2022/09/11 16:56:58 - 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: 1015203268 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 ------------------------------------------------------------ 2022/09/11 16:56:58 - mmengine - INFO - Config: model = dict( type='Recognizer3D', backbone=dict( type='ResNet3dSlowOnly', depth=50, pretrained=None, lateral=False, out_indices=(2, 3), conv1_kernel=(1, 7, 7), conv1_stride_t=1, pool1_stride_t=1, inflate=(0, 0, 1, 1), norm_eval=False), neck=dict( type='TPN', in_channels=(1024, 2048), out_channels=1024, spatial_modulation_cfg=dict( in_channels=(1024, 2048), out_channels=2048), temporal_modulation_cfg=dict(downsample_scales=(8, 8)), upsample_cfg=dict(scale_factor=(1, 1, 1)), downsample_cfg=dict(downsample_scale=(1, 1, 1)), level_fusion_cfg=dict( in_channels=(1024, 1024), mid_channels=(1024, 1024), out_channels=2048, downsample_scales=((1, 1, 1), (1, 1, 1))), aux_head_cfg=dict(out_channels=400, loss_weight=0.5)), cls_head=dict( type='TPNHead', num_classes=400, in_channels=2048, spatial_type='avg', consensus=dict(type='AvgConsensus', dim=1), dropout_ratio=0.5, init_std=0.01, average_clips='prob'), data_preprocessor=dict( type='ActionDataPreprocessor', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], format_shape='NCTHW'), train_cfg=None, test_cfg=dict(fcn_test=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, max_keep_ckpts=5, 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 = None resume = True 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=8, frame_interval=8, num_clips=1), dict(type='DecordDecode'), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='ColorJitter'), dict(type='FormatShape', input_format='NCTHW'), 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=8, frame_interval=8, num_clips=1, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='ColorJitter'), dict(type='FormatShape', input_format='NCTHW'), 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=8, frame_interval=8, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ] train_dataloader = dict( batch_size=32, 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=8, frame_interval=8, num_clips=1), dict(type='DecordDecode'), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='ColorJitter'), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ])) val_dataloader = dict( batch_size=8, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='VideoDataset', ann_file='data/kinetics400/kinetics400_val_list_videos.txt', data_prefix=dict(video='data/kinetics400/videos_val'), pipeline=[ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/kinetics400': 's254:s3://openmmlab/datasets/action/Kinetics400' })), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='ColorJitter'), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True)) test_dataloader = dict( batch_size=1, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='VideoDataset', ann_file='data/kinetics400/kinetics400_val_list_videos.txt', data_prefix=dict(video='data/kinetics400/videos_val'), pipeline=[ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/kinetics400': 's254:s3://openmmlab/datasets/action/Kinetics400' })), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True)) val_evaluator = dict(type='AccMetric') test_evaluator = dict(type='AccMetric') train_cfg = dict( type='EpochBasedTrainLoop', max_epochs=150, val_begin=1, val_interval=10) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') optim_wrapper = dict( optimizer=dict( type='SGD', lr=0.04, momentum=0.9, weight_decay=0.0001, nesterov=True), clip_grad=dict(max_norm=40, norm_type=2)) param_scheduler = [ dict( type='MultiStepLR', begin=0, end=150, by_epoch=True, milestones=[75, 125], gamma=0.1) ] launcher = 'slurm' work_dir = './work_dirs/tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb' 2022/09/11 16:57:01 - mmengine - INFO - Auto resumed from the latest checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb/epoch_112.pth. 2022/09/11 16:57:07 - mmengine - INFO - Load checkpoint from /mnt/cache/lilin/Repos/mmaction2/work_dirs/tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb/epoch_112.pth 2022/09/11 16:57:07 - mmengine - INFO - resumed epoch: 112, iter: 105280 2022/09/11 16:57:07 - mmengine - INFO - Checkpoints will be saved to /mnt/cache/lilin/Repos/mmaction2/work_dirs/tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb by HardDiskBackend. 2022/09/11 16:58:58 - mmengine - INFO - Epoch(train) [113][20/940] lr: 4.0000e-03 eta: 2 days, 7:21:52 time: 5.5830 data_time: 4.3873 memory: 23705 grad_norm: 4.8598 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4600 loss_aux: 0.9199 loss: 2.3799 2022/09/11 16:59:16 - mmengine - INFO - Epoch(train) [113][40/940] lr: 4.0000e-03 eta: 1 day, 8:08:48 time: 0.9040 data_time: 0.1799 memory: 23705 grad_norm: 4.8397 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6116 loss_aux: 1.0094 loss: 2.6210 2022/09/11 16:59:35 - mmengine - INFO - Epoch(train) [113][60/940] lr: 4.0000e-03 eta: 1 day, 0:30:05 time: 0.9335 data_time: 0.1240 memory: 23705 grad_norm: 4.8134 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.5713 loss_aux: 1.0028 loss: 2.5741 2022/09/11 16:59:53 - mmengine - INFO - Epoch(train) [113][80/940] lr: 4.0000e-03 eta: 20:30:54 time: 0.8683 data_time: 0.2017 memory: 23705 grad_norm: 4.8652 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.6108 loss_aux: 1.0420 loss: 2.6528 2022/09/11 17:00:16 - mmengine - INFO - Epoch(train) [113][100/940] lr: 4.0000e-03 eta: 18:44:26 time: 1.1814 data_time: 0.5232 memory: 23705 grad_norm: 4.8317 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.5918 loss_aux: 0.9887 loss: 2.5805 2022/09/11 17:00:31 - mmengine - INFO - Epoch(train) [113][120/940] lr: 4.0000e-03 eta: 16:47:43 time: 0.7202 data_time: 0.0652 memory: 23705 grad_norm: 4.8540 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4577 loss_aux: 0.9211 loss: 2.3788 2022/09/11 17:00:45 - mmengine - INFO - Epoch(train) [113][140/940] lr: 4.0000e-03 eta: 15:22:21 time: 0.6973 data_time: 0.0325 memory: 23705 grad_norm: 4.8849 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.7051 loss_aux: 1.0800 loss: 2.7851 2022/09/11 17:00:59 - mmengine - INFO - Epoch(train) [113][160/940] lr: 4.0000e-03 eta: 14:18:52 time: 0.7055 data_time: 0.0315 memory: 23705 grad_norm: 4.8639 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4523 loss_aux: 0.9239 loss: 2.3762 2022/09/11 17:01:13 - mmengine - INFO - Epoch(train) [113][180/940] lr: 4.0000e-03 eta: 13:29:30 time: 0.7064 data_time: 0.0299 memory: 23705 grad_norm: 4.8881 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.7159 loss_aux: 1.0840 loss: 2.7998 2022/09/11 17:01:27 - mmengine - INFO - Epoch(train) [113][200/940] lr: 4.0000e-03 eta: 12:49:27 time: 0.6978 data_time: 0.0475 memory: 23705 grad_norm: 4.8191 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5702 loss_aux: 0.9904 loss: 2.5606 2022/09/11 17:01:41 - mmengine - INFO - Epoch(train) [113][220/940] lr: 4.0000e-03 eta: 12:17:09 time: 0.7073 data_time: 0.0425 memory: 23705 grad_norm: 4.7906 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5758 loss_aux: 0.9735 loss: 2.5493 2022/09/11 17:01:58 - mmengine - INFO - Epoch(train) [113][240/940] lr: 4.0000e-03 eta: 11:57:34 time: 0.8570 data_time: 0.0346 memory: 23705 grad_norm: 4.8292 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5778 loss_aux: 1.0041 loss: 2.5819 2022/09/11 17:02:12 - mmengine - INFO - Epoch(train) [113][260/940] lr: 4.0000e-03 eta: 11:33:57 time: 0.7029 data_time: 0.0397 memory: 23705 grad_norm: 4.8778 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6328 loss_aux: 1.0389 loss: 2.6717 2022/09/11 17:02:26 - mmengine - INFO - Epoch(train) [113][280/940] lr: 4.0000e-03 eta: 11:13:26 time: 0.6972 data_time: 0.0322 memory: 23705 grad_norm: 4.8445 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4205 loss_aux: 0.9321 loss: 2.3526 2022/09/11 17:02:40 - mmengine - INFO - Epoch(train) [113][300/940] lr: 4.0000e-03 eta: 10:56:05 time: 0.7088 data_time: 0.0343 memory: 23705 grad_norm: 4.7627 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.6390 loss_aux: 1.0278 loss: 2.6668 2022/09/11 17:02:54 - mmengine - INFO - Epoch(train) [113][320/940] lr: 4.0000e-03 eta: 10:40:36 time: 0.7017 data_time: 0.0387 memory: 23705 grad_norm: 4.8098 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.5158 loss_aux: 0.9789 loss: 2.4947 2022/09/11 17:03:08 - mmengine - INFO - Epoch(train) [113][340/940] lr: 4.0000e-03 eta: 10:26:25 time: 0.6874 data_time: 0.0366 memory: 23705 grad_norm: 4.8619 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6099 loss_aux: 1.0501 loss: 2.6600 2022/09/11 17:03:22 - mmengine - INFO - Epoch(train) [113][360/940] lr: 4.0000e-03 eta: 10:13:51 time: 0.6891 data_time: 0.0462 memory: 23705 grad_norm: 4.9757 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.5435 loss_aux: 0.9956 loss: 2.5391 2022/09/11 17:03:35 - mmengine - INFO - Epoch(train) [113][380/940] lr: 4.0000e-03 eta: 10:02:09 time: 0.6758 data_time: 0.0325 memory: 23705 grad_norm: 4.8939 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4793 loss_aux: 0.9531 loss: 2.4324 2022/09/11 17:03:49 - mmengine - INFO - Epoch(train) [113][400/940] lr: 4.0000e-03 eta: 9:51:53 time: 0.6850 data_time: 0.0439 memory: 23705 grad_norm: 4.8623 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4779 loss_aux: 0.9675 loss: 2.4454 2022/09/11 17:04:03 - mmengine - INFO - Epoch(train) [113][420/940] lr: 4.0000e-03 eta: 9:43:06 time: 0.7037 data_time: 0.0360 memory: 23705 grad_norm: 4.8597 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5519 loss_aux: 0.9741 loss: 2.5260 2022/09/11 17:04:17 - mmengine - INFO - Epoch(train) [113][440/940] lr: 4.0000e-03 eta: 9:34:47 time: 0.6923 data_time: 0.0331 memory: 23705 grad_norm: 4.8772 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.5958 loss_aux: 0.9849 loss: 2.5806 2022/09/11 17:04:31 - mmengine - INFO - Epoch(train) [113][460/940] lr: 4.0000e-03 eta: 9:27:47 time: 0.7165 data_time: 0.0366 memory: 23705 grad_norm: 4.9137 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6098 loss_aux: 1.0353 loss: 2.6451 2022/09/11 17:04:45 - mmengine - INFO - Epoch(train) [113][480/940] lr: 4.0000e-03 eta: 9:21:09 time: 0.7084 data_time: 0.0403 memory: 23705 grad_norm: 4.7908 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5613 loss_aux: 0.9969 loss: 2.5582 2022/09/11 17:05:02 - mmengine - INFO - Epoch(train) [113][500/940] lr: 4.0000e-03 eta: 9:18:16 time: 0.8462 data_time: 0.0353 memory: 23705 grad_norm: 4.9127 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4970 loss_aux: 0.9379 loss: 2.4349 2022/09/11 17:05:16 - mmengine - INFO - Epoch(train) [113][520/940] lr: 4.0000e-03 eta: 9:11:50 time: 0.6799 data_time: 0.0334 memory: 23705 grad_norm: 4.8560 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6939 loss_aux: 1.0791 loss: 2.7730 2022/09/11 17:05:30 - mmengine - INFO - Epoch(train) [113][540/940] lr: 4.0000e-03 eta: 9:06:15 time: 0.6982 data_time: 0.0378 memory: 23705 grad_norm: 4.7133 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4878 loss_aux: 0.9595 loss: 2.4473 2022/09/11 17:05:44 - mmengine - INFO - Epoch(train) [113][560/940] lr: 4.0000e-03 eta: 9:00:58 time: 0.6935 data_time: 0.0456 memory: 23705 grad_norm: 4.8149 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4694 loss_aux: 0.9713 loss: 2.4408 2022/09/11 17:05:58 - mmengine - INFO - Epoch(train) [113][580/940] lr: 4.0000e-03 eta: 8:56:08 time: 0.6991 data_time: 0.0335 memory: 23705 grad_norm: 4.9019 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4635 loss_aux: 0.9467 loss: 2.4102 2022/09/11 17:06:12 - mmengine - INFO - Epoch(train) [113][600/940] lr: 4.0000e-03 eta: 8:51:30 time: 0.6942 data_time: 0.0379 memory: 23705 grad_norm: 4.8407 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5215 loss_aux: 0.9542 loss: 2.4757 2022/09/11 17:06:26 - mmengine - INFO - Epoch(train) [113][620/940] lr: 4.0000e-03 eta: 8:47:15 time: 0.6986 data_time: 0.0381 memory: 23705 grad_norm: 4.8657 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3362 loss_aux: 0.8847 loss: 2.2209 2022/09/11 17:06:40 - mmengine - INFO - Epoch(train) [113][640/940] lr: 4.0000e-03 eta: 8:43:11 time: 0.6953 data_time: 0.0427 memory: 23705 grad_norm: 4.8272 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5349 loss_aux: 0.9606 loss: 2.4956 2022/09/11 17:06:53 - mmengine - INFO - Epoch(train) [113][660/940] lr: 4.0000e-03 eta: 8:39:05 time: 0.6795 data_time: 0.0354 memory: 23705 grad_norm: 4.9212 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.5737 loss_aux: 0.9937 loss: 2.5675 2022/09/11 17:07:07 - mmengine - INFO - Epoch(train) [113][680/940] lr: 4.0000e-03 eta: 8:35:31 time: 0.6987 data_time: 0.0405 memory: 23705 grad_norm: 4.9244 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4906 loss_aux: 0.9818 loss: 2.4724 2022/09/11 17:07:21 - mmengine - INFO - Epoch(train) [113][700/940] lr: 4.0000e-03 eta: 8:31:54 time: 0.6833 data_time: 0.0370 memory: 23705 grad_norm: 4.9269 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6789 loss_aux: 1.0398 loss: 2.7187 2022/09/11 17:07:36 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 17:07:36 - mmengine - INFO - Epoch(train) [113][720/940] lr: 4.0000e-03 eta: 8:29:26 time: 0.7427 data_time: 0.0401 memory: 23705 grad_norm: 4.9110 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5943 loss_aux: 1.0405 loss: 2.6348 2022/09/11 17:07:49 - mmengine - INFO - Epoch(train) [113][740/940] lr: 4.0000e-03 eta: 8:26:14 time: 0.6891 data_time: 0.0359 memory: 23705 grad_norm: 4.8395 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3780 loss_aux: 0.8983 loss: 2.2762 2022/09/11 17:08:03 - mmengine - INFO - Epoch(train) [113][760/940] lr: 4.0000e-03 eta: 8:23:12 time: 0.6892 data_time: 0.0477 memory: 23705 grad_norm: 4.8332 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.4977 loss_aux: 0.9580 loss: 2.4556 2022/09/11 17:08:17 - mmengine - INFO - Epoch(train) [113][780/940] lr: 4.0000e-03 eta: 8:20:10 time: 0.6798 data_time: 0.0351 memory: 23705 grad_norm: 4.9476 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5041 loss_aux: 0.9623 loss: 2.4664 2022/09/11 17:08:31 - mmengine - INFO - Epoch(train) [113][800/940] lr: 4.0000e-03 eta: 8:17:28 time: 0.6923 data_time: 0.0350 memory: 23705 grad_norm: 4.9279 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.6035 loss_aux: 1.0102 loss: 2.6138 2022/09/11 17:08:44 - mmengine - INFO - Epoch(train) [113][820/940] lr: 4.0000e-03 eta: 8:14:47 time: 0.6859 data_time: 0.0375 memory: 23705 grad_norm: 4.9537 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5374 loss_aux: 0.9532 loss: 2.4907 2022/09/11 17:08:58 - mmengine - INFO - Epoch(train) [113][840/940] lr: 4.0000e-03 eta: 8:12:23 time: 0.6982 data_time: 0.0407 memory: 23705 grad_norm: 4.8443 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5288 loss_aux: 0.9696 loss: 2.4984 2022/09/11 17:09:12 - mmengine - INFO - Epoch(train) [113][860/940] lr: 4.0000e-03 eta: 8:10:02 time: 0.6938 data_time: 0.0439 memory: 23705 grad_norm: 4.9101 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4098 loss_aux: 0.8893 loss: 2.2991 2022/09/11 17:09:26 - mmengine - INFO - Epoch(train) [113][880/940] lr: 4.0000e-03 eta: 8:07:51 time: 0.6993 data_time: 0.0410 memory: 23705 grad_norm: 4.8842 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5173 loss_aux: 1.0020 loss: 2.5194 2022/09/11 17:09:40 - mmengine - INFO - Epoch(train) [113][900/940] lr: 4.0000e-03 eta: 8:05:48 time: 0.7036 data_time: 0.0388 memory: 23705 grad_norm: 4.9116 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5817 loss_aux: 0.9816 loss: 2.5633 2022/09/11 17:09:54 - mmengine - INFO - Epoch(train) [113][920/940] lr: 4.0000e-03 eta: 8:03:47 time: 0.6988 data_time: 0.0401 memory: 23705 grad_norm: 4.8983 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4925 loss_aux: 0.9482 loss: 2.4407 2022/09/11 17:10:07 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 17:10:07 - mmengine - INFO - Epoch(train) [113][940/940] lr: 4.0000e-03 eta: 8:01:09 time: 0.6427 data_time: 0.0301 memory: 23705 grad_norm: 5.0941 top1_acc: 0.4286 top5_acc: 0.5714 loss_cls: 1.6081 loss_aux: 1.0285 loss: 2.6366 2022/09/11 17:10:07 - mmengine - INFO - Saving checkpoint at 113 epochs 2022/09/11 17:10:32 - mmengine - INFO - Epoch(train) [114][20/940] lr: 4.0000e-03 eta: 8:02:10 time: 0.9370 data_time: 0.2932 memory: 23705 grad_norm: 4.8500 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4836 loss_aux: 0.9431 loss: 2.4267 2022/09/11 17:10:46 - mmengine - INFO - Epoch(train) [114][40/940] lr: 4.0000e-03 eta: 8:00:03 time: 0.6766 data_time: 0.0278 memory: 23705 grad_norm: 4.8347 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5969 loss_aux: 0.9882 loss: 2.5851 2022/09/11 17:10:59 - mmengine - INFO - Epoch(train) [114][60/940] lr: 4.0000e-03 eta: 7:57:56 time: 0.6706 data_time: 0.0308 memory: 23705 grad_norm: 4.8843 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5690 loss_aux: 1.0005 loss: 2.5695 2022/09/11 17:11:13 - mmengine - INFO - Epoch(train) [114][80/940] lr: 4.0000e-03 eta: 7:56:01 time: 0.6813 data_time: 0.0404 memory: 23705 grad_norm: 4.8184 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4644 loss_aux: 0.9420 loss: 2.4064 2022/09/11 17:11:27 - mmengine - INFO - Epoch(train) [114][100/940] lr: 4.0000e-03 eta: 7:54:23 time: 0.7015 data_time: 0.0400 memory: 23705 grad_norm: 4.8263 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4542 loss_aux: 0.9330 loss: 2.3872 2022/09/11 17:11:41 - mmengine - INFO - Epoch(train) [114][120/940] lr: 4.0000e-03 eta: 7:52:28 time: 0.6691 data_time: 0.0317 memory: 23705 grad_norm: 4.8444 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6883 loss_aux: 1.0639 loss: 2.7522 2022/09/11 17:11:54 - mmengine - INFO - Epoch(train) [114][140/940] lr: 4.0000e-03 eta: 7:50:35 time: 0.6681 data_time: 0.0317 memory: 23705 grad_norm: 4.8338 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5060 loss_aux: 0.9541 loss: 2.4600 2022/09/11 17:12:07 - mmengine - INFO - Epoch(train) [114][160/940] lr: 4.0000e-03 eta: 7:48:45 time: 0.6653 data_time: 0.0345 memory: 23705 grad_norm: 4.8434 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4445 loss_aux: 0.9339 loss: 2.3785 2022/09/11 17:12:21 - mmengine - INFO - Epoch(train) [114][180/940] lr: 4.0000e-03 eta: 7:47:04 time: 0.6760 data_time: 0.0400 memory: 23705 grad_norm: 4.8281 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5529 loss_aux: 1.0069 loss: 2.5598 2022/09/11 17:12:34 - mmengine - INFO - Epoch(train) [114][200/940] lr: 4.0000e-03 eta: 7:45:23 time: 0.6692 data_time: 0.0321 memory: 23705 grad_norm: 4.8152 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6357 loss_aux: 1.0206 loss: 2.6563 2022/09/11 17:12:48 - mmengine - INFO - Epoch(train) [114][220/940] lr: 4.0000e-03 eta: 7:43:46 time: 0.6718 data_time: 0.0385 memory: 23705 grad_norm: 4.8043 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.5166 loss_aux: 1.0040 loss: 2.5205 2022/09/11 17:13:01 - mmengine - INFO - Epoch(train) [114][240/940] lr: 4.0000e-03 eta: 7:42:20 time: 0.6869 data_time: 0.0347 memory: 23705 grad_norm: 4.9374 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5113 loss_aux: 0.9418 loss: 2.4532 2022/09/11 17:13:18 - mmengine - INFO - Epoch(train) [114][260/940] lr: 4.0000e-03 eta: 7:42:11 time: 0.8144 data_time: 0.0479 memory: 23705 grad_norm: 4.8810 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4707 loss_aux: 0.9464 loss: 2.4171 2022/09/11 17:13:31 - mmengine - INFO - Epoch(train) [114][280/940] lr: 4.0000e-03 eta: 7:40:48 time: 0.6847 data_time: 0.0304 memory: 23705 grad_norm: 4.8752 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4813 loss_aux: 0.9497 loss: 2.4310 2022/09/11 17:13:45 - mmengine - INFO - Epoch(train) [114][300/940] lr: 4.0000e-03 eta: 7:39:20 time: 0.6720 data_time: 0.0313 memory: 23705 grad_norm: 4.8985 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4163 loss_aux: 0.9256 loss: 2.3419 2022/09/11 17:13:58 - mmengine - INFO - Epoch(train) [114][320/940] lr: 4.0000e-03 eta: 7:37:54 time: 0.6730 data_time: 0.0339 memory: 23705 grad_norm: 4.9849 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4769 loss_aux: 0.9683 loss: 2.4452 2022/09/11 17:14:12 - mmengine - INFO - Epoch(train) [114][340/940] lr: 4.0000e-03 eta: 7:36:45 time: 0.6973 data_time: 0.0436 memory: 23705 grad_norm: 4.9040 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.6050 loss_aux: 1.0092 loss: 2.6142 2022/09/11 17:14:26 - mmengine - INFO - Epoch(train) [114][360/940] lr: 4.0000e-03 eta: 7:35:26 time: 0.6775 data_time: 0.0303 memory: 23705 grad_norm: 4.8934 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.6133 loss_aux: 1.0460 loss: 2.6593 2022/09/11 17:14:39 - mmengine - INFO - Epoch(train) [114][380/940] lr: 4.0000e-03 eta: 7:34:11 time: 0.6798 data_time: 0.0355 memory: 23705 grad_norm: 4.9368 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.6163 loss_aux: 1.0383 loss: 2.6546 2022/09/11 17:14:53 - mmengine - INFO - Epoch(train) [114][400/940] lr: 4.0000e-03 eta: 7:33:08 time: 0.7004 data_time: 0.0350 memory: 23705 grad_norm: 4.8362 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3327 loss_aux: 0.8580 loss: 2.1908 2022/09/11 17:15:07 - mmengine - INFO - Epoch(train) [114][420/940] lr: 4.0000e-03 eta: 7:32:04 time: 0.6956 data_time: 0.0469 memory: 23705 grad_norm: 4.8844 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.6268 loss_aux: 1.0391 loss: 2.6659 2022/09/11 17:15:21 - mmengine - INFO - Epoch(train) [114][440/940] lr: 4.0000e-03 eta: 7:31:04 time: 0.7016 data_time: 0.0282 memory: 23705 grad_norm: 4.8310 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6339 loss_aux: 0.9934 loss: 2.6273 2022/09/11 17:15:35 - mmengine - INFO - Epoch(train) [114][460/940] lr: 4.0000e-03 eta: 7:29:58 time: 0.6844 data_time: 0.0316 memory: 23705 grad_norm: 4.9314 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.6473 loss_aux: 1.0447 loss: 2.6921 2022/09/11 17:15:49 - mmengine - INFO - Epoch(train) [114][480/940] lr: 4.0000e-03 eta: 7:28:57 time: 0.6924 data_time: 0.0349 memory: 23705 grad_norm: 4.8451 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5942 loss_aux: 0.9833 loss: 2.5775 2022/09/11 17:16:03 - mmengine - INFO - Epoch(train) [114][500/940] lr: 4.0000e-03 eta: 7:27:55 time: 0.6884 data_time: 0.0466 memory: 23705 grad_norm: 4.8535 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4761 loss_aux: 0.9547 loss: 2.4308 2022/09/11 17:16:16 - mmengine - INFO - Epoch(train) [114][520/940] lr: 4.0000e-03 eta: 7:26:48 time: 0.6746 data_time: 0.0311 memory: 23705 grad_norm: 4.8648 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5037 loss_aux: 0.9685 loss: 2.4722 2022/09/11 17:16:31 - mmengine - INFO - Epoch(train) [114][540/940] lr: 4.0000e-03 eta: 7:26:16 time: 0.7470 data_time: 0.0280 memory: 23705 grad_norm: 4.9350 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4897 loss_aux: 0.9945 loss: 2.4842 2022/09/11 17:17:25 - mmengine - INFO - Epoch(train) [114][560/940] lr: 4.0000e-03 eta: 7:40:41 time: 2.7125 data_time: 0.7404 memory: 23705 grad_norm: 4.8432 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4067 loss_aux: 0.8864 loss: 2.2930 2022/09/11 17:17:39 - mmengine - INFO - Epoch(train) [114][580/940] lr: 4.0000e-03 eta: 7:39:38 time: 0.7043 data_time: 0.0561 memory: 23705 grad_norm: 4.8224 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4766 loss_aux: 0.9667 loss: 2.4432 2022/09/11 17:17:53 - mmengine - INFO - Epoch(train) [114][600/940] lr: 4.0000e-03 eta: 7:38:30 time: 0.6896 data_time: 0.0346 memory: 23705 grad_norm: 4.9410 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4239 loss_aux: 0.8959 loss: 2.3197 2022/09/11 17:18:07 - mmengine - INFO - Epoch(train) [114][620/940] lr: 4.0000e-03 eta: 7:37:27 time: 0.6982 data_time: 0.0376 memory: 23705 grad_norm: 4.8320 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.5541 loss_aux: 0.9737 loss: 2.5278 2022/09/11 17:18:21 - mmengine - INFO - Epoch(train) [114][640/940] lr: 4.0000e-03 eta: 7:36:25 time: 0.6963 data_time: 0.0416 memory: 23705 grad_norm: 4.9254 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.7280 loss_aux: 1.0567 loss: 2.7847 2022/09/11 17:18:35 - mmengine - INFO - Epoch(train) [114][660/940] lr: 4.0000e-03 eta: 7:35:26 time: 0.7015 data_time: 0.0404 memory: 23705 grad_norm: 4.9183 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5947 loss_aux: 1.0180 loss: 2.6127 2022/09/11 17:18:49 - mmengine - INFO - Epoch(train) [114][680/940] lr: 4.0000e-03 eta: 7:34:18 time: 0.6781 data_time: 0.0335 memory: 23705 grad_norm: 4.9330 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3909 loss_aux: 0.9244 loss: 2.3153 2022/09/11 17:19:03 - mmengine - INFO - Epoch(train) [114][700/940] lr: 4.0000e-03 eta: 7:33:24 time: 0.7070 data_time: 0.0404 memory: 23705 grad_norm: 4.9576 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5625 loss_aux: 0.9509 loss: 2.5134 2022/09/11 17:19:16 - mmengine - INFO - Epoch(train) [114][720/940] lr: 4.0000e-03 eta: 7:32:22 time: 0.6865 data_time: 0.0412 memory: 23705 grad_norm: 4.9017 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4832 loss_aux: 0.9636 loss: 2.4468 2022/09/11 17:19:30 - mmengine - INFO - Epoch(train) [114][740/940] lr: 4.0000e-03 eta: 7:31:23 time: 0.6901 data_time: 0.0380 memory: 23705 grad_norm: 4.8969 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.5185 loss_aux: 0.9619 loss: 2.4805 2022/09/11 17:19:44 - mmengine - INFO - Epoch(train) [114][760/940] lr: 4.0000e-03 eta: 7:30:23 time: 0.6852 data_time: 0.0371 memory: 23705 grad_norm: 4.9779 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5371 loss_aux: 0.9773 loss: 2.5144 2022/09/11 17:19:58 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 17:19:58 - mmengine - INFO - Epoch(train) [114][780/940] lr: 4.0000e-03 eta: 7:29:30 time: 0.7011 data_time: 0.0330 memory: 23705 grad_norm: 4.9234 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4655 loss_aux: 0.8994 loss: 2.3649 2022/09/11 17:20:12 - mmengine - INFO - Epoch(train) [114][800/940] lr: 4.0000e-03 eta: 7:28:39 time: 0.7031 data_time: 0.0380 memory: 23705 grad_norm: 4.8754 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.5314 loss_aux: 0.9943 loss: 2.5257 2022/09/11 17:20:26 - mmengine - INFO - Epoch(train) [114][820/940] lr: 4.0000e-03 eta: 7:27:43 time: 0.6893 data_time: 0.0402 memory: 23705 grad_norm: 4.8888 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4643 loss_aux: 0.9313 loss: 2.3956 2022/09/11 17:20:39 - mmengine - INFO - Epoch(train) [114][840/940] lr: 4.0000e-03 eta: 7:26:44 time: 0.6779 data_time: 0.0349 memory: 23705 grad_norm: 4.9468 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.4693 loss_aux: 0.9281 loss: 2.3973 2022/09/11 17:20:53 - mmengine - INFO - Epoch(train) [114][860/940] lr: 4.0000e-03 eta: 7:25:55 time: 0.7015 data_time: 0.0437 memory: 23705 grad_norm: 4.9182 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5580 loss_aux: 1.0147 loss: 2.5727 2022/09/11 17:21:07 - mmengine - INFO - Epoch(train) [114][880/940] lr: 4.0000e-03 eta: 7:24:57 time: 0.6741 data_time: 0.0351 memory: 23705 grad_norm: 4.8940 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5289 loss_aux: 0.9571 loss: 2.4860 2022/09/11 17:21:21 - mmengine - INFO - Epoch(train) [114][900/940] lr: 4.0000e-03 eta: 7:24:11 time: 0.7046 data_time: 0.0398 memory: 23705 grad_norm: 4.9248 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5330 loss_aux: 0.9388 loss: 2.4718 2022/09/11 17:21:34 - mmengine - INFO - Epoch(train) [114][920/940] lr: 4.0000e-03 eta: 7:23:12 time: 0.6697 data_time: 0.0337 memory: 23705 grad_norm: 4.9215 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.5350 loss_aux: 0.9701 loss: 2.5051 2022/09/11 17:21:48 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 17:21:48 - mmengine - INFO - Epoch(train) [114][940/940] lr: 4.0000e-03 eta: 7:22:11 time: 0.6589 data_time: 0.0298 memory: 23705 grad_norm: 5.1301 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.6034 loss_aux: 1.0019 loss: 2.6052 2022/09/11 17:21:48 - mmengine - INFO - Saving checkpoint at 114 epochs 2022/09/11 17:22:13 - mmengine - INFO - Epoch(train) [115][20/940] lr: 4.0000e-03 eta: 7:22:54 time: 0.9478 data_time: 0.2824 memory: 23705 grad_norm: 4.8221 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5002 loss_aux: 0.9897 loss: 2.4899 2022/09/11 17:22:27 - mmengine - INFO - Epoch(train) [115][40/940] lr: 4.0000e-03 eta: 7:22:06 time: 0.6964 data_time: 0.0371 memory: 23705 grad_norm: 4.8274 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4802 loss_aux: 0.9521 loss: 2.4324 2022/09/11 17:22:41 - mmengine - INFO - Epoch(train) [115][60/940] lr: 4.0000e-03 eta: 7:21:15 time: 0.6831 data_time: 0.0304 memory: 23705 grad_norm: 4.9486 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5592 loss_aux: 0.9941 loss: 2.5532 2022/09/11 17:22:55 - mmengine - INFO - Epoch(train) [115][80/940] lr: 4.0000e-03 eta: 7:20:30 time: 0.6974 data_time: 0.0341 memory: 23705 grad_norm: 4.9300 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5466 loss_aux: 0.9743 loss: 2.5209 2022/09/11 17:23:09 - mmengine - INFO - Epoch(train) [115][100/940] lr: 4.0000e-03 eta: 7:19:47 time: 0.7031 data_time: 0.0468 memory: 23705 grad_norm: 4.8096 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2362 loss_aux: 0.8586 loss: 2.0948 2022/09/11 17:23:23 - mmengine - INFO - Epoch(train) [115][120/940] lr: 4.0000e-03 eta: 7:19:00 time: 0.6877 data_time: 0.0309 memory: 23705 grad_norm: 4.8169 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4062 loss_aux: 0.9119 loss: 2.3181 2022/09/11 17:23:36 - mmengine - INFO - Epoch(train) [115][140/940] lr: 4.0000e-03 eta: 7:18:11 time: 0.6838 data_time: 0.0321 memory: 23705 grad_norm: 4.9288 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5135 loss_aux: 0.9670 loss: 2.4805 2022/09/11 17:23:50 - mmengine - INFO - Epoch(train) [115][160/940] lr: 4.0000e-03 eta: 7:17:21 time: 0.6730 data_time: 0.0329 memory: 23705 grad_norm: 4.9067 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.4365 loss_aux: 0.9383 loss: 2.3748 2022/09/11 17:24:04 - mmengine - INFO - Epoch(train) [115][180/940] lr: 4.0000e-03 eta: 7:16:40 time: 0.7021 data_time: 0.0575 memory: 23705 grad_norm: 4.9213 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6125 loss_aux: 0.9986 loss: 2.6111 2022/09/11 17:24:18 - mmengine - INFO - Epoch(train) [115][200/940] lr: 4.0000e-03 eta: 7:15:54 time: 0.6860 data_time: 0.0330 memory: 23705 grad_norm: 4.9134 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5239 loss_aux: 0.9577 loss: 2.4816 2022/09/11 17:24:31 - mmengine - INFO - Epoch(train) [115][220/940] lr: 4.0000e-03 eta: 7:15:11 time: 0.6900 data_time: 0.0321 memory: 23705 grad_norm: 4.9792 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6420 loss_aux: 1.0293 loss: 2.6713 2022/09/11 17:24:45 - mmengine - INFO - Epoch(train) [115][240/940] lr: 4.0000e-03 eta: 7:14:25 time: 0.6824 data_time: 0.0370 memory: 23705 grad_norm: 4.9024 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.5790 loss_aux: 1.0024 loss: 2.5814 2022/09/11 17:24:59 - mmengine - INFO - Epoch(train) [115][260/940] lr: 4.0000e-03 eta: 7:13:46 time: 0.6999 data_time: 0.0483 memory: 23705 grad_norm: 4.8982 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4686 loss_aux: 0.9261 loss: 2.3947 2022/09/11 17:25:13 - mmengine - INFO - Epoch(train) [115][280/940] lr: 4.0000e-03 eta: 7:13:05 time: 0.6935 data_time: 0.0324 memory: 23705 grad_norm: 4.9287 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4601 loss_aux: 0.9498 loss: 2.4099 2022/09/11 17:25:27 - mmengine - INFO - Epoch(train) [115][300/940] lr: 4.0000e-03 eta: 7:12:23 time: 0.6863 data_time: 0.0328 memory: 23705 grad_norm: 5.0083 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5584 loss_aux: 0.9451 loss: 2.5035 2022/09/11 17:25:41 - mmengine - INFO - Epoch(train) [115][320/940] lr: 4.0000e-03 eta: 7:11:46 time: 0.7029 data_time: 0.0337 memory: 23705 grad_norm: 4.9880 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.6486 loss_aux: 1.0591 loss: 2.7076 2022/09/11 17:25:55 - mmengine - INFO - Epoch(train) [115][340/940] lr: 4.0000e-03 eta: 7:11:10 time: 0.7059 data_time: 0.0503 memory: 23705 grad_norm: 4.7697 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.4603 loss_aux: 0.9543 loss: 2.4146 2022/09/11 17:26:09 - mmengine - INFO - Epoch(train) [115][360/940] lr: 4.0000e-03 eta: 7:10:29 time: 0.6876 data_time: 0.0298 memory: 23705 grad_norm: 4.8512 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.4966 loss_aux: 0.9701 loss: 2.4667 2022/09/11 17:26:22 - mmengine - INFO - Epoch(train) [115][380/940] lr: 4.0000e-03 eta: 7:09:51 time: 0.6946 data_time: 0.0427 memory: 23705 grad_norm: 4.9310 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.5338 loss_aux: 0.9760 loss: 2.5098 2022/09/11 17:26:36 - mmengine - INFO - Epoch(train) [115][400/940] lr: 4.0000e-03 eta: 7:09:13 time: 0.6939 data_time: 0.0333 memory: 23705 grad_norm: 4.9203 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.6486 loss_aux: 1.0258 loss: 2.6743 2022/09/11 17:26:51 - mmengine - INFO - Epoch(train) [115][420/940] lr: 4.0000e-03 eta: 7:08:40 time: 0.7104 data_time: 0.0455 memory: 23705 grad_norm: 4.8609 top1_acc: 0.5000 top5_acc: 0.9062 loss_cls: 1.3826 loss_aux: 0.8878 loss: 2.2705 2022/09/11 17:27:04 - mmengine - INFO - Epoch(train) [115][440/940] lr: 4.0000e-03 eta: 7:08:03 time: 0.6933 data_time: 0.0343 memory: 23705 grad_norm: 4.8198 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.5673 loss_aux: 0.9836 loss: 2.5509 2022/09/11 17:27:18 - mmengine - INFO - Epoch(train) [115][460/940] lr: 4.0000e-03 eta: 7:07:24 time: 0.6863 data_time: 0.0328 memory: 23705 grad_norm: 4.8408 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4311 loss_aux: 0.9444 loss: 2.3755 2022/09/11 17:27:32 - mmengine - INFO - Epoch(train) [115][480/940] lr: 4.0000e-03 eta: 7:06:53 time: 0.7148 data_time: 0.0363 memory: 23705 grad_norm: 4.9197 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5136 loss_aux: 0.9679 loss: 2.4816 2022/09/11 17:27:47 - mmengine - INFO - Epoch(train) [115][500/940] lr: 4.0000e-03 eta: 7:06:21 time: 0.7051 data_time: 0.0468 memory: 23705 grad_norm: 4.8666 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5829 loss_aux: 0.9783 loss: 2.5612 2022/09/11 17:28:00 - mmengine - INFO - Epoch(train) [115][520/940] lr: 4.0000e-03 eta: 7:05:44 time: 0.6917 data_time: 0.0338 memory: 23705 grad_norm: 4.8254 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.5519 loss_aux: 0.9820 loss: 2.5339 2022/09/11 17:28:14 - mmengine - INFO - Epoch(train) [115][540/940] lr: 4.0000e-03 eta: 7:05:11 time: 0.7013 data_time: 0.0343 memory: 23705 grad_norm: 4.9553 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4444 loss_aux: 0.9223 loss: 2.3667 2022/09/11 17:28:29 - mmengine - INFO - Epoch(train) [115][560/940] lr: 4.0000e-03 eta: 7:04:41 time: 0.7140 data_time: 0.0354 memory: 23705 grad_norm: 4.8360 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.5820 loss_aux: 0.9669 loss: 2.5489 2022/09/11 17:28:43 - mmengine - INFO - Epoch(train) [115][580/940] lr: 4.0000e-03 eta: 7:04:09 time: 0.7040 data_time: 0.0557 memory: 23705 grad_norm: 4.9605 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.5734 loss_aux: 0.9877 loss: 2.5611 2022/09/11 17:28:57 - mmengine - INFO - Epoch(train) [115][600/940] lr: 4.0000e-03 eta: 7:03:34 time: 0.6921 data_time: 0.0332 memory: 23705 grad_norm: 4.8586 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.4813 loss_aux: 0.9646 loss: 2.4459 2022/09/11 17:29:10 - mmengine - INFO - Epoch(train) [115][620/940] lr: 4.0000e-03 eta: 7:03:00 time: 0.6924 data_time: 0.0393 memory: 23705 grad_norm: 4.9612 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4918 loss_aux: 0.9616 loss: 2.4534 2022/09/11 17:29:25 - mmengine - INFO - Epoch(train) [115][640/940] lr: 4.0000e-03 eta: 7:02:31 time: 0.7110 data_time: 0.0344 memory: 23705 grad_norm: 4.7805 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4902 loss_aux: 0.9676 loss: 2.4578 2022/09/11 17:29:39 - mmengine - INFO - Epoch(train) [115][660/940] lr: 4.0000e-03 eta: 7:01:59 time: 0.7025 data_time: 0.0475 memory: 23705 grad_norm: 4.9329 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5627 loss_aux: 0.9817 loss: 2.5444 2022/09/11 17:29:52 - mmengine - INFO - Epoch(train) [115][680/940] lr: 4.0000e-03 eta: 7:01:23 time: 0.6797 data_time: 0.0297 memory: 23705 grad_norm: 4.9537 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5329 loss_aux: 0.9574 loss: 2.4902 2022/09/11 17:30:06 - mmengine - INFO - Epoch(train) [115][700/940] lr: 4.0000e-03 eta: 7:00:47 time: 0.6828 data_time: 0.0359 memory: 23705 grad_norm: 4.9368 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5326 loss_aux: 0.9681 loss: 2.5007 2022/09/11 17:30:20 - mmengine - INFO - Epoch(train) [115][720/940] lr: 4.0000e-03 eta: 7:00:15 time: 0.6974 data_time: 0.0431 memory: 23705 grad_norm: 4.9941 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.6268 loss_aux: 0.9936 loss: 2.6204 2022/09/11 17:30:34 - mmengine - INFO - Epoch(train) [115][740/940] lr: 4.0000e-03 eta: 6:59:42 time: 0.6893 data_time: 0.0355 memory: 23705 grad_norm: 4.8939 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5589 loss_aux: 0.9702 loss: 2.5291 2022/09/11 17:30:48 - mmengine - INFO - Epoch(train) [115][760/940] lr: 4.0000e-03 eta: 6:59:16 time: 0.7186 data_time: 0.0329 memory: 23705 grad_norm: 4.9459 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6097 loss_aux: 1.0014 loss: 2.6111 2022/09/11 17:31:02 - mmengine - INFO - Epoch(train) [115][780/940] lr: 4.0000e-03 eta: 6:58:50 time: 0.7162 data_time: 0.0340 memory: 23705 grad_norm: 4.8937 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4848 loss_aux: 0.9289 loss: 2.4137 2022/09/11 17:31:16 - mmengine - INFO - Epoch(train) [115][800/940] lr: 4.0000e-03 eta: 6:58:19 time: 0.6950 data_time: 0.0391 memory: 23705 grad_norm: 4.9416 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5826 loss_aux: 1.0010 loss: 2.5836 2022/09/11 17:31:30 - mmengine - INFO - Epoch(train) [115][820/940] lr: 4.0000e-03 eta: 6:57:48 time: 0.6957 data_time: 0.0320 memory: 23705 grad_norm: 4.9321 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5307 loss_aux: 0.9797 loss: 2.5103 2022/09/11 17:31:44 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 17:31:44 - mmengine - INFO - Epoch(train) [115][840/940] lr: 4.0000e-03 eta: 6:57:11 time: 0.6712 data_time: 0.0312 memory: 23705 grad_norm: 4.8667 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.5093 loss_aux: 0.9881 loss: 2.4974 2022/09/11 17:31:58 - mmengine - INFO - Epoch(train) [115][860/940] lr: 4.0000e-03 eta: 6:56:40 time: 0.6928 data_time: 0.0353 memory: 23705 grad_norm: 4.8873 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4782 loss_aux: 0.9505 loss: 2.4287 2022/09/11 17:32:12 - mmengine - INFO - Epoch(train) [115][880/940] lr: 4.0000e-03 eta: 6:56:10 time: 0.6966 data_time: 0.0401 memory: 23705 grad_norm: 4.9524 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.5927 loss_aux: 1.0047 loss: 2.5974 2022/09/11 17:32:25 - mmengine - INFO - Epoch(train) [115][900/940] lr: 4.0000e-03 eta: 6:55:40 time: 0.6928 data_time: 0.0291 memory: 23705 grad_norm: 4.8915 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5477 loss_aux: 0.9826 loss: 2.5303 2022/09/11 17:32:39 - mmengine - INFO - Epoch(train) [115][920/940] lr: 4.0000e-03 eta: 6:55:04 time: 0.6680 data_time: 0.0283 memory: 23705 grad_norm: 5.0039 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.5561 loss_aux: 0.9906 loss: 2.5467 2022/09/11 17:32:52 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 17:32:52 - mmengine - INFO - Epoch(train) [115][940/940] lr: 4.0000e-03 eta: 6:54:29 time: 0.6722 data_time: 0.0424 memory: 23705 grad_norm: 5.0985 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.5518 loss_aux: 0.9855 loss: 2.5373 2022/09/11 17:32:52 - mmengine - INFO - Saving checkpoint at 115 epochs 2022/09/11 17:33:18 - mmengine - INFO - Epoch(train) [116][20/940] lr: 4.0000e-03 eta: 6:55:11 time: 1.0028 data_time: 0.3042 memory: 23705 grad_norm: 4.9340 top1_acc: 0.5938 top5_acc: 0.6250 loss_cls: 1.4759 loss_aux: 0.9598 loss: 2.4357 2022/09/11 17:33:32 - mmengine - INFO - Epoch(train) [116][40/940] lr: 4.0000e-03 eta: 6:54:45 time: 0.7127 data_time: 0.0274 memory: 23705 grad_norm: 4.8458 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5237 loss_aux: 0.9943 loss: 2.5180 2022/09/11 17:33:46 - mmengine - INFO - Epoch(train) [116][60/940] lr: 4.0000e-03 eta: 6:54:11 time: 0.6742 data_time: 0.0329 memory: 23705 grad_norm: 4.9517 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.5385 loss_aux: 0.9743 loss: 2.5128 2022/09/11 17:34:00 - mmengine - INFO - Epoch(train) [116][80/940] lr: 4.0000e-03 eta: 6:53:43 time: 0.6997 data_time: 0.0314 memory: 23705 grad_norm: 4.8974 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.5211 loss_aux: 0.9844 loss: 2.5056 2022/09/11 17:34:14 - mmengine - INFO - Epoch(train) [116][100/940] lr: 4.0000e-03 eta: 6:53:17 time: 0.7064 data_time: 0.0379 memory: 23705 grad_norm: 4.9508 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3781 loss_aux: 0.9036 loss: 2.2817 2022/09/11 17:34:28 - mmengine - INFO - Epoch(train) [116][120/940] lr: 4.0000e-03 eta: 6:52:46 time: 0.6869 data_time: 0.0370 memory: 23705 grad_norm: 4.9105 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4763 loss_aux: 0.9346 loss: 2.4109 2022/09/11 17:34:42 - mmengine - INFO - Epoch(train) [116][140/940] lr: 4.0000e-03 eta: 6:52:17 time: 0.6909 data_time: 0.0357 memory: 23705 grad_norm: 4.7854 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4963 loss_aux: 0.9753 loss: 2.4716 2022/09/11 17:34:55 - mmengine - INFO - Epoch(train) [116][160/940] lr: 4.0000e-03 eta: 6:51:48 time: 0.6902 data_time: 0.0394 memory: 23705 grad_norm: 4.9787 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4752 loss_aux: 0.9184 loss: 2.3937 2022/09/11 17:35:09 - mmengine - INFO - Epoch(train) [116][180/940] lr: 4.0000e-03 eta: 6:51:20 time: 0.6988 data_time: 0.0389 memory: 23705 grad_norm: 4.9932 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4772 loss_aux: 0.9596 loss: 2.4367 2022/09/11 17:35:24 - mmengine - INFO - Epoch(train) [116][200/940] lr: 4.0000e-03 eta: 6:50:55 time: 0.7092 data_time: 0.0322 memory: 23705 grad_norm: 4.9284 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5272 loss_aux: 0.9482 loss: 2.4754 2022/09/11 17:35:37 - mmengine - INFO - Epoch(train) [116][220/940] lr: 4.0000e-03 eta: 6:50:27 time: 0.6897 data_time: 0.0367 memory: 23705 grad_norm: 4.9103 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4641 loss_aux: 0.9191 loss: 2.3832 2022/09/11 17:35:51 - mmengine - INFO - Epoch(train) [116][240/940] lr: 4.0000e-03 eta: 6:49:58 time: 0.6900 data_time: 0.0308 memory: 23705 grad_norm: 4.9420 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4917 loss_aux: 0.9719 loss: 2.4636 2022/09/11 17:36:06 - mmengine - INFO - Epoch(train) [116][260/940] lr: 4.0000e-03 eta: 6:49:36 time: 0.7202 data_time: 0.0396 memory: 23705 grad_norm: 4.9979 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5184 loss_aux: 0.9391 loss: 2.4575 2022/09/11 17:36:20 - mmengine - INFO - Epoch(train) [116][280/940] lr: 4.0000e-03 eta: 6:49:08 time: 0.6942 data_time: 0.0299 memory: 23705 grad_norm: 4.9348 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3721 loss_aux: 0.9011 loss: 2.2731 2022/09/11 17:36:33 - mmengine - INFO - Epoch(train) [116][300/940] lr: 4.0000e-03 eta: 6:48:40 time: 0.6870 data_time: 0.0375 memory: 23705 grad_norm: 5.0566 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5485 loss_aux: 0.9610 loss: 2.5095 2022/09/11 17:36:47 - mmengine - INFO - Epoch(train) [116][320/940] lr: 4.0000e-03 eta: 6:48:11 time: 0.6884 data_time: 0.0341 memory: 23705 grad_norm: 4.9897 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4946 loss_aux: 0.9631 loss: 2.4577 2022/09/11 17:37:01 - mmengine - INFO - Epoch(train) [116][340/940] lr: 4.0000e-03 eta: 6:47:45 time: 0.6970 data_time: 0.0425 memory: 23705 grad_norm: 4.9409 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.6249 loss_aux: 1.0123 loss: 2.6372 2022/09/11 17:37:15 - mmengine - INFO - Epoch(train) [116][360/940] lr: 4.0000e-03 eta: 6:47:20 time: 0.7033 data_time: 0.0363 memory: 23705 grad_norm: 4.9294 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3848 loss_aux: 0.8989 loss: 2.2837 2022/09/11 17:37:29 - mmengine - INFO - Epoch(train) [116][380/940] lr: 4.0000e-03 eta: 6:46:55 time: 0.6987 data_time: 0.0395 memory: 23705 grad_norm: 4.9804 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5795 loss_aux: 0.9756 loss: 2.5551 2022/09/11 17:37:43 - mmengine - INFO - Epoch(train) [116][400/940] lr: 4.0000e-03 eta: 6:46:32 time: 0.7129 data_time: 0.0372 memory: 23705 grad_norm: 4.9340 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5444 loss_aux: 1.0121 loss: 2.5564 2022/09/11 17:37:57 - mmengine - INFO - Epoch(train) [116][420/940] lr: 4.0000e-03 eta: 6:46:08 time: 0.7039 data_time: 0.0428 memory: 23705 grad_norm: 4.8609 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4856 loss_aux: 0.9790 loss: 2.4646 2022/09/11 17:38:11 - mmengine - INFO - Epoch(train) [116][440/940] lr: 4.0000e-03 eta: 6:45:40 time: 0.6855 data_time: 0.0319 memory: 23705 grad_norm: 5.0075 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4662 loss_aux: 0.9614 loss: 2.4276 2022/09/11 17:38:25 - mmengine - INFO - Epoch(train) [116][460/940] lr: 4.0000e-03 eta: 6:45:18 time: 0.7175 data_time: 0.0395 memory: 23705 grad_norm: 4.9999 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6649 loss_aux: 1.0325 loss: 2.6974 2022/09/11 17:38:39 - mmengine - INFO - Epoch(train) [116][480/940] lr: 4.0000e-03 eta: 6:44:51 time: 0.6864 data_time: 0.0395 memory: 23705 grad_norm: 5.0069 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.6356 loss_aux: 1.0397 loss: 2.6753 2022/09/11 17:38:53 - mmengine - INFO - Epoch(train) [116][500/940] lr: 4.0000e-03 eta: 6:44:27 time: 0.7030 data_time: 0.0413 memory: 23705 grad_norm: 5.0006 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4435 loss_aux: 0.9436 loss: 2.3871 2022/09/11 17:39:07 - mmengine - INFO - Epoch(train) [116][520/940] lr: 4.0000e-03 eta: 6:44:00 time: 0.6899 data_time: 0.0339 memory: 23705 grad_norm: 4.8955 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.4372 loss_aux: 0.9564 loss: 2.3936 2022/09/11 17:39:21 - mmengine - INFO - Epoch(train) [116][540/940] lr: 4.0000e-03 eta: 6:43:37 time: 0.7033 data_time: 0.0385 memory: 23705 grad_norm: 4.9682 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4631 loss_aux: 0.9410 loss: 2.4041 2022/09/11 17:39:35 - mmengine - INFO - Epoch(train) [116][560/940] lr: 4.0000e-03 eta: 6:43:12 time: 0.6983 data_time: 0.0476 memory: 23705 grad_norm: 4.9484 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.5618 loss_aux: 0.9931 loss: 2.5549 2022/09/11 17:39:49 - mmengine - INFO - Epoch(train) [116][580/940] lr: 4.0000e-03 eta: 6:42:49 time: 0.7060 data_time: 0.0402 memory: 23705 grad_norm: 4.8691 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4454 loss_aux: 0.9287 loss: 2.3741 2022/09/11 17:40:03 - mmengine - INFO - Epoch(train) [116][600/940] lr: 4.0000e-03 eta: 6:42:24 time: 0.6913 data_time: 0.0313 memory: 23705 grad_norm: 4.9764 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.6009 loss_aux: 0.9865 loss: 2.5874 2022/09/11 17:40:17 - mmengine - INFO - Epoch(train) [116][620/940] lr: 4.0000e-03 eta: 6:41:58 time: 0.6898 data_time: 0.0394 memory: 23705 grad_norm: 4.8554 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5026 loss_aux: 0.9514 loss: 2.4540 2022/09/11 17:40:31 - mmengine - INFO - Epoch(train) [116][640/940] lr: 4.0000e-03 eta: 6:41:32 time: 0.6865 data_time: 0.0384 memory: 23705 grad_norm: 4.9428 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4876 loss_aux: 0.9401 loss: 2.4277 2022/09/11 17:40:45 - mmengine - INFO - Epoch(train) [116][660/940] lr: 4.0000e-03 eta: 6:41:07 time: 0.6974 data_time: 0.0428 memory: 23705 grad_norm: 4.8858 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.5467 loss_aux: 0.9804 loss: 2.5271 2022/09/11 17:40:59 - mmengine - INFO - Epoch(train) [116][680/940] lr: 4.0000e-03 eta: 6:40:44 time: 0.7028 data_time: 0.0322 memory: 23705 grad_norm: 4.8586 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6716 loss_aux: 0.9984 loss: 2.6700 2022/09/11 17:41:12 - mmengine - INFO - Epoch(train) [116][700/940] lr: 4.0000e-03 eta: 6:40:19 time: 0.6902 data_time: 0.0374 memory: 23705 grad_norm: 4.9775 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4806 loss_aux: 0.9438 loss: 2.4245 2022/09/11 17:41:26 - mmengine - INFO - Epoch(train) [116][720/940] lr: 4.0000e-03 eta: 6:39:53 time: 0.6823 data_time: 0.0370 memory: 23705 grad_norm: 5.0223 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.6133 loss_aux: 0.9971 loss: 2.6103 2022/09/11 17:41:40 - mmengine - INFO - Epoch(train) [116][740/940] lr: 4.0000e-03 eta: 6:39:29 time: 0.6948 data_time: 0.0373 memory: 23705 grad_norm: 5.0644 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4555 loss_aux: 0.9152 loss: 2.3706 2022/09/11 17:41:54 - mmengine - INFO - Epoch(train) [116][760/940] lr: 4.0000e-03 eta: 6:39:04 time: 0.6933 data_time: 0.0425 memory: 23705 grad_norm: 4.8908 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5035 loss_aux: 0.9863 loss: 2.4898 2022/09/11 17:42:08 - mmengine - INFO - Epoch(train) [116][780/940] lr: 4.0000e-03 eta: 6:38:40 time: 0.6907 data_time: 0.0400 memory: 23705 grad_norm: 5.0072 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5251 loss_aux: 0.9602 loss: 2.4853 2022/09/11 17:42:22 - mmengine - INFO - Epoch(train) [116][800/940] lr: 4.0000e-03 eta: 6:38:17 time: 0.6994 data_time: 0.0374 memory: 23705 grad_norm: 4.9597 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4778 loss_aux: 0.9706 loss: 2.4484 2022/09/11 17:42:36 - mmengine - INFO - Epoch(train) [116][820/940] lr: 4.0000e-03 eta: 6:37:54 time: 0.7012 data_time: 0.0386 memory: 23705 grad_norm: 4.9582 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.5532 loss_aux: 0.9687 loss: 2.5219 2022/09/11 17:42:49 - mmengine - INFO - Epoch(train) [116][840/940] lr: 4.0000e-03 eta: 6:37:30 time: 0.6911 data_time: 0.0335 memory: 23705 grad_norm: 5.0366 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5147 loss_aux: 0.9384 loss: 2.4531 2022/09/11 17:43:04 - mmengine - INFO - Epoch(train) [116][860/940] lr: 4.0000e-03 eta: 6:37:11 time: 0.7163 data_time: 0.0443 memory: 23705 grad_norm: 4.9272 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6454 loss_aux: 1.0041 loss: 2.6494 2022/09/11 17:43:17 - mmengine - INFO - Epoch(train) [116][880/940] lr: 4.0000e-03 eta: 6:36:45 time: 0.6800 data_time: 0.0389 memory: 23705 grad_norm: 4.8935 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.5362 loss_aux: 0.9780 loss: 2.5142 2022/09/11 17:43:31 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 17:43:31 - mmengine - INFO - Epoch(train) [116][900/940] lr: 4.0000e-03 eta: 6:36:22 time: 0.6973 data_time: 0.0386 memory: 23705 grad_norm: 4.9767 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.6200 loss_aux: 1.0365 loss: 2.6565 2022/09/11 17:43:45 - mmengine - INFO - Epoch(train) [116][920/940] lr: 4.0000e-03 eta: 6:35:57 time: 0.6880 data_time: 0.0314 memory: 23705 grad_norm: 4.9267 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.5127 loss_aux: 0.9378 loss: 2.4505 2022/09/11 17:43:58 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 17:43:58 - mmengine - INFO - Epoch(train) [116][940/940] lr: 4.0000e-03 eta: 6:35:29 time: 0.6624 data_time: 0.0290 memory: 23705 grad_norm: 5.2314 top1_acc: 0.5714 top5_acc: 1.0000 loss_cls: 1.5976 loss_aux: 1.0403 loss: 2.6379 2022/09/11 17:43:58 - mmengine - INFO - Saving checkpoint at 116 epochs 2022/09/11 17:44:24 - mmengine - INFO - Epoch(train) [117][20/940] lr: 4.0000e-03 eta: 6:35:46 time: 0.9292 data_time: 0.2816 memory: 23705 grad_norm: 5.0247 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.5008 loss_aux: 0.9690 loss: 2.4699 2022/09/11 17:44:37 - mmengine - INFO - Epoch(train) [117][40/940] lr: 4.0000e-03 eta: 6:35:20 time: 0.6804 data_time: 0.0363 memory: 23705 grad_norm: 4.9319 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5613 loss_aux: 1.0075 loss: 2.5688 2022/09/11 17:44:51 - mmengine - INFO - Epoch(train) [117][60/940] lr: 4.0000e-03 eta: 6:34:55 time: 0.6807 data_time: 0.0309 memory: 23705 grad_norm: 4.8968 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5086 loss_aux: 0.9818 loss: 2.4905 2022/09/11 17:45:05 - mmengine - INFO - Epoch(train) [117][80/940] lr: 4.0000e-03 eta: 6:34:32 time: 0.6944 data_time: 0.0419 memory: 23705 grad_norm: 4.9960 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.5880 loss_aux: 1.0195 loss: 2.6075 2022/09/11 17:45:19 - mmengine - INFO - Epoch(train) [117][100/940] lr: 4.0000e-03 eta: 6:34:10 time: 0.6995 data_time: 0.0492 memory: 23705 grad_norm: 5.0265 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.5262 loss_aux: 0.9880 loss: 2.5142 2022/09/11 17:45:32 - mmengine - INFO - Epoch(train) [117][120/940] lr: 4.0000e-03 eta: 6:33:47 time: 0.6900 data_time: 0.0345 memory: 23705 grad_norm: 4.8989 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4563 loss_aux: 0.9665 loss: 2.4229 2022/09/11 17:45:46 - mmengine - INFO - Epoch(train) [117][140/940] lr: 4.0000e-03 eta: 6:33:24 time: 0.6963 data_time: 0.0318 memory: 23705 grad_norm: 5.0108 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4882 loss_aux: 0.9480 loss: 2.4362 2022/09/11 17:46:00 - mmengine - INFO - Epoch(train) [117][160/940] lr: 4.0000e-03 eta: 6:32:59 time: 0.6783 data_time: 0.0352 memory: 23705 grad_norm: 5.0558 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6770 loss_aux: 1.0730 loss: 2.7500 2022/09/11 17:46:14 - mmengine - INFO - Epoch(train) [117][180/940] lr: 4.0000e-03 eta: 6:32:37 time: 0.6959 data_time: 0.0418 memory: 23705 grad_norm: 4.9874 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4743 loss_aux: 0.9637 loss: 2.4380 2022/09/11 17:46:28 - mmengine - INFO - Epoch(train) [117][200/940] lr: 4.0000e-03 eta: 6:32:13 time: 0.6867 data_time: 0.0346 memory: 23705 grad_norm: 4.9585 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4933 loss_aux: 0.9668 loss: 2.4601 2022/09/11 17:46:41 - mmengine - INFO - Epoch(train) [117][220/940] lr: 4.0000e-03 eta: 6:31:49 time: 0.6839 data_time: 0.0373 memory: 23705 grad_norm: 5.0329 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6452 loss_aux: 1.0102 loss: 2.6554 2022/09/11 17:46:55 - mmengine - INFO - Epoch(train) [117][240/940] lr: 4.0000e-03 eta: 6:31:28 time: 0.6962 data_time: 0.0446 memory: 23705 grad_norm: 5.0023 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4833 loss_aux: 0.9819 loss: 2.4653 2022/09/11 17:47:10 - mmengine - INFO - Epoch(train) [117][260/940] lr: 4.0000e-03 eta: 6:31:10 time: 0.7231 data_time: 0.0402 memory: 23705 grad_norm: 4.9382 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4795 loss_aux: 0.9044 loss: 2.3840 2022/09/11 17:47:24 - mmengine - INFO - Epoch(train) [117][280/940] lr: 4.0000e-03 eta: 6:30:48 time: 0.6934 data_time: 0.0360 memory: 23705 grad_norm: 4.9182 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 1.5069 loss_aux: 0.9634 loss: 2.4703 2022/09/11 17:47:37 - mmengine - INFO - Epoch(train) [117][300/940] lr: 4.0000e-03 eta: 6:30:25 time: 0.6867 data_time: 0.0370 memory: 23705 grad_norm: 4.9858 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4964 loss_aux: 0.9781 loss: 2.4745 2022/09/11 17:47:51 - mmengine - INFO - Epoch(train) [117][320/940] lr: 4.0000e-03 eta: 6:30:02 time: 0.6888 data_time: 0.0404 memory: 23705 grad_norm: 4.9566 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.5674 loss_aux: 0.9701 loss: 2.5375 2022/09/11 17:48:05 - mmengine - INFO - Epoch(train) [117][340/940] lr: 4.0000e-03 eta: 6:29:42 time: 0.7084 data_time: 0.0398 memory: 23705 grad_norm: 4.9966 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4673 loss_aux: 0.9565 loss: 2.4238 2022/09/11 17:48:19 - mmengine - INFO - Epoch(train) [117][360/940] lr: 4.0000e-03 eta: 6:29:19 time: 0.6837 data_time: 0.0297 memory: 23705 grad_norm: 4.8952 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.5425 loss_aux: 0.9948 loss: 2.5373 2022/09/11 17:48:33 - mmengine - INFO - Epoch(train) [117][380/940] lr: 4.0000e-03 eta: 6:28:56 time: 0.6841 data_time: 0.0299 memory: 23705 grad_norm: 4.9554 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6047 loss_aux: 1.0025 loss: 2.6073 2022/09/11 17:48:46 - mmengine - INFO - Epoch(train) [117][400/940] lr: 4.0000e-03 eta: 6:28:33 time: 0.6835 data_time: 0.0348 memory: 23705 grad_norm: 5.0055 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.5687 loss_aux: 1.0253 loss: 2.5940 2022/09/11 17:49:00 - mmengine - INFO - Epoch(train) [117][420/940] lr: 4.0000e-03 eta: 6:28:12 time: 0.6999 data_time: 0.0420 memory: 23705 grad_norm: 4.9538 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.5856 loss_aux: 1.0108 loss: 2.5964 2022/09/11 17:49:14 - mmengine - INFO - Epoch(train) [117][440/940] lr: 4.0000e-03 eta: 6:27:49 time: 0.6855 data_time: 0.0301 memory: 23705 grad_norm: 5.1323 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5143 loss_aux: 0.9430 loss: 2.4572 2022/09/11 17:49:28 - mmengine - INFO - Epoch(train) [117][460/940] lr: 4.0000e-03 eta: 6:27:30 time: 0.7062 data_time: 0.0360 memory: 23705 grad_norm: 4.9678 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5990 loss_aux: 0.9800 loss: 2.5790 2022/09/11 17:49:42 - mmengine - INFO - Epoch(train) [117][480/940] lr: 4.0000e-03 eta: 6:27:06 time: 0.6799 data_time: 0.0321 memory: 23705 grad_norm: 5.0728 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4089 loss_aux: 0.9120 loss: 2.3209 2022/09/11 17:49:56 - mmengine - INFO - Epoch(train) [117][500/940] lr: 4.0000e-03 eta: 6:26:50 time: 0.7284 data_time: 0.0547 memory: 23705 grad_norm: 5.0786 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.5929 loss_aux: 1.0165 loss: 2.6094 2022/09/11 17:50:10 - mmengine - INFO - Epoch(train) [117][520/940] lr: 4.0000e-03 eta: 6:26:27 time: 0.6779 data_time: 0.0313 memory: 23705 grad_norm: 5.0528 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4915 loss_aux: 0.9569 loss: 2.4484 2022/09/11 17:50:24 - mmengine - INFO - Epoch(train) [117][540/940] lr: 4.0000e-03 eta: 6:26:04 time: 0.6866 data_time: 0.0308 memory: 23705 grad_norm: 4.9858 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5328 loss_aux: 0.9738 loss: 2.5066 2022/09/11 17:50:38 - mmengine - INFO - Epoch(train) [117][560/940] lr: 4.0000e-03 eta: 6:25:48 time: 0.7271 data_time: 0.0452 memory: 23705 grad_norm: 5.0603 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.5757 loss_aux: 1.0072 loss: 2.5829 2022/09/11 17:50:52 - mmengine - INFO - Epoch(train) [117][580/940] lr: 4.0000e-03 eta: 6:25:27 time: 0.6956 data_time: 0.0290 memory: 23705 grad_norm: 5.0002 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4719 loss_aux: 0.9466 loss: 2.4185 2022/09/11 17:51:06 - mmengine - INFO - Epoch(train) [117][600/940] lr: 4.0000e-03 eta: 6:25:06 time: 0.6901 data_time: 0.0324 memory: 23705 grad_norm: 5.0107 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5592 loss_aux: 0.9691 loss: 2.5283 2022/09/11 17:51:20 - mmengine - INFO - Epoch(train) [117][620/940] lr: 4.0000e-03 eta: 6:24:44 time: 0.6887 data_time: 0.0357 memory: 23705 grad_norm: 4.9765 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4673 loss_aux: 0.9366 loss: 2.4039 2022/09/11 17:51:33 - mmengine - INFO - Epoch(train) [117][640/940] lr: 4.0000e-03 eta: 6:24:23 time: 0.6935 data_time: 0.0424 memory: 23705 grad_norm: 4.9681 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4946 loss_aux: 0.9442 loss: 2.4387 2022/09/11 17:51:48 - mmengine - INFO - Epoch(train) [117][660/940] lr: 4.0000e-03 eta: 6:24:04 time: 0.7016 data_time: 0.0322 memory: 23705 grad_norm: 5.0249 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.5359 loss_aux: 0.9798 loss: 2.5156 2022/09/11 17:52:01 - mmengine - INFO - Epoch(train) [117][680/940] lr: 4.0000e-03 eta: 6:23:42 time: 0.6893 data_time: 0.0327 memory: 23705 grad_norm: 5.0133 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5631 loss_aux: 0.9886 loss: 2.5517 2022/09/11 17:52:16 - mmengine - INFO - Epoch(train) [117][700/940] lr: 4.0000e-03 eta: 6:23:26 time: 0.7249 data_time: 0.0452 memory: 23705 grad_norm: 4.9014 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4615 loss_aux: 0.9454 loss: 2.4068 2022/09/11 17:52:30 - mmengine - INFO - Epoch(train) [117][720/940] lr: 4.0000e-03 eta: 6:23:08 time: 0.7123 data_time: 0.0401 memory: 23705 grad_norm: 5.0474 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4556 loss_aux: 0.9407 loss: 2.3964 2022/09/11 17:52:44 - mmengine - INFO - Epoch(train) [117][740/940] lr: 4.0000e-03 eta: 6:22:50 time: 0.7114 data_time: 0.0304 memory: 23705 grad_norm: 5.0383 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6037 loss_aux: 1.0237 loss: 2.6275 2022/09/11 17:52:58 - mmengine - INFO - Epoch(train) [117][760/940] lr: 4.0000e-03 eta: 6:22:29 time: 0.6936 data_time: 0.0328 memory: 23705 grad_norm: 5.0085 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4258 loss_aux: 0.9278 loss: 2.3537 2022/09/11 17:53:12 - mmengine - INFO - Epoch(train) [117][780/940] lr: 4.0000e-03 eta: 6:22:09 time: 0.6900 data_time: 0.0342 memory: 23705 grad_norm: 5.0181 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.6363 loss_aux: 0.9943 loss: 2.6306 2022/09/11 17:53:26 - mmengine - INFO - Epoch(train) [117][800/940] lr: 4.0000e-03 eta: 6:21:49 time: 0.7015 data_time: 0.0441 memory: 23705 grad_norm: 5.0290 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4527 loss_aux: 0.9637 loss: 2.4163 2022/09/11 17:53:40 - mmengine - INFO - Epoch(train) [117][820/940] lr: 4.0000e-03 eta: 6:21:30 time: 0.7006 data_time: 0.0312 memory: 23705 grad_norm: 5.0526 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.6186 loss_aux: 1.0392 loss: 2.6579 2022/09/11 17:53:54 - mmengine - INFO - Epoch(train) [117][840/940] lr: 4.0000e-03 eta: 6:21:12 time: 0.7157 data_time: 0.0313 memory: 23705 grad_norm: 4.9683 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4630 loss_aux: 0.9590 loss: 2.4220 2022/09/11 17:54:09 - mmengine - INFO - Epoch(train) [117][860/940] lr: 4.0000e-03 eta: 6:20:54 time: 0.7078 data_time: 0.0341 memory: 23705 grad_norm: 5.0349 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4169 loss_aux: 0.9350 loss: 2.3519 2022/09/11 17:54:23 - mmengine - INFO - Epoch(train) [117][880/940] lr: 4.0000e-03 eta: 6:20:37 time: 0.7139 data_time: 0.0536 memory: 23705 grad_norm: 5.1049 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5934 loss_aux: 1.0272 loss: 2.6207 2022/09/11 17:54:37 - mmengine - INFO - Epoch(train) [117][900/940] lr: 4.0000e-03 eta: 6:20:19 time: 0.7160 data_time: 0.0275 memory: 23705 grad_norm: 4.9927 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6044 loss_aux: 1.0039 loss: 2.6083 2022/09/11 17:54:51 - mmengine - INFO - Epoch(train) [117][920/940] lr: 4.0000e-03 eta: 6:19:57 time: 0.6796 data_time: 0.0313 memory: 23705 grad_norm: 4.9522 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5484 loss_aux: 0.9848 loss: 2.5332 2022/09/11 17:55:04 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 17:55:04 - mmengine - INFO - Epoch(train) [117][940/940] lr: 4.0000e-03 eta: 6:19:31 time: 0.6434 data_time: 0.0339 memory: 23705 grad_norm: 5.3106 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.5608 loss_aux: 0.9965 loss: 2.5572 2022/09/11 17:55:04 - mmengine - INFO - Saving checkpoint at 117 epochs 2022/09/11 17:55:29 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 17:55:29 - mmengine - INFO - Epoch(train) [118][20/940] lr: 4.0000e-03 eta: 6:19:47 time: 0.9669 data_time: 0.3134 memory: 23705 grad_norm: 5.0186 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.5091 loss_aux: 0.9768 loss: 2.4859 2022/09/11 17:55:42 - mmengine - INFO - Epoch(train) [118][40/940] lr: 4.0000e-03 eta: 6:19:23 time: 0.6705 data_time: 0.0329 memory: 23705 grad_norm: 4.8999 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.4304 loss_aux: 0.9294 loss: 2.3598 2022/09/11 17:55:56 - mmengine - INFO - Epoch(train) [118][60/940] lr: 4.0000e-03 eta: 6:19:01 time: 0.6777 data_time: 0.0394 memory: 23705 grad_norm: 5.0001 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.4108 loss_aux: 0.9275 loss: 2.3383 2022/09/11 17:56:09 - mmengine - INFO - Epoch(train) [118][80/940] lr: 4.0000e-03 eta: 6:18:38 time: 0.6706 data_time: 0.0334 memory: 23705 grad_norm: 5.0381 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4546 loss_aux: 0.9478 loss: 2.4024 2022/09/11 17:56:23 - mmengine - INFO - Epoch(train) [118][100/940] lr: 4.0000e-03 eta: 6:18:19 time: 0.6990 data_time: 0.0390 memory: 23705 grad_norm: 4.9643 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.4843 loss_aux: 0.9350 loss: 2.4192 2022/09/11 17:56:37 - mmengine - INFO - Epoch(train) [118][120/940] lr: 4.0000e-03 eta: 6:17:57 time: 0.6770 data_time: 0.0313 memory: 23705 grad_norm: 4.9777 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5162 loss_aux: 0.9842 loss: 2.5004 2022/09/11 17:56:50 - mmengine - INFO - Epoch(train) [118][140/940] lr: 4.0000e-03 eta: 6:17:35 time: 0.6773 data_time: 0.0343 memory: 23705 grad_norm: 5.0288 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5006 loss_aux: 0.9870 loss: 2.4876 2022/09/11 17:57:04 - mmengine - INFO - Epoch(train) [118][160/940] lr: 4.0000e-03 eta: 6:17:14 time: 0.6824 data_time: 0.0347 memory: 23705 grad_norm: 4.8901 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4315 loss_aux: 0.9422 loss: 2.3737 2022/09/11 17:57:18 - mmengine - INFO - Epoch(train) [118][180/940] lr: 4.0000e-03 eta: 6:16:56 time: 0.7057 data_time: 0.0376 memory: 23705 grad_norm: 5.0030 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5322 loss_aux: 0.9857 loss: 2.5179 2022/09/11 17:57:32 - mmengine - INFO - Epoch(train) [118][200/940] lr: 4.0000e-03 eta: 6:16:34 time: 0.6742 data_time: 0.0306 memory: 23705 grad_norm: 4.9505 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.4946 loss_aux: 0.9819 loss: 2.4765 2022/09/11 17:57:46 - mmengine - INFO - Epoch(train) [118][220/940] lr: 4.0000e-03 eta: 6:16:15 time: 0.6991 data_time: 0.0415 memory: 23705 grad_norm: 5.0033 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5124 loss_aux: 0.9728 loss: 2.4852 2022/09/11 17:57:59 - mmengine - INFO - Epoch(train) [118][240/940] lr: 4.0000e-03 eta: 6:15:53 time: 0.6785 data_time: 0.0334 memory: 23705 grad_norm: 5.0077 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.4154 loss_aux: 0.9164 loss: 2.3318 2022/09/11 17:58:13 - mmengine - INFO - Epoch(train) [118][260/940] lr: 4.0000e-03 eta: 6:15:34 time: 0.6941 data_time: 0.0408 memory: 23705 grad_norm: 5.0179 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4602 loss_aux: 0.9552 loss: 2.4154 2022/09/11 17:58:27 - mmengine - INFO - Epoch(train) [118][280/940] lr: 4.0000e-03 eta: 6:15:12 time: 0.6773 data_time: 0.0309 memory: 23705 grad_norm: 5.0097 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4425 loss_aux: 0.9338 loss: 2.3763 2022/09/11 17:58:40 - mmengine - INFO - Epoch(train) [118][300/940] lr: 4.0000e-03 eta: 6:14:51 time: 0.6756 data_time: 0.0341 memory: 23705 grad_norm: 4.9919 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4765 loss_aux: 0.9794 loss: 2.4559 2022/09/11 17:58:54 - mmengine - INFO - Epoch(train) [118][320/940] lr: 4.0000e-03 eta: 6:14:29 time: 0.6775 data_time: 0.0358 memory: 23705 grad_norm: 5.0156 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.6056 loss_aux: 0.9871 loss: 2.5927 2022/09/11 17:59:07 - mmengine - INFO - Epoch(train) [118][340/940] lr: 4.0000e-03 eta: 6:14:10 time: 0.6928 data_time: 0.0434 memory: 23705 grad_norm: 5.0852 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4964 loss_aux: 0.9679 loss: 2.4642 2022/09/11 17:59:21 - mmengine - INFO - Epoch(train) [118][360/940] lr: 4.0000e-03 eta: 6:13:49 time: 0.6804 data_time: 0.0296 memory: 23705 grad_norm: 5.0217 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.4832 loss_aux: 0.9292 loss: 2.4124 2022/09/11 17:59:35 - mmengine - INFO - Epoch(train) [118][380/940] lr: 4.0000e-03 eta: 6:13:30 time: 0.6921 data_time: 0.0419 memory: 23705 grad_norm: 5.0853 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.6802 loss_aux: 1.0500 loss: 2.7302 2022/09/11 17:59:49 - mmengine - INFO - Epoch(train) [118][400/940] lr: 4.0000e-03 eta: 6:13:10 time: 0.6873 data_time: 0.0357 memory: 23705 grad_norm: 5.0438 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4248 loss_aux: 0.9021 loss: 2.3269 2022/09/11 18:00:06 - mmengine - INFO - Epoch(train) [118][420/940] lr: 4.0000e-03 eta: 6:13:10 time: 0.8528 data_time: 0.0433 memory: 23705 grad_norm: 5.0045 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5793 loss_aux: 0.9986 loss: 2.5779 2022/09/11 18:00:19 - mmengine - INFO - Epoch(train) [118][440/940] lr: 4.0000e-03 eta: 6:12:48 time: 0.6717 data_time: 0.0307 memory: 23705 grad_norm: 4.9854 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6238 loss_aux: 1.0085 loss: 2.6323 2022/09/11 18:00:33 - mmengine - INFO - Epoch(train) [118][460/940] lr: 4.0000e-03 eta: 6:12:29 time: 0.6940 data_time: 0.0354 memory: 23705 grad_norm: 5.0580 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5479 loss_aux: 0.9832 loss: 2.5311 2022/09/11 18:00:47 - mmengine - INFO - Epoch(train) [118][480/940] lr: 4.0000e-03 eta: 6:12:10 time: 0.6933 data_time: 0.0345 memory: 23705 grad_norm: 5.0332 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4214 loss_aux: 0.9246 loss: 2.3460 2022/09/11 18:01:01 - mmengine - INFO - Epoch(train) [118][500/940] lr: 4.0000e-03 eta: 6:11:50 time: 0.6885 data_time: 0.0394 memory: 23705 grad_norm: 4.9869 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.6077 loss_aux: 1.0121 loss: 2.6198 2022/09/11 18:01:14 - mmengine - INFO - Epoch(train) [118][520/940] lr: 4.0000e-03 eta: 6:11:29 time: 0.6744 data_time: 0.0295 memory: 23705 grad_norm: 5.0291 top1_acc: 0.4062 top5_acc: 0.8125 loss_cls: 1.7202 loss_aux: 1.0614 loss: 2.7815 2022/09/11 18:01:28 - mmengine - INFO - Epoch(train) [118][540/940] lr: 4.0000e-03 eta: 6:11:10 time: 0.6964 data_time: 0.0328 memory: 23705 grad_norm: 5.0889 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4078 loss_aux: 0.9443 loss: 2.3521 2022/09/11 18:01:42 - mmengine - INFO - Epoch(train) [118][560/940] lr: 4.0000e-03 eta: 6:10:50 time: 0.6855 data_time: 0.0342 memory: 23705 grad_norm: 5.0470 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.4757 loss_aux: 0.9623 loss: 2.4380 2022/09/11 18:01:56 - mmengine - INFO - Epoch(train) [118][580/940] lr: 4.0000e-03 eta: 6:10:31 time: 0.6887 data_time: 0.0388 memory: 23705 grad_norm: 5.0670 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.4663 loss_aux: 0.9450 loss: 2.4113 2022/09/11 18:02:09 - mmengine - INFO - Epoch(train) [118][600/940] lr: 4.0000e-03 eta: 6:10:10 time: 0.6704 data_time: 0.0310 memory: 23705 grad_norm: 5.0517 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.7079 loss_aux: 1.0570 loss: 2.7649 2022/09/11 18:02:23 - mmengine - INFO - Epoch(train) [118][620/940] lr: 4.0000e-03 eta: 6:09:49 time: 0.6802 data_time: 0.0382 memory: 23705 grad_norm: 4.9818 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4400 loss_aux: 0.9230 loss: 2.3629 2022/09/11 18:02:36 - mmengine - INFO - Epoch(train) [118][640/940] lr: 4.0000e-03 eta: 6:09:30 time: 0.6890 data_time: 0.0386 memory: 23705 grad_norm: 5.0730 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4745 loss_aux: 0.9881 loss: 2.4626 2022/09/11 18:02:50 - mmengine - INFO - Epoch(train) [118][660/940] lr: 4.0000e-03 eta: 6:09:10 time: 0.6840 data_time: 0.0402 memory: 23705 grad_norm: 5.0441 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.5603 loss_aux: 0.9811 loss: 2.5413 2022/09/11 18:03:04 - mmengine - INFO - Epoch(train) [118][680/940] lr: 4.0000e-03 eta: 6:08:51 time: 0.6885 data_time: 0.0332 memory: 23705 grad_norm: 5.0953 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5851 loss_aux: 1.0072 loss: 2.5922 2022/09/11 18:03:18 - mmengine - INFO - Epoch(train) [118][700/940] lr: 4.0000e-03 eta: 6:08:32 time: 0.6895 data_time: 0.0323 memory: 23705 grad_norm: 5.0872 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5993 loss_aux: 1.0099 loss: 2.6093 2022/09/11 18:03:31 - mmengine - INFO - Epoch(train) [118][720/940] lr: 4.0000e-03 eta: 6:08:12 time: 0.6801 data_time: 0.0369 memory: 23705 grad_norm: 5.1114 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.5244 loss_aux: 0.9791 loss: 2.5034 2022/09/11 18:03:45 - mmengine - INFO - Epoch(train) [118][740/940] lr: 4.0000e-03 eta: 6:07:53 time: 0.6892 data_time: 0.0368 memory: 23705 grad_norm: 5.0941 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.5777 loss_aux: 1.0334 loss: 2.6111 2022/09/11 18:03:59 - mmengine - INFO - Epoch(train) [118][760/940] lr: 4.0000e-03 eta: 6:07:35 time: 0.7000 data_time: 0.0386 memory: 23705 grad_norm: 5.0197 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5962 loss_aux: 1.0215 loss: 2.6177 2022/09/11 18:04:13 - mmengine - INFO - Epoch(train) [118][780/940] lr: 4.0000e-03 eta: 6:07:15 time: 0.6795 data_time: 0.0354 memory: 23705 grad_norm: 5.0707 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.5473 loss_aux: 0.9817 loss: 2.5291 2022/09/11 18:04:26 - mmengine - INFO - Epoch(train) [118][800/940] lr: 4.0000e-03 eta: 6:06:55 time: 0.6824 data_time: 0.0415 memory: 23705 grad_norm: 5.0864 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5505 loss_aux: 0.9733 loss: 2.5238 2022/09/11 18:04:41 - mmengine - INFO - Epoch(train) [118][820/940] lr: 4.0000e-03 eta: 6:06:39 time: 0.7141 data_time: 0.0406 memory: 23705 grad_norm: 5.1066 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6223 loss_aux: 1.0031 loss: 2.6254 2022/09/11 18:04:54 - mmengine - INFO - Epoch(train) [118][840/940] lr: 4.0000e-03 eta: 6:06:20 time: 0.6899 data_time: 0.0309 memory: 23705 grad_norm: 5.0003 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4493 loss_aux: 0.9557 loss: 2.4050 2022/09/11 18:05:08 - mmengine - INFO - Epoch(train) [118][860/940] lr: 4.0000e-03 eta: 6:06:01 time: 0.6851 data_time: 0.0386 memory: 23705 grad_norm: 5.1373 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5155 loss_aux: 0.9671 loss: 2.4825 2022/09/11 18:05:22 - mmengine - INFO - Epoch(train) [118][880/940] lr: 4.0000e-03 eta: 6:05:44 time: 0.7038 data_time: 0.0364 memory: 23705 grad_norm: 4.9734 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.4538 loss_aux: 0.9328 loss: 2.3867 2022/09/11 18:05:36 - mmengine - INFO - Epoch(train) [118][900/940] lr: 4.0000e-03 eta: 6:05:26 time: 0.6977 data_time: 0.0305 memory: 23705 grad_norm: 5.0519 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 1.4911 loss_aux: 0.9679 loss: 2.4590 2022/09/11 18:05:50 - mmengine - INFO - Epoch(train) [118][920/940] lr: 4.0000e-03 eta: 6:05:07 time: 0.6879 data_time: 0.0317 memory: 23705 grad_norm: 4.9561 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.5237 loss_aux: 0.9797 loss: 2.5034 2022/09/11 18:06:03 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 18:06:03 - mmengine - INFO - Epoch(train) [118][940/940] lr: 4.0000e-03 eta: 6:04:44 time: 0.6444 data_time: 0.0272 memory: 23705 grad_norm: 5.3331 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.5613 loss_aux: 1.0131 loss: 2.5743 2022/09/11 18:06:03 - mmengine - INFO - Saving checkpoint at 118 epochs 2022/09/11 18:06:27 - mmengine - INFO - Epoch(train) [119][20/940] lr: 4.0000e-03 eta: 6:04:54 time: 0.9562 data_time: 0.3105 memory: 23705 grad_norm: 4.9992 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4815 loss_aux: 0.9562 loss: 2.4376 2022/09/11 18:06:41 - mmengine - INFO - Epoch(train) [119][40/940] lr: 4.0000e-03 eta: 6:04:33 time: 0.6672 data_time: 0.0258 memory: 23705 grad_norm: 4.8937 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5663 loss_aux: 0.9990 loss: 2.5653 2022/09/11 18:06:54 - mmengine - INFO - Epoch(train) [119][60/940] lr: 4.0000e-03 eta: 6:04:12 time: 0.6760 data_time: 0.0316 memory: 23705 grad_norm: 5.1027 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.4920 loss_aux: 0.9549 loss: 2.4470 2022/09/11 18:07:08 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 18:07:08 - mmengine - INFO - Epoch(train) [119][80/940] lr: 4.0000e-03 eta: 6:03:54 time: 0.6936 data_time: 0.0334 memory: 23705 grad_norm: 4.9413 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5556 loss_aux: 1.0013 loss: 2.5569 2022/09/11 18:07:22 - mmengine - INFO - Epoch(train) [119][100/940] lr: 4.0000e-03 eta: 6:03:36 time: 0.6901 data_time: 0.0430 memory: 23705 grad_norm: 5.0305 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5739 loss_aux: 1.0040 loss: 2.5779 2022/09/11 18:07:36 - mmengine - INFO - Epoch(train) [119][120/940] lr: 4.0000e-03 eta: 6:03:17 time: 0.6848 data_time: 0.0296 memory: 23705 grad_norm: 5.0707 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5039 loss_aux: 0.9857 loss: 2.4896 2022/09/11 18:07:49 - mmengine - INFO - Epoch(train) [119][140/940] lr: 4.0000e-03 eta: 6:02:58 time: 0.6876 data_time: 0.0371 memory: 23705 grad_norm: 5.0381 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.5721 loss_aux: 0.9874 loss: 2.5595 2022/09/11 18:08:03 - mmengine - INFO - Epoch(train) [119][160/940] lr: 4.0000e-03 eta: 6:02:37 time: 0.6644 data_time: 0.0313 memory: 23705 grad_norm: 5.0773 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4360 loss_aux: 0.9608 loss: 2.3968 2022/09/11 18:08:17 - mmengine - INFO - Epoch(train) [119][180/940] lr: 4.0000e-03 eta: 6:02:20 time: 0.6985 data_time: 0.0466 memory: 23705 grad_norm: 5.1192 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5076 loss_aux: 0.9442 loss: 2.4518 2022/09/11 18:08:30 - mmengine - INFO - Epoch(train) [119][200/940] lr: 4.0000e-03 eta: 6:01:59 time: 0.6731 data_time: 0.0304 memory: 23705 grad_norm: 4.9644 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5135 loss_aux: 0.9647 loss: 2.4782 2022/09/11 18:08:43 - mmengine - INFO - Epoch(train) [119][220/940] lr: 4.0000e-03 eta: 6:01:39 time: 0.6709 data_time: 0.0317 memory: 23705 grad_norm: 4.9585 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.5329 loss_aux: 0.9763 loss: 2.5092 2022/09/11 18:08:57 - mmengine - INFO - Epoch(train) [119][240/940] lr: 4.0000e-03 eta: 6:01:20 time: 0.6805 data_time: 0.0372 memory: 23705 grad_norm: 5.0182 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.6211 loss_aux: 1.0355 loss: 2.6565 2022/09/11 18:09:11 - mmengine - INFO - Epoch(train) [119][260/940] lr: 4.0000e-03 eta: 6:01:02 time: 0.6919 data_time: 0.0380 memory: 23705 grad_norm: 5.0794 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4235 loss_aux: 0.9459 loss: 2.3694 2022/09/11 18:09:24 - mmengine - INFO - Epoch(train) [119][280/940] lr: 4.0000e-03 eta: 6:00:42 time: 0.6745 data_time: 0.0369 memory: 23705 grad_norm: 5.0128 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.4810 loss_aux: 0.9294 loss: 2.4104 2022/09/11 18:09:38 - mmengine - INFO - Epoch(train) [119][300/940] lr: 4.0000e-03 eta: 6:00:23 time: 0.6746 data_time: 0.0306 memory: 23705 grad_norm: 4.9807 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5150 loss_aux: 0.9895 loss: 2.5044 2022/09/11 18:09:51 - mmengine - INFO - Epoch(train) [119][320/940] lr: 4.0000e-03 eta: 6:00:03 time: 0.6771 data_time: 0.0347 memory: 23705 grad_norm: 5.0914 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.4675 loss_aux: 0.9439 loss: 2.4114 2022/09/11 18:10:05 - mmengine - INFO - Epoch(train) [119][340/940] lr: 4.0000e-03 eta: 5:59:45 time: 0.6859 data_time: 0.0350 memory: 23705 grad_norm: 5.0311 top1_acc: 0.7812 top5_acc: 0.7812 loss_cls: 1.5175 loss_aux: 0.9797 loss: 2.4972 2022/09/11 18:10:19 - mmengine - INFO - Epoch(train) [119][360/940] lr: 4.0000e-03 eta: 5:59:25 time: 0.6748 data_time: 0.0374 memory: 23705 grad_norm: 4.9966 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3939 loss_aux: 0.9114 loss: 2.3053 2022/09/11 18:10:33 - mmengine - INFO - Epoch(train) [119][380/940] lr: 4.0000e-03 eta: 5:59:08 time: 0.7027 data_time: 0.0382 memory: 23705 grad_norm: 5.1087 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.4576 loss_aux: 0.9600 loss: 2.4176 2022/09/11 18:10:46 - mmengine - INFO - Epoch(train) [119][400/940] lr: 4.0000e-03 eta: 5:58:48 time: 0.6712 data_time: 0.0361 memory: 23705 grad_norm: 5.0629 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4435 loss_aux: 0.9263 loss: 2.3698 2022/09/11 18:11:00 - mmengine - INFO - Epoch(train) [119][420/940] lr: 4.0000e-03 eta: 5:58:31 time: 0.6908 data_time: 0.0372 memory: 23705 grad_norm: 5.0252 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4743 loss_aux: 0.9319 loss: 2.4062 2022/09/11 18:11:14 - mmengine - INFO - Epoch(train) [119][440/940] lr: 4.0000e-03 eta: 5:58:12 time: 0.6862 data_time: 0.0324 memory: 23705 grad_norm: 5.1368 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.6123 loss_aux: 0.9706 loss: 2.5829 2022/09/11 18:11:28 - mmengine - INFO - Epoch(train) [119][460/940] lr: 4.0000e-03 eta: 5:57:55 time: 0.6932 data_time: 0.0329 memory: 23705 grad_norm: 5.0821 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5082 loss_aux: 0.9929 loss: 2.5011 2022/09/11 18:11:41 - mmengine - INFO - Epoch(train) [119][480/940] lr: 4.0000e-03 eta: 5:57:37 time: 0.6881 data_time: 0.0324 memory: 23705 grad_norm: 5.0582 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.5408 loss_aux: 0.9691 loss: 2.5099 2022/09/11 18:11:55 - mmengine - INFO - Epoch(train) [119][500/940] lr: 4.0000e-03 eta: 5:57:19 time: 0.6986 data_time: 0.0380 memory: 23705 grad_norm: 5.0493 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.4712 loss_aux: 0.9628 loss: 2.4340 2022/09/11 18:12:09 - mmengine - INFO - Epoch(train) [119][520/940] lr: 4.0000e-03 eta: 5:57:03 time: 0.7050 data_time: 0.0304 memory: 23705 grad_norm: 5.0717 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5524 loss_aux: 0.9734 loss: 2.5258 2022/09/11 18:12:23 - mmengine - INFO - Epoch(train) [119][540/940] lr: 4.0000e-03 eta: 5:56:45 time: 0.6867 data_time: 0.0322 memory: 23705 grad_norm: 5.0669 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5011 loss_aux: 0.9616 loss: 2.4627 2022/09/11 18:12:37 - mmengine - INFO - Epoch(train) [119][560/940] lr: 4.0000e-03 eta: 5:56:28 time: 0.6950 data_time: 0.0341 memory: 23705 grad_norm: 5.0421 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.5427 loss_aux: 0.9817 loss: 2.5244 2022/09/11 18:12:51 - mmengine - INFO - Epoch(train) [119][580/940] lr: 4.0000e-03 eta: 5:56:10 time: 0.6948 data_time: 0.0400 memory: 23705 grad_norm: 5.1950 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4593 loss_aux: 0.9594 loss: 2.4187 2022/09/11 18:13:05 - mmengine - INFO - Epoch(train) [119][600/940] lr: 4.0000e-03 eta: 5:55:53 time: 0.6892 data_time: 0.0367 memory: 23705 grad_norm: 5.0762 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4581 loss_aux: 0.9705 loss: 2.4285 2022/09/11 18:13:19 - mmengine - INFO - Epoch(train) [119][620/940] lr: 4.0000e-03 eta: 5:55:35 time: 0.6936 data_time: 0.0347 memory: 23705 grad_norm: 5.0272 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3372 loss_aux: 0.8905 loss: 2.2277 2022/09/11 18:13:32 - mmengine - INFO - Epoch(train) [119][640/940] lr: 4.0000e-03 eta: 5:55:18 time: 0.6931 data_time: 0.0349 memory: 23705 grad_norm: 5.0774 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.4329 loss_aux: 0.9222 loss: 2.3550 2022/09/11 18:13:47 - mmengine - INFO - Epoch(train) [119][660/940] lr: 4.0000e-03 eta: 5:55:03 time: 0.7267 data_time: 0.0373 memory: 23705 grad_norm: 5.0943 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5197 loss_aux: 0.9655 loss: 2.4852 2022/09/11 18:14:01 - mmengine - INFO - Epoch(train) [119][680/940] lr: 4.0000e-03 eta: 5:54:46 time: 0.6941 data_time: 0.0353 memory: 23705 grad_norm: 4.9930 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5637 loss_aux: 0.9913 loss: 2.5550 2022/09/11 18:14:15 - mmengine - INFO - Epoch(train) [119][700/940] lr: 4.0000e-03 eta: 5:54:30 time: 0.7008 data_time: 0.0331 memory: 23705 grad_norm: 5.1063 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5728 loss_aux: 0.9797 loss: 2.5525 2022/09/11 18:14:29 - mmengine - INFO - Epoch(train) [119][720/940] lr: 4.0000e-03 eta: 5:54:14 time: 0.7094 data_time: 0.0333 memory: 23705 grad_norm: 5.1157 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5497 loss_aux: 0.9584 loss: 2.5081 2022/09/11 18:14:43 - mmengine - INFO - Epoch(train) [119][740/940] lr: 4.0000e-03 eta: 5:53:58 time: 0.7063 data_time: 0.0408 memory: 23705 grad_norm: 5.0936 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4091 loss_aux: 0.9115 loss: 2.3207 2022/09/11 18:14:57 - mmengine - INFO - Epoch(train) [119][760/940] lr: 4.0000e-03 eta: 5:53:41 time: 0.6964 data_time: 0.0287 memory: 23705 grad_norm: 5.1355 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.5886 loss_aux: 1.0009 loss: 2.5895 2022/09/11 18:15:11 - mmengine - INFO - Epoch(train) [119][780/940] lr: 4.0000e-03 eta: 5:53:24 time: 0.6964 data_time: 0.0350 memory: 23705 grad_norm: 5.0010 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.4897 loss_aux: 0.9528 loss: 2.4425 2022/09/11 18:15:25 - mmengine - INFO - Epoch(train) [119][800/940] lr: 4.0000e-03 eta: 5:53:08 time: 0.7071 data_time: 0.0355 memory: 23705 grad_norm: 5.0515 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.5035 loss_aux: 0.9530 loss: 2.4565 2022/09/11 18:15:39 - mmengine - INFO - Epoch(train) [119][820/940] lr: 4.0000e-03 eta: 5:52:52 time: 0.7055 data_time: 0.0465 memory: 23705 grad_norm: 5.0190 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.4542 loss_aux: 0.9217 loss: 2.3759 2022/09/11 18:15:53 - mmengine - INFO - Epoch(train) [119][840/940] lr: 4.0000e-03 eta: 5:52:34 time: 0.6881 data_time: 0.0331 memory: 23705 grad_norm: 5.0019 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5122 loss_aux: 1.0048 loss: 2.5170 2022/09/11 18:16:07 - mmengine - INFO - Epoch(train) [119][860/940] lr: 4.0000e-03 eta: 5:52:17 time: 0.6992 data_time: 0.0334 memory: 23705 grad_norm: 5.0871 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4875 loss_aux: 0.9799 loss: 2.4675 2022/09/11 18:16:21 - mmengine - INFO - Epoch(train) [119][880/940] lr: 4.0000e-03 eta: 5:52:02 time: 0.7152 data_time: 0.0457 memory: 23705 grad_norm: 5.0489 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5353 loss_aux: 1.0254 loss: 2.5607 2022/09/11 18:16:35 - mmengine - INFO - Epoch(train) [119][900/940] lr: 4.0000e-03 eta: 5:51:45 time: 0.6924 data_time: 0.0268 memory: 23705 grad_norm: 5.0513 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.4723 loss_aux: 0.9593 loss: 2.4316 2022/09/11 18:16:49 - mmengine - INFO - Epoch(train) [119][920/940] lr: 4.0000e-03 eta: 5:51:28 time: 0.6913 data_time: 0.0403 memory: 23705 grad_norm: 5.0479 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4234 loss_aux: 0.9195 loss: 2.3428 2022/09/11 18:17:02 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 18:17:02 - mmengine - INFO - Epoch(train) [119][940/940] lr: 4.0000e-03 eta: 5:51:07 time: 0.6535 data_time: 0.0345 memory: 23705 grad_norm: 5.2818 top1_acc: 0.5714 top5_acc: 1.0000 loss_cls: 1.4774 loss_aux: 0.9647 loss: 2.4422 2022/09/11 18:17:02 - mmengine - INFO - Saving checkpoint at 119 epochs 2022/09/11 18:17:27 - mmengine - INFO - Epoch(train) [120][20/940] lr: 4.0000e-03 eta: 5:51:13 time: 0.9610 data_time: 0.3077 memory: 23705 grad_norm: 5.0352 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.4219 loss_aux: 0.9559 loss: 2.3778 2022/09/11 18:17:41 - mmengine - INFO - Epoch(train) [120][40/940] lr: 4.0000e-03 eta: 5:50:54 time: 0.6678 data_time: 0.0331 memory: 23705 grad_norm: 5.0432 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.4390 loss_aux: 0.9259 loss: 2.3649 2022/09/11 18:17:54 - mmengine - INFO - Epoch(train) [120][60/940] lr: 4.0000e-03 eta: 5:50:36 time: 0.6839 data_time: 0.0386 memory: 23705 grad_norm: 5.0457 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5890 loss_aux: 1.0546 loss: 2.6436 2022/09/11 18:18:08 - mmengine - INFO - Epoch(train) [120][80/940] lr: 4.0000e-03 eta: 5:50:18 time: 0.6806 data_time: 0.0390 memory: 23705 grad_norm: 5.1731 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5843 loss_aux: 1.0070 loss: 2.5913 2022/09/11 18:18:22 - mmengine - INFO - Epoch(train) [120][100/940] lr: 4.0000e-03 eta: 5:50:01 time: 0.6921 data_time: 0.0395 memory: 23705 grad_norm: 5.1260 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5701 loss_aux: 0.9935 loss: 2.5635 2022/09/11 18:18:35 - mmengine - INFO - Epoch(train) [120][120/940] lr: 4.0000e-03 eta: 5:49:43 time: 0.6823 data_time: 0.0352 memory: 23705 grad_norm: 5.0276 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4392 loss_aux: 0.9291 loss: 2.3683 2022/09/11 18:18:49 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 18:18:49 - mmengine - INFO - Epoch(train) [120][140/940] lr: 4.0000e-03 eta: 5:49:26 time: 0.6964 data_time: 0.0326 memory: 23705 grad_norm: 5.1786 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.5224 loss_aux: 0.9975 loss: 2.5199 2022/09/11 18:19:03 - mmengine - INFO - Epoch(train) [120][160/940] lr: 4.0000e-03 eta: 5:49:08 time: 0.6778 data_time: 0.0352 memory: 23705 grad_norm: 5.1078 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4922 loss_aux: 0.9511 loss: 2.4433 2022/09/11 18:19:17 - mmengine - INFO - Epoch(train) [120][180/940] lr: 4.0000e-03 eta: 5:48:52 time: 0.7097 data_time: 0.0458 memory: 23705 grad_norm: 5.0784 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5565 loss_aux: 1.0174 loss: 2.5739 2022/09/11 18:19:31 - mmengine - INFO - Epoch(train) [120][200/940] lr: 4.0000e-03 eta: 5:48:33 time: 0.6747 data_time: 0.0331 memory: 23705 grad_norm: 4.9873 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4701 loss_aux: 0.9486 loss: 2.4187 2022/09/11 18:19:44 - mmengine - INFO - Epoch(train) [120][220/940] lr: 4.0000e-03 eta: 5:48:16 time: 0.6880 data_time: 0.0357 memory: 23705 grad_norm: 5.0646 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.6519 loss_aux: 1.0097 loss: 2.6616 2022/09/11 18:19:58 - mmengine - INFO - Epoch(train) [120][240/940] lr: 4.0000e-03 eta: 5:47:58 time: 0.6850 data_time: 0.0379 memory: 23705 grad_norm: 5.0290 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5730 loss_aux: 0.9706 loss: 2.5436 2022/09/11 18:20:12 - mmengine - INFO - Epoch(train) [120][260/940] lr: 4.0000e-03 eta: 5:47:42 time: 0.6992 data_time: 0.0450 memory: 23705 grad_norm: 5.0753 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3434 loss_aux: 0.8946 loss: 2.2380 2022/09/11 18:20:26 - mmengine - INFO - Epoch(train) [120][280/940] lr: 4.0000e-03 eta: 5:47:24 time: 0.6808 data_time: 0.0320 memory: 23705 grad_norm: 5.1179 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5328 loss_aux: 0.9750 loss: 2.5078 2022/09/11 18:20:40 - mmengine - INFO - Epoch(train) [120][300/940] lr: 4.0000e-03 eta: 5:47:07 time: 0.6960 data_time: 0.0401 memory: 23705 grad_norm: 5.0328 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.4515 loss_aux: 0.9212 loss: 2.3727 2022/09/11 18:20:54 - mmengine - INFO - Epoch(train) [120][320/940] lr: 4.0000e-03 eta: 5:46:52 time: 0.7074 data_time: 0.0368 memory: 23705 grad_norm: 5.0762 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.5225 loss_aux: 0.9714 loss: 2.4939 2022/09/11 18:21:08 - mmengine - INFO - Epoch(train) [120][340/940] lr: 4.0000e-03 eta: 5:46:36 time: 0.7047 data_time: 0.0378 memory: 23705 grad_norm: 5.0973 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4546 loss_aux: 0.9443 loss: 2.3989 2022/09/11 18:21:22 - mmengine - INFO - Epoch(train) [120][360/940] lr: 4.0000e-03 eta: 5:46:20 time: 0.7043 data_time: 0.0328 memory: 23705 grad_norm: 5.0964 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4607 loss_aux: 0.9622 loss: 2.4229 2022/09/11 18:21:36 - mmengine - INFO - Epoch(train) [120][380/940] lr: 4.0000e-03 eta: 5:46:05 time: 0.7154 data_time: 0.0365 memory: 23705 grad_norm: 5.0022 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4031 loss_aux: 0.9126 loss: 2.3157 2022/09/11 18:21:52 - mmengine - INFO - Epoch(train) [120][400/940] lr: 4.0000e-03 eta: 5:45:56 time: 0.7909 data_time: 0.0470 memory: 23705 grad_norm: 5.0076 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4739 loss_aux: 0.9873 loss: 2.4612 2022/09/11 18:22:06 - mmengine - INFO - Epoch(train) [120][420/940] lr: 4.0000e-03 eta: 5:45:41 time: 0.7115 data_time: 0.0447 memory: 23705 grad_norm: 5.1368 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4458 loss_aux: 0.9425 loss: 2.3882 2022/09/11 18:22:21 - mmengine - INFO - Epoch(train) [120][440/940] lr: 4.0000e-03 eta: 5:45:26 time: 0.7126 data_time: 0.0324 memory: 23705 grad_norm: 5.0270 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4833 loss_aux: 0.9625 loss: 2.4458 2022/09/11 18:22:35 - mmengine - INFO - Epoch(train) [120][460/940] lr: 4.0000e-03 eta: 5:45:09 time: 0.6978 data_time: 0.0345 memory: 23705 grad_norm: 5.0693 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5534 loss_aux: 0.9877 loss: 2.5411 2022/09/11 18:22:49 - mmengine - INFO - Epoch(train) [120][480/940] lr: 4.0000e-03 eta: 5:44:54 time: 0.7078 data_time: 0.0356 memory: 23705 grad_norm: 5.1280 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4320 loss_aux: 0.9152 loss: 2.3472 2022/09/11 18:23:03 - mmengine - INFO - Epoch(train) [120][500/940] lr: 4.0000e-03 eta: 5:44:38 time: 0.7035 data_time: 0.0499 memory: 23705 grad_norm: 5.1656 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6048 loss_aux: 1.0222 loss: 2.6270 2022/09/11 18:23:17 - mmengine - INFO - Epoch(train) [120][520/940] lr: 4.0000e-03 eta: 5:44:22 time: 0.7131 data_time: 0.0334 memory: 23705 grad_norm: 5.0447 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3968 loss_aux: 0.9188 loss: 2.3156 2022/09/11 18:23:31 - mmengine - INFO - Epoch(train) [120][540/940] lr: 4.0000e-03 eta: 5:44:07 time: 0.7041 data_time: 0.0337 memory: 23705 grad_norm: 5.0350 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4427 loss_aux: 0.9334 loss: 2.3762 2022/09/11 18:23:45 - mmengine - INFO - Epoch(train) [120][560/940] lr: 4.0000e-03 eta: 5:43:50 time: 0.6974 data_time: 0.0338 memory: 23705 grad_norm: 5.0596 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4039 loss_aux: 0.9315 loss: 2.3353 2022/09/11 18:23:59 - mmengine - INFO - Epoch(train) [120][580/940] lr: 4.0000e-03 eta: 5:43:35 time: 0.7154 data_time: 0.0437 memory: 23705 grad_norm: 5.0560 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5899 loss_aux: 0.9871 loss: 2.5770 2022/09/11 18:24:14 - mmengine - INFO - Epoch(train) [120][600/940] lr: 4.0000e-03 eta: 5:43:21 time: 0.7191 data_time: 0.0316 memory: 23705 grad_norm: 5.0383 top1_acc: 0.5938 top5_acc: 0.9375 loss_cls: 1.4802 loss_aux: 0.9571 loss: 2.4373 2022/09/11 18:24:28 - mmengine - INFO - Epoch(train) [120][620/940] lr: 4.0000e-03 eta: 5:43:06 time: 0.7197 data_time: 0.0341 memory: 23705 grad_norm: 5.0995 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5142 loss_aux: 0.9759 loss: 2.4901 2022/09/11 18:24:42 - mmengine - INFO - Epoch(train) [120][640/940] lr: 4.0000e-03 eta: 5:42:50 time: 0.6998 data_time: 0.0411 memory: 23705 grad_norm: 5.0933 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4967 loss_aux: 0.9668 loss: 2.4635 2022/09/11 18:24:57 - mmengine - INFO - Epoch(train) [120][660/940] lr: 4.0000e-03 eta: 5:42:36 time: 0.7241 data_time: 0.0395 memory: 23705 grad_norm: 5.1562 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4217 loss_aux: 0.9367 loss: 2.3583 2022/09/11 18:25:11 - mmengine - INFO - Epoch(train) [120][680/940] lr: 4.0000e-03 eta: 5:42:21 time: 0.7195 data_time: 0.0375 memory: 23705 grad_norm: 5.0977 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6172 loss_aux: 1.0333 loss: 2.6506 2022/09/11 18:25:25 - mmengine - INFO - Epoch(train) [120][700/940] lr: 4.0000e-03 eta: 5:42:05 time: 0.7066 data_time: 0.0327 memory: 23705 grad_norm: 5.0768 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4508 loss_aux: 0.9514 loss: 2.4022 2022/09/11 18:25:39 - mmengine - INFO - Epoch(train) [120][720/940] lr: 4.0000e-03 eta: 5:41:50 time: 0.7099 data_time: 0.0345 memory: 23705 grad_norm: 5.1147 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5340 loss_aux: 0.9830 loss: 2.5170 2022/09/11 18:25:54 - mmengine - INFO - Epoch(train) [120][740/940] lr: 4.0000e-03 eta: 5:41:36 time: 0.7225 data_time: 0.0404 memory: 23705 grad_norm: 5.1555 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4615 loss_aux: 0.9561 loss: 2.4176 2022/09/11 18:26:08 - mmengine - INFO - Epoch(train) [120][760/940] lr: 4.0000e-03 eta: 5:41:22 time: 0.7293 data_time: 0.0310 memory: 23705 grad_norm: 5.1363 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5772 loss_aux: 0.9763 loss: 2.5535 2022/09/11 18:26:23 - mmengine - INFO - Epoch(train) [120][780/940] lr: 4.0000e-03 eta: 5:41:06 time: 0.7064 data_time: 0.0295 memory: 23705 grad_norm: 5.0967 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4291 loss_aux: 0.9402 loss: 2.3693 2022/09/11 18:26:37 - mmengine - INFO - Epoch(train) [120][800/940] lr: 4.0000e-03 eta: 5:40:50 time: 0.6971 data_time: 0.0305 memory: 23705 grad_norm: 5.1870 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.5389 loss_aux: 0.9536 loss: 2.4924 2022/09/11 18:26:51 - mmengine - INFO - Epoch(train) [120][820/940] lr: 4.0000e-03 eta: 5:40:35 time: 0.7122 data_time: 0.0420 memory: 23705 grad_norm: 5.1257 top1_acc: 0.6875 top5_acc: 0.7188 loss_cls: 1.3832 loss_aux: 0.8765 loss: 2.2596 2022/09/11 18:27:05 - mmengine - INFO - Epoch(train) [120][840/940] lr: 4.0000e-03 eta: 5:40:20 time: 0.7186 data_time: 0.0373 memory: 23705 grad_norm: 5.0124 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3851 loss_aux: 0.9236 loss: 2.3086 2022/09/11 18:27:19 - mmengine - INFO - Epoch(train) [120][860/940] lr: 4.0000e-03 eta: 5:40:05 time: 0.7136 data_time: 0.0331 memory: 23705 grad_norm: 5.0598 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4789 loss_aux: 0.9795 loss: 2.4584 2022/09/11 18:27:33 - mmengine - INFO - Epoch(train) [120][880/940] lr: 4.0000e-03 eta: 5:39:48 time: 0.6937 data_time: 0.0348 memory: 23705 grad_norm: 5.1933 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.5117 loss_aux: 0.9804 loss: 2.4920 2022/09/11 18:27:47 - mmengine - INFO - Epoch(train) [120][900/940] lr: 4.0000e-03 eta: 5:39:33 time: 0.7037 data_time: 0.0387 memory: 23705 grad_norm: 5.1109 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3681 loss_aux: 0.8927 loss: 2.2608 2022/09/11 18:28:01 - mmengine - INFO - Epoch(train) [120][920/940] lr: 4.0000e-03 eta: 5:39:16 time: 0.6962 data_time: 0.0271 memory: 23705 grad_norm: 5.0428 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.4262 loss_aux: 0.9164 loss: 2.3426 2022/09/11 18:28:14 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 18:28:14 - mmengine - INFO - Epoch(train) [120][940/940] lr: 4.0000e-03 eta: 5:38:56 time: 0.6426 data_time: 0.0262 memory: 23705 grad_norm: 5.3861 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.5700 loss_aux: 0.9714 loss: 2.5414 2022/09/11 18:28:14 - mmengine - INFO - Saving checkpoint at 120 epochs 2022/09/11 18:29:20 - mmengine - INFO - Epoch(val) [120][20/310] eta: 0:14:02 time: 2.9050 data_time: 2.8266 memory: 2130 2022/09/11 18:29:23 - mmengine - INFO - Epoch(val) [120][40/310] eta: 0:00:49 time: 0.1851 data_time: 0.1118 memory: 2130 2022/09/11 18:29:31 - mmengine - INFO - Epoch(val) [120][60/310] eta: 0:01:37 time: 0.3905 data_time: 0.3069 memory: 2130 2022/09/11 18:29:35 - mmengine - INFO - Epoch(val) [120][80/310] eta: 0:00:50 time: 0.2178 data_time: 0.1442 memory: 2130 2022/09/11 18:29:39 - mmengine - INFO - Epoch(val) [120][100/310] eta: 0:00:42 time: 0.2032 data_time: 0.1284 memory: 2130 2022/09/11 18:29:48 - mmengine - INFO - Epoch(val) [120][120/310] eta: 0:01:21 time: 0.4278 data_time: 0.3525 memory: 2130 2022/09/11 18:29:56 - mmengine - INFO - Epoch(val) [120][140/310] eta: 0:01:04 time: 0.3811 data_time: 0.3026 memory: 2130 2022/09/11 18:30:03 - mmengine - INFO - Epoch(val) [120][160/310] eta: 0:00:51 time: 0.3452 data_time: 0.2699 memory: 2130 2022/09/11 18:30:06 - mmengine - INFO - Epoch(val) [120][180/310] eta: 0:00:25 time: 0.1968 data_time: 0.1223 memory: 2130 2022/09/11 18:30:13 - mmengine - INFO - Epoch(val) [120][200/310] eta: 0:00:36 time: 0.3278 data_time: 0.2432 memory: 2130 2022/09/11 18:30:18 - mmengine - INFO - Epoch(val) [120][220/310] eta: 0:00:21 time: 0.2422 data_time: 0.1663 memory: 2130 2022/09/11 18:30:23 - mmengine - INFO - Epoch(val) [120][240/310] eta: 0:00:18 time: 0.2618 data_time: 0.1848 memory: 2130 2022/09/11 18:30:28 - mmengine - INFO - Epoch(val) [120][260/310] eta: 0:00:13 time: 0.2613 data_time: 0.1803 memory: 2130 2022/09/11 18:30:33 - mmengine - INFO - Epoch(val) [120][280/310] eta: 0:00:07 time: 0.2470 data_time: 0.1729 memory: 2130 2022/09/11 18:30:40 - mmengine - INFO - Epoch(val) [120][300/310] eta: 0:00:03 time: 0.3429 data_time: 0.2639 memory: 2130 2022/09/11 18:30:47 - mmengine - INFO - Epoch(val) [120][310/310] acc/top1: 0.6474 acc/top5: 0.8593 acc/mean1: 0.6473 2022/09/11 18:30:47 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb/best_acc/top1_epoch_100.pth is removed 2022/09/11 18:30:50 - mmengine - INFO - The best checkpoint with 0.6474 acc/top1 at 120 epoch is saved to best_acc/top1_epoch_120.pth. 2022/09/11 18:31:10 - mmengine - INFO - Epoch(train) [121][20/940] lr: 4.0000e-03 eta: 5:39:00 time: 0.9701 data_time: 0.3187 memory: 23708 grad_norm: 5.1160 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4455 loss_aux: 0.9437 loss: 2.3893 2022/09/11 18:31:23 - mmengine - INFO - Epoch(train) [121][40/940] lr: 4.0000e-03 eta: 5:38:43 time: 0.6807 data_time: 0.0241 memory: 23708 grad_norm: 5.0774 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.6115 loss_aux: 1.0174 loss: 2.6289 2022/09/11 18:31:37 - mmengine - INFO - Epoch(train) [121][60/940] lr: 4.0000e-03 eta: 5:38:26 time: 0.6865 data_time: 0.0399 memory: 23708 grad_norm: 5.1167 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4199 loss_aux: 0.9361 loss: 2.3561 2022/09/11 18:31:50 - mmengine - INFO - Epoch(train) [121][80/940] lr: 4.0000e-03 eta: 5:38:08 time: 0.6760 data_time: 0.0375 memory: 23708 grad_norm: 5.1138 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5234 loss_aux: 0.9524 loss: 2.4758 2022/09/11 18:32:05 - mmengine - INFO - Epoch(train) [121][100/940] lr: 4.0000e-03 eta: 5:37:52 time: 0.7017 data_time: 0.0399 memory: 23708 grad_norm: 5.1171 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4267 loss_aux: 0.9302 loss: 2.3568 2022/09/11 18:32:18 - mmengine - INFO - Epoch(train) [121][120/940] lr: 4.0000e-03 eta: 5:37:35 time: 0.6942 data_time: 0.0296 memory: 23708 grad_norm: 5.0741 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.4773 loss_aux: 0.9608 loss: 2.4381 2022/09/11 18:32:32 - mmengine - INFO - Epoch(train) [121][140/940] lr: 4.0000e-03 eta: 5:37:19 time: 0.6937 data_time: 0.0389 memory: 23708 grad_norm: 5.1428 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5629 loss_aux: 1.0259 loss: 2.5888 2022/09/11 18:32:46 - mmengine - INFO - Epoch(train) [121][160/940] lr: 4.0000e-03 eta: 5:37:02 time: 0.6804 data_time: 0.0433 memory: 23708 grad_norm: 5.1421 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5044 loss_aux: 0.9634 loss: 2.4678 2022/09/11 18:33:02 - mmengine - INFO - Epoch(train) [121][180/940] lr: 4.0000e-03 eta: 5:36:53 time: 0.8002 data_time: 0.1400 memory: 23708 grad_norm: 5.0891 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3910 loss_aux: 0.9114 loss: 2.3024 2022/09/11 18:33:16 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 18:33:16 - mmengine - INFO - Epoch(train) [121][200/940] lr: 4.0000e-03 eta: 5:36:37 time: 0.6936 data_time: 0.0338 memory: 23708 grad_norm: 5.1410 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4862 loss_aux: 0.9373 loss: 2.4235 2022/09/11 18:33:29 - mmengine - INFO - Epoch(train) [121][220/940] lr: 4.0000e-03 eta: 5:36:19 time: 0.6826 data_time: 0.0313 memory: 23708 grad_norm: 5.1405 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6143 loss_aux: 1.0196 loss: 2.6339 2022/09/11 18:33:43 - mmengine - INFO - Epoch(train) [121][240/940] lr: 4.0000e-03 eta: 5:36:02 time: 0.6881 data_time: 0.0365 memory: 23708 grad_norm: 5.0459 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4862 loss_aux: 0.9448 loss: 2.4309 2022/09/11 18:33:57 - mmengine - INFO - Epoch(train) [121][260/940] lr: 4.0000e-03 eta: 5:35:46 time: 0.6909 data_time: 0.0422 memory: 23708 grad_norm: 5.2033 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6397 loss_aux: 1.0139 loss: 2.6536 2022/09/11 18:34:11 - mmengine - INFO - Epoch(train) [121][280/940] lr: 4.0000e-03 eta: 5:35:30 time: 0.7005 data_time: 0.0405 memory: 23708 grad_norm: 5.1715 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6323 loss_aux: 0.9831 loss: 2.6154 2022/09/11 18:34:25 - mmengine - INFO - Epoch(train) [121][300/940] lr: 4.0000e-03 eta: 5:35:14 time: 0.6924 data_time: 0.0218 memory: 23708 grad_norm: 5.0800 top1_acc: 0.4375 top5_acc: 0.6562 loss_cls: 1.5077 loss_aux: 0.9819 loss: 2.4896 2022/09/11 18:34:39 - mmengine - INFO - Epoch(train) [121][320/940] lr: 4.0000e-03 eta: 5:34:57 time: 0.6874 data_time: 0.0358 memory: 23708 grad_norm: 5.0490 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6266 loss_aux: 1.0118 loss: 2.6383 2022/09/11 18:34:53 - mmengine - INFO - Epoch(train) [121][340/940] lr: 4.0000e-03 eta: 5:34:41 time: 0.7039 data_time: 0.0407 memory: 23708 grad_norm: 5.0725 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4920 loss_aux: 0.9546 loss: 2.4466 2022/09/11 18:35:07 - mmengine - INFO - Epoch(train) [121][360/940] lr: 4.0000e-03 eta: 5:34:25 time: 0.6967 data_time: 0.0346 memory: 23708 grad_norm: 5.0842 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5035 loss_aux: 0.9298 loss: 2.4333 2022/09/11 18:35:20 - mmengine - INFO - Epoch(train) [121][380/940] lr: 4.0000e-03 eta: 5:34:08 time: 0.6902 data_time: 0.0308 memory: 23708 grad_norm: 5.1052 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5270 loss_aux: 0.9874 loss: 2.5145 2022/09/11 18:35:34 - mmengine - INFO - Epoch(train) [121][400/940] lr: 4.0000e-03 eta: 5:33:52 time: 0.6909 data_time: 0.0391 memory: 23708 grad_norm: 5.1066 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.6455 loss_aux: 1.0355 loss: 2.6810 2022/09/11 18:35:48 - mmengine - INFO - Epoch(train) [121][420/940] lr: 4.0000e-03 eta: 5:33:36 time: 0.7038 data_time: 0.0370 memory: 23708 grad_norm: 5.1650 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4970 loss_aux: 0.9541 loss: 2.4511 2022/09/11 18:36:03 - mmengine - INFO - Epoch(train) [121][440/940] lr: 4.0000e-03 eta: 5:33:21 time: 0.7098 data_time: 0.0361 memory: 23708 grad_norm: 5.1263 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4156 loss_aux: 0.9189 loss: 2.3346 2022/09/11 18:36:17 - mmengine - INFO - Epoch(train) [121][460/940] lr: 4.0000e-03 eta: 5:33:06 time: 0.7091 data_time: 0.0325 memory: 23708 grad_norm: 5.1049 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.5809 loss_aux: 1.0423 loss: 2.6232 2022/09/11 18:36:31 - mmengine - INFO - Epoch(train) [121][480/940] lr: 4.0000e-03 eta: 5:32:50 time: 0.6924 data_time: 0.0374 memory: 23708 grad_norm: 5.2125 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5015 loss_aux: 0.9848 loss: 2.4863 2022/09/11 18:36:45 - mmengine - INFO - Epoch(train) [121][500/940] lr: 4.0000e-03 eta: 5:32:34 time: 0.7074 data_time: 0.0379 memory: 23708 grad_norm: 5.1213 top1_acc: 0.6875 top5_acc: 0.7188 loss_cls: 1.4923 loss_aux: 0.9549 loss: 2.4472 2022/09/11 18:36:58 - mmengine - INFO - Epoch(train) [121][520/940] lr: 4.0000e-03 eta: 5:32:17 time: 0.6856 data_time: 0.0293 memory: 23708 grad_norm: 5.1882 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6323 loss_aux: 1.0209 loss: 2.6532 2022/09/11 18:37:12 - mmengine - INFO - Epoch(train) [121][540/940] lr: 4.0000e-03 eta: 5:32:02 time: 0.6995 data_time: 0.0331 memory: 23708 grad_norm: 5.0676 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4474 loss_aux: 0.9357 loss: 2.3831 2022/09/11 18:37:26 - mmengine - INFO - Epoch(train) [121][560/940] lr: 4.0000e-03 eta: 5:31:45 time: 0.6917 data_time: 0.0370 memory: 23708 grad_norm: 5.0981 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.5736 loss_aux: 1.0051 loss: 2.5787 2022/09/11 18:37:41 - mmengine - INFO - Epoch(train) [121][580/940] lr: 4.0000e-03 eta: 5:31:30 time: 0.7113 data_time: 0.0379 memory: 23708 grad_norm: 5.0257 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4696 loss_aux: 0.9273 loss: 2.3968 2022/09/11 18:37:55 - mmengine - INFO - Epoch(train) [121][600/940] lr: 4.0000e-03 eta: 5:31:15 time: 0.7097 data_time: 0.0322 memory: 23708 grad_norm: 5.1660 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4879 loss_aux: 0.9489 loss: 2.4369 2022/09/11 18:38:09 - mmengine - INFO - Epoch(train) [121][620/940] lr: 4.0000e-03 eta: 5:31:01 time: 0.7300 data_time: 0.0348 memory: 23708 grad_norm: 5.1261 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4678 loss_aux: 0.9353 loss: 2.4032 2022/09/11 18:38:23 - mmengine - INFO - Epoch(train) [121][640/940] lr: 4.0000e-03 eta: 5:30:45 time: 0.6928 data_time: 0.0361 memory: 23708 grad_norm: 5.0836 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.4339 loss_aux: 0.9290 loss: 2.3629 2022/09/11 18:38:37 - mmengine - INFO - Epoch(train) [121][660/940] lr: 4.0000e-03 eta: 5:30:30 time: 0.7137 data_time: 0.0453 memory: 23708 grad_norm: 5.1302 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5510 loss_aux: 0.9944 loss: 2.5454 2022/09/11 18:38:51 - mmengine - INFO - Epoch(train) [121][680/940] lr: 4.0000e-03 eta: 5:30:15 time: 0.6986 data_time: 0.0356 memory: 23708 grad_norm: 5.1574 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.5679 loss_aux: 1.0306 loss: 2.5985 2022/09/11 18:39:05 - mmengine - INFO - Epoch(train) [121][700/940] lr: 4.0000e-03 eta: 5:29:59 time: 0.7017 data_time: 0.0329 memory: 23708 grad_norm: 5.1648 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.6627 loss_aux: 1.0384 loss: 2.7011 2022/09/11 18:39:19 - mmengine - INFO - Epoch(train) [121][720/940] lr: 4.0000e-03 eta: 5:29:43 time: 0.6994 data_time: 0.0421 memory: 23708 grad_norm: 5.1592 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.6089 loss_aux: 1.0014 loss: 2.6104 2022/09/11 18:39:33 - mmengine - INFO - Epoch(train) [121][740/940] lr: 4.0000e-03 eta: 5:29:27 time: 0.6998 data_time: 0.0366 memory: 23708 grad_norm: 5.1364 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4429 loss_aux: 0.9155 loss: 2.3584 2022/09/11 18:39:48 - mmengine - INFO - Epoch(train) [121][760/940] lr: 4.0000e-03 eta: 5:29:12 time: 0.7040 data_time: 0.0304 memory: 23708 grad_norm: 5.1543 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5188 loss_aux: 0.9963 loss: 2.5151 2022/09/11 18:40:02 - mmengine - INFO - Epoch(train) [121][780/940] lr: 4.0000e-03 eta: 5:28:58 time: 0.7249 data_time: 0.0518 memory: 23708 grad_norm: 5.1239 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.4917 loss_aux: 0.9531 loss: 2.4448 2022/09/11 18:40:16 - mmengine - INFO - Epoch(train) [121][800/940] lr: 4.0000e-03 eta: 5:28:42 time: 0.6996 data_time: 0.0363 memory: 23708 grad_norm: 5.2241 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.6172 loss_aux: 1.0273 loss: 2.6446 2022/09/11 18:40:30 - mmengine - INFO - Epoch(train) [121][820/940] lr: 4.0000e-03 eta: 5:28:27 time: 0.7044 data_time: 0.0344 memory: 23708 grad_norm: 5.1725 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.5326 loss_aux: 0.9526 loss: 2.4853 2022/09/11 18:40:44 - mmengine - INFO - Epoch(train) [121][840/940] lr: 4.0000e-03 eta: 5:28:11 time: 0.6949 data_time: 0.0361 memory: 23708 grad_norm: 5.1928 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4814 loss_aux: 0.9450 loss: 2.4264 2022/09/11 18:40:58 - mmengine - INFO - Epoch(train) [121][860/940] lr: 4.0000e-03 eta: 5:27:55 time: 0.7023 data_time: 0.0377 memory: 23708 grad_norm: 5.1158 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4484 loss_aux: 0.9217 loss: 2.3700 2022/09/11 18:41:12 - mmengine - INFO - Epoch(train) [121][880/940] lr: 4.0000e-03 eta: 5:27:39 time: 0.6928 data_time: 0.0381 memory: 23708 grad_norm: 5.0926 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4155 loss_aux: 0.9243 loss: 2.3397 2022/09/11 18:41:26 - mmengine - INFO - Epoch(train) [121][900/940] lr: 4.0000e-03 eta: 5:27:23 time: 0.6979 data_time: 0.0367 memory: 23708 grad_norm: 5.0260 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4599 loss_aux: 0.9365 loss: 2.3964 2022/09/11 18:41:40 - mmengine - INFO - Epoch(train) [121][920/940] lr: 4.0000e-03 eta: 5:27:08 time: 0.7014 data_time: 0.0316 memory: 23708 grad_norm: 5.1793 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4892 loss_aux: 0.9783 loss: 2.4675 2022/09/11 18:41:53 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 18:41:53 - mmengine - INFO - Epoch(train) [121][940/940] lr: 4.0000e-03 eta: 5:26:48 time: 0.6413 data_time: 0.0316 memory: 23708 grad_norm: 5.3973 top1_acc: 0.2857 top5_acc: 0.5714 loss_cls: 1.5315 loss_aux: 0.9535 loss: 2.4850 2022/09/11 18:41:53 - mmengine - INFO - Saving checkpoint at 121 epochs 2022/09/11 18:42:19 - mmengine - INFO - Epoch(train) [122][20/940] lr: 4.0000e-03 eta: 5:26:51 time: 0.9821 data_time: 0.2882 memory: 23708 grad_norm: 5.2412 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4718 loss_aux: 0.9417 loss: 2.4135 2022/09/11 18:42:33 - mmengine - INFO - Epoch(train) [122][40/940] lr: 4.0000e-03 eta: 5:26:34 time: 0.6818 data_time: 0.0349 memory: 23708 grad_norm: 5.1279 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.4408 loss_aux: 0.9250 loss: 2.3658 2022/09/11 18:42:46 - mmengine - INFO - Epoch(train) [122][60/940] lr: 4.0000e-03 eta: 5:26:16 time: 0.6673 data_time: 0.0355 memory: 23708 grad_norm: 5.0953 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3574 loss_aux: 0.9019 loss: 2.2593 2022/09/11 18:43:00 - mmengine - INFO - Epoch(train) [122][80/940] lr: 4.0000e-03 eta: 5:26:00 time: 0.6892 data_time: 0.0327 memory: 23708 grad_norm: 5.0113 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.4608 loss_aux: 0.9182 loss: 2.3791 2022/09/11 18:43:13 - mmengine - INFO - Epoch(train) [122][100/940] lr: 4.0000e-03 eta: 5:25:43 time: 0.6837 data_time: 0.0433 memory: 23708 grad_norm: 5.0627 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4177 loss_aux: 0.9108 loss: 2.3285 2022/09/11 18:43:27 - mmengine - INFO - Epoch(train) [122][120/940] lr: 4.0000e-03 eta: 5:25:26 time: 0.6762 data_time: 0.0331 memory: 23708 grad_norm: 4.9839 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4049 loss_aux: 0.9341 loss: 2.3390 2022/09/11 18:43:41 - mmengine - INFO - Epoch(train) [122][140/940] lr: 4.0000e-03 eta: 5:25:10 time: 0.6921 data_time: 0.0345 memory: 23708 grad_norm: 5.1669 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4793 loss_aux: 0.9391 loss: 2.4185 2022/09/11 18:43:55 - mmengine - INFO - Epoch(train) [122][160/940] lr: 4.0000e-03 eta: 5:24:54 time: 0.6920 data_time: 0.0441 memory: 23708 grad_norm: 5.1567 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4309 loss_aux: 0.9091 loss: 2.3401 2022/09/11 18:44:08 - mmengine - INFO - Epoch(train) [122][180/940] lr: 4.0000e-03 eta: 5:24:38 time: 0.6940 data_time: 0.0425 memory: 23708 grad_norm: 5.1439 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4830 loss_aux: 0.9463 loss: 2.4293 2022/09/11 18:44:22 - mmengine - INFO - Epoch(train) [122][200/940] lr: 4.0000e-03 eta: 5:24:22 time: 0.7020 data_time: 0.0398 memory: 23708 grad_norm: 5.0647 top1_acc: 0.5625 top5_acc: 0.9688 loss_cls: 1.4177 loss_aux: 0.9383 loss: 2.3559 2022/09/11 18:44:36 - mmengine - INFO - Epoch(train) [122][220/940] lr: 4.0000e-03 eta: 5:24:06 time: 0.6869 data_time: 0.0438 memory: 23708 grad_norm: 5.1219 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4821 loss_aux: 0.9551 loss: 2.4372 2022/09/11 18:44:50 - mmengine - INFO - Epoch(train) [122][240/940] lr: 4.0000e-03 eta: 5:23:50 time: 0.6900 data_time: 0.0384 memory: 23708 grad_norm: 5.0931 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4969 loss_aux: 0.9824 loss: 2.4793 2022/09/11 18:45:04 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 18:45:04 - mmengine - INFO - Epoch(train) [122][260/940] lr: 4.0000e-03 eta: 5:23:35 time: 0.7094 data_time: 0.0497 memory: 23708 grad_norm: 5.0930 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4112 loss_aux: 0.9334 loss: 2.3446 2022/09/11 18:45:19 - mmengine - INFO - Epoch(train) [122][280/940] lr: 4.0000e-03 eta: 5:23:20 time: 0.7195 data_time: 0.0368 memory: 23708 grad_norm: 5.1532 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4448 loss_aux: 0.9305 loss: 2.3753 2022/09/11 18:45:33 - mmengine - INFO - Epoch(train) [122][300/940] lr: 4.0000e-03 eta: 5:23:06 time: 0.7159 data_time: 0.0455 memory: 23708 grad_norm: 5.2377 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.5635 loss_aux: 1.0029 loss: 2.5665 2022/09/11 18:45:47 - mmengine - INFO - Epoch(train) [122][320/940] lr: 4.0000e-03 eta: 5:22:50 time: 0.6882 data_time: 0.0363 memory: 23708 grad_norm: 5.1128 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.7255 loss_aux: 1.0905 loss: 2.8160 2022/09/11 18:46:01 - mmengine - INFO - Epoch(train) [122][340/940] lr: 4.0000e-03 eta: 5:22:34 time: 0.7040 data_time: 0.0485 memory: 23708 grad_norm: 5.0477 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5894 loss_aux: 1.0084 loss: 2.5978 2022/09/11 18:46:15 - mmengine - INFO - Epoch(train) [122][360/940] lr: 4.0000e-03 eta: 5:22:19 time: 0.7034 data_time: 0.0320 memory: 23708 grad_norm: 5.1764 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3568 loss_aux: 0.9049 loss: 2.2617 2022/09/11 18:46:29 - mmengine - INFO - Epoch(train) [122][380/940] lr: 4.0000e-03 eta: 5:22:03 time: 0.6931 data_time: 0.0354 memory: 23708 grad_norm: 5.1304 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.6937 loss_aux: 1.0470 loss: 2.7406 2022/09/11 18:46:43 - mmengine - INFO - Epoch(train) [122][400/940] lr: 4.0000e-03 eta: 5:21:47 time: 0.6940 data_time: 0.0372 memory: 23708 grad_norm: 5.0663 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5573 loss_aux: 1.0019 loss: 2.5592 2022/09/11 18:46:57 - mmengine - INFO - Epoch(train) [122][420/940] lr: 4.0000e-03 eta: 5:21:32 time: 0.7079 data_time: 0.0430 memory: 23708 grad_norm: 5.0721 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.4467 loss_aux: 0.9251 loss: 2.3718 2022/09/11 18:47:11 - mmengine - INFO - Epoch(train) [122][440/940] lr: 4.0000e-03 eta: 5:21:17 time: 0.7163 data_time: 0.0315 memory: 23708 grad_norm: 5.0812 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4510 loss_aux: 0.9279 loss: 2.3790 2022/09/11 18:47:25 - mmengine - INFO - Epoch(train) [122][460/940] lr: 4.0000e-03 eta: 5:21:02 time: 0.7002 data_time: 0.0323 memory: 23708 grad_norm: 5.1785 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.5534 loss_aux: 1.0282 loss: 2.5816 2022/09/11 18:47:39 - mmengine - INFO - Epoch(train) [122][480/940] lr: 4.0000e-03 eta: 5:20:47 time: 0.7065 data_time: 0.0464 memory: 23708 grad_norm: 5.1655 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5135 loss_aux: 0.9738 loss: 2.4873 2022/09/11 18:47:53 - mmengine - INFO - Epoch(train) [122][500/940] lr: 4.0000e-03 eta: 5:20:32 time: 0.7123 data_time: 0.0394 memory: 23708 grad_norm: 5.1957 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5110 loss_aux: 0.9671 loss: 2.4781 2022/09/11 18:48:08 - mmengine - INFO - Epoch(train) [122][520/940] lr: 4.0000e-03 eta: 5:20:17 time: 0.7128 data_time: 0.0405 memory: 23708 grad_norm: 5.1621 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5118 loss_aux: 0.9851 loss: 2.4969 2022/09/11 18:48:22 - mmengine - INFO - Epoch(train) [122][540/940] lr: 4.0000e-03 eta: 5:20:03 time: 0.7226 data_time: 0.0326 memory: 23708 grad_norm: 5.0993 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.4349 loss_aux: 0.9373 loss: 2.3722 2022/09/11 18:48:36 - mmengine - INFO - Epoch(train) [122][560/940] lr: 4.0000e-03 eta: 5:19:48 time: 0.7096 data_time: 0.0355 memory: 23708 grad_norm: 5.1311 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2974 loss_aux: 0.8691 loss: 2.1666 2022/09/11 18:48:51 - mmengine - INFO - Epoch(train) [122][580/940] lr: 4.0000e-03 eta: 5:19:35 time: 0.7345 data_time: 0.0456 memory: 23708 grad_norm: 5.0950 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5473 loss_aux: 0.9769 loss: 2.5242 2022/09/11 18:49:05 - mmengine - INFO - Epoch(train) [122][600/940] lr: 4.0000e-03 eta: 5:19:20 time: 0.7090 data_time: 0.0336 memory: 23708 grad_norm: 5.1757 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.5163 loss_aux: 0.9842 loss: 2.5005 2022/09/11 18:49:19 - mmengine - INFO - Epoch(train) [122][620/940] lr: 4.0000e-03 eta: 5:19:05 time: 0.7085 data_time: 0.0357 memory: 23708 grad_norm: 5.2136 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.5728 loss_aux: 0.9983 loss: 2.5711 2022/09/11 18:49:34 - mmengine - INFO - Epoch(train) [122][640/940] lr: 4.0000e-03 eta: 5:18:50 time: 0.7083 data_time: 0.0440 memory: 23708 grad_norm: 5.1994 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3984 loss_aux: 0.9306 loss: 2.3290 2022/09/11 18:49:48 - mmengine - INFO - Epoch(train) [122][660/940] lr: 4.0000e-03 eta: 5:18:35 time: 0.7107 data_time: 0.0431 memory: 23708 grad_norm: 5.1300 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.4111 loss_aux: 0.9268 loss: 2.3379 2022/09/11 18:50:02 - mmengine - INFO - Epoch(train) [122][680/940] lr: 4.0000e-03 eta: 5:18:20 time: 0.7031 data_time: 0.0377 memory: 23708 grad_norm: 5.1326 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4605 loss_aux: 0.9380 loss: 2.3985 2022/09/11 18:50:16 - mmengine - INFO - Epoch(train) [122][700/940] lr: 4.0000e-03 eta: 5:18:04 time: 0.6926 data_time: 0.0383 memory: 23708 grad_norm: 5.2132 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5279 loss_aux: 0.9774 loss: 2.5054 2022/09/11 18:50:30 - mmengine - INFO - Epoch(train) [122][720/940] lr: 4.0000e-03 eta: 5:17:49 time: 0.7069 data_time: 0.0411 memory: 23708 grad_norm: 5.0852 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3148 loss_aux: 0.8677 loss: 2.1825 2022/09/11 18:50:44 - mmengine - INFO - Epoch(train) [122][740/940] lr: 4.0000e-03 eta: 5:17:34 time: 0.7099 data_time: 0.0423 memory: 23708 grad_norm: 5.2202 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4876 loss_aux: 0.9345 loss: 2.4221 2022/09/11 18:50:58 - mmengine - INFO - Epoch(train) [122][760/940] lr: 4.0000e-03 eta: 5:17:19 time: 0.6984 data_time: 0.0337 memory: 23708 grad_norm: 5.1605 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5680 loss_aux: 0.9848 loss: 2.5528 2022/09/11 18:51:12 - mmengine - INFO - Epoch(train) [122][780/940] lr: 4.0000e-03 eta: 5:17:03 time: 0.6935 data_time: 0.0390 memory: 23708 grad_norm: 5.3042 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.5092 loss_aux: 0.9843 loss: 2.4935 2022/09/11 18:51:26 - mmengine - INFO - Epoch(train) [122][800/940] lr: 4.0000e-03 eta: 5:16:47 time: 0.7007 data_time: 0.0395 memory: 23708 grad_norm: 5.2313 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.5101 loss_aux: 1.0099 loss: 2.5200 2022/09/11 18:51:40 - mmengine - INFO - Epoch(train) [122][820/940] lr: 4.0000e-03 eta: 5:16:32 time: 0.6937 data_time: 0.0410 memory: 23708 grad_norm: 5.1453 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.6108 loss_aux: 1.0135 loss: 2.6243 2022/09/11 18:51:54 - mmengine - INFO - Epoch(train) [122][840/940] lr: 4.0000e-03 eta: 5:16:16 time: 0.6968 data_time: 0.0332 memory: 23708 grad_norm: 5.1702 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5666 loss_aux: 0.9977 loss: 2.5643 2022/09/11 18:52:08 - mmengine - INFO - Epoch(train) [122][860/940] lr: 4.0000e-03 eta: 5:16:01 time: 0.7006 data_time: 0.0341 memory: 23708 grad_norm: 5.1974 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.6403 loss_aux: 1.0295 loss: 2.6698 2022/09/11 18:52:22 - mmengine - INFO - Epoch(train) [122][880/940] lr: 4.0000e-03 eta: 5:15:46 time: 0.7155 data_time: 0.0397 memory: 23708 grad_norm: 5.1614 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5567 loss_aux: 0.9948 loss: 2.5515 2022/09/11 18:52:36 - mmengine - INFO - Epoch(train) [122][900/940] lr: 4.0000e-03 eta: 5:15:31 time: 0.6968 data_time: 0.0430 memory: 23708 grad_norm: 5.1084 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4735 loss_aux: 0.9617 loss: 2.4351 2022/09/11 18:52:50 - mmengine - INFO - Epoch(train) [122][920/940] lr: 4.0000e-03 eta: 5:15:16 time: 0.7098 data_time: 0.0276 memory: 23708 grad_norm: 5.1643 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5358 loss_aux: 0.9752 loss: 2.5110 2022/09/11 18:53:03 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 18:53:03 - mmengine - INFO - Epoch(train) [122][940/940] lr: 4.0000e-03 eta: 5:14:58 time: 0.6530 data_time: 0.0391 memory: 23708 grad_norm: 5.5832 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.5086 loss_aux: 1.0003 loss: 2.5089 2022/09/11 18:53:03 - mmengine - INFO - Saving checkpoint at 122 epochs 2022/09/11 18:53:28 - mmengine - INFO - Epoch(train) [123][20/940] lr: 4.0000e-03 eta: 5:14:55 time: 0.9347 data_time: 0.2872 memory: 23708 grad_norm: 5.1645 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4685 loss_aux: 0.9853 loss: 2.4538 2022/09/11 18:53:42 - mmengine - INFO - Epoch(train) [123][40/940] lr: 4.0000e-03 eta: 5:14:39 time: 0.6855 data_time: 0.0331 memory: 23708 grad_norm: 5.1332 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2227 loss_aux: 0.8385 loss: 2.0613 2022/09/11 18:53:55 - mmengine - INFO - Epoch(train) [123][60/940] lr: 4.0000e-03 eta: 5:14:22 time: 0.6747 data_time: 0.0337 memory: 23708 grad_norm: 5.0683 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3616 loss_aux: 0.9205 loss: 2.2821 2022/09/11 18:54:09 - mmengine - INFO - Epoch(train) [123][80/940] lr: 4.0000e-03 eta: 5:14:06 time: 0.6719 data_time: 0.0321 memory: 23708 grad_norm: 5.2212 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3930 loss_aux: 0.9293 loss: 2.3224 2022/09/11 18:54:22 - mmengine - INFO - Epoch(train) [123][100/940] lr: 4.0000e-03 eta: 5:13:50 time: 0.6936 data_time: 0.0424 memory: 23708 grad_norm: 5.1836 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3619 loss_aux: 0.9143 loss: 2.2762 2022/09/11 18:54:36 - mmengine - INFO - Epoch(train) [123][120/940] lr: 4.0000e-03 eta: 5:13:34 time: 0.6934 data_time: 0.0326 memory: 23708 grad_norm: 5.1764 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4561 loss_aux: 0.9517 loss: 2.4078 2022/09/11 18:54:50 - mmengine - INFO - Epoch(train) [123][140/940] lr: 4.0000e-03 eta: 5:13:17 time: 0.6751 data_time: 0.0286 memory: 23708 grad_norm: 5.1723 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5615 loss_aux: 0.9441 loss: 2.5056 2022/09/11 18:55:03 - mmengine - INFO - Epoch(train) [123][160/940] lr: 4.0000e-03 eta: 5:13:01 time: 0.6839 data_time: 0.0385 memory: 23708 grad_norm: 5.1194 top1_acc: 0.9375 top5_acc: 0.9375 loss_cls: 1.3535 loss_aux: 0.8843 loss: 2.2378 2022/09/11 18:55:17 - mmengine - INFO - Epoch(train) [123][180/940] lr: 4.0000e-03 eta: 5:12:45 time: 0.6872 data_time: 0.0407 memory: 23708 grad_norm: 5.1935 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.5130 loss_aux: 0.9653 loss: 2.4783 2022/09/11 18:55:31 - mmengine - INFO - Epoch(train) [123][200/940] lr: 4.0000e-03 eta: 5:12:29 time: 0.6863 data_time: 0.0334 memory: 23708 grad_norm: 5.1519 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6027 loss_aux: 1.0335 loss: 2.6362 2022/09/11 18:55:45 - mmengine - INFO - Epoch(train) [123][220/940] lr: 4.0000e-03 eta: 5:12:13 time: 0.6854 data_time: 0.0329 memory: 23708 grad_norm: 5.2259 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.5779 loss_aux: 0.9998 loss: 2.5777 2022/09/11 18:55:58 - mmengine - INFO - Epoch(train) [123][240/940] lr: 4.0000e-03 eta: 5:11:57 time: 0.6852 data_time: 0.0347 memory: 23708 grad_norm: 5.1988 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5202 loss_aux: 0.9783 loss: 2.4985 2022/09/11 18:56:13 - mmengine - INFO - Epoch(train) [123][260/940] lr: 4.0000e-03 eta: 5:11:42 time: 0.7126 data_time: 0.0491 memory: 23708 grad_norm: 5.2276 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5211 loss_aux: 0.9731 loss: 2.4942 2022/09/11 18:56:26 - mmengine - INFO - Epoch(train) [123][280/940] lr: 4.0000e-03 eta: 5:11:26 time: 0.6860 data_time: 0.0312 memory: 23708 grad_norm: 5.1803 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5390 loss_aux: 0.9764 loss: 2.5154 2022/09/11 18:56:40 - mmengine - INFO - Epoch(train) [123][300/940] lr: 4.0000e-03 eta: 5:11:10 time: 0.6859 data_time: 0.0308 memory: 23708 grad_norm: 5.1140 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4407 loss_aux: 0.9283 loss: 2.3690 2022/09/11 18:56:54 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 18:56:54 - mmengine - INFO - Epoch(train) [123][320/940] lr: 4.0000e-03 eta: 5:10:55 time: 0.7139 data_time: 0.0432 memory: 23708 grad_norm: 5.1082 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3532 loss_aux: 0.9005 loss: 2.2537 2022/09/11 18:57:08 - mmengine - INFO - Epoch(train) [123][340/940] lr: 4.0000e-03 eta: 5:10:40 time: 0.6987 data_time: 0.0442 memory: 23708 grad_norm: 5.1675 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3244 loss_aux: 0.9002 loss: 2.2246 2022/09/11 18:57:22 - mmengine - INFO - Epoch(train) [123][360/940] lr: 4.0000e-03 eta: 5:10:25 time: 0.6933 data_time: 0.0318 memory: 23708 grad_norm: 5.1376 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.5563 loss_aux: 0.9655 loss: 2.5218 2022/09/11 18:57:36 - mmengine - INFO - Epoch(train) [123][380/940] lr: 4.0000e-03 eta: 5:10:08 time: 0.6783 data_time: 0.0324 memory: 23708 grad_norm: 5.2626 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3148 loss_aux: 0.8691 loss: 2.1839 2022/09/11 18:57:50 - mmengine - INFO - Epoch(train) [123][400/940] lr: 4.0000e-03 eta: 5:09:53 time: 0.6965 data_time: 0.0424 memory: 23708 grad_norm: 5.2589 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.4658 loss_aux: 0.9318 loss: 2.3976 2022/09/11 18:58:04 - mmengine - INFO - Epoch(train) [123][420/940] lr: 4.0000e-03 eta: 5:09:38 time: 0.7064 data_time: 0.0434 memory: 23708 grad_norm: 5.3134 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.4683 loss_aux: 0.9800 loss: 2.4484 2022/09/11 18:58:18 - mmengine - INFO - Epoch(train) [123][440/940] lr: 4.0000e-03 eta: 5:09:23 time: 0.7087 data_time: 0.0396 memory: 23708 grad_norm: 5.2202 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5254 loss_aux: 0.9462 loss: 2.4716 2022/09/11 18:58:32 - mmengine - INFO - Epoch(train) [123][460/940] lr: 4.0000e-03 eta: 5:09:07 time: 0.6957 data_time: 0.0348 memory: 23708 grad_norm: 5.3130 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.4336 loss_aux: 0.9094 loss: 2.3430 2022/09/11 18:58:46 - mmengine - INFO - Epoch(train) [123][480/940] lr: 4.0000e-03 eta: 5:08:52 time: 0.6918 data_time: 0.0368 memory: 23708 grad_norm: 5.2826 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4609 loss_aux: 0.9311 loss: 2.3921 2022/09/11 18:59:00 - mmengine - INFO - Epoch(train) [123][500/940] lr: 4.0000e-03 eta: 5:08:37 time: 0.7014 data_time: 0.0484 memory: 23708 grad_norm: 5.2529 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5480 loss_aux: 0.9942 loss: 2.5422 2022/09/11 18:59:14 - mmengine - INFO - Epoch(train) [123][520/940] lr: 4.0000e-03 eta: 5:08:22 time: 0.7083 data_time: 0.0365 memory: 23708 grad_norm: 5.1296 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4971 loss_aux: 0.9897 loss: 2.4867 2022/09/11 18:59:28 - mmengine - INFO - Epoch(train) [123][540/940] lr: 4.0000e-03 eta: 5:08:06 time: 0.6958 data_time: 0.0347 memory: 23708 grad_norm: 5.2295 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.5025 loss_aux: 0.9709 loss: 2.4735 2022/09/11 18:59:42 - mmengine - INFO - Epoch(train) [123][560/940] lr: 4.0000e-03 eta: 5:07:51 time: 0.6909 data_time: 0.0408 memory: 23708 grad_norm: 5.1961 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5933 loss_aux: 1.0491 loss: 2.6424 2022/09/11 18:59:56 - mmengine - INFO - Epoch(train) [123][580/940] lr: 4.0000e-03 eta: 5:07:35 time: 0.7002 data_time: 0.0451 memory: 23708 grad_norm: 5.1654 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4913 loss_aux: 0.9352 loss: 2.4265 2022/09/11 19:00:10 - mmengine - INFO - Epoch(train) [123][600/940] lr: 4.0000e-03 eta: 5:07:20 time: 0.7029 data_time: 0.0307 memory: 23708 grad_norm: 5.3459 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.5805 loss_aux: 1.0433 loss: 2.6239 2022/09/11 19:00:23 - mmengine - INFO - Epoch(train) [123][620/940] lr: 4.0000e-03 eta: 5:07:04 time: 0.6775 data_time: 0.0301 memory: 23708 grad_norm: 5.2217 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5394 loss_aux: 0.9686 loss: 2.5079 2022/09/11 19:00:37 - mmengine - INFO - Epoch(train) [123][640/940] lr: 4.0000e-03 eta: 5:06:48 time: 0.6934 data_time: 0.0432 memory: 23708 grad_norm: 5.0895 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5433 loss_aux: 0.9876 loss: 2.5308 2022/09/11 19:00:51 - mmengine - INFO - Epoch(train) [123][660/940] lr: 4.0000e-03 eta: 5:06:33 time: 0.7009 data_time: 0.0410 memory: 23708 grad_norm: 5.1261 top1_acc: 0.6250 top5_acc: 0.6562 loss_cls: 1.4396 loss_aux: 0.9339 loss: 2.3735 2022/09/11 19:01:05 - mmengine - INFO - Epoch(train) [123][680/940] lr: 4.0000e-03 eta: 5:06:18 time: 0.6906 data_time: 0.0357 memory: 23708 grad_norm: 5.1496 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3023 loss_aux: 0.8951 loss: 2.1974 2022/09/11 19:01:19 - mmengine - INFO - Epoch(train) [123][700/940] lr: 4.0000e-03 eta: 5:06:01 time: 0.6803 data_time: 0.0441 memory: 23708 grad_norm: 5.1267 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3758 loss_aux: 0.9031 loss: 2.2790 2022/09/11 19:01:32 - mmengine - INFO - Epoch(train) [123][720/940] lr: 4.0000e-03 eta: 5:05:45 time: 0.6847 data_time: 0.0389 memory: 23708 grad_norm: 5.1655 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4916 loss_aux: 0.9770 loss: 2.4686 2022/09/11 19:01:46 - mmengine - INFO - Epoch(train) [123][740/940] lr: 4.0000e-03 eta: 5:05:30 time: 0.6952 data_time: 0.0453 memory: 23708 grad_norm: 5.1839 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2957 loss_aux: 0.8718 loss: 2.1676 2022/09/11 19:02:01 - mmengine - INFO - Epoch(train) [123][760/940] lr: 4.0000e-03 eta: 5:05:16 time: 0.7154 data_time: 0.0334 memory: 23708 grad_norm: 5.2096 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.5603 loss_aux: 1.0035 loss: 2.5639 2022/09/11 19:02:14 - mmengine - INFO - Epoch(train) [123][780/940] lr: 4.0000e-03 eta: 5:05:00 time: 0.6898 data_time: 0.0393 memory: 23708 grad_norm: 5.1653 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.6329 loss_aux: 1.0182 loss: 2.6510 2022/09/11 19:02:28 - mmengine - INFO - Epoch(train) [123][800/940] lr: 4.0000e-03 eta: 5:04:45 time: 0.7016 data_time: 0.0368 memory: 23708 grad_norm: 5.1968 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.5288 loss_aux: 0.9709 loss: 2.4997 2022/09/11 19:02:42 - mmengine - INFO - Epoch(train) [123][820/940] lr: 4.0000e-03 eta: 5:04:29 time: 0.6936 data_time: 0.0444 memory: 23708 grad_norm: 5.2906 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5946 loss_aux: 1.0026 loss: 2.5972 2022/09/11 19:02:56 - mmengine - INFO - Epoch(train) [123][840/940] lr: 4.0000e-03 eta: 5:04:14 time: 0.6923 data_time: 0.0313 memory: 23708 grad_norm: 5.1970 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4677 loss_aux: 0.9482 loss: 2.4159 2022/09/11 19:03:10 - mmengine - INFO - Epoch(train) [123][860/940] lr: 4.0000e-03 eta: 5:03:58 time: 0.6886 data_time: 0.0334 memory: 23708 grad_norm: 5.1654 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5686 loss_aux: 1.0248 loss: 2.5934 2022/09/11 19:03:24 - mmengine - INFO - Epoch(train) [123][880/940] lr: 4.0000e-03 eta: 5:03:43 time: 0.7037 data_time: 0.0415 memory: 23708 grad_norm: 5.1600 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.6118 loss_aux: 1.0126 loss: 2.6244 2022/09/11 19:03:38 - mmengine - INFO - Epoch(train) [123][900/940] lr: 4.0000e-03 eta: 5:03:29 time: 0.7167 data_time: 0.0429 memory: 23708 grad_norm: 5.1470 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5622 loss_aux: 0.9826 loss: 2.5449 2022/09/11 19:03:52 - mmengine - INFO - Epoch(train) [123][920/940] lr: 4.0000e-03 eta: 5:03:13 time: 0.6873 data_time: 0.0298 memory: 23708 grad_norm: 5.3756 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.5472 loss_aux: 0.9728 loss: 2.5199 2022/09/11 19:04:05 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 19:04:05 - mmengine - INFO - Epoch(train) [123][940/940] lr: 4.0000e-03 eta: 5:02:56 time: 0.6493 data_time: 0.0313 memory: 23708 grad_norm: 5.4235 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.4098 loss_aux: 0.9207 loss: 2.3306 2022/09/11 19:04:05 - mmengine - INFO - Saving checkpoint at 123 epochs 2022/09/11 19:04:30 - mmengine - INFO - Epoch(train) [124][20/940] lr: 4.0000e-03 eta: 5:02:53 time: 0.9536 data_time: 0.2991 memory: 23708 grad_norm: 5.1632 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3942 loss_aux: 0.9131 loss: 2.3073 2022/09/11 19:04:44 - mmengine - INFO - Epoch(train) [124][40/940] lr: 4.0000e-03 eta: 5:02:37 time: 0.6817 data_time: 0.0300 memory: 23708 grad_norm: 5.1403 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5750 loss_aux: 0.9807 loss: 2.5557 2022/09/11 19:04:57 - mmengine - INFO - Epoch(train) [124][60/940] lr: 4.0000e-03 eta: 5:02:21 time: 0.6838 data_time: 0.0350 memory: 23708 grad_norm: 5.1052 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4680 loss_aux: 0.9377 loss: 2.4057 2022/09/11 19:05:11 - mmengine - INFO - Epoch(train) [124][80/940] lr: 4.0000e-03 eta: 5:02:05 time: 0.6854 data_time: 0.0454 memory: 23708 grad_norm: 5.1539 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5977 loss_aux: 1.0200 loss: 2.6177 2022/09/11 19:05:25 - mmengine - INFO - Epoch(train) [124][100/940] lr: 4.0000e-03 eta: 5:01:50 time: 0.6974 data_time: 0.0444 memory: 23708 grad_norm: 5.2290 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.4418 loss_aux: 0.9379 loss: 2.3797 2022/09/11 19:05:39 - mmengine - INFO - Epoch(train) [124][120/940] lr: 4.0000e-03 eta: 5:01:35 time: 0.7016 data_time: 0.0358 memory: 23708 grad_norm: 5.2238 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5140 loss_aux: 0.9699 loss: 2.4839 2022/09/11 19:05:53 - mmengine - INFO - Epoch(train) [124][140/940] lr: 4.0000e-03 eta: 5:01:19 time: 0.6942 data_time: 0.0411 memory: 23708 grad_norm: 5.2842 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4026 loss_aux: 0.9719 loss: 2.3745 2022/09/11 19:06:07 - mmengine - INFO - Epoch(train) [124][160/940] lr: 4.0000e-03 eta: 5:01:05 time: 0.7094 data_time: 0.0370 memory: 23708 grad_norm: 5.2016 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.6025 loss_aux: 1.0397 loss: 2.6421 2022/09/11 19:06:21 - mmengine - INFO - Epoch(train) [124][180/940] lr: 4.0000e-03 eta: 5:00:50 time: 0.6991 data_time: 0.0385 memory: 23708 grad_norm: 5.2781 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4406 loss_aux: 0.9516 loss: 2.3922 2022/09/11 19:06:35 - mmengine - INFO - Epoch(train) [124][200/940] lr: 4.0000e-03 eta: 5:00:34 time: 0.6818 data_time: 0.0363 memory: 23708 grad_norm: 5.0836 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4451 loss_aux: 0.9338 loss: 2.3789 2022/09/11 19:06:48 - mmengine - INFO - Epoch(train) [124][220/940] lr: 4.0000e-03 eta: 5:00:18 time: 0.6879 data_time: 0.0411 memory: 23708 grad_norm: 5.2246 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4794 loss_aux: 0.9579 loss: 2.4373 2022/09/11 19:07:02 - mmengine - INFO - Epoch(train) [124][240/940] lr: 4.0000e-03 eta: 5:00:03 time: 0.6977 data_time: 0.0413 memory: 23708 grad_norm: 5.0525 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4008 loss_aux: 0.9083 loss: 2.3091 2022/09/11 19:07:16 - mmengine - INFO - Epoch(train) [124][260/940] lr: 4.0000e-03 eta: 4:59:48 time: 0.7005 data_time: 0.0368 memory: 23708 grad_norm: 5.1753 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4838 loss_aux: 0.9459 loss: 2.4297 2022/09/11 19:07:30 - mmengine - INFO - Epoch(train) [124][280/940] lr: 4.0000e-03 eta: 4:59:32 time: 0.6866 data_time: 0.0386 memory: 23708 grad_norm: 5.2413 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5278 loss_aux: 1.0024 loss: 2.5303 2022/09/11 19:07:44 - mmengine - INFO - Epoch(train) [124][300/940] lr: 4.0000e-03 eta: 4:59:16 time: 0.6823 data_time: 0.0360 memory: 23708 grad_norm: 5.2446 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.5288 loss_aux: 1.0166 loss: 2.5453 2022/09/11 19:07:57 - mmengine - INFO - Epoch(train) [124][320/940] lr: 4.0000e-03 eta: 4:59:00 time: 0.6773 data_time: 0.0364 memory: 23708 grad_norm: 5.2053 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.5035 loss_aux: 0.9759 loss: 2.4795 2022/09/11 19:08:11 - mmengine - INFO - Epoch(train) [124][340/940] lr: 4.0000e-03 eta: 4:58:45 time: 0.6949 data_time: 0.0378 memory: 23708 grad_norm: 5.2896 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4552 loss_aux: 0.9904 loss: 2.4456 2022/09/11 19:08:25 - mmengine - INFO - Epoch(train) [124][360/940] lr: 4.0000e-03 eta: 4:58:29 time: 0.6882 data_time: 0.0357 memory: 23708 grad_norm: 5.1987 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5094 loss_aux: 0.9891 loss: 2.4985 2022/09/11 19:08:39 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 19:08:39 - mmengine - INFO - Epoch(train) [124][380/940] lr: 4.0000e-03 eta: 4:58:13 time: 0.6905 data_time: 0.0404 memory: 23708 grad_norm: 5.2505 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.4671 loss_aux: 0.9649 loss: 2.4320 2022/09/11 19:08:53 - mmengine - INFO - Epoch(train) [124][400/940] lr: 4.0000e-03 eta: 4:57:58 time: 0.6970 data_time: 0.0378 memory: 23708 grad_norm: 5.2136 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3978 loss_aux: 0.9071 loss: 2.3050 2022/09/11 19:09:07 - mmengine - INFO - Epoch(train) [124][420/940] lr: 4.0000e-03 eta: 4:57:43 time: 0.6997 data_time: 0.0456 memory: 23708 grad_norm: 5.1631 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.5667 loss_aux: 0.9935 loss: 2.5602 2022/09/11 19:09:20 - mmengine - INFO - Epoch(train) [124][440/940] lr: 4.0000e-03 eta: 4:57:28 time: 0.6849 data_time: 0.0372 memory: 23708 grad_norm: 5.3571 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.5935 loss_aux: 1.0218 loss: 2.6153 2022/09/11 19:09:35 - mmengine - INFO - Epoch(train) [124][460/940] lr: 4.0000e-03 eta: 4:57:14 time: 0.7243 data_time: 0.0336 memory: 23708 grad_norm: 5.3029 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5069 loss_aux: 0.9703 loss: 2.4772 2022/09/11 19:09:49 - mmengine - INFO - Epoch(train) [124][480/940] lr: 4.0000e-03 eta: 4:56:59 time: 0.7090 data_time: 0.0424 memory: 23708 grad_norm: 5.3115 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4444 loss_aux: 0.9342 loss: 2.3785 2022/09/11 19:10:03 - mmengine - INFO - Epoch(train) [124][500/940] lr: 4.0000e-03 eta: 4:56:45 time: 0.7156 data_time: 0.0456 memory: 23708 grad_norm: 5.2865 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4497 loss_aux: 0.9764 loss: 2.4261 2022/09/11 19:10:18 - mmengine - INFO - Epoch(train) [124][520/940] lr: 4.0000e-03 eta: 4:56:30 time: 0.7096 data_time: 0.0420 memory: 23708 grad_norm: 5.3200 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.5292 loss_aux: 0.9670 loss: 2.4962 2022/09/11 19:10:32 - mmengine - INFO - Epoch(train) [124][540/940] lr: 4.0000e-03 eta: 4:56:16 time: 0.7174 data_time: 0.0436 memory: 23708 grad_norm: 5.3048 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5286 loss_aux: 0.9979 loss: 2.5265 2022/09/11 19:10:46 - mmengine - INFO - Epoch(train) [124][560/940] lr: 4.0000e-03 eta: 4:56:01 time: 0.6949 data_time: 0.0407 memory: 23708 grad_norm: 5.1554 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.5884 loss_aux: 0.9889 loss: 2.5772 2022/09/11 19:11:00 - mmengine - INFO - Epoch(train) [124][580/940] lr: 4.0000e-03 eta: 4:55:46 time: 0.7088 data_time: 0.0396 memory: 23708 grad_norm: 5.1423 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4869 loss_aux: 0.9452 loss: 2.4321 2022/09/11 19:11:15 - mmengine - INFO - Epoch(train) [124][600/940] lr: 4.0000e-03 eta: 4:55:32 time: 0.7255 data_time: 0.0385 memory: 23708 grad_norm: 5.3277 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5715 loss_aux: 0.9907 loss: 2.5622 2022/09/11 19:11:29 - mmengine - INFO - Epoch(train) [124][620/940] lr: 4.0000e-03 eta: 4:55:18 time: 0.7187 data_time: 0.0395 memory: 23708 grad_norm: 5.3580 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4838 loss_aux: 0.9618 loss: 2.4457 2022/09/11 19:11:43 - mmengine - INFO - Epoch(train) [124][640/940] lr: 4.0000e-03 eta: 4:55:03 time: 0.7051 data_time: 0.0375 memory: 23708 grad_norm: 5.2293 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5475 loss_aux: 0.9925 loss: 2.5400 2022/09/11 19:11:57 - mmengine - INFO - Epoch(train) [124][660/940] lr: 4.0000e-03 eta: 4:54:48 time: 0.7058 data_time: 0.0397 memory: 23708 grad_norm: 5.1780 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.5944 loss_aux: 1.0131 loss: 2.6075 2022/09/11 19:12:11 - mmengine - INFO - Epoch(train) [124][680/940] lr: 4.0000e-03 eta: 4:54:34 time: 0.7072 data_time: 0.0368 memory: 23708 grad_norm: 5.2226 top1_acc: 0.4062 top5_acc: 0.6562 loss_cls: 1.6041 loss_aux: 1.0314 loss: 2.6354 2022/09/11 19:12:25 - mmengine - INFO - Epoch(train) [124][700/940] lr: 4.0000e-03 eta: 4:54:19 time: 0.7066 data_time: 0.0371 memory: 23708 grad_norm: 5.1296 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4343 loss_aux: 0.9093 loss: 2.3436 2022/09/11 19:12:39 - mmengine - INFO - Epoch(train) [124][720/940] lr: 4.0000e-03 eta: 4:54:04 time: 0.6977 data_time: 0.0439 memory: 23708 grad_norm: 5.1311 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.4190 loss_aux: 0.9279 loss: 2.3469 2022/09/11 19:12:54 - mmengine - INFO - Epoch(train) [124][740/940] lr: 4.0000e-03 eta: 4:53:49 time: 0.7063 data_time: 0.0423 memory: 23708 grad_norm: 5.1369 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5075 loss_aux: 0.9612 loss: 2.4687 2022/09/11 19:13:08 - mmengine - INFO - Epoch(train) [124][760/940] lr: 4.0000e-03 eta: 4:53:34 time: 0.7003 data_time: 0.0389 memory: 23708 grad_norm: 5.2146 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4465 loss_aux: 0.9354 loss: 2.3819 2022/09/11 19:13:22 - mmengine - INFO - Epoch(train) [124][780/940] lr: 4.0000e-03 eta: 4:53:19 time: 0.7029 data_time: 0.0381 memory: 23708 grad_norm: 5.1437 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3932 loss_aux: 0.9271 loss: 2.3203 2022/09/11 19:13:36 - mmengine - INFO - Epoch(train) [124][800/940] lr: 4.0000e-03 eta: 4:53:04 time: 0.6961 data_time: 0.0348 memory: 23708 grad_norm: 5.3054 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4841 loss_aux: 0.9602 loss: 2.4443 2022/09/11 19:13:50 - mmengine - INFO - Epoch(train) [124][820/940] lr: 4.0000e-03 eta: 4:52:49 time: 0.7010 data_time: 0.0388 memory: 23708 grad_norm: 5.2600 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.4727 loss_aux: 0.9401 loss: 2.4129 2022/09/11 19:14:04 - mmengine - INFO - Epoch(train) [124][840/940] lr: 4.0000e-03 eta: 4:52:34 time: 0.7040 data_time: 0.0418 memory: 23708 grad_norm: 5.3203 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5612 loss_aux: 0.9851 loss: 2.5463 2022/09/11 19:14:18 - mmengine - INFO - Epoch(train) [124][860/940] lr: 4.0000e-03 eta: 4:52:20 time: 0.7078 data_time: 0.0376 memory: 23708 grad_norm: 5.2783 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4374 loss_aux: 0.9359 loss: 2.3734 2022/09/11 19:14:32 - mmengine - INFO - Epoch(train) [124][880/940] lr: 4.0000e-03 eta: 4:52:05 time: 0.7048 data_time: 0.0385 memory: 23708 grad_norm: 5.2436 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4979 loss_aux: 0.9677 loss: 2.4656 2022/09/11 19:14:46 - mmengine - INFO - Epoch(train) [124][900/940] lr: 4.0000e-03 eta: 4:51:50 time: 0.7031 data_time: 0.0429 memory: 23708 grad_norm: 5.2726 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5217 loss_aux: 0.9734 loss: 2.4951 2022/09/11 19:15:00 - mmengine - INFO - Epoch(train) [124][920/940] lr: 4.0000e-03 eta: 4:51:35 time: 0.6867 data_time: 0.0347 memory: 23708 grad_norm: 5.2746 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5414 loss_aux: 0.9603 loss: 2.5017 2022/09/11 19:15:13 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 19:15:14 - mmengine - INFO - Epoch(train) [124][940/940] lr: 4.0000e-03 eta: 4:51:19 time: 0.6876 data_time: 0.0452 memory: 23708 grad_norm: 5.4854 top1_acc: 0.4286 top5_acc: 0.5714 loss_cls: 1.6071 loss_aux: 1.0161 loss: 2.6231 2022/09/11 19:15:14 - mmengine - INFO - Saving checkpoint at 124 epochs 2022/09/11 19:15:39 - mmengine - INFO - Epoch(train) [125][20/940] lr: 4.0000e-03 eta: 4:51:16 time: 0.9799 data_time: 0.3108 memory: 23708 grad_norm: 5.1721 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4940 loss_aux: 0.9642 loss: 2.4582 2022/09/11 19:15:53 - mmengine - INFO - Epoch(train) [125][40/940] lr: 4.0000e-03 eta: 4:51:01 time: 0.6858 data_time: 0.0314 memory: 23708 grad_norm: 5.2496 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4539 loss_aux: 0.9076 loss: 2.3615 2022/09/11 19:16:06 - mmengine - INFO - Epoch(train) [125][60/940] lr: 4.0000e-03 eta: 4:50:44 time: 0.6663 data_time: 0.0330 memory: 23708 grad_norm: 5.2593 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5533 loss_aux: 1.0174 loss: 2.5707 2022/09/11 19:16:20 - mmengine - INFO - Epoch(train) [125][80/940] lr: 4.0000e-03 eta: 4:50:29 time: 0.6852 data_time: 0.0349 memory: 23708 grad_norm: 5.2218 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3593 loss_aux: 0.8913 loss: 2.2506 2022/09/11 19:16:34 - mmengine - INFO - Epoch(train) [125][100/940] lr: 4.0000e-03 eta: 4:50:13 time: 0.6966 data_time: 0.0478 memory: 23708 grad_norm: 5.2059 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5123 loss_aux: 0.9854 loss: 2.4976 2022/09/11 19:16:48 - mmengine - INFO - Epoch(train) [125][120/940] lr: 4.0000e-03 eta: 4:49:58 time: 0.6993 data_time: 0.0379 memory: 23708 grad_norm: 5.2428 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4639 loss_aux: 0.9720 loss: 2.4359 2022/09/11 19:17:02 - mmengine - INFO - Epoch(train) [125][140/940] lr: 4.0000e-03 eta: 4:49:43 time: 0.6868 data_time: 0.0322 memory: 23708 grad_norm: 5.3350 top1_acc: 0.7188 top5_acc: 0.7500 loss_cls: 1.4623 loss_aux: 0.9524 loss: 2.4147 2022/09/11 19:17:15 - mmengine - INFO - Epoch(train) [125][160/940] lr: 4.0000e-03 eta: 4:49:28 time: 0.6912 data_time: 0.0405 memory: 23708 grad_norm: 5.1964 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.5399 loss_aux: 0.9921 loss: 2.5320 2022/09/11 19:17:29 - mmengine - INFO - Epoch(train) [125][180/940] lr: 4.0000e-03 eta: 4:49:13 time: 0.6997 data_time: 0.0434 memory: 23708 grad_norm: 5.2068 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.4270 loss_aux: 0.9499 loss: 2.3769 2022/09/11 19:17:43 - mmengine - INFO - Epoch(train) [125][200/940] lr: 4.0000e-03 eta: 4:48:57 time: 0.6936 data_time: 0.0401 memory: 23708 grad_norm: 5.2204 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4982 loss_aux: 0.9291 loss: 2.4273 2022/09/11 19:17:57 - mmengine - INFO - Epoch(train) [125][220/940] lr: 4.0000e-03 eta: 4:48:42 time: 0.6991 data_time: 0.0351 memory: 23708 grad_norm: 5.3653 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5415 loss_aux: 1.0170 loss: 2.5585 2022/09/11 19:18:11 - mmengine - INFO - Epoch(train) [125][240/940] lr: 4.0000e-03 eta: 4:48:27 time: 0.6887 data_time: 0.0399 memory: 23708 grad_norm: 5.4123 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4811 loss_aux: 0.9796 loss: 2.4608 2022/09/11 19:18:25 - mmengine - INFO - Epoch(train) [125][260/940] lr: 4.0000e-03 eta: 4:48:13 time: 0.7148 data_time: 0.0469 memory: 23708 grad_norm: 5.2619 top1_acc: 0.4688 top5_acc: 0.9062 loss_cls: 1.3454 loss_aux: 0.9160 loss: 2.2613 2022/09/11 19:18:40 - mmengine - INFO - Epoch(train) [125][280/940] lr: 4.0000e-03 eta: 4:47:58 time: 0.7104 data_time: 0.0446 memory: 23708 grad_norm: 5.2711 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4157 loss_aux: 0.9300 loss: 2.3457 2022/09/11 19:18:54 - mmengine - INFO - Epoch(train) [125][300/940] lr: 4.0000e-03 eta: 4:47:43 time: 0.7005 data_time: 0.0334 memory: 23708 grad_norm: 5.2975 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5049 loss_aux: 0.9643 loss: 2.4692 2022/09/11 19:19:08 - mmengine - INFO - Epoch(train) [125][320/940] lr: 4.0000e-03 eta: 4:47:28 time: 0.6990 data_time: 0.0378 memory: 23708 grad_norm: 5.3432 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.5442 loss_aux: 1.0027 loss: 2.5469 2022/09/11 19:19:22 - mmengine - INFO - Epoch(train) [125][340/940] lr: 4.0000e-03 eta: 4:47:13 time: 0.7023 data_time: 0.0444 memory: 23708 grad_norm: 5.2201 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4588 loss_aux: 0.9446 loss: 2.4034 2022/09/11 19:19:36 - mmengine - INFO - Epoch(train) [125][360/940] lr: 4.0000e-03 eta: 4:46:59 time: 0.7018 data_time: 0.0430 memory: 23708 grad_norm: 5.2477 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4710 loss_aux: 0.9796 loss: 2.4505 2022/09/11 19:19:49 - mmengine - INFO - Epoch(train) [125][380/940] lr: 4.0000e-03 eta: 4:46:43 time: 0.6860 data_time: 0.0378 memory: 23708 grad_norm: 5.2538 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.5685 loss_aux: 0.9879 loss: 2.5564 2022/09/11 19:20:03 - mmengine - INFO - Epoch(train) [125][400/940] lr: 4.0000e-03 eta: 4:46:28 time: 0.6858 data_time: 0.0410 memory: 23708 grad_norm: 5.2089 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.5089 loss_aux: 0.9566 loss: 2.4655 2022/09/11 19:20:17 - mmengine - INFO - Epoch(train) [125][420/940] lr: 4.0000e-03 eta: 4:46:13 time: 0.6986 data_time: 0.0414 memory: 23708 grad_norm: 5.1717 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.4931 loss_aux: 0.9710 loss: 2.4641 2022/09/11 19:20:31 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 19:20:31 - mmengine - INFO - Epoch(train) [125][440/940] lr: 4.0000e-03 eta: 4:45:57 time: 0.6896 data_time: 0.0359 memory: 23708 grad_norm: 5.1380 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4496 loss_aux: 0.9423 loss: 2.3918 2022/09/11 19:20:45 - mmengine - INFO - Epoch(train) [125][460/940] lr: 4.0000e-03 eta: 4:45:42 time: 0.6971 data_time: 0.0333 memory: 23708 grad_norm: 5.2724 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.4952 loss_aux: 0.9909 loss: 2.4862 2022/09/11 19:20:59 - mmengine - INFO - Epoch(train) [125][480/940] lr: 4.0000e-03 eta: 4:45:27 time: 0.6912 data_time: 0.0391 memory: 23708 grad_norm: 5.3162 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5931 loss_aux: 1.0127 loss: 2.6058 2022/09/11 19:21:13 - mmengine - INFO - Epoch(train) [125][500/940] lr: 4.0000e-03 eta: 4:45:12 time: 0.7030 data_time: 0.0442 memory: 23708 grad_norm: 5.3252 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5610 loss_aux: 1.0249 loss: 2.5860 2022/09/11 19:21:27 - mmengine - INFO - Epoch(train) [125][520/940] lr: 4.0000e-03 eta: 4:44:57 time: 0.6958 data_time: 0.0383 memory: 23708 grad_norm: 5.2756 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4330 loss_aux: 0.9414 loss: 2.3744 2022/09/11 19:21:41 - mmengine - INFO - Epoch(train) [125][540/940] lr: 4.0000e-03 eta: 4:44:42 time: 0.6963 data_time: 0.0371 memory: 23708 grad_norm: 5.2070 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4564 loss_aux: 0.9182 loss: 2.3746 2022/09/11 19:21:55 - mmengine - INFO - Epoch(train) [125][560/940] lr: 4.0000e-03 eta: 4:44:27 time: 0.6950 data_time: 0.0428 memory: 23708 grad_norm: 5.2030 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5415 loss_aux: 0.9849 loss: 2.5263 2022/09/11 19:22:08 - mmengine - INFO - Epoch(train) [125][580/940] lr: 4.0000e-03 eta: 4:44:12 time: 0.6941 data_time: 0.0463 memory: 23708 grad_norm: 5.2728 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.6217 loss_aux: 1.0117 loss: 2.6334 2022/09/11 19:22:22 - mmengine - INFO - Epoch(train) [125][600/940] lr: 4.0000e-03 eta: 4:43:56 time: 0.6844 data_time: 0.0384 memory: 23708 grad_norm: 5.2405 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4797 loss_aux: 0.9566 loss: 2.4363 2022/09/11 19:22:38 - mmengine - INFO - Epoch(train) [125][620/940] lr: 4.0000e-03 eta: 4:43:45 time: 0.7952 data_time: 0.1466 memory: 23708 grad_norm: 5.1634 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.4839 loss_aux: 0.9723 loss: 2.4562 2022/09/11 19:22:52 - mmengine - INFO - Epoch(train) [125][640/940] lr: 4.0000e-03 eta: 4:43:30 time: 0.6893 data_time: 0.0395 memory: 23708 grad_norm: 5.1701 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4580 loss_aux: 0.9585 loss: 2.4165 2022/09/11 19:23:06 - mmengine - INFO - Epoch(train) [125][660/940] lr: 4.0000e-03 eta: 4:43:15 time: 0.6970 data_time: 0.0401 memory: 23708 grad_norm: 5.2937 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.5364 loss_aux: 0.9720 loss: 2.5084 2022/09/11 19:23:20 - mmengine - INFO - Epoch(train) [125][680/940] lr: 4.0000e-03 eta: 4:43:00 time: 0.6934 data_time: 0.0380 memory: 23708 grad_norm: 5.2902 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.6236 loss_aux: 1.0518 loss: 2.6754 2022/09/11 19:23:34 - mmengine - INFO - Epoch(train) [125][700/940] lr: 4.0000e-03 eta: 4:42:45 time: 0.7091 data_time: 0.0358 memory: 23708 grad_norm: 5.3191 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.4202 loss_aux: 0.9288 loss: 2.3490 2022/09/11 19:23:48 - mmengine - INFO - Epoch(train) [125][720/940] lr: 4.0000e-03 eta: 4:42:30 time: 0.6952 data_time: 0.0372 memory: 23708 grad_norm: 5.2487 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.5000 loss_aux: 0.9259 loss: 2.4259 2022/09/11 19:24:03 - mmengine - INFO - Epoch(train) [125][740/940] lr: 4.0000e-03 eta: 4:42:17 time: 0.7469 data_time: 0.0438 memory: 23708 grad_norm: 5.1438 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.6474 loss_aux: 1.0465 loss: 2.6939 2022/09/11 19:24:17 - mmengine - INFO - Epoch(train) [125][760/940] lr: 4.0000e-03 eta: 4:42:02 time: 0.6961 data_time: 0.0473 memory: 23708 grad_norm: 5.2860 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.6168 loss_aux: 1.0322 loss: 2.6490 2022/09/11 19:24:30 - mmengine - INFO - Epoch(train) [125][780/940] lr: 4.0000e-03 eta: 4:41:47 time: 0.6769 data_time: 0.0351 memory: 23708 grad_norm: 5.2756 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4661 loss_aux: 0.9448 loss: 2.4110 2022/09/11 19:24:44 - mmengine - INFO - Epoch(train) [125][800/940] lr: 4.0000e-03 eta: 4:41:31 time: 0.6954 data_time: 0.0433 memory: 23708 grad_norm: 5.2561 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4936 loss_aux: 0.9522 loss: 2.4458 2022/09/11 19:24:58 - mmengine - INFO - Epoch(train) [125][820/940] lr: 4.0000e-03 eta: 4:41:17 time: 0.7016 data_time: 0.0528 memory: 23708 grad_norm: 5.2653 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4801 loss_aux: 0.9308 loss: 2.4109 2022/09/11 19:25:12 - mmengine - INFO - Epoch(train) [125][840/940] lr: 4.0000e-03 eta: 4:41:02 time: 0.7026 data_time: 0.0383 memory: 23708 grad_norm: 5.2391 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.5594 loss_aux: 0.9858 loss: 2.5452 2022/09/11 19:25:26 - mmengine - INFO - Epoch(train) [125][860/940] lr: 4.0000e-03 eta: 4:40:46 time: 0.6796 data_time: 0.0341 memory: 23708 grad_norm: 5.3205 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.5857 loss_aux: 1.0208 loss: 2.6065 2022/09/11 19:25:40 - mmengine - INFO - Epoch(train) [125][880/940] lr: 4.0000e-03 eta: 4:40:31 time: 0.6860 data_time: 0.0367 memory: 23708 grad_norm: 5.1967 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3835 loss_aux: 0.9305 loss: 2.3139 2022/09/11 19:25:54 - mmengine - INFO - Epoch(train) [125][900/940] lr: 4.0000e-03 eta: 4:40:16 time: 0.7087 data_time: 0.0459 memory: 23708 grad_norm: 5.2199 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4722 loss_aux: 0.9839 loss: 2.4561 2022/09/11 19:26:08 - mmengine - INFO - Epoch(train) [125][920/940] lr: 4.0000e-03 eta: 4:40:02 time: 0.6998 data_time: 0.0354 memory: 23708 grad_norm: 5.2755 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4891 loss_aux: 0.9744 loss: 2.4634 2022/09/11 19:26:20 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 19:26:20 - mmengine - INFO - Epoch(train) [125][940/940] lr: 4.0000e-03 eta: 4:39:44 time: 0.6350 data_time: 0.0274 memory: 23708 grad_norm: 5.5792 top1_acc: 0.2857 top5_acc: 0.7143 loss_cls: 1.4731 loss_aux: 0.9629 loss: 2.4360 2022/09/11 19:26:20 - mmengine - INFO - Saving checkpoint at 125 epochs 2022/09/11 19:26:47 - mmengine - INFO - Epoch(train) [126][20/940] lr: 4.0000e-04 eta: 4:39:37 time: 0.9080 data_time: 0.2400 memory: 23708 grad_norm: 5.1590 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4814 loss_aux: 0.9673 loss: 2.4487 2022/09/11 19:27:01 - mmengine - INFO - Epoch(train) [126][40/940] lr: 4.0000e-04 eta: 4:39:22 time: 0.6760 data_time: 0.0283 memory: 23708 grad_norm: 5.1946 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5092 loss_aux: 0.9744 loss: 2.4836 2022/09/11 19:27:14 - mmengine - INFO - Epoch(train) [126][60/940] lr: 4.0000e-04 eta: 4:39:06 time: 0.6794 data_time: 0.0393 memory: 23708 grad_norm: 5.1789 top1_acc: 0.5938 top5_acc: 0.6875 loss_cls: 1.3840 loss_aux: 0.9340 loss: 2.3181 2022/09/11 19:27:28 - mmengine - INFO - Epoch(train) [126][80/940] lr: 4.0000e-04 eta: 4:38:51 time: 0.6929 data_time: 0.0363 memory: 23708 grad_norm: 5.1463 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5051 loss_aux: 0.9690 loss: 2.4741 2022/09/11 19:27:42 - mmengine - INFO - Epoch(train) [126][100/940] lr: 4.0000e-04 eta: 4:38:35 time: 0.6836 data_time: 0.0419 memory: 23708 grad_norm: 5.1349 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3129 loss_aux: 0.8870 loss: 2.1998 2022/09/11 19:27:55 - mmengine - INFO - Epoch(train) [126][120/940] lr: 4.0000e-04 eta: 4:38:19 time: 0.6637 data_time: 0.0317 memory: 23708 grad_norm: 5.1091 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4037 loss_aux: 0.9262 loss: 2.3299 2022/09/11 19:28:09 - mmengine - INFO - Epoch(train) [126][140/940] lr: 4.0000e-04 eta: 4:38:04 time: 0.7025 data_time: 0.0422 memory: 23708 grad_norm: 5.1989 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5419 loss_aux: 1.0246 loss: 2.5665 2022/09/11 19:28:23 - mmengine - INFO - Epoch(train) [126][160/940] lr: 4.0000e-04 eta: 4:37:49 time: 0.6834 data_time: 0.0344 memory: 23708 grad_norm: 5.0874 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4336 loss_aux: 0.9340 loss: 2.3675 2022/09/11 19:28:37 - mmengine - INFO - Epoch(train) [126][180/940] lr: 4.0000e-04 eta: 4:37:35 time: 0.7157 data_time: 0.0594 memory: 23708 grad_norm: 5.0442 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4478 loss_aux: 0.9498 loss: 2.3976 2022/09/11 19:28:51 - mmengine - INFO - Epoch(train) [126][200/940] lr: 4.0000e-04 eta: 4:37:19 time: 0.6844 data_time: 0.0328 memory: 23708 grad_norm: 5.2264 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4759 loss_aux: 0.9721 loss: 2.4480 2022/09/11 19:29:05 - mmengine - INFO - Epoch(train) [126][220/940] lr: 4.0000e-04 eta: 4:37:05 time: 0.7125 data_time: 0.0389 memory: 23708 grad_norm: 4.9579 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2944 loss_aux: 0.9027 loss: 2.1971 2022/09/11 19:29:19 - mmengine - INFO - Epoch(train) [126][240/940] lr: 4.0000e-04 eta: 4:36:50 time: 0.6850 data_time: 0.0395 memory: 23708 grad_norm: 5.1285 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4881 loss_aux: 0.9914 loss: 2.4795 2022/09/11 19:29:33 - mmengine - INFO - Epoch(train) [126][260/940] lr: 4.0000e-04 eta: 4:36:35 time: 0.7157 data_time: 0.0449 memory: 23708 grad_norm: 5.0741 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4311 loss_aux: 0.9485 loss: 2.3796 2022/09/11 19:29:47 - mmengine - INFO - Epoch(train) [126][280/940] lr: 4.0000e-04 eta: 4:36:20 time: 0.6791 data_time: 0.0348 memory: 23708 grad_norm: 5.0669 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.4509 loss_aux: 0.9721 loss: 2.4230 2022/09/11 19:30:01 - mmengine - INFO - Epoch(train) [126][300/940] lr: 4.0000e-04 eta: 4:36:05 time: 0.7092 data_time: 0.0356 memory: 23708 grad_norm: 5.1967 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4535 loss_aux: 0.9545 loss: 2.4081 2022/09/11 19:30:15 - mmengine - INFO - Epoch(train) [126][320/940] lr: 4.0000e-04 eta: 4:35:50 time: 0.6978 data_time: 0.0505 memory: 23708 grad_norm: 5.1491 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4113 loss_aux: 0.9366 loss: 2.3478 2022/09/11 19:30:29 - mmengine - INFO - Epoch(train) [126][340/940] lr: 4.0000e-04 eta: 4:35:36 time: 0.7089 data_time: 0.0411 memory: 23708 grad_norm: 5.1541 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.5001 loss_aux: 0.9523 loss: 2.4523 2022/09/11 19:30:43 - mmengine - INFO - Epoch(train) [126][360/940] lr: 4.0000e-04 eta: 4:35:22 time: 0.7090 data_time: 0.0403 memory: 23708 grad_norm: 5.1242 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.5524 loss_aux: 1.0067 loss: 2.5591 2022/09/11 19:30:58 - mmengine - INFO - Epoch(train) [126][380/940] lr: 4.0000e-04 eta: 4:35:07 time: 0.7197 data_time: 0.0310 memory: 23708 grad_norm: 5.1393 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3865 loss_aux: 0.9471 loss: 2.3336 2022/09/11 19:31:11 - mmengine - INFO - Epoch(train) [126][400/940] lr: 4.0000e-04 eta: 4:34:52 time: 0.6869 data_time: 0.0317 memory: 23708 grad_norm: 5.1791 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4424 loss_aux: 0.9669 loss: 2.4094 2022/09/11 19:31:26 - mmengine - INFO - Epoch(train) [126][420/940] lr: 4.0000e-04 eta: 4:34:38 time: 0.7117 data_time: 0.0377 memory: 23708 grad_norm: 5.1071 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3667 loss_aux: 0.9102 loss: 2.2770 2022/09/11 19:31:40 - mmengine - INFO - Epoch(train) [126][440/940] lr: 4.0000e-04 eta: 4:34:24 time: 0.7374 data_time: 0.0501 memory: 23708 grad_norm: 5.2026 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.4116 loss_aux: 0.9282 loss: 2.3398 2022/09/11 19:31:55 - mmengine - INFO - Epoch(train) [126][460/940] lr: 4.0000e-04 eta: 4:34:10 time: 0.7151 data_time: 0.0306 memory: 23708 grad_norm: 5.1320 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2601 loss_aux: 0.8790 loss: 2.1391 2022/09/11 19:32:09 - mmengine - INFO - Epoch(train) [126][480/940] lr: 4.0000e-04 eta: 4:33:55 time: 0.6936 data_time: 0.0302 memory: 23708 grad_norm: 5.1470 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.4549 loss_aux: 0.9837 loss: 2.4386 2022/09/11 19:32:23 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 19:32:23 - mmengine - INFO - Epoch(train) [126][500/940] lr: 4.0000e-04 eta: 4:33:41 time: 0.7056 data_time: 0.0372 memory: 23708 grad_norm: 5.1744 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.5100 loss_aux: 0.9831 loss: 2.4930 2022/09/11 19:32:37 - mmengine - INFO - Epoch(train) [126][520/940] lr: 4.0000e-04 eta: 4:33:26 time: 0.7063 data_time: 0.0402 memory: 23708 grad_norm: 5.1290 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3353 loss_aux: 0.8988 loss: 2.2341 2022/09/11 19:32:51 - mmengine - INFO - Epoch(train) [126][540/940] lr: 4.0000e-04 eta: 4:33:12 time: 0.7087 data_time: 0.0340 memory: 23708 grad_norm: 5.0580 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3001 loss_aux: 0.8783 loss: 2.1784 2022/09/11 19:33:06 - mmengine - INFO - Epoch(train) [126][560/940] lr: 4.0000e-04 eta: 4:32:57 time: 0.7201 data_time: 0.0401 memory: 23708 grad_norm: 5.1084 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4439 loss_aux: 0.9684 loss: 2.4123 2022/09/11 19:33:20 - mmengine - INFO - Epoch(train) [126][580/940] lr: 4.0000e-04 eta: 4:32:43 time: 0.7080 data_time: 0.0380 memory: 23708 grad_norm: 5.1259 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4335 loss_aux: 0.9373 loss: 2.3708 2022/09/11 19:33:34 - mmengine - INFO - Epoch(train) [126][600/940] lr: 4.0000e-04 eta: 4:32:28 time: 0.6991 data_time: 0.0320 memory: 23708 grad_norm: 5.1832 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3740 loss_aux: 0.9377 loss: 2.3116 2022/09/11 19:33:47 - mmengine - INFO - Epoch(train) [126][620/940] lr: 4.0000e-04 eta: 4:32:13 time: 0.6944 data_time: 0.0321 memory: 23708 grad_norm: 5.1670 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3530 loss_aux: 0.9105 loss: 2.2635 2022/09/11 19:34:02 - mmengine - INFO - Epoch(train) [126][640/940] lr: 4.0000e-04 eta: 4:31:59 time: 0.7066 data_time: 0.0392 memory: 23708 grad_norm: 5.1079 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4133 loss_aux: 0.9119 loss: 2.3252 2022/09/11 19:34:16 - mmengine - INFO - Epoch(train) [126][660/940] lr: 4.0000e-04 eta: 4:31:45 time: 0.7234 data_time: 0.0317 memory: 23708 grad_norm: 5.2133 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4099 loss_aux: 0.9380 loss: 2.3479 2022/09/11 19:34:30 - mmengine - INFO - Epoch(train) [126][680/940] lr: 4.0000e-04 eta: 4:31:30 time: 0.7127 data_time: 0.0403 memory: 23708 grad_norm: 5.2407 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.4608 loss_aux: 0.9487 loss: 2.4096 2022/09/11 19:34:44 - mmengine - INFO - Epoch(train) [126][700/940] lr: 4.0000e-04 eta: 4:31:16 time: 0.6996 data_time: 0.0357 memory: 23708 grad_norm: 5.1014 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4257 loss_aux: 0.9281 loss: 2.3539 2022/09/11 19:34:58 - mmengine - INFO - Epoch(train) [126][720/940] lr: 4.0000e-04 eta: 4:31:01 time: 0.7047 data_time: 0.0465 memory: 23708 grad_norm: 5.2226 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5522 loss_aux: 0.9884 loss: 2.5406 2022/09/11 19:35:13 - mmengine - INFO - Epoch(train) [126][740/940] lr: 4.0000e-04 eta: 4:30:47 time: 0.7164 data_time: 0.0481 memory: 23708 grad_norm: 5.0404 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.3798 loss_aux: 0.9151 loss: 2.2950 2022/09/11 19:35:27 - mmengine - INFO - Epoch(train) [126][760/940] lr: 4.0000e-04 eta: 4:30:32 time: 0.7116 data_time: 0.0332 memory: 23708 grad_norm: 5.1294 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3745 loss_aux: 0.9039 loss: 2.2784 2022/09/11 19:35:41 - mmengine - INFO - Epoch(train) [126][780/940] lr: 4.0000e-04 eta: 4:30:18 time: 0.6961 data_time: 0.0345 memory: 23708 grad_norm: 5.1858 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5320 loss_aux: 0.9719 loss: 2.5039 2022/09/11 19:35:55 - mmengine - INFO - Epoch(train) [126][800/940] lr: 4.0000e-04 eta: 4:30:04 time: 0.7243 data_time: 0.0410 memory: 23708 grad_norm: 5.1498 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3463 loss_aux: 0.8953 loss: 2.2416 2022/09/11 19:36:09 - mmengine - INFO - Epoch(train) [126][820/940] lr: 4.0000e-04 eta: 4:29:49 time: 0.7030 data_time: 0.0300 memory: 23708 grad_norm: 5.1194 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4661 loss_aux: 0.9750 loss: 2.4411 2022/09/11 19:36:23 - mmengine - INFO - Epoch(train) [126][840/940] lr: 4.0000e-04 eta: 4:29:34 time: 0.6921 data_time: 0.0311 memory: 23708 grad_norm: 5.1877 top1_acc: 0.4375 top5_acc: 0.6875 loss_cls: 1.4451 loss_aux: 0.9320 loss: 2.3771 2022/09/11 19:36:38 - mmengine - INFO - Epoch(train) [126][860/940] lr: 4.0000e-04 eta: 4:29:20 time: 0.7280 data_time: 0.0353 memory: 23708 grad_norm: 5.2254 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3179 loss_aux: 0.9084 loss: 2.2263 2022/09/11 19:36:52 - mmengine - INFO - Epoch(train) [126][880/940] lr: 4.0000e-04 eta: 4:29:05 time: 0.6993 data_time: 0.0398 memory: 23708 grad_norm: 5.1659 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2610 loss_aux: 0.8421 loss: 2.1031 2022/09/11 19:37:06 - mmengine - INFO - Epoch(train) [126][900/940] lr: 4.0000e-04 eta: 4:28:51 time: 0.7136 data_time: 0.0314 memory: 23708 grad_norm: 5.2762 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.1670 loss_aux: 0.8406 loss: 2.0077 2022/09/11 19:37:20 - mmengine - INFO - Epoch(train) [126][920/940] lr: 4.0000e-04 eta: 4:28:36 time: 0.6893 data_time: 0.0408 memory: 23708 grad_norm: 5.1203 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4277 loss_aux: 0.9448 loss: 2.3724 2022/09/11 19:37:33 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 19:37:33 - mmengine - INFO - Epoch(train) [126][940/940] lr: 4.0000e-04 eta: 4:28:20 time: 0.6497 data_time: 0.0359 memory: 23708 grad_norm: 5.2975 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.2479 loss_aux: 0.8591 loss: 2.1070 2022/09/11 19:37:33 - mmengine - INFO - Saving checkpoint at 126 epochs 2022/09/11 19:37:58 - mmengine - INFO - Epoch(train) [127][20/940] lr: 4.0000e-04 eta: 4:28:14 time: 0.9604 data_time: 0.2981 memory: 23708 grad_norm: 5.2397 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.4095 loss_aux: 0.9572 loss: 2.3667 2022/09/11 19:38:11 - mmengine - INFO - Epoch(train) [127][40/940] lr: 4.0000e-04 eta: 4:27:59 time: 0.6887 data_time: 0.0358 memory: 23708 grad_norm: 5.2354 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.3950 loss_aux: 0.9476 loss: 2.3426 2022/09/11 19:38:25 - mmengine - INFO - Epoch(train) [127][60/940] lr: 4.0000e-04 eta: 4:27:43 time: 0.6799 data_time: 0.0300 memory: 23708 grad_norm: 5.1826 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4303 loss_aux: 0.9264 loss: 2.3567 2022/09/11 19:38:39 - mmengine - INFO - Epoch(train) [127][80/940] lr: 4.0000e-04 eta: 4:27:29 time: 0.7039 data_time: 0.0393 memory: 23708 grad_norm: 5.0496 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4465 loss_aux: 0.9550 loss: 2.4015 2022/09/11 19:38:53 - mmengine - INFO - Epoch(train) [127][100/940] lr: 4.0000e-04 eta: 4:27:13 time: 0.6866 data_time: 0.0434 memory: 23708 grad_norm: 5.1038 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4782 loss_aux: 0.9601 loss: 2.4383 2022/09/11 19:39:07 - mmengine - INFO - Epoch(train) [127][120/940] lr: 4.0000e-04 eta: 4:26:59 time: 0.7109 data_time: 0.0427 memory: 23708 grad_norm: 5.1753 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3784 loss_aux: 0.9606 loss: 2.3390 2022/09/11 19:39:21 - mmengine - INFO - Epoch(train) [127][140/940] lr: 4.0000e-04 eta: 4:26:44 time: 0.6901 data_time: 0.0302 memory: 23708 grad_norm: 5.1735 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3559 loss_aux: 0.9350 loss: 2.2909 2022/09/11 19:39:35 - mmengine - INFO - Epoch(train) [127][160/940] lr: 4.0000e-04 eta: 4:26:29 time: 0.7001 data_time: 0.0406 memory: 23708 grad_norm: 5.1455 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4215 loss_aux: 0.9484 loss: 2.3699 2022/09/11 19:39:49 - mmengine - INFO - Epoch(train) [127][180/940] lr: 4.0000e-04 eta: 4:26:15 time: 0.7091 data_time: 0.0577 memory: 23708 grad_norm: 5.1383 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2942 loss_aux: 0.9004 loss: 2.1945 2022/09/11 19:40:03 - mmengine - INFO - Epoch(train) [127][200/940] lr: 4.0000e-04 eta: 4:26:00 time: 0.6933 data_time: 0.0221 memory: 23708 grad_norm: 5.1785 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2721 loss_aux: 0.8936 loss: 2.1657 2022/09/11 19:40:17 - mmengine - INFO - Epoch(train) [127][220/940] lr: 4.0000e-04 eta: 4:25:45 time: 0.7073 data_time: 0.0298 memory: 23708 grad_norm: 5.2096 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4687 loss_aux: 0.9498 loss: 2.4185 2022/09/11 19:40:31 - mmengine - INFO - Epoch(train) [127][240/940] lr: 4.0000e-04 eta: 4:25:31 time: 0.7013 data_time: 0.0350 memory: 23708 grad_norm: 5.1839 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4892 loss_aux: 0.9702 loss: 2.4594 2022/09/11 19:40:45 - mmengine - INFO - Epoch(train) [127][260/940] lr: 4.0000e-04 eta: 4:25:16 time: 0.7055 data_time: 0.0447 memory: 23708 grad_norm: 5.0860 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2627 loss_aux: 0.8737 loss: 2.1364 2022/09/11 19:40:59 - mmengine - INFO - Epoch(train) [127][280/940] lr: 4.0000e-04 eta: 4:25:01 time: 0.6910 data_time: 0.0351 memory: 23708 grad_norm: 5.2691 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2624 loss_aux: 0.9143 loss: 2.1767 2022/09/11 19:41:13 - mmengine - INFO - Epoch(train) [127][300/940] lr: 4.0000e-04 eta: 4:24:46 time: 0.6969 data_time: 0.0295 memory: 23708 grad_norm: 5.1828 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3442 loss_aux: 0.8911 loss: 2.2353 2022/09/11 19:41:27 - mmengine - INFO - Epoch(train) [127][320/940] lr: 4.0000e-04 eta: 4:24:32 time: 0.7114 data_time: 0.0441 memory: 23708 grad_norm: 5.1854 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4261 loss_aux: 0.9478 loss: 2.3739 2022/09/11 19:41:41 - mmengine - INFO - Epoch(train) [127][340/940] lr: 4.0000e-04 eta: 4:24:17 time: 0.7118 data_time: 0.0378 memory: 23708 grad_norm: 5.2232 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4855 loss_aux: 0.9397 loss: 2.4252 2022/09/11 19:41:56 - mmengine - INFO - Epoch(train) [127][360/940] lr: 4.0000e-04 eta: 4:24:03 time: 0.7152 data_time: 0.0393 memory: 23708 grad_norm: 5.2811 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.4658 loss_aux: 0.9578 loss: 2.4236 2022/09/11 19:42:10 - mmengine - INFO - Epoch(train) [127][380/940] lr: 4.0000e-04 eta: 4:23:48 time: 0.6893 data_time: 0.0228 memory: 23708 grad_norm: 5.1728 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4427 loss_aux: 0.9251 loss: 2.3678 2022/09/11 19:42:26 - mmengine - INFO - Epoch(train) [127][400/940] lr: 4.0000e-04 eta: 4:23:38 time: 0.8438 data_time: 0.0361 memory: 23708 grad_norm: 5.1551 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3671 loss_aux: 0.9059 loss: 2.2730 2022/09/11 19:42:40 - mmengine - INFO - Epoch(train) [127][420/940] lr: 4.0000e-04 eta: 4:23:23 time: 0.6898 data_time: 0.0450 memory: 23708 grad_norm: 5.2416 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.5475 loss_aux: 1.0226 loss: 2.5701 2022/09/11 19:42:54 - mmengine - INFO - Epoch(train) [127][440/940] lr: 4.0000e-04 eta: 4:23:08 time: 0.6914 data_time: 0.0408 memory: 23708 grad_norm: 5.2250 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3814 loss_aux: 0.9007 loss: 2.2822 2022/09/11 19:43:08 - mmengine - INFO - Epoch(train) [127][460/940] lr: 4.0000e-04 eta: 4:22:54 time: 0.7106 data_time: 0.0470 memory: 23708 grad_norm: 5.2334 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3579 loss_aux: 0.9235 loss: 2.2814 2022/09/11 19:43:22 - mmengine - INFO - Epoch(train) [127][480/940] lr: 4.0000e-04 eta: 4:22:39 time: 0.7067 data_time: 0.0404 memory: 23708 grad_norm: 5.2889 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.5230 loss_aux: 0.9794 loss: 2.5025 2022/09/11 19:43:37 - mmengine - INFO - Epoch(train) [127][500/940] lr: 4.0000e-04 eta: 4:22:25 time: 0.7222 data_time: 0.0410 memory: 23708 grad_norm: 5.1424 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5657 loss_aux: 0.9992 loss: 2.5650 2022/09/11 19:43:51 - mmengine - INFO - Epoch(train) [127][520/940] lr: 4.0000e-04 eta: 4:22:10 time: 0.6924 data_time: 0.0360 memory: 23708 grad_norm: 5.1588 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.4660 loss_aux: 0.9537 loss: 2.4197 2022/09/11 19:44:05 - mmengine - INFO - Epoch(train) [127][540/940] lr: 4.0000e-04 eta: 4:21:56 time: 0.7024 data_time: 0.0361 memory: 23708 grad_norm: 5.1876 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.2706 loss_aux: 0.8978 loss: 2.1684 2022/09/11 19:44:19 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 19:44:19 - mmengine - INFO - Epoch(train) [127][560/940] lr: 4.0000e-04 eta: 4:21:41 time: 0.6920 data_time: 0.0387 memory: 23708 grad_norm: 5.2386 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3186 loss_aux: 0.9277 loss: 2.2462 2022/09/11 19:44:32 - mmengine - INFO - Epoch(train) [127][580/940] lr: 4.0000e-04 eta: 4:21:25 time: 0.6845 data_time: 0.0363 memory: 23708 grad_norm: 5.1932 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3744 loss_aux: 0.9294 loss: 2.3038 2022/09/11 19:44:47 - mmengine - INFO - Epoch(train) [127][600/940] lr: 4.0000e-04 eta: 4:21:11 time: 0.7184 data_time: 0.0497 memory: 23708 grad_norm: 5.1927 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.4077 loss_aux: 0.8981 loss: 2.3058 2022/09/11 19:45:00 - mmengine - INFO - Epoch(train) [127][620/940] lr: 4.0000e-04 eta: 4:20:56 time: 0.6918 data_time: 0.0393 memory: 23708 grad_norm: 5.2235 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2984 loss_aux: 0.8822 loss: 2.1806 2022/09/11 19:45:15 - mmengine - INFO - Epoch(train) [127][640/940] lr: 4.0000e-04 eta: 4:20:41 time: 0.6937 data_time: 0.0399 memory: 23708 grad_norm: 5.2024 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4347 loss_aux: 0.9437 loss: 2.3784 2022/09/11 19:45:28 - mmengine - INFO - Epoch(train) [127][660/940] lr: 4.0000e-04 eta: 4:20:27 time: 0.7022 data_time: 0.0462 memory: 23708 grad_norm: 5.1110 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.4087 loss_aux: 0.9457 loss: 2.3544 2022/09/11 19:45:42 - mmengine - INFO - Epoch(train) [127][680/940] lr: 4.0000e-04 eta: 4:20:12 time: 0.6923 data_time: 0.0410 memory: 23708 grad_norm: 5.2162 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4836 loss_aux: 0.9670 loss: 2.4506 2022/09/11 19:45:56 - mmengine - INFO - Epoch(train) [127][700/940] lr: 4.0000e-04 eta: 4:19:57 time: 0.6900 data_time: 0.0376 memory: 23708 grad_norm: 5.1822 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3846 loss_aux: 0.9293 loss: 2.3139 2022/09/11 19:46:10 - mmengine - INFO - Epoch(train) [127][720/940] lr: 4.0000e-04 eta: 4:19:42 time: 0.6871 data_time: 0.0369 memory: 23708 grad_norm: 5.2250 top1_acc: 0.5625 top5_acc: 0.9375 loss_cls: 1.4353 loss_aux: 0.9456 loss: 2.3808 2022/09/11 19:46:24 - mmengine - INFO - Epoch(train) [127][740/940] lr: 4.0000e-04 eta: 4:19:27 time: 0.6939 data_time: 0.0405 memory: 23708 grad_norm: 5.2195 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.4009 loss_aux: 0.9581 loss: 2.3590 2022/09/11 19:46:38 - mmengine - INFO - Epoch(train) [127][760/940] lr: 4.0000e-04 eta: 4:19:12 time: 0.6945 data_time: 0.0417 memory: 23708 grad_norm: 5.2477 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2545 loss_aux: 0.8535 loss: 2.1080 2022/09/11 19:46:51 - mmengine - INFO - Epoch(train) [127][780/940] lr: 4.0000e-04 eta: 4:18:57 time: 0.6917 data_time: 0.0388 memory: 23708 grad_norm: 5.2433 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3940 loss_aux: 0.9478 loss: 2.3418 2022/09/11 19:47:06 - mmengine - INFO - Epoch(train) [127][800/940] lr: 4.0000e-04 eta: 4:18:43 time: 0.7207 data_time: 0.0338 memory: 23708 grad_norm: 5.1490 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.4121 loss_aux: 0.9428 loss: 2.3548 2022/09/11 19:47:20 - mmengine - INFO - Epoch(train) [127][820/940] lr: 4.0000e-04 eta: 4:18:29 time: 0.7066 data_time: 0.0382 memory: 23708 grad_norm: 5.1190 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2666 loss_aux: 0.8550 loss: 2.1216 2022/09/11 19:47:34 - mmengine - INFO - Epoch(train) [127][840/940] lr: 4.0000e-04 eta: 4:18:14 time: 0.6940 data_time: 0.0357 memory: 23708 grad_norm: 5.2394 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4913 loss_aux: 0.9285 loss: 2.4199 2022/09/11 19:47:48 - mmengine - INFO - Epoch(train) [127][860/940] lr: 4.0000e-04 eta: 4:17:59 time: 0.7024 data_time: 0.0408 memory: 23708 grad_norm: 5.1312 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3203 loss_aux: 0.8859 loss: 2.2063 2022/09/11 19:48:02 - mmengine - INFO - Epoch(train) [127][880/940] lr: 4.0000e-04 eta: 4:17:44 time: 0.6911 data_time: 0.0387 memory: 23708 grad_norm: 5.3200 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.2526 loss_aux: 0.8607 loss: 2.1132 2022/09/11 19:48:16 - mmengine - INFO - Epoch(train) [127][900/940] lr: 4.0000e-04 eta: 4:17:30 time: 0.7040 data_time: 0.0371 memory: 23708 grad_norm: 5.1966 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4650 loss_aux: 0.9812 loss: 2.4463 2022/09/11 19:48:30 - mmengine - INFO - Epoch(train) [127][920/940] lr: 4.0000e-04 eta: 4:17:14 time: 0.6863 data_time: 0.0358 memory: 23708 grad_norm: 5.2489 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4404 loss_aux: 0.9761 loss: 2.4165 2022/09/11 19:48:42 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 19:48:42 - mmengine - INFO - Epoch(train) [127][940/940] lr: 4.0000e-04 eta: 4:16:58 time: 0.6411 data_time: 0.0317 memory: 23708 grad_norm: 5.5233 top1_acc: 0.4286 top5_acc: 0.5714 loss_cls: 1.4634 loss_aux: 0.9707 loss: 2.4341 2022/09/11 19:48:42 - mmengine - INFO - Saving checkpoint at 127 epochs 2022/09/11 19:49:07 - mmengine - INFO - Epoch(train) [128][20/940] lr: 4.0000e-04 eta: 4:16:51 time: 0.9621 data_time: 0.3098 memory: 23708 grad_norm: 5.1328 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3775 loss_aux: 0.9403 loss: 2.3178 2022/09/11 19:49:21 - mmengine - INFO - Epoch(train) [128][40/940] lr: 4.0000e-04 eta: 4:16:36 time: 0.6711 data_time: 0.0298 memory: 23708 grad_norm: 5.2314 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3243 loss_aux: 0.9022 loss: 2.2265 2022/09/11 19:49:34 - mmengine - INFO - Epoch(train) [128][60/940] lr: 4.0000e-04 eta: 4:16:21 time: 0.6823 data_time: 0.0299 memory: 23708 grad_norm: 5.1937 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3517 loss_aux: 0.9231 loss: 2.2748 2022/09/11 19:49:48 - mmengine - INFO - Epoch(train) [128][80/940] lr: 4.0000e-04 eta: 4:16:05 time: 0.6774 data_time: 0.0343 memory: 23708 grad_norm: 5.1150 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3598 loss_aux: 0.9272 loss: 2.2871 2022/09/11 19:50:02 - mmengine - INFO - Epoch(train) [128][100/940] lr: 4.0000e-04 eta: 4:15:51 time: 0.7020 data_time: 0.0425 memory: 23708 grad_norm: 5.2561 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4085 loss_aux: 0.9016 loss: 2.3101 2022/09/11 19:50:16 - mmengine - INFO - Epoch(train) [128][120/940] lr: 4.0000e-04 eta: 4:15:35 time: 0.6822 data_time: 0.0355 memory: 23708 grad_norm: 5.3203 top1_acc: 0.5312 top5_acc: 0.9062 loss_cls: 1.4361 loss_aux: 0.9400 loss: 2.3762 2022/09/11 19:50:29 - mmengine - INFO - Epoch(train) [128][140/940] lr: 4.0000e-04 eta: 4:15:20 time: 0.6916 data_time: 0.0339 memory: 23708 grad_norm: 5.2032 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3360 loss_aux: 0.9033 loss: 2.2393 2022/09/11 19:50:43 - mmengine - INFO - Epoch(train) [128][160/940] lr: 4.0000e-04 eta: 4:15:05 time: 0.6891 data_time: 0.0493 memory: 23708 grad_norm: 5.1867 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2363 loss_aux: 0.8816 loss: 2.1179 2022/09/11 19:50:57 - mmengine - INFO - Epoch(train) [128][180/940] lr: 4.0000e-04 eta: 4:14:50 time: 0.6895 data_time: 0.0416 memory: 23708 grad_norm: 5.1623 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3917 loss_aux: 0.8885 loss: 2.2801 2022/09/11 19:51:11 - mmengine - INFO - Epoch(train) [128][200/940] lr: 4.0000e-04 eta: 4:14:35 time: 0.6764 data_time: 0.0323 memory: 23708 grad_norm: 5.0895 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3093 loss_aux: 0.8878 loss: 2.1971 2022/09/11 19:51:24 - mmengine - INFO - Epoch(train) [128][220/940] lr: 4.0000e-04 eta: 4:14:20 time: 0.6726 data_time: 0.0303 memory: 23708 grad_norm: 5.1016 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3364 loss_aux: 0.8810 loss: 2.2174 2022/09/11 19:51:38 - mmengine - INFO - Epoch(train) [128][240/940] lr: 4.0000e-04 eta: 4:14:05 time: 0.6905 data_time: 0.0357 memory: 23708 grad_norm: 5.1737 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2926 loss_aux: 0.8804 loss: 2.1730 2022/09/11 19:51:52 - mmengine - INFO - Epoch(train) [128][260/940] lr: 4.0000e-04 eta: 4:13:50 time: 0.7149 data_time: 0.0394 memory: 23708 grad_norm: 5.2765 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3504 loss_aux: 0.8931 loss: 2.2435 2022/09/11 19:52:06 - mmengine - INFO - Epoch(train) [128][280/940] lr: 4.0000e-04 eta: 4:13:36 time: 0.7051 data_time: 0.0333 memory: 23708 grad_norm: 5.2389 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4177 loss_aux: 0.9849 loss: 2.4025 2022/09/11 19:52:20 - mmengine - INFO - Epoch(train) [128][300/940] lr: 4.0000e-04 eta: 4:13:21 time: 0.6767 data_time: 0.0392 memory: 23708 grad_norm: 5.3106 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3278 loss_aux: 0.9073 loss: 2.2352 2022/09/11 19:52:34 - mmengine - INFO - Epoch(train) [128][320/940] lr: 4.0000e-04 eta: 4:13:06 time: 0.6901 data_time: 0.0332 memory: 23708 grad_norm: 5.2063 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3909 loss_aux: 0.9176 loss: 2.3085 2022/09/11 19:52:48 - mmengine - INFO - Epoch(train) [128][340/940] lr: 4.0000e-04 eta: 4:12:51 time: 0.6950 data_time: 0.0352 memory: 23708 grad_norm: 5.2157 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4388 loss_aux: 0.9669 loss: 2.4057 2022/09/11 19:53:01 - mmengine - INFO - Epoch(train) [128][360/940] lr: 4.0000e-04 eta: 4:12:36 time: 0.6877 data_time: 0.0518 memory: 23708 grad_norm: 5.2548 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4290 loss_aux: 0.9668 loss: 2.3958 2022/09/11 19:53:16 - mmengine - INFO - Epoch(train) [128][380/940] lr: 4.0000e-04 eta: 4:12:22 time: 0.7132 data_time: 0.0384 memory: 23708 grad_norm: 5.2224 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4348 loss_aux: 0.9669 loss: 2.4017 2022/09/11 19:53:29 - mmengine - INFO - Epoch(train) [128][400/940] lr: 4.0000e-04 eta: 4:12:07 time: 0.6895 data_time: 0.0356 memory: 23708 grad_norm: 5.1796 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3137 loss_aux: 0.9158 loss: 2.2295 2022/09/11 19:53:43 - mmengine - INFO - Epoch(train) [128][420/940] lr: 4.0000e-04 eta: 4:11:52 time: 0.6962 data_time: 0.0332 memory: 23708 grad_norm: 5.1664 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3820 loss_aux: 0.9324 loss: 2.3143 2022/09/11 19:53:57 - mmengine - INFO - Epoch(train) [128][440/940] lr: 4.0000e-04 eta: 4:11:38 time: 0.7089 data_time: 0.0567 memory: 23708 grad_norm: 5.2137 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4137 loss_aux: 0.9597 loss: 2.3733 2022/09/11 19:54:11 - mmengine - INFO - Epoch(train) [128][460/940] lr: 4.0000e-04 eta: 4:11:23 time: 0.6913 data_time: 0.0438 memory: 23708 grad_norm: 5.1457 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2372 loss_aux: 0.8412 loss: 2.0784 2022/09/11 19:54:25 - mmengine - INFO - Epoch(train) [128][480/940] lr: 4.0000e-04 eta: 4:11:08 time: 0.6836 data_time: 0.0351 memory: 23708 grad_norm: 5.1060 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2657 loss_aux: 0.8551 loss: 2.1209 2022/09/11 19:54:39 - mmengine - INFO - Epoch(train) [128][500/940] lr: 4.0000e-04 eta: 4:10:53 time: 0.7105 data_time: 0.0352 memory: 23708 grad_norm: 5.1783 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4375 loss_aux: 0.9372 loss: 2.3747 2022/09/11 19:54:53 - mmengine - INFO - Epoch(train) [128][520/940] lr: 4.0000e-04 eta: 4:10:39 time: 0.6989 data_time: 0.0430 memory: 23708 grad_norm: 5.1831 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.1467 loss_aux: 0.7657 loss: 1.9123 2022/09/11 19:55:07 - mmengine - INFO - Epoch(train) [128][540/940] lr: 4.0000e-04 eta: 4:10:24 time: 0.7010 data_time: 0.0397 memory: 23708 grad_norm: 5.3139 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3484 loss_aux: 0.9105 loss: 2.2589 2022/09/11 19:55:21 - mmengine - INFO - Epoch(train) [128][560/940] lr: 4.0000e-04 eta: 4:10:09 time: 0.6872 data_time: 0.0416 memory: 23708 grad_norm: 5.2945 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4687 loss_aux: 0.9815 loss: 2.4502 2022/09/11 19:55:35 - mmengine - INFO - Epoch(train) [128][580/940] lr: 4.0000e-04 eta: 4:09:55 time: 0.7069 data_time: 0.0345 memory: 23708 grad_norm: 5.2437 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3720 loss_aux: 0.9117 loss: 2.2837 2022/09/11 19:55:49 - mmengine - INFO - Epoch(train) [128][600/940] lr: 4.0000e-04 eta: 4:09:40 time: 0.6885 data_time: 0.0465 memory: 23708 grad_norm: 5.2446 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4590 loss_aux: 0.9347 loss: 2.3937 2022/09/11 19:56:03 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 19:56:03 - mmengine - INFO - Epoch(train) [128][620/940] lr: 4.0000e-04 eta: 4:09:25 time: 0.6870 data_time: 0.0404 memory: 23708 grad_norm: 5.2182 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3935 loss_aux: 0.9522 loss: 2.3457 2022/09/11 19:56:17 - mmengine - INFO - Epoch(train) [128][640/940] lr: 4.0000e-04 eta: 4:09:11 time: 0.7437 data_time: 0.0330 memory: 23708 grad_norm: 5.2566 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4227 loss_aux: 0.9374 loss: 2.3601 2022/09/11 19:56:31 - mmengine - INFO - Epoch(train) [128][660/940] lr: 4.0000e-04 eta: 4:08:57 time: 0.6986 data_time: 0.0356 memory: 23708 grad_norm: 5.1676 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2410 loss_aux: 0.8543 loss: 2.0953 2022/09/11 19:56:46 - mmengine - INFO - Epoch(train) [128][680/940] lr: 4.0000e-04 eta: 4:08:42 time: 0.7032 data_time: 0.0431 memory: 23708 grad_norm: 5.1703 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3530 loss_aux: 0.9204 loss: 2.2735 2022/09/11 19:57:00 - mmengine - INFO - Epoch(train) [128][700/940] lr: 4.0000e-04 eta: 4:08:28 time: 0.7145 data_time: 0.0469 memory: 23708 grad_norm: 5.2282 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3694 loss_aux: 0.9131 loss: 2.2825 2022/09/11 19:57:14 - mmengine - INFO - Epoch(train) [128][720/940] lr: 4.0000e-04 eta: 4:08:13 time: 0.6891 data_time: 0.0333 memory: 23708 grad_norm: 5.2652 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4172 loss_aux: 0.9224 loss: 2.3397 2022/09/11 19:57:28 - mmengine - INFO - Epoch(train) [128][740/940] lr: 4.0000e-04 eta: 4:07:58 time: 0.7004 data_time: 0.0377 memory: 23708 grad_norm: 5.3676 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.5293 loss_aux: 0.9516 loss: 2.4809 2022/09/11 19:57:41 - mmengine - INFO - Epoch(train) [128][760/940] lr: 4.0000e-04 eta: 4:07:43 time: 0.6859 data_time: 0.0435 memory: 23708 grad_norm: 5.1504 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3563 loss_aux: 0.9329 loss: 2.2893 2022/09/11 19:57:55 - mmengine - INFO - Epoch(train) [128][780/940] lr: 4.0000e-04 eta: 4:07:28 time: 0.6843 data_time: 0.0410 memory: 23708 grad_norm: 5.2083 top1_acc: 0.8750 top5_acc: 0.9375 loss_cls: 1.2148 loss_aux: 0.8483 loss: 2.0631 2022/09/11 19:58:09 - mmengine - INFO - Epoch(train) [128][800/940] lr: 4.0000e-04 eta: 4:07:14 time: 0.7043 data_time: 0.0468 memory: 23708 grad_norm: 5.2913 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.4190 loss_aux: 0.9488 loss: 2.3678 2022/09/11 19:58:23 - mmengine - INFO - Epoch(train) [128][820/940] lr: 4.0000e-04 eta: 4:06:59 time: 0.6908 data_time: 0.0358 memory: 23708 grad_norm: 5.2010 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4848 loss_aux: 0.9579 loss: 2.4427 2022/09/11 19:58:37 - mmengine - INFO - Epoch(train) [128][840/940] lr: 4.0000e-04 eta: 4:06:44 time: 0.6979 data_time: 0.0441 memory: 23708 grad_norm: 5.2627 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3816 loss_aux: 0.9276 loss: 2.3092 2022/09/11 19:58:51 - mmengine - INFO - Epoch(train) [128][860/940] lr: 4.0000e-04 eta: 4:06:30 time: 0.6917 data_time: 0.0420 memory: 23708 grad_norm: 5.3075 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2941 loss_aux: 0.8732 loss: 2.1673 2022/09/11 19:59:05 - mmengine - INFO - Epoch(train) [128][880/940] lr: 4.0000e-04 eta: 4:06:15 time: 0.6968 data_time: 0.0352 memory: 23708 grad_norm: 5.1837 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3394 loss_aux: 0.9094 loss: 2.2488 2022/09/11 19:59:19 - mmengine - INFO - Epoch(train) [128][900/940] lr: 4.0000e-04 eta: 4:06:00 time: 0.7057 data_time: 0.0439 memory: 23708 grad_norm: 5.2063 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3649 loss_aux: 0.9382 loss: 2.3031 2022/09/11 19:59:32 - mmengine - INFO - Epoch(train) [128][920/940] lr: 4.0000e-04 eta: 4:05:45 time: 0.6777 data_time: 0.0382 memory: 23708 grad_norm: 5.3411 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4140 loss_aux: 0.9553 loss: 2.3693 2022/09/11 19:59:45 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 19:59:45 - mmengine - INFO - Epoch(train) [128][940/940] lr: 4.0000e-04 eta: 4:05:29 time: 0.6441 data_time: 0.0273 memory: 23708 grad_norm: 5.4476 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.3927 loss_aux: 0.9242 loss: 2.3169 2022/09/11 19:59:45 - mmengine - INFO - Saving checkpoint at 128 epochs 2022/09/11 20:00:11 - mmengine - INFO - Epoch(train) [129][20/940] lr: 4.0000e-04 eta: 4:05:21 time: 0.9437 data_time: 0.2962 memory: 23708 grad_norm: 5.2580 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.3974 loss_aux: 0.9572 loss: 2.3546 2022/09/11 20:00:24 - mmengine - INFO - Epoch(train) [129][40/940] lr: 4.0000e-04 eta: 4:05:06 time: 0.6681 data_time: 0.0301 memory: 23708 grad_norm: 5.3067 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3956 loss_aux: 0.9400 loss: 2.3355 2022/09/11 20:00:38 - mmengine - INFO - Epoch(train) [129][60/940] lr: 4.0000e-04 eta: 4:04:51 time: 0.6849 data_time: 0.0313 memory: 23708 grad_norm: 5.2162 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2941 loss_aux: 0.8791 loss: 2.1731 2022/09/11 20:00:51 - mmengine - INFO - Epoch(train) [129][80/940] lr: 4.0000e-04 eta: 4:04:35 time: 0.6708 data_time: 0.0330 memory: 23708 grad_norm: 5.2281 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3393 loss_aux: 0.9202 loss: 2.2595 2022/09/11 20:01:05 - mmengine - INFO - Epoch(train) [129][100/940] lr: 4.0000e-04 eta: 4:04:21 time: 0.7067 data_time: 0.0415 memory: 23708 grad_norm: 5.2167 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2996 loss_aux: 0.8792 loss: 2.1788 2022/09/11 20:01:19 - mmengine - INFO - Epoch(train) [129][120/940] lr: 4.0000e-04 eta: 4:04:06 time: 0.6860 data_time: 0.0322 memory: 23708 grad_norm: 5.2653 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2955 loss_aux: 0.9066 loss: 2.2021 2022/09/11 20:01:33 - mmengine - INFO - Epoch(train) [129][140/940] lr: 4.0000e-04 eta: 4:03:51 time: 0.6684 data_time: 0.0308 memory: 23708 grad_norm: 5.2527 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4181 loss_aux: 0.9313 loss: 2.3494 2022/09/11 20:01:46 - mmengine - INFO - Epoch(train) [129][160/940] lr: 4.0000e-04 eta: 4:03:36 time: 0.6845 data_time: 0.0441 memory: 23708 grad_norm: 5.2445 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3810 loss_aux: 0.9556 loss: 2.3367 2022/09/11 20:02:00 - mmengine - INFO - Epoch(train) [129][180/940] lr: 4.0000e-04 eta: 4:03:21 time: 0.7122 data_time: 0.0475 memory: 23708 grad_norm: 5.3019 top1_acc: 0.5312 top5_acc: 0.5625 loss_cls: 1.5648 loss_aux: 1.0215 loss: 2.5863 2022/09/11 20:02:14 - mmengine - INFO - Epoch(train) [129][200/940] lr: 4.0000e-04 eta: 4:03:07 time: 0.6901 data_time: 0.0319 memory: 23708 grad_norm: 5.1540 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3371 loss_aux: 0.9309 loss: 2.2680 2022/09/11 20:02:28 - mmengine - INFO - Epoch(train) [129][220/940] lr: 4.0000e-04 eta: 4:02:52 time: 0.7043 data_time: 0.0308 memory: 23708 grad_norm: 5.1247 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3372 loss_aux: 0.9024 loss: 2.2395 2022/09/11 20:02:42 - mmengine - INFO - Epoch(train) [129][240/940] lr: 4.0000e-04 eta: 4:02:37 time: 0.6916 data_time: 0.0355 memory: 23708 grad_norm: 5.2461 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3445 loss_aux: 0.8968 loss: 2.2413 2022/09/11 20:02:56 - mmengine - INFO - Epoch(train) [129][260/940] lr: 4.0000e-04 eta: 4:02:23 time: 0.6981 data_time: 0.0460 memory: 23708 grad_norm: 5.1519 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3624 loss_aux: 0.8848 loss: 2.2472 2022/09/11 20:03:10 - mmengine - INFO - Epoch(train) [129][280/940] lr: 4.0000e-04 eta: 4:02:08 time: 0.6856 data_time: 0.0312 memory: 23708 grad_norm: 5.2731 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4068 loss_aux: 0.9535 loss: 2.3604 2022/09/11 20:03:24 - mmengine - INFO - Epoch(train) [129][300/940] lr: 4.0000e-04 eta: 4:01:53 time: 0.7030 data_time: 0.0307 memory: 23708 grad_norm: 5.2927 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2972 loss_aux: 0.8810 loss: 2.1782 2022/09/11 20:03:38 - mmengine - INFO - Epoch(train) [129][320/940] lr: 4.0000e-04 eta: 4:01:39 time: 0.7038 data_time: 0.0459 memory: 23708 grad_norm: 5.2342 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2678 loss_aux: 0.8620 loss: 2.1298 2022/09/11 20:03:52 - mmengine - INFO - Epoch(train) [129][340/940] lr: 4.0000e-04 eta: 4:01:24 time: 0.7098 data_time: 0.0427 memory: 23708 grad_norm: 5.2356 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4534 loss_aux: 0.9589 loss: 2.4123 2022/09/11 20:04:06 - mmengine - INFO - Epoch(train) [129][360/940] lr: 4.0000e-04 eta: 4:01:10 time: 0.6941 data_time: 0.0314 memory: 23708 grad_norm: 5.2270 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.4909 loss_aux: 0.9570 loss: 2.4480 2022/09/11 20:04:20 - mmengine - INFO - Epoch(train) [129][380/940] lr: 4.0000e-04 eta: 4:00:56 time: 0.7204 data_time: 0.0349 memory: 23708 grad_norm: 5.1538 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3006 loss_aux: 0.8844 loss: 2.1850 2022/09/11 20:04:35 - mmengine - INFO - Epoch(train) [129][400/940] lr: 4.0000e-04 eta: 4:00:41 time: 0.7121 data_time: 0.0406 memory: 23708 grad_norm: 5.2724 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.2972 loss_aux: 0.8609 loss: 2.1581 2022/09/11 20:04:49 - mmengine - INFO - Epoch(train) [129][420/940] lr: 4.0000e-04 eta: 4:00:27 time: 0.7021 data_time: 0.0440 memory: 23708 grad_norm: 5.2209 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.2947 loss_aux: 0.8940 loss: 2.1887 2022/09/11 20:05:03 - mmengine - INFO - Epoch(train) [129][440/940] lr: 4.0000e-04 eta: 4:00:12 time: 0.6895 data_time: 0.0291 memory: 23708 grad_norm: 5.2063 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2255 loss_aux: 0.8231 loss: 2.0486 2022/09/11 20:05:17 - mmengine - INFO - Epoch(train) [129][460/940] lr: 4.0000e-04 eta: 3:59:58 time: 0.7123 data_time: 0.0378 memory: 23708 grad_norm: 5.1993 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3668 loss_aux: 0.9221 loss: 2.2890 2022/09/11 20:05:31 - mmengine - INFO - Epoch(train) [129][480/940] lr: 4.0000e-04 eta: 3:59:43 time: 0.7049 data_time: 0.0371 memory: 23708 grad_norm: 5.1266 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.4236 loss_aux: 0.9378 loss: 2.3614 2022/09/11 20:05:45 - mmengine - INFO - Epoch(train) [129][500/940] lr: 4.0000e-04 eta: 3:59:29 time: 0.7031 data_time: 0.0408 memory: 23708 grad_norm: 5.2458 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.5057 loss_aux: 1.0059 loss: 2.5116 2022/09/11 20:05:59 - mmengine - INFO - Epoch(train) [129][520/940] lr: 4.0000e-04 eta: 3:59:14 time: 0.6963 data_time: 0.0313 memory: 23708 grad_norm: 5.2893 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3469 loss_aux: 0.9373 loss: 2.2842 2022/09/11 20:06:13 - mmengine - INFO - Epoch(train) [129][540/940] lr: 4.0000e-04 eta: 3:59:00 time: 0.7053 data_time: 0.0321 memory: 23708 grad_norm: 5.3158 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3532 loss_aux: 0.9152 loss: 2.2684 2022/09/11 20:06:27 - mmengine - INFO - Epoch(train) [129][560/940] lr: 4.0000e-04 eta: 3:58:45 time: 0.7051 data_time: 0.0358 memory: 23708 grad_norm: 5.2567 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.4063 loss_aux: 0.9211 loss: 2.3274 2022/09/11 20:06:41 - mmengine - INFO - Epoch(train) [129][580/940] lr: 4.0000e-04 eta: 3:58:31 time: 0.7018 data_time: 0.0403 memory: 23708 grad_norm: 5.2553 top1_acc: 0.4688 top5_acc: 0.6875 loss_cls: 1.5558 loss_aux: 1.0007 loss: 2.5565 2022/09/11 20:06:55 - mmengine - INFO - Epoch(train) [129][600/940] lr: 4.0000e-04 eta: 3:58:16 time: 0.6995 data_time: 0.0389 memory: 23708 grad_norm: 5.2241 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3915 loss_aux: 0.9091 loss: 2.3006 2022/09/11 20:07:09 - mmengine - INFO - Epoch(train) [129][620/940] lr: 4.0000e-04 eta: 3:58:02 time: 0.7071 data_time: 0.0305 memory: 23708 grad_norm: 5.2996 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4239 loss_aux: 0.9498 loss: 2.3737 2022/09/11 20:07:23 - mmengine - INFO - Epoch(train) [129][640/940] lr: 4.0000e-04 eta: 3:57:47 time: 0.6985 data_time: 0.0365 memory: 23708 grad_norm: 5.2496 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2815 loss_aux: 0.8577 loss: 2.1393 2022/09/11 20:07:38 - mmengine - INFO - Epoch(train) [129][660/940] lr: 4.0000e-04 eta: 3:57:33 time: 0.7149 data_time: 0.0420 memory: 23708 grad_norm: 5.2620 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2677 loss_aux: 0.8929 loss: 2.1606 2022/09/11 20:07:51 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 20:07:51 - mmengine - INFO - Epoch(train) [129][680/940] lr: 4.0000e-04 eta: 3:57:19 time: 0.6935 data_time: 0.0343 memory: 23708 grad_norm: 5.2600 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3676 loss_aux: 0.8873 loss: 2.2548 2022/09/11 20:08:06 - mmengine - INFO - Epoch(train) [129][700/940] lr: 4.0000e-04 eta: 3:57:05 time: 0.7189 data_time: 0.0330 memory: 23708 grad_norm: 5.2853 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.3109 loss_aux: 0.8682 loss: 2.1791 2022/09/11 20:08:20 - mmengine - INFO - Epoch(train) [129][720/940] lr: 4.0000e-04 eta: 3:56:51 time: 0.7220 data_time: 0.0421 memory: 23708 grad_norm: 5.2174 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4247 loss_aux: 0.9142 loss: 2.3390 2022/09/11 20:08:34 - mmengine - INFO - Epoch(train) [129][740/940] lr: 4.0000e-04 eta: 3:56:36 time: 0.7071 data_time: 0.0427 memory: 23708 grad_norm: 5.2494 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3378 loss_aux: 0.9162 loss: 2.2541 2022/09/11 20:08:49 - mmengine - INFO - Epoch(train) [129][760/940] lr: 4.0000e-04 eta: 3:56:22 time: 0.7219 data_time: 0.0280 memory: 23708 grad_norm: 5.2022 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3524 loss_aux: 0.8991 loss: 2.2515 2022/09/11 20:09:04 - mmengine - INFO - Epoch(train) [129][780/940] lr: 4.0000e-04 eta: 3:56:09 time: 0.7391 data_time: 0.0353 memory: 23708 grad_norm: 5.2568 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4497 loss_aux: 0.9313 loss: 2.3810 2022/09/11 20:09:18 - mmengine - INFO - Epoch(train) [129][800/940] lr: 4.0000e-04 eta: 3:55:55 time: 0.7171 data_time: 0.0370 memory: 23708 grad_norm: 5.3230 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4297 loss_aux: 0.9335 loss: 2.3632 2022/09/11 20:09:32 - mmengine - INFO - Epoch(train) [129][820/940] lr: 4.0000e-04 eta: 3:55:40 time: 0.7013 data_time: 0.0426 memory: 23708 grad_norm: 5.4154 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4875 loss_aux: 0.9759 loss: 2.4634 2022/09/11 20:09:46 - mmengine - INFO - Epoch(train) [129][840/940] lr: 4.0000e-04 eta: 3:55:26 time: 0.7056 data_time: 0.0289 memory: 23708 grad_norm: 5.2492 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3446 loss_aux: 0.8985 loss: 2.2431 2022/09/11 20:10:01 - mmengine - INFO - Epoch(train) [129][860/940] lr: 4.0000e-04 eta: 3:55:12 time: 0.7212 data_time: 0.0407 memory: 23708 grad_norm: 5.2580 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2623 loss_aux: 0.8768 loss: 2.1391 2022/09/11 20:10:16 - mmengine - INFO - Epoch(train) [129][880/940] lr: 4.0000e-04 eta: 3:54:58 time: 0.7549 data_time: 0.0371 memory: 23708 grad_norm: 5.2707 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3380 loss_aux: 0.8930 loss: 2.2310 2022/09/11 20:10:30 - mmengine - INFO - Epoch(train) [129][900/940] lr: 4.0000e-04 eta: 3:54:44 time: 0.7037 data_time: 0.0427 memory: 23708 grad_norm: 5.1946 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3055 loss_aux: 0.8810 loss: 2.1866 2022/09/11 20:10:43 - mmengine - INFO - Epoch(train) [129][920/940] lr: 4.0000e-04 eta: 3:54:29 time: 0.6881 data_time: 0.0284 memory: 23708 grad_norm: 5.3160 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.5649 loss_aux: 1.0337 loss: 2.5985 2022/09/11 20:10:56 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 20:10:56 - mmengine - INFO - Epoch(train) [129][940/940] lr: 4.0000e-04 eta: 3:54:13 time: 0.6441 data_time: 0.0294 memory: 23708 grad_norm: 5.5525 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.2535 loss_aux: 0.8565 loss: 2.1100 2022/09/11 20:10:57 - mmengine - INFO - Saving checkpoint at 129 epochs 2022/09/11 20:11:22 - mmengine - INFO - Epoch(train) [130][20/940] lr: 4.0000e-04 eta: 3:54:06 time: 0.9879 data_time: 0.3092 memory: 23708 grad_norm: 5.1917 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4377 loss_aux: 0.9607 loss: 2.3984 2022/09/11 20:11:36 - mmengine - INFO - Epoch(train) [130][40/940] lr: 4.0000e-04 eta: 3:53:51 time: 0.6720 data_time: 0.0229 memory: 23708 grad_norm: 5.2438 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4780 loss_aux: 0.9667 loss: 2.4447 2022/09/11 20:11:49 - mmengine - INFO - Epoch(train) [130][60/940] lr: 4.0000e-04 eta: 3:53:35 time: 0.6763 data_time: 0.0435 memory: 23708 grad_norm: 5.1938 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4005 loss_aux: 0.9374 loss: 2.3378 2022/09/11 20:12:03 - mmengine - INFO - Epoch(train) [130][80/940] lr: 4.0000e-04 eta: 3:53:20 time: 0.6797 data_time: 0.0397 memory: 23708 grad_norm: 5.2249 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4235 loss_aux: 0.9874 loss: 2.4109 2022/09/11 20:12:17 - mmengine - INFO - Epoch(train) [130][100/940] lr: 4.0000e-04 eta: 3:53:06 time: 0.6925 data_time: 0.0404 memory: 23708 grad_norm: 5.4238 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4218 loss_aux: 0.9492 loss: 2.3710 2022/09/11 20:12:30 - mmengine - INFO - Epoch(train) [130][120/940] lr: 4.0000e-04 eta: 3:52:51 time: 0.6765 data_time: 0.0345 memory: 23708 grad_norm: 5.1617 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3274 loss_aux: 0.8897 loss: 2.2171 2022/09/11 20:12:44 - mmengine - INFO - Epoch(train) [130][140/940] lr: 4.0000e-04 eta: 3:52:36 time: 0.6831 data_time: 0.0365 memory: 23708 grad_norm: 5.1840 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3112 loss_aux: 0.8648 loss: 2.1760 2022/09/11 20:12:58 - mmengine - INFO - Epoch(train) [130][160/940] lr: 4.0000e-04 eta: 3:52:21 time: 0.6820 data_time: 0.0351 memory: 23708 grad_norm: 5.2624 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4203 loss_aux: 0.9591 loss: 2.3794 2022/09/11 20:13:12 - mmengine - INFO - Epoch(train) [130][180/940] lr: 4.0000e-04 eta: 3:52:06 time: 0.6913 data_time: 0.0420 memory: 23708 grad_norm: 5.2585 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.5264 loss_aux: 1.0172 loss: 2.5436 2022/09/11 20:13:25 - mmengine - INFO - Epoch(train) [130][200/940] lr: 4.0000e-04 eta: 3:51:51 time: 0.6953 data_time: 0.0313 memory: 23708 grad_norm: 5.2054 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3336 loss_aux: 0.9143 loss: 2.2479 2022/09/11 20:13:39 - mmengine - INFO - Epoch(train) [130][220/940] lr: 4.0000e-04 eta: 3:51:37 time: 0.6924 data_time: 0.0410 memory: 23708 grad_norm: 5.3041 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4308 loss_aux: 0.9634 loss: 2.3941 2022/09/11 20:13:53 - mmengine - INFO - Epoch(train) [130][240/940] lr: 4.0000e-04 eta: 3:51:22 time: 0.6803 data_time: 0.0359 memory: 23708 grad_norm: 5.1775 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.2942 loss_aux: 0.8966 loss: 2.1908 2022/09/11 20:14:07 - mmengine - INFO - Epoch(train) [130][260/940] lr: 4.0000e-04 eta: 3:51:07 time: 0.7027 data_time: 0.0407 memory: 23708 grad_norm: 5.3220 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2358 loss_aux: 0.8659 loss: 2.1017 2022/09/11 20:14:21 - mmengine - INFO - Epoch(train) [130][280/940] lr: 4.0000e-04 eta: 3:50:53 time: 0.7062 data_time: 0.0412 memory: 23708 grad_norm: 5.2869 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4263 loss_aux: 0.9457 loss: 2.3721 2022/09/11 20:14:35 - mmengine - INFO - Epoch(train) [130][300/940] lr: 4.0000e-04 eta: 3:50:38 time: 0.6906 data_time: 0.0338 memory: 23708 grad_norm: 5.3375 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3486 loss_aux: 0.8857 loss: 2.2343 2022/09/11 20:14:49 - mmengine - INFO - Epoch(train) [130][320/940] lr: 4.0000e-04 eta: 3:50:24 time: 0.7091 data_time: 0.0362 memory: 23708 grad_norm: 5.3036 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4045 loss_aux: 0.9236 loss: 2.3282 2022/09/11 20:15:03 - mmengine - INFO - Epoch(train) [130][340/940] lr: 4.0000e-04 eta: 3:50:09 time: 0.7108 data_time: 0.0394 memory: 23708 grad_norm: 5.3769 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.4472 loss_aux: 0.9652 loss: 2.4124 2022/09/11 20:15:17 - mmengine - INFO - Epoch(train) [130][360/940] lr: 4.0000e-04 eta: 3:49:55 time: 0.6961 data_time: 0.0401 memory: 23708 grad_norm: 5.2141 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3267 loss_aux: 0.8847 loss: 2.2114 2022/09/11 20:15:31 - mmengine - INFO - Epoch(train) [130][380/940] lr: 4.0000e-04 eta: 3:49:40 time: 0.7016 data_time: 0.0332 memory: 23708 grad_norm: 5.3111 top1_acc: 0.4688 top5_acc: 0.7812 loss_cls: 1.4420 loss_aux: 0.9609 loss: 2.4029 2022/09/11 20:15:45 - mmengine - INFO - Epoch(train) [130][400/940] lr: 4.0000e-04 eta: 3:49:26 time: 0.6972 data_time: 0.0363 memory: 23708 grad_norm: 5.2694 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3756 loss_aux: 0.9462 loss: 2.3218 2022/09/11 20:16:00 - mmengine - INFO - Epoch(train) [130][420/940] lr: 4.0000e-04 eta: 3:49:12 time: 0.7285 data_time: 0.0489 memory: 23708 grad_norm: 5.3195 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3192 loss_aux: 0.8699 loss: 2.1890 2022/09/11 20:16:14 - mmengine - INFO - Epoch(train) [130][440/940] lr: 4.0000e-04 eta: 3:48:57 time: 0.7002 data_time: 0.0366 memory: 23708 grad_norm: 5.3188 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2825 loss_aux: 0.8681 loss: 2.1505 2022/09/11 20:16:28 - mmengine - INFO - Epoch(train) [130][460/940] lr: 4.0000e-04 eta: 3:48:43 time: 0.6926 data_time: 0.0357 memory: 23708 grad_norm: 5.2166 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3491 loss_aux: 0.8850 loss: 2.2341 2022/09/11 20:16:42 - mmengine - INFO - Epoch(train) [130][480/940] lr: 4.0000e-04 eta: 3:48:28 time: 0.6930 data_time: 0.0381 memory: 23708 grad_norm: 5.2593 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2709 loss_aux: 0.8696 loss: 2.1405 2022/09/11 20:16:56 - mmengine - INFO - Epoch(train) [130][500/940] lr: 4.0000e-04 eta: 3:48:14 time: 0.7187 data_time: 0.0389 memory: 23708 grad_norm: 5.3751 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3784 loss_aux: 0.9476 loss: 2.3260 2022/09/11 20:17:10 - mmengine - INFO - Epoch(train) [130][520/940] lr: 4.0000e-04 eta: 3:48:00 time: 0.7050 data_time: 0.0403 memory: 23708 grad_norm: 5.3321 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4116 loss_aux: 0.9435 loss: 2.3551 2022/09/11 20:17:24 - mmengine - INFO - Epoch(train) [130][540/940] lr: 4.0000e-04 eta: 3:47:45 time: 0.6923 data_time: 0.0350 memory: 23708 grad_norm: 5.2940 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.4114 loss_aux: 0.9614 loss: 2.3728 2022/09/11 20:17:38 - mmengine - INFO - Epoch(train) [130][560/940] lr: 4.0000e-04 eta: 3:47:30 time: 0.6958 data_time: 0.0385 memory: 23708 grad_norm: 5.3868 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4418 loss_aux: 0.9500 loss: 2.3918 2022/09/11 20:17:52 - mmengine - INFO - Epoch(train) [130][580/940] lr: 4.0000e-04 eta: 3:47:16 time: 0.7054 data_time: 0.0445 memory: 23708 grad_norm: 5.3390 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3490 loss_aux: 0.9326 loss: 2.2816 2022/09/11 20:18:06 - mmengine - INFO - Epoch(train) [130][600/940] lr: 4.0000e-04 eta: 3:47:01 time: 0.6951 data_time: 0.0315 memory: 23708 grad_norm: 5.2529 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3951 loss_aux: 0.8997 loss: 2.2948 2022/09/11 20:18:20 - mmengine - INFO - Epoch(train) [130][620/940] lr: 4.0000e-04 eta: 3:46:47 time: 0.7159 data_time: 0.0372 memory: 23708 grad_norm: 5.2157 top1_acc: 0.5000 top5_acc: 0.6875 loss_cls: 1.2868 loss_aux: 0.9111 loss: 2.1979 2022/09/11 20:18:34 - mmengine - INFO - Epoch(train) [130][640/940] lr: 4.0000e-04 eta: 3:46:33 time: 0.6989 data_time: 0.0383 memory: 23708 grad_norm: 5.3279 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4439 loss_aux: 0.9611 loss: 2.4049 2022/09/11 20:18:48 - mmengine - INFO - Epoch(train) [130][660/940] lr: 4.0000e-04 eta: 3:46:18 time: 0.7009 data_time: 0.0383 memory: 23708 grad_norm: 5.3416 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4414 loss_aux: 0.9769 loss: 2.4183 2022/09/11 20:19:02 - mmengine - INFO - Epoch(train) [130][680/940] lr: 4.0000e-04 eta: 3:46:04 time: 0.6984 data_time: 0.0339 memory: 23708 grad_norm: 5.1977 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3675 loss_aux: 0.9214 loss: 2.2888 2022/09/11 20:19:16 - mmengine - INFO - Epoch(train) [130][700/940] lr: 4.0000e-04 eta: 3:45:49 time: 0.6979 data_time: 0.0369 memory: 23708 grad_norm: 5.2708 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3154 loss_aux: 0.8872 loss: 2.2026 2022/09/11 20:19:30 - mmengine - INFO - Epoch(train) [130][720/940] lr: 4.0000e-04 eta: 3:45:35 time: 0.7117 data_time: 0.0391 memory: 23708 grad_norm: 5.1976 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3567 loss_aux: 0.9231 loss: 2.2798 2022/09/11 20:19:44 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 20:19:44 - mmengine - INFO - Epoch(train) [130][740/940] lr: 4.0000e-04 eta: 3:45:20 time: 0.7082 data_time: 0.0381 memory: 23708 grad_norm: 5.1969 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.3770 loss_aux: 0.9097 loss: 2.2866 2022/09/11 20:19:58 - mmengine - INFO - Epoch(train) [130][760/940] lr: 4.0000e-04 eta: 3:45:06 time: 0.6993 data_time: 0.0327 memory: 23708 grad_norm: 5.2125 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3726 loss_aux: 0.9357 loss: 2.3084 2022/09/11 20:20:12 - mmengine - INFO - Epoch(train) [130][780/940] lr: 4.0000e-04 eta: 3:44:51 time: 0.6952 data_time: 0.0323 memory: 23708 grad_norm: 5.3558 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.6051 loss_aux: 1.0375 loss: 2.6426 2022/09/11 20:20:27 - mmengine - INFO - Epoch(train) [130][800/940] lr: 4.0000e-04 eta: 3:44:37 time: 0.7163 data_time: 0.0406 memory: 23708 grad_norm: 5.4007 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.5232 loss_aux: 0.9976 loss: 2.5207 2022/09/11 20:20:41 - mmengine - INFO - Epoch(train) [130][820/940] lr: 4.0000e-04 eta: 3:44:23 time: 0.6950 data_time: 0.0401 memory: 23708 grad_norm: 5.3544 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3114 loss_aux: 0.8612 loss: 2.1726 2022/09/11 20:20:55 - mmengine - INFO - Epoch(train) [130][840/940] lr: 4.0000e-04 eta: 3:44:08 time: 0.6971 data_time: 0.0294 memory: 23708 grad_norm: 5.3006 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3820 loss_aux: 0.9648 loss: 2.3469 2022/09/11 20:21:09 - mmengine - INFO - Epoch(train) [130][860/940] lr: 4.0000e-04 eta: 3:43:54 time: 0.7076 data_time: 0.0362 memory: 23708 grad_norm: 5.2466 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3263 loss_aux: 0.8871 loss: 2.2134 2022/09/11 20:21:23 - mmengine - INFO - Epoch(train) [130][880/940] lr: 4.0000e-04 eta: 3:43:40 time: 0.7188 data_time: 0.0465 memory: 23708 grad_norm: 5.3476 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.4471 loss_aux: 0.9652 loss: 2.4123 2022/09/11 20:21:37 - mmengine - INFO - Epoch(train) [130][900/940] lr: 4.0000e-04 eta: 3:43:25 time: 0.7098 data_time: 0.0416 memory: 23708 grad_norm: 5.3116 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4182 loss_aux: 0.9617 loss: 2.3799 2022/09/11 20:21:51 - mmengine - INFO - Epoch(train) [130][920/940] lr: 4.0000e-04 eta: 3:43:11 time: 0.7002 data_time: 0.0294 memory: 23708 grad_norm: 5.2234 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4830 loss_aux: 0.9636 loss: 2.4467 2022/09/11 20:22:04 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 20:22:04 - mmengine - INFO - Epoch(train) [130][940/940] lr: 4.0000e-04 eta: 3:42:55 time: 0.6491 data_time: 0.0280 memory: 23708 grad_norm: 5.5843 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.3205 loss_aux: 0.8981 loss: 2.2186 2022/09/11 20:22:04 - mmengine - INFO - Saving checkpoint at 130 epochs 2022/09/11 20:22:14 - mmengine - INFO - Epoch(val) [130][20/310] eta: 0:01:02 time: 0.2172 data_time: 0.1337 memory: 2130 2022/09/11 20:22:17 - mmengine - INFO - Epoch(val) [130][40/310] eta: 0:00:37 time: 0.1401 data_time: 0.0611 memory: 2130 2022/09/11 20:22:20 - mmengine - INFO - Epoch(val) [130][60/310] eta: 0:00:40 time: 0.1625 data_time: 0.0832 memory: 2130 2022/09/11 20:22:23 - mmengine - INFO - Epoch(val) [130][80/310] eta: 0:00:33 time: 0.1476 data_time: 0.0673 memory: 2130 2022/09/11 20:22:27 - mmengine - INFO - Epoch(val) [130][100/310] eta: 0:00:35 time: 0.1682 data_time: 0.0873 memory: 2130 2022/09/11 20:22:30 - mmengine - INFO - Epoch(val) [130][120/310] eta: 0:00:28 time: 0.1495 data_time: 0.0707 memory: 2130 2022/09/11 20:22:33 - mmengine - INFO - Epoch(val) [130][140/310] eta: 0:00:31 time: 0.1851 data_time: 0.1067 memory: 2130 2022/09/11 20:22:36 - mmengine - INFO - Epoch(val) [130][160/310] eta: 0:00:22 time: 0.1512 data_time: 0.0737 memory: 2130 2022/09/11 20:22:40 - mmengine - INFO - Epoch(val) [130][180/310] eta: 0:00:21 time: 0.1683 data_time: 0.0909 memory: 2130 2022/09/11 20:22:42 - mmengine - INFO - Epoch(val) [130][200/310] eta: 0:00:15 time: 0.1407 data_time: 0.0606 memory: 2130 2022/09/11 20:22:46 - mmengine - INFO - Epoch(val) [130][220/310] eta: 0:00:14 time: 0.1578 data_time: 0.0788 memory: 2130 2022/09/11 20:22:49 - mmengine - INFO - Epoch(val) [130][240/310] eta: 0:00:10 time: 0.1521 data_time: 0.0705 memory: 2130 2022/09/11 20:22:52 - mmengine - INFO - Epoch(val) [130][260/310] eta: 0:00:08 time: 0.1608 data_time: 0.0816 memory: 2130 2022/09/11 20:22:55 - mmengine - INFO - Epoch(val) [130][280/310] eta: 0:00:05 time: 0.1807 data_time: 0.1049 memory: 2130 2022/09/11 20:22:58 - mmengine - INFO - Epoch(val) [130][300/310] eta: 0:00:01 time: 0.1210 data_time: 0.0482 memory: 2130 2022/09/11 20:23:00 - mmengine - INFO - Epoch(val) [130][310/310] acc/top1: 0.6672 acc/top5: 0.8674 acc/mean1: 0.6671 2022/09/11 20:23:00 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb/best_acc/top1_epoch_120.pth is removed 2022/09/11 20:23:04 - mmengine - INFO - The best checkpoint with 0.6672 acc/top1 at 130 epoch is saved to best_acc/top1_epoch_130.pth. 2022/09/11 20:23:24 - mmengine - INFO - Epoch(train) [131][20/940] lr: 4.0000e-04 eta: 3:42:47 time: 0.9840 data_time: 0.3281 memory: 23708 grad_norm: 5.2587 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.4041 loss_aux: 0.9724 loss: 2.3764 2022/09/11 20:23:37 - mmengine - INFO - Epoch(train) [131][40/940] lr: 4.0000e-04 eta: 3:42:32 time: 0.6707 data_time: 0.0306 memory: 23708 grad_norm: 5.2498 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.3760 loss_aux: 0.9048 loss: 2.2808 2022/09/11 20:23:51 - mmengine - INFO - Epoch(train) [131][60/940] lr: 4.0000e-04 eta: 3:42:17 time: 0.6789 data_time: 0.0302 memory: 23708 grad_norm: 5.3916 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4547 loss_aux: 0.9553 loss: 2.4100 2022/09/11 20:24:05 - mmengine - INFO - Epoch(train) [131][80/940] lr: 4.0000e-04 eta: 3:42:02 time: 0.6804 data_time: 0.0409 memory: 23708 grad_norm: 5.1897 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.4052 loss_aux: 0.9009 loss: 2.3061 2022/09/11 20:24:19 - mmengine - INFO - Epoch(train) [131][100/940] lr: 4.0000e-04 eta: 3:41:48 time: 0.6957 data_time: 0.0433 memory: 23708 grad_norm: 5.3076 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4015 loss_aux: 0.9761 loss: 2.3776 2022/09/11 20:24:32 - mmengine - INFO - Epoch(train) [131][120/940] lr: 4.0000e-04 eta: 3:41:33 time: 0.6814 data_time: 0.0340 memory: 23708 grad_norm: 5.1938 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.4317 loss_aux: 0.9495 loss: 2.3812 2022/09/11 20:24:46 - mmengine - INFO - Epoch(train) [131][140/940] lr: 4.0000e-04 eta: 3:41:18 time: 0.6749 data_time: 0.0312 memory: 23708 grad_norm: 5.3143 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2541 loss_aux: 0.8776 loss: 2.1316 2022/09/11 20:24:59 - mmengine - INFO - Epoch(train) [131][160/940] lr: 4.0000e-04 eta: 3:41:03 time: 0.6751 data_time: 0.0366 memory: 23708 grad_norm: 5.2839 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3822 loss_aux: 0.9175 loss: 2.2997 2022/09/11 20:25:13 - mmengine - INFO - Epoch(train) [131][180/940] lr: 4.0000e-04 eta: 3:40:48 time: 0.6845 data_time: 0.0442 memory: 23708 grad_norm: 5.2955 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2633 loss_aux: 0.8266 loss: 2.0899 2022/09/11 20:25:26 - mmengine - INFO - Epoch(train) [131][200/940] lr: 4.0000e-04 eta: 3:40:33 time: 0.6758 data_time: 0.0329 memory: 23708 grad_norm: 5.3839 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4545 loss_aux: 0.9929 loss: 2.4475 2022/09/11 20:25:40 - mmengine - INFO - Epoch(train) [131][220/940] lr: 4.0000e-04 eta: 3:40:18 time: 0.6700 data_time: 0.0299 memory: 23708 grad_norm: 5.3224 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4280 loss_aux: 0.9326 loss: 2.3606 2022/09/11 20:25:53 - mmengine - INFO - Epoch(train) [131][240/940] lr: 4.0000e-04 eta: 3:40:03 time: 0.6806 data_time: 0.0370 memory: 23708 grad_norm: 5.2587 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3503 loss_aux: 0.9292 loss: 2.2795 2022/09/11 20:26:07 - mmengine - INFO - Epoch(train) [131][260/940] lr: 4.0000e-04 eta: 3:39:48 time: 0.6826 data_time: 0.0486 memory: 23708 grad_norm: 5.3241 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2488 loss_aux: 0.9070 loss: 2.1559 2022/09/11 20:26:20 - mmengine - INFO - Epoch(train) [131][280/940] lr: 4.0000e-04 eta: 3:39:33 time: 0.6692 data_time: 0.0346 memory: 23708 grad_norm: 5.3867 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.3304 loss_aux: 0.9127 loss: 2.2431 2022/09/11 20:26:34 - mmengine - INFO - Epoch(train) [131][300/940] lr: 4.0000e-04 eta: 3:39:18 time: 0.6828 data_time: 0.0412 memory: 23708 grad_norm: 5.3133 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3437 loss_aux: 0.8936 loss: 2.2373 2022/09/11 20:26:48 - mmengine - INFO - Epoch(train) [131][320/940] lr: 4.0000e-04 eta: 3:39:03 time: 0.6736 data_time: 0.0351 memory: 23708 grad_norm: 5.3371 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4148 loss_aux: 0.9258 loss: 2.3406 2022/09/11 20:27:01 - mmengine - INFO - Epoch(train) [131][340/940] lr: 4.0000e-04 eta: 3:38:48 time: 0.6838 data_time: 0.0457 memory: 23708 grad_norm: 5.2544 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2920 loss_aux: 0.8951 loss: 2.1871 2022/09/11 20:27:15 - mmengine - INFO - Epoch(train) [131][360/940] lr: 4.0000e-04 eta: 3:38:33 time: 0.6639 data_time: 0.0326 memory: 23708 grad_norm: 5.2752 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3463 loss_aux: 0.9118 loss: 2.2581 2022/09/11 20:27:28 - mmengine - INFO - Epoch(train) [131][380/940] lr: 4.0000e-04 eta: 3:38:18 time: 0.6637 data_time: 0.0352 memory: 23708 grad_norm: 5.3210 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2913 loss_aux: 0.8641 loss: 2.1554 2022/09/11 20:27:41 - mmengine - INFO - Epoch(train) [131][400/940] lr: 4.0000e-04 eta: 3:38:02 time: 0.6692 data_time: 0.0367 memory: 23708 grad_norm: 5.2005 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4495 loss_aux: 0.9527 loss: 2.4021 2022/09/11 20:27:55 - mmengine - INFO - Epoch(train) [131][420/940] lr: 4.0000e-04 eta: 3:37:48 time: 0.6797 data_time: 0.0465 memory: 23708 grad_norm: 5.2671 top1_acc: 0.8438 top5_acc: 1.0000 loss_cls: 1.3951 loss_aux: 0.9300 loss: 2.3250 2022/09/11 20:28:08 - mmengine - INFO - Epoch(train) [131][440/940] lr: 4.0000e-04 eta: 3:37:33 time: 0.6778 data_time: 0.0367 memory: 23708 grad_norm: 5.3130 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3279 loss_aux: 0.9183 loss: 2.2461 2022/09/11 20:28:22 - mmengine - INFO - Epoch(train) [131][460/940] lr: 4.0000e-04 eta: 3:37:18 time: 0.6903 data_time: 0.0352 memory: 23708 grad_norm: 5.3723 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.5149 loss_aux: 0.9955 loss: 2.5105 2022/09/11 20:28:36 - mmengine - INFO - Epoch(train) [131][480/940] lr: 4.0000e-04 eta: 3:37:03 time: 0.6817 data_time: 0.0381 memory: 23708 grad_norm: 5.3921 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4297 loss_aux: 0.9395 loss: 2.3692 2022/09/11 20:28:50 - mmengine - INFO - Epoch(train) [131][500/940] lr: 4.0000e-04 eta: 3:36:49 time: 0.6981 data_time: 0.0452 memory: 23708 grad_norm: 5.2830 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4091 loss_aux: 0.9418 loss: 2.3510 2022/09/11 20:29:04 - mmengine - INFO - Epoch(train) [131][520/940] lr: 4.0000e-04 eta: 3:36:34 time: 0.6872 data_time: 0.0434 memory: 23708 grad_norm: 5.3093 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4274 loss_aux: 0.9421 loss: 2.3695 2022/09/11 20:29:17 - mmengine - INFO - Epoch(train) [131][540/940] lr: 4.0000e-04 eta: 3:36:19 time: 0.6769 data_time: 0.0288 memory: 23708 grad_norm: 5.2065 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3111 loss_aux: 0.8937 loss: 2.2048 2022/09/11 20:29:31 - mmengine - INFO - Epoch(train) [131][560/940] lr: 4.0000e-04 eta: 3:36:04 time: 0.6850 data_time: 0.0350 memory: 23708 grad_norm: 5.1789 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.2799 loss_aux: 0.8455 loss: 2.1254 2022/09/11 20:29:45 - mmengine - INFO - Epoch(train) [131][580/940] lr: 4.0000e-04 eta: 3:35:50 time: 0.7004 data_time: 0.0465 memory: 23708 grad_norm: 5.2958 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4872 loss_aux: 0.9871 loss: 2.4743 2022/09/11 20:29:59 - mmengine - INFO - Epoch(train) [131][600/940] lr: 4.0000e-04 eta: 3:35:35 time: 0.6977 data_time: 0.0397 memory: 23708 grad_norm: 5.2953 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4187 loss_aux: 0.9362 loss: 2.3550 2022/09/11 20:30:12 - mmengine - INFO - Epoch(train) [131][620/940] lr: 4.0000e-04 eta: 3:35:20 time: 0.6750 data_time: 0.0343 memory: 23708 grad_norm: 5.3014 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4146 loss_aux: 0.9086 loss: 2.3232 2022/09/11 20:30:26 - mmengine - INFO - Epoch(train) [131][640/940] lr: 4.0000e-04 eta: 3:35:06 time: 0.6850 data_time: 0.0326 memory: 23708 grad_norm: 5.3214 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.3875 loss_aux: 0.9346 loss: 2.3222 2022/09/11 20:30:40 - mmengine - INFO - Epoch(train) [131][660/940] lr: 4.0000e-04 eta: 3:34:51 time: 0.7095 data_time: 0.0448 memory: 23708 grad_norm: 5.3306 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4198 loss_aux: 0.9506 loss: 2.3703 2022/09/11 20:30:54 - mmengine - INFO - Epoch(train) [131][680/940] lr: 4.0000e-04 eta: 3:34:37 time: 0.7094 data_time: 0.0438 memory: 23708 grad_norm: 5.3751 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3296 loss_aux: 0.9056 loss: 2.2352 2022/09/11 20:31:08 - mmengine - INFO - Epoch(train) [131][700/940] lr: 4.0000e-04 eta: 3:34:22 time: 0.6740 data_time: 0.0332 memory: 23708 grad_norm: 5.3427 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3401 loss_aux: 0.8859 loss: 2.2260 2022/09/11 20:31:22 - mmengine - INFO - Epoch(train) [131][720/940] lr: 4.0000e-04 eta: 3:34:08 time: 0.7144 data_time: 0.0375 memory: 23708 grad_norm: 5.2446 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5156 loss_aux: 0.9752 loss: 2.4908 2022/09/11 20:31:36 - mmengine - INFO - Epoch(train) [131][740/940] lr: 4.0000e-04 eta: 3:33:54 time: 0.6974 data_time: 0.0425 memory: 23708 grad_norm: 5.3387 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4457 loss_aux: 0.9651 loss: 2.4108 2022/09/11 20:31:50 - mmengine - INFO - Epoch(train) [131][760/940] lr: 4.0000e-04 eta: 3:33:39 time: 0.6936 data_time: 0.0305 memory: 23708 grad_norm: 5.3721 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2853 loss_aux: 0.8791 loss: 2.1644 2022/09/11 20:32:04 - mmengine - INFO - Epoch(train) [131][780/940] lr: 4.0000e-04 eta: 3:33:24 time: 0.6838 data_time: 0.0306 memory: 23708 grad_norm: 5.3346 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3709 loss_aux: 0.9140 loss: 2.2849 2022/09/11 20:32:17 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 20:32:17 - mmengine - INFO - Epoch(train) [131][800/940] lr: 4.0000e-04 eta: 3:33:09 time: 0.6823 data_time: 0.0391 memory: 23708 grad_norm: 5.3327 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3611 loss_aux: 0.9338 loss: 2.2949 2022/09/11 20:32:31 - mmengine - INFO - Epoch(train) [131][820/940] lr: 4.0000e-04 eta: 3:32:55 time: 0.7046 data_time: 0.0526 memory: 23708 grad_norm: 5.3297 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3740 loss_aux: 0.9298 loss: 2.3038 2022/09/11 20:32:46 - mmengine - INFO - Epoch(train) [131][840/940] lr: 4.0000e-04 eta: 3:32:41 time: 0.7117 data_time: 0.0322 memory: 23708 grad_norm: 5.2862 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3715 loss_aux: 0.9181 loss: 2.2896 2022/09/11 20:33:02 - mmengine - INFO - Epoch(train) [131][860/940] lr: 4.0000e-04 eta: 3:32:29 time: 0.8151 data_time: 0.0312 memory: 23708 grad_norm: 5.4187 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4409 loss_aux: 0.9412 loss: 2.3822 2022/09/11 20:33:16 - mmengine - INFO - Epoch(train) [131][880/940] lr: 4.0000e-04 eta: 3:32:14 time: 0.6944 data_time: 0.0345 memory: 23708 grad_norm: 5.3277 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3957 loss_aux: 0.9420 loss: 2.3377 2022/09/11 20:33:30 - mmengine - INFO - Epoch(train) [131][900/940] lr: 4.0000e-04 eta: 3:32:00 time: 0.7162 data_time: 0.0419 memory: 23708 grad_norm: 5.2892 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.3275 loss_aux: 0.8888 loss: 2.2163 2022/09/11 20:33:44 - mmengine - INFO - Epoch(train) [131][920/940] lr: 4.0000e-04 eta: 3:31:46 time: 0.7060 data_time: 0.0279 memory: 23708 grad_norm: 5.3123 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3274 loss_aux: 0.9304 loss: 2.2577 2022/09/11 20:33:57 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 20:33:57 - mmengine - INFO - Epoch(train) [131][940/940] lr: 4.0000e-04 eta: 3:31:31 time: 0.6553 data_time: 0.0271 memory: 23708 grad_norm: 5.4800 top1_acc: 0.2857 top5_acc: 0.5714 loss_cls: 1.5069 loss_aux: 0.9714 loss: 2.4783 2022/09/11 20:33:57 - mmengine - INFO - Saving checkpoint at 131 epochs 2022/09/11 20:34:22 - mmengine - INFO - Epoch(train) [132][20/940] lr: 4.0000e-04 eta: 3:31:22 time: 0.9795 data_time: 0.3252 memory: 23708 grad_norm: 5.2592 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3900 loss_aux: 0.9441 loss: 2.3341 2022/09/11 20:34:36 - mmengine - INFO - Epoch(train) [132][40/940] lr: 4.0000e-04 eta: 3:31:07 time: 0.6762 data_time: 0.0263 memory: 23708 grad_norm: 5.2096 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4230 loss_aux: 0.9489 loss: 2.3719 2022/09/11 20:34:50 - mmengine - INFO - Epoch(train) [132][60/940] lr: 4.0000e-04 eta: 3:30:52 time: 0.6846 data_time: 0.0378 memory: 23708 grad_norm: 5.2669 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3166 loss_aux: 0.9082 loss: 2.2249 2022/09/11 20:35:03 - mmengine - INFO - Epoch(train) [132][80/940] lr: 4.0000e-04 eta: 3:30:37 time: 0.6699 data_time: 0.0329 memory: 23708 grad_norm: 5.3330 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3416 loss_aux: 0.8966 loss: 2.2382 2022/09/11 20:35:17 - mmengine - INFO - Epoch(train) [132][100/940] lr: 4.0000e-04 eta: 3:30:23 time: 0.6954 data_time: 0.0389 memory: 23708 grad_norm: 5.2979 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3789 loss_aux: 0.9343 loss: 2.3132 2022/09/11 20:35:31 - mmengine - INFO - Epoch(train) [132][120/940] lr: 4.0000e-04 eta: 3:30:08 time: 0.6884 data_time: 0.0356 memory: 23708 grad_norm: 5.3144 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4093 loss_aux: 0.9089 loss: 2.3182 2022/09/11 20:35:45 - mmengine - INFO - Epoch(train) [132][140/940] lr: 4.0000e-04 eta: 3:29:53 time: 0.6940 data_time: 0.0456 memory: 23708 grad_norm: 5.3859 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3951 loss_aux: 0.9517 loss: 2.3467 2022/09/11 20:35:59 - mmengine - INFO - Epoch(train) [132][160/940] lr: 4.0000e-04 eta: 3:29:39 time: 0.6938 data_time: 0.0345 memory: 23708 grad_norm: 5.2871 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4029 loss_aux: 0.9173 loss: 2.3203 2022/09/11 20:36:13 - mmengine - INFO - Epoch(train) [132][180/940] lr: 4.0000e-04 eta: 3:29:24 time: 0.7019 data_time: 0.0415 memory: 23708 grad_norm: 5.1723 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4224 loss_aux: 0.9692 loss: 2.3916 2022/09/11 20:36:26 - mmengine - INFO - Epoch(train) [132][200/940] lr: 4.0000e-04 eta: 3:29:10 time: 0.6870 data_time: 0.0317 memory: 23708 grad_norm: 5.3054 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2804 loss_aux: 0.9020 loss: 2.1824 2022/09/11 20:36:40 - mmengine - INFO - Epoch(train) [132][220/940] lr: 4.0000e-04 eta: 3:28:55 time: 0.6923 data_time: 0.0344 memory: 23708 grad_norm: 5.3927 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3447 loss_aux: 0.9178 loss: 2.2625 2022/09/11 20:36:54 - mmengine - INFO - Epoch(train) [132][240/940] lr: 4.0000e-04 eta: 3:28:41 time: 0.6988 data_time: 0.0448 memory: 23708 grad_norm: 5.3282 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3686 loss_aux: 0.9222 loss: 2.2908 2022/09/11 20:37:08 - mmengine - INFO - Epoch(train) [132][260/940] lr: 4.0000e-04 eta: 3:28:26 time: 0.6999 data_time: 0.0381 memory: 23708 grad_norm: 5.3645 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3766 loss_aux: 0.9183 loss: 2.2949 2022/09/11 20:37:22 - mmengine - INFO - Epoch(train) [132][280/940] lr: 4.0000e-04 eta: 3:28:12 time: 0.7036 data_time: 0.0320 memory: 23708 grad_norm: 5.3077 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3967 loss_aux: 0.9189 loss: 2.3156 2022/09/11 20:37:36 - mmengine - INFO - Epoch(train) [132][300/940] lr: 4.0000e-04 eta: 3:27:57 time: 0.6860 data_time: 0.0368 memory: 23708 grad_norm: 5.4022 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4766 loss_aux: 0.9884 loss: 2.4650 2022/09/11 20:37:50 - mmengine - INFO - Epoch(train) [132][320/940] lr: 4.0000e-04 eta: 3:27:43 time: 0.7015 data_time: 0.0380 memory: 23708 grad_norm: 5.2579 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3847 loss_aux: 0.9503 loss: 2.3350 2022/09/11 20:38:04 - mmengine - INFO - Epoch(train) [132][340/940] lr: 4.0000e-04 eta: 3:27:29 time: 0.7026 data_time: 0.0437 memory: 23708 grad_norm: 5.3089 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4112 loss_aux: 0.9683 loss: 2.3795 2022/09/11 20:38:18 - mmengine - INFO - Epoch(train) [132][360/940] lr: 4.0000e-04 eta: 3:27:14 time: 0.7033 data_time: 0.0326 memory: 23708 grad_norm: 5.3186 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.2706 loss_aux: 0.8822 loss: 2.1527 2022/09/11 20:38:32 - mmengine - INFO - Epoch(train) [132][380/940] lr: 4.0000e-04 eta: 3:27:00 time: 0.7040 data_time: 0.0349 memory: 23708 grad_norm: 5.2707 top1_acc: 0.8125 top5_acc: 1.0000 loss_cls: 1.3829 loss_aux: 0.9339 loss: 2.3168 2022/09/11 20:38:46 - mmengine - INFO - Epoch(train) [132][400/940] lr: 4.0000e-04 eta: 3:26:46 time: 0.7113 data_time: 0.0569 memory: 23708 grad_norm: 5.3452 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4854 loss_aux: 0.9626 loss: 2.4480 2022/09/11 20:39:01 - mmengine - INFO - Epoch(train) [132][420/940] lr: 4.0000e-04 eta: 3:26:32 time: 0.7224 data_time: 0.0373 memory: 23708 grad_norm: 5.3219 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2964 loss_aux: 0.8557 loss: 2.1521 2022/09/11 20:39:15 - mmengine - INFO - Epoch(train) [132][440/940] lr: 4.0000e-04 eta: 3:26:17 time: 0.6941 data_time: 0.0325 memory: 23708 grad_norm: 5.3071 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3790 loss_aux: 0.9182 loss: 2.2971 2022/09/11 20:39:28 - mmengine - INFO - Epoch(train) [132][460/940] lr: 4.0000e-04 eta: 3:26:02 time: 0.6836 data_time: 0.0365 memory: 23708 grad_norm: 5.3058 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3446 loss_aux: 0.9254 loss: 2.2700 2022/09/11 20:39:42 - mmengine - INFO - Epoch(train) [132][480/940] lr: 4.0000e-04 eta: 3:25:48 time: 0.7012 data_time: 0.0383 memory: 23708 grad_norm: 5.3780 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4137 loss_aux: 0.9438 loss: 2.3575 2022/09/11 20:39:56 - mmengine - INFO - Epoch(train) [132][500/940] lr: 4.0000e-04 eta: 3:25:34 time: 0.6983 data_time: 0.0381 memory: 23708 grad_norm: 5.2724 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3439 loss_aux: 0.9009 loss: 2.2448 2022/09/11 20:40:11 - mmengine - INFO - Epoch(train) [132][520/940] lr: 4.0000e-04 eta: 3:25:19 time: 0.7122 data_time: 0.0329 memory: 23708 grad_norm: 5.3972 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3362 loss_aux: 0.9580 loss: 2.2943 2022/09/11 20:40:25 - mmengine - INFO - Epoch(train) [132][540/940] lr: 4.0000e-04 eta: 3:25:05 time: 0.6973 data_time: 0.0433 memory: 23708 grad_norm: 5.3921 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.5146 loss_aux: 0.9822 loss: 2.4968 2022/09/11 20:40:39 - mmengine - INFO - Epoch(train) [132][560/940] lr: 4.0000e-04 eta: 3:24:51 time: 0.7144 data_time: 0.0335 memory: 23708 grad_norm: 5.3815 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3956 loss_aux: 0.9328 loss: 2.3283 2022/09/11 20:40:53 - mmengine - INFO - Epoch(train) [132][580/940] lr: 4.0000e-04 eta: 3:24:37 time: 0.7198 data_time: 0.0412 memory: 23708 grad_norm: 5.3165 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3178 loss_aux: 0.9003 loss: 2.2180 2022/09/11 20:41:07 - mmengine - INFO - Epoch(train) [132][600/940] lr: 4.0000e-04 eta: 3:24:23 time: 0.7072 data_time: 0.0359 memory: 23708 grad_norm: 5.3597 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.3490 loss_aux: 0.9160 loss: 2.2650 2022/09/11 20:41:22 - mmengine - INFO - Epoch(train) [132][620/940] lr: 4.0000e-04 eta: 3:24:08 time: 0.7126 data_time: 0.0369 memory: 23708 grad_norm: 5.2499 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3975 loss_aux: 0.9252 loss: 2.3226 2022/09/11 20:41:36 - mmengine - INFO - Epoch(train) [132][640/940] lr: 4.0000e-04 eta: 3:23:54 time: 0.7152 data_time: 0.0409 memory: 23708 grad_norm: 5.3377 top1_acc: 0.4375 top5_acc: 0.7812 loss_cls: 1.3679 loss_aux: 0.9317 loss: 2.2996 2022/09/11 20:41:51 - mmengine - INFO - Epoch(train) [132][660/940] lr: 4.0000e-04 eta: 3:23:40 time: 0.7309 data_time: 0.0339 memory: 23708 grad_norm: 5.4771 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3590 loss_aux: 0.8749 loss: 2.2340 2022/09/11 20:42:05 - mmengine - INFO - Epoch(train) [132][680/940] lr: 4.0000e-04 eta: 3:23:26 time: 0.7116 data_time: 0.0396 memory: 23708 grad_norm: 5.3610 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3938 loss_aux: 0.9245 loss: 2.3182 2022/09/11 20:42:19 - mmengine - INFO - Epoch(train) [132][700/940] lr: 4.0000e-04 eta: 3:23:12 time: 0.7205 data_time: 0.0278 memory: 23708 grad_norm: 5.4403 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.4316 loss_aux: 0.9545 loss: 2.3861 2022/09/11 20:42:33 - mmengine - INFO - Epoch(train) [132][720/940] lr: 4.0000e-04 eta: 3:22:58 time: 0.7089 data_time: 0.0298 memory: 23708 grad_norm: 5.3335 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4858 loss_aux: 0.9861 loss: 2.4719 2022/09/11 20:42:48 - mmengine - INFO - Epoch(train) [132][740/940] lr: 4.0000e-04 eta: 3:22:44 time: 0.7103 data_time: 0.0365 memory: 23708 grad_norm: 5.2752 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3214 loss_aux: 0.8912 loss: 2.2126 2022/09/11 20:43:02 - mmengine - INFO - Epoch(train) [132][760/940] lr: 4.0000e-04 eta: 3:22:30 time: 0.7272 data_time: 0.0475 memory: 23708 grad_norm: 5.3746 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3305 loss_aux: 0.9096 loss: 2.2401 2022/09/11 20:43:16 - mmengine - INFO - Epoch(train) [132][780/940] lr: 4.0000e-04 eta: 3:22:16 time: 0.7129 data_time: 0.0383 memory: 23708 grad_norm: 5.3719 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.3890 loss_aux: 0.9329 loss: 2.3219 2022/09/11 20:43:30 - mmengine - INFO - Epoch(train) [132][800/940] lr: 4.0000e-04 eta: 3:22:01 time: 0.6846 data_time: 0.0340 memory: 23708 grad_norm: 5.3494 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3711 loss_aux: 0.9307 loss: 2.3018 2022/09/11 20:43:44 - mmengine - INFO - Epoch(train) [132][820/940] lr: 4.0000e-04 eta: 3:21:47 time: 0.7027 data_time: 0.0353 memory: 23708 grad_norm: 5.4087 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3453 loss_aux: 0.9337 loss: 2.2790 2022/09/11 20:43:58 - mmengine - INFO - Epoch(train) [132][840/940] lr: 4.0000e-04 eta: 3:21:32 time: 0.6998 data_time: 0.0395 memory: 23708 grad_norm: 5.2597 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3992 loss_aux: 0.9544 loss: 2.3536 2022/09/11 20:44:13 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 20:44:13 - mmengine - INFO - Epoch(train) [132][860/940] lr: 4.0000e-04 eta: 3:21:18 time: 0.7143 data_time: 0.0312 memory: 23708 grad_norm: 5.3143 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3631 loss_aux: 0.9343 loss: 2.2974 2022/09/11 20:44:27 - mmengine - INFO - Epoch(train) [132][880/940] lr: 4.0000e-04 eta: 3:21:04 time: 0.7009 data_time: 0.0308 memory: 23708 grad_norm: 5.3079 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4407 loss_aux: 0.9802 loss: 2.4209 2022/09/11 20:44:41 - mmengine - INFO - Epoch(train) [132][900/940] lr: 4.0000e-04 eta: 3:20:49 time: 0.7076 data_time: 0.0378 memory: 23708 grad_norm: 5.3149 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3692 loss_aux: 0.9317 loss: 2.3009 2022/09/11 20:44:54 - mmengine - INFO - Epoch(train) [132][920/940] lr: 4.0000e-04 eta: 3:20:35 time: 0.6859 data_time: 0.0379 memory: 23708 grad_norm: 5.3642 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3595 loss_aux: 0.8912 loss: 2.2507 2022/09/11 20:45:07 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 20:45:07 - mmengine - INFO - Epoch(train) [132][940/940] lr: 4.0000e-04 eta: 3:20:19 time: 0.6406 data_time: 0.0233 memory: 23708 grad_norm: 5.4799 top1_acc: 0.7143 top5_acc: 0.8571 loss_cls: 1.4739 loss_aux: 0.9541 loss: 2.4280 2022/09/11 20:45:07 - mmengine - INFO - Saving checkpoint at 132 epochs 2022/09/11 20:45:32 - mmengine - INFO - Epoch(train) [133][20/940] lr: 4.0000e-04 eta: 3:20:10 time: 0.9716 data_time: 0.3060 memory: 23708 grad_norm: 5.4051 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.3549 loss_aux: 0.8802 loss: 2.2351 2022/09/11 20:45:46 - mmengine - INFO - Epoch(train) [133][40/940] lr: 4.0000e-04 eta: 3:19:55 time: 0.6699 data_time: 0.0316 memory: 23708 grad_norm: 5.3260 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2451 loss_aux: 0.8764 loss: 2.1215 2022/09/11 20:46:00 - mmengine - INFO - Epoch(train) [133][60/940] lr: 4.0000e-04 eta: 3:19:40 time: 0.7006 data_time: 0.0325 memory: 23708 grad_norm: 5.3674 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3552 loss_aux: 0.9206 loss: 2.2758 2022/09/11 20:46:13 - mmengine - INFO - Epoch(train) [133][80/940] lr: 4.0000e-04 eta: 3:19:26 time: 0.6739 data_time: 0.0373 memory: 23708 grad_norm: 5.3278 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3669 loss_aux: 0.8891 loss: 2.2560 2022/09/11 20:46:27 - mmengine - INFO - Epoch(train) [133][100/940] lr: 4.0000e-04 eta: 3:19:11 time: 0.7016 data_time: 0.0465 memory: 23708 grad_norm: 5.3211 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3057 loss_aux: 0.8822 loss: 2.1879 2022/09/11 20:46:44 - mmengine - INFO - Epoch(train) [133][120/940] lr: 4.0000e-04 eta: 3:18:59 time: 0.8128 data_time: 0.0354 memory: 23708 grad_norm: 5.3638 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4618 loss_aux: 0.9533 loss: 2.4152 2022/09/11 20:46:57 - mmengine - INFO - Epoch(train) [133][140/940] lr: 4.0000e-04 eta: 3:18:44 time: 0.7032 data_time: 0.0409 memory: 23708 grad_norm: 5.2808 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4374 loss_aux: 0.9287 loss: 2.3661 2022/09/11 20:47:11 - mmengine - INFO - Epoch(train) [133][160/940] lr: 4.0000e-04 eta: 3:18:30 time: 0.6854 data_time: 0.0501 memory: 23708 grad_norm: 5.4011 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4325 loss_aux: 0.9120 loss: 2.3446 2022/09/11 20:47:25 - mmengine - INFO - Epoch(train) [133][180/940] lr: 4.0000e-04 eta: 3:18:15 time: 0.7018 data_time: 0.0411 memory: 23708 grad_norm: 5.3750 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3184 loss_aux: 0.8631 loss: 2.1814 2022/09/11 20:47:39 - mmengine - INFO - Epoch(train) [133][200/940] lr: 4.0000e-04 eta: 3:18:01 time: 0.6945 data_time: 0.0322 memory: 23708 grad_norm: 5.2735 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.3720 loss_aux: 0.9332 loss: 2.3052 2022/09/11 20:47:53 - mmengine - INFO - Epoch(train) [133][220/940] lr: 4.0000e-04 eta: 3:17:46 time: 0.6812 data_time: 0.0315 memory: 23708 grad_norm: 5.2959 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3865 loss_aux: 0.9370 loss: 2.3236 2022/09/11 20:48:07 - mmengine - INFO - Epoch(train) [133][240/940] lr: 4.0000e-04 eta: 3:17:32 time: 0.6968 data_time: 0.0368 memory: 23708 grad_norm: 5.3831 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4129 loss_aux: 0.9265 loss: 2.3394 2022/09/11 20:48:21 - mmengine - INFO - Epoch(train) [133][260/940] lr: 4.0000e-04 eta: 3:17:17 time: 0.6979 data_time: 0.0402 memory: 23708 grad_norm: 5.3098 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3036 loss_aux: 0.8572 loss: 2.1608 2022/09/11 20:48:34 - mmengine - INFO - Epoch(train) [133][280/940] lr: 4.0000e-04 eta: 3:17:03 time: 0.6769 data_time: 0.0310 memory: 23708 grad_norm: 5.3146 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3733 loss_aux: 0.9163 loss: 2.2896 2022/09/11 20:48:48 - mmengine - INFO - Epoch(train) [133][300/940] lr: 4.0000e-04 eta: 3:16:48 time: 0.6978 data_time: 0.0287 memory: 23708 grad_norm: 5.2829 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4036 loss_aux: 0.9486 loss: 2.3521 2022/09/11 20:49:02 - mmengine - INFO - Epoch(train) [133][320/940] lr: 4.0000e-04 eta: 3:16:34 time: 0.6940 data_time: 0.0372 memory: 23708 grad_norm: 5.3944 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4536 loss_aux: 0.9638 loss: 2.4174 2022/09/11 20:49:16 - mmengine - INFO - Epoch(train) [133][340/940] lr: 4.0000e-04 eta: 3:16:19 time: 0.6936 data_time: 0.0406 memory: 23708 grad_norm: 5.3082 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2978 loss_aux: 0.8813 loss: 2.1791 2022/09/11 20:49:30 - mmengine - INFO - Epoch(train) [133][360/940] lr: 4.0000e-04 eta: 3:16:05 time: 0.6921 data_time: 0.0368 memory: 23708 grad_norm: 5.3249 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3674 loss_aux: 0.9040 loss: 2.2715 2022/09/11 20:49:44 - mmengine - INFO - Epoch(train) [133][380/940] lr: 4.0000e-04 eta: 3:15:50 time: 0.7059 data_time: 0.0330 memory: 23708 grad_norm: 5.3436 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4738 loss_aux: 0.9771 loss: 2.4509 2022/09/11 20:49:58 - mmengine - INFO - Epoch(train) [133][400/940] lr: 4.0000e-04 eta: 3:15:36 time: 0.6954 data_time: 0.0348 memory: 23708 grad_norm: 5.2671 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3433 loss_aux: 0.9286 loss: 2.2719 2022/09/11 20:50:12 - mmengine - INFO - Epoch(train) [133][420/940] lr: 4.0000e-04 eta: 3:15:22 time: 0.7084 data_time: 0.0481 memory: 23708 grad_norm: 5.3943 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4357 loss_aux: 0.9545 loss: 2.3902 2022/09/11 20:50:26 - mmengine - INFO - Epoch(train) [133][440/940] lr: 4.0000e-04 eta: 3:15:07 time: 0.6806 data_time: 0.0334 memory: 23708 grad_norm: 5.3658 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4503 loss_aux: 0.9558 loss: 2.4062 2022/09/11 20:50:40 - mmengine - INFO - Epoch(train) [133][460/940] lr: 4.0000e-04 eta: 3:14:52 time: 0.7025 data_time: 0.0327 memory: 23708 grad_norm: 5.2893 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4088 loss_aux: 0.9150 loss: 2.3238 2022/09/11 20:50:54 - mmengine - INFO - Epoch(train) [133][480/940] lr: 4.0000e-04 eta: 3:14:38 time: 0.6953 data_time: 0.0451 memory: 23708 grad_norm: 5.2807 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.4354 loss_aux: 0.9451 loss: 2.3806 2022/09/11 20:51:08 - mmengine - INFO - Epoch(train) [133][500/940] lr: 4.0000e-04 eta: 3:14:24 time: 0.6965 data_time: 0.0416 memory: 23708 grad_norm: 5.4017 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.4138 loss_aux: 0.9335 loss: 2.3472 2022/09/11 20:51:21 - mmengine - INFO - Epoch(train) [133][520/940] lr: 4.0000e-04 eta: 3:14:09 time: 0.6945 data_time: 0.0403 memory: 23708 grad_norm: 5.3956 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.4066 loss_aux: 0.9541 loss: 2.3607 2022/09/11 20:51:35 - mmengine - INFO - Epoch(train) [133][540/940] lr: 4.0000e-04 eta: 3:13:55 time: 0.6887 data_time: 0.0320 memory: 23708 grad_norm: 5.3058 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3300 loss_aux: 0.9235 loss: 2.2535 2022/09/11 20:51:49 - mmengine - INFO - Epoch(train) [133][560/940] lr: 4.0000e-04 eta: 3:13:40 time: 0.6847 data_time: 0.0376 memory: 23708 grad_norm: 5.3512 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3684 loss_aux: 0.9129 loss: 2.2813 2022/09/11 20:52:03 - mmengine - INFO - Epoch(train) [133][580/940] lr: 4.0000e-04 eta: 3:13:26 time: 0.7305 data_time: 0.0446 memory: 23708 grad_norm: 5.3939 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4045 loss_aux: 0.9295 loss: 2.3341 2022/09/11 20:52:17 - mmengine - INFO - Epoch(train) [133][600/940] lr: 4.0000e-04 eta: 3:13:11 time: 0.6876 data_time: 0.0368 memory: 23708 grad_norm: 5.3347 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.4393 loss_aux: 0.9448 loss: 2.3841 2022/09/11 20:52:32 - mmengine - INFO - Epoch(train) [133][620/940] lr: 4.0000e-04 eta: 3:12:57 time: 0.7193 data_time: 0.0357 memory: 23708 grad_norm: 5.3958 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4578 loss_aux: 0.9598 loss: 2.4176 2022/09/11 20:52:45 - mmengine - INFO - Epoch(train) [133][640/940] lr: 4.0000e-04 eta: 3:12:43 time: 0.6826 data_time: 0.0391 memory: 23708 grad_norm: 5.3156 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.3028 loss_aux: 0.8981 loss: 2.2009 2022/09/11 20:52:59 - mmengine - INFO - Epoch(train) [133][660/940] lr: 4.0000e-04 eta: 3:12:28 time: 0.7010 data_time: 0.0418 memory: 23708 grad_norm: 5.3732 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2635 loss_aux: 0.8588 loss: 2.1224 2022/09/11 20:53:13 - mmengine - INFO - Epoch(train) [133][680/940] lr: 4.0000e-04 eta: 3:12:14 time: 0.6848 data_time: 0.0381 memory: 23708 grad_norm: 5.3662 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.4258 loss_aux: 0.9446 loss: 2.3705 2022/09/11 20:53:27 - mmengine - INFO - Epoch(train) [133][700/940] lr: 4.0000e-04 eta: 3:11:59 time: 0.6873 data_time: 0.0360 memory: 23708 grad_norm: 5.3175 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.3636 loss_aux: 0.9505 loss: 2.3141 2022/09/11 20:53:40 - mmengine - INFO - Epoch(train) [133][720/940] lr: 4.0000e-04 eta: 3:11:44 time: 0.6814 data_time: 0.0377 memory: 23708 grad_norm: 5.3642 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2771 loss_aux: 0.9160 loss: 2.1931 2022/09/11 20:53:54 - mmengine - INFO - Epoch(train) [133][740/940] lr: 4.0000e-04 eta: 3:11:30 time: 0.7022 data_time: 0.0430 memory: 23708 grad_norm: 5.3634 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3585 loss_aux: 0.9231 loss: 2.2816 2022/09/11 20:54:08 - mmengine - INFO - Epoch(train) [133][760/940] lr: 4.0000e-04 eta: 3:11:15 time: 0.6836 data_time: 0.0361 memory: 23708 grad_norm: 5.3526 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3852 loss_aux: 0.8843 loss: 2.2695 2022/09/11 20:54:22 - mmengine - INFO - Epoch(train) [133][780/940] lr: 4.0000e-04 eta: 3:11:01 time: 0.6966 data_time: 0.0419 memory: 23708 grad_norm: 5.3613 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3683 loss_aux: 0.9508 loss: 2.3191 2022/09/11 20:54:36 - mmengine - INFO - Epoch(train) [133][800/940] lr: 4.0000e-04 eta: 3:10:47 time: 0.7017 data_time: 0.0446 memory: 23708 grad_norm: 5.2957 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3882 loss_aux: 0.9313 loss: 2.3195 2022/09/11 20:54:50 - mmengine - INFO - Epoch(train) [133][820/940] lr: 4.0000e-04 eta: 3:10:32 time: 0.7009 data_time: 0.0399 memory: 23708 grad_norm: 5.3602 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3975 loss_aux: 0.9214 loss: 2.3190 2022/09/11 20:55:04 - mmengine - INFO - Epoch(train) [133][840/940] lr: 4.0000e-04 eta: 3:10:18 time: 0.7007 data_time: 0.0429 memory: 23708 grad_norm: 5.3516 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2562 loss_aux: 0.8918 loss: 2.1480 2022/09/11 20:55:18 - mmengine - INFO - Epoch(train) [133][860/940] lr: 4.0000e-04 eta: 3:10:04 time: 0.7060 data_time: 0.0380 memory: 23708 grad_norm: 5.4311 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3549 loss_aux: 0.9170 loss: 2.2719 2022/09/11 20:55:32 - mmengine - INFO - Epoch(train) [133][880/940] lr: 4.0000e-04 eta: 3:09:49 time: 0.6966 data_time: 0.0399 memory: 23708 grad_norm: 5.3675 top1_acc: 0.7812 top5_acc: 0.7812 loss_cls: 1.3787 loss_aux: 0.9223 loss: 2.3010 2022/09/11 20:55:46 - mmengine - INFO - Epoch(train) [133][900/940] lr: 4.0000e-04 eta: 3:09:35 time: 0.6992 data_time: 0.0437 memory: 23708 grad_norm: 5.3480 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4088 loss_aux: 0.9302 loss: 2.3390 2022/09/11 20:56:00 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 20:56:00 - mmengine - INFO - Epoch(train) [133][920/940] lr: 4.0000e-04 eta: 3:09:20 time: 0.6873 data_time: 0.0344 memory: 23708 grad_norm: 5.4493 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.5342 loss_aux: 1.0421 loss: 2.5763 2022/09/11 20:56:13 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 20:56:13 - mmengine - INFO - Epoch(train) [133][940/940] lr: 4.0000e-04 eta: 3:09:05 time: 0.6692 data_time: 0.0282 memory: 23708 grad_norm: 5.6067 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2069 loss_aux: 0.8716 loss: 2.0785 2022/09/11 20:56:13 - mmengine - INFO - Saving checkpoint at 133 epochs 2022/09/11 20:56:38 - mmengine - INFO - Epoch(train) [134][20/940] lr: 4.0000e-04 eta: 3:08:56 time: 0.9921 data_time: 0.3180 memory: 23708 grad_norm: 5.3055 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.3794 loss_aux: 0.9373 loss: 2.3167 2022/09/11 20:56:52 - mmengine - INFO - Epoch(train) [134][40/940] lr: 4.0000e-04 eta: 3:08:41 time: 0.6691 data_time: 0.0281 memory: 23708 grad_norm: 5.3674 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3578 loss_aux: 0.9216 loss: 2.2794 2022/09/11 20:57:05 - mmengine - INFO - Epoch(train) [134][60/940] lr: 4.0000e-04 eta: 3:08:26 time: 0.6653 data_time: 0.0290 memory: 23708 grad_norm: 5.3405 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3699 loss_aux: 0.9125 loss: 2.2824 2022/09/11 20:57:19 - mmengine - INFO - Epoch(train) [134][80/940] lr: 4.0000e-04 eta: 3:08:11 time: 0.6759 data_time: 0.0391 memory: 23708 grad_norm: 5.3367 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4562 loss_aux: 0.9682 loss: 2.4244 2022/09/11 20:57:32 - mmengine - INFO - Epoch(train) [134][100/940] lr: 4.0000e-04 eta: 3:07:57 time: 0.6857 data_time: 0.0409 memory: 23708 grad_norm: 5.2549 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.3432 loss_aux: 0.9019 loss: 2.2450 2022/09/11 20:57:46 - mmengine - INFO - Epoch(train) [134][120/940] lr: 4.0000e-04 eta: 3:07:42 time: 0.6663 data_time: 0.0311 memory: 23708 grad_norm: 5.2797 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3344 loss_aux: 0.8936 loss: 2.2280 2022/09/11 20:57:59 - mmengine - INFO - Epoch(train) [134][140/940] lr: 4.0000e-04 eta: 3:07:27 time: 0.6695 data_time: 0.0351 memory: 23708 grad_norm: 5.2893 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3046 loss_aux: 0.8565 loss: 2.1612 2022/09/11 20:58:13 - mmengine - INFO - Epoch(train) [134][160/940] lr: 4.0000e-04 eta: 3:07:12 time: 0.6854 data_time: 0.0386 memory: 23708 grad_norm: 5.3744 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2988 loss_aux: 0.9062 loss: 2.2050 2022/09/11 20:58:27 - mmengine - INFO - Epoch(train) [134][180/940] lr: 4.0000e-04 eta: 3:06:58 time: 0.6929 data_time: 0.0456 memory: 23708 grad_norm: 5.3387 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3707 loss_aux: 0.9336 loss: 2.3042 2022/09/11 20:58:40 - mmengine - INFO - Epoch(train) [134][200/940] lr: 4.0000e-04 eta: 3:06:43 time: 0.6828 data_time: 0.0302 memory: 23708 grad_norm: 5.3789 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.5223 loss_aux: 1.0040 loss: 2.5264 2022/09/11 20:58:54 - mmengine - INFO - Epoch(train) [134][220/940] lr: 4.0000e-04 eta: 3:06:29 time: 0.6757 data_time: 0.0364 memory: 23708 grad_norm: 5.3519 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3497 loss_aux: 0.9405 loss: 2.2902 2022/09/11 20:59:08 - mmengine - INFO - Epoch(train) [134][240/940] lr: 4.0000e-04 eta: 3:06:14 time: 0.6844 data_time: 0.0400 memory: 23708 grad_norm: 5.4567 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3823 loss_aux: 0.9757 loss: 2.3580 2022/09/11 20:59:22 - mmengine - INFO - Epoch(train) [134][260/940] lr: 4.0000e-04 eta: 3:06:00 time: 0.7103 data_time: 0.0312 memory: 23708 grad_norm: 5.3734 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4387 loss_aux: 0.9707 loss: 2.4094 2022/09/11 20:59:35 - mmengine - INFO - Epoch(train) [134][280/940] lr: 4.0000e-04 eta: 3:05:45 time: 0.6795 data_time: 0.0363 memory: 23708 grad_norm: 5.3530 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2977 loss_aux: 0.8925 loss: 2.1902 2022/09/11 20:59:49 - mmengine - INFO - Epoch(train) [134][300/940] lr: 4.0000e-04 eta: 3:05:30 time: 0.6786 data_time: 0.0376 memory: 23708 grad_norm: 5.3660 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.4550 loss_aux: 0.9645 loss: 2.4196 2022/09/11 21:00:03 - mmengine - INFO - Epoch(train) [134][320/940] lr: 4.0000e-04 eta: 3:05:16 time: 0.6905 data_time: 0.0422 memory: 23708 grad_norm: 5.3130 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4976 loss_aux: 0.9609 loss: 2.4585 2022/09/11 21:00:17 - mmengine - INFO - Epoch(train) [134][340/940] lr: 4.0000e-04 eta: 3:05:01 time: 0.6879 data_time: 0.0305 memory: 23708 grad_norm: 5.3672 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.3670 loss_aux: 0.9138 loss: 2.2809 2022/09/11 21:00:30 - mmengine - INFO - Epoch(train) [134][360/940] lr: 4.0000e-04 eta: 3:04:47 time: 0.6784 data_time: 0.0384 memory: 23708 grad_norm: 5.4819 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4730 loss_aux: 1.0107 loss: 2.4836 2022/09/11 21:00:44 - mmengine - INFO - Epoch(train) [134][380/940] lr: 4.0000e-04 eta: 3:04:32 time: 0.7003 data_time: 0.0356 memory: 23708 grad_norm: 5.3672 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4432 loss_aux: 0.9245 loss: 2.3676 2022/09/11 21:00:58 - mmengine - INFO - Epoch(train) [134][400/940] lr: 4.0000e-04 eta: 3:04:18 time: 0.7035 data_time: 0.0454 memory: 23708 grad_norm: 5.3150 top1_acc: 0.4688 top5_acc: 0.8438 loss_cls: 1.2614 loss_aux: 0.8864 loss: 2.1478 2022/09/11 21:01:12 - mmengine - INFO - Epoch(train) [134][420/940] lr: 4.0000e-04 eta: 3:04:04 time: 0.7020 data_time: 0.0316 memory: 23708 grad_norm: 5.3745 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1885 loss_aux: 0.8327 loss: 2.0212 2022/09/11 21:01:26 - mmengine - INFO - Epoch(train) [134][440/940] lr: 4.0000e-04 eta: 3:03:49 time: 0.6982 data_time: 0.0396 memory: 23708 grad_norm: 5.3885 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3867 loss_aux: 0.8886 loss: 2.2753 2022/09/11 21:01:40 - mmengine - INFO - Epoch(train) [134][460/940] lr: 4.0000e-04 eta: 3:03:35 time: 0.6877 data_time: 0.0304 memory: 23708 grad_norm: 5.4083 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2841 loss_aux: 0.8638 loss: 2.1479 2022/09/11 21:01:54 - mmengine - INFO - Epoch(train) [134][480/940] lr: 4.0000e-04 eta: 3:03:20 time: 0.6854 data_time: 0.0293 memory: 23708 grad_norm: 5.4171 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3803 loss_aux: 0.9199 loss: 2.3002 2022/09/11 21:02:08 - mmengine - INFO - Epoch(train) [134][500/940] lr: 4.0000e-04 eta: 3:03:06 time: 0.6989 data_time: 0.0339 memory: 23708 grad_norm: 5.3237 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.3362 loss_aux: 0.8876 loss: 2.2238 2022/09/11 21:02:21 - mmengine - INFO - Epoch(train) [134][520/940] lr: 4.0000e-04 eta: 3:02:51 time: 0.6871 data_time: 0.0450 memory: 23708 grad_norm: 5.3507 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3329 loss_aux: 0.8673 loss: 2.2002 2022/09/11 21:02:35 - mmengine - INFO - Epoch(train) [134][540/940] lr: 4.0000e-04 eta: 3:02:37 time: 0.7030 data_time: 0.0332 memory: 23708 grad_norm: 5.4220 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2434 loss_aux: 0.8648 loss: 2.1082 2022/09/11 21:02:49 - mmengine - INFO - Epoch(train) [134][560/940] lr: 4.0000e-04 eta: 3:02:23 time: 0.6927 data_time: 0.0392 memory: 23708 grad_norm: 5.3937 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3688 loss_aux: 0.9090 loss: 2.2778 2022/09/11 21:03:03 - mmengine - INFO - Epoch(train) [134][580/940] lr: 4.0000e-04 eta: 3:02:08 time: 0.6890 data_time: 0.0381 memory: 23708 grad_norm: 5.2949 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.2992 loss_aux: 0.8896 loss: 2.1887 2022/09/11 21:03:17 - mmengine - INFO - Epoch(train) [134][600/940] lr: 4.0000e-04 eta: 3:01:53 time: 0.6844 data_time: 0.0427 memory: 23708 grad_norm: 5.4937 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3397 loss_aux: 0.9365 loss: 2.2762 2022/09/11 21:03:31 - mmengine - INFO - Epoch(train) [134][620/940] lr: 4.0000e-04 eta: 3:01:39 time: 0.6928 data_time: 0.0318 memory: 23708 grad_norm: 5.2962 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2403 loss_aux: 0.8522 loss: 2.0925 2022/09/11 21:03:45 - mmengine - INFO - Epoch(train) [134][640/940] lr: 4.0000e-04 eta: 3:01:25 time: 0.6971 data_time: 0.0375 memory: 23708 grad_norm: 5.3832 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5243 loss_aux: 1.0038 loss: 2.5281 2022/09/11 21:03:58 - mmengine - INFO - Epoch(train) [134][660/940] lr: 4.0000e-04 eta: 3:01:10 time: 0.6888 data_time: 0.0352 memory: 23708 grad_norm: 5.4698 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.4359 loss_aux: 0.9744 loss: 2.4102 2022/09/11 21:04:12 - mmengine - INFO - Epoch(train) [134][680/940] lr: 4.0000e-04 eta: 3:00:56 time: 0.6883 data_time: 0.0410 memory: 23708 grad_norm: 5.2586 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3443 loss_aux: 0.9088 loss: 2.2531 2022/09/11 21:04:26 - mmengine - INFO - Epoch(train) [134][700/940] lr: 4.0000e-04 eta: 3:00:41 time: 0.6919 data_time: 0.0327 memory: 23708 grad_norm: 5.3373 top1_acc: 0.4688 top5_acc: 0.6562 loss_cls: 1.3786 loss_aux: 0.9163 loss: 2.2949 2022/09/11 21:04:40 - mmengine - INFO - Epoch(train) [134][720/940] lr: 4.0000e-04 eta: 3:00:27 time: 0.6889 data_time: 0.0365 memory: 23708 grad_norm: 5.4366 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2729 loss_aux: 0.8639 loss: 2.1368 2022/09/11 21:04:54 - mmengine - INFO - Epoch(train) [134][740/940] lr: 4.0000e-04 eta: 3:00:12 time: 0.6880 data_time: 0.0388 memory: 23708 grad_norm: 5.3416 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4170 loss_aux: 0.9541 loss: 2.3712 2022/09/11 21:05:07 - mmengine - INFO - Epoch(train) [134][760/940] lr: 4.0000e-04 eta: 2:59:58 time: 0.6846 data_time: 0.0420 memory: 23708 grad_norm: 5.4111 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3642 loss_aux: 0.9271 loss: 2.2913 2022/09/11 21:05:21 - mmengine - INFO - Epoch(train) [134][780/940] lr: 4.0000e-04 eta: 2:59:43 time: 0.6912 data_time: 0.0382 memory: 23708 grad_norm: 5.2884 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3686 loss_aux: 0.9386 loss: 2.3072 2022/09/11 21:05:35 - mmengine - INFO - Epoch(train) [134][800/940] lr: 4.0000e-04 eta: 2:59:29 time: 0.6903 data_time: 0.0352 memory: 23708 grad_norm: 5.2995 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2936 loss_aux: 0.8773 loss: 2.1710 2022/09/11 21:05:49 - mmengine - INFO - Epoch(train) [134][820/940] lr: 4.0000e-04 eta: 2:59:15 time: 0.7233 data_time: 0.0363 memory: 23708 grad_norm: 5.3816 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.4891 loss_aux: 0.9733 loss: 2.4623 2022/09/11 21:06:03 - mmengine - INFO - Epoch(train) [134][840/940] lr: 4.0000e-04 eta: 2:59:00 time: 0.6935 data_time: 0.0404 memory: 23708 grad_norm: 5.4152 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2470 loss_aux: 0.8462 loss: 2.0932 2022/09/11 21:06:17 - mmengine - INFO - Epoch(train) [134][860/940] lr: 4.0000e-04 eta: 2:58:46 time: 0.6848 data_time: 0.0353 memory: 23708 grad_norm: 5.3473 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.3483 loss_aux: 0.8761 loss: 2.2244 2022/09/11 21:06:31 - mmengine - INFO - Epoch(train) [134][880/940] lr: 4.0000e-04 eta: 2:58:32 time: 0.7122 data_time: 0.0487 memory: 23708 grad_norm: 5.3644 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.4161 loss_aux: 0.9431 loss: 2.3592 2022/09/11 21:06:46 - mmengine - INFO - Epoch(train) [134][900/940] lr: 4.0000e-04 eta: 2:58:17 time: 0.7167 data_time: 0.0349 memory: 23708 grad_norm: 5.3535 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.5273 loss_aux: 0.9787 loss: 2.5060 2022/09/11 21:06:59 - mmengine - INFO - Epoch(train) [134][920/940] lr: 4.0000e-04 eta: 2:58:03 time: 0.6651 data_time: 0.0355 memory: 23708 grad_norm: 5.2399 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3064 loss_aux: 0.9089 loss: 2.2153 2022/09/11 21:07:12 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 21:07:12 - mmengine - INFO - Epoch(train) [134][940/940] lr: 4.0000e-04 eta: 2:57:47 time: 0.6377 data_time: 0.0247 memory: 23708 grad_norm: 5.7487 top1_acc: 0.4286 top5_acc: 0.7143 loss_cls: 1.5663 loss_aux: 0.9938 loss: 2.5601 2022/09/11 21:07:12 - mmengine - INFO - Saving checkpoint at 134 epochs 2022/09/11 21:07:37 - mmengine - INFO - Epoch(train) [135][20/940] lr: 4.0000e-04 eta: 2:57:37 time: 0.9442 data_time: 0.2948 memory: 23708 grad_norm: 5.4345 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3821 loss_aux: 0.9144 loss: 2.2966 2022/09/11 21:07:50 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 21:07:50 - mmengine - INFO - Epoch(train) [135][40/940] lr: 4.0000e-04 eta: 2:57:22 time: 0.6628 data_time: 0.0352 memory: 23708 grad_norm: 5.3835 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.4275 loss_aux: 0.9604 loss: 2.3879 2022/09/11 21:08:04 - mmengine - INFO - Epoch(train) [135][60/940] lr: 4.0000e-04 eta: 2:57:07 time: 0.6816 data_time: 0.0317 memory: 23708 grad_norm: 5.3609 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4267 loss_aux: 0.9418 loss: 2.3685 2022/09/11 21:08:18 - mmengine - INFO - Epoch(train) [135][80/940] lr: 4.0000e-04 eta: 2:56:53 time: 0.6838 data_time: 0.0415 memory: 23708 grad_norm: 5.3752 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3148 loss_aux: 0.8813 loss: 2.1961 2022/09/11 21:08:31 - mmengine - INFO - Epoch(train) [135][100/940] lr: 4.0000e-04 eta: 2:56:38 time: 0.6825 data_time: 0.0395 memory: 23708 grad_norm: 5.2716 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3767 loss_aux: 0.9279 loss: 2.3046 2022/09/11 21:08:45 - mmengine - INFO - Epoch(train) [135][120/940] lr: 4.0000e-04 eta: 2:56:23 time: 0.6673 data_time: 0.0404 memory: 23708 grad_norm: 5.3793 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1816 loss_aux: 0.8326 loss: 2.0143 2022/09/11 21:08:58 - mmengine - INFO - Epoch(train) [135][140/940] lr: 4.0000e-04 eta: 2:56:09 time: 0.6747 data_time: 0.0327 memory: 23708 grad_norm: 5.4789 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3424 loss_aux: 0.9245 loss: 2.2669 2022/09/11 21:09:12 - mmengine - INFO - Epoch(train) [135][160/940] lr: 4.0000e-04 eta: 2:55:54 time: 0.6767 data_time: 0.0378 memory: 23708 grad_norm: 5.4073 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3946 loss_aux: 0.9171 loss: 2.3117 2022/09/11 21:09:25 - mmengine - INFO - Epoch(train) [135][180/940] lr: 4.0000e-04 eta: 2:55:39 time: 0.6792 data_time: 0.0458 memory: 23708 grad_norm: 5.3223 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2971 loss_aux: 0.8486 loss: 2.1457 2022/09/11 21:09:38 - mmengine - INFO - Epoch(train) [135][200/940] lr: 4.0000e-04 eta: 2:55:25 time: 0.6669 data_time: 0.0365 memory: 23708 grad_norm: 5.4540 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.3592 loss_aux: 0.9420 loss: 2.3012 2022/09/11 21:09:52 - mmengine - INFO - Epoch(train) [135][220/940] lr: 4.0000e-04 eta: 2:55:10 time: 0.6642 data_time: 0.0328 memory: 23708 grad_norm: 5.4072 top1_acc: 0.6875 top5_acc: 0.7500 loss_cls: 1.3234 loss_aux: 0.8686 loss: 2.1919 2022/09/11 21:10:05 - mmengine - INFO - Epoch(train) [135][240/940] lr: 4.0000e-04 eta: 2:54:55 time: 0.6644 data_time: 0.0357 memory: 23708 grad_norm: 5.3609 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.4144 loss_aux: 0.9490 loss: 2.3634 2022/09/11 21:10:19 - mmengine - INFO - Epoch(train) [135][260/940] lr: 4.0000e-04 eta: 2:54:40 time: 0.6845 data_time: 0.0406 memory: 23708 grad_norm: 5.3912 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3718 loss_aux: 0.9001 loss: 2.2718 2022/09/11 21:10:32 - mmengine - INFO - Epoch(train) [135][280/940] lr: 4.0000e-04 eta: 2:54:26 time: 0.6796 data_time: 0.0359 memory: 23708 grad_norm: 5.3916 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4019 loss_aux: 0.9336 loss: 2.3355 2022/09/11 21:10:46 - mmengine - INFO - Epoch(train) [135][300/940] lr: 4.0000e-04 eta: 2:54:11 time: 0.6818 data_time: 0.0335 memory: 23708 grad_norm: 5.3547 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3255 loss_aux: 0.9068 loss: 2.2323 2022/09/11 21:10:59 - mmengine - INFO - Epoch(train) [135][320/940] lr: 4.0000e-04 eta: 2:53:56 time: 0.6717 data_time: 0.0343 memory: 23708 grad_norm: 5.4174 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3849 loss_aux: 0.9361 loss: 2.3210 2022/09/11 21:11:13 - mmengine - INFO - Epoch(train) [135][340/940] lr: 4.0000e-04 eta: 2:53:42 time: 0.6982 data_time: 0.0457 memory: 23708 grad_norm: 5.3263 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4276 loss_aux: 0.9758 loss: 2.4034 2022/09/11 21:11:27 - mmengine - INFO - Epoch(train) [135][360/940] lr: 4.0000e-04 eta: 2:53:28 time: 0.6771 data_time: 0.0384 memory: 23708 grad_norm: 5.3964 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4615 loss_aux: 0.9651 loss: 2.4266 2022/09/11 21:11:41 - mmengine - INFO - Epoch(train) [135][380/940] lr: 4.0000e-04 eta: 2:53:13 time: 0.6780 data_time: 0.0338 memory: 23708 grad_norm: 5.3846 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.5213 loss_aux: 0.9977 loss: 2.5191 2022/09/11 21:11:54 - mmengine - INFO - Epoch(train) [135][400/940] lr: 4.0000e-04 eta: 2:52:58 time: 0.6742 data_time: 0.0373 memory: 23708 grad_norm: 5.2760 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2309 loss_aux: 0.8534 loss: 2.0843 2022/09/11 21:12:08 - mmengine - INFO - Epoch(train) [135][420/940] lr: 4.0000e-04 eta: 2:52:44 time: 0.6813 data_time: 0.0429 memory: 23708 grad_norm: 5.3224 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3847 loss_aux: 0.9207 loss: 2.3054 2022/09/11 21:12:21 - mmengine - INFO - Epoch(train) [135][440/940] lr: 4.0000e-04 eta: 2:52:29 time: 0.6718 data_time: 0.0385 memory: 23708 grad_norm: 5.3690 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2882 loss_aux: 0.8978 loss: 2.1860 2022/09/11 21:12:35 - mmengine - INFO - Epoch(train) [135][460/940] lr: 4.0000e-04 eta: 2:52:14 time: 0.6806 data_time: 0.0305 memory: 23708 grad_norm: 5.3384 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3392 loss_aux: 0.9066 loss: 2.2458 2022/09/11 21:12:49 - mmengine - INFO - Epoch(train) [135][480/940] lr: 4.0000e-04 eta: 2:52:00 time: 0.6941 data_time: 0.0319 memory: 23708 grad_norm: 5.3444 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.3643 loss_aux: 0.9386 loss: 2.3028 2022/09/11 21:13:02 - mmengine - INFO - Epoch(train) [135][500/940] lr: 4.0000e-04 eta: 2:51:46 time: 0.6878 data_time: 0.0405 memory: 23708 grad_norm: 5.5025 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3930 loss_aux: 0.9045 loss: 2.2975 2022/09/11 21:13:17 - mmengine - INFO - Epoch(train) [135][520/940] lr: 4.0000e-04 eta: 2:51:31 time: 0.7030 data_time: 0.0386 memory: 23708 grad_norm: 5.3847 top1_acc: 0.4062 top5_acc: 0.6875 loss_cls: 1.3182 loss_aux: 0.8864 loss: 2.2047 2022/09/11 21:13:30 - mmengine - INFO - Epoch(train) [135][540/940] lr: 4.0000e-04 eta: 2:51:17 time: 0.7021 data_time: 0.0359 memory: 23708 grad_norm: 5.3503 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4269 loss_aux: 0.9737 loss: 2.4007 2022/09/11 21:13:44 - mmengine - INFO - Epoch(train) [135][560/940] lr: 4.0000e-04 eta: 2:51:03 time: 0.6900 data_time: 0.0347 memory: 23708 grad_norm: 5.4944 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3661 loss_aux: 0.9531 loss: 2.3192 2022/09/11 21:13:58 - mmengine - INFO - Epoch(train) [135][580/940] lr: 4.0000e-04 eta: 2:50:48 time: 0.6849 data_time: 0.0471 memory: 23708 grad_norm: 5.3632 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2870 loss_aux: 0.8973 loss: 2.1843 2022/09/11 21:14:12 - mmengine - INFO - Epoch(train) [135][600/940] lr: 4.0000e-04 eta: 2:50:34 time: 0.6924 data_time: 0.0377 memory: 23708 grad_norm: 5.3425 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3993 loss_aux: 0.9307 loss: 2.3300 2022/09/11 21:14:26 - mmengine - INFO - Epoch(train) [135][620/940] lr: 4.0000e-04 eta: 2:50:19 time: 0.7004 data_time: 0.0319 memory: 23708 grad_norm: 5.3346 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4666 loss_aux: 0.9334 loss: 2.4000 2022/09/11 21:14:40 - mmengine - INFO - Epoch(train) [135][640/940] lr: 4.0000e-04 eta: 2:50:05 time: 0.6881 data_time: 0.0329 memory: 23708 grad_norm: 5.3384 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3507 loss_aux: 0.8883 loss: 2.2389 2022/09/11 21:14:54 - mmengine - INFO - Epoch(train) [135][660/940] lr: 4.0000e-04 eta: 2:49:51 time: 0.7116 data_time: 0.0428 memory: 23708 grad_norm: 5.3076 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3640 loss_aux: 0.9235 loss: 2.2875 2022/09/11 21:15:08 - mmengine - INFO - Epoch(train) [135][680/940] lr: 4.0000e-04 eta: 2:49:36 time: 0.6944 data_time: 0.0442 memory: 23708 grad_norm: 5.4586 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4266 loss_aux: 0.9492 loss: 2.3759 2022/09/11 21:15:21 - mmengine - INFO - Epoch(train) [135][700/940] lr: 4.0000e-04 eta: 2:49:22 time: 0.6807 data_time: 0.0319 memory: 23708 grad_norm: 5.4557 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4179 loss_aux: 1.0095 loss: 2.4274 2022/09/11 21:15:36 - mmengine - INFO - Epoch(train) [135][720/940] lr: 4.0000e-04 eta: 2:49:08 time: 0.7105 data_time: 0.0337 memory: 23708 grad_norm: 5.4104 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.5221 loss_aux: 0.9796 loss: 2.5016 2022/09/11 21:15:50 - mmengine - INFO - Epoch(train) [135][740/940] lr: 4.0000e-04 eta: 2:48:54 time: 0.7312 data_time: 0.0499 memory: 23708 grad_norm: 5.4347 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3099 loss_aux: 0.8916 loss: 2.2015 2022/09/11 21:16:04 - mmengine - INFO - Epoch(train) [135][760/940] lr: 4.0000e-04 eta: 2:48:40 time: 0.6986 data_time: 0.0314 memory: 23708 grad_norm: 5.3681 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 1.3296 loss_aux: 0.9082 loss: 2.2378 2022/09/11 21:16:18 - mmengine - INFO - Epoch(train) [135][780/940] lr: 4.0000e-04 eta: 2:48:25 time: 0.6853 data_time: 0.0320 memory: 23708 grad_norm: 5.2805 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1771 loss_aux: 0.8376 loss: 2.0146 2022/09/11 21:16:32 - mmengine - INFO - Epoch(train) [135][800/940] lr: 4.0000e-04 eta: 2:48:11 time: 0.7123 data_time: 0.0321 memory: 23708 grad_norm: 5.4168 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3656 loss_aux: 0.8758 loss: 2.2414 2022/09/11 21:16:46 - mmengine - INFO - Epoch(train) [135][820/940] lr: 4.0000e-04 eta: 2:47:57 time: 0.6973 data_time: 0.0438 memory: 23708 grad_norm: 5.4389 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2851 loss_aux: 0.8712 loss: 2.1563 2022/09/11 21:17:00 - mmengine - INFO - Epoch(train) [135][840/940] lr: 4.0000e-04 eta: 2:47:42 time: 0.7019 data_time: 0.0341 memory: 23708 grad_norm: 5.3753 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4690 loss_aux: 0.9437 loss: 2.4127 2022/09/11 21:17:14 - mmengine - INFO - Epoch(train) [135][860/940] lr: 4.0000e-04 eta: 2:47:28 time: 0.7038 data_time: 0.0364 memory: 23708 grad_norm: 5.3730 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3887 loss_aux: 0.9211 loss: 2.3099 2022/09/11 21:17:28 - mmengine - INFO - Epoch(train) [135][880/940] lr: 4.0000e-04 eta: 2:47:14 time: 0.6973 data_time: 0.0330 memory: 23708 grad_norm: 5.4251 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2939 loss_aux: 0.9112 loss: 2.2051 2022/09/11 21:17:42 - mmengine - INFO - Epoch(train) [135][900/940] lr: 4.0000e-04 eta: 2:47:00 time: 0.7010 data_time: 0.0465 memory: 23708 grad_norm: 5.3693 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4295 loss_aux: 0.9513 loss: 2.3808 2022/09/11 21:17:56 - mmengine - INFO - Epoch(train) [135][920/940] lr: 4.0000e-04 eta: 2:46:45 time: 0.6983 data_time: 0.0277 memory: 23708 grad_norm: 5.3807 top1_acc: 0.5625 top5_acc: 0.6875 loss_cls: 1.2943 loss_aux: 0.8910 loss: 2.1853 2022/09/11 21:18:09 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 21:18:09 - mmengine - INFO - Epoch(train) [135][940/940] lr: 4.0000e-04 eta: 2:46:30 time: 0.6393 data_time: 0.0247 memory: 23708 grad_norm: 5.6255 top1_acc: 0.5714 top5_acc: 0.7143 loss_cls: 1.4394 loss_aux: 0.9180 loss: 2.3574 2022/09/11 21:18:09 - mmengine - INFO - Saving checkpoint at 135 epochs 2022/09/11 21:18:35 - mmengine - INFO - Epoch(train) [136][20/940] lr: 4.0000e-04 eta: 2:46:20 time: 1.0038 data_time: 0.3337 memory: 23708 grad_norm: 5.3784 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2620 loss_aux: 0.8845 loss: 2.1465 2022/09/11 21:18:48 - mmengine - INFO - Epoch(train) [136][40/940] lr: 4.0000e-04 eta: 2:46:05 time: 0.6687 data_time: 0.0316 memory: 23708 grad_norm: 5.3327 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1955 loss_aux: 0.8754 loss: 2.0708 2022/09/11 21:19:01 - mmengine - INFO - Epoch(train) [136][60/940] lr: 4.0000e-04 eta: 2:45:51 time: 0.6822 data_time: 0.0366 memory: 23708 grad_norm: 5.3939 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3168 loss_aux: 0.9059 loss: 2.2227 2022/09/11 21:19:15 - mmengine - INFO - Epoch(train) [136][80/940] lr: 4.0000e-04 eta: 2:45:36 time: 0.6791 data_time: 0.0384 memory: 23708 grad_norm: 5.2854 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2998 loss_aux: 0.9282 loss: 2.2281 2022/09/11 21:19:29 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 21:19:29 - mmengine - INFO - Epoch(train) [136][100/940] lr: 4.0000e-04 eta: 2:45:22 time: 0.6996 data_time: 0.0413 memory: 23708 grad_norm: 5.3592 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2626 loss_aux: 0.8540 loss: 2.1165 2022/09/11 21:19:42 - mmengine - INFO - Epoch(train) [136][120/940] lr: 4.0000e-04 eta: 2:45:07 time: 0.6668 data_time: 0.0291 memory: 23708 grad_norm: 5.3474 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.3113 loss_aux: 0.9141 loss: 2.2254 2022/09/11 21:19:56 - mmengine - INFO - Epoch(train) [136][140/940] lr: 4.0000e-04 eta: 2:44:52 time: 0.6716 data_time: 0.0376 memory: 23708 grad_norm: 5.3582 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4800 loss_aux: 0.9620 loss: 2.4421 2022/09/11 21:20:09 - mmengine - INFO - Epoch(train) [136][160/940] lr: 4.0000e-04 eta: 2:44:38 time: 0.6733 data_time: 0.0390 memory: 23708 grad_norm: 5.4931 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3590 loss_aux: 0.8943 loss: 2.2533 2022/09/11 21:20:23 - mmengine - INFO - Epoch(train) [136][180/940] lr: 4.0000e-04 eta: 2:44:23 time: 0.6834 data_time: 0.0423 memory: 23708 grad_norm: 5.4109 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2958 loss_aux: 0.8785 loss: 2.1743 2022/09/11 21:20:36 - mmengine - INFO - Epoch(train) [136][200/940] lr: 4.0000e-04 eta: 2:44:09 time: 0.6674 data_time: 0.0307 memory: 23708 grad_norm: 5.4592 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5905 loss_aux: 1.0176 loss: 2.6080 2022/09/11 21:20:50 - mmengine - INFO - Epoch(train) [136][220/940] lr: 4.0000e-04 eta: 2:43:54 time: 0.6723 data_time: 0.0355 memory: 23708 grad_norm: 5.3636 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3688 loss_aux: 0.9028 loss: 2.2716 2022/09/11 21:21:03 - mmengine - INFO - Epoch(train) [136][240/940] lr: 4.0000e-04 eta: 2:43:39 time: 0.6755 data_time: 0.0412 memory: 23708 grad_norm: 5.4948 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.1481 loss_aux: 0.8305 loss: 1.9786 2022/09/11 21:21:17 - mmengine - INFO - Epoch(train) [136][260/940] lr: 4.0000e-04 eta: 2:43:25 time: 0.6806 data_time: 0.0392 memory: 23708 grad_norm: 5.3759 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.3239 loss_aux: 0.9033 loss: 2.2272 2022/09/11 21:21:31 - mmengine - INFO - Epoch(train) [136][280/940] lr: 4.0000e-04 eta: 2:43:10 time: 0.6834 data_time: 0.0365 memory: 23708 grad_norm: 5.3966 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2723 loss_aux: 0.8939 loss: 2.1662 2022/09/11 21:21:44 - mmengine - INFO - Epoch(train) [136][300/940] lr: 4.0000e-04 eta: 2:42:56 time: 0.6702 data_time: 0.0328 memory: 23708 grad_norm: 5.4332 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3170 loss_aux: 0.9053 loss: 2.2223 2022/09/11 21:21:58 - mmengine - INFO - Epoch(train) [136][320/940] lr: 4.0000e-04 eta: 2:42:41 time: 0.6852 data_time: 0.0359 memory: 23708 grad_norm: 5.3941 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.4032 loss_aux: 0.9641 loss: 2.3674 2022/09/11 21:22:11 - mmengine - INFO - Epoch(train) [136][340/940] lr: 4.0000e-04 eta: 2:42:27 time: 0.6840 data_time: 0.0416 memory: 23708 grad_norm: 5.3785 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3831 loss_aux: 0.9302 loss: 2.3133 2022/09/11 21:22:25 - mmengine - INFO - Epoch(train) [136][360/940] lr: 4.0000e-04 eta: 2:42:12 time: 0.6775 data_time: 0.0356 memory: 23708 grad_norm: 5.4086 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3537 loss_aux: 0.8938 loss: 2.2475 2022/09/11 21:22:38 - mmengine - INFO - Epoch(train) [136][380/940] lr: 4.0000e-04 eta: 2:41:58 time: 0.6746 data_time: 0.0363 memory: 23708 grad_norm: 5.4798 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2975 loss_aux: 0.8752 loss: 2.1726 2022/09/11 21:22:52 - mmengine - INFO - Epoch(train) [136][400/940] lr: 4.0000e-04 eta: 2:41:43 time: 0.6833 data_time: 0.0359 memory: 23708 grad_norm: 5.3515 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3882 loss_aux: 0.9246 loss: 2.3129 2022/09/11 21:23:06 - mmengine - INFO - Epoch(train) [136][420/940] lr: 4.0000e-04 eta: 2:41:29 time: 0.6977 data_time: 0.0433 memory: 23708 grad_norm: 5.3852 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.4281 loss_aux: 0.9456 loss: 2.3736 2022/09/11 21:23:20 - mmengine - INFO - Epoch(train) [136][440/940] lr: 4.0000e-04 eta: 2:41:14 time: 0.6781 data_time: 0.0416 memory: 23708 grad_norm: 5.4990 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4278 loss_aux: 0.9618 loss: 2.3896 2022/09/11 21:23:33 - mmengine - INFO - Epoch(train) [136][460/940] lr: 4.0000e-04 eta: 2:41:00 time: 0.6788 data_time: 0.0409 memory: 23708 grad_norm: 5.4054 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3800 loss_aux: 0.9101 loss: 2.2901 2022/09/11 21:23:47 - mmengine - INFO - Epoch(train) [136][480/940] lr: 4.0000e-04 eta: 2:40:45 time: 0.6869 data_time: 0.0371 memory: 23708 grad_norm: 5.4419 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3841 loss_aux: 0.9349 loss: 2.3190 2022/09/11 21:24:01 - mmengine - INFO - Epoch(train) [136][500/940] lr: 4.0000e-04 eta: 2:40:31 time: 0.6924 data_time: 0.0414 memory: 23708 grad_norm: 5.3621 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3640 loss_aux: 0.9057 loss: 2.2697 2022/09/11 21:24:15 - mmengine - INFO - Epoch(train) [136][520/940] lr: 4.0000e-04 eta: 2:40:17 time: 0.6945 data_time: 0.0379 memory: 23708 grad_norm: 5.4432 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2811 loss_aux: 0.8901 loss: 2.1712 2022/09/11 21:24:28 - mmengine - INFO - Epoch(train) [136][540/940] lr: 4.0000e-04 eta: 2:40:02 time: 0.6798 data_time: 0.0381 memory: 23708 grad_norm: 5.3893 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2494 loss_aux: 0.8526 loss: 2.1020 2022/09/11 21:24:42 - mmengine - INFO - Epoch(train) [136][560/940] lr: 4.0000e-04 eta: 2:39:48 time: 0.6806 data_time: 0.0384 memory: 23708 grad_norm: 5.4205 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3531 loss_aux: 0.9214 loss: 2.2745 2022/09/11 21:24:56 - mmengine - INFO - Epoch(train) [136][580/940] lr: 4.0000e-04 eta: 2:39:33 time: 0.6887 data_time: 0.0367 memory: 23708 grad_norm: 5.3773 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3457 loss_aux: 0.9075 loss: 2.2532 2022/09/11 21:25:09 - mmengine - INFO - Epoch(train) [136][600/940] lr: 4.0000e-04 eta: 2:39:19 time: 0.6817 data_time: 0.0320 memory: 23708 grad_norm: 5.3821 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.5020 loss_aux: 0.9788 loss: 2.4808 2022/09/11 21:25:23 - mmengine - INFO - Epoch(train) [136][620/940] lr: 4.0000e-04 eta: 2:39:04 time: 0.6909 data_time: 0.0409 memory: 23708 grad_norm: 5.3986 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3738 loss_aux: 0.9542 loss: 2.3280 2022/09/11 21:25:37 - mmengine - INFO - Epoch(train) [136][640/940] lr: 4.0000e-04 eta: 2:38:50 time: 0.7002 data_time: 0.0330 memory: 23708 grad_norm: 5.4402 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.2634 loss_aux: 0.8647 loss: 2.1281 2022/09/11 21:25:51 - mmengine - INFO - Epoch(train) [136][660/940] lr: 4.0000e-04 eta: 2:38:36 time: 0.6936 data_time: 0.0399 memory: 23708 grad_norm: 5.3380 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3641 loss_aux: 0.8947 loss: 2.2588 2022/09/11 21:26:05 - mmengine - INFO - Epoch(train) [136][680/940] lr: 4.0000e-04 eta: 2:38:21 time: 0.6780 data_time: 0.0381 memory: 23708 grad_norm: 5.3401 top1_acc: 0.9062 top5_acc: 0.9375 loss_cls: 1.3814 loss_aux: 0.9386 loss: 2.3201 2022/09/11 21:26:18 - mmengine - INFO - Epoch(train) [136][700/940] lr: 4.0000e-04 eta: 2:38:07 time: 0.6808 data_time: 0.0399 memory: 23708 grad_norm: 5.4432 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3898 loss_aux: 0.9222 loss: 2.3120 2022/09/11 21:26:32 - mmengine - INFO - Epoch(train) [136][720/940] lr: 4.0000e-04 eta: 2:37:52 time: 0.6789 data_time: 0.0336 memory: 23708 grad_norm: 5.4498 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4301 loss_aux: 0.9483 loss: 2.3784 2022/09/11 21:26:46 - mmengine - INFO - Epoch(train) [136][740/940] lr: 4.0000e-04 eta: 2:37:38 time: 0.7075 data_time: 0.0496 memory: 23708 grad_norm: 5.3996 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3340 loss_aux: 0.8799 loss: 2.2139 2022/09/11 21:27:00 - mmengine - INFO - Epoch(train) [136][760/940] lr: 4.0000e-04 eta: 2:37:24 time: 0.6879 data_time: 0.0417 memory: 23708 grad_norm: 5.3620 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4952 loss_aux: 0.9667 loss: 2.4619 2022/09/11 21:27:14 - mmengine - INFO - Epoch(train) [136][780/940] lr: 4.0000e-04 eta: 2:37:09 time: 0.6839 data_time: 0.0421 memory: 23708 grad_norm: 5.3953 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3866 loss_aux: 0.9328 loss: 2.3194 2022/09/11 21:27:27 - mmengine - INFO - Epoch(train) [136][800/940] lr: 4.0000e-04 eta: 2:36:55 time: 0.6881 data_time: 0.0398 memory: 23708 grad_norm: 5.3843 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4256 loss_aux: 0.9236 loss: 2.3491 2022/09/11 21:27:41 - mmengine - INFO - Epoch(train) [136][820/940] lr: 4.0000e-04 eta: 2:36:41 time: 0.7091 data_time: 0.0360 memory: 23708 grad_norm: 5.4485 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2674 loss_aux: 0.8673 loss: 2.1346 2022/09/11 21:27:55 - mmengine - INFO - Epoch(train) [136][840/940] lr: 4.0000e-04 eta: 2:36:26 time: 0.6938 data_time: 0.0413 memory: 23708 grad_norm: 5.3985 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3810 loss_aux: 0.9289 loss: 2.3098 2022/09/11 21:28:09 - mmengine - INFO - Epoch(train) [136][860/940] lr: 4.0000e-04 eta: 2:36:12 time: 0.6899 data_time: 0.0423 memory: 23708 grad_norm: 5.3909 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3788 loss_aux: 0.9332 loss: 2.3120 2022/09/11 21:28:23 - mmengine - INFO - Epoch(train) [136][880/940] lr: 4.0000e-04 eta: 2:35:58 time: 0.6827 data_time: 0.0350 memory: 23708 grad_norm: 5.4273 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3341 loss_aux: 0.8899 loss: 2.2240 2022/09/11 21:28:37 - mmengine - INFO - Epoch(train) [136][900/940] lr: 4.0000e-04 eta: 2:35:43 time: 0.6993 data_time: 0.0393 memory: 23708 grad_norm: 5.4812 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3992 loss_aux: 0.9253 loss: 2.3245 2022/09/11 21:28:50 - mmengine - INFO - Epoch(train) [136][920/940] lr: 4.0000e-04 eta: 2:35:29 time: 0.6749 data_time: 0.0378 memory: 23708 grad_norm: 5.3895 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3030 loss_aux: 0.8838 loss: 2.1868 2022/09/11 21:29:03 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 21:29:03 - mmengine - INFO - Epoch(train) [136][940/940] lr: 4.0000e-04 eta: 2:35:14 time: 0.6386 data_time: 0.0293 memory: 23708 grad_norm: 5.6255 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.3223 loss_aux: 0.9223 loss: 2.2446 2022/09/11 21:29:03 - mmengine - INFO - Saving checkpoint at 136 epochs 2022/09/11 21:29:28 - mmengine - INFO - Epoch(train) [137][20/940] lr: 4.0000e-04 eta: 2:35:03 time: 0.9720 data_time: 0.3067 memory: 23708 grad_norm: 5.3370 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2810 loss_aux: 0.8808 loss: 2.1618 2022/09/11 21:29:42 - mmengine - INFO - Epoch(train) [137][40/940] lr: 4.0000e-04 eta: 2:34:48 time: 0.6904 data_time: 0.0423 memory: 23708 grad_norm: 5.3669 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3643 loss_aux: 0.9177 loss: 2.2820 2022/09/11 21:29:56 - mmengine - INFO - Epoch(train) [137][60/940] lr: 4.0000e-04 eta: 2:34:34 time: 0.6834 data_time: 0.0300 memory: 23708 grad_norm: 5.2971 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3076 loss_aux: 0.8796 loss: 2.1872 2022/09/11 21:30:10 - mmengine - INFO - Epoch(train) [137][80/940] lr: 4.0000e-04 eta: 2:34:20 time: 0.7117 data_time: 0.0380 memory: 23708 grad_norm: 5.3837 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3491 loss_aux: 0.9121 loss: 2.2611 2022/09/11 21:30:24 - mmengine - INFO - Epoch(train) [137][100/940] lr: 4.0000e-04 eta: 2:34:06 time: 0.7004 data_time: 0.0403 memory: 23708 grad_norm: 5.4719 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4520 loss_aux: 0.9527 loss: 2.4047 2022/09/11 21:30:38 - mmengine - INFO - Epoch(train) [137][120/940] lr: 4.0000e-04 eta: 2:33:51 time: 0.7080 data_time: 0.0464 memory: 23708 grad_norm: 5.3469 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2456 loss_aux: 0.8587 loss: 2.1043 2022/09/11 21:30:52 - mmengine - INFO - Epoch(train) [137][140/940] lr: 4.0000e-04 eta: 2:33:37 time: 0.6888 data_time: 0.0410 memory: 23708 grad_norm: 5.4970 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3505 loss_aux: 0.9265 loss: 2.2770 2022/09/11 21:31:06 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 21:31:06 - mmengine - INFO - Epoch(train) [137][160/940] lr: 4.0000e-04 eta: 2:33:23 time: 0.7106 data_time: 0.0317 memory: 23708 grad_norm: 5.4291 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3838 loss_aux: 0.9036 loss: 2.2874 2022/09/11 21:31:20 - mmengine - INFO - Epoch(train) [137][180/940] lr: 4.0000e-04 eta: 2:33:09 time: 0.6933 data_time: 0.0411 memory: 23708 grad_norm: 5.3937 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2585 loss_aux: 0.9019 loss: 2.1604 2022/09/11 21:31:34 - mmengine - INFO - Epoch(train) [137][200/940] lr: 4.0000e-04 eta: 2:32:54 time: 0.6975 data_time: 0.0424 memory: 23708 grad_norm: 5.3645 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2949 loss_aux: 0.8877 loss: 2.1826 2022/09/11 21:31:48 - mmengine - INFO - Epoch(train) [137][220/940] lr: 4.0000e-04 eta: 2:32:40 time: 0.6986 data_time: 0.0379 memory: 23708 grad_norm: 5.3509 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4044 loss_aux: 0.9375 loss: 2.3418 2022/09/11 21:32:01 - mmengine - INFO - Epoch(train) [137][240/940] lr: 4.0000e-04 eta: 2:32:26 time: 0.6872 data_time: 0.0308 memory: 23708 grad_norm: 5.4484 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.4168 loss_aux: 0.9606 loss: 2.3774 2022/09/11 21:32:16 - mmengine - INFO - Epoch(train) [137][260/940] lr: 4.0000e-04 eta: 2:32:12 time: 0.7185 data_time: 0.0362 memory: 23708 grad_norm: 5.3345 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3437 loss_aux: 0.9237 loss: 2.2674 2022/09/11 21:32:30 - mmengine - INFO - Epoch(train) [137][280/940] lr: 4.0000e-04 eta: 2:31:57 time: 0.7063 data_time: 0.0487 memory: 23708 grad_norm: 5.3998 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4185 loss_aux: 0.9715 loss: 2.3900 2022/09/11 21:32:44 - mmengine - INFO - Epoch(train) [137][300/940] lr: 4.0000e-04 eta: 2:31:43 time: 0.6948 data_time: 0.0325 memory: 23708 grad_norm: 5.4921 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3549 loss_aux: 0.8959 loss: 2.2508 2022/09/11 21:32:58 - mmengine - INFO - Epoch(train) [137][320/940] lr: 4.0000e-04 eta: 2:31:29 time: 0.7105 data_time: 0.0330 memory: 23708 grad_norm: 5.4931 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3883 loss_aux: 0.9404 loss: 2.3287 2022/09/11 21:33:12 - mmengine - INFO - Epoch(train) [137][340/940] lr: 4.0000e-04 eta: 2:31:15 time: 0.6981 data_time: 0.0384 memory: 23708 grad_norm: 5.3394 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3284 loss_aux: 0.8968 loss: 2.2252 2022/09/11 21:33:26 - mmengine - INFO - Epoch(train) [137][360/940] lr: 4.0000e-04 eta: 2:31:01 time: 0.7034 data_time: 0.0435 memory: 23708 grad_norm: 5.4427 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.3149 loss_aux: 0.8644 loss: 2.1792 2022/09/11 21:33:40 - mmengine - INFO - Epoch(train) [137][380/940] lr: 4.0000e-04 eta: 2:30:46 time: 0.6967 data_time: 0.0313 memory: 23708 grad_norm: 5.4049 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2903 loss_aux: 0.9041 loss: 2.1944 2022/09/11 21:33:54 - mmengine - INFO - Epoch(train) [137][400/940] lr: 4.0000e-04 eta: 2:30:32 time: 0.6874 data_time: 0.0392 memory: 23708 grad_norm: 5.4198 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3715 loss_aux: 0.9329 loss: 2.3044 2022/09/11 21:34:08 - mmengine - INFO - Epoch(train) [137][420/940] lr: 4.0000e-04 eta: 2:30:18 time: 0.7033 data_time: 0.0443 memory: 23708 grad_norm: 5.3929 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2587 loss_aux: 0.8624 loss: 2.1211 2022/09/11 21:34:22 - mmengine - INFO - Epoch(train) [137][440/940] lr: 4.0000e-04 eta: 2:30:04 time: 0.7120 data_time: 0.0396 memory: 23708 grad_norm: 5.3048 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2672 loss_aux: 0.8848 loss: 2.1520 2022/09/11 21:34:36 - mmengine - INFO - Epoch(train) [137][460/940] lr: 4.0000e-04 eta: 2:29:49 time: 0.6896 data_time: 0.0331 memory: 23708 grad_norm: 5.3769 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4536 loss_aux: 0.9532 loss: 2.4069 2022/09/11 21:34:50 - mmengine - INFO - Epoch(train) [137][480/940] lr: 4.0000e-04 eta: 2:29:35 time: 0.6954 data_time: 0.0322 memory: 23708 grad_norm: 5.4482 top1_acc: 0.5625 top5_acc: 0.6562 loss_cls: 1.3797 loss_aux: 0.9264 loss: 2.3061 2022/09/11 21:35:04 - mmengine - INFO - Epoch(train) [137][500/940] lr: 4.0000e-04 eta: 2:29:21 time: 0.7009 data_time: 0.0407 memory: 23708 grad_norm: 5.5158 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4204 loss_aux: 0.9566 loss: 2.3770 2022/09/11 21:35:18 - mmengine - INFO - Epoch(train) [137][520/940] lr: 4.0000e-04 eta: 2:29:06 time: 0.7040 data_time: 0.0478 memory: 23708 grad_norm: 5.4667 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.2832 loss_aux: 0.9028 loss: 2.1860 2022/09/11 21:35:32 - mmengine - INFO - Epoch(train) [137][540/940] lr: 4.0000e-04 eta: 2:28:52 time: 0.6994 data_time: 0.0344 memory: 23708 grad_norm: 5.4118 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4544 loss_aux: 0.9551 loss: 2.4095 2022/09/11 21:35:46 - mmengine - INFO - Epoch(train) [137][560/940] lr: 4.0000e-04 eta: 2:28:38 time: 0.6949 data_time: 0.0361 memory: 23708 grad_norm: 5.5439 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.4921 loss_aux: 0.9727 loss: 2.4649 2022/09/11 21:36:00 - mmengine - INFO - Epoch(train) [137][580/940] lr: 4.0000e-04 eta: 2:28:24 time: 0.7195 data_time: 0.0418 memory: 23708 grad_norm: 5.4305 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2687 loss_aux: 0.8829 loss: 2.1516 2022/09/11 21:36:14 - mmengine - INFO - Epoch(train) [137][600/940] lr: 4.0000e-04 eta: 2:28:10 time: 0.6995 data_time: 0.0428 memory: 23708 grad_norm: 5.4194 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3276 loss_aux: 0.8861 loss: 2.2137 2022/09/11 21:36:28 - mmengine - INFO - Epoch(train) [137][620/940] lr: 4.0000e-04 eta: 2:27:55 time: 0.6952 data_time: 0.0333 memory: 23708 grad_norm: 5.4394 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3633 loss_aux: 0.9437 loss: 2.3070 2022/09/11 21:36:42 - mmengine - INFO - Epoch(train) [137][640/940] lr: 4.0000e-04 eta: 2:27:41 time: 0.7027 data_time: 0.0421 memory: 23708 grad_norm: 5.3602 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3404 loss_aux: 0.9033 loss: 2.2438 2022/09/11 21:36:57 - mmengine - INFO - Epoch(train) [137][660/940] lr: 4.0000e-04 eta: 2:27:27 time: 0.7199 data_time: 0.0399 memory: 23708 grad_norm: 5.4745 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3886 loss_aux: 0.8996 loss: 2.2882 2022/09/11 21:37:10 - mmengine - INFO - Epoch(train) [137][680/940] lr: 4.0000e-04 eta: 2:27:13 time: 0.6986 data_time: 0.0484 memory: 23708 grad_norm: 5.4713 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4087 loss_aux: 0.9698 loss: 2.3785 2022/09/11 21:37:24 - mmengine - INFO - Epoch(train) [137][700/940] lr: 4.0000e-04 eta: 2:26:58 time: 0.6791 data_time: 0.0318 memory: 23708 grad_norm: 5.4505 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.4508 loss_aux: 0.9366 loss: 2.3874 2022/09/11 21:37:38 - mmengine - INFO - Epoch(train) [137][720/940] lr: 4.0000e-04 eta: 2:26:44 time: 0.6854 data_time: 0.0333 memory: 23708 grad_norm: 5.4893 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.4224 loss_aux: 0.9659 loss: 2.3883 2022/09/11 21:37:52 - mmengine - INFO - Epoch(train) [137][740/940] lr: 4.0000e-04 eta: 2:26:30 time: 0.6918 data_time: 0.0417 memory: 23708 grad_norm: 5.3941 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.4340 loss_aux: 0.9312 loss: 2.3652 2022/09/11 21:38:05 - mmengine - INFO - Epoch(train) [137][760/940] lr: 4.0000e-04 eta: 2:26:15 time: 0.6894 data_time: 0.0430 memory: 23708 grad_norm: 5.4426 top1_acc: 0.7188 top5_acc: 1.0000 loss_cls: 1.3972 loss_aux: 0.9486 loss: 2.3457 2022/09/11 21:38:19 - mmengine - INFO - Epoch(train) [137][780/940] lr: 4.0000e-04 eta: 2:26:01 time: 0.6897 data_time: 0.0311 memory: 23708 grad_norm: 5.4379 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4127 loss_aux: 0.9541 loss: 2.3667 2022/09/11 21:38:33 - mmengine - INFO - Epoch(train) [137][800/940] lr: 4.0000e-04 eta: 2:25:47 time: 0.6793 data_time: 0.0339 memory: 23708 grad_norm: 5.4439 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4594 loss_aux: 0.9903 loss: 2.4498 2022/09/11 21:38:47 - mmengine - INFO - Epoch(train) [137][820/940] lr: 4.0000e-04 eta: 2:25:32 time: 0.6913 data_time: 0.0397 memory: 23708 grad_norm: 5.5085 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3225 loss_aux: 0.8854 loss: 2.2080 2022/09/11 21:39:00 - mmengine - INFO - Epoch(train) [137][840/940] lr: 4.0000e-04 eta: 2:25:18 time: 0.6851 data_time: 0.0406 memory: 23708 grad_norm: 5.4964 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3935 loss_aux: 0.9309 loss: 2.3244 2022/09/11 21:39:14 - mmengine - INFO - Epoch(train) [137][860/940] lr: 4.0000e-04 eta: 2:25:03 time: 0.6828 data_time: 0.0324 memory: 23708 grad_norm: 5.4372 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3996 loss_aux: 0.9442 loss: 2.3439 2022/09/11 21:39:28 - mmengine - INFO - Epoch(train) [137][880/940] lr: 4.0000e-04 eta: 2:24:49 time: 0.6815 data_time: 0.0321 memory: 23708 grad_norm: 5.4426 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3916 loss_aux: 0.9428 loss: 2.3344 2022/09/11 21:39:42 - mmengine - INFO - Epoch(train) [137][900/940] lr: 4.0000e-04 eta: 2:24:35 time: 0.7065 data_time: 0.0452 memory: 23708 grad_norm: 5.4416 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3387 loss_aux: 0.9113 loss: 2.2499 2022/09/11 21:39:56 - mmengine - INFO - Epoch(train) [137][920/940] lr: 4.0000e-04 eta: 2:24:20 time: 0.6902 data_time: 0.0400 memory: 23708 grad_norm: 5.3290 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3380 loss_aux: 0.9055 loss: 2.2435 2022/09/11 21:40:08 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 21:40:08 - mmengine - INFO - Epoch(train) [137][940/940] lr: 4.0000e-04 eta: 2:24:06 time: 0.6328 data_time: 0.0259 memory: 23708 grad_norm: 5.7673 top1_acc: 0.1429 top5_acc: 0.7143 loss_cls: 1.3807 loss_aux: 0.9048 loss: 2.2855 2022/09/11 21:40:08 - mmengine - INFO - Saving checkpoint at 137 epochs 2022/09/11 21:40:34 - mmengine - INFO - Epoch(train) [138][20/940] lr: 4.0000e-04 eta: 2:23:54 time: 0.9461 data_time: 0.2905 memory: 23708 grad_norm: 5.4232 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4029 loss_aux: 0.9255 loss: 2.3285 2022/09/11 21:40:47 - mmengine - INFO - Epoch(train) [138][40/940] lr: 4.0000e-04 eta: 2:23:39 time: 0.6723 data_time: 0.0249 memory: 23708 grad_norm: 5.4070 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2770 loss_aux: 0.8753 loss: 2.1523 2022/09/11 21:41:01 - mmengine - INFO - Epoch(train) [138][60/940] lr: 4.0000e-04 eta: 2:23:25 time: 0.6878 data_time: 0.0372 memory: 23708 grad_norm: 5.5122 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3684 loss_aux: 0.9442 loss: 2.3125 2022/09/11 21:41:15 - mmengine - INFO - Epoch(train) [138][80/940] lr: 4.0000e-04 eta: 2:23:11 time: 0.7084 data_time: 0.0353 memory: 23708 grad_norm: 5.5254 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4890 loss_aux: 0.9553 loss: 2.4443 2022/09/11 21:41:29 - mmengine - INFO - Epoch(train) [138][100/940] lr: 4.0000e-04 eta: 2:22:57 time: 0.7142 data_time: 0.0479 memory: 23708 grad_norm: 5.5169 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3818 loss_aux: 0.9377 loss: 2.3194 2022/09/11 21:41:43 - mmengine - INFO - Epoch(train) [138][120/940] lr: 4.0000e-04 eta: 2:22:42 time: 0.6966 data_time: 0.0350 memory: 23708 grad_norm: 5.4394 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4376 loss_aux: 0.9601 loss: 2.3978 2022/09/11 21:41:58 - mmengine - INFO - Epoch(train) [138][140/940] lr: 4.0000e-04 eta: 2:22:28 time: 0.7107 data_time: 0.0340 memory: 23708 grad_norm: 5.4131 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3908 loss_aux: 0.9294 loss: 2.3202 2022/09/11 21:42:12 - mmengine - INFO - Epoch(train) [138][160/940] lr: 4.0000e-04 eta: 2:22:14 time: 0.7201 data_time: 0.0397 memory: 23708 grad_norm: 5.4252 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4006 loss_aux: 0.9573 loss: 2.3579 2022/09/11 21:42:26 - mmengine - INFO - Epoch(train) [138][180/940] lr: 4.0000e-04 eta: 2:22:00 time: 0.7131 data_time: 0.0314 memory: 23708 grad_norm: 5.4435 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2337 loss_aux: 0.8361 loss: 2.0698 2022/09/11 21:42:41 - mmengine - INFO - Epoch(train) [138][200/940] lr: 4.0000e-04 eta: 2:21:46 time: 0.7224 data_time: 0.0309 memory: 23708 grad_norm: 5.4721 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3132 loss_aux: 0.9183 loss: 2.2315 2022/09/11 21:42:55 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 21:42:55 - mmengine - INFO - Epoch(train) [138][220/940] lr: 4.0000e-04 eta: 2:21:32 time: 0.7234 data_time: 0.0340 memory: 23708 grad_norm: 5.3803 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3754 loss_aux: 0.9274 loss: 2.3028 2022/09/11 21:43:09 - mmengine - INFO - Epoch(train) [138][240/940] lr: 4.0000e-04 eta: 2:21:18 time: 0.7118 data_time: 0.0436 memory: 23708 grad_norm: 5.4856 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4180 loss_aux: 0.9581 loss: 2.3761 2022/09/11 21:43:24 - mmengine - INFO - Epoch(train) [138][260/940] lr: 4.0000e-04 eta: 2:21:04 time: 0.7224 data_time: 0.0321 memory: 23708 grad_norm: 5.3921 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2996 loss_aux: 0.9120 loss: 2.2116 2022/09/11 21:43:38 - mmengine - INFO - Epoch(train) [138][280/940] lr: 4.0000e-04 eta: 2:20:50 time: 0.7270 data_time: 0.0302 memory: 23708 grad_norm: 5.4554 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3733 loss_aux: 0.9091 loss: 2.2824 2022/09/11 21:43:52 - mmengine - INFO - Epoch(train) [138][300/940] lr: 4.0000e-04 eta: 2:20:36 time: 0.7017 data_time: 0.0338 memory: 23708 grad_norm: 5.3850 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2364 loss_aux: 0.8468 loss: 2.0832 2022/09/11 21:44:07 - mmengine - INFO - Epoch(train) [138][320/940] lr: 4.0000e-04 eta: 2:20:22 time: 0.7055 data_time: 0.0376 memory: 23708 grad_norm: 5.5274 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3615 loss_aux: 0.9190 loss: 2.2805 2022/09/11 21:44:21 - mmengine - INFO - Epoch(train) [138][340/940] lr: 4.0000e-04 eta: 2:20:08 time: 0.7126 data_time: 0.0291 memory: 23708 grad_norm: 5.4645 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3378 loss_aux: 0.9320 loss: 2.2698 2022/09/11 21:44:35 - mmengine - INFO - Epoch(train) [138][360/940] lr: 4.0000e-04 eta: 2:19:53 time: 0.6971 data_time: 0.0354 memory: 23708 grad_norm: 5.4325 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3102 loss_aux: 0.8894 loss: 2.1997 2022/09/11 21:44:49 - mmengine - INFO - Epoch(train) [138][380/940] lr: 4.0000e-04 eta: 2:19:39 time: 0.7007 data_time: 0.0405 memory: 23708 grad_norm: 5.4956 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.3375 loss_aux: 0.9150 loss: 2.2525 2022/09/11 21:45:03 - mmengine - INFO - Epoch(train) [138][400/940] lr: 4.0000e-04 eta: 2:19:25 time: 0.7028 data_time: 0.0380 memory: 23708 grad_norm: 5.4256 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2807 loss_aux: 0.9000 loss: 2.1807 2022/09/11 21:45:17 - mmengine - INFO - Epoch(train) [138][420/940] lr: 4.0000e-04 eta: 2:19:11 time: 0.7158 data_time: 0.0293 memory: 23708 grad_norm: 5.4933 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3387 loss_aux: 0.9233 loss: 2.2621 2022/09/11 21:45:31 - mmengine - INFO - Epoch(train) [138][440/940] lr: 4.0000e-04 eta: 2:18:57 time: 0.7025 data_time: 0.0438 memory: 23708 grad_norm: 5.5337 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.3910 loss_aux: 0.9534 loss: 2.3444 2022/09/11 21:45:45 - mmengine - INFO - Epoch(train) [138][460/940] lr: 4.0000e-04 eta: 2:18:42 time: 0.6966 data_time: 0.0331 memory: 23708 grad_norm: 5.4342 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4383 loss_aux: 0.9552 loss: 2.3935 2022/09/11 21:45:59 - mmengine - INFO - Epoch(train) [138][480/940] lr: 4.0000e-04 eta: 2:18:28 time: 0.7113 data_time: 0.0421 memory: 23708 grad_norm: 5.3467 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3294 loss_aux: 0.8746 loss: 2.2040 2022/09/11 21:46:14 - mmengine - INFO - Epoch(train) [138][500/940] lr: 4.0000e-04 eta: 2:18:14 time: 0.7099 data_time: 0.0321 memory: 23708 grad_norm: 5.3819 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3910 loss_aux: 0.9205 loss: 2.3115 2022/09/11 21:46:27 - mmengine - INFO - Epoch(train) [138][520/940] lr: 4.0000e-04 eta: 2:18:00 time: 0.6946 data_time: 0.0328 memory: 23708 grad_norm: 5.4249 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4698 loss_aux: 0.9828 loss: 2.4526 2022/09/11 21:46:42 - mmengine - INFO - Epoch(train) [138][540/940] lr: 4.0000e-04 eta: 2:17:46 time: 0.7032 data_time: 0.0325 memory: 23708 grad_norm: 5.4206 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2970 loss_aux: 0.8965 loss: 2.1934 2022/09/11 21:46:56 - mmengine - INFO - Epoch(train) [138][560/940] lr: 4.0000e-04 eta: 2:17:31 time: 0.7007 data_time: 0.0367 memory: 23708 grad_norm: 5.4791 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4141 loss_aux: 0.9438 loss: 2.3579 2022/09/11 21:47:10 - mmengine - INFO - Epoch(train) [138][580/940] lr: 4.0000e-04 eta: 2:17:17 time: 0.7092 data_time: 0.0339 memory: 23708 grad_norm: 5.3759 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4706 loss_aux: 0.9820 loss: 2.4526 2022/09/11 21:47:24 - mmengine - INFO - Epoch(train) [138][600/940] lr: 4.0000e-04 eta: 2:17:03 time: 0.7046 data_time: 0.0290 memory: 23708 grad_norm: 5.3609 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3672 loss_aux: 0.8958 loss: 2.2630 2022/09/11 21:47:38 - mmengine - INFO - Epoch(train) [138][620/940] lr: 4.0000e-04 eta: 2:16:49 time: 0.7024 data_time: 0.0364 memory: 23708 grad_norm: 5.4366 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3458 loss_aux: 0.9187 loss: 2.2645 2022/09/11 21:47:52 - mmengine - INFO - Epoch(train) [138][640/940] lr: 4.0000e-04 eta: 2:16:35 time: 0.7246 data_time: 0.0517 memory: 23708 grad_norm: 5.3111 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.4600 loss_aux: 0.9252 loss: 2.3853 2022/09/11 21:48:06 - mmengine - INFO - Epoch(train) [138][660/940] lr: 4.0000e-04 eta: 2:16:21 time: 0.6968 data_time: 0.0276 memory: 23708 grad_norm: 5.4686 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.4073 loss_aux: 0.9402 loss: 2.3475 2022/09/11 21:48:20 - mmengine - INFO - Epoch(train) [138][680/940] lr: 4.0000e-04 eta: 2:16:06 time: 0.7020 data_time: 0.0340 memory: 23708 grad_norm: 5.5046 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3684 loss_aux: 0.9404 loss: 2.3088 2022/09/11 21:48:34 - mmengine - INFO - Epoch(train) [138][700/940] lr: 4.0000e-04 eta: 2:15:52 time: 0.6928 data_time: 0.0329 memory: 23708 grad_norm: 5.4884 top1_acc: 0.5000 top5_acc: 0.7188 loss_cls: 1.2708 loss_aux: 0.8599 loss: 2.1308 2022/09/11 21:48:48 - mmengine - INFO - Epoch(train) [138][720/940] lr: 4.0000e-04 eta: 2:15:38 time: 0.6961 data_time: 0.0397 memory: 23708 grad_norm: 5.5480 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3881 loss_aux: 0.9419 loss: 2.3300 2022/09/11 21:49:02 - mmengine - INFO - Epoch(train) [138][740/940] lr: 4.0000e-04 eta: 2:15:24 time: 0.7085 data_time: 0.0374 memory: 23708 grad_norm: 5.4143 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2895 loss_aux: 0.8955 loss: 2.1850 2022/09/11 21:49:16 - mmengine - INFO - Epoch(train) [138][760/940] lr: 4.0000e-04 eta: 2:15:09 time: 0.6922 data_time: 0.0356 memory: 23708 grad_norm: 5.4713 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3757 loss_aux: 0.9230 loss: 2.2987 2022/09/11 21:49:30 - mmengine - INFO - Epoch(train) [138][780/940] lr: 4.0000e-04 eta: 2:14:55 time: 0.6983 data_time: 0.0345 memory: 23708 grad_norm: 5.3830 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3114 loss_aux: 0.8986 loss: 2.2100 2022/09/11 21:49:44 - mmengine - INFO - Epoch(train) [138][800/940] lr: 4.0000e-04 eta: 2:14:41 time: 0.7093 data_time: 0.0418 memory: 23708 grad_norm: 5.4056 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3622 loss_aux: 0.9128 loss: 2.2749 2022/09/11 21:49:59 - mmengine - INFO - Epoch(train) [138][820/940] lr: 4.0000e-04 eta: 2:14:27 time: 0.7091 data_time: 0.0313 memory: 23708 grad_norm: 5.4669 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3016 loss_aux: 0.8928 loss: 2.1944 2022/09/11 21:50:13 - mmengine - INFO - Epoch(train) [138][840/940] lr: 4.0000e-04 eta: 2:14:13 time: 0.7020 data_time: 0.0319 memory: 23708 grad_norm: 5.4078 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3158 loss_aux: 0.9236 loss: 2.2394 2022/09/11 21:50:27 - mmengine - INFO - Epoch(train) [138][860/940] lr: 4.0000e-04 eta: 2:13:59 time: 0.7092 data_time: 0.0404 memory: 23708 grad_norm: 5.4977 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.3147 loss_aux: 0.9119 loss: 2.2266 2022/09/11 21:50:41 - mmengine - INFO - Epoch(train) [138][880/940] lr: 4.0000e-04 eta: 2:13:44 time: 0.7001 data_time: 0.0414 memory: 23708 grad_norm: 5.5025 top1_acc: 0.7812 top5_acc: 1.0000 loss_cls: 1.3405 loss_aux: 0.9092 loss: 2.2497 2022/09/11 21:50:55 - mmengine - INFO - Epoch(train) [138][900/940] lr: 4.0000e-04 eta: 2:13:30 time: 0.6923 data_time: 0.0333 memory: 23708 grad_norm: 5.4973 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3585 loss_aux: 0.9217 loss: 2.2801 2022/09/11 21:51:08 - mmengine - INFO - Epoch(train) [138][920/940] lr: 4.0000e-04 eta: 2:13:16 time: 0.6918 data_time: 0.0355 memory: 23708 grad_norm: 5.5295 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3091 loss_aux: 0.9246 loss: 2.2337 2022/09/11 21:51:21 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 21:51:21 - mmengine - INFO - Epoch(train) [138][940/940] lr: 4.0000e-04 eta: 2:13:01 time: 0.6374 data_time: 0.0279 memory: 23708 grad_norm: 5.7647 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4072 loss_aux: 0.9143 loss: 2.3214 2022/09/11 21:51:21 - mmengine - INFO - Saving checkpoint at 138 epochs 2022/09/11 21:51:47 - mmengine - INFO - Epoch(train) [139][20/940] lr: 4.0000e-04 eta: 2:12:49 time: 0.9758 data_time: 0.3081 memory: 23708 grad_norm: 5.4216 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3190 loss_aux: 0.9103 loss: 2.2293 2022/09/11 21:52:01 - mmengine - INFO - Epoch(train) [139][40/940] lr: 4.0000e-04 eta: 2:12:35 time: 0.6817 data_time: 0.0315 memory: 23708 grad_norm: 5.4342 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3304 loss_aux: 0.8895 loss: 2.2199 2022/09/11 21:52:14 - mmengine - INFO - Epoch(train) [139][60/940] lr: 4.0000e-04 eta: 2:12:20 time: 0.6664 data_time: 0.0325 memory: 23708 grad_norm: 5.3916 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3244 loss_aux: 0.9006 loss: 2.2249 2022/09/11 21:52:28 - mmengine - INFO - Epoch(train) [139][80/940] lr: 4.0000e-04 eta: 2:12:06 time: 0.6831 data_time: 0.0414 memory: 23708 grad_norm: 5.3303 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3166 loss_aux: 0.8678 loss: 2.1845 2022/09/11 21:52:42 - mmengine - INFO - Epoch(train) [139][100/940] lr: 4.0000e-04 eta: 2:11:52 time: 0.7008 data_time: 0.0430 memory: 23708 grad_norm: 5.4876 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4301 loss_aux: 1.0162 loss: 2.4463 2022/09/11 21:52:55 - mmengine - INFO - Epoch(train) [139][120/940] lr: 4.0000e-04 eta: 2:11:37 time: 0.6621 data_time: 0.0324 memory: 23708 grad_norm: 5.3892 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.4260 loss_aux: 0.9862 loss: 2.4122 2022/09/11 21:53:08 - mmengine - INFO - Epoch(train) [139][140/940] lr: 4.0000e-04 eta: 2:11:23 time: 0.6664 data_time: 0.0343 memory: 23708 grad_norm: 5.4300 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.5716 loss_aux: 0.9966 loss: 2.5683 2022/09/11 21:53:22 - mmengine - INFO - Epoch(train) [139][160/940] lr: 4.0000e-04 eta: 2:11:08 time: 0.6734 data_time: 0.0438 memory: 23708 grad_norm: 5.3662 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3602 loss_aux: 0.9631 loss: 2.3233 2022/09/11 21:53:36 - mmengine - INFO - Epoch(train) [139][180/940] lr: 4.0000e-04 eta: 2:10:54 time: 0.6934 data_time: 0.0389 memory: 23708 grad_norm: 5.5216 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3953 loss_aux: 0.9180 loss: 2.3132 2022/09/11 21:53:49 - mmengine - INFO - Epoch(train) [139][200/940] lr: 4.0000e-04 eta: 2:10:39 time: 0.6758 data_time: 0.0424 memory: 23708 grad_norm: 5.4520 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3737 loss_aux: 0.9447 loss: 2.3185 2022/09/11 21:54:02 - mmengine - INFO - Epoch(train) [139][220/940] lr: 4.0000e-04 eta: 2:10:25 time: 0.6703 data_time: 0.0349 memory: 23708 grad_norm: 5.4810 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3104 loss_aux: 0.8708 loss: 2.1812 2022/09/11 21:54:16 - mmengine - INFO - Epoch(train) [139][240/940] lr: 4.0000e-04 eta: 2:10:11 time: 0.6820 data_time: 0.0359 memory: 23708 grad_norm: 5.3610 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2483 loss_aux: 0.8847 loss: 2.1330 2022/09/11 21:54:30 - mmengine - INFO - Epoch(train) [139][260/940] lr: 4.0000e-04 eta: 2:09:56 time: 0.6938 data_time: 0.0416 memory: 23708 grad_norm: 5.2731 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2456 loss_aux: 0.8551 loss: 2.1007 2022/09/11 21:54:44 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 21:54:44 - mmengine - INFO - Epoch(train) [139][280/940] lr: 4.0000e-04 eta: 2:09:42 time: 0.6845 data_time: 0.0368 memory: 23708 grad_norm: 5.5568 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.4335 loss_aux: 0.9793 loss: 2.4127 2022/09/11 21:54:57 - mmengine - INFO - Epoch(train) [139][300/940] lr: 4.0000e-04 eta: 2:09:28 time: 0.6805 data_time: 0.0361 memory: 23708 grad_norm: 5.4389 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1821 loss_aux: 0.8072 loss: 1.9893 2022/09/11 21:55:11 - mmengine - INFO - Epoch(train) [139][320/940] lr: 4.0000e-04 eta: 2:09:13 time: 0.6720 data_time: 0.0406 memory: 23708 grad_norm: 5.5199 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2705 loss_aux: 0.9134 loss: 2.1840 2022/09/11 21:55:25 - mmengine - INFO - Epoch(train) [139][340/940] lr: 4.0000e-04 eta: 2:08:59 time: 0.7003 data_time: 0.0391 memory: 23708 grad_norm: 5.4623 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4289 loss_aux: 0.9740 loss: 2.4029 2022/09/11 21:55:38 - mmengine - INFO - Epoch(train) [139][360/940] lr: 4.0000e-04 eta: 2:08:45 time: 0.6842 data_time: 0.0419 memory: 23708 grad_norm: 5.5153 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3694 loss_aux: 0.9063 loss: 2.2757 2022/09/11 21:55:52 - mmengine - INFO - Epoch(train) [139][380/940] lr: 4.0000e-04 eta: 2:08:30 time: 0.6869 data_time: 0.0371 memory: 23708 grad_norm: 5.4836 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.2438 loss_aux: 0.8456 loss: 2.0894 2022/09/11 21:56:06 - mmengine - INFO - Epoch(train) [139][400/940] lr: 4.0000e-04 eta: 2:08:16 time: 0.6884 data_time: 0.0423 memory: 23708 grad_norm: 5.4002 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4203 loss_aux: 0.9419 loss: 2.3622 2022/09/11 21:56:21 - mmengine - INFO - Epoch(train) [139][420/940] lr: 4.0000e-04 eta: 2:08:02 time: 0.7299 data_time: 0.0515 memory: 23708 grad_norm: 5.4642 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3963 loss_aux: 0.9408 loss: 2.3371 2022/09/11 21:56:34 - mmengine - INFO - Epoch(train) [139][440/940] lr: 4.0000e-04 eta: 2:07:48 time: 0.6786 data_time: 0.0338 memory: 23708 grad_norm: 5.5148 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.4167 loss_aux: 0.9518 loss: 2.3685 2022/09/11 21:56:48 - mmengine - INFO - Epoch(train) [139][460/940] lr: 4.0000e-04 eta: 2:07:33 time: 0.6736 data_time: 0.0386 memory: 23708 grad_norm: 5.4610 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4361 loss_aux: 0.9310 loss: 2.3671 2022/09/11 21:57:01 - mmengine - INFO - Epoch(train) [139][480/940] lr: 4.0000e-04 eta: 2:07:19 time: 0.6777 data_time: 0.0419 memory: 23708 grad_norm: 5.5192 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3469 loss_aux: 0.8948 loss: 2.2417 2022/09/11 21:57:15 - mmengine - INFO - Epoch(train) [139][500/940] lr: 4.0000e-04 eta: 2:07:04 time: 0.6971 data_time: 0.0433 memory: 23708 grad_norm: 5.4255 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.4042 loss_aux: 0.9439 loss: 2.3480 2022/09/11 21:57:29 - mmengine - INFO - Epoch(train) [139][520/940] lr: 4.0000e-04 eta: 2:06:50 time: 0.6934 data_time: 0.0381 memory: 23708 grad_norm: 5.4557 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.1880 loss_aux: 0.8578 loss: 2.0459 2022/09/11 21:57:43 - mmengine - INFO - Epoch(train) [139][540/940] lr: 4.0000e-04 eta: 2:06:36 time: 0.6783 data_time: 0.0410 memory: 23708 grad_norm: 5.3688 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4272 loss_aux: 0.9564 loss: 2.3836 2022/09/11 21:57:56 - mmengine - INFO - Epoch(train) [139][560/940] lr: 4.0000e-04 eta: 2:06:21 time: 0.6787 data_time: 0.0379 memory: 23708 grad_norm: 5.4885 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4349 loss_aux: 0.9654 loss: 2.4004 2022/09/11 21:58:10 - mmengine - INFO - Epoch(train) [139][580/940] lr: 4.0000e-04 eta: 2:06:07 time: 0.6963 data_time: 0.0385 memory: 23708 grad_norm: 5.4272 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3529 loss_aux: 0.8995 loss: 2.2525 2022/09/11 21:58:24 - mmengine - INFO - Epoch(train) [139][600/940] lr: 4.0000e-04 eta: 2:05:53 time: 0.6875 data_time: 0.0364 memory: 23708 grad_norm: 5.5208 top1_acc: 0.4688 top5_acc: 0.7500 loss_cls: 1.2938 loss_aux: 0.9343 loss: 2.2281 2022/09/11 21:58:37 - mmengine - INFO - Epoch(train) [139][620/940] lr: 4.0000e-04 eta: 2:05:38 time: 0.6726 data_time: 0.0405 memory: 23708 grad_norm: 5.4664 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4248 loss_aux: 0.9048 loss: 2.3296 2022/09/11 21:58:51 - mmengine - INFO - Epoch(train) [139][640/940] lr: 4.0000e-04 eta: 2:05:24 time: 0.6952 data_time: 0.0371 memory: 23708 grad_norm: 5.4074 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.3796 loss_aux: 0.9413 loss: 2.3208 2022/09/11 21:59:05 - mmengine - INFO - Epoch(train) [139][660/940] lr: 4.0000e-04 eta: 2:05:10 time: 0.6945 data_time: 0.0289 memory: 23708 grad_norm: 5.4911 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2593 loss_aux: 0.8728 loss: 2.1321 2022/09/11 21:59:19 - mmengine - INFO - Epoch(train) [139][680/940] lr: 4.0000e-04 eta: 2:04:56 time: 0.6919 data_time: 0.0449 memory: 23708 grad_norm: 5.4693 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3028 loss_aux: 0.8842 loss: 2.1870 2022/09/11 21:59:33 - mmengine - INFO - Epoch(train) [139][700/940] lr: 4.0000e-04 eta: 2:04:41 time: 0.6904 data_time: 0.0402 memory: 23708 grad_norm: 5.3737 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.1672 loss_aux: 0.8537 loss: 2.0209 2022/09/11 21:59:46 - mmengine - INFO - Epoch(train) [139][720/940] lr: 4.0000e-04 eta: 2:04:27 time: 0.6808 data_time: 0.0317 memory: 23708 grad_norm: 5.4520 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3538 loss_aux: 0.9059 loss: 2.2598 2022/09/11 22:00:01 - mmengine - INFO - Epoch(train) [139][740/940] lr: 4.0000e-04 eta: 2:04:13 time: 0.7093 data_time: 0.0377 memory: 23708 grad_norm: 5.5423 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.3788 loss_aux: 0.9342 loss: 2.3130 2022/09/11 22:00:14 - mmengine - INFO - Epoch(train) [139][760/940] lr: 4.0000e-04 eta: 2:03:59 time: 0.6921 data_time: 0.0467 memory: 23708 grad_norm: 5.3994 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3003 loss_aux: 0.9172 loss: 2.2175 2022/09/11 22:00:28 - mmengine - INFO - Epoch(train) [139][780/940] lr: 4.0000e-04 eta: 2:03:44 time: 0.6948 data_time: 0.0425 memory: 23708 grad_norm: 5.5459 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.5221 loss_aux: 0.9845 loss: 2.5066 2022/09/11 22:00:42 - mmengine - INFO - Epoch(train) [139][800/940] lr: 4.0000e-04 eta: 2:03:30 time: 0.7005 data_time: 0.0392 memory: 23708 grad_norm: 5.4265 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3791 loss_aux: 0.9442 loss: 2.3233 2022/09/11 22:00:56 - mmengine - INFO - Epoch(train) [139][820/940] lr: 4.0000e-04 eta: 2:03:16 time: 0.7004 data_time: 0.0418 memory: 23708 grad_norm: 5.3892 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.4635 loss_aux: 0.9646 loss: 2.4281 2022/09/11 22:01:10 - mmengine - INFO - Epoch(train) [139][840/940] lr: 4.0000e-04 eta: 2:03:02 time: 0.6869 data_time: 0.0416 memory: 23708 grad_norm: 5.3860 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3604 loss_aux: 0.9044 loss: 2.2648 2022/09/11 22:01:24 - mmengine - INFO - Epoch(train) [139][860/940] lr: 4.0000e-04 eta: 2:02:47 time: 0.6885 data_time: 0.0412 memory: 23708 grad_norm: 5.5414 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.5945 loss_aux: 1.0392 loss: 2.6337 2022/09/11 22:01:38 - mmengine - INFO - Epoch(train) [139][880/940] lr: 4.0000e-04 eta: 2:02:33 time: 0.6933 data_time: 0.0328 memory: 23708 grad_norm: 5.5050 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.4336 loss_aux: 0.9621 loss: 2.3957 2022/09/11 22:01:52 - mmengine - INFO - Epoch(train) [139][900/940] lr: 4.0000e-04 eta: 2:02:19 time: 0.7091 data_time: 0.0388 memory: 23708 grad_norm: 5.5449 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3683 loss_aux: 0.9173 loss: 2.2857 2022/09/11 22:02:06 - mmengine - INFO - Epoch(train) [139][920/940] lr: 4.0000e-04 eta: 2:02:05 time: 0.6885 data_time: 0.0366 memory: 23708 grad_norm: 5.4215 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.2970 loss_aux: 0.8638 loss: 2.1608 2022/09/11 22:02:19 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 22:02:19 - mmengine - INFO - Epoch(train) [139][940/940] lr: 4.0000e-04 eta: 2:01:50 time: 0.6665 data_time: 0.0293 memory: 23708 grad_norm: 5.7759 top1_acc: 0.2857 top5_acc: 0.8571 loss_cls: 1.4731 loss_aux: 0.9913 loss: 2.4645 2022/09/11 22:02:19 - mmengine - INFO - Saving checkpoint at 139 epochs 2022/09/11 22:02:45 - mmengine - INFO - Epoch(train) [140][20/940] lr: 4.0000e-04 eta: 2:01:38 time: 0.9846 data_time: 0.3098 memory: 23708 grad_norm: 5.4030 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3843 loss_aux: 0.9283 loss: 2.3126 2022/09/11 22:02:58 - mmengine - INFO - Epoch(train) [140][40/940] lr: 4.0000e-04 eta: 2:01:24 time: 0.6820 data_time: 0.0323 memory: 23708 grad_norm: 5.3853 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3364 loss_aux: 0.9047 loss: 2.2411 2022/09/11 22:03:12 - mmengine - INFO - Epoch(train) [140][60/940] lr: 4.0000e-04 eta: 2:01:10 time: 0.6756 data_time: 0.0382 memory: 23708 grad_norm: 5.5619 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5040 loss_aux: 0.9706 loss: 2.4746 2022/09/11 22:03:26 - mmengine - INFO - Epoch(train) [140][80/940] lr: 4.0000e-04 eta: 2:00:55 time: 0.6824 data_time: 0.0329 memory: 23708 grad_norm: 5.4992 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3683 loss_aux: 0.9453 loss: 2.3136 2022/09/11 22:03:39 - mmengine - INFO - Epoch(train) [140][100/940] lr: 4.0000e-04 eta: 2:00:41 time: 0.6877 data_time: 0.0383 memory: 23708 grad_norm: 5.5539 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4694 loss_aux: 0.9847 loss: 2.4542 2022/09/11 22:03:53 - mmengine - INFO - Epoch(train) [140][120/940] lr: 4.0000e-04 eta: 2:00:27 time: 0.6782 data_time: 0.0311 memory: 23708 grad_norm: 5.4995 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2288 loss_aux: 0.8608 loss: 2.0896 2022/09/11 22:04:07 - mmengine - INFO - Epoch(train) [140][140/940] lr: 4.0000e-04 eta: 2:00:12 time: 0.7082 data_time: 0.0441 memory: 23708 grad_norm: 5.4367 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3929 loss_aux: 0.9058 loss: 2.2987 2022/09/11 22:04:21 - mmengine - INFO - Epoch(train) [140][160/940] lr: 4.0000e-04 eta: 1:59:58 time: 0.6722 data_time: 0.0351 memory: 23708 grad_norm: 5.4710 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.5551 loss_aux: 1.0049 loss: 2.5600 2022/09/11 22:04:34 - mmengine - INFO - Epoch(train) [140][180/940] lr: 4.0000e-04 eta: 1:59:44 time: 0.6826 data_time: 0.0396 memory: 23708 grad_norm: 5.4610 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4028 loss_aux: 0.9527 loss: 2.3556 2022/09/11 22:04:48 - mmengine - INFO - Epoch(train) [140][200/940] lr: 4.0000e-04 eta: 1:59:29 time: 0.6876 data_time: 0.0335 memory: 23708 grad_norm: 5.4963 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.4030 loss_aux: 0.9197 loss: 2.3226 2022/09/11 22:05:02 - mmengine - INFO - Epoch(train) [140][220/940] lr: 4.0000e-04 eta: 1:59:15 time: 0.7096 data_time: 0.0434 memory: 23708 grad_norm: 5.4304 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2298 loss_aux: 0.8633 loss: 2.0931 2022/09/11 22:05:16 - mmengine - INFO - Epoch(train) [140][240/940] lr: 4.0000e-04 eta: 1:59:01 time: 0.6907 data_time: 0.0355 memory: 23708 grad_norm: 5.5058 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3174 loss_aux: 0.9209 loss: 2.2383 2022/09/11 22:05:30 - mmengine - INFO - Epoch(train) [140][260/940] lr: 4.0000e-04 eta: 1:58:47 time: 0.7085 data_time: 0.0363 memory: 23708 grad_norm: 5.4451 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.3954 loss_aux: 0.9407 loss: 2.3360 2022/09/11 22:05:44 - mmengine - INFO - Epoch(train) [140][280/940] lr: 4.0000e-04 eta: 1:58:33 time: 0.7036 data_time: 0.0440 memory: 23708 grad_norm: 5.3944 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3546 loss_aux: 0.9109 loss: 2.2655 2022/09/11 22:05:58 - mmengine - INFO - Epoch(train) [140][300/940] lr: 4.0000e-04 eta: 1:58:18 time: 0.6875 data_time: 0.0353 memory: 23708 grad_norm: 5.3489 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3998 loss_aux: 0.9206 loss: 2.3204 2022/09/11 22:06:12 - mmengine - INFO - Epoch(train) [140][320/940] lr: 4.0000e-04 eta: 1:58:04 time: 0.7014 data_time: 0.0387 memory: 23708 grad_norm: 5.4958 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4302 loss_aux: 0.9630 loss: 2.3932 2022/09/11 22:06:26 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 22:06:26 - mmengine - INFO - Epoch(train) [140][340/940] lr: 4.0000e-04 eta: 1:57:50 time: 0.7101 data_time: 0.0419 memory: 23708 grad_norm: 5.5729 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3238 loss_aux: 0.9344 loss: 2.2582 2022/09/11 22:06:40 - mmengine - INFO - Epoch(train) [140][360/940] lr: 4.0000e-04 eta: 1:57:36 time: 0.6978 data_time: 0.0342 memory: 23708 grad_norm: 5.4185 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.4044 loss_aux: 0.9222 loss: 2.3267 2022/09/11 22:06:55 - mmengine - INFO - Epoch(train) [140][380/940] lr: 4.0000e-04 eta: 1:57:22 time: 0.7154 data_time: 0.0330 memory: 23708 grad_norm: 5.3574 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4097 loss_aux: 0.9248 loss: 2.3346 2022/09/11 22:07:08 - mmengine - INFO - Epoch(train) [140][400/940] lr: 4.0000e-04 eta: 1:57:08 time: 0.6967 data_time: 0.0333 memory: 23708 grad_norm: 5.5052 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2399 loss_aux: 0.8526 loss: 2.0925 2022/09/11 22:07:23 - mmengine - INFO - Epoch(train) [140][420/940] lr: 4.0000e-04 eta: 1:56:53 time: 0.7079 data_time: 0.0461 memory: 23708 grad_norm: 5.5035 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4156 loss_aux: 0.9178 loss: 2.3334 2022/09/11 22:07:36 - mmengine - INFO - Epoch(train) [140][440/940] lr: 4.0000e-04 eta: 1:56:39 time: 0.6940 data_time: 0.0326 memory: 23708 grad_norm: 5.3825 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2704 loss_aux: 0.8870 loss: 2.1574 2022/09/11 22:07:51 - mmengine - INFO - Epoch(train) [140][460/940] lr: 4.0000e-04 eta: 1:56:25 time: 0.7109 data_time: 0.0363 memory: 23708 grad_norm: 5.4527 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2617 loss_aux: 0.8712 loss: 2.1330 2022/09/11 22:08:05 - mmengine - INFO - Epoch(train) [140][480/940] lr: 4.0000e-04 eta: 1:56:11 time: 0.7129 data_time: 0.0392 memory: 23708 grad_norm: 5.4654 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2588 loss_aux: 0.8671 loss: 2.1259 2022/09/11 22:08:19 - mmengine - INFO - Epoch(train) [140][500/940] lr: 4.0000e-04 eta: 1:55:57 time: 0.7010 data_time: 0.0357 memory: 23708 grad_norm: 5.5894 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3983 loss_aux: 0.9356 loss: 2.3339 2022/09/11 22:08:33 - mmengine - INFO - Epoch(train) [140][520/940] lr: 4.0000e-04 eta: 1:55:43 time: 0.6966 data_time: 0.0314 memory: 23708 grad_norm: 5.5542 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3684 loss_aux: 0.9344 loss: 2.3028 2022/09/11 22:08:47 - mmengine - INFO - Epoch(train) [140][540/940] lr: 4.0000e-04 eta: 1:55:29 time: 0.7171 data_time: 0.0379 memory: 23708 grad_norm: 5.5807 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2939 loss_aux: 0.9078 loss: 2.2017 2022/09/11 22:09:02 - mmengine - INFO - Epoch(train) [140][560/940] lr: 4.0000e-04 eta: 1:55:14 time: 0.7154 data_time: 0.0341 memory: 23708 grad_norm: 5.5609 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2629 loss_aux: 0.8864 loss: 2.1493 2022/09/11 22:09:16 - mmengine - INFO - Epoch(train) [140][580/940] lr: 4.0000e-04 eta: 1:55:00 time: 0.7125 data_time: 0.0445 memory: 23708 grad_norm: 5.4727 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4583 loss_aux: 0.9680 loss: 2.4263 2022/09/11 22:09:30 - mmengine - INFO - Epoch(train) [140][600/940] lr: 4.0000e-04 eta: 1:54:46 time: 0.7184 data_time: 0.0311 memory: 23708 grad_norm: 5.5028 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3520 loss_aux: 0.9100 loss: 2.2620 2022/09/11 22:09:44 - mmengine - INFO - Epoch(train) [140][620/940] lr: 4.0000e-04 eta: 1:54:32 time: 0.7060 data_time: 0.0352 memory: 23708 grad_norm: 5.5899 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3797 loss_aux: 0.9391 loss: 2.3189 2022/09/11 22:09:58 - mmengine - INFO - Epoch(train) [140][640/940] lr: 4.0000e-04 eta: 1:54:18 time: 0.7028 data_time: 0.0344 memory: 23708 grad_norm: 5.4480 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.4217 loss_aux: 0.9352 loss: 2.3569 2022/09/11 22:10:13 - mmengine - INFO - Epoch(train) [140][660/940] lr: 4.0000e-04 eta: 1:54:04 time: 0.7172 data_time: 0.0371 memory: 23708 grad_norm: 5.4476 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.2446 loss_aux: 0.8738 loss: 2.1184 2022/09/11 22:10:27 - mmengine - INFO - Epoch(train) [140][680/940] lr: 4.0000e-04 eta: 1:53:50 time: 0.6937 data_time: 0.0338 memory: 23708 grad_norm: 5.4703 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4599 loss_aux: 0.9199 loss: 2.3798 2022/09/11 22:10:41 - mmengine - INFO - Epoch(train) [140][700/940] lr: 4.0000e-04 eta: 1:53:36 time: 0.7269 data_time: 0.0405 memory: 23708 grad_norm: 5.4722 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3308 loss_aux: 0.9113 loss: 2.2420 2022/09/11 22:10:55 - mmengine - INFO - Epoch(train) [140][720/940] lr: 4.0000e-04 eta: 1:53:22 time: 0.7025 data_time: 0.0316 memory: 23708 grad_norm: 5.5254 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.4120 loss_aux: 0.9558 loss: 2.3678 2022/09/11 22:11:10 - mmengine - INFO - Epoch(train) [140][740/940] lr: 4.0000e-04 eta: 1:53:07 time: 0.7246 data_time: 0.0421 memory: 23708 grad_norm: 5.5459 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4350 loss_aux: 0.9551 loss: 2.3900 2022/09/11 22:11:24 - mmengine - INFO - Epoch(train) [140][760/940] lr: 4.0000e-04 eta: 1:52:53 time: 0.6939 data_time: 0.0298 memory: 23708 grad_norm: 5.4715 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2815 loss_aux: 0.8742 loss: 2.1556 2022/09/11 22:11:38 - mmengine - INFO - Epoch(train) [140][780/940] lr: 4.0000e-04 eta: 1:52:39 time: 0.7037 data_time: 0.0354 memory: 23708 grad_norm: 5.4336 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3256 loss_aux: 0.9054 loss: 2.2310 2022/09/11 22:11:52 - mmengine - INFO - Epoch(train) [140][800/940] lr: 4.0000e-04 eta: 1:52:25 time: 0.7024 data_time: 0.0369 memory: 23708 grad_norm: 5.5150 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4202 loss_aux: 0.9575 loss: 2.3776 2022/09/11 22:12:06 - mmengine - INFO - Epoch(train) [140][820/940] lr: 4.0000e-04 eta: 1:52:11 time: 0.7083 data_time: 0.0375 memory: 23708 grad_norm: 5.4609 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.4944 loss_aux: 1.0016 loss: 2.4960 2022/09/11 22:12:20 - mmengine - INFO - Epoch(train) [140][840/940] lr: 4.0000e-04 eta: 1:51:57 time: 0.6951 data_time: 0.0280 memory: 23708 grad_norm: 5.4619 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3170 loss_aux: 0.9224 loss: 2.2394 2022/09/11 22:12:34 - mmengine - INFO - Epoch(train) [140][860/940] lr: 4.0000e-04 eta: 1:51:42 time: 0.7143 data_time: 0.0393 memory: 23708 grad_norm: 5.5323 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3133 loss_aux: 0.8959 loss: 2.2091 2022/09/11 22:12:48 - mmengine - INFO - Epoch(train) [140][880/940] lr: 4.0000e-04 eta: 1:51:28 time: 0.7027 data_time: 0.0321 memory: 23708 grad_norm: 5.4722 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3484 loss_aux: 0.9086 loss: 2.2570 2022/09/11 22:13:03 - mmengine - INFO - Epoch(train) [140][900/940] lr: 4.0000e-04 eta: 1:51:14 time: 0.7197 data_time: 0.0422 memory: 23708 grad_norm: 5.5098 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4014 loss_aux: 0.9149 loss: 2.3163 2022/09/11 22:13:16 - mmengine - INFO - Epoch(train) [140][920/940] lr: 4.0000e-04 eta: 1:51:00 time: 0.6841 data_time: 0.0278 memory: 23708 grad_norm: 5.4953 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3820 loss_aux: 0.9029 loss: 2.2849 2022/09/11 22:13:30 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 22:13:30 - mmengine - INFO - Epoch(train) [140][940/940] lr: 4.0000e-04 eta: 1:50:46 time: 0.6693 data_time: 0.0365 memory: 23708 grad_norm: 5.8773 top1_acc: 0.4286 top5_acc: 0.8571 loss_cls: 1.3878 loss_aux: 0.9093 loss: 2.2971 2022/09/11 22:13:30 - mmengine - INFO - Saving checkpoint at 140 epochs 2022/09/11 22:13:40 - mmengine - INFO - Epoch(val) [140][20/310] eta: 0:01:02 time: 0.2147 data_time: 0.1352 memory: 2130 2022/09/11 22:13:43 - mmengine - INFO - Epoch(val) [140][40/310] eta: 0:00:37 time: 0.1406 data_time: 0.0630 memory: 2130 2022/09/11 22:13:46 - mmengine - INFO - Epoch(val) [140][60/310] eta: 0:00:39 time: 0.1568 data_time: 0.0776 memory: 2130 2022/09/11 22:13:49 - mmengine - INFO - Epoch(val) [140][80/310] eta: 0:00:38 time: 0.1666 data_time: 0.0882 memory: 2130 2022/09/11 22:13:52 - mmengine - INFO - Epoch(val) [140][100/310] eta: 0:00:31 time: 0.1484 data_time: 0.0672 memory: 2130 2022/09/11 22:13:55 - mmengine - INFO - Epoch(val) [140][120/310] eta: 0:00:31 time: 0.1633 data_time: 0.0821 memory: 2130 2022/09/11 22:13:59 - mmengine - INFO - Epoch(val) [140][140/310] eta: 0:00:29 time: 0.1747 data_time: 0.0962 memory: 2130 2022/09/11 22:14:02 - mmengine - INFO - Epoch(val) [140][160/310] eta: 0:00:21 time: 0.1412 data_time: 0.0611 memory: 2130 2022/09/11 22:14:05 - mmengine - INFO - Epoch(val) [140][180/310] eta: 0:00:22 time: 0.1755 data_time: 0.0945 memory: 2130 2022/09/11 22:14:08 - mmengine - INFO - Epoch(val) [140][200/310] eta: 0:00:15 time: 0.1391 data_time: 0.0603 memory: 2130 2022/09/11 22:14:11 - mmengine - INFO - Epoch(val) [140][220/310] eta: 0:00:13 time: 0.1542 data_time: 0.0745 memory: 2130 2022/09/11 22:14:14 - mmengine - INFO - Epoch(val) [140][240/310] eta: 0:00:10 time: 0.1534 data_time: 0.0759 memory: 2130 2022/09/11 22:14:17 - mmengine - INFO - Epoch(val) [140][260/310] eta: 0:00:07 time: 0.1514 data_time: 0.0742 memory: 2130 2022/09/11 22:14:20 - mmengine - INFO - Epoch(val) [140][280/310] eta: 0:00:03 time: 0.1312 data_time: 0.0556 memory: 2130 2022/09/11 22:14:22 - mmengine - INFO - Epoch(val) [140][300/310] eta: 0:00:01 time: 0.1160 data_time: 0.0430 memory: 2130 2022/09/11 22:14:25 - mmengine - INFO - Epoch(val) [140][310/310] acc/top1: 0.6656 acc/top5: 0.8668 acc/mean1: 0.6656 2022/09/11 22:14:44 - mmengine - INFO - Epoch(train) [141][20/940] lr: 4.0000e-04 eta: 1:50:33 time: 0.9900 data_time: 0.3051 memory: 23708 grad_norm: 5.4539 top1_acc: 0.4062 top5_acc: 0.7812 loss_cls: 1.4633 loss_aux: 0.9751 loss: 2.4385 2022/09/11 22:14:58 - mmengine - INFO - Epoch(train) [141][40/940] lr: 4.0000e-04 eta: 1:50:19 time: 0.6673 data_time: 0.0331 memory: 23708 grad_norm: 5.4014 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2829 loss_aux: 0.8732 loss: 2.1562 2022/09/11 22:15:12 - mmengine - INFO - Epoch(train) [141][60/940] lr: 4.0000e-04 eta: 1:50:05 time: 0.6862 data_time: 0.0315 memory: 23708 grad_norm: 5.4239 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4255 loss_aux: 0.9617 loss: 2.3872 2022/09/11 22:15:25 - mmengine - INFO - Epoch(train) [141][80/940] lr: 4.0000e-04 eta: 1:49:50 time: 0.6749 data_time: 0.0335 memory: 23708 grad_norm: 5.4005 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2249 loss_aux: 0.8761 loss: 2.1011 2022/09/11 22:15:39 - mmengine - INFO - Epoch(train) [141][100/940] lr: 4.0000e-04 eta: 1:49:36 time: 0.6841 data_time: 0.0396 memory: 23708 grad_norm: 5.2989 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1652 loss_aux: 0.8368 loss: 2.0020 2022/09/11 22:15:53 - mmengine - INFO - Epoch(train) [141][120/940] lr: 4.0000e-04 eta: 1:49:22 time: 0.6995 data_time: 0.0418 memory: 23708 grad_norm: 5.4597 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2148 loss_aux: 0.8714 loss: 2.0861 2022/09/11 22:16:06 - mmengine - INFO - Epoch(train) [141][140/940] lr: 4.0000e-04 eta: 1:49:07 time: 0.6781 data_time: 0.0377 memory: 23708 grad_norm: 5.5570 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3031 loss_aux: 0.9129 loss: 2.2160 2022/09/11 22:16:20 - mmengine - INFO - Epoch(train) [141][160/940] lr: 4.0000e-04 eta: 1:48:53 time: 0.6783 data_time: 0.0363 memory: 23708 grad_norm: 5.4587 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3246 loss_aux: 0.9299 loss: 2.2545 2022/09/11 22:16:33 - mmengine - INFO - Epoch(train) [141][180/940] lr: 4.0000e-04 eta: 1:48:39 time: 0.6801 data_time: 0.0357 memory: 23708 grad_norm: 5.4603 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3776 loss_aux: 0.9254 loss: 2.3030 2022/09/11 22:16:47 - mmengine - INFO - Epoch(train) [141][200/940] lr: 4.0000e-04 eta: 1:48:24 time: 0.6793 data_time: 0.0427 memory: 23708 grad_norm: 5.4559 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.2902 loss_aux: 0.8824 loss: 2.1726 2022/09/11 22:17:01 - mmengine - INFO - Epoch(train) [141][220/940] lr: 4.0000e-04 eta: 1:48:10 time: 0.6881 data_time: 0.0320 memory: 23708 grad_norm: 5.3867 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3957 loss_aux: 0.9594 loss: 2.3551 2022/09/11 22:17:14 - mmengine - INFO - Epoch(train) [141][240/940] lr: 4.0000e-04 eta: 1:47:56 time: 0.6709 data_time: 0.0369 memory: 23708 grad_norm: 5.4870 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3528 loss_aux: 0.9014 loss: 2.2543 2022/09/11 22:17:30 - mmengine - INFO - Epoch(train) [141][260/940] lr: 4.0000e-04 eta: 1:47:42 time: 0.7707 data_time: 0.0419 memory: 23708 grad_norm: 5.3856 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2735 loss_aux: 0.8797 loss: 2.1532 2022/09/11 22:17:44 - mmengine - INFO - Epoch(train) [141][280/940] lr: 4.0000e-04 eta: 1:47:28 time: 0.6979 data_time: 0.0409 memory: 23708 grad_norm: 5.5050 top1_acc: 0.5312 top5_acc: 0.6562 loss_cls: 1.4626 loss_aux: 0.9702 loss: 2.4328 2022/09/11 22:17:57 - mmengine - INFO - Epoch(train) [141][300/940] lr: 4.0000e-04 eta: 1:47:14 time: 0.6812 data_time: 0.0355 memory: 23708 grad_norm: 5.5675 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.3626 loss_aux: 0.9157 loss: 2.2783 2022/09/11 22:18:11 - mmengine - INFO - Epoch(train) [141][320/940] lr: 4.0000e-04 eta: 1:46:59 time: 0.6832 data_time: 0.0383 memory: 23708 grad_norm: 5.5696 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4398 loss_aux: 0.9574 loss: 2.3972 2022/09/11 22:18:25 - mmengine - INFO - Epoch(train) [141][340/940] lr: 4.0000e-04 eta: 1:46:45 time: 0.6887 data_time: 0.0397 memory: 23708 grad_norm: 5.4925 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4152 loss_aux: 0.9580 loss: 2.3732 2022/09/11 22:18:38 - mmengine - INFO - Epoch(train) [141][360/940] lr: 4.0000e-04 eta: 1:46:31 time: 0.6875 data_time: 0.0448 memory: 23708 grad_norm: 5.4905 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.4054 loss_aux: 0.9717 loss: 2.3771 2022/09/11 22:18:52 - mmengine - INFO - Epoch(train) [141][380/940] lr: 4.0000e-04 eta: 1:46:17 time: 0.7011 data_time: 0.0339 memory: 23708 grad_norm: 5.4750 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4564 loss_aux: 0.9852 loss: 2.4416 2022/09/11 22:19:06 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 22:19:06 - mmengine - INFO - Epoch(train) [141][400/940] lr: 4.0000e-04 eta: 1:46:02 time: 0.6797 data_time: 0.0428 memory: 23708 grad_norm: 5.5068 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.1618 loss_aux: 0.8405 loss: 2.0023 2022/09/11 22:19:20 - mmengine - INFO - Epoch(train) [141][420/940] lr: 4.0000e-04 eta: 1:45:48 time: 0.6844 data_time: 0.0399 memory: 23708 grad_norm: 5.3778 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.3448 loss_aux: 0.9307 loss: 2.2755 2022/09/11 22:19:34 - mmengine - INFO - Epoch(train) [141][440/940] lr: 4.0000e-04 eta: 1:45:34 time: 0.7024 data_time: 0.0445 memory: 23708 grad_norm: 5.5146 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4009 loss_aux: 0.9508 loss: 2.3518 2022/09/11 22:19:48 - mmengine - INFO - Epoch(train) [141][460/940] lr: 4.0000e-04 eta: 1:45:20 time: 0.7239 data_time: 0.0680 memory: 23708 grad_norm: 5.3961 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3263 loss_aux: 0.8866 loss: 2.2129 2022/09/11 22:20:03 - mmengine - INFO - Epoch(train) [141][480/940] lr: 4.0000e-04 eta: 1:45:06 time: 0.7166 data_time: 0.0315 memory: 23708 grad_norm: 5.4274 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.2649 loss_aux: 0.8633 loss: 2.1281 2022/09/11 22:20:16 - mmengine - INFO - Epoch(train) [141][500/940] lr: 4.0000e-04 eta: 1:44:51 time: 0.6910 data_time: 0.0381 memory: 23708 grad_norm: 5.4563 top1_acc: 0.5312 top5_acc: 0.8750 loss_cls: 1.3187 loss_aux: 0.8974 loss: 2.2161 2022/09/11 22:20:30 - mmengine - INFO - Epoch(train) [141][520/940] lr: 4.0000e-04 eta: 1:44:37 time: 0.6934 data_time: 0.0476 memory: 23708 grad_norm: 5.4483 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4516 loss_aux: 0.9799 loss: 2.4316 2022/09/11 22:20:44 - mmengine - INFO - Epoch(train) [141][540/940] lr: 4.0000e-04 eta: 1:44:23 time: 0.6906 data_time: 0.0354 memory: 23708 grad_norm: 5.4787 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.1795 loss_aux: 0.8322 loss: 2.0117 2022/09/11 22:20:58 - mmengine - INFO - Epoch(train) [141][560/940] lr: 4.0000e-04 eta: 1:44:09 time: 0.6832 data_time: 0.0396 memory: 23708 grad_norm: 5.5007 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.4637 loss_aux: 0.9406 loss: 2.4043 2022/09/11 22:21:12 - mmengine - INFO - Epoch(train) [141][580/940] lr: 4.0000e-04 eta: 1:43:54 time: 0.6910 data_time: 0.0375 memory: 23708 grad_norm: 5.4482 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3170 loss_aux: 0.8882 loss: 2.2052 2022/09/11 22:21:26 - mmengine - INFO - Epoch(train) [141][600/940] lr: 4.0000e-04 eta: 1:43:40 time: 0.6946 data_time: 0.0491 memory: 23708 grad_norm: 5.5530 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3359 loss_aux: 0.8957 loss: 2.2316 2022/09/11 22:21:39 - mmengine - INFO - Epoch(train) [141][620/940] lr: 4.0000e-04 eta: 1:43:26 time: 0.6872 data_time: 0.0311 memory: 23708 grad_norm: 5.5622 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3345 loss_aux: 0.9042 loss: 2.2387 2022/09/11 22:21:53 - mmengine - INFO - Epoch(train) [141][640/940] lr: 4.0000e-04 eta: 1:43:12 time: 0.6867 data_time: 0.0331 memory: 23708 grad_norm: 5.4781 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2304 loss_aux: 0.8628 loss: 2.0932 2022/09/11 22:22:07 - mmengine - INFO - Epoch(train) [141][660/940] lr: 4.0000e-04 eta: 1:42:57 time: 0.6866 data_time: 0.0403 memory: 23708 grad_norm: 5.4627 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3696 loss_aux: 0.9505 loss: 2.3201 2022/09/11 22:22:21 - mmengine - INFO - Epoch(train) [141][680/940] lr: 4.0000e-04 eta: 1:42:43 time: 0.7196 data_time: 0.0445 memory: 23708 grad_norm: 5.3405 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.3659 loss_aux: 0.9339 loss: 2.2998 2022/09/11 22:22:35 - mmengine - INFO - Epoch(train) [141][700/940] lr: 4.0000e-04 eta: 1:42:29 time: 0.6951 data_time: 0.0327 memory: 23708 grad_norm: 5.4856 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3294 loss_aux: 0.9028 loss: 2.2322 2022/09/11 22:22:49 - mmengine - INFO - Epoch(train) [141][720/940] lr: 4.0000e-04 eta: 1:42:15 time: 0.6810 data_time: 0.0344 memory: 23708 grad_norm: 5.5249 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.3893 loss_aux: 0.9448 loss: 2.3341 2022/09/11 22:23:03 - mmengine - INFO - Epoch(train) [141][740/940] lr: 4.0000e-04 eta: 1:42:01 time: 0.7230 data_time: 0.0474 memory: 23708 grad_norm: 5.4845 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3995 loss_aux: 0.9462 loss: 2.3457 2022/09/11 22:23:17 - mmengine - INFO - Epoch(train) [141][760/940] lr: 4.0000e-04 eta: 1:41:46 time: 0.6828 data_time: 0.0273 memory: 23708 grad_norm: 5.5875 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3245 loss_aux: 0.8957 loss: 2.2202 2022/09/11 22:23:31 - mmengine - INFO - Epoch(train) [141][780/940] lr: 4.0000e-04 eta: 1:41:32 time: 0.6923 data_time: 0.0309 memory: 23708 grad_norm: 5.5649 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.4011 loss_aux: 0.9407 loss: 2.3418 2022/09/11 22:23:44 - mmengine - INFO - Epoch(train) [141][800/940] lr: 4.0000e-04 eta: 1:41:18 time: 0.6846 data_time: 0.0361 memory: 23708 grad_norm: 5.4226 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3149 loss_aux: 0.8824 loss: 2.1974 2022/09/11 22:23:59 - mmengine - INFO - Epoch(train) [141][820/940] lr: 4.0000e-04 eta: 1:41:04 time: 0.7089 data_time: 0.0417 memory: 23708 grad_norm: 5.3056 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2712 loss_aux: 0.8863 loss: 2.1575 2022/09/11 22:24:12 - mmengine - INFO - Epoch(train) [141][840/940] lr: 4.0000e-04 eta: 1:40:50 time: 0.6821 data_time: 0.0292 memory: 23708 grad_norm: 5.5403 top1_acc: 0.5625 top5_acc: 0.7500 loss_cls: 1.3139 loss_aux: 0.8860 loss: 2.1999 2022/09/11 22:24:26 - mmengine - INFO - Epoch(train) [141][860/940] lr: 4.0000e-04 eta: 1:40:35 time: 0.6896 data_time: 0.0321 memory: 23708 grad_norm: 5.3806 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4450 loss_aux: 0.9808 loss: 2.4259 2022/09/11 22:24:40 - mmengine - INFO - Epoch(train) [141][880/940] lr: 4.0000e-04 eta: 1:40:21 time: 0.6799 data_time: 0.0342 memory: 23708 grad_norm: 5.5011 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4522 loss_aux: 0.9629 loss: 2.4151 2022/09/11 22:24:54 - mmengine - INFO - Epoch(train) [141][900/940] lr: 4.0000e-04 eta: 1:40:07 time: 0.7019 data_time: 0.0434 memory: 23708 grad_norm: 5.5385 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.4177 loss_aux: 0.9597 loss: 2.3774 2022/09/11 22:25:07 - mmengine - INFO - Epoch(train) [141][920/940] lr: 4.0000e-04 eta: 1:39:53 time: 0.6905 data_time: 0.0289 memory: 23708 grad_norm: 5.5264 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2888 loss_aux: 0.8941 loss: 2.1829 2022/09/11 22:25:20 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 22:25:20 - mmengine - INFO - Epoch(train) [141][940/940] lr: 4.0000e-04 eta: 1:39:38 time: 0.6440 data_time: 0.0240 memory: 23708 grad_norm: 5.7614 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.2944 loss_aux: 0.9097 loss: 2.2041 2022/09/11 22:25:20 - mmengine - INFO - Saving checkpoint at 141 epochs 2022/09/11 22:25:46 - mmengine - INFO - Epoch(train) [142][20/940] lr: 4.0000e-04 eta: 1:39:26 time: 0.9858 data_time: 0.3223 memory: 23708 grad_norm: 5.4122 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2207 loss_aux: 0.8565 loss: 2.0772 2022/09/11 22:25:59 - mmengine - INFO - Epoch(train) [142][40/940] lr: 4.0000e-04 eta: 1:39:11 time: 0.6589 data_time: 0.0264 memory: 23708 grad_norm: 5.4715 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3757 loss_aux: 0.9330 loss: 2.3087 2022/09/11 22:26:13 - mmengine - INFO - Epoch(train) [142][60/940] lr: 4.0000e-04 eta: 1:38:57 time: 0.6845 data_time: 0.0345 memory: 23708 grad_norm: 5.5379 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2778 loss_aux: 0.8701 loss: 2.1479 2022/09/11 22:26:26 - mmengine - INFO - Epoch(train) [142][80/940] lr: 4.0000e-04 eta: 1:38:43 time: 0.6811 data_time: 0.0367 memory: 23708 grad_norm: 5.4581 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2591 loss_aux: 0.8949 loss: 2.1540 2022/09/11 22:26:40 - mmengine - INFO - Epoch(train) [142][100/940] lr: 4.0000e-04 eta: 1:38:28 time: 0.6876 data_time: 0.0381 memory: 23708 grad_norm: 5.4297 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.2838 loss_aux: 0.8750 loss: 2.1588 2022/09/11 22:26:53 - mmengine - INFO - Epoch(train) [142][120/940] lr: 4.0000e-04 eta: 1:38:14 time: 0.6649 data_time: 0.0297 memory: 23708 grad_norm: 5.4143 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4204 loss_aux: 0.9244 loss: 2.3448 2022/09/11 22:27:07 - mmengine - INFO - Epoch(train) [142][140/940] lr: 4.0000e-04 eta: 1:38:00 time: 0.6721 data_time: 0.0318 memory: 23708 grad_norm: 5.5067 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3441 loss_aux: 0.9213 loss: 2.2654 2022/09/11 22:27:21 - mmengine - INFO - Epoch(train) [142][160/940] lr: 4.0000e-04 eta: 1:37:45 time: 0.6858 data_time: 0.0350 memory: 23708 grad_norm: 5.4765 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.2655 loss_aux: 0.8913 loss: 2.1569 2022/09/11 22:27:34 - mmengine - INFO - Epoch(train) [142][180/940] lr: 4.0000e-04 eta: 1:37:31 time: 0.6874 data_time: 0.0361 memory: 23708 grad_norm: 5.5108 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4843 loss_aux: 0.9598 loss: 2.4441 2022/09/11 22:27:48 - mmengine - INFO - Epoch(train) [142][200/940] lr: 4.0000e-04 eta: 1:37:17 time: 0.6785 data_time: 0.0408 memory: 23708 grad_norm: 5.5697 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.4030 loss_aux: 0.9564 loss: 2.3594 2022/09/11 22:28:01 - mmengine - INFO - Epoch(train) [142][220/940] lr: 4.0000e-04 eta: 1:37:03 time: 0.6673 data_time: 0.0341 memory: 23708 grad_norm: 5.5347 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3500 loss_aux: 0.9491 loss: 2.2991 2022/09/11 22:28:15 - mmengine - INFO - Epoch(train) [142][240/940] lr: 4.0000e-04 eta: 1:36:48 time: 0.6714 data_time: 0.0365 memory: 23708 grad_norm: 5.5172 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3498 loss_aux: 0.9209 loss: 2.2707 2022/09/11 22:28:29 - mmengine - INFO - Epoch(train) [142][260/940] lr: 4.0000e-04 eta: 1:36:34 time: 0.7084 data_time: 0.0379 memory: 23708 grad_norm: 5.4055 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3364 loss_aux: 0.9366 loss: 2.2730 2022/09/11 22:28:42 - mmengine - INFO - Epoch(train) [142][280/940] lr: 4.0000e-04 eta: 1:36:20 time: 0.6702 data_time: 0.0293 memory: 23708 grad_norm: 5.5297 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.4257 loss_aux: 0.9737 loss: 2.3995 2022/09/11 22:28:57 - mmengine - INFO - Epoch(train) [142][300/940] lr: 4.0000e-04 eta: 1:36:06 time: 0.7145 data_time: 0.0344 memory: 23708 grad_norm: 5.4710 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4551 loss_aux: 0.9722 loss: 2.4273 2022/09/11 22:29:10 - mmengine - INFO - Epoch(train) [142][320/940] lr: 4.0000e-04 eta: 1:35:51 time: 0.6783 data_time: 0.0379 memory: 23708 grad_norm: 5.5259 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4402 loss_aux: 0.9830 loss: 2.4233 2022/09/11 22:29:24 - mmengine - INFO - Epoch(train) [142][340/940] lr: 4.0000e-04 eta: 1:35:37 time: 0.6931 data_time: 0.0411 memory: 23708 grad_norm: 5.5377 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2896 loss_aux: 0.8813 loss: 2.1709 2022/09/11 22:29:37 - mmengine - INFO - Epoch(train) [142][360/940] lr: 4.0000e-04 eta: 1:35:23 time: 0.6714 data_time: 0.0304 memory: 23708 grad_norm: 5.4162 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4195 loss_aux: 0.9478 loss: 2.3674 2022/09/11 22:29:51 - mmengine - INFO - Epoch(train) [142][380/940] lr: 4.0000e-04 eta: 1:35:08 time: 0.6646 data_time: 0.0344 memory: 23708 grad_norm: 5.5697 top1_acc: 0.8750 top5_acc: 0.9062 loss_cls: 1.4269 loss_aux: 0.9681 loss: 2.3950 2022/09/11 22:30:04 - mmengine - INFO - Epoch(train) [142][400/940] lr: 4.0000e-04 eta: 1:34:54 time: 0.6684 data_time: 0.0395 memory: 23708 grad_norm: 5.4522 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.3265 loss_aux: 0.9047 loss: 2.2312 2022/09/11 22:30:18 - mmengine - INFO - Epoch(train) [142][420/940] lr: 4.0000e-04 eta: 1:34:40 time: 0.6838 data_time: 0.0496 memory: 23708 grad_norm: 5.4857 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2607 loss_aux: 0.8844 loss: 2.1451 2022/09/11 22:30:31 - mmengine - INFO - Epoch(train) [142][440/940] lr: 4.0000e-04 eta: 1:34:25 time: 0.6826 data_time: 0.0339 memory: 23708 grad_norm: 5.5120 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2933 loss_aux: 0.8982 loss: 2.1915 2022/09/11 22:30:45 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 22:30:45 - mmengine - INFO - Epoch(train) [142][460/940] lr: 4.0000e-04 eta: 1:34:11 time: 0.6837 data_time: 0.0430 memory: 23708 grad_norm: 5.4854 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3330 loss_aux: 0.8921 loss: 2.2251 2022/09/11 22:30:59 - mmengine - INFO - Epoch(train) [142][480/940] lr: 4.0000e-04 eta: 1:33:57 time: 0.6750 data_time: 0.0370 memory: 23708 grad_norm: 5.4259 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3262 loss_aux: 0.8773 loss: 2.2035 2022/09/11 22:31:12 - mmengine - INFO - Epoch(train) [142][500/940] lr: 4.0000e-04 eta: 1:33:43 time: 0.6875 data_time: 0.0506 memory: 23708 grad_norm: 5.4956 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.3518 loss_aux: 0.9314 loss: 2.2832 2022/09/11 22:31:26 - mmengine - INFO - Epoch(train) [142][520/940] lr: 4.0000e-04 eta: 1:33:28 time: 0.6792 data_time: 0.0340 memory: 23708 grad_norm: 5.5389 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3879 loss_aux: 0.9013 loss: 2.2891 2022/09/11 22:31:40 - mmengine - INFO - Epoch(train) [142][540/940] lr: 4.0000e-04 eta: 1:33:14 time: 0.6879 data_time: 0.0353 memory: 23708 grad_norm: 5.4503 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3687 loss_aux: 0.9255 loss: 2.2943 2022/09/11 22:31:53 - mmengine - INFO - Epoch(train) [142][560/940] lr: 4.0000e-04 eta: 1:33:00 time: 0.6762 data_time: 0.0400 memory: 23708 grad_norm: 5.5777 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3183 loss_aux: 0.9055 loss: 2.2238 2022/09/11 22:32:07 - mmengine - INFO - Epoch(train) [142][580/940] lr: 4.0000e-04 eta: 1:32:46 time: 0.6924 data_time: 0.0444 memory: 23708 grad_norm: 5.5040 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4042 loss_aux: 0.9382 loss: 2.3423 2022/09/11 22:32:21 - mmengine - INFO - Epoch(train) [142][600/940] lr: 4.0000e-04 eta: 1:32:31 time: 0.6781 data_time: 0.0361 memory: 23708 grad_norm: 5.5690 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.4697 loss_aux: 0.9731 loss: 2.4427 2022/09/11 22:32:34 - mmengine - INFO - Epoch(train) [142][620/940] lr: 4.0000e-04 eta: 1:32:17 time: 0.6881 data_time: 0.0356 memory: 23708 grad_norm: 5.5067 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4209 loss_aux: 0.9474 loss: 2.3682 2022/09/11 22:32:48 - mmengine - INFO - Epoch(train) [142][640/940] lr: 4.0000e-04 eta: 1:32:03 time: 0.6866 data_time: 0.0421 memory: 23708 grad_norm: 5.5234 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4488 loss_aux: 0.9665 loss: 2.4153 2022/09/11 22:33:02 - mmengine - INFO - Epoch(train) [142][660/940] lr: 4.0000e-04 eta: 1:31:49 time: 0.7087 data_time: 0.0423 memory: 23708 grad_norm: 5.5794 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3795 loss_aux: 0.9410 loss: 2.3205 2022/09/11 22:33:16 - mmengine - INFO - Epoch(train) [142][680/940] lr: 4.0000e-04 eta: 1:31:35 time: 0.6873 data_time: 0.0403 memory: 23708 grad_norm: 5.5290 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3086 loss_aux: 0.8901 loss: 2.1987 2022/09/11 22:33:30 - mmengine - INFO - Epoch(train) [142][700/940] lr: 4.0000e-04 eta: 1:31:20 time: 0.6997 data_time: 0.0330 memory: 23708 grad_norm: 5.5043 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3042 loss_aux: 0.9056 loss: 2.2097 2022/09/11 22:33:44 - mmengine - INFO - Epoch(train) [142][720/940] lr: 4.0000e-04 eta: 1:31:06 time: 0.6902 data_time: 0.0360 memory: 23708 grad_norm: 5.5350 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3050 loss_aux: 0.8572 loss: 2.1622 2022/09/11 22:33:58 - mmengine - INFO - Epoch(train) [142][740/940] lr: 4.0000e-04 eta: 1:30:52 time: 0.6991 data_time: 0.0412 memory: 23708 grad_norm: 5.5564 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4217 loss_aux: 0.9860 loss: 2.4077 2022/09/11 22:34:11 - mmengine - INFO - Epoch(train) [142][760/940] lr: 4.0000e-04 eta: 1:30:38 time: 0.6764 data_time: 0.0306 memory: 23708 grad_norm: 5.5138 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.2041 loss_aux: 0.8774 loss: 2.0815 2022/09/11 22:34:25 - mmengine - INFO - Epoch(train) [142][780/940] lr: 4.0000e-04 eta: 1:30:24 time: 0.6955 data_time: 0.0350 memory: 23708 grad_norm: 5.5169 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.3094 loss_aux: 0.9086 loss: 2.2180 2022/09/11 22:34:39 - mmengine - INFO - Epoch(train) [142][800/940] lr: 4.0000e-04 eta: 1:30:09 time: 0.6886 data_time: 0.0359 memory: 23708 grad_norm: 5.5431 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.3930 loss_aux: 0.9510 loss: 2.3439 2022/09/11 22:34:53 - mmengine - INFO - Epoch(train) [142][820/940] lr: 4.0000e-04 eta: 1:29:55 time: 0.6978 data_time: 0.0438 memory: 23708 grad_norm: 5.5281 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3760 loss_aux: 0.9287 loss: 2.3046 2022/09/11 22:35:07 - mmengine - INFO - Epoch(train) [142][840/940] lr: 4.0000e-04 eta: 1:29:41 time: 0.6962 data_time: 0.0352 memory: 23708 grad_norm: 5.5400 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3243 loss_aux: 0.9023 loss: 2.2266 2022/09/11 22:35:21 - mmengine - INFO - Epoch(train) [142][860/940] lr: 4.0000e-04 eta: 1:29:27 time: 0.7057 data_time: 0.0551 memory: 23708 grad_norm: 5.4981 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.3725 loss_aux: 0.9364 loss: 2.3090 2022/09/11 22:35:35 - mmengine - INFO - Epoch(train) [142][880/940] lr: 4.0000e-04 eta: 1:29:13 time: 0.6969 data_time: 0.0359 memory: 23708 grad_norm: 5.4706 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.4109 loss_aux: 0.9361 loss: 2.3470 2022/09/11 22:35:49 - mmengine - INFO - Epoch(train) [142][900/940] lr: 4.0000e-04 eta: 1:28:59 time: 0.7141 data_time: 0.0382 memory: 23708 grad_norm: 5.4636 top1_acc: 0.5000 top5_acc: 0.8438 loss_cls: 1.3263 loss_aux: 0.9218 loss: 2.2481 2022/09/11 22:36:03 - mmengine - INFO - Epoch(train) [142][920/940] lr: 4.0000e-04 eta: 1:28:44 time: 0.6694 data_time: 0.0266 memory: 23708 grad_norm: 5.5875 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3622 loss_aux: 0.9672 loss: 2.3294 2022/09/11 22:36:16 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 22:36:16 - mmengine - INFO - Epoch(train) [142][940/940] lr: 4.0000e-04 eta: 1:28:30 time: 0.6620 data_time: 0.0295 memory: 23708 grad_norm: 5.8201 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.4100 loss_aux: 0.9758 loss: 2.3858 2022/09/11 22:36:16 - mmengine - INFO - Saving checkpoint at 142 epochs 2022/09/11 22:36:41 - mmengine - INFO - Epoch(train) [143][20/940] lr: 4.0000e-04 eta: 1:28:17 time: 0.9262 data_time: 0.2654 memory: 23708 grad_norm: 5.6313 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3374 loss_aux: 0.9143 loss: 2.2517 2022/09/11 22:36:55 - mmengine - INFO - Epoch(train) [143][40/940] lr: 4.0000e-04 eta: 1:28:03 time: 0.6772 data_time: 0.0410 memory: 23708 grad_norm: 5.4944 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3955 loss_aux: 0.9406 loss: 2.3362 2022/09/11 22:37:08 - mmengine - INFO - Epoch(train) [143][60/940] lr: 4.0000e-04 eta: 1:27:48 time: 0.6886 data_time: 0.0380 memory: 23708 grad_norm: 5.3958 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3159 loss_aux: 0.8860 loss: 2.2019 2022/09/11 22:37:22 - mmengine - INFO - Epoch(train) [143][80/940] lr: 4.0000e-04 eta: 1:27:34 time: 0.6845 data_time: 0.0345 memory: 23708 grad_norm: 5.5030 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.4619 loss_aux: 0.9577 loss: 2.4197 2022/09/11 22:37:36 - mmengine - INFO - Epoch(train) [143][100/940] lr: 4.0000e-04 eta: 1:27:20 time: 0.6978 data_time: 0.0399 memory: 23708 grad_norm: 5.5359 top1_acc: 0.4375 top5_acc: 0.7500 loss_cls: 1.4370 loss_aux: 0.9770 loss: 2.4140 2022/09/11 22:37:50 - mmengine - INFO - Epoch(train) [143][120/940] lr: 4.0000e-04 eta: 1:27:06 time: 0.6879 data_time: 0.0353 memory: 23708 grad_norm: 5.5049 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.1761 loss_aux: 0.8263 loss: 2.0024 2022/09/11 22:38:04 - mmengine - INFO - Epoch(train) [143][140/940] lr: 4.0000e-04 eta: 1:26:52 time: 0.7144 data_time: 0.0391 memory: 23708 grad_norm: 5.5383 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3764 loss_aux: 0.9420 loss: 2.3184 2022/09/11 22:38:18 - mmengine - INFO - Epoch(train) [143][160/940] lr: 4.0000e-04 eta: 1:26:37 time: 0.6810 data_time: 0.0321 memory: 23708 grad_norm: 5.4817 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3451 loss_aux: 0.9237 loss: 2.2687 2022/09/11 22:38:32 - mmengine - INFO - Epoch(train) [143][180/940] lr: 4.0000e-04 eta: 1:26:23 time: 0.7156 data_time: 0.0403 memory: 23708 grad_norm: 5.4727 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3162 loss_aux: 0.8896 loss: 2.2059 2022/09/11 22:38:46 - mmengine - INFO - Epoch(train) [143][200/940] lr: 4.0000e-04 eta: 1:26:09 time: 0.6909 data_time: 0.0342 memory: 23708 grad_norm: 5.5197 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.2739 loss_aux: 0.8596 loss: 2.1336 2022/09/11 22:39:00 - mmengine - INFO - Epoch(train) [143][220/940] lr: 4.0000e-04 eta: 1:25:55 time: 0.6882 data_time: 0.0438 memory: 23708 grad_norm: 5.6310 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.3715 loss_aux: 0.9611 loss: 2.3327 2022/09/11 22:39:14 - mmengine - INFO - Epoch(train) [143][240/940] lr: 4.0000e-04 eta: 1:25:41 time: 0.6984 data_time: 0.0334 memory: 23708 grad_norm: 5.5713 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2658 loss_aux: 0.9124 loss: 2.1782 2022/09/11 22:39:28 - mmengine - INFO - Epoch(train) [143][260/940] lr: 4.0000e-04 eta: 1:25:27 time: 0.7065 data_time: 0.0412 memory: 23708 grad_norm: 5.5462 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2623 loss_aux: 0.8833 loss: 2.1456 2022/09/11 22:39:42 - mmengine - INFO - Epoch(train) [143][280/940] lr: 4.0000e-04 eta: 1:25:12 time: 0.6920 data_time: 0.0401 memory: 23708 grad_norm: 5.5838 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3974 loss_aux: 0.9349 loss: 2.3322 2022/09/11 22:39:55 - mmengine - INFO - Epoch(train) [143][300/940] lr: 4.0000e-04 eta: 1:24:58 time: 0.6819 data_time: 0.0366 memory: 23708 grad_norm: 5.4897 top1_acc: 0.7812 top5_acc: 0.8438 loss_cls: 1.1973 loss_aux: 0.8291 loss: 2.0264 2022/09/11 22:40:09 - mmengine - INFO - Epoch(train) [143][320/940] lr: 4.0000e-04 eta: 1:24:44 time: 0.6920 data_time: 0.0335 memory: 23708 grad_norm: 5.5756 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3492 loss_aux: 0.9361 loss: 2.2853 2022/09/11 22:40:23 - mmengine - INFO - Epoch(train) [143][340/940] lr: 4.0000e-04 eta: 1:24:30 time: 0.6935 data_time: 0.0382 memory: 23708 grad_norm: 5.5578 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4642 loss_aux: 0.9102 loss: 2.3744 2022/09/11 22:40:37 - mmengine - INFO - Epoch(train) [143][360/940] lr: 4.0000e-04 eta: 1:24:16 time: 0.6899 data_time: 0.0361 memory: 23708 grad_norm: 5.5926 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3776 loss_aux: 0.9199 loss: 2.2974 2022/09/11 22:40:51 - mmengine - INFO - Epoch(train) [143][380/940] lr: 4.0000e-04 eta: 1:24:01 time: 0.6903 data_time: 0.0379 memory: 23708 grad_norm: 5.5189 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3230 loss_aux: 0.8838 loss: 2.2068 2022/09/11 22:41:05 - mmengine - INFO - Epoch(train) [143][400/940] lr: 4.0000e-04 eta: 1:23:47 time: 0.6942 data_time: 0.0429 memory: 23708 grad_norm: 5.5343 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2535 loss_aux: 0.8504 loss: 2.1039 2022/09/11 22:41:19 - mmengine - INFO - Epoch(train) [143][420/940] lr: 4.0000e-04 eta: 1:23:33 time: 0.7119 data_time: 0.0380 memory: 23708 grad_norm: 5.4772 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3622 loss_aux: 0.9287 loss: 2.2910 2022/09/11 22:41:33 - mmengine - INFO - Epoch(train) [143][440/940] lr: 4.0000e-04 eta: 1:23:19 time: 0.6909 data_time: 0.0399 memory: 23708 grad_norm: 5.4429 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.4547 loss_aux: 0.9867 loss: 2.4414 2022/09/11 22:41:46 - mmengine - INFO - Epoch(train) [143][460/940] lr: 4.0000e-04 eta: 1:23:05 time: 0.6847 data_time: 0.0386 memory: 23708 grad_norm: 5.5747 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.4011 loss_aux: 0.9408 loss: 2.3419 2022/09/11 22:42:00 - mmengine - INFO - Epoch(train) [143][480/940] lr: 4.0000e-04 eta: 1:22:51 time: 0.6889 data_time: 0.0342 memory: 23708 grad_norm: 5.4705 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.2106 loss_aux: 0.8514 loss: 2.0619 2022/09/11 22:42:14 - mmengine - INFO - Epoch(train) [143][500/940] lr: 4.0000e-04 eta: 1:22:36 time: 0.7154 data_time: 0.0415 memory: 23708 grad_norm: 5.4962 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2950 loss_aux: 0.9299 loss: 2.2249 2022/09/11 22:42:28 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 22:42:28 - mmengine - INFO - Epoch(train) [143][520/940] lr: 4.0000e-04 eta: 1:22:22 time: 0.6832 data_time: 0.0333 memory: 23708 grad_norm: 5.4958 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3435 loss_aux: 0.9519 loss: 2.2954 2022/09/11 22:42:42 - mmengine - INFO - Epoch(train) [143][540/940] lr: 4.0000e-04 eta: 1:22:08 time: 0.6956 data_time: 0.0390 memory: 23708 grad_norm: 5.5328 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3840 loss_aux: 0.9497 loss: 2.3337 2022/09/11 22:42:56 - mmengine - INFO - Epoch(train) [143][560/940] lr: 4.0000e-04 eta: 1:21:54 time: 0.7060 data_time: 0.0353 memory: 23708 grad_norm: 5.4835 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3500 loss_aux: 0.9495 loss: 2.2995 2022/09/11 22:43:12 - mmengine - INFO - Epoch(train) [143][580/940] lr: 4.0000e-04 eta: 1:21:40 time: 0.8200 data_time: 0.0417 memory: 23708 grad_norm: 5.4903 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2505 loss_aux: 0.8996 loss: 2.1502 2022/09/11 22:43:26 - mmengine - INFO - Epoch(train) [143][600/940] lr: 4.0000e-04 eta: 1:21:26 time: 0.6890 data_time: 0.0379 memory: 23708 grad_norm: 5.5966 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3073 loss_aux: 0.9009 loss: 2.2082 2022/09/11 22:43:40 - mmengine - INFO - Epoch(train) [143][620/940] lr: 4.0000e-04 eta: 1:21:12 time: 0.6968 data_time: 0.0364 memory: 23708 grad_norm: 5.6138 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.4126 loss_aux: 0.9657 loss: 2.3782 2022/09/11 22:43:54 - mmengine - INFO - Epoch(train) [143][640/940] lr: 4.0000e-04 eta: 1:20:58 time: 0.7127 data_time: 0.0495 memory: 23708 grad_norm: 5.4368 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3982 loss_aux: 0.9314 loss: 2.3295 2022/09/11 22:44:09 - mmengine - INFO - Epoch(train) [143][660/940] lr: 4.0000e-04 eta: 1:20:44 time: 0.7109 data_time: 0.0423 memory: 23708 grad_norm: 5.5092 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2233 loss_aux: 0.8680 loss: 2.0913 2022/09/11 22:44:23 - mmengine - INFO - Epoch(train) [143][680/940] lr: 4.0000e-04 eta: 1:20:30 time: 0.7130 data_time: 0.0357 memory: 23708 grad_norm: 5.4938 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3970 loss_aux: 0.9726 loss: 2.3696 2022/09/11 22:44:37 - mmengine - INFO - Epoch(train) [143][700/940] lr: 4.0000e-04 eta: 1:20:16 time: 0.7099 data_time: 0.0390 memory: 23708 grad_norm: 5.4957 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1966 loss_aux: 0.8665 loss: 2.0630 2022/09/11 22:44:51 - mmengine - INFO - Epoch(train) [143][720/940] lr: 4.0000e-04 eta: 1:20:02 time: 0.7113 data_time: 0.0350 memory: 23708 grad_norm: 5.5368 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3373 loss_aux: 0.9419 loss: 2.2792 2022/09/11 22:45:06 - mmengine - INFO - Epoch(train) [143][740/940] lr: 4.0000e-04 eta: 1:19:47 time: 0.7205 data_time: 0.0415 memory: 23708 grad_norm: 5.5086 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4251 loss_aux: 0.9558 loss: 2.3809 2022/09/11 22:45:20 - mmengine - INFO - Epoch(train) [143][760/940] lr: 4.0000e-04 eta: 1:19:33 time: 0.7106 data_time: 0.0350 memory: 23708 grad_norm: 5.6582 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4407 loss_aux: 0.9638 loss: 2.4044 2022/09/11 22:45:34 - mmengine - INFO - Epoch(train) [143][780/940] lr: 4.0000e-04 eta: 1:19:19 time: 0.7193 data_time: 0.0396 memory: 23708 grad_norm: 5.5893 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3781 loss_aux: 0.9155 loss: 2.2936 2022/09/11 22:45:48 - mmengine - INFO - Epoch(train) [143][800/940] lr: 4.0000e-04 eta: 1:19:05 time: 0.7029 data_time: 0.0367 memory: 23708 grad_norm: 5.5418 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3711 loss_aux: 0.9252 loss: 2.2964 2022/09/11 22:46:03 - mmengine - INFO - Epoch(train) [143][820/940] lr: 4.0000e-04 eta: 1:18:51 time: 0.7231 data_time: 0.0364 memory: 23708 grad_norm: 5.4443 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2839 loss_aux: 0.9088 loss: 2.1927 2022/09/11 22:46:17 - mmengine - INFO - Epoch(train) [143][840/940] lr: 4.0000e-04 eta: 1:18:37 time: 0.6990 data_time: 0.0368 memory: 23708 grad_norm: 5.5716 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4512 loss_aux: 0.9639 loss: 2.4151 2022/09/11 22:46:31 - mmengine - INFO - Epoch(train) [143][860/940] lr: 4.0000e-04 eta: 1:18:23 time: 0.6948 data_time: 0.0338 memory: 23708 grad_norm: 5.4984 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3183 loss_aux: 0.9102 loss: 2.2285 2022/09/11 22:46:45 - mmengine - INFO - Epoch(train) [143][880/940] lr: 4.0000e-04 eta: 1:18:09 time: 0.7086 data_time: 0.0350 memory: 23708 grad_norm: 5.5852 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4439 loss_aux: 0.9515 loss: 2.3955 2022/09/11 22:46:59 - mmengine - INFO - Epoch(train) [143][900/940] lr: 4.0000e-04 eta: 1:17:55 time: 0.7160 data_time: 0.0391 memory: 23708 grad_norm: 5.5636 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3424 loss_aux: 0.9055 loss: 2.2480 2022/09/11 22:47:13 - mmengine - INFO - Epoch(train) [143][920/940] lr: 4.0000e-04 eta: 1:17:40 time: 0.6839 data_time: 0.0277 memory: 23708 grad_norm: 5.5668 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4288 loss_aux: 0.9442 loss: 2.3730 2022/09/11 22:47:27 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 22:47:27 - mmengine - INFO - Epoch(train) [143][940/940] lr: 4.0000e-04 eta: 1:17:26 time: 0.6898 data_time: 0.0346 memory: 23708 grad_norm: 5.7572 top1_acc: 0.7143 top5_acc: 0.7143 loss_cls: 1.3023 loss_aux: 0.8985 loss: 2.2008 2022/09/11 22:47:27 - mmengine - INFO - Saving checkpoint at 143 epochs 2022/09/11 22:47:52 - mmengine - INFO - Epoch(train) [144][20/940] lr: 4.0000e-04 eta: 1:17:13 time: 0.9205 data_time: 0.2739 memory: 23708 grad_norm: 5.5221 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3158 loss_aux: 0.8788 loss: 2.1946 2022/09/11 22:48:05 - mmengine - INFO - Epoch(train) [144][40/940] lr: 4.0000e-04 eta: 1:16:59 time: 0.6684 data_time: 0.0318 memory: 23708 grad_norm: 5.5068 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2390 loss_aux: 0.8792 loss: 2.1182 2022/09/11 22:48:19 - mmengine - INFO - Epoch(train) [144][60/940] lr: 4.0000e-04 eta: 1:16:44 time: 0.6698 data_time: 0.0321 memory: 23708 grad_norm: 5.4833 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.2926 loss_aux: 0.8800 loss: 2.1726 2022/09/11 22:48:32 - mmengine - INFO - Epoch(train) [144][80/940] lr: 4.0000e-04 eta: 1:16:30 time: 0.6721 data_time: 0.0352 memory: 23708 grad_norm: 5.4723 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2567 loss_aux: 0.8757 loss: 2.1325 2022/09/11 22:48:46 - mmengine - INFO - Epoch(train) [144][100/940] lr: 4.0000e-04 eta: 1:16:16 time: 0.6939 data_time: 0.0378 memory: 23708 grad_norm: 5.5204 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3647 loss_aux: 0.8936 loss: 2.2583 2022/09/11 22:49:00 - mmengine - INFO - Epoch(train) [144][120/940] lr: 4.0000e-04 eta: 1:16:02 time: 0.6845 data_time: 0.0401 memory: 23708 grad_norm: 5.5391 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3350 loss_aux: 0.9175 loss: 2.2525 2022/09/11 22:49:13 - mmengine - INFO - Epoch(train) [144][140/940] lr: 4.0000e-04 eta: 1:15:47 time: 0.6687 data_time: 0.0381 memory: 23708 grad_norm: 5.4806 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3571 loss_aux: 0.9033 loss: 2.2603 2022/09/11 22:49:27 - mmengine - INFO - Epoch(train) [144][160/940] lr: 4.0000e-04 eta: 1:15:33 time: 0.6801 data_time: 0.0336 memory: 23708 grad_norm: 5.5028 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3132 loss_aux: 0.9066 loss: 2.2198 2022/09/11 22:49:40 - mmengine - INFO - Epoch(train) [144][180/940] lr: 4.0000e-04 eta: 1:15:19 time: 0.6892 data_time: 0.0395 memory: 23708 grad_norm: 5.4699 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.3239 loss_aux: 0.9365 loss: 2.2604 2022/09/11 22:49:54 - mmengine - INFO - Epoch(train) [144][200/940] lr: 4.0000e-04 eta: 1:15:05 time: 0.6895 data_time: 0.0342 memory: 23708 grad_norm: 5.6260 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4512 loss_aux: 1.0145 loss: 2.4657 2022/09/11 22:50:08 - mmengine - INFO - Epoch(train) [144][220/940] lr: 4.0000e-04 eta: 1:14:51 time: 0.6774 data_time: 0.0344 memory: 23708 grad_norm: 5.4215 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3041 loss_aux: 0.8469 loss: 2.1510 2022/09/11 22:50:21 - mmengine - INFO - Epoch(train) [144][240/940] lr: 4.0000e-04 eta: 1:14:36 time: 0.6734 data_time: 0.0317 memory: 23708 grad_norm: 5.5204 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3542 loss_aux: 0.9322 loss: 2.2864 2022/09/11 22:50:35 - mmengine - INFO - Epoch(train) [144][260/940] lr: 4.0000e-04 eta: 1:14:22 time: 0.7019 data_time: 0.0534 memory: 23708 grad_norm: 5.4268 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.1353 loss_aux: 0.8268 loss: 1.9621 2022/09/11 22:50:49 - mmengine - INFO - Epoch(train) [144][280/940] lr: 4.0000e-04 eta: 1:14:08 time: 0.6838 data_time: 0.0331 memory: 23708 grad_norm: 5.6187 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.4099 loss_aux: 0.9126 loss: 2.3225 2022/09/11 22:51:03 - mmengine - INFO - Epoch(train) [144][300/940] lr: 4.0000e-04 eta: 1:13:54 time: 0.6992 data_time: 0.0367 memory: 23708 grad_norm: 5.5464 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.3240 loss_aux: 0.8903 loss: 2.2143 2022/09/11 22:51:16 - mmengine - INFO - Epoch(train) [144][320/940] lr: 4.0000e-04 eta: 1:13:40 time: 0.6752 data_time: 0.0349 memory: 23708 grad_norm: 5.4795 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3925 loss_aux: 0.9636 loss: 2.3560 2022/09/11 22:51:30 - mmengine - INFO - Epoch(train) [144][340/940] lr: 4.0000e-04 eta: 1:13:25 time: 0.6801 data_time: 0.0393 memory: 23708 grad_norm: 5.5524 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2912 loss_aux: 0.8808 loss: 2.1720 2022/09/11 22:51:44 - mmengine - INFO - Epoch(train) [144][360/940] lr: 4.0000e-04 eta: 1:13:11 time: 0.6901 data_time: 0.0389 memory: 23708 grad_norm: 5.4913 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.4446 loss_aux: 0.9586 loss: 2.4032 2022/09/11 22:51:58 - mmengine - INFO - Epoch(train) [144][380/940] lr: 4.0000e-04 eta: 1:12:57 time: 0.6931 data_time: 0.0344 memory: 23708 grad_norm: 5.5053 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2835 loss_aux: 0.8780 loss: 2.1614 2022/09/11 22:52:11 - mmengine - INFO - Epoch(train) [144][400/940] lr: 4.0000e-04 eta: 1:12:43 time: 0.6851 data_time: 0.0434 memory: 23708 grad_norm: 5.5785 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3771 loss_aux: 0.9183 loss: 2.2953 2022/09/11 22:52:26 - mmengine - INFO - Epoch(train) [144][420/940] lr: 4.0000e-04 eta: 1:12:29 time: 0.7107 data_time: 0.0490 memory: 23708 grad_norm: 5.5553 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2293 loss_aux: 0.8653 loss: 2.0946 2022/09/11 22:52:39 - mmengine - INFO - Epoch(train) [144][440/940] lr: 4.0000e-04 eta: 1:12:14 time: 0.6817 data_time: 0.0339 memory: 23708 grad_norm: 5.5672 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4468 loss_aux: 0.9622 loss: 2.4089 2022/09/11 22:52:53 - mmengine - INFO - Epoch(train) [144][460/940] lr: 4.0000e-04 eta: 1:12:00 time: 0.7107 data_time: 0.0365 memory: 23708 grad_norm: 5.5041 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4252 loss_aux: 0.9567 loss: 2.3819 2022/09/11 22:53:07 - mmengine - INFO - Epoch(train) [144][480/940] lr: 4.0000e-04 eta: 1:11:46 time: 0.6883 data_time: 0.0378 memory: 23708 grad_norm: 5.5422 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.1949 loss_aux: 0.8163 loss: 2.0112 2022/09/11 22:53:21 - mmengine - INFO - Epoch(train) [144][500/940] lr: 4.0000e-04 eta: 1:11:32 time: 0.6882 data_time: 0.0383 memory: 23708 grad_norm: 5.6184 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.3870 loss_aux: 0.9352 loss: 2.3223 2022/09/11 22:53:35 - mmengine - INFO - Epoch(train) [144][520/940] lr: 4.0000e-04 eta: 1:11:18 time: 0.6958 data_time: 0.0419 memory: 23708 grad_norm: 5.4751 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.2127 loss_aux: 0.8671 loss: 2.0798 2022/09/11 22:53:49 - mmengine - INFO - Epoch(train) [144][540/940] lr: 4.0000e-04 eta: 1:11:04 time: 0.6893 data_time: 0.0369 memory: 23708 grad_norm: 5.5585 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3607 loss_aux: 0.9315 loss: 2.2921 2022/09/11 22:54:02 - mmengine - INFO - Epoch(train) [144][560/940] lr: 4.0000e-04 eta: 1:10:49 time: 0.6821 data_time: 0.0360 memory: 23708 grad_norm: 5.5456 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3946 loss_aux: 0.9169 loss: 2.3115 2022/09/11 22:54:17 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 22:54:17 - mmengine - INFO - Epoch(train) [144][580/940] lr: 4.0000e-04 eta: 1:10:35 time: 0.7134 data_time: 0.0421 memory: 23708 grad_norm: 5.4139 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2140 loss_aux: 0.8557 loss: 2.0696 2022/09/11 22:54:30 - mmengine - INFO - Epoch(train) [144][600/940] lr: 4.0000e-04 eta: 1:10:21 time: 0.6822 data_time: 0.0371 memory: 23708 grad_norm: 5.4115 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.2702 loss_aux: 0.8937 loss: 2.1639 2022/09/11 22:54:44 - mmengine - INFO - Epoch(train) [144][620/940] lr: 4.0000e-04 eta: 1:10:07 time: 0.6920 data_time: 0.0383 memory: 23708 grad_norm: 5.4893 top1_acc: 0.5625 top5_acc: 0.8750 loss_cls: 1.2361 loss_aux: 0.8641 loss: 2.1002 2022/09/11 22:54:58 - mmengine - INFO - Epoch(train) [144][640/940] lr: 4.0000e-04 eta: 1:09:53 time: 0.6854 data_time: 0.0472 memory: 23708 grad_norm: 5.4977 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2750 loss_aux: 0.9231 loss: 2.1981 2022/09/11 22:55:12 - mmengine - INFO - Epoch(train) [144][660/940] lr: 4.0000e-04 eta: 1:09:38 time: 0.6914 data_time: 0.0292 memory: 23708 grad_norm: 5.6137 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3210 loss_aux: 0.8993 loss: 2.2203 2022/09/11 22:55:26 - mmengine - INFO - Epoch(train) [144][680/940] lr: 4.0000e-04 eta: 1:09:24 time: 0.6963 data_time: 0.0279 memory: 23708 grad_norm: 5.4081 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3015 loss_aux: 0.9264 loss: 2.2279 2022/09/11 22:55:40 - mmengine - INFO - Epoch(train) [144][700/940] lr: 4.0000e-04 eta: 1:09:10 time: 0.6957 data_time: 0.0337 memory: 23708 grad_norm: 5.6314 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3893 loss_aux: 0.8964 loss: 2.2856 2022/09/11 22:55:53 - mmengine - INFO - Epoch(train) [144][720/940] lr: 4.0000e-04 eta: 1:08:56 time: 0.6931 data_time: 0.0451 memory: 23708 grad_norm: 5.5986 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.4019 loss_aux: 0.9513 loss: 2.3532 2022/09/11 22:56:07 - mmengine - INFO - Epoch(train) [144][740/940] lr: 4.0000e-04 eta: 1:08:42 time: 0.6926 data_time: 0.0306 memory: 23708 grad_norm: 5.5495 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.1966 loss_aux: 0.8325 loss: 2.0291 2022/09/11 22:56:21 - mmengine - INFO - Epoch(train) [144][760/940] lr: 4.0000e-04 eta: 1:08:28 time: 0.6934 data_time: 0.0319 memory: 23708 grad_norm: 5.4494 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.2752 loss_aux: 0.8782 loss: 2.1534 2022/09/11 22:56:35 - mmengine - INFO - Epoch(train) [144][780/940] lr: 4.0000e-04 eta: 1:08:14 time: 0.6956 data_time: 0.0361 memory: 23708 grad_norm: 5.5206 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.4951 loss_aux: 0.9843 loss: 2.4794 2022/09/11 22:56:49 - mmengine - INFO - Epoch(train) [144][800/940] lr: 4.0000e-04 eta: 1:07:59 time: 0.6991 data_time: 0.0416 memory: 23708 grad_norm: 5.5266 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3120 loss_aux: 0.8729 loss: 2.1850 2022/09/11 22:57:03 - mmengine - INFO - Epoch(train) [144][820/940] lr: 4.0000e-04 eta: 1:07:45 time: 0.6866 data_time: 0.0334 memory: 23708 grad_norm: 5.5435 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3154 loss_aux: 0.9176 loss: 2.2330 2022/09/11 22:57:17 - mmengine - INFO - Epoch(train) [144][840/940] lr: 4.0000e-04 eta: 1:07:31 time: 0.7185 data_time: 0.0478 memory: 23708 grad_norm: 5.5865 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4540 loss_aux: 0.9374 loss: 2.3913 2022/09/11 22:57:31 - mmengine - INFO - Epoch(train) [144][860/940] lr: 4.0000e-04 eta: 1:07:17 time: 0.6841 data_time: 0.0278 memory: 23708 grad_norm: 5.5878 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2121 loss_aux: 0.8786 loss: 2.0907 2022/09/11 22:57:44 - mmengine - INFO - Epoch(train) [144][880/940] lr: 4.0000e-04 eta: 1:07:03 time: 0.6799 data_time: 0.0307 memory: 23708 grad_norm: 5.6239 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.3276 loss_aux: 0.8979 loss: 2.2255 2022/09/11 22:57:58 - mmengine - INFO - Epoch(train) [144][900/940] lr: 4.0000e-04 eta: 1:06:49 time: 0.6947 data_time: 0.0339 memory: 23708 grad_norm: 5.6194 top1_acc: 0.6562 top5_acc: 0.9688 loss_cls: 1.3466 loss_aux: 0.9283 loss: 2.2748 2022/09/11 22:58:12 - mmengine - INFO - Epoch(train) [144][920/940] lr: 4.0000e-04 eta: 1:06:34 time: 0.6914 data_time: 0.0437 memory: 23708 grad_norm: 5.4914 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3289 loss_aux: 0.8693 loss: 2.1982 2022/09/11 22:58:25 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 22:58:25 - mmengine - INFO - Epoch(train) [144][940/940] lr: 4.0000e-04 eta: 1:06:20 time: 0.6537 data_time: 0.0229 memory: 23708 grad_norm: 5.7843 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.3630 loss_aux: 0.9258 loss: 2.2887 2022/09/11 22:58:25 - mmengine - INFO - Saving checkpoint at 144 epochs 2022/09/11 22:58:50 - mmengine - INFO - Epoch(train) [145][20/940] lr: 4.0000e-04 eta: 1:06:07 time: 0.9126 data_time: 0.2685 memory: 23708 grad_norm: 5.4717 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3028 loss_aux: 0.9116 loss: 2.2143 2022/09/11 22:59:04 - mmengine - INFO - Epoch(train) [145][40/940] lr: 4.0000e-04 eta: 1:05:53 time: 0.6915 data_time: 0.0324 memory: 23708 grad_norm: 5.5953 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2331 loss_aux: 0.8514 loss: 2.0846 2022/09/11 22:59:17 - mmengine - INFO - Epoch(train) [145][60/940] lr: 4.0000e-04 eta: 1:05:38 time: 0.6777 data_time: 0.0347 memory: 23708 grad_norm: 5.4795 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.2772 loss_aux: 0.8893 loss: 2.1665 2022/09/11 22:59:31 - mmengine - INFO - Epoch(train) [145][80/940] lr: 4.0000e-04 eta: 1:05:24 time: 0.6786 data_time: 0.0357 memory: 23708 grad_norm: 5.6091 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3193 loss_aux: 0.9098 loss: 2.2291 2022/09/11 22:59:45 - mmengine - INFO - Epoch(train) [145][100/940] lr: 4.0000e-04 eta: 1:05:10 time: 0.7160 data_time: 0.0497 memory: 23708 grad_norm: 5.6514 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4011 loss_aux: 0.9350 loss: 2.3361 2022/09/11 22:59:59 - mmengine - INFO - Epoch(train) [145][120/940] lr: 4.0000e-04 eta: 1:04:56 time: 0.6804 data_time: 0.0373 memory: 23708 grad_norm: 5.5252 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.5124 loss_aux: 1.0106 loss: 2.5231 2022/09/11 23:00:13 - mmengine - INFO - Epoch(train) [145][140/940] lr: 4.0000e-04 eta: 1:04:42 time: 0.6883 data_time: 0.0367 memory: 23708 grad_norm: 5.6043 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3678 loss_aux: 0.9397 loss: 2.3074 2022/09/11 23:00:26 - mmengine - INFO - Epoch(train) [145][160/940] lr: 4.0000e-04 eta: 1:04:27 time: 0.6830 data_time: 0.0364 memory: 23708 grad_norm: 5.5984 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3518 loss_aux: 0.9186 loss: 2.2704 2022/09/11 23:00:40 - mmengine - INFO - Epoch(train) [145][180/940] lr: 4.0000e-04 eta: 1:04:13 time: 0.7007 data_time: 0.0459 memory: 23708 grad_norm: 5.5132 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3675 loss_aux: 0.9587 loss: 2.3262 2022/09/11 23:00:54 - mmengine - INFO - Epoch(train) [145][200/940] lr: 4.0000e-04 eta: 1:03:59 time: 0.6844 data_time: 0.0372 memory: 23708 grad_norm: 5.5678 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3395 loss_aux: 0.8887 loss: 2.2282 2022/09/11 23:01:08 - mmengine - INFO - Epoch(train) [145][220/940] lr: 4.0000e-04 eta: 1:03:45 time: 0.6854 data_time: 0.0347 memory: 23708 grad_norm: 5.5408 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.2674 loss_aux: 0.8741 loss: 2.1414 2022/09/11 23:01:22 - mmengine - INFO - Epoch(train) [145][240/940] lr: 4.0000e-04 eta: 1:03:31 time: 0.6942 data_time: 0.0397 memory: 23708 grad_norm: 5.4074 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2627 loss_aux: 0.8753 loss: 2.1380 2022/09/11 23:01:36 - mmengine - INFO - Epoch(train) [145][260/940] lr: 4.0000e-04 eta: 1:03:17 time: 0.7218 data_time: 0.0500 memory: 23708 grad_norm: 5.5779 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.4247 loss_aux: 0.9480 loss: 2.3727 2022/09/11 23:01:50 - mmengine - INFO - Epoch(train) [145][280/940] lr: 4.0000e-04 eta: 1:03:03 time: 0.6893 data_time: 0.0379 memory: 23708 grad_norm: 5.5201 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2470 loss_aux: 0.8484 loss: 2.0954 2022/09/11 23:02:04 - mmengine - INFO - Epoch(train) [145][300/940] lr: 4.0000e-04 eta: 1:02:48 time: 0.6897 data_time: 0.0413 memory: 23708 grad_norm: 5.6156 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4370 loss_aux: 0.9417 loss: 2.3788 2022/09/11 23:02:18 - mmengine - INFO - Epoch(train) [145][320/940] lr: 4.0000e-04 eta: 1:02:34 time: 0.6932 data_time: 0.0417 memory: 23708 grad_norm: 5.5113 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3441 loss_aux: 0.8891 loss: 2.2332 2022/09/11 23:02:32 - mmengine - INFO - Epoch(train) [145][340/940] lr: 4.0000e-04 eta: 1:02:20 time: 0.7043 data_time: 0.0400 memory: 23708 grad_norm: 5.5734 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3569 loss_aux: 0.9183 loss: 2.2752 2022/09/11 23:02:45 - mmengine - INFO - Epoch(train) [145][360/940] lr: 4.0000e-04 eta: 1:02:06 time: 0.6904 data_time: 0.0338 memory: 23708 grad_norm: 5.5500 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3100 loss_aux: 0.9168 loss: 2.2269 2022/09/11 23:03:00 - mmengine - INFO - Epoch(train) [145][380/940] lr: 4.0000e-04 eta: 1:01:52 time: 0.7113 data_time: 0.0374 memory: 23708 grad_norm: 5.4887 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.2680 loss_aux: 0.8562 loss: 2.1242 2022/09/11 23:03:14 - mmengine - INFO - Epoch(train) [145][400/940] lr: 4.0000e-04 eta: 1:01:38 time: 0.6957 data_time: 0.0404 memory: 23708 grad_norm: 5.6079 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3307 loss_aux: 0.9177 loss: 2.2484 2022/09/11 23:03:28 - mmengine - INFO - Epoch(train) [145][420/940] lr: 4.0000e-04 eta: 1:01:24 time: 0.6983 data_time: 0.0445 memory: 23708 grad_norm: 5.4592 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.3580 loss_aux: 0.8851 loss: 2.2430 2022/09/11 23:03:41 - mmengine - INFO - Epoch(train) [145][440/940] lr: 4.0000e-04 eta: 1:01:09 time: 0.6936 data_time: 0.0333 memory: 23708 grad_norm: 5.5225 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2226 loss_aux: 0.8537 loss: 2.0763 2022/09/11 23:03:55 - mmengine - INFO - Epoch(train) [145][460/940] lr: 4.0000e-04 eta: 1:00:55 time: 0.6948 data_time: 0.0359 memory: 23708 grad_norm: 5.5274 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3132 loss_aux: 0.8976 loss: 2.2108 2022/09/11 23:04:10 - mmengine - INFO - Epoch(train) [145][480/940] lr: 4.0000e-04 eta: 1:00:41 time: 0.7055 data_time: 0.0350 memory: 23708 grad_norm: 5.5352 top1_acc: 0.6250 top5_acc: 0.9375 loss_cls: 1.2910 loss_aux: 0.9003 loss: 2.1913 2022/09/11 23:04:24 - mmengine - INFO - Epoch(train) [145][500/940] lr: 4.0000e-04 eta: 1:00:27 time: 0.7231 data_time: 0.0456 memory: 23708 grad_norm: 5.5633 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2443 loss_aux: 0.8814 loss: 2.1257 2022/09/11 23:04:38 - mmengine - INFO - Epoch(train) [145][520/940] lr: 4.0000e-04 eta: 1:00:13 time: 0.6842 data_time: 0.0322 memory: 23708 grad_norm: 5.4979 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.3797 loss_aux: 0.9313 loss: 2.3110 2022/09/11 23:04:51 - mmengine - INFO - Epoch(train) [145][540/940] lr: 4.0000e-04 eta: 0:59:59 time: 0.6861 data_time: 0.0354 memory: 23708 grad_norm: 5.5086 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3735 loss_aux: 0.9205 loss: 2.2940 2022/09/11 23:05:05 - mmengine - INFO - Epoch(train) [145][560/940] lr: 4.0000e-04 eta: 0:59:44 time: 0.6864 data_time: 0.0370 memory: 23708 grad_norm: 5.5203 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3757 loss_aux: 0.9476 loss: 2.3234 2022/09/11 23:05:19 - mmengine - INFO - Epoch(train) [145][580/940] lr: 4.0000e-04 eta: 0:59:30 time: 0.7006 data_time: 0.0418 memory: 23708 grad_norm: 5.3610 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3537 loss_aux: 0.9369 loss: 2.2906 2022/09/11 23:05:33 - mmengine - INFO - Epoch(train) [145][600/940] lr: 4.0000e-04 eta: 0:59:16 time: 0.6902 data_time: 0.0318 memory: 23708 grad_norm: 5.6419 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.4321 loss_aux: 0.9456 loss: 2.3777 2022/09/11 23:05:47 - mmengine - INFO - Epoch(train) [145][620/940] lr: 4.0000e-04 eta: 0:59:02 time: 0.7016 data_time: 0.0334 memory: 23708 grad_norm: 5.5145 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2773 loss_aux: 0.8712 loss: 2.1484 2022/09/11 23:06:01 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 23:06:01 - mmengine - INFO - Epoch(train) [145][640/940] lr: 4.0000e-04 eta: 0:58:48 time: 0.6949 data_time: 0.0367 memory: 23708 grad_norm: 5.4699 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3457 loss_aux: 0.9406 loss: 2.2864 2022/09/11 23:06:15 - mmengine - INFO - Epoch(train) [145][660/940] lr: 4.0000e-04 eta: 0:58:34 time: 0.7091 data_time: 0.0450 memory: 23708 grad_norm: 5.6143 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.5175 loss_aux: 1.0099 loss: 2.5274 2022/09/11 23:06:29 - mmengine - INFO - Epoch(train) [145][680/940] lr: 4.0000e-04 eta: 0:58:20 time: 0.6892 data_time: 0.0345 memory: 23708 grad_norm: 5.5186 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3094 loss_aux: 0.8872 loss: 2.1966 2022/09/11 23:06:43 - mmengine - INFO - Epoch(train) [145][700/940] lr: 4.0000e-04 eta: 0:58:06 time: 0.7015 data_time: 0.0446 memory: 23708 grad_norm: 5.5051 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.4208 loss_aux: 0.9605 loss: 2.3813 2022/09/11 23:06:57 - mmengine - INFO - Epoch(train) [145][720/940] lr: 4.0000e-04 eta: 0:57:51 time: 0.6955 data_time: 0.0414 memory: 23708 grad_norm: 5.5345 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3329 loss_aux: 0.9151 loss: 2.2480 2022/09/11 23:07:11 - mmengine - INFO - Epoch(train) [145][740/940] lr: 4.0000e-04 eta: 0:57:37 time: 0.7027 data_time: 0.0433 memory: 23708 grad_norm: 5.6203 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3758 loss_aux: 0.9590 loss: 2.3349 2022/09/11 23:07:25 - mmengine - INFO - Epoch(train) [145][760/940] lr: 4.0000e-04 eta: 0:57:23 time: 0.6960 data_time: 0.0321 memory: 23708 grad_norm: 5.5159 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.2437 loss_aux: 0.8694 loss: 2.1131 2022/09/11 23:07:39 - mmengine - INFO - Epoch(train) [145][780/940] lr: 4.0000e-04 eta: 0:57:09 time: 0.7089 data_time: 0.0415 memory: 23708 grad_norm: 5.6460 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3566 loss_aux: 0.9100 loss: 2.2667 2022/09/11 23:07:53 - mmengine - INFO - Epoch(train) [145][800/940] lr: 4.0000e-04 eta: 0:56:55 time: 0.6944 data_time: 0.0398 memory: 23708 grad_norm: 5.4657 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3397 loss_aux: 0.9071 loss: 2.2468 2022/09/11 23:08:08 - mmengine - INFO - Epoch(train) [145][820/940] lr: 4.0000e-04 eta: 0:56:41 time: 0.7345 data_time: 0.0442 memory: 23708 grad_norm: 5.5158 top1_acc: 0.8438 top5_acc: 0.9688 loss_cls: 1.2187 loss_aux: 0.8574 loss: 2.0761 2022/09/11 23:08:22 - mmengine - INFO - Epoch(train) [145][840/940] lr: 4.0000e-04 eta: 0:56:27 time: 0.7035 data_time: 0.0414 memory: 23708 grad_norm: 5.5869 top1_acc: 0.5000 top5_acc: 0.7812 loss_cls: 1.3648 loss_aux: 0.9108 loss: 2.2756 2022/09/11 23:08:36 - mmengine - INFO - Epoch(train) [145][860/940] lr: 4.0000e-04 eta: 0:56:13 time: 0.6966 data_time: 0.0360 memory: 23708 grad_norm: 5.4905 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2800 loss_aux: 0.8771 loss: 2.1571 2022/09/11 23:08:50 - mmengine - INFO - Epoch(train) [145][880/940] lr: 4.0000e-04 eta: 0:55:58 time: 0.7006 data_time: 0.0437 memory: 23708 grad_norm: 5.4724 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3870 loss_aux: 0.9323 loss: 2.3193 2022/09/11 23:09:04 - mmengine - INFO - Epoch(train) [145][900/940] lr: 4.0000e-04 eta: 0:55:44 time: 0.7175 data_time: 0.0469 memory: 23708 grad_norm: 5.6286 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4161 loss_aux: 0.9283 loss: 2.3444 2022/09/11 23:09:18 - mmengine - INFO - Epoch(train) [145][920/940] lr: 4.0000e-04 eta: 0:55:30 time: 0.7005 data_time: 0.0359 memory: 23708 grad_norm: 5.5386 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3393 loss_aux: 0.9192 loss: 2.2584 2022/09/11 23:09:31 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 23:09:31 - mmengine - INFO - Epoch(train) [145][940/940] lr: 4.0000e-04 eta: 0:55:16 time: 0.6406 data_time: 0.0327 memory: 23708 grad_norm: 5.7391 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.4459 loss_aux: 0.9845 loss: 2.4304 2022/09/11 23:09:31 - mmengine - INFO - Saving checkpoint at 145 epochs 2022/09/11 23:09:56 - mmengine - INFO - Epoch(train) [146][20/940] lr: 4.0000e-04 eta: 0:55:03 time: 0.9670 data_time: 0.2972 memory: 23708 grad_norm: 5.5412 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2408 loss_aux: 0.8583 loss: 2.0991 2022/09/11 23:10:10 - mmengine - INFO - Epoch(train) [146][40/940] lr: 4.0000e-04 eta: 0:54:48 time: 0.6869 data_time: 0.0483 memory: 23708 grad_norm: 5.5588 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2778 loss_aux: 0.8708 loss: 2.1486 2022/09/11 23:10:23 - mmengine - INFO - Epoch(train) [146][60/940] lr: 4.0000e-04 eta: 0:54:34 time: 0.6773 data_time: 0.0335 memory: 23708 grad_norm: 5.4939 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3493 loss_aux: 0.9113 loss: 2.2606 2022/09/11 23:10:37 - mmengine - INFO - Epoch(train) [146][80/940] lr: 4.0000e-04 eta: 0:54:20 time: 0.6748 data_time: 0.0305 memory: 23708 grad_norm: 5.5584 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3799 loss_aux: 0.9386 loss: 2.3184 2022/09/11 23:10:51 - mmengine - INFO - Epoch(train) [146][100/940] lr: 4.0000e-04 eta: 0:54:06 time: 0.6945 data_time: 0.0439 memory: 23708 grad_norm: 5.4752 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2761 loss_aux: 0.8915 loss: 2.1677 2022/09/11 23:11:04 - mmengine - INFO - Epoch(train) [146][120/940] lr: 4.0000e-04 eta: 0:53:52 time: 0.6808 data_time: 0.0346 memory: 23708 grad_norm: 5.4930 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3521 loss_aux: 0.9408 loss: 2.2929 2022/09/11 23:11:18 - mmengine - INFO - Epoch(train) [146][140/940] lr: 4.0000e-04 eta: 0:53:38 time: 0.7033 data_time: 0.0325 memory: 23708 grad_norm: 5.4880 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3160 loss_aux: 0.8704 loss: 2.1864 2022/09/11 23:11:32 - mmengine - INFO - Epoch(train) [146][160/940] lr: 4.0000e-04 eta: 0:53:23 time: 0.6900 data_time: 0.0380 memory: 23708 grad_norm: 5.6191 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4177 loss_aux: 0.9414 loss: 2.3591 2022/09/11 23:11:46 - mmengine - INFO - Epoch(train) [146][180/940] lr: 4.0000e-04 eta: 0:53:09 time: 0.7090 data_time: 0.0532 memory: 23708 grad_norm: 5.5436 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.4017 loss_aux: 0.9357 loss: 2.3374 2022/09/11 23:12:01 - mmengine - INFO - Epoch(train) [146][200/940] lr: 4.0000e-04 eta: 0:52:55 time: 0.7117 data_time: 0.0408 memory: 23708 grad_norm: 5.5098 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3683 loss_aux: 0.9197 loss: 2.2880 2022/09/11 23:12:15 - mmengine - INFO - Epoch(train) [146][220/940] lr: 4.0000e-04 eta: 0:52:41 time: 0.7139 data_time: 0.0349 memory: 23708 grad_norm: 5.4227 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.3088 loss_aux: 0.8922 loss: 2.2009 2022/09/11 23:12:29 - mmengine - INFO - Epoch(train) [146][240/940] lr: 4.0000e-04 eta: 0:52:27 time: 0.7022 data_time: 0.0439 memory: 23708 grad_norm: 5.5046 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2599 loss_aux: 0.8672 loss: 2.1271 2022/09/11 23:12:43 - mmengine - INFO - Epoch(train) [146][260/940] lr: 4.0000e-04 eta: 0:52:13 time: 0.7028 data_time: 0.0485 memory: 23708 grad_norm: 5.4444 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2830 loss_aux: 0.8918 loss: 2.1748 2022/09/11 23:12:57 - mmengine - INFO - Epoch(train) [146][280/940] lr: 4.0000e-04 eta: 0:51:59 time: 0.7095 data_time: 0.0454 memory: 23708 grad_norm: 5.6184 top1_acc: 0.6562 top5_acc: 0.9375 loss_cls: 1.3520 loss_aux: 0.9332 loss: 2.2851 2022/09/11 23:13:11 - mmengine - INFO - Epoch(train) [146][300/940] lr: 4.0000e-04 eta: 0:51:45 time: 0.6958 data_time: 0.0356 memory: 23708 grad_norm: 5.6016 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3749 loss_aux: 0.9040 loss: 2.2788 2022/09/11 23:13:25 - mmengine - INFO - Epoch(train) [146][320/940] lr: 4.0000e-04 eta: 0:51:30 time: 0.7006 data_time: 0.0412 memory: 23708 grad_norm: 5.5385 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4726 loss_aux: 0.9849 loss: 2.4575 2022/09/11 23:13:39 - mmengine - INFO - Epoch(train) [146][340/940] lr: 4.0000e-04 eta: 0:51:16 time: 0.7122 data_time: 0.0453 memory: 23708 grad_norm: 5.5936 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2244 loss_aux: 0.8886 loss: 2.1130 2022/09/11 23:13:54 - mmengine - INFO - Epoch(train) [146][360/940] lr: 4.0000e-04 eta: 0:51:02 time: 0.7155 data_time: 0.0420 memory: 23708 grad_norm: 5.5001 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3641 loss_aux: 0.9252 loss: 2.2893 2022/09/11 23:14:08 - mmengine - INFO - Epoch(train) [146][380/940] lr: 4.0000e-04 eta: 0:50:48 time: 0.7133 data_time: 0.0356 memory: 23708 grad_norm: 5.6538 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.3665 loss_aux: 0.9064 loss: 2.2728 2022/09/11 23:14:22 - mmengine - INFO - Epoch(train) [146][400/940] lr: 4.0000e-04 eta: 0:50:34 time: 0.6975 data_time: 0.0371 memory: 23708 grad_norm: 5.4707 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3514 loss_aux: 0.9217 loss: 2.2731 2022/09/11 23:14:36 - mmengine - INFO - Epoch(train) [146][420/940] lr: 4.0000e-04 eta: 0:50:20 time: 0.7129 data_time: 0.0510 memory: 23708 grad_norm: 5.6346 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3858 loss_aux: 0.9280 loss: 2.3138 2022/09/11 23:14:50 - mmengine - INFO - Epoch(train) [146][440/940] lr: 4.0000e-04 eta: 0:50:06 time: 0.6904 data_time: 0.0382 memory: 23708 grad_norm: 5.6175 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3975 loss_aux: 0.9372 loss: 2.3347 2022/09/11 23:15:04 - mmengine - INFO - Epoch(train) [146][460/940] lr: 4.0000e-04 eta: 0:49:52 time: 0.6929 data_time: 0.0384 memory: 23708 grad_norm: 5.4982 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3148 loss_aux: 0.8751 loss: 2.1899 2022/09/11 23:15:18 - mmengine - INFO - Epoch(train) [146][480/940] lr: 4.0000e-04 eta: 0:49:38 time: 0.6978 data_time: 0.0449 memory: 23708 grad_norm: 5.6066 top1_acc: 0.5312 top5_acc: 0.8125 loss_cls: 1.3740 loss_aux: 0.9008 loss: 2.2748 2022/09/11 23:15:32 - mmengine - INFO - Epoch(train) [146][500/940] lr: 4.0000e-04 eta: 0:49:23 time: 0.7039 data_time: 0.0432 memory: 23708 grad_norm: 5.6166 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.1546 loss_aux: 0.8449 loss: 1.9995 2022/09/11 23:15:46 - mmengine - INFO - Epoch(train) [146][520/940] lr: 4.0000e-04 eta: 0:49:09 time: 0.7159 data_time: 0.0414 memory: 23708 grad_norm: 5.6122 top1_acc: 0.5312 top5_acc: 0.7188 loss_cls: 1.3875 loss_aux: 0.9301 loss: 2.3176 2022/09/11 23:16:01 - mmengine - INFO - Epoch(train) [146][540/940] lr: 4.0000e-04 eta: 0:48:55 time: 0.7169 data_time: 0.0400 memory: 23708 grad_norm: 5.5999 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4135 loss_aux: 0.9886 loss: 2.4021 2022/09/11 23:16:15 - mmengine - INFO - Epoch(train) [146][560/940] lr: 4.0000e-04 eta: 0:48:41 time: 0.7142 data_time: 0.0429 memory: 23708 grad_norm: 5.5487 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3249 loss_aux: 0.8993 loss: 2.2242 2022/09/11 23:16:29 - mmengine - INFO - Epoch(train) [146][580/940] lr: 4.0000e-04 eta: 0:48:27 time: 0.7000 data_time: 0.0437 memory: 23708 grad_norm: 5.5891 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3698 loss_aux: 0.9295 loss: 2.2993 2022/09/11 23:16:43 - mmengine - INFO - Epoch(train) [146][600/940] lr: 4.0000e-04 eta: 0:48:13 time: 0.7026 data_time: 0.0384 memory: 23708 grad_norm: 5.5933 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3524 loss_aux: 0.9126 loss: 2.2649 2022/09/11 23:16:57 - mmengine - INFO - Epoch(train) [146][620/940] lr: 4.0000e-04 eta: 0:47:59 time: 0.7067 data_time: 0.0346 memory: 23708 grad_norm: 5.5491 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.5506 loss_aux: 1.0042 loss: 2.5548 2022/09/11 23:17:11 - mmengine - INFO - Epoch(train) [146][640/940] lr: 4.0000e-04 eta: 0:47:45 time: 0.7060 data_time: 0.0397 memory: 23708 grad_norm: 5.5791 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.4656 loss_aux: 0.9380 loss: 2.4036 2022/09/11 23:17:25 - mmengine - INFO - Epoch(train) [146][660/940] lr: 4.0000e-04 eta: 0:47:31 time: 0.7073 data_time: 0.0484 memory: 23708 grad_norm: 5.5274 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3106 loss_aux: 0.8860 loss: 2.1965 2022/09/11 23:17:39 - mmengine - INFO - Epoch(train) [146][680/940] lr: 4.0000e-04 eta: 0:47:16 time: 0.6997 data_time: 0.0362 memory: 23708 grad_norm: 5.5588 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3324 loss_aux: 0.8854 loss: 2.2178 2022/09/11 23:17:53 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 23:17:53 - mmengine - INFO - Epoch(train) [146][700/940] lr: 4.0000e-04 eta: 0:47:02 time: 0.6960 data_time: 0.0359 memory: 23708 grad_norm: 5.6564 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3851 loss_aux: 0.9137 loss: 2.2988 2022/09/11 23:18:07 - mmengine - INFO - Epoch(train) [146][720/940] lr: 4.0000e-04 eta: 0:46:48 time: 0.7060 data_time: 0.0429 memory: 23708 grad_norm: 5.5313 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2798 loss_aux: 0.8631 loss: 2.1429 2022/09/11 23:18:22 - mmengine - INFO - Epoch(train) [146][740/940] lr: 4.0000e-04 eta: 0:46:34 time: 0.7118 data_time: 0.0459 memory: 23708 grad_norm: 5.5077 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3887 loss_aux: 0.9060 loss: 2.2947 2022/09/11 23:18:36 - mmengine - INFO - Epoch(train) [146][760/940] lr: 4.0000e-04 eta: 0:46:20 time: 0.7160 data_time: 0.0427 memory: 23708 grad_norm: 5.5944 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.3658 loss_aux: 0.9040 loss: 2.2698 2022/09/11 23:18:50 - mmengine - INFO - Epoch(train) [146][780/940] lr: 4.0000e-04 eta: 0:46:06 time: 0.7077 data_time: 0.0368 memory: 23708 grad_norm: 5.5467 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.4253 loss_aux: 0.9608 loss: 2.3862 2022/09/11 23:19:04 - mmengine - INFO - Epoch(train) [146][800/940] lr: 4.0000e-04 eta: 0:45:52 time: 0.7018 data_time: 0.0440 memory: 23708 grad_norm: 5.5524 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.3384 loss_aux: 0.9447 loss: 2.2831 2022/09/11 23:19:18 - mmengine - INFO - Epoch(train) [146][820/940] lr: 4.0000e-04 eta: 0:45:38 time: 0.7035 data_time: 0.0436 memory: 23708 grad_norm: 5.5271 top1_acc: 0.6875 top5_acc: 0.7812 loss_cls: 1.2993 loss_aux: 0.9093 loss: 2.2086 2022/09/11 23:19:32 - mmengine - INFO - Epoch(train) [146][840/940] lr: 4.0000e-04 eta: 0:45:24 time: 0.6993 data_time: 0.0322 memory: 23708 grad_norm: 5.5876 top1_acc: 0.8438 top5_acc: 0.8750 loss_cls: 1.3202 loss_aux: 0.9090 loss: 2.2292 2022/09/11 23:19:47 - mmengine - INFO - Epoch(train) [146][860/940] lr: 4.0000e-04 eta: 0:45:09 time: 0.7244 data_time: 0.0322 memory: 23708 grad_norm: 5.5707 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.4612 loss_aux: 0.9727 loss: 2.4339 2022/09/11 23:20:01 - mmengine - INFO - Epoch(train) [146][880/940] lr: 4.0000e-04 eta: 0:44:55 time: 0.6928 data_time: 0.0360 memory: 23708 grad_norm: 5.4937 top1_acc: 0.5625 top5_acc: 0.7812 loss_cls: 1.3376 loss_aux: 0.9004 loss: 2.2379 2022/09/11 23:20:15 - mmengine - INFO - Epoch(train) [146][900/940] lr: 4.0000e-04 eta: 0:44:41 time: 0.7006 data_time: 0.0418 memory: 23708 grad_norm: 5.5502 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.2177 loss_aux: 0.8481 loss: 2.0657 2022/09/11 23:20:29 - mmengine - INFO - Epoch(train) [146][920/940] lr: 4.0000e-04 eta: 0:44:27 time: 0.7180 data_time: 0.0404 memory: 23708 grad_norm: 5.6103 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4114 loss_aux: 0.9321 loss: 2.3435 2022/09/11 23:20:42 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 23:20:42 - mmengine - INFO - Epoch(train) [146][940/940] lr: 4.0000e-04 eta: 0:44:13 time: 0.6508 data_time: 0.0332 memory: 23708 grad_norm: 5.8420 top1_acc: 0.2857 top5_acc: 0.7143 loss_cls: 1.4481 loss_aux: 0.9592 loss: 2.4073 2022/09/11 23:20:42 - mmengine - INFO - Saving checkpoint at 146 epochs 2022/09/11 23:21:07 - mmengine - INFO - Epoch(train) [147][20/940] lr: 4.0000e-04 eta: 0:43:59 time: 0.9405 data_time: 0.2818 memory: 23708 grad_norm: 5.6222 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4254 loss_aux: 0.9487 loss: 2.3741 2022/09/11 23:21:20 - mmengine - INFO - Epoch(train) [147][40/940] lr: 4.0000e-04 eta: 0:43:45 time: 0.6797 data_time: 0.0389 memory: 23708 grad_norm: 5.4428 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.2740 loss_aux: 0.9014 loss: 2.1755 2022/09/11 23:21:34 - mmengine - INFO - Epoch(train) [147][60/940] lr: 4.0000e-04 eta: 0:43:31 time: 0.6722 data_time: 0.0379 memory: 23708 grad_norm: 5.6715 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.2903 loss_aux: 0.8722 loss: 2.1625 2022/09/11 23:21:47 - mmengine - INFO - Epoch(train) [147][80/940] lr: 4.0000e-04 eta: 0:43:17 time: 0.6781 data_time: 0.0341 memory: 23708 grad_norm: 5.5416 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3372 loss_aux: 0.8933 loss: 2.2305 2022/09/11 23:22:01 - mmengine - INFO - Epoch(train) [147][100/940] lr: 4.0000e-04 eta: 0:43:03 time: 0.7054 data_time: 0.0461 memory: 23708 grad_norm: 5.6146 top1_acc: 0.5000 top5_acc: 0.6562 loss_cls: 1.4283 loss_aux: 0.9634 loss: 2.3917 2022/09/11 23:22:15 - mmengine - INFO - Epoch(train) [147][120/940] lr: 4.0000e-04 eta: 0:42:48 time: 0.6826 data_time: 0.0403 memory: 23708 grad_norm: 5.6202 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.3463 loss_aux: 0.9001 loss: 2.2463 2022/09/11 23:22:29 - mmengine - INFO - Epoch(train) [147][140/940] lr: 4.0000e-04 eta: 0:42:34 time: 0.6858 data_time: 0.0386 memory: 23708 grad_norm: 5.5269 top1_acc: 0.6562 top5_acc: 0.7188 loss_cls: 1.2893 loss_aux: 0.8856 loss: 2.1750 2022/09/11 23:22:43 - mmengine - INFO - Epoch(train) [147][160/940] lr: 4.0000e-04 eta: 0:42:20 time: 0.6888 data_time: 0.0315 memory: 23708 grad_norm: 5.5271 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2906 loss_aux: 0.8857 loss: 2.1763 2022/09/11 23:22:57 - mmengine - INFO - Epoch(train) [147][180/940] lr: 4.0000e-04 eta: 0:42:06 time: 0.7017 data_time: 0.0499 memory: 23708 grad_norm: 5.5781 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2742 loss_aux: 0.8772 loss: 2.1514 2022/09/11 23:23:10 - mmengine - INFO - Epoch(train) [147][200/940] lr: 4.0000e-04 eta: 0:41:52 time: 0.6819 data_time: 0.0388 memory: 23708 grad_norm: 5.5658 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.2593 loss_aux: 0.8789 loss: 2.1382 2022/09/11 23:23:25 - mmengine - INFO - Epoch(train) [147][220/940] lr: 4.0000e-04 eta: 0:41:38 time: 0.7081 data_time: 0.0373 memory: 23708 grad_norm: 5.6171 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4049 loss_aux: 0.9370 loss: 2.3419 2022/09/11 23:23:38 - mmengine - INFO - Epoch(train) [147][240/940] lr: 4.0000e-04 eta: 0:41:24 time: 0.6876 data_time: 0.0346 memory: 23708 grad_norm: 5.5486 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.1914 loss_aux: 0.8501 loss: 2.0415 2022/09/11 23:23:52 - mmengine - INFO - Epoch(train) [147][260/940] lr: 4.0000e-04 eta: 0:41:09 time: 0.7093 data_time: 0.0435 memory: 23708 grad_norm: 5.5411 top1_acc: 0.7188 top5_acc: 0.7812 loss_cls: 1.3928 loss_aux: 0.9223 loss: 2.3151 2022/09/11 23:24:06 - mmengine - INFO - Epoch(train) [147][280/940] lr: 4.0000e-04 eta: 0:40:55 time: 0.6992 data_time: 0.0380 memory: 23708 grad_norm: 5.5184 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3412 loss_aux: 0.9611 loss: 2.3022 2022/09/11 23:24:20 - mmengine - INFO - Epoch(train) [147][300/940] lr: 4.0000e-04 eta: 0:40:41 time: 0.6930 data_time: 0.0454 memory: 23708 grad_norm: 5.5297 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2827 loss_aux: 0.8746 loss: 2.1574 2022/09/11 23:24:34 - mmengine - INFO - Epoch(train) [147][320/940] lr: 4.0000e-04 eta: 0:40:27 time: 0.6824 data_time: 0.0332 memory: 23708 grad_norm: 5.4601 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.4149 loss_aux: 0.9508 loss: 2.3657 2022/09/11 23:24:48 - mmengine - INFO - Epoch(train) [147][340/940] lr: 4.0000e-04 eta: 0:40:13 time: 0.7159 data_time: 0.0418 memory: 23708 grad_norm: 5.5482 top1_acc: 0.5625 top5_acc: 0.7188 loss_cls: 1.5122 loss_aux: 0.9952 loss: 2.5074 2022/09/11 23:25:02 - mmengine - INFO - Epoch(train) [147][360/940] lr: 4.0000e-04 eta: 0:39:59 time: 0.6885 data_time: 0.0388 memory: 23708 grad_norm: 5.5161 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.3152 loss_aux: 0.9022 loss: 2.2174 2022/09/11 23:25:16 - mmengine - INFO - Epoch(train) [147][380/940] lr: 4.0000e-04 eta: 0:39:45 time: 0.7010 data_time: 0.0416 memory: 23708 grad_norm: 5.5912 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3459 loss_aux: 0.9425 loss: 2.2884 2022/09/11 23:25:30 - mmengine - INFO - Epoch(train) [147][400/940] lr: 4.0000e-04 eta: 0:39:31 time: 0.6891 data_time: 0.0442 memory: 23708 grad_norm: 5.6405 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.2664 loss_aux: 0.8824 loss: 2.1488 2022/09/11 23:25:44 - mmengine - INFO - Epoch(train) [147][420/940] lr: 4.0000e-04 eta: 0:39:16 time: 0.6949 data_time: 0.0399 memory: 23708 grad_norm: 5.6672 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2644 loss_aux: 0.8826 loss: 2.1470 2022/09/11 23:25:58 - mmengine - INFO - Epoch(train) [147][440/940] lr: 4.0000e-04 eta: 0:39:02 time: 0.7063 data_time: 0.0391 memory: 23708 grad_norm: 5.6016 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.4519 loss_aux: 0.9745 loss: 2.4264 2022/09/11 23:26:12 - mmengine - INFO - Epoch(train) [147][460/940] lr: 4.0000e-04 eta: 0:38:48 time: 0.7009 data_time: 0.0404 memory: 23708 grad_norm: 5.5854 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3629 loss_aux: 0.9525 loss: 2.3154 2022/09/11 23:26:26 - mmengine - INFO - Epoch(train) [147][480/940] lr: 4.0000e-04 eta: 0:38:34 time: 0.6970 data_time: 0.0331 memory: 23708 grad_norm: 5.5221 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3205 loss_aux: 0.8735 loss: 2.1941 2022/09/11 23:26:40 - mmengine - INFO - Epoch(train) [147][500/940] lr: 4.0000e-04 eta: 0:38:20 time: 0.7162 data_time: 0.0400 memory: 23708 grad_norm: 5.6063 top1_acc: 0.5938 top5_acc: 0.7188 loss_cls: 1.3938 loss_aux: 0.9408 loss: 2.3346 2022/09/11 23:26:54 - mmengine - INFO - Epoch(train) [147][520/940] lr: 4.0000e-04 eta: 0:38:06 time: 0.7007 data_time: 0.0423 memory: 23708 grad_norm: 5.5994 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.3963 loss_aux: 0.9226 loss: 2.3189 2022/09/11 23:27:08 - mmengine - INFO - Epoch(train) [147][540/940] lr: 4.0000e-04 eta: 0:37:52 time: 0.6967 data_time: 0.0374 memory: 23708 grad_norm: 5.5432 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3823 loss_aux: 0.9462 loss: 2.3285 2022/09/11 23:27:22 - mmengine - INFO - Epoch(train) [147][560/940] lr: 4.0000e-04 eta: 0:37:38 time: 0.6864 data_time: 0.0340 memory: 23708 grad_norm: 5.5718 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3595 loss_aux: 0.9124 loss: 2.2719 2022/09/11 23:27:36 - mmengine - INFO - Epoch(train) [147][580/940] lr: 4.0000e-04 eta: 0:37:23 time: 0.7008 data_time: 0.0427 memory: 23708 grad_norm: 5.5937 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2201 loss_aux: 0.8627 loss: 2.0828 2022/09/11 23:27:51 - mmengine - INFO - Epoch(train) [147][600/940] lr: 4.0000e-04 eta: 0:37:09 time: 0.7412 data_time: 0.0385 memory: 23708 grad_norm: 5.6348 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3359 loss_aux: 0.9041 loss: 2.2400 2022/09/11 23:28:05 - mmengine - INFO - Epoch(train) [147][620/940] lr: 4.0000e-04 eta: 0:36:55 time: 0.6925 data_time: 0.0377 memory: 23708 grad_norm: 5.5695 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3567 loss_aux: 0.9195 loss: 2.2762 2022/09/11 23:28:19 - mmengine - INFO - Epoch(train) [147][640/940] lr: 4.0000e-04 eta: 0:36:41 time: 0.7005 data_time: 0.0395 memory: 23708 grad_norm: 5.6241 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4072 loss_aux: 0.9435 loss: 2.3507 2022/09/11 23:28:33 - mmengine - INFO - Epoch(train) [147][660/940] lr: 4.0000e-04 eta: 0:36:27 time: 0.7094 data_time: 0.0420 memory: 23708 grad_norm: 5.5392 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2683 loss_aux: 0.8660 loss: 2.1343 2022/09/11 23:28:47 - mmengine - INFO - Epoch(train) [147][680/940] lr: 4.0000e-04 eta: 0:36:13 time: 0.6934 data_time: 0.0350 memory: 23708 grad_norm: 5.6045 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2322 loss_aux: 0.8220 loss: 2.0542 2022/09/11 23:29:01 - mmengine - INFO - Epoch(train) [147][700/940] lr: 4.0000e-04 eta: 0:35:59 time: 0.7060 data_time: 0.0426 memory: 23708 grad_norm: 5.5472 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3702 loss_aux: 0.9262 loss: 2.2964 2022/09/11 23:29:15 - mmengine - INFO - Epoch(train) [147][720/940] lr: 4.0000e-04 eta: 0:35:45 time: 0.6978 data_time: 0.0419 memory: 23708 grad_norm: 5.5866 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.4558 loss_aux: 0.9868 loss: 2.4426 2022/09/11 23:29:29 - mmengine - INFO - Epoch(train) [147][740/940] lr: 4.0000e-04 eta: 0:35:31 time: 0.7038 data_time: 0.0419 memory: 23708 grad_norm: 5.4700 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.2631 loss_aux: 0.8609 loss: 2.1241 2022/09/11 23:29:43 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 23:29:43 - mmengine - INFO - Epoch(train) [147][760/940] lr: 4.0000e-04 eta: 0:35:16 time: 0.6952 data_time: 0.0358 memory: 23708 grad_norm: 5.5426 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4422 loss_aux: 0.9477 loss: 2.3899 2022/09/11 23:29:57 - mmengine - INFO - Epoch(train) [147][780/940] lr: 4.0000e-04 eta: 0:35:02 time: 0.6987 data_time: 0.0387 memory: 23708 grad_norm: 5.6643 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3509 loss_aux: 0.8890 loss: 2.2399 2022/09/11 23:30:10 - mmengine - INFO - Epoch(train) [147][800/940] lr: 4.0000e-04 eta: 0:34:48 time: 0.6870 data_time: 0.0352 memory: 23708 grad_norm: 5.5599 top1_acc: 0.6562 top5_acc: 0.7500 loss_cls: 1.4083 loss_aux: 0.9738 loss: 2.3821 2022/09/11 23:30:24 - mmengine - INFO - Epoch(train) [147][820/940] lr: 4.0000e-04 eta: 0:34:34 time: 0.6945 data_time: 0.0395 memory: 23708 grad_norm: 5.6405 top1_acc: 0.7812 top5_acc: 0.9375 loss_cls: 1.3605 loss_aux: 0.9113 loss: 2.2719 2022/09/11 23:30:39 - mmengine - INFO - Epoch(train) [147][840/940] lr: 4.0000e-04 eta: 0:34:20 time: 0.7233 data_time: 0.0400 memory: 23708 grad_norm: 5.5909 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3400 loss_aux: 0.9061 loss: 2.2460 2022/09/11 23:30:53 - mmengine - INFO - Epoch(train) [147][860/940] lr: 4.0000e-04 eta: 0:34:06 time: 0.7031 data_time: 0.0398 memory: 23708 grad_norm: 5.5831 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3666 loss_aux: 0.9037 loss: 2.2704 2022/09/11 23:31:07 - mmengine - INFO - Epoch(train) [147][880/940] lr: 4.0000e-04 eta: 0:33:52 time: 0.7035 data_time: 0.0368 memory: 23708 grad_norm: 5.6136 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.3845 loss_aux: 0.9330 loss: 2.3175 2022/09/11 23:31:21 - mmengine - INFO - Epoch(train) [147][900/940] lr: 4.0000e-04 eta: 0:33:38 time: 0.7053 data_time: 0.0413 memory: 23708 grad_norm: 5.6677 top1_acc: 0.8125 top5_acc: 0.9688 loss_cls: 1.2282 loss_aux: 0.8924 loss: 2.1206 2022/09/11 23:31:35 - mmengine - INFO - Epoch(train) [147][920/940] lr: 4.0000e-04 eta: 0:33:23 time: 0.6853 data_time: 0.0349 memory: 23708 grad_norm: 5.6664 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.4510 loss_aux: 0.9658 loss: 2.4168 2022/09/11 23:31:48 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 23:31:48 - mmengine - INFO - Epoch(train) [147][940/940] lr: 4.0000e-04 eta: 0:33:09 time: 0.6543 data_time: 0.0335 memory: 23708 grad_norm: 5.9045 top1_acc: 0.7143 top5_acc: 1.0000 loss_cls: 1.2877 loss_aux: 0.9028 loss: 2.1905 2022/09/11 23:31:48 - mmengine - INFO - Saving checkpoint at 147 epochs 2022/09/11 23:32:13 - mmengine - INFO - Epoch(train) [148][20/940] lr: 4.0000e-04 eta: 0:32:56 time: 0.9481 data_time: 0.3103 memory: 23708 grad_norm: 5.5679 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3360 loss_aux: 0.8835 loss: 2.2195 2022/09/11 23:32:26 - mmengine - INFO - Epoch(train) [148][40/940] lr: 4.0000e-04 eta: 0:32:41 time: 0.6638 data_time: 0.0258 memory: 23708 grad_norm: 5.6290 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3736 loss_aux: 0.9416 loss: 2.3151 2022/09/11 23:32:40 - mmengine - INFO - Epoch(train) [148][60/940] lr: 4.0000e-04 eta: 0:32:27 time: 0.6971 data_time: 0.0327 memory: 23708 grad_norm: 5.5134 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.2887 loss_aux: 0.9034 loss: 2.1921 2022/09/11 23:32:54 - mmengine - INFO - Epoch(train) [148][80/940] lr: 4.0000e-04 eta: 0:32:13 time: 0.6965 data_time: 0.0330 memory: 23708 grad_norm: 5.5235 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3146 loss_aux: 0.9178 loss: 2.2325 2022/09/11 23:33:08 - mmengine - INFO - Epoch(train) [148][100/940] lr: 4.0000e-04 eta: 0:31:59 time: 0.7191 data_time: 0.0414 memory: 23708 grad_norm: 5.6320 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3235 loss_aux: 0.9302 loss: 2.2537 2022/09/11 23:33:22 - mmengine - INFO - Epoch(train) [148][120/940] lr: 4.0000e-04 eta: 0:31:45 time: 0.6989 data_time: 0.0310 memory: 23708 grad_norm: 5.5853 top1_acc: 0.7812 top5_acc: 0.9688 loss_cls: 1.3912 loss_aux: 0.9579 loss: 2.3490 2022/09/11 23:33:36 - mmengine - INFO - Epoch(train) [148][140/940] lr: 4.0000e-04 eta: 0:31:31 time: 0.7027 data_time: 0.0387 memory: 23708 grad_norm: 5.6662 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.2692 loss_aux: 0.8570 loss: 2.1262 2022/09/11 23:33:50 - mmengine - INFO - Epoch(train) [148][160/940] lr: 4.0000e-04 eta: 0:31:17 time: 0.6899 data_time: 0.0351 memory: 23708 grad_norm: 5.6857 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4195 loss_aux: 0.9528 loss: 2.3723 2022/09/11 23:34:04 - mmengine - INFO - Epoch(train) [148][180/940] lr: 4.0000e-04 eta: 0:31:02 time: 0.6938 data_time: 0.0400 memory: 23708 grad_norm: 5.5360 top1_acc: 0.5625 top5_acc: 0.9062 loss_cls: 1.3619 loss_aux: 0.9166 loss: 2.2785 2022/09/11 23:34:18 - mmengine - INFO - Epoch(train) [148][200/940] lr: 4.0000e-04 eta: 0:30:48 time: 0.6983 data_time: 0.0368 memory: 23708 grad_norm: 5.6185 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4228 loss_aux: 0.9464 loss: 2.3692 2022/09/11 23:34:32 - mmengine - INFO - Epoch(train) [148][220/940] lr: 4.0000e-04 eta: 0:30:34 time: 0.6988 data_time: 0.0438 memory: 23708 grad_norm: 5.6200 top1_acc: 0.7500 top5_acc: 0.8125 loss_cls: 1.3724 loss_aux: 0.9296 loss: 2.3020 2022/09/11 23:34:46 - mmengine - INFO - Epoch(train) [148][240/940] lr: 4.0000e-04 eta: 0:30:20 time: 0.6927 data_time: 0.0318 memory: 23708 grad_norm: 5.6162 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3793 loss_aux: 0.9245 loss: 2.3038 2022/09/11 23:35:00 - mmengine - INFO - Epoch(train) [148][260/940] lr: 4.0000e-04 eta: 0:30:06 time: 0.6987 data_time: 0.0429 memory: 23708 grad_norm: 5.4670 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2572 loss_aux: 0.8612 loss: 2.1185 2022/09/11 23:35:13 - mmengine - INFO - Epoch(train) [148][280/940] lr: 4.0000e-04 eta: 0:29:52 time: 0.6800 data_time: 0.0314 memory: 23708 grad_norm: 5.6210 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3804 loss_aux: 0.9243 loss: 2.3047 2022/09/11 23:35:27 - mmengine - INFO - Epoch(train) [148][300/940] lr: 4.0000e-04 eta: 0:29:38 time: 0.6958 data_time: 0.0316 memory: 23708 grad_norm: 5.5033 top1_acc: 0.8438 top5_acc: 0.9062 loss_cls: 1.2132 loss_aux: 0.8696 loss: 2.0827 2022/09/11 23:35:41 - mmengine - INFO - Epoch(train) [148][320/940] lr: 4.0000e-04 eta: 0:29:24 time: 0.7015 data_time: 0.0333 memory: 23708 grad_norm: 5.5813 top1_acc: 0.8125 top5_acc: 0.9375 loss_cls: 1.2148 loss_aux: 0.8479 loss: 2.0627 2022/09/11 23:35:55 - mmengine - INFO - Epoch(train) [148][340/940] lr: 4.0000e-04 eta: 0:29:09 time: 0.7009 data_time: 0.0415 memory: 23708 grad_norm: 5.6698 top1_acc: 0.8125 top5_acc: 0.9062 loss_cls: 1.3391 loss_aux: 0.8941 loss: 2.2332 2022/09/11 23:36:09 - mmengine - INFO - Epoch(train) [148][360/940] lr: 4.0000e-04 eta: 0:28:55 time: 0.6844 data_time: 0.0332 memory: 23708 grad_norm: 5.6355 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.4202 loss_aux: 0.9672 loss: 2.3874 2022/09/11 23:36:23 - mmengine - INFO - Epoch(train) [148][380/940] lr: 4.0000e-04 eta: 0:28:41 time: 0.7011 data_time: 0.0300 memory: 23708 grad_norm: 5.5990 top1_acc: 0.5938 top5_acc: 0.9062 loss_cls: 1.3642 loss_aux: 0.9037 loss: 2.2680 2022/09/11 23:36:37 - mmengine - INFO - Epoch(train) [148][400/940] lr: 4.0000e-04 eta: 0:28:27 time: 0.6955 data_time: 0.0397 memory: 23708 grad_norm: 5.6662 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2694 loss_aux: 0.8889 loss: 2.1583 2022/09/11 23:36:51 - mmengine - INFO - Epoch(train) [148][420/940] lr: 4.0000e-04 eta: 0:28:13 time: 0.7172 data_time: 0.0469 memory: 23708 grad_norm: 5.6029 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3413 loss_aux: 0.9227 loss: 2.2641 2022/09/11 23:37:05 - mmengine - INFO - Epoch(train) [148][440/940] lr: 4.0000e-04 eta: 0:27:59 time: 0.6833 data_time: 0.0313 memory: 23708 grad_norm: 5.5954 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2587 loss_aux: 0.8662 loss: 2.1250 2022/09/11 23:37:19 - mmengine - INFO - Epoch(train) [148][460/940] lr: 4.0000e-04 eta: 0:27:45 time: 0.7054 data_time: 0.0393 memory: 23708 grad_norm: 5.7837 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3604 loss_aux: 0.9042 loss: 2.2647 2022/09/11 23:37:33 - mmengine - INFO - Epoch(train) [148][480/940] lr: 4.0000e-04 eta: 0:27:31 time: 0.6855 data_time: 0.0328 memory: 23708 grad_norm: 5.6542 top1_acc: 0.7188 top5_acc: 0.9375 loss_cls: 1.4129 loss_aux: 0.9646 loss: 2.3775 2022/09/11 23:37:47 - mmengine - INFO - Epoch(train) [148][500/940] lr: 4.0000e-04 eta: 0:27:16 time: 0.7025 data_time: 0.0425 memory: 23708 grad_norm: 5.5721 top1_acc: 0.6562 top5_acc: 0.8125 loss_cls: 1.2984 loss_aux: 0.8864 loss: 2.1848 2022/09/11 23:38:01 - mmengine - INFO - Epoch(train) [148][520/940] lr: 4.0000e-04 eta: 0:27:02 time: 0.6832 data_time: 0.0308 memory: 23708 grad_norm: 5.6662 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2216 loss_aux: 0.8685 loss: 2.0901 2022/09/11 23:38:15 - mmengine - INFO - Epoch(train) [148][540/940] lr: 4.0000e-04 eta: 0:26:48 time: 0.6946 data_time: 0.0340 memory: 23708 grad_norm: 5.6315 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3921 loss_aux: 0.9215 loss: 2.3136 2022/09/11 23:38:29 - mmengine - INFO - Epoch(train) [148][560/940] lr: 4.0000e-04 eta: 0:26:34 time: 0.7063 data_time: 0.0401 memory: 23708 grad_norm: 5.5764 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.4926 loss_aux: 0.9730 loss: 2.4656 2022/09/11 23:38:43 - mmengine - INFO - Epoch(train) [148][580/940] lr: 4.0000e-04 eta: 0:26:20 time: 0.7139 data_time: 0.0488 memory: 23708 grad_norm: 5.6990 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.2887 loss_aux: 0.8731 loss: 2.1618 2022/09/11 23:38:57 - mmengine - INFO - Epoch(train) [148][600/940] lr: 4.0000e-04 eta: 0:26:06 time: 0.6827 data_time: 0.0343 memory: 23708 grad_norm: 5.5438 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.3857 loss_aux: 0.9203 loss: 2.3060 2022/09/11 23:39:11 - mmengine - INFO - Epoch(train) [148][620/940] lr: 4.0000e-04 eta: 0:25:52 time: 0.7072 data_time: 0.0305 memory: 23708 grad_norm: 5.6325 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4157 loss_aux: 0.9459 loss: 2.3617 2022/09/11 23:39:25 - mmengine - INFO - Epoch(train) [148][640/940] lr: 4.0000e-04 eta: 0:25:38 time: 0.6904 data_time: 0.0337 memory: 23708 grad_norm: 5.6953 top1_acc: 0.5312 top5_acc: 0.8438 loss_cls: 1.2582 loss_aux: 0.8720 loss: 2.1303 2022/09/11 23:39:39 - mmengine - INFO - Epoch(train) [148][660/940] lr: 4.0000e-04 eta: 0:25:23 time: 0.7073 data_time: 0.0424 memory: 23708 grad_norm: 5.6297 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3587 loss_aux: 0.9390 loss: 2.2977 2022/09/11 23:39:53 - mmengine - INFO - Epoch(train) [148][680/940] lr: 4.0000e-04 eta: 0:25:09 time: 0.6920 data_time: 0.0406 memory: 23708 grad_norm: 5.6049 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4032 loss_aux: 0.9545 loss: 2.3577 2022/09/11 23:40:07 - mmengine - INFO - Epoch(train) [148][700/940] lr: 4.0000e-04 eta: 0:24:55 time: 0.7002 data_time: 0.0353 memory: 23708 grad_norm: 5.4794 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3040 loss_aux: 0.8960 loss: 2.2000 2022/09/11 23:40:21 - mmengine - INFO - Epoch(train) [148][720/940] lr: 4.0000e-04 eta: 0:24:41 time: 0.7102 data_time: 0.0400 memory: 23708 grad_norm: 5.5536 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.2415 loss_aux: 0.8513 loss: 2.0928 2022/09/11 23:40:35 - mmengine - INFO - Epoch(train) [148][740/940] lr: 4.0000e-04 eta: 0:24:27 time: 0.7068 data_time: 0.0402 memory: 23708 grad_norm: 5.5834 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.3574 loss_aux: 0.9271 loss: 2.2845 2022/09/11 23:40:49 - mmengine - INFO - Epoch(train) [148][760/940] lr: 4.0000e-04 eta: 0:24:13 time: 0.7088 data_time: 0.0348 memory: 23708 grad_norm: 5.6326 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.1966 loss_aux: 0.8496 loss: 2.0462 2022/09/11 23:41:04 - mmengine - INFO - Epoch(train) [148][780/940] lr: 4.0000e-04 eta: 0:23:59 time: 0.7257 data_time: 0.0397 memory: 23708 grad_norm: 5.5569 top1_acc: 0.7500 top5_acc: 0.7812 loss_cls: 1.4034 loss_aux: 0.9088 loss: 2.3122 2022/09/11 23:41:17 - mmengine - INFO - Epoch(train) [148][800/940] lr: 4.0000e-04 eta: 0:23:45 time: 0.6926 data_time: 0.0286 memory: 23708 grad_norm: 5.5624 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3007 loss_aux: 0.8882 loss: 2.1889 2022/09/11 23:41:31 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 23:41:31 - mmengine - INFO - Epoch(train) [148][820/940] lr: 4.0000e-04 eta: 0:23:31 time: 0.7004 data_time: 0.0329 memory: 23708 grad_norm: 5.6135 top1_acc: 0.6250 top5_acc: 0.7188 loss_cls: 1.4075 loss_aux: 0.9576 loss: 2.3651 2022/09/11 23:41:46 - mmengine - INFO - Epoch(train) [148][840/940] lr: 4.0000e-04 eta: 0:23:16 time: 0.7076 data_time: 0.0340 memory: 23708 grad_norm: 5.4322 top1_acc: 0.6875 top5_acc: 0.9375 loss_cls: 1.3514 loss_aux: 0.9275 loss: 2.2789 2022/09/11 23:42:00 - mmengine - INFO - Epoch(train) [148][860/940] lr: 4.0000e-04 eta: 0:23:02 time: 0.6972 data_time: 0.0460 memory: 23708 grad_norm: 5.6050 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4227 loss_aux: 0.9641 loss: 2.3868 2022/09/11 23:42:13 - mmengine - INFO - Epoch(train) [148][880/940] lr: 4.0000e-04 eta: 0:22:48 time: 0.6893 data_time: 0.0320 memory: 23708 grad_norm: 5.4755 top1_acc: 0.5312 top5_acc: 0.7812 loss_cls: 1.2845 loss_aux: 0.8884 loss: 2.1729 2022/09/11 23:42:28 - mmengine - INFO - Epoch(train) [148][900/940] lr: 4.0000e-04 eta: 0:22:34 time: 0.7534 data_time: 0.0294 memory: 23708 grad_norm: 5.6104 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.2630 loss_aux: 0.8637 loss: 2.1267 2022/09/11 23:42:42 - mmengine - INFO - Epoch(train) [148][920/940] lr: 4.0000e-04 eta: 0:22:20 time: 0.6810 data_time: 0.0338 memory: 23708 grad_norm: 5.5860 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3555 loss_aux: 0.9208 loss: 2.2763 2022/09/11 23:42:55 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 23:42:55 - mmengine - INFO - Epoch(train) [148][940/940] lr: 4.0000e-04 eta: 0:22:06 time: 0.6632 data_time: 0.0462 memory: 23708 grad_norm: 5.8849 top1_acc: 0.8571 top5_acc: 1.0000 loss_cls: 1.4128 loss_aux: 0.9451 loss: 2.3579 2022/09/11 23:42:55 - mmengine - INFO - Saving checkpoint at 148 epochs 2022/09/11 23:43:20 - mmengine - INFO - Epoch(train) [149][20/940] lr: 4.0000e-04 eta: 0:21:52 time: 0.9511 data_time: 0.2981 memory: 23708 grad_norm: 5.5940 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4956 loss_aux: 0.9954 loss: 2.4910 2022/09/11 23:43:34 - mmengine - INFO - Epoch(train) [149][40/940] lr: 4.0000e-04 eta: 0:21:38 time: 0.6967 data_time: 0.0321 memory: 23708 grad_norm: 5.5466 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.2830 loss_aux: 0.8689 loss: 2.1519 2022/09/11 23:43:48 - mmengine - INFO - Epoch(train) [149][60/940] lr: 4.0000e-04 eta: 0:21:24 time: 0.6940 data_time: 0.0371 memory: 23708 grad_norm: 5.5563 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.3593 loss_aux: 0.9346 loss: 2.2939 2022/09/11 23:44:01 - mmengine - INFO - Epoch(train) [149][80/940] lr: 4.0000e-04 eta: 0:21:10 time: 0.6847 data_time: 0.0323 memory: 23708 grad_norm: 5.5767 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3582 loss_aux: 0.9219 loss: 2.2801 2022/09/11 23:44:15 - mmengine - INFO - Epoch(train) [149][100/940] lr: 4.0000e-04 eta: 0:20:56 time: 0.6949 data_time: 0.0498 memory: 23708 grad_norm: 5.4441 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3839 loss_aux: 0.9384 loss: 2.3223 2022/09/11 23:44:29 - mmengine - INFO - Epoch(train) [149][120/940] lr: 4.0000e-04 eta: 0:20:41 time: 0.6957 data_time: 0.0322 memory: 23708 grad_norm: 5.6417 top1_acc: 0.6875 top5_acc: 0.8438 loss_cls: 1.4009 loss_aux: 0.9437 loss: 2.3446 2022/09/11 23:44:43 - mmengine - INFO - Epoch(train) [149][140/940] lr: 4.0000e-04 eta: 0:20:27 time: 0.7083 data_time: 0.0450 memory: 23708 grad_norm: 5.6435 top1_acc: 0.6250 top5_acc: 0.9688 loss_cls: 1.3001 loss_aux: 0.8783 loss: 2.1784 2022/09/11 23:44:57 - mmengine - INFO - Epoch(train) [149][160/940] lr: 4.0000e-04 eta: 0:20:13 time: 0.6837 data_time: 0.0372 memory: 23708 grad_norm: 5.6516 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3122 loss_aux: 0.9190 loss: 2.2311 2022/09/11 23:45:11 - mmengine - INFO - Epoch(train) [149][180/940] lr: 4.0000e-04 eta: 0:19:59 time: 0.7072 data_time: 0.0375 memory: 23708 grad_norm: 5.6222 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.3356 loss_aux: 0.9026 loss: 2.2381 2022/09/11 23:45:25 - mmengine - INFO - Epoch(train) [149][200/940] lr: 4.0000e-04 eta: 0:19:45 time: 0.6742 data_time: 0.0314 memory: 23708 grad_norm: 5.5211 top1_acc: 0.7500 top5_acc: 0.9062 loss_cls: 1.5150 loss_aux: 1.0385 loss: 2.5535 2022/09/11 23:45:38 - mmengine - INFO - Epoch(train) [149][220/940] lr: 4.0000e-04 eta: 0:19:31 time: 0.6879 data_time: 0.0409 memory: 23708 grad_norm: 5.5951 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.2774 loss_aux: 0.8634 loss: 2.1408 2022/09/11 23:45:52 - mmengine - INFO - Epoch(train) [149][240/940] lr: 4.0000e-04 eta: 0:19:17 time: 0.6913 data_time: 0.0328 memory: 23708 grad_norm: 5.6479 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4272 loss_aux: 0.9483 loss: 2.3755 2022/09/11 23:46:06 - mmengine - INFO - Epoch(train) [149][260/940] lr: 4.0000e-04 eta: 0:19:03 time: 0.7108 data_time: 0.0386 memory: 23708 grad_norm: 5.6103 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3945 loss_aux: 0.9157 loss: 2.3102 2022/09/11 23:46:21 - mmengine - INFO - Epoch(train) [149][280/940] lr: 4.0000e-04 eta: 0:18:48 time: 0.7020 data_time: 0.0308 memory: 23708 grad_norm: 5.6092 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.4248 loss_aux: 0.9643 loss: 2.3891 2022/09/11 23:46:34 - mmengine - INFO - Epoch(train) [149][300/940] lr: 4.0000e-04 eta: 0:18:34 time: 0.6981 data_time: 0.0403 memory: 23708 grad_norm: 5.6236 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3186 loss_aux: 0.8991 loss: 2.2177 2022/09/11 23:46:49 - mmengine - INFO - Epoch(train) [149][320/940] lr: 4.0000e-04 eta: 0:18:20 time: 0.7050 data_time: 0.0353 memory: 23708 grad_norm: 5.5654 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4378 loss_aux: 0.9710 loss: 2.4088 2022/09/11 23:47:03 - mmengine - INFO - Epoch(train) [149][340/940] lr: 4.0000e-04 eta: 0:18:06 time: 0.7188 data_time: 0.0387 memory: 23708 grad_norm: 5.6302 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3477 loss_aux: 0.9231 loss: 2.2709 2022/09/11 23:47:17 - mmengine - INFO - Epoch(train) [149][360/940] lr: 4.0000e-04 eta: 0:17:52 time: 0.6947 data_time: 0.0316 memory: 23708 grad_norm: 5.5280 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3187 loss_aux: 0.9065 loss: 2.2252 2022/09/11 23:47:31 - mmengine - INFO - Epoch(train) [149][380/940] lr: 4.0000e-04 eta: 0:17:38 time: 0.7088 data_time: 0.0474 memory: 23708 grad_norm: 5.6016 top1_acc: 0.5312 top5_acc: 0.6875 loss_cls: 1.2479 loss_aux: 0.8632 loss: 2.1111 2022/09/11 23:47:45 - mmengine - INFO - Epoch(train) [149][400/940] lr: 4.0000e-04 eta: 0:17:24 time: 0.6981 data_time: 0.0288 memory: 23708 grad_norm: 5.6426 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.4100 loss_aux: 0.8870 loss: 2.2970 2022/09/11 23:47:59 - mmengine - INFO - Epoch(train) [149][420/940] lr: 4.0000e-04 eta: 0:17:10 time: 0.7027 data_time: 0.0289 memory: 23708 grad_norm: 5.6190 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.2808 loss_aux: 0.8881 loss: 2.1690 2022/09/11 23:48:13 - mmengine - INFO - Epoch(train) [149][440/940] lr: 4.0000e-04 eta: 0:16:56 time: 0.7059 data_time: 0.0337 memory: 23708 grad_norm: 5.6222 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3577 loss_aux: 0.9170 loss: 2.2747 2022/09/11 23:48:27 - mmengine - INFO - Epoch(train) [149][460/940] lr: 4.0000e-04 eta: 0:16:41 time: 0.7051 data_time: 0.0431 memory: 23708 grad_norm: 5.5855 top1_acc: 0.5000 top5_acc: 0.8125 loss_cls: 1.3492 loss_aux: 0.9537 loss: 2.3029 2022/09/11 23:48:41 - mmengine - INFO - Epoch(train) [149][480/940] lr: 4.0000e-04 eta: 0:16:27 time: 0.6958 data_time: 0.0283 memory: 23708 grad_norm: 5.6808 top1_acc: 0.7500 top5_acc: 0.8438 loss_cls: 1.2932 loss_aux: 0.9159 loss: 2.2091 2022/09/11 23:48:56 - mmengine - INFO - Epoch(train) [149][500/940] lr: 4.0000e-04 eta: 0:16:13 time: 0.7150 data_time: 0.0339 memory: 23708 grad_norm: 5.6186 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3412 loss_aux: 0.9273 loss: 2.2684 2022/09/11 23:49:10 - mmengine - INFO - Epoch(train) [149][520/940] lr: 4.0000e-04 eta: 0:15:59 time: 0.7091 data_time: 0.0370 memory: 23708 grad_norm: 5.6281 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3540 loss_aux: 0.9275 loss: 2.2814 2022/09/11 23:49:24 - mmengine - INFO - Epoch(train) [149][540/940] lr: 4.0000e-04 eta: 0:15:45 time: 0.7204 data_time: 0.0520 memory: 23708 grad_norm: 5.6503 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3505 loss_aux: 0.8848 loss: 2.2353 2022/09/11 23:49:38 - mmengine - INFO - Epoch(train) [149][560/940] lr: 4.0000e-04 eta: 0:15:31 time: 0.6925 data_time: 0.0316 memory: 23708 grad_norm: 5.5137 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.2579 loss_aux: 0.8761 loss: 2.1341 2022/09/11 23:49:52 - mmengine - INFO - Epoch(train) [149][580/940] lr: 4.0000e-04 eta: 0:15:17 time: 0.7091 data_time: 0.0342 memory: 23708 grad_norm: 5.5531 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2357 loss_aux: 0.8582 loss: 2.0939 2022/09/11 23:50:06 - mmengine - INFO - Epoch(train) [149][600/940] lr: 4.0000e-04 eta: 0:15:03 time: 0.7003 data_time: 0.0364 memory: 23708 grad_norm: 5.6272 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2831 loss_aux: 0.8876 loss: 2.1707 2022/09/11 23:50:21 - mmengine - INFO - Epoch(train) [149][620/940] lr: 4.0000e-04 eta: 0:14:49 time: 0.7104 data_time: 0.0437 memory: 23708 grad_norm: 5.6637 top1_acc: 0.6562 top5_acc: 0.7812 loss_cls: 1.2182 loss_aux: 0.8183 loss: 2.0365 2022/09/11 23:50:34 - mmengine - INFO - Epoch(train) [149][640/940] lr: 4.0000e-04 eta: 0:14:34 time: 0.6970 data_time: 0.0420 memory: 23708 grad_norm: 5.6145 top1_acc: 0.7812 top5_acc: 0.9062 loss_cls: 1.3758 loss_aux: 0.9196 loss: 2.2954 2022/09/11 23:50:49 - mmengine - INFO - Epoch(train) [149][660/940] lr: 4.0000e-04 eta: 0:14:20 time: 0.7083 data_time: 0.0314 memory: 23708 grad_norm: 5.5951 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3274 loss_aux: 0.9041 loss: 2.2315 2022/09/11 23:51:03 - mmengine - INFO - Epoch(train) [149][680/940] lr: 4.0000e-04 eta: 0:14:06 time: 0.7098 data_time: 0.0402 memory: 23708 grad_norm: 5.6566 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3345 loss_aux: 0.8931 loss: 2.2276 2022/09/11 23:51:17 - mmengine - INFO - Epoch(train) [149][700/940] lr: 4.0000e-04 eta: 0:13:52 time: 0.7011 data_time: 0.0488 memory: 23708 grad_norm: 5.6196 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3528 loss_aux: 0.9215 loss: 2.2742 2022/09/11 23:51:31 - mmengine - INFO - Epoch(train) [149][720/940] lr: 4.0000e-04 eta: 0:13:38 time: 0.6918 data_time: 0.0335 memory: 23708 grad_norm: 5.7429 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3152 loss_aux: 0.8738 loss: 2.1891 2022/09/11 23:51:45 - mmengine - INFO - Epoch(train) [149][740/940] lr: 4.0000e-04 eta: 0:13:24 time: 0.7041 data_time: 0.0321 memory: 23708 grad_norm: 5.5601 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3333 loss_aux: 0.9358 loss: 2.2691 2022/09/11 23:51:59 - mmengine - INFO - Epoch(train) [149][760/940] lr: 4.0000e-04 eta: 0:13:10 time: 0.7093 data_time: 0.0348 memory: 23708 grad_norm: 5.4229 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.2427 loss_aux: 0.8675 loss: 2.1103 2022/09/11 23:52:13 - mmengine - INFO - Epoch(train) [149][780/940] lr: 4.0000e-04 eta: 0:12:56 time: 0.7094 data_time: 0.0462 memory: 23708 grad_norm: 5.6758 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.3486 loss_aux: 0.9302 loss: 2.2787 2022/09/11 23:52:27 - mmengine - INFO - Epoch(train) [149][800/940] lr: 4.0000e-04 eta: 0:12:42 time: 0.7029 data_time: 0.0314 memory: 23708 grad_norm: 5.6242 top1_acc: 0.6250 top5_acc: 0.7812 loss_cls: 1.3792 loss_aux: 0.9591 loss: 2.3382 2022/09/11 23:52:41 - mmengine - INFO - Epoch(train) [149][820/940] lr: 4.0000e-04 eta: 0:12:27 time: 0.7008 data_time: 0.0338 memory: 23708 grad_norm: 5.5560 top1_acc: 0.9062 top5_acc: 0.9688 loss_cls: 1.2064 loss_aux: 0.8454 loss: 2.0517 2022/09/11 23:52:55 - mmengine - INFO - Epoch(train) [149][840/940] lr: 4.0000e-04 eta: 0:12:13 time: 0.7042 data_time: 0.0348 memory: 23708 grad_norm: 5.6085 top1_acc: 0.5625 top5_acc: 0.8438 loss_cls: 1.4077 loss_aux: 0.9556 loss: 2.3633 2022/09/11 23:53:09 - mmengine - INFO - Epoch(train) [149][860/940] lr: 4.0000e-04 eta: 0:11:59 time: 0.6979 data_time: 0.0433 memory: 23708 grad_norm: 5.6295 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3263 loss_aux: 0.9178 loss: 2.2441 2022/09/11 23:53:23 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 23:53:23 - mmengine - INFO - Epoch(train) [149][880/940] lr: 4.0000e-04 eta: 0:11:45 time: 0.6919 data_time: 0.0356 memory: 23708 grad_norm: 5.6805 top1_acc: 0.8125 top5_acc: 0.8438 loss_cls: 1.2538 loss_aux: 0.8566 loss: 2.1104 2022/09/11 23:53:37 - mmengine - INFO - Epoch(train) [149][900/940] lr: 4.0000e-04 eta: 0:11:31 time: 0.7026 data_time: 0.0348 memory: 23708 grad_norm: 5.6102 top1_acc: 0.5938 top5_acc: 0.8438 loss_cls: 1.4457 loss_aux: 0.9544 loss: 2.4001 2022/09/11 23:53:51 - mmengine - INFO - Epoch(train) [149][920/940] lr: 4.0000e-04 eta: 0:11:17 time: 0.7090 data_time: 0.0391 memory: 23708 grad_norm: 5.7402 top1_acc: 0.7500 top5_acc: 0.9688 loss_cls: 1.2186 loss_aux: 0.8224 loss: 2.0411 2022/09/11 23:54:04 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/11 23:54:04 - mmengine - INFO - Epoch(train) [149][940/940] lr: 4.0000e-04 eta: 0:11:03 time: 0.6454 data_time: 0.0376 memory: 23708 grad_norm: 5.9516 top1_acc: 0.5714 top5_acc: 0.8571 loss_cls: 1.4824 loss_aux: 0.9664 loss: 2.4488 2022/09/11 23:54:04 - mmengine - INFO - Saving checkpoint at 149 epochs 2022/09/11 23:54:30 - mmengine - INFO - Epoch(train) [150][20/940] lr: 4.0000e-04 eta: 0:10:49 time: 0.9898 data_time: 0.3294 memory: 23708 grad_norm: 5.6419 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3511 loss_aux: 0.9299 loss: 2.2810 2022/09/11 23:54:43 - mmengine - INFO - Epoch(train) [150][40/940] lr: 4.0000e-04 eta: 0:10:35 time: 0.6746 data_time: 0.0258 memory: 23708 grad_norm: 5.5237 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3123 loss_aux: 0.8677 loss: 2.1800 2022/09/11 23:54:57 - mmengine - INFO - Epoch(train) [150][60/940] lr: 4.0000e-04 eta: 0:10:20 time: 0.6658 data_time: 0.0364 memory: 23708 grad_norm: 5.6737 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3274 loss_aux: 0.8870 loss: 2.2143 2022/09/11 23:55:11 - mmengine - INFO - Epoch(train) [150][80/940] lr: 4.0000e-04 eta: 0:10:06 time: 0.6867 data_time: 0.0366 memory: 23708 grad_norm: 5.6064 top1_acc: 0.5625 top5_acc: 0.8125 loss_cls: 1.4155 loss_aux: 0.9557 loss: 2.3711 2022/09/11 23:55:24 - mmengine - INFO - Epoch(train) [150][100/940] lr: 4.0000e-04 eta: 0:09:52 time: 0.6922 data_time: 0.0404 memory: 23708 grad_norm: 5.6056 top1_acc: 0.6875 top5_acc: 0.9062 loss_cls: 1.3152 loss_aux: 0.9268 loss: 2.2419 2022/09/11 23:55:38 - mmengine - INFO - Epoch(train) [150][120/940] lr: 4.0000e-04 eta: 0:09:38 time: 0.6854 data_time: 0.0301 memory: 23708 grad_norm: 5.5613 top1_acc: 0.6875 top5_acc: 0.8125 loss_cls: 1.3095 loss_aux: 0.8753 loss: 2.1847 2022/09/11 23:55:52 - mmengine - INFO - Epoch(train) [150][140/940] lr: 4.0000e-04 eta: 0:09:24 time: 0.6792 data_time: 0.0423 memory: 23708 grad_norm: 5.6043 top1_acc: 0.7188 top5_acc: 0.8750 loss_cls: 1.4618 loss_aux: 0.9669 loss: 2.4287 2022/09/11 23:56:05 - mmengine - INFO - Epoch(train) [150][160/940] lr: 4.0000e-04 eta: 0:09:10 time: 0.6747 data_time: 0.0372 memory: 23708 grad_norm: 5.7137 top1_acc: 0.5938 top5_acc: 0.7500 loss_cls: 1.3431 loss_aux: 0.9432 loss: 2.2863 2022/09/11 23:56:19 - mmengine - INFO - Epoch(train) [150][180/940] lr: 4.0000e-04 eta: 0:08:56 time: 0.7015 data_time: 0.0371 memory: 23708 grad_norm: 5.6403 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3972 loss_aux: 0.9458 loss: 2.3430 2022/09/11 23:56:33 - mmengine - INFO - Epoch(train) [150][200/940] lr: 4.0000e-04 eta: 0:08:42 time: 0.6877 data_time: 0.0340 memory: 23708 grad_norm: 5.4961 top1_acc: 0.7188 top5_acc: 0.9688 loss_cls: 1.3491 loss_aux: 0.9137 loss: 2.2628 2022/09/11 23:56:46 - mmengine - INFO - Epoch(train) [150][220/940] lr: 4.0000e-04 eta: 0:08:27 time: 0.6715 data_time: 0.0330 memory: 23708 grad_norm: 5.5973 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3182 loss_aux: 0.9010 loss: 2.2192 2022/09/11 23:57:00 - mmengine - INFO - Epoch(train) [150][240/940] lr: 4.0000e-04 eta: 0:08:13 time: 0.6784 data_time: 0.0410 memory: 23708 grad_norm: 5.5289 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3144 loss_aux: 0.9117 loss: 2.2260 2022/09/11 23:57:14 - mmengine - INFO - Epoch(train) [150][260/940] lr: 4.0000e-04 eta: 0:07:59 time: 0.7059 data_time: 0.0377 memory: 23708 grad_norm: 5.6131 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.2357 loss_aux: 0.8784 loss: 2.1141 2022/09/11 23:57:27 - mmengine - INFO - Epoch(train) [150][280/940] lr: 4.0000e-04 eta: 0:07:45 time: 0.6664 data_time: 0.0296 memory: 23708 grad_norm: 5.5499 top1_acc: 0.8125 top5_acc: 0.8125 loss_cls: 1.3129 loss_aux: 0.9030 loss: 2.2159 2022/09/11 23:57:41 - mmengine - INFO - Epoch(train) [150][300/940] lr: 4.0000e-04 eta: 0:07:31 time: 0.6746 data_time: 0.0366 memory: 23708 grad_norm: 5.6823 top1_acc: 0.6562 top5_acc: 0.9062 loss_cls: 1.2778 loss_aux: 0.8476 loss: 2.1255 2022/09/11 23:57:55 - mmengine - INFO - Epoch(train) [150][320/940] lr: 4.0000e-04 eta: 0:07:17 time: 0.6952 data_time: 0.0369 memory: 23708 grad_norm: 5.6661 top1_acc: 0.5312 top5_acc: 0.7500 loss_cls: 1.4946 loss_aux: 1.0005 loss: 2.4950 2022/09/11 23:58:09 - mmengine - INFO - Epoch(train) [150][340/940] lr: 4.0000e-04 eta: 0:07:03 time: 0.6860 data_time: 0.0366 memory: 23708 grad_norm: 5.6287 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.2475 loss_aux: 0.8659 loss: 2.1134 2022/09/11 23:58:22 - mmengine - INFO - Epoch(train) [150][360/940] lr: 4.0000e-04 eta: 0:06:49 time: 0.6877 data_time: 0.0298 memory: 23708 grad_norm: 5.6791 top1_acc: 0.6250 top5_acc: 0.8125 loss_cls: 1.3080 loss_aux: 0.8519 loss: 2.1598 2022/09/11 23:58:36 - mmengine - INFO - Epoch(train) [150][380/940] lr: 4.0000e-04 eta: 0:06:35 time: 0.6702 data_time: 0.0354 memory: 23708 grad_norm: 5.6400 top1_acc: 0.8438 top5_acc: 0.9375 loss_cls: 1.3195 loss_aux: 0.9078 loss: 2.2273 2022/09/11 23:58:50 - mmengine - INFO - Epoch(train) [150][400/940] lr: 4.0000e-04 eta: 0:06:20 time: 0.7016 data_time: 0.0439 memory: 23708 grad_norm: 5.6184 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.2712 loss_aux: 0.8838 loss: 2.1550 2022/09/11 23:59:04 - mmengine - INFO - Epoch(train) [150][420/940] lr: 4.0000e-04 eta: 0:06:06 time: 0.6963 data_time: 0.0464 memory: 23708 grad_norm: 5.6403 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3244 loss_aux: 0.9225 loss: 2.2469 2022/09/11 23:59:17 - mmengine - INFO - Epoch(train) [150][440/940] lr: 4.0000e-04 eta: 0:05:52 time: 0.6690 data_time: 0.0313 memory: 23708 grad_norm: 5.5879 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.3492 loss_aux: 0.9390 loss: 2.2881 2022/09/11 23:59:31 - mmengine - INFO - Epoch(train) [150][460/940] lr: 4.0000e-04 eta: 0:05:38 time: 0.6725 data_time: 0.0344 memory: 23708 grad_norm: 5.6566 top1_acc: 0.5938 top5_acc: 0.8750 loss_cls: 1.3278 loss_aux: 0.9177 loss: 2.2455 2022/09/11 23:59:44 - mmengine - INFO - Epoch(train) [150][480/940] lr: 4.0000e-04 eta: 0:05:24 time: 0.6802 data_time: 0.0387 memory: 23708 grad_norm: 5.7233 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.4275 loss_aux: 0.9532 loss: 2.3807 2022/09/11 23:59:58 - mmengine - INFO - Epoch(train) [150][500/940] lr: 4.0000e-04 eta: 0:05:10 time: 0.6893 data_time: 0.0378 memory: 23708 grad_norm: 5.6286 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3958 loss_aux: 0.9482 loss: 2.3440 2022/09/12 00:00:15 - mmengine - INFO - Epoch(train) [150][520/940] lr: 4.0000e-04 eta: 0:04:56 time: 0.8624 data_time: 0.1129 memory: 23708 grad_norm: 5.6381 top1_acc: 0.5938 top5_acc: 0.7812 loss_cls: 1.3885 loss_aux: 0.9524 loss: 2.3409 2022/09/12 00:00:29 - mmengine - INFO - Epoch(train) [150][540/940] lr: 4.0000e-04 eta: 0:04:42 time: 0.7120 data_time: 0.0455 memory: 23708 grad_norm: 5.6216 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3350 loss_aux: 0.9010 loss: 2.2360 2022/09/12 00:00:43 - mmengine - INFO - Epoch(train) [150][560/940] lr: 4.0000e-04 eta: 0:04:28 time: 0.6850 data_time: 0.0372 memory: 23708 grad_norm: 5.6497 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3983 loss_aux: 0.9433 loss: 2.3416 2022/09/12 00:00:57 - mmengine - INFO - Epoch(train) [150][580/940] lr: 4.0000e-04 eta: 0:04:13 time: 0.6953 data_time: 0.0389 memory: 23708 grad_norm: 5.6361 top1_acc: 0.7812 top5_acc: 0.8750 loss_cls: 1.4103 loss_aux: 0.9319 loss: 2.3422 2022/09/12 00:01:11 - mmengine - INFO - Epoch(train) [150][600/940] lr: 4.0000e-04 eta: 0:03:59 time: 0.7091 data_time: 0.0320 memory: 23708 grad_norm: 5.6086 top1_acc: 0.4688 top5_acc: 0.8125 loss_cls: 1.3263 loss_aux: 0.9034 loss: 2.2298 2022/09/12 00:01:25 - mmengine - INFO - Epoch(train) [150][620/940] lr: 4.0000e-04 eta: 0:03:45 time: 0.6905 data_time: 0.0336 memory: 23708 grad_norm: 5.5958 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3738 loss_aux: 0.9281 loss: 2.3019 2022/09/12 00:01:39 - mmengine - INFO - Epoch(train) [150][640/940] lr: 4.0000e-04 eta: 0:03:31 time: 0.6813 data_time: 0.0370 memory: 23708 grad_norm: 5.5781 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.2803 loss_aux: 0.8396 loss: 2.1199 2022/09/12 00:01:53 - mmengine - INFO - Epoch(train) [150][660/940] lr: 4.0000e-04 eta: 0:03:17 time: 0.6956 data_time: 0.0431 memory: 23708 grad_norm: 5.6517 top1_acc: 0.6562 top5_acc: 0.8750 loss_cls: 1.3205 loss_aux: 0.9147 loss: 2.2352 2022/09/12 00:02:06 - mmengine - INFO - Epoch(train) [150][680/940] lr: 4.0000e-04 eta: 0:03:03 time: 0.6724 data_time: 0.0317 memory: 23708 grad_norm: 5.5678 top1_acc: 0.6875 top5_acc: 0.9688 loss_cls: 1.3270 loss_aux: 0.9201 loss: 2.2471 2022/09/12 00:02:20 - mmengine - INFO - Epoch(train) [150][700/940] lr: 4.0000e-04 eta: 0:02:49 time: 0.6940 data_time: 0.0333 memory: 23708 grad_norm: 5.6639 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.3852 loss_aux: 0.9041 loss: 2.2893 2022/09/12 00:02:34 - mmengine - INFO - Epoch(train) [150][720/940] lr: 4.0000e-04 eta: 0:02:35 time: 0.6820 data_time: 0.0387 memory: 23708 grad_norm: 5.6263 top1_acc: 0.6250 top5_acc: 0.9062 loss_cls: 1.3000 loss_aux: 0.8646 loss: 2.1646 2022/09/12 00:02:48 - mmengine - INFO - Epoch(train) [150][740/940] lr: 4.0000e-04 eta: 0:02:21 time: 0.7017 data_time: 0.0382 memory: 23708 grad_norm: 5.5935 top1_acc: 0.6250 top5_acc: 0.8438 loss_cls: 1.4163 loss_aux: 0.9450 loss: 2.3613 2022/09/12 00:03:02 - mmengine - INFO - Epoch(train) [150][760/940] lr: 4.0000e-04 eta: 0:02:06 time: 0.6992 data_time: 0.0338 memory: 23708 grad_norm: 5.6674 top1_acc: 0.7188 top5_acc: 0.8125 loss_cls: 1.3561 loss_aux: 0.9050 loss: 2.2611 2022/09/12 00:03:16 - mmengine - INFO - Epoch(train) [150][780/940] lr: 4.0000e-04 eta: 0:01:52 time: 0.7073 data_time: 0.0350 memory: 23708 grad_norm: 5.5915 top1_acc: 0.8125 top5_acc: 0.8750 loss_cls: 1.3362 loss_aux: 0.9266 loss: 2.2628 2022/09/12 00:03:30 - mmengine - INFO - Epoch(train) [150][800/940] lr: 4.0000e-04 eta: 0:01:38 time: 0.7031 data_time: 0.0455 memory: 23708 grad_norm: 5.5851 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3572 loss_aux: 0.9104 loss: 2.2677 2022/09/12 00:03:44 - mmengine - INFO - Epoch(train) [150][820/940] lr: 4.0000e-04 eta: 0:01:24 time: 0.6974 data_time: 0.0411 memory: 23708 grad_norm: 5.5259 top1_acc: 0.5938 top5_acc: 0.8125 loss_cls: 1.3193 loss_aux: 0.8917 loss: 2.2110 2022/09/12 00:03:58 - mmengine - INFO - Epoch(train) [150][840/940] lr: 4.0000e-04 eta: 0:01:10 time: 0.6865 data_time: 0.0343 memory: 23708 grad_norm: 5.6450 top1_acc: 0.7188 top5_acc: 0.8438 loss_cls: 1.3332 loss_aux: 0.9106 loss: 2.2438 2022/09/12 00:04:11 - mmengine - INFO - Epoch(train) [150][860/940] lr: 4.0000e-04 eta: 0:00:56 time: 0.6950 data_time: 0.0333 memory: 23708 grad_norm: 5.6491 top1_acc: 0.6562 top5_acc: 0.8438 loss_cls: 1.3520 loss_aux: 0.9189 loss: 2.2709 2022/09/12 00:04:25 - mmengine - INFO - Epoch(train) [150][880/940] lr: 4.0000e-04 eta: 0:00:42 time: 0.6904 data_time: 0.0386 memory: 23708 grad_norm: 5.6332 top1_acc: 0.7500 top5_acc: 0.9375 loss_cls: 1.1858 loss_aux: 0.8318 loss: 2.0176 2022/09/12 00:04:39 - mmengine - INFO - Epoch(train) [150][900/940] lr: 4.0000e-04 eta: 0:00:28 time: 0.7008 data_time: 0.0368 memory: 23708 grad_norm: 5.5856 top1_acc: 0.7188 top5_acc: 0.9062 loss_cls: 1.3207 loss_aux: 0.8996 loss: 2.2203 2022/09/12 00:04:53 - mmengine - INFO - Epoch(train) [150][920/940] lr: 4.0000e-04 eta: 0:00:14 time: 0.6845 data_time: 0.0289 memory: 23708 grad_norm: 5.5839 top1_acc: 0.6875 top5_acc: 0.8750 loss_cls: 1.4554 loss_aux: 0.9694 loss: 2.4249 2022/09/12 00:05:06 - mmengine - INFO - Exp name: tpn-slowonly_r50_8xb8-8x8x1-150e_kinetics400-rgb_20220911_165647 2022/09/12 00:05:06 - mmengine - INFO - Epoch(train) [150][940/940] lr: 4.0000e-04 eta: 0:00:00 time: 0.6445 data_time: 0.0281 memory: 23708 grad_norm: 5.9574 top1_acc: 0.8571 top5_acc: 0.8571 loss_cls: 1.3976 loss_aux: 0.9505 loss: 2.3481 2022/09/12 00:05:06 - mmengine - INFO - Saving checkpoint at 150 epochs 2022/09/12 00:05:16 - mmengine - INFO - Epoch(val) [150][20/310] eta: 0:01:02 time: 0.2153 data_time: 0.1359 memory: 2130 2022/09/12 00:05:18 - mmengine - INFO - Epoch(val) [150][40/310] eta: 0:00:38 time: 0.1414 data_time: 0.0644 memory: 2130 2022/09/12 00:05:22 - mmengine - INFO - Epoch(val) [150][60/310] eta: 0:00:40 time: 0.1611 data_time: 0.0812 memory: 2130 2022/09/12 00:05:25 - mmengine - INFO - Epoch(val) [150][80/310] eta: 0:00:33 time: 0.1439 data_time: 0.0659 memory: 2130 2022/09/12 00:05:28 - mmengine - INFO - Epoch(val) [150][100/310] eta: 0:00:34 time: 0.1642 data_time: 0.0871 memory: 2130 2022/09/12 00:05:31 - mmengine - INFO - Epoch(val) [150][120/310] eta: 0:00:28 time: 0.1478 data_time: 0.0653 memory: 2130 2022/09/12 00:05:35 - mmengine - INFO - Epoch(val) [150][140/310] eta: 0:00:31 time: 0.1875 data_time: 0.1066 memory: 2130 2022/09/12 00:05:39 - mmengine - INFO - Epoch(val) [150][160/310] eta: 0:00:31 time: 0.2121 data_time: 0.1348 memory: 2130 2022/09/12 00:05:42 - mmengine - INFO - Epoch(val) [150][180/310] eta: 0:00:19 time: 0.1509 data_time: 0.0721 memory: 2130 2022/09/12 00:05:45 - mmengine - INFO - Epoch(val) [150][200/310] eta: 0:00:16 time: 0.1545 data_time: 0.0755 memory: 2130 2022/09/12 00:05:48 - mmengine - INFO - Epoch(val) [150][220/310] eta: 0:00:12 time: 0.1347 data_time: 0.0552 memory: 2130 2022/09/12 00:05:51 - mmengine - INFO - Epoch(val) [150][240/310] eta: 0:00:10 time: 0.1531 data_time: 0.0759 memory: 2130 2022/09/12 00:05:54 - mmengine - INFO - Epoch(val) [150][260/310] eta: 0:00:07 time: 0.1596 data_time: 0.0814 memory: 2130 2022/09/12 00:05:56 - mmengine - INFO - Epoch(val) [150][280/310] eta: 0:00:03 time: 0.1271 data_time: 0.0530 memory: 2130 2022/09/12 00:05:59 - mmengine - INFO - Epoch(val) [150][300/310] eta: 0:00:01 time: 0.1152 data_time: 0.0427 memory: 2130 2022/09/12 00:06:01 - mmengine - INFO - Epoch(val) [150][310/310] acc/top1: 0.6616 acc/top5: 0.8664 acc/mean1: 0.6615