2022/09/08 10:34:30 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.7.13 (default, Mar 29 2022, 02:18:16) [GCC 7.5.0] CUDA available: True numpy_random_seed: 307517676 GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/cache/share/cuda-11.1 NVCC: Cuda compilation tools, release 11.1, V11.1.74 GCC: gcc (GCC) 5.4.0 PyTorch: 1.9.0+cu111 PyTorch compiling details: PyTorch built with: - GCC 7.3 - C++ Version: 201402 - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.1.2 (Git Hash 98be7e8afa711dc9b66c8ff3504129cb82013cdb) - OpenMP 201511 (a.k.a. OpenMP 4.5) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86 - CuDNN 8.0.5 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -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=1.9.0, 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: 0.10.0+cu111 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 ------------------------------------------------------------ 2022/09/08 10:34:30 - mmengine - INFO - Config: preprocess_cfg = dict( mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], format_shape='NCHW') model = dict( type='Recognizer2D', backbone=dict( type='ResNetTIN', pretrained='torchvision://resnet50', depth=50, norm_eval=False, shift_div=4), cls_head=dict( type='TSMHead', num_classes=400, in_channels=2048, spatial_type='avg', consensus=dict(type='AvgConsensus', dim=1), dropout_ratio=0.5, init_std=0.001, is_shift=True, average_clips='prob'), data_preprocessor=dict( type='ActionDataPreprocessor', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], format_shape='NCHW'), train_cfg=None, test_cfg=dict(average_clips=None)) train_cfg = dict( type='EpochBasedTrainLoop', max_epochs=50, val_begin=1, val_interval=5) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') param_scheduler = [ dict( type='MultiStepLR', begin=0, end=50, by_epoch=True, milestones=[20, 40], gamma=0.1) ] optim_wrapper = dict( optimizer=dict(type='SGD', lr=0.04, momentum=0.9, weight_decay=0.0001), clip_grad=dict(max_norm=40, norm_type=2), constructor='TSMOptimWrapperConstructor', paramwise_cfg=dict(fc_lr5=True)) 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=-1, save_best='auto'), 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 = 'https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_50e_kinetics400_rgb/tsm_r50_1x1x8_50e_kinetics400_rgb_20200607-af7fb746.pth' resume = False file_client_args = dict( io_backend='petrel', path_mapping=dict({ 'data/kinetics400': 's254:s3://openmmlab/datasets/action/Kinetics400' })) 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' ann_file_test = 'data/kinetics400/kinetics400_val_list_videos.txt' train_pipeline = [ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/kinetics400': 's254:s3://openmmlab/datasets/action/Kinetics400' })), dict(type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8), 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='NCHW'), dict(type='PackActionInputs') ] val_pipeline = [ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/kinetics400': 's254:s3://openmmlab/datasets/action/Kinetics400' })), dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ] test_pipeline = [ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/kinetics400': 's254:s3://openmmlab/datasets/action/Kinetics400' })), dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ] train_dataloader = dict( batch_size=24, num_workers=16, 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': 's254:s3://openmmlab/datasets/action/Kinetics400' })), dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8), 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='NCHW'), dict(type='PackActionInputs') ])) val_dataloader = dict( batch_size=24, num_workers=16, 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': 's254:s3://openmmlab/datasets/action/Kinetics400' })), dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ], test_mode=True)) test_dataloader = dict( batch_size=1, num_workers=2, 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': 's254:s3://openmmlab/datasets/action/Kinetics400' })), dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ], test_mode=True)) val_evaluator = dict(type='AccMetric') test_evaluator = dict(type='AccMetric') launcher = 'slurm' work_dir = './work_dirs/tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb' 2022/09/08 10:34:32 - mmengine - INFO - These parameters in pretrained checkpoint are not loaded: {'fc.weight', 'fc.bias'} 2022/09/08 10:34:35 - mmengine - INFO - Load checkpoint from https://download.openmmlab.com/mmaction/recognition/tsm/tsm_r50_1x1x8_50e_kinetics400_rgb/tsm_r50_1x1x8_50e_kinetics400_rgb_20200607-af7fb746.pth 2022/09/08 10:34:35 - mmengine - INFO - Checkpoints will be saved to /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb by HardDiskBackend. 2022/09/08 10:36:12 - mmengine - INFO - Epoch(train) [1][20/1253] lr: 4.0000e-02 eta: 3 days, 12:42:05 time: 4.8687 data_time: 4.2301 memory: 23504 grad_norm: 7.9434 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 2.9459 loss: 2.9459 2022/09/08 10:36:23 - mmengine - INFO - Epoch(train) [1][40/1253] lr: 4.0000e-02 eta: 1 day, 23:21:40 time: 0.5778 data_time: 0.0399 memory: 23504 grad_norm: 4.3915 top1_acc: 0.2500 top5_acc: 0.6667 loss_cls: 3.1783 loss: 3.1783 2022/09/08 10:36:35 - mmengine - INFO - Epoch(train) [1][60/1253] lr: 4.0000e-02 eta: 1 day, 10:49:00 time: 0.5613 data_time: 0.0313 memory: 23504 grad_norm: 4.0864 top1_acc: 0.2083 top5_acc: 0.5417 loss_cls: 2.9206 loss: 2.9206 2022/09/08 10:36:46 - mmengine - INFO - Epoch(train) [1][80/1253] lr: 4.0000e-02 eta: 1 day, 4:30:16 time: 0.5524 data_time: 0.0395 memory: 23504 grad_norm: 3.7824 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 2.7047 loss: 2.7047 2022/09/08 10:36:57 - mmengine - INFO - Epoch(train) [1][100/1253] lr: 4.0000e-02 eta: 1 day, 0:48:43 time: 0.5801 data_time: 0.0469 memory: 23504 grad_norm: 3.9721 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6607 loss: 2.6607 2022/09/08 10:37:08 - mmengine - INFO - Epoch(train) [1][120/1253] lr: 4.0000e-02 eta: 22:16:51 time: 0.5564 data_time: 0.0446 memory: 23504 grad_norm: 3.7948 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.6373 loss: 2.6373 2022/09/08 10:37:21 - mmengine - INFO - Epoch(train) [1][140/1253] lr: 4.0000e-02 eta: 20:35:47 time: 0.6066 data_time: 0.0462 memory: 23504 grad_norm: 3.8177 top1_acc: 0.6667 top5_acc: 0.7500 loss_cls: 2.4801 loss: 2.4801 2022/09/08 10:37:32 - mmengine - INFO - Epoch(train) [1][160/1253] lr: 4.0000e-02 eta: 19:12:51 time: 0.5523 data_time: 0.0459 memory: 23504 grad_norm: 3.7968 top1_acc: 0.2917 top5_acc: 0.5417 loss_cls: 2.6304 loss: 2.6304 2022/09/08 10:37:44 - mmengine - INFO - Epoch(train) [1][180/1253] lr: 4.0000e-02 eta: 18:14:44 time: 0.6077 data_time: 0.0558 memory: 23504 grad_norm: 3.6961 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4048 loss: 2.4048 2022/09/08 10:37:55 - mmengine - INFO - Epoch(train) [1][200/1253] lr: 4.0000e-02 eta: 17:23:53 time: 0.5662 data_time: 0.0355 memory: 23504 grad_norm: 3.8185 top1_acc: 0.2917 top5_acc: 0.5417 loss_cls: 2.6030 loss: 2.6030 2022/09/08 10:38:06 - mmengine - INFO - Epoch(train) [1][220/1253] lr: 4.0000e-02 eta: 16:41:54 time: 0.5626 data_time: 0.0463 memory: 23504 grad_norm: 3.6613 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4110 loss: 2.4110 2022/09/08 10:38:18 - mmengine - INFO - Epoch(train) [1][240/1253] lr: 4.0000e-02 eta: 16:07:15 time: 0.5670 data_time: 0.0410 memory: 23504 grad_norm: 3.6736 top1_acc: 0.4583 top5_acc: 0.5833 loss_cls: 2.4608 loss: 2.4608 2022/09/08 10:38:29 - mmengine - INFO - Epoch(train) [1][260/1253] lr: 4.0000e-02 eta: 15:38:46 time: 0.5777 data_time: 0.0619 memory: 23504 grad_norm: 3.6542 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.3213 loss: 2.3213 2022/09/08 10:38:41 - mmengine - INFO - Epoch(train) [1][280/1253] lr: 4.0000e-02 eta: 15:13:15 time: 0.5632 data_time: 0.0404 memory: 23504 grad_norm: 3.6509 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4301 loss: 2.4301 2022/09/08 10:38:52 - mmengine - INFO - Epoch(train) [1][300/1253] lr: 4.0000e-02 eta: 14:52:22 time: 0.5814 data_time: 0.0481 memory: 23504 grad_norm: 3.6706 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.3593 loss: 2.3593 2022/09/08 10:39:04 - mmengine - INFO - Epoch(train) [1][320/1253] lr: 4.0000e-02 eta: 14:33:27 time: 0.5716 data_time: 0.0442 memory: 23504 grad_norm: 3.6139 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1867 loss: 2.1867 2022/09/08 10:39:16 - mmengine - INFO - Epoch(train) [1][340/1253] lr: 4.0000e-02 eta: 14:18:45 time: 0.6048 data_time: 0.0839 memory: 23504 grad_norm: 3.6119 top1_acc: 0.3750 top5_acc: 0.7917 loss_cls: 2.2786 loss: 2.2786 2022/09/08 10:39:27 - mmengine - INFO - Epoch(train) [1][360/1253] lr: 4.0000e-02 eta: 14:02:01 time: 0.5417 data_time: 0.0341 memory: 23504 grad_norm: 3.5783 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.3278 loss: 2.3278 2022/09/08 10:39:37 - mmengine - INFO - Epoch(train) [1][380/1253] lr: 4.0000e-02 eta: 13:46:58 time: 0.5404 data_time: 0.0425 memory: 23504 grad_norm: 3.4679 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 2.1852 loss: 2.1852 2022/09/08 10:39:49 - mmengine - INFO - Epoch(train) [1][400/1253] lr: 4.0000e-02 eta: 13:34:33 time: 0.5627 data_time: 0.0428 memory: 23504 grad_norm: 3.6193 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.1910 loss: 2.1910 2022/09/08 10:40:00 - mmengine - INFO - Epoch(train) [1][420/1253] lr: 4.0000e-02 eta: 13:23:44 time: 0.5713 data_time: 0.0503 memory: 23504 grad_norm: 3.4856 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.2979 loss: 2.2979 2022/09/08 10:40:11 - mmengine - INFO - Epoch(train) [1][440/1253] lr: 4.0000e-02 eta: 13:13:27 time: 0.5623 data_time: 0.0393 memory: 23504 grad_norm: 3.5169 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 2.2161 loss: 2.2161 2022/09/08 10:40:23 - mmengine - INFO - Epoch(train) [1][460/1253] lr: 4.0000e-02 eta: 13:04:16 time: 0.5672 data_time: 0.0486 memory: 23504 grad_norm: 3.5449 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.9807 loss: 1.9807 2022/09/08 10:40:34 - mmengine - INFO - Epoch(train) [1][480/1253] lr: 4.0000e-02 eta: 12:55:12 time: 0.5524 data_time: 0.0430 memory: 23504 grad_norm: 3.4744 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 2.3395 loss: 2.3395 2022/09/08 10:40:45 - mmengine - INFO - Epoch(train) [1][500/1253] lr: 4.0000e-02 eta: 12:48:09 time: 0.5841 data_time: 0.0526 memory: 23504 grad_norm: 3.4443 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.2440 loss: 2.2440 2022/09/08 10:40:57 - mmengine - INFO - Epoch(train) [1][520/1253] lr: 4.0000e-02 eta: 12:41:33 time: 0.5821 data_time: 0.0412 memory: 23504 grad_norm: 3.4686 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.3251 loss: 2.3251 2022/09/08 10:41:09 - mmengine - INFO - Epoch(train) [1][540/1253] lr: 4.0000e-02 eta: 12:35:32 time: 0.5849 data_time: 0.0371 memory: 23504 grad_norm: 3.3806 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.3615 loss: 2.3615 2022/09/08 10:41:20 - mmengine - INFO - Epoch(train) [1][560/1253] lr: 4.0000e-02 eta: 12:29:18 time: 0.5679 data_time: 0.0431 memory: 23504 grad_norm: 3.5394 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 2.2840 loss: 2.2840 2022/09/08 10:41:33 - mmengine - INFO - Epoch(train) [1][580/1253] lr: 4.0000e-02 eta: 12:26:56 time: 0.6642 data_time: 0.0508 memory: 23504 grad_norm: 3.3993 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 2.1572 loss: 2.1572 2022/09/08 10:41:45 - mmengine - INFO - Epoch(train) [1][600/1253] lr: 4.0000e-02 eta: 12:21:32 time: 0.5725 data_time: 0.0409 memory: 23504 grad_norm: 3.3814 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.2408 loss: 2.2408 2022/09/08 10:41:56 - mmengine - INFO - Epoch(train) [1][620/1253] lr: 4.0000e-02 eta: 12:16:38 time: 0.5772 data_time: 0.0390 memory: 23504 grad_norm: 3.3561 top1_acc: 0.4583 top5_acc: 0.5833 loss_cls: 2.3940 loss: 2.3940 2022/09/08 10:42:08 - mmengine - INFO - Epoch(train) [1][640/1253] lr: 4.0000e-02 eta: 12:11:42 time: 0.5674 data_time: 0.0460 memory: 23504 grad_norm: 3.4051 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.0834 loss: 2.0834 2022/09/08 10:42:19 - mmengine - INFO - Epoch(train) [1][660/1253] lr: 4.0000e-02 eta: 12:07:21 time: 0.5767 data_time: 0.0483 memory: 23504 grad_norm: 3.3377 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 2.2180 loss: 2.2180 2022/09/08 10:42:31 - mmengine - INFO - Epoch(train) [1][680/1253] lr: 4.0000e-02 eta: 12:02:54 time: 0.5650 data_time: 0.0407 memory: 23504 grad_norm: 3.3386 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.2180 loss: 2.2180 2022/09/08 10:42:42 - mmengine - INFO - Epoch(train) [1][700/1253] lr: 4.0000e-02 eta: 11:58:54 time: 0.5721 data_time: 0.0404 memory: 23504 grad_norm: 3.3773 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.1694 loss: 2.1694 2022/09/08 10:42:53 - mmengine - INFO - Epoch(train) [1][720/1253] lr: 4.0000e-02 eta: 11:55:13 time: 0.5760 data_time: 0.0423 memory: 23504 grad_norm: 3.2921 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 2.2929 loss: 2.2929 2022/09/08 10:43:05 - mmengine - INFO - Epoch(train) [1][740/1253] lr: 4.0000e-02 eta: 11:51:14 time: 0.5584 data_time: 0.0472 memory: 23504 grad_norm: 3.2980 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.1644 loss: 2.1644 2022/09/08 10:43:16 - mmengine - INFO - Epoch(train) [1][760/1253] lr: 4.0000e-02 eta: 11:47:39 time: 0.5659 data_time: 0.0416 memory: 23504 grad_norm: 3.3514 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1755 loss: 2.1755 2022/09/08 10:43:28 - mmengine - INFO - Epoch(train) [1][780/1253] lr: 4.0000e-02 eta: 11:44:40 time: 0.5820 data_time: 0.0458 memory: 23504 grad_norm: 3.3613 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.1204 loss: 2.1204 2022/09/08 10:43:39 - mmengine - INFO - Epoch(train) [1][800/1253] lr: 4.0000e-02 eta: 11:41:45 time: 0.5788 data_time: 0.0430 memory: 23504 grad_norm: 3.3366 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 2.3004 loss: 2.3004 2022/09/08 10:43:51 - mmengine - INFO - Epoch(train) [1][820/1253] lr: 4.0000e-02 eta: 11:38:47 time: 0.5717 data_time: 0.0435 memory: 23504 grad_norm: 3.4126 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3465 loss: 2.3465 2022/09/08 10:44:02 - mmengine - INFO - Epoch(train) [1][840/1253] lr: 4.0000e-02 eta: 11:36:26 time: 0.5914 data_time: 0.0445 memory: 23504 grad_norm: 3.2141 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 2.1597 loss: 2.1597 2022/09/08 10:44:14 - mmengine - INFO - Epoch(train) [1][860/1253] lr: 4.0000e-02 eta: 11:33:39 time: 0.5693 data_time: 0.0418 memory: 23504 grad_norm: 3.3614 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 2.0939 loss: 2.0939 2022/09/08 10:44:25 - mmengine - INFO - Epoch(train) [1][880/1253] lr: 4.0000e-02 eta: 11:30:50 time: 0.5627 data_time: 0.0459 memory: 23504 grad_norm: 3.2983 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2353 loss: 2.2353 2022/09/08 10:44:37 - mmengine - INFO - Epoch(train) [1][900/1253] lr: 4.0000e-02 eta: 11:28:28 time: 0.5778 data_time: 0.0482 memory: 23504 grad_norm: 3.2208 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 2.0872 loss: 2.0872 2022/09/08 10:44:48 - mmengine - INFO - Epoch(train) [1][920/1253] lr: 4.0000e-02 eta: 11:26:19 time: 0.5826 data_time: 0.0476 memory: 23504 grad_norm: 3.2699 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.1977 loss: 2.1977 2022/09/08 10:45:00 - mmengine - INFO - Epoch(train) [1][940/1253] lr: 4.0000e-02 eta: 11:24:05 time: 0.5754 data_time: 0.0427 memory: 23504 grad_norm: 3.3236 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 2.0692 loss: 2.0692 2022/09/08 10:45:12 - mmengine - INFO - Epoch(train) [1][960/1253] lr: 4.0000e-02 eta: 11:22:15 time: 0.5895 data_time: 0.0432 memory: 23504 grad_norm: 3.2105 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 2.2051 loss: 2.2051 2022/09/08 10:45:23 - mmengine - INFO - Epoch(train) [1][980/1253] lr: 4.0000e-02 eta: 11:19:58 time: 0.5656 data_time: 0.0516 memory: 23504 grad_norm: 3.2737 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 2.1129 loss: 2.1129 2022/09/08 10:45:34 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 10:45:34 - mmengine - INFO - Epoch(train) [1][1000/1253] lr: 4.0000e-02 eta: 11:18:03 time: 0.5785 data_time: 0.0479 memory: 23504 grad_norm: 3.2895 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 2.1493 loss: 2.1493 2022/09/08 10:45:46 - mmengine - INFO - Epoch(train) [1][1020/1253] lr: 4.0000e-02 eta: 11:16:19 time: 0.5853 data_time: 0.0382 memory: 23504 grad_norm: 3.3138 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.2312 loss: 2.2312 2022/09/08 10:45:58 - mmengine - INFO - Epoch(train) [1][1040/1253] lr: 4.0000e-02 eta: 11:14:35 time: 0.5820 data_time: 0.0454 memory: 23504 grad_norm: 3.1352 top1_acc: 0.3750 top5_acc: 0.7917 loss_cls: 2.0839 loss: 2.0839 2022/09/08 10:46:10 - mmengine - INFO - Epoch(train) [1][1060/1253] lr: 4.0000e-02 eta: 11:13:00 time: 0.5862 data_time: 0.0531 memory: 23504 grad_norm: 3.2273 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.1528 loss: 2.1528 2022/09/08 10:46:21 - mmengine - INFO - Epoch(train) [1][1080/1253] lr: 4.0000e-02 eta: 11:10:57 time: 0.5596 data_time: 0.0457 memory: 23504 grad_norm: 3.2371 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0061 loss: 2.0061 2022/09/08 10:46:32 - mmengine - INFO - Epoch(train) [1][1100/1253] lr: 4.0000e-02 eta: 11:09:09 time: 0.5683 data_time: 0.0492 memory: 23504 grad_norm: 3.2795 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0936 loss: 2.0936 2022/09/08 10:46:44 - mmengine - INFO - Epoch(train) [1][1120/1253] lr: 4.0000e-02 eta: 11:07:32 time: 0.5764 data_time: 0.0456 memory: 23504 grad_norm: 3.2194 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 2.0136 loss: 2.0136 2022/09/08 10:46:55 - mmengine - INFO - Epoch(train) [1][1140/1253] lr: 4.0000e-02 eta: 11:06:01 time: 0.5784 data_time: 0.0691 memory: 23504 grad_norm: 3.2159 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.9454 loss: 1.9454 2022/09/08 10:47:07 - mmengine - INFO - Epoch(train) [1][1160/1253] lr: 4.0000e-02 eta: 11:04:26 time: 0.5729 data_time: 0.0484 memory: 23504 grad_norm: 3.2675 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.2258 loss: 2.2258 2022/09/08 10:47:18 - mmengine - INFO - Epoch(train) [1][1180/1253] lr: 4.0000e-02 eta: 11:02:37 time: 0.5555 data_time: 0.0396 memory: 23504 grad_norm: 3.2849 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.2030 loss: 2.2030 2022/09/08 10:47:29 - mmengine - INFO - Epoch(train) [1][1200/1253] lr: 4.0000e-02 eta: 11:00:56 time: 0.5615 data_time: 0.0486 memory: 23504 grad_norm: 3.2285 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.2429 loss: 2.2429 2022/09/08 10:47:42 - mmengine - INFO - Epoch(train) [1][1220/1253] lr: 4.0000e-02 eta: 11:00:23 time: 0.6246 data_time: 0.0803 memory: 23504 grad_norm: 3.2250 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.1820 loss: 2.1820 2022/09/08 10:47:51 - mmengine - INFO - Epoch(train) [1][1240/1253] lr: 4.0000e-02 eta: 10:57:25 time: 0.4784 data_time: 0.0298 memory: 23504 grad_norm: 3.2217 top1_acc: 0.3750 top5_acc: 0.7917 loss_cls: 2.0962 loss: 2.0962 2022/09/08 10:47:56 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 10:47:56 - mmengine - INFO - Epoch(train) [1][1253/1253] lr: 4.0000e-02 eta: 10:57:25 time: 0.4297 data_time: 0.0150 memory: 23504 grad_norm: 3.3120 top1_acc: 0.2857 top5_acc: 0.5714 loss_cls: 2.2399 loss: 2.2399 2022/09/08 10:48:18 - mmengine - INFO - Epoch(train) [2][20/1253] lr: 4.0000e-02 eta: 10:57:07 time: 1.0635 data_time: 0.4368 memory: 23504 grad_norm: 3.1446 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.0035 loss: 2.0035 2022/09/08 10:48:30 - mmengine - INFO - Epoch(train) [2][40/1253] lr: 4.0000e-02 eta: 10:56:34 time: 0.6207 data_time: 0.1058 memory: 23504 grad_norm: 3.1968 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.8737 loss: 1.8737 2022/09/08 10:48:42 - mmengine - INFO - Epoch(train) [2][60/1253] lr: 4.0000e-02 eta: 10:55:07 time: 0.5635 data_time: 0.0528 memory: 23504 grad_norm: 3.1862 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.1295 loss: 2.1295 2022/09/08 10:48:52 - mmengine - INFO - Epoch(train) [2][80/1253] lr: 4.0000e-02 eta: 10:53:18 time: 0.5364 data_time: 0.0375 memory: 23504 grad_norm: 3.1249 top1_acc: 0.5833 top5_acc: 0.6667 loss_cls: 1.9936 loss: 1.9936 2022/09/08 10:49:05 - mmengine - INFO - Epoch(train) [2][100/1253] lr: 4.0000e-02 eta: 10:53:24 time: 0.6600 data_time: 0.0571 memory: 23504 grad_norm: 3.2278 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.9819 loss: 1.9819 2022/09/08 10:49:17 - mmengine - INFO - Epoch(train) [2][120/1253] lr: 4.0000e-02 eta: 10:52:04 time: 0.5637 data_time: 0.0414 memory: 23504 grad_norm: 3.2396 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.0613 loss: 2.0613 2022/09/08 10:49:29 - mmengine - INFO - Epoch(train) [2][140/1253] lr: 4.0000e-02 eta: 10:51:38 time: 0.6235 data_time: 0.0420 memory: 23504 grad_norm: 3.1540 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.1266 loss: 2.1266 2022/09/08 10:49:40 - mmengine - INFO - Epoch(train) [2][160/1253] lr: 4.0000e-02 eta: 10:50:14 time: 0.5559 data_time: 0.0432 memory: 23504 grad_norm: 3.1878 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 2.1635 loss: 2.1635 2022/09/08 10:49:52 - mmengine - INFO - Epoch(train) [2][180/1253] lr: 4.0000e-02 eta: 10:49:28 time: 0.5982 data_time: 0.0550 memory: 23504 grad_norm: 3.1843 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.9747 loss: 1.9747 2022/09/08 10:50:03 - mmengine - INFO - Epoch(train) [2][200/1253] lr: 4.0000e-02 eta: 10:48:11 time: 0.5604 data_time: 0.0409 memory: 23504 grad_norm: 3.1922 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 2.0663 loss: 2.0663 2022/09/08 10:50:15 - mmengine - INFO - Epoch(train) [2][220/1253] lr: 4.0000e-02 eta: 10:46:50 time: 0.5538 data_time: 0.0386 memory: 23504 grad_norm: 3.2092 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0884 loss: 2.0884 2022/09/08 10:50:26 - mmengine - INFO - Epoch(train) [2][240/1253] lr: 4.0000e-02 eta: 10:45:35 time: 0.5579 data_time: 0.0365 memory: 23504 grad_norm: 3.1475 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.8338 loss: 1.8338 2022/09/08 10:50:38 - mmengine - INFO - Epoch(train) [2][260/1253] lr: 4.0000e-02 eta: 10:44:57 time: 0.6024 data_time: 0.0538 memory: 23504 grad_norm: 3.1765 top1_acc: 0.2083 top5_acc: 0.7500 loss_cls: 2.0286 loss: 2.0286 2022/09/08 10:50:49 - mmengine - INFO - Epoch(train) [2][280/1253] lr: 4.0000e-02 eta: 10:43:55 time: 0.5709 data_time: 0.0346 memory: 23504 grad_norm: 3.2116 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2899 loss: 2.2899 2022/09/08 10:51:01 - mmengine - INFO - Epoch(train) [2][300/1253] lr: 4.0000e-02 eta: 10:43:23 time: 0.6073 data_time: 0.0461 memory: 23504 grad_norm: 3.1803 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 2.2628 loss: 2.2628 2022/09/08 10:51:13 - mmengine - INFO - Epoch(train) [2][320/1253] lr: 4.0000e-02 eta: 10:42:22 time: 0.5693 data_time: 0.0369 memory: 23504 grad_norm: 3.0612 top1_acc: 0.6667 top5_acc: 0.7500 loss_cls: 1.9069 loss: 1.9069 2022/09/08 10:51:24 - mmengine - INFO - Epoch(train) [2][340/1253] lr: 4.0000e-02 eta: 10:41:28 time: 0.5771 data_time: 0.0502 memory: 23504 grad_norm: 3.2038 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 2.0223 loss: 2.0223 2022/09/08 10:51:35 - mmengine - INFO - Epoch(train) [2][360/1253] lr: 4.0000e-02 eta: 10:40:17 time: 0.5535 data_time: 0.0397 memory: 23504 grad_norm: 3.1173 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 2.0626 loss: 2.0626 2022/09/08 10:51:47 - mmengine - INFO - Epoch(train) [2][380/1253] lr: 4.0000e-02 eta: 10:39:22 time: 0.5724 data_time: 0.0473 memory: 23504 grad_norm: 3.1321 top1_acc: 0.5833 top5_acc: 0.6667 loss_cls: 1.9151 loss: 1.9151 2022/09/08 10:51:58 - mmengine - INFO - Epoch(train) [2][400/1253] lr: 4.0000e-02 eta: 10:38:16 time: 0.5561 data_time: 0.0421 memory: 23504 grad_norm: 3.1246 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.0802 loss: 2.0802 2022/09/08 10:52:09 - mmengine - INFO - Epoch(train) [2][420/1253] lr: 4.0000e-02 eta: 10:37:23 time: 0.5734 data_time: 0.0492 memory: 23504 grad_norm: 3.1864 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 2.0287 loss: 2.0287 2022/09/08 10:52:21 - mmengine - INFO - Epoch(train) [2][440/1253] lr: 4.0000e-02 eta: 10:36:44 time: 0.5898 data_time: 0.0384 memory: 23504 grad_norm: 3.0910 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.9225 loss: 1.9225 2022/09/08 10:52:34 - mmengine - INFO - Epoch(train) [2][460/1253] lr: 4.0000e-02 eta: 10:36:28 time: 0.6220 data_time: 0.0531 memory: 23504 grad_norm: 3.2318 top1_acc: 0.6667 top5_acc: 0.7500 loss_cls: 2.1117 loss: 2.1117 2022/09/08 10:52:45 - mmengine - INFO - Epoch(train) [2][480/1253] lr: 4.0000e-02 eta: 10:35:33 time: 0.5661 data_time: 0.0467 memory: 23504 grad_norm: 3.0725 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 2.0865 loss: 2.0865 2022/09/08 10:52:57 - mmengine - INFO - Epoch(train) [2][500/1253] lr: 4.0000e-02 eta: 10:34:47 time: 0.5782 data_time: 0.0491 memory: 23504 grad_norm: 3.1179 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 2.0218 loss: 2.0218 2022/09/08 10:53:08 - mmengine - INFO - Epoch(train) [2][520/1253] lr: 4.0000e-02 eta: 10:34:00 time: 0.5748 data_time: 0.0410 memory: 23504 grad_norm: 3.1445 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1741 loss: 2.1741 2022/09/08 10:53:19 - mmengine - INFO - Epoch(train) [2][540/1253] lr: 4.0000e-02 eta: 10:33:01 time: 0.5562 data_time: 0.0390 memory: 23504 grad_norm: 3.0731 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.9481 loss: 1.9481 2022/09/08 10:53:30 - mmengine - INFO - Epoch(train) [2][560/1253] lr: 4.0000e-02 eta: 10:32:08 time: 0.5638 data_time: 0.0499 memory: 23504 grad_norm: 3.1817 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 2.1254 loss: 2.1254 2022/09/08 10:53:42 - mmengine - INFO - Epoch(train) [2][580/1253] lr: 4.0000e-02 eta: 10:31:19 time: 0.5689 data_time: 0.0498 memory: 23504 grad_norm: 3.0869 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.7607 loss: 1.7607 2022/09/08 10:53:53 - mmengine - INFO - Epoch(train) [2][600/1253] lr: 4.0000e-02 eta: 10:30:35 time: 0.5750 data_time: 0.0518 memory: 23504 grad_norm: 3.1221 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 2.1111 loss: 2.1111 2022/09/08 10:54:05 - mmengine - INFO - Epoch(train) [2][620/1253] lr: 4.0000e-02 eta: 10:29:45 time: 0.5642 data_time: 0.0378 memory: 23504 grad_norm: 3.0533 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.8981 loss: 1.8981 2022/09/08 10:54:17 - mmengine - INFO - Epoch(train) [2][640/1253] lr: 4.0000e-02 eta: 10:29:43 time: 0.6378 data_time: 0.1196 memory: 23504 grad_norm: 3.1337 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 2.0318 loss: 2.0318 2022/09/08 10:54:29 - mmengine - INFO - Epoch(train) [2][660/1253] lr: 4.0000e-02 eta: 10:29:00 time: 0.5731 data_time: 0.0455 memory: 23504 grad_norm: 3.0743 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.9572 loss: 1.9572 2022/09/08 10:54:40 - mmengine - INFO - Epoch(train) [2][680/1253] lr: 4.0000e-02 eta: 10:27:55 time: 0.5388 data_time: 0.0404 memory: 23504 grad_norm: 3.0738 top1_acc: 0.3333 top5_acc: 0.5417 loss_cls: 1.9791 loss: 1.9791 2022/09/08 10:54:51 - mmengine - INFO - Epoch(train) [2][700/1253] lr: 4.0000e-02 eta: 10:27:05 time: 0.5588 data_time: 0.0453 memory: 23504 grad_norm: 3.1515 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 2.0816 loss: 2.0816 2022/09/08 10:55:02 - mmengine - INFO - Epoch(train) [2][720/1253] lr: 4.0000e-02 eta: 10:26:23 time: 0.5716 data_time: 0.0399 memory: 23504 grad_norm: 3.1299 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.9670 loss: 1.9670 2022/09/08 10:55:14 - mmengine - INFO - Epoch(train) [2][740/1253] lr: 4.0000e-02 eta: 10:25:43 time: 0.5751 data_time: 0.0527 memory: 23504 grad_norm: 3.1830 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 2.1395 loss: 2.1395 2022/09/08 10:55:18 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 10:55:25 - mmengine - INFO - Epoch(train) [2][760/1253] lr: 4.0000e-02 eta: 10:25:03 time: 0.5737 data_time: 0.0433 memory: 23504 grad_norm: 3.1440 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.0767 loss: 2.0767 2022/09/08 10:55:37 - mmengine - INFO - Epoch(train) [2][780/1253] lr: 4.0000e-02 eta: 10:24:41 time: 0.6022 data_time: 0.0780 memory: 23504 grad_norm: 3.0562 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.0639 loss: 2.0639 2022/09/08 10:55:49 - mmengine - INFO - Epoch(train) [2][800/1253] lr: 4.0000e-02 eta: 10:24:22 time: 0.6059 data_time: 0.0493 memory: 23504 grad_norm: 2.9987 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1772 loss: 2.1772 2022/09/08 10:56:01 - mmengine - INFO - Epoch(train) [2][820/1253] lr: 4.0000e-02 eta: 10:23:39 time: 0.5661 data_time: 0.0393 memory: 23504 grad_norm: 3.0410 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.9815 loss: 1.9815 2022/09/08 10:56:13 - mmengine - INFO - Epoch(train) [2][840/1253] lr: 4.0000e-02 eta: 10:23:23 time: 0.6120 data_time: 0.0512 memory: 23504 grad_norm: 3.0203 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.8988 loss: 1.8988 2022/09/08 10:56:25 - mmengine - INFO - Epoch(train) [2][860/1253] lr: 4.0000e-02 eta: 10:22:50 time: 0.5820 data_time: 0.0460 memory: 23504 grad_norm: 3.0542 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.9922 loss: 1.9922 2022/09/08 10:56:36 - mmengine - INFO - Epoch(train) [2][880/1253] lr: 4.0000e-02 eta: 10:22:25 time: 0.5949 data_time: 0.0372 memory: 23504 grad_norm: 3.0933 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 2.0220 loss: 2.0220 2022/09/08 10:56:48 - mmengine - INFO - Epoch(train) [2][900/1253] lr: 4.0000e-02 eta: 10:21:46 time: 0.5688 data_time: 0.0446 memory: 23504 grad_norm: 3.0654 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.9466 loss: 1.9466 2022/09/08 10:56:59 - mmengine - INFO - Epoch(train) [2][920/1253] lr: 4.0000e-02 eta: 10:21:16 time: 0.5849 data_time: 0.0613 memory: 23504 grad_norm: 3.1059 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 2.1321 loss: 2.1321 2022/09/08 10:57:11 - mmengine - INFO - Epoch(train) [2][940/1253] lr: 4.0000e-02 eta: 10:20:37 time: 0.5690 data_time: 0.0435 memory: 23504 grad_norm: 2.9901 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.9911 loss: 1.9911 2022/09/08 10:57:23 - mmengine - INFO - Epoch(train) [2][960/1253] lr: 4.0000e-02 eta: 10:20:08 time: 0.5840 data_time: 0.0403 memory: 23504 grad_norm: 3.0297 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 2.2898 loss: 2.2898 2022/09/08 10:57:34 - mmengine - INFO - Epoch(train) [2][980/1253] lr: 4.0000e-02 eta: 10:19:29 time: 0.5664 data_time: 0.0342 memory: 23504 grad_norm: 3.0090 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0851 loss: 2.0851 2022/09/08 10:57:45 - mmengine - INFO - Epoch(train) [2][1000/1253] lr: 4.0000e-02 eta: 10:18:55 time: 0.5746 data_time: 0.0530 memory: 23504 grad_norm: 2.9978 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 1.9903 loss: 1.9903 2022/09/08 10:57:57 - mmengine - INFO - Epoch(train) [2][1020/1253] lr: 4.0000e-02 eta: 10:18:22 time: 0.5761 data_time: 0.0398 memory: 23504 grad_norm: 2.9685 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 1.9471 loss: 1.9471 2022/09/08 10:58:08 - mmengine - INFO - Epoch(train) [2][1040/1253] lr: 4.0000e-02 eta: 10:17:40 time: 0.5586 data_time: 0.0438 memory: 23504 grad_norm: 3.0928 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 1.9771 loss: 1.9771 2022/09/08 10:58:19 - mmengine - INFO - Epoch(train) [2][1060/1253] lr: 4.0000e-02 eta: 10:16:58 time: 0.5573 data_time: 0.0464 memory: 23504 grad_norm: 3.0539 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9256 loss: 1.9256 2022/09/08 10:58:30 - mmengine - INFO - Epoch(train) [2][1080/1253] lr: 4.0000e-02 eta: 10:16:20 time: 0.5644 data_time: 0.0486 memory: 23504 grad_norm: 3.0283 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1239 loss: 2.1239 2022/09/08 10:58:42 - mmengine - INFO - Epoch(train) [2][1100/1253] lr: 4.0000e-02 eta: 10:15:38 time: 0.5543 data_time: 0.0409 memory: 23504 grad_norm: 3.0106 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 2.0953 loss: 2.0953 2022/09/08 10:58:53 - mmengine - INFO - Epoch(train) [2][1120/1253] lr: 4.0000e-02 eta: 10:15:05 time: 0.5713 data_time: 0.0422 memory: 23504 grad_norm: 2.9773 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.0450 loss: 2.0450 2022/09/08 10:59:04 - mmengine - INFO - Epoch(train) [2][1140/1253] lr: 4.0000e-02 eta: 10:14:33 time: 0.5740 data_time: 0.0427 memory: 23504 grad_norm: 3.0739 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 2.1071 loss: 2.1071 2022/09/08 10:59:16 - mmengine - INFO - Epoch(train) [2][1160/1253] lr: 4.0000e-02 eta: 10:14:08 time: 0.5849 data_time: 0.0448 memory: 23504 grad_norm: 2.9492 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 2.0438 loss: 2.0438 2022/09/08 10:59:28 - mmengine - INFO - Epoch(train) [2][1180/1253] lr: 4.0000e-02 eta: 10:13:40 time: 0.5811 data_time: 0.0441 memory: 23504 grad_norm: 2.9493 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 1.9874 loss: 1.9874 2022/09/08 10:59:40 - mmengine - INFO - Epoch(train) [2][1200/1253] lr: 4.0000e-02 eta: 10:13:20 time: 0.5951 data_time: 0.0589 memory: 23504 grad_norm: 2.9834 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9464 loss: 1.9464 2022/09/08 10:59:51 - mmengine - INFO - Epoch(train) [2][1220/1253] lr: 4.0000e-02 eta: 10:12:48 time: 0.5702 data_time: 0.0442 memory: 23504 grad_norm: 3.0304 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7495 loss: 1.7495 2022/09/08 11:00:01 - mmengine - INFO - Epoch(train) [2][1240/1253] lr: 4.0000e-02 eta: 10:11:42 time: 0.5001 data_time: 0.0332 memory: 23504 grad_norm: 2.9786 top1_acc: 0.4583 top5_acc: 0.8750 loss_cls: 1.9177 loss: 1.9177 2022/09/08 11:00:07 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 11:00:07 - mmengine - INFO - Epoch(train) [2][1253/1253] lr: 4.0000e-02 eta: 10:11:42 time: 0.4313 data_time: 0.0177 memory: 23504 grad_norm: 3.0894 top1_acc: 0.2857 top5_acc: 1.0000 loss_cls: 1.9452 loss: 1.9452 2022/09/08 11:00:29 - mmengine - INFO - Epoch(train) [3][20/1253] lr: 4.0000e-02 eta: 10:12:04 time: 1.0964 data_time: 0.4484 memory: 23504 grad_norm: 3.0176 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.7597 loss: 1.7597 2022/09/08 11:00:40 - mmengine - INFO - Epoch(train) [3][40/1253] lr: 4.0000e-02 eta: 10:11:40 time: 0.5842 data_time: 0.0450 memory: 23504 grad_norm: 2.9853 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9837 loss: 1.9837 2022/09/08 11:00:52 - mmengine - INFO - Epoch(train) [3][60/1253] lr: 4.0000e-02 eta: 10:11:22 time: 0.5989 data_time: 0.0378 memory: 23504 grad_norm: 3.0668 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 1.8239 loss: 1.8239 2022/09/08 11:01:04 - mmengine - INFO - Epoch(train) [3][80/1253] lr: 4.0000e-02 eta: 10:10:50 time: 0.5675 data_time: 0.0394 memory: 23504 grad_norm: 2.9595 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.7775 loss: 1.7775 2022/09/08 11:01:17 - mmengine - INFO - Epoch(train) [3][100/1253] lr: 4.0000e-02 eta: 10:11:07 time: 0.6730 data_time: 0.0518 memory: 23504 grad_norm: 3.0130 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9547 loss: 1.9547 2022/09/08 11:01:29 - mmengine - INFO - Epoch(train) [3][120/1253] lr: 4.0000e-02 eta: 10:10:38 time: 0.5760 data_time: 0.0438 memory: 23504 grad_norm: 3.0387 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.9394 loss: 1.9394 2022/09/08 11:01:39 - mmengine - INFO - Epoch(train) [3][140/1253] lr: 4.0000e-02 eta: 10:09:56 time: 0.5435 data_time: 0.0362 memory: 23504 grad_norm: 3.0930 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9268 loss: 1.9268 2022/09/08 11:01:51 - mmengine - INFO - Epoch(train) [3][160/1253] lr: 4.0000e-02 eta: 10:09:22 time: 0.5609 data_time: 0.0322 memory: 23504 grad_norm: 2.9838 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.9218 loss: 1.9218 2022/09/08 11:02:03 - mmengine - INFO - Epoch(train) [3][180/1253] lr: 4.0000e-02 eta: 10:09:04 time: 0.5973 data_time: 0.0546 memory: 23504 grad_norm: 3.0239 top1_acc: 0.4583 top5_acc: 0.5833 loss_cls: 2.0395 loss: 2.0395 2022/09/08 11:02:14 - mmengine - INFO - Epoch(train) [3][200/1253] lr: 4.0000e-02 eta: 10:08:41 time: 0.5853 data_time: 0.0513 memory: 23504 grad_norm: 2.9582 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8383 loss: 1.8383 2022/09/08 11:02:25 - mmengine - INFO - Epoch(train) [3][220/1253] lr: 4.0000e-02 eta: 10:08:08 time: 0.5607 data_time: 0.0459 memory: 23504 grad_norm: 2.9525 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.8453 loss: 1.8453 2022/09/08 11:02:37 - mmengine - INFO - Epoch(train) [3][240/1253] lr: 4.0000e-02 eta: 10:07:36 time: 0.5652 data_time: 0.0472 memory: 23504 grad_norm: 2.9634 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.8755 loss: 1.8755 2022/09/08 11:02:48 - mmengine - INFO - Epoch(train) [3][260/1253] lr: 4.0000e-02 eta: 10:07:07 time: 0.5681 data_time: 0.0459 memory: 23504 grad_norm: 3.0275 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0662 loss: 2.0662 2022/09/08 11:02:59 - mmengine - INFO - Epoch(train) [3][280/1253] lr: 4.0000e-02 eta: 10:06:34 time: 0.5612 data_time: 0.0465 memory: 23504 grad_norm: 2.9649 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 2.1787 loss: 2.1787 2022/09/08 11:03:11 - mmengine - INFO - Epoch(train) [3][300/1253] lr: 4.0000e-02 eta: 10:06:01 time: 0.5596 data_time: 0.0402 memory: 23504 grad_norm: 3.0243 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.9027 loss: 1.9027 2022/09/08 11:03:22 - mmengine - INFO - Epoch(train) [3][320/1253] lr: 4.0000e-02 eta: 10:05:31 time: 0.5653 data_time: 0.0458 memory: 23504 grad_norm: 3.0184 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0073 loss: 2.0073 2022/09/08 11:03:33 - mmengine - INFO - Epoch(train) [3][340/1253] lr: 4.0000e-02 eta: 10:05:06 time: 0.5765 data_time: 0.0358 memory: 23504 grad_norm: 2.9890 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 1.9874 loss: 1.9874 2022/09/08 11:03:46 - mmengine - INFO - Epoch(train) [3][360/1253] lr: 4.0000e-02 eta: 10:05:07 time: 0.6372 data_time: 0.0652 memory: 23504 grad_norm: 2.9170 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 1.8871 loss: 1.8871 2022/09/08 11:03:58 - mmengine - INFO - Epoch(train) [3][380/1253] lr: 4.0000e-02 eta: 10:04:44 time: 0.5812 data_time: 0.0433 memory: 23504 grad_norm: 2.9584 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.9564 loss: 1.9564 2022/09/08 11:04:09 - mmengine - INFO - Epoch(train) [3][400/1253] lr: 4.0000e-02 eta: 10:04:17 time: 0.5706 data_time: 0.0454 memory: 23504 grad_norm: 2.9544 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.8698 loss: 1.8698 2022/09/08 11:04:20 - mmengine - INFO - Epoch(train) [3][420/1253] lr: 4.0000e-02 eta: 10:03:44 time: 0.5559 data_time: 0.0344 memory: 23504 grad_norm: 2.9256 top1_acc: 0.4167 top5_acc: 0.8333 loss_cls: 1.9236 loss: 1.9236 2022/09/08 11:04:32 - mmengine - INFO - Epoch(train) [3][440/1253] lr: 4.0000e-02 eta: 10:03:22 time: 0.5840 data_time: 0.0440 memory: 23504 grad_norm: 2.9207 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 2.0298 loss: 2.0298 2022/09/08 11:04:43 - mmengine - INFO - Epoch(train) [3][460/1253] lr: 4.0000e-02 eta: 10:02:55 time: 0.5691 data_time: 0.0501 memory: 23504 grad_norm: 2.9051 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 1.7938 loss: 1.7938 2022/09/08 11:04:55 - mmengine - INFO - Epoch(train) [3][480/1253] lr: 4.0000e-02 eta: 10:02:35 time: 0.5855 data_time: 0.0452 memory: 23504 grad_norm: 3.0625 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.9406 loss: 1.9406 2022/09/08 11:05:03 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 11:05:06 - mmengine - INFO - Epoch(train) [3][500/1253] lr: 4.0000e-02 eta: 10:02:08 time: 0.5691 data_time: 0.0404 memory: 23504 grad_norm: 3.0894 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.9669 loss: 1.9669 2022/09/08 11:05:19 - mmengine - INFO - Epoch(train) [3][520/1253] lr: 4.0000e-02 eta: 10:01:56 time: 0.6062 data_time: 0.0396 memory: 23504 grad_norm: 3.0443 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.8571 loss: 1.8571 2022/09/08 11:05:30 - mmengine - INFO - Epoch(train) [3][540/1253] lr: 4.0000e-02 eta: 10:01:31 time: 0.5724 data_time: 0.0496 memory: 23504 grad_norm: 3.0397 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 2.0443 loss: 2.0443 2022/09/08 11:05:41 - mmengine - INFO - Epoch(train) [3][560/1253] lr: 4.0000e-02 eta: 10:01:05 time: 0.5692 data_time: 0.0395 memory: 23504 grad_norm: 2.9778 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 1.7782 loss: 1.7782 2022/09/08 11:05:53 - mmengine - INFO - Epoch(train) [3][580/1253] lr: 4.0000e-02 eta: 10:00:34 time: 0.5563 data_time: 0.0500 memory: 23504 grad_norm: 2.9222 top1_acc: 0.6667 top5_acc: 0.7083 loss_cls: 1.9674 loss: 1.9674 2022/09/08 11:06:04 - mmengine - INFO - Epoch(train) [3][600/1253] lr: 4.0000e-02 eta: 10:00:06 time: 0.5631 data_time: 0.0471 memory: 23504 grad_norm: 2.9106 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.0907 loss: 2.0907 2022/09/08 11:06:15 - mmengine - INFO - Epoch(train) [3][620/1253] lr: 4.0000e-02 eta: 9:59:35 time: 0.5556 data_time: 0.0498 memory: 23504 grad_norm: 3.0167 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 1.9398 loss: 1.9398 2022/09/08 11:06:26 - mmengine - INFO - Epoch(train) [3][640/1253] lr: 4.0000e-02 eta: 9:59:05 time: 0.5584 data_time: 0.0451 memory: 23504 grad_norm: 2.8579 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 2.0654 loss: 2.0654 2022/09/08 11:06:38 - mmengine - INFO - Epoch(train) [3][660/1253] lr: 4.0000e-02 eta: 9:58:47 time: 0.5878 data_time: 0.0461 memory: 23504 grad_norm: 2.9541 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.8746 loss: 1.8746 2022/09/08 11:06:50 - mmengine - INFO - Epoch(train) [3][680/1253] lr: 4.0000e-02 eta: 9:58:33 time: 0.5998 data_time: 0.0457 memory: 23504 grad_norm: 2.9970 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.8754 loss: 1.8754 2022/09/08 11:07:01 - mmengine - INFO - Epoch(train) [3][700/1253] lr: 4.0000e-02 eta: 9:58:07 time: 0.5665 data_time: 0.0583 memory: 23504 grad_norm: 3.0735 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 2.0735 loss: 2.0735 2022/09/08 11:07:13 - mmengine - INFO - Epoch(train) [3][720/1253] lr: 4.0000e-02 eta: 9:57:51 time: 0.5914 data_time: 0.0436 memory: 23504 grad_norm: 2.9607 top1_acc: 0.4583 top5_acc: 0.8750 loss_cls: 1.8630 loss: 1.8630 2022/09/08 11:07:25 - mmengine - INFO - Epoch(train) [3][740/1253] lr: 4.0000e-02 eta: 9:57:32 time: 0.5856 data_time: 0.0349 memory: 23504 grad_norm: 2.9846 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 1.8513 loss: 1.8513 2022/09/08 11:07:36 - mmengine - INFO - Epoch(train) [3][760/1253] lr: 4.0000e-02 eta: 9:57:13 time: 0.5827 data_time: 0.0387 memory: 23504 grad_norm: 2.9373 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.8520 loss: 1.8520 2022/09/08 11:07:50 - mmengine - INFO - Epoch(train) [3][780/1253] lr: 4.0000e-02 eta: 9:57:29 time: 0.6824 data_time: 0.0499 memory: 23504 grad_norm: 2.9876 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0589 loss: 2.0589 2022/09/08 11:08:01 - mmengine - INFO - Epoch(train) [3][800/1253] lr: 4.0000e-02 eta: 9:56:58 time: 0.5498 data_time: 0.0421 memory: 23504 grad_norm: 3.0143 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.8812 loss: 1.8812 2022/09/08 11:08:12 - mmengine - INFO - Epoch(train) [3][820/1253] lr: 4.0000e-02 eta: 9:56:29 time: 0.5578 data_time: 0.0403 memory: 23504 grad_norm: 2.9566 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.9355 loss: 1.9355 2022/09/08 11:08:23 - mmengine - INFO - Epoch(train) [3][840/1253] lr: 4.0000e-02 eta: 9:55:57 time: 0.5479 data_time: 0.0510 memory: 23504 grad_norm: 2.9782 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 1.8240 loss: 1.8240 2022/09/08 11:08:34 - mmengine - INFO - Epoch(train) [3][860/1253] lr: 4.0000e-02 eta: 9:55:24 time: 0.5418 data_time: 0.0440 memory: 23504 grad_norm: 2.9289 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.8406 loss: 1.8406 2022/09/08 11:08:45 - mmengine - INFO - Epoch(train) [3][880/1253] lr: 4.0000e-02 eta: 9:55:02 time: 0.5737 data_time: 0.0469 memory: 23504 grad_norm: 2.9468 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.9341 loss: 1.9341 2022/09/08 11:08:57 - mmengine - INFO - Epoch(train) [3][900/1253] lr: 4.0000e-02 eta: 9:54:39 time: 0.5709 data_time: 0.0467 memory: 23504 grad_norm: 2.9742 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8861 loss: 1.8861 2022/09/08 11:09:08 - mmengine - INFO - Epoch(train) [3][920/1253] lr: 4.0000e-02 eta: 9:54:18 time: 0.5771 data_time: 0.0405 memory: 23504 grad_norm: 2.8911 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9011 loss: 1.9011 2022/09/08 11:09:20 - mmengine - INFO - Epoch(train) [3][940/1253] lr: 4.0000e-02 eta: 9:53:53 time: 0.5654 data_time: 0.0463 memory: 23504 grad_norm: 2.9215 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.9834 loss: 1.9834 2022/09/08 11:09:31 - mmengine - INFO - Epoch(train) [3][960/1253] lr: 4.0000e-02 eta: 9:53:36 time: 0.5865 data_time: 0.0682 memory: 23504 grad_norm: 3.0094 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.9150 loss: 1.9150 2022/09/08 11:09:43 - mmengine - INFO - Epoch(train) [3][980/1253] lr: 4.0000e-02 eta: 9:53:19 time: 0.5863 data_time: 0.0439 memory: 23504 grad_norm: 2.8883 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.8475 loss: 1.8475 2022/09/08 11:09:55 - mmengine - INFO - Epoch(train) [3][1000/1253] lr: 4.0000e-02 eta: 9:52:59 time: 0.5801 data_time: 0.0351 memory: 23504 grad_norm: 2.9319 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7315 loss: 1.7315 2022/09/08 11:10:07 - mmengine - INFO - Epoch(train) [3][1020/1253] lr: 4.0000e-02 eta: 9:52:43 time: 0.5888 data_time: 0.0396 memory: 23504 grad_norm: 3.0039 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.7596 loss: 1.7596 2022/09/08 11:10:18 - mmengine - INFO - Epoch(train) [3][1040/1253] lr: 4.0000e-02 eta: 9:52:27 time: 0.5908 data_time: 0.0492 memory: 23504 grad_norm: 2.9509 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.8369 loss: 1.8369 2022/09/08 11:10:30 - mmengine - INFO - Epoch(train) [3][1060/1253] lr: 4.0000e-02 eta: 9:52:09 time: 0.5825 data_time: 0.0331 memory: 23504 grad_norm: 2.9250 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 1.8749 loss: 1.8749 2022/09/08 11:10:42 - mmengine - INFO - Epoch(train) [3][1080/1253] lr: 4.0000e-02 eta: 9:51:50 time: 0.5800 data_time: 0.0538 memory: 23504 grad_norm: 3.0343 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.9106 loss: 1.9106 2022/09/08 11:10:52 - mmengine - INFO - Epoch(train) [3][1100/1253] lr: 4.0000e-02 eta: 9:51:18 time: 0.5410 data_time: 0.0407 memory: 23504 grad_norm: 2.8942 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7380 loss: 1.7380 2022/09/08 11:11:03 - mmengine - INFO - Epoch(train) [3][1120/1253] lr: 4.0000e-02 eta: 9:50:49 time: 0.5488 data_time: 0.0430 memory: 23504 grad_norm: 2.9318 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 1.9804 loss: 1.9804 2022/09/08 11:11:14 - mmengine - INFO - Epoch(train) [3][1140/1253] lr: 4.0000e-02 eta: 9:50:21 time: 0.5513 data_time: 0.0496 memory: 23504 grad_norm: 2.9690 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0179 loss: 2.0179 2022/09/08 11:11:26 - mmengine - INFO - Epoch(train) [3][1160/1253] lr: 4.0000e-02 eta: 9:49:55 time: 0.5555 data_time: 0.0401 memory: 23504 grad_norm: 2.9039 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 1.9550 loss: 1.9550 2022/09/08 11:11:37 - mmengine - INFO - Epoch(train) [3][1180/1253] lr: 4.0000e-02 eta: 9:49:34 time: 0.5733 data_time: 0.0446 memory: 23504 grad_norm: 2.9366 top1_acc: 0.5417 top5_acc: 0.6667 loss_cls: 1.9239 loss: 1.9239 2022/09/08 11:11:49 - mmengine - INFO - Epoch(train) [3][1200/1253] lr: 4.0000e-02 eta: 9:49:20 time: 0.5938 data_time: 0.0577 memory: 23504 grad_norm: 2.9680 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 2.1506 loss: 2.1506 2022/09/08 11:12:00 - mmengine - INFO - Epoch(train) [3][1220/1253] lr: 4.0000e-02 eta: 9:48:59 time: 0.5691 data_time: 0.0415 memory: 23504 grad_norm: 2.9417 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.1352 loss: 2.1352 2022/09/08 11:12:10 - mmengine - INFO - Epoch(train) [3][1240/1253] lr: 4.0000e-02 eta: 9:48:18 time: 0.5091 data_time: 0.0222 memory: 23504 grad_norm: 2.9362 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.8027 loss: 1.8027 2022/09/08 11:12:16 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 11:12:16 - mmengine - INFO - Epoch(train) [3][1253/1253] lr: 4.0000e-02 eta: 9:48:18 time: 0.4316 data_time: 0.0164 memory: 23504 grad_norm: 2.9956 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.7938 loss: 1.7938 2022/09/08 11:12:37 - mmengine - INFO - Epoch(train) [4][20/1253] lr: 4.0000e-02 eta: 9:48:13 time: 1.0365 data_time: 0.4710 memory: 23504 grad_norm: 2.9265 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.9341 loss: 1.9341 2022/09/08 11:12:49 - mmengine - INFO - Epoch(train) [4][40/1253] lr: 4.0000e-02 eta: 9:47:58 time: 0.5887 data_time: 0.0440 memory: 23504 grad_norm: 2.9090 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.8517 loss: 1.8517 2022/09/08 11:13:00 - mmengine - INFO - Epoch(train) [4][60/1253] lr: 4.0000e-02 eta: 9:47:39 time: 0.5771 data_time: 0.0387 memory: 23504 grad_norm: 2.8912 top1_acc: 0.5000 top5_acc: 0.9167 loss_cls: 1.9913 loss: 1.9913 2022/09/08 11:13:11 - mmengine - INFO - Epoch(train) [4][80/1253] lr: 4.0000e-02 eta: 9:47:16 time: 0.5630 data_time: 0.0418 memory: 23504 grad_norm: 2.9435 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8608 loss: 1.8608 2022/09/08 11:13:23 - mmengine - INFO - Epoch(train) [4][100/1253] lr: 4.0000e-02 eta: 9:47:06 time: 0.6043 data_time: 0.0556 memory: 23504 grad_norm: 2.9202 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8837 loss: 1.8837 2022/09/08 11:13:34 - mmengine - INFO - Epoch(train) [4][120/1253] lr: 4.0000e-02 eta: 9:46:35 time: 0.5364 data_time: 0.0405 memory: 23504 grad_norm: 2.9829 top1_acc: 0.5000 top5_acc: 0.9583 loss_cls: 1.8964 loss: 1.8964 2022/09/08 11:13:46 - mmengine - INFO - Epoch(train) [4][140/1253] lr: 4.0000e-02 eta: 9:46:22 time: 0.5984 data_time: 0.1022 memory: 23504 grad_norm: 2.9532 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8611 loss: 1.8611 2022/09/08 11:13:57 - mmengine - INFO - Epoch(train) [4][160/1253] lr: 4.0000e-02 eta: 9:46:01 time: 0.5665 data_time: 0.0668 memory: 23504 grad_norm: 2.9701 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.7857 loss: 1.7857 2022/09/08 11:14:10 - mmengine - INFO - Epoch(train) [4][180/1253] lr: 4.0000e-02 eta: 9:45:57 time: 0.6271 data_time: 0.0843 memory: 23504 grad_norm: 2.9352 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.9210 loss: 1.9210 2022/09/08 11:14:22 - mmengine - INFO - Epoch(train) [4][200/1253] lr: 4.0000e-02 eta: 9:45:39 time: 0.5784 data_time: 0.0670 memory: 23504 grad_norm: 2.9709 top1_acc: 0.7500 top5_acc: 0.7917 loss_cls: 1.7823 loss: 1.7823 2022/09/08 11:14:33 - mmengine - INFO - Epoch(train) [4][220/1253] lr: 4.0000e-02 eta: 9:45:21 time: 0.5775 data_time: 0.0424 memory: 23504 grad_norm: 2.9636 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.7357 loss: 1.7357 2022/09/08 11:14:44 - mmengine - INFO - Epoch(train) [4][240/1253] lr: 4.0000e-02 eta: 9:44:52 time: 0.5420 data_time: 0.0391 memory: 23504 grad_norm: 2.9246 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.9851 loss: 1.9851 2022/09/08 11:14:45 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 11:14:56 - mmengine - INFO - Epoch(train) [4][260/1253] lr: 4.0000e-02 eta: 9:44:35 time: 0.5804 data_time: 0.0500 memory: 23504 grad_norm: 2.9139 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8757 loss: 1.8757 2022/09/08 11:15:07 - mmengine - INFO - Epoch(train) [4][280/1253] lr: 4.0000e-02 eta: 9:44:18 time: 0.5786 data_time: 0.0720 memory: 23504 grad_norm: 2.8570 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.8822 loss: 1.8822 2022/09/08 11:15:19 - mmengine - INFO - Epoch(train) [4][300/1253] lr: 4.0000e-02 eta: 9:44:05 time: 0.5976 data_time: 0.0820 memory: 23504 grad_norm: 2.8960 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.8549 loss: 1.8549 2022/09/08 11:15:30 - mmengine - INFO - Epoch(train) [4][320/1253] lr: 4.0000e-02 eta: 9:43:44 time: 0.5637 data_time: 0.0428 memory: 23504 grad_norm: 2.9206 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.6911 loss: 1.6911 2022/09/08 11:15:42 - mmengine - INFO - Epoch(train) [4][340/1253] lr: 4.0000e-02 eta: 9:43:33 time: 0.6015 data_time: 0.0601 memory: 23504 grad_norm: 3.0341 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 1.7458 loss: 1.7458 2022/09/08 11:15:54 - mmengine - INFO - Epoch(train) [4][360/1253] lr: 4.0000e-02 eta: 9:43:14 time: 0.5729 data_time: 0.0431 memory: 23504 grad_norm: 2.9132 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 1.8045 loss: 1.8045 2022/09/08 11:16:05 - mmengine - INFO - Epoch(train) [4][380/1253] lr: 4.0000e-02 eta: 9:42:52 time: 0.5641 data_time: 0.0364 memory: 23504 grad_norm: 2.9691 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8793 loss: 1.8793 2022/09/08 11:16:17 - mmengine - INFO - Epoch(train) [4][400/1253] lr: 4.0000e-02 eta: 9:42:36 time: 0.5819 data_time: 0.0364 memory: 23504 grad_norm: 2.9691 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 2.0605 loss: 2.0605 2022/09/08 11:16:29 - mmengine - INFO - Epoch(train) [4][420/1253] lr: 4.0000e-02 eta: 9:42:28 time: 0.6116 data_time: 0.0458 memory: 23504 grad_norm: 2.8715 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7195 loss: 1.7195 2022/09/08 11:16:41 - mmengine - INFO - Epoch(train) [4][440/1253] lr: 4.0000e-02 eta: 9:42:14 time: 0.5921 data_time: 0.0416 memory: 23504 grad_norm: 2.8948 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.7635 loss: 1.7635 2022/09/08 11:16:53 - mmengine - INFO - Epoch(train) [4][460/1253] lr: 4.0000e-02 eta: 9:42:03 time: 0.5992 data_time: 0.0395 memory: 23504 grad_norm: 2.8962 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 2.0018 loss: 2.0018 2022/09/08 11:17:06 - mmengine - INFO - Epoch(train) [4][480/1253] lr: 4.0000e-02 eta: 9:42:05 time: 0.6501 data_time: 0.0415 memory: 23504 grad_norm: 2.9817 top1_acc: 0.3333 top5_acc: 0.6250 loss_cls: 1.8357 loss: 1.8357 2022/09/08 11:17:17 - mmengine - INFO - Epoch(train) [4][500/1253] lr: 4.0000e-02 eta: 9:41:44 time: 0.5637 data_time: 0.0405 memory: 23504 grad_norm: 2.8397 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.9214 loss: 1.9214 2022/09/08 11:17:29 - mmengine - INFO - Epoch(train) [4][520/1253] lr: 4.0000e-02 eta: 9:41:34 time: 0.6050 data_time: 0.0291 memory: 23504 grad_norm: 2.9351 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 1.8327 loss: 1.8327 2022/09/08 11:17:43 - mmengine - INFO - Epoch(train) [4][540/1253] lr: 4.0000e-02 eta: 9:41:39 time: 0.6616 data_time: 0.0307 memory: 23504 grad_norm: 2.9859 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.8589 loss: 1.8589 2022/09/08 11:17:54 - mmengine - INFO - Epoch(train) [4][560/1253] lr: 4.0000e-02 eta: 9:41:16 time: 0.5557 data_time: 0.0489 memory: 23504 grad_norm: 2.9040 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 1.9759 loss: 1.9759 2022/09/08 11:18:05 - mmengine - INFO - Epoch(train) [4][580/1253] lr: 4.0000e-02 eta: 9:40:50 time: 0.5471 data_time: 0.0447 memory: 23504 grad_norm: 2.8943 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.8187 loss: 1.8187 2022/09/08 11:18:16 - mmengine - INFO - Epoch(train) [4][600/1253] lr: 4.0000e-02 eta: 9:40:28 time: 0.5618 data_time: 0.0562 memory: 23504 grad_norm: 2.7915 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8378 loss: 1.8378 2022/09/08 11:18:27 - mmengine - INFO - Epoch(train) [4][620/1253] lr: 4.0000e-02 eta: 9:40:03 time: 0.5482 data_time: 0.0387 memory: 23504 grad_norm: 2.9508 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.9052 loss: 1.9052 2022/09/08 11:18:40 - mmengine - INFO - Epoch(train) [4][640/1253] lr: 4.0000e-02 eta: 9:40:08 time: 0.6602 data_time: 0.1440 memory: 23504 grad_norm: 2.8278 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.9233 loss: 1.9233 2022/09/08 11:18:51 - mmengine - INFO - Epoch(train) [4][660/1253] lr: 4.0000e-02 eta: 9:39:48 time: 0.5656 data_time: 0.0347 memory: 23504 grad_norm: 2.9489 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8986 loss: 1.8986 2022/09/08 11:19:04 - mmengine - INFO - Epoch(train) [4][680/1253] lr: 4.0000e-02 eta: 9:39:40 time: 0.6149 data_time: 0.0747 memory: 23504 grad_norm: 2.8586 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9217 loss: 1.9217 2022/09/08 11:19:15 - mmengine - INFO - Epoch(train) [4][700/1253] lr: 4.0000e-02 eta: 9:39:20 time: 0.5654 data_time: 0.0450 memory: 23504 grad_norm: 3.0629 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0021 loss: 2.0021 2022/09/08 11:19:26 - mmengine - INFO - Epoch(train) [4][720/1253] lr: 4.0000e-02 eta: 9:38:55 time: 0.5464 data_time: 0.0352 memory: 23504 grad_norm: 2.8386 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8442 loss: 1.8442 2022/09/08 11:19:37 - mmengine - INFO - Epoch(train) [4][740/1253] lr: 4.0000e-02 eta: 9:38:38 time: 0.5784 data_time: 0.0444 memory: 23504 grad_norm: 2.9615 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.9604 loss: 1.9604 2022/09/08 11:19:49 - mmengine - INFO - Epoch(train) [4][760/1253] lr: 4.0000e-02 eta: 9:38:24 time: 0.5885 data_time: 0.0478 memory: 23504 grad_norm: 2.8130 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9201 loss: 1.9201 2022/09/08 11:20:00 - mmengine - INFO - Epoch(train) [4][780/1253] lr: 4.0000e-02 eta: 9:38:05 time: 0.5678 data_time: 0.0500 memory: 23504 grad_norm: 2.9049 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.9266 loss: 1.9266 2022/09/08 11:20:12 - mmengine - INFO - Epoch(train) [4][800/1253] lr: 4.0000e-02 eta: 9:37:46 time: 0.5726 data_time: 0.0466 memory: 23504 grad_norm: 2.9193 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 1.9995 loss: 1.9995 2022/09/08 11:20:25 - mmengine - INFO - Epoch(train) [4][820/1253] lr: 4.0000e-02 eta: 9:37:47 time: 0.6471 data_time: 0.0371 memory: 23504 grad_norm: 2.8754 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 2.0434 loss: 2.0434 2022/09/08 11:20:36 - mmengine - INFO - Epoch(train) [4][840/1253] lr: 4.0000e-02 eta: 9:37:23 time: 0.5485 data_time: 0.0465 memory: 23504 grad_norm: 2.8936 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 1.9425 loss: 1.9425 2022/09/08 11:20:47 - mmengine - INFO - Epoch(train) [4][860/1253] lr: 4.0000e-02 eta: 9:37:03 time: 0.5655 data_time: 0.0405 memory: 23504 grad_norm: 2.8290 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 1.8419 loss: 1.8419 2022/09/08 11:20:59 - mmengine - INFO - Epoch(train) [4][880/1253] lr: 4.0000e-02 eta: 9:36:46 time: 0.5766 data_time: 0.0472 memory: 23504 grad_norm: 2.9641 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 1.7951 loss: 1.7951 2022/09/08 11:21:11 - mmengine - INFO - Epoch(train) [4][900/1253] lr: 4.0000e-02 eta: 9:36:45 time: 0.6396 data_time: 0.0464 memory: 23504 grad_norm: 2.9662 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 2.0191 loss: 2.0191 2022/09/08 11:21:23 - mmengine - INFO - Epoch(train) [4][920/1253] lr: 4.0000e-02 eta: 9:36:22 time: 0.5524 data_time: 0.0404 memory: 23504 grad_norm: 2.9007 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.7553 loss: 1.7553 2022/09/08 11:21:34 - mmengine - INFO - Epoch(train) [4][940/1253] lr: 4.0000e-02 eta: 9:36:03 time: 0.5655 data_time: 0.0447 memory: 23504 grad_norm: 2.8305 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.8834 loss: 1.8834 2022/09/08 11:21:45 - mmengine - INFO - Epoch(train) [4][960/1253] lr: 4.0000e-02 eta: 9:35:43 time: 0.5664 data_time: 0.0434 memory: 23504 grad_norm: 2.9354 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 1.8236 loss: 1.8236 2022/09/08 11:21:57 - mmengine - INFO - Epoch(train) [4][980/1253] lr: 4.0000e-02 eta: 9:35:26 time: 0.5724 data_time: 0.0384 memory: 23504 grad_norm: 2.9151 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.8603 loss: 1.8603 2022/09/08 11:22:08 - mmengine - INFO - Epoch(train) [4][1000/1253] lr: 4.0000e-02 eta: 9:35:07 time: 0.5687 data_time: 0.0506 memory: 23504 grad_norm: 2.8288 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.7123 loss: 1.7123 2022/09/08 11:22:19 - mmengine - INFO - Epoch(train) [4][1020/1253] lr: 4.0000e-02 eta: 9:34:48 time: 0.5684 data_time: 0.0393 memory: 23504 grad_norm: 2.8936 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8787 loss: 1.8787 2022/09/08 11:22:31 - mmengine - INFO - Epoch(train) [4][1040/1253] lr: 4.0000e-02 eta: 9:34:35 time: 0.5886 data_time: 0.0448 memory: 23504 grad_norm: 3.0075 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 1.7475 loss: 1.7475 2022/09/08 11:22:43 - mmengine - INFO - Epoch(train) [4][1060/1253] lr: 4.0000e-02 eta: 9:34:19 time: 0.5793 data_time: 0.0433 memory: 23504 grad_norm: 2.9252 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 1.8846 loss: 1.8846 2022/09/08 11:22:54 - mmengine - INFO - Epoch(train) [4][1080/1253] lr: 4.0000e-02 eta: 9:34:02 time: 0.5761 data_time: 0.0477 memory: 23504 grad_norm: 2.9079 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7171 loss: 1.7171 2022/09/08 11:23:06 - mmengine - INFO - Epoch(train) [4][1100/1253] lr: 4.0000e-02 eta: 9:33:47 time: 0.5808 data_time: 0.0423 memory: 23504 grad_norm: 2.8629 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9546 loss: 1.9546 2022/09/08 11:23:17 - mmengine - INFO - Epoch(train) [4][1120/1253] lr: 4.0000e-02 eta: 9:33:29 time: 0.5710 data_time: 0.0457 memory: 23504 grad_norm: 2.9053 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.0010 loss: 2.0010 2022/09/08 11:23:28 - mmengine - INFO - Epoch(train) [4][1140/1253] lr: 4.0000e-02 eta: 9:33:06 time: 0.5507 data_time: 0.0546 memory: 23504 grad_norm: 2.7944 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8141 loss: 1.8141 2022/09/08 11:23:39 - mmengine - INFO - Epoch(train) [4][1160/1253] lr: 4.0000e-02 eta: 9:32:45 time: 0.5572 data_time: 0.0466 memory: 23504 grad_norm: 2.8785 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7984 loss: 1.7984 2022/09/08 11:23:51 - mmengine - INFO - Epoch(train) [4][1180/1253] lr: 4.0000e-02 eta: 9:32:24 time: 0.5550 data_time: 0.0453 memory: 23504 grad_norm: 2.8599 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.8545 loss: 1.8545 2022/09/08 11:24:02 - mmengine - INFO - Epoch(train) [4][1200/1253] lr: 4.0000e-02 eta: 9:32:02 time: 0.5528 data_time: 0.0399 memory: 23504 grad_norm: 2.8963 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.8126 loss: 1.8126 2022/09/08 11:24:13 - mmengine - INFO - Epoch(train) [4][1220/1253] lr: 4.0000e-02 eta: 9:31:44 time: 0.5652 data_time: 0.0521 memory: 23504 grad_norm: 2.7888 top1_acc: 0.7917 top5_acc: 0.7917 loss_cls: 1.8654 loss: 1.8654 2022/09/08 11:24:23 - mmengine - INFO - Epoch(train) [4][1240/1253] lr: 4.0000e-02 eta: 9:31:11 time: 0.5057 data_time: 0.0354 memory: 23504 grad_norm: 2.8470 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.7879 loss: 1.7879 2022/09/08 11:24:23 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 11:24:29 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 11:24:29 - mmengine - INFO - Epoch(train) [4][1253/1253] lr: 4.0000e-02 eta: 9:31:11 time: 0.4337 data_time: 0.0227 memory: 23504 grad_norm: 3.0132 top1_acc: 0.2857 top5_acc: 0.7143 loss_cls: 1.9816 loss: 1.9816 2022/09/08 11:24:50 - mmengine - INFO - Epoch(train) [5][20/1253] lr: 4.0000e-02 eta: 9:31:14 time: 1.0781 data_time: 0.4816 memory: 23504 grad_norm: 2.9298 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.7456 loss: 1.7456 2022/09/08 11:25:02 - mmengine - INFO - Epoch(train) [5][40/1253] lr: 4.0000e-02 eta: 9:31:02 time: 0.5976 data_time: 0.0401 memory: 23504 grad_norm: 2.8581 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.6420 loss: 1.6420 2022/09/08 11:25:14 - mmengine - INFO - Epoch(train) [5][60/1253] lr: 4.0000e-02 eta: 9:30:48 time: 0.5816 data_time: 0.0419 memory: 23504 grad_norm: 2.8636 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.8389 loss: 1.8389 2022/09/08 11:25:25 - mmengine - INFO - Epoch(train) [5][80/1253] lr: 4.0000e-02 eta: 9:30:34 time: 0.5871 data_time: 0.0361 memory: 23504 grad_norm: 2.8934 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 1.7740 loss: 1.7740 2022/09/08 11:25:37 - mmengine - INFO - Epoch(train) [5][100/1253] lr: 4.0000e-02 eta: 9:30:16 time: 0.5661 data_time: 0.0483 memory: 23504 grad_norm: 2.8423 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.7671 loss: 1.7671 2022/09/08 11:25:48 - mmengine - INFO - Epoch(train) [5][120/1253] lr: 4.0000e-02 eta: 9:30:02 time: 0.5869 data_time: 0.0644 memory: 23504 grad_norm: 2.9655 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 1.6660 loss: 1.6660 2022/09/08 11:26:00 - mmengine - INFO - Epoch(train) [5][140/1253] lr: 4.0000e-02 eta: 9:29:49 time: 0.5897 data_time: 0.0415 memory: 23504 grad_norm: 2.9283 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.9694 loss: 1.9694 2022/09/08 11:26:12 - mmengine - INFO - Epoch(train) [5][160/1253] lr: 4.0000e-02 eta: 9:29:32 time: 0.5698 data_time: 0.0353 memory: 23504 grad_norm: 2.9282 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.7343 loss: 1.7343 2022/09/08 11:26:23 - mmengine - INFO - Epoch(train) [5][180/1253] lr: 4.0000e-02 eta: 9:29:16 time: 0.5768 data_time: 0.0452 memory: 23504 grad_norm: 2.8558 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 1.8205 loss: 1.8205 2022/09/08 11:26:35 - mmengine - INFO - Epoch(train) [5][200/1253] lr: 4.0000e-02 eta: 9:28:58 time: 0.5676 data_time: 0.0478 memory: 23504 grad_norm: 2.8344 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6672 loss: 1.6672 2022/09/08 11:26:46 - mmengine - INFO - Epoch(train) [5][220/1253] lr: 4.0000e-02 eta: 9:28:45 time: 0.5890 data_time: 0.0586 memory: 23504 grad_norm: 2.9756 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.7577 loss: 1.7577 2022/09/08 11:26:58 - mmengine - INFO - Epoch(train) [5][240/1253] lr: 4.0000e-02 eta: 9:28:25 time: 0.5595 data_time: 0.0463 memory: 23504 grad_norm: 2.8784 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8989 loss: 1.8989 2022/09/08 11:27:09 - mmengine - INFO - Epoch(train) [5][260/1253] lr: 4.0000e-02 eta: 9:28:14 time: 0.5972 data_time: 0.0435 memory: 23504 grad_norm: 2.8815 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.7558 loss: 1.7558 2022/09/08 11:27:23 - mmengine - INFO - Epoch(train) [5][280/1253] lr: 4.0000e-02 eta: 9:28:24 time: 0.6949 data_time: 0.0475 memory: 23504 grad_norm: 2.8574 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6828 loss: 1.6828 2022/09/08 11:27:34 - mmengine - INFO - Epoch(train) [5][300/1253] lr: 4.0000e-02 eta: 9:28:02 time: 0.5471 data_time: 0.0381 memory: 23504 grad_norm: 2.8643 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.7469 loss: 1.7469 2022/09/08 11:27:46 - mmengine - INFO - Epoch(train) [5][320/1253] lr: 4.0000e-02 eta: 9:27:44 time: 0.5647 data_time: 0.0362 memory: 23504 grad_norm: 2.9129 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9541 loss: 1.9541 2022/09/08 11:27:57 - mmengine - INFO - Epoch(train) [5][340/1253] lr: 4.0000e-02 eta: 9:27:27 time: 0.5715 data_time: 0.0513 memory: 23504 grad_norm: 2.8648 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.8494 loss: 1.8494 2022/09/08 11:28:08 - mmengine - INFO - Epoch(train) [5][360/1253] lr: 4.0000e-02 eta: 9:27:05 time: 0.5465 data_time: 0.0495 memory: 23504 grad_norm: 2.8046 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8264 loss: 1.8264 2022/09/08 11:28:19 - mmengine - INFO - Epoch(train) [5][380/1253] lr: 4.0000e-02 eta: 9:26:47 time: 0.5668 data_time: 0.0429 memory: 23504 grad_norm: 2.9334 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 1.7543 loss: 1.7543 2022/09/08 11:28:32 - mmengine - INFO - Epoch(train) [5][400/1253] lr: 4.0000e-02 eta: 9:26:43 time: 0.6307 data_time: 0.0475 memory: 23504 grad_norm: 2.9537 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.8086 loss: 1.8086 2022/09/08 11:28:43 - mmengine - INFO - Epoch(train) [5][420/1253] lr: 4.0000e-02 eta: 9:26:27 time: 0.5737 data_time: 0.0435 memory: 23504 grad_norm: 2.8646 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.8773 loss: 1.8773 2022/09/08 11:28:55 - mmengine - INFO - Epoch(train) [5][440/1253] lr: 4.0000e-02 eta: 9:26:08 time: 0.5628 data_time: 0.0567 memory: 23504 grad_norm: 2.9020 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8490 loss: 1.8490 2022/09/08 11:29:06 - mmengine - INFO - Epoch(train) [5][460/1253] lr: 4.0000e-02 eta: 9:25:49 time: 0.5572 data_time: 0.0476 memory: 23504 grad_norm: 2.8817 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.7549 loss: 1.7549 2022/09/08 11:29:17 - mmengine - INFO - Epoch(train) [5][480/1253] lr: 4.0000e-02 eta: 9:25:31 time: 0.5656 data_time: 0.0513 memory: 23504 grad_norm: 2.8681 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 1.8138 loss: 1.8138 2022/09/08 11:29:28 - mmengine - INFO - Epoch(train) [5][500/1253] lr: 4.0000e-02 eta: 9:25:14 time: 0.5672 data_time: 0.0465 memory: 23504 grad_norm: 2.8992 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.9007 loss: 1.9007 2022/09/08 11:29:41 - mmengine - INFO - Epoch(train) [5][520/1253] lr: 4.0000e-02 eta: 9:25:05 time: 0.6081 data_time: 0.0484 memory: 23504 grad_norm: 2.8920 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 1.8013 loss: 1.8013 2022/09/08 11:29:53 - mmengine - INFO - Epoch(train) [5][540/1253] lr: 4.0000e-02 eta: 9:24:56 time: 0.6101 data_time: 0.0444 memory: 23504 grad_norm: 2.8783 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7866 loss: 1.7866 2022/09/08 11:30:05 - mmengine - INFO - Epoch(train) [5][560/1253] lr: 4.0000e-02 eta: 9:24:43 time: 0.5853 data_time: 0.0398 memory: 23504 grad_norm: 2.8536 top1_acc: 0.6250 top5_acc: 0.7083 loss_cls: 1.6227 loss: 1.6227 2022/09/08 11:30:16 - mmengine - INFO - Epoch(train) [5][580/1253] lr: 4.0000e-02 eta: 9:24:26 time: 0.5676 data_time: 0.0435 memory: 23504 grad_norm: 2.9023 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.9119 loss: 1.9119 2022/09/08 11:30:27 - mmengine - INFO - Epoch(train) [5][600/1253] lr: 4.0000e-02 eta: 9:24:09 time: 0.5709 data_time: 0.0457 memory: 23504 grad_norm: 2.8804 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8827 loss: 1.8827 2022/09/08 11:30:39 - mmengine - INFO - Epoch(train) [5][620/1253] lr: 4.0000e-02 eta: 9:23:53 time: 0.5712 data_time: 0.0518 memory: 23504 grad_norm: 2.8783 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 1.7510 loss: 1.7510 2022/09/08 11:30:51 - mmengine - INFO - Epoch(train) [5][640/1253] lr: 4.0000e-02 eta: 9:23:41 time: 0.5910 data_time: 0.0428 memory: 23504 grad_norm: 2.8841 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7703 loss: 1.7703 2022/09/08 11:31:02 - mmengine - INFO - Epoch(train) [5][660/1253] lr: 4.0000e-02 eta: 9:23:26 time: 0.5802 data_time: 0.0390 memory: 23504 grad_norm: 2.8194 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 1.7902 loss: 1.7902 2022/09/08 11:31:14 - mmengine - INFO - Epoch(train) [5][680/1253] lr: 4.0000e-02 eta: 9:23:16 time: 0.6036 data_time: 0.0674 memory: 23504 grad_norm: 2.8757 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.8050 loss: 1.8050 2022/09/08 11:31:25 - mmengine - INFO - Epoch(train) [5][700/1253] lr: 4.0000e-02 eta: 9:22:57 time: 0.5546 data_time: 0.0381 memory: 23504 grad_norm: 2.8708 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.8462 loss: 1.8462 2022/09/08 11:31:36 - mmengine - INFO - Epoch(train) [5][720/1253] lr: 4.0000e-02 eta: 9:22:36 time: 0.5477 data_time: 0.0385 memory: 23504 grad_norm: 2.8737 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.9612 loss: 1.9612 2022/09/08 11:31:47 - mmengine - INFO - Epoch(train) [5][740/1253] lr: 4.0000e-02 eta: 9:22:15 time: 0.5471 data_time: 0.0389 memory: 23504 grad_norm: 2.9103 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.8128 loss: 1.8128 2022/09/08 11:31:59 - mmengine - INFO - Epoch(train) [5][760/1253] lr: 4.0000e-02 eta: 9:21:58 time: 0.5699 data_time: 0.0467 memory: 23504 grad_norm: 2.8837 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.8504 loss: 1.8504 2022/09/08 11:32:11 - mmengine - INFO - Epoch(train) [5][780/1253] lr: 4.0000e-02 eta: 9:21:47 time: 0.5936 data_time: 0.0673 memory: 23504 grad_norm: 2.8037 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7732 loss: 1.7732 2022/09/08 11:32:22 - mmengine - INFO - Epoch(train) [5][800/1253] lr: 4.0000e-02 eta: 9:21:34 time: 0.5896 data_time: 0.0447 memory: 23504 grad_norm: 2.8862 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.7762 loss: 1.7762 2022/09/08 11:32:34 - mmengine - INFO - Epoch(train) [5][820/1253] lr: 4.0000e-02 eta: 9:21:18 time: 0.5714 data_time: 0.0419 memory: 23504 grad_norm: 2.8623 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7922 loss: 1.7922 2022/09/08 11:32:45 - mmengine - INFO - Epoch(train) [5][840/1253] lr: 4.0000e-02 eta: 9:21:04 time: 0.5817 data_time: 0.0473 memory: 23504 grad_norm: 2.9016 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.7131 loss: 1.7131 2022/09/08 11:32:57 - mmengine - INFO - Epoch(train) [5][860/1253] lr: 4.0000e-02 eta: 9:20:50 time: 0.5806 data_time: 0.0457 memory: 23504 grad_norm: 2.8923 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.8835 loss: 1.8835 2022/09/08 11:33:08 - mmengine - INFO - Epoch(train) [5][880/1253] lr: 4.0000e-02 eta: 9:20:32 time: 0.5611 data_time: 0.0405 memory: 23504 grad_norm: 2.9402 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9230 loss: 1.9230 2022/09/08 11:33:19 - mmengine - INFO - Epoch(train) [5][900/1253] lr: 4.0000e-02 eta: 9:20:14 time: 0.5609 data_time: 0.0448 memory: 23504 grad_norm: 2.8238 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.8233 loss: 1.8233 2022/09/08 11:33:31 - mmengine - INFO - Epoch(train) [5][920/1253] lr: 4.0000e-02 eta: 9:20:00 time: 0.5798 data_time: 0.0521 memory: 23504 grad_norm: 2.9359 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 1.8977 loss: 1.8977 2022/09/08 11:33:43 - mmengine - INFO - Epoch(train) [5][940/1253] lr: 4.0000e-02 eta: 9:19:46 time: 0.5797 data_time: 0.0351 memory: 23504 grad_norm: 2.9254 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.9256 loss: 1.9256 2022/09/08 11:33:54 - mmengine - INFO - Epoch(train) [5][960/1253] lr: 4.0000e-02 eta: 9:19:28 time: 0.5641 data_time: 0.0405 memory: 23504 grad_norm: 2.8532 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.9930 loss: 1.9930 2022/09/08 11:34:05 - mmengine - INFO - Epoch(train) [5][980/1253] lr: 4.0000e-02 eta: 9:19:09 time: 0.5552 data_time: 0.0396 memory: 23504 grad_norm: 2.9047 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.7314 loss: 1.7314 2022/09/08 11:34:10 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 11:34:17 - mmengine - INFO - Epoch(train) [5][1000/1253] lr: 4.0000e-02 eta: 9:19:03 time: 0.6185 data_time: 0.0744 memory: 23504 grad_norm: 2.7900 top1_acc: 0.6667 top5_acc: 0.7500 loss_cls: 1.8041 loss: 1.8041 2022/09/08 11:34:29 - mmengine - INFO - Epoch(train) [5][1020/1253] lr: 4.0000e-02 eta: 9:18:46 time: 0.5682 data_time: 0.0337 memory: 23504 grad_norm: 2.8479 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7153 loss: 1.7153 2022/09/08 11:34:40 - mmengine - INFO - Epoch(train) [5][1040/1253] lr: 4.0000e-02 eta: 9:18:30 time: 0.5672 data_time: 0.0374 memory: 23504 grad_norm: 2.8952 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 2.0124 loss: 2.0124 2022/09/08 11:34:51 - mmengine - INFO - Epoch(train) [5][1060/1253] lr: 4.0000e-02 eta: 9:18:13 time: 0.5642 data_time: 0.0426 memory: 23504 grad_norm: 2.8826 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.8410 loss: 1.8410 2022/09/08 11:35:03 - mmengine - INFO - Epoch(train) [5][1080/1253] lr: 4.0000e-02 eta: 9:18:01 time: 0.5920 data_time: 0.0494 memory: 23504 grad_norm: 2.8748 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.7215 loss: 1.7215 2022/09/08 11:35:15 - mmengine - INFO - Epoch(train) [5][1100/1253] lr: 4.0000e-02 eta: 9:17:51 time: 0.6015 data_time: 0.0569 memory: 23504 grad_norm: 2.8713 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.8875 loss: 1.8875 2022/09/08 11:35:27 - mmengine - INFO - Epoch(train) [5][1120/1253] lr: 4.0000e-02 eta: 9:17:35 time: 0.5690 data_time: 0.0486 memory: 23504 grad_norm: 2.8577 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8623 loss: 1.8623 2022/09/08 11:35:38 - mmengine - INFO - Epoch(train) [5][1140/1253] lr: 4.0000e-02 eta: 9:17:17 time: 0.5607 data_time: 0.0390 memory: 23504 grad_norm: 2.8411 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.6969 loss: 1.6969 2022/09/08 11:35:49 - mmengine - INFO - Epoch(train) [5][1160/1253] lr: 4.0000e-02 eta: 9:17:00 time: 0.5640 data_time: 0.0477 memory: 23504 grad_norm: 2.8636 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.8265 loss: 1.8265 2022/09/08 11:36:00 - mmengine - INFO - Epoch(train) [5][1180/1253] lr: 4.0000e-02 eta: 9:16:44 time: 0.5684 data_time: 0.0392 memory: 23504 grad_norm: 2.8696 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.9852 loss: 1.9852 2022/09/08 11:36:11 - mmengine - INFO - Epoch(train) [5][1200/1253] lr: 4.0000e-02 eta: 9:16:25 time: 0.5491 data_time: 0.0469 memory: 23504 grad_norm: 2.8438 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.7430 loss: 1.7430 2022/09/08 11:36:23 - mmengine - INFO - Epoch(train) [5][1220/1253] lr: 4.0000e-02 eta: 9:16:10 time: 0.5781 data_time: 0.0685 memory: 23504 grad_norm: 2.8705 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9002 loss: 1.9002 2022/09/08 11:36:33 - mmengine - INFO - Epoch(train) [5][1240/1253] lr: 4.0000e-02 eta: 9:15:41 time: 0.4941 data_time: 0.0335 memory: 23504 grad_norm: 2.8722 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.7336 loss: 1.7336 2022/09/08 11:36:38 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 11:36:38 - mmengine - INFO - Epoch(train) [5][1253/1253] lr: 4.0000e-02 eta: 9:15:41 time: 0.4321 data_time: 0.0174 memory: 23504 grad_norm: 3.0009 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.8474 loss: 1.8474 2022/09/08 11:38:15 - mmengine - INFO - Epoch(val) [5][20/104] eta: 0:06:45 time: 4.8312 data_time: 4.6479 memory: 2699 2022/09/08 11:38:23 - mmengine - INFO - Epoch(val) [5][40/104] eta: 0:00:25 time: 0.4041 data_time: 0.2617 memory: 2699 2022/09/08 11:38:34 - mmengine - INFO - Epoch(val) [5][60/104] eta: 0:00:22 time: 0.5164 data_time: 0.3708 memory: 2699 2022/09/08 11:38:43 - mmengine - INFO - Epoch(val) [5][80/104] eta: 0:00:11 time: 0.4941 data_time: 0.3511 memory: 2699 2022/09/08 11:38:52 - mmengine - INFO - Epoch(val) [5][100/104] eta: 0:00:01 time: 0.4223 data_time: 0.2962 memory: 2699 2022/09/08 11:38:54 - mmengine - INFO - Epoch(val) [5][104/104] acc/top1: 0.5683 acc/top5: 0.8048 acc/mean1: 0.5681 2022/09/08 11:38:55 - mmengine - INFO - The best checkpoint with 0.5683 acc/top1 at 5 epoch is saved to best_acc/top1_epoch_5.pth. 2022/09/08 11:39:17 - mmengine - INFO - Epoch(train) [6][20/1253] lr: 4.0000e-02 eta: 9:15:43 time: 1.0957 data_time: 0.4003 memory: 23504 grad_norm: 2.8838 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.8211 loss: 1.8211 2022/09/08 11:39:28 - mmengine - INFO - Epoch(train) [6][40/1253] lr: 4.0000e-02 eta: 9:15:25 time: 0.5569 data_time: 0.0575 memory: 23504 grad_norm: 2.8195 top1_acc: 0.5417 top5_acc: 0.6667 loss_cls: 1.7752 loss: 1.7752 2022/09/08 11:39:39 - mmengine - INFO - Epoch(train) [6][60/1253] lr: 4.0000e-02 eta: 9:15:06 time: 0.5533 data_time: 0.0354 memory: 23504 grad_norm: 2.8907 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.7413 loss: 1.7413 2022/09/08 11:39:51 - mmengine - INFO - Epoch(train) [6][80/1253] lr: 4.0000e-02 eta: 9:14:53 time: 0.5831 data_time: 0.0379 memory: 23504 grad_norm: 2.8759 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 1.8208 loss: 1.8208 2022/09/08 11:40:03 - mmengine - INFO - Epoch(train) [6][100/1253] lr: 4.0000e-02 eta: 9:14:43 time: 0.5993 data_time: 0.0517 memory: 23504 grad_norm: 2.9705 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.6834 loss: 1.6834 2022/09/08 11:40:15 - mmengine - INFO - Epoch(train) [6][120/1253] lr: 4.0000e-02 eta: 9:14:31 time: 0.5952 data_time: 0.0557 memory: 23504 grad_norm: 2.8118 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.6855 loss: 1.6855 2022/09/08 11:40:26 - mmengine - INFO - Epoch(train) [6][140/1253] lr: 4.0000e-02 eta: 9:14:15 time: 0.5663 data_time: 0.0354 memory: 23504 grad_norm: 2.8800 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.6195 loss: 1.6195 2022/09/08 11:40:38 - mmengine - INFO - Epoch(train) [6][160/1253] lr: 4.0000e-02 eta: 9:14:02 time: 0.5829 data_time: 0.0335 memory: 23504 grad_norm: 2.8208 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7714 loss: 1.7714 2022/09/08 11:40:49 - mmengine - INFO - Epoch(train) [6][180/1253] lr: 4.0000e-02 eta: 9:13:46 time: 0.5698 data_time: 0.0526 memory: 23504 grad_norm: 2.9168 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6817 loss: 1.6817 2022/09/08 11:41:00 - mmengine - INFO - Epoch(train) [6][200/1253] lr: 4.0000e-02 eta: 9:13:27 time: 0.5496 data_time: 0.0445 memory: 23504 grad_norm: 2.7569 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.6936 loss: 1.6936 2022/09/08 11:41:11 - mmengine - INFO - Epoch(train) [6][220/1253] lr: 4.0000e-02 eta: 9:13:10 time: 0.5614 data_time: 0.0438 memory: 23504 grad_norm: 2.8461 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.7654 loss: 1.7654 2022/09/08 11:41:22 - mmengine - INFO - Epoch(train) [6][240/1253] lr: 4.0000e-02 eta: 9:12:53 time: 0.5609 data_time: 0.0415 memory: 23504 grad_norm: 2.8582 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.7281 loss: 1.7281 2022/09/08 11:41:35 - mmengine - INFO - Epoch(train) [6][260/1253] lr: 4.0000e-02 eta: 9:12:45 time: 0.6118 data_time: 0.0762 memory: 23504 grad_norm: 2.8394 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.5514 loss: 1.5514 2022/09/08 11:41:47 - mmengine - INFO - Epoch(train) [6][280/1253] lr: 4.0000e-02 eta: 9:12:37 time: 0.6113 data_time: 0.0628 memory: 23504 grad_norm: 2.9285 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.7309 loss: 1.7309 2022/09/08 11:41:58 - mmengine - INFO - Epoch(train) [6][300/1253] lr: 4.0000e-02 eta: 9:12:20 time: 0.5617 data_time: 0.0358 memory: 23504 grad_norm: 2.7894 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.6679 loss: 1.6679 2022/09/08 11:42:09 - mmengine - INFO - Epoch(train) [6][320/1253] lr: 4.0000e-02 eta: 9:12:01 time: 0.5498 data_time: 0.0389 memory: 23504 grad_norm: 2.8619 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.7871 loss: 1.7871 2022/09/08 11:42:21 - mmengine - INFO - Epoch(train) [6][340/1253] lr: 4.0000e-02 eta: 9:11:46 time: 0.5714 data_time: 0.0484 memory: 23504 grad_norm: 2.9398 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6989 loss: 1.6989 2022/09/08 11:42:32 - mmengine - INFO - Epoch(train) [6][360/1253] lr: 4.0000e-02 eta: 9:11:30 time: 0.5629 data_time: 0.0474 memory: 23504 grad_norm: 2.8326 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.6347 loss: 1.6347 2022/09/08 11:42:44 - mmengine - INFO - Epoch(train) [6][380/1253] lr: 4.0000e-02 eta: 9:11:18 time: 0.5924 data_time: 0.0386 memory: 23504 grad_norm: 2.8332 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.8399 loss: 1.8399 2022/09/08 11:42:56 - mmengine - INFO - Epoch(train) [6][400/1253] lr: 4.0000e-02 eta: 9:11:09 time: 0.6049 data_time: 0.0354 memory: 23504 grad_norm: 2.8246 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.6860 loss: 1.6860 2022/09/08 11:43:07 - mmengine - INFO - Epoch(train) [6][420/1253] lr: 4.0000e-02 eta: 9:10:56 time: 0.5860 data_time: 0.0485 memory: 23504 grad_norm: 2.8782 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.7017 loss: 1.7017 2022/09/08 11:43:19 - mmengine - INFO - Epoch(train) [6][440/1253] lr: 4.0000e-02 eta: 9:10:42 time: 0.5791 data_time: 0.0414 memory: 23504 grad_norm: 2.8883 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7220 loss: 1.7220 2022/09/08 11:43:31 - mmengine - INFO - Epoch(train) [6][460/1253] lr: 4.0000e-02 eta: 9:10:33 time: 0.6042 data_time: 0.0386 memory: 23504 grad_norm: 2.8723 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8258 loss: 1.8258 2022/09/08 11:43:43 - mmengine - INFO - Epoch(train) [6][480/1253] lr: 4.0000e-02 eta: 9:10:19 time: 0.5816 data_time: 0.0298 memory: 23504 grad_norm: 2.8725 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8307 loss: 1.8307 2022/09/08 11:43:54 - mmengine - INFO - Epoch(train) [6][500/1253] lr: 4.0000e-02 eta: 9:10:01 time: 0.5527 data_time: 0.0473 memory: 23504 grad_norm: 2.7885 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.7742 loss: 1.7742 2022/09/08 11:44:05 - mmengine - INFO - Epoch(train) [6][520/1253] lr: 4.0000e-02 eta: 9:09:46 time: 0.5688 data_time: 0.0517 memory: 23504 grad_norm: 2.8922 top1_acc: 0.4167 top5_acc: 0.8333 loss_cls: 1.7592 loss: 1.7592 2022/09/08 11:44:17 - mmengine - INFO - Epoch(train) [6][540/1253] lr: 4.0000e-02 eta: 9:09:32 time: 0.5763 data_time: 0.0461 memory: 23504 grad_norm: 2.9317 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.9487 loss: 1.9487 2022/09/08 11:44:28 - mmengine - INFO - Epoch(train) [6][560/1253] lr: 4.0000e-02 eta: 9:09:17 time: 0.5711 data_time: 0.0430 memory: 23504 grad_norm: 2.8568 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6812 loss: 1.6812 2022/09/08 11:44:40 - mmengine - INFO - Epoch(train) [6][580/1253] lr: 4.0000e-02 eta: 9:09:05 time: 0.5906 data_time: 0.0483 memory: 23504 grad_norm: 2.8779 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 1.7281 loss: 1.7281 2022/09/08 11:44:52 - mmengine - INFO - Epoch(train) [6][600/1253] lr: 4.0000e-02 eta: 9:08:52 time: 0.5842 data_time: 0.0527 memory: 23504 grad_norm: 2.7703 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7962 loss: 1.7962 2022/09/08 11:45:03 - mmengine - INFO - Epoch(train) [6][620/1253] lr: 4.0000e-02 eta: 9:08:36 time: 0.5640 data_time: 0.0415 memory: 23504 grad_norm: 2.8052 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 1.8153 loss: 1.8153 2022/09/08 11:45:15 - mmengine - INFO - Epoch(train) [6][640/1253] lr: 4.0000e-02 eta: 9:08:27 time: 0.6052 data_time: 0.0391 memory: 23504 grad_norm: 2.9382 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.6521 loss: 1.6521 2022/09/08 11:45:26 - mmengine - INFO - Epoch(train) [6][660/1253] lr: 4.0000e-02 eta: 9:08:11 time: 0.5631 data_time: 0.0359 memory: 23504 grad_norm: 2.9488 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.7548 loss: 1.7548 2022/09/08 11:45:38 - mmengine - INFO - Epoch(train) [6][680/1253] lr: 4.0000e-02 eta: 9:08:01 time: 0.6048 data_time: 0.0710 memory: 23504 grad_norm: 2.8591 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 1.8883 loss: 1.8883 2022/09/08 11:45:51 - mmengine - INFO - Epoch(train) [6][700/1253] lr: 4.0000e-02 eta: 9:07:56 time: 0.6342 data_time: 0.0369 memory: 23504 grad_norm: 2.9193 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.8017 loss: 1.8017 2022/09/08 11:46:03 - mmengine - INFO - Epoch(train) [6][720/1253] lr: 4.0000e-02 eta: 9:07:41 time: 0.5710 data_time: 0.0298 memory: 23504 grad_norm: 2.8213 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.8232 loss: 1.8232 2022/09/08 11:46:11 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 11:46:14 - mmengine - INFO - Epoch(train) [6][740/1253] lr: 4.0000e-02 eta: 9:07:24 time: 0.5532 data_time: 0.0467 memory: 23504 grad_norm: 2.8117 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.7680 loss: 1.7680 2022/09/08 11:46:25 - mmengine - INFO - Epoch(train) [6][760/1253] lr: 4.0000e-02 eta: 9:07:06 time: 0.5554 data_time: 0.0493 memory: 23504 grad_norm: 2.8716 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9302 loss: 1.9302 2022/09/08 11:46:36 - mmengine - INFO - Epoch(train) [6][780/1253] lr: 4.0000e-02 eta: 9:06:49 time: 0.5560 data_time: 0.0388 memory: 23504 grad_norm: 2.8706 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.6874 loss: 1.6874 2022/09/08 11:46:48 - mmengine - INFO - Epoch(train) [6][800/1253] lr: 4.0000e-02 eta: 9:06:37 time: 0.5856 data_time: 0.0503 memory: 23504 grad_norm: 2.8822 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 1.6667 loss: 1.6667 2022/09/08 11:46:59 - mmengine - INFO - Epoch(train) [6][820/1253] lr: 4.0000e-02 eta: 9:06:20 time: 0.5611 data_time: 0.0496 memory: 23504 grad_norm: 2.8683 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.7591 loss: 1.7591 2022/09/08 11:47:11 - mmengine - INFO - Epoch(train) [6][840/1253] lr: 4.0000e-02 eta: 9:06:09 time: 0.5905 data_time: 0.0459 memory: 23504 grad_norm: 2.7496 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.8905 loss: 1.8905 2022/09/08 11:47:22 - mmengine - INFO - Epoch(train) [6][860/1253] lr: 4.0000e-02 eta: 9:05:54 time: 0.5718 data_time: 0.0378 memory: 23504 grad_norm: 2.8752 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.9785 loss: 1.9785 2022/09/08 11:47:33 - mmengine - INFO - Epoch(train) [6][880/1253] lr: 4.0000e-02 eta: 9:05:38 time: 0.5606 data_time: 0.0399 memory: 23504 grad_norm: 2.8012 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.8145 loss: 1.8145 2022/09/08 11:47:45 - mmengine - INFO - Epoch(train) [6][900/1253] lr: 4.0000e-02 eta: 9:05:23 time: 0.5694 data_time: 0.0522 memory: 23504 grad_norm: 2.8518 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 1.9026 loss: 1.9026 2022/09/08 11:47:56 - mmengine - INFO - Epoch(train) [6][920/1253] lr: 4.0000e-02 eta: 9:05:11 time: 0.5878 data_time: 0.0472 memory: 23504 grad_norm: 2.8366 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.7661 loss: 1.7661 2022/09/08 11:48:08 - mmengine - INFO - Epoch(train) [6][940/1253] lr: 4.0000e-02 eta: 9:04:57 time: 0.5783 data_time: 0.0432 memory: 23504 grad_norm: 2.8744 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.7433 loss: 1.7433 2022/09/08 11:48:19 - mmengine - INFO - Epoch(train) [6][960/1253] lr: 4.0000e-02 eta: 9:04:42 time: 0.5679 data_time: 0.0380 memory: 23504 grad_norm: 2.8904 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.8138 loss: 1.8138 2022/09/08 11:48:30 - mmengine - INFO - Epoch(train) [6][980/1253] lr: 4.0000e-02 eta: 9:04:25 time: 0.5568 data_time: 0.0442 memory: 23504 grad_norm: 2.8069 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.7918 loss: 1.7918 2022/09/08 11:48:43 - mmengine - INFO - Epoch(train) [6][1000/1253] lr: 4.0000e-02 eta: 9:04:16 time: 0.6053 data_time: 0.0554 memory: 23504 grad_norm: 2.8765 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9046 loss: 1.9046 2022/09/08 11:48:54 - mmengine - INFO - Epoch(train) [6][1020/1253] lr: 4.0000e-02 eta: 9:04:01 time: 0.5713 data_time: 0.0489 memory: 23504 grad_norm: 2.8039 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8739 loss: 1.8739 2022/09/08 11:49:06 - mmengine - INFO - Epoch(train) [6][1040/1253] lr: 4.0000e-02 eta: 9:03:43 time: 0.5485 data_time: 0.0457 memory: 23504 grad_norm: 2.8161 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.8812 loss: 1.8812 2022/09/08 11:49:17 - mmengine - INFO - Epoch(train) [6][1060/1253] lr: 4.0000e-02 eta: 9:03:32 time: 0.5967 data_time: 0.0906 memory: 23504 grad_norm: 2.8482 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.7635 loss: 1.7635 2022/09/08 11:49:28 - mmengine - INFO - Epoch(train) [6][1080/1253] lr: 4.0000e-02 eta: 9:03:17 time: 0.5658 data_time: 0.0456 memory: 23504 grad_norm: 2.8964 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.9175 loss: 1.9175 2022/09/08 11:49:39 - mmengine - INFO - Epoch(train) [6][1100/1253] lr: 4.0000e-02 eta: 9:03:01 time: 0.5611 data_time: 0.0547 memory: 23504 grad_norm: 2.9034 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.8231 loss: 1.8231 2022/09/08 11:49:51 - mmengine - INFO - Epoch(train) [6][1120/1253] lr: 4.0000e-02 eta: 9:02:48 time: 0.5812 data_time: 0.0440 memory: 23504 grad_norm: 2.8756 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.7727 loss: 1.7727 2022/09/08 11:50:02 - mmengine - INFO - Epoch(train) [6][1140/1253] lr: 4.0000e-02 eta: 9:02:33 time: 0.5652 data_time: 0.0596 memory: 23504 grad_norm: 2.8312 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7644 loss: 1.7644 2022/09/08 11:50:14 - mmengine - INFO - Epoch(train) [6][1160/1253] lr: 4.0000e-02 eta: 9:02:19 time: 0.5744 data_time: 0.0508 memory: 23504 grad_norm: 2.7842 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8744 loss: 1.8744 2022/09/08 11:50:26 - mmengine - INFO - Epoch(train) [6][1180/1253] lr: 4.0000e-02 eta: 9:02:09 time: 0.6005 data_time: 0.0403 memory: 23504 grad_norm: 2.8128 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.9028 loss: 1.9028 2022/09/08 11:50:37 - mmengine - INFO - Epoch(train) [6][1200/1253] lr: 4.0000e-02 eta: 9:01:52 time: 0.5573 data_time: 0.0514 memory: 23504 grad_norm: 2.8192 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9885 loss: 1.9885 2022/09/08 11:50:48 - mmengine - INFO - Epoch(train) [6][1220/1253] lr: 4.0000e-02 eta: 9:01:37 time: 0.5685 data_time: 0.0423 memory: 23504 grad_norm: 2.8773 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 1.9097 loss: 1.9097 2022/09/08 11:50:58 - mmengine - INFO - Epoch(train) [6][1240/1253] lr: 4.0000e-02 eta: 9:01:11 time: 0.4934 data_time: 0.0337 memory: 23504 grad_norm: 2.8214 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.7461 loss: 1.7461 2022/09/08 11:51:04 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 11:51:04 - mmengine - INFO - Epoch(train) [6][1253/1253] lr: 4.0000e-02 eta: 9:01:11 time: 0.4276 data_time: 0.0162 memory: 23504 grad_norm: 2.8529 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.6157 loss: 1.6157 2022/09/08 11:51:25 - mmengine - INFO - Epoch(train) [7][20/1253] lr: 4.0000e-02 eta: 9:01:03 time: 1.0508 data_time: 0.4176 memory: 23504 grad_norm: 2.9123 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.6840 loss: 1.6840 2022/09/08 11:51:37 - mmengine - INFO - Epoch(train) [7][40/1253] lr: 4.0000e-02 eta: 9:00:54 time: 0.6053 data_time: 0.0554 memory: 23504 grad_norm: 2.8414 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 1.8054 loss: 1.8054 2022/09/08 11:51:50 - mmengine - INFO - Epoch(train) [7][60/1253] lr: 4.0000e-02 eta: 9:00:50 time: 0.6414 data_time: 0.0838 memory: 23504 grad_norm: 2.7931 top1_acc: 0.4583 top5_acc: 0.9583 loss_cls: 1.6860 loss: 1.6860 2022/09/08 11:52:01 - mmengine - INFO - Epoch(train) [7][80/1253] lr: 4.0000e-02 eta: 9:00:34 time: 0.5630 data_time: 0.0397 memory: 23504 grad_norm: 2.8051 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.7241 loss: 1.7241 2022/09/08 11:52:13 - mmengine - INFO - Epoch(train) [7][100/1253] lr: 4.0000e-02 eta: 9:00:21 time: 0.5819 data_time: 0.0499 memory: 23504 grad_norm: 2.9213 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.8365 loss: 1.8365 2022/09/08 11:52:24 - mmengine - INFO - Epoch(train) [7][120/1253] lr: 4.0000e-02 eta: 9:00:04 time: 0.5486 data_time: 0.0411 memory: 23504 grad_norm: 2.8146 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.8481 loss: 1.8481 2022/09/08 11:52:36 - mmengine - INFO - Epoch(train) [7][140/1253] lr: 4.0000e-02 eta: 8:59:56 time: 0.6198 data_time: 0.0437 memory: 23504 grad_norm: 2.8808 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.6516 loss: 1.6516 2022/09/08 11:52:47 - mmengine - INFO - Epoch(train) [7][160/1253] lr: 4.0000e-02 eta: 8:59:39 time: 0.5462 data_time: 0.0450 memory: 23504 grad_norm: 2.7925 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7682 loss: 1.7682 2022/09/08 11:52:59 - mmengine - INFO - Epoch(train) [7][180/1253] lr: 4.0000e-02 eta: 8:59:31 time: 0.6152 data_time: 0.0393 memory: 23504 grad_norm: 2.8912 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.7949 loss: 1.7949 2022/09/08 11:53:11 - mmengine - INFO - Epoch(train) [7][200/1253] lr: 4.0000e-02 eta: 8:59:19 time: 0.5882 data_time: 0.0440 memory: 23504 grad_norm: 2.9913 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.6313 loss: 1.6313 2022/09/08 11:53:23 - mmengine - INFO - Epoch(train) [7][220/1253] lr: 4.0000e-02 eta: 8:59:07 time: 0.5882 data_time: 0.0491 memory: 23504 grad_norm: 2.9551 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7230 loss: 1.7230 2022/09/08 11:53:34 - mmengine - INFO - Epoch(train) [7][240/1253] lr: 4.0000e-02 eta: 8:58:52 time: 0.5683 data_time: 0.0435 memory: 23504 grad_norm: 2.8553 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.6129 loss: 1.6129 2022/09/08 11:53:46 - mmengine - INFO - Epoch(train) [7][260/1253] lr: 4.0000e-02 eta: 8:58:41 time: 0.5975 data_time: 0.0473 memory: 23504 grad_norm: 2.7869 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.7629 loss: 1.7629 2022/09/08 11:53:58 - mmengine - INFO - Epoch(train) [7][280/1253] lr: 4.0000e-02 eta: 8:58:29 time: 0.5842 data_time: 0.0460 memory: 23504 grad_norm: 2.8608 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6394 loss: 1.6394 2022/09/08 11:54:10 - mmengine - INFO - Epoch(train) [7][300/1253] lr: 4.0000e-02 eta: 8:58:18 time: 0.5947 data_time: 0.0561 memory: 23504 grad_norm: 2.8255 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5696 loss: 1.5696 2022/09/08 11:54:21 - mmengine - INFO - Epoch(train) [7][320/1253] lr: 4.0000e-02 eta: 8:58:01 time: 0.5511 data_time: 0.0382 memory: 23504 grad_norm: 2.9251 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.6408 loss: 1.6408 2022/09/08 11:54:32 - mmengine - INFO - Epoch(train) [7][340/1253] lr: 4.0000e-02 eta: 8:57:45 time: 0.5611 data_time: 0.0540 memory: 23504 grad_norm: 2.8871 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.7759 loss: 1.7759 2022/09/08 11:54:43 - mmengine - INFO - Epoch(train) [7][360/1253] lr: 4.0000e-02 eta: 8:57:30 time: 0.5643 data_time: 0.0493 memory: 23504 grad_norm: 2.8978 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.7340 loss: 1.7340 2022/09/08 11:54:55 - mmengine - INFO - Epoch(train) [7][380/1253] lr: 4.0000e-02 eta: 8:57:18 time: 0.5844 data_time: 0.0386 memory: 23504 grad_norm: 2.7910 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.7029 loss: 1.7029 2022/09/08 11:55:07 - mmengine - INFO - Epoch(train) [7][400/1253] lr: 4.0000e-02 eta: 8:57:08 time: 0.6051 data_time: 0.0387 memory: 23504 grad_norm: 2.8573 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.7270 loss: 1.7270 2022/09/08 11:55:19 - mmengine - INFO - Epoch(train) [7][420/1253] lr: 4.0000e-02 eta: 8:56:55 time: 0.5822 data_time: 0.0526 memory: 23504 grad_norm: 2.9284 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.7907 loss: 1.7907 2022/09/08 11:55:30 - mmengine - INFO - Epoch(train) [7][440/1253] lr: 4.0000e-02 eta: 8:56:44 time: 0.5934 data_time: 0.0387 memory: 23504 grad_norm: 2.8553 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.7989 loss: 1.7989 2022/09/08 11:55:42 - mmengine - INFO - Epoch(train) [7][460/1253] lr: 4.0000e-02 eta: 8:56:31 time: 0.5799 data_time: 0.0445 memory: 23504 grad_norm: 2.9343 top1_acc: 0.6250 top5_acc: 0.7083 loss_cls: 1.8591 loss: 1.8591 2022/09/08 11:55:54 - mmengine - INFO - Epoch(train) [7][480/1253] lr: 4.0000e-02 eta: 8:56:18 time: 0.5785 data_time: 0.0388 memory: 23504 grad_norm: 2.8666 top1_acc: 0.7083 top5_acc: 1.0000 loss_cls: 1.7204 loss: 1.7204 2022/09/08 11:55:55 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 11:56:05 - mmengine - INFO - Epoch(train) [7][500/1253] lr: 4.0000e-02 eta: 8:56:07 time: 0.5913 data_time: 0.0472 memory: 23504 grad_norm: 2.8979 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5944 loss: 1.5944 2022/09/08 11:56:17 - mmengine - INFO - Epoch(train) [7][520/1253] lr: 4.0000e-02 eta: 8:55:55 time: 0.5914 data_time: 0.0531 memory: 23504 grad_norm: 2.8663 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.8117 loss: 1.8117 2022/09/08 11:56:29 - mmengine - INFO - Epoch(train) [7][540/1253] lr: 4.0000e-02 eta: 8:55:42 time: 0.5808 data_time: 0.0421 memory: 23504 grad_norm: 2.8220 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6499 loss: 1.6499 2022/09/08 11:56:40 - mmengine - INFO - Epoch(train) [7][560/1253] lr: 4.0000e-02 eta: 8:55:26 time: 0.5530 data_time: 0.0339 memory: 23504 grad_norm: 2.9372 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7632 loss: 1.7632 2022/09/08 11:56:51 - mmengine - INFO - Epoch(train) [7][580/1253] lr: 4.0000e-02 eta: 8:55:11 time: 0.5647 data_time: 0.0516 memory: 23504 grad_norm: 2.8884 top1_acc: 0.6250 top5_acc: 0.6667 loss_cls: 1.7819 loss: 1.7819 2022/09/08 11:57:03 - mmengine - INFO - Epoch(train) [7][600/1253] lr: 4.0000e-02 eta: 8:54:56 time: 0.5637 data_time: 0.0453 memory: 23504 grad_norm: 2.9377 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.7950 loss: 1.7950 2022/09/08 11:57:14 - mmengine - INFO - Epoch(train) [7][620/1253] lr: 4.0000e-02 eta: 8:54:45 time: 0.5971 data_time: 0.0459 memory: 23504 grad_norm: 2.8177 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.6640 loss: 1.6640 2022/09/08 11:57:28 - mmengine - INFO - Epoch(train) [7][640/1253] lr: 4.0000e-02 eta: 8:54:42 time: 0.6555 data_time: 0.0450 memory: 23504 grad_norm: 2.8440 top1_acc: 0.4167 top5_acc: 0.8750 loss_cls: 1.7157 loss: 1.7157 2022/09/08 11:57:38 - mmengine - INFO - Epoch(train) [7][660/1253] lr: 4.0000e-02 eta: 8:54:24 time: 0.5428 data_time: 0.0386 memory: 23504 grad_norm: 2.8997 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.8832 loss: 1.8832 2022/09/08 11:57:49 - mmengine - INFO - Epoch(train) [7][680/1253] lr: 4.0000e-02 eta: 8:54:05 time: 0.5327 data_time: 0.0425 memory: 23504 grad_norm: 2.8098 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 1.7530 loss: 1.7530 2022/09/08 11:58:00 - mmengine - INFO - Epoch(train) [7][700/1253] lr: 4.0000e-02 eta: 8:53:48 time: 0.5497 data_time: 0.0463 memory: 23504 grad_norm: 2.9392 top1_acc: 0.5417 top5_acc: 0.6667 loss_cls: 1.6964 loss: 1.6964 2022/09/08 11:58:11 - mmengine - INFO - Epoch(train) [7][720/1253] lr: 4.0000e-02 eta: 8:53:31 time: 0.5468 data_time: 0.0448 memory: 23504 grad_norm: 2.8113 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 2.0025 loss: 2.0025 2022/09/08 11:58:22 - mmengine - INFO - Epoch(train) [7][740/1253] lr: 4.0000e-02 eta: 8:53:17 time: 0.5692 data_time: 0.0427 memory: 23504 grad_norm: 2.8517 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7089 loss: 1.7089 2022/09/08 11:58:37 - mmengine - INFO - Epoch(train) [7][760/1253] lr: 4.0000e-02 eta: 8:53:23 time: 0.7289 data_time: 0.0379 memory: 23504 grad_norm: 2.9744 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.8263 loss: 1.8263 2022/09/08 11:58:48 - mmengine - INFO - Epoch(train) [7][780/1253] lr: 4.0000e-02 eta: 8:53:08 time: 0.5634 data_time: 0.0789 memory: 23504 grad_norm: 2.8653 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.6251 loss: 1.6251 2022/09/08 11:58:59 - mmengine - INFO - Epoch(train) [7][800/1253] lr: 4.0000e-02 eta: 8:52:50 time: 0.5377 data_time: 0.0402 memory: 23504 grad_norm: 2.8387 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7819 loss: 1.7819 2022/09/08 11:59:10 - mmengine - INFO - Epoch(train) [7][820/1253] lr: 4.0000e-02 eta: 8:52:35 time: 0.5637 data_time: 0.0471 memory: 23504 grad_norm: 2.8446 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.6429 loss: 1.6429 2022/09/08 11:59:22 - mmengine - INFO - Epoch(train) [7][840/1253] lr: 4.0000e-02 eta: 8:52:21 time: 0.5737 data_time: 0.0365 memory: 23504 grad_norm: 2.8562 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.9405 loss: 1.9405 2022/09/08 11:59:34 - mmengine - INFO - Epoch(train) [7][860/1253] lr: 4.0000e-02 eta: 8:52:11 time: 0.6023 data_time: 0.0407 memory: 23504 grad_norm: 2.7865 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.8907 loss: 1.8907 2022/09/08 11:59:45 - mmengine - INFO - Epoch(train) [7][880/1253] lr: 4.0000e-02 eta: 8:51:59 time: 0.5831 data_time: 0.0429 memory: 23504 grad_norm: 2.8013 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.6309 loss: 1.6309 2022/09/08 11:59:57 - mmengine - INFO - Epoch(train) [7][900/1253] lr: 4.0000e-02 eta: 8:51:45 time: 0.5753 data_time: 0.0464 memory: 23504 grad_norm: 2.8199 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.9056 loss: 1.9056 2022/09/08 12:00:12 - mmengine - INFO - Epoch(train) [7][920/1253] lr: 4.0000e-02 eta: 8:51:54 time: 0.7444 data_time: 0.0412 memory: 23504 grad_norm: 2.7815 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.8029 loss: 1.8029 2022/09/08 12:00:23 - mmengine - INFO - Epoch(train) [7][940/1253] lr: 4.0000e-02 eta: 8:51:38 time: 0.5614 data_time: 0.0308 memory: 23504 grad_norm: 2.8556 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.7890 loss: 1.7890 2022/09/08 12:00:34 - mmengine - INFO - Epoch(train) [7][960/1253] lr: 4.0000e-02 eta: 8:51:20 time: 0.5388 data_time: 0.0445 memory: 23504 grad_norm: 2.8667 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.6831 loss: 1.6831 2022/09/08 12:00:45 - mmengine - INFO - Epoch(train) [7][980/1253] lr: 4.0000e-02 eta: 8:51:06 time: 0.5672 data_time: 0.0653 memory: 23504 grad_norm: 2.8241 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 1.7135 loss: 1.7135 2022/09/08 12:00:58 - mmengine - INFO - Epoch(train) [7][1000/1253] lr: 4.0000e-02 eta: 8:50:59 time: 0.6286 data_time: 0.0422 memory: 23504 grad_norm: 2.8082 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7365 loss: 1.7365 2022/09/08 12:01:09 - mmengine - INFO - Epoch(train) [7][1020/1253] lr: 4.0000e-02 eta: 8:50:43 time: 0.5566 data_time: 0.0442 memory: 23504 grad_norm: 2.8321 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.8049 loss: 1.8049 2022/09/08 12:01:20 - mmengine - INFO - Epoch(train) [7][1040/1253] lr: 4.0000e-02 eta: 8:50:29 time: 0.5699 data_time: 0.0463 memory: 23504 grad_norm: 2.8165 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7163 loss: 1.7163 2022/09/08 12:01:31 - mmengine - INFO - Epoch(train) [7][1060/1253] lr: 4.0000e-02 eta: 8:50:12 time: 0.5487 data_time: 0.0395 memory: 23504 grad_norm: 2.7825 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.7044 loss: 1.7044 2022/09/08 12:01:42 - mmengine - INFO - Epoch(train) [7][1080/1253] lr: 4.0000e-02 eta: 8:49:55 time: 0.5447 data_time: 0.0450 memory: 23504 grad_norm: 2.8730 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8746 loss: 1.8746 2022/09/08 12:01:54 - mmengine - INFO - Epoch(train) [7][1100/1253] lr: 4.0000e-02 eta: 8:49:41 time: 0.5733 data_time: 0.0560 memory: 23504 grad_norm: 2.7867 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.7787 loss: 1.7787 2022/09/08 12:02:05 - mmengine - INFO - Epoch(train) [7][1120/1253] lr: 4.0000e-02 eta: 8:49:29 time: 0.5830 data_time: 0.0431 memory: 23504 grad_norm: 2.8657 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.9313 loss: 1.9313 2022/09/08 12:02:22 - mmengine - INFO - Epoch(train) [7][1140/1253] lr: 4.0000e-02 eta: 8:49:45 time: 0.8112 data_time: 0.0382 memory: 23504 grad_norm: 2.8642 top1_acc: 0.5833 top5_acc: 0.6667 loss_cls: 1.8381 loss: 1.8381 2022/09/08 12:02:32 - mmengine - INFO - Epoch(train) [7][1160/1253] lr: 4.0000e-02 eta: 8:49:27 time: 0.5371 data_time: 0.0325 memory: 23504 grad_norm: 2.8202 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.8097 loss: 1.8097 2022/09/08 12:02:47 - mmengine - INFO - Epoch(train) [7][1180/1253] lr: 4.0000e-02 eta: 8:49:36 time: 0.7586 data_time: 0.0371 memory: 23504 grad_norm: 2.9378 top1_acc: 0.6250 top5_acc: 0.7083 loss_cls: 1.7743 loss: 1.7743 2022/09/08 12:02:58 - mmengine - INFO - Epoch(train) [7][1200/1253] lr: 4.0000e-02 eta: 8:49:14 time: 0.5018 data_time: 0.0356 memory: 23504 grad_norm: 2.8193 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.6779 loss: 1.6779 2022/09/08 12:03:10 - mmengine - INFO - Epoch(train) [7][1220/1253] lr: 4.0000e-02 eta: 8:49:04 time: 0.6062 data_time: 0.0361 memory: 23504 grad_norm: 2.7404 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.8479 loss: 1.8479 2022/09/08 12:03:19 - mmengine - INFO - Epoch(train) [7][1240/1253] lr: 4.0000e-02 eta: 8:48:37 time: 0.4653 data_time: 0.0262 memory: 23504 grad_norm: 2.8011 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.7331 loss: 1.7331 2022/09/08 12:03:24 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 12:03:24 - mmengine - INFO - Epoch(train) [7][1253/1253] lr: 4.0000e-02 eta: 8:48:37 time: 0.4252 data_time: 0.0157 memory: 23504 grad_norm: 2.8659 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.7296 loss: 1.7296 2022/09/08 12:03:47 - mmengine - INFO - Epoch(train) [8][20/1253] lr: 4.0000e-02 eta: 8:48:36 time: 1.1222 data_time: 0.4428 memory: 23504 grad_norm: 2.8134 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6584 loss: 1.6584 2022/09/08 12:04:04 - mmengine - INFO - Epoch(train) [8][40/1253] lr: 4.0000e-02 eta: 8:48:57 time: 0.8547 data_time: 0.0275 memory: 23504 grad_norm: 2.8356 top1_acc: 0.4583 top5_acc: 0.8750 loss_cls: 1.7040 loss: 1.7040 2022/09/08 12:04:15 - mmengine - INFO - Epoch(train) [8][60/1253] lr: 4.0000e-02 eta: 8:48:38 time: 0.5354 data_time: 0.0413 memory: 23504 grad_norm: 2.8639 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.6466 loss: 1.6466 2022/09/08 12:04:25 - mmengine - INFO - Epoch(train) [8][80/1253] lr: 4.0000e-02 eta: 8:48:21 time: 0.5410 data_time: 0.0352 memory: 23504 grad_norm: 2.8625 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.7012 loss: 1.7012 2022/09/08 12:04:37 - mmengine - INFO - Epoch(train) [8][100/1253] lr: 4.0000e-02 eta: 8:48:10 time: 0.5973 data_time: 0.0498 memory: 23504 grad_norm: 2.9104 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.7764 loss: 1.7764 2022/09/08 12:04:48 - mmengine - INFO - Epoch(train) [8][120/1253] lr: 4.0000e-02 eta: 8:47:54 time: 0.5512 data_time: 0.0522 memory: 23504 grad_norm: 2.7833 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.7336 loss: 1.7336 2022/09/08 12:05:00 - mmengine - INFO - Epoch(train) [8][140/1253] lr: 4.0000e-02 eta: 8:47:39 time: 0.5633 data_time: 0.0474 memory: 23504 grad_norm: 2.8513 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.6449 loss: 1.6449 2022/09/08 12:05:11 - mmengine - INFO - Epoch(train) [8][160/1253] lr: 4.0000e-02 eta: 8:47:24 time: 0.5632 data_time: 0.0415 memory: 23504 grad_norm: 2.8497 top1_acc: 0.6667 top5_acc: 0.7500 loss_cls: 1.4874 loss: 1.4874 2022/09/08 12:05:22 - mmengine - INFO - Epoch(train) [8][180/1253] lr: 4.0000e-02 eta: 8:47:10 time: 0.5695 data_time: 0.0483 memory: 23504 grad_norm: 2.9233 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.7029 loss: 1.7029 2022/09/08 12:05:36 - mmengine - INFO - Epoch(train) [8][200/1253] lr: 4.0000e-02 eta: 8:47:06 time: 0.6602 data_time: 0.0421 memory: 23504 grad_norm: 2.7806 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6095 loss: 1.6095 2022/09/08 12:05:47 - mmengine - INFO - Epoch(train) [8][220/1253] lr: 4.0000e-02 eta: 8:46:52 time: 0.5673 data_time: 0.0379 memory: 23504 grad_norm: 2.8133 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.7892 loss: 1.7892 2022/09/08 12:05:52 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 12:05:58 - mmengine - INFO - Epoch(train) [8][240/1253] lr: 4.0000e-02 eta: 8:46:38 time: 0.5718 data_time: 0.0452 memory: 23504 grad_norm: 2.8596 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.7443 loss: 1.7443 2022/09/08 12:06:11 - mmengine - INFO - Epoch(train) [8][260/1253] lr: 4.0000e-02 eta: 8:46:30 time: 0.6192 data_time: 0.0434 memory: 23504 grad_norm: 2.8722 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.7291 loss: 1.7291 2022/09/08 12:06:22 - mmengine - INFO - Epoch(train) [8][280/1253] lr: 4.0000e-02 eta: 8:46:16 time: 0.5748 data_time: 0.0413 memory: 23504 grad_norm: 2.8786 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.8010 loss: 1.8010 2022/09/08 12:06:34 - mmengine - INFO - Epoch(train) [8][300/1253] lr: 4.0000e-02 eta: 8:46:02 time: 0.5669 data_time: 0.0415 memory: 23504 grad_norm: 2.8686 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.7839 loss: 1.7839 2022/09/08 12:06:45 - mmengine - INFO - Epoch(train) [8][320/1253] lr: 4.0000e-02 eta: 8:45:46 time: 0.5530 data_time: 0.0417 memory: 23504 grad_norm: 2.9026 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6216 loss: 1.6216 2022/09/08 12:06:57 - mmengine - INFO - Epoch(train) [8][340/1253] lr: 4.0000e-02 eta: 8:45:35 time: 0.5930 data_time: 0.0423 memory: 23504 grad_norm: 2.8495 top1_acc: 0.4167 top5_acc: 0.8333 loss_cls: 1.8423 loss: 1.8423 2022/09/08 12:07:08 - mmengine - INFO - Epoch(train) [8][360/1253] lr: 4.0000e-02 eta: 8:45:19 time: 0.5584 data_time: 0.0436 memory: 23504 grad_norm: 2.7736 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.8034 loss: 1.8034 2022/09/08 12:07:19 - mmengine - INFO - Epoch(train) [8][380/1253] lr: 4.0000e-02 eta: 8:45:05 time: 0.5705 data_time: 0.0490 memory: 23504 grad_norm: 2.7776 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.6209 loss: 1.6209 2022/09/08 12:07:30 - mmengine - INFO - Epoch(train) [8][400/1253] lr: 4.0000e-02 eta: 8:44:51 time: 0.5683 data_time: 0.0437 memory: 23504 grad_norm: 2.9060 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.7468 loss: 1.7468 2022/09/08 12:07:43 - mmengine - INFO - Epoch(train) [8][420/1253] lr: 4.0000e-02 eta: 8:44:42 time: 0.6119 data_time: 0.0496 memory: 23504 grad_norm: 2.8762 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.8143 loss: 1.8143 2022/09/08 12:07:54 - mmengine - INFO - Epoch(train) [8][440/1253] lr: 4.0000e-02 eta: 8:44:30 time: 0.5824 data_time: 0.0593 memory: 23504 grad_norm: 2.8889 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8531 loss: 1.8531 2022/09/08 12:08:07 - mmengine - INFO - Epoch(train) [8][460/1253] lr: 4.0000e-02 eta: 8:44:21 time: 0.6154 data_time: 0.0331 memory: 23504 grad_norm: 2.8151 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.7556 loss: 1.7556 2022/09/08 12:08:18 - mmengine - INFO - Epoch(train) [8][480/1253] lr: 4.0000e-02 eta: 8:44:06 time: 0.5619 data_time: 0.0509 memory: 23504 grad_norm: 2.8462 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.7687 loss: 1.7687 2022/09/08 12:08:29 - mmengine - INFO - Epoch(train) [8][500/1253] lr: 4.0000e-02 eta: 8:43:52 time: 0.5738 data_time: 0.0416 memory: 23504 grad_norm: 2.8392 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 1.7109 loss: 1.7109 2022/09/08 12:08:41 - mmengine - INFO - Epoch(train) [8][520/1253] lr: 4.0000e-02 eta: 8:43:38 time: 0.5623 data_time: 0.0604 memory: 23504 grad_norm: 2.8484 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 1.8197 loss: 1.8197 2022/09/08 12:08:52 - mmengine - INFO - Epoch(train) [8][540/1253] lr: 4.0000e-02 eta: 8:43:23 time: 0.5673 data_time: 0.0589 memory: 23504 grad_norm: 2.8761 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.5786 loss: 1.5786 2022/09/08 12:09:03 - mmengine - INFO - Epoch(train) [8][560/1253] lr: 4.0000e-02 eta: 8:43:09 time: 0.5622 data_time: 0.0402 memory: 23504 grad_norm: 2.8815 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 1.7574 loss: 1.7574 2022/09/08 12:09:15 - mmengine - INFO - Epoch(train) [8][580/1253] lr: 4.0000e-02 eta: 8:42:56 time: 0.5833 data_time: 0.0431 memory: 23504 grad_norm: 2.8091 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 1.7190 loss: 1.7190 2022/09/08 12:09:27 - mmengine - INFO - Epoch(train) [8][600/1253] lr: 4.0000e-02 eta: 8:42:44 time: 0.5901 data_time: 0.0407 memory: 23504 grad_norm: 2.8302 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.9345 loss: 1.9345 2022/09/08 12:09:39 - mmengine - INFO - Epoch(train) [8][620/1253] lr: 4.0000e-02 eta: 8:42:34 time: 0.5978 data_time: 0.0481 memory: 23504 grad_norm: 2.8662 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.6091 loss: 1.6091 2022/09/08 12:09:50 - mmengine - INFO - Epoch(train) [8][640/1253] lr: 4.0000e-02 eta: 8:42:22 time: 0.5862 data_time: 0.0381 memory: 23504 grad_norm: 2.8901 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7647 loss: 1.7647 2022/09/08 12:10:02 - mmengine - INFO - Epoch(train) [8][660/1253] lr: 4.0000e-02 eta: 8:42:12 time: 0.6055 data_time: 0.0444 memory: 23504 grad_norm: 2.8147 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.8309 loss: 1.8309 2022/09/08 12:10:14 - mmengine - INFO - Epoch(train) [8][680/1253] lr: 4.0000e-02 eta: 8:41:57 time: 0.5595 data_time: 0.0319 memory: 23504 grad_norm: 2.8606 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.8724 loss: 1.8724 2022/09/08 12:10:25 - mmengine - INFO - Epoch(train) [8][700/1253] lr: 4.0000e-02 eta: 8:41:42 time: 0.5602 data_time: 0.0456 memory: 23504 grad_norm: 2.9204 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9032 loss: 1.9032 2022/09/08 12:10:36 - mmengine - INFO - Epoch(train) [8][720/1253] lr: 4.0000e-02 eta: 8:41:27 time: 0.5597 data_time: 0.0461 memory: 23504 grad_norm: 2.8765 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6022 loss: 1.6022 2022/09/08 12:10:48 - mmengine - INFO - Epoch(train) [8][740/1253] lr: 4.0000e-02 eta: 8:41:15 time: 0.5889 data_time: 0.0430 memory: 23504 grad_norm: 2.7609 top1_acc: 0.5000 top5_acc: 0.5833 loss_cls: 1.7708 loss: 1.7708 2022/09/08 12:11:02 - mmengine - INFO - Epoch(train) [8][760/1253] lr: 4.0000e-02 eta: 8:41:15 time: 0.6973 data_time: 0.0431 memory: 23504 grad_norm: 2.8319 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.7501 loss: 1.7501 2022/09/08 12:11:13 - mmengine - INFO - Epoch(train) [8][780/1253] lr: 4.0000e-02 eta: 8:41:01 time: 0.5655 data_time: 0.0379 memory: 23504 grad_norm: 2.7848 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.8114 loss: 1.8114 2022/09/08 12:11:24 - mmengine - INFO - Epoch(train) [8][800/1253] lr: 4.0000e-02 eta: 8:40:46 time: 0.5609 data_time: 0.0714 memory: 23504 grad_norm: 2.7642 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.8832 loss: 1.8832 2022/09/08 12:11:36 - mmengine - INFO - Epoch(train) [8][820/1253] lr: 4.0000e-02 eta: 8:40:32 time: 0.5646 data_time: 0.0465 memory: 23504 grad_norm: 2.8991 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6965 loss: 1.6965 2022/09/08 12:11:47 - mmengine - INFO - Epoch(train) [8][840/1253] lr: 4.0000e-02 eta: 8:40:17 time: 0.5617 data_time: 0.0449 memory: 23504 grad_norm: 2.8434 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.7043 loss: 1.7043 2022/09/08 12:11:58 - mmengine - INFO - Epoch(train) [8][860/1253] lr: 4.0000e-02 eta: 8:40:00 time: 0.5457 data_time: 0.0489 memory: 23504 grad_norm: 2.9014 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.6631 loss: 1.6631 2022/09/08 12:12:09 - mmengine - INFO - Epoch(train) [8][880/1253] lr: 4.0000e-02 eta: 8:39:45 time: 0.5543 data_time: 0.0477 memory: 23504 grad_norm: 2.7849 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7113 loss: 1.7113 2022/09/08 12:12:20 - mmengine - INFO - Epoch(train) [8][900/1253] lr: 4.0000e-02 eta: 8:39:29 time: 0.5459 data_time: 0.0449 memory: 23504 grad_norm: 2.8347 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.8795 loss: 1.8795 2022/09/08 12:12:31 - mmengine - INFO - Epoch(train) [8][920/1253] lr: 4.0000e-02 eta: 8:39:14 time: 0.5601 data_time: 0.0444 memory: 23504 grad_norm: 2.8486 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.8089 loss: 1.8089 2022/09/08 12:12:42 - mmengine - INFO - Epoch(train) [8][940/1253] lr: 4.0000e-02 eta: 8:38:59 time: 0.5630 data_time: 0.0424 memory: 23504 grad_norm: 2.8175 top1_acc: 0.3750 top5_acc: 0.5417 loss_cls: 1.9583 loss: 1.9583 2022/09/08 12:12:54 - mmengine - INFO - Epoch(train) [8][960/1253] lr: 4.0000e-02 eta: 8:38:45 time: 0.5699 data_time: 0.0474 memory: 23504 grad_norm: 2.8634 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 1.7739 loss: 1.7739 2022/09/08 12:13:05 - mmengine - INFO - Epoch(train) [8][980/1253] lr: 4.0000e-02 eta: 8:38:31 time: 0.5611 data_time: 0.0450 memory: 23504 grad_norm: 2.7662 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.6978 loss: 1.6978 2022/09/08 12:13:16 - mmengine - INFO - Epoch(train) [8][1000/1253] lr: 4.0000e-02 eta: 8:38:16 time: 0.5571 data_time: 0.0400 memory: 23504 grad_norm: 2.8880 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7798 loss: 1.7798 2022/09/08 12:13:27 - mmengine - INFO - Epoch(train) [8][1020/1253] lr: 4.0000e-02 eta: 8:38:01 time: 0.5580 data_time: 0.0465 memory: 23504 grad_norm: 2.8610 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.8348 loss: 1.8348 2022/09/08 12:13:39 - mmengine - INFO - Epoch(train) [8][1040/1253] lr: 4.0000e-02 eta: 8:37:47 time: 0.5731 data_time: 0.0495 memory: 23504 grad_norm: 2.7910 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8601 loss: 1.8601 2022/09/08 12:13:50 - mmengine - INFO - Epoch(train) [8][1060/1253] lr: 4.0000e-02 eta: 8:37:34 time: 0.5731 data_time: 0.0445 memory: 23504 grad_norm: 2.7715 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.5966 loss: 1.5966 2022/09/08 12:14:03 - mmengine - INFO - Epoch(train) [8][1080/1253] lr: 4.0000e-02 eta: 8:37:29 time: 0.6561 data_time: 0.0434 memory: 23504 grad_norm: 2.8299 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.5528 loss: 1.5528 2022/09/08 12:14:15 - mmengine - INFO - Epoch(train) [8][1100/1253] lr: 4.0000e-02 eta: 8:37:17 time: 0.5827 data_time: 0.0771 memory: 23504 grad_norm: 2.8375 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7544 loss: 1.7544 2022/09/08 12:14:30 - mmengine - INFO - Epoch(train) [8][1120/1253] lr: 4.0000e-02 eta: 8:37:21 time: 0.7334 data_time: 0.0436 memory: 23504 grad_norm: 2.8891 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 1.8667 loss: 1.8667 2022/09/08 12:14:41 - mmengine - INFO - Epoch(train) [8][1140/1253] lr: 4.0000e-02 eta: 8:37:09 time: 0.5909 data_time: 0.0477 memory: 23504 grad_norm: 2.8154 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.7287 loss: 1.7287 2022/09/08 12:14:53 - mmengine - INFO - Epoch(train) [8][1160/1253] lr: 4.0000e-02 eta: 8:36:56 time: 0.5709 data_time: 0.0382 memory: 23504 grad_norm: 2.8494 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.8207 loss: 1.8207 2022/09/08 12:15:05 - mmengine - INFO - Epoch(train) [8][1180/1253] lr: 4.0000e-02 eta: 8:36:45 time: 0.5949 data_time: 0.0479 memory: 23504 grad_norm: 2.7853 top1_acc: 0.6250 top5_acc: 0.6667 loss_cls: 1.8518 loss: 1.8518 2022/09/08 12:15:17 - mmengine - INFO - Epoch(train) [8][1200/1253] lr: 4.0000e-02 eta: 8:36:35 time: 0.6093 data_time: 0.0384 memory: 23504 grad_norm: 2.7508 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6663 loss: 1.6663 2022/09/08 12:15:29 - mmengine - INFO - Epoch(train) [8][1220/1253] lr: 4.0000e-02 eta: 8:36:23 time: 0.5832 data_time: 0.0441 memory: 23504 grad_norm: 2.8076 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.8886 loss: 1.8886 2022/09/08 12:15:33 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 12:15:38 - mmengine - INFO - Epoch(train) [8][1240/1253] lr: 4.0000e-02 eta: 8:36:00 time: 0.4805 data_time: 0.0301 memory: 23504 grad_norm: 2.8839 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 1.7286 loss: 1.7286 2022/09/08 12:15:44 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 12:15:44 - mmengine - INFO - Epoch(train) [8][1253/1253] lr: 4.0000e-02 eta: 8:36:00 time: 0.4345 data_time: 0.0235 memory: 23504 grad_norm: 2.8943 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.7106 loss: 1.7106 2022/09/08 12:16:06 - mmengine - INFO - Epoch(train) [9][20/1253] lr: 4.0000e-02 eta: 8:35:57 time: 1.1286 data_time: 0.4531 memory: 23504 grad_norm: 2.8790 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7300 loss: 1.7300 2022/09/08 12:16:18 - mmengine - INFO - Epoch(train) [9][40/1253] lr: 4.0000e-02 eta: 8:35:47 time: 0.6054 data_time: 0.0565 memory: 23504 grad_norm: 2.7496 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5535 loss: 1.5535 2022/09/08 12:16:31 - mmengine - INFO - Epoch(train) [9][60/1253] lr: 4.0000e-02 eta: 8:35:37 time: 0.6067 data_time: 0.0574 memory: 23504 grad_norm: 2.8502 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7288 loss: 1.7288 2022/09/08 12:16:43 - mmengine - INFO - Epoch(train) [9][80/1253] lr: 4.0000e-02 eta: 8:35:27 time: 0.6067 data_time: 0.1017 memory: 23504 grad_norm: 2.8072 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.6434 loss: 1.6434 2022/09/08 12:16:55 - mmengine - INFO - Epoch(train) [9][100/1253] lr: 4.0000e-02 eta: 8:35:18 time: 0.6162 data_time: 0.0489 memory: 23504 grad_norm: 2.7904 top1_acc: 0.5000 top5_acc: 0.9167 loss_cls: 1.7504 loss: 1.7504 2022/09/08 12:17:06 - mmengine - INFO - Epoch(train) [9][120/1253] lr: 4.0000e-02 eta: 8:35:04 time: 0.5630 data_time: 0.0342 memory: 23504 grad_norm: 2.8301 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 1.6487 loss: 1.6487 2022/09/08 12:17:18 - mmengine - INFO - Epoch(train) [9][140/1253] lr: 4.0000e-02 eta: 8:34:52 time: 0.5927 data_time: 0.0337 memory: 23504 grad_norm: 2.7807 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.6181 loss: 1.6181 2022/09/08 12:17:29 - mmengine - INFO - Epoch(train) [9][160/1253] lr: 4.0000e-02 eta: 8:34:38 time: 0.5646 data_time: 0.0462 memory: 23504 grad_norm: 2.8833 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6978 loss: 1.6978 2022/09/08 12:17:41 - mmengine - INFO - Epoch(train) [9][180/1253] lr: 4.0000e-02 eta: 8:34:26 time: 0.5850 data_time: 0.0481 memory: 23504 grad_norm: 3.0068 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 1.4970 loss: 1.4970 2022/09/08 12:17:53 - mmengine - INFO - Epoch(train) [9][200/1253] lr: 4.0000e-02 eta: 8:34:12 time: 0.5711 data_time: 0.0375 memory: 23504 grad_norm: 2.8514 top1_acc: 0.6667 top5_acc: 0.7500 loss_cls: 1.7353 loss: 1.7353 2022/09/08 12:18:04 - mmengine - INFO - Epoch(train) [9][220/1253] lr: 4.0000e-02 eta: 8:33:58 time: 0.5644 data_time: 0.0322 memory: 23504 grad_norm: 2.8498 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.6195 loss: 1.6195 2022/09/08 12:18:16 - mmengine - INFO - Epoch(train) [9][240/1253] lr: 4.0000e-02 eta: 8:33:46 time: 0.5841 data_time: 0.0424 memory: 23504 grad_norm: 2.8273 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7917 loss: 1.7917 2022/09/08 12:18:27 - mmengine - INFO - Epoch(train) [9][260/1253] lr: 4.0000e-02 eta: 8:33:33 time: 0.5737 data_time: 0.0394 memory: 23504 grad_norm: 2.8505 top1_acc: 0.5417 top5_acc: 0.9583 loss_cls: 1.6503 loss: 1.6503 2022/09/08 12:18:39 - mmengine - INFO - Epoch(train) [9][280/1253] lr: 4.0000e-02 eta: 8:33:22 time: 0.5986 data_time: 0.0417 memory: 23504 grad_norm: 2.8515 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.7284 loss: 1.7284 2022/09/08 12:18:51 - mmengine - INFO - Epoch(train) [9][300/1253] lr: 4.0000e-02 eta: 8:33:10 time: 0.5871 data_time: 0.0419 memory: 23504 grad_norm: 2.8036 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7555 loss: 1.7555 2022/09/08 12:19:02 - mmengine - INFO - Epoch(train) [9][320/1253] lr: 4.0000e-02 eta: 8:32:55 time: 0.5584 data_time: 0.0441 memory: 23504 grad_norm: 2.9058 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.7790 loss: 1.7790 2022/09/08 12:19:14 - mmengine - INFO - Epoch(train) [9][340/1253] lr: 4.0000e-02 eta: 8:32:43 time: 0.5807 data_time: 0.0432 memory: 23504 grad_norm: 2.8242 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.7796 loss: 1.7796 2022/09/08 12:19:25 - mmengine - INFO - Epoch(train) [9][360/1253] lr: 4.0000e-02 eta: 8:32:29 time: 0.5712 data_time: 0.0458 memory: 23504 grad_norm: 2.8405 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.7955 loss: 1.7955 2022/09/08 12:19:36 - mmengine - INFO - Epoch(train) [9][380/1253] lr: 4.0000e-02 eta: 8:32:15 time: 0.5592 data_time: 0.0532 memory: 23504 grad_norm: 2.7614 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.6449 loss: 1.6449 2022/09/08 12:19:48 - mmengine - INFO - Epoch(train) [9][400/1253] lr: 4.0000e-02 eta: 8:32:01 time: 0.5696 data_time: 0.0437 memory: 23504 grad_norm: 2.8720 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.6139 loss: 1.6139 2022/09/08 12:20:00 - mmengine - INFO - Epoch(train) [9][420/1253] lr: 4.0000e-02 eta: 8:31:50 time: 0.5990 data_time: 0.0470 memory: 23504 grad_norm: 2.8981 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.6963 loss: 1.6963 2022/09/08 12:20:12 - mmengine - INFO - Epoch(train) [9][440/1253] lr: 4.0000e-02 eta: 8:31:43 time: 0.6304 data_time: 0.1076 memory: 23504 grad_norm: 2.8507 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.6183 loss: 1.6183 2022/09/08 12:20:24 - mmengine - INFO - Epoch(train) [9][460/1253] lr: 4.0000e-02 eta: 8:31:29 time: 0.5688 data_time: 0.0485 memory: 23504 grad_norm: 2.8049 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 1.5914 loss: 1.5914 2022/09/08 12:20:35 - mmengine - INFO - Epoch(train) [9][480/1253] lr: 4.0000e-02 eta: 8:31:16 time: 0.5739 data_time: 0.0533 memory: 23504 grad_norm: 2.8446 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 1.7416 loss: 1.7416 2022/09/08 12:20:46 - mmengine - INFO - Epoch(train) [9][500/1253] lr: 4.0000e-02 eta: 8:31:02 time: 0.5708 data_time: 0.0388 memory: 23504 grad_norm: 2.7911 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 1.8177 loss: 1.8177 2022/09/08 12:20:58 - mmengine - INFO - Epoch(train) [9][520/1253] lr: 4.0000e-02 eta: 8:30:50 time: 0.5844 data_time: 0.0409 memory: 23504 grad_norm: 2.8253 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7730 loss: 1.7730 2022/09/08 12:21:10 - mmengine - INFO - Epoch(train) [9][540/1253] lr: 4.0000e-02 eta: 8:30:41 time: 0.6190 data_time: 0.0413 memory: 23504 grad_norm: 2.8410 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.6018 loss: 1.6018 2022/09/08 12:21:22 - mmengine - INFO - Epoch(train) [9][560/1253] lr: 4.0000e-02 eta: 8:30:28 time: 0.5708 data_time: 0.0339 memory: 23504 grad_norm: 2.8386 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.5965 loss: 1.5965 2022/09/08 12:21:33 - mmengine - INFO - Epoch(train) [9][580/1253] lr: 4.0000e-02 eta: 8:30:15 time: 0.5766 data_time: 0.0449 memory: 23504 grad_norm: 2.8593 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.8154 loss: 1.8154 2022/09/08 12:21:44 - mmengine - INFO - Epoch(train) [9][600/1253] lr: 4.0000e-02 eta: 8:29:59 time: 0.5475 data_time: 0.0423 memory: 23504 grad_norm: 2.7717 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6843 loss: 1.6843 2022/09/08 12:21:56 - mmengine - INFO - Epoch(train) [9][620/1253] lr: 4.0000e-02 eta: 8:29:48 time: 0.5905 data_time: 0.0563 memory: 23504 grad_norm: 2.8378 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.5092 loss: 1.5092 2022/09/08 12:22:08 - mmengine - INFO - Epoch(train) [9][640/1253] lr: 4.0000e-02 eta: 8:29:37 time: 0.5961 data_time: 0.0385 memory: 23504 grad_norm: 2.8388 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.8346 loss: 1.8346 2022/09/08 12:22:20 - mmengine - INFO - Epoch(train) [9][660/1253] lr: 4.0000e-02 eta: 8:29:24 time: 0.5759 data_time: 0.0403 memory: 23504 grad_norm: 2.8567 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6462 loss: 1.6462 2022/09/08 12:22:31 - mmengine - INFO - Epoch(train) [9][680/1253] lr: 4.0000e-02 eta: 8:29:11 time: 0.5802 data_time: 0.0417 memory: 23504 grad_norm: 2.8316 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.6604 loss: 1.6604 2022/09/08 12:22:43 - mmengine - INFO - Epoch(train) [9][700/1253] lr: 4.0000e-02 eta: 8:28:58 time: 0.5682 data_time: 0.0465 memory: 23504 grad_norm: 2.8249 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.5237 loss: 1.5237 2022/09/08 12:22:54 - mmengine - INFO - Epoch(train) [9][720/1253] lr: 4.0000e-02 eta: 8:28:42 time: 0.5525 data_time: 0.0369 memory: 23504 grad_norm: 2.8604 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.7557 loss: 1.7557 2022/09/08 12:23:05 - mmengine - INFO - Epoch(train) [9][740/1253] lr: 4.0000e-02 eta: 8:28:28 time: 0.5651 data_time: 0.0452 memory: 23504 grad_norm: 2.8086 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.6995 loss: 1.6995 2022/09/08 12:23:16 - mmengine - INFO - Epoch(train) [9][760/1253] lr: 4.0000e-02 eta: 8:28:14 time: 0.5595 data_time: 0.0474 memory: 23504 grad_norm: 2.7915 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.7996 loss: 1.7996 2022/09/08 12:23:28 - mmengine - INFO - Epoch(train) [9][780/1253] lr: 4.0000e-02 eta: 8:28:03 time: 0.5935 data_time: 0.0471 memory: 23504 grad_norm: 2.7745 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.6863 loss: 1.6863 2022/09/08 12:23:39 - mmengine - INFO - Epoch(train) [9][800/1253] lr: 4.0000e-02 eta: 8:27:49 time: 0.5703 data_time: 0.0446 memory: 23504 grad_norm: 2.7909 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.6853 loss: 1.6853 2022/09/08 12:23:51 - mmengine - INFO - Epoch(train) [9][820/1253] lr: 4.0000e-02 eta: 8:27:36 time: 0.5721 data_time: 0.0424 memory: 23504 grad_norm: 2.8570 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.7122 loss: 1.7122 2022/09/08 12:24:02 - mmengine - INFO - Epoch(train) [9][840/1253] lr: 4.0000e-02 eta: 8:27:22 time: 0.5689 data_time: 0.0412 memory: 23504 grad_norm: 2.8263 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.6733 loss: 1.6733 2022/09/08 12:24:14 - mmengine - INFO - Epoch(train) [9][860/1253] lr: 4.0000e-02 eta: 8:27:09 time: 0.5692 data_time: 0.0501 memory: 23504 grad_norm: 2.8499 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.6789 loss: 1.6789 2022/09/08 12:24:25 - mmengine - INFO - Epoch(train) [9][880/1253] lr: 4.0000e-02 eta: 8:26:55 time: 0.5693 data_time: 0.0406 memory: 23504 grad_norm: 2.7691 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.7214 loss: 1.7214 2022/09/08 12:24:37 - mmengine - INFO - Epoch(train) [9][900/1253] lr: 4.0000e-02 eta: 8:26:43 time: 0.5828 data_time: 0.0412 memory: 23504 grad_norm: 2.8542 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 1.6661 loss: 1.6661 2022/09/08 12:24:48 - mmengine - INFO - Epoch(train) [9][920/1253] lr: 4.0000e-02 eta: 8:26:31 time: 0.5854 data_time: 0.0415 memory: 23504 grad_norm: 2.8016 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.7251 loss: 1.7251 2022/09/08 12:25:00 - mmengine - INFO - Epoch(train) [9][940/1253] lr: 4.0000e-02 eta: 8:26:19 time: 0.5846 data_time: 0.0505 memory: 23504 grad_norm: 2.7765 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.7793 loss: 1.7793 2022/09/08 12:25:12 - mmengine - INFO - Epoch(train) [9][960/1253] lr: 4.0000e-02 eta: 8:26:06 time: 0.5760 data_time: 0.0451 memory: 23504 grad_norm: 2.8594 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.8236 loss: 1.8236 2022/09/08 12:25:22 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 12:25:24 - mmengine - INFO - Epoch(train) [9][980/1253] lr: 4.0000e-02 eta: 8:25:57 time: 0.6119 data_time: 0.0554 memory: 23504 grad_norm: 2.8358 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.7262 loss: 1.7262 2022/09/08 12:25:35 - mmengine - INFO - Epoch(train) [9][1000/1253] lr: 4.0000e-02 eta: 8:25:42 time: 0.5551 data_time: 0.0387 memory: 23504 grad_norm: 2.8217 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.8091 loss: 1.8091 2022/09/08 12:25:46 - mmengine - INFO - Epoch(train) [9][1020/1253] lr: 4.0000e-02 eta: 8:25:27 time: 0.5588 data_time: 0.0468 memory: 23504 grad_norm: 2.8759 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.7425 loss: 1.7425 2022/09/08 12:25:58 - mmengine - INFO - Epoch(train) [9][1040/1253] lr: 4.0000e-02 eta: 8:25:18 time: 0.6079 data_time: 0.0523 memory: 23504 grad_norm: 2.8411 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.6927 loss: 1.6927 2022/09/08 12:26:10 - mmengine - INFO - Epoch(train) [9][1060/1253] lr: 4.0000e-02 eta: 8:25:04 time: 0.5632 data_time: 0.0447 memory: 23504 grad_norm: 2.8325 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.6911 loss: 1.6911 2022/09/08 12:26:21 - mmengine - INFO - Epoch(train) [9][1080/1253] lr: 4.0000e-02 eta: 8:24:48 time: 0.5465 data_time: 0.0396 memory: 23504 grad_norm: 2.8008 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6319 loss: 1.6319 2022/09/08 12:26:32 - mmengine - INFO - Epoch(train) [9][1100/1253] lr: 4.0000e-02 eta: 8:24:36 time: 0.5869 data_time: 0.0422 memory: 23504 grad_norm: 2.8091 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.7198 loss: 1.7198 2022/09/08 12:26:44 - mmengine - INFO - Epoch(train) [9][1120/1253] lr: 4.0000e-02 eta: 8:24:23 time: 0.5699 data_time: 0.0503 memory: 23504 grad_norm: 2.7721 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.6582 loss: 1.6582 2022/09/08 12:26:56 - mmengine - INFO - Epoch(train) [9][1140/1253] lr: 4.0000e-02 eta: 8:24:14 time: 0.6240 data_time: 0.0412 memory: 23504 grad_norm: 2.7478 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 1.5688 loss: 1.5688 2022/09/08 12:27:07 - mmengine - INFO - Epoch(train) [9][1160/1253] lr: 4.0000e-02 eta: 8:23:59 time: 0.5519 data_time: 0.0425 memory: 23504 grad_norm: 2.8391 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.6413 loss: 1.6413 2022/09/08 12:27:19 - mmengine - INFO - Epoch(train) [9][1180/1253] lr: 4.0000e-02 eta: 8:23:46 time: 0.5731 data_time: 0.0510 memory: 23504 grad_norm: 2.7467 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.6261 loss: 1.6261 2022/09/08 12:27:30 - mmengine - INFO - Epoch(train) [9][1200/1253] lr: 4.0000e-02 eta: 8:23:33 time: 0.5686 data_time: 0.0421 memory: 23504 grad_norm: 2.9122 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.8053 loss: 1.8053 2022/09/08 12:27:42 - mmengine - INFO - Epoch(train) [9][1220/1253] lr: 4.0000e-02 eta: 8:23:22 time: 0.5974 data_time: 0.0471 memory: 23504 grad_norm: 2.7271 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.6371 loss: 1.6371 2022/09/08 12:27:52 - mmengine - INFO - Epoch(train) [9][1240/1253] lr: 4.0000e-02 eta: 8:23:01 time: 0.4861 data_time: 0.0312 memory: 23504 grad_norm: 2.8590 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 1.6601 loss: 1.6601 2022/09/08 12:27:57 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 12:27:57 - mmengine - INFO - Epoch(train) [9][1253/1253] lr: 4.0000e-02 eta: 8:23:01 time: 0.4286 data_time: 0.0174 memory: 23504 grad_norm: 2.9393 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.8574 loss: 1.8574 2022/09/08 12:28:19 - mmengine - INFO - Epoch(train) [10][20/1253] lr: 4.0000e-02 eta: 8:22:51 time: 1.0689 data_time: 0.4381 memory: 23504 grad_norm: 2.8002 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6727 loss: 1.6727 2022/09/08 12:28:31 - mmengine - INFO - Epoch(train) [10][40/1253] lr: 4.0000e-02 eta: 8:22:43 time: 0.6353 data_time: 0.0420 memory: 23504 grad_norm: 2.8781 top1_acc: 0.5833 top5_acc: 0.9583 loss_cls: 1.5089 loss: 1.5089 2022/09/08 12:28:42 - mmengine - INFO - Epoch(train) [10][60/1253] lr: 4.0000e-02 eta: 8:22:29 time: 0.5578 data_time: 0.0432 memory: 23504 grad_norm: 2.8247 top1_acc: 0.6250 top5_acc: 0.7083 loss_cls: 1.6824 loss: 1.6824 2022/09/08 12:28:54 - mmengine - INFO - Epoch(train) [10][80/1253] lr: 4.0000e-02 eta: 8:22:15 time: 0.5685 data_time: 0.0368 memory: 23504 grad_norm: 2.8563 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7397 loss: 1.7397 2022/09/08 12:29:06 - mmengine - INFO - Epoch(train) [10][100/1253] lr: 4.0000e-02 eta: 8:22:08 time: 0.6364 data_time: 0.0507 memory: 23504 grad_norm: 2.7932 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.5237 loss: 1.5237 2022/09/08 12:29:20 - mmengine - INFO - Epoch(train) [10][120/1253] lr: 4.0000e-02 eta: 8:22:06 time: 0.6944 data_time: 0.0446 memory: 23504 grad_norm: 2.8770 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.6133 loss: 1.6133 2022/09/08 12:29:31 - mmengine - INFO - Epoch(train) [10][140/1253] lr: 4.0000e-02 eta: 8:21:49 time: 0.5321 data_time: 0.0397 memory: 23504 grad_norm: 2.9303 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.6362 loss: 1.6362 2022/09/08 12:29:44 - mmengine - INFO - Epoch(train) [10][160/1253] lr: 4.0000e-02 eta: 8:21:41 time: 0.6294 data_time: 0.0386 memory: 23504 grad_norm: 2.8592 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.6779 loss: 1.6779 2022/09/08 12:29:55 - mmengine - INFO - Epoch(train) [10][180/1253] lr: 4.0000e-02 eta: 8:21:29 time: 0.5831 data_time: 0.0448 memory: 23504 grad_norm: 2.8000 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 1.7015 loss: 1.7015 2022/09/08 12:30:06 - mmengine - INFO - Epoch(train) [10][200/1253] lr: 4.0000e-02 eta: 8:21:13 time: 0.5448 data_time: 0.0429 memory: 23504 grad_norm: 2.8544 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5822 loss: 1.5822 2022/09/08 12:30:18 - mmengine - INFO - Epoch(train) [10][220/1253] lr: 4.0000e-02 eta: 8:21:01 time: 0.5791 data_time: 0.0723 memory: 23504 grad_norm: 2.8455 top1_acc: 0.5000 top5_acc: 0.9583 loss_cls: 1.7109 loss: 1.7109 2022/09/08 12:30:31 - mmengine - INFO - Epoch(train) [10][240/1253] lr: 4.0000e-02 eta: 8:20:54 time: 0.6397 data_time: 0.0535 memory: 23504 grad_norm: 2.7996 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.7189 loss: 1.7189 2022/09/08 12:30:42 - mmengine - INFO - Epoch(train) [10][260/1253] lr: 4.0000e-02 eta: 8:20:41 time: 0.5730 data_time: 0.0448 memory: 23504 grad_norm: 2.8249 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.6741 loss: 1.6741 2022/09/08 12:30:53 - mmengine - INFO - Epoch(train) [10][280/1253] lr: 4.0000e-02 eta: 8:20:26 time: 0.5607 data_time: 0.0426 memory: 23504 grad_norm: 2.8210 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7027 loss: 1.7027 2022/09/08 12:31:05 - mmengine - INFO - Epoch(train) [10][300/1253] lr: 4.0000e-02 eta: 8:20:16 time: 0.6040 data_time: 0.0424 memory: 23504 grad_norm: 2.7958 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.4892 loss: 1.4892 2022/09/08 12:31:17 - mmengine - INFO - Epoch(train) [10][320/1253] lr: 4.0000e-02 eta: 8:20:02 time: 0.5642 data_time: 0.0433 memory: 23504 grad_norm: 2.8699 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.6301 loss: 1.6301 2022/09/08 12:31:29 - mmengine - INFO - Epoch(train) [10][340/1253] lr: 4.0000e-02 eta: 8:19:55 time: 0.6340 data_time: 0.0460 memory: 23504 grad_norm: 2.8127 top1_acc: 0.7917 top5_acc: 0.7917 loss_cls: 1.5139 loss: 1.5139 2022/09/08 12:31:40 - mmengine - INFO - Epoch(train) [10][360/1253] lr: 4.0000e-02 eta: 8:19:40 time: 0.5563 data_time: 0.0356 memory: 23504 grad_norm: 2.8340 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.6825 loss: 1.6825 2022/09/08 12:31:52 - mmengine - INFO - Epoch(train) [10][380/1253] lr: 4.0000e-02 eta: 8:19:26 time: 0.5602 data_time: 0.0481 memory: 23504 grad_norm: 2.8878 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.7149 loss: 1.7149 2022/09/08 12:32:03 - mmengine - INFO - Epoch(train) [10][400/1253] lr: 4.0000e-02 eta: 8:19:14 time: 0.5809 data_time: 0.0447 memory: 23504 grad_norm: 2.8057 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.7809 loss: 1.7809 2022/09/08 12:32:15 - mmengine - INFO - Epoch(train) [10][420/1253] lr: 4.0000e-02 eta: 8:19:01 time: 0.5824 data_time: 0.0384 memory: 23504 grad_norm: 2.8002 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.7363 loss: 1.7363 2022/09/08 12:32:26 - mmengine - INFO - Epoch(train) [10][440/1253] lr: 4.0000e-02 eta: 8:18:46 time: 0.5519 data_time: 0.0413 memory: 23504 grad_norm: 2.9455 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.8695 loss: 1.8695 2022/09/08 12:32:37 - mmengine - INFO - Epoch(train) [10][460/1253] lr: 4.0000e-02 eta: 8:18:32 time: 0.5577 data_time: 0.0425 memory: 23504 grad_norm: 2.8814 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.7287 loss: 1.7287 2022/09/08 12:32:48 - mmengine - INFO - Epoch(train) [10][480/1253] lr: 4.0000e-02 eta: 8:18:18 time: 0.5595 data_time: 0.0383 memory: 23504 grad_norm: 2.8290 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 1.5988 loss: 1.5988 2022/09/08 12:33:00 - mmengine - INFO - Epoch(train) [10][500/1253] lr: 4.0000e-02 eta: 8:18:07 time: 0.5919 data_time: 0.0470 memory: 23504 grad_norm: 2.8744 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.6329 loss: 1.6329 2022/09/08 12:33:12 - mmengine - INFO - Epoch(train) [10][520/1253] lr: 4.0000e-02 eta: 8:17:54 time: 0.5733 data_time: 0.0441 memory: 23504 grad_norm: 2.8440 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 1.7309 loss: 1.7309 2022/09/08 12:33:24 - mmengine - INFO - Epoch(train) [10][540/1253] lr: 4.0000e-02 eta: 8:17:43 time: 0.5987 data_time: 0.0567 memory: 23504 grad_norm: 2.8360 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.7897 loss: 1.7897 2022/09/08 12:33:35 - mmengine - INFO - Epoch(train) [10][560/1253] lr: 4.0000e-02 eta: 8:17:31 time: 0.5879 data_time: 0.0550 memory: 23504 grad_norm: 2.8529 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.5098 loss: 1.5098 2022/09/08 12:33:50 - mmengine - INFO - Epoch(train) [10][580/1253] lr: 4.0000e-02 eta: 8:17:33 time: 0.7432 data_time: 0.0300 memory: 23504 grad_norm: 2.8749 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.7921 loss: 1.7921 2022/09/08 12:34:01 - mmengine - INFO - Epoch(train) [10][600/1253] lr: 4.0000e-02 eta: 8:17:17 time: 0.5386 data_time: 0.0410 memory: 23504 grad_norm: 2.7484 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.6074 loss: 1.6074 2022/09/08 12:34:12 - mmengine - INFO - Epoch(train) [10][620/1253] lr: 4.0000e-02 eta: 8:17:02 time: 0.5555 data_time: 0.0451 memory: 23504 grad_norm: 2.8385 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 1.7474 loss: 1.7474 2022/09/08 12:34:23 - mmengine - INFO - Epoch(train) [10][640/1253] lr: 4.0000e-02 eta: 8:16:49 time: 0.5700 data_time: 0.0458 memory: 23504 grad_norm: 2.8357 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.6741 loss: 1.6741 2022/09/08 12:34:35 - mmengine - INFO - Epoch(train) [10][660/1253] lr: 4.0000e-02 eta: 8:16:35 time: 0.5644 data_time: 0.0415 memory: 23504 grad_norm: 2.7630 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.5288 loss: 1.5288 2022/09/08 12:34:46 - mmengine - INFO - Epoch(train) [10][680/1253] lr: 4.0000e-02 eta: 8:16:22 time: 0.5639 data_time: 0.0527 memory: 23504 grad_norm: 2.8818 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.6795 loss: 1.6795 2022/09/08 12:34:58 - mmengine - INFO - Epoch(train) [10][700/1253] lr: 4.0000e-02 eta: 8:16:09 time: 0.5831 data_time: 0.0463 memory: 23504 grad_norm: 2.7250 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.5855 loss: 1.5855 2022/09/08 12:35:10 - mmengine - INFO - Epoch(train) [10][720/1253] lr: 4.0000e-02 eta: 8:15:59 time: 0.6002 data_time: 0.0442 memory: 23504 grad_norm: 2.7831 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.5509 loss: 1.5509 2022/09/08 12:35:11 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 12:35:22 - mmengine - INFO - Epoch(train) [10][740/1253] lr: 4.0000e-02 eta: 8:15:48 time: 0.6008 data_time: 0.0426 memory: 23504 grad_norm: 2.8673 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.6898 loss: 1.6898 2022/09/08 12:35:33 - mmengine - INFO - Epoch(train) [10][760/1253] lr: 4.0000e-02 eta: 8:15:34 time: 0.5627 data_time: 0.0574 memory: 23504 grad_norm: 2.9345 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.6161 loss: 1.6161 2022/09/08 12:35:45 - mmengine - INFO - Epoch(train) [10][780/1253] lr: 4.0000e-02 eta: 8:15:22 time: 0.5848 data_time: 0.0669 memory: 23504 grad_norm: 2.7599 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6529 loss: 1.6529 2022/09/08 12:35:56 - mmengine - INFO - Epoch(train) [10][800/1253] lr: 4.0000e-02 eta: 8:15:08 time: 0.5624 data_time: 0.0474 memory: 23504 grad_norm: 2.7605 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6768 loss: 1.6768 2022/09/08 12:36:08 - mmengine - INFO - Epoch(train) [10][820/1253] lr: 4.0000e-02 eta: 8:14:57 time: 0.5957 data_time: 0.0476 memory: 23504 grad_norm: 2.8363 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 1.5986 loss: 1.5986 2022/09/08 12:36:19 - mmengine - INFO - Epoch(train) [10][840/1253] lr: 4.0000e-02 eta: 8:14:42 time: 0.5483 data_time: 0.0465 memory: 23504 grad_norm: 2.8102 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.8239 loss: 1.8239 2022/09/08 12:36:30 - mmengine - INFO - Epoch(train) [10][860/1253] lr: 4.0000e-02 eta: 8:14:29 time: 0.5731 data_time: 0.0490 memory: 23504 grad_norm: 2.8042 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.7384 loss: 1.7384 2022/09/08 12:36:42 - mmengine - INFO - Epoch(train) [10][880/1253] lr: 4.0000e-02 eta: 8:14:18 time: 0.5876 data_time: 0.0431 memory: 23504 grad_norm: 2.8896 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.7932 loss: 1.7932 2022/09/08 12:36:56 - mmengine - INFO - Epoch(train) [10][900/1253] lr: 4.0000e-02 eta: 8:14:16 time: 0.7126 data_time: 0.0454 memory: 23504 grad_norm: 2.9398 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.6253 loss: 1.6253 2022/09/08 12:37:07 - mmengine - INFO - Epoch(train) [10][920/1253] lr: 4.0000e-02 eta: 8:14:01 time: 0.5492 data_time: 0.0388 memory: 23504 grad_norm: 2.8594 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.6280 loss: 1.6280 2022/09/08 12:37:18 - mmengine - INFO - Epoch(train) [10][940/1253] lr: 4.0000e-02 eta: 8:13:46 time: 0.5407 data_time: 0.0461 memory: 23504 grad_norm: 2.7755 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7234 loss: 1.7234 2022/09/08 12:37:29 - mmengine - INFO - Epoch(train) [10][960/1253] lr: 4.0000e-02 eta: 8:13:32 time: 0.5597 data_time: 0.0479 memory: 23504 grad_norm: 2.8164 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.7614 loss: 1.7614 2022/09/08 12:37:41 - mmengine - INFO - Epoch(train) [10][980/1253] lr: 4.0000e-02 eta: 8:13:20 time: 0.5891 data_time: 0.0750 memory: 23504 grad_norm: 2.8204 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8087 loss: 1.8087 2022/09/08 12:37:52 - mmengine - INFO - Epoch(train) [10][1000/1253] lr: 4.0000e-02 eta: 8:13:06 time: 0.5535 data_time: 0.0507 memory: 23504 grad_norm: 2.8077 top1_acc: 0.5000 top5_acc: 0.9167 loss_cls: 1.6185 loss: 1.6185 2022/09/08 12:38:03 - mmengine - INFO - Epoch(train) [10][1020/1253] lr: 4.0000e-02 eta: 8:12:52 time: 0.5611 data_time: 0.0498 memory: 23504 grad_norm: 2.8846 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.8562 loss: 1.8562 2022/09/08 12:38:15 - mmengine - INFO - Epoch(train) [10][1040/1253] lr: 4.0000e-02 eta: 8:12:38 time: 0.5653 data_time: 0.0520 memory: 23504 grad_norm: 2.8470 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.6929 loss: 1.6929 2022/09/08 12:38:27 - mmengine - INFO - Epoch(train) [10][1060/1253] lr: 4.0000e-02 eta: 8:12:27 time: 0.5936 data_time: 0.0518 memory: 23504 grad_norm: 2.7582 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.5580 loss: 1.5580 2022/09/08 12:38:38 - mmengine - INFO - Epoch(train) [10][1080/1253] lr: 4.0000e-02 eta: 8:12:13 time: 0.5576 data_time: 0.0407 memory: 23504 grad_norm: 2.7906 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.6511 loss: 1.6511 2022/09/08 12:38:51 - mmengine - INFO - Epoch(train) [10][1100/1253] lr: 4.0000e-02 eta: 8:12:06 time: 0.6522 data_time: 0.0524 memory: 23504 grad_norm: 2.7995 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6839 loss: 1.6839 2022/09/08 12:39:02 - mmengine - INFO - Epoch(train) [10][1120/1253] lr: 4.0000e-02 eta: 8:11:52 time: 0.5594 data_time: 0.0475 memory: 23504 grad_norm: 2.7692 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.6785 loss: 1.6785 2022/09/08 12:39:14 - mmengine - INFO - Epoch(train) [10][1140/1253] lr: 4.0000e-02 eta: 8:11:41 time: 0.5873 data_time: 0.0470 memory: 23504 grad_norm: 2.7903 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.8353 loss: 1.8353 2022/09/08 12:39:25 - mmengine - INFO - Epoch(train) [10][1160/1253] lr: 4.0000e-02 eta: 8:11:29 time: 0.5842 data_time: 0.0458 memory: 23504 grad_norm: 2.8621 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.7102 loss: 1.7102 2022/09/08 12:39:38 - mmengine - INFO - Epoch(train) [10][1180/1253] lr: 4.0000e-02 eta: 8:11:20 time: 0.6213 data_time: 0.0748 memory: 23504 grad_norm: 2.8580 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7122 loss: 1.7122 2022/09/08 12:39:50 - mmengine - INFO - Epoch(train) [10][1200/1253] lr: 4.0000e-02 eta: 8:11:08 time: 0.5865 data_time: 0.0358 memory: 23504 grad_norm: 2.7485 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.8170 loss: 1.8170 2022/09/08 12:40:01 - mmengine - INFO - Epoch(train) [10][1220/1253] lr: 4.0000e-02 eta: 8:10:56 time: 0.5866 data_time: 0.0466 memory: 23504 grad_norm: 2.7809 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.8436 loss: 1.8436 2022/09/08 12:40:11 - mmengine - INFO - Epoch(train) [10][1240/1253] lr: 4.0000e-02 eta: 8:10:38 time: 0.5058 data_time: 0.0210 memory: 23504 grad_norm: 2.8031 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 1.7274 loss: 1.7274 2022/09/08 12:40:17 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 12:40:17 - mmengine - INFO - Epoch(train) [10][1253/1253] lr: 4.0000e-02 eta: 8:10:38 time: 0.4485 data_time: 0.0202 memory: 23504 grad_norm: 2.9349 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.6334 loss: 1.6334 2022/09/08 12:40:39 - mmengine - INFO - Epoch(val) [10][20/104] eta: 0:01:32 time: 1.1020 data_time: 0.9552 memory: 2699 2022/09/08 12:40:51 - mmengine - INFO - Epoch(val) [10][40/104] eta: 0:00:39 time: 0.6151 data_time: 0.4706 memory: 2699 2022/09/08 12:41:02 - mmengine - INFO - Epoch(val) [10][60/104] eta: 0:00:23 time: 0.5256 data_time: 0.3822 memory: 2699 2022/09/08 12:41:11 - mmengine - INFO - Epoch(val) [10][80/104] eta: 0:00:11 time: 0.4671 data_time: 0.2716 memory: 2699 2022/09/08 12:41:23 - mmengine - INFO - Epoch(val) [10][100/104] eta: 0:00:02 time: 0.5747 data_time: 0.4554 memory: 2699 2022/09/08 12:41:30 - mmengine - INFO - Epoch(val) [10][104/104] acc/top1: 0.5971 acc/top5: 0.8323 acc/mean1: 0.5971 2022/09/08 12:41:30 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb/best_acc/top1_epoch_5.pth is removed 2022/09/08 12:41:31 - mmengine - INFO - The best checkpoint with 0.5971 acc/top1 at 10 epoch is saved to best_acc/top1_epoch_10.pth. 2022/09/08 12:41:54 - mmengine - INFO - Epoch(train) [11][20/1253] lr: 4.0000e-02 eta: 8:10:31 time: 1.1261 data_time: 0.4704 memory: 23504 grad_norm: 2.8664 top1_acc: 0.6250 top5_acc: 0.7083 loss_cls: 1.6074 loss: 1.6074 2022/09/08 12:42:05 - mmengine - INFO - Epoch(train) [11][40/1253] lr: 4.0000e-02 eta: 8:10:15 time: 0.5357 data_time: 0.0330 memory: 23504 grad_norm: 2.7826 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.4412 loss: 1.4412 2022/09/08 12:42:16 - mmengine - INFO - Epoch(train) [11][60/1253] lr: 4.0000e-02 eta: 8:10:01 time: 0.5556 data_time: 0.0379 memory: 23504 grad_norm: 2.7955 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7586 loss: 1.7586 2022/09/08 12:42:27 - mmengine - INFO - Epoch(train) [11][80/1253] lr: 4.0000e-02 eta: 8:09:49 time: 0.5871 data_time: 0.0552 memory: 23504 grad_norm: 2.9033 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.6500 loss: 1.6500 2022/09/08 12:42:40 - mmengine - INFO - Epoch(train) [11][100/1253] lr: 4.0000e-02 eta: 8:09:40 time: 0.6225 data_time: 0.0756 memory: 23504 grad_norm: 2.8027 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.6213 loss: 1.6213 2022/09/08 12:42:52 - mmengine - INFO - Epoch(train) [11][120/1253] lr: 4.0000e-02 eta: 8:09:30 time: 0.6047 data_time: 0.0657 memory: 23504 grad_norm: 2.7876 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.7512 loss: 1.7512 2022/09/08 12:43:07 - mmengine - INFO - Epoch(train) [11][140/1253] lr: 4.0000e-02 eta: 8:09:31 time: 0.7598 data_time: 0.2478 memory: 23504 grad_norm: 2.8079 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.6396 loss: 1.6396 2022/09/08 12:43:18 - mmengine - INFO - Epoch(train) [11][160/1253] lr: 4.0000e-02 eta: 8:09:17 time: 0.5499 data_time: 0.0191 memory: 23504 grad_norm: 2.9050 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.7585 loss: 1.7585 2022/09/08 12:43:30 - mmengine - INFO - Epoch(train) [11][180/1253] lr: 4.0000e-02 eta: 8:09:04 time: 0.5699 data_time: 0.0424 memory: 23504 grad_norm: 2.8939 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6852 loss: 1.6852 2022/09/08 12:43:41 - mmengine - INFO - Epoch(train) [11][200/1253] lr: 4.0000e-02 eta: 8:08:50 time: 0.5598 data_time: 0.0424 memory: 23504 grad_norm: 2.8725 top1_acc: 0.5833 top5_acc: 0.6667 loss_cls: 1.6538 loss: 1.6538 2022/09/08 12:43:52 - mmengine - INFO - Epoch(train) [11][220/1253] lr: 4.0000e-02 eta: 8:08:36 time: 0.5653 data_time: 0.0398 memory: 23504 grad_norm: 2.8484 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.4752 loss: 1.4752 2022/09/08 12:44:04 - mmengine - INFO - Epoch(train) [11][240/1253] lr: 4.0000e-02 eta: 8:08:23 time: 0.5744 data_time: 0.0441 memory: 23504 grad_norm: 2.8474 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6191 loss: 1.6191 2022/09/08 12:44:15 - mmengine - INFO - Epoch(train) [11][260/1253] lr: 4.0000e-02 eta: 8:08:10 time: 0.5728 data_time: 0.0463 memory: 23504 grad_norm: 2.8709 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.7031 loss: 1.7031 2022/09/08 12:44:27 - mmengine - INFO - Epoch(train) [11][280/1253] lr: 4.0000e-02 eta: 8:07:58 time: 0.5845 data_time: 0.0517 memory: 23504 grad_norm: 2.8533 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6677 loss: 1.6677 2022/09/08 12:44:38 - mmengine - INFO - Epoch(train) [11][300/1253] lr: 4.0000e-02 eta: 8:07:45 time: 0.5710 data_time: 0.0361 memory: 23504 grad_norm: 2.8451 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.6347 loss: 1.6347 2022/09/08 12:44:50 - mmengine - INFO - Epoch(train) [11][320/1253] lr: 4.0000e-02 eta: 8:07:33 time: 0.5729 data_time: 0.0332 memory: 23504 grad_norm: 2.8833 top1_acc: 0.6667 top5_acc: 0.7500 loss_cls: 1.6701 loss: 1.6701 2022/09/08 12:45:01 - mmengine - INFO - Epoch(train) [11][340/1253] lr: 4.0000e-02 eta: 8:07:21 time: 0.5886 data_time: 0.0543 memory: 23504 grad_norm: 2.8726 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.7254 loss: 1.7254 2022/09/08 12:45:13 - mmengine - INFO - Epoch(train) [11][360/1253] lr: 4.0000e-02 eta: 8:07:07 time: 0.5653 data_time: 0.0389 memory: 23504 grad_norm: 2.7675 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.6406 loss: 1.6406 2022/09/08 12:45:24 - mmengine - INFO - Epoch(train) [11][380/1253] lr: 4.0000e-02 eta: 8:06:55 time: 0.5753 data_time: 0.0400 memory: 23504 grad_norm: 2.7718 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6331 loss: 1.6331 2022/09/08 12:45:36 - mmengine - INFO - Epoch(train) [11][400/1253] lr: 4.0000e-02 eta: 8:06:42 time: 0.5675 data_time: 0.0471 memory: 23504 grad_norm: 2.9511 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 1.7403 loss: 1.7403 2022/09/08 12:45:47 - mmengine - INFO - Epoch(train) [11][420/1253] lr: 4.0000e-02 eta: 8:06:29 time: 0.5751 data_time: 0.0491 memory: 23504 grad_norm: 2.7710 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6861 loss: 1.6861 2022/09/08 12:46:00 - mmengine - INFO - Epoch(train) [11][440/1253] lr: 4.0000e-02 eta: 8:06:21 time: 0.6400 data_time: 0.0420 memory: 23504 grad_norm: 2.7726 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.5935 loss: 1.5935 2022/09/08 12:46:12 - mmengine - INFO - Epoch(train) [11][460/1253] lr: 4.0000e-02 eta: 8:06:10 time: 0.5889 data_time: 0.0458 memory: 23504 grad_norm: 2.8425 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6956 loss: 1.6956 2022/09/08 12:46:17 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 12:46:23 - mmengine - INFO - Epoch(train) [11][480/1253] lr: 4.0000e-02 eta: 8:05:57 time: 0.5724 data_time: 0.0441 memory: 23504 grad_norm: 2.8250 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.6722 loss: 1.6722 2022/09/08 12:46:34 - mmengine - INFO - Epoch(train) [11][500/1253] lr: 4.0000e-02 eta: 8:05:43 time: 0.5614 data_time: 0.0321 memory: 23504 grad_norm: 2.8176 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.8131 loss: 1.8131 2022/09/08 12:46:46 - mmengine - INFO - Epoch(train) [11][520/1253] lr: 4.0000e-02 eta: 8:05:30 time: 0.5680 data_time: 0.0443 memory: 23504 grad_norm: 2.8311 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 1.6492 loss: 1.6492 2022/09/08 12:46:57 - mmengine - INFO - Epoch(train) [11][540/1253] lr: 4.0000e-02 eta: 8:05:16 time: 0.5662 data_time: 0.0498 memory: 23504 grad_norm: 2.7861 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7524 loss: 1.7524 2022/09/08 12:47:09 - mmengine - INFO - Epoch(train) [11][560/1253] lr: 4.0000e-02 eta: 8:05:04 time: 0.5848 data_time: 0.0390 memory: 23504 grad_norm: 2.8215 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.6853 loss: 1.6853 2022/09/08 12:47:21 - mmengine - INFO - Epoch(train) [11][580/1253] lr: 4.0000e-02 eta: 8:04:53 time: 0.5926 data_time: 0.0441 memory: 23504 grad_norm: 2.8789 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.6259 loss: 1.6259 2022/09/08 12:47:33 - mmengine - INFO - Epoch(train) [11][600/1253] lr: 4.0000e-02 eta: 8:04:42 time: 0.6022 data_time: 0.0397 memory: 23504 grad_norm: 2.7419 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4600 loss: 1.4600 2022/09/08 12:47:44 - mmengine - INFO - Epoch(train) [11][620/1253] lr: 4.0000e-02 eta: 8:04:29 time: 0.5674 data_time: 0.0520 memory: 23504 grad_norm: 2.8003 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.5255 loss: 1.5255 2022/09/08 12:47:55 - mmengine - INFO - Epoch(train) [11][640/1253] lr: 4.0000e-02 eta: 8:04:16 time: 0.5720 data_time: 0.0425 memory: 23504 grad_norm: 2.8412 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.6241 loss: 1.6241 2022/09/08 12:48:07 - mmengine - INFO - Epoch(train) [11][660/1253] lr: 4.0000e-02 eta: 8:04:04 time: 0.5750 data_time: 0.0483 memory: 23504 grad_norm: 2.8135 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 1.6161 loss: 1.6161 2022/09/08 12:48:18 - mmengine - INFO - Epoch(train) [11][680/1253] lr: 4.0000e-02 eta: 8:03:51 time: 0.5721 data_time: 0.0492 memory: 23504 grad_norm: 2.8889 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.6351 loss: 1.6351 2022/09/08 12:48:30 - mmengine - INFO - Epoch(train) [11][700/1253] lr: 4.0000e-02 eta: 8:03:39 time: 0.5853 data_time: 0.0406 memory: 23504 grad_norm: 2.8649 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.6189 loss: 1.6189 2022/09/08 12:48:41 - mmengine - INFO - Epoch(train) [11][720/1253] lr: 4.0000e-02 eta: 8:03:25 time: 0.5636 data_time: 0.0434 memory: 23504 grad_norm: 2.8732 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.7419 loss: 1.7419 2022/09/08 12:48:52 - mmengine - INFO - Epoch(train) [11][740/1253] lr: 4.0000e-02 eta: 8:03:11 time: 0.5577 data_time: 0.0475 memory: 23504 grad_norm: 2.8244 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7704 loss: 1.7704 2022/09/08 12:49:04 - mmengine - INFO - Epoch(train) [11][760/1253] lr: 4.0000e-02 eta: 8:02:59 time: 0.5813 data_time: 0.0512 memory: 23504 grad_norm: 2.8512 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7028 loss: 1.7028 2022/09/08 12:49:16 - mmengine - INFO - Epoch(train) [11][780/1253] lr: 4.0000e-02 eta: 8:02:49 time: 0.6125 data_time: 0.0768 memory: 23504 grad_norm: 2.8617 top1_acc: 0.5000 top5_acc: 0.9583 loss_cls: 1.8178 loss: 1.8178 2022/09/08 12:49:28 - mmengine - INFO - Epoch(train) [11][800/1253] lr: 4.0000e-02 eta: 8:02:38 time: 0.5940 data_time: 0.0395 memory: 23504 grad_norm: 2.7957 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.7903 loss: 1.7903 2022/09/08 12:49:40 - mmengine - INFO - Epoch(train) [11][820/1253] lr: 4.0000e-02 eta: 8:02:25 time: 0.5716 data_time: 0.0362 memory: 23504 grad_norm: 2.8169 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8073 loss: 1.8073 2022/09/08 12:49:52 - mmengine - INFO - Epoch(train) [11][840/1253] lr: 4.0000e-02 eta: 8:02:16 time: 0.6261 data_time: 0.0359 memory: 23504 grad_norm: 2.8336 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.8424 loss: 1.8424 2022/09/08 12:50:03 - mmengine - INFO - Epoch(train) [11][860/1253] lr: 4.0000e-02 eta: 8:02:03 time: 0.5625 data_time: 0.0377 memory: 23504 grad_norm: 2.7866 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.7931 loss: 1.7931 2022/09/08 12:50:15 - mmengine - INFO - Epoch(train) [11][880/1253] lr: 4.0000e-02 eta: 8:01:50 time: 0.5773 data_time: 0.0743 memory: 23504 grad_norm: 2.8125 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.8566 loss: 1.8566 2022/09/08 12:50:29 - mmengine - INFO - Epoch(train) [11][900/1253] lr: 4.0000e-02 eta: 8:01:47 time: 0.7031 data_time: 0.0306 memory: 23504 grad_norm: 2.7748 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.7238 loss: 1.7238 2022/09/08 12:50:40 - mmengine - INFO - Epoch(train) [11][920/1253] lr: 4.0000e-02 eta: 8:01:33 time: 0.5496 data_time: 0.0477 memory: 23504 grad_norm: 2.7708 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.6648 loss: 1.6648 2022/09/08 12:50:51 - mmengine - INFO - Epoch(train) [11][940/1253] lr: 4.0000e-02 eta: 8:01:18 time: 0.5526 data_time: 0.0360 memory: 23504 grad_norm: 2.8656 top1_acc: 0.3750 top5_acc: 0.7917 loss_cls: 1.7766 loss: 1.7766 2022/09/08 12:51:02 - mmengine - INFO - Epoch(train) [11][960/1253] lr: 4.0000e-02 eta: 8:01:04 time: 0.5580 data_time: 0.0527 memory: 23504 grad_norm: 2.8915 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6442 loss: 1.6442 2022/09/08 12:51:14 - mmengine - INFO - Epoch(train) [11][980/1253] lr: 4.0000e-02 eta: 8:00:51 time: 0.5662 data_time: 0.0434 memory: 23504 grad_norm: 2.8748 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.7059 loss: 1.7059 2022/09/08 12:51:26 - mmengine - INFO - Epoch(train) [11][1000/1253] lr: 4.0000e-02 eta: 8:00:40 time: 0.5982 data_time: 0.0506 memory: 23504 grad_norm: 2.8857 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.5280 loss: 1.5280 2022/09/08 12:51:37 - mmengine - INFO - Epoch(train) [11][1020/1253] lr: 4.0000e-02 eta: 8:00:26 time: 0.5533 data_time: 0.0479 memory: 23504 grad_norm: 2.8482 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.5466 loss: 1.5466 2022/09/08 12:51:48 - mmengine - INFO - Epoch(train) [11][1040/1253] lr: 4.0000e-02 eta: 8:00:12 time: 0.5542 data_time: 0.0409 memory: 23504 grad_norm: 2.8472 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.7207 loss: 1.7207 2022/09/08 12:51:58 - mmengine - INFO - Epoch(train) [11][1060/1253] lr: 4.0000e-02 eta: 7:59:57 time: 0.5394 data_time: 0.0469 memory: 23504 grad_norm: 2.8204 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.6227 loss: 1.6227 2022/09/08 12:52:11 - mmengine - INFO - Epoch(train) [11][1080/1253] lr: 4.0000e-02 eta: 7:59:48 time: 0.6339 data_time: 0.0436 memory: 23504 grad_norm: 2.7930 top1_acc: 0.5833 top5_acc: 0.9583 loss_cls: 1.5777 loss: 1.5777 2022/09/08 12:52:22 - mmengine - INFO - Epoch(train) [11][1100/1253] lr: 4.0000e-02 eta: 7:59:34 time: 0.5559 data_time: 0.0461 memory: 23504 grad_norm: 2.8721 top1_acc: 0.3333 top5_acc: 0.7500 loss_cls: 1.8987 loss: 1.8987 2022/09/08 12:52:35 - mmengine - INFO - Epoch(train) [11][1120/1253] lr: 4.0000e-02 eta: 7:59:27 time: 0.6463 data_time: 0.0417 memory: 23504 grad_norm: 2.7502 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.7254 loss: 1.7254 2022/09/08 12:52:47 - mmengine - INFO - Epoch(train) [11][1140/1253] lr: 4.0000e-02 eta: 7:59:17 time: 0.6133 data_time: 0.0357 memory: 23504 grad_norm: 2.7634 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.7151 loss: 1.7151 2022/09/08 12:52:59 - mmengine - INFO - Epoch(train) [11][1160/1253] lr: 4.0000e-02 eta: 7:59:05 time: 0.5782 data_time: 0.0370 memory: 23504 grad_norm: 2.7665 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.7655 loss: 1.7655 2022/09/08 12:53:11 - mmengine - INFO - Epoch(train) [11][1180/1253] lr: 4.0000e-02 eta: 7:58:53 time: 0.5936 data_time: 0.0473 memory: 23504 grad_norm: 2.7584 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7184 loss: 1.7184 2022/09/08 12:53:25 - mmengine - INFO - Epoch(train) [11][1200/1253] lr: 4.0000e-02 eta: 7:58:50 time: 0.7092 data_time: 0.0392 memory: 23504 grad_norm: 2.7928 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6963 loss: 1.6963 2022/09/08 12:53:36 - mmengine - INFO - Epoch(train) [11][1220/1253] lr: 4.0000e-02 eta: 7:58:35 time: 0.5407 data_time: 0.0345 memory: 23504 grad_norm: 2.8116 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.7921 loss: 1.7921 2022/09/08 12:53:47 - mmengine - INFO - Epoch(train) [11][1240/1253] lr: 4.0000e-02 eta: 7:58:20 time: 0.5315 data_time: 0.0250 memory: 23504 grad_norm: 2.7844 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.4941 loss: 1.4941 2022/09/08 12:53:52 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 12:53:52 - mmengine - INFO - Epoch(train) [11][1253/1253] lr: 4.0000e-02 eta: 7:58:20 time: 0.4373 data_time: 0.0191 memory: 23504 grad_norm: 2.9751 top1_acc: 0.4286 top5_acc: 0.5714 loss_cls: 1.6388 loss: 1.6388 2022/09/08 12:54:17 - mmengine - INFO - Epoch(train) [12][20/1253] lr: 4.0000e-02 eta: 7:58:19 time: 1.2381 data_time: 0.5795 memory: 23504 grad_norm: 2.8055 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6823 loss: 1.6823 2022/09/08 12:54:28 - mmengine - INFO - Epoch(train) [12][40/1253] lr: 4.0000e-02 eta: 7:58:06 time: 0.5660 data_time: 0.0347 memory: 23504 grad_norm: 2.7511 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.5162 loss: 1.5162 2022/09/08 12:54:39 - mmengine - INFO - Epoch(train) [12][60/1253] lr: 4.0000e-02 eta: 7:57:51 time: 0.5355 data_time: 0.0354 memory: 23504 grad_norm: 2.7859 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.4797 loss: 1.4797 2022/09/08 12:54:50 - mmengine - INFO - Epoch(train) [12][80/1253] lr: 4.0000e-02 eta: 7:57:37 time: 0.5563 data_time: 0.0395 memory: 23504 grad_norm: 2.9159 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5646 loss: 1.5646 2022/09/08 12:55:02 - mmengine - INFO - Epoch(train) [12][100/1253] lr: 4.0000e-02 eta: 7:57:26 time: 0.5976 data_time: 0.0594 memory: 23504 grad_norm: 2.8004 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.6795 loss: 1.6795 2022/09/08 12:55:13 - mmengine - INFO - Epoch(train) [12][120/1253] lr: 4.0000e-02 eta: 7:57:12 time: 0.5622 data_time: 0.0348 memory: 23504 grad_norm: 2.8471 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.7048 loss: 1.7048 2022/09/08 12:55:27 - mmengine - INFO - Epoch(train) [12][140/1253] lr: 4.0000e-02 eta: 7:57:07 time: 0.6753 data_time: 0.1342 memory: 23504 grad_norm: 2.8166 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6698 loss: 1.6698 2022/09/08 12:55:38 - mmengine - INFO - Epoch(train) [12][160/1253] lr: 4.0000e-02 eta: 7:56:54 time: 0.5720 data_time: 0.0475 memory: 23504 grad_norm: 2.8064 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7273 loss: 1.7273 2022/09/08 12:55:50 - mmengine - INFO - Epoch(train) [12][180/1253] lr: 4.0000e-02 eta: 7:56:42 time: 0.5887 data_time: 0.0463 memory: 23504 grad_norm: 2.8060 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.6214 loss: 1.6214 2022/09/08 12:56:01 - mmengine - INFO - Epoch(train) [12][200/1253] lr: 4.0000e-02 eta: 7:56:27 time: 0.5467 data_time: 0.0320 memory: 23504 grad_norm: 2.8789 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.5672 loss: 1.5672 2022/09/08 12:56:11 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 12:56:14 - mmengine - INFO - Epoch(train) [12][220/1253] lr: 4.0000e-02 eta: 7:56:18 time: 0.6209 data_time: 0.0758 memory: 23504 grad_norm: 2.8047 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.7859 loss: 1.7859 2022/09/08 12:56:25 - mmengine - INFO - Epoch(train) [12][240/1253] lr: 4.0000e-02 eta: 7:56:06 time: 0.5872 data_time: 0.0689 memory: 23504 grad_norm: 2.8037 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6227 loss: 1.6227 2022/09/08 12:56:36 - mmengine - INFO - Epoch(train) [12][260/1253] lr: 4.0000e-02 eta: 7:55:52 time: 0.5540 data_time: 0.0360 memory: 23504 grad_norm: 2.8199 top1_acc: 0.5000 top5_acc: 0.9167 loss_cls: 1.6676 loss: 1.6676 2022/09/08 12:56:48 - mmengine - INFO - Epoch(train) [12][280/1253] lr: 4.0000e-02 eta: 7:55:39 time: 0.5621 data_time: 0.0454 memory: 23504 grad_norm: 2.8574 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.8528 loss: 1.8528 2022/09/08 12:56:59 - mmengine - INFO - Epoch(train) [12][300/1253] lr: 4.0000e-02 eta: 7:55:27 time: 0.5834 data_time: 0.0561 memory: 23504 grad_norm: 2.8332 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 1.8439 loss: 1.8439 2022/09/08 12:57:11 - mmengine - INFO - Epoch(train) [12][320/1253] lr: 4.0000e-02 eta: 7:55:16 time: 0.6070 data_time: 0.0413 memory: 23504 grad_norm: 2.8733 top1_acc: 0.5417 top5_acc: 0.6667 loss_cls: 1.6231 loss: 1.6231 2022/09/08 12:57:23 - mmengine - INFO - Epoch(train) [12][340/1253] lr: 4.0000e-02 eta: 7:55:03 time: 0.5655 data_time: 0.0367 memory: 23504 grad_norm: 2.8148 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.7121 loss: 1.7121 2022/09/08 12:57:34 - mmengine - INFO - Epoch(train) [12][360/1253] lr: 4.0000e-02 eta: 7:54:50 time: 0.5637 data_time: 0.0403 memory: 23504 grad_norm: 2.8336 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.5550 loss: 1.5550 2022/09/08 12:57:46 - mmengine - INFO - Epoch(train) [12][380/1253] lr: 4.0000e-02 eta: 7:54:39 time: 0.6075 data_time: 0.0561 memory: 23504 grad_norm: 2.7550 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.5908 loss: 1.5908 2022/09/08 12:57:58 - mmengine - INFO - Epoch(train) [12][400/1253] lr: 4.0000e-02 eta: 7:54:27 time: 0.5776 data_time: 0.0335 memory: 23504 grad_norm: 2.8431 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.5884 loss: 1.5884 2022/09/08 12:58:09 - mmengine - INFO - Epoch(train) [12][420/1253] lr: 4.0000e-02 eta: 7:54:15 time: 0.5793 data_time: 0.0373 memory: 23504 grad_norm: 2.8072 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.5833 loss: 1.5833 2022/09/08 12:58:21 - mmengine - INFO - Epoch(train) [12][440/1253] lr: 4.0000e-02 eta: 7:54:02 time: 0.5687 data_time: 0.0451 memory: 23504 grad_norm: 2.8979 top1_acc: 0.5417 top5_acc: 0.6250 loss_cls: 1.7703 loss: 1.7703 2022/09/08 12:58:33 - mmengine - INFO - Epoch(train) [12][460/1253] lr: 4.0000e-02 eta: 7:53:51 time: 0.6113 data_time: 0.0520 memory: 23504 grad_norm: 2.8603 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.7092 loss: 1.7092 2022/09/08 12:58:44 - mmengine - INFO - Epoch(train) [12][480/1253] lr: 4.0000e-02 eta: 7:53:37 time: 0.5457 data_time: 0.0314 memory: 23504 grad_norm: 2.8625 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6089 loss: 1.6089 2022/09/08 12:58:55 - mmengine - INFO - Epoch(train) [12][500/1253] lr: 4.0000e-02 eta: 7:53:24 time: 0.5775 data_time: 0.0602 memory: 23504 grad_norm: 2.8737 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 1.6043 loss: 1.6043 2022/09/08 12:59:06 - mmengine - INFO - Epoch(train) [12][520/1253] lr: 4.0000e-02 eta: 7:53:11 time: 0.5606 data_time: 0.0440 memory: 23504 grad_norm: 2.8829 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.6521 loss: 1.6521 2022/09/08 12:59:18 - mmengine - INFO - Epoch(train) [12][540/1253] lr: 4.0000e-02 eta: 7:52:59 time: 0.5906 data_time: 0.0397 memory: 23504 grad_norm: 2.8936 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.5038 loss: 1.5038 2022/09/08 12:59:30 - mmengine - INFO - Epoch(train) [12][560/1253] lr: 4.0000e-02 eta: 7:52:48 time: 0.5875 data_time: 0.0490 memory: 23504 grad_norm: 2.9095 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8035 loss: 1.8035 2022/09/08 12:59:44 - mmengine - INFO - Epoch(train) [12][580/1253] lr: 4.0000e-02 eta: 7:52:42 time: 0.6838 data_time: 0.0375 memory: 23504 grad_norm: 2.8121 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7896 loss: 1.7896 2022/09/08 12:59:55 - mmengine - INFO - Epoch(train) [12][600/1253] lr: 4.0000e-02 eta: 7:52:28 time: 0.5451 data_time: 0.0305 memory: 23504 grad_norm: 2.8141 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.6220 loss: 1.6220 2022/09/08 13:00:06 - mmengine - INFO - Epoch(train) [12][620/1253] lr: 4.0000e-02 eta: 7:52:15 time: 0.5700 data_time: 0.0383 memory: 23504 grad_norm: 2.8530 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.5285 loss: 1.5285 2022/09/08 13:00:18 - mmengine - INFO - Epoch(train) [12][640/1253] lr: 4.0000e-02 eta: 7:52:03 time: 0.5794 data_time: 0.0725 memory: 23504 grad_norm: 2.8684 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.7671 loss: 1.7671 2022/09/08 13:00:29 - mmengine - INFO - Epoch(train) [12][660/1253] lr: 4.0000e-02 eta: 7:51:48 time: 0.5487 data_time: 0.0412 memory: 23504 grad_norm: 2.8491 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.5368 loss: 1.5368 2022/09/08 13:00:40 - mmengine - INFO - Epoch(train) [12][680/1253] lr: 4.0000e-02 eta: 7:51:35 time: 0.5611 data_time: 0.0556 memory: 23504 grad_norm: 2.8176 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6506 loss: 1.6506 2022/09/08 13:00:51 - mmengine - INFO - Epoch(train) [12][700/1253] lr: 4.0000e-02 eta: 7:51:21 time: 0.5530 data_time: 0.0439 memory: 23504 grad_norm: 2.8328 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.6680 loss: 1.6680 2022/09/08 13:01:02 - mmengine - INFO - Epoch(train) [12][720/1253] lr: 4.0000e-02 eta: 7:51:07 time: 0.5613 data_time: 0.0485 memory: 23504 grad_norm: 2.8318 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.6996 loss: 1.6996 2022/09/08 13:01:13 - mmengine - INFO - Epoch(train) [12][740/1253] lr: 4.0000e-02 eta: 7:50:54 time: 0.5673 data_time: 0.0530 memory: 23504 grad_norm: 2.9399 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.6843 loss: 1.6843 2022/09/08 13:01:25 - mmengine - INFO - Epoch(train) [12][760/1253] lr: 4.0000e-02 eta: 7:50:43 time: 0.5920 data_time: 0.0382 memory: 23504 grad_norm: 2.7803 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.6693 loss: 1.6693 2022/09/08 13:01:38 - mmengine - INFO - Epoch(train) [12][780/1253] lr: 4.0000e-02 eta: 7:50:34 time: 0.6248 data_time: 0.0947 memory: 23504 grad_norm: 2.8562 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.8349 loss: 1.8349 2022/09/08 13:01:49 - mmengine - INFO - Epoch(train) [12][800/1253] lr: 4.0000e-02 eta: 7:50:20 time: 0.5581 data_time: 0.0391 memory: 23504 grad_norm: 2.7739 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.5835 loss: 1.5835 2022/09/08 13:02:00 - mmengine - INFO - Epoch(train) [12][820/1253] lr: 4.0000e-02 eta: 7:50:07 time: 0.5709 data_time: 0.0403 memory: 23504 grad_norm: 2.8048 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6820 loss: 1.6820 2022/09/08 13:02:13 - mmengine - INFO - Epoch(train) [12][840/1253] lr: 4.0000e-02 eta: 7:49:57 time: 0.6111 data_time: 0.0903 memory: 23504 grad_norm: 2.8563 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 1.7528 loss: 1.7528 2022/09/08 13:02:27 - mmengine - INFO - Epoch(train) [12][860/1253] lr: 4.0000e-02 eta: 7:49:52 time: 0.6941 data_time: 0.0436 memory: 23504 grad_norm: 2.7799 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.6092 loss: 1.6092 2022/09/08 13:02:37 - mmengine - INFO - Epoch(train) [12][880/1253] lr: 4.0000e-02 eta: 7:49:38 time: 0.5437 data_time: 0.0349 memory: 23504 grad_norm: 2.7969 top1_acc: 0.7083 top5_acc: 1.0000 loss_cls: 1.4974 loss: 1.4974 2022/09/08 13:02:49 - mmengine - INFO - Epoch(train) [12][900/1253] lr: 4.0000e-02 eta: 7:49:26 time: 0.5881 data_time: 0.0380 memory: 23504 grad_norm: 2.8305 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.7355 loss: 1.7355 2022/09/08 13:03:00 - mmengine - INFO - Epoch(train) [12][920/1253] lr: 4.0000e-02 eta: 7:49:12 time: 0.5463 data_time: 0.0376 memory: 23504 grad_norm: 2.7585 top1_acc: 0.6250 top5_acc: 0.7083 loss_cls: 1.6948 loss: 1.6948 2022/09/08 13:03:12 - mmengine - INFO - Epoch(train) [12][940/1253] lr: 4.0000e-02 eta: 7:49:00 time: 0.5836 data_time: 0.0432 memory: 23504 grad_norm: 2.8344 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7725 loss: 1.7725 2022/09/08 13:03:24 - mmengine - INFO - Epoch(train) [12][960/1253] lr: 4.0000e-02 eta: 7:48:49 time: 0.6039 data_time: 0.0866 memory: 23504 grad_norm: 2.8994 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.6177 loss: 1.6177 2022/09/08 13:03:35 - mmengine - INFO - Epoch(train) [12][980/1253] lr: 4.0000e-02 eta: 7:48:37 time: 0.5807 data_time: 0.0463 memory: 23504 grad_norm: 2.9304 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.7778 loss: 1.7778 2022/09/08 13:03:46 - mmengine - INFO - Epoch(train) [12][1000/1253] lr: 4.0000e-02 eta: 7:48:22 time: 0.5425 data_time: 0.0444 memory: 23504 grad_norm: 2.8284 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.8109 loss: 1.8109 2022/09/08 13:03:57 - mmengine - INFO - Epoch(train) [12][1020/1253] lr: 4.0000e-02 eta: 7:48:08 time: 0.5459 data_time: 0.0411 memory: 23504 grad_norm: 2.7987 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.7026 loss: 1.7026 2022/09/08 13:04:08 - mmengine - INFO - Epoch(train) [12][1040/1253] lr: 4.0000e-02 eta: 7:47:54 time: 0.5613 data_time: 0.0398 memory: 23504 grad_norm: 2.9033 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.8430 loss: 1.8430 2022/09/08 13:04:19 - mmengine - INFO - Epoch(train) [12][1060/1253] lr: 4.0000e-02 eta: 7:47:40 time: 0.5461 data_time: 0.0384 memory: 23504 grad_norm: 2.7611 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.5710 loss: 1.5710 2022/09/08 13:04:31 - mmengine - INFO - Epoch(train) [12][1080/1253] lr: 4.0000e-02 eta: 7:47:27 time: 0.5732 data_time: 0.0489 memory: 23504 grad_norm: 2.8406 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.6667 loss: 1.6667 2022/09/08 13:04:42 - mmengine - INFO - Epoch(train) [12][1100/1253] lr: 4.0000e-02 eta: 7:47:15 time: 0.5799 data_time: 0.0501 memory: 23504 grad_norm: 2.8869 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.7170 loss: 1.7170 2022/09/08 13:04:53 - mmengine - INFO - Epoch(train) [12][1120/1253] lr: 4.0000e-02 eta: 7:47:01 time: 0.5515 data_time: 0.0364 memory: 23504 grad_norm: 2.8366 top1_acc: 0.4167 top5_acc: 0.8333 loss_cls: 1.7235 loss: 1.7235 2022/09/08 13:05:06 - mmengine - INFO - Epoch(train) [12][1140/1253] lr: 4.0000e-02 eta: 7:46:51 time: 0.6157 data_time: 0.0788 memory: 23504 grad_norm: 2.8601 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.8228 loss: 1.8228 2022/09/08 13:05:20 - mmengine - INFO - Epoch(train) [12][1160/1253] lr: 4.0000e-02 eta: 7:46:48 time: 0.7193 data_time: 0.2149 memory: 23504 grad_norm: 2.8014 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.7815 loss: 1.7815 2022/09/08 13:05:31 - mmengine - INFO - Epoch(train) [12][1180/1253] lr: 4.0000e-02 eta: 7:46:35 time: 0.5645 data_time: 0.0496 memory: 23504 grad_norm: 2.8142 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.7298 loss: 1.7298 2022/09/08 13:05:43 - mmengine - INFO - Epoch(train) [12][1200/1253] lr: 4.0000e-02 eta: 7:46:22 time: 0.5679 data_time: 0.0410 memory: 23504 grad_norm: 2.8101 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.6276 loss: 1.6276 2022/09/08 13:05:55 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 13:05:56 - mmengine - INFO - Epoch(train) [12][1220/1253] lr: 4.0000e-02 eta: 7:46:16 time: 0.6758 data_time: 0.1598 memory: 23504 grad_norm: 2.8353 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.6689 loss: 1.6689 2022/09/08 13:06:06 - mmengine - INFO - Epoch(train) [12][1240/1253] lr: 4.0000e-02 eta: 7:45:57 time: 0.4708 data_time: 0.0163 memory: 23504 grad_norm: 2.7814 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.6333 loss: 1.6333 2022/09/08 13:06:11 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 13:06:11 - mmengine - INFO - Epoch(train) [12][1253/1253] lr: 4.0000e-02 eta: 7:45:57 time: 0.4310 data_time: 0.0114 memory: 23504 grad_norm: 2.8759 top1_acc: 0.2857 top5_acc: 0.4286 loss_cls: 1.8993 loss: 1.8993 2022/09/08 13:06:33 - mmengine - INFO - Epoch(train) [13][20/1253] lr: 4.0000e-02 eta: 7:45:44 time: 1.0751 data_time: 0.4320 memory: 23504 grad_norm: 2.7919 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.5683 loss: 1.5683 2022/09/08 13:06:46 - mmengine - INFO - Epoch(train) [13][40/1253] lr: 4.0000e-02 eta: 7:45:37 time: 0.6647 data_time: 0.0429 memory: 23504 grad_norm: 2.7492 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6000 loss: 1.6000 2022/09/08 13:06:58 - mmengine - INFO - Epoch(train) [13][60/1253] lr: 4.0000e-02 eta: 7:45:25 time: 0.5782 data_time: 0.0357 memory: 23504 grad_norm: 2.8341 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5356 loss: 1.5356 2022/09/08 13:07:09 - mmengine - INFO - Epoch(train) [13][80/1253] lr: 4.0000e-02 eta: 7:45:11 time: 0.5482 data_time: 0.0341 memory: 23504 grad_norm: 2.7824 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.6680 loss: 1.6680 2022/09/08 13:07:21 - mmengine - INFO - Epoch(train) [13][100/1253] lr: 4.0000e-02 eta: 7:45:01 time: 0.6212 data_time: 0.0466 memory: 23504 grad_norm: 2.8757 top1_acc: 0.5417 top5_acc: 0.6667 loss_cls: 1.8403 loss: 1.8403 2022/09/08 13:07:34 - mmengine - INFO - Epoch(train) [13][120/1253] lr: 4.0000e-02 eta: 7:44:54 time: 0.6631 data_time: 0.1123 memory: 23504 grad_norm: 2.8447 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6096 loss: 1.6096 2022/09/08 13:07:46 - mmengine - INFO - Epoch(train) [13][140/1253] lr: 4.0000e-02 eta: 7:44:41 time: 0.5624 data_time: 0.0381 memory: 23504 grad_norm: 2.8266 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.6765 loss: 1.6765 2022/09/08 13:07:58 - mmengine - INFO - Epoch(train) [13][160/1253] lr: 4.0000e-02 eta: 7:44:30 time: 0.6115 data_time: 0.0418 memory: 23504 grad_norm: 2.7699 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.5826 loss: 1.5826 2022/09/08 13:08:10 - mmengine - INFO - Epoch(train) [13][180/1253] lr: 4.0000e-02 eta: 7:44:19 time: 0.5927 data_time: 0.0459 memory: 23504 grad_norm: 2.9051 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5094 loss: 1.5094 2022/09/08 13:08:21 - mmengine - INFO - Epoch(train) [13][200/1253] lr: 4.0000e-02 eta: 7:44:07 time: 0.5773 data_time: 0.0555 memory: 23504 grad_norm: 2.8292 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6449 loss: 1.6449 2022/09/08 13:08:32 - mmengine - INFO - Epoch(train) [13][220/1253] lr: 4.0000e-02 eta: 7:43:53 time: 0.5623 data_time: 0.0380 memory: 23504 grad_norm: 2.8044 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.5702 loss: 1.5702 2022/09/08 13:08:45 - mmengine - INFO - Epoch(train) [13][240/1253] lr: 4.0000e-02 eta: 7:43:45 time: 0.6418 data_time: 0.0415 memory: 23504 grad_norm: 2.8707 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 1.6410 loss: 1.6410 2022/09/08 13:08:56 - mmengine - INFO - Epoch(train) [13][260/1253] lr: 4.0000e-02 eta: 7:43:32 time: 0.5596 data_time: 0.0405 memory: 23504 grad_norm: 2.8266 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.5502 loss: 1.5502 2022/09/08 13:09:10 - mmengine - INFO - Epoch(train) [13][280/1253] lr: 4.0000e-02 eta: 7:43:25 time: 0.6703 data_time: 0.1471 memory: 23504 grad_norm: 2.8376 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.6845 loss: 1.6845 2022/09/08 13:09:21 - mmengine - INFO - Epoch(train) [13][300/1253] lr: 4.0000e-02 eta: 7:43:11 time: 0.5482 data_time: 0.0383 memory: 23504 grad_norm: 2.8443 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.5323 loss: 1.5323 2022/09/08 13:09:32 - mmengine - INFO - Epoch(train) [13][320/1253] lr: 4.0000e-02 eta: 7:42:57 time: 0.5578 data_time: 0.0456 memory: 23504 grad_norm: 2.9109 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.6150 loss: 1.6150 2022/09/08 13:09:43 - mmengine - INFO - Epoch(train) [13][340/1253] lr: 4.0000e-02 eta: 7:42:43 time: 0.5532 data_time: 0.0476 memory: 23504 grad_norm: 2.8884 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.6188 loss: 1.6188 2022/09/08 13:09:55 - mmengine - INFO - Epoch(train) [13][360/1253] lr: 4.0000e-02 eta: 7:42:31 time: 0.5780 data_time: 0.0486 memory: 23504 grad_norm: 2.8515 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.6045 loss: 1.6045 2022/09/08 13:10:06 - mmengine - INFO - Epoch(train) [13][380/1253] lr: 4.0000e-02 eta: 7:42:18 time: 0.5694 data_time: 0.0382 memory: 23504 grad_norm: 2.8161 top1_acc: 0.3750 top5_acc: 0.7917 loss_cls: 1.7547 loss: 1.7547 2022/09/08 13:10:17 - mmengine - INFO - Epoch(train) [13][400/1253] lr: 4.0000e-02 eta: 7:42:06 time: 0.5724 data_time: 0.0526 memory: 23504 grad_norm: 2.8159 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7968 loss: 1.7968 2022/09/08 13:10:30 - mmengine - INFO - Epoch(train) [13][420/1253] lr: 4.0000e-02 eta: 7:41:56 time: 0.6221 data_time: 0.0358 memory: 23504 grad_norm: 2.8212 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.5051 loss: 1.5051 2022/09/08 13:10:41 - mmengine - INFO - Epoch(train) [13][440/1253] lr: 4.0000e-02 eta: 7:41:43 time: 0.5678 data_time: 0.0456 memory: 23504 grad_norm: 2.7799 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 1.7847 loss: 1.7847 2022/09/08 13:10:52 - mmengine - INFO - Epoch(train) [13][460/1253] lr: 4.0000e-02 eta: 7:41:30 time: 0.5602 data_time: 0.0360 memory: 23504 grad_norm: 2.8315 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.5948 loss: 1.5948 2022/09/08 13:11:04 - mmengine - INFO - Epoch(train) [13][480/1253] lr: 4.0000e-02 eta: 7:41:18 time: 0.5844 data_time: 0.0648 memory: 23504 grad_norm: 2.8317 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.7754 loss: 1.7754 2022/09/08 13:11:15 - mmengine - INFO - Epoch(train) [13][500/1253] lr: 4.0000e-02 eta: 7:41:04 time: 0.5583 data_time: 0.0420 memory: 23504 grad_norm: 2.8520 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6752 loss: 1.6752 2022/09/08 13:11:27 - mmengine - INFO - Epoch(train) [13][520/1253] lr: 4.0000e-02 eta: 7:40:53 time: 0.5887 data_time: 0.0485 memory: 23504 grad_norm: 2.8735 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.5619 loss: 1.5619 2022/09/08 13:11:39 - mmengine - INFO - Epoch(train) [13][540/1253] lr: 4.0000e-02 eta: 7:40:41 time: 0.5845 data_time: 0.0439 memory: 23504 grad_norm: 2.8254 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.7604 loss: 1.7604 2022/09/08 13:11:50 - mmengine - INFO - Epoch(train) [13][560/1253] lr: 4.0000e-02 eta: 7:40:29 time: 0.5816 data_time: 0.0354 memory: 23504 grad_norm: 2.9595 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.5703 loss: 1.5703 2022/09/08 13:12:02 - mmengine - INFO - Epoch(train) [13][580/1253] lr: 4.0000e-02 eta: 7:40:17 time: 0.5861 data_time: 0.0470 memory: 23504 grad_norm: 2.8455 top1_acc: 0.7083 top5_acc: 1.0000 loss_cls: 1.6497 loss: 1.6497 2022/09/08 13:12:14 - mmengine - INFO - Epoch(train) [13][600/1253] lr: 4.0000e-02 eta: 7:40:05 time: 0.5795 data_time: 0.0421 memory: 23504 grad_norm: 2.8480 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 1.6308 loss: 1.6308 2022/09/08 13:12:26 - mmengine - INFO - Epoch(train) [13][620/1253] lr: 4.0000e-02 eta: 7:39:53 time: 0.5951 data_time: 0.0403 memory: 23504 grad_norm: 2.8442 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.6830 loss: 1.6830 2022/09/08 13:12:37 - mmengine - INFO - Epoch(train) [13][640/1253] lr: 4.0000e-02 eta: 7:39:41 time: 0.5773 data_time: 0.0318 memory: 23504 grad_norm: 2.8411 top1_acc: 0.6250 top5_acc: 0.7083 loss_cls: 1.5892 loss: 1.5892 2022/09/08 13:12:49 - mmengine - INFO - Epoch(train) [13][660/1253] lr: 4.0000e-02 eta: 7:39:30 time: 0.5971 data_time: 0.0471 memory: 23504 grad_norm: 2.8291 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.6675 loss: 1.6675 2022/09/08 13:13:00 - mmengine - INFO - Epoch(train) [13][680/1253] lr: 4.0000e-02 eta: 7:39:16 time: 0.5495 data_time: 0.0386 memory: 23504 grad_norm: 2.8808 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.3125 loss: 1.3125 2022/09/08 13:13:11 - mmengine - INFO - Epoch(train) [13][700/1253] lr: 4.0000e-02 eta: 7:39:02 time: 0.5584 data_time: 0.0399 memory: 23504 grad_norm: 2.8903 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.5602 loss: 1.5602 2022/09/08 13:13:23 - mmengine - INFO - Epoch(train) [13][720/1253] lr: 4.0000e-02 eta: 7:38:49 time: 0.5680 data_time: 0.0474 memory: 23504 grad_norm: 2.8125 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.6902 loss: 1.6902 2022/09/08 13:13:34 - mmengine - INFO - Epoch(train) [13][740/1253] lr: 4.0000e-02 eta: 7:38:38 time: 0.5890 data_time: 0.0650 memory: 23504 grad_norm: 2.9048 top1_acc: 0.6250 top5_acc: 0.6667 loss_cls: 1.7384 loss: 1.7384 2022/09/08 13:13:46 - mmengine - INFO - Epoch(train) [13][760/1253] lr: 4.0000e-02 eta: 7:38:25 time: 0.5690 data_time: 0.0557 memory: 23504 grad_norm: 2.8820 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 1.7746 loss: 1.7746 2022/09/08 13:13:57 - mmengine - INFO - Epoch(train) [13][780/1253] lr: 4.0000e-02 eta: 7:38:13 time: 0.5741 data_time: 0.0409 memory: 23504 grad_norm: 2.8511 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.4585 loss: 1.4585 2022/09/08 13:14:09 - mmengine - INFO - Epoch(train) [13][800/1253] lr: 4.0000e-02 eta: 7:37:59 time: 0.5587 data_time: 0.0421 memory: 23504 grad_norm: 2.8814 top1_acc: 0.5000 top5_acc: 0.9167 loss_cls: 1.8028 loss: 1.8028 2022/09/08 13:14:20 - mmengine - INFO - Epoch(train) [13][820/1253] lr: 4.0000e-02 eta: 7:37:46 time: 0.5665 data_time: 0.0370 memory: 23504 grad_norm: 2.8624 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 1.6829 loss: 1.6829 2022/09/08 13:14:32 - mmengine - INFO - Epoch(train) [13][840/1253] lr: 4.0000e-02 eta: 7:37:36 time: 0.6125 data_time: 0.0799 memory: 23504 grad_norm: 2.8103 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.5209 loss: 1.5209 2022/09/08 13:14:45 - mmengine - INFO - Epoch(train) [13][860/1253] lr: 4.0000e-02 eta: 7:37:28 time: 0.6554 data_time: 0.1120 memory: 23504 grad_norm: 2.7952 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.8112 loss: 1.8112 2022/09/08 13:14:57 - mmengine - INFO - Epoch(train) [13][880/1253] lr: 4.0000e-02 eta: 7:37:16 time: 0.5825 data_time: 0.0575 memory: 23504 grad_norm: 2.7927 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.6463 loss: 1.6463 2022/09/08 13:15:08 - mmengine - INFO - Epoch(train) [13][900/1253] lr: 4.0000e-02 eta: 7:37:03 time: 0.5542 data_time: 0.0448 memory: 23504 grad_norm: 2.8357 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.7471 loss: 1.7471 2022/09/08 13:15:19 - mmengine - INFO - Epoch(train) [13][920/1253] lr: 4.0000e-02 eta: 7:36:50 time: 0.5665 data_time: 0.0390 memory: 23504 grad_norm: 2.8346 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.5712 loss: 1.5712 2022/09/08 13:15:31 - mmengine - INFO - Epoch(train) [13][940/1253] lr: 4.0000e-02 eta: 7:36:38 time: 0.5837 data_time: 0.0385 memory: 23504 grad_norm: 2.8673 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.5200 loss: 1.5200 2022/09/08 13:15:43 - mmengine - INFO - Epoch(train) [13][960/1253] lr: 4.0000e-02 eta: 7:36:27 time: 0.6055 data_time: 0.0531 memory: 23504 grad_norm: 2.7709 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.6301 loss: 1.6301 2022/09/08 13:15:45 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 13:15:54 - mmengine - INFO - Epoch(train) [13][980/1253] lr: 4.0000e-02 eta: 7:36:14 time: 0.5660 data_time: 0.0330 memory: 23504 grad_norm: 2.7749 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.8143 loss: 1.8143 2022/09/08 13:16:06 - mmengine - INFO - Epoch(train) [13][1000/1253] lr: 4.0000e-02 eta: 7:36:03 time: 0.6033 data_time: 0.0418 memory: 23504 grad_norm: 2.7910 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.5948 loss: 1.5948 2022/09/08 13:16:19 - mmengine - INFO - Epoch(train) [13][1020/1253] lr: 4.0000e-02 eta: 7:35:53 time: 0.6156 data_time: 0.0717 memory: 23504 grad_norm: 2.8019 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7450 loss: 1.7450 2022/09/08 13:16:31 - mmengine - INFO - Epoch(train) [13][1040/1253] lr: 4.0000e-02 eta: 7:35:43 time: 0.6149 data_time: 0.1061 memory: 23504 grad_norm: 2.7671 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.6044 loss: 1.6044 2022/09/08 13:16:42 - mmengine - INFO - Epoch(train) [13][1060/1253] lr: 4.0000e-02 eta: 7:35:29 time: 0.5505 data_time: 0.0436 memory: 23504 grad_norm: 2.8340 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6187 loss: 1.6187 2022/09/08 13:16:53 - mmengine - INFO - Epoch(train) [13][1080/1253] lr: 4.0000e-02 eta: 7:35:15 time: 0.5507 data_time: 0.0332 memory: 23504 grad_norm: 2.8280 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6552 loss: 1.6552 2022/09/08 13:17:04 - mmengine - INFO - Epoch(train) [13][1100/1253] lr: 4.0000e-02 eta: 7:35:02 time: 0.5619 data_time: 0.0445 memory: 23504 grad_norm: 2.8668 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7485 loss: 1.7485 2022/09/08 13:17:16 - mmengine - INFO - Epoch(train) [13][1120/1253] lr: 4.0000e-02 eta: 7:34:49 time: 0.5630 data_time: 0.0429 memory: 23504 grad_norm: 2.8459 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.6000 loss: 1.6000 2022/09/08 13:17:28 - mmengine - INFO - Epoch(train) [13][1140/1253] lr: 4.0000e-02 eta: 7:34:39 time: 0.6144 data_time: 0.0505 memory: 23504 grad_norm: 2.8305 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.7585 loss: 1.7585 2022/09/08 13:17:39 - mmengine - INFO - Epoch(train) [13][1160/1253] lr: 4.0000e-02 eta: 7:34:25 time: 0.5453 data_time: 0.0328 memory: 23504 grad_norm: 2.8524 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 1.5886 loss: 1.5886 2022/09/08 13:17:51 - mmengine - INFO - Epoch(train) [13][1180/1253] lr: 4.0000e-02 eta: 7:34:14 time: 0.5969 data_time: 0.0490 memory: 23504 grad_norm: 2.7759 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.6968 loss: 1.6968 2022/09/08 13:18:02 - mmengine - INFO - Epoch(train) [13][1200/1253] lr: 4.0000e-02 eta: 7:34:01 time: 0.5645 data_time: 0.0391 memory: 23504 grad_norm: 2.8578 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.7371 loss: 1.7371 2022/09/08 13:18:14 - mmengine - INFO - Epoch(train) [13][1220/1253] lr: 4.0000e-02 eta: 7:33:51 time: 0.6224 data_time: 0.0908 memory: 23504 grad_norm: 2.8455 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7440 loss: 1.7440 2022/09/08 13:18:25 - mmengine - INFO - Epoch(train) [13][1240/1253] lr: 4.0000e-02 eta: 7:33:35 time: 0.5119 data_time: 0.0524 memory: 23504 grad_norm: 2.7849 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6659 loss: 1.6659 2022/09/08 13:18:30 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 13:18:30 - mmengine - INFO - Epoch(train) [13][1253/1253] lr: 4.0000e-02 eta: 7:33:35 time: 0.4386 data_time: 0.0143 memory: 23504 grad_norm: 2.8851 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.7401 loss: 1.7401 2022/09/08 13:18:53 - mmengine - INFO - Epoch(train) [14][20/1253] lr: 4.0000e-02 eta: 7:33:24 time: 1.1152 data_time: 0.4687 memory: 23504 grad_norm: 2.8541 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.7319 loss: 1.7319 2022/09/08 13:19:05 - mmengine - INFO - Epoch(train) [14][40/1253] lr: 4.0000e-02 eta: 7:33:12 time: 0.5935 data_time: 0.0521 memory: 23504 grad_norm: 2.8197 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.5141 loss: 1.5141 2022/09/08 13:19:16 - mmengine - INFO - Epoch(train) [14][60/1253] lr: 4.0000e-02 eta: 7:33:00 time: 0.5790 data_time: 0.0374 memory: 23504 grad_norm: 2.8512 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.5847 loss: 1.5847 2022/09/08 13:19:30 - mmengine - INFO - Epoch(train) [14][80/1253] lr: 4.0000e-02 eta: 7:32:55 time: 0.6960 data_time: 0.0389 memory: 23504 grad_norm: 2.8527 top1_acc: 0.5833 top5_acc: 1.0000 loss_cls: 1.5744 loss: 1.5744 2022/09/08 13:19:41 - mmengine - INFO - Epoch(train) [14][100/1253] lr: 4.0000e-02 eta: 7:32:42 time: 0.5661 data_time: 0.0425 memory: 23504 grad_norm: 2.8502 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.7802 loss: 1.7802 2022/09/08 13:19:53 - mmengine - INFO - Epoch(train) [14][120/1253] lr: 4.0000e-02 eta: 7:32:28 time: 0.5585 data_time: 0.0435 memory: 23504 grad_norm: 2.9015 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.7723 loss: 1.7723 2022/09/08 13:20:04 - mmengine - INFO - Epoch(train) [14][140/1253] lr: 4.0000e-02 eta: 7:32:16 time: 0.5837 data_time: 0.0446 memory: 23504 grad_norm: 2.7689 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5899 loss: 1.5899 2022/09/08 13:20:16 - mmengine - INFO - Epoch(train) [14][160/1253] lr: 4.0000e-02 eta: 7:32:04 time: 0.5755 data_time: 0.0473 memory: 23504 grad_norm: 2.7754 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.6198 loss: 1.6198 2022/09/08 13:20:27 - mmengine - INFO - Epoch(train) [14][180/1253] lr: 4.0000e-02 eta: 7:31:51 time: 0.5642 data_time: 0.0422 memory: 23504 grad_norm: 2.8263 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4812 loss: 1.4812 2022/09/08 13:20:39 - mmengine - INFO - Epoch(train) [14][200/1253] lr: 4.0000e-02 eta: 7:31:41 time: 0.6202 data_time: 0.0495 memory: 23504 grad_norm: 2.7878 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.6984 loss: 1.6984 2022/09/08 13:20:51 - mmengine - INFO - Epoch(train) [14][220/1253] lr: 4.0000e-02 eta: 7:31:30 time: 0.5954 data_time: 0.0435 memory: 23504 grad_norm: 2.7620 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6237 loss: 1.6237 2022/09/08 13:21:03 - mmengine - INFO - Epoch(train) [14][240/1253] lr: 4.0000e-02 eta: 7:31:17 time: 0.5681 data_time: 0.0656 memory: 23504 grad_norm: 2.8105 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6153 loss: 1.6153 2022/09/08 13:21:14 - mmengine - INFO - Epoch(train) [14][260/1253] lr: 4.0000e-02 eta: 7:31:03 time: 0.5538 data_time: 0.0433 memory: 23504 grad_norm: 2.8128 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.5850 loss: 1.5850 2022/09/08 13:21:25 - mmengine - INFO - Epoch(train) [14][280/1253] lr: 4.0000e-02 eta: 7:30:51 time: 0.5773 data_time: 0.0458 memory: 23504 grad_norm: 2.8508 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6110 loss: 1.6110 2022/09/08 13:21:37 - mmengine - INFO - Epoch(train) [14][300/1253] lr: 4.0000e-02 eta: 7:30:39 time: 0.5826 data_time: 0.0547 memory: 23504 grad_norm: 2.8150 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.6183 loss: 1.6183 2022/09/08 13:21:50 - mmengine - INFO - Epoch(train) [14][320/1253] lr: 4.0000e-02 eta: 7:30:31 time: 0.6437 data_time: 0.0332 memory: 23504 grad_norm: 2.6935 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.6644 loss: 1.6644 2022/09/08 13:22:01 - mmengine - INFO - Epoch(train) [14][340/1253] lr: 4.0000e-02 eta: 7:30:18 time: 0.5674 data_time: 0.0364 memory: 23504 grad_norm: 2.8186 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.5739 loss: 1.5739 2022/09/08 13:22:13 - mmengine - INFO - Epoch(train) [14][360/1253] lr: 4.0000e-02 eta: 7:30:05 time: 0.5754 data_time: 0.0460 memory: 23504 grad_norm: 2.8273 top1_acc: 0.5833 top5_acc: 0.6667 loss_cls: 1.7299 loss: 1.7299 2022/09/08 13:22:24 - mmengine - INFO - Epoch(train) [14][380/1253] lr: 4.0000e-02 eta: 7:29:53 time: 0.5857 data_time: 0.0535 memory: 23504 grad_norm: 2.8186 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 1.5607 loss: 1.5607 2022/09/08 13:22:38 - mmengine - INFO - Epoch(train) [14][400/1253] lr: 4.0000e-02 eta: 7:29:47 time: 0.6759 data_time: 0.0319 memory: 23504 grad_norm: 2.8207 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.5341 loss: 1.5341 2022/09/08 13:22:49 - mmengine - INFO - Epoch(train) [14][420/1253] lr: 4.0000e-02 eta: 7:29:32 time: 0.5407 data_time: 0.0269 memory: 23504 grad_norm: 2.8709 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.7035 loss: 1.7035 2022/09/08 13:23:00 - mmengine - INFO - Epoch(train) [14][440/1253] lr: 4.0000e-02 eta: 7:29:19 time: 0.5560 data_time: 0.0529 memory: 23504 grad_norm: 2.8123 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 1.6350 loss: 1.6350 2022/09/08 13:23:11 - mmengine - INFO - Epoch(train) [14][460/1253] lr: 4.0000e-02 eta: 7:29:05 time: 0.5553 data_time: 0.0509 memory: 23504 grad_norm: 2.8345 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.6149 loss: 1.6149 2022/09/08 13:23:22 - mmengine - INFO - Epoch(train) [14][480/1253] lr: 4.0000e-02 eta: 7:28:52 time: 0.5611 data_time: 0.0430 memory: 23504 grad_norm: 2.8461 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.5705 loss: 1.5705 2022/09/08 13:23:34 - mmengine - INFO - Epoch(train) [14][500/1253] lr: 4.0000e-02 eta: 7:28:40 time: 0.5724 data_time: 0.0492 memory: 23504 grad_norm: 2.8729 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.7107 loss: 1.7107 2022/09/08 13:23:46 - mmengine - INFO - Epoch(train) [14][520/1253] lr: 4.0000e-02 eta: 7:28:29 time: 0.6038 data_time: 0.0442 memory: 23504 grad_norm: 2.8820 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.6627 loss: 1.6627 2022/09/08 13:23:57 - mmengine - INFO - Epoch(train) [14][540/1253] lr: 4.0000e-02 eta: 7:28:17 time: 0.5768 data_time: 0.0582 memory: 23504 grad_norm: 2.8408 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.8117 loss: 1.8117 2022/09/08 13:24:09 - mmengine - INFO - Epoch(train) [14][560/1253] lr: 4.0000e-02 eta: 7:28:04 time: 0.5768 data_time: 0.0451 memory: 23504 grad_norm: 2.8531 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6289 loss: 1.6289 2022/09/08 13:24:20 - mmengine - INFO - Epoch(train) [14][580/1253] lr: 4.0000e-02 eta: 7:27:51 time: 0.5553 data_time: 0.0360 memory: 23504 grad_norm: 2.8078 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.6548 loss: 1.6548 2022/09/08 13:24:31 - mmengine - INFO - Epoch(train) [14][600/1253] lr: 4.0000e-02 eta: 7:27:38 time: 0.5752 data_time: 0.0460 memory: 23504 grad_norm: 2.7937 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.8402 loss: 1.8402 2022/09/08 13:24:46 - mmengine - INFO - Epoch(train) [14][620/1253] lr: 4.0000e-02 eta: 7:27:34 time: 0.7171 data_time: 0.0452 memory: 23504 grad_norm: 2.8051 top1_acc: 0.5833 top5_acc: 0.9583 loss_cls: 1.6922 loss: 1.6922 2022/09/08 13:24:57 - mmengine - INFO - Epoch(train) [14][640/1253] lr: 4.0000e-02 eta: 7:27:20 time: 0.5446 data_time: 0.0422 memory: 23504 grad_norm: 2.7943 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5548 loss: 1.5548 2022/09/08 13:25:08 - mmengine - INFO - Epoch(train) [14][660/1253] lr: 4.0000e-02 eta: 7:27:07 time: 0.5730 data_time: 0.0449 memory: 23504 grad_norm: 2.8395 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 1.7636 loss: 1.7636 2022/09/08 13:25:20 - mmengine - INFO - Epoch(train) [14][680/1253] lr: 4.0000e-02 eta: 7:26:55 time: 0.5698 data_time: 0.0387 memory: 23504 grad_norm: 2.7736 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.4570 loss: 1.4570 2022/09/08 13:25:31 - mmengine - INFO - Epoch(train) [14][700/1253] lr: 4.0000e-02 eta: 7:26:42 time: 0.5714 data_time: 0.0503 memory: 23504 grad_norm: 2.8390 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.6735 loss: 1.6735 2022/09/08 13:25:37 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 13:25:42 - mmengine - INFO - Epoch(train) [14][720/1253] lr: 4.0000e-02 eta: 7:26:30 time: 0.5737 data_time: 0.0483 memory: 23504 grad_norm: 2.8871 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.7278 loss: 1.7278 2022/09/08 13:25:54 - mmengine - INFO - Epoch(train) [14][740/1253] lr: 4.0000e-02 eta: 7:26:16 time: 0.5576 data_time: 0.0447 memory: 23504 grad_norm: 2.7446 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.6730 loss: 1.6730 2022/09/08 13:26:05 - mmengine - INFO - Epoch(train) [14][760/1253] lr: 4.0000e-02 eta: 7:26:04 time: 0.5847 data_time: 0.0504 memory: 23504 grad_norm: 2.7985 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7078 loss: 1.7078 2022/09/08 13:26:16 - mmengine - INFO - Epoch(train) [14][780/1253] lr: 4.0000e-02 eta: 7:25:51 time: 0.5562 data_time: 0.0465 memory: 23504 grad_norm: 2.8430 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.5895 loss: 1.5895 2022/09/08 13:26:30 - mmengine - INFO - Epoch(train) [14][800/1253] lr: 4.0000e-02 eta: 7:25:44 time: 0.6805 data_time: 0.0448 memory: 23504 grad_norm: 2.8647 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6828 loss: 1.6828 2022/09/08 13:26:41 - mmengine - INFO - Epoch(train) [14][820/1253] lr: 4.0000e-02 eta: 7:25:30 time: 0.5439 data_time: 0.0447 memory: 23504 grad_norm: 2.8664 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.6140 loss: 1.6140 2022/09/08 13:26:52 - mmengine - INFO - Epoch(train) [14][840/1253] lr: 4.0000e-02 eta: 7:25:17 time: 0.5606 data_time: 0.0420 memory: 23504 grad_norm: 2.9213 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 1.7189 loss: 1.7189 2022/09/08 13:27:04 - mmengine - INFO - Epoch(train) [14][860/1253] lr: 4.0000e-02 eta: 7:25:04 time: 0.5673 data_time: 0.0520 memory: 23504 grad_norm: 2.8848 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7147 loss: 1.7147 2022/09/08 13:27:16 - mmengine - INFO - Epoch(train) [14][880/1253] lr: 4.0000e-02 eta: 7:24:53 time: 0.6032 data_time: 0.0508 memory: 23504 grad_norm: 2.8278 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.5852 loss: 1.5852 2022/09/08 13:27:27 - mmengine - INFO - Epoch(train) [14][900/1253] lr: 4.0000e-02 eta: 7:24:39 time: 0.5459 data_time: 0.0438 memory: 23504 grad_norm: 2.8033 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.7677 loss: 1.7677 2022/09/08 13:27:38 - mmengine - INFO - Epoch(train) [14][920/1253] lr: 4.0000e-02 eta: 7:24:27 time: 0.5755 data_time: 0.0527 memory: 23504 grad_norm: 2.8013 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5454 loss: 1.5454 2022/09/08 13:27:49 - mmengine - INFO - Epoch(train) [14][940/1253] lr: 4.0000e-02 eta: 7:24:14 time: 0.5650 data_time: 0.0534 memory: 23504 grad_norm: 2.8578 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 1.9131 loss: 1.9131 2022/09/08 13:28:01 - mmengine - INFO - Epoch(train) [14][960/1253] lr: 4.0000e-02 eta: 7:24:03 time: 0.6044 data_time: 0.0506 memory: 23504 grad_norm: 2.7671 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.7395 loss: 1.7395 2022/09/08 13:28:13 - mmengine - INFO - Epoch(train) [14][980/1253] lr: 4.0000e-02 eta: 7:23:50 time: 0.5571 data_time: 0.0367 memory: 23504 grad_norm: 2.7703 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.6996 loss: 1.6996 2022/09/08 13:28:24 - mmengine - INFO - Epoch(train) [14][1000/1253] lr: 4.0000e-02 eta: 7:23:38 time: 0.5736 data_time: 0.0382 memory: 23504 grad_norm: 2.8565 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.6642 loss: 1.6642 2022/09/08 13:28:37 - mmengine - INFO - Epoch(train) [14][1020/1253] lr: 4.0000e-02 eta: 7:23:28 time: 0.6314 data_time: 0.0448 memory: 23504 grad_norm: 2.7923 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.6466 loss: 1.6466 2022/09/08 13:28:48 - mmengine - INFO - Epoch(train) [14][1040/1253] lr: 4.0000e-02 eta: 7:23:16 time: 0.5777 data_time: 0.0536 memory: 23504 grad_norm: 2.7975 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7492 loss: 1.7492 2022/09/08 13:28:59 - mmengine - INFO - Epoch(train) [14][1060/1253] lr: 4.0000e-02 eta: 7:23:02 time: 0.5400 data_time: 0.0377 memory: 23504 grad_norm: 2.8623 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7476 loss: 1.7476 2022/09/08 13:29:10 - mmengine - INFO - Epoch(train) [14][1080/1253] lr: 4.0000e-02 eta: 7:22:49 time: 0.5658 data_time: 0.0310 memory: 23504 grad_norm: 2.8629 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.6098 loss: 1.6098 2022/09/08 13:29:21 - mmengine - INFO - Epoch(train) [14][1100/1253] lr: 4.0000e-02 eta: 7:22:35 time: 0.5496 data_time: 0.0430 memory: 23504 grad_norm: 2.7792 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.6050 loss: 1.6050 2022/09/08 13:29:33 - mmengine - INFO - Epoch(train) [14][1120/1253] lr: 4.0000e-02 eta: 7:22:25 time: 0.6046 data_time: 0.0460 memory: 23504 grad_norm: 2.8255 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.5173 loss: 1.5173 2022/09/08 13:29:45 - mmengine - INFO - Epoch(train) [14][1140/1253] lr: 4.0000e-02 eta: 7:22:11 time: 0.5555 data_time: 0.0379 memory: 23504 grad_norm: 2.7576 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.8154 loss: 1.8154 2022/09/08 13:29:57 - mmengine - INFO - Epoch(train) [14][1160/1253] lr: 4.0000e-02 eta: 7:22:01 time: 0.6057 data_time: 0.0405 memory: 23504 grad_norm: 2.7966 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.7524 loss: 1.7524 2022/09/08 13:30:08 - mmengine - INFO - Epoch(train) [14][1180/1253] lr: 4.0000e-02 eta: 7:21:48 time: 0.5670 data_time: 0.0494 memory: 23504 grad_norm: 2.8733 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.6550 loss: 1.6550 2022/09/08 13:30:20 - mmengine - INFO - Epoch(train) [14][1200/1253] lr: 4.0000e-02 eta: 7:21:36 time: 0.5799 data_time: 0.0473 memory: 23504 grad_norm: 2.8395 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.7926 loss: 1.7926 2022/09/08 13:30:31 - mmengine - INFO - Epoch(train) [14][1220/1253] lr: 4.0000e-02 eta: 7:21:23 time: 0.5652 data_time: 0.0422 memory: 23504 grad_norm: 2.8670 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.7045 loss: 1.7045 2022/09/08 13:30:41 - mmengine - INFO - Epoch(train) [14][1240/1253] lr: 4.0000e-02 eta: 7:21:06 time: 0.4973 data_time: 0.0265 memory: 23504 grad_norm: 2.8131 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.8594 loss: 1.8594 2022/09/08 13:30:46 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 13:30:46 - mmengine - INFO - Epoch(train) [14][1253/1253] lr: 4.0000e-02 eta: 7:21:06 time: 0.4260 data_time: 0.0138 memory: 23504 grad_norm: 2.8341 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.6926 loss: 1.6926 2022/09/08 13:31:11 - mmengine - INFO - Epoch(train) [15][20/1253] lr: 4.0000e-02 eta: 7:21:01 time: 1.2338 data_time: 0.4832 memory: 23504 grad_norm: 2.7423 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5361 loss: 1.5361 2022/09/08 13:31:22 - mmengine - INFO - Epoch(train) [15][40/1253] lr: 4.0000e-02 eta: 7:20:48 time: 0.5657 data_time: 0.0383 memory: 23504 grad_norm: 2.8148 top1_acc: 0.5417 top5_acc: 0.6250 loss_cls: 1.7122 loss: 1.7122 2022/09/08 13:31:34 - mmengine - INFO - Epoch(train) [15][60/1253] lr: 4.0000e-02 eta: 7:20:35 time: 0.5594 data_time: 0.0302 memory: 23504 grad_norm: 2.8051 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.6405 loss: 1.6405 2022/09/08 13:31:47 - mmengine - INFO - Epoch(train) [15][80/1253] lr: 4.0000e-02 eta: 7:20:26 time: 0.6492 data_time: 0.0324 memory: 23504 grad_norm: 2.8420 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.6063 loss: 1.6063 2022/09/08 13:31:58 - mmengine - INFO - Epoch(train) [15][100/1253] lr: 4.0000e-02 eta: 7:20:13 time: 0.5586 data_time: 0.0460 memory: 23504 grad_norm: 2.8516 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.5152 loss: 1.5152 2022/09/08 13:32:12 - mmengine - INFO - Epoch(train) [15][120/1253] lr: 4.0000e-02 eta: 7:20:07 time: 0.7052 data_time: 0.0380 memory: 23504 grad_norm: 2.8858 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.6935 loss: 1.6935 2022/09/08 13:32:22 - mmengine - INFO - Epoch(train) [15][140/1253] lr: 4.0000e-02 eta: 7:19:52 time: 0.5194 data_time: 0.0383 memory: 23504 grad_norm: 2.8941 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6156 loss: 1.6156 2022/09/08 13:32:33 - mmengine - INFO - Epoch(train) [15][160/1253] lr: 4.0000e-02 eta: 7:19:39 time: 0.5497 data_time: 0.0395 memory: 23504 grad_norm: 2.8339 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.5607 loss: 1.5607 2022/09/08 13:32:44 - mmengine - INFO - Epoch(train) [15][180/1253] lr: 4.0000e-02 eta: 7:19:26 time: 0.5618 data_time: 0.0498 memory: 23504 grad_norm: 2.7944 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.5762 loss: 1.5762 2022/09/08 13:32:56 - mmengine - INFO - Epoch(train) [15][200/1253] lr: 4.0000e-02 eta: 7:19:13 time: 0.5633 data_time: 0.0348 memory: 23504 grad_norm: 2.8197 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.5996 loss: 1.5996 2022/09/08 13:33:08 - mmengine - INFO - Epoch(train) [15][220/1253] lr: 4.0000e-02 eta: 7:19:02 time: 0.6096 data_time: 0.0447 memory: 23504 grad_norm: 2.8438 top1_acc: 0.6250 top5_acc: 0.7083 loss_cls: 1.5909 loss: 1.5909 2022/09/08 13:33:19 - mmengine - INFO - Epoch(train) [15][240/1253] lr: 4.0000e-02 eta: 7:18:49 time: 0.5699 data_time: 0.0386 memory: 23504 grad_norm: 2.8216 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8515 loss: 1.8515 2022/09/08 13:33:31 - mmengine - INFO - Epoch(train) [15][260/1253] lr: 4.0000e-02 eta: 7:18:37 time: 0.5631 data_time: 0.0461 memory: 23504 grad_norm: 2.8904 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.5714 loss: 1.5714 2022/09/08 13:33:43 - mmengine - INFO - Epoch(train) [15][280/1253] lr: 4.0000e-02 eta: 7:18:26 time: 0.6029 data_time: 0.0443 memory: 23504 grad_norm: 2.8278 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6702 loss: 1.6702 2022/09/08 13:33:54 - mmengine - INFO - Epoch(train) [15][300/1253] lr: 4.0000e-02 eta: 7:18:14 time: 0.5887 data_time: 0.0433 memory: 23504 grad_norm: 2.8609 top1_acc: 0.5833 top5_acc: 0.9583 loss_cls: 1.5749 loss: 1.5749 2022/09/08 13:34:07 - mmengine - INFO - Epoch(train) [15][320/1253] lr: 4.0000e-02 eta: 7:18:05 time: 0.6413 data_time: 0.0353 memory: 23504 grad_norm: 2.7859 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7088 loss: 1.7088 2022/09/08 13:34:19 - mmengine - INFO - Epoch(train) [15][340/1253] lr: 4.0000e-02 eta: 7:17:52 time: 0.5714 data_time: 0.0355 memory: 23504 grad_norm: 2.8026 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.6149 loss: 1.6149 2022/09/08 13:34:30 - mmengine - INFO - Epoch(train) [15][360/1253] lr: 4.0000e-02 eta: 7:17:39 time: 0.5579 data_time: 0.0480 memory: 23504 grad_norm: 2.8943 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.6826 loss: 1.6826 2022/09/08 13:34:41 - mmengine - INFO - Epoch(train) [15][380/1253] lr: 4.0000e-02 eta: 7:17:26 time: 0.5483 data_time: 0.0422 memory: 23504 grad_norm: 2.9037 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 1.6810 loss: 1.6810 2022/09/08 13:34:52 - mmengine - INFO - Epoch(train) [15][400/1253] lr: 4.0000e-02 eta: 7:17:13 time: 0.5625 data_time: 0.0454 memory: 23504 grad_norm: 2.8032 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.5783 loss: 1.5783 2022/09/08 13:35:06 - mmengine - INFO - Epoch(train) [15][420/1253] lr: 4.0000e-02 eta: 7:17:07 time: 0.7011 data_time: 0.0337 memory: 23504 grad_norm: 2.8250 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.6035 loss: 1.6035 2022/09/08 13:35:17 - mmengine - INFO - Epoch(train) [15][440/1253] lr: 4.0000e-02 eta: 7:16:53 time: 0.5432 data_time: 0.0500 memory: 23504 grad_norm: 2.8474 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.6334 loss: 1.6334 2022/09/08 13:35:27 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 13:35:28 - mmengine - INFO - Epoch(train) [15][460/1253] lr: 4.0000e-02 eta: 7:16:40 time: 0.5669 data_time: 0.0437 memory: 23504 grad_norm: 2.9264 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.6906 loss: 1.6906 2022/09/08 13:35:40 - mmengine - INFO - Epoch(train) [15][480/1253] lr: 4.0000e-02 eta: 7:16:28 time: 0.5792 data_time: 0.0557 memory: 23504 grad_norm: 2.7569 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.5735 loss: 1.5735 2022/09/08 13:35:51 - mmengine - INFO - Epoch(train) [15][500/1253] lr: 4.0000e-02 eta: 7:16:15 time: 0.5655 data_time: 0.0341 memory: 23504 grad_norm: 2.8045 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.7210 loss: 1.7210 2022/09/08 13:36:03 - mmengine - INFO - Epoch(train) [15][520/1253] lr: 4.0000e-02 eta: 7:16:03 time: 0.5711 data_time: 0.0446 memory: 23504 grad_norm: 2.8680 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.6432 loss: 1.6432 2022/09/08 13:36:17 - mmengine - INFO - Epoch(train) [15][540/1253] lr: 4.0000e-02 eta: 7:15:58 time: 0.7263 data_time: 0.1373 memory: 23504 grad_norm: 2.8383 top1_acc: 0.3750 top5_acc: 0.7917 loss_cls: 1.6628 loss: 1.6628 2022/09/08 13:36:28 - mmengine - INFO - Epoch(train) [15][560/1253] lr: 4.0000e-02 eta: 7:15:44 time: 0.5407 data_time: 0.0251 memory: 23504 grad_norm: 2.8634 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.8237 loss: 1.8237 2022/09/08 13:36:39 - mmengine - INFO - Epoch(train) [15][580/1253] lr: 4.0000e-02 eta: 7:15:30 time: 0.5519 data_time: 0.0295 memory: 23504 grad_norm: 2.8043 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.6850 loss: 1.6850 2022/09/08 13:36:50 - mmengine - INFO - Epoch(train) [15][600/1253] lr: 4.0000e-02 eta: 7:15:16 time: 0.5393 data_time: 0.0381 memory: 23504 grad_norm: 2.9006 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.5619 loss: 1.5619 2022/09/08 13:37:01 - mmengine - INFO - Epoch(train) [15][620/1253] lr: 4.0000e-02 eta: 7:15:03 time: 0.5659 data_time: 0.0529 memory: 23504 grad_norm: 2.8918 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.6417 loss: 1.6417 2022/09/08 13:37:12 - mmengine - INFO - Epoch(train) [15][640/1253] lr: 4.0000e-02 eta: 7:14:51 time: 0.5711 data_time: 0.0450 memory: 23504 grad_norm: 2.8657 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6003 loss: 1.6003 2022/09/08 13:37:24 - mmengine - INFO - Epoch(train) [15][660/1253] lr: 4.0000e-02 eta: 7:14:39 time: 0.5878 data_time: 0.0429 memory: 23504 grad_norm: 2.8284 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5760 loss: 1.5760 2022/09/08 13:37:38 - mmengine - INFO - Epoch(train) [15][680/1253] lr: 4.0000e-02 eta: 7:14:32 time: 0.6843 data_time: 0.0404 memory: 23504 grad_norm: 2.8698 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.5650 loss: 1.5650 2022/09/08 13:37:49 - mmengine - INFO - Epoch(train) [15][700/1253] lr: 4.0000e-02 eta: 7:14:20 time: 0.5710 data_time: 0.0539 memory: 23504 grad_norm: 2.8347 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.5426 loss: 1.5426 2022/09/08 13:38:01 - mmengine - INFO - Epoch(train) [15][720/1253] lr: 4.0000e-02 eta: 7:14:07 time: 0.5568 data_time: 0.0346 memory: 23504 grad_norm: 2.8795 top1_acc: 0.4583 top5_acc: 0.9167 loss_cls: 1.5784 loss: 1.5784 2022/09/08 13:38:12 - mmengine - INFO - Epoch(train) [15][740/1253] lr: 4.0000e-02 eta: 7:13:54 time: 0.5789 data_time: 0.0383 memory: 23504 grad_norm: 2.8710 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.7328 loss: 1.7328 2022/09/08 13:38:25 - mmengine - INFO - Epoch(train) [15][760/1253] lr: 4.0000e-02 eta: 7:13:45 time: 0.6342 data_time: 0.0409 memory: 23504 grad_norm: 2.8718 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.5400 loss: 1.5400 2022/09/08 13:38:38 - mmengine - INFO - Epoch(train) [15][780/1253] lr: 4.0000e-02 eta: 7:13:36 time: 0.6381 data_time: 0.0387 memory: 23504 grad_norm: 2.7829 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.6752 loss: 1.6752 2022/09/08 13:38:49 - mmengine - INFO - Epoch(train) [15][800/1253] lr: 4.0000e-02 eta: 7:13:22 time: 0.5499 data_time: 0.0385 memory: 23504 grad_norm: 2.8143 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.6079 loss: 1.6079 2022/09/08 13:39:01 - mmengine - INFO - Epoch(train) [15][820/1253] lr: 4.0000e-02 eta: 7:13:12 time: 0.6157 data_time: 0.0432 memory: 23504 grad_norm: 2.7791 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.5710 loss: 1.5710 2022/09/08 13:39:13 - mmengine - INFO - Epoch(train) [15][840/1253] lr: 4.0000e-02 eta: 7:13:00 time: 0.5850 data_time: 0.0428 memory: 23504 grad_norm: 2.7490 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.5720 loss: 1.5720 2022/09/08 13:39:24 - mmengine - INFO - Epoch(train) [15][860/1253] lr: 4.0000e-02 eta: 7:12:48 time: 0.5722 data_time: 0.0437 memory: 23504 grad_norm: 2.7695 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.7238 loss: 1.7238 2022/09/08 13:39:35 - mmengine - INFO - Epoch(train) [15][880/1253] lr: 4.0000e-02 eta: 7:12:35 time: 0.5701 data_time: 0.0585 memory: 23504 grad_norm: 2.8421 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.7061 loss: 1.7061 2022/09/08 13:39:47 - mmengine - INFO - Epoch(train) [15][900/1253] lr: 4.0000e-02 eta: 7:12:24 time: 0.6022 data_time: 0.0380 memory: 23504 grad_norm: 2.8521 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.7247 loss: 1.7247 2022/09/08 13:39:59 - mmengine - INFO - Epoch(train) [15][920/1253] lr: 4.0000e-02 eta: 7:12:11 time: 0.5643 data_time: 0.0409 memory: 23504 grad_norm: 2.8397 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.6215 loss: 1.6215 2022/09/08 13:40:10 - mmengine - INFO - Epoch(train) [15][940/1253] lr: 4.0000e-02 eta: 7:11:59 time: 0.5712 data_time: 0.0420 memory: 23504 grad_norm: 2.7760 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8072 loss: 1.8072 2022/09/08 13:40:22 - mmengine - INFO - Epoch(train) [15][960/1253] lr: 4.0000e-02 eta: 7:11:47 time: 0.5767 data_time: 0.0453 memory: 23504 grad_norm: 2.8680 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.5300 loss: 1.5300 2022/09/08 13:40:34 - mmengine - INFO - Epoch(train) [15][980/1253] lr: 4.0000e-02 eta: 7:11:35 time: 0.5919 data_time: 0.0492 memory: 23504 grad_norm: 2.8444 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.6256 loss: 1.6256 2022/09/08 13:40:45 - mmengine - INFO - Epoch(train) [15][1000/1253] lr: 4.0000e-02 eta: 7:11:22 time: 0.5563 data_time: 0.0498 memory: 23504 grad_norm: 2.8086 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6384 loss: 1.6384 2022/09/08 13:40:57 - mmengine - INFO - Epoch(train) [15][1020/1253] lr: 4.0000e-02 eta: 7:11:10 time: 0.5925 data_time: 0.0417 memory: 23504 grad_norm: 2.8120 top1_acc: 0.5417 top5_acc: 0.6667 loss_cls: 1.7141 loss: 1.7141 2022/09/08 13:41:08 - mmengine - INFO - Epoch(train) [15][1040/1253] lr: 4.0000e-02 eta: 7:10:58 time: 0.5703 data_time: 0.0350 memory: 23504 grad_norm: 2.9055 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.6254 loss: 1.6254 2022/09/08 13:41:20 - mmengine - INFO - Epoch(train) [15][1060/1253] lr: 4.0000e-02 eta: 7:10:46 time: 0.5839 data_time: 0.0668 memory: 23504 grad_norm: 2.8292 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6579 loss: 1.6579 2022/09/08 13:41:31 - mmengine - INFO - Epoch(train) [15][1080/1253] lr: 4.0000e-02 eta: 7:10:33 time: 0.5703 data_time: 0.0314 memory: 23504 grad_norm: 2.8088 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 1.6491 loss: 1.6491 2022/09/08 13:41:42 - mmengine - INFO - Epoch(train) [15][1100/1253] lr: 4.0000e-02 eta: 7:10:21 time: 0.5625 data_time: 0.0370 memory: 23504 grad_norm: 2.8906 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.6597 loss: 1.6597 2022/09/08 13:41:54 - mmengine - INFO - Epoch(train) [15][1120/1253] lr: 4.0000e-02 eta: 7:10:08 time: 0.5637 data_time: 0.0371 memory: 23504 grad_norm: 2.8838 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.8505 loss: 1.8505 2022/09/08 13:42:06 - mmengine - INFO - Epoch(train) [15][1140/1253] lr: 4.0000e-02 eta: 7:09:59 time: 0.6411 data_time: 0.0536 memory: 23504 grad_norm: 2.8375 top1_acc: 0.5417 top5_acc: 0.6667 loss_cls: 1.6848 loss: 1.6848 2022/09/08 13:42:19 - mmengine - INFO - Epoch(train) [15][1160/1253] lr: 4.0000e-02 eta: 7:09:48 time: 0.6060 data_time: 0.0325 memory: 23504 grad_norm: 2.8618 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7891 loss: 1.7891 2022/09/08 13:42:32 - mmengine - INFO - Epoch(train) [15][1180/1253] lr: 4.0000e-02 eta: 7:09:40 time: 0.6624 data_time: 0.0302 memory: 23504 grad_norm: 2.7361 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.7258 loss: 1.7258 2022/09/08 13:42:43 - mmengine - INFO - Epoch(train) [15][1200/1253] lr: 4.0000e-02 eta: 7:09:26 time: 0.5410 data_time: 0.0325 memory: 23504 grad_norm: 2.7799 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6470 loss: 1.6470 2022/09/08 13:42:54 - mmengine - INFO - Epoch(train) [15][1220/1253] lr: 4.0000e-02 eta: 7:09:12 time: 0.5497 data_time: 0.0473 memory: 23504 grad_norm: 2.8428 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.7099 loss: 1.7099 2022/09/08 13:43:05 - mmengine - INFO - Epoch(train) [15][1240/1253] lr: 4.0000e-02 eta: 7:08:59 time: 0.5612 data_time: 0.0304 memory: 23504 grad_norm: 2.8005 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.7096 loss: 1.7096 2022/09/08 13:43:10 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 13:43:10 - mmengine - INFO - Epoch(train) [15][1253/1253] lr: 4.0000e-02 eta: 7:08:59 time: 0.4877 data_time: 0.0181 memory: 23504 grad_norm: 2.8715 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.6125 loss: 1.6125 2022/09/08 13:43:32 - mmengine - INFO - Epoch(val) [15][20/104] eta: 0:01:30 time: 1.0819 data_time: 0.9310 memory: 2699 2022/09/08 13:43:47 - mmengine - INFO - Epoch(val) [15][40/104] eta: 0:00:49 time: 0.7689 data_time: 0.6314 memory: 2699 2022/09/08 13:43:53 - mmengine - INFO - Epoch(val) [15][60/104] eta: 0:00:13 time: 0.2976 data_time: 0.1668 memory: 2699 2022/09/08 13:44:05 - mmengine - INFO - Epoch(val) [15][80/104] eta: 0:00:13 time: 0.5759 data_time: 0.4390 memory: 2699 2022/09/08 13:44:17 - mmengine - INFO - Epoch(val) [15][100/104] eta: 0:00:02 time: 0.6006 data_time: 0.4765 memory: 2699 2022/09/08 13:44:30 - mmengine - INFO - Epoch(val) [15][104/104] acc/top1: 0.6108 acc/top5: 0.8407 acc/mean1: 0.6108 2022/09/08 13:44:30 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb/best_acc/top1_epoch_10.pth is removed 2022/09/08 13:44:32 - mmengine - INFO - The best checkpoint with 0.6108 acc/top1 at 15 epoch is saved to best_acc/top1_epoch_15.pth. 2022/09/08 13:44:53 - mmengine - INFO - Epoch(train) [16][20/1253] lr: 4.0000e-02 eta: 7:08:44 time: 1.0527 data_time: 0.4842 memory: 23504 grad_norm: 2.8340 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6263 loss: 1.6263 2022/09/08 13:45:06 - mmengine - INFO - Epoch(train) [16][40/1253] lr: 4.0000e-02 eta: 7:08:34 time: 0.6336 data_time: 0.0388 memory: 23504 grad_norm: 2.8777 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.7776 loss: 1.7776 2022/09/08 13:45:17 - mmengine - INFO - Epoch(train) [16][60/1253] lr: 4.0000e-02 eta: 7:08:21 time: 0.5506 data_time: 0.0335 memory: 23504 grad_norm: 2.8707 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.5547 loss: 1.5547 2022/09/08 13:45:28 - mmengine - INFO - Epoch(train) [16][80/1253] lr: 4.0000e-02 eta: 7:08:07 time: 0.5469 data_time: 0.0388 memory: 23504 grad_norm: 2.7931 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7242 loss: 1.7242 2022/09/08 13:45:41 - mmengine - INFO - Epoch(train) [16][100/1253] lr: 4.0000e-02 eta: 7:07:58 time: 0.6490 data_time: 0.1284 memory: 23504 grad_norm: 2.8432 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.6251 loss: 1.6251 2022/09/08 13:45:52 - mmengine - INFO - Epoch(train) [16][120/1253] lr: 4.0000e-02 eta: 7:07:45 time: 0.5582 data_time: 0.0438 memory: 23504 grad_norm: 2.8568 top1_acc: 0.5833 top5_acc: 0.9583 loss_cls: 1.4652 loss: 1.4652 2022/09/08 13:46:03 - mmengine - INFO - Epoch(train) [16][140/1253] lr: 4.0000e-02 eta: 7:07:33 time: 0.5660 data_time: 0.0399 memory: 23504 grad_norm: 2.7970 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7254 loss: 1.7254 2022/09/08 13:46:15 - mmengine - INFO - Epoch(train) [16][160/1253] lr: 4.0000e-02 eta: 7:07:21 time: 0.5820 data_time: 0.0371 memory: 23504 grad_norm: 2.8147 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.4834 loss: 1.4834 2022/09/08 13:46:27 - mmengine - INFO - Epoch(train) [16][180/1253] lr: 4.0000e-02 eta: 7:07:10 time: 0.6176 data_time: 0.0554 memory: 23504 grad_norm: 2.8455 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.6542 loss: 1.6542 2022/09/08 13:46:39 - mmengine - INFO - Epoch(train) [16][200/1253] lr: 4.0000e-02 eta: 7:06:59 time: 0.5858 data_time: 0.0477 memory: 23504 grad_norm: 2.8509 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7049 loss: 1.7049 2022/09/08 13:46:46 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 13:46:53 - mmengine - INFO - Epoch(train) [16][220/1253] lr: 4.0000e-02 eta: 7:06:54 time: 0.7372 data_time: 0.0380 memory: 23504 grad_norm: 2.8292 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.5438 loss: 1.5438 2022/09/08 13:47:05 - mmengine - INFO - Epoch(train) [16][240/1253] lr: 4.0000e-02 eta: 7:06:41 time: 0.5622 data_time: 0.0486 memory: 23504 grad_norm: 2.8081 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.6297 loss: 1.6297 2022/09/08 13:47:16 - mmengine - INFO - Epoch(train) [16][260/1253] lr: 4.0000e-02 eta: 7:06:28 time: 0.5536 data_time: 0.0414 memory: 23504 grad_norm: 2.8975 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.5990 loss: 1.5990 2022/09/08 13:47:27 - mmengine - INFO - Epoch(train) [16][280/1253] lr: 4.0000e-02 eta: 7:06:16 time: 0.5828 data_time: 0.0589 memory: 23504 grad_norm: 2.9128 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.6485 loss: 1.6485 2022/09/08 13:47:38 - mmengine - INFO - Epoch(train) [16][300/1253] lr: 4.0000e-02 eta: 7:06:02 time: 0.5475 data_time: 0.0343 memory: 23504 grad_norm: 2.8700 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 1.6540 loss: 1.6540 2022/09/08 13:47:50 - mmengine - INFO - Epoch(train) [16][320/1253] lr: 4.0000e-02 eta: 7:05:51 time: 0.5900 data_time: 0.0371 memory: 23504 grad_norm: 2.8268 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.4956 loss: 1.4956 2022/09/08 13:48:03 - mmengine - INFO - Epoch(train) [16][340/1253] lr: 4.0000e-02 eta: 7:05:40 time: 0.6159 data_time: 0.0507 memory: 23504 grad_norm: 2.9365 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 1.7488 loss: 1.7488 2022/09/08 13:48:15 - mmengine - INFO - Epoch(train) [16][360/1253] lr: 4.0000e-02 eta: 7:05:30 time: 0.6250 data_time: 0.0587 memory: 23504 grad_norm: 2.9091 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.4837 loss: 1.4837 2022/09/08 13:48:28 - mmengine - INFO - Epoch(train) [16][380/1253] lr: 4.0000e-02 eta: 7:05:20 time: 0.6283 data_time: 0.0336 memory: 23504 grad_norm: 2.8852 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.6926 loss: 1.6926 2022/09/08 13:48:39 - mmengine - INFO - Epoch(train) [16][400/1253] lr: 4.0000e-02 eta: 7:05:08 time: 0.5734 data_time: 0.0376 memory: 23504 grad_norm: 2.8398 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.4699 loss: 1.4699 2022/09/08 13:48:50 - mmengine - INFO - Epoch(train) [16][420/1253] lr: 4.0000e-02 eta: 7:04:55 time: 0.5557 data_time: 0.0494 memory: 23504 grad_norm: 2.8028 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.5823 loss: 1.5823 2022/09/08 13:49:01 - mmengine - INFO - Epoch(train) [16][440/1253] lr: 4.0000e-02 eta: 7:04:42 time: 0.5635 data_time: 0.0466 memory: 23504 grad_norm: 2.8356 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.5295 loss: 1.5295 2022/09/08 13:49:13 - mmengine - INFO - Epoch(train) [16][460/1253] lr: 4.0000e-02 eta: 7:04:29 time: 0.5631 data_time: 0.0488 memory: 23504 grad_norm: 2.8490 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.7333 loss: 1.7333 2022/09/08 13:49:24 - mmengine - INFO - Epoch(train) [16][480/1253] lr: 4.0000e-02 eta: 7:04:16 time: 0.5587 data_time: 0.0493 memory: 23504 grad_norm: 2.8283 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5790 loss: 1.5790 2022/09/08 13:49:36 - mmengine - INFO - Epoch(train) [16][500/1253] lr: 4.0000e-02 eta: 7:04:04 time: 0.5877 data_time: 0.0432 memory: 23504 grad_norm: 2.8942 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6068 loss: 1.6068 2022/09/08 13:49:49 - mmengine - INFO - Epoch(train) [16][520/1253] lr: 4.0000e-02 eta: 7:03:55 time: 0.6443 data_time: 0.0390 memory: 23504 grad_norm: 2.9157 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7353 loss: 1.7353 2022/09/08 13:50:00 - mmengine - INFO - Epoch(train) [16][540/1253] lr: 4.0000e-02 eta: 7:03:43 time: 0.5758 data_time: 0.0669 memory: 23504 grad_norm: 2.8314 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.5054 loss: 1.5054 2022/09/08 13:50:11 - mmengine - INFO - Epoch(train) [16][560/1253] lr: 4.0000e-02 eta: 7:03:30 time: 0.5695 data_time: 0.0397 memory: 23504 grad_norm: 2.9381 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6518 loss: 1.6518 2022/09/08 13:50:23 - mmengine - INFO - Epoch(train) [16][580/1253] lr: 4.0000e-02 eta: 7:03:19 time: 0.5893 data_time: 0.0462 memory: 23504 grad_norm: 2.8531 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.6580 loss: 1.6580 2022/09/08 13:50:35 - mmengine - INFO - Epoch(train) [16][600/1253] lr: 4.0000e-02 eta: 7:03:07 time: 0.5775 data_time: 0.0363 memory: 23504 grad_norm: 2.8169 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.6251 loss: 1.6251 2022/09/08 13:50:46 - mmengine - INFO - Epoch(train) [16][620/1253] lr: 4.0000e-02 eta: 7:02:55 time: 0.5774 data_time: 0.0332 memory: 23504 grad_norm: 2.8737 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.6441 loss: 1.6441 2022/09/08 13:50:59 - mmengine - INFO - Epoch(train) [16][640/1253] lr: 4.0000e-02 eta: 7:02:45 time: 0.6286 data_time: 0.0963 memory: 23504 grad_norm: 2.8377 top1_acc: 0.4583 top5_acc: 0.9167 loss_cls: 1.5798 loss: 1.5798 2022/09/08 13:51:10 - mmengine - INFO - Epoch(train) [16][660/1253] lr: 4.0000e-02 eta: 7:02:33 time: 0.5796 data_time: 0.0419 memory: 23504 grad_norm: 2.8798 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.6051 loss: 1.6051 2022/09/08 13:51:23 - mmengine - INFO - Epoch(train) [16][680/1253] lr: 4.0000e-02 eta: 7:02:23 time: 0.6347 data_time: 0.0712 memory: 23504 grad_norm: 2.8233 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.6940 loss: 1.6940 2022/09/08 13:51:35 - mmengine - INFO - Epoch(train) [16][700/1253] lr: 4.0000e-02 eta: 7:02:11 time: 0.5921 data_time: 0.0407 memory: 23504 grad_norm: 2.7812 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.5755 loss: 1.5755 2022/09/08 13:51:47 - mmengine - INFO - Epoch(train) [16][720/1253] lr: 4.0000e-02 eta: 7:02:00 time: 0.5862 data_time: 0.0381 memory: 23504 grad_norm: 2.8859 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.4561 loss: 1.4561 2022/09/08 13:51:58 - mmengine - INFO - Epoch(train) [16][740/1253] lr: 4.0000e-02 eta: 7:01:47 time: 0.5715 data_time: 0.0321 memory: 23504 grad_norm: 2.8957 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5600 loss: 1.5600 2022/09/08 13:52:12 - mmengine - INFO - Epoch(train) [16][760/1253] lr: 4.0000e-02 eta: 7:01:39 time: 0.6753 data_time: 0.0473 memory: 23504 grad_norm: 2.8718 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6627 loss: 1.6627 2022/09/08 13:52:23 - mmengine - INFO - Epoch(train) [16][780/1253] lr: 4.0000e-02 eta: 7:01:26 time: 0.5517 data_time: 0.0361 memory: 23504 grad_norm: 2.8395 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.7836 loss: 1.7836 2022/09/08 13:52:35 - mmengine - INFO - Epoch(train) [16][800/1253] lr: 4.0000e-02 eta: 7:01:14 time: 0.5889 data_time: 0.0379 memory: 23504 grad_norm: 2.8128 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.6217 loss: 1.6217 2022/09/08 13:52:46 - mmengine - INFO - Epoch(train) [16][820/1253] lr: 4.0000e-02 eta: 7:01:02 time: 0.5763 data_time: 0.0455 memory: 23504 grad_norm: 2.8565 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.7857 loss: 1.7857 2022/09/08 13:52:58 - mmengine - INFO - Epoch(train) [16][840/1253] lr: 4.0000e-02 eta: 7:00:50 time: 0.5838 data_time: 0.0354 memory: 23504 grad_norm: 2.8276 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.8151 loss: 1.8151 2022/09/08 13:53:10 - mmengine - INFO - Epoch(train) [16][860/1253] lr: 4.0000e-02 eta: 7:00:39 time: 0.6044 data_time: 0.0932 memory: 23504 grad_norm: 2.8661 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5414 loss: 1.5414 2022/09/08 13:53:21 - mmengine - INFO - Epoch(train) [16][880/1253] lr: 4.0000e-02 eta: 7:00:26 time: 0.5517 data_time: 0.0356 memory: 23504 grad_norm: 2.8012 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.7469 loss: 1.7469 2022/09/08 13:53:33 - mmengine - INFO - Epoch(train) [16][900/1253] lr: 4.0000e-02 eta: 7:00:16 time: 0.6284 data_time: 0.0452 memory: 23504 grad_norm: 2.8559 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.5704 loss: 1.5704 2022/09/08 13:53:45 - mmengine - INFO - Epoch(train) [16][920/1253] lr: 4.0000e-02 eta: 7:00:04 time: 0.5798 data_time: 0.0463 memory: 23504 grad_norm: 2.9023 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.4589 loss: 1.4589 2022/09/08 13:53:57 - mmengine - INFO - Epoch(train) [16][940/1253] lr: 4.0000e-02 eta: 6:59:54 time: 0.6200 data_time: 0.0387 memory: 23504 grad_norm: 2.9181 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.5656 loss: 1.5656 2022/09/08 13:54:09 - mmengine - INFO - Epoch(train) [16][960/1253] lr: 4.0000e-02 eta: 6:59:41 time: 0.5651 data_time: 0.0479 memory: 23504 grad_norm: 2.9333 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.6211 loss: 1.6211 2022/09/08 13:54:21 - mmengine - INFO - Epoch(train) [16][980/1253] lr: 4.0000e-02 eta: 6:59:30 time: 0.5929 data_time: 0.0638 memory: 23504 grad_norm: 2.8260 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.7323 loss: 1.7323 2022/09/08 13:54:32 - mmengine - INFO - Epoch(train) [16][1000/1253] lr: 4.0000e-02 eta: 6:59:18 time: 0.5802 data_time: 0.0378 memory: 23504 grad_norm: 2.7649 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.5433 loss: 1.5433 2022/09/08 13:54:44 - mmengine - INFO - Epoch(train) [16][1020/1253] lr: 4.0000e-02 eta: 6:59:05 time: 0.5782 data_time: 0.0446 memory: 23504 grad_norm: 2.9285 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.7626 loss: 1.7626 2022/09/08 13:54:55 - mmengine - INFO - Epoch(train) [16][1040/1253] lr: 4.0000e-02 eta: 6:58:53 time: 0.5632 data_time: 0.0354 memory: 23504 grad_norm: 2.8303 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.5759 loss: 1.5759 2022/09/08 13:55:07 - mmengine - INFO - Epoch(train) [16][1060/1253] lr: 4.0000e-02 eta: 6:58:41 time: 0.5783 data_time: 0.0401 memory: 23504 grad_norm: 2.8600 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.8264 loss: 1.8264 2022/09/08 13:55:19 - mmengine - INFO - Epoch(train) [16][1080/1253] lr: 4.0000e-02 eta: 6:58:30 time: 0.6200 data_time: 0.0358 memory: 23504 grad_norm: 2.8683 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.5524 loss: 1.5524 2022/09/08 13:55:31 - mmengine - INFO - Epoch(train) [16][1100/1253] lr: 4.0000e-02 eta: 6:58:18 time: 0.5788 data_time: 0.0465 memory: 23504 grad_norm: 2.8891 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.5780 loss: 1.5780 2022/09/08 13:55:42 - mmengine - INFO - Epoch(train) [16][1120/1253] lr: 4.0000e-02 eta: 6:58:06 time: 0.5736 data_time: 0.0434 memory: 23504 grad_norm: 2.8020 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 1.7402 loss: 1.7402 2022/09/08 13:55:56 - mmengine - INFO - Epoch(train) [16][1140/1253] lr: 4.0000e-02 eta: 6:57:58 time: 0.6736 data_time: 0.0572 memory: 23504 grad_norm: 2.9337 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5131 loss: 1.5131 2022/09/08 13:56:07 - mmengine - INFO - Epoch(train) [16][1160/1253] lr: 4.0000e-02 eta: 6:57:46 time: 0.5857 data_time: 0.0303 memory: 23504 grad_norm: 2.8053 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7455 loss: 1.7455 2022/09/08 13:56:19 - mmengine - INFO - Epoch(train) [16][1180/1253] lr: 4.0000e-02 eta: 6:57:34 time: 0.5753 data_time: 0.0343 memory: 23504 grad_norm: 2.8043 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.6777 loss: 1.6777 2022/09/08 13:56:30 - mmengine - INFO - Epoch(train) [16][1200/1253] lr: 4.0000e-02 eta: 6:57:21 time: 0.5660 data_time: 0.0386 memory: 23504 grad_norm: 2.7924 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.6824 loss: 1.6824 2022/09/08 13:56:33 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 13:56:41 - mmengine - INFO - Epoch(train) [16][1220/1253] lr: 4.0000e-02 eta: 6:57:08 time: 0.5559 data_time: 0.0464 memory: 23504 grad_norm: 2.8664 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.5116 loss: 1.5116 2022/09/08 13:56:51 - mmengine - INFO - Epoch(train) [16][1240/1253] lr: 4.0000e-02 eta: 6:56:52 time: 0.4933 data_time: 0.0329 memory: 23504 grad_norm: 2.8718 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.5783 loss: 1.5783 2022/09/08 13:56:57 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 13:56:57 - mmengine - INFO - Epoch(train) [16][1253/1253] lr: 4.0000e-02 eta: 6:56:52 time: 0.4303 data_time: 0.0162 memory: 23504 grad_norm: 2.9533 top1_acc: 0.4286 top5_acc: 0.5714 loss_cls: 1.5815 loss: 1.5815 2022/09/08 13:57:21 - mmengine - INFO - Epoch(train) [17][20/1253] lr: 4.0000e-02 eta: 6:56:44 time: 1.2278 data_time: 0.4231 memory: 23504 grad_norm: 2.7810 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5921 loss: 1.5921 2022/09/08 13:57:33 - mmengine - INFO - Epoch(train) [17][40/1253] lr: 4.0000e-02 eta: 6:56:32 time: 0.5907 data_time: 0.0725 memory: 23504 grad_norm: 2.7920 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.6251 loss: 1.6251 2022/09/08 13:57:46 - mmengine - INFO - Epoch(train) [17][60/1253] lr: 4.0000e-02 eta: 6:56:23 time: 0.6555 data_time: 0.0348 memory: 23504 grad_norm: 2.8383 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.5224 loss: 1.5224 2022/09/08 13:57:57 - mmengine - INFO - Epoch(train) [17][80/1253] lr: 4.0000e-02 eta: 6:56:11 time: 0.5618 data_time: 0.0313 memory: 23504 grad_norm: 2.8290 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.5252 loss: 1.5252 2022/09/08 13:58:11 - mmengine - INFO - Epoch(train) [17][100/1253] lr: 4.0000e-02 eta: 6:56:02 time: 0.6626 data_time: 0.0377 memory: 23504 grad_norm: 2.7954 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.4614 loss: 1.4614 2022/09/08 13:58:22 - mmengine - INFO - Epoch(train) [17][120/1253] lr: 4.0000e-02 eta: 6:55:49 time: 0.5433 data_time: 0.0499 memory: 23504 grad_norm: 2.7947 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.5707 loss: 1.5707 2022/09/08 13:58:33 - mmengine - INFO - Epoch(train) [17][140/1253] lr: 4.0000e-02 eta: 6:55:37 time: 0.5865 data_time: 0.0385 memory: 23504 grad_norm: 2.8527 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7415 loss: 1.7415 2022/09/08 13:58:44 - mmengine - INFO - Epoch(train) [17][160/1253] lr: 4.0000e-02 eta: 6:55:23 time: 0.5481 data_time: 0.0442 memory: 23504 grad_norm: 2.8243 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 1.4956 loss: 1.4956 2022/09/08 13:58:55 - mmengine - INFO - Epoch(train) [17][180/1253] lr: 4.0000e-02 eta: 6:55:11 time: 0.5628 data_time: 0.0414 memory: 23504 grad_norm: 2.7839 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5353 loss: 1.5353 2022/09/08 13:59:12 - mmengine - INFO - Epoch(train) [17][200/1253] lr: 4.0000e-02 eta: 6:55:08 time: 0.8030 data_time: 0.0415 memory: 23504 grad_norm: 2.8664 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.4533 loss: 1.4533 2022/09/08 13:59:23 - mmengine - INFO - Epoch(train) [17][220/1253] lr: 4.0000e-02 eta: 6:54:55 time: 0.5680 data_time: 0.0287 memory: 23504 grad_norm: 2.8864 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.7102 loss: 1.7102 2022/09/08 13:59:34 - mmengine - INFO - Epoch(train) [17][240/1253] lr: 4.0000e-02 eta: 6:54:42 time: 0.5392 data_time: 0.0386 memory: 23504 grad_norm: 2.8787 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.4618 loss: 1.4618 2022/09/08 13:59:45 - mmengine - INFO - Epoch(train) [17][260/1253] lr: 4.0000e-02 eta: 6:54:29 time: 0.5708 data_time: 0.0703 memory: 23504 grad_norm: 2.8420 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6626 loss: 1.6626 2022/09/08 13:59:57 - mmengine - INFO - Epoch(train) [17][280/1253] lr: 4.0000e-02 eta: 6:54:17 time: 0.5725 data_time: 0.0413 memory: 23504 grad_norm: 2.8085 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.6087 loss: 1.6087 2022/09/08 14:00:08 - mmengine - INFO - Epoch(train) [17][300/1253] lr: 4.0000e-02 eta: 6:54:05 time: 0.5770 data_time: 0.0420 memory: 23504 grad_norm: 2.8299 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.5940 loss: 1.5940 2022/09/08 14:00:20 - mmengine - INFO - Epoch(train) [17][320/1253] lr: 4.0000e-02 eta: 6:53:52 time: 0.5797 data_time: 0.0461 memory: 23504 grad_norm: 2.7776 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.5443 loss: 1.5443 2022/09/08 14:00:32 - mmengine - INFO - Epoch(train) [17][340/1253] lr: 4.0000e-02 eta: 6:53:41 time: 0.5918 data_time: 0.0382 memory: 23504 grad_norm: 2.8439 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.4906 loss: 1.4906 2022/09/08 14:00:43 - mmengine - INFO - Epoch(train) [17][360/1253] lr: 4.0000e-02 eta: 6:53:29 time: 0.5817 data_time: 0.0458 memory: 23504 grad_norm: 2.8469 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.5790 loss: 1.5790 2022/09/08 14:00:54 - mmengine - INFO - Epoch(train) [17][380/1253] lr: 4.0000e-02 eta: 6:53:15 time: 0.5458 data_time: 0.0410 memory: 23504 grad_norm: 2.9112 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.5111 loss: 1.5111 2022/09/08 14:01:06 - mmengine - INFO - Epoch(train) [17][400/1253] lr: 4.0000e-02 eta: 6:53:04 time: 0.5832 data_time: 0.0391 memory: 23504 grad_norm: 2.8195 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5733 loss: 1.5733 2022/09/08 14:01:18 - mmengine - INFO - Epoch(train) [17][420/1253] lr: 4.0000e-02 eta: 6:52:52 time: 0.5884 data_time: 0.0440 memory: 23504 grad_norm: 2.8734 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5325 loss: 1.5325 2022/09/08 14:01:29 - mmengine - INFO - Epoch(train) [17][440/1253] lr: 4.0000e-02 eta: 6:52:40 time: 0.5820 data_time: 0.0487 memory: 23504 grad_norm: 2.8884 top1_acc: 0.7083 top5_acc: 0.7500 loss_cls: 1.5394 loss: 1.5394 2022/09/08 14:01:41 - mmengine - INFO - Epoch(train) [17][460/1253] lr: 4.0000e-02 eta: 6:52:28 time: 0.5835 data_time: 0.0351 memory: 23504 grad_norm: 2.7971 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.6503 loss: 1.6503 2022/09/08 14:01:54 - mmengine - INFO - Epoch(train) [17][480/1253] lr: 4.0000e-02 eta: 6:52:20 time: 0.6814 data_time: 0.0438 memory: 23504 grad_norm: 2.8349 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.5980 loss: 1.5980 2022/09/08 14:02:05 - mmengine - INFO - Epoch(train) [17][500/1253] lr: 4.0000e-02 eta: 6:52:07 time: 0.5477 data_time: 0.0415 memory: 23504 grad_norm: 2.8658 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.6655 loss: 1.6655 2022/09/08 14:02:17 - mmengine - INFO - Epoch(train) [17][520/1253] lr: 4.0000e-02 eta: 6:51:54 time: 0.5724 data_time: 0.0415 memory: 23504 grad_norm: 2.9077 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.6743 loss: 1.6743 2022/09/08 14:02:29 - mmengine - INFO - Epoch(train) [17][540/1253] lr: 4.0000e-02 eta: 6:51:44 time: 0.6190 data_time: 0.0432 memory: 23504 grad_norm: 2.8544 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 1.5936 loss: 1.5936 2022/09/08 14:02:42 - mmengine - INFO - Epoch(train) [17][560/1253] lr: 4.0000e-02 eta: 6:51:34 time: 0.6334 data_time: 0.0734 memory: 23504 grad_norm: 2.8592 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6632 loss: 1.6632 2022/09/08 14:02:53 - mmengine - INFO - Epoch(train) [17][580/1253] lr: 4.0000e-02 eta: 6:51:21 time: 0.5574 data_time: 0.0341 memory: 23504 grad_norm: 2.8585 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.5637 loss: 1.5637 2022/09/08 14:03:04 - mmengine - INFO - Epoch(train) [17][600/1253] lr: 4.0000e-02 eta: 6:51:08 time: 0.5632 data_time: 0.0492 memory: 23504 grad_norm: 2.8385 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.6932 loss: 1.6932 2022/09/08 14:03:16 - mmengine - INFO - Epoch(train) [17][620/1253] lr: 4.0000e-02 eta: 6:50:55 time: 0.5561 data_time: 0.0453 memory: 23504 grad_norm: 2.8144 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5600 loss: 1.5600 2022/09/08 14:03:27 - mmengine - INFO - Epoch(train) [17][640/1253] lr: 4.0000e-02 eta: 6:50:42 time: 0.5506 data_time: 0.0570 memory: 23504 grad_norm: 2.8920 top1_acc: 0.5833 top5_acc: 0.9583 loss_cls: 1.5263 loss: 1.5263 2022/09/08 14:03:39 - mmengine - INFO - Epoch(train) [17][660/1253] lr: 4.0000e-02 eta: 6:50:33 time: 0.6400 data_time: 0.0608 memory: 23504 grad_norm: 2.9760 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 1.7345 loss: 1.7345 2022/09/08 14:03:51 - mmengine - INFO - Epoch(train) [17][680/1253] lr: 4.0000e-02 eta: 6:50:20 time: 0.5706 data_time: 0.0439 memory: 23504 grad_norm: 2.8113 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.5470 loss: 1.5470 2022/09/08 14:04:02 - mmengine - INFO - Epoch(train) [17][700/1253] lr: 4.0000e-02 eta: 6:50:07 time: 0.5628 data_time: 0.0473 memory: 23504 grad_norm: 2.8248 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 1.6395 loss: 1.6395 2022/09/08 14:04:13 - mmengine - INFO - Epoch(train) [17][720/1253] lr: 4.0000e-02 eta: 6:49:55 time: 0.5742 data_time: 0.0495 memory: 23504 grad_norm: 2.7937 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.7580 loss: 1.7580 2022/09/08 14:04:25 - mmengine - INFO - Epoch(train) [17][740/1253] lr: 4.0000e-02 eta: 6:49:43 time: 0.5700 data_time: 0.0433 memory: 23504 grad_norm: 2.8729 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7613 loss: 1.7613 2022/09/08 14:04:36 - mmengine - INFO - Epoch(train) [17][760/1253] lr: 4.0000e-02 eta: 6:49:29 time: 0.5460 data_time: 0.0438 memory: 23504 grad_norm: 2.8293 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.5339 loss: 1.5339 2022/09/08 14:04:47 - mmengine - INFO - Epoch(train) [17][780/1253] lr: 4.0000e-02 eta: 6:49:17 time: 0.5719 data_time: 0.0547 memory: 23504 grad_norm: 2.8090 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.5970 loss: 1.5970 2022/09/08 14:05:00 - mmengine - INFO - Epoch(train) [17][800/1253] lr: 4.0000e-02 eta: 6:49:08 time: 0.6567 data_time: 0.0906 memory: 23504 grad_norm: 2.8798 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.7351 loss: 1.7351 2022/09/08 14:05:13 - mmengine - INFO - Epoch(train) [17][820/1253] lr: 4.0000e-02 eta: 6:48:57 time: 0.6159 data_time: 0.0314 memory: 23504 grad_norm: 2.8633 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.6081 loss: 1.6081 2022/09/08 14:05:24 - mmengine - INFO - Epoch(train) [17][840/1253] lr: 4.0000e-02 eta: 6:48:45 time: 0.5625 data_time: 0.0385 memory: 23504 grad_norm: 2.8759 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.6021 loss: 1.6021 2022/09/08 14:05:35 - mmengine - INFO - Epoch(train) [17][860/1253] lr: 4.0000e-02 eta: 6:48:32 time: 0.5753 data_time: 0.0482 memory: 23504 grad_norm: 2.8222 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6059 loss: 1.6059 2022/09/08 14:05:47 - mmengine - INFO - Epoch(train) [17][880/1253] lr: 4.0000e-02 eta: 6:48:21 time: 0.5861 data_time: 0.0416 memory: 23504 grad_norm: 2.9389 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.7048 loss: 1.7048 2022/09/08 14:05:59 - mmengine - INFO - Epoch(train) [17][900/1253] lr: 4.0000e-02 eta: 6:48:09 time: 0.5812 data_time: 0.0385 memory: 23504 grad_norm: 2.8875 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6134 loss: 1.6134 2022/09/08 14:06:11 - mmengine - INFO - Epoch(train) [17][920/1253] lr: 4.0000e-02 eta: 6:47:58 time: 0.6281 data_time: 0.0848 memory: 23504 grad_norm: 2.8423 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.5764 loss: 1.5764 2022/09/08 14:06:23 - mmengine - INFO - Epoch(train) [17][940/1253] lr: 4.0000e-02 eta: 6:47:46 time: 0.5676 data_time: 0.0336 memory: 23504 grad_norm: 2.8855 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.7284 loss: 1.7284 2022/09/08 14:06:30 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 14:06:34 - mmengine - INFO - Epoch(train) [17][960/1253] lr: 4.0000e-02 eta: 6:47:33 time: 0.5676 data_time: 0.0453 memory: 23504 grad_norm: 2.8437 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.7267 loss: 1.7267 2022/09/08 14:06:45 - mmengine - INFO - Epoch(train) [17][980/1253] lr: 4.0000e-02 eta: 6:47:21 time: 0.5656 data_time: 0.0407 memory: 23504 grad_norm: 2.7378 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 1.5661 loss: 1.5661 2022/09/08 14:07:00 - mmengine - INFO - Epoch(train) [17][1000/1253] lr: 4.0000e-02 eta: 6:47:14 time: 0.7051 data_time: 0.0402 memory: 23504 grad_norm: 2.8427 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6860 loss: 1.6860 2022/09/08 14:07:11 - mmengine - INFO - Epoch(train) [17][1020/1253] lr: 4.0000e-02 eta: 6:47:01 time: 0.5683 data_time: 0.0373 memory: 23504 grad_norm: 2.8078 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8163 loss: 1.8163 2022/09/08 14:07:22 - mmengine - INFO - Epoch(train) [17][1040/1253] lr: 4.0000e-02 eta: 6:46:48 time: 0.5553 data_time: 0.0517 memory: 23504 grad_norm: 2.8116 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 1.5416 loss: 1.5416 2022/09/08 14:07:33 - mmengine - INFO - Epoch(train) [17][1060/1253] lr: 4.0000e-02 eta: 6:46:36 time: 0.5629 data_time: 0.0404 memory: 23504 grad_norm: 2.8389 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.6965 loss: 1.6965 2022/09/08 14:07:45 - mmengine - INFO - Epoch(train) [17][1080/1253] lr: 4.0000e-02 eta: 6:46:23 time: 0.5760 data_time: 0.0348 memory: 23504 grad_norm: 2.8599 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5975 loss: 1.5975 2022/09/08 14:07:58 - mmengine - INFO - Epoch(train) [17][1100/1253] lr: 4.0000e-02 eta: 6:46:14 time: 0.6523 data_time: 0.0869 memory: 23504 grad_norm: 2.9177 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.6033 loss: 1.6033 2022/09/08 14:08:09 - mmengine - INFO - Epoch(train) [17][1120/1253] lr: 4.0000e-02 eta: 6:46:01 time: 0.5589 data_time: 0.0429 memory: 23504 grad_norm: 2.8359 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.7165 loss: 1.7165 2022/09/08 14:08:20 - mmengine - INFO - Epoch(train) [17][1140/1253] lr: 4.0000e-02 eta: 6:45:49 time: 0.5624 data_time: 0.0358 memory: 23504 grad_norm: 2.7616 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.6505 loss: 1.6505 2022/09/08 14:08:32 - mmengine - INFO - Epoch(train) [17][1160/1253] lr: 4.0000e-02 eta: 6:45:37 time: 0.5848 data_time: 0.0453 memory: 23504 grad_norm: 2.8995 top1_acc: 0.5000 top5_acc: 0.9167 loss_cls: 1.8132 loss: 1.8132 2022/09/08 14:08:43 - mmengine - INFO - Epoch(train) [17][1180/1253] lr: 4.0000e-02 eta: 6:45:24 time: 0.5561 data_time: 0.0425 memory: 23504 grad_norm: 2.8490 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5542 loss: 1.5542 2022/09/08 14:08:54 - mmengine - INFO - Epoch(train) [17][1200/1253] lr: 4.0000e-02 eta: 6:45:11 time: 0.5652 data_time: 0.0414 memory: 23504 grad_norm: 2.8771 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.5948 loss: 1.5948 2022/09/08 14:09:07 - mmengine - INFO - Epoch(train) [17][1220/1253] lr: 4.0000e-02 eta: 6:45:01 time: 0.6352 data_time: 0.0469 memory: 23504 grad_norm: 2.8128 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.6312 loss: 1.6312 2022/09/08 14:09:17 - mmengine - INFO - Epoch(train) [17][1240/1253] lr: 4.0000e-02 eta: 6:44:46 time: 0.4934 data_time: 0.0201 memory: 23504 grad_norm: 2.9085 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.6110 loss: 1.6110 2022/09/08 14:09:23 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 14:09:23 - mmengine - INFO - Epoch(train) [17][1253/1253] lr: 4.0000e-02 eta: 6:44:46 time: 0.4330 data_time: 0.0213 memory: 23504 grad_norm: 2.9728 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.4247 loss: 1.4247 2022/09/08 14:09:46 - mmengine - INFO - Epoch(train) [18][20/1253] lr: 4.0000e-02 eta: 6:44:34 time: 1.1623 data_time: 0.4096 memory: 23504 grad_norm: 2.8478 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.6709 loss: 1.6709 2022/09/08 14:09:59 - mmengine - INFO - Epoch(train) [18][40/1253] lr: 4.0000e-02 eta: 6:44:26 time: 0.6733 data_time: 0.0589 memory: 23504 grad_norm: 2.8221 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7089 loss: 1.7089 2022/09/08 14:10:10 - mmengine - INFO - Epoch(train) [18][60/1253] lr: 4.0000e-02 eta: 6:44:12 time: 0.5465 data_time: 0.0324 memory: 23504 grad_norm: 2.8021 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5572 loss: 1.5572 2022/09/08 14:10:21 - mmengine - INFO - Epoch(train) [18][80/1253] lr: 4.0000e-02 eta: 6:43:59 time: 0.5514 data_time: 0.0323 memory: 23504 grad_norm: 2.7774 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6033 loss: 1.6033 2022/09/08 14:10:37 - mmengine - INFO - Epoch(train) [18][100/1253] lr: 4.0000e-02 eta: 6:43:55 time: 0.7750 data_time: 0.0336 memory: 23504 grad_norm: 3.0035 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.7648 loss: 1.7648 2022/09/08 14:10:48 - mmengine - INFO - Epoch(train) [18][120/1253] lr: 4.0000e-02 eta: 6:43:43 time: 0.5822 data_time: 0.0340 memory: 23504 grad_norm: 2.9214 top1_acc: 0.4583 top5_acc: 0.8750 loss_cls: 1.4937 loss: 1.4937 2022/09/08 14:11:00 - mmengine - INFO - Epoch(train) [18][140/1253] lr: 4.0000e-02 eta: 6:43:31 time: 0.5793 data_time: 0.0756 memory: 23504 grad_norm: 2.8821 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.7137 loss: 1.7137 2022/09/08 14:11:12 - mmengine - INFO - Epoch(train) [18][160/1253] lr: 4.0000e-02 eta: 6:43:19 time: 0.5891 data_time: 0.0523 memory: 23504 grad_norm: 2.8240 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5494 loss: 1.5494 2022/09/08 14:11:23 - mmengine - INFO - Epoch(train) [18][180/1253] lr: 4.0000e-02 eta: 6:43:06 time: 0.5639 data_time: 0.0438 memory: 23504 grad_norm: 2.8890 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.6291 loss: 1.6291 2022/09/08 14:11:35 - mmengine - INFO - Epoch(train) [18][200/1253] lr: 4.0000e-02 eta: 6:42:55 time: 0.5927 data_time: 0.0416 memory: 23504 grad_norm: 2.9258 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6808 loss: 1.6808 2022/09/08 14:11:46 - mmengine - INFO - Epoch(train) [18][220/1253] lr: 4.0000e-02 eta: 6:42:42 time: 0.5676 data_time: 0.0318 memory: 23504 grad_norm: 2.9423 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.6264 loss: 1.6264 2022/09/08 14:11:58 - mmengine - INFO - Epoch(train) [18][240/1253] lr: 4.0000e-02 eta: 6:42:31 time: 0.6015 data_time: 0.0528 memory: 23504 grad_norm: 2.8700 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.7232 loss: 1.7232 2022/09/08 14:12:10 - mmengine - INFO - Epoch(train) [18][260/1253] lr: 4.0000e-02 eta: 6:42:19 time: 0.5702 data_time: 0.0422 memory: 23504 grad_norm: 2.9633 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.6550 loss: 1.6550 2022/09/08 14:12:21 - mmengine - INFO - Epoch(train) [18][280/1253] lr: 4.0000e-02 eta: 6:42:06 time: 0.5553 data_time: 0.0467 memory: 23504 grad_norm: 2.8633 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.4931 loss: 1.4931 2022/09/08 14:12:32 - mmengine - INFO - Epoch(train) [18][300/1253] lr: 4.0000e-02 eta: 6:41:53 time: 0.5685 data_time: 0.0448 memory: 23504 grad_norm: 2.9208 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.4921 loss: 1.4921 2022/09/08 14:12:45 - mmengine - INFO - Epoch(train) [18][320/1253] lr: 4.0000e-02 eta: 6:41:43 time: 0.6227 data_time: 0.0399 memory: 23504 grad_norm: 2.8724 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 1.4233 loss: 1.4233 2022/09/08 14:12:56 - mmengine - INFO - Epoch(train) [18][340/1253] lr: 4.0000e-02 eta: 6:41:30 time: 0.5599 data_time: 0.0467 memory: 23504 grad_norm: 2.8357 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6245 loss: 1.6245 2022/09/08 14:13:07 - mmengine - INFO - Epoch(train) [18][360/1253] lr: 4.0000e-02 eta: 6:41:18 time: 0.5724 data_time: 0.0441 memory: 23504 grad_norm: 2.9904 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.3714 loss: 1.3714 2022/09/08 14:13:20 - mmengine - INFO - Epoch(train) [18][380/1253] lr: 4.0000e-02 eta: 6:41:08 time: 0.6428 data_time: 0.0406 memory: 23504 grad_norm: 2.8322 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.5412 loss: 1.5412 2022/09/08 14:13:34 - mmengine - INFO - Epoch(train) [18][400/1253] lr: 4.0000e-02 eta: 6:40:59 time: 0.6701 data_time: 0.0300 memory: 23504 grad_norm: 2.8604 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.5807 loss: 1.5807 2022/09/08 14:13:45 - mmengine - INFO - Epoch(train) [18][420/1253] lr: 4.0000e-02 eta: 6:40:47 time: 0.5607 data_time: 0.0455 memory: 23504 grad_norm: 2.9793 top1_acc: 0.7500 top5_acc: 0.7917 loss_cls: 1.5215 loss: 1.5215 2022/09/08 14:13:56 - mmengine - INFO - Epoch(train) [18][440/1253] lr: 4.0000e-02 eta: 6:40:34 time: 0.5640 data_time: 0.0431 memory: 23504 grad_norm: 2.8034 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.6722 loss: 1.6722 2022/09/08 14:14:07 - mmengine - INFO - Epoch(train) [18][460/1253] lr: 4.0000e-02 eta: 6:40:21 time: 0.5653 data_time: 0.0508 memory: 23504 grad_norm: 2.9643 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.7112 loss: 1.7112 2022/09/08 14:14:21 - mmengine - INFO - Epoch(train) [18][480/1253] lr: 4.0000e-02 eta: 6:40:13 time: 0.6901 data_time: 0.0387 memory: 23504 grad_norm: 2.7731 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 1.6857 loss: 1.6857 2022/09/08 14:14:32 - mmengine - INFO - Epoch(train) [18][500/1253] lr: 4.0000e-02 eta: 6:40:00 time: 0.5553 data_time: 0.0378 memory: 23504 grad_norm: 2.8280 top1_acc: 0.3750 top5_acc: 0.7917 loss_cls: 1.6349 loss: 1.6349 2022/09/08 14:14:43 - mmengine - INFO - Epoch(train) [18][520/1253] lr: 4.0000e-02 eta: 6:39:47 time: 0.5512 data_time: 0.0385 memory: 23504 grad_norm: 2.8580 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.5722 loss: 1.5722 2022/09/08 14:14:54 - mmengine - INFO - Epoch(train) [18][540/1253] lr: 4.0000e-02 eta: 6:39:34 time: 0.5472 data_time: 0.0389 memory: 23504 grad_norm: 2.9024 top1_acc: 0.5833 top5_acc: 0.9583 loss_cls: 1.5793 loss: 1.5793 2022/09/08 14:15:06 - mmengine - INFO - Epoch(train) [18][560/1253] lr: 4.0000e-02 eta: 6:39:22 time: 0.5786 data_time: 0.0455 memory: 23504 grad_norm: 2.8584 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.5893 loss: 1.5893 2022/09/08 14:15:18 - mmengine - INFO - Epoch(train) [18][580/1253] lr: 4.0000e-02 eta: 6:39:11 time: 0.6081 data_time: 0.0583 memory: 23504 grad_norm: 2.8501 top1_acc: 0.6250 top5_acc: 0.7083 loss_cls: 1.7308 loss: 1.7308 2022/09/08 14:15:30 - mmengine - INFO - Epoch(train) [18][600/1253] lr: 4.0000e-02 eta: 6:39:01 time: 0.6221 data_time: 0.0359 memory: 23504 grad_norm: 2.7748 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.5931 loss: 1.5931 2022/09/08 14:15:42 - mmengine - INFO - Epoch(train) [18][620/1253] lr: 4.0000e-02 eta: 6:38:49 time: 0.5925 data_time: 0.0329 memory: 23504 grad_norm: 2.9351 top1_acc: 0.5417 top5_acc: 0.6667 loss_cls: 1.5911 loss: 1.5911 2022/09/08 14:15:54 - mmengine - INFO - Epoch(train) [18][640/1253] lr: 4.0000e-02 eta: 6:38:38 time: 0.5971 data_time: 0.0506 memory: 23504 grad_norm: 2.8260 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.6037 loss: 1.6037 2022/09/08 14:16:06 - mmengine - INFO - Epoch(train) [18][660/1253] lr: 4.0000e-02 eta: 6:38:26 time: 0.5856 data_time: 0.0411 memory: 23504 grad_norm: 2.8876 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 1.7638 loss: 1.7638 2022/09/08 14:16:17 - mmengine - INFO - Epoch(train) [18][680/1253] lr: 4.0000e-02 eta: 6:38:13 time: 0.5567 data_time: 0.0379 memory: 23504 grad_norm: 2.8362 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6926 loss: 1.6926 2022/09/08 14:16:28 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 14:16:29 - mmengine - INFO - Epoch(train) [18][700/1253] lr: 4.0000e-02 eta: 6:38:01 time: 0.5753 data_time: 0.0544 memory: 23504 grad_norm: 2.8496 top1_acc: 0.5833 top5_acc: 0.9583 loss_cls: 1.7147 loss: 1.7147 2022/09/08 14:16:40 - mmengine - INFO - Epoch(train) [18][720/1253] lr: 4.0000e-02 eta: 6:37:49 time: 0.5811 data_time: 0.0417 memory: 23504 grad_norm: 2.7785 top1_acc: 0.4167 top5_acc: 0.8750 loss_cls: 1.6653 loss: 1.6653 2022/09/08 14:16:52 - mmengine - INFO - Epoch(train) [18][740/1253] lr: 4.0000e-02 eta: 6:37:37 time: 0.5891 data_time: 0.0397 memory: 23504 grad_norm: 2.8117 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.5609 loss: 1.5609 2022/09/08 14:17:04 - mmengine - INFO - Epoch(train) [18][760/1253] lr: 4.0000e-02 eta: 6:37:25 time: 0.5900 data_time: 0.0547 memory: 23504 grad_norm: 2.8347 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.6361 loss: 1.6361 2022/09/08 14:17:17 - mmengine - INFO - Epoch(train) [18][780/1253] lr: 4.0000e-02 eta: 6:37:17 time: 0.6749 data_time: 0.0449 memory: 23504 grad_norm: 2.8742 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 1.6289 loss: 1.6289 2022/09/08 14:17:28 - mmengine - INFO - Epoch(train) [18][800/1253] lr: 4.0000e-02 eta: 6:37:03 time: 0.5405 data_time: 0.0306 memory: 23504 grad_norm: 2.8949 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.5744 loss: 1.5744 2022/09/08 14:17:40 - mmengine - INFO - Epoch(train) [18][820/1253] lr: 4.0000e-02 eta: 6:36:52 time: 0.5943 data_time: 0.0442 memory: 23504 grad_norm: 2.9313 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.5482 loss: 1.5482 2022/09/08 14:17:51 - mmengine - INFO - Epoch(train) [18][840/1253] lr: 4.0000e-02 eta: 6:36:39 time: 0.5540 data_time: 0.0469 memory: 23504 grad_norm: 2.9095 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.8059 loss: 1.8059 2022/09/08 14:18:03 - mmengine - INFO - Epoch(train) [18][860/1253] lr: 4.0000e-02 eta: 6:36:27 time: 0.5830 data_time: 0.0486 memory: 23504 grad_norm: 2.8751 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.4843 loss: 1.4843 2022/09/08 14:18:15 - mmengine - INFO - Epoch(train) [18][880/1253] lr: 4.0000e-02 eta: 6:36:16 time: 0.6091 data_time: 0.0833 memory: 23504 grad_norm: 2.8660 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.6069 loss: 1.6069 2022/09/08 14:18:26 - mmengine - INFO - Epoch(train) [18][900/1253] lr: 4.0000e-02 eta: 6:36:03 time: 0.5487 data_time: 0.0367 memory: 23504 grad_norm: 2.8269 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.4544 loss: 1.4544 2022/09/08 14:18:39 - mmengine - INFO - Epoch(train) [18][920/1253] lr: 4.0000e-02 eta: 6:35:53 time: 0.6509 data_time: 0.0363 memory: 23504 grad_norm: 2.8453 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.3374 loss: 1.3374 2022/09/08 14:18:51 - mmengine - INFO - Epoch(train) [18][940/1253] lr: 4.0000e-02 eta: 6:35:42 time: 0.6021 data_time: 0.0369 memory: 23504 grad_norm: 2.8924 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.6269 loss: 1.6269 2022/09/08 14:19:02 - mmengine - INFO - Epoch(train) [18][960/1253] lr: 4.0000e-02 eta: 6:35:29 time: 0.5591 data_time: 0.0423 memory: 23504 grad_norm: 2.8423 top1_acc: 0.3750 top5_acc: 0.7917 loss_cls: 1.8626 loss: 1.8626 2022/09/08 14:19:13 - mmengine - INFO - Epoch(train) [18][980/1253] lr: 4.0000e-02 eta: 6:35:16 time: 0.5484 data_time: 0.0415 memory: 23504 grad_norm: 2.8149 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.6154 loss: 1.6154 2022/09/08 14:19:24 - mmengine - INFO - Epoch(train) [18][1000/1253] lr: 4.0000e-02 eta: 6:35:03 time: 0.5536 data_time: 0.0392 memory: 23504 grad_norm: 2.9514 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 1.7302 loss: 1.7302 2022/09/08 14:19:36 - mmengine - INFO - Epoch(train) [18][1020/1253] lr: 4.0000e-02 eta: 6:34:51 time: 0.5858 data_time: 0.0480 memory: 23504 grad_norm: 2.8376 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.7461 loss: 1.7461 2022/09/08 14:19:47 - mmengine - INFO - Epoch(train) [18][1040/1253] lr: 4.0000e-02 eta: 6:34:39 time: 0.5643 data_time: 0.0450 memory: 23504 grad_norm: 2.8360 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.5788 loss: 1.5788 2022/09/08 14:19:59 - mmengine - INFO - Epoch(train) [18][1060/1253] lr: 4.0000e-02 eta: 6:34:28 time: 0.6095 data_time: 0.0444 memory: 23504 grad_norm: 2.8492 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.6326 loss: 1.6326 2022/09/08 14:20:11 - mmengine - INFO - Epoch(train) [18][1080/1253] lr: 4.0000e-02 eta: 6:34:16 time: 0.5807 data_time: 0.0444 memory: 23504 grad_norm: 2.7696 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6586 loss: 1.6586 2022/09/08 14:20:23 - mmengine - INFO - Epoch(train) [18][1100/1253] lr: 4.0000e-02 eta: 6:34:04 time: 0.5795 data_time: 0.0494 memory: 23504 grad_norm: 2.8744 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.7480 loss: 1.7480 2022/09/08 14:20:34 - mmengine - INFO - Epoch(train) [18][1120/1253] lr: 4.0000e-02 eta: 6:33:52 time: 0.5759 data_time: 0.0484 memory: 23504 grad_norm: 2.8353 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.5474 loss: 1.5474 2022/09/08 14:20:46 - mmengine - INFO - Epoch(train) [18][1140/1253] lr: 4.0000e-02 eta: 6:33:39 time: 0.5691 data_time: 0.0415 memory: 23504 grad_norm: 2.9159 top1_acc: 0.2917 top5_acc: 0.7083 loss_cls: 1.6570 loss: 1.6570 2022/09/08 14:20:57 - mmengine - INFO - Epoch(train) [18][1160/1253] lr: 4.0000e-02 eta: 6:33:28 time: 0.5915 data_time: 0.0473 memory: 23504 grad_norm: 2.8271 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.7393 loss: 1.7393 2022/09/08 14:21:09 - mmengine - INFO - Epoch(train) [18][1180/1253] lr: 4.0000e-02 eta: 6:33:16 time: 0.5812 data_time: 0.0363 memory: 23504 grad_norm: 2.7668 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.6134 loss: 1.6134 2022/09/08 14:21:22 - mmengine - INFO - Epoch(train) [18][1200/1253] lr: 4.0000e-02 eta: 6:33:05 time: 0.6302 data_time: 0.0415 memory: 23504 grad_norm: 2.8681 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.6689 loss: 1.6689 2022/09/08 14:21:33 - mmengine - INFO - Epoch(train) [18][1220/1253] lr: 4.0000e-02 eta: 6:32:53 time: 0.5644 data_time: 0.0393 memory: 23504 grad_norm: 2.8673 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5717 loss: 1.5717 2022/09/08 14:21:43 - mmengine - INFO - Epoch(train) [18][1240/1253] lr: 4.0000e-02 eta: 6:32:38 time: 0.5014 data_time: 0.0229 memory: 23504 grad_norm: 2.7807 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.5618 loss: 1.5618 2022/09/08 14:21:48 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 14:21:48 - mmengine - INFO - Epoch(train) [18][1253/1253] lr: 4.0000e-02 eta: 6:32:38 time: 0.4345 data_time: 0.0211 memory: 23504 grad_norm: 2.9611 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.6616 loss: 1.6616 2022/09/08 14:22:13 - mmengine - INFO - Epoch(train) [19][20/1253] lr: 4.0000e-02 eta: 6:32:28 time: 1.2201 data_time: 0.4669 memory: 23504 grad_norm: 2.7638 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.7094 loss: 1.7094 2022/09/08 14:22:24 - mmengine - INFO - Epoch(train) [19][40/1253] lr: 4.0000e-02 eta: 6:32:15 time: 0.5693 data_time: 0.0723 memory: 23504 grad_norm: 2.8623 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.5982 loss: 1.5982 2022/09/08 14:22:37 - mmengine - INFO - Epoch(train) [19][60/1253] lr: 4.0000e-02 eta: 6:32:05 time: 0.6336 data_time: 0.0363 memory: 23504 grad_norm: 2.7628 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 1.5801 loss: 1.5801 2022/09/08 14:22:48 - mmengine - INFO - Epoch(train) [19][80/1253] lr: 4.0000e-02 eta: 6:31:53 time: 0.5655 data_time: 0.0450 memory: 23504 grad_norm: 2.8799 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.6150 loss: 1.6150 2022/09/08 14:23:00 - mmengine - INFO - Epoch(train) [19][100/1253] lr: 4.0000e-02 eta: 6:31:40 time: 0.5657 data_time: 0.0400 memory: 23504 grad_norm: 2.8449 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.4581 loss: 1.4581 2022/09/08 14:23:11 - mmengine - INFO - Epoch(train) [19][120/1253] lr: 4.0000e-02 eta: 6:31:28 time: 0.5810 data_time: 0.0540 memory: 23504 grad_norm: 2.7975 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4510 loss: 1.4510 2022/09/08 14:23:23 - mmengine - INFO - Epoch(train) [19][140/1253] lr: 4.0000e-02 eta: 6:31:17 time: 0.6085 data_time: 0.0323 memory: 23504 grad_norm: 2.7887 top1_acc: 0.6250 top5_acc: 0.7083 loss_cls: 1.4868 loss: 1.4868 2022/09/08 14:23:35 - mmengine - INFO - Epoch(train) [19][160/1253] lr: 4.0000e-02 eta: 6:31:05 time: 0.5773 data_time: 0.0465 memory: 23504 grad_norm: 2.8574 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.6218 loss: 1.6218 2022/09/08 14:23:46 - mmengine - INFO - Epoch(train) [19][180/1253] lr: 4.0000e-02 eta: 6:30:53 time: 0.5689 data_time: 0.0329 memory: 23504 grad_norm: 2.8369 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5500 loss: 1.5500 2022/09/08 14:23:58 - mmengine - INFO - Epoch(train) [19][200/1253] lr: 4.0000e-02 eta: 6:30:40 time: 0.5752 data_time: 0.0552 memory: 23504 grad_norm: 2.8941 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.8164 loss: 1.8164 2022/09/08 14:24:10 - mmengine - INFO - Epoch(train) [19][220/1253] lr: 4.0000e-02 eta: 6:30:29 time: 0.5953 data_time: 0.0364 memory: 23504 grad_norm: 2.8223 top1_acc: 0.5417 top5_acc: 0.6667 loss_cls: 1.6689 loss: 1.6689 2022/09/08 14:24:22 - mmengine - INFO - Epoch(train) [19][240/1253] lr: 4.0000e-02 eta: 6:30:19 time: 0.6327 data_time: 0.0413 memory: 23504 grad_norm: 2.9050 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 1.5802 loss: 1.5802 2022/09/08 14:24:33 - mmengine - INFO - Epoch(train) [19][260/1253] lr: 4.0000e-02 eta: 6:30:06 time: 0.5539 data_time: 0.0352 memory: 23504 grad_norm: 2.8895 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.5350 loss: 1.5350 2022/09/08 14:24:44 - mmengine - INFO - Epoch(train) [19][280/1253] lr: 4.0000e-02 eta: 6:29:53 time: 0.5457 data_time: 0.0370 memory: 23504 grad_norm: 2.9098 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 1.5457 loss: 1.5457 2022/09/08 14:24:56 - mmengine - INFO - Epoch(train) [19][300/1253] lr: 4.0000e-02 eta: 6:29:40 time: 0.5711 data_time: 0.0514 memory: 23504 grad_norm: 2.7876 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.5387 loss: 1.5387 2022/09/08 14:25:10 - mmengine - INFO - Epoch(train) [19][320/1253] lr: 4.0000e-02 eta: 6:29:33 time: 0.7034 data_time: 0.0307 memory: 23504 grad_norm: 2.8788 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.5469 loss: 1.5469 2022/09/08 14:25:21 - mmengine - INFO - Epoch(train) [19][340/1253] lr: 4.0000e-02 eta: 6:29:20 time: 0.5530 data_time: 0.0444 memory: 23504 grad_norm: 2.8667 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6585 loss: 1.6585 2022/09/08 14:25:32 - mmengine - INFO - Epoch(train) [19][360/1253] lr: 4.0000e-02 eta: 6:29:07 time: 0.5512 data_time: 0.0459 memory: 23504 grad_norm: 2.7931 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 1.6047 loss: 1.6047 2022/09/08 14:25:44 - mmengine - INFO - Epoch(train) [19][380/1253] lr: 4.0000e-02 eta: 6:28:55 time: 0.5796 data_time: 0.0520 memory: 23504 grad_norm: 2.9079 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6586 loss: 1.6586 2022/09/08 14:25:55 - mmengine - INFO - Epoch(train) [19][400/1253] lr: 4.0000e-02 eta: 6:28:43 time: 0.5832 data_time: 0.0419 memory: 23504 grad_norm: 2.8059 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.6090 loss: 1.6090 2022/09/08 14:26:07 - mmengine - INFO - Epoch(train) [19][420/1253] lr: 4.0000e-02 eta: 6:28:31 time: 0.5848 data_time: 0.0370 memory: 23504 grad_norm: 2.9062 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5932 loss: 1.5932 2022/09/08 14:26:19 - mmengine - INFO - Epoch(train) [19][440/1253] lr: 4.0000e-02 eta: 6:28:19 time: 0.5914 data_time: 0.0446 memory: 23504 grad_norm: 2.8042 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.5733 loss: 1.5733 2022/09/08 14:26:22 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 14:26:31 - mmengine - INFO - Epoch(train) [19][460/1253] lr: 4.0000e-02 eta: 6:28:07 time: 0.5881 data_time: 0.0386 memory: 23504 grad_norm: 2.8714 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6327 loss: 1.6327 2022/09/08 14:26:43 - mmengine - INFO - Epoch(train) [19][480/1253] lr: 4.0000e-02 eta: 6:27:56 time: 0.6050 data_time: 0.0495 memory: 23504 grad_norm: 2.8708 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.4652 loss: 1.4652 2022/09/08 14:26:54 - mmengine - INFO - Epoch(train) [19][500/1253] lr: 4.0000e-02 eta: 6:27:45 time: 0.5893 data_time: 0.0387 memory: 23504 grad_norm: 2.8463 top1_acc: 0.5000 top5_acc: 0.5833 loss_cls: 1.6669 loss: 1.6669 2022/09/08 14:27:06 - mmengine - INFO - Epoch(train) [19][520/1253] lr: 4.0000e-02 eta: 6:27:32 time: 0.5755 data_time: 0.0640 memory: 23504 grad_norm: 2.8208 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.4209 loss: 1.4209 2022/09/08 14:27:17 - mmengine - INFO - Epoch(train) [19][540/1253] lr: 4.0000e-02 eta: 6:27:20 time: 0.5545 data_time: 0.0483 memory: 23504 grad_norm: 2.8338 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5740 loss: 1.5740 2022/09/08 14:27:29 - mmengine - INFO - Epoch(train) [19][560/1253] lr: 4.0000e-02 eta: 6:27:08 time: 0.5819 data_time: 0.0478 memory: 23504 grad_norm: 2.9281 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5505 loss: 1.5505 2022/09/08 14:27:40 - mmengine - INFO - Epoch(train) [19][580/1253] lr: 4.0000e-02 eta: 6:26:55 time: 0.5682 data_time: 0.0507 memory: 23504 grad_norm: 2.8876 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.7686 loss: 1.7686 2022/09/08 14:27:52 - mmengine - INFO - Epoch(train) [19][600/1253] lr: 4.0000e-02 eta: 6:26:43 time: 0.5847 data_time: 0.0354 memory: 23504 grad_norm: 2.9004 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.7241 loss: 1.7241 2022/09/08 14:28:03 - mmengine - INFO - Epoch(train) [19][620/1253] lr: 4.0000e-02 eta: 6:26:31 time: 0.5700 data_time: 0.0395 memory: 23504 grad_norm: 2.8914 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.7172 loss: 1.7172 2022/09/08 14:28:14 - mmengine - INFO - Epoch(train) [19][640/1253] lr: 4.0000e-02 eta: 6:26:18 time: 0.5604 data_time: 0.0421 memory: 23504 grad_norm: 2.8115 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5358 loss: 1.5358 2022/09/08 14:28:26 - mmengine - INFO - Epoch(train) [19][660/1253] lr: 4.0000e-02 eta: 6:26:06 time: 0.5628 data_time: 0.0403 memory: 23504 grad_norm: 2.8291 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.6556 loss: 1.6556 2022/09/08 14:28:36 - mmengine - INFO - Epoch(train) [19][680/1253] lr: 4.0000e-02 eta: 6:25:52 time: 0.5406 data_time: 0.0467 memory: 23504 grad_norm: 2.8700 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.4521 loss: 1.4521 2022/09/08 14:28:51 - mmengine - INFO - Epoch(train) [19][700/1253] lr: 4.0000e-02 eta: 6:25:44 time: 0.6841 data_time: 0.0461 memory: 23504 grad_norm: 2.8537 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.6100 loss: 1.6100 2022/09/08 14:29:02 - mmengine - INFO - Epoch(train) [19][720/1253] lr: 4.0000e-02 eta: 6:25:33 time: 0.5978 data_time: 0.0705 memory: 23504 grad_norm: 2.8172 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.6520 loss: 1.6520 2022/09/08 14:29:14 - mmengine - INFO - Epoch(train) [19][740/1253] lr: 4.0000e-02 eta: 6:25:20 time: 0.5734 data_time: 0.0306 memory: 23504 grad_norm: 2.7781 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.3893 loss: 1.3893 2022/09/08 14:29:25 - mmengine - INFO - Epoch(train) [19][760/1253] lr: 4.0000e-02 eta: 6:25:08 time: 0.5691 data_time: 0.0427 memory: 23504 grad_norm: 2.9016 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.6697 loss: 1.6697 2022/09/08 14:29:37 - mmengine - INFO - Epoch(train) [19][780/1253] lr: 4.0000e-02 eta: 6:24:57 time: 0.6164 data_time: 0.0404 memory: 23504 grad_norm: 2.8949 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.7495 loss: 1.7495 2022/09/08 14:29:49 - mmengine - INFO - Epoch(train) [19][800/1253] lr: 4.0000e-02 eta: 6:24:46 time: 0.5957 data_time: 0.0431 memory: 23504 grad_norm: 2.9229 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.8545 loss: 1.8545 2022/09/08 14:30:02 - mmengine - INFO - Epoch(train) [19][820/1253] lr: 4.0000e-02 eta: 6:24:35 time: 0.6234 data_time: 0.0431 memory: 23504 grad_norm: 2.8229 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.4436 loss: 1.4436 2022/09/08 14:30:12 - mmengine - INFO - Epoch(train) [19][840/1253] lr: 4.0000e-02 eta: 6:24:22 time: 0.5410 data_time: 0.0449 memory: 23504 grad_norm: 2.8043 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.7412 loss: 1.7412 2022/09/08 14:30:24 - mmengine - INFO - Epoch(train) [19][860/1253] lr: 4.0000e-02 eta: 6:24:09 time: 0.5646 data_time: 0.0389 memory: 23504 grad_norm: 2.7738 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6098 loss: 1.6098 2022/09/08 14:30:35 - mmengine - INFO - Epoch(train) [19][880/1253] lr: 4.0000e-02 eta: 6:23:57 time: 0.5795 data_time: 0.0470 memory: 23504 grad_norm: 2.8228 top1_acc: 0.2917 top5_acc: 0.8333 loss_cls: 1.7022 loss: 1.7022 2022/09/08 14:30:47 - mmengine - INFO - Epoch(train) [19][900/1253] lr: 4.0000e-02 eta: 6:23:45 time: 0.5776 data_time: 0.0464 memory: 23504 grad_norm: 2.8750 top1_acc: 0.4167 top5_acc: 0.8750 loss_cls: 1.6303 loss: 1.6303 2022/09/08 14:30:59 - mmengine - INFO - Epoch(train) [19][920/1253] lr: 4.0000e-02 eta: 6:23:33 time: 0.5797 data_time: 0.0522 memory: 23504 grad_norm: 2.8991 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.6226 loss: 1.6226 2022/09/08 14:31:12 - mmengine - INFO - Epoch(train) [19][940/1253] lr: 4.0000e-02 eta: 6:23:24 time: 0.6533 data_time: 0.0302 memory: 23504 grad_norm: 2.8502 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.7357 loss: 1.7357 2022/09/08 14:31:23 - mmengine - INFO - Epoch(train) [19][960/1253] lr: 4.0000e-02 eta: 6:23:11 time: 0.5742 data_time: 0.0428 memory: 23504 grad_norm: 2.8335 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.6573 loss: 1.6573 2022/09/08 14:31:35 - mmengine - INFO - Epoch(train) [19][980/1253] lr: 4.0000e-02 eta: 6:22:59 time: 0.5785 data_time: 0.0447 memory: 23504 grad_norm: 2.8294 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.6258 loss: 1.6258 2022/09/08 14:31:46 - mmengine - INFO - Epoch(train) [19][1000/1253] lr: 4.0000e-02 eta: 6:22:48 time: 0.5835 data_time: 0.0491 memory: 23504 grad_norm: 2.9142 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.6160 loss: 1.6160 2022/09/08 14:31:58 - mmengine - INFO - Epoch(train) [19][1020/1253] lr: 4.0000e-02 eta: 6:22:35 time: 0.5640 data_time: 0.0381 memory: 23504 grad_norm: 2.8764 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.6446 loss: 1.6446 2022/09/08 14:32:09 - mmengine - INFO - Epoch(train) [19][1040/1253] lr: 4.0000e-02 eta: 6:22:22 time: 0.5509 data_time: 0.0492 memory: 23504 grad_norm: 2.7944 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.7616 loss: 1.7616 2022/09/08 14:32:20 - mmengine - INFO - Epoch(train) [19][1060/1253] lr: 4.0000e-02 eta: 6:22:09 time: 0.5502 data_time: 0.0457 memory: 23504 grad_norm: 2.9070 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.7157 loss: 1.7157 2022/09/08 14:32:32 - mmengine - INFO - Epoch(train) [19][1080/1253] lr: 4.0000e-02 eta: 6:21:58 time: 0.5943 data_time: 0.0465 memory: 23504 grad_norm: 2.8107 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5681 loss: 1.5681 2022/09/08 14:32:44 - mmengine - INFO - Epoch(train) [19][1100/1253] lr: 4.0000e-02 eta: 6:21:48 time: 0.6393 data_time: 0.0518 memory: 23504 grad_norm: 2.8391 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5635 loss: 1.5635 2022/09/08 14:32:57 - mmengine - INFO - Epoch(train) [19][1120/1253] lr: 4.0000e-02 eta: 6:21:37 time: 0.6131 data_time: 0.0365 memory: 23504 grad_norm: 2.9567 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.6474 loss: 1.6474 2022/09/08 14:33:08 - mmengine - INFO - Epoch(train) [19][1140/1253] lr: 4.0000e-02 eta: 6:21:25 time: 0.5924 data_time: 0.0387 memory: 23504 grad_norm: 2.7689 top1_acc: 0.5833 top5_acc: 0.9583 loss_cls: 1.4646 loss: 1.4646 2022/09/08 14:33:21 - mmengine - INFO - Epoch(train) [19][1160/1253] lr: 4.0000e-02 eta: 6:21:14 time: 0.6245 data_time: 0.0448 memory: 23504 grad_norm: 2.8495 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.6642 loss: 1.6642 2022/09/08 14:33:34 - mmengine - INFO - Epoch(train) [19][1180/1253] lr: 4.0000e-02 eta: 6:21:04 time: 0.6327 data_time: 0.0405 memory: 23504 grad_norm: 2.9019 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.6313 loss: 1.6313 2022/09/08 14:33:45 - mmengine - INFO - Epoch(train) [19][1200/1253] lr: 4.0000e-02 eta: 6:20:52 time: 0.5651 data_time: 0.0486 memory: 23504 grad_norm: 2.8507 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.7783 loss: 1.7783 2022/09/08 14:33:56 - mmengine - INFO - Epoch(train) [19][1220/1253] lr: 4.0000e-02 eta: 6:20:39 time: 0.5494 data_time: 0.0421 memory: 23504 grad_norm: 2.8553 top1_acc: 0.3750 top5_acc: 0.8333 loss_cls: 1.5774 loss: 1.5774 2022/09/08 14:34:06 - mmengine - INFO - Epoch(train) [19][1240/1253] lr: 4.0000e-02 eta: 6:20:24 time: 0.4880 data_time: 0.0330 memory: 23504 grad_norm: 2.8591 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.8285 loss: 1.8285 2022/09/08 14:34:11 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 14:34:11 - mmengine - INFO - Epoch(train) [19][1253/1253] lr: 4.0000e-02 eta: 6:20:24 time: 0.4356 data_time: 0.0188 memory: 23504 grad_norm: 3.0703 top1_acc: 0.2857 top5_acc: 0.4286 loss_cls: 1.6481 loss: 1.6481 2022/09/08 14:34:35 - mmengine - INFO - Epoch(train) [20][20/1253] lr: 4.0000e-02 eta: 6:20:11 time: 1.1825 data_time: 0.4439 memory: 23504 grad_norm: 2.8397 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.5598 loss: 1.5598 2022/09/08 14:34:47 - mmengine - INFO - Epoch(train) [20][40/1253] lr: 4.0000e-02 eta: 6:19:59 time: 0.5819 data_time: 0.0375 memory: 23504 grad_norm: 2.8537 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.4443 loss: 1.4443 2022/09/08 14:34:58 - mmengine - INFO - Epoch(train) [20][60/1253] lr: 4.0000e-02 eta: 6:19:47 time: 0.5549 data_time: 0.0343 memory: 23504 grad_norm: 2.8359 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 1.5002 loss: 1.5002 2022/09/08 14:35:10 - mmengine - INFO - Epoch(train) [20][80/1253] lr: 4.0000e-02 eta: 6:19:35 time: 0.6061 data_time: 0.0898 memory: 23504 grad_norm: 2.8489 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4752 loss: 1.4752 2022/09/08 14:35:22 - mmengine - INFO - Epoch(train) [20][100/1253] lr: 4.0000e-02 eta: 6:19:24 time: 0.5944 data_time: 0.0513 memory: 23504 grad_norm: 2.8806 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.6710 loss: 1.6710 2022/09/08 14:35:34 - mmengine - INFO - Epoch(train) [20][120/1253] lr: 4.0000e-02 eta: 6:19:12 time: 0.5962 data_time: 0.0438 memory: 23504 grad_norm: 2.8248 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.6171 loss: 1.6171 2022/09/08 14:35:45 - mmengine - INFO - Epoch(train) [20][140/1253] lr: 4.0000e-02 eta: 6:19:00 time: 0.5776 data_time: 0.0407 memory: 23504 grad_norm: 2.8746 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 1.5053 loss: 1.5053 2022/09/08 14:35:57 - mmengine - INFO - Epoch(train) [20][160/1253] lr: 4.0000e-02 eta: 6:18:48 time: 0.5839 data_time: 0.0484 memory: 23504 grad_norm: 2.9042 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.5524 loss: 1.5524 2022/09/08 14:36:09 - mmengine - INFO - Epoch(train) [20][180/1253] lr: 4.0000e-02 eta: 6:18:37 time: 0.5869 data_time: 0.0420 memory: 23504 grad_norm: 2.8811 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 1.5406 loss: 1.5406 2022/09/08 14:36:16 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 14:36:20 - mmengine - INFO - Epoch(train) [20][200/1253] lr: 4.0000e-02 eta: 6:18:24 time: 0.5700 data_time: 0.0559 memory: 23504 grad_norm: 2.8487 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5687 loss: 1.5687 2022/09/08 14:36:32 - mmengine - INFO - Epoch(train) [20][220/1253] lr: 4.0000e-02 eta: 6:18:12 time: 0.5714 data_time: 0.0356 memory: 23504 grad_norm: 2.7937 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.5687 loss: 1.5687 2022/09/08 14:36:43 - mmengine - INFO - Epoch(train) [20][240/1253] lr: 4.0000e-02 eta: 6:18:00 time: 0.5923 data_time: 0.0462 memory: 23504 grad_norm: 2.8371 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5329 loss: 1.5329 2022/09/08 14:36:56 - mmengine - INFO - Epoch(train) [20][260/1253] lr: 4.0000e-02 eta: 6:17:51 time: 0.6445 data_time: 0.1025 memory: 23504 grad_norm: 2.8108 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.5497 loss: 1.5497 2022/09/08 14:37:07 - mmengine - INFO - Epoch(train) [20][280/1253] lr: 4.0000e-02 eta: 6:17:38 time: 0.5492 data_time: 0.0262 memory: 23504 grad_norm: 2.8162 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.5836 loss: 1.5836 2022/09/08 14:37:19 - mmengine - INFO - Epoch(train) [20][300/1253] lr: 4.0000e-02 eta: 6:17:25 time: 0.5737 data_time: 0.0340 memory: 23504 grad_norm: 2.8502 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.3459 loss: 1.3459 2022/09/08 14:37:32 - mmengine - INFO - Epoch(train) [20][320/1253] lr: 4.0000e-02 eta: 6:17:17 time: 0.6805 data_time: 0.0424 memory: 23504 grad_norm: 2.8649 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.6082 loss: 1.6082 2022/09/08 14:37:43 - mmengine - INFO - Epoch(train) [20][340/1253] lr: 4.0000e-02 eta: 6:17:04 time: 0.5566 data_time: 0.0383 memory: 23504 grad_norm: 2.9430 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.7134 loss: 1.7134 2022/09/08 14:37:55 - mmengine - INFO - Epoch(train) [20][360/1253] lr: 4.0000e-02 eta: 6:16:51 time: 0.5565 data_time: 0.0315 memory: 23504 grad_norm: 2.8524 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.5494 loss: 1.5494 2022/09/08 14:38:07 - mmengine - INFO - Epoch(train) [20][380/1253] lr: 4.0000e-02 eta: 6:16:40 time: 0.6171 data_time: 0.0406 memory: 23504 grad_norm: 2.9193 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.6234 loss: 1.6234 2022/09/08 14:38:18 - mmengine - INFO - Epoch(train) [20][400/1253] lr: 4.0000e-02 eta: 6:16:28 time: 0.5647 data_time: 0.0329 memory: 23504 grad_norm: 2.9258 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4395 loss: 1.4395 2022/09/08 14:38:30 - mmengine - INFO - Epoch(train) [20][420/1253] lr: 4.0000e-02 eta: 6:16:16 time: 0.5786 data_time: 0.0492 memory: 23504 grad_norm: 2.9575 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.6439 loss: 1.6439 2022/09/08 14:38:42 - mmengine - INFO - Epoch(train) [20][440/1253] lr: 4.0000e-02 eta: 6:16:05 time: 0.6177 data_time: 0.0335 memory: 23504 grad_norm: 2.8716 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5492 loss: 1.5492 2022/09/08 14:38:55 - mmengine - INFO - Epoch(train) [20][460/1253] lr: 4.0000e-02 eta: 6:15:54 time: 0.6268 data_time: 0.0393 memory: 23504 grad_norm: 2.8895 top1_acc: 0.4167 top5_acc: 0.8750 loss_cls: 1.4213 loss: 1.4213 2022/09/08 14:39:06 - mmengine - INFO - Epoch(train) [20][480/1253] lr: 4.0000e-02 eta: 6:15:42 time: 0.5605 data_time: 0.0644 memory: 23504 grad_norm: 2.8455 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5166 loss: 1.5166 2022/09/08 14:39:17 - mmengine - INFO - Epoch(train) [20][500/1253] lr: 4.0000e-02 eta: 6:15:29 time: 0.5537 data_time: 0.0561 memory: 23504 grad_norm: 2.8733 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.4786 loss: 1.4786 2022/09/08 14:39:28 - mmengine - INFO - Epoch(train) [20][520/1253] lr: 4.0000e-02 eta: 6:15:17 time: 0.5705 data_time: 0.0351 memory: 23504 grad_norm: 2.9529 top1_acc: 0.5417 top5_acc: 0.9583 loss_cls: 1.5918 loss: 1.5918 2022/09/08 14:39:40 - mmengine - INFO - Epoch(train) [20][540/1253] lr: 4.0000e-02 eta: 6:15:05 time: 0.5867 data_time: 0.0541 memory: 23504 grad_norm: 2.9118 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.6788 loss: 1.6788 2022/09/08 14:39:52 - mmengine - INFO - Epoch(train) [20][560/1253] lr: 4.0000e-02 eta: 6:14:53 time: 0.5754 data_time: 0.0541 memory: 23504 grad_norm: 2.8913 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.5985 loss: 1.5985 2022/09/08 14:40:04 - mmengine - INFO - Epoch(train) [20][580/1253] lr: 4.0000e-02 eta: 6:14:41 time: 0.5978 data_time: 0.0952 memory: 23504 grad_norm: 2.7998 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.5549 loss: 1.5549 2022/09/08 14:40:15 - mmengine - INFO - Epoch(train) [20][600/1253] lr: 4.0000e-02 eta: 6:14:29 time: 0.5504 data_time: 0.0374 memory: 23504 grad_norm: 2.8772 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6399 loss: 1.6399 2022/09/08 14:40:27 - mmengine - INFO - Epoch(train) [20][620/1253] lr: 4.0000e-02 eta: 6:14:17 time: 0.6017 data_time: 0.0395 memory: 23504 grad_norm: 2.8565 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6279 loss: 1.6279 2022/09/08 14:40:38 - mmengine - INFO - Epoch(train) [20][640/1253] lr: 4.0000e-02 eta: 6:14:05 time: 0.5793 data_time: 0.0540 memory: 23504 grad_norm: 2.7462 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 1.4622 loss: 1.4622 2022/09/08 14:40:51 - mmengine - INFO - Epoch(train) [20][660/1253] lr: 4.0000e-02 eta: 6:13:55 time: 0.6334 data_time: 0.0383 memory: 23504 grad_norm: 2.8426 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 1.6140 loss: 1.6140 2022/09/08 14:41:05 - mmengine - INFO - Epoch(train) [20][680/1253] lr: 4.0000e-02 eta: 6:13:46 time: 0.6811 data_time: 0.0330 memory: 23504 grad_norm: 2.8613 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 1.6446 loss: 1.6446 2022/09/08 14:41:16 - mmengine - INFO - Epoch(train) [20][700/1253] lr: 4.0000e-02 eta: 6:13:34 time: 0.5702 data_time: 0.0440 memory: 23504 grad_norm: 2.7488 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.6004 loss: 1.6004 2022/09/08 14:41:27 - mmengine - INFO - Epoch(train) [20][720/1253] lr: 4.0000e-02 eta: 6:13:21 time: 0.5682 data_time: 0.0434 memory: 23504 grad_norm: 2.9379 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.7028 loss: 1.7028 2022/09/08 14:41:39 - mmengine - INFO - Epoch(train) [20][740/1253] lr: 4.0000e-02 eta: 6:13:09 time: 0.5639 data_time: 0.0394 memory: 23504 grad_norm: 2.8828 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5280 loss: 1.5280 2022/09/08 14:41:50 - mmengine - INFO - Epoch(train) [20][760/1253] lr: 4.0000e-02 eta: 6:12:57 time: 0.5681 data_time: 0.0368 memory: 23504 grad_norm: 2.8212 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 1.6219 loss: 1.6219 2022/09/08 14:42:02 - mmengine - INFO - Epoch(train) [20][780/1253] lr: 4.0000e-02 eta: 6:12:44 time: 0.5781 data_time: 0.0534 memory: 23504 grad_norm: 2.9179 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.6166 loss: 1.6166 2022/09/08 14:42:13 - mmengine - INFO - Epoch(train) [20][800/1253] lr: 4.0000e-02 eta: 6:12:33 time: 0.5798 data_time: 0.0619 memory: 23504 grad_norm: 2.8179 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7660 loss: 1.7660 2022/09/08 14:42:27 - mmengine - INFO - Epoch(train) [20][820/1253] lr: 4.0000e-02 eta: 6:12:24 time: 0.6918 data_time: 0.0313 memory: 23504 grad_norm: 2.8181 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.5948 loss: 1.5948 2022/09/08 14:42:38 - mmengine - INFO - Epoch(train) [20][840/1253] lr: 4.0000e-02 eta: 6:12:11 time: 0.5529 data_time: 0.0370 memory: 23504 grad_norm: 2.8197 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6371 loss: 1.6371 2022/09/08 14:42:49 - mmengine - INFO - Epoch(train) [20][860/1253] lr: 4.0000e-02 eta: 6:11:58 time: 0.5497 data_time: 0.0346 memory: 23504 grad_norm: 2.7757 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 1.6206 loss: 1.6206 2022/09/08 14:43:01 - mmengine - INFO - Epoch(train) [20][880/1253] lr: 4.0000e-02 eta: 6:11:47 time: 0.5993 data_time: 0.0453 memory: 23504 grad_norm: 2.7976 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5135 loss: 1.5135 2022/09/08 14:43:12 - mmengine - INFO - Epoch(train) [20][900/1253] lr: 4.0000e-02 eta: 6:11:34 time: 0.5646 data_time: 0.0549 memory: 23504 grad_norm: 2.8431 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.3628 loss: 1.3628 2022/09/08 14:43:24 - mmengine - INFO - Epoch(train) [20][920/1253] lr: 4.0000e-02 eta: 6:11:22 time: 0.5706 data_time: 0.0339 memory: 23504 grad_norm: 2.9158 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6072 loss: 1.6072 2022/09/08 14:43:37 - mmengine - INFO - Epoch(train) [20][940/1253] lr: 4.0000e-02 eta: 6:11:12 time: 0.6502 data_time: 0.0403 memory: 23504 grad_norm: 2.8398 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.5904 loss: 1.5904 2022/09/08 14:43:48 - mmengine - INFO - Epoch(train) [20][960/1253] lr: 4.0000e-02 eta: 6:11:00 time: 0.5695 data_time: 0.0418 memory: 23504 grad_norm: 2.8751 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.5290 loss: 1.5290 2022/09/08 14:43:59 - mmengine - INFO - Epoch(train) [20][980/1253] lr: 4.0000e-02 eta: 6:10:47 time: 0.5619 data_time: 0.0424 memory: 23504 grad_norm: 2.8315 top1_acc: 0.5833 top5_acc: 0.6250 loss_cls: 1.4690 loss: 1.4690 2022/09/08 14:44:10 - mmengine - INFO - Epoch(train) [20][1000/1253] lr: 4.0000e-02 eta: 6:10:35 time: 0.5554 data_time: 0.0435 memory: 23504 grad_norm: 2.8178 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.5805 loss: 1.5805 2022/09/08 14:44:23 - mmengine - INFO - Epoch(train) [20][1020/1253] lr: 4.0000e-02 eta: 6:10:23 time: 0.5856 data_time: 0.0443 memory: 23504 grad_norm: 2.7402 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.4516 loss: 1.4516 2022/09/08 14:44:34 - mmengine - INFO - Epoch(train) [20][1040/1253] lr: 4.0000e-02 eta: 6:10:11 time: 0.5670 data_time: 0.0588 memory: 23504 grad_norm: 2.9033 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 1.6282 loss: 1.6282 2022/09/08 14:44:45 - mmengine - INFO - Epoch(train) [20][1060/1253] lr: 4.0000e-02 eta: 6:09:59 time: 0.5902 data_time: 0.0784 memory: 23504 grad_norm: 2.8638 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.5455 loss: 1.5455 2022/09/08 14:44:57 - mmengine - INFO - Epoch(train) [20][1080/1253] lr: 4.0000e-02 eta: 6:09:47 time: 0.5801 data_time: 0.0313 memory: 23504 grad_norm: 2.9176 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.4458 loss: 1.4458 2022/09/08 14:45:08 - mmengine - INFO - Epoch(train) [20][1100/1253] lr: 4.0000e-02 eta: 6:09:34 time: 0.5550 data_time: 0.0480 memory: 23504 grad_norm: 2.8643 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.6645 loss: 1.6645 2022/09/08 14:45:20 - mmengine - INFO - Epoch(train) [20][1120/1253] lr: 4.0000e-02 eta: 6:09:22 time: 0.5796 data_time: 0.0442 memory: 23504 grad_norm: 2.8128 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.5617 loss: 1.5617 2022/09/08 14:45:32 - mmengine - INFO - Epoch(train) [20][1140/1253] lr: 4.0000e-02 eta: 6:09:12 time: 0.6383 data_time: 0.0351 memory: 23504 grad_norm: 2.8448 top1_acc: 0.5000 top5_acc: 0.9583 loss_cls: 1.5817 loss: 1.5817 2022/09/08 14:45:46 - mmengine - INFO - Epoch(train) [20][1160/1253] lr: 4.0000e-02 eta: 6:09:03 time: 0.6824 data_time: 0.1685 memory: 23504 grad_norm: 2.8374 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.6732 loss: 1.6732 2022/09/08 14:45:57 - mmengine - INFO - Epoch(train) [20][1180/1253] lr: 4.0000e-02 eta: 6:08:50 time: 0.5370 data_time: 0.0234 memory: 23504 grad_norm: 2.7487 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.6281 loss: 1.6281 2022/09/08 14:46:05 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 14:46:08 - mmengine - INFO - Epoch(train) [20][1200/1253] lr: 4.0000e-02 eta: 6:08:37 time: 0.5699 data_time: 0.0464 memory: 23504 grad_norm: 2.8329 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.5403 loss: 1.5403 2022/09/08 14:46:20 - mmengine - INFO - Epoch(train) [20][1220/1253] lr: 4.0000e-02 eta: 6:08:25 time: 0.5729 data_time: 0.0517 memory: 23504 grad_norm: 2.8858 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.7619 loss: 1.7619 2022/09/08 14:46:30 - mmengine - INFO - Epoch(train) [20][1240/1253] lr: 4.0000e-02 eta: 6:08:11 time: 0.5160 data_time: 0.0221 memory: 23504 grad_norm: 2.8663 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.5466 loss: 1.5466 2022/09/08 14:46:36 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 14:46:36 - mmengine - INFO - Epoch(train) [20][1253/1253] lr: 4.0000e-02 eta: 6:08:11 time: 0.4355 data_time: 0.0194 memory: 23504 grad_norm: 2.9795 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.6280 loss: 1.6280 2022/09/08 14:46:58 - mmengine - INFO - Epoch(val) [20][20/104] eta: 0:01:34 time: 1.1299 data_time: 0.9846 memory: 2699 2022/09/08 14:47:10 - mmengine - INFO - Epoch(val) [20][40/104] eta: 0:00:36 time: 0.5733 data_time: 0.4340 memory: 2699 2022/09/08 14:47:19 - mmengine - INFO - Epoch(val) [20][60/104] eta: 0:00:20 time: 0.4575 data_time: 0.3165 memory: 2699 2022/09/08 14:47:27 - mmengine - INFO - Epoch(val) [20][80/104] eta: 0:00:10 time: 0.4303 data_time: 0.2893 memory: 2699 2022/09/08 14:47:35 - mmengine - INFO - Epoch(val) [20][100/104] eta: 0:00:01 time: 0.3837 data_time: 0.2571 memory: 2699 2022/09/08 14:47:44 - mmengine - INFO - Epoch(val) [20][104/104] acc/top1: 0.6142 acc/top5: 0.8369 acc/mean1: 0.6140 2022/09/08 14:47:44 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb/best_acc/top1_epoch_15.pth is removed 2022/09/08 14:47:46 - mmengine - INFO - The best checkpoint with 0.6142 acc/top1 at 20 epoch is saved to best_acc/top1_epoch_20.pth. 2022/09/08 14:48:06 - mmengine - INFO - Epoch(train) [21][20/1253] lr: 4.0000e-03 eta: 6:07:54 time: 1.0336 data_time: 0.5001 memory: 23504 grad_norm: 2.7584 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5874 loss: 1.5874 2022/09/08 14:48:20 - mmengine - INFO - Epoch(train) [21][40/1253] lr: 4.0000e-03 eta: 6:07:44 time: 0.6652 data_time: 0.0419 memory: 23504 grad_norm: 2.6004 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.4551 loss: 1.4551 2022/09/08 14:48:30 - mmengine - INFO - Epoch(train) [21][60/1253] lr: 4.0000e-03 eta: 6:07:31 time: 0.5210 data_time: 0.0354 memory: 23504 grad_norm: 2.6450 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 1.3211 loss: 1.3211 2022/09/08 14:48:43 - mmengine - INFO - Epoch(train) [21][80/1253] lr: 4.0000e-03 eta: 6:07:21 time: 0.6602 data_time: 0.0395 memory: 23504 grad_norm: 2.5978 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5059 loss: 1.5059 2022/09/08 14:48:56 - mmengine - INFO - Epoch(train) [21][100/1253] lr: 4.0000e-03 eta: 6:07:10 time: 0.6215 data_time: 0.0863 memory: 23504 grad_norm: 2.6565 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.5138 loss: 1.5138 2022/09/08 14:49:07 - mmengine - INFO - Epoch(train) [21][120/1253] lr: 4.0000e-03 eta: 6:06:58 time: 0.5804 data_time: 0.0455 memory: 23504 grad_norm: 2.6421 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.4613 loss: 1.4613 2022/09/08 14:49:19 - mmengine - INFO - Epoch(train) [21][140/1253] lr: 4.0000e-03 eta: 6:06:47 time: 0.5883 data_time: 0.0428 memory: 23504 grad_norm: 2.6699 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.3251 loss: 1.3251 2022/09/08 14:49:31 - mmengine - INFO - Epoch(train) [21][160/1253] lr: 4.0000e-03 eta: 6:06:36 time: 0.6143 data_time: 0.0616 memory: 23504 grad_norm: 2.5909 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.2778 loss: 1.2778 2022/09/08 14:49:43 - mmengine - INFO - Epoch(train) [21][180/1253] lr: 4.0000e-03 eta: 6:06:24 time: 0.5804 data_time: 0.0273 memory: 23504 grad_norm: 2.5477 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3694 loss: 1.3694 2022/09/08 14:49:54 - mmengine - INFO - Epoch(train) [21][200/1253] lr: 4.0000e-03 eta: 6:06:11 time: 0.5658 data_time: 0.0507 memory: 23504 grad_norm: 2.6518 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.2030 loss: 1.2030 2022/09/08 14:50:08 - mmengine - INFO - Epoch(train) [21][220/1253] lr: 4.0000e-03 eta: 6:06:02 time: 0.6810 data_time: 0.0317 memory: 23504 grad_norm: 2.6205 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 1.2621 loss: 1.2621 2022/09/08 14:50:19 - mmengine - INFO - Epoch(train) [21][240/1253] lr: 4.0000e-03 eta: 6:05:50 time: 0.5585 data_time: 0.0243 memory: 23504 grad_norm: 2.6721 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.2850 loss: 1.2850 2022/09/08 14:50:30 - mmengine - INFO - Epoch(train) [21][260/1253] lr: 4.0000e-03 eta: 6:05:37 time: 0.5619 data_time: 0.0412 memory: 23504 grad_norm: 2.7054 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3875 loss: 1.3875 2022/09/08 14:50:42 - mmengine - INFO - Epoch(train) [21][280/1253] lr: 4.0000e-03 eta: 6:05:25 time: 0.5666 data_time: 0.0444 memory: 23504 grad_norm: 2.6649 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.3829 loss: 1.3829 2022/09/08 14:50:53 - mmengine - INFO - Epoch(train) [21][300/1253] lr: 4.0000e-03 eta: 6:05:13 time: 0.5806 data_time: 0.0472 memory: 23504 grad_norm: 2.6223 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.1427 loss: 1.1427 2022/09/08 14:51:05 - mmengine - INFO - Epoch(train) [21][320/1253] lr: 4.0000e-03 eta: 6:05:01 time: 0.5854 data_time: 0.0504 memory: 23504 grad_norm: 2.6543 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.2655 loss: 1.2655 2022/09/08 14:51:16 - mmengine - INFO - Epoch(train) [21][340/1253] lr: 4.0000e-03 eta: 6:04:48 time: 0.5551 data_time: 0.0395 memory: 23504 grad_norm: 2.7321 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.3075 loss: 1.3075 2022/09/08 14:51:28 - mmengine - INFO - Epoch(train) [21][360/1253] lr: 4.0000e-03 eta: 6:04:37 time: 0.5853 data_time: 0.0448 memory: 23504 grad_norm: 2.6834 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.2478 loss: 1.2478 2022/09/08 14:51:41 - mmengine - INFO - Epoch(train) [21][380/1253] lr: 4.0000e-03 eta: 6:04:27 time: 0.6647 data_time: 0.0354 memory: 23504 grad_norm: 2.6132 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.3345 loss: 1.3345 2022/09/08 14:51:52 - mmengine - INFO - Epoch(train) [21][400/1253] lr: 4.0000e-03 eta: 6:04:14 time: 0.5516 data_time: 0.0444 memory: 23504 grad_norm: 2.6452 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.3443 loss: 1.3443 2022/09/08 14:52:03 - mmengine - INFO - Epoch(train) [21][420/1253] lr: 4.0000e-03 eta: 6:04:01 time: 0.5346 data_time: 0.0467 memory: 23504 grad_norm: 2.6438 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.2400 loss: 1.2400 2022/09/08 14:52:14 - mmengine - INFO - Epoch(train) [21][440/1253] lr: 4.0000e-03 eta: 6:03:48 time: 0.5539 data_time: 0.0438 memory: 23504 grad_norm: 2.6862 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0863 loss: 1.0863 2022/09/08 14:52:25 - mmengine - INFO - Epoch(train) [21][460/1253] lr: 4.0000e-03 eta: 6:03:36 time: 0.5612 data_time: 0.0344 memory: 23504 grad_norm: 2.7444 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.2832 loss: 1.2832 2022/09/08 14:52:37 - mmengine - INFO - Epoch(train) [21][480/1253] lr: 4.0000e-03 eta: 6:03:24 time: 0.5838 data_time: 0.0466 memory: 23504 grad_norm: 2.6664 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.2508 loss: 1.2508 2022/09/08 14:52:52 - mmengine - INFO - Epoch(train) [21][500/1253] lr: 4.0000e-03 eta: 6:03:17 time: 0.7438 data_time: 0.2482 memory: 23504 grad_norm: 2.6624 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.0677 loss: 1.0677 2022/09/08 14:53:03 - mmengine - INFO - Epoch(train) [21][520/1253] lr: 4.0000e-03 eta: 6:03:04 time: 0.5538 data_time: 0.0265 memory: 23504 grad_norm: 2.6875 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 1.2477 loss: 1.2477 2022/09/08 14:53:14 - mmengine - INFO - Epoch(train) [21][540/1253] lr: 4.0000e-03 eta: 6:02:51 time: 0.5605 data_time: 0.0540 memory: 23504 grad_norm: 2.6742 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.1879 loss: 1.1879 2022/09/08 14:53:27 - mmengine - INFO - Epoch(train) [21][560/1253] lr: 4.0000e-03 eta: 6:02:42 time: 0.6732 data_time: 0.0783 memory: 23504 grad_norm: 2.7504 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.0882 loss: 1.0882 2022/09/08 14:53:39 - mmengine - INFO - Epoch(train) [21][580/1253] lr: 4.0000e-03 eta: 6:02:30 time: 0.5772 data_time: 0.0446 memory: 23504 grad_norm: 2.7320 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.2107 loss: 1.2107 2022/09/08 14:53:51 - mmengine - INFO - Epoch(train) [21][600/1253] lr: 4.0000e-03 eta: 6:02:18 time: 0.5907 data_time: 0.0249 memory: 23504 grad_norm: 2.6772 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 1.2328 loss: 1.2328 2022/09/08 14:54:02 - mmengine - INFO - Epoch(train) [21][620/1253] lr: 4.0000e-03 eta: 6:02:06 time: 0.5569 data_time: 0.0423 memory: 23504 grad_norm: 2.7665 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.2334 loss: 1.2334 2022/09/08 14:54:13 - mmengine - INFO - Epoch(train) [21][640/1253] lr: 4.0000e-03 eta: 6:01:53 time: 0.5665 data_time: 0.0361 memory: 23504 grad_norm: 2.7838 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 1.1401 loss: 1.1401 2022/09/08 14:54:27 - mmengine - INFO - Epoch(train) [21][660/1253] lr: 4.0000e-03 eta: 6:01:45 time: 0.7105 data_time: 0.1969 memory: 23504 grad_norm: 2.7441 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.1155 loss: 1.1155 2022/09/08 14:54:39 - mmengine - INFO - Epoch(train) [21][680/1253] lr: 4.0000e-03 eta: 6:01:32 time: 0.5541 data_time: 0.0427 memory: 23504 grad_norm: 2.7038 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.1701 loss: 1.1701 2022/09/08 14:54:50 - mmengine - INFO - Epoch(train) [21][700/1253] lr: 4.0000e-03 eta: 6:01:20 time: 0.5535 data_time: 0.0324 memory: 23504 grad_norm: 2.7201 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.3059 loss: 1.3059 2022/09/08 14:55:01 - mmengine - INFO - Epoch(train) [21][720/1253] lr: 4.0000e-03 eta: 6:01:07 time: 0.5577 data_time: 0.0375 memory: 23504 grad_norm: 2.7292 top1_acc: 0.4583 top5_acc: 0.5833 loss_cls: 1.2474 loss: 1.2474 2022/09/08 14:55:12 - mmengine - INFO - Epoch(train) [21][740/1253] lr: 4.0000e-03 eta: 6:00:55 time: 0.5805 data_time: 0.0428 memory: 23504 grad_norm: 2.6445 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.2468 loss: 1.2468 2022/09/08 14:55:25 - mmengine - INFO - Epoch(train) [21][760/1253] lr: 4.0000e-03 eta: 6:00:44 time: 0.6140 data_time: 0.0899 memory: 23504 grad_norm: 2.7054 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.2101 loss: 1.2101 2022/09/08 14:55:36 - mmengine - INFO - Epoch(train) [21][780/1253] lr: 4.0000e-03 eta: 6:00:32 time: 0.5729 data_time: 0.0317 memory: 23504 grad_norm: 2.6449 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 1.1627 loss: 1.1627 2022/09/08 14:55:48 - mmengine - INFO - Epoch(train) [21][800/1253] lr: 4.0000e-03 eta: 6:00:20 time: 0.5854 data_time: 0.0519 memory: 23504 grad_norm: 2.7353 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.2119 loss: 1.2119 2022/09/08 14:55:59 - mmengine - INFO - Epoch(train) [21][820/1253] lr: 4.0000e-03 eta: 6:00:08 time: 0.5834 data_time: 0.0679 memory: 23504 grad_norm: 2.7303 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.2240 loss: 1.2240 2022/09/08 14:56:11 - mmengine - INFO - Epoch(train) [21][840/1253] lr: 4.0000e-03 eta: 5:59:56 time: 0.5620 data_time: 0.0451 memory: 23504 grad_norm: 2.6999 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1124 loss: 1.1124 2022/09/08 14:56:22 - mmengine - INFO - Epoch(train) [21][860/1253] lr: 4.0000e-03 eta: 5:59:43 time: 0.5662 data_time: 0.0345 memory: 23504 grad_norm: 2.7229 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.2572 loss: 1.2572 2022/09/08 14:56:35 - mmengine - INFO - Epoch(train) [21][880/1253] lr: 4.0000e-03 eta: 5:59:34 time: 0.6640 data_time: 0.0772 memory: 23504 grad_norm: 2.6494 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1852 loss: 1.1852 2022/09/08 14:56:47 - mmengine - INFO - Epoch(train) [21][900/1253] lr: 4.0000e-03 eta: 5:59:22 time: 0.5983 data_time: 0.0798 memory: 23504 grad_norm: 2.6932 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.1473 loss: 1.1473 2022/09/08 14:57:00 - mmengine - INFO - Epoch(train) [21][920/1253] lr: 4.0000e-03 eta: 5:59:12 time: 0.6504 data_time: 0.1338 memory: 23504 grad_norm: 2.7501 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 1.1127 loss: 1.1127 2022/09/08 14:57:11 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 14:57:11 - mmengine - INFO - Epoch(train) [21][940/1253] lr: 4.0000e-03 eta: 5:59:00 time: 0.5497 data_time: 0.0278 memory: 23504 grad_norm: 2.7395 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.1686 loss: 1.1686 2022/09/08 14:57:23 - mmengine - INFO - Epoch(train) [21][960/1253] lr: 4.0000e-03 eta: 5:58:48 time: 0.5822 data_time: 0.0509 memory: 23504 grad_norm: 2.7325 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3612 loss: 1.3612 2022/09/08 14:57:34 - mmengine - INFO - Epoch(train) [21][980/1253] lr: 4.0000e-03 eta: 5:58:35 time: 0.5671 data_time: 0.0362 memory: 23504 grad_norm: 2.7120 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.2758 loss: 1.2758 2022/09/08 14:57:47 - mmengine - INFO - Epoch(train) [21][1000/1253] lr: 4.0000e-03 eta: 5:58:24 time: 0.6147 data_time: 0.0833 memory: 23504 grad_norm: 2.8251 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4238 loss: 1.4238 2022/09/08 14:57:58 - mmengine - INFO - Epoch(train) [21][1020/1253] lr: 4.0000e-03 eta: 5:58:12 time: 0.5792 data_time: 0.0341 memory: 23504 grad_norm: 2.7184 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2220 loss: 1.2220 2022/09/08 14:58:10 - mmengine - INFO - Epoch(train) [21][1040/1253] lr: 4.0000e-03 eta: 5:58:00 time: 0.5760 data_time: 0.0462 memory: 23504 grad_norm: 2.7414 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.1708 loss: 1.1708 2022/09/08 14:58:22 - mmengine - INFO - Epoch(train) [21][1060/1253] lr: 4.0000e-03 eta: 5:57:49 time: 0.5926 data_time: 0.0383 memory: 23504 grad_norm: 2.6459 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.1246 loss: 1.1246 2022/09/08 14:58:33 - mmengine - INFO - Epoch(train) [21][1080/1253] lr: 4.0000e-03 eta: 5:57:37 time: 0.5854 data_time: 0.0377 memory: 23504 grad_norm: 2.7516 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.1663 loss: 1.1663 2022/09/08 14:58:46 - mmengine - INFO - Epoch(train) [21][1100/1253] lr: 4.0000e-03 eta: 5:57:27 time: 0.6551 data_time: 0.0383 memory: 23504 grad_norm: 2.7386 top1_acc: 0.5833 top5_acc: 1.0000 loss_cls: 1.1027 loss: 1.1027 2022/09/08 14:58:58 - mmengine - INFO - Epoch(train) [21][1120/1253] lr: 4.0000e-03 eta: 5:57:14 time: 0.5619 data_time: 0.0444 memory: 23504 grad_norm: 2.7561 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.2009 loss: 1.2009 2022/09/08 14:59:09 - mmengine - INFO - Epoch(train) [21][1140/1253] lr: 4.0000e-03 eta: 5:57:02 time: 0.5582 data_time: 0.0344 memory: 23504 grad_norm: 2.6764 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3014 loss: 1.3014 2022/09/08 14:59:20 - mmengine - INFO - Epoch(train) [21][1160/1253] lr: 4.0000e-03 eta: 5:56:49 time: 0.5643 data_time: 0.0358 memory: 23504 grad_norm: 2.6773 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.1778 loss: 1.1778 2022/09/08 14:59:31 - mmengine - INFO - Epoch(train) [21][1180/1253] lr: 4.0000e-03 eta: 5:56:37 time: 0.5647 data_time: 0.0395 memory: 23504 grad_norm: 2.7146 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.2021 loss: 1.2021 2022/09/08 14:59:43 - mmengine - INFO - Epoch(train) [21][1200/1253] lr: 4.0000e-03 eta: 5:56:25 time: 0.5697 data_time: 0.0509 memory: 23504 grad_norm: 2.7474 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.0165 loss: 1.0165 2022/09/08 14:59:54 - mmengine - INFO - Epoch(train) [21][1220/1253] lr: 4.0000e-03 eta: 5:56:13 time: 0.5681 data_time: 0.0370 memory: 23504 grad_norm: 2.7843 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.1600 loss: 1.1600 2022/09/08 15:00:04 - mmengine - INFO - Epoch(train) [21][1240/1253] lr: 4.0000e-03 eta: 5:55:58 time: 0.4859 data_time: 0.0284 memory: 23504 grad_norm: 2.6768 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.1385 loss: 1.1385 2022/09/08 15:00:09 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 15:00:09 - mmengine - INFO - Epoch(train) [21][1253/1253] lr: 4.0000e-03 eta: 5:55:58 time: 0.4330 data_time: 0.0113 memory: 23504 grad_norm: 2.8692 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.2404 loss: 1.2404 2022/09/08 15:00:35 - mmengine - INFO - Epoch(train) [22][20/1253] lr: 4.0000e-03 eta: 5:55:48 time: 1.2987 data_time: 0.6470 memory: 23504 grad_norm: 2.6677 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 1.1332 loss: 1.1332 2022/09/08 15:00:46 - mmengine - INFO - Epoch(train) [22][40/1253] lr: 4.0000e-03 eta: 5:55:34 time: 0.5277 data_time: 0.0261 memory: 23504 grad_norm: 2.7276 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.0992 loss: 1.0992 2022/09/08 15:00:57 - mmengine - INFO - Epoch(train) [22][60/1253] lr: 4.0000e-03 eta: 5:55:21 time: 0.5443 data_time: 0.0393 memory: 23504 grad_norm: 2.6415 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0826 loss: 1.0826 2022/09/08 15:01:10 - mmengine - INFO - Epoch(train) [22][80/1253] lr: 4.0000e-03 eta: 5:55:11 time: 0.6394 data_time: 0.0368 memory: 23504 grad_norm: 2.6886 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.2222 loss: 1.2222 2022/09/08 15:01:22 - mmengine - INFO - Epoch(train) [22][100/1253] lr: 4.0000e-03 eta: 5:54:59 time: 0.5893 data_time: 0.0722 memory: 23504 grad_norm: 2.7353 top1_acc: 0.6667 top5_acc: 0.7500 loss_cls: 1.1323 loss: 1.1323 2022/09/08 15:01:33 - mmengine - INFO - Epoch(train) [22][120/1253] lr: 4.0000e-03 eta: 5:54:47 time: 0.5740 data_time: 0.0372 memory: 23504 grad_norm: 2.6615 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.1194 loss: 1.1194 2022/09/08 15:01:46 - mmengine - INFO - Epoch(train) [22][140/1253] lr: 4.0000e-03 eta: 5:54:36 time: 0.6297 data_time: 0.1190 memory: 23504 grad_norm: 2.6907 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.9315 loss: 0.9315 2022/09/08 15:01:57 - mmengine - INFO - Epoch(train) [22][160/1253] lr: 4.0000e-03 eta: 5:54:24 time: 0.5589 data_time: 0.0270 memory: 23504 grad_norm: 2.6797 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.0723 loss: 1.0723 2022/09/08 15:02:08 - mmengine - INFO - Epoch(train) [22][180/1253] lr: 4.0000e-03 eta: 5:54:12 time: 0.5812 data_time: 0.0557 memory: 23504 grad_norm: 2.7564 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.2239 loss: 1.2239 2022/09/08 15:02:20 - mmengine - INFO - Epoch(train) [22][200/1253] lr: 4.0000e-03 eta: 5:54:00 time: 0.5755 data_time: 0.0364 memory: 23504 grad_norm: 2.7201 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.1231 loss: 1.1231 2022/09/08 15:02:32 - mmengine - INFO - Epoch(train) [22][220/1253] lr: 4.0000e-03 eta: 5:53:48 time: 0.5851 data_time: 0.0349 memory: 23504 grad_norm: 2.7438 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0672 loss: 1.0672 2022/09/08 15:02:44 - mmengine - INFO - Epoch(train) [22][240/1253] lr: 4.0000e-03 eta: 5:53:37 time: 0.6188 data_time: 0.0438 memory: 23504 grad_norm: 2.6935 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.1472 loss: 1.1472 2022/09/08 15:02:55 - mmengine - INFO - Epoch(train) [22][260/1253] lr: 4.0000e-03 eta: 5:53:25 time: 0.5599 data_time: 0.0451 memory: 23504 grad_norm: 2.7337 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.0967 loss: 1.0967 2022/09/08 15:03:07 - mmengine - INFO - Epoch(train) [22][280/1253] lr: 4.0000e-03 eta: 5:53:13 time: 0.5931 data_time: 0.0387 memory: 23504 grad_norm: 2.6875 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 1.1762 loss: 1.1762 2022/09/08 15:03:19 - mmengine - INFO - Epoch(train) [22][300/1253] lr: 4.0000e-03 eta: 5:53:01 time: 0.5755 data_time: 0.0430 memory: 23504 grad_norm: 2.6914 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.0881 loss: 1.0881 2022/09/08 15:03:30 - mmengine - INFO - Epoch(train) [22][320/1253] lr: 4.0000e-03 eta: 5:52:48 time: 0.5545 data_time: 0.0515 memory: 23504 grad_norm: 2.8160 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.1300 loss: 1.1300 2022/09/08 15:03:41 - mmengine - INFO - Epoch(train) [22][340/1253] lr: 4.0000e-03 eta: 5:52:36 time: 0.5526 data_time: 0.0470 memory: 23504 grad_norm: 2.7623 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.0896 loss: 1.0896 2022/09/08 15:03:52 - mmengine - INFO - Epoch(train) [22][360/1253] lr: 4.0000e-03 eta: 5:52:23 time: 0.5507 data_time: 0.0423 memory: 23504 grad_norm: 2.7030 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1438 loss: 1.1438 2022/09/08 15:04:03 - mmengine - INFO - Epoch(train) [22][380/1253] lr: 4.0000e-03 eta: 5:52:10 time: 0.5655 data_time: 0.0418 memory: 23504 grad_norm: 2.7776 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.2327 loss: 1.2327 2022/09/08 15:04:15 - mmengine - INFO - Epoch(train) [22][400/1253] lr: 4.0000e-03 eta: 5:51:58 time: 0.5787 data_time: 0.0530 memory: 23504 grad_norm: 2.7423 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1995 loss: 1.1995 2022/09/08 15:04:27 - mmengine - INFO - Epoch(train) [22][420/1253] lr: 4.0000e-03 eta: 5:51:47 time: 0.5928 data_time: 0.0441 memory: 23504 grad_norm: 2.7533 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.0994 loss: 1.0994 2022/09/08 15:04:39 - mmengine - INFO - Epoch(train) [22][440/1253] lr: 4.0000e-03 eta: 5:51:36 time: 0.6049 data_time: 0.0485 memory: 23504 grad_norm: 2.7025 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.2740 loss: 1.2740 2022/09/08 15:04:51 - mmengine - INFO - Epoch(train) [22][460/1253] lr: 4.0000e-03 eta: 5:51:24 time: 0.6031 data_time: 0.0679 memory: 23504 grad_norm: 2.7831 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.1644 loss: 1.1644 2022/09/08 15:05:04 - mmengine - INFO - Epoch(train) [22][480/1253] lr: 4.0000e-03 eta: 5:51:15 time: 0.6722 data_time: 0.1608 memory: 23504 grad_norm: 2.7022 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.1764 loss: 1.1764 2022/09/08 15:05:15 - mmengine - INFO - Epoch(train) [22][500/1253] lr: 4.0000e-03 eta: 5:51:02 time: 0.5633 data_time: 0.0293 memory: 23504 grad_norm: 2.7936 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0576 loss: 1.0576 2022/09/08 15:05:27 - mmengine - INFO - Epoch(train) [22][520/1253] lr: 4.0000e-03 eta: 5:50:51 time: 0.6005 data_time: 0.0302 memory: 23504 grad_norm: 2.6986 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.2224 loss: 1.2224 2022/09/08 15:05:39 - mmengine - INFO - Epoch(train) [22][540/1253] lr: 4.0000e-03 eta: 5:50:39 time: 0.5825 data_time: 0.0665 memory: 23504 grad_norm: 2.8004 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.1747 loss: 1.1747 2022/09/08 15:05:50 - mmengine - INFO - Epoch(train) [22][560/1253] lr: 4.0000e-03 eta: 5:50:26 time: 0.5507 data_time: 0.0301 memory: 23504 grad_norm: 2.7105 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.0932 loss: 1.0932 2022/09/08 15:06:01 - mmengine - INFO - Epoch(train) [22][580/1253] lr: 4.0000e-03 eta: 5:50:14 time: 0.5705 data_time: 0.0312 memory: 23504 grad_norm: 2.7838 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.1258 loss: 1.1258 2022/09/08 15:06:17 - mmengine - INFO - Epoch(train) [22][600/1253] lr: 4.0000e-03 eta: 5:50:07 time: 0.7563 data_time: 0.0374 memory: 23504 grad_norm: 2.8264 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.0408 loss: 1.0408 2022/09/08 15:06:28 - mmengine - INFO - Epoch(train) [22][620/1253] lr: 4.0000e-03 eta: 5:49:54 time: 0.5562 data_time: 0.0366 memory: 23504 grad_norm: 2.7639 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.1706 loss: 1.1706 2022/09/08 15:06:39 - mmengine - INFO - Epoch(train) [22][640/1253] lr: 4.0000e-03 eta: 5:49:41 time: 0.5474 data_time: 0.0443 memory: 23504 grad_norm: 2.7876 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 1.2233 loss: 1.2233 2022/09/08 15:06:50 - mmengine - INFO - Epoch(train) [22][660/1253] lr: 4.0000e-03 eta: 5:49:29 time: 0.5741 data_time: 0.0458 memory: 23504 grad_norm: 2.7944 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.1502 loss: 1.1502 2022/09/08 15:07:01 - mmengine - INFO - Epoch(train) [22][680/1253] lr: 4.0000e-03 eta: 5:49:17 time: 0.5614 data_time: 0.0436 memory: 23504 grad_norm: 2.7819 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.0756 loss: 1.0756 2022/09/08 15:07:06 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 15:07:13 - mmengine - INFO - Epoch(train) [22][700/1253] lr: 4.0000e-03 eta: 5:49:05 time: 0.5972 data_time: 0.0521 memory: 23504 grad_norm: 2.8179 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2567 loss: 1.2567 2022/09/08 15:07:25 - mmengine - INFO - Epoch(train) [22][720/1253] lr: 4.0000e-03 eta: 5:48:54 time: 0.5879 data_time: 0.0353 memory: 23504 grad_norm: 2.7702 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0415 loss: 1.0415 2022/09/08 15:07:37 - mmengine - INFO - Epoch(train) [22][740/1253] lr: 4.0000e-03 eta: 5:48:41 time: 0.5752 data_time: 0.0445 memory: 23504 grad_norm: 2.7622 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.2527 loss: 1.2527 2022/09/08 15:07:48 - mmengine - INFO - Epoch(train) [22][760/1253] lr: 4.0000e-03 eta: 5:48:29 time: 0.5531 data_time: 0.0529 memory: 23504 grad_norm: 2.7617 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.0981 loss: 1.0981 2022/09/08 15:07:59 - mmengine - INFO - Epoch(train) [22][780/1253] lr: 4.0000e-03 eta: 5:48:17 time: 0.5795 data_time: 0.0630 memory: 23504 grad_norm: 2.7338 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0425 loss: 1.0425 2022/09/08 15:08:14 - mmengine - INFO - Epoch(train) [22][800/1253] lr: 4.0000e-03 eta: 5:48:08 time: 0.7169 data_time: 0.0293 memory: 23504 grad_norm: 2.8062 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.2098 loss: 1.2098 2022/09/08 15:08:25 - mmengine - INFO - Epoch(train) [22][820/1253] lr: 4.0000e-03 eta: 5:47:56 time: 0.5554 data_time: 0.0365 memory: 23504 grad_norm: 2.7499 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.1758 loss: 1.1758 2022/09/08 15:08:36 - mmengine - INFO - Epoch(train) [22][840/1253] lr: 4.0000e-03 eta: 5:47:43 time: 0.5526 data_time: 0.0470 memory: 23504 grad_norm: 2.7968 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.1693 loss: 1.1693 2022/09/08 15:08:47 - mmengine - INFO - Epoch(train) [22][860/1253] lr: 4.0000e-03 eta: 5:47:31 time: 0.5647 data_time: 0.0441 memory: 23504 grad_norm: 2.8116 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.1722 loss: 1.1722 2022/09/08 15:08:58 - mmengine - INFO - Epoch(train) [22][880/1253] lr: 4.0000e-03 eta: 5:47:19 time: 0.5672 data_time: 0.0356 memory: 23504 grad_norm: 2.8570 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.1772 loss: 1.1772 2022/09/08 15:09:10 - mmengine - INFO - Epoch(train) [22][900/1253] lr: 4.0000e-03 eta: 5:47:07 time: 0.5854 data_time: 0.0479 memory: 23504 grad_norm: 2.8017 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.1877 loss: 1.1877 2022/09/08 15:09:23 - mmengine - INFO - Epoch(train) [22][920/1253] lr: 4.0000e-03 eta: 5:46:57 time: 0.6599 data_time: 0.0331 memory: 23504 grad_norm: 2.7990 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1067 loss: 1.1067 2022/09/08 15:09:35 - mmengine - INFO - Epoch(train) [22][940/1253] lr: 4.0000e-03 eta: 5:46:44 time: 0.5652 data_time: 0.0379 memory: 23504 grad_norm: 2.8024 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0492 loss: 1.0492 2022/09/08 15:09:46 - mmengine - INFO - Epoch(train) [22][960/1253] lr: 4.0000e-03 eta: 5:46:33 time: 0.5818 data_time: 0.0471 memory: 23504 grad_norm: 2.7767 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.1811 loss: 1.1811 2022/09/08 15:09:58 - mmengine - INFO - Epoch(train) [22][980/1253] lr: 4.0000e-03 eta: 5:46:20 time: 0.5732 data_time: 0.0445 memory: 23504 grad_norm: 2.7962 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.1496 loss: 1.1496 2022/09/08 15:10:10 - mmengine - INFO - Epoch(train) [22][1000/1253] lr: 4.0000e-03 eta: 5:46:09 time: 0.6099 data_time: 0.0459 memory: 23504 grad_norm: 2.7765 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3033 loss: 1.3033 2022/09/08 15:10:22 - mmengine - INFO - Epoch(train) [22][1020/1253] lr: 4.0000e-03 eta: 5:45:58 time: 0.5922 data_time: 0.0400 memory: 23504 grad_norm: 2.7874 top1_acc: 0.7083 top5_acc: 0.7500 loss_cls: 1.1707 loss: 1.1707 2022/09/08 15:10:33 - mmengine - INFO - Epoch(train) [22][1040/1253] lr: 4.0000e-03 eta: 5:45:45 time: 0.5682 data_time: 0.0335 memory: 23504 grad_norm: 2.8029 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9982 loss: 0.9982 2022/09/08 15:10:46 - mmengine - INFO - Epoch(train) [22][1060/1253] lr: 4.0000e-03 eta: 5:45:35 time: 0.6236 data_time: 0.0452 memory: 23504 grad_norm: 2.7669 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.0715 loss: 1.0715 2022/09/08 15:10:57 - mmengine - INFO - Epoch(train) [22][1080/1253] lr: 4.0000e-03 eta: 5:45:22 time: 0.5527 data_time: 0.0427 memory: 23504 grad_norm: 2.7656 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 1.1764 loss: 1.1764 2022/09/08 15:11:09 - mmengine - INFO - Epoch(train) [22][1100/1253] lr: 4.0000e-03 eta: 5:45:10 time: 0.5916 data_time: 0.0435 memory: 23504 grad_norm: 2.7781 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.1212 loss: 1.1212 2022/09/08 15:11:20 - mmengine - INFO - Epoch(train) [22][1120/1253] lr: 4.0000e-03 eta: 5:44:58 time: 0.5586 data_time: 0.0446 memory: 23504 grad_norm: 2.7538 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 1.2116 loss: 1.2116 2022/09/08 15:11:30 - mmengine - INFO - Epoch(train) [22][1140/1253] lr: 4.0000e-03 eta: 5:44:45 time: 0.5335 data_time: 0.0426 memory: 23504 grad_norm: 2.8024 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.0513 loss: 1.0513 2022/09/08 15:11:42 - mmengine - INFO - Epoch(train) [22][1160/1253] lr: 4.0000e-03 eta: 5:44:32 time: 0.5682 data_time: 0.0496 memory: 23504 grad_norm: 2.7424 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.2092 loss: 1.2092 2022/09/08 15:11:53 - mmengine - INFO - Epoch(train) [22][1180/1253] lr: 4.0000e-03 eta: 5:44:20 time: 0.5748 data_time: 0.0375 memory: 23504 grad_norm: 2.8421 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.1681 loss: 1.1681 2022/09/08 15:12:05 - mmengine - INFO - Epoch(train) [22][1200/1253] lr: 4.0000e-03 eta: 5:44:08 time: 0.5731 data_time: 0.0480 memory: 23504 grad_norm: 2.7705 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.2360 loss: 1.2360 2022/09/08 15:12:17 - mmengine - INFO - Epoch(train) [22][1220/1253] lr: 4.0000e-03 eta: 5:43:57 time: 0.6270 data_time: 0.0452 memory: 23504 grad_norm: 2.8046 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.1125 loss: 1.1125 2022/09/08 15:12:28 - mmengine - INFO - Epoch(train) [22][1240/1253] lr: 4.0000e-03 eta: 5:43:45 time: 0.5561 data_time: 0.0271 memory: 23504 grad_norm: 2.7401 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.1056 loss: 1.1056 2022/09/08 15:12:34 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 15:12:34 - mmengine - INFO - Epoch(train) [22][1253/1253] lr: 4.0000e-03 eta: 5:43:45 time: 0.4314 data_time: 0.0182 memory: 23504 grad_norm: 2.8452 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.0095 loss: 1.0095 2022/09/08 15:13:00 - mmengine - INFO - Epoch(train) [23][20/1253] lr: 4.0000e-03 eta: 5:43:34 time: 1.2896 data_time: 0.6626 memory: 23504 grad_norm: 2.7402 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.1302 loss: 1.1302 2022/09/08 15:13:10 - mmengine - INFO - Epoch(train) [23][40/1253] lr: 4.0000e-03 eta: 5:43:20 time: 0.5191 data_time: 0.0355 memory: 23504 grad_norm: 2.7302 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0385 loss: 1.0385 2022/09/08 15:13:21 - mmengine - INFO - Epoch(train) [23][60/1253] lr: 4.0000e-03 eta: 5:43:07 time: 0.5316 data_time: 0.0344 memory: 23504 grad_norm: 2.6562 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.0990 loss: 1.0990 2022/09/08 15:13:32 - mmengine - INFO - Epoch(train) [23][80/1253] lr: 4.0000e-03 eta: 5:42:54 time: 0.5599 data_time: 0.0366 memory: 23504 grad_norm: 2.7400 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.0298 loss: 1.0298 2022/09/08 15:13:44 - mmengine - INFO - Epoch(train) [23][100/1253] lr: 4.0000e-03 eta: 5:42:43 time: 0.6211 data_time: 0.0621 memory: 23504 grad_norm: 2.7944 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.1307 loss: 1.1307 2022/09/08 15:13:56 - mmengine - INFO - Epoch(train) [23][120/1253] lr: 4.0000e-03 eta: 5:42:32 time: 0.6045 data_time: 0.0472 memory: 23504 grad_norm: 2.8281 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.0591 loss: 1.0591 2022/09/08 15:14:08 - mmengine - INFO - Epoch(train) [23][140/1253] lr: 4.0000e-03 eta: 5:42:20 time: 0.5770 data_time: 0.0369 memory: 23504 grad_norm: 2.7075 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 0.9901 loss: 0.9901 2022/09/08 15:14:19 - mmengine - INFO - Epoch(train) [23][160/1253] lr: 4.0000e-03 eta: 5:42:08 time: 0.5696 data_time: 0.0422 memory: 23504 grad_norm: 2.6712 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0859 loss: 1.0859 2022/09/08 15:14:32 - mmengine - INFO - Epoch(train) [23][180/1253] lr: 4.0000e-03 eta: 5:41:57 time: 0.6090 data_time: 0.0522 memory: 23504 grad_norm: 2.7930 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.1003 loss: 1.1003 2022/09/08 15:14:43 - mmengine - INFO - Epoch(train) [23][200/1253] lr: 4.0000e-03 eta: 5:41:44 time: 0.5602 data_time: 0.0410 memory: 23504 grad_norm: 2.6850 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0658 loss: 1.0658 2022/09/08 15:14:56 - mmengine - INFO - Epoch(train) [23][220/1253] lr: 4.0000e-03 eta: 5:41:34 time: 0.6370 data_time: 0.0370 memory: 23504 grad_norm: 2.8222 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.1037 loss: 1.1037 2022/09/08 15:15:07 - mmengine - INFO - Epoch(train) [23][240/1253] lr: 4.0000e-03 eta: 5:41:22 time: 0.5777 data_time: 0.0402 memory: 23504 grad_norm: 2.8396 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.1026 loss: 1.1026 2022/09/08 15:15:19 - mmengine - INFO - Epoch(train) [23][260/1253] lr: 4.0000e-03 eta: 5:41:10 time: 0.5754 data_time: 0.0455 memory: 23504 grad_norm: 2.7670 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0416 loss: 1.0416 2022/09/08 15:15:30 - mmengine - INFO - Epoch(train) [23][280/1253] lr: 4.0000e-03 eta: 5:40:58 time: 0.5803 data_time: 0.0464 memory: 23504 grad_norm: 2.8057 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.0668 loss: 1.0668 2022/09/08 15:15:41 - mmengine - INFO - Epoch(train) [23][300/1253] lr: 4.0000e-03 eta: 5:40:45 time: 0.5569 data_time: 0.0400 memory: 23504 grad_norm: 2.7738 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.1444 loss: 1.1444 2022/09/08 15:15:53 - mmengine - INFO - Epoch(train) [23][320/1253] lr: 4.0000e-03 eta: 5:40:33 time: 0.5899 data_time: 0.0528 memory: 23504 grad_norm: 2.8215 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.0651 loss: 1.0651 2022/09/08 15:16:05 - mmengine - INFO - Epoch(train) [23][340/1253] lr: 4.0000e-03 eta: 5:40:21 time: 0.5792 data_time: 0.0415 memory: 23504 grad_norm: 2.6666 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 0.9998 loss: 0.9998 2022/09/08 15:16:17 - mmengine - INFO - Epoch(train) [23][360/1253] lr: 4.0000e-03 eta: 5:40:10 time: 0.5963 data_time: 0.0343 memory: 23504 grad_norm: 2.8534 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.0875 loss: 1.0875 2022/09/08 15:16:29 - mmengine - INFO - Epoch(train) [23][380/1253] lr: 4.0000e-03 eta: 5:39:58 time: 0.5966 data_time: 0.0338 memory: 23504 grad_norm: 2.7759 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.0883 loss: 1.0883 2022/09/08 15:16:40 - mmengine - INFO - Epoch(train) [23][400/1253] lr: 4.0000e-03 eta: 5:39:46 time: 0.5728 data_time: 0.0396 memory: 23504 grad_norm: 2.7737 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.0605 loss: 1.0605 2022/09/08 15:16:52 - mmengine - INFO - Epoch(train) [23][420/1253] lr: 4.0000e-03 eta: 5:39:35 time: 0.6070 data_time: 0.0407 memory: 23504 grad_norm: 2.7848 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.1600 loss: 1.1600 2022/09/08 15:17:01 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 15:17:04 - mmengine - INFO - Epoch(train) [23][440/1253] lr: 4.0000e-03 eta: 5:39:24 time: 0.6090 data_time: 0.0390 memory: 23504 grad_norm: 2.8298 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.0956 loss: 1.0956 2022/09/08 15:17:17 - mmengine - INFO - Epoch(train) [23][460/1253] lr: 4.0000e-03 eta: 5:39:12 time: 0.6043 data_time: 0.0343 memory: 23504 grad_norm: 2.8303 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.9588 loss: 0.9588 2022/09/08 15:17:28 - mmengine - INFO - Epoch(train) [23][480/1253] lr: 4.0000e-03 eta: 5:39:00 time: 0.5799 data_time: 0.0509 memory: 23504 grad_norm: 2.7731 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0970 loss: 1.0970 2022/09/08 15:17:40 - mmengine - INFO - Epoch(train) [23][500/1253] lr: 4.0000e-03 eta: 5:38:49 time: 0.5995 data_time: 0.0392 memory: 23504 grad_norm: 2.8284 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.1031 loss: 1.1031 2022/09/08 15:17:51 - mmengine - INFO - Epoch(train) [23][520/1253] lr: 4.0000e-03 eta: 5:38:37 time: 0.5697 data_time: 0.0366 memory: 23504 grad_norm: 2.7713 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.1362 loss: 1.1362 2022/09/08 15:18:03 - mmengine - INFO - Epoch(train) [23][540/1253] lr: 4.0000e-03 eta: 5:38:25 time: 0.5673 data_time: 0.0477 memory: 23504 grad_norm: 2.7397 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.1761 loss: 1.1761 2022/09/08 15:18:16 - mmengine - INFO - Epoch(train) [23][560/1253] lr: 4.0000e-03 eta: 5:38:15 time: 0.6674 data_time: 0.0516 memory: 23504 grad_norm: 2.8487 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9737 loss: 0.9737 2022/09/08 15:18:28 - mmengine - INFO - Epoch(train) [23][580/1253] lr: 4.0000e-03 eta: 5:38:03 time: 0.5958 data_time: 0.0511 memory: 23504 grad_norm: 2.8583 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.0112 loss: 1.0112 2022/09/08 15:18:40 - mmengine - INFO - Epoch(train) [23][600/1253] lr: 4.0000e-03 eta: 5:37:51 time: 0.5813 data_time: 0.0377 memory: 23504 grad_norm: 2.8119 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.0772 loss: 1.0772 2022/09/08 15:18:51 - mmengine - INFO - Epoch(train) [23][620/1253] lr: 4.0000e-03 eta: 5:37:38 time: 0.5407 data_time: 0.0420 memory: 23504 grad_norm: 2.8365 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.1303 loss: 1.1303 2022/09/08 15:19:02 - mmengine - INFO - Epoch(train) [23][640/1253] lr: 4.0000e-03 eta: 5:37:26 time: 0.5686 data_time: 0.0452 memory: 23504 grad_norm: 2.8626 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1168 loss: 1.1168 2022/09/08 15:19:14 - mmengine - INFO - Epoch(train) [23][660/1253] lr: 4.0000e-03 eta: 5:37:15 time: 0.6102 data_time: 0.0873 memory: 23504 grad_norm: 2.7973 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.1023 loss: 1.1023 2022/09/08 15:19:25 - mmengine - INFO - Epoch(train) [23][680/1253] lr: 4.0000e-03 eta: 5:37:02 time: 0.5576 data_time: 0.0439 memory: 23504 grad_norm: 2.8393 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.0754 loss: 1.0754 2022/09/08 15:19:36 - mmengine - INFO - Epoch(train) [23][700/1253] lr: 4.0000e-03 eta: 5:36:50 time: 0.5463 data_time: 0.0452 memory: 23504 grad_norm: 2.8083 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.0944 loss: 1.0944 2022/09/08 15:19:48 - mmengine - INFO - Epoch(train) [23][720/1253] lr: 4.0000e-03 eta: 5:36:38 time: 0.5762 data_time: 0.0454 memory: 23504 grad_norm: 2.8063 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0733 loss: 1.0733 2022/09/08 15:20:01 - mmengine - INFO - Epoch(train) [23][740/1253] lr: 4.0000e-03 eta: 5:36:28 time: 0.6729 data_time: 0.0443 memory: 23504 grad_norm: 2.8131 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 1.1901 loss: 1.1901 2022/09/08 15:20:12 - mmengine - INFO - Epoch(train) [23][760/1253] lr: 4.0000e-03 eta: 5:36:15 time: 0.5564 data_time: 0.0443 memory: 23504 grad_norm: 2.8499 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.1757 loss: 1.1757 2022/09/08 15:20:24 - mmengine - INFO - Epoch(train) [23][780/1253] lr: 4.0000e-03 eta: 5:36:03 time: 0.5751 data_time: 0.0408 memory: 23504 grad_norm: 2.7954 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.1805 loss: 1.1805 2022/09/08 15:20:35 - mmengine - INFO - Epoch(train) [23][800/1253] lr: 4.0000e-03 eta: 5:35:51 time: 0.5806 data_time: 0.0605 memory: 23504 grad_norm: 2.8123 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.2897 loss: 1.2897 2022/09/08 15:20:47 - mmengine - INFO - Epoch(train) [23][820/1253] lr: 4.0000e-03 eta: 5:35:39 time: 0.5692 data_time: 0.0505 memory: 23504 grad_norm: 2.7753 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.1158 loss: 1.1158 2022/09/08 15:20:59 - mmengine - INFO - Epoch(train) [23][840/1253] lr: 4.0000e-03 eta: 5:35:28 time: 0.5923 data_time: 0.0325 memory: 23504 grad_norm: 2.8325 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0426 loss: 1.0426 2022/09/08 15:21:13 - mmengine - INFO - Epoch(train) [23][860/1253] lr: 4.0000e-03 eta: 5:35:19 time: 0.7264 data_time: 0.0391 memory: 23504 grad_norm: 2.7735 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.9997 loss: 0.9997 2022/09/08 15:21:24 - mmengine - INFO - Epoch(train) [23][880/1253] lr: 4.0000e-03 eta: 5:35:06 time: 0.5357 data_time: 0.0340 memory: 23504 grad_norm: 2.8872 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.1047 loss: 1.1047 2022/09/08 15:21:35 - mmengine - INFO - Epoch(train) [23][900/1253] lr: 4.0000e-03 eta: 5:34:54 time: 0.5648 data_time: 0.0429 memory: 23504 grad_norm: 2.8168 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.1193 loss: 1.1193 2022/09/08 15:21:47 - mmengine - INFO - Epoch(train) [23][920/1253] lr: 4.0000e-03 eta: 5:34:41 time: 0.5633 data_time: 0.0398 memory: 23504 grad_norm: 2.6839 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.0641 loss: 1.0641 2022/09/08 15:21:59 - mmengine - INFO - Epoch(train) [23][940/1253] lr: 4.0000e-03 eta: 5:34:30 time: 0.6002 data_time: 0.0474 memory: 23504 grad_norm: 2.8654 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0111 loss: 1.0111 2022/09/08 15:22:10 - mmengine - INFO - Epoch(train) [23][960/1253] lr: 4.0000e-03 eta: 5:34:18 time: 0.5850 data_time: 0.0403 memory: 23504 grad_norm: 2.8600 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.1173 loss: 1.1173 2022/09/08 15:22:22 - mmengine - INFO - Epoch(train) [23][980/1253] lr: 4.0000e-03 eta: 5:34:06 time: 0.5629 data_time: 0.0479 memory: 23504 grad_norm: 2.7778 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8648 loss: 0.8648 2022/09/08 15:22:33 - mmengine - INFO - Epoch(train) [23][1000/1253] lr: 4.0000e-03 eta: 5:33:54 time: 0.5930 data_time: 0.0495 memory: 23504 grad_norm: 2.8004 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 1.1603 loss: 1.1603 2022/09/08 15:22:45 - mmengine - INFO - Epoch(train) [23][1020/1253] lr: 4.0000e-03 eta: 5:33:42 time: 0.5733 data_time: 0.0398 memory: 23504 grad_norm: 2.7299 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.2356 loss: 1.2356 2022/09/08 15:22:56 - mmengine - INFO - Epoch(train) [23][1040/1253] lr: 4.0000e-03 eta: 5:33:30 time: 0.5665 data_time: 0.0395 memory: 23504 grad_norm: 2.8390 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1706 loss: 1.1706 2022/09/08 15:23:08 - mmengine - INFO - Epoch(train) [23][1060/1253] lr: 4.0000e-03 eta: 5:33:18 time: 0.5797 data_time: 0.0482 memory: 23504 grad_norm: 2.7972 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0541 loss: 1.0541 2022/09/08 15:23:20 - mmengine - INFO - Epoch(train) [23][1080/1253] lr: 4.0000e-03 eta: 5:33:07 time: 0.6260 data_time: 0.0463 memory: 23504 grad_norm: 2.8254 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.2395 loss: 1.2395 2022/09/08 15:23:32 - mmengine - INFO - Epoch(train) [23][1100/1253] lr: 4.0000e-03 eta: 5:32:55 time: 0.5756 data_time: 0.0417 memory: 23504 grad_norm: 2.7940 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.1467 loss: 1.1467 2022/09/08 15:23:44 - mmengine - INFO - Epoch(train) [23][1120/1253] lr: 4.0000e-03 eta: 5:32:44 time: 0.6321 data_time: 0.0382 memory: 23504 grad_norm: 2.8366 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.0641 loss: 1.0641 2022/09/08 15:23:55 - mmengine - INFO - Epoch(train) [23][1140/1253] lr: 4.0000e-03 eta: 5:32:32 time: 0.5470 data_time: 0.0394 memory: 23504 grad_norm: 2.8098 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.0486 loss: 1.0486 2022/09/08 15:24:08 - mmengine - INFO - Epoch(train) [23][1160/1253] lr: 4.0000e-03 eta: 5:32:21 time: 0.6185 data_time: 0.0460 memory: 23504 grad_norm: 2.8281 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 1.0984 loss: 1.0984 2022/09/08 15:24:20 - mmengine - INFO - Epoch(train) [23][1180/1253] lr: 4.0000e-03 eta: 5:32:09 time: 0.6034 data_time: 0.0462 memory: 23504 grad_norm: 2.7373 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9864 loss: 0.9864 2022/09/08 15:24:31 - mmengine - INFO - Epoch(train) [23][1200/1253] lr: 4.0000e-03 eta: 5:31:57 time: 0.5731 data_time: 0.0475 memory: 23504 grad_norm: 2.7997 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.0069 loss: 1.0069 2022/09/08 15:24:43 - mmengine - INFO - Epoch(train) [23][1220/1253] lr: 4.0000e-03 eta: 5:31:45 time: 0.5632 data_time: 0.0450 memory: 23504 grad_norm: 2.7856 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9061 loss: 0.9061 2022/09/08 15:24:53 - mmengine - INFO - Epoch(train) [23][1240/1253] lr: 4.0000e-03 eta: 5:31:31 time: 0.4961 data_time: 0.0276 memory: 23504 grad_norm: 2.8202 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.0965 loss: 1.0965 2022/09/08 15:24:58 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 15:24:58 - mmengine - INFO - Epoch(train) [23][1253/1253] lr: 4.0000e-03 eta: 5:31:31 time: 0.4324 data_time: 0.0177 memory: 23504 grad_norm: 2.9015 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.2108 loss: 1.2108 2022/09/08 15:25:26 - mmengine - INFO - Epoch(train) [24][20/1253] lr: 4.0000e-03 eta: 5:31:21 time: 1.3933 data_time: 0.5223 memory: 23504 grad_norm: 2.8167 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.0417 loss: 1.0417 2022/09/08 15:25:39 - mmengine - INFO - Epoch(train) [24][40/1253] lr: 4.0000e-03 eta: 5:31:11 time: 0.6377 data_time: 0.0318 memory: 23504 grad_norm: 2.7816 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 1.0213 loss: 1.0213 2022/09/08 15:25:49 - mmengine - INFO - Epoch(train) [24][60/1253] lr: 4.0000e-03 eta: 5:30:57 time: 0.5169 data_time: 0.0322 memory: 23504 grad_norm: 2.8746 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.1911 loss: 1.1911 2022/09/08 15:26:01 - mmengine - INFO - Epoch(train) [24][80/1253] lr: 4.0000e-03 eta: 5:30:45 time: 0.5754 data_time: 0.0436 memory: 23504 grad_norm: 2.7710 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0307 loss: 1.0307 2022/09/08 15:26:12 - mmengine - INFO - Epoch(train) [24][100/1253] lr: 4.0000e-03 eta: 5:30:33 time: 0.5599 data_time: 0.0406 memory: 23504 grad_norm: 2.7437 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.1972 loss: 1.1972 2022/09/08 15:26:23 - mmengine - INFO - Epoch(train) [24][120/1253] lr: 4.0000e-03 eta: 5:30:21 time: 0.5703 data_time: 0.0430 memory: 23504 grad_norm: 2.8458 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.1964 loss: 1.1964 2022/09/08 15:26:35 - mmengine - INFO - Epoch(train) [24][140/1253] lr: 4.0000e-03 eta: 5:30:09 time: 0.5729 data_time: 0.0460 memory: 23504 grad_norm: 2.8081 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.0801 loss: 1.0801 2022/09/08 15:26:46 - mmengine - INFO - Epoch(train) [24][160/1253] lr: 4.0000e-03 eta: 5:29:56 time: 0.5663 data_time: 0.0488 memory: 23504 grad_norm: 2.7910 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 0.9966 loss: 0.9966 2022/09/08 15:26:58 - mmengine - INFO - Epoch(train) [24][180/1253] lr: 4.0000e-03 eta: 5:29:44 time: 0.5844 data_time: 0.0404 memory: 23504 grad_norm: 2.8243 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.0877 loss: 1.0877 2022/09/08 15:26:58 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 15:27:09 - mmengine - INFO - Epoch(train) [24][200/1253] lr: 4.0000e-03 eta: 5:29:32 time: 0.5616 data_time: 0.0364 memory: 23504 grad_norm: 2.7509 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 1.0608 loss: 1.0608 2022/09/08 15:27:20 - mmengine - INFO - Epoch(train) [24][220/1253] lr: 4.0000e-03 eta: 5:29:20 time: 0.5763 data_time: 0.0513 memory: 23504 grad_norm: 2.8121 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9410 loss: 0.9410 2022/09/08 15:27:32 - mmengine - INFO - Epoch(train) [24][240/1253] lr: 4.0000e-03 eta: 5:29:08 time: 0.5778 data_time: 0.0390 memory: 23504 grad_norm: 2.8220 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1629 loss: 1.1629 2022/09/08 15:27:44 - mmengine - INFO - Epoch(train) [24][260/1253] lr: 4.0000e-03 eta: 5:28:56 time: 0.5865 data_time: 0.0497 memory: 23504 grad_norm: 2.7739 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0530 loss: 1.0530 2022/09/08 15:27:57 - mmengine - INFO - Epoch(train) [24][280/1253] lr: 4.0000e-03 eta: 5:28:47 time: 0.6811 data_time: 0.0394 memory: 23504 grad_norm: 2.8610 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.1267 loss: 1.1267 2022/09/08 15:28:09 - mmengine - INFO - Epoch(train) [24][300/1253] lr: 4.0000e-03 eta: 5:28:35 time: 0.5847 data_time: 0.0695 memory: 23504 grad_norm: 2.8375 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.0651 loss: 1.0651 2022/09/08 15:28:20 - mmengine - INFO - Epoch(train) [24][320/1253] lr: 4.0000e-03 eta: 5:28:22 time: 0.5488 data_time: 0.0327 memory: 23504 grad_norm: 2.8202 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.0850 loss: 1.0850 2022/09/08 15:28:31 - mmengine - INFO - Epoch(train) [24][340/1253] lr: 4.0000e-03 eta: 5:28:10 time: 0.5680 data_time: 0.0328 memory: 23504 grad_norm: 2.8042 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 1.0789 loss: 1.0789 2022/09/08 15:28:43 - mmengine - INFO - Epoch(train) [24][360/1253] lr: 4.0000e-03 eta: 5:27:58 time: 0.5607 data_time: 0.0394 memory: 23504 grad_norm: 2.8196 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.0727 loss: 1.0727 2022/09/08 15:28:55 - mmengine - INFO - Epoch(train) [24][380/1253] lr: 4.0000e-03 eta: 5:27:47 time: 0.6232 data_time: 0.0823 memory: 23504 grad_norm: 2.8969 top1_acc: 0.4583 top5_acc: 0.9583 loss_cls: 1.0282 loss: 1.0282 2022/09/08 15:29:07 - mmengine - INFO - Epoch(train) [24][400/1253] lr: 4.0000e-03 eta: 5:27:35 time: 0.5799 data_time: 0.0281 memory: 23504 grad_norm: 2.8117 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9178 loss: 0.9178 2022/09/08 15:29:18 - mmengine - INFO - Epoch(train) [24][420/1253] lr: 4.0000e-03 eta: 5:27:22 time: 0.5614 data_time: 0.0427 memory: 23504 grad_norm: 2.8468 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.0020 loss: 1.0020 2022/09/08 15:29:29 - mmengine - INFO - Epoch(train) [24][440/1253] lr: 4.0000e-03 eta: 5:27:10 time: 0.5633 data_time: 0.0373 memory: 23504 grad_norm: 2.8217 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.0628 loss: 1.0628 2022/09/08 15:29:41 - mmengine - INFO - Epoch(train) [24][460/1253] lr: 4.0000e-03 eta: 5:26:58 time: 0.5815 data_time: 0.0469 memory: 23504 grad_norm: 2.7586 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.0004 loss: 1.0004 2022/09/08 15:29:52 - mmengine - INFO - Epoch(train) [24][480/1253] lr: 4.0000e-03 eta: 5:26:46 time: 0.5852 data_time: 0.0442 memory: 23504 grad_norm: 2.7480 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0116 loss: 1.0116 2022/09/08 15:30:04 - mmengine - INFO - Epoch(train) [24][500/1253] lr: 4.0000e-03 eta: 5:26:34 time: 0.5641 data_time: 0.0374 memory: 23504 grad_norm: 2.9880 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2392 loss: 1.2392 2022/09/08 15:30:16 - mmengine - INFO - Epoch(train) [24][520/1253] lr: 4.0000e-03 eta: 5:26:22 time: 0.5896 data_time: 0.0489 memory: 23504 grad_norm: 2.8187 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.0131 loss: 1.0131 2022/09/08 15:30:28 - mmengine - INFO - Epoch(train) [24][540/1253] lr: 4.0000e-03 eta: 5:26:11 time: 0.5978 data_time: 0.0939 memory: 23504 grad_norm: 2.7905 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.1385 loss: 1.1385 2022/09/08 15:30:43 - mmengine - INFO - Epoch(train) [24][560/1253] lr: 4.0000e-03 eta: 5:26:03 time: 0.7553 data_time: 0.0388 memory: 23504 grad_norm: 2.8320 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.0318 loss: 1.0318 2022/09/08 15:30:53 - mmengine - INFO - Epoch(train) [24][580/1253] lr: 4.0000e-03 eta: 5:25:50 time: 0.5248 data_time: 0.0354 memory: 23504 grad_norm: 2.8318 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.9980 loss: 0.9980 2022/09/08 15:31:04 - mmengine - INFO - Epoch(train) [24][600/1253] lr: 4.0000e-03 eta: 5:25:37 time: 0.5465 data_time: 0.0371 memory: 23504 grad_norm: 2.8289 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.0978 loss: 1.0978 2022/09/08 15:31:15 - mmengine - INFO - Epoch(train) [24][620/1253] lr: 4.0000e-03 eta: 5:25:25 time: 0.5663 data_time: 0.0488 memory: 23504 grad_norm: 2.7414 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9587 loss: 0.9587 2022/09/08 15:31:27 - mmengine - INFO - Epoch(train) [24][640/1253] lr: 4.0000e-03 eta: 5:25:12 time: 0.5716 data_time: 0.0430 memory: 23504 grad_norm: 2.8642 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.9992 loss: 0.9992 2022/09/08 15:31:38 - mmengine - INFO - Epoch(train) [24][660/1253] lr: 4.0000e-03 eta: 5:25:00 time: 0.5677 data_time: 0.0460 memory: 23504 grad_norm: 2.8617 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0703 loss: 1.0703 2022/09/08 15:31:50 - mmengine - INFO - Epoch(train) [24][680/1253] lr: 4.0000e-03 eta: 5:24:48 time: 0.5822 data_time: 0.0381 memory: 23504 grad_norm: 2.8488 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.0519 loss: 1.0519 2022/09/08 15:32:02 - mmengine - INFO - Epoch(train) [24][700/1253] lr: 4.0000e-03 eta: 5:24:37 time: 0.5838 data_time: 0.0481 memory: 23504 grad_norm: 2.8101 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.0565 loss: 1.0565 2022/09/08 15:32:13 - mmengine - INFO - Epoch(train) [24][720/1253] lr: 4.0000e-03 eta: 5:24:24 time: 0.5730 data_time: 0.0443 memory: 23504 grad_norm: 2.8087 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.1333 loss: 1.1333 2022/09/08 15:32:25 - mmengine - INFO - Epoch(train) [24][740/1253] lr: 4.0000e-03 eta: 5:24:13 time: 0.6026 data_time: 0.0446 memory: 23504 grad_norm: 2.7765 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.9705 loss: 0.9705 2022/09/08 15:32:37 - mmengine - INFO - Epoch(train) [24][760/1253] lr: 4.0000e-03 eta: 5:24:02 time: 0.6018 data_time: 0.0408 memory: 23504 grad_norm: 2.8843 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0944 loss: 1.0944 2022/09/08 15:32:48 - mmengine - INFO - Epoch(train) [24][780/1253] lr: 4.0000e-03 eta: 5:23:49 time: 0.5606 data_time: 0.0587 memory: 23504 grad_norm: 2.8392 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1503 loss: 1.1503 2022/09/08 15:33:00 - mmengine - INFO - Epoch(train) [24][800/1253] lr: 4.0000e-03 eta: 5:23:37 time: 0.5866 data_time: 0.0469 memory: 23504 grad_norm: 2.8331 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.1052 loss: 1.1052 2022/09/08 15:33:12 - mmengine - INFO - Epoch(train) [24][820/1253] lr: 4.0000e-03 eta: 5:23:25 time: 0.5760 data_time: 0.0479 memory: 23504 grad_norm: 2.8253 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1148 loss: 1.1148 2022/09/08 15:33:23 - mmengine - INFO - Epoch(train) [24][840/1253] lr: 4.0000e-03 eta: 5:23:13 time: 0.5637 data_time: 0.0407 memory: 23504 grad_norm: 2.8673 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.2270 loss: 1.2270 2022/09/08 15:33:34 - mmengine - INFO - Epoch(train) [24][860/1253] lr: 4.0000e-03 eta: 5:23:01 time: 0.5591 data_time: 0.0400 memory: 23504 grad_norm: 2.8388 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.0648 loss: 1.0648 2022/09/08 15:33:46 - mmengine - INFO - Epoch(train) [24][880/1253] lr: 4.0000e-03 eta: 5:22:49 time: 0.5830 data_time: 0.0487 memory: 23504 grad_norm: 2.8291 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 1.1611 loss: 1.1611 2022/09/08 15:33:59 - mmengine - INFO - Epoch(train) [24][900/1253] lr: 4.0000e-03 eta: 5:22:38 time: 0.6414 data_time: 0.0499 memory: 23504 grad_norm: 2.8672 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.1091 loss: 1.1091 2022/09/08 15:34:10 - mmengine - INFO - Epoch(train) [24][920/1253] lr: 4.0000e-03 eta: 5:22:26 time: 0.5634 data_time: 0.0538 memory: 23504 grad_norm: 2.8423 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.0492 loss: 1.0492 2022/09/08 15:34:21 - mmengine - INFO - Epoch(train) [24][940/1253] lr: 4.0000e-03 eta: 5:22:14 time: 0.5652 data_time: 0.0454 memory: 23504 grad_norm: 2.8974 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0357 loss: 1.0357 2022/09/08 15:34:33 - mmengine - INFO - Epoch(train) [24][960/1253] lr: 4.0000e-03 eta: 5:22:02 time: 0.6116 data_time: 0.0453 memory: 23504 grad_norm: 2.9088 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.0918 loss: 1.0918 2022/09/08 15:34:46 - mmengine - INFO - Epoch(train) [24][980/1253] lr: 4.0000e-03 eta: 5:21:51 time: 0.6186 data_time: 0.0431 memory: 23504 grad_norm: 2.7681 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 1.0524 loss: 1.0524 2022/09/08 15:34:57 - mmengine - INFO - Epoch(train) [24][1000/1253] lr: 4.0000e-03 eta: 5:21:39 time: 0.5800 data_time: 0.0451 memory: 23504 grad_norm: 2.8737 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0663 loss: 1.0663 2022/09/08 15:35:09 - mmengine - INFO - Epoch(train) [24][1020/1253] lr: 4.0000e-03 eta: 5:21:27 time: 0.5605 data_time: 0.0357 memory: 23504 grad_norm: 2.9019 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 1.1379 loss: 1.1379 2022/09/08 15:35:20 - mmengine - INFO - Epoch(train) [24][1040/1253] lr: 4.0000e-03 eta: 5:21:15 time: 0.5618 data_time: 0.0431 memory: 23504 grad_norm: 2.9380 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9155 loss: 0.9155 2022/09/08 15:35:32 - mmengine - INFO - Epoch(train) [24][1060/1253] lr: 4.0000e-03 eta: 5:21:03 time: 0.5900 data_time: 0.0386 memory: 23504 grad_norm: 2.8184 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.1137 loss: 1.1137 2022/09/08 15:35:43 - mmengine - INFO - Epoch(train) [24][1080/1253] lr: 4.0000e-03 eta: 5:20:51 time: 0.5669 data_time: 0.0501 memory: 23504 grad_norm: 2.8306 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.1263 loss: 1.1263 2022/09/08 15:35:56 - mmengine - INFO - Epoch(train) [24][1100/1253] lr: 4.0000e-03 eta: 5:20:41 time: 0.6705 data_time: 0.0302 memory: 23504 grad_norm: 2.8168 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0773 loss: 1.0773 2022/09/08 15:36:09 - mmengine - INFO - Epoch(train) [24][1120/1253] lr: 4.0000e-03 eta: 5:20:30 time: 0.6149 data_time: 0.0370 memory: 23504 grad_norm: 2.9179 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.2028 loss: 1.2028 2022/09/08 15:36:20 - mmengine - INFO - Epoch(train) [24][1140/1253] lr: 4.0000e-03 eta: 5:20:17 time: 0.5645 data_time: 0.0431 memory: 23504 grad_norm: 2.8785 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.0924 loss: 1.0924 2022/09/08 15:36:32 - mmengine - INFO - Epoch(train) [24][1160/1253] lr: 4.0000e-03 eta: 5:20:06 time: 0.5778 data_time: 0.0417 memory: 23504 grad_norm: 2.8102 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.1186 loss: 1.1186 2022/09/08 15:36:44 - mmengine - INFO - Epoch(train) [24][1180/1253] lr: 4.0000e-03 eta: 5:19:54 time: 0.6050 data_time: 0.0481 memory: 23504 grad_norm: 2.8891 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0699 loss: 1.0699 2022/09/08 15:36:44 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 15:36:55 - mmengine - INFO - Epoch(train) [24][1200/1253] lr: 4.0000e-03 eta: 5:19:42 time: 0.5773 data_time: 0.0356 memory: 23504 grad_norm: 2.8674 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.0582 loss: 1.0582 2022/09/08 15:37:09 - mmengine - INFO - Epoch(train) [24][1220/1253] lr: 4.0000e-03 eta: 5:19:33 time: 0.6892 data_time: 0.0336 memory: 23504 grad_norm: 2.8792 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.2141 loss: 1.2141 2022/09/08 15:37:18 - mmengine - INFO - Epoch(train) [24][1240/1253] lr: 4.0000e-03 eta: 5:19:18 time: 0.4764 data_time: 0.0339 memory: 23504 grad_norm: 2.8706 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.1653 loss: 1.1653 2022/09/08 15:37:24 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 15:37:24 - mmengine - INFO - Epoch(train) [24][1253/1253] lr: 4.0000e-03 eta: 5:19:18 time: 0.4261 data_time: 0.0161 memory: 23504 grad_norm: 2.9566 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.1169 loss: 1.1169 2022/09/08 15:37:46 - mmengine - INFO - Epoch(train) [25][20/1253] lr: 4.0000e-03 eta: 5:19:02 time: 1.1066 data_time: 0.4277 memory: 23504 grad_norm: 2.7986 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9304 loss: 0.9304 2022/09/08 15:38:00 - mmengine - INFO - Epoch(train) [25][40/1253] lr: 4.0000e-03 eta: 5:18:53 time: 0.7006 data_time: 0.0418 memory: 23504 grad_norm: 2.8045 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.1815 loss: 1.1815 2022/09/08 15:38:12 - mmengine - INFO - Epoch(train) [25][60/1253] lr: 4.0000e-03 eta: 5:18:41 time: 0.6072 data_time: 0.0363 memory: 23504 grad_norm: 2.8520 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.1235 loss: 1.1235 2022/09/08 15:38:23 - mmengine - INFO - Epoch(train) [25][80/1253] lr: 4.0000e-03 eta: 5:18:29 time: 0.5464 data_time: 0.0448 memory: 23504 grad_norm: 2.8358 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.0902 loss: 1.0902 2022/09/08 15:38:35 - mmengine - INFO - Epoch(train) [25][100/1253] lr: 4.0000e-03 eta: 5:18:16 time: 0.5647 data_time: 0.0482 memory: 23504 grad_norm: 2.7514 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 0.9444 loss: 0.9444 2022/09/08 15:38:47 - mmengine - INFO - Epoch(train) [25][120/1253] lr: 4.0000e-03 eta: 5:18:06 time: 0.6315 data_time: 0.0450 memory: 23504 grad_norm: 2.9033 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.0230 loss: 1.0230 2022/09/08 15:38:59 - mmengine - INFO - Epoch(train) [25][140/1253] lr: 4.0000e-03 eta: 5:17:53 time: 0.5716 data_time: 0.0365 memory: 23504 grad_norm: 2.8140 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.0786 loss: 1.0786 2022/09/08 15:39:10 - mmengine - INFO - Epoch(train) [25][160/1253] lr: 4.0000e-03 eta: 5:17:41 time: 0.5755 data_time: 0.0388 memory: 23504 grad_norm: 2.8634 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 1.0837 loss: 1.0837 2022/09/08 15:39:22 - mmengine - INFO - Epoch(train) [25][180/1253] lr: 4.0000e-03 eta: 5:17:29 time: 0.5697 data_time: 0.0520 memory: 23504 grad_norm: 2.8058 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 0.9841 loss: 0.9841 2022/09/08 15:39:35 - mmengine - INFO - Epoch(train) [25][200/1253] lr: 4.0000e-03 eta: 5:17:19 time: 0.6740 data_time: 0.0315 memory: 23504 grad_norm: 2.7928 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.1608 loss: 1.1608 2022/09/08 15:39:47 - mmengine - INFO - Epoch(train) [25][220/1253] lr: 4.0000e-03 eta: 5:17:08 time: 0.5894 data_time: 0.0313 memory: 23504 grad_norm: 2.7373 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0870 loss: 1.0870 2022/09/08 15:39:59 - mmengine - INFO - Epoch(train) [25][240/1253] lr: 4.0000e-03 eta: 5:16:57 time: 0.6313 data_time: 0.0431 memory: 23504 grad_norm: 2.8663 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.1220 loss: 1.1220 2022/09/08 15:40:11 - mmengine - INFO - Epoch(train) [25][260/1253] lr: 4.0000e-03 eta: 5:16:44 time: 0.5580 data_time: 0.0493 memory: 23504 grad_norm: 2.8015 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0316 loss: 1.0316 2022/09/08 15:40:21 - mmengine - INFO - Epoch(train) [25][280/1253] lr: 4.0000e-03 eta: 5:16:32 time: 0.5448 data_time: 0.0427 memory: 23504 grad_norm: 2.8588 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1662 loss: 1.1662 2022/09/08 15:40:34 - mmengine - INFO - Epoch(train) [25][300/1253] lr: 4.0000e-03 eta: 5:16:21 time: 0.6271 data_time: 0.0533 memory: 23504 grad_norm: 2.7699 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0444 loss: 1.0444 2022/09/08 15:40:46 - mmengine - INFO - Epoch(train) [25][320/1253] lr: 4.0000e-03 eta: 5:16:09 time: 0.5889 data_time: 0.0748 memory: 23504 grad_norm: 2.7976 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0777 loss: 1.0777 2022/09/08 15:40:57 - mmengine - INFO - Epoch(train) [25][340/1253] lr: 4.0000e-03 eta: 5:15:57 time: 0.5550 data_time: 0.0408 memory: 23504 grad_norm: 2.8416 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.0851 loss: 1.0851 2022/09/08 15:41:08 - mmengine - INFO - Epoch(train) [25][360/1253] lr: 4.0000e-03 eta: 5:15:45 time: 0.5755 data_time: 0.0535 memory: 23504 grad_norm: 2.8945 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.0512 loss: 1.0512 2022/09/08 15:41:20 - mmengine - INFO - Epoch(train) [25][380/1253] lr: 4.0000e-03 eta: 5:15:33 time: 0.5819 data_time: 0.0448 memory: 23504 grad_norm: 2.8811 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9848 loss: 0.9848 2022/09/08 15:41:31 - mmengine - INFO - Epoch(train) [25][400/1253] lr: 4.0000e-03 eta: 5:15:20 time: 0.5662 data_time: 0.0420 memory: 23504 grad_norm: 2.9079 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0728 loss: 1.0728 2022/09/08 15:41:43 - mmengine - INFO - Epoch(train) [25][420/1253] lr: 4.0000e-03 eta: 5:15:08 time: 0.5662 data_time: 0.0420 memory: 23504 grad_norm: 2.8109 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.1801 loss: 1.1801 2022/09/08 15:41:54 - mmengine - INFO - Epoch(train) [25][440/1253] lr: 4.0000e-03 eta: 5:14:56 time: 0.5658 data_time: 0.0420 memory: 23504 grad_norm: 2.8914 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0042 loss: 1.0042 2022/09/08 15:42:07 - mmengine - INFO - Epoch(train) [25][460/1253] lr: 4.0000e-03 eta: 5:14:45 time: 0.6363 data_time: 0.0367 memory: 23504 grad_norm: 2.8122 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0072 loss: 1.0072 2022/09/08 15:42:19 - mmengine - INFO - Epoch(train) [25][480/1253] lr: 4.0000e-03 eta: 5:14:34 time: 0.6216 data_time: 0.0360 memory: 23504 grad_norm: 2.8847 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.0420 loss: 1.0420 2022/09/08 15:42:31 - mmengine - INFO - Epoch(train) [25][500/1253] lr: 4.0000e-03 eta: 5:14:22 time: 0.5699 data_time: 0.0434 memory: 23504 grad_norm: 2.8625 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9892 loss: 0.9892 2022/09/08 15:42:42 - mmengine - INFO - Epoch(train) [25][520/1253] lr: 4.0000e-03 eta: 5:14:10 time: 0.5582 data_time: 0.0527 memory: 23504 grad_norm: 2.8492 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 1.0088 loss: 1.0088 2022/09/08 15:42:53 - mmengine - INFO - Epoch(train) [25][540/1253] lr: 4.0000e-03 eta: 5:13:58 time: 0.5706 data_time: 0.0350 memory: 23504 grad_norm: 2.8946 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.1213 loss: 1.1213 2022/09/08 15:43:06 - mmengine - INFO - Epoch(train) [25][560/1253] lr: 4.0000e-03 eta: 5:13:47 time: 0.6469 data_time: 0.0377 memory: 23504 grad_norm: 2.8713 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0686 loss: 1.0686 2022/09/08 15:43:18 - mmengine - INFO - Epoch(train) [25][580/1253] lr: 4.0000e-03 eta: 5:13:35 time: 0.5714 data_time: 0.0369 memory: 23504 grad_norm: 2.8213 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0870 loss: 1.0870 2022/09/08 15:43:29 - mmengine - INFO - Epoch(train) [25][600/1253] lr: 4.0000e-03 eta: 5:13:23 time: 0.5697 data_time: 0.0464 memory: 23504 grad_norm: 2.8413 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9593 loss: 0.9593 2022/09/08 15:43:42 - mmengine - INFO - Epoch(train) [25][620/1253] lr: 4.0000e-03 eta: 5:13:12 time: 0.6529 data_time: 0.0370 memory: 23504 grad_norm: 2.8742 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.1083 loss: 1.1083 2022/09/08 15:43:53 - mmengine - INFO - Epoch(train) [25][640/1253] lr: 4.0000e-03 eta: 5:13:00 time: 0.5495 data_time: 0.0452 memory: 23504 grad_norm: 2.8305 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.0357 loss: 1.0357 2022/09/08 15:44:04 - mmengine - INFO - Epoch(train) [25][660/1253] lr: 4.0000e-03 eta: 5:12:48 time: 0.5719 data_time: 0.0390 memory: 23504 grad_norm: 2.8036 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 1.0888 loss: 1.0888 2022/09/08 15:44:17 - mmengine - INFO - Epoch(train) [25][680/1253] lr: 4.0000e-03 eta: 5:12:36 time: 0.6156 data_time: 0.0417 memory: 23504 grad_norm: 2.8639 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.1119 loss: 1.1119 2022/09/08 15:44:28 - mmengine - INFO - Epoch(train) [25][700/1253] lr: 4.0000e-03 eta: 5:12:25 time: 0.5811 data_time: 0.0393 memory: 23504 grad_norm: 2.8634 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0063 loss: 1.0063 2022/09/08 15:44:40 - mmengine - INFO - Epoch(train) [25][720/1253] lr: 4.0000e-03 eta: 5:12:12 time: 0.5602 data_time: 0.0398 memory: 23504 grad_norm: 2.8351 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 1.0748 loss: 1.0748 2022/09/08 15:44:51 - mmengine - INFO - Epoch(train) [25][740/1253] lr: 4.0000e-03 eta: 5:12:00 time: 0.5650 data_time: 0.0466 memory: 23504 grad_norm: 2.8116 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.0225 loss: 1.0225 2022/09/08 15:45:02 - mmengine - INFO - Epoch(train) [25][760/1253] lr: 4.0000e-03 eta: 5:11:48 time: 0.5736 data_time: 0.0436 memory: 23504 grad_norm: 2.9687 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.1132 loss: 1.1132 2022/09/08 15:45:14 - mmengine - INFO - Epoch(train) [25][780/1253] lr: 4.0000e-03 eta: 5:11:36 time: 0.5745 data_time: 0.0431 memory: 23504 grad_norm: 2.8064 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.1130 loss: 1.1130 2022/09/08 15:45:25 - mmengine - INFO - Epoch(train) [25][800/1253] lr: 4.0000e-03 eta: 5:11:24 time: 0.5781 data_time: 0.0466 memory: 23504 grad_norm: 2.8828 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0542 loss: 1.0542 2022/09/08 15:45:37 - mmengine - INFO - Epoch(train) [25][820/1253] lr: 4.0000e-03 eta: 5:11:12 time: 0.5559 data_time: 0.0494 memory: 23504 grad_norm: 2.8400 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.0826 loss: 1.0826 2022/09/08 15:45:48 - mmengine - INFO - Epoch(train) [25][840/1253] lr: 4.0000e-03 eta: 5:10:59 time: 0.5543 data_time: 0.0453 memory: 23504 grad_norm: 2.8022 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.0295 loss: 1.0295 2022/09/08 15:46:01 - mmengine - INFO - Epoch(train) [25][860/1253] lr: 4.0000e-03 eta: 5:10:49 time: 0.6676 data_time: 0.0369 memory: 23504 grad_norm: 2.9212 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.0811 loss: 1.0811 2022/09/08 15:46:13 - mmengine - INFO - Epoch(train) [25][880/1253] lr: 4.0000e-03 eta: 5:10:38 time: 0.6045 data_time: 0.0336 memory: 23504 grad_norm: 2.8415 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8508 loss: 0.8508 2022/09/08 15:46:24 - mmengine - INFO - Epoch(train) [25][900/1253] lr: 4.0000e-03 eta: 5:10:25 time: 0.5560 data_time: 0.0401 memory: 23504 grad_norm: 2.9001 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.1604 loss: 1.1604 2022/09/08 15:46:35 - mmengine - INFO - Epoch(train) [25][920/1253] lr: 4.0000e-03 eta: 5:10:13 time: 0.5598 data_time: 0.0376 memory: 23504 grad_norm: 2.8684 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 0.9694 loss: 0.9694 2022/09/08 15:46:41 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 15:46:47 - mmengine - INFO - Epoch(train) [25][940/1253] lr: 4.0000e-03 eta: 5:10:01 time: 0.5941 data_time: 0.0847 memory: 23504 grad_norm: 2.8634 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8802 loss: 0.8802 2022/09/08 15:46:59 - mmengine - INFO - Epoch(train) [25][960/1253] lr: 4.0000e-03 eta: 5:09:49 time: 0.5845 data_time: 0.0404 memory: 23504 grad_norm: 2.8414 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0417 loss: 1.0417 2022/09/08 15:47:11 - mmengine - INFO - Epoch(train) [25][980/1253] lr: 4.0000e-03 eta: 5:09:38 time: 0.5922 data_time: 0.0533 memory: 23504 grad_norm: 2.8864 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9666 loss: 0.9666 2022/09/08 15:47:22 - mmengine - INFO - Epoch(train) [25][1000/1253] lr: 4.0000e-03 eta: 5:09:26 time: 0.5693 data_time: 0.0379 memory: 23504 grad_norm: 2.8924 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.9317 loss: 0.9317 2022/09/08 15:47:34 - mmengine - INFO - Epoch(train) [25][1020/1253] lr: 4.0000e-03 eta: 5:09:14 time: 0.5847 data_time: 0.0457 memory: 23504 grad_norm: 2.8446 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.0346 loss: 1.0346 2022/09/08 15:47:48 - mmengine - INFO - Epoch(train) [25][1040/1253] lr: 4.0000e-03 eta: 5:09:04 time: 0.6816 data_time: 0.0294 memory: 23504 grad_norm: 2.8155 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.1312 loss: 1.1312 2022/09/08 15:47:59 - mmengine - INFO - Epoch(train) [25][1060/1253] lr: 4.0000e-03 eta: 5:08:51 time: 0.5581 data_time: 0.0390 memory: 23504 grad_norm: 2.9577 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.0594 loss: 1.0594 2022/09/08 15:48:10 - mmengine - INFO - Epoch(train) [25][1080/1253] lr: 4.0000e-03 eta: 5:08:39 time: 0.5699 data_time: 0.0395 memory: 23504 grad_norm: 2.8856 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.1290 loss: 1.1290 2022/09/08 15:48:22 - mmengine - INFO - Epoch(train) [25][1100/1253] lr: 4.0000e-03 eta: 5:08:27 time: 0.5678 data_time: 0.0424 memory: 23504 grad_norm: 2.8154 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 1.0866 loss: 1.0866 2022/09/08 15:48:33 - mmengine - INFO - Epoch(train) [25][1120/1253] lr: 4.0000e-03 eta: 5:08:15 time: 0.5795 data_time: 0.0622 memory: 23504 grad_norm: 2.8422 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1203 loss: 1.1203 2022/09/08 15:48:45 - mmengine - INFO - Epoch(train) [25][1140/1253] lr: 4.0000e-03 eta: 5:08:03 time: 0.5814 data_time: 0.0446 memory: 23504 grad_norm: 2.9192 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.1338 loss: 1.1338 2022/09/08 15:48:56 - mmengine - INFO - Epoch(train) [25][1160/1253] lr: 4.0000e-03 eta: 5:07:51 time: 0.5710 data_time: 0.0363 memory: 23504 grad_norm: 2.8532 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.0178 loss: 1.0178 2022/09/08 15:49:08 - mmengine - INFO - Epoch(train) [25][1180/1253] lr: 4.0000e-03 eta: 5:07:39 time: 0.5779 data_time: 0.0558 memory: 23504 grad_norm: 2.9525 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.0467 loss: 1.0467 2022/09/08 15:49:19 - mmengine - INFO - Epoch(train) [25][1200/1253] lr: 4.0000e-03 eta: 5:07:27 time: 0.5651 data_time: 0.0400 memory: 23504 grad_norm: 2.8423 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.0831 loss: 1.0831 2022/09/08 15:49:30 - mmengine - INFO - Epoch(train) [25][1220/1253] lr: 4.0000e-03 eta: 5:07:15 time: 0.5551 data_time: 0.0380 memory: 23504 grad_norm: 2.9225 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 1.1189 loss: 1.1189 2022/09/08 15:49:41 - mmengine - INFO - Epoch(train) [25][1240/1253] lr: 4.0000e-03 eta: 5:07:02 time: 0.5196 data_time: 0.0479 memory: 23504 grad_norm: 2.9247 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.1186 loss: 1.1186 2022/09/08 15:49:47 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 15:49:47 - mmengine - INFO - Epoch(train) [25][1253/1253] lr: 4.0000e-03 eta: 5:07:02 time: 0.4692 data_time: 0.0428 memory: 23504 grad_norm: 3.0043 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.2121 loss: 1.2121 2022/09/08 15:50:11 - mmengine - INFO - Epoch(val) [25][20/104] eta: 0:01:42 time: 1.2261 data_time: 1.0762 memory: 2699 2022/09/08 15:50:28 - mmengine - INFO - Epoch(val) [25][40/104] eta: 0:00:53 time: 0.8328 data_time: 0.6899 memory: 2699 2022/09/08 15:50:37 - mmengine - INFO - Epoch(val) [25][60/104] eta: 0:00:19 time: 0.4324 data_time: 0.2844 memory: 2699 2022/09/08 15:50:45 - mmengine - INFO - Epoch(val) [25][80/104] eta: 0:00:09 time: 0.4162 data_time: 0.2784 memory: 2699 2022/09/08 15:50:50 - mmengine - INFO - Epoch(val) [25][100/104] eta: 0:00:00 time: 0.2444 data_time: 0.1266 memory: 2699 2022/09/08 15:50:56 - mmengine - INFO - Epoch(val) [25][104/104] acc/top1: 0.7076 acc/top5: 0.8979 acc/mean1: 0.7075 2022/09/08 15:50:56 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb/best_acc/top1_epoch_20.pth is removed 2022/09/08 15:50:57 - mmengine - INFO - The best checkpoint with 0.7076 acc/top1 at 25 epoch is saved to best_acc/top1_epoch_25.pth. 2022/09/08 15:51:19 - mmengine - INFO - Epoch(train) [26][20/1253] lr: 4.0000e-03 eta: 5:06:44 time: 1.0864 data_time: 0.5539 memory: 23504 grad_norm: 2.8829 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.0558 loss: 1.0558 2022/09/08 15:51:34 - mmengine - INFO - Epoch(train) [26][40/1253] lr: 4.0000e-03 eta: 5:06:36 time: 0.7541 data_time: 0.0366 memory: 23504 grad_norm: 2.8589 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 1.0582 loss: 1.0582 2022/09/08 15:51:45 - mmengine - INFO - Epoch(train) [26][60/1253] lr: 4.0000e-03 eta: 5:06:23 time: 0.5406 data_time: 0.0348 memory: 23504 grad_norm: 2.8414 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 0.9146 loss: 0.9146 2022/09/08 15:51:56 - mmengine - INFO - Epoch(train) [26][80/1253] lr: 4.0000e-03 eta: 5:06:11 time: 0.5587 data_time: 0.0392 memory: 23504 grad_norm: 2.8280 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9809 loss: 0.9809 2022/09/08 15:52:08 - mmengine - INFO - Epoch(train) [26][100/1253] lr: 4.0000e-03 eta: 5:05:59 time: 0.5969 data_time: 0.0514 memory: 23504 grad_norm: 2.8133 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9999 loss: 0.9999 2022/09/08 15:52:20 - mmengine - INFO - Epoch(train) [26][120/1253] lr: 4.0000e-03 eta: 5:05:48 time: 0.6008 data_time: 0.0297 memory: 23504 grad_norm: 2.9074 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.0606 loss: 1.0606 2022/09/08 15:52:32 - mmengine - INFO - Epoch(train) [26][140/1253] lr: 4.0000e-03 eta: 5:05:36 time: 0.6041 data_time: 0.0416 memory: 23504 grad_norm: 2.8764 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0327 loss: 1.0327 2022/09/08 15:52:43 - mmengine - INFO - Epoch(train) [26][160/1253] lr: 4.0000e-03 eta: 5:05:24 time: 0.5520 data_time: 0.0375 memory: 23504 grad_norm: 2.8599 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0223 loss: 1.0223 2022/09/08 15:52:55 - mmengine - INFO - Epoch(train) [26][180/1253] lr: 4.0000e-03 eta: 5:05:12 time: 0.5777 data_time: 0.0508 memory: 23504 grad_norm: 2.8545 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.0309 loss: 1.0309 2022/09/08 15:53:06 - mmengine - INFO - Epoch(train) [26][200/1253] lr: 4.0000e-03 eta: 5:05:00 time: 0.5861 data_time: 0.0810 memory: 23504 grad_norm: 2.8807 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.9281 loss: 0.9281 2022/09/08 15:53:18 - mmengine - INFO - Epoch(train) [26][220/1253] lr: 4.0000e-03 eta: 5:04:48 time: 0.5650 data_time: 0.0439 memory: 23504 grad_norm: 2.8611 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.0635 loss: 1.0635 2022/09/08 15:53:29 - mmengine - INFO - Epoch(train) [26][240/1253] lr: 4.0000e-03 eta: 5:04:36 time: 0.5834 data_time: 0.0420 memory: 23504 grad_norm: 2.8425 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0917 loss: 1.0917 2022/09/08 15:53:41 - mmengine - INFO - Epoch(train) [26][260/1253] lr: 4.0000e-03 eta: 5:04:24 time: 0.5771 data_time: 0.0488 memory: 23504 grad_norm: 2.8822 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.0381 loss: 1.0381 2022/09/08 15:53:54 - mmengine - INFO - Epoch(train) [26][280/1253] lr: 4.0000e-03 eta: 5:04:14 time: 0.6545 data_time: 0.0393 memory: 23504 grad_norm: 2.8920 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0563 loss: 1.0563 2022/09/08 15:54:06 - mmengine - INFO - Epoch(train) [26][300/1253] lr: 4.0000e-03 eta: 5:04:02 time: 0.5950 data_time: 0.0284 memory: 23504 grad_norm: 2.9178 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.0874 loss: 1.0874 2022/09/08 15:54:17 - mmengine - INFO - Epoch(train) [26][320/1253] lr: 4.0000e-03 eta: 5:03:50 time: 0.5755 data_time: 0.0574 memory: 23504 grad_norm: 2.8988 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.0952 loss: 1.0952 2022/09/08 15:54:29 - mmengine - INFO - Epoch(train) [26][340/1253] lr: 4.0000e-03 eta: 5:03:38 time: 0.5919 data_time: 0.0534 memory: 23504 grad_norm: 2.9400 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 1.0284 loss: 1.0284 2022/09/08 15:54:40 - mmengine - INFO - Epoch(train) [26][360/1253] lr: 4.0000e-03 eta: 5:03:26 time: 0.5623 data_time: 0.0388 memory: 23504 grad_norm: 2.8952 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 0.8875 loss: 0.8875 2022/09/08 15:54:52 - mmengine - INFO - Epoch(train) [26][380/1253] lr: 4.0000e-03 eta: 5:03:14 time: 0.5760 data_time: 0.0458 memory: 23504 grad_norm: 2.8039 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.1045 loss: 1.1045 2022/09/08 15:55:04 - mmengine - INFO - Epoch(train) [26][400/1253] lr: 4.0000e-03 eta: 5:03:02 time: 0.5888 data_time: 0.0420 memory: 23504 grad_norm: 2.9892 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.0766 loss: 1.0766 2022/09/08 15:55:17 - mmengine - INFO - Epoch(train) [26][420/1253] lr: 4.0000e-03 eta: 5:02:52 time: 0.6752 data_time: 0.0391 memory: 23504 grad_norm: 2.8451 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 0.9294 loss: 0.9294 2022/09/08 15:55:28 - mmengine - INFO - Epoch(train) [26][440/1253] lr: 4.0000e-03 eta: 5:02:40 time: 0.5490 data_time: 0.0363 memory: 23504 grad_norm: 2.8851 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.0365 loss: 1.0365 2022/09/08 15:55:41 - mmengine - INFO - Epoch(train) [26][460/1253] lr: 4.0000e-03 eta: 5:02:29 time: 0.6149 data_time: 0.0803 memory: 23504 grad_norm: 2.8748 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 0.8946 loss: 0.8946 2022/09/08 15:55:52 - mmengine - INFO - Epoch(train) [26][480/1253] lr: 4.0000e-03 eta: 5:02:16 time: 0.5518 data_time: 0.0386 memory: 23504 grad_norm: 2.7961 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.9335 loss: 0.9335 2022/09/08 15:56:05 - mmengine - INFO - Epoch(train) [26][500/1253] lr: 4.0000e-03 eta: 5:02:06 time: 0.6819 data_time: 0.0448 memory: 23504 grad_norm: 2.9582 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8958 loss: 0.8958 2022/09/08 15:56:16 - mmengine - INFO - Epoch(train) [26][520/1253] lr: 4.0000e-03 eta: 5:01:54 time: 0.5422 data_time: 0.0357 memory: 23504 grad_norm: 2.8225 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0086 loss: 1.0086 2022/09/08 15:56:27 - mmengine - INFO - Epoch(train) [26][540/1253] lr: 4.0000e-03 eta: 5:01:41 time: 0.5610 data_time: 0.0409 memory: 23504 grad_norm: 2.9702 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.2272 loss: 1.2272 2022/09/08 15:56:38 - mmengine - INFO - Epoch(train) [26][560/1253] lr: 4.0000e-03 eta: 5:01:29 time: 0.5480 data_time: 0.0503 memory: 23504 grad_norm: 2.8923 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.0248 loss: 1.0248 2022/09/08 15:56:49 - mmengine - INFO - Epoch(train) [26][580/1253] lr: 4.0000e-03 eta: 5:01:16 time: 0.5375 data_time: 0.0464 memory: 23504 grad_norm: 2.9156 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 1.0369 loss: 1.0369 2022/09/08 15:57:01 - mmengine - INFO - Epoch(train) [26][600/1253] lr: 4.0000e-03 eta: 5:01:05 time: 0.6213 data_time: 0.0430 memory: 23504 grad_norm: 2.9237 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0108 loss: 1.0108 2022/09/08 15:57:13 - mmengine - INFO - Epoch(train) [26][620/1253] lr: 4.0000e-03 eta: 5:00:53 time: 0.5650 data_time: 0.0451 memory: 23504 grad_norm: 2.8795 top1_acc: 0.9583 top5_acc: 1.0000 loss_cls: 1.0792 loss: 1.0792 2022/09/08 15:57:25 - mmengine - INFO - Epoch(train) [26][640/1253] lr: 4.0000e-03 eta: 5:00:41 time: 0.6037 data_time: 0.0391 memory: 23504 grad_norm: 2.8899 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 0.9097 loss: 0.9097 2022/09/08 15:57:38 - mmengine - INFO - Epoch(train) [26][660/1253] lr: 4.0000e-03 eta: 5:00:30 time: 0.6359 data_time: 0.0351 memory: 23504 grad_norm: 2.9029 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.0802 loss: 1.0802 2022/09/08 15:57:46 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 15:57:50 - mmengine - INFO - Epoch(train) [26][680/1253] lr: 4.0000e-03 eta: 5:00:19 time: 0.6004 data_time: 0.0420 memory: 23504 grad_norm: 2.9046 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0559 loss: 1.0559 2022/09/08 15:58:01 - mmengine - INFO - Epoch(train) [26][700/1253] lr: 4.0000e-03 eta: 5:00:07 time: 0.5889 data_time: 0.0462 memory: 23504 grad_norm: 2.9928 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9338 loss: 0.9338 2022/09/08 15:58:13 - mmengine - INFO - Epoch(train) [26][720/1253] lr: 4.0000e-03 eta: 4:59:55 time: 0.5707 data_time: 0.0344 memory: 23504 grad_norm: 2.9550 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9338 loss: 0.9338 2022/09/08 15:58:24 - mmengine - INFO - Epoch(train) [26][740/1253] lr: 4.0000e-03 eta: 4:59:43 time: 0.5785 data_time: 0.0387 memory: 23504 grad_norm: 2.8900 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 1.0194 loss: 1.0194 2022/09/08 15:58:36 - mmengine - INFO - Epoch(train) [26][760/1253] lr: 4.0000e-03 eta: 4:59:31 time: 0.5665 data_time: 0.0490 memory: 23504 grad_norm: 2.9313 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0824 loss: 1.0824 2022/09/08 15:58:47 - mmengine - INFO - Epoch(train) [26][780/1253] lr: 4.0000e-03 eta: 4:59:19 time: 0.5857 data_time: 0.0410 memory: 23504 grad_norm: 2.8852 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.1171 loss: 1.1171 2022/09/08 15:58:59 - mmengine - INFO - Epoch(train) [26][800/1253] lr: 4.0000e-03 eta: 4:59:07 time: 0.5739 data_time: 0.0422 memory: 23504 grad_norm: 2.9013 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.9930 loss: 0.9930 2022/09/08 15:59:10 - mmengine - INFO - Epoch(train) [26][820/1253] lr: 4.0000e-03 eta: 4:58:55 time: 0.5668 data_time: 0.0365 memory: 23504 grad_norm: 2.9581 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.0823 loss: 1.0823 2022/09/08 15:59:22 - mmengine - INFO - Epoch(train) [26][840/1253] lr: 4.0000e-03 eta: 4:58:43 time: 0.5747 data_time: 0.0396 memory: 23504 grad_norm: 2.9771 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.0331 loss: 1.0331 2022/09/08 15:59:34 - mmengine - INFO - Epoch(train) [26][860/1253] lr: 4.0000e-03 eta: 4:58:32 time: 0.6137 data_time: 0.0459 memory: 23504 grad_norm: 2.9378 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.1289 loss: 1.1289 2022/09/08 15:59:46 - mmengine - INFO - Epoch(train) [26][880/1253] lr: 4.0000e-03 eta: 4:58:20 time: 0.6200 data_time: 0.0522 memory: 23504 grad_norm: 2.8489 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.0341 loss: 1.0341 2022/09/08 15:59:58 - mmengine - INFO - Epoch(train) [26][900/1253] lr: 4.0000e-03 eta: 4:58:09 time: 0.5983 data_time: 0.0485 memory: 23504 grad_norm: 2.9723 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9891 loss: 0.9891 2022/09/08 16:00:10 - mmengine - INFO - Epoch(train) [26][920/1253] lr: 4.0000e-03 eta: 4:57:57 time: 0.5725 data_time: 0.0397 memory: 23504 grad_norm: 2.8379 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 0.9867 loss: 0.9867 2022/09/08 16:00:21 - mmengine - INFO - Epoch(train) [26][940/1253] lr: 4.0000e-03 eta: 4:57:45 time: 0.5571 data_time: 0.0413 memory: 23504 grad_norm: 2.8552 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.9070 loss: 0.9070 2022/09/08 16:00:33 - mmengine - INFO - Epoch(train) [26][960/1253] lr: 4.0000e-03 eta: 4:57:33 time: 0.5888 data_time: 0.0527 memory: 23504 grad_norm: 2.8395 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.0014 loss: 1.0014 2022/09/08 16:00:43 - mmengine - INFO - Epoch(train) [26][980/1253] lr: 4.0000e-03 eta: 4:57:20 time: 0.5329 data_time: 0.0363 memory: 23504 grad_norm: 2.9640 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.1252 loss: 1.1252 2022/09/08 16:00:55 - mmengine - INFO - Epoch(train) [26][1000/1253] lr: 4.0000e-03 eta: 4:57:08 time: 0.5652 data_time: 0.0456 memory: 23504 grad_norm: 2.8751 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0643 loss: 1.0643 2022/09/08 16:01:08 - mmengine - INFO - Epoch(train) [26][1020/1253] lr: 4.0000e-03 eta: 4:56:58 time: 0.6706 data_time: 0.0524 memory: 23504 grad_norm: 2.8536 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.0522 loss: 1.0522 2022/09/08 16:01:22 - mmengine - INFO - Epoch(train) [26][1040/1253] lr: 4.0000e-03 eta: 4:56:47 time: 0.6713 data_time: 0.0328 memory: 23504 grad_norm: 2.9336 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.0901 loss: 1.0901 2022/09/08 16:01:33 - mmengine - INFO - Epoch(train) [26][1060/1253] lr: 4.0000e-03 eta: 4:56:35 time: 0.5716 data_time: 0.0531 memory: 23504 grad_norm: 2.8952 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.0021 loss: 1.0021 2022/09/08 16:01:44 - mmengine - INFO - Epoch(train) [26][1080/1253] lr: 4.0000e-03 eta: 4:56:23 time: 0.5389 data_time: 0.0431 memory: 23504 grad_norm: 2.8620 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0006 loss: 1.0006 2022/09/08 16:01:55 - mmengine - INFO - Epoch(train) [26][1100/1253] lr: 4.0000e-03 eta: 4:56:10 time: 0.5525 data_time: 0.0457 memory: 23504 grad_norm: 2.8841 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0064 loss: 1.0064 2022/09/08 16:02:06 - mmengine - INFO - Epoch(train) [26][1120/1253] lr: 4.0000e-03 eta: 4:55:58 time: 0.5623 data_time: 0.0418 memory: 23504 grad_norm: 2.9745 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.1384 loss: 1.1384 2022/09/08 16:02:18 - mmengine - INFO - Epoch(train) [26][1140/1253] lr: 4.0000e-03 eta: 4:55:46 time: 0.5796 data_time: 0.0511 memory: 23504 grad_norm: 2.8566 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.0247 loss: 1.0247 2022/09/08 16:02:29 - mmengine - INFO - Epoch(train) [26][1160/1253] lr: 4.0000e-03 eta: 4:55:34 time: 0.5711 data_time: 0.0419 memory: 23504 grad_norm: 2.9358 top1_acc: 0.6667 top5_acc: 0.7500 loss_cls: 0.9737 loss: 0.9737 2022/09/08 16:02:44 - mmengine - INFO - Epoch(train) [26][1180/1253] lr: 4.0000e-03 eta: 4:55:25 time: 0.7450 data_time: 0.0403 memory: 23504 grad_norm: 2.8953 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0359 loss: 1.0359 2022/09/08 16:02:56 - mmengine - INFO - Epoch(train) [26][1200/1253] lr: 4.0000e-03 eta: 4:55:13 time: 0.5895 data_time: 0.0327 memory: 23504 grad_norm: 2.9138 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.1569 loss: 1.1569 2022/09/08 16:03:07 - mmengine - INFO - Epoch(train) [26][1220/1253] lr: 4.0000e-03 eta: 4:55:01 time: 0.5458 data_time: 0.0375 memory: 23504 grad_norm: 2.9351 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.9155 loss: 0.9155 2022/09/08 16:03:16 - mmengine - INFO - Epoch(train) [26][1240/1253] lr: 4.0000e-03 eta: 4:54:47 time: 0.4838 data_time: 0.0352 memory: 23504 grad_norm: 2.9346 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8984 loss: 0.8984 2022/09/08 16:03:22 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 16:03:22 - mmengine - INFO - Epoch(train) [26][1253/1253] lr: 4.0000e-03 eta: 4:54:47 time: 0.4274 data_time: 0.0167 memory: 23504 grad_norm: 3.0320 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 0.9584 loss: 0.9584 2022/09/08 16:03:44 - mmengine - INFO - Epoch(train) [27][20/1253] lr: 4.0000e-03 eta: 4:54:30 time: 1.0969 data_time: 0.5583 memory: 23504 grad_norm: 2.8753 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.0605 loss: 1.0605 2022/09/08 16:03:56 - mmengine - INFO - Epoch(train) [27][40/1253] lr: 4.0000e-03 eta: 4:54:18 time: 0.5892 data_time: 0.0424 memory: 23504 grad_norm: 2.8207 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.9625 loss: 0.9625 2022/09/08 16:04:09 - mmengine - INFO - Epoch(train) [27][60/1253] lr: 4.0000e-03 eta: 4:54:08 time: 0.6611 data_time: 0.0391 memory: 23504 grad_norm: 2.9195 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9869 loss: 0.9869 2022/09/08 16:04:21 - mmengine - INFO - Epoch(train) [27][80/1253] lr: 4.0000e-03 eta: 4:53:56 time: 0.5998 data_time: 0.0377 memory: 23504 grad_norm: 2.9704 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.0116 loss: 1.0116 2022/09/08 16:04:34 - mmengine - INFO - Epoch(train) [27][100/1253] lr: 4.0000e-03 eta: 4:53:46 time: 0.6460 data_time: 0.0509 memory: 23504 grad_norm: 2.8422 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0198 loss: 1.0198 2022/09/08 16:04:45 - mmengine - INFO - Epoch(train) [27][120/1253] lr: 4.0000e-03 eta: 4:53:33 time: 0.5522 data_time: 0.0292 memory: 23504 grad_norm: 2.8388 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8872 loss: 0.8872 2022/09/08 16:04:57 - mmengine - INFO - Epoch(train) [27][140/1253] lr: 4.0000e-03 eta: 4:53:21 time: 0.5806 data_time: 0.0504 memory: 23504 grad_norm: 2.9194 top1_acc: 0.7083 top5_acc: 0.7500 loss_cls: 0.9252 loss: 0.9252 2022/09/08 16:05:11 - mmengine - INFO - Epoch(train) [27][160/1253] lr: 4.0000e-03 eta: 4:53:12 time: 0.7392 data_time: 0.0330 memory: 23504 grad_norm: 2.8308 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9521 loss: 0.9521 2022/09/08 16:05:25 - mmengine - INFO - Epoch(train) [27][180/1253] lr: 4.0000e-03 eta: 4:53:02 time: 0.6592 data_time: 0.0371 memory: 23504 grad_norm: 2.8643 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.0645 loss: 1.0645 2022/09/08 16:05:36 - mmengine - INFO - Epoch(train) [27][200/1253] lr: 4.0000e-03 eta: 4:52:49 time: 0.5453 data_time: 0.0533 memory: 23504 grad_norm: 2.8990 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.1167 loss: 1.1167 2022/09/08 16:05:47 - mmengine - INFO - Epoch(train) [27][220/1253] lr: 4.0000e-03 eta: 4:52:37 time: 0.5547 data_time: 0.0450 memory: 23504 grad_norm: 2.8943 top1_acc: 0.5833 top5_acc: 1.0000 loss_cls: 1.0990 loss: 1.0990 2022/09/08 16:05:58 - mmengine - INFO - Epoch(train) [27][240/1253] lr: 4.0000e-03 eta: 4:52:25 time: 0.5848 data_time: 0.0544 memory: 23504 grad_norm: 3.0086 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0330 loss: 1.0330 2022/09/08 16:06:10 - mmengine - INFO - Epoch(train) [27][260/1253] lr: 4.0000e-03 eta: 4:52:13 time: 0.5740 data_time: 0.0390 memory: 23504 grad_norm: 2.8687 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9315 loss: 0.9315 2022/09/08 16:06:22 - mmengine - INFO - Epoch(train) [27][280/1253] lr: 4.0000e-03 eta: 4:52:02 time: 0.5921 data_time: 0.0376 memory: 23504 grad_norm: 2.9297 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.0589 loss: 1.0589 2022/09/08 16:06:34 - mmengine - INFO - Epoch(train) [27][300/1253] lr: 4.0000e-03 eta: 4:51:50 time: 0.6034 data_time: 0.0472 memory: 23504 grad_norm: 2.8707 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9578 loss: 0.9578 2022/09/08 16:06:46 - mmengine - INFO - Epoch(train) [27][320/1253] lr: 4.0000e-03 eta: 4:51:38 time: 0.5920 data_time: 0.0262 memory: 23504 grad_norm: 2.8688 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9178 loss: 0.9178 2022/09/08 16:06:57 - mmengine - INFO - Epoch(train) [27][340/1253] lr: 4.0000e-03 eta: 4:51:26 time: 0.5803 data_time: 0.0432 memory: 23504 grad_norm: 2.9088 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0211 loss: 1.0211 2022/09/08 16:07:09 - mmengine - INFO - Epoch(train) [27][360/1253] lr: 4.0000e-03 eta: 4:51:15 time: 0.6064 data_time: 0.0348 memory: 23504 grad_norm: 2.8625 top1_acc: 0.9167 top5_acc: 0.9167 loss_cls: 0.9772 loss: 0.9772 2022/09/08 16:07:21 - mmengine - INFO - Epoch(train) [27][380/1253] lr: 4.0000e-03 eta: 4:51:03 time: 0.5858 data_time: 0.0568 memory: 23504 grad_norm: 2.9691 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1214 loss: 1.1214 2022/09/08 16:07:33 - mmengine - INFO - Epoch(train) [27][400/1253] lr: 4.0000e-03 eta: 4:50:51 time: 0.5747 data_time: 0.0424 memory: 23504 grad_norm: 2.9633 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9744 loss: 0.9744 2022/09/08 16:07:44 - mmengine - INFO - Epoch(train) [27][420/1253] lr: 4.0000e-03 eta: 4:50:39 time: 0.5621 data_time: 0.0395 memory: 23504 grad_norm: 2.9497 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 0.9829 loss: 0.9829 2022/09/08 16:07:45 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 16:07:55 - mmengine - INFO - Epoch(train) [27][440/1253] lr: 4.0000e-03 eta: 4:50:27 time: 0.5615 data_time: 0.0490 memory: 23504 grad_norm: 2.9424 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.8930 loss: 0.8930 2022/09/08 16:08:07 - mmengine - INFO - Epoch(train) [27][460/1253] lr: 4.0000e-03 eta: 4:50:15 time: 0.5806 data_time: 0.0472 memory: 23504 grad_norm: 2.9210 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.0817 loss: 1.0817 2022/09/08 16:08:22 - mmengine - INFO - Epoch(train) [27][480/1253] lr: 4.0000e-03 eta: 4:50:06 time: 0.7722 data_time: 0.0395 memory: 23504 grad_norm: 2.9659 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.0078 loss: 1.0078 2022/09/08 16:08:33 - mmengine - INFO - Epoch(train) [27][500/1253] lr: 4.0000e-03 eta: 4:49:54 time: 0.5291 data_time: 0.0427 memory: 23504 grad_norm: 2.9417 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.0508 loss: 1.0508 2022/09/08 16:08:44 - mmengine - INFO - Epoch(train) [27][520/1253] lr: 4.0000e-03 eta: 4:49:41 time: 0.5402 data_time: 0.0322 memory: 23504 grad_norm: 2.9847 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 0.9361 loss: 0.9361 2022/09/08 16:08:55 - mmengine - INFO - Epoch(train) [27][540/1253] lr: 4.0000e-03 eta: 4:49:29 time: 0.5769 data_time: 0.0481 memory: 23504 grad_norm: 2.9495 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.0160 loss: 1.0160 2022/09/08 16:09:07 - mmengine - INFO - Epoch(train) [27][560/1253] lr: 4.0000e-03 eta: 4:49:17 time: 0.5887 data_time: 0.0436 memory: 23504 grad_norm: 2.8707 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0516 loss: 1.0516 2022/09/08 16:09:19 - mmengine - INFO - Epoch(train) [27][580/1253] lr: 4.0000e-03 eta: 4:49:06 time: 0.6126 data_time: 0.0464 memory: 23504 grad_norm: 2.9232 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.0764 loss: 1.0764 2022/09/08 16:09:33 - mmengine - INFO - Epoch(train) [27][600/1253] lr: 4.0000e-03 eta: 4:48:56 time: 0.6955 data_time: 0.0349 memory: 23504 grad_norm: 2.9052 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9724 loss: 0.9724 2022/09/08 16:09:46 - mmengine - INFO - Epoch(train) [27][620/1253] lr: 4.0000e-03 eta: 4:48:46 time: 0.6748 data_time: 0.0408 memory: 23504 grad_norm: 2.9691 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.0050 loss: 1.0050 2022/09/08 16:09:57 - mmengine - INFO - Epoch(train) [27][640/1253] lr: 4.0000e-03 eta: 4:48:33 time: 0.5265 data_time: 0.0385 memory: 23504 grad_norm: 2.9331 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.9457 loss: 0.9457 2022/09/08 16:10:08 - mmengine - INFO - Epoch(train) [27][660/1253] lr: 4.0000e-03 eta: 4:48:21 time: 0.5589 data_time: 0.0385 memory: 23504 grad_norm: 2.9723 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.9540 loss: 0.9540 2022/09/08 16:10:19 - mmengine - INFO - Epoch(train) [27][680/1253] lr: 4.0000e-03 eta: 4:48:08 time: 0.5508 data_time: 0.0350 memory: 23504 grad_norm: 2.9010 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.0188 loss: 1.0188 2022/09/08 16:10:31 - mmengine - INFO - Epoch(train) [27][700/1253] lr: 4.0000e-03 eta: 4:47:57 time: 0.6096 data_time: 0.0478 memory: 23504 grad_norm: 2.9185 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.0277 loss: 1.0277 2022/09/08 16:10:43 - mmengine - INFO - Epoch(train) [27][720/1253] lr: 4.0000e-03 eta: 4:47:44 time: 0.5548 data_time: 0.0387 memory: 23504 grad_norm: 2.8799 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.2163 loss: 1.2163 2022/09/08 16:10:54 - mmengine - INFO - Epoch(train) [27][740/1253] lr: 4.0000e-03 eta: 4:47:32 time: 0.5707 data_time: 0.0403 memory: 23504 grad_norm: 3.0005 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 0.9395 loss: 0.9395 2022/09/08 16:11:07 - mmengine - INFO - Epoch(train) [27][760/1253] lr: 4.0000e-03 eta: 4:47:22 time: 0.6576 data_time: 0.0392 memory: 23504 grad_norm: 2.9381 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.0596 loss: 1.0596 2022/09/08 16:11:19 - mmengine - INFO - Epoch(train) [27][780/1253] lr: 4.0000e-03 eta: 4:47:10 time: 0.5802 data_time: 0.0345 memory: 23504 grad_norm: 2.9359 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.0086 loss: 1.0086 2022/09/08 16:11:30 - mmengine - INFO - Epoch(train) [27][800/1253] lr: 4.0000e-03 eta: 4:46:58 time: 0.5683 data_time: 0.0385 memory: 23504 grad_norm: 2.9938 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.0720 loss: 1.0720 2022/09/08 16:11:42 - mmengine - INFO - Epoch(train) [27][820/1253] lr: 4.0000e-03 eta: 4:46:46 time: 0.5884 data_time: 0.0473 memory: 23504 grad_norm: 2.9590 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0620 loss: 1.0620 2022/09/08 16:11:53 - mmengine - INFO - Epoch(train) [27][840/1253] lr: 4.0000e-03 eta: 4:46:34 time: 0.5546 data_time: 0.0489 memory: 23504 grad_norm: 2.9527 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 1.0690 loss: 1.0690 2022/09/08 16:12:04 - mmengine - INFO - Epoch(train) [27][860/1253] lr: 4.0000e-03 eta: 4:46:22 time: 0.5638 data_time: 0.0433 memory: 23504 grad_norm: 2.9493 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 0.8843 loss: 0.8843 2022/09/08 16:12:16 - mmengine - INFO - Epoch(train) [27][880/1253] lr: 4.0000e-03 eta: 4:46:10 time: 0.5808 data_time: 0.0398 memory: 23504 grad_norm: 2.9999 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.9306 loss: 0.9306 2022/09/08 16:12:27 - mmengine - INFO - Epoch(train) [27][900/1253] lr: 4.0000e-03 eta: 4:45:58 time: 0.5756 data_time: 0.0365 memory: 23504 grad_norm: 2.9400 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.0244 loss: 1.0244 2022/09/08 16:12:42 - mmengine - INFO - Epoch(train) [27][920/1253] lr: 4.0000e-03 eta: 4:45:49 time: 0.7398 data_time: 0.0435 memory: 23504 grad_norm: 2.9309 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.0776 loss: 1.0776 2022/09/08 16:12:53 - mmengine - INFO - Epoch(train) [27][940/1253] lr: 4.0000e-03 eta: 4:45:36 time: 0.5357 data_time: 0.0361 memory: 23504 grad_norm: 2.9966 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1329 loss: 1.1329 2022/09/08 16:13:04 - mmengine - INFO - Epoch(train) [27][960/1253] lr: 4.0000e-03 eta: 4:45:23 time: 0.5545 data_time: 0.0325 memory: 23504 grad_norm: 3.0660 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9646 loss: 0.9646 2022/09/08 16:13:16 - mmengine - INFO - Epoch(train) [27][980/1253] lr: 4.0000e-03 eta: 4:45:12 time: 0.5802 data_time: 0.0441 memory: 23504 grad_norm: 2.9960 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.8679 loss: 0.8679 2022/09/08 16:13:28 - mmengine - INFO - Epoch(train) [27][1000/1253] lr: 4.0000e-03 eta: 4:45:00 time: 0.6072 data_time: 0.0481 memory: 23504 grad_norm: 3.0327 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0953 loss: 1.0953 2022/09/08 16:13:40 - mmengine - INFO - Epoch(train) [27][1020/1253] lr: 4.0000e-03 eta: 4:44:49 time: 0.6194 data_time: 0.0797 memory: 23504 grad_norm: 2.9272 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.0702 loss: 1.0702 2022/09/08 16:13:52 - mmengine - INFO - Epoch(train) [27][1040/1253] lr: 4.0000e-03 eta: 4:44:38 time: 0.6101 data_time: 0.0407 memory: 23504 grad_norm: 3.0222 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9461 loss: 0.9461 2022/09/08 16:14:04 - mmengine - INFO - Epoch(train) [27][1060/1253] lr: 4.0000e-03 eta: 4:44:25 time: 0.5710 data_time: 0.0304 memory: 23504 grad_norm: 2.9845 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.0339 loss: 1.0339 2022/09/08 16:14:15 - mmengine - INFO - Epoch(train) [27][1080/1253] lr: 4.0000e-03 eta: 4:44:13 time: 0.5498 data_time: 0.0370 memory: 23504 grad_norm: 2.9894 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0954 loss: 1.0954 2022/09/08 16:14:26 - mmengine - INFO - Epoch(train) [27][1100/1253] lr: 4.0000e-03 eta: 4:44:01 time: 0.5760 data_time: 0.0485 memory: 23504 grad_norm: 2.8704 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8859 loss: 0.8859 2022/09/08 16:14:38 - mmengine - INFO - Epoch(train) [27][1120/1253] lr: 4.0000e-03 eta: 4:43:49 time: 0.5931 data_time: 0.0307 memory: 23504 grad_norm: 2.9100 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.9455 loss: 0.9455 2022/09/08 16:14:52 - mmengine - INFO - Epoch(train) [27][1140/1253] lr: 4.0000e-03 eta: 4:43:39 time: 0.6881 data_time: 0.0346 memory: 23504 grad_norm: 2.9124 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 1.0244 loss: 1.0244 2022/09/08 16:15:03 - mmengine - INFO - Epoch(train) [27][1160/1253] lr: 4.0000e-03 eta: 4:43:27 time: 0.5387 data_time: 0.0384 memory: 23504 grad_norm: 3.0015 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9631 loss: 0.9631 2022/09/08 16:15:14 - mmengine - INFO - Epoch(train) [27][1180/1253] lr: 4.0000e-03 eta: 4:43:14 time: 0.5562 data_time: 0.0357 memory: 23504 grad_norm: 2.9664 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9872 loss: 0.9872 2022/09/08 16:15:25 - mmengine - INFO - Epoch(train) [27][1200/1253] lr: 4.0000e-03 eta: 4:43:02 time: 0.5714 data_time: 0.0542 memory: 23504 grad_norm: 2.9573 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 0.9962 loss: 0.9962 2022/09/08 16:15:37 - mmengine - INFO - Epoch(train) [27][1220/1253] lr: 4.0000e-03 eta: 4:42:50 time: 0.5643 data_time: 0.0497 memory: 23504 grad_norm: 2.9609 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.0107 loss: 1.0107 2022/09/08 16:15:46 - mmengine - INFO - Epoch(train) [27][1240/1253] lr: 4.0000e-03 eta: 4:42:37 time: 0.4974 data_time: 0.0335 memory: 23504 grad_norm: 3.0241 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.0998 loss: 1.0998 2022/09/08 16:15:52 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 16:15:52 - mmengine - INFO - Epoch(train) [27][1253/1253] lr: 4.0000e-03 eta: 4:42:37 time: 0.4383 data_time: 0.0174 memory: 23504 grad_norm: 3.1156 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.0870 loss: 1.0870 2022/09/08 16:16:15 - mmengine - INFO - Epoch(train) [28][20/1253] lr: 4.0000e-03 eta: 4:42:20 time: 1.1432 data_time: 0.4229 memory: 23504 grad_norm: 2.8550 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.9754 loss: 0.9754 2022/09/08 16:16:31 - mmengine - INFO - Epoch(train) [28][40/1253] lr: 4.0000e-03 eta: 4:42:12 time: 0.7741 data_time: 0.0372 memory: 23504 grad_norm: 2.9216 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9502 loss: 0.9502 2022/09/08 16:16:41 - mmengine - INFO - Epoch(train) [28][60/1253] lr: 4.0000e-03 eta: 4:41:59 time: 0.5373 data_time: 0.0339 memory: 23504 grad_norm: 2.9170 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.0914 loss: 1.0914 2022/09/08 16:16:55 - mmengine - INFO - Epoch(train) [28][80/1253] lr: 4.0000e-03 eta: 4:41:49 time: 0.6909 data_time: 0.0293 memory: 23504 grad_norm: 2.9364 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0792 loss: 1.0792 2022/09/08 16:17:07 - mmengine - INFO - Epoch(train) [28][100/1253] lr: 4.0000e-03 eta: 4:41:37 time: 0.5779 data_time: 0.0399 memory: 23504 grad_norm: 3.0036 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.8282 loss: 0.8282 2022/09/08 16:17:18 - mmengine - INFO - Epoch(train) [28][120/1253] lr: 4.0000e-03 eta: 4:41:25 time: 0.5463 data_time: 0.0431 memory: 23504 grad_norm: 2.9554 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9534 loss: 0.9534 2022/09/08 16:17:29 - mmengine - INFO - Epoch(train) [28][140/1253] lr: 4.0000e-03 eta: 4:41:12 time: 0.5590 data_time: 0.0473 memory: 23504 grad_norm: 2.9529 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.0616 loss: 1.0616 2022/09/08 16:17:42 - mmengine - INFO - Epoch(train) [28][160/1253] lr: 4.0000e-03 eta: 4:41:02 time: 0.6508 data_time: 0.0382 memory: 23504 grad_norm: 2.8959 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9407 loss: 0.9407 2022/09/08 16:17:48 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 16:17:54 - mmengine - INFO - Epoch(train) [28][180/1253] lr: 4.0000e-03 eta: 4:40:51 time: 0.6261 data_time: 0.0388 memory: 23504 grad_norm: 2.9210 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.9760 loss: 0.9760 2022/09/08 16:18:06 - mmengine - INFO - Epoch(train) [28][200/1253] lr: 4.0000e-03 eta: 4:40:39 time: 0.5922 data_time: 0.0394 memory: 23504 grad_norm: 2.8935 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.8869 loss: 0.8869 2022/09/08 16:18:17 - mmengine - INFO - Epoch(train) [28][220/1253] lr: 4.0000e-03 eta: 4:40:26 time: 0.5488 data_time: 0.0431 memory: 23504 grad_norm: 2.9733 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9893 loss: 0.9893 2022/09/08 16:18:29 - mmengine - INFO - Epoch(train) [28][240/1253] lr: 4.0000e-03 eta: 4:40:14 time: 0.5686 data_time: 0.0407 memory: 23504 grad_norm: 2.9047 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 0.9617 loss: 0.9617 2022/09/08 16:18:41 - mmengine - INFO - Epoch(train) [28][260/1253] lr: 4.0000e-03 eta: 4:40:03 time: 0.6135 data_time: 0.0343 memory: 23504 grad_norm: 2.9009 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.9337 loss: 0.9337 2022/09/08 16:18:53 - mmengine - INFO - Epoch(train) [28][280/1253] lr: 4.0000e-03 eta: 4:39:52 time: 0.6147 data_time: 0.0439 memory: 23504 grad_norm: 2.9302 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9242 loss: 0.9242 2022/09/08 16:19:04 - mmengine - INFO - Epoch(train) [28][300/1253] lr: 4.0000e-03 eta: 4:39:40 time: 0.5639 data_time: 0.0457 memory: 23504 grad_norm: 2.9351 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 0.9633 loss: 0.9633 2022/09/08 16:19:16 - mmengine - INFO - Epoch(train) [28][320/1253] lr: 4.0000e-03 eta: 4:39:28 time: 0.5872 data_time: 0.0350 memory: 23504 grad_norm: 3.0135 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.1059 loss: 1.1059 2022/09/08 16:19:28 - mmengine - INFO - Epoch(train) [28][340/1253] lr: 4.0000e-03 eta: 4:39:16 time: 0.5783 data_time: 0.0421 memory: 23504 grad_norm: 2.9912 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.0167 loss: 1.0167 2022/09/08 16:19:40 - mmengine - INFO - Epoch(train) [28][360/1253] lr: 4.0000e-03 eta: 4:39:04 time: 0.5989 data_time: 0.0611 memory: 23504 grad_norm: 2.9477 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.1306 loss: 1.1306 2022/09/08 16:19:51 - mmengine - INFO - Epoch(train) [28][380/1253] lr: 4.0000e-03 eta: 4:38:52 time: 0.5750 data_time: 0.0467 memory: 23504 grad_norm: 2.8836 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.0683 loss: 1.0683 2022/09/08 16:20:03 - mmengine - INFO - Epoch(train) [28][400/1253] lr: 4.0000e-03 eta: 4:38:41 time: 0.5950 data_time: 0.0701 memory: 23504 grad_norm: 2.9788 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.0534 loss: 1.0534 2022/09/08 16:20:14 - mmengine - INFO - Epoch(train) [28][420/1253] lr: 4.0000e-03 eta: 4:38:28 time: 0.5576 data_time: 0.0469 memory: 23504 grad_norm: 2.9808 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9902 loss: 0.9902 2022/09/08 16:20:25 - mmengine - INFO - Epoch(train) [28][440/1253] lr: 4.0000e-03 eta: 4:38:16 time: 0.5444 data_time: 0.0411 memory: 23504 grad_norm: 3.0061 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.0667 loss: 1.0667 2022/09/08 16:20:37 - mmengine - INFO - Epoch(train) [28][460/1253] lr: 4.0000e-03 eta: 4:38:04 time: 0.5787 data_time: 0.0648 memory: 23504 grad_norm: 2.8759 top1_acc: 0.7083 top5_acc: 1.0000 loss_cls: 1.0292 loss: 1.0292 2022/09/08 16:20:50 - mmengine - INFO - Epoch(train) [28][480/1253] lr: 4.0000e-03 eta: 4:37:53 time: 0.6516 data_time: 0.0375 memory: 23504 grad_norm: 2.9532 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.0002 loss: 1.0002 2022/09/08 16:21:03 - mmengine - INFO - Epoch(train) [28][500/1253] lr: 4.0000e-03 eta: 4:37:43 time: 0.6688 data_time: 0.0382 memory: 23504 grad_norm: 2.9168 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.0233 loss: 1.0233 2022/09/08 16:21:14 - mmengine - INFO - Epoch(train) [28][520/1253] lr: 4.0000e-03 eta: 4:37:30 time: 0.5522 data_time: 0.0319 memory: 23504 grad_norm: 2.9949 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9744 loss: 0.9744 2022/09/08 16:21:25 - mmengine - INFO - Epoch(train) [28][540/1253] lr: 4.0000e-03 eta: 4:37:18 time: 0.5377 data_time: 0.0296 memory: 23504 grad_norm: 2.9827 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 1.0873 loss: 1.0873 2022/09/08 16:21:36 - mmengine - INFO - Epoch(train) [28][560/1253] lr: 4.0000e-03 eta: 4:37:05 time: 0.5539 data_time: 0.0437 memory: 23504 grad_norm: 2.9890 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9403 loss: 0.9403 2022/09/08 16:21:48 - mmengine - INFO - Epoch(train) [28][580/1253] lr: 4.0000e-03 eta: 4:36:54 time: 0.6054 data_time: 0.0433 memory: 23504 grad_norm: 2.9814 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9925 loss: 0.9925 2022/09/08 16:22:00 - mmengine - INFO - Epoch(train) [28][600/1253] lr: 4.0000e-03 eta: 4:36:42 time: 0.5720 data_time: 0.0360 memory: 23504 grad_norm: 2.9829 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9742 loss: 0.9742 2022/09/08 16:22:12 - mmengine - INFO - Epoch(train) [28][620/1253] lr: 4.0000e-03 eta: 4:36:30 time: 0.6011 data_time: 0.0405 memory: 23504 grad_norm: 2.9996 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9748 loss: 0.9748 2022/09/08 16:22:23 - mmengine - INFO - Epoch(train) [28][640/1253] lr: 4.0000e-03 eta: 4:36:18 time: 0.5712 data_time: 0.0450 memory: 23504 grad_norm: 2.9851 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8732 loss: 0.8732 2022/09/08 16:22:36 - mmengine - INFO - Epoch(train) [28][660/1253] lr: 4.0000e-03 eta: 4:36:07 time: 0.6219 data_time: 0.0451 memory: 23504 grad_norm: 2.9788 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.8819 loss: 0.8819 2022/09/08 16:22:48 - mmengine - INFO - Epoch(train) [28][680/1253] lr: 4.0000e-03 eta: 4:35:56 time: 0.6314 data_time: 0.0505 memory: 23504 grad_norm: 2.9188 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.9920 loss: 0.9920 2022/09/08 16:22:59 - mmengine - INFO - Epoch(train) [28][700/1253] lr: 4.0000e-03 eta: 4:35:44 time: 0.5521 data_time: 0.0289 memory: 23504 grad_norm: 2.9537 top1_acc: 0.7083 top5_acc: 1.0000 loss_cls: 1.0428 loss: 1.0428 2022/09/08 16:23:11 - mmengine - INFO - Epoch(train) [28][720/1253] lr: 4.0000e-03 eta: 4:35:32 time: 0.5812 data_time: 0.0489 memory: 23504 grad_norm: 2.9680 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.0993 loss: 1.0993 2022/09/08 16:23:23 - mmengine - INFO - Epoch(train) [28][740/1253] lr: 4.0000e-03 eta: 4:35:20 time: 0.5840 data_time: 0.0363 memory: 23504 grad_norm: 3.0319 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9913 loss: 0.9913 2022/09/08 16:23:34 - mmengine - INFO - Epoch(train) [28][760/1253] lr: 4.0000e-03 eta: 4:35:08 time: 0.5805 data_time: 0.0468 memory: 23504 grad_norm: 2.9573 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9135 loss: 0.9135 2022/09/08 16:23:45 - mmengine - INFO - Epoch(train) [28][780/1253] lr: 4.0000e-03 eta: 4:34:56 time: 0.5600 data_time: 0.0410 memory: 23504 grad_norm: 2.9610 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8528 loss: 0.8528 2022/09/08 16:23:58 - mmengine - INFO - Epoch(train) [28][800/1253] lr: 4.0000e-03 eta: 4:34:44 time: 0.6124 data_time: 0.0539 memory: 23504 grad_norm: 3.0181 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.9389 loss: 0.9389 2022/09/08 16:24:09 - mmengine - INFO - Epoch(train) [28][820/1253] lr: 4.0000e-03 eta: 4:34:32 time: 0.5683 data_time: 0.0332 memory: 23504 grad_norm: 3.0719 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.0308 loss: 1.0308 2022/09/08 16:24:21 - mmengine - INFO - Epoch(train) [28][840/1253] lr: 4.0000e-03 eta: 4:34:21 time: 0.6226 data_time: 0.0823 memory: 23504 grad_norm: 3.0018 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0268 loss: 1.0268 2022/09/08 16:24:32 - mmengine - INFO - Epoch(train) [28][860/1253] lr: 4.0000e-03 eta: 4:34:09 time: 0.5406 data_time: 0.0379 memory: 23504 grad_norm: 2.9177 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9956 loss: 0.9956 2022/09/08 16:24:44 - mmengine - INFO - Epoch(train) [28][880/1253] lr: 4.0000e-03 eta: 4:33:57 time: 0.5750 data_time: 0.0467 memory: 23504 grad_norm: 2.8795 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9465 loss: 0.9465 2022/09/08 16:24:55 - mmengine - INFO - Epoch(train) [28][900/1253] lr: 4.0000e-03 eta: 4:33:45 time: 0.5742 data_time: 0.0333 memory: 23504 grad_norm: 2.9597 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 1.0194 loss: 1.0194 2022/09/08 16:25:10 - mmengine - INFO - Epoch(train) [28][920/1253] lr: 4.0000e-03 eta: 4:33:35 time: 0.7116 data_time: 0.0457 memory: 23504 grad_norm: 2.9712 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.9564 loss: 0.9564 2022/09/08 16:25:20 - mmengine - INFO - Epoch(train) [28][940/1253] lr: 4.0000e-03 eta: 4:33:22 time: 0.5391 data_time: 0.0261 memory: 23504 grad_norm: 2.8986 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 0.9635 loss: 0.9635 2022/09/08 16:25:32 - mmengine - INFO - Epoch(train) [28][960/1253] lr: 4.0000e-03 eta: 4:33:10 time: 0.5609 data_time: 0.0339 memory: 23504 grad_norm: 2.9808 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9739 loss: 0.9739 2022/09/08 16:25:43 - mmengine - INFO - Epoch(train) [28][980/1253] lr: 4.0000e-03 eta: 4:32:58 time: 0.5545 data_time: 0.0394 memory: 23504 grad_norm: 2.9314 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 1.0366 loss: 1.0366 2022/09/08 16:25:58 - mmengine - INFO - Epoch(train) [28][1000/1253] lr: 4.0000e-03 eta: 4:32:48 time: 0.7452 data_time: 0.0400 memory: 23504 grad_norm: 3.0211 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.9496 loss: 0.9496 2022/09/08 16:26:09 - mmengine - INFO - Epoch(train) [28][1020/1253] lr: 4.0000e-03 eta: 4:32:36 time: 0.5740 data_time: 0.0371 memory: 23504 grad_norm: 3.0060 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.0325 loss: 1.0325 2022/09/08 16:26:20 - mmengine - INFO - Epoch(train) [28][1040/1253] lr: 4.0000e-03 eta: 4:32:24 time: 0.5694 data_time: 0.0331 memory: 23504 grad_norm: 2.9931 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9545 loss: 0.9545 2022/09/08 16:26:32 - mmengine - INFO - Epoch(train) [28][1060/1253] lr: 4.0000e-03 eta: 4:32:12 time: 0.5732 data_time: 0.0355 memory: 23504 grad_norm: 3.0570 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1576 loss: 1.1576 2022/09/08 16:26:44 - mmengine - INFO - Epoch(train) [28][1080/1253] lr: 4.0000e-03 eta: 4:32:01 time: 0.6095 data_time: 0.0860 memory: 23504 grad_norm: 3.0809 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.0126 loss: 1.0126 2022/09/08 16:26:57 - mmengine - INFO - Epoch(train) [28][1100/1253] lr: 4.0000e-03 eta: 4:31:50 time: 0.6305 data_time: 0.0415 memory: 23504 grad_norm: 2.9284 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.0478 loss: 1.0478 2022/09/08 16:27:09 - mmengine - INFO - Epoch(train) [28][1120/1253] lr: 4.0000e-03 eta: 4:31:39 time: 0.6169 data_time: 0.0358 memory: 23504 grad_norm: 3.0088 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0465 loss: 1.0465 2022/09/08 16:27:20 - mmengine - INFO - Epoch(train) [28][1140/1253] lr: 4.0000e-03 eta: 4:31:26 time: 0.5488 data_time: 0.0338 memory: 23504 grad_norm: 3.0004 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.9742 loss: 0.9742 2022/09/08 16:27:32 - mmengine - INFO - Epoch(train) [28][1160/1253] lr: 4.0000e-03 eta: 4:31:14 time: 0.5810 data_time: 0.0436 memory: 23504 grad_norm: 2.9160 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0538 loss: 1.0538 2022/09/08 16:27:37 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 16:27:44 - mmengine - INFO - Epoch(train) [28][1180/1253] lr: 4.0000e-03 eta: 4:31:03 time: 0.5982 data_time: 0.0720 memory: 23504 grad_norm: 2.9926 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0302 loss: 1.0302 2022/09/08 16:27:55 - mmengine - INFO - Epoch(train) [28][1200/1253] lr: 4.0000e-03 eta: 4:30:51 time: 0.5805 data_time: 0.0360 memory: 23504 grad_norm: 2.8981 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0891 loss: 1.0891 2022/09/08 16:28:07 - mmengine - INFO - Epoch(train) [28][1220/1253] lr: 4.0000e-03 eta: 4:30:39 time: 0.5769 data_time: 0.0493 memory: 23504 grad_norm: 2.9104 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0068 loss: 1.0068 2022/09/08 16:28:17 - mmengine - INFO - Epoch(train) [28][1240/1253] lr: 4.0000e-03 eta: 4:30:26 time: 0.4985 data_time: 0.0275 memory: 23504 grad_norm: 2.9312 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 0.9827 loss: 0.9827 2022/09/08 16:28:22 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 16:28:22 - mmengine - INFO - Epoch(train) [28][1253/1253] lr: 4.0000e-03 eta: 4:30:26 time: 0.4359 data_time: 0.0150 memory: 23504 grad_norm: 3.1260 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2074 loss: 1.2074 2022/09/08 16:28:48 - mmengine - INFO - Epoch(train) [29][20/1253] lr: 4.0000e-03 eta: 4:30:11 time: 1.3021 data_time: 0.4236 memory: 23504 grad_norm: 2.8721 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.9268 loss: 0.9268 2022/09/08 16:29:00 - mmengine - INFO - Epoch(train) [29][40/1253] lr: 4.0000e-03 eta: 4:30:00 time: 0.5857 data_time: 0.0316 memory: 23504 grad_norm: 2.9937 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8591 loss: 0.8591 2022/09/08 16:29:11 - mmengine - INFO - Epoch(train) [29][60/1253] lr: 4.0000e-03 eta: 4:29:47 time: 0.5474 data_time: 0.0418 memory: 23504 grad_norm: 2.9109 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0554 loss: 1.0554 2022/09/08 16:29:22 - mmengine - INFO - Epoch(train) [29][80/1253] lr: 4.0000e-03 eta: 4:29:35 time: 0.5655 data_time: 0.0460 memory: 23504 grad_norm: 2.9808 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.0220 loss: 1.0220 2022/09/08 16:29:39 - mmengine - INFO - Epoch(train) [29][100/1253] lr: 4.0000e-03 eta: 4:29:27 time: 0.8036 data_time: 0.0327 memory: 23504 grad_norm: 2.9591 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9176 loss: 0.9176 2022/09/08 16:29:49 - mmengine - INFO - Epoch(train) [29][120/1253] lr: 4.0000e-03 eta: 4:29:14 time: 0.5279 data_time: 0.0358 memory: 23504 grad_norm: 3.0061 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.0118 loss: 1.0118 2022/09/08 16:30:00 - mmengine - INFO - Epoch(train) [29][140/1253] lr: 4.0000e-03 eta: 4:29:01 time: 0.5443 data_time: 0.0389 memory: 23504 grad_norm: 2.9306 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.9203 loss: 0.9203 2022/09/08 16:30:12 - mmengine - INFO - Epoch(train) [29][160/1253] lr: 4.0000e-03 eta: 4:28:50 time: 0.6194 data_time: 0.0379 memory: 23504 grad_norm: 3.0118 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8925 loss: 0.8925 2022/09/08 16:30:24 - mmengine - INFO - Epoch(train) [29][180/1253] lr: 4.0000e-03 eta: 4:28:38 time: 0.5624 data_time: 0.0415 memory: 23504 grad_norm: 2.9142 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.9552 loss: 0.9552 2022/09/08 16:30:35 - mmengine - INFO - Epoch(train) [29][200/1253] lr: 4.0000e-03 eta: 4:28:26 time: 0.5543 data_time: 0.0483 memory: 23504 grad_norm: 2.9527 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.0102 loss: 1.0102 2022/09/08 16:30:46 - mmengine - INFO - Epoch(train) [29][220/1253] lr: 4.0000e-03 eta: 4:28:13 time: 0.5574 data_time: 0.0501 memory: 23504 grad_norm: 2.9420 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.0125 loss: 1.0125 2022/09/08 16:30:57 - mmengine - INFO - Epoch(train) [29][240/1253] lr: 4.0000e-03 eta: 4:28:01 time: 0.5597 data_time: 0.0388 memory: 23504 grad_norm: 2.9649 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9402 loss: 0.9402 2022/09/08 16:31:09 - mmengine - INFO - Epoch(train) [29][260/1253] lr: 4.0000e-03 eta: 4:27:50 time: 0.5986 data_time: 0.0411 memory: 23504 grad_norm: 2.9733 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 1.0150 loss: 1.0150 2022/09/08 16:31:22 - mmengine - INFO - Epoch(train) [29][280/1253] lr: 4.0000e-03 eta: 4:27:38 time: 0.6238 data_time: 0.0401 memory: 23504 grad_norm: 2.9708 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.0848 loss: 1.0848 2022/09/08 16:31:33 - mmengine - INFO - Epoch(train) [29][300/1253] lr: 4.0000e-03 eta: 4:27:26 time: 0.5644 data_time: 0.0448 memory: 23504 grad_norm: 2.9547 top1_acc: 0.7917 top5_acc: 0.7917 loss_cls: 0.9380 loss: 0.9380 2022/09/08 16:31:45 - mmengine - INFO - Epoch(train) [29][320/1253] lr: 4.0000e-03 eta: 4:27:14 time: 0.5866 data_time: 0.0406 memory: 23504 grad_norm: 3.0276 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.0286 loss: 1.0286 2022/09/08 16:31:58 - mmengine - INFO - Epoch(train) [29][340/1253] lr: 4.0000e-03 eta: 4:27:04 time: 0.6871 data_time: 0.0377 memory: 23504 grad_norm: 2.8380 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9233 loss: 0.9233 2022/09/08 16:32:10 - mmengine - INFO - Epoch(train) [29][360/1253] lr: 4.0000e-03 eta: 4:26:52 time: 0.5610 data_time: 0.0360 memory: 23504 grad_norm: 2.8991 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9157 loss: 0.9157 2022/09/08 16:32:21 - mmengine - INFO - Epoch(train) [29][380/1253] lr: 4.0000e-03 eta: 4:26:40 time: 0.5599 data_time: 0.0384 memory: 23504 grad_norm: 2.9551 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0351 loss: 1.0351 2022/09/08 16:32:32 - mmengine - INFO - Epoch(train) [29][400/1253] lr: 4.0000e-03 eta: 4:26:27 time: 0.5438 data_time: 0.0485 memory: 23504 grad_norm: 3.0387 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 1.0178 loss: 1.0178 2022/09/08 16:32:43 - mmengine - INFO - Epoch(train) [29][420/1253] lr: 4.0000e-03 eta: 4:26:15 time: 0.5640 data_time: 0.0439 memory: 23504 grad_norm: 2.9515 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9849 loss: 0.9849 2022/09/08 16:32:54 - mmengine - INFO - Epoch(train) [29][440/1253] lr: 4.0000e-03 eta: 4:26:03 time: 0.5775 data_time: 0.0418 memory: 23504 grad_norm: 2.9778 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 0.9598 loss: 0.9598 2022/09/08 16:33:07 - mmengine - INFO - Epoch(train) [29][460/1253] lr: 4.0000e-03 eta: 4:25:52 time: 0.6067 data_time: 0.0441 memory: 23504 grad_norm: 3.0360 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.1020 loss: 1.1020 2022/09/08 16:33:19 - mmengine - INFO - Epoch(train) [29][480/1253] lr: 4.0000e-03 eta: 4:25:40 time: 0.6025 data_time: 0.0594 memory: 23504 grad_norm: 2.9898 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0969 loss: 1.0969 2022/09/08 16:33:32 - mmengine - INFO - Epoch(train) [29][500/1253] lr: 4.0000e-03 eta: 4:25:29 time: 0.6584 data_time: 0.0783 memory: 23504 grad_norm: 2.8734 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9135 loss: 0.9135 2022/09/08 16:33:43 - mmengine - INFO - Epoch(train) [29][520/1253] lr: 4.0000e-03 eta: 4:25:17 time: 0.5521 data_time: 0.0320 memory: 23504 grad_norm: 3.0727 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0790 loss: 1.0790 2022/09/08 16:33:54 - mmengine - INFO - Epoch(train) [29][540/1253] lr: 4.0000e-03 eta: 4:25:05 time: 0.5442 data_time: 0.0369 memory: 23504 grad_norm: 2.9054 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.0281 loss: 1.0281 2022/09/08 16:34:05 - mmengine - INFO - Epoch(train) [29][560/1253] lr: 4.0000e-03 eta: 4:24:53 time: 0.5837 data_time: 0.0367 memory: 23504 grad_norm: 3.0507 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 1.0050 loss: 1.0050 2022/09/08 16:34:17 - mmengine - INFO - Epoch(train) [29][580/1253] lr: 4.0000e-03 eta: 4:24:41 time: 0.6020 data_time: 0.0450 memory: 23504 grad_norm: 2.9764 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 0.9450 loss: 0.9450 2022/09/08 16:34:29 - mmengine - INFO - Epoch(train) [29][600/1253] lr: 4.0000e-03 eta: 4:24:29 time: 0.5849 data_time: 0.0355 memory: 23504 grad_norm: 2.9489 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.9504 loss: 0.9504 2022/09/08 16:34:42 - mmengine - INFO - Epoch(train) [29][620/1253] lr: 4.0000e-03 eta: 4:24:19 time: 0.6456 data_time: 0.0852 memory: 23504 grad_norm: 2.9794 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.0652 loss: 1.0652 2022/09/08 16:34:53 - mmengine - INFO - Epoch(train) [29][640/1253] lr: 4.0000e-03 eta: 4:24:06 time: 0.5663 data_time: 0.0326 memory: 23504 grad_norm: 2.9580 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9198 loss: 0.9198 2022/09/08 16:35:05 - mmengine - INFO - Epoch(train) [29][660/1253] lr: 4.0000e-03 eta: 4:23:55 time: 0.5991 data_time: 0.0451 memory: 23504 grad_norm: 2.9245 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9406 loss: 0.9406 2022/09/08 16:35:19 - mmengine - INFO - Epoch(train) [29][680/1253] lr: 4.0000e-03 eta: 4:23:44 time: 0.6656 data_time: 0.0360 memory: 23504 grad_norm: 2.9707 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.1320 loss: 1.1320 2022/09/08 16:35:30 - mmengine - INFO - Epoch(train) [29][700/1253] lr: 4.0000e-03 eta: 4:23:32 time: 0.5468 data_time: 0.0439 memory: 23504 grad_norm: 2.9962 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0397 loss: 1.0397 2022/09/08 16:35:41 - mmengine - INFO - Epoch(train) [29][720/1253] lr: 4.0000e-03 eta: 4:23:20 time: 0.5615 data_time: 0.0471 memory: 23504 grad_norm: 2.9652 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9992 loss: 0.9992 2022/09/08 16:35:53 - mmengine - INFO - Epoch(train) [29][740/1253] lr: 4.0000e-03 eta: 4:23:08 time: 0.5865 data_time: 0.0460 memory: 23504 grad_norm: 3.0755 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0450 loss: 1.0450 2022/09/08 16:36:04 - mmengine - INFO - Epoch(train) [29][760/1253] lr: 4.0000e-03 eta: 4:22:56 time: 0.5885 data_time: 0.0476 memory: 23504 grad_norm: 3.0134 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.0781 loss: 1.0781 2022/09/08 16:36:16 - mmengine - INFO - Epoch(train) [29][780/1253] lr: 4.0000e-03 eta: 4:22:44 time: 0.5723 data_time: 0.0398 memory: 23504 grad_norm: 3.1135 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.0777 loss: 1.0777 2022/09/08 16:36:27 - mmengine - INFO - Epoch(train) [29][800/1253] lr: 4.0000e-03 eta: 4:22:32 time: 0.5618 data_time: 0.0489 memory: 23504 grad_norm: 3.0021 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9783 loss: 0.9783 2022/09/08 16:36:38 - mmengine - INFO - Epoch(train) [29][820/1253] lr: 4.0000e-03 eta: 4:22:20 time: 0.5561 data_time: 0.0471 memory: 23504 grad_norm: 3.0455 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0014 loss: 1.0014 2022/09/08 16:36:50 - mmengine - INFO - Epoch(train) [29][840/1253] lr: 4.0000e-03 eta: 4:22:08 time: 0.5657 data_time: 0.0459 memory: 23504 grad_norm: 3.0254 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.9208 loss: 0.9208 2022/09/08 16:37:01 - mmengine - INFO - Epoch(train) [29][860/1253] lr: 4.0000e-03 eta: 4:21:56 time: 0.5712 data_time: 0.0418 memory: 23504 grad_norm: 2.9729 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0557 loss: 1.0557 2022/09/08 16:37:14 - mmengine - INFO - Epoch(train) [29][880/1253] lr: 4.0000e-03 eta: 4:21:44 time: 0.6000 data_time: 0.0374 memory: 23504 grad_norm: 3.0139 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.0920 loss: 1.0920 2022/09/08 16:37:25 - mmengine - INFO - Epoch(train) [29][900/1253] lr: 4.0000e-03 eta: 4:21:32 time: 0.6059 data_time: 0.0777 memory: 23504 grad_norm: 3.0450 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1087 loss: 1.1087 2022/09/08 16:37:35 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 16:37:37 - mmengine - INFO - Epoch(train) [29][920/1253] lr: 4.0000e-03 eta: 4:21:20 time: 0.5734 data_time: 0.0278 memory: 23504 grad_norm: 3.0562 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 1.0068 loss: 1.0068 2022/09/08 16:37:49 - mmengine - INFO - Epoch(train) [29][940/1253] lr: 4.0000e-03 eta: 4:21:09 time: 0.6260 data_time: 0.0415 memory: 23504 grad_norm: 3.0158 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.9729 loss: 0.9729 2022/09/08 16:38:00 - mmengine - INFO - Epoch(train) [29][960/1253] lr: 4.0000e-03 eta: 4:20:57 time: 0.5640 data_time: 0.0426 memory: 23504 grad_norm: 3.0994 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0095 loss: 1.0095 2022/09/08 16:38:13 - mmengine - INFO - Epoch(train) [29][980/1253] lr: 4.0000e-03 eta: 4:20:46 time: 0.6161 data_time: 0.0402 memory: 23504 grad_norm: 3.0220 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.0604 loss: 1.0604 2022/09/08 16:38:25 - mmengine - INFO - Epoch(train) [29][1000/1253] lr: 4.0000e-03 eta: 4:20:34 time: 0.6039 data_time: 0.0421 memory: 23504 grad_norm: 3.1281 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.0480 loss: 1.0480 2022/09/08 16:38:38 - mmengine - INFO - Epoch(train) [29][1020/1253] lr: 4.0000e-03 eta: 4:20:23 time: 0.6366 data_time: 0.0377 memory: 23504 grad_norm: 3.0398 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0528 loss: 1.0528 2022/09/08 16:38:49 - mmengine - INFO - Epoch(train) [29][1040/1253] lr: 4.0000e-03 eta: 4:20:11 time: 0.5658 data_time: 0.0409 memory: 23504 grad_norm: 2.9893 top1_acc: 0.9583 top5_acc: 1.0000 loss_cls: 1.0605 loss: 1.0605 2022/09/08 16:39:00 - mmengine - INFO - Epoch(train) [29][1060/1253] lr: 4.0000e-03 eta: 4:19:59 time: 0.5648 data_time: 0.0419 memory: 23504 grad_norm: 3.0880 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 0.9823 loss: 0.9823 2022/09/08 16:39:11 - mmengine - INFO - Epoch(train) [29][1080/1253] lr: 4.0000e-03 eta: 4:19:47 time: 0.5637 data_time: 0.0400 memory: 23504 grad_norm: 3.0272 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.0165 loss: 1.0165 2022/09/08 16:39:23 - mmengine - INFO - Epoch(train) [29][1100/1253] lr: 4.0000e-03 eta: 4:19:35 time: 0.5657 data_time: 0.0496 memory: 23504 grad_norm: 3.0316 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0035 loss: 1.0035 2022/09/08 16:39:34 - mmengine - INFO - Epoch(train) [29][1120/1253] lr: 4.0000e-03 eta: 4:19:23 time: 0.5781 data_time: 0.0450 memory: 23504 grad_norm: 2.9896 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9775 loss: 0.9775 2022/09/08 16:39:47 - mmengine - INFO - Epoch(train) [29][1140/1253] lr: 4.0000e-03 eta: 4:19:12 time: 0.6405 data_time: 0.0362 memory: 23504 grad_norm: 3.0063 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0178 loss: 1.0178 2022/09/08 16:39:59 - mmengine - INFO - Epoch(train) [29][1160/1253] lr: 4.0000e-03 eta: 4:19:00 time: 0.6008 data_time: 0.0448 memory: 23504 grad_norm: 3.0200 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9685 loss: 0.9685 2022/09/08 16:40:11 - mmengine - INFO - Epoch(train) [29][1180/1253] lr: 4.0000e-03 eta: 4:18:48 time: 0.5717 data_time: 0.0380 memory: 23504 grad_norm: 3.0312 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 0.9761 loss: 0.9761 2022/09/08 16:40:22 - mmengine - INFO - Epoch(train) [29][1200/1253] lr: 4.0000e-03 eta: 4:18:36 time: 0.5674 data_time: 0.0402 memory: 23504 grad_norm: 3.0681 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 0.9305 loss: 0.9305 2022/09/08 16:40:35 - mmengine - INFO - Epoch(train) [29][1220/1253] lr: 4.0000e-03 eta: 4:18:25 time: 0.6317 data_time: 0.0336 memory: 23504 grad_norm: 3.0219 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9902 loss: 0.9902 2022/09/08 16:40:44 - mmengine - INFO - Epoch(train) [29][1240/1253] lr: 4.0000e-03 eta: 4:18:12 time: 0.4856 data_time: 0.0268 memory: 23504 grad_norm: 3.1209 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0575 loss: 1.0575 2022/09/08 16:40:50 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 16:40:50 - mmengine - INFO - Epoch(train) [29][1253/1253] lr: 4.0000e-03 eta: 4:18:12 time: 0.4310 data_time: 0.0159 memory: 23504 grad_norm: 3.1844 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.0374 loss: 1.0374 2022/09/08 16:41:11 - mmengine - INFO - Epoch(train) [30][20/1253] lr: 4.0000e-03 eta: 4:17:54 time: 1.0811 data_time: 0.4712 memory: 23504 grad_norm: 3.0026 top1_acc: 0.7083 top5_acc: 1.0000 loss_cls: 0.9312 loss: 0.9312 2022/09/08 16:41:24 - mmengine - INFO - Epoch(train) [30][40/1253] lr: 4.0000e-03 eta: 4:17:42 time: 0.6154 data_time: 0.0384 memory: 23504 grad_norm: 3.0139 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0156 loss: 1.0156 2022/09/08 16:41:35 - mmengine - INFO - Epoch(train) [30][60/1253] lr: 4.0000e-03 eta: 4:17:30 time: 0.5648 data_time: 0.0429 memory: 23504 grad_norm: 2.9521 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0329 loss: 1.0329 2022/09/08 16:41:49 - mmengine - INFO - Epoch(train) [30][80/1253] lr: 4.0000e-03 eta: 4:17:20 time: 0.7078 data_time: 0.0393 memory: 23504 grad_norm: 3.0188 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9847 loss: 0.9847 2022/09/08 16:42:01 - mmengine - INFO - Epoch(train) [30][100/1253] lr: 4.0000e-03 eta: 4:17:09 time: 0.6047 data_time: 0.0412 memory: 23504 grad_norm: 3.0587 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.1147 loss: 1.1147 2022/09/08 16:42:14 - mmengine - INFO - Epoch(train) [30][120/1253] lr: 4.0000e-03 eta: 4:16:57 time: 0.6284 data_time: 0.0371 memory: 23504 grad_norm: 2.9986 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8737 loss: 0.8737 2022/09/08 16:42:25 - mmengine - INFO - Epoch(train) [30][140/1253] lr: 4.0000e-03 eta: 4:16:45 time: 0.5632 data_time: 0.0419 memory: 23504 grad_norm: 3.0192 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.9500 loss: 0.9500 2022/09/08 16:42:37 - mmengine - INFO - Epoch(train) [30][160/1253] lr: 4.0000e-03 eta: 4:16:33 time: 0.5783 data_time: 0.0325 memory: 23504 grad_norm: 2.9875 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8393 loss: 0.8393 2022/09/08 16:42:48 - mmengine - INFO - Epoch(train) [30][180/1253] lr: 4.0000e-03 eta: 4:16:21 time: 0.5695 data_time: 0.0446 memory: 23504 grad_norm: 3.0800 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.1033 loss: 1.1033 2022/09/08 16:43:03 - mmengine - INFO - Epoch(train) [30][200/1253] lr: 4.0000e-03 eta: 4:16:12 time: 0.7300 data_time: 0.0370 memory: 23504 grad_norm: 3.0626 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 0.9603 loss: 0.9603 2022/09/08 16:43:13 - mmengine - INFO - Epoch(train) [30][220/1253] lr: 4.0000e-03 eta: 4:15:59 time: 0.5362 data_time: 0.0401 memory: 23504 grad_norm: 3.0368 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 0.9784 loss: 0.9784 2022/09/08 16:43:25 - mmengine - INFO - Epoch(train) [30][240/1253] lr: 4.0000e-03 eta: 4:15:47 time: 0.5775 data_time: 0.0387 memory: 23504 grad_norm: 2.9530 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9706 loss: 0.9706 2022/09/08 16:43:37 - mmengine - INFO - Epoch(train) [30][260/1253] lr: 4.0000e-03 eta: 4:15:35 time: 0.5914 data_time: 0.0370 memory: 23504 grad_norm: 3.0284 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.0062 loss: 1.0062 2022/09/08 16:43:50 - mmengine - INFO - Epoch(train) [30][280/1253] lr: 4.0000e-03 eta: 4:15:25 time: 0.6650 data_time: 0.0794 memory: 23504 grad_norm: 2.9409 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9777 loss: 0.9777 2022/09/08 16:44:01 - mmengine - INFO - Epoch(train) [30][300/1253] lr: 4.0000e-03 eta: 4:15:13 time: 0.5637 data_time: 0.0255 memory: 23504 grad_norm: 3.0067 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 1.0293 loss: 1.0293 2022/09/08 16:44:14 - mmengine - INFO - Epoch(train) [30][320/1253] lr: 4.0000e-03 eta: 4:15:02 time: 0.6347 data_time: 0.0416 memory: 23504 grad_norm: 3.0155 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.0141 loss: 1.0141 2022/09/08 16:44:25 - mmengine - INFO - Epoch(train) [30][340/1253] lr: 4.0000e-03 eta: 4:14:49 time: 0.5563 data_time: 0.0418 memory: 23504 grad_norm: 3.1275 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0245 loss: 1.0245 2022/09/08 16:44:36 - mmengine - INFO - Epoch(train) [30][360/1253] lr: 4.0000e-03 eta: 4:14:37 time: 0.5655 data_time: 0.0451 memory: 23504 grad_norm: 3.0434 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9271 loss: 0.9271 2022/09/08 16:44:51 - mmengine - INFO - Epoch(train) [30][380/1253] lr: 4.0000e-03 eta: 4:14:27 time: 0.7077 data_time: 0.0413 memory: 23504 grad_norm: 3.0189 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9768 loss: 0.9768 2022/09/08 16:45:02 - mmengine - INFO - Epoch(train) [30][400/1253] lr: 4.0000e-03 eta: 4:14:15 time: 0.5475 data_time: 0.0360 memory: 23504 grad_norm: 3.0678 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 0.9776 loss: 0.9776 2022/09/08 16:45:12 - mmengine - INFO - Epoch(train) [30][420/1253] lr: 4.0000e-03 eta: 4:14:02 time: 0.5413 data_time: 0.0446 memory: 23504 grad_norm: 3.0844 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0642 loss: 1.0642 2022/09/08 16:45:24 - mmengine - INFO - Epoch(train) [30][440/1253] lr: 4.0000e-03 eta: 4:13:50 time: 0.5689 data_time: 0.0448 memory: 23504 grad_norm: 2.9942 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.0464 loss: 1.0464 2022/09/08 16:45:35 - mmengine - INFO - Epoch(train) [30][460/1253] lr: 4.0000e-03 eta: 4:13:38 time: 0.5835 data_time: 0.0494 memory: 23504 grad_norm: 3.0452 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.8920 loss: 0.8920 2022/09/08 16:45:47 - mmengine - INFO - Epoch(train) [30][480/1253] lr: 4.0000e-03 eta: 4:13:26 time: 0.5631 data_time: 0.0364 memory: 23504 grad_norm: 3.1403 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0660 loss: 1.0660 2022/09/08 16:45:58 - mmengine - INFO - Epoch(train) [30][500/1253] lr: 4.0000e-03 eta: 4:13:14 time: 0.5778 data_time: 0.0390 memory: 23504 grad_norm: 3.0007 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8760 loss: 0.8760 2022/09/08 16:46:12 - mmengine - INFO - Epoch(train) [30][520/1253] lr: 4.0000e-03 eta: 4:13:04 time: 0.6771 data_time: 0.0404 memory: 23504 grad_norm: 3.0273 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 0.9620 loss: 0.9620 2022/09/08 16:46:23 - mmengine - INFO - Epoch(train) [30][540/1253] lr: 4.0000e-03 eta: 4:12:52 time: 0.5788 data_time: 0.0316 memory: 23504 grad_norm: 2.9690 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.8979 loss: 0.8979 2022/09/08 16:46:35 - mmengine - INFO - Epoch(train) [30][560/1253] lr: 4.0000e-03 eta: 4:12:40 time: 0.5772 data_time: 0.0348 memory: 23504 grad_norm: 3.0058 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.0296 loss: 1.0296 2022/09/08 16:46:47 - mmengine - INFO - Epoch(train) [30][580/1253] lr: 4.0000e-03 eta: 4:12:28 time: 0.5809 data_time: 0.0469 memory: 23504 grad_norm: 3.0769 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.0220 loss: 1.0220 2022/09/08 16:47:00 - mmengine - INFO - Epoch(train) [30][600/1253] lr: 4.0000e-03 eta: 4:12:18 time: 0.6804 data_time: 0.0301 memory: 23504 grad_norm: 3.0978 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.9104 loss: 0.9104 2022/09/08 16:47:12 - mmengine - INFO - Epoch(train) [30][620/1253] lr: 4.0000e-03 eta: 4:12:06 time: 0.5917 data_time: 0.0839 memory: 23504 grad_norm: 3.0575 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9570 loss: 0.9570 2022/09/08 16:47:24 - mmengine - INFO - Epoch(train) [30][640/1253] lr: 4.0000e-03 eta: 4:11:54 time: 0.5817 data_time: 0.0350 memory: 23504 grad_norm: 3.0288 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 1.0058 loss: 1.0058 2022/09/08 16:47:37 - mmengine - INFO - Epoch(train) [30][660/1253] lr: 4.0000e-03 eta: 4:11:43 time: 0.6640 data_time: 0.0447 memory: 23504 grad_norm: 3.0708 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0164 loss: 1.0164 2022/09/08 16:47:38 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 16:47:48 - mmengine - INFO - Epoch(train) [30][680/1253] lr: 4.0000e-03 eta: 4:11:31 time: 0.5293 data_time: 0.0409 memory: 23504 grad_norm: 3.0871 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 0.9307 loss: 0.9307 2022/09/08 16:47:59 - mmengine - INFO - Epoch(train) [30][700/1253] lr: 4.0000e-03 eta: 4:11:19 time: 0.5693 data_time: 0.0454 memory: 23504 grad_norm: 3.0239 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9627 loss: 0.9627 2022/09/08 16:48:12 - mmengine - INFO - Epoch(train) [30][720/1253] lr: 4.0000e-03 eta: 4:11:08 time: 0.6614 data_time: 0.0365 memory: 23504 grad_norm: 3.0465 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9050 loss: 0.9050 2022/09/08 16:48:23 - mmengine - INFO - Epoch(train) [30][740/1253] lr: 4.0000e-03 eta: 4:10:56 time: 0.5629 data_time: 0.0384 memory: 23504 grad_norm: 3.0263 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9427 loss: 0.9427 2022/09/08 16:48:35 - mmengine - INFO - Epoch(train) [30][760/1253] lr: 4.0000e-03 eta: 4:10:43 time: 0.5557 data_time: 0.0404 memory: 23504 grad_norm: 3.0549 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.0616 loss: 1.0616 2022/09/08 16:48:47 - mmengine - INFO - Epoch(train) [30][780/1253] lr: 4.0000e-03 eta: 4:10:32 time: 0.6292 data_time: 0.0455 memory: 23504 grad_norm: 3.1049 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 1.0386 loss: 1.0386 2022/09/08 16:48:59 - mmengine - INFO - Epoch(train) [30][800/1253] lr: 4.0000e-03 eta: 4:10:20 time: 0.5883 data_time: 0.0443 memory: 23504 grad_norm: 3.0072 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.0219 loss: 1.0219 2022/09/08 16:49:10 - mmengine - INFO - Epoch(train) [30][820/1253] lr: 4.0000e-03 eta: 4:10:08 time: 0.5477 data_time: 0.0507 memory: 23504 grad_norm: 3.1791 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.0048 loss: 1.0048 2022/09/08 16:49:21 - mmengine - INFO - Epoch(train) [30][840/1253] lr: 4.0000e-03 eta: 4:09:56 time: 0.5415 data_time: 0.0382 memory: 23504 grad_norm: 3.0334 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 1.1258 loss: 1.1258 2022/09/08 16:49:32 - mmengine - INFO - Epoch(train) [30][860/1253] lr: 4.0000e-03 eta: 4:09:43 time: 0.5502 data_time: 0.0582 memory: 23504 grad_norm: 3.0743 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.9992 loss: 0.9992 2022/09/08 16:49:44 - mmengine - INFO - Epoch(train) [30][880/1253] lr: 4.0000e-03 eta: 4:09:32 time: 0.5896 data_time: 0.0368 memory: 23504 grad_norm: 3.0605 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 0.9874 loss: 0.9874 2022/09/08 16:49:55 - mmengine - INFO - Epoch(train) [30][900/1253] lr: 4.0000e-03 eta: 4:09:20 time: 0.5856 data_time: 0.0460 memory: 23504 grad_norm: 3.0158 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.9217 loss: 0.9217 2022/09/08 16:50:08 - mmengine - INFO - Epoch(train) [30][920/1253] lr: 4.0000e-03 eta: 4:09:09 time: 0.6240 data_time: 0.0555 memory: 23504 grad_norm: 2.9931 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.1226 loss: 1.1226 2022/09/08 16:50:20 - mmengine - INFO - Epoch(train) [30][940/1253] lr: 4.0000e-03 eta: 4:08:57 time: 0.5961 data_time: 0.0368 memory: 23504 grad_norm: 3.0557 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.0341 loss: 1.0341 2022/09/08 16:50:33 - mmengine - INFO - Epoch(train) [30][960/1253] lr: 4.0000e-03 eta: 4:08:46 time: 0.6760 data_time: 0.0274 memory: 23504 grad_norm: 3.0465 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9215 loss: 0.9215 2022/09/08 16:50:44 - mmengine - INFO - Epoch(train) [30][980/1253] lr: 4.0000e-03 eta: 4:08:34 time: 0.5418 data_time: 0.0321 memory: 23504 grad_norm: 3.0287 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9660 loss: 0.9660 2022/09/08 16:50:55 - mmengine - INFO - Epoch(train) [30][1000/1253] lr: 4.0000e-03 eta: 4:08:22 time: 0.5610 data_time: 0.0428 memory: 23504 grad_norm: 3.0168 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9509 loss: 0.9509 2022/09/08 16:51:07 - mmengine - INFO - Epoch(train) [30][1020/1253] lr: 4.0000e-03 eta: 4:08:10 time: 0.5735 data_time: 0.0491 memory: 23504 grad_norm: 3.0621 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.0731 loss: 1.0731 2022/09/08 16:51:18 - mmengine - INFO - Epoch(train) [30][1040/1253] lr: 4.0000e-03 eta: 4:07:58 time: 0.5615 data_time: 0.0389 memory: 23504 grad_norm: 3.0157 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.9443 loss: 0.9443 2022/09/08 16:51:29 - mmengine - INFO - Epoch(train) [30][1060/1253] lr: 4.0000e-03 eta: 4:07:46 time: 0.5722 data_time: 0.0347 memory: 23504 grad_norm: 3.0703 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9886 loss: 0.9886 2022/09/08 16:51:43 - mmengine - INFO - Epoch(train) [30][1080/1253] lr: 4.0000e-03 eta: 4:07:35 time: 0.6978 data_time: 0.0535 memory: 23504 grad_norm: 3.0284 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9081 loss: 0.9081 2022/09/08 16:51:54 - mmengine - INFO - Epoch(train) [30][1100/1253] lr: 4.0000e-03 eta: 4:07:23 time: 0.5436 data_time: 0.0323 memory: 23504 grad_norm: 2.9985 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.0336 loss: 1.0336 2022/09/08 16:52:06 - mmengine - INFO - Epoch(train) [30][1120/1253] lr: 4.0000e-03 eta: 4:07:11 time: 0.5707 data_time: 0.0406 memory: 23504 grad_norm: 3.0890 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0679 loss: 1.0679 2022/09/08 16:52:17 - mmengine - INFO - Epoch(train) [30][1140/1253] lr: 4.0000e-03 eta: 4:06:59 time: 0.5734 data_time: 0.0423 memory: 23504 grad_norm: 2.9672 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.0199 loss: 1.0199 2022/09/08 16:52:29 - mmengine - INFO - Epoch(train) [30][1160/1253] lr: 4.0000e-03 eta: 4:06:47 time: 0.5796 data_time: 0.0498 memory: 23504 grad_norm: 3.1321 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 1.0285 loss: 1.0285 2022/09/08 16:52:40 - mmengine - INFO - Epoch(train) [30][1180/1253] lr: 4.0000e-03 eta: 4:06:35 time: 0.5860 data_time: 0.0561 memory: 23504 grad_norm: 3.0570 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9229 loss: 0.9229 2022/09/08 16:52:52 - mmengine - INFO - Epoch(train) [30][1200/1253] lr: 4.0000e-03 eta: 4:06:23 time: 0.5587 data_time: 0.0433 memory: 23504 grad_norm: 3.0885 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.0368 loss: 1.0368 2022/09/08 16:53:03 - mmengine - INFO - Epoch(train) [30][1220/1253] lr: 4.0000e-03 eta: 4:06:11 time: 0.5906 data_time: 0.0507 memory: 23504 grad_norm: 3.0342 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9891 loss: 0.9891 2022/09/08 16:53:13 - mmengine - INFO - Epoch(train) [30][1240/1253] lr: 4.0000e-03 eta: 4:05:58 time: 0.4992 data_time: 0.0309 memory: 23504 grad_norm: 3.0107 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 0.9155 loss: 0.9155 2022/09/08 16:53:19 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 16:53:19 - mmengine - INFO - Epoch(train) [30][1253/1253] lr: 4.0000e-03 eta: 4:05:58 time: 0.4370 data_time: 0.0166 memory: 23504 grad_norm: 3.1195 top1_acc: 0.5714 top5_acc: 0.5714 loss_cls: 1.0413 loss: 1.0413 2022/09/08 16:53:46 - mmengine - INFO - Epoch(val) [30][20/104] eta: 0:01:52 time: 1.3342 data_time: 1.1878 memory: 2699 2022/09/08 16:53:55 - mmengine - INFO - Epoch(val) [30][40/104] eta: 0:00:31 time: 0.4889 data_time: 0.3534 memory: 2699 2022/09/08 16:54:09 - mmengine - INFO - Epoch(val) [30][60/104] eta: 0:00:29 time: 0.6603 data_time: 0.5217 memory: 2699 2022/09/08 16:54:19 - mmengine - INFO - Epoch(val) [30][80/104] eta: 0:00:11 time: 0.4942 data_time: 0.3581 memory: 2699 2022/09/08 16:54:23 - mmengine - INFO - Epoch(val) [30][100/104] eta: 0:00:00 time: 0.2488 data_time: 0.1330 memory: 2699 2022/09/08 16:54:30 - mmengine - INFO - Epoch(val) [30][104/104] acc/top1: 0.7089 acc/top5: 0.9003 acc/mean1: 0.7088 2022/09/08 16:54:30 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb/best_acc/top1_epoch_25.pth is removed 2022/09/08 16:54:31 - mmengine - INFO - The best checkpoint with 0.7089 acc/top1 at 30 epoch is saved to best_acc/top1_epoch_30.pth. 2022/09/08 16:54:54 - mmengine - INFO - Epoch(train) [31][20/1253] lr: 4.0000e-03 eta: 4:05:41 time: 1.1537 data_time: 0.5617 memory: 23504 grad_norm: 2.9849 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9317 loss: 0.9317 2022/09/08 16:55:06 - mmengine - INFO - Epoch(train) [31][40/1253] lr: 4.0000e-03 eta: 4:05:30 time: 0.5913 data_time: 0.0800 memory: 23504 grad_norm: 3.0157 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9583 loss: 0.9583 2022/09/08 16:55:20 - mmengine - INFO - Epoch(train) [31][60/1253] lr: 4.0000e-03 eta: 4:05:19 time: 0.6930 data_time: 0.1748 memory: 23504 grad_norm: 3.0566 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9444 loss: 0.9444 2022/09/08 16:55:30 - mmengine - INFO - Epoch(train) [31][80/1253] lr: 4.0000e-03 eta: 4:05:07 time: 0.5385 data_time: 0.0302 memory: 23504 grad_norm: 3.0270 top1_acc: 0.7083 top5_acc: 1.0000 loss_cls: 0.9476 loss: 0.9476 2022/09/08 16:55:42 - mmengine - INFO - Epoch(train) [31][100/1253] lr: 4.0000e-03 eta: 4:04:55 time: 0.5757 data_time: 0.0747 memory: 23504 grad_norm: 3.1258 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.0202 loss: 1.0202 2022/09/08 16:55:53 - mmengine - INFO - Epoch(train) [31][120/1253] lr: 4.0000e-03 eta: 4:04:43 time: 0.5538 data_time: 0.0425 memory: 23504 grad_norm: 3.1662 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0163 loss: 1.0163 2022/09/08 16:56:04 - mmengine - INFO - Epoch(train) [31][140/1253] lr: 4.0000e-03 eta: 4:04:31 time: 0.5705 data_time: 0.0399 memory: 23504 grad_norm: 3.0237 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9053 loss: 0.9053 2022/09/08 16:56:16 - mmengine - INFO - Epoch(train) [31][160/1253] lr: 4.0000e-03 eta: 4:04:19 time: 0.5771 data_time: 0.0411 memory: 23504 grad_norm: 3.1273 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.9540 loss: 0.9540 2022/09/08 16:56:27 - mmengine - INFO - Epoch(train) [31][180/1253] lr: 4.0000e-03 eta: 4:04:07 time: 0.5711 data_time: 0.0449 memory: 23504 grad_norm: 3.0011 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.0771 loss: 1.0771 2022/09/08 16:56:39 - mmengine - INFO - Epoch(train) [31][200/1253] lr: 4.0000e-03 eta: 4:03:55 time: 0.5938 data_time: 0.0433 memory: 23504 grad_norm: 2.9910 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8622 loss: 0.8622 2022/09/08 16:56:51 - mmengine - INFO - Epoch(train) [31][220/1253] lr: 4.0000e-03 eta: 4:03:43 time: 0.5624 data_time: 0.0423 memory: 23504 grad_norm: 3.0870 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9559 loss: 0.9559 2022/09/08 16:57:02 - mmengine - INFO - Epoch(train) [31][240/1253] lr: 4.0000e-03 eta: 4:03:31 time: 0.5851 data_time: 0.0394 memory: 23504 grad_norm: 3.0924 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.9601 loss: 0.9601 2022/09/08 16:57:13 - mmengine - INFO - Epoch(train) [31][260/1253] lr: 4.0000e-03 eta: 4:03:19 time: 0.5458 data_time: 0.0412 memory: 23504 grad_norm: 3.0963 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9331 loss: 0.9331 2022/09/08 16:57:26 - mmengine - INFO - Epoch(train) [31][280/1253] lr: 4.0000e-03 eta: 4:03:07 time: 0.6269 data_time: 0.0506 memory: 23504 grad_norm: 3.1044 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9795 loss: 0.9795 2022/09/08 16:57:39 - mmengine - INFO - Epoch(train) [31][300/1253] lr: 4.0000e-03 eta: 4:02:56 time: 0.6494 data_time: 0.0710 memory: 23504 grad_norm: 2.9975 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9605 loss: 0.9605 2022/09/08 16:57:52 - mmengine - INFO - Epoch(train) [31][320/1253] lr: 4.0000e-03 eta: 4:02:45 time: 0.6547 data_time: 0.0297 memory: 23504 grad_norm: 3.0515 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9263 loss: 0.9263 2022/09/08 16:58:03 - mmengine - INFO - Epoch(train) [31][340/1253] lr: 4.0000e-03 eta: 4:02:33 time: 0.5526 data_time: 0.0364 memory: 23504 grad_norm: 3.0963 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9297 loss: 0.9297 2022/09/08 16:58:14 - mmengine - INFO - Epoch(train) [31][360/1253] lr: 4.0000e-03 eta: 4:02:21 time: 0.5694 data_time: 0.0415 memory: 23504 grad_norm: 3.0236 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9614 loss: 0.9614 2022/09/08 16:58:25 - mmengine - INFO - Epoch(train) [31][380/1253] lr: 4.0000e-03 eta: 4:02:09 time: 0.5537 data_time: 0.0467 memory: 23504 grad_norm: 3.1310 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9266 loss: 0.9266 2022/09/08 16:58:37 - mmengine - INFO - Epoch(train) [31][400/1253] lr: 4.0000e-03 eta: 4:01:57 time: 0.6013 data_time: 0.0820 memory: 23504 grad_norm: 3.1167 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 0.9569 loss: 0.9569 2022/09/08 16:58:44 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 16:58:50 - mmengine - INFO - Epoch(train) [31][420/1253] lr: 4.0000e-03 eta: 4:01:46 time: 0.6332 data_time: 0.0815 memory: 23504 grad_norm: 3.0912 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.0068 loss: 1.0068 2022/09/08 16:59:02 - mmengine - INFO - Epoch(train) [31][440/1253] lr: 4.0000e-03 eta: 4:01:34 time: 0.5757 data_time: 0.0408 memory: 23504 grad_norm: 3.0242 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9204 loss: 0.9204 2022/09/08 16:59:16 - mmengine - INFO - Epoch(train) [31][460/1253] lr: 4.0000e-03 eta: 4:01:24 time: 0.7143 data_time: 0.1632 memory: 23504 grad_norm: 2.9877 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0800 loss: 1.0800 2022/09/08 16:59:27 - mmengine - INFO - Epoch(train) [31][480/1253] lr: 4.0000e-03 eta: 4:01:12 time: 0.5478 data_time: 0.0228 memory: 23504 grad_norm: 3.0333 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0071 loss: 1.0071 2022/09/08 16:59:38 - mmengine - INFO - Epoch(train) [31][500/1253] lr: 4.0000e-03 eta: 4:01:00 time: 0.5649 data_time: 0.0288 memory: 23504 grad_norm: 3.0898 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.9561 loss: 0.9561 2022/09/08 16:59:49 - mmengine - INFO - Epoch(train) [31][520/1253] lr: 4.0000e-03 eta: 4:00:47 time: 0.5589 data_time: 0.0487 memory: 23504 grad_norm: 3.0912 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9108 loss: 0.9108 2022/09/08 17:00:01 - mmengine - INFO - Epoch(train) [31][540/1253] lr: 4.0000e-03 eta: 4:00:36 time: 0.5772 data_time: 0.0457 memory: 23504 grad_norm: 3.1073 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0505 loss: 1.0505 2022/09/08 17:00:13 - mmengine - INFO - Epoch(train) [31][560/1253] lr: 4.0000e-03 eta: 4:00:24 time: 0.5887 data_time: 0.0338 memory: 23504 grad_norm: 3.0498 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0124 loss: 1.0124 2022/09/08 17:00:27 - mmengine - INFO - Epoch(train) [31][580/1253] lr: 4.0000e-03 eta: 4:00:14 time: 0.7216 data_time: 0.0332 memory: 23504 grad_norm: 3.1041 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.0686 loss: 1.0686 2022/09/08 17:00:38 - mmengine - INFO - Epoch(train) [31][600/1253] lr: 4.0000e-03 eta: 4:00:02 time: 0.5727 data_time: 0.0583 memory: 23504 grad_norm: 3.0425 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0203 loss: 1.0203 2022/09/08 17:00:49 - mmengine - INFO - Epoch(train) [31][620/1253] lr: 4.0000e-03 eta: 3:59:49 time: 0.5499 data_time: 0.0407 memory: 23504 grad_norm: 3.0340 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.8771 loss: 0.8771 2022/09/08 17:01:00 - mmengine - INFO - Epoch(train) [31][640/1253] lr: 4.0000e-03 eta: 3:59:37 time: 0.5498 data_time: 0.0424 memory: 23504 grad_norm: 3.1024 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9368 loss: 0.9368 2022/09/08 17:01:12 - mmengine - INFO - Epoch(train) [31][660/1253] lr: 4.0000e-03 eta: 3:59:25 time: 0.5616 data_time: 0.0498 memory: 23504 grad_norm: 3.1123 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 1.0156 loss: 1.0156 2022/09/08 17:01:23 - mmengine - INFO - Epoch(train) [31][680/1253] lr: 4.0000e-03 eta: 3:59:13 time: 0.5850 data_time: 0.0461 memory: 23504 grad_norm: 3.0475 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.9493 loss: 0.9493 2022/09/08 17:01:35 - mmengine - INFO - Epoch(train) [31][700/1253] lr: 4.0000e-03 eta: 3:59:01 time: 0.5789 data_time: 0.0382 memory: 23504 grad_norm: 3.0394 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9567 loss: 0.9567 2022/09/08 17:01:48 - mmengine - INFO - Epoch(train) [31][720/1253] lr: 4.0000e-03 eta: 3:58:51 time: 0.6622 data_time: 0.0599 memory: 23504 grad_norm: 3.1245 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 0.9790 loss: 0.9790 2022/09/08 17:02:04 - mmengine - INFO - Epoch(train) [31][740/1253] lr: 4.0000e-03 eta: 3:58:41 time: 0.7769 data_time: 0.0374 memory: 23504 grad_norm: 3.1163 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.9909 loss: 0.9909 2022/09/08 17:02:14 - mmengine - INFO - Epoch(train) [31][760/1253] lr: 4.0000e-03 eta: 3:58:29 time: 0.5267 data_time: 0.0346 memory: 23504 grad_norm: 3.1147 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9920 loss: 0.9920 2022/09/08 17:02:31 - mmengine - INFO - Epoch(train) [31][780/1253] lr: 4.0000e-03 eta: 3:58:20 time: 0.8508 data_time: 0.0454 memory: 23504 grad_norm: 3.1002 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0394 loss: 1.0394 2022/09/08 17:02:42 - mmengine - INFO - Epoch(train) [31][800/1253] lr: 4.0000e-03 eta: 3:58:07 time: 0.5085 data_time: 0.0347 memory: 23504 grad_norm: 3.1648 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 0.9170 loss: 0.9170 2022/09/08 17:02:52 - mmengine - INFO - Epoch(train) [31][820/1253] lr: 4.0000e-03 eta: 3:57:55 time: 0.5480 data_time: 0.0442 memory: 23504 grad_norm: 3.1261 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0308 loss: 1.0308 2022/09/08 17:03:04 - mmengine - INFO - Epoch(train) [31][840/1253] lr: 4.0000e-03 eta: 3:57:43 time: 0.5587 data_time: 0.0482 memory: 23504 grad_norm: 3.0831 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9891 loss: 0.9891 2022/09/08 17:03:17 - mmengine - INFO - Epoch(train) [31][860/1253] lr: 4.0000e-03 eta: 3:57:32 time: 0.6474 data_time: 0.0826 memory: 23504 grad_norm: 3.0821 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.0716 loss: 1.0716 2022/09/08 17:03:29 - mmengine - INFO - Epoch(train) [31][880/1253] lr: 4.0000e-03 eta: 3:57:20 time: 0.6022 data_time: 0.0463 memory: 23504 grad_norm: 3.1250 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.1543 loss: 1.1543 2022/09/08 17:03:40 - mmengine - INFO - Epoch(train) [31][900/1253] lr: 4.0000e-03 eta: 3:57:08 time: 0.5895 data_time: 0.0389 memory: 23504 grad_norm: 3.0604 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0180 loss: 1.0180 2022/09/08 17:03:51 - mmengine - INFO - Epoch(train) [31][920/1253] lr: 4.0000e-03 eta: 3:56:56 time: 0.5354 data_time: 0.0374 memory: 23504 grad_norm: 3.0069 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 0.9014 loss: 0.9014 2022/09/08 17:04:02 - mmengine - INFO - Epoch(train) [31][940/1253] lr: 4.0000e-03 eta: 3:56:44 time: 0.5460 data_time: 0.0464 memory: 23504 grad_norm: 3.1379 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.8866 loss: 0.8866 2022/09/08 17:04:13 - mmengine - INFO - Epoch(train) [31][960/1253] lr: 4.0000e-03 eta: 3:56:32 time: 0.5645 data_time: 0.0488 memory: 23504 grad_norm: 3.0110 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9777 loss: 0.9777 2022/09/08 17:04:28 - mmengine - INFO - Epoch(train) [31][980/1253] lr: 4.0000e-03 eta: 3:56:21 time: 0.7213 data_time: 0.0395 memory: 23504 grad_norm: 3.1091 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 0.9260 loss: 0.9260 2022/09/08 17:04:39 - mmengine - INFO - Epoch(train) [31][1000/1253] lr: 4.0000e-03 eta: 3:56:09 time: 0.5631 data_time: 0.0408 memory: 23504 grad_norm: 3.1536 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.0696 loss: 1.0696 2022/09/08 17:04:50 - mmengine - INFO - Epoch(train) [31][1020/1253] lr: 4.0000e-03 eta: 3:55:57 time: 0.5650 data_time: 0.0449 memory: 23504 grad_norm: 3.0879 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7992 loss: 0.7992 2022/09/08 17:05:01 - mmengine - INFO - Epoch(train) [31][1040/1253] lr: 4.0000e-03 eta: 3:55:45 time: 0.5523 data_time: 0.0463 memory: 23504 grad_norm: 3.1034 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.1352 loss: 1.1352 2022/09/08 17:05:15 - mmengine - INFO - Epoch(train) [31][1060/1253] lr: 4.0000e-03 eta: 3:55:34 time: 0.6873 data_time: 0.0354 memory: 23504 grad_norm: 3.0590 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9302 loss: 0.9302 2022/09/08 17:05:26 - mmengine - INFO - Epoch(train) [31][1080/1253] lr: 4.0000e-03 eta: 3:55:22 time: 0.5324 data_time: 0.0521 memory: 23504 grad_norm: 3.0029 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9418 loss: 0.9418 2022/09/08 17:05:39 - mmengine - INFO - Epoch(train) [31][1100/1253] lr: 4.0000e-03 eta: 3:55:11 time: 0.6488 data_time: 0.1206 memory: 23504 grad_norm: 3.1262 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9125 loss: 0.9125 2022/09/08 17:05:50 - mmengine - INFO - Epoch(train) [31][1120/1253] lr: 4.0000e-03 eta: 3:54:59 time: 0.5546 data_time: 0.0324 memory: 23504 grad_norm: 3.1740 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9942 loss: 0.9942 2022/09/08 17:06:01 - mmengine - INFO - Epoch(train) [31][1140/1253] lr: 4.0000e-03 eta: 3:54:47 time: 0.5662 data_time: 0.0384 memory: 23504 grad_norm: 3.1053 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9273 loss: 0.9273 2022/09/08 17:06:15 - mmengine - INFO - Epoch(train) [31][1160/1253] lr: 4.0000e-03 eta: 3:54:36 time: 0.6728 data_time: 0.0500 memory: 23504 grad_norm: 3.1193 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0531 loss: 1.0531 2022/09/08 17:06:26 - mmengine - INFO - Epoch(train) [31][1180/1253] lr: 4.0000e-03 eta: 3:54:24 time: 0.5601 data_time: 0.0316 memory: 23504 grad_norm: 3.1199 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 0.9703 loss: 0.9703 2022/09/08 17:06:38 - mmengine - INFO - Epoch(train) [31][1200/1253] lr: 4.0000e-03 eta: 3:54:12 time: 0.5779 data_time: 0.0402 memory: 23504 grad_norm: 3.0528 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9275 loss: 0.9275 2022/09/08 17:06:49 - mmengine - INFO - Epoch(train) [31][1220/1253] lr: 4.0000e-03 eta: 3:54:00 time: 0.5633 data_time: 0.0405 memory: 23504 grad_norm: 3.0671 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0143 loss: 1.0143 2022/09/08 17:06:59 - mmengine - INFO - Epoch(train) [31][1240/1253] lr: 4.0000e-03 eta: 3:53:47 time: 0.4871 data_time: 0.0246 memory: 23504 grad_norm: 3.2163 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9235 loss: 0.9235 2022/09/08 17:07:04 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 17:07:04 - mmengine - INFO - Epoch(train) [31][1253/1253] lr: 4.0000e-03 eta: 3:53:47 time: 0.4324 data_time: 0.0166 memory: 23504 grad_norm: 3.2756 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 0.8927 loss: 0.8927 2022/09/08 17:07:28 - mmengine - INFO - Epoch(train) [32][20/1253] lr: 4.0000e-03 eta: 3:53:30 time: 1.1767 data_time: 0.4170 memory: 23504 grad_norm: 3.0775 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8794 loss: 0.8794 2022/09/08 17:07:41 - mmengine - INFO - Epoch(train) [32][40/1253] lr: 4.0000e-03 eta: 3:53:19 time: 0.6650 data_time: 0.0359 memory: 23504 grad_norm: 3.0741 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.8987 loss: 0.8987 2022/09/08 17:07:52 - mmengine - INFO - Epoch(train) [32][60/1253] lr: 4.0000e-03 eta: 3:53:07 time: 0.5559 data_time: 0.0351 memory: 23504 grad_norm: 3.0366 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.9632 loss: 0.9632 2022/09/08 17:08:03 - mmengine - INFO - Epoch(train) [32][80/1253] lr: 4.0000e-03 eta: 3:52:54 time: 0.5442 data_time: 0.0396 memory: 23504 grad_norm: 3.1093 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9624 loss: 0.9624 2022/09/08 17:08:16 - mmengine - INFO - Epoch(train) [32][100/1253] lr: 4.0000e-03 eta: 3:52:44 time: 0.6716 data_time: 0.0439 memory: 23504 grad_norm: 3.0852 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0198 loss: 1.0198 2022/09/08 17:08:27 - mmengine - INFO - Epoch(train) [32][120/1253] lr: 4.0000e-03 eta: 3:52:31 time: 0.5533 data_time: 0.0467 memory: 23504 grad_norm: 3.0112 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.8934 loss: 0.8934 2022/09/08 17:08:39 - mmengine - INFO - Epoch(train) [32][140/1253] lr: 4.0000e-03 eta: 3:52:20 time: 0.5856 data_time: 0.0465 memory: 23504 grad_norm: 3.1388 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.0051 loss: 1.0051 2022/09/08 17:08:49 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 17:08:51 - mmengine - INFO - Epoch(train) [32][160/1253] lr: 4.0000e-03 eta: 3:52:08 time: 0.5738 data_time: 0.0507 memory: 23504 grad_norm: 3.1057 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.0044 loss: 1.0044 2022/09/08 17:09:02 - mmengine - INFO - Epoch(train) [32][180/1253] lr: 4.0000e-03 eta: 3:51:55 time: 0.5470 data_time: 0.0402 memory: 23504 grad_norm: 3.0945 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 0.9235 loss: 0.9235 2022/09/08 17:09:13 - mmengine - INFO - Epoch(train) [32][200/1253] lr: 4.0000e-03 eta: 3:51:43 time: 0.5650 data_time: 0.0423 memory: 23504 grad_norm: 3.1160 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0040 loss: 1.0040 2022/09/08 17:09:25 - mmengine - INFO - Epoch(train) [32][220/1253] lr: 4.0000e-03 eta: 3:51:31 time: 0.5794 data_time: 0.0414 memory: 23504 grad_norm: 3.1196 top1_acc: 0.7083 top5_acc: 0.7500 loss_cls: 1.0375 loss: 1.0375 2022/09/08 17:09:38 - mmengine - INFO - Epoch(train) [32][240/1253] lr: 4.0000e-03 eta: 3:51:20 time: 0.6532 data_time: 0.0554 memory: 23504 grad_norm: 3.0877 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9888 loss: 0.9888 2022/09/08 17:09:49 - mmengine - INFO - Epoch(train) [32][260/1253] lr: 4.0000e-03 eta: 3:51:08 time: 0.5567 data_time: 0.0311 memory: 23504 grad_norm: 3.1535 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9092 loss: 0.9092 2022/09/08 17:10:00 - mmengine - INFO - Epoch(train) [32][280/1253] lr: 4.0000e-03 eta: 3:50:56 time: 0.5700 data_time: 0.0393 memory: 23504 grad_norm: 3.0899 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 1.0393 loss: 1.0393 2022/09/08 17:10:12 - mmengine - INFO - Epoch(train) [32][300/1253] lr: 4.0000e-03 eta: 3:50:45 time: 0.6056 data_time: 0.0367 memory: 23504 grad_norm: 3.0780 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9522 loss: 0.9522 2022/09/08 17:10:25 - mmengine - INFO - Epoch(train) [32][320/1253] lr: 4.0000e-03 eta: 3:50:34 time: 0.6403 data_time: 0.1055 memory: 23504 grad_norm: 3.0698 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.9619 loss: 0.9619 2022/09/08 17:10:37 - mmengine - INFO - Epoch(train) [32][340/1253] lr: 4.0000e-03 eta: 3:50:22 time: 0.5796 data_time: 0.0347 memory: 23504 grad_norm: 3.1177 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9329 loss: 0.9329 2022/09/08 17:10:48 - mmengine - INFO - Epoch(train) [32][360/1253] lr: 4.0000e-03 eta: 3:50:09 time: 0.5543 data_time: 0.0323 memory: 23504 grad_norm: 3.1634 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.0048 loss: 1.0048 2022/09/08 17:11:00 - mmengine - INFO - Epoch(train) [32][380/1253] lr: 4.0000e-03 eta: 3:49:58 time: 0.6292 data_time: 0.0385 memory: 23504 grad_norm: 3.0368 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9378 loss: 0.9378 2022/09/08 17:11:13 - mmengine - INFO - Epoch(train) [32][400/1253] lr: 4.0000e-03 eta: 3:49:47 time: 0.6078 data_time: 0.0417 memory: 23504 grad_norm: 3.0629 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.9895 loss: 0.9895 2022/09/08 17:11:26 - mmengine - INFO - Epoch(train) [32][420/1253] lr: 4.0000e-03 eta: 3:49:36 time: 0.6850 data_time: 0.1457 memory: 23504 grad_norm: 3.1097 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 0.9748 loss: 0.9748 2022/09/08 17:11:37 - mmengine - INFO - Epoch(train) [32][440/1253] lr: 4.0000e-03 eta: 3:49:24 time: 0.5439 data_time: 0.0298 memory: 23504 grad_norm: 3.1028 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 0.9120 loss: 0.9120 2022/09/08 17:11:48 - mmengine - INFO - Epoch(train) [32][460/1253] lr: 4.0000e-03 eta: 3:49:11 time: 0.5495 data_time: 0.0400 memory: 23504 grad_norm: 3.0831 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.9904 loss: 0.9904 2022/09/08 17:12:00 - mmengine - INFO - Epoch(train) [32][480/1253] lr: 4.0000e-03 eta: 3:49:00 time: 0.6017 data_time: 0.0862 memory: 23504 grad_norm: 3.2256 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9771 loss: 0.9771 2022/09/08 17:12:11 - mmengine - INFO - Epoch(train) [32][500/1253] lr: 4.0000e-03 eta: 3:48:48 time: 0.5622 data_time: 0.0382 memory: 23504 grad_norm: 3.0839 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8695 loss: 0.8695 2022/09/08 17:12:23 - mmengine - INFO - Epoch(train) [32][520/1253] lr: 4.0000e-03 eta: 3:48:36 time: 0.5994 data_time: 0.0457 memory: 23504 grad_norm: 3.1690 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9826 loss: 0.9826 2022/09/08 17:12:35 - mmengine - INFO - Epoch(train) [32][540/1253] lr: 4.0000e-03 eta: 3:48:24 time: 0.5898 data_time: 0.0461 memory: 23504 grad_norm: 3.1488 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.8991 loss: 0.8991 2022/09/08 17:12:47 - mmengine - INFO - Epoch(train) [32][560/1253] lr: 4.0000e-03 eta: 3:48:12 time: 0.5813 data_time: 0.0477 memory: 23504 grad_norm: 3.1356 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.1177 loss: 1.1177 2022/09/08 17:12:58 - mmengine - INFO - Epoch(train) [32][580/1253] lr: 4.0000e-03 eta: 3:48:00 time: 0.5741 data_time: 0.0442 memory: 23504 grad_norm: 3.1965 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.1023 loss: 1.1023 2022/09/08 17:13:10 - mmengine - INFO - Epoch(train) [32][600/1253] lr: 4.0000e-03 eta: 3:47:49 time: 0.5976 data_time: 0.0278 memory: 23504 grad_norm: 3.0972 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.9922 loss: 0.9922 2022/09/08 17:13:25 - mmengine - INFO - Epoch(train) [32][620/1253] lr: 4.0000e-03 eta: 3:47:39 time: 0.7293 data_time: 0.0391 memory: 23504 grad_norm: 2.9899 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.8873 loss: 0.8873 2022/09/08 17:13:37 - mmengine - INFO - Epoch(train) [32][640/1253] lr: 4.0000e-03 eta: 3:47:27 time: 0.6058 data_time: 0.0330 memory: 23504 grad_norm: 3.1956 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.0382 loss: 1.0382 2022/09/08 17:13:49 - mmengine - INFO - Epoch(train) [32][660/1253] lr: 4.0000e-03 eta: 3:47:15 time: 0.5850 data_time: 0.0378 memory: 23504 grad_norm: 3.0670 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9038 loss: 0.9038 2022/09/08 17:14:00 - mmengine - INFO - Epoch(train) [32][680/1253] lr: 4.0000e-03 eta: 3:47:03 time: 0.5447 data_time: 0.0327 memory: 23504 grad_norm: 3.1002 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 0.9817 loss: 0.9817 2022/09/08 17:14:11 - mmengine - INFO - Epoch(train) [32][700/1253] lr: 4.0000e-03 eta: 3:46:51 time: 0.5799 data_time: 0.0459 memory: 23504 grad_norm: 3.1152 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9918 loss: 0.9918 2022/09/08 17:14:23 - mmengine - INFO - Epoch(train) [32][720/1253] lr: 4.0000e-03 eta: 3:46:39 time: 0.6091 data_time: 0.0479 memory: 23504 grad_norm: 3.0784 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8610 loss: 0.8610 2022/09/08 17:14:36 - mmengine - INFO - Epoch(train) [32][740/1253] lr: 4.0000e-03 eta: 3:46:28 time: 0.6135 data_time: 0.0404 memory: 23504 grad_norm: 3.1657 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0545 loss: 1.0545 2022/09/08 17:14:49 - mmengine - INFO - Epoch(train) [32][760/1253] lr: 4.0000e-03 eta: 3:46:17 time: 0.6538 data_time: 0.0336 memory: 23504 grad_norm: 3.1331 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9216 loss: 0.9216 2022/09/08 17:15:00 - mmengine - INFO - Epoch(train) [32][780/1253] lr: 4.0000e-03 eta: 3:46:05 time: 0.5616 data_time: 0.0373 memory: 23504 grad_norm: 3.0953 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9971 loss: 0.9971 2022/09/08 17:15:11 - mmengine - INFO - Epoch(train) [32][800/1253] lr: 4.0000e-03 eta: 3:45:53 time: 0.5435 data_time: 0.0409 memory: 23504 grad_norm: 3.0959 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.0170 loss: 1.0170 2022/09/08 17:15:22 - mmengine - INFO - Epoch(train) [32][820/1253] lr: 4.0000e-03 eta: 3:45:40 time: 0.5563 data_time: 0.0476 memory: 23504 grad_norm: 3.0975 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0285 loss: 1.0285 2022/09/08 17:15:34 - mmengine - INFO - Epoch(train) [32][840/1253] lr: 4.0000e-03 eta: 3:45:29 time: 0.6159 data_time: 0.0504 memory: 23504 grad_norm: 3.1806 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9352 loss: 0.9352 2022/09/08 17:15:47 - mmengine - INFO - Epoch(train) [32][860/1253] lr: 4.0000e-03 eta: 3:45:17 time: 0.6248 data_time: 0.1113 memory: 23504 grad_norm: 3.1263 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.9681 loss: 0.9681 2022/09/08 17:15:59 - mmengine - INFO - Epoch(train) [32][880/1253] lr: 4.0000e-03 eta: 3:45:06 time: 0.6271 data_time: 0.0259 memory: 23504 grad_norm: 3.0568 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9176 loss: 0.9176 2022/09/08 17:16:10 - mmengine - INFO - Epoch(train) [32][900/1253] lr: 4.0000e-03 eta: 3:44:54 time: 0.5567 data_time: 0.0302 memory: 23504 grad_norm: 3.1198 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9162 loss: 0.9162 2022/09/08 17:16:22 - mmengine - INFO - Epoch(train) [32][920/1253] lr: 4.0000e-03 eta: 3:44:42 time: 0.5566 data_time: 0.0471 memory: 23504 grad_norm: 3.1533 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9311 loss: 0.9311 2022/09/08 17:16:33 - mmengine - INFO - Epoch(train) [32][940/1253] lr: 4.0000e-03 eta: 3:44:30 time: 0.5863 data_time: 0.0419 memory: 23504 grad_norm: 3.2097 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8910 loss: 0.8910 2022/09/08 17:16:45 - mmengine - INFO - Epoch(train) [32][960/1253] lr: 4.0000e-03 eta: 3:44:18 time: 0.5783 data_time: 0.0401 memory: 23504 grad_norm: 3.1714 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9306 loss: 0.9306 2022/09/08 17:16:56 - mmengine - INFO - Epoch(train) [32][980/1253] lr: 4.0000e-03 eta: 3:44:06 time: 0.5753 data_time: 0.0361 memory: 23504 grad_norm: 3.1638 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9340 loss: 0.9340 2022/09/08 17:17:08 - mmengine - INFO - Epoch(train) [32][1000/1253] lr: 4.0000e-03 eta: 3:43:54 time: 0.5740 data_time: 0.0482 memory: 23504 grad_norm: 3.1694 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9666 loss: 0.9666 2022/09/08 17:17:19 - mmengine - INFO - Epoch(train) [32][1020/1253] lr: 4.0000e-03 eta: 3:43:42 time: 0.5748 data_time: 0.0425 memory: 23504 grad_norm: 3.0942 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9993 loss: 0.9993 2022/09/08 17:17:32 - mmengine - INFO - Epoch(train) [32][1040/1253] lr: 4.0000e-03 eta: 3:43:31 time: 0.6110 data_time: 0.0503 memory: 23504 grad_norm: 3.1170 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9551 loss: 0.9551 2022/09/08 17:17:46 - mmengine - INFO - Epoch(train) [32][1060/1253] lr: 4.0000e-03 eta: 3:43:21 time: 0.7414 data_time: 0.0352 memory: 23504 grad_norm: 3.1432 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 1.0411 loss: 1.0411 2022/09/08 17:17:58 - mmengine - INFO - Epoch(train) [32][1080/1253] lr: 4.0000e-03 eta: 3:43:09 time: 0.5552 data_time: 0.0279 memory: 23504 grad_norm: 3.1285 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.9228 loss: 0.9228 2022/09/08 17:18:08 - mmengine - INFO - Epoch(train) [32][1100/1253] lr: 4.0000e-03 eta: 3:42:56 time: 0.5448 data_time: 0.0263 memory: 23504 grad_norm: 3.0525 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9330 loss: 0.9330 2022/09/08 17:18:20 - mmengine - INFO - Epoch(train) [32][1120/1253] lr: 4.0000e-03 eta: 3:42:44 time: 0.5775 data_time: 0.0442 memory: 23504 grad_norm: 3.1672 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 1.1397 loss: 1.1397 2022/09/08 17:18:34 - mmengine - INFO - Epoch(train) [32][1140/1253] lr: 4.0000e-03 eta: 3:42:34 time: 0.7068 data_time: 0.0328 memory: 23504 grad_norm: 3.1146 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8376 loss: 0.8376 2022/09/08 17:18:44 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 17:18:46 - mmengine - INFO - Epoch(train) [32][1160/1253] lr: 4.0000e-03 eta: 3:42:22 time: 0.5921 data_time: 0.0750 memory: 23504 grad_norm: 3.0993 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.0844 loss: 1.0844 2022/09/08 17:18:57 - mmengine - INFO - Epoch(train) [32][1180/1253] lr: 4.0000e-03 eta: 3:42:10 time: 0.5618 data_time: 0.0418 memory: 23504 grad_norm: 3.1602 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 1.0630 loss: 1.0630 2022/09/08 17:19:09 - mmengine - INFO - Epoch(train) [32][1200/1253] lr: 4.0000e-03 eta: 3:41:58 time: 0.5667 data_time: 0.0450 memory: 23504 grad_norm: 3.1121 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 1.0326 loss: 1.0326 2022/09/08 17:19:21 - mmengine - INFO - Epoch(train) [32][1220/1253] lr: 4.0000e-03 eta: 3:41:46 time: 0.5967 data_time: 0.0353 memory: 23504 grad_norm: 3.1730 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.0801 loss: 1.0801 2022/09/08 17:19:30 - mmengine - INFO - Epoch(train) [32][1240/1253] lr: 4.0000e-03 eta: 3:41:33 time: 0.4755 data_time: 0.0243 memory: 23504 grad_norm: 3.0869 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 0.9512 loss: 0.9512 2022/09/08 17:19:36 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 17:19:36 - mmengine - INFO - Epoch(train) [32][1253/1253] lr: 4.0000e-03 eta: 3:41:33 time: 0.4361 data_time: 0.0160 memory: 23504 grad_norm: 3.3101 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.0201 loss: 1.0201 2022/09/08 17:20:01 - mmengine - INFO - Epoch(train) [33][20/1253] lr: 4.0000e-03 eta: 3:41:17 time: 1.2867 data_time: 0.4559 memory: 23504 grad_norm: 3.0503 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9872 loss: 0.9872 2022/09/08 17:20:12 - mmengine - INFO - Epoch(train) [33][40/1253] lr: 4.0000e-03 eta: 3:41:05 time: 0.5331 data_time: 0.0327 memory: 23504 grad_norm: 3.0543 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8382 loss: 0.8382 2022/09/08 17:20:23 - mmengine - INFO - Epoch(train) [33][60/1253] lr: 4.0000e-03 eta: 3:40:53 time: 0.5472 data_time: 0.0312 memory: 23504 grad_norm: 3.0643 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9355 loss: 0.9355 2022/09/08 17:20:34 - mmengine - INFO - Epoch(train) [33][80/1253] lr: 4.0000e-03 eta: 3:40:40 time: 0.5530 data_time: 0.0427 memory: 23504 grad_norm: 3.1352 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 0.9917 loss: 0.9917 2022/09/08 17:20:46 - mmengine - INFO - Epoch(train) [33][100/1253] lr: 4.0000e-03 eta: 3:40:29 time: 0.5913 data_time: 0.0492 memory: 23504 grad_norm: 3.2147 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.0607 loss: 1.0607 2022/09/08 17:20:57 - mmengine - INFO - Epoch(train) [33][120/1253] lr: 4.0000e-03 eta: 3:40:17 time: 0.5803 data_time: 0.0428 memory: 23504 grad_norm: 3.1976 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 1.0479 loss: 1.0479 2022/09/08 17:21:09 - mmengine - INFO - Epoch(train) [33][140/1253] lr: 4.0000e-03 eta: 3:40:05 time: 0.5803 data_time: 0.0466 memory: 23504 grad_norm: 3.1240 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9142 loss: 0.9142 2022/09/08 17:21:21 - mmengine - INFO - Epoch(train) [33][160/1253] lr: 4.0000e-03 eta: 3:39:53 time: 0.5814 data_time: 0.0562 memory: 23504 grad_norm: 3.1360 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9702 loss: 0.9702 2022/09/08 17:21:32 - mmengine - INFO - Epoch(train) [33][180/1253] lr: 4.0000e-03 eta: 3:39:41 time: 0.5619 data_time: 0.0462 memory: 23504 grad_norm: 3.0697 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8784 loss: 0.8784 2022/09/08 17:21:46 - mmengine - INFO - Epoch(train) [33][200/1253] lr: 4.0000e-03 eta: 3:39:30 time: 0.6975 data_time: 0.0437 memory: 23504 grad_norm: 3.0510 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8666 loss: 0.8666 2022/09/08 17:21:57 - mmengine - INFO - Epoch(train) [33][220/1253] lr: 4.0000e-03 eta: 3:39:18 time: 0.5583 data_time: 0.0436 memory: 23504 grad_norm: 3.0249 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9537 loss: 0.9537 2022/09/08 17:22:10 - mmengine - INFO - Epoch(train) [33][240/1253] lr: 4.0000e-03 eta: 3:39:07 time: 0.6220 data_time: 0.0431 memory: 23504 grad_norm: 3.1103 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9458 loss: 0.9458 2022/09/08 17:22:22 - mmengine - INFO - Epoch(train) [33][260/1253] lr: 4.0000e-03 eta: 3:38:55 time: 0.6238 data_time: 0.0367 memory: 23504 grad_norm: 3.2007 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.9474 loss: 0.9474 2022/09/08 17:22:33 - mmengine - INFO - Epoch(train) [33][280/1253] lr: 4.0000e-03 eta: 3:38:43 time: 0.5624 data_time: 0.0302 memory: 23504 grad_norm: 3.1793 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.0439 loss: 1.0439 2022/09/08 17:22:45 - mmengine - INFO - Epoch(train) [33][300/1253] lr: 4.0000e-03 eta: 3:38:31 time: 0.5714 data_time: 0.0505 memory: 23504 grad_norm: 3.2221 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 0.9931 loss: 0.9931 2022/09/08 17:22:59 - mmengine - INFO - Epoch(train) [33][320/1253] lr: 4.0000e-03 eta: 3:38:21 time: 0.7113 data_time: 0.2085 memory: 23504 grad_norm: 3.1391 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.9252 loss: 0.9252 2022/09/08 17:23:10 - mmengine - INFO - Epoch(train) [33][340/1253] lr: 4.0000e-03 eta: 3:38:09 time: 0.5426 data_time: 0.0258 memory: 23504 grad_norm: 3.1564 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8648 loss: 0.8648 2022/09/08 17:23:21 - mmengine - INFO - Epoch(train) [33][360/1253] lr: 4.0000e-03 eta: 3:37:57 time: 0.5629 data_time: 0.0341 memory: 23504 grad_norm: 3.0959 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9195 loss: 0.9195 2022/09/08 17:23:33 - mmengine - INFO - Epoch(train) [33][380/1253] lr: 4.0000e-03 eta: 3:37:45 time: 0.5963 data_time: 0.0489 memory: 23504 grad_norm: 3.1417 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9483 loss: 0.9483 2022/09/08 17:23:44 - mmengine - INFO - Epoch(train) [33][400/1253] lr: 4.0000e-03 eta: 3:37:33 time: 0.5671 data_time: 0.0436 memory: 23504 grad_norm: 3.2140 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9558 loss: 0.9558 2022/09/08 17:23:56 - mmengine - INFO - Epoch(train) [33][420/1253] lr: 4.0000e-03 eta: 3:37:21 time: 0.5704 data_time: 0.0444 memory: 23504 grad_norm: 3.1675 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.0643 loss: 1.0643 2022/09/08 17:24:07 - mmengine - INFO - Epoch(train) [33][440/1253] lr: 4.0000e-03 eta: 3:37:09 time: 0.5758 data_time: 0.0394 memory: 23504 grad_norm: 3.1824 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9012 loss: 0.9012 2022/09/08 17:24:19 - mmengine - INFO - Epoch(train) [33][460/1253] lr: 4.0000e-03 eta: 3:36:57 time: 0.5820 data_time: 0.0481 memory: 23504 grad_norm: 3.1477 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9402 loss: 0.9402 2022/09/08 17:24:31 - mmengine - INFO - Epoch(train) [33][480/1253] lr: 4.0000e-03 eta: 3:36:46 time: 0.6068 data_time: 0.0393 memory: 23504 grad_norm: 3.2143 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9610 loss: 0.9610 2022/09/08 17:24:43 - mmengine - INFO - Epoch(train) [33][500/1253] lr: 4.0000e-03 eta: 3:36:34 time: 0.6068 data_time: 0.0507 memory: 23504 grad_norm: 3.2109 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 0.9727 loss: 0.9727 2022/09/08 17:24:55 - mmengine - INFO - Epoch(train) [33][520/1253] lr: 4.0000e-03 eta: 3:36:22 time: 0.5780 data_time: 0.0458 memory: 23504 grad_norm: 3.0625 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0203 loss: 1.0203 2022/09/08 17:25:06 - mmengine - INFO - Epoch(train) [33][540/1253] lr: 4.0000e-03 eta: 3:36:10 time: 0.5675 data_time: 0.0392 memory: 23504 grad_norm: 3.0993 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7589 loss: 0.7589 2022/09/08 17:25:18 - mmengine - INFO - Epoch(train) [33][560/1253] lr: 4.0000e-03 eta: 3:35:58 time: 0.6050 data_time: 0.0771 memory: 23504 grad_norm: 3.1663 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9132 loss: 0.9132 2022/09/08 17:25:29 - mmengine - INFO - Epoch(train) [33][580/1253] lr: 4.0000e-03 eta: 3:35:46 time: 0.5544 data_time: 0.0492 memory: 23504 grad_norm: 3.1437 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.8592 loss: 0.8592 2022/09/08 17:25:41 - mmengine - INFO - Epoch(train) [33][600/1253] lr: 4.0000e-03 eta: 3:35:34 time: 0.5929 data_time: 0.0413 memory: 23504 grad_norm: 3.1651 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9541 loss: 0.9541 2022/09/08 17:25:52 - mmengine - INFO - Epoch(train) [33][620/1253] lr: 4.0000e-03 eta: 3:35:22 time: 0.5607 data_time: 0.0437 memory: 23504 grad_norm: 3.2442 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9360 loss: 0.9360 2022/09/08 17:26:04 - mmengine - INFO - Epoch(train) [33][640/1253] lr: 4.0000e-03 eta: 3:35:11 time: 0.5848 data_time: 0.0586 memory: 23504 grad_norm: 3.1315 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.7158 loss: 0.7158 2022/09/08 17:26:17 - mmengine - INFO - Epoch(train) [33][660/1253] lr: 4.0000e-03 eta: 3:34:59 time: 0.6274 data_time: 0.0423 memory: 23504 grad_norm: 3.1623 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9738 loss: 0.9738 2022/09/08 17:26:28 - mmengine - INFO - Epoch(train) [33][680/1253] lr: 4.0000e-03 eta: 3:34:47 time: 0.5812 data_time: 0.0405 memory: 23504 grad_norm: 3.1926 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 0.9929 loss: 0.9929 2022/09/08 17:26:41 - mmengine - INFO - Epoch(train) [33][700/1253] lr: 4.0000e-03 eta: 3:34:36 time: 0.6261 data_time: 0.0842 memory: 23504 grad_norm: 3.2281 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.9544 loss: 0.9544 2022/09/08 17:26:52 - mmengine - INFO - Epoch(train) [33][720/1253] lr: 4.0000e-03 eta: 3:34:24 time: 0.5643 data_time: 0.0302 memory: 23504 grad_norm: 3.1225 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.8912 loss: 0.8912 2022/09/08 17:27:04 - mmengine - INFO - Epoch(train) [33][740/1253] lr: 4.0000e-03 eta: 3:34:12 time: 0.5878 data_time: 0.0546 memory: 23504 grad_norm: 3.1288 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 0.9715 loss: 0.9715 2022/09/08 17:27:15 - mmengine - INFO - Epoch(train) [33][760/1253] lr: 4.0000e-03 eta: 3:34:00 time: 0.5654 data_time: 0.0330 memory: 23504 grad_norm: 3.2587 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.0287 loss: 1.0287 2022/09/08 17:27:27 - mmengine - INFO - Epoch(train) [33][780/1253] lr: 4.0000e-03 eta: 3:33:48 time: 0.5697 data_time: 0.0380 memory: 23504 grad_norm: 3.1316 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8932 loss: 0.8932 2022/09/08 17:27:38 - mmengine - INFO - Epoch(train) [33][800/1253] lr: 4.0000e-03 eta: 3:33:36 time: 0.5842 data_time: 0.0316 memory: 23504 grad_norm: 3.1978 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.0506 loss: 1.0506 2022/09/08 17:27:51 - mmengine - INFO - Epoch(train) [33][820/1253] lr: 4.0000e-03 eta: 3:33:25 time: 0.6331 data_time: 0.0583 memory: 23504 grad_norm: 3.2412 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0609 loss: 1.0609 2022/09/08 17:28:03 - mmengine - INFO - Epoch(train) [33][840/1253] lr: 4.0000e-03 eta: 3:33:13 time: 0.6018 data_time: 0.0316 memory: 23504 grad_norm: 3.2290 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9551 loss: 0.9551 2022/09/08 17:28:15 - mmengine - INFO - Epoch(train) [33][860/1253] lr: 4.0000e-03 eta: 3:33:02 time: 0.6058 data_time: 0.0317 memory: 23504 grad_norm: 3.1778 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.9961 loss: 0.9961 2022/09/08 17:28:31 - mmengine - INFO - Epoch(train) [33][880/1253] lr: 4.0000e-03 eta: 3:32:52 time: 0.7793 data_time: 0.0214 memory: 23504 grad_norm: 3.1035 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 0.9576 loss: 0.9576 2022/09/08 17:28:42 - mmengine - INFO - Epoch(train) [33][900/1253] lr: 4.0000e-03 eta: 3:32:40 time: 0.5546 data_time: 0.0343 memory: 23504 grad_norm: 3.1659 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9600 loss: 0.9600 2022/09/08 17:28:44 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 17:28:53 - mmengine - INFO - Epoch(train) [33][920/1253] lr: 4.0000e-03 eta: 3:32:28 time: 0.5568 data_time: 0.0422 memory: 23504 grad_norm: 3.1793 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0425 loss: 1.0425 2022/09/08 17:29:04 - mmengine - INFO - Epoch(train) [33][940/1253] lr: 4.0000e-03 eta: 3:32:16 time: 0.5692 data_time: 0.0408 memory: 23504 grad_norm: 3.2542 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9506 loss: 0.9506 2022/09/08 17:29:17 - mmengine - INFO - Epoch(train) [33][960/1253] lr: 4.0000e-03 eta: 3:32:04 time: 0.6181 data_time: 0.0492 memory: 23504 grad_norm: 3.1599 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.0279 loss: 1.0279 2022/09/08 17:29:28 - mmengine - INFO - Epoch(train) [33][980/1253] lr: 4.0000e-03 eta: 3:31:52 time: 0.5820 data_time: 0.0498 memory: 23504 grad_norm: 3.1569 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.9905 loss: 0.9905 2022/09/08 17:29:40 - mmengine - INFO - Epoch(train) [33][1000/1253] lr: 4.0000e-03 eta: 3:31:40 time: 0.5760 data_time: 0.0478 memory: 23504 grad_norm: 3.1651 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.8864 loss: 0.8864 2022/09/08 17:29:52 - mmengine - INFO - Epoch(train) [33][1020/1253] lr: 4.0000e-03 eta: 3:31:29 time: 0.6178 data_time: 0.0593 memory: 23504 grad_norm: 3.1796 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9108 loss: 0.9108 2022/09/08 17:30:04 - mmengine - INFO - Epoch(train) [33][1040/1253] lr: 4.0000e-03 eta: 3:31:17 time: 0.5660 data_time: 0.0461 memory: 23504 grad_norm: 3.1753 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9232 loss: 0.9232 2022/09/08 17:30:16 - mmengine - INFO - Epoch(train) [33][1060/1253] lr: 4.0000e-03 eta: 3:31:06 time: 0.6384 data_time: 0.0405 memory: 23504 grad_norm: 3.1414 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 0.9070 loss: 0.9070 2022/09/08 17:30:28 - mmengine - INFO - Epoch(train) [33][1080/1253] lr: 4.0000e-03 eta: 3:30:54 time: 0.5798 data_time: 0.0378 memory: 23504 grad_norm: 3.2571 top1_acc: 0.6667 top5_acc: 0.7500 loss_cls: 1.0218 loss: 1.0218 2022/09/08 17:30:39 - mmengine - INFO - Epoch(train) [33][1100/1253] lr: 4.0000e-03 eta: 3:30:42 time: 0.5781 data_time: 0.0427 memory: 23504 grad_norm: 3.1671 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 0.8776 loss: 0.8776 2022/09/08 17:30:51 - mmengine - INFO - Epoch(train) [33][1120/1253] lr: 4.0000e-03 eta: 3:30:30 time: 0.5620 data_time: 0.0520 memory: 23504 grad_norm: 3.2042 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.0123 loss: 1.0123 2022/09/08 17:31:02 - mmengine - INFO - Epoch(train) [33][1140/1253] lr: 4.0000e-03 eta: 3:30:18 time: 0.5572 data_time: 0.0387 memory: 23504 grad_norm: 3.1347 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9543 loss: 0.9543 2022/09/08 17:31:13 - mmengine - INFO - Epoch(train) [33][1160/1253] lr: 4.0000e-03 eta: 3:30:05 time: 0.5584 data_time: 0.0411 memory: 23504 grad_norm: 3.1459 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.1744 loss: 1.1744 2022/09/08 17:31:26 - mmengine - INFO - Epoch(train) [33][1180/1253] lr: 4.0000e-03 eta: 3:29:54 time: 0.6669 data_time: 0.0639 memory: 23504 grad_norm: 3.1434 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 0.9432 loss: 0.9432 2022/09/08 17:31:38 - mmengine - INFO - Epoch(train) [33][1200/1253] lr: 4.0000e-03 eta: 3:29:43 time: 0.5765 data_time: 0.0276 memory: 23504 grad_norm: 3.2702 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9310 loss: 0.9310 2022/09/08 17:31:49 - mmengine - INFO - Epoch(train) [33][1220/1253] lr: 4.0000e-03 eta: 3:29:30 time: 0.5604 data_time: 0.0446 memory: 23504 grad_norm: 3.2180 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9763 loss: 0.9763 2022/09/08 17:31:59 - mmengine - INFO - Epoch(train) [33][1240/1253] lr: 4.0000e-03 eta: 3:29:18 time: 0.5023 data_time: 0.0382 memory: 23504 grad_norm: 3.1133 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9569 loss: 0.9569 2022/09/08 17:32:05 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 17:32:05 - mmengine - INFO - Epoch(train) [33][1253/1253] lr: 4.0000e-03 eta: 3:29:18 time: 0.4317 data_time: 0.0133 memory: 23504 grad_norm: 3.3178 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 0.9167 loss: 0.9167 2022/09/08 17:32:27 - mmengine - INFO - Epoch(train) [34][20/1253] lr: 4.0000e-03 eta: 3:29:00 time: 1.0968 data_time: 0.4972 memory: 23504 grad_norm: 3.1158 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9759 loss: 0.9759 2022/09/08 17:32:43 - mmengine - INFO - Epoch(train) [34][40/1253] lr: 4.0000e-03 eta: 3:28:50 time: 0.7907 data_time: 0.0958 memory: 23504 grad_norm: 3.0970 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9538 loss: 0.9538 2022/09/08 17:32:54 - mmengine - INFO - Epoch(train) [34][60/1253] lr: 4.0000e-03 eta: 3:28:38 time: 0.5903 data_time: 0.0305 memory: 23504 grad_norm: 3.1087 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9498 loss: 0.9498 2022/09/08 17:33:05 - mmengine - INFO - Epoch(train) [34][80/1253] lr: 4.0000e-03 eta: 3:28:26 time: 0.5511 data_time: 0.0337 memory: 23504 grad_norm: 3.1532 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8351 loss: 0.8351 2022/09/08 17:33:17 - mmengine - INFO - Epoch(train) [34][100/1253] lr: 4.0000e-03 eta: 3:28:14 time: 0.6050 data_time: 0.0498 memory: 23504 grad_norm: 3.1043 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.8879 loss: 0.8879 2022/09/08 17:33:29 - mmengine - INFO - Epoch(train) [34][120/1253] lr: 4.0000e-03 eta: 3:28:02 time: 0.5640 data_time: 0.0317 memory: 23504 grad_norm: 3.1391 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9433 loss: 0.9433 2022/09/08 17:33:41 - mmengine - INFO - Epoch(train) [34][140/1253] lr: 4.0000e-03 eta: 3:27:51 time: 0.6067 data_time: 0.0391 memory: 23504 grad_norm: 3.1963 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9898 loss: 0.9898 2022/09/08 17:33:52 - mmengine - INFO - Epoch(train) [34][160/1253] lr: 4.0000e-03 eta: 3:27:39 time: 0.5556 data_time: 0.0409 memory: 23504 grad_norm: 3.1794 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8969 loss: 0.8969 2022/09/08 17:34:03 - mmengine - INFO - Epoch(train) [34][180/1253] lr: 4.0000e-03 eta: 3:27:26 time: 0.5566 data_time: 0.0501 memory: 23504 grad_norm: 3.2026 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9712 loss: 0.9712 2022/09/08 17:34:16 - mmengine - INFO - Epoch(train) [34][200/1253] lr: 4.0000e-03 eta: 3:27:15 time: 0.6664 data_time: 0.0329 memory: 23504 grad_norm: 3.1087 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8572 loss: 0.8572 2022/09/08 17:34:28 - mmengine - INFO - Epoch(train) [34][220/1253] lr: 4.0000e-03 eta: 3:27:03 time: 0.5653 data_time: 0.0325 memory: 23504 grad_norm: 3.2063 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.0276 loss: 1.0276 2022/09/08 17:34:41 - mmengine - INFO - Epoch(train) [34][240/1253] lr: 4.0000e-03 eta: 3:26:52 time: 0.6579 data_time: 0.1536 memory: 23504 grad_norm: 3.1663 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.8580 loss: 0.8580 2022/09/08 17:34:52 - mmengine - INFO - Epoch(train) [34][260/1253] lr: 4.0000e-03 eta: 3:26:40 time: 0.5604 data_time: 0.0352 memory: 23504 grad_norm: 3.3005 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9858 loss: 0.9858 2022/09/08 17:35:04 - mmengine - INFO - Epoch(train) [34][280/1253] lr: 4.0000e-03 eta: 3:26:28 time: 0.5833 data_time: 0.0311 memory: 23504 grad_norm: 3.2535 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.0495 loss: 1.0495 2022/09/08 17:35:15 - mmengine - INFO - Epoch(train) [34][300/1253] lr: 4.0000e-03 eta: 3:26:16 time: 0.5603 data_time: 0.0533 memory: 23504 grad_norm: 3.1896 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9593 loss: 0.9593 2022/09/08 17:35:27 - mmengine - INFO - Epoch(train) [34][320/1253] lr: 4.0000e-03 eta: 3:26:04 time: 0.5816 data_time: 0.0449 memory: 23504 grad_norm: 3.2687 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9150 loss: 0.9150 2022/09/08 17:35:39 - mmengine - INFO - Epoch(train) [34][340/1253] lr: 4.0000e-03 eta: 3:25:53 time: 0.6389 data_time: 0.0702 memory: 23504 grad_norm: 3.1635 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8835 loss: 0.8835 2022/09/08 17:35:51 - mmengine - INFO - Epoch(train) [34][360/1253] lr: 4.0000e-03 eta: 3:25:41 time: 0.5771 data_time: 0.0316 memory: 23504 grad_norm: 3.2647 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8512 loss: 0.8512 2022/09/08 17:36:03 - mmengine - INFO - Epoch(train) [34][380/1253] lr: 4.0000e-03 eta: 3:25:30 time: 0.6189 data_time: 0.1028 memory: 23504 grad_norm: 3.2040 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8834 loss: 0.8834 2022/09/08 17:36:16 - mmengine - INFO - Epoch(train) [34][400/1253] lr: 4.0000e-03 eta: 3:25:18 time: 0.6192 data_time: 0.0842 memory: 23504 grad_norm: 3.1965 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8682 loss: 0.8682 2022/09/08 17:36:29 - mmengine - INFO - Epoch(train) [34][420/1253] lr: 4.0000e-03 eta: 3:25:07 time: 0.6786 data_time: 0.1547 memory: 23504 grad_norm: 3.1283 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.9001 loss: 0.9001 2022/09/08 17:36:40 - mmengine - INFO - Epoch(train) [34][440/1253] lr: 4.0000e-03 eta: 3:24:55 time: 0.5266 data_time: 0.0246 memory: 23504 grad_norm: 3.1624 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9266 loss: 0.9266 2022/09/08 17:36:51 - mmengine - INFO - Epoch(train) [34][460/1253] lr: 4.0000e-03 eta: 3:24:43 time: 0.5556 data_time: 0.0395 memory: 23504 grad_norm: 3.2704 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9668 loss: 0.9668 2022/09/08 17:37:03 - mmengine - INFO - Epoch(train) [34][480/1253] lr: 4.0000e-03 eta: 3:24:31 time: 0.5855 data_time: 0.0463 memory: 23504 grad_norm: 3.2041 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.9427 loss: 0.9427 2022/09/08 17:37:14 - mmengine - INFO - Epoch(train) [34][500/1253] lr: 4.0000e-03 eta: 3:24:19 time: 0.5787 data_time: 0.0394 memory: 23504 grad_norm: 3.1859 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.9229 loss: 0.9229 2022/09/08 17:37:26 - mmengine - INFO - Epoch(train) [34][520/1253] lr: 4.0000e-03 eta: 3:24:07 time: 0.5786 data_time: 0.0529 memory: 23504 grad_norm: 3.2239 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.9817 loss: 0.9817 2022/09/08 17:37:37 - mmengine - INFO - Epoch(train) [34][540/1253] lr: 4.0000e-03 eta: 3:23:55 time: 0.5716 data_time: 0.0379 memory: 23504 grad_norm: 3.3016 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9470 loss: 0.9470 2022/09/08 17:37:49 - mmengine - INFO - Epoch(train) [34][560/1253] lr: 4.0000e-03 eta: 3:23:43 time: 0.5798 data_time: 0.0481 memory: 23504 grad_norm: 3.2598 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9002 loss: 0.9002 2022/09/08 17:38:01 - mmengine - INFO - Epoch(train) [34][580/1253] lr: 4.0000e-03 eta: 3:23:31 time: 0.5774 data_time: 0.0405 memory: 23504 grad_norm: 3.1917 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9566 loss: 0.9566 2022/09/08 17:38:12 - mmengine - INFO - Epoch(train) [34][600/1253] lr: 4.0000e-03 eta: 3:23:19 time: 0.5557 data_time: 0.0470 memory: 23504 grad_norm: 3.2652 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8812 loss: 0.8812 2022/09/08 17:38:24 - mmengine - INFO - Epoch(train) [34][620/1253] lr: 4.0000e-03 eta: 3:23:08 time: 0.6104 data_time: 0.0710 memory: 23504 grad_norm: 3.2729 top1_acc: 0.5833 top5_acc: 0.9583 loss_cls: 1.0467 loss: 1.0467 2022/09/08 17:38:36 - mmengine - INFO - Epoch(train) [34][640/1253] lr: 4.0000e-03 eta: 3:22:56 time: 0.6309 data_time: 0.1146 memory: 23504 grad_norm: 3.2643 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.9472 loss: 0.9472 2022/09/08 17:38:42 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 17:38:48 - mmengine - INFO - Epoch(train) [34][660/1253] lr: 4.0000e-03 eta: 3:22:44 time: 0.5534 data_time: 0.0349 memory: 23504 grad_norm: 3.2447 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.0011 loss: 1.0011 2022/09/08 17:38:59 - mmengine - INFO - Epoch(train) [34][680/1253] lr: 4.0000e-03 eta: 3:22:32 time: 0.5956 data_time: 0.0529 memory: 23504 grad_norm: 3.3204 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.0035 loss: 1.0035 2022/09/08 17:39:11 - mmengine - INFO - Epoch(train) [34][700/1253] lr: 4.0000e-03 eta: 3:22:21 time: 0.5902 data_time: 0.0765 memory: 23504 grad_norm: 3.3151 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9992 loss: 0.9992 2022/09/08 17:39:25 - mmengine - INFO - Epoch(train) [34][720/1253] lr: 4.0000e-03 eta: 3:22:10 time: 0.6952 data_time: 0.0308 memory: 23504 grad_norm: 3.2768 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8183 loss: 0.8183 2022/09/08 17:39:36 - mmengine - INFO - Epoch(train) [34][740/1253] lr: 4.0000e-03 eta: 3:21:58 time: 0.5592 data_time: 0.0405 memory: 23504 grad_norm: 3.1664 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8270 loss: 0.8270 2022/09/08 17:39:48 - mmengine - INFO - Epoch(train) [34][760/1253] lr: 4.0000e-03 eta: 3:21:46 time: 0.5858 data_time: 0.0391 memory: 23504 grad_norm: 3.2592 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.9870 loss: 0.9870 2022/09/08 17:40:00 - mmengine - INFO - Epoch(train) [34][780/1253] lr: 4.0000e-03 eta: 3:21:34 time: 0.5826 data_time: 0.0383 memory: 23504 grad_norm: 3.2635 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9933 loss: 0.9933 2022/09/08 17:40:12 - mmengine - INFO - Epoch(train) [34][800/1253] lr: 4.0000e-03 eta: 3:21:22 time: 0.5920 data_time: 0.0600 memory: 23504 grad_norm: 3.2287 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 0.9394 loss: 0.9394 2022/09/08 17:40:23 - mmengine - INFO - Epoch(train) [34][820/1253] lr: 4.0000e-03 eta: 3:21:10 time: 0.5634 data_time: 0.0391 memory: 23504 grad_norm: 3.2467 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8122 loss: 0.8122 2022/09/08 17:40:35 - mmengine - INFO - Epoch(train) [34][840/1253] lr: 4.0000e-03 eta: 3:20:59 time: 0.5978 data_time: 0.0384 memory: 23504 grad_norm: 3.2431 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.0463 loss: 1.0463 2022/09/08 17:40:46 - mmengine - INFO - Epoch(train) [34][860/1253] lr: 4.0000e-03 eta: 3:20:47 time: 0.5716 data_time: 0.0452 memory: 23504 grad_norm: 3.2497 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.9153 loss: 0.9153 2022/09/08 17:40:58 - mmengine - INFO - Epoch(train) [34][880/1253] lr: 4.0000e-03 eta: 3:20:35 time: 0.5630 data_time: 0.0464 memory: 23504 grad_norm: 3.1682 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 0.9463 loss: 0.9463 2022/09/08 17:41:09 - mmengine - INFO - Epoch(train) [34][900/1253] lr: 4.0000e-03 eta: 3:20:23 time: 0.5616 data_time: 0.0377 memory: 23504 grad_norm: 3.2470 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9665 loss: 0.9665 2022/09/08 17:41:21 - mmengine - INFO - Epoch(train) [34][920/1253] lr: 4.0000e-03 eta: 3:20:11 time: 0.6196 data_time: 0.0344 memory: 23504 grad_norm: 3.2064 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.8902 loss: 0.8902 2022/09/08 17:41:32 - mmengine - INFO - Epoch(train) [34][940/1253] lr: 4.0000e-03 eta: 3:19:59 time: 0.5610 data_time: 0.0426 memory: 23504 grad_norm: 3.2052 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.0336 loss: 1.0336 2022/09/08 17:41:44 - mmengine - INFO - Epoch(train) [34][960/1253] lr: 4.0000e-03 eta: 3:19:47 time: 0.5881 data_time: 0.0417 memory: 23504 grad_norm: 3.2234 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.0145 loss: 1.0145 2022/09/08 17:41:56 - mmengine - INFO - Epoch(train) [34][980/1253] lr: 4.0000e-03 eta: 3:19:36 time: 0.6161 data_time: 0.0515 memory: 23504 grad_norm: 3.1789 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.9128 loss: 0.9128 2022/09/08 17:42:09 - mmengine - INFO - Epoch(train) [34][1000/1253] lr: 4.0000e-03 eta: 3:19:24 time: 0.6129 data_time: 0.0636 memory: 23504 grad_norm: 3.2365 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.9390 loss: 0.9390 2022/09/08 17:42:20 - mmengine - INFO - Epoch(train) [34][1020/1253] lr: 4.0000e-03 eta: 3:19:12 time: 0.5566 data_time: 0.0476 memory: 23504 grad_norm: 3.1896 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9051 loss: 0.9051 2022/09/08 17:42:31 - mmengine - INFO - Epoch(train) [34][1040/1253] lr: 4.0000e-03 eta: 3:19:00 time: 0.5504 data_time: 0.0476 memory: 23504 grad_norm: 3.2478 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9882 loss: 0.9882 2022/09/08 17:42:42 - mmengine - INFO - Epoch(train) [34][1060/1253] lr: 4.0000e-03 eta: 3:18:48 time: 0.5694 data_time: 0.0343 memory: 23504 grad_norm: 3.2296 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9375 loss: 0.9375 2022/09/08 17:42:55 - mmengine - INFO - Epoch(train) [34][1080/1253] lr: 4.0000e-03 eta: 3:18:37 time: 0.6585 data_time: 0.0516 memory: 23504 grad_norm: 3.2249 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.9821 loss: 0.9821 2022/09/08 17:43:08 - mmengine - INFO - Epoch(train) [34][1100/1253] lr: 4.0000e-03 eta: 3:18:25 time: 0.6094 data_time: 0.0338 memory: 23504 grad_norm: 3.3694 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.9642 loss: 0.9642 2022/09/08 17:43:18 - mmengine - INFO - Epoch(train) [34][1120/1253] lr: 4.0000e-03 eta: 3:18:13 time: 0.5368 data_time: 0.0341 memory: 23504 grad_norm: 3.2351 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9768 loss: 0.9768 2022/09/08 17:43:30 - mmengine - INFO - Epoch(train) [34][1140/1253] lr: 4.0000e-03 eta: 3:18:01 time: 0.5764 data_time: 0.0430 memory: 23504 grad_norm: 3.1650 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9271 loss: 0.9271 2022/09/08 17:43:43 - mmengine - INFO - Epoch(train) [34][1160/1253] lr: 4.0000e-03 eta: 3:17:50 time: 0.6399 data_time: 0.0415 memory: 23504 grad_norm: 3.2101 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 0.9400 loss: 0.9400 2022/09/08 17:43:54 - mmengine - INFO - Epoch(train) [34][1180/1253] lr: 4.0000e-03 eta: 3:17:38 time: 0.5757 data_time: 0.0404 memory: 23504 grad_norm: 3.2248 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 0.9616 loss: 0.9616 2022/09/08 17:44:06 - mmengine - INFO - Epoch(train) [34][1200/1253] lr: 4.0000e-03 eta: 3:17:26 time: 0.6032 data_time: 0.0657 memory: 23504 grad_norm: 3.2665 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9190 loss: 0.9190 2022/09/08 17:44:18 - mmengine - INFO - Epoch(train) [34][1220/1253] lr: 4.0000e-03 eta: 3:17:14 time: 0.5971 data_time: 0.0469 memory: 23504 grad_norm: 3.2853 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0106 loss: 1.0106 2022/09/08 17:44:28 - mmengine - INFO - Epoch(train) [34][1240/1253] lr: 4.0000e-03 eta: 3:17:02 time: 0.4823 data_time: 0.0263 memory: 23504 grad_norm: 3.1917 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9837 loss: 0.9837 2022/09/08 17:44:33 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 17:44:33 - mmengine - INFO - Epoch(train) [34][1253/1253] lr: 4.0000e-03 eta: 3:17:02 time: 0.4363 data_time: 0.0168 memory: 23504 grad_norm: 3.3955 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.0156 loss: 1.0156 2022/09/08 17:44:59 - mmengine - INFO - Epoch(train) [35][20/1253] lr: 4.0000e-03 eta: 3:16:45 time: 1.2589 data_time: 0.4644 memory: 23504 grad_norm: 3.1984 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9714 loss: 0.9714 2022/09/08 17:45:10 - mmengine - INFO - Epoch(train) [35][40/1253] lr: 4.0000e-03 eta: 3:16:33 time: 0.5452 data_time: 0.0290 memory: 23504 grad_norm: 3.1904 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0186 loss: 1.0186 2022/09/08 17:45:21 - mmengine - INFO - Epoch(train) [35][60/1253] lr: 4.0000e-03 eta: 3:16:21 time: 0.5886 data_time: 0.0420 memory: 23504 grad_norm: 3.2092 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.0538 loss: 1.0538 2022/09/08 17:45:34 - mmengine - INFO - Epoch(train) [35][80/1253] lr: 4.0000e-03 eta: 3:16:09 time: 0.6137 data_time: 0.0440 memory: 23504 grad_norm: 3.1945 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.8074 loss: 0.8074 2022/09/08 17:45:45 - mmengine - INFO - Epoch(train) [35][100/1253] lr: 4.0000e-03 eta: 3:15:57 time: 0.5811 data_time: 0.0426 memory: 23504 grad_norm: 3.1236 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8478 loss: 0.8478 2022/09/08 17:45:57 - mmengine - INFO - Epoch(train) [35][120/1253] lr: 4.0000e-03 eta: 3:15:46 time: 0.5887 data_time: 0.0426 memory: 23504 grad_norm: 3.1870 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8922 loss: 0.8922 2022/09/08 17:46:10 - mmengine - INFO - Epoch(train) [35][140/1253] lr: 4.0000e-03 eta: 3:15:34 time: 0.6440 data_time: 0.0393 memory: 23504 grad_norm: 3.2961 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.8920 loss: 0.8920 2022/09/08 17:46:21 - mmengine - INFO - Epoch(train) [35][160/1253] lr: 4.0000e-03 eta: 3:15:22 time: 0.5703 data_time: 0.0450 memory: 23504 grad_norm: 3.2508 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8951 loss: 0.8951 2022/09/08 17:46:33 - mmengine - INFO - Epoch(train) [35][180/1253] lr: 4.0000e-03 eta: 3:15:10 time: 0.5597 data_time: 0.0412 memory: 23504 grad_norm: 3.1807 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8298 loss: 0.8298 2022/09/08 17:46:44 - mmengine - INFO - Epoch(train) [35][200/1253] lr: 4.0000e-03 eta: 3:14:58 time: 0.5609 data_time: 0.0428 memory: 23504 grad_norm: 3.2920 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 0.8545 loss: 0.8545 2022/09/08 17:46:55 - mmengine - INFO - Epoch(train) [35][220/1253] lr: 4.0000e-03 eta: 3:14:46 time: 0.5650 data_time: 0.0476 memory: 23504 grad_norm: 3.1713 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9319 loss: 0.9319 2022/09/08 17:47:09 - mmengine - INFO - Epoch(train) [35][240/1253] lr: 4.0000e-03 eta: 3:14:35 time: 0.6775 data_time: 0.1483 memory: 23504 grad_norm: 3.1871 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 0.8953 loss: 0.8953 2022/09/08 17:47:20 - mmengine - INFO - Epoch(train) [35][260/1253] lr: 4.0000e-03 eta: 3:14:23 time: 0.5598 data_time: 0.0395 memory: 23504 grad_norm: 3.1796 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9198 loss: 0.9198 2022/09/08 17:47:31 - mmengine - INFO - Epoch(train) [35][280/1253] lr: 4.0000e-03 eta: 3:14:11 time: 0.5481 data_time: 0.0368 memory: 23504 grad_norm: 3.1190 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8911 loss: 0.8911 2022/09/08 17:47:42 - mmengine - INFO - Epoch(train) [35][300/1253] lr: 4.0000e-03 eta: 3:13:59 time: 0.5642 data_time: 0.0317 memory: 23504 grad_norm: 3.2262 top1_acc: 0.7500 top5_acc: 0.7917 loss_cls: 0.8352 loss: 0.8352 2022/09/08 17:47:57 - mmengine - INFO - Epoch(train) [35][320/1253] lr: 4.0000e-03 eta: 3:13:49 time: 0.7321 data_time: 0.0849 memory: 23504 grad_norm: 3.1445 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.8872 loss: 0.8872 2022/09/08 17:48:08 - mmengine - INFO - Epoch(train) [35][340/1253] lr: 4.0000e-03 eta: 3:13:37 time: 0.5614 data_time: 0.0475 memory: 23504 grad_norm: 3.1457 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.9294 loss: 0.9294 2022/09/08 17:48:19 - mmengine - INFO - Epoch(train) [35][360/1253] lr: 4.0000e-03 eta: 3:13:24 time: 0.5470 data_time: 0.0306 memory: 23504 grad_norm: 3.2169 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8908 loss: 0.8908 2022/09/08 17:48:31 - mmengine - INFO - Epoch(train) [35][380/1253] lr: 4.0000e-03 eta: 3:13:13 time: 0.5837 data_time: 0.0427 memory: 23504 grad_norm: 3.2645 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8391 loss: 0.8391 2022/09/08 17:48:44 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 17:48:45 - mmengine - INFO - Epoch(train) [35][400/1253] lr: 4.0000e-03 eta: 3:13:02 time: 0.7085 data_time: 0.0424 memory: 23504 grad_norm: 3.1812 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 1.0200 loss: 1.0200 2022/09/08 17:48:56 - mmengine - INFO - Epoch(train) [35][420/1253] lr: 4.0000e-03 eta: 3:12:50 time: 0.5674 data_time: 0.0384 memory: 23504 grad_norm: 3.1176 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.7873 loss: 0.7873 2022/09/08 17:49:07 - mmengine - INFO - Epoch(train) [35][440/1253] lr: 4.0000e-03 eta: 3:12:38 time: 0.5585 data_time: 0.0547 memory: 23504 grad_norm: 3.1889 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9220 loss: 0.9220 2022/09/08 17:49:19 - mmengine - INFO - Epoch(train) [35][460/1253] lr: 4.0000e-03 eta: 3:12:26 time: 0.5852 data_time: 0.0497 memory: 23504 grad_norm: 3.2820 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8798 loss: 0.8798 2022/09/08 17:49:30 - mmengine - INFO - Epoch(train) [35][480/1253] lr: 4.0000e-03 eta: 3:12:14 time: 0.5642 data_time: 0.0362 memory: 23504 grad_norm: 3.2511 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.8987 loss: 0.8987 2022/09/08 17:49:42 - mmengine - INFO - Epoch(train) [35][500/1253] lr: 4.0000e-03 eta: 3:12:02 time: 0.5968 data_time: 0.0506 memory: 23504 grad_norm: 3.2101 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.7658 loss: 0.7658 2022/09/08 17:49:54 - mmengine - INFO - Epoch(train) [35][520/1253] lr: 4.0000e-03 eta: 3:11:51 time: 0.6016 data_time: 0.0541 memory: 23504 grad_norm: 3.1834 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8973 loss: 0.8973 2022/09/08 17:50:06 - mmengine - INFO - Epoch(train) [35][540/1253] lr: 4.0000e-03 eta: 3:11:39 time: 0.5966 data_time: 0.0408 memory: 23504 grad_norm: 3.1947 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.7761 loss: 0.7761 2022/09/08 17:50:18 - mmengine - INFO - Epoch(train) [35][560/1253] lr: 4.0000e-03 eta: 3:11:27 time: 0.5836 data_time: 0.0401 memory: 23504 grad_norm: 3.2499 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 0.8360 loss: 0.8360 2022/09/08 17:50:29 - mmengine - INFO - Epoch(train) [35][580/1253] lr: 4.0000e-03 eta: 3:11:15 time: 0.5712 data_time: 0.0406 memory: 23504 grad_norm: 3.2285 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 0.9854 loss: 0.9854 2022/09/08 17:50:41 - mmengine - INFO - Epoch(train) [35][600/1253] lr: 4.0000e-03 eta: 3:11:03 time: 0.5813 data_time: 0.0521 memory: 23504 grad_norm: 3.2421 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8142 loss: 0.8142 2022/09/08 17:50:52 - mmengine - INFO - Epoch(train) [35][620/1253] lr: 4.0000e-03 eta: 3:10:51 time: 0.5691 data_time: 0.0371 memory: 23504 grad_norm: 3.2746 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.0627 loss: 1.0627 2022/09/08 17:51:05 - mmengine - INFO - Epoch(train) [35][640/1253] lr: 4.0000e-03 eta: 3:10:40 time: 0.6250 data_time: 0.0388 memory: 23504 grad_norm: 3.2015 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9699 loss: 0.9699 2022/09/08 17:51:16 - mmengine - INFO - Epoch(train) [35][660/1253] lr: 4.0000e-03 eta: 3:10:28 time: 0.5636 data_time: 0.0582 memory: 23504 grad_norm: 3.1739 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8665 loss: 0.8665 2022/09/08 17:51:31 - mmengine - INFO - Epoch(train) [35][680/1253] lr: 4.0000e-03 eta: 3:10:17 time: 0.7286 data_time: 0.0421 memory: 23504 grad_norm: 3.2663 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.9721 loss: 0.9721 2022/09/08 17:51:42 - mmengine - INFO - Epoch(train) [35][700/1253] lr: 4.0000e-03 eta: 3:10:05 time: 0.5751 data_time: 0.0477 memory: 23504 grad_norm: 3.2684 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.7920 loss: 0.7920 2022/09/08 17:51:54 - mmengine - INFO - Epoch(train) [35][720/1253] lr: 4.0000e-03 eta: 3:09:53 time: 0.5786 data_time: 0.0395 memory: 23504 grad_norm: 3.3164 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.0521 loss: 1.0521 2022/09/08 17:52:05 - mmengine - INFO - Epoch(train) [35][740/1253] lr: 4.0000e-03 eta: 3:09:41 time: 0.5417 data_time: 0.0446 memory: 23504 grad_norm: 3.3564 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8690 loss: 0.8690 2022/09/08 17:52:17 - mmengine - INFO - Epoch(train) [35][760/1253] lr: 4.0000e-03 eta: 3:09:29 time: 0.5997 data_time: 0.0793 memory: 23504 grad_norm: 3.2081 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9356 loss: 0.9356 2022/09/08 17:52:28 - mmengine - INFO - Epoch(train) [35][780/1253] lr: 4.0000e-03 eta: 3:09:17 time: 0.5658 data_time: 0.0419 memory: 23504 grad_norm: 3.1566 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.8716 loss: 0.8716 2022/09/08 17:52:40 - mmengine - INFO - Epoch(train) [35][800/1253] lr: 4.0000e-03 eta: 3:09:06 time: 0.5993 data_time: 0.0839 memory: 23504 grad_norm: 3.3210 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8503 loss: 0.8503 2022/09/08 17:52:51 - mmengine - INFO - Epoch(train) [35][820/1253] lr: 4.0000e-03 eta: 3:08:54 time: 0.5719 data_time: 0.0442 memory: 23504 grad_norm: 3.2981 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7581 loss: 0.7581 2022/09/08 17:53:03 - mmengine - INFO - Epoch(train) [35][840/1253] lr: 4.0000e-03 eta: 3:08:42 time: 0.5627 data_time: 0.0380 memory: 23504 grad_norm: 3.2088 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9146 loss: 0.9146 2022/09/08 17:53:15 - mmengine - INFO - Epoch(train) [35][860/1253] lr: 4.0000e-03 eta: 3:08:30 time: 0.6130 data_time: 0.0499 memory: 23504 grad_norm: 3.2636 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 0.9637 loss: 0.9637 2022/09/08 17:53:27 - mmengine - INFO - Epoch(train) [35][880/1253] lr: 4.0000e-03 eta: 3:08:18 time: 0.5800 data_time: 0.0477 memory: 23504 grad_norm: 3.2610 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7622 loss: 0.7622 2022/09/08 17:53:41 - mmengine - INFO - Epoch(train) [35][900/1253] lr: 4.0000e-03 eta: 3:08:08 time: 0.7386 data_time: 0.0338 memory: 23504 grad_norm: 3.2017 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9034 loss: 0.9034 2022/09/08 17:53:53 - mmengine - INFO - Epoch(train) [35][920/1253] lr: 4.0000e-03 eta: 3:07:56 time: 0.5744 data_time: 0.0682 memory: 23504 grad_norm: 3.2645 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.7584 loss: 0.7584 2022/09/08 17:54:04 - mmengine - INFO - Epoch(train) [35][940/1253] lr: 4.0000e-03 eta: 3:07:44 time: 0.5381 data_time: 0.0436 memory: 23504 grad_norm: 3.2331 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9993 loss: 0.9993 2022/09/08 17:54:16 - mmengine - INFO - Epoch(train) [35][960/1253] lr: 4.0000e-03 eta: 3:07:32 time: 0.5946 data_time: 0.0492 memory: 23504 grad_norm: 3.2724 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 0.9402 loss: 0.9402 2022/09/08 17:54:27 - mmengine - INFO - Epoch(train) [35][980/1253] lr: 4.0000e-03 eta: 3:07:20 time: 0.5713 data_time: 0.0415 memory: 23504 grad_norm: 3.2536 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9527 loss: 0.9527 2022/09/08 17:54:38 - mmengine - INFO - Epoch(train) [35][1000/1253] lr: 4.0000e-03 eta: 3:07:08 time: 0.5748 data_time: 0.0395 memory: 23504 grad_norm: 3.2532 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.9127 loss: 0.9127 2022/09/08 17:54:50 - mmengine - INFO - Epoch(train) [35][1020/1253] lr: 4.0000e-03 eta: 3:06:56 time: 0.5766 data_time: 0.0419 memory: 23504 grad_norm: 3.3241 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.0775 loss: 1.0775 2022/09/08 17:55:02 - mmengine - INFO - Epoch(train) [35][1040/1253] lr: 4.0000e-03 eta: 3:06:44 time: 0.5877 data_time: 0.0425 memory: 23504 grad_norm: 3.3100 top1_acc: 0.9583 top5_acc: 1.0000 loss_cls: 0.9641 loss: 0.9641 2022/09/08 17:55:13 - mmengine - INFO - Epoch(train) [35][1060/1253] lr: 4.0000e-03 eta: 3:06:32 time: 0.5533 data_time: 0.0431 memory: 23504 grad_norm: 3.3214 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9998 loss: 0.9998 2022/09/08 17:55:25 - mmengine - INFO - Epoch(train) [35][1080/1253] lr: 4.0000e-03 eta: 3:06:20 time: 0.5923 data_time: 0.0414 memory: 23504 grad_norm: 3.2512 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8980 loss: 0.8980 2022/09/08 17:55:36 - mmengine - INFO - Epoch(train) [35][1100/1253] lr: 4.0000e-03 eta: 3:06:09 time: 0.5881 data_time: 0.0449 memory: 23504 grad_norm: 3.3149 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8778 loss: 0.8778 2022/09/08 17:55:48 - mmengine - INFO - Epoch(train) [35][1120/1253] lr: 4.0000e-03 eta: 3:05:57 time: 0.5996 data_time: 0.0538 memory: 23504 grad_norm: 3.2360 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8727 loss: 0.8727 2022/09/08 17:56:04 - mmengine - INFO - Epoch(train) [35][1140/1253] lr: 4.0000e-03 eta: 3:05:47 time: 0.7666 data_time: 0.2246 memory: 23504 grad_norm: 3.3041 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.0532 loss: 1.0532 2022/09/08 17:56:15 - mmengine - INFO - Epoch(train) [35][1160/1253] lr: 4.0000e-03 eta: 3:05:34 time: 0.5383 data_time: 0.0255 memory: 23504 grad_norm: 3.3050 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.9412 loss: 0.9412 2022/09/08 17:56:26 - mmengine - INFO - Epoch(train) [35][1180/1253] lr: 4.0000e-03 eta: 3:05:22 time: 0.5518 data_time: 0.0321 memory: 23504 grad_norm: 3.2015 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9229 loss: 0.9229 2022/09/08 17:56:37 - mmengine - INFO - Epoch(train) [35][1200/1253] lr: 4.0000e-03 eta: 3:05:11 time: 0.5918 data_time: 0.0719 memory: 23504 grad_norm: 3.3421 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0678 loss: 1.0678 2022/09/08 17:56:49 - mmengine - INFO - Epoch(train) [35][1220/1253] lr: 4.0000e-03 eta: 3:04:59 time: 0.5694 data_time: 0.0438 memory: 23504 grad_norm: 3.2506 top1_acc: 0.3750 top5_acc: 0.8333 loss_cls: 0.9766 loss: 0.9766 2022/09/08 17:56:59 - mmengine - INFO - Epoch(train) [35][1240/1253] lr: 4.0000e-03 eta: 3:04:46 time: 0.4892 data_time: 0.0229 memory: 23504 grad_norm: 3.2805 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 0.9861 loss: 0.9861 2022/09/08 17:57:04 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 17:57:04 - mmengine - INFO - Epoch(train) [35][1253/1253] lr: 4.0000e-03 eta: 3:04:46 time: 0.4427 data_time: 0.0159 memory: 23504 grad_norm: 3.4339 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 0.9122 loss: 0.9122 2022/09/08 17:57:32 - mmengine - INFO - Epoch(val) [35][20/104] eta: 0:01:56 time: 1.3886 data_time: 1.2418 memory: 2699 2022/09/08 17:57:43 - mmengine - INFO - Epoch(val) [35][40/104] eta: 0:00:33 time: 0.5291 data_time: 0.3914 memory: 2699 2022/09/08 17:57:51 - mmengine - INFO - Epoch(val) [35][60/104] eta: 0:00:17 time: 0.4056 data_time: 0.2681 memory: 2699 2022/09/08 17:58:03 - mmengine - INFO - Epoch(val) [35][80/104] eta: 0:00:14 time: 0.5873 data_time: 0.4561 memory: 2699 2022/09/08 17:58:12 - mmengine - INFO - Epoch(val) [35][100/104] eta: 0:00:01 time: 0.4494 data_time: 0.3303 memory: 2699 2022/09/08 17:58:18 - mmengine - INFO - Epoch(val) [35][104/104] acc/top1: 0.7094 acc/top5: 0.8990 acc/mean1: 0.7093 2022/09/08 17:58:18 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb/best_acc/top1_epoch_30.pth is removed 2022/09/08 17:58:19 - mmengine - INFO - The best checkpoint with 0.7094 acc/top1 at 35 epoch is saved to best_acc/top1_epoch_35.pth. 2022/09/08 17:58:40 - mmengine - INFO - Epoch(train) [36][20/1253] lr: 4.0000e-03 eta: 3:04:27 time: 1.0230 data_time: 0.5260 memory: 23504 grad_norm: 3.1938 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0113 loss: 1.0113 2022/09/08 17:58:51 - mmengine - INFO - Epoch(train) [36][40/1253] lr: 4.0000e-03 eta: 3:04:15 time: 0.5917 data_time: 0.0825 memory: 23504 grad_norm: 3.2466 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.9067 loss: 0.9067 2022/09/08 17:59:03 - mmengine - INFO - Epoch(train) [36][60/1253] lr: 4.0000e-03 eta: 3:04:03 time: 0.5974 data_time: 0.0873 memory: 23504 grad_norm: 3.1891 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.8401 loss: 0.8401 2022/09/08 17:59:17 - mmengine - INFO - Epoch(train) [36][80/1253] lr: 4.0000e-03 eta: 3:03:53 time: 0.6935 data_time: 0.0356 memory: 23504 grad_norm: 3.2510 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8849 loss: 0.8849 2022/09/08 17:59:29 - mmengine - INFO - Epoch(train) [36][100/1253] lr: 4.0000e-03 eta: 3:03:41 time: 0.5681 data_time: 0.0565 memory: 23504 grad_norm: 3.1609 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.8441 loss: 0.8441 2022/09/08 17:59:40 - mmengine - INFO - Epoch(train) [36][120/1253] lr: 4.0000e-03 eta: 3:03:29 time: 0.5644 data_time: 0.0493 memory: 23504 grad_norm: 3.3074 top1_acc: 0.7083 top5_acc: 1.0000 loss_cls: 0.9407 loss: 0.9407 2022/09/08 17:59:51 - mmengine - INFO - Epoch(train) [36][140/1253] lr: 4.0000e-03 eta: 3:03:17 time: 0.5792 data_time: 0.0441 memory: 23504 grad_norm: 3.2814 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9360 loss: 0.9360 2022/09/08 17:59:55 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 18:00:07 - mmengine - INFO - Epoch(train) [36][160/1253] lr: 4.0000e-03 eta: 3:03:06 time: 0.7610 data_time: 0.0613 memory: 23504 grad_norm: 3.2602 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8809 loss: 0.8809 2022/09/08 18:00:18 - mmengine - INFO - Epoch(train) [36][180/1253] lr: 4.0000e-03 eta: 3:02:54 time: 0.5757 data_time: 0.0382 memory: 23504 grad_norm: 3.3485 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9730 loss: 0.9730 2022/09/08 18:00:30 - mmengine - INFO - Epoch(train) [36][200/1253] lr: 4.0000e-03 eta: 3:02:43 time: 0.5806 data_time: 0.0405 memory: 23504 grad_norm: 3.3343 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9010 loss: 0.9010 2022/09/08 18:00:43 - mmengine - INFO - Epoch(train) [36][220/1253] lr: 4.0000e-03 eta: 3:02:31 time: 0.6574 data_time: 0.0330 memory: 23504 grad_norm: 3.1996 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8949 loss: 0.8949 2022/09/08 18:00:55 - mmengine - INFO - Epoch(train) [36][240/1253] lr: 4.0000e-03 eta: 3:02:19 time: 0.5796 data_time: 0.0372 memory: 23504 grad_norm: 3.2867 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9753 loss: 0.9753 2022/09/08 18:01:07 - mmengine - INFO - Epoch(train) [36][260/1253] lr: 4.0000e-03 eta: 3:02:08 time: 0.6168 data_time: 0.0438 memory: 23504 grad_norm: 3.3023 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.0784 loss: 1.0784 2022/09/08 18:01:18 - mmengine - INFO - Epoch(train) [36][280/1253] lr: 4.0000e-03 eta: 3:01:56 time: 0.5418 data_time: 0.0433 memory: 23504 grad_norm: 3.2344 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9594 loss: 0.9594 2022/09/08 18:01:30 - mmengine - INFO - Epoch(train) [36][300/1253] lr: 4.0000e-03 eta: 3:01:44 time: 0.6084 data_time: 0.0428 memory: 23504 grad_norm: 3.2861 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9165 loss: 0.9165 2022/09/08 18:01:43 - mmengine - INFO - Epoch(train) [36][320/1253] lr: 4.0000e-03 eta: 3:01:33 time: 0.6546 data_time: 0.0466 memory: 23504 grad_norm: 3.2542 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8838 loss: 0.8838 2022/09/08 18:01:54 - mmengine - INFO - Epoch(train) [36][340/1253] lr: 4.0000e-03 eta: 3:01:21 time: 0.5535 data_time: 0.0480 memory: 23504 grad_norm: 3.2464 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.8863 loss: 0.8863 2022/09/08 18:02:05 - mmengine - INFO - Epoch(train) [36][360/1253] lr: 4.0000e-03 eta: 3:01:09 time: 0.5618 data_time: 0.0389 memory: 23504 grad_norm: 3.2668 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8266 loss: 0.8266 2022/09/08 18:02:17 - mmengine - INFO - Epoch(train) [36][380/1253] lr: 4.0000e-03 eta: 3:00:57 time: 0.5934 data_time: 0.0762 memory: 23504 grad_norm: 3.2560 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9071 loss: 0.9071 2022/09/08 18:02:28 - mmengine - INFO - Epoch(train) [36][400/1253] lr: 4.0000e-03 eta: 3:00:45 time: 0.5524 data_time: 0.0415 memory: 23504 grad_norm: 3.3278 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9294 loss: 0.9294 2022/09/08 18:02:40 - mmengine - INFO - Epoch(train) [36][420/1253] lr: 4.0000e-03 eta: 3:00:33 time: 0.5664 data_time: 0.0436 memory: 23504 grad_norm: 3.2663 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 0.9395 loss: 0.9395 2022/09/08 18:02:52 - mmengine - INFO - Epoch(train) [36][440/1253] lr: 4.0000e-03 eta: 3:00:21 time: 0.6259 data_time: 0.0292 memory: 23504 grad_norm: 3.2905 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8667 loss: 0.8667 2022/09/08 18:03:04 - mmengine - INFO - Epoch(train) [36][460/1253] lr: 4.0000e-03 eta: 3:00:10 time: 0.5799 data_time: 0.0502 memory: 23504 grad_norm: 3.2791 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.9293 loss: 0.9293 2022/09/08 18:03:15 - mmengine - INFO - Epoch(train) [36][480/1253] lr: 4.0000e-03 eta: 2:59:58 time: 0.5691 data_time: 0.0365 memory: 23504 grad_norm: 3.2466 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 0.8949 loss: 0.8949 2022/09/08 18:03:27 - mmengine - INFO - Epoch(train) [36][500/1253] lr: 4.0000e-03 eta: 2:59:46 time: 0.5742 data_time: 0.0407 memory: 23504 grad_norm: 3.2648 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9286 loss: 0.9286 2022/09/08 18:03:38 - mmengine - INFO - Epoch(train) [36][520/1253] lr: 4.0000e-03 eta: 2:59:34 time: 0.5701 data_time: 0.0470 memory: 23504 grad_norm: 3.2687 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.7831 loss: 0.7831 2022/09/08 18:03:50 - mmengine - INFO - Epoch(train) [36][540/1253] lr: 4.0000e-03 eta: 2:59:22 time: 0.5848 data_time: 0.0836 memory: 23504 grad_norm: 3.3115 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.8933 loss: 0.8933 2022/09/08 18:04:01 - mmengine - INFO - Epoch(train) [36][560/1253] lr: 4.0000e-03 eta: 2:59:10 time: 0.5597 data_time: 0.0461 memory: 23504 grad_norm: 3.3904 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9818 loss: 0.9818 2022/09/08 18:04:12 - mmengine - INFO - Epoch(train) [36][580/1253] lr: 4.0000e-03 eta: 2:58:58 time: 0.5609 data_time: 0.0410 memory: 23504 grad_norm: 3.2274 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 0.9587 loss: 0.9587 2022/09/08 18:04:23 - mmengine - INFO - Epoch(train) [36][600/1253] lr: 4.0000e-03 eta: 2:58:46 time: 0.5563 data_time: 0.0508 memory: 23504 grad_norm: 3.2947 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 0.9442 loss: 0.9442 2022/09/08 18:04:35 - mmengine - INFO - Epoch(train) [36][620/1253] lr: 4.0000e-03 eta: 2:58:34 time: 0.5715 data_time: 0.0449 memory: 23504 grad_norm: 3.2712 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.8595 loss: 0.8595 2022/09/08 18:04:46 - mmengine - INFO - Epoch(train) [36][640/1253] lr: 4.0000e-03 eta: 2:58:22 time: 0.5633 data_time: 0.0499 memory: 23504 grad_norm: 3.2995 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9343 loss: 0.9343 2022/09/08 18:04:57 - mmengine - INFO - Epoch(train) [36][660/1253] lr: 4.0000e-03 eta: 2:58:10 time: 0.5522 data_time: 0.0418 memory: 23504 grad_norm: 3.3316 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9648 loss: 0.9648 2022/09/08 18:05:08 - mmengine - INFO - Epoch(train) [36][680/1253] lr: 4.0000e-03 eta: 2:57:58 time: 0.5616 data_time: 0.0412 memory: 23504 grad_norm: 3.3183 top1_acc: 0.3750 top5_acc: 0.9167 loss_cls: 0.9930 loss: 0.9930 2022/09/08 18:05:20 - mmengine - INFO - Epoch(train) [36][700/1253] lr: 4.0000e-03 eta: 2:57:46 time: 0.5700 data_time: 0.0515 memory: 23504 grad_norm: 3.2393 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.0102 loss: 1.0102 2022/09/08 18:05:31 - mmengine - INFO - Epoch(train) [36][720/1253] lr: 4.0000e-03 eta: 2:57:34 time: 0.5726 data_time: 0.0479 memory: 23504 grad_norm: 3.3659 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9127 loss: 0.9127 2022/09/08 18:05:43 - mmengine - INFO - Epoch(train) [36][740/1253] lr: 4.0000e-03 eta: 2:57:22 time: 0.6000 data_time: 0.0451 memory: 23504 grad_norm: 3.2730 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.9235 loss: 0.9235 2022/09/08 18:05:55 - mmengine - INFO - Epoch(train) [36][760/1253] lr: 4.0000e-03 eta: 2:57:10 time: 0.5793 data_time: 0.0457 memory: 23504 grad_norm: 3.3296 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9571 loss: 0.9571 2022/09/08 18:06:07 - mmengine - INFO - Epoch(train) [36][780/1253] lr: 4.0000e-03 eta: 2:56:58 time: 0.5963 data_time: 0.0443 memory: 23504 grad_norm: 3.3594 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 0.9032 loss: 0.9032 2022/09/08 18:06:18 - mmengine - INFO - Epoch(train) [36][800/1253] lr: 4.0000e-03 eta: 2:56:47 time: 0.5746 data_time: 0.0403 memory: 23504 grad_norm: 3.3271 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.0220 loss: 1.0220 2022/09/08 18:06:30 - mmengine - INFO - Epoch(train) [36][820/1253] lr: 4.0000e-03 eta: 2:56:35 time: 0.6083 data_time: 0.0637 memory: 23504 grad_norm: 3.3253 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9794 loss: 0.9794 2022/09/08 18:06:42 - mmengine - INFO - Epoch(train) [36][840/1253] lr: 4.0000e-03 eta: 2:56:23 time: 0.6012 data_time: 0.0483 memory: 23504 grad_norm: 3.3477 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.9097 loss: 0.9097 2022/09/08 18:06:54 - mmengine - INFO - Epoch(train) [36][860/1253] lr: 4.0000e-03 eta: 2:56:11 time: 0.5925 data_time: 0.0500 memory: 23504 grad_norm: 3.3332 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9151 loss: 0.9151 2022/09/08 18:07:07 - mmengine - INFO - Epoch(train) [36][880/1253] lr: 4.0000e-03 eta: 2:56:00 time: 0.6286 data_time: 0.0299 memory: 23504 grad_norm: 3.3810 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 0.8960 loss: 0.8960 2022/09/08 18:07:18 - mmengine - INFO - Epoch(train) [36][900/1253] lr: 4.0000e-03 eta: 2:55:48 time: 0.5409 data_time: 0.0445 memory: 23504 grad_norm: 3.3781 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9715 loss: 0.9715 2022/09/08 18:07:29 - mmengine - INFO - Epoch(train) [36][920/1253] lr: 4.0000e-03 eta: 2:55:36 time: 0.5441 data_time: 0.0418 memory: 23504 grad_norm: 3.3023 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.8501 loss: 0.8501 2022/09/08 18:07:39 - mmengine - INFO - Epoch(train) [36][940/1253] lr: 4.0000e-03 eta: 2:55:24 time: 0.5480 data_time: 0.0483 memory: 23504 grad_norm: 3.2844 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 0.8560 loss: 0.8560 2022/09/08 18:07:51 - mmengine - INFO - Epoch(train) [36][960/1253] lr: 4.0000e-03 eta: 2:55:12 time: 0.5611 data_time: 0.0456 memory: 23504 grad_norm: 3.2888 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9007 loss: 0.9007 2022/09/08 18:08:02 - mmengine - INFO - Epoch(train) [36][980/1253] lr: 4.0000e-03 eta: 2:55:00 time: 0.5746 data_time: 0.0494 memory: 23504 grad_norm: 3.2946 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.8743 loss: 0.8743 2022/09/08 18:08:14 - mmengine - INFO - Epoch(train) [36][1000/1253] lr: 4.0000e-03 eta: 2:54:48 time: 0.5803 data_time: 0.0499 memory: 23504 grad_norm: 3.3466 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9459 loss: 0.9459 2022/09/08 18:08:25 - mmengine - INFO - Epoch(train) [36][1020/1253] lr: 4.0000e-03 eta: 2:54:36 time: 0.5592 data_time: 0.0460 memory: 23504 grad_norm: 3.3544 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8141 loss: 0.8141 2022/09/08 18:08:36 - mmengine - INFO - Epoch(train) [36][1040/1253] lr: 4.0000e-03 eta: 2:54:24 time: 0.5724 data_time: 0.0426 memory: 23504 grad_norm: 3.2434 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.0249 loss: 1.0249 2022/09/08 18:08:48 - mmengine - INFO - Epoch(train) [36][1060/1253] lr: 4.0000e-03 eta: 2:54:12 time: 0.5700 data_time: 0.0525 memory: 23504 grad_norm: 3.3330 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.8080 loss: 0.8080 2022/09/08 18:09:01 - mmengine - INFO - Epoch(train) [36][1080/1253] lr: 4.0000e-03 eta: 2:54:01 time: 0.6752 data_time: 0.0400 memory: 23504 grad_norm: 3.3730 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8808 loss: 0.8808 2022/09/08 18:09:13 - mmengine - INFO - Epoch(train) [36][1100/1253] lr: 4.0000e-03 eta: 2:53:49 time: 0.5783 data_time: 0.0350 memory: 23504 grad_norm: 3.2556 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.0384 loss: 1.0384 2022/09/08 18:09:25 - mmengine - INFO - Epoch(train) [36][1120/1253] lr: 4.0000e-03 eta: 2:53:37 time: 0.5955 data_time: 0.0398 memory: 23504 grad_norm: 3.2891 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8918 loss: 0.8918 2022/09/08 18:09:36 - mmengine - INFO - Epoch(train) [36][1140/1253] lr: 4.0000e-03 eta: 2:53:25 time: 0.5577 data_time: 0.0490 memory: 23504 grad_norm: 3.3120 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8094 loss: 0.8094 2022/09/08 18:09:39 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 18:09:49 - mmengine - INFO - Epoch(train) [36][1160/1253] lr: 4.0000e-03 eta: 2:53:14 time: 0.6456 data_time: 0.0322 memory: 23504 grad_norm: 3.2747 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.8977 loss: 0.8977 2022/09/08 18:10:00 - mmengine - INFO - Epoch(train) [36][1180/1253] lr: 4.0000e-03 eta: 2:53:02 time: 0.5569 data_time: 0.0379 memory: 23504 grad_norm: 3.2187 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.8664 loss: 0.8664 2022/09/08 18:10:13 - mmengine - INFO - Epoch(train) [36][1200/1253] lr: 4.0000e-03 eta: 2:52:50 time: 0.6297 data_time: 0.0517 memory: 23504 grad_norm: 3.3349 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0498 loss: 1.0498 2022/09/08 18:10:25 - mmengine - INFO - Epoch(train) [36][1220/1253] lr: 4.0000e-03 eta: 2:52:39 time: 0.6387 data_time: 0.0441 memory: 23504 grad_norm: 3.3135 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.0450 loss: 1.0450 2022/09/08 18:10:37 - mmengine - INFO - Epoch(train) [36][1240/1253] lr: 4.0000e-03 eta: 2:52:27 time: 0.5854 data_time: 0.0295 memory: 23504 grad_norm: 3.2541 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8583 loss: 0.8583 2022/09/08 18:10:43 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 18:10:43 - mmengine - INFO - Epoch(train) [36][1253/1253] lr: 4.0000e-03 eta: 2:52:27 time: 0.5558 data_time: 0.0191 memory: 23504 grad_norm: 3.3915 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 0.8362 loss: 0.8362 2022/09/08 18:11:07 - mmengine - INFO - Epoch(train) [37][20/1253] lr: 4.0000e-03 eta: 2:52:09 time: 1.2007 data_time: 0.5434 memory: 23504 grad_norm: 3.2903 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8199 loss: 0.8199 2022/09/08 18:11:18 - mmengine - INFO - Epoch(train) [37][40/1253] lr: 4.0000e-03 eta: 2:51:57 time: 0.5439 data_time: 0.0333 memory: 23504 grad_norm: 3.2670 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.9330 loss: 0.9330 2022/09/08 18:11:29 - mmengine - INFO - Epoch(train) [37][60/1253] lr: 4.0000e-03 eta: 2:51:45 time: 0.5695 data_time: 0.0371 memory: 23504 grad_norm: 3.2827 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.8813 loss: 0.8813 2022/09/08 18:11:42 - mmengine - INFO - Epoch(train) [37][80/1253] lr: 4.0000e-03 eta: 2:51:34 time: 0.6570 data_time: 0.0373 memory: 23504 grad_norm: 3.3165 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.9143 loss: 0.9143 2022/09/08 18:11:54 - mmengine - INFO - Epoch(train) [37][100/1253] lr: 4.0000e-03 eta: 2:51:22 time: 0.5743 data_time: 0.0480 memory: 23504 grad_norm: 3.2218 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 0.8476 loss: 0.8476 2022/09/08 18:12:06 - mmengine - INFO - Epoch(train) [37][120/1253] lr: 4.0000e-03 eta: 2:51:11 time: 0.6183 data_time: 0.0755 memory: 23504 grad_norm: 3.3342 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9679 loss: 0.9679 2022/09/08 18:12:18 - mmengine - INFO - Epoch(train) [37][140/1253] lr: 4.0000e-03 eta: 2:50:59 time: 0.5748 data_time: 0.0462 memory: 23504 grad_norm: 3.3264 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9563 loss: 0.9563 2022/09/08 18:12:29 - mmengine - INFO - Epoch(train) [37][160/1253] lr: 4.0000e-03 eta: 2:50:47 time: 0.5585 data_time: 0.0399 memory: 23504 grad_norm: 3.3283 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.1158 loss: 1.1158 2022/09/08 18:12:40 - mmengine - INFO - Epoch(train) [37][180/1253] lr: 4.0000e-03 eta: 2:50:35 time: 0.5543 data_time: 0.0384 memory: 23504 grad_norm: 3.3224 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 0.8911 loss: 0.8911 2022/09/08 18:12:51 - mmengine - INFO - Epoch(train) [37][200/1253] lr: 4.0000e-03 eta: 2:50:23 time: 0.5709 data_time: 0.0468 memory: 23504 grad_norm: 3.3562 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 0.9391 loss: 0.9391 2022/09/08 18:13:03 - mmengine - INFO - Epoch(train) [37][220/1253] lr: 4.0000e-03 eta: 2:50:11 time: 0.5981 data_time: 0.0904 memory: 23504 grad_norm: 3.3406 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9127 loss: 0.9127 2022/09/08 18:13:15 - mmengine - INFO - Epoch(train) [37][240/1253] lr: 4.0000e-03 eta: 2:49:59 time: 0.5975 data_time: 0.0419 memory: 23504 grad_norm: 3.3307 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.8920 loss: 0.8920 2022/09/08 18:13:27 - mmengine - INFO - Epoch(train) [37][260/1253] lr: 4.0000e-03 eta: 2:49:47 time: 0.5975 data_time: 0.0354 memory: 23504 grad_norm: 3.2660 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.0457 loss: 1.0457 2022/09/08 18:13:40 - mmengine - INFO - Epoch(train) [37][280/1253] lr: 4.0000e-03 eta: 2:49:36 time: 0.6480 data_time: 0.0277 memory: 23504 grad_norm: 3.3997 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9606 loss: 0.9606 2022/09/08 18:13:52 - mmengine - INFO - Epoch(train) [37][300/1253] lr: 4.0000e-03 eta: 2:49:24 time: 0.5865 data_time: 0.0382 memory: 23504 grad_norm: 3.3633 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.8784 loss: 0.8784 2022/09/08 18:14:03 - mmengine - INFO - Epoch(train) [37][320/1253] lr: 4.0000e-03 eta: 2:49:12 time: 0.5792 data_time: 0.0367 memory: 23504 grad_norm: 3.2924 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 0.9385 loss: 0.9385 2022/09/08 18:14:15 - mmengine - INFO - Epoch(train) [37][340/1253] lr: 4.0000e-03 eta: 2:49:01 time: 0.5801 data_time: 0.0386 memory: 23504 grad_norm: 3.3225 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.9762 loss: 0.9762 2022/09/08 18:14:26 - mmengine - INFO - Epoch(train) [37][360/1253] lr: 4.0000e-03 eta: 2:48:49 time: 0.5679 data_time: 0.0545 memory: 23504 grad_norm: 3.2764 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8690 loss: 0.8690 2022/09/08 18:14:38 - mmengine - INFO - Epoch(train) [37][380/1253] lr: 4.0000e-03 eta: 2:48:37 time: 0.5819 data_time: 0.0325 memory: 23504 grad_norm: 3.3195 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.0119 loss: 1.0119 2022/09/08 18:14:53 - mmengine - INFO - Epoch(train) [37][400/1253] lr: 4.0000e-03 eta: 2:48:26 time: 0.7410 data_time: 0.0452 memory: 23504 grad_norm: 3.3574 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9080 loss: 0.9080 2022/09/08 18:15:04 - mmengine - INFO - Epoch(train) [37][420/1253] lr: 4.0000e-03 eta: 2:48:14 time: 0.5414 data_time: 0.0309 memory: 23504 grad_norm: 3.2117 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.9217 loss: 0.9217 2022/09/08 18:15:15 - mmengine - INFO - Epoch(train) [37][440/1253] lr: 4.0000e-03 eta: 2:48:02 time: 0.5570 data_time: 0.0405 memory: 23504 grad_norm: 3.2840 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8576 loss: 0.8576 2022/09/08 18:15:27 - mmengine - INFO - Epoch(train) [37][460/1253] lr: 4.0000e-03 eta: 2:47:50 time: 0.5877 data_time: 0.0414 memory: 23504 grad_norm: 3.3953 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8808 loss: 0.8808 2022/09/08 18:15:38 - mmengine - INFO - Epoch(train) [37][480/1253] lr: 4.0000e-03 eta: 2:47:38 time: 0.5627 data_time: 0.0421 memory: 23504 grad_norm: 3.4624 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9770 loss: 0.9770 2022/09/08 18:15:50 - mmengine - INFO - Epoch(train) [37][500/1253] lr: 4.0000e-03 eta: 2:47:26 time: 0.5944 data_time: 0.0422 memory: 23504 grad_norm: 3.2655 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.9172 loss: 0.9172 2022/09/08 18:16:01 - mmengine - INFO - Epoch(train) [37][520/1253] lr: 4.0000e-03 eta: 2:47:14 time: 0.5669 data_time: 0.0394 memory: 23504 grad_norm: 3.2737 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8522 loss: 0.8522 2022/09/08 18:16:13 - mmengine - INFO - Epoch(train) [37][540/1253] lr: 4.0000e-03 eta: 2:47:03 time: 0.5827 data_time: 0.0485 memory: 23504 grad_norm: 3.3839 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.9165 loss: 0.9165 2022/09/08 18:16:24 - mmengine - INFO - Epoch(train) [37][560/1253] lr: 4.0000e-03 eta: 2:46:51 time: 0.5769 data_time: 0.0408 memory: 23504 grad_norm: 3.3524 top1_acc: 0.7083 top5_acc: 1.0000 loss_cls: 0.9417 loss: 0.9417 2022/09/08 18:16:36 - mmengine - INFO - Epoch(train) [37][580/1253] lr: 4.0000e-03 eta: 2:46:39 time: 0.5635 data_time: 0.0406 memory: 23504 grad_norm: 3.4014 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8826 loss: 0.8826 2022/09/08 18:16:47 - mmengine - INFO - Epoch(train) [37][600/1253] lr: 4.0000e-03 eta: 2:46:27 time: 0.5643 data_time: 0.0456 memory: 23504 grad_norm: 3.2971 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.8892 loss: 0.8892 2022/09/08 18:16:58 - mmengine - INFO - Epoch(train) [37][620/1253] lr: 4.0000e-03 eta: 2:46:15 time: 0.5450 data_time: 0.0412 memory: 23504 grad_norm: 3.2410 top1_acc: 0.9583 top5_acc: 0.9583 loss_cls: 0.9338 loss: 0.9338 2022/09/08 18:17:12 - mmengine - INFO - Epoch(train) [37][640/1253] lr: 4.0000e-03 eta: 2:46:04 time: 0.6952 data_time: 0.0501 memory: 23504 grad_norm: 3.2983 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9281 loss: 0.9281 2022/09/08 18:17:23 - mmengine - INFO - Epoch(train) [37][660/1253] lr: 4.0000e-03 eta: 2:45:52 time: 0.5726 data_time: 0.0390 memory: 23504 grad_norm: 3.4147 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9052 loss: 0.9052 2022/09/08 18:17:35 - mmengine - INFO - Epoch(train) [37][680/1253] lr: 4.0000e-03 eta: 2:45:40 time: 0.5815 data_time: 0.0573 memory: 23504 grad_norm: 3.3281 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9381 loss: 0.9381 2022/09/08 18:17:46 - mmengine - INFO - Epoch(train) [37][700/1253] lr: 4.0000e-03 eta: 2:45:28 time: 0.5567 data_time: 0.0506 memory: 23504 grad_norm: 3.3648 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0821 loss: 1.0821 2022/09/08 18:17:57 - mmengine - INFO - Epoch(train) [37][720/1253] lr: 4.0000e-03 eta: 2:45:16 time: 0.5690 data_time: 0.0483 memory: 23504 grad_norm: 3.3403 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.9799 loss: 0.9799 2022/09/08 18:18:11 - mmengine - INFO - Epoch(train) [37][740/1253] lr: 4.0000e-03 eta: 2:45:05 time: 0.6976 data_time: 0.0472 memory: 23504 grad_norm: 3.3340 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.9880 loss: 0.9880 2022/09/08 18:18:22 - mmengine - INFO - Epoch(train) [37][760/1253] lr: 4.0000e-03 eta: 2:44:53 time: 0.5351 data_time: 0.0316 memory: 23504 grad_norm: 3.3639 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9970 loss: 0.9970 2022/09/08 18:18:33 - mmengine - INFO - Epoch(train) [37][780/1253] lr: 4.0000e-03 eta: 2:44:41 time: 0.5758 data_time: 0.0587 memory: 23504 grad_norm: 3.3495 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9331 loss: 0.9331 2022/09/08 18:18:45 - mmengine - INFO - Epoch(train) [37][800/1253] lr: 4.0000e-03 eta: 2:44:29 time: 0.5909 data_time: 0.0398 memory: 23504 grad_norm: 3.3755 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.0212 loss: 1.0212 2022/09/08 18:18:57 - mmengine - INFO - Epoch(train) [37][820/1253] lr: 4.0000e-03 eta: 2:44:17 time: 0.5819 data_time: 0.0381 memory: 23504 grad_norm: 3.3219 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 0.8817 loss: 0.8817 2022/09/08 18:19:08 - mmengine - INFO - Epoch(train) [37][840/1253] lr: 4.0000e-03 eta: 2:44:05 time: 0.5702 data_time: 0.0415 memory: 23504 grad_norm: 3.3480 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.0622 loss: 1.0622 2022/09/08 18:19:20 - mmengine - INFO - Epoch(train) [37][860/1253] lr: 4.0000e-03 eta: 2:43:53 time: 0.5802 data_time: 0.0553 memory: 23504 grad_norm: 3.3535 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.8850 loss: 0.8850 2022/09/08 18:19:31 - mmengine - INFO - Epoch(train) [37][880/1253] lr: 4.0000e-03 eta: 2:43:41 time: 0.5711 data_time: 0.0317 memory: 23504 grad_norm: 3.2459 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8680 loss: 0.8680 2022/09/08 18:19:38 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 18:19:43 - mmengine - INFO - Epoch(train) [37][900/1253] lr: 4.0000e-03 eta: 2:43:29 time: 0.5623 data_time: 0.0399 memory: 23504 grad_norm: 3.2087 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8990 loss: 0.8990 2022/09/08 18:19:54 - mmengine - INFO - Epoch(train) [37][920/1253] lr: 4.0000e-03 eta: 2:43:17 time: 0.5704 data_time: 0.0426 memory: 23504 grad_norm: 3.3417 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9229 loss: 0.9229 2022/09/08 18:20:07 - mmengine - INFO - Epoch(train) [37][940/1253] lr: 4.0000e-03 eta: 2:43:06 time: 0.6214 data_time: 0.0450 memory: 23504 grad_norm: 3.3664 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.9960 loss: 0.9960 2022/09/08 18:20:19 - mmengine - INFO - Epoch(train) [37][960/1253] lr: 4.0000e-03 eta: 2:42:55 time: 0.6477 data_time: 0.0389 memory: 23504 grad_norm: 3.2823 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.7862 loss: 0.7862 2022/09/08 18:20:33 - mmengine - INFO - Epoch(train) [37][980/1253] lr: 4.0000e-03 eta: 2:42:43 time: 0.6521 data_time: 0.1239 memory: 23504 grad_norm: 3.3569 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8826 loss: 0.8826 2022/09/08 18:20:44 - mmengine - INFO - Epoch(train) [37][1000/1253] lr: 4.0000e-03 eta: 2:42:31 time: 0.5617 data_time: 0.0414 memory: 23504 grad_norm: 3.3237 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8215 loss: 0.8215 2022/09/08 18:20:55 - mmengine - INFO - Epoch(train) [37][1020/1253] lr: 4.0000e-03 eta: 2:42:19 time: 0.5459 data_time: 0.0324 memory: 23504 grad_norm: 3.4032 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.8759 loss: 0.8759 2022/09/08 18:21:07 - mmengine - INFO - Epoch(train) [37][1040/1253] lr: 4.0000e-03 eta: 2:42:08 time: 0.6326 data_time: 0.0397 memory: 23504 grad_norm: 3.2674 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.9925 loss: 0.9925 2022/09/08 18:21:19 - mmengine - INFO - Epoch(train) [37][1060/1253] lr: 4.0000e-03 eta: 2:41:56 time: 0.5688 data_time: 0.0492 memory: 23504 grad_norm: 3.3705 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9657 loss: 0.9657 2022/09/08 18:21:33 - mmengine - INFO - Epoch(train) [37][1080/1253] lr: 4.0000e-03 eta: 2:41:45 time: 0.7023 data_time: 0.1803 memory: 23504 grad_norm: 3.4291 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.1122 loss: 1.1122 2022/09/08 18:21:44 - mmengine - INFO - Epoch(train) [37][1100/1253] lr: 4.0000e-03 eta: 2:41:33 time: 0.5423 data_time: 0.0266 memory: 23504 grad_norm: 3.2992 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.8669 loss: 0.8669 2022/09/08 18:21:55 - mmengine - INFO - Epoch(train) [37][1120/1253] lr: 4.0000e-03 eta: 2:41:21 time: 0.5626 data_time: 0.0442 memory: 23504 grad_norm: 3.5115 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0697 loss: 1.0697 2022/09/08 18:22:06 - mmengine - INFO - Epoch(train) [37][1140/1253] lr: 4.0000e-03 eta: 2:41:09 time: 0.5587 data_time: 0.0462 memory: 23504 grad_norm: 3.3198 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8637 loss: 0.8637 2022/09/08 18:22:17 - mmengine - INFO - Epoch(train) [37][1160/1253] lr: 4.0000e-03 eta: 2:40:57 time: 0.5526 data_time: 0.0351 memory: 23504 grad_norm: 3.3730 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.8891 loss: 0.8891 2022/09/08 18:22:31 - mmengine - INFO - Epoch(train) [37][1180/1253] lr: 4.0000e-03 eta: 2:40:45 time: 0.6763 data_time: 0.0424 memory: 23504 grad_norm: 3.4032 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0288 loss: 1.0288 2022/09/08 18:22:43 - mmengine - INFO - Epoch(train) [37][1200/1253] lr: 4.0000e-03 eta: 2:40:34 time: 0.6254 data_time: 0.0412 memory: 23504 grad_norm: 3.4390 top1_acc: 0.7500 top5_acc: 0.7917 loss_cls: 0.8340 loss: 0.8340 2022/09/08 18:22:55 - mmengine - INFO - Epoch(train) [37][1220/1253] lr: 4.0000e-03 eta: 2:40:22 time: 0.5906 data_time: 0.0414 memory: 23504 grad_norm: 3.3737 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8297 loss: 0.8297 2022/09/08 18:23:05 - mmengine - INFO - Epoch(train) [37][1240/1253] lr: 4.0000e-03 eta: 2:40:09 time: 0.4788 data_time: 0.0303 memory: 23504 grad_norm: 3.3419 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.9093 loss: 0.9093 2022/09/08 18:23:10 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 18:23:10 - mmengine - INFO - Epoch(train) [37][1253/1253] lr: 4.0000e-03 eta: 2:40:09 time: 0.4344 data_time: 0.0186 memory: 23504 grad_norm: 3.5387 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 0.8857 loss: 0.8857 2022/09/08 18:23:34 - mmengine - INFO - Epoch(train) [38][20/1253] lr: 4.0000e-03 eta: 2:39:52 time: 1.1847 data_time: 0.5915 memory: 23504 grad_norm: 3.3533 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 0.9986 loss: 0.9986 2022/09/08 18:23:48 - mmengine - INFO - Epoch(train) [38][40/1253] lr: 4.0000e-03 eta: 2:39:41 time: 0.7048 data_time: 0.0705 memory: 23504 grad_norm: 3.3182 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9345 loss: 0.9345 2022/09/08 18:23:59 - mmengine - INFO - Epoch(train) [38][60/1253] lr: 4.0000e-03 eta: 2:39:28 time: 0.5373 data_time: 0.0305 memory: 23504 grad_norm: 3.3748 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8556 loss: 0.8556 2022/09/08 18:24:10 - mmengine - INFO - Epoch(train) [38][80/1253] lr: 4.0000e-03 eta: 2:39:16 time: 0.5532 data_time: 0.0412 memory: 23504 grad_norm: 3.3087 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8906 loss: 0.8906 2022/09/08 18:24:21 - mmengine - INFO - Epoch(train) [38][100/1253] lr: 4.0000e-03 eta: 2:39:04 time: 0.5807 data_time: 0.0479 memory: 23504 grad_norm: 3.3349 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9880 loss: 0.9880 2022/09/08 18:24:33 - mmengine - INFO - Epoch(train) [38][120/1253] lr: 4.0000e-03 eta: 2:38:53 time: 0.5840 data_time: 0.0493 memory: 23504 grad_norm: 3.2856 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.8731 loss: 0.8731 2022/09/08 18:24:45 - mmengine - INFO - Epoch(train) [38][140/1253] lr: 4.0000e-03 eta: 2:38:41 time: 0.5755 data_time: 0.0473 memory: 23504 grad_norm: 3.2992 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.9138 loss: 0.9138 2022/09/08 18:24:56 - mmengine - INFO - Epoch(train) [38][160/1253] lr: 4.0000e-03 eta: 2:38:29 time: 0.5618 data_time: 0.0392 memory: 23504 grad_norm: 3.3267 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8424 loss: 0.8424 2022/09/08 18:25:07 - mmengine - INFO - Epoch(train) [38][180/1253] lr: 4.0000e-03 eta: 2:38:17 time: 0.5727 data_time: 0.0448 memory: 23504 grad_norm: 3.1907 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7883 loss: 0.7883 2022/09/08 18:25:19 - mmengine - INFO - Epoch(train) [38][200/1253] lr: 4.0000e-03 eta: 2:38:05 time: 0.5794 data_time: 0.0375 memory: 23504 grad_norm: 3.3150 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.9473 loss: 0.9473 2022/09/08 18:25:33 - mmengine - INFO - Epoch(train) [38][220/1253] lr: 4.0000e-03 eta: 2:37:54 time: 0.6851 data_time: 0.0400 memory: 23504 grad_norm: 3.3682 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.0752 loss: 1.0752 2022/09/08 18:25:44 - mmengine - INFO - Epoch(train) [38][240/1253] lr: 4.0000e-03 eta: 2:37:42 time: 0.5483 data_time: 0.0377 memory: 23504 grad_norm: 3.2938 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 0.9443 loss: 0.9443 2022/09/08 18:25:55 - mmengine - INFO - Epoch(train) [38][260/1253] lr: 4.0000e-03 eta: 2:37:30 time: 0.5625 data_time: 0.0418 memory: 23504 grad_norm: 3.2958 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.9124 loss: 0.9124 2022/09/08 18:26:06 - mmengine - INFO - Epoch(train) [38][280/1253] lr: 4.0000e-03 eta: 2:37:18 time: 0.5736 data_time: 0.0427 memory: 23504 grad_norm: 3.3972 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8531 loss: 0.8531 2022/09/08 18:26:20 - mmengine - INFO - Epoch(train) [38][300/1253] lr: 4.0000e-03 eta: 2:37:07 time: 0.6722 data_time: 0.0376 memory: 23504 grad_norm: 3.3356 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.8279 loss: 0.8279 2022/09/08 18:26:31 - mmengine - INFO - Epoch(train) [38][320/1253] lr: 4.0000e-03 eta: 2:36:55 time: 0.5679 data_time: 0.0389 memory: 23504 grad_norm: 3.3336 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.8166 loss: 0.8166 2022/09/08 18:26:44 - mmengine - INFO - Epoch(train) [38][340/1253] lr: 4.0000e-03 eta: 2:36:43 time: 0.6525 data_time: 0.0464 memory: 23504 grad_norm: 3.4001 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 0.8901 loss: 0.8901 2022/09/08 18:26:55 - mmengine - INFO - Epoch(train) [38][360/1253] lr: 4.0000e-03 eta: 2:36:31 time: 0.5639 data_time: 0.0354 memory: 23504 grad_norm: 3.3019 top1_acc: 0.9583 top5_acc: 0.9583 loss_cls: 0.8644 loss: 0.8644 2022/09/08 18:27:08 - mmengine - INFO - Epoch(train) [38][380/1253] lr: 4.0000e-03 eta: 2:36:20 time: 0.6356 data_time: 0.0249 memory: 23504 grad_norm: 3.3333 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.9770 loss: 0.9770 2022/09/08 18:27:20 - mmengine - INFO - Epoch(train) [38][400/1253] lr: 4.0000e-03 eta: 2:36:08 time: 0.5667 data_time: 0.0382 memory: 23504 grad_norm: 3.3370 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 0.8285 loss: 0.8285 2022/09/08 18:27:31 - mmengine - INFO - Epoch(train) [38][420/1253] lr: 4.0000e-03 eta: 2:35:56 time: 0.5673 data_time: 0.0481 memory: 23504 grad_norm: 3.4586 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 0.8572 loss: 0.8572 2022/09/08 18:27:42 - mmengine - INFO - Epoch(train) [38][440/1253] lr: 4.0000e-03 eta: 2:35:44 time: 0.5768 data_time: 0.0539 memory: 23504 grad_norm: 3.3966 top1_acc: 0.7083 top5_acc: 1.0000 loss_cls: 0.9349 loss: 0.9349 2022/09/08 18:27:54 - mmengine - INFO - Epoch(train) [38][460/1253] lr: 4.0000e-03 eta: 2:35:32 time: 0.5746 data_time: 0.0438 memory: 23504 grad_norm: 3.3116 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.7245 loss: 0.7245 2022/09/08 18:28:05 - mmengine - INFO - Epoch(train) [38][480/1253] lr: 4.0000e-03 eta: 2:35:20 time: 0.5723 data_time: 0.0431 memory: 23504 grad_norm: 3.3131 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.9198 loss: 0.9198 2022/09/08 18:28:17 - mmengine - INFO - Epoch(train) [38][500/1253] lr: 4.0000e-03 eta: 2:35:08 time: 0.5603 data_time: 0.0458 memory: 23504 grad_norm: 3.3168 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.9049 loss: 0.9049 2022/09/08 18:28:28 - mmengine - INFO - Epoch(train) [38][520/1253] lr: 4.0000e-03 eta: 2:34:56 time: 0.5657 data_time: 0.0468 memory: 23504 grad_norm: 3.3315 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 0.8895 loss: 0.8895 2022/09/08 18:28:42 - mmengine - INFO - Epoch(train) [38][540/1253] lr: 4.0000e-03 eta: 2:34:46 time: 0.7257 data_time: 0.0363 memory: 23504 grad_norm: 3.3709 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.9594 loss: 0.9594 2022/09/08 18:28:54 - mmengine - INFO - Epoch(train) [38][560/1253] lr: 4.0000e-03 eta: 2:34:34 time: 0.5705 data_time: 0.0421 memory: 23504 grad_norm: 3.3862 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.8375 loss: 0.8375 2022/09/08 18:29:05 - mmengine - INFO - Epoch(train) [38][580/1253] lr: 4.0000e-03 eta: 2:34:22 time: 0.5510 data_time: 0.0450 memory: 23504 grad_norm: 3.2947 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.8751 loss: 0.8751 2022/09/08 18:29:16 - mmengine - INFO - Epoch(train) [38][600/1253] lr: 4.0000e-03 eta: 2:34:10 time: 0.5468 data_time: 0.0398 memory: 23504 grad_norm: 3.3661 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8727 loss: 0.8727 2022/09/08 18:29:30 - mmengine - INFO - Epoch(train) [38][620/1253] lr: 4.0000e-03 eta: 2:33:58 time: 0.6977 data_time: 0.0738 memory: 23504 grad_norm: 3.4373 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9341 loss: 0.9341 2022/09/08 18:29:40 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 18:29:40 - mmengine - INFO - Epoch(train) [38][640/1253] lr: 4.0000e-03 eta: 2:33:46 time: 0.5352 data_time: 0.0430 memory: 23504 grad_norm: 3.4915 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.9454 loss: 0.9454 2022/09/08 18:29:52 - mmengine - INFO - Epoch(train) [38][660/1253] lr: 4.0000e-03 eta: 2:33:34 time: 0.5567 data_time: 0.0480 memory: 23504 grad_norm: 3.3081 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.9873 loss: 0.9873 2022/09/08 18:30:03 - mmengine - INFO - Epoch(train) [38][680/1253] lr: 4.0000e-03 eta: 2:33:22 time: 0.5753 data_time: 0.0528 memory: 23504 grad_norm: 3.4106 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9522 loss: 0.9522 2022/09/08 18:30:14 - mmengine - INFO - Epoch(train) [38][700/1253] lr: 4.0000e-03 eta: 2:33:10 time: 0.5654 data_time: 0.0305 memory: 23504 grad_norm: 3.4254 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 0.9782 loss: 0.9782 2022/09/08 18:30:26 - mmengine - INFO - Epoch(train) [38][720/1253] lr: 4.0000e-03 eta: 2:32:58 time: 0.5565 data_time: 0.0477 memory: 23504 grad_norm: 3.4017 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.8862 loss: 0.8862 2022/09/08 18:30:38 - mmengine - INFO - Epoch(train) [38][740/1253] lr: 4.0000e-03 eta: 2:32:47 time: 0.6181 data_time: 0.0356 memory: 23504 grad_norm: 3.2967 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 1.0474 loss: 1.0474 2022/09/08 18:30:50 - mmengine - INFO - Epoch(train) [38][760/1253] lr: 4.0000e-03 eta: 2:32:35 time: 0.5987 data_time: 0.0497 memory: 23504 grad_norm: 3.4212 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0424 loss: 1.0424 2022/09/08 18:31:01 - mmengine - INFO - Epoch(train) [38][780/1253] lr: 4.0000e-03 eta: 2:32:23 time: 0.5650 data_time: 0.0388 memory: 23504 grad_norm: 3.4645 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9294 loss: 0.9294 2022/09/08 18:31:13 - mmengine - INFO - Epoch(train) [38][800/1253] lr: 4.0000e-03 eta: 2:32:11 time: 0.5772 data_time: 0.0409 memory: 23504 grad_norm: 3.4672 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.9432 loss: 0.9432 2022/09/08 18:31:24 - mmengine - INFO - Epoch(train) [38][820/1253] lr: 4.0000e-03 eta: 2:31:59 time: 0.5787 data_time: 0.0408 memory: 23504 grad_norm: 3.4039 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 0.9565 loss: 0.9565 2022/09/08 18:31:37 - mmengine - INFO - Epoch(train) [38][840/1253] lr: 4.0000e-03 eta: 2:31:48 time: 0.6166 data_time: 0.0538 memory: 23504 grad_norm: 3.4266 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8453 loss: 0.8453 2022/09/08 18:31:48 - mmengine - INFO - Epoch(train) [38][860/1253] lr: 4.0000e-03 eta: 2:31:36 time: 0.5825 data_time: 0.0441 memory: 23504 grad_norm: 3.3862 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9465 loss: 0.9465 2022/09/08 18:32:00 - mmengine - INFO - Epoch(train) [38][880/1253] lr: 4.0000e-03 eta: 2:31:24 time: 0.5651 data_time: 0.0354 memory: 23504 grad_norm: 3.3161 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8283 loss: 0.8283 2022/09/08 18:32:13 - mmengine - INFO - Epoch(train) [38][900/1253] lr: 4.0000e-03 eta: 2:31:13 time: 0.6519 data_time: 0.0343 memory: 23504 grad_norm: 3.3577 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.9813 loss: 0.9813 2022/09/08 18:32:25 - mmengine - INFO - Epoch(train) [38][920/1253] lr: 4.0000e-03 eta: 2:31:01 time: 0.5966 data_time: 0.0328 memory: 23504 grad_norm: 3.3882 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8673 loss: 0.8673 2022/09/08 18:32:36 - mmengine - INFO - Epoch(train) [38][940/1253] lr: 4.0000e-03 eta: 2:30:49 time: 0.5576 data_time: 0.0560 memory: 23504 grad_norm: 3.3703 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.8766 loss: 0.8766 2022/09/08 18:32:47 - mmengine - INFO - Epoch(train) [38][960/1253] lr: 4.0000e-03 eta: 2:30:37 time: 0.5803 data_time: 0.0342 memory: 23504 grad_norm: 3.3860 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.8701 loss: 0.8701 2022/09/08 18:32:59 - mmengine - INFO - Epoch(train) [38][980/1253] lr: 4.0000e-03 eta: 2:30:25 time: 0.5824 data_time: 0.0393 memory: 23504 grad_norm: 3.3764 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.8127 loss: 0.8127 2022/09/08 18:33:11 - mmengine - INFO - Epoch(train) [38][1000/1253] lr: 4.0000e-03 eta: 2:30:13 time: 0.5879 data_time: 0.0350 memory: 23504 grad_norm: 3.4186 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9859 loss: 0.9859 2022/09/08 18:33:22 - mmengine - INFO - Epoch(train) [38][1020/1253] lr: 4.0000e-03 eta: 2:30:01 time: 0.5660 data_time: 0.0525 memory: 23504 grad_norm: 3.3609 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 0.8579 loss: 0.8579 2022/09/08 18:33:33 - mmengine - INFO - Epoch(train) [38][1040/1253] lr: 4.0000e-03 eta: 2:29:49 time: 0.5593 data_time: 0.0335 memory: 23504 grad_norm: 3.4200 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9605 loss: 0.9605 2022/09/08 18:33:45 - mmengine - INFO - Epoch(train) [38][1060/1253] lr: 4.0000e-03 eta: 2:29:38 time: 0.5749 data_time: 0.0336 memory: 23504 grad_norm: 3.3974 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8289 loss: 0.8289 2022/09/08 18:33:57 - mmengine - INFO - Epoch(train) [38][1080/1253] lr: 4.0000e-03 eta: 2:29:26 time: 0.5818 data_time: 0.0483 memory: 23504 grad_norm: 3.4128 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9130 loss: 0.9130 2022/09/08 18:34:09 - mmengine - INFO - Epoch(train) [38][1100/1253] lr: 4.0000e-03 eta: 2:29:14 time: 0.6069 data_time: 0.0538 memory: 23504 grad_norm: 3.3894 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9615 loss: 0.9615 2022/09/08 18:34:20 - mmengine - INFO - Epoch(train) [38][1120/1253] lr: 4.0000e-03 eta: 2:29:02 time: 0.5687 data_time: 0.0369 memory: 23504 grad_norm: 3.3238 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8916 loss: 0.8916 2022/09/08 18:34:32 - mmengine - INFO - Epoch(train) [38][1140/1253] lr: 4.0000e-03 eta: 2:28:50 time: 0.5898 data_time: 0.0355 memory: 23504 grad_norm: 3.3835 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9228 loss: 0.9228 2022/09/08 18:34:43 - mmengine - INFO - Epoch(train) [38][1160/1253] lr: 4.0000e-03 eta: 2:28:38 time: 0.5767 data_time: 0.0436 memory: 23504 grad_norm: 3.3655 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 1.0137 loss: 1.0137 2022/09/08 18:34:55 - mmengine - INFO - Epoch(train) [38][1180/1253] lr: 4.0000e-03 eta: 2:28:27 time: 0.5878 data_time: 0.0493 memory: 23504 grad_norm: 3.4316 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.9263 loss: 0.9263 2022/09/08 18:35:07 - mmengine - INFO - Epoch(train) [38][1200/1253] lr: 4.0000e-03 eta: 2:28:15 time: 0.6069 data_time: 0.0700 memory: 23504 grad_norm: 3.4071 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9168 loss: 0.9168 2022/09/08 18:35:19 - mmengine - INFO - Epoch(train) [38][1220/1253] lr: 4.0000e-03 eta: 2:28:03 time: 0.5796 data_time: 0.0432 memory: 23504 grad_norm: 3.3655 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9267 loss: 0.9267 2022/09/08 18:35:31 - mmengine - INFO - Epoch(train) [38][1240/1253] lr: 4.0000e-03 eta: 2:27:51 time: 0.5848 data_time: 0.0317 memory: 23504 grad_norm: 3.3875 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 0.9643 loss: 0.9643 2022/09/08 18:35:36 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 18:35:36 - mmengine - INFO - Epoch(train) [38][1253/1253] lr: 4.0000e-03 eta: 2:27:51 time: 0.4431 data_time: 0.0213 memory: 23504 grad_norm: 3.6872 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.0561 loss: 1.0561 2022/09/08 18:36:00 - mmengine - INFO - Epoch(train) [39][20/1253] lr: 4.0000e-03 eta: 2:27:33 time: 1.1722 data_time: 0.6366 memory: 23504 grad_norm: 3.3443 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 0.8421 loss: 0.8421 2022/09/08 18:36:13 - mmengine - INFO - Epoch(train) [39][40/1253] lr: 4.0000e-03 eta: 2:27:22 time: 0.6738 data_time: 0.1506 memory: 23504 grad_norm: 3.4629 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 0.9263 loss: 0.9263 2022/09/08 18:36:24 - mmengine - INFO - Epoch(train) [39][60/1253] lr: 4.0000e-03 eta: 2:27:10 time: 0.5384 data_time: 0.0348 memory: 23504 grad_norm: 3.2956 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8925 loss: 0.8925 2022/09/08 18:36:35 - mmengine - INFO - Epoch(train) [39][80/1253] lr: 4.0000e-03 eta: 2:26:58 time: 0.5589 data_time: 0.0480 memory: 23504 grad_norm: 3.4120 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.9034 loss: 0.9034 2022/09/08 18:36:47 - mmengine - INFO - Epoch(train) [39][100/1253] lr: 4.0000e-03 eta: 2:26:46 time: 0.5916 data_time: 0.0490 memory: 23504 grad_norm: 3.3504 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9236 loss: 0.9236 2022/09/08 18:37:01 - mmengine - INFO - Epoch(train) [39][120/1253] lr: 4.0000e-03 eta: 2:26:35 time: 0.7104 data_time: 0.1026 memory: 23504 grad_norm: 3.3539 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9779 loss: 0.9779 2022/09/08 18:37:13 - mmengine - INFO - Epoch(train) [39][140/1253] lr: 4.0000e-03 eta: 2:26:23 time: 0.5675 data_time: 0.0336 memory: 23504 grad_norm: 3.4317 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.8932 loss: 0.8932 2022/09/08 18:37:24 - mmengine - INFO - Epoch(train) [39][160/1253] lr: 4.0000e-03 eta: 2:26:11 time: 0.5501 data_time: 0.0334 memory: 23504 grad_norm: 3.3326 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8327 loss: 0.8327 2022/09/08 18:37:35 - mmengine - INFO - Epoch(train) [39][180/1253] lr: 4.0000e-03 eta: 2:25:59 time: 0.5533 data_time: 0.0409 memory: 23504 grad_norm: 3.3915 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8516 loss: 0.8516 2022/09/08 18:37:46 - mmengine - INFO - Epoch(train) [39][200/1253] lr: 4.0000e-03 eta: 2:25:47 time: 0.5719 data_time: 0.0545 memory: 23504 grad_norm: 3.3100 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7735 loss: 0.7735 2022/09/08 18:37:58 - mmengine - INFO - Epoch(train) [39][220/1253] lr: 4.0000e-03 eta: 2:25:35 time: 0.5877 data_time: 0.0415 memory: 23504 grad_norm: 3.3959 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8558 loss: 0.8558 2022/09/08 18:38:12 - mmengine - INFO - Epoch(train) [39][240/1253] lr: 4.0000e-03 eta: 2:25:24 time: 0.6805 data_time: 0.0381 memory: 23504 grad_norm: 3.4609 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9814 loss: 0.9814 2022/09/08 18:38:22 - mmengine - INFO - Epoch(train) [39][260/1253] lr: 4.0000e-03 eta: 2:25:12 time: 0.5455 data_time: 0.0395 memory: 23504 grad_norm: 3.4151 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8024 loss: 0.8024 2022/09/08 18:38:33 - mmengine - INFO - Epoch(train) [39][280/1253] lr: 4.0000e-03 eta: 2:25:00 time: 0.5485 data_time: 0.0436 memory: 23504 grad_norm: 3.3428 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 0.8851 loss: 0.8851 2022/09/08 18:38:45 - mmengine - INFO - Epoch(train) [39][300/1253] lr: 4.0000e-03 eta: 2:24:48 time: 0.5738 data_time: 0.0424 memory: 23504 grad_norm: 3.4163 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.8030 loss: 0.8030 2022/09/08 18:38:56 - mmengine - INFO - Epoch(train) [39][320/1253] lr: 4.0000e-03 eta: 2:24:36 time: 0.5640 data_time: 0.0543 memory: 23504 grad_norm: 3.4398 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.8366 loss: 0.8366 2022/09/08 18:39:07 - mmengine - INFO - Epoch(train) [39][340/1253] lr: 4.0000e-03 eta: 2:24:24 time: 0.5469 data_time: 0.0355 memory: 23504 grad_norm: 3.4238 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 0.8880 loss: 0.8880 2022/09/08 18:39:21 - mmengine - INFO - Epoch(train) [39][360/1253] lr: 4.0000e-03 eta: 2:24:13 time: 0.6817 data_time: 0.1608 memory: 23504 grad_norm: 3.4018 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.9728 loss: 0.9728 2022/09/08 18:39:32 - mmengine - INFO - Epoch(train) [39][380/1253] lr: 4.0000e-03 eta: 2:24:01 time: 0.5585 data_time: 0.0481 memory: 23504 grad_norm: 3.4553 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8198 loss: 0.8198 2022/09/08 18:39:38 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 18:39:46 - mmengine - INFO - Epoch(train) [39][400/1253] lr: 4.0000e-03 eta: 2:23:50 time: 0.7083 data_time: 0.0319 memory: 23504 grad_norm: 3.4262 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 0.9681 loss: 0.9681 2022/09/08 18:39:57 - mmengine - INFO - Epoch(train) [39][420/1253] lr: 4.0000e-03 eta: 2:23:38 time: 0.5602 data_time: 0.0458 memory: 23504 grad_norm: 3.4383 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.0264 loss: 1.0264 2022/09/08 18:40:09 - mmengine - INFO - Epoch(train) [39][440/1253] lr: 4.0000e-03 eta: 2:23:26 time: 0.5596 data_time: 0.0475 memory: 23504 grad_norm: 3.2981 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.8820 loss: 0.8820 2022/09/08 18:40:20 - mmengine - INFO - Epoch(train) [39][460/1253] lr: 4.0000e-03 eta: 2:23:14 time: 0.5632 data_time: 0.0391 memory: 23504 grad_norm: 3.3678 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 0.8639 loss: 0.8639 2022/09/08 18:40:32 - mmengine - INFO - Epoch(train) [39][480/1253] lr: 4.0000e-03 eta: 2:23:02 time: 0.6050 data_time: 0.0384 memory: 23504 grad_norm: 3.3343 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8527 loss: 0.8527 2022/09/08 18:40:44 - mmengine - INFO - Epoch(train) [39][500/1253] lr: 4.0000e-03 eta: 2:22:50 time: 0.6078 data_time: 0.0356 memory: 23504 grad_norm: 3.4694 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.0154 loss: 1.0154 2022/09/08 18:40:56 - mmengine - INFO - Epoch(train) [39][520/1253] lr: 4.0000e-03 eta: 2:22:39 time: 0.6007 data_time: 0.0685 memory: 23504 grad_norm: 3.5558 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 0.9187 loss: 0.9187 2022/09/08 18:41:08 - mmengine - INFO - Epoch(train) [39][540/1253] lr: 4.0000e-03 eta: 2:22:27 time: 0.5971 data_time: 0.0747 memory: 23504 grad_norm: 3.4208 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.0215 loss: 1.0215 2022/09/08 18:41:20 - mmengine - INFO - Epoch(train) [39][560/1253] lr: 4.0000e-03 eta: 2:22:15 time: 0.6063 data_time: 0.0397 memory: 23504 grad_norm: 3.3969 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8512 loss: 0.8512 2022/09/08 18:41:31 - mmengine - INFO - Epoch(train) [39][580/1253] lr: 4.0000e-03 eta: 2:22:03 time: 0.5607 data_time: 0.0434 memory: 23504 grad_norm: 3.4462 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9361 loss: 0.9361 2022/09/08 18:41:44 - mmengine - INFO - Epoch(train) [39][600/1253] lr: 4.0000e-03 eta: 2:21:52 time: 0.6102 data_time: 0.0494 memory: 23504 grad_norm: 3.4272 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8392 loss: 0.8392 2022/09/08 18:41:55 - mmengine - INFO - Epoch(train) [39][620/1253] lr: 4.0000e-03 eta: 2:21:40 time: 0.5835 data_time: 0.0508 memory: 23504 grad_norm: 3.4168 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 0.8605 loss: 0.8605 2022/09/08 18:42:06 - mmengine - INFO - Epoch(train) [39][640/1253] lr: 4.0000e-03 eta: 2:21:28 time: 0.5481 data_time: 0.0530 memory: 23504 grad_norm: 3.4815 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.7149 loss: 0.7149 2022/09/08 18:42:18 - mmengine - INFO - Epoch(train) [39][660/1253] lr: 4.0000e-03 eta: 2:21:16 time: 0.5733 data_time: 0.0423 memory: 23504 grad_norm: 3.4618 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9659 loss: 0.9659 2022/09/08 18:42:29 - mmengine - INFO - Epoch(train) [39][680/1253] lr: 4.0000e-03 eta: 2:21:04 time: 0.5775 data_time: 0.0528 memory: 23504 grad_norm: 3.3867 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9144 loss: 0.9144 2022/09/08 18:42:42 - mmengine - INFO - Epoch(train) [39][700/1253] lr: 4.0000e-03 eta: 2:20:53 time: 0.6465 data_time: 0.0913 memory: 23504 grad_norm: 3.4787 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.8662 loss: 0.8662 2022/09/08 18:42:54 - mmengine - INFO - Epoch(train) [39][720/1253] lr: 4.0000e-03 eta: 2:20:41 time: 0.5998 data_time: 0.0318 memory: 23504 grad_norm: 3.3734 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8465 loss: 0.8465 2022/09/08 18:43:06 - mmengine - INFO - Epoch(train) [39][740/1253] lr: 4.0000e-03 eta: 2:20:29 time: 0.5689 data_time: 0.0329 memory: 23504 grad_norm: 3.5019 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.9096 loss: 0.9096 2022/09/08 18:43:19 - mmengine - INFO - Epoch(train) [39][760/1253] lr: 4.0000e-03 eta: 2:20:18 time: 0.6858 data_time: 0.1750 memory: 23504 grad_norm: 3.3949 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.9372 loss: 0.9372 2022/09/08 18:43:30 - mmengine - INFO - Epoch(train) [39][780/1253] lr: 4.0000e-03 eta: 2:20:06 time: 0.5550 data_time: 0.0300 memory: 23504 grad_norm: 3.4958 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8998 loss: 0.8998 2022/09/08 18:43:42 - mmengine - INFO - Epoch(train) [39][800/1253] lr: 4.0000e-03 eta: 2:19:54 time: 0.5664 data_time: 0.0343 memory: 23504 grad_norm: 3.4297 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0240 loss: 1.0240 2022/09/08 18:43:54 - mmengine - INFO - Epoch(train) [39][820/1253] lr: 4.0000e-03 eta: 2:19:42 time: 0.6122 data_time: 0.0367 memory: 23504 grad_norm: 3.4125 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9162 loss: 0.9162 2022/09/08 18:44:07 - mmengine - INFO - Epoch(train) [39][840/1253] lr: 4.0000e-03 eta: 2:19:31 time: 0.6685 data_time: 0.0376 memory: 23504 grad_norm: 3.4816 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9247 loss: 0.9247 2022/09/08 18:44:19 - mmengine - INFO - Epoch(train) [39][860/1253] lr: 4.0000e-03 eta: 2:19:19 time: 0.5657 data_time: 0.0337 memory: 23504 grad_norm: 3.5370 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8426 loss: 0.8426 2022/09/08 18:44:30 - mmengine - INFO - Epoch(train) [39][880/1253] lr: 4.0000e-03 eta: 2:19:07 time: 0.5619 data_time: 0.0498 memory: 23504 grad_norm: 3.4050 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.8331 loss: 0.8331 2022/09/08 18:44:42 - mmengine - INFO - Epoch(train) [39][900/1253] lr: 4.0000e-03 eta: 2:18:55 time: 0.5764 data_time: 0.0504 memory: 23504 grad_norm: 3.3802 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.8817 loss: 0.8817 2022/09/08 18:44:53 - mmengine - INFO - Epoch(train) [39][920/1253] lr: 4.0000e-03 eta: 2:18:43 time: 0.5770 data_time: 0.0379 memory: 23504 grad_norm: 3.3220 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.8401 loss: 0.8401 2022/09/08 18:45:05 - mmengine - INFO - Epoch(train) [39][940/1253] lr: 4.0000e-03 eta: 2:18:31 time: 0.5912 data_time: 0.0484 memory: 23504 grad_norm: 3.3788 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8953 loss: 0.8953 2022/09/08 18:45:17 - mmengine - INFO - Epoch(train) [39][960/1253] lr: 4.0000e-03 eta: 2:18:20 time: 0.6158 data_time: 0.0436 memory: 23504 grad_norm: 3.4954 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9626 loss: 0.9626 2022/09/08 18:45:29 - mmengine - INFO - Epoch(train) [39][980/1253] lr: 4.0000e-03 eta: 2:18:08 time: 0.5868 data_time: 0.0474 memory: 23504 grad_norm: 3.4060 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8337 loss: 0.8337 2022/09/08 18:45:41 - mmengine - INFO - Epoch(train) [39][1000/1253] lr: 4.0000e-03 eta: 2:17:56 time: 0.5815 data_time: 0.0408 memory: 23504 grad_norm: 3.4115 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8571 loss: 0.8571 2022/09/08 18:45:53 - mmengine - INFO - Epoch(train) [39][1020/1253] lr: 4.0000e-03 eta: 2:17:45 time: 0.6402 data_time: 0.0369 memory: 23504 grad_norm: 3.5135 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.9543 loss: 0.9543 2022/09/08 18:46:05 - mmengine - INFO - Epoch(train) [39][1040/1253] lr: 4.0000e-03 eta: 2:17:33 time: 0.5623 data_time: 0.0384 memory: 23504 grad_norm: 3.4532 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9695 loss: 0.9695 2022/09/08 18:46:16 - mmengine - INFO - Epoch(train) [39][1060/1253] lr: 4.0000e-03 eta: 2:17:21 time: 0.5603 data_time: 0.0450 memory: 23504 grad_norm: 3.3214 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9410 loss: 0.9410 2022/09/08 18:46:27 - mmengine - INFO - Epoch(train) [39][1080/1253] lr: 4.0000e-03 eta: 2:17:09 time: 0.5768 data_time: 0.0616 memory: 23504 grad_norm: 3.3979 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.9501 loss: 0.9501 2022/09/08 18:46:39 - mmengine - INFO - Epoch(train) [39][1100/1253] lr: 4.0000e-03 eta: 2:16:57 time: 0.5576 data_time: 0.0386 memory: 23504 grad_norm: 3.3514 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.8997 loss: 0.8997 2022/09/08 18:46:51 - mmengine - INFO - Epoch(train) [39][1120/1253] lr: 4.0000e-03 eta: 2:16:45 time: 0.6045 data_time: 0.0399 memory: 23504 grad_norm: 3.3450 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.9025 loss: 0.9025 2022/09/08 18:47:02 - mmengine - INFO - Epoch(train) [39][1140/1253] lr: 4.0000e-03 eta: 2:16:33 time: 0.5841 data_time: 0.0486 memory: 23504 grad_norm: 3.4154 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.9214 loss: 0.9214 2022/09/08 18:47:15 - mmengine - INFO - Epoch(train) [39][1160/1253] lr: 4.0000e-03 eta: 2:16:22 time: 0.6103 data_time: 0.0475 memory: 23504 grad_norm: 3.4660 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9413 loss: 0.9413 2022/09/08 18:47:26 - mmengine - INFO - Epoch(train) [39][1180/1253] lr: 4.0000e-03 eta: 2:16:10 time: 0.5863 data_time: 0.0305 memory: 23504 grad_norm: 3.4752 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 0.9454 loss: 0.9454 2022/09/08 18:47:38 - mmengine - INFO - Epoch(train) [39][1200/1253] lr: 4.0000e-03 eta: 2:15:58 time: 0.5921 data_time: 0.0400 memory: 23504 grad_norm: 3.5460 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 0.9253 loss: 0.9253 2022/09/08 18:47:51 - mmengine - INFO - Epoch(train) [39][1220/1253] lr: 4.0000e-03 eta: 2:15:47 time: 0.6567 data_time: 0.0378 memory: 23504 grad_norm: 3.5095 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9868 loss: 0.9868 2022/09/08 18:48:01 - mmengine - INFO - Epoch(train) [39][1240/1253] lr: 4.0000e-03 eta: 2:15:34 time: 0.4783 data_time: 0.0260 memory: 23504 grad_norm: 3.4771 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9702 loss: 0.9702 2022/09/08 18:48:06 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 18:48:06 - mmengine - INFO - Epoch(train) [39][1253/1253] lr: 4.0000e-03 eta: 2:15:34 time: 0.4343 data_time: 0.0185 memory: 23504 grad_norm: 3.5225 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.8870 loss: 0.8870 2022/09/08 18:48:30 - mmengine - INFO - Epoch(train) [40][20/1253] lr: 4.0000e-03 eta: 2:15:16 time: 1.1724 data_time: 0.4726 memory: 23504 grad_norm: 3.3578 top1_acc: 0.9583 top5_acc: 0.9583 loss_cls: 0.8104 loss: 0.8104 2022/09/08 18:48:41 - mmengine - INFO - Epoch(train) [40][40/1253] lr: 4.0000e-03 eta: 2:15:04 time: 0.5489 data_time: 0.0393 memory: 23504 grad_norm: 3.4066 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.9489 loss: 0.9489 2022/09/08 18:48:52 - mmengine - INFO - Epoch(train) [40][60/1253] lr: 4.0000e-03 eta: 2:14:52 time: 0.5674 data_time: 0.0428 memory: 23504 grad_norm: 3.3882 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8657 loss: 0.8657 2022/09/08 18:49:03 - mmengine - INFO - Epoch(train) [40][80/1253] lr: 4.0000e-03 eta: 2:14:40 time: 0.5557 data_time: 0.0374 memory: 23504 grad_norm: 3.3711 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.8628 loss: 0.8628 2022/09/08 18:49:18 - mmengine - INFO - Epoch(train) [40][100/1253] lr: 4.0000e-03 eta: 2:14:29 time: 0.7366 data_time: 0.0394 memory: 23504 grad_norm: 3.4022 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8210 loss: 0.8210 2022/09/08 18:49:31 - mmengine - INFO - Epoch(train) [40][120/1253] lr: 4.0000e-03 eta: 2:14:17 time: 0.6493 data_time: 0.0397 memory: 23504 grad_norm: 3.4791 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.8091 loss: 0.8091 2022/09/08 18:49:40 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 18:49:44 - mmengine - INFO - Epoch(train) [40][140/1253] lr: 4.0000e-03 eta: 2:14:06 time: 0.6461 data_time: 0.0327 memory: 23504 grad_norm: 3.4017 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 0.7716 loss: 0.7716 2022/09/08 18:49:55 - mmengine - INFO - Epoch(train) [40][160/1253] lr: 4.0000e-03 eta: 2:13:54 time: 0.5397 data_time: 0.0332 memory: 23504 grad_norm: 3.4031 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8889 loss: 0.8889 2022/09/08 18:50:07 - mmengine - INFO - Epoch(train) [40][180/1253] lr: 4.0000e-03 eta: 2:13:42 time: 0.5918 data_time: 0.0440 memory: 23504 grad_norm: 3.4343 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8277 loss: 0.8277 2022/09/08 18:50:18 - mmengine - INFO - Epoch(train) [40][200/1253] lr: 4.0000e-03 eta: 2:13:30 time: 0.5708 data_time: 0.0506 memory: 23504 grad_norm: 3.4152 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8193 loss: 0.8193 2022/09/08 18:50:30 - mmengine - INFO - Epoch(train) [40][220/1253] lr: 4.0000e-03 eta: 2:13:18 time: 0.5763 data_time: 0.0437 memory: 23504 grad_norm: 3.4991 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.8646 loss: 0.8646 2022/09/08 18:50:41 - mmengine - INFO - Epoch(train) [40][240/1253] lr: 4.0000e-03 eta: 2:13:06 time: 0.5663 data_time: 0.0570 memory: 23504 grad_norm: 3.4491 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.8988 loss: 0.8988 2022/09/08 18:50:52 - mmengine - INFO - Epoch(train) [40][260/1253] lr: 4.0000e-03 eta: 2:12:54 time: 0.5623 data_time: 0.0381 memory: 23504 grad_norm: 3.3415 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.8646 loss: 0.8646 2022/09/08 18:51:04 - mmengine - INFO - Epoch(train) [40][280/1253] lr: 4.0000e-03 eta: 2:12:43 time: 0.6003 data_time: 0.0783 memory: 23504 grad_norm: 3.4024 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8192 loss: 0.8192 2022/09/08 18:51:18 - mmengine - INFO - Epoch(train) [40][300/1253] lr: 4.0000e-03 eta: 2:12:31 time: 0.6673 data_time: 0.0388 memory: 23504 grad_norm: 3.4419 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9191 loss: 0.9191 2022/09/08 18:51:30 - mmengine - INFO - Epoch(train) [40][320/1253] lr: 4.0000e-03 eta: 2:12:20 time: 0.5919 data_time: 0.0458 memory: 23504 grad_norm: 3.6346 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.0217 loss: 1.0217 2022/09/08 18:51:41 - mmengine - INFO - Epoch(train) [40][340/1253] lr: 4.0000e-03 eta: 2:12:08 time: 0.5665 data_time: 0.0353 memory: 23504 grad_norm: 3.4567 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 0.8414 loss: 0.8414 2022/09/08 18:51:52 - mmengine - INFO - Epoch(train) [40][360/1253] lr: 4.0000e-03 eta: 2:11:56 time: 0.5581 data_time: 0.0370 memory: 23504 grad_norm: 3.4687 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.8059 loss: 0.8059 2022/09/08 18:52:03 - mmengine - INFO - Epoch(train) [40][380/1253] lr: 4.0000e-03 eta: 2:11:44 time: 0.5679 data_time: 0.0394 memory: 23504 grad_norm: 3.5114 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 0.8853 loss: 0.8853 2022/09/08 18:52:15 - mmengine - INFO - Epoch(train) [40][400/1253] lr: 4.0000e-03 eta: 2:11:32 time: 0.5910 data_time: 0.0503 memory: 23504 grad_norm: 3.3371 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8918 loss: 0.8918 2022/09/08 18:52:27 - mmengine - INFO - Epoch(train) [40][420/1253] lr: 4.0000e-03 eta: 2:11:20 time: 0.5696 data_time: 0.0330 memory: 23504 grad_norm: 3.4229 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8580 loss: 0.8580 2022/09/08 18:52:38 - mmengine - INFO - Epoch(train) [40][440/1253] lr: 4.0000e-03 eta: 2:11:08 time: 0.5767 data_time: 0.0360 memory: 23504 grad_norm: 3.4176 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8576 loss: 0.8576 2022/09/08 18:52:49 - mmengine - INFO - Epoch(train) [40][460/1253] lr: 4.0000e-03 eta: 2:10:56 time: 0.5645 data_time: 0.0403 memory: 23504 grad_norm: 3.4139 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9177 loss: 0.9177 2022/09/08 18:53:01 - mmengine - INFO - Epoch(train) [40][480/1253] lr: 4.0000e-03 eta: 2:10:44 time: 0.5799 data_time: 0.0486 memory: 23504 grad_norm: 3.3580 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8048 loss: 0.8048 2022/09/08 18:53:13 - mmengine - INFO - Epoch(train) [40][500/1253] lr: 4.0000e-03 eta: 2:10:33 time: 0.5767 data_time: 0.0491 memory: 23504 grad_norm: 3.4759 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8797 loss: 0.8797 2022/09/08 18:53:25 - mmengine - INFO - Epoch(train) [40][520/1253] lr: 4.0000e-03 eta: 2:10:21 time: 0.5982 data_time: 0.0335 memory: 23504 grad_norm: 3.5161 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8110 loss: 0.8110 2022/09/08 18:53:36 - mmengine - INFO - Epoch(train) [40][540/1253] lr: 4.0000e-03 eta: 2:10:09 time: 0.5710 data_time: 0.0432 memory: 23504 grad_norm: 3.5694 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 0.9108 loss: 0.9108 2022/09/08 18:53:49 - mmengine - INFO - Epoch(train) [40][560/1253] lr: 4.0000e-03 eta: 2:09:58 time: 0.6610 data_time: 0.0450 memory: 23504 grad_norm: 3.3949 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8507 loss: 0.8507 2022/09/08 18:54:02 - mmengine - INFO - Epoch(train) [40][580/1253] lr: 4.0000e-03 eta: 2:09:46 time: 0.6211 data_time: 0.0390 memory: 23504 grad_norm: 3.3795 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7814 loss: 0.7814 2022/09/08 18:54:13 - mmengine - INFO - Epoch(train) [40][600/1253] lr: 4.0000e-03 eta: 2:09:34 time: 0.5512 data_time: 0.0436 memory: 23504 grad_norm: 3.4247 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8282 loss: 0.8282 2022/09/08 18:54:24 - mmengine - INFO - Epoch(train) [40][620/1253] lr: 4.0000e-03 eta: 2:09:22 time: 0.5570 data_time: 0.0391 memory: 23504 grad_norm: 3.4877 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 0.9070 loss: 0.9070 2022/09/08 18:54:35 - mmengine - INFO - Epoch(train) [40][640/1253] lr: 4.0000e-03 eta: 2:09:10 time: 0.5594 data_time: 0.0482 memory: 23504 grad_norm: 3.5565 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 0.8168 loss: 0.8168 2022/09/08 18:54:50 - mmengine - INFO - Epoch(train) [40][660/1253] lr: 4.0000e-03 eta: 2:08:59 time: 0.7575 data_time: 0.0429 memory: 23504 grad_norm: 3.5111 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.8674 loss: 0.8674 2022/09/08 18:55:01 - mmengine - INFO - Epoch(train) [40][680/1253] lr: 4.0000e-03 eta: 2:08:47 time: 0.5367 data_time: 0.0558 memory: 23504 grad_norm: 3.4657 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 0.9786 loss: 0.9786 2022/09/08 18:55:12 - mmengine - INFO - Epoch(train) [40][700/1253] lr: 4.0000e-03 eta: 2:08:35 time: 0.5469 data_time: 0.0448 memory: 23504 grad_norm: 3.4439 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9537 loss: 0.9537 2022/09/08 18:55:23 - mmengine - INFO - Epoch(train) [40][720/1253] lr: 4.0000e-03 eta: 2:08:23 time: 0.5619 data_time: 0.0479 memory: 23504 grad_norm: 3.4907 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.0300 loss: 1.0300 2022/09/08 18:55:37 - mmengine - INFO - Epoch(train) [40][740/1253] lr: 4.0000e-03 eta: 2:08:12 time: 0.7182 data_time: 0.1767 memory: 23504 grad_norm: 3.3952 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.8688 loss: 0.8688 2022/09/08 18:55:48 - mmengine - INFO - Epoch(train) [40][760/1253] lr: 4.0000e-03 eta: 2:08:00 time: 0.5455 data_time: 0.0310 memory: 23504 grad_norm: 3.4489 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.7586 loss: 0.7586 2022/09/08 18:56:02 - mmengine - INFO - Epoch(train) [40][780/1253] lr: 4.0000e-03 eta: 2:07:49 time: 0.6902 data_time: 0.0500 memory: 23504 grad_norm: 3.4141 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.8232 loss: 0.8232 2022/09/08 18:56:13 - mmengine - INFO - Epoch(train) [40][800/1253] lr: 4.0000e-03 eta: 2:07:36 time: 0.5288 data_time: 0.0382 memory: 23504 grad_norm: 3.4767 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8062 loss: 0.8062 2022/09/08 18:56:24 - mmengine - INFO - Epoch(train) [40][820/1253] lr: 4.0000e-03 eta: 2:07:24 time: 0.5432 data_time: 0.0314 memory: 23504 grad_norm: 3.5191 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.8285 loss: 0.8285 2022/09/08 18:56:35 - mmengine - INFO - Epoch(train) [40][840/1253] lr: 4.0000e-03 eta: 2:07:13 time: 0.5880 data_time: 0.0432 memory: 23504 grad_norm: 3.5042 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8372 loss: 0.8372 2022/09/08 18:56:48 - mmengine - INFO - Epoch(train) [40][860/1253] lr: 4.0000e-03 eta: 2:07:01 time: 0.6163 data_time: 0.0520 memory: 23504 grad_norm: 3.5048 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8620 loss: 0.8620 2022/09/08 18:56:59 - mmengine - INFO - Epoch(train) [40][880/1253] lr: 4.0000e-03 eta: 2:06:49 time: 0.5702 data_time: 0.0339 memory: 23504 grad_norm: 3.4611 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 0.9680 loss: 0.9680 2022/09/08 18:57:11 - mmengine - INFO - Epoch(train) [40][900/1253] lr: 4.0000e-03 eta: 2:06:37 time: 0.5684 data_time: 0.0412 memory: 23504 grad_norm: 3.4789 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.0451 loss: 1.0451 2022/09/08 18:57:25 - mmengine - INFO - Epoch(train) [40][920/1253] lr: 4.0000e-03 eta: 2:06:26 time: 0.7095 data_time: 0.0494 memory: 23504 grad_norm: 3.4429 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9598 loss: 0.9598 2022/09/08 18:57:37 - mmengine - INFO - Epoch(train) [40][940/1253] lr: 4.0000e-03 eta: 2:06:14 time: 0.6157 data_time: 0.0322 memory: 23504 grad_norm: 3.4776 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7763 loss: 0.7763 2022/09/08 18:57:48 - mmengine - INFO - Epoch(train) [40][960/1253] lr: 4.0000e-03 eta: 2:06:02 time: 0.5381 data_time: 0.0317 memory: 23504 grad_norm: 3.4572 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.9591 loss: 0.9591 2022/09/08 18:58:01 - mmengine - INFO - Epoch(train) [40][980/1253] lr: 4.0000e-03 eta: 2:05:51 time: 0.6412 data_time: 0.0400 memory: 23504 grad_norm: 3.4910 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 0.9049 loss: 0.9049 2022/09/08 18:58:12 - mmengine - INFO - Epoch(train) [40][1000/1253] lr: 4.0000e-03 eta: 2:05:39 time: 0.5584 data_time: 0.0426 memory: 23504 grad_norm: 3.4558 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.7578 loss: 0.7578 2022/09/08 18:58:23 - mmengine - INFO - Epoch(train) [40][1020/1253] lr: 4.0000e-03 eta: 2:05:27 time: 0.5828 data_time: 0.0824 memory: 23504 grad_norm: 3.5285 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9502 loss: 0.9502 2022/09/08 18:58:34 - mmengine - INFO - Epoch(train) [40][1040/1253] lr: 4.0000e-03 eta: 2:05:15 time: 0.5407 data_time: 0.0455 memory: 23504 grad_norm: 3.6028 top1_acc: 0.5833 top5_acc: 0.9583 loss_cls: 1.0751 loss: 1.0751 2022/09/08 18:58:45 - mmengine - INFO - Epoch(train) [40][1060/1253] lr: 4.0000e-03 eta: 2:05:03 time: 0.5523 data_time: 0.0481 memory: 23504 grad_norm: 3.5296 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 0.9106 loss: 0.9106 2022/09/08 18:58:57 - mmengine - INFO - Epoch(train) [40][1080/1253] lr: 4.0000e-03 eta: 2:04:51 time: 0.5628 data_time: 0.0409 memory: 23504 grad_norm: 3.4765 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.9487 loss: 0.9487 2022/09/08 18:59:11 - mmengine - INFO - Epoch(train) [40][1100/1253] lr: 4.0000e-03 eta: 2:04:40 time: 0.7041 data_time: 0.0461 memory: 23504 grad_norm: 3.5358 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 0.9421 loss: 0.9421 2022/09/08 18:59:22 - mmengine - INFO - Epoch(train) [40][1120/1253] lr: 4.0000e-03 eta: 2:04:28 time: 0.5413 data_time: 0.0380 memory: 23504 grad_norm: 3.4787 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.9659 loss: 0.9659 2022/09/08 18:59:29 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 18:59:33 - mmengine - INFO - Epoch(train) [40][1140/1253] lr: 4.0000e-03 eta: 2:04:16 time: 0.5737 data_time: 0.0511 memory: 23504 grad_norm: 3.4389 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.8080 loss: 0.8080 2022/09/08 18:59:45 - mmengine - INFO - Epoch(train) [40][1160/1253] lr: 4.0000e-03 eta: 2:04:04 time: 0.6026 data_time: 0.0354 memory: 23504 grad_norm: 3.5166 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.9381 loss: 0.9381 2022/09/08 18:59:57 - mmengine - INFO - Epoch(train) [40][1180/1253] lr: 4.0000e-03 eta: 2:03:52 time: 0.5821 data_time: 0.0484 memory: 23504 grad_norm: 3.5668 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.0726 loss: 1.0726 2022/09/08 19:00:10 - mmengine - INFO - Epoch(train) [40][1200/1253] lr: 4.0000e-03 eta: 2:03:41 time: 0.6415 data_time: 0.0298 memory: 23504 grad_norm: 3.5323 top1_acc: 0.7917 top5_acc: 0.7917 loss_cls: 0.9218 loss: 0.9218 2022/09/08 19:00:21 - mmengine - INFO - Epoch(train) [40][1220/1253] lr: 4.0000e-03 eta: 2:03:29 time: 0.5677 data_time: 0.0519 memory: 23504 grad_norm: 3.5201 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8486 loss: 0.8486 2022/09/08 19:00:30 - mmengine - INFO - Epoch(train) [40][1240/1253] lr: 4.0000e-03 eta: 2:03:17 time: 0.4764 data_time: 0.0228 memory: 23504 grad_norm: 3.5417 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.9253 loss: 0.9253 2022/09/08 19:00:36 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 19:00:36 - mmengine - INFO - Epoch(train) [40][1253/1253] lr: 4.0000e-03 eta: 2:03:17 time: 0.4318 data_time: 0.0172 memory: 23504 grad_norm: 4.1264 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.8999 loss: 0.8999 2022/09/08 19:00:58 - mmengine - INFO - Epoch(val) [40][20/104] eta: 0:01:30 time: 1.0742 data_time: 0.9289 memory: 2699 2022/09/08 19:01:07 - mmengine - INFO - Epoch(val) [40][40/104] eta: 0:00:31 time: 0.4876 data_time: 0.3462 memory: 2699 2022/09/08 19:01:25 - mmengine - INFO - Epoch(val) [40][60/104] eta: 0:00:38 time: 0.8637 data_time: 0.7248 memory: 2699 2022/09/08 19:01:38 - mmengine - INFO - Epoch(val) [40][80/104] eta: 0:00:16 time: 0.6904 data_time: 0.5583 memory: 2699 2022/09/08 19:01:43 - mmengine - INFO - Epoch(val) [40][100/104] eta: 0:00:01 time: 0.2564 data_time: 0.1396 memory: 2699 2022/09/08 19:01:49 - mmengine - INFO - Epoch(val) [40][104/104] acc/top1: 0.7120 acc/top5: 0.9006 acc/mean1: 0.7119 2022/09/08 19:01:49 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb/best_acc/top1_epoch_35.pth is removed 2022/09/08 19:01:50 - mmengine - INFO - The best checkpoint with 0.7120 acc/top1 at 40 epoch is saved to best_acc/top1_epoch_40.pth. 2022/09/08 19:02:14 - mmengine - INFO - Epoch(train) [41][20/1253] lr: 4.0000e-04 eta: 2:02:58 time: 1.2120 data_time: 0.5235 memory: 23504 grad_norm: 3.3865 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.7428 loss: 0.7428 2022/09/08 19:02:25 - mmengine - INFO - Epoch(train) [41][40/1253] lr: 4.0000e-04 eta: 2:02:46 time: 0.5591 data_time: 0.0447 memory: 23504 grad_norm: 3.3506 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.8637 loss: 0.8637 2022/09/08 19:02:37 - mmengine - INFO - Epoch(train) [41][60/1253] lr: 4.0000e-04 eta: 2:02:35 time: 0.6003 data_time: 0.0810 memory: 23504 grad_norm: 3.4580 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 0.9786 loss: 0.9786 2022/09/08 19:02:48 - mmengine - INFO - Epoch(train) [41][80/1253] lr: 4.0000e-04 eta: 2:02:23 time: 0.5487 data_time: 0.0322 memory: 23504 grad_norm: 3.2824 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.8475 loss: 0.8475 2022/09/08 19:03:00 - mmengine - INFO - Epoch(train) [41][100/1253] lr: 4.0000e-04 eta: 2:02:11 time: 0.5674 data_time: 0.0486 memory: 23504 grad_norm: 3.3661 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8825 loss: 0.8825 2022/09/08 19:03:11 - mmengine - INFO - Epoch(train) [41][120/1253] lr: 4.0000e-04 eta: 2:01:59 time: 0.5826 data_time: 0.0375 memory: 23504 grad_norm: 3.3499 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8917 loss: 0.8917 2022/09/08 19:03:26 - mmengine - INFO - Epoch(train) [41][140/1253] lr: 4.0000e-04 eta: 2:01:48 time: 0.7052 data_time: 0.1647 memory: 23504 grad_norm: 3.3566 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.7353 loss: 0.7353 2022/09/08 19:03:36 - mmengine - INFO - Epoch(train) [41][160/1253] lr: 4.0000e-04 eta: 2:01:36 time: 0.5401 data_time: 0.0283 memory: 23504 grad_norm: 3.2861 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.7776 loss: 0.7776 2022/09/08 19:03:48 - mmengine - INFO - Epoch(train) [41][180/1253] lr: 4.0000e-04 eta: 2:01:24 time: 0.5767 data_time: 0.0509 memory: 23504 grad_norm: 3.3546 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 0.7911 loss: 0.7911 2022/09/08 19:03:59 - mmengine - INFO - Epoch(train) [41][200/1253] lr: 4.0000e-04 eta: 2:01:12 time: 0.5745 data_time: 0.0388 memory: 23504 grad_norm: 3.4747 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 0.8646 loss: 0.8646 2022/09/08 19:04:11 - mmengine - INFO - Epoch(train) [41][220/1253] lr: 4.0000e-04 eta: 2:01:00 time: 0.5637 data_time: 0.0341 memory: 23504 grad_norm: 3.4490 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9175 loss: 0.9175 2022/09/08 19:04:24 - mmengine - INFO - Epoch(train) [41][240/1253] lr: 4.0000e-04 eta: 2:00:48 time: 0.6561 data_time: 0.0547 memory: 23504 grad_norm: 3.3217 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.7119 loss: 0.7119 2022/09/08 19:04:35 - mmengine - INFO - Epoch(train) [41][260/1253] lr: 4.0000e-04 eta: 2:00:36 time: 0.5601 data_time: 0.0379 memory: 23504 grad_norm: 3.4074 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9614 loss: 0.9614 2022/09/08 19:04:46 - mmengine - INFO - Epoch(train) [41][280/1253] lr: 4.0000e-04 eta: 2:00:25 time: 0.5711 data_time: 0.0391 memory: 23504 grad_norm: 3.3836 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.0469 loss: 1.0469 2022/09/08 19:04:58 - mmengine - INFO - Epoch(train) [41][300/1253] lr: 4.0000e-04 eta: 2:00:13 time: 0.5630 data_time: 0.0518 memory: 23504 grad_norm: 3.3813 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.9172 loss: 0.9172 2022/09/08 19:05:09 - mmengine - INFO - Epoch(train) [41][320/1253] lr: 4.0000e-04 eta: 2:00:01 time: 0.5741 data_time: 0.0324 memory: 23504 grad_norm: 3.4244 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7798 loss: 0.7798 2022/09/08 19:05:22 - mmengine - INFO - Epoch(train) [41][340/1253] lr: 4.0000e-04 eta: 1:59:49 time: 0.6456 data_time: 0.0352 memory: 23504 grad_norm: 3.4060 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.9642 loss: 0.9642 2022/09/08 19:05:34 - mmengine - INFO - Epoch(train) [41][360/1253] lr: 4.0000e-04 eta: 1:59:38 time: 0.6136 data_time: 0.0490 memory: 23504 grad_norm: 3.3851 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.8582 loss: 0.8582 2022/09/08 19:05:48 - mmengine - INFO - Epoch(train) [41][380/1253] lr: 4.0000e-04 eta: 1:59:26 time: 0.6726 data_time: 0.0224 memory: 23504 grad_norm: 3.3814 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9059 loss: 0.9059 2022/09/08 19:05:59 - mmengine - INFO - Epoch(train) [41][400/1253] lr: 4.0000e-04 eta: 1:59:14 time: 0.5612 data_time: 0.0293 memory: 23504 grad_norm: 3.3780 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.8229 loss: 0.8229 2022/09/08 19:06:10 - mmengine - INFO - Epoch(train) [41][420/1253] lr: 4.0000e-04 eta: 1:59:02 time: 0.5542 data_time: 0.0385 memory: 23504 grad_norm: 3.3486 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8812 loss: 0.8812 2022/09/08 19:06:21 - mmengine - INFO - Epoch(train) [41][440/1253] lr: 4.0000e-04 eta: 1:58:50 time: 0.5561 data_time: 0.0432 memory: 23504 grad_norm: 3.3688 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8869 loss: 0.8869 2022/09/08 19:06:33 - mmengine - INFO - Epoch(train) [41][460/1253] lr: 4.0000e-04 eta: 1:58:39 time: 0.5901 data_time: 0.0482 memory: 23504 grad_norm: 3.4065 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.8240 loss: 0.8240 2022/09/08 19:06:45 - mmengine - INFO - Epoch(train) [41][480/1253] lr: 4.0000e-04 eta: 1:58:27 time: 0.5754 data_time: 0.0377 memory: 23504 grad_norm: 3.3911 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8971 loss: 0.8971 2022/09/08 19:06:56 - mmengine - INFO - Epoch(train) [41][500/1253] lr: 4.0000e-04 eta: 1:58:15 time: 0.5860 data_time: 0.0358 memory: 23504 grad_norm: 3.4813 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.8647 loss: 0.8647 2022/09/08 19:07:09 - mmengine - INFO - Epoch(train) [41][520/1253] lr: 4.0000e-04 eta: 1:58:03 time: 0.6192 data_time: 0.0599 memory: 23504 grad_norm: 3.3629 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8698 loss: 0.8698 2022/09/08 19:07:20 - mmengine - INFO - Epoch(train) [41][540/1253] lr: 4.0000e-04 eta: 1:57:51 time: 0.5748 data_time: 0.0422 memory: 23504 grad_norm: 3.4636 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.8833 loss: 0.8833 2022/09/08 19:07:31 - mmengine - INFO - Epoch(train) [41][560/1253] lr: 4.0000e-04 eta: 1:57:39 time: 0.5596 data_time: 0.0332 memory: 23504 grad_norm: 3.3553 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8341 loss: 0.8341 2022/09/08 19:07:43 - mmengine - INFO - Epoch(train) [41][580/1253] lr: 4.0000e-04 eta: 1:57:28 time: 0.5942 data_time: 0.0431 memory: 23504 grad_norm: 3.3735 top1_acc: 0.6667 top5_acc: 0.7500 loss_cls: 0.9920 loss: 0.9920 2022/09/08 19:07:55 - mmengine - INFO - Epoch(train) [41][600/1253] lr: 4.0000e-04 eta: 1:57:16 time: 0.5653 data_time: 0.0515 memory: 23504 grad_norm: 3.3532 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.9296 loss: 0.9296 2022/09/08 19:08:07 - mmengine - INFO - Epoch(train) [41][620/1253] lr: 4.0000e-04 eta: 1:57:04 time: 0.6066 data_time: 0.0401 memory: 23504 grad_norm: 3.4019 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8904 loss: 0.8904 2022/09/08 19:08:19 - mmengine - INFO - Epoch(train) [41][640/1253] lr: 4.0000e-04 eta: 1:56:52 time: 0.5993 data_time: 0.0475 memory: 23504 grad_norm: 3.3295 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.8221 loss: 0.8221 2022/09/08 19:08:30 - mmengine - INFO - Epoch(train) [41][660/1253] lr: 4.0000e-04 eta: 1:56:40 time: 0.5744 data_time: 0.0304 memory: 23504 grad_norm: 3.2717 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.7507 loss: 0.7507 2022/09/08 19:08:42 - mmengine - INFO - Epoch(train) [41][680/1253] lr: 4.0000e-04 eta: 1:56:29 time: 0.5939 data_time: 0.0376 memory: 23504 grad_norm: 3.4458 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 0.8771 loss: 0.8771 2022/09/08 19:08:57 - mmengine - INFO - Epoch(train) [41][700/1253] lr: 4.0000e-04 eta: 1:56:17 time: 0.7245 data_time: 0.0459 memory: 23504 grad_norm: 3.4148 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.8892 loss: 0.8892 2022/09/08 19:09:08 - mmengine - INFO - Epoch(train) [41][720/1253] lr: 4.0000e-04 eta: 1:56:05 time: 0.5426 data_time: 0.0356 memory: 23504 grad_norm: 3.3895 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.9130 loss: 0.9130 2022/09/08 19:09:19 - mmengine - INFO - Epoch(train) [41][740/1253] lr: 4.0000e-04 eta: 1:55:53 time: 0.5635 data_time: 0.0403 memory: 23504 grad_norm: 3.2971 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.7772 loss: 0.7772 2022/09/08 19:09:30 - mmengine - INFO - Epoch(train) [41][760/1253] lr: 4.0000e-04 eta: 1:55:42 time: 0.5645 data_time: 0.0464 memory: 23504 grad_norm: 3.3369 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.7478 loss: 0.7478 2022/09/08 19:09:42 - mmengine - INFO - Epoch(train) [41][780/1253] lr: 4.0000e-04 eta: 1:55:30 time: 0.5809 data_time: 0.0490 memory: 23504 grad_norm: 3.3093 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.8138 loss: 0.8138 2022/09/08 19:09:54 - mmengine - INFO - Epoch(train) [41][800/1253] lr: 4.0000e-04 eta: 1:55:18 time: 0.6099 data_time: 0.0482 memory: 23504 grad_norm: 3.3564 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.7679 loss: 0.7679 2022/09/08 19:10:05 - mmengine - INFO - Epoch(train) [41][820/1253] lr: 4.0000e-04 eta: 1:55:06 time: 0.5681 data_time: 0.0478 memory: 23504 grad_norm: 3.4781 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.8678 loss: 0.8678 2022/09/08 19:10:17 - mmengine - INFO - Epoch(train) [41][840/1253] lr: 4.0000e-04 eta: 1:54:54 time: 0.5797 data_time: 0.0383 memory: 23504 grad_norm: 3.3612 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.9164 loss: 0.9164 2022/09/08 19:10:29 - mmengine - INFO - Epoch(train) [41][860/1253] lr: 4.0000e-04 eta: 1:54:43 time: 0.6180 data_time: 0.0407 memory: 23504 grad_norm: 3.3449 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8629 loss: 0.8629 2022/09/08 19:10:41 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 19:10:41 - mmengine - INFO - Epoch(train) [41][880/1253] lr: 4.0000e-04 eta: 1:54:31 time: 0.5841 data_time: 0.0536 memory: 23504 grad_norm: 3.3692 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.7553 loss: 0.7553 2022/09/08 19:10:52 - mmengine - INFO - Epoch(train) [41][900/1253] lr: 4.0000e-04 eta: 1:54:19 time: 0.5636 data_time: 0.0344 memory: 23504 grad_norm: 3.3856 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.8968 loss: 0.8968 2022/09/08 19:11:04 - mmengine - INFO - Epoch(train) [41][920/1253] lr: 4.0000e-04 eta: 1:54:07 time: 0.5942 data_time: 0.0677 memory: 23504 grad_norm: 3.3205 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.6832 loss: 0.6832 2022/09/08 19:11:16 - mmengine - INFO - Epoch(train) [41][940/1253] lr: 4.0000e-04 eta: 1:53:55 time: 0.5689 data_time: 0.0486 memory: 23504 grad_norm: 3.4269 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.7856 loss: 0.7856 2022/09/08 19:11:27 - mmengine - INFO - Epoch(train) [41][960/1253] lr: 4.0000e-04 eta: 1:53:43 time: 0.5513 data_time: 0.0368 memory: 23504 grad_norm: 3.4548 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.8099 loss: 0.8099 2022/09/08 19:11:38 - mmengine - INFO - Epoch(train) [41][980/1253] lr: 4.0000e-04 eta: 1:53:31 time: 0.5616 data_time: 0.0413 memory: 23504 grad_norm: 3.4358 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.7983 loss: 0.7983 2022/09/08 19:11:50 - mmengine - INFO - Epoch(train) [41][1000/1253] lr: 4.0000e-04 eta: 1:53:20 time: 0.5991 data_time: 0.0699 memory: 23504 grad_norm: 3.3484 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8382 loss: 0.8382 2022/09/08 19:12:04 - mmengine - INFO - Epoch(train) [41][1020/1253] lr: 4.0000e-04 eta: 1:53:08 time: 0.7128 data_time: 0.0467 memory: 23504 grad_norm: 3.4565 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8875 loss: 0.8875 2022/09/08 19:12:15 - mmengine - INFO - Epoch(train) [41][1040/1253] lr: 4.0000e-04 eta: 1:52:56 time: 0.5532 data_time: 0.0283 memory: 23504 grad_norm: 3.3753 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.8361 loss: 0.8361 2022/09/08 19:12:26 - mmengine - INFO - Epoch(train) [41][1060/1253] lr: 4.0000e-04 eta: 1:52:44 time: 0.5541 data_time: 0.0395 memory: 23504 grad_norm: 3.3713 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.9101 loss: 0.9101 2022/09/08 19:12:39 - mmengine - INFO - Epoch(train) [41][1080/1253] lr: 4.0000e-04 eta: 1:52:33 time: 0.6232 data_time: 0.0399 memory: 23504 grad_norm: 3.3542 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8445 loss: 0.8445 2022/09/08 19:12:50 - mmengine - INFO - Epoch(train) [41][1100/1253] lr: 4.0000e-04 eta: 1:52:21 time: 0.5719 data_time: 0.0388 memory: 23504 grad_norm: 3.3706 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 0.8665 loss: 0.8665 2022/09/08 19:13:02 - mmengine - INFO - Epoch(train) [41][1120/1253] lr: 4.0000e-04 eta: 1:52:09 time: 0.5742 data_time: 0.0351 memory: 23504 grad_norm: 3.3875 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8737 loss: 0.8737 2022/09/08 19:13:15 - mmengine - INFO - Epoch(train) [41][1140/1253] lr: 4.0000e-04 eta: 1:51:58 time: 0.6574 data_time: 0.0511 memory: 23504 grad_norm: 3.3492 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.9783 loss: 0.9783 2022/09/08 19:13:27 - mmengine - INFO - Epoch(train) [41][1160/1253] lr: 4.0000e-04 eta: 1:51:46 time: 0.6134 data_time: 0.0402 memory: 23504 grad_norm: 3.4029 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.8463 loss: 0.8463 2022/09/08 19:13:38 - mmengine - INFO - Epoch(train) [41][1180/1253] lr: 4.0000e-04 eta: 1:51:34 time: 0.5614 data_time: 0.0436 memory: 23504 grad_norm: 3.4712 top1_acc: 0.7083 top5_acc: 1.0000 loss_cls: 0.8030 loss: 0.8030 2022/09/08 19:13:50 - mmengine - INFO - Epoch(train) [41][1200/1253] lr: 4.0000e-04 eta: 1:51:22 time: 0.5887 data_time: 0.0637 memory: 23504 grad_norm: 3.3890 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.8172 loss: 0.8172 2022/09/08 19:14:02 - mmengine - INFO - Epoch(train) [41][1220/1253] lr: 4.0000e-04 eta: 1:51:10 time: 0.5773 data_time: 0.0423 memory: 23504 grad_norm: 3.3519 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.8056 loss: 0.8056 2022/09/08 19:14:12 - mmengine - INFO - Epoch(train) [41][1240/1253] lr: 4.0000e-04 eta: 1:50:58 time: 0.5220 data_time: 0.0331 memory: 23504 grad_norm: 3.3799 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.7803 loss: 0.7803 2022/09/08 19:14:18 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 19:14:18 - mmengine - INFO - Epoch(train) [41][1253/1253] lr: 4.0000e-04 eta: 1:50:58 time: 0.4398 data_time: 0.0192 memory: 23504 grad_norm: 3.5777 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 0.8243 loss: 0.8243 2022/09/08 19:14:42 - mmengine - INFO - Epoch(train) [42][20/1253] lr: 4.0000e-04 eta: 1:50:40 time: 1.2001 data_time: 0.6019 memory: 23504 grad_norm: 3.3491 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8685 loss: 0.8685 2022/09/08 19:14:53 - mmengine - INFO - Epoch(train) [42][40/1253] lr: 4.0000e-04 eta: 1:50:28 time: 0.5716 data_time: 0.0661 memory: 23504 grad_norm: 3.3403 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7335 loss: 0.7335 2022/09/08 19:15:06 - mmengine - INFO - Epoch(train) [42][60/1253] lr: 4.0000e-04 eta: 1:50:16 time: 0.6402 data_time: 0.0385 memory: 23504 grad_norm: 3.3389 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8717 loss: 0.8717 2022/09/08 19:15:17 - mmengine - INFO - Epoch(train) [42][80/1253] lr: 4.0000e-04 eta: 1:50:04 time: 0.5687 data_time: 0.0367 memory: 23504 grad_norm: 3.3921 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8818 loss: 0.8818 2022/09/08 19:15:30 - mmengine - INFO - Epoch(train) [42][100/1253] lr: 4.0000e-04 eta: 1:49:53 time: 0.6087 data_time: 0.0570 memory: 23504 grad_norm: 3.3683 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8037 loss: 0.8037 2022/09/08 19:15:43 - mmengine - INFO - Epoch(train) [42][120/1253] lr: 4.0000e-04 eta: 1:49:41 time: 0.6804 data_time: 0.0392 memory: 23504 grad_norm: 3.3858 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7261 loss: 0.7261 2022/09/08 19:15:54 - mmengine - INFO - Epoch(train) [42][140/1253] lr: 4.0000e-04 eta: 1:49:29 time: 0.5447 data_time: 0.0368 memory: 23504 grad_norm: 3.3047 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7809 loss: 0.7809 2022/09/08 19:16:05 - mmengine - INFO - Epoch(train) [42][160/1253] lr: 4.0000e-04 eta: 1:49:17 time: 0.5689 data_time: 0.0456 memory: 23504 grad_norm: 3.3093 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8078 loss: 0.8078 2022/09/08 19:16:18 - mmengine - INFO - Epoch(train) [42][180/1253] lr: 4.0000e-04 eta: 1:49:06 time: 0.6462 data_time: 0.0384 memory: 23504 grad_norm: 3.3994 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.8325 loss: 0.8325 2022/09/08 19:16:30 - mmengine - INFO - Epoch(train) [42][200/1253] lr: 4.0000e-04 eta: 1:48:54 time: 0.5862 data_time: 0.0460 memory: 23504 grad_norm: 3.3194 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8096 loss: 0.8096 2022/09/08 19:16:41 - mmengine - INFO - Epoch(train) [42][220/1253] lr: 4.0000e-04 eta: 1:48:42 time: 0.5478 data_time: 0.0368 memory: 23504 grad_norm: 3.2986 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.6995 loss: 0.6995 2022/09/08 19:16:52 - mmengine - INFO - Epoch(train) [42][240/1253] lr: 4.0000e-04 eta: 1:48:30 time: 0.5494 data_time: 0.0418 memory: 23504 grad_norm: 3.4162 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8207 loss: 0.8207 2022/09/08 19:17:03 - mmengine - INFO - Epoch(train) [42][260/1253] lr: 4.0000e-04 eta: 1:48:18 time: 0.5690 data_time: 0.0491 memory: 23504 grad_norm: 3.3925 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.8228 loss: 0.8228 2022/09/08 19:17:16 - mmengine - INFO - Epoch(train) [42][280/1253] lr: 4.0000e-04 eta: 1:48:06 time: 0.6037 data_time: 0.0360 memory: 23504 grad_norm: 3.3571 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.7982 loss: 0.7982 2022/09/08 19:17:28 - mmengine - INFO - Epoch(train) [42][300/1253] lr: 4.0000e-04 eta: 1:47:55 time: 0.6385 data_time: 0.0345 memory: 23504 grad_norm: 3.4224 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8757 loss: 0.8757 2022/09/08 19:17:41 - mmengine - INFO - Epoch(train) [42][320/1253] lr: 4.0000e-04 eta: 1:47:43 time: 0.6085 data_time: 0.0336 memory: 23504 grad_norm: 3.3139 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.9024 loss: 0.9024 2022/09/08 19:17:52 - mmengine - INFO - Epoch(train) [42][340/1253] lr: 4.0000e-04 eta: 1:47:31 time: 0.5575 data_time: 0.0469 memory: 23504 grad_norm: 3.3978 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8465 loss: 0.8465 2022/09/08 19:18:03 - mmengine - INFO - Epoch(train) [42][360/1253] lr: 4.0000e-04 eta: 1:47:19 time: 0.5762 data_time: 0.0394 memory: 23504 grad_norm: 3.3830 top1_acc: 0.9167 top5_acc: 0.9167 loss_cls: 0.8207 loss: 0.8207 2022/09/08 19:18:15 - mmengine - INFO - Epoch(train) [42][380/1253] lr: 4.0000e-04 eta: 1:47:08 time: 0.5958 data_time: 0.0386 memory: 23504 grad_norm: 3.3825 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.7716 loss: 0.7716 2022/09/08 19:18:27 - mmengine - INFO - Epoch(train) [42][400/1253] lr: 4.0000e-04 eta: 1:46:56 time: 0.6117 data_time: 0.0437 memory: 23504 grad_norm: 3.4793 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.9027 loss: 0.9027 2022/09/08 19:18:40 - mmengine - INFO - Epoch(train) [42][420/1253] lr: 4.0000e-04 eta: 1:46:44 time: 0.6249 data_time: 0.0462 memory: 23504 grad_norm: 3.4585 top1_acc: 0.7083 top5_acc: 1.0000 loss_cls: 0.9197 loss: 0.9197 2022/09/08 19:18:53 - mmengine - INFO - Epoch(train) [42][440/1253] lr: 4.0000e-04 eta: 1:46:33 time: 0.6637 data_time: 0.0314 memory: 23504 grad_norm: 3.3801 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 0.8732 loss: 0.8732 2022/09/08 19:19:04 - mmengine - INFO - Epoch(train) [42][460/1253] lr: 4.0000e-04 eta: 1:46:21 time: 0.5618 data_time: 0.0370 memory: 23504 grad_norm: 3.2966 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8044 loss: 0.8044 2022/09/08 19:19:16 - mmengine - INFO - Epoch(train) [42][480/1253] lr: 4.0000e-04 eta: 1:46:09 time: 0.5672 data_time: 0.0384 memory: 23504 grad_norm: 3.4156 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8686 loss: 0.8686 2022/09/08 19:19:28 - mmengine - INFO - Epoch(train) [42][500/1253] lr: 4.0000e-04 eta: 1:45:57 time: 0.5945 data_time: 0.0461 memory: 23504 grad_norm: 3.3893 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8467 loss: 0.8467 2022/09/08 19:19:39 - mmengine - INFO - Epoch(train) [42][520/1253] lr: 4.0000e-04 eta: 1:45:45 time: 0.5578 data_time: 0.0358 memory: 23504 grad_norm: 3.2741 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.7444 loss: 0.7444 2022/09/08 19:19:50 - mmengine - INFO - Epoch(train) [42][540/1253] lr: 4.0000e-04 eta: 1:45:33 time: 0.5747 data_time: 0.0436 memory: 23504 grad_norm: 3.3757 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8724 loss: 0.8724 2022/09/08 19:20:01 - mmengine - INFO - Epoch(train) [42][560/1253] lr: 4.0000e-04 eta: 1:45:21 time: 0.5562 data_time: 0.0411 memory: 23504 grad_norm: 3.3530 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.7594 loss: 0.7594 2022/09/08 19:20:13 - mmengine - INFO - Epoch(train) [42][580/1253] lr: 4.0000e-04 eta: 1:45:09 time: 0.5688 data_time: 0.0459 memory: 23504 grad_norm: 3.4479 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.8122 loss: 0.8122 2022/09/08 19:20:26 - mmengine - INFO - Epoch(train) [42][600/1253] lr: 4.0000e-04 eta: 1:44:58 time: 0.6672 data_time: 0.0491 memory: 23504 grad_norm: 3.3089 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8333 loss: 0.8333 2022/09/08 19:20:38 - mmengine - INFO - Epoch(train) [42][620/1253] lr: 4.0000e-04 eta: 1:44:46 time: 0.5679 data_time: 0.0340 memory: 23504 grad_norm: 3.3766 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.7861 loss: 0.7861 2022/09/08 19:20:42 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 19:20:49 - mmengine - INFO - Epoch(train) [42][640/1253] lr: 4.0000e-04 eta: 1:44:34 time: 0.5949 data_time: 0.0665 memory: 23504 grad_norm: 3.3471 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7950 loss: 0.7950 2022/09/08 19:21:03 - mmengine - INFO - Epoch(train) [42][660/1253] lr: 4.0000e-04 eta: 1:44:23 time: 0.6569 data_time: 0.0346 memory: 23504 grad_norm: 3.3570 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.7584 loss: 0.7584 2022/09/08 19:21:14 - mmengine - INFO - Epoch(train) [42][680/1253] lr: 4.0000e-04 eta: 1:44:11 time: 0.5798 data_time: 0.0365 memory: 23504 grad_norm: 3.3445 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.7915 loss: 0.7915 2022/09/08 19:21:25 - mmengine - INFO - Epoch(train) [42][700/1253] lr: 4.0000e-04 eta: 1:43:59 time: 0.5619 data_time: 0.0476 memory: 23504 grad_norm: 3.3571 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8386 loss: 0.8386 2022/09/08 19:21:37 - mmengine - INFO - Epoch(train) [42][720/1253] lr: 4.0000e-04 eta: 1:43:47 time: 0.5683 data_time: 0.0364 memory: 23504 grad_norm: 3.3575 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.9504 loss: 0.9504 2022/09/08 19:21:48 - mmengine - INFO - Epoch(train) [42][740/1253] lr: 4.0000e-04 eta: 1:43:35 time: 0.5634 data_time: 0.0333 memory: 23504 grad_norm: 3.3568 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8073 loss: 0.8073 2022/09/08 19:22:00 - mmengine - INFO - Epoch(train) [42][760/1253] lr: 4.0000e-04 eta: 1:43:24 time: 0.6063 data_time: 0.0399 memory: 23504 grad_norm: 3.3385 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.7577 loss: 0.7577 2022/09/08 19:22:12 - mmengine - INFO - Epoch(train) [42][780/1253] lr: 4.0000e-04 eta: 1:43:12 time: 0.6029 data_time: 0.0479 memory: 23504 grad_norm: 3.3941 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 0.8692 loss: 0.8692 2022/09/08 19:22:24 - mmengine - INFO - Epoch(train) [42][800/1253] lr: 4.0000e-04 eta: 1:43:00 time: 0.5691 data_time: 0.0289 memory: 23504 grad_norm: 3.4288 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.8154 loss: 0.8154 2022/09/08 19:22:35 - mmengine - INFO - Epoch(train) [42][820/1253] lr: 4.0000e-04 eta: 1:42:48 time: 0.5568 data_time: 0.0434 memory: 23504 grad_norm: 3.2748 top1_acc: 0.9583 top5_acc: 1.0000 loss_cls: 0.8289 loss: 0.8289 2022/09/08 19:22:47 - mmengine - INFO - Epoch(train) [42][840/1253] lr: 4.0000e-04 eta: 1:42:36 time: 0.5872 data_time: 0.0503 memory: 23504 grad_norm: 3.3082 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.7430 loss: 0.7430 2022/09/08 19:22:59 - mmengine - INFO - Epoch(train) [42][860/1253] lr: 4.0000e-04 eta: 1:42:24 time: 0.5987 data_time: 0.0466 memory: 23504 grad_norm: 3.4352 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8440 loss: 0.8440 2022/09/08 19:23:11 - mmengine - INFO - Epoch(train) [42][880/1253] lr: 4.0000e-04 eta: 1:42:13 time: 0.6110 data_time: 0.0450 memory: 23504 grad_norm: 3.4270 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.7271 loss: 0.7271 2022/09/08 19:23:22 - mmengine - INFO - Epoch(train) [42][900/1253] lr: 4.0000e-04 eta: 1:42:01 time: 0.5730 data_time: 0.0407 memory: 23504 grad_norm: 3.4550 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 0.9098 loss: 0.9098 2022/09/08 19:23:34 - mmengine - INFO - Epoch(train) [42][920/1253] lr: 4.0000e-04 eta: 1:41:49 time: 0.5815 data_time: 0.0360 memory: 23504 grad_norm: 3.3304 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8385 loss: 0.8385 2022/09/08 19:23:45 - mmengine - INFO - Epoch(train) [42][940/1253] lr: 4.0000e-04 eta: 1:41:37 time: 0.5811 data_time: 0.0512 memory: 23504 grad_norm: 3.3887 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.8593 loss: 0.8593 2022/09/08 19:23:57 - mmengine - INFO - Epoch(train) [42][960/1253] lr: 4.0000e-04 eta: 1:41:25 time: 0.5800 data_time: 0.0468 memory: 23504 grad_norm: 3.3770 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8610 loss: 0.8610 2022/09/08 19:24:10 - mmengine - INFO - Epoch(train) [42][980/1253] lr: 4.0000e-04 eta: 1:41:14 time: 0.6441 data_time: 0.1124 memory: 23504 grad_norm: 3.4424 top1_acc: 0.9167 top5_acc: 0.9167 loss_cls: 0.8258 loss: 0.8258 2022/09/08 19:24:22 - mmengine - INFO - Epoch(train) [42][1000/1253] lr: 4.0000e-04 eta: 1:41:02 time: 0.6180 data_time: 0.1180 memory: 23504 grad_norm: 3.3125 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.7683 loss: 0.7683 2022/09/08 19:24:33 - mmengine - INFO - Epoch(train) [42][1020/1253] lr: 4.0000e-04 eta: 1:40:50 time: 0.5370 data_time: 0.0323 memory: 23504 grad_norm: 3.3766 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.0038 loss: 1.0038 2022/09/08 19:24:44 - mmengine - INFO - Epoch(train) [42][1040/1253] lr: 4.0000e-04 eta: 1:40:38 time: 0.5675 data_time: 0.0484 memory: 23504 grad_norm: 3.3768 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8833 loss: 0.8833 2022/09/08 19:24:58 - mmengine - INFO - Epoch(train) [42][1060/1253] lr: 4.0000e-04 eta: 1:40:27 time: 0.6643 data_time: 0.0984 memory: 23504 grad_norm: 3.4219 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7996 loss: 0.7996 2022/09/08 19:25:09 - mmengine - INFO - Epoch(train) [42][1080/1253] lr: 4.0000e-04 eta: 1:40:15 time: 0.5495 data_time: 0.0281 memory: 23504 grad_norm: 3.3138 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.7873 loss: 0.7873 2022/09/08 19:25:21 - mmengine - INFO - Epoch(train) [42][1100/1253] lr: 4.0000e-04 eta: 1:40:03 time: 0.6082 data_time: 0.0874 memory: 23504 grad_norm: 3.3729 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9256 loss: 0.9256 2022/09/08 19:25:33 - mmengine - INFO - Epoch(train) [42][1120/1253] lr: 4.0000e-04 eta: 1:39:51 time: 0.6163 data_time: 0.1003 memory: 23504 grad_norm: 3.2821 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.0053 loss: 1.0053 2022/09/08 19:25:45 - mmengine - INFO - Epoch(train) [42][1140/1253] lr: 4.0000e-04 eta: 1:39:39 time: 0.5709 data_time: 0.0374 memory: 23504 grad_norm: 3.3774 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8465 loss: 0.8465 2022/09/08 19:25:56 - mmengine - INFO - Epoch(train) [42][1160/1253] lr: 4.0000e-04 eta: 1:39:28 time: 0.5683 data_time: 0.0352 memory: 23504 grad_norm: 3.3823 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.6893 loss: 0.6893 2022/09/08 19:26:07 - mmengine - INFO - Epoch(train) [42][1180/1253] lr: 4.0000e-04 eta: 1:39:16 time: 0.5680 data_time: 0.0391 memory: 23504 grad_norm: 3.3803 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9682 loss: 0.9682 2022/09/08 19:26:20 - mmengine - INFO - Epoch(train) [42][1200/1253] lr: 4.0000e-04 eta: 1:39:04 time: 0.6105 data_time: 0.0398 memory: 23504 grad_norm: 3.4756 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.8663 loss: 0.8663 2022/09/08 19:26:31 - mmengine - INFO - Epoch(train) [42][1220/1253] lr: 4.0000e-04 eta: 1:38:52 time: 0.5779 data_time: 0.0383 memory: 23504 grad_norm: 3.3849 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7851 loss: 0.7851 2022/09/08 19:26:45 - mmengine - INFO - Epoch(train) [42][1240/1253] lr: 4.0000e-04 eta: 1:38:41 time: 0.6851 data_time: 0.0262 memory: 23504 grad_norm: 3.3149 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7485 loss: 0.7485 2022/09/08 19:26:50 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 19:26:50 - mmengine - INFO - Epoch(train) [42][1253/1253] lr: 4.0000e-04 eta: 1:38:41 time: 0.4380 data_time: 0.0207 memory: 23504 grad_norm: 3.4739 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 0.8316 loss: 0.8316 2022/09/08 19:27:15 - mmengine - INFO - Epoch(train) [43][20/1253] lr: 4.0000e-04 eta: 1:38:22 time: 1.2326 data_time: 0.4456 memory: 23504 grad_norm: 3.3045 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.8197 loss: 0.8197 2022/09/08 19:27:27 - mmengine - INFO - Epoch(train) [43][40/1253] lr: 4.0000e-04 eta: 1:38:10 time: 0.5849 data_time: 0.0357 memory: 23504 grad_norm: 3.4142 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9734 loss: 0.9734 2022/09/08 19:27:38 - mmengine - INFO - Epoch(train) [43][60/1253] lr: 4.0000e-04 eta: 1:37:59 time: 0.5803 data_time: 0.0354 memory: 23504 grad_norm: 3.3965 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8356 loss: 0.8356 2022/09/08 19:27:50 - mmengine - INFO - Epoch(train) [43][80/1253] lr: 4.0000e-04 eta: 1:37:47 time: 0.5714 data_time: 0.0377 memory: 23504 grad_norm: 3.4046 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8627 loss: 0.8627 2022/09/08 19:28:03 - mmengine - INFO - Epoch(train) [43][100/1253] lr: 4.0000e-04 eta: 1:37:35 time: 0.6398 data_time: 0.0378 memory: 23504 grad_norm: 3.3346 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8197 loss: 0.8197 2022/09/08 19:28:15 - mmengine - INFO - Epoch(train) [43][120/1253] lr: 4.0000e-04 eta: 1:37:23 time: 0.6053 data_time: 0.0425 memory: 23504 grad_norm: 3.4593 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8787 loss: 0.8787 2022/09/08 19:28:26 - mmengine - INFO - Epoch(train) [43][140/1253] lr: 4.0000e-04 eta: 1:37:11 time: 0.5565 data_time: 0.0343 memory: 23504 grad_norm: 3.4125 top1_acc: 0.9583 top5_acc: 1.0000 loss_cls: 0.8512 loss: 0.8512 2022/09/08 19:28:37 - mmengine - INFO - Epoch(train) [43][160/1253] lr: 4.0000e-04 eta: 1:36:59 time: 0.5453 data_time: 0.0491 memory: 23504 grad_norm: 3.3657 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.7537 loss: 0.7537 2022/09/08 19:28:51 - mmengine - INFO - Epoch(train) [43][180/1253] lr: 4.0000e-04 eta: 1:36:48 time: 0.6977 data_time: 0.0474 memory: 23504 grad_norm: 3.3002 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8795 loss: 0.8795 2022/09/08 19:29:02 - mmengine - INFO - Epoch(train) [43][200/1253] lr: 4.0000e-04 eta: 1:36:36 time: 0.5410 data_time: 0.0373 memory: 23504 grad_norm: 3.3172 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.8368 loss: 0.8368 2022/09/08 19:29:13 - mmengine - INFO - Epoch(train) [43][220/1253] lr: 4.0000e-04 eta: 1:36:24 time: 0.5581 data_time: 0.0337 memory: 23504 grad_norm: 3.4042 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 0.8655 loss: 0.8655 2022/09/08 19:29:24 - mmengine - INFO - Epoch(train) [43][240/1253] lr: 4.0000e-04 eta: 1:36:12 time: 0.5797 data_time: 0.0391 memory: 23504 grad_norm: 3.4139 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9415 loss: 0.9415 2022/09/08 19:29:38 - mmengine - INFO - Epoch(train) [43][260/1253] lr: 4.0000e-04 eta: 1:36:01 time: 0.6744 data_time: 0.0436 memory: 23504 grad_norm: 3.2605 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8375 loss: 0.8375 2022/09/08 19:29:49 - mmengine - INFO - Epoch(train) [43][280/1253] lr: 4.0000e-04 eta: 1:35:49 time: 0.5467 data_time: 0.0385 memory: 23504 grad_norm: 3.3937 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7886 loss: 0.7886 2022/09/08 19:30:00 - mmengine - INFO - Epoch(train) [43][300/1253] lr: 4.0000e-04 eta: 1:35:37 time: 0.5607 data_time: 0.0424 memory: 23504 grad_norm: 3.4705 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8192 loss: 0.8192 2022/09/08 19:30:12 - mmengine - INFO - Epoch(train) [43][320/1253] lr: 4.0000e-04 eta: 1:35:25 time: 0.5773 data_time: 0.0422 memory: 23504 grad_norm: 3.4246 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8604 loss: 0.8604 2022/09/08 19:30:25 - mmengine - INFO - Epoch(train) [43][340/1253] lr: 4.0000e-04 eta: 1:35:14 time: 0.6822 data_time: 0.0398 memory: 23504 grad_norm: 3.3225 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.8188 loss: 0.8188 2022/09/08 19:30:36 - mmengine - INFO - Epoch(train) [43][360/1253] lr: 4.0000e-04 eta: 1:35:02 time: 0.5596 data_time: 0.0493 memory: 23504 grad_norm: 3.3554 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7549 loss: 0.7549 2022/09/08 19:30:45 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 19:30:48 - mmengine - INFO - Epoch(train) [43][380/1253] lr: 4.0000e-04 eta: 1:34:50 time: 0.5656 data_time: 0.0398 memory: 23504 grad_norm: 3.3216 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.7593 loss: 0.7593 2022/09/08 19:30:59 - mmengine - INFO - Epoch(train) [43][400/1253] lr: 4.0000e-04 eta: 1:34:38 time: 0.5439 data_time: 0.0412 memory: 23504 grad_norm: 3.3763 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.7897 loss: 0.7897 2022/09/08 19:31:10 - mmengine - INFO - Epoch(train) [43][420/1253] lr: 4.0000e-04 eta: 1:34:26 time: 0.5718 data_time: 0.0594 memory: 23504 grad_norm: 3.3424 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.7642 loss: 0.7642 2022/09/08 19:31:24 - mmengine - INFO - Epoch(train) [43][440/1253] lr: 4.0000e-04 eta: 1:34:14 time: 0.6701 data_time: 0.0479 memory: 23504 grad_norm: 3.3032 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.6917 loss: 0.6917 2022/09/08 19:31:35 - mmengine - INFO - Epoch(train) [43][460/1253] lr: 4.0000e-04 eta: 1:34:03 time: 0.5587 data_time: 0.0368 memory: 23504 grad_norm: 3.3244 top1_acc: 0.9583 top5_acc: 0.9583 loss_cls: 0.7452 loss: 0.7452 2022/09/08 19:31:46 - mmengine - INFO - Epoch(train) [43][480/1253] lr: 4.0000e-04 eta: 1:33:51 time: 0.5723 data_time: 0.0456 memory: 23504 grad_norm: 3.3968 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.8689 loss: 0.8689 2022/09/08 19:31:58 - mmengine - INFO - Epoch(train) [43][500/1253] lr: 4.0000e-04 eta: 1:33:39 time: 0.6117 data_time: 0.0506 memory: 23504 grad_norm: 3.3663 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 0.7778 loss: 0.7778 2022/09/08 19:32:10 - mmengine - INFO - Epoch(train) [43][520/1253] lr: 4.0000e-04 eta: 1:33:27 time: 0.5766 data_time: 0.0427 memory: 23504 grad_norm: 3.3088 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.7399 loss: 0.7399 2022/09/08 19:32:22 - mmengine - INFO - Epoch(train) [43][540/1253] lr: 4.0000e-04 eta: 1:33:15 time: 0.5843 data_time: 0.0505 memory: 23504 grad_norm: 3.4345 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 0.8988 loss: 0.8988 2022/09/08 19:32:33 - mmengine - INFO - Epoch(train) [43][560/1253] lr: 4.0000e-04 eta: 1:33:03 time: 0.5775 data_time: 0.0426 memory: 23504 grad_norm: 3.4039 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.7816 loss: 0.7816 2022/09/08 19:32:45 - mmengine - INFO - Epoch(train) [43][580/1253] lr: 4.0000e-04 eta: 1:32:52 time: 0.5946 data_time: 0.0440 memory: 23504 grad_norm: 3.4376 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8127 loss: 0.8127 2022/09/08 19:32:57 - mmengine - INFO - Epoch(train) [43][600/1253] lr: 4.0000e-04 eta: 1:32:40 time: 0.6176 data_time: 0.0439 memory: 23504 grad_norm: 3.3189 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7829 loss: 0.7829 2022/09/08 19:33:09 - mmengine - INFO - Epoch(train) [43][620/1253] lr: 4.0000e-04 eta: 1:32:28 time: 0.5622 data_time: 0.0485 memory: 23504 grad_norm: 3.3414 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7950 loss: 0.7950 2022/09/08 19:33:21 - mmengine - INFO - Epoch(train) [43][640/1253] lr: 4.0000e-04 eta: 1:32:16 time: 0.5976 data_time: 0.0435 memory: 23504 grad_norm: 3.4665 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.8384 loss: 0.8384 2022/09/08 19:33:32 - mmengine - INFO - Epoch(train) [43][660/1253] lr: 4.0000e-04 eta: 1:32:04 time: 0.5774 data_time: 0.0363 memory: 23504 grad_norm: 3.4567 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8518 loss: 0.8518 2022/09/08 19:33:46 - mmengine - INFO - Epoch(train) [43][680/1253] lr: 4.0000e-04 eta: 1:31:53 time: 0.6808 data_time: 0.0309 memory: 23504 grad_norm: 3.3383 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8669 loss: 0.8669 2022/09/08 19:33:57 - mmengine - INFO - Epoch(train) [43][700/1253] lr: 4.0000e-04 eta: 1:31:41 time: 0.5593 data_time: 0.0330 memory: 23504 grad_norm: 3.3738 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.6774 loss: 0.6774 2022/09/08 19:34:09 - mmengine - INFO - Epoch(train) [43][720/1253] lr: 4.0000e-04 eta: 1:31:29 time: 0.5788 data_time: 0.0526 memory: 23504 grad_norm: 3.4195 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.8476 loss: 0.8476 2022/09/08 19:34:20 - mmengine - INFO - Epoch(train) [43][740/1253] lr: 4.0000e-04 eta: 1:31:17 time: 0.5754 data_time: 0.0379 memory: 23504 grad_norm: 3.3483 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8724 loss: 0.8724 2022/09/08 19:34:32 - mmengine - INFO - Epoch(train) [43][760/1253] lr: 4.0000e-04 eta: 1:31:05 time: 0.5731 data_time: 0.0324 memory: 23504 grad_norm: 3.3811 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8310 loss: 0.8310 2022/09/08 19:34:45 - mmengine - INFO - Epoch(train) [43][780/1253] lr: 4.0000e-04 eta: 1:30:54 time: 0.6616 data_time: 0.0323 memory: 23504 grad_norm: 3.4268 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.7927 loss: 0.7927 2022/09/08 19:34:56 - mmengine - INFO - Epoch(train) [43][800/1253] lr: 4.0000e-04 eta: 1:30:42 time: 0.5664 data_time: 0.0444 memory: 23504 grad_norm: 3.4330 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.0154 loss: 1.0154 2022/09/08 19:35:08 - mmengine - INFO - Epoch(train) [43][820/1253] lr: 4.0000e-04 eta: 1:30:30 time: 0.5870 data_time: 0.0339 memory: 23504 grad_norm: 3.4005 top1_acc: 0.5833 top5_acc: 0.9583 loss_cls: 0.8800 loss: 0.8800 2022/09/08 19:35:20 - mmengine - INFO - Epoch(train) [43][840/1253] lr: 4.0000e-04 eta: 1:30:18 time: 0.5943 data_time: 0.0428 memory: 23504 grad_norm: 3.4748 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.6660 loss: 0.6660 2022/09/08 19:35:32 - mmengine - INFO - Epoch(train) [43][860/1253] lr: 4.0000e-04 eta: 1:30:07 time: 0.6140 data_time: 0.0436 memory: 23504 grad_norm: 3.4101 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9801 loss: 0.9801 2022/09/08 19:35:43 - mmengine - INFO - Epoch(train) [43][880/1253] lr: 4.0000e-04 eta: 1:29:55 time: 0.5686 data_time: 0.0406 memory: 23504 grad_norm: 3.4278 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.7837 loss: 0.7837 2022/09/08 19:35:55 - mmengine - INFO - Epoch(train) [43][900/1253] lr: 4.0000e-04 eta: 1:29:43 time: 0.5974 data_time: 0.0436 memory: 23504 grad_norm: 3.2832 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.7912 loss: 0.7912 2022/09/08 19:36:07 - mmengine - INFO - Epoch(train) [43][920/1253] lr: 4.0000e-04 eta: 1:29:31 time: 0.5669 data_time: 0.0412 memory: 23504 grad_norm: 3.4130 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7685 loss: 0.7685 2022/09/08 19:36:19 - mmengine - INFO - Epoch(train) [43][940/1253] lr: 4.0000e-04 eta: 1:29:20 time: 0.6291 data_time: 0.0382 memory: 23504 grad_norm: 3.3651 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.8572 loss: 0.8572 2022/09/08 19:36:31 - mmengine - INFO - Epoch(train) [43][960/1253] lr: 4.0000e-04 eta: 1:29:08 time: 0.5839 data_time: 0.0708 memory: 23504 grad_norm: 3.4735 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.8743 loss: 0.8743 2022/09/08 19:36:42 - mmengine - INFO - Epoch(train) [43][980/1253] lr: 4.0000e-04 eta: 1:28:56 time: 0.5707 data_time: 0.0474 memory: 23504 grad_norm: 3.4952 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7615 loss: 0.7615 2022/09/08 19:36:54 - mmengine - INFO - Epoch(train) [43][1000/1253] lr: 4.0000e-04 eta: 1:28:44 time: 0.5945 data_time: 0.0391 memory: 23504 grad_norm: 3.4264 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.8337 loss: 0.8337 2022/09/08 19:37:06 - mmengine - INFO - Epoch(train) [43][1020/1253] lr: 4.0000e-04 eta: 1:28:32 time: 0.5877 data_time: 0.0490 memory: 23504 grad_norm: 3.4193 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.8331 loss: 0.8331 2022/09/08 19:37:18 - mmengine - INFO - Epoch(train) [43][1040/1253] lr: 4.0000e-04 eta: 1:28:20 time: 0.5731 data_time: 0.0378 memory: 23504 grad_norm: 3.3911 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.7957 loss: 0.7957 2022/09/08 19:37:29 - mmengine - INFO - Epoch(train) [43][1060/1253] lr: 4.0000e-04 eta: 1:28:09 time: 0.5697 data_time: 0.0466 memory: 23504 grad_norm: 3.3769 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.8527 loss: 0.8527 2022/09/08 19:37:41 - mmengine - INFO - Epoch(train) [43][1080/1253] lr: 4.0000e-04 eta: 1:27:57 time: 0.6223 data_time: 0.0450 memory: 23504 grad_norm: 3.3752 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.8276 loss: 0.8276 2022/09/08 19:37:53 - mmengine - INFO - Epoch(train) [43][1100/1253] lr: 4.0000e-04 eta: 1:27:45 time: 0.5673 data_time: 0.0545 memory: 23504 grad_norm: 3.4106 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.8115 loss: 0.8115 2022/09/08 19:38:04 - mmengine - INFO - Epoch(train) [43][1120/1253] lr: 4.0000e-04 eta: 1:27:33 time: 0.5756 data_time: 0.0711 memory: 23504 grad_norm: 3.4013 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.7884 loss: 0.7884 2022/09/08 19:38:19 - mmengine - INFO - Epoch(train) [43][1140/1253] lr: 4.0000e-04 eta: 1:27:22 time: 0.7447 data_time: 0.0355 memory: 23504 grad_norm: 3.4546 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.7883 loss: 0.7883 2022/09/08 19:38:30 - mmengine - INFO - Epoch(train) [43][1160/1253] lr: 4.0000e-04 eta: 1:27:10 time: 0.5580 data_time: 0.0316 memory: 23504 grad_norm: 3.4822 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.7502 loss: 0.7502 2022/09/08 19:38:43 - mmengine - INFO - Epoch(train) [43][1180/1253] lr: 4.0000e-04 eta: 1:26:58 time: 0.6090 data_time: 0.0441 memory: 23504 grad_norm: 3.4307 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8389 loss: 0.8389 2022/09/08 19:38:54 - mmengine - INFO - Epoch(train) [43][1200/1253] lr: 4.0000e-04 eta: 1:26:46 time: 0.5573 data_time: 0.0508 memory: 23504 grad_norm: 3.4368 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.7842 loss: 0.7842 2022/09/08 19:39:05 - mmengine - INFO - Epoch(train) [43][1220/1253] lr: 4.0000e-04 eta: 1:26:34 time: 0.5592 data_time: 0.0412 memory: 23504 grad_norm: 3.3627 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 0.8501 loss: 0.8501 2022/09/08 19:39:15 - mmengine - INFO - Epoch(train) [43][1240/1253] lr: 4.0000e-04 eta: 1:26:22 time: 0.5088 data_time: 0.0264 memory: 23504 grad_norm: 3.4060 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.7150 loss: 0.7150 2022/09/08 19:39:21 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 19:39:21 - mmengine - INFO - Epoch(train) [43][1253/1253] lr: 4.0000e-04 eta: 1:26:22 time: 0.4456 data_time: 0.0266 memory: 23504 grad_norm: 3.6160 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 0.8009 loss: 0.8009 2022/09/08 19:39:47 - mmengine - INFO - Epoch(train) [44][20/1253] lr: 4.0000e-04 eta: 1:26:04 time: 1.2837 data_time: 0.5147 memory: 23504 grad_norm: 3.3320 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.8718 loss: 0.8718 2022/09/08 19:40:00 - mmengine - INFO - Epoch(train) [44][40/1253] lr: 4.0000e-04 eta: 1:25:52 time: 0.6856 data_time: 0.0384 memory: 23504 grad_norm: 3.3994 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.7725 loss: 0.7725 2022/09/08 19:40:11 - mmengine - INFO - Epoch(train) [44][60/1253] lr: 4.0000e-04 eta: 1:25:40 time: 0.5359 data_time: 0.0356 memory: 23504 grad_norm: 3.3756 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.7015 loss: 0.7015 2022/09/08 19:40:22 - mmengine - INFO - Epoch(train) [44][80/1253] lr: 4.0000e-04 eta: 1:25:28 time: 0.5381 data_time: 0.0432 memory: 23504 grad_norm: 3.4410 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8397 loss: 0.8397 2022/09/08 19:40:35 - mmengine - INFO - Epoch(train) [44][100/1253] lr: 4.0000e-04 eta: 1:25:17 time: 0.6495 data_time: 0.0498 memory: 23504 grad_norm: 3.3421 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.7710 loss: 0.7710 2022/09/08 19:40:49 - mmengine - INFO - Epoch(train) [44][120/1253] lr: 4.0000e-04 eta: 1:25:05 time: 0.7089 data_time: 0.0326 memory: 23504 grad_norm: 3.3879 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.9772 loss: 0.9772 2022/09/08 19:40:50 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 19:40:59 - mmengine - INFO - Epoch(train) [44][140/1253] lr: 4.0000e-04 eta: 1:24:53 time: 0.5229 data_time: 0.0305 memory: 23504 grad_norm: 3.3554 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7110 loss: 0.7110 2022/09/08 19:41:11 - mmengine - INFO - Epoch(train) [44][160/1253] lr: 4.0000e-04 eta: 1:24:41 time: 0.5673 data_time: 0.0367 memory: 23504 grad_norm: 3.3778 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8181 loss: 0.8181 2022/09/08 19:41:25 - mmengine - INFO - Epoch(train) [44][180/1253] lr: 4.0000e-04 eta: 1:24:30 time: 0.7127 data_time: 0.1470 memory: 23504 grad_norm: 3.4482 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7945 loss: 0.7945 2022/09/08 19:41:36 - mmengine - INFO - Epoch(train) [44][200/1253] lr: 4.0000e-04 eta: 1:24:18 time: 0.5417 data_time: 0.0289 memory: 23504 grad_norm: 3.4901 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.9312 loss: 0.9312 2022/09/08 19:41:47 - mmengine - INFO - Epoch(train) [44][220/1253] lr: 4.0000e-04 eta: 1:24:06 time: 0.5731 data_time: 0.0272 memory: 23504 grad_norm: 3.4488 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8799 loss: 0.8799 2022/09/08 19:41:58 - mmengine - INFO - Epoch(train) [44][240/1253] lr: 4.0000e-04 eta: 1:23:54 time: 0.5555 data_time: 0.0340 memory: 23504 grad_norm: 3.3758 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.6882 loss: 0.6882 2022/09/08 19:42:11 - mmengine - INFO - Epoch(train) [44][260/1253] lr: 4.0000e-04 eta: 1:23:43 time: 0.6060 data_time: 0.0902 memory: 23504 grad_norm: 3.4202 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.7835 loss: 0.7835 2022/09/08 19:42:22 - mmengine - INFO - Epoch(train) [44][280/1253] lr: 4.0000e-04 eta: 1:23:31 time: 0.5773 data_time: 0.0371 memory: 23504 grad_norm: 3.3685 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8147 loss: 0.8147 2022/09/08 19:42:33 - mmengine - INFO - Epoch(train) [44][300/1253] lr: 4.0000e-04 eta: 1:23:19 time: 0.5563 data_time: 0.0380 memory: 23504 grad_norm: 3.3856 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.8167 loss: 0.8167 2022/09/08 19:42:45 - mmengine - INFO - Epoch(train) [44][320/1253] lr: 4.0000e-04 eta: 1:23:07 time: 0.5828 data_time: 0.0428 memory: 23504 grad_norm: 3.4896 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8254 loss: 0.8254 2022/09/08 19:42:58 - mmengine - INFO - Epoch(train) [44][340/1253] lr: 4.0000e-04 eta: 1:22:55 time: 0.6525 data_time: 0.0477 memory: 23504 grad_norm: 3.3956 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8618 loss: 0.8618 2022/09/08 19:43:12 - mmengine - INFO - Epoch(train) [44][360/1253] lr: 4.0000e-04 eta: 1:22:44 time: 0.6909 data_time: 0.0251 memory: 23504 grad_norm: 3.4042 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8651 loss: 0.8651 2022/09/08 19:43:23 - mmengine - INFO - Epoch(train) [44][380/1253] lr: 4.0000e-04 eta: 1:22:32 time: 0.5538 data_time: 0.0493 memory: 23504 grad_norm: 3.3680 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.8651 loss: 0.8651 2022/09/08 19:43:34 - mmengine - INFO - Epoch(train) [44][400/1253] lr: 4.0000e-04 eta: 1:22:20 time: 0.5559 data_time: 0.0451 memory: 23504 grad_norm: 3.4397 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9071 loss: 0.9071 2022/09/08 19:43:48 - mmengine - INFO - Epoch(train) [44][420/1253] lr: 4.0000e-04 eta: 1:22:09 time: 0.6814 data_time: 0.0426 memory: 23504 grad_norm: 3.3958 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.7573 loss: 0.7573 2022/09/08 19:44:00 - mmengine - INFO - Epoch(train) [44][440/1253] lr: 4.0000e-04 eta: 1:21:57 time: 0.6165 data_time: 0.0473 memory: 23504 grad_norm: 3.3916 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.7930 loss: 0.7930 2022/09/08 19:44:12 - mmengine - INFO - Epoch(train) [44][460/1253] lr: 4.0000e-04 eta: 1:21:45 time: 0.6035 data_time: 0.0379 memory: 23504 grad_norm: 3.3918 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8204 loss: 0.8204 2022/09/08 19:44:23 - mmengine - INFO - Epoch(train) [44][480/1253] lr: 4.0000e-04 eta: 1:21:33 time: 0.5551 data_time: 0.0395 memory: 23504 grad_norm: 3.5071 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 0.9307 loss: 0.9307 2022/09/08 19:44:35 - mmengine - INFO - Epoch(train) [44][500/1253] lr: 4.0000e-04 eta: 1:21:21 time: 0.5876 data_time: 0.0410 memory: 23504 grad_norm: 3.2844 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8688 loss: 0.8688 2022/09/08 19:44:47 - mmengine - INFO - Epoch(train) [44][520/1253] lr: 4.0000e-04 eta: 1:21:09 time: 0.5801 data_time: 0.0500 memory: 23504 grad_norm: 3.4456 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.6532 loss: 0.6532 2022/09/08 19:44:58 - mmengine - INFO - Epoch(train) [44][540/1253] lr: 4.0000e-04 eta: 1:20:58 time: 0.5466 data_time: 0.0278 memory: 23504 grad_norm: 3.4306 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.8296 loss: 0.8296 2022/09/08 19:45:09 - mmengine - INFO - Epoch(train) [44][560/1253] lr: 4.0000e-04 eta: 1:20:46 time: 0.5854 data_time: 0.0630 memory: 23504 grad_norm: 3.3899 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7931 loss: 0.7931 2022/09/08 19:45:22 - mmengine - INFO - Epoch(train) [44][580/1253] lr: 4.0000e-04 eta: 1:20:34 time: 0.6245 data_time: 0.0421 memory: 23504 grad_norm: 3.3915 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8033 loss: 0.8033 2022/09/08 19:45:35 - mmengine - INFO - Epoch(train) [44][600/1253] lr: 4.0000e-04 eta: 1:20:22 time: 0.6690 data_time: 0.1307 memory: 23504 grad_norm: 3.3109 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.7294 loss: 0.7294 2022/09/08 19:45:46 - mmengine - INFO - Epoch(train) [44][620/1253] lr: 4.0000e-04 eta: 1:20:11 time: 0.5487 data_time: 0.0373 memory: 23504 grad_norm: 3.3905 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.8509 loss: 0.8509 2022/09/08 19:45:57 - mmengine - INFO - Epoch(train) [44][640/1253] lr: 4.0000e-04 eta: 1:19:59 time: 0.5600 data_time: 0.0364 memory: 23504 grad_norm: 3.3675 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.8619 loss: 0.8619 2022/09/08 19:46:09 - mmengine - INFO - Epoch(train) [44][660/1253] lr: 4.0000e-04 eta: 1:19:47 time: 0.5692 data_time: 0.0335 memory: 23504 grad_norm: 3.4654 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.8075 loss: 0.8075 2022/09/08 19:46:21 - mmengine - INFO - Epoch(train) [44][680/1253] lr: 4.0000e-04 eta: 1:19:35 time: 0.6014 data_time: 0.0505 memory: 23504 grad_norm: 3.4141 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8631 loss: 0.8631 2022/09/08 19:46:33 - mmengine - INFO - Epoch(train) [44][700/1253] lr: 4.0000e-04 eta: 1:19:23 time: 0.5901 data_time: 0.0773 memory: 23504 grad_norm: 3.4962 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.8658 loss: 0.8658 2022/09/08 19:46:44 - mmengine - INFO - Epoch(train) [44][720/1253] lr: 4.0000e-04 eta: 1:19:11 time: 0.5496 data_time: 0.0325 memory: 23504 grad_norm: 3.3733 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8162 loss: 0.8162 2022/09/08 19:46:55 - mmengine - INFO - Epoch(train) [44][740/1253] lr: 4.0000e-04 eta: 1:18:59 time: 0.5480 data_time: 0.0391 memory: 23504 grad_norm: 3.4161 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.8596 loss: 0.8596 2022/09/08 19:47:07 - mmengine - INFO - Epoch(train) [44][760/1253] lr: 4.0000e-04 eta: 1:18:48 time: 0.6365 data_time: 0.0597 memory: 23504 grad_norm: 3.3002 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7526 loss: 0.7526 2022/09/08 19:47:20 - mmengine - INFO - Epoch(train) [44][780/1253] lr: 4.0000e-04 eta: 1:18:36 time: 0.6425 data_time: 0.0325 memory: 23504 grad_norm: 3.3978 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.9066 loss: 0.9066 2022/09/08 19:47:34 - mmengine - INFO - Epoch(train) [44][800/1253] lr: 4.0000e-04 eta: 1:18:25 time: 0.7082 data_time: 0.0369 memory: 23504 grad_norm: 3.3680 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.7332 loss: 0.7332 2022/09/08 19:47:45 - mmengine - INFO - Epoch(train) [44][820/1253] lr: 4.0000e-04 eta: 1:18:13 time: 0.5436 data_time: 0.0441 memory: 23504 grad_norm: 3.3513 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7562 loss: 0.7562 2022/09/08 19:47:56 - mmengine - INFO - Epoch(train) [44][840/1253] lr: 4.0000e-04 eta: 1:18:01 time: 0.5576 data_time: 0.0517 memory: 23504 grad_norm: 3.3468 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.7920 loss: 0.7920 2022/09/08 19:48:07 - mmengine - INFO - Epoch(train) [44][860/1253] lr: 4.0000e-04 eta: 1:17:49 time: 0.5558 data_time: 0.0439 memory: 23504 grad_norm: 3.4784 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8500 loss: 0.8500 2022/09/08 19:48:19 - mmengine - INFO - Epoch(train) [44][880/1253] lr: 4.0000e-04 eta: 1:17:37 time: 0.5796 data_time: 0.0404 memory: 23504 grad_norm: 3.4213 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7917 loss: 0.7917 2022/09/08 19:48:31 - mmengine - INFO - Epoch(train) [44][900/1253] lr: 4.0000e-04 eta: 1:17:25 time: 0.5946 data_time: 0.0576 memory: 23504 grad_norm: 3.3884 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7214 loss: 0.7214 2022/09/08 19:48:44 - mmengine - INFO - Epoch(train) [44][920/1253] lr: 4.0000e-04 eta: 1:17:14 time: 0.6408 data_time: 0.0460 memory: 23504 grad_norm: 3.5558 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.7746 loss: 0.7746 2022/09/08 19:48:56 - mmengine - INFO - Epoch(train) [44][940/1253] lr: 4.0000e-04 eta: 1:17:02 time: 0.5992 data_time: 0.0365 memory: 23504 grad_norm: 3.4471 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.7232 loss: 0.7232 2022/09/08 19:49:07 - mmengine - INFO - Epoch(train) [44][960/1253] lr: 4.0000e-04 eta: 1:16:50 time: 0.5604 data_time: 0.0377 memory: 23504 grad_norm: 3.3367 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.9202 loss: 0.9202 2022/09/08 19:49:19 - mmengine - INFO - Epoch(train) [44][980/1253] lr: 4.0000e-04 eta: 1:16:38 time: 0.5919 data_time: 0.0310 memory: 23504 grad_norm: 3.4258 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.9064 loss: 0.9064 2022/09/08 19:49:31 - mmengine - INFO - Epoch(train) [44][1000/1253] lr: 4.0000e-04 eta: 1:16:26 time: 0.6219 data_time: 0.0435 memory: 23504 grad_norm: 3.4478 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8365 loss: 0.8365 2022/09/08 19:49:43 - mmengine - INFO - Epoch(train) [44][1020/1253] lr: 4.0000e-04 eta: 1:16:15 time: 0.5938 data_time: 0.0367 memory: 23504 grad_norm: 3.4343 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.7012 loss: 0.7012 2022/09/08 19:49:55 - mmengine - INFO - Epoch(train) [44][1040/1253] lr: 4.0000e-04 eta: 1:16:03 time: 0.5919 data_time: 0.0440 memory: 23504 grad_norm: 3.4496 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.8353 loss: 0.8353 2022/09/08 19:50:06 - mmengine - INFO - Epoch(train) [44][1060/1253] lr: 4.0000e-04 eta: 1:15:51 time: 0.5493 data_time: 0.0437 memory: 23504 grad_norm: 3.3624 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8475 loss: 0.8475 2022/09/08 19:50:18 - mmengine - INFO - Epoch(train) [44][1080/1253] lr: 4.0000e-04 eta: 1:15:39 time: 0.5829 data_time: 0.0452 memory: 23504 grad_norm: 3.3973 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8162 loss: 0.8162 2022/09/08 19:50:34 - mmengine - INFO - Epoch(train) [44][1100/1253] lr: 4.0000e-04 eta: 1:15:28 time: 0.8013 data_time: 0.0777 memory: 23504 grad_norm: 3.4745 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.8277 loss: 0.8277 2022/09/08 19:50:44 - mmengine - INFO - Epoch(train) [44][1120/1253] lr: 4.0000e-04 eta: 1:15:16 time: 0.5338 data_time: 0.0416 memory: 23504 grad_norm: 3.4461 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.7951 loss: 0.7951 2022/09/08 19:50:45 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 19:50:55 - mmengine - INFO - Epoch(train) [44][1140/1253] lr: 4.0000e-04 eta: 1:15:04 time: 0.5514 data_time: 0.0428 memory: 23504 grad_norm: 3.3897 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8576 loss: 0.8576 2022/09/08 19:51:07 - mmengine - INFO - Epoch(train) [44][1160/1253] lr: 4.0000e-04 eta: 1:14:52 time: 0.5744 data_time: 0.0775 memory: 23504 grad_norm: 3.3682 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.7898 loss: 0.7898 2022/09/08 19:51:18 - mmengine - INFO - Epoch(train) [44][1180/1253] lr: 4.0000e-04 eta: 1:14:40 time: 0.5435 data_time: 0.0438 memory: 23504 grad_norm: 3.4740 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8327 loss: 0.8327 2022/09/08 19:51:29 - mmengine - INFO - Epoch(train) [44][1200/1253] lr: 4.0000e-04 eta: 1:14:28 time: 0.5459 data_time: 0.0389 memory: 23504 grad_norm: 3.4636 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7985 loss: 0.7985 2022/09/08 19:51:40 - mmengine - INFO - Epoch(train) [44][1220/1253] lr: 4.0000e-04 eta: 1:14:16 time: 0.5806 data_time: 0.0453 memory: 23504 grad_norm: 3.3709 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8401 loss: 0.8401 2022/09/08 19:51:52 - mmengine - INFO - Epoch(train) [44][1240/1253] lr: 4.0000e-04 eta: 1:14:04 time: 0.5653 data_time: 0.0366 memory: 23504 grad_norm: 3.3988 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8108 loss: 0.8108 2022/09/08 19:51:57 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 19:51:57 - mmengine - INFO - Epoch(train) [44][1253/1253] lr: 4.0000e-04 eta: 1:14:04 time: 0.4378 data_time: 0.0208 memory: 23504 grad_norm: 3.6818 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 0.8863 loss: 0.8863 2022/09/08 19:52:21 - mmengine - INFO - Epoch(train) [45][20/1253] lr: 4.0000e-04 eta: 1:13:46 time: 1.1693 data_time: 0.3937 memory: 23504 grad_norm: 3.3253 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 0.8669 loss: 0.8669 2022/09/08 19:52:34 - mmengine - INFO - Epoch(train) [45][40/1253] lr: 4.0000e-04 eta: 1:13:34 time: 0.6905 data_time: 0.0430 memory: 23504 grad_norm: 3.3864 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8119 loss: 0.8119 2022/09/08 19:52:45 - mmengine - INFO - Epoch(train) [45][60/1253] lr: 4.0000e-04 eta: 1:13:22 time: 0.5303 data_time: 0.0399 memory: 23504 grad_norm: 3.5067 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8583 loss: 0.8583 2022/09/08 19:52:56 - mmengine - INFO - Epoch(train) [45][80/1253] lr: 4.0000e-04 eta: 1:13:10 time: 0.5520 data_time: 0.0488 memory: 23504 grad_norm: 3.4628 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.7864 loss: 0.7864 2022/09/08 19:53:09 - mmengine - INFO - Epoch(train) [45][100/1253] lr: 4.0000e-04 eta: 1:12:59 time: 0.6646 data_time: 0.0512 memory: 23504 grad_norm: 3.4151 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9204 loss: 0.9204 2022/09/08 19:53:22 - mmengine - INFO - Epoch(train) [45][120/1253] lr: 4.0000e-04 eta: 1:12:47 time: 0.6472 data_time: 0.0299 memory: 23504 grad_norm: 3.3081 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7896 loss: 0.7896 2022/09/08 19:53:33 - mmengine - INFO - Epoch(train) [45][140/1253] lr: 4.0000e-04 eta: 1:12:35 time: 0.5497 data_time: 0.0419 memory: 23504 grad_norm: 3.3980 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8324 loss: 0.8324 2022/09/08 19:53:45 - mmengine - INFO - Epoch(train) [45][160/1253] lr: 4.0000e-04 eta: 1:12:23 time: 0.5772 data_time: 0.0451 memory: 23504 grad_norm: 3.3528 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.6143 loss: 0.6143 2022/09/08 19:53:56 - mmengine - INFO - Epoch(train) [45][180/1253] lr: 4.0000e-04 eta: 1:12:11 time: 0.5770 data_time: 0.0411 memory: 23504 grad_norm: 3.4601 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8254 loss: 0.8254 2022/09/08 19:54:09 - mmengine - INFO - Epoch(train) [45][200/1253] lr: 4.0000e-04 eta: 1:12:00 time: 0.6230 data_time: 0.0381 memory: 23504 grad_norm: 3.3460 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.7645 loss: 0.7645 2022/09/08 19:54:20 - mmengine - INFO - Epoch(train) [45][220/1253] lr: 4.0000e-04 eta: 1:11:48 time: 0.5577 data_time: 0.0393 memory: 23504 grad_norm: 3.4723 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.7232 loss: 0.7232 2022/09/08 19:54:31 - mmengine - INFO - Epoch(train) [45][240/1253] lr: 4.0000e-04 eta: 1:11:36 time: 0.5587 data_time: 0.0337 memory: 23504 grad_norm: 3.4130 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7808 loss: 0.7808 2022/09/08 19:54:43 - mmengine - INFO - Epoch(train) [45][260/1253] lr: 4.0000e-04 eta: 1:11:24 time: 0.5948 data_time: 0.0521 memory: 23504 grad_norm: 3.3882 top1_acc: 0.9583 top5_acc: 1.0000 loss_cls: 0.7439 loss: 0.7439 2022/09/08 19:54:57 - mmengine - INFO - Epoch(train) [45][280/1253] lr: 4.0000e-04 eta: 1:11:12 time: 0.6796 data_time: 0.0408 memory: 23504 grad_norm: 3.4694 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.7403 loss: 0.7403 2022/09/08 19:55:08 - mmengine - INFO - Epoch(train) [45][300/1253] lr: 4.0000e-04 eta: 1:11:01 time: 0.5666 data_time: 0.0396 memory: 23504 grad_norm: 3.5291 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7954 loss: 0.7954 2022/09/08 19:55:20 - mmengine - INFO - Epoch(train) [45][320/1253] lr: 4.0000e-04 eta: 1:10:49 time: 0.5778 data_time: 0.0545 memory: 23504 grad_norm: 3.4116 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8195 loss: 0.8195 2022/09/08 19:55:31 - mmengine - INFO - Epoch(train) [45][340/1253] lr: 4.0000e-04 eta: 1:10:37 time: 0.5691 data_time: 0.0402 memory: 23504 grad_norm: 3.4322 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8124 loss: 0.8124 2022/09/08 19:55:43 - mmengine - INFO - Epoch(train) [45][360/1253] lr: 4.0000e-04 eta: 1:10:25 time: 0.5790 data_time: 0.0551 memory: 23504 grad_norm: 3.4420 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.8413 loss: 0.8413 2022/09/08 19:55:54 - mmengine - INFO - Epoch(train) [45][380/1253] lr: 4.0000e-04 eta: 1:10:13 time: 0.5635 data_time: 0.0344 memory: 23504 grad_norm: 3.3266 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.7976 loss: 0.7976 2022/09/08 19:56:06 - mmengine - INFO - Epoch(train) [45][400/1253] lr: 4.0000e-04 eta: 1:10:01 time: 0.5922 data_time: 0.0492 memory: 23504 grad_norm: 3.3926 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.8565 loss: 0.8565 2022/09/08 19:56:18 - mmengine - INFO - Epoch(train) [45][420/1253] lr: 4.0000e-04 eta: 1:09:50 time: 0.6289 data_time: 0.0360 memory: 23504 grad_norm: 3.4438 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.9181 loss: 0.9181 2022/09/08 19:56:30 - mmengine - INFO - Epoch(train) [45][440/1253] lr: 4.0000e-04 eta: 1:09:38 time: 0.6014 data_time: 0.0438 memory: 23504 grad_norm: 3.3852 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7974 loss: 0.7974 2022/09/08 19:56:42 - mmengine - INFO - Epoch(train) [45][460/1253] lr: 4.0000e-04 eta: 1:09:26 time: 0.5843 data_time: 0.0454 memory: 23504 grad_norm: 3.4861 top1_acc: 0.9167 top5_acc: 0.9167 loss_cls: 0.8399 loss: 0.8399 2022/09/08 19:56:57 - mmengine - INFO - Epoch(train) [45][480/1253] lr: 4.0000e-04 eta: 1:09:15 time: 0.7422 data_time: 0.2099 memory: 23504 grad_norm: 3.4114 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7640 loss: 0.7640 2022/09/08 19:57:08 - mmengine - INFO - Epoch(train) [45][500/1253] lr: 4.0000e-04 eta: 1:09:03 time: 0.5421 data_time: 0.0262 memory: 23504 grad_norm: 3.4578 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 0.8068 loss: 0.8068 2022/09/08 19:57:19 - mmengine - INFO - Epoch(train) [45][520/1253] lr: 4.0000e-04 eta: 1:08:51 time: 0.5576 data_time: 0.0340 memory: 23504 grad_norm: 3.4467 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7817 loss: 0.7817 2022/09/08 19:57:30 - mmengine - INFO - Epoch(train) [45][540/1253] lr: 4.0000e-04 eta: 1:08:39 time: 0.5568 data_time: 0.0549 memory: 23504 grad_norm: 3.3089 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7735 loss: 0.7735 2022/09/08 19:57:42 - mmengine - INFO - Epoch(train) [45][560/1253] lr: 4.0000e-04 eta: 1:08:27 time: 0.6171 data_time: 0.0343 memory: 23504 grad_norm: 3.3935 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.6905 loss: 0.6905 2022/09/08 19:57:54 - mmengine - INFO - Epoch(train) [45][580/1253] lr: 4.0000e-04 eta: 1:08:15 time: 0.5583 data_time: 0.0355 memory: 23504 grad_norm: 3.4593 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.9193 loss: 0.9193 2022/09/08 19:58:04 - mmengine - INFO - Epoch(train) [45][600/1253] lr: 4.0000e-04 eta: 1:08:03 time: 0.5449 data_time: 0.0416 memory: 23504 grad_norm: 3.4583 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7843 loss: 0.7843 2022/09/08 19:58:16 - mmengine - INFO - Epoch(train) [45][620/1253] lr: 4.0000e-04 eta: 1:07:51 time: 0.5824 data_time: 0.0434 memory: 23504 grad_norm: 3.4175 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.8242 loss: 0.8242 2022/09/08 19:58:28 - mmengine - INFO - Epoch(train) [45][640/1253] lr: 4.0000e-04 eta: 1:07:40 time: 0.5949 data_time: 0.0318 memory: 23504 grad_norm: 3.4543 top1_acc: 0.9167 top5_acc: 0.9167 loss_cls: 0.7044 loss: 0.7044 2022/09/08 19:58:41 - mmengine - INFO - Epoch(train) [45][660/1253] lr: 4.0000e-04 eta: 1:07:28 time: 0.6400 data_time: 0.0347 memory: 23504 grad_norm: 3.3147 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8802 loss: 0.8802 2022/09/08 19:58:53 - mmengine - INFO - Epoch(train) [45][680/1253] lr: 4.0000e-04 eta: 1:07:16 time: 0.6109 data_time: 0.0709 memory: 23504 grad_norm: 3.3979 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.8586 loss: 0.8586 2022/09/08 19:59:05 - mmengine - INFO - Epoch(train) [45][700/1253] lr: 4.0000e-04 eta: 1:07:04 time: 0.6004 data_time: 0.0522 memory: 23504 grad_norm: 3.3794 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.7648 loss: 0.7648 2022/09/08 19:59:16 - mmengine - INFO - Epoch(train) [45][720/1253] lr: 4.0000e-04 eta: 1:06:53 time: 0.5628 data_time: 0.0432 memory: 23504 grad_norm: 3.4058 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8267 loss: 0.8267 2022/09/08 19:59:29 - mmengine - INFO - Epoch(train) [45][740/1253] lr: 4.0000e-04 eta: 1:06:41 time: 0.6166 data_time: 0.0407 memory: 23504 grad_norm: 3.4194 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8196 loss: 0.8196 2022/09/08 19:59:40 - mmengine - INFO - Epoch(train) [45][760/1253] lr: 4.0000e-04 eta: 1:06:29 time: 0.5830 data_time: 0.0486 memory: 23504 grad_norm: 3.4242 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 0.9361 loss: 0.9361 2022/09/08 19:59:52 - mmengine - INFO - Epoch(train) [45][780/1253] lr: 4.0000e-04 eta: 1:06:17 time: 0.5595 data_time: 0.0510 memory: 23504 grad_norm: 3.4181 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.7463 loss: 0.7463 2022/09/08 20:00:03 - mmengine - INFO - Epoch(train) [45][800/1253] lr: 4.0000e-04 eta: 1:06:05 time: 0.5618 data_time: 0.0490 memory: 23504 grad_norm: 3.5403 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.9605 loss: 0.9605 2022/09/08 20:00:15 - mmengine - INFO - Epoch(train) [45][820/1253] lr: 4.0000e-04 eta: 1:05:54 time: 0.6022 data_time: 0.0409 memory: 23504 grad_norm: 3.4033 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8063 loss: 0.8063 2022/09/08 20:00:26 - mmengine - INFO - Epoch(train) [45][840/1253] lr: 4.0000e-04 eta: 1:05:42 time: 0.5834 data_time: 0.0380 memory: 23504 grad_norm: 3.3705 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.7996 loss: 0.7996 2022/09/08 20:00:39 - mmengine - INFO - Epoch(train) [45][860/1253] lr: 4.0000e-04 eta: 1:05:30 time: 0.6475 data_time: 0.0362 memory: 23504 grad_norm: 3.4303 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.7906 loss: 0.7906 2022/09/08 20:00:44 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 20:00:51 - mmengine - INFO - Epoch(train) [45][880/1253] lr: 4.0000e-04 eta: 1:05:18 time: 0.5658 data_time: 0.0497 memory: 23504 grad_norm: 3.2919 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.8045 loss: 0.8045 2022/09/08 20:01:02 - mmengine - INFO - Epoch(train) [45][900/1253] lr: 4.0000e-04 eta: 1:05:06 time: 0.5702 data_time: 0.0292 memory: 23504 grad_norm: 3.3621 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.7884 loss: 0.7884 2022/09/08 20:01:14 - mmengine - INFO - Epoch(train) [45][920/1253] lr: 4.0000e-04 eta: 1:04:54 time: 0.5673 data_time: 0.0403 memory: 23504 grad_norm: 3.4472 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.7502 loss: 0.7502 2022/09/08 20:01:25 - mmengine - INFO - Epoch(train) [45][940/1253] lr: 4.0000e-04 eta: 1:04:43 time: 0.5719 data_time: 0.0392 memory: 23504 grad_norm: 3.3988 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7742 loss: 0.7742 2022/09/08 20:01:37 - mmengine - INFO - Epoch(train) [45][960/1253] lr: 4.0000e-04 eta: 1:04:31 time: 0.6038 data_time: 0.0494 memory: 23504 grad_norm: 3.3072 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.7938 loss: 0.7938 2022/09/08 20:01:48 - mmengine - INFO - Epoch(train) [45][980/1253] lr: 4.0000e-04 eta: 1:04:19 time: 0.5599 data_time: 0.0368 memory: 23504 grad_norm: 3.4090 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8324 loss: 0.8324 2022/09/08 20:02:00 - mmengine - INFO - Epoch(train) [45][1000/1253] lr: 4.0000e-04 eta: 1:04:07 time: 0.5849 data_time: 0.0491 memory: 23504 grad_norm: 3.4565 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7545 loss: 0.7545 2022/09/08 20:02:12 - mmengine - INFO - Epoch(train) [45][1020/1253] lr: 4.0000e-04 eta: 1:03:55 time: 0.6174 data_time: 0.0391 memory: 23504 grad_norm: 3.3910 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.0016 loss: 1.0016 2022/09/08 20:02:27 - mmengine - INFO - Epoch(train) [45][1040/1253] lr: 4.0000e-04 eta: 1:03:44 time: 0.7109 data_time: 0.0401 memory: 23504 grad_norm: 3.4340 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8798 loss: 0.8798 2022/09/08 20:02:38 - mmengine - INFO - Epoch(train) [45][1060/1253] lr: 4.0000e-04 eta: 1:03:32 time: 0.5836 data_time: 0.0422 memory: 23504 grad_norm: 3.3692 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 0.7869 loss: 0.7869 2022/09/08 20:02:49 - mmengine - INFO - Epoch(train) [45][1080/1253] lr: 4.0000e-04 eta: 1:03:20 time: 0.5376 data_time: 0.0421 memory: 23504 grad_norm: 3.4718 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.7018 loss: 0.7018 2022/09/08 20:03:00 - mmengine - INFO - Epoch(train) [45][1100/1253] lr: 4.0000e-04 eta: 1:03:08 time: 0.5413 data_time: 0.0466 memory: 23504 grad_norm: 3.3987 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 0.8160 loss: 0.8160 2022/09/08 20:03:11 - mmengine - INFO - Epoch(train) [45][1120/1253] lr: 4.0000e-04 eta: 1:02:56 time: 0.5734 data_time: 0.0432 memory: 23504 grad_norm: 3.4460 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7430 loss: 0.7430 2022/09/08 20:03:23 - mmengine - INFO - Epoch(train) [45][1140/1253] lr: 4.0000e-04 eta: 1:02:44 time: 0.5701 data_time: 0.0506 memory: 23504 grad_norm: 3.4367 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 0.8106 loss: 0.8106 2022/09/08 20:03:34 - mmengine - INFO - Epoch(train) [45][1160/1253] lr: 4.0000e-04 eta: 1:02:33 time: 0.5632 data_time: 0.0436 memory: 23504 grad_norm: 3.3487 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.8201 loss: 0.8201 2022/09/08 20:03:45 - mmengine - INFO - Epoch(train) [45][1180/1253] lr: 4.0000e-04 eta: 1:02:21 time: 0.5701 data_time: 0.0466 memory: 23504 grad_norm: 3.5407 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.9132 loss: 0.9132 2022/09/08 20:03:57 - mmengine - INFO - Epoch(train) [45][1200/1253] lr: 4.0000e-04 eta: 1:02:09 time: 0.5983 data_time: 0.0417 memory: 23504 grad_norm: 3.4854 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7918 loss: 0.7918 2022/09/08 20:04:09 - mmengine - INFO - Epoch(train) [45][1220/1253] lr: 4.0000e-04 eta: 1:01:57 time: 0.5773 data_time: 0.0478 memory: 23504 grad_norm: 3.3850 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.7963 loss: 0.7963 2022/09/08 20:04:19 - mmengine - INFO - Epoch(train) [45][1240/1253] lr: 4.0000e-04 eta: 1:01:45 time: 0.5069 data_time: 0.0291 memory: 23504 grad_norm: 3.4645 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.7791 loss: 0.7791 2022/09/08 20:04:25 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 20:04:25 - mmengine - INFO - Epoch(train) [45][1253/1253] lr: 4.0000e-04 eta: 1:01:45 time: 0.4371 data_time: 0.0222 memory: 23504 grad_norm: 3.5660 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 0.7785 loss: 0.7785 2022/09/08 20:04:45 - mmengine - INFO - Epoch(val) [45][20/104] eta: 0:01:25 time: 1.0142 data_time: 0.8710 memory: 2699 2022/09/08 20:04:54 - mmengine - INFO - Epoch(val) [45][40/104] eta: 0:00:28 time: 0.4500 data_time: 0.3067 memory: 2699 2022/09/08 20:05:04 - mmengine - INFO - Epoch(val) [45][60/104] eta: 0:00:23 time: 0.5239 data_time: 0.3649 memory: 2699 2022/09/08 20:05:14 - mmengine - INFO - Epoch(val) [45][80/104] eta: 0:00:11 time: 0.4718 data_time: 0.3266 memory: 2699 2022/09/08 20:05:25 - mmengine - INFO - Epoch(val) [45][100/104] eta: 0:00:02 time: 0.5526 data_time: 0.4262 memory: 2699 2022/09/08 20:05:33 - mmengine - INFO - Epoch(val) [45][104/104] acc/top1: 0.7173 acc/top5: 0.9030 acc/mean1: 0.7172 2022/09/08 20:05:33 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb/best_acc/top1_epoch_40.pth is removed 2022/09/08 20:05:34 - mmengine - INFO - The best checkpoint with 0.7173 acc/top1 at 45 epoch is saved to best_acc/top1_epoch_45.pth. 2022/09/08 20:05:58 - mmengine - INFO - Epoch(train) [46][20/1253] lr: 4.0000e-04 eta: 1:01:26 time: 1.1505 data_time: 0.6017 memory: 23504 grad_norm: 3.4114 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.7525 loss: 0.7525 2022/09/08 20:06:09 - mmengine - INFO - Epoch(train) [46][40/1253] lr: 4.0000e-04 eta: 1:01:14 time: 0.5846 data_time: 0.0644 memory: 23504 grad_norm: 3.4049 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.7300 loss: 0.7300 2022/09/08 20:06:21 - mmengine - INFO - Epoch(train) [46][60/1253] lr: 4.0000e-04 eta: 1:01:02 time: 0.5967 data_time: 0.0663 memory: 23504 grad_norm: 3.4651 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8068 loss: 0.8068 2022/09/08 20:06:34 - mmengine - INFO - Epoch(train) [46][80/1253] lr: 4.0000e-04 eta: 1:00:51 time: 0.6480 data_time: 0.0328 memory: 23504 grad_norm: 3.3881 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8026 loss: 0.8026 2022/09/08 20:06:45 - mmengine - INFO - Epoch(train) [46][100/1253] lr: 4.0000e-04 eta: 1:00:39 time: 0.5840 data_time: 0.0350 memory: 23504 grad_norm: 3.3292 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7473 loss: 0.7473 2022/09/08 20:06:57 - mmengine - INFO - Epoch(train) [46][120/1253] lr: 4.0000e-04 eta: 1:00:27 time: 0.5819 data_time: 0.0450 memory: 23504 grad_norm: 3.4380 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8556 loss: 0.8556 2022/09/08 20:07:08 - mmengine - INFO - Epoch(train) [46][140/1253] lr: 4.0000e-04 eta: 1:00:15 time: 0.5664 data_time: 0.0386 memory: 23504 grad_norm: 3.4351 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.7849 loss: 0.7849 2022/09/08 20:07:20 - mmengine - INFO - Epoch(train) [46][160/1253] lr: 4.0000e-04 eta: 1:00:03 time: 0.5769 data_time: 0.0433 memory: 23504 grad_norm: 3.5364 top1_acc: 0.9583 top5_acc: 1.0000 loss_cls: 0.8828 loss: 0.8828 2022/09/08 20:07:31 - mmengine - INFO - Epoch(train) [46][180/1253] lr: 4.0000e-04 eta: 0:59:52 time: 0.5711 data_time: 0.0422 memory: 23504 grad_norm: 3.4270 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 0.7549 loss: 0.7549 2022/09/08 20:07:43 - mmengine - INFO - Epoch(train) [46][200/1253] lr: 4.0000e-04 eta: 0:59:40 time: 0.5821 data_time: 0.0457 memory: 23504 grad_norm: 3.4733 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.9044 loss: 0.9044 2022/09/08 20:07:55 - mmengine - INFO - Epoch(train) [46][220/1253] lr: 4.0000e-04 eta: 0:59:28 time: 0.6188 data_time: 0.0426 memory: 23504 grad_norm: 3.3621 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.8144 loss: 0.8144 2022/09/08 20:08:09 - mmengine - INFO - Epoch(train) [46][240/1253] lr: 4.0000e-04 eta: 0:59:16 time: 0.6711 data_time: 0.0368 memory: 23504 grad_norm: 3.4404 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.8529 loss: 0.8529 2022/09/08 20:08:21 - mmengine - INFO - Epoch(train) [46][260/1253] lr: 4.0000e-04 eta: 0:59:05 time: 0.6104 data_time: 0.0350 memory: 23504 grad_norm: 3.4714 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.8313 loss: 0.8313 2022/09/08 20:08:32 - mmengine - INFO - Epoch(train) [46][280/1253] lr: 4.0000e-04 eta: 0:58:53 time: 0.5419 data_time: 0.0445 memory: 23504 grad_norm: 3.4155 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.7644 loss: 0.7644 2022/09/08 20:08:43 - mmengine - INFO - Epoch(train) [46][300/1253] lr: 4.0000e-04 eta: 0:58:41 time: 0.5903 data_time: 0.0593 memory: 23504 grad_norm: 3.4938 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.7519 loss: 0.7519 2022/09/08 20:08:58 - mmengine - INFO - Epoch(train) [46][320/1253] lr: 4.0000e-04 eta: 0:58:29 time: 0.7066 data_time: 0.2075 memory: 23504 grad_norm: 3.3740 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8207 loss: 0.8207 2022/09/08 20:09:09 - mmengine - INFO - Epoch(train) [46][340/1253] lr: 4.0000e-04 eta: 0:58:18 time: 0.5889 data_time: 0.0863 memory: 23504 grad_norm: 3.4483 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.7899 loss: 0.7899 2022/09/08 20:09:23 - mmengine - INFO - Epoch(train) [46][360/1253] lr: 4.0000e-04 eta: 0:58:06 time: 0.6650 data_time: 0.1781 memory: 23504 grad_norm: 3.4072 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8513 loss: 0.8513 2022/09/08 20:09:34 - mmengine - INFO - Epoch(train) [46][380/1253] lr: 4.0000e-04 eta: 0:57:54 time: 0.5677 data_time: 0.0390 memory: 23504 grad_norm: 3.5275 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.8005 loss: 0.8005 2022/09/08 20:09:47 - mmengine - INFO - Epoch(train) [46][400/1253] lr: 4.0000e-04 eta: 0:57:42 time: 0.6312 data_time: 0.1287 memory: 23504 grad_norm: 3.3330 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8421 loss: 0.8421 2022/09/08 20:09:58 - mmengine - INFO - Epoch(train) [46][420/1253] lr: 4.0000e-04 eta: 0:57:30 time: 0.5650 data_time: 0.0573 memory: 23504 grad_norm: 3.4537 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 0.7471 loss: 0.7471 2022/09/08 20:10:09 - mmengine - INFO - Epoch(train) [46][440/1253] lr: 4.0000e-04 eta: 0:57:19 time: 0.5483 data_time: 0.0318 memory: 23504 grad_norm: 3.4537 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.7534 loss: 0.7534 2022/09/08 20:10:20 - mmengine - INFO - Epoch(train) [46][460/1253] lr: 4.0000e-04 eta: 0:57:07 time: 0.5660 data_time: 0.0405 memory: 23504 grad_norm: 3.4205 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9322 loss: 0.9322 2022/09/08 20:10:32 - mmengine - INFO - Epoch(train) [46][480/1253] lr: 4.0000e-04 eta: 0:56:55 time: 0.5816 data_time: 0.0442 memory: 23504 grad_norm: 3.4078 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.8969 loss: 0.8969 2022/09/08 20:10:44 - mmengine - INFO - Epoch(train) [46][500/1253] lr: 4.0000e-04 eta: 0:56:43 time: 0.5813 data_time: 0.0466 memory: 23504 grad_norm: 3.3936 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 0.9526 loss: 0.9526 2022/09/08 20:10:55 - mmengine - INFO - Epoch(train) [46][520/1253] lr: 4.0000e-04 eta: 0:56:31 time: 0.5876 data_time: 0.0687 memory: 23504 grad_norm: 3.3544 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8664 loss: 0.8664 2022/09/08 20:11:08 - mmengine - INFO - Epoch(train) [46][540/1253] lr: 4.0000e-04 eta: 0:56:19 time: 0.6148 data_time: 0.0414 memory: 23504 grad_norm: 3.3272 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7717 loss: 0.7717 2022/09/08 20:11:21 - mmengine - INFO - Epoch(train) [46][560/1253] lr: 4.0000e-04 eta: 0:56:08 time: 0.6795 data_time: 0.0414 memory: 23504 grad_norm: 3.4307 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.8865 loss: 0.8865 2022/09/08 20:11:33 - mmengine - INFO - Epoch(train) [46][580/1253] lr: 4.0000e-04 eta: 0:55:56 time: 0.5716 data_time: 0.0329 memory: 23504 grad_norm: 3.3513 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.8953 loss: 0.8953 2022/09/08 20:11:46 - mmengine - INFO - Epoch(train) [46][600/1253] lr: 4.0000e-04 eta: 0:55:44 time: 0.6758 data_time: 0.0334 memory: 23504 grad_norm: 3.4287 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 0.9195 loss: 0.9195 2022/09/08 20:12:01 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 20:12:03 - mmengine - INFO - Epoch(train) [46][620/1253] lr: 4.0000e-04 eta: 0:55:33 time: 0.8535 data_time: 0.0344 memory: 23504 grad_norm: 3.4317 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8756 loss: 0.8756 2022/09/08 20:12:14 - mmengine - INFO - Epoch(train) [46][640/1253] lr: 4.0000e-04 eta: 0:55:21 time: 0.5237 data_time: 0.0326 memory: 23504 grad_norm: 3.4324 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.7390 loss: 0.7390 2022/09/08 20:12:25 - mmengine - INFO - Epoch(train) [46][660/1253] lr: 4.0000e-04 eta: 0:55:09 time: 0.5756 data_time: 0.0393 memory: 23504 grad_norm: 3.3889 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8319 loss: 0.8319 2022/09/08 20:12:36 - mmengine - INFO - Epoch(train) [46][680/1253] lr: 4.0000e-04 eta: 0:54:57 time: 0.5458 data_time: 0.0404 memory: 23504 grad_norm: 3.4064 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.9146 loss: 0.9146 2022/09/08 20:12:52 - mmengine - INFO - Epoch(train) [46][700/1253] lr: 4.0000e-04 eta: 0:54:46 time: 0.7895 data_time: 0.0444 memory: 23504 grad_norm: 3.3261 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.7465 loss: 0.7465 2022/09/08 20:13:03 - mmengine - INFO - Epoch(train) [46][720/1253] lr: 4.0000e-04 eta: 0:54:34 time: 0.5546 data_time: 0.0341 memory: 23504 grad_norm: 3.4699 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8425 loss: 0.8425 2022/09/08 20:13:14 - mmengine - INFO - Epoch(train) [46][740/1253] lr: 4.0000e-04 eta: 0:54:22 time: 0.5584 data_time: 0.0424 memory: 23504 grad_norm: 3.3898 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7809 loss: 0.7809 2022/09/08 20:13:28 - mmengine - INFO - Epoch(train) [46][760/1253] lr: 4.0000e-04 eta: 0:54:11 time: 0.6801 data_time: 0.0361 memory: 23504 grad_norm: 3.4516 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.8741 loss: 0.8741 2022/09/08 20:13:41 - mmengine - INFO - Epoch(train) [46][780/1253] lr: 4.0000e-04 eta: 0:53:59 time: 0.6409 data_time: 0.0469 memory: 23504 grad_norm: 3.4633 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8402 loss: 0.8402 2022/09/08 20:13:53 - mmengine - INFO - Epoch(train) [46][800/1253] lr: 4.0000e-04 eta: 0:53:47 time: 0.6111 data_time: 0.0339 memory: 23504 grad_norm: 3.3891 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.8385 loss: 0.8385 2022/09/08 20:14:08 - mmengine - INFO - Epoch(train) [46][820/1253] lr: 4.0000e-04 eta: 0:53:36 time: 0.7576 data_time: 0.0394 memory: 23504 grad_norm: 3.3540 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.8750 loss: 0.8750 2022/09/08 20:14:18 - mmengine - INFO - Epoch(train) [46][840/1253] lr: 4.0000e-04 eta: 0:53:24 time: 0.5110 data_time: 0.0294 memory: 23504 grad_norm: 3.4609 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.8232 loss: 0.8232 2022/09/08 20:14:29 - mmengine - INFO - Epoch(train) [46][860/1253] lr: 4.0000e-04 eta: 0:53:12 time: 0.5294 data_time: 0.0314 memory: 23504 grad_norm: 3.4785 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.7676 loss: 0.7676 2022/09/08 20:14:40 - mmengine - INFO - Epoch(train) [46][880/1253] lr: 4.0000e-04 eta: 0:53:00 time: 0.5683 data_time: 0.0510 memory: 23504 grad_norm: 3.3925 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7526 loss: 0.7526 2022/09/08 20:14:52 - mmengine - INFO - Epoch(train) [46][900/1253] lr: 4.0000e-04 eta: 0:52:48 time: 0.5752 data_time: 0.0409 memory: 23504 grad_norm: 3.3990 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7885 loss: 0.7885 2022/09/08 20:15:04 - mmengine - INFO - Epoch(train) [46][920/1253] lr: 4.0000e-04 eta: 0:52:36 time: 0.6244 data_time: 0.0377 memory: 23504 grad_norm: 3.4602 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8259 loss: 0.8259 2022/09/08 20:15:17 - mmengine - INFO - Epoch(train) [46][940/1253] lr: 4.0000e-04 eta: 0:52:25 time: 0.6344 data_time: 0.0421 memory: 23504 grad_norm: 3.4990 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.7131 loss: 0.7131 2022/09/08 20:15:32 - mmengine - INFO - Epoch(train) [46][960/1253] lr: 4.0000e-04 eta: 0:52:13 time: 0.7734 data_time: 0.0266 memory: 23504 grad_norm: 3.4409 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8931 loss: 0.8931 2022/09/08 20:15:44 - mmengine - INFO - Epoch(train) [46][980/1253] lr: 4.0000e-04 eta: 0:52:01 time: 0.5807 data_time: 0.0337 memory: 23504 grad_norm: 3.4375 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.7948 loss: 0.7948 2022/09/08 20:15:56 - mmengine - INFO - Epoch(train) [46][1000/1253] lr: 4.0000e-04 eta: 0:51:49 time: 0.6144 data_time: 0.0438 memory: 23504 grad_norm: 3.4745 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9090 loss: 0.9090 2022/09/08 20:16:08 - mmengine - INFO - Epoch(train) [46][1020/1253] lr: 4.0000e-04 eta: 0:51:38 time: 0.5901 data_time: 0.0405 memory: 23504 grad_norm: 3.4622 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 0.8501 loss: 0.8501 2022/09/08 20:16:20 - mmengine - INFO - Epoch(train) [46][1040/1253] lr: 4.0000e-04 eta: 0:51:26 time: 0.5669 data_time: 0.0442 memory: 23504 grad_norm: 3.4982 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.8669 loss: 0.8669 2022/09/08 20:16:31 - mmengine - INFO - Epoch(train) [46][1060/1253] lr: 4.0000e-04 eta: 0:51:14 time: 0.5665 data_time: 0.0254 memory: 23504 grad_norm: 3.5165 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8553 loss: 0.8553 2022/09/08 20:16:44 - mmengine - INFO - Epoch(train) [46][1080/1253] lr: 4.0000e-04 eta: 0:51:02 time: 0.6801 data_time: 0.0368 memory: 23504 grad_norm: 3.3659 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7335 loss: 0.7335 2022/09/08 20:16:59 - mmengine - INFO - Epoch(train) [46][1100/1253] lr: 4.0000e-04 eta: 0:50:51 time: 0.7158 data_time: 0.0408 memory: 23504 grad_norm: 3.4784 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.7534 loss: 0.7534 2022/09/08 20:17:11 - mmengine - INFO - Epoch(train) [46][1120/1253] lr: 4.0000e-04 eta: 0:50:39 time: 0.6205 data_time: 0.0327 memory: 23504 grad_norm: 3.4278 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 0.8633 loss: 0.8633 2022/09/08 20:17:22 - mmengine - INFO - Epoch(train) [46][1140/1253] lr: 4.0000e-04 eta: 0:50:27 time: 0.5468 data_time: 0.0359 memory: 23504 grad_norm: 3.3436 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8609 loss: 0.8609 2022/09/08 20:17:34 - mmengine - INFO - Epoch(train) [46][1160/1253] lr: 4.0000e-04 eta: 0:50:15 time: 0.5827 data_time: 0.0827 memory: 23504 grad_norm: 3.4573 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.0178 loss: 1.0178 2022/09/08 20:17:45 - mmengine - INFO - Epoch(train) [46][1180/1253] lr: 4.0000e-04 eta: 0:50:03 time: 0.5822 data_time: 0.0642 memory: 23504 grad_norm: 3.4048 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 0.9067 loss: 0.9067 2022/09/08 20:17:57 - mmengine - INFO - Epoch(train) [46][1200/1253] lr: 4.0000e-04 eta: 0:49:51 time: 0.5719 data_time: 0.0477 memory: 23504 grad_norm: 3.4173 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.7480 loss: 0.7480 2022/09/08 20:18:09 - mmengine - INFO - Epoch(train) [46][1220/1253] lr: 4.0000e-04 eta: 0:49:40 time: 0.5921 data_time: 0.0530 memory: 23504 grad_norm: 3.4348 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.7915 loss: 0.7915 2022/09/08 20:18:22 - mmengine - INFO - Epoch(train) [46][1240/1253] lr: 4.0000e-04 eta: 0:49:28 time: 0.6565 data_time: 0.0248 memory: 23504 grad_norm: 3.4084 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7580 loss: 0.7580 2022/09/08 20:18:27 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 20:18:27 - mmengine - INFO - Epoch(train) [46][1253/1253] lr: 4.0000e-04 eta: 0:49:28 time: 0.4305 data_time: 0.0177 memory: 23504 grad_norm: 3.5366 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 0.8569 loss: 0.8569 2022/09/08 20:18:52 - mmengine - INFO - Epoch(train) [47][20/1253] lr: 4.0000e-04 eta: 0:49:09 time: 1.2440 data_time: 0.4793 memory: 23504 grad_norm: 3.4390 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 0.8908 loss: 0.8908 2022/09/08 20:19:07 - mmengine - INFO - Epoch(train) [47][40/1253] lr: 4.0000e-04 eta: 0:48:57 time: 0.7433 data_time: 0.0388 memory: 23504 grad_norm: 3.4432 top1_acc: 0.9583 top5_acc: 1.0000 loss_cls: 0.7259 loss: 0.7259 2022/09/08 20:19:22 - mmengine - INFO - Epoch(train) [47][60/1253] lr: 4.0000e-04 eta: 0:48:46 time: 0.7210 data_time: 0.0288 memory: 23504 grad_norm: 3.3389 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.7366 loss: 0.7366 2022/09/08 20:19:32 - mmengine - INFO - Epoch(train) [47][80/1253] lr: 4.0000e-04 eta: 0:48:34 time: 0.5202 data_time: 0.0331 memory: 23504 grad_norm: 3.4269 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8349 loss: 0.8349 2022/09/08 20:19:48 - mmengine - INFO - Epoch(train) [47][100/1253] lr: 4.0000e-04 eta: 0:48:22 time: 0.7956 data_time: 0.0530 memory: 23504 grad_norm: 3.3456 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8201 loss: 0.8201 2022/09/08 20:19:58 - mmengine - INFO - Epoch(train) [47][120/1253] lr: 4.0000e-04 eta: 0:48:10 time: 0.5144 data_time: 0.0354 memory: 23504 grad_norm: 3.3780 top1_acc: 0.9167 top5_acc: 0.9167 loss_cls: 0.8717 loss: 0.8717 2022/09/08 20:20:09 - mmengine - INFO - Epoch(train) [47][140/1253] lr: 4.0000e-04 eta: 0:47:59 time: 0.5616 data_time: 0.0380 memory: 23504 grad_norm: 3.4381 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8287 loss: 0.8287 2022/09/08 20:20:22 - mmengine - INFO - Epoch(train) [47][160/1253] lr: 4.0000e-04 eta: 0:47:47 time: 0.6336 data_time: 0.0387 memory: 23504 grad_norm: 3.3930 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8973 loss: 0.8973 2022/09/08 20:20:36 - mmengine - INFO - Epoch(train) [47][180/1253] lr: 4.0000e-04 eta: 0:47:35 time: 0.7045 data_time: 0.0303 memory: 23504 grad_norm: 3.4489 top1_acc: 0.9583 top5_acc: 0.9583 loss_cls: 0.8072 loss: 0.8072 2022/09/08 20:20:47 - mmengine - INFO - Epoch(train) [47][200/1253] lr: 4.0000e-04 eta: 0:47:23 time: 0.5476 data_time: 0.0526 memory: 23504 grad_norm: 3.4227 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.7893 loss: 0.7893 2022/09/08 20:21:00 - mmengine - INFO - Epoch(train) [47][220/1253] lr: 4.0000e-04 eta: 0:47:12 time: 0.6360 data_time: 0.1171 memory: 23504 grad_norm: 3.4620 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7469 loss: 0.7469 2022/09/08 20:21:11 - mmengine - INFO - Epoch(train) [47][240/1253] lr: 4.0000e-04 eta: 0:47:00 time: 0.5634 data_time: 0.0265 memory: 23504 grad_norm: 3.4856 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 0.8728 loss: 0.8728 2022/09/08 20:21:22 - mmengine - INFO - Epoch(train) [47][260/1253] lr: 4.0000e-04 eta: 0:46:48 time: 0.5589 data_time: 0.0355 memory: 23504 grad_norm: 3.4311 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7289 loss: 0.7289 2022/09/08 20:21:36 - mmengine - INFO - Epoch(train) [47][280/1253] lr: 4.0000e-04 eta: 0:46:36 time: 0.6628 data_time: 0.0377 memory: 23504 grad_norm: 3.4915 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8438 loss: 0.8438 2022/09/08 20:21:49 - mmengine - INFO - Epoch(train) [47][300/1253] lr: 4.0000e-04 eta: 0:46:24 time: 0.6434 data_time: 0.0347 memory: 23504 grad_norm: 3.4269 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 0.7103 loss: 0.7103 2022/09/08 20:22:02 - mmengine - INFO - Epoch(train) [47][320/1253] lr: 4.0000e-04 eta: 0:46:13 time: 0.6844 data_time: 0.0344 memory: 23504 grad_norm: 3.3725 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7793 loss: 0.7793 2022/09/08 20:22:13 - mmengine - INFO - Epoch(train) [47][340/1253] lr: 4.0000e-04 eta: 0:46:01 time: 0.5394 data_time: 0.0387 memory: 23504 grad_norm: 3.4203 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7989 loss: 0.7989 2022/09/08 20:22:25 - mmengine - INFO - Epoch(train) [47][360/1253] lr: 4.0000e-04 eta: 0:45:49 time: 0.5880 data_time: 0.0383 memory: 23504 grad_norm: 3.4107 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7685 loss: 0.7685 2022/09/08 20:22:27 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 20:22:37 - mmengine - INFO - Epoch(train) [47][380/1253] lr: 4.0000e-04 eta: 0:45:37 time: 0.6156 data_time: 0.0425 memory: 23504 grad_norm: 3.4111 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.8556 loss: 0.8556 2022/09/08 20:22:50 - mmengine - INFO - Epoch(train) [47][400/1253] lr: 4.0000e-04 eta: 0:45:25 time: 0.6334 data_time: 0.0425 memory: 23504 grad_norm: 3.3330 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7809 loss: 0.7809 2022/09/08 20:23:02 - mmengine - INFO - Epoch(train) [47][420/1253] lr: 4.0000e-04 eta: 0:45:14 time: 0.5872 data_time: 0.0442 memory: 23504 grad_norm: 3.4322 top1_acc: 0.7500 top5_acc: 0.7917 loss_cls: 0.8570 loss: 0.8570 2022/09/08 20:23:13 - mmengine - INFO - Epoch(train) [47][440/1253] lr: 4.0000e-04 eta: 0:45:02 time: 0.5786 data_time: 0.0377 memory: 23504 grad_norm: 3.4745 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.8625 loss: 0.8625 2022/09/08 20:23:26 - mmengine - INFO - Epoch(train) [47][460/1253] lr: 4.0000e-04 eta: 0:44:50 time: 0.6273 data_time: 0.0729 memory: 23504 grad_norm: 3.4660 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.7090 loss: 0.7090 2022/09/08 20:23:37 - mmengine - INFO - Epoch(train) [47][480/1253] lr: 4.0000e-04 eta: 0:44:38 time: 0.5617 data_time: 0.0300 memory: 23504 grad_norm: 3.4659 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8899 loss: 0.8899 2022/09/08 20:23:50 - mmengine - INFO - Epoch(train) [47][500/1253] lr: 4.0000e-04 eta: 0:44:26 time: 0.6624 data_time: 0.0445 memory: 23504 grad_norm: 3.3718 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 0.7598 loss: 0.7598 2022/09/08 20:24:02 - mmengine - INFO - Epoch(train) [47][520/1253] lr: 4.0000e-04 eta: 0:44:15 time: 0.5974 data_time: 0.0296 memory: 23504 grad_norm: 3.4168 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.6997 loss: 0.6997 2022/09/08 20:24:16 - mmengine - INFO - Epoch(train) [47][540/1253] lr: 4.0000e-04 eta: 0:44:03 time: 0.6770 data_time: 0.1443 memory: 23504 grad_norm: 3.4099 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.7439 loss: 0.7439 2022/09/08 20:24:27 - mmengine - INFO - Epoch(train) [47][560/1253] lr: 4.0000e-04 eta: 0:43:51 time: 0.5456 data_time: 0.0294 memory: 23504 grad_norm: 3.4737 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8391 loss: 0.8391 2022/09/08 20:24:39 - mmengine - INFO - Epoch(train) [47][580/1253] lr: 4.0000e-04 eta: 0:43:39 time: 0.5999 data_time: 0.0304 memory: 23504 grad_norm: 3.3578 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.7521 loss: 0.7521 2022/09/08 20:24:50 - mmengine - INFO - Epoch(train) [47][600/1253] lr: 4.0000e-04 eta: 0:43:27 time: 0.5693 data_time: 0.0349 memory: 23504 grad_norm: 3.3694 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8221 loss: 0.8221 2022/09/08 20:25:02 - mmengine - INFO - Epoch(train) [47][620/1253] lr: 4.0000e-04 eta: 0:43:16 time: 0.5810 data_time: 0.0483 memory: 23504 grad_norm: 3.5100 top1_acc: 0.9583 top5_acc: 1.0000 loss_cls: 0.7914 loss: 0.7914 2022/09/08 20:25:16 - mmengine - INFO - Epoch(train) [47][640/1253] lr: 4.0000e-04 eta: 0:43:04 time: 0.7110 data_time: 0.0371 memory: 23504 grad_norm: 3.4376 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.8276 loss: 0.8276 2022/09/08 20:25:30 - mmengine - INFO - Epoch(train) [47][660/1253] lr: 4.0000e-04 eta: 0:42:52 time: 0.6880 data_time: 0.0258 memory: 23504 grad_norm: 3.3626 top1_acc: 0.9167 top5_acc: 0.9167 loss_cls: 0.8105 loss: 0.8105 2022/09/08 20:25:40 - mmengine - INFO - Epoch(train) [47][680/1253] lr: 4.0000e-04 eta: 0:42:40 time: 0.5352 data_time: 0.0242 memory: 23504 grad_norm: 3.4572 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8246 loss: 0.8246 2022/09/08 20:25:55 - mmengine - INFO - Epoch(train) [47][700/1253] lr: 4.0000e-04 eta: 0:42:29 time: 0.7597 data_time: 0.0287 memory: 23504 grad_norm: 3.4093 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8632 loss: 0.8632 2022/09/08 20:26:06 - mmengine - INFO - Epoch(train) [47][720/1253] lr: 4.0000e-04 eta: 0:42:17 time: 0.5284 data_time: 0.0359 memory: 23504 grad_norm: 3.3834 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.8074 loss: 0.8074 2022/09/08 20:26:18 - mmengine - INFO - Epoch(train) [47][740/1253] lr: 4.0000e-04 eta: 0:42:05 time: 0.5980 data_time: 0.0384 memory: 23504 grad_norm: 3.4971 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7462 loss: 0.7462 2022/09/08 20:26:31 - mmengine - INFO - Epoch(train) [47][760/1253] lr: 4.0000e-04 eta: 0:41:53 time: 0.6449 data_time: 0.1527 memory: 23504 grad_norm: 3.4811 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8726 loss: 0.8726 2022/09/08 20:26:44 - mmengine - INFO - Epoch(train) [47][780/1253] lr: 4.0000e-04 eta: 0:41:42 time: 0.6328 data_time: 0.1200 memory: 23504 grad_norm: 3.5365 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 0.9098 loss: 0.9098 2022/09/08 20:26:57 - mmengine - INFO - Epoch(train) [47][800/1253] lr: 4.0000e-04 eta: 0:41:30 time: 0.6660 data_time: 0.1542 memory: 23504 grad_norm: 3.4006 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.8519 loss: 0.8519 2022/09/08 20:27:08 - mmengine - INFO - Epoch(train) [47][820/1253] lr: 4.0000e-04 eta: 0:41:18 time: 0.5469 data_time: 0.0318 memory: 23504 grad_norm: 3.4201 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8627 loss: 0.8627 2022/09/08 20:27:19 - mmengine - INFO - Epoch(train) [47][840/1253] lr: 4.0000e-04 eta: 0:41:06 time: 0.5799 data_time: 0.0522 memory: 23504 grad_norm: 3.4110 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7927 loss: 0.7927 2022/09/08 20:27:31 - mmengine - INFO - Epoch(train) [47][860/1253] lr: 4.0000e-04 eta: 0:40:54 time: 0.5900 data_time: 0.0375 memory: 23504 grad_norm: 3.5464 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.7146 loss: 0.7146 2022/09/08 20:27:45 - mmengine - INFO - Epoch(train) [47][880/1253] lr: 4.0000e-04 eta: 0:40:43 time: 0.6743 data_time: 0.0353 memory: 23504 grad_norm: 3.4729 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8421 loss: 0.8421 2022/09/08 20:27:57 - mmengine - INFO - Epoch(train) [47][900/1253] lr: 4.0000e-04 eta: 0:40:31 time: 0.6356 data_time: 0.0351 memory: 23504 grad_norm: 3.3841 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8517 loss: 0.8517 2022/09/08 20:28:08 - mmengine - INFO - Epoch(train) [47][920/1253] lr: 4.0000e-04 eta: 0:40:19 time: 0.5434 data_time: 0.0448 memory: 23504 grad_norm: 3.4987 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.7945 loss: 0.7945 2022/09/08 20:28:21 - mmengine - INFO - Epoch(train) [47][940/1253] lr: 4.0000e-04 eta: 0:40:07 time: 0.6172 data_time: 0.0372 memory: 23504 grad_norm: 3.5090 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.7707 loss: 0.7707 2022/09/08 20:28:32 - mmengine - INFO - Epoch(train) [47][960/1253] lr: 4.0000e-04 eta: 0:39:55 time: 0.5756 data_time: 0.0311 memory: 23504 grad_norm: 3.4229 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.8268 loss: 0.8268 2022/09/08 20:28:46 - mmengine - INFO - Epoch(train) [47][980/1253] lr: 4.0000e-04 eta: 0:39:44 time: 0.7107 data_time: 0.0398 memory: 23504 grad_norm: 3.3885 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.8051 loss: 0.8051 2022/09/08 20:28:58 - mmengine - INFO - Epoch(train) [47][1000/1253] lr: 4.0000e-04 eta: 0:39:32 time: 0.5645 data_time: 0.0411 memory: 23504 grad_norm: 3.3482 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.6809 loss: 0.6809 2022/09/08 20:29:10 - mmengine - INFO - Epoch(train) [47][1020/1253] lr: 4.0000e-04 eta: 0:39:20 time: 0.6153 data_time: 0.0351 memory: 23504 grad_norm: 3.4681 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7779 loss: 0.7779 2022/09/08 20:29:24 - mmengine - INFO - Epoch(train) [47][1040/1253] lr: 4.0000e-04 eta: 0:39:08 time: 0.7025 data_time: 0.0330 memory: 23504 grad_norm: 3.4272 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.7763 loss: 0.7763 2022/09/08 20:29:35 - mmengine - INFO - Epoch(train) [47][1060/1253] lr: 4.0000e-04 eta: 0:38:56 time: 0.5390 data_time: 0.0421 memory: 23504 grad_norm: 3.4134 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8640 loss: 0.8640 2022/09/08 20:29:46 - mmengine - INFO - Epoch(train) [47][1080/1253] lr: 4.0000e-04 eta: 0:38:44 time: 0.5583 data_time: 0.0395 memory: 23504 grad_norm: 3.4881 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7524 loss: 0.7524 2022/09/08 20:29:59 - mmengine - INFO - Epoch(train) [47][1100/1253] lr: 4.0000e-04 eta: 0:38:33 time: 0.6383 data_time: 0.0423 memory: 23504 grad_norm: 3.4067 top1_acc: 0.7500 top5_acc: 0.7917 loss_cls: 0.8075 loss: 0.8075 2022/09/08 20:30:13 - mmengine - INFO - Epoch(train) [47][1120/1253] lr: 4.0000e-04 eta: 0:38:21 time: 0.7022 data_time: 0.0413 memory: 23504 grad_norm: 3.4849 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.7849 loss: 0.7849 2022/09/08 20:30:24 - mmengine - INFO - Epoch(train) [47][1140/1253] lr: 4.0000e-04 eta: 0:38:09 time: 0.5392 data_time: 0.0373 memory: 23504 grad_norm: 3.4478 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9608 loss: 0.9608 2022/09/08 20:30:35 - mmengine - INFO - Epoch(train) [47][1160/1253] lr: 4.0000e-04 eta: 0:37:57 time: 0.5514 data_time: 0.0300 memory: 23504 grad_norm: 3.4199 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7742 loss: 0.7742 2022/09/08 20:30:47 - mmengine - INFO - Epoch(train) [47][1180/1253] lr: 4.0000e-04 eta: 0:37:45 time: 0.6156 data_time: 0.0322 memory: 23504 grad_norm: 3.4412 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.8852 loss: 0.8852 2022/09/08 20:30:59 - mmengine - INFO - Epoch(train) [47][1200/1253] lr: 4.0000e-04 eta: 0:37:34 time: 0.6011 data_time: 0.0469 memory: 23504 grad_norm: 3.4809 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.8383 loss: 0.8383 2022/09/08 20:31:13 - mmengine - INFO - Epoch(train) [47][1220/1253] lr: 4.0000e-04 eta: 0:37:22 time: 0.7065 data_time: 0.1633 memory: 23504 grad_norm: 3.4094 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7969 loss: 0.7969 2022/09/08 20:31:23 - mmengine - INFO - Epoch(train) [47][1240/1253] lr: 4.0000e-04 eta: 0:37:10 time: 0.4804 data_time: 0.0294 memory: 23504 grad_norm: 3.4081 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.8458 loss: 0.8458 2022/09/08 20:31:28 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 20:31:28 - mmengine - INFO - Epoch(train) [47][1253/1253] lr: 4.0000e-04 eta: 0:37:10 time: 0.4514 data_time: 0.0284 memory: 23504 grad_norm: 3.6131 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 0.7991 loss: 0.7991 2022/09/08 20:31:52 - mmengine - INFO - Epoch(train) [48][20/1253] lr: 4.0000e-04 eta: 0:36:51 time: 1.1781 data_time: 0.4058 memory: 23504 grad_norm: 3.4279 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.6842 loss: 0.6842 2022/09/08 20:32:07 - mmengine - INFO - Epoch(train) [48][40/1253] lr: 4.0000e-04 eta: 0:36:39 time: 0.7520 data_time: 0.0437 memory: 23504 grad_norm: 3.4170 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8028 loss: 0.8028 2022/09/08 20:32:19 - mmengine - INFO - Epoch(train) [48][60/1253] lr: 4.0000e-04 eta: 0:36:27 time: 0.6040 data_time: 0.0433 memory: 23504 grad_norm: 3.3947 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 0.7487 loss: 0.7487 2022/09/08 20:32:32 - mmengine - INFO - Epoch(train) [48][80/1253] lr: 4.0000e-04 eta: 0:36:16 time: 0.6495 data_time: 0.0292 memory: 23504 grad_norm: 3.5298 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.7447 loss: 0.7447 2022/09/08 20:32:43 - mmengine - INFO - Epoch(train) [48][100/1253] lr: 4.0000e-04 eta: 0:36:04 time: 0.5403 data_time: 0.0302 memory: 23504 grad_norm: 3.4108 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8389 loss: 0.8389 2022/09/08 20:32:48 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 20:32:55 - mmengine - INFO - Epoch(train) [48][120/1253] lr: 4.0000e-04 eta: 0:35:52 time: 0.5777 data_time: 0.0430 memory: 23504 grad_norm: 3.4267 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.8794 loss: 0.8794 2022/09/08 20:33:08 - mmengine - INFO - Epoch(train) [48][140/1253] lr: 4.0000e-04 eta: 0:35:40 time: 0.6521 data_time: 0.0485 memory: 23504 grad_norm: 3.4190 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7241 loss: 0.7241 2022/09/08 20:33:20 - mmengine - INFO - Epoch(train) [48][160/1253] lr: 4.0000e-04 eta: 0:35:28 time: 0.5959 data_time: 0.0328 memory: 23504 grad_norm: 3.4852 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8637 loss: 0.8637 2022/09/08 20:33:32 - mmengine - INFO - Epoch(train) [48][180/1253] lr: 4.0000e-04 eta: 0:35:16 time: 0.6141 data_time: 0.0427 memory: 23504 grad_norm: 3.4834 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 0.8797 loss: 0.8797 2022/09/08 20:33:43 - mmengine - INFO - Epoch(train) [48][200/1253] lr: 4.0000e-04 eta: 0:35:05 time: 0.5595 data_time: 0.0359 memory: 23504 grad_norm: 3.4001 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.8216 loss: 0.8216 2022/09/08 20:33:54 - mmengine - INFO - Epoch(train) [48][220/1253] lr: 4.0000e-04 eta: 0:34:53 time: 0.5536 data_time: 0.0383 memory: 23504 grad_norm: 3.5468 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.7948 loss: 0.7948 2022/09/08 20:34:11 - mmengine - INFO - Epoch(train) [48][240/1253] lr: 4.0000e-04 eta: 0:34:41 time: 0.8331 data_time: 0.0347 memory: 23504 grad_norm: 3.4619 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.8143 loss: 0.8143 2022/09/08 20:34:22 - mmengine - INFO - Epoch(train) [48][260/1253] lr: 4.0000e-04 eta: 0:34:29 time: 0.5422 data_time: 0.0366 memory: 23504 grad_norm: 3.5602 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8588 loss: 0.8588 2022/09/08 20:34:35 - mmengine - INFO - Epoch(train) [48][280/1253] lr: 4.0000e-04 eta: 0:34:18 time: 0.6696 data_time: 0.0370 memory: 23504 grad_norm: 3.4415 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.8764 loss: 0.8764 2022/09/08 20:34:46 - mmengine - INFO - Epoch(train) [48][300/1253] lr: 4.0000e-04 eta: 0:34:06 time: 0.5426 data_time: 0.0335 memory: 23504 grad_norm: 3.4171 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.7728 loss: 0.7728 2022/09/08 20:34:57 - mmengine - INFO - Epoch(train) [48][320/1253] lr: 4.0000e-04 eta: 0:33:54 time: 0.5566 data_time: 0.0435 memory: 23504 grad_norm: 3.4341 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.9214 loss: 0.9214 2022/09/08 20:35:11 - mmengine - INFO - Epoch(train) [48][340/1253] lr: 4.0000e-04 eta: 0:33:42 time: 0.7123 data_time: 0.0367 memory: 23504 grad_norm: 3.4147 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8589 loss: 0.8589 2022/09/08 20:35:22 - mmengine - INFO - Epoch(train) [48][360/1253] lr: 4.0000e-04 eta: 0:33:30 time: 0.5531 data_time: 0.0344 memory: 23504 grad_norm: 3.4499 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.7509 loss: 0.7509 2022/09/08 20:35:35 - mmengine - INFO - Epoch(train) [48][380/1253] lr: 4.0000e-04 eta: 0:33:18 time: 0.6098 data_time: 0.0323 memory: 23504 grad_norm: 3.3699 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7803 loss: 0.7803 2022/09/08 20:35:46 - mmengine - INFO - Epoch(train) [48][400/1253] lr: 4.0000e-04 eta: 0:33:07 time: 0.5927 data_time: 0.0450 memory: 23504 grad_norm: 3.4105 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.7889 loss: 0.7889 2022/09/08 20:36:03 - mmengine - INFO - Epoch(train) [48][420/1253] lr: 4.0000e-04 eta: 0:32:55 time: 0.8522 data_time: 0.3038 memory: 23504 grad_norm: 3.5140 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.8480 loss: 0.8480 2022/09/08 20:36:14 - mmengine - INFO - Epoch(train) [48][440/1253] lr: 4.0000e-04 eta: 0:32:43 time: 0.5253 data_time: 0.0192 memory: 23504 grad_norm: 3.4661 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.8027 loss: 0.8027 2022/09/08 20:36:25 - mmengine - INFO - Epoch(train) [48][460/1253] lr: 4.0000e-04 eta: 0:32:31 time: 0.5347 data_time: 0.0359 memory: 23504 grad_norm: 3.3907 top1_acc: 0.7083 top5_acc: 1.0000 loss_cls: 0.8455 loss: 0.8455 2022/09/08 20:36:37 - mmengine - INFO - Epoch(train) [48][480/1253] lr: 4.0000e-04 eta: 0:32:19 time: 0.6403 data_time: 0.0469 memory: 23504 grad_norm: 3.4224 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8061 loss: 0.8061 2022/09/08 20:36:50 - mmengine - INFO - Epoch(train) [48][500/1253] lr: 4.0000e-04 eta: 0:32:08 time: 0.6125 data_time: 0.0389 memory: 23504 grad_norm: 3.4052 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.7583 loss: 0.7583 2022/09/08 20:37:01 - mmengine - INFO - Epoch(train) [48][520/1253] lr: 4.0000e-04 eta: 0:31:56 time: 0.5645 data_time: 0.0460 memory: 23504 grad_norm: 3.4665 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8463 loss: 0.8463 2022/09/08 20:37:14 - mmengine - INFO - Epoch(train) [48][540/1253] lr: 4.0000e-04 eta: 0:31:44 time: 0.6722 data_time: 0.0413 memory: 23504 grad_norm: 3.5243 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9679 loss: 0.9679 2022/09/08 20:37:28 - mmengine - INFO - Epoch(train) [48][560/1253] lr: 4.0000e-04 eta: 0:31:32 time: 0.7010 data_time: 0.0379 memory: 23504 grad_norm: 3.2711 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.7673 loss: 0.7673 2022/09/08 20:37:39 - mmengine - INFO - Epoch(train) [48][580/1253] lr: 4.0000e-04 eta: 0:31:20 time: 0.5439 data_time: 0.0343 memory: 23504 grad_norm: 3.4192 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7282 loss: 0.7282 2022/09/08 20:37:50 - mmengine - INFO - Epoch(train) [48][600/1253] lr: 4.0000e-04 eta: 0:31:09 time: 0.5419 data_time: 0.0367 memory: 23504 grad_norm: 3.4052 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8484 loss: 0.8484 2022/09/08 20:38:05 - mmengine - INFO - Epoch(train) [48][620/1253] lr: 4.0000e-04 eta: 0:30:57 time: 0.7383 data_time: 0.0311 memory: 23504 grad_norm: 3.4799 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.8043 loss: 0.8043 2022/09/08 20:38:16 - mmengine - INFO - Epoch(train) [48][640/1253] lr: 4.0000e-04 eta: 0:30:45 time: 0.5466 data_time: 0.0340 memory: 23504 grad_norm: 3.4283 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7526 loss: 0.7526 2022/09/08 20:38:27 - mmengine - INFO - Epoch(train) [48][660/1253] lr: 4.0000e-04 eta: 0:30:33 time: 0.5745 data_time: 0.0447 memory: 23504 grad_norm: 3.4485 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8822 loss: 0.8822 2022/09/08 20:38:42 - mmengine - INFO - Epoch(train) [48][680/1253] lr: 4.0000e-04 eta: 0:30:21 time: 0.7394 data_time: 0.0360 memory: 23504 grad_norm: 3.4239 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 0.8258 loss: 0.8258 2022/09/08 20:38:53 - mmengine - INFO - Epoch(train) [48][700/1253] lr: 4.0000e-04 eta: 0:30:10 time: 0.5336 data_time: 0.0306 memory: 23504 grad_norm: 3.5036 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.7734 loss: 0.7734 2022/09/08 20:39:04 - mmengine - INFO - Epoch(train) [48][720/1253] lr: 4.0000e-04 eta: 0:29:58 time: 0.5544 data_time: 0.0458 memory: 23504 grad_norm: 3.5110 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8016 loss: 0.8016 2022/09/08 20:39:18 - mmengine - INFO - Epoch(train) [48][740/1253] lr: 4.0000e-04 eta: 0:29:46 time: 0.6945 data_time: 0.0369 memory: 23504 grad_norm: 3.4459 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 0.9329 loss: 0.9329 2022/09/08 20:39:29 - mmengine - INFO - Epoch(train) [48][760/1253] lr: 4.0000e-04 eta: 0:29:34 time: 0.5387 data_time: 0.0392 memory: 23504 grad_norm: 3.4273 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.9089 loss: 0.9089 2022/09/08 20:39:43 - mmengine - INFO - Epoch(train) [48][780/1253] lr: 4.0000e-04 eta: 0:29:22 time: 0.7104 data_time: 0.1289 memory: 23504 grad_norm: 3.4219 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 0.7846 loss: 0.7846 2022/09/08 20:39:56 - mmengine - INFO - Epoch(train) [48][800/1253] lr: 4.0000e-04 eta: 0:29:11 time: 0.6350 data_time: 0.0249 memory: 23504 grad_norm: 3.4430 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.7277 loss: 0.7277 2022/09/08 20:40:09 - mmengine - INFO - Epoch(train) [48][820/1253] lr: 4.0000e-04 eta: 0:28:59 time: 0.6834 data_time: 0.0321 memory: 23504 grad_norm: 3.4464 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.7177 loss: 0.7177 2022/09/08 20:40:20 - mmengine - INFO - Epoch(train) [48][840/1253] lr: 4.0000e-04 eta: 0:28:47 time: 0.5309 data_time: 0.0354 memory: 23504 grad_norm: 3.4394 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 0.8453 loss: 0.8453 2022/09/08 20:40:31 - mmengine - INFO - Epoch(train) [48][860/1253] lr: 4.0000e-04 eta: 0:28:35 time: 0.5619 data_time: 0.0367 memory: 23504 grad_norm: 3.4315 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7698 loss: 0.7698 2022/09/08 20:40:45 - mmengine - INFO - Epoch(train) [48][880/1253] lr: 4.0000e-04 eta: 0:28:23 time: 0.6941 data_time: 0.0339 memory: 23504 grad_norm: 3.5156 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8173 loss: 0.8173 2022/09/08 20:40:57 - mmengine - INFO - Epoch(train) [48][900/1253] lr: 4.0000e-04 eta: 0:28:11 time: 0.6059 data_time: 0.0372 memory: 23504 grad_norm: 3.4824 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7152 loss: 0.7152 2022/09/08 20:41:09 - mmengine - INFO - Epoch(train) [48][920/1253] lr: 4.0000e-04 eta: 0:28:00 time: 0.5770 data_time: 0.0504 memory: 23504 grad_norm: 3.3872 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 0.6613 loss: 0.6613 2022/09/08 20:41:21 - mmengine - INFO - Epoch(train) [48][940/1253] lr: 4.0000e-04 eta: 0:27:48 time: 0.5960 data_time: 0.0425 memory: 23504 grad_norm: 3.5417 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9012 loss: 0.9012 2022/09/08 20:41:32 - mmengine - INFO - Epoch(train) [48][960/1253] lr: 4.0000e-04 eta: 0:27:36 time: 0.5522 data_time: 0.0316 memory: 23504 grad_norm: 3.3772 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.7818 loss: 0.7818 2022/09/08 20:41:44 - mmengine - INFO - Epoch(train) [48][980/1253] lr: 4.0000e-04 eta: 0:27:24 time: 0.6096 data_time: 0.0396 memory: 23504 grad_norm: 3.4104 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.7626 loss: 0.7626 2022/09/08 20:41:55 - mmengine - INFO - Epoch(train) [48][1000/1253] lr: 4.0000e-04 eta: 0:27:12 time: 0.5655 data_time: 0.0342 memory: 23504 grad_norm: 3.4009 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.8451 loss: 0.8451 2022/09/08 20:42:07 - mmengine - INFO - Epoch(train) [48][1020/1253] lr: 4.0000e-04 eta: 0:27:00 time: 0.5825 data_time: 0.0397 memory: 23504 grad_norm: 3.4250 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.0107 loss: 1.0107 2022/09/08 20:42:21 - mmengine - INFO - Epoch(train) [48][1040/1253] lr: 4.0000e-04 eta: 0:26:49 time: 0.7020 data_time: 0.0436 memory: 23504 grad_norm: 3.4813 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8351 loss: 0.8351 2022/09/08 20:42:33 - mmengine - INFO - Epoch(train) [48][1060/1253] lr: 4.0000e-04 eta: 0:26:37 time: 0.5902 data_time: 0.0762 memory: 23504 grad_norm: 3.4236 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.8931 loss: 0.8931 2022/09/08 20:42:44 - mmengine - INFO - Epoch(train) [48][1080/1253] lr: 4.0000e-04 eta: 0:26:25 time: 0.5846 data_time: 0.0464 memory: 23504 grad_norm: 3.4043 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.7925 loss: 0.7925 2022/09/08 20:42:58 - mmengine - INFO - Epoch(train) [48][1100/1253] lr: 4.0000e-04 eta: 0:26:13 time: 0.7024 data_time: 0.1941 memory: 23504 grad_norm: 3.4674 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.7441 loss: 0.7441 2022/09/08 20:43:03 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 20:43:10 - mmengine - INFO - Epoch(train) [48][1120/1253] lr: 4.0000e-04 eta: 0:26:01 time: 0.5696 data_time: 0.0645 memory: 23504 grad_norm: 3.3751 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.7380 loss: 0.7380 2022/09/08 20:43:22 - mmengine - INFO - Epoch(train) [48][1140/1253] lr: 4.0000e-04 eta: 0:25:50 time: 0.6298 data_time: 0.0353 memory: 23504 grad_norm: 3.4542 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.8260 loss: 0.8260 2022/09/08 20:43:35 - mmengine - INFO - Epoch(train) [48][1160/1253] lr: 4.0000e-04 eta: 0:25:38 time: 0.6241 data_time: 0.1055 memory: 23504 grad_norm: 3.3474 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.7528 loss: 0.7528 2022/09/08 20:43:49 - mmengine - INFO - Epoch(train) [48][1180/1253] lr: 4.0000e-04 eta: 0:25:26 time: 0.7061 data_time: 0.1734 memory: 23504 grad_norm: 3.4118 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 0.8616 loss: 0.8616 2022/09/08 20:44:00 - mmengine - INFO - Epoch(train) [48][1200/1253] lr: 4.0000e-04 eta: 0:25:14 time: 0.5209 data_time: 0.0267 memory: 23504 grad_norm: 3.4627 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.7784 loss: 0.7784 2022/09/08 20:44:14 - mmengine - INFO - Epoch(train) [48][1220/1253] lr: 4.0000e-04 eta: 0:25:02 time: 0.7099 data_time: 0.0307 memory: 23504 grad_norm: 3.4455 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.7874 loss: 0.7874 2022/09/08 20:44:23 - mmengine - INFO - Epoch(train) [48][1240/1253] lr: 4.0000e-04 eta: 0:24:50 time: 0.4703 data_time: 0.0205 memory: 23504 grad_norm: 3.5137 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7360 loss: 0.7360 2022/09/08 20:44:29 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 20:44:29 - mmengine - INFO - Epoch(train) [48][1253/1253] lr: 4.0000e-04 eta: 0:24:50 time: 0.4317 data_time: 0.0157 memory: 23504 grad_norm: 3.6603 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 0.8793 loss: 0.8793 2022/09/08 20:45:00 - mmengine - INFO - Epoch(train) [49][20/1253] lr: 4.0000e-04 eta: 0:24:31 time: 1.5656 data_time: 0.3975 memory: 23504 grad_norm: 3.3931 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.7907 loss: 0.7907 2022/09/08 20:45:10 - mmengine - INFO - Epoch(train) [49][40/1253] lr: 4.0000e-04 eta: 0:24:20 time: 0.5100 data_time: 0.0337 memory: 23504 grad_norm: 3.4798 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8110 loss: 0.8110 2022/09/08 20:45:21 - mmengine - INFO - Epoch(train) [49][60/1253] lr: 4.0000e-04 eta: 0:24:08 time: 0.5175 data_time: 0.0305 memory: 23504 grad_norm: 3.3450 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 0.7790 loss: 0.7790 2022/09/08 20:45:32 - mmengine - INFO - Epoch(train) [49][80/1253] lr: 4.0000e-04 eta: 0:23:56 time: 0.5904 data_time: 0.0458 memory: 23504 grad_norm: 3.4570 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 0.7782 loss: 0.7782 2022/09/08 20:45:45 - mmengine - INFO - Epoch(train) [49][100/1253] lr: 4.0000e-04 eta: 0:23:44 time: 0.6441 data_time: 0.0395 memory: 23504 grad_norm: 3.3636 top1_acc: 0.9583 top5_acc: 1.0000 loss_cls: 0.7560 loss: 0.7560 2022/09/08 20:46:01 - mmengine - INFO - Epoch(train) [49][120/1253] lr: 4.0000e-04 eta: 0:23:32 time: 0.7770 data_time: 0.0299 memory: 23504 grad_norm: 3.4229 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7405 loss: 0.7405 2022/09/08 20:46:11 - mmengine - INFO - Epoch(train) [49][140/1253] lr: 4.0000e-04 eta: 0:23:20 time: 0.5182 data_time: 0.0327 memory: 23504 grad_norm: 3.4422 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.8718 loss: 0.8718 2022/09/08 20:46:22 - mmengine - INFO - Epoch(train) [49][160/1253] lr: 4.0000e-04 eta: 0:23:08 time: 0.5409 data_time: 0.0487 memory: 23504 grad_norm: 3.4392 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8750 loss: 0.8750 2022/09/08 20:46:34 - mmengine - INFO - Epoch(train) [49][180/1253] lr: 4.0000e-04 eta: 0:22:57 time: 0.5915 data_time: 0.0348 memory: 23504 grad_norm: 3.5352 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8553 loss: 0.8553 2022/09/08 20:46:50 - mmengine - INFO - Epoch(train) [49][200/1253] lr: 4.0000e-04 eta: 0:22:45 time: 0.7965 data_time: 0.0611 memory: 23504 grad_norm: 3.3133 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7052 loss: 0.7052 2022/09/08 20:47:01 - mmengine - INFO - Epoch(train) [49][220/1253] lr: 4.0000e-04 eta: 0:22:33 time: 0.5545 data_time: 0.0410 memory: 23504 grad_norm: 3.4298 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.7708 loss: 0.7708 2022/09/08 20:47:13 - mmengine - INFO - Epoch(train) [49][240/1253] lr: 4.0000e-04 eta: 0:22:21 time: 0.5877 data_time: 0.0429 memory: 23504 grad_norm: 3.4568 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.7918 loss: 0.7918 2022/09/08 20:47:26 - mmengine - INFO - Epoch(train) [49][260/1253] lr: 4.0000e-04 eta: 0:22:09 time: 0.6601 data_time: 0.0322 memory: 23504 grad_norm: 3.4652 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.7745 loss: 0.7745 2022/09/08 20:47:37 - mmengine - INFO - Epoch(train) [49][280/1253] lr: 4.0000e-04 eta: 0:21:58 time: 0.5419 data_time: 0.0367 memory: 23504 grad_norm: 3.4239 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8125 loss: 0.8125 2022/09/08 20:47:52 - mmengine - INFO - Epoch(train) [49][300/1253] lr: 4.0000e-04 eta: 0:21:46 time: 0.7752 data_time: 0.0410 memory: 23504 grad_norm: 3.4000 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.7464 loss: 0.7464 2022/09/08 20:48:03 - mmengine - INFO - Epoch(train) [49][320/1253] lr: 4.0000e-04 eta: 0:21:34 time: 0.5389 data_time: 0.0395 memory: 23504 grad_norm: 3.5104 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8560 loss: 0.8560 2022/09/08 20:48:15 - mmengine - INFO - Epoch(train) [49][340/1253] lr: 4.0000e-04 eta: 0:21:22 time: 0.5838 data_time: 0.0356 memory: 23504 grad_norm: 3.4995 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8861 loss: 0.8861 2022/09/08 20:48:28 - mmengine - INFO - Epoch(train) [49][360/1253] lr: 4.0000e-04 eta: 0:21:10 time: 0.6447 data_time: 0.0404 memory: 23504 grad_norm: 3.4471 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7870 loss: 0.7870 2022/09/08 20:48:40 - mmengine - INFO - Epoch(train) [49][380/1253] lr: 4.0000e-04 eta: 0:20:59 time: 0.6151 data_time: 0.0419 memory: 23504 grad_norm: 3.3548 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7569 loss: 0.7569 2022/09/08 20:48:52 - mmengine - INFO - Epoch(train) [49][400/1253] lr: 4.0000e-04 eta: 0:20:47 time: 0.5842 data_time: 0.0270 memory: 23504 grad_norm: 3.4171 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7433 loss: 0.7433 2022/09/08 20:49:03 - mmengine - INFO - Epoch(train) [49][420/1253] lr: 4.0000e-04 eta: 0:20:35 time: 0.5842 data_time: 0.0426 memory: 23504 grad_norm: 3.4672 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.8080 loss: 0.8080 2022/09/08 20:49:15 - mmengine - INFO - Epoch(train) [49][440/1253] lr: 4.0000e-04 eta: 0:20:23 time: 0.5624 data_time: 0.0374 memory: 23504 grad_norm: 3.4539 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8159 loss: 0.8159 2022/09/08 20:49:27 - mmengine - INFO - Epoch(train) [49][460/1253] lr: 4.0000e-04 eta: 0:20:11 time: 0.6432 data_time: 0.0489 memory: 23504 grad_norm: 3.4188 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 0.7465 loss: 0.7465 2022/09/08 20:49:39 - mmengine - INFO - Epoch(train) [49][480/1253] lr: 4.0000e-04 eta: 0:19:59 time: 0.5786 data_time: 0.0320 memory: 23504 grad_norm: 3.3514 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7421 loss: 0.7421 2022/09/08 20:49:50 - mmengine - INFO - Epoch(train) [49][500/1253] lr: 4.0000e-04 eta: 0:19:47 time: 0.5658 data_time: 0.0465 memory: 23504 grad_norm: 3.4532 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8238 loss: 0.8238 2022/09/08 20:50:04 - mmengine - INFO - Epoch(train) [49][520/1253] lr: 4.0000e-04 eta: 0:19:36 time: 0.7087 data_time: 0.1567 memory: 23504 grad_norm: 3.3691 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8694 loss: 0.8694 2022/09/08 20:50:19 - mmengine - INFO - Epoch(train) [49][540/1253] lr: 4.0000e-04 eta: 0:19:24 time: 0.7137 data_time: 0.2180 memory: 23504 grad_norm: 3.4024 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7732 loss: 0.7732 2022/09/08 20:50:31 - mmengine - INFO - Epoch(train) [49][560/1253] lr: 4.0000e-04 eta: 0:19:12 time: 0.5904 data_time: 0.0894 memory: 23504 grad_norm: 3.5092 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7828 loss: 0.7828 2022/09/08 20:50:41 - mmengine - INFO - Epoch(train) [49][580/1253] lr: 4.0000e-04 eta: 0:19:00 time: 0.5331 data_time: 0.0272 memory: 23504 grad_norm: 3.5080 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 0.7607 loss: 0.7607 2022/09/08 20:50:54 - mmengine - INFO - Epoch(train) [49][600/1253] lr: 4.0000e-04 eta: 0:18:48 time: 0.6348 data_time: 0.0437 memory: 23504 grad_norm: 3.4981 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7688 loss: 0.7688 2022/09/08 20:51:06 - mmengine - INFO - Epoch(train) [49][620/1253] lr: 4.0000e-04 eta: 0:18:36 time: 0.5909 data_time: 0.0481 memory: 23504 grad_norm: 3.4015 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 0.7034 loss: 0.7034 2022/09/08 20:51:18 - mmengine - INFO - Epoch(train) [49][640/1253] lr: 4.0000e-04 eta: 0:18:25 time: 0.6313 data_time: 0.0404 memory: 23504 grad_norm: 3.4189 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.8450 loss: 0.8450 2022/09/08 20:51:31 - mmengine - INFO - Epoch(train) [49][660/1253] lr: 4.0000e-04 eta: 0:18:13 time: 0.6178 data_time: 0.0345 memory: 23504 grad_norm: 3.4478 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8688 loss: 0.8688 2022/09/08 20:51:44 - mmengine - INFO - Epoch(train) [49][680/1253] lr: 4.0000e-04 eta: 0:18:01 time: 0.6737 data_time: 0.0310 memory: 23504 grad_norm: 3.3781 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.7234 loss: 0.7234 2022/09/08 20:51:55 - mmengine - INFO - Epoch(train) [49][700/1253] lr: 4.0000e-04 eta: 0:17:49 time: 0.5350 data_time: 0.0401 memory: 23504 grad_norm: 3.4324 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8019 loss: 0.8019 2022/09/08 20:52:06 - mmengine - INFO - Epoch(train) [49][720/1253] lr: 4.0000e-04 eta: 0:17:37 time: 0.5657 data_time: 0.0353 memory: 23504 grad_norm: 3.3843 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7714 loss: 0.7714 2022/09/08 20:52:20 - mmengine - INFO - Epoch(train) [49][740/1253] lr: 4.0000e-04 eta: 0:17:26 time: 0.6986 data_time: 0.0388 memory: 23504 grad_norm: 3.4418 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7026 loss: 0.7026 2022/09/08 20:52:31 - mmengine - INFO - Epoch(train) [49][760/1253] lr: 4.0000e-04 eta: 0:17:14 time: 0.5498 data_time: 0.0523 memory: 23504 grad_norm: 3.4270 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7348 loss: 0.7348 2022/09/08 20:52:42 - mmengine - INFO - Epoch(train) [49][780/1253] lr: 4.0000e-04 eta: 0:17:02 time: 0.5420 data_time: 0.0450 memory: 23504 grad_norm: 3.5211 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.8021 loss: 0.8021 2022/09/08 20:52:53 - mmengine - INFO - Epoch(train) [49][800/1253] lr: 4.0000e-04 eta: 0:16:50 time: 0.5626 data_time: 0.0412 memory: 23504 grad_norm: 3.3614 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8006 loss: 0.8006 2022/09/08 20:53:11 - mmengine - INFO - Epoch(train) [49][820/1253] lr: 4.0000e-04 eta: 0:16:38 time: 0.8803 data_time: 0.0364 memory: 23504 grad_norm: 3.4619 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.8549 loss: 0.8549 2022/09/08 20:53:25 - mmengine - INFO - Epoch(train) [49][840/1253] lr: 4.0000e-04 eta: 0:16:26 time: 0.6905 data_time: 0.0337 memory: 23504 grad_norm: 3.4681 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.8437 loss: 0.8437 2022/09/08 20:53:34 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 20:53:36 - mmengine - INFO - Epoch(train) [49][860/1253] lr: 4.0000e-04 eta: 0:16:15 time: 0.5689 data_time: 0.0340 memory: 23504 grad_norm: 3.4238 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8258 loss: 0.8258 2022/09/08 20:53:47 - mmengine - INFO - Epoch(train) [49][880/1253] lr: 4.0000e-04 eta: 0:16:03 time: 0.5467 data_time: 0.0379 memory: 23504 grad_norm: 3.4686 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.7395 loss: 0.7395 2022/09/08 20:54:00 - mmengine - INFO - Epoch(train) [49][900/1253] lr: 4.0000e-04 eta: 0:15:51 time: 0.6619 data_time: 0.0675 memory: 23504 grad_norm: 3.4316 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.8088 loss: 0.8088 2022/09/08 20:54:12 - mmengine - INFO - Epoch(train) [49][920/1253] lr: 4.0000e-04 eta: 0:15:39 time: 0.5883 data_time: 0.0320 memory: 23504 grad_norm: 3.4665 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 0.7777 loss: 0.7777 2022/09/08 20:54:23 - mmengine - INFO - Epoch(train) [49][940/1253] lr: 4.0000e-04 eta: 0:15:27 time: 0.5545 data_time: 0.0383 memory: 23504 grad_norm: 3.4493 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8897 loss: 0.8897 2022/09/08 20:54:35 - mmengine - INFO - Epoch(train) [49][960/1253] lr: 4.0000e-04 eta: 0:15:15 time: 0.5645 data_time: 0.0428 memory: 23504 grad_norm: 3.4050 top1_acc: 0.7083 top5_acc: 1.0000 loss_cls: 0.7845 loss: 0.7845 2022/09/08 20:54:48 - mmengine - INFO - Epoch(train) [49][980/1253] lr: 4.0000e-04 eta: 0:15:04 time: 0.6745 data_time: 0.0369 memory: 23504 grad_norm: 3.4492 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.7956 loss: 0.7956 2022/09/08 20:55:03 - mmengine - INFO - Epoch(train) [49][1000/1253] lr: 4.0000e-04 eta: 0:14:52 time: 0.7269 data_time: 0.0381 memory: 23504 grad_norm: 3.4416 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8457 loss: 0.8457 2022/09/08 20:55:14 - mmengine - INFO - Epoch(train) [49][1020/1253] lr: 4.0000e-04 eta: 0:14:40 time: 0.5622 data_time: 0.0326 memory: 23504 grad_norm: 3.4277 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8389 loss: 0.8389 2022/09/08 20:55:27 - mmengine - INFO - Epoch(train) [49][1040/1253] lr: 4.0000e-04 eta: 0:14:28 time: 0.6773 data_time: 0.0365 memory: 23504 grad_norm: 3.4636 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.9094 loss: 0.9094 2022/09/08 20:55:39 - mmengine - INFO - Epoch(train) [49][1060/1253] lr: 4.0000e-04 eta: 0:14:16 time: 0.5604 data_time: 0.0403 memory: 23504 grad_norm: 3.4233 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8557 loss: 0.8557 2022/09/08 20:55:52 - mmengine - INFO - Epoch(train) [49][1080/1253] lr: 4.0000e-04 eta: 0:14:04 time: 0.6561 data_time: 0.0492 memory: 23504 grad_norm: 3.4226 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.9242 loss: 0.9242 2022/09/08 20:56:03 - mmengine - INFO - Epoch(train) [49][1100/1253] lr: 4.0000e-04 eta: 0:13:53 time: 0.5771 data_time: 0.0339 memory: 23504 grad_norm: 3.4147 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 0.8913 loss: 0.8913 2022/09/08 20:56:16 - mmengine - INFO - Epoch(train) [49][1120/1253] lr: 4.0000e-04 eta: 0:13:41 time: 0.6293 data_time: 0.0339 memory: 23504 grad_norm: 3.4283 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7109 loss: 0.7109 2022/09/08 20:56:27 - mmengine - INFO - Epoch(train) [49][1140/1253] lr: 4.0000e-04 eta: 0:13:29 time: 0.5601 data_time: 0.0378 memory: 23504 grad_norm: 3.4806 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 0.8248 loss: 0.8248 2022/09/08 20:56:39 - mmengine - INFO - Epoch(train) [49][1160/1253] lr: 4.0000e-04 eta: 0:13:17 time: 0.5895 data_time: 0.0430 memory: 23504 grad_norm: 3.5025 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.8742 loss: 0.8742 2022/09/08 20:56:50 - mmengine - INFO - Epoch(train) [49][1180/1253] lr: 4.0000e-04 eta: 0:13:05 time: 0.5673 data_time: 0.0452 memory: 23504 grad_norm: 3.3901 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 0.9225 loss: 0.9225 2022/09/08 20:57:01 - mmengine - INFO - Epoch(train) [49][1200/1253] lr: 4.0000e-04 eta: 0:12:53 time: 0.5575 data_time: 0.0361 memory: 23504 grad_norm: 3.3613 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.8397 loss: 0.8397 2022/09/08 20:57:14 - mmengine - INFO - Epoch(train) [49][1220/1253] lr: 4.0000e-04 eta: 0:12:41 time: 0.6156 data_time: 0.0350 memory: 23504 grad_norm: 3.4529 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8164 loss: 0.8164 2022/09/08 20:57:24 - mmengine - INFO - Epoch(train) [49][1240/1253] lr: 4.0000e-04 eta: 0:12:30 time: 0.4942 data_time: 0.0358 memory: 23504 grad_norm: 3.5438 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8938 loss: 0.8938 2022/09/08 20:57:30 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 20:57:30 - mmengine - INFO - Epoch(train) [49][1253/1253] lr: 4.0000e-04 eta: 0:12:30 time: 0.4944 data_time: 0.0186 memory: 23504 grad_norm: 3.7469 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 0.8100 loss: 0.8100 2022/09/08 20:57:57 - mmengine - INFO - Epoch(train) [50][20/1253] lr: 4.0000e-04 eta: 0:12:10 time: 1.3371 data_time: 0.8190 memory: 23504 grad_norm: 3.4625 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7746 loss: 0.7746 2022/09/08 20:58:08 - mmengine - INFO - Epoch(train) [50][40/1253] lr: 4.0000e-04 eta: 0:11:58 time: 0.5708 data_time: 0.0248 memory: 23504 grad_norm: 3.4934 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7992 loss: 0.7992 2022/09/08 20:58:22 - mmengine - INFO - Epoch(train) [50][60/1253] lr: 4.0000e-04 eta: 0:11:46 time: 0.6672 data_time: 0.0323 memory: 23504 grad_norm: 3.5346 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8873 loss: 0.8873 2022/09/08 20:58:33 - mmengine - INFO - Epoch(train) [50][80/1253] lr: 4.0000e-04 eta: 0:11:35 time: 0.5490 data_time: 0.0389 memory: 23504 grad_norm: 3.3241 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.7690 loss: 0.7690 2022/09/08 20:58:44 - mmengine - INFO - Epoch(train) [50][100/1253] lr: 4.0000e-04 eta: 0:11:23 time: 0.5541 data_time: 0.0459 memory: 23504 grad_norm: 3.4392 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 0.8244 loss: 0.8244 2022/09/08 20:58:58 - mmengine - INFO - Epoch(train) [50][120/1253] lr: 4.0000e-04 eta: 0:11:11 time: 0.7076 data_time: 0.0325 memory: 23504 grad_norm: 3.5587 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.8080 loss: 0.8080 2022/09/08 20:59:10 - mmengine - INFO - Epoch(train) [50][140/1253] lr: 4.0000e-04 eta: 0:10:59 time: 0.6261 data_time: 0.0354 memory: 23504 grad_norm: 3.4642 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8130 loss: 0.8130 2022/09/08 20:59:24 - mmengine - INFO - Epoch(train) [50][160/1253] lr: 4.0000e-04 eta: 0:10:47 time: 0.6663 data_time: 0.0317 memory: 23504 grad_norm: 3.5436 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8425 loss: 0.8425 2022/09/08 20:59:37 - mmengine - INFO - Epoch(train) [50][180/1253] lr: 4.0000e-04 eta: 0:10:35 time: 0.6661 data_time: 0.0317 memory: 23504 grad_norm: 3.5083 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 0.8130 loss: 0.8130 2022/09/08 20:59:48 - mmengine - INFO - Epoch(train) [50][200/1253] lr: 4.0000e-04 eta: 0:10:24 time: 0.5265 data_time: 0.0361 memory: 23504 grad_norm: 3.4778 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.6849 loss: 0.6849 2022/09/08 20:59:59 - mmengine - INFO - Epoch(train) [50][220/1253] lr: 4.0000e-04 eta: 0:10:12 time: 0.5891 data_time: 0.0502 memory: 23504 grad_norm: 3.4171 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8571 loss: 0.8571 2022/09/08 21:00:14 - mmengine - INFO - Epoch(train) [50][240/1253] lr: 4.0000e-04 eta: 0:10:00 time: 0.7280 data_time: 0.0403 memory: 23504 grad_norm: 3.5503 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.8750 loss: 0.8750 2022/09/08 21:00:25 - mmengine - INFO - Epoch(train) [50][260/1253] lr: 4.0000e-04 eta: 0:09:48 time: 0.5359 data_time: 0.0294 memory: 23504 grad_norm: 3.4353 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8191 loss: 0.8191 2022/09/08 21:00:37 - mmengine - INFO - Epoch(train) [50][280/1253] lr: 4.0000e-04 eta: 0:09:36 time: 0.6319 data_time: 0.0367 memory: 23504 grad_norm: 3.4441 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.7806 loss: 0.7806 2022/09/08 21:00:49 - mmengine - INFO - Epoch(train) [50][300/1253] lr: 4.0000e-04 eta: 0:09:24 time: 0.5714 data_time: 0.0365 memory: 23504 grad_norm: 3.5147 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.9184 loss: 0.9184 2022/09/08 21:01:00 - mmengine - INFO - Epoch(train) [50][320/1253] lr: 4.0000e-04 eta: 0:09:12 time: 0.5518 data_time: 0.0401 memory: 23504 grad_norm: 3.5242 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7778 loss: 0.7778 2022/09/08 21:01:11 - mmengine - INFO - Epoch(train) [50][340/1253] lr: 4.0000e-04 eta: 0:09:01 time: 0.5775 data_time: 0.0398 memory: 23504 grad_norm: 3.4286 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8775 loss: 0.8775 2022/09/08 21:01:25 - mmengine - INFO - Epoch(train) [50][360/1253] lr: 4.0000e-04 eta: 0:08:49 time: 0.6901 data_time: 0.0315 memory: 23504 grad_norm: 3.5234 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8643 loss: 0.8643 2022/09/08 21:01:37 - mmengine - INFO - Epoch(train) [50][380/1253] lr: 4.0000e-04 eta: 0:08:37 time: 0.6057 data_time: 0.0414 memory: 23504 grad_norm: 3.4398 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8402 loss: 0.8402 2022/09/08 21:01:52 - mmengine - INFO - Epoch(train) [50][400/1253] lr: 4.0000e-04 eta: 0:08:25 time: 0.7157 data_time: 0.0860 memory: 23504 grad_norm: 3.5708 top1_acc: 0.7083 top5_acc: 1.0000 loss_cls: 0.8847 loss: 0.8847 2022/09/08 21:02:02 - mmengine - INFO - Epoch(train) [50][420/1253] lr: 4.0000e-04 eta: 0:08:13 time: 0.5408 data_time: 0.0271 memory: 23504 grad_norm: 3.4636 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8056 loss: 0.8056 2022/09/08 21:02:14 - mmengine - INFO - Epoch(train) [50][440/1253] lr: 4.0000e-04 eta: 0:08:01 time: 0.5631 data_time: 0.0356 memory: 23504 grad_norm: 3.4638 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 0.8401 loss: 0.8401 2022/09/08 21:02:26 - mmengine - INFO - Epoch(train) [50][460/1253] lr: 4.0000e-04 eta: 0:07:49 time: 0.6316 data_time: 0.0603 memory: 23504 grad_norm: 3.4796 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.7614 loss: 0.7614 2022/09/08 21:02:39 - mmengine - INFO - Epoch(train) [50][480/1253] lr: 4.0000e-04 eta: 0:07:38 time: 0.6516 data_time: 0.0402 memory: 23504 grad_norm: 3.4564 top1_acc: 0.9167 top5_acc: 1.0000 loss_cls: 0.7925 loss: 0.7925 2022/09/08 21:02:54 - mmengine - INFO - Epoch(train) [50][500/1253] lr: 4.0000e-04 eta: 0:07:26 time: 0.7122 data_time: 0.0289 memory: 23504 grad_norm: 3.4511 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8061 loss: 0.8061 2022/09/08 21:03:04 - mmengine - INFO - Epoch(train) [50][520/1253] lr: 4.0000e-04 eta: 0:07:14 time: 0.5305 data_time: 0.0344 memory: 23504 grad_norm: 3.4248 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7405 loss: 0.7405 2022/09/08 21:03:18 - mmengine - INFO - Epoch(train) [50][540/1253] lr: 4.0000e-04 eta: 0:07:02 time: 0.7057 data_time: 0.0458 memory: 23504 grad_norm: 3.5013 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8409 loss: 0.8409 2022/09/08 21:03:30 - mmengine - INFO - Epoch(train) [50][560/1253] lr: 4.0000e-04 eta: 0:06:50 time: 0.5690 data_time: 0.0332 memory: 23504 grad_norm: 3.5036 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.8061 loss: 0.8061 2022/09/08 21:03:44 - mmengine - INFO - Epoch(train) [50][580/1253] lr: 4.0000e-04 eta: 0:06:38 time: 0.6996 data_time: 0.0392 memory: 23504 grad_norm: 3.4599 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 0.7898 loss: 0.7898 2022/09/08 21:03:55 - mmengine - INFO - Epoch(train) [50][600/1253] lr: 4.0000e-04 eta: 0:06:27 time: 0.5496 data_time: 0.0371 memory: 23504 grad_norm: 3.3798 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 0.8045 loss: 0.8045 2022/09/08 21:03:56 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 21:04:06 - mmengine - INFO - Epoch(train) [50][620/1253] lr: 4.0000e-04 eta: 0:06:15 time: 0.5729 data_time: 0.0383 memory: 23504 grad_norm: 3.3866 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.7944 loss: 0.7944 2022/09/08 21:04:18 - mmengine - INFO - Epoch(train) [50][640/1253] lr: 4.0000e-04 eta: 0:06:03 time: 0.5626 data_time: 0.0389 memory: 23504 grad_norm: 3.4826 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.8432 loss: 0.8432 2022/09/08 21:04:32 - mmengine - INFO - Epoch(train) [50][660/1253] lr: 4.0000e-04 eta: 0:05:51 time: 0.7018 data_time: 0.0355 memory: 23504 grad_norm: 3.4863 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.7812 loss: 0.7812 2022/09/08 21:04:43 - mmengine - INFO - Epoch(train) [50][680/1253] lr: 4.0000e-04 eta: 0:05:39 time: 0.5622 data_time: 0.0450 memory: 23504 grad_norm: 3.4369 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 0.7045 loss: 0.7045 2022/09/08 21:04:54 - mmengine - INFO - Epoch(train) [50][700/1253] lr: 4.0000e-04 eta: 0:05:27 time: 0.5567 data_time: 0.0293 memory: 23504 grad_norm: 3.5221 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.7900 loss: 0.7900 2022/09/08 21:05:05 - mmengine - INFO - Epoch(train) [50][720/1253] lr: 4.0000e-04 eta: 0:05:15 time: 0.5488 data_time: 0.0375 memory: 23504 grad_norm: 3.4254 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.8548 loss: 0.8548 2022/09/08 21:05:17 - mmengine - INFO - Epoch(train) [50][740/1253] lr: 4.0000e-04 eta: 0:05:04 time: 0.6197 data_time: 0.1054 memory: 23504 grad_norm: 3.4192 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.8729 loss: 0.8729 2022/09/08 21:05:29 - mmengine - INFO - Epoch(train) [50][760/1253] lr: 4.0000e-04 eta: 0:04:52 time: 0.5709 data_time: 0.0390 memory: 23504 grad_norm: 3.3991 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.8745 loss: 0.8745 2022/09/08 21:05:40 - mmengine - INFO - Epoch(train) [50][780/1253] lr: 4.0000e-04 eta: 0:04:40 time: 0.5808 data_time: 0.0363 memory: 23504 grad_norm: 3.4105 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 0.7342 loss: 0.7342 2022/09/08 21:05:54 - mmengine - INFO - Epoch(train) [50][800/1253] lr: 4.0000e-04 eta: 0:04:28 time: 0.6723 data_time: 0.0391 memory: 23504 grad_norm: 3.4453 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 0.7027 loss: 0.7027 2022/09/08 21:06:08 - mmengine - INFO - Epoch(train) [50][820/1253] lr: 4.0000e-04 eta: 0:04:16 time: 0.7326 data_time: 0.1247 memory: 23504 grad_norm: 3.5193 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 0.7953 loss: 0.7953 2022/09/08 21:06:19 - mmengine - INFO - Epoch(train) [50][840/1253] lr: 4.0000e-04 eta: 0:04:04 time: 0.5476 data_time: 0.0257 memory: 23504 grad_norm: 3.5503 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 0.7479 loss: 0.7479 2022/09/08 21:06:31 - mmengine - INFO - Epoch(train) [50][860/1253] lr: 4.0000e-04 eta: 0:03:52 time: 0.5784 data_time: 0.0309 memory: 23504 grad_norm: 3.3240 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.8466 loss: 0.8466 2022/09/08 21:06:43 - mmengine - INFO - Epoch(train) [50][880/1253] lr: 4.0000e-04 eta: 0:03:41 time: 0.5794 data_time: 0.0529 memory: 23504 grad_norm: 3.3394 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.8792 loss: 0.8792 2022/09/08 21:06:56 - mmengine - INFO - Epoch(train) [50][900/1253] lr: 4.0000e-04 eta: 0:03:29 time: 0.6920 data_time: 0.0354 memory: 23504 grad_norm: 3.3528 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.7787 loss: 0.7787 2022/09/08 21:07:08 - mmengine - INFO - Epoch(train) [50][920/1253] lr: 4.0000e-04 eta: 0:03:17 time: 0.5676 data_time: 0.0508 memory: 23504 grad_norm: 3.4227 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 0.7316 loss: 0.7316 2022/09/08 21:07:21 - mmengine - INFO - Epoch(train) [50][940/1253] lr: 4.0000e-04 eta: 0:03:05 time: 0.6726 data_time: 0.0358 memory: 23504 grad_norm: 3.4323 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 0.8064 loss: 0.8064 2022/09/08 21:07:32 - mmengine - INFO - Epoch(train) [50][960/1253] lr: 4.0000e-04 eta: 0:02:53 time: 0.5560 data_time: 0.0369 memory: 23504 grad_norm: 3.3725 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.7926 loss: 0.7926 2022/09/08 21:07:47 - mmengine - INFO - Epoch(train) [50][980/1253] lr: 4.0000e-04 eta: 0:02:41 time: 0.7275 data_time: 0.1848 memory: 23504 grad_norm: 3.3789 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 0.6868 loss: 0.6868 2022/09/08 21:07:58 - mmengine - INFO - Epoch(train) [50][1000/1253] lr: 4.0000e-04 eta: 0:02:29 time: 0.5372 data_time: 0.0275 memory: 23504 grad_norm: 3.4861 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 0.7907 loss: 0.7907 2022/09/08 21:08:09 - mmengine - INFO - Epoch(train) [50][1020/1253] lr: 4.0000e-04 eta: 0:02:18 time: 0.5662 data_time: 0.0301 memory: 23504 grad_norm: 3.4542 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8931 loss: 0.8931 2022/09/08 21:08:20 - mmengine - INFO - Epoch(train) [50][1040/1253] lr: 4.0000e-04 eta: 0:02:06 time: 0.5517 data_time: 0.0427 memory: 23504 grad_norm: 3.4385 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 0.8147 loss: 0.8147 2022/09/08 21:08:32 - mmengine - INFO - Epoch(train) [50][1060/1253] lr: 4.0000e-04 eta: 0:01:54 time: 0.5727 data_time: 0.0370 memory: 23504 grad_norm: 3.4333 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 0.7685 loss: 0.7685 2022/09/08 21:08:43 - mmengine - INFO - Epoch(train) [50][1080/1253] lr: 4.0000e-04 eta: 0:01:42 time: 0.5901 data_time: 0.0375 memory: 23504 grad_norm: 3.4661 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 0.8161 loss: 0.8161 2022/09/08 21:08:59 - mmengine - INFO - Epoch(train) [50][1100/1253] lr: 4.0000e-04 eta: 0:01:30 time: 0.7781 data_time: 0.0323 memory: 23504 grad_norm: 3.4755 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.8509 loss: 0.8509 2022/09/08 21:09:10 - mmengine - INFO - Epoch(train) [50][1120/1253] lr: 4.0000e-04 eta: 0:01:18 time: 0.5446 data_time: 0.0345 memory: 23504 grad_norm: 3.5031 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 0.9226 loss: 0.9226 2022/09/08 21:09:24 - mmengine - INFO - Epoch(train) [50][1140/1253] lr: 4.0000e-04 eta: 0:01:06 time: 0.7089 data_time: 0.0340 memory: 23504 grad_norm: 3.4862 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 0.7216 loss: 0.7216 2022/09/08 21:09:35 - mmengine - INFO - Epoch(train) [50][1160/1253] lr: 4.0000e-04 eta: 0:00:55 time: 0.5449 data_time: 0.0387 memory: 23504 grad_norm: 3.5069 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 0.8175 loss: 0.8175 2022/09/08 21:09:46 - mmengine - INFO - Epoch(train) [50][1180/1253] lr: 4.0000e-04 eta: 0:00:43 time: 0.5620 data_time: 0.0350 memory: 23504 grad_norm: 3.4038 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.7609 loss: 0.7609 2022/09/08 21:09:58 - mmengine - INFO - Epoch(train) [50][1200/1253] lr: 4.0000e-04 eta: 0:00:31 time: 0.5859 data_time: 0.0372 memory: 23504 grad_norm: 3.4625 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 0.7912 loss: 0.7912 2022/09/08 21:10:09 - mmengine - INFO - Epoch(train) [50][1220/1253] lr: 4.0000e-04 eta: 0:00:19 time: 0.5398 data_time: 0.0375 memory: 23504 grad_norm: 3.3599 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 0.7347 loss: 0.7347 2022/09/08 21:10:21 - mmengine - INFO - Epoch(train) [50][1240/1253] lr: 4.0000e-04 eta: 0:00:07 time: 0.6070 data_time: 0.0507 memory: 23504 grad_norm: 3.5824 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 0.7863 loss: 0.7863 2022/09/08 21:10:27 - mmengine - INFO - Exp name: tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb_20220908_103421 2022/09/08 21:10:27 - mmengine - INFO - Epoch(train) [50][1253/1253] lr: 4.0000e-04 eta: 0:00:07 time: 0.4632 data_time: 0.0338 memory: 23504 grad_norm: 3.7473 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 0.8860 loss: 0.8860 2022/09/08 21:10:27 - mmengine - INFO - Saving checkpoint at 50 epochs 2022/09/08 21:11:03 - mmengine - INFO - Epoch(val) [50][20/104] eta: 0:02:18 time: 1.6543 data_time: 1.5256 memory: 2699 2022/09/08 21:11:15 - mmengine - INFO - Epoch(val) [50][40/104] eta: 0:00:38 time: 0.6078 data_time: 0.4746 memory: 2699 2022/09/08 21:11:24 - mmengine - INFO - Epoch(val) [50][60/104] eta: 0:00:19 time: 0.4386 data_time: 0.3085 memory: 2699 2022/09/08 21:11:38 - mmengine - INFO - Epoch(val) [50][80/104] eta: 0:00:16 time: 0.6772 data_time: 0.5578 memory: 2699 2022/09/08 21:11:47 - mmengine - INFO - Epoch(val) [50][100/104] eta: 0:00:01 time: 0.4808 data_time: 0.3636 memory: 2699 2022/09/08 21:11:49 - mmengine - INFO - Epoch(val) [50][104/104] acc/top1: 0.7177 acc/top5: 0.9036 acc/mean1: 0.7176 2022/09/08 21:11:49 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_kinetics400-pretrained-tsm-r50_1x1x8-50e_kinetics400-rgb/best_acc/top1_epoch_45.pth is removed 2022/09/08 21:11:51 - mmengine - INFO - The best checkpoint with 0.7177 acc/top1 at 50 epoch is saved to best_acc/top1_epoch_50.pth.