: 1.0000e-02 eta: 10:11:55 time: 0.5360 data_time: 0.0377 memory: 17006 grad_norm: 4.0330 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7674 loss: 1.7674 2022/10/13 02:00:30 - mmengine - INFO - Epoch(train) [24][860/940] lr: 1.0000e-02 eta: 10:11:42 time: 0.4767 data_time: 0.0296 memory: 17006 grad_norm: 4.0690 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.7740 loss: 1.7740 2022/10/13 02:00:40 - mmengine - INFO - Epoch(train) [24][880/940] lr: 1.0000e-02 eta: 10:11:32 time: 0.5145 data_time: 0.0353 memory: 17006 grad_norm: 3.9365 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8573 loss: 1.8573 2022/10/13 02:00:49 - mmengine - INFO - Epoch(train) [24][900/940] lr: 1.0000e-02 eta: 10:11:18 time: 0.4504 data_time: 0.0263 memory: 17006 grad_norm: 4.0518 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.8501 loss: 1.8501 2022/10/13 02:01:01 - mmengine - INFO - Epoch(train) [24][920/940] lr: 1.0000e-02 eta: 10:11:12 time: 0.5846 data_time: 0.0280 memory: 17006 grad_norm: 4.1350 top1_acc: 0.3438 top5_acc: 0.6562 loss_cls: 1.8512 loss: 1.8512 2022/10/13 02:01:09 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 02:01:09 - mmengine - INFO - Epoch(train) [24][940/940] lr: 1.0000e-02 eta: 10:10:55 time: 0.4124 data_time: 0.0300 memory: 17006 grad_norm: 4.2241 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.7758 loss: 1.7758 2022/10/13 02:01:09 - mmengine - INFO - Saving checkpoint at 24 epochs 2022/10/13 02:01:22 - mmengine - INFO - Epoch(val) [24][20/78] eta: 0:00:36 time: 0.6231 data_time: 0.5306 memory: 3172 2022/10/13 02:01:31 - mmengine - INFO - Epoch(val) [24][40/78] eta: 0:00:16 time: 0.4296 data_time: 0.3375 memory: 3172 2022/10/13 02:01:43 - mmengine - INFO - Epoch(val) [24][60/78] eta: 0:00:10 time: 0.5818 data_time: 0.4913 memory: 3172 2022/10/13 02:01:52 - mmengine - INFO - Epoch(val) [24][78/78] acc/top1: 0.6163 acc/top5: 0.8356 acc/mean1: 0.6162 2022/10/13 02:02:06 - mmengine - INFO - Epoch(train) [25][20/940] lr: 1.0000e-02 eta: 10:10:58 time: 0.7233 data_time: 0.3137 memory: 17006 grad_norm: 4.0473 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7446 loss: 1.7446 2022/10/13 02:02:16 - mmengine - INFO - Epoch(train) [25][40/940] lr: 1.0000e-02 eta: 10:10:46 time: 0.4809 data_time: 0.0502 memory: 17006 grad_norm: 3.9820 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.7600 loss: 1.7600 2022/10/13 02:02:27 - mmengine - INFO - Epoch(train) [25][60/940] lr: 1.0000e-02 eta: 10:10:37 time: 0.5402 data_time: 0.0658 memory: 17006 grad_norm: 3.9824 top1_acc: 0.3438 top5_acc: 0.5938 loss_cls: 1.6958 loss: 1.6958 2022/10/13 02:02:37 - mmengine - INFO - Epoch(train) [25][80/940] lr: 1.0000e-02 eta: 10:10:27 time: 0.5107 data_time: 0.0359 memory: 17006 grad_norm: 3.9845 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 1.7550 loss: 1.7550 2022/10/13 02:02:48 - mmengine - INFO - Epoch(train) [25][100/940] lr: 1.0000e-02 eta: 10:10:21 time: 0.5766 data_time: 0.0319 memory: 17006 grad_norm: 4.0577 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.8103 loss: 1.8103 2022/10/13 02:02:58 - mmengine - INFO - Epoch(train) [25][120/940] lr: 1.0000e-02 eta: 10:10:07 time: 0.4657 data_time: 0.0330 memory: 17006 grad_norm: 3.9732 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.8770 loss: 1.8770 2022/10/13 02:03:08 - mmengine - INFO - Epoch(train) [25][140/940] lr: 1.0000e-02 eta: 10:09:57 time: 0.5175 data_time: 0.0323 memory: 17006 grad_norm: 4.0058 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.8164 loss: 1.8164 2022/10/13 02:03:18 - mmengine - INFO - Epoch(train) [25][160/940] lr: 1.0000e-02 eta: 10:09:45 time: 0.4885 data_time: 0.0342 memory: 17006 grad_norm: 3.9985 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7849 loss: 1.7849 2022/10/13 02:03:29 - mmengine - INFO - Epoch(train) [25][180/940] lr: 1.0000e-02 eta: 10:09:39 time: 0.5673 data_time: 0.0305 memory: 17006 grad_norm: 4.0150 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.7907 loss: 1.7907 2022/10/13 02:03:39 - mmengine - INFO - Epoch(train) [25][200/940] lr: 1.0000e-02 eta: 10:09:26 time: 0.4757 data_time: 0.0317 memory: 17006 grad_norm: 4.0389 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.7620 loss: 1.7620 2022/10/13 02:03:50 - mmengine - INFO - Epoch(train) [25][220/940] lr: 1.0000e-02 eta: 10:09:19 time: 0.5669 data_time: 0.0318 memory: 17006 grad_norm: 3.9821 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7610 loss: 1.7610 2022/10/13 02:03:59 - mmengine - INFO - Epoch(train) [25][240/940] lr: 1.0000e-02 eta: 10:09:04 time: 0.4302 data_time: 0.0314 memory: 17006 grad_norm: 4.0011 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 1.7755 loss: 1.7755 2022/10/13 02:04:10 - mmengine - INFO - Epoch(train) [25][260/940] lr: 1.0000e-02 eta: 10:08:57 time: 0.5654 data_time: 0.0318 memory: 17006 grad_norm: 4.0801 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.7221 loss: 1.7221 2022/10/13 02:04:19 - mmengine - INFO - Epoch(train) [25][280/940] lr: 1.0000e-02 eta: 10:08:43 time: 0.4597 data_time: 0.0367 memory: 17006 grad_norm: 4.0259 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7555 loss: 1.7555 2022/10/13 02:04:30 - mmengine - INFO - Epoch(train) [25][300/940] lr: 1.0000e-02 eta: 10:08:34 time: 0.5348 data_time: 0.0338 memory: 17006 grad_norm: 3.9669 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8544 loss: 1.8544 2022/10/13 02:04:39 - mmengine - INFO - Epoch(train) [25][320/940] lr: 1.0000e-02 eta: 10:08:21 time: 0.4637 data_time: 0.0373 memory: 17006 grad_norm: 4.0255 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7807 loss: 1.7807 2022/10/13 02:04:50 - mmengine - INFO - Epoch(train) [25][340/940] lr: 1.0000e-02 eta: 10:08:14 time: 0.5626 data_time: 0.0341 memory: 17006 grad_norm: 4.0184 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6993 loss: 1.6993 2022/10/13 02:04:59 - mmengine - INFO - Epoch(train) [25][360/940] lr: 1.0000e-02 eta: 10:08:00 time: 0.4581 data_time: 0.0353 memory: 17006 grad_norm: 4.1035 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8696 loss: 1.8696 2022/10/13 02:05:11 - mmengine - INFO - Epoch(train) [25][380/940] lr: 1.0000e-02 eta: 10:07:54 time: 0.5919 data_time: 0.0331 memory: 17006 grad_norm: 4.0220 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.7118 loss: 1.7118 2022/10/13 02:05:21 - mmengine - INFO - Epoch(train) [25][400/940] lr: 1.0000e-02 eta: 10:07:42 time: 0.4791 data_time: 0.0301 memory: 17006 grad_norm: 4.0712 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8560 loss: 1.8560 2022/10/13 02:05:31 - mmengine - INFO - Epoch(train) [25][420/940] lr: 1.0000e-02 eta: 10:07:32 time: 0.5135 data_time: 0.0437 memory: 17006 grad_norm: 4.0285 top1_acc: 0.3438 top5_acc: 0.6875 loss_cls: 1.7105 loss: 1.7105 2022/10/13 02:05:40 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 02:05:40 - mmengine - INFO - Epoch(train) [25][440/940] lr: 1.0000e-02 eta: 10:07:19 time: 0.4646 data_time: 0.0280 memory: 17006 grad_norm: 4.0231 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7524 loss: 1.7524 2022/10/13 02:05:52 - mmengine - INFO - Epoch(train) [25][460/940] lr: 1.0000e-02 eta: 10:07:11 time: 0.5552 data_time: 0.0353 memory: 17006 grad_norm: 4.1180 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9080 loss: 1.9080 2022/10/13 02:06:01 - mmengine - INFO - Epoch(train) [25][480/940] lr: 1.0000e-02 eta: 10:06:58 time: 0.4662 data_time: 0.0314 memory: 17006 grad_norm: 4.0204 top1_acc: 0.3125 top5_acc: 0.5625 loss_cls: 1.8747 loss: 1.8747 2022/10/13 02:06:12 - mmengine - INFO - Epoch(train) [25][500/940] lr: 1.0000e-02 eta: 10:06:49 time: 0.5451 data_time: 0.0369 memory: 17006 grad_norm: 4.1374 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.8502 loss: 1.8502 2022/10/13 02:06:21 - mmengine - INFO - Epoch(train) [25][520/940] lr: 1.0000e-02 eta: 10:06:37 time: 0.4719 data_time: 0.0307 memory: 17006 grad_norm: 4.1007 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.8944 loss: 1.8944 2022/10/13 02:06:32 - mmengine - INFO - Epoch(train) [25][540/940] lr: 1.0000e-02 eta: 10:06:29 time: 0.5596 data_time: 0.0288 memory: 17006 grad_norm: 4.0379 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.9048 loss: 1.9048 2022/10/13 02:06:40 - mmengine - INFO - Epoch(train) [25][560/940] lr: 1.0000e-02 eta: 10:06:12 time: 0.4027 data_time: 0.0343 memory: 17006 grad_norm: 3.9964 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9047 loss: 1.9047 2022/10/13 02:06:52 - mmengine - INFO - Epoch(train) [25][580/940] lr: 1.0000e-02 eta: 10:06:06 time: 0.5861 data_time: 0.0303 memory: 17006 grad_norm: 4.0208 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8312 loss: 1.8312 2022/10/13 02:07:01 - mmengine - INFO - Epoch(train) [25][600/940] lr: 1.0000e-02 eta: 10:05:52 time: 0.4501 data_time: 0.0306 memory: 17006 grad_norm: 3.9908 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8176 loss: 1.8176 2022/10/13 02:07:13 - mmengine - INFO - Epoch(train) [25][620/940] lr: 1.0000e-02 eta: 10:05:47 time: 0.5942 data_time: 0.0309 memory: 17006 grad_norm: 4.0795 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.9086 loss: 1.9086 2022/10/13 02:07:22 - mmengine - INFO - Epoch(train) [25][640/940] lr: 1.0000e-02 eta: 10:05:34 time: 0.4625 data_time: 0.0268 memory: 17006 grad_norm: 4.0626 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8138 loss: 1.8138 2022/10/13 02:07:32 - mmengine - INFO - Epoch(train) [25][660/940] lr: 1.0000e-02 eta: 10:05:22 time: 0.4948 data_time: 0.0375 memory: 17006 grad_norm: 4.0392 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7981 loss: 1.7981 2022/10/13 02:07:43 - mmengine - INFO - Epoch(train) [25][680/940] lr: 1.0000e-02 eta: 10:05:14 time: 0.5452 data_time: 0.0324 memory: 17006 grad_norm: 4.0227 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.8260 loss: 1.8260 2022/10/13 02:07:53 - mmengine - INFO - Epoch(train) [25][700/940] lr: 1.0000e-02 eta: 10:05:02 time: 0.4948 data_time: 0.0332 memory: 17006 grad_norm: 4.1093 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.8147 loss: 1.8147 2022/10/13 02:08:03 - mmengine - INFO - Epoch(train) [25][720/940] lr: 1.0000e-02 eta: 10:04:51 time: 0.4912 data_time: 0.0265 memory: 17006 grad_norm: 4.0283 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.8000 loss: 1.8000 2022/10/13 02:08:13 - mmengine - INFO - Epoch(train) [25][740/940] lr: 1.0000e-02 eta: 10:04:40 time: 0.4986 data_time: 0.0286 memory: 17006 grad_norm: 4.1594 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.9216 loss: 1.9216 2022/10/13 02:08:22 - mmengine - INFO - Epoch(train) [25][760/940] lr: 1.0000e-02 eta: 10:04:27 time: 0.4713 data_time: 0.0308 memory: 17006 grad_norm: 3.9331 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.7840 loss: 1.7840 2022/10/13 02:08:32 - mmengine - INFO - Epoch(train) [25][780/940] lr: 1.0000e-02 eta: 10:04:15 time: 0.4911 data_time: 0.0356 memory: 17006 grad_norm: 4.0655 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8597 loss: 1.8597 2022/10/13 02:08:43 - mmengine - INFO - Epoch(train) [25][800/940] lr: 1.0000e-02 eta: 10:04:06 time: 0.5303 data_time: 0.0293 memory: 17006 grad_norm: 4.1037 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 2.0266 loss: 2.0266 2022/10/13 02:08:53 - mmengine - INFO - Epoch(train) [25][820/940] lr: 1.0000e-02 eta: 10:03:56 time: 0.5135 data_time: 0.0333 memory: 17006 grad_norm: 4.0731 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7031 loss: 1.7031 2022/10/13 02:09:03 - mmengine - INFO - Epoch(train) [25][840/940] lr: 1.0000e-02 eta: 10:03:46 time: 0.5244 data_time: 0.0282 memory: 17006 grad_norm: 4.0638 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6788 loss: 1.6788 2022/10/13 02:09:14 - mmengine - INFO - Epoch(train) [25][860/940] lr: 1.0000e-02 eta: 10:03:37 time: 0.5338 data_time: 0.0274 memory: 17006 grad_norm: 4.0624 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7683 loss: 1.7683 2022/10/13 02:09:25 - mmengine - INFO - Epoch(train) [25][880/940] lr: 1.0000e-02 eta: 10:03:28 time: 0.5263 data_time: 0.0386 memory: 17006 grad_norm: 4.0926 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.8892 loss: 1.8892 2022/10/13 02:09:35 - mmengine - INFO - Epoch(train) [25][900/940] lr: 1.0000e-02 eta: 10:03:19 time: 0.5337 data_time: 0.0335 memory: 17006 grad_norm: 4.0513 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.8364 loss: 1.8364 2022/10/13 02:09:45 - mmengine - INFO - Epoch(train) [25][920/940] lr: 1.0000e-02 eta: 10:03:07 time: 0.4827 data_time: 0.0284 memory: 17006 grad_norm: 4.0813 top1_acc: 0.4688 top5_acc: 0.6250 loss_cls: 1.9653 loss: 1.9653 2022/10/13 02:09:55 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 02:09:55 - mmengine - INFO - Epoch(train) [25][940/940] lr: 1.0000e-02 eta: 10:02:55 time: 0.4969 data_time: 0.0236 memory: 17006 grad_norm: 4.2190 top1_acc: 0.1429 top5_acc: 0.7143 loss_cls: 1.7634 loss: 1.7634 2022/10/13 02:10:08 - mmengine - INFO - Epoch(val) [25][20/78] eta: 0:00:36 time: 0.6325 data_time: 0.5361 memory: 3172 2022/10/13 02:10:16 - mmengine - INFO - Epoch(val) [25][40/78] eta: 0:00:16 time: 0.4307 data_time: 0.3369 memory: 3172 2022/10/13 02:10:28 - mmengine - INFO - Epoch(val) [25][60/78] eta: 0:00:10 time: 0.5792 data_time: 0.4865 memory: 3172 2022/10/13 02:10:38 - mmengine - INFO - Epoch(val) [25][78/78] acc/top1: 0.6194 acc/top5: 0.8356 acc/mean1: 0.6192 2022/10/13 02:10:51 - mmengine - INFO - Epoch(train) [26][20/940] lr: 1.0000e-02 eta: 10:02:56 time: 0.6888 data_time: 0.3238 memory: 17006 grad_norm: 4.0279 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7117 loss: 1.7117 2022/10/13 02:11:01 - mmengine - INFO - Epoch(train) [26][40/940] lr: 1.0000e-02 eta: 10:02:45 time: 0.5050 data_time: 0.0995 memory: 17006 grad_norm: 4.0172 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7216 loss: 1.7216 2022/10/13 02:11:12 - mmengine - INFO - Epoch(train) [26][60/940] lr: 1.0000e-02 eta: 10:02:37 time: 0.5501 data_time: 0.0480 memory: 17006 grad_norm: 4.0422 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.6480 loss: 1.6480 2022/10/13 02:11:22 - mmengine - INFO - Epoch(train) [26][80/940] lr: 1.0000e-02 eta: 10:02:25 time: 0.4938 data_time: 0.0284 memory: 17006 grad_norm: 4.0091 top1_acc: 0.4375 top5_acc: 0.5938 loss_cls: 1.9482 loss: 1.9482 2022/10/13 02:11:33 - mmengine - INFO - Epoch(train) [26][100/940] lr: 1.0000e-02 eta: 10:02:17 time: 0.5495 data_time: 0.0385 memory: 17006 grad_norm: 4.0610 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.8964 loss: 1.8964 2022/10/13 02:11:43 - mmengine - INFO - Epoch(train) [26][120/940] lr: 1.0000e-02 eta: 10:02:05 time: 0.4813 data_time: 0.0260 memory: 17006 grad_norm: 4.0039 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8086 loss: 1.8086 2022/10/13 02:11:54 - mmengine - INFO - Epoch(train) [26][140/940] lr: 1.0000e-02 eta: 10:01:56 time: 0.5375 data_time: 0.0296 memory: 17006 grad_norm: 3.9899 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7391 loss: 1.7391 2022/10/13 02:12:03 - mmengine - INFO - Epoch(train) [26][160/940] lr: 1.0000e-02 eta: 10:01:44 time: 0.4836 data_time: 0.0306 memory: 17006 grad_norm: 3.9900 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6911 loss: 1.6911 2022/10/13 02:12:14 - mmengine - INFO - Epoch(train) [26][180/940] lr: 1.0000e-02 eta: 10:01:35 time: 0.5249 data_time: 0.0350 memory: 17006 grad_norm: 4.0151 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.8049 loss: 1.8049 2022/10/13 02:12:24 - mmengine - INFO - Epoch(train) [26][200/940] lr: 1.0000e-02 eta: 10:01:23 time: 0.4842 data_time: 0.0290 memory: 17006 grad_norm: 4.0336 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6729 loss: 1.6729 2022/10/13 02:12:35 - mmengine - INFO - Epoch(train) [26][220/940] lr: 1.0000e-02 eta: 10:01:15 time: 0.5606 data_time: 0.0353 memory: 17006 grad_norm: 4.0316 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7153 loss: 1.7153 2022/10/13 02:12:44 - mmengine - INFO - Epoch(train) [26][240/940] lr: 1.0000e-02 eta: 10:01:02 time: 0.4618 data_time: 0.0353 memory: 17006 grad_norm: 4.1300 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7401 loss: 1.7401 2022/10/13 02:12:55 - mmengine - INFO - Epoch(train) [26][260/940] lr: 1.0000e-02 eta: 10:00:55 time: 0.5645 data_time: 0.0315 memory: 17006 grad_norm: 4.1494 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7758 loss: 1.7758 2022/10/13 02:13:04 - mmengine - INFO - Epoch(train) [26][280/940] lr: 1.0000e-02 eta: 10:00:40 time: 0.4360 data_time: 0.0327 memory: 17006 grad_norm: 4.0285 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.7639 loss: 1.7639 2022/10/13 02:13:15 - mmengine - INFO - Epoch(train) [26][300/940] lr: 1.0000e-02 eta: 10:00:31 time: 0.5351 data_time: 0.0323 memory: 17006 grad_norm: 4.0975 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.8415 loss: 1.8415 2022/10/13 02:13:25 - mmengine - INFO - Epoch(train) [26][320/940] lr: 1.0000e-02 eta: 10:00:22 time: 0.5279 data_time: 0.0345 memory: 17006 grad_norm: 4.0689 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8539 loss: 1.8539 2022/10/13 02:13:35 - mmengine - INFO - Epoch(train) [26][340/940] lr: 1.0000e-02 eta: 10:00:10 time: 0.5004 data_time: 0.0292 memory: 17006 grad_norm: 3.9965 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6721 loss: 1.6721 2022/10/13 02:13:45 - mmengine - INFO - Epoch(train) [26][360/940] lr: 1.0000e-02 eta: 9:59:58 time: 0.4724 data_time: 0.0309 memory: 17006 grad_norm: 4.0476 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.8151 loss: 1.8151 2022/10/13 02:13:55 - mmengine - INFO - Epoch(train) [26][380/940] lr: 1.0000e-02 eta: 9:59:48 time: 0.5170 data_time: 0.0327 memory: 17006 grad_norm: 4.0345 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.7236 loss: 1.7236 2022/10/13 02:14:05 - mmengine - INFO - Epoch(train) [26][400/940] lr: 1.0000e-02 eta: 9:59:37 time: 0.4980 data_time: 0.0337 memory: 17006 grad_norm: 4.1384 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7053 loss: 1.7053 2022/10/13 02:14:16 - mmengine - INFO - Epoch(train) [26][420/940] lr: 1.0000e-02 eta: 9:59:27 time: 0.5305 data_time: 0.0315 memory: 17006 grad_norm: 3.9847 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7737 loss: 1.7737 2022/10/13 02:14:25 - mmengine - INFO - Epoch(train) [26][440/940] lr: 1.0000e-02 eta: 9:59:14 time: 0.4616 data_time: 0.0334 memory: 17006 grad_norm: 4.0896 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7789 loss: 1.7789 2022/10/13 02:14:35 - mmengine - INFO - Epoch(train) [26][460/940] lr: 1.0000e-02 eta: 9:59:04 time: 0.5161 data_time: 0.0319 memory: 17006 grad_norm: 4.0572 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 1.6989 loss: 1.6989 2022/10/13 02:14:45 - mmengine - INFO - Epoch(train) [26][480/940] lr: 1.0000e-02 eta: 9:58:53 time: 0.5015 data_time: 0.0314 memory: 17006 grad_norm: 3.9457 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.7470 loss: 1.7470 2022/10/13 02:14:55 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 02:14:55 - mmengine - INFO - Epoch(train) [26][500/940] lr: 1.0000e-02 eta: 9:58:42 time: 0.4920 data_time: 0.0578 memory: 17006 grad_norm: 4.1159 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8304 loss: 1.8304 2022/10/13 02:15:05 - mmengine - INFO - Epoch(train) [26][520/940] lr: 1.0000e-02 eta: 9:58:29 time: 0.4766 data_time: 0.0389 memory: 17006 grad_norm: 3.9696 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.9903 loss: 1.9903 2022/10/13 02:15:16 - mmengine - INFO - Epoch(train) [26][540/940] lr: 1.0000e-02 eta: 9:58:21 time: 0.5537 data_time: 0.1017 memory: 17006 grad_norm: 4.1130 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.9611 loss: 1.9611 2022/10/13 02:15:25 - mmengine - INFO - Epoch(train) [26][560/940] lr: 1.0000e-02 eta: 9:58:09 time: 0.4879 data_time: 0.0482 memory: 17006 grad_norm: 4.1058 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7804 loss: 1.7804 2022/10/13 02:15:36 - mmengine - INFO - Epoch(train) [26][580/940] lr: 1.0000e-02 eta: 9:58:02 time: 0.5524 data_time: 0.1947 memory: 17006 grad_norm: 4.0832 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.8262 loss: 1.8262 2022/10/13 02:15:46 - mmengine - INFO - Epoch(train) [26][600/940] lr: 1.0000e-02 eta: 9:57:48 time: 0.4618 data_time: 0.1121 memory: 17006 grad_norm: 4.0401 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6939 loss: 1.6939 2022/10/13 02:15:56 - mmengine - INFO - Epoch(train) [26][620/940] lr: 1.0000e-02 eta: 9:57:39 time: 0.5271 data_time: 0.1527 memory: 17006 grad_norm: 4.0459 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.8753 loss: 1.8753 2022/10/13 02:16:06 - mmengine - INFO - Epoch(train) [26][640/940] lr: 1.0000e-02 eta: 9:57:26 time: 0.4675 data_time: 0.0698 memory: 17006 grad_norm: 4.0416 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.7775 loss: 1.7775 2022/10/13 02:16:17 - mmengine - INFO - Epoch(train) [26][660/940] lr: 1.0000e-02 eta: 9:57:18 time: 0.5553 data_time: 0.1038 memory: 17006 grad_norm: 4.1282 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9135 loss: 1.9135 2022/10/13 02:16:27 - mmengine - INFO - Epoch(train) [26][680/940] lr: 1.0000e-02 eta: 9:57:07 time: 0.5008 data_time: 0.0267 memory: 17006 grad_norm: 4.1203 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8544 loss: 1.8544 2022/10/13 02:16:38 - mmengine - INFO - Epoch(train) [26][700/940] lr: 1.0000e-02 eta: 9:56:59 time: 0.5482 data_time: 0.0340 memory: 17006 grad_norm: 4.0006 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8201 loss: 1.8201 2022/10/13 02:16:48 - mmengine - INFO - Epoch(train) [26][720/940] lr: 1.0000e-02 eta: 9:56:48 time: 0.5075 data_time: 0.0308 memory: 17006 grad_norm: 4.0318 top1_acc: 0.3438 top5_acc: 0.5312 loss_cls: 1.7798 loss: 1.7798 2022/10/13 02:16:59 - mmengine - INFO - Epoch(train) [26][740/940] lr: 1.0000e-02 eta: 9:56:40 time: 0.5460 data_time: 0.0282 memory: 17006 grad_norm: 4.0075 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7123 loss: 1.7123 2022/10/13 02:17:08 - mmengine - INFO - Epoch(train) [26][760/940] lr: 1.0000e-02 eta: 9:56:27 time: 0.4683 data_time: 0.0354 memory: 17006 grad_norm: 4.0137 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.8495 loss: 1.8495 2022/10/13 02:17:19 - mmengine - INFO - Epoch(train) [26][780/940] lr: 1.0000e-02 eta: 9:56:20 time: 0.5612 data_time: 0.0283 memory: 17006 grad_norm: 4.1243 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6825 loss: 1.6825 2022/10/13 02:17:29 - mmengine - INFO - Epoch(train) [26][800/940] lr: 1.0000e-02 eta: 9:56:09 time: 0.5062 data_time: 0.0279 memory: 17006 grad_norm: 4.0956 top1_acc: 0.3750 top5_acc: 0.6562 loss_cls: 1.8367 loss: 1.8367 2022/10/13 02:17:40 - mmengine - INFO - Epoch(train) [26][820/940] lr: 1.0000e-02 eta: 9:56:00 time: 0.5287 data_time: 0.0266 memory: 17006 grad_norm: 4.1303 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.8273 loss: 1.8273 2022/10/13 02:17:49 - mmengine - INFO - Epoch(train) [26][840/940] lr: 1.0000e-02 eta: 9:55:47 time: 0.4692 data_time: 0.0274 memory: 17006 grad_norm: 4.0763 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6722 loss: 1.6722 2022/10/13 02:18:00 - mmengine - INFO - Epoch(train) [26][860/940] lr: 1.0000e-02 eta: 9:55:38 time: 0.5438 data_time: 0.0312 memory: 17006 grad_norm: 4.1376 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 2.0078 loss: 2.0078 2022/10/13 02:18:11 - mmengine - INFO - Epoch(train) [26][880/940] lr: 1.0000e-02 eta: 9:55:28 time: 0.5146 data_time: 0.0379 memory: 17006 grad_norm: 4.0787 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7760 loss: 1.7760 2022/10/13 02:18:21 - mmengine - INFO - Epoch(train) [26][900/940] lr: 1.0000e-02 eta: 9:55:17 time: 0.5074 data_time: 0.0316 memory: 17006 grad_norm: 4.0739 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7794 loss: 1.7794 2022/10/13 02:18:29 - mmengine - INFO - Epoch(train) [26][920/940] lr: 1.0000e-02 eta: 9:55:02 time: 0.4229 data_time: 0.0365 memory: 17006 grad_norm: 4.1351 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7852 loss: 1.7852 2022/10/13 02:18:38 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 02:18:38 - mmengine - INFO - Epoch(train) [26][940/940] lr: 1.0000e-02 eta: 9:54:48 time: 0.4549 data_time: 0.0240 memory: 17006 grad_norm: 4.2860 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.9503 loss: 1.9503 2022/10/13 02:18:51 - mmengine - INFO - Epoch(val) [26][20/78] eta: 0:00:36 time: 0.6298 data_time: 0.5333 memory: 3172 2022/10/13 02:19:00 - mmengine - INFO - Epoch(val) [26][40/78] eta: 0:00:16 time: 0.4318 data_time: 0.3415 memory: 3172 2022/10/13 02:19:11 - mmengine - INFO - Epoch(val) [26][60/78] eta: 0:00:10 time: 0.5756 data_time: 0.4849 memory: 3172 2022/10/13 02:19:21 - mmengine - INFO - Epoch(val) [26][78/78] acc/top1: 0.6229 acc/top5: 0.8401 acc/mean1: 0.6228 2022/10/13 02:19:21 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_22.pth is removed 2022/10/13 02:19:21 - mmengine - INFO - The best checkpoint with 0.6229 acc/top1 at 26 epoch is saved to best_acc/top1_epoch_26.pth. 2022/10/13 02:19:34 - mmengine - INFO - Epoch(train) [27][20/940] lr: 1.0000e-02 eta: 9:54:46 time: 0.6543 data_time: 0.3449 memory: 17006 grad_norm: 4.0863 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6862 loss: 1.6862 2022/10/13 02:19:45 - mmengine - INFO - Epoch(train) [27][40/940] lr: 1.0000e-02 eta: 9:54:36 time: 0.5106 data_time: 0.1013 memory: 17006 grad_norm: 4.0023 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7329 loss: 1.7329 2022/10/13 02:19:55 - mmengine - INFO - Epoch(train) [27][60/940] lr: 1.0000e-02 eta: 9:54:25 time: 0.5121 data_time: 0.0403 memory: 17006 grad_norm: 3.9564 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.7634 loss: 1.7634 2022/10/13 02:20:05 - mmengine - INFO - Epoch(train) [27][80/940] lr: 1.0000e-02 eta: 9:54:14 time: 0.4929 data_time: 0.0278 memory: 17006 grad_norm: 4.0771 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7701 loss: 1.7701 2022/10/13 02:20:16 - mmengine - INFO - Epoch(train) [27][100/940] lr: 1.0000e-02 eta: 9:54:07 time: 0.5753 data_time: 0.0291 memory: 17006 grad_norm: 4.0210 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6692 loss: 1.6692 2022/10/13 02:20:26 - mmengine - INFO - Epoch(train) [27][120/940] lr: 1.0000e-02 eta: 9:53:55 time: 0.4839 data_time: 0.0283 memory: 17006 grad_norm: 4.0010 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7212 loss: 1.7212 2022/10/13 02:20:36 - mmengine - INFO - Epoch(train) [27][140/940] lr: 1.0000e-02 eta: 9:53:46 time: 0.5254 data_time: 0.0311 memory: 17006 grad_norm: 4.0642 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8279 loss: 1.8279 2022/10/13 02:20:45 - mmengine - INFO - Epoch(train) [27][160/940] lr: 1.0000e-02 eta: 9:53:32 time: 0.4465 data_time: 0.0328 memory: 17006 grad_norm: 4.1789 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6983 loss: 1.6983 2022/10/13 02:20:57 - mmengine - INFO - Epoch(train) [27][180/940] lr: 1.0000e-02 eta: 9:53:25 time: 0.5715 data_time: 0.0350 memory: 17006 grad_norm: 4.0688 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6887 loss: 1.6887 2022/10/13 02:21:06 - mmengine - INFO - Epoch(train) [27][200/940] lr: 1.0000e-02 eta: 9:53:12 time: 0.4668 data_time: 0.0358 memory: 17006 grad_norm: 4.0157 top1_acc: 0.3750 top5_acc: 0.9062 loss_cls: 1.6930 loss: 1.6930 2022/10/13 02:21:17 - mmengine - INFO - Epoch(train) [27][220/940] lr: 1.0000e-02 eta: 9:53:05 time: 0.5633 data_time: 0.0344 memory: 17006 grad_norm: 4.0151 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.7625 loss: 1.7625 2022/10/13 02:21:27 - mmengine - INFO - Epoch(train) [27][240/940] lr: 1.0000e-02 eta: 9:52:52 time: 0.4752 data_time: 0.0335 memory: 17006 grad_norm: 4.0484 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7946 loss: 1.7946 2022/10/13 02:21:37 - mmengine - INFO - Epoch(train) [27][260/940] lr: 1.0000e-02 eta: 9:52:42 time: 0.5236 data_time: 0.0311 memory: 17006 grad_norm: 4.0077 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.7385 loss: 1.7385 2022/10/13 02:21:47 - mmengine - INFO - Epoch(train) [27][280/940] lr: 1.0000e-02 eta: 9:52:32 time: 0.5027 data_time: 0.0342 memory: 17006 grad_norm: 4.1764 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8718 loss: 1.8718 2022/10/13 02:21:58 - mmengine - INFO - Epoch(train) [27][300/940] lr: 1.0000e-02 eta: 9:52:23 time: 0.5519 data_time: 0.0300 memory: 17006 grad_norm: 3.9798 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7448 loss: 1.7448 2022/10/13 02:22:07 - mmengine - INFO - Epoch(train) [27][320/940] lr: 1.0000e-02 eta: 9:52:09 time: 0.4292 data_time: 0.0327 memory: 17006 grad_norm: 4.0694 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8718 loss: 1.8718 2022/10/13 02:22:18 - mmengine - INFO - Epoch(train) [27][340/940] lr: 1.0000e-02 eta: 9:52:00 time: 0.5455 data_time: 0.0371 memory: 17006 grad_norm: 4.0360 top1_acc: 0.4688 top5_acc: 0.9062 loss_cls: 1.7217 loss: 1.7217 2022/10/13 02:22:27 - mmengine - INFO - Epoch(train) [27][360/940] lr: 1.0000e-02 eta: 9:51:46 time: 0.4494 data_time: 0.0306 memory: 17006 grad_norm: 4.0405 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.8178 loss: 1.8178 2022/10/13 02:22:38 - mmengine - INFO - Epoch(train) [27][380/940] lr: 1.0000e-02 eta: 9:51:39 time: 0.5716 data_time: 0.0323 memory: 17006 grad_norm: 4.0664 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.7272 loss: 1.7272 2022/10/13 02:22:48 - mmengine - INFO - Epoch(train) [27][400/940] lr: 1.0000e-02 eta: 9:51:27 time: 0.4687 data_time: 0.0395 memory: 17006 grad_norm: 4.1128 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8778 loss: 1.8778 2022/10/13 02:22:58 - mmengine - INFO - Epoch(train) [27][420/940] lr: 1.0000e-02 eta: 9:51:17 time: 0.5248 data_time: 0.0324 memory: 17006 grad_norm: 4.1160 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.6831 loss: 1.6831 2022/10/13 02:23:09 - mmengine - INFO - Epoch(train) [27][440/940] lr: 1.0000e-02 eta: 9:51:07 time: 0.5257 data_time: 0.0362 memory: 17006 grad_norm: 4.0873 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7698 loss: 1.7698 2022/10/13 02:23:20 - mmengine - INFO - Epoch(train) [27][460/940] lr: 1.0000e-02 eta: 9:51:00 time: 0.5700 data_time: 0.0296 memory: 17006 grad_norm: 4.0808 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8539 loss: 1.8539 2022/10/13 02:23:30 - mmengine - INFO - Epoch(train) [27][480/940] lr: 1.0000e-02 eta: 9:50:49 time: 0.5021 data_time: 0.0276 memory: 17006 grad_norm: 4.0644 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.9239 loss: 1.9239 2022/10/13 02:23:40 - mmengine - INFO - Epoch(train) [27][500/940] lr: 1.0000e-02 eta: 9:50:38 time: 0.4925 data_time: 0.0315 memory: 17006 grad_norm: 4.1334 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7789 loss: 1.7789 2022/10/13 02:23:50 - mmengine - INFO - Epoch(train) [27][520/940] lr: 1.0000e-02 eta: 9:50:27 time: 0.4927 data_time: 0.0321 memory: 17006 grad_norm: 4.1100 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7330 loss: 1.7330 2022/10/13 02:24:01 - mmengine - INFO - Epoch(train) [27][540/940] lr: 1.0000e-02 eta: 9:50:20 time: 0.5745 data_time: 0.0288 memory: 17006 grad_norm: 4.1348 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7193 loss: 1.7193 2022/10/13 02:24:11 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 02:24:11 - mmengine - INFO - Epoch(train) [27][560/940] lr: 1.0000e-02 eta: 9:50:08 time: 0.4796 data_time: 0.0358 memory: 17006 grad_norm: 4.0552 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6698 loss: 1.6698 2022/10/13 02:24:21 - mmengine - INFO - Epoch(train) [27][580/940] lr: 1.0000e-02 eta: 9:49:57 time: 0.5067 data_time: 0.0325 memory: 17006 grad_norm: 4.0549 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.7951 loss: 1.7951 2022/10/13 02:24:31 - mmengine - INFO - Epoch(train) [27][600/940] lr: 1.0000e-02 eta: 9:49:44 time: 0.4729 data_time: 0.0301 memory: 17006 grad_norm: 4.1480 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6653 loss: 1.6653 2022/10/13 02:24:42 - mmengine - INFO - Epoch(train) [27][620/940] lr: 1.0000e-02 eta: 9:49:37 time: 0.5700 data_time: 0.0294 memory: 17006 grad_norm: 4.1097 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7201 loss: 1.7201 2022/10/13 02:24:52 - mmengine - INFO - Epoch(train) [27][640/940] lr: 1.0000e-02 eta: 9:49:25 time: 0.4838 data_time: 0.0378 memory: 17006 grad_norm: 4.0792 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8196 loss: 1.8196 2022/10/13 02:25:03 - mmengine - INFO - Epoch(train) [27][660/940] lr: 1.0000e-02 eta: 9:49:17 time: 0.5455 data_time: 0.0312 memory: 17006 grad_norm: 4.0614 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7975 loss: 1.7975 2022/10/13 02:25:11 - mmengine - INFO - Epoch(train) [27][680/940] lr: 1.0000e-02 eta: 9:49:03 time: 0.4382 data_time: 0.0317 memory: 17006 grad_norm: 4.0696 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6434 loss: 1.6434 2022/10/13 02:25:21 - mmengine - INFO - Epoch(train) [27][700/940] lr: 1.0000e-02 eta: 9:48:52 time: 0.4985 data_time: 0.0305 memory: 17006 grad_norm: 4.0815 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6464 loss: 1.6464 2022/10/13 02:25:31 - mmengine - INFO - Epoch(train) [27][720/940] lr: 1.0000e-02 eta: 9:48:39 time: 0.4670 data_time: 0.0333 memory: 17006 grad_norm: 4.1031 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7509 loss: 1.7509 2022/10/13 02:25:42 - mmengine - INFO - Epoch(train) [27][740/940] lr: 1.0000e-02 eta: 9:48:31 time: 0.5586 data_time: 0.0326 memory: 17006 grad_norm: 4.0974 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.6772 loss: 1.6772 2022/10/13 02:25:51 - mmengine - INFO - Epoch(train) [27][760/940] lr: 1.0000e-02 eta: 9:48:19 time: 0.4761 data_time: 0.0303 memory: 17006 grad_norm: 4.0384 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6984 loss: 1.6984 2022/10/13 02:26:02 - mmengine - INFO - Epoch(train) [27][780/940] lr: 1.0000e-02 eta: 9:48:10 time: 0.5379 data_time: 0.0365 memory: 17006 grad_norm: 4.0208 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7645 loss: 1.7645 2022/10/13 02:26:12 - mmengine - INFO - Epoch(train) [27][800/940] lr: 1.0000e-02 eta: 9:47:58 time: 0.4940 data_time: 0.0354 memory: 17006 grad_norm: 4.0937 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7396 loss: 1.7396 2022/10/13 02:26:22 - mmengine - INFO - Epoch(train) [27][820/940] lr: 1.0000e-02 eta: 9:47:48 time: 0.5148 data_time: 0.0327 memory: 17006 grad_norm: 4.0406 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7135 loss: 1.7135 2022/10/13 02:26:31 - mmengine - INFO - Epoch(train) [27][840/940] lr: 1.0000e-02 eta: 9:47:35 time: 0.4588 data_time: 0.0318 memory: 17006 grad_norm: 4.1022 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.6813 loss: 1.6813 2022/10/13 02:26:43 - mmengine - INFO - Epoch(train) [27][860/940] lr: 1.0000e-02 eta: 9:47:27 time: 0.5587 data_time: 0.0309 memory: 17006 grad_norm: 4.0908 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.7501 loss: 1.7501 2022/10/13 02:26:52 - mmengine - INFO - Epoch(train) [27][880/940] lr: 1.0000e-02 eta: 9:47:15 time: 0.4713 data_time: 0.0319 memory: 17006 grad_norm: 4.1122 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.9942 loss: 1.9942 2022/10/13 02:27:02 - mmengine - INFO - Epoch(train) [27][900/940] lr: 1.0000e-02 eta: 9:47:04 time: 0.5014 data_time: 0.0355 memory: 17006 grad_norm: 4.1219 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8221 loss: 1.8221 2022/10/13 02:27:12 - mmengine - INFO - Epoch(train) [27][920/940] lr: 1.0000e-02 eta: 9:46:52 time: 0.4764 data_time: 0.0422 memory: 17006 grad_norm: 4.1072 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7338 loss: 1.7338 2022/10/13 02:27:22 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 02:27:22 - mmengine - INFO - Epoch(train) [27][940/940] lr: 1.0000e-02 eta: 9:46:42 time: 0.5170 data_time: 0.0290 memory: 17006 grad_norm: 4.2288 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.7372 loss: 1.7372 2022/10/13 02:27:22 - mmengine - INFO - Saving checkpoint at 27 epochs 2022/10/13 02:27:35 - mmengine - INFO - Epoch(val) [27][20/78] eta: 0:00:36 time: 0.6249 data_time: 0.5336 memory: 3172 2022/10/13 02:27:44 - mmengine - INFO - Epoch(val) [27][40/78] eta: 0:00:16 time: 0.4248 data_time: 0.3362 memory: 3172 2022/10/13 02:27:55 - mmengine - INFO - Epoch(val) [27][60/78] eta: 0:00:10 time: 0.5808 data_time: 0.4906 memory: 3172 2022/10/13 02:28:04 - mmengine - INFO - Epoch(val) [27][78/78] acc/top1: 0.6225 acc/top5: 0.8413 acc/mean1: 0.6224 2022/10/13 02:28:19 - mmengine - INFO - Epoch(train) [28][20/940] lr: 1.0000e-02 eta: 9:46:42 time: 0.7069 data_time: 0.2092 memory: 17006 grad_norm: 4.0334 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7665 loss: 1.7665 2022/10/13 02:28:29 - mmengine - INFO - Epoch(train) [28][40/940] lr: 1.0000e-02 eta: 9:46:31 time: 0.5002 data_time: 0.0254 memory: 17006 grad_norm: 4.0541 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.8366 loss: 1.8366 2022/10/13 02:28:40 - mmengine - INFO - Epoch(train) [28][60/940] lr: 1.0000e-02 eta: 9:46:23 time: 0.5652 data_time: 0.0341 memory: 17006 grad_norm: 3.9869 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.7087 loss: 1.7087 2022/10/13 02:28:49 - mmengine - INFO - Epoch(train) [28][80/940] lr: 1.0000e-02 eta: 9:46:11 time: 0.4765 data_time: 0.0283 memory: 17006 grad_norm: 4.0598 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.7590 loss: 1.7590 2022/10/13 02:29:00 - mmengine - INFO - Epoch(train) [28][100/940] lr: 1.0000e-02 eta: 9:46:02 time: 0.5328 data_time: 0.0308 memory: 17006 grad_norm: 3.9784 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.6766 loss: 1.6766 2022/10/13 02:29:09 - mmengine - INFO - Epoch(train) [28][120/940] lr: 1.0000e-02 eta: 9:45:48 time: 0.4483 data_time: 0.0319 memory: 17006 grad_norm: 3.9975 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7294 loss: 1.7294 2022/10/13 02:29:21 - mmengine - INFO - Epoch(train) [28][140/940] lr: 1.0000e-02 eta: 9:45:42 time: 0.5886 data_time: 0.0291 memory: 17006 grad_norm: 4.0509 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.8477 loss: 1.8477 2022/10/13 02:29:30 - mmengine - INFO - Epoch(train) [28][160/940] lr: 1.0000e-02 eta: 9:45:30 time: 0.4759 data_time: 0.0304 memory: 17006 grad_norm: 4.1079 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7890 loss: 1.7890 2022/10/13 02:29:41 - mmengine - INFO - Epoch(train) [28][180/940] lr: 1.0000e-02 eta: 9:45:22 time: 0.5551 data_time: 0.0291 memory: 17006 grad_norm: 4.1119 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.6566 loss: 1.6566 2022/10/13 02:29:50 - mmengine - INFO - Epoch(train) [28][200/940] lr: 1.0000e-02 eta: 9:45:08 time: 0.4495 data_time: 0.0307 memory: 17006 grad_norm: 4.0685 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7163 loss: 1.7163 2022/10/13 02:30:00 - mmengine - INFO - Epoch(train) [28][220/940] lr: 1.0000e-02 eta: 9:44:57 time: 0.5038 data_time: 0.0282 memory: 17006 grad_norm: 4.1159 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.8516 loss: 1.8516 2022/10/13 02:30:10 - mmengine - INFO - Epoch(train) [28][240/940] lr: 1.0000e-02 eta: 9:44:44 time: 0.4556 data_time: 0.0339 memory: 17006 grad_norm: 4.1038 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.4650 loss: 1.4650 2022/10/13 02:30:21 - mmengine - INFO - Epoch(train) [28][260/940] lr: 1.0000e-02 eta: 9:44:36 time: 0.5485 data_time: 0.0358 memory: 17006 grad_norm: 4.1257 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8150 loss: 1.8150 2022/10/13 02:30:31 - mmengine - INFO - Epoch(train) [28][280/940] lr: 1.0000e-02 eta: 9:44:25 time: 0.5117 data_time: 0.0372 memory: 17006 grad_norm: 4.1421 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.7254 loss: 1.7254 2022/10/13 02:30:42 - mmengine - INFO - Epoch(train) [28][300/940] lr: 1.0000e-02 eta: 9:44:18 time: 0.5644 data_time: 0.0307 memory: 17006 grad_norm: 4.1513 top1_acc: 0.4375 top5_acc: 0.6250 loss_cls: 1.7140 loss: 1.7140 2022/10/13 02:30:51 - mmengine - INFO - Epoch(train) [28][320/940] lr: 1.0000e-02 eta: 9:44:05 time: 0.4710 data_time: 0.0324 memory: 17006 grad_norm: 4.1264 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.8398 loss: 1.8398 2022/10/13 02:31:02 - mmengine - INFO - Epoch(train) [28][340/940] lr: 1.0000e-02 eta: 9:43:56 time: 0.5407 data_time: 0.0318 memory: 17006 grad_norm: 4.1338 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.7769 loss: 1.7769 2022/10/13 02:31:13 - mmengine - INFO - Epoch(train) [28][360/940] lr: 1.0000e-02 eta: 9:43:47 time: 0.5276 data_time: 0.0391 memory: 17006 grad_norm: 4.1263 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.8239 loss: 1.8239 2022/10/13 02:31:23 - mmengine - INFO - Epoch(train) [28][380/940] lr: 1.0000e-02 eta: 9:43:37 time: 0.5230 data_time: 0.0305 memory: 17006 grad_norm: 4.1222 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8298 loss: 1.8298 2022/10/13 02:31:34 - mmengine - INFO - Epoch(train) [28][400/940] lr: 1.0000e-02 eta: 9:43:27 time: 0.5119 data_time: 0.0363 memory: 17006 grad_norm: 4.1009 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.7231 loss: 1.7231 2022/10/13 02:31:44 - mmengine - INFO - Epoch(train) [28][420/940] lr: 1.0000e-02 eta: 9:43:16 time: 0.5031 data_time: 0.0352 memory: 17006 grad_norm: 4.1642 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.8275 loss: 1.8275 2022/10/13 02:31:54 - mmengine - INFO - Epoch(train) [28][440/940] lr: 1.0000e-02 eta: 9:43:06 time: 0.5170 data_time: 0.0279 memory: 17006 grad_norm: 4.0862 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7136 loss: 1.7136 2022/10/13 02:32:03 - mmengine - INFO - Epoch(train) [28][460/940] lr: 1.0000e-02 eta: 9:42:52 time: 0.4480 data_time: 0.0334 memory: 17006 grad_norm: 4.1268 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.7385 loss: 1.7385 2022/10/13 02:32:13 - mmengine - INFO - Epoch(train) [28][480/940] lr: 1.0000e-02 eta: 9:42:41 time: 0.4967 data_time: 0.0275 memory: 17006 grad_norm: 4.1019 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7993 loss: 1.7993 2022/10/13 02:32:23 - mmengine - INFO - Epoch(train) [28][500/940] lr: 1.0000e-02 eta: 9:42:31 time: 0.5078 data_time: 0.0312 memory: 17006 grad_norm: 4.0596 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.8298 loss: 1.8298 2022/10/13 02:32:33 - mmengine - INFO - Epoch(train) [28][520/940] lr: 1.0000e-02 eta: 9:42:21 time: 0.5192 data_time: 0.0283 memory: 17006 grad_norm: 4.1529 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8890 loss: 1.8890 2022/10/13 02:32:44 - mmengine - INFO - Epoch(train) [28][540/940] lr: 1.0000e-02 eta: 9:42:12 time: 0.5453 data_time: 0.0319 memory: 17006 grad_norm: 4.0225 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.6326 loss: 1.6326 2022/10/13 02:32:54 - mmengine - INFO - Epoch(train) [28][560/940] lr: 1.0000e-02 eta: 9:42:01 time: 0.4958 data_time: 0.0349 memory: 17006 grad_norm: 4.1509 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.8677 loss: 1.8677 2022/10/13 02:33:04 - mmengine - INFO - Epoch(train) [28][580/940] lr: 1.0000e-02 eta: 9:41:51 time: 0.5132 data_time: 0.0270 memory: 17006 grad_norm: 4.0611 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7892 loss: 1.7892 2022/10/13 02:33:14 - mmengine - INFO - Epoch(train) [28][600/940] lr: 1.0000e-02 eta: 9:41:38 time: 0.4701 data_time: 0.0307 memory: 17006 grad_norm: 4.1287 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.7759 loss: 1.7759 2022/10/13 02:33:25 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 02:33:25 - mmengine - INFO - Epoch(train) [28][620/940] lr: 1.0000e-02 eta: 9:41:30 time: 0.5573 data_time: 0.0364 memory: 17006 grad_norm: 4.0622 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.9823 loss: 1.9823 2022/10/13 02:33:34 - mmengine - INFO - Epoch(train) [28][640/940] lr: 1.0000e-02 eta: 9:41:18 time: 0.4723 data_time: 0.0295 memory: 17006 grad_norm: 4.2591 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8634 loss: 1.8634 2022/10/13 02:33:45 - mmengine - INFO - Epoch(train) [28][660/940] lr: 1.0000e-02 eta: 9:41:09 time: 0.5312 data_time: 0.0273 memory: 17006 grad_norm: 4.0505 top1_acc: 0.5938 top5_acc: 0.6562 loss_cls: 1.8656 loss: 1.8656 2022/10/13 02:33:55 - mmengine - INFO - Epoch(train) [28][680/940] lr: 1.0000e-02 eta: 9:40:58 time: 0.5058 data_time: 0.0347 memory: 17006 grad_norm: 4.0633 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8756 loss: 1.8756 2022/10/13 02:34:06 - mmengine - INFO - Epoch(train) [28][700/940] lr: 1.0000e-02 eta: 9:40:48 time: 0.5180 data_time: 0.0280 memory: 17006 grad_norm: 4.1208 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8084 loss: 1.8084 2022/10/13 02:34:15 - mmengine - INFO - Epoch(train) [28][720/940] lr: 1.0000e-02 eta: 9:40:35 time: 0.4541 data_time: 0.0332 memory: 17006 grad_norm: 4.0829 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7971 loss: 1.7971 2022/10/13 02:34:26 - mmengine - INFO - Epoch(train) [28][740/940] lr: 1.0000e-02 eta: 9:40:27 time: 0.5665 data_time: 0.0363 memory: 17006 grad_norm: 4.1410 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.9223 loss: 1.9223 2022/10/13 02:34:36 - mmengine - INFO - Epoch(train) [28][760/940] lr: 1.0000e-02 eta: 9:40:15 time: 0.4792 data_time: 0.0346 memory: 17006 grad_norm: 3.9950 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.8106 loss: 1.8106 2022/10/13 02:34:46 - mmengine - INFO - Epoch(train) [28][780/940] lr: 1.0000e-02 eta: 9:40:06 time: 0.5434 data_time: 0.0339 memory: 17006 grad_norm: 4.0624 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.7132 loss: 1.7132 2022/10/13 02:34:57 - mmengine - INFO - Epoch(train) [28][800/940] lr: 1.0000e-02 eta: 9:39:56 time: 0.5073 data_time: 0.0324 memory: 17006 grad_norm: 4.0326 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.8292 loss: 1.8292 2022/10/13 02:35:07 - mmengine - INFO - Epoch(train) [28][820/940] lr: 1.0000e-02 eta: 9:39:47 time: 0.5455 data_time: 0.0267 memory: 17006 grad_norm: 4.0744 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8432 loss: 1.8432 2022/10/13 02:35:17 - mmengine - INFO - Epoch(train) [28][840/940] lr: 1.0000e-02 eta: 9:39:34 time: 0.4640 data_time: 0.0316 memory: 17006 grad_norm: 4.1129 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7234 loss: 1.7234 2022/10/13 02:35:28 - mmengine - INFO - Epoch(train) [28][860/940] lr: 1.0000e-02 eta: 9:39:28 time: 0.5818 data_time: 0.0338 memory: 17006 grad_norm: 4.1306 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8115 loss: 1.8115 2022/10/13 02:35:38 - mmengine - INFO - Epoch(train) [28][880/940] lr: 1.0000e-02 eta: 9:39:16 time: 0.4806 data_time: 0.0300 memory: 17006 grad_norm: 4.0569 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6890 loss: 1.6890 2022/10/13 02:35:48 - mmengine - INFO - Epoch(train) [28][900/940] lr: 1.0000e-02 eta: 9:39:05 time: 0.4944 data_time: 0.0369 memory: 17006 grad_norm: 4.1415 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7319 loss: 1.7319 2022/10/13 02:35:58 - mmengine - INFO - Epoch(train) [28][920/940] lr: 1.0000e-02 eta: 9:38:53 time: 0.4802 data_time: 0.0321 memory: 17006 grad_norm: 4.0531 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7305 loss: 1.7305 2022/10/13 02:36:07 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 02:36:07 - mmengine - INFO - Epoch(train) [28][940/940] lr: 1.0000e-02 eta: 9:38:41 time: 0.4847 data_time: 0.0259 memory: 17006 grad_norm: 4.2141 top1_acc: 0.2857 top5_acc: 0.4286 loss_cls: 1.9317 loss: 1.9317 2022/10/13 02:36:20 - mmengine - INFO - Epoch(val) [28][20/78] eta: 0:00:36 time: 0.6226 data_time: 0.5301 memory: 3172 2022/10/13 02:36:28 - mmengine - INFO - Epoch(val) [28][40/78] eta: 0:00:16 time: 0.4282 data_time: 0.3371 memory: 3172 2022/10/13 02:36:40 - mmengine - INFO - Epoch(val) [28][60/78] eta: 0:00:10 time: 0.5779 data_time: 0.4866 memory: 3172 2022/10/13 02:36:50 - mmengine - INFO - Epoch(val) [28][78/78] acc/top1: 0.6237 acc/top5: 0.8413 acc/mean1: 0.6235 2022/10/13 02:36:50 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_26.pth is removed 2022/10/13 02:36:50 - mmengine - INFO - The best checkpoint with 0.6237 acc/top1 at 28 epoch is saved to best_acc/top1_epoch_28.pth. 2022/10/13 02:37:04 - mmengine - INFO - Epoch(train) [29][20/940] lr: 1.0000e-02 eta: 9:38:38 time: 0.6608 data_time: 0.3471 memory: 17006 grad_norm: 3.9832 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7026 loss: 1.7026 2022/10/13 02:37:13 - mmengine - INFO - Epoch(train) [29][40/940] lr: 1.0000e-02 eta: 9:38:26 time: 0.4740 data_time: 0.1278 memory: 17006 grad_norm: 4.1194 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7629 loss: 1.7629 2022/10/13 02:37:24 - mmengine - INFO - Epoch(train) [29][60/940] lr: 1.0000e-02 eta: 9:38:18 time: 0.5597 data_time: 0.0816 memory: 17006 grad_norm: 4.0276 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6498 loss: 1.6498 2022/10/13 02:37:34 - mmengine - INFO - Epoch(train) [29][80/940] lr: 1.0000e-02 eta: 9:38:06 time: 0.4850 data_time: 0.1275 memory: 17006 grad_norm: 4.0529 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5831 loss: 1.5831 2022/10/13 02:37:45 - mmengine - INFO - Epoch(train) [29][100/940] lr: 1.0000e-02 eta: 9:37:59 time: 0.5627 data_time: 0.1303 memory: 17006 grad_norm: 4.0800 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.8170 loss: 1.8170 2022/10/13 02:37:54 - mmengine - INFO - Epoch(train) [29][120/940] lr: 1.0000e-02 eta: 9:37:45 time: 0.4457 data_time: 0.0409 memory: 17006 grad_norm: 4.0169 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.6964 loss: 1.6964 2022/10/13 02:38:05 - mmengine - INFO - Epoch(train) [29][140/940] lr: 1.0000e-02 eta: 9:37:37 time: 0.5577 data_time: 0.0659 memory: 17006 grad_norm: 4.0735 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.6478 loss: 1.6478 2022/10/13 02:38:15 - mmengine - INFO - Epoch(train) [29][160/940] lr: 1.0000e-02 eta: 9:37:26 time: 0.4916 data_time: 0.0817 memory: 17006 grad_norm: 4.0378 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6277 loss: 1.6277 2022/10/13 02:38:26 - mmengine - INFO - Epoch(train) [29][180/940] lr: 1.0000e-02 eta: 9:37:17 time: 0.5457 data_time: 0.0396 memory: 17006 grad_norm: 4.0544 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.7370 loss: 1.7370 2022/10/13 02:38:36 - mmengine - INFO - Epoch(train) [29][200/940] lr: 1.0000e-02 eta: 9:37:06 time: 0.5037 data_time: 0.0748 memory: 17006 grad_norm: 4.0807 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6832 loss: 1.6832 2022/10/13 02:38:47 - mmengine - INFO - Epoch(train) [29][220/940] lr: 1.0000e-02 eta: 9:36:58 time: 0.5466 data_time: 0.0329 memory: 17006 grad_norm: 4.1296 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7735 loss: 1.7735 2022/10/13 02:38:56 - mmengine - INFO - Epoch(train) [29][240/940] lr: 1.0000e-02 eta: 9:36:45 time: 0.4689 data_time: 0.0280 memory: 17006 grad_norm: 4.0847 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.5499 loss: 1.5499 2022/10/13 02:39:08 - mmengine - INFO - Epoch(train) [29][260/940] lr: 1.0000e-02 eta: 9:36:37 time: 0.5557 data_time: 0.0388 memory: 17006 grad_norm: 4.0614 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8250 loss: 1.8250 2022/10/13 02:39:17 - mmengine - INFO - Epoch(train) [29][280/940] lr: 1.0000e-02 eta: 9:36:24 time: 0.4500 data_time: 0.0293 memory: 17006 grad_norm: 4.0453 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.7785 loss: 1.7785 2022/10/13 02:39:27 - mmengine - INFO - Epoch(train) [29][300/940] lr: 1.0000e-02 eta: 9:36:13 time: 0.5030 data_time: 0.0516 memory: 17006 grad_norm: 4.2034 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7590 loss: 1.7590 2022/10/13 02:39:36 - mmengine - INFO - Epoch(train) [29][320/940] lr: 1.0000e-02 eta: 9:35:59 time: 0.4524 data_time: 0.0909 memory: 17006 grad_norm: 4.0902 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7592 loss: 1.7592 2022/10/13 02:39:46 - mmengine - INFO - Epoch(train) [29][340/940] lr: 1.0000e-02 eta: 9:35:49 time: 0.5103 data_time: 0.0943 memory: 17006 grad_norm: 4.2026 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7239 loss: 1.7239 2022/10/13 02:39:56 - mmengine - INFO - Epoch(train) [29][360/940] lr: 1.0000e-02 eta: 9:35:38 time: 0.5022 data_time: 0.0332 memory: 17006 grad_norm: 4.0778 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8588 loss: 1.8588 2022/10/13 02:40:06 - mmengine - INFO - Epoch(train) [29][380/940] lr: 1.0000e-02 eta: 9:35:28 time: 0.5131 data_time: 0.0686 memory: 17006 grad_norm: 4.1857 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.7641 loss: 1.7641 2022/10/13 02:40:17 - mmengine - INFO - Epoch(train) [29][400/940] lr: 1.0000e-02 eta: 9:35:18 time: 0.5252 data_time: 0.0556 memory: 17006 grad_norm: 4.1324 top1_acc: 0.7188 top5_acc: 0.7500 loss_cls: 1.7475 loss: 1.7475 2022/10/13 02:40:27 - mmengine - INFO - Epoch(train) [29][420/940] lr: 1.0000e-02 eta: 9:35:09 time: 0.5248 data_time: 0.0365 memory: 17006 grad_norm: 4.0988 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5711 loss: 1.5711 2022/10/13 02:40:37 - mmengine - INFO - Epoch(train) [29][440/940] lr: 1.0000e-02 eta: 9:34:58 time: 0.5119 data_time: 0.0328 memory: 17006 grad_norm: 4.1242 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6856 loss: 1.6856 2022/10/13 02:40:47 - mmengine - INFO - Epoch(train) [29][460/940] lr: 1.0000e-02 eta: 9:34:47 time: 0.4895 data_time: 0.0256 memory: 17006 grad_norm: 4.1183 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.8271 loss: 1.8271 2022/10/13 02:40:58 - mmengine - INFO - Epoch(train) [29][480/940] lr: 1.0000e-02 eta: 9:34:37 time: 0.5296 data_time: 0.0376 memory: 17006 grad_norm: 4.1433 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7772 loss: 1.7772 2022/10/13 02:41:07 - mmengine - INFO - Epoch(train) [29][500/940] lr: 1.0000e-02 eta: 9:34:26 time: 0.4805 data_time: 0.0329 memory: 17006 grad_norm: 4.0798 top1_acc: 0.4688 top5_acc: 0.8750 loss_cls: 1.8519 loss: 1.8519 2022/10/13 02:41:17 - mmengine - INFO - Epoch(train) [29][520/940] lr: 1.0000e-02 eta: 9:34:15 time: 0.5014 data_time: 0.0327 memory: 17006 grad_norm: 4.1299 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.8969 loss: 1.8969 2022/10/13 02:41:27 - mmengine - INFO - Epoch(train) [29][540/940] lr: 1.0000e-02 eta: 9:34:04 time: 0.4962 data_time: 0.0291 memory: 17006 grad_norm: 4.1927 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.7075 loss: 1.7075 2022/10/13 02:41:38 - mmengine - INFO - Epoch(train) [29][560/940] lr: 1.0000e-02 eta: 9:33:55 time: 0.5413 data_time: 0.0319 memory: 17006 grad_norm: 4.1746 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6879 loss: 1.6879 2022/10/13 02:41:48 - mmengine - INFO - Epoch(train) [29][580/940] lr: 1.0000e-02 eta: 9:33:43 time: 0.4878 data_time: 0.0353 memory: 17006 grad_norm: 4.1658 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.8560 loss: 1.8560 2022/10/13 02:41:59 - mmengine - INFO - Epoch(train) [29][600/940] lr: 1.0000e-02 eta: 9:33:36 time: 0.5713 data_time: 0.0356 memory: 17006 grad_norm: 4.0949 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7493 loss: 1.7493 2022/10/13 02:42:09 - mmengine - INFO - Epoch(train) [29][620/940] lr: 1.0000e-02 eta: 9:33:23 time: 0.4644 data_time: 0.0318 memory: 17006 grad_norm: 4.0566 top1_acc: 0.4688 top5_acc: 0.9062 loss_cls: 1.7651 loss: 1.7651 2022/10/13 02:42:19 - mmengine - INFO - Epoch(train) [29][640/940] lr: 1.0000e-02 eta: 9:33:13 time: 0.5133 data_time: 0.0300 memory: 17006 grad_norm: 4.1480 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6974 loss: 1.6974 2022/10/13 02:42:29 - mmengine - INFO - Epoch(train) [29][660/940] lr: 1.0000e-02 eta: 9:33:02 time: 0.4940 data_time: 0.0359 memory: 17006 grad_norm: 4.1295 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8948 loss: 1.8948 2022/10/13 02:42:38 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 02:42:38 - mmengine - INFO - Epoch(train) [29][680/940] lr: 1.0000e-02 eta: 9:32:49 time: 0.4580 data_time: 0.0338 memory: 17006 grad_norm: 4.1251 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.7395 loss: 1.7395 2022/10/13 02:42:48 - mmengine - INFO - Epoch(train) [29][700/940] lr: 1.0000e-02 eta: 9:32:38 time: 0.5003 data_time: 0.0314 memory: 17006 grad_norm: 4.1817 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6359 loss: 1.6359 2022/10/13 02:42:59 - mmengine - INFO - Epoch(train) [29][720/940] lr: 1.0000e-02 eta: 9:32:29 time: 0.5478 data_time: 0.0291 memory: 17006 grad_norm: 4.1034 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6404 loss: 1.6404 2022/10/13 02:43:09 - mmengine - INFO - Epoch(train) [29][740/940] lr: 1.0000e-02 eta: 9:32:18 time: 0.4851 data_time: 0.0305 memory: 17006 grad_norm: 4.1881 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.8209 loss: 1.8209 2022/10/13 02:43:19 - mmengine - INFO - Epoch(train) [29][760/940] lr: 1.0000e-02 eta: 9:32:07 time: 0.4970 data_time: 0.0346 memory: 17006 grad_norm: 4.1125 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.8401 loss: 1.8401 2022/10/13 02:43:29 - mmengine - INFO - Epoch(train) [29][780/940] lr: 1.0000e-02 eta: 9:31:56 time: 0.4989 data_time: 0.0347 memory: 17006 grad_norm: 4.0852 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7485 loss: 1.7485 2022/10/13 02:43:39 - mmengine - INFO - Epoch(train) [29][800/940] lr: 1.0000e-02 eta: 9:31:45 time: 0.5112 data_time: 0.0309 memory: 17006 grad_norm: 4.1156 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7080 loss: 1.7080 2022/10/13 02:43:49 - mmengine - INFO - Epoch(train) [29][820/940] lr: 1.0000e-02 eta: 9:31:35 time: 0.5051 data_time: 0.0339 memory: 17006 grad_norm: 4.1304 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7423 loss: 1.7423 2022/10/13 02:44:00 - mmengine - INFO - Epoch(train) [29][840/940] lr: 1.0000e-02 eta: 9:31:26 time: 0.5535 data_time: 0.0365 memory: 17006 grad_norm: 4.0825 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.8032 loss: 1.8032 2022/10/13 02:44:09 - mmengine - INFO - Epoch(train) [29][860/940] lr: 1.0000e-02 eta: 9:31:14 time: 0.4686 data_time: 0.0324 memory: 17006 grad_norm: 4.1758 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.7279 loss: 1.7279 2022/10/13 02:44:19 - mmengine - INFO - Epoch(train) [29][880/940] lr: 1.0000e-02 eta: 9:31:03 time: 0.5045 data_time: 0.0386 memory: 17006 grad_norm: 4.0999 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.8159 loss: 1.8159 2022/10/13 02:44:30 - mmengine - INFO - Epoch(train) [29][900/940] lr: 1.0000e-02 eta: 9:30:53 time: 0.5035 data_time: 0.0268 memory: 17006 grad_norm: 4.0801 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7198 loss: 1.7198 2022/10/13 02:44:41 - mmengine - INFO - Epoch(train) [29][920/940] lr: 1.0000e-02 eta: 9:30:45 time: 0.5701 data_time: 0.0323 memory: 17006 grad_norm: 4.2157 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7096 loss: 1.7096 2022/10/13 02:44:50 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 02:44:50 - mmengine - INFO - Epoch(train) [29][940/940] lr: 1.0000e-02 eta: 9:30:32 time: 0.4514 data_time: 0.0282 memory: 17006 grad_norm: 4.3052 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.8106 loss: 1.8106 2022/10/13 02:45:03 - mmengine - INFO - Epoch(val) [29][20/78] eta: 0:00:37 time: 0.6390 data_time: 0.5431 memory: 3172 2022/10/13 02:45:11 - mmengine - INFO - Epoch(val) [29][40/78] eta: 0:00:16 time: 0.4317 data_time: 0.3397 memory: 3172 2022/10/13 02:45:23 - mmengine - INFO - Epoch(val) [29][60/78] eta: 0:00:10 time: 0.5671 data_time: 0.4764 memory: 3172 2022/10/13 02:45:32 - mmengine - INFO - Epoch(val) [29][78/78] acc/top1: 0.6266 acc/top5: 0.8451 acc/mean1: 0.6265 2022/10/13 02:45:33 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_28.pth is removed 2022/10/13 02:45:33 - mmengine - INFO - The best checkpoint with 0.6266 acc/top1 at 29 epoch is saved to best_acc/top1_epoch_29.pth. 2022/10/13 02:45:46 - mmengine - INFO - Epoch(train) [30][20/940] lr: 1.0000e-02 eta: 9:30:29 time: 0.6699 data_time: 0.3561 memory: 17006 grad_norm: 4.1004 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8275 loss: 1.8275 2022/10/13 02:45:57 - mmengine - INFO - Epoch(train) [30][40/940] lr: 1.0000e-02 eta: 9:30:20 time: 0.5346 data_time: 0.1118 memory: 17006 grad_norm: 4.1193 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6742 loss: 1.6742 2022/10/13 02:46:07 - mmengine - INFO - Epoch(train) [30][60/940] lr: 1.0000e-02 eta: 9:30:10 time: 0.5090 data_time: 0.0397 memory: 17006 grad_norm: 4.1107 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.7680 loss: 1.7680 2022/10/13 02:46:17 - mmengine - INFO - Epoch(train) [30][80/940] lr: 1.0000e-02 eta: 9:29:57 time: 0.4618 data_time: 0.0723 memory: 17006 grad_norm: 4.0261 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.7750 loss: 1.7750 2022/10/13 02:46:27 - mmengine - INFO - Epoch(train) [30][100/940] lr: 1.0000e-02 eta: 9:29:48 time: 0.5352 data_time: 0.1209 memory: 17006 grad_norm: 4.0589 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7605 loss: 1.7605 2022/10/13 02:46:36 - mmengine - INFO - Epoch(train) [30][120/940] lr: 1.0000e-02 eta: 9:29:35 time: 0.4532 data_time: 0.1401 memory: 17006 grad_norm: 4.1287 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7641 loss: 1.7641 2022/10/13 02:46:48 - mmengine - INFO - Epoch(train) [30][140/940] lr: 1.0000e-02 eta: 9:29:27 time: 0.5627 data_time: 0.0828 memory: 17006 grad_norm: 4.1164 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6287 loss: 1.6287 2022/10/13 02:46:57 - mmengine - INFO - Epoch(train) [30][160/940] lr: 1.0000e-02 eta: 9:29:14 time: 0.4558 data_time: 0.0323 memory: 17006 grad_norm: 4.1170 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7666 loss: 1.7666 2022/10/13 02:47:08 - mmengine - INFO - Epoch(train) [30][180/940] lr: 1.0000e-02 eta: 9:29:05 time: 0.5547 data_time: 0.0336 memory: 17006 grad_norm: 4.0418 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5802 loss: 1.5802 2022/10/13 02:47:17 - mmengine - INFO - Epoch(train) [30][200/940] lr: 1.0000e-02 eta: 9:28:54 time: 0.4787 data_time: 0.0357 memory: 17006 grad_norm: 4.1230 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7504 loss: 1.7504 2022/10/13 02:47:28 - mmengine - INFO - Epoch(train) [30][220/940] lr: 1.0000e-02 eta: 9:28:43 time: 0.5165 data_time: 0.0322 memory: 17006 grad_norm: 4.1497 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.8334 loss: 1.8334 2022/10/13 02:47:38 - mmengine - INFO - Epoch(train) [30][240/940] lr: 1.0000e-02 eta: 9:28:33 time: 0.5013 data_time: 0.0305 memory: 17006 grad_norm: 4.1786 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7579 loss: 1.7579 2022/10/13 02:47:48 - mmengine - INFO - Epoch(train) [30][260/940] lr: 1.0000e-02 eta: 9:28:22 time: 0.5060 data_time: 0.0307 memory: 17006 grad_norm: 4.1942 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7024 loss: 1.7024 2022/10/13 02:47:58 - mmengine - INFO - Epoch(train) [30][280/940] lr: 1.0000e-02 eta: 9:28:11 time: 0.4993 data_time: 0.0346 memory: 17006 grad_norm: 4.1037 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8602 loss: 1.8602 2022/10/13 02:48:08 - mmengine - INFO - Epoch(train) [30][300/940] lr: 1.0000e-02 eta: 9:28:00 time: 0.4976 data_time: 0.0350 memory: 17006 grad_norm: 4.1655 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.7961 loss: 1.7961 2022/10/13 02:48:18 - mmengine - INFO - Epoch(train) [30][320/940] lr: 1.0000e-02 eta: 9:27:49 time: 0.5024 data_time: 0.0334 memory: 17006 grad_norm: 4.0709 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 1.6604 loss: 1.6604 2022/10/13 02:48:28 - mmengine - INFO - Epoch(train) [30][340/940] lr: 1.0000e-02 eta: 9:27:38 time: 0.4868 data_time: 0.0369 memory: 17006 grad_norm: 4.1772 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7438 loss: 1.7438 2022/10/13 02:48:39 - mmengine - INFO - Epoch(train) [30][360/940] lr: 1.0000e-02 eta: 9:27:29 time: 0.5515 data_time: 0.0347 memory: 17006 grad_norm: 4.2060 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7545 loss: 1.7545 2022/10/13 02:48:49 - mmengine - INFO - Epoch(train) [30][380/940] lr: 1.0000e-02 eta: 9:27:19 time: 0.5017 data_time: 0.0304 memory: 17006 grad_norm: 4.2018 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.6553 loss: 1.6553 2022/10/13 02:48:58 - mmengine - INFO - Epoch(train) [30][400/940] lr: 1.0000e-02 eta: 9:27:05 time: 0.4485 data_time: 0.0325 memory: 17006 grad_norm: 4.1951 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6187 loss: 1.6187 2022/10/13 02:49:08 - mmengine - INFO - Epoch(train) [30][420/940] lr: 1.0000e-02 eta: 9:26:55 time: 0.5086 data_time: 0.0305 memory: 17006 grad_norm: 4.2411 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8042 loss: 1.8042 2022/10/13 02:49:18 - mmengine - INFO - Epoch(train) [30][440/940] lr: 1.0000e-02 eta: 9:26:44 time: 0.5065 data_time: 0.0339 memory: 17006 grad_norm: 4.2004 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7447 loss: 1.7447 2022/10/13 02:49:30 - mmengine - INFO - Epoch(train) [30][460/940] lr: 1.0000e-02 eta: 9:26:38 time: 0.5985 data_time: 0.0315 memory: 17006 grad_norm: 4.0987 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.6859 loss: 1.6859 2022/10/13 02:49:39 - mmengine - INFO - Epoch(train) [30][480/940] lr: 1.0000e-02 eta: 9:26:26 time: 0.4723 data_time: 0.0357 memory: 17006 grad_norm: 4.2112 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.6471 loss: 1.6471 2022/10/13 02:49:49 - mmengine - INFO - Epoch(train) [30][500/940] lr: 1.0000e-02 eta: 9:26:15 time: 0.5024 data_time: 0.0325 memory: 17006 grad_norm: 4.1767 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7276 loss: 1.7276 2022/10/13 02:50:00 - mmengine - INFO - Epoch(train) [30][520/940] lr: 1.0000e-02 eta: 9:26:05 time: 0.5090 data_time: 0.0335 memory: 17006 grad_norm: 4.1559 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6989 loss: 1.6989 2022/10/13 02:50:10 - mmengine - INFO - Epoch(train) [30][540/940] lr: 1.0000e-02 eta: 9:25:55 time: 0.5360 data_time: 0.0280 memory: 17006 grad_norm: 4.1229 top1_acc: 0.5938 top5_acc: 0.6562 loss_cls: 1.7577 loss: 1.7577 2022/10/13 02:50:20 - mmengine - INFO - Epoch(train) [30][560/940] lr: 1.0000e-02 eta: 9:25:44 time: 0.4858 data_time: 0.0335 memory: 17006 grad_norm: 4.1857 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7997 loss: 1.7997 2022/10/13 02:50:30 - mmengine - INFO - Epoch(train) [30][580/940] lr: 1.0000e-02 eta: 9:25:33 time: 0.4888 data_time: 0.0292 memory: 17006 grad_norm: 4.1552 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7819 loss: 1.7819 2022/10/13 02:50:40 - mmengine - INFO - Epoch(train) [30][600/940] lr: 1.0000e-02 eta: 9:25:22 time: 0.5159 data_time: 0.0388 memory: 17006 grad_norm: 4.0779 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8522 loss: 1.8522 2022/10/13 02:50:51 - mmengine - INFO - Epoch(train) [30][620/940] lr: 1.0000e-02 eta: 9:25:15 time: 0.5667 data_time: 0.0252 memory: 17006 grad_norm: 4.1554 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 1.7179 loss: 1.7179 2022/10/13 02:51:01 - mmengine - INFO - Epoch(train) [30][640/940] lr: 1.0000e-02 eta: 9:25:03 time: 0.4918 data_time: 0.0355 memory: 17006 grad_norm: 4.1742 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7308 loss: 1.7308 2022/10/13 02:51:12 - mmengine - INFO - Epoch(train) [30][660/940] lr: 1.0000e-02 eta: 9:24:55 time: 0.5602 data_time: 0.0341 memory: 17006 grad_norm: 4.0518 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.8043 loss: 1.8043 2022/10/13 02:51:22 - mmengine - INFO - Epoch(train) [30][680/940] lr: 1.0000e-02 eta: 9:24:44 time: 0.4778 data_time: 0.0329 memory: 17006 grad_norm: 4.0880 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8053 loss: 1.8053 2022/10/13 02:51:32 - mmengine - INFO - Epoch(train) [30][700/940] lr: 1.0000e-02 eta: 9:24:32 time: 0.4955 data_time: 0.0321 memory: 17006 grad_norm: 4.0477 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 1.7779 loss: 1.7779 2022/10/13 02:51:41 - mmengine - INFO - Epoch(train) [30][720/940] lr: 1.0000e-02 eta: 9:24:20 time: 0.4683 data_time: 0.0306 memory: 17006 grad_norm: 4.0857 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.6012 loss: 1.6012 2022/10/13 02:51:51 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 02:51:51 - mmengine - INFO - Epoch(train) [30][740/940] lr: 1.0000e-02 eta: 9:24:10 time: 0.5065 data_time: 0.0360 memory: 17006 grad_norm: 4.2050 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.7150 loss: 1.7150 2022/10/13 02:52:01 - mmengine - INFO - Epoch(train) [30][760/940] lr: 1.0000e-02 eta: 9:23:57 time: 0.4658 data_time: 0.0265 memory: 17006 grad_norm: 4.1526 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6478 loss: 1.6478 2022/10/13 02:52:11 - mmengine - INFO - Epoch(train) [30][780/940] lr: 1.0000e-02 eta: 9:23:46 time: 0.4989 data_time: 0.0353 memory: 17006 grad_norm: 4.0717 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8988 loss: 1.8988 2022/10/13 02:52:21 - mmengine - INFO - Epoch(train) [30][800/940] lr: 1.0000e-02 eta: 9:23:36 time: 0.5081 data_time: 0.0285 memory: 17006 grad_norm: 4.1131 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.8394 loss: 1.8394 2022/10/13 02:52:31 - mmengine - INFO - Epoch(train) [30][820/940] lr: 1.0000e-02 eta: 9:23:25 time: 0.4999 data_time: 0.0319 memory: 17006 grad_norm: 4.0674 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.7855 loss: 1.7855 2022/10/13 02:52:42 - mmengine - INFO - Epoch(train) [30][840/940] lr: 1.0000e-02 eta: 9:23:16 time: 0.5404 data_time: 0.0322 memory: 17006 grad_norm: 4.1371 top1_acc: 0.6250 top5_acc: 0.6562 loss_cls: 1.6464 loss: 1.6464 2022/10/13 02:52:51 - mmengine - INFO - Epoch(train) [30][860/940] lr: 1.0000e-02 eta: 9:23:03 time: 0.4565 data_time: 0.0331 memory: 17006 grad_norm: 4.1700 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6846 loss: 1.6846 2022/10/13 02:53:02 - mmengine - INFO - Epoch(train) [30][880/940] lr: 1.0000e-02 eta: 9:22:54 time: 0.5470 data_time: 0.0398 memory: 17006 grad_norm: 4.1798 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6290 loss: 1.6290 2022/10/13 02:53:13 - mmengine - INFO - Epoch(train) [30][900/940] lr: 1.0000e-02 eta: 9:22:46 time: 0.5519 data_time: 0.0267 memory: 17006 grad_norm: 4.1725 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7654 loss: 1.7654 2022/10/13 02:53:23 - mmengine - INFO - Epoch(train) [30][920/940] lr: 1.0000e-02 eta: 9:22:34 time: 0.4866 data_time: 0.0352 memory: 17006 grad_norm: 4.1271 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7411 loss: 1.7411 2022/10/13 02:53:32 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 02:53:32 - mmengine - INFO - Epoch(train) [30][940/940] lr: 1.0000e-02 eta: 9:22:23 time: 0.4886 data_time: 0.0284 memory: 17006 grad_norm: 4.3618 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.6432 loss: 1.6432 2022/10/13 02:53:32 - mmengine - INFO - Saving checkpoint at 30 epochs 2022/10/13 02:53:46 - mmengine - INFO - Epoch(val) [30][20/78] eta: 0:00:36 time: 0.6337 data_time: 0.5429 memory: 3172 2022/10/13 02:53:54 - mmengine - INFO - Epoch(val) [30][40/78] eta: 0:00:16 time: 0.4289 data_time: 0.3389 memory: 3172 2022/10/13 02:54:06 - mmengine - INFO - Epoch(val) [30][60/78] eta: 0:00:10 time: 0.5735 data_time: 0.4835 memory: 3172 2022/10/13 02:54:15 - mmengine - INFO - Epoch(val) [30][78/78] acc/top1: 0.6191 acc/top5: 0.8379 acc/mean1: 0.6190 2022/10/13 02:54:29 - mmengine - INFO - Epoch(train) [31][20/940] lr: 1.0000e-02 eta: 9:22:21 time: 0.6819 data_time: 0.3360 memory: 17006 grad_norm: 4.1232 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.8023 loss: 1.8023 2022/10/13 02:54:38 - mmengine - INFO - Epoch(train) [31][40/940] lr: 1.0000e-02 eta: 9:22:08 time: 0.4682 data_time: 0.0531 memory: 17006 grad_norm: 4.0471 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6936 loss: 1.6936 2022/10/13 02:54:50 - mmengine - INFO - Epoch(train) [31][60/940] lr: 1.0000e-02 eta: 9:22:02 time: 0.5943 data_time: 0.0848 memory: 17006 grad_norm: 4.1191 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.8438 loss: 1.8438 2022/10/13 02:54:59 - mmengine - INFO - Epoch(train) [31][80/940] lr: 1.0000e-02 eta: 9:21:50 time: 0.4770 data_time: 0.0297 memory: 17006 grad_norm: 4.1277 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6958 loss: 1.6958 2022/10/13 02:55:10 - mmengine - INFO - Epoch(train) [31][100/940] lr: 1.0000e-02 eta: 9:21:40 time: 0.5303 data_time: 0.0403 memory: 17006 grad_norm: 4.1029 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6908 loss: 1.6908 2022/10/13 02:55:19 - mmengine - INFO - Epoch(train) [31][120/940] lr: 1.0000e-02 eta: 9:21:28 time: 0.4697 data_time: 0.0286 memory: 17006 grad_norm: 4.1175 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7018 loss: 1.7018 2022/10/13 02:55:31 - mmengine - INFO - Epoch(train) [31][140/940] lr: 1.0000e-02 eta: 9:21:20 time: 0.5592 data_time: 0.0315 memory: 17006 grad_norm: 4.1270 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7174 loss: 1.7174 2022/10/13 02:55:40 - mmengine - INFO - Epoch(train) [31][160/940] lr: 1.0000e-02 eta: 9:21:08 time: 0.4786 data_time: 0.0275 memory: 17006 grad_norm: 4.0873 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.5876 loss: 1.5876 2022/10/13 02:55:51 - mmengine - INFO - Epoch(train) [31][180/940] lr: 1.0000e-02 eta: 9:20:59 time: 0.5456 data_time: 0.0303 memory: 17006 grad_norm: 4.1590 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6826 loss: 1.6826 2022/10/13 02:56:01 - mmengine - INFO - Epoch(train) [31][200/940] lr: 1.0000e-02 eta: 9:20:47 time: 0.4735 data_time: 0.0398 memory: 17006 grad_norm: 4.1084 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7002 loss: 1.7002 2022/10/13 02:56:12 - mmengine - INFO - Epoch(train) [31][220/940] lr: 1.0000e-02 eta: 9:20:39 time: 0.5645 data_time: 0.0323 memory: 17006 grad_norm: 4.1733 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.9007 loss: 1.9007 2022/10/13 02:56:21 - mmengine - INFO - Epoch(train) [31][240/940] lr: 1.0000e-02 eta: 9:20:26 time: 0.4528 data_time: 0.0338 memory: 17006 grad_norm: 4.1500 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6653 loss: 1.6653 2022/10/13 02:56:32 - mmengine - INFO - Epoch(train) [31][260/940] lr: 1.0000e-02 eta: 9:20:18 time: 0.5490 data_time: 0.0345 memory: 17006 grad_norm: 4.2019 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7323 loss: 1.7323 2022/10/13 02:56:42 - mmengine - INFO - Epoch(train) [31][280/940] lr: 1.0000e-02 eta: 9:20:07 time: 0.4898 data_time: 0.0295 memory: 17006 grad_norm: 4.1804 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.6709 loss: 1.6709 2022/10/13 02:56:52 - mmengine - INFO - Epoch(train) [31][300/940] lr: 1.0000e-02 eta: 9:19:56 time: 0.5059 data_time: 0.0314 memory: 17006 grad_norm: 4.1573 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6453 loss: 1.6453 2022/10/13 02:57:02 - mmengine - INFO - Epoch(train) [31][320/940] lr: 1.0000e-02 eta: 9:19:46 time: 0.5106 data_time: 0.0273 memory: 17006 grad_norm: 4.1863 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.6589 loss: 1.6589 2022/10/13 02:57:13 - mmengine - INFO - Epoch(train) [31][340/940] lr: 1.0000e-02 eta: 9:19:36 time: 0.5244 data_time: 0.0341 memory: 17006 grad_norm: 4.1685 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6386 loss: 1.6386 2022/10/13 02:57:21 - mmengine - INFO - Epoch(train) [31][360/940] lr: 1.0000e-02 eta: 9:19:22 time: 0.4396 data_time: 0.0276 memory: 17006 grad_norm: 4.1388 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7573 loss: 1.7573 2022/10/13 02:57:32 - mmengine - INFO - Epoch(train) [31][380/940] lr: 1.0000e-02 eta: 9:19:13 time: 0.5360 data_time: 0.0341 memory: 17006 grad_norm: 4.1895 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6114 loss: 1.6114 2022/10/13 02:57:42 - mmengine - INFO - Epoch(train) [31][400/940] lr: 1.0000e-02 eta: 9:19:02 time: 0.4993 data_time: 0.0328 memory: 17006 grad_norm: 4.1518 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6454 loss: 1.6454 2022/10/13 02:57:53 - mmengine - INFO - Epoch(train) [31][420/940] lr: 1.0000e-02 eta: 9:18:53 time: 0.5325 data_time: 0.0365 memory: 17006 grad_norm: 4.1030 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.8402 loss: 1.8402 2022/10/13 02:58:02 - mmengine - INFO - Epoch(train) [31][440/940] lr: 1.0000e-02 eta: 9:18:40 time: 0.4581 data_time: 0.0282 memory: 17006 grad_norm: 4.1999 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6704 loss: 1.6704 2022/10/13 02:58:13 - mmengine - INFO - Epoch(train) [31][460/940] lr: 1.0000e-02 eta: 9:18:31 time: 0.5459 data_time: 0.0359 memory: 17006 grad_norm: 4.1218 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7898 loss: 1.7898 2022/10/13 02:58:22 - mmengine - INFO - Epoch(train) [31][480/940] lr: 1.0000e-02 eta: 9:18:20 time: 0.4842 data_time: 0.0336 memory: 17006 grad_norm: 4.2474 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7660 loss: 1.7660 2022/10/13 02:58:34 - mmengine - INFO - Epoch(train) [31][500/940] lr: 1.0000e-02 eta: 9:18:12 time: 0.5675 data_time: 0.0264 memory: 17006 grad_norm: 4.2308 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.8776 loss: 1.8776 2022/10/13 02:58:44 - mmengine - INFO - Epoch(train) [31][520/940] lr: 1.0000e-02 eta: 9:18:01 time: 0.5043 data_time: 0.0295 memory: 17006 grad_norm: 4.2229 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.8755 loss: 1.8755 2022/10/13 02:58:54 - mmengine - INFO - Epoch(train) [31][540/940] lr: 1.0000e-02 eta: 9:17:52 time: 0.5279 data_time: 0.0324 memory: 17006 grad_norm: 4.1031 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7430 loss: 1.7430 2022/10/13 02:59:04 - mmengine - INFO - Epoch(train) [31][560/940] lr: 1.0000e-02 eta: 9:17:40 time: 0.4854 data_time: 0.0346 memory: 17006 grad_norm: 4.1921 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7508 loss: 1.7508 2022/10/13 02:59:15 - mmengine - INFO - Epoch(train) [31][580/940] lr: 1.0000e-02 eta: 9:17:32 time: 0.5639 data_time: 0.0354 memory: 17006 grad_norm: 4.1930 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.7297 loss: 1.7297 2022/10/13 02:59:25 - mmengine - INFO - Epoch(train) [31][600/940] lr: 1.0000e-02 eta: 9:17:20 time: 0.4733 data_time: 0.0277 memory: 17006 grad_norm: 4.1873 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6252 loss: 1.6252 2022/10/13 02:59:37 - mmengine - INFO - Epoch(train) [31][620/940] lr: 1.0000e-02 eta: 9:17:13 time: 0.5868 data_time: 0.0291 memory: 17006 grad_norm: 4.0864 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7349 loss: 1.7349 2022/10/13 02:59:46 - mmengine - INFO - Epoch(train) [31][640/940] lr: 1.0000e-02 eta: 9:17:02 time: 0.4848 data_time: 0.0331 memory: 17006 grad_norm: 4.1722 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7332 loss: 1.7332 2022/10/13 02:59:57 - mmengine - INFO - Epoch(train) [31][660/940] lr: 1.0000e-02 eta: 9:16:52 time: 0.5152 data_time: 0.0319 memory: 17006 grad_norm: 4.1886 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7959 loss: 1.7959 2022/10/13 03:00:07 - mmengine - INFO - Epoch(train) [31][680/940] lr: 1.0000e-02 eta: 9:16:42 time: 0.5325 data_time: 0.0264 memory: 17006 grad_norm: 4.2627 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.6462 loss: 1.6462 2022/10/13 03:00:18 - mmengine - INFO - Epoch(train) [31][700/940] lr: 1.0000e-02 eta: 9:16:33 time: 0.5466 data_time: 0.0287 memory: 17006 grad_norm: 4.2188 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.6223 loss: 1.6223 2022/10/13 03:00:28 - mmengine - INFO - Epoch(train) [31][720/940] lr: 1.0000e-02 eta: 9:16:22 time: 0.4798 data_time: 0.0335 memory: 17006 grad_norm: 4.1733 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.8615 loss: 1.8615 2022/10/13 03:00:38 - mmengine - INFO - Epoch(train) [31][740/940] lr: 1.0000e-02 eta: 9:16:11 time: 0.5108 data_time: 0.0291 memory: 17006 grad_norm: 4.1842 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.7791 loss: 1.7791 2022/10/13 03:00:48 - mmengine - INFO - Epoch(train) [31][760/940] lr: 1.0000e-02 eta: 9:16:00 time: 0.4964 data_time: 0.0357 memory: 17006 grad_norm: 4.1736 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7199 loss: 1.7199 2022/10/13 03:00:59 - mmengine - INFO - Epoch(train) [31][780/940] lr: 1.0000e-02 eta: 9:15:51 time: 0.5403 data_time: 0.0360 memory: 17006 grad_norm: 4.1283 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6902 loss: 1.6902 2022/10/13 03:01:08 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 03:01:08 - mmengine - INFO - Epoch(train) [31][800/940] lr: 1.0000e-02 eta: 9:15:38 time: 0.4538 data_time: 0.0359 memory: 17006 grad_norm: 4.1368 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7061 loss: 1.7061 2022/10/13 03:01:19 - mmengine - INFO - Epoch(train) [31][820/940] lr: 1.0000e-02 eta: 9:15:30 time: 0.5598 data_time: 0.0341 memory: 17006 grad_norm: 4.2175 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.8266 loss: 1.8266 2022/10/13 03:01:29 - mmengine - INFO - Epoch(train) [31][840/940] lr: 1.0000e-02 eta: 9:15:19 time: 0.4810 data_time: 0.0346 memory: 17006 grad_norm: 4.1324 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8089 loss: 1.8089 2022/10/13 03:01:39 - mmengine - INFO - Epoch(train) [31][860/940] lr: 1.0000e-02 eta: 9:15:08 time: 0.4980 data_time: 0.0313 memory: 17006 grad_norm: 4.1045 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.7121 loss: 1.7121 2022/10/13 03:01:47 - mmengine - INFO - Epoch(train) [31][880/940] lr: 1.0000e-02 eta: 9:14:54 time: 0.4395 data_time: 0.0345 memory: 17006 grad_norm: 4.1922 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8106 loss: 1.8106 2022/10/13 03:01:57 - mmengine - INFO - Epoch(train) [31][900/940] lr: 1.0000e-02 eta: 9:14:42 time: 0.4788 data_time: 0.0272 memory: 17006 grad_norm: 4.1894 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.7541 loss: 1.7541 2022/10/13 03:02:07 - mmengine - INFO - Epoch(train) [31][920/940] lr: 1.0000e-02 eta: 9:14:32 time: 0.5121 data_time: 0.0338 memory: 17006 grad_norm: 4.1072 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6496 loss: 1.6496 2022/10/13 03:02:17 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 03:02:17 - mmengine - INFO - Epoch(train) [31][940/940] lr: 1.0000e-02 eta: 9:14:20 time: 0.4616 data_time: 0.0292 memory: 17006 grad_norm: 4.4161 top1_acc: 0.1429 top5_acc: 0.2857 loss_cls: 1.9211 loss: 1.9211 2022/10/13 03:02:29 - mmengine - INFO - Epoch(val) [31][20/78] eta: 0:00:36 time: 0.6355 data_time: 0.5415 memory: 3172 2022/10/13 03:02:38 - mmengine - INFO - Epoch(val) [31][40/78] eta: 0:00:16 time: 0.4328 data_time: 0.3413 memory: 3172 2022/10/13 03:02:49 - mmengine - INFO - Epoch(val) [31][60/78] eta: 0:00:10 time: 0.5762 data_time: 0.4858 memory: 3172 2022/10/13 03:02:59 - mmengine - INFO - Epoch(val) [31][78/78] acc/top1: 0.6186 acc/top5: 0.8387 acc/mean1: 0.6184 2022/10/13 03:03:13 - mmengine - INFO - Epoch(train) [32][20/940] lr: 1.0000e-02 eta: 9:14:18 time: 0.7034 data_time: 0.2423 memory: 17006 grad_norm: 4.1064 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7977 loss: 1.7977 2022/10/13 03:03:23 - mmengine - INFO - Epoch(train) [32][40/940] lr: 1.0000e-02 eta: 9:14:06 time: 0.4710 data_time: 0.1070 memory: 17006 grad_norm: 4.1463 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6134 loss: 1.6134 2022/10/13 03:03:33 - mmengine - INFO - Epoch(train) [32][60/940] lr: 1.0000e-02 eta: 9:13:56 time: 0.5361 data_time: 0.1184 memory: 17006 grad_norm: 4.0660 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.5806 loss: 1.5806 2022/10/13 03:03:43 - mmengine - INFO - Epoch(train) [32][80/940] lr: 1.0000e-02 eta: 9:13:45 time: 0.4841 data_time: 0.0469 memory: 17006 grad_norm: 4.0564 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6672 loss: 1.6672 2022/10/13 03:03:54 - mmengine - INFO - Epoch(train) [32][100/940] lr: 1.0000e-02 eta: 9:13:36 time: 0.5347 data_time: 0.0340 memory: 17006 grad_norm: 4.1707 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6225 loss: 1.6225 2022/10/13 03:04:04 - mmengine - INFO - Epoch(train) [32][120/940] lr: 1.0000e-02 eta: 9:13:25 time: 0.5080 data_time: 0.0252 memory: 17006 grad_norm: 4.1001 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.5381 loss: 1.5381 2022/10/13 03:04:14 - mmengine - INFO - Epoch(train) [32][140/940] lr: 1.0000e-02 eta: 9:13:15 time: 0.5269 data_time: 0.0311 memory: 17006 grad_norm: 4.1080 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7216 loss: 1.7216 2022/10/13 03:04:24 - mmengine - INFO - Epoch(train) [32][160/940] lr: 1.0000e-02 eta: 9:13:04 time: 0.4908 data_time: 0.0261 memory: 17006 grad_norm: 4.1258 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7048 loss: 1.7048 2022/10/13 03:04:35 - mmengine - INFO - Epoch(train) [32][180/940] lr: 1.0000e-02 eta: 9:12:55 time: 0.5333 data_time: 0.0331 memory: 17006 grad_norm: 4.1836 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7383 loss: 1.7383 2022/10/13 03:04:45 - mmengine - INFO - Epoch(train) [32][200/940] lr: 1.0000e-02 eta: 9:12:44 time: 0.5096 data_time: 0.0241 memory: 17006 grad_norm: 4.1128 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7125 loss: 1.7125 2022/10/13 03:04:57 - mmengine - INFO - Epoch(train) [32][220/940] lr: 1.0000e-02 eta: 9:12:37 time: 0.5809 data_time: 0.0279 memory: 17006 grad_norm: 4.1343 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6201 loss: 1.6201 2022/10/13 03:05:06 - mmengine - INFO - Epoch(train) [32][240/940] lr: 1.0000e-02 eta: 9:12:25 time: 0.4639 data_time: 0.0339 memory: 17006 grad_norm: 4.1394 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.7187 loss: 1.7187 2022/10/13 03:05:16 - mmengine - INFO - Epoch(train) [32][260/940] lr: 1.0000e-02 eta: 9:12:14 time: 0.5110 data_time: 0.0365 memory: 17006 grad_norm: 4.1057 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.5760 loss: 1.5760 2022/10/13 03:05:25 - mmengine - INFO - Epoch(train) [32][280/940] lr: 1.0000e-02 eta: 9:12:02 time: 0.4565 data_time: 0.0329 memory: 17006 grad_norm: 4.1084 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7502 loss: 1.7502 2022/10/13 03:05:37 - mmengine - INFO - Epoch(train) [32][300/940] lr: 1.0000e-02 eta: 9:11:54 time: 0.5640 data_time: 0.0350 memory: 17006 grad_norm: 4.2664 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7454 loss: 1.7454 2022/10/13 03:05:46 - mmengine - INFO - Epoch(train) [32][320/940] lr: 1.0000e-02 eta: 9:11:41 time: 0.4662 data_time: 0.0302 memory: 17006 grad_norm: 4.1365 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.6682 loss: 1.6682 2022/10/13 03:05:57 - mmengine - INFO - Epoch(train) [32][340/940] lr: 1.0000e-02 eta: 9:11:32 time: 0.5345 data_time: 0.0319 memory: 17006 grad_norm: 4.0837 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7331 loss: 1.7331 2022/10/13 03:06:06 - mmengine - INFO - Epoch(train) [32][360/940] lr: 1.0000e-02 eta: 9:11:20 time: 0.4789 data_time: 0.0335 memory: 17006 grad_norm: 4.1420 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.7319 loss: 1.7319 2022/10/13 03:06:17 - mmengine - INFO - Epoch(train) [32][380/940] lr: 1.0000e-02 eta: 9:11:11 time: 0.5332 data_time: 0.0321 memory: 17006 grad_norm: 4.1603 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.7359 loss: 1.7359 2022/10/13 03:06:25 - mmengine - INFO - Epoch(train) [32][400/940] lr: 1.0000e-02 eta: 9:10:57 time: 0.4349 data_time: 0.0396 memory: 17006 grad_norm: 4.2282 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8177 loss: 1.8177 2022/10/13 03:06:37 - mmengine - INFO - Epoch(train) [32][420/940] lr: 1.0000e-02 eta: 9:10:49 time: 0.5613 data_time: 0.0327 memory: 17006 grad_norm: 4.1206 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.7301 loss: 1.7301 2022/10/13 03:06:46 - mmengine - INFO - Epoch(train) [32][440/940] lr: 1.0000e-02 eta: 9:10:36 time: 0.4430 data_time: 0.0283 memory: 17006 grad_norm: 4.1319 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7347 loss: 1.7347 2022/10/13 03:06:56 - mmengine - INFO - Epoch(train) [32][460/940] lr: 1.0000e-02 eta: 9:10:27 time: 0.5369 data_time: 0.0326 memory: 17006 grad_norm: 4.1130 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.7696 loss: 1.7696 2022/10/13 03:07:06 - mmengine - INFO - Epoch(train) [32][480/940] lr: 1.0000e-02 eta: 9:10:15 time: 0.4779 data_time: 0.0288 memory: 17006 grad_norm: 4.2546 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7033 loss: 1.7033 2022/10/13 03:07:17 - mmengine - INFO - Epoch(train) [32][500/940] lr: 1.0000e-02 eta: 9:10:08 time: 0.5808 data_time: 0.0348 memory: 17006 grad_norm: 4.0966 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.6365 loss: 1.6365 2022/10/13 03:07:27 - mmengine - INFO - Epoch(train) [32][520/940] lr: 1.0000e-02 eta: 9:09:55 time: 0.4510 data_time: 0.0259 memory: 17006 grad_norm: 4.1741 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6621 loss: 1.6621 2022/10/13 03:07:37 - mmengine - INFO - Epoch(train) [32][540/940] lr: 1.0000e-02 eta: 9:09:46 time: 0.5491 data_time: 0.0293 memory: 17006 grad_norm: 4.1645 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.7039 loss: 1.7039 2022/10/13 03:07:47 - mmengine - INFO - Epoch(train) [32][560/940] lr: 1.0000e-02 eta: 9:09:35 time: 0.4897 data_time: 0.0308 memory: 17006 grad_norm: 4.1274 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6826 loss: 1.6826 2022/10/13 03:07:57 - mmengine - INFO - Epoch(train) [32][580/940] lr: 1.0000e-02 eta: 9:09:24 time: 0.4933 data_time: 0.0323 memory: 17006 grad_norm: 4.1697 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.7441 loss: 1.7441 2022/10/13 03:08:08 - mmengine - INFO - Epoch(train) [32][600/940] lr: 1.0000e-02 eta: 9:09:14 time: 0.5191 data_time: 0.0322 memory: 17006 grad_norm: 4.2712 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.7489 loss: 1.7489 2022/10/13 03:08:17 - mmengine - INFO - Epoch(train) [32][620/940] lr: 1.0000e-02 eta: 9:09:02 time: 0.4728 data_time: 0.0306 memory: 17006 grad_norm: 4.1751 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.9282 loss: 1.9282 2022/10/13 03:08:28 - mmengine - INFO - Epoch(train) [32][640/940] lr: 1.0000e-02 eta: 9:08:53 time: 0.5406 data_time: 0.0267 memory: 17006 grad_norm: 4.1540 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.7932 loss: 1.7932 2022/10/13 03:08:38 - mmengine - INFO - Epoch(train) [32][660/940] lr: 1.0000e-02 eta: 9:08:42 time: 0.5024 data_time: 0.0340 memory: 17006 grad_norm: 4.1323 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.6428 loss: 1.6428 2022/10/13 03:08:48 - mmengine - INFO - Epoch(train) [32][680/940] lr: 1.0000e-02 eta: 9:08:30 time: 0.4827 data_time: 0.0271 memory: 17006 grad_norm: 4.1288 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8172 loss: 1.8172 2022/10/13 03:08:57 - mmengine - INFO - Epoch(train) [32][700/940] lr: 1.0000e-02 eta: 9:08:19 time: 0.4812 data_time: 0.0435 memory: 17006 grad_norm: 4.3155 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7976 loss: 1.7976 2022/10/13 03:09:09 - mmengine - INFO - Epoch(train) [32][720/940] lr: 1.0000e-02 eta: 9:08:11 time: 0.5781 data_time: 0.0270 memory: 17006 grad_norm: 4.1982 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.5972 loss: 1.5972 2022/10/13 03:09:18 - mmengine - INFO - Epoch(train) [32][740/940] lr: 1.0000e-02 eta: 9:07:59 time: 0.4747 data_time: 0.0344 memory: 17006 grad_norm: 4.1904 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.7578 loss: 1.7578 2022/10/13 03:09:29 - mmengine - INFO - Epoch(train) [32][760/940] lr: 1.0000e-02 eta: 9:07:50 time: 0.5354 data_time: 0.0292 memory: 17006 grad_norm: 4.0424 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.7356 loss: 1.7356 2022/10/13 03:09:38 - mmengine - INFO - Epoch(train) [32][780/940] lr: 1.0000e-02 eta: 9:07:38 time: 0.4612 data_time: 0.0385 memory: 17006 grad_norm: 4.1166 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.8128 loss: 1.8128 2022/10/13 03:09:49 - mmengine - INFO - Epoch(train) [32][800/940] lr: 1.0000e-02 eta: 9:07:28 time: 0.5338 data_time: 0.0272 memory: 17006 grad_norm: 4.1950 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.6331 loss: 1.6331 2022/10/13 03:09:58 - mmengine - INFO - Epoch(train) [32][820/940] lr: 1.0000e-02 eta: 9:07:16 time: 0.4698 data_time: 0.0453 memory: 17006 grad_norm: 4.2103 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.7609 loss: 1.7609 2022/10/13 03:10:10 - mmengine - INFO - Epoch(train) [32][840/940] lr: 1.0000e-02 eta: 9:07:08 time: 0.5673 data_time: 0.0251 memory: 17006 grad_norm: 4.1952 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7346 loss: 1.7346 2022/10/13 03:10:18 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 03:10:18 - mmengine - INFO - Epoch(train) [32][860/940] lr: 1.0000e-02 eta: 9:06:55 time: 0.4417 data_time: 0.0369 memory: 17006 grad_norm: 4.2669 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.8716 loss: 1.8716 2022/10/13 03:10:29 - mmengine - INFO - Epoch(train) [32][880/940] lr: 1.0000e-02 eta: 9:06:44 time: 0.5086 data_time: 0.0282 memory: 17006 grad_norm: 4.2378 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7134 loss: 1.7134 2022/10/13 03:10:40 - mmengine - INFO - Epoch(train) [32][900/940] lr: 1.0000e-02 eta: 9:06:36 time: 0.5516 data_time: 0.0291 memory: 17006 grad_norm: 4.1984 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5974 loss: 1.5974 2022/10/13 03:10:50 - mmengine - INFO - Epoch(train) [32][920/940] lr: 1.0000e-02 eta: 9:06:25 time: 0.4999 data_time: 0.0324 memory: 17006 grad_norm: 4.1112 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.6609 loss: 1.6609 2022/10/13 03:10:59 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 03:10:59 - mmengine - INFO - Epoch(train) [32][940/940] lr: 1.0000e-02 eta: 9:06:13 time: 0.4750 data_time: 0.0242 memory: 17006 grad_norm: 4.3867 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.7153 loss: 1.7153 2022/10/13 03:11:12 - mmengine - INFO - Epoch(val) [32][20/78] eta: 0:00:35 time: 0.6202 data_time: 0.5257 memory: 3172 2022/10/13 03:11:20 - mmengine - INFO - Epoch(val) [32][40/78] eta: 0:00:16 time: 0.4378 data_time: 0.3473 memory: 3172 2022/10/13 03:11:32 - mmengine - INFO - Epoch(val) [32][60/78] eta: 0:00:10 time: 0.5785 data_time: 0.4879 memory: 3172 2022/10/13 03:11:42 - mmengine - INFO - Epoch(val) [32][78/78] acc/top1: 0.6246 acc/top5: 0.8413 acc/mean1: 0.6245 2022/10/13 03:11:56 - mmengine - INFO - Epoch(train) [33][20/940] lr: 1.0000e-02 eta: 9:06:11 time: 0.7040 data_time: 0.2773 memory: 17006 grad_norm: 4.1588 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6852 loss: 1.6852 2022/10/13 03:12:05 - mmengine - INFO - Epoch(train) [33][40/940] lr: 1.0000e-02 eta: 9:05:59 time: 0.4739 data_time: 0.0296 memory: 17006 grad_norm: 4.1273 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.7653 loss: 1.7653 2022/10/13 03:12:17 - mmengine - INFO - Epoch(train) [33][60/940] lr: 1.0000e-02 eta: 9:05:51 time: 0.5646 data_time: 0.0324 memory: 17006 grad_norm: 4.0648 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 1.7556 loss: 1.7556 2022/10/13 03:12:26 - mmengine - INFO - Epoch(train) [33][80/940] lr: 1.0000e-02 eta: 9:05:38 time: 0.4544 data_time: 0.0250 memory: 17006 grad_norm: 4.1266 top1_acc: 0.3438 top5_acc: 0.7188 loss_cls: 1.7039 loss: 1.7039 2022/10/13 03:12:37 - mmengine - INFO - Epoch(train) [33][100/940] lr: 1.0000e-02 eta: 9:05:31 time: 0.5759 data_time: 0.0324 memory: 17006 grad_norm: 4.1389 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7053 loss: 1.7053 2022/10/13 03:12:47 - mmengine - INFO - Epoch(train) [33][120/940] lr: 1.0000e-02 eta: 9:05:19 time: 0.4826 data_time: 0.0256 memory: 17006 grad_norm: 4.0739 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6101 loss: 1.6101 2022/10/13 03:12:57 - mmengine - INFO - Epoch(train) [33][140/940] lr: 1.0000e-02 eta: 9:05:09 time: 0.5179 data_time: 0.0349 memory: 17006 grad_norm: 4.1473 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5846 loss: 1.5846 2022/10/13 03:13:07 - mmengine - INFO - Epoch(train) [33][160/940] lr: 1.0000e-02 eta: 9:04:58 time: 0.4990 data_time: 0.0270 memory: 17006 grad_norm: 4.1533 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5386 loss: 1.5386 2022/10/13 03:13:17 - mmengine - INFO - Epoch(train) [33][180/940] lr: 1.0000e-02 eta: 9:04:47 time: 0.4947 data_time: 0.0343 memory: 17006 grad_norm: 4.1977 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6567 loss: 1.6567 2022/10/13 03:13:27 - mmengine - INFO - Epoch(train) [33][200/940] lr: 1.0000e-02 eta: 9:04:35 time: 0.4724 data_time: 0.0255 memory: 17006 grad_norm: 4.1622 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7719 loss: 1.7719 2022/10/13 03:13:37 - mmengine - INFO - Epoch(train) [33][220/940] lr: 1.0000e-02 eta: 9:04:26 time: 0.5376 data_time: 0.0312 memory: 17006 grad_norm: 4.2030 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.7204 loss: 1.7204 2022/10/13 03:13:47 - mmengine - INFO - Epoch(train) [33][240/940] lr: 1.0000e-02 eta: 9:04:14 time: 0.4767 data_time: 0.0279 memory: 17006 grad_norm: 4.0409 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.9180 loss: 1.9180 2022/10/13 03:13:58 - mmengine - INFO - Epoch(train) [33][260/940] lr: 1.0000e-02 eta: 9:04:05 time: 0.5372 data_time: 0.0403 memory: 17006 grad_norm: 4.1081 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.5606 loss: 1.5606 2022/10/13 03:14:08 - mmengine - INFO - Epoch(train) [33][280/940] lr: 1.0000e-02 eta: 9:03:55 time: 0.5051 data_time: 0.0298 memory: 17006 grad_norm: 4.1307 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7189 loss: 1.7189 2022/10/13 03:14:19 - mmengine - INFO - Epoch(train) [33][300/940] lr: 1.0000e-02 eta: 9:03:46 time: 0.5481 data_time: 0.0324 memory: 17006 grad_norm: 4.2116 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7049 loss: 1.7049 2022/10/13 03:14:28 - mmengine - INFO - Epoch(train) [33][320/940] lr: 1.0000e-02 eta: 9:03:34 time: 0.4638 data_time: 0.0327 memory: 17006 grad_norm: 4.1449 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7034 loss: 1.7034 2022/10/13 03:14:38 - mmengine - INFO - Epoch(train) [33][340/940] lr: 1.0000e-02 eta: 9:03:24 time: 0.5234 data_time: 0.0322 memory: 17006 grad_norm: 4.1917 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.7024 loss: 1.7024 2022/10/13 03:14:48 - mmengine - INFO - Epoch(train) [33][360/940] lr: 1.0000e-02 eta: 9:03:12 time: 0.4752 data_time: 0.0324 memory: 17006 grad_norm: 4.1848 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6786 loss: 1.6786 2022/10/13 03:14:59 - mmengine - INFO - Epoch(train) [33][380/940] lr: 1.0000e-02 eta: 9:03:03 time: 0.5431 data_time: 0.0360 memory: 17006 grad_norm: 4.1392 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.8339 loss: 1.8339 2022/10/13 03:15:09 - mmengine - INFO - Epoch(train) [33][400/940] lr: 1.0000e-02 eta: 9:02:52 time: 0.4905 data_time: 0.0337 memory: 17006 grad_norm: 4.1646 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7921 loss: 1.7921 2022/10/13 03:15:19 - mmengine - INFO - Epoch(train) [33][420/940] lr: 1.0000e-02 eta: 9:02:42 time: 0.5165 data_time: 0.0314 memory: 17006 grad_norm: 4.1954 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.5839 loss: 1.5839 2022/10/13 03:15:29 - mmengine - INFO - Epoch(train) [33][440/940] lr: 1.0000e-02 eta: 9:02:31 time: 0.4954 data_time: 0.0285 memory: 17006 grad_norm: 4.1271 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5836 loss: 1.5836 2022/10/13 03:15:39 - mmengine - INFO - Epoch(train) [33][460/940] lr: 1.0000e-02 eta: 9:02:21 time: 0.5184 data_time: 0.0289 memory: 17006 grad_norm: 4.0988 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6957 loss: 1.6957 2022/10/13 03:15:48 - mmengine - INFO - Epoch(train) [33][480/940] lr: 1.0000e-02 eta: 9:02:08 time: 0.4637 data_time: 0.0273 memory: 17006 grad_norm: 4.2150 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7666 loss: 1.7666 2022/10/13 03:15:59 - mmengine - INFO - Epoch(train) [33][500/940] lr: 1.0000e-02 eta: 9:01:59 time: 0.5269 data_time: 0.0367 memory: 17006 grad_norm: 4.1169 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7555 loss: 1.7555 2022/10/13 03:16:08 - mmengine - INFO - Epoch(train) [33][520/940] lr: 1.0000e-02 eta: 9:01:47 time: 0.4682 data_time: 0.0256 memory: 17006 grad_norm: 4.1412 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.7173 loss: 1.7173 2022/10/13 03:16:19 - mmengine - INFO - Epoch(train) [33][540/940] lr: 1.0000e-02 eta: 9:01:37 time: 0.5210 data_time: 0.0317 memory: 17006 grad_norm: 4.2794 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7591 loss: 1.7591 2022/10/13 03:16:29 - mmengine - INFO - Epoch(train) [33][560/940] lr: 1.0000e-02 eta: 9:01:27 time: 0.5263 data_time: 0.0248 memory: 17006 grad_norm: 4.1068 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.7794 loss: 1.7794 2022/10/13 03:16:39 - mmengine - INFO - Epoch(train) [33][580/940] lr: 1.0000e-02 eta: 9:01:16 time: 0.4987 data_time: 0.0347 memory: 17006 grad_norm: 4.2105 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.7747 loss: 1.7747 2022/10/13 03:16:50 - mmengine - INFO - Epoch(train) [33][600/940] lr: 1.0000e-02 eta: 9:01:06 time: 0.5152 data_time: 0.0593 memory: 17006 grad_norm: 4.1580 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.7137 loss: 1.7137 2022/10/13 03:17:00 - mmengine - INFO - Epoch(train) [33][620/940] lr: 1.0000e-02 eta: 9:00:55 time: 0.5071 data_time: 0.0340 memory: 17006 grad_norm: 4.1493 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7635 loss: 1.7635 2022/10/13 03:17:10 - mmengine - INFO - Epoch(train) [33][640/940] lr: 1.0000e-02 eta: 9:00:45 time: 0.5155 data_time: 0.0273 memory: 17006 grad_norm: 4.1778 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.8679 loss: 1.8679 2022/10/13 03:17:20 - mmengine - INFO - Epoch(train) [33][660/940] lr: 1.0000e-02 eta: 9:00:34 time: 0.4794 data_time: 0.0346 memory: 17006 grad_norm: 4.2177 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.8107 loss: 1.8107 2022/10/13 03:17:30 - mmengine - INFO - Epoch(train) [33][680/940] lr: 1.0000e-02 eta: 9:00:23 time: 0.5106 data_time: 0.0318 memory: 17006 grad_norm: 4.2316 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7294 loss: 1.7294 2022/10/13 03:17:40 - mmengine - INFO - Epoch(train) [33][700/940] lr: 1.0000e-02 eta: 9:00:12 time: 0.4908 data_time: 0.0315 memory: 17006 grad_norm: 4.1886 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 1.8495 loss: 1.8495 2022/10/13 03:17:50 - mmengine - INFO - Epoch(train) [33][720/940] lr: 1.0000e-02 eta: 9:00:02 time: 0.5138 data_time: 0.0299 memory: 17006 grad_norm: 4.1446 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7866 loss: 1.7866 2022/10/13 03:18:00 - mmengine - INFO - Epoch(train) [33][740/940] lr: 1.0000e-02 eta: 8:59:52 time: 0.5150 data_time: 0.0322 memory: 17006 grad_norm: 4.2573 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7202 loss: 1.7202 2022/10/13 03:18:10 - mmengine - INFO - Epoch(train) [33][760/940] lr: 1.0000e-02 eta: 8:59:41 time: 0.4971 data_time: 0.0309 memory: 17006 grad_norm: 4.1696 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5935 loss: 1.5935 2022/10/13 03:18:20 - mmengine - INFO - Epoch(train) [33][780/940] lr: 1.0000e-02 eta: 8:59:29 time: 0.4822 data_time: 0.0306 memory: 17006 grad_norm: 4.2682 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7932 loss: 1.7932 2022/10/13 03:18:31 - mmengine - INFO - Epoch(train) [33][800/940] lr: 1.0000e-02 eta: 8:59:22 time: 0.5733 data_time: 0.0336 memory: 17006 grad_norm: 4.2591 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.8126 loss: 1.8126 2022/10/13 03:18:41 - mmengine - INFO - Epoch(train) [33][820/940] lr: 1.0000e-02 eta: 8:59:10 time: 0.4730 data_time: 0.0297 memory: 17006 grad_norm: 4.2518 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6205 loss: 1.6205 2022/10/13 03:18:52 - mmengine - INFO - Epoch(train) [33][840/940] lr: 1.0000e-02 eta: 8:59:01 time: 0.5424 data_time: 0.0366 memory: 17006 grad_norm: 4.1056 top1_acc: 0.4688 top5_acc: 0.5938 loss_cls: 1.6285 loss: 1.6285 2022/10/13 03:19:00 - mmengine - INFO - Epoch(train) [33][860/940] lr: 1.0000e-02 eta: 8:58:47 time: 0.4290 data_time: 0.0295 memory: 17006 grad_norm: 4.2413 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.7798 loss: 1.7798 2022/10/13 03:19:11 - mmengine - INFO - Epoch(train) [33][880/940] lr: 1.0000e-02 eta: 8:58:38 time: 0.5458 data_time: 0.0415 memory: 17006 grad_norm: 4.0877 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6786 loss: 1.6786 2022/10/13 03:19:20 - mmengine - INFO - Epoch(train) [33][900/940] lr: 1.0000e-02 eta: 8:58:26 time: 0.4544 data_time: 0.0274 memory: 17006 grad_norm: 4.2187 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7435 loss: 1.7435 2022/10/13 03:19:30 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 03:19:30 - mmengine - INFO - Epoch(train) [33][920/940] lr: 1.0000e-02 eta: 8:58:15 time: 0.5050 data_time: 0.0336 memory: 17006 grad_norm: 4.1757 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6831 loss: 1.6831 2022/10/13 03:19:39 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 03:19:39 - mmengine - INFO - Epoch(train) [33][940/940] lr: 1.0000e-02 eta: 8:58:02 time: 0.4453 data_time: 0.0275 memory: 17006 grad_norm: 4.4143 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.7908 loss: 1.7908 2022/10/13 03:19:39 - mmengine - INFO - Saving checkpoint at 33 epochs 2022/10/13 03:19:53 - mmengine - INFO - Epoch(val) [33][20/78] eta: 0:00:37 time: 0.6380 data_time: 0.5474 memory: 3172 2022/10/13 03:20:01 - mmengine - INFO - Epoch(val) [33][40/78] eta: 0:00:16 time: 0.4288 data_time: 0.3389 memory: 3172 2022/10/13 03:20:13 - mmengine - INFO - Epoch(val) [33][60/78] eta: 0:00:10 time: 0.5667 data_time: 0.4762 memory: 3172 2022/10/13 03:20:22 - mmengine - INFO - Epoch(val) [33][78/78] acc/top1: 0.6236 acc/top5: 0.8394 acc/mean1: 0.6235 2022/10/13 03:20:36 - mmengine - INFO - Epoch(train) [34][20/940] lr: 1.0000e-02 eta: 8:58:00 time: 0.7170 data_time: 0.4034 memory: 17006 grad_norm: 4.1831 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6998 loss: 1.6998 2022/10/13 03:20:45 - mmengine - INFO - Epoch(train) [34][40/940] lr: 1.0000e-02 eta: 8:57:48 time: 0.4657 data_time: 0.1602 memory: 17006 grad_norm: 4.2071 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7004 loss: 1.7004 2022/10/13 03:20:56 - mmengine - INFO - Epoch(train) [34][60/940] lr: 1.0000e-02 eta: 8:57:39 time: 0.5342 data_time: 0.1013 memory: 17006 grad_norm: 4.1937 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6424 loss: 1.6424 2022/10/13 03:21:06 - mmengine - INFO - Epoch(train) [34][80/940] lr: 1.0000e-02 eta: 8:57:27 time: 0.4789 data_time: 0.0264 memory: 17006 grad_norm: 4.1397 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7631 loss: 1.7631 2022/10/13 03:21:17 - mmengine - INFO - Epoch(train) [34][100/940] lr: 1.0000e-02 eta: 8:57:19 time: 0.5810 data_time: 0.0314 memory: 17006 grad_norm: 4.0836 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6653 loss: 1.6653 2022/10/13 03:21:26 - mmengine - INFO - Epoch(train) [34][120/940] lr: 1.0000e-02 eta: 8:57:06 time: 0.4398 data_time: 0.0295 memory: 17006 grad_norm: 4.2159 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5850 loss: 1.5850 2022/10/13 03:21:37 - mmengine - INFO - Epoch(train) [34][140/940] lr: 1.0000e-02 eta: 8:56:57 time: 0.5335 data_time: 0.0301 memory: 17006 grad_norm: 4.1667 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7637 loss: 1.7637 2022/10/13 03:21:46 - mmengine - INFO - Epoch(train) [34][160/940] lr: 1.0000e-02 eta: 8:56:45 time: 0.4832 data_time: 0.0312 memory: 17006 grad_norm: 4.2048 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.7373 loss: 1.7373 2022/10/13 03:21:57 - mmengine - INFO - Epoch(train) [34][180/940] lr: 1.0000e-02 eta: 8:56:36 time: 0.5337 data_time: 0.0324 memory: 17006 grad_norm: 4.0920 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6577 loss: 1.6577 2022/10/13 03:22:07 - mmengine - INFO - Epoch(train) [34][200/940] lr: 1.0000e-02 eta: 8:56:26 time: 0.5136 data_time: 0.0303 memory: 17006 grad_norm: 4.1712 top1_acc: 0.4688 top5_acc: 0.8750 loss_cls: 1.6641 loss: 1.6641 2022/10/13 03:22:19 - mmengine - INFO - Epoch(train) [34][220/940] lr: 1.0000e-02 eta: 8:56:17 time: 0.5612 data_time: 0.0352 memory: 17006 grad_norm: 4.2058 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5772 loss: 1.5772 2022/10/13 03:22:28 - mmengine - INFO - Epoch(train) [34][240/940] lr: 1.0000e-02 eta: 8:56:04 time: 0.4461 data_time: 0.0295 memory: 17006 grad_norm: 4.1761 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7235 loss: 1.7235 2022/10/13 03:22:38 - mmengine - INFO - Epoch(train) [34][260/940] lr: 1.0000e-02 eta: 8:55:55 time: 0.5307 data_time: 0.0310 memory: 17006 grad_norm: 4.1874 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.7084 loss: 1.7084 2022/10/13 03:22:48 - mmengine - INFO - Epoch(train) [34][280/940] lr: 1.0000e-02 eta: 8:55:43 time: 0.4728 data_time: 0.0307 memory: 17006 grad_norm: 4.2373 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7356 loss: 1.7356 2022/10/13 03:22:58 - mmengine - INFO - Epoch(train) [34][300/940] lr: 1.0000e-02 eta: 8:55:33 time: 0.5234 data_time: 0.0328 memory: 17006 grad_norm: 4.1253 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5802 loss: 1.5802 2022/10/13 03:23:08 - mmengine - INFO - Epoch(train) [34][320/940] lr: 1.0000e-02 eta: 8:55:22 time: 0.4805 data_time: 0.0399 memory: 17006 grad_norm: 4.1937 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7334 loss: 1.7334 2022/10/13 03:23:18 - mmengine - INFO - Epoch(train) [34][340/940] lr: 1.0000e-02 eta: 8:55:12 time: 0.5264 data_time: 0.0404 memory: 17006 grad_norm: 4.1654 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.6091 loss: 1.6091 2022/10/13 03:23:28 - mmengine - INFO - Epoch(train) [34][360/940] lr: 1.0000e-02 eta: 8:55:00 time: 0.4661 data_time: 0.0333 memory: 17006 grad_norm: 4.2197 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.7198 loss: 1.7198 2022/10/13 03:23:38 - mmengine - INFO - Epoch(train) [34][380/940] lr: 1.0000e-02 eta: 8:54:51 time: 0.5475 data_time: 0.0316 memory: 17006 grad_norm: 4.2748 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.7530 loss: 1.7530 2022/10/13 03:23:49 - mmengine - INFO - Epoch(train) [34][400/940] lr: 1.0000e-02 eta: 8:54:41 time: 0.5077 data_time: 0.0284 memory: 17006 grad_norm: 4.1191 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.5809 loss: 1.5809 2022/10/13 03:23:59 - mmengine - INFO - Epoch(train) [34][420/940] lr: 1.0000e-02 eta: 8:54:30 time: 0.5021 data_time: 0.0321 memory: 17006 grad_norm: 4.2750 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7520 loss: 1.7520 2022/10/13 03:24:09 - mmengine - INFO - Epoch(train) [34][440/940] lr: 1.0000e-02 eta: 8:54:21 time: 0.5344 data_time: 0.0335 memory: 17006 grad_norm: 4.2317 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6384 loss: 1.6384 2022/10/13 03:24:19 - mmengine - INFO - Epoch(train) [34][460/940] lr: 1.0000e-02 eta: 8:54:10 time: 0.5021 data_time: 0.0318 memory: 17006 grad_norm: 4.1806 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6372 loss: 1.6372 2022/10/13 03:24:29 - mmengine - INFO - Epoch(train) [34][480/940] lr: 1.0000e-02 eta: 8:53:59 time: 0.4930 data_time: 0.0307 memory: 17006 grad_norm: 4.2267 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7019 loss: 1.7019 2022/10/13 03:24:40 - mmengine - INFO - Epoch(train) [34][500/940] lr: 1.0000e-02 eta: 8:53:49 time: 0.5114 data_time: 0.0362 memory: 17006 grad_norm: 4.3019 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.7528 loss: 1.7528 2022/10/13 03:24:50 - mmengine - INFO - Epoch(train) [34][520/940] lr: 1.0000e-02 eta: 8:53:39 time: 0.5248 data_time: 0.0293 memory: 17006 grad_norm: 4.1358 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.6524 loss: 1.6524 2022/10/13 03:25:00 - mmengine - INFO - Epoch(train) [34][540/940] lr: 1.0000e-02 eta: 8:53:29 time: 0.5229 data_time: 0.0351 memory: 17006 grad_norm: 4.1506 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5873 loss: 1.5873 2022/10/13 03:25:11 - mmengine - INFO - Epoch(train) [34][560/940] lr: 1.0000e-02 eta: 8:53:19 time: 0.5223 data_time: 0.0316 memory: 17006 grad_norm: 4.1595 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.6806 loss: 1.6806 2022/10/13 03:25:21 - mmengine - INFO - Epoch(train) [34][580/940] lr: 1.0000e-02 eta: 8:53:09 time: 0.5105 data_time: 0.0299 memory: 17006 grad_norm: 4.1706 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.6863 loss: 1.6863 2022/10/13 03:25:32 - mmengine - INFO - Epoch(train) [34][600/940] lr: 1.0000e-02 eta: 8:52:59 time: 0.5375 data_time: 0.0310 memory: 17006 grad_norm: 4.2209 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8170 loss: 1.8170 2022/10/13 03:25:42 - mmengine - INFO - Epoch(train) [34][620/940] lr: 1.0000e-02 eta: 8:52:48 time: 0.4948 data_time: 0.0312 memory: 17006 grad_norm: 4.2804 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6605 loss: 1.6605 2022/10/13 03:25:52 - mmengine - INFO - Epoch(train) [34][640/940] lr: 1.0000e-02 eta: 8:52:38 time: 0.4957 data_time: 0.0280 memory: 17006 grad_norm: 4.2090 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6045 loss: 1.6045 2022/10/13 03:26:00 - mmengine - INFO - Epoch(train) [34][660/940] lr: 1.0000e-02 eta: 8:52:24 time: 0.4319 data_time: 0.0314 memory: 17006 grad_norm: 4.1591 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7571 loss: 1.7571 2022/10/13 03:26:11 - mmengine - INFO - Epoch(train) [34][680/940] lr: 1.0000e-02 eta: 8:52:15 time: 0.5312 data_time: 0.0370 memory: 17006 grad_norm: 4.1841 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6502 loss: 1.6502 2022/10/13 03:26:21 - mmengine - INFO - Epoch(train) [34][700/940] lr: 1.0000e-02 eta: 8:52:05 time: 0.5170 data_time: 0.0275 memory: 17006 grad_norm: 4.2106 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6260 loss: 1.6260 2022/10/13 03:26:31 - mmengine - INFO - Epoch(train) [34][720/940] lr: 1.0000e-02 eta: 8:51:54 time: 0.5005 data_time: 0.0376 memory: 17006 grad_norm: 4.2567 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.5893 loss: 1.5893 2022/10/13 03:26:41 - mmengine - INFO - Epoch(train) [34][740/940] lr: 1.0000e-02 eta: 8:51:42 time: 0.4717 data_time: 0.0304 memory: 17006 grad_norm: 4.2054 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.8383 loss: 1.8383 2022/10/13 03:26:52 - mmengine - INFO - Epoch(train) [34][760/940] lr: 1.0000e-02 eta: 8:51:33 time: 0.5529 data_time: 0.0386 memory: 17006 grad_norm: 4.3103 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.7799 loss: 1.7799 2022/10/13 03:27:02 - mmengine - INFO - Epoch(train) [34][780/940] lr: 1.0000e-02 eta: 8:51:22 time: 0.4924 data_time: 0.0318 memory: 17006 grad_norm: 4.2377 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6033 loss: 1.6033 2022/10/13 03:27:13 - mmengine - INFO - Epoch(train) [34][800/940] lr: 1.0000e-02 eta: 8:51:14 time: 0.5716 data_time: 0.0372 memory: 17006 grad_norm: 4.1179 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6785 loss: 1.6785 2022/10/13 03:27:23 - mmengine - INFO - Epoch(train) [34][820/940] lr: 1.0000e-02 eta: 8:51:02 time: 0.4728 data_time: 0.0284 memory: 17006 grad_norm: 4.1498 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6507 loss: 1.6507 2022/10/13 03:27:32 - mmengine - INFO - Epoch(train) [34][840/940] lr: 1.0000e-02 eta: 8:50:51 time: 0.4739 data_time: 0.0296 memory: 17006 grad_norm: 4.1709 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6618 loss: 1.6618 2022/10/13 03:27:42 - mmengine - INFO - Epoch(train) [34][860/940] lr: 1.0000e-02 eta: 8:50:40 time: 0.5013 data_time: 0.0332 memory: 17006 grad_norm: 4.2080 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6565 loss: 1.6565 2022/10/13 03:27:51 - mmengine - INFO - Epoch(train) [34][880/940] lr: 1.0000e-02 eta: 8:50:28 time: 0.4668 data_time: 0.0325 memory: 17006 grad_norm: 4.1972 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7177 loss: 1.7177 2022/10/13 03:28:03 - mmengine - INFO - Epoch(train) [34][900/940] lr: 1.0000e-02 eta: 8:50:20 time: 0.5774 data_time: 0.0338 memory: 17006 grad_norm: 4.2285 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7626 loss: 1.7626 2022/10/13 03:28:12 - mmengine - INFO - Epoch(train) [34][920/940] lr: 1.0000e-02 eta: 8:50:08 time: 0.4628 data_time: 0.0299 memory: 17006 grad_norm: 4.2119 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.8123 loss: 1.8123 2022/10/13 03:28:22 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 03:28:22 - mmengine - INFO - Epoch(train) [34][940/940] lr: 1.0000e-02 eta: 8:49:58 time: 0.5105 data_time: 0.0299 memory: 17006 grad_norm: 4.4337 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.7648 loss: 1.7648 2022/10/13 03:28:35 - mmengine - INFO - Epoch(val) [34][20/78] eta: 0:00:36 time: 0.6244 data_time: 0.5316 memory: 3172 2022/10/13 03:28:44 - mmengine - INFO - Epoch(val) [34][40/78] eta: 0:00:16 time: 0.4356 data_time: 0.3438 memory: 3172 2022/10/13 03:28:55 - mmengine - INFO - Epoch(val) [34][60/78] eta: 0:00:10 time: 0.5801 data_time: 0.4880 memory: 3172 2022/10/13 03:29:05 - mmengine - INFO - Epoch(val) [34][78/78] acc/top1: 0.6174 acc/top5: 0.8323 acc/mean1: 0.6174 2022/10/13 03:29:19 - mmengine - INFO - Epoch(train) [35][20/940] lr: 1.0000e-02 eta: 8:49:56 time: 0.7213 data_time: 0.2785 memory: 17006 grad_norm: 4.1730 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6899 loss: 1.6899 2022/10/13 03:29:29 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 03:29:29 - mmengine - INFO - Epoch(train) [35][40/940] lr: 1.0000e-02 eta: 8:49:44 time: 0.4758 data_time: 0.0265 memory: 17006 grad_norm: 4.2740 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7882 loss: 1.7882 2022/10/13 03:29:41 - mmengine - INFO - Epoch(train) [35][60/940] lr: 1.0000e-02 eta: 8:49:36 time: 0.5795 data_time: 0.0366 memory: 17006 grad_norm: 4.2277 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7582 loss: 1.7582 2022/10/13 03:29:50 - mmengine - INFO - Epoch(train) [35][80/940] lr: 1.0000e-02 eta: 8:49:25 time: 0.4815 data_time: 0.0284 memory: 17006 grad_norm: 4.1737 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6548 loss: 1.6548 2022/10/13 03:30:00 - mmengine - INFO - Epoch(train) [35][100/940] lr: 1.0000e-02 eta: 8:49:13 time: 0.4794 data_time: 0.0322 memory: 17006 grad_norm: 4.1274 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6056 loss: 1.6056 2022/10/13 03:30:10 - mmengine - INFO - Epoch(train) [35][120/940] lr: 1.0000e-02 eta: 8:49:03 time: 0.5113 data_time: 0.0293 memory: 17006 grad_norm: 4.2225 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5980 loss: 1.5980 2022/10/13 03:30:20 - mmengine - INFO - Epoch(train) [35][140/940] lr: 1.0000e-02 eta: 8:48:52 time: 0.5067 data_time: 0.0308 memory: 17006 grad_norm: 4.2387 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6450 loss: 1.6450 2022/10/13 03:30:31 - mmengine - INFO - Epoch(train) [35][160/940] lr: 1.0000e-02 eta: 8:48:43 time: 0.5390 data_time: 0.0285 memory: 17006 grad_norm: 4.1975 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6617 loss: 1.6617 2022/10/13 03:30:41 - mmengine - INFO - Epoch(train) [35][180/940] lr: 1.0000e-02 eta: 8:48:32 time: 0.4858 data_time: 0.0332 memory: 17006 grad_norm: 4.1795 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6374 loss: 1.6374 2022/10/13 03:30:51 - mmengine - INFO - Epoch(train) [35][200/940] lr: 1.0000e-02 eta: 8:48:22 time: 0.5248 data_time: 0.0298 memory: 17006 grad_norm: 4.1926 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5792 loss: 1.5792 2022/10/13 03:31:02 - mmengine - INFO - Epoch(train) [35][220/940] lr: 1.0000e-02 eta: 8:48:13 time: 0.5406 data_time: 0.0286 memory: 17006 grad_norm: 4.1997 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.8658 loss: 1.8658 2022/10/13 03:31:13 - mmengine - INFO - Epoch(train) [35][240/940] lr: 1.0000e-02 eta: 8:48:04 time: 0.5580 data_time: 0.0278 memory: 17006 grad_norm: 4.2550 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7605 loss: 1.7605 2022/10/13 03:31:23 - mmengine - INFO - Epoch(train) [35][260/940] lr: 1.0000e-02 eta: 8:47:53 time: 0.4812 data_time: 0.0357 memory: 17006 grad_norm: 4.1621 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.6579 loss: 1.6579 2022/10/13 03:31:34 - mmengine - INFO - Epoch(train) [35][280/940] lr: 1.0000e-02 eta: 8:47:44 time: 0.5363 data_time: 0.0395 memory: 17006 grad_norm: 4.2598 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7167 loss: 1.7167 2022/10/13 03:31:43 - mmengine - INFO - Epoch(train) [35][300/940] lr: 1.0000e-02 eta: 8:47:32 time: 0.4770 data_time: 0.0266 memory: 17006 grad_norm: 4.1446 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7438 loss: 1.7438 2022/10/13 03:31:54 - mmengine - INFO - Epoch(train) [35][320/940] lr: 1.0000e-02 eta: 8:47:23 time: 0.5447 data_time: 0.0331 memory: 17006 grad_norm: 4.2051 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7555 loss: 1.7555 2022/10/13 03:32:02 - mmengine - INFO - Epoch(train) [35][340/940] lr: 1.0000e-02 eta: 8:47:09 time: 0.4216 data_time: 0.0359 memory: 17006 grad_norm: 4.2177 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7034 loss: 1.7034 2022/10/13 03:32:13 - mmengine - INFO - Epoch(train) [35][360/940] lr: 1.0000e-02 eta: 8:47:01 time: 0.5529 data_time: 0.0327 memory: 17006 grad_norm: 4.1553 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6004 loss: 1.6004 2022/10/13 03:32:23 - mmengine - INFO - Epoch(train) [35][380/940] lr: 1.0000e-02 eta: 8:46:49 time: 0.4903 data_time: 0.0377 memory: 17006 grad_norm: 4.2438 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.7953 loss: 1.7953 2022/10/13 03:32:34 - mmengine - INFO - Epoch(train) [35][400/940] lr: 1.0000e-02 eta: 8:46:41 time: 0.5513 data_time: 0.0339 memory: 17006 grad_norm: 4.2061 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7473 loss: 1.7473 2022/10/13 03:32:44 - mmengine - INFO - Epoch(train) [35][420/940] lr: 1.0000e-02 eta: 8:46:29 time: 0.4813 data_time: 0.0291 memory: 17006 grad_norm: 4.2184 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6482 loss: 1.6482 2022/10/13 03:32:54 - mmengine - INFO - Epoch(train) [35][440/940] lr: 1.0000e-02 eta: 8:46:19 time: 0.5040 data_time: 0.0344 memory: 17006 grad_norm: 4.1743 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.7153 loss: 1.7153 2022/10/13 03:33:03 - mmengine - INFO - Epoch(train) [35][460/940] lr: 1.0000e-02 eta: 8:46:05 time: 0.4324 data_time: 0.0268 memory: 17006 grad_norm: 4.1629 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.7791 loss: 1.7791 2022/10/13 03:33:14 - mmengine - INFO - Epoch(train) [35][480/940] lr: 1.0000e-02 eta: 8:45:56 time: 0.5459 data_time: 0.0332 memory: 17006 grad_norm: 4.1912 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7765 loss: 1.7765 2022/10/13 03:33:22 - mmengine - INFO - Epoch(train) [35][500/940] lr: 1.0000e-02 eta: 8:45:44 time: 0.4449 data_time: 0.0262 memory: 17006 grad_norm: 4.2843 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.8015 loss: 1.8015 2022/10/13 03:33:33 - mmengine - INFO - Epoch(train) [35][520/940] lr: 1.0000e-02 eta: 8:45:33 time: 0.5071 data_time: 0.0419 memory: 17006 grad_norm: 4.2868 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7581 loss: 1.7581 2022/10/13 03:33:42 - mmengine - INFO - Epoch(train) [35][540/940] lr: 1.0000e-02 eta: 8:45:22 time: 0.4949 data_time: 0.0342 memory: 17006 grad_norm: 4.2183 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.8120 loss: 1.8120 2022/10/13 03:33:54 - mmengine - INFO - Epoch(train) [35][560/940] lr: 1.0000e-02 eta: 8:45:14 time: 0.5762 data_time: 0.0324 memory: 17006 grad_norm: 4.2061 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7456 loss: 1.7456 2022/10/13 03:34:03 - mmengine - INFO - Epoch(train) [35][580/940] lr: 1.0000e-02 eta: 8:45:02 time: 0.4682 data_time: 0.0272 memory: 17006 grad_norm: 4.2330 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7123 loss: 1.7123 2022/10/13 03:34:14 - mmengine - INFO - Epoch(train) [35][600/940] lr: 1.0000e-02 eta: 8:44:53 time: 0.5289 data_time: 0.0391 memory: 17006 grad_norm: 4.1244 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6489 loss: 1.6489 2022/10/13 03:34:24 - mmengine - INFO - Epoch(train) [35][620/940] lr: 1.0000e-02 eta: 8:44:43 time: 0.5190 data_time: 0.0280 memory: 17006 grad_norm: 4.1852 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.6763 loss: 1.6763 2022/10/13 03:34:34 - mmengine - INFO - Epoch(train) [35][640/940] lr: 1.0000e-02 eta: 8:44:31 time: 0.4800 data_time: 0.0343 memory: 17006 grad_norm: 4.1390 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6351 loss: 1.6351 2022/10/13 03:34:43 - mmengine - INFO - Epoch(train) [35][660/940] lr: 1.0000e-02 eta: 8:44:19 time: 0.4542 data_time: 0.0301 memory: 17006 grad_norm: 4.1869 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 1.7119 loss: 1.7119 2022/10/13 03:34:53 - mmengine - INFO - Epoch(train) [35][680/940] lr: 1.0000e-02 eta: 8:44:09 time: 0.5222 data_time: 0.0310 memory: 17006 grad_norm: 4.1673 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6623 loss: 1.6623 2022/10/13 03:35:03 - mmengine - INFO - Epoch(train) [35][700/940] lr: 1.0000e-02 eta: 8:43:57 time: 0.4786 data_time: 0.0377 memory: 17006 grad_norm: 4.1852 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6985 loss: 1.6985 2022/10/13 03:35:14 - mmengine - INFO - Epoch(train) [35][720/940] lr: 1.0000e-02 eta: 8:43:49 time: 0.5543 data_time: 0.0636 memory: 17006 grad_norm: 4.1467 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7647 loss: 1.7647 2022/10/13 03:35:24 - mmengine - INFO - Epoch(train) [35][740/940] lr: 1.0000e-02 eta: 8:43:38 time: 0.5076 data_time: 0.1239 memory: 17006 grad_norm: 4.1771 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.6495 loss: 1.6495 2022/10/13 03:35:34 - mmengine - INFO - Epoch(train) [35][760/940] lr: 1.0000e-02 eta: 8:43:27 time: 0.4851 data_time: 0.0693 memory: 17006 grad_norm: 4.2220 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6673 loss: 1.6673 2022/10/13 03:35:44 - mmengine - INFO - Epoch(train) [35][780/940] lr: 1.0000e-02 eta: 8:43:16 time: 0.4978 data_time: 0.0507 memory: 17006 grad_norm: 4.2991 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.7393 loss: 1.7393 2022/10/13 03:35:55 - mmengine - INFO - Epoch(train) [35][800/940] lr: 1.0000e-02 eta: 8:43:07 time: 0.5297 data_time: 0.0255 memory: 17006 grad_norm: 4.2248 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7057 loss: 1.7057 2022/10/13 03:36:04 - mmengine - INFO - Epoch(train) [35][820/940] lr: 1.0000e-02 eta: 8:42:56 time: 0.4915 data_time: 0.0317 memory: 17006 grad_norm: 4.1855 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7057 loss: 1.7057 2022/10/13 03:36:16 - mmengine - INFO - Epoch(train) [35][840/940] lr: 1.0000e-02 eta: 8:42:47 time: 0.5600 data_time: 0.0276 memory: 17006 grad_norm: 4.1854 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5651 loss: 1.5651 2022/10/13 03:36:26 - mmengine - INFO - Epoch(train) [35][860/940] lr: 1.0000e-02 eta: 8:42:36 time: 0.4998 data_time: 0.0353 memory: 17006 grad_norm: 4.2456 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.7137 loss: 1.7137 2022/10/13 03:36:36 - mmengine - INFO - Epoch(train) [35][880/940] lr: 1.0000e-02 eta: 8:42:27 time: 0.5261 data_time: 0.0293 memory: 17006 grad_norm: 4.2319 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.8965 loss: 1.8965 2022/10/13 03:36:45 - mmengine - INFO - Epoch(train) [35][900/940] lr: 1.0000e-02 eta: 8:42:15 time: 0.4629 data_time: 0.0300 memory: 17006 grad_norm: 4.2369 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.8349 loss: 1.8349 2022/10/13 03:36:56 - mmengine - INFO - Epoch(train) [35][920/940] lr: 1.0000e-02 eta: 8:42:05 time: 0.5248 data_time: 0.0394 memory: 17006 grad_norm: 4.1517 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7633 loss: 1.7633 2022/10/13 03:37:04 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 03:37:04 - mmengine - INFO - Epoch(train) [35][940/940] lr: 1.0000e-02 eta: 8:41:51 time: 0.4243 data_time: 0.0271 memory: 17006 grad_norm: 4.3665 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.6494 loss: 1.6494 2022/10/13 03:37:17 - mmengine - INFO - Epoch(val) [35][20/78] eta: 0:00:36 time: 0.6293 data_time: 0.5360 memory: 3172 2022/10/13 03:37:26 - mmengine - INFO - Epoch(val) [35][40/78] eta: 0:00:16 time: 0.4385 data_time: 0.3465 memory: 3172 2022/10/13 03:37:37 - mmengine - INFO - Epoch(val) [35][60/78] eta: 0:00:10 time: 0.5634 data_time: 0.4719 memory: 3172 2022/10/13 03:37:47 - mmengine - INFO - Epoch(val) [35][78/78] acc/top1: 0.6287 acc/top5: 0.8430 acc/mean1: 0.6286 2022/10/13 03:37:47 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_29.pth is removed 2022/10/13 03:37:48 - mmengine - INFO - The best checkpoint with 0.6287 acc/top1 at 35 epoch is saved to best_acc/top1_epoch_35.pth. 2022/10/13 03:38:01 - mmengine - INFO - Epoch(train) [36][20/940] lr: 1.0000e-02 eta: 8:41:47 time: 0.6876 data_time: 0.3715 memory: 17006 grad_norm: 4.2913 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.6753 loss: 1.6753 2022/10/13 03:38:11 - mmengine - INFO - Epoch(train) [36][40/940] lr: 1.0000e-02 eta: 8:41:37 time: 0.5056 data_time: 0.1883 memory: 17006 grad_norm: 4.1924 top1_acc: 0.5938 top5_acc: 0.9688 loss_cls: 1.7458 loss: 1.7458 2022/10/13 03:38:22 - mmengine - INFO - Epoch(train) [36][60/940] lr: 1.0000e-02 eta: 8:41:27 time: 0.5274 data_time: 0.2040 memory: 17006 grad_norm: 4.1656 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.6851 loss: 1.6851 2022/10/13 03:38:31 - mmengine - INFO - Epoch(train) [36][80/940] lr: 1.0000e-02 eta: 8:41:14 time: 0.4389 data_time: 0.1101 memory: 17006 grad_norm: 4.1469 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6032 loss: 1.6032 2022/10/13 03:38:41 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 03:38:41 - mmengine - INFO - Epoch(train) [36][100/940] lr: 1.0000e-02 eta: 8:41:05 time: 0.5314 data_time: 0.1640 memory: 17006 grad_norm: 4.1509 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6295 loss: 1.6295 2022/10/13 03:38:51 - mmengine - INFO - Epoch(train) [36][120/940] lr: 1.0000e-02 eta: 8:40:53 time: 0.4701 data_time: 0.0855 memory: 17006 grad_norm: 4.2006 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7542 loss: 1.7542 2022/10/13 03:39:01 - mmengine - INFO - Epoch(train) [36][140/940] lr: 1.0000e-02 eta: 8:40:43 time: 0.5351 data_time: 0.2020 memory: 17006 grad_norm: 4.1534 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.5335 loss: 1.5335 2022/10/13 03:39:11 - mmengine - INFO - Epoch(train) [36][160/940] lr: 1.0000e-02 eta: 8:40:32 time: 0.4888 data_time: 0.1582 memory: 17006 grad_norm: 4.2834 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.6390 loss: 1.6390 2022/10/13 03:39:22 - mmengine - INFO - Epoch(train) [36][180/940] lr: 1.0000e-02 eta: 8:40:23 time: 0.5417 data_time: 0.1515 memory: 17006 grad_norm: 4.2246 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.7293 loss: 1.7293 2022/10/13 03:39:32 - mmengine - INFO - Epoch(train) [36][200/940] lr: 1.0000e-02 eta: 8:40:13 time: 0.5162 data_time: 0.1611 memory: 17006 grad_norm: 4.2378 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.6710 loss: 1.6710 2022/10/13 03:39:43 - mmengine - INFO - Epoch(train) [36][220/940] lr: 1.0000e-02 eta: 8:40:04 time: 0.5413 data_time: 0.0950 memory: 17006 grad_norm: 4.2528 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.5953 loss: 1.5953 2022/10/13 03:39:53 - mmengine - INFO - Epoch(train) [36][240/940] lr: 1.0000e-02 eta: 8:39:52 time: 0.4801 data_time: 0.0280 memory: 17006 grad_norm: 4.2299 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6591 loss: 1.6591 2022/10/13 03:40:04 - mmengine - INFO - Epoch(train) [36][260/940] lr: 1.0000e-02 eta: 8:39:44 time: 0.5552 data_time: 0.0364 memory: 17006 grad_norm: 4.2866 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.6499 loss: 1.6499 2022/10/13 03:40:13 - mmengine - INFO - Epoch(train) [36][280/940] lr: 1.0000e-02 eta: 8:39:32 time: 0.4706 data_time: 0.0326 memory: 17006 grad_norm: 4.2664 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.8535 loss: 1.8535 2022/10/13 03:40:24 - mmengine - INFO - Epoch(train) [36][300/940] lr: 1.0000e-02 eta: 8:39:22 time: 0.5090 data_time: 0.0379 memory: 17006 grad_norm: 4.1585 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6882 loss: 1.6882 2022/10/13 03:40:34 - mmengine - INFO - Epoch(train) [36][320/940] lr: 1.0000e-02 eta: 8:39:11 time: 0.5117 data_time: 0.0320 memory: 17006 grad_norm: 4.2197 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6567 loss: 1.6567 2022/10/13 03:40:45 - mmengine - INFO - Epoch(train) [36][340/940] lr: 1.0000e-02 eta: 8:39:03 time: 0.5792 data_time: 0.0306 memory: 17006 grad_norm: 4.2316 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.6719 loss: 1.6719 2022/10/13 03:40:55 - mmengine - INFO - Epoch(train) [36][360/940] lr: 1.0000e-02 eta: 8:38:52 time: 0.4851 data_time: 0.0331 memory: 17006 grad_norm: 4.2784 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.6583 loss: 1.6583 2022/10/13 03:41:05 - mmengine - INFO - Epoch(train) [36][380/940] lr: 1.0000e-02 eta: 8:38:42 time: 0.5212 data_time: 0.0280 memory: 17006 grad_norm: 4.1862 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6747 loss: 1.6747 2022/10/13 03:41:15 - mmengine - INFO - Epoch(train) [36][400/940] lr: 1.0000e-02 eta: 8:38:31 time: 0.4715 data_time: 0.0278 memory: 17006 grad_norm: 4.2555 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7802 loss: 1.7802 2022/10/13 03:41:24 - mmengine - INFO - Epoch(train) [36][420/940] lr: 1.0000e-02 eta: 8:38:19 time: 0.4767 data_time: 0.0339 memory: 17006 grad_norm: 4.2158 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7107 loss: 1.7107 2022/10/13 03:41:34 - mmengine - INFO - Epoch(train) [36][440/940] lr: 1.0000e-02 eta: 8:38:08 time: 0.4848 data_time: 0.0337 memory: 17006 grad_norm: 4.2233 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.5986 loss: 1.5986 2022/10/13 03:41:45 - mmengine - INFO - Epoch(train) [36][460/940] lr: 1.0000e-02 eta: 8:37:59 time: 0.5577 data_time: 0.0338 memory: 17006 grad_norm: 4.2752 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7786 loss: 1.7786 2022/10/13 03:41:55 - mmengine - INFO - Epoch(train) [36][480/940] lr: 1.0000e-02 eta: 8:37:48 time: 0.4804 data_time: 0.0296 memory: 17006 grad_norm: 4.1333 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6695 loss: 1.6695 2022/10/13 03:42:06 - mmengine - INFO - Epoch(train) [36][500/940] lr: 1.0000e-02 eta: 8:37:39 time: 0.5659 data_time: 0.0310 memory: 17006 grad_norm: 4.1950 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7132 loss: 1.7132 2022/10/13 03:42:16 - mmengine - INFO - Epoch(train) [36][520/940] lr: 1.0000e-02 eta: 8:37:29 time: 0.5096 data_time: 0.0351 memory: 17006 grad_norm: 4.1983 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.7504 loss: 1.7504 2022/10/13 03:42:27 - mmengine - INFO - Epoch(train) [36][540/940] lr: 1.0000e-02 eta: 8:37:20 time: 0.5376 data_time: 0.0315 memory: 17006 grad_norm: 4.2199 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7638 loss: 1.7638 2022/10/13 03:42:36 - mmengine - INFO - Epoch(train) [36][560/940] lr: 1.0000e-02 eta: 8:37:06 time: 0.4295 data_time: 0.0374 memory: 17006 grad_norm: 4.2577 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6712 loss: 1.6712 2022/10/13 03:42:46 - mmengine - INFO - Epoch(train) [36][580/940] lr: 1.0000e-02 eta: 8:36:57 time: 0.5337 data_time: 0.0272 memory: 17006 grad_norm: 4.1688 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7240 loss: 1.7240 2022/10/13 03:42:55 - mmengine - INFO - Epoch(train) [36][600/940] lr: 1.0000e-02 eta: 8:36:43 time: 0.4233 data_time: 0.0342 memory: 17006 grad_norm: 4.2474 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.7193 loss: 1.7193 2022/10/13 03:43:06 - mmengine - INFO - Epoch(train) [36][620/940] lr: 1.0000e-02 eta: 8:36:35 time: 0.5719 data_time: 0.0296 memory: 17006 grad_norm: 4.2172 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6710 loss: 1.6710 2022/10/13 03:43:16 - mmengine - INFO - Epoch(train) [36][640/940] lr: 1.0000e-02 eta: 8:36:23 time: 0.4659 data_time: 0.0428 memory: 17006 grad_norm: 4.2609 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6967 loss: 1.6967 2022/10/13 03:43:26 - mmengine - INFO - Epoch(train) [36][660/940] lr: 1.0000e-02 eta: 8:36:14 time: 0.5369 data_time: 0.0279 memory: 17006 grad_norm: 4.3328 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.8084 loss: 1.8084 2022/10/13 03:43:36 - mmengine - INFO - Epoch(train) [36][680/940] lr: 1.0000e-02 eta: 8:36:03 time: 0.4986 data_time: 0.0376 memory: 17006 grad_norm: 4.2575 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.7837 loss: 1.7837 2022/10/13 03:43:47 - mmengine - INFO - Epoch(train) [36][700/940] lr: 1.0000e-02 eta: 8:35:53 time: 0.5169 data_time: 0.0337 memory: 17006 grad_norm: 4.2661 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.7196 loss: 1.7196 2022/10/13 03:43:57 - mmengine - INFO - Epoch(train) [36][720/940] lr: 1.0000e-02 eta: 8:35:42 time: 0.4919 data_time: 0.0400 memory: 17006 grad_norm: 4.2242 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5684 loss: 1.5684 2022/10/13 03:44:07 - mmengine - INFO - Epoch(train) [36][740/940] lr: 1.0000e-02 eta: 8:35:32 time: 0.5113 data_time: 0.0259 memory: 17006 grad_norm: 4.2053 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.6675 loss: 1.6675 2022/10/13 03:44:17 - mmengine - INFO - Epoch(train) [36][760/940] lr: 1.0000e-02 eta: 8:35:21 time: 0.4946 data_time: 0.0333 memory: 17006 grad_norm: 4.2544 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.6689 loss: 1.6689 2022/10/13 03:44:28 - mmengine - INFO - Epoch(train) [36][780/940] lr: 1.0000e-02 eta: 8:35:12 time: 0.5450 data_time: 0.0336 memory: 17006 grad_norm: 4.1899 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7686 loss: 1.7686 2022/10/13 03:44:38 - mmengine - INFO - Epoch(train) [36][800/940] lr: 1.0000e-02 eta: 8:35:02 time: 0.5072 data_time: 0.0274 memory: 17006 grad_norm: 4.1418 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7419 loss: 1.7419 2022/10/13 03:44:49 - mmengine - INFO - Epoch(train) [36][820/940] lr: 1.0000e-02 eta: 8:34:53 time: 0.5564 data_time: 0.0345 memory: 17006 grad_norm: 4.2599 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6638 loss: 1.6638 2022/10/13 03:44:58 - mmengine - INFO - Epoch(train) [36][840/940] lr: 1.0000e-02 eta: 8:34:40 time: 0.4372 data_time: 0.0309 memory: 17006 grad_norm: 4.1443 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.7523 loss: 1.7523 2022/10/13 03:45:07 - mmengine - INFO - Epoch(train) [36][860/940] lr: 1.0000e-02 eta: 8:34:29 time: 0.4865 data_time: 0.0336 memory: 17006 grad_norm: 4.2454 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.6847 loss: 1.6847 2022/10/13 03:45:17 - mmengine - INFO - Epoch(train) [36][880/940] lr: 1.0000e-02 eta: 8:34:18 time: 0.5016 data_time: 0.0340 memory: 17006 grad_norm: 4.2291 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.6052 loss: 1.6052 2022/10/13 03:45:28 - mmengine - INFO - Epoch(train) [36][900/940] lr: 1.0000e-02 eta: 8:34:08 time: 0.5154 data_time: 0.0321 memory: 17006 grad_norm: 4.2026 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7234 loss: 1.7234 2022/10/13 03:45:38 - mmengine - INFO - Epoch(train) [36][920/940] lr: 1.0000e-02 eta: 8:33:57 time: 0.5041 data_time: 0.0328 memory: 17006 grad_norm: 4.0815 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.6675 loss: 1.6675 2022/10/13 03:45:47 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 03:45:47 - mmengine - INFO - Epoch(train) [36][940/940] lr: 1.0000e-02 eta: 8:33:46 time: 0.4773 data_time: 0.0287 memory: 17006 grad_norm: 4.3827 top1_acc: 0.5714 top5_acc: 1.0000 loss_cls: 1.7510 loss: 1.7510 2022/10/13 03:45:47 - mmengine - INFO - Saving checkpoint at 36 epochs 2022/10/13 03:46:01 - mmengine - INFO - Epoch(val) [36][20/78] eta: 0:00:36 time: 0.6271 data_time: 0.5353 memory: 3172 2022/10/13 03:46:09 - mmengine - INFO - Epoch(val) [36][40/78] eta: 0:00:16 time: 0.4246 data_time: 0.3340 memory: 3172 2022/10/13 03:46:21 - mmengine - INFO - Epoch(val) [36][60/78] eta: 0:00:10 time: 0.5895 data_time: 0.4982 memory: 3172 2022/10/13 03:46:30 - mmengine - INFO - Epoch(val) [36][78/78] acc/top1: 0.6209 acc/top5: 0.8386 acc/mean1: 0.6208 2022/10/13 03:46:43 - mmengine - INFO - Epoch(train) [37][20/940] lr: 1.0000e-02 eta: 8:33:41 time: 0.6764 data_time: 0.2598 memory: 17006 grad_norm: 4.1322 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.7918 loss: 1.7918 2022/10/13 03:46:53 - mmengine - INFO - Epoch(train) [37][40/940] lr: 1.0000e-02 eta: 8:33:30 time: 0.4674 data_time: 0.0354 memory: 17006 grad_norm: 4.2049 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.6121 loss: 1.6121 2022/10/13 03:47:05 - mmengine - INFO - Epoch(train) [37][60/940] lr: 1.0000e-02 eta: 8:33:23 time: 0.6137 data_time: 0.0324 memory: 17006 grad_norm: 4.1484 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7247 loss: 1.7247 2022/10/13 03:47:15 - mmengine - INFO - Epoch(train) [37][80/940] lr: 1.0000e-02 eta: 8:33:11 time: 0.4744 data_time: 0.0283 memory: 17006 grad_norm: 4.1716 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4724 loss: 1.4724 2022/10/13 03:47:25 - mmengine - INFO - Epoch(train) [37][100/940] lr: 1.0000e-02 eta: 8:33:02 time: 0.5259 data_time: 0.0365 memory: 17006 grad_norm: 4.2150 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.6891 loss: 1.6891 2022/10/13 03:47:34 - mmengine - INFO - Epoch(train) [37][120/940] lr: 1.0000e-02 eta: 8:32:50 time: 0.4654 data_time: 0.0254 memory: 17006 grad_norm: 4.2461 top1_acc: 0.5000 top5_acc: 0.9062 loss_cls: 1.7829 loss: 1.7829 2022/10/13 03:47:46 - mmengine - INFO - Epoch(train) [37][140/940] lr: 1.0000e-02 eta: 8:32:41 time: 0.5680 data_time: 0.0372 memory: 17006 grad_norm: 4.1291 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6041 loss: 1.6041 2022/10/13 03:47:55 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 03:47:55 - mmengine - INFO - Epoch(train) [37][160/940] lr: 1.0000e-02 eta: 8:32:29 time: 0.4474 data_time: 0.0269 memory: 17006 grad_norm: 4.1270 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.5052 loss: 1.5052 2022/10/13 03:48:06 - mmengine - INFO - Epoch(train) [37][180/940] lr: 1.0000e-02 eta: 8:32:20 time: 0.5573 data_time: 0.0330 memory: 17006 grad_norm: 4.2689 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.7271 loss: 1.7271 2022/10/13 03:48:15 - mmengine - INFO - Epoch(train) [37][200/940] lr: 1.0000e-02 eta: 8:32:07 time: 0.4373 data_time: 0.0300 memory: 17006 grad_norm: 4.2019 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5591 loss: 1.5591 2022/10/13 03:48:26 - mmengine - INFO - Epoch(train) [37][220/940] lr: 1.0000e-02 eta: 8:31:59 time: 0.5813 data_time: 0.0354 memory: 17006 grad_norm: 4.2603 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.7650 loss: 1.7650 2022/10/13 03:48:36 - mmengine - INFO - Epoch(train) [37][240/940] lr: 1.0000e-02 eta: 8:31:48 time: 0.4749 data_time: 0.0285 memory: 17006 grad_norm: 4.2481 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6103 loss: 1.6103 2022/10/13 03:48:47 - mmengine - INFO - Epoch(train) [37][260/940] lr: 1.0000e-02 eta: 8:31:40 time: 0.5834 data_time: 0.0277 memory: 17006 grad_norm: 4.3172 top1_acc: 0.3750 top5_acc: 0.6875 loss_cls: 1.6843 loss: 1.6843 2022/10/13 03:48:57 - mmengine - INFO - Epoch(train) [37][280/940] lr: 1.0000e-02 eta: 8:31:29 time: 0.4801 data_time: 0.0335 memory: 17006 grad_norm: 4.2460 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7248 loss: 1.7248 2022/10/13 03:49:08 - mmengine - INFO - Epoch(train) [37][300/940] lr: 1.0000e-02 eta: 8:31:20 time: 0.5459 data_time: 0.0332 memory: 17006 grad_norm: 4.2681 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.7856 loss: 1.7856 2022/10/13 03:49:17 - mmengine - INFO - Epoch(train) [37][320/940] lr: 1.0000e-02 eta: 8:31:08 time: 0.4780 data_time: 0.0295 memory: 17006 grad_norm: 4.2454 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6821 loss: 1.6821 2022/10/13 03:49:28 - mmengine - INFO - Epoch(train) [37][340/940] lr: 1.0000e-02 eta: 8:30:58 time: 0.5045 data_time: 0.0266 memory: 17006 grad_norm: 4.2236 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6590 loss: 1.6590 2022/10/13 03:49:37 - mmengine - INFO - Epoch(train) [37][360/940] lr: 1.0000e-02 eta: 8:30:46 time: 0.4691 data_time: 0.0318 memory: 17006 grad_norm: 4.1991 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.7581 loss: 1.7581 2022/10/13 03:49:49 - mmengine - INFO - Epoch(train) [37][380/940] lr: 1.0000e-02 eta: 8:30:38 time: 0.5912 data_time: 0.0334 memory: 17006 grad_norm: 4.2427 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.5997 loss: 1.5997 2022/10/13 03:49:58 - mmengine - INFO - Epoch(train) [37][400/940] lr: 1.0000e-02 eta: 8:30:26 time: 0.4593 data_time: 0.0259 memory: 17006 grad_norm: 4.2323 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6911 loss: 1.6911 2022/10/13 03:50:09 - mmengine - INFO - Epoch(train) [37][420/940] lr: 1.0000e-02 eta: 8:30:17 time: 0.5348 data_time: 0.0347 memory: 17006 grad_norm: 4.2503 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.5485 loss: 1.5485 2022/10/13 03:50:17 - mmengine - INFO - Epoch(train) [37][440/940] lr: 1.0000e-02 eta: 8:30:04 time: 0.4407 data_time: 0.0324 memory: 17006 grad_norm: 4.1795 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6979 loss: 1.6979 2022/10/13 03:50:28 - mmengine - INFO - Epoch(train) [37][460/940] lr: 1.0000e-02 eta: 8:29:55 time: 0.5418 data_time: 0.0288 memory: 17006 grad_norm: 4.2546 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.5952 loss: 1.5952 2022/10/13 03:50:37 - mmengine - INFO - Epoch(train) [37][480/940] lr: 1.0000e-02 eta: 8:29:42 time: 0.4341 data_time: 0.0309 memory: 17006 grad_norm: 4.2672 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.7545 loss: 1.7545 2022/10/13 03:50:48 - mmengine - INFO - Epoch(train) [37][500/940] lr: 1.0000e-02 eta: 8:29:33 time: 0.5416 data_time: 0.0295 memory: 17006 grad_norm: 4.1761 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 1.6644 loss: 1.6644 2022/10/13 03:50:58 - mmengine - INFO - Epoch(train) [37][520/940] lr: 1.0000e-02 eta: 8:29:22 time: 0.4940 data_time: 0.0375 memory: 17006 grad_norm: 4.1893 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7327 loss: 1.7327 2022/10/13 03:51:07 - mmengine - INFO - Epoch(train) [37][540/940] lr: 1.0000e-02 eta: 8:29:10 time: 0.4820 data_time: 0.0277 memory: 17006 grad_norm: 4.1217 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6249 loss: 1.6249 2022/10/13 03:51:17 - mmengine - INFO - Epoch(train) [37][560/940] lr: 1.0000e-02 eta: 8:29:00 time: 0.5052 data_time: 0.0327 memory: 17006 grad_norm: 4.1573 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.6021 loss: 1.6021 2022/10/13 03:51:27 - mmengine - INFO - Epoch(train) [37][580/940] lr: 1.0000e-02 eta: 8:28:49 time: 0.4946 data_time: 0.0312 memory: 17006 grad_norm: 4.2048 top1_acc: 0.7188 top5_acc: 0.7500 loss_cls: 1.6193 loss: 1.6193 2022/10/13 03:51:37 - mmengine - INFO - Epoch(train) [37][600/940] lr: 1.0000e-02 eta: 8:28:38 time: 0.4766 data_time: 0.0348 memory: 17006 grad_norm: 4.1812 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.7419 loss: 1.7419 2022/10/13 03:51:48 - mmengine - INFO - Epoch(train) [37][620/940] lr: 1.0000e-02 eta: 8:28:29 time: 0.5615 data_time: 0.0296 memory: 17006 grad_norm: 4.2652 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.9181 loss: 1.9181 2022/10/13 03:51:58 - mmengine - INFO - Epoch(train) [37][640/940] lr: 1.0000e-02 eta: 8:28:18 time: 0.4910 data_time: 0.0287 memory: 17006 grad_norm: 4.3151 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.8565 loss: 1.8565 2022/10/13 03:52:10 - mmengine - INFO - Epoch(train) [37][660/940] lr: 1.0000e-02 eta: 8:28:11 time: 0.5934 data_time: 0.0333 memory: 17006 grad_norm: 4.2437 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.7289 loss: 1.7289 2022/10/13 03:52:19 - mmengine - INFO - Epoch(train) [37][680/940] lr: 1.0000e-02 eta: 8:27:59 time: 0.4677 data_time: 0.0352 memory: 17006 grad_norm: 4.2125 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6575 loss: 1.6575 2022/10/13 03:52:30 - mmengine - INFO - Epoch(train) [37][700/940] lr: 1.0000e-02 eta: 8:27:49 time: 0.5265 data_time: 0.0293 memory: 17006 grad_norm: 4.3435 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6834 loss: 1.6834 2022/10/13 03:52:39 - mmengine - INFO - Epoch(train) [37][720/940] lr: 1.0000e-02 eta: 8:27:38 time: 0.4873 data_time: 0.0298 memory: 17006 grad_norm: 4.3207 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7522 loss: 1.7522 2022/10/13 03:52:50 - mmengine - INFO - Epoch(train) [37][740/940] lr: 1.0000e-02 eta: 8:27:28 time: 0.5199 data_time: 0.0309 memory: 17006 grad_norm: 4.2521 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.9021 loss: 1.9021 2022/10/13 03:53:00 - mmengine - INFO - Epoch(train) [37][760/940] lr: 1.0000e-02 eta: 8:27:17 time: 0.4982 data_time: 0.0342 memory: 17006 grad_norm: 4.1784 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6411 loss: 1.6411 2022/10/13 03:53:10 - mmengine - INFO - Epoch(train) [37][780/940] lr: 1.0000e-02 eta: 8:27:07 time: 0.5231 data_time: 0.0322 memory: 17006 grad_norm: 4.2699 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6604 loss: 1.6604 2022/10/13 03:53:20 - mmengine - INFO - Epoch(train) [37][800/940] lr: 1.0000e-02 eta: 8:26:56 time: 0.4929 data_time: 0.0330 memory: 17006 grad_norm: 4.2149 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.7041 loss: 1.7041 2022/10/13 03:53:30 - mmengine - INFO - Epoch(train) [37][820/940] lr: 1.0000e-02 eta: 8:26:46 time: 0.5165 data_time: 0.0347 memory: 17006 grad_norm: 4.2727 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.8096 loss: 1.8096 2022/10/13 03:53:40 - mmengine - INFO - Epoch(train) [37][840/940] lr: 1.0000e-02 eta: 8:26:34 time: 0.4515 data_time: 0.0287 memory: 17006 grad_norm: 4.3046 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7222 loss: 1.7222 2022/10/13 03:53:50 - mmengine - INFO - Epoch(train) [37][860/940] lr: 1.0000e-02 eta: 8:26:24 time: 0.5339 data_time: 0.0367 memory: 17006 grad_norm: 4.3689 top1_acc: 0.3125 top5_acc: 0.6562 loss_cls: 1.8807 loss: 1.8807 2022/10/13 03:54:00 - mmengine - INFO - Epoch(train) [37][880/940] lr: 1.0000e-02 eta: 8:26:14 time: 0.5000 data_time: 0.0329 memory: 17006 grad_norm: 4.3637 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7704 loss: 1.7704 2022/10/13 03:54:11 - mmengine - INFO - Epoch(train) [37][900/940] lr: 1.0000e-02 eta: 8:26:04 time: 0.5411 data_time: 0.0279 memory: 17006 grad_norm: 4.3452 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7253 loss: 1.7253 2022/10/13 03:54:21 - mmengine - INFO - Epoch(train) [37][920/940] lr: 1.0000e-02 eta: 8:25:54 time: 0.5001 data_time: 0.0318 memory: 17006 grad_norm: 4.2182 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6448 loss: 1.6448 2022/10/13 03:54:30 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 03:54:30 - mmengine - INFO - Epoch(train) [37][940/940] lr: 1.0000e-02 eta: 8:25:42 time: 0.4579 data_time: 0.0241 memory: 17006 grad_norm: 4.4595 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.4874 loss: 1.4874 2022/10/13 03:54:43 - mmengine - INFO - Epoch(val) [37][20/78] eta: 0:00:36 time: 0.6318 data_time: 0.5397 memory: 3172 2022/10/13 03:54:52 - mmengine - INFO - Epoch(val) [37][40/78] eta: 0:00:16 time: 0.4352 data_time: 0.3413 memory: 3172 2022/10/13 03:55:03 - mmengine - INFO - Epoch(val) [37][60/78] eta: 0:00:10 time: 0.5677 data_time: 0.4771 memory: 3172 2022/10/13 03:55:13 - mmengine - INFO - Epoch(val) [37][78/78] acc/top1: 0.6211 acc/top5: 0.8412 acc/mean1: 0.6209 2022/10/13 03:55:27 - mmengine - INFO - Epoch(train) [38][20/940] lr: 1.0000e-02 eta: 8:25:37 time: 0.6880 data_time: 0.3666 memory: 17006 grad_norm: 4.2426 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.7031 loss: 1.7031 2022/10/13 03:55:36 - mmengine - INFO - Epoch(train) [38][40/940] lr: 1.0000e-02 eta: 8:25:26 time: 0.4829 data_time: 0.1770 memory: 17006 grad_norm: 4.1437 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.6745 loss: 1.6745 2022/10/13 03:55:47 - mmengine - INFO - Epoch(train) [38][60/940] lr: 1.0000e-02 eta: 8:25:17 time: 0.5477 data_time: 0.2242 memory: 17006 grad_norm: 4.2123 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.7075 loss: 1.7075 2022/10/13 03:55:57 - mmengine - INFO - Epoch(train) [38][80/940] lr: 1.0000e-02 eta: 8:25:06 time: 0.4895 data_time: 0.1627 memory: 17006 grad_norm: 4.2212 top1_acc: 0.7812 top5_acc: 0.7812 loss_cls: 1.6030 loss: 1.6030 2022/10/13 03:56:08 - mmengine - INFO - Epoch(train) [38][100/940] lr: 1.0000e-02 eta: 8:24:57 time: 0.5390 data_time: 0.2120 memory: 17006 grad_norm: 4.1873 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7200 loss: 1.7200 2022/10/13 03:56:18 - mmengine - INFO - Epoch(train) [38][120/940] lr: 1.0000e-02 eta: 8:24:47 time: 0.5151 data_time: 0.1913 memory: 17006 grad_norm: 4.2105 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.5216 loss: 1.5216 2022/10/13 03:56:28 - mmengine - INFO - Epoch(train) [38][140/940] lr: 1.0000e-02 eta: 8:24:36 time: 0.5064 data_time: 0.1875 memory: 17006 grad_norm: 4.2028 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5309 loss: 1.5309 2022/10/13 03:56:37 - mmengine - INFO - Epoch(train) [38][160/940] lr: 1.0000e-02 eta: 8:24:24 time: 0.4469 data_time: 0.1169 memory: 17006 grad_norm: 4.1903 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6128 loss: 1.6128 2022/10/13 03:56:48 - mmengine - INFO - Epoch(train) [38][180/940] lr: 1.0000e-02 eta: 8:24:14 time: 0.5370 data_time: 0.1703 memory: 17006 grad_norm: 4.2635 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5203 loss: 1.5203 2022/10/13 03:56:58 - mmengine - INFO - Epoch(train) [38][200/940] lr: 1.0000e-02 eta: 8:24:03 time: 0.4959 data_time: 0.1049 memory: 17006 grad_norm: 4.2181 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7929 loss: 1.7929 2022/10/13 03:57:08 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 03:57:08 - mmengine - INFO - Epoch(train) [38][220/940] lr: 1.0000e-02 eta: 8:23:54 time: 0.5258 data_time: 0.0963 memory: 17006 grad_norm: 4.3207 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.7012 loss: 1.7012 2022/10/13 03:57:19 - mmengine - INFO - Epoch(train) [38][240/940] lr: 1.0000e-02 eta: 8:23:44 time: 0.5394 data_time: 0.0665 memory: 17006 grad_norm: 4.1790 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.5328 loss: 1.5328 2022/10/13 03:57:30 - mmengine - INFO - Epoch(train) [38][260/940] lr: 1.0000e-02 eta: 8:23:35 time: 0.5531 data_time: 0.0347 memory: 17006 grad_norm: 4.3183 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.6520 loss: 1.6520 2022/10/13 03:57:40 - mmengine - INFO - Epoch(train) [38][280/940] lr: 1.0000e-02 eta: 8:23:24 time: 0.4650 data_time: 0.0260 memory: 17006 grad_norm: 4.2738 top1_acc: 0.4688 top5_acc: 0.8750 loss_cls: 1.7972 loss: 1.7972 2022/10/13 03:57:50 - mmengine - INFO - Epoch(train) [38][300/940] lr: 1.0000e-02 eta: 8:23:14 time: 0.5427 data_time: 0.0327 memory: 17006 grad_norm: 4.2721 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6241 loss: 1.6241 2022/10/13 03:58:00 - mmengine - INFO - Epoch(train) [38][320/940] lr: 1.0000e-02 eta: 8:23:03 time: 0.4794 data_time: 0.0340 memory: 17006 grad_norm: 4.1909 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.7001 loss: 1.7001 2022/10/13 03:58:11 - mmengine - INFO - Epoch(train) [38][340/940] lr: 1.0000e-02 eta: 8:22:53 time: 0.5272 data_time: 0.0326 memory: 17006 grad_norm: 4.2716 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6223 loss: 1.6223 2022/10/13 03:58:20 - mmengine - INFO - Epoch(train) [38][360/940] lr: 1.0000e-02 eta: 8:22:41 time: 0.4493 data_time: 0.0307 memory: 17006 grad_norm: 4.2710 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5951 loss: 1.5951 2022/10/13 03:58:30 - mmengine - INFO - Epoch(train) [38][380/940] lr: 1.0000e-02 eta: 8:22:30 time: 0.5005 data_time: 0.0339 memory: 17006 grad_norm: 4.2668 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6760 loss: 1.6760 2022/10/13 03:58:40 - mmengine - INFO - Epoch(train) [38][400/940] lr: 1.0000e-02 eta: 8:22:20 time: 0.5085 data_time: 0.0376 memory: 17006 grad_norm: 4.2454 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6931 loss: 1.6931 2022/10/13 03:58:50 - mmengine - INFO - Epoch(train) [38][420/940] lr: 1.0000e-02 eta: 8:22:10 time: 0.5168 data_time: 0.0334 memory: 17006 grad_norm: 4.2542 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.6974 loss: 1.6974 2022/10/13 03:59:00 - mmengine - INFO - Epoch(train) [38][440/940] lr: 1.0000e-02 eta: 8:21:58 time: 0.4826 data_time: 0.0335 memory: 17006 grad_norm: 4.2493 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.7113 loss: 1.7113 2022/10/13 03:59:10 - mmengine - INFO - Epoch(train) [38][460/940] lr: 1.0000e-02 eta: 8:21:48 time: 0.5088 data_time: 0.0333 memory: 17006 grad_norm: 4.2993 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.7830 loss: 1.7830 2022/10/13 03:59:20 - mmengine - INFO - Epoch(train) [38][480/940] lr: 1.0000e-02 eta: 8:21:37 time: 0.4941 data_time: 0.0312 memory: 17006 grad_norm: 4.3056 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6639 loss: 1.6639 2022/10/13 03:59:31 - mmengine - INFO - Epoch(train) [38][500/940] lr: 1.0000e-02 eta: 8:21:29 time: 0.5576 data_time: 0.0337 memory: 17006 grad_norm: 4.2410 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5871 loss: 1.5871 2022/10/13 03:59:41 - mmengine - INFO - Epoch(train) [38][520/940] lr: 1.0000e-02 eta: 8:21:18 time: 0.5162 data_time: 0.0264 memory: 17006 grad_norm: 4.2914 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6914 loss: 1.6914 2022/10/13 03:59:51 - mmengine - INFO - Epoch(train) [38][540/940] lr: 1.0000e-02 eta: 8:21:08 time: 0.4940 data_time: 0.0362 memory: 17006 grad_norm: 4.2036 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6724 loss: 1.6724 2022/10/13 04:00:02 - mmengine - INFO - Epoch(train) [38][560/940] lr: 1.0000e-02 eta: 8:20:58 time: 0.5335 data_time: 0.0287 memory: 17006 grad_norm: 4.3597 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.5206 loss: 1.5206 2022/10/13 04:00:12 - mmengine - INFO - Epoch(train) [38][580/940] lr: 1.0000e-02 eta: 8:20:48 time: 0.5136 data_time: 0.0316 memory: 17006 grad_norm: 4.2369 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6244 loss: 1.6244 2022/10/13 04:00:23 - mmengine - INFO - Epoch(train) [38][600/940] lr: 1.0000e-02 eta: 8:20:39 time: 0.5619 data_time: 0.0286 memory: 17006 grad_norm: 4.1952 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.7912 loss: 1.7912 2022/10/13 04:00:32 - mmengine - INFO - Epoch(train) [38][620/940] lr: 1.0000e-02 eta: 8:20:27 time: 0.4448 data_time: 0.0302 memory: 17006 grad_norm: 4.2142 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.6649 loss: 1.6649 2022/10/13 04:00:43 - mmengine - INFO - Epoch(train) [38][640/940] lr: 1.0000e-02 eta: 8:20:17 time: 0.5411 data_time: 0.0304 memory: 17006 grad_norm: 4.3481 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.6291 loss: 1.6291 2022/10/13 04:00:53 - mmengine - INFO - Epoch(train) [38][660/940] lr: 1.0000e-02 eta: 8:20:07 time: 0.5132 data_time: 0.0293 memory: 17006 grad_norm: 4.2611 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5867 loss: 1.5867 2022/10/13 04:01:05 - mmengine - INFO - Epoch(train) [38][680/940] lr: 1.0000e-02 eta: 8:19:59 time: 0.5692 data_time: 0.0328 memory: 17006 grad_norm: 4.2660 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.7264 loss: 1.7264 2022/10/13 04:01:14 - mmengine - INFO - Epoch(train) [38][700/940] lr: 1.0000e-02 eta: 8:19:47 time: 0.4704 data_time: 0.0288 memory: 17006 grad_norm: 4.2973 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.7121 loss: 1.7121 2022/10/13 04:01:25 - mmengine - INFO - Epoch(train) [38][720/940] lr: 1.0000e-02 eta: 8:19:38 time: 0.5485 data_time: 0.0388 memory: 17006 grad_norm: 4.2413 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.7011 loss: 1.7011 2022/10/13 04:01:34 - mmengine - INFO - Epoch(train) [38][740/940] lr: 1.0000e-02 eta: 8:19:25 time: 0.4344 data_time: 0.0287 memory: 17006 grad_norm: 4.2796 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6914 loss: 1.6914 2022/10/13 04:01:45 - mmengine - INFO - Epoch(train) [38][760/940] lr: 1.0000e-02 eta: 8:19:16 time: 0.5539 data_time: 0.0337 memory: 17006 grad_norm: 4.2458 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5933 loss: 1.5933 2022/10/13 04:01:55 - mmengine - INFO - Epoch(train) [38][780/940] lr: 1.0000e-02 eta: 8:19:05 time: 0.4855 data_time: 0.0331 memory: 17006 grad_norm: 4.3099 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.6711 loss: 1.6711 2022/10/13 04:02:06 - mmengine - INFO - Epoch(train) [38][800/940] lr: 1.0000e-02 eta: 8:18:57 time: 0.5643 data_time: 0.0275 memory: 17006 grad_norm: 4.2932 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6281 loss: 1.6281 2022/10/13 04:02:16 - mmengine - INFO - Epoch(train) [38][820/940] lr: 1.0000e-02 eta: 8:18:46 time: 0.5002 data_time: 0.0285 memory: 17006 grad_norm: 4.3005 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7111 loss: 1.7111 2022/10/13 04:02:26 - mmengine - INFO - Epoch(train) [38][840/940] lr: 1.0000e-02 eta: 8:18:35 time: 0.4980 data_time: 0.0330 memory: 17006 grad_norm: 4.2294 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6821 loss: 1.6821 2022/10/13 04:02:35 - mmengine - INFO - Epoch(train) [38][860/940] lr: 1.0000e-02 eta: 8:18:24 time: 0.4762 data_time: 0.0366 memory: 17006 grad_norm: 4.1944 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.7972 loss: 1.7972 2022/10/13 04:02:46 - mmengine - INFO - Epoch(train) [38][880/940] lr: 1.0000e-02 eta: 8:18:15 time: 0.5553 data_time: 0.0261 memory: 17006 grad_norm: 4.3459 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7323 loss: 1.7323 2022/10/13 04:02:56 - mmengine - INFO - Epoch(train) [38][900/940] lr: 1.0000e-02 eta: 8:18:04 time: 0.4742 data_time: 0.0335 memory: 17006 grad_norm: 4.2931 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6755 loss: 1.6755 2022/10/13 04:03:07 - mmengine - INFO - Epoch(train) [38][920/940] lr: 1.0000e-02 eta: 8:17:55 time: 0.5526 data_time: 0.0303 memory: 17006 grad_norm: 4.3370 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6087 loss: 1.6087 2022/10/13 04:03:15 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 04:03:15 - mmengine - INFO - Epoch(train) [38][940/940] lr: 1.0000e-02 eta: 8:17:41 time: 0.4222 data_time: 0.0293 memory: 17006 grad_norm: 4.4265 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.5915 loss: 1.5915 2022/10/13 04:03:28 - mmengine - INFO - Epoch(val) [38][20/78] eta: 0:00:36 time: 0.6257 data_time: 0.5316 memory: 3172 2022/10/13 04:03:37 - mmengine - INFO - Epoch(val) [38][40/78] eta: 0:00:16 time: 0.4313 data_time: 0.3381 memory: 3172 2022/10/13 04:03:48 - mmengine - INFO - Epoch(val) [38][60/78] eta: 0:00:10 time: 0.5738 data_time: 0.4799 memory: 3172 2022/10/13 04:03:58 - mmengine - INFO - Epoch(val) [38][78/78] acc/top1: 0.6303 acc/top5: 0.8454 acc/mean1: 0.6301 2022/10/13 04:03:58 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_35.pth is removed 2022/10/13 04:03:59 - mmengine - INFO - The best checkpoint with 0.6303 acc/top1 at 38 epoch is saved to best_acc/top1_epoch_38.pth. 2022/10/13 04:04:12 - mmengine - INFO - Epoch(train) [39][20/940] lr: 1.0000e-02 eta: 8:17:37 time: 0.6826 data_time: 0.3628 memory: 17006 grad_norm: 4.1740 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.5729 loss: 1.5729 2022/10/13 04:04:22 - mmengine - INFO - Epoch(train) [39][40/940] lr: 1.0000e-02 eta: 8:17:25 time: 0.4660 data_time: 0.1501 memory: 17006 grad_norm: 4.2987 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6139 loss: 1.6139 2022/10/13 04:04:33 - mmengine - INFO - Epoch(train) [39][60/940] lr: 1.0000e-02 eta: 8:17:16 time: 0.5469 data_time: 0.2139 memory: 17006 grad_norm: 4.2401 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5574 loss: 1.5574 2022/10/13 04:04:42 - mmengine - INFO - Epoch(train) [39][80/940] lr: 1.0000e-02 eta: 8:17:04 time: 0.4595 data_time: 0.1294 memory: 17006 grad_norm: 4.3988 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6504 loss: 1.6504 2022/10/13 04:04:52 - mmengine - INFO - Epoch(train) [39][100/940] lr: 1.0000e-02 eta: 8:16:53 time: 0.5010 data_time: 0.1813 memory: 17006 grad_norm: 4.2361 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5982 loss: 1.5982 2022/10/13 04:05:02 - mmengine - INFO - Epoch(train) [39][120/940] lr: 1.0000e-02 eta: 8:16:43 time: 0.5178 data_time: 0.1314 memory: 17006 grad_norm: 4.1627 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6488 loss: 1.6488 2022/10/13 04:05:12 - mmengine - INFO - Epoch(train) [39][140/940] lr: 1.0000e-02 eta: 8:16:32 time: 0.4957 data_time: 0.0351 memory: 17006 grad_norm: 4.2948 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6393 loss: 1.6393 2022/10/13 04:05:22 - mmengine - INFO - Epoch(train) [39][160/940] lr: 1.0000e-02 eta: 8:16:22 time: 0.5236 data_time: 0.0315 memory: 17006 grad_norm: 4.3724 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.7442 loss: 1.7442 2022/10/13 04:05:32 - mmengine - INFO - Epoch(train) [39][180/940] lr: 1.0000e-02 eta: 8:16:11 time: 0.4669 data_time: 0.0292 memory: 17006 grad_norm: 4.2136 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6619 loss: 1.6619 2022/10/13 04:05:43 - mmengine - INFO - Epoch(train) [39][200/940] lr: 1.0000e-02 eta: 8:16:02 time: 0.5648 data_time: 0.0323 memory: 17006 grad_norm: 4.2001 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4378 loss: 1.4378 2022/10/13 04:05:53 - mmengine - INFO - Epoch(train) [39][220/940] lr: 1.0000e-02 eta: 8:15:51 time: 0.4970 data_time: 0.0339 memory: 17006 grad_norm: 4.2266 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.7391 loss: 1.7391 2022/10/13 04:06:04 - mmengine - INFO - Epoch(train) [39][240/940] lr: 1.0000e-02 eta: 8:15:42 time: 0.5499 data_time: 0.0324 memory: 17006 grad_norm: 4.1632 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.8025 loss: 1.8025 2022/10/13 04:06:14 - mmengine - INFO - Epoch(train) [39][260/940] lr: 1.0000e-02 eta: 8:15:31 time: 0.4775 data_time: 0.0337 memory: 17006 grad_norm: 4.2683 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.7656 loss: 1.7656 2022/10/13 04:06:24 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 04:06:24 - mmengine - INFO - Epoch(train) [39][280/940] lr: 1.0000e-02 eta: 8:15:22 time: 0.5396 data_time: 0.0320 memory: 17006 grad_norm: 4.2030 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6581 loss: 1.6581 2022/10/13 04:06:34 - mmengine - INFO - Epoch(train) [39][300/940] lr: 1.0000e-02 eta: 8:15:10 time: 0.4772 data_time: 0.0343 memory: 17006 grad_norm: 4.2530 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5057 loss: 1.5057 2022/10/13 04:06:45 - mmengine - INFO - Epoch(train) [39][320/940] lr: 1.0000e-02 eta: 8:15:02 time: 0.5713 data_time: 0.0383 memory: 17006 grad_norm: 4.2501 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6610 loss: 1.6610 2022/10/13 04:06:55 - mmengine - INFO - Epoch(train) [39][340/940] lr: 1.0000e-02 eta: 8:14:50 time: 0.4709 data_time: 0.0322 memory: 17006 grad_norm: 4.3039 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6396 loss: 1.6396 2022/10/13 04:07:06 - mmengine - INFO - Epoch(train) [39][360/940] lr: 1.0000e-02 eta: 8:14:41 time: 0.5475 data_time: 0.0283 memory: 17006 grad_norm: 4.3952 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6463 loss: 1.6463 2022/10/13 04:07:15 - mmengine - INFO - Epoch(train) [39][380/940] lr: 1.0000e-02 eta: 8:14:29 time: 0.4554 data_time: 0.0298 memory: 17006 grad_norm: 4.3476 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6755 loss: 1.6755 2022/10/13 04:07:25 - mmengine - INFO - Epoch(train) [39][400/940] lr: 1.0000e-02 eta: 8:14:19 time: 0.5239 data_time: 0.0293 memory: 17006 grad_norm: 4.2807 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6441 loss: 1.6441 2022/10/13 04:07:36 - mmengine - INFO - Epoch(train) [39][420/940] lr: 1.0000e-02 eta: 8:14:09 time: 0.5106 data_time: 0.0304 memory: 17006 grad_norm: 4.2182 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5626 loss: 1.5626 2022/10/13 04:07:46 - mmengine - INFO - Epoch(train) [39][440/940] lr: 1.0000e-02 eta: 8:13:59 time: 0.5125 data_time: 0.0413 memory: 17006 grad_norm: 4.2415 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7508 loss: 1.7508 2022/10/13 04:07:56 - mmengine - INFO - Epoch(train) [39][460/940] lr: 1.0000e-02 eta: 8:13:48 time: 0.4863 data_time: 0.0323 memory: 17006 grad_norm: 4.2316 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.7201 loss: 1.7201 2022/10/13 04:08:06 - mmengine - INFO - Epoch(train) [39][480/940] lr: 1.0000e-02 eta: 8:13:38 time: 0.5238 data_time: 0.0328 memory: 17006 grad_norm: 4.1827 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.8772 loss: 1.8772 2022/10/13 04:08:17 - mmengine - INFO - Epoch(train) [39][500/940] lr: 1.0000e-02 eta: 8:13:28 time: 0.5352 data_time: 0.0266 memory: 17006 grad_norm: 4.2343 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.6172 loss: 1.6172 2022/10/13 04:08:27 - mmengine - INFO - Epoch(train) [39][520/940] lr: 1.0000e-02 eta: 8:13:18 time: 0.5193 data_time: 0.0314 memory: 17006 grad_norm: 4.1758 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5762 loss: 1.5762 2022/10/13 04:08:37 - mmengine - INFO - Epoch(train) [39][540/940] lr: 1.0000e-02 eta: 8:13:08 time: 0.5137 data_time: 0.0245 memory: 17006 grad_norm: 4.3105 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5913 loss: 1.5913 2022/10/13 04:08:48 - mmengine - INFO - Epoch(train) [39][560/940] lr: 1.0000e-02 eta: 8:12:59 time: 0.5372 data_time: 0.0276 memory: 17006 grad_norm: 4.2802 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6749 loss: 1.6749 2022/10/13 04:08:58 - mmengine - INFO - Epoch(train) [39][580/940] lr: 1.0000e-02 eta: 8:12:48 time: 0.4931 data_time: 0.0343 memory: 17006 grad_norm: 4.2931 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7315 loss: 1.7315 2022/10/13 04:09:08 - mmengine - INFO - Epoch(train) [39][600/940] lr: 1.0000e-02 eta: 8:12:37 time: 0.5078 data_time: 0.0273 memory: 17006 grad_norm: 4.2679 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5513 loss: 1.5513 2022/10/13 04:09:17 - mmengine - INFO - Epoch(train) [39][620/940] lr: 1.0000e-02 eta: 8:12:25 time: 0.4528 data_time: 0.0335 memory: 17006 grad_norm: 4.3005 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6823 loss: 1.6823 2022/10/13 04:09:28 - mmengine - INFO - Epoch(train) [39][640/940] lr: 1.0000e-02 eta: 8:12:16 time: 0.5432 data_time: 0.0356 memory: 17006 grad_norm: 4.3581 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.5916 loss: 1.5916 2022/10/13 04:09:37 - mmengine - INFO - Epoch(train) [39][660/940] lr: 1.0000e-02 eta: 8:12:04 time: 0.4674 data_time: 0.0415 memory: 17006 grad_norm: 4.3050 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7174 loss: 1.7174 2022/10/13 04:09:47 - mmengine - INFO - Epoch(train) [39][680/940] lr: 1.0000e-02 eta: 8:11:54 time: 0.5006 data_time: 0.0299 memory: 17006 grad_norm: 4.2010 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4918 loss: 1.4918 2022/10/13 04:09:57 - mmengine - INFO - Epoch(train) [39][700/940] lr: 1.0000e-02 eta: 8:11:43 time: 0.4883 data_time: 0.0303 memory: 17006 grad_norm: 4.2357 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8145 loss: 1.8145 2022/10/13 04:10:07 - mmengine - INFO - Epoch(train) [39][720/940] lr: 1.0000e-02 eta: 8:11:32 time: 0.5101 data_time: 0.0312 memory: 17006 grad_norm: 4.2992 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7341 loss: 1.7341 2022/10/13 04:10:17 - mmengine - INFO - Epoch(train) [39][740/940] lr: 1.0000e-02 eta: 8:11:22 time: 0.5029 data_time: 0.0343 memory: 17006 grad_norm: 4.3002 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7097 loss: 1.7097 2022/10/13 04:10:28 - mmengine - INFO - Epoch(train) [39][760/940] lr: 1.0000e-02 eta: 8:11:12 time: 0.5349 data_time: 0.0323 memory: 17006 grad_norm: 4.1976 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.4832 loss: 1.4832 2022/10/13 04:10:38 - mmengine - INFO - Epoch(train) [39][780/940] lr: 1.0000e-02 eta: 8:11:01 time: 0.5003 data_time: 0.0354 memory: 17006 grad_norm: 4.2507 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.6680 loss: 1.6680 2022/10/13 04:10:48 - mmengine - INFO - Epoch(train) [39][800/940] lr: 1.0000e-02 eta: 8:10:50 time: 0.4683 data_time: 0.0271 memory: 17006 grad_norm: 4.3220 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.7019 loss: 1.7019 2022/10/13 04:10:59 - mmengine - INFO - Epoch(train) [39][820/940] lr: 1.0000e-02 eta: 8:10:41 time: 0.5579 data_time: 0.0331 memory: 17006 grad_norm: 4.3132 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4873 loss: 1.4873 2022/10/13 04:11:08 - mmengine - INFO - Epoch(train) [39][840/940] lr: 1.0000e-02 eta: 8:10:30 time: 0.4773 data_time: 0.0272 memory: 17006 grad_norm: 4.2855 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6395 loss: 1.6395 2022/10/13 04:11:19 - mmengine - INFO - Epoch(train) [39][860/940] lr: 1.0000e-02 eta: 8:10:20 time: 0.5258 data_time: 0.0343 memory: 17006 grad_norm: 4.1888 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.7309 loss: 1.7309 2022/10/13 04:11:28 - mmengine - INFO - Epoch(train) [39][880/940] lr: 1.0000e-02 eta: 8:10:08 time: 0.4760 data_time: 0.0338 memory: 17006 grad_norm: 4.2391 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5897 loss: 1.5897 2022/10/13 04:11:39 - mmengine - INFO - Epoch(train) [39][900/940] lr: 1.0000e-02 eta: 8:09:59 time: 0.5440 data_time: 0.0330 memory: 17006 grad_norm: 4.2393 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5065 loss: 1.5065 2022/10/13 04:11:48 - mmengine - INFO - Epoch(train) [39][920/940] lr: 1.0000e-02 eta: 8:09:47 time: 0.4558 data_time: 0.0385 memory: 17006 grad_norm: 4.3143 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5771 loss: 1.5771 2022/10/13 04:11:58 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 04:11:58 - mmengine - INFO - Epoch(train) [39][940/940] lr: 1.0000e-02 eta: 8:09:36 time: 0.4758 data_time: 0.0287 memory: 17006 grad_norm: 4.6211 top1_acc: 0.1429 top5_acc: 0.7143 loss_cls: 1.6753 loss: 1.6753 2022/10/13 04:11:58 - mmengine - INFO - Saving checkpoint at 39 epochs 2022/10/13 04:12:11 - mmengine - INFO - Epoch(val) [39][20/78] eta: 0:00:36 time: 0.6318 data_time: 0.5419 memory: 3172 2022/10/13 04:12:20 - mmengine - INFO - Epoch(val) [39][40/78] eta: 0:00:16 time: 0.4285 data_time: 0.3386 memory: 3172 2022/10/13 04:12:31 - mmengine - INFO - Epoch(val) [39][60/78] eta: 0:00:10 time: 0.5748 data_time: 0.4850 memory: 3172 2022/10/13 04:12:40 - mmengine - INFO - Epoch(val) [39][78/78] acc/top1: 0.6167 acc/top5: 0.8309 acc/mean1: 0.6165 2022/10/13 04:12:54 - mmengine - INFO - Epoch(train) [40][20/940] lr: 1.0000e-02 eta: 8:09:31 time: 0.6959 data_time: 0.2229 memory: 17006 grad_norm: 4.3714 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6852 loss: 1.6852 2022/10/13 04:13:04 - mmengine - INFO - Epoch(train) [40][40/940] lr: 1.0000e-02 eta: 8:09:20 time: 0.4816 data_time: 0.0261 memory: 17006 grad_norm: 4.2740 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6643 loss: 1.6643 2022/10/13 04:13:15 - mmengine - INFO - Epoch(train) [40][60/940] lr: 1.0000e-02 eta: 8:09:11 time: 0.5618 data_time: 0.0376 memory: 17006 grad_norm: 4.3354 top1_acc: 0.5312 top5_acc: 0.9375 loss_cls: 1.6764 loss: 1.6764 2022/10/13 04:13:25 - mmengine - INFO - Epoch(train) [40][80/940] lr: 1.0000e-02 eta: 8:09:00 time: 0.4667 data_time: 0.0274 memory: 17006 grad_norm: 4.2343 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.5414 loss: 1.5414 2022/10/13 04:13:36 - mmengine - INFO - Epoch(train) [40][100/940] lr: 1.0000e-02 eta: 8:08:51 time: 0.5626 data_time: 0.0422 memory: 17006 grad_norm: 4.1990 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5183 loss: 1.5183 2022/10/13 04:13:45 - mmengine - INFO - Epoch(train) [40][120/940] lr: 1.0000e-02 eta: 8:08:40 time: 0.4813 data_time: 0.0282 memory: 17006 grad_norm: 4.3624 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6530 loss: 1.6530 2022/10/13 04:13:57 - mmengine - INFO - Epoch(train) [40][140/940] lr: 1.0000e-02 eta: 8:08:31 time: 0.5691 data_time: 0.0263 memory: 17006 grad_norm: 4.1788 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.6155 loss: 1.6155 2022/10/13 04:14:07 - mmengine - INFO - Epoch(train) [40][160/940] lr: 1.0000e-02 eta: 8:08:21 time: 0.4950 data_time: 0.0339 memory: 17006 grad_norm: 4.2034 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6293 loss: 1.6293 2022/10/13 04:14:16 - mmengine - INFO - Epoch(train) [40][180/940] lr: 1.0000e-02 eta: 8:08:10 time: 0.4900 data_time: 0.0380 memory: 17006 grad_norm: 4.2769 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6036 loss: 1.6036 2022/10/13 04:14:27 - mmengine - INFO - Epoch(train) [40][200/940] lr: 1.0000e-02 eta: 8:07:59 time: 0.5124 data_time: 0.0264 memory: 17006 grad_norm: 4.2611 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5172 loss: 1.5172 2022/10/13 04:14:38 - mmengine - INFO - Epoch(train) [40][220/940] lr: 1.0000e-02 eta: 8:07:51 time: 0.5628 data_time: 0.0362 memory: 17006 grad_norm: 4.3859 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.5509 loss: 1.5509 2022/10/13 04:14:47 - mmengine - INFO - Epoch(train) [40][240/940] lr: 1.0000e-02 eta: 8:07:38 time: 0.4455 data_time: 0.0273 memory: 17006 grad_norm: 4.2350 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.6361 loss: 1.6361 2022/10/13 04:14:58 - mmengine - INFO - Epoch(train) [40][260/940] lr: 1.0000e-02 eta: 8:07:29 time: 0.5474 data_time: 0.0322 memory: 17006 grad_norm: 4.2412 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.6009 loss: 1.6009 2022/10/13 04:15:07 - mmengine - INFO - Epoch(train) [40][280/940] lr: 1.0000e-02 eta: 8:07:17 time: 0.4485 data_time: 0.0269 memory: 17006 grad_norm: 4.3236 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5341 loss: 1.5341 2022/10/13 04:15:17 - mmengine - INFO - Epoch(train) [40][300/940] lr: 1.0000e-02 eta: 8:07:06 time: 0.5026 data_time: 0.0323 memory: 17006 grad_norm: 4.3115 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6706 loss: 1.6706 2022/10/13 04:15:27 - mmengine - INFO - Epoch(train) [40][320/940] lr: 1.0000e-02 eta: 8:06:56 time: 0.4988 data_time: 0.0311 memory: 17006 grad_norm: 4.3306 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.7203 loss: 1.7203 2022/10/13 04:15:38 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 04:15:38 - mmengine - INFO - Epoch(train) [40][340/940] lr: 1.0000e-02 eta: 8:06:47 time: 0.5462 data_time: 0.0323 memory: 17006 grad_norm: 4.2569 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.5909 loss: 1.5909 2022/10/13 04:15:47 - mmengine - INFO - Epoch(train) [40][360/940] lr: 1.0000e-02 eta: 8:06:35 time: 0.4561 data_time: 0.0296 memory: 17006 grad_norm: 4.3304 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6783 loss: 1.6783 2022/10/13 04:15:58 - mmengine - INFO - Epoch(train) [40][380/940] lr: 1.0000e-02 eta: 8:06:26 time: 0.5545 data_time: 0.0332 memory: 17006 grad_norm: 4.2674 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6836 loss: 1.6836 2022/10/13 04:16:08 - mmengine - INFO - Epoch(train) [40][400/940] lr: 1.0000e-02 eta: 8:06:14 time: 0.4755 data_time: 0.0302 memory: 17006 grad_norm: 4.2986 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6289 loss: 1.6289 2022/10/13 04:16:18 - mmengine - INFO - Epoch(train) [40][420/940] lr: 1.0000e-02 eta: 8:06:04 time: 0.5250 data_time: 0.0353 memory: 17006 grad_norm: 4.3094 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.6839 loss: 1.6839 2022/10/13 04:16:28 - mmengine - INFO - Epoch(train) [40][440/940] lr: 1.0000e-02 eta: 8:05:54 time: 0.4974 data_time: 0.0353 memory: 17006 grad_norm: 4.2980 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6387 loss: 1.6387 2022/10/13 04:16:38 - mmengine - INFO - Epoch(train) [40][460/940] lr: 1.0000e-02 eta: 8:05:44 time: 0.5174 data_time: 0.0316 memory: 17006 grad_norm: 4.2429 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.6350 loss: 1.6350 2022/10/13 04:16:48 - mmengine - INFO - Epoch(train) [40][480/940] lr: 1.0000e-02 eta: 8:05:33 time: 0.4907 data_time: 0.0339 memory: 17006 grad_norm: 4.1414 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.7145 loss: 1.7145 2022/10/13 04:16:59 - mmengine - INFO - Epoch(train) [40][500/940] lr: 1.0000e-02 eta: 8:05:23 time: 0.5211 data_time: 0.0301 memory: 17006 grad_norm: 4.3022 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6640 loss: 1.6640 2022/10/13 04:17:08 - mmengine - INFO - Epoch(train) [40][520/940] lr: 1.0000e-02 eta: 8:05:12 time: 0.4857 data_time: 0.0369 memory: 17006 grad_norm: 4.2411 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6466 loss: 1.6466 2022/10/13 04:17:19 - mmengine - INFO - Epoch(train) [40][540/940] lr: 1.0000e-02 eta: 8:05:03 time: 0.5571 data_time: 0.0345 memory: 17006 grad_norm: 4.2377 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.7757 loss: 1.7757 2022/10/13 04:17:29 - mmengine - INFO - Epoch(train) [40][560/940] lr: 1.0000e-02 eta: 8:04:51 time: 0.4647 data_time: 0.0317 memory: 17006 grad_norm: 4.3001 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.7054 loss: 1.7054 2022/10/13 04:17:39 - mmengine - INFO - Epoch(train) [40][580/940] lr: 1.0000e-02 eta: 8:04:41 time: 0.5139 data_time: 0.0309 memory: 17006 grad_norm: 4.3025 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.6527 loss: 1.6527 2022/10/13 04:17:48 - mmengine - INFO - Epoch(train) [40][600/940] lr: 1.0000e-02 eta: 8:04:29 time: 0.4472 data_time: 0.0290 memory: 17006 grad_norm: 4.3622 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5762 loss: 1.5762 2022/10/13 04:17:58 - mmengine - INFO - Epoch(train) [40][620/940] lr: 1.0000e-02 eta: 8:04:19 time: 0.5262 data_time: 0.0328 memory: 17006 grad_norm: 4.2348 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.5856 loss: 1.5856 2022/10/13 04:18:08 - mmengine - INFO - Epoch(train) [40][640/940] lr: 1.0000e-02 eta: 8:04:08 time: 0.4958 data_time: 0.0366 memory: 17006 grad_norm: 4.2722 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.6206 loss: 1.6206 2022/10/13 04:18:19 - mmengine - INFO - Epoch(train) [40][660/940] lr: 1.0000e-02 eta: 8:03:59 time: 0.5517 data_time: 0.0316 memory: 17006 grad_norm: 4.3576 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.7380 loss: 1.7380 2022/10/13 04:18:30 - mmengine - INFO - Epoch(train) [40][680/940] lr: 1.0000e-02 eta: 8:03:49 time: 0.5109 data_time: 0.0336 memory: 17006 grad_norm: 4.2728 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6208 loss: 1.6208 2022/10/13 04:18:41 - mmengine - INFO - Epoch(train) [40][700/940] lr: 1.0000e-02 eta: 8:03:40 time: 0.5570 data_time: 0.0329 memory: 17006 grad_norm: 4.3638 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6921 loss: 1.6921 2022/10/13 04:18:51 - mmengine - INFO - Epoch(train) [40][720/940] lr: 1.0000e-02 eta: 8:03:29 time: 0.4958 data_time: 0.0308 memory: 17006 grad_norm: 4.4115 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.6746 loss: 1.6746 2022/10/13 04:19:01 - mmengine - INFO - Epoch(train) [40][740/940] lr: 1.0000e-02 eta: 8:03:19 time: 0.5091 data_time: 0.0335 memory: 17006 grad_norm: 4.3570 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6726 loss: 1.6726 2022/10/13 04:19:10 - mmengine - INFO - Epoch(train) [40][760/940] lr: 1.0000e-02 eta: 8:03:06 time: 0.4385 data_time: 0.0366 memory: 17006 grad_norm: 4.3271 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.7727 loss: 1.7727 2022/10/13 04:19:20 - mmengine - INFO - Epoch(train) [40][780/940] lr: 1.0000e-02 eta: 8:02:57 time: 0.5378 data_time: 0.0371 memory: 17006 grad_norm: 4.3081 top1_acc: 0.3750 top5_acc: 0.7188 loss_cls: 1.7583 loss: 1.7583 2022/10/13 04:19:29 - mmengine - INFO - Epoch(train) [40][800/940] lr: 1.0000e-02 eta: 8:02:45 time: 0.4489 data_time: 0.0271 memory: 17006 grad_norm: 4.2862 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7309 loss: 1.7309 2022/10/13 04:19:40 - mmengine - INFO - Epoch(train) [40][820/940] lr: 1.0000e-02 eta: 8:02:35 time: 0.5234 data_time: 0.0286 memory: 17006 grad_norm: 4.2613 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.7290 loss: 1.7290 2022/10/13 04:19:49 - mmengine - INFO - Epoch(train) [40][840/940] lr: 1.0000e-02 eta: 8:02:23 time: 0.4755 data_time: 0.0315 memory: 17006 grad_norm: 4.2379 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.6478 loss: 1.6478 2022/10/13 04:20:01 - mmengine - INFO - Epoch(train) [40][860/940] lr: 1.0000e-02 eta: 8:02:15 time: 0.5804 data_time: 0.0326 memory: 17006 grad_norm: 4.2475 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.6925 loss: 1.6925 2022/10/13 04:20:11 - mmengine - INFO - Epoch(train) [40][880/940] lr: 1.0000e-02 eta: 8:02:04 time: 0.4813 data_time: 0.0319 memory: 17006 grad_norm: 4.2774 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.7043 loss: 1.7043 2022/10/13 04:20:22 - mmengine - INFO - Epoch(train) [40][900/940] lr: 1.0000e-02 eta: 8:01:55 time: 0.5501 data_time: 0.0315 memory: 17006 grad_norm: 4.3129 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.6828 loss: 1.6828 2022/10/13 04:20:32 - mmengine - INFO - Epoch(train) [40][920/940] lr: 1.0000e-02 eta: 8:01:44 time: 0.5005 data_time: 0.0355 memory: 17006 grad_norm: 4.2776 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.7992 loss: 1.7992 2022/10/13 04:20:40 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 04:20:40 - mmengine - INFO - Epoch(train) [40][940/940] lr: 1.0000e-02 eta: 8:01:31 time: 0.4192 data_time: 0.0225 memory: 17006 grad_norm: 4.5043 top1_acc: 0.1429 top5_acc: 0.7143 loss_cls: 1.6931 loss: 1.6931 2022/10/13 04:20:53 - mmengine - INFO - Epoch(val) [40][20/78] eta: 0:00:36 time: 0.6270 data_time: 0.5333 memory: 3172 2022/10/13 04:21:01 - mmengine - INFO - Epoch(val) [40][40/78] eta: 0:00:16 time: 0.4268 data_time: 0.3360 memory: 3172 2022/10/13 04:21:13 - mmengine - INFO - Epoch(val) [40][60/78] eta: 0:00:10 time: 0.5849 data_time: 0.4949 memory: 3172 2022/10/13 04:21:23 - mmengine - INFO - Epoch(val) [40][78/78] acc/top1: 0.6301 acc/top5: 0.8416 acc/mean1: 0.6300 2022/10/13 04:21:36 - mmengine - INFO - Epoch(train) [41][20/940] lr: 1.0000e-03 eta: 8:01:26 time: 0.6887 data_time: 0.3022 memory: 17006 grad_norm: 4.2035 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6476 loss: 1.6476 2022/10/13 04:21:46 - mmengine - INFO - Epoch(train) [41][40/940] lr: 1.0000e-03 eta: 8:01:15 time: 0.4695 data_time: 0.0860 memory: 17006 grad_norm: 4.0919 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5949 loss: 1.5949 2022/10/13 04:21:57 - mmengine - INFO - Epoch(train) [41][60/940] lr: 1.0000e-03 eta: 8:01:06 time: 0.5796 data_time: 0.0337 memory: 17006 grad_norm: 4.0687 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6614 loss: 1.6614 2022/10/13 04:22:07 - mmengine - INFO - Epoch(train) [41][80/940] lr: 1.0000e-03 eta: 8:00:55 time: 0.4818 data_time: 0.0306 memory: 17006 grad_norm: 4.0978 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.5780 loss: 1.5780 2022/10/13 04:22:17 - mmengine - INFO - Epoch(train) [41][100/940] lr: 1.0000e-03 eta: 8:00:45 time: 0.5105 data_time: 0.0296 memory: 17006 grad_norm: 4.0480 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.6844 loss: 1.6844 2022/10/13 04:22:27 - mmengine - INFO - Epoch(train) [41][120/940] lr: 1.0000e-03 eta: 8:00:34 time: 0.4728 data_time: 0.0303 memory: 17006 grad_norm: 4.1099 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.6317 loss: 1.6317 2022/10/13 04:22:37 - mmengine - INFO - Epoch(train) [41][140/940] lr: 1.0000e-03 eta: 8:00:24 time: 0.5284 data_time: 0.0305 memory: 17006 grad_norm: 4.0783 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6199 loss: 1.6199 2022/10/13 04:22:46 - mmengine - INFO - Epoch(train) [41][160/940] lr: 1.0000e-03 eta: 8:00:12 time: 0.4502 data_time: 0.0305 memory: 17006 grad_norm: 3.9299 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6101 loss: 1.6101 2022/10/13 04:22:57 - mmengine - INFO - Epoch(train) [41][180/940] lr: 1.0000e-03 eta: 8:00:03 time: 0.5644 data_time: 0.0688 memory: 17006 grad_norm: 3.9628 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.6199 loss: 1.6199 2022/10/13 04:23:08 - mmengine - INFO - Epoch(train) [41][200/940] lr: 1.0000e-03 eta: 7:59:53 time: 0.5060 data_time: 0.0456 memory: 17006 grad_norm: 4.0798 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.4940 loss: 1.4940 2022/10/13 04:23:19 - mmengine - INFO - Epoch(train) [41][220/940] lr: 1.0000e-03 eta: 7:59:44 time: 0.5784 data_time: 0.0320 memory: 17006 grad_norm: 4.0076 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5854 loss: 1.5854 2022/10/13 04:23:29 - mmengine - INFO - Epoch(train) [41][240/940] lr: 1.0000e-03 eta: 7:59:33 time: 0.4826 data_time: 0.0311 memory: 17006 grad_norm: 4.1386 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.6439 loss: 1.6439 2022/10/13 04:23:38 - mmengine - INFO - Epoch(train) [41][260/940] lr: 1.0000e-03 eta: 7:59:22 time: 0.4803 data_time: 0.0319 memory: 17006 grad_norm: 4.0741 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.5833 loss: 1.5833 2022/10/13 04:23:48 - mmengine - INFO - Epoch(train) [41][280/940] lr: 1.0000e-03 eta: 7:59:11 time: 0.4722 data_time: 0.0337 memory: 17006 grad_norm: 4.0995 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5642 loss: 1.5642 2022/10/13 04:23:59 - mmengine - INFO - Epoch(train) [41][300/940] lr: 1.0000e-03 eta: 7:59:02 time: 0.5582 data_time: 0.0332 memory: 17006 grad_norm: 4.1228 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.6516 loss: 1.6516 2022/10/13 04:24:08 - mmengine - INFO - Epoch(train) [41][320/940] lr: 1.0000e-03 eta: 7:58:50 time: 0.4572 data_time: 0.0330 memory: 17006 grad_norm: 4.0467 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6189 loss: 1.6189 2022/10/13 04:24:20 - mmengine - INFO - Epoch(train) [41][340/940] lr: 1.0000e-03 eta: 7:58:41 time: 0.5709 data_time: 0.0326 memory: 17006 grad_norm: 4.0537 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.6232 loss: 1.6232 2022/10/13 04:24:29 - mmengine - INFO - Epoch(train) [41][360/940] lr: 1.0000e-03 eta: 7:58:29 time: 0.4605 data_time: 0.0328 memory: 17006 grad_norm: 3.9998 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.4648 loss: 1.4648 2022/10/13 04:24:40 - mmengine - INFO - Epoch(train) [41][380/940] lr: 1.0000e-03 eta: 7:58:20 time: 0.5480 data_time: 0.0380 memory: 17006 grad_norm: 4.0845 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5239 loss: 1.5239 2022/10/13 04:24:49 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 04:24:49 - mmengine - INFO - Epoch(train) [41][400/940] lr: 1.0000e-03 eta: 7:58:08 time: 0.4506 data_time: 0.0334 memory: 17006 grad_norm: 4.0650 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3990 loss: 1.3990 2022/10/13 04:25:00 - mmengine - INFO - Epoch(train) [41][420/940] lr: 1.0000e-03 eta: 7:57:59 time: 0.5411 data_time: 0.0391 memory: 17006 grad_norm: 4.1322 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5793 loss: 1.5793 2022/10/13 04:25:10 - mmengine - INFO - Epoch(train) [41][440/940] lr: 1.0000e-03 eta: 7:57:48 time: 0.5097 data_time: 0.0292 memory: 17006 grad_norm: 4.0495 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.4873 loss: 1.4873 2022/10/13 04:25:21 - mmengine - INFO - Epoch(train) [41][460/940] lr: 1.0000e-03 eta: 7:57:39 time: 0.5392 data_time: 0.0356 memory: 17006 grad_norm: 4.0616 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4963 loss: 1.4963 2022/10/13 04:25:30 - mmengine - INFO - Epoch(train) [41][480/940] lr: 1.0000e-03 eta: 7:57:28 time: 0.4805 data_time: 0.0303 memory: 17006 grad_norm: 4.1281 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5838 loss: 1.5838 2022/10/13 04:25:42 - mmengine - INFO - Epoch(train) [41][500/940] lr: 1.0000e-03 eta: 7:57:20 time: 0.5784 data_time: 0.0339 memory: 17006 grad_norm: 4.0284 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5467 loss: 1.5467 2022/10/13 04:25:50 - mmengine - INFO - Epoch(train) [41][520/940] lr: 1.0000e-03 eta: 7:57:07 time: 0.4275 data_time: 0.0291 memory: 17006 grad_norm: 4.0218 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6029 loss: 1.6029 2022/10/13 04:26:01 - mmengine - INFO - Epoch(train) [41][540/940] lr: 1.0000e-03 eta: 7:56:57 time: 0.5132 data_time: 0.0323 memory: 17006 grad_norm: 4.0883 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5239 loss: 1.5239 2022/10/13 04:26:10 - mmengine - INFO - Epoch(train) [41][560/940] lr: 1.0000e-03 eta: 7:56:46 time: 0.4861 data_time: 0.0328 memory: 17006 grad_norm: 4.0754 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5722 loss: 1.5722 2022/10/13 04:26:21 - mmengine - INFO - Epoch(train) [41][580/940] lr: 1.0000e-03 eta: 7:56:35 time: 0.5092 data_time: 0.0302 memory: 17006 grad_norm: 4.0766 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3715 loss: 1.3715 2022/10/13 04:26:30 - mmengine - INFO - Epoch(train) [41][600/940] lr: 1.0000e-03 eta: 7:56:23 time: 0.4603 data_time: 0.0334 memory: 17006 grad_norm: 4.0413 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4451 loss: 1.4451 2022/10/13 04:26:41 - mmengine - INFO - Epoch(train) [41][620/940] lr: 1.0000e-03 eta: 7:56:15 time: 0.5670 data_time: 0.0269 memory: 17006 grad_norm: 4.0664 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.5077 loss: 1.5077 2022/10/13 04:26:50 - mmengine - INFO - Epoch(train) [41][640/940] lr: 1.0000e-03 eta: 7:56:03 time: 0.4575 data_time: 0.0334 memory: 17006 grad_norm: 4.0785 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5388 loss: 1.5388 2022/10/13 04:27:01 - mmengine - INFO - Epoch(train) [41][660/940] lr: 1.0000e-03 eta: 7:55:53 time: 0.5291 data_time: 0.0293 memory: 17006 grad_norm: 4.0705 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.4735 loss: 1.4735 2022/10/13 04:27:11 - mmengine - INFO - Epoch(train) [41][680/940] lr: 1.0000e-03 eta: 7:55:43 time: 0.5007 data_time: 0.0359 memory: 17006 grad_norm: 4.1308 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.4386 loss: 1.4386 2022/10/13 04:27:22 - mmengine - INFO - Epoch(train) [41][700/940] lr: 1.0000e-03 eta: 7:55:33 time: 0.5377 data_time: 0.0340 memory: 17006 grad_norm: 4.0666 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.5309 loss: 1.5309 2022/10/13 04:27:31 - mmengine - INFO - Epoch(train) [41][720/940] lr: 1.0000e-03 eta: 7:55:21 time: 0.4574 data_time: 0.0326 memory: 17006 grad_norm: 4.0208 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.5506 loss: 1.5506 2022/10/13 04:27:42 - mmengine - INFO - Epoch(train) [41][740/940] lr: 1.0000e-03 eta: 7:55:12 time: 0.5401 data_time: 0.0282 memory: 17006 grad_norm: 4.0739 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.5410 loss: 1.5410 2022/10/13 04:27:51 - mmengine - INFO - Epoch(train) [41][760/940] lr: 1.0000e-03 eta: 7:55:00 time: 0.4595 data_time: 0.0327 memory: 17006 grad_norm: 4.0560 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.5663 loss: 1.5663 2022/10/13 04:28:01 - mmengine - INFO - Epoch(train) [41][780/940] lr: 1.0000e-03 eta: 7:54:49 time: 0.4904 data_time: 0.0369 memory: 17006 grad_norm: 4.1726 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5561 loss: 1.5561 2022/10/13 04:28:11 - mmengine - INFO - Epoch(train) [41][800/940] lr: 1.0000e-03 eta: 7:54:39 time: 0.5023 data_time: 0.0282 memory: 17006 grad_norm: 4.1223 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6872 loss: 1.6872 2022/10/13 04:28:21 - mmengine - INFO - Epoch(train) [41][820/940] lr: 1.0000e-03 eta: 7:54:28 time: 0.5053 data_time: 0.0326 memory: 17006 grad_norm: 4.1236 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4534 loss: 1.4534 2022/10/13 04:28:31 - mmengine - INFO - Epoch(train) [41][840/940] lr: 1.0000e-03 eta: 7:54:19 time: 0.5332 data_time: 0.0294 memory: 17006 grad_norm: 4.0683 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 1.4854 loss: 1.4854 2022/10/13 04:28:42 - mmengine - INFO - Epoch(train) [41][860/940] lr: 1.0000e-03 eta: 7:54:09 time: 0.5332 data_time: 0.0314 memory: 17006 grad_norm: 4.0815 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4978 loss: 1.4978 2022/10/13 04:28:52 - mmengine - INFO - Epoch(train) [41][880/940] lr: 1.0000e-03 eta: 7:53:59 time: 0.5065 data_time: 0.0311 memory: 17006 grad_norm: 4.1739 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.6200 loss: 1.6200 2022/10/13 04:29:02 - mmengine - INFO - Epoch(train) [41][900/940] lr: 1.0000e-03 eta: 7:53:48 time: 0.5155 data_time: 0.0292 memory: 17006 grad_norm: 3.9977 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3572 loss: 1.3572 2022/10/13 04:29:11 - mmengine - INFO - Epoch(train) [41][920/940] lr: 1.0000e-03 eta: 7:53:36 time: 0.4333 data_time: 0.0308 memory: 17006 grad_norm: 4.1353 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3901 loss: 1.3901 2022/10/13 04:29:21 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 04:29:21 - mmengine - INFO - Epoch(train) [41][940/940] lr: 1.0000e-03 eta: 7:53:25 time: 0.4997 data_time: 0.0274 memory: 17006 grad_norm: 4.3239 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.4331 loss: 1.4331 2022/10/13 04:29:34 - mmengine - INFO - Epoch(val) [41][20/78] eta: 0:00:36 time: 0.6324 data_time: 0.5363 memory: 3172 2022/10/13 04:29:43 - mmengine - INFO - Epoch(val) [41][40/78] eta: 0:00:16 time: 0.4288 data_time: 0.3361 memory: 3172 2022/10/13 04:29:54 - mmengine - INFO - Epoch(val) [41][60/78] eta: 0:00:10 time: 0.5895 data_time: 0.4982 memory: 3172 2022/10/13 04:30:04 - mmengine - INFO - Epoch(val) [41][78/78] acc/top1: 0.6619 acc/top5: 0.8611 acc/mean1: 0.6618 2022/10/13 04:30:04 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_38.pth is removed 2022/10/13 04:30:04 - mmengine - INFO - The best checkpoint with 0.6619 acc/top1 at 41 epoch is saved to best_acc/top1_epoch_41.pth. 2022/10/13 04:30:18 - mmengine - INFO - Epoch(train) [42][20/940] lr: 1.0000e-03 eta: 7:53:20 time: 0.6755 data_time: 0.2535 memory: 17006 grad_norm: 4.0879 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.4061 loss: 1.4061 2022/10/13 04:30:27 - mmengine - INFO - Epoch(train) [42][40/940] lr: 1.0000e-03 eta: 7:53:08 time: 0.4611 data_time: 0.0296 memory: 17006 grad_norm: 4.1403 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5708 loss: 1.5708 2022/10/13 04:30:39 - mmengine - INFO - Epoch(train) [42][60/940] lr: 1.0000e-03 eta: 7:52:59 time: 0.5662 data_time: 0.0401 memory: 17006 grad_norm: 4.1215 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.5509 loss: 1.5509 2022/10/13 04:30:48 - mmengine - INFO - Epoch(train) [42][80/940] lr: 1.0000e-03 eta: 7:52:48 time: 0.4624 data_time: 0.0362 memory: 17006 grad_norm: 4.0976 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4655 loss: 1.4655 2022/10/13 04:30:59 - mmengine - INFO - Epoch(train) [42][100/940] lr: 1.0000e-03 eta: 7:52:38 time: 0.5483 data_time: 0.0967 memory: 17006 grad_norm: 4.0297 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5135 loss: 1.5135 2022/10/13 04:31:08 - mmengine - INFO - Epoch(train) [42][120/940] lr: 1.0000e-03 eta: 7:52:27 time: 0.4796 data_time: 0.0748 memory: 17006 grad_norm: 4.0418 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3106 loss: 1.3106 2022/10/13 04:31:19 - mmengine - INFO - Epoch(train) [42][140/940] lr: 1.0000e-03 eta: 7:52:18 time: 0.5300 data_time: 0.0427 memory: 17006 grad_norm: 4.1011 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.4759 loss: 1.4759 2022/10/13 04:31:29 - mmengine - INFO - Epoch(train) [42][160/940] lr: 1.0000e-03 eta: 7:52:07 time: 0.4901 data_time: 0.0378 memory: 17006 grad_norm: 4.1026 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.4295 loss: 1.4295 2022/10/13 04:31:40 - mmengine - INFO - Epoch(train) [42][180/940] lr: 1.0000e-03 eta: 7:51:58 time: 0.5683 data_time: 0.0305 memory: 17006 grad_norm: 4.1249 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5077 loss: 1.5077 2022/10/13 04:31:49 - mmengine - INFO - Epoch(train) [42][200/940] lr: 1.0000e-03 eta: 7:51:46 time: 0.4492 data_time: 0.0347 memory: 17006 grad_norm: 4.1221 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.3749 loss: 1.3749 2022/10/13 04:32:00 - mmengine - INFO - Epoch(train) [42][220/940] lr: 1.0000e-03 eta: 7:51:37 time: 0.5594 data_time: 0.0278 memory: 17006 grad_norm: 4.1680 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.4231 loss: 1.4231 2022/10/13 04:32:10 - mmengine - INFO - Epoch(train) [42][240/940] lr: 1.0000e-03 eta: 7:51:26 time: 0.4805 data_time: 0.0302 memory: 17006 grad_norm: 4.0456 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.3950 loss: 1.3950 2022/10/13 04:32:21 - mmengine - INFO - Epoch(train) [42][260/940] lr: 1.0000e-03 eta: 7:51:17 time: 0.5435 data_time: 0.0320 memory: 17006 grad_norm: 4.1273 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.3467 loss: 1.3467 2022/10/13 04:32:30 - mmengine - INFO - Epoch(train) [42][280/940] lr: 1.0000e-03 eta: 7:51:05 time: 0.4734 data_time: 0.0338 memory: 17006 grad_norm: 4.1009 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4743 loss: 1.4743 2022/10/13 04:32:41 - mmengine - INFO - Epoch(train) [42][300/940] lr: 1.0000e-03 eta: 7:50:56 time: 0.5446 data_time: 0.0313 memory: 17006 grad_norm: 4.1436 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5014 loss: 1.5014 2022/10/13 04:32:51 - mmengine - INFO - Epoch(train) [42][320/940] lr: 1.0000e-03 eta: 7:50:45 time: 0.4777 data_time: 0.0303 memory: 17006 grad_norm: 4.1191 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4817 loss: 1.4817 2022/10/13 04:33:02 - mmengine - INFO - Epoch(train) [42][340/940] lr: 1.0000e-03 eta: 7:50:35 time: 0.5433 data_time: 0.0390 memory: 17006 grad_norm: 4.1568 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4797 loss: 1.4797 2022/10/13 04:33:11 - mmengine - INFO - Epoch(train) [42][360/940] lr: 1.0000e-03 eta: 7:50:24 time: 0.4598 data_time: 0.0300 memory: 17006 grad_norm: 4.0077 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4251 loss: 1.4251 2022/10/13 04:33:23 - mmengine - INFO - Epoch(train) [42][380/940] lr: 1.0000e-03 eta: 7:50:17 time: 0.6277 data_time: 0.0306 memory: 17006 grad_norm: 4.2181 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4844 loss: 1.4844 2022/10/13 04:33:33 - mmengine - INFO - Epoch(train) [42][400/940] lr: 1.0000e-03 eta: 7:50:06 time: 0.4938 data_time: 0.0304 memory: 17006 grad_norm: 4.2201 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.5008 loss: 1.5008 2022/10/13 04:33:45 - mmengine - INFO - Epoch(train) [42][420/940] lr: 1.0000e-03 eta: 7:49:57 time: 0.5668 data_time: 0.0342 memory: 17006 grad_norm: 4.1155 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.5253 loss: 1.5253 2022/10/13 04:33:54 - mmengine - INFO - Epoch(train) [42][440/940] lr: 1.0000e-03 eta: 7:49:45 time: 0.4573 data_time: 0.0285 memory: 17006 grad_norm: 4.0301 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4332 loss: 1.4332 2022/10/13 04:34:05 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 04:34:05 - mmengine - INFO - Epoch(train) [42][460/940] lr: 1.0000e-03 eta: 7:49:37 time: 0.5799 data_time: 0.0325 memory: 17006 grad_norm: 4.0902 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.4511 loss: 1.4511 2022/10/13 04:34:14 - mmengine - INFO - Epoch(train) [42][480/940] lr: 1.0000e-03 eta: 7:49:25 time: 0.4506 data_time: 0.0317 memory: 17006 grad_norm: 4.1863 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5211 loss: 1.5211 2022/10/13 04:34:25 - mmengine - INFO - Epoch(train) [42][500/940] lr: 1.0000e-03 eta: 7:49:15 time: 0.5227 data_time: 0.0320 memory: 17006 grad_norm: 4.1117 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3765 loss: 1.3765 2022/10/13 04:34:33 - mmengine - INFO - Epoch(train) [42][520/940] lr: 1.0000e-03 eta: 7:49:02 time: 0.4303 data_time: 0.0315 memory: 17006 grad_norm: 4.1127 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4734 loss: 1.4734 2022/10/13 04:34:44 - mmengine - INFO - Epoch(train) [42][540/940] lr: 1.0000e-03 eta: 7:48:53 time: 0.5530 data_time: 0.0279 memory: 17006 grad_norm: 4.0796 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3629 loss: 1.3629 2022/10/13 04:34:53 - mmengine - INFO - Epoch(train) [42][560/940] lr: 1.0000e-03 eta: 7:48:41 time: 0.4474 data_time: 0.0370 memory: 17006 grad_norm: 4.1750 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4383 loss: 1.4383 2022/10/13 04:35:05 - mmengine - INFO - Epoch(train) [42][580/940] lr: 1.0000e-03 eta: 7:48:33 time: 0.5777 data_time: 0.0309 memory: 17006 grad_norm: 4.1912 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4444 loss: 1.4444 2022/10/13 04:35:14 - mmengine - INFO - Epoch(train) [42][600/940] lr: 1.0000e-03 eta: 7:48:21 time: 0.4680 data_time: 0.0358 memory: 17006 grad_norm: 4.1801 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5126 loss: 1.5126 2022/10/13 04:35:25 - mmengine - INFO - Epoch(train) [42][620/940] lr: 1.0000e-03 eta: 7:48:11 time: 0.5227 data_time: 0.0316 memory: 17006 grad_norm: 4.1904 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.5792 loss: 1.5792 2022/10/13 04:35:35 - mmengine - INFO - Epoch(train) [42][640/940] lr: 1.0000e-03 eta: 7:48:01 time: 0.4910 data_time: 0.0333 memory: 17006 grad_norm: 4.1224 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.4561 loss: 1.4561 2022/10/13 04:35:45 - mmengine - INFO - Epoch(train) [42][660/940] lr: 1.0000e-03 eta: 7:47:51 time: 0.5352 data_time: 0.0298 memory: 17006 grad_norm: 4.1820 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5244 loss: 1.5244 2022/10/13 04:35:56 - mmengine - INFO - Epoch(train) [42][680/940] lr: 1.0000e-03 eta: 7:47:41 time: 0.5320 data_time: 0.0386 memory: 17006 grad_norm: 4.1860 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4569 loss: 1.4569 2022/10/13 04:36:07 - mmengine - INFO - Epoch(train) [42][700/940] lr: 1.0000e-03 eta: 7:47:32 time: 0.5366 data_time: 0.0305 memory: 17006 grad_norm: 4.2004 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4959 loss: 1.4959 2022/10/13 04:36:16 - mmengine - INFO - Epoch(train) [42][720/940] lr: 1.0000e-03 eta: 7:47:20 time: 0.4685 data_time: 0.0383 memory: 17006 grad_norm: 4.1302 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4639 loss: 1.4639 2022/10/13 04:36:26 - mmengine - INFO - Epoch(train) [42][740/940] lr: 1.0000e-03 eta: 7:47:10 time: 0.5083 data_time: 0.0334 memory: 17006 grad_norm: 4.1064 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.5723 loss: 1.5723 2022/10/13 04:36:36 - mmengine - INFO - Epoch(train) [42][760/940] lr: 1.0000e-03 eta: 7:46:59 time: 0.4821 data_time: 0.0351 memory: 17006 grad_norm: 4.1637 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5331 loss: 1.5331 2022/10/13 04:36:46 - mmengine - INFO - Epoch(train) [42][780/940] lr: 1.0000e-03 eta: 7:46:49 time: 0.5279 data_time: 0.0291 memory: 17006 grad_norm: 4.1338 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5531 loss: 1.5531 2022/10/13 04:36:56 - mmengine - INFO - Epoch(train) [42][800/940] lr: 1.0000e-03 eta: 7:46:37 time: 0.4610 data_time: 0.0360 memory: 17006 grad_norm: 4.0827 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5764 loss: 1.5764 2022/10/13 04:37:06 - mmengine - INFO - Epoch(train) [42][820/940] lr: 1.0000e-03 eta: 7:46:27 time: 0.5209 data_time: 0.0320 memory: 17006 grad_norm: 4.1620 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.3859 loss: 1.3859 2022/10/13 04:37:16 - mmengine - INFO - Epoch(train) [42][840/940] lr: 1.0000e-03 eta: 7:46:17 time: 0.4915 data_time: 0.0364 memory: 17006 grad_norm: 4.1512 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4734 loss: 1.4734 2022/10/13 04:37:25 - mmengine - INFO - Epoch(train) [42][860/940] lr: 1.0000e-03 eta: 7:46:05 time: 0.4794 data_time: 0.0321 memory: 17006 grad_norm: 4.1641 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3245 loss: 1.3245 2022/10/13 04:37:35 - mmengine - INFO - Epoch(train) [42][880/940] lr: 1.0000e-03 eta: 7:45:55 time: 0.4915 data_time: 0.0375 memory: 17006 grad_norm: 4.1219 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4040 loss: 1.4040 2022/10/13 04:37:46 - mmengine - INFO - Epoch(train) [42][900/940] lr: 1.0000e-03 eta: 7:45:45 time: 0.5294 data_time: 0.0385 memory: 17006 grad_norm: 4.1515 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.4046 loss: 1.4046 2022/10/13 04:37:57 - mmengine - INFO - Epoch(train) [42][920/940] lr: 1.0000e-03 eta: 7:45:36 time: 0.5530 data_time: 0.0280 memory: 17006 grad_norm: 4.1686 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4687 loss: 1.4687 2022/10/13 04:38:06 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 04:38:06 - mmengine - INFO - Epoch(train) [42][940/940] lr: 1.0000e-03 eta: 7:45:24 time: 0.4545 data_time: 0.0230 memory: 17006 grad_norm: 4.3869 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.4651 loss: 1.4651 2022/10/13 04:38:06 - mmengine - INFO - Saving checkpoint at 42 epochs 2022/10/13 04:38:19 - mmengine - INFO - Epoch(val) [42][20/78] eta: 0:00:36 time: 0.6262 data_time: 0.5356 memory: 3172 2022/10/13 04:38:28 - mmengine - INFO - Epoch(val) [42][40/78] eta: 0:00:16 time: 0.4300 data_time: 0.3408 memory: 3172 2022/10/13 04:38:40 - mmengine - INFO - Epoch(val) [42][60/78] eta: 0:00:10 time: 0.5920 data_time: 0.5023 memory: 3172 2022/10/13 04:38:49 - mmengine - INFO - Epoch(val) [42][78/78] acc/top1: 0.6649 acc/top5: 0.8662 acc/mean1: 0.6648 2022/10/13 04:38:49 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_41.pth is removed 2022/10/13 04:38:50 - mmengine - INFO - The best checkpoint with 0.6649 acc/top1 at 42 epoch is saved to best_acc/top1_epoch_42.pth. 2022/10/13 04:39:04 - mmengine - INFO - Epoch(train) [43][20/940] lr: 1.0000e-03 eta: 7:45:20 time: 0.7433 data_time: 0.4314 memory: 17006 grad_norm: 4.1778 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.4832 loss: 1.4832 2022/10/13 04:39:14 - mmengine - INFO - Epoch(train) [43][40/940] lr: 1.0000e-03 eta: 7:45:09 time: 0.4690 data_time: 0.1431 memory: 17006 grad_norm: 4.1271 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4291 loss: 1.4291 2022/10/13 04:39:25 - mmengine - INFO - Epoch(train) [43][60/940] lr: 1.0000e-03 eta: 7:45:00 time: 0.5667 data_time: 0.2351 memory: 17006 grad_norm: 4.2015 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4722 loss: 1.4722 2022/10/13 04:39:34 - mmengine - INFO - Epoch(train) [43][80/940] lr: 1.0000e-03 eta: 7:44:48 time: 0.4559 data_time: 0.1223 memory: 17006 grad_norm: 4.0932 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4116 loss: 1.4116 2022/10/13 04:39:45 - mmengine - INFO - Epoch(train) [43][100/940] lr: 1.0000e-03 eta: 7:44:38 time: 0.5154 data_time: 0.1907 memory: 17006 grad_norm: 4.1783 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4900 loss: 1.4900 2022/10/13 04:39:54 - mmengine - INFO - Epoch(train) [43][120/940] lr: 1.0000e-03 eta: 7:44:26 time: 0.4494 data_time: 0.1222 memory: 17006 grad_norm: 4.1177 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.3480 loss: 1.3480 2022/10/13 04:40:04 - mmengine - INFO - Epoch(train) [43][140/940] lr: 1.0000e-03 eta: 7:44:16 time: 0.5266 data_time: 0.1392 memory: 17006 grad_norm: 4.1674 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3383 loss: 1.3383 2022/10/13 04:40:14 - mmengine - INFO - Epoch(train) [43][160/940] lr: 1.0000e-03 eta: 7:44:05 time: 0.4821 data_time: 0.0650 memory: 17006 grad_norm: 4.0843 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.4723 loss: 1.4723 2022/10/13 04:40:24 - mmengine - INFO - Epoch(train) [43][180/940] lr: 1.0000e-03 eta: 7:43:55 time: 0.5315 data_time: 0.0836 memory: 17006 grad_norm: 4.1939 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4669 loss: 1.4669 2022/10/13 04:40:34 - mmengine - INFO - Epoch(train) [43][200/940] lr: 1.0000e-03 eta: 7:43:44 time: 0.4800 data_time: 0.0785 memory: 17006 grad_norm: 4.1346 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3321 loss: 1.3321 2022/10/13 04:40:45 - mmengine - INFO - Epoch(train) [43][220/940] lr: 1.0000e-03 eta: 7:43:35 time: 0.5576 data_time: 0.0356 memory: 17006 grad_norm: 4.2649 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5578 loss: 1.5578 2022/10/13 04:40:55 - mmengine - INFO - Epoch(train) [43][240/940] lr: 1.0000e-03 eta: 7:43:24 time: 0.4970 data_time: 0.0285 memory: 17006 grad_norm: 4.1208 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.5032 loss: 1.5032 2022/10/13 04:41:04 - mmengine - INFO - Epoch(train) [43][260/940] lr: 1.0000e-03 eta: 7:43:13 time: 0.4661 data_time: 0.0347 memory: 17006 grad_norm: 4.1212 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4211 loss: 1.4211 2022/10/13 04:41:14 - mmengine - INFO - Epoch(train) [43][280/940] lr: 1.0000e-03 eta: 7:43:02 time: 0.4941 data_time: 0.0331 memory: 17006 grad_norm: 4.1692 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4758 loss: 1.4758 2022/10/13 04:41:25 - mmengine - INFO - Epoch(train) [43][300/940] lr: 1.0000e-03 eta: 7:42:52 time: 0.5270 data_time: 0.0348 memory: 17006 grad_norm: 4.1751 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.4845 loss: 1.4845 2022/10/13 04:41:35 - mmengine - INFO - Epoch(train) [43][320/940] lr: 1.0000e-03 eta: 7:42:41 time: 0.4875 data_time: 0.0373 memory: 17006 grad_norm: 4.1473 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5616 loss: 1.5616 2022/10/13 04:41:46 - mmengine - INFO - Epoch(train) [43][340/940] lr: 1.0000e-03 eta: 7:42:33 time: 0.5783 data_time: 0.0356 memory: 17006 grad_norm: 4.1480 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4971 loss: 1.4971 2022/10/13 04:41:55 - mmengine - INFO - Epoch(train) [43][360/940] lr: 1.0000e-03 eta: 7:42:21 time: 0.4612 data_time: 0.0304 memory: 17006 grad_norm: 4.1558 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3854 loss: 1.3854 2022/10/13 04:42:06 - mmengine - INFO - Epoch(train) [43][380/940] lr: 1.0000e-03 eta: 7:42:11 time: 0.5158 data_time: 0.0304 memory: 17006 grad_norm: 4.2258 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4353 loss: 1.4353 2022/10/13 04:42:15 - mmengine - INFO - Epoch(train) [43][400/940] lr: 1.0000e-03 eta: 7:42:00 time: 0.4866 data_time: 0.0337 memory: 17006 grad_norm: 4.1135 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4255 loss: 1.4255 2022/10/13 04:42:26 - mmengine - INFO - Epoch(train) [43][420/940] lr: 1.0000e-03 eta: 7:41:51 time: 0.5336 data_time: 0.0338 memory: 17006 grad_norm: 4.1364 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.5534 loss: 1.5534 2022/10/13 04:42:36 - mmengine - INFO - Epoch(train) [43][440/940] lr: 1.0000e-03 eta: 7:41:40 time: 0.5095 data_time: 0.0366 memory: 17006 grad_norm: 4.1335 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3495 loss: 1.3495 2022/10/13 04:42:46 - mmengine - INFO - Epoch(train) [43][460/940] lr: 1.0000e-03 eta: 7:41:29 time: 0.4657 data_time: 0.0266 memory: 17006 grad_norm: 4.1726 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4276 loss: 1.4276 2022/10/13 04:42:56 - mmengine - INFO - Epoch(train) [43][480/940] lr: 1.0000e-03 eta: 7:41:19 time: 0.5177 data_time: 0.0386 memory: 17006 grad_norm: 4.2027 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6016 loss: 1.6016 2022/10/13 04:43:06 - mmengine - INFO - Epoch(train) [43][500/940] lr: 1.0000e-03 eta: 7:41:08 time: 0.4888 data_time: 0.0393 memory: 17006 grad_norm: 4.1863 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4089 loss: 1.4089 2022/10/13 04:43:16 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 04:43:16 - mmengine - INFO - Epoch(train) [43][520/940] lr: 1.0000e-03 eta: 7:40:58 time: 0.5233 data_time: 0.0360 memory: 17006 grad_norm: 4.1691 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6151 loss: 1.6151 2022/10/13 04:43:25 - mmengine - INFO - Epoch(train) [43][540/940] lr: 1.0000e-03 eta: 7:40:46 time: 0.4644 data_time: 0.0269 memory: 17006 grad_norm: 4.2124 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4367 loss: 1.4367 2022/10/13 04:43:36 - mmengine - INFO - Epoch(train) [43][560/940] lr: 1.0000e-03 eta: 7:40:36 time: 0.5121 data_time: 0.0335 memory: 17006 grad_norm: 4.1121 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3252 loss: 1.3252 2022/10/13 04:43:46 - mmengine - INFO - Epoch(train) [43][580/940] lr: 1.0000e-03 eta: 7:40:26 time: 0.5294 data_time: 0.0300 memory: 17006 grad_norm: 4.1527 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4553 loss: 1.4553 2022/10/13 04:43:56 - mmengine - INFO - Epoch(train) [43][600/940] lr: 1.0000e-03 eta: 7:40:15 time: 0.4726 data_time: 0.0332 memory: 17006 grad_norm: 4.2055 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5843 loss: 1.5843 2022/10/13 04:44:06 - mmengine - INFO - Epoch(train) [43][620/940] lr: 1.0000e-03 eta: 7:40:04 time: 0.4942 data_time: 0.0306 memory: 17006 grad_norm: 4.2081 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3623 loss: 1.3623 2022/10/13 04:44:16 - mmengine - INFO - Epoch(train) [43][640/940] lr: 1.0000e-03 eta: 7:39:55 time: 0.5431 data_time: 0.0347 memory: 17006 grad_norm: 4.2430 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6446 loss: 1.6446 2022/10/13 04:44:26 - mmengine - INFO - Epoch(train) [43][660/940] lr: 1.0000e-03 eta: 7:39:44 time: 0.4875 data_time: 0.0264 memory: 17006 grad_norm: 4.2188 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4475 loss: 1.4475 2022/10/13 04:44:37 - mmengine - INFO - Epoch(train) [43][680/940] lr: 1.0000e-03 eta: 7:39:34 time: 0.5169 data_time: 0.0339 memory: 17006 grad_norm: 4.2086 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.4824 loss: 1.4824 2022/10/13 04:44:47 - mmengine - INFO - Epoch(train) [43][700/940] lr: 1.0000e-03 eta: 7:39:23 time: 0.5078 data_time: 0.0285 memory: 17006 grad_norm: 4.1970 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.3797 loss: 1.3797 2022/10/13 04:44:57 - mmengine - INFO - Epoch(train) [43][720/940] lr: 1.0000e-03 eta: 7:39:13 time: 0.5118 data_time: 0.0362 memory: 17006 grad_norm: 4.1342 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.5035 loss: 1.5035 2022/10/13 04:45:08 - mmengine - INFO - Epoch(train) [43][740/940] lr: 1.0000e-03 eta: 7:39:04 time: 0.5566 data_time: 0.0303 memory: 17006 grad_norm: 4.1616 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4897 loss: 1.4897 2022/10/13 04:45:18 - mmengine - INFO - Epoch(train) [43][760/940] lr: 1.0000e-03 eta: 7:38:53 time: 0.4773 data_time: 0.0342 memory: 17006 grad_norm: 4.1399 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.5110 loss: 1.5110 2022/10/13 04:45:28 - mmengine - INFO - Epoch(train) [43][780/940] lr: 1.0000e-03 eta: 7:38:43 time: 0.5397 data_time: 0.0318 memory: 17006 grad_norm: 4.1081 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3792 loss: 1.3792 2022/10/13 04:45:39 - mmengine - INFO - Epoch(train) [43][800/940] lr: 1.0000e-03 eta: 7:38:34 time: 0.5248 data_time: 0.0338 memory: 17006 grad_norm: 4.1186 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5398 loss: 1.5398 2022/10/13 04:45:49 - mmengine - INFO - Epoch(train) [43][820/940] lr: 1.0000e-03 eta: 7:38:23 time: 0.4975 data_time: 0.0375 memory: 17006 grad_norm: 4.1637 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.4892 loss: 1.4892 2022/10/13 04:45:59 - mmengine - INFO - Epoch(train) [43][840/940] lr: 1.0000e-03 eta: 7:38:12 time: 0.4896 data_time: 0.0365 memory: 17006 grad_norm: 4.2106 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4755 loss: 1.4755 2022/10/13 04:46:09 - mmengine - INFO - Epoch(train) [43][860/940] lr: 1.0000e-03 eta: 7:38:02 time: 0.4992 data_time: 0.0295 memory: 17006 grad_norm: 4.1458 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.3544 loss: 1.3544 2022/10/13 04:46:19 - mmengine - INFO - Epoch(train) [43][880/940] lr: 1.0000e-03 eta: 7:37:52 time: 0.5252 data_time: 0.0422 memory: 17006 grad_norm: 4.1582 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4754 loss: 1.4754 2022/10/13 04:46:29 - mmengine - INFO - Epoch(train) [43][900/940] lr: 1.0000e-03 eta: 7:37:40 time: 0.4774 data_time: 0.0328 memory: 17006 grad_norm: 4.1845 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3250 loss: 1.3250 2022/10/13 04:46:39 - mmengine - INFO - Epoch(train) [43][920/940] lr: 1.0000e-03 eta: 7:37:30 time: 0.5043 data_time: 0.0347 memory: 17006 grad_norm: 4.1973 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4243 loss: 1.4243 2022/10/13 04:46:48 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 04:46:48 - mmengine - INFO - Epoch(train) [43][940/940] lr: 1.0000e-03 eta: 7:37:18 time: 0.4581 data_time: 0.0282 memory: 17006 grad_norm: 4.5648 top1_acc: 0.5714 top5_acc: 1.0000 loss_cls: 1.4793 loss: 1.4793 2022/10/13 04:47:01 - mmengine - INFO - Epoch(val) [43][20/78] eta: 0:00:36 time: 0.6340 data_time: 0.5403 memory: 3172 2022/10/13 04:47:09 - mmengine - INFO - Epoch(val) [43][40/78] eta: 0:00:16 time: 0.4278 data_time: 0.3364 memory: 3172 2022/10/13 04:47:21 - mmengine - INFO - Epoch(val) [43][60/78] eta: 0:00:10 time: 0.5654 data_time: 0.4744 memory: 3172 2022/10/13 04:47:31 - mmengine - INFO - Epoch(val) [43][78/78] acc/top1: 0.6662 acc/top5: 0.8658 acc/mean1: 0.6661 2022/10/13 04:47:31 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_42.pth is removed 2022/10/13 04:47:32 - mmengine - INFO - The best checkpoint with 0.6662 acc/top1 at 43 epoch is saved to best_acc/top1_epoch_43.pth. 2022/10/13 04:47:45 - mmengine - INFO - Epoch(train) [44][20/940] lr: 1.0000e-03 eta: 7:37:12 time: 0.6718 data_time: 0.3230 memory: 17006 grad_norm: 4.1633 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4953 loss: 1.4953 2022/10/13 04:47:54 - mmengine - INFO - Epoch(train) [44][40/940] lr: 1.0000e-03 eta: 7:37:01 time: 0.4608 data_time: 0.1037 memory: 17006 grad_norm: 4.1789 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.5399 loss: 1.5399 2022/10/13 04:48:05 - mmengine - INFO - Epoch(train) [44][60/940] lr: 1.0000e-03 eta: 7:36:52 time: 0.5546 data_time: 0.0798 memory: 17006 grad_norm: 4.1608 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3617 loss: 1.3617 2022/10/13 04:48:15 - mmengine - INFO - Epoch(train) [44][80/940] lr: 1.0000e-03 eta: 7:36:41 time: 0.5059 data_time: 0.0904 memory: 17006 grad_norm: 4.1909 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4247 loss: 1.4247 2022/10/13 04:48:25 - mmengine - INFO - Epoch(train) [44][100/940] lr: 1.0000e-03 eta: 7:36:31 time: 0.4978 data_time: 0.1502 memory: 17006 grad_norm: 4.1754 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4210 loss: 1.4210 2022/10/13 04:48:36 - mmengine - INFO - Epoch(train) [44][120/940] lr: 1.0000e-03 eta: 7:36:20 time: 0.5098 data_time: 0.1702 memory: 17006 grad_norm: 4.1492 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4318 loss: 1.4318 2022/10/13 04:48:46 - mmengine - INFO - Epoch(train) [44][140/940] lr: 1.0000e-03 eta: 7:36:10 time: 0.5163 data_time: 0.1199 memory: 17006 grad_norm: 4.1516 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3621 loss: 1.3621 2022/10/13 04:48:56 - mmengine - INFO - Epoch(train) [44][160/940] lr: 1.0000e-03 eta: 7:36:00 time: 0.5103 data_time: 0.0350 memory: 17006 grad_norm: 4.1621 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.3823 loss: 1.3823 2022/10/13 04:49:06 - mmengine - INFO - Epoch(train) [44][180/940] lr: 1.0000e-03 eta: 7:35:49 time: 0.4954 data_time: 0.0304 memory: 17006 grad_norm: 4.2000 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 1.5039 loss: 1.5039 2022/10/13 04:49:17 - mmengine - INFO - Epoch(train) [44][200/940] lr: 1.0000e-03 eta: 7:35:40 time: 0.5412 data_time: 0.0404 memory: 17006 grad_norm: 4.1746 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4950 loss: 1.4950 2022/10/13 04:49:27 - mmengine - INFO - Epoch(train) [44][220/940] lr: 1.0000e-03 eta: 7:35:29 time: 0.5020 data_time: 0.0632 memory: 17006 grad_norm: 4.1962 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.2941 loss: 1.2941 2022/10/13 04:49:37 - mmengine - INFO - Epoch(train) [44][240/940] lr: 1.0000e-03 eta: 7:35:18 time: 0.4871 data_time: 0.0370 memory: 17006 grad_norm: 4.2230 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.3441 loss: 1.3441 2022/10/13 04:49:47 - mmengine - INFO - Epoch(train) [44][260/940] lr: 1.0000e-03 eta: 7:35:08 time: 0.5138 data_time: 0.0268 memory: 17006 grad_norm: 4.1684 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.4545 loss: 1.4545 2022/10/13 04:49:57 - mmengine - INFO - Epoch(train) [44][280/940] lr: 1.0000e-03 eta: 7:34:58 time: 0.5159 data_time: 0.0382 memory: 17006 grad_norm: 4.2303 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4150 loss: 1.4150 2022/10/13 04:50:07 - mmengine - INFO - Epoch(train) [44][300/940] lr: 1.0000e-03 eta: 7:34:47 time: 0.4787 data_time: 0.0290 memory: 17006 grad_norm: 4.2765 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2850 loss: 1.2850 2022/10/13 04:50:17 - mmengine - INFO - Epoch(train) [44][320/940] lr: 1.0000e-03 eta: 7:34:37 time: 0.5115 data_time: 0.0355 memory: 17006 grad_norm: 4.2038 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.4043 loss: 1.4043 2022/10/13 04:50:27 - mmengine - INFO - Epoch(train) [44][340/940] lr: 1.0000e-03 eta: 7:34:26 time: 0.5200 data_time: 0.0329 memory: 17006 grad_norm: 4.2099 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.5584 loss: 1.5584 2022/10/13 04:50:37 - mmengine - INFO - Epoch(train) [44][360/940] lr: 1.0000e-03 eta: 7:34:15 time: 0.4649 data_time: 0.0351 memory: 17006 grad_norm: 4.1933 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4685 loss: 1.4685 2022/10/13 04:50:48 - mmengine - INFO - Epoch(train) [44][380/940] lr: 1.0000e-03 eta: 7:34:06 time: 0.5412 data_time: 0.0301 memory: 17006 grad_norm: 4.1268 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.4135 loss: 1.4135 2022/10/13 04:50:57 - mmengine - INFO - Epoch(train) [44][400/940] lr: 1.0000e-03 eta: 7:33:54 time: 0.4715 data_time: 0.0305 memory: 17006 grad_norm: 4.2410 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3296 loss: 1.3296 2022/10/13 04:51:07 - mmengine - INFO - Epoch(train) [44][420/940] lr: 1.0000e-03 eta: 7:33:44 time: 0.4986 data_time: 0.0352 memory: 17006 grad_norm: 4.2241 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.5188 loss: 1.5188 2022/10/13 04:51:17 - mmengine - INFO - Epoch(train) [44][440/940] lr: 1.0000e-03 eta: 7:33:33 time: 0.5009 data_time: 0.0328 memory: 17006 grad_norm: 4.2380 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5485 loss: 1.5485 2022/10/13 04:51:27 - mmengine - INFO - Epoch(train) [44][460/940] lr: 1.0000e-03 eta: 7:33:23 time: 0.5021 data_time: 0.0340 memory: 17006 grad_norm: 4.2095 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5047 loss: 1.5047 2022/10/13 04:51:37 - mmengine - INFO - Epoch(train) [44][480/940] lr: 1.0000e-03 eta: 7:33:12 time: 0.5138 data_time: 0.0359 memory: 17006 grad_norm: 4.1314 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4627 loss: 1.4627 2022/10/13 04:51:47 - mmengine - INFO - Epoch(train) [44][500/940] lr: 1.0000e-03 eta: 7:33:01 time: 0.4833 data_time: 0.0332 memory: 17006 grad_norm: 4.1855 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.4959 loss: 1.4959 2022/10/13 04:51:58 - mmengine - INFO - Epoch(train) [44][520/940] lr: 1.0000e-03 eta: 7:32:52 time: 0.5601 data_time: 0.0349 memory: 17006 grad_norm: 4.0988 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4407 loss: 1.4407 2022/10/13 04:52:09 - mmengine - INFO - Epoch(train) [44][540/940] lr: 1.0000e-03 eta: 7:32:42 time: 0.5251 data_time: 0.0496 memory: 17006 grad_norm: 4.1754 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5081 loss: 1.5081 2022/10/13 04:52:19 - mmengine - INFO - Epoch(train) [44][560/940] lr: 1.0000e-03 eta: 7:32:33 time: 0.5286 data_time: 0.0368 memory: 17006 grad_norm: 4.1601 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2782 loss: 1.2782 2022/10/13 04:52:29 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 04:52:29 - mmengine - INFO - Epoch(train) [44][580/940] lr: 1.0000e-03 eta: 7:32:21 time: 0.4668 data_time: 0.0300 memory: 17006 grad_norm: 4.2041 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5358 loss: 1.5358 2022/10/13 04:52:39 - mmengine - INFO - Epoch(train) [44][600/940] lr: 1.0000e-03 eta: 7:32:11 time: 0.5213 data_time: 0.0322 memory: 17006 grad_norm: 4.1889 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3830 loss: 1.3830 2022/10/13 04:52:49 - mmengine - INFO - Epoch(train) [44][620/940] lr: 1.0000e-03 eta: 7:32:01 time: 0.4964 data_time: 0.0365 memory: 17006 grad_norm: 4.1713 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3838 loss: 1.3838 2022/10/13 04:52:59 - mmengine - INFO - Epoch(train) [44][640/940] lr: 1.0000e-03 eta: 7:31:51 time: 0.5194 data_time: 0.0363 memory: 17006 grad_norm: 4.2699 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5535 loss: 1.5535 2022/10/13 04:53:09 - mmengine - INFO - Epoch(train) [44][660/940] lr: 1.0000e-03 eta: 7:31:39 time: 0.4763 data_time: 0.0308 memory: 17006 grad_norm: 4.2434 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4827 loss: 1.4827 2022/10/13 04:53:19 - mmengine - INFO - Epoch(train) [44][680/940] lr: 1.0000e-03 eta: 7:31:29 time: 0.4906 data_time: 0.0305 memory: 17006 grad_norm: 4.2362 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3516 loss: 1.3516 2022/10/13 04:53:30 - mmengine - INFO - Epoch(train) [44][700/940] lr: 1.0000e-03 eta: 7:31:19 time: 0.5504 data_time: 0.0310 memory: 17006 grad_norm: 4.2205 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5883 loss: 1.5883 2022/10/13 04:53:39 - mmengine - INFO - Epoch(train) [44][720/940] lr: 1.0000e-03 eta: 7:31:08 time: 0.4792 data_time: 0.0329 memory: 17006 grad_norm: 4.2355 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4199 loss: 1.4199 2022/10/13 04:53:49 - mmengine - INFO - Epoch(train) [44][740/940] lr: 1.0000e-03 eta: 7:30:58 time: 0.5110 data_time: 0.0350 memory: 17006 grad_norm: 4.2466 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5129 loss: 1.5129 2022/10/13 04:53:58 - mmengine - INFO - Epoch(train) [44][760/940] lr: 1.0000e-03 eta: 7:30:46 time: 0.4410 data_time: 0.0311 memory: 17006 grad_norm: 4.1621 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4042 loss: 1.4042 2022/10/13 04:54:09 - mmengine - INFO - Epoch(train) [44][780/940] lr: 1.0000e-03 eta: 7:30:36 time: 0.5239 data_time: 0.0291 memory: 17006 grad_norm: 4.2159 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.5094 loss: 1.5094 2022/10/13 04:54:19 - mmengine - INFO - Epoch(train) [44][800/940] lr: 1.0000e-03 eta: 7:30:25 time: 0.4906 data_time: 0.0316 memory: 17006 grad_norm: 4.2102 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5376 loss: 1.5376 2022/10/13 04:54:29 - mmengine - INFO - Epoch(train) [44][820/940] lr: 1.0000e-03 eta: 7:30:15 time: 0.5092 data_time: 0.0304 memory: 17006 grad_norm: 4.1889 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5236 loss: 1.5236 2022/10/13 04:54:38 - mmengine - INFO - Epoch(train) [44][840/940] lr: 1.0000e-03 eta: 7:30:04 time: 0.4859 data_time: 0.0310 memory: 17006 grad_norm: 4.2029 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4044 loss: 1.4044 2022/10/13 04:54:49 - mmengine - INFO - Epoch(train) [44][860/940] lr: 1.0000e-03 eta: 7:29:54 time: 0.5151 data_time: 0.0321 memory: 17006 grad_norm: 4.1960 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3713 loss: 1.3713 2022/10/13 04:54:58 - mmengine - INFO - Epoch(train) [44][880/940] lr: 1.0000e-03 eta: 7:29:43 time: 0.4843 data_time: 0.0396 memory: 17006 grad_norm: 4.2353 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4297 loss: 1.4297 2022/10/13 04:55:09 - mmengine - INFO - Epoch(train) [44][900/940] lr: 1.0000e-03 eta: 7:29:33 time: 0.5394 data_time: 0.0341 memory: 17006 grad_norm: 4.2433 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5394 loss: 1.5394 2022/10/13 04:55:19 - mmengine - INFO - Epoch(train) [44][920/940] lr: 1.0000e-03 eta: 7:29:22 time: 0.4883 data_time: 0.0351 memory: 17006 grad_norm: 4.2261 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4336 loss: 1.4336 2022/10/13 04:55:29 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 04:55:29 - mmengine - INFO - Epoch(train) [44][940/940] lr: 1.0000e-03 eta: 7:29:12 time: 0.4995 data_time: 0.0301 memory: 17006 grad_norm: 4.4173 top1_acc: 0.5714 top5_acc: 1.0000 loss_cls: 1.3811 loss: 1.3811 2022/10/13 04:55:42 - mmengine - INFO - Epoch(val) [44][20/78] eta: 0:00:36 time: 0.6226 data_time: 0.5295 memory: 3172 2022/10/13 04:55:50 - mmengine - INFO - Epoch(val) [44][40/78] eta: 0:00:16 time: 0.4354 data_time: 0.3448 memory: 3172 2022/10/13 04:56:02 - mmengine - INFO - Epoch(val) [44][60/78] eta: 0:00:10 time: 0.5817 data_time: 0.4910 memory: 3172 2022/10/13 04:56:11 - mmengine - INFO - Epoch(val) [44][78/78] acc/top1: 0.6686 acc/top5: 0.8659 acc/mean1: 0.6685 2022/10/13 04:56:12 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_43.pth is removed 2022/10/13 04:56:12 - mmengine - INFO - The best checkpoint with 0.6686 acc/top1 at 44 epoch is saved to best_acc/top1_epoch_44.pth. 2022/10/13 04:56:25 - mmengine - INFO - Epoch(train) [45][20/940] lr: 1.0000e-03 eta: 7:29:05 time: 0.6563 data_time: 0.3237 memory: 17006 grad_norm: 4.2424 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.4737 loss: 1.4737 2022/10/13 04:56:35 - mmengine - INFO - Epoch(train) [45][40/940] lr: 1.0000e-03 eta: 7:28:54 time: 0.4869 data_time: 0.1828 memory: 17006 grad_norm: 4.1921 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.4823 loss: 1.4823 2022/10/13 04:56:46 - mmengine - INFO - Epoch(train) [45][60/940] lr: 1.0000e-03 eta: 7:28:46 time: 0.5688 data_time: 0.2525 memory: 17006 grad_norm: 4.2197 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4616 loss: 1.4616 2022/10/13 04:56:56 - mmengine - INFO - Epoch(train) [45][80/940] lr: 1.0000e-03 eta: 7:28:35 time: 0.4950 data_time: 0.1728 memory: 17006 grad_norm: 4.0973 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3123 loss: 1.3123 2022/10/13 04:57:07 - mmengine - INFO - Epoch(train) [45][100/940] lr: 1.0000e-03 eta: 7:28:25 time: 0.5410 data_time: 0.1996 memory: 17006 grad_norm: 4.2472 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.4276 loss: 1.4276 2022/10/13 04:57:17 - mmengine - INFO - Epoch(train) [45][120/940] lr: 1.0000e-03 eta: 7:28:15 time: 0.4838 data_time: 0.1497 memory: 17006 grad_norm: 4.1132 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5049 loss: 1.5049 2022/10/13 04:57:28 - mmengine - INFO - Epoch(train) [45][140/940] lr: 1.0000e-03 eta: 7:28:05 time: 0.5518 data_time: 0.2273 memory: 17006 grad_norm: 4.2220 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.4816 loss: 1.4816 2022/10/13 04:57:37 - mmengine - INFO - Epoch(train) [45][160/940] lr: 1.0000e-03 eta: 7:27:53 time: 0.4436 data_time: 0.1020 memory: 17006 grad_norm: 4.2387 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3210 loss: 1.3210 2022/10/13 04:57:47 - mmengine - INFO - Epoch(train) [45][180/940] lr: 1.0000e-03 eta: 7:27:43 time: 0.5136 data_time: 0.0736 memory: 17006 grad_norm: 4.2218 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3806 loss: 1.3806 2022/10/13 04:57:56 - mmengine - INFO - Epoch(train) [45][200/940] lr: 1.0000e-03 eta: 7:27:32 time: 0.4761 data_time: 0.0308 memory: 17006 grad_norm: 4.2442 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5121 loss: 1.5121 2022/10/13 04:58:07 - mmengine - INFO - Epoch(train) [45][220/940] lr: 1.0000e-03 eta: 7:27:22 time: 0.5382 data_time: 0.0341 memory: 17006 grad_norm: 4.2100 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.5840 loss: 1.5840 2022/10/13 04:58:17 - mmengine - INFO - Epoch(train) [45][240/940] lr: 1.0000e-03 eta: 7:27:11 time: 0.4755 data_time: 0.0377 memory: 17006 grad_norm: 4.1760 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3269 loss: 1.3269 2022/10/13 04:58:27 - mmengine - INFO - Epoch(train) [45][260/940] lr: 1.0000e-03 eta: 7:27:01 time: 0.5269 data_time: 0.0345 memory: 17006 grad_norm: 4.1883 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3743 loss: 1.3743 2022/10/13 04:58:37 - mmengine - INFO - Epoch(train) [45][280/940] lr: 1.0000e-03 eta: 7:26:51 time: 0.5009 data_time: 0.0348 memory: 17006 grad_norm: 4.1795 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4817 loss: 1.4817 2022/10/13 04:58:48 - mmengine - INFO - Epoch(train) [45][300/940] lr: 1.0000e-03 eta: 7:26:41 time: 0.5407 data_time: 0.0403 memory: 17006 grad_norm: 4.3616 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5077 loss: 1.5077 2022/10/13 04:58:58 - mmengine - INFO - Epoch(train) [45][320/940] lr: 1.0000e-03 eta: 7:26:30 time: 0.4874 data_time: 0.0330 memory: 17006 grad_norm: 4.2277 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2658 loss: 1.2658 2022/10/13 04:59:07 - mmengine - INFO - Epoch(train) [45][340/940] lr: 1.0000e-03 eta: 7:26:19 time: 0.4834 data_time: 0.0345 memory: 17006 grad_norm: 4.2382 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4047 loss: 1.4047 2022/10/13 04:59:17 - mmengine - INFO - Epoch(train) [45][360/940] lr: 1.0000e-03 eta: 7:26:08 time: 0.4799 data_time: 0.0308 memory: 17006 grad_norm: 4.2221 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4081 loss: 1.4081 2022/10/13 04:59:28 - mmengine - INFO - Epoch(train) [45][380/940] lr: 1.0000e-03 eta: 7:25:59 time: 0.5318 data_time: 0.0382 memory: 17006 grad_norm: 4.3135 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5166 loss: 1.5166 2022/10/13 04:59:37 - mmengine - INFO - Epoch(train) [45][400/940] lr: 1.0000e-03 eta: 7:25:47 time: 0.4734 data_time: 0.0319 memory: 17006 grad_norm: 4.1525 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4146 loss: 1.4146 2022/10/13 04:59:48 - mmengine - INFO - Epoch(train) [45][420/940] lr: 1.0000e-03 eta: 7:25:37 time: 0.5162 data_time: 0.0371 memory: 17006 grad_norm: 4.1977 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5222 loss: 1.5222 2022/10/13 04:59:57 - mmengine - INFO - Epoch(train) [45][440/940] lr: 1.0000e-03 eta: 7:25:27 time: 0.4925 data_time: 0.0262 memory: 17006 grad_norm: 4.2100 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4076 loss: 1.4076 2022/10/13 05:00:08 - mmengine - INFO - Epoch(train) [45][460/940] lr: 1.0000e-03 eta: 7:25:17 time: 0.5465 data_time: 0.0366 memory: 17006 grad_norm: 4.2014 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.4312 loss: 1.4312 2022/10/13 05:00:18 - mmengine - INFO - Epoch(train) [45][480/940] lr: 1.0000e-03 eta: 7:25:06 time: 0.4899 data_time: 0.0341 memory: 17006 grad_norm: 4.2067 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.4441 loss: 1.4441 2022/10/13 05:00:28 - mmengine - INFO - Epoch(train) [45][500/940] lr: 1.0000e-03 eta: 7:24:56 time: 0.5194 data_time: 0.0337 memory: 17006 grad_norm: 4.2455 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5645 loss: 1.5645 2022/10/13 05:00:39 - mmengine - INFO - Epoch(train) [45][520/940] lr: 1.0000e-03 eta: 7:24:46 time: 0.5077 data_time: 0.0334 memory: 17006 grad_norm: 4.1731 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4430 loss: 1.4430 2022/10/13 05:00:48 - mmengine - INFO - Epoch(train) [45][540/940] lr: 1.0000e-03 eta: 7:24:35 time: 0.4920 data_time: 0.0343 memory: 17006 grad_norm: 4.2591 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3589 loss: 1.3589 2022/10/13 05:00:59 - mmengine - INFO - Epoch(train) [45][560/940] lr: 1.0000e-03 eta: 7:24:25 time: 0.5072 data_time: 0.0262 memory: 17006 grad_norm: 4.2381 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4397 loss: 1.4397 2022/10/13 05:01:09 - mmengine - INFO - Epoch(train) [45][580/940] lr: 1.0000e-03 eta: 7:24:15 time: 0.5196 data_time: 0.0376 memory: 17006 grad_norm: 4.2955 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5413 loss: 1.5413 2022/10/13 05:01:20 - mmengine - INFO - Epoch(train) [45][600/940] lr: 1.0000e-03 eta: 7:24:05 time: 0.5288 data_time: 0.0328 memory: 17006 grad_norm: 4.1506 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3253 loss: 1.3253 2022/10/13 05:01:30 - mmengine - INFO - Epoch(train) [45][620/940] lr: 1.0000e-03 eta: 7:23:55 time: 0.4998 data_time: 0.0338 memory: 17006 grad_norm: 4.2375 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4568 loss: 1.4568 2022/10/13 05:01:41 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 05:01:41 - mmengine - INFO - Epoch(train) [45][640/940] lr: 1.0000e-03 eta: 7:23:46 time: 0.5728 data_time: 0.0340 memory: 17006 grad_norm: 4.3067 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.4987 loss: 1.4987 2022/10/13 05:01:50 - mmengine - INFO - Epoch(train) [45][660/940] lr: 1.0000e-03 eta: 7:23:34 time: 0.4611 data_time: 0.0376 memory: 17006 grad_norm: 4.3548 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3736 loss: 1.3736 2022/10/13 05:02:01 - mmengine - INFO - Epoch(train) [45][680/940] lr: 1.0000e-03 eta: 7:23:24 time: 0.5199 data_time: 0.0346 memory: 17006 grad_norm: 4.2885 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.4225 loss: 1.4225 2022/10/13 05:02:10 - mmengine - INFO - Epoch(train) [45][700/940] lr: 1.0000e-03 eta: 7:23:13 time: 0.4707 data_time: 0.0303 memory: 17006 grad_norm: 4.2553 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4660 loss: 1.4660 2022/10/13 05:02:20 - mmengine - INFO - Epoch(train) [45][720/940] lr: 1.0000e-03 eta: 7:23:02 time: 0.4883 data_time: 0.0346 memory: 17006 grad_norm: 4.2834 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6687 loss: 1.6687 2022/10/13 05:02:31 - mmengine - INFO - Epoch(train) [45][740/940] lr: 1.0000e-03 eta: 7:22:53 time: 0.5514 data_time: 0.0351 memory: 17006 grad_norm: 4.2529 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3495 loss: 1.3495 2022/10/13 05:02:41 - mmengine - INFO - Epoch(train) [45][760/940] lr: 1.0000e-03 eta: 7:22:42 time: 0.4854 data_time: 0.0357 memory: 17006 grad_norm: 4.2304 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5305 loss: 1.5305 2022/10/13 05:02:52 - mmengine - INFO - Epoch(train) [45][780/940] lr: 1.0000e-03 eta: 7:22:33 time: 0.5622 data_time: 0.0270 memory: 17006 grad_norm: 4.3217 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4831 loss: 1.4831 2022/10/13 05:03:02 - mmengine - INFO - Epoch(train) [45][800/940] lr: 1.0000e-03 eta: 7:22:22 time: 0.5017 data_time: 0.0339 memory: 17006 grad_norm: 4.2746 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.4605 loss: 1.4605 2022/10/13 05:03:12 - mmengine - INFO - Epoch(train) [45][820/940] lr: 1.0000e-03 eta: 7:22:12 time: 0.5158 data_time: 0.0306 memory: 17006 grad_norm: 4.2991 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5146 loss: 1.5146 2022/10/13 05:03:22 - mmengine - INFO - Epoch(train) [45][840/940] lr: 1.0000e-03 eta: 7:22:01 time: 0.4770 data_time: 0.0307 memory: 17006 grad_norm: 4.2319 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4603 loss: 1.4603 2022/10/13 05:03:32 - mmengine - INFO - Epoch(train) [45][860/940] lr: 1.0000e-03 eta: 7:21:51 time: 0.5248 data_time: 0.0346 memory: 17006 grad_norm: 4.1547 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4974 loss: 1.4974 2022/10/13 05:03:42 - mmengine - INFO - Epoch(train) [45][880/940] lr: 1.0000e-03 eta: 7:21:41 time: 0.5046 data_time: 0.0326 memory: 17006 grad_norm: 4.2980 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3342 loss: 1.3342 2022/10/13 05:03:53 - mmengine - INFO - Epoch(train) [45][900/940] lr: 1.0000e-03 eta: 7:21:31 time: 0.5199 data_time: 0.0288 memory: 17006 grad_norm: 4.2056 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4872 loss: 1.4872 2022/10/13 05:04:02 - mmengine - INFO - Epoch(train) [45][920/940] lr: 1.0000e-03 eta: 7:21:20 time: 0.4699 data_time: 0.0318 memory: 17006 grad_norm: 4.1828 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.5637 loss: 1.5637 2022/10/13 05:04:11 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 05:04:11 - mmengine - INFO - Epoch(train) [45][940/940] lr: 1.0000e-03 eta: 7:21:08 time: 0.4652 data_time: 0.0250 memory: 17006 grad_norm: 4.4050 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.3269 loss: 1.3269 2022/10/13 05:04:11 - mmengine - INFO - Saving checkpoint at 45 epochs 2022/10/13 05:04:25 - mmengine - INFO - Epoch(val) [45][20/78] eta: 0:00:36 time: 0.6231 data_time: 0.5321 memory: 3172 2022/10/13 05:04:33 - mmengine - INFO - Epoch(val) [45][40/78] eta: 0:00:16 time: 0.4273 data_time: 0.3366 memory: 3172 2022/10/13 05:04:45 - mmengine - INFO - Epoch(val) [45][60/78] eta: 0:00:10 time: 0.5843 data_time: 0.4933 memory: 3172 2022/10/13 05:04:54 - mmengine - INFO - Epoch(val) [45][78/78] acc/top1: 0.6666 acc/top5: 0.8669 acc/mean1: 0.6665 2022/10/13 05:05:08 - mmengine - INFO - Epoch(train) [46][20/940] lr: 1.0000e-03 eta: 7:21:02 time: 0.6714 data_time: 0.2646 memory: 17006 grad_norm: 4.2003 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3634 loss: 1.3634 2022/10/13 05:05:17 - mmengine - INFO - Epoch(train) [46][40/940] lr: 1.0000e-03 eta: 7:20:51 time: 0.4735 data_time: 0.0731 memory: 17006 grad_norm: 4.1772 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4618 loss: 1.4618 2022/10/13 05:05:28 - mmengine - INFO - Epoch(train) [46][60/940] lr: 1.0000e-03 eta: 7:20:41 time: 0.5486 data_time: 0.0809 memory: 17006 grad_norm: 4.2312 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4025 loss: 1.4025 2022/10/13 05:05:38 - mmengine - INFO - Epoch(train) [46][80/940] lr: 1.0000e-03 eta: 7:20:30 time: 0.4815 data_time: 0.0293 memory: 17006 grad_norm: 4.3272 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3946 loss: 1.3946 2022/10/13 05:05:49 - mmengine - INFO - Epoch(train) [46][100/940] lr: 1.0000e-03 eta: 7:20:22 time: 0.5745 data_time: 0.0317 memory: 17006 grad_norm: 4.2291 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4878 loss: 1.4878 2022/10/13 05:05:59 - mmengine - INFO - Epoch(train) [46][120/940] lr: 1.0000e-03 eta: 7:20:11 time: 0.4874 data_time: 0.0306 memory: 17006 grad_norm: 4.2583 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4336 loss: 1.4336 2022/10/13 05:06:09 - mmengine - INFO - Epoch(train) [46][140/940] lr: 1.0000e-03 eta: 7:20:00 time: 0.5023 data_time: 0.0437 memory: 17006 grad_norm: 4.2620 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3537 loss: 1.3537 2022/10/13 05:06:19 - mmengine - INFO - Epoch(train) [46][160/940] lr: 1.0000e-03 eta: 7:19:50 time: 0.5007 data_time: 0.0253 memory: 17006 grad_norm: 4.2423 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4774 loss: 1.4774 2022/10/13 05:06:30 - mmengine - INFO - Epoch(train) [46][180/940] lr: 1.0000e-03 eta: 7:19:40 time: 0.5505 data_time: 0.0415 memory: 17006 grad_norm: 4.1519 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1889 loss: 1.1889 2022/10/13 05:06:39 - mmengine - INFO - Epoch(train) [46][200/940] lr: 1.0000e-03 eta: 7:19:29 time: 0.4658 data_time: 0.0250 memory: 17006 grad_norm: 4.2499 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2728 loss: 1.2728 2022/10/13 05:06:50 - mmengine - INFO - Epoch(train) [46][220/940] lr: 1.0000e-03 eta: 7:19:20 time: 0.5427 data_time: 0.0447 memory: 17006 grad_norm: 4.2353 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3323 loss: 1.3323 2022/10/13 05:07:00 - mmengine - INFO - Epoch(train) [46][240/940] lr: 1.0000e-03 eta: 7:19:09 time: 0.4833 data_time: 0.0307 memory: 17006 grad_norm: 4.2763 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.2865 loss: 1.2865 2022/10/13 05:07:10 - mmengine - INFO - Epoch(train) [46][260/940] lr: 1.0000e-03 eta: 7:18:59 time: 0.5184 data_time: 0.0730 memory: 17006 grad_norm: 4.2231 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4039 loss: 1.4039 2022/10/13 05:07:20 - mmengine - INFO - Epoch(train) [46][280/940] lr: 1.0000e-03 eta: 7:18:47 time: 0.4683 data_time: 0.0266 memory: 17006 grad_norm: 4.2367 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4375 loss: 1.4375 2022/10/13 05:07:31 - mmengine - INFO - Epoch(train) [46][300/940] lr: 1.0000e-03 eta: 7:18:38 time: 0.5603 data_time: 0.0367 memory: 17006 grad_norm: 4.3004 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4498 loss: 1.4498 2022/10/13 05:07:41 - mmengine - INFO - Epoch(train) [46][320/940] lr: 1.0000e-03 eta: 7:18:27 time: 0.4909 data_time: 0.0244 memory: 17006 grad_norm: 4.3431 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5713 loss: 1.5713 2022/10/13 05:07:52 - mmengine - INFO - Epoch(train) [46][340/940] lr: 1.0000e-03 eta: 7:18:19 time: 0.5761 data_time: 0.0395 memory: 17006 grad_norm: 4.2096 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4251 loss: 1.4251 2022/10/13 05:08:01 - mmengine - INFO - Epoch(train) [46][360/940] lr: 1.0000e-03 eta: 7:18:07 time: 0.4635 data_time: 0.0295 memory: 17006 grad_norm: 4.2364 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4607 loss: 1.4607 2022/10/13 05:08:12 - mmengine - INFO - Epoch(train) [46][380/940] lr: 1.0000e-03 eta: 7:17:58 time: 0.5434 data_time: 0.0396 memory: 17006 grad_norm: 4.2497 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5102 loss: 1.5102 2022/10/13 05:08:22 - mmengine - INFO - Epoch(train) [46][400/940] lr: 1.0000e-03 eta: 7:17:47 time: 0.4872 data_time: 0.0310 memory: 17006 grad_norm: 4.2457 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.4154 loss: 1.4154 2022/10/13 05:08:34 - mmengine - INFO - Epoch(train) [46][420/940] lr: 1.0000e-03 eta: 7:17:38 time: 0.5765 data_time: 0.0325 memory: 17006 grad_norm: 4.1583 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.4339 loss: 1.4339 2022/10/13 05:08:43 - mmengine - INFO - Epoch(train) [46][440/940] lr: 1.0000e-03 eta: 7:17:27 time: 0.4861 data_time: 0.0368 memory: 17006 grad_norm: 4.2232 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5345 loss: 1.5345 2022/10/13 05:08:54 - mmengine - INFO - Epoch(train) [46][460/940] lr: 1.0000e-03 eta: 7:17:18 time: 0.5370 data_time: 0.0314 memory: 17006 grad_norm: 4.3402 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3667 loss: 1.3667 2022/10/13 05:09:04 - mmengine - INFO - Epoch(train) [46][480/940] lr: 1.0000e-03 eta: 7:17:07 time: 0.4752 data_time: 0.0369 memory: 17006 grad_norm: 4.2426 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4461 loss: 1.4461 2022/10/13 05:09:14 - mmengine - INFO - Epoch(train) [46][500/940] lr: 1.0000e-03 eta: 7:16:56 time: 0.5022 data_time: 0.0308 memory: 17006 grad_norm: 4.3375 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.4050 loss: 1.4050 2022/10/13 05:09:23 - mmengine - INFO - Epoch(train) [46][520/940] lr: 1.0000e-03 eta: 7:16:45 time: 0.4513 data_time: 0.0344 memory: 17006 grad_norm: 4.2112 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4091 loss: 1.4091 2022/10/13 05:09:33 - mmengine - INFO - Epoch(train) [46][540/940] lr: 1.0000e-03 eta: 7:16:35 time: 0.5428 data_time: 0.0335 memory: 17006 grad_norm: 4.2623 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2831 loss: 1.2831 2022/10/13 05:09:43 - mmengine - INFO - Epoch(train) [46][560/940] lr: 1.0000e-03 eta: 7:16:24 time: 0.4752 data_time: 0.0304 memory: 17006 grad_norm: 4.2327 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4094 loss: 1.4094 2022/10/13 05:09:54 - mmengine - INFO - Epoch(train) [46][580/940] lr: 1.0000e-03 eta: 7:16:14 time: 0.5358 data_time: 0.0326 memory: 17006 grad_norm: 4.3060 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5466 loss: 1.5466 2022/10/13 05:10:03 - mmengine - INFO - Epoch(train) [46][600/940] lr: 1.0000e-03 eta: 7:16:03 time: 0.4653 data_time: 0.0253 memory: 17006 grad_norm: 4.3309 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4270 loss: 1.4270 2022/10/13 05:10:13 - mmengine - INFO - Epoch(train) [46][620/940] lr: 1.0000e-03 eta: 7:15:53 time: 0.5196 data_time: 0.0326 memory: 17006 grad_norm: 4.3026 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4857 loss: 1.4857 2022/10/13 05:10:23 - mmengine - INFO - Epoch(train) [46][640/940] lr: 1.0000e-03 eta: 7:15:42 time: 0.4840 data_time: 0.0294 memory: 17006 grad_norm: 4.2862 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3872 loss: 1.3872 2022/10/13 05:10:34 - mmengine - INFO - Epoch(train) [46][660/940] lr: 1.0000e-03 eta: 7:15:33 time: 0.5529 data_time: 0.0335 memory: 17006 grad_norm: 4.3163 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4292 loss: 1.4292 2022/10/13 05:10:44 - mmengine - INFO - Epoch(train) [46][680/940] lr: 1.0000e-03 eta: 7:15:22 time: 0.4812 data_time: 0.0244 memory: 17006 grad_norm: 4.2196 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.3807 loss: 1.3807 2022/10/13 05:10:54 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 05:10:54 - mmengine - INFO - Epoch(train) [46][700/940] lr: 1.0000e-03 eta: 7:15:12 time: 0.5166 data_time: 0.0389 memory: 17006 grad_norm: 4.3036 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4738 loss: 1.4738 2022/10/13 05:11:04 - mmengine - INFO - Epoch(train) [46][720/940] lr: 1.0000e-03 eta: 7:15:01 time: 0.4860 data_time: 0.0269 memory: 17006 grad_norm: 4.2244 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4923 loss: 1.4923 2022/10/13 05:11:14 - mmengine - INFO - Epoch(train) [46][740/940] lr: 1.0000e-03 eta: 7:14:50 time: 0.5093 data_time: 0.0364 memory: 17006 grad_norm: 4.3584 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.4495 loss: 1.4495 2022/10/13 05:11:25 - mmengine - INFO - Epoch(train) [46][760/940] lr: 1.0000e-03 eta: 7:14:41 time: 0.5339 data_time: 0.0286 memory: 17006 grad_norm: 4.2702 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.4583 loss: 1.4583 2022/10/13 05:11:35 - mmengine - INFO - Epoch(train) [46][780/940] lr: 1.0000e-03 eta: 7:14:31 time: 0.5209 data_time: 0.0318 memory: 17006 grad_norm: 4.3287 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.4304 loss: 1.4304 2022/10/13 05:11:44 - mmengine - INFO - Epoch(train) [46][800/940] lr: 1.0000e-03 eta: 7:14:19 time: 0.4570 data_time: 0.0275 memory: 17006 grad_norm: 4.3826 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5502 loss: 1.5502 2022/10/13 05:11:55 - mmengine - INFO - Epoch(train) [46][820/940] lr: 1.0000e-03 eta: 7:14:09 time: 0.5308 data_time: 0.0363 memory: 17006 grad_norm: 4.3298 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.3711 loss: 1.3711 2022/10/13 05:12:04 - mmengine - INFO - Epoch(train) [46][840/940] lr: 1.0000e-03 eta: 7:13:57 time: 0.4424 data_time: 0.0304 memory: 17006 grad_norm: 4.3139 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4549 loss: 1.4549 2022/10/13 05:12:15 - mmengine - INFO - Epoch(train) [46][860/940] lr: 1.0000e-03 eta: 7:13:48 time: 0.5554 data_time: 0.0385 memory: 17006 grad_norm: 4.3627 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.4915 loss: 1.4915 2022/10/13 05:12:24 - mmengine - INFO - Epoch(train) [46][880/940] lr: 1.0000e-03 eta: 7:13:37 time: 0.4521 data_time: 0.0278 memory: 17006 grad_norm: 4.3693 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4453 loss: 1.4453 2022/10/13 05:12:34 - mmengine - INFO - Epoch(train) [46][900/940] lr: 1.0000e-03 eta: 7:13:27 time: 0.5246 data_time: 0.0361 memory: 17006 grad_norm: 4.2667 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3491 loss: 1.3491 2022/10/13 05:12:44 - mmengine - INFO - Epoch(train) [46][920/940] lr: 1.0000e-03 eta: 7:13:16 time: 0.4765 data_time: 0.0308 memory: 17006 grad_norm: 4.2450 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4365 loss: 1.4365 2022/10/13 05:12:53 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 05:12:53 - mmengine - INFO - Epoch(train) [46][940/940] lr: 1.0000e-03 eta: 7:13:04 time: 0.4774 data_time: 0.0243 memory: 17006 grad_norm: 4.4596 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.4202 loss: 1.4202 2022/10/13 05:13:06 - mmengine - INFO - Epoch(val) [46][20/78] eta: 0:00:36 time: 0.6325 data_time: 0.5387 memory: 3172 2022/10/13 05:13:15 - mmengine - INFO - Epoch(val) [46][40/78] eta: 0:00:16 time: 0.4398 data_time: 0.3494 memory: 3172 2022/10/13 05:13:26 - mmengine - INFO - Epoch(val) [46][60/78] eta: 0:00:10 time: 0.5646 data_time: 0.4743 memory: 3172 2022/10/13 05:13:36 - mmengine - INFO - Epoch(val) [46][78/78] acc/top1: 0.6700 acc/top5: 0.8670 acc/mean1: 0.6699 2022/10/13 05:13:36 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_44.pth is removed 2022/10/13 05:13:36 - mmengine - INFO - The best checkpoint with 0.6700 acc/top1 at 46 epoch is saved to best_acc/top1_epoch_46.pth. 2022/10/13 05:13:50 - mmengine - INFO - Epoch(train) [47][20/940] lr: 1.0000e-03 eta: 7:12:58 time: 0.6562 data_time: 0.3271 memory: 17006 grad_norm: 4.2794 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4679 loss: 1.4679 2022/10/13 05:14:00 - mmengine - INFO - Epoch(train) [47][40/940] lr: 1.0000e-03 eta: 7:12:47 time: 0.5039 data_time: 0.1184 memory: 17006 grad_norm: 4.2705 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4159 loss: 1.4159 2022/10/13 05:14:11 - mmengine - INFO - Epoch(train) [47][60/940] lr: 1.0000e-03 eta: 7:12:38 time: 0.5449 data_time: 0.1415 memory: 17006 grad_norm: 4.3188 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.4483 loss: 1.4483 2022/10/13 05:14:20 - mmengine - INFO - Epoch(train) [47][80/940] lr: 1.0000e-03 eta: 7:12:27 time: 0.4824 data_time: 0.0852 memory: 17006 grad_norm: 4.2634 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.4479 loss: 1.4479 2022/10/13 05:14:31 - mmengine - INFO - Epoch(train) [47][100/940] lr: 1.0000e-03 eta: 7:12:17 time: 0.5335 data_time: 0.1452 memory: 17006 grad_norm: 4.2661 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4330 loss: 1.4330 2022/10/13 05:14:40 - mmengine - INFO - Epoch(train) [47][120/940] lr: 1.0000e-03 eta: 7:12:06 time: 0.4695 data_time: 0.0824 memory: 17006 grad_norm: 4.2930 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4306 loss: 1.4306 2022/10/13 05:14:51 - mmengine - INFO - Epoch(train) [47][140/940] lr: 1.0000e-03 eta: 7:11:56 time: 0.5257 data_time: 0.1067 memory: 17006 grad_norm: 4.2107 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3877 loss: 1.3877 2022/10/13 05:15:01 - mmengine - INFO - Epoch(train) [47][160/940] lr: 1.0000e-03 eta: 7:11:45 time: 0.5016 data_time: 0.0842 memory: 17006 grad_norm: 4.3347 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.4629 loss: 1.4629 2022/10/13 05:15:12 - mmengine - INFO - Epoch(train) [47][180/940] lr: 1.0000e-03 eta: 7:11:37 time: 0.5778 data_time: 0.0510 memory: 17006 grad_norm: 4.2269 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4293 loss: 1.4293 2022/10/13 05:15:22 - mmengine - INFO - Epoch(train) [47][200/940] lr: 1.0000e-03 eta: 7:11:26 time: 0.4878 data_time: 0.0312 memory: 17006 grad_norm: 4.2406 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4429 loss: 1.4429 2022/10/13 05:15:33 - mmengine - INFO - Epoch(train) [47][220/940] lr: 1.0000e-03 eta: 7:11:17 time: 0.5588 data_time: 0.0338 memory: 17006 grad_norm: 4.3115 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.3838 loss: 1.3838 2022/10/13 05:15:43 - mmengine - INFO - Epoch(train) [47][240/940] lr: 1.0000e-03 eta: 7:11:06 time: 0.4825 data_time: 0.0302 memory: 17006 grad_norm: 4.2782 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4754 loss: 1.4754 2022/10/13 05:15:53 - mmengine - INFO - Epoch(train) [47][260/940] lr: 1.0000e-03 eta: 7:10:55 time: 0.4917 data_time: 0.0343 memory: 17006 grad_norm: 4.2893 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3919 loss: 1.3919 2022/10/13 05:16:03 - mmengine - INFO - Epoch(train) [47][280/940] lr: 1.0000e-03 eta: 7:10:45 time: 0.5108 data_time: 0.0333 memory: 17006 grad_norm: 4.3549 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3782 loss: 1.3782 2022/10/13 05:16:13 - mmengine - INFO - Epoch(train) [47][300/940] lr: 1.0000e-03 eta: 7:10:34 time: 0.5044 data_time: 0.0293 memory: 17006 grad_norm: 4.3098 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4443 loss: 1.4443 2022/10/13 05:16:22 - mmengine - INFO - Epoch(train) [47][320/940] lr: 1.0000e-03 eta: 7:10:22 time: 0.4244 data_time: 0.0469 memory: 17006 grad_norm: 4.2238 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2979 loss: 1.2979 2022/10/13 05:16:33 - mmengine - INFO - Epoch(train) [47][340/940] lr: 1.0000e-03 eta: 7:10:13 time: 0.5737 data_time: 0.0307 memory: 17006 grad_norm: 4.3219 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4769 loss: 1.4769 2022/10/13 05:16:43 - mmengine - INFO - Epoch(train) [47][360/940] lr: 1.0000e-03 eta: 7:10:03 time: 0.4857 data_time: 0.0296 memory: 17006 grad_norm: 4.2366 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3708 loss: 1.3708 2022/10/13 05:16:53 - mmengine - INFO - Epoch(train) [47][380/940] lr: 1.0000e-03 eta: 7:09:52 time: 0.4851 data_time: 0.0316 memory: 17006 grad_norm: 4.2801 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5517 loss: 1.5517 2022/10/13 05:17:02 - mmengine - INFO - Epoch(train) [47][400/940] lr: 1.0000e-03 eta: 7:09:40 time: 0.4522 data_time: 0.0359 memory: 17006 grad_norm: 4.2983 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.5462 loss: 1.5462 2022/10/13 05:17:12 - mmengine - INFO - Epoch(train) [47][420/940] lr: 1.0000e-03 eta: 7:09:30 time: 0.5392 data_time: 0.0298 memory: 17006 grad_norm: 4.2453 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3793 loss: 1.3793 2022/10/13 05:17:23 - mmengine - INFO - Epoch(train) [47][440/940] lr: 1.0000e-03 eta: 7:09:21 time: 0.5430 data_time: 0.0326 memory: 17006 grad_norm: 4.2930 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4557 loss: 1.4557 2022/10/13 05:17:33 - mmengine - INFO - Epoch(train) [47][460/940] lr: 1.0000e-03 eta: 7:09:10 time: 0.4688 data_time: 0.0294 memory: 17006 grad_norm: 4.3282 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.4281 loss: 1.4281 2022/10/13 05:17:42 - mmengine - INFO - Epoch(train) [47][480/940] lr: 1.0000e-03 eta: 7:08:59 time: 0.4904 data_time: 0.0323 memory: 17006 grad_norm: 4.3288 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5530 loss: 1.5530 2022/10/13 05:17:53 - mmengine - INFO - Epoch(train) [47][500/940] lr: 1.0000e-03 eta: 7:08:49 time: 0.5119 data_time: 0.0328 memory: 17006 grad_norm: 4.2457 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2758 loss: 1.2758 2022/10/13 05:18:03 - mmengine - INFO - Epoch(train) [47][520/940] lr: 1.0000e-03 eta: 7:08:38 time: 0.5035 data_time: 0.0346 memory: 17006 grad_norm: 4.2237 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3190 loss: 1.3190 2022/10/13 05:18:13 - mmengine - INFO - Epoch(train) [47][540/940] lr: 1.0000e-03 eta: 7:08:29 time: 0.5378 data_time: 0.0348 memory: 17006 grad_norm: 4.2662 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.4535 loss: 1.4535 2022/10/13 05:18:23 - mmengine - INFO - Epoch(train) [47][560/940] lr: 1.0000e-03 eta: 7:08:17 time: 0.4629 data_time: 0.0351 memory: 17006 grad_norm: 4.2633 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3795 loss: 1.3795 2022/10/13 05:18:33 - mmengine - INFO - Epoch(train) [47][580/940] lr: 1.0000e-03 eta: 7:08:07 time: 0.5033 data_time: 0.0307 memory: 17006 grad_norm: 4.3133 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4459 loss: 1.4459 2022/10/13 05:18:43 - mmengine - INFO - Epoch(train) [47][600/940] lr: 1.0000e-03 eta: 7:07:56 time: 0.4982 data_time: 0.0360 memory: 17006 grad_norm: 4.3222 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4794 loss: 1.4794 2022/10/13 05:18:53 - mmengine - INFO - Epoch(train) [47][620/940] lr: 1.0000e-03 eta: 7:07:46 time: 0.5206 data_time: 0.0297 memory: 17006 grad_norm: 4.2234 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4660 loss: 1.4660 2022/10/13 05:19:03 - mmengine - INFO - Epoch(train) [47][640/940] lr: 1.0000e-03 eta: 7:07:36 time: 0.5148 data_time: 0.0307 memory: 17006 grad_norm: 4.2801 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4793 loss: 1.4793 2022/10/13 05:19:14 - mmengine - INFO - Epoch(train) [47][660/940] lr: 1.0000e-03 eta: 7:07:26 time: 0.5238 data_time: 0.0436 memory: 17006 grad_norm: 4.2363 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5195 loss: 1.5195 2022/10/13 05:19:24 - mmengine - INFO - Epoch(train) [47][680/940] lr: 1.0000e-03 eta: 7:07:16 time: 0.4981 data_time: 0.0339 memory: 17006 grad_norm: 4.4599 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4805 loss: 1.4805 2022/10/13 05:19:34 - mmengine - INFO - Epoch(train) [47][700/940] lr: 1.0000e-03 eta: 7:07:06 time: 0.5257 data_time: 0.0285 memory: 17006 grad_norm: 4.2942 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4296 loss: 1.4296 2022/10/13 05:19:44 - mmengine - INFO - Epoch(train) [47][720/940] lr: 1.0000e-03 eta: 7:06:55 time: 0.4973 data_time: 0.0341 memory: 17006 grad_norm: 4.3417 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.4125 loss: 1.4125 2022/10/13 05:19:56 - mmengine - INFO - Epoch(train) [47][740/940] lr: 1.0000e-03 eta: 7:06:46 time: 0.5666 data_time: 0.0293 memory: 17006 grad_norm: 4.2814 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4131 loss: 1.4131 2022/10/13 05:20:05 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 05:20:05 - mmengine - INFO - Epoch(train) [47][760/940] lr: 1.0000e-03 eta: 7:06:35 time: 0.4616 data_time: 0.0291 memory: 17006 grad_norm: 4.1372 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2936 loss: 1.2936 2022/10/13 05:20:15 - mmengine - INFO - Epoch(train) [47][780/940] lr: 1.0000e-03 eta: 7:06:25 time: 0.5264 data_time: 0.0329 memory: 17006 grad_norm: 4.3025 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5278 loss: 1.5278 2022/10/13 05:20:24 - mmengine - INFO - Epoch(train) [47][800/940] lr: 1.0000e-03 eta: 7:06:13 time: 0.4432 data_time: 0.0427 memory: 17006 grad_norm: 4.2605 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3547 loss: 1.3547 2022/10/13 05:20:34 - mmengine - INFO - Epoch(train) [47][820/940] lr: 1.0000e-03 eta: 7:06:02 time: 0.4905 data_time: 0.0482 memory: 17006 grad_norm: 4.3150 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3192 loss: 1.3192 2022/10/13 05:20:44 - mmengine - INFO - Epoch(train) [47][840/940] lr: 1.0000e-03 eta: 7:05:51 time: 0.4826 data_time: 0.0332 memory: 17006 grad_norm: 4.2425 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2517 loss: 1.2517 2022/10/13 05:20:54 - mmengine - INFO - Epoch(train) [47][860/940] lr: 1.0000e-03 eta: 7:05:41 time: 0.5270 data_time: 0.0333 memory: 17006 grad_norm: 4.3252 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4164 loss: 1.4164 2022/10/13 05:21:04 - mmengine - INFO - Epoch(train) [47][880/940] lr: 1.0000e-03 eta: 7:05:31 time: 0.4854 data_time: 0.0283 memory: 17006 grad_norm: 4.2968 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3684 loss: 1.3684 2022/10/13 05:21:15 - mmengine - INFO - Epoch(train) [47][900/940] lr: 1.0000e-03 eta: 7:05:21 time: 0.5352 data_time: 0.0327 memory: 17006 grad_norm: 4.2860 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4922 loss: 1.4922 2022/10/13 05:21:24 - mmengine - INFO - Epoch(train) [47][920/940] lr: 1.0000e-03 eta: 7:05:10 time: 0.4743 data_time: 0.0291 memory: 17006 grad_norm: 4.2664 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.4630 loss: 1.4630 2022/10/13 05:21:34 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 05:21:34 - mmengine - INFO - Epoch(train) [47][940/940] lr: 1.0000e-03 eta: 7:04:59 time: 0.5044 data_time: 0.0261 memory: 17006 grad_norm: 4.5303 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.3797 loss: 1.3797 2022/10/13 05:21:47 - mmengine - INFO - Epoch(val) [47][20/78] eta: 0:00:36 time: 0.6275 data_time: 0.5311 memory: 3172 2022/10/13 05:21:56 - mmengine - INFO - Epoch(val) [47][40/78] eta: 0:00:16 time: 0.4344 data_time: 0.3420 memory: 3172 2022/10/13 05:22:07 - mmengine - INFO - Epoch(val) [47][60/78] eta: 0:00:10 time: 0.5750 data_time: 0.4820 memory: 3172 2022/10/13 05:22:17 - mmengine - INFO - Epoch(val) [47][78/78] acc/top1: 0.6693 acc/top5: 0.8673 acc/mean1: 0.6692 2022/10/13 05:22:31 - mmengine - INFO - Epoch(train) [48][20/940] lr: 1.0000e-03 eta: 7:04:53 time: 0.6837 data_time: 0.3144 memory: 17006 grad_norm: 4.3360 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3902 loss: 1.3902 2022/10/13 05:22:40 - mmengine - INFO - Epoch(train) [48][40/940] lr: 1.0000e-03 eta: 7:04:42 time: 0.4774 data_time: 0.1042 memory: 17006 grad_norm: 4.3212 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3627 loss: 1.3627 2022/10/13 05:22:52 - mmengine - INFO - Epoch(train) [48][60/940] lr: 1.0000e-03 eta: 7:04:33 time: 0.5737 data_time: 0.0810 memory: 17006 grad_norm: 4.2812 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.5119 loss: 1.5119 2022/10/13 05:23:01 - mmengine - INFO - Epoch(train) [48][80/940] lr: 1.0000e-03 eta: 7:04:22 time: 0.4846 data_time: 0.0267 memory: 17006 grad_norm: 4.1920 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1489 loss: 1.1489 2022/10/13 05:23:13 - mmengine - INFO - Epoch(train) [48][100/940] lr: 1.0000e-03 eta: 7:04:13 time: 0.5733 data_time: 0.0285 memory: 17006 grad_norm: 4.3346 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3846 loss: 1.3846 2022/10/13 05:23:22 - mmengine - INFO - Epoch(train) [48][120/940] lr: 1.0000e-03 eta: 7:04:02 time: 0.4718 data_time: 0.0310 memory: 17006 grad_norm: 4.2343 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2574 loss: 1.2574 2022/10/13 05:23:33 - mmengine - INFO - Epoch(train) [48][140/940] lr: 1.0000e-03 eta: 7:03:53 time: 0.5486 data_time: 0.0293 memory: 17006 grad_norm: 4.1800 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3347 loss: 1.3347 2022/10/13 05:23:42 - mmengine - INFO - Epoch(train) [48][160/940] lr: 1.0000e-03 eta: 7:03:41 time: 0.4557 data_time: 0.0306 memory: 17006 grad_norm: 4.3877 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.3810 loss: 1.3810 2022/10/13 05:23:53 - mmengine - INFO - Epoch(train) [48][180/940] lr: 1.0000e-03 eta: 7:03:31 time: 0.5172 data_time: 0.0319 memory: 17006 grad_norm: 4.3510 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3702 loss: 1.3702 2022/10/13 05:24:03 - mmengine - INFO - Epoch(train) [48][200/940] lr: 1.0000e-03 eta: 7:03:21 time: 0.4915 data_time: 0.0340 memory: 17006 grad_norm: 4.2754 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3454 loss: 1.3454 2022/10/13 05:24:13 - mmengine - INFO - Epoch(train) [48][220/940] lr: 1.0000e-03 eta: 7:03:11 time: 0.5365 data_time: 0.0365 memory: 17006 grad_norm: 4.3377 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4594 loss: 1.4594 2022/10/13 05:24:23 - mmengine - INFO - Epoch(train) [48][240/940] lr: 1.0000e-03 eta: 7:03:00 time: 0.4751 data_time: 0.0320 memory: 17006 grad_norm: 4.3042 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4289 loss: 1.4289 2022/10/13 05:24:34 - mmengine - INFO - Epoch(train) [48][260/940] lr: 1.0000e-03 eta: 7:02:51 time: 0.5517 data_time: 0.0324 memory: 17006 grad_norm: 4.2116 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.4443 loss: 1.4443 2022/10/13 05:24:43 - mmengine - INFO - Epoch(train) [48][280/940] lr: 1.0000e-03 eta: 7:02:39 time: 0.4381 data_time: 0.0346 memory: 17006 grad_norm: 4.3062 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.4709 loss: 1.4709 2022/10/13 05:24:54 - mmengine - INFO - Epoch(train) [48][300/940] lr: 1.0000e-03 eta: 7:02:29 time: 0.5534 data_time: 0.0326 memory: 17006 grad_norm: 4.3116 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3984 loss: 1.3984 2022/10/13 05:25:04 - mmengine - INFO - Epoch(train) [48][320/940] lr: 1.0000e-03 eta: 7:02:19 time: 0.5197 data_time: 0.0312 memory: 17006 grad_norm: 4.3008 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4122 loss: 1.4122 2022/10/13 05:25:15 - mmengine - INFO - Epoch(train) [48][340/940] lr: 1.0000e-03 eta: 7:02:10 time: 0.5404 data_time: 0.0353 memory: 17006 grad_norm: 4.3297 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4237 loss: 1.4237 2022/10/13 05:25:24 - mmengine - INFO - Epoch(train) [48][360/940] lr: 1.0000e-03 eta: 7:01:59 time: 0.4825 data_time: 0.0318 memory: 17006 grad_norm: 4.3158 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.2799 loss: 1.2799 2022/10/13 05:25:34 - mmengine - INFO - Epoch(train) [48][380/940] lr: 1.0000e-03 eta: 7:01:48 time: 0.4928 data_time: 0.0309 memory: 17006 grad_norm: 4.3462 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3950 loss: 1.3950 2022/10/13 05:25:45 - mmengine - INFO - Epoch(train) [48][400/940] lr: 1.0000e-03 eta: 7:01:38 time: 0.5209 data_time: 0.0321 memory: 17006 grad_norm: 4.2704 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3286 loss: 1.3286 2022/10/13 05:25:55 - mmengine - INFO - Epoch(train) [48][420/940] lr: 1.0000e-03 eta: 7:01:28 time: 0.5056 data_time: 0.0322 memory: 17006 grad_norm: 4.2619 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3624 loss: 1.3624 2022/10/13 05:26:06 - mmengine - INFO - Epoch(train) [48][440/940] lr: 1.0000e-03 eta: 7:01:19 time: 0.5714 data_time: 0.0315 memory: 17006 grad_norm: 4.3279 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4772 loss: 1.4772 2022/10/13 05:26:15 - mmengine - INFO - Epoch(train) [48][460/940] lr: 1.0000e-03 eta: 7:01:07 time: 0.4308 data_time: 0.0315 memory: 17006 grad_norm: 4.2648 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4212 loss: 1.4212 2022/10/13 05:26:26 - mmengine - INFO - Epoch(train) [48][480/940] lr: 1.0000e-03 eta: 7:00:57 time: 0.5306 data_time: 0.0320 memory: 17006 grad_norm: 4.3404 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4081 loss: 1.4081 2022/10/13 05:26:35 - mmengine - INFO - Epoch(train) [48][500/940] lr: 1.0000e-03 eta: 7:00:45 time: 0.4560 data_time: 0.0279 memory: 17006 grad_norm: 4.3520 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.4790 loss: 1.4790 2022/10/13 05:26:45 - mmengine - INFO - Epoch(train) [48][520/940] lr: 1.0000e-03 eta: 7:00:35 time: 0.5142 data_time: 0.0348 memory: 17006 grad_norm: 4.2895 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.3770 loss: 1.3770 2022/10/13 05:26:55 - mmengine - INFO - Epoch(train) [48][540/940] lr: 1.0000e-03 eta: 7:00:24 time: 0.4782 data_time: 0.0336 memory: 17006 grad_norm: 4.3922 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.4688 loss: 1.4688 2022/10/13 05:27:05 - mmengine - INFO - Epoch(train) [48][560/940] lr: 1.0000e-03 eta: 7:00:15 time: 0.5396 data_time: 0.0308 memory: 17006 grad_norm: 4.2624 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3855 loss: 1.3855 2022/10/13 05:27:15 - mmengine - INFO - Epoch(train) [48][580/940] lr: 1.0000e-03 eta: 7:00:04 time: 0.4842 data_time: 0.0324 memory: 17006 grad_norm: 4.3958 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4134 loss: 1.4134 2022/10/13 05:27:25 - mmengine - INFO - Epoch(train) [48][600/940] lr: 1.0000e-03 eta: 6:59:53 time: 0.4849 data_time: 0.0367 memory: 17006 grad_norm: 4.3526 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.3263 loss: 1.3263 2022/10/13 05:27:36 - mmengine - INFO - Epoch(train) [48][620/940] lr: 1.0000e-03 eta: 6:59:43 time: 0.5431 data_time: 0.0336 memory: 17006 grad_norm: 4.3488 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.5544 loss: 1.5544 2022/10/13 05:27:46 - mmengine - INFO - Epoch(train) [48][640/940] lr: 1.0000e-03 eta: 6:59:33 time: 0.5030 data_time: 0.0363 memory: 17006 grad_norm: 4.3386 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.4322 loss: 1.4322 2022/10/13 05:27:56 - mmengine - INFO - Epoch(train) [48][660/940] lr: 1.0000e-03 eta: 6:59:23 time: 0.5261 data_time: 0.0316 memory: 17006 grad_norm: 4.3402 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3501 loss: 1.3501 2022/10/13 05:28:06 - mmengine - INFO - Epoch(train) [48][680/940] lr: 1.0000e-03 eta: 6:59:13 time: 0.4975 data_time: 0.0349 memory: 17006 grad_norm: 4.3253 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3712 loss: 1.3712 2022/10/13 05:28:17 - mmengine - INFO - Epoch(train) [48][700/940] lr: 1.0000e-03 eta: 6:59:03 time: 0.5508 data_time: 0.0398 memory: 17006 grad_norm: 4.3346 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.4883 loss: 1.4883 2022/10/13 05:28:26 - mmengine - INFO - Epoch(train) [48][720/940] lr: 1.0000e-03 eta: 6:58:51 time: 0.4386 data_time: 0.0319 memory: 17006 grad_norm: 4.3742 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5542 loss: 1.5542 2022/10/13 05:28:37 - mmengine - INFO - Epoch(train) [48][740/940] lr: 1.0000e-03 eta: 6:58:42 time: 0.5445 data_time: 0.0329 memory: 17006 grad_norm: 4.3174 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3322 loss: 1.3322 2022/10/13 05:28:46 - mmengine - INFO - Epoch(train) [48][760/940] lr: 1.0000e-03 eta: 6:58:31 time: 0.4738 data_time: 0.0356 memory: 17006 grad_norm: 4.2813 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5036 loss: 1.5036 2022/10/13 05:28:57 - mmengine - INFO - Epoch(train) [48][780/940] lr: 1.0000e-03 eta: 6:58:21 time: 0.5341 data_time: 0.0270 memory: 17006 grad_norm: 4.3406 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4771 loss: 1.4771 2022/10/13 05:29:07 - mmengine - INFO - Epoch(train) [48][800/940] lr: 1.0000e-03 eta: 6:58:11 time: 0.5124 data_time: 0.0379 memory: 17006 grad_norm: 4.3647 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4808 loss: 1.4808 2022/10/13 05:29:17 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 05:29:17 - mmengine - INFO - Epoch(train) [48][820/940] lr: 1.0000e-03 eta: 6:58:00 time: 0.4965 data_time: 0.0309 memory: 17006 grad_norm: 4.3876 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.4326 loss: 1.4326 2022/10/13 05:29:27 - mmengine - INFO - Epoch(train) [48][840/940] lr: 1.0000e-03 eta: 6:57:49 time: 0.4795 data_time: 0.0369 memory: 17006 grad_norm: 4.3392 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3233 loss: 1.3233 2022/10/13 05:29:38 - mmengine - INFO - Epoch(train) [48][860/940] lr: 1.0000e-03 eta: 6:57:40 time: 0.5443 data_time: 0.0303 memory: 17006 grad_norm: 4.3558 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.3907 loss: 1.3907 2022/10/13 05:29:47 - mmengine - INFO - Epoch(train) [48][880/940] lr: 1.0000e-03 eta: 6:57:28 time: 0.4565 data_time: 0.0304 memory: 17006 grad_norm: 4.2525 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5570 loss: 1.5570 2022/10/13 05:29:58 - mmengine - INFO - Epoch(train) [48][900/940] lr: 1.0000e-03 eta: 6:57:19 time: 0.5645 data_time: 0.0337 memory: 17006 grad_norm: 4.3285 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4222 loss: 1.4222 2022/10/13 05:30:08 - mmengine - INFO - Epoch(train) [48][920/940] lr: 1.0000e-03 eta: 6:57:09 time: 0.5089 data_time: 0.0314 memory: 17006 grad_norm: 4.2653 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3473 loss: 1.3473 2022/10/13 05:30:17 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 05:30:17 - mmengine - INFO - Epoch(train) [48][940/940] lr: 1.0000e-03 eta: 6:56:57 time: 0.4413 data_time: 0.0251 memory: 17006 grad_norm: 4.5662 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.3186 loss: 1.3186 2022/10/13 05:30:17 - mmengine - INFO - Saving checkpoint at 48 epochs 2022/10/13 05:30:30 - mmengine - INFO - Epoch(val) [48][20/78] eta: 0:00:36 time: 0.6241 data_time: 0.5328 memory: 3172 2022/10/13 05:30:39 - mmengine - INFO - Epoch(val) [48][40/78] eta: 0:00:16 time: 0.4255 data_time: 0.3327 memory: 3172 2022/10/13 05:30:50 - mmengine - INFO - Epoch(val) [48][60/78] eta: 0:00:10 time: 0.5812 data_time: 0.4900 memory: 3172 2022/10/13 05:31:00 - mmengine - INFO - Epoch(val) [48][78/78] acc/top1: 0.6706 acc/top5: 0.8670 acc/mean1: 0.6705 2022/10/13 05:31:00 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_46.pth is removed 2022/10/13 05:31:00 - mmengine - INFO - The best checkpoint with 0.6706 acc/top1 at 48 epoch is saved to best_acc/top1_epoch_48.pth. 2022/10/13 05:31:14 - mmengine - INFO - Epoch(train) [49][20/940] lr: 1.0000e-03 eta: 6:56:51 time: 0.7142 data_time: 0.3992 memory: 17006 grad_norm: 4.3071 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4435 loss: 1.4435 2022/10/13 05:31:24 - mmengine - INFO - Epoch(train) [49][40/940] lr: 1.0000e-03 eta: 6:56:40 time: 0.4564 data_time: 0.1511 memory: 17006 grad_norm: 4.3688 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4530 loss: 1.4530 2022/10/13 05:31:34 - mmengine - INFO - Epoch(train) [49][60/940] lr: 1.0000e-03 eta: 6:56:30 time: 0.5268 data_time: 0.1798 memory: 17006 grad_norm: 4.3371 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3458 loss: 1.3458 2022/10/13 05:31:43 - mmengine - INFO - Epoch(train) [49][80/940] lr: 1.0000e-03 eta: 6:56:18 time: 0.4594 data_time: 0.0946 memory: 17006 grad_norm: 4.2493 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5942 loss: 1.5942 2022/10/13 05:31:55 - mmengine - INFO - Epoch(train) [49][100/940] lr: 1.0000e-03 eta: 6:56:09 time: 0.5686 data_time: 0.1920 memory: 17006 grad_norm: 4.3287 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3853 loss: 1.3853 2022/10/13 05:32:04 - mmengine - INFO - Epoch(train) [49][120/940] lr: 1.0000e-03 eta: 6:55:59 time: 0.4852 data_time: 0.1648 memory: 17006 grad_norm: 4.2238 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3072 loss: 1.3072 2022/10/13 05:32:15 - mmengine - INFO - Epoch(train) [49][140/940] lr: 1.0000e-03 eta: 6:55:49 time: 0.5416 data_time: 0.0967 memory: 17006 grad_norm: 4.2798 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4101 loss: 1.4101 2022/10/13 05:32:24 - mmengine - INFO - Epoch(train) [49][160/940] lr: 1.0000e-03 eta: 6:55:38 time: 0.4573 data_time: 0.0384 memory: 17006 grad_norm: 4.3908 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.4785 loss: 1.4785 2022/10/13 05:32:36 - mmengine - INFO - Epoch(train) [49][180/940] lr: 1.0000e-03 eta: 6:55:29 time: 0.5632 data_time: 0.0384 memory: 17006 grad_norm: 4.2634 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.4397 loss: 1.4397 2022/10/13 05:32:45 - mmengine - INFO - Epoch(train) [49][200/940] lr: 1.0000e-03 eta: 6:55:18 time: 0.4871 data_time: 0.0259 memory: 17006 grad_norm: 4.3377 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.4428 loss: 1.4428 2022/10/13 05:32:56 - mmengine - INFO - Epoch(train) [49][220/940] lr: 1.0000e-03 eta: 6:55:07 time: 0.5089 data_time: 0.0328 memory: 17006 grad_norm: 4.2768 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3738 loss: 1.3738 2022/10/13 05:33:05 - mmengine - INFO - Epoch(train) [49][240/940] lr: 1.0000e-03 eta: 6:54:56 time: 0.4712 data_time: 0.0291 memory: 17006 grad_norm: 4.2716 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4541 loss: 1.4541 2022/10/13 05:33:15 - mmengine - INFO - Epoch(train) [49][260/940] lr: 1.0000e-03 eta: 6:54:46 time: 0.4906 data_time: 0.0377 memory: 17006 grad_norm: 4.2833 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3043 loss: 1.3043 2022/10/13 05:33:24 - mmengine - INFO - Epoch(train) [49][280/940] lr: 1.0000e-03 eta: 6:54:35 time: 0.4816 data_time: 0.0293 memory: 17006 grad_norm: 4.2530 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.4562 loss: 1.4562 2022/10/13 05:33:35 - mmengine - INFO - Epoch(train) [49][300/940] lr: 1.0000e-03 eta: 6:54:25 time: 0.5356 data_time: 0.0339 memory: 17006 grad_norm: 4.3968 top1_acc: 0.5312 top5_acc: 0.9375 loss_cls: 1.5234 loss: 1.5234 2022/10/13 05:33:44 - mmengine - INFO - Epoch(train) [49][320/940] lr: 1.0000e-03 eta: 6:54:14 time: 0.4616 data_time: 0.0269 memory: 17006 grad_norm: 4.3031 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3291 loss: 1.3291 2022/10/13 05:33:56 - mmengine - INFO - Epoch(train) [49][340/940] lr: 1.0000e-03 eta: 6:54:04 time: 0.5584 data_time: 0.0467 memory: 17006 grad_norm: 4.3957 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4493 loss: 1.4493 2022/10/13 05:34:05 - mmengine - INFO - Epoch(train) [49][360/940] lr: 1.0000e-03 eta: 6:53:54 time: 0.4793 data_time: 0.0276 memory: 17006 grad_norm: 4.2879 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3825 loss: 1.3825 2022/10/13 05:34:16 - mmengine - INFO - Epoch(train) [49][380/940] lr: 1.0000e-03 eta: 6:53:44 time: 0.5303 data_time: 0.0328 memory: 17006 grad_norm: 4.2679 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3521 loss: 1.3521 2022/10/13 05:34:25 - mmengine - INFO - Epoch(train) [49][400/940] lr: 1.0000e-03 eta: 6:53:33 time: 0.4676 data_time: 0.0302 memory: 17006 grad_norm: 4.3411 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.3410 loss: 1.3410 2022/10/13 05:34:36 - mmengine - INFO - Epoch(train) [49][420/940] lr: 1.0000e-03 eta: 6:53:23 time: 0.5630 data_time: 0.0331 memory: 17006 grad_norm: 4.4478 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5576 loss: 1.5576 2022/10/13 05:34:46 - mmengine - INFO - Epoch(train) [49][440/940] lr: 1.0000e-03 eta: 6:53:12 time: 0.4705 data_time: 0.0358 memory: 17006 grad_norm: 4.2441 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3966 loss: 1.3966 2022/10/13 05:34:57 - mmengine - INFO - Epoch(train) [49][460/940] lr: 1.0000e-03 eta: 6:53:03 time: 0.5799 data_time: 0.0310 memory: 17006 grad_norm: 4.3468 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4137 loss: 1.4137 2022/10/13 05:35:07 - mmengine - INFO - Epoch(train) [49][480/940] lr: 1.0000e-03 eta: 6:52:53 time: 0.4881 data_time: 0.0350 memory: 17006 grad_norm: 4.3272 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3895 loss: 1.3895 2022/10/13 05:35:18 - mmengine - INFO - Epoch(train) [49][500/940] lr: 1.0000e-03 eta: 6:52:43 time: 0.5288 data_time: 0.0300 memory: 17006 grad_norm: 4.3319 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4701 loss: 1.4701 2022/10/13 05:35:27 - mmengine - INFO - Epoch(train) [49][520/940] lr: 1.0000e-03 eta: 6:52:32 time: 0.4759 data_time: 0.0349 memory: 17006 grad_norm: 4.4717 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.3008 loss: 1.3008 2022/10/13 05:35:37 - mmengine - INFO - Epoch(train) [49][540/940] lr: 1.0000e-03 eta: 6:52:22 time: 0.5092 data_time: 0.0380 memory: 17006 grad_norm: 4.3545 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3572 loss: 1.3572 2022/10/13 05:35:47 - mmengine - INFO - Epoch(train) [49][560/940] lr: 1.0000e-03 eta: 6:52:11 time: 0.4829 data_time: 0.0300 memory: 17006 grad_norm: 4.3099 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3741 loss: 1.3741 2022/10/13 05:35:57 - mmengine - INFO - Epoch(train) [49][580/940] lr: 1.0000e-03 eta: 6:52:00 time: 0.5009 data_time: 0.0357 memory: 17006 grad_norm: 4.3394 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.4053 loss: 1.4053 2022/10/13 05:36:07 - mmengine - INFO - Epoch(train) [49][600/940] lr: 1.0000e-03 eta: 6:51:50 time: 0.5074 data_time: 0.0357 memory: 17006 grad_norm: 4.3084 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3880 loss: 1.3880 2022/10/13 05:36:18 - mmengine - INFO - Epoch(train) [49][620/940] lr: 1.0000e-03 eta: 6:51:40 time: 0.5235 data_time: 0.0322 memory: 17006 grad_norm: 4.3795 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4698 loss: 1.4698 2022/10/13 05:36:28 - mmengine - INFO - Epoch(train) [49][640/940] lr: 1.0000e-03 eta: 6:51:29 time: 0.4931 data_time: 0.0320 memory: 17006 grad_norm: 4.3763 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4217 loss: 1.4217 2022/10/13 05:36:38 - mmengine - INFO - Epoch(train) [49][660/940] lr: 1.0000e-03 eta: 6:51:19 time: 0.5090 data_time: 0.0328 memory: 17006 grad_norm: 4.3327 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3028 loss: 1.3028 2022/10/13 05:36:47 - mmengine - INFO - Epoch(train) [49][680/940] lr: 1.0000e-03 eta: 6:51:08 time: 0.4706 data_time: 0.0345 memory: 17006 grad_norm: 4.3530 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.5033 loss: 1.5033 2022/10/13 05:36:58 - mmengine - INFO - Epoch(train) [49][700/940] lr: 1.0000e-03 eta: 6:50:58 time: 0.5410 data_time: 0.0297 memory: 17006 grad_norm: 4.3412 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.3862 loss: 1.3862 2022/10/13 05:37:08 - mmengine - INFO - Epoch(train) [49][720/940] lr: 1.0000e-03 eta: 6:50:47 time: 0.4783 data_time: 0.0326 memory: 17006 grad_norm: 4.3232 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4395 loss: 1.4395 2022/10/13 05:37:19 - mmengine - INFO - Epoch(train) [49][740/940] lr: 1.0000e-03 eta: 6:50:38 time: 0.5569 data_time: 0.0386 memory: 17006 grad_norm: 4.3709 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2882 loss: 1.2882 2022/10/13 05:37:27 - mmengine - INFO - Epoch(train) [49][760/940] lr: 1.0000e-03 eta: 6:50:26 time: 0.4272 data_time: 0.0373 memory: 17006 grad_norm: 4.3531 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5351 loss: 1.5351 2022/10/13 05:37:38 - mmengine - INFO - Epoch(train) [49][780/940] lr: 1.0000e-03 eta: 6:50:16 time: 0.5138 data_time: 0.0298 memory: 17006 grad_norm: 4.3445 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3433 loss: 1.3433 2022/10/13 05:37:48 - mmengine - INFO - Epoch(train) [49][800/940] lr: 1.0000e-03 eta: 6:50:06 time: 0.5367 data_time: 0.1369 memory: 17006 grad_norm: 4.3963 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3620 loss: 1.3620 2022/10/13 05:37:58 - mmengine - INFO - Epoch(train) [49][820/940] lr: 1.0000e-03 eta: 6:49:55 time: 0.4720 data_time: 0.0662 memory: 17006 grad_norm: 4.3012 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2982 loss: 1.2982 2022/10/13 05:38:09 - mmengine - INFO - Epoch(train) [49][840/940] lr: 1.0000e-03 eta: 6:49:46 time: 0.5543 data_time: 0.1014 memory: 17006 grad_norm: 4.3866 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5375 loss: 1.5375 2022/10/13 05:38:18 - mmengine - INFO - Epoch(train) [49][860/940] lr: 1.0000e-03 eta: 6:49:35 time: 0.4673 data_time: 0.0500 memory: 17006 grad_norm: 4.3999 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4662 loss: 1.4662 2022/10/13 05:38:29 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 05:38:29 - mmengine - INFO - Epoch(train) [49][880/940] lr: 1.0000e-03 eta: 6:49:25 time: 0.5434 data_time: 0.0419 memory: 17006 grad_norm: 4.2241 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3635 loss: 1.3635 2022/10/13 05:38:38 - mmengine - INFO - Epoch(train) [49][900/940] lr: 1.0000e-03 eta: 6:49:14 time: 0.4701 data_time: 0.0278 memory: 17006 grad_norm: 4.3767 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3900 loss: 1.3900 2022/10/13 05:38:49 - mmengine - INFO - Epoch(train) [49][920/940] lr: 1.0000e-03 eta: 6:49:04 time: 0.5474 data_time: 0.0356 memory: 17006 grad_norm: 4.4297 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4158 loss: 1.4158 2022/10/13 05:38:58 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 05:38:58 - mmengine - INFO - Epoch(train) [49][940/940] lr: 1.0000e-03 eta: 6:48:52 time: 0.4244 data_time: 0.0263 memory: 17006 grad_norm: 4.6750 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.3924 loss: 1.3924 2022/10/13 05:39:10 - mmengine - INFO - Epoch(val) [49][20/78] eta: 0:00:36 time: 0.6247 data_time: 0.5304 memory: 3172 2022/10/13 05:39:19 - mmengine - INFO - Epoch(val) [49][40/78] eta: 0:00:16 time: 0.4330 data_time: 0.3405 memory: 3172 2022/10/13 05:39:31 - mmengine - INFO - Epoch(val) [49][60/78] eta: 0:00:10 time: 0.5888 data_time: 0.4981 memory: 3172 2022/10/13 05:39:41 - mmengine - INFO - Epoch(val) [49][78/78] acc/top1: 0.6689 acc/top5: 0.8690 acc/mean1: 0.6688 2022/10/13 05:39:54 - mmengine - INFO - Epoch(train) [50][20/940] lr: 1.0000e-03 eta: 6:48:46 time: 0.6841 data_time: 0.3093 memory: 17006 grad_norm: 4.2772 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3003 loss: 1.3003 2022/10/13 05:40:04 - mmengine - INFO - Epoch(train) [50][40/940] lr: 1.0000e-03 eta: 6:48:35 time: 0.4836 data_time: 0.1532 memory: 17006 grad_norm: 4.3929 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4794 loss: 1.4794 2022/10/13 05:40:15 - mmengine - INFO - Epoch(train) [50][60/940] lr: 1.0000e-03 eta: 6:48:26 time: 0.5655 data_time: 0.2340 memory: 17006 grad_norm: 4.3652 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4083 loss: 1.4083 2022/10/13 05:40:25 - mmengine - INFO - Epoch(train) [50][80/940] lr: 1.0000e-03 eta: 6:48:15 time: 0.4752 data_time: 0.1325 memory: 17006 grad_norm: 4.3724 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5254 loss: 1.5254 2022/10/13 05:40:36 - mmengine - INFO - Epoch(train) [50][100/940] lr: 1.0000e-03 eta: 6:48:05 time: 0.5521 data_time: 0.0951 memory: 17006 grad_norm: 4.3479 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3673 loss: 1.3673 2022/10/13 05:40:46 - mmengine - INFO - Epoch(train) [50][120/940] lr: 1.0000e-03 eta: 6:47:55 time: 0.4891 data_time: 0.0269 memory: 17006 grad_norm: 4.4376 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4011 loss: 1.4011 2022/10/13 05:40:56 - mmengine - INFO - Epoch(train) [50][140/940] lr: 1.0000e-03 eta: 6:47:45 time: 0.5210 data_time: 0.0314 memory: 17006 grad_norm: 4.4004 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3978 loss: 1.3978 2022/10/13 05:41:05 - mmengine - INFO - Epoch(train) [50][160/940] lr: 1.0000e-03 eta: 6:47:33 time: 0.4658 data_time: 0.0290 memory: 17006 grad_norm: 4.3451 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2648 loss: 1.2648 2022/10/13 05:41:16 - mmengine - INFO - Epoch(train) [50][180/940] lr: 1.0000e-03 eta: 6:47:23 time: 0.5276 data_time: 0.0336 memory: 17006 grad_norm: 4.3217 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3592 loss: 1.3592 2022/10/13 05:41:25 - mmengine - INFO - Epoch(train) [50][200/940] lr: 1.0000e-03 eta: 6:47:12 time: 0.4758 data_time: 0.0325 memory: 17006 grad_norm: 4.3282 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4443 loss: 1.4443 2022/10/13 05:41:36 - mmengine - INFO - Epoch(train) [50][220/940] lr: 1.0000e-03 eta: 6:47:03 time: 0.5394 data_time: 0.0313 memory: 17006 grad_norm: 4.3281 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3317 loss: 1.3317 2022/10/13 05:41:46 - mmengine - INFO - Epoch(train) [50][240/940] lr: 1.0000e-03 eta: 6:46:52 time: 0.5024 data_time: 0.0322 memory: 17006 grad_norm: 4.2909 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4534 loss: 1.4534 2022/10/13 05:41:56 - mmengine - INFO - Epoch(train) [50][260/940] lr: 1.0000e-03 eta: 6:46:42 time: 0.4885 data_time: 0.0353 memory: 17006 grad_norm: 4.3195 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2967 loss: 1.2967 2022/10/13 05:42:06 - mmengine - INFO - Epoch(train) [50][280/940] lr: 1.0000e-03 eta: 6:46:31 time: 0.4902 data_time: 0.0366 memory: 17006 grad_norm: 4.3185 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2551 loss: 1.2551 2022/10/13 05:42:16 - mmengine - INFO - Epoch(train) [50][300/940] lr: 1.0000e-03 eta: 6:46:21 time: 0.5001 data_time: 0.0493 memory: 17006 grad_norm: 4.3814 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3248 loss: 1.3248 2022/10/13 05:42:25 - mmengine - INFO - Epoch(train) [50][320/940] lr: 1.0000e-03 eta: 6:46:10 time: 0.4819 data_time: 0.0494 memory: 17006 grad_norm: 4.4045 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5621 loss: 1.5621 2022/10/13 05:42:36 - mmengine - INFO - Epoch(train) [50][340/940] lr: 1.0000e-03 eta: 6:45:59 time: 0.5056 data_time: 0.0624 memory: 17006 grad_norm: 4.4392 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4343 loss: 1.4343 2022/10/13 05:42:46 - mmengine - INFO - Epoch(train) [50][360/940] lr: 1.0000e-03 eta: 6:45:49 time: 0.5252 data_time: 0.0301 memory: 17006 grad_norm: 4.3648 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.4733 loss: 1.4733 2022/10/13 05:42:57 - mmengine - INFO - Epoch(train) [50][380/940] lr: 1.0000e-03 eta: 6:45:40 time: 0.5455 data_time: 0.1785 memory: 17006 grad_norm: 4.3336 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.4019 loss: 1.4019 2022/10/13 05:43:07 - mmengine - INFO - Epoch(train) [50][400/940] lr: 1.0000e-03 eta: 6:45:29 time: 0.4968 data_time: 0.0433 memory: 17006 grad_norm: 4.3414 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.5366 loss: 1.5366 2022/10/13 05:43:16 - mmengine - INFO - Epoch(train) [50][420/940] lr: 1.0000e-03 eta: 6:45:18 time: 0.4578 data_time: 0.0365 memory: 17006 grad_norm: 4.4552 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3584 loss: 1.3584 2022/10/13 05:43:27 - mmengine - INFO - Epoch(train) [50][440/940] lr: 1.0000e-03 eta: 6:45:08 time: 0.5462 data_time: 0.0277 memory: 17006 grad_norm: 4.3651 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4635 loss: 1.4635 2022/10/13 05:43:36 - mmengine - INFO - Epoch(train) [50][460/940] lr: 1.0000e-03 eta: 6:44:57 time: 0.4765 data_time: 0.0328 memory: 17006 grad_norm: 4.4009 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3070 loss: 1.3070 2022/10/13 05:43:47 - mmengine - INFO - Epoch(train) [50][480/940] lr: 1.0000e-03 eta: 6:44:48 time: 0.5357 data_time: 0.0316 memory: 17006 grad_norm: 4.4154 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4129 loss: 1.4129 2022/10/13 05:43:57 - mmengine - INFO - Epoch(train) [50][500/940] lr: 1.0000e-03 eta: 6:44:37 time: 0.4995 data_time: 0.0396 memory: 17006 grad_norm: 4.3211 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4566 loss: 1.4566 2022/10/13 05:44:08 - mmengine - INFO - Epoch(train) [50][520/940] lr: 1.0000e-03 eta: 6:44:27 time: 0.5316 data_time: 0.0271 memory: 17006 grad_norm: 4.3096 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3694 loss: 1.3694 2022/10/13 05:44:17 - mmengine - INFO - Epoch(train) [50][540/940] lr: 1.0000e-03 eta: 6:44:16 time: 0.4765 data_time: 0.0354 memory: 17006 grad_norm: 4.3506 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3990 loss: 1.3990 2022/10/13 05:44:29 - mmengine - INFO - Epoch(train) [50][560/940] lr: 1.0000e-03 eta: 6:44:07 time: 0.5699 data_time: 0.0346 memory: 17006 grad_norm: 4.4120 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.5724 loss: 1.5724 2022/10/13 05:44:37 - mmengine - INFO - Epoch(train) [50][580/940] lr: 1.0000e-03 eta: 6:43:55 time: 0.4053 data_time: 0.0292 memory: 17006 grad_norm: 4.3667 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5536 loss: 1.5536 2022/10/13 05:44:48 - mmengine - INFO - Epoch(train) [50][600/940] lr: 1.0000e-03 eta: 6:43:45 time: 0.5373 data_time: 0.0310 memory: 17006 grad_norm: 4.3673 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4299 loss: 1.4299 2022/10/13 05:44:57 - mmengine - INFO - Epoch(train) [50][620/940] lr: 1.0000e-03 eta: 6:43:34 time: 0.4677 data_time: 0.0283 memory: 17006 grad_norm: 4.3785 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.4417 loss: 1.4417 2022/10/13 05:45:07 - mmengine - INFO - Epoch(train) [50][640/940] lr: 1.0000e-03 eta: 6:43:24 time: 0.5157 data_time: 0.0307 memory: 17006 grad_norm: 4.4640 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2791 loss: 1.2791 2022/10/13 05:45:18 - mmengine - INFO - Epoch(train) [50][660/940] lr: 1.0000e-03 eta: 6:43:14 time: 0.5294 data_time: 0.0392 memory: 17006 grad_norm: 4.2613 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.4054 loss: 1.4054 2022/10/13 05:45:28 - mmengine - INFO - Epoch(train) [50][680/940] lr: 1.0000e-03 eta: 6:43:03 time: 0.4871 data_time: 0.0271 memory: 17006 grad_norm: 4.3354 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4160 loss: 1.4160 2022/10/13 05:45:37 - mmengine - INFO - Epoch(train) [50][700/940] lr: 1.0000e-03 eta: 6:42:53 time: 0.4833 data_time: 0.0362 memory: 17006 grad_norm: 4.3209 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3255 loss: 1.3255 2022/10/13 05:45:46 - mmengine - INFO - Epoch(train) [50][720/940] lr: 1.0000e-03 eta: 6:42:41 time: 0.4546 data_time: 0.0336 memory: 17006 grad_norm: 4.3494 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2005 loss: 1.2005 2022/10/13 05:45:58 - mmengine - INFO - Epoch(train) [50][740/940] lr: 1.0000e-03 eta: 6:42:32 time: 0.5603 data_time: 0.0348 memory: 17006 grad_norm: 4.3803 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4993 loss: 1.4993 2022/10/13 05:46:07 - mmengine - INFO - Epoch(train) [50][760/940] lr: 1.0000e-03 eta: 6:42:21 time: 0.4650 data_time: 0.0276 memory: 17006 grad_norm: 4.2736 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.3434 loss: 1.3434 2022/10/13 05:46:18 - mmengine - INFO - Epoch(train) [50][780/940] lr: 1.0000e-03 eta: 6:42:11 time: 0.5494 data_time: 0.0373 memory: 17006 grad_norm: 4.4272 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4985 loss: 1.4985 2022/10/13 05:46:27 - mmengine - INFO - Epoch(train) [50][800/940] lr: 1.0000e-03 eta: 6:42:00 time: 0.4701 data_time: 0.0261 memory: 17006 grad_norm: 4.4334 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3965 loss: 1.3965 2022/10/13 05:46:38 - mmengine - INFO - Epoch(train) [50][820/940] lr: 1.0000e-03 eta: 6:41:50 time: 0.5306 data_time: 0.0317 memory: 17006 grad_norm: 4.4061 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3623 loss: 1.3623 2022/10/13 05:46:48 - mmengine - INFO - Epoch(train) [50][840/940] lr: 1.0000e-03 eta: 6:41:40 time: 0.4892 data_time: 0.0303 memory: 17006 grad_norm: 4.4327 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4792 loss: 1.4792 2022/10/13 05:46:58 - mmengine - INFO - Epoch(train) [50][860/940] lr: 1.0000e-03 eta: 6:41:30 time: 0.5401 data_time: 0.0373 memory: 17006 grad_norm: 4.4090 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3913 loss: 1.3913 2022/10/13 05:47:08 - mmengine - INFO - Epoch(train) [50][880/940] lr: 1.0000e-03 eta: 6:41:19 time: 0.4771 data_time: 0.0267 memory: 17006 grad_norm: 4.4147 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4502 loss: 1.4502 2022/10/13 05:47:19 - mmengine - INFO - Epoch(train) [50][900/940] lr: 1.0000e-03 eta: 6:41:10 time: 0.5705 data_time: 0.0340 memory: 17006 grad_norm: 4.4075 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5105 loss: 1.5105 2022/10/13 05:47:29 - mmengine - INFO - Epoch(train) [50][920/940] lr: 1.0000e-03 eta: 6:40:59 time: 0.4847 data_time: 0.0332 memory: 17006 grad_norm: 4.2724 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3185 loss: 1.3185 2022/10/13 05:47:39 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 05:47:39 - mmengine - INFO - Epoch(train) [50][940/940] lr: 1.0000e-03 eta: 6:40:49 time: 0.4907 data_time: 0.0246 memory: 17006 grad_norm: 4.6661 top1_acc: 0.4286 top5_acc: 1.0000 loss_cls: 1.3603 loss: 1.3603 2022/10/13 05:47:52 - mmengine - INFO - Epoch(val) [50][20/78] eta: 0:00:36 time: 0.6355 data_time: 0.5426 memory: 3172 2022/10/13 05:48:00 - mmengine - INFO - Epoch(val) [50][40/78] eta: 0:00:16 time: 0.4311 data_time: 0.3394 memory: 3172 2022/10/13 05:48:12 - mmengine - INFO - Epoch(val) [50][60/78] eta: 0:00:10 time: 0.5685 data_time: 0.4760 memory: 3172 2022/10/13 05:48:21 - mmengine - INFO - Epoch(val) [50][78/78] acc/top1: 0.6699 acc/top5: 0.8681 acc/mean1: 0.6698 2022/10/13 05:48:35 - mmengine - INFO - Epoch(train) [51][20/940] lr: 1.0000e-03 eta: 6:40:42 time: 0.6954 data_time: 0.3024 memory: 17006 grad_norm: 4.5055 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3904 loss: 1.3904 2022/10/13 05:48:45 - mmengine - INFO - Epoch(train) [51][40/940] lr: 1.0000e-03 eta: 6:40:31 time: 0.4775 data_time: 0.0505 memory: 17006 grad_norm: 4.2700 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4431 loss: 1.4431 2022/10/13 05:48:57 - mmengine - INFO - Epoch(train) [51][60/940] lr: 1.0000e-03 eta: 6:40:22 time: 0.5790 data_time: 0.0326 memory: 17006 grad_norm: 4.4090 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.4625 loss: 1.4625 2022/10/13 05:49:06 - mmengine - INFO - Epoch(train) [51][80/940] lr: 1.0000e-03 eta: 6:40:11 time: 0.4550 data_time: 0.0295 memory: 17006 grad_norm: 4.4209 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4854 loss: 1.4854 2022/10/13 05:49:16 - mmengine - INFO - Epoch(train) [51][100/940] lr: 1.0000e-03 eta: 6:40:01 time: 0.5296 data_time: 0.0354 memory: 17006 grad_norm: 4.3966 top1_acc: 0.9062 top5_acc: 0.9062 loss_cls: 1.1411 loss: 1.1411 2022/10/13 05:49:26 - mmengine - INFO - Epoch(train) [51][120/940] lr: 1.0000e-03 eta: 6:39:50 time: 0.4705 data_time: 0.0326 memory: 17006 grad_norm: 4.3214 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4215 loss: 1.4215 2022/10/13 05:49:36 - mmengine - INFO - Epoch(train) [51][140/940] lr: 1.0000e-03 eta: 6:39:40 time: 0.5425 data_time: 0.0326 memory: 17006 grad_norm: 4.4020 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.6647 loss: 1.6647 2022/10/13 05:49:46 - mmengine - INFO - Epoch(train) [51][160/940] lr: 1.0000e-03 eta: 6:39:29 time: 0.4772 data_time: 0.0288 memory: 17006 grad_norm: 4.5005 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.4528 loss: 1.4528 2022/10/13 05:49:57 - mmengine - INFO - Epoch(train) [51][180/940] lr: 1.0000e-03 eta: 6:39:20 time: 0.5704 data_time: 0.0349 memory: 17006 grad_norm: 4.4388 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4561 loss: 1.4561 2022/10/13 05:50:06 - mmengine - INFO - Epoch(train) [51][200/940] lr: 1.0000e-03 eta: 6:39:09 time: 0.4437 data_time: 0.0257 memory: 17006 grad_norm: 4.3444 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3315 loss: 1.3315 2022/10/13 05:50:17 - mmengine - INFO - Epoch(train) [51][220/940] lr: 1.0000e-03 eta: 6:38:59 time: 0.5201 data_time: 0.0391 memory: 17006 grad_norm: 4.4265 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3294 loss: 1.3294 2022/10/13 05:50:26 - mmengine - INFO - Epoch(train) [51][240/940] lr: 1.0000e-03 eta: 6:38:48 time: 0.4680 data_time: 0.0693 memory: 17006 grad_norm: 4.4239 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4021 loss: 1.4021 2022/10/13 05:50:37 - mmengine - INFO - Epoch(train) [51][260/940] lr: 1.0000e-03 eta: 6:38:38 time: 0.5382 data_time: 0.0831 memory: 17006 grad_norm: 4.3803 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.4522 loss: 1.4522 2022/10/13 05:50:47 - mmengine - INFO - Epoch(train) [51][280/940] lr: 1.0000e-03 eta: 6:38:27 time: 0.4926 data_time: 0.0494 memory: 17006 grad_norm: 4.4735 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3955 loss: 1.3955 2022/10/13 05:50:57 - mmengine - INFO - Epoch(train) [51][300/940] lr: 1.0000e-03 eta: 6:38:17 time: 0.5297 data_time: 0.0550 memory: 17006 grad_norm: 4.3575 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3741 loss: 1.3741 2022/10/13 05:51:08 - mmengine - INFO - Epoch(train) [51][320/940] lr: 1.0000e-03 eta: 6:38:07 time: 0.5158 data_time: 0.0321 memory: 17006 grad_norm: 4.4083 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.4133 loss: 1.4133 2022/10/13 05:51:17 - mmengine - INFO - Epoch(train) [51][340/940] lr: 1.0000e-03 eta: 6:37:57 time: 0.4924 data_time: 0.0501 memory: 17006 grad_norm: 4.5272 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4504 loss: 1.4504 2022/10/13 05:51:28 - mmengine - INFO - Epoch(train) [51][360/940] lr: 1.0000e-03 eta: 6:37:47 time: 0.5282 data_time: 0.0325 memory: 17006 grad_norm: 4.3710 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3299 loss: 1.3299 2022/10/13 05:51:38 - mmengine - INFO - Epoch(train) [51][380/940] lr: 1.0000e-03 eta: 6:37:36 time: 0.4988 data_time: 0.0269 memory: 17006 grad_norm: 4.4210 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2908 loss: 1.2908 2022/10/13 05:51:48 - mmengine - INFO - Epoch(train) [51][400/940] lr: 1.0000e-03 eta: 6:37:26 time: 0.4958 data_time: 0.0360 memory: 17006 grad_norm: 4.4199 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3680 loss: 1.3680 2022/10/13 05:51:59 - mmengine - INFO - Epoch(train) [51][420/940] lr: 1.0000e-03 eta: 6:37:16 time: 0.5416 data_time: 0.0428 memory: 17006 grad_norm: 4.3762 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3289 loss: 1.3289 2022/10/13 05:52:08 - mmengine - INFO - Epoch(train) [51][440/940] lr: 1.0000e-03 eta: 6:37:05 time: 0.4711 data_time: 0.0323 memory: 17006 grad_norm: 4.5564 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4348 loss: 1.4348 2022/10/13 05:52:19 - mmengine - INFO - Epoch(train) [51][460/940] lr: 1.0000e-03 eta: 6:36:55 time: 0.5190 data_time: 0.0331 memory: 17006 grad_norm: 4.3657 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3632 loss: 1.3632 2022/10/13 05:52:28 - mmengine - INFO - Epoch(train) [51][480/940] lr: 1.0000e-03 eta: 6:36:44 time: 0.4630 data_time: 0.0346 memory: 17006 grad_norm: 4.2739 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3438 loss: 1.3438 2022/10/13 05:52:39 - mmengine - INFO - Epoch(train) [51][500/940] lr: 1.0000e-03 eta: 6:36:35 time: 0.5698 data_time: 0.0300 memory: 17006 grad_norm: 4.3412 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.4060 loss: 1.4060 2022/10/13 05:52:49 - mmengine - INFO - Epoch(train) [51][520/940] lr: 1.0000e-03 eta: 6:36:24 time: 0.4720 data_time: 0.0353 memory: 17006 grad_norm: 4.3126 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3785 loss: 1.3785 2022/10/13 05:52:59 - mmengine - INFO - Epoch(train) [51][540/940] lr: 1.0000e-03 eta: 6:36:14 time: 0.5402 data_time: 0.0258 memory: 17006 grad_norm: 4.3519 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4604 loss: 1.4604 2022/10/13 05:53:10 - mmengine - INFO - Epoch(train) [51][560/940] lr: 1.0000e-03 eta: 6:36:04 time: 0.5086 data_time: 0.0341 memory: 17006 grad_norm: 4.4031 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3569 loss: 1.3569 2022/10/13 05:53:21 - mmengine - INFO - Epoch(train) [51][580/940] lr: 1.0000e-03 eta: 6:35:54 time: 0.5479 data_time: 0.0328 memory: 17006 grad_norm: 4.3865 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3959 loss: 1.3959 2022/10/13 05:53:30 - mmengine - INFO - Epoch(train) [51][600/940] lr: 1.0000e-03 eta: 6:35:43 time: 0.4723 data_time: 0.0329 memory: 17006 grad_norm: 4.4256 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3124 loss: 1.3124 2022/10/13 05:53:41 - mmengine - INFO - Epoch(train) [51][620/940] lr: 1.0000e-03 eta: 6:35:34 time: 0.5567 data_time: 0.0351 memory: 17006 grad_norm: 4.3472 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.5482 loss: 1.5482 2022/10/13 05:53:51 - mmengine - INFO - Epoch(train) [51][640/940] lr: 1.0000e-03 eta: 6:35:23 time: 0.4743 data_time: 0.0365 memory: 17006 grad_norm: 4.5301 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4051 loss: 1.4051 2022/10/13 05:54:01 - mmengine - INFO - Epoch(train) [51][660/940] lr: 1.0000e-03 eta: 6:35:13 time: 0.5334 data_time: 0.0320 memory: 17006 grad_norm: 4.3940 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3535 loss: 1.3535 2022/10/13 05:54:10 - mmengine - INFO - Epoch(train) [51][680/940] lr: 1.0000e-03 eta: 6:35:01 time: 0.4232 data_time: 0.0359 memory: 17006 grad_norm: 4.3469 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5366 loss: 1.5366 2022/10/13 05:54:20 - mmengine - INFO - Epoch(train) [51][700/940] lr: 1.0000e-03 eta: 6:34:51 time: 0.5213 data_time: 0.0303 memory: 17006 grad_norm: 4.3452 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3277 loss: 1.3277 2022/10/13 05:54:31 - mmengine - INFO - Epoch(train) [51][720/940] lr: 1.0000e-03 eta: 6:34:41 time: 0.5204 data_time: 0.1259 memory: 17006 grad_norm: 4.3964 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.4165 loss: 1.4165 2022/10/13 05:54:41 - mmengine - INFO - Epoch(train) [51][740/940] lr: 1.0000e-03 eta: 6:34:30 time: 0.4969 data_time: 0.0953 memory: 17006 grad_norm: 4.4300 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.3632 loss: 1.3632 2022/10/13 05:54:51 - mmengine - INFO - Epoch(train) [51][760/940] lr: 1.0000e-03 eta: 6:34:20 time: 0.5177 data_time: 0.0530 memory: 17006 grad_norm: 4.3936 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4033 loss: 1.4033 2022/10/13 05:55:01 - mmengine - INFO - Epoch(train) [51][780/940] lr: 1.0000e-03 eta: 6:34:10 time: 0.4988 data_time: 0.0265 memory: 17006 grad_norm: 4.3789 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3651 loss: 1.3651 2022/10/13 05:55:12 - mmengine - INFO - Epoch(train) [51][800/940] lr: 1.0000e-03 eta: 6:34:00 time: 0.5441 data_time: 0.0405 memory: 17006 grad_norm: 4.4836 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4091 loss: 1.4091 2022/10/13 05:55:21 - mmengine - INFO - Epoch(train) [51][820/940] lr: 1.0000e-03 eta: 6:33:49 time: 0.4698 data_time: 0.0531 memory: 17006 grad_norm: 4.2783 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3118 loss: 1.3118 2022/10/13 05:55:32 - mmengine - INFO - Epoch(train) [51][840/940] lr: 1.0000e-03 eta: 6:33:39 time: 0.5424 data_time: 0.1491 memory: 17006 grad_norm: 4.5171 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2881 loss: 1.2881 2022/10/13 05:55:42 - mmengine - INFO - Epoch(train) [51][860/940] lr: 1.0000e-03 eta: 6:33:29 time: 0.4768 data_time: 0.0790 memory: 17006 grad_norm: 4.4021 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4138 loss: 1.4138 2022/10/13 05:55:53 - mmengine - INFO - Epoch(train) [51][880/940] lr: 1.0000e-03 eta: 6:33:20 time: 0.5817 data_time: 0.2041 memory: 17006 grad_norm: 4.3418 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2731 loss: 1.2731 2022/10/13 05:56:02 - mmengine - INFO - Epoch(train) [51][900/940] lr: 1.0000e-03 eta: 6:33:08 time: 0.4628 data_time: 0.1198 memory: 17006 grad_norm: 4.4648 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2863 loss: 1.2863 2022/10/13 05:56:12 - mmengine - INFO - Epoch(train) [51][920/940] lr: 1.0000e-03 eta: 6:32:58 time: 0.4876 data_time: 0.0983 memory: 17006 grad_norm: 4.4285 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3404 loss: 1.3404 2022/10/13 05:56:21 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 05:56:21 - mmengine - INFO - Epoch(train) [51][940/940] lr: 1.0000e-03 eta: 6:32:46 time: 0.4540 data_time: 0.0218 memory: 17006 grad_norm: 4.7459 top1_acc: 0.2857 top5_acc: 0.4286 loss_cls: 1.5706 loss: 1.5706 2022/10/13 05:56:21 - mmengine - INFO - Saving checkpoint at 51 epochs 2022/10/13 05:56:35 - mmengine - INFO - Epoch(val) [51][20/78] eta: 0:00:36 time: 0.6246 data_time: 0.5348 memory: 3172 2022/10/13 05:56:43 - mmengine - INFO - Epoch(val) [51][40/78] eta: 0:00:16 time: 0.4320 data_time: 0.3425 memory: 3172 2022/10/13 05:56:55 - mmengine - INFO - Epoch(val) [51][60/78] eta: 0:00:10 time: 0.5792 data_time: 0.4890 memory: 3172 2022/10/13 05:57:04 - mmengine - INFO - Epoch(val) [51][78/78] acc/top1: 0.6702 acc/top5: 0.8682 acc/mean1: 0.6701 2022/10/13 05:57:18 - mmengine - INFO - Epoch(train) [52][20/940] lr: 1.0000e-03 eta: 6:32:39 time: 0.6824 data_time: 0.2343 memory: 17006 grad_norm: 4.4379 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4305 loss: 1.4305 2022/10/13 05:57:27 - mmengine - INFO - Epoch(train) [52][40/940] lr: 1.0000e-03 eta: 6:32:29 time: 0.4918 data_time: 0.0573 memory: 17006 grad_norm: 4.3731 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3829 loss: 1.3829 2022/10/13 05:57:39 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 05:57:39 - mmengine - INFO - Epoch(train) [52][60/940] lr: 1.0000e-03 eta: 6:32:19 time: 0.5556 data_time: 0.0455 memory: 17006 grad_norm: 4.4168 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2833 loss: 1.2833 2022/10/13 05:57:48 - mmengine - INFO - Epoch(train) [52][80/940] lr: 1.0000e-03 eta: 6:32:09 time: 0.4971 data_time: 0.0264 memory: 17006 grad_norm: 4.3668 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2763 loss: 1.2763 2022/10/13 05:57:58 - mmengine - INFO - Epoch(train) [52][100/940] lr: 1.0000e-03 eta: 6:31:58 time: 0.4985 data_time: 0.0550 memory: 17006 grad_norm: 4.3647 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4025 loss: 1.4025 2022/10/13 05:58:08 - mmengine - INFO - Epoch(train) [52][120/940] lr: 1.0000e-03 eta: 6:31:48 time: 0.4778 data_time: 0.1522 memory: 17006 grad_norm: 4.3643 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3921 loss: 1.3921 2022/10/13 05:58:19 - mmengine - INFO - Epoch(train) [52][140/940] lr: 1.0000e-03 eta: 6:31:38 time: 0.5454 data_time: 0.2322 memory: 17006 grad_norm: 4.3905 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.5211 loss: 1.5211 2022/10/13 05:58:29 - mmengine - INFO - Epoch(train) [52][160/940] lr: 1.0000e-03 eta: 6:31:27 time: 0.4878 data_time: 0.1323 memory: 17006 grad_norm: 4.3930 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3166 loss: 1.3166 2022/10/13 05:58:40 - mmengine - INFO - Epoch(train) [52][180/940] lr: 1.0000e-03 eta: 6:31:18 time: 0.5434 data_time: 0.1536 memory: 17006 grad_norm: 4.3996 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2849 loss: 1.2849 2022/10/13 05:58:49 - mmengine - INFO - Epoch(train) [52][200/940] lr: 1.0000e-03 eta: 6:31:07 time: 0.4633 data_time: 0.1291 memory: 17006 grad_norm: 4.3836 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4199 loss: 1.4199 2022/10/13 05:59:00 - mmengine - INFO - Epoch(train) [52][220/940] lr: 1.0000e-03 eta: 6:30:57 time: 0.5645 data_time: 0.1277 memory: 17006 grad_norm: 4.4276 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5119 loss: 1.5119 2022/10/13 05:59:10 - mmengine - INFO - Epoch(train) [52][240/940] lr: 1.0000e-03 eta: 6:30:47 time: 0.5050 data_time: 0.0259 memory: 17006 grad_norm: 4.3938 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.3520 loss: 1.3520 2022/10/13 05:59:22 - mmengine - INFO - Epoch(train) [52][260/940] lr: 1.0000e-03 eta: 6:30:38 time: 0.5755 data_time: 0.0327 memory: 17006 grad_norm: 4.3635 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3315 loss: 1.3315 2022/10/13 05:59:30 - mmengine - INFO - Epoch(train) [52][280/940] lr: 1.0000e-03 eta: 6:30:26 time: 0.4251 data_time: 0.0345 memory: 17006 grad_norm: 4.4268 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3610 loss: 1.3610 2022/10/13 05:59:41 - mmengine - INFO - Epoch(train) [52][300/940] lr: 1.0000e-03 eta: 6:30:16 time: 0.5278 data_time: 0.0317 memory: 17006 grad_norm: 4.3694 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3587 loss: 1.3587 2022/10/13 05:59:50 - mmengine - INFO - Epoch(train) [52][320/940] lr: 1.0000e-03 eta: 6:30:05 time: 0.4643 data_time: 0.0333 memory: 17006 grad_norm: 4.4687 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.4898 loss: 1.4898 2022/10/13 06:00:01 - mmengine - INFO - Epoch(train) [52][340/940] lr: 1.0000e-03 eta: 6:29:55 time: 0.5301 data_time: 0.0330 memory: 17006 grad_norm: 4.4106 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4652 loss: 1.4652 2022/10/13 06:00:10 - mmengine - INFO - Epoch(train) [52][360/940] lr: 1.0000e-03 eta: 6:29:44 time: 0.4906 data_time: 0.0316 memory: 17006 grad_norm: 4.4391 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3106 loss: 1.3106 2022/10/13 06:00:21 - mmengine - INFO - Epoch(train) [52][380/940] lr: 1.0000e-03 eta: 6:29:35 time: 0.5304 data_time: 0.0331 memory: 17006 grad_norm: 4.4665 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.4103 loss: 1.4103 2022/10/13 06:00:31 - mmengine - INFO - Epoch(train) [52][400/940] lr: 1.0000e-03 eta: 6:29:24 time: 0.4791 data_time: 0.0296 memory: 17006 grad_norm: 4.5307 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.5727 loss: 1.5727 2022/10/13 06:00:41 - mmengine - INFO - Epoch(train) [52][420/940] lr: 1.0000e-03 eta: 6:29:14 time: 0.5246 data_time: 0.0359 memory: 17006 grad_norm: 4.4559 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.4266 loss: 1.4266 2022/10/13 06:00:52 - mmengine - INFO - Epoch(train) [52][440/940] lr: 1.0000e-03 eta: 6:29:04 time: 0.5403 data_time: 0.0290 memory: 17006 grad_norm: 4.4221 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.4998 loss: 1.4998 2022/10/13 06:01:02 - mmengine - INFO - Epoch(train) [52][460/940] lr: 1.0000e-03 eta: 6:28:53 time: 0.4817 data_time: 0.0387 memory: 17006 grad_norm: 4.4877 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.3085 loss: 1.3085 2022/10/13 06:01:12 - mmengine - INFO - Epoch(train) [52][480/940] lr: 1.0000e-03 eta: 6:28:44 time: 0.5390 data_time: 0.0302 memory: 17006 grad_norm: 4.2927 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3908 loss: 1.3908 2022/10/13 06:01:22 - mmengine - INFO - Epoch(train) [52][500/940] lr: 1.0000e-03 eta: 6:28:33 time: 0.4777 data_time: 0.0307 memory: 17006 grad_norm: 4.4600 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4089 loss: 1.4089 2022/10/13 06:01:33 - mmengine - INFO - Epoch(train) [52][520/940] lr: 1.0000e-03 eta: 6:28:23 time: 0.5468 data_time: 0.0304 memory: 17006 grad_norm: 4.4461 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4624 loss: 1.4624 2022/10/13 06:01:42 - mmengine - INFO - Epoch(train) [52][540/940] lr: 1.0000e-03 eta: 6:28:11 time: 0.4380 data_time: 0.0377 memory: 17006 grad_norm: 4.4064 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4343 loss: 1.4343 2022/10/13 06:01:53 - mmengine - INFO - Epoch(train) [52][560/940] lr: 1.0000e-03 eta: 6:28:02 time: 0.5779 data_time: 0.0255 memory: 17006 grad_norm: 4.3799 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4148 loss: 1.4148 2022/10/13 06:02:03 - mmengine - INFO - Epoch(train) [52][580/940] lr: 1.0000e-03 eta: 6:27:52 time: 0.4928 data_time: 0.0304 memory: 17006 grad_norm: 4.3785 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4842 loss: 1.4842 2022/10/13 06:02:13 - mmengine - INFO - Epoch(train) [52][600/940] lr: 1.0000e-03 eta: 6:27:41 time: 0.4949 data_time: 0.0290 memory: 17006 grad_norm: 4.4631 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.3087 loss: 1.3087 2022/10/13 06:02:22 - mmengine - INFO - Epoch(train) [52][620/940] lr: 1.0000e-03 eta: 6:27:30 time: 0.4599 data_time: 0.0282 memory: 17006 grad_norm: 4.4590 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2655 loss: 1.2655 2022/10/13 06:02:33 - mmengine - INFO - Epoch(train) [52][640/940] lr: 1.0000e-03 eta: 6:27:20 time: 0.5190 data_time: 0.0316 memory: 17006 grad_norm: 4.3603 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3151 loss: 1.3151 2022/10/13 06:02:42 - mmengine - INFO - Epoch(train) [52][660/940] lr: 1.0000e-03 eta: 6:27:09 time: 0.4958 data_time: 0.0314 memory: 17006 grad_norm: 4.4455 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4255 loss: 1.4255 2022/10/13 06:02:53 - mmengine - INFO - Epoch(train) [52][680/940] lr: 1.0000e-03 eta: 6:26:59 time: 0.5157 data_time: 0.0338 memory: 17006 grad_norm: 4.5161 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4509 loss: 1.4509 2022/10/13 06:03:03 - mmengine - INFO - Epoch(train) [52][700/940] lr: 1.0000e-03 eta: 6:26:49 time: 0.5082 data_time: 0.0337 memory: 17006 grad_norm: 4.3949 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4921 loss: 1.4921 2022/10/13 06:03:13 - mmengine - INFO - Epoch(train) [52][720/940] lr: 1.0000e-03 eta: 6:26:39 time: 0.5192 data_time: 0.0473 memory: 17006 grad_norm: 4.4180 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4424 loss: 1.4424 2022/10/13 06:03:24 - mmengine - INFO - Epoch(train) [52][740/940] lr: 1.0000e-03 eta: 6:26:29 time: 0.5137 data_time: 0.0333 memory: 17006 grad_norm: 4.4144 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3578 loss: 1.3578 2022/10/13 06:03:34 - mmengine - INFO - Epoch(train) [52][760/940] lr: 1.0000e-03 eta: 6:26:19 time: 0.5225 data_time: 0.0274 memory: 17006 grad_norm: 4.4202 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2598 loss: 1.2598 2022/10/13 06:03:45 - mmengine - INFO - Epoch(train) [52][780/940] lr: 1.0000e-03 eta: 6:26:09 time: 0.5233 data_time: 0.0370 memory: 17006 grad_norm: 4.4436 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4464 loss: 1.4464 2022/10/13 06:03:56 - mmengine - INFO - Epoch(train) [52][800/940] lr: 1.0000e-03 eta: 6:25:59 time: 0.5547 data_time: 0.0301 memory: 17006 grad_norm: 4.3963 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3743 loss: 1.3743 2022/10/13 06:04:04 - mmengine - INFO - Epoch(train) [52][820/940] lr: 1.0000e-03 eta: 6:25:48 time: 0.4345 data_time: 0.0309 memory: 17006 grad_norm: 4.4336 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3825 loss: 1.3825 2022/10/13 06:04:15 - mmengine - INFO - Epoch(train) [52][840/940] lr: 1.0000e-03 eta: 6:25:38 time: 0.5582 data_time: 0.0356 memory: 17006 grad_norm: 4.4137 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4102 loss: 1.4102 2022/10/13 06:04:25 - mmengine - INFO - Epoch(train) [52][860/940] lr: 1.0000e-03 eta: 6:25:28 time: 0.4992 data_time: 0.0311 memory: 17006 grad_norm: 4.4066 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4710 loss: 1.4710 2022/10/13 06:04:36 - mmengine - INFO - Epoch(train) [52][880/940] lr: 1.0000e-03 eta: 6:25:18 time: 0.5144 data_time: 0.0271 memory: 17006 grad_norm: 4.4000 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3484 loss: 1.3484 2022/10/13 06:04:45 - mmengine - INFO - Epoch(train) [52][900/940] lr: 1.0000e-03 eta: 6:25:07 time: 0.4881 data_time: 0.0372 memory: 17006 grad_norm: 4.3827 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4541 loss: 1.4541 2022/10/13 06:04:55 - mmengine - INFO - Epoch(train) [52][920/940] lr: 1.0000e-03 eta: 6:24:56 time: 0.4928 data_time: 0.0280 memory: 17006 grad_norm: 4.3427 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3536 loss: 1.3536 2022/10/13 06:05:04 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 06:05:04 - mmengine - INFO - Epoch(train) [52][940/940] lr: 1.0000e-03 eta: 6:24:44 time: 0.4188 data_time: 0.0275 memory: 17006 grad_norm: 4.6033 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.3862 loss: 1.3862 2022/10/13 06:05:17 - mmengine - INFO - Epoch(val) [52][20/78] eta: 0:00:36 time: 0.6298 data_time: 0.5351 memory: 3172 2022/10/13 06:05:25 - mmengine - INFO - Epoch(val) [52][40/78] eta: 0:00:16 time: 0.4263 data_time: 0.3348 memory: 3172 2022/10/13 06:05:37 - mmengine - INFO - Epoch(val) [52][60/78] eta: 0:00:10 time: 0.5798 data_time: 0.4876 memory: 3172 2022/10/13 06:05:46 - mmengine - INFO - Epoch(val) [52][78/78] acc/top1: 0.6722 acc/top5: 0.8693 acc/mean1: 0.6720 2022/10/13 06:05:46 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_48.pth is removed 2022/10/13 06:05:47 - mmengine - INFO - The best checkpoint with 0.6722 acc/top1 at 52 epoch is saved to best_acc/top1_epoch_52.pth. 2022/10/13 06:06:01 - mmengine - INFO - Epoch(train) [53][20/940] lr: 1.0000e-03 eta: 6:24:37 time: 0.6883 data_time: 0.3303 memory: 17006 grad_norm: 4.4613 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3831 loss: 1.3831 2022/10/13 06:06:10 - mmengine - INFO - Epoch(train) [53][40/940] lr: 1.0000e-03 eta: 6:24:26 time: 0.4513 data_time: 0.0894 memory: 17006 grad_norm: 4.3877 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4782 loss: 1.4782 2022/10/13 06:06:21 - mmengine - INFO - Epoch(train) [53][60/940] lr: 1.0000e-03 eta: 6:24:17 time: 0.5712 data_time: 0.1449 memory: 17006 grad_norm: 4.3653 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.4151 loss: 1.4151 2022/10/13 06:06:31 - mmengine - INFO - Epoch(train) [53][80/940] lr: 1.0000e-03 eta: 6:24:06 time: 0.4609 data_time: 0.0791 memory: 17006 grad_norm: 4.3756 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3780 loss: 1.3780 2022/10/13 06:06:41 - mmengine - INFO - Epoch(train) [53][100/940] lr: 1.0000e-03 eta: 6:23:56 time: 0.5312 data_time: 0.0343 memory: 17006 grad_norm: 4.3920 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3792 loss: 1.3792 2022/10/13 06:06:51 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 06:06:51 - mmengine - INFO - Epoch(train) [53][120/940] lr: 1.0000e-03 eta: 6:23:45 time: 0.4822 data_time: 0.0274 memory: 17006 grad_norm: 4.4293 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3032 loss: 1.3032 2022/10/13 06:07:02 - mmengine - INFO - Epoch(train) [53][140/940] lr: 1.0000e-03 eta: 6:23:35 time: 0.5423 data_time: 0.0563 memory: 17006 grad_norm: 4.4907 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4569 loss: 1.4569 2022/10/13 06:07:11 - mmengine - INFO - Epoch(train) [53][160/940] lr: 1.0000e-03 eta: 6:23:25 time: 0.4833 data_time: 0.1548 memory: 17006 grad_norm: 4.4456 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4462 loss: 1.4462 2022/10/13 06:07:22 - mmengine - INFO - Epoch(train) [53][180/940] lr: 1.0000e-03 eta: 6:23:15 time: 0.5509 data_time: 0.1426 memory: 17006 grad_norm: 4.4803 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4396 loss: 1.4396 2022/10/13 06:07:32 - mmengine - INFO - Epoch(train) [53][200/940] lr: 1.0000e-03 eta: 6:23:05 time: 0.5035 data_time: 0.0274 memory: 17006 grad_norm: 4.3909 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4144 loss: 1.4144 2022/10/13 06:07:44 - mmengine - INFO - Epoch(train) [53][220/940] lr: 1.0000e-03 eta: 6:22:55 time: 0.5567 data_time: 0.0327 memory: 17006 grad_norm: 4.4860 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3830 loss: 1.3830 2022/10/13 06:07:53 - mmengine - INFO - Epoch(train) [53][240/940] lr: 1.0000e-03 eta: 6:22:45 time: 0.4872 data_time: 0.0374 memory: 17006 grad_norm: 4.3679 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3579 loss: 1.3579 2022/10/13 06:08:03 - mmengine - INFO - Epoch(train) [53][260/940] lr: 1.0000e-03 eta: 6:22:34 time: 0.4820 data_time: 0.0321 memory: 17006 grad_norm: 4.4416 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3399 loss: 1.3399 2022/10/13 06:08:13 - mmengine - INFO - Epoch(train) [53][280/940] lr: 1.0000e-03 eta: 6:22:23 time: 0.4852 data_time: 0.0646 memory: 17006 grad_norm: 4.3273 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.3613 loss: 1.3613 2022/10/13 06:08:22 - mmengine - INFO - Epoch(train) [53][300/940] lr: 1.0000e-03 eta: 6:22:12 time: 0.4809 data_time: 0.0282 memory: 17006 grad_norm: 4.3869 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3964 loss: 1.3964 2022/10/13 06:08:32 - mmengine - INFO - Epoch(train) [53][320/940] lr: 1.0000e-03 eta: 6:22:02 time: 0.5007 data_time: 0.0504 memory: 17006 grad_norm: 4.4747 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3861 loss: 1.3861 2022/10/13 06:08:42 - mmengine - INFO - Epoch(train) [53][340/940] lr: 1.0000e-03 eta: 6:21:51 time: 0.4829 data_time: 0.0307 memory: 17006 grad_norm: 4.3692 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3214 loss: 1.3214 2022/10/13 06:08:52 - mmengine - INFO - Epoch(train) [53][360/940] lr: 1.0000e-03 eta: 6:21:41 time: 0.5048 data_time: 0.0374 memory: 17006 grad_norm: 4.3983 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3474 loss: 1.3474 2022/10/13 06:09:03 - mmengine - INFO - Epoch(train) [53][380/940] lr: 1.0000e-03 eta: 6:21:31 time: 0.5335 data_time: 0.0338 memory: 17006 grad_norm: 4.5373 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.4358 loss: 1.4358 2022/10/13 06:09:12 - mmengine - INFO - Epoch(train) [53][400/940] lr: 1.0000e-03 eta: 6:21:20 time: 0.4868 data_time: 0.0323 memory: 17006 grad_norm: 4.3764 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4157 loss: 1.4157 2022/10/13 06:09:23 - mmengine - INFO - Epoch(train) [53][420/940] lr: 1.0000e-03 eta: 6:21:11 time: 0.5433 data_time: 0.0651 memory: 17006 grad_norm: 4.5131 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.4933 loss: 1.4933 2022/10/13 06:09:33 - mmengine - INFO - Epoch(train) [53][440/940] lr: 1.0000e-03 eta: 6:21:00 time: 0.4847 data_time: 0.1273 memory: 17006 grad_norm: 4.3924 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.4082 loss: 1.4082 2022/10/13 06:09:43 - mmengine - INFO - Epoch(train) [53][460/940] lr: 1.0000e-03 eta: 6:20:50 time: 0.5077 data_time: 0.1178 memory: 17006 grad_norm: 4.3983 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3146 loss: 1.3146 2022/10/13 06:09:53 - mmengine - INFO - Epoch(train) [53][480/940] lr: 1.0000e-03 eta: 6:20:39 time: 0.4752 data_time: 0.0437 memory: 17006 grad_norm: 4.3886 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4772 loss: 1.4772 2022/10/13 06:10:03 - mmengine - INFO - Epoch(train) [53][500/940] lr: 1.0000e-03 eta: 6:20:29 time: 0.5425 data_time: 0.0347 memory: 17006 grad_norm: 4.4223 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3465 loss: 1.3465 2022/10/13 06:10:13 - mmengine - INFO - Epoch(train) [53][520/940] lr: 1.0000e-03 eta: 6:20:18 time: 0.4879 data_time: 0.0296 memory: 17006 grad_norm: 4.3310 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3052 loss: 1.3052 2022/10/13 06:10:24 - mmengine - INFO - Epoch(train) [53][540/940] lr: 1.0000e-03 eta: 6:20:09 time: 0.5375 data_time: 0.0372 memory: 17006 grad_norm: 4.4460 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.4830 loss: 1.4830 2022/10/13 06:10:34 - mmengine - INFO - Epoch(train) [53][560/940] lr: 1.0000e-03 eta: 6:19:58 time: 0.5000 data_time: 0.0322 memory: 17006 grad_norm: 4.5028 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4848 loss: 1.4848 2022/10/13 06:10:44 - mmengine - INFO - Epoch(train) [53][580/940] lr: 1.0000e-03 eta: 6:19:48 time: 0.5092 data_time: 0.0307 memory: 17006 grad_norm: 4.4359 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.3576 loss: 1.3576 2022/10/13 06:10:54 - mmengine - INFO - Epoch(train) [53][600/940] lr: 1.0000e-03 eta: 6:19:37 time: 0.4797 data_time: 0.0356 memory: 17006 grad_norm: 4.5410 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3660 loss: 1.3660 2022/10/13 06:11:04 - mmengine - INFO - Epoch(train) [53][620/940] lr: 1.0000e-03 eta: 6:19:27 time: 0.5224 data_time: 0.0295 memory: 17006 grad_norm: 4.3865 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3247 loss: 1.3247 2022/10/13 06:11:14 - mmengine - INFO - Epoch(train) [53][640/940] lr: 1.0000e-03 eta: 6:19:17 time: 0.5074 data_time: 0.0395 memory: 17006 grad_norm: 4.4161 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3102 loss: 1.3102 2022/10/13 06:11:24 - mmengine - INFO - Epoch(train) [53][660/940] lr: 1.0000e-03 eta: 6:19:06 time: 0.5037 data_time: 0.0324 memory: 17006 grad_norm: 4.4454 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3474 loss: 1.3474 2022/10/13 06:11:35 - mmengine - INFO - Epoch(train) [53][680/940] lr: 1.0000e-03 eta: 6:18:56 time: 0.5028 data_time: 0.0373 memory: 17006 grad_norm: 4.4834 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.4242 loss: 1.4242 2022/10/13 06:11:46 - mmengine - INFO - Epoch(train) [53][700/940] lr: 1.0000e-03 eta: 6:18:46 time: 0.5527 data_time: 0.0239 memory: 17006 grad_norm: 4.3994 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3497 loss: 1.3497 2022/10/13 06:11:55 - mmengine - INFO - Epoch(train) [53][720/940] lr: 1.0000e-03 eta: 6:18:35 time: 0.4479 data_time: 0.0415 memory: 17006 grad_norm: 4.5030 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5022 loss: 1.5022 2022/10/13 06:12:05 - mmengine - INFO - Epoch(train) [53][740/940] lr: 1.0000e-03 eta: 6:18:25 time: 0.5185 data_time: 0.0263 memory: 17006 grad_norm: 4.5394 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4817 loss: 1.4817 2022/10/13 06:12:14 - mmengine - INFO - Epoch(train) [53][760/940] lr: 1.0000e-03 eta: 6:18:14 time: 0.4701 data_time: 0.0362 memory: 17006 grad_norm: 4.3448 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3726 loss: 1.3726 2022/10/13 06:12:25 - mmengine - INFO - Epoch(train) [53][780/940] lr: 1.0000e-03 eta: 6:18:04 time: 0.5476 data_time: 0.0362 memory: 17006 grad_norm: 4.5200 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3858 loss: 1.3858 2022/10/13 06:12:35 - mmengine - INFO - Epoch(train) [53][800/940] lr: 1.0000e-03 eta: 6:17:54 time: 0.4824 data_time: 0.0353 memory: 17006 grad_norm: 4.4216 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3387 loss: 1.3387 2022/10/13 06:12:46 - mmengine - INFO - Epoch(train) [53][820/940] lr: 1.0000e-03 eta: 6:17:44 time: 0.5307 data_time: 0.0309 memory: 17006 grad_norm: 4.4135 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2746 loss: 1.2746 2022/10/13 06:12:55 - mmengine - INFO - Epoch(train) [53][840/940] lr: 1.0000e-03 eta: 6:17:33 time: 0.4919 data_time: 0.0723 memory: 17006 grad_norm: 4.5032 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4890 loss: 1.4890 2022/10/13 06:13:06 - mmengine - INFO - Epoch(train) [53][860/940] lr: 1.0000e-03 eta: 6:17:23 time: 0.5112 data_time: 0.0274 memory: 17006 grad_norm: 4.5685 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3630 loss: 1.3630 2022/10/13 06:13:15 - mmengine - INFO - Epoch(train) [53][880/940] lr: 1.0000e-03 eta: 6:17:12 time: 0.4953 data_time: 0.0329 memory: 17006 grad_norm: 4.4013 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3956 loss: 1.3956 2022/10/13 06:13:26 - mmengine - INFO - Epoch(train) [53][900/940] lr: 1.0000e-03 eta: 6:17:03 time: 0.5387 data_time: 0.0254 memory: 17006 grad_norm: 4.5208 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3512 loss: 1.3512 2022/10/13 06:13:36 - mmengine - INFO - Epoch(train) [53][920/940] lr: 1.0000e-03 eta: 6:16:52 time: 0.5034 data_time: 0.0346 memory: 17006 grad_norm: 4.4985 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4430 loss: 1.4430 2022/10/13 06:13:45 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 06:13:45 - mmengine - INFO - Epoch(train) [53][940/940] lr: 1.0000e-03 eta: 6:16:41 time: 0.4561 data_time: 0.0232 memory: 17006 grad_norm: 4.7842 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.5107 loss: 1.5107 2022/10/13 06:13:58 - mmengine - INFO - Epoch(val) [53][20/78] eta: 0:00:36 time: 0.6266 data_time: 0.5334 memory: 3172 2022/10/13 06:14:07 - mmengine - INFO - Epoch(val) [53][40/78] eta: 0:00:16 time: 0.4322 data_time: 0.3417 memory: 3172 2022/10/13 06:14:18 - mmengine - INFO - Epoch(val) [53][60/78] eta: 0:00:10 time: 0.5847 data_time: 0.4906 memory: 3172 2022/10/13 06:14:28 - mmengine - INFO - Epoch(val) [53][78/78] acc/top1: 0.6706 acc/top5: 0.8684 acc/mean1: 0.6706 2022/10/13 06:14:42 - mmengine - INFO - Epoch(train) [54][20/940] lr: 1.0000e-03 eta: 6:16:34 time: 0.6987 data_time: 0.2211 memory: 17006 grad_norm: 4.3684 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.3338 loss: 1.3338 2022/10/13 06:14:51 - mmengine - INFO - Epoch(train) [54][40/940] lr: 1.0000e-03 eta: 6:16:23 time: 0.4706 data_time: 0.0274 memory: 17006 grad_norm: 4.5411 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3610 loss: 1.3610 2022/10/13 06:15:02 - mmengine - INFO - Epoch(train) [54][60/940] lr: 1.0000e-03 eta: 6:16:13 time: 0.5398 data_time: 0.0341 memory: 17006 grad_norm: 4.4244 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3295 loss: 1.3295 2022/10/13 06:15:12 - mmengine - INFO - Epoch(train) [54][80/940] lr: 1.0000e-03 eta: 6:16:03 time: 0.4863 data_time: 0.0294 memory: 17006 grad_norm: 4.3560 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.3941 loss: 1.3941 2022/10/13 06:15:23 - mmengine - INFO - Epoch(train) [54][100/940] lr: 1.0000e-03 eta: 6:15:53 time: 0.5279 data_time: 0.0353 memory: 17006 grad_norm: 4.4062 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4071 loss: 1.4071 2022/10/13 06:15:32 - mmengine - INFO - Epoch(train) [54][120/940] lr: 1.0000e-03 eta: 6:15:42 time: 0.4520 data_time: 0.0321 memory: 17006 grad_norm: 4.4216 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.4070 loss: 1.4070 2022/10/13 06:15:43 - mmengine - INFO - Epoch(train) [54][140/940] lr: 1.0000e-03 eta: 6:15:32 time: 0.5678 data_time: 0.0336 memory: 17006 grad_norm: 4.4130 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4524 loss: 1.4524 2022/10/13 06:15:52 - mmengine - INFO - Epoch(train) [54][160/940] lr: 1.0000e-03 eta: 6:15:21 time: 0.4519 data_time: 0.0279 memory: 17006 grad_norm: 4.4093 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3848 loss: 1.3848 2022/10/13 06:16:03 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 06:16:03 - mmengine - INFO - Epoch(train) [54][180/940] lr: 1.0000e-03 eta: 6:15:12 time: 0.5689 data_time: 0.0356 memory: 17006 grad_norm: 4.5304 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3821 loss: 1.3821 2022/10/13 06:16:13 - mmengine - INFO - Epoch(train) [54][200/940] lr: 1.0000e-03 eta: 6:15:01 time: 0.4877 data_time: 0.0256 memory: 17006 grad_norm: 4.4952 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4823 loss: 1.4823 2022/10/13 06:16:24 - mmengine - INFO - Epoch(train) [54][220/940] lr: 1.0000e-03 eta: 6:14:52 time: 0.5509 data_time: 0.0359 memory: 17006 grad_norm: 4.5462 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4345 loss: 1.4345 2022/10/13 06:16:34 - mmengine - INFO - Epoch(train) [54][240/940] lr: 1.0000e-03 eta: 6:14:41 time: 0.4782 data_time: 0.0249 memory: 17006 grad_norm: 4.3627 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3868 loss: 1.3868 2022/10/13 06:16:45 - mmengine - INFO - Epoch(train) [54][260/940] lr: 1.0000e-03 eta: 6:14:31 time: 0.5527 data_time: 0.0389 memory: 17006 grad_norm: 4.4554 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3654 loss: 1.3654 2022/10/13 06:16:54 - mmengine - INFO - Epoch(train) [54][280/940] lr: 1.0000e-03 eta: 6:14:20 time: 0.4625 data_time: 0.0260 memory: 17006 grad_norm: 4.4453 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2447 loss: 1.2447 2022/10/13 06:17:04 - mmengine - INFO - Epoch(train) [54][300/940] lr: 1.0000e-03 eta: 6:14:10 time: 0.5221 data_time: 0.0347 memory: 17006 grad_norm: 4.5101 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4297 loss: 1.4297 2022/10/13 06:17:14 - mmengine - INFO - Epoch(train) [54][320/940] lr: 1.0000e-03 eta: 6:13:59 time: 0.4814 data_time: 0.0269 memory: 17006 grad_norm: 4.4196 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2119 loss: 1.2119 2022/10/13 06:17:25 - mmengine - INFO - Epoch(train) [54][340/940] lr: 1.0000e-03 eta: 6:13:50 time: 0.5413 data_time: 0.0340 memory: 17006 grad_norm: 4.5118 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3029 loss: 1.3029 2022/10/13 06:17:34 - mmengine - INFO - Epoch(train) [54][360/940] lr: 1.0000e-03 eta: 6:13:39 time: 0.4752 data_time: 0.0270 memory: 17006 grad_norm: 4.3786 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3075 loss: 1.3075 2022/10/13 06:17:46 - mmengine - INFO - Epoch(train) [54][380/940] lr: 1.0000e-03 eta: 6:13:30 time: 0.5731 data_time: 0.0389 memory: 17006 grad_norm: 4.4677 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3239 loss: 1.3239 2022/10/13 06:17:55 - mmengine - INFO - Epoch(train) [54][400/940] lr: 1.0000e-03 eta: 6:13:18 time: 0.4560 data_time: 0.0257 memory: 17006 grad_norm: 4.5479 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3853 loss: 1.3853 2022/10/13 06:18:06 - mmengine - INFO - Epoch(train) [54][420/940] lr: 1.0000e-03 eta: 6:13:09 time: 0.5440 data_time: 0.0342 memory: 17006 grad_norm: 4.4286 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3773 loss: 1.3773 2022/10/13 06:18:15 - mmengine - INFO - Epoch(train) [54][440/940] lr: 1.0000e-03 eta: 6:12:58 time: 0.4733 data_time: 0.0273 memory: 17006 grad_norm: 4.4242 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4188 loss: 1.4188 2022/10/13 06:18:26 - mmengine - INFO - Epoch(train) [54][460/940] lr: 1.0000e-03 eta: 6:12:48 time: 0.5462 data_time: 0.0356 memory: 17006 grad_norm: 4.5436 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4035 loss: 1.4035 2022/10/13 06:18:36 - mmengine - INFO - Epoch(train) [54][480/940] lr: 1.0000e-03 eta: 6:12:38 time: 0.5067 data_time: 0.0258 memory: 17006 grad_norm: 4.4686 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2956 loss: 1.2956 2022/10/13 06:18:47 - mmengine - INFO - Epoch(train) [54][500/940] lr: 1.0000e-03 eta: 6:12:28 time: 0.5089 data_time: 0.0351 memory: 17006 grad_norm: 4.3570 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2408 loss: 1.2408 2022/10/13 06:18:56 - mmengine - INFO - Epoch(train) [54][520/940] lr: 1.0000e-03 eta: 6:12:17 time: 0.4801 data_time: 0.0253 memory: 17006 grad_norm: 4.4997 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3499 loss: 1.3499 2022/10/13 06:19:07 - mmengine - INFO - Epoch(train) [54][540/940] lr: 1.0000e-03 eta: 6:12:07 time: 0.5175 data_time: 0.0373 memory: 17006 grad_norm: 4.4842 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3566 loss: 1.3566 2022/10/13 06:19:15 - mmengine - INFO - Epoch(train) [54][560/940] lr: 1.0000e-03 eta: 6:11:55 time: 0.4404 data_time: 0.0312 memory: 17006 grad_norm: 4.4327 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.4607 loss: 1.4607 2022/10/13 06:19:26 - mmengine - INFO - Epoch(train) [54][580/940] lr: 1.0000e-03 eta: 6:11:45 time: 0.5258 data_time: 0.0345 memory: 17006 grad_norm: 4.4329 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3131 loss: 1.3131 2022/10/13 06:19:36 - mmengine - INFO - Epoch(train) [54][600/940] lr: 1.0000e-03 eta: 6:11:35 time: 0.4928 data_time: 0.0270 memory: 17006 grad_norm: 4.4542 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4489 loss: 1.4489 2022/10/13 06:19:47 - mmengine - INFO - Epoch(train) [54][620/940] lr: 1.0000e-03 eta: 6:11:25 time: 0.5530 data_time: 0.0355 memory: 17006 grad_norm: 4.4497 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4965 loss: 1.4965 2022/10/13 06:19:57 - mmengine - INFO - Epoch(train) [54][640/940] lr: 1.0000e-03 eta: 6:11:15 time: 0.5147 data_time: 0.0275 memory: 17006 grad_norm: 4.5233 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3714 loss: 1.3714 2022/10/13 06:20:08 - mmengine - INFO - Epoch(train) [54][660/940] lr: 1.0000e-03 eta: 6:11:05 time: 0.5416 data_time: 0.0300 memory: 17006 grad_norm: 4.4569 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3482 loss: 1.3482 2022/10/13 06:20:17 - mmengine - INFO - Epoch(train) [54][680/940] lr: 1.0000e-03 eta: 6:10:54 time: 0.4667 data_time: 0.0274 memory: 17006 grad_norm: 4.4715 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2438 loss: 1.2438 2022/10/13 06:20:28 - mmengine - INFO - Epoch(train) [54][700/940] lr: 1.0000e-03 eta: 6:10:45 time: 0.5411 data_time: 0.0324 memory: 17006 grad_norm: 4.4297 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.4571 loss: 1.4571 2022/10/13 06:20:38 - mmengine - INFO - Epoch(train) [54][720/940] lr: 1.0000e-03 eta: 6:10:34 time: 0.5074 data_time: 0.0327 memory: 17006 grad_norm: 4.3704 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2748 loss: 1.2748 2022/10/13 06:20:48 - mmengine - INFO - Epoch(train) [54][740/940] lr: 1.0000e-03 eta: 6:10:24 time: 0.5049 data_time: 0.0304 memory: 17006 grad_norm: 4.3990 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3652 loss: 1.3652 2022/10/13 06:20:58 - mmengine - INFO - Epoch(train) [54][760/940] lr: 1.0000e-03 eta: 6:10:13 time: 0.4902 data_time: 0.0297 memory: 17006 grad_norm: 4.4673 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2717 loss: 1.2717 2022/10/13 06:21:08 - mmengine - INFO - Epoch(train) [54][780/940] lr: 1.0000e-03 eta: 6:10:03 time: 0.5018 data_time: 0.0322 memory: 17006 grad_norm: 4.3575 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3434 loss: 1.3434 2022/10/13 06:21:18 - mmengine - INFO - Epoch(train) [54][800/940] lr: 1.0000e-03 eta: 6:09:52 time: 0.4645 data_time: 0.0317 memory: 17006 grad_norm: 4.4236 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3245 loss: 1.3245 2022/10/13 06:21:27 - mmengine - INFO - Epoch(train) [54][820/940] lr: 1.0000e-03 eta: 6:09:41 time: 0.4929 data_time: 0.0357 memory: 17006 grad_norm: 4.4725 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4664 loss: 1.4664 2022/10/13 06:21:37 - mmengine - INFO - Epoch(train) [54][840/940] lr: 1.0000e-03 eta: 6:09:31 time: 0.4885 data_time: 0.0383 memory: 17006 grad_norm: 4.3818 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.4343 loss: 1.4343 2022/10/13 06:21:48 - mmengine - INFO - Epoch(train) [54][860/940] lr: 1.0000e-03 eta: 6:09:21 time: 0.5409 data_time: 0.0286 memory: 17006 grad_norm: 4.5278 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3374 loss: 1.3374 2022/10/13 06:21:59 - mmengine - INFO - Epoch(train) [54][880/940] lr: 1.0000e-03 eta: 6:09:11 time: 0.5311 data_time: 0.0379 memory: 17006 grad_norm: 4.4311 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2685 loss: 1.2685 2022/10/13 06:22:08 - mmengine - INFO - Epoch(train) [54][900/940] lr: 1.0000e-03 eta: 6:09:00 time: 0.4891 data_time: 0.0343 memory: 17006 grad_norm: 4.5792 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3745 loss: 1.3745 2022/10/13 06:22:19 - mmengine - INFO - Epoch(train) [54][920/940] lr: 1.0000e-03 eta: 6:08:50 time: 0.5112 data_time: 0.0253 memory: 17006 grad_norm: 4.3892 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2548 loss: 1.2548 2022/10/13 06:22:27 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 06:22:27 - mmengine - INFO - Epoch(train) [54][940/940] lr: 1.0000e-03 eta: 6:08:39 time: 0.4355 data_time: 0.0341 memory: 17006 grad_norm: 4.6866 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.3361 loss: 1.3361 2022/10/13 06:22:27 - mmengine - INFO - Saving checkpoint at 54 epochs 2022/10/13 06:22:41 - mmengine - INFO - Epoch(val) [54][20/78] eta: 0:00:36 time: 0.6237 data_time: 0.5322 memory: 3172 2022/10/13 06:22:49 - mmengine - INFO - Epoch(val) [54][40/78] eta: 0:00:16 time: 0.4299 data_time: 0.3398 memory: 3172 2022/10/13 06:23:01 - mmengine - INFO - Epoch(val) [54][60/78] eta: 0:00:10 time: 0.5814 data_time: 0.4912 memory: 3172 2022/10/13 06:23:10 - mmengine - INFO - Epoch(val) [54][78/78] acc/top1: 0.6710 acc/top5: 0.8677 acc/mean1: 0.6710 2022/10/13 06:23:24 - mmengine - INFO - Epoch(train) [55][20/940] lr: 1.0000e-03 eta: 6:08:32 time: 0.7179 data_time: 0.2186 memory: 17006 grad_norm: 4.6062 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.4169 loss: 1.4169 2022/10/13 06:23:34 - mmengine - INFO - Epoch(train) [55][40/940] lr: 1.0000e-03 eta: 6:08:21 time: 0.4699 data_time: 0.0298 memory: 17006 grad_norm: 4.4393 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2808 loss: 1.2808 2022/10/13 06:23:44 - mmengine - INFO - Epoch(train) [55][60/940] lr: 1.0000e-03 eta: 6:08:11 time: 0.5433 data_time: 0.0306 memory: 17006 grad_norm: 4.4603 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3441 loss: 1.3441 2022/10/13 06:23:54 - mmengine - INFO - Epoch(train) [55][80/940] lr: 1.0000e-03 eta: 6:08:00 time: 0.4557 data_time: 0.0247 memory: 17006 grad_norm: 4.4050 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.3114 loss: 1.3114 2022/10/13 06:24:05 - mmengine - INFO - Epoch(train) [55][100/940] lr: 1.0000e-03 eta: 6:07:51 time: 0.5497 data_time: 0.0325 memory: 17006 grad_norm: 4.3965 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4353 loss: 1.4353 2022/10/13 06:24:14 - mmengine - INFO - Epoch(train) [55][120/940] lr: 1.0000e-03 eta: 6:07:40 time: 0.4807 data_time: 0.0340 memory: 17006 grad_norm: 4.5585 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3588 loss: 1.3588 2022/10/13 06:24:25 - mmengine - INFO - Epoch(train) [55][140/940] lr: 1.0000e-03 eta: 6:07:30 time: 0.5373 data_time: 0.0289 memory: 17006 grad_norm: 4.4858 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.3343 loss: 1.3343 2022/10/13 06:24:35 - mmengine - INFO - Epoch(train) [55][160/940] lr: 1.0000e-03 eta: 6:07:19 time: 0.4793 data_time: 0.0329 memory: 17006 grad_norm: 4.4434 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3616 loss: 1.3616 2022/10/13 06:24:46 - mmengine - INFO - Epoch(train) [55][180/940] lr: 1.0000e-03 eta: 6:07:10 time: 0.5595 data_time: 0.0315 memory: 17006 grad_norm: 4.4206 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2186 loss: 1.2186 2022/10/13 06:24:54 - mmengine - INFO - Epoch(train) [55][200/940] lr: 1.0000e-03 eta: 6:06:58 time: 0.4379 data_time: 0.0321 memory: 17006 grad_norm: 4.3873 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3440 loss: 1.3440 2022/10/13 06:25:04 - mmengine - INFO - Epoch(train) [55][220/940] lr: 1.0000e-03 eta: 6:06:48 time: 0.4981 data_time: 0.0356 memory: 17006 grad_norm: 4.4644 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.4857 loss: 1.4857 2022/10/13 06:25:14 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 06:25:14 - mmengine - INFO - Epoch(train) [55][240/940] lr: 1.0000e-03 eta: 6:06:37 time: 0.4870 data_time: 0.0324 memory: 17006 grad_norm: 4.3940 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2480 loss: 1.2480 2022/10/13 06:25:25 - mmengine - INFO - Epoch(train) [55][260/940] lr: 1.0000e-03 eta: 6:06:27 time: 0.5343 data_time: 0.0306 memory: 17006 grad_norm: 4.4740 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5947 loss: 1.5947 2022/10/13 06:25:34 - mmengine - INFO - Epoch(train) [55][280/940] lr: 1.0000e-03 eta: 6:06:16 time: 0.4650 data_time: 0.0323 memory: 17006 grad_norm: 4.4610 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4161 loss: 1.4161 2022/10/13 06:25:45 - mmengine - INFO - Epoch(train) [55][300/940] lr: 1.0000e-03 eta: 6:06:07 time: 0.5640 data_time: 0.0364 memory: 17006 grad_norm: 4.4243 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3000 loss: 1.3000 2022/10/13 06:25:55 - mmengine - INFO - Epoch(train) [55][320/940] lr: 1.0000e-03 eta: 6:05:56 time: 0.4744 data_time: 0.0332 memory: 17006 grad_norm: 4.5010 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3876 loss: 1.3876 2022/10/13 06:26:05 - mmengine - INFO - Epoch(train) [55][340/940] lr: 1.0000e-03 eta: 6:05:46 time: 0.5172 data_time: 0.0350 memory: 17006 grad_norm: 4.4910 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2837 loss: 1.2837 2022/10/13 06:26:15 - mmengine - INFO - Epoch(train) [55][360/940] lr: 1.0000e-03 eta: 6:05:35 time: 0.4742 data_time: 0.0324 memory: 17006 grad_norm: 4.3200 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4824 loss: 1.4824 2022/10/13 06:26:26 - mmengine - INFO - Epoch(train) [55][380/940] lr: 1.0000e-03 eta: 6:05:26 time: 0.5757 data_time: 0.0362 memory: 17006 grad_norm: 4.4868 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3695 loss: 1.3695 2022/10/13 06:26:35 - mmengine - INFO - Epoch(train) [55][400/940] lr: 1.0000e-03 eta: 6:05:14 time: 0.4335 data_time: 0.0319 memory: 17006 grad_norm: 4.4346 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3760 loss: 1.3760 2022/10/13 06:26:46 - mmengine - INFO - Epoch(train) [55][420/940] lr: 1.0000e-03 eta: 6:05:05 time: 0.5530 data_time: 0.0292 memory: 17006 grad_norm: 4.4675 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.4646 loss: 1.4646 2022/10/13 06:26:55 - mmengine - INFO - Epoch(train) [55][440/940] lr: 1.0000e-03 eta: 6:04:54 time: 0.4681 data_time: 0.0300 memory: 17006 grad_norm: 4.5126 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4240 loss: 1.4240 2022/10/13 06:27:06 - mmengine - INFO - Epoch(train) [55][460/940] lr: 1.0000e-03 eta: 6:04:44 time: 0.5108 data_time: 0.0311 memory: 17006 grad_norm: 4.4793 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3180 loss: 1.3180 2022/10/13 06:27:15 - mmengine - INFO - Epoch(train) [55][480/940] lr: 1.0000e-03 eta: 6:04:33 time: 0.4766 data_time: 0.0358 memory: 17006 grad_norm: 4.4364 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.3604 loss: 1.3604 2022/10/13 06:27:26 - mmengine - INFO - Epoch(train) [55][500/940] lr: 1.0000e-03 eta: 6:04:23 time: 0.5319 data_time: 0.0293 memory: 17006 grad_norm: 4.5001 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3819 loss: 1.3819 2022/10/13 06:27:35 - mmengine - INFO - Epoch(train) [55][520/940] lr: 1.0000e-03 eta: 6:04:12 time: 0.4734 data_time: 0.0530 memory: 17006 grad_norm: 4.4437 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3095 loss: 1.3095 2022/10/13 06:27:46 - mmengine - INFO - Epoch(train) [55][540/940] lr: 1.0000e-03 eta: 6:04:02 time: 0.5210 data_time: 0.1061 memory: 17006 grad_norm: 4.4768 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3511 loss: 1.3511 2022/10/13 06:27:56 - mmengine - INFO - Epoch(train) [55][560/940] lr: 1.0000e-03 eta: 6:03:52 time: 0.5260 data_time: 0.1658 memory: 17006 grad_norm: 4.4763 top1_acc: 0.4062 top5_acc: 0.8438 loss_cls: 1.3787 loss: 1.3787 2022/10/13 06:28:06 - mmengine - INFO - Epoch(train) [55][580/940] lr: 1.0000e-03 eta: 6:03:42 time: 0.4967 data_time: 0.1311 memory: 17006 grad_norm: 4.5040 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2648 loss: 1.2648 2022/10/13 06:28:16 - mmengine - INFO - Epoch(train) [55][600/940] lr: 1.0000e-03 eta: 6:03:31 time: 0.4787 data_time: 0.1347 memory: 17006 grad_norm: 4.4647 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3800 loss: 1.3800 2022/10/13 06:28:27 - mmengine - INFO - Epoch(train) [55][620/940] lr: 1.0000e-03 eta: 6:03:21 time: 0.5541 data_time: 0.0248 memory: 17006 grad_norm: 4.5834 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3080 loss: 1.3080 2022/10/13 06:28:37 - mmengine - INFO - Epoch(train) [55][640/940] lr: 1.0000e-03 eta: 6:03:11 time: 0.4883 data_time: 0.0391 memory: 17006 grad_norm: 4.5415 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.5293 loss: 1.5293 2022/10/13 06:28:47 - mmengine - INFO - Epoch(train) [55][660/940] lr: 1.0000e-03 eta: 6:03:00 time: 0.5076 data_time: 0.0237 memory: 17006 grad_norm: 4.5661 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.3522 loss: 1.3522 2022/10/13 06:28:57 - mmengine - INFO - Epoch(train) [55][680/940] lr: 1.0000e-03 eta: 6:02:50 time: 0.5114 data_time: 0.1354 memory: 17006 grad_norm: 4.4815 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3451 loss: 1.3451 2022/10/13 06:29:07 - mmengine - INFO - Epoch(train) [55][700/940] lr: 1.0000e-03 eta: 6:02:40 time: 0.4900 data_time: 0.1387 memory: 17006 grad_norm: 4.5728 top1_acc: 0.4688 top5_acc: 0.8750 loss_cls: 1.4303 loss: 1.4303 2022/10/13 06:29:16 - mmengine - INFO - Epoch(train) [55][720/940] lr: 1.0000e-03 eta: 6:02:29 time: 0.4840 data_time: 0.1102 memory: 17006 grad_norm: 4.6328 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3574 loss: 1.3574 2022/10/13 06:29:27 - mmengine - INFO - Epoch(train) [55][740/940] lr: 1.0000e-03 eta: 6:02:19 time: 0.5153 data_time: 0.0422 memory: 17006 grad_norm: 4.5666 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2340 loss: 1.2340 2022/10/13 06:29:37 - mmengine - INFO - Epoch(train) [55][760/940] lr: 1.0000e-03 eta: 6:02:09 time: 0.5323 data_time: 0.1932 memory: 17006 grad_norm: 4.5060 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4332 loss: 1.4332 2022/10/13 06:29:47 - mmengine - INFO - Epoch(train) [55][780/940] lr: 1.0000e-03 eta: 6:01:58 time: 0.4812 data_time: 0.1333 memory: 17006 grad_norm: 4.4548 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2731 loss: 1.2731 2022/10/13 06:29:59 - mmengine - INFO - Epoch(train) [55][800/940] lr: 1.0000e-03 eta: 6:01:49 time: 0.5888 data_time: 0.2622 memory: 17006 grad_norm: 4.5010 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.3173 loss: 1.3173 2022/10/13 06:30:09 - mmengine - INFO - Epoch(train) [55][820/940] lr: 1.0000e-03 eta: 6:01:39 time: 0.4920 data_time: 0.1533 memory: 17006 grad_norm: 4.4893 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3633 loss: 1.3633 2022/10/13 06:30:20 - mmengine - INFO - Epoch(train) [55][840/940] lr: 1.0000e-03 eta: 6:01:29 time: 0.5499 data_time: 0.2260 memory: 17006 grad_norm: 4.4714 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4068 loss: 1.4068 2022/10/13 06:30:29 - mmengine - INFO - Epoch(train) [55][860/940] lr: 1.0000e-03 eta: 6:01:18 time: 0.4665 data_time: 0.1400 memory: 17006 grad_norm: 4.5637 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3700 loss: 1.3700 2022/10/13 06:30:39 - mmengine - INFO - Epoch(train) [55][880/940] lr: 1.0000e-03 eta: 6:01:08 time: 0.5012 data_time: 0.1689 memory: 17006 grad_norm: 4.4868 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3868 loss: 1.3868 2022/10/13 06:30:49 - mmengine - INFO - Epoch(train) [55][900/940] lr: 1.0000e-03 eta: 6:00:57 time: 0.4837 data_time: 0.1531 memory: 17006 grad_norm: 4.4396 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2886 loss: 1.2886 2022/10/13 06:30:59 - mmengine - INFO - Epoch(train) [55][920/940] lr: 1.0000e-03 eta: 6:00:47 time: 0.5130 data_time: 0.1661 memory: 17006 grad_norm: 4.5396 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.4820 loss: 1.4820 2022/10/13 06:31:08 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 06:31:08 - mmengine - INFO - Epoch(train) [55][940/940] lr: 1.0000e-03 eta: 6:00:35 time: 0.4338 data_time: 0.0713 memory: 17006 grad_norm: 4.7351 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.3803 loss: 1.3803 2022/10/13 06:31:20 - mmengine - INFO - Epoch(val) [55][20/78] eta: 0:00:36 time: 0.6244 data_time: 0.5310 memory: 3172 2022/10/13 06:31:29 - mmengine - INFO - Epoch(val) [55][40/78] eta: 0:00:16 time: 0.4363 data_time: 0.3431 memory: 3172 2022/10/13 06:31:40 - mmengine - INFO - Epoch(val) [55][60/78] eta: 0:00:10 time: 0.5808 data_time: 0.4906 memory: 3172 2022/10/13 06:31:50 - mmengine - INFO - Epoch(val) [55][78/78] acc/top1: 0.6712 acc/top5: 0.8686 acc/mean1: 0.6711 2022/10/13 06:32:04 - mmengine - INFO - Epoch(train) [56][20/940] lr: 1.0000e-03 eta: 6:00:28 time: 0.7065 data_time: 0.3752 memory: 17006 grad_norm: 4.4856 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3605 loss: 1.3605 2022/10/13 06:32:14 - mmengine - INFO - Epoch(train) [56][40/940] lr: 1.0000e-03 eta: 6:00:17 time: 0.4600 data_time: 0.1423 memory: 17006 grad_norm: 4.3662 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3261 loss: 1.3261 2022/10/13 06:32:25 - mmengine - INFO - Epoch(train) [56][60/940] lr: 1.0000e-03 eta: 6:00:08 time: 0.5708 data_time: 0.1681 memory: 17006 grad_norm: 4.4566 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2809 loss: 1.2809 2022/10/13 06:32:34 - mmengine - INFO - Epoch(train) [56][80/940] lr: 1.0000e-03 eta: 5:59:57 time: 0.4702 data_time: 0.0788 memory: 17006 grad_norm: 4.4359 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2732 loss: 1.2732 2022/10/13 06:32:46 - mmengine - INFO - Epoch(train) [56][100/940] lr: 1.0000e-03 eta: 5:59:48 time: 0.5658 data_time: 0.0768 memory: 17006 grad_norm: 4.5217 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5625 loss: 1.5625 2022/10/13 06:32:55 - mmengine - INFO - Epoch(train) [56][120/940] lr: 1.0000e-03 eta: 5:59:37 time: 0.4787 data_time: 0.0231 memory: 17006 grad_norm: 4.4711 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3113 loss: 1.3113 2022/10/13 06:33:06 - mmengine - INFO - Epoch(train) [56][140/940] lr: 1.0000e-03 eta: 5:59:27 time: 0.5286 data_time: 0.0420 memory: 17006 grad_norm: 4.5061 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4536 loss: 1.4536 2022/10/13 06:33:15 - mmengine - INFO - Epoch(train) [56][160/940] lr: 1.0000e-03 eta: 5:59:16 time: 0.4476 data_time: 0.0364 memory: 17006 grad_norm: 4.4893 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.3609 loss: 1.3609 2022/10/13 06:33:26 - mmengine - INFO - Epoch(train) [56][180/940] lr: 1.0000e-03 eta: 5:59:06 time: 0.5422 data_time: 0.0880 memory: 17006 grad_norm: 4.5318 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2767 loss: 1.2767 2022/10/13 06:33:36 - mmengine - INFO - Epoch(train) [56][200/940] lr: 1.0000e-03 eta: 5:58:56 time: 0.5038 data_time: 0.1291 memory: 17006 grad_norm: 4.3998 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3219 loss: 1.3219 2022/10/13 06:33:47 - mmengine - INFO - Epoch(train) [56][220/940] lr: 1.0000e-03 eta: 5:58:46 time: 0.5533 data_time: 0.1630 memory: 17006 grad_norm: 4.5481 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3095 loss: 1.3095 2022/10/13 06:33:56 - mmengine - INFO - Epoch(train) [56][240/940] lr: 1.0000e-03 eta: 5:58:35 time: 0.4803 data_time: 0.1320 memory: 17006 grad_norm: 4.5054 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4038 loss: 1.4038 2022/10/13 06:34:07 - mmengine - INFO - Epoch(train) [56][260/940] lr: 1.0000e-03 eta: 5:58:26 time: 0.5474 data_time: 0.2197 memory: 17006 grad_norm: 4.5462 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4230 loss: 1.4230 2022/10/13 06:34:16 - mmengine - INFO - Epoch(train) [56][280/940] lr: 1.0000e-03 eta: 5:58:14 time: 0.4502 data_time: 0.1137 memory: 17006 grad_norm: 4.4602 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2754 loss: 1.2754 2022/10/13 06:34:28 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 06:34:28 - mmengine - INFO - Epoch(train) [56][300/940] lr: 1.0000e-03 eta: 5:58:05 time: 0.5608 data_time: 0.2351 memory: 17006 grad_norm: 4.5029 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.3511 loss: 1.3511 2022/10/13 06:34:37 - mmengine - INFO - Epoch(train) [56][320/940] lr: 1.0000e-03 eta: 5:57:54 time: 0.4629 data_time: 0.1453 memory: 17006 grad_norm: 4.4964 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3493 loss: 1.3493 2022/10/13 06:34:48 - mmengine - INFO - Epoch(train) [56][340/940] lr: 1.0000e-03 eta: 5:57:44 time: 0.5421 data_time: 0.1652 memory: 17006 grad_norm: 4.4964 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3370 loss: 1.3370 2022/10/13 06:34:57 - mmengine - INFO - Epoch(train) [56][360/940] lr: 1.0000e-03 eta: 5:57:33 time: 0.4492 data_time: 0.0843 memory: 17006 grad_norm: 4.5123 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4263 loss: 1.4263 2022/10/13 06:35:08 - mmengine - INFO - Epoch(train) [56][380/940] lr: 1.0000e-03 eta: 5:57:24 time: 0.5727 data_time: 0.2330 memory: 17006 grad_norm: 4.5292 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.3498 loss: 1.3498 2022/10/13 06:35:18 - mmengine - INFO - Epoch(train) [56][400/940] lr: 1.0000e-03 eta: 5:57:13 time: 0.4807 data_time: 0.1457 memory: 17006 grad_norm: 4.5137 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2947 loss: 1.2947 2022/10/13 06:35:28 - mmengine - INFO - Epoch(train) [56][420/940] lr: 1.0000e-03 eta: 5:57:03 time: 0.5113 data_time: 0.1849 memory: 17006 grad_norm: 4.4917 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.3269 loss: 1.3269 2022/10/13 06:35:37 - mmengine - INFO - Epoch(train) [56][440/940] lr: 1.0000e-03 eta: 5:56:52 time: 0.4690 data_time: 0.1161 memory: 17006 grad_norm: 4.4575 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.4223 loss: 1.4223 2022/10/13 06:35:48 - mmengine - INFO - Epoch(train) [56][460/940] lr: 1.0000e-03 eta: 5:56:42 time: 0.5481 data_time: 0.2194 memory: 17006 grad_norm: 4.6235 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.4155 loss: 1.4155 2022/10/13 06:35:58 - mmengine - INFO - Epoch(train) [56][480/940] lr: 1.0000e-03 eta: 5:56:32 time: 0.4937 data_time: 0.1619 memory: 17006 grad_norm: 4.6955 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5206 loss: 1.5206 2022/10/13 06:36:10 - mmengine - INFO - Epoch(train) [56][500/940] lr: 1.0000e-03 eta: 5:56:23 time: 0.5931 data_time: 0.2653 memory: 17006 grad_norm: 4.5233 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3372 loss: 1.3372 2022/10/13 06:36:19 - mmengine - INFO - Epoch(train) [56][520/940] lr: 1.0000e-03 eta: 5:56:12 time: 0.4623 data_time: 0.1250 memory: 17006 grad_norm: 4.5503 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3297 loss: 1.3297 2022/10/13 06:36:29 - mmengine - INFO - Epoch(train) [56][540/940] lr: 1.0000e-03 eta: 5:56:01 time: 0.5067 data_time: 0.1787 memory: 17006 grad_norm: 4.4625 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4157 loss: 1.4157 2022/10/13 06:36:39 - mmengine - INFO - Epoch(train) [56][560/940] lr: 1.0000e-03 eta: 5:55:50 time: 0.4653 data_time: 0.1134 memory: 17006 grad_norm: 4.5737 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.4395 loss: 1.4395 2022/10/13 06:36:49 - mmengine - INFO - Epoch(train) [56][580/940] lr: 1.0000e-03 eta: 5:55:40 time: 0.5265 data_time: 0.0390 memory: 17006 grad_norm: 4.5241 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5183 loss: 1.5183 2022/10/13 06:37:00 - mmengine - INFO - Epoch(train) [56][600/940] lr: 1.0000e-03 eta: 5:55:31 time: 0.5461 data_time: 0.0303 memory: 17006 grad_norm: 4.4502 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4699 loss: 1.4699 2022/10/13 06:37:10 - mmengine - INFO - Epoch(train) [56][620/940] lr: 1.0000e-03 eta: 5:55:20 time: 0.4803 data_time: 0.0389 memory: 17006 grad_norm: 4.6271 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4278 loss: 1.4278 2022/10/13 06:37:20 - mmengine - INFO - Epoch(train) [56][640/940] lr: 1.0000e-03 eta: 5:55:10 time: 0.4931 data_time: 0.0296 memory: 17006 grad_norm: 4.5171 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4284 loss: 1.4284 2022/10/13 06:37:29 - mmengine - INFO - Epoch(train) [56][660/940] lr: 1.0000e-03 eta: 5:54:59 time: 0.4634 data_time: 0.0504 memory: 17006 grad_norm: 4.4565 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2314 loss: 1.2314 2022/10/13 06:37:40 - mmengine - INFO - Epoch(train) [56][680/940] lr: 1.0000e-03 eta: 5:54:49 time: 0.5630 data_time: 0.0295 memory: 17006 grad_norm: 4.5200 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3507 loss: 1.3507 2022/10/13 06:37:50 - mmengine - INFO - Epoch(train) [56][700/940] lr: 1.0000e-03 eta: 5:54:39 time: 0.4922 data_time: 0.0504 memory: 17006 grad_norm: 4.5780 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2773 loss: 1.2773 2022/10/13 06:38:01 - mmengine - INFO - Epoch(train) [56][720/940] lr: 1.0000e-03 eta: 5:54:29 time: 0.5440 data_time: 0.0271 memory: 17006 grad_norm: 4.5327 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4174 loss: 1.4174 2022/10/13 06:38:09 - mmengine - INFO - Epoch(train) [56][740/940] lr: 1.0000e-03 eta: 5:54:17 time: 0.4304 data_time: 0.0357 memory: 17006 grad_norm: 4.4041 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3236 loss: 1.3236 2022/10/13 06:38:21 - mmengine - INFO - Epoch(train) [56][760/940] lr: 1.0000e-03 eta: 5:54:08 time: 0.5764 data_time: 0.0286 memory: 17006 grad_norm: 4.4801 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3819 loss: 1.3819 2022/10/13 06:38:30 - mmengine - INFO - Epoch(train) [56][780/940] lr: 1.0000e-03 eta: 5:53:57 time: 0.4542 data_time: 0.0371 memory: 17006 grad_norm: 4.5520 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4533 loss: 1.4533 2022/10/13 06:38:40 - mmengine - INFO - Epoch(train) [56][800/940] lr: 1.0000e-03 eta: 5:53:46 time: 0.4773 data_time: 0.0643 memory: 17006 grad_norm: 4.4787 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.4311 loss: 1.4311 2022/10/13 06:38:50 - mmengine - INFO - Epoch(train) [56][820/940] lr: 1.0000e-03 eta: 5:53:37 time: 0.5431 data_time: 0.2213 memory: 17006 grad_norm: 4.4461 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.2640 loss: 1.2640 2022/10/13 06:39:00 - mmengine - INFO - Epoch(train) [56][840/940] lr: 1.0000e-03 eta: 5:53:26 time: 0.4896 data_time: 0.1189 memory: 17006 grad_norm: 4.5298 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4217 loss: 1.4217 2022/10/13 06:39:11 - mmengine - INFO - Epoch(train) [56][860/940] lr: 1.0000e-03 eta: 5:53:16 time: 0.5318 data_time: 0.0937 memory: 17006 grad_norm: 4.4878 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3613 loss: 1.3613 2022/10/13 06:39:21 - mmengine - INFO - Epoch(train) [56][880/940] lr: 1.0000e-03 eta: 5:53:06 time: 0.5280 data_time: 0.0288 memory: 17006 grad_norm: 4.5077 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4137 loss: 1.4137 2022/10/13 06:39:31 - mmengine - INFO - Epoch(train) [56][900/940] lr: 1.0000e-03 eta: 5:52:55 time: 0.4842 data_time: 0.0445 memory: 17006 grad_norm: 4.5014 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3443 loss: 1.3443 2022/10/13 06:39:42 - mmengine - INFO - Epoch(train) [56][920/940] lr: 1.0000e-03 eta: 5:52:45 time: 0.5233 data_time: 0.0259 memory: 17006 grad_norm: 4.5232 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2736 loss: 1.2736 2022/10/13 06:39:50 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 06:39:50 - mmengine - INFO - Epoch(train) [56][940/940] lr: 1.0000e-03 eta: 5:52:34 time: 0.4418 data_time: 0.0262 memory: 17006 grad_norm: 4.6143 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.4131 loss: 1.4131 2022/10/13 06:40:03 - mmengine - INFO - Epoch(val) [56][20/78] eta: 0:00:36 time: 0.6231 data_time: 0.5285 memory: 3172 2022/10/13 06:40:12 - mmengine - INFO - Epoch(val) [56][40/78] eta: 0:00:16 time: 0.4336 data_time: 0.3424 memory: 3172 2022/10/13 06:40:23 - mmengine - INFO - Epoch(val) [56][60/78] eta: 0:00:10 time: 0.5771 data_time: 0.4849 memory: 3172 2022/10/13 06:40:33 - mmengine - INFO - Epoch(val) [56][78/78] acc/top1: 0.6719 acc/top5: 0.8679 acc/mean1: 0.6718 2022/10/13 06:40:47 - mmengine - INFO - Epoch(train) [57][20/940] lr: 1.0000e-03 eta: 5:52:27 time: 0.6972 data_time: 0.3324 memory: 17006 grad_norm: 4.5340 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2939 loss: 1.2939 2022/10/13 06:40:57 - mmengine - INFO - Epoch(train) [57][40/940] lr: 1.0000e-03 eta: 5:52:16 time: 0.5063 data_time: 0.0518 memory: 17006 grad_norm: 4.4191 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2881 loss: 1.2881 2022/10/13 06:41:08 - mmengine - INFO - Epoch(train) [57][60/940] lr: 1.0000e-03 eta: 5:52:07 time: 0.5606 data_time: 0.0351 memory: 17006 grad_norm: 4.4403 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3151 loss: 1.3151 2022/10/13 06:41:17 - mmengine - INFO - Epoch(train) [57][80/940] lr: 1.0000e-03 eta: 5:51:56 time: 0.4344 data_time: 0.0247 memory: 17006 grad_norm: 4.5452 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4644 loss: 1.4644 2022/10/13 06:41:28 - mmengine - INFO - Epoch(train) [57][100/940] lr: 1.0000e-03 eta: 5:51:45 time: 0.5196 data_time: 0.0340 memory: 17006 grad_norm: 4.4664 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3223 loss: 1.3223 2022/10/13 06:41:37 - mmengine - INFO - Epoch(train) [57][120/940] lr: 1.0000e-03 eta: 5:51:34 time: 0.4667 data_time: 0.0324 memory: 17006 grad_norm: 4.4525 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4536 loss: 1.4536 2022/10/13 06:41:48 - mmengine - INFO - Epoch(train) [57][140/940] lr: 1.0000e-03 eta: 5:51:25 time: 0.5333 data_time: 0.0366 memory: 17006 grad_norm: 4.5149 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2944 loss: 1.2944 2022/10/13 06:41:57 - mmengine - INFO - Epoch(train) [57][160/940] lr: 1.0000e-03 eta: 5:51:14 time: 0.4903 data_time: 0.0292 memory: 17006 grad_norm: 4.4747 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3149 loss: 1.3149 2022/10/13 06:42:09 - mmengine - INFO - Epoch(train) [57][180/940] lr: 1.0000e-03 eta: 5:51:05 time: 0.5671 data_time: 0.0342 memory: 17006 grad_norm: 4.4542 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2788 loss: 1.2788 2022/10/13 06:42:18 - mmengine - INFO - Epoch(train) [57][200/940] lr: 1.0000e-03 eta: 5:50:54 time: 0.4710 data_time: 0.0541 memory: 17006 grad_norm: 4.4402 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2550 loss: 1.2550 2022/10/13 06:42:30 - mmengine - INFO - Epoch(train) [57][220/940] lr: 1.0000e-03 eta: 5:50:45 time: 0.5771 data_time: 0.0270 memory: 17006 grad_norm: 4.5271 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.4358 loss: 1.4358 2022/10/13 06:42:39 - mmengine - INFO - Epoch(train) [57][240/940] lr: 1.0000e-03 eta: 5:50:34 time: 0.4806 data_time: 0.0342 memory: 17006 grad_norm: 4.5164 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3658 loss: 1.3658 2022/10/13 06:42:50 - mmengine - INFO - Epoch(train) [57][260/940] lr: 1.0000e-03 eta: 5:50:24 time: 0.5281 data_time: 0.0294 memory: 17006 grad_norm: 4.5139 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4218 loss: 1.4218 2022/10/13 06:42:59 - mmengine - INFO - Epoch(train) [57][280/940] lr: 1.0000e-03 eta: 5:50:13 time: 0.4733 data_time: 0.0386 memory: 17006 grad_norm: 4.5807 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3451 loss: 1.3451 2022/10/13 06:43:10 - mmengine - INFO - Epoch(train) [57][300/940] lr: 1.0000e-03 eta: 5:50:04 time: 0.5560 data_time: 0.0255 memory: 17006 grad_norm: 4.6148 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4155 loss: 1.4155 2022/10/13 06:43:20 - mmengine - INFO - Epoch(train) [57][320/940] lr: 1.0000e-03 eta: 5:49:53 time: 0.5011 data_time: 0.0380 memory: 17006 grad_norm: 4.4607 top1_acc: 0.7188 top5_acc: 0.7500 loss_cls: 1.2613 loss: 1.2613 2022/10/13 06:43:31 - mmengine - INFO - Epoch(train) [57][340/940] lr: 1.0000e-03 eta: 5:49:43 time: 0.5319 data_time: 0.0312 memory: 17006 grad_norm: 4.5753 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.3221 loss: 1.3221 2022/10/13 06:43:41 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 06:43:41 - mmengine - INFO - Epoch(train) [57][360/940] lr: 1.0000e-03 eta: 5:49:32 time: 0.4746 data_time: 0.0370 memory: 17006 grad_norm: 4.5094 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2240 loss: 1.2240 2022/10/13 06:43:51 - mmengine - INFO - Epoch(train) [57][380/940] lr: 1.0000e-03 eta: 5:49:23 time: 0.5440 data_time: 0.0301 memory: 17006 grad_norm: 4.5234 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2711 loss: 1.2711 2022/10/13 06:44:00 - mmengine - INFO - Epoch(train) [57][400/940] lr: 1.0000e-03 eta: 5:49:11 time: 0.4239 data_time: 0.0307 memory: 17006 grad_norm: 4.4718 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3324 loss: 1.3324 2022/10/13 06:44:11 - mmengine - INFO - Epoch(train) [57][420/940] lr: 1.0000e-03 eta: 5:49:02 time: 0.5601 data_time: 0.0350 memory: 17006 grad_norm: 4.4718 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2996 loss: 1.2996 2022/10/13 06:44:21 - mmengine - INFO - Epoch(train) [57][440/940] lr: 1.0000e-03 eta: 5:48:51 time: 0.4707 data_time: 0.0523 memory: 17006 grad_norm: 4.4539 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3205 loss: 1.3205 2022/10/13 06:44:31 - mmengine - INFO - Epoch(train) [57][460/940] lr: 1.0000e-03 eta: 5:48:41 time: 0.5222 data_time: 0.1482 memory: 17006 grad_norm: 4.4941 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2392 loss: 1.2392 2022/10/13 06:44:41 - mmengine - INFO - Epoch(train) [57][480/940] lr: 1.0000e-03 eta: 5:48:30 time: 0.4903 data_time: 0.0859 memory: 17006 grad_norm: 4.4896 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3036 loss: 1.3036 2022/10/13 06:44:51 - mmengine - INFO - Epoch(train) [57][500/940] lr: 1.0000e-03 eta: 5:48:20 time: 0.4961 data_time: 0.0626 memory: 17006 grad_norm: 4.4953 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2611 loss: 1.2611 2022/10/13 06:45:01 - mmengine - INFO - Epoch(train) [57][520/940] lr: 1.0000e-03 eta: 5:48:10 time: 0.5158 data_time: 0.1437 memory: 17006 grad_norm: 4.5447 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.4435 loss: 1.4435 2022/10/13 06:45:12 - mmengine - INFO - Epoch(train) [57][540/940] lr: 1.0000e-03 eta: 5:48:00 time: 0.5354 data_time: 0.1617 memory: 17006 grad_norm: 4.5288 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3475 loss: 1.3475 2022/10/13 06:45:23 - mmengine - INFO - Epoch(train) [57][560/940] lr: 1.0000e-03 eta: 5:47:50 time: 0.5498 data_time: 0.2114 memory: 17006 grad_norm: 4.4865 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4393 loss: 1.4393 2022/10/13 06:45:32 - mmengine - INFO - Epoch(train) [57][580/940] lr: 1.0000e-03 eta: 5:47:39 time: 0.4710 data_time: 0.1266 memory: 17006 grad_norm: 4.5098 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4902 loss: 1.4902 2022/10/13 06:45:43 - mmengine - INFO - Epoch(train) [57][600/940] lr: 1.0000e-03 eta: 5:47:29 time: 0.5204 data_time: 0.1860 memory: 17006 grad_norm: 4.5333 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2234 loss: 1.2234 2022/10/13 06:45:52 - mmengine - INFO - Epoch(train) [57][620/940] lr: 1.0000e-03 eta: 5:47:18 time: 0.4698 data_time: 0.1259 memory: 17006 grad_norm: 4.4725 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3404 loss: 1.3404 2022/10/13 06:46:03 - mmengine - INFO - Epoch(train) [57][640/940] lr: 1.0000e-03 eta: 5:47:09 time: 0.5620 data_time: 0.2286 memory: 17006 grad_norm: 4.5976 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3329 loss: 1.3329 2022/10/13 06:46:13 - mmengine - INFO - Epoch(train) [57][660/940] lr: 1.0000e-03 eta: 5:46:58 time: 0.4821 data_time: 0.1471 memory: 17006 grad_norm: 4.5524 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5309 loss: 1.5309 2022/10/13 06:46:23 - mmengine - INFO - Epoch(train) [57][680/940] lr: 1.0000e-03 eta: 5:46:48 time: 0.5035 data_time: 0.1803 memory: 17006 grad_norm: 4.5181 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3824 loss: 1.3824 2022/10/13 06:46:33 - mmengine - INFO - Epoch(train) [57][700/940] lr: 1.0000e-03 eta: 5:46:37 time: 0.4879 data_time: 0.1593 memory: 17006 grad_norm: 4.5579 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3866 loss: 1.3866 2022/10/13 06:46:44 - mmengine - INFO - Epoch(train) [57][720/940] lr: 1.0000e-03 eta: 5:46:28 time: 0.5672 data_time: 0.2534 memory: 17006 grad_norm: 4.4994 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4176 loss: 1.4176 2022/10/13 06:46:54 - mmengine - INFO - Epoch(train) [57][740/940] lr: 1.0000e-03 eta: 5:46:17 time: 0.5099 data_time: 0.1748 memory: 17006 grad_norm: 4.5017 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3034 loss: 1.3034 2022/10/13 06:47:06 - mmengine - INFO - Epoch(train) [57][760/940] lr: 1.0000e-03 eta: 5:46:08 time: 0.5661 data_time: 0.2400 memory: 17006 grad_norm: 4.4887 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3112 loss: 1.3112 2022/10/13 06:47:15 - mmengine - INFO - Epoch(train) [57][780/940] lr: 1.0000e-03 eta: 5:45:57 time: 0.4632 data_time: 0.1304 memory: 17006 grad_norm: 4.6197 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3382 loss: 1.3382 2022/10/13 06:47:25 - mmengine - INFO - Epoch(train) [57][800/940] lr: 1.0000e-03 eta: 5:45:47 time: 0.5221 data_time: 0.1903 memory: 17006 grad_norm: 4.6128 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4059 loss: 1.4059 2022/10/13 06:47:35 - mmengine - INFO - Epoch(train) [57][820/940] lr: 1.0000e-03 eta: 5:45:36 time: 0.4757 data_time: 0.1393 memory: 17006 grad_norm: 4.5290 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3035 loss: 1.3035 2022/10/13 06:47:45 - mmengine - INFO - Epoch(train) [57][840/940] lr: 1.0000e-03 eta: 5:45:26 time: 0.5295 data_time: 0.2039 memory: 17006 grad_norm: 4.6025 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2814 loss: 1.2814 2022/10/13 06:47:56 - mmengine - INFO - Epoch(train) [57][860/940] lr: 1.0000e-03 eta: 5:45:16 time: 0.5115 data_time: 0.1809 memory: 17006 grad_norm: 4.5350 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2858 loss: 1.2858 2022/10/13 06:48:06 - mmengine - INFO - Epoch(train) [57][880/940] lr: 1.0000e-03 eta: 5:45:06 time: 0.5161 data_time: 0.1897 memory: 17006 grad_norm: 4.5094 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3529 loss: 1.3529 2022/10/13 06:48:17 - mmengine - INFO - Epoch(train) [57][900/940] lr: 1.0000e-03 eta: 5:44:56 time: 0.5290 data_time: 0.1932 memory: 17006 grad_norm: 4.5052 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3911 loss: 1.3911 2022/10/13 06:48:27 - mmengine - INFO - Epoch(train) [57][920/940] lr: 1.0000e-03 eta: 5:44:46 time: 0.5295 data_time: 0.2003 memory: 17006 grad_norm: 4.5829 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3191 loss: 1.3191 2022/10/13 06:48:35 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 06:48:35 - mmengine - INFO - Epoch(train) [57][940/940] lr: 1.0000e-03 eta: 5:44:34 time: 0.4156 data_time: 0.1083 memory: 17006 grad_norm: 4.8257 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.2756 loss: 1.2756 2022/10/13 06:48:35 - mmengine - INFO - Saving checkpoint at 57 epochs 2022/10/13 06:48:49 - mmengine - INFO - Epoch(val) [57][20/78] eta: 0:00:36 time: 0.6324 data_time: 0.5411 memory: 3172 2022/10/13 06:48:57 - mmengine - INFO - Epoch(val) [57][40/78] eta: 0:00:16 time: 0.4243 data_time: 0.3341 memory: 3172 2022/10/13 06:49:09 - mmengine - INFO - Epoch(val) [57][60/78] eta: 0:00:10 time: 0.5876 data_time: 0.4961 memory: 3172 2022/10/13 06:49:18 - mmengine - INFO - Epoch(val) [57][78/78] acc/top1: 0.6715 acc/top5: 0.8682 acc/mean1: 0.6714 2022/10/13 06:49:32 - mmengine - INFO - Epoch(train) [58][20/940] lr: 1.0000e-03 eta: 5:44:27 time: 0.6746 data_time: 0.2573 memory: 17006 grad_norm: 4.5287 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3529 loss: 1.3529 2022/10/13 06:49:41 - mmengine - INFO - Epoch(train) [58][40/940] lr: 1.0000e-03 eta: 5:44:16 time: 0.4784 data_time: 0.0575 memory: 17006 grad_norm: 4.4858 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3593 loss: 1.3593 2022/10/13 06:49:52 - mmengine - INFO - Epoch(train) [58][60/940] lr: 1.0000e-03 eta: 5:44:06 time: 0.5568 data_time: 0.1633 memory: 17006 grad_norm: 4.5401 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2420 loss: 1.2420 2022/10/13 06:50:02 - mmengine - INFO - Epoch(train) [58][80/940] lr: 1.0000e-03 eta: 5:43:55 time: 0.4728 data_time: 0.0695 memory: 17006 grad_norm: 4.4766 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2422 loss: 1.2422 2022/10/13 06:50:12 - mmengine - INFO - Epoch(train) [58][100/940] lr: 1.0000e-03 eta: 5:43:45 time: 0.5292 data_time: 0.0357 memory: 17006 grad_norm: 4.5040 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4500 loss: 1.4500 2022/10/13 06:50:22 - mmengine - INFO - Epoch(train) [58][120/940] lr: 1.0000e-03 eta: 5:43:35 time: 0.4840 data_time: 0.0320 memory: 17006 grad_norm: 4.5250 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4531 loss: 1.4531 2022/10/13 06:50:33 - mmengine - INFO - Epoch(train) [58][140/940] lr: 1.0000e-03 eta: 5:43:25 time: 0.5440 data_time: 0.0611 memory: 17006 grad_norm: 4.4477 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2510 loss: 1.2510 2022/10/13 06:50:43 - mmengine - INFO - Epoch(train) [58][160/940] lr: 1.0000e-03 eta: 5:43:15 time: 0.4974 data_time: 0.0305 memory: 17006 grad_norm: 4.4839 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2869 loss: 1.2869 2022/10/13 06:50:54 - mmengine - INFO - Epoch(train) [58][180/940] lr: 1.0000e-03 eta: 5:43:05 time: 0.5438 data_time: 0.1582 memory: 17006 grad_norm: 4.6292 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4358 loss: 1.4358 2022/10/13 06:51:04 - mmengine - INFO - Epoch(train) [58][200/940] lr: 1.0000e-03 eta: 5:42:54 time: 0.4929 data_time: 0.0660 memory: 17006 grad_norm: 4.5759 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1839 loss: 1.1839 2022/10/13 06:51:15 - mmengine - INFO - Epoch(train) [58][220/940] lr: 1.0000e-03 eta: 5:42:45 time: 0.5403 data_time: 0.1397 memory: 17006 grad_norm: 4.4870 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3481 loss: 1.3481 2022/10/13 06:51:24 - mmengine - INFO - Epoch(train) [58][240/940] lr: 1.0000e-03 eta: 5:42:34 time: 0.4960 data_time: 0.1593 memory: 17006 grad_norm: 4.4110 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2040 loss: 1.2040 2022/10/13 06:51:36 - mmengine - INFO - Epoch(train) [58][260/940] lr: 1.0000e-03 eta: 5:42:25 time: 0.5558 data_time: 0.2079 memory: 17006 grad_norm: 4.5343 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3229 loss: 1.3229 2022/10/13 06:51:46 - mmengine - INFO - Epoch(train) [58][280/940] lr: 1.0000e-03 eta: 5:42:14 time: 0.5050 data_time: 0.1679 memory: 17006 grad_norm: 4.5873 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.4559 loss: 1.4559 2022/10/13 06:51:56 - mmengine - INFO - Epoch(train) [58][300/940] lr: 1.0000e-03 eta: 5:42:04 time: 0.5115 data_time: 0.1878 memory: 17006 grad_norm: 4.5295 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3002 loss: 1.3002 2022/10/13 06:52:05 - mmengine - INFO - Epoch(train) [58][320/940] lr: 1.0000e-03 eta: 5:41:53 time: 0.4379 data_time: 0.1010 memory: 17006 grad_norm: 4.5967 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3183 loss: 1.3183 2022/10/13 06:52:15 - mmengine - INFO - Epoch(train) [58][340/940] lr: 1.0000e-03 eta: 5:41:43 time: 0.5331 data_time: 0.2069 memory: 17006 grad_norm: 4.5440 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4502 loss: 1.4502 2022/10/13 06:52:24 - mmengine - INFO - Epoch(train) [58][360/940] lr: 1.0000e-03 eta: 5:41:32 time: 0.4424 data_time: 0.1121 memory: 17006 grad_norm: 4.5690 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3623 loss: 1.3623 2022/10/13 06:52:35 - mmengine - INFO - Epoch(train) [58][380/940] lr: 1.0000e-03 eta: 5:41:22 time: 0.5322 data_time: 0.2157 memory: 17006 grad_norm: 4.5625 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3919 loss: 1.3919 2022/10/13 06:52:44 - mmengine - INFO - Epoch(train) [58][400/940] lr: 1.0000e-03 eta: 5:41:11 time: 0.4764 data_time: 0.1446 memory: 17006 grad_norm: 4.5719 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2916 loss: 1.2916 2022/10/13 06:52:55 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 06:52:55 - mmengine - INFO - Epoch(train) [58][420/940] lr: 1.0000e-03 eta: 5:41:01 time: 0.5420 data_time: 0.2244 memory: 17006 grad_norm: 4.6258 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3774 loss: 1.3774 2022/10/13 06:53:05 - mmengine - INFO - Epoch(train) [58][440/940] lr: 1.0000e-03 eta: 5:40:50 time: 0.4783 data_time: 0.1510 memory: 17006 grad_norm: 4.5928 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4053 loss: 1.4053 2022/10/13 06:53:15 - mmengine - INFO - Epoch(train) [58][460/940] lr: 1.0000e-03 eta: 5:40:40 time: 0.5175 data_time: 0.1870 memory: 17006 grad_norm: 4.5015 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.5788 loss: 1.5788 2022/10/13 06:53:25 - mmengine - INFO - Epoch(train) [58][480/940] lr: 1.0000e-03 eta: 5:40:30 time: 0.4912 data_time: 0.1286 memory: 17006 grad_norm: 4.4664 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.4445 loss: 1.4445 2022/10/13 06:53:35 - mmengine - INFO - Epoch(train) [58][500/940] lr: 1.0000e-03 eta: 5:40:19 time: 0.5139 data_time: 0.1474 memory: 17006 grad_norm: 4.4581 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3060 loss: 1.3060 2022/10/13 06:53:45 - mmengine - INFO - Epoch(train) [58][520/940] lr: 1.0000e-03 eta: 5:40:09 time: 0.5115 data_time: 0.1796 memory: 17006 grad_norm: 4.5247 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3469 loss: 1.3469 2022/10/13 06:53:56 - mmengine - INFO - Epoch(train) [58][540/940] lr: 1.0000e-03 eta: 5:39:59 time: 0.5096 data_time: 0.1478 memory: 17006 grad_norm: 4.5175 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4056 loss: 1.4056 2022/10/13 06:54:05 - mmengine - INFO - Epoch(train) [58][560/940] lr: 1.0000e-03 eta: 5:39:48 time: 0.4751 data_time: 0.1229 memory: 17006 grad_norm: 4.6006 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3281 loss: 1.3281 2022/10/13 06:54:16 - mmengine - INFO - Epoch(train) [58][580/940] lr: 1.0000e-03 eta: 5:39:39 time: 0.5606 data_time: 0.0467 memory: 17006 grad_norm: 4.5276 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.3187 loss: 1.3187 2022/10/13 06:54:26 - mmengine - INFO - Epoch(train) [58][600/940] lr: 1.0000e-03 eta: 5:39:28 time: 0.4658 data_time: 0.0300 memory: 17006 grad_norm: 4.4918 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.2942 loss: 1.2942 2022/10/13 06:54:37 - mmengine - INFO - Epoch(train) [58][620/940] lr: 1.0000e-03 eta: 5:39:18 time: 0.5521 data_time: 0.0366 memory: 17006 grad_norm: 4.5472 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3930 loss: 1.3930 2022/10/13 06:54:46 - mmengine - INFO - Epoch(train) [58][640/940] lr: 1.0000e-03 eta: 5:39:07 time: 0.4568 data_time: 0.0280 memory: 17006 grad_norm: 4.5100 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3633 loss: 1.3633 2022/10/13 06:54:58 - mmengine - INFO - Epoch(train) [58][660/940] lr: 1.0000e-03 eta: 5:38:58 time: 0.5845 data_time: 0.0335 memory: 17006 grad_norm: 4.5568 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3806 loss: 1.3806 2022/10/13 06:55:07 - mmengine - INFO - Epoch(train) [58][680/940] lr: 1.0000e-03 eta: 5:38:47 time: 0.4833 data_time: 0.0300 memory: 17006 grad_norm: 4.5697 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4005 loss: 1.4005 2022/10/13 06:55:17 - mmengine - INFO - Epoch(train) [58][700/940] lr: 1.0000e-03 eta: 5:38:37 time: 0.5008 data_time: 0.0335 memory: 17006 grad_norm: 4.4828 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2912 loss: 1.2912 2022/10/13 06:55:26 - mmengine - INFO - Epoch(train) [58][720/940] lr: 1.0000e-03 eta: 5:38:26 time: 0.4387 data_time: 0.0333 memory: 17006 grad_norm: 4.5376 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2622 loss: 1.2622 2022/10/13 06:55:36 - mmengine - INFO - Epoch(train) [58][740/940] lr: 1.0000e-03 eta: 5:38:15 time: 0.5127 data_time: 0.0286 memory: 17006 grad_norm: 4.5531 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3764 loss: 1.3764 2022/10/13 06:55:47 - mmengine - INFO - Epoch(train) [58][760/940] lr: 1.0000e-03 eta: 5:38:05 time: 0.5104 data_time: 0.0362 memory: 17006 grad_norm: 4.5291 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2302 loss: 1.2302 2022/10/13 06:55:57 - mmengine - INFO - Epoch(train) [58][780/940] lr: 1.0000e-03 eta: 5:37:55 time: 0.5021 data_time: 0.0350 memory: 17006 grad_norm: 4.5204 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3416 loss: 1.3416 2022/10/13 06:56:06 - mmengine - INFO - Epoch(train) [58][800/940] lr: 1.0000e-03 eta: 5:37:44 time: 0.4718 data_time: 0.0242 memory: 17006 grad_norm: 4.6629 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3346 loss: 1.3346 2022/10/13 06:56:17 - mmengine - INFO - Epoch(train) [58][820/940] lr: 1.0000e-03 eta: 5:37:34 time: 0.5378 data_time: 0.0673 memory: 17006 grad_norm: 4.6279 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.4620 loss: 1.4620 2022/10/13 06:56:27 - mmengine - INFO - Epoch(train) [58][840/940] lr: 1.0000e-03 eta: 5:37:24 time: 0.4970 data_time: 0.0711 memory: 17006 grad_norm: 4.5330 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3168 loss: 1.3168 2022/10/13 06:56:38 - mmengine - INFO - Epoch(train) [58][860/940] lr: 1.0000e-03 eta: 5:37:14 time: 0.5590 data_time: 0.1988 memory: 17006 grad_norm: 4.5793 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3381 loss: 1.3381 2022/10/13 06:56:47 - mmengine - INFO - Epoch(train) [58][880/940] lr: 1.0000e-03 eta: 5:37:03 time: 0.4529 data_time: 0.1142 memory: 17006 grad_norm: 4.4646 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2755 loss: 1.2755 2022/10/13 06:56:58 - mmengine - INFO - Epoch(train) [58][900/940] lr: 1.0000e-03 eta: 5:36:54 time: 0.5653 data_time: 0.1979 memory: 17006 grad_norm: 4.5188 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.4538 loss: 1.4538 2022/10/13 06:57:07 - mmengine - INFO - Epoch(train) [58][920/940] lr: 1.0000e-03 eta: 5:36:43 time: 0.4599 data_time: 0.1212 memory: 17006 grad_norm: 4.5518 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3503 loss: 1.3503 2022/10/13 06:57:16 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 06:57:16 - mmengine - INFO - Epoch(train) [58][940/940] lr: 1.0000e-03 eta: 5:36:31 time: 0.4292 data_time: 0.1237 memory: 17006 grad_norm: 4.7910 top1_acc: 0.1429 top5_acc: 0.7143 loss_cls: 1.3994 loss: 1.3994 2022/10/13 06:57:29 - mmengine - INFO - Epoch(val) [58][20/78] eta: 0:00:36 time: 0.6355 data_time: 0.5413 memory: 3172 2022/10/13 06:57:38 - mmengine - INFO - Epoch(val) [58][40/78] eta: 0:00:16 time: 0.4438 data_time: 0.3516 memory: 3172 2022/10/13 06:57:49 - mmengine - INFO - Epoch(val) [58][60/78] eta: 0:00:10 time: 0.5640 data_time: 0.4721 memory: 3172 2022/10/13 06:57:59 - mmengine - INFO - Epoch(val) [58][78/78] acc/top1: 0.6729 acc/top5: 0.8683 acc/mean1: 0.6728 2022/10/13 06:57:59 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_52.pth is removed 2022/10/13 06:57:59 - mmengine - INFO - The best checkpoint with 0.6729 acc/top1 at 58 epoch is saved to best_acc/top1_epoch_58.pth. 2022/10/13 06:58:13 - mmengine - INFO - Epoch(train) [59][20/940] lr: 1.0000e-03 eta: 5:36:24 time: 0.6836 data_time: 0.3694 memory: 17006 grad_norm: 4.5674 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3286 loss: 1.3286 2022/10/13 06:58:23 - mmengine - INFO - Epoch(train) [59][40/940] lr: 1.0000e-03 eta: 5:36:13 time: 0.4828 data_time: 0.1494 memory: 17006 grad_norm: 4.4536 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3692 loss: 1.3692 2022/10/13 06:58:34 - mmengine - INFO - Epoch(train) [59][60/940] lr: 1.0000e-03 eta: 5:36:03 time: 0.5595 data_time: 0.0989 memory: 17006 grad_norm: 4.4698 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.3207 loss: 1.3207 2022/10/13 06:58:43 - mmengine - INFO - Epoch(train) [59][80/940] lr: 1.0000e-03 eta: 5:35:52 time: 0.4564 data_time: 0.0367 memory: 17006 grad_norm: 4.5031 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2001 loss: 1.2001 2022/10/13 06:58:54 - mmengine - INFO - Epoch(train) [59][100/940] lr: 1.0000e-03 eta: 5:35:43 time: 0.5465 data_time: 0.0473 memory: 17006 grad_norm: 4.4834 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4011 loss: 1.4011 2022/10/13 06:59:03 - mmengine - INFO - Epoch(train) [59][120/940] lr: 1.0000e-03 eta: 5:35:32 time: 0.4666 data_time: 0.0256 memory: 17006 grad_norm: 4.5086 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4663 loss: 1.4663 2022/10/13 06:59:14 - mmengine - INFO - Epoch(train) [59][140/940] lr: 1.0000e-03 eta: 5:35:22 time: 0.5646 data_time: 0.0333 memory: 17006 grad_norm: 4.4467 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3634 loss: 1.3634 2022/10/13 06:59:24 - mmengine - INFO - Epoch(train) [59][160/940] lr: 1.0000e-03 eta: 5:35:11 time: 0.4560 data_time: 0.0321 memory: 17006 grad_norm: 4.4843 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4172 loss: 1.4172 2022/10/13 06:59:34 - mmengine - INFO - Epoch(train) [59][180/940] lr: 1.0000e-03 eta: 5:35:01 time: 0.5371 data_time: 0.0311 memory: 17006 grad_norm: 4.5976 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4465 loss: 1.4465 2022/10/13 06:59:45 - mmengine - INFO - Epoch(train) [59][200/940] lr: 1.0000e-03 eta: 5:34:51 time: 0.5197 data_time: 0.0391 memory: 17006 grad_norm: 4.5253 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3440 loss: 1.3440 2022/10/13 06:59:55 - mmengine - INFO - Epoch(train) [59][220/940] lr: 1.0000e-03 eta: 5:34:41 time: 0.5208 data_time: 0.0342 memory: 17006 grad_norm: 4.5072 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3144 loss: 1.3144 2022/10/13 07:00:05 - mmengine - INFO - Epoch(train) [59][240/940] lr: 1.0000e-03 eta: 5:34:31 time: 0.4887 data_time: 0.0382 memory: 17006 grad_norm: 4.5150 top1_acc: 0.4375 top5_acc: 0.8125 loss_cls: 1.4058 loss: 1.4058 2022/10/13 07:00:15 - mmengine - INFO - Epoch(train) [59][260/940] lr: 1.0000e-03 eta: 5:34:20 time: 0.4839 data_time: 0.0271 memory: 17006 grad_norm: 4.5848 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3288 loss: 1.3288 2022/10/13 07:00:24 - mmengine - INFO - Epoch(train) [59][280/940] lr: 1.0000e-03 eta: 5:34:09 time: 0.4617 data_time: 0.0320 memory: 17006 grad_norm: 4.6850 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.3188 loss: 1.3188 2022/10/13 07:00:35 - mmengine - INFO - Epoch(train) [59][300/940] lr: 1.0000e-03 eta: 5:34:00 time: 0.5620 data_time: 0.0353 memory: 17006 grad_norm: 4.5517 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4143 loss: 1.4143 2022/10/13 07:00:45 - mmengine - INFO - Epoch(train) [59][320/940] lr: 1.0000e-03 eta: 5:33:49 time: 0.4859 data_time: 0.0392 memory: 17006 grad_norm: 4.5752 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.4187 loss: 1.4187 2022/10/13 07:00:56 - mmengine - INFO - Epoch(train) [59][340/940] lr: 1.0000e-03 eta: 5:33:39 time: 0.5548 data_time: 0.0271 memory: 17006 grad_norm: 4.4964 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3236 loss: 1.3236 2022/10/13 07:01:05 - mmengine - INFO - Epoch(train) [59][360/940] lr: 1.0000e-03 eta: 5:33:28 time: 0.4537 data_time: 0.0315 memory: 17006 grad_norm: 4.5572 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3446 loss: 1.3446 2022/10/13 07:01:15 - mmengine - INFO - Epoch(train) [59][380/940] lr: 1.0000e-03 eta: 5:33:18 time: 0.5096 data_time: 0.0347 memory: 17006 grad_norm: 4.5909 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5280 loss: 1.5280 2022/10/13 07:01:24 - mmengine - INFO - Epoch(train) [59][400/940] lr: 1.0000e-03 eta: 5:33:07 time: 0.4574 data_time: 0.0322 memory: 17006 grad_norm: 4.5871 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2904 loss: 1.2904 2022/10/13 07:01:35 - mmengine - INFO - Epoch(train) [59][420/940] lr: 1.0000e-03 eta: 5:32:57 time: 0.5537 data_time: 0.0296 memory: 17006 grad_norm: 4.5088 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3849 loss: 1.3849 2022/10/13 07:01:45 - mmengine - INFO - Epoch(train) [59][440/940] lr: 1.0000e-03 eta: 5:32:47 time: 0.4800 data_time: 0.0345 memory: 17006 grad_norm: 4.6152 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3164 loss: 1.3164 2022/10/13 07:01:55 - mmengine - INFO - Epoch(train) [59][460/940] lr: 1.0000e-03 eta: 5:32:36 time: 0.4809 data_time: 0.0353 memory: 17006 grad_norm: 4.5444 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4532 loss: 1.4532 2022/10/13 07:02:05 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 07:02:05 - mmengine - INFO - Epoch(train) [59][480/940] lr: 1.0000e-03 eta: 5:32:26 time: 0.5183 data_time: 0.0356 memory: 17006 grad_norm: 4.4984 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1639 loss: 1.1639 2022/10/13 07:02:16 - mmengine - INFO - Epoch(train) [59][500/940] lr: 1.0000e-03 eta: 5:32:16 time: 0.5388 data_time: 0.0334 memory: 17006 grad_norm: 4.5049 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3103 loss: 1.3103 2022/10/13 07:02:26 - mmengine - INFO - Epoch(train) [59][520/940] lr: 1.0000e-03 eta: 5:32:06 time: 0.4950 data_time: 0.0337 memory: 17006 grad_norm: 4.6394 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4098 loss: 1.4098 2022/10/13 07:02:35 - mmengine - INFO - Epoch(train) [59][540/940] lr: 1.0000e-03 eta: 5:31:55 time: 0.4729 data_time: 0.0727 memory: 17006 grad_norm: 4.5468 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.4278 loss: 1.4278 2022/10/13 07:02:46 - mmengine - INFO - Epoch(train) [59][560/940] lr: 1.0000e-03 eta: 5:31:45 time: 0.5286 data_time: 0.1839 memory: 17006 grad_norm: 4.4855 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4249 loss: 1.4249 2022/10/13 07:02:56 - mmengine - INFO - Epoch(train) [59][580/940] lr: 1.0000e-03 eta: 5:31:35 time: 0.5145 data_time: 0.1136 memory: 17006 grad_norm: 4.4937 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3869 loss: 1.3869 2022/10/13 07:03:06 - mmengine - INFO - Epoch(train) [59][600/940] lr: 1.0000e-03 eta: 5:31:24 time: 0.5095 data_time: 0.0506 memory: 17006 grad_norm: 4.5655 top1_acc: 0.4062 top5_acc: 0.8438 loss_cls: 1.4017 loss: 1.4017 2022/10/13 07:03:17 - mmengine - INFO - Epoch(train) [59][620/940] lr: 1.0000e-03 eta: 5:31:14 time: 0.5243 data_time: 0.0796 memory: 17006 grad_norm: 4.5686 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.2867 loss: 1.2867 2022/10/13 07:03:27 - mmengine - INFO - Epoch(train) [59][640/940] lr: 1.0000e-03 eta: 5:31:04 time: 0.5230 data_time: 0.0916 memory: 17006 grad_norm: 4.4871 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4105 loss: 1.4105 2022/10/13 07:03:37 - mmengine - INFO - Epoch(train) [59][660/940] lr: 1.0000e-03 eta: 5:30:54 time: 0.4850 data_time: 0.0322 memory: 17006 grad_norm: 4.5710 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3559 loss: 1.3559 2022/10/13 07:03:49 - mmengine - INFO - Epoch(train) [59][680/940] lr: 1.0000e-03 eta: 5:30:45 time: 0.5929 data_time: 0.0302 memory: 17006 grad_norm: 4.5002 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.3721 loss: 1.3721 2022/10/13 07:03:59 - mmengine - INFO - Epoch(train) [59][700/940] lr: 1.0000e-03 eta: 5:30:34 time: 0.4926 data_time: 0.0315 memory: 17006 grad_norm: 4.4847 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3983 loss: 1.3983 2022/10/13 07:04:08 - mmengine - INFO - Epoch(train) [59][720/940] lr: 1.0000e-03 eta: 5:30:23 time: 0.4836 data_time: 0.0288 memory: 17006 grad_norm: 4.6729 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4543 loss: 1.4543 2022/10/13 07:04:17 - mmengine - INFO - Epoch(train) [59][740/940] lr: 1.0000e-03 eta: 5:30:13 time: 0.4655 data_time: 0.0312 memory: 17006 grad_norm: 4.5720 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.3017 loss: 1.3017 2022/10/13 07:04:29 - mmengine - INFO - Epoch(train) [59][760/940] lr: 1.0000e-03 eta: 5:30:03 time: 0.5638 data_time: 0.0324 memory: 17006 grad_norm: 4.5879 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2214 loss: 1.2214 2022/10/13 07:04:39 - mmengine - INFO - Epoch(train) [59][780/940] lr: 1.0000e-03 eta: 5:29:53 time: 0.4927 data_time: 0.0334 memory: 17006 grad_norm: 4.5551 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2907 loss: 1.2907 2022/10/13 07:04:49 - mmengine - INFO - Epoch(train) [59][800/940] lr: 1.0000e-03 eta: 5:29:43 time: 0.5303 data_time: 0.0310 memory: 17006 grad_norm: 4.5761 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.4111 loss: 1.4111 2022/10/13 07:04:59 - mmengine - INFO - Epoch(train) [59][820/940] lr: 1.0000e-03 eta: 5:29:32 time: 0.4694 data_time: 0.0334 memory: 17006 grad_norm: 4.5519 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4265 loss: 1.4265 2022/10/13 07:05:09 - mmengine - INFO - Epoch(train) [59][840/940] lr: 1.0000e-03 eta: 5:29:22 time: 0.5049 data_time: 0.0316 memory: 17006 grad_norm: 4.5853 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3436 loss: 1.3436 2022/10/13 07:05:19 - mmengine - INFO - Epoch(train) [59][860/940] lr: 1.0000e-03 eta: 5:29:11 time: 0.5128 data_time: 0.0366 memory: 17006 grad_norm: 4.5482 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3147 loss: 1.3147 2022/10/13 07:05:28 - mmengine - INFO - Epoch(train) [59][880/940] lr: 1.0000e-03 eta: 5:29:01 time: 0.4753 data_time: 0.0269 memory: 17006 grad_norm: 4.5689 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1913 loss: 1.1913 2022/10/13 07:05:38 - mmengine - INFO - Epoch(train) [59][900/940] lr: 1.0000e-03 eta: 5:28:50 time: 0.4816 data_time: 0.0322 memory: 17006 grad_norm: 4.5667 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4089 loss: 1.4089 2022/10/13 07:05:49 - mmengine - INFO - Epoch(train) [59][920/940] lr: 1.0000e-03 eta: 5:28:40 time: 0.5476 data_time: 0.0295 memory: 17006 grad_norm: 4.6249 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3896 loss: 1.3896 2022/10/13 07:05:58 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 07:05:58 - mmengine - INFO - Epoch(train) [59][940/940] lr: 1.0000e-03 eta: 5:28:29 time: 0.4300 data_time: 0.0306 memory: 17006 grad_norm: 4.7664 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.3353 loss: 1.3353 2022/10/13 07:06:11 - mmengine - INFO - Epoch(val) [59][20/78] eta: 0:00:36 time: 0.6364 data_time: 0.5444 memory: 3172 2022/10/13 07:06:19 - mmengine - INFO - Epoch(val) [59][40/78] eta: 0:00:16 time: 0.4347 data_time: 0.3431 memory: 3172 2022/10/13 07:06:31 - mmengine - INFO - Epoch(val) [59][60/78] eta: 0:00:10 time: 0.5660 data_time: 0.4755 memory: 3172 2022/10/13 07:06:40 - mmengine - INFO - Epoch(val) [59][78/78] acc/top1: 0.6722 acc/top5: 0.8692 acc/mean1: 0.6721 2022/10/13 07:06:54 - mmengine - INFO - Epoch(train) [60][20/940] lr: 1.0000e-03 eta: 5:28:21 time: 0.7041 data_time: 0.2647 memory: 17006 grad_norm: 4.5794 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3988 loss: 1.3988 2022/10/13 07:07:04 - mmengine - INFO - Epoch(train) [60][40/940] lr: 1.0000e-03 eta: 5:28:11 time: 0.4844 data_time: 0.0691 memory: 17006 grad_norm: 4.5366 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3290 loss: 1.3290 2022/10/13 07:07:15 - mmengine - INFO - Epoch(train) [60][60/940] lr: 1.0000e-03 eta: 5:28:01 time: 0.5461 data_time: 0.1219 memory: 17006 grad_norm: 4.5522 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.3710 loss: 1.3710 2022/10/13 07:07:25 - mmengine - INFO - Epoch(train) [60][80/940] lr: 1.0000e-03 eta: 5:27:50 time: 0.4943 data_time: 0.1671 memory: 17006 grad_norm: 4.5519 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.2154 loss: 1.2154 2022/10/13 07:07:36 - mmengine - INFO - Epoch(train) [60][100/940] lr: 1.0000e-03 eta: 5:27:41 time: 0.5708 data_time: 0.2406 memory: 17006 grad_norm: 4.5536 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3739 loss: 1.3739 2022/10/13 07:07:46 - mmengine - INFO - Epoch(train) [60][120/940] lr: 1.0000e-03 eta: 5:27:30 time: 0.4839 data_time: 0.1568 memory: 17006 grad_norm: 4.6805 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4525 loss: 1.4525 2022/10/13 07:07:56 - mmengine - INFO - Epoch(train) [60][140/940] lr: 1.0000e-03 eta: 5:27:20 time: 0.5156 data_time: 0.1887 memory: 17006 grad_norm: 4.5439 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3316 loss: 1.3316 2022/10/13 07:08:06 - mmengine - INFO - Epoch(train) [60][160/940] lr: 1.0000e-03 eta: 5:27:09 time: 0.4685 data_time: 0.1399 memory: 17006 grad_norm: 4.5870 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3443 loss: 1.3443 2022/10/13 07:08:16 - mmengine - INFO - Epoch(train) [60][180/940] lr: 1.0000e-03 eta: 5:26:59 time: 0.5229 data_time: 0.1874 memory: 17006 grad_norm: 4.5075 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3052 loss: 1.3052 2022/10/13 07:08:26 - mmengine - INFO - Epoch(train) [60][200/940] lr: 1.0000e-03 eta: 5:26:49 time: 0.5117 data_time: 0.1800 memory: 17006 grad_norm: 4.5649 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3743 loss: 1.3743 2022/10/13 07:08:38 - mmengine - INFO - Epoch(train) [60][220/940] lr: 1.0000e-03 eta: 5:26:40 time: 0.5612 data_time: 0.2247 memory: 17006 grad_norm: 4.5327 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2771 loss: 1.2771 2022/10/13 07:08:47 - mmengine - INFO - Epoch(train) [60][240/940] lr: 1.0000e-03 eta: 5:26:29 time: 0.4698 data_time: 0.1334 memory: 17006 grad_norm: 4.6363 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3040 loss: 1.3040 2022/10/13 07:08:57 - mmengine - INFO - Epoch(train) [60][260/940] lr: 1.0000e-03 eta: 5:26:19 time: 0.5212 data_time: 0.1941 memory: 17006 grad_norm: 4.5797 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3973 loss: 1.3973 2022/10/13 07:09:07 - mmengine - INFO - Epoch(train) [60][280/940] lr: 1.0000e-03 eta: 5:26:08 time: 0.4691 data_time: 0.1421 memory: 17006 grad_norm: 4.5672 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4752 loss: 1.4752 2022/10/13 07:09:16 - mmengine - INFO - Epoch(train) [60][300/940] lr: 1.0000e-03 eta: 5:25:57 time: 0.4648 data_time: 0.1386 memory: 17006 grad_norm: 4.5867 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.4400 loss: 1.4400 2022/10/13 07:09:26 - mmengine - INFO - Epoch(train) [60][320/940] lr: 1.0000e-03 eta: 5:25:46 time: 0.4812 data_time: 0.1526 memory: 17006 grad_norm: 4.5686 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3647 loss: 1.3647 2022/10/13 07:09:36 - mmengine - INFO - Epoch(train) [60][340/940] lr: 1.0000e-03 eta: 5:25:36 time: 0.5204 data_time: 0.1817 memory: 17006 grad_norm: 4.5947 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3179 loss: 1.3179 2022/10/13 07:09:46 - mmengine - INFO - Epoch(train) [60][360/940] lr: 1.0000e-03 eta: 5:25:26 time: 0.5058 data_time: 0.1239 memory: 17006 grad_norm: 4.6888 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.4165 loss: 1.4165 2022/10/13 07:09:57 - mmengine - INFO - Epoch(train) [60][380/940] lr: 1.0000e-03 eta: 5:25:16 time: 0.5192 data_time: 0.0786 memory: 17006 grad_norm: 4.5522 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3814 loss: 1.3814 2022/10/13 07:10:06 - mmengine - INFO - Epoch(train) [60][400/940] lr: 1.0000e-03 eta: 5:25:05 time: 0.4836 data_time: 0.0312 memory: 17006 grad_norm: 4.6516 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2948 loss: 1.2948 2022/10/13 07:10:17 - mmengine - INFO - Epoch(train) [60][420/940] lr: 1.0000e-03 eta: 5:24:55 time: 0.5444 data_time: 0.1182 memory: 17006 grad_norm: 4.5889 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3028 loss: 1.3028 2022/10/13 07:10:27 - mmengine - INFO - Epoch(train) [60][440/940] lr: 1.0000e-03 eta: 5:24:45 time: 0.4929 data_time: 0.0365 memory: 17006 grad_norm: 4.5227 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2969 loss: 1.2969 2022/10/13 07:10:38 - mmengine - INFO - Epoch(train) [60][460/940] lr: 1.0000e-03 eta: 5:24:35 time: 0.5521 data_time: 0.0318 memory: 17006 grad_norm: 4.6165 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2547 loss: 1.2547 2022/10/13 07:10:48 - mmengine - INFO - Epoch(train) [60][480/940] lr: 1.0000e-03 eta: 5:24:25 time: 0.4733 data_time: 0.0264 memory: 17006 grad_norm: 4.4496 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2470 loss: 1.2470 2022/10/13 07:10:58 - mmengine - INFO - Epoch(train) [60][500/940] lr: 1.0000e-03 eta: 5:24:14 time: 0.5207 data_time: 0.0295 memory: 17006 grad_norm: 4.5195 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.3811 loss: 1.3811 2022/10/13 07:11:07 - mmengine - INFO - Epoch(train) [60][520/940] lr: 1.0000e-03 eta: 5:24:04 time: 0.4702 data_time: 0.0374 memory: 17006 grad_norm: 4.6817 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.4309 loss: 1.4309 2022/10/13 07:11:18 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 07:11:18 - mmengine - INFO - Epoch(train) [60][540/940] lr: 1.0000e-03 eta: 5:23:53 time: 0.5123 data_time: 0.0347 memory: 17006 grad_norm: 4.6187 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4071 loss: 1.4071 2022/10/13 07:11:28 - mmengine - INFO - Epoch(train) [60][560/940] lr: 1.0000e-03 eta: 5:23:43 time: 0.5061 data_time: 0.0307 memory: 17006 grad_norm: 4.6035 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3854 loss: 1.3854 2022/10/13 07:11:38 - mmengine - INFO - Epoch(train) [60][580/940] lr: 1.0000e-03 eta: 5:23:33 time: 0.5163 data_time: 0.0336 memory: 17006 grad_norm: 4.5803 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4204 loss: 1.4204 2022/10/13 07:11:48 - mmengine - INFO - Epoch(train) [60][600/940] lr: 1.0000e-03 eta: 5:23:22 time: 0.4807 data_time: 0.0311 memory: 17006 grad_norm: 4.6147 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2829 loss: 1.2829 2022/10/13 07:11:59 - mmengine - INFO - Epoch(train) [60][620/940] lr: 1.0000e-03 eta: 5:23:13 time: 0.5716 data_time: 0.0343 memory: 17006 grad_norm: 4.4664 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2444 loss: 1.2444 2022/10/13 07:12:08 - mmengine - INFO - Epoch(train) [60][640/940] lr: 1.0000e-03 eta: 5:23:02 time: 0.4251 data_time: 0.0351 memory: 17006 grad_norm: 4.5354 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4322 loss: 1.4322 2022/10/13 07:12:19 - mmengine - INFO - Epoch(train) [60][660/940] lr: 1.0000e-03 eta: 5:22:52 time: 0.5699 data_time: 0.0376 memory: 17006 grad_norm: 4.6625 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.2787 loss: 1.2787 2022/10/13 07:12:28 - mmengine - INFO - Epoch(train) [60][680/940] lr: 1.0000e-03 eta: 5:22:41 time: 0.4478 data_time: 0.0289 memory: 17006 grad_norm: 4.5515 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3408 loss: 1.3408 2022/10/13 07:12:39 - mmengine - INFO - Epoch(train) [60][700/940] lr: 1.0000e-03 eta: 5:22:31 time: 0.5516 data_time: 0.0319 memory: 17006 grad_norm: 4.6720 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.4306 loss: 1.4306 2022/10/13 07:12:49 - mmengine - INFO - Epoch(train) [60][720/940] lr: 1.0000e-03 eta: 5:22:21 time: 0.4820 data_time: 0.0288 memory: 17006 grad_norm: 4.4781 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1304 loss: 1.1304 2022/10/13 07:12:59 - mmengine - INFO - Epoch(train) [60][740/940] lr: 1.0000e-03 eta: 5:22:11 time: 0.5298 data_time: 0.0333 memory: 17006 grad_norm: 4.6237 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3503 loss: 1.3503 2022/10/13 07:13:09 - mmengine - INFO - Epoch(train) [60][760/940] lr: 1.0000e-03 eta: 5:22:00 time: 0.5083 data_time: 0.0430 memory: 17006 grad_norm: 4.7119 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3880 loss: 1.3880 2022/10/13 07:13:20 - mmengine - INFO - Epoch(train) [60][780/940] lr: 1.0000e-03 eta: 5:21:50 time: 0.5167 data_time: 0.0398 memory: 17006 grad_norm: 4.6372 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.3617 loss: 1.3617 2022/10/13 07:13:30 - mmengine - INFO - Epoch(train) [60][800/940] lr: 1.0000e-03 eta: 5:21:40 time: 0.4967 data_time: 0.0334 memory: 17006 grad_norm: 4.6349 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3364 loss: 1.3364 2022/10/13 07:13:40 - mmengine - INFO - Epoch(train) [60][820/940] lr: 1.0000e-03 eta: 5:21:30 time: 0.5238 data_time: 0.0373 memory: 17006 grad_norm: 4.6368 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2759 loss: 1.2759 2022/10/13 07:13:50 - mmengine - INFO - Epoch(train) [60][840/940] lr: 1.0000e-03 eta: 5:21:20 time: 0.5160 data_time: 0.0341 memory: 17006 grad_norm: 4.5815 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4015 loss: 1.4015 2022/10/13 07:13:59 - mmengine - INFO - Epoch(train) [60][860/940] lr: 1.0000e-03 eta: 5:21:08 time: 0.4052 data_time: 0.0397 memory: 17006 grad_norm: 4.6297 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3308 loss: 1.3308 2022/10/13 07:14:11 - mmengine - INFO - Epoch(train) [60][880/940] lr: 1.0000e-03 eta: 5:20:59 time: 0.6005 data_time: 0.0296 memory: 17006 grad_norm: 4.6172 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2784 loss: 1.2784 2022/10/13 07:14:20 - mmengine - INFO - Epoch(train) [60][900/940] lr: 1.0000e-03 eta: 5:20:48 time: 0.4691 data_time: 0.0322 memory: 17006 grad_norm: 4.5764 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.3441 loss: 1.3441 2022/10/13 07:14:30 - mmengine - INFO - Epoch(train) [60][920/940] lr: 1.0000e-03 eta: 5:20:38 time: 0.5254 data_time: 0.0308 memory: 17006 grad_norm: 4.6287 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3083 loss: 1.3083 2022/10/13 07:14:39 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 07:14:39 - mmengine - INFO - Epoch(train) [60][940/940] lr: 1.0000e-03 eta: 5:20:27 time: 0.4309 data_time: 0.0266 memory: 17006 grad_norm: 4.9615 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.5311 loss: 1.5311 2022/10/13 07:14:39 - mmengine - INFO - Saving checkpoint at 60 epochs 2022/10/13 07:14:52 - mmengine - INFO - Epoch(val) [60][20/78] eta: 0:00:36 time: 0.6268 data_time: 0.5367 memory: 3172 2022/10/13 07:15:01 - mmengine - INFO - Epoch(val) [60][40/78] eta: 0:00:16 time: 0.4312 data_time: 0.3408 memory: 3172 2022/10/13 07:15:12 - mmengine - INFO - Epoch(val) [60][60/78] eta: 0:00:10 time: 0.5710 data_time: 0.4797 memory: 3172 2022/10/13 07:15:22 - mmengine - INFO - Epoch(val) [60][78/78] acc/top1: 0.6721 acc/top5: 0.8687 acc/mean1: 0.6719 2022/10/13 07:15:35 - mmengine - INFO - Epoch(train) [61][20/940] lr: 1.0000e-03 eta: 5:20:19 time: 0.6807 data_time: 0.2957 memory: 17006 grad_norm: 4.6434 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3197 loss: 1.3197 2022/10/13 07:15:45 - mmengine - INFO - Epoch(train) [61][40/940] lr: 1.0000e-03 eta: 5:20:08 time: 0.4786 data_time: 0.1107 memory: 17006 grad_norm: 4.5582 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4917 loss: 1.4917 2022/10/13 07:15:55 - mmengine - INFO - Epoch(train) [61][60/940] lr: 1.0000e-03 eta: 5:19:58 time: 0.5331 data_time: 0.0575 memory: 17006 grad_norm: 4.5996 top1_acc: 0.4062 top5_acc: 0.6250 loss_cls: 1.3827 loss: 1.3827 2022/10/13 07:16:05 - mmengine - INFO - Epoch(train) [61][80/940] lr: 1.0000e-03 eta: 5:19:48 time: 0.4810 data_time: 0.0566 memory: 17006 grad_norm: 4.5554 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3741 loss: 1.3741 2022/10/13 07:16:16 - mmengine - INFO - Epoch(train) [61][100/940] lr: 1.0000e-03 eta: 5:19:38 time: 0.5224 data_time: 0.0447 memory: 17006 grad_norm: 4.5738 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3981 loss: 1.3981 2022/10/13 07:16:26 - mmengine - INFO - Epoch(train) [61][120/940] lr: 1.0000e-03 eta: 5:19:27 time: 0.5195 data_time: 0.0309 memory: 17006 grad_norm: 4.6351 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.4810 loss: 1.4810 2022/10/13 07:16:37 - mmengine - INFO - Epoch(train) [61][140/940] lr: 1.0000e-03 eta: 5:19:18 time: 0.5467 data_time: 0.0344 memory: 17006 grad_norm: 4.5687 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3313 loss: 1.3313 2022/10/13 07:16:47 - mmengine - INFO - Epoch(train) [61][160/940] lr: 1.0000e-03 eta: 5:19:07 time: 0.4971 data_time: 0.0327 memory: 17006 grad_norm: 4.5889 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4343 loss: 1.4343 2022/10/13 07:16:57 - mmengine - INFO - Epoch(train) [61][180/940] lr: 1.0000e-03 eta: 5:18:57 time: 0.5265 data_time: 0.0315 memory: 17006 grad_norm: 4.5817 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3454 loss: 1.3454 2022/10/13 07:17:06 - mmengine - INFO - Epoch(train) [61][200/940] lr: 1.0000e-03 eta: 5:18:46 time: 0.4491 data_time: 0.0332 memory: 17006 grad_norm: 4.5662 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3332 loss: 1.3332 2022/10/13 07:17:17 - mmengine - INFO - Epoch(train) [61][220/940] lr: 1.0000e-03 eta: 5:18:37 time: 0.5563 data_time: 0.0317 memory: 17006 grad_norm: 4.6150 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3327 loss: 1.3327 2022/10/13 07:17:26 - mmengine - INFO - Epoch(train) [61][240/940] lr: 1.0000e-03 eta: 5:18:25 time: 0.4321 data_time: 0.0326 memory: 17006 grad_norm: 4.6087 top1_acc: 0.6875 top5_acc: 0.7188 loss_cls: 1.4726 loss: 1.4726 2022/10/13 07:17:37 - mmengine - INFO - Epoch(train) [61][260/940] lr: 1.0000e-03 eta: 5:18:15 time: 0.5394 data_time: 0.0309 memory: 17006 grad_norm: 4.6384 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3611 loss: 1.3611 2022/10/13 07:17:47 - mmengine - INFO - Epoch(train) [61][280/940] lr: 1.0000e-03 eta: 5:18:05 time: 0.4881 data_time: 0.0380 memory: 17006 grad_norm: 4.6796 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4430 loss: 1.4430 2022/10/13 07:17:58 - mmengine - INFO - Epoch(train) [61][300/940] lr: 1.0000e-03 eta: 5:17:55 time: 0.5529 data_time: 0.0309 memory: 17006 grad_norm: 4.5230 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2300 loss: 1.2300 2022/10/13 07:18:06 - mmengine - INFO - Epoch(train) [61][320/940] lr: 1.0000e-03 eta: 5:17:44 time: 0.4317 data_time: 0.0296 memory: 17006 grad_norm: 4.6510 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3112 loss: 1.3112 2022/10/13 07:18:17 - mmengine - INFO - Epoch(train) [61][340/940] lr: 1.0000e-03 eta: 5:17:34 time: 0.5189 data_time: 0.0339 memory: 17006 grad_norm: 4.6583 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3773 loss: 1.3773 2022/10/13 07:18:27 - mmengine - INFO - Epoch(train) [61][360/940] lr: 1.0000e-03 eta: 5:17:23 time: 0.5070 data_time: 0.0333 memory: 17006 grad_norm: 4.6206 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.4065 loss: 1.4065 2022/10/13 07:18:37 - mmengine - INFO - Epoch(train) [61][380/940] lr: 1.0000e-03 eta: 5:17:13 time: 0.5219 data_time: 0.0330 memory: 17006 grad_norm: 4.5558 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5279 loss: 1.5279 2022/10/13 07:18:49 - mmengine - INFO - Epoch(train) [61][400/940] lr: 1.0000e-03 eta: 5:17:04 time: 0.5596 data_time: 0.0336 memory: 17006 grad_norm: 4.5413 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3270 loss: 1.3270 2022/10/13 07:18:59 - mmengine - INFO - Epoch(train) [61][420/940] lr: 1.0000e-03 eta: 5:16:54 time: 0.5103 data_time: 0.0296 memory: 17006 grad_norm: 4.6043 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4520 loss: 1.4520 2022/10/13 07:19:09 - mmengine - INFO - Epoch(train) [61][440/940] lr: 1.0000e-03 eta: 5:16:43 time: 0.5227 data_time: 0.0352 memory: 17006 grad_norm: 4.5811 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2956 loss: 1.2956 2022/10/13 07:19:18 - mmengine - INFO - Epoch(train) [61][460/940] lr: 1.0000e-03 eta: 5:16:32 time: 0.4448 data_time: 0.0313 memory: 17006 grad_norm: 4.5586 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5063 loss: 1.5063 2022/10/13 07:19:30 - mmengine - INFO - Epoch(train) [61][480/940] lr: 1.0000e-03 eta: 5:16:23 time: 0.5725 data_time: 0.0334 memory: 17006 grad_norm: 4.5574 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3946 loss: 1.3946 2022/10/13 07:19:39 - mmengine - INFO - Epoch(train) [61][500/940] lr: 1.0000e-03 eta: 5:16:12 time: 0.4634 data_time: 0.0271 memory: 17006 grad_norm: 4.6250 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2959 loss: 1.2959 2022/10/13 07:19:50 - mmengine - INFO - Epoch(train) [61][520/940] lr: 1.0000e-03 eta: 5:16:02 time: 0.5516 data_time: 0.0346 memory: 17006 grad_norm: 4.6340 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3512 loss: 1.3512 2022/10/13 07:19:59 - mmengine - INFO - Epoch(train) [61][540/940] lr: 1.0000e-03 eta: 5:15:52 time: 0.4668 data_time: 0.0332 memory: 17006 grad_norm: 4.6503 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.3897 loss: 1.3897 2022/10/13 07:20:10 - mmengine - INFO - Epoch(train) [61][560/940] lr: 1.0000e-03 eta: 5:15:42 time: 0.5439 data_time: 0.0324 memory: 17006 grad_norm: 4.5900 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2173 loss: 1.2173 2022/10/13 07:20:19 - mmengine - INFO - Epoch(train) [61][580/940] lr: 1.0000e-03 eta: 5:15:31 time: 0.4556 data_time: 0.0315 memory: 17006 grad_norm: 4.6905 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4527 loss: 1.4527 2022/10/13 07:20:30 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 07:20:30 - mmengine - INFO - Epoch(train) [61][600/940] lr: 1.0000e-03 eta: 5:15:21 time: 0.5471 data_time: 0.0327 memory: 17006 grad_norm: 4.5903 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5193 loss: 1.5193 2022/10/13 07:20:39 - mmengine - INFO - Epoch(train) [61][620/940] lr: 1.0000e-03 eta: 5:15:10 time: 0.4673 data_time: 0.0299 memory: 17006 grad_norm: 4.6651 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3236 loss: 1.3236 2022/10/13 07:20:50 - mmengine - INFO - Epoch(train) [61][640/940] lr: 1.0000e-03 eta: 5:15:00 time: 0.5308 data_time: 0.0331 memory: 17006 grad_norm: 4.6291 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3473 loss: 1.3473 2022/10/13 07:21:00 - mmengine - INFO - Epoch(train) [61][660/940] lr: 1.0000e-03 eta: 5:14:50 time: 0.4912 data_time: 0.0340 memory: 17006 grad_norm: 4.5541 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4749 loss: 1.4749 2022/10/13 07:21:12 - mmengine - INFO - Epoch(train) [61][680/940] lr: 1.0000e-03 eta: 5:14:40 time: 0.5821 data_time: 0.0345 memory: 17006 grad_norm: 4.5043 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3150 loss: 1.3150 2022/10/13 07:21:20 - mmengine - INFO - Epoch(train) [61][700/940] lr: 1.0000e-03 eta: 5:14:29 time: 0.4146 data_time: 0.0360 memory: 17006 grad_norm: 4.4870 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4731 loss: 1.4731 2022/10/13 07:21:30 - mmengine - INFO - Epoch(train) [61][720/940] lr: 1.0000e-03 eta: 5:14:19 time: 0.5141 data_time: 0.0345 memory: 17006 grad_norm: 4.5957 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3555 loss: 1.3555 2022/10/13 07:21:39 - mmengine - INFO - Epoch(train) [61][740/940] lr: 1.0000e-03 eta: 5:14:08 time: 0.4623 data_time: 0.0349 memory: 17006 grad_norm: 4.5134 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2923 loss: 1.2923 2022/10/13 07:21:50 - mmengine - INFO - Epoch(train) [61][760/940] lr: 1.0000e-03 eta: 5:13:58 time: 0.5352 data_time: 0.0281 memory: 17006 grad_norm: 4.5879 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3344 loss: 1.3344 2022/10/13 07:22:00 - mmengine - INFO - Epoch(train) [61][780/940] lr: 1.0000e-03 eta: 5:13:47 time: 0.4870 data_time: 0.0363 memory: 17006 grad_norm: 4.6529 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2850 loss: 1.2850 2022/10/13 07:22:10 - mmengine - INFO - Epoch(train) [61][800/940] lr: 1.0000e-03 eta: 5:13:37 time: 0.5307 data_time: 0.0395 memory: 17006 grad_norm: 4.6698 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2478 loss: 1.2478 2022/10/13 07:22:21 - mmengine - INFO - Epoch(train) [61][820/940] lr: 1.0000e-03 eta: 5:13:27 time: 0.5076 data_time: 0.0376 memory: 17006 grad_norm: 4.6776 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3671 loss: 1.3671 2022/10/13 07:22:31 - mmengine - INFO - Epoch(train) [61][840/940] lr: 1.0000e-03 eta: 5:13:17 time: 0.5056 data_time: 0.0280 memory: 17006 grad_norm: 4.6161 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3107 loss: 1.3107 2022/10/13 07:22:41 - mmengine - INFO - Epoch(train) [61][860/940] lr: 1.0000e-03 eta: 5:13:07 time: 0.5294 data_time: 0.0391 memory: 17006 grad_norm: 4.6858 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.3804 loss: 1.3804 2022/10/13 07:22:52 - mmengine - INFO - Epoch(train) [61][880/940] lr: 1.0000e-03 eta: 5:12:57 time: 0.5300 data_time: 0.0291 memory: 17006 grad_norm: 4.4990 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3934 loss: 1.3934 2022/10/13 07:23:01 - mmengine - INFO - Epoch(train) [61][900/940] lr: 1.0000e-03 eta: 5:12:46 time: 0.4455 data_time: 0.0327 memory: 17006 grad_norm: 4.5744 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1385 loss: 1.1385 2022/10/13 07:23:11 - mmengine - INFO - Epoch(train) [61][920/940] lr: 1.0000e-03 eta: 5:12:36 time: 0.5071 data_time: 0.0332 memory: 17006 grad_norm: 4.5050 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.3243 loss: 1.3243 2022/10/13 07:23:20 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 07:23:20 - mmengine - INFO - Epoch(train) [61][940/940] lr: 1.0000e-03 eta: 5:12:25 time: 0.4487 data_time: 0.0271 memory: 17006 grad_norm: 4.9372 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.3475 loss: 1.3475 2022/10/13 07:23:33 - mmengine - INFO - Epoch(val) [61][20/78] eta: 0:00:37 time: 0.6386 data_time: 0.5440 memory: 3172 2022/10/13 07:23:41 - mmengine - INFO - Epoch(val) [61][40/78] eta: 0:00:16 time: 0.4250 data_time: 0.3343 memory: 3172 2022/10/13 07:23:53 - mmengine - INFO - Epoch(val) [61][60/78] eta: 0:00:10 time: 0.5689 data_time: 0.4769 memory: 3172 2022/10/13 07:24:03 - mmengine - INFO - Epoch(val) [61][78/78] acc/top1: 0.6713 acc/top5: 0.8696 acc/mean1: 0.6711 2022/10/13 07:24:17 - mmengine - INFO - Epoch(train) [62][20/940] lr: 1.0000e-03 eta: 5:12:17 time: 0.6904 data_time: 0.1983 memory: 17006 grad_norm: 4.5570 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.1451 loss: 1.1451 2022/10/13 07:24:26 - mmengine - INFO - Epoch(train) [62][40/940] lr: 1.0000e-03 eta: 5:12:06 time: 0.4869 data_time: 0.0264 memory: 17006 grad_norm: 4.6144 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.3687 loss: 1.3687 2022/10/13 07:24:37 - mmengine - INFO - Epoch(train) [62][60/940] lr: 1.0000e-03 eta: 5:11:56 time: 0.5455 data_time: 0.0323 memory: 17006 grad_norm: 4.5999 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3523 loss: 1.3523 2022/10/13 07:24:47 - mmengine - INFO - Epoch(train) [62][80/940] lr: 1.0000e-03 eta: 5:11:46 time: 0.4996 data_time: 0.0412 memory: 17006 grad_norm: 4.6117 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2841 loss: 1.2841 2022/10/13 07:24:58 - mmengine - INFO - Epoch(train) [62][100/940] lr: 1.0000e-03 eta: 5:11:36 time: 0.5209 data_time: 0.1503 memory: 17006 grad_norm: 4.6591 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2784 loss: 1.2784 2022/10/13 07:25:07 - mmengine - INFO - Epoch(train) [62][120/940] lr: 1.0000e-03 eta: 5:11:25 time: 0.4713 data_time: 0.0398 memory: 17006 grad_norm: 4.5846 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3340 loss: 1.3340 2022/10/13 07:25:18 - mmengine - INFO - Epoch(train) [62][140/940] lr: 1.0000e-03 eta: 5:11:16 time: 0.5641 data_time: 0.0742 memory: 17006 grad_norm: 4.5554 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1906 loss: 1.1906 2022/10/13 07:25:27 - mmengine - INFO - Epoch(train) [62][160/940] lr: 1.0000e-03 eta: 5:11:04 time: 0.4432 data_time: 0.0270 memory: 17006 grad_norm: 4.5923 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.3808 loss: 1.3808 2022/10/13 07:25:38 - mmengine - INFO - Epoch(train) [62][180/940] lr: 1.0000e-03 eta: 5:10:55 time: 0.5398 data_time: 0.0369 memory: 17006 grad_norm: 4.6959 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2784 loss: 1.2784 2022/10/13 07:25:48 - mmengine - INFO - Epoch(train) [62][200/940] lr: 1.0000e-03 eta: 5:10:44 time: 0.4825 data_time: 0.0292 memory: 17006 grad_norm: 4.6109 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4449 loss: 1.4449 2022/10/13 07:25:59 - mmengine - INFO - Epoch(train) [62][220/940] lr: 1.0000e-03 eta: 5:10:34 time: 0.5664 data_time: 0.0335 memory: 17006 grad_norm: 4.5839 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2995 loss: 1.2995 2022/10/13 07:26:09 - mmengine - INFO - Epoch(train) [62][240/940] lr: 1.0000e-03 eta: 5:10:24 time: 0.4834 data_time: 0.0319 memory: 17006 grad_norm: 4.5424 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2122 loss: 1.2122 2022/10/13 07:26:20 - mmengine - INFO - Epoch(train) [62][260/940] lr: 1.0000e-03 eta: 5:10:14 time: 0.5449 data_time: 0.0337 memory: 17006 grad_norm: 4.6886 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.4057 loss: 1.4057 2022/10/13 07:26:29 - mmengine - INFO - Epoch(train) [62][280/940] lr: 1.0000e-03 eta: 5:10:03 time: 0.4779 data_time: 0.0262 memory: 17006 grad_norm: 4.6563 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4680 loss: 1.4680 2022/10/13 07:26:39 - mmengine - INFO - Epoch(train) [62][300/940] lr: 1.0000e-03 eta: 5:09:53 time: 0.5161 data_time: 0.0318 memory: 17006 grad_norm: 4.5831 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3601 loss: 1.3601 2022/10/13 07:26:49 - mmengine - INFO - Epoch(train) [62][320/940] lr: 1.0000e-03 eta: 5:09:43 time: 0.4928 data_time: 0.0299 memory: 17006 grad_norm: 4.6273 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2611 loss: 1.2611 2022/10/13 07:27:00 - mmengine - INFO - Epoch(train) [62][340/940] lr: 1.0000e-03 eta: 5:09:33 time: 0.5162 data_time: 0.0322 memory: 17006 grad_norm: 4.5711 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3081 loss: 1.3081 2022/10/13 07:27:09 - mmengine - INFO - Epoch(train) [62][360/940] lr: 1.0000e-03 eta: 5:09:22 time: 0.4946 data_time: 0.0378 memory: 17006 grad_norm: 4.5787 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2386 loss: 1.2386 2022/10/13 07:27:21 - mmengine - INFO - Epoch(train) [62][380/940] lr: 1.0000e-03 eta: 5:09:12 time: 0.5549 data_time: 0.0359 memory: 17006 grad_norm: 4.5032 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3093 loss: 1.3093 2022/10/13 07:27:30 - mmengine - INFO - Epoch(train) [62][400/940] lr: 1.0000e-03 eta: 5:09:02 time: 0.4669 data_time: 0.0332 memory: 17006 grad_norm: 4.7642 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2546 loss: 1.2546 2022/10/13 07:27:40 - mmengine - INFO - Epoch(train) [62][420/940] lr: 1.0000e-03 eta: 5:08:51 time: 0.4906 data_time: 0.0268 memory: 17006 grad_norm: 4.6610 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2843 loss: 1.2843 2022/10/13 07:27:49 - mmengine - INFO - Epoch(train) [62][440/940] lr: 1.0000e-03 eta: 5:08:40 time: 0.4548 data_time: 0.0380 memory: 17006 grad_norm: 4.6985 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4615 loss: 1.4615 2022/10/13 07:27:59 - mmengine - INFO - Epoch(train) [62][460/940] lr: 1.0000e-03 eta: 5:08:30 time: 0.5148 data_time: 0.0309 memory: 17006 grad_norm: 4.6402 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3349 loss: 1.3349 2022/10/13 07:28:09 - mmengine - INFO - Epoch(train) [62][480/940] lr: 1.0000e-03 eta: 5:08:19 time: 0.4776 data_time: 0.0365 memory: 17006 grad_norm: 4.5522 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3571 loss: 1.3571 2022/10/13 07:28:19 - mmengine - INFO - Epoch(train) [62][500/940] lr: 1.0000e-03 eta: 5:08:09 time: 0.5220 data_time: 0.0357 memory: 17006 grad_norm: 4.6981 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3142 loss: 1.3142 2022/10/13 07:28:29 - mmengine - INFO - Epoch(train) [62][520/940] lr: 1.0000e-03 eta: 5:07:59 time: 0.5173 data_time: 0.0340 memory: 17006 grad_norm: 4.6755 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4251 loss: 1.4251 2022/10/13 07:28:40 - mmengine - INFO - Epoch(train) [62][540/940] lr: 1.0000e-03 eta: 5:07:49 time: 0.5198 data_time: 0.0264 memory: 17006 grad_norm: 4.6477 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3752 loss: 1.3752 2022/10/13 07:28:51 - mmengine - INFO - Epoch(train) [62][560/940] lr: 1.0000e-03 eta: 5:07:39 time: 0.5520 data_time: 0.0358 memory: 17006 grad_norm: 4.6405 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3684 loss: 1.3684 2022/10/13 07:29:00 - mmengine - INFO - Epoch(train) [62][580/940] lr: 1.0000e-03 eta: 5:07:28 time: 0.4589 data_time: 0.0256 memory: 17006 grad_norm: 4.5063 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2762 loss: 1.2762 2022/10/13 07:29:11 - mmengine - INFO - Epoch(train) [62][600/940] lr: 1.0000e-03 eta: 5:07:18 time: 0.5314 data_time: 0.0332 memory: 17006 grad_norm: 4.6750 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3930 loss: 1.3930 2022/10/13 07:29:19 - mmengine - INFO - Epoch(train) [62][620/940] lr: 1.0000e-03 eta: 5:07:07 time: 0.4392 data_time: 0.0296 memory: 17006 grad_norm: 4.6933 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2980 loss: 1.2980 2022/10/13 07:29:29 - mmengine - INFO - Epoch(train) [62][640/940] lr: 1.0000e-03 eta: 5:06:57 time: 0.4912 data_time: 0.0369 memory: 17006 grad_norm: 4.6283 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3774 loss: 1.3774 2022/10/13 07:29:41 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 07:29:41 - mmengine - INFO - Epoch(train) [62][660/940] lr: 1.0000e-03 eta: 5:06:47 time: 0.5706 data_time: 0.0316 memory: 17006 grad_norm: 4.6181 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.3886 loss: 1.3886 2022/10/13 07:29:50 - mmengine - INFO - Epoch(train) [62][680/940] lr: 1.0000e-03 eta: 5:06:37 time: 0.4781 data_time: 0.0350 memory: 17006 grad_norm: 4.5876 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3592 loss: 1.3592 2022/10/13 07:30:01 - mmengine - INFO - Epoch(train) [62][700/940] lr: 1.0000e-03 eta: 5:06:27 time: 0.5415 data_time: 0.0271 memory: 17006 grad_norm: 4.6077 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.3618 loss: 1.3618 2022/10/13 07:30:12 - mmengine - INFO - Epoch(train) [62][720/940] lr: 1.0000e-03 eta: 5:06:17 time: 0.5204 data_time: 0.0311 memory: 17006 grad_norm: 4.6580 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3234 loss: 1.3234 2022/10/13 07:30:21 - mmengine - INFO - Epoch(train) [62][740/940] lr: 1.0000e-03 eta: 5:06:06 time: 0.4966 data_time: 0.0291 memory: 17006 grad_norm: 4.5865 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2884 loss: 1.2884 2022/10/13 07:30:31 - mmengine - INFO - Epoch(train) [62][760/940] lr: 1.0000e-03 eta: 5:05:56 time: 0.4967 data_time: 0.0338 memory: 17006 grad_norm: 4.6969 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4618 loss: 1.4618 2022/10/13 07:30:42 - mmengine - INFO - Epoch(train) [62][780/940] lr: 1.0000e-03 eta: 5:05:46 time: 0.5425 data_time: 0.0288 memory: 17006 grad_norm: 4.6388 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.4164 loss: 1.4164 2022/10/13 07:30:52 - mmengine - INFO - Epoch(train) [62][800/940] lr: 1.0000e-03 eta: 5:05:36 time: 0.5039 data_time: 0.0354 memory: 17006 grad_norm: 4.6028 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2845 loss: 1.2845 2022/10/13 07:31:02 - mmengine - INFO - Epoch(train) [62][820/940] lr: 1.0000e-03 eta: 5:05:25 time: 0.4724 data_time: 0.0359 memory: 17006 grad_norm: 4.6604 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4168 loss: 1.4168 2022/10/13 07:31:13 - mmengine - INFO - Epoch(train) [62][840/940] lr: 1.0000e-03 eta: 5:05:15 time: 0.5403 data_time: 0.0290 memory: 17006 grad_norm: 4.5620 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.2744 loss: 1.2744 2022/10/13 07:31:23 - mmengine - INFO - Epoch(train) [62][860/940] lr: 1.0000e-03 eta: 5:05:05 time: 0.5295 data_time: 0.0339 memory: 17006 grad_norm: 4.5208 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3559 loss: 1.3559 2022/10/13 07:31:33 - mmengine - INFO - Epoch(train) [62][880/940] lr: 1.0000e-03 eta: 5:04:55 time: 0.4767 data_time: 0.0352 memory: 17006 grad_norm: 4.5996 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4054 loss: 1.4054 2022/10/13 07:31:44 - mmengine - INFO - Epoch(train) [62][900/940] lr: 1.0000e-03 eta: 5:04:45 time: 0.5499 data_time: 0.0345 memory: 17006 grad_norm: 4.7033 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3769 loss: 1.3769 2022/10/13 07:31:54 - mmengine - INFO - Epoch(train) [62][920/940] lr: 1.0000e-03 eta: 5:04:34 time: 0.4957 data_time: 0.0340 memory: 17006 grad_norm: 4.5741 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3472 loss: 1.3472 2022/10/13 07:32:04 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 07:32:04 - mmengine - INFO - Epoch(train) [62][940/940] lr: 1.0000e-03 eta: 5:04:24 time: 0.5034 data_time: 0.0262 memory: 17006 grad_norm: 4.8017 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.3125 loss: 1.3125 2022/10/13 07:32:16 - mmengine - INFO - Epoch(val) [62][20/78] eta: 0:00:36 time: 0.6260 data_time: 0.5312 memory: 3172 2022/10/13 07:32:25 - mmengine - INFO - Epoch(val) [62][40/78] eta: 0:00:16 time: 0.4282 data_time: 0.3354 memory: 3172 2022/10/13 07:32:36 - mmengine - INFO - Epoch(val) [62][60/78] eta: 0:00:10 time: 0.5743 data_time: 0.4829 memory: 3172 2022/10/13 07:32:46 - mmengine - INFO - Epoch(val) [62][78/78] acc/top1: 0.6727 acc/top5: 0.8703 acc/mean1: 0.6725 2022/10/13 07:33:00 - mmengine - INFO - Epoch(train) [63][20/940] lr: 1.0000e-03 eta: 5:04:16 time: 0.7037 data_time: 0.2024 memory: 17006 grad_norm: 4.6156 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3762 loss: 1.3762 2022/10/13 07:33:10 - mmengine - INFO - Epoch(train) [63][40/940] lr: 1.0000e-03 eta: 5:04:06 time: 0.4866 data_time: 0.0285 memory: 17006 grad_norm: 4.5685 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4568 loss: 1.4568 2022/10/13 07:33:21 - mmengine - INFO - Epoch(train) [63][60/940] lr: 1.0000e-03 eta: 5:03:56 time: 0.5764 data_time: 0.0334 memory: 17006 grad_norm: 4.5102 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2145 loss: 1.2145 2022/10/13 07:33:31 - mmengine - INFO - Epoch(train) [63][80/940] lr: 1.0000e-03 eta: 5:03:46 time: 0.4887 data_time: 0.0263 memory: 17006 grad_norm: 4.6108 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3542 loss: 1.3542 2022/10/13 07:33:42 - mmengine - INFO - Epoch(train) [63][100/940] lr: 1.0000e-03 eta: 5:03:36 time: 0.5429 data_time: 0.0391 memory: 17006 grad_norm: 4.6799 top1_acc: 0.5938 top5_acc: 0.9688 loss_cls: 1.3395 loss: 1.3395 2022/10/13 07:33:52 - mmengine - INFO - Epoch(train) [63][120/940] lr: 1.0000e-03 eta: 5:03:25 time: 0.4972 data_time: 0.0275 memory: 17006 grad_norm: 4.5903 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3219 loss: 1.3219 2022/10/13 07:34:02 - mmengine - INFO - Epoch(train) [63][140/940] lr: 1.0000e-03 eta: 5:03:15 time: 0.5035 data_time: 0.0363 memory: 17006 grad_norm: 4.5166 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1852 loss: 1.1852 2022/10/13 07:34:11 - mmengine - INFO - Epoch(train) [63][160/940] lr: 1.0000e-03 eta: 5:03:04 time: 0.4481 data_time: 0.0279 memory: 17006 grad_norm: 4.6455 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3605 loss: 1.3605 2022/10/13 07:34:22 - mmengine - INFO - Epoch(train) [63][180/940] lr: 1.0000e-03 eta: 5:02:54 time: 0.5425 data_time: 0.0396 memory: 17006 grad_norm: 4.6352 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3874 loss: 1.3874 2022/10/13 07:34:31 - mmengine - INFO - Epoch(train) [63][200/940] lr: 1.0000e-03 eta: 5:02:44 time: 0.4815 data_time: 0.0271 memory: 17006 grad_norm: 4.6163 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3980 loss: 1.3980 2022/10/13 07:34:43 - mmengine - INFO - Epoch(train) [63][220/940] lr: 1.0000e-03 eta: 5:02:34 time: 0.5743 data_time: 0.0348 memory: 17006 grad_norm: 4.5314 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3044 loss: 1.3044 2022/10/13 07:34:53 - mmengine - INFO - Epoch(train) [63][240/940] lr: 1.0000e-03 eta: 5:02:24 time: 0.5024 data_time: 0.0322 memory: 17006 grad_norm: 4.6605 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.3985 loss: 1.3985 2022/10/13 07:35:03 - mmengine - INFO - Epoch(train) [63][260/940] lr: 1.0000e-03 eta: 5:02:14 time: 0.5061 data_time: 0.0337 memory: 17006 grad_norm: 4.7297 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2656 loss: 1.2656 2022/10/13 07:35:13 - mmengine - INFO - Epoch(train) [63][280/940] lr: 1.0000e-03 eta: 5:02:03 time: 0.5005 data_time: 0.0345 memory: 17006 grad_norm: 4.5984 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3474 loss: 1.3474 2022/10/13 07:35:23 - mmengine - INFO - Epoch(train) [63][300/940] lr: 1.0000e-03 eta: 5:01:53 time: 0.5082 data_time: 0.0319 memory: 17006 grad_norm: 4.6394 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3412 loss: 1.3412 2022/10/13 07:35:33 - mmengine - INFO - Epoch(train) [63][320/940] lr: 1.0000e-03 eta: 5:01:43 time: 0.4967 data_time: 0.0366 memory: 17006 grad_norm: 4.5174 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3691 loss: 1.3691 2022/10/13 07:35:44 - mmengine - INFO - Epoch(train) [63][340/940] lr: 1.0000e-03 eta: 5:01:33 time: 0.5445 data_time: 0.0302 memory: 17006 grad_norm: 4.6888 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3334 loss: 1.3334 2022/10/13 07:35:53 - mmengine - INFO - Epoch(train) [63][360/940] lr: 1.0000e-03 eta: 5:01:22 time: 0.4592 data_time: 0.0331 memory: 17006 grad_norm: 4.6306 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2619 loss: 1.2619 2022/10/13 07:36:04 - mmengine - INFO - Epoch(train) [63][380/940] lr: 1.0000e-03 eta: 5:01:12 time: 0.5309 data_time: 0.0318 memory: 17006 grad_norm: 4.7138 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4116 loss: 1.4116 2022/10/13 07:36:14 - mmengine - INFO - Epoch(train) [63][400/940] lr: 1.0000e-03 eta: 5:01:01 time: 0.4933 data_time: 0.0356 memory: 17006 grad_norm: 4.6463 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3845 loss: 1.3845 2022/10/13 07:36:25 - mmengine - INFO - Epoch(train) [63][420/940] lr: 1.0000e-03 eta: 5:00:52 time: 0.5357 data_time: 0.0316 memory: 17006 grad_norm: 4.6195 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3503 loss: 1.3503 2022/10/13 07:36:34 - mmengine - INFO - Epoch(train) [63][440/940] lr: 1.0000e-03 eta: 5:00:41 time: 0.4672 data_time: 0.0373 memory: 17006 grad_norm: 4.5673 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3018 loss: 1.3018 2022/10/13 07:36:45 - mmengine - INFO - Epoch(train) [63][460/940] lr: 1.0000e-03 eta: 5:00:31 time: 0.5307 data_time: 0.0271 memory: 17006 grad_norm: 4.6088 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2687 loss: 1.2687 2022/10/13 07:36:54 - mmengine - INFO - Epoch(train) [63][480/940] lr: 1.0000e-03 eta: 5:00:20 time: 0.4676 data_time: 0.0346 memory: 17006 grad_norm: 4.6779 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2854 loss: 1.2854 2022/10/13 07:37:04 - mmengine - INFO - Epoch(train) [63][500/940] lr: 1.0000e-03 eta: 5:00:10 time: 0.5083 data_time: 0.0301 memory: 17006 grad_norm: 4.5737 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2841 loss: 1.2841 2022/10/13 07:37:14 - mmengine - INFO - Epoch(train) [63][520/940] lr: 1.0000e-03 eta: 4:59:59 time: 0.4924 data_time: 0.0345 memory: 17006 grad_norm: 4.7029 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3297 loss: 1.3297 2022/10/13 07:37:24 - mmengine - INFO - Epoch(train) [63][540/940] lr: 1.0000e-03 eta: 4:59:49 time: 0.5228 data_time: 0.0297 memory: 17006 grad_norm: 4.6787 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4624 loss: 1.4624 2022/10/13 07:37:34 - mmengine - INFO - Epoch(train) [63][560/940] lr: 1.0000e-03 eta: 4:59:38 time: 0.4639 data_time: 0.0380 memory: 17006 grad_norm: 4.6485 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4779 loss: 1.4779 2022/10/13 07:37:45 - mmengine - INFO - Epoch(train) [63][580/940] lr: 1.0000e-03 eta: 4:59:29 time: 0.5581 data_time: 0.0326 memory: 17006 grad_norm: 4.5372 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3394 loss: 1.3394 2022/10/13 07:37:55 - mmengine - INFO - Epoch(train) [63][600/940] lr: 1.0000e-03 eta: 4:59:18 time: 0.4971 data_time: 0.0343 memory: 17006 grad_norm: 4.6621 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3531 loss: 1.3531 2022/10/13 07:38:06 - mmengine - INFO - Epoch(train) [63][620/940] lr: 1.0000e-03 eta: 4:59:09 time: 0.5469 data_time: 0.0329 memory: 17006 grad_norm: 4.6405 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4550 loss: 1.4550 2022/10/13 07:38:15 - mmengine - INFO - Epoch(train) [63][640/940] lr: 1.0000e-03 eta: 4:58:58 time: 0.4853 data_time: 0.0383 memory: 17006 grad_norm: 4.6841 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2578 loss: 1.2578 2022/10/13 07:38:27 - mmengine - INFO - Epoch(train) [63][660/940] lr: 1.0000e-03 eta: 4:58:49 time: 0.5872 data_time: 0.0311 memory: 17006 grad_norm: 4.6477 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2211 loss: 1.2211 2022/10/13 07:38:37 - mmengine - INFO - Epoch(train) [63][680/940] lr: 1.0000e-03 eta: 4:58:38 time: 0.4749 data_time: 0.0320 memory: 17006 grad_norm: 4.5518 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2348 loss: 1.2348 2022/10/13 07:38:47 - mmengine - INFO - Epoch(train) [63][700/940] lr: 1.0000e-03 eta: 4:58:28 time: 0.5264 data_time: 0.0301 memory: 17006 grad_norm: 4.5939 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3110 loss: 1.3110 2022/10/13 07:38:57 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 07:38:57 - mmengine - INFO - Epoch(train) [63][720/940] lr: 1.0000e-03 eta: 4:58:17 time: 0.4705 data_time: 0.0414 memory: 17006 grad_norm: 4.7250 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3264 loss: 1.3264 2022/10/13 07:39:08 - mmengine - INFO - Epoch(train) [63][740/940] lr: 1.0000e-03 eta: 4:58:08 time: 0.5606 data_time: 0.0299 memory: 17006 grad_norm: 4.6579 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2441 loss: 1.2441 2022/10/13 07:39:17 - mmengine - INFO - Epoch(train) [63][760/940] lr: 1.0000e-03 eta: 4:57:57 time: 0.4612 data_time: 0.0286 memory: 17006 grad_norm: 4.5936 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3697 loss: 1.3697 2022/10/13 07:39:28 - mmengine - INFO - Epoch(train) [63][780/940] lr: 1.0000e-03 eta: 4:57:47 time: 0.5405 data_time: 0.0290 memory: 17006 grad_norm: 4.6275 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2759 loss: 1.2759 2022/10/13 07:39:37 - mmengine - INFO - Epoch(train) [63][800/940] lr: 1.0000e-03 eta: 4:57:36 time: 0.4847 data_time: 0.0315 memory: 17006 grad_norm: 4.6150 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3350 loss: 1.3350 2022/10/13 07:39:48 - mmengine - INFO - Epoch(train) [63][820/940] lr: 1.0000e-03 eta: 4:57:26 time: 0.5163 data_time: 0.0352 memory: 17006 grad_norm: 4.6160 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3206 loss: 1.3206 2022/10/13 07:39:57 - mmengine - INFO - Epoch(train) [63][840/940] lr: 1.0000e-03 eta: 4:57:15 time: 0.4548 data_time: 0.0307 memory: 17006 grad_norm: 4.6577 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3836 loss: 1.3836 2022/10/13 07:40:08 - mmengine - INFO - Epoch(train) [63][860/940] lr: 1.0000e-03 eta: 4:57:05 time: 0.5321 data_time: 0.0302 memory: 17006 grad_norm: 4.5897 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3306 loss: 1.3306 2022/10/13 07:40:18 - mmengine - INFO - Epoch(train) [63][880/940] lr: 1.0000e-03 eta: 4:56:55 time: 0.4990 data_time: 0.0324 memory: 17006 grad_norm: 4.8158 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4019 loss: 1.4019 2022/10/13 07:40:29 - mmengine - INFO - Epoch(train) [63][900/940] lr: 1.0000e-03 eta: 4:56:45 time: 0.5721 data_time: 0.0292 memory: 17006 grad_norm: 4.7511 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3756 loss: 1.3756 2022/10/13 07:40:38 - mmengine - INFO - Epoch(train) [63][920/940] lr: 1.0000e-03 eta: 4:56:35 time: 0.4594 data_time: 0.0311 memory: 17006 grad_norm: 4.7136 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2563 loss: 1.2563 2022/10/13 07:40:48 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 07:40:48 - mmengine - INFO - Epoch(train) [63][940/940] lr: 1.0000e-03 eta: 4:56:24 time: 0.4850 data_time: 0.0283 memory: 17006 grad_norm: 4.8585 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.3236 loss: 1.3236 2022/10/13 07:40:48 - mmengine - INFO - Saving checkpoint at 63 epochs 2022/10/13 07:41:01 - mmengine - INFO - Epoch(val) [63][20/78] eta: 0:00:36 time: 0.6279 data_time: 0.5380 memory: 3172 2022/10/13 07:41:10 - mmengine - INFO - Epoch(val) [63][40/78] eta: 0:00:16 time: 0.4216 data_time: 0.3326 memory: 3172 2022/10/13 07:41:21 - mmengine - INFO - Epoch(val) [63][60/78] eta: 0:00:10 time: 0.5774 data_time: 0.4858 memory: 3172 2022/10/13 07:41:30 - mmengine - INFO - Epoch(val) [63][78/78] acc/top1: 0.6708 acc/top5: 0.8683 acc/mean1: 0.6707 2022/10/13 07:41:44 - mmengine - INFO - Epoch(train) [64][20/940] lr: 1.0000e-03 eta: 4:56:16 time: 0.6729 data_time: 0.2707 memory: 17006 grad_norm: 4.6400 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3217 loss: 1.3217 2022/10/13 07:41:54 - mmengine - INFO - Epoch(train) [64][40/940] lr: 1.0000e-03 eta: 4:56:05 time: 0.4828 data_time: 0.0826 memory: 17006 grad_norm: 4.6401 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1954 loss: 1.1954 2022/10/13 07:42:04 - mmengine - INFO - Epoch(train) [64][60/940] lr: 1.0000e-03 eta: 4:55:55 time: 0.5319 data_time: 0.0346 memory: 17006 grad_norm: 4.6706 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3610 loss: 1.3610 2022/10/13 07:42:14 - mmengine - INFO - Epoch(train) [64][80/940] lr: 1.0000e-03 eta: 4:55:45 time: 0.4911 data_time: 0.0296 memory: 17006 grad_norm: 4.6040 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1054 loss: 1.1054 2022/10/13 07:42:24 - mmengine - INFO - Epoch(train) [64][100/940] lr: 1.0000e-03 eta: 4:55:35 time: 0.5191 data_time: 0.0310 memory: 17006 grad_norm: 4.7825 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3122 loss: 1.3122 2022/10/13 07:42:34 - mmengine - INFO - Epoch(train) [64][120/940] lr: 1.0000e-03 eta: 4:55:24 time: 0.4653 data_time: 0.0334 memory: 17006 grad_norm: 4.7010 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4899 loss: 1.4899 2022/10/13 07:42:44 - mmengine - INFO - Epoch(train) [64][140/940] lr: 1.0000e-03 eta: 4:55:14 time: 0.5346 data_time: 0.0351 memory: 17006 grad_norm: 4.5925 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1813 loss: 1.1813 2022/10/13 07:42:54 - mmengine - INFO - Epoch(train) [64][160/940] lr: 1.0000e-03 eta: 4:55:03 time: 0.4910 data_time: 0.0319 memory: 17006 grad_norm: 4.6594 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4344 loss: 1.4344 2022/10/13 07:43:05 - mmengine - INFO - Epoch(train) [64][180/940] lr: 1.0000e-03 eta: 4:54:53 time: 0.5345 data_time: 0.0346 memory: 17006 grad_norm: 4.6667 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2568 loss: 1.2568 2022/10/13 07:43:15 - mmengine - INFO - Epoch(train) [64][200/940] lr: 1.0000e-03 eta: 4:54:43 time: 0.4916 data_time: 0.0317 memory: 17006 grad_norm: 4.6727 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3495 loss: 1.3495 2022/10/13 07:43:25 - mmengine - INFO - Epoch(train) [64][220/940] lr: 1.0000e-03 eta: 4:54:33 time: 0.5164 data_time: 0.0346 memory: 17006 grad_norm: 4.6728 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3712 loss: 1.3712 2022/10/13 07:43:35 - mmengine - INFO - Epoch(train) [64][240/940] lr: 1.0000e-03 eta: 4:54:22 time: 0.5025 data_time: 0.0255 memory: 17006 grad_norm: 4.6218 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3248 loss: 1.3248 2022/10/13 07:43:46 - mmengine - INFO - Epoch(train) [64][260/940] lr: 1.0000e-03 eta: 4:54:13 time: 0.5537 data_time: 0.0306 memory: 17006 grad_norm: 4.6080 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3889 loss: 1.3889 2022/10/13 07:43:56 - mmengine - INFO - Epoch(train) [64][280/940] lr: 1.0000e-03 eta: 4:54:02 time: 0.4820 data_time: 0.0255 memory: 17006 grad_norm: 4.6615 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2171 loss: 1.2171 2022/10/13 07:44:07 - mmengine - INFO - Epoch(train) [64][300/940] lr: 1.0000e-03 eta: 4:53:52 time: 0.5467 data_time: 0.0355 memory: 17006 grad_norm: 4.5711 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2625 loss: 1.2625 2022/10/13 07:44:16 - mmengine - INFO - Epoch(train) [64][320/940] lr: 1.0000e-03 eta: 4:53:42 time: 0.4619 data_time: 0.0293 memory: 17006 grad_norm: 4.5949 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3273 loss: 1.3273 2022/10/13 07:44:26 - mmengine - INFO - Epoch(train) [64][340/940] lr: 1.0000e-03 eta: 4:53:31 time: 0.5068 data_time: 0.0304 memory: 17006 grad_norm: 4.6966 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3537 loss: 1.3537 2022/10/13 07:44:36 - mmengine - INFO - Epoch(train) [64][360/940] lr: 1.0000e-03 eta: 4:53:21 time: 0.4782 data_time: 0.0391 memory: 17006 grad_norm: 4.5409 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4049 loss: 1.4049 2022/10/13 07:44:47 - mmengine - INFO - Epoch(train) [64][380/940] lr: 1.0000e-03 eta: 4:53:11 time: 0.5385 data_time: 0.0969 memory: 17006 grad_norm: 4.6404 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3180 loss: 1.3180 2022/10/13 07:44:56 - mmengine - INFO - Epoch(train) [64][400/940] lr: 1.0000e-03 eta: 4:53:00 time: 0.4924 data_time: 0.0328 memory: 17006 grad_norm: 4.5747 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.2794 loss: 1.2794 2022/10/13 07:45:07 - mmengine - INFO - Epoch(train) [64][420/940] lr: 1.0000e-03 eta: 4:52:51 time: 0.5501 data_time: 0.0339 memory: 17006 grad_norm: 4.7004 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3853 loss: 1.3853 2022/10/13 07:45:17 - mmengine - INFO - Epoch(train) [64][440/940] lr: 1.0000e-03 eta: 4:52:40 time: 0.4640 data_time: 0.0310 memory: 17006 grad_norm: 4.6098 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3379 loss: 1.3379 2022/10/13 07:45:28 - mmengine - INFO - Epoch(train) [64][460/940] lr: 1.0000e-03 eta: 4:52:30 time: 0.5585 data_time: 0.0317 memory: 17006 grad_norm: 4.5843 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3424 loss: 1.3424 2022/10/13 07:45:37 - mmengine - INFO - Epoch(train) [64][480/940] lr: 1.0000e-03 eta: 4:52:19 time: 0.4704 data_time: 0.0313 memory: 17006 grad_norm: 4.8108 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3781 loss: 1.3781 2022/10/13 07:45:47 - mmengine - INFO - Epoch(train) [64][500/940] lr: 1.0000e-03 eta: 4:52:09 time: 0.4883 data_time: 0.0288 memory: 17006 grad_norm: 4.6954 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4041 loss: 1.4041 2022/10/13 07:45:56 - mmengine - INFO - Epoch(train) [64][520/940] lr: 1.0000e-03 eta: 4:51:58 time: 0.4715 data_time: 0.0333 memory: 17006 grad_norm: 4.5844 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2411 loss: 1.2411 2022/10/13 07:46:07 - mmengine - INFO - Epoch(train) [64][540/940] lr: 1.0000e-03 eta: 4:51:48 time: 0.5422 data_time: 0.0297 memory: 17006 grad_norm: 4.7087 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3972 loss: 1.3972 2022/10/13 07:46:17 - mmengine - INFO - Epoch(train) [64][560/940] lr: 1.0000e-03 eta: 4:51:38 time: 0.4924 data_time: 0.0356 memory: 17006 grad_norm: 4.6507 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2099 loss: 1.2099 2022/10/13 07:46:28 - mmengine - INFO - Epoch(train) [64][580/940] lr: 1.0000e-03 eta: 4:51:28 time: 0.5506 data_time: 0.0308 memory: 17006 grad_norm: 4.6668 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3257 loss: 1.3257 2022/10/13 07:46:38 - mmengine - INFO - Epoch(train) [64][600/940] lr: 1.0000e-03 eta: 4:51:18 time: 0.4842 data_time: 0.0371 memory: 17006 grad_norm: 4.6841 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.3102 loss: 1.3102 2022/10/13 07:46:48 - mmengine - INFO - Epoch(train) [64][620/940] lr: 1.0000e-03 eta: 4:51:07 time: 0.5004 data_time: 0.0286 memory: 17006 grad_norm: 4.7616 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4070 loss: 1.4070 2022/10/13 07:46:58 - mmengine - INFO - Epoch(train) [64][640/940] lr: 1.0000e-03 eta: 4:50:57 time: 0.5186 data_time: 0.0374 memory: 17006 grad_norm: 4.6249 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3573 loss: 1.3573 2022/10/13 07:47:08 - mmengine - INFO - Epoch(train) [64][660/940] lr: 1.0000e-03 eta: 4:50:46 time: 0.4777 data_time: 0.0275 memory: 17006 grad_norm: 4.6469 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.4304 loss: 1.4304 2022/10/13 07:47:18 - mmengine - INFO - Epoch(train) [64][680/940] lr: 1.0000e-03 eta: 4:50:36 time: 0.5134 data_time: 0.0368 memory: 17006 grad_norm: 4.6603 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.4645 loss: 1.4645 2022/10/13 07:47:28 - mmengine - INFO - Epoch(train) [64][700/940] lr: 1.0000e-03 eta: 4:50:26 time: 0.5005 data_time: 0.0300 memory: 17006 grad_norm: 4.6763 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3859 loss: 1.3859 2022/10/13 07:47:38 - mmengine - INFO - Epoch(train) [64][720/940] lr: 1.0000e-03 eta: 4:50:16 time: 0.5010 data_time: 0.0368 memory: 17006 grad_norm: 4.5814 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2561 loss: 1.2561 2022/10/13 07:47:48 - mmengine - INFO - Epoch(train) [64][740/940] lr: 1.0000e-03 eta: 4:50:05 time: 0.5057 data_time: 0.0272 memory: 17006 grad_norm: 4.6725 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2138 loss: 1.2138 2022/10/13 07:47:57 - mmengine - INFO - Epoch(train) [64][760/940] lr: 1.0000e-03 eta: 4:49:54 time: 0.4599 data_time: 0.0337 memory: 17006 grad_norm: 4.8169 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4985 loss: 1.4985 2022/10/13 07:48:08 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 07:48:08 - mmengine - INFO - Epoch(train) [64][780/940] lr: 1.0000e-03 eta: 4:49:45 time: 0.5441 data_time: 0.0356 memory: 17006 grad_norm: 4.6494 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3540 loss: 1.3540 2022/10/13 07:48:17 - mmengine - INFO - Epoch(train) [64][800/940] lr: 1.0000e-03 eta: 4:49:34 time: 0.4541 data_time: 0.0407 memory: 17006 grad_norm: 4.6369 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2902 loss: 1.2902 2022/10/13 07:48:28 - mmengine - INFO - Epoch(train) [64][820/940] lr: 1.0000e-03 eta: 4:49:24 time: 0.5480 data_time: 0.0292 memory: 17006 grad_norm: 4.6733 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3711 loss: 1.3711 2022/10/13 07:48:39 - mmengine - INFO - Epoch(train) [64][840/940] lr: 1.0000e-03 eta: 4:49:14 time: 0.5113 data_time: 0.0287 memory: 17006 grad_norm: 4.7602 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2567 loss: 1.2567 2022/10/13 07:48:49 - mmengine - INFO - Epoch(train) [64][860/940] lr: 1.0000e-03 eta: 4:49:03 time: 0.5123 data_time: 0.0357 memory: 17006 grad_norm: 4.7352 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3950 loss: 1.3950 2022/10/13 07:48:59 - mmengine - INFO - Epoch(train) [64][880/940] lr: 1.0000e-03 eta: 4:48:53 time: 0.5175 data_time: 0.0304 memory: 17006 grad_norm: 4.6186 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3522 loss: 1.3522 2022/10/13 07:49:09 - mmengine - INFO - Epoch(train) [64][900/940] lr: 1.0000e-03 eta: 4:48:43 time: 0.5140 data_time: 0.0301 memory: 17006 grad_norm: 4.6330 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2657 loss: 1.2657 2022/10/13 07:49:19 - mmengine - INFO - Epoch(train) [64][920/940] lr: 1.0000e-03 eta: 4:48:33 time: 0.4845 data_time: 0.0326 memory: 17006 grad_norm: 4.6750 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2946 loss: 1.2946 2022/10/13 07:49:29 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 07:49:29 - mmengine - INFO - Epoch(train) [64][940/940] lr: 1.0000e-03 eta: 4:48:22 time: 0.5121 data_time: 0.0290 memory: 17006 grad_norm: 4.8056 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.3609 loss: 1.3609 2022/10/13 07:49:42 - mmengine - INFO - Epoch(val) [64][20/78] eta: 0:00:36 time: 0.6270 data_time: 0.5339 memory: 3172 2022/10/13 07:49:51 - mmengine - INFO - Epoch(val) [64][40/78] eta: 0:00:16 time: 0.4331 data_time: 0.3401 memory: 3172 2022/10/13 07:50:02 - mmengine - INFO - Epoch(val) [64][60/78] eta: 0:00:10 time: 0.5727 data_time: 0.4813 memory: 3172 2022/10/13 07:50:12 - mmengine - INFO - Epoch(val) [64][78/78] acc/top1: 0.6697 acc/top5: 0.8693 acc/mean1: 0.6696 2022/10/13 07:50:26 - mmengine - INFO - Epoch(train) [65][20/940] lr: 1.0000e-03 eta: 4:48:14 time: 0.6872 data_time: 0.2432 memory: 17006 grad_norm: 4.7649 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4713 loss: 1.4713 2022/10/13 07:50:35 - mmengine - INFO - Epoch(train) [65][40/940] lr: 1.0000e-03 eta: 4:48:03 time: 0.4744 data_time: 0.1131 memory: 17006 grad_norm: 4.7190 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.3172 loss: 1.3172 2022/10/13 07:50:47 - mmengine - INFO - Epoch(train) [65][60/940] lr: 1.0000e-03 eta: 4:47:54 time: 0.5638 data_time: 0.1271 memory: 17006 grad_norm: 4.6308 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2859 loss: 1.2859 2022/10/13 07:50:56 - mmengine - INFO - Epoch(train) [65][80/940] lr: 1.0000e-03 eta: 4:47:43 time: 0.4851 data_time: 0.0336 memory: 17006 grad_norm: 4.5902 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3269 loss: 1.3269 2022/10/13 07:51:08 - mmengine - INFO - Epoch(train) [65][100/940] lr: 1.0000e-03 eta: 4:47:34 time: 0.6009 data_time: 0.0362 memory: 17006 grad_norm: 4.6828 top1_acc: 0.5938 top5_acc: 0.9688 loss_cls: 1.3129 loss: 1.3129 2022/10/13 07:51:18 - mmengine - INFO - Epoch(train) [65][120/940] lr: 1.0000e-03 eta: 4:47:24 time: 0.4928 data_time: 0.0313 memory: 17006 grad_norm: 4.5740 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3339 loss: 1.3339 2022/10/13 07:51:29 - mmengine - INFO - Epoch(train) [65][140/940] lr: 1.0000e-03 eta: 4:47:14 time: 0.5560 data_time: 0.0309 memory: 17006 grad_norm: 4.6314 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2291 loss: 1.2291 2022/10/13 07:51:39 - mmengine - INFO - Epoch(train) [65][160/940] lr: 1.0000e-03 eta: 4:47:04 time: 0.4928 data_time: 0.0300 memory: 17006 grad_norm: 4.6765 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3992 loss: 1.3992 2022/10/13 07:51:50 - mmengine - INFO - Epoch(train) [65][180/940] lr: 1.0000e-03 eta: 4:46:54 time: 0.5456 data_time: 0.0320 memory: 17006 grad_norm: 4.6458 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2847 loss: 1.2847 2022/10/13 07:51:59 - mmengine - INFO - Epoch(train) [65][200/940] lr: 1.0000e-03 eta: 4:46:43 time: 0.4582 data_time: 0.0312 memory: 17006 grad_norm: 4.6795 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4240 loss: 1.4240 2022/10/13 07:52:10 - mmengine - INFO - Epoch(train) [65][220/940] lr: 1.0000e-03 eta: 4:46:33 time: 0.5499 data_time: 0.0349 memory: 17006 grad_norm: 4.7576 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.3773 loss: 1.3773 2022/10/13 07:52:20 - mmengine - INFO - Epoch(train) [65][240/940] lr: 1.0000e-03 eta: 4:46:23 time: 0.4907 data_time: 0.0287 memory: 17006 grad_norm: 4.7306 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3081 loss: 1.3081 2022/10/13 07:52:31 - mmengine - INFO - Epoch(train) [65][260/940] lr: 1.0000e-03 eta: 4:46:13 time: 0.5366 data_time: 0.0299 memory: 17006 grad_norm: 4.6747 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2371 loss: 1.2371 2022/10/13 07:52:40 - mmengine - INFO - Epoch(train) [65][280/940] lr: 1.0000e-03 eta: 4:46:02 time: 0.4557 data_time: 0.0326 memory: 17006 grad_norm: 4.5758 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1977 loss: 1.1977 2022/10/13 07:52:51 - mmengine - INFO - Epoch(train) [65][300/940] lr: 1.0000e-03 eta: 4:45:52 time: 0.5513 data_time: 0.0304 memory: 17006 grad_norm: 4.6721 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2460 loss: 1.2460 2022/10/13 07:53:01 - mmengine - INFO - Epoch(train) [65][320/940] lr: 1.0000e-03 eta: 4:45:42 time: 0.4937 data_time: 0.0320 memory: 17006 grad_norm: 4.6928 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3857 loss: 1.3857 2022/10/13 07:53:12 - mmengine - INFO - Epoch(train) [65][340/940] lr: 1.0000e-03 eta: 4:45:32 time: 0.5810 data_time: 0.0257 memory: 17006 grad_norm: 4.7354 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3924 loss: 1.3924 2022/10/13 07:53:22 - mmengine - INFO - Epoch(train) [65][360/940] lr: 1.0000e-03 eta: 4:45:22 time: 0.4999 data_time: 0.0322 memory: 17006 grad_norm: 4.8081 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3717 loss: 1.3717 2022/10/13 07:53:33 - mmengine - INFO - Epoch(train) [65][380/940] lr: 1.0000e-03 eta: 4:45:12 time: 0.5442 data_time: 0.0396 memory: 17006 grad_norm: 4.5502 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3093 loss: 1.3093 2022/10/13 07:53:43 - mmengine - INFO - Epoch(train) [65][400/940] lr: 1.0000e-03 eta: 4:45:01 time: 0.4679 data_time: 0.0342 memory: 17006 grad_norm: 4.6743 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2148 loss: 1.2148 2022/10/13 07:53:54 - mmengine - INFO - Epoch(train) [65][420/940] lr: 1.0000e-03 eta: 4:44:51 time: 0.5495 data_time: 0.0306 memory: 17006 grad_norm: 4.7228 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3950 loss: 1.3950 2022/10/13 07:54:03 - mmengine - INFO - Epoch(train) [65][440/940] lr: 1.0000e-03 eta: 4:44:41 time: 0.4839 data_time: 0.0301 memory: 17006 grad_norm: 4.7107 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2981 loss: 1.2981 2022/10/13 07:54:14 - mmengine - INFO - Epoch(train) [65][460/940] lr: 1.0000e-03 eta: 4:44:31 time: 0.5560 data_time: 0.0374 memory: 17006 grad_norm: 4.5895 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.2759 loss: 1.2759 2022/10/13 07:54:23 - mmengine - INFO - Epoch(train) [65][480/940] lr: 1.0000e-03 eta: 4:44:20 time: 0.4507 data_time: 0.0321 memory: 17006 grad_norm: 4.6618 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2601 loss: 1.2601 2022/10/13 07:54:35 - mmengine - INFO - Epoch(train) [65][500/940] lr: 1.0000e-03 eta: 4:44:11 time: 0.5891 data_time: 0.0318 memory: 17006 grad_norm: 4.7480 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2611 loss: 1.2611 2022/10/13 07:54:44 - mmengine - INFO - Epoch(train) [65][520/940] lr: 1.0000e-03 eta: 4:44:00 time: 0.4502 data_time: 0.0340 memory: 17006 grad_norm: 4.6552 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2924 loss: 1.2924 2022/10/13 07:54:55 - mmengine - INFO - Epoch(train) [65][540/940] lr: 1.0000e-03 eta: 4:43:50 time: 0.5496 data_time: 0.0313 memory: 17006 grad_norm: 4.5610 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4049 loss: 1.4049 2022/10/13 07:55:05 - mmengine - INFO - Epoch(train) [65][560/940] lr: 1.0000e-03 eta: 4:43:40 time: 0.4913 data_time: 0.0327 memory: 17006 grad_norm: 4.7239 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4523 loss: 1.4523 2022/10/13 07:55:15 - mmengine - INFO - Epoch(train) [65][580/940] lr: 1.0000e-03 eta: 4:43:29 time: 0.4799 data_time: 0.0323 memory: 17006 grad_norm: 4.6148 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3210 loss: 1.3210 2022/10/13 07:55:24 - mmengine - INFO - Epoch(train) [65][600/940] lr: 1.0000e-03 eta: 4:43:19 time: 0.4858 data_time: 0.0299 memory: 17006 grad_norm: 4.6692 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3427 loss: 1.3427 2022/10/13 07:55:34 - mmengine - INFO - Epoch(train) [65][620/940] lr: 1.0000e-03 eta: 4:43:08 time: 0.5076 data_time: 0.0268 memory: 17006 grad_norm: 4.7146 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3994 loss: 1.3994 2022/10/13 07:55:44 - mmengine - INFO - Epoch(train) [65][640/940] lr: 1.0000e-03 eta: 4:42:58 time: 0.4952 data_time: 0.0311 memory: 17006 grad_norm: 4.6410 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3527 loss: 1.3527 2022/10/13 07:55:55 - mmengine - INFO - Epoch(train) [65][660/940] lr: 1.0000e-03 eta: 4:42:48 time: 0.5400 data_time: 0.0346 memory: 17006 grad_norm: 4.6871 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2727 loss: 1.2727 2022/10/13 07:56:05 - mmengine - INFO - Epoch(train) [65][680/940] lr: 1.0000e-03 eta: 4:42:38 time: 0.4871 data_time: 0.0310 memory: 17006 grad_norm: 4.6247 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3044 loss: 1.3044 2022/10/13 07:56:15 - mmengine - INFO - Epoch(train) [65][700/940] lr: 1.0000e-03 eta: 4:42:27 time: 0.4982 data_time: 0.0323 memory: 17006 grad_norm: 4.7524 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4430 loss: 1.4430 2022/10/13 07:56:25 - mmengine - INFO - Epoch(train) [65][720/940] lr: 1.0000e-03 eta: 4:42:17 time: 0.4988 data_time: 0.0354 memory: 17006 grad_norm: 4.6431 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2687 loss: 1.2687 2022/10/13 07:56:36 - mmengine - INFO - Epoch(train) [65][740/940] lr: 1.0000e-03 eta: 4:42:07 time: 0.5600 data_time: 0.0377 memory: 17006 grad_norm: 4.7266 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3141 loss: 1.3141 2022/10/13 07:56:45 - mmengine - INFO - Epoch(train) [65][760/940] lr: 1.0000e-03 eta: 4:41:56 time: 0.4581 data_time: 0.0324 memory: 17006 grad_norm: 4.7133 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.2951 loss: 1.2951 2022/10/13 07:56:56 - mmengine - INFO - Epoch(train) [65][780/940] lr: 1.0000e-03 eta: 4:41:46 time: 0.5428 data_time: 0.0320 memory: 17006 grad_norm: 4.6874 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4195 loss: 1.4195 2022/10/13 07:57:06 - mmengine - INFO - Epoch(train) [65][800/940] lr: 1.0000e-03 eta: 4:41:36 time: 0.5024 data_time: 0.0331 memory: 17006 grad_norm: 4.7725 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3121 loss: 1.3121 2022/10/13 07:57:18 - mmengine - INFO - Epoch(train) [65][820/940] lr: 1.0000e-03 eta: 4:41:26 time: 0.5678 data_time: 0.0375 memory: 17006 grad_norm: 4.7430 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2218 loss: 1.2218 2022/10/13 07:57:27 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 07:57:27 - mmengine - INFO - Epoch(train) [65][840/940] lr: 1.0000e-03 eta: 4:41:16 time: 0.4542 data_time: 0.0380 memory: 17006 grad_norm: 4.6084 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2370 loss: 1.2370 2022/10/13 07:57:37 - mmengine - INFO - Epoch(train) [65][860/940] lr: 1.0000e-03 eta: 4:41:06 time: 0.5413 data_time: 0.0316 memory: 17006 grad_norm: 4.7005 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4015 loss: 1.4015 2022/10/13 07:57:47 - mmengine - INFO - Epoch(train) [65][880/940] lr: 1.0000e-03 eta: 4:40:55 time: 0.4544 data_time: 0.0363 memory: 17006 grad_norm: 4.6529 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3992 loss: 1.3992 2022/10/13 07:57:57 - mmengine - INFO - Epoch(train) [65][900/940] lr: 1.0000e-03 eta: 4:40:45 time: 0.5374 data_time: 0.0301 memory: 17006 grad_norm: 4.7467 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.4287 loss: 1.4287 2022/10/13 07:58:07 - mmengine - INFO - Epoch(train) [65][920/940] lr: 1.0000e-03 eta: 4:40:35 time: 0.4962 data_time: 0.0374 memory: 17006 grad_norm: 4.7209 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3007 loss: 1.3007 2022/10/13 07:58:16 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 07:58:16 - mmengine - INFO - Epoch(train) [65][940/940] lr: 1.0000e-03 eta: 4:40:24 time: 0.4443 data_time: 0.0237 memory: 17006 grad_norm: 4.9805 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.1957 loss: 1.1957 2022/10/13 07:58:29 - mmengine - INFO - Epoch(val) [65][20/78] eta: 0:00:36 time: 0.6286 data_time: 0.5324 memory: 3172 2022/10/13 07:58:38 - mmengine - INFO - Epoch(val) [65][40/78] eta: 0:00:16 time: 0.4383 data_time: 0.3452 memory: 3172 2022/10/13 07:58:49 - mmengine - INFO - Epoch(val) [65][60/78] eta: 0:00:10 time: 0.5925 data_time: 0.5011 memory: 3172 2022/10/13 07:58:59 - mmengine - INFO - Epoch(val) [65][78/78] acc/top1: 0.6715 acc/top5: 0.8705 acc/mean1: 0.6715 2022/10/13 07:59:14 - mmengine - INFO - Epoch(train) [66][20/940] lr: 1.0000e-03 eta: 4:40:16 time: 0.7440 data_time: 0.2327 memory: 17006 grad_norm: 4.6142 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3186 loss: 1.3186 2022/10/13 07:59:23 - mmengine - INFO - Epoch(train) [66][40/940] lr: 1.0000e-03 eta: 4:40:05 time: 0.4456 data_time: 0.0346 memory: 17006 grad_norm: 4.5574 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2664 loss: 1.2664 2022/10/13 07:59:33 - mmengine - INFO - Epoch(train) [66][60/940] lr: 1.0000e-03 eta: 4:39:55 time: 0.5352 data_time: 0.1152 memory: 17006 grad_norm: 4.7604 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.2897 loss: 1.2897 2022/10/13 07:59:42 - mmengine - INFO - Epoch(train) [66][80/940] lr: 1.0000e-03 eta: 4:39:44 time: 0.4592 data_time: 0.0758 memory: 17006 grad_norm: 4.7263 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3910 loss: 1.3910 2022/10/13 07:59:54 - mmengine - INFO - Epoch(train) [66][100/940] lr: 1.0000e-03 eta: 4:39:34 time: 0.5640 data_time: 0.0456 memory: 17006 grad_norm: 4.6631 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4262 loss: 1.4262 2022/10/13 08:00:03 - mmengine - INFO - Epoch(train) [66][120/940] lr: 1.0000e-03 eta: 4:39:24 time: 0.4618 data_time: 0.0280 memory: 17006 grad_norm: 4.6280 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3835 loss: 1.3835 2022/10/13 08:00:14 - mmengine - INFO - Epoch(train) [66][140/940] lr: 1.0000e-03 eta: 4:39:14 time: 0.5556 data_time: 0.0329 memory: 17006 grad_norm: 4.6669 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2139 loss: 1.2139 2022/10/13 08:00:24 - mmengine - INFO - Epoch(train) [66][160/940] lr: 1.0000e-03 eta: 4:39:03 time: 0.4854 data_time: 0.0277 memory: 17006 grad_norm: 4.6850 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4867 loss: 1.4867 2022/10/13 08:00:35 - mmengine - INFO - Epoch(train) [66][180/940] lr: 1.0000e-03 eta: 4:38:54 time: 0.5660 data_time: 0.0299 memory: 17006 grad_norm: 4.6419 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3771 loss: 1.3771 2022/10/13 08:00:45 - mmengine - INFO - Epoch(train) [66][200/940] lr: 1.0000e-03 eta: 4:38:43 time: 0.4876 data_time: 0.0299 memory: 17006 grad_norm: 4.7458 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3240 loss: 1.3240 2022/10/13 08:00:56 - mmengine - INFO - Epoch(train) [66][220/940] lr: 1.0000e-03 eta: 4:38:34 time: 0.5782 data_time: 0.0300 memory: 17006 grad_norm: 4.7744 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2976 loss: 1.2976 2022/10/13 08:01:06 - mmengine - INFO - Epoch(train) [66][240/940] lr: 1.0000e-03 eta: 4:38:23 time: 0.4760 data_time: 0.0329 memory: 17006 grad_norm: 4.6933 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3884 loss: 1.3884 2022/10/13 08:01:17 - mmengine - INFO - Epoch(train) [66][260/940] lr: 1.0000e-03 eta: 4:38:13 time: 0.5363 data_time: 0.0290 memory: 17006 grad_norm: 4.7138 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3285 loss: 1.3285 2022/10/13 08:01:26 - mmengine - INFO - Epoch(train) [66][280/940] lr: 1.0000e-03 eta: 4:38:03 time: 0.4886 data_time: 0.0338 memory: 17006 grad_norm: 4.6123 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3613 loss: 1.3613 2022/10/13 08:01:37 - mmengine - INFO - Epoch(train) [66][300/940] lr: 1.0000e-03 eta: 4:37:53 time: 0.5489 data_time: 0.0306 memory: 17006 grad_norm: 4.6867 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2757 loss: 1.2757 2022/10/13 08:01:46 - mmengine - INFO - Epoch(train) [66][320/940] lr: 1.0000e-03 eta: 4:37:42 time: 0.4260 data_time: 0.0302 memory: 17006 grad_norm: 4.6619 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3291 loss: 1.3291 2022/10/13 08:01:56 - mmengine - INFO - Epoch(train) [66][340/940] lr: 1.0000e-03 eta: 4:37:31 time: 0.4943 data_time: 0.0286 memory: 17006 grad_norm: 4.6532 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3210 loss: 1.3210 2022/10/13 08:02:05 - mmengine - INFO - Epoch(train) [66][360/940] lr: 1.0000e-03 eta: 4:37:21 time: 0.4618 data_time: 0.0319 memory: 17006 grad_norm: 4.6935 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3418 loss: 1.3418 2022/10/13 08:02:16 - mmengine - INFO - Epoch(train) [66][380/940] lr: 1.0000e-03 eta: 4:37:11 time: 0.5361 data_time: 0.0287 memory: 17006 grad_norm: 4.7144 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3407 loss: 1.3407 2022/10/13 08:02:25 - mmengine - INFO - Epoch(train) [66][400/940] lr: 1.0000e-03 eta: 4:37:00 time: 0.4779 data_time: 0.0555 memory: 17006 grad_norm: 4.7446 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.4073 loss: 1.4073 2022/10/13 08:02:36 - mmengine - INFO - Epoch(train) [66][420/940] lr: 1.0000e-03 eta: 4:36:50 time: 0.5412 data_time: 0.0697 memory: 17006 grad_norm: 4.7416 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.4427 loss: 1.4427 2022/10/13 08:02:46 - mmengine - INFO - Epoch(train) [66][440/940] lr: 1.0000e-03 eta: 4:36:40 time: 0.4945 data_time: 0.0344 memory: 17006 grad_norm: 4.7224 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3190 loss: 1.3190 2022/10/13 08:02:57 - mmengine - INFO - Epoch(train) [66][460/940] lr: 1.0000e-03 eta: 4:36:30 time: 0.5375 data_time: 0.0273 memory: 17006 grad_norm: 4.7801 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3331 loss: 1.3331 2022/10/13 08:03:07 - mmengine - INFO - Epoch(train) [66][480/940] lr: 1.0000e-03 eta: 4:36:19 time: 0.4955 data_time: 0.0329 memory: 17006 grad_norm: 4.6165 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3912 loss: 1.3912 2022/10/13 08:03:17 - mmengine - INFO - Epoch(train) [66][500/940] lr: 1.0000e-03 eta: 4:36:09 time: 0.5145 data_time: 0.0303 memory: 17006 grad_norm: 4.8463 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.4572 loss: 1.4572 2022/10/13 08:03:28 - mmengine - INFO - Epoch(train) [66][520/940] lr: 1.0000e-03 eta: 4:35:59 time: 0.5248 data_time: 0.0376 memory: 17006 grad_norm: 4.6256 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3583 loss: 1.3583 2022/10/13 08:03:37 - mmengine - INFO - Epoch(train) [66][540/940] lr: 1.0000e-03 eta: 4:35:49 time: 0.4949 data_time: 0.0305 memory: 17006 grad_norm: 4.6201 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3521 loss: 1.3521 2022/10/13 08:03:47 - mmengine - INFO - Epoch(train) [66][560/940] lr: 1.0000e-03 eta: 4:35:38 time: 0.4780 data_time: 0.0314 memory: 17006 grad_norm: 4.7101 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.4116 loss: 1.4116 2022/10/13 08:03:57 - mmengine - INFO - Epoch(train) [66][580/940] lr: 1.0000e-03 eta: 4:35:28 time: 0.5006 data_time: 0.0369 memory: 17006 grad_norm: 4.7064 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3386 loss: 1.3386 2022/10/13 08:04:08 - mmengine - INFO - Epoch(train) [66][600/940] lr: 1.0000e-03 eta: 4:35:18 time: 0.5311 data_time: 0.0331 memory: 17006 grad_norm: 4.6499 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3427 loss: 1.3427 2022/10/13 08:04:18 - mmengine - INFO - Epoch(train) [66][620/940] lr: 1.0000e-03 eta: 4:35:08 time: 0.5221 data_time: 0.0301 memory: 17006 grad_norm: 4.8046 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3586 loss: 1.3586 2022/10/13 08:04:28 - mmengine - INFO - Epoch(train) [66][640/940] lr: 1.0000e-03 eta: 4:34:57 time: 0.5167 data_time: 0.0301 memory: 17006 grad_norm: 4.7415 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3642 loss: 1.3642 2022/10/13 08:04:38 - mmengine - INFO - Epoch(train) [66][660/940] lr: 1.0000e-03 eta: 4:34:47 time: 0.5033 data_time: 0.0311 memory: 17006 grad_norm: 4.6541 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4768 loss: 1.4768 2022/10/13 08:04:49 - mmengine - INFO - Epoch(train) [66][680/940] lr: 1.0000e-03 eta: 4:34:37 time: 0.5032 data_time: 0.0313 memory: 17006 grad_norm: 4.7370 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3513 loss: 1.3513 2022/10/13 08:04:58 - mmengine - INFO - Epoch(train) [66][700/940] lr: 1.0000e-03 eta: 4:34:26 time: 0.4722 data_time: 0.0365 memory: 17006 grad_norm: 4.7581 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4247 loss: 1.4247 2022/10/13 08:05:08 - mmengine - INFO - Epoch(train) [66][720/940] lr: 1.0000e-03 eta: 4:34:16 time: 0.5243 data_time: 0.0336 memory: 17006 grad_norm: 4.6803 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3629 loss: 1.3629 2022/10/13 08:05:19 - mmengine - INFO - Epoch(train) [66][740/940] lr: 1.0000e-03 eta: 4:34:06 time: 0.5025 data_time: 0.0285 memory: 17006 grad_norm: 4.6806 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3137 loss: 1.3137 2022/10/13 08:05:29 - mmengine - INFO - Epoch(train) [66][760/940] lr: 1.0000e-03 eta: 4:33:56 time: 0.5191 data_time: 0.0286 memory: 17006 grad_norm: 4.7086 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4460 loss: 1.4460 2022/10/13 08:05:38 - mmengine - INFO - Epoch(train) [66][780/940] lr: 1.0000e-03 eta: 4:33:45 time: 0.4533 data_time: 0.0332 memory: 17006 grad_norm: 4.6451 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2950 loss: 1.2950 2022/10/13 08:05:48 - mmengine - INFO - Epoch(train) [66][800/940] lr: 1.0000e-03 eta: 4:33:34 time: 0.4783 data_time: 0.0295 memory: 17006 grad_norm: 4.7282 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3239 loss: 1.3239 2022/10/13 08:05:58 - mmengine - INFO - Epoch(train) [66][820/940] lr: 1.0000e-03 eta: 4:33:24 time: 0.5187 data_time: 0.0324 memory: 17006 grad_norm: 4.7628 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2230 loss: 1.2230 2022/10/13 08:06:08 - mmengine - INFO - Epoch(train) [66][840/940] lr: 1.0000e-03 eta: 4:33:14 time: 0.5093 data_time: 0.0364 memory: 17006 grad_norm: 4.6849 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3622 loss: 1.3622 2022/10/13 08:06:18 - mmengine - INFO - Epoch(train) [66][860/940] lr: 1.0000e-03 eta: 4:33:04 time: 0.5029 data_time: 0.0349 memory: 17006 grad_norm: 4.7338 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3559 loss: 1.3559 2022/10/13 08:06:28 - mmengine - INFO - Epoch(train) [66][880/940] lr: 1.0000e-03 eta: 4:32:53 time: 0.5110 data_time: 0.0350 memory: 17006 grad_norm: 4.7066 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2981 loss: 1.2981 2022/10/13 08:06:38 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 08:06:38 - mmengine - INFO - Epoch(train) [66][900/940] lr: 1.0000e-03 eta: 4:32:43 time: 0.5041 data_time: 0.0325 memory: 17006 grad_norm: 4.6857 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3254 loss: 1.3254 2022/10/13 08:06:49 - mmengine - INFO - Epoch(train) [66][920/940] lr: 1.0000e-03 eta: 4:32:33 time: 0.5250 data_time: 0.0364 memory: 17006 grad_norm: 4.7774 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3618 loss: 1.3618 2022/10/13 08:06:58 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 08:06:58 - mmengine - INFO - Epoch(train) [66][940/940] lr: 1.0000e-03 eta: 4:32:22 time: 0.4294 data_time: 0.0236 memory: 17006 grad_norm: 5.0125 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.4497 loss: 1.4497 2022/10/13 08:06:58 - mmengine - INFO - Saving checkpoint at 66 epochs 2022/10/13 08:07:11 - mmengine - INFO - Epoch(val) [66][20/78] eta: 0:00:36 time: 0.6298 data_time: 0.5377 memory: 3172 2022/10/13 08:07:20 - mmengine - INFO - Epoch(val) [66][40/78] eta: 0:00:16 time: 0.4303 data_time: 0.3408 memory: 3172 2022/10/13 08:07:31 - mmengine - INFO - Epoch(val) [66][60/78] eta: 0:00:10 time: 0.5872 data_time: 0.4969 memory: 3172 2022/10/13 08:07:40 - mmengine - INFO - Epoch(val) [66][78/78] acc/top1: 0.6726 acc/top5: 0.8695 acc/mean1: 0.6726 2022/10/13 08:07:55 - mmengine - INFO - Epoch(train) [67][20/940] lr: 1.0000e-03 eta: 4:32:14 time: 0.7269 data_time: 0.2156 memory: 17006 grad_norm: 4.7654 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2862 loss: 1.2862 2022/10/13 08:08:04 - mmengine - INFO - Epoch(train) [67][40/940] lr: 1.0000e-03 eta: 4:32:03 time: 0.4225 data_time: 0.0289 memory: 17006 grad_norm: 4.7730 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2600 loss: 1.2600 2022/10/13 08:08:14 - mmengine - INFO - Epoch(train) [67][60/940] lr: 1.0000e-03 eta: 4:31:52 time: 0.5036 data_time: 0.0974 memory: 17006 grad_norm: 4.6705 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1931 loss: 1.1931 2022/10/13 08:08:23 - mmengine - INFO - Epoch(train) [67][80/940] lr: 1.0000e-03 eta: 4:31:42 time: 0.4704 data_time: 0.1481 memory: 17006 grad_norm: 4.7133 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.4243 loss: 1.4243 2022/10/13 08:08:34 - mmengine - INFO - Epoch(train) [67][100/940] lr: 1.0000e-03 eta: 4:31:32 time: 0.5671 data_time: 0.1809 memory: 17006 grad_norm: 4.8540 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4553 loss: 1.4553 2022/10/13 08:08:44 - mmengine - INFO - Epoch(train) [67][120/940] lr: 1.0000e-03 eta: 4:31:22 time: 0.5059 data_time: 0.1371 memory: 17006 grad_norm: 4.6647 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3209 loss: 1.3209 2022/10/13 08:08:55 - mmengine - INFO - Epoch(train) [67][140/940] lr: 1.0000e-03 eta: 4:31:12 time: 0.5159 data_time: 0.0359 memory: 17006 grad_norm: 4.6825 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4045 loss: 1.4045 2022/10/13 08:09:04 - mmengine - INFO - Epoch(train) [67][160/940] lr: 1.0000e-03 eta: 4:31:01 time: 0.4724 data_time: 0.0353 memory: 17006 grad_norm: 4.6565 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3010 loss: 1.3010 2022/10/13 08:09:15 - mmengine - INFO - Epoch(train) [67][180/940] lr: 1.0000e-03 eta: 4:30:51 time: 0.5620 data_time: 0.0369 memory: 17006 grad_norm: 4.7249 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2919 loss: 1.2919 2022/10/13 08:09:26 - mmengine - INFO - Epoch(train) [67][200/940] lr: 1.0000e-03 eta: 4:30:41 time: 0.5082 data_time: 0.0335 memory: 17006 grad_norm: 4.6984 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3440 loss: 1.3440 2022/10/13 08:09:35 - mmengine - INFO - Epoch(train) [67][220/940] lr: 1.0000e-03 eta: 4:30:31 time: 0.4871 data_time: 0.0356 memory: 17006 grad_norm: 4.6907 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2702 loss: 1.2702 2022/10/13 08:09:44 - mmengine - INFO - Epoch(train) [67][240/940] lr: 1.0000e-03 eta: 4:30:20 time: 0.4395 data_time: 0.0270 memory: 17006 grad_norm: 4.7578 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3074 loss: 1.3074 2022/10/13 08:09:55 - mmengine - INFO - Epoch(train) [67][260/940] lr: 1.0000e-03 eta: 4:30:09 time: 0.5191 data_time: 0.0319 memory: 17006 grad_norm: 4.6919 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2735 loss: 1.2735 2022/10/13 08:10:05 - mmengine - INFO - Epoch(train) [67][280/940] lr: 1.0000e-03 eta: 4:29:59 time: 0.5348 data_time: 0.0341 memory: 17006 grad_norm: 4.6570 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3544 loss: 1.3544 2022/10/13 08:10:15 - mmengine - INFO - Epoch(train) [67][300/940] lr: 1.0000e-03 eta: 4:29:49 time: 0.4756 data_time: 0.0435 memory: 17006 grad_norm: 4.5485 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3237 loss: 1.3237 2022/10/13 08:10:25 - mmengine - INFO - Epoch(train) [67][320/940] lr: 1.0000e-03 eta: 4:29:39 time: 0.4985 data_time: 0.0399 memory: 17006 grad_norm: 4.7409 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3993 loss: 1.3993 2022/10/13 08:10:35 - mmengine - INFO - Epoch(train) [67][340/940] lr: 1.0000e-03 eta: 4:29:28 time: 0.5134 data_time: 0.0335 memory: 17006 grad_norm: 4.6567 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3247 loss: 1.3247 2022/10/13 08:10:45 - mmengine - INFO - Epoch(train) [67][360/940] lr: 1.0000e-03 eta: 4:29:18 time: 0.5107 data_time: 0.0453 memory: 17006 grad_norm: 4.6884 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2516 loss: 1.2516 2022/10/13 08:10:56 - mmengine - INFO - Epoch(train) [67][380/940] lr: 1.0000e-03 eta: 4:29:08 time: 0.5310 data_time: 0.0318 memory: 17006 grad_norm: 4.6680 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3443 loss: 1.3443 2022/10/13 08:11:06 - mmengine - INFO - Epoch(train) [67][400/940] lr: 1.0000e-03 eta: 4:28:58 time: 0.5106 data_time: 0.0257 memory: 17006 grad_norm: 4.6915 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3223 loss: 1.3223 2022/10/13 08:11:17 - mmengine - INFO - Epoch(train) [67][420/940] lr: 1.0000e-03 eta: 4:28:48 time: 0.5244 data_time: 0.0385 memory: 17006 grad_norm: 4.6053 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2890 loss: 1.2890 2022/10/13 08:11:26 - mmengine - INFO - Epoch(train) [67][440/940] lr: 1.0000e-03 eta: 4:28:37 time: 0.4682 data_time: 0.0266 memory: 17006 grad_norm: 4.6851 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3922 loss: 1.3922 2022/10/13 08:11:37 - mmengine - INFO - Epoch(train) [67][460/940] lr: 1.0000e-03 eta: 4:28:27 time: 0.5306 data_time: 0.0340 memory: 17006 grad_norm: 4.6609 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2972 loss: 1.2972 2022/10/13 08:11:46 - mmengine - INFO - Epoch(train) [67][480/940] lr: 1.0000e-03 eta: 4:28:17 time: 0.4924 data_time: 0.0379 memory: 17006 grad_norm: 4.7383 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2059 loss: 1.2059 2022/10/13 08:11:57 - mmengine - INFO - Epoch(train) [67][500/940] lr: 1.0000e-03 eta: 4:28:07 time: 0.5260 data_time: 0.0703 memory: 17006 grad_norm: 4.7390 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3169 loss: 1.3169 2022/10/13 08:12:07 - mmengine - INFO - Epoch(train) [67][520/940] lr: 1.0000e-03 eta: 4:27:56 time: 0.5210 data_time: 0.0507 memory: 17006 grad_norm: 4.6797 top1_acc: 0.6875 top5_acc: 1.0000 loss_cls: 1.2983 loss: 1.2983 2022/10/13 08:12:18 - mmengine - INFO - Epoch(train) [67][540/940] lr: 1.0000e-03 eta: 4:27:46 time: 0.5332 data_time: 0.0310 memory: 17006 grad_norm: 4.7726 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4400 loss: 1.4400 2022/10/13 08:12:28 - mmengine - INFO - Epoch(train) [67][560/940] lr: 1.0000e-03 eta: 4:27:36 time: 0.4912 data_time: 0.0316 memory: 17006 grad_norm: 4.7388 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3539 loss: 1.3539 2022/10/13 08:12:38 - mmengine - INFO - Epoch(train) [67][580/940] lr: 1.0000e-03 eta: 4:27:25 time: 0.4876 data_time: 0.0340 memory: 17006 grad_norm: 4.7205 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4304 loss: 1.4304 2022/10/13 08:12:48 - mmengine - INFO - Epoch(train) [67][600/940] lr: 1.0000e-03 eta: 4:27:15 time: 0.5325 data_time: 0.0554 memory: 17006 grad_norm: 4.7179 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4066 loss: 1.4066 2022/10/13 08:12:58 - mmengine - INFO - Epoch(train) [67][620/940] lr: 1.0000e-03 eta: 4:27:05 time: 0.5065 data_time: 0.0759 memory: 17006 grad_norm: 4.5921 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2949 loss: 1.2949 2022/10/13 08:13:08 - mmengine - INFO - Epoch(train) [67][640/940] lr: 1.0000e-03 eta: 4:26:55 time: 0.4850 data_time: 0.0316 memory: 17006 grad_norm: 4.6969 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3576 loss: 1.3576 2022/10/13 08:13:18 - mmengine - INFO - Epoch(train) [67][660/940] lr: 1.0000e-03 eta: 4:26:44 time: 0.4947 data_time: 0.0367 memory: 17006 grad_norm: 4.6547 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3396 loss: 1.3396 2022/10/13 08:13:28 - mmengine - INFO - Epoch(train) [67][680/940] lr: 1.0000e-03 eta: 4:26:34 time: 0.5059 data_time: 0.0311 memory: 17006 grad_norm: 4.7504 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.4139 loss: 1.4139 2022/10/13 08:13:38 - mmengine - INFO - Epoch(train) [67][700/940] lr: 1.0000e-03 eta: 4:26:24 time: 0.4875 data_time: 0.0335 memory: 17006 grad_norm: 4.6685 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3088 loss: 1.3088 2022/10/13 08:13:49 - mmengine - INFO - Epoch(train) [67][720/940] lr: 1.0000e-03 eta: 4:26:14 time: 0.5417 data_time: 0.0286 memory: 17006 grad_norm: 4.6249 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2988 loss: 1.2988 2022/10/13 08:13:58 - mmengine - INFO - Epoch(train) [67][740/940] lr: 1.0000e-03 eta: 4:26:03 time: 0.4460 data_time: 0.0351 memory: 17006 grad_norm: 4.7329 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4215 loss: 1.4215 2022/10/13 08:14:08 - mmengine - INFO - Epoch(train) [67][760/940] lr: 1.0000e-03 eta: 4:25:53 time: 0.5424 data_time: 0.0335 memory: 17006 grad_norm: 4.6997 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.4464 loss: 1.4464 2022/10/13 08:14:18 - mmengine - INFO - Epoch(train) [67][780/940] lr: 1.0000e-03 eta: 4:25:42 time: 0.4955 data_time: 0.0316 memory: 17006 grad_norm: 4.6320 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3568 loss: 1.3568 2022/10/13 08:14:29 - mmengine - INFO - Epoch(train) [67][800/940] lr: 1.0000e-03 eta: 4:25:32 time: 0.5340 data_time: 0.0333 memory: 17006 grad_norm: 4.6858 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3241 loss: 1.3241 2022/10/13 08:14:38 - mmengine - INFO - Epoch(train) [67][820/940] lr: 1.0000e-03 eta: 4:25:22 time: 0.4602 data_time: 0.0319 memory: 17006 grad_norm: 4.6888 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3624 loss: 1.3624 2022/10/13 08:14:49 - mmengine - INFO - Epoch(train) [67][840/940] lr: 1.0000e-03 eta: 4:25:12 time: 0.5196 data_time: 0.0328 memory: 17006 grad_norm: 4.7074 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.3632 loss: 1.3632 2022/10/13 08:14:59 - mmengine - INFO - Epoch(train) [67][860/940] lr: 1.0000e-03 eta: 4:25:01 time: 0.5113 data_time: 0.0351 memory: 17006 grad_norm: 4.7165 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.3648 loss: 1.3648 2022/10/13 08:15:09 - mmengine - INFO - Epoch(train) [67][880/940] lr: 1.0000e-03 eta: 4:24:51 time: 0.5058 data_time: 0.0304 memory: 17006 grad_norm: 4.8153 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3166 loss: 1.3166 2022/10/13 08:15:20 - mmengine - INFO - Epoch(train) [67][900/940] lr: 1.0000e-03 eta: 4:24:41 time: 0.5563 data_time: 0.0282 memory: 17006 grad_norm: 4.7264 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3662 loss: 1.3662 2022/10/13 08:15:29 - mmengine - INFO - Epoch(train) [67][920/940] lr: 1.0000e-03 eta: 4:24:31 time: 0.4526 data_time: 0.0314 memory: 17006 grad_norm: 4.7454 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2681 loss: 1.2681 2022/10/13 08:15:39 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 08:15:39 - mmengine - INFO - Epoch(train) [67][940/940] lr: 1.0000e-03 eta: 4:24:20 time: 0.4832 data_time: 0.0266 memory: 17006 grad_norm: 4.9016 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.3199 loss: 1.3199 2022/10/13 08:15:52 - mmengine - INFO - Epoch(val) [67][20/78] eta: 0:00:36 time: 0.6345 data_time: 0.5400 memory: 3172 2022/10/13 08:16:00 - mmengine - INFO - Epoch(val) [67][40/78] eta: 0:00:16 time: 0.4327 data_time: 0.3417 memory: 3172 2022/10/13 08:16:12 - mmengine - INFO - Epoch(val) [67][60/78] eta: 0:00:10 time: 0.5653 data_time: 0.4740 memory: 3172 2022/10/13 08:16:21 - mmengine - INFO - Epoch(val) [67][78/78] acc/top1: 0.6712 acc/top5: 0.8689 acc/mean1: 0.6711 2022/10/13 08:16:35 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 08:16:35 - mmengine - INFO - Epoch(train) [68][20/940] lr: 1.0000e-03 eta: 4:24:12 time: 0.6939 data_time: 0.3027 memory: 17006 grad_norm: 4.6897 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3838 loss: 1.3838 2022/10/13 08:16:45 - mmengine - INFO - Epoch(train) [68][40/940] lr: 1.0000e-03 eta: 4:24:01 time: 0.4941 data_time: 0.0601 memory: 17006 grad_norm: 4.7318 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3416 loss: 1.3416 2022/10/13 08:16:56 - mmengine - INFO - Epoch(train) [68][60/940] lr: 1.0000e-03 eta: 4:23:51 time: 0.5429 data_time: 0.0348 memory: 17006 grad_norm: 4.8161 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2850 loss: 1.2850 2022/10/13 08:17:05 - mmengine - INFO - Epoch(train) [68][80/940] lr: 1.0000e-03 eta: 4:23:41 time: 0.4646 data_time: 0.0331 memory: 17006 grad_norm: 4.6999 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.3515 loss: 1.3515 2022/10/13 08:17:16 - mmengine - INFO - Epoch(train) [68][100/940] lr: 1.0000e-03 eta: 4:23:31 time: 0.5544 data_time: 0.0437 memory: 17006 grad_norm: 4.6580 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2279 loss: 1.2279 2022/10/13 08:17:26 - mmengine - INFO - Epoch(train) [68][120/940] lr: 1.0000e-03 eta: 4:23:20 time: 0.5037 data_time: 0.0271 memory: 17006 grad_norm: 4.6988 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4080 loss: 1.4080 2022/10/13 08:17:37 - mmengine - INFO - Epoch(train) [68][140/940] lr: 1.0000e-03 eta: 4:23:10 time: 0.5081 data_time: 0.0316 memory: 17006 grad_norm: 4.7445 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2524 loss: 1.2524 2022/10/13 08:17:46 - mmengine - INFO - Epoch(train) [68][160/940] lr: 1.0000e-03 eta: 4:23:00 time: 0.4827 data_time: 0.0302 memory: 17006 grad_norm: 4.6022 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.4105 loss: 1.4105 2022/10/13 08:17:57 - mmengine - INFO - Epoch(train) [68][180/940] lr: 1.0000e-03 eta: 4:22:50 time: 0.5173 data_time: 0.0324 memory: 17006 grad_norm: 4.6686 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2602 loss: 1.2602 2022/10/13 08:18:07 - mmengine - INFO - Epoch(train) [68][200/940] lr: 1.0000e-03 eta: 4:22:39 time: 0.5316 data_time: 0.0352 memory: 17006 grad_norm: 4.6353 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2419 loss: 1.2419 2022/10/13 08:18:17 - mmengine - INFO - Epoch(train) [68][220/940] lr: 1.0000e-03 eta: 4:22:29 time: 0.4866 data_time: 0.0313 memory: 17006 grad_norm: 4.6753 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2427 loss: 1.2427 2022/10/13 08:18:27 - mmengine - INFO - Epoch(train) [68][240/940] lr: 1.0000e-03 eta: 4:22:19 time: 0.5173 data_time: 0.0353 memory: 17006 grad_norm: 4.6965 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2459 loss: 1.2459 2022/10/13 08:18:38 - mmengine - INFO - Epoch(train) [68][260/940] lr: 1.0000e-03 eta: 4:22:09 time: 0.5136 data_time: 0.0341 memory: 17006 grad_norm: 4.6263 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3481 loss: 1.3481 2022/10/13 08:18:49 - mmengine - INFO - Epoch(train) [68][280/940] lr: 1.0000e-03 eta: 4:21:59 time: 0.5624 data_time: 0.0321 memory: 17006 grad_norm: 4.6652 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5112 loss: 1.5112 2022/10/13 08:18:58 - mmengine - INFO - Epoch(train) [68][300/940] lr: 1.0000e-03 eta: 4:21:48 time: 0.4609 data_time: 0.0313 memory: 17006 grad_norm: 4.7083 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2445 loss: 1.2445 2022/10/13 08:19:08 - mmengine - INFO - Epoch(train) [68][320/940] lr: 1.0000e-03 eta: 4:21:38 time: 0.5112 data_time: 0.0329 memory: 17006 grad_norm: 4.6780 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3140 loss: 1.3140 2022/10/13 08:19:18 - mmengine - INFO - Epoch(train) [68][340/940] lr: 1.0000e-03 eta: 4:21:28 time: 0.4857 data_time: 0.0293 memory: 17006 grad_norm: 4.7242 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3220 loss: 1.3220 2022/10/13 08:19:28 - mmengine - INFO - Epoch(train) [68][360/940] lr: 1.0000e-03 eta: 4:21:17 time: 0.4928 data_time: 0.0346 memory: 17006 grad_norm: 4.6689 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3269 loss: 1.3269 2022/10/13 08:19:38 - mmengine - INFO - Epoch(train) [68][380/940] lr: 1.0000e-03 eta: 4:21:07 time: 0.5223 data_time: 0.0325 memory: 17006 grad_norm: 4.8377 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.2629 loss: 1.2629 2022/10/13 08:19:48 - mmengine - INFO - Epoch(train) [68][400/940] lr: 1.0000e-03 eta: 4:20:56 time: 0.4808 data_time: 0.0334 memory: 17006 grad_norm: 4.7252 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3379 loss: 1.3379 2022/10/13 08:19:58 - mmengine - INFO - Epoch(train) [68][420/940] lr: 1.0000e-03 eta: 4:20:46 time: 0.4850 data_time: 0.0336 memory: 17006 grad_norm: 4.6478 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3608 loss: 1.3608 2022/10/13 08:20:08 - mmengine - INFO - Epoch(train) [68][440/940] lr: 1.0000e-03 eta: 4:20:36 time: 0.5386 data_time: 0.0371 memory: 17006 grad_norm: 4.7398 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4196 loss: 1.4196 2022/10/13 08:20:18 - mmengine - INFO - Epoch(train) [68][460/940] lr: 1.0000e-03 eta: 4:20:26 time: 0.4931 data_time: 0.0320 memory: 17006 grad_norm: 4.6367 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.4070 loss: 1.4070 2022/10/13 08:20:28 - mmengine - INFO - Epoch(train) [68][480/940] lr: 1.0000e-03 eta: 4:20:15 time: 0.4891 data_time: 0.0318 memory: 17006 grad_norm: 4.8005 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.1868 loss: 1.1868 2022/10/13 08:20:38 - mmengine - INFO - Epoch(train) [68][500/940] lr: 1.0000e-03 eta: 4:20:05 time: 0.5160 data_time: 0.0346 memory: 17006 grad_norm: 4.5688 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3759 loss: 1.3759 2022/10/13 08:20:50 - mmengine - INFO - Epoch(train) [68][520/940] lr: 1.0000e-03 eta: 4:19:55 time: 0.5768 data_time: 0.0342 memory: 17006 grad_norm: 4.6250 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2329 loss: 1.2329 2022/10/13 08:20:59 - mmengine - INFO - Epoch(train) [68][540/940] lr: 1.0000e-03 eta: 4:19:45 time: 0.4606 data_time: 0.0359 memory: 17006 grad_norm: 4.7188 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3906 loss: 1.3906 2022/10/13 08:21:09 - mmengine - INFO - Epoch(train) [68][560/940] lr: 1.0000e-03 eta: 4:19:34 time: 0.4969 data_time: 0.0300 memory: 17006 grad_norm: 4.7487 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3133 loss: 1.3133 2022/10/13 08:21:19 - mmengine - INFO - Epoch(train) [68][580/940] lr: 1.0000e-03 eta: 4:19:24 time: 0.5042 data_time: 0.0361 memory: 17006 grad_norm: 4.7388 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.2712 loss: 1.2712 2022/10/13 08:21:30 - mmengine - INFO - Epoch(train) [68][600/940] lr: 1.0000e-03 eta: 4:19:14 time: 0.5201 data_time: 0.0315 memory: 17006 grad_norm: 4.7782 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2562 loss: 1.2562 2022/10/13 08:21:41 - mmengine - INFO - Epoch(train) [68][620/940] lr: 1.0000e-03 eta: 4:19:04 time: 0.5487 data_time: 0.0358 memory: 17006 grad_norm: 4.6753 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3113 loss: 1.3113 2022/10/13 08:21:50 - mmengine - INFO - Epoch(train) [68][640/940] lr: 1.0000e-03 eta: 4:18:53 time: 0.4527 data_time: 0.0361 memory: 17006 grad_norm: 4.7317 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2819 loss: 1.2819 2022/10/13 08:22:00 - mmengine - INFO - Epoch(train) [68][660/940] lr: 1.0000e-03 eta: 4:18:43 time: 0.5308 data_time: 0.0321 memory: 17006 grad_norm: 4.6982 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2365 loss: 1.2365 2022/10/13 08:22:10 - mmengine - INFO - Epoch(train) [68][680/940] lr: 1.0000e-03 eta: 4:18:33 time: 0.4723 data_time: 0.0320 memory: 17006 grad_norm: 4.6535 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3563 loss: 1.3563 2022/10/13 08:22:19 - mmengine - INFO - Epoch(train) [68][700/940] lr: 1.0000e-03 eta: 4:18:22 time: 0.4801 data_time: 0.0316 memory: 17006 grad_norm: 4.7181 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2884 loss: 1.2884 2022/10/13 08:22:29 - mmengine - INFO - Epoch(train) [68][720/940] lr: 1.0000e-03 eta: 4:18:11 time: 0.4660 data_time: 0.0314 memory: 17006 grad_norm: 4.6522 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.1999 loss: 1.1999 2022/10/13 08:22:41 - mmengine - INFO - Epoch(train) [68][740/940] lr: 1.0000e-03 eta: 4:18:02 time: 0.6090 data_time: 0.0338 memory: 17006 grad_norm: 4.7961 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2987 loss: 1.2987 2022/10/13 08:22:50 - mmengine - INFO - Epoch(train) [68][760/940] lr: 1.0000e-03 eta: 4:17:51 time: 0.4420 data_time: 0.0293 memory: 17006 grad_norm: 4.7822 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4728 loss: 1.4728 2022/10/13 08:23:00 - mmengine - INFO - Epoch(train) [68][780/940] lr: 1.0000e-03 eta: 4:17:41 time: 0.5393 data_time: 0.0332 memory: 17006 grad_norm: 4.6728 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2085 loss: 1.2085 2022/10/13 08:23:10 - mmengine - INFO - Epoch(train) [68][800/940] lr: 1.0000e-03 eta: 4:17:31 time: 0.4679 data_time: 0.0318 memory: 17006 grad_norm: 4.6664 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.3265 loss: 1.3265 2022/10/13 08:23:21 - mmengine - INFO - Epoch(train) [68][820/940] lr: 1.0000e-03 eta: 4:17:21 time: 0.5609 data_time: 0.0382 memory: 17006 grad_norm: 4.8461 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3391 loss: 1.3391 2022/10/13 08:23:31 - mmengine - INFO - Epoch(train) [68][840/940] lr: 1.0000e-03 eta: 4:17:10 time: 0.4887 data_time: 0.0318 memory: 17006 grad_norm: 4.7618 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3613 loss: 1.3613 2022/10/13 08:23:41 - mmengine - INFO - Epoch(train) [68][860/940] lr: 1.0000e-03 eta: 4:17:00 time: 0.5013 data_time: 0.0315 memory: 17006 grad_norm: 4.6857 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2762 loss: 1.2762 2022/10/13 08:23:50 - mmengine - INFO - Epoch(train) [68][880/940] lr: 1.0000e-03 eta: 4:16:49 time: 0.4709 data_time: 0.0307 memory: 17006 grad_norm: 4.7900 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3084 loss: 1.3084 2022/10/13 08:24:00 - mmengine - INFO - Epoch(train) [68][900/940] lr: 1.0000e-03 eta: 4:16:39 time: 0.4957 data_time: 0.0342 memory: 17006 grad_norm: 4.6976 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1899 loss: 1.1899 2022/10/13 08:24:11 - mmengine - INFO - Epoch(train) [68][920/940] lr: 1.0000e-03 eta: 4:16:29 time: 0.5373 data_time: 0.0330 memory: 17006 grad_norm: 4.8157 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3557 loss: 1.3557 2022/10/13 08:24:20 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 08:24:20 - mmengine - INFO - Epoch(train) [68][940/940] lr: 1.0000e-03 eta: 4:16:18 time: 0.4369 data_time: 0.0299 memory: 17006 grad_norm: 5.0912 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.4049 loss: 1.4049 2022/10/13 08:24:32 - mmengine - INFO - Epoch(val) [68][20/78] eta: 0:00:36 time: 0.6253 data_time: 0.5325 memory: 3172 2022/10/13 08:24:41 - mmengine - INFO - Epoch(val) [68][40/78] eta: 0:00:16 time: 0.4304 data_time: 0.3363 memory: 3172 2022/10/13 08:24:52 - mmengine - INFO - Epoch(val) [68][60/78] eta: 0:00:10 time: 0.5783 data_time: 0.4861 memory: 3172 2022/10/13 08:25:02 - mmengine - INFO - Epoch(val) [68][78/78] acc/top1: 0.6686 acc/top5: 0.8671 acc/mean1: 0.6685 2022/10/13 08:25:16 - mmengine - INFO - Epoch(train) [69][20/940] lr: 1.0000e-03 eta: 4:16:10 time: 0.6942 data_time: 0.3281 memory: 17006 grad_norm: 4.7115 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2658 loss: 1.2658 2022/10/13 08:25:25 - mmengine - INFO - Epoch(train) [69][40/940] lr: 1.0000e-03 eta: 4:15:59 time: 0.4650 data_time: 0.1089 memory: 17006 grad_norm: 4.7280 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4027 loss: 1.4027 2022/10/13 08:25:37 - mmengine - INFO - Epoch(train) [69][60/940] lr: 1.0000e-03 eta: 4:15:49 time: 0.5625 data_time: 0.0465 memory: 17006 grad_norm: 4.6547 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2369 loss: 1.2369 2022/10/13 08:25:46 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 08:25:46 - mmengine - INFO - Epoch(train) [69][80/940] lr: 1.0000e-03 eta: 4:15:39 time: 0.4832 data_time: 0.0268 memory: 17006 grad_norm: 4.7364 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4538 loss: 1.4538 2022/10/13 08:25:58 - mmengine - INFO - Epoch(train) [69][100/940] lr: 1.0000e-03 eta: 4:15:29 time: 0.5729 data_time: 0.0383 memory: 17006 grad_norm: 4.6936 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2773 loss: 1.2773 2022/10/13 08:26:07 - mmengine - INFO - Epoch(train) [69][120/940] lr: 1.0000e-03 eta: 4:15:18 time: 0.4562 data_time: 0.0260 memory: 17006 grad_norm: 4.6453 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2200 loss: 1.2200 2022/10/13 08:26:17 - mmengine - INFO - Epoch(train) [69][140/940] lr: 1.0000e-03 eta: 4:15:08 time: 0.5117 data_time: 0.0331 memory: 17006 grad_norm: 4.7226 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1985 loss: 1.1985 2022/10/13 08:26:26 - mmengine - INFO - Epoch(train) [69][160/940] lr: 1.0000e-03 eta: 4:14:57 time: 0.4348 data_time: 0.0272 memory: 17006 grad_norm: 4.7687 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3730 loss: 1.3730 2022/10/13 08:26:36 - mmengine - INFO - Epoch(train) [69][180/940] lr: 1.0000e-03 eta: 4:14:47 time: 0.5334 data_time: 0.0323 memory: 17006 grad_norm: 4.7528 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2375 loss: 1.2375 2022/10/13 08:26:46 - mmengine - INFO - Epoch(train) [69][200/940] lr: 1.0000e-03 eta: 4:14:37 time: 0.4717 data_time: 0.0288 memory: 17006 grad_norm: 4.7383 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2662 loss: 1.2662 2022/10/13 08:26:57 - mmengine - INFO - Epoch(train) [69][220/940] lr: 1.0000e-03 eta: 4:14:27 time: 0.5636 data_time: 0.0401 memory: 17006 grad_norm: 4.8787 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3853 loss: 1.3853 2022/10/13 08:27:07 - mmengine - INFO - Epoch(train) [69][240/940] lr: 1.0000e-03 eta: 4:14:17 time: 0.4969 data_time: 0.0328 memory: 17006 grad_norm: 4.7364 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4118 loss: 1.4118 2022/10/13 08:27:18 - mmengine - INFO - Epoch(train) [69][260/940] lr: 1.0000e-03 eta: 4:14:06 time: 0.5225 data_time: 0.0317 memory: 17006 grad_norm: 4.7178 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2602 loss: 1.2602 2022/10/13 08:27:28 - mmengine - INFO - Epoch(train) [69][280/940] lr: 1.0000e-03 eta: 4:13:56 time: 0.5006 data_time: 0.0295 memory: 17006 grad_norm: 4.7316 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4880 loss: 1.4880 2022/10/13 08:27:38 - mmengine - INFO - Epoch(train) [69][300/940] lr: 1.0000e-03 eta: 4:13:46 time: 0.5105 data_time: 0.0326 memory: 17006 grad_norm: 4.7778 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3819 loss: 1.3819 2022/10/13 08:27:48 - mmengine - INFO - Epoch(train) [69][320/940] lr: 1.0000e-03 eta: 4:13:36 time: 0.5092 data_time: 0.0291 memory: 17006 grad_norm: 4.7840 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3250 loss: 1.3250 2022/10/13 08:27:57 - mmengine - INFO - Epoch(train) [69][340/940] lr: 1.0000e-03 eta: 4:13:25 time: 0.4744 data_time: 0.0337 memory: 17006 grad_norm: 4.7732 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3777 loss: 1.3777 2022/10/13 08:28:08 - mmengine - INFO - Epoch(train) [69][360/940] lr: 1.0000e-03 eta: 4:13:15 time: 0.5358 data_time: 0.0288 memory: 17006 grad_norm: 4.8006 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3567 loss: 1.3567 2022/10/13 08:28:18 - mmengine - INFO - Epoch(train) [69][380/940] lr: 1.0000e-03 eta: 4:13:04 time: 0.4679 data_time: 0.0361 memory: 17006 grad_norm: 4.7116 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2686 loss: 1.2686 2022/10/13 08:28:30 - mmengine - INFO - Epoch(train) [69][400/940] lr: 1.0000e-03 eta: 4:12:55 time: 0.5989 data_time: 0.0305 memory: 17006 grad_norm: 4.6739 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.2252 loss: 1.2252 2022/10/13 08:28:39 - mmengine - INFO - Epoch(train) [69][420/940] lr: 1.0000e-03 eta: 4:12:45 time: 0.4902 data_time: 0.0285 memory: 17006 grad_norm: 4.7366 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2361 loss: 1.2361 2022/10/13 08:28:49 - mmengine - INFO - Epoch(train) [69][440/940] lr: 1.0000e-03 eta: 4:12:34 time: 0.5080 data_time: 0.0301 memory: 17006 grad_norm: 4.7044 top1_acc: 0.6250 top5_acc: 0.6875 loss_cls: 1.3969 loss: 1.3969 2022/10/13 08:28:59 - mmengine - INFO - Epoch(train) [69][460/940] lr: 1.0000e-03 eta: 4:12:24 time: 0.4860 data_time: 0.0341 memory: 17006 grad_norm: 4.7281 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.1490 loss: 1.1490 2022/10/13 08:29:10 - mmengine - INFO - Epoch(train) [69][480/940] lr: 1.0000e-03 eta: 4:12:14 time: 0.5319 data_time: 0.0335 memory: 17006 grad_norm: 4.8957 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3813 loss: 1.3813 2022/10/13 08:29:20 - mmengine - INFO - Epoch(train) [69][500/940] lr: 1.0000e-03 eta: 4:12:03 time: 0.4870 data_time: 0.0280 memory: 17006 grad_norm: 4.7898 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4444 loss: 1.4444 2022/10/13 08:29:29 - mmengine - INFO - Epoch(train) [69][520/940] lr: 1.0000e-03 eta: 4:11:53 time: 0.4946 data_time: 0.0302 memory: 17006 grad_norm: 4.8510 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3396 loss: 1.3396 2022/10/13 08:29:38 - mmengine - INFO - Epoch(train) [69][540/940] lr: 1.0000e-03 eta: 4:11:42 time: 0.4409 data_time: 0.0310 memory: 17006 grad_norm: 4.7804 top1_acc: 0.7188 top5_acc: 0.7500 loss_cls: 1.2972 loss: 1.2972 2022/10/13 08:29:49 - mmengine - INFO - Epoch(train) [69][560/940] lr: 1.0000e-03 eta: 4:11:32 time: 0.5208 data_time: 0.0354 memory: 17006 grad_norm: 4.7954 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3017 loss: 1.3017 2022/10/13 08:29:58 - mmengine - INFO - Epoch(train) [69][580/940] lr: 1.0000e-03 eta: 4:11:22 time: 0.4807 data_time: 0.0334 memory: 17006 grad_norm: 4.8255 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3095 loss: 1.3095 2022/10/13 08:30:09 - mmengine - INFO - Epoch(train) [69][600/940] lr: 1.0000e-03 eta: 4:11:11 time: 0.5327 data_time: 0.0344 memory: 17006 grad_norm: 4.8407 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.3026 loss: 1.3026 2022/10/13 08:30:19 - mmengine - INFO - Epoch(train) [69][620/940] lr: 1.0000e-03 eta: 4:11:01 time: 0.5228 data_time: 0.0317 memory: 17006 grad_norm: 4.8619 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3545 loss: 1.3545 2022/10/13 08:30:29 - mmengine - INFO - Epoch(train) [69][640/940] lr: 1.0000e-03 eta: 4:10:51 time: 0.4925 data_time: 0.0311 memory: 17006 grad_norm: 4.7578 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2077 loss: 1.2077 2022/10/13 08:30:39 - mmengine - INFO - Epoch(train) [69][660/940] lr: 1.0000e-03 eta: 4:10:41 time: 0.4922 data_time: 0.0347 memory: 17006 grad_norm: 4.8215 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2848 loss: 1.2848 2022/10/13 08:30:49 - mmengine - INFO - Epoch(train) [69][680/940] lr: 1.0000e-03 eta: 4:10:30 time: 0.4993 data_time: 0.0372 memory: 17006 grad_norm: 4.7766 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.3437 loss: 1.3437 2022/10/13 08:31:00 - mmengine - INFO - Epoch(train) [69][700/940] lr: 1.0000e-03 eta: 4:10:20 time: 0.5265 data_time: 0.0337 memory: 17006 grad_norm: 4.6995 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1817 loss: 1.1817 2022/10/13 08:31:09 - mmengine - INFO - Epoch(train) [69][720/940] lr: 1.0000e-03 eta: 4:10:09 time: 0.4631 data_time: 0.0338 memory: 17006 grad_norm: 4.8221 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3074 loss: 1.3074 2022/10/13 08:31:20 - mmengine - INFO - Epoch(train) [69][740/940] lr: 1.0000e-03 eta: 4:10:00 time: 0.5743 data_time: 0.0353 memory: 17006 grad_norm: 4.6609 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2946 loss: 1.2946 2022/10/13 08:31:30 - mmengine - INFO - Epoch(train) [69][760/940] lr: 1.0000e-03 eta: 4:09:49 time: 0.4662 data_time: 0.0308 memory: 17006 grad_norm: 4.7983 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4357 loss: 1.4357 2022/10/13 08:31:40 - mmengine - INFO - Epoch(train) [69][780/940] lr: 1.0000e-03 eta: 4:09:39 time: 0.5304 data_time: 0.0340 memory: 17006 grad_norm: 4.8401 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3338 loss: 1.3338 2022/10/13 08:31:50 - mmengine - INFO - Epoch(train) [69][800/940] lr: 1.0000e-03 eta: 4:09:29 time: 0.4743 data_time: 0.0410 memory: 17006 grad_norm: 4.7449 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2997 loss: 1.2997 2022/10/13 08:32:00 - mmengine - INFO - Epoch(train) [69][820/940] lr: 1.0000e-03 eta: 4:09:18 time: 0.5026 data_time: 0.0506 memory: 17006 grad_norm: 4.6719 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3492 loss: 1.3492 2022/10/13 08:32:10 - mmengine - INFO - Epoch(train) [69][840/940] lr: 1.0000e-03 eta: 4:09:08 time: 0.5079 data_time: 0.1036 memory: 17006 grad_norm: 4.8119 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4184 loss: 1.4184 2022/10/13 08:32:20 - mmengine - INFO - Epoch(train) [69][860/940] lr: 1.0000e-03 eta: 4:08:58 time: 0.5168 data_time: 0.1045 memory: 17006 grad_norm: 4.7736 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3044 loss: 1.3044 2022/10/13 08:32:31 - mmengine - INFO - Epoch(train) [69][880/940] lr: 1.0000e-03 eta: 4:08:48 time: 0.5096 data_time: 0.0281 memory: 17006 grad_norm: 4.8347 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.3439 loss: 1.3439 2022/10/13 08:32:40 - mmengine - INFO - Epoch(train) [69][900/940] lr: 1.0000e-03 eta: 4:08:37 time: 0.4742 data_time: 0.0644 memory: 17006 grad_norm: 4.7247 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2928 loss: 1.2928 2022/10/13 08:32:50 - mmengine - INFO - Epoch(train) [69][920/940] lr: 1.0000e-03 eta: 4:08:27 time: 0.4960 data_time: 0.0340 memory: 17006 grad_norm: 4.7782 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3686 loss: 1.3686 2022/10/13 08:32:59 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 08:32:59 - mmengine - INFO - Epoch(train) [69][940/940] lr: 1.0000e-03 eta: 4:08:16 time: 0.4310 data_time: 0.0287 memory: 17006 grad_norm: 4.9185 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.2418 loss: 1.2418 2022/10/13 08:32:59 - mmengine - INFO - Saving checkpoint at 69 epochs 2022/10/13 08:33:12 - mmengine - INFO - Epoch(val) [69][20/78] eta: 0:00:36 time: 0.6312 data_time: 0.5409 memory: 3172 2022/10/13 08:33:21 - mmengine - INFO - Epoch(val) [69][40/78] eta: 0:00:16 time: 0.4269 data_time: 0.3378 memory: 3172 2022/10/13 08:33:32 - mmengine - INFO - Epoch(val) [69][60/78] eta: 0:00:10 time: 0.5824 data_time: 0.4922 memory: 3172 2022/10/13 08:33:41 - mmengine - INFO - Epoch(val) [69][78/78] acc/top1: 0.6723 acc/top5: 0.8692 acc/mean1: 0.6722 2022/10/13 08:33:55 - mmengine - INFO - Epoch(train) [70][20/940] lr: 1.0000e-03 eta: 4:08:07 time: 0.6849 data_time: 0.1938 memory: 17006 grad_norm: 4.7308 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3150 loss: 1.3150 2022/10/13 08:34:05 - mmengine - INFO - Epoch(train) [70][40/940] lr: 1.0000e-03 eta: 4:07:57 time: 0.4962 data_time: 0.1161 memory: 17006 grad_norm: 4.7840 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2773 loss: 1.2773 2022/10/13 08:34:17 - mmengine - INFO - Epoch(train) [70][60/940] lr: 1.0000e-03 eta: 4:07:47 time: 0.5825 data_time: 0.1968 memory: 17006 grad_norm: 4.7508 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2452 loss: 1.2452 2022/10/13 08:34:27 - mmengine - INFO - Epoch(train) [70][80/940] lr: 1.0000e-03 eta: 4:07:37 time: 0.4949 data_time: 0.0943 memory: 17006 grad_norm: 4.7099 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2295 loss: 1.2295 2022/10/13 08:34:37 - mmengine - INFO - Epoch(train) [70][100/940] lr: 1.0000e-03 eta: 4:07:27 time: 0.5126 data_time: 0.0461 memory: 17006 grad_norm: 4.6316 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3066 loss: 1.3066 2022/10/13 08:34:46 - mmengine - INFO - Epoch(train) [70][120/940] lr: 1.0000e-03 eta: 4:07:16 time: 0.4765 data_time: 0.0867 memory: 17006 grad_norm: 4.8265 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.2528 loss: 1.2528 2022/10/13 08:34:57 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 08:34:57 - mmengine - INFO - Epoch(train) [70][140/940] lr: 1.0000e-03 eta: 4:07:06 time: 0.5388 data_time: 0.0963 memory: 17006 grad_norm: 4.8630 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2328 loss: 1.2328 2022/10/13 08:35:07 - mmengine - INFO - Epoch(train) [70][160/940] lr: 1.0000e-03 eta: 4:06:55 time: 0.4728 data_time: 0.0306 memory: 17006 grad_norm: 4.6339 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2357 loss: 1.2357 2022/10/13 08:35:17 - mmengine - INFO - Epoch(train) [70][180/940] lr: 1.0000e-03 eta: 4:06:45 time: 0.5075 data_time: 0.0320 memory: 17006 grad_norm: 4.7931 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3136 loss: 1.3136 2022/10/13 08:35:26 - mmengine - INFO - Epoch(train) [70][200/940] lr: 1.0000e-03 eta: 4:06:35 time: 0.4668 data_time: 0.0296 memory: 17006 grad_norm: 4.7250 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.3419 loss: 1.3419 2022/10/13 08:35:37 - mmengine - INFO - Epoch(train) [70][220/940] lr: 1.0000e-03 eta: 4:06:25 time: 0.5474 data_time: 0.0671 memory: 17006 grad_norm: 4.7045 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4785 loss: 1.4785 2022/10/13 08:35:47 - mmengine - INFO - Epoch(train) [70][240/940] lr: 1.0000e-03 eta: 4:06:14 time: 0.4787 data_time: 0.0284 memory: 17006 grad_norm: 4.7417 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3873 loss: 1.3873 2022/10/13 08:35:57 - mmengine - INFO - Epoch(train) [70][260/940] lr: 1.0000e-03 eta: 4:06:04 time: 0.5228 data_time: 0.0316 memory: 17006 grad_norm: 4.7980 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2946 loss: 1.2946 2022/10/13 08:36:06 - mmengine - INFO - Epoch(train) [70][280/940] lr: 1.0000e-03 eta: 4:05:53 time: 0.4459 data_time: 0.0637 memory: 17006 grad_norm: 4.7251 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2683 loss: 1.2683 2022/10/13 08:36:18 - mmengine - INFO - Epoch(train) [70][300/940] lr: 1.0000e-03 eta: 4:05:44 time: 0.5789 data_time: 0.0749 memory: 17006 grad_norm: 4.8613 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3370 loss: 1.3370 2022/10/13 08:36:27 - mmengine - INFO - Epoch(train) [70][320/940] lr: 1.0000e-03 eta: 4:05:33 time: 0.4681 data_time: 0.0307 memory: 17006 grad_norm: 4.7208 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2185 loss: 1.2185 2022/10/13 08:36:38 - mmengine - INFO - Epoch(train) [70][340/940] lr: 1.0000e-03 eta: 4:05:23 time: 0.5712 data_time: 0.0303 memory: 17006 grad_norm: 4.7638 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2821 loss: 1.2821 2022/10/13 08:36:48 - mmengine - INFO - Epoch(train) [70][360/940] lr: 1.0000e-03 eta: 4:05:13 time: 0.4571 data_time: 0.0250 memory: 17006 grad_norm: 4.7860 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2995 loss: 1.2995 2022/10/13 08:36:59 - mmengine - INFO - Epoch(train) [70][380/940] lr: 1.0000e-03 eta: 4:05:03 time: 0.5553 data_time: 0.0303 memory: 17006 grad_norm: 4.8204 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2753 loss: 1.2753 2022/10/13 08:37:08 - mmengine - INFO - Epoch(train) [70][400/940] lr: 1.0000e-03 eta: 4:04:52 time: 0.4902 data_time: 0.0280 memory: 17006 grad_norm: 4.8263 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2288 loss: 1.2288 2022/10/13 08:37:19 - mmengine - INFO - Epoch(train) [70][420/940] lr: 1.0000e-03 eta: 4:04:42 time: 0.5198 data_time: 0.0336 memory: 17006 grad_norm: 4.6621 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2462 loss: 1.2462 2022/10/13 08:37:28 - mmengine - INFO - Epoch(train) [70][440/940] lr: 1.0000e-03 eta: 4:04:32 time: 0.4706 data_time: 0.0753 memory: 17006 grad_norm: 4.6978 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2590 loss: 1.2590 2022/10/13 08:37:39 - mmengine - INFO - Epoch(train) [70][460/940] lr: 1.0000e-03 eta: 4:04:22 time: 0.5365 data_time: 0.0695 memory: 17006 grad_norm: 4.7979 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2988 loss: 1.2988 2022/10/13 08:37:49 - mmengine - INFO - Epoch(train) [70][480/940] lr: 1.0000e-03 eta: 4:04:11 time: 0.5045 data_time: 0.1399 memory: 17006 grad_norm: 4.7266 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.2993 loss: 1.2993 2022/10/13 08:37:59 - mmengine - INFO - Epoch(train) [70][500/940] lr: 1.0000e-03 eta: 4:04:01 time: 0.5150 data_time: 0.1837 memory: 17006 grad_norm: 4.6721 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2674 loss: 1.2674 2022/10/13 08:38:09 - mmengine - INFO - Epoch(train) [70][520/940] lr: 1.0000e-03 eta: 4:03:50 time: 0.4541 data_time: 0.1196 memory: 17006 grad_norm: 4.7301 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2834 loss: 1.2834 2022/10/13 08:38:20 - mmengine - INFO - Epoch(train) [70][540/940] lr: 1.0000e-03 eta: 4:03:41 time: 0.5784 data_time: 0.1886 memory: 17006 grad_norm: 4.7441 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2318 loss: 1.2318 2022/10/13 08:38:29 - mmengine - INFO - Epoch(train) [70][560/940] lr: 1.0000e-03 eta: 4:03:30 time: 0.4351 data_time: 0.1047 memory: 17006 grad_norm: 4.8611 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2818 loss: 1.2818 2022/10/13 08:38:41 - mmengine - INFO - Epoch(train) [70][580/940] lr: 1.0000e-03 eta: 4:03:20 time: 0.5956 data_time: 0.1553 memory: 17006 grad_norm: 4.7748 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3650 loss: 1.3650 2022/10/13 08:38:50 - mmengine - INFO - Epoch(train) [70][600/940] lr: 1.0000e-03 eta: 4:03:10 time: 0.4754 data_time: 0.0279 memory: 17006 grad_norm: 4.8473 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.3202 loss: 1.3202 2022/10/13 08:39:00 - mmengine - INFO - Epoch(train) [70][620/940] lr: 1.0000e-03 eta: 4:02:59 time: 0.4922 data_time: 0.0309 memory: 17006 grad_norm: 4.8792 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4266 loss: 1.4266 2022/10/13 08:39:10 - mmengine - INFO - Epoch(train) [70][640/940] lr: 1.0000e-03 eta: 4:02:49 time: 0.5076 data_time: 0.0271 memory: 17006 grad_norm: 4.8076 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2785 loss: 1.2785 2022/10/13 08:39:21 - mmengine - INFO - Epoch(train) [70][660/940] lr: 1.0000e-03 eta: 4:02:39 time: 0.5211 data_time: 0.0337 memory: 17006 grad_norm: 4.7853 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.4807 loss: 1.4807 2022/10/13 08:39:30 - mmengine - INFO - Epoch(train) [70][680/940] lr: 1.0000e-03 eta: 4:02:28 time: 0.4534 data_time: 0.0288 memory: 17006 grad_norm: 4.8740 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3104 loss: 1.3104 2022/10/13 08:39:39 - mmengine - INFO - Epoch(train) [70][700/940] lr: 1.0000e-03 eta: 4:02:18 time: 0.4642 data_time: 0.0378 memory: 17006 grad_norm: 4.8541 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3995 loss: 1.3995 2022/10/13 08:39:50 - mmengine - INFO - Epoch(train) [70][720/940] lr: 1.0000e-03 eta: 4:02:08 time: 0.5571 data_time: 0.0266 memory: 17006 grad_norm: 4.7500 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3132 loss: 1.3132 2022/10/13 08:40:00 - mmengine - INFO - Epoch(train) [70][740/940] lr: 1.0000e-03 eta: 4:01:58 time: 0.4940 data_time: 0.0342 memory: 17006 grad_norm: 4.7841 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2400 loss: 1.2400 2022/10/13 08:40:10 - mmengine - INFO - Epoch(train) [70][760/940] lr: 1.0000e-03 eta: 4:01:47 time: 0.5055 data_time: 0.0350 memory: 17006 grad_norm: 4.8500 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4527 loss: 1.4527 2022/10/13 08:40:21 - mmengine - INFO - Epoch(train) [70][780/940] lr: 1.0000e-03 eta: 4:01:37 time: 0.5272 data_time: 0.0372 memory: 17006 grad_norm: 4.7928 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3650 loss: 1.3650 2022/10/13 08:40:31 - mmengine - INFO - Epoch(train) [70][800/940] lr: 1.0000e-03 eta: 4:01:27 time: 0.4950 data_time: 0.0306 memory: 17006 grad_norm: 4.8079 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3091 loss: 1.3091 2022/10/13 08:40:41 - mmengine - INFO - Epoch(train) [70][820/940] lr: 1.0000e-03 eta: 4:01:17 time: 0.5136 data_time: 0.0351 memory: 17006 grad_norm: 4.8094 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3721 loss: 1.3721 2022/10/13 08:40:51 - mmengine - INFO - Epoch(train) [70][840/940] lr: 1.0000e-03 eta: 4:01:06 time: 0.4952 data_time: 0.0322 memory: 17006 grad_norm: 4.8170 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2201 loss: 1.2201 2022/10/13 08:41:00 - mmengine - INFO - Epoch(train) [70][860/940] lr: 1.0000e-03 eta: 4:00:56 time: 0.4739 data_time: 0.0340 memory: 17006 grad_norm: 4.8003 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2879 loss: 1.2879 2022/10/13 08:41:10 - mmengine - INFO - Epoch(train) [70][880/940] lr: 1.0000e-03 eta: 4:00:45 time: 0.4685 data_time: 0.0300 memory: 17006 grad_norm: 4.8033 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2032 loss: 1.2032 2022/10/13 08:41:20 - mmengine - INFO - Epoch(train) [70][900/940] lr: 1.0000e-03 eta: 4:00:35 time: 0.5327 data_time: 0.0372 memory: 17006 grad_norm: 4.8460 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3234 loss: 1.3234 2022/10/13 08:41:31 - mmengine - INFO - Epoch(train) [70][920/940] lr: 1.0000e-03 eta: 4:00:25 time: 0.5582 data_time: 0.0343 memory: 17006 grad_norm: 4.7219 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3053 loss: 1.3053 2022/10/13 08:41:40 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 08:41:40 - mmengine - INFO - Epoch(train) [70][940/940] lr: 1.0000e-03 eta: 4:00:14 time: 0.4303 data_time: 0.0276 memory: 17006 grad_norm: 5.1275 top1_acc: 0.2857 top5_acc: 0.4286 loss_cls: 1.4091 loss: 1.4091 2022/10/13 08:41:53 - mmengine - INFO - Epoch(val) [70][20/78] eta: 0:00:36 time: 0.6330 data_time: 0.5374 memory: 3172 2022/10/13 08:42:01 - mmengine - INFO - Epoch(val) [70][40/78] eta: 0:00:16 time: 0.4310 data_time: 0.3379 memory: 3172 2022/10/13 08:42:13 - mmengine - INFO - Epoch(val) [70][60/78] eta: 0:00:10 time: 0.5744 data_time: 0.4826 memory: 3172 2022/10/13 08:42:23 - mmengine - INFO - Epoch(val) [70][78/78] acc/top1: 0.6745 acc/top5: 0.8713 acc/mean1: 0.6743 2022/10/13 08:42:23 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_58.pth is removed 2022/10/13 08:42:23 - mmengine - INFO - The best checkpoint with 0.6745 acc/top1 at 70 epoch is saved to best_acc/top1_epoch_70.pth. 2022/10/13 08:42:38 - mmengine - INFO - Epoch(train) [71][20/940] lr: 1.0000e-03 eta: 4:00:06 time: 0.7231 data_time: 0.2385 memory: 17006 grad_norm: 4.7892 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2230 loss: 1.2230 2022/10/13 08:42:47 - mmengine - INFO - Epoch(train) [71][40/940] lr: 1.0000e-03 eta: 3:59:55 time: 0.4430 data_time: 0.0252 memory: 17006 grad_norm: 4.9035 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.4207 loss: 1.4207 2022/10/13 08:42:57 - mmengine - INFO - Epoch(train) [71][60/940] lr: 1.0000e-03 eta: 3:59:45 time: 0.5169 data_time: 0.0323 memory: 17006 grad_norm: 4.7141 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3453 loss: 1.3453 2022/10/13 08:43:06 - mmengine - INFO - Epoch(train) [71][80/940] lr: 1.0000e-03 eta: 3:59:34 time: 0.4655 data_time: 0.0504 memory: 17006 grad_norm: 4.7237 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.3802 loss: 1.3802 2022/10/13 08:43:17 - mmengine - INFO - Epoch(train) [71][100/940] lr: 1.0000e-03 eta: 3:59:24 time: 0.5417 data_time: 0.0602 memory: 17006 grad_norm: 4.8354 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2685 loss: 1.2685 2022/10/13 08:43:27 - mmengine - INFO - Epoch(train) [71][120/940] lr: 1.0000e-03 eta: 3:59:14 time: 0.5195 data_time: 0.0431 memory: 17006 grad_norm: 4.8159 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1907 loss: 1.1907 2022/10/13 08:43:37 - mmengine - INFO - Epoch(train) [71][140/940] lr: 1.0000e-03 eta: 3:59:04 time: 0.4665 data_time: 0.0340 memory: 17006 grad_norm: 4.7357 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2659 loss: 1.2659 2022/10/13 08:43:47 - mmengine - INFO - Epoch(train) [71][160/940] lr: 1.0000e-03 eta: 3:58:53 time: 0.5191 data_time: 0.0322 memory: 17006 grad_norm: 4.7477 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3699 loss: 1.3699 2022/10/13 08:43:58 - mmengine - INFO - Epoch(train) [71][180/940] lr: 1.0000e-03 eta: 3:58:43 time: 0.5192 data_time: 0.0355 memory: 17006 grad_norm: 4.8841 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2768 loss: 1.2768 2022/10/13 08:44:07 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 08:44:07 - mmengine - INFO - Epoch(train) [71][200/940] lr: 1.0000e-03 eta: 3:58:33 time: 0.4944 data_time: 0.0339 memory: 17006 grad_norm: 4.7341 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4612 loss: 1.4612 2022/10/13 08:44:19 - mmengine - INFO - Epoch(train) [71][220/940] lr: 1.0000e-03 eta: 3:58:23 time: 0.5570 data_time: 0.0309 memory: 17006 grad_norm: 4.7211 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2581 loss: 1.2581 2022/10/13 08:44:28 - mmengine - INFO - Epoch(train) [71][240/940] lr: 1.0000e-03 eta: 3:58:13 time: 0.4723 data_time: 0.0344 memory: 17006 grad_norm: 4.8081 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2939 loss: 1.2939 2022/10/13 08:44:39 - mmengine - INFO - Epoch(train) [71][260/940] lr: 1.0000e-03 eta: 3:58:02 time: 0.5293 data_time: 0.0303 memory: 17006 grad_norm: 4.8947 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2552 loss: 1.2552 2022/10/13 08:44:48 - mmengine - INFO - Epoch(train) [71][280/940] lr: 1.0000e-03 eta: 3:57:52 time: 0.4800 data_time: 0.0298 memory: 17006 grad_norm: 4.8555 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3727 loss: 1.3727 2022/10/13 08:45:00 - mmengine - INFO - Epoch(train) [71][300/940] lr: 1.0000e-03 eta: 3:57:42 time: 0.5881 data_time: 0.0308 memory: 17006 grad_norm: 4.8020 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4050 loss: 1.4050 2022/10/13 08:45:10 - mmengine - INFO - Epoch(train) [71][320/940] lr: 1.0000e-03 eta: 3:57:32 time: 0.5001 data_time: 0.0323 memory: 17006 grad_norm: 4.6913 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3117 loss: 1.3117 2022/10/13 08:45:20 - mmengine - INFO - Epoch(train) [71][340/940] lr: 1.0000e-03 eta: 3:57:22 time: 0.5205 data_time: 0.0306 memory: 17006 grad_norm: 4.8005 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3418 loss: 1.3418 2022/10/13 08:45:30 - mmengine - INFO - Epoch(train) [71][360/940] lr: 1.0000e-03 eta: 3:57:11 time: 0.4781 data_time: 0.0341 memory: 17006 grad_norm: 4.8605 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3083 loss: 1.3083 2022/10/13 08:45:40 - mmengine - INFO - Epoch(train) [71][380/940] lr: 1.0000e-03 eta: 3:57:01 time: 0.5192 data_time: 0.0275 memory: 17006 grad_norm: 4.7881 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3680 loss: 1.3680 2022/10/13 08:45:50 - mmengine - INFO - Epoch(train) [71][400/940] lr: 1.0000e-03 eta: 3:56:51 time: 0.4760 data_time: 0.0324 memory: 17006 grad_norm: 4.8033 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3962 loss: 1.3962 2022/10/13 08:46:01 - mmengine - INFO - Epoch(train) [71][420/940] lr: 1.0000e-03 eta: 3:56:41 time: 0.5390 data_time: 0.0241 memory: 17006 grad_norm: 4.7586 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3086 loss: 1.3086 2022/10/13 08:46:10 - mmengine - INFO - Epoch(train) [71][440/940] lr: 1.0000e-03 eta: 3:56:30 time: 0.4643 data_time: 0.0308 memory: 17006 grad_norm: 4.7674 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2970 loss: 1.2970 2022/10/13 08:46:20 - mmengine - INFO - Epoch(train) [71][460/940] lr: 1.0000e-03 eta: 3:56:20 time: 0.4966 data_time: 0.0268 memory: 17006 grad_norm: 4.7835 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.3226 loss: 1.3226 2022/10/13 08:46:30 - mmengine - INFO - Epoch(train) [71][480/940] lr: 1.0000e-03 eta: 3:56:10 time: 0.5050 data_time: 0.0380 memory: 17006 grad_norm: 4.7189 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2429 loss: 1.2429 2022/10/13 08:46:41 - mmengine - INFO - Epoch(train) [71][500/940] lr: 1.0000e-03 eta: 3:56:00 time: 0.5426 data_time: 0.0313 memory: 17006 grad_norm: 4.8593 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2071 loss: 1.2071 2022/10/13 08:46:50 - mmengine - INFO - Epoch(train) [71][520/940] lr: 1.0000e-03 eta: 3:55:49 time: 0.4707 data_time: 0.0306 memory: 17006 grad_norm: 4.8388 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3446 loss: 1.3446 2022/10/13 08:47:01 - mmengine - INFO - Epoch(train) [71][540/940] lr: 1.0000e-03 eta: 3:55:39 time: 0.5132 data_time: 0.0331 memory: 17006 grad_norm: 4.7980 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2694 loss: 1.2694 2022/10/13 08:47:10 - mmengine - INFO - Epoch(train) [71][560/940] lr: 1.0000e-03 eta: 3:55:28 time: 0.4691 data_time: 0.0286 memory: 17006 grad_norm: 4.7907 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4014 loss: 1.4014 2022/10/13 08:47:20 - mmengine - INFO - Epoch(train) [71][580/940] lr: 1.0000e-03 eta: 3:55:18 time: 0.4869 data_time: 0.0488 memory: 17006 grad_norm: 4.7566 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2325 loss: 1.2325 2022/10/13 08:47:30 - mmengine - INFO - Epoch(train) [71][600/940] lr: 1.0000e-03 eta: 3:55:08 time: 0.5379 data_time: 0.0321 memory: 17006 grad_norm: 4.8224 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2351 loss: 1.2351 2022/10/13 08:47:40 - mmengine - INFO - Epoch(train) [71][620/940] lr: 1.0000e-03 eta: 3:54:57 time: 0.4662 data_time: 0.0352 memory: 17006 grad_norm: 4.7793 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.1899 loss: 1.1899 2022/10/13 08:47:50 - mmengine - INFO - Epoch(train) [71][640/940] lr: 1.0000e-03 eta: 3:54:47 time: 0.5252 data_time: 0.0297 memory: 17006 grad_norm: 4.7750 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2870 loss: 1.2870 2022/10/13 08:48:00 - mmengine - INFO - Epoch(train) [71][660/940] lr: 1.0000e-03 eta: 3:54:37 time: 0.4807 data_time: 0.0340 memory: 17006 grad_norm: 4.7201 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2400 loss: 1.2400 2022/10/13 08:48:10 - mmengine - INFO - Epoch(train) [71][680/940] lr: 1.0000e-03 eta: 3:54:26 time: 0.5100 data_time: 0.0431 memory: 17006 grad_norm: 4.8581 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3101 loss: 1.3101 2022/10/13 08:48:21 - mmengine - INFO - Epoch(train) [71][700/940] lr: 1.0000e-03 eta: 3:54:16 time: 0.5269 data_time: 0.0960 memory: 17006 grad_norm: 4.7194 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3241 loss: 1.3241 2022/10/13 08:48:32 - mmengine - INFO - Epoch(train) [71][720/940] lr: 1.0000e-03 eta: 3:54:06 time: 0.5531 data_time: 0.0360 memory: 17006 grad_norm: 4.7983 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3035 loss: 1.3035 2022/10/13 08:48:41 - mmengine - INFO - Epoch(train) [71][740/940] lr: 1.0000e-03 eta: 3:53:56 time: 0.4648 data_time: 0.0343 memory: 17006 grad_norm: 4.7955 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.2283 loss: 1.2283 2022/10/13 08:48:51 - mmengine - INFO - Epoch(train) [71][760/940] lr: 1.0000e-03 eta: 3:53:46 time: 0.5243 data_time: 0.0347 memory: 17006 grad_norm: 4.7937 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 1.4102 loss: 1.4102 2022/10/13 08:49:02 - mmengine - INFO - Epoch(train) [71][780/940] lr: 1.0000e-03 eta: 3:53:35 time: 0.5079 data_time: 0.0376 memory: 17006 grad_norm: 4.8440 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2804 loss: 1.2804 2022/10/13 08:49:12 - mmengine - INFO - Epoch(train) [71][800/940] lr: 1.0000e-03 eta: 3:53:26 time: 0.5446 data_time: 0.0260 memory: 17006 grad_norm: 4.7499 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3019 loss: 1.3019 2022/10/13 08:49:22 - mmengine - INFO - Epoch(train) [71][820/940] lr: 1.0000e-03 eta: 3:53:15 time: 0.4924 data_time: 0.0322 memory: 17006 grad_norm: 4.8864 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3666 loss: 1.3666 2022/10/13 08:49:32 - mmengine - INFO - Epoch(train) [71][840/940] lr: 1.0000e-03 eta: 3:53:05 time: 0.4917 data_time: 0.0328 memory: 17006 grad_norm: 4.8575 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.2707 loss: 1.2707 2022/10/13 08:49:43 - mmengine - INFO - Epoch(train) [71][860/940] lr: 1.0000e-03 eta: 3:52:55 time: 0.5524 data_time: 0.0367 memory: 17006 grad_norm: 4.8236 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3330 loss: 1.3330 2022/10/13 08:49:53 - mmengine - INFO - Epoch(train) [71][880/940] lr: 1.0000e-03 eta: 3:52:45 time: 0.5015 data_time: 0.0389 memory: 17006 grad_norm: 4.7514 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2624 loss: 1.2624 2022/10/13 08:50:04 - mmengine - INFO - Epoch(train) [71][900/940] lr: 1.0000e-03 eta: 3:52:34 time: 0.5169 data_time: 0.0353 memory: 17006 grad_norm: 4.7171 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2487 loss: 1.2487 2022/10/13 08:50:13 - mmengine - INFO - Epoch(train) [71][920/940] lr: 1.0000e-03 eta: 3:52:24 time: 0.4563 data_time: 0.0368 memory: 17006 grad_norm: 4.8361 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3019 loss: 1.3019 2022/10/13 08:50:22 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 08:50:22 - mmengine - INFO - Epoch(train) [71][940/940] lr: 1.0000e-03 eta: 3:52:13 time: 0.4484 data_time: 0.0264 memory: 17006 grad_norm: 5.0329 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.3752 loss: 1.3752 2022/10/13 08:50:34 - mmengine - INFO - Epoch(val) [71][20/78] eta: 0:00:36 time: 0.6211 data_time: 0.5286 memory: 3172 2022/10/13 08:50:43 - mmengine - INFO - Epoch(val) [71][40/78] eta: 0:00:16 time: 0.4401 data_time: 0.3498 memory: 3172 2022/10/13 08:50:54 - mmengine - INFO - Epoch(val) [71][60/78] eta: 0:00:10 time: 0.5753 data_time: 0.4824 memory: 3172 2022/10/13 08:51:04 - mmengine - INFO - Epoch(val) [71][78/78] acc/top1: 0.6732 acc/top5: 0.8704 acc/mean1: 0.6731 2022/10/13 08:51:18 - mmengine - INFO - Epoch(train) [72][20/940] lr: 1.0000e-03 eta: 3:52:04 time: 0.6943 data_time: 0.1771 memory: 17006 grad_norm: 4.7798 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2700 loss: 1.2700 2022/10/13 08:51:28 - mmengine - INFO - Epoch(train) [72][40/940] lr: 1.0000e-03 eta: 3:51:54 time: 0.4928 data_time: 0.0288 memory: 17006 grad_norm: 4.7358 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.3643 loss: 1.3643 2022/10/13 08:51:39 - mmengine - INFO - Epoch(train) [72][60/940] lr: 1.0000e-03 eta: 3:51:44 time: 0.5320 data_time: 0.0374 memory: 17006 grad_norm: 4.7650 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3230 loss: 1.3230 2022/10/13 08:51:49 - mmengine - INFO - Epoch(train) [72][80/940] lr: 1.0000e-03 eta: 3:51:34 time: 0.5101 data_time: 0.0268 memory: 17006 grad_norm: 4.8252 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3057 loss: 1.3057 2022/10/13 08:52:01 - mmengine - INFO - Epoch(train) [72][100/940] lr: 1.0000e-03 eta: 3:51:24 time: 0.5894 data_time: 0.0358 memory: 17006 grad_norm: 4.7685 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2706 loss: 1.2706 2022/10/13 08:52:10 - mmengine - INFO - Epoch(train) [72][120/940] lr: 1.0000e-03 eta: 3:51:13 time: 0.4728 data_time: 0.0305 memory: 17006 grad_norm: 4.8597 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3585 loss: 1.3585 2022/10/13 08:52:21 - mmengine - INFO - Epoch(train) [72][140/940] lr: 1.0000e-03 eta: 3:51:04 time: 0.5514 data_time: 0.0263 memory: 17006 grad_norm: 4.8827 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3572 loss: 1.3572 2022/10/13 08:52:31 - mmengine - INFO - Epoch(train) [72][160/940] lr: 1.0000e-03 eta: 3:50:53 time: 0.4839 data_time: 0.0290 memory: 17006 grad_norm: 4.7625 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.2330 loss: 1.2330 2022/10/13 08:52:41 - mmengine - INFO - Epoch(train) [72][180/940] lr: 1.0000e-03 eta: 3:50:43 time: 0.5187 data_time: 0.0368 memory: 17006 grad_norm: 4.8383 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2701 loss: 1.2701 2022/10/13 08:52:52 - mmengine - INFO - Epoch(train) [72][200/940] lr: 1.0000e-03 eta: 3:50:33 time: 0.5282 data_time: 0.0328 memory: 17006 grad_norm: 4.8357 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2199 loss: 1.2199 2022/10/13 08:53:02 - mmengine - INFO - Epoch(train) [72][220/940] lr: 1.0000e-03 eta: 3:50:23 time: 0.4968 data_time: 0.0279 memory: 17006 grad_norm: 4.8181 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2684 loss: 1.2684 2022/10/13 08:53:11 - mmengine - INFO - Epoch(train) [72][240/940] lr: 1.0000e-03 eta: 3:50:12 time: 0.4561 data_time: 0.0335 memory: 17006 grad_norm: 4.8527 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3270 loss: 1.3270 2022/10/13 08:53:21 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 08:53:21 - mmengine - INFO - Epoch(train) [72][260/940] lr: 1.0000e-03 eta: 3:50:01 time: 0.4851 data_time: 0.0332 memory: 17006 grad_norm: 4.9783 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3331 loss: 1.3331 2022/10/13 08:53:31 - mmengine - INFO - Epoch(train) [72][280/940] lr: 1.0000e-03 eta: 3:49:51 time: 0.5261 data_time: 0.0384 memory: 17006 grad_norm: 4.8524 top1_acc: 0.7188 top5_acc: 0.7500 loss_cls: 1.3558 loss: 1.3558 2022/10/13 08:53:41 - mmengine - INFO - Epoch(train) [72][300/940] lr: 1.0000e-03 eta: 3:49:41 time: 0.5144 data_time: 0.0324 memory: 17006 grad_norm: 4.7841 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3135 loss: 1.3135 2022/10/13 08:53:52 - mmengine - INFO - Epoch(train) [72][320/940] lr: 1.0000e-03 eta: 3:49:31 time: 0.5227 data_time: 0.0351 memory: 17006 grad_norm: 4.7042 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.2948 loss: 1.2948 2022/10/13 08:54:01 - mmengine - INFO - Epoch(train) [72][340/940] lr: 1.0000e-03 eta: 3:49:20 time: 0.4738 data_time: 0.0336 memory: 17006 grad_norm: 4.7688 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3159 loss: 1.3159 2022/10/13 08:54:13 - mmengine - INFO - Epoch(train) [72][360/940] lr: 1.0000e-03 eta: 3:49:11 time: 0.5626 data_time: 0.0342 memory: 17006 grad_norm: 4.6439 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2725 loss: 1.2725 2022/10/13 08:54:22 - mmengine - INFO - Epoch(train) [72][380/940] lr: 1.0000e-03 eta: 3:49:00 time: 0.4708 data_time: 0.0362 memory: 17006 grad_norm: 4.7999 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2755 loss: 1.2755 2022/10/13 08:54:34 - mmengine - INFO - Epoch(train) [72][400/940] lr: 1.0000e-03 eta: 3:48:50 time: 0.5807 data_time: 0.0371 memory: 17006 grad_norm: 4.7148 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1762 loss: 1.1762 2022/10/13 08:54:42 - mmengine - INFO - Epoch(train) [72][420/940] lr: 1.0000e-03 eta: 3:48:40 time: 0.4437 data_time: 0.0392 memory: 17006 grad_norm: 4.7427 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.3147 loss: 1.3147 2022/10/13 08:54:53 - mmengine - INFO - Epoch(train) [72][440/940] lr: 1.0000e-03 eta: 3:48:30 time: 0.5411 data_time: 0.0331 memory: 17006 grad_norm: 4.9765 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4211 loss: 1.4211 2022/10/13 08:55:02 - mmengine - INFO - Epoch(train) [72][460/940] lr: 1.0000e-03 eta: 3:48:19 time: 0.4620 data_time: 0.0324 memory: 17006 grad_norm: 4.8037 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3041 loss: 1.3041 2022/10/13 08:55:12 - mmengine - INFO - Epoch(train) [72][480/940] lr: 1.0000e-03 eta: 3:48:09 time: 0.4739 data_time: 0.0311 memory: 17006 grad_norm: 4.7525 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2279 loss: 1.2279 2022/10/13 08:55:22 - mmengine - INFO - Epoch(train) [72][500/940] lr: 1.0000e-03 eta: 3:47:58 time: 0.4956 data_time: 0.0340 memory: 17006 grad_norm: 4.7480 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1690 loss: 1.1690 2022/10/13 08:55:33 - mmengine - INFO - Epoch(train) [72][520/940] lr: 1.0000e-03 eta: 3:47:48 time: 0.5633 data_time: 0.0307 memory: 17006 grad_norm: 4.7304 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1782 loss: 1.1782 2022/10/13 08:55:43 - mmengine - INFO - Epoch(train) [72][540/940] lr: 1.0000e-03 eta: 3:47:38 time: 0.4938 data_time: 0.0334 memory: 17006 grad_norm: 4.8309 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3063 loss: 1.3063 2022/10/13 08:55:55 - mmengine - INFO - Epoch(train) [72][560/940] lr: 1.0000e-03 eta: 3:47:28 time: 0.5743 data_time: 0.0288 memory: 17006 grad_norm: 4.7493 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3394 loss: 1.3394 2022/10/13 08:56:04 - mmengine - INFO - Epoch(train) [72][580/940] lr: 1.0000e-03 eta: 3:47:18 time: 0.4506 data_time: 0.0314 memory: 17006 grad_norm: 4.8291 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.3370 loss: 1.3370 2022/10/13 08:56:13 - mmengine - INFO - Epoch(train) [72][600/940] lr: 1.0000e-03 eta: 3:47:07 time: 0.4920 data_time: 0.0311 memory: 17006 grad_norm: 4.7641 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3942 loss: 1.3942 2022/10/13 08:56:23 - mmengine - INFO - Epoch(train) [72][620/940] lr: 1.0000e-03 eta: 3:46:57 time: 0.4918 data_time: 0.0330 memory: 17006 grad_norm: 4.7672 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.3347 loss: 1.3347 2022/10/13 08:56:33 - mmengine - INFO - Epoch(train) [72][640/940] lr: 1.0000e-03 eta: 3:46:47 time: 0.4979 data_time: 0.0330 memory: 17006 grad_norm: 4.8768 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3614 loss: 1.3614 2022/10/13 08:56:43 - mmengine - INFO - Epoch(train) [72][660/940] lr: 1.0000e-03 eta: 3:46:36 time: 0.5028 data_time: 0.0316 memory: 17006 grad_norm: 4.8875 top1_acc: 0.4062 top5_acc: 0.7500 loss_cls: 1.4681 loss: 1.4681 2022/10/13 08:56:54 - mmengine - INFO - Epoch(train) [72][680/940] lr: 1.0000e-03 eta: 3:46:26 time: 0.5498 data_time: 0.0318 memory: 17006 grad_norm: 4.8261 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2610 loss: 1.2610 2022/10/13 08:57:03 - mmengine - INFO - Epoch(train) [72][700/940] lr: 1.0000e-03 eta: 3:46:16 time: 0.4501 data_time: 0.0331 memory: 17006 grad_norm: 4.8633 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4696 loss: 1.4696 2022/10/13 08:57:15 - mmengine - INFO - Epoch(train) [72][720/940] lr: 1.0000e-03 eta: 3:46:06 time: 0.5999 data_time: 0.0293 memory: 17006 grad_norm: 4.8013 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2903 loss: 1.2903 2022/10/13 08:57:24 - mmengine - INFO - Epoch(train) [72][740/940] lr: 1.0000e-03 eta: 3:45:55 time: 0.4510 data_time: 0.0296 memory: 17006 grad_norm: 4.7834 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3204 loss: 1.3204 2022/10/13 08:57:35 - mmengine - INFO - Epoch(train) [72][760/940] lr: 1.0000e-03 eta: 3:45:45 time: 0.5191 data_time: 0.0370 memory: 17006 grad_norm: 4.8663 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2870 loss: 1.2870 2022/10/13 08:57:44 - mmengine - INFO - Epoch(train) [72][780/940] lr: 1.0000e-03 eta: 3:45:35 time: 0.4787 data_time: 0.0309 memory: 17006 grad_norm: 4.7567 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.3362 loss: 1.3362 2022/10/13 08:57:55 - mmengine - INFO - Epoch(train) [72][800/940] lr: 1.0000e-03 eta: 3:45:25 time: 0.5215 data_time: 0.0356 memory: 17006 grad_norm: 4.7959 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2676 loss: 1.2676 2022/10/13 08:58:05 - mmengine - INFO - Epoch(train) [72][820/940] lr: 1.0000e-03 eta: 3:45:14 time: 0.5077 data_time: 0.0262 memory: 17006 grad_norm: 4.8954 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4891 loss: 1.4891 2022/10/13 08:58:15 - mmengine - INFO - Epoch(train) [72][840/940] lr: 1.0000e-03 eta: 3:45:04 time: 0.5314 data_time: 0.0339 memory: 17006 grad_norm: 4.7543 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2240 loss: 1.2240 2022/10/13 08:58:25 - mmengine - INFO - Epoch(train) [72][860/940] lr: 1.0000e-03 eta: 3:44:54 time: 0.5009 data_time: 0.0327 memory: 17006 grad_norm: 4.8518 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.4260 loss: 1.4260 2022/10/13 08:58:36 - mmengine - INFO - Epoch(train) [72][880/940] lr: 1.0000e-03 eta: 3:44:44 time: 0.5130 data_time: 0.0321 memory: 17006 grad_norm: 4.8149 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3210 loss: 1.3210 2022/10/13 08:58:46 - mmengine - INFO - Epoch(train) [72][900/940] lr: 1.0000e-03 eta: 3:44:34 time: 0.5256 data_time: 0.0312 memory: 17006 grad_norm: 4.7989 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2960 loss: 1.2960 2022/10/13 08:58:56 - mmengine - INFO - Epoch(train) [72][920/940] lr: 1.0000e-03 eta: 3:44:23 time: 0.5062 data_time: 0.0338 memory: 17006 grad_norm: 4.8204 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4153 loss: 1.4153 2022/10/13 08:59:05 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 08:59:05 - mmengine - INFO - Epoch(train) [72][940/940] lr: 1.0000e-03 eta: 3:44:13 time: 0.4225 data_time: 0.0246 memory: 17006 grad_norm: 5.8653 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.3960 loss: 1.3960 2022/10/13 08:59:05 - mmengine - INFO - Saving checkpoint at 72 epochs 2022/10/13 08:59:18 - mmengine - INFO - Epoch(val) [72][20/78] eta: 0:00:36 time: 0.6309 data_time: 0.5395 memory: 3172 2022/10/13 08:59:27 - mmengine - INFO - Epoch(val) [72][40/78] eta: 0:00:16 time: 0.4301 data_time: 0.3415 memory: 3172 2022/10/13 08:59:38 - mmengine - INFO - Epoch(val) [72][60/78] eta: 0:00:10 time: 0.5721 data_time: 0.4804 memory: 3172 2022/10/13 08:59:47 - mmengine - INFO - Epoch(val) [72][78/78] acc/top1: 0.6742 acc/top5: 0.8691 acc/mean1: 0.6741 2022/10/13 09:00:02 - mmengine - INFO - Epoch(train) [73][20/940] lr: 1.0000e-03 eta: 3:44:04 time: 0.7336 data_time: 0.2137 memory: 17006 grad_norm: 4.7313 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3378 loss: 1.3378 2022/10/13 09:00:11 - mmengine - INFO - Epoch(train) [73][40/940] lr: 1.0000e-03 eta: 3:43:53 time: 0.4512 data_time: 0.0303 memory: 17006 grad_norm: 4.8133 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2713 loss: 1.2713 2022/10/13 09:00:23 - mmengine - INFO - Epoch(train) [73][60/940] lr: 1.0000e-03 eta: 3:43:44 time: 0.5820 data_time: 0.0379 memory: 17006 grad_norm: 4.7442 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2346 loss: 1.2346 2022/10/13 09:00:32 - mmengine - INFO - Epoch(train) [73][80/940] lr: 1.0000e-03 eta: 3:43:33 time: 0.4799 data_time: 0.0290 memory: 17006 grad_norm: 4.7948 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3610 loss: 1.3610 2022/10/13 09:00:43 - mmengine - INFO - Epoch(train) [73][100/940] lr: 1.0000e-03 eta: 3:43:23 time: 0.5036 data_time: 0.0367 memory: 17006 grad_norm: 4.8383 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3313 loss: 1.3313 2022/10/13 09:00:52 - mmengine - INFO - Epoch(train) [73][120/940] lr: 1.0000e-03 eta: 3:43:13 time: 0.4924 data_time: 0.0307 memory: 17006 grad_norm: 4.8102 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1866 loss: 1.1866 2022/10/13 09:01:03 - mmengine - INFO - Epoch(train) [73][140/940] lr: 1.0000e-03 eta: 3:43:02 time: 0.5341 data_time: 0.0303 memory: 17006 grad_norm: 4.9394 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2904 loss: 1.2904 2022/10/13 09:01:13 - mmengine - INFO - Epoch(train) [73][160/940] lr: 1.0000e-03 eta: 3:42:52 time: 0.4857 data_time: 0.0343 memory: 17006 grad_norm: 4.8807 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2230 loss: 1.2230 2022/10/13 09:01:24 - mmengine - INFO - Epoch(train) [73][180/940] lr: 1.0000e-03 eta: 3:42:42 time: 0.5505 data_time: 0.0338 memory: 17006 grad_norm: 4.7505 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2757 loss: 1.2757 2022/10/13 09:01:33 - mmengine - INFO - Epoch(train) [73][200/940] lr: 1.0000e-03 eta: 3:42:32 time: 0.4600 data_time: 0.0395 memory: 17006 grad_norm: 4.9044 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3629 loss: 1.3629 2022/10/13 09:01:44 - mmengine - INFO - Epoch(train) [73][220/940] lr: 1.0000e-03 eta: 3:42:22 time: 0.5488 data_time: 0.0341 memory: 17006 grad_norm: 4.8225 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3473 loss: 1.3473 2022/10/13 09:01:54 - mmengine - INFO - Epoch(train) [73][240/940] lr: 1.0000e-03 eta: 3:42:11 time: 0.4788 data_time: 0.0359 memory: 17006 grad_norm: 4.9070 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3657 loss: 1.3657 2022/10/13 09:02:05 - mmengine - INFO - Epoch(train) [73][260/940] lr: 1.0000e-03 eta: 3:42:01 time: 0.5535 data_time: 0.0369 memory: 17006 grad_norm: 4.8524 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.3671 loss: 1.3671 2022/10/13 09:02:14 - mmengine - INFO - Epoch(train) [73][280/940] lr: 1.0000e-03 eta: 3:41:51 time: 0.4640 data_time: 0.0367 memory: 17006 grad_norm: 4.8057 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2326 loss: 1.2326 2022/10/13 09:02:24 - mmengine - INFO - Epoch(train) [73][300/940] lr: 1.0000e-03 eta: 3:41:41 time: 0.5237 data_time: 0.0296 memory: 17006 grad_norm: 4.8672 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3919 loss: 1.3919 2022/10/13 09:02:34 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 09:02:34 - mmengine - INFO - Epoch(train) [73][320/940] lr: 1.0000e-03 eta: 3:41:30 time: 0.4843 data_time: 0.0339 memory: 17006 grad_norm: 4.7743 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3277 loss: 1.3277 2022/10/13 09:02:44 - mmengine - INFO - Epoch(train) [73][340/940] lr: 1.0000e-03 eta: 3:41:20 time: 0.5079 data_time: 0.0297 memory: 17006 grad_norm: 4.7742 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2164 loss: 1.2164 2022/10/13 09:02:53 - mmengine - INFO - Epoch(train) [73][360/940] lr: 1.0000e-03 eta: 3:41:09 time: 0.4472 data_time: 0.0342 memory: 17006 grad_norm: 4.9216 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3726 loss: 1.3726 2022/10/13 09:03:04 - mmengine - INFO - Epoch(train) [73][380/940] lr: 1.0000e-03 eta: 3:40:59 time: 0.5679 data_time: 0.0341 memory: 17006 grad_norm: 4.7249 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.1994 loss: 1.1994 2022/10/13 09:03:14 - mmengine - INFO - Epoch(train) [73][400/940] lr: 1.0000e-03 eta: 3:40:49 time: 0.4813 data_time: 0.0314 memory: 17006 grad_norm: 4.9229 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3663 loss: 1.3663 2022/10/13 09:03:25 - mmengine - INFO - Epoch(train) [73][420/940] lr: 1.0000e-03 eta: 3:40:39 time: 0.5323 data_time: 0.0330 memory: 17006 grad_norm: 4.8658 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2210 loss: 1.2210 2022/10/13 09:03:34 - mmengine - INFO - Epoch(train) [73][440/940] lr: 1.0000e-03 eta: 3:40:28 time: 0.4812 data_time: 0.0311 memory: 17006 grad_norm: 4.8302 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3698 loss: 1.3698 2022/10/13 09:03:45 - mmengine - INFO - Epoch(train) [73][460/940] lr: 1.0000e-03 eta: 3:40:18 time: 0.5293 data_time: 0.0333 memory: 17006 grad_norm: 4.7571 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2927 loss: 1.2927 2022/10/13 09:03:55 - mmengine - INFO - Epoch(train) [73][480/940] lr: 1.0000e-03 eta: 3:40:08 time: 0.4782 data_time: 0.0261 memory: 17006 grad_norm: 4.7804 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3597 loss: 1.3597 2022/10/13 09:04:05 - mmengine - INFO - Epoch(train) [73][500/940] lr: 1.0000e-03 eta: 3:39:58 time: 0.5267 data_time: 0.0349 memory: 17006 grad_norm: 4.7750 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2207 loss: 1.2207 2022/10/13 09:04:15 - mmengine - INFO - Epoch(train) [73][520/940] lr: 1.0000e-03 eta: 3:39:47 time: 0.4779 data_time: 0.0365 memory: 17006 grad_norm: 4.7963 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.1966 loss: 1.1966 2022/10/13 09:04:25 - mmengine - INFO - Epoch(train) [73][540/940] lr: 1.0000e-03 eta: 3:39:37 time: 0.5242 data_time: 0.0309 memory: 17006 grad_norm: 4.6936 top1_acc: 0.6562 top5_acc: 1.0000 loss_cls: 1.2607 loss: 1.2607 2022/10/13 09:04:35 - mmengine - INFO - Epoch(train) [73][560/940] lr: 1.0000e-03 eta: 3:39:27 time: 0.4776 data_time: 0.0321 memory: 17006 grad_norm: 4.8742 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3478 loss: 1.3478 2022/10/13 09:04:45 - mmengine - INFO - Epoch(train) [73][580/940] lr: 1.0000e-03 eta: 3:39:17 time: 0.5354 data_time: 0.0294 memory: 17006 grad_norm: 4.9102 top1_acc: 0.4375 top5_acc: 0.7188 loss_cls: 1.3370 loss: 1.3370 2022/10/13 09:04:55 - mmengine - INFO - Epoch(train) [73][600/940] lr: 1.0000e-03 eta: 3:39:06 time: 0.4989 data_time: 0.0346 memory: 17006 grad_norm: 4.7923 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3968 loss: 1.3968 2022/10/13 09:05:05 - mmengine - INFO - Epoch(train) [73][620/940] lr: 1.0000e-03 eta: 3:38:56 time: 0.4900 data_time: 0.0319 memory: 17006 grad_norm: 4.8881 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2609 loss: 1.2609 2022/10/13 09:05:15 - mmengine - INFO - Epoch(train) [73][640/940] lr: 1.0000e-03 eta: 3:38:46 time: 0.5075 data_time: 0.0320 memory: 17006 grad_norm: 4.8052 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3745 loss: 1.3745 2022/10/13 09:05:26 - mmengine - INFO - Epoch(train) [73][660/940] lr: 1.0000e-03 eta: 3:38:35 time: 0.5138 data_time: 0.0396 memory: 17006 grad_norm: 4.8529 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.3857 loss: 1.3857 2022/10/13 09:05:36 - mmengine - INFO - Epoch(train) [73][680/940] lr: 1.0000e-03 eta: 3:38:25 time: 0.5205 data_time: 0.0371 memory: 17006 grad_norm: 4.8302 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2973 loss: 1.2973 2022/10/13 09:05:46 - mmengine - INFO - Epoch(train) [73][700/940] lr: 1.0000e-03 eta: 3:38:15 time: 0.5094 data_time: 0.0328 memory: 17006 grad_norm: 4.8418 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3822 loss: 1.3822 2022/10/13 09:05:56 - mmengine - INFO - Epoch(train) [73][720/940] lr: 1.0000e-03 eta: 3:38:05 time: 0.4907 data_time: 0.0283 memory: 17006 grad_norm: 4.8367 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3855 loss: 1.3855 2022/10/13 09:06:06 - mmengine - INFO - Epoch(train) [73][740/940] lr: 1.0000e-03 eta: 3:37:54 time: 0.4802 data_time: 0.0363 memory: 17006 grad_norm: 4.7564 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3727 loss: 1.3727 2022/10/13 09:06:16 - mmengine - INFO - Epoch(train) [73][760/940] lr: 1.0000e-03 eta: 3:37:44 time: 0.5148 data_time: 0.0332 memory: 17006 grad_norm: 4.8235 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4252 loss: 1.4252 2022/10/13 09:06:25 - mmengine - INFO - Epoch(train) [73][780/940] lr: 1.0000e-03 eta: 3:37:33 time: 0.4685 data_time: 0.0329 memory: 17006 grad_norm: 4.8298 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2610 loss: 1.2610 2022/10/13 09:06:36 - mmengine - INFO - Epoch(train) [73][800/940] lr: 1.0000e-03 eta: 3:37:23 time: 0.5200 data_time: 0.0312 memory: 17006 grad_norm: 4.7490 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3025 loss: 1.3025 2022/10/13 09:06:45 - mmengine - INFO - Epoch(train) [73][820/940] lr: 1.0000e-03 eta: 3:37:13 time: 0.4826 data_time: 0.0364 memory: 17006 grad_norm: 4.9597 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.3472 loss: 1.3472 2022/10/13 09:06:56 - mmengine - INFO - Epoch(train) [73][840/940] lr: 1.0000e-03 eta: 3:37:03 time: 0.5206 data_time: 0.0332 memory: 17006 grad_norm: 4.8679 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2836 loss: 1.2836 2022/10/13 09:07:05 - mmengine - INFO - Epoch(train) [73][860/940] lr: 1.0000e-03 eta: 3:36:52 time: 0.4754 data_time: 0.0371 memory: 17006 grad_norm: 4.7850 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3749 loss: 1.3749 2022/10/13 09:07:16 - mmengine - INFO - Epoch(train) [73][880/940] lr: 1.0000e-03 eta: 3:36:42 time: 0.5118 data_time: 0.0309 memory: 17006 grad_norm: 4.7441 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1998 loss: 1.1998 2022/10/13 09:07:26 - mmengine - INFO - Epoch(train) [73][900/940] lr: 1.0000e-03 eta: 3:36:32 time: 0.5146 data_time: 0.0850 memory: 17006 grad_norm: 4.8335 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.2516 loss: 1.2516 2022/10/13 09:07:36 - mmengine - INFO - Epoch(train) [73][920/940] lr: 1.0000e-03 eta: 3:36:22 time: 0.5288 data_time: 0.0297 memory: 17006 grad_norm: 4.8328 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3626 loss: 1.3626 2022/10/13 09:07:45 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 09:07:45 - mmengine - INFO - Epoch(train) [73][940/940] lr: 1.0000e-03 eta: 3:36:11 time: 0.4354 data_time: 0.0343 memory: 17006 grad_norm: 5.2290 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.4835 loss: 1.4835 2022/10/13 09:07:58 - mmengine - INFO - Epoch(val) [73][20/78] eta: 0:00:36 time: 0.6209 data_time: 0.5283 memory: 3172 2022/10/13 09:08:06 - mmengine - INFO - Epoch(val) [73][40/78] eta: 0:00:16 time: 0.4356 data_time: 0.3433 memory: 3172 2022/10/13 09:08:18 - mmengine - INFO - Epoch(val) [73][60/78] eta: 0:00:10 time: 0.6018 data_time: 0.5103 memory: 3172 2022/10/13 09:08:28 - mmengine - INFO - Epoch(val) [73][78/78] acc/top1: 0.6740 acc/top5: 0.8695 acc/mean1: 0.6739 2022/10/13 09:08:41 - mmengine - INFO - Epoch(train) [74][20/940] lr: 1.0000e-03 eta: 3:36:02 time: 0.6738 data_time: 0.2715 memory: 17006 grad_norm: 4.8304 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3282 loss: 1.3282 2022/10/13 09:08:51 - mmengine - INFO - Epoch(train) [74][40/940] lr: 1.0000e-03 eta: 3:35:51 time: 0.4665 data_time: 0.1261 memory: 17006 grad_norm: 4.8048 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2643 loss: 1.2643 2022/10/13 09:09:02 - mmengine - INFO - Epoch(train) [74][60/940] lr: 1.0000e-03 eta: 3:35:42 time: 0.5834 data_time: 0.1307 memory: 17006 grad_norm: 4.8443 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3099 loss: 1.3099 2022/10/13 09:09:12 - mmengine - INFO - Epoch(train) [74][80/940] lr: 1.0000e-03 eta: 3:35:31 time: 0.4833 data_time: 0.0254 memory: 17006 grad_norm: 4.8344 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.3267 loss: 1.3267 2022/10/13 09:09:23 - mmengine - INFO - Epoch(train) [74][100/940] lr: 1.0000e-03 eta: 3:35:21 time: 0.5436 data_time: 0.0362 memory: 17006 grad_norm: 4.8950 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2633 loss: 1.2633 2022/10/13 09:09:32 - mmengine - INFO - Epoch(train) [74][120/940] lr: 1.0000e-03 eta: 3:35:11 time: 0.4524 data_time: 0.0694 memory: 17006 grad_norm: 4.8064 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3625 loss: 1.3625 2022/10/13 09:09:42 - mmengine - INFO - Epoch(train) [74][140/940] lr: 1.0000e-03 eta: 3:35:01 time: 0.5286 data_time: 0.0730 memory: 17006 grad_norm: 4.8272 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2489 loss: 1.2489 2022/10/13 09:09:52 - mmengine - INFO - Epoch(train) [74][160/940] lr: 1.0000e-03 eta: 3:34:50 time: 0.5035 data_time: 0.0820 memory: 17006 grad_norm: 4.7775 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4842 loss: 1.4842 2022/10/13 09:10:03 - mmengine - INFO - Epoch(train) [74][180/940] lr: 1.0000e-03 eta: 3:34:40 time: 0.5255 data_time: 0.0569 memory: 17006 grad_norm: 4.8500 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2835 loss: 1.2835 2022/10/13 09:10:13 - mmengine - INFO - Epoch(train) [74][200/940] lr: 1.0000e-03 eta: 3:34:30 time: 0.4904 data_time: 0.0237 memory: 17006 grad_norm: 4.8614 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.3337 loss: 1.3337 2022/10/13 09:10:23 - mmengine - INFO - Epoch(train) [74][220/940] lr: 1.0000e-03 eta: 3:34:20 time: 0.5099 data_time: 0.0302 memory: 17006 grad_norm: 4.8041 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2600 loss: 1.2600 2022/10/13 09:10:33 - mmengine - INFO - Epoch(train) [74][240/940] lr: 1.0000e-03 eta: 3:34:09 time: 0.4777 data_time: 0.0289 memory: 17006 grad_norm: 4.8208 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2748 loss: 1.2748 2022/10/13 09:10:44 - mmengine - INFO - Epoch(train) [74][260/940] lr: 1.0000e-03 eta: 3:33:59 time: 0.5506 data_time: 0.0345 memory: 17006 grad_norm: 4.8303 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1778 loss: 1.1778 2022/10/13 09:10:53 - mmengine - INFO - Epoch(train) [74][280/940] lr: 1.0000e-03 eta: 3:33:49 time: 0.4794 data_time: 0.0306 memory: 17006 grad_norm: 4.7744 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3042 loss: 1.3042 2022/10/13 09:11:03 - mmengine - INFO - Epoch(train) [74][300/940] lr: 1.0000e-03 eta: 3:33:38 time: 0.5098 data_time: 0.0321 memory: 17006 grad_norm: 4.8150 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3018 loss: 1.3018 2022/10/13 09:11:14 - mmengine - INFO - Epoch(train) [74][320/940] lr: 1.0000e-03 eta: 3:33:28 time: 0.5114 data_time: 0.0356 memory: 17006 grad_norm: 4.8655 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3588 loss: 1.3588 2022/10/13 09:11:23 - mmengine - INFO - Epoch(train) [74][340/940] lr: 1.0000e-03 eta: 3:33:18 time: 0.4568 data_time: 0.0340 memory: 17006 grad_norm: 4.9168 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2369 loss: 1.2369 2022/10/13 09:11:34 - mmengine - INFO - Epoch(train) [74][360/940] lr: 1.0000e-03 eta: 3:33:08 time: 0.5702 data_time: 0.0351 memory: 17006 grad_norm: 4.8901 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1905 loss: 1.1905 2022/10/13 09:11:44 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 09:11:44 - mmengine - INFO - Epoch(train) [74][380/940] lr: 1.0000e-03 eta: 3:32:58 time: 0.5039 data_time: 0.0276 memory: 17006 grad_norm: 4.7659 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.4919 loss: 1.4919 2022/10/13 09:11:54 - mmengine - INFO - Epoch(train) [74][400/940] lr: 1.0000e-03 eta: 3:32:47 time: 0.5098 data_time: 0.0362 memory: 17006 grad_norm: 4.8520 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3385 loss: 1.3385 2022/10/13 09:12:05 - mmengine - INFO - Epoch(train) [74][420/940] lr: 1.0000e-03 eta: 3:32:37 time: 0.5112 data_time: 0.0271 memory: 17006 grad_norm: 4.7630 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1886 loss: 1.1886 2022/10/13 09:12:15 - mmengine - INFO - Epoch(train) [74][440/940] lr: 1.0000e-03 eta: 3:32:27 time: 0.5218 data_time: 0.0358 memory: 17006 grad_norm: 4.8171 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2935 loss: 1.2935 2022/10/13 09:12:25 - mmengine - INFO - Epoch(train) [74][460/940] lr: 1.0000e-03 eta: 3:32:17 time: 0.4938 data_time: 0.0358 memory: 17006 grad_norm: 4.7943 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3971 loss: 1.3971 2022/10/13 09:12:35 - mmengine - INFO - Epoch(train) [74][480/940] lr: 1.0000e-03 eta: 3:32:06 time: 0.5025 data_time: 0.0326 memory: 17006 grad_norm: 4.8041 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2135 loss: 1.2135 2022/10/13 09:12:45 - mmengine - INFO - Epoch(train) [74][500/940] lr: 1.0000e-03 eta: 3:31:56 time: 0.4922 data_time: 0.0312 memory: 17006 grad_norm: 4.8360 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2957 loss: 1.2957 2022/10/13 09:12:56 - mmengine - INFO - Epoch(train) [74][520/940] lr: 1.0000e-03 eta: 3:31:46 time: 0.5663 data_time: 0.0357 memory: 17006 grad_norm: 4.9117 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3387 loss: 1.3387 2022/10/13 09:13:05 - mmengine - INFO - Epoch(train) [74][540/940] lr: 1.0000e-03 eta: 3:31:35 time: 0.4373 data_time: 0.0315 memory: 17006 grad_norm: 4.9170 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2935 loss: 1.2935 2022/10/13 09:13:16 - mmengine - INFO - Epoch(train) [74][560/940] lr: 1.0000e-03 eta: 3:31:26 time: 0.5649 data_time: 0.0335 memory: 17006 grad_norm: 4.7664 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2182 loss: 1.2182 2022/10/13 09:13:26 - mmengine - INFO - Epoch(train) [74][580/940] lr: 1.0000e-03 eta: 3:31:15 time: 0.4776 data_time: 0.0303 memory: 17006 grad_norm: 5.0057 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4805 loss: 1.4805 2022/10/13 09:13:36 - mmengine - INFO - Epoch(train) [74][600/940] lr: 1.0000e-03 eta: 3:31:05 time: 0.5302 data_time: 0.0281 memory: 17006 grad_norm: 4.8295 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3497 loss: 1.3497 2022/10/13 09:13:46 - mmengine - INFO - Epoch(train) [74][620/940] lr: 1.0000e-03 eta: 3:30:54 time: 0.4708 data_time: 0.0352 memory: 17006 grad_norm: 4.7493 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2178 loss: 1.2178 2022/10/13 09:13:57 - mmengine - INFO - Epoch(train) [74][640/940] lr: 1.0000e-03 eta: 3:30:45 time: 0.5480 data_time: 0.0294 memory: 17006 grad_norm: 4.7767 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2193 loss: 1.2193 2022/10/13 09:14:06 - mmengine - INFO - Epoch(train) [74][660/940] lr: 1.0000e-03 eta: 3:30:34 time: 0.4822 data_time: 0.0324 memory: 17006 grad_norm: 4.8730 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3645 loss: 1.3645 2022/10/13 09:14:17 - mmengine - INFO - Epoch(train) [74][680/940] lr: 1.0000e-03 eta: 3:30:24 time: 0.5294 data_time: 0.0309 memory: 17006 grad_norm: 4.7522 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3862 loss: 1.3862 2022/10/13 09:14:27 - mmengine - INFO - Epoch(train) [74][700/940] lr: 1.0000e-03 eta: 3:30:14 time: 0.4867 data_time: 0.0341 memory: 17006 grad_norm: 4.7817 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1692 loss: 1.1692 2022/10/13 09:14:37 - mmengine - INFO - Epoch(train) [74][720/940] lr: 1.0000e-03 eta: 3:30:04 time: 0.5308 data_time: 0.0328 memory: 17006 grad_norm: 4.8941 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3144 loss: 1.3144 2022/10/13 09:14:47 - mmengine - INFO - Epoch(train) [74][740/940] lr: 1.0000e-03 eta: 3:29:53 time: 0.4712 data_time: 0.0264 memory: 17006 grad_norm: 4.8791 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2388 loss: 1.2388 2022/10/13 09:14:57 - mmengine - INFO - Epoch(train) [74][760/940] lr: 1.0000e-03 eta: 3:29:43 time: 0.5323 data_time: 0.0344 memory: 17006 grad_norm: 4.8730 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.3153 loss: 1.3153 2022/10/13 09:15:07 - mmengine - INFO - Epoch(train) [74][780/940] lr: 1.0000e-03 eta: 3:29:32 time: 0.4742 data_time: 0.0339 memory: 17006 grad_norm: 4.8554 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2793 loss: 1.2793 2022/10/13 09:15:17 - mmengine - INFO - Epoch(train) [74][800/940] lr: 1.0000e-03 eta: 3:29:22 time: 0.5051 data_time: 0.0299 memory: 17006 grad_norm: 4.8655 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2854 loss: 1.2854 2022/10/13 09:15:26 - mmengine - INFO - Epoch(train) [74][820/940] lr: 1.0000e-03 eta: 3:29:12 time: 0.4722 data_time: 0.0304 memory: 17006 grad_norm: 4.8198 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4138 loss: 1.4138 2022/10/13 09:15:38 - mmengine - INFO - Epoch(train) [74][840/940] lr: 1.0000e-03 eta: 3:29:02 time: 0.5559 data_time: 0.0312 memory: 17006 grad_norm: 4.8496 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4005 loss: 1.4005 2022/10/13 09:15:46 - mmengine - INFO - Epoch(train) [74][860/940] lr: 1.0000e-03 eta: 3:28:51 time: 0.4395 data_time: 0.0373 memory: 17006 grad_norm: 4.8110 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2907 loss: 1.2907 2022/10/13 09:15:56 - mmengine - INFO - Epoch(train) [74][880/940] lr: 1.0000e-03 eta: 3:28:41 time: 0.5018 data_time: 0.0320 memory: 17006 grad_norm: 4.8498 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3272 loss: 1.3272 2022/10/13 09:16:07 - mmengine - INFO - Epoch(train) [74][900/940] lr: 1.0000e-03 eta: 3:28:31 time: 0.5235 data_time: 0.0337 memory: 17006 grad_norm: 4.9447 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2627 loss: 1.2627 2022/10/13 09:16:17 - mmengine - INFO - Epoch(train) [74][920/940] lr: 1.0000e-03 eta: 3:28:20 time: 0.5181 data_time: 0.0282 memory: 17006 grad_norm: 4.7596 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3097 loss: 1.3097 2022/10/13 09:16:26 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 09:16:26 - mmengine - INFO - Epoch(train) [74][940/940] lr: 1.0000e-03 eta: 3:28:10 time: 0.4334 data_time: 0.0268 memory: 17006 grad_norm: 5.2135 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.3742 loss: 1.3742 2022/10/13 09:16:39 - mmengine - INFO - Epoch(val) [74][20/78] eta: 0:00:36 time: 0.6291 data_time: 0.5338 memory: 3172 2022/10/13 09:16:47 - mmengine - INFO - Epoch(val) [74][40/78] eta: 0:00:16 time: 0.4320 data_time: 0.3409 memory: 3172 2022/10/13 09:16:59 - mmengine - INFO - Epoch(val) [74][60/78] eta: 0:00:10 time: 0.5697 data_time: 0.4769 memory: 3172 2022/10/13 09:17:08 - mmengine - INFO - Epoch(val) [74][78/78] acc/top1: 0.6721 acc/top5: 0.8700 acc/mean1: 0.6720 2022/10/13 09:17:22 - mmengine - INFO - Epoch(train) [75][20/940] lr: 1.0000e-03 eta: 3:28:01 time: 0.6747 data_time: 0.2246 memory: 17006 grad_norm: 4.8628 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2713 loss: 1.2713 2022/10/13 09:17:31 - mmengine - INFO - Epoch(train) [75][40/940] lr: 1.0000e-03 eta: 3:27:50 time: 0.4709 data_time: 0.0271 memory: 17006 grad_norm: 4.8428 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2095 loss: 1.2095 2022/10/13 09:17:43 - mmengine - INFO - Epoch(train) [75][60/940] lr: 1.0000e-03 eta: 3:27:40 time: 0.5779 data_time: 0.0413 memory: 17006 grad_norm: 4.7788 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.3014 loss: 1.3014 2022/10/13 09:17:52 - mmengine - INFO - Epoch(train) [75][80/940] lr: 1.0000e-03 eta: 3:27:30 time: 0.4586 data_time: 0.0258 memory: 17006 grad_norm: 4.8483 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3065 loss: 1.3065 2022/10/13 09:18:04 - mmengine - INFO - Epoch(train) [75][100/940] lr: 1.0000e-03 eta: 3:27:20 time: 0.5714 data_time: 0.0893 memory: 17006 grad_norm: 4.7851 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1102 loss: 1.1102 2022/10/13 09:18:12 - mmengine - INFO - Epoch(train) [75][120/940] lr: 1.0000e-03 eta: 3:27:09 time: 0.4428 data_time: 0.0647 memory: 17006 grad_norm: 4.8284 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3315 loss: 1.3315 2022/10/13 09:18:24 - mmengine - INFO - Epoch(train) [75][140/940] lr: 1.0000e-03 eta: 3:26:59 time: 0.5571 data_time: 0.1057 memory: 17006 grad_norm: 4.8351 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2980 loss: 1.2980 2022/10/13 09:18:33 - mmengine - INFO - Epoch(train) [75][160/940] lr: 1.0000e-03 eta: 3:26:49 time: 0.4678 data_time: 0.0274 memory: 17006 grad_norm: 4.8164 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1767 loss: 1.1767 2022/10/13 09:18:45 - mmengine - INFO - Epoch(train) [75][180/940] lr: 1.0000e-03 eta: 3:26:39 time: 0.5822 data_time: 0.0363 memory: 17006 grad_norm: 4.7535 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2406 loss: 1.2406 2022/10/13 09:18:54 - mmengine - INFO - Epoch(train) [75][200/940] lr: 1.0000e-03 eta: 3:26:29 time: 0.4768 data_time: 0.0272 memory: 17006 grad_norm: 4.7859 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3316 loss: 1.3316 2022/10/13 09:19:04 - mmengine - INFO - Epoch(train) [75][220/940] lr: 1.0000e-03 eta: 3:26:18 time: 0.5111 data_time: 0.0356 memory: 17006 grad_norm: 4.9024 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4087 loss: 1.4087 2022/10/13 09:19:14 - mmengine - INFO - Epoch(train) [75][240/940] lr: 1.0000e-03 eta: 3:26:08 time: 0.4701 data_time: 0.0300 memory: 17006 grad_norm: 4.9660 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2758 loss: 1.2758 2022/10/13 09:19:24 - mmengine - INFO - Epoch(train) [75][260/940] lr: 1.0000e-03 eta: 3:25:58 time: 0.5290 data_time: 0.0380 memory: 17006 grad_norm: 4.8214 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.2591 loss: 1.2591 2022/10/13 09:19:34 - mmengine - INFO - Epoch(train) [75][280/940] lr: 1.0000e-03 eta: 3:25:48 time: 0.4992 data_time: 0.0310 memory: 17006 grad_norm: 4.7443 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.2579 loss: 1.2579 2022/10/13 09:19:45 - mmengine - INFO - Epoch(train) [75][300/940] lr: 1.0000e-03 eta: 3:25:38 time: 0.5551 data_time: 0.0343 memory: 17006 grad_norm: 4.8247 top1_acc: 0.4688 top5_acc: 0.7188 loss_cls: 1.3277 loss: 1.3277 2022/10/13 09:19:55 - mmengine - INFO - Epoch(train) [75][320/940] lr: 1.0000e-03 eta: 3:25:27 time: 0.5011 data_time: 0.0357 memory: 17006 grad_norm: 4.8152 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2774 loss: 1.2774 2022/10/13 09:20:05 - mmengine - INFO - Epoch(train) [75][340/940] lr: 1.0000e-03 eta: 3:25:17 time: 0.4983 data_time: 0.0391 memory: 17006 grad_norm: 4.8675 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3624 loss: 1.3624 2022/10/13 09:20:15 - mmengine - INFO - Epoch(train) [75][360/940] lr: 1.0000e-03 eta: 3:25:07 time: 0.4781 data_time: 0.0329 memory: 17006 grad_norm: 4.9437 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2830 loss: 1.2830 2022/10/13 09:20:25 - mmengine - INFO - Epoch(train) [75][380/940] lr: 1.0000e-03 eta: 3:24:56 time: 0.5242 data_time: 0.0330 memory: 17006 grad_norm: 4.9286 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2597 loss: 1.2597 2022/10/13 09:20:35 - mmengine - INFO - Epoch(train) [75][400/940] lr: 1.0000e-03 eta: 3:24:46 time: 0.4679 data_time: 0.0261 memory: 17006 grad_norm: 4.8357 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2535 loss: 1.2535 2022/10/13 09:20:46 - mmengine - INFO - Epoch(train) [75][420/940] lr: 1.0000e-03 eta: 3:24:36 time: 0.5393 data_time: 0.0338 memory: 17006 grad_norm: 4.7798 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3088 loss: 1.3088 2022/10/13 09:20:55 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 09:20:55 - mmengine - INFO - Epoch(train) [75][440/940] lr: 1.0000e-03 eta: 3:24:25 time: 0.4594 data_time: 0.0241 memory: 17006 grad_norm: 4.9045 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5100 loss: 1.5100 2022/10/13 09:21:05 - mmengine - INFO - Epoch(train) [75][460/940] lr: 1.0000e-03 eta: 3:24:15 time: 0.5111 data_time: 0.0337 memory: 17006 grad_norm: 4.8974 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.3274 loss: 1.3274 2022/10/13 09:21:15 - mmengine - INFO - Epoch(train) [75][480/940] lr: 1.0000e-03 eta: 3:24:05 time: 0.5157 data_time: 0.0308 memory: 17006 grad_norm: 4.9026 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2697 loss: 1.2697 2022/10/13 09:21:26 - mmengine - INFO - Epoch(train) [75][500/940] lr: 1.0000e-03 eta: 3:23:55 time: 0.5178 data_time: 0.0375 memory: 17006 grad_norm: 4.9709 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4129 loss: 1.4129 2022/10/13 09:21:36 - mmengine - INFO - Epoch(train) [75][520/940] lr: 1.0000e-03 eta: 3:23:45 time: 0.5210 data_time: 0.0342 memory: 17006 grad_norm: 4.8190 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.2716 loss: 1.2716 2022/10/13 09:21:46 - mmengine - INFO - Epoch(train) [75][540/940] lr: 1.0000e-03 eta: 3:23:34 time: 0.4905 data_time: 0.0357 memory: 17006 grad_norm: 4.8224 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3057 loss: 1.3057 2022/10/13 09:21:56 - mmengine - INFO - Epoch(train) [75][560/940] lr: 1.0000e-03 eta: 3:23:24 time: 0.5206 data_time: 0.0294 memory: 17006 grad_norm: 4.9971 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3522 loss: 1.3522 2022/10/13 09:22:06 - mmengine - INFO - Epoch(train) [75][580/940] lr: 1.0000e-03 eta: 3:23:14 time: 0.4657 data_time: 0.0308 memory: 17006 grad_norm: 4.9792 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2132 loss: 1.2132 2022/10/13 09:22:16 - mmengine - INFO - Epoch(train) [75][600/940] lr: 1.0000e-03 eta: 3:23:03 time: 0.5228 data_time: 0.0390 memory: 17006 grad_norm: 4.8126 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2867 loss: 1.2867 2022/10/13 09:22:27 - mmengine - INFO - Epoch(train) [75][620/940] lr: 1.0000e-03 eta: 3:22:53 time: 0.5391 data_time: 0.0299 memory: 17006 grad_norm: 4.9554 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3564 loss: 1.3564 2022/10/13 09:22:37 - mmengine - INFO - Epoch(train) [75][640/940] lr: 1.0000e-03 eta: 3:22:43 time: 0.4964 data_time: 0.0340 memory: 17006 grad_norm: 4.9752 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2550 loss: 1.2550 2022/10/13 09:22:48 - mmengine - INFO - Epoch(train) [75][660/940] lr: 1.0000e-03 eta: 3:22:33 time: 0.5711 data_time: 0.0331 memory: 17006 grad_norm: 4.8880 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2857 loss: 1.2857 2022/10/13 09:22:58 - mmengine - INFO - Epoch(train) [75][680/940] lr: 1.0000e-03 eta: 3:22:23 time: 0.4972 data_time: 0.0294 memory: 17006 grad_norm: 4.8142 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3260 loss: 1.3260 2022/10/13 09:23:08 - mmengine - INFO - Epoch(train) [75][700/940] lr: 1.0000e-03 eta: 3:22:13 time: 0.4960 data_time: 0.0348 memory: 17006 grad_norm: 4.8804 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2952 loss: 1.2952 2022/10/13 09:23:17 - mmengine - INFO - Epoch(train) [75][720/940] lr: 1.0000e-03 eta: 3:22:02 time: 0.4602 data_time: 0.0336 memory: 17006 grad_norm: 4.9598 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2453 loss: 1.2453 2022/10/13 09:23:28 - mmengine - INFO - Epoch(train) [75][740/940] lr: 1.0000e-03 eta: 3:21:52 time: 0.5318 data_time: 0.0384 memory: 17006 grad_norm: 4.7789 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3176 loss: 1.3176 2022/10/13 09:23:38 - mmengine - INFO - Epoch(train) [75][760/940] lr: 1.0000e-03 eta: 3:21:42 time: 0.4916 data_time: 0.0311 memory: 17006 grad_norm: 4.8272 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2102 loss: 1.2102 2022/10/13 09:23:49 - mmengine - INFO - Epoch(train) [75][780/940] lr: 1.0000e-03 eta: 3:21:32 time: 0.5491 data_time: 0.0385 memory: 17006 grad_norm: 4.9102 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3053 loss: 1.3053 2022/10/13 09:23:59 - mmengine - INFO - Epoch(train) [75][800/940] lr: 1.0000e-03 eta: 3:21:21 time: 0.5000 data_time: 0.0268 memory: 17006 grad_norm: 4.8835 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3803 loss: 1.3803 2022/10/13 09:24:10 - mmengine - INFO - Epoch(train) [75][820/940] lr: 1.0000e-03 eta: 3:21:11 time: 0.5471 data_time: 0.0314 memory: 17006 grad_norm: 4.8314 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2202 loss: 1.2202 2022/10/13 09:24:19 - mmengine - INFO - Epoch(train) [75][840/940] lr: 1.0000e-03 eta: 3:21:01 time: 0.4672 data_time: 0.0318 memory: 17006 grad_norm: 4.9347 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2751 loss: 1.2751 2022/10/13 09:24:30 - mmengine - INFO - Epoch(train) [75][860/940] lr: 1.0000e-03 eta: 3:20:51 time: 0.5302 data_time: 0.0302 memory: 17006 grad_norm: 4.8428 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2347 loss: 1.2347 2022/10/13 09:24:40 - mmengine - INFO - Epoch(train) [75][880/940] lr: 1.0000e-03 eta: 3:20:40 time: 0.4996 data_time: 0.0361 memory: 17006 grad_norm: 4.8221 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2322 loss: 1.2322 2022/10/13 09:24:50 - mmengine - INFO - Epoch(train) [75][900/940] lr: 1.0000e-03 eta: 3:20:30 time: 0.5035 data_time: 0.0286 memory: 17006 grad_norm: 4.8643 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.4773 loss: 1.4773 2022/10/13 09:24:59 - mmengine - INFO - Epoch(train) [75][920/940] lr: 1.0000e-03 eta: 3:20:20 time: 0.4843 data_time: 0.0352 memory: 17006 grad_norm: 4.9843 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2702 loss: 1.2702 2022/10/13 09:25:09 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 09:25:09 - mmengine - INFO - Epoch(train) [75][940/940] lr: 1.0000e-03 eta: 3:20:09 time: 0.4755 data_time: 0.0245 memory: 17006 grad_norm: 5.1106 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1645 loss: 1.1645 2022/10/13 09:25:09 - mmengine - INFO - Saving checkpoint at 75 epochs 2022/10/13 09:25:22 - mmengine - INFO - Epoch(val) [75][20/78] eta: 0:00:35 time: 0.6202 data_time: 0.5303 memory: 3172 2022/10/13 09:25:31 - mmengine - INFO - Epoch(val) [75][40/78] eta: 0:00:16 time: 0.4325 data_time: 0.3414 memory: 3172 2022/10/13 09:25:42 - mmengine - INFO - Epoch(val) [75][60/78] eta: 0:00:10 time: 0.5782 data_time: 0.4885 memory: 3172 2022/10/13 09:25:52 - mmengine - INFO - Epoch(val) [75][78/78] acc/top1: 0.6733 acc/top5: 0.8685 acc/mean1: 0.6732 2022/10/13 09:26:06 - mmengine - INFO - Epoch(train) [76][20/940] lr: 1.0000e-03 eta: 3:20:00 time: 0.6987 data_time: 0.2914 memory: 17006 grad_norm: 4.8184 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.4248 loss: 1.4248 2022/10/13 09:26:16 - mmengine - INFO - Epoch(train) [76][40/940] lr: 1.0000e-03 eta: 3:19:50 time: 0.4957 data_time: 0.0271 memory: 17006 grad_norm: 4.8948 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.2941 loss: 1.2941 2022/10/13 09:26:27 - mmengine - INFO - Epoch(train) [76][60/940] lr: 1.0000e-03 eta: 3:19:40 time: 0.5732 data_time: 0.0316 memory: 17006 grad_norm: 4.8729 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2379 loss: 1.2379 2022/10/13 09:26:37 - mmengine - INFO - Epoch(train) [76][80/940] lr: 1.0000e-03 eta: 3:19:30 time: 0.4783 data_time: 0.0287 memory: 17006 grad_norm: 4.8351 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2026 loss: 1.2026 2022/10/13 09:26:47 - mmengine - INFO - Epoch(train) [76][100/940] lr: 1.0000e-03 eta: 3:19:20 time: 0.5334 data_time: 0.0382 memory: 17006 grad_norm: 4.8855 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2554 loss: 1.2554 2022/10/13 09:26:56 - mmengine - INFO - Epoch(train) [76][120/940] lr: 1.0000e-03 eta: 3:19:09 time: 0.4476 data_time: 0.0317 memory: 17006 grad_norm: 4.8020 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2489 loss: 1.2489 2022/10/13 09:27:08 - mmengine - INFO - Epoch(train) [76][140/940] lr: 1.0000e-03 eta: 3:18:59 time: 0.5809 data_time: 0.0339 memory: 17006 grad_norm: 4.8257 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.1157 loss: 1.1157 2022/10/13 09:27:18 - mmengine - INFO - Epoch(train) [76][160/940] lr: 1.0000e-03 eta: 3:18:49 time: 0.4814 data_time: 0.0271 memory: 17006 grad_norm: 4.8664 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2216 loss: 1.2216 2022/10/13 09:27:29 - mmengine - INFO - Epoch(train) [76][180/940] lr: 1.0000e-03 eta: 3:18:39 time: 0.5493 data_time: 0.0385 memory: 17006 grad_norm: 4.8529 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2245 loss: 1.2245 2022/10/13 09:27:38 - mmengine - INFO - Epoch(train) [76][200/940] lr: 1.0000e-03 eta: 3:18:28 time: 0.4595 data_time: 0.0279 memory: 17006 grad_norm: 4.7789 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2009 loss: 1.2009 2022/10/13 09:27:50 - mmengine - INFO - Epoch(train) [76][220/940] lr: 1.0000e-03 eta: 3:18:19 time: 0.5906 data_time: 0.0365 memory: 17006 grad_norm: 4.8590 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3358 loss: 1.3358 2022/10/13 09:27:59 - mmengine - INFO - Epoch(train) [76][240/940] lr: 1.0000e-03 eta: 3:18:08 time: 0.4646 data_time: 0.0272 memory: 17006 grad_norm: 4.8478 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2292 loss: 1.2292 2022/10/13 09:28:10 - mmengine - INFO - Epoch(train) [76][260/940] lr: 1.0000e-03 eta: 3:17:58 time: 0.5797 data_time: 0.0291 memory: 17006 grad_norm: 4.8474 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2497 loss: 1.2497 2022/10/13 09:28:19 - mmengine - INFO - Epoch(train) [76][280/940] lr: 1.0000e-03 eta: 3:17:47 time: 0.4180 data_time: 0.0270 memory: 17006 grad_norm: 5.0326 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3550 loss: 1.3550 2022/10/13 09:28:30 - mmengine - INFO - Epoch(train) [76][300/940] lr: 1.0000e-03 eta: 3:17:38 time: 0.5642 data_time: 0.0313 memory: 17006 grad_norm: 4.8486 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3677 loss: 1.3677 2022/10/13 09:28:39 - mmengine - INFO - Epoch(train) [76][320/940] lr: 1.0000e-03 eta: 3:17:27 time: 0.4514 data_time: 0.0301 memory: 17006 grad_norm: 4.9479 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3342 loss: 1.3342 2022/10/13 09:28:50 - mmengine - INFO - Epoch(train) [76][340/940] lr: 1.0000e-03 eta: 3:17:17 time: 0.5564 data_time: 0.0313 memory: 17006 grad_norm: 4.8692 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3930 loss: 1.3930 2022/10/13 09:29:00 - mmengine - INFO - Epoch(train) [76][360/940] lr: 1.0000e-03 eta: 3:17:07 time: 0.4851 data_time: 0.0297 memory: 17006 grad_norm: 4.9681 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2849 loss: 1.2849 2022/10/13 09:29:12 - mmengine - INFO - Epoch(train) [76][380/940] lr: 1.0000e-03 eta: 3:16:57 time: 0.5899 data_time: 0.0361 memory: 17006 grad_norm: 4.8584 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2849 loss: 1.2849 2022/10/13 09:29:21 - mmengine - INFO - Epoch(train) [76][400/940] lr: 1.0000e-03 eta: 3:16:47 time: 0.4723 data_time: 0.0303 memory: 17006 grad_norm: 4.8344 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2942 loss: 1.2942 2022/10/13 09:29:32 - mmengine - INFO - Epoch(train) [76][420/940] lr: 1.0000e-03 eta: 3:16:37 time: 0.5638 data_time: 0.0297 memory: 17006 grad_norm: 4.8760 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2052 loss: 1.2052 2022/10/13 09:29:42 - mmengine - INFO - Epoch(train) [76][440/940] lr: 1.0000e-03 eta: 3:16:26 time: 0.4960 data_time: 0.0280 memory: 17006 grad_norm: 5.0240 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3698 loss: 1.3698 2022/10/13 09:29:53 - mmengine - INFO - Epoch(train) [76][460/940] lr: 1.0000e-03 eta: 3:16:16 time: 0.5459 data_time: 0.0316 memory: 17006 grad_norm: 4.8510 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2339 loss: 1.2339 2022/10/13 09:30:02 - mmengine - INFO - Epoch(train) [76][480/940] lr: 1.0000e-03 eta: 3:16:06 time: 0.4329 data_time: 0.0257 memory: 17006 grad_norm: 4.8806 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2725 loss: 1.2725 2022/10/13 09:30:12 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 09:30:12 - mmengine - INFO - Epoch(train) [76][500/940] lr: 1.0000e-03 eta: 3:15:55 time: 0.5135 data_time: 0.0354 memory: 17006 grad_norm: 4.8266 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2784 loss: 1.2784 2022/10/13 09:30:22 - mmengine - INFO - Epoch(train) [76][520/940] lr: 1.0000e-03 eta: 3:15:45 time: 0.5062 data_time: 0.0370 memory: 17006 grad_norm: 4.8328 top1_acc: 0.5938 top5_acc: 0.6562 loss_cls: 1.1983 loss: 1.1983 2022/10/13 09:30:33 - mmengine - INFO - Epoch(train) [76][540/940] lr: 1.0000e-03 eta: 3:15:35 time: 0.5306 data_time: 0.0320 memory: 17006 grad_norm: 4.8983 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3045 loss: 1.3045 2022/10/13 09:30:43 - mmengine - INFO - Epoch(train) [76][560/940] lr: 1.0000e-03 eta: 3:15:25 time: 0.4845 data_time: 0.0326 memory: 17006 grad_norm: 4.8385 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3160 loss: 1.3160 2022/10/13 09:30:54 - mmengine - INFO - Epoch(train) [76][580/940] lr: 1.0000e-03 eta: 3:15:15 time: 0.5586 data_time: 0.0352 memory: 17006 grad_norm: 4.9300 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.4243 loss: 1.4243 2022/10/13 09:31:03 - mmengine - INFO - Epoch(train) [76][600/940] lr: 1.0000e-03 eta: 3:15:04 time: 0.4462 data_time: 0.0305 memory: 17006 grad_norm: 4.9602 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4496 loss: 1.4496 2022/10/13 09:31:13 - mmengine - INFO - Epoch(train) [76][620/940] lr: 1.0000e-03 eta: 3:14:54 time: 0.5113 data_time: 0.0297 memory: 17006 grad_norm: 4.8213 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3179 loss: 1.3179 2022/10/13 09:31:23 - mmengine - INFO - Epoch(train) [76][640/940] lr: 1.0000e-03 eta: 3:14:44 time: 0.5126 data_time: 0.0333 memory: 17006 grad_norm: 4.7914 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3486 loss: 1.3486 2022/10/13 09:31:34 - mmengine - INFO - Epoch(train) [76][660/940] lr: 1.0000e-03 eta: 3:14:34 time: 0.5557 data_time: 0.0314 memory: 17006 grad_norm: 4.8938 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3390 loss: 1.3390 2022/10/13 09:31:43 - mmengine - INFO - Epoch(train) [76][680/940] lr: 1.0000e-03 eta: 3:14:23 time: 0.4532 data_time: 0.0367 memory: 17006 grad_norm: 4.8736 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2982 loss: 1.2982 2022/10/13 09:31:54 - mmengine - INFO - Epoch(train) [76][700/940] lr: 1.0000e-03 eta: 3:14:13 time: 0.5387 data_time: 0.0248 memory: 17006 grad_norm: 4.9268 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2030 loss: 1.2030 2022/10/13 09:32:03 - mmengine - INFO - Epoch(train) [76][720/940] lr: 1.0000e-03 eta: 3:14:02 time: 0.4405 data_time: 0.0356 memory: 17006 grad_norm: 4.8862 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2282 loss: 1.2282 2022/10/13 09:32:14 - mmengine - INFO - Epoch(train) [76][740/940] lr: 1.0000e-03 eta: 3:13:52 time: 0.5422 data_time: 0.0261 memory: 17006 grad_norm: 4.8504 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3886 loss: 1.3886 2022/10/13 09:32:24 - mmengine - INFO - Epoch(train) [76][760/940] lr: 1.0000e-03 eta: 3:13:42 time: 0.4882 data_time: 0.0379 memory: 17006 grad_norm: 4.8587 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3433 loss: 1.3433 2022/10/13 09:32:34 - mmengine - INFO - Epoch(train) [76][780/940] lr: 1.0000e-03 eta: 3:13:32 time: 0.5344 data_time: 0.0285 memory: 17006 grad_norm: 4.8317 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2253 loss: 1.2253 2022/10/13 09:32:44 - mmengine - INFO - Epoch(train) [76][800/940] lr: 1.0000e-03 eta: 3:13:22 time: 0.5079 data_time: 0.0375 memory: 17006 grad_norm: 4.8386 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2678 loss: 1.2678 2022/10/13 09:32:55 - mmengine - INFO - Epoch(train) [76][820/940] lr: 1.0000e-03 eta: 3:13:11 time: 0.5030 data_time: 0.0319 memory: 17006 grad_norm: 4.9296 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.4088 loss: 1.4088 2022/10/13 09:33:04 - mmengine - INFO - Epoch(train) [76][840/940] lr: 1.0000e-03 eta: 3:13:01 time: 0.4575 data_time: 0.0331 memory: 17006 grad_norm: 4.8581 top1_acc: 0.7812 top5_acc: 0.7812 loss_cls: 1.2251 loss: 1.2251 2022/10/13 09:33:14 - mmengine - INFO - Epoch(train) [76][860/940] lr: 1.0000e-03 eta: 3:12:51 time: 0.5068 data_time: 0.0378 memory: 17006 grad_norm: 4.8763 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3276 loss: 1.3276 2022/10/13 09:33:24 - mmengine - INFO - Epoch(train) [76][880/940] lr: 1.0000e-03 eta: 3:12:40 time: 0.4906 data_time: 0.0314 memory: 17006 grad_norm: 5.0435 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3789 loss: 1.3789 2022/10/13 09:33:34 - mmengine - INFO - Epoch(train) [76][900/940] lr: 1.0000e-03 eta: 3:12:30 time: 0.5304 data_time: 0.0305 memory: 17006 grad_norm: 4.8867 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2583 loss: 1.2583 2022/10/13 09:33:44 - mmengine - INFO - Epoch(train) [76][920/940] lr: 1.0000e-03 eta: 3:12:20 time: 0.4861 data_time: 0.0377 memory: 17006 grad_norm: 4.8651 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2287 loss: 1.2287 2022/10/13 09:33:54 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 09:33:54 - mmengine - INFO - Epoch(train) [76][940/940] lr: 1.0000e-03 eta: 3:12:10 time: 0.5193 data_time: 0.0246 memory: 17006 grad_norm: 5.3028 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.3024 loss: 1.3024 2022/10/13 09:34:07 - mmengine - INFO - Epoch(val) [76][20/78] eta: 0:00:36 time: 0.6273 data_time: 0.5339 memory: 3172 2022/10/13 09:34:16 - mmengine - INFO - Epoch(val) [76][40/78] eta: 0:00:16 time: 0.4351 data_time: 0.3425 memory: 3172 2022/10/13 09:34:27 - mmengine - INFO - Epoch(val) [76][60/78] eta: 0:00:10 time: 0.5710 data_time: 0.4804 memory: 3172 2022/10/13 09:34:37 - mmengine - INFO - Epoch(val) [76][78/78] acc/top1: 0.6731 acc/top5: 0.8685 acc/mean1: 0.6730 2022/10/13 09:34:52 - mmengine - INFO - Epoch(train) [77][20/940] lr: 1.0000e-03 eta: 3:12:01 time: 0.7332 data_time: 0.2611 memory: 17006 grad_norm: 4.9034 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3323 loss: 1.3323 2022/10/13 09:35:01 - mmengine - INFO - Epoch(train) [77][40/940] lr: 1.0000e-03 eta: 3:11:50 time: 0.4509 data_time: 0.0325 memory: 17006 grad_norm: 4.8749 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2935 loss: 1.2935 2022/10/13 09:35:12 - mmengine - INFO - Epoch(train) [77][60/940] lr: 1.0000e-03 eta: 3:11:40 time: 0.5488 data_time: 0.0372 memory: 17006 grad_norm: 4.8952 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3169 loss: 1.3169 2022/10/13 09:35:21 - mmengine - INFO - Epoch(train) [77][80/940] lr: 1.0000e-03 eta: 3:11:30 time: 0.4739 data_time: 0.0289 memory: 17006 grad_norm: 4.8261 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.2091 loss: 1.2091 2022/10/13 09:35:32 - mmengine - INFO - Epoch(train) [77][100/940] lr: 1.0000e-03 eta: 3:11:20 time: 0.5175 data_time: 0.0317 memory: 17006 grad_norm: 4.9200 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3473 loss: 1.3473 2022/10/13 09:35:41 - mmengine - INFO - Epoch(train) [77][120/940] lr: 1.0000e-03 eta: 3:11:09 time: 0.4734 data_time: 0.0360 memory: 17006 grad_norm: 4.8319 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.3096 loss: 1.3096 2022/10/13 09:35:52 - mmengine - INFO - Epoch(train) [77][140/940] lr: 1.0000e-03 eta: 3:10:59 time: 0.5497 data_time: 0.0323 memory: 17006 grad_norm: 4.9401 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.5268 loss: 1.5268 2022/10/13 09:36:01 - mmengine - INFO - Epoch(train) [77][160/940] lr: 1.0000e-03 eta: 3:10:49 time: 0.4568 data_time: 0.0321 memory: 17006 grad_norm: 4.9505 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2874 loss: 1.2874 2022/10/13 09:36:12 - mmengine - INFO - Epoch(train) [77][180/940] lr: 1.0000e-03 eta: 3:10:39 time: 0.5452 data_time: 0.0319 memory: 17006 grad_norm: 4.9400 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4481 loss: 1.4481 2022/10/13 09:36:22 - mmengine - INFO - Epoch(train) [77][200/940] lr: 1.0000e-03 eta: 3:10:28 time: 0.4885 data_time: 0.0336 memory: 17006 grad_norm: 4.9404 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2729 loss: 1.2729 2022/10/13 09:36:33 - mmengine - INFO - Epoch(train) [77][220/940] lr: 1.0000e-03 eta: 3:10:18 time: 0.5527 data_time: 0.0318 memory: 17006 grad_norm: 5.0016 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3894 loss: 1.3894 2022/10/13 09:36:43 - mmengine - INFO - Epoch(train) [77][240/940] lr: 1.0000e-03 eta: 3:10:08 time: 0.5047 data_time: 0.0292 memory: 17006 grad_norm: 4.8751 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2736 loss: 1.2736 2022/10/13 09:36:54 - mmengine - INFO - Epoch(train) [77][260/940] lr: 1.0000e-03 eta: 3:09:58 time: 0.5449 data_time: 0.0334 memory: 17006 grad_norm: 4.9996 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3277 loss: 1.3277 2022/10/13 09:37:03 - mmengine - INFO - Epoch(train) [77][280/940] lr: 1.0000e-03 eta: 3:09:47 time: 0.4657 data_time: 0.0312 memory: 17006 grad_norm: 4.8282 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3014 loss: 1.3014 2022/10/13 09:37:15 - mmengine - INFO - Epoch(train) [77][300/940] lr: 1.0000e-03 eta: 3:09:38 time: 0.5684 data_time: 0.0313 memory: 17006 grad_norm: 4.9261 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3199 loss: 1.3199 2022/10/13 09:37:24 - mmengine - INFO - Epoch(train) [77][320/940] lr: 1.0000e-03 eta: 3:09:27 time: 0.4883 data_time: 0.0345 memory: 17006 grad_norm: 4.9445 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3315 loss: 1.3315 2022/10/13 09:37:35 - mmengine - INFO - Epoch(train) [77][340/940] lr: 1.0000e-03 eta: 3:09:17 time: 0.5048 data_time: 0.0320 memory: 17006 grad_norm: 4.8301 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3631 loss: 1.3631 2022/10/13 09:37:45 - mmengine - INFO - Epoch(train) [77][360/940] lr: 1.0000e-03 eta: 3:09:07 time: 0.5081 data_time: 0.0309 memory: 17006 grad_norm: 4.9493 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2033 loss: 1.2033 2022/10/13 09:37:54 - mmengine - INFO - Epoch(train) [77][380/940] lr: 1.0000e-03 eta: 3:08:56 time: 0.4599 data_time: 0.0291 memory: 17006 grad_norm: 4.8998 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2459 loss: 1.2459 2022/10/13 09:38:04 - mmengine - INFO - Epoch(train) [77][400/940] lr: 1.0000e-03 eta: 3:08:46 time: 0.5033 data_time: 0.0370 memory: 17006 grad_norm: 5.0694 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3817 loss: 1.3817 2022/10/13 09:38:15 - mmengine - INFO - Epoch(train) [77][420/940] lr: 1.0000e-03 eta: 3:08:36 time: 0.5304 data_time: 0.0371 memory: 17006 grad_norm: 4.9398 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.2761 loss: 1.2761 2022/10/13 09:38:24 - mmengine - INFO - Epoch(train) [77][440/940] lr: 1.0000e-03 eta: 3:08:25 time: 0.4862 data_time: 0.0370 memory: 17006 grad_norm: 4.9195 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3591 loss: 1.3591 2022/10/13 09:38:34 - mmengine - INFO - Epoch(train) [77][460/940] lr: 1.0000e-03 eta: 3:08:15 time: 0.5032 data_time: 0.0306 memory: 17006 grad_norm: 4.8625 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2824 loss: 1.2824 2022/10/13 09:38:45 - mmengine - INFO - Epoch(train) [77][480/940] lr: 1.0000e-03 eta: 3:08:05 time: 0.5308 data_time: 0.0321 memory: 17006 grad_norm: 4.9586 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3145 loss: 1.3145 2022/10/13 09:38:56 - mmengine - INFO - Epoch(train) [77][500/940] lr: 1.0000e-03 eta: 3:07:55 time: 0.5260 data_time: 0.0323 memory: 17006 grad_norm: 5.0166 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4177 loss: 1.4177 2022/10/13 09:39:05 - mmengine - INFO - Epoch(train) [77][520/940] lr: 1.0000e-03 eta: 3:07:44 time: 0.4777 data_time: 0.0354 memory: 17006 grad_norm: 4.8726 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2950 loss: 1.2950 2022/10/13 09:39:15 - mmengine - INFO - Epoch(train) [77][540/940] lr: 1.0000e-03 eta: 3:07:34 time: 0.5186 data_time: 0.0342 memory: 17006 grad_norm: 4.9405 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2667 loss: 1.2667 2022/10/13 09:39:25 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 09:39:25 - mmengine - INFO - Epoch(train) [77][560/940] lr: 1.0000e-03 eta: 3:07:24 time: 0.4959 data_time: 0.0343 memory: 17006 grad_norm: 4.9118 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2843 loss: 1.2843 2022/10/13 09:39:36 - mmengine - INFO - Epoch(train) [77][580/940] lr: 1.0000e-03 eta: 3:07:14 time: 0.5152 data_time: 0.0349 memory: 17006 grad_norm: 4.9717 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.3435 loss: 1.3435 2022/10/13 09:39:45 - mmengine - INFO - Epoch(train) [77][600/940] lr: 1.0000e-03 eta: 3:07:03 time: 0.4608 data_time: 0.0365 memory: 17006 grad_norm: 4.8994 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2425 loss: 1.2425 2022/10/13 09:39:55 - mmengine - INFO - Epoch(train) [77][620/940] lr: 1.0000e-03 eta: 3:06:53 time: 0.5099 data_time: 0.0337 memory: 17006 grad_norm: 4.9592 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3353 loss: 1.3353 2022/10/13 09:40:05 - mmengine - INFO - Epoch(train) [77][640/940] lr: 1.0000e-03 eta: 3:06:43 time: 0.4816 data_time: 0.0339 memory: 17006 grad_norm: 4.8616 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2835 loss: 1.2835 2022/10/13 09:40:15 - mmengine - INFO - Epoch(train) [77][660/940] lr: 1.0000e-03 eta: 3:06:32 time: 0.5076 data_time: 0.0328 memory: 17006 grad_norm: 4.8579 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1924 loss: 1.1924 2022/10/13 09:40:26 - mmengine - INFO - Epoch(train) [77][680/940] lr: 1.0000e-03 eta: 3:06:22 time: 0.5422 data_time: 0.0316 memory: 17006 grad_norm: 4.8880 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2845 loss: 1.2845 2022/10/13 09:40:35 - mmengine - INFO - Epoch(train) [77][700/940] lr: 1.0000e-03 eta: 3:06:12 time: 0.4813 data_time: 0.0347 memory: 17006 grad_norm: 4.8249 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3556 loss: 1.3556 2022/10/13 09:40:46 - mmengine - INFO - Epoch(train) [77][720/940] lr: 1.0000e-03 eta: 3:06:02 time: 0.5272 data_time: 0.0374 memory: 17006 grad_norm: 4.9032 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2915 loss: 1.2915 2022/10/13 09:40:57 - mmengine - INFO - Epoch(train) [77][740/940] lr: 1.0000e-03 eta: 3:05:52 time: 0.5476 data_time: 0.0299 memory: 17006 grad_norm: 4.8975 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1951 loss: 1.1951 2022/10/13 09:41:07 - mmengine - INFO - Epoch(train) [77][760/940] lr: 1.0000e-03 eta: 3:05:41 time: 0.4950 data_time: 0.0444 memory: 17006 grad_norm: 4.7904 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2543 loss: 1.2543 2022/10/13 09:41:18 - mmengine - INFO - Epoch(train) [77][780/940] lr: 1.0000e-03 eta: 3:05:31 time: 0.5420 data_time: 0.0331 memory: 17006 grad_norm: 5.0517 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2167 loss: 1.2167 2022/10/13 09:41:27 - mmengine - INFO - Epoch(train) [77][800/940] lr: 1.0000e-03 eta: 3:05:21 time: 0.4758 data_time: 0.0383 memory: 17006 grad_norm: 4.9257 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4290 loss: 1.4290 2022/10/13 09:41:37 - mmengine - INFO - Epoch(train) [77][820/940] lr: 1.0000e-03 eta: 3:05:11 time: 0.4797 data_time: 0.0356 memory: 17006 grad_norm: 4.8933 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2691 loss: 1.2691 2022/10/13 09:41:46 - mmengine - INFO - Epoch(train) [77][840/940] lr: 1.0000e-03 eta: 3:05:00 time: 0.4729 data_time: 0.0356 memory: 17006 grad_norm: 4.9445 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2970 loss: 1.2970 2022/10/13 09:41:57 - mmengine - INFO - Epoch(train) [77][860/940] lr: 1.0000e-03 eta: 3:04:50 time: 0.5414 data_time: 0.0312 memory: 17006 grad_norm: 4.8884 top1_acc: 0.9375 top5_acc: 1.0000 loss_cls: 1.3292 loss: 1.3292 2022/10/13 09:42:07 - mmengine - INFO - Epoch(train) [77][880/940] lr: 1.0000e-03 eta: 3:04:40 time: 0.5069 data_time: 0.0364 memory: 17006 grad_norm: 4.7851 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2191 loss: 1.2191 2022/10/13 09:42:18 - mmengine - INFO - Epoch(train) [77][900/940] lr: 1.0000e-03 eta: 3:04:30 time: 0.5321 data_time: 0.0344 memory: 17006 grad_norm: 4.8499 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2244 loss: 1.2244 2022/10/13 09:42:27 - mmengine - INFO - Epoch(train) [77][920/940] lr: 1.0000e-03 eta: 3:04:19 time: 0.4781 data_time: 0.0414 memory: 17006 grad_norm: 4.9091 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3230 loss: 1.3230 2022/10/13 09:42:37 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 09:42:37 - mmengine - INFO - Epoch(train) [77][940/940] lr: 1.0000e-03 eta: 3:04:09 time: 0.4576 data_time: 0.0267 memory: 17006 grad_norm: 5.0798 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.2978 loss: 1.2978 2022/10/13 09:42:49 - mmengine - INFO - Epoch(val) [77][20/78] eta: 0:00:36 time: 0.6318 data_time: 0.5368 memory: 3172 2022/10/13 09:42:58 - mmengine - INFO - Epoch(val) [77][40/78] eta: 0:00:16 time: 0.4347 data_time: 0.3435 memory: 3172 2022/10/13 09:43:09 - mmengine - INFO - Epoch(val) [77][60/78] eta: 0:00:10 time: 0.5793 data_time: 0.4877 memory: 3172 2022/10/13 09:43:19 - mmengine - INFO - Epoch(val) [77][78/78] acc/top1: 0.6712 acc/top5: 0.8682 acc/mean1: 0.6711 2022/10/13 09:43:33 - mmengine - INFO - Epoch(train) [78][20/940] lr: 1.0000e-03 eta: 3:04:00 time: 0.7009 data_time: 0.2771 memory: 17006 grad_norm: 4.8931 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3139 loss: 1.3139 2022/10/13 09:43:42 - mmengine - INFO - Epoch(train) [78][40/940] lr: 1.0000e-03 eta: 3:03:49 time: 0.4744 data_time: 0.0403 memory: 17006 grad_norm: 4.9189 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3095 loss: 1.3095 2022/10/13 09:43:54 - mmengine - INFO - Epoch(train) [78][60/940] lr: 1.0000e-03 eta: 3:03:39 time: 0.5836 data_time: 0.0334 memory: 17006 grad_norm: 4.8970 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4344 loss: 1.4344 2022/10/13 09:44:03 - mmengine - INFO - Epoch(train) [78][80/940] lr: 1.0000e-03 eta: 3:03:29 time: 0.4369 data_time: 0.0575 memory: 17006 grad_norm: 4.8515 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2427 loss: 1.2427 2022/10/13 09:44:14 - mmengine - INFO - Epoch(train) [78][100/940] lr: 1.0000e-03 eta: 3:03:19 time: 0.5351 data_time: 0.1261 memory: 17006 grad_norm: 4.7409 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2577 loss: 1.2577 2022/10/13 09:44:24 - mmengine - INFO - Epoch(train) [78][120/940] lr: 1.0000e-03 eta: 3:03:09 time: 0.5133 data_time: 0.0346 memory: 17006 grad_norm: 5.0188 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2226 loss: 1.2226 2022/10/13 09:44:34 - mmengine - INFO - Epoch(train) [78][140/940] lr: 1.0000e-03 eta: 3:02:58 time: 0.4938 data_time: 0.1435 memory: 17006 grad_norm: 4.8431 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2082 loss: 1.2082 2022/10/13 09:44:44 - mmengine - INFO - Epoch(train) [78][160/940] lr: 1.0000e-03 eta: 3:02:48 time: 0.5071 data_time: 0.1021 memory: 17006 grad_norm: 4.8066 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.2717 loss: 1.2717 2022/10/13 09:44:54 - mmengine - INFO - Epoch(train) [78][180/940] lr: 1.0000e-03 eta: 3:02:38 time: 0.5021 data_time: 0.1347 memory: 17006 grad_norm: 4.8683 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2296 loss: 1.2296 2022/10/13 09:45:04 - mmengine - INFO - Epoch(train) [78][200/940] lr: 1.0000e-03 eta: 3:02:28 time: 0.5170 data_time: 0.1205 memory: 17006 grad_norm: 4.9784 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2731 loss: 1.2731 2022/10/13 09:45:14 - mmengine - INFO - Epoch(train) [78][220/940] lr: 1.0000e-03 eta: 3:02:17 time: 0.4865 data_time: 0.0548 memory: 17006 grad_norm: 4.8677 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2477 loss: 1.2477 2022/10/13 09:45:24 - mmengine - INFO - Epoch(train) [78][240/940] lr: 1.0000e-03 eta: 3:02:07 time: 0.5051 data_time: 0.0321 memory: 17006 grad_norm: 4.7613 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2235 loss: 1.2235 2022/10/13 09:45:34 - mmengine - INFO - Epoch(train) [78][260/940] lr: 1.0000e-03 eta: 3:01:57 time: 0.5113 data_time: 0.0377 memory: 17006 grad_norm: 4.8435 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2627 loss: 1.2627 2022/10/13 09:45:44 - mmengine - INFO - Epoch(train) [78][280/940] lr: 1.0000e-03 eta: 3:01:46 time: 0.4968 data_time: 0.0276 memory: 17006 grad_norm: 4.9887 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.2342 loss: 1.2342 2022/10/13 09:45:56 - mmengine - INFO - Epoch(train) [78][300/940] lr: 1.0000e-03 eta: 3:01:36 time: 0.5663 data_time: 0.0360 memory: 17006 grad_norm: 4.9353 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.3986 loss: 1.3986 2022/10/13 09:46:05 - mmengine - INFO - Epoch(train) [78][320/940] lr: 1.0000e-03 eta: 3:01:26 time: 0.4595 data_time: 0.0316 memory: 17006 grad_norm: 4.7993 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3322 loss: 1.3322 2022/10/13 09:46:16 - mmengine - INFO - Epoch(train) [78][340/940] lr: 1.0000e-03 eta: 3:01:16 time: 0.5528 data_time: 0.0342 memory: 17006 grad_norm: 4.9337 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3106 loss: 1.3106 2022/10/13 09:46:25 - mmengine - INFO - Epoch(train) [78][360/940] lr: 1.0000e-03 eta: 3:01:05 time: 0.4351 data_time: 0.0279 memory: 17006 grad_norm: 4.8915 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3468 loss: 1.3468 2022/10/13 09:46:36 - mmengine - INFO - Epoch(train) [78][380/940] lr: 1.0000e-03 eta: 3:00:55 time: 0.5825 data_time: 0.0370 memory: 17006 grad_norm: 4.9329 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2665 loss: 1.2665 2022/10/13 09:46:45 - mmengine - INFO - Epoch(train) [78][400/940] lr: 1.0000e-03 eta: 3:00:45 time: 0.4420 data_time: 0.0362 memory: 17006 grad_norm: 4.9697 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3276 loss: 1.3276 2022/10/13 09:46:56 - mmengine - INFO - Epoch(train) [78][420/940] lr: 1.0000e-03 eta: 3:00:35 time: 0.5328 data_time: 0.0324 memory: 17006 grad_norm: 4.9129 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.4366 loss: 1.4366 2022/10/13 09:47:05 - mmengine - INFO - Epoch(train) [78][440/940] lr: 1.0000e-03 eta: 3:00:24 time: 0.4737 data_time: 0.0363 memory: 17006 grad_norm: 4.8863 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1889 loss: 1.1889 2022/10/13 09:47:17 - mmengine - INFO - Epoch(train) [78][460/940] lr: 1.0000e-03 eta: 3:00:14 time: 0.5768 data_time: 0.0369 memory: 17006 grad_norm: 5.0203 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4544 loss: 1.4544 2022/10/13 09:47:26 - mmengine - INFO - Epoch(train) [78][480/940] lr: 1.0000e-03 eta: 3:00:04 time: 0.4770 data_time: 0.0316 memory: 17006 grad_norm: 4.9460 top1_acc: 0.4688 top5_acc: 0.8750 loss_cls: 1.3191 loss: 1.3191 2022/10/13 09:47:37 - mmengine - INFO - Epoch(train) [78][500/940] lr: 1.0000e-03 eta: 2:59:54 time: 0.5201 data_time: 0.0321 memory: 17006 grad_norm: 4.9573 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3149 loss: 1.3149 2022/10/13 09:47:46 - mmengine - INFO - Epoch(train) [78][520/940] lr: 1.0000e-03 eta: 2:59:43 time: 0.4772 data_time: 0.0319 memory: 17006 grad_norm: 4.9614 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3004 loss: 1.3004 2022/10/13 09:47:57 - mmengine - INFO - Epoch(train) [78][540/940] lr: 1.0000e-03 eta: 2:59:34 time: 0.5574 data_time: 0.0427 memory: 17006 grad_norm: 4.9109 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.2900 loss: 1.2900 2022/10/13 09:48:08 - mmengine - INFO - Epoch(train) [78][560/940] lr: 1.0000e-03 eta: 2:59:23 time: 0.5133 data_time: 0.0303 memory: 17006 grad_norm: 4.8938 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3232 loss: 1.3232 2022/10/13 09:48:18 - mmengine - INFO - Epoch(train) [78][580/940] lr: 1.0000e-03 eta: 2:59:13 time: 0.5405 data_time: 0.0327 memory: 17006 grad_norm: 5.0462 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.4366 loss: 1.4366 2022/10/13 09:48:28 - mmengine - INFO - Epoch(train) [78][600/940] lr: 1.0000e-03 eta: 2:59:03 time: 0.4696 data_time: 0.0260 memory: 17006 grad_norm: 4.8685 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3218 loss: 1.3218 2022/10/13 09:48:38 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 09:48:38 - mmengine - INFO - Epoch(train) [78][620/940] lr: 1.0000e-03 eta: 2:58:53 time: 0.5073 data_time: 0.0320 memory: 17006 grad_norm: 4.9554 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3218 loss: 1.3218 2022/10/13 09:48:47 - mmengine - INFO - Epoch(train) [78][640/940] lr: 1.0000e-03 eta: 2:58:42 time: 0.4588 data_time: 0.0295 memory: 17006 grad_norm: 4.8469 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2887 loss: 1.2887 2022/10/13 09:48:57 - mmengine - INFO - Epoch(train) [78][660/940] lr: 1.0000e-03 eta: 2:58:32 time: 0.4967 data_time: 0.0320 memory: 17006 grad_norm: 4.9410 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3205 loss: 1.3205 2022/10/13 09:49:06 - mmengine - INFO - Epoch(train) [78][680/940] lr: 1.0000e-03 eta: 2:58:21 time: 0.4566 data_time: 0.0347 memory: 17006 grad_norm: 4.8611 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3514 loss: 1.3514 2022/10/13 09:49:17 - mmengine - INFO - Epoch(train) [78][700/940] lr: 1.0000e-03 eta: 2:58:11 time: 0.5357 data_time: 0.0327 memory: 17006 grad_norm: 4.9422 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2301 loss: 1.2301 2022/10/13 09:49:27 - mmengine - INFO - Epoch(train) [78][720/940] lr: 1.0000e-03 eta: 2:58:01 time: 0.4973 data_time: 0.0325 memory: 17006 grad_norm: 5.0678 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3780 loss: 1.3780 2022/10/13 09:49:37 - mmengine - INFO - Epoch(train) [78][740/940] lr: 1.0000e-03 eta: 2:57:51 time: 0.5001 data_time: 0.0363 memory: 17006 grad_norm: 4.8568 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2824 loss: 1.2824 2022/10/13 09:49:47 - mmengine - INFO - Epoch(train) [78][760/940] lr: 1.0000e-03 eta: 2:57:40 time: 0.4906 data_time: 0.0297 memory: 17006 grad_norm: 5.0462 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2043 loss: 1.2043 2022/10/13 09:49:58 - mmengine - INFO - Epoch(train) [78][780/940] lr: 1.0000e-03 eta: 2:57:30 time: 0.5562 data_time: 0.0349 memory: 17006 grad_norm: 4.9588 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3609 loss: 1.3609 2022/10/13 09:50:08 - mmengine - INFO - Epoch(train) [78][800/940] lr: 1.0000e-03 eta: 2:57:20 time: 0.5039 data_time: 0.0321 memory: 17006 grad_norm: 5.0731 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3152 loss: 1.3152 2022/10/13 09:50:18 - mmengine - INFO - Epoch(train) [78][820/940] lr: 1.0000e-03 eta: 2:57:10 time: 0.5190 data_time: 0.0301 memory: 17006 grad_norm: 4.8966 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3471 loss: 1.3471 2022/10/13 09:50:28 - mmengine - INFO - Epoch(train) [78][840/940] lr: 1.0000e-03 eta: 2:56:59 time: 0.4747 data_time: 0.0326 memory: 17006 grad_norm: 4.9343 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4087 loss: 1.4087 2022/10/13 09:50:38 - mmengine - INFO - Epoch(train) [78][860/940] lr: 1.0000e-03 eta: 2:56:49 time: 0.5083 data_time: 0.0286 memory: 17006 grad_norm: 4.8907 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2440 loss: 1.2440 2022/10/13 09:50:48 - mmengine - INFO - Epoch(train) [78][880/940] lr: 1.0000e-03 eta: 2:56:39 time: 0.4962 data_time: 0.0356 memory: 17006 grad_norm: 4.8735 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3332 loss: 1.3332 2022/10/13 09:51:00 - mmengine - INFO - Epoch(train) [78][900/940] lr: 1.0000e-03 eta: 2:56:29 time: 0.5830 data_time: 0.0352 memory: 17006 grad_norm: 4.8774 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2775 loss: 1.2775 2022/10/13 09:51:09 - mmengine - INFO - Epoch(train) [78][920/940] lr: 1.0000e-03 eta: 2:56:18 time: 0.4566 data_time: 0.0322 memory: 17006 grad_norm: 4.9486 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2669 loss: 1.2669 2022/10/13 09:51:19 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 09:51:19 - mmengine - INFO - Epoch(train) [78][940/940] lr: 1.0000e-03 eta: 2:56:08 time: 0.5159 data_time: 0.0254 memory: 17006 grad_norm: 5.2032 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.3340 loss: 1.3340 2022/10/13 09:51:19 - mmengine - INFO - Saving checkpoint at 78 epochs 2022/10/13 09:51:32 - mmengine - INFO - Epoch(val) [78][20/78] eta: 0:00:36 time: 0.6290 data_time: 0.5394 memory: 3172 2022/10/13 09:51:41 - mmengine - INFO - Epoch(val) [78][40/78] eta: 0:00:16 time: 0.4369 data_time: 0.3460 memory: 3172 2022/10/13 09:51:52 - mmengine - INFO - Epoch(val) [78][60/78] eta: 0:00:10 time: 0.5620 data_time: 0.4703 memory: 3172 2022/10/13 09:52:02 - mmengine - INFO - Epoch(val) [78][78/78] acc/top1: 0.6743 acc/top5: 0.8683 acc/mean1: 0.6742 2022/10/13 09:52:16 - mmengine - INFO - Epoch(train) [79][20/940] lr: 1.0000e-03 eta: 2:55:59 time: 0.7088 data_time: 0.3774 memory: 17006 grad_norm: 4.9929 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2919 loss: 1.2919 2022/10/13 09:52:26 - mmengine - INFO - Epoch(train) [79][40/940] lr: 1.0000e-03 eta: 2:55:49 time: 0.4874 data_time: 0.1761 memory: 17006 grad_norm: 4.8183 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3554 loss: 1.3554 2022/10/13 09:52:36 - mmengine - INFO - Epoch(train) [79][60/940] lr: 1.0000e-03 eta: 2:55:39 time: 0.5281 data_time: 0.2025 memory: 17006 grad_norm: 4.9013 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3266 loss: 1.3266 2022/10/13 09:52:46 - mmengine - INFO - Epoch(train) [79][80/940] lr: 1.0000e-03 eta: 2:55:28 time: 0.4652 data_time: 0.1513 memory: 17006 grad_norm: 4.8721 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2644 loss: 1.2644 2022/10/13 09:52:56 - mmengine - INFO - Epoch(train) [79][100/940] lr: 1.0000e-03 eta: 2:55:18 time: 0.5356 data_time: 0.2066 memory: 17006 grad_norm: 4.8691 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1918 loss: 1.1918 2022/10/13 09:53:06 - mmengine - INFO - Epoch(train) [79][120/940] lr: 1.0000e-03 eta: 2:55:08 time: 0.4904 data_time: 0.1511 memory: 17006 grad_norm: 4.8517 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2285 loss: 1.2285 2022/10/13 09:53:17 - mmengine - INFO - Epoch(train) [79][140/940] lr: 1.0000e-03 eta: 2:54:58 time: 0.5448 data_time: 0.2404 memory: 17006 grad_norm: 4.8450 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2586 loss: 1.2586 2022/10/13 09:53:26 - mmengine - INFO - Epoch(train) [79][160/940] lr: 1.0000e-03 eta: 2:54:47 time: 0.4659 data_time: 0.1108 memory: 17006 grad_norm: 4.8816 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2211 loss: 1.2211 2022/10/13 09:53:37 - mmengine - INFO - Epoch(train) [79][180/940] lr: 1.0000e-03 eta: 2:54:37 time: 0.5525 data_time: 0.1230 memory: 17006 grad_norm: 4.9644 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3341 loss: 1.3341 2022/10/13 09:53:47 - mmengine - INFO - Epoch(train) [79][200/940] lr: 1.0000e-03 eta: 2:54:27 time: 0.4645 data_time: 0.0253 memory: 17006 grad_norm: 4.8368 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2584 loss: 1.2584 2022/10/13 09:53:58 - mmengine - INFO - Epoch(train) [79][220/940] lr: 1.0000e-03 eta: 2:54:17 time: 0.5572 data_time: 0.0338 memory: 17006 grad_norm: 5.0188 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2826 loss: 1.2826 2022/10/13 09:54:06 - mmengine - INFO - Epoch(train) [79][240/940] lr: 1.0000e-03 eta: 2:54:06 time: 0.4298 data_time: 0.0349 memory: 17006 grad_norm: 4.9126 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3421 loss: 1.3421 2022/10/13 09:54:17 - mmengine - INFO - Epoch(train) [79][260/940] lr: 1.0000e-03 eta: 2:53:56 time: 0.5547 data_time: 0.0312 memory: 17006 grad_norm: 4.8749 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3424 loss: 1.3424 2022/10/13 09:54:27 - mmengine - INFO - Epoch(train) [79][280/940] lr: 1.0000e-03 eta: 2:53:46 time: 0.4728 data_time: 0.0341 memory: 17006 grad_norm: 4.9543 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4578 loss: 1.4578 2022/10/13 09:54:37 - mmengine - INFO - Epoch(train) [79][300/940] lr: 1.0000e-03 eta: 2:53:36 time: 0.5181 data_time: 0.0317 memory: 17006 grad_norm: 4.8835 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3055 loss: 1.3055 2022/10/13 09:54:47 - mmengine - INFO - Epoch(train) [79][320/940] lr: 1.0000e-03 eta: 2:53:25 time: 0.5034 data_time: 0.0349 memory: 17006 grad_norm: 5.0431 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3232 loss: 1.3232 2022/10/13 09:54:57 - mmengine - INFO - Epoch(train) [79][340/940] lr: 1.0000e-03 eta: 2:53:15 time: 0.4899 data_time: 0.0349 memory: 17006 grad_norm: 4.9181 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4047 loss: 1.4047 2022/10/13 09:55:08 - mmengine - INFO - Epoch(train) [79][360/940] lr: 1.0000e-03 eta: 2:53:05 time: 0.5514 data_time: 0.0316 memory: 17006 grad_norm: 5.0229 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3913 loss: 1.3913 2022/10/13 09:55:18 - mmengine - INFO - Epoch(train) [79][380/940] lr: 1.0000e-03 eta: 2:52:55 time: 0.4748 data_time: 0.0328 memory: 17006 grad_norm: 5.0275 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3119 loss: 1.3119 2022/10/13 09:55:29 - mmengine - INFO - Epoch(train) [79][400/940] lr: 1.0000e-03 eta: 2:52:44 time: 0.5410 data_time: 0.0339 memory: 17006 grad_norm: 4.8457 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2859 loss: 1.2859 2022/10/13 09:55:38 - mmengine - INFO - Epoch(train) [79][420/940] lr: 1.0000e-03 eta: 2:52:34 time: 0.4615 data_time: 0.0299 memory: 17006 grad_norm: 4.9052 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2001 loss: 1.2001 2022/10/13 09:55:49 - mmengine - INFO - Epoch(train) [79][440/940] lr: 1.0000e-03 eta: 2:52:24 time: 0.5607 data_time: 0.0375 memory: 17006 grad_norm: 4.8568 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1618 loss: 1.1618 2022/10/13 09:55:58 - mmengine - INFO - Epoch(train) [79][460/940] lr: 1.0000e-03 eta: 2:52:14 time: 0.4661 data_time: 0.0277 memory: 17006 grad_norm: 4.9066 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1999 loss: 1.1999 2022/10/13 09:56:09 - mmengine - INFO - Epoch(train) [79][480/940] lr: 1.0000e-03 eta: 2:52:03 time: 0.5334 data_time: 0.0425 memory: 17006 grad_norm: 4.9697 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1927 loss: 1.1927 2022/10/13 09:56:19 - mmengine - INFO - Epoch(train) [79][500/940] lr: 1.0000e-03 eta: 2:51:53 time: 0.4889 data_time: 0.0392 memory: 17006 grad_norm: 4.7772 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3421 loss: 1.3421 2022/10/13 09:56:29 - mmengine - INFO - Epoch(train) [79][520/940] lr: 1.0000e-03 eta: 2:51:43 time: 0.5318 data_time: 0.0264 memory: 17006 grad_norm: 4.9277 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3975 loss: 1.3975 2022/10/13 09:56:39 - mmengine - INFO - Epoch(train) [79][540/940] lr: 1.0000e-03 eta: 2:51:33 time: 0.4729 data_time: 0.0348 memory: 17006 grad_norm: 4.9783 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2718 loss: 1.2718 2022/10/13 09:56:49 - mmengine - INFO - Epoch(train) [79][560/940] lr: 1.0000e-03 eta: 2:51:22 time: 0.5054 data_time: 0.0393 memory: 17006 grad_norm: 4.9426 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3151 loss: 1.3151 2022/10/13 09:56:59 - mmengine - INFO - Epoch(train) [79][580/940] lr: 1.0000e-03 eta: 2:51:12 time: 0.4959 data_time: 0.0304 memory: 17006 grad_norm: 4.8792 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2593 loss: 1.2593 2022/10/13 09:57:10 - mmengine - INFO - Epoch(train) [79][600/940] lr: 1.0000e-03 eta: 2:51:02 time: 0.5424 data_time: 0.0367 memory: 17006 grad_norm: 4.9235 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.1993 loss: 1.1993 2022/10/13 09:57:20 - mmengine - INFO - Epoch(train) [79][620/940] lr: 1.0000e-03 eta: 2:50:52 time: 0.4914 data_time: 0.0302 memory: 17006 grad_norm: 4.9633 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2389 loss: 1.2389 2022/10/13 09:57:30 - mmengine - INFO - Epoch(train) [79][640/940] lr: 1.0000e-03 eta: 2:50:41 time: 0.5205 data_time: 0.0393 memory: 17006 grad_norm: 4.9937 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3284 loss: 1.3284 2022/10/13 09:57:39 - mmengine - INFO - Epoch(train) [79][660/940] lr: 1.0000e-03 eta: 2:50:31 time: 0.4570 data_time: 0.0312 memory: 17006 grad_norm: 4.9128 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2872 loss: 1.2872 2022/10/13 09:57:49 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 09:57:49 - mmengine - INFO - Epoch(train) [79][680/940] lr: 1.0000e-03 eta: 2:50:21 time: 0.4936 data_time: 0.0342 memory: 17006 grad_norm: 4.8975 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3598 loss: 1.3598 2022/10/13 09:57:59 - mmengine - INFO - Epoch(train) [79][700/940] lr: 1.0000e-03 eta: 2:50:10 time: 0.5090 data_time: 0.0278 memory: 17006 grad_norm: 4.9358 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3433 loss: 1.3433 2022/10/13 09:58:11 - mmengine - INFO - Epoch(train) [79][720/940] lr: 1.0000e-03 eta: 2:50:01 time: 0.5815 data_time: 0.0442 memory: 17006 grad_norm: 4.9971 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3202 loss: 1.3202 2022/10/13 09:58:19 - mmengine - INFO - Epoch(train) [79][740/940] lr: 1.0000e-03 eta: 2:49:50 time: 0.4304 data_time: 0.0280 memory: 17006 grad_norm: 4.8052 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3028 loss: 1.3028 2022/10/13 09:58:31 - mmengine - INFO - Epoch(train) [79][760/940] lr: 1.0000e-03 eta: 2:49:40 time: 0.5640 data_time: 0.0372 memory: 17006 grad_norm: 5.0404 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3150 loss: 1.3150 2022/10/13 09:58:40 - mmengine - INFO - Epoch(train) [79][780/940] lr: 1.0000e-03 eta: 2:49:29 time: 0.4533 data_time: 0.0285 memory: 17006 grad_norm: 4.9680 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3987 loss: 1.3987 2022/10/13 09:58:50 - mmengine - INFO - Epoch(train) [79][800/940] lr: 1.0000e-03 eta: 2:49:19 time: 0.5329 data_time: 0.0345 memory: 17006 grad_norm: 4.9367 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2525 loss: 1.2525 2022/10/13 09:59:01 - mmengine - INFO - Epoch(train) [79][820/940] lr: 1.0000e-03 eta: 2:49:09 time: 0.5198 data_time: 0.0320 memory: 17006 grad_norm: 5.1066 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4233 loss: 1.4233 2022/10/13 09:59:11 - mmengine - INFO - Epoch(train) [79][840/940] lr: 1.0000e-03 eta: 2:48:59 time: 0.5094 data_time: 0.0310 memory: 17006 grad_norm: 4.8818 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2325 loss: 1.2325 2022/10/13 09:59:21 - mmengine - INFO - Epoch(train) [79][860/940] lr: 1.0000e-03 eta: 2:48:49 time: 0.4967 data_time: 0.0313 memory: 17006 grad_norm: 4.9922 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2911 loss: 1.2911 2022/10/13 09:59:31 - mmengine - INFO - Epoch(train) [79][880/940] lr: 1.0000e-03 eta: 2:48:38 time: 0.5050 data_time: 0.0397 memory: 17006 grad_norm: 5.0469 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3331 loss: 1.3331 2022/10/13 09:59:40 - mmengine - INFO - Epoch(train) [79][900/940] lr: 1.0000e-03 eta: 2:48:28 time: 0.4617 data_time: 0.0368 memory: 17006 grad_norm: 4.9393 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2204 loss: 1.2204 2022/10/13 09:59:51 - mmengine - INFO - Epoch(train) [79][920/940] lr: 1.0000e-03 eta: 2:48:18 time: 0.5455 data_time: 0.0375 memory: 17006 grad_norm: 5.0661 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4063 loss: 1.4063 2022/10/13 10:00:00 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 10:00:00 - mmengine - INFO - Epoch(train) [79][940/940] lr: 1.0000e-03 eta: 2:48:07 time: 0.4359 data_time: 0.0293 memory: 17006 grad_norm: 5.2313 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.3512 loss: 1.3512 2022/10/13 10:00:12 - mmengine - INFO - Epoch(val) [79][20/78] eta: 0:00:35 time: 0.6204 data_time: 0.5249 memory: 3172 2022/10/13 10:00:21 - mmengine - INFO - Epoch(val) [79][40/78] eta: 0:00:16 time: 0.4394 data_time: 0.3438 memory: 3172 2022/10/13 10:00:32 - mmengine - INFO - Epoch(val) [79][60/78] eta: 0:00:10 time: 0.5632 data_time: 0.4719 memory: 3172 2022/10/13 10:00:42 - mmengine - INFO - Epoch(val) [79][78/78] acc/top1: 0.6711 acc/top5: 0.8691 acc/mean1: 0.6710 2022/10/13 10:00:56 - mmengine - INFO - Epoch(train) [80][20/940] lr: 1.0000e-03 eta: 2:47:58 time: 0.6978 data_time: 0.3484 memory: 17006 grad_norm: 4.9307 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2984 loss: 1.2984 2022/10/13 10:01:06 - mmengine - INFO - Epoch(train) [80][40/940] lr: 1.0000e-03 eta: 2:47:48 time: 0.4813 data_time: 0.1600 memory: 17006 grad_norm: 4.8783 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3374 loss: 1.3374 2022/10/13 10:01:17 - mmengine - INFO - Epoch(train) [80][60/940] lr: 1.0000e-03 eta: 2:47:38 time: 0.5549 data_time: 0.1536 memory: 17006 grad_norm: 4.8312 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3333 loss: 1.3333 2022/10/13 10:01:26 - mmengine - INFO - Epoch(train) [80][80/940] lr: 1.0000e-03 eta: 2:47:27 time: 0.4672 data_time: 0.0817 memory: 17006 grad_norm: 4.9441 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3135 loss: 1.3135 2022/10/13 10:01:37 - mmengine - INFO - Epoch(train) [80][100/940] lr: 1.0000e-03 eta: 2:47:17 time: 0.5469 data_time: 0.0772 memory: 17006 grad_norm: 4.8835 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1816 loss: 1.1816 2022/10/13 10:01:47 - mmengine - INFO - Epoch(train) [80][120/940] lr: 1.0000e-03 eta: 2:47:07 time: 0.4696 data_time: 0.0267 memory: 17006 grad_norm: 4.8107 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2772 loss: 1.2772 2022/10/13 10:01:57 - mmengine - INFO - Epoch(train) [80][140/940] lr: 1.0000e-03 eta: 2:46:57 time: 0.5294 data_time: 0.0342 memory: 17006 grad_norm: 4.8567 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3323 loss: 1.3323 2022/10/13 10:02:07 - mmengine - INFO - Epoch(train) [80][160/940] lr: 1.0000e-03 eta: 2:46:46 time: 0.4842 data_time: 0.0301 memory: 17006 grad_norm: 4.9125 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2953 loss: 1.2953 2022/10/13 10:02:19 - mmengine - INFO - Epoch(train) [80][180/940] lr: 1.0000e-03 eta: 2:46:36 time: 0.5844 data_time: 0.0255 memory: 17006 grad_norm: 4.9676 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3585 loss: 1.3585 2022/10/13 10:02:27 - mmengine - INFO - Epoch(train) [80][200/940] lr: 1.0000e-03 eta: 2:46:26 time: 0.4184 data_time: 0.0305 memory: 17006 grad_norm: 4.9071 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3621 loss: 1.3621 2022/10/13 10:02:38 - mmengine - INFO - Epoch(train) [80][220/940] lr: 1.0000e-03 eta: 2:46:16 time: 0.5568 data_time: 0.0341 memory: 17006 grad_norm: 4.8779 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.2650 loss: 1.2650 2022/10/13 10:02:48 - mmengine - INFO - Epoch(train) [80][240/940] lr: 1.0000e-03 eta: 2:46:05 time: 0.4744 data_time: 0.0328 memory: 17006 grad_norm: 4.8968 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2895 loss: 1.2895 2022/10/13 10:02:58 - mmengine - INFO - Epoch(train) [80][260/940] lr: 1.0000e-03 eta: 2:45:55 time: 0.5242 data_time: 0.0317 memory: 17006 grad_norm: 4.9540 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3211 loss: 1.3211 2022/10/13 10:03:08 - mmengine - INFO - Epoch(train) [80][280/940] lr: 1.0000e-03 eta: 2:45:45 time: 0.4826 data_time: 0.0346 memory: 17006 grad_norm: 4.8960 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3206 loss: 1.3206 2022/10/13 10:03:18 - mmengine - INFO - Epoch(train) [80][300/940] lr: 1.0000e-03 eta: 2:45:35 time: 0.5343 data_time: 0.0323 memory: 17006 grad_norm: 4.9608 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1355 loss: 1.1355 2022/10/13 10:03:28 - mmengine - INFO - Epoch(train) [80][320/940] lr: 1.0000e-03 eta: 2:45:24 time: 0.4683 data_time: 0.0324 memory: 17006 grad_norm: 4.9255 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2580 loss: 1.2580 2022/10/13 10:03:38 - mmengine - INFO - Epoch(train) [80][340/940] lr: 1.0000e-03 eta: 2:45:14 time: 0.5214 data_time: 0.0307 memory: 17006 grad_norm: 4.9221 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2994 loss: 1.2994 2022/10/13 10:03:48 - mmengine - INFO - Epoch(train) [80][360/940] lr: 1.0000e-03 eta: 2:45:04 time: 0.4852 data_time: 0.0360 memory: 17006 grad_norm: 4.9508 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3193 loss: 1.3193 2022/10/13 10:03:59 - mmengine - INFO - Epoch(train) [80][380/940] lr: 1.0000e-03 eta: 2:44:54 time: 0.5592 data_time: 0.0350 memory: 17006 grad_norm: 4.9459 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3262 loss: 1.3262 2022/10/13 10:04:09 - mmengine - INFO - Epoch(train) [80][400/940] lr: 1.0000e-03 eta: 2:44:43 time: 0.5015 data_time: 0.0396 memory: 17006 grad_norm: 5.0472 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4766 loss: 1.4766 2022/10/13 10:04:21 - mmengine - INFO - Epoch(train) [80][420/940] lr: 1.0000e-03 eta: 2:44:34 time: 0.5718 data_time: 0.0275 memory: 17006 grad_norm: 4.8969 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.3347 loss: 1.3347 2022/10/13 10:04:30 - mmengine - INFO - Epoch(train) [80][440/940] lr: 1.0000e-03 eta: 2:44:23 time: 0.4619 data_time: 0.0341 memory: 17006 grad_norm: 4.9515 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.3366 loss: 1.3366 2022/10/13 10:04:42 - mmengine - INFO - Epoch(train) [80][460/940] lr: 1.0000e-03 eta: 2:44:13 time: 0.5900 data_time: 0.0308 memory: 17006 grad_norm: 4.9838 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3926 loss: 1.3926 2022/10/13 10:04:51 - mmengine - INFO - Epoch(train) [80][480/940] lr: 1.0000e-03 eta: 2:44:03 time: 0.4538 data_time: 0.0372 memory: 17006 grad_norm: 5.0347 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2627 loss: 1.2627 2022/10/13 10:05:01 - mmengine - INFO - Epoch(train) [80][500/940] lr: 1.0000e-03 eta: 2:43:53 time: 0.5204 data_time: 0.0326 memory: 17006 grad_norm: 4.9063 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2491 loss: 1.2491 2022/10/13 10:05:11 - mmengine - INFO - Epoch(train) [80][520/940] lr: 1.0000e-03 eta: 2:43:42 time: 0.4761 data_time: 0.0350 memory: 17006 grad_norm: 4.8318 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3330 loss: 1.3330 2022/10/13 10:05:22 - mmengine - INFO - Epoch(train) [80][540/940] lr: 1.0000e-03 eta: 2:43:32 time: 0.5647 data_time: 0.0314 memory: 17006 grad_norm: 5.0178 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.2568 loss: 1.2568 2022/10/13 10:05:32 - mmengine - INFO - Epoch(train) [80][560/940] lr: 1.0000e-03 eta: 2:43:22 time: 0.4877 data_time: 0.0342 memory: 17006 grad_norm: 4.9735 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4214 loss: 1.4214 2022/10/13 10:05:42 - mmengine - INFO - Epoch(train) [80][580/940] lr: 1.0000e-03 eta: 2:43:12 time: 0.5231 data_time: 0.0290 memory: 17006 grad_norm: 4.9971 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3327 loss: 1.3327 2022/10/13 10:05:51 - mmengine - INFO - Epoch(train) [80][600/940] lr: 1.0000e-03 eta: 2:43:01 time: 0.4576 data_time: 0.0322 memory: 17006 grad_norm: 4.8772 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3190 loss: 1.3190 2022/10/13 10:06:01 - mmengine - INFO - Epoch(train) [80][620/940] lr: 1.0000e-03 eta: 2:42:51 time: 0.4971 data_time: 0.0263 memory: 17006 grad_norm: 5.0198 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3808 loss: 1.3808 2022/10/13 10:06:10 - mmengine - INFO - Epoch(train) [80][640/940] lr: 1.0000e-03 eta: 2:42:40 time: 0.4592 data_time: 0.0374 memory: 17006 grad_norm: 4.8982 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2954 loss: 1.2954 2022/10/13 10:06:21 - mmengine - INFO - Epoch(train) [80][660/940] lr: 1.0000e-03 eta: 2:42:30 time: 0.5198 data_time: 0.0344 memory: 17006 grad_norm: 5.0028 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3352 loss: 1.3352 2022/10/13 10:06:31 - mmengine - INFO - Epoch(train) [80][680/940] lr: 1.0000e-03 eta: 2:42:20 time: 0.4867 data_time: 0.0357 memory: 17006 grad_norm: 4.9984 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3978 loss: 1.3978 2022/10/13 10:06:42 - mmengine - INFO - Epoch(train) [80][700/940] lr: 1.0000e-03 eta: 2:42:10 time: 0.5750 data_time: 0.0303 memory: 17006 grad_norm: 4.8205 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.1615 loss: 1.1615 2022/10/13 10:06:52 - mmengine - INFO - Epoch(train) [80][720/940] lr: 1.0000e-03 eta: 2:42:00 time: 0.4777 data_time: 0.0312 memory: 17006 grad_norm: 5.0654 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1759 loss: 1.1759 2022/10/13 10:07:03 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 10:07:03 - mmengine - INFO - Epoch(train) [80][740/940] lr: 1.0000e-03 eta: 2:41:50 time: 0.5685 data_time: 0.0290 memory: 17006 grad_norm: 4.9194 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3680 loss: 1.3680 2022/10/13 10:07:13 - mmengine - INFO - Epoch(train) [80][760/940] lr: 1.0000e-03 eta: 2:41:39 time: 0.4900 data_time: 0.0319 memory: 17006 grad_norm: 4.7845 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2462 loss: 1.2462 2022/10/13 10:07:24 - mmengine - INFO - Epoch(train) [80][780/940] lr: 1.0000e-03 eta: 2:41:29 time: 0.5616 data_time: 0.0296 memory: 17006 grad_norm: 4.9850 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2826 loss: 1.2826 2022/10/13 10:07:33 - mmengine - INFO - Epoch(train) [80][800/940] lr: 1.0000e-03 eta: 2:41:19 time: 0.4595 data_time: 0.0355 memory: 17006 grad_norm: 4.9531 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3035 loss: 1.3035 2022/10/13 10:07:44 - mmengine - INFO - Epoch(train) [80][820/940] lr: 1.0000e-03 eta: 2:41:09 time: 0.5172 data_time: 0.0361 memory: 17006 grad_norm: 4.9776 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3043 loss: 1.3043 2022/10/13 10:07:53 - mmengine - INFO - Epoch(train) [80][840/940] lr: 1.0000e-03 eta: 2:40:58 time: 0.4704 data_time: 0.0318 memory: 17006 grad_norm: 4.8963 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3254 loss: 1.3254 2022/10/13 10:08:04 - mmengine - INFO - Epoch(train) [80][860/940] lr: 1.0000e-03 eta: 2:40:48 time: 0.5461 data_time: 0.0364 memory: 17006 grad_norm: 4.9726 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3091 loss: 1.3091 2022/10/13 10:08:13 - mmengine - INFO - Epoch(train) [80][880/940] lr: 1.0000e-03 eta: 2:40:38 time: 0.4554 data_time: 0.0368 memory: 17006 grad_norm: 4.9527 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3182 loss: 1.3182 2022/10/13 10:08:24 - mmengine - INFO - Epoch(train) [80][900/940] lr: 1.0000e-03 eta: 2:40:28 time: 0.5558 data_time: 0.0318 memory: 17006 grad_norm: 5.0356 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3323 loss: 1.3323 2022/10/13 10:08:33 - mmengine - INFO - Epoch(train) [80][920/940] lr: 1.0000e-03 eta: 2:40:17 time: 0.4585 data_time: 0.0308 memory: 17006 grad_norm: 4.9889 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2215 loss: 1.2215 2022/10/13 10:08:43 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 10:08:43 - mmengine - INFO - Epoch(train) [80][940/940] lr: 1.0000e-03 eta: 2:40:07 time: 0.4703 data_time: 0.0288 memory: 17006 grad_norm: 5.2148 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.3316 loss: 1.3316 2022/10/13 10:08:55 - mmengine - INFO - Epoch(val) [80][20/78] eta: 0:00:35 time: 0.6174 data_time: 0.5250 memory: 3172 2022/10/13 10:09:04 - mmengine - INFO - Epoch(val) [80][40/78] eta: 0:00:16 time: 0.4363 data_time: 0.3451 memory: 3172 2022/10/13 10:09:15 - mmengine - INFO - Epoch(val) [80][60/78] eta: 0:00:10 time: 0.5739 data_time: 0.4814 memory: 3172 2022/10/13 10:09:25 - mmengine - INFO - Epoch(val) [80][78/78] acc/top1: 0.6719 acc/top5: 0.8686 acc/mean1: 0.6718 2022/10/13 10:09:40 - mmengine - INFO - Epoch(train) [81][20/940] lr: 1.0000e-04 eta: 2:39:58 time: 0.7247 data_time: 0.2094 memory: 17006 grad_norm: 4.9808 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3218 loss: 1.3218 2022/10/13 10:09:50 - mmengine - INFO - Epoch(train) [81][40/940] lr: 1.0000e-04 eta: 2:39:47 time: 0.4982 data_time: 0.0457 memory: 17006 grad_norm: 4.9664 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3864 loss: 1.3864 2022/10/13 10:10:00 - mmengine - INFO - Epoch(train) [81][60/940] lr: 1.0000e-04 eta: 2:39:37 time: 0.5369 data_time: 0.0359 memory: 17006 grad_norm: 4.9987 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3755 loss: 1.3755 2022/10/13 10:10:10 - mmengine - INFO - Epoch(train) [81][80/940] lr: 1.0000e-04 eta: 2:39:27 time: 0.4691 data_time: 0.0272 memory: 17006 grad_norm: 4.9262 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3123 loss: 1.3123 2022/10/13 10:10:21 - mmengine - INFO - Epoch(train) [81][100/940] lr: 1.0000e-04 eta: 2:39:17 time: 0.5557 data_time: 0.0321 memory: 17006 grad_norm: 4.9370 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4454 loss: 1.4454 2022/10/13 10:10:30 - mmengine - INFO - Epoch(train) [81][120/940] lr: 1.0000e-04 eta: 2:39:07 time: 0.4751 data_time: 0.0331 memory: 17006 grad_norm: 4.8345 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2950 loss: 1.2950 2022/10/13 10:10:40 - mmengine - INFO - Epoch(train) [81][140/940] lr: 1.0000e-04 eta: 2:38:56 time: 0.4945 data_time: 0.0308 memory: 17006 grad_norm: 4.9789 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3410 loss: 1.3410 2022/10/13 10:10:50 - mmengine - INFO - Epoch(train) [81][160/940] lr: 1.0000e-04 eta: 2:38:46 time: 0.5039 data_time: 0.0286 memory: 17006 grad_norm: 4.9422 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2816 loss: 1.2816 2022/10/13 10:11:01 - mmengine - INFO - Epoch(train) [81][180/940] lr: 1.0000e-04 eta: 2:38:36 time: 0.5132 data_time: 0.0309 memory: 17006 grad_norm: 4.8437 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2762 loss: 1.2762 2022/10/13 10:11:10 - mmengine - INFO - Epoch(train) [81][200/940] lr: 1.0000e-04 eta: 2:38:25 time: 0.4842 data_time: 0.0297 memory: 17006 grad_norm: 4.9213 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3377 loss: 1.3377 2022/10/13 10:11:21 - mmengine - INFO - Epoch(train) [81][220/940] lr: 1.0000e-04 eta: 2:38:15 time: 0.5506 data_time: 0.0361 memory: 17006 grad_norm: 5.0262 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2743 loss: 1.2743 2022/10/13 10:11:32 - mmengine - INFO - Epoch(train) [81][240/940] lr: 1.0000e-04 eta: 2:38:05 time: 0.5073 data_time: 0.0322 memory: 17006 grad_norm: 4.9120 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3083 loss: 1.3083 2022/10/13 10:11:42 - mmengine - INFO - Epoch(train) [81][260/940] lr: 1.0000e-04 eta: 2:37:55 time: 0.5207 data_time: 0.0368 memory: 17006 grad_norm: 4.9845 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3830 loss: 1.3830 2022/10/13 10:11:51 - mmengine - INFO - Epoch(train) [81][280/940] lr: 1.0000e-04 eta: 2:37:44 time: 0.4527 data_time: 0.0319 memory: 17006 grad_norm: 4.8739 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.1889 loss: 1.1889 2022/10/13 10:12:02 - mmengine - INFO - Epoch(train) [81][300/940] lr: 1.0000e-04 eta: 2:37:34 time: 0.5473 data_time: 0.0350 memory: 17006 grad_norm: 4.8585 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3455 loss: 1.3455 2022/10/13 10:12:11 - mmengine - INFO - Epoch(train) [81][320/940] lr: 1.0000e-04 eta: 2:37:24 time: 0.4445 data_time: 0.0336 memory: 17006 grad_norm: 4.9347 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1750 loss: 1.1750 2022/10/13 10:12:22 - mmengine - INFO - Epoch(train) [81][340/940] lr: 1.0000e-04 eta: 2:37:14 time: 0.5712 data_time: 0.0305 memory: 17006 grad_norm: 4.8341 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2876 loss: 1.2876 2022/10/13 10:12:32 - mmengine - INFO - Epoch(train) [81][360/940] lr: 1.0000e-04 eta: 2:37:04 time: 0.5059 data_time: 0.0301 memory: 17006 grad_norm: 5.0141 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2002 loss: 1.2002 2022/10/13 10:12:42 - mmengine - INFO - Epoch(train) [81][380/940] lr: 1.0000e-04 eta: 2:36:53 time: 0.4710 data_time: 0.0318 memory: 17006 grad_norm: 4.9367 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2609 loss: 1.2609 2022/10/13 10:12:53 - mmengine - INFO - Epoch(train) [81][400/940] lr: 1.0000e-04 eta: 2:36:43 time: 0.5540 data_time: 0.0343 memory: 17006 grad_norm: 4.8671 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2903 loss: 1.2903 2022/10/13 10:13:03 - mmengine - INFO - Epoch(train) [81][420/940] lr: 1.0000e-04 eta: 2:36:33 time: 0.5120 data_time: 0.0361 memory: 17006 grad_norm: 4.8943 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1201 loss: 1.1201 2022/10/13 10:13:13 - mmengine - INFO - Epoch(train) [81][440/940] lr: 1.0000e-04 eta: 2:36:23 time: 0.4783 data_time: 0.0285 memory: 17006 grad_norm: 4.9387 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2970 loss: 1.2970 2022/10/13 10:13:22 - mmengine - INFO - Epoch(train) [81][460/940] lr: 1.0000e-04 eta: 2:36:12 time: 0.4742 data_time: 0.0362 memory: 17006 grad_norm: 4.8397 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.1720 loss: 1.1720 2022/10/13 10:13:32 - mmengine - INFO - Epoch(train) [81][480/940] lr: 1.0000e-04 eta: 2:36:02 time: 0.4956 data_time: 0.0263 memory: 17006 grad_norm: 4.9886 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2583 loss: 1.2583 2022/10/13 10:13:43 - mmengine - INFO - Epoch(train) [81][500/940] lr: 1.0000e-04 eta: 2:35:52 time: 0.5633 data_time: 0.0345 memory: 17006 grad_norm: 4.7875 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4083 loss: 1.4083 2022/10/13 10:13:53 - mmengine - INFO - Epoch(train) [81][520/940] lr: 1.0000e-04 eta: 2:35:42 time: 0.4607 data_time: 0.0322 memory: 17006 grad_norm: 4.8436 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1617 loss: 1.1617 2022/10/13 10:14:03 - mmengine - INFO - Epoch(train) [81][540/940] lr: 1.0000e-04 eta: 2:35:31 time: 0.4998 data_time: 0.0417 memory: 17006 grad_norm: 4.9810 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.3277 loss: 1.3277 2022/10/13 10:14:12 - mmengine - INFO - Epoch(train) [81][560/940] lr: 1.0000e-04 eta: 2:35:21 time: 0.4698 data_time: 0.1109 memory: 17006 grad_norm: 4.9300 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2955 loss: 1.2955 2022/10/13 10:14:23 - mmengine - INFO - Epoch(train) [81][580/940] lr: 1.0000e-04 eta: 2:35:11 time: 0.5418 data_time: 0.0911 memory: 17006 grad_norm: 4.8314 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.2721 loss: 1.2721 2022/10/13 10:14:32 - mmengine - INFO - Epoch(train) [81][600/940] lr: 1.0000e-04 eta: 2:35:00 time: 0.4784 data_time: 0.0816 memory: 17006 grad_norm: 4.8383 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2523 loss: 1.2523 2022/10/13 10:14:43 - mmengine - INFO - Epoch(train) [81][620/940] lr: 1.0000e-04 eta: 2:34:50 time: 0.5523 data_time: 0.0413 memory: 17006 grad_norm: 4.9049 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.3923 loss: 1.3923 2022/10/13 10:14:53 - mmengine - INFO - Epoch(train) [81][640/940] lr: 1.0000e-04 eta: 2:34:40 time: 0.4781 data_time: 0.0293 memory: 17006 grad_norm: 4.9375 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1735 loss: 1.1735 2022/10/13 10:15:05 - mmengine - INFO - Epoch(train) [81][660/940] lr: 1.0000e-04 eta: 2:34:30 time: 0.6173 data_time: 0.0325 memory: 17006 grad_norm: 4.8675 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1662 loss: 1.1662 2022/10/13 10:15:15 - mmengine - INFO - Epoch(train) [81][680/940] lr: 1.0000e-04 eta: 2:34:20 time: 0.4898 data_time: 0.0301 memory: 17006 grad_norm: 4.9256 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2942 loss: 1.2942 2022/10/13 10:15:26 - mmengine - INFO - Epoch(train) [81][700/940] lr: 1.0000e-04 eta: 2:34:10 time: 0.5323 data_time: 0.0301 memory: 17006 grad_norm: 4.8822 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3103 loss: 1.3103 2022/10/13 10:15:36 - mmengine - INFO - Epoch(train) [81][720/940] lr: 1.0000e-04 eta: 2:34:00 time: 0.4954 data_time: 0.0326 memory: 17006 grad_norm: 4.9908 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2083 loss: 1.2083 2022/10/13 10:15:46 - mmengine - INFO - Epoch(train) [81][740/940] lr: 1.0000e-04 eta: 2:33:49 time: 0.4931 data_time: 0.0299 memory: 17006 grad_norm: 4.8491 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2558 loss: 1.2558 2022/10/13 10:15:55 - mmengine - INFO - Epoch(train) [81][760/940] lr: 1.0000e-04 eta: 2:33:39 time: 0.4823 data_time: 0.0430 memory: 17006 grad_norm: 5.0462 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2633 loss: 1.2633 2022/10/13 10:16:05 - mmengine - INFO - Epoch(train) [81][780/940] lr: 1.0000e-04 eta: 2:33:29 time: 0.4969 data_time: 0.0273 memory: 17006 grad_norm: 5.0267 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3278 loss: 1.3278 2022/10/13 10:16:15 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 10:16:15 - mmengine - INFO - Epoch(train) [81][800/940] lr: 1.0000e-04 eta: 2:33:18 time: 0.4784 data_time: 0.0365 memory: 17006 grad_norm: 4.8416 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3439 loss: 1.3439 2022/10/13 10:16:25 - mmengine - INFO - Epoch(train) [81][820/940] lr: 1.0000e-04 eta: 2:33:08 time: 0.5262 data_time: 0.0318 memory: 17006 grad_norm: 4.8822 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2082 loss: 1.2082 2022/10/13 10:16:35 - mmengine - INFO - Epoch(train) [81][840/940] lr: 1.0000e-04 eta: 2:32:58 time: 0.4810 data_time: 0.0363 memory: 17006 grad_norm: 4.8751 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2200 loss: 1.2200 2022/10/13 10:16:46 - mmengine - INFO - Epoch(train) [81][860/940] lr: 1.0000e-04 eta: 2:32:48 time: 0.5442 data_time: 0.0288 memory: 17006 grad_norm: 4.8569 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1899 loss: 1.1899 2022/10/13 10:16:56 - mmengine - INFO - Epoch(train) [81][880/940] lr: 1.0000e-04 eta: 2:32:37 time: 0.5083 data_time: 0.0358 memory: 17006 grad_norm: 5.0090 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2729 loss: 1.2729 2022/10/13 10:17:06 - mmengine - INFO - Epoch(train) [81][900/940] lr: 1.0000e-04 eta: 2:32:27 time: 0.5200 data_time: 0.0334 memory: 17006 grad_norm: 4.9563 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3187 loss: 1.3187 2022/10/13 10:17:16 - mmengine - INFO - Epoch(train) [81][920/940] lr: 1.0000e-04 eta: 2:32:17 time: 0.4733 data_time: 0.0347 memory: 17006 grad_norm: 4.9286 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2421 loss: 1.2421 2022/10/13 10:17:25 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 10:17:25 - mmengine - INFO - Epoch(train) [81][940/940] lr: 1.0000e-04 eta: 2:32:06 time: 0.4745 data_time: 0.0264 memory: 17006 grad_norm: 5.1574 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.3405 loss: 1.3405 2022/10/13 10:17:25 - mmengine - INFO - Saving checkpoint at 81 epochs 2022/10/13 10:17:39 - mmengine - INFO - Epoch(val) [81][20/78] eta: 0:00:37 time: 0.6389 data_time: 0.5490 memory: 3172 2022/10/13 10:17:47 - mmengine - INFO - Epoch(val) [81][40/78] eta: 0:00:16 time: 0.4280 data_time: 0.3383 memory: 3172 2022/10/13 10:17:59 - mmengine - INFO - Epoch(val) [81][60/78] eta: 0:00:10 time: 0.5695 data_time: 0.4778 memory: 3172 2022/10/13 10:18:08 - mmengine - INFO - Epoch(val) [81][78/78] acc/top1: 0.6738 acc/top5: 0.8702 acc/mean1: 0.6737 2022/10/13 10:18:22 - mmengine - INFO - Epoch(train) [82][20/940] lr: 1.0000e-04 eta: 2:31:57 time: 0.6884 data_time: 0.3062 memory: 17006 grad_norm: 4.8599 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1917 loss: 1.1917 2022/10/13 10:18:32 - mmengine - INFO - Epoch(train) [82][40/940] lr: 1.0000e-04 eta: 2:31:47 time: 0.4983 data_time: 0.0419 memory: 17006 grad_norm: 4.8966 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2515 loss: 1.2515 2022/10/13 10:18:43 - mmengine - INFO - Epoch(train) [82][60/940] lr: 1.0000e-04 eta: 2:31:37 time: 0.5486 data_time: 0.0361 memory: 17006 grad_norm: 4.8638 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1986 loss: 1.1986 2022/10/13 10:18:52 - mmengine - INFO - Epoch(train) [82][80/940] lr: 1.0000e-04 eta: 2:31:26 time: 0.4829 data_time: 0.0298 memory: 17006 grad_norm: 4.9370 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2842 loss: 1.2842 2022/10/13 10:19:03 - mmengine - INFO - Epoch(train) [82][100/940] lr: 1.0000e-04 eta: 2:31:16 time: 0.5255 data_time: 0.0340 memory: 17006 grad_norm: 4.9780 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3151 loss: 1.3151 2022/10/13 10:19:12 - mmengine - INFO - Epoch(train) [82][120/940] lr: 1.0000e-04 eta: 2:31:06 time: 0.4745 data_time: 0.0277 memory: 17006 grad_norm: 4.7689 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2859 loss: 1.2859 2022/10/13 10:19:24 - mmengine - INFO - Epoch(train) [82][140/940] lr: 1.0000e-04 eta: 2:30:56 time: 0.5778 data_time: 0.0340 memory: 17006 grad_norm: 4.9605 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1446 loss: 1.1446 2022/10/13 10:19:33 - mmengine - INFO - Epoch(train) [82][160/940] lr: 1.0000e-04 eta: 2:30:45 time: 0.4505 data_time: 0.0319 memory: 17006 grad_norm: 4.8521 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2286 loss: 1.2286 2022/10/13 10:19:44 - mmengine - INFO - Epoch(train) [82][180/940] lr: 1.0000e-04 eta: 2:30:35 time: 0.5436 data_time: 0.0336 memory: 17006 grad_norm: 4.9173 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2449 loss: 1.2449 2022/10/13 10:19:54 - mmengine - INFO - Epoch(train) [82][200/940] lr: 1.0000e-04 eta: 2:30:25 time: 0.4864 data_time: 0.0329 memory: 17006 grad_norm: 4.8802 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.1373 loss: 1.1373 2022/10/13 10:20:04 - mmengine - INFO - Epoch(train) [82][220/940] lr: 1.0000e-04 eta: 2:30:15 time: 0.5147 data_time: 0.0399 memory: 17006 grad_norm: 4.9061 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.0970 loss: 1.0970 2022/10/13 10:20:14 - mmengine - INFO - Epoch(train) [82][240/940] lr: 1.0000e-04 eta: 2:30:05 time: 0.4982 data_time: 0.0350 memory: 17006 grad_norm: 4.8793 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2468 loss: 1.2468 2022/10/13 10:20:25 - mmengine - INFO - Epoch(train) [82][260/940] lr: 1.0000e-04 eta: 2:29:54 time: 0.5469 data_time: 0.0309 memory: 17006 grad_norm: 4.8836 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3436 loss: 1.3436 2022/10/13 10:20:35 - mmengine - INFO - Epoch(train) [82][280/940] lr: 1.0000e-04 eta: 2:29:44 time: 0.5303 data_time: 0.0336 memory: 17006 grad_norm: 4.9649 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3077 loss: 1.3077 2022/10/13 10:20:45 - mmengine - INFO - Epoch(train) [82][300/940] lr: 1.0000e-04 eta: 2:29:34 time: 0.4587 data_time: 0.0317 memory: 17006 grad_norm: 4.9893 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2936 loss: 1.2936 2022/10/13 10:20:54 - mmengine - INFO - Epoch(train) [82][320/940] lr: 1.0000e-04 eta: 2:29:23 time: 0.4756 data_time: 0.0335 memory: 17006 grad_norm: 4.8928 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2094 loss: 1.2094 2022/10/13 10:21:05 - mmengine - INFO - Epoch(train) [82][340/940] lr: 1.0000e-04 eta: 2:29:13 time: 0.5503 data_time: 0.0305 memory: 17006 grad_norm: 4.8495 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3359 loss: 1.3359 2022/10/13 10:21:14 - mmengine - INFO - Epoch(train) [82][360/940] lr: 1.0000e-04 eta: 2:29:03 time: 0.4610 data_time: 0.0381 memory: 17006 grad_norm: 4.9256 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2649 loss: 1.2649 2022/10/13 10:21:25 - mmengine - INFO - Epoch(train) [82][380/940] lr: 1.0000e-04 eta: 2:28:53 time: 0.5139 data_time: 0.0299 memory: 17006 grad_norm: 4.9662 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2412 loss: 1.2412 2022/10/13 10:21:34 - mmengine - INFO - Epoch(train) [82][400/940] lr: 1.0000e-04 eta: 2:28:42 time: 0.4669 data_time: 0.0320 memory: 17006 grad_norm: 4.8982 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2753 loss: 1.2753 2022/10/13 10:21:44 - mmengine - INFO - Epoch(train) [82][420/940] lr: 1.0000e-04 eta: 2:28:32 time: 0.5194 data_time: 0.0328 memory: 17006 grad_norm: 4.8739 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.1554 loss: 1.1554 2022/10/13 10:21:55 - mmengine - INFO - Epoch(train) [82][440/940] lr: 1.0000e-04 eta: 2:28:22 time: 0.5149 data_time: 0.0354 memory: 17006 grad_norm: 4.9172 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.3613 loss: 1.3613 2022/10/13 10:22:06 - mmengine - INFO - Epoch(train) [82][460/940] lr: 1.0000e-04 eta: 2:28:12 time: 0.5797 data_time: 0.0303 memory: 17006 grad_norm: 5.0244 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3007 loss: 1.3007 2022/10/13 10:22:16 - mmengine - INFO - Epoch(train) [82][480/940] lr: 1.0000e-04 eta: 2:28:02 time: 0.4688 data_time: 0.0271 memory: 17006 grad_norm: 5.0169 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2522 loss: 1.2522 2022/10/13 10:22:25 - mmengine - INFO - Epoch(train) [82][500/940] lr: 1.0000e-04 eta: 2:27:51 time: 0.4787 data_time: 0.0329 memory: 17006 grad_norm: 4.9329 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1722 loss: 1.1722 2022/10/13 10:22:36 - mmengine - INFO - Epoch(train) [82][520/940] lr: 1.0000e-04 eta: 2:27:41 time: 0.5188 data_time: 0.0384 memory: 17006 grad_norm: 4.8478 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1575 loss: 1.1575 2022/10/13 10:22:45 - mmengine - INFO - Epoch(train) [82][540/940] lr: 1.0000e-04 eta: 2:27:31 time: 0.4928 data_time: 0.0300 memory: 17006 grad_norm: 4.9520 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2716 loss: 1.2716 2022/10/13 10:22:56 - mmengine - INFO - Epoch(train) [82][560/940] lr: 1.0000e-04 eta: 2:27:21 time: 0.5246 data_time: 0.0372 memory: 17006 grad_norm: 4.8177 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2939 loss: 1.2939 2022/10/13 10:23:06 - mmengine - INFO - Epoch(train) [82][580/940] lr: 1.0000e-04 eta: 2:27:10 time: 0.5222 data_time: 0.0388 memory: 17006 grad_norm: 4.8843 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2599 loss: 1.2599 2022/10/13 10:23:16 - mmengine - INFO - Epoch(train) [82][600/940] lr: 1.0000e-04 eta: 2:27:00 time: 0.4671 data_time: 0.0316 memory: 17006 grad_norm: 4.8458 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.2221 loss: 1.2221 2022/10/13 10:23:26 - mmengine - INFO - Epoch(train) [82][620/940] lr: 1.0000e-04 eta: 2:26:50 time: 0.5162 data_time: 0.0307 memory: 17006 grad_norm: 4.7459 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2029 loss: 1.2029 2022/10/13 10:23:36 - mmengine - INFO - Epoch(train) [82][640/940] lr: 1.0000e-04 eta: 2:26:40 time: 0.5090 data_time: 0.0313 memory: 17006 grad_norm: 4.8803 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3138 loss: 1.3138 2022/10/13 10:23:46 - mmengine - INFO - Epoch(train) [82][660/940] lr: 1.0000e-04 eta: 2:26:29 time: 0.5083 data_time: 0.0355 memory: 17006 grad_norm: 4.9867 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2819 loss: 1.2819 2022/10/13 10:23:56 - mmengine - INFO - Epoch(train) [82][680/940] lr: 1.0000e-04 eta: 2:26:19 time: 0.4652 data_time: 0.0317 memory: 17006 grad_norm: 4.9663 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2368 loss: 1.2368 2022/10/13 10:24:06 - mmengine - INFO - Epoch(train) [82][700/940] lr: 1.0000e-04 eta: 2:26:09 time: 0.4984 data_time: 0.0307 memory: 17006 grad_norm: 4.9744 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3881 loss: 1.3881 2022/10/13 10:24:16 - mmengine - INFO - Epoch(train) [82][720/940] lr: 1.0000e-04 eta: 2:25:58 time: 0.5162 data_time: 0.0328 memory: 17006 grad_norm: 4.9861 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1922 loss: 1.1922 2022/10/13 10:24:27 - mmengine - INFO - Epoch(train) [82][740/940] lr: 1.0000e-04 eta: 2:25:48 time: 0.5457 data_time: 0.0308 memory: 17006 grad_norm: 4.8639 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2492 loss: 1.2492 2022/10/13 10:24:37 - mmengine - INFO - Epoch(train) [82][760/940] lr: 1.0000e-04 eta: 2:25:38 time: 0.5037 data_time: 0.0342 memory: 17006 grad_norm: 4.9217 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1784 loss: 1.1784 2022/10/13 10:24:47 - mmengine - INFO - Epoch(train) [82][780/940] lr: 1.0000e-04 eta: 2:25:28 time: 0.4956 data_time: 0.0290 memory: 17006 grad_norm: 4.8084 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3010 loss: 1.3010 2022/10/13 10:24:57 - mmengine - INFO - Epoch(train) [82][800/940] lr: 1.0000e-04 eta: 2:25:18 time: 0.4844 data_time: 0.0318 memory: 17006 grad_norm: 4.9754 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3887 loss: 1.3887 2022/10/13 10:25:07 - mmengine - INFO - Epoch(train) [82][820/940] lr: 1.0000e-04 eta: 2:25:07 time: 0.5263 data_time: 0.0307 memory: 17006 grad_norm: 4.8765 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3080 loss: 1.3080 2022/10/13 10:25:17 - mmengine - INFO - Epoch(train) [82][840/940] lr: 1.0000e-04 eta: 2:24:57 time: 0.4999 data_time: 0.0293 memory: 17006 grad_norm: 4.8521 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.2811 loss: 1.2811 2022/10/13 10:25:27 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 10:25:27 - mmengine - INFO - Epoch(train) [82][860/940] lr: 1.0000e-04 eta: 2:24:47 time: 0.4849 data_time: 0.0321 memory: 17006 grad_norm: 4.9260 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2847 loss: 1.2847 2022/10/13 10:25:37 - mmengine - INFO - Epoch(train) [82][880/940] lr: 1.0000e-04 eta: 2:24:37 time: 0.5060 data_time: 0.0305 memory: 17006 grad_norm: 4.8266 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2390 loss: 1.2390 2022/10/13 10:25:47 - mmengine - INFO - Epoch(train) [82][900/940] lr: 1.0000e-04 eta: 2:24:26 time: 0.5153 data_time: 0.0393 memory: 17006 grad_norm: 4.9661 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3476 loss: 1.3476 2022/10/13 10:25:58 - mmengine - INFO - Epoch(train) [82][920/940] lr: 1.0000e-04 eta: 2:24:16 time: 0.5560 data_time: 0.0310 memory: 17006 grad_norm: 4.8833 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.3597 loss: 1.3597 2022/10/13 10:26:06 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 10:26:06 - mmengine - INFO - Epoch(train) [82][940/940] lr: 1.0000e-04 eta: 2:24:06 time: 0.4064 data_time: 0.0258 memory: 17006 grad_norm: 5.1292 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.1969 loss: 1.1969 2022/10/13 10:26:19 - mmengine - INFO - Epoch(val) [82][20/78] eta: 0:00:36 time: 0.6319 data_time: 0.5399 memory: 3172 2022/10/13 10:26:28 - mmengine - INFO - Epoch(val) [82][40/78] eta: 0:00:16 time: 0.4331 data_time: 0.3425 memory: 3172 2022/10/13 10:26:39 - mmengine - INFO - Epoch(val) [82][60/78] eta: 0:00:10 time: 0.5670 data_time: 0.4750 memory: 3172 2022/10/13 10:26:49 - mmengine - INFO - Epoch(val) [82][78/78] acc/top1: 0.6757 acc/top5: 0.8690 acc/mean1: 0.6756 2022/10/13 10:26:49 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_70.pth is removed 2022/10/13 10:26:50 - mmengine - INFO - The best checkpoint with 0.6757 acc/top1 at 82 epoch is saved to best_acc/top1_epoch_82.pth. 2022/10/13 10:27:03 - mmengine - INFO - Epoch(train) [83][20/940] lr: 1.0000e-04 eta: 2:23:56 time: 0.6875 data_time: 0.3636 memory: 17006 grad_norm: 4.9550 top1_acc: 0.7188 top5_acc: 0.7500 loss_cls: 1.2813 loss: 1.2813 2022/10/13 10:27:13 - mmengine - INFO - Epoch(train) [83][40/940] lr: 1.0000e-04 eta: 2:23:46 time: 0.4655 data_time: 0.0958 memory: 17006 grad_norm: 4.9492 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3011 loss: 1.3011 2022/10/13 10:27:24 - mmengine - INFO - Epoch(train) [83][60/940] lr: 1.0000e-04 eta: 2:23:36 time: 0.5530 data_time: 0.0402 memory: 17006 grad_norm: 4.8873 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2270 loss: 1.2270 2022/10/13 10:27:33 - mmengine - INFO - Epoch(train) [83][80/940] lr: 1.0000e-04 eta: 2:23:25 time: 0.4628 data_time: 0.0441 memory: 17006 grad_norm: 4.7615 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2104 loss: 1.2104 2022/10/13 10:27:44 - mmengine - INFO - Epoch(train) [83][100/940] lr: 1.0000e-04 eta: 2:23:15 time: 0.5581 data_time: 0.0481 memory: 17006 grad_norm: 4.9139 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2990 loss: 1.2990 2022/10/13 10:27:53 - mmengine - INFO - Epoch(train) [83][120/940] lr: 1.0000e-04 eta: 2:23:05 time: 0.4669 data_time: 0.0277 memory: 17006 grad_norm: 4.8861 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3117 loss: 1.3117 2022/10/13 10:28:03 - mmengine - INFO - Epoch(train) [83][140/940] lr: 1.0000e-04 eta: 2:22:54 time: 0.4798 data_time: 0.1300 memory: 17006 grad_norm: 4.7883 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2382 loss: 1.2382 2022/10/13 10:28:12 - mmengine - INFO - Epoch(train) [83][160/940] lr: 1.0000e-04 eta: 2:22:44 time: 0.4606 data_time: 0.1077 memory: 17006 grad_norm: 4.9908 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2127 loss: 1.2127 2022/10/13 10:28:23 - mmengine - INFO - Epoch(train) [83][180/940] lr: 1.0000e-04 eta: 2:22:34 time: 0.5524 data_time: 0.1273 memory: 17006 grad_norm: 4.8926 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2962 loss: 1.2962 2022/10/13 10:28:33 - mmengine - INFO - Epoch(train) [83][200/940] lr: 1.0000e-04 eta: 2:22:24 time: 0.4954 data_time: 0.0340 memory: 17006 grad_norm: 4.9508 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2432 loss: 1.2432 2022/10/13 10:28:43 - mmengine - INFO - Epoch(train) [83][220/940] lr: 1.0000e-04 eta: 2:22:13 time: 0.4894 data_time: 0.0452 memory: 17006 grad_norm: 4.9491 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3730 loss: 1.3730 2022/10/13 10:28:53 - mmengine - INFO - Epoch(train) [83][240/940] lr: 1.0000e-04 eta: 2:22:03 time: 0.5052 data_time: 0.0336 memory: 17006 grad_norm: 4.9063 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2175 loss: 1.2175 2022/10/13 10:29:04 - mmengine - INFO - Epoch(train) [83][260/940] lr: 1.0000e-04 eta: 2:21:53 time: 0.5570 data_time: 0.0305 memory: 17006 grad_norm: 4.8775 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2377 loss: 1.2377 2022/10/13 10:29:14 - mmengine - INFO - Epoch(train) [83][280/940] lr: 1.0000e-04 eta: 2:21:43 time: 0.4867 data_time: 0.0312 memory: 17006 grad_norm: 5.0047 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.4115 loss: 1.4115 2022/10/13 10:29:24 - mmengine - INFO - Epoch(train) [83][300/940] lr: 1.0000e-04 eta: 2:21:33 time: 0.4967 data_time: 0.0368 memory: 17006 grad_norm: 4.8814 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2554 loss: 1.2554 2022/10/13 10:29:35 - mmengine - INFO - Epoch(train) [83][320/940] lr: 1.0000e-04 eta: 2:21:22 time: 0.5526 data_time: 0.0281 memory: 17006 grad_norm: 5.0220 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.3433 loss: 1.3433 2022/10/13 10:29:45 - mmengine - INFO - Epoch(train) [83][340/940] lr: 1.0000e-04 eta: 2:21:12 time: 0.5106 data_time: 0.0353 memory: 17006 grad_norm: 5.0256 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3483 loss: 1.3483 2022/10/13 10:29:56 - mmengine - INFO - Epoch(train) [83][360/940] lr: 1.0000e-04 eta: 2:21:02 time: 0.5575 data_time: 0.0324 memory: 17006 grad_norm: 4.9680 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.2616 loss: 1.2616 2022/10/13 10:30:06 - mmengine - INFO - Epoch(train) [83][380/940] lr: 1.0000e-04 eta: 2:20:52 time: 0.4636 data_time: 0.0328 memory: 17006 grad_norm: 4.9247 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2459 loss: 1.2459 2022/10/13 10:30:17 - mmengine - INFO - Epoch(train) [83][400/940] lr: 1.0000e-04 eta: 2:20:42 time: 0.5787 data_time: 0.0383 memory: 17006 grad_norm: 4.9982 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2724 loss: 1.2724 2022/10/13 10:30:27 - mmengine - INFO - Epoch(train) [83][420/940] lr: 1.0000e-04 eta: 2:20:32 time: 0.4730 data_time: 0.0283 memory: 17006 grad_norm: 4.9966 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3274 loss: 1.3274 2022/10/13 10:30:37 - mmengine - INFO - Epoch(train) [83][440/940] lr: 1.0000e-04 eta: 2:20:21 time: 0.5271 data_time: 0.0339 memory: 17006 grad_norm: 4.8961 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3468 loss: 1.3468 2022/10/13 10:30:46 - mmengine - INFO - Epoch(train) [83][460/940] lr: 1.0000e-04 eta: 2:20:11 time: 0.4330 data_time: 0.0335 memory: 17006 grad_norm: 4.8476 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2726 loss: 1.2726 2022/10/13 10:30:57 - mmengine - INFO - Epoch(train) [83][480/940] lr: 1.0000e-04 eta: 2:20:01 time: 0.5762 data_time: 0.0363 memory: 17006 grad_norm: 4.7731 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2807 loss: 1.2807 2022/10/13 10:31:08 - mmengine - INFO - Epoch(train) [83][500/940] lr: 1.0000e-04 eta: 2:19:51 time: 0.5084 data_time: 0.0284 memory: 17006 grad_norm: 4.9920 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3082 loss: 1.3082 2022/10/13 10:31:19 - mmengine - INFO - Epoch(train) [83][520/940] lr: 1.0000e-04 eta: 2:19:41 time: 0.5482 data_time: 0.0297 memory: 17006 grad_norm: 4.9416 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1370 loss: 1.1370 2022/10/13 10:31:28 - mmengine - INFO - Epoch(train) [83][540/940] lr: 1.0000e-04 eta: 2:19:30 time: 0.4763 data_time: 0.0289 memory: 17006 grad_norm: 4.9074 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1844 loss: 1.1844 2022/10/13 10:31:39 - mmengine - INFO - Epoch(train) [83][560/940] lr: 1.0000e-04 eta: 2:19:20 time: 0.5371 data_time: 0.0340 memory: 17006 grad_norm: 4.9659 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2410 loss: 1.2410 2022/10/13 10:31:48 - mmengine - INFO - Epoch(train) [83][580/940] lr: 1.0000e-04 eta: 2:19:10 time: 0.4543 data_time: 0.0292 memory: 17006 grad_norm: 4.8247 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3505 loss: 1.3505 2022/10/13 10:31:59 - mmengine - INFO - Epoch(train) [83][600/940] lr: 1.0000e-04 eta: 2:19:00 time: 0.5784 data_time: 0.0303 memory: 17006 grad_norm: 4.9130 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2429 loss: 1.2429 2022/10/13 10:32:09 - mmengine - INFO - Epoch(train) [83][620/940] lr: 1.0000e-04 eta: 2:18:49 time: 0.4543 data_time: 0.0343 memory: 17006 grad_norm: 4.9445 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1445 loss: 1.1445 2022/10/13 10:32:19 - mmengine - INFO - Epoch(train) [83][640/940] lr: 1.0000e-04 eta: 2:18:39 time: 0.5082 data_time: 0.0357 memory: 17006 grad_norm: 4.8198 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.1143 loss: 1.1143 2022/10/13 10:32:28 - mmengine - INFO - Epoch(train) [83][660/940] lr: 1.0000e-04 eta: 2:18:29 time: 0.4891 data_time: 0.0282 memory: 17006 grad_norm: 4.9787 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.2875 loss: 1.2875 2022/10/13 10:32:39 - mmengine - INFO - Epoch(train) [83][680/940] lr: 1.0000e-04 eta: 2:18:19 time: 0.5246 data_time: 0.0309 memory: 17006 grad_norm: 4.8324 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2550 loss: 1.2550 2022/10/13 10:32:48 - mmengine - INFO - Epoch(train) [83][700/940] lr: 1.0000e-04 eta: 2:18:08 time: 0.4526 data_time: 0.0343 memory: 17006 grad_norm: 5.0110 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2914 loss: 1.2914 2022/10/13 10:33:00 - mmengine - INFO - Epoch(train) [83][720/940] lr: 1.0000e-04 eta: 2:17:58 time: 0.5927 data_time: 0.0300 memory: 17006 grad_norm: 4.8115 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2590 loss: 1.2590 2022/10/13 10:33:10 - mmengine - INFO - Epoch(train) [83][740/940] lr: 1.0000e-04 eta: 2:17:48 time: 0.5095 data_time: 0.0360 memory: 17006 grad_norm: 4.8915 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2428 loss: 1.2428 2022/10/13 10:33:20 - mmengine - INFO - Epoch(train) [83][760/940] lr: 1.0000e-04 eta: 2:17:38 time: 0.4896 data_time: 0.0345 memory: 17006 grad_norm: 4.9306 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.0799 loss: 1.0799 2022/10/13 10:33:30 - mmengine - INFO - Epoch(train) [83][780/940] lr: 1.0000e-04 eta: 2:17:27 time: 0.4844 data_time: 0.0337 memory: 17006 grad_norm: 4.9585 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2652 loss: 1.2652 2022/10/13 10:33:40 - mmengine - INFO - Epoch(train) [83][800/940] lr: 1.0000e-04 eta: 2:17:17 time: 0.5160 data_time: 0.0310 memory: 17006 grad_norm: 4.9467 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2514 loss: 1.2514 2022/10/13 10:33:49 - mmengine - INFO - Epoch(train) [83][820/940] lr: 1.0000e-04 eta: 2:17:07 time: 0.4619 data_time: 0.0300 memory: 17006 grad_norm: 4.9600 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.2822 loss: 1.2822 2022/10/13 10:34:00 - mmengine - INFO - Epoch(train) [83][840/940] lr: 1.0000e-04 eta: 2:16:57 time: 0.5593 data_time: 0.0340 memory: 17006 grad_norm: 5.0110 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2513 loss: 1.2513 2022/10/13 10:34:10 - mmengine - INFO - Epoch(train) [83][860/940] lr: 1.0000e-04 eta: 2:16:46 time: 0.4799 data_time: 0.0279 memory: 17006 grad_norm: 4.8254 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1327 loss: 1.1327 2022/10/13 10:34:21 - mmengine - INFO - Epoch(train) [83][880/940] lr: 1.0000e-04 eta: 2:16:36 time: 0.5378 data_time: 0.0325 memory: 17006 grad_norm: 4.9735 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1891 loss: 1.1891 2022/10/13 10:34:30 - mmengine - INFO - Epoch(train) [83][900/940] lr: 1.0000e-04 eta: 2:16:26 time: 0.4896 data_time: 0.0337 memory: 17006 grad_norm: 5.0531 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2471 loss: 1.2471 2022/10/13 10:34:40 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 10:34:40 - mmengine - INFO - Epoch(train) [83][920/940] lr: 1.0000e-04 eta: 2:16:16 time: 0.4996 data_time: 0.0292 memory: 17006 grad_norm: 4.9591 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2129 loss: 1.2129 2022/10/13 10:34:50 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 10:34:50 - mmengine - INFO - Epoch(train) [83][940/940] lr: 1.0000e-04 eta: 2:16:05 time: 0.4592 data_time: 0.0308 memory: 17006 grad_norm: 5.2649 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.4254 loss: 1.4254 2022/10/13 10:35:02 - mmengine - INFO - Epoch(val) [83][20/78] eta: 0:00:36 time: 0.6311 data_time: 0.5395 memory: 3172 2022/10/13 10:35:11 - mmengine - INFO - Epoch(val) [83][40/78] eta: 0:00:16 time: 0.4382 data_time: 0.3464 memory: 3172 2022/10/13 10:35:23 - mmengine - INFO - Epoch(val) [83][60/78] eta: 0:00:10 time: 0.5714 data_time: 0.4787 memory: 3172 2022/10/13 10:35:32 - mmengine - INFO - Epoch(val) [83][78/78] acc/top1: 0.6762 acc/top5: 0.8699 acc/mean1: 0.6761 2022/10/13 10:35:32 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_82.pth is removed 2022/10/13 10:35:33 - mmengine - INFO - The best checkpoint with 0.6762 acc/top1 at 83 epoch is saved to best_acc/top1_epoch_83.pth. 2022/10/13 10:35:46 - mmengine - INFO - Epoch(train) [84][20/940] lr: 1.0000e-04 eta: 2:15:56 time: 0.6627 data_time: 0.3242 memory: 17006 grad_norm: 4.9368 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2025 loss: 1.2025 2022/10/13 10:35:56 - mmengine - INFO - Epoch(train) [84][40/940] lr: 1.0000e-04 eta: 2:15:45 time: 0.4827 data_time: 0.0760 memory: 17006 grad_norm: 4.8884 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2834 loss: 1.2834 2022/10/13 10:36:07 - mmengine - INFO - Epoch(train) [84][60/940] lr: 1.0000e-04 eta: 2:15:35 time: 0.5356 data_time: 0.0432 memory: 17006 grad_norm: 4.9846 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2874 loss: 1.2874 2022/10/13 10:36:16 - mmengine - INFO - Epoch(train) [84][80/940] lr: 1.0000e-04 eta: 2:15:25 time: 0.4668 data_time: 0.0256 memory: 17006 grad_norm: 4.9174 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.2967 loss: 1.2967 2022/10/13 10:36:27 - mmengine - INFO - Epoch(train) [84][100/940] lr: 1.0000e-04 eta: 2:15:15 time: 0.5516 data_time: 0.0336 memory: 17006 grad_norm: 5.0170 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3002 loss: 1.3002 2022/10/13 10:36:37 - mmengine - INFO - Epoch(train) [84][120/940] lr: 1.0000e-04 eta: 2:15:04 time: 0.4869 data_time: 0.0282 memory: 17006 grad_norm: 4.8559 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2687 loss: 1.2687 2022/10/13 10:36:48 - mmengine - INFO - Epoch(train) [84][140/940] lr: 1.0000e-04 eta: 2:14:54 time: 0.5630 data_time: 0.0339 memory: 17006 grad_norm: 4.8629 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3709 loss: 1.3709 2022/10/13 10:36:57 - mmengine - INFO - Epoch(train) [84][160/940] lr: 1.0000e-04 eta: 2:14:44 time: 0.4780 data_time: 0.0244 memory: 17006 grad_norm: 4.9528 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2293 loss: 1.2293 2022/10/13 10:37:08 - mmengine - INFO - Epoch(train) [84][180/940] lr: 1.0000e-04 eta: 2:14:34 time: 0.5474 data_time: 0.0327 memory: 17006 grad_norm: 5.0081 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2904 loss: 1.2904 2022/10/13 10:37:17 - mmengine - INFO - Epoch(train) [84][200/940] lr: 1.0000e-04 eta: 2:14:23 time: 0.4425 data_time: 0.0283 memory: 17006 grad_norm: 4.8818 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2599 loss: 1.2599 2022/10/13 10:37:29 - mmengine - INFO - Epoch(train) [84][220/940] lr: 1.0000e-04 eta: 2:14:13 time: 0.5742 data_time: 0.0291 memory: 17006 grad_norm: 4.9140 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2951 loss: 1.2951 2022/10/13 10:37:38 - mmengine - INFO - Epoch(train) [84][240/940] lr: 1.0000e-04 eta: 2:14:03 time: 0.4514 data_time: 0.0309 memory: 17006 grad_norm: 4.8736 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2565 loss: 1.2565 2022/10/13 10:37:49 - mmengine - INFO - Epoch(train) [84][260/940] lr: 1.0000e-04 eta: 2:13:53 time: 0.5815 data_time: 0.0383 memory: 17006 grad_norm: 4.9243 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2299 loss: 1.2299 2022/10/13 10:37:59 - mmengine - INFO - Epoch(train) [84][280/940] lr: 1.0000e-04 eta: 2:13:43 time: 0.4676 data_time: 0.0341 memory: 17006 grad_norm: 4.8825 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2066 loss: 1.2066 2022/10/13 10:38:10 - mmengine - INFO - Epoch(train) [84][300/940] lr: 1.0000e-04 eta: 2:13:33 time: 0.5569 data_time: 0.0347 memory: 17006 grad_norm: 4.9751 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2381 loss: 1.2381 2022/10/13 10:38:19 - mmengine - INFO - Epoch(train) [84][320/940] lr: 1.0000e-04 eta: 2:13:22 time: 0.4592 data_time: 0.0337 memory: 17006 grad_norm: 4.8804 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2437 loss: 1.2437 2022/10/13 10:38:29 - mmengine - INFO - Epoch(train) [84][340/940] lr: 1.0000e-04 eta: 2:13:12 time: 0.5124 data_time: 0.0331 memory: 17006 grad_norm: 4.9342 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.2755 loss: 1.2755 2022/10/13 10:38:38 - mmengine - INFO - Epoch(train) [84][360/940] lr: 1.0000e-04 eta: 2:13:02 time: 0.4571 data_time: 0.0353 memory: 17006 grad_norm: 4.9440 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3810 loss: 1.3810 2022/10/13 10:38:49 - mmengine - INFO - Epoch(train) [84][380/940] lr: 1.0000e-04 eta: 2:12:51 time: 0.5435 data_time: 0.0368 memory: 17006 grad_norm: 4.9421 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1806 loss: 1.1806 2022/10/13 10:38:59 - mmengine - INFO - Epoch(train) [84][400/940] lr: 1.0000e-04 eta: 2:12:41 time: 0.4952 data_time: 0.0363 memory: 17006 grad_norm: 4.9659 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.3866 loss: 1.3866 2022/10/13 10:39:10 - mmengine - INFO - Epoch(train) [84][420/940] lr: 1.0000e-04 eta: 2:12:31 time: 0.5537 data_time: 0.0298 memory: 17006 grad_norm: 4.7631 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2422 loss: 1.2422 2022/10/13 10:39:21 - mmengine - INFO - Epoch(train) [84][440/940] lr: 1.0000e-04 eta: 2:12:21 time: 0.5096 data_time: 0.0347 memory: 17006 grad_norm: 4.9021 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2412 loss: 1.2412 2022/10/13 10:39:31 - mmengine - INFO - Epoch(train) [84][460/940] lr: 1.0000e-04 eta: 2:12:11 time: 0.5441 data_time: 0.0334 memory: 17006 grad_norm: 4.8154 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3669 loss: 1.3669 2022/10/13 10:39:41 - mmengine - INFO - Epoch(train) [84][480/940] lr: 1.0000e-04 eta: 2:12:00 time: 0.4546 data_time: 0.0369 memory: 17006 grad_norm: 4.9293 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2491 loss: 1.2491 2022/10/13 10:39:51 - mmengine - INFO - Epoch(train) [84][500/940] lr: 1.0000e-04 eta: 2:11:50 time: 0.5431 data_time: 0.0298 memory: 17006 grad_norm: 4.8780 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.1638 loss: 1.1638 2022/10/13 10:40:01 - mmengine - INFO - Epoch(train) [84][520/940] lr: 1.0000e-04 eta: 2:11:40 time: 0.4704 data_time: 0.0380 memory: 17006 grad_norm: 4.8331 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2474 loss: 1.2474 2022/10/13 10:40:12 - mmengine - INFO - Epoch(train) [84][540/940] lr: 1.0000e-04 eta: 2:11:30 time: 0.5544 data_time: 0.0395 memory: 17006 grad_norm: 4.9959 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3675 loss: 1.3675 2022/10/13 10:40:21 - mmengine - INFO - Epoch(train) [84][560/940] lr: 1.0000e-04 eta: 2:11:19 time: 0.4607 data_time: 0.0305 memory: 17006 grad_norm: 4.9860 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2596 loss: 1.2596 2022/10/13 10:40:32 - mmengine - INFO - Epoch(train) [84][580/940] lr: 1.0000e-04 eta: 2:11:09 time: 0.5380 data_time: 0.0407 memory: 17006 grad_norm: 4.9250 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3497 loss: 1.3497 2022/10/13 10:40:42 - mmengine - INFO - Epoch(train) [84][600/940] lr: 1.0000e-04 eta: 2:10:59 time: 0.4894 data_time: 0.0265 memory: 17006 grad_norm: 4.8320 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3134 loss: 1.3134 2022/10/13 10:40:53 - mmengine - INFO - Epoch(train) [84][620/940] lr: 1.0000e-04 eta: 2:10:49 time: 0.5653 data_time: 0.0371 memory: 17006 grad_norm: 4.9236 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2318 loss: 1.2318 2022/10/13 10:41:03 - mmengine - INFO - Epoch(train) [84][640/940] lr: 1.0000e-04 eta: 2:10:39 time: 0.5059 data_time: 0.0325 memory: 17006 grad_norm: 5.0141 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3707 loss: 1.3707 2022/10/13 10:41:14 - mmengine - INFO - Epoch(train) [84][660/940] lr: 1.0000e-04 eta: 2:10:29 time: 0.5615 data_time: 0.0277 memory: 17006 grad_norm: 4.9529 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3105 loss: 1.3105 2022/10/13 10:41:24 - mmengine - INFO - Epoch(train) [84][680/940] lr: 1.0000e-04 eta: 2:10:18 time: 0.4753 data_time: 0.0310 memory: 17006 grad_norm: 4.9177 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2733 loss: 1.2733 2022/10/13 10:41:35 - mmengine - INFO - Epoch(train) [84][700/940] lr: 1.0000e-04 eta: 2:10:08 time: 0.5570 data_time: 0.0292 memory: 17006 grad_norm: 4.9188 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2166 loss: 1.2166 2022/10/13 10:41:44 - mmengine - INFO - Epoch(train) [84][720/940] lr: 1.0000e-04 eta: 2:09:58 time: 0.4704 data_time: 0.0335 memory: 17006 grad_norm: 5.0256 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2936 loss: 1.2936 2022/10/13 10:41:54 - mmengine - INFO - Epoch(train) [84][740/940] lr: 1.0000e-04 eta: 2:09:48 time: 0.4966 data_time: 0.0301 memory: 17006 grad_norm: 4.9243 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3020 loss: 1.3020 2022/10/13 10:42:03 - mmengine - INFO - Epoch(train) [84][760/940] lr: 1.0000e-04 eta: 2:09:37 time: 0.4353 data_time: 0.0346 memory: 17006 grad_norm: 4.8784 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2677 loss: 1.2677 2022/10/13 10:42:13 - mmengine - INFO - Epoch(train) [84][780/940] lr: 1.0000e-04 eta: 2:09:27 time: 0.5065 data_time: 0.0378 memory: 17006 grad_norm: 5.0430 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3420 loss: 1.3420 2022/10/13 10:42:24 - mmengine - INFO - Epoch(train) [84][800/940] lr: 1.0000e-04 eta: 2:09:17 time: 0.5226 data_time: 0.0361 memory: 17006 grad_norm: 4.9155 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.1303 loss: 1.1303 2022/10/13 10:42:33 - mmengine - INFO - Epoch(train) [84][820/940] lr: 1.0000e-04 eta: 2:09:06 time: 0.4664 data_time: 0.0326 memory: 17006 grad_norm: 4.9636 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2886 loss: 1.2886 2022/10/13 10:42:44 - mmengine - INFO - Epoch(train) [84][840/940] lr: 1.0000e-04 eta: 2:08:56 time: 0.5379 data_time: 0.0355 memory: 17006 grad_norm: 4.8803 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.1461 loss: 1.1461 2022/10/13 10:42:53 - mmengine - INFO - Epoch(train) [84][860/940] lr: 1.0000e-04 eta: 2:08:46 time: 0.4791 data_time: 0.0289 memory: 17006 grad_norm: 4.9204 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3028 loss: 1.3028 2022/10/13 10:43:04 - mmengine - INFO - Epoch(train) [84][880/940] lr: 1.0000e-04 eta: 2:08:36 time: 0.5369 data_time: 0.0336 memory: 17006 grad_norm: 4.9622 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2272 loss: 1.2272 2022/10/13 10:43:14 - mmengine - INFO - Epoch(train) [84][900/940] lr: 1.0000e-04 eta: 2:08:25 time: 0.4844 data_time: 0.0306 memory: 17006 grad_norm: 4.8886 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3037 loss: 1.3037 2022/10/13 10:43:24 - mmengine - INFO - Epoch(train) [84][920/940] lr: 1.0000e-04 eta: 2:08:15 time: 0.5378 data_time: 0.0384 memory: 17006 grad_norm: 4.9605 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3617 loss: 1.3617 2022/10/13 10:43:33 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 10:43:33 - mmengine - INFO - Epoch(train) [84][940/940] lr: 1.0000e-04 eta: 2:08:05 time: 0.4441 data_time: 0.0250 memory: 17006 grad_norm: 5.2080 top1_acc: 0.0000 top5_acc: 0.2857 loss_cls: 1.5216 loss: 1.5216 2022/10/13 10:43:34 - mmengine - INFO - Saving checkpoint at 84 epochs 2022/10/13 10:43:47 - mmengine - INFO - Epoch(val) [84][20/78] eta: 0:00:35 time: 0.6182 data_time: 0.5280 memory: 3172 2022/10/13 10:43:55 - mmengine - INFO - Epoch(val) [84][40/78] eta: 0:00:16 time: 0.4283 data_time: 0.3371 memory: 3172 2022/10/13 10:44:07 - mmengine - INFO - Epoch(val) [84][60/78] eta: 0:00:10 time: 0.5830 data_time: 0.4925 memory: 3172 2022/10/13 10:44:16 - mmengine - INFO - Epoch(val) [84][78/78] acc/top1: 0.6742 acc/top5: 0.8688 acc/mean1: 0.6741 2022/10/13 10:44:31 - mmengine - INFO - Epoch(train) [85][20/940] lr: 1.0000e-04 eta: 2:07:55 time: 0.7118 data_time: 0.3175 memory: 17006 grad_norm: 4.8274 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1833 loss: 1.1833 2022/10/13 10:44:40 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 10:44:40 - mmengine - INFO - Epoch(train) [85][40/940] lr: 1.0000e-04 eta: 2:07:45 time: 0.4689 data_time: 0.1326 memory: 17006 grad_norm: 4.8653 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1776 loss: 1.1776 2022/10/13 10:44:52 - mmengine - INFO - Epoch(train) [85][60/940] lr: 1.0000e-04 eta: 2:07:35 time: 0.6198 data_time: 0.2639 memory: 17006 grad_norm: 4.9727 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3693 loss: 1.3693 2022/10/13 10:45:02 - mmengine - INFO - Epoch(train) [85][80/940] lr: 1.0000e-04 eta: 2:07:25 time: 0.4601 data_time: 0.1315 memory: 17006 grad_norm: 4.9832 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2247 loss: 1.2247 2022/10/13 10:45:13 - mmengine - INFO - Epoch(train) [85][100/940] lr: 1.0000e-04 eta: 2:07:15 time: 0.5431 data_time: 0.2130 memory: 17006 grad_norm: 4.9377 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2832 loss: 1.2832 2022/10/13 10:45:22 - mmengine - INFO - Epoch(train) [85][120/940] lr: 1.0000e-04 eta: 2:07:04 time: 0.4862 data_time: 0.1362 memory: 17006 grad_norm: 4.8993 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2533 loss: 1.2533 2022/10/13 10:45:33 - mmengine - INFO - Epoch(train) [85][140/940] lr: 1.0000e-04 eta: 2:06:54 time: 0.5385 data_time: 0.2048 memory: 17006 grad_norm: 5.0175 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1959 loss: 1.1959 2022/10/13 10:45:42 - mmengine - INFO - Epoch(train) [85][160/940] lr: 1.0000e-04 eta: 2:06:44 time: 0.4617 data_time: 0.1271 memory: 17006 grad_norm: 4.9685 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2748 loss: 1.2748 2022/10/13 10:45:53 - mmengine - INFO - Epoch(train) [85][180/940] lr: 1.0000e-04 eta: 2:06:34 time: 0.5483 data_time: 0.2110 memory: 17006 grad_norm: 4.8225 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2596 loss: 1.2596 2022/10/13 10:46:02 - mmengine - INFO - Epoch(train) [85][200/940] lr: 1.0000e-04 eta: 2:06:23 time: 0.4413 data_time: 0.1163 memory: 17006 grad_norm: 4.8741 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.2720 loss: 1.2720 2022/10/13 10:46:13 - mmengine - INFO - Epoch(train) [85][220/940] lr: 1.0000e-04 eta: 2:06:13 time: 0.5675 data_time: 0.2260 memory: 17006 grad_norm: 4.9084 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2622 loss: 1.2622 2022/10/13 10:46:23 - mmengine - INFO - Epoch(train) [85][240/940] lr: 1.0000e-04 eta: 2:06:03 time: 0.4684 data_time: 0.1329 memory: 17006 grad_norm: 4.8468 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2403 loss: 1.2403 2022/10/13 10:46:34 - mmengine - INFO - Epoch(train) [85][260/940] lr: 1.0000e-04 eta: 2:05:53 time: 0.5561 data_time: 0.2337 memory: 17006 grad_norm: 4.8919 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2961 loss: 1.2961 2022/10/13 10:46:43 - mmengine - INFO - Epoch(train) [85][280/940] lr: 1.0000e-04 eta: 2:05:42 time: 0.4677 data_time: 0.1467 memory: 17006 grad_norm: 4.9324 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.3123 loss: 1.3123 2022/10/13 10:46:53 - mmengine - INFO - Epoch(train) [85][300/940] lr: 1.0000e-04 eta: 2:05:32 time: 0.4760 data_time: 0.1158 memory: 17006 grad_norm: 4.9136 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3701 loss: 1.3701 2022/10/13 10:47:03 - mmengine - INFO - Epoch(train) [85][320/940] lr: 1.0000e-04 eta: 2:05:22 time: 0.4962 data_time: 0.1298 memory: 17006 grad_norm: 4.8771 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2356 loss: 1.2356 2022/10/13 10:47:12 - mmengine - INFO - Epoch(train) [85][340/940] lr: 1.0000e-04 eta: 2:05:12 time: 0.4786 data_time: 0.0811 memory: 17006 grad_norm: 4.9208 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4014 loss: 1.4014 2022/10/13 10:47:23 - mmengine - INFO - Epoch(train) [85][360/940] lr: 1.0000e-04 eta: 2:05:01 time: 0.5390 data_time: 0.0266 memory: 17006 grad_norm: 4.9324 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2531 loss: 1.2531 2022/10/13 10:47:34 - mmengine - INFO - Epoch(train) [85][380/940] lr: 1.0000e-04 eta: 2:04:51 time: 0.5467 data_time: 0.0335 memory: 17006 grad_norm: 4.9932 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2703 loss: 1.2703 2022/10/13 10:47:44 - mmengine - INFO - Epoch(train) [85][400/940] lr: 1.0000e-04 eta: 2:04:41 time: 0.4880 data_time: 0.0308 memory: 17006 grad_norm: 4.8943 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2310 loss: 1.2310 2022/10/13 10:47:54 - mmengine - INFO - Epoch(train) [85][420/940] lr: 1.0000e-04 eta: 2:04:31 time: 0.5166 data_time: 0.0318 memory: 17006 grad_norm: 4.9374 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3020 loss: 1.3020 2022/10/13 10:48:04 - mmengine - INFO - Epoch(train) [85][440/940] lr: 1.0000e-04 eta: 2:04:21 time: 0.5079 data_time: 0.0355 memory: 17006 grad_norm: 4.9548 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2591 loss: 1.2591 2022/10/13 10:48:14 - mmengine - INFO - Epoch(train) [85][460/940] lr: 1.0000e-04 eta: 2:04:10 time: 0.5010 data_time: 0.0300 memory: 17006 grad_norm: 4.9504 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0858 loss: 1.0858 2022/10/13 10:48:24 - mmengine - INFO - Epoch(train) [85][480/940] lr: 1.0000e-04 eta: 2:04:00 time: 0.4866 data_time: 0.0321 memory: 17006 grad_norm: 4.8843 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2869 loss: 1.2869 2022/10/13 10:48:35 - mmengine - INFO - Epoch(train) [85][500/940] lr: 1.0000e-04 eta: 2:03:50 time: 0.5350 data_time: 0.0292 memory: 17006 grad_norm: 4.9486 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2519 loss: 1.2519 2022/10/13 10:48:44 - mmengine - INFO - Epoch(train) [85][520/940] lr: 1.0000e-04 eta: 2:03:40 time: 0.4746 data_time: 0.0342 memory: 17006 grad_norm: 4.9244 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3071 loss: 1.3071 2022/10/13 10:48:56 - mmengine - INFO - Epoch(train) [85][540/940] lr: 1.0000e-04 eta: 2:03:30 time: 0.5775 data_time: 0.0310 memory: 17006 grad_norm: 4.8581 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.0978 loss: 1.0978 2022/10/13 10:49:06 - mmengine - INFO - Epoch(train) [85][560/940] lr: 1.0000e-04 eta: 2:03:19 time: 0.4906 data_time: 0.0275 memory: 17006 grad_norm: 4.9158 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.3137 loss: 1.3137 2022/10/13 10:49:15 - mmengine - INFO - Epoch(train) [85][580/940] lr: 1.0000e-04 eta: 2:03:09 time: 0.4863 data_time: 0.0332 memory: 17006 grad_norm: 4.8377 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1991 loss: 1.1991 2022/10/13 10:49:25 - mmengine - INFO - Epoch(train) [85][600/940] lr: 1.0000e-04 eta: 2:02:59 time: 0.4770 data_time: 0.0367 memory: 17006 grad_norm: 4.8859 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2962 loss: 1.2962 2022/10/13 10:49:36 - mmengine - INFO - Epoch(train) [85][620/940] lr: 1.0000e-04 eta: 2:02:48 time: 0.5444 data_time: 0.0400 memory: 17006 grad_norm: 5.0089 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3771 loss: 1.3771 2022/10/13 10:49:46 - mmengine - INFO - Epoch(train) [85][640/940] lr: 1.0000e-04 eta: 2:02:38 time: 0.4934 data_time: 0.0306 memory: 17006 grad_norm: 4.9350 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2251 loss: 1.2251 2022/10/13 10:49:56 - mmengine - INFO - Epoch(train) [85][660/940] lr: 1.0000e-04 eta: 2:02:28 time: 0.5078 data_time: 0.0297 memory: 17006 grad_norm: 4.8997 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.3826 loss: 1.3826 2022/10/13 10:50:05 - mmengine - INFO - Epoch(train) [85][680/940] lr: 1.0000e-04 eta: 2:02:18 time: 0.4817 data_time: 0.0317 memory: 17006 grad_norm: 4.9102 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2928 loss: 1.2928 2022/10/13 10:50:16 - mmengine - INFO - Epoch(train) [85][700/940] lr: 1.0000e-04 eta: 2:02:07 time: 0.5220 data_time: 0.0308 memory: 17006 grad_norm: 4.7894 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2153 loss: 1.2153 2022/10/13 10:50:26 - mmengine - INFO - Epoch(train) [85][720/940] lr: 1.0000e-04 eta: 2:01:57 time: 0.4926 data_time: 0.0334 memory: 17006 grad_norm: 4.8923 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0757 loss: 1.0757 2022/10/13 10:50:36 - mmengine - INFO - Epoch(train) [85][740/940] lr: 1.0000e-04 eta: 2:01:47 time: 0.5258 data_time: 0.0324 memory: 17006 grad_norm: 4.7802 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2091 loss: 1.2091 2022/10/13 10:50:46 - mmengine - INFO - Epoch(train) [85][760/940] lr: 1.0000e-04 eta: 2:01:37 time: 0.4780 data_time: 0.0339 memory: 17006 grad_norm: 4.9710 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3081 loss: 1.3081 2022/10/13 10:50:56 - mmengine - INFO - Epoch(train) [85][780/940] lr: 1.0000e-04 eta: 2:01:27 time: 0.5339 data_time: 0.0293 memory: 17006 grad_norm: 5.0210 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1562 loss: 1.1562 2022/10/13 10:51:07 - mmengine - INFO - Epoch(train) [85][800/940] lr: 1.0000e-04 eta: 2:01:16 time: 0.5298 data_time: 0.0351 memory: 17006 grad_norm: 4.9338 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2417 loss: 1.2417 2022/10/13 10:51:17 - mmengine - INFO - Epoch(train) [85][820/940] lr: 1.0000e-04 eta: 2:01:06 time: 0.4908 data_time: 0.0337 memory: 17006 grad_norm: 4.8541 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.2733 loss: 1.2733 2022/10/13 10:51:28 - mmengine - INFO - Epoch(train) [85][840/940] lr: 1.0000e-04 eta: 2:00:56 time: 0.5327 data_time: 0.0332 memory: 17006 grad_norm: 4.9242 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2415 loss: 1.2415 2022/10/13 10:51:36 - mmengine - INFO - Epoch(train) [85][860/940] lr: 1.0000e-04 eta: 2:00:45 time: 0.4419 data_time: 0.0286 memory: 17006 grad_norm: 4.9067 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1358 loss: 1.1358 2022/10/13 10:51:47 - mmengine - INFO - Epoch(train) [85][880/940] lr: 1.0000e-04 eta: 2:00:35 time: 0.5109 data_time: 0.0351 memory: 17006 grad_norm: 4.8852 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2299 loss: 1.2299 2022/10/13 10:51:56 - mmengine - INFO - Epoch(train) [85][900/940] lr: 1.0000e-04 eta: 2:00:25 time: 0.4815 data_time: 0.0295 memory: 17006 grad_norm: 4.9243 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2803 loss: 1.2803 2022/10/13 10:52:07 - mmengine - INFO - Epoch(train) [85][920/940] lr: 1.0000e-04 eta: 2:00:15 time: 0.5298 data_time: 0.0358 memory: 17006 grad_norm: 5.0096 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.3864 loss: 1.3864 2022/10/13 10:52:16 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 10:52:16 - mmengine - INFO - Epoch(train) [85][940/940] lr: 1.0000e-04 eta: 2:00:04 time: 0.4752 data_time: 0.0270 memory: 17006 grad_norm: 5.1811 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.2485 loss: 1.2485 2022/10/13 10:52:29 - mmengine - INFO - Epoch(val) [85][20/78] eta: 0:00:36 time: 0.6286 data_time: 0.5342 memory: 3172 2022/10/13 10:52:38 - mmengine - INFO - Epoch(val) [85][40/78] eta: 0:00:16 time: 0.4368 data_time: 0.3408 memory: 3172 2022/10/13 10:52:49 - mmengine - INFO - Epoch(val) [85][60/78] eta: 0:00:10 time: 0.5878 data_time: 0.4953 memory: 3172 2022/10/13 10:52:59 - mmengine - INFO - Epoch(val) [85][78/78] acc/top1: 0.6744 acc/top5: 0.8699 acc/mean1: 0.6743 2022/10/13 10:53:13 - mmengine - INFO - Epoch(train) [86][20/940] lr: 1.0000e-04 eta: 1:59:55 time: 0.6865 data_time: 0.3042 memory: 17006 grad_norm: 5.0399 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3883 loss: 1.3883 2022/10/13 10:53:22 - mmengine - INFO - Epoch(train) [86][40/940] lr: 1.0000e-04 eta: 1:59:44 time: 0.4640 data_time: 0.0576 memory: 17006 grad_norm: 4.8824 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3444 loss: 1.3444 2022/10/13 10:53:34 - mmengine - INFO - Epoch(train) [86][60/940] lr: 1.0000e-04 eta: 1:59:35 time: 0.5870 data_time: 0.0517 memory: 17006 grad_norm: 4.9610 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.1363 loss: 1.1363 2022/10/13 10:53:43 - mmengine - INFO - Epoch(train) [86][80/940] lr: 1.0000e-04 eta: 1:59:24 time: 0.4764 data_time: 0.0282 memory: 17006 grad_norm: 4.9052 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2712 loss: 1.2712 2022/10/13 10:53:54 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 10:53:54 - mmengine - INFO - Epoch(train) [86][100/940] lr: 1.0000e-04 eta: 1:59:14 time: 0.5569 data_time: 0.0352 memory: 17006 grad_norm: 4.9589 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2889 loss: 1.2889 2022/10/13 10:54:04 - mmengine - INFO - Epoch(train) [86][120/940] lr: 1.0000e-04 eta: 1:59:04 time: 0.5080 data_time: 0.0271 memory: 17006 grad_norm: 4.9776 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.2152 loss: 1.2152 2022/10/13 10:54:15 - mmengine - INFO - Epoch(train) [86][140/940] lr: 1.0000e-04 eta: 1:58:54 time: 0.5298 data_time: 0.0311 memory: 17006 grad_norm: 4.8869 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.1577 loss: 1.1577 2022/10/13 10:54:25 - mmengine - INFO - Epoch(train) [86][160/940] lr: 1.0000e-04 eta: 1:58:44 time: 0.5154 data_time: 0.0352 memory: 17006 grad_norm: 4.9444 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3041 loss: 1.3041 2022/10/13 10:54:35 - mmengine - INFO - Epoch(train) [86][180/940] lr: 1.0000e-04 eta: 1:58:33 time: 0.4617 data_time: 0.0301 memory: 17006 grad_norm: 4.9742 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2887 loss: 1.2887 2022/10/13 10:54:44 - mmengine - INFO - Epoch(train) [86][200/940] lr: 1.0000e-04 eta: 1:58:23 time: 0.4947 data_time: 0.0347 memory: 17006 grad_norm: 4.8634 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2039 loss: 1.2039 2022/10/13 10:54:55 - mmengine - INFO - Epoch(train) [86][220/940] lr: 1.0000e-04 eta: 1:58:13 time: 0.5119 data_time: 0.0308 memory: 17006 grad_norm: 4.9363 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.1963 loss: 1.1963 2022/10/13 10:55:04 - mmengine - INFO - Epoch(train) [86][240/940] lr: 1.0000e-04 eta: 1:58:02 time: 0.4589 data_time: 0.0389 memory: 17006 grad_norm: 4.8299 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3097 loss: 1.3097 2022/10/13 10:55:15 - mmengine - INFO - Epoch(train) [86][260/940] lr: 1.0000e-04 eta: 1:57:52 time: 0.5787 data_time: 0.0317 memory: 17006 grad_norm: 4.9099 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2681 loss: 1.2681 2022/10/13 10:55:25 - mmengine - INFO - Epoch(train) [86][280/940] lr: 1.0000e-04 eta: 1:57:42 time: 0.4901 data_time: 0.0329 memory: 17006 grad_norm: 4.8602 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3083 loss: 1.3083 2022/10/13 10:55:36 - mmengine - INFO - Epoch(train) [86][300/940] lr: 1.0000e-04 eta: 1:57:32 time: 0.5181 data_time: 0.0336 memory: 17006 grad_norm: 4.8675 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1687 loss: 1.1687 2022/10/13 10:55:45 - mmengine - INFO - Epoch(train) [86][320/940] lr: 1.0000e-04 eta: 1:57:21 time: 0.4565 data_time: 0.0298 memory: 17006 grad_norm: 4.9145 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1818 loss: 1.1818 2022/10/13 10:55:56 - mmengine - INFO - Epoch(train) [86][340/940] lr: 1.0000e-04 eta: 1:57:11 time: 0.5500 data_time: 0.0335 memory: 17006 grad_norm: 4.9883 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1971 loss: 1.1971 2022/10/13 10:56:06 - mmengine - INFO - Epoch(train) [86][360/940] lr: 1.0000e-04 eta: 1:57:01 time: 0.4912 data_time: 0.0317 memory: 17006 grad_norm: 4.9149 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2056 loss: 1.2056 2022/10/13 10:56:16 - mmengine - INFO - Epoch(train) [86][380/940] lr: 1.0000e-04 eta: 1:56:51 time: 0.5108 data_time: 0.0295 memory: 17006 grad_norm: 4.9846 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3418 loss: 1.3418 2022/10/13 10:56:25 - mmengine - INFO - Epoch(train) [86][400/940] lr: 1.0000e-04 eta: 1:56:40 time: 0.4487 data_time: 0.0303 memory: 17006 grad_norm: 4.9463 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2068 loss: 1.2068 2022/10/13 10:56:36 - mmengine - INFO - Epoch(train) [86][420/940] lr: 1.0000e-04 eta: 1:56:30 time: 0.5452 data_time: 0.0324 memory: 17006 grad_norm: 4.9097 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2530 loss: 1.2530 2022/10/13 10:56:45 - mmengine - INFO - Epoch(train) [86][440/940] lr: 1.0000e-04 eta: 1:56:20 time: 0.4701 data_time: 0.0317 memory: 17006 grad_norm: 5.0092 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4024 loss: 1.4024 2022/10/13 10:56:56 - mmengine - INFO - Epoch(train) [86][460/940] lr: 1.0000e-04 eta: 1:56:10 time: 0.5439 data_time: 0.0360 memory: 17006 grad_norm: 5.0083 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1903 loss: 1.1903 2022/10/13 10:57:06 - mmengine - INFO - Epoch(train) [86][480/940] lr: 1.0000e-04 eta: 1:55:59 time: 0.4999 data_time: 0.0271 memory: 17006 grad_norm: 4.9196 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3425 loss: 1.3425 2022/10/13 10:57:16 - mmengine - INFO - Epoch(train) [86][500/940] lr: 1.0000e-04 eta: 1:55:49 time: 0.5152 data_time: 0.0338 memory: 17006 grad_norm: 4.9823 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2730 loss: 1.2730 2022/10/13 10:57:26 - mmengine - INFO - Epoch(train) [86][520/940] lr: 1.0000e-04 eta: 1:55:39 time: 0.4709 data_time: 0.0292 memory: 17006 grad_norm: 4.8734 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2752 loss: 1.2752 2022/10/13 10:57:37 - mmengine - INFO - Epoch(train) [86][540/940] lr: 1.0000e-04 eta: 1:55:29 time: 0.5433 data_time: 0.0293 memory: 17006 grad_norm: 4.8214 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.3008 loss: 1.3008 2022/10/13 10:57:47 - mmengine - INFO - Epoch(train) [86][560/940] lr: 1.0000e-04 eta: 1:55:19 time: 0.5027 data_time: 0.0396 memory: 17006 grad_norm: 4.9853 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2462 loss: 1.2462 2022/10/13 10:57:58 - mmengine - INFO - Epoch(train) [86][580/940] lr: 1.0000e-04 eta: 1:55:09 time: 0.5676 data_time: 0.0319 memory: 17006 grad_norm: 5.0474 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4229 loss: 1.4229 2022/10/13 10:58:08 - mmengine - INFO - Epoch(train) [86][600/940] lr: 1.0000e-04 eta: 1:54:58 time: 0.4779 data_time: 0.0298 memory: 17006 grad_norm: 4.7870 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2637 loss: 1.2637 2022/10/13 10:58:18 - mmengine - INFO - Epoch(train) [86][620/940] lr: 1.0000e-04 eta: 1:54:48 time: 0.5087 data_time: 0.0300 memory: 17006 grad_norm: 4.9516 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3655 loss: 1.3655 2022/10/13 10:58:27 - mmengine - INFO - Epoch(train) [86][640/940] lr: 1.0000e-04 eta: 1:54:38 time: 0.4689 data_time: 0.0326 memory: 17006 grad_norm: 4.8380 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3663 loss: 1.3663 2022/10/13 10:58:38 - mmengine - INFO - Epoch(train) [86][660/940] lr: 1.0000e-04 eta: 1:54:28 time: 0.5632 data_time: 0.0361 memory: 17006 grad_norm: 4.9178 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4266 loss: 1.4266 2022/10/13 10:58:48 - mmengine - INFO - Epoch(train) [86][680/940] lr: 1.0000e-04 eta: 1:54:17 time: 0.4834 data_time: 0.0358 memory: 17006 grad_norm: 4.9003 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4184 loss: 1.4184 2022/10/13 10:58:59 - mmengine - INFO - Epoch(train) [86][700/940] lr: 1.0000e-04 eta: 1:54:07 time: 0.5345 data_time: 0.0346 memory: 17006 grad_norm: 4.9177 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3321 loss: 1.3321 2022/10/13 10:59:08 - mmengine - INFO - Epoch(train) [86][720/940] lr: 1.0000e-04 eta: 1:53:57 time: 0.4879 data_time: 0.0375 memory: 17006 grad_norm: 5.1197 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3701 loss: 1.3701 2022/10/13 10:59:19 - mmengine - INFO - Epoch(train) [86][740/940] lr: 1.0000e-04 eta: 1:53:47 time: 0.5060 data_time: 0.0408 memory: 17006 grad_norm: 4.9659 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1048 loss: 1.1048 2022/10/13 10:59:28 - mmengine - INFO - Epoch(train) [86][760/940] lr: 1.0000e-04 eta: 1:53:36 time: 0.4701 data_time: 0.0351 memory: 17006 grad_norm: 4.9123 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2282 loss: 1.2282 2022/10/13 10:59:39 - mmengine - INFO - Epoch(train) [86][780/940] lr: 1.0000e-04 eta: 1:53:26 time: 0.5292 data_time: 0.0342 memory: 17006 grad_norm: 4.9907 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2048 loss: 1.2048 2022/10/13 10:59:48 - mmengine - INFO - Epoch(train) [86][800/940] lr: 1.0000e-04 eta: 1:53:16 time: 0.4757 data_time: 0.0362 memory: 17006 grad_norm: 4.9292 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2926 loss: 1.2926 2022/10/13 10:59:59 - mmengine - INFO - Epoch(train) [86][820/940] lr: 1.0000e-04 eta: 1:53:06 time: 0.5591 data_time: 0.0343 memory: 17006 grad_norm: 4.9524 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2675 loss: 1.2675 2022/10/13 11:00:09 - mmengine - INFO - Epoch(train) [86][840/940] lr: 1.0000e-04 eta: 1:52:55 time: 0.4619 data_time: 0.0320 memory: 17006 grad_norm: 4.8529 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.0895 loss: 1.0895 2022/10/13 11:00:19 - mmengine - INFO - Epoch(train) [86][860/940] lr: 1.0000e-04 eta: 1:52:45 time: 0.5125 data_time: 0.0363 memory: 17006 grad_norm: 4.9687 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3673 loss: 1.3673 2022/10/13 11:00:28 - mmengine - INFO - Epoch(train) [86][880/940] lr: 1.0000e-04 eta: 1:52:35 time: 0.4656 data_time: 0.0261 memory: 17006 grad_norm: 4.8944 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2955 loss: 1.2955 2022/10/13 11:00:40 - mmengine - INFO - Epoch(train) [86][900/940] lr: 1.0000e-04 eta: 1:52:25 time: 0.5726 data_time: 0.0417 memory: 17006 grad_norm: 4.9947 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2562 loss: 1.2562 2022/10/13 11:00:49 - mmengine - INFO - Epoch(train) [86][920/940] lr: 1.0000e-04 eta: 1:52:14 time: 0.4708 data_time: 0.0262 memory: 17006 grad_norm: 4.9198 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2881 loss: 1.2881 2022/10/13 11:00:58 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 11:00:58 - mmengine - INFO - Epoch(train) [86][940/940] lr: 1.0000e-04 eta: 1:52:04 time: 0.4670 data_time: 0.0270 memory: 17006 grad_norm: 5.1383 top1_acc: 0.2857 top5_acc: 0.7143 loss_cls: 1.3137 loss: 1.3137 2022/10/13 11:01:11 - mmengine - INFO - Epoch(val) [86][20/78] eta: 0:00:36 time: 0.6255 data_time: 0.5311 memory: 3172 2022/10/13 11:01:20 - mmengine - INFO - Epoch(val) [86][40/78] eta: 0:00:16 time: 0.4362 data_time: 0.3425 memory: 3172 2022/10/13 11:01:31 - mmengine - INFO - Epoch(val) [86][60/78] eta: 0:00:10 time: 0.5698 data_time: 0.4765 memory: 3172 2022/10/13 11:01:41 - mmengine - INFO - Epoch(val) [86][78/78] acc/top1: 0.6736 acc/top5: 0.8698 acc/mean1: 0.6735 2022/10/13 11:01:56 - mmengine - INFO - Epoch(train) [87][20/940] lr: 1.0000e-04 eta: 1:51:54 time: 0.7404 data_time: 0.1863 memory: 17006 grad_norm: 4.8222 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2526 loss: 1.2526 2022/10/13 11:02:05 - mmengine - INFO - Epoch(train) [87][40/940] lr: 1.0000e-04 eta: 1:51:44 time: 0.4719 data_time: 0.0255 memory: 17006 grad_norm: 4.9711 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.2816 loss: 1.2816 2022/10/13 11:02:16 - mmengine - INFO - Epoch(train) [87][60/940] lr: 1.0000e-04 eta: 1:51:34 time: 0.5448 data_time: 0.0574 memory: 17006 grad_norm: 4.9540 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4288 loss: 1.4288 2022/10/13 11:02:26 - mmengine - INFO - Epoch(train) [87][80/940] lr: 1.0000e-04 eta: 1:51:24 time: 0.4678 data_time: 0.0245 memory: 17006 grad_norm: 4.8738 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.2098 loss: 1.2098 2022/10/13 11:02:37 - mmengine - INFO - Epoch(train) [87][100/940] lr: 1.0000e-04 eta: 1:51:14 time: 0.5736 data_time: 0.0409 memory: 17006 grad_norm: 4.9258 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2436 loss: 1.2436 2022/10/13 11:02:47 - mmengine - INFO - Epoch(train) [87][120/940] lr: 1.0000e-04 eta: 1:51:03 time: 0.4799 data_time: 0.0244 memory: 17006 grad_norm: 4.9843 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2375 loss: 1.2375 2022/10/13 11:02:57 - mmengine - INFO - Epoch(train) [87][140/940] lr: 1.0000e-04 eta: 1:50:53 time: 0.5378 data_time: 0.0358 memory: 17006 grad_norm: 4.8283 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2280 loss: 1.2280 2022/10/13 11:03:07 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 11:03:07 - mmengine - INFO - Epoch(train) [87][160/940] lr: 1.0000e-04 eta: 1:50:43 time: 0.4679 data_time: 0.0322 memory: 17006 grad_norm: 4.8744 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2252 loss: 1.2252 2022/10/13 11:03:17 - mmengine - INFO - Epoch(train) [87][180/940] lr: 1.0000e-04 eta: 1:50:33 time: 0.5273 data_time: 0.0385 memory: 17006 grad_norm: 4.8147 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2372 loss: 1.2372 2022/10/13 11:03:27 - mmengine - INFO - Epoch(train) [87][200/940] lr: 1.0000e-04 eta: 1:50:22 time: 0.4692 data_time: 0.0273 memory: 17006 grad_norm: 4.9486 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2217 loss: 1.2217 2022/10/13 11:03:37 - mmengine - INFO - Epoch(train) [87][220/940] lr: 1.0000e-04 eta: 1:50:12 time: 0.5253 data_time: 0.0364 memory: 17006 grad_norm: 4.9110 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2579 loss: 1.2579 2022/10/13 11:03:48 - mmengine - INFO - Epoch(train) [87][240/940] lr: 1.0000e-04 eta: 1:50:02 time: 0.5175 data_time: 0.0293 memory: 17006 grad_norm: 4.8587 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3004 loss: 1.3004 2022/10/13 11:03:58 - mmengine - INFO - Epoch(train) [87][260/940] lr: 1.0000e-04 eta: 1:49:52 time: 0.5275 data_time: 0.0372 memory: 17006 grad_norm: 4.9946 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1503 loss: 1.1503 2022/10/13 11:04:08 - mmengine - INFO - Epoch(train) [87][280/940] lr: 1.0000e-04 eta: 1:49:42 time: 0.5035 data_time: 0.0264 memory: 17006 grad_norm: 4.8394 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.0748 loss: 1.0748 2022/10/13 11:04:18 - mmengine - INFO - Epoch(train) [87][300/940] lr: 1.0000e-04 eta: 1:49:31 time: 0.5024 data_time: 0.0354 memory: 17006 grad_norm: 4.8563 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2723 loss: 1.2723 2022/10/13 11:04:28 - mmengine - INFO - Epoch(train) [87][320/940] lr: 1.0000e-04 eta: 1:49:21 time: 0.4776 data_time: 0.0267 memory: 17006 grad_norm: 4.8230 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.2517 loss: 1.2517 2022/10/13 11:04:38 - mmengine - INFO - Epoch(train) [87][340/940] lr: 1.0000e-04 eta: 1:49:11 time: 0.5192 data_time: 0.0330 memory: 17006 grad_norm: 4.8773 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.1688 loss: 1.1688 2022/10/13 11:04:48 - mmengine - INFO - Epoch(train) [87][360/940] lr: 1.0000e-04 eta: 1:49:00 time: 0.4986 data_time: 0.0270 memory: 17006 grad_norm: 4.7842 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2887 loss: 1.2887 2022/10/13 11:04:58 - mmengine - INFO - Epoch(train) [87][380/940] lr: 1.0000e-04 eta: 1:48:50 time: 0.5091 data_time: 0.0375 memory: 17006 grad_norm: 4.8926 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2648 loss: 1.2648 2022/10/13 11:05:07 - mmengine - INFO - Epoch(train) [87][400/940] lr: 1.0000e-04 eta: 1:48:40 time: 0.4547 data_time: 0.0326 memory: 17006 grad_norm: 4.9902 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3408 loss: 1.3408 2022/10/13 11:05:19 - mmengine - INFO - Epoch(train) [87][420/940] lr: 1.0000e-04 eta: 1:48:30 time: 0.5616 data_time: 0.0408 memory: 17006 grad_norm: 5.0189 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2989 loss: 1.2989 2022/10/13 11:05:29 - mmengine - INFO - Epoch(train) [87][440/940] lr: 1.0000e-04 eta: 1:48:20 time: 0.5193 data_time: 0.0241 memory: 17006 grad_norm: 4.8203 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1505 loss: 1.1505 2022/10/13 11:05:39 - mmengine - INFO - Epoch(train) [87][460/940] lr: 1.0000e-04 eta: 1:48:09 time: 0.4918 data_time: 0.0327 memory: 17006 grad_norm: 4.8372 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.1497 loss: 1.1497 2022/10/13 11:05:49 - mmengine - INFO - Epoch(train) [87][480/940] lr: 1.0000e-04 eta: 1:47:59 time: 0.4953 data_time: 0.0237 memory: 17006 grad_norm: 4.9308 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.2572 loss: 1.2572 2022/10/13 11:05:59 - mmengine - INFO - Epoch(train) [87][500/940] lr: 1.0000e-04 eta: 1:47:49 time: 0.5134 data_time: 0.0336 memory: 17006 grad_norm: 4.9331 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2324 loss: 1.2324 2022/10/13 11:06:09 - mmengine - INFO - Epoch(train) [87][520/940] lr: 1.0000e-04 eta: 1:47:39 time: 0.4686 data_time: 0.0276 memory: 17006 grad_norm: 4.7922 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.2051 loss: 1.2051 2022/10/13 11:06:19 - mmengine - INFO - Epoch(train) [87][540/940] lr: 1.0000e-04 eta: 1:47:28 time: 0.5116 data_time: 0.0323 memory: 17006 grad_norm: 4.9235 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2923 loss: 1.2923 2022/10/13 11:06:28 - mmengine - INFO - Epoch(train) [87][560/940] lr: 1.0000e-04 eta: 1:47:18 time: 0.4590 data_time: 0.0277 memory: 17006 grad_norm: 4.9912 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2299 loss: 1.2299 2022/10/13 11:06:39 - mmengine - INFO - Epoch(train) [87][580/940] lr: 1.0000e-04 eta: 1:47:08 time: 0.5416 data_time: 0.0325 memory: 17006 grad_norm: 5.0045 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3220 loss: 1.3220 2022/10/13 11:06:49 - mmengine - INFO - Epoch(train) [87][600/940] lr: 1.0000e-04 eta: 1:46:58 time: 0.5358 data_time: 0.0305 memory: 17006 grad_norm: 4.9786 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1242 loss: 1.1242 2022/10/13 11:06:59 - mmengine - INFO - Epoch(train) [87][620/940] lr: 1.0000e-04 eta: 1:46:47 time: 0.4826 data_time: 0.0303 memory: 17006 grad_norm: 4.9419 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2991 loss: 1.2991 2022/10/13 11:07:10 - mmengine - INFO - Epoch(train) [87][640/940] lr: 1.0000e-04 eta: 1:46:37 time: 0.5310 data_time: 0.0379 memory: 17006 grad_norm: 5.0420 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2711 loss: 1.2711 2022/10/13 11:07:20 - mmengine - INFO - Epoch(train) [87][660/940] lr: 1.0000e-04 eta: 1:46:27 time: 0.4913 data_time: 0.0333 memory: 17006 grad_norm: 4.9466 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.1915 loss: 1.1915 2022/10/13 11:07:30 - mmengine - INFO - Epoch(train) [87][680/940] lr: 1.0000e-04 eta: 1:46:17 time: 0.5394 data_time: 0.0346 memory: 17006 grad_norm: 4.9913 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2267 loss: 1.2267 2022/10/13 11:07:40 - mmengine - INFO - Epoch(train) [87][700/940] lr: 1.0000e-04 eta: 1:46:06 time: 0.4743 data_time: 0.0344 memory: 17006 grad_norm: 4.9382 top1_acc: 0.4062 top5_acc: 0.7188 loss_cls: 1.3873 loss: 1.3873 2022/10/13 11:07:51 - mmengine - INFO - Epoch(train) [87][720/940] lr: 1.0000e-04 eta: 1:45:56 time: 0.5457 data_time: 0.0310 memory: 17006 grad_norm: 4.8799 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1876 loss: 1.1876 2022/10/13 11:08:00 - mmengine - INFO - Epoch(train) [87][740/940] lr: 1.0000e-04 eta: 1:45:46 time: 0.4574 data_time: 0.0331 memory: 17006 grad_norm: 4.9099 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1179 loss: 1.1179 2022/10/13 11:08:11 - mmengine - INFO - Epoch(train) [87][760/940] lr: 1.0000e-04 eta: 1:45:36 time: 0.5367 data_time: 0.0317 memory: 17006 grad_norm: 4.8398 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2259 loss: 1.2259 2022/10/13 11:08:20 - mmengine - INFO - Epoch(train) [87][780/940] lr: 1.0000e-04 eta: 1:45:25 time: 0.4866 data_time: 0.0316 memory: 17006 grad_norm: 4.9760 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1574 loss: 1.1574 2022/10/13 11:08:31 - mmengine - INFO - Epoch(train) [87][800/940] lr: 1.0000e-04 eta: 1:45:15 time: 0.5361 data_time: 0.0359 memory: 17006 grad_norm: 4.8492 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2289 loss: 1.2289 2022/10/13 11:08:42 - mmengine - INFO - Epoch(train) [87][820/940] lr: 1.0000e-04 eta: 1:45:05 time: 0.5261 data_time: 0.0365 memory: 17006 grad_norm: 4.9473 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2617 loss: 1.2617 2022/10/13 11:08:52 - mmengine - INFO - Epoch(train) [87][840/940] lr: 1.0000e-04 eta: 1:44:55 time: 0.5113 data_time: 0.0326 memory: 17006 grad_norm: 4.9102 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2882 loss: 1.2882 2022/10/13 11:09:01 - mmengine - INFO - Epoch(train) [87][860/940] lr: 1.0000e-04 eta: 1:44:45 time: 0.4636 data_time: 0.0346 memory: 17006 grad_norm: 4.9214 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3481 loss: 1.3481 2022/10/13 11:09:12 - mmengine - INFO - Epoch(train) [87][880/940] lr: 1.0000e-04 eta: 1:44:34 time: 0.5242 data_time: 0.0339 memory: 17006 grad_norm: 4.9219 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1679 loss: 1.1679 2022/10/13 11:09:22 - mmengine - INFO - Epoch(train) [87][900/940] lr: 1.0000e-04 eta: 1:44:24 time: 0.5029 data_time: 0.0326 memory: 17006 grad_norm: 4.9951 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2078 loss: 1.2078 2022/10/13 11:09:32 - mmengine - INFO - Epoch(train) [87][920/940] lr: 1.0000e-04 eta: 1:44:14 time: 0.5199 data_time: 0.0332 memory: 17006 grad_norm: 4.8373 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2188 loss: 1.2188 2022/10/13 11:09:41 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 11:09:41 - mmengine - INFO - Epoch(train) [87][940/940] lr: 1.0000e-04 eta: 1:44:04 time: 0.4560 data_time: 0.0250 memory: 17006 grad_norm: 5.3698 top1_acc: 0.1429 top5_acc: 0.8571 loss_cls: 1.4122 loss: 1.4122 2022/10/13 11:09:41 - mmengine - INFO - Saving checkpoint at 87 epochs 2022/10/13 11:09:55 - mmengine - INFO - Epoch(val) [87][20/78] eta: 0:00:36 time: 0.6295 data_time: 0.5413 memory: 3172 2022/10/13 11:10:03 - mmengine - INFO - Epoch(val) [87][40/78] eta: 0:00:16 time: 0.4383 data_time: 0.3489 memory: 3172 2022/10/13 11:10:15 - mmengine - INFO - Epoch(val) [87][60/78] eta: 0:00:10 time: 0.5726 data_time: 0.4804 memory: 3172 2022/10/13 11:10:24 - mmengine - INFO - Epoch(val) [87][78/78] acc/top1: 0.6742 acc/top5: 0.8692 acc/mean1: 0.6741 2022/10/13 11:10:38 - mmengine - INFO - Epoch(train) [88][20/940] lr: 1.0000e-04 eta: 1:43:54 time: 0.6803 data_time: 0.2374 memory: 17006 grad_norm: 4.9499 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.1836 loss: 1.1836 2022/10/13 11:10:47 - mmengine - INFO - Epoch(train) [88][40/940] lr: 1.0000e-04 eta: 1:43:44 time: 0.4785 data_time: 0.0524 memory: 17006 grad_norm: 4.9789 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2240 loss: 1.2240 2022/10/13 11:10:58 - mmengine - INFO - Epoch(train) [88][60/940] lr: 1.0000e-04 eta: 1:43:33 time: 0.5574 data_time: 0.0711 memory: 17006 grad_norm: 4.9150 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2745 loss: 1.2745 2022/10/13 11:11:08 - mmengine - INFO - Epoch(train) [88][80/940] lr: 1.0000e-04 eta: 1:43:23 time: 0.4972 data_time: 0.0345 memory: 17006 grad_norm: 4.9737 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.3151 loss: 1.3151 2022/10/13 11:11:20 - mmengine - INFO - Epoch(train) [88][100/940] lr: 1.0000e-04 eta: 1:43:13 time: 0.5618 data_time: 0.0372 memory: 17006 grad_norm: 4.9102 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1831 loss: 1.1831 2022/10/13 11:11:29 - mmengine - INFO - Epoch(train) [88][120/940] lr: 1.0000e-04 eta: 1:43:03 time: 0.4892 data_time: 0.0264 memory: 17006 grad_norm: 4.9189 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1758 loss: 1.1758 2022/10/13 11:11:40 - mmengine - INFO - Epoch(train) [88][140/940] lr: 1.0000e-04 eta: 1:42:53 time: 0.5329 data_time: 0.0390 memory: 17006 grad_norm: 4.9773 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2524 loss: 1.2524 2022/10/13 11:11:51 - mmengine - INFO - Epoch(train) [88][160/940] lr: 1.0000e-04 eta: 1:42:43 time: 0.5252 data_time: 0.0248 memory: 17006 grad_norm: 4.9147 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3242 loss: 1.3242 2022/10/13 11:12:02 - mmengine - INFO - Epoch(train) [88][180/940] lr: 1.0000e-04 eta: 1:42:32 time: 0.5482 data_time: 0.0411 memory: 17006 grad_norm: 4.9369 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2661 loss: 1.2661 2022/10/13 11:12:11 - mmengine - INFO - Epoch(train) [88][200/940] lr: 1.0000e-04 eta: 1:42:22 time: 0.4950 data_time: 0.0294 memory: 17006 grad_norm: 4.8481 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.3061 loss: 1.3061 2022/10/13 11:12:22 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 11:12:22 - mmengine - INFO - Epoch(train) [88][220/940] lr: 1.0000e-04 eta: 1:42:12 time: 0.5263 data_time: 0.0334 memory: 17006 grad_norm: 4.8584 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.2043 loss: 1.2043 2022/10/13 11:12:32 - mmengine - INFO - Epoch(train) [88][240/940] lr: 1.0000e-04 eta: 1:42:02 time: 0.4792 data_time: 0.0314 memory: 17006 grad_norm: 4.9958 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3379 loss: 1.3379 2022/10/13 11:12:42 - mmengine - INFO - Epoch(train) [88][260/940] lr: 1.0000e-04 eta: 1:41:51 time: 0.5257 data_time: 0.0402 memory: 17006 grad_norm: 4.9338 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2938 loss: 1.2938 2022/10/13 11:12:52 - mmengine - INFO - Epoch(train) [88][280/940] lr: 1.0000e-04 eta: 1:41:41 time: 0.4780 data_time: 0.0336 memory: 17006 grad_norm: 4.8936 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2345 loss: 1.2345 2022/10/13 11:13:02 - mmengine - INFO - Epoch(train) [88][300/940] lr: 1.0000e-04 eta: 1:41:31 time: 0.5359 data_time: 0.0331 memory: 17006 grad_norm: 4.9273 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2660 loss: 1.2660 2022/10/13 11:13:13 - mmengine - INFO - Epoch(train) [88][320/940] lr: 1.0000e-04 eta: 1:41:21 time: 0.5077 data_time: 0.0356 memory: 17006 grad_norm: 4.8511 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2458 loss: 1.2458 2022/10/13 11:13:23 - mmengine - INFO - Epoch(train) [88][340/940] lr: 1.0000e-04 eta: 1:41:11 time: 0.5478 data_time: 0.0319 memory: 17006 grad_norm: 5.0340 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3118 loss: 1.3118 2022/10/13 11:13:33 - mmengine - INFO - Epoch(train) [88][360/940] lr: 1.0000e-04 eta: 1:41:00 time: 0.4556 data_time: 0.0351 memory: 17006 grad_norm: 4.9182 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2260 loss: 1.2260 2022/10/13 11:13:43 - mmengine - INFO - Epoch(train) [88][380/940] lr: 1.0000e-04 eta: 1:40:50 time: 0.5337 data_time: 0.0345 memory: 17006 grad_norm: 4.9609 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3868 loss: 1.3868 2022/10/13 11:13:53 - mmengine - INFO - Epoch(train) [88][400/940] lr: 1.0000e-04 eta: 1:40:40 time: 0.4691 data_time: 0.0359 memory: 17006 grad_norm: 4.8244 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2668 loss: 1.2668 2022/10/13 11:14:03 - mmengine - INFO - Epoch(train) [88][420/940] lr: 1.0000e-04 eta: 1:40:30 time: 0.5239 data_time: 0.0304 memory: 17006 grad_norm: 4.8975 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3278 loss: 1.3278 2022/10/13 11:14:12 - mmengine - INFO - Epoch(train) [88][440/940] lr: 1.0000e-04 eta: 1:40:19 time: 0.4503 data_time: 0.0328 memory: 17006 grad_norm: 4.8886 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.1456 loss: 1.1456 2022/10/13 11:14:24 - mmengine - INFO - Epoch(train) [88][460/940] lr: 1.0000e-04 eta: 1:40:09 time: 0.5704 data_time: 0.0317 memory: 17006 grad_norm: 4.9255 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.2649 loss: 1.2649 2022/10/13 11:14:34 - mmengine - INFO - Epoch(train) [88][480/940] lr: 1.0000e-04 eta: 1:39:59 time: 0.4965 data_time: 0.0384 memory: 17006 grad_norm: 4.9014 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2050 loss: 1.2050 2022/10/13 11:14:45 - mmengine - INFO - Epoch(train) [88][500/940] lr: 1.0000e-04 eta: 1:39:49 time: 0.5541 data_time: 0.0315 memory: 17006 grad_norm: 4.9885 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3622 loss: 1.3622 2022/10/13 11:14:54 - mmengine - INFO - Epoch(train) [88][520/940] lr: 1.0000e-04 eta: 1:39:38 time: 0.4476 data_time: 0.0349 memory: 17006 grad_norm: 4.9607 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2224 loss: 1.2224 2022/10/13 11:15:05 - mmengine - INFO - Epoch(train) [88][540/940] lr: 1.0000e-04 eta: 1:39:28 time: 0.5673 data_time: 0.0325 memory: 17006 grad_norm: 4.9685 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2621 loss: 1.2621 2022/10/13 11:15:14 - mmengine - INFO - Epoch(train) [88][560/940] lr: 1.0000e-04 eta: 1:39:18 time: 0.4572 data_time: 0.0380 memory: 17006 grad_norm: 4.9187 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1541 loss: 1.1541 2022/10/13 11:15:25 - mmengine - INFO - Epoch(train) [88][580/940] lr: 1.0000e-04 eta: 1:39:08 time: 0.5469 data_time: 0.0316 memory: 17006 grad_norm: 4.8803 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1737 loss: 1.1737 2022/10/13 11:15:34 - mmengine - INFO - Epoch(train) [88][600/940] lr: 1.0000e-04 eta: 1:38:57 time: 0.4528 data_time: 0.0338 memory: 17006 grad_norm: 5.0211 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3148 loss: 1.3148 2022/10/13 11:15:44 - mmengine - INFO - Epoch(train) [88][620/940] lr: 1.0000e-04 eta: 1:38:47 time: 0.4775 data_time: 0.0312 memory: 17006 grad_norm: 5.0174 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2771 loss: 1.2771 2022/10/13 11:15:54 - mmengine - INFO - Epoch(train) [88][640/940] lr: 1.0000e-04 eta: 1:38:37 time: 0.5396 data_time: 0.0375 memory: 17006 grad_norm: 4.9184 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3409 loss: 1.3409 2022/10/13 11:16:04 - mmengine - INFO - Epoch(train) [88][660/940] lr: 1.0000e-04 eta: 1:38:27 time: 0.4965 data_time: 0.0366 memory: 17006 grad_norm: 4.8971 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.2544 loss: 1.2544 2022/10/13 11:16:14 - mmengine - INFO - Epoch(train) [88][680/940] lr: 1.0000e-04 eta: 1:38:16 time: 0.4855 data_time: 0.0359 memory: 17006 grad_norm: 4.9673 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.1713 loss: 1.1713 2022/10/13 11:16:25 - mmengine - INFO - Epoch(train) [88][700/940] lr: 1.0000e-04 eta: 1:38:06 time: 0.5285 data_time: 0.0283 memory: 17006 grad_norm: 4.8430 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1475 loss: 1.1475 2022/10/13 11:16:35 - mmengine - INFO - Epoch(train) [88][720/940] lr: 1.0000e-04 eta: 1:37:56 time: 0.5402 data_time: 0.0348 memory: 17006 grad_norm: 4.9538 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1905 loss: 1.1905 2022/10/13 11:16:45 - mmengine - INFO - Epoch(train) [88][740/940] lr: 1.0000e-04 eta: 1:37:46 time: 0.4875 data_time: 0.0353 memory: 17006 grad_norm: 4.8809 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2448 loss: 1.2448 2022/10/13 11:16:55 - mmengine - INFO - Epoch(train) [88][760/940] lr: 1.0000e-04 eta: 1:37:36 time: 0.4723 data_time: 0.0331 memory: 17006 grad_norm: 4.8876 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3445 loss: 1.3445 2022/10/13 11:17:05 - mmengine - INFO - Epoch(train) [88][780/940] lr: 1.0000e-04 eta: 1:37:25 time: 0.5147 data_time: 0.0376 memory: 17006 grad_norm: 4.9320 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3127 loss: 1.3127 2022/10/13 11:17:15 - mmengine - INFO - Epoch(train) [88][800/940] lr: 1.0000e-04 eta: 1:37:15 time: 0.4831 data_time: 0.0366 memory: 17006 grad_norm: 4.8443 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2275 loss: 1.2275 2022/10/13 11:17:24 - mmengine - INFO - Epoch(train) [88][820/940] lr: 1.0000e-04 eta: 1:37:05 time: 0.4957 data_time: 0.0328 memory: 17006 grad_norm: 4.8274 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3627 loss: 1.3627 2022/10/13 11:17:35 - mmengine - INFO - Epoch(train) [88][840/940] lr: 1.0000e-04 eta: 1:36:55 time: 0.5460 data_time: 0.0328 memory: 17006 grad_norm: 4.9303 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4043 loss: 1.4043 2022/10/13 11:17:46 - mmengine - INFO - Epoch(train) [88][860/940] lr: 1.0000e-04 eta: 1:36:44 time: 0.5195 data_time: 0.0326 memory: 17006 grad_norm: 4.8813 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2990 loss: 1.2990 2022/10/13 11:17:56 - mmengine - INFO - Epoch(train) [88][880/940] lr: 1.0000e-04 eta: 1:36:34 time: 0.5014 data_time: 0.0346 memory: 17006 grad_norm: 4.9539 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2430 loss: 1.2430 2022/10/13 11:18:06 - mmengine - INFO - Epoch(train) [88][900/940] lr: 1.0000e-04 eta: 1:36:24 time: 0.5276 data_time: 0.0337 memory: 17006 grad_norm: 4.9213 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2659 loss: 1.2659 2022/10/13 11:18:16 - mmengine - INFO - Epoch(train) [88][920/940] lr: 1.0000e-04 eta: 1:36:14 time: 0.5020 data_time: 0.0258 memory: 17006 grad_norm: 4.8922 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1051 loss: 1.1051 2022/10/13 11:18:26 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 11:18:26 - mmengine - INFO - Epoch(train) [88][940/940] lr: 1.0000e-04 eta: 1:36:03 time: 0.4860 data_time: 0.0251 memory: 17006 grad_norm: 5.1045 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.3234 loss: 1.3234 2022/10/13 11:18:39 - mmengine - INFO - Epoch(val) [88][20/78] eta: 0:00:36 time: 0.6373 data_time: 0.5427 memory: 3172 2022/10/13 11:18:48 - mmengine - INFO - Epoch(val) [88][40/78] eta: 0:00:17 time: 0.4475 data_time: 0.3548 memory: 3172 2022/10/13 11:18:59 - mmengine - INFO - Epoch(val) [88][60/78] eta: 0:00:10 time: 0.5621 data_time: 0.4710 memory: 3172 2022/10/13 11:19:09 - mmengine - INFO - Epoch(val) [88][78/78] acc/top1: 0.6750 acc/top5: 0.8706 acc/mean1: 0.6750 2022/10/13 11:19:23 - mmengine - INFO - Epoch(train) [89][20/940] lr: 1.0000e-04 eta: 1:35:54 time: 0.6804 data_time: 0.3363 memory: 17006 grad_norm: 4.8166 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2259 loss: 1.2259 2022/10/13 11:19:32 - mmengine - INFO - Epoch(train) [89][40/940] lr: 1.0000e-04 eta: 1:35:43 time: 0.4887 data_time: 0.0769 memory: 17006 grad_norm: 5.0670 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3039 loss: 1.3039 2022/10/13 11:19:44 - mmengine - INFO - Epoch(train) [89][60/940] lr: 1.0000e-04 eta: 1:35:33 time: 0.5642 data_time: 0.0373 memory: 17006 grad_norm: 4.8459 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.0928 loss: 1.0928 2022/10/13 11:19:54 - mmengine - INFO - Epoch(train) [89][80/940] lr: 1.0000e-04 eta: 1:35:23 time: 0.4956 data_time: 0.0319 memory: 17006 grad_norm: 4.9994 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2732 loss: 1.2732 2022/10/13 11:20:04 - mmengine - INFO - Epoch(train) [89][100/940] lr: 1.0000e-04 eta: 1:35:13 time: 0.4991 data_time: 0.0306 memory: 17006 grad_norm: 4.8511 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1258 loss: 1.1258 2022/10/13 11:20:13 - mmengine - INFO - Epoch(train) [89][120/940] lr: 1.0000e-04 eta: 1:35:03 time: 0.4664 data_time: 0.0805 memory: 17006 grad_norm: 4.9250 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.3369 loss: 1.3369 2022/10/13 11:20:24 - mmengine - INFO - Epoch(train) [89][140/940] lr: 1.0000e-04 eta: 1:34:52 time: 0.5511 data_time: 0.0969 memory: 17006 grad_norm: 4.9336 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1777 loss: 1.1777 2022/10/13 11:20:33 - mmengine - INFO - Epoch(train) [89][160/940] lr: 1.0000e-04 eta: 1:34:42 time: 0.4718 data_time: 0.1318 memory: 17006 grad_norm: 4.9042 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.3384 loss: 1.3384 2022/10/13 11:20:44 - mmengine - INFO - Epoch(train) [89][180/940] lr: 1.0000e-04 eta: 1:34:32 time: 0.5216 data_time: 0.1108 memory: 17006 grad_norm: 5.0159 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3176 loss: 1.3176 2022/10/13 11:20:53 - mmengine - INFO - Epoch(train) [89][200/940] lr: 1.0000e-04 eta: 1:34:22 time: 0.4539 data_time: 0.0588 memory: 17006 grad_norm: 4.9851 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2985 loss: 1.2985 2022/10/13 11:21:04 - mmengine - INFO - Epoch(train) [89][220/940] lr: 1.0000e-04 eta: 1:34:11 time: 0.5459 data_time: 0.0886 memory: 17006 grad_norm: 4.9216 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1469 loss: 1.1469 2022/10/13 11:21:14 - mmengine - INFO - Epoch(train) [89][240/940] lr: 1.0000e-04 eta: 1:34:01 time: 0.5010 data_time: 0.0478 memory: 17006 grad_norm: 4.9527 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.2287 loss: 1.2287 2022/10/13 11:21:25 - mmengine - INFO - Epoch(train) [89][260/940] lr: 1.0000e-04 eta: 1:33:51 time: 0.5428 data_time: 0.0419 memory: 17006 grad_norm: 4.9182 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2853 loss: 1.2853 2022/10/13 11:21:35 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 11:21:35 - mmengine - INFO - Epoch(train) [89][280/940] lr: 1.0000e-04 eta: 1:33:41 time: 0.4899 data_time: 0.0283 memory: 17006 grad_norm: 5.0522 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2941 loss: 1.2941 2022/10/13 11:21:45 - mmengine - INFO - Epoch(train) [89][300/940] lr: 1.0000e-04 eta: 1:33:31 time: 0.5164 data_time: 0.0765 memory: 17006 grad_norm: 4.8529 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2515 loss: 1.2515 2022/10/13 11:21:55 - mmengine - INFO - Epoch(train) [89][320/940] lr: 1.0000e-04 eta: 1:33:20 time: 0.5183 data_time: 0.1083 memory: 17006 grad_norm: 4.8947 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.2479 loss: 1.2479 2022/10/13 11:22:06 - mmengine - INFO - Epoch(train) [89][340/940] lr: 1.0000e-04 eta: 1:33:10 time: 0.5138 data_time: 0.0993 memory: 17006 grad_norm: 4.9878 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3797 loss: 1.3797 2022/10/13 11:22:15 - mmengine - INFO - Epoch(train) [89][360/940] lr: 1.0000e-04 eta: 1:33:00 time: 0.4556 data_time: 0.0480 memory: 17006 grad_norm: 4.9268 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.3478 loss: 1.3478 2022/10/13 11:22:25 - mmengine - INFO - Epoch(train) [89][380/940] lr: 1.0000e-04 eta: 1:32:49 time: 0.4991 data_time: 0.1036 memory: 17006 grad_norm: 4.8966 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.0809 loss: 1.0809 2022/10/13 11:22:35 - mmengine - INFO - Epoch(train) [89][400/940] lr: 1.0000e-04 eta: 1:32:39 time: 0.5109 data_time: 0.1415 memory: 17006 grad_norm: 4.8868 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.2655 loss: 1.2655 2022/10/13 11:22:45 - mmengine - INFO - Epoch(train) [89][420/940] lr: 1.0000e-04 eta: 1:32:29 time: 0.5123 data_time: 0.1356 memory: 17006 grad_norm: 4.9813 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3726 loss: 1.3726 2022/10/13 11:22:55 - mmengine - INFO - Epoch(train) [89][440/940] lr: 1.0000e-04 eta: 1:32:19 time: 0.5098 data_time: 0.0336 memory: 17006 grad_norm: 4.9492 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2734 loss: 1.2734 2022/10/13 11:23:05 - mmengine - INFO - Epoch(train) [89][460/940] lr: 1.0000e-04 eta: 1:32:09 time: 0.4972 data_time: 0.0472 memory: 17006 grad_norm: 4.8133 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3211 loss: 1.3211 2022/10/13 11:23:15 - mmengine - INFO - Epoch(train) [89][480/940] lr: 1.0000e-04 eta: 1:31:58 time: 0.4966 data_time: 0.0289 memory: 17006 grad_norm: 4.9977 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2817 loss: 1.2817 2022/10/13 11:23:25 - mmengine - INFO - Epoch(train) [89][500/940] lr: 1.0000e-04 eta: 1:31:48 time: 0.5077 data_time: 0.0437 memory: 17006 grad_norm: 4.9163 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3070 loss: 1.3070 2022/10/13 11:23:35 - mmengine - INFO - Epoch(train) [89][520/940] lr: 1.0000e-04 eta: 1:31:38 time: 0.4732 data_time: 0.0316 memory: 17006 grad_norm: 4.9146 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1991 loss: 1.1991 2022/10/13 11:23:45 - mmengine - INFO - Epoch(train) [89][540/940] lr: 1.0000e-04 eta: 1:31:28 time: 0.5209 data_time: 0.0846 memory: 17006 grad_norm: 4.9506 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3030 loss: 1.3030 2022/10/13 11:23:56 - mmengine - INFO - Epoch(train) [89][560/940] lr: 1.0000e-04 eta: 1:31:17 time: 0.5233 data_time: 0.0323 memory: 17006 grad_norm: 4.8763 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.1619 loss: 1.1619 2022/10/13 11:24:06 - mmengine - INFO - Epoch(train) [89][580/940] lr: 1.0000e-04 eta: 1:31:07 time: 0.4980 data_time: 0.0321 memory: 17006 grad_norm: 5.0004 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2366 loss: 1.2366 2022/10/13 11:24:17 - mmengine - INFO - Epoch(train) [89][600/940] lr: 1.0000e-04 eta: 1:30:57 time: 0.5514 data_time: 0.0377 memory: 17006 grad_norm: 4.8739 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2541 loss: 1.2541 2022/10/13 11:24:26 - mmengine - INFO - Epoch(train) [89][620/940] lr: 1.0000e-04 eta: 1:30:47 time: 0.4780 data_time: 0.0261 memory: 17006 grad_norm: 5.0018 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2179 loss: 1.2179 2022/10/13 11:24:38 - mmengine - INFO - Epoch(train) [89][640/940] lr: 1.0000e-04 eta: 1:30:37 time: 0.5698 data_time: 0.0411 memory: 17006 grad_norm: 4.8961 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2188 loss: 1.2188 2022/10/13 11:24:47 - mmengine - INFO - Epoch(train) [89][660/940] lr: 1.0000e-04 eta: 1:30:26 time: 0.4554 data_time: 0.0291 memory: 17006 grad_norm: 4.9889 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.2489 loss: 1.2489 2022/10/13 11:24:58 - mmengine - INFO - Epoch(train) [89][680/940] lr: 1.0000e-04 eta: 1:30:16 time: 0.5502 data_time: 0.0364 memory: 17006 grad_norm: 4.9478 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1569 loss: 1.1569 2022/10/13 11:25:08 - mmengine - INFO - Epoch(train) [89][700/940] lr: 1.0000e-04 eta: 1:30:06 time: 0.4930 data_time: 0.0294 memory: 17006 grad_norm: 4.9858 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3162 loss: 1.3162 2022/10/13 11:25:18 - mmengine - INFO - Epoch(train) [89][720/940] lr: 1.0000e-04 eta: 1:29:56 time: 0.5398 data_time: 0.0391 memory: 17006 grad_norm: 4.9127 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1319 loss: 1.1319 2022/10/13 11:25:27 - mmengine - INFO - Epoch(train) [89][740/940] lr: 1.0000e-04 eta: 1:29:45 time: 0.4512 data_time: 0.0315 memory: 17006 grad_norm: 4.9471 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2871 loss: 1.2871 2022/10/13 11:25:39 - mmengine - INFO - Epoch(train) [89][760/940] lr: 1.0000e-04 eta: 1:29:35 time: 0.5732 data_time: 0.0339 memory: 17006 grad_norm: 4.9952 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3434 loss: 1.3434 2022/10/13 11:25:48 - mmengine - INFO - Epoch(train) [89][780/940] lr: 1.0000e-04 eta: 1:29:25 time: 0.4555 data_time: 0.0426 memory: 17006 grad_norm: 4.9298 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2487 loss: 1.2487 2022/10/13 11:25:58 - mmengine - INFO - Epoch(train) [89][800/940] lr: 1.0000e-04 eta: 1:29:15 time: 0.5183 data_time: 0.0338 memory: 17006 grad_norm: 5.0428 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2799 loss: 1.2799 2022/10/13 11:26:08 - mmengine - INFO - Epoch(train) [89][820/940] lr: 1.0000e-04 eta: 1:29:04 time: 0.4739 data_time: 0.0360 memory: 17006 grad_norm: 5.0024 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2063 loss: 1.2063 2022/10/13 11:26:20 - mmengine - INFO - Epoch(train) [89][840/940] lr: 1.0000e-04 eta: 1:28:54 time: 0.5824 data_time: 0.0346 memory: 17006 grad_norm: 4.9547 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2271 loss: 1.2271 2022/10/13 11:26:30 - mmengine - INFO - Epoch(train) [89][860/940] lr: 1.0000e-04 eta: 1:28:44 time: 0.5089 data_time: 0.0315 memory: 17006 grad_norm: 4.9306 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.3183 loss: 1.3183 2022/10/13 11:26:40 - mmengine - INFO - Epoch(train) [89][880/940] lr: 1.0000e-04 eta: 1:28:34 time: 0.4943 data_time: 0.0386 memory: 17006 grad_norm: 4.9365 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.2586 loss: 1.2586 2022/10/13 11:26:50 - mmengine - INFO - Epoch(train) [89][900/940] lr: 1.0000e-04 eta: 1:28:24 time: 0.5092 data_time: 0.0324 memory: 17006 grad_norm: 4.9702 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3107 loss: 1.3107 2022/10/13 11:27:01 - mmengine - INFO - Epoch(train) [89][920/940] lr: 1.0000e-04 eta: 1:28:14 time: 0.5527 data_time: 0.0374 memory: 17006 grad_norm: 4.9099 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2163 loss: 1.2163 2022/10/13 11:27:10 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 11:27:10 - mmengine - INFO - Epoch(train) [89][940/940] lr: 1.0000e-04 eta: 1:28:03 time: 0.4337 data_time: 0.0214 memory: 17006 grad_norm: 5.4374 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.3123 loss: 1.3123 2022/10/13 11:27:22 - mmengine - INFO - Epoch(val) [89][20/78] eta: 0:00:36 time: 0.6309 data_time: 0.5350 memory: 3172 2022/10/13 11:27:31 - mmengine - INFO - Epoch(val) [89][40/78] eta: 0:00:16 time: 0.4329 data_time: 0.3396 memory: 3172 2022/10/13 11:27:42 - mmengine - INFO - Epoch(val) [89][60/78] eta: 0:00:10 time: 0.5824 data_time: 0.4917 memory: 3172 2022/10/13 11:27:52 - mmengine - INFO - Epoch(val) [89][78/78] acc/top1: 0.6752 acc/top5: 0.8700 acc/mean1: 0.6751 2022/10/13 11:28:06 - mmengine - INFO - Epoch(train) [90][20/940] lr: 1.0000e-04 eta: 1:27:53 time: 0.7067 data_time: 0.2566 memory: 17006 grad_norm: 4.9316 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3556 loss: 1.3556 2022/10/13 11:28:16 - mmengine - INFO - Epoch(train) [90][40/940] lr: 1.0000e-04 eta: 1:27:43 time: 0.4524 data_time: 0.0303 memory: 17006 grad_norm: 4.9006 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2651 loss: 1.2651 2022/10/13 11:28:27 - mmengine - INFO - Epoch(train) [90][60/940] lr: 1.0000e-04 eta: 1:27:33 time: 0.5637 data_time: 0.0307 memory: 17006 grad_norm: 4.9824 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4843 loss: 1.4843 2022/10/13 11:28:37 - mmengine - INFO - Epoch(train) [90][80/940] lr: 1.0000e-04 eta: 1:27:23 time: 0.4930 data_time: 0.0388 memory: 17006 grad_norm: 4.9462 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3401 loss: 1.3401 2022/10/13 11:28:47 - mmengine - INFO - Epoch(train) [90][100/940] lr: 1.0000e-04 eta: 1:27:12 time: 0.5156 data_time: 0.0656 memory: 17006 grad_norm: 4.9455 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2318 loss: 1.2318 2022/10/13 11:28:57 - mmengine - INFO - Epoch(train) [90][120/940] lr: 1.0000e-04 eta: 1:27:02 time: 0.4838 data_time: 0.0443 memory: 17006 grad_norm: 5.0599 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2899 loss: 1.2899 2022/10/13 11:29:08 - mmengine - INFO - Epoch(train) [90][140/940] lr: 1.0000e-04 eta: 1:26:52 time: 0.5765 data_time: 0.0346 memory: 17006 grad_norm: 4.9512 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.3221 loss: 1.3221 2022/10/13 11:29:18 - mmengine - INFO - Epoch(train) [90][160/940] lr: 1.0000e-04 eta: 1:26:42 time: 0.4861 data_time: 0.0328 memory: 17006 grad_norm: 5.0253 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2604 loss: 1.2604 2022/10/13 11:29:29 - mmengine - INFO - Epoch(train) [90][180/940] lr: 1.0000e-04 eta: 1:26:32 time: 0.5505 data_time: 0.0320 memory: 17006 grad_norm: 5.0418 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1340 loss: 1.1340 2022/10/13 11:29:38 - mmengine - INFO - Epoch(train) [90][200/940] lr: 1.0000e-04 eta: 1:26:21 time: 0.4618 data_time: 0.0344 memory: 17006 grad_norm: 4.8912 top1_acc: 0.9375 top5_acc: 0.9688 loss_cls: 1.2842 loss: 1.2842 2022/10/13 11:29:49 - mmengine - INFO - Epoch(train) [90][220/940] lr: 1.0000e-04 eta: 1:26:11 time: 0.5353 data_time: 0.0324 memory: 17006 grad_norm: 4.9424 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2693 loss: 1.2693 2022/10/13 11:29:59 - mmengine - INFO - Epoch(train) [90][240/940] lr: 1.0000e-04 eta: 1:26:01 time: 0.4862 data_time: 0.0357 memory: 17006 grad_norm: 5.0428 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3194 loss: 1.3194 2022/10/13 11:30:10 - mmengine - INFO - Epoch(train) [90][260/940] lr: 1.0000e-04 eta: 1:25:51 time: 0.5474 data_time: 0.0314 memory: 17006 grad_norm: 4.8948 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2433 loss: 1.2433 2022/10/13 11:30:20 - mmengine - INFO - Epoch(train) [90][280/940] lr: 1.0000e-04 eta: 1:25:41 time: 0.5053 data_time: 0.0360 memory: 17006 grad_norm: 5.0312 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2461 loss: 1.2461 2022/10/13 11:30:30 - mmengine - INFO - Epoch(train) [90][300/940] lr: 1.0000e-04 eta: 1:25:30 time: 0.5196 data_time: 0.0321 memory: 17006 grad_norm: 4.9801 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.2964 loss: 1.2964 2022/10/13 11:30:39 - mmengine - INFO - Epoch(train) [90][320/940] lr: 1.0000e-04 eta: 1:25:20 time: 0.4497 data_time: 0.0291 memory: 17006 grad_norm: 4.9838 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2130 loss: 1.2130 2022/10/13 11:30:50 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 11:30:50 - mmengine - INFO - Epoch(train) [90][340/940] lr: 1.0000e-04 eta: 1:25:10 time: 0.5438 data_time: 0.0363 memory: 17006 grad_norm: 5.0268 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2975 loss: 1.2975 2022/10/13 11:31:00 - mmengine - INFO - Epoch(train) [90][360/940] lr: 1.0000e-04 eta: 1:25:00 time: 0.5069 data_time: 0.0496 memory: 17006 grad_norm: 4.9622 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1845 loss: 1.1845 2022/10/13 11:31:11 - mmengine - INFO - Epoch(train) [90][380/940] lr: 1.0000e-04 eta: 1:24:50 time: 0.5597 data_time: 0.0307 memory: 17006 grad_norm: 4.9433 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2811 loss: 1.2811 2022/10/13 11:31:21 - mmengine - INFO - Epoch(train) [90][400/940] lr: 1.0000e-04 eta: 1:24:39 time: 0.4705 data_time: 0.0299 memory: 17006 grad_norm: 4.9298 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3046 loss: 1.3046 2022/10/13 11:31:31 - mmengine - INFO - Epoch(train) [90][420/940] lr: 1.0000e-04 eta: 1:24:29 time: 0.5375 data_time: 0.0290 memory: 17006 grad_norm: 4.9637 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.2618 loss: 1.2618 2022/10/13 11:31:41 - mmengine - INFO - Epoch(train) [90][440/940] lr: 1.0000e-04 eta: 1:24:19 time: 0.4703 data_time: 0.0364 memory: 17006 grad_norm: 4.9811 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2297 loss: 1.2297 2022/10/13 11:31:51 - mmengine - INFO - Epoch(train) [90][460/940] lr: 1.0000e-04 eta: 1:24:09 time: 0.5180 data_time: 0.0258 memory: 17006 grad_norm: 4.9484 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2471 loss: 1.2471 2022/10/13 11:32:00 - mmengine - INFO - Epoch(train) [90][480/940] lr: 1.0000e-04 eta: 1:23:58 time: 0.4482 data_time: 0.0323 memory: 17006 grad_norm: 4.8617 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2615 loss: 1.2615 2022/10/13 11:32:11 - mmengine - INFO - Epoch(train) [90][500/940] lr: 1.0000e-04 eta: 1:23:48 time: 0.5315 data_time: 0.0348 memory: 17006 grad_norm: 5.0108 top1_acc: 0.7188 top5_acc: 0.7500 loss_cls: 1.4268 loss: 1.4268 2022/10/13 11:32:21 - mmengine - INFO - Epoch(train) [90][520/940] lr: 1.0000e-04 eta: 1:23:38 time: 0.4955 data_time: 0.0386 memory: 17006 grad_norm: 4.9051 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1631 loss: 1.1631 2022/10/13 11:32:32 - mmengine - INFO - Epoch(train) [90][540/940] lr: 1.0000e-04 eta: 1:23:28 time: 0.5527 data_time: 0.0327 memory: 17006 grad_norm: 4.9560 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3383 loss: 1.3383 2022/10/13 11:32:42 - mmengine - INFO - Epoch(train) [90][560/940] lr: 1.0000e-04 eta: 1:23:17 time: 0.4881 data_time: 0.0325 memory: 17006 grad_norm: 5.0390 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2802 loss: 1.2802 2022/10/13 11:32:52 - mmengine - INFO - Epoch(train) [90][580/940] lr: 1.0000e-04 eta: 1:23:07 time: 0.5194 data_time: 0.0324 memory: 17006 grad_norm: 4.9611 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1883 loss: 1.1883 2022/10/13 11:33:01 - mmengine - INFO - Epoch(train) [90][600/940] lr: 1.0000e-04 eta: 1:22:57 time: 0.4686 data_time: 0.0300 memory: 17006 grad_norm: 4.9861 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2729 loss: 1.2729 2022/10/13 11:33:12 - mmengine - INFO - Epoch(train) [90][620/940] lr: 1.0000e-04 eta: 1:22:47 time: 0.5467 data_time: 0.0320 memory: 17006 grad_norm: 4.9476 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2983 loss: 1.2983 2022/10/13 11:33:22 - mmengine - INFO - Epoch(train) [90][640/940] lr: 1.0000e-04 eta: 1:22:36 time: 0.4766 data_time: 0.0273 memory: 17006 grad_norm: 4.8381 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1075 loss: 1.1075 2022/10/13 11:33:33 - mmengine - INFO - Epoch(train) [90][660/940] lr: 1.0000e-04 eta: 1:22:26 time: 0.5419 data_time: 0.0362 memory: 17006 grad_norm: 4.9712 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3099 loss: 1.3099 2022/10/13 11:33:44 - mmengine - INFO - Epoch(train) [90][680/940] lr: 1.0000e-04 eta: 1:22:16 time: 0.5783 data_time: 0.0271 memory: 17006 grad_norm: 4.9813 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1705 loss: 1.1705 2022/10/13 11:33:53 - mmengine - INFO - Epoch(train) [90][700/940] lr: 1.0000e-04 eta: 1:22:06 time: 0.4529 data_time: 0.0275 memory: 17006 grad_norm: 4.8989 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1613 loss: 1.1613 2022/10/13 11:34:04 - mmengine - INFO - Epoch(train) [90][720/940] lr: 1.0000e-04 eta: 1:21:56 time: 0.5292 data_time: 0.0328 memory: 17006 grad_norm: 4.8457 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2781 loss: 1.2781 2022/10/13 11:34:14 - mmengine - INFO - Epoch(train) [90][740/940] lr: 1.0000e-04 eta: 1:21:45 time: 0.5152 data_time: 0.0335 memory: 17006 grad_norm: 4.9610 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.2256 loss: 1.2256 2022/10/13 11:34:25 - mmengine - INFO - Epoch(train) [90][760/940] lr: 1.0000e-04 eta: 1:21:35 time: 0.5256 data_time: 0.0329 memory: 17006 grad_norm: 4.8573 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2504 loss: 1.2504 2022/10/13 11:34:35 - mmengine - INFO - Epoch(train) [90][780/940] lr: 1.0000e-04 eta: 1:21:25 time: 0.5195 data_time: 0.0337 memory: 17006 grad_norm: 4.8417 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1907 loss: 1.1907 2022/10/13 11:34:46 - mmengine - INFO - Epoch(train) [90][800/940] lr: 1.0000e-04 eta: 1:21:15 time: 0.5547 data_time: 0.0326 memory: 17006 grad_norm: 4.8923 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2598 loss: 1.2598 2022/10/13 11:34:56 - mmengine - INFO - Epoch(train) [90][820/940] lr: 1.0000e-04 eta: 1:21:05 time: 0.5075 data_time: 0.0286 memory: 17006 grad_norm: 4.9870 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2518 loss: 1.2518 2022/10/13 11:35:06 - mmengine - INFO - Epoch(train) [90][840/940] lr: 1.0000e-04 eta: 1:20:54 time: 0.5090 data_time: 0.0343 memory: 17006 grad_norm: 4.9547 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3114 loss: 1.3114 2022/10/13 11:35:17 - mmengine - INFO - Epoch(train) [90][860/940] lr: 1.0000e-04 eta: 1:20:44 time: 0.5234 data_time: 0.0319 memory: 17006 grad_norm: 4.8713 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.1726 loss: 1.1726 2022/10/13 11:35:27 - mmengine - INFO - Epoch(train) [90][880/940] lr: 1.0000e-04 eta: 1:20:34 time: 0.5104 data_time: 0.0330 memory: 17006 grad_norm: 4.9071 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2644 loss: 1.2644 2022/10/13 11:35:36 - mmengine - INFO - Epoch(train) [90][900/940] lr: 1.0000e-04 eta: 1:20:24 time: 0.4280 data_time: 0.0340 memory: 17006 grad_norm: 4.9770 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2202 loss: 1.2202 2022/10/13 11:35:46 - mmengine - INFO - Epoch(train) [90][920/940] lr: 1.0000e-04 eta: 1:20:13 time: 0.5227 data_time: 0.0258 memory: 17006 grad_norm: 4.8231 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3176 loss: 1.3176 2022/10/13 11:35:55 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 11:35:55 - mmengine - INFO - Epoch(train) [90][940/940] lr: 1.0000e-04 eta: 1:20:03 time: 0.4597 data_time: 0.0240 memory: 17006 grad_norm: 5.2355 top1_acc: 0.2857 top5_acc: 0.4286 loss_cls: 1.2829 loss: 1.2829 2022/10/13 11:35:55 - mmengine - INFO - Saving checkpoint at 90 epochs 2022/10/13 11:36:09 - mmengine - INFO - Epoch(val) [90][20/78] eta: 0:00:36 time: 0.6372 data_time: 0.5451 memory: 3172 2022/10/13 11:36:18 - mmengine - INFO - Epoch(val) [90][40/78] eta: 0:00:16 time: 0.4339 data_time: 0.3430 memory: 3172 2022/10/13 11:36:30 - mmengine - INFO - Epoch(val) [90][60/78] eta: 0:00:10 time: 0.5988 data_time: 0.5085 memory: 3172 2022/10/13 11:36:38 - mmengine - INFO - Epoch(val) [90][78/78] acc/top1: 0.6735 acc/top5: 0.8702 acc/mean1: 0.6734 2022/10/13 11:36:53 - mmengine - INFO - Epoch(train) [91][20/940] lr: 1.0000e-04 eta: 1:19:53 time: 0.7139 data_time: 0.2520 memory: 17006 grad_norm: 4.8178 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1559 loss: 1.1559 2022/10/13 11:37:02 - mmengine - INFO - Epoch(train) [91][40/940] lr: 1.0000e-04 eta: 1:19:43 time: 0.4750 data_time: 0.0268 memory: 17006 grad_norm: 4.9452 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2687 loss: 1.2687 2022/10/13 11:37:13 - mmengine - INFO - Epoch(train) [91][60/940] lr: 1.0000e-04 eta: 1:19:33 time: 0.5609 data_time: 0.0324 memory: 17006 grad_norm: 4.9733 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2831 loss: 1.2831 2022/10/13 11:37:23 - mmengine - INFO - Epoch(train) [91][80/940] lr: 1.0000e-04 eta: 1:19:23 time: 0.4864 data_time: 0.0271 memory: 17006 grad_norm: 4.9488 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1768 loss: 1.1768 2022/10/13 11:37:34 - mmengine - INFO - Epoch(train) [91][100/940] lr: 1.0000e-04 eta: 1:19:12 time: 0.5330 data_time: 0.0340 memory: 17006 grad_norm: 4.9151 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2802 loss: 1.2802 2022/10/13 11:37:44 - mmengine - INFO - Epoch(train) [91][120/940] lr: 1.0000e-04 eta: 1:19:02 time: 0.5044 data_time: 0.0274 memory: 17006 grad_norm: 4.8483 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2125 loss: 1.2125 2022/10/13 11:37:55 - mmengine - INFO - Epoch(train) [91][140/940] lr: 1.0000e-04 eta: 1:18:52 time: 0.5568 data_time: 0.0358 memory: 17006 grad_norm: 4.9472 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2579 loss: 1.2579 2022/10/13 11:38:06 - mmengine - INFO - Epoch(train) [91][160/940] lr: 1.0000e-04 eta: 1:18:42 time: 0.5516 data_time: 0.0365 memory: 17006 grad_norm: 4.9739 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3942 loss: 1.3942 2022/10/13 11:38:17 - mmengine - INFO - Epoch(train) [91][180/940] lr: 1.0000e-04 eta: 1:18:32 time: 0.5665 data_time: 0.0326 memory: 17006 grad_norm: 4.9110 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3155 loss: 1.3155 2022/10/13 11:38:27 - mmengine - INFO - Epoch(train) [91][200/940] lr: 1.0000e-04 eta: 1:18:22 time: 0.4605 data_time: 0.0259 memory: 17006 grad_norm: 4.9743 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3308 loss: 1.3308 2022/10/13 11:38:38 - mmengine - INFO - Epoch(train) [91][220/940] lr: 1.0000e-04 eta: 1:18:11 time: 0.5540 data_time: 0.0411 memory: 17006 grad_norm: 5.0815 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2842 loss: 1.2842 2022/10/13 11:38:48 - mmengine - INFO - Epoch(train) [91][240/940] lr: 1.0000e-04 eta: 1:18:01 time: 0.4986 data_time: 0.0348 memory: 17006 grad_norm: 4.9037 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1209 loss: 1.1209 2022/10/13 11:38:58 - mmengine - INFO - Epoch(train) [91][260/940] lr: 1.0000e-04 eta: 1:17:51 time: 0.5239 data_time: 0.0274 memory: 17006 grad_norm: 4.9435 top1_acc: 0.9688 top5_acc: 1.0000 loss_cls: 1.2948 loss: 1.2948 2022/10/13 11:39:07 - mmengine - INFO - Epoch(train) [91][280/940] lr: 1.0000e-04 eta: 1:17:41 time: 0.4598 data_time: 0.0358 memory: 17006 grad_norm: 4.9572 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2146 loss: 1.2146 2022/10/13 11:39:18 - mmengine - INFO - Epoch(train) [91][300/940] lr: 1.0000e-04 eta: 1:17:30 time: 0.5323 data_time: 0.0266 memory: 17006 grad_norm: 4.7990 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2060 loss: 1.2060 2022/10/13 11:39:27 - mmengine - INFO - Epoch(train) [91][320/940] lr: 1.0000e-04 eta: 1:17:20 time: 0.4597 data_time: 0.0336 memory: 17006 grad_norm: 4.9410 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3028 loss: 1.3028 2022/10/13 11:39:38 - mmengine - INFO - Epoch(train) [91][340/940] lr: 1.0000e-04 eta: 1:17:10 time: 0.5494 data_time: 0.0338 memory: 17006 grad_norm: 4.9194 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2668 loss: 1.2668 2022/10/13 11:39:48 - mmengine - INFO - Epoch(train) [91][360/940] lr: 1.0000e-04 eta: 1:17:00 time: 0.4813 data_time: 0.0340 memory: 17006 grad_norm: 4.9293 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2916 loss: 1.2916 2022/10/13 11:39:59 - mmengine - INFO - Epoch(train) [91][380/940] lr: 1.0000e-04 eta: 1:16:50 time: 0.5382 data_time: 0.0337 memory: 17006 grad_norm: 4.9915 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2501 loss: 1.2501 2022/10/13 11:40:08 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 11:40:08 - mmengine - INFO - Epoch(train) [91][400/940] lr: 1.0000e-04 eta: 1:16:39 time: 0.4796 data_time: 0.0559 memory: 17006 grad_norm: 5.0195 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3070 loss: 1.3070 2022/10/13 11:40:19 - mmengine - INFO - Epoch(train) [91][420/940] lr: 1.0000e-04 eta: 1:16:29 time: 0.5431 data_time: 0.1723 memory: 17006 grad_norm: 4.9487 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3676 loss: 1.3676 2022/10/13 11:40:29 - mmengine - INFO - Epoch(train) [91][440/940] lr: 1.0000e-04 eta: 1:16:19 time: 0.5074 data_time: 0.1549 memory: 17006 grad_norm: 4.8986 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2888 loss: 1.2888 2022/10/13 11:40:40 - mmengine - INFO - Epoch(train) [91][460/940] lr: 1.0000e-04 eta: 1:16:09 time: 0.5309 data_time: 0.1061 memory: 17006 grad_norm: 4.8954 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3782 loss: 1.3782 2022/10/13 11:40:50 - mmengine - INFO - Epoch(train) [91][480/940] lr: 1.0000e-04 eta: 1:15:58 time: 0.5041 data_time: 0.1116 memory: 17006 grad_norm: 4.9746 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2336 loss: 1.2336 2022/10/13 11:41:02 - mmengine - INFO - Epoch(train) [91][500/940] lr: 1.0000e-04 eta: 1:15:48 time: 0.5851 data_time: 0.2616 memory: 17006 grad_norm: 4.9173 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.2485 loss: 1.2485 2022/10/13 11:41:11 - mmengine - INFO - Epoch(train) [91][520/940] lr: 1.0000e-04 eta: 1:15:38 time: 0.4772 data_time: 0.1534 memory: 17006 grad_norm: 4.9737 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1980 loss: 1.1980 2022/10/13 11:41:21 - mmengine - INFO - Epoch(train) [91][540/940] lr: 1.0000e-04 eta: 1:15:28 time: 0.4828 data_time: 0.1633 memory: 17006 grad_norm: 4.9583 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1933 loss: 1.1933 2022/10/13 11:41:30 - mmengine - INFO - Epoch(train) [91][560/940] lr: 1.0000e-04 eta: 1:15:17 time: 0.4478 data_time: 0.1149 memory: 17006 grad_norm: 4.9896 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.3688 loss: 1.3688 2022/10/13 11:41:40 - mmengine - INFO - Epoch(train) [91][580/940] lr: 1.0000e-04 eta: 1:15:07 time: 0.5216 data_time: 0.0805 memory: 17006 grad_norm: 4.9243 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1422 loss: 1.1422 2022/10/13 11:41:51 - mmengine - INFO - Epoch(train) [91][600/940] lr: 1.0000e-04 eta: 1:14:57 time: 0.5291 data_time: 0.0321 memory: 17006 grad_norm: 4.8236 top1_acc: 0.9062 top5_acc: 1.0000 loss_cls: 1.2158 loss: 1.2158 2022/10/13 11:42:02 - mmengine - INFO - Epoch(train) [91][620/940] lr: 1.0000e-04 eta: 1:14:47 time: 0.5622 data_time: 0.0312 memory: 17006 grad_norm: 4.9356 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2664 loss: 1.2664 2022/10/13 11:42:12 - mmengine - INFO - Epoch(train) [91][640/940] lr: 1.0000e-04 eta: 1:14:37 time: 0.5160 data_time: 0.0367 memory: 17006 grad_norm: 4.9678 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3548 loss: 1.3548 2022/10/13 11:42:23 - mmengine - INFO - Epoch(train) [91][660/940] lr: 1.0000e-04 eta: 1:14:27 time: 0.5226 data_time: 0.0261 memory: 17006 grad_norm: 4.9293 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2030 loss: 1.2030 2022/10/13 11:42:33 - mmengine - INFO - Epoch(train) [91][680/940] lr: 1.0000e-04 eta: 1:14:16 time: 0.5298 data_time: 0.0376 memory: 17006 grad_norm: 5.0029 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3030 loss: 1.3030 2022/10/13 11:42:43 - mmengine - INFO - Epoch(train) [91][700/940] lr: 1.0000e-04 eta: 1:14:06 time: 0.4838 data_time: 0.0272 memory: 17006 grad_norm: 4.9449 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1550 loss: 1.1550 2022/10/13 11:42:55 - mmengine - INFO - Epoch(train) [91][720/940] lr: 1.0000e-04 eta: 1:13:56 time: 0.5780 data_time: 0.0354 memory: 17006 grad_norm: 4.8927 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2306 loss: 1.2306 2022/10/13 11:43:04 - mmengine - INFO - Epoch(train) [91][740/940] lr: 1.0000e-04 eta: 1:13:46 time: 0.4605 data_time: 0.0362 memory: 17006 grad_norm: 4.9305 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3046 loss: 1.3046 2022/10/13 11:43:15 - mmengine - INFO - Epoch(train) [91][760/940] lr: 1.0000e-04 eta: 1:13:36 time: 0.5361 data_time: 0.0312 memory: 17006 grad_norm: 4.9806 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3513 loss: 1.3513 2022/10/13 11:43:25 - mmengine - INFO - Epoch(train) [91][780/940] lr: 1.0000e-04 eta: 1:13:25 time: 0.5040 data_time: 0.0322 memory: 17006 grad_norm: 4.8900 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2468 loss: 1.2468 2022/10/13 11:43:36 - mmengine - INFO - Epoch(train) [91][800/940] lr: 1.0000e-04 eta: 1:13:15 time: 0.5405 data_time: 0.0284 memory: 17006 grad_norm: 4.9577 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1613 loss: 1.1613 2022/10/13 11:43:45 - mmengine - INFO - Epoch(train) [91][820/940] lr: 1.0000e-04 eta: 1:13:05 time: 0.4820 data_time: 0.0353 memory: 17006 grad_norm: 4.9044 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1568 loss: 1.1568 2022/10/13 11:43:56 - mmengine - INFO - Epoch(train) [91][840/940] lr: 1.0000e-04 eta: 1:12:55 time: 0.5565 data_time: 0.0343 memory: 17006 grad_norm: 5.0322 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1713 loss: 1.1713 2022/10/13 11:44:05 - mmengine - INFO - Epoch(train) [91][860/940] lr: 1.0000e-04 eta: 1:12:44 time: 0.4561 data_time: 0.0323 memory: 17006 grad_norm: 4.8381 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.1864 loss: 1.1864 2022/10/13 11:44:17 - mmengine - INFO - Epoch(train) [91][880/940] lr: 1.0000e-04 eta: 1:12:34 time: 0.5673 data_time: 0.0386 memory: 17006 grad_norm: 4.8790 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.3462 loss: 1.3462 2022/10/13 11:44:26 - mmengine - INFO - Epoch(train) [91][900/940] lr: 1.0000e-04 eta: 1:12:24 time: 0.4679 data_time: 0.0321 memory: 17006 grad_norm: 4.9620 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.3543 loss: 1.3543 2022/10/13 11:44:37 - mmengine - INFO - Epoch(train) [91][920/940] lr: 1.0000e-04 eta: 1:12:14 time: 0.5456 data_time: 0.0338 memory: 17006 grad_norm: 4.9647 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2743 loss: 1.2743 2022/10/13 11:44:46 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 11:44:46 - mmengine - INFO - Epoch(train) [91][940/940] lr: 1.0000e-04 eta: 1:12:03 time: 0.4405 data_time: 0.0253 memory: 17006 grad_norm: 5.2522 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.3755 loss: 1.3755 2022/10/13 11:44:58 - mmengine - INFO - Epoch(val) [91][20/78] eta: 0:00:36 time: 0.6273 data_time: 0.5341 memory: 3172 2022/10/13 11:45:07 - mmengine - INFO - Epoch(val) [91][40/78] eta: 0:00:16 time: 0.4430 data_time: 0.3511 memory: 3172 2022/10/13 11:45:19 - mmengine - INFO - Epoch(val) [91][60/78] eta: 0:00:10 time: 0.5914 data_time: 0.4975 memory: 3172 2022/10/13 11:45:29 - mmengine - INFO - Epoch(val) [91][78/78] acc/top1: 0.6760 acc/top5: 0.8698 acc/mean1: 0.6760 2022/10/13 11:45:43 - mmengine - INFO - Epoch(train) [92][20/940] lr: 1.0000e-04 eta: 1:11:54 time: 0.6975 data_time: 0.3626 memory: 17006 grad_norm: 4.9686 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1510 loss: 1.1510 2022/10/13 11:45:53 - mmengine - INFO - Epoch(train) [92][40/940] lr: 1.0000e-04 eta: 1:11:43 time: 0.5032 data_time: 0.0640 memory: 17006 grad_norm: 5.0688 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3794 loss: 1.3794 2022/10/13 11:46:04 - mmengine - INFO - Epoch(train) [92][60/940] lr: 1.0000e-04 eta: 1:11:33 time: 0.5847 data_time: 0.1514 memory: 17006 grad_norm: 4.9486 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2501 loss: 1.2501 2022/10/13 11:46:14 - mmengine - INFO - Epoch(train) [92][80/940] lr: 1.0000e-04 eta: 1:11:23 time: 0.4644 data_time: 0.0274 memory: 17006 grad_norm: 4.9628 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1749 loss: 1.1749 2022/10/13 11:46:25 - mmengine - INFO - Epoch(train) [92][100/940] lr: 1.0000e-04 eta: 1:11:13 time: 0.5510 data_time: 0.1757 memory: 17006 grad_norm: 4.9970 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3122 loss: 1.3122 2022/10/13 11:46:34 - mmengine - INFO - Epoch(train) [92][120/940] lr: 1.0000e-04 eta: 1:11:03 time: 0.4778 data_time: 0.1419 memory: 17006 grad_norm: 4.9849 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2760 loss: 1.2760 2022/10/13 11:46:45 - mmengine - INFO - Epoch(train) [92][140/940] lr: 1.0000e-04 eta: 1:10:52 time: 0.5493 data_time: 0.1640 memory: 17006 grad_norm: 4.9058 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3241 loss: 1.3241 2022/10/13 11:46:55 - mmengine - INFO - Epoch(train) [92][160/940] lr: 1.0000e-04 eta: 1:10:42 time: 0.4754 data_time: 0.0870 memory: 17006 grad_norm: 4.9543 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2377 loss: 1.2377 2022/10/13 11:47:05 - mmengine - INFO - Epoch(train) [92][180/940] lr: 1.0000e-04 eta: 1:10:32 time: 0.5253 data_time: 0.0550 memory: 17006 grad_norm: 4.9653 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2596 loss: 1.2596 2022/10/13 11:47:14 - mmengine - INFO - Epoch(train) [92][200/940] lr: 1.0000e-04 eta: 1:10:22 time: 0.4640 data_time: 0.0356 memory: 17006 grad_norm: 4.9893 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3269 loss: 1.3269 2022/10/13 11:47:25 - mmengine - INFO - Epoch(train) [92][220/940] lr: 1.0000e-04 eta: 1:10:11 time: 0.5069 data_time: 0.0303 memory: 17006 grad_norm: 4.9284 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4324 loss: 1.4324 2022/10/13 11:47:35 - mmengine - INFO - Epoch(train) [92][240/940] lr: 1.0000e-04 eta: 1:10:01 time: 0.5048 data_time: 0.0303 memory: 17006 grad_norm: 5.0057 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2728 loss: 1.2728 2022/10/13 11:47:45 - mmengine - INFO - Epoch(train) [92][260/940] lr: 1.0000e-04 eta: 1:09:51 time: 0.5379 data_time: 0.0338 memory: 17006 grad_norm: 4.9406 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.1719 loss: 1.1719 2022/10/13 11:47:55 - mmengine - INFO - Epoch(train) [92][280/940] lr: 1.0000e-04 eta: 1:09:41 time: 0.4705 data_time: 0.0311 memory: 17006 grad_norm: 5.0312 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2232 loss: 1.2232 2022/10/13 11:48:06 - mmengine - INFO - Epoch(train) [92][300/940] lr: 1.0000e-04 eta: 1:09:30 time: 0.5388 data_time: 0.0387 memory: 17006 grad_norm: 4.9700 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2008 loss: 1.2008 2022/10/13 11:48:16 - mmengine - INFO - Epoch(train) [92][320/940] lr: 1.0000e-04 eta: 1:09:20 time: 0.5085 data_time: 0.0367 memory: 17006 grad_norm: 4.9605 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2738 loss: 1.2738 2022/10/13 11:48:27 - mmengine - INFO - Epoch(train) [92][340/940] lr: 1.0000e-04 eta: 1:09:10 time: 0.5423 data_time: 0.0327 memory: 17006 grad_norm: 4.8702 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2432 loss: 1.2432 2022/10/13 11:48:37 - mmengine - INFO - Epoch(train) [92][360/940] lr: 1.0000e-04 eta: 1:09:00 time: 0.5269 data_time: 0.0319 memory: 17006 grad_norm: 4.9067 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2742 loss: 1.2742 2022/10/13 11:48:47 - mmengine - INFO - Epoch(train) [92][380/940] lr: 1.0000e-04 eta: 1:08:50 time: 0.4916 data_time: 0.0332 memory: 17006 grad_norm: 4.9615 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2376 loss: 1.2376 2022/10/13 11:48:57 - mmengine - INFO - Epoch(train) [92][400/940] lr: 1.0000e-04 eta: 1:08:39 time: 0.5066 data_time: 0.0352 memory: 17006 grad_norm: 4.9618 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2768 loss: 1.2768 2022/10/13 11:49:08 - mmengine - INFO - Epoch(train) [92][420/940] lr: 1.0000e-04 eta: 1:08:29 time: 0.5301 data_time: 0.0345 memory: 17006 grad_norm: 4.9430 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1595 loss: 1.1595 2022/10/13 11:49:18 - mmengine - INFO - Epoch(train) [92][440/940] lr: 1.0000e-04 eta: 1:08:19 time: 0.5192 data_time: 0.0356 memory: 17006 grad_norm: 4.9301 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2369 loss: 1.2369 2022/10/13 11:49:29 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 11:49:29 - mmengine - INFO - Epoch(train) [92][460/940] lr: 1.0000e-04 eta: 1:08:09 time: 0.5589 data_time: 0.0327 memory: 17006 grad_norm: 5.1405 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3176 loss: 1.3176 2022/10/13 11:49:39 - mmengine - INFO - Epoch(train) [92][480/940] lr: 1.0000e-04 eta: 1:07:59 time: 0.4955 data_time: 0.0334 memory: 17006 grad_norm: 4.9725 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2472 loss: 1.2472 2022/10/13 11:49:49 - mmengine - INFO - Epoch(train) [92][500/940] lr: 1.0000e-04 eta: 1:07:48 time: 0.5078 data_time: 0.0293 memory: 17006 grad_norm: 4.9960 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2172 loss: 1.2172 2022/10/13 11:49:58 - mmengine - INFO - Epoch(train) [92][520/940] lr: 1.0000e-04 eta: 1:07:38 time: 0.4358 data_time: 0.0337 memory: 17006 grad_norm: 4.8948 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1712 loss: 1.1712 2022/10/13 11:50:09 - mmengine - INFO - Epoch(train) [92][540/940] lr: 1.0000e-04 eta: 1:07:28 time: 0.5513 data_time: 0.0368 memory: 17006 grad_norm: 4.8954 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4002 loss: 1.4002 2022/10/13 11:50:19 - mmengine - INFO - Epoch(train) [92][560/940] lr: 1.0000e-04 eta: 1:07:18 time: 0.4923 data_time: 0.0322 memory: 17006 grad_norm: 4.9646 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1885 loss: 1.1885 2022/10/13 11:50:31 - mmengine - INFO - Epoch(train) [92][580/940] lr: 1.0000e-04 eta: 1:07:08 time: 0.5824 data_time: 0.0279 memory: 17006 grad_norm: 4.8728 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2608 loss: 1.2608 2022/10/13 11:50:40 - mmengine - INFO - Epoch(train) [92][600/940] lr: 1.0000e-04 eta: 1:06:57 time: 0.4747 data_time: 0.0317 memory: 17006 grad_norm: 5.0439 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3415 loss: 1.3415 2022/10/13 11:50:50 - mmengine - INFO - Epoch(train) [92][620/940] lr: 1.0000e-04 eta: 1:06:47 time: 0.4994 data_time: 0.0343 memory: 17006 grad_norm: 5.0603 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3312 loss: 1.3312 2022/10/13 11:51:01 - mmengine - INFO - Epoch(train) [92][640/940] lr: 1.0000e-04 eta: 1:06:37 time: 0.5487 data_time: 0.0339 memory: 17006 grad_norm: 5.0484 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.2765 loss: 1.2765 2022/10/13 11:51:12 - mmengine - INFO - Epoch(train) [92][660/940] lr: 1.0000e-04 eta: 1:06:27 time: 0.5279 data_time: 0.0307 memory: 17006 grad_norm: 4.9564 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1509 loss: 1.1509 2022/10/13 11:51:21 - mmengine - INFO - Epoch(train) [92][680/940] lr: 1.0000e-04 eta: 1:06:16 time: 0.4700 data_time: 0.0298 memory: 17006 grad_norm: 5.0418 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2653 loss: 1.2653 2022/10/13 11:51:33 - mmengine - INFO - Epoch(train) [92][700/940] lr: 1.0000e-04 eta: 1:06:06 time: 0.5769 data_time: 0.0305 memory: 17006 grad_norm: 4.9348 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2753 loss: 1.2753 2022/10/13 11:51:43 - mmengine - INFO - Epoch(train) [92][720/940] lr: 1.0000e-04 eta: 1:05:56 time: 0.4997 data_time: 0.0304 memory: 17006 grad_norm: 4.8915 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1829 loss: 1.1829 2022/10/13 11:51:53 - mmengine - INFO - Epoch(train) [92][740/940] lr: 1.0000e-04 eta: 1:05:46 time: 0.5284 data_time: 0.0320 memory: 17006 grad_norm: 4.8749 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.0593 loss: 1.0593 2022/10/13 11:52:03 - mmengine - INFO - Epoch(train) [92][760/940] lr: 1.0000e-04 eta: 1:05:36 time: 0.4801 data_time: 0.0314 memory: 17006 grad_norm: 5.0020 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4078 loss: 1.4078 2022/10/13 11:52:14 - mmengine - INFO - Epoch(train) [92][780/940] lr: 1.0000e-04 eta: 1:05:25 time: 0.5534 data_time: 0.0329 memory: 17006 grad_norm: 4.8736 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2582 loss: 1.2582 2022/10/13 11:52:23 - mmengine - INFO - Epoch(train) [92][800/940] lr: 1.0000e-04 eta: 1:05:15 time: 0.4693 data_time: 0.0361 memory: 17006 grad_norm: 4.9628 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3551 loss: 1.3551 2022/10/13 11:52:34 - mmengine - INFO - Epoch(train) [92][820/940] lr: 1.0000e-04 eta: 1:05:05 time: 0.5099 data_time: 0.0315 memory: 17006 grad_norm: 4.9900 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1398 loss: 1.1398 2022/10/13 11:52:43 - mmengine - INFO - Epoch(train) [92][840/940] lr: 1.0000e-04 eta: 1:04:55 time: 0.4888 data_time: 0.0317 memory: 17006 grad_norm: 4.9575 top1_acc: 0.8750 top5_acc: 0.9688 loss_cls: 1.2030 loss: 1.2030 2022/10/13 11:52:54 - mmengine - INFO - Epoch(train) [92][860/940] lr: 1.0000e-04 eta: 1:04:44 time: 0.5539 data_time: 0.0358 memory: 17006 grad_norm: 4.9554 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2940 loss: 1.2940 2022/10/13 11:53:04 - mmengine - INFO - Epoch(train) [92][880/940] lr: 1.0000e-04 eta: 1:04:34 time: 0.4735 data_time: 0.0292 memory: 17006 grad_norm: 4.9269 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.2561 loss: 1.2561 2022/10/13 11:53:15 - mmengine - INFO - Epoch(train) [92][900/940] lr: 1.0000e-04 eta: 1:04:24 time: 0.5438 data_time: 0.0306 memory: 17006 grad_norm: 4.7685 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1453 loss: 1.1453 2022/10/13 11:53:24 - mmengine - INFO - Epoch(train) [92][920/940] lr: 1.0000e-04 eta: 1:04:14 time: 0.4841 data_time: 0.0349 memory: 17006 grad_norm: 4.9086 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3204 loss: 1.3204 2022/10/13 11:53:33 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 11:53:33 - mmengine - INFO - Epoch(train) [92][940/940] lr: 1.0000e-04 eta: 1:04:03 time: 0.4245 data_time: 0.0281 memory: 17006 grad_norm: 5.1705 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2974 loss: 1.2974 2022/10/13 11:53:45 - mmengine - INFO - Epoch(val) [92][20/78] eta: 0:00:36 time: 0.6225 data_time: 0.5296 memory: 3172 2022/10/13 11:53:54 - mmengine - INFO - Epoch(val) [92][40/78] eta: 0:00:16 time: 0.4367 data_time: 0.3434 memory: 3172 2022/10/13 11:54:06 - mmengine - INFO - Epoch(val) [92][60/78] eta: 0:00:10 time: 0.5822 data_time: 0.4912 memory: 3172 2022/10/13 11:54:16 - mmengine - INFO - Epoch(val) [92][78/78] acc/top1: 0.6753 acc/top5: 0.8706 acc/mean1: 0.6752 2022/10/13 11:54:30 - mmengine - INFO - Epoch(train) [93][20/940] lr: 1.0000e-04 eta: 1:03:53 time: 0.7175 data_time: 0.2024 memory: 17006 grad_norm: 4.9437 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2747 loss: 1.2747 2022/10/13 11:54:39 - mmengine - INFO - Epoch(train) [93][40/940] lr: 1.0000e-04 eta: 1:03:43 time: 0.4595 data_time: 0.0311 memory: 17006 grad_norm: 4.9048 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2853 loss: 1.2853 2022/10/13 11:54:51 - mmengine - INFO - Epoch(train) [93][60/940] lr: 1.0000e-04 eta: 1:03:33 time: 0.5626 data_time: 0.0507 memory: 17006 grad_norm: 5.0449 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2536 loss: 1.2536 2022/10/13 11:55:00 - mmengine - INFO - Epoch(train) [93][80/940] lr: 1.0000e-04 eta: 1:03:23 time: 0.4686 data_time: 0.1304 memory: 17006 grad_norm: 4.9563 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2503 loss: 1.2503 2022/10/13 11:55:11 - mmengine - INFO - Epoch(train) [93][100/940] lr: 1.0000e-04 eta: 1:03:13 time: 0.5653 data_time: 0.2258 memory: 17006 grad_norm: 4.9146 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2025 loss: 1.2025 2022/10/13 11:55:21 - mmengine - INFO - Epoch(train) [93][120/940] lr: 1.0000e-04 eta: 1:03:02 time: 0.4786 data_time: 0.0626 memory: 17006 grad_norm: 4.8333 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2970 loss: 1.2970 2022/10/13 11:55:32 - mmengine - INFO - Epoch(train) [93][140/940] lr: 1.0000e-04 eta: 1:02:52 time: 0.5644 data_time: 0.1638 memory: 17006 grad_norm: 4.9542 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3032 loss: 1.3032 2022/10/13 11:55:43 - mmengine - INFO - Epoch(train) [93][160/940] lr: 1.0000e-04 eta: 1:02:42 time: 0.5387 data_time: 0.0258 memory: 17006 grad_norm: 4.9232 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2495 loss: 1.2495 2022/10/13 11:55:53 - mmengine - INFO - Epoch(train) [93][180/940] lr: 1.0000e-04 eta: 1:02:32 time: 0.4868 data_time: 0.0811 memory: 17006 grad_norm: 5.0024 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2286 loss: 1.2286 2022/10/13 11:56:02 - mmengine - INFO - Epoch(train) [93][200/940] lr: 1.0000e-04 eta: 1:02:21 time: 0.4800 data_time: 0.1385 memory: 17006 grad_norm: 5.0334 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2896 loss: 1.2896 2022/10/13 11:56:13 - mmengine - INFO - Epoch(train) [93][220/940] lr: 1.0000e-04 eta: 1:02:11 time: 0.5412 data_time: 0.1404 memory: 17006 grad_norm: 4.9444 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1613 loss: 1.1613 2022/10/13 11:56:23 - mmengine - INFO - Epoch(train) [93][240/940] lr: 1.0000e-04 eta: 1:02:01 time: 0.4951 data_time: 0.0743 memory: 17006 grad_norm: 4.9767 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2012 loss: 1.2012 2022/10/13 11:56:34 - mmengine - INFO - Epoch(train) [93][260/940] lr: 1.0000e-04 eta: 1:01:51 time: 0.5454 data_time: 0.0918 memory: 17006 grad_norm: 4.9349 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1800 loss: 1.1800 2022/10/13 11:56:44 - mmengine - INFO - Epoch(train) [93][280/940] lr: 1.0000e-04 eta: 1:01:41 time: 0.4992 data_time: 0.0417 memory: 17006 grad_norm: 4.9645 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2227 loss: 1.2227 2022/10/13 11:56:55 - mmengine - INFO - Epoch(train) [93][300/940] lr: 1.0000e-04 eta: 1:01:30 time: 0.5716 data_time: 0.0906 memory: 17006 grad_norm: 4.9945 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2285 loss: 1.2285 2022/10/13 11:57:05 - mmengine - INFO - Epoch(train) [93][320/940] lr: 1.0000e-04 eta: 1:01:20 time: 0.4990 data_time: 0.0391 memory: 17006 grad_norm: 4.9491 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2111 loss: 1.2111 2022/10/13 11:57:16 - mmengine - INFO - Epoch(train) [93][340/940] lr: 1.0000e-04 eta: 1:01:10 time: 0.5188 data_time: 0.1682 memory: 17006 grad_norm: 4.9070 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2394 loss: 1.2394 2022/10/13 11:57:26 - mmengine - INFO - Epoch(train) [93][360/940] lr: 1.0000e-04 eta: 1:01:00 time: 0.5144 data_time: 0.1821 memory: 17006 grad_norm: 4.9966 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.4114 loss: 1.4114 2022/10/13 11:57:36 - mmengine - INFO - Epoch(train) [93][380/940] lr: 1.0000e-04 eta: 1:00:50 time: 0.5180 data_time: 0.1612 memory: 17006 grad_norm: 4.8772 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2870 loss: 1.2870 2022/10/13 11:57:46 - mmengine - INFO - Epoch(train) [93][400/940] lr: 1.0000e-04 eta: 1:00:39 time: 0.4892 data_time: 0.1489 memory: 17006 grad_norm: 4.9060 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2065 loss: 1.2065 2022/10/13 11:57:57 - mmengine - INFO - Epoch(train) [93][420/940] lr: 1.0000e-04 eta: 1:00:29 time: 0.5495 data_time: 0.1654 memory: 17006 grad_norm: 5.0127 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2330 loss: 1.2330 2022/10/13 11:58:08 - mmengine - INFO - Epoch(train) [93][440/940] lr: 1.0000e-04 eta: 1:00:19 time: 0.5431 data_time: 0.0412 memory: 17006 grad_norm: 5.0690 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3310 loss: 1.3310 2022/10/13 11:58:18 - mmengine - INFO - Epoch(train) [93][460/940] lr: 1.0000e-04 eta: 1:00:09 time: 0.4858 data_time: 0.0338 memory: 17006 grad_norm: 4.8602 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.1607 loss: 1.1607 2022/10/13 11:58:28 - mmengine - INFO - Epoch(train) [93][480/940] lr: 1.0000e-04 eta: 0:59:59 time: 0.5292 data_time: 0.0318 memory: 17006 grad_norm: 4.9055 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3069 loss: 1.3069 2022/10/13 11:58:38 - mmengine - INFO - Epoch(train) [93][500/940] lr: 1.0000e-04 eta: 0:59:48 time: 0.4979 data_time: 0.0384 memory: 17006 grad_norm: 4.9278 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.1684 loss: 1.1684 2022/10/13 11:58:49 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 11:58:49 - mmengine - INFO - Epoch(train) [93][520/940] lr: 1.0000e-04 eta: 0:59:38 time: 0.5199 data_time: 0.0282 memory: 17006 grad_norm: 4.9640 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4000 loss: 1.4000 2022/10/13 11:58:58 - mmengine - INFO - Epoch(train) [93][540/940] lr: 1.0000e-04 eta: 0:59:28 time: 0.4596 data_time: 0.0382 memory: 17006 grad_norm: 4.9668 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2550 loss: 1.2550 2022/10/13 11:59:08 - mmengine - INFO - Epoch(train) [93][560/940] lr: 1.0000e-04 eta: 0:59:18 time: 0.5062 data_time: 0.0351 memory: 17006 grad_norm: 4.9254 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2325 loss: 1.2325 2022/10/13 11:59:18 - mmengine - INFO - Epoch(train) [93][580/940] lr: 1.0000e-04 eta: 0:59:07 time: 0.5205 data_time: 0.0269 memory: 17006 grad_norm: 4.9765 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.2266 loss: 1.2266 2022/10/13 11:59:29 - mmengine - INFO - Epoch(train) [93][600/940] lr: 1.0000e-04 eta: 0:58:57 time: 0.5390 data_time: 0.0389 memory: 17006 grad_norm: 4.9849 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3326 loss: 1.3326 2022/10/13 11:59:39 - mmengine - INFO - Epoch(train) [93][620/940] lr: 1.0000e-04 eta: 0:58:47 time: 0.4703 data_time: 0.0273 memory: 17006 grad_norm: 4.9062 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3058 loss: 1.3058 2022/10/13 11:59:50 - mmengine - INFO - Epoch(train) [93][640/940] lr: 1.0000e-04 eta: 0:58:37 time: 0.5745 data_time: 0.0311 memory: 17006 grad_norm: 5.0019 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3552 loss: 1.3552 2022/10/13 12:00:01 - mmengine - INFO - Epoch(train) [93][660/940] lr: 1.0000e-04 eta: 0:58:27 time: 0.5203 data_time: 0.0264 memory: 17006 grad_norm: 4.9571 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3265 loss: 1.3265 2022/10/13 12:00:11 - mmengine - INFO - Epoch(train) [93][680/940] lr: 1.0000e-04 eta: 0:58:16 time: 0.5455 data_time: 0.0371 memory: 17006 grad_norm: 5.0437 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2164 loss: 1.2164 2022/10/13 12:00:22 - mmengine - INFO - Epoch(train) [93][700/940] lr: 1.0000e-04 eta: 0:58:06 time: 0.5177 data_time: 0.0265 memory: 17006 grad_norm: 4.9945 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2995 loss: 1.2995 2022/10/13 12:00:33 - mmengine - INFO - Epoch(train) [93][720/940] lr: 1.0000e-04 eta: 0:57:56 time: 0.5704 data_time: 0.0268 memory: 17006 grad_norm: 4.9905 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2226 loss: 1.2226 2022/10/13 12:00:42 - mmengine - INFO - Epoch(train) [93][740/940] lr: 1.0000e-04 eta: 0:57:46 time: 0.4374 data_time: 0.0355 memory: 17006 grad_norm: 4.7987 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2172 loss: 1.2172 2022/10/13 12:00:52 - mmengine - INFO - Epoch(train) [93][760/940] lr: 1.0000e-04 eta: 0:57:35 time: 0.5062 data_time: 0.0294 memory: 17006 grad_norm: 4.9295 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1622 loss: 1.1622 2022/10/13 12:01:02 - mmengine - INFO - Epoch(train) [93][780/940] lr: 1.0000e-04 eta: 0:57:25 time: 0.5108 data_time: 0.0398 memory: 17006 grad_norm: 4.9351 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2765 loss: 1.2765 2022/10/13 12:01:12 - mmengine - INFO - Epoch(train) [93][800/940] lr: 1.0000e-04 eta: 0:57:15 time: 0.5032 data_time: 0.0296 memory: 17006 grad_norm: 4.9232 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3112 loss: 1.3112 2022/10/13 12:01:22 - mmengine - INFO - Epoch(train) [93][820/940] lr: 1.0000e-04 eta: 0:57:05 time: 0.4817 data_time: 0.0332 memory: 17006 grad_norm: 4.9197 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3207 loss: 1.3207 2022/10/13 12:01:32 - mmengine - INFO - Epoch(train) [93][840/940] lr: 1.0000e-04 eta: 0:56:54 time: 0.5038 data_time: 0.0370 memory: 17006 grad_norm: 4.9124 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1975 loss: 1.1975 2022/10/13 12:01:43 - mmengine - INFO - Epoch(train) [93][860/940] lr: 1.0000e-04 eta: 0:56:44 time: 0.5428 data_time: 0.0330 memory: 17006 grad_norm: 4.9201 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3187 loss: 1.3187 2022/10/13 12:01:53 - mmengine - INFO - Epoch(train) [93][880/940] lr: 1.0000e-04 eta: 0:56:34 time: 0.5105 data_time: 0.0324 memory: 17006 grad_norm: 4.9518 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3323 loss: 1.3323 2022/10/13 12:02:05 - mmengine - INFO - Epoch(train) [93][900/940] lr: 1.0000e-04 eta: 0:56:24 time: 0.5965 data_time: 0.0307 memory: 17006 grad_norm: 4.8714 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1168 loss: 1.1168 2022/10/13 12:02:14 - mmengine - INFO - Epoch(train) [93][920/940] lr: 1.0000e-04 eta: 0:56:14 time: 0.4412 data_time: 0.0327 memory: 17006 grad_norm: 4.9239 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2483 loss: 1.2483 2022/10/13 12:02:23 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 12:02:23 - mmengine - INFO - Epoch(train) [93][940/940] lr: 1.0000e-04 eta: 0:56:03 time: 0.4530 data_time: 0.0284 memory: 17006 grad_norm: 5.2149 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.1788 loss: 1.1788 2022/10/13 12:02:23 - mmengine - INFO - Saving checkpoint at 93 epochs 2022/10/13 12:02:37 - mmengine - INFO - Epoch(val) [93][20/78] eta: 0:00:37 time: 0.6490 data_time: 0.5591 memory: 3172 2022/10/13 12:02:46 - mmengine - INFO - Epoch(val) [93][40/78] eta: 0:00:16 time: 0.4389 data_time: 0.3496 memory: 3172 2022/10/13 12:02:58 - mmengine - INFO - Epoch(val) [93][60/78] eta: 0:00:11 time: 0.6257 data_time: 0.5345 memory: 3172 2022/10/13 12:03:07 - mmengine - INFO - Epoch(val) [93][78/78] acc/top1: 0.6752 acc/top5: 0.8695 acc/mean1: 0.6751 2022/10/13 12:03:22 - mmengine - INFO - Epoch(train) [94][20/940] lr: 1.0000e-04 eta: 0:55:53 time: 0.7301 data_time: 0.2591 memory: 17006 grad_norm: 4.9122 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2332 loss: 1.2332 2022/10/13 12:03:31 - mmengine - INFO - Epoch(train) [94][40/940] lr: 1.0000e-04 eta: 0:55:43 time: 0.4771 data_time: 0.0272 memory: 17006 grad_norm: 4.9779 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2512 loss: 1.2512 2022/10/13 12:03:42 - mmengine - INFO - Epoch(train) [94][60/940] lr: 1.0000e-04 eta: 0:55:33 time: 0.5590 data_time: 0.0283 memory: 17006 grad_norm: 5.0056 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3830 loss: 1.3830 2022/10/13 12:03:52 - mmengine - INFO - Epoch(train) [94][80/940] lr: 1.0000e-04 eta: 0:55:23 time: 0.4836 data_time: 0.0271 memory: 17006 grad_norm: 4.8642 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1972 loss: 1.1972 2022/10/13 12:04:03 - mmengine - INFO - Epoch(train) [94][100/940] lr: 1.0000e-04 eta: 0:55:13 time: 0.5317 data_time: 0.0313 memory: 17006 grad_norm: 4.8735 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1979 loss: 1.1979 2022/10/13 12:04:13 - mmengine - INFO - Epoch(train) [94][120/940] lr: 1.0000e-04 eta: 0:55:02 time: 0.4969 data_time: 0.0278 memory: 17006 grad_norm: 4.9184 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2388 loss: 1.2388 2022/10/13 12:04:24 - mmengine - INFO - Epoch(train) [94][140/940] lr: 1.0000e-04 eta: 0:54:52 time: 0.5748 data_time: 0.0317 memory: 17006 grad_norm: 4.8183 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2065 loss: 1.2065 2022/10/13 12:04:33 - mmengine - INFO - Epoch(train) [94][160/940] lr: 1.0000e-04 eta: 0:54:42 time: 0.4423 data_time: 0.0304 memory: 17006 grad_norm: 4.8474 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.3864 loss: 1.3864 2022/10/13 12:04:44 - mmengine - INFO - Epoch(train) [94][180/940] lr: 1.0000e-04 eta: 0:54:32 time: 0.5425 data_time: 0.0313 memory: 17006 grad_norm: 4.9654 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2512 loss: 1.2512 2022/10/13 12:04:54 - mmengine - INFO - Epoch(train) [94][200/940] lr: 1.0000e-04 eta: 0:54:21 time: 0.5116 data_time: 0.0370 memory: 17006 grad_norm: 4.9282 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2818 loss: 1.2818 2022/10/13 12:05:05 - mmengine - INFO - Epoch(train) [94][220/940] lr: 1.0000e-04 eta: 0:54:11 time: 0.5468 data_time: 0.0316 memory: 17006 grad_norm: 4.9544 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3084 loss: 1.3084 2022/10/13 12:05:14 - mmengine - INFO - Epoch(train) [94][240/940] lr: 1.0000e-04 eta: 0:54:01 time: 0.4713 data_time: 0.0303 memory: 17006 grad_norm: 5.0261 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2559 loss: 1.2559 2022/10/13 12:05:25 - mmengine - INFO - Epoch(train) [94][260/940] lr: 1.0000e-04 eta: 0:53:51 time: 0.5521 data_time: 0.0284 memory: 17006 grad_norm: 5.0568 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2194 loss: 1.2194 2022/10/13 12:05:36 - mmengine - INFO - Epoch(train) [94][280/940] lr: 1.0000e-04 eta: 0:53:41 time: 0.5179 data_time: 0.0315 memory: 17006 grad_norm: 5.0436 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3505 loss: 1.3505 2022/10/13 12:05:46 - mmengine - INFO - Epoch(train) [94][300/940] lr: 1.0000e-04 eta: 0:53:30 time: 0.4984 data_time: 0.0302 memory: 17006 grad_norm: 4.9181 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2384 loss: 1.2384 2022/10/13 12:05:56 - mmengine - INFO - Epoch(train) [94][320/940] lr: 1.0000e-04 eta: 0:53:20 time: 0.5031 data_time: 0.0240 memory: 17006 grad_norm: 5.0210 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2417 loss: 1.2417 2022/10/13 12:06:07 - mmengine - INFO - Epoch(train) [94][340/940] lr: 1.0000e-04 eta: 0:53:10 time: 0.5394 data_time: 0.0371 memory: 17006 grad_norm: 5.0508 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1660 loss: 1.1660 2022/10/13 12:06:17 - mmengine - INFO - Epoch(train) [94][360/940] lr: 1.0000e-04 eta: 0:53:00 time: 0.5008 data_time: 0.0310 memory: 17006 grad_norm: 5.0154 top1_acc: 0.9062 top5_acc: 0.9062 loss_cls: 1.2255 loss: 1.2255 2022/10/13 12:06:27 - mmengine - INFO - Epoch(train) [94][380/940] lr: 1.0000e-04 eta: 0:52:50 time: 0.5384 data_time: 0.0294 memory: 17006 grad_norm: 4.8739 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1723 loss: 1.1723 2022/10/13 12:06:37 - mmengine - INFO - Epoch(train) [94][400/940] lr: 1.0000e-04 eta: 0:52:39 time: 0.4877 data_time: 0.0287 memory: 17006 grad_norm: 4.9494 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2918 loss: 1.2918 2022/10/13 12:06:50 - mmengine - INFO - Epoch(train) [94][420/940] lr: 1.0000e-04 eta: 0:52:29 time: 0.6237 data_time: 0.0302 memory: 17006 grad_norm: 4.8852 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1771 loss: 1.1771 2022/10/13 12:06:58 - mmengine - INFO - Epoch(train) [94][440/940] lr: 1.0000e-04 eta: 0:52:19 time: 0.4410 data_time: 0.0366 memory: 17006 grad_norm: 5.0647 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2584 loss: 1.2584 2022/10/13 12:07:09 - mmengine - INFO - Epoch(train) [94][460/940] lr: 1.0000e-04 eta: 0:52:09 time: 0.5291 data_time: 0.0312 memory: 17006 grad_norm: 5.0112 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3288 loss: 1.3288 2022/10/13 12:07:19 - mmengine - INFO - Epoch(train) [94][480/940] lr: 1.0000e-04 eta: 0:51:58 time: 0.4831 data_time: 0.0329 memory: 17006 grad_norm: 4.9163 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2689 loss: 1.2689 2022/10/13 12:07:30 - mmengine - INFO - Epoch(train) [94][500/940] lr: 1.0000e-04 eta: 0:51:48 time: 0.5632 data_time: 0.0345 memory: 17006 grad_norm: 4.9898 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2380 loss: 1.2380 2022/10/13 12:07:40 - mmengine - INFO - Epoch(train) [94][520/940] lr: 1.0000e-04 eta: 0:51:38 time: 0.4998 data_time: 0.0320 memory: 17006 grad_norm: 4.9975 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.2056 loss: 1.2056 2022/10/13 12:07:50 - mmengine - INFO - Epoch(train) [94][540/940] lr: 1.0000e-04 eta: 0:51:28 time: 0.5030 data_time: 0.0362 memory: 17006 grad_norm: 4.9129 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2365 loss: 1.2365 2022/10/13 12:08:00 - mmengine - INFO - Epoch(train) [94][560/940] lr: 1.0000e-04 eta: 0:51:18 time: 0.5099 data_time: 0.0560 memory: 17006 grad_norm: 4.9082 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2407 loss: 1.2407 2022/10/13 12:08:11 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 12:08:11 - mmengine - INFO - Epoch(train) [94][580/940] lr: 1.0000e-04 eta: 0:51:07 time: 0.5171 data_time: 0.0241 memory: 17006 grad_norm: 4.9462 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.3531 loss: 1.3531 2022/10/13 12:08:22 - mmengine - INFO - Epoch(train) [94][600/940] lr: 1.0000e-04 eta: 0:50:57 time: 0.5567 data_time: 0.0351 memory: 17006 grad_norm: 4.8855 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3041 loss: 1.3041 2022/10/13 12:08:32 - mmengine - INFO - Epoch(train) [94][620/940] lr: 1.0000e-04 eta: 0:50:47 time: 0.4916 data_time: 0.0303 memory: 17006 grad_norm: 4.8448 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2079 loss: 1.2079 2022/10/13 12:08:43 - mmengine - INFO - Epoch(train) [94][640/940] lr: 1.0000e-04 eta: 0:50:37 time: 0.5581 data_time: 0.0307 memory: 17006 grad_norm: 5.0099 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1775 loss: 1.1775 2022/10/13 12:08:53 - mmengine - INFO - Epoch(train) [94][660/940] lr: 1.0000e-04 eta: 0:50:27 time: 0.5249 data_time: 0.0318 memory: 17006 grad_norm: 4.8568 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1372 loss: 1.1372 2022/10/13 12:09:03 - mmengine - INFO - Epoch(train) [94][680/940] lr: 1.0000e-04 eta: 0:50:16 time: 0.5050 data_time: 0.0393 memory: 17006 grad_norm: 4.9877 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3164 loss: 1.3164 2022/10/13 12:09:13 - mmengine - INFO - Epoch(train) [94][700/940] lr: 1.0000e-04 eta: 0:50:06 time: 0.4942 data_time: 0.0322 memory: 17006 grad_norm: 4.8712 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2454 loss: 1.2454 2022/10/13 12:09:24 - mmengine - INFO - Epoch(train) [94][720/940] lr: 1.0000e-04 eta: 0:49:56 time: 0.5148 data_time: 0.0342 memory: 17006 grad_norm: 4.9240 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.0825 loss: 1.0825 2022/10/13 12:09:33 - mmengine - INFO - Epoch(train) [94][740/940] lr: 1.0000e-04 eta: 0:49:46 time: 0.4749 data_time: 0.0365 memory: 17006 grad_norm: 5.0250 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4695 loss: 1.4695 2022/10/13 12:09:44 - mmengine - INFO - Epoch(train) [94][760/940] lr: 1.0000e-04 eta: 0:49:35 time: 0.5402 data_time: 0.0311 memory: 17006 grad_norm: 4.9030 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2292 loss: 1.2292 2022/10/13 12:09:55 - mmengine - INFO - Epoch(train) [94][780/940] lr: 1.0000e-04 eta: 0:49:25 time: 0.5352 data_time: 0.0329 memory: 17006 grad_norm: 4.9218 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3243 loss: 1.3243 2022/10/13 12:10:06 - mmengine - INFO - Epoch(train) [94][800/940] lr: 1.0000e-04 eta: 0:49:15 time: 0.5626 data_time: 0.0276 memory: 17006 grad_norm: 4.9527 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1894 loss: 1.1894 2022/10/13 12:10:16 - mmengine - INFO - Epoch(train) [94][820/940] lr: 1.0000e-04 eta: 0:49:05 time: 0.5168 data_time: 0.0303 memory: 17006 grad_norm: 4.9977 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3685 loss: 1.3685 2022/10/13 12:10:27 - mmengine - INFO - Epoch(train) [94][840/940] lr: 1.0000e-04 eta: 0:48:55 time: 0.5237 data_time: 0.0358 memory: 17006 grad_norm: 4.8578 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2474 loss: 1.2474 2022/10/13 12:10:36 - mmengine - INFO - Epoch(train) [94][860/940] lr: 1.0000e-04 eta: 0:48:44 time: 0.4774 data_time: 0.0273 memory: 17006 grad_norm: 4.9865 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3445 loss: 1.3445 2022/10/13 12:10:48 - mmengine - INFO - Epoch(train) [94][880/940] lr: 1.0000e-04 eta: 0:48:34 time: 0.5772 data_time: 0.0333 memory: 17006 grad_norm: 4.9859 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.3451 loss: 1.3451 2022/10/13 12:10:57 - mmengine - INFO - Epoch(train) [94][900/940] lr: 1.0000e-04 eta: 0:48:24 time: 0.4529 data_time: 0.0292 memory: 17006 grad_norm: 4.9144 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3380 loss: 1.3380 2022/10/13 12:11:08 - mmengine - INFO - Epoch(train) [94][920/940] lr: 1.0000e-04 eta: 0:48:14 time: 0.5696 data_time: 0.0345 memory: 17006 grad_norm: 4.8989 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2851 loss: 1.2851 2022/10/13 12:11:17 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 12:11:17 - mmengine - INFO - Epoch(train) [94][940/940] lr: 1.0000e-04 eta: 0:48:03 time: 0.4568 data_time: 0.0234 memory: 17006 grad_norm: 5.2512 top1_acc: 0.5714 top5_acc: 1.0000 loss_cls: 1.2425 loss: 1.2425 2022/10/13 12:11:30 - mmengine - INFO - Epoch(val) [94][20/78] eta: 0:00:36 time: 0.6289 data_time: 0.5342 memory: 3172 2022/10/13 12:11:39 - mmengine - INFO - Epoch(val) [94][40/78] eta: 0:00:16 time: 0.4355 data_time: 0.3451 memory: 3172 2022/10/13 12:11:50 - mmengine - INFO - Epoch(val) [94][60/78] eta: 0:00:10 time: 0.5696 data_time: 0.4762 memory: 3172 2022/10/13 12:12:01 - mmengine - INFO - Epoch(val) [94][78/78] acc/top1: 0.6754 acc/top5: 0.8692 acc/mean1: 0.6753 2022/10/13 12:12:14 - mmengine - INFO - Epoch(train) [95][20/940] lr: 1.0000e-04 eta: 0:47:53 time: 0.6735 data_time: 0.3207 memory: 17006 grad_norm: 4.8220 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2136 loss: 1.2136 2022/10/13 12:12:24 - mmengine - INFO - Epoch(train) [95][40/940] lr: 1.0000e-04 eta: 0:47:43 time: 0.4867 data_time: 0.0929 memory: 17006 grad_norm: 4.9657 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1940 loss: 1.1940 2022/10/13 12:12:36 - mmengine - INFO - Epoch(train) [95][60/940] lr: 1.0000e-04 eta: 0:47:33 time: 0.5858 data_time: 0.1694 memory: 17006 grad_norm: 4.9420 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2383 loss: 1.2383 2022/10/13 12:12:45 - mmengine - INFO - Epoch(train) [95][80/940] lr: 1.0000e-04 eta: 0:47:23 time: 0.4653 data_time: 0.0270 memory: 17006 grad_norm: 4.9484 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2671 loss: 1.2671 2022/10/13 12:12:56 - mmengine - INFO - Epoch(train) [95][100/940] lr: 1.0000e-04 eta: 0:47:13 time: 0.5764 data_time: 0.0348 memory: 17006 grad_norm: 4.9182 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1885 loss: 1.1885 2022/10/13 12:13:07 - mmengine - INFO - Epoch(train) [95][120/940] lr: 1.0000e-04 eta: 0:47:02 time: 0.5269 data_time: 0.0262 memory: 17006 grad_norm: 4.9057 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3054 loss: 1.3054 2022/10/13 12:13:18 - mmengine - INFO - Epoch(train) [95][140/940] lr: 1.0000e-04 eta: 0:46:52 time: 0.5661 data_time: 0.0321 memory: 17006 grad_norm: 4.8270 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2668 loss: 1.2668 2022/10/13 12:13:28 - mmengine - INFO - Epoch(train) [95][160/940] lr: 1.0000e-04 eta: 0:46:42 time: 0.4695 data_time: 0.0275 memory: 17006 grad_norm: 4.9155 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2347 loss: 1.2347 2022/10/13 12:13:38 - mmengine - INFO - Epoch(train) [95][180/940] lr: 1.0000e-04 eta: 0:46:32 time: 0.5231 data_time: 0.0354 memory: 17006 grad_norm: 4.9607 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1698 loss: 1.1698 2022/10/13 12:13:48 - mmengine - INFO - Epoch(train) [95][200/940] lr: 1.0000e-04 eta: 0:46:21 time: 0.4954 data_time: 0.0295 memory: 17006 grad_norm: 4.9608 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1864 loss: 1.1864 2022/10/13 12:13:59 - mmengine - INFO - Epoch(train) [95][220/940] lr: 1.0000e-04 eta: 0:46:11 time: 0.5426 data_time: 0.0339 memory: 17006 grad_norm: 4.9667 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.2286 loss: 1.2286 2022/10/13 12:14:09 - mmengine - INFO - Epoch(train) [95][240/940] lr: 1.0000e-04 eta: 0:46:01 time: 0.5265 data_time: 0.0295 memory: 17006 grad_norm: 4.9681 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3085 loss: 1.3085 2022/10/13 12:14:20 - mmengine - INFO - Epoch(train) [95][260/940] lr: 1.0000e-04 eta: 0:45:51 time: 0.5324 data_time: 0.0282 memory: 17006 grad_norm: 4.9171 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2152 loss: 1.2152 2022/10/13 12:14:30 - mmengine - INFO - Epoch(train) [95][280/940] lr: 1.0000e-04 eta: 0:45:41 time: 0.4874 data_time: 0.0341 memory: 17006 grad_norm: 4.9437 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1795 loss: 1.1795 2022/10/13 12:14:41 - mmengine - INFO - Epoch(train) [95][300/940] lr: 1.0000e-04 eta: 0:45:30 time: 0.5662 data_time: 0.0364 memory: 17006 grad_norm: 4.9483 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2923 loss: 1.2923 2022/10/13 12:14:52 - mmengine - INFO - Epoch(train) [95][320/940] lr: 1.0000e-04 eta: 0:45:20 time: 0.5174 data_time: 0.0310 memory: 17006 grad_norm: 4.8737 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1272 loss: 1.1272 2022/10/13 12:15:02 - mmengine - INFO - Epoch(train) [95][340/940] lr: 1.0000e-04 eta: 0:45:10 time: 0.5368 data_time: 0.0364 memory: 17006 grad_norm: 4.9788 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2840 loss: 1.2840 2022/10/13 12:15:12 - mmengine - INFO - Epoch(train) [95][360/940] lr: 1.0000e-04 eta: 0:45:00 time: 0.4817 data_time: 0.0294 memory: 17006 grad_norm: 4.9710 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2465 loss: 1.2465 2022/10/13 12:15:22 - mmengine - INFO - Epoch(train) [95][380/940] lr: 1.0000e-04 eta: 0:44:50 time: 0.5220 data_time: 0.0305 memory: 17006 grad_norm: 4.9574 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3017 loss: 1.3017 2022/10/13 12:15:31 - mmengine - INFO - Epoch(train) [95][400/940] lr: 1.0000e-04 eta: 0:44:39 time: 0.4556 data_time: 0.0351 memory: 17006 grad_norm: 4.9601 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.1992 loss: 1.1992 2022/10/13 12:15:42 - mmengine - INFO - Epoch(train) [95][420/940] lr: 1.0000e-04 eta: 0:44:29 time: 0.5394 data_time: 0.0296 memory: 17006 grad_norm: 4.8952 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2475 loss: 1.2475 2022/10/13 12:15:52 - mmengine - INFO - Epoch(train) [95][440/940] lr: 1.0000e-04 eta: 0:44:19 time: 0.4817 data_time: 0.0379 memory: 17006 grad_norm: 5.0624 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3149 loss: 1.3149 2022/10/13 12:16:02 - mmengine - INFO - Epoch(train) [95][460/940] lr: 1.0000e-04 eta: 0:44:09 time: 0.5295 data_time: 0.0281 memory: 17006 grad_norm: 4.8842 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2051 loss: 1.2051 2022/10/13 12:16:13 - mmengine - INFO - Epoch(train) [95][480/940] lr: 1.0000e-04 eta: 0:43:58 time: 0.5090 data_time: 0.0371 memory: 17006 grad_norm: 4.8951 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2448 loss: 1.2448 2022/10/13 12:16:22 - mmengine - INFO - Epoch(train) [95][500/940] lr: 1.0000e-04 eta: 0:43:48 time: 0.4906 data_time: 0.0367 memory: 17006 grad_norm: 4.9675 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2053 loss: 1.2053 2022/10/13 12:16:34 - mmengine - INFO - Epoch(train) [95][520/940] lr: 1.0000e-04 eta: 0:43:38 time: 0.5798 data_time: 0.1048 memory: 17006 grad_norm: 4.9724 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.1962 loss: 1.1962 2022/10/13 12:16:44 - mmengine - INFO - Epoch(train) [95][540/940] lr: 1.0000e-04 eta: 0:43:28 time: 0.4995 data_time: 0.0315 memory: 17006 grad_norm: 5.0429 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4035 loss: 1.4035 2022/10/13 12:16:54 - mmengine - INFO - Epoch(train) [95][560/940] lr: 1.0000e-04 eta: 0:43:17 time: 0.5181 data_time: 0.0359 memory: 17006 grad_norm: 4.9027 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1177 loss: 1.1177 2022/10/13 12:17:04 - mmengine - INFO - Epoch(train) [95][580/940] lr: 1.0000e-04 eta: 0:43:07 time: 0.4726 data_time: 0.0299 memory: 17006 grad_norm: 4.9754 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3292 loss: 1.3292 2022/10/13 12:17:15 - mmengine - INFO - Epoch(train) [95][600/940] lr: 1.0000e-04 eta: 0:42:57 time: 0.5345 data_time: 0.0433 memory: 17006 grad_norm: 4.8950 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.1588 loss: 1.1588 2022/10/13 12:17:24 - mmengine - INFO - Epoch(train) [95][620/940] lr: 1.0000e-04 eta: 0:42:47 time: 0.4912 data_time: 0.0314 memory: 17006 grad_norm: 5.0352 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4220 loss: 1.4220 2022/10/13 12:17:35 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 12:17:35 - mmengine - INFO - Epoch(train) [95][640/940] lr: 1.0000e-04 eta: 0:42:37 time: 0.5518 data_time: 0.0378 memory: 17006 grad_norm: 4.8695 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4718 loss: 1.4718 2022/10/13 12:17:46 - mmengine - INFO - Epoch(train) [95][660/940] lr: 1.0000e-04 eta: 0:42:26 time: 0.5057 data_time: 0.0356 memory: 17006 grad_norm: 5.0159 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1705 loss: 1.1705 2022/10/13 12:17:57 - mmengine - INFO - Epoch(train) [95][680/940] lr: 1.0000e-04 eta: 0:42:16 time: 0.5850 data_time: 0.0363 memory: 17006 grad_norm: 4.8462 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1886 loss: 1.1886 2022/10/13 12:18:06 - mmengine - INFO - Epoch(train) [95][700/940] lr: 1.0000e-04 eta: 0:42:06 time: 0.4531 data_time: 0.0316 memory: 17006 grad_norm: 5.0003 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2344 loss: 1.2344 2022/10/13 12:18:17 - mmengine - INFO - Epoch(train) [95][720/940] lr: 1.0000e-04 eta: 0:41:56 time: 0.5425 data_time: 0.0315 memory: 17006 grad_norm: 5.0166 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2548 loss: 1.2548 2022/10/13 12:18:27 - mmengine - INFO - Epoch(train) [95][740/940] lr: 1.0000e-04 eta: 0:41:45 time: 0.4856 data_time: 0.0329 memory: 17006 grad_norm: 4.9929 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2771 loss: 1.2771 2022/10/13 12:18:37 - mmengine - INFO - Epoch(train) [95][760/940] lr: 1.0000e-04 eta: 0:41:35 time: 0.4976 data_time: 0.0393 memory: 17006 grad_norm: 4.9243 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2720 loss: 1.2720 2022/10/13 12:18:47 - mmengine - INFO - Epoch(train) [95][780/940] lr: 1.0000e-04 eta: 0:41:25 time: 0.4907 data_time: 0.0595 memory: 17006 grad_norm: 5.0144 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2773 loss: 1.2773 2022/10/13 12:18:58 - mmengine - INFO - Epoch(train) [95][800/940] lr: 1.0000e-04 eta: 0:41:15 time: 0.5636 data_time: 0.0337 memory: 17006 grad_norm: 5.0134 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2165 loss: 1.2165 2022/10/13 12:19:08 - mmengine - INFO - Epoch(train) [95][820/940] lr: 1.0000e-04 eta: 0:41:05 time: 0.5034 data_time: 0.0298 memory: 17006 grad_norm: 5.0032 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2042 loss: 1.2042 2022/10/13 12:19:19 - mmengine - INFO - Epoch(train) [95][840/940] lr: 1.0000e-04 eta: 0:40:54 time: 0.5305 data_time: 0.0335 memory: 17006 grad_norm: 4.9889 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2239 loss: 1.2239 2022/10/13 12:19:29 - mmengine - INFO - Epoch(train) [95][860/940] lr: 1.0000e-04 eta: 0:40:44 time: 0.5047 data_time: 0.0332 memory: 17006 grad_norm: 4.8779 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3531 loss: 1.3531 2022/10/13 12:19:39 - mmengine - INFO - Epoch(train) [95][880/940] lr: 1.0000e-04 eta: 0:40:34 time: 0.5006 data_time: 0.0401 memory: 17006 grad_norm: 5.0073 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3181 loss: 1.3181 2022/10/13 12:19:49 - mmengine - INFO - Epoch(train) [95][900/940] lr: 1.0000e-04 eta: 0:40:24 time: 0.5091 data_time: 0.0316 memory: 17006 grad_norm: 4.9101 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3444 loss: 1.3444 2022/10/13 12:19:59 - mmengine - INFO - Epoch(train) [95][920/940] lr: 1.0000e-04 eta: 0:40:13 time: 0.4841 data_time: 0.0395 memory: 17006 grad_norm: 4.9722 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3291 loss: 1.3291 2022/10/13 12:20:09 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 12:20:09 - mmengine - INFO - Epoch(train) [95][940/940] lr: 1.0000e-04 eta: 0:40:03 time: 0.4952 data_time: 0.0242 memory: 17006 grad_norm: 5.2917 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.2757 loss: 1.2757 2022/10/13 12:20:21 - mmengine - INFO - Epoch(val) [95][20/78] eta: 0:00:36 time: 0.6372 data_time: 0.5447 memory: 3172 2022/10/13 12:20:30 - mmengine - INFO - Epoch(val) [95][40/78] eta: 0:00:16 time: 0.4276 data_time: 0.3374 memory: 3172 2022/10/13 12:20:41 - mmengine - INFO - Epoch(val) [95][60/78] eta: 0:00:10 time: 0.5700 data_time: 0.4781 memory: 3172 2022/10/13 12:20:51 - mmengine - INFO - Epoch(val) [95][78/78] acc/top1: 0.6755 acc/top5: 0.8700 acc/mean1: 0.6755 2022/10/13 12:21:06 - mmengine - INFO - Epoch(train) [96][20/940] lr: 1.0000e-04 eta: 0:39:53 time: 0.7358 data_time: 0.3284 memory: 17006 grad_norm: 4.9015 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2360 loss: 1.2360 2022/10/13 12:21:15 - mmengine - INFO - Epoch(train) [96][40/940] lr: 1.0000e-04 eta: 0:39:43 time: 0.4545 data_time: 0.0574 memory: 17006 grad_norm: 4.9215 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2652 loss: 1.2652 2022/10/13 12:21:26 - mmengine - INFO - Epoch(train) [96][60/940] lr: 1.0000e-04 eta: 0:39:33 time: 0.5641 data_time: 0.1432 memory: 17006 grad_norm: 4.8262 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2729 loss: 1.2729 2022/10/13 12:21:37 - mmengine - INFO - Epoch(train) [96][80/940] lr: 1.0000e-04 eta: 0:39:22 time: 0.5387 data_time: 0.1984 memory: 17006 grad_norm: 4.8859 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3201 loss: 1.3201 2022/10/13 12:21:49 - mmengine - INFO - Epoch(train) [96][100/940] lr: 1.0000e-04 eta: 0:39:12 time: 0.5828 data_time: 0.1500 memory: 17006 grad_norm: 4.8754 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3113 loss: 1.3113 2022/10/13 12:22:00 - mmengine - INFO - Epoch(train) [96][120/940] lr: 1.0000e-04 eta: 0:39:02 time: 0.5384 data_time: 0.1225 memory: 17006 grad_norm: 5.0113 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2743 loss: 1.2743 2022/10/13 12:22:09 - mmengine - INFO - Epoch(train) [96][140/940] lr: 1.0000e-04 eta: 0:38:52 time: 0.4655 data_time: 0.1232 memory: 17006 grad_norm: 4.8912 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2437 loss: 1.2437 2022/10/13 12:22:19 - mmengine - INFO - Epoch(train) [96][160/940] lr: 1.0000e-04 eta: 0:38:42 time: 0.4964 data_time: 0.1653 memory: 17006 grad_norm: 4.9042 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1764 loss: 1.1764 2022/10/13 12:22:29 - mmengine - INFO - Epoch(train) [96][180/940] lr: 1.0000e-04 eta: 0:38:31 time: 0.5145 data_time: 0.0924 memory: 17006 grad_norm: 5.0360 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3336 loss: 1.3336 2022/10/13 12:22:39 - mmengine - INFO - Epoch(train) [96][200/940] lr: 1.0000e-04 eta: 0:38:21 time: 0.5084 data_time: 0.0315 memory: 17006 grad_norm: 4.9944 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2694 loss: 1.2694 2022/10/13 12:22:51 - mmengine - INFO - Epoch(train) [96][220/940] lr: 1.0000e-04 eta: 0:38:11 time: 0.5689 data_time: 0.0308 memory: 17006 grad_norm: 4.9236 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2355 loss: 1.2355 2022/10/13 12:23:00 - mmengine - INFO - Epoch(train) [96][240/940] lr: 1.0000e-04 eta: 0:38:01 time: 0.4522 data_time: 0.0338 memory: 17006 grad_norm: 4.9398 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2234 loss: 1.2234 2022/10/13 12:23:11 - mmengine - INFO - Epoch(train) [96][260/940] lr: 1.0000e-04 eta: 0:37:50 time: 0.5708 data_time: 0.0271 memory: 17006 grad_norm: 4.9909 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2153 loss: 1.2153 2022/10/13 12:23:21 - mmengine - INFO - Epoch(train) [96][280/940] lr: 1.0000e-04 eta: 0:37:40 time: 0.4812 data_time: 0.0336 memory: 17006 grad_norm: 5.0129 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1759 loss: 1.1759 2022/10/13 12:23:31 - mmengine - INFO - Epoch(train) [96][300/940] lr: 1.0000e-04 eta: 0:37:30 time: 0.5137 data_time: 0.0341 memory: 17006 grad_norm: 4.9108 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1777 loss: 1.1777 2022/10/13 12:23:42 - mmengine - INFO - Epoch(train) [96][320/940] lr: 1.0000e-04 eta: 0:37:20 time: 0.5390 data_time: 0.0570 memory: 17006 grad_norm: 4.8622 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1778 loss: 1.1778 2022/10/13 12:23:52 - mmengine - INFO - Epoch(train) [96][340/940] lr: 1.0000e-04 eta: 0:37:10 time: 0.5298 data_time: 0.0270 memory: 17006 grad_norm: 4.8496 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3617 loss: 1.3617 2022/10/13 12:24:02 - mmengine - INFO - Epoch(train) [96][360/940] lr: 1.0000e-04 eta: 0:36:59 time: 0.4704 data_time: 0.0323 memory: 17006 grad_norm: 4.9096 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.1085 loss: 1.1085 2022/10/13 12:24:13 - mmengine - INFO - Epoch(train) [96][380/940] lr: 1.0000e-04 eta: 0:36:49 time: 0.5725 data_time: 0.0332 memory: 17006 grad_norm: 4.9093 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3241 loss: 1.3241 2022/10/13 12:24:23 - mmengine - INFO - Epoch(train) [96][400/940] lr: 1.0000e-04 eta: 0:36:39 time: 0.4913 data_time: 0.0371 memory: 17006 grad_norm: 4.9496 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2983 loss: 1.2983 2022/10/13 12:24:34 - mmengine - INFO - Epoch(train) [96][420/940] lr: 1.0000e-04 eta: 0:36:29 time: 0.5655 data_time: 0.0317 memory: 17006 grad_norm: 4.8618 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2125 loss: 1.2125 2022/10/13 12:24:45 - mmengine - INFO - Epoch(train) [96][440/940] lr: 1.0000e-04 eta: 0:36:19 time: 0.5145 data_time: 0.0319 memory: 17006 grad_norm: 4.9608 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.2687 loss: 1.2687 2022/10/13 12:24:56 - mmengine - INFO - Epoch(train) [96][460/940] lr: 1.0000e-04 eta: 0:36:08 time: 0.5711 data_time: 0.0277 memory: 17006 grad_norm: 4.9527 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3116 loss: 1.3116 2022/10/13 12:25:05 - mmengine - INFO - Epoch(train) [96][480/940] lr: 1.0000e-04 eta: 0:35:58 time: 0.4395 data_time: 0.0322 memory: 17006 grad_norm: 4.9626 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3264 loss: 1.3264 2022/10/13 12:25:15 - mmengine - INFO - Epoch(train) [96][500/940] lr: 1.0000e-04 eta: 0:35:48 time: 0.5228 data_time: 0.0347 memory: 17006 grad_norm: 5.0054 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2868 loss: 1.2868 2022/10/13 12:25:25 - mmengine - INFO - Epoch(train) [96][520/940] lr: 1.0000e-04 eta: 0:35:38 time: 0.4796 data_time: 0.0329 memory: 17006 grad_norm: 4.9859 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2442 loss: 1.2442 2022/10/13 12:25:36 - mmengine - INFO - Epoch(train) [96][540/940] lr: 1.0000e-04 eta: 0:35:27 time: 0.5665 data_time: 0.0351 memory: 17006 grad_norm: 5.0357 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2170 loss: 1.2170 2022/10/13 12:25:46 - mmengine - INFO - Epoch(train) [96][560/940] lr: 1.0000e-04 eta: 0:35:17 time: 0.4703 data_time: 0.0367 memory: 17006 grad_norm: 4.9284 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2544 loss: 1.2544 2022/10/13 12:25:56 - mmengine - INFO - Epoch(train) [96][580/940] lr: 1.0000e-04 eta: 0:35:07 time: 0.5317 data_time: 0.0278 memory: 17006 grad_norm: 5.0344 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3030 loss: 1.3030 2022/10/13 12:26:06 - mmengine - INFO - Epoch(train) [96][600/940] lr: 1.0000e-04 eta: 0:34:57 time: 0.4769 data_time: 0.0420 memory: 17006 grad_norm: 5.0331 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2859 loss: 1.2859 2022/10/13 12:26:17 - mmengine - INFO - Epoch(train) [96][620/940] lr: 1.0000e-04 eta: 0:34:46 time: 0.5377 data_time: 0.0378 memory: 17006 grad_norm: 4.9583 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2475 loss: 1.2475 2022/10/13 12:26:27 - mmengine - INFO - Epoch(train) [96][640/940] lr: 1.0000e-04 eta: 0:34:36 time: 0.5137 data_time: 0.0363 memory: 17006 grad_norm: 4.9726 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2027 loss: 1.2027 2022/10/13 12:26:38 - mmengine - INFO - Epoch(train) [96][660/940] lr: 1.0000e-04 eta: 0:34:26 time: 0.5368 data_time: 0.0307 memory: 17006 grad_norm: 4.8711 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3082 loss: 1.3082 2022/10/13 12:26:48 - mmengine - INFO - Epoch(train) [96][680/940] lr: 1.0000e-04 eta: 0:34:16 time: 0.5171 data_time: 0.0388 memory: 17006 grad_norm: 5.0377 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2441 loss: 1.2441 2022/10/13 12:26:58 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 12:26:58 - mmengine - INFO - Epoch(train) [96][700/940] lr: 1.0000e-04 eta: 0:34:06 time: 0.5131 data_time: 0.0337 memory: 17006 grad_norm: 4.9923 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2184 loss: 1.2184 2022/10/13 12:27:09 - mmengine - INFO - Epoch(train) [96][720/940] lr: 1.0000e-04 eta: 0:33:55 time: 0.5250 data_time: 0.0324 memory: 17006 grad_norm: 4.9509 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.1563 loss: 1.1563 2022/10/13 12:27:19 - mmengine - INFO - Epoch(train) [96][740/940] lr: 1.0000e-04 eta: 0:33:45 time: 0.4963 data_time: 0.0313 memory: 17006 grad_norm: 4.8462 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.1923 loss: 1.1923 2022/10/13 12:27:29 - mmengine - INFO - Epoch(train) [96][760/940] lr: 1.0000e-04 eta: 0:33:35 time: 0.5177 data_time: 0.0342 memory: 17006 grad_norm: 5.0206 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3145 loss: 1.3145 2022/10/13 12:27:40 - mmengine - INFO - Epoch(train) [96][780/940] lr: 1.0000e-04 eta: 0:33:25 time: 0.5441 data_time: 0.0331 memory: 17006 grad_norm: 5.0739 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2209 loss: 1.2209 2022/10/13 12:27:50 - mmengine - INFO - Epoch(train) [96][800/940] lr: 1.0000e-04 eta: 0:33:14 time: 0.5209 data_time: 0.0354 memory: 17006 grad_norm: 4.8643 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2795 loss: 1.2795 2022/10/13 12:28:00 - mmengine - INFO - Epoch(train) [96][820/940] lr: 1.0000e-04 eta: 0:33:04 time: 0.4681 data_time: 0.0315 memory: 17006 grad_norm: 4.9128 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2402 loss: 1.2402 2022/10/13 12:28:11 - mmengine - INFO - Epoch(train) [96][840/940] lr: 1.0000e-04 eta: 0:32:54 time: 0.5694 data_time: 0.0325 memory: 17006 grad_norm: 5.0252 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2534 loss: 1.2534 2022/10/13 12:28:21 - mmengine - INFO - Epoch(train) [96][860/940] lr: 1.0000e-04 eta: 0:32:44 time: 0.4840 data_time: 0.0304 memory: 17006 grad_norm: 5.0582 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.3405 loss: 1.3405 2022/10/13 12:28:31 - mmengine - INFO - Epoch(train) [96][880/940] lr: 1.0000e-04 eta: 0:32:33 time: 0.5207 data_time: 0.0297 memory: 17006 grad_norm: 4.9895 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.1706 loss: 1.1706 2022/10/13 12:28:42 - mmengine - INFO - Epoch(train) [96][900/940] lr: 1.0000e-04 eta: 0:32:23 time: 0.5360 data_time: 0.0295 memory: 17006 grad_norm: 5.0537 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3669 loss: 1.3669 2022/10/13 12:28:52 - mmengine - INFO - Epoch(train) [96][920/940] lr: 1.0000e-04 eta: 0:32:13 time: 0.4856 data_time: 0.0350 memory: 17006 grad_norm: 4.8881 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.1254 loss: 1.1254 2022/10/13 12:29:01 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 12:29:01 - mmengine - INFO - Epoch(train) [96][940/940] lr: 1.0000e-04 eta: 0:32:03 time: 0.4664 data_time: 0.0272 memory: 17006 grad_norm: 5.4112 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.2637 loss: 1.2637 2022/10/13 12:29:01 - mmengine - INFO - Saving checkpoint at 96 epochs 2022/10/13 12:29:15 - mmengine - INFO - Epoch(val) [96][20/78] eta: 0:00:37 time: 0.6508 data_time: 0.5623 memory: 3172 2022/10/13 12:29:24 - mmengine - INFO - Epoch(val) [96][40/78] eta: 0:00:17 time: 0.4625 data_time: 0.3743 memory: 3172 2022/10/13 12:29:35 - mmengine - INFO - Epoch(val) [96][60/78] eta: 0:00:09 time: 0.5332 data_time: 0.4434 memory: 3172 2022/10/13 12:29:45 - mmengine - INFO - Epoch(val) [96][78/78] acc/top1: 0.6758 acc/top5: 0.8697 acc/mean1: 0.6757 2022/10/13 12:29:59 - mmengine - INFO - Epoch(train) [97][20/940] lr: 1.0000e-04 eta: 0:31:53 time: 0.6944 data_time: 0.2809 memory: 17006 grad_norm: 4.9133 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2528 loss: 1.2528 2022/10/13 12:30:10 - mmengine - INFO - Epoch(train) [97][40/940] lr: 1.0000e-04 eta: 0:31:43 time: 0.5628 data_time: 0.0420 memory: 17006 grad_norm: 4.9556 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2545 loss: 1.2545 2022/10/13 12:30:21 - mmengine - INFO - Epoch(train) [97][60/940] lr: 1.0000e-04 eta: 0:31:32 time: 0.5490 data_time: 0.0335 memory: 17006 grad_norm: 4.8475 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0232 loss: 1.0232 2022/10/13 12:30:30 - mmengine - INFO - Epoch(train) [97][80/940] lr: 1.0000e-04 eta: 0:31:22 time: 0.4263 data_time: 0.0272 memory: 17006 grad_norm: 4.8951 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2155 loss: 1.2155 2022/10/13 12:30:42 - mmengine - INFO - Epoch(train) [97][100/940] lr: 1.0000e-04 eta: 0:31:12 time: 0.6079 data_time: 0.0274 memory: 17006 grad_norm: 4.9589 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1950 loss: 1.1950 2022/10/13 12:30:51 - mmengine - INFO - Epoch(train) [97][120/940] lr: 1.0000e-04 eta: 0:31:02 time: 0.4692 data_time: 0.0336 memory: 17006 grad_norm: 5.0010 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3546 loss: 1.3546 2022/10/13 12:31:03 - mmengine - INFO - Epoch(train) [97][140/940] lr: 1.0000e-04 eta: 0:30:51 time: 0.5887 data_time: 0.0349 memory: 17006 grad_norm: 4.8822 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2950 loss: 1.2950 2022/10/13 12:31:13 - mmengine - INFO - Epoch(train) [97][160/940] lr: 1.0000e-04 eta: 0:30:41 time: 0.4876 data_time: 0.0362 memory: 17006 grad_norm: 5.0293 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.1643 loss: 1.1643 2022/10/13 12:31:23 - mmengine - INFO - Epoch(train) [97][180/940] lr: 1.0000e-04 eta: 0:30:31 time: 0.5127 data_time: 0.0316 memory: 17006 grad_norm: 5.0527 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3506 loss: 1.3506 2022/10/13 12:31:32 - mmengine - INFO - Epoch(train) [97][200/940] lr: 1.0000e-04 eta: 0:30:21 time: 0.4489 data_time: 0.0278 memory: 17006 grad_norm: 4.9084 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2801 loss: 1.2801 2022/10/13 12:31:42 - mmengine - INFO - Epoch(train) [97][220/940] lr: 1.0000e-04 eta: 0:30:10 time: 0.5179 data_time: 0.0344 memory: 17006 grad_norm: 4.9902 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.2089 loss: 1.2089 2022/10/13 12:31:52 - mmengine - INFO - Epoch(train) [97][240/940] lr: 1.0000e-04 eta: 0:30:00 time: 0.5122 data_time: 0.0362 memory: 17006 grad_norm: 4.8751 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1775 loss: 1.1775 2022/10/13 12:32:03 - mmengine - INFO - Epoch(train) [97][260/940] lr: 1.0000e-04 eta: 0:29:50 time: 0.5254 data_time: 0.0372 memory: 17006 grad_norm: 5.0049 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2196 loss: 1.2196 2022/10/13 12:32:13 - mmengine - INFO - Epoch(train) [97][280/940] lr: 1.0000e-04 eta: 0:29:40 time: 0.5124 data_time: 0.0280 memory: 17006 grad_norm: 4.9424 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2445 loss: 1.2445 2022/10/13 12:32:23 - mmengine - INFO - Epoch(train) [97][300/940] lr: 1.0000e-04 eta: 0:29:30 time: 0.4993 data_time: 0.0325 memory: 17006 grad_norm: 5.0046 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4026 loss: 1.4026 2022/10/13 12:32:33 - mmengine - INFO - Epoch(train) [97][320/940] lr: 1.0000e-04 eta: 0:29:19 time: 0.4850 data_time: 0.0283 memory: 17006 grad_norm: 4.9917 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3251 loss: 1.3251 2022/10/13 12:32:44 - mmengine - INFO - Epoch(train) [97][340/940] lr: 1.0000e-04 eta: 0:29:09 time: 0.5522 data_time: 0.0374 memory: 17006 grad_norm: 5.0527 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3484 loss: 1.3484 2022/10/13 12:32:54 - mmengine - INFO - Epoch(train) [97][360/940] lr: 1.0000e-04 eta: 0:28:59 time: 0.5118 data_time: 0.0285 memory: 17006 grad_norm: 4.8607 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3074 loss: 1.3074 2022/10/13 12:33:05 - mmengine - INFO - Epoch(train) [97][380/940] lr: 1.0000e-04 eta: 0:28:49 time: 0.5645 data_time: 0.0342 memory: 17006 grad_norm: 4.9489 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2796 loss: 1.2796 2022/10/13 12:33:15 - mmengine - INFO - Epoch(train) [97][400/940] lr: 1.0000e-04 eta: 0:28:38 time: 0.4800 data_time: 0.0356 memory: 17006 grad_norm: 5.0392 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.1387 loss: 1.1387 2022/10/13 12:33:26 - mmengine - INFO - Epoch(train) [97][420/940] lr: 1.0000e-04 eta: 0:28:28 time: 0.5395 data_time: 0.0329 memory: 17006 grad_norm: 4.9358 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.1608 loss: 1.1608 2022/10/13 12:33:35 - mmengine - INFO - Epoch(train) [97][440/940] lr: 1.0000e-04 eta: 0:28:18 time: 0.4735 data_time: 0.0283 memory: 17006 grad_norm: 4.8917 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2059 loss: 1.2059 2022/10/13 12:33:47 - mmengine - INFO - Epoch(train) [97][460/940] lr: 1.0000e-04 eta: 0:28:08 time: 0.5759 data_time: 0.0369 memory: 17006 grad_norm: 4.9201 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2374 loss: 1.2374 2022/10/13 12:33:57 - mmengine - INFO - Epoch(train) [97][480/940] lr: 1.0000e-04 eta: 0:27:57 time: 0.5073 data_time: 0.0269 memory: 17006 grad_norm: 4.9296 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3104 loss: 1.3104 2022/10/13 12:34:07 - mmengine - INFO - Epoch(train) [97][500/940] lr: 1.0000e-04 eta: 0:27:47 time: 0.4916 data_time: 0.0323 memory: 17006 grad_norm: 4.9292 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2168 loss: 1.2168 2022/10/13 12:34:16 - mmengine - INFO - Epoch(train) [97][520/940] lr: 1.0000e-04 eta: 0:27:37 time: 0.4820 data_time: 0.0311 memory: 17006 grad_norm: 4.7732 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2218 loss: 1.2218 2022/10/13 12:34:27 - mmengine - INFO - Epoch(train) [97][540/940] lr: 1.0000e-04 eta: 0:27:27 time: 0.5158 data_time: 0.0367 memory: 17006 grad_norm: 4.9845 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1569 loss: 1.1569 2022/10/13 12:34:37 - mmengine - INFO - Epoch(train) [97][560/940] lr: 1.0000e-04 eta: 0:27:17 time: 0.5197 data_time: 0.0337 memory: 17006 grad_norm: 5.0181 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2599 loss: 1.2599 2022/10/13 12:34:48 - mmengine - INFO - Epoch(train) [97][580/940] lr: 1.0000e-04 eta: 0:27:06 time: 0.5210 data_time: 0.0303 memory: 17006 grad_norm: 4.9386 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.1081 loss: 1.1081 2022/10/13 12:34:59 - mmengine - INFO - Epoch(train) [97][600/940] lr: 1.0000e-04 eta: 0:26:56 time: 0.5713 data_time: 0.0402 memory: 17006 grad_norm: 4.9430 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.2980 loss: 1.2980 2022/10/13 12:35:10 - mmengine - INFO - Epoch(train) [97][620/940] lr: 1.0000e-04 eta: 0:26:46 time: 0.5443 data_time: 0.0275 memory: 17006 grad_norm: 4.9589 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3161 loss: 1.3161 2022/10/13 12:35:21 - mmengine - INFO - Epoch(train) [97][640/940] lr: 1.0000e-04 eta: 0:26:36 time: 0.5389 data_time: 0.0310 memory: 17006 grad_norm: 4.9391 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.2809 loss: 1.2809 2022/10/13 12:35:30 - mmengine - INFO - Epoch(train) [97][660/940] lr: 1.0000e-04 eta: 0:26:25 time: 0.4535 data_time: 0.0299 memory: 17006 grad_norm: 4.9049 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2491 loss: 1.2491 2022/10/13 12:35:41 - mmengine - INFO - Epoch(train) [97][680/940] lr: 1.0000e-04 eta: 0:26:15 time: 0.5711 data_time: 0.0338 memory: 17006 grad_norm: 5.0189 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1196 loss: 1.1196 2022/10/13 12:35:50 - mmengine - INFO - Epoch(train) [97][700/940] lr: 1.0000e-04 eta: 0:26:05 time: 0.4576 data_time: 0.0328 memory: 17006 grad_norm: 5.0231 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3048 loss: 1.3048 2022/10/13 12:36:01 - mmengine - INFO - Epoch(train) [97][720/940] lr: 1.0000e-04 eta: 0:25:55 time: 0.5394 data_time: 0.0271 memory: 17006 grad_norm: 4.9366 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3764 loss: 1.3764 2022/10/13 12:36:11 - mmengine - INFO - Epoch(train) [97][740/940] lr: 1.0000e-04 eta: 0:25:45 time: 0.4997 data_time: 0.0322 memory: 17006 grad_norm: 4.9165 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1895 loss: 1.1895 2022/10/13 12:36:23 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 12:36:23 - mmengine - INFO - Epoch(train) [97][760/940] lr: 1.0000e-04 eta: 0:25:34 time: 0.5765 data_time: 0.0299 memory: 17006 grad_norm: 4.9635 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.3634 loss: 1.3634 2022/10/13 12:36:32 - mmengine - INFO - Epoch(train) [97][780/940] lr: 1.0000e-04 eta: 0:25:24 time: 0.4804 data_time: 0.0308 memory: 17006 grad_norm: 4.9590 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3411 loss: 1.3411 2022/10/13 12:36:43 - mmengine - INFO - Epoch(train) [97][800/940] lr: 1.0000e-04 eta: 0:25:14 time: 0.5340 data_time: 0.0329 memory: 17006 grad_norm: 5.0386 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4708 loss: 1.4708 2022/10/13 12:36:53 - mmengine - INFO - Epoch(train) [97][820/940] lr: 1.0000e-04 eta: 0:25:04 time: 0.5072 data_time: 0.0268 memory: 17006 grad_norm: 4.9874 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1758 loss: 1.1758 2022/10/13 12:37:04 - mmengine - INFO - Epoch(train) [97][840/940] lr: 1.0000e-04 eta: 0:24:53 time: 0.5239 data_time: 0.0313 memory: 17006 grad_norm: 4.9522 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2182 loss: 1.2182 2022/10/13 12:37:13 - mmengine - INFO - Epoch(train) [97][860/940] lr: 1.0000e-04 eta: 0:24:43 time: 0.4714 data_time: 0.0342 memory: 17006 grad_norm: 4.8826 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1545 loss: 1.1545 2022/10/13 12:37:23 - mmengine - INFO - Epoch(train) [97][880/940] lr: 1.0000e-04 eta: 0:24:33 time: 0.5185 data_time: 0.0384 memory: 17006 grad_norm: 4.8446 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2007 loss: 1.2007 2022/10/13 12:37:33 - mmengine - INFO - Epoch(train) [97][900/940] lr: 1.0000e-04 eta: 0:24:23 time: 0.4980 data_time: 0.0376 memory: 17006 grad_norm: 5.0450 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.1640 loss: 1.1640 2022/10/13 12:37:44 - mmengine - INFO - Epoch(train) [97][920/940] lr: 1.0000e-04 eta: 0:24:12 time: 0.5403 data_time: 0.0339 memory: 17006 grad_norm: 4.9521 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.3372 loss: 1.3372 2022/10/13 12:37:54 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 12:37:54 - mmengine - INFO - Epoch(train) [97][940/940] lr: 1.0000e-04 eta: 0:24:02 time: 0.4827 data_time: 0.0252 memory: 17006 grad_norm: 5.2949 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.3601 loss: 1.3601 2022/10/13 12:38:07 - mmengine - INFO - Epoch(val) [97][20/78] eta: 0:00:38 time: 0.6614 data_time: 0.5696 memory: 3172 2022/10/13 12:38:16 - mmengine - INFO - Epoch(val) [97][40/78] eta: 0:00:16 time: 0.4293 data_time: 0.3364 memory: 3172 2022/10/13 12:38:27 - mmengine - INFO - Epoch(val) [97][60/78] eta: 0:00:10 time: 0.5771 data_time: 0.4861 memory: 3172 2022/10/13 12:38:38 - mmengine - INFO - Epoch(val) [97][78/78] acc/top1: 0.6759 acc/top5: 0.8687 acc/mean1: 0.6758 2022/10/13 12:38:52 - mmengine - INFO - Epoch(train) [98][20/940] lr: 1.0000e-04 eta: 0:23:52 time: 0.7014 data_time: 0.2873 memory: 17006 grad_norm: 4.9092 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2795 loss: 1.2795 2022/10/13 12:39:02 - mmengine - INFO - Epoch(train) [98][40/940] lr: 1.0000e-04 eta: 0:23:42 time: 0.4930 data_time: 0.0260 memory: 17006 grad_norm: 4.9922 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3299 loss: 1.3299 2022/10/13 12:39:12 - mmengine - INFO - Epoch(train) [98][60/940] lr: 1.0000e-04 eta: 0:23:32 time: 0.5458 data_time: 0.0313 memory: 17006 grad_norm: 5.0464 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2743 loss: 1.2743 2022/10/13 12:39:23 - mmengine - INFO - Epoch(train) [98][80/940] lr: 1.0000e-04 eta: 0:23:21 time: 0.5238 data_time: 0.0251 memory: 17006 grad_norm: 4.9549 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2731 loss: 1.2731 2022/10/13 12:39:34 - mmengine - INFO - Epoch(train) [98][100/940] lr: 1.0000e-04 eta: 0:23:11 time: 0.5546 data_time: 0.0317 memory: 17006 grad_norm: 4.9087 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2116 loss: 1.2116 2022/10/13 12:39:43 - mmengine - INFO - Epoch(train) [98][120/940] lr: 1.0000e-04 eta: 0:23:01 time: 0.4643 data_time: 0.0382 memory: 17006 grad_norm: 5.0340 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2517 loss: 1.2517 2022/10/13 12:39:55 - mmengine - INFO - Epoch(train) [98][140/940] lr: 1.0000e-04 eta: 0:22:51 time: 0.5941 data_time: 0.0308 memory: 17006 grad_norm: 5.0731 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.2963 loss: 1.2963 2022/10/13 12:40:05 - mmengine - INFO - Epoch(train) [98][160/940] lr: 1.0000e-04 eta: 0:22:40 time: 0.4683 data_time: 0.0314 memory: 17006 grad_norm: 4.9729 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2764 loss: 1.2764 2022/10/13 12:40:15 - mmengine - INFO - Epoch(train) [98][180/940] lr: 1.0000e-04 eta: 0:22:30 time: 0.5279 data_time: 0.0326 memory: 17006 grad_norm: 4.9030 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3501 loss: 1.3501 2022/10/13 12:40:24 - mmengine - INFO - Epoch(train) [98][200/940] lr: 1.0000e-04 eta: 0:22:20 time: 0.4513 data_time: 0.0324 memory: 17006 grad_norm: 4.9390 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.1288 loss: 1.1288 2022/10/13 12:40:36 - mmengine - INFO - Epoch(train) [98][220/940] lr: 1.0000e-04 eta: 0:22:10 time: 0.5912 data_time: 0.0381 memory: 17006 grad_norm: 4.9049 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2879 loss: 1.2879 2022/10/13 12:40:45 - mmengine - INFO - Epoch(train) [98][240/940] lr: 1.0000e-04 eta: 0:22:00 time: 0.4715 data_time: 0.0316 memory: 17006 grad_norm: 4.9991 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3550 loss: 1.3550 2022/10/13 12:40:57 - mmengine - INFO - Epoch(train) [98][260/940] lr: 1.0000e-04 eta: 0:21:49 time: 0.5693 data_time: 0.0335 memory: 17006 grad_norm: 4.8918 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.1918 loss: 1.1918 2022/10/13 12:41:06 - mmengine - INFO - Epoch(train) [98][280/940] lr: 1.0000e-04 eta: 0:21:39 time: 0.4617 data_time: 0.0287 memory: 17006 grad_norm: 4.8599 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.2325 loss: 1.2325 2022/10/13 12:41:18 - mmengine - INFO - Epoch(train) [98][300/940] lr: 1.0000e-04 eta: 0:21:29 time: 0.5844 data_time: 0.0390 memory: 17006 grad_norm: 5.0337 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3192 loss: 1.3192 2022/10/13 12:41:27 - mmengine - INFO - Epoch(train) [98][320/940] lr: 1.0000e-04 eta: 0:21:19 time: 0.4761 data_time: 0.0337 memory: 17006 grad_norm: 4.9689 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3219 loss: 1.3219 2022/10/13 12:41:38 - mmengine - INFO - Epoch(train) [98][340/940] lr: 1.0000e-04 eta: 0:21:08 time: 0.5282 data_time: 0.0323 memory: 17006 grad_norm: 5.0226 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2641 loss: 1.2641 2022/10/13 12:41:49 - mmengine - INFO - Epoch(train) [98][360/940] lr: 1.0000e-04 eta: 0:20:58 time: 0.5377 data_time: 0.0303 memory: 17006 grad_norm: 4.9738 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2833 loss: 1.2833 2022/10/13 12:41:59 - mmengine - INFO - Epoch(train) [98][380/940] lr: 1.0000e-04 eta: 0:20:48 time: 0.5007 data_time: 0.0272 memory: 17006 grad_norm: 4.9045 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1375 loss: 1.1375 2022/10/13 12:42:08 - mmengine - INFO - Epoch(train) [98][400/940] lr: 1.0000e-04 eta: 0:20:38 time: 0.4603 data_time: 0.0315 memory: 17006 grad_norm: 4.8062 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.1495 loss: 1.1495 2022/10/13 12:42:19 - mmengine - INFO - Epoch(train) [98][420/940] lr: 1.0000e-04 eta: 0:20:27 time: 0.5436 data_time: 0.0301 memory: 17006 grad_norm: 4.9763 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.1923 loss: 1.1923 2022/10/13 12:42:28 - mmengine - INFO - Epoch(train) [98][440/940] lr: 1.0000e-04 eta: 0:20:17 time: 0.4771 data_time: 0.0401 memory: 17006 grad_norm: 4.8859 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1091 loss: 1.1091 2022/10/13 12:42:38 - mmengine - INFO - Epoch(train) [98][460/940] lr: 1.0000e-04 eta: 0:20:07 time: 0.5076 data_time: 0.0318 memory: 17006 grad_norm: 4.9205 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2874 loss: 1.2874 2022/10/13 12:42:50 - mmengine - INFO - Epoch(train) [98][480/940] lr: 1.0000e-04 eta: 0:19:57 time: 0.5656 data_time: 0.0386 memory: 17006 grad_norm: 4.9605 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2811 loss: 1.2811 2022/10/13 12:42:59 - mmengine - INFO - Epoch(train) [98][500/940] lr: 1.0000e-04 eta: 0:19:47 time: 0.4633 data_time: 0.0287 memory: 17006 grad_norm: 5.1133 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3277 loss: 1.3277 2022/10/13 12:43:10 - mmengine - INFO - Epoch(train) [98][520/940] lr: 1.0000e-04 eta: 0:19:36 time: 0.5354 data_time: 0.0377 memory: 17006 grad_norm: 4.8622 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.2823 loss: 1.2823 2022/10/13 12:43:19 - mmengine - INFO - Epoch(train) [98][540/940] lr: 1.0000e-04 eta: 0:19:26 time: 0.4683 data_time: 0.0278 memory: 17006 grad_norm: 4.9262 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.3065 loss: 1.3065 2022/10/13 12:43:29 - mmengine - INFO - Epoch(train) [98][560/940] lr: 1.0000e-04 eta: 0:19:16 time: 0.5228 data_time: 0.0374 memory: 17006 grad_norm: 4.9423 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3379 loss: 1.3379 2022/10/13 12:43:40 - mmengine - INFO - Epoch(train) [98][580/940] lr: 1.0000e-04 eta: 0:19:06 time: 0.5132 data_time: 0.0327 memory: 17006 grad_norm: 4.9033 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2855 loss: 1.2855 2022/10/13 12:43:50 - mmengine - INFO - Epoch(train) [98][600/940] lr: 1.0000e-04 eta: 0:18:55 time: 0.5347 data_time: 0.0327 memory: 17006 grad_norm: 4.8930 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2904 loss: 1.2904 2022/10/13 12:44:02 - mmengine - INFO - Epoch(train) [98][620/940] lr: 1.0000e-04 eta: 0:18:45 time: 0.5593 data_time: 0.0358 memory: 17006 grad_norm: 4.8690 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1878 loss: 1.1878 2022/10/13 12:44:11 - mmengine - INFO - Epoch(train) [98][640/940] lr: 1.0000e-04 eta: 0:18:35 time: 0.4746 data_time: 0.0327 memory: 17006 grad_norm: 4.9496 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2524 loss: 1.2524 2022/10/13 12:44:22 - mmengine - INFO - Epoch(train) [98][660/940] lr: 1.0000e-04 eta: 0:18:25 time: 0.5411 data_time: 0.0313 memory: 17006 grad_norm: 5.0197 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2479 loss: 1.2479 2022/10/13 12:44:32 - mmengine - INFO - Epoch(train) [98][680/940] lr: 1.0000e-04 eta: 0:18:14 time: 0.4948 data_time: 0.0327 memory: 17006 grad_norm: 4.9644 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2175 loss: 1.2175 2022/10/13 12:44:43 - mmengine - INFO - Epoch(train) [98][700/940] lr: 1.0000e-04 eta: 0:18:04 time: 0.5393 data_time: 0.0326 memory: 17006 grad_norm: 4.9220 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2542 loss: 1.2542 2022/10/13 12:44:53 - mmengine - INFO - Epoch(train) [98][720/940] lr: 1.0000e-04 eta: 0:17:54 time: 0.5000 data_time: 0.0310 memory: 17006 grad_norm: 4.9680 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.2348 loss: 1.2348 2022/10/13 12:45:03 - mmengine - INFO - Epoch(train) [98][740/940] lr: 1.0000e-04 eta: 0:17:44 time: 0.5143 data_time: 0.0352 memory: 17006 grad_norm: 5.0649 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1390 loss: 1.1390 2022/10/13 12:45:13 - mmengine - INFO - Epoch(train) [98][760/940] lr: 1.0000e-04 eta: 0:17:34 time: 0.5008 data_time: 0.0372 memory: 17006 grad_norm: 4.9648 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.2666 loss: 1.2666 2022/10/13 12:45:25 - mmengine - INFO - Epoch(train) [98][780/940] lr: 1.0000e-04 eta: 0:17:23 time: 0.5883 data_time: 0.0332 memory: 17006 grad_norm: 4.8696 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1527 loss: 1.1527 2022/10/13 12:45:34 - mmengine - INFO - Epoch(train) [98][800/940] lr: 1.0000e-04 eta: 0:17:13 time: 0.4712 data_time: 0.0377 memory: 17006 grad_norm: 5.1368 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.4074 loss: 1.4074 2022/10/13 12:45:45 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 12:45:45 - mmengine - INFO - Epoch(train) [98][820/940] lr: 1.0000e-04 eta: 0:17:03 time: 0.5211 data_time: 0.0366 memory: 17006 grad_norm: 4.9797 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.3640 loss: 1.3640 2022/10/13 12:45:55 - mmengine - INFO - Epoch(train) [98][840/940] lr: 1.0000e-04 eta: 0:16:53 time: 0.5426 data_time: 0.0321 memory: 17006 grad_norm: 5.1187 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2315 loss: 1.2315 2022/10/13 12:46:06 - mmengine - INFO - Epoch(train) [98][860/940] lr: 1.0000e-04 eta: 0:16:42 time: 0.5176 data_time: 0.0310 memory: 17006 grad_norm: 4.9307 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3377 loss: 1.3377 2022/10/13 12:46:15 - mmengine - INFO - Epoch(train) [98][880/940] lr: 1.0000e-04 eta: 0:16:32 time: 0.4727 data_time: 0.0331 memory: 17006 grad_norm: 4.8226 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2176 loss: 1.2176 2022/10/13 12:46:25 - mmengine - INFO - Epoch(train) [98][900/940] lr: 1.0000e-04 eta: 0:16:22 time: 0.4953 data_time: 0.0322 memory: 17006 grad_norm: 4.8905 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1187 loss: 1.1187 2022/10/13 12:46:36 - mmengine - INFO - Epoch(train) [98][920/940] lr: 1.0000e-04 eta: 0:16:12 time: 0.5351 data_time: 0.0402 memory: 17006 grad_norm: 4.9543 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3060 loss: 1.3060 2022/10/13 12:46:46 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 12:46:46 - mmengine - INFO - Epoch(train) [98][940/940] lr: 1.0000e-04 eta: 0:16:01 time: 0.4984 data_time: 0.0329 memory: 17006 grad_norm: 5.2417 top1_acc: 0.2857 top5_acc: 0.7143 loss_cls: 1.3343 loss: 1.3343 2022/10/13 12:46:59 - mmengine - INFO - Epoch(val) [98][20/78] eta: 0:00:37 time: 0.6471 data_time: 0.5543 memory: 3172 2022/10/13 12:47:07 - mmengine - INFO - Epoch(val) [98][40/78] eta: 0:00:16 time: 0.4343 data_time: 0.3413 memory: 3172 2022/10/13 12:47:19 - mmengine - INFO - Epoch(val) [98][60/78] eta: 0:00:10 time: 0.5872 data_time: 0.4968 memory: 3172 2022/10/13 12:47:30 - mmengine - INFO - Epoch(val) [98][78/78] acc/top1: 0.6769 acc/top5: 0.8698 acc/mean1: 0.6768 2022/10/13 12:47:30 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/wangyiqin/open-mmlab/mmaction2/work_dirs/c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb/best_acc/top1_epoch_83.pth is removed 2022/10/13 12:47:31 - mmengine - INFO - The best checkpoint with 0.6769 acc/top1 at 98 epoch is saved to best_acc/top1_epoch_98.pth. 2022/10/13 12:47:45 - mmengine - INFO - Epoch(train) [99][20/940] lr: 1.0000e-04 eta: 0:15:51 time: 0.7056 data_time: 0.3617 memory: 17006 grad_norm: 4.9854 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2769 loss: 1.2769 2022/10/13 12:47:55 - mmengine - INFO - Epoch(train) [99][40/940] lr: 1.0000e-04 eta: 0:15:41 time: 0.5069 data_time: 0.1092 memory: 17006 grad_norm: 4.9943 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2168 loss: 1.2168 2022/10/13 12:48:06 - mmengine - INFO - Epoch(train) [99][60/940] lr: 1.0000e-04 eta: 0:15:31 time: 0.5499 data_time: 0.0606 memory: 17006 grad_norm: 4.8941 top1_acc: 0.7812 top5_acc: 0.8125 loss_cls: 1.2812 loss: 1.2812 2022/10/13 12:48:16 - mmengine - INFO - Epoch(train) [99][80/940] lr: 1.0000e-04 eta: 0:15:21 time: 0.4929 data_time: 0.1260 memory: 17006 grad_norm: 4.9793 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2607 loss: 1.2607 2022/10/13 12:48:28 - mmengine - INFO - Epoch(train) [99][100/940] lr: 1.0000e-04 eta: 0:15:10 time: 0.5738 data_time: 0.2072 memory: 17006 grad_norm: 5.0181 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3584 loss: 1.3584 2022/10/13 12:48:37 - mmengine - INFO - Epoch(train) [99][120/940] lr: 1.0000e-04 eta: 0:15:00 time: 0.4873 data_time: 0.0712 memory: 17006 grad_norm: 4.9822 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2359 loss: 1.2359 2022/10/13 12:48:49 - mmengine - INFO - Epoch(train) [99][140/940] lr: 1.0000e-04 eta: 0:14:50 time: 0.5622 data_time: 0.0452 memory: 17006 grad_norm: 4.9713 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3444 loss: 1.3444 2022/10/13 12:48:59 - mmengine - INFO - Epoch(train) [99][160/940] lr: 1.0000e-04 eta: 0:14:40 time: 0.5033 data_time: 0.0259 memory: 17006 grad_norm: 4.9831 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1452 loss: 1.1452 2022/10/13 12:49:09 - mmengine - INFO - Epoch(train) [99][180/940] lr: 1.0000e-04 eta: 0:14:29 time: 0.5146 data_time: 0.0433 memory: 17006 grad_norm: 4.9348 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.1809 loss: 1.1809 2022/10/13 12:49:19 - mmengine - INFO - Epoch(train) [99][200/940] lr: 1.0000e-04 eta: 0:14:19 time: 0.4925 data_time: 0.0430 memory: 17006 grad_norm: 4.9477 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3550 loss: 1.3550 2022/10/13 12:49:30 - mmengine - INFO - Epoch(train) [99][220/940] lr: 1.0000e-04 eta: 0:14:09 time: 0.5797 data_time: 0.0327 memory: 17006 grad_norm: 4.9118 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2567 loss: 1.2567 2022/10/13 12:49:41 - mmengine - INFO - Epoch(train) [99][240/940] lr: 1.0000e-04 eta: 0:13:59 time: 0.5072 data_time: 0.0254 memory: 17006 grad_norm: 5.0273 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2745 loss: 1.2745 2022/10/13 12:49:51 - mmengine - INFO - Epoch(train) [99][260/940] lr: 1.0000e-04 eta: 0:13:49 time: 0.4964 data_time: 0.0316 memory: 17006 grad_norm: 5.0532 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3507 loss: 1.3507 2022/10/13 12:50:00 - mmengine - INFO - Epoch(train) [99][280/940] lr: 1.0000e-04 eta: 0:13:38 time: 0.4822 data_time: 0.0315 memory: 17006 grad_norm: 4.9620 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.1771 loss: 1.1771 2022/10/13 12:50:11 - mmengine - INFO - Epoch(train) [99][300/940] lr: 1.0000e-04 eta: 0:13:28 time: 0.5209 data_time: 0.0306 memory: 17006 grad_norm: 5.0242 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.1828 loss: 1.1828 2022/10/13 12:50:20 - mmengine - INFO - Epoch(train) [99][320/940] lr: 1.0000e-04 eta: 0:13:18 time: 0.4913 data_time: 0.0277 memory: 17006 grad_norm: 4.9495 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1570 loss: 1.1570 2022/10/13 12:50:31 - mmengine - INFO - Epoch(train) [99][340/940] lr: 1.0000e-04 eta: 0:13:08 time: 0.5395 data_time: 0.0335 memory: 17006 grad_norm: 4.8424 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2505 loss: 1.2505 2022/10/13 12:50:42 - mmengine - INFO - Epoch(train) [99][360/940] lr: 1.0000e-04 eta: 0:12:57 time: 0.5211 data_time: 0.0339 memory: 17006 grad_norm: 5.0209 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2096 loss: 1.2096 2022/10/13 12:50:52 - mmengine - INFO - Epoch(train) [99][380/940] lr: 1.0000e-04 eta: 0:12:47 time: 0.5345 data_time: 0.0287 memory: 17006 grad_norm: 4.8940 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1873 loss: 1.1873 2022/10/13 12:51:03 - mmengine - INFO - Epoch(train) [99][400/940] lr: 1.0000e-04 eta: 0:12:37 time: 0.5491 data_time: 0.0277 memory: 17006 grad_norm: 4.9879 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3500 loss: 1.3500 2022/10/13 12:51:13 - mmengine - INFO - Epoch(train) [99][420/940] lr: 1.0000e-04 eta: 0:12:27 time: 0.4602 data_time: 0.0361 memory: 17006 grad_norm: 5.0217 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2911 loss: 1.2911 2022/10/13 12:51:24 - mmengine - INFO - Epoch(train) [99][440/940] lr: 1.0000e-04 eta: 0:12:16 time: 0.5609 data_time: 0.0313 memory: 17006 grad_norm: 4.9393 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2732 loss: 1.2732 2022/10/13 12:51:34 - mmengine - INFO - Epoch(train) [99][460/940] lr: 1.0000e-04 eta: 0:12:06 time: 0.4953 data_time: 0.0315 memory: 17006 grad_norm: 4.9439 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2754 loss: 1.2754 2022/10/13 12:51:44 - mmengine - INFO - Epoch(train) [99][480/940] lr: 1.0000e-04 eta: 0:11:56 time: 0.5351 data_time: 0.0300 memory: 17006 grad_norm: 4.8285 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.0725 loss: 1.0725 2022/10/13 12:51:54 - mmengine - INFO - Epoch(train) [99][500/940] lr: 1.0000e-04 eta: 0:11:46 time: 0.4834 data_time: 0.0339 memory: 17006 grad_norm: 5.0015 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2781 loss: 1.2781 2022/10/13 12:52:05 - mmengine - INFO - Epoch(train) [99][520/940] lr: 1.0000e-04 eta: 0:11:35 time: 0.5658 data_time: 0.0298 memory: 17006 grad_norm: 5.0022 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2488 loss: 1.2488 2022/10/13 12:52:16 - mmengine - INFO - Epoch(train) [99][540/940] lr: 1.0000e-04 eta: 0:11:25 time: 0.5103 data_time: 0.0342 memory: 17006 grad_norm: 4.9850 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1633 loss: 1.1633 2022/10/13 12:52:27 - mmengine - INFO - Epoch(train) [99][560/940] lr: 1.0000e-04 eta: 0:11:15 time: 0.5826 data_time: 0.0304 memory: 17006 grad_norm: 5.0148 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2600 loss: 1.2600 2022/10/13 12:52:37 - mmengine - INFO - Epoch(train) [99][580/940] lr: 1.0000e-04 eta: 0:11:05 time: 0.4768 data_time: 0.0301 memory: 17006 grad_norm: 4.9219 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2223 loss: 1.2223 2022/10/13 12:52:47 - mmengine - INFO - Epoch(train) [99][600/940] lr: 1.0000e-04 eta: 0:10:55 time: 0.5350 data_time: 0.0272 memory: 17006 grad_norm: 4.9133 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.1534 loss: 1.1534 2022/10/13 12:52:57 - mmengine - INFO - Epoch(train) [99][620/940] lr: 1.0000e-04 eta: 0:10:44 time: 0.4835 data_time: 0.0319 memory: 17006 grad_norm: 4.8521 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.1429 loss: 1.1429 2022/10/13 12:53:07 - mmengine - INFO - Epoch(train) [99][640/940] lr: 1.0000e-04 eta: 0:10:34 time: 0.4983 data_time: 0.0382 memory: 17006 grad_norm: 4.9144 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2810 loss: 1.2810 2022/10/13 12:53:18 - mmengine - INFO - Epoch(train) [99][660/940] lr: 1.0000e-04 eta: 0:10:24 time: 0.5622 data_time: 0.0321 memory: 17006 grad_norm: 4.9277 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3060 loss: 1.3060 2022/10/13 12:53:28 - mmengine - INFO - Epoch(train) [99][680/940] lr: 1.0000e-04 eta: 0:10:14 time: 0.4579 data_time: 0.0398 memory: 17006 grad_norm: 4.9377 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1377 loss: 1.1377 2022/10/13 12:53:39 - mmengine - INFO - Epoch(train) [99][700/940] lr: 1.0000e-04 eta: 0:10:03 time: 0.5947 data_time: 0.0299 memory: 17006 grad_norm: 5.0639 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1643 loss: 1.1643 2022/10/13 12:53:50 - mmengine - INFO - Epoch(train) [99][720/940] lr: 1.0000e-04 eta: 0:09:53 time: 0.5100 data_time: 0.0356 memory: 17006 grad_norm: 4.9444 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3384 loss: 1.3384 2022/10/13 12:54:01 - mmengine - INFO - Epoch(train) [99][740/940] lr: 1.0000e-04 eta: 0:09:43 time: 0.5741 data_time: 0.0245 memory: 17006 grad_norm: 4.8150 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2112 loss: 1.2112 2022/10/13 12:54:11 - mmengine - INFO - Epoch(train) [99][760/940] lr: 1.0000e-04 eta: 0:09:33 time: 0.5092 data_time: 0.0260 memory: 17006 grad_norm: 4.8743 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3060 loss: 1.3060 2022/10/13 12:54:23 - mmengine - INFO - Epoch(train) [99][780/940] lr: 1.0000e-04 eta: 0:09:22 time: 0.5742 data_time: 0.0380 memory: 17006 grad_norm: 4.9984 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2352 loss: 1.2352 2022/10/13 12:54:32 - mmengine - INFO - Epoch(train) [99][800/940] lr: 1.0000e-04 eta: 0:09:12 time: 0.4527 data_time: 0.0276 memory: 17006 grad_norm: 4.9368 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3093 loss: 1.3093 2022/10/13 12:54:42 - mmengine - INFO - Epoch(train) [99][820/940] lr: 1.0000e-04 eta: 0:09:02 time: 0.5052 data_time: 0.0288 memory: 17006 grad_norm: 4.9872 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2034 loss: 1.2034 2022/10/13 12:54:51 - mmengine - INFO - Epoch(train) [99][840/940] lr: 1.0000e-04 eta: 0:08:52 time: 0.4743 data_time: 0.0350 memory: 17006 grad_norm: 5.0123 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2936 loss: 1.2936 2022/10/13 12:55:02 - mmengine - INFO - Epoch(train) [99][860/940] lr: 1.0000e-04 eta: 0:08:42 time: 0.5314 data_time: 0.0370 memory: 17006 grad_norm: 4.9275 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3132 loss: 1.3132 2022/10/13 12:55:12 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 12:55:12 - mmengine - INFO - Epoch(train) [99][880/940] lr: 1.0000e-04 eta: 0:08:31 time: 0.4795 data_time: 0.0365 memory: 17006 grad_norm: 4.9631 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2888 loss: 1.2888 2022/10/13 12:55:22 - mmengine - INFO - Epoch(train) [99][900/940] lr: 1.0000e-04 eta: 0:08:21 time: 0.5215 data_time: 0.0327 memory: 17006 grad_norm: 5.0240 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2086 loss: 1.2086 2022/10/13 12:55:32 - mmengine - INFO - Epoch(train) [99][920/940] lr: 1.0000e-04 eta: 0:08:11 time: 0.5013 data_time: 0.0330 memory: 17006 grad_norm: 4.8475 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1554 loss: 1.1554 2022/10/13 12:55:42 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 12:55:42 - mmengine - INFO - Epoch(train) [99][940/940] lr: 1.0000e-04 eta: 0:08:01 time: 0.4904 data_time: 0.0257 memory: 17006 grad_norm: 5.1720 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.3158 loss: 1.3158 2022/10/13 12:55:42 - mmengine - INFO - Saving checkpoint at 99 epochs 2022/10/13 12:55:55 - mmengine - INFO - Epoch(val) [99][20/78] eta: 0:00:36 time: 0.6281 data_time: 0.5378 memory: 3172 2022/10/13 12:56:04 - mmengine - INFO - Epoch(val) [99][40/78] eta: 0:00:16 time: 0.4338 data_time: 0.3441 memory: 3172 2022/10/13 12:56:16 - mmengine - INFO - Epoch(val) [99][60/78] eta: 0:00:10 time: 0.5959 data_time: 0.5039 memory: 3172 2022/10/13 12:56:26 - mmengine - INFO - Epoch(val) [99][78/78] acc/top1: 0.6750 acc/top5: 0.8700 acc/mean1: 0.6749 2022/10/13 12:56:40 - mmengine - INFO - Epoch(train) [100][20/940] lr: 1.0000e-04 eta: 0:07:50 time: 0.6987 data_time: 0.3134 memory: 17006 grad_norm: 4.8811 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2951 loss: 1.2951 2022/10/13 12:56:49 - mmengine - INFO - Epoch(train) [100][40/940] lr: 1.0000e-04 eta: 0:07:40 time: 0.4806 data_time: 0.1099 memory: 17006 grad_norm: 4.9550 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2329 loss: 1.2329 2022/10/13 12:57:01 - mmengine - INFO - Epoch(train) [100][60/940] lr: 1.0000e-04 eta: 0:07:30 time: 0.5662 data_time: 0.2424 memory: 17006 grad_norm: 4.9371 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.2303 loss: 1.2303 2022/10/13 12:57:10 - mmengine - INFO - Epoch(train) [100][80/940] lr: 1.0000e-04 eta: 0:07:20 time: 0.4830 data_time: 0.1454 memory: 17006 grad_norm: 4.9994 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2668 loss: 1.2668 2022/10/13 12:57:21 - mmengine - INFO - Epoch(train) [100][100/940] lr: 1.0000e-04 eta: 0:07:09 time: 0.5538 data_time: 0.1655 memory: 17006 grad_norm: 4.8561 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.1978 loss: 1.1978 2022/10/13 12:57:31 - mmengine - INFO - Epoch(train) [100][120/940] lr: 1.0000e-04 eta: 0:06:59 time: 0.4760 data_time: 0.1362 memory: 17006 grad_norm: 4.9853 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2385 loss: 1.2385 2022/10/13 12:57:42 - mmengine - INFO - Epoch(train) [100][140/940] lr: 1.0000e-04 eta: 0:06:49 time: 0.5671 data_time: 0.1347 memory: 17006 grad_norm: 4.9869 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3168 loss: 1.3168 2022/10/13 12:57:53 - mmengine - INFO - Epoch(train) [100][160/940] lr: 1.0000e-04 eta: 0:06:39 time: 0.5435 data_time: 0.0746 memory: 17006 grad_norm: 4.9806 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.2795 loss: 1.2795 2022/10/13 12:58:03 - mmengine - INFO - Epoch(train) [100][180/940] lr: 1.0000e-04 eta: 0:06:28 time: 0.5132 data_time: 0.0361 memory: 17006 grad_norm: 5.0492 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.2415 loss: 1.2415 2022/10/13 12:58:14 - mmengine - INFO - Epoch(train) [100][200/940] lr: 1.0000e-04 eta: 0:06:18 time: 0.5138 data_time: 0.0279 memory: 17006 grad_norm: 4.9331 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3490 loss: 1.3490 2022/10/13 12:58:24 - mmengine - INFO - Epoch(train) [100][220/940] lr: 1.0000e-04 eta: 0:06:08 time: 0.5425 data_time: 0.0357 memory: 17006 grad_norm: 5.0221 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2048 loss: 1.2048 2022/10/13 12:58:34 - mmengine - INFO - Epoch(train) [100][240/940] lr: 1.0000e-04 eta: 0:05:58 time: 0.4981 data_time: 0.0271 memory: 17006 grad_norm: 5.0705 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2271 loss: 1.2271 2022/10/13 12:58:44 - mmengine - INFO - Epoch(train) [100][260/940] lr: 1.0000e-04 eta: 0:05:48 time: 0.5016 data_time: 0.0349 memory: 17006 grad_norm: 4.8947 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3446 loss: 1.3446 2022/10/13 12:58:55 - mmengine - INFO - Epoch(train) [100][280/940] lr: 1.0000e-04 eta: 0:05:37 time: 0.5177 data_time: 0.0328 memory: 17006 grad_norm: 4.9525 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2148 loss: 1.2148 2022/10/13 12:59:05 - mmengine - INFO - Epoch(train) [100][300/940] lr: 1.0000e-04 eta: 0:05:27 time: 0.5070 data_time: 0.0389 memory: 17006 grad_norm: 5.0894 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.3623 loss: 1.3623 2022/10/13 12:59:16 - mmengine - INFO - Epoch(train) [100][320/940] lr: 1.0000e-04 eta: 0:05:17 time: 0.5401 data_time: 0.0287 memory: 17006 grad_norm: 5.0724 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3838 loss: 1.3838 2022/10/13 12:59:25 - mmengine - INFO - Epoch(train) [100][340/940] lr: 1.0000e-04 eta: 0:05:07 time: 0.4696 data_time: 0.0375 memory: 17006 grad_norm: 4.9257 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3283 loss: 1.3283 2022/10/13 12:59:37 - mmengine - INFO - Epoch(train) [100][360/940] lr: 1.0000e-04 eta: 0:04:56 time: 0.5807 data_time: 0.0310 memory: 17006 grad_norm: 5.0107 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2291 loss: 1.2291 2022/10/13 12:59:46 - mmengine - INFO - Epoch(train) [100][380/940] lr: 1.0000e-04 eta: 0:04:46 time: 0.4805 data_time: 0.0395 memory: 17006 grad_norm: 4.9667 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2460 loss: 1.2460 2022/10/13 12:59:57 - mmengine - INFO - Epoch(train) [100][400/940] lr: 1.0000e-04 eta: 0:04:36 time: 0.5222 data_time: 0.0264 memory: 17006 grad_norm: 5.0329 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3482 loss: 1.3482 2022/10/13 13:00:07 - mmengine - INFO - Epoch(train) [100][420/940] lr: 1.0000e-04 eta: 0:04:26 time: 0.5102 data_time: 0.0979 memory: 17006 grad_norm: 4.9078 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2615 loss: 1.2615 2022/10/13 13:00:18 - mmengine - INFO - Epoch(train) [100][440/940] lr: 1.0000e-04 eta: 0:04:15 time: 0.5343 data_time: 0.0638 memory: 17006 grad_norm: 4.9663 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2752 loss: 1.2752 2022/10/13 13:00:27 - mmengine - INFO - Epoch(train) [100][460/940] lr: 1.0000e-04 eta: 0:04:05 time: 0.4465 data_time: 0.0546 memory: 17006 grad_norm: 5.0235 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2501 loss: 1.2501 2022/10/13 13:00:38 - mmengine - INFO - Epoch(train) [100][480/940] lr: 1.0000e-04 eta: 0:03:55 time: 0.5667 data_time: 0.0363 memory: 17006 grad_norm: 4.9016 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3416 loss: 1.3416 2022/10/13 13:00:48 - mmengine - INFO - Epoch(train) [100][500/940] lr: 1.0000e-04 eta: 0:03:45 time: 0.5005 data_time: 0.0380 memory: 17006 grad_norm: 4.9579 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3123 loss: 1.3123 2022/10/13 13:01:00 - mmengine - INFO - Epoch(train) [100][520/940] lr: 1.0000e-04 eta: 0:03:34 time: 0.5771 data_time: 0.0291 memory: 17006 grad_norm: 4.9266 top1_acc: 0.5312 top5_acc: 0.9375 loss_cls: 1.2660 loss: 1.2660 2022/10/13 13:01:10 - mmengine - INFO - Epoch(train) [100][540/940] lr: 1.0000e-04 eta: 0:03:24 time: 0.5258 data_time: 0.0280 memory: 17006 grad_norm: 4.9599 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.2737 loss: 1.2737 2022/10/13 13:01:20 - mmengine - INFO - Epoch(train) [100][560/940] lr: 1.0000e-04 eta: 0:03:14 time: 0.4734 data_time: 0.0291 memory: 17006 grad_norm: 4.9587 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.1652 loss: 1.1652 2022/10/13 13:01:29 - mmengine - INFO - Epoch(train) [100][580/940] lr: 1.0000e-04 eta: 0:03:04 time: 0.4627 data_time: 0.0374 memory: 17006 grad_norm: 5.0471 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2647 loss: 1.2647 2022/10/13 13:01:39 - mmengine - INFO - Epoch(train) [100][600/940] lr: 1.0000e-04 eta: 0:02:54 time: 0.5198 data_time: 0.0323 memory: 17006 grad_norm: 4.9273 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2280 loss: 1.2280 2022/10/13 13:01:49 - mmengine - INFO - Epoch(train) [100][620/940] lr: 1.0000e-04 eta: 0:02:43 time: 0.4702 data_time: 0.0382 memory: 17006 grad_norm: 4.9608 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3362 loss: 1.3362 2022/10/13 13:02:00 - mmengine - INFO - Epoch(train) [100][640/940] lr: 1.0000e-04 eta: 0:02:33 time: 0.5914 data_time: 0.0532 memory: 17006 grad_norm: 4.9064 top1_acc: 0.7188 top5_acc: 0.7500 loss_cls: 1.3831 loss: 1.3831 2022/10/13 13:02:10 - mmengine - INFO - Epoch(train) [100][660/940] lr: 1.0000e-04 eta: 0:02:23 time: 0.4651 data_time: 0.0311 memory: 17006 grad_norm: 5.0612 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3545 loss: 1.3545 2022/10/13 13:02:21 - mmengine - INFO - Epoch(train) [100][680/940] lr: 1.0000e-04 eta: 0:02:13 time: 0.5547 data_time: 0.0338 memory: 17006 grad_norm: 4.9389 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1571 loss: 1.1571 2022/10/13 13:02:30 - mmengine - INFO - Epoch(train) [100][700/940] lr: 1.0000e-04 eta: 0:02:02 time: 0.4663 data_time: 0.0366 memory: 17006 grad_norm: 4.9357 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2883 loss: 1.2883 2022/10/13 13:02:43 - mmengine - INFO - Epoch(train) [100][720/940] lr: 1.0000e-04 eta: 0:01:52 time: 0.6188 data_time: 0.0315 memory: 17006 grad_norm: 5.0073 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2423 loss: 1.2423 2022/10/13 13:02:52 - mmengine - INFO - Epoch(train) [100][740/940] lr: 1.0000e-04 eta: 0:01:42 time: 0.4646 data_time: 0.0338 memory: 17006 grad_norm: 5.0324 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.1900 loss: 1.1900 2022/10/13 13:03:03 - mmengine - INFO - Epoch(train) [100][760/940] lr: 1.0000e-04 eta: 0:01:32 time: 0.5430 data_time: 0.0297 memory: 17006 grad_norm: 5.0224 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.1741 loss: 1.1741 2022/10/13 13:03:12 - mmengine - INFO - Epoch(train) [100][780/940] lr: 1.0000e-04 eta: 0:01:21 time: 0.4890 data_time: 0.0309 memory: 17006 grad_norm: 4.9474 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.3431 loss: 1.3431 2022/10/13 13:03:24 - mmengine - INFO - Epoch(train) [100][800/940] lr: 1.0000e-04 eta: 0:01:11 time: 0.5881 data_time: 0.0299 memory: 17006 grad_norm: 4.9268 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1520 loss: 1.1520 2022/10/13 13:03:34 - mmengine - INFO - Epoch(train) [100][820/940] lr: 1.0000e-04 eta: 0:01:01 time: 0.4740 data_time: 0.0323 memory: 17006 grad_norm: 4.9210 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2890 loss: 1.2890 2022/10/13 13:03:44 - mmengine - INFO - Epoch(train) [100][840/940] lr: 1.0000e-04 eta: 0:00:51 time: 0.4957 data_time: 0.0298 memory: 17006 grad_norm: 4.9947 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2170 loss: 1.2170 2022/10/13 13:03:53 - mmengine - INFO - Epoch(train) [100][860/940] lr: 1.0000e-04 eta: 0:00:40 time: 0.4910 data_time: 0.0327 memory: 17006 grad_norm: 4.9691 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2146 loss: 1.2146 2022/10/13 13:04:05 - mmengine - INFO - Epoch(train) [100][880/940] lr: 1.0000e-04 eta: 0:00:30 time: 0.5683 data_time: 0.0308 memory: 17006 grad_norm: 5.0601 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3597 loss: 1.3597 2022/10/13 13:04:15 - mmengine - INFO - Epoch(train) [100][900/940] lr: 1.0000e-04 eta: 0:00:20 time: 0.4860 data_time: 0.0392 memory: 17006 grad_norm: 4.9837 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3368 loss: 1.3368 2022/10/13 13:04:25 - mmengine - INFO - Epoch(train) [100][920/940] lr: 1.0000e-04 eta: 0:00:10 time: 0.5200 data_time: 0.0272 memory: 17006 grad_norm: 4.9198 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2474 loss: 1.2474 2022/10/13 13:04:33 - mmengine - INFO - Exp name: c2d_r50-in1k-pre_8xb32-8x8x1-100e_kinetics400-rgb_20221012_223120 2022/10/13 13:04:33 - mmengine - INFO - Epoch(train) [100][940/940] lr: 1.0000e-04 eta: 0:00:00 time: 0.4244 data_time: 0.0264 memory: 17006 grad_norm: 5.2848 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.2120 loss: 1.2120 2022/10/13 13:04:33 - mmengine - INFO - Saving checkpoint at 100 epochs 2022/10/13 13:04:47 - mmengine - INFO - Epoch(val) [100][20/78] eta: 0:00:35 time: 0.6165 data_time: 0.5260 memory: 3172 2022/10/13 13:04:57 - mmengine - INFO - Epoch(val) [100][40/78] eta: 0:00:18 time: 0.4969 data_time: 0.4060 memory: 3172 2022/10/13 13:05:09 - mmengine - INFO - Epoch(val) [100][60/78] eta: 0:00:10 time: 0.5989 data_time: 0.5080 memory: 3172 2022/10/13 13:05:18 - mmengine - INFO - Epoch(val) [100][78/78] acc/top1: 0.6767 acc/top5: 0.8701 acc/mean1: 0.6766