2022/09/08 10:54:17 - 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: 748239878 GPU 0,1,2,3,4,5,6,7: A100-SXM-80GB CUDA_HOME: /mnt/cache/share/cuda-11.1 NVCC: Cuda compilation tools, release 11.1, V11.1.74 GCC: gcc (GCC) 5.4.0 PyTorch: 1.9.0+cu111 PyTorch compiling details: PyTorch built with: - GCC 7.3 - C++ Version: 201402 - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.1.2 (Git Hash 98be7e8afa711dc9b66c8ff3504129cb82013cdb) - OpenMP 201511 (a.k.a. OpenMP 4.5) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86 - CuDNN 8.0.5 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.9.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, TorchVision: 0.10.0+cu111 OpenCV: 4.6.0 MMEngine: 0.1.0 Runtime environment: cudnn_benchmark: False mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: None Distributed launcher: slurm Distributed training: True GPU number: 8 ------------------------------------------------------------ 2022/09/08 10:54:17 - mmengine - INFO - Config: preprocess_cfg = dict( mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], format_shape='NCHW') model = dict( type='Recognizer2D', backbone=dict( type='ResNetTIN', pretrained='torchvision://resnet50', depth=50, norm_eval=False, shift_div=4), cls_head=dict( type='TSMHead', num_classes=174, in_channels=2048, spatial_type='avg', consensus=dict(type='AvgConsensus', dim=1), dropout_ratio=0.8, init_std=0.001, is_shift=False, average_clips='prob'), data_preprocessor=dict( type='ActionDataPreprocessor', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], format_shape='NCHW'), train_cfg=None, test_cfg=dict(average_clips=None)) default_scope = 'mmaction' default_hooks = dict( runtime_info=dict(type='RuntimeInfoHook'), timer=dict(type='IterTimerHook'), logger=dict(type='LoggerHook', interval=20, ignore_last=False), param_scheduler=dict(type='ParamSchedulerHook'), checkpoint=dict(type='CheckpointHook', interval=-1, save_best='auto'), sampler_seed=dict(type='DistSamplerSeedHook')) env_cfg = dict( cudnn_benchmark=False, mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0), dist_cfg=dict(backend='nccl')) log_processor = dict(type='LogProcessor', window_size=20, by_epoch=True) vis_backends = [dict(type='LocalVisBackend')] visualizer = dict( type='ActionVisualizer', vis_backends=[dict(type='LocalVisBackend')]) log_level = 'INFO' load_from = None resume = False file_client_args = dict( io_backend='petrel', path_mapping=dict( {'data/sthv2': 's254:s3://openmmlab/datasets/action/sthv2'})) dataset_type = 'VideoDataset' data_root = 'data/sthv2/videos' data_root_val = 'data/sthv2/videos' ann_file_train = 'data/sthv2/sthv2_train_list_videos.txt' ann_file_val = 'data/sthv2/sthv2_val_list_videos.txt' ann_file_test = 'data/sthv2/sthv2_val_list_videos.txt' train_pipeline = [ dict( type='DecordInit', io_backend='petrel', path_mapping=dict( {'data/sthv2': 's254:s3://openmmlab/datasets/action/sthv2'})), dict(type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict( type='MultiScaleCrop', input_size=224, scales=(1, 0.875, 0.75, 0.66), random_crop=False, max_wh_scale_gap=1), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ] val_pipeline = [ dict( type='DecordInit', io_backend='petrel', path_mapping=dict( {'data/sthv2': 's254:s3://openmmlab/datasets/action/sthv2'})), dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ] test_pipeline = [ dict( type='DecordInit', io_backend='petrel', path_mapping=dict( {'data/sthv2': 's254:s3://openmmlab/datasets/action/sthv2'})), dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ] train_dataloader = dict( batch_size=24, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='VideoDataset', ann_file='data/sthv2/sthv2_train_list_videos.txt', data_prefix=dict(video='data/sthv2/videos'), pipeline=[ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/sthv2': 's254:s3://openmmlab/datasets/action/sthv2' })), dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict( type='MultiScaleCrop', input_size=224, scales=(1, 0.875, 0.75, 0.66), random_crop=False, max_wh_scale_gap=1), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ])) val_dataloader = dict( batch_size=24, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='VideoDataset', ann_file='data/sthv2/sthv2_val_list_videos.txt', data_prefix=dict(video='data/sthv2/videos'), pipeline=[ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/sthv2': 's254:s3://openmmlab/datasets/action/sthv2' })), dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ], test_mode=True)) test_dataloader = dict( batch_size=1, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='VideoDataset', ann_file='data/sthv2/sthv2_val_list_videos.txt', data_prefix=dict(video='data/sthv2/videos'), pipeline=[ dict( type='DecordInit', io_backend='petrel', path_mapping=dict({ 'data/sthv2': 's254:s3://openmmlab/datasets/action/sthv2' })), dict( type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCHW'), dict(type='PackActionInputs') ], test_mode=True)) val_evaluator = dict(type='AccMetric') test_evaluator = dict(type='AccMetric') optim_wrapper = dict( optimizer=dict(type='SGD', lr=0.04, momentum=0.9, weight_decay=0.0005), constructor='TSMOptimWrapperConstructor', paramwise_cfg=dict(fc_lr5=True), clip_grad=dict(max_norm=20, norm_type=2)) param_scheduler = [ dict( type='LinearLR', start_factor=0.1, by_epoch=True, begin=0, end=1, convert_to_iter_based=True), dict( type='CosineAnnealingLR', T_max=39, eta_min=0, by_epoch=True, begin=1, end=40) ] train_cfg = dict( type='EpochBasedTrainLoop', max_epochs=40, val_begin=1, val_interval=2) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') launcher = 'slurm' work_dir = 'work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4' 2022/09/08 10:54:20 - mmengine - INFO - These parameters in pretrained checkpoint are not loaded: {'fc.weight', 'fc.bias'} 2022/09/08 10:54:22 - mmengine - INFO - Checkpoints will be saved to /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4 by HardDiskBackend. 2022/09/08 10:55:08 - mmengine - INFO - Epoch(train) [1][20/880] lr: 4.7782e-03 eta: 22:19:55 time: 2.2853 data_time: 1.7757 memory: 23498 grad_norm: 2.4126 top1_acc: 0.0000 top5_acc: 0.0833 loss_cls: 5.0977 loss: 5.0977 2022/09/08 10:55:17 - mmengine - INFO - Epoch(train) [1][40/880] lr: 5.5973e-03 eta: 13:22:45 time: 0.4545 data_time: 0.0222 memory: 23498 grad_norm: 2.5594 top1_acc: 0.0417 top5_acc: 0.1250 loss_cls: 5.0602 loss: 5.0602 2022/09/08 10:55:26 - mmengine - INFO - Epoch(train) [1][60/880] lr: 6.4164e-03 eta: 10:23:21 time: 0.4533 data_time: 0.0188 memory: 23498 grad_norm: 2.8772 top1_acc: 0.0833 top5_acc: 0.1250 loss_cls: 4.8741 loss: 4.8741 2022/09/08 10:55:35 - mmengine - INFO - Epoch(train) [1][80/880] lr: 7.2355e-03 eta: 8:52:11 time: 0.4437 data_time: 0.0186 memory: 23498 grad_norm: 3.0264 top1_acc: 0.0833 top5_acc: 0.2917 loss_cls: 4.7332 loss: 4.7332 2022/09/08 10:55:43 - mmengine - INFO - Epoch(train) [1][100/880] lr: 8.0546e-03 eta: 7:56:40 time: 0.4373 data_time: 0.0166 memory: 23498 grad_norm: 3.2290 top1_acc: 0.0833 top5_acc: 0.1667 loss_cls: 4.7947 loss: 4.7947 2022/09/08 10:55:52 - mmengine - INFO - Epoch(train) [1][120/880] lr: 8.8737e-03 eta: 7:19:41 time: 0.4381 data_time: 0.0199 memory: 23498 grad_norm: 3.3337 top1_acc: 0.0833 top5_acc: 0.2083 loss_cls: 4.4896 loss: 4.4896 2022/09/08 10:56:01 - mmengine - INFO - Epoch(train) [1][140/880] lr: 9.6928e-03 eta: 6:53:40 time: 0.4433 data_time: 0.0193 memory: 23498 grad_norm: 3.5215 top1_acc: 0.0417 top5_acc: 0.2083 loss_cls: 4.5460 loss: 4.5460 2022/09/08 10:56:10 - mmengine - INFO - Epoch(train) [1][160/880] lr: 1.0512e-02 eta: 6:34:24 time: 0.4473 data_time: 0.0216 memory: 23498 grad_norm: 3.7545 top1_acc: 0.0417 top5_acc: 0.2917 loss_cls: 4.4610 loss: 4.4610 2022/09/08 10:56:19 - mmengine - INFO - Epoch(train) [1][180/880] lr: 1.1331e-02 eta: 6:20:32 time: 0.4649 data_time: 0.0223 memory: 23498 grad_norm: 3.9271 top1_acc: 0.0417 top5_acc: 0.0417 loss_cls: 4.4615 loss: 4.4615 2022/09/08 10:56:28 - mmengine - INFO - Epoch(train) [1][200/880] lr: 1.2150e-02 eta: 6:08:06 time: 0.4426 data_time: 0.0212 memory: 23498 grad_norm: 4.0024 top1_acc: 0.1667 top5_acc: 0.2917 loss_cls: 4.3304 loss: 4.3304 2022/09/08 10:56:37 - mmengine - INFO - Epoch(train) [1][220/880] lr: 1.2969e-02 eta: 5:57:56 time: 0.4432 data_time: 0.0248 memory: 23498 grad_norm: 4.0375 top1_acc: 0.0417 top5_acc: 0.2083 loss_cls: 4.3387 loss: 4.3387 2022/09/08 10:56:46 - mmengine - INFO - Epoch(train) [1][240/880] lr: 1.3788e-02 eta: 5:49:16 time: 0.4398 data_time: 0.0182 memory: 23498 grad_norm: 4.0817 top1_acc: 0.0417 top5_acc: 0.1250 loss_cls: 4.3531 loss: 4.3531 2022/09/08 10:56:55 - mmengine - INFO - Epoch(train) [1][260/880] lr: 1.4608e-02 eta: 5:41:58 time: 0.4409 data_time: 0.0192 memory: 23498 grad_norm: 4.1237 top1_acc: 0.0833 top5_acc: 0.2500 loss_cls: 4.2930 loss: 4.2930 2022/09/08 10:57:03 - mmengine - INFO - Epoch(train) [1][280/880] lr: 1.5427e-02 eta: 5:35:36 time: 0.4387 data_time: 0.0207 memory: 23498 grad_norm: 4.0623 top1_acc: 0.0417 top5_acc: 0.2083 loss_cls: 4.2582 loss: 4.2582 2022/09/08 10:57:12 - mmengine - INFO - Epoch(train) [1][300/880] lr: 1.6246e-02 eta: 5:30:13 time: 0.4431 data_time: 0.0177 memory: 23498 grad_norm: 4.0707 top1_acc: 0.1250 top5_acc: 0.2083 loss_cls: 4.1835 loss: 4.1835 2022/09/08 10:57:21 - mmengine - INFO - Epoch(train) [1][320/880] lr: 1.7065e-02 eta: 5:25:36 time: 0.4456 data_time: 0.0200 memory: 23498 grad_norm: 4.0616 top1_acc: 0.0417 top5_acc: 0.6250 loss_cls: 4.2345 loss: 4.2345 2022/09/08 10:57:30 - mmengine - INFO - Epoch(train) [1][340/880] lr: 1.7884e-02 eta: 5:21:19 time: 0.4405 data_time: 0.0175 memory: 23498 grad_norm: 3.8751 top1_acc: 0.0833 top5_acc: 0.2500 loss_cls: 4.2033 loss: 4.2033 2022/09/08 10:57:39 - mmengine - INFO - Epoch(train) [1][360/880] lr: 1.8703e-02 eta: 5:17:32 time: 0.4413 data_time: 0.0200 memory: 23498 grad_norm: 3.7889 top1_acc: 0.0417 top5_acc: 0.2500 loss_cls: 4.2210 loss: 4.2210 2022/09/08 10:57:48 - mmengine - INFO - Epoch(train) [1][380/880] lr: 1.9522e-02 eta: 5:14:11 time: 0.4432 data_time: 0.0175 memory: 23498 grad_norm: 3.8219 top1_acc: 0.0417 top5_acc: 0.1250 loss_cls: 4.3136 loss: 4.3136 2022/09/08 10:57:57 - mmengine - INFO - Epoch(train) [1][400/880] lr: 2.0341e-02 eta: 5:11:35 time: 0.4580 data_time: 0.0186 memory: 23498 grad_norm: 3.7112 top1_acc: 0.2500 top5_acc: 0.4583 loss_cls: 4.1398 loss: 4.1398 2022/09/08 10:58:06 - mmengine - INFO - Epoch(train) [1][420/880] lr: 2.1160e-02 eta: 5:08:44 time: 0.4404 data_time: 0.0171 memory: 23498 grad_norm: 3.8472 top1_acc: 0.1250 top5_acc: 0.5417 loss_cls: 4.1179 loss: 4.1179 2022/09/08 10:58:15 - mmengine - INFO - Epoch(train) [1][440/880] lr: 2.1980e-02 eta: 5:06:20 time: 0.4479 data_time: 0.0199 memory: 23498 grad_norm: 3.5499 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.2371 loss: 4.2371 2022/09/08 10:58:23 - mmengine - INFO - Epoch(train) [1][460/880] lr: 2.2799e-02 eta: 5:03:50 time: 0.4368 data_time: 0.0187 memory: 23498 grad_norm: 3.6164 top1_acc: 0.0417 top5_acc: 0.2500 loss_cls: 4.1835 loss: 4.1835 2022/09/08 10:58:32 - mmengine - INFO - Epoch(train) [1][480/880] lr: 2.3618e-02 eta: 5:01:39 time: 0.4415 data_time: 0.0206 memory: 23498 grad_norm: 3.5426 top1_acc: 0.2083 top5_acc: 0.4167 loss_cls: 4.0823 loss: 4.0823 2022/09/08 10:58:41 - mmengine - INFO - Epoch(train) [1][500/880] lr: 2.4437e-02 eta: 4:59:58 time: 0.4561 data_time: 0.0177 memory: 23498 grad_norm: 3.5153 top1_acc: 0.0833 top5_acc: 0.3750 loss_cls: 4.0772 loss: 4.0772 2022/09/08 10:58:50 - mmengine - INFO - Epoch(train) [1][520/880] lr: 2.5256e-02 eta: 4:58:07 time: 0.4434 data_time: 0.0206 memory: 23498 grad_norm: 3.3490 top1_acc: 0.0833 top5_acc: 0.2083 loss_cls: 4.1640 loss: 4.1640 2022/09/08 10:58:59 - mmengine - INFO - Epoch(train) [1][540/880] lr: 2.6075e-02 eta: 4:56:19 time: 0.4392 data_time: 0.0193 memory: 23498 grad_norm: 3.4472 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.0593 loss: 4.0593 2022/09/08 10:59:08 - mmengine - INFO - Epoch(train) [1][560/880] lr: 2.6894e-02 eta: 4:54:38 time: 0.4398 data_time: 0.0191 memory: 23498 grad_norm: 3.3984 top1_acc: 0.1667 top5_acc: 0.3750 loss_cls: 4.0947 loss: 4.0947 2022/09/08 10:59:17 - mmengine - INFO - Epoch(train) [1][580/880] lr: 2.7713e-02 eta: 4:53:10 time: 0.4452 data_time: 0.0175 memory: 23498 grad_norm: 3.3670 top1_acc: 0.1667 top5_acc: 0.4167 loss_cls: 4.1462 loss: 4.1462 2022/09/08 10:59:25 - mmengine - INFO - Epoch(train) [1][600/880] lr: 2.8532e-02 eta: 4:51:40 time: 0.4385 data_time: 0.0192 memory: 23498 grad_norm: 3.3932 top1_acc: 0.1250 top5_acc: 0.3333 loss_cls: 4.0630 loss: 4.0630 2022/09/08 10:59:34 - mmengine - INFO - Epoch(train) [1][620/880] lr: 2.9352e-02 eta: 4:50:14 time: 0.4384 data_time: 0.0179 memory: 23498 grad_norm: 3.3194 top1_acc: 0.2500 top5_acc: 0.3333 loss_cls: 4.0029 loss: 4.0029 2022/09/08 10:59:43 - mmengine - INFO - Epoch(train) [1][640/880] lr: 3.0171e-02 eta: 4:48:58 time: 0.4425 data_time: 0.0202 memory: 23498 grad_norm: 3.1888 top1_acc: 0.0833 top5_acc: 0.2917 loss_cls: 4.1108 loss: 4.1108 2022/09/08 10:59:52 - mmengine - INFO - Epoch(train) [1][660/880] lr: 3.0990e-02 eta: 4:47:42 time: 0.4389 data_time: 0.0187 memory: 23498 grad_norm: 3.3170 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 4.0185 loss: 4.0185 2022/09/08 11:00:01 - mmengine - INFO - Epoch(train) [1][680/880] lr: 3.1809e-02 eta: 4:46:44 time: 0.4526 data_time: 0.0202 memory: 23498 grad_norm: 3.2804 top1_acc: 0.0833 top5_acc: 0.3333 loss_cls: 3.9538 loss: 3.9538 2022/09/08 11:00:10 - mmengine - INFO - Epoch(train) [1][700/880] lr: 3.2628e-02 eta: 4:45:36 time: 0.4386 data_time: 0.0188 memory: 23498 grad_norm: 3.2230 top1_acc: 0.1250 top5_acc: 0.4167 loss_cls: 3.9951 loss: 3.9951 2022/09/08 11:00:18 - mmengine - INFO - Epoch(train) [1][720/880] lr: 3.3447e-02 eta: 4:44:32 time: 0.4412 data_time: 0.0210 memory: 23498 grad_norm: 3.2858 top1_acc: 0.1667 top5_acc: 0.4583 loss_cls: 3.7600 loss: 3.7600 2022/09/08 11:00:27 - mmengine - INFO - Epoch(train) [1][740/880] lr: 3.4266e-02 eta: 4:43:31 time: 0.4394 data_time: 0.0175 memory: 23498 grad_norm: 3.2650 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 3.7966 loss: 3.7966 2022/09/08 11:00:36 - mmengine - INFO - Epoch(train) [1][760/880] lr: 3.5085e-02 eta: 4:42:32 time: 0.4403 data_time: 0.0202 memory: 23498 grad_norm: 3.2616 top1_acc: 0.0833 top5_acc: 0.4583 loss_cls: 3.8108 loss: 3.8108 2022/09/08 11:00:45 - mmengine - INFO - Epoch(train) [1][780/880] lr: 3.5904e-02 eta: 4:41:39 time: 0.4433 data_time: 0.0182 memory: 23498 grad_norm: 3.2024 top1_acc: 0.1250 top5_acc: 0.2917 loss_cls: 3.9705 loss: 3.9705 2022/09/08 11:00:54 - mmengine - INFO - Epoch(train) [1][800/880] lr: 3.6724e-02 eta: 4:40:49 time: 0.4440 data_time: 0.0197 memory: 23498 grad_norm: 3.1444 top1_acc: 0.1250 top5_acc: 0.2917 loss_cls: 3.9117 loss: 3.9117 2022/09/08 11:01:03 - mmengine - INFO - Epoch(train) [1][820/880] lr: 3.7543e-02 eta: 4:40:08 time: 0.4529 data_time: 0.0195 memory: 23498 grad_norm: 3.1150 top1_acc: 0.1667 top5_acc: 0.4583 loss_cls: 3.8858 loss: 3.8858 2022/09/08 11:01:12 - mmengine - INFO - Epoch(train) [1][840/880] lr: 3.8362e-02 eta: 4:39:20 time: 0.4414 data_time: 0.0201 memory: 23498 grad_norm: 3.1345 top1_acc: 0.2500 top5_acc: 0.4167 loss_cls: 3.8822 loss: 3.8822 2022/09/08 11:01:21 - mmengine - INFO - Epoch(train) [1][860/880] lr: 3.9181e-02 eta: 4:38:32 time: 0.4403 data_time: 0.0211 memory: 23498 grad_norm: 3.1931 top1_acc: 0.1667 top5_acc: 0.5417 loss_cls: 3.6552 loss: 3.6552 2022/09/08 11:01:29 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 11:01:29 - mmengine - INFO - Epoch(train) [1][880/880] lr: 4.0000e-02 eta: 4:37:41 time: 0.4335 data_time: 0.0186 memory: 23498 grad_norm: 3.2852 top1_acc: 0.1053 top5_acc: 0.2632 loss_cls: 3.8528 loss: 3.8528 2022/09/08 11:01:39 - mmengine - INFO - Epoch(train) [2][20/880] lr: 4.0000e-02 eta: 4:37:50 time: 0.5096 data_time: 0.0761 memory: 23498 grad_norm: 3.2794 top1_acc: 0.2083 top5_acc: 0.3750 loss_cls: 3.9525 loss: 3.9525 2022/09/08 11:01:48 - mmengine - INFO - Epoch(train) [2][40/880] lr: 4.0000e-02 eta: 4:37:15 time: 0.4531 data_time: 0.0223 memory: 23498 grad_norm: 3.3104 top1_acc: 0.2500 top5_acc: 0.4167 loss_cls: 3.7339 loss: 3.7339 2022/09/08 11:01:57 - mmengine - INFO - Epoch(train) [2][60/880] lr: 4.0000e-02 eta: 4:36:34 time: 0.4421 data_time: 0.0224 memory: 23498 grad_norm: 3.2358 top1_acc: 0.2917 top5_acc: 0.5000 loss_cls: 3.7305 loss: 3.7305 2022/09/08 11:02:06 - mmengine - INFO - Epoch(train) [2][80/880] lr: 4.0000e-02 eta: 4:35:56 time: 0.4440 data_time: 0.0221 memory: 23498 grad_norm: 3.2591 top1_acc: 0.2083 top5_acc: 0.4167 loss_cls: 3.9530 loss: 3.9530 2022/09/08 11:02:15 - mmengine - INFO - Epoch(train) [2][100/880] lr: 4.0000e-02 eta: 4:35:15 time: 0.4399 data_time: 0.0208 memory: 23498 grad_norm: 3.2692 top1_acc: 0.1667 top5_acc: 0.3750 loss_cls: 3.7294 loss: 3.7294 2022/09/08 11:02:24 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 11:02:24 - mmengine - INFO - Epoch(train) [2][120/880] lr: 4.0000e-02 eta: 4:34:37 time: 0.4404 data_time: 0.0223 memory: 23498 grad_norm: 3.4035 top1_acc: 0.1250 top5_acc: 0.3333 loss_cls: 3.7020 loss: 3.7020 2022/09/08 11:02:33 - mmengine - INFO - Epoch(train) [2][140/880] lr: 4.0000e-02 eta: 4:34:05 time: 0.4480 data_time: 0.0271 memory: 23498 grad_norm: 3.1756 top1_acc: 0.1667 top5_acc: 0.3750 loss_cls: 3.8029 loss: 3.8029 2022/09/08 11:02:42 - mmengine - INFO - Epoch(train) [2][160/880] lr: 4.0000e-02 eta: 4:33:27 time: 0.4392 data_time: 0.0200 memory: 23498 grad_norm: 3.3090 top1_acc: 0.1667 top5_acc: 0.3750 loss_cls: 3.8980 loss: 3.8980 2022/09/08 11:02:50 - mmengine - INFO - Epoch(train) [2][180/880] lr: 4.0000e-02 eta: 4:32:55 time: 0.4449 data_time: 0.0213 memory: 23498 grad_norm: 3.3079 top1_acc: 0.2500 top5_acc: 0.4583 loss_cls: 3.5973 loss: 3.5973 2022/09/08 11:02:59 - mmengine - INFO - Epoch(train) [2][200/880] lr: 4.0000e-02 eta: 4:32:22 time: 0.4428 data_time: 0.0223 memory: 23498 grad_norm: 3.1333 top1_acc: 0.1250 top5_acc: 0.4583 loss_cls: 3.7467 loss: 3.7467 2022/09/08 11:03:08 - mmengine - INFO - Epoch(train) [2][220/880] lr: 4.0000e-02 eta: 4:31:50 time: 0.4425 data_time: 0.0203 memory: 23498 grad_norm: 3.1343 top1_acc: 0.2083 top5_acc: 0.3333 loss_cls: 3.7251 loss: 3.7251 2022/09/08 11:03:17 - mmengine - INFO - Epoch(train) [2][240/880] lr: 4.0000e-02 eta: 4:31:19 time: 0.4435 data_time: 0.0229 memory: 23498 grad_norm: 3.3536 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.6246 loss: 3.6246 2022/09/08 11:03:26 - mmengine - INFO - Epoch(train) [2][260/880] lr: 4.0000e-02 eta: 4:30:50 time: 0.4449 data_time: 0.0223 memory: 23498 grad_norm: 3.4043 top1_acc: 0.1667 top5_acc: 0.4583 loss_cls: 3.8394 loss: 3.8394 2022/09/08 11:03:35 - mmengine - INFO - Epoch(train) [2][280/880] lr: 4.0000e-02 eta: 4:30:20 time: 0.4421 data_time: 0.0220 memory: 23498 grad_norm: 3.6574 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.8344 loss: 3.8344 2022/09/08 11:03:44 - mmengine - INFO - Epoch(train) [2][300/880] lr: 4.0000e-02 eta: 4:29:50 time: 0.4408 data_time: 0.0195 memory: 23498 grad_norm: 3.7677 top1_acc: 0.2083 top5_acc: 0.4583 loss_cls: 3.6442 loss: 3.6442 2022/09/08 11:03:53 - mmengine - INFO - Epoch(train) [2][320/880] lr: 4.0000e-02 eta: 4:29:25 time: 0.4487 data_time: 0.0231 memory: 23498 grad_norm: 3.7924 top1_acc: 0.2083 top5_acc: 0.5000 loss_cls: 3.7809 loss: 3.7809 2022/09/08 11:04:01 - mmengine - INFO - Epoch(train) [2][340/880] lr: 4.0000e-02 eta: 4:28:59 time: 0.4469 data_time: 0.0204 memory: 23498 grad_norm: 3.5537 top1_acc: 0.1667 top5_acc: 0.2083 loss_cls: 3.7281 loss: 3.7281 2022/09/08 11:04:10 - mmengine - INFO - Epoch(train) [2][360/880] lr: 4.0000e-02 eta: 4:28:34 time: 0.4454 data_time: 0.0243 memory: 23498 grad_norm: 3.6365 top1_acc: 0.2500 top5_acc: 0.4583 loss_cls: 3.9292 loss: 3.9292 2022/09/08 11:04:19 - mmengine - INFO - Epoch(train) [2][380/880] lr: 4.0000e-02 eta: 4:28:07 time: 0.4417 data_time: 0.0217 memory: 23498 grad_norm: 3.4434 top1_acc: 0.0417 top5_acc: 0.2917 loss_cls: 3.7622 loss: 3.7622 2022/09/08 11:04:28 - mmengine - INFO - Epoch(train) [2][400/880] lr: 4.0000e-02 eta: 4:27:44 time: 0.4489 data_time: 0.0220 memory: 23498 grad_norm: 3.2000 top1_acc: 0.2500 top5_acc: 0.4167 loss_cls: 3.7200 loss: 3.7200 2022/09/08 11:04:37 - mmengine - INFO - Epoch(train) [2][420/880] lr: 4.0000e-02 eta: 4:27:21 time: 0.4475 data_time: 0.0197 memory: 23498 grad_norm: 3.0114 top1_acc: 0.3750 top5_acc: 0.5417 loss_cls: 3.7980 loss: 3.7980 2022/09/08 11:04:46 - mmengine - INFO - Epoch(train) [2][440/880] lr: 4.0000e-02 eta: 4:26:56 time: 0.4441 data_time: 0.0241 memory: 23498 grad_norm: 3.0844 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 3.5743 loss: 3.5743 2022/09/08 11:04:55 - mmengine - INFO - Epoch(train) [2][460/880] lr: 4.0000e-02 eta: 4:26:34 time: 0.4468 data_time: 0.0194 memory: 23498 grad_norm: 3.0458 top1_acc: 0.2500 top5_acc: 0.4583 loss_cls: 3.7754 loss: 3.7754 2022/09/08 11:05:04 - mmengine - INFO - Epoch(train) [2][480/880] lr: 4.0000e-02 eta: 4:26:09 time: 0.4421 data_time: 0.0227 memory: 23498 grad_norm: 3.2128 top1_acc: 0.0833 top5_acc: 0.2500 loss_cls: 3.5950 loss: 3.5950 2022/09/08 11:05:13 - mmengine - INFO - Epoch(train) [2][500/880] lr: 4.0000e-02 eta: 4:25:46 time: 0.4448 data_time: 0.0225 memory: 23498 grad_norm: 3.1371 top1_acc: 0.2917 top5_acc: 0.5417 loss_cls: 3.6205 loss: 3.6205 2022/09/08 11:05:22 - mmengine - INFO - Epoch(train) [2][520/880] lr: 4.0000e-02 eta: 4:25:24 time: 0.4444 data_time: 0.0225 memory: 23498 grad_norm: 3.3011 top1_acc: 0.2917 top5_acc: 0.4167 loss_cls: 3.5748 loss: 3.5748 2022/09/08 11:05:31 - mmengine - INFO - Epoch(train) [2][540/880] lr: 4.0000e-02 eta: 4:25:02 time: 0.4451 data_time: 0.0220 memory: 23498 grad_norm: 3.3987 top1_acc: 0.1667 top5_acc: 0.4583 loss_cls: 3.6410 loss: 3.6410 2022/09/08 11:05:40 - mmengine - INFO - Epoch(train) [2][560/880] lr: 4.0000e-02 eta: 4:24:44 time: 0.4526 data_time: 0.0233 memory: 23498 grad_norm: 3.4940 top1_acc: 0.2500 top5_acc: 0.4167 loss_cls: 3.5525 loss: 3.5525 2022/09/08 11:05:48 - mmengine - INFO - Epoch(train) [2][580/880] lr: 4.0000e-02 eta: 4:24:22 time: 0.4434 data_time: 0.0229 memory: 23498 grad_norm: 3.6834 top1_acc: 0.2500 top5_acc: 0.4583 loss_cls: 3.5570 loss: 3.5570 2022/09/08 11:05:57 - mmengine - INFO - Epoch(train) [2][600/880] lr: 4.0000e-02 eta: 4:24:00 time: 0.4427 data_time: 0.0228 memory: 23498 grad_norm: 4.5510 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.7806 loss: 3.7806 2022/09/08 11:06:06 - mmengine - INFO - Epoch(train) [2][620/880] lr: 4.0000e-02 eta: 4:23:40 time: 0.4452 data_time: 0.0227 memory: 23498 grad_norm: 3.6997 top1_acc: 0.2083 top5_acc: 0.5000 loss_cls: 3.7474 loss: 3.7474 2022/09/08 11:06:15 - mmengine - INFO - Epoch(train) [2][640/880] lr: 4.0000e-02 eta: 4:23:19 time: 0.4443 data_time: 0.0234 memory: 23498 grad_norm: 3.7501 top1_acc: 0.2500 top5_acc: 0.5833 loss_cls: 3.8326 loss: 3.8326 2022/09/08 11:06:24 - mmengine - INFO - Epoch(train) [2][660/880] lr: 4.0000e-02 eta: 4:22:58 time: 0.4414 data_time: 0.0209 memory: 23498 grad_norm: 3.3496 top1_acc: 0.2500 top5_acc: 0.6667 loss_cls: 3.8855 loss: 3.8855 2022/09/08 11:06:33 - mmengine - INFO - Epoch(train) [2][680/880] lr: 4.0000e-02 eta: 4:22:41 time: 0.4508 data_time: 0.0231 memory: 23498 grad_norm: 3.0194 top1_acc: 0.0833 top5_acc: 0.2083 loss_cls: 3.7858 loss: 3.7858 2022/09/08 11:06:42 - mmengine - INFO - Epoch(train) [2][700/880] lr: 4.0000e-02 eta: 4:22:20 time: 0.4417 data_time: 0.0196 memory: 23498 grad_norm: 3.1167 top1_acc: 0.2500 top5_acc: 0.4583 loss_cls: 3.7394 loss: 3.7394 2022/09/08 11:06:51 - mmengine - INFO - Epoch(train) [2][720/880] lr: 4.0000e-02 eta: 4:22:01 time: 0.4450 data_time: 0.0244 memory: 23498 grad_norm: 3.1155 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 3.5605 loss: 3.5605 2022/09/08 11:06:59 - mmengine - INFO - Epoch(train) [2][740/880] lr: 4.0000e-02 eta: 4:21:41 time: 0.4420 data_time: 0.0203 memory: 23498 grad_norm: 3.2007 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.6949 loss: 3.6949 2022/09/08 11:07:09 - mmengine - INFO - Epoch(train) [2][760/880] lr: 4.0000e-02 eta: 4:21:30 time: 0.4630 data_time: 0.0236 memory: 23498 grad_norm: 3.2908 top1_acc: 0.2500 top5_acc: 0.4167 loss_cls: 3.6000 loss: 3.6000 2022/09/08 11:07:18 - mmengine - INFO - Epoch(train) [2][780/880] lr: 4.0000e-02 eta: 4:21:09 time: 0.4411 data_time: 0.0208 memory: 23498 grad_norm: 3.4037 top1_acc: 0.2083 top5_acc: 0.4167 loss_cls: 3.5269 loss: 3.5269 2022/09/08 11:07:26 - mmengine - INFO - Epoch(train) [2][800/880] lr: 4.0000e-02 eta: 4:20:51 time: 0.4434 data_time: 0.0230 memory: 23498 grad_norm: 3.1332 top1_acc: 0.2083 top5_acc: 0.4583 loss_cls: 3.5224 loss: 3.5224 2022/09/08 11:07:35 - mmengine - INFO - Epoch(train) [2][820/880] lr: 4.0000e-02 eta: 4:20:33 time: 0.4462 data_time: 0.0210 memory: 23498 grad_norm: 3.0441 top1_acc: 0.2083 top5_acc: 0.4167 loss_cls: 3.4156 loss: 3.4156 2022/09/08 11:07:44 - mmengine - INFO - Epoch(train) [2][840/880] lr: 4.0000e-02 eta: 4:20:15 time: 0.4430 data_time: 0.0234 memory: 23498 grad_norm: 3.2335 top1_acc: 0.2083 top5_acc: 0.4167 loss_cls: 3.6441 loss: 3.6441 2022/09/08 11:07:53 - mmengine - INFO - Epoch(train) [2][860/880] lr: 4.0000e-02 eta: 4:19:58 time: 0.4463 data_time: 0.0213 memory: 23498 grad_norm: 3.3026 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 3.4173 loss: 3.4173 2022/09/08 11:08:02 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 11:08:02 - mmengine - INFO - Epoch(train) [2][880/880] lr: 4.0000e-02 eta: 4:19:36 time: 0.4333 data_time: 0.0200 memory: 23498 grad_norm: 3.2419 top1_acc: 0.1579 top5_acc: 0.3684 loss_cls: 3.5222 loss: 3.5222 2022/09/08 11:09:04 - mmengine - INFO - Epoch(val) [2][20/130] eta: 0:05:43 time: 3.1218 data_time: 2.9937 memory: 2693 2022/09/08 11:09:07 - mmengine - INFO - Epoch(val) [2][40/130] eta: 0:00:12 time: 0.1393 data_time: 0.0175 memory: 2693 2022/09/08 11:09:10 - mmengine - INFO - Epoch(val) [2][60/130] eta: 0:00:11 time: 0.1593 data_time: 0.0297 memory: 2693 2022/09/08 11:09:14 - mmengine - INFO - Epoch(val) [2][80/130] eta: 0:00:08 time: 0.1626 data_time: 0.0384 memory: 2693 2022/09/08 11:09:17 - mmengine - INFO - Epoch(val) [2][100/130] eta: 0:00:05 time: 0.1994 data_time: 0.0668 memory: 2693 2022/09/08 11:09:20 - mmengine - INFO - Epoch(val) [2][120/130] eta: 0:00:01 time: 0.1418 data_time: 0.0148 memory: 2693 2022/09/08 11:09:31 - mmengine - INFO - Epoch(val) [2][130/130] acc/top1: 0.1872 acc/top5: 0.4266 acc/mean1: 0.1357 2022/09/08 11:09:32 - mmengine - INFO - The best checkpoint with 0.1872 acc/top1 at 2 epoch is saved to best_acc/top1_epoch_2.pth. 2022/09/08 11:09:42 - mmengine - INFO - Epoch(train) [3][20/880] lr: 3.9935e-02 eta: 4:19:37 time: 0.4936 data_time: 0.0676 memory: 23498 grad_norm: 3.3537 top1_acc: 0.2083 top5_acc: 0.5000 loss_cls: 3.5844 loss: 3.5844 2022/09/08 11:09:51 - mmengine - INFO - Epoch(train) [3][40/880] lr: 3.9935e-02 eta: 4:19:21 time: 0.4491 data_time: 0.0263 memory: 23498 grad_norm: 3.0774 top1_acc: 0.1667 top5_acc: 0.2500 loss_cls: 3.4617 loss: 3.4617 2022/09/08 11:10:00 - mmengine - INFO - Epoch(train) [3][60/880] lr: 3.9935e-02 eta: 4:19:03 time: 0.4420 data_time: 0.0229 memory: 23498 grad_norm: 3.1576 top1_acc: 0.2917 top5_acc: 0.4167 loss_cls: 3.5701 loss: 3.5701 2022/09/08 11:10:09 - mmengine - INFO - Epoch(train) [3][80/880] lr: 3.9935e-02 eta: 4:18:45 time: 0.4421 data_time: 0.0217 memory: 23498 grad_norm: 3.1849 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.4325 loss: 3.4325 2022/09/08 11:10:18 - mmengine - INFO - Epoch(train) [3][100/880] lr: 3.9935e-02 eta: 4:18:26 time: 0.4385 data_time: 0.0184 memory: 23498 grad_norm: 3.3385 top1_acc: 0.2083 top5_acc: 0.5417 loss_cls: 3.4960 loss: 3.4960 2022/09/08 11:10:27 - mmengine - INFO - Epoch(train) [3][120/880] lr: 3.9935e-02 eta: 4:18:12 time: 0.4514 data_time: 0.0244 memory: 23498 grad_norm: 3.2739 top1_acc: 0.2500 top5_acc: 0.5833 loss_cls: 3.3738 loss: 3.3738 2022/09/08 11:10:35 - mmengine - INFO - Epoch(train) [3][140/880] lr: 3.9935e-02 eta: 4:17:54 time: 0.4396 data_time: 0.0193 memory: 23498 grad_norm: 3.2586 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.4093 loss: 3.4093 2022/09/08 11:10:44 - mmengine - INFO - Epoch(train) [3][160/880] lr: 3.9935e-02 eta: 4:17:37 time: 0.4422 data_time: 0.0238 memory: 23498 grad_norm: 3.2309 top1_acc: 0.1667 top5_acc: 0.3750 loss_cls: 3.4545 loss: 3.4545 2022/09/08 11:10:53 - mmengine - INFO - Epoch(train) [3][180/880] lr: 3.9935e-02 eta: 4:17:21 time: 0.4467 data_time: 0.0228 memory: 23498 grad_norm: 3.0353 top1_acc: 0.2500 top5_acc: 0.4583 loss_cls: 3.3150 loss: 3.3150 2022/09/08 11:11:02 - mmengine - INFO - Epoch(train) [3][200/880] lr: 3.9935e-02 eta: 4:17:05 time: 0.4438 data_time: 0.0241 memory: 23498 grad_norm: 3.0598 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.5821 loss: 3.5821 2022/09/08 11:11:11 - mmengine - INFO - Epoch(train) [3][220/880] lr: 3.9935e-02 eta: 4:16:51 time: 0.4498 data_time: 0.0214 memory: 23498 grad_norm: 3.3960 top1_acc: 0.2083 top5_acc: 0.4583 loss_cls: 3.3820 loss: 3.3820 2022/09/08 11:11:20 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 11:11:20 - mmengine - INFO - Epoch(train) [3][240/880] lr: 3.9935e-02 eta: 4:16:37 time: 0.4482 data_time: 0.0248 memory: 23498 grad_norm: 3.2384 top1_acc: 0.2917 top5_acc: 0.6667 loss_cls: 3.3492 loss: 3.3492 2022/09/08 11:11:29 - mmengine - INFO - Epoch(train) [3][260/880] lr: 3.9935e-02 eta: 4:16:21 time: 0.4433 data_time: 0.0208 memory: 23498 grad_norm: 3.3602 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.3048 loss: 3.3048 2022/09/08 11:11:38 - mmengine - INFO - Epoch(train) [3][280/880] lr: 3.9935e-02 eta: 4:16:06 time: 0.4481 data_time: 0.0242 memory: 23498 grad_norm: 3.3672 top1_acc: 0.2917 top5_acc: 0.6667 loss_cls: 3.4656 loss: 3.4656 2022/09/08 11:11:47 - mmengine - INFO - Epoch(train) [3][300/880] lr: 3.9935e-02 eta: 4:15:51 time: 0.4430 data_time: 0.0225 memory: 23498 grad_norm: 3.4092 top1_acc: 0.1250 top5_acc: 0.4583 loss_cls: 3.3431 loss: 3.3431 2022/09/08 11:11:56 - mmengine - INFO - Epoch(train) [3][320/880] lr: 3.9935e-02 eta: 4:15:37 time: 0.4485 data_time: 0.0233 memory: 23498 grad_norm: 3.4992 top1_acc: 0.1667 top5_acc: 0.4167 loss_cls: 3.4330 loss: 3.4330 2022/09/08 11:12:05 - mmengine - INFO - Epoch(train) [3][340/880] lr: 3.9935e-02 eta: 4:15:21 time: 0.4426 data_time: 0.0210 memory: 23498 grad_norm: 3.4217 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 3.5753 loss: 3.5753 2022/09/08 11:12:13 - mmengine - INFO - Epoch(train) [3][360/880] lr: 3.9935e-02 eta: 4:15:06 time: 0.4442 data_time: 0.0238 memory: 23498 grad_norm: 3.1343 top1_acc: 0.2917 top5_acc: 0.5417 loss_cls: 3.3759 loss: 3.3759 2022/09/08 11:12:22 - mmengine - INFO - Epoch(train) [3][380/880] lr: 3.9935e-02 eta: 4:14:51 time: 0.4436 data_time: 0.0213 memory: 23498 grad_norm: 3.0653 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.5394 loss: 3.5394 2022/09/08 11:12:31 - mmengine - INFO - Epoch(train) [3][400/880] lr: 3.9935e-02 eta: 4:14:35 time: 0.4419 data_time: 0.0231 memory: 23498 grad_norm: 3.1800 top1_acc: 0.2917 top5_acc: 0.5000 loss_cls: 3.2601 loss: 3.2601 2022/09/08 11:12:40 - mmengine - INFO - Epoch(train) [3][420/880] lr: 3.9935e-02 eta: 4:14:20 time: 0.4418 data_time: 0.0221 memory: 23498 grad_norm: 3.6538 top1_acc: 0.0417 top5_acc: 0.2500 loss_cls: 3.4081 loss: 3.4081 2022/09/08 11:12:49 - mmengine - INFO - Epoch(train) [3][440/880] lr: 3.9935e-02 eta: 4:14:05 time: 0.4428 data_time: 0.0235 memory: 23498 grad_norm: 3.2863 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 3.4040 loss: 3.4040 2022/09/08 11:12:58 - mmengine - INFO - Epoch(train) [3][460/880] lr: 3.9935e-02 eta: 4:13:50 time: 0.4454 data_time: 0.0221 memory: 23498 grad_norm: 3.2349 top1_acc: 0.2083 top5_acc: 0.5417 loss_cls: 3.4712 loss: 3.4712 2022/09/08 11:13:07 - mmengine - INFO - Epoch(train) [3][480/880] lr: 3.9935e-02 eta: 4:13:36 time: 0.4434 data_time: 0.0243 memory: 23498 grad_norm: 3.4689 top1_acc: 0.2500 top5_acc: 0.5417 loss_cls: 3.3225 loss: 3.3225 2022/09/08 11:13:16 - mmengine - INFO - Epoch(train) [3][500/880] lr: 3.9935e-02 eta: 4:13:27 time: 0.4647 data_time: 0.0216 memory: 23498 grad_norm: 3.2162 top1_acc: 0.3333 top5_acc: 0.5417 loss_cls: 3.4149 loss: 3.4149 2022/09/08 11:13:25 - mmengine - INFO - Epoch(train) [3][520/880] lr: 3.9935e-02 eta: 4:13:13 time: 0.4433 data_time: 0.0233 memory: 23498 grad_norm: 3.0796 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 3.3837 loss: 3.3837 2022/09/08 11:13:34 - mmengine - INFO - Epoch(train) [3][540/880] lr: 3.9935e-02 eta: 4:12:58 time: 0.4425 data_time: 0.0225 memory: 23498 grad_norm: 3.2387 top1_acc: 0.2083 top5_acc: 0.4167 loss_cls: 3.5415 loss: 3.5415 2022/09/08 11:13:43 - mmengine - INFO - Epoch(train) [3][560/880] lr: 3.9935e-02 eta: 4:12:46 time: 0.4503 data_time: 0.0242 memory: 23498 grad_norm: 3.0479 top1_acc: 0.1667 top5_acc: 0.3750 loss_cls: 3.4485 loss: 3.4485 2022/09/08 11:13:52 - mmengine - INFO - Epoch(train) [3][580/880] lr: 3.9935e-02 eta: 4:12:33 time: 0.4476 data_time: 0.0262 memory: 23498 grad_norm: 3.2250 top1_acc: 0.1667 top5_acc: 0.5417 loss_cls: 3.3135 loss: 3.3135 2022/09/08 11:14:00 - mmengine - INFO - Epoch(train) [3][600/880] lr: 3.9935e-02 eta: 4:12:19 time: 0.4467 data_time: 0.0253 memory: 23498 grad_norm: 3.3528 top1_acc: 0.2083 top5_acc: 0.5000 loss_cls: 3.3958 loss: 3.3958 2022/09/08 11:14:09 - mmengine - INFO - Epoch(train) [3][620/880] lr: 3.9935e-02 eta: 4:12:06 time: 0.4439 data_time: 0.0221 memory: 23498 grad_norm: 3.0527 top1_acc: 0.2917 top5_acc: 0.4583 loss_cls: 3.4983 loss: 3.4983 2022/09/08 11:14:18 - mmengine - INFO - Epoch(train) [3][640/880] lr: 3.9935e-02 eta: 4:11:54 time: 0.4513 data_time: 0.0253 memory: 23498 grad_norm: 2.9932 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 3.3476 loss: 3.3476 2022/09/08 11:14:27 - mmengine - INFO - Epoch(train) [3][660/880] lr: 3.9935e-02 eta: 4:11:40 time: 0.4447 data_time: 0.0216 memory: 23498 grad_norm: 3.2493 top1_acc: 0.1667 top5_acc: 0.3750 loss_cls: 3.4670 loss: 3.4670 2022/09/08 11:14:36 - mmengine - INFO - Epoch(train) [3][680/880] lr: 3.9935e-02 eta: 4:11:28 time: 0.4502 data_time: 0.0255 memory: 23498 grad_norm: 3.0925 top1_acc: 0.1667 top5_acc: 0.3750 loss_cls: 3.4507 loss: 3.4507 2022/09/08 11:14:45 - mmengine - INFO - Epoch(train) [3][700/880] lr: 3.9935e-02 eta: 4:11:15 time: 0.4448 data_time: 0.0217 memory: 23498 grad_norm: 3.1437 top1_acc: 0.2083 top5_acc: 0.5417 loss_cls: 3.2623 loss: 3.2623 2022/09/08 11:14:54 - mmengine - INFO - Epoch(train) [3][720/880] lr: 3.9935e-02 eta: 4:11:01 time: 0.4447 data_time: 0.0239 memory: 23498 grad_norm: 3.1831 top1_acc: 0.2917 top5_acc: 0.3750 loss_cls: 3.3429 loss: 3.3429 2022/09/08 11:15:03 - mmengine - INFO - Epoch(train) [3][740/880] lr: 3.9935e-02 eta: 4:10:48 time: 0.4441 data_time: 0.0213 memory: 23498 grad_norm: 3.2170 top1_acc: 0.2500 top5_acc: 0.5417 loss_cls: 3.4680 loss: 3.4680 2022/09/08 11:15:12 - mmengine - INFO - Epoch(train) [3][760/880] lr: 3.9935e-02 eta: 4:10:34 time: 0.4433 data_time: 0.0238 memory: 23498 grad_norm: 3.1946 top1_acc: 0.1667 top5_acc: 0.3750 loss_cls: 3.4122 loss: 3.4122 2022/09/08 11:15:21 - mmengine - INFO - Epoch(train) [3][780/880] lr: 3.9935e-02 eta: 4:10:22 time: 0.4460 data_time: 0.0229 memory: 23498 grad_norm: 3.3813 top1_acc: 0.4167 top5_acc: 0.5000 loss_cls: 3.2217 loss: 3.2217 2022/09/08 11:15:30 - mmengine - INFO - Epoch(train) [3][800/880] lr: 3.9935e-02 eta: 4:10:09 time: 0.4451 data_time: 0.0245 memory: 23498 grad_norm: 3.1107 top1_acc: 0.2917 top5_acc: 0.5000 loss_cls: 3.2312 loss: 3.2312 2022/09/08 11:15:39 - mmengine - INFO - Epoch(train) [3][820/880] lr: 3.9935e-02 eta: 4:09:56 time: 0.4481 data_time: 0.0222 memory: 23498 grad_norm: 3.0796 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 3.2120 loss: 3.2120 2022/09/08 11:15:48 - mmengine - INFO - Epoch(train) [3][840/880] lr: 3.9935e-02 eta: 4:09:44 time: 0.4454 data_time: 0.0249 memory: 23498 grad_norm: 3.2251 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 3.2747 loss: 3.2747 2022/09/08 11:15:57 - mmengine - INFO - Epoch(train) [3][860/880] lr: 3.9935e-02 eta: 4:09:34 time: 0.4588 data_time: 0.0227 memory: 23498 grad_norm: 3.2365 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.2332 loss: 3.2332 2022/09/08 11:16:05 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 11:16:05 - mmengine - INFO - Epoch(train) [3][880/880] lr: 3.9935e-02 eta: 4:09:19 time: 0.4350 data_time: 0.0220 memory: 23498 grad_norm: 3.1650 top1_acc: 0.3158 top5_acc: 0.4737 loss_cls: 3.3297 loss: 3.3297 2022/09/08 11:16:16 - mmengine - INFO - Epoch(train) [4][20/880] lr: 3.9741e-02 eta: 4:09:23 time: 0.5128 data_time: 0.0695 memory: 23498 grad_norm: 3.0956 top1_acc: 0.3333 top5_acc: 0.6250 loss_cls: 3.1769 loss: 3.1769 2022/09/08 11:16:25 - mmengine - INFO - Epoch(train) [4][40/880] lr: 3.9741e-02 eta: 4:09:10 time: 0.4470 data_time: 0.0211 memory: 23498 grad_norm: 3.0495 top1_acc: 0.2500 top5_acc: 0.5833 loss_cls: 3.2663 loss: 3.2663 2022/09/08 11:16:34 - mmengine - INFO - Epoch(train) [4][60/880] lr: 3.9741e-02 eta: 4:08:59 time: 0.4487 data_time: 0.0190 memory: 23498 grad_norm: 3.0166 top1_acc: 0.2500 top5_acc: 0.4583 loss_cls: 3.0237 loss: 3.0237 2022/09/08 11:16:43 - mmengine - INFO - Epoch(train) [4][80/880] lr: 3.9741e-02 eta: 4:08:46 time: 0.4452 data_time: 0.0217 memory: 23498 grad_norm: 3.0620 top1_acc: 0.2500 top5_acc: 0.5833 loss_cls: 3.2864 loss: 3.2864 2022/09/08 11:16:51 - mmengine - INFO - Epoch(train) [4][100/880] lr: 3.9741e-02 eta: 4:08:33 time: 0.4448 data_time: 0.0178 memory: 23498 grad_norm: 3.1052 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 3.2080 loss: 3.2080 2022/09/08 11:17:00 - mmengine - INFO - Epoch(train) [4][120/880] lr: 3.9741e-02 eta: 4:08:21 time: 0.4452 data_time: 0.0220 memory: 23498 grad_norm: 3.1665 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 3.2177 loss: 3.2177 2022/09/08 11:17:09 - mmengine - INFO - Epoch(train) [4][140/880] lr: 3.9741e-02 eta: 4:08:08 time: 0.4454 data_time: 0.0186 memory: 23498 grad_norm: 3.1539 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.0740 loss: 3.0740 2022/09/08 11:17:18 - mmengine - INFO - Epoch(train) [4][160/880] lr: 3.9741e-02 eta: 4:07:55 time: 0.4424 data_time: 0.0217 memory: 23498 grad_norm: 3.3112 top1_acc: 0.2917 top5_acc: 0.7500 loss_cls: 3.0879 loss: 3.0879 2022/09/08 11:17:27 - mmengine - INFO - Epoch(train) [4][180/880] lr: 3.9741e-02 eta: 4:07:42 time: 0.4407 data_time: 0.0195 memory: 23498 grad_norm: 3.2090 top1_acc: 0.2917 top5_acc: 0.5000 loss_cls: 3.2168 loss: 3.2168 2022/09/08 11:17:36 - mmengine - INFO - Epoch(train) [4][200/880] lr: 3.9741e-02 eta: 4:07:31 time: 0.4504 data_time: 0.0228 memory: 23498 grad_norm: 3.3892 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 3.0560 loss: 3.0560 2022/09/08 11:17:45 - mmengine - INFO - Epoch(train) [4][220/880] lr: 3.9741e-02 eta: 4:07:17 time: 0.4398 data_time: 0.0191 memory: 23498 grad_norm: 3.2183 top1_acc: 0.2083 top5_acc: 0.5417 loss_cls: 3.2735 loss: 3.2735 2022/09/08 11:17:54 - mmengine - INFO - Epoch(train) [4][240/880] lr: 3.9741e-02 eta: 4:07:05 time: 0.4452 data_time: 0.0234 memory: 23498 grad_norm: 3.1040 top1_acc: 0.4167 top5_acc: 0.5000 loss_cls: 3.1614 loss: 3.1614 2022/09/08 11:18:03 - mmengine - INFO - Epoch(train) [4][260/880] lr: 3.9741e-02 eta: 4:06:57 time: 0.4623 data_time: 0.0217 memory: 23498 grad_norm: 3.0583 top1_acc: 0.2917 top5_acc: 0.5000 loss_cls: 3.2874 loss: 3.2874 2022/09/08 11:18:12 - mmengine - INFO - Epoch(train) [4][280/880] lr: 3.9741e-02 eta: 4:06:43 time: 0.4409 data_time: 0.0233 memory: 23498 grad_norm: 3.1455 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.2198 loss: 3.2198 2022/09/08 11:18:21 - mmengine - INFO - Epoch(train) [4][300/880] lr: 3.9741e-02 eta: 4:06:31 time: 0.4417 data_time: 0.0231 memory: 23498 grad_norm: 3.3056 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 3.1932 loss: 3.1932 2022/09/08 11:18:29 - mmengine - INFO - Epoch(train) [4][320/880] lr: 3.9741e-02 eta: 4:06:18 time: 0.4435 data_time: 0.0244 memory: 23498 grad_norm: 3.1773 top1_acc: 0.3333 top5_acc: 0.4583 loss_cls: 3.2448 loss: 3.2448 2022/09/08 11:18:38 - mmengine - INFO - Epoch(train) [4][340/880] lr: 3.9741e-02 eta: 4:06:05 time: 0.4424 data_time: 0.0215 memory: 23498 grad_norm: 3.2621 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 3.2923 loss: 3.2923 2022/09/08 11:18:47 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 11:18:47 - mmengine - INFO - Epoch(train) [4][360/880] lr: 3.9741e-02 eta: 4:05:53 time: 0.4445 data_time: 0.0240 memory: 23498 grad_norm: 3.1427 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.2847 loss: 3.2847 2022/09/08 11:18:56 - mmengine - INFO - Epoch(train) [4][380/880] lr: 3.9741e-02 eta: 4:05:41 time: 0.4443 data_time: 0.0218 memory: 23498 grad_norm: 3.2548 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.1318 loss: 3.1318 2022/09/08 11:19:05 - mmengine - INFO - Epoch(train) [4][400/880] lr: 3.9741e-02 eta: 4:05:29 time: 0.4430 data_time: 0.0237 memory: 23498 grad_norm: 3.2369 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.2238 loss: 3.2238 2022/09/08 11:19:14 - mmengine - INFO - Epoch(train) [4][420/880] lr: 3.9741e-02 eta: 4:05:17 time: 0.4431 data_time: 0.0221 memory: 23498 grad_norm: 3.0692 top1_acc: 0.2917 top5_acc: 0.5417 loss_cls: 3.0266 loss: 3.0266 2022/09/08 11:19:23 - mmengine - INFO - Epoch(train) [4][440/880] lr: 3.9741e-02 eta: 4:05:09 time: 0.4659 data_time: 0.0251 memory: 23498 grad_norm: 2.9806 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.2674 loss: 3.2674 2022/09/08 11:19:32 - mmengine - INFO - Epoch(train) [4][460/880] lr: 3.9741e-02 eta: 4:04:57 time: 0.4436 data_time: 0.0217 memory: 23498 grad_norm: 3.1629 top1_acc: 0.2083 top5_acc: 0.5833 loss_cls: 3.1588 loss: 3.1588 2022/09/08 11:19:41 - mmengine - INFO - Epoch(train) [4][480/880] lr: 3.9741e-02 eta: 4:04:49 time: 0.4632 data_time: 0.0251 memory: 23498 grad_norm: 3.2946 top1_acc: 0.2083 top5_acc: 0.5000 loss_cls: 3.1483 loss: 3.1483 2022/09/08 11:19:50 - mmengine - INFO - Epoch(train) [4][500/880] lr: 3.9741e-02 eta: 4:04:38 time: 0.4485 data_time: 0.0258 memory: 23498 grad_norm: 3.3784 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.1909 loss: 3.1909 2022/09/08 11:19:59 - mmengine - INFO - Epoch(train) [4][520/880] lr: 3.9741e-02 eta: 4:04:28 time: 0.4553 data_time: 0.0256 memory: 23498 grad_norm: 3.2709 top1_acc: 0.2083 top5_acc: 0.2917 loss_cls: 3.1195 loss: 3.1195 2022/09/08 11:20:08 - mmengine - INFO - Epoch(train) [4][540/880] lr: 3.9741e-02 eta: 4:04:16 time: 0.4447 data_time: 0.0230 memory: 23498 grad_norm: 3.1751 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 3.0470 loss: 3.0470 2022/09/08 11:20:17 - mmengine - INFO - Epoch(train) [4][560/880] lr: 3.9741e-02 eta: 4:04:05 time: 0.4469 data_time: 0.0249 memory: 23498 grad_norm: 3.1720 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1407 loss: 3.1407 2022/09/08 11:20:26 - mmengine - INFO - Epoch(train) [4][580/880] lr: 3.9741e-02 eta: 4:03:53 time: 0.4437 data_time: 0.0213 memory: 23498 grad_norm: 3.2680 top1_acc: 0.1667 top5_acc: 0.4167 loss_cls: 3.1640 loss: 3.1640 2022/09/08 11:20:35 - mmengine - INFO - Epoch(train) [4][600/880] lr: 3.9741e-02 eta: 4:03:41 time: 0.4445 data_time: 0.0236 memory: 23498 grad_norm: 3.3610 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.2430 loss: 3.2430 2022/09/08 11:20:44 - mmengine - INFO - Epoch(train) [4][620/880] lr: 3.9741e-02 eta: 4:03:30 time: 0.4457 data_time: 0.0220 memory: 23498 grad_norm: 3.4420 top1_acc: 0.1250 top5_acc: 0.4583 loss_cls: 3.3410 loss: 3.3410 2022/09/08 11:20:53 - mmengine - INFO - Epoch(train) [4][640/880] lr: 3.9741e-02 eta: 4:03:19 time: 0.4471 data_time: 0.0244 memory: 23498 grad_norm: 3.1685 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 3.1216 loss: 3.1216 2022/09/08 11:21:02 - mmengine - INFO - Epoch(train) [4][660/880] lr: 3.9741e-02 eta: 4:03:07 time: 0.4451 data_time: 0.0236 memory: 23498 grad_norm: 3.0843 top1_acc: 0.2500 top5_acc: 0.5833 loss_cls: 3.1320 loss: 3.1320 2022/09/08 11:21:11 - mmengine - INFO - Epoch(train) [4][680/880] lr: 3.9741e-02 eta: 4:02:55 time: 0.4439 data_time: 0.0232 memory: 23498 grad_norm: 3.2227 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 3.0655 loss: 3.0655 2022/09/08 11:21:19 - mmengine - INFO - Epoch(train) [4][700/880] lr: 3.9741e-02 eta: 4:02:44 time: 0.4452 data_time: 0.0222 memory: 23498 grad_norm: 3.5350 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 3.1563 loss: 3.1563 2022/09/08 11:21:28 - mmengine - INFO - Epoch(train) [4][720/880] lr: 3.9741e-02 eta: 4:02:32 time: 0.4441 data_time: 0.0247 memory: 23498 grad_norm: 3.4254 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 3.2553 loss: 3.2553 2022/09/08 11:21:37 - mmengine - INFO - Epoch(train) [4][740/880] lr: 3.9741e-02 eta: 4:02:21 time: 0.4457 data_time: 0.0212 memory: 23498 grad_norm: 3.3068 top1_acc: 0.3333 top5_acc: 0.6250 loss_cls: 3.2058 loss: 3.2058 2022/09/08 11:21:46 - mmengine - INFO - Epoch(train) [4][760/880] lr: 3.9741e-02 eta: 4:02:10 time: 0.4453 data_time: 0.0256 memory: 23498 grad_norm: 3.1837 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 2.9471 loss: 2.9471 2022/09/08 11:21:55 - mmengine - INFO - Epoch(train) [4][780/880] lr: 3.9741e-02 eta: 4:01:58 time: 0.4428 data_time: 0.0209 memory: 23498 grad_norm: 3.1406 top1_acc: 0.2083 top5_acc: 0.4167 loss_cls: 3.1708 loss: 3.1708 2022/09/08 11:22:04 - mmengine - INFO - Epoch(train) [4][800/880] lr: 3.9741e-02 eta: 4:01:47 time: 0.4454 data_time: 0.0253 memory: 23498 grad_norm: 3.0224 top1_acc: 0.2917 top5_acc: 0.3333 loss_cls: 3.1789 loss: 3.1789 2022/09/08 11:22:13 - mmengine - INFO - Epoch(train) [4][820/880] lr: 3.9741e-02 eta: 4:01:35 time: 0.4428 data_time: 0.0213 memory: 23498 grad_norm: 3.3693 top1_acc: 0.4167 top5_acc: 0.5417 loss_cls: 3.1001 loss: 3.1001 2022/09/08 11:22:22 - mmengine - INFO - Epoch(train) [4][840/880] lr: 3.9741e-02 eta: 4:01:24 time: 0.4483 data_time: 0.0256 memory: 23498 grad_norm: 3.4347 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 3.2739 loss: 3.2739 2022/09/08 11:22:31 - mmengine - INFO - Epoch(train) [4][860/880] lr: 3.9741e-02 eta: 4:01:13 time: 0.4429 data_time: 0.0214 memory: 23498 grad_norm: 3.3896 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.2072 loss: 3.2072 2022/09/08 11:22:40 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 11:22:40 - mmengine - INFO - Epoch(train) [4][880/880] lr: 3.9741e-02 eta: 4:01:02 time: 0.4468 data_time: 0.0225 memory: 23498 grad_norm: 3.2521 top1_acc: 0.3684 top5_acc: 0.5789 loss_cls: 3.2345 loss: 3.2345 2022/09/08 11:22:44 - mmengine - INFO - Epoch(val) [4][20/130] eta: 0:00:24 time: 0.2214 data_time: 0.0853 memory: 2693 2022/09/08 11:22:47 - mmengine - INFO - Epoch(val) [4][40/130] eta: 0:00:14 time: 0.1608 data_time: 0.0253 memory: 2693 2022/09/08 11:22:51 - mmengine - INFO - Epoch(val) [4][60/130] eta: 0:00:11 time: 0.1684 data_time: 0.0317 memory: 2693 2022/09/08 11:22:54 - mmengine - INFO - Epoch(val) [4][80/130] eta: 0:00:07 time: 0.1579 data_time: 0.0230 memory: 2693 2022/09/08 11:22:57 - mmengine - INFO - Epoch(val) [4][100/130] eta: 0:00:05 time: 0.1668 data_time: 0.0305 memory: 2693 2022/09/08 11:23:00 - mmengine - INFO - Epoch(val) [4][120/130] eta: 0:00:01 time: 0.1646 data_time: 0.0268 memory: 2693 2022/09/08 11:23:03 - mmengine - INFO - Epoch(val) [4][130/130] acc/top1: 0.2521 acc/top5: 0.5251 acc/mean1: 0.1827 2022/09/08 11:23:03 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4/best_acc/top1_epoch_2.pth is removed 2022/09/08 11:23:04 - mmengine - INFO - The best checkpoint with 0.2521 acc/top1 at 4 epoch is saved to best_acc/top1_epoch_4.pth. 2022/09/08 11:23:14 - mmengine - INFO - Epoch(train) [5][20/880] lr: 3.9419e-02 eta: 4:00:59 time: 0.4925 data_time: 0.0657 memory: 23498 grad_norm: 3.3883 top1_acc: 0.2917 top5_acc: 0.5000 loss_cls: 3.1951 loss: 3.1951 2022/09/08 11:23:23 - mmengine - INFO - Epoch(train) [5][40/880] lr: 3.9419e-02 eta: 4:00:49 time: 0.4491 data_time: 0.0210 memory: 23498 grad_norm: 3.4566 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.0200 loss: 3.0200 2022/09/08 11:23:32 - mmengine - INFO - Epoch(train) [5][60/880] lr: 3.9419e-02 eta: 4:00:38 time: 0.4504 data_time: 0.0220 memory: 23498 grad_norm: 3.5655 top1_acc: 0.1667 top5_acc: 0.3750 loss_cls: 3.2662 loss: 3.2662 2022/09/08 11:23:41 - mmengine - INFO - Epoch(train) [5][80/880] lr: 3.9419e-02 eta: 4:00:27 time: 0.4449 data_time: 0.0204 memory: 23498 grad_norm: 3.1745 top1_acc: 0.0833 top5_acc: 0.3333 loss_cls: 3.3608 loss: 3.3608 2022/09/08 11:23:50 - mmengine - INFO - Epoch(train) [5][100/880] lr: 3.9419e-02 eta: 4:00:16 time: 0.4442 data_time: 0.0219 memory: 23498 grad_norm: 3.3141 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 3.0675 loss: 3.0675 2022/09/08 11:23:59 - mmengine - INFO - Epoch(train) [5][120/880] lr: 3.9419e-02 eta: 4:00:06 time: 0.4488 data_time: 0.0230 memory: 23498 grad_norm: 3.2297 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9727 loss: 2.9727 2022/09/08 11:24:08 - mmengine - INFO - Epoch(train) [5][140/880] lr: 3.9419e-02 eta: 3:59:56 time: 0.4514 data_time: 0.0191 memory: 23498 grad_norm: 3.1153 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 3.1025 loss: 3.1025 2022/09/08 11:24:17 - mmengine - INFO - Epoch(train) [5][160/880] lr: 3.9419e-02 eta: 3:59:44 time: 0.4415 data_time: 0.0204 memory: 23498 grad_norm: 3.3148 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 3.0229 loss: 3.0229 2022/09/08 11:24:25 - mmengine - INFO - Epoch(train) [5][180/880] lr: 3.9419e-02 eta: 3:59:32 time: 0.4408 data_time: 0.0223 memory: 23498 grad_norm: 3.3250 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0483 loss: 3.0483 2022/09/08 11:24:34 - mmengine - INFO - Epoch(train) [5][200/880] lr: 3.9419e-02 eta: 3:59:21 time: 0.4429 data_time: 0.0221 memory: 23498 grad_norm: 3.3651 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 3.0608 loss: 3.0608 2022/09/08 11:24:43 - mmengine - INFO - Epoch(train) [5][220/880] lr: 3.9419e-02 eta: 3:59:10 time: 0.4461 data_time: 0.0211 memory: 23498 grad_norm: 2.9858 top1_acc: 0.2083 top5_acc: 0.5000 loss_cls: 3.1625 loss: 3.1625 2022/09/08 11:24:52 - mmengine - INFO - Epoch(train) [5][240/880] lr: 3.9419e-02 eta: 3:58:59 time: 0.4456 data_time: 0.0234 memory: 23498 grad_norm: 3.0710 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 3.1614 loss: 3.1614 2022/09/08 11:25:01 - mmengine - INFO - Epoch(train) [5][260/880] lr: 3.9419e-02 eta: 3:58:48 time: 0.4437 data_time: 0.0234 memory: 23498 grad_norm: 3.1207 top1_acc: 0.2500 top5_acc: 0.5833 loss_cls: 3.1384 loss: 3.1384 2022/09/08 11:25:10 - mmengine - INFO - Epoch(train) [5][280/880] lr: 3.9419e-02 eta: 3:58:37 time: 0.4465 data_time: 0.0267 memory: 23498 grad_norm: 3.1743 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 3.1720 loss: 3.1720 2022/09/08 11:25:19 - mmengine - INFO - Epoch(train) [5][300/880] lr: 3.9419e-02 eta: 3:58:26 time: 0.4446 data_time: 0.0229 memory: 23498 grad_norm: 3.3006 top1_acc: 0.2500 top5_acc: 0.5833 loss_cls: 2.9460 loss: 2.9460 2022/09/08 11:25:28 - mmengine - INFO - Epoch(train) [5][320/880] lr: 3.9419e-02 eta: 3:58:15 time: 0.4452 data_time: 0.0245 memory: 23498 grad_norm: 3.3166 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 3.0313 loss: 3.0313 2022/09/08 11:25:37 - mmengine - INFO - Epoch(train) [5][340/880] lr: 3.9419e-02 eta: 3:58:04 time: 0.4453 data_time: 0.0236 memory: 23498 grad_norm: 3.2211 top1_acc: 0.3333 top5_acc: 0.5417 loss_cls: 3.1151 loss: 3.1151 2022/09/08 11:25:46 - mmengine - INFO - Epoch(train) [5][360/880] lr: 3.9419e-02 eta: 3:57:53 time: 0.4442 data_time: 0.0248 memory: 23498 grad_norm: 3.0696 top1_acc: 0.2083 top5_acc: 0.3333 loss_cls: 3.2930 loss: 3.2930 2022/09/08 11:25:54 - mmengine - INFO - Epoch(train) [5][380/880] lr: 3.9419e-02 eta: 3:57:43 time: 0.4465 data_time: 0.0233 memory: 23498 grad_norm: 3.1530 top1_acc: 0.3333 top5_acc: 0.6250 loss_cls: 2.9080 loss: 2.9080 2022/09/08 11:26:03 - mmengine - INFO - Epoch(train) [5][400/880] lr: 3.9419e-02 eta: 3:57:32 time: 0.4455 data_time: 0.0250 memory: 23498 grad_norm: 3.3488 top1_acc: 0.2500 top5_acc: 0.5417 loss_cls: 3.0413 loss: 3.0413 2022/09/08 11:26:12 - mmengine - INFO - Epoch(train) [5][420/880] lr: 3.9419e-02 eta: 3:57:21 time: 0.4433 data_time: 0.0215 memory: 23498 grad_norm: 3.4227 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 2.9525 loss: 2.9525 2022/09/08 11:26:21 - mmengine - INFO - Epoch(train) [5][440/880] lr: 3.9419e-02 eta: 3:57:10 time: 0.4465 data_time: 0.0258 memory: 23498 grad_norm: 3.2530 top1_acc: 0.2500 top5_acc: 0.4167 loss_cls: 3.1197 loss: 3.1197 2022/09/08 11:26:30 - mmengine - INFO - Epoch(train) [5][460/880] lr: 3.9419e-02 eta: 3:57:00 time: 0.4437 data_time: 0.0219 memory: 23498 grad_norm: 3.0573 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0946 loss: 3.0946 2022/09/08 11:26:39 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 11:26:39 - mmengine - INFO - Epoch(train) [5][480/880] lr: 3.9419e-02 eta: 3:56:52 time: 0.4632 data_time: 0.0231 memory: 23498 grad_norm: 3.1302 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 2.9305 loss: 2.9305 2022/09/08 11:26:48 - mmengine - INFO - Epoch(train) [5][500/880] lr: 3.9419e-02 eta: 3:56:41 time: 0.4442 data_time: 0.0219 memory: 23498 grad_norm: 3.2179 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 3.1345 loss: 3.1345 2022/09/08 11:26:57 - mmengine - INFO - Epoch(train) [5][520/880] lr: 3.9419e-02 eta: 3:56:31 time: 0.4504 data_time: 0.0251 memory: 23498 grad_norm: 3.0484 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 3.0545 loss: 3.0545 2022/09/08 11:27:06 - mmengine - INFO - Epoch(train) [5][540/880] lr: 3.9419e-02 eta: 3:56:20 time: 0.4440 data_time: 0.0225 memory: 23498 grad_norm: 3.1373 top1_acc: 0.2083 top5_acc: 0.5833 loss_cls: 3.0225 loss: 3.0225 2022/09/08 11:27:15 - mmengine - INFO - Epoch(train) [5][560/880] lr: 3.9419e-02 eta: 3:56:09 time: 0.4440 data_time: 0.0239 memory: 23498 grad_norm: 3.2689 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 3.0712 loss: 3.0712 2022/09/08 11:27:24 - mmengine - INFO - Epoch(train) [5][580/880] lr: 3.9419e-02 eta: 3:56:02 time: 0.4680 data_time: 0.0233 memory: 23498 grad_norm: 3.2008 top1_acc: 0.2917 top5_acc: 0.4583 loss_cls: 3.0892 loss: 3.0892 2022/09/08 11:27:34 - mmengine - INFO - Epoch(train) [5][600/880] lr: 3.9419e-02 eta: 3:55:54 time: 0.4631 data_time: 0.0289 memory: 23498 grad_norm: 3.2055 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.8534 loss: 2.8534 2022/09/08 11:27:43 - mmengine - INFO - Epoch(train) [5][620/880] lr: 3.9419e-02 eta: 3:55:43 time: 0.4428 data_time: 0.0220 memory: 23498 grad_norm: 3.2445 top1_acc: 0.1250 top5_acc: 0.5833 loss_cls: 3.0303 loss: 3.0303 2022/09/08 11:27:51 - mmengine - INFO - Epoch(train) [5][640/880] lr: 3.9419e-02 eta: 3:55:33 time: 0.4521 data_time: 0.0310 memory: 23498 grad_norm: 3.3698 top1_acc: 0.2500 top5_acc: 0.4583 loss_cls: 2.9954 loss: 2.9954 2022/09/08 11:28:01 - mmengine - INFO - Epoch(train) [5][660/880] lr: 3.9419e-02 eta: 3:55:26 time: 0.4658 data_time: 0.0224 memory: 23498 grad_norm: 3.3597 top1_acc: 0.3750 top5_acc: 0.5417 loss_cls: 3.0580 loss: 3.0580 2022/09/08 11:28:10 - mmengine - INFO - Epoch(train) [5][680/880] lr: 3.9419e-02 eta: 3:55:16 time: 0.4509 data_time: 0.0300 memory: 23498 grad_norm: 3.4336 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 3.0066 loss: 3.0066 2022/09/08 11:28:19 - mmengine - INFO - Epoch(train) [5][700/880] lr: 3.9419e-02 eta: 3:55:07 time: 0.4562 data_time: 0.0223 memory: 23498 grad_norm: 3.2561 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 3.0712 loss: 3.0712 2022/09/08 11:28:28 - mmengine - INFO - Epoch(train) [5][720/880] lr: 3.9419e-02 eta: 3:54:56 time: 0.4446 data_time: 0.0242 memory: 23498 grad_norm: 3.3906 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 3.1390 loss: 3.1390 2022/09/08 11:28:37 - mmengine - INFO - Epoch(train) [5][740/880] lr: 3.9419e-02 eta: 3:54:48 time: 0.4610 data_time: 0.0234 memory: 23498 grad_norm: 3.1891 top1_acc: 0.2917 top5_acc: 0.5000 loss_cls: 2.9405 loss: 2.9405 2022/09/08 11:28:46 - mmengine - INFO - Epoch(train) [5][760/880] lr: 3.9419e-02 eta: 3:54:38 time: 0.4472 data_time: 0.0242 memory: 23498 grad_norm: 3.2588 top1_acc: 0.2083 top5_acc: 0.4583 loss_cls: 3.1220 loss: 3.1220 2022/09/08 11:28:55 - mmengine - INFO - Epoch(train) [5][780/880] lr: 3.9419e-02 eta: 3:54:28 time: 0.4486 data_time: 0.0268 memory: 23498 grad_norm: 3.2754 top1_acc: 0.3333 top5_acc: 0.5417 loss_cls: 3.0617 loss: 3.0617 2022/09/08 11:29:04 - mmengine - INFO - Epoch(train) [5][800/880] lr: 3.9419e-02 eta: 3:54:18 time: 0.4487 data_time: 0.0247 memory: 23498 grad_norm: 3.1961 top1_acc: 0.2083 top5_acc: 0.6250 loss_cls: 2.9706 loss: 2.9706 2022/09/08 11:29:13 - mmengine - INFO - Epoch(train) [5][820/880] lr: 3.9419e-02 eta: 3:54:07 time: 0.4444 data_time: 0.0242 memory: 23498 grad_norm: 3.1712 top1_acc: 0.1667 top5_acc: 0.5417 loss_cls: 3.2718 loss: 3.2718 2022/09/08 11:29:22 - mmengine - INFO - Epoch(train) [5][840/880] lr: 3.9419e-02 eta: 3:53:57 time: 0.4477 data_time: 0.0249 memory: 23498 grad_norm: 3.3233 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.8882 loss: 2.8882 2022/09/08 11:29:31 - mmengine - INFO - Epoch(train) [5][860/880] lr: 3.9419e-02 eta: 3:53:46 time: 0.4449 data_time: 0.0227 memory: 23498 grad_norm: 3.3143 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 3.1936 loss: 3.1936 2022/09/08 11:29:39 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 11:29:39 - mmengine - INFO - Epoch(train) [5][880/880] lr: 3.9419e-02 eta: 3:53:35 time: 0.4379 data_time: 0.0230 memory: 23498 grad_norm: 3.2625 top1_acc: 0.1579 top5_acc: 0.4211 loss_cls: 3.2324 loss: 3.2324 2022/09/08 11:29:50 - mmengine - INFO - Epoch(train) [6][20/880] lr: 3.8971e-02 eta: 3:53:35 time: 0.5212 data_time: 0.0898 memory: 23498 grad_norm: 3.1171 top1_acc: 0.2500 top5_acc: 0.5417 loss_cls: 2.9671 loss: 2.9671 2022/09/08 11:29:59 - mmengine - INFO - Epoch(train) [6][40/880] lr: 3.8971e-02 eta: 3:53:25 time: 0.4474 data_time: 0.0231 memory: 23498 grad_norm: 3.2766 top1_acc: 0.2083 top5_acc: 0.5000 loss_cls: 2.9261 loss: 2.9261 2022/09/08 11:30:08 - mmengine - INFO - Epoch(train) [6][60/880] lr: 3.8971e-02 eta: 3:53:15 time: 0.4481 data_time: 0.0218 memory: 23498 grad_norm: 3.0322 top1_acc: 0.2917 top5_acc: 0.7083 loss_cls: 2.7882 loss: 2.7882 2022/09/08 11:30:17 - mmengine - INFO - Epoch(train) [6][80/880] lr: 3.8971e-02 eta: 3:53:04 time: 0.4450 data_time: 0.0214 memory: 23498 grad_norm: 3.3030 top1_acc: 0.2083 top5_acc: 0.4167 loss_cls: 2.9623 loss: 2.9623 2022/09/08 11:30:26 - mmengine - INFO - Epoch(train) [6][100/880] lr: 3.8971e-02 eta: 3:52:54 time: 0.4475 data_time: 0.0208 memory: 23498 grad_norm: 3.1826 top1_acc: 0.1667 top5_acc: 0.7500 loss_cls: 3.0567 loss: 3.0567 2022/09/08 11:30:35 - mmengine - INFO - Epoch(train) [6][120/880] lr: 3.8971e-02 eta: 3:52:43 time: 0.4443 data_time: 0.0223 memory: 23498 grad_norm: 3.2367 top1_acc: 0.2917 top5_acc: 0.6667 loss_cls: 2.9413 loss: 2.9413 2022/09/08 11:30:43 - mmengine - INFO - Epoch(train) [6][140/880] lr: 3.8971e-02 eta: 3:52:33 time: 0.4428 data_time: 0.0217 memory: 23498 grad_norm: 3.2610 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0270 loss: 3.0270 2022/09/08 11:30:52 - mmengine - INFO - Epoch(train) [6][160/880] lr: 3.8971e-02 eta: 3:52:22 time: 0.4421 data_time: 0.0229 memory: 23498 grad_norm: 3.2933 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9658 loss: 2.9658 2022/09/08 11:31:01 - mmengine - INFO - Epoch(train) [6][180/880] lr: 3.8971e-02 eta: 3:52:11 time: 0.4433 data_time: 0.0216 memory: 23498 grad_norm: 3.2622 top1_acc: 0.3333 top5_acc: 0.5417 loss_cls: 3.0065 loss: 3.0065 2022/09/08 11:31:10 - mmengine - INFO - Epoch(train) [6][200/880] lr: 3.8971e-02 eta: 3:52:00 time: 0.4424 data_time: 0.0228 memory: 23498 grad_norm: 3.1930 top1_acc: 0.4167 top5_acc: 0.5417 loss_cls: 2.8874 loss: 2.8874 2022/09/08 11:31:19 - mmengine - INFO - Epoch(train) [6][220/880] lr: 3.8971e-02 eta: 3:51:50 time: 0.4441 data_time: 0.0210 memory: 23498 grad_norm: 3.1337 top1_acc: 0.2500 top5_acc: 0.6667 loss_cls: 2.7409 loss: 2.7409 2022/09/08 11:31:28 - mmengine - INFO - Epoch(train) [6][240/880] lr: 3.8971e-02 eta: 3:51:39 time: 0.4410 data_time: 0.0223 memory: 23498 grad_norm: 3.1182 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.8526 loss: 2.8526 2022/09/08 11:31:36 - mmengine - INFO - Epoch(train) [6][260/880] lr: 3.8971e-02 eta: 3:51:28 time: 0.4404 data_time: 0.0217 memory: 23498 grad_norm: 3.2279 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 2.8747 loss: 2.8747 2022/09/08 11:31:45 - mmengine - INFO - Epoch(train) [6][280/880] lr: 3.8971e-02 eta: 3:51:18 time: 0.4448 data_time: 0.0239 memory: 23498 grad_norm: 3.4404 top1_acc: 0.2500 top5_acc: 0.4583 loss_cls: 3.0891 loss: 3.0891 2022/09/08 11:31:54 - mmengine - INFO - Epoch(train) [6][300/880] lr: 3.8971e-02 eta: 3:51:07 time: 0.4417 data_time: 0.0221 memory: 23498 grad_norm: 3.5349 top1_acc: 0.3333 top5_acc: 0.5417 loss_cls: 2.9617 loss: 2.9617 2022/09/08 11:32:03 - mmengine - INFO - Epoch(train) [6][320/880] lr: 3.8971e-02 eta: 3:50:56 time: 0.4435 data_time: 0.0240 memory: 23498 grad_norm: 3.5946 top1_acc: 0.2500 top5_acc: 0.5417 loss_cls: 2.9644 loss: 2.9644 2022/09/08 11:32:12 - mmengine - INFO - Epoch(train) [6][340/880] lr: 3.8971e-02 eta: 3:50:45 time: 0.4412 data_time: 0.0218 memory: 23498 grad_norm: 3.2439 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.9013 loss: 2.9013 2022/09/08 11:32:21 - mmengine - INFO - Epoch(train) [6][360/880] lr: 3.8971e-02 eta: 3:50:35 time: 0.4448 data_time: 0.0239 memory: 23498 grad_norm: 3.2452 top1_acc: 0.1250 top5_acc: 0.4167 loss_cls: 3.0905 loss: 3.0905 2022/09/08 11:32:30 - mmengine - INFO - Epoch(train) [6][380/880] lr: 3.8971e-02 eta: 3:50:24 time: 0.4418 data_time: 0.0227 memory: 23498 grad_norm: 3.3001 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 3.0188 loss: 3.0188 2022/09/08 11:32:39 - mmengine - INFO - Epoch(train) [6][400/880] lr: 3.8971e-02 eta: 3:50:15 time: 0.4525 data_time: 0.0250 memory: 23498 grad_norm: 3.2120 top1_acc: 0.2917 top5_acc: 0.3750 loss_cls: 3.0239 loss: 3.0239 2022/09/08 11:32:48 - mmengine - INFO - Epoch(train) [6][420/880] lr: 3.8971e-02 eta: 3:50:04 time: 0.4432 data_time: 0.0216 memory: 23498 grad_norm: 3.2628 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 3.0675 loss: 3.0675 2022/09/08 11:32:56 - mmengine - INFO - Epoch(train) [6][440/880] lr: 3.8971e-02 eta: 3:49:54 time: 0.4442 data_time: 0.0237 memory: 23498 grad_norm: 3.5493 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0538 loss: 3.0538 2022/09/08 11:33:05 - mmengine - INFO - Epoch(train) [6][460/880] lr: 3.8971e-02 eta: 3:49:44 time: 0.4440 data_time: 0.0215 memory: 23498 grad_norm: 3.2840 top1_acc: 0.5000 top5_acc: 0.5833 loss_cls: 3.0232 loss: 3.0232 2022/09/08 11:33:14 - mmengine - INFO - Epoch(train) [6][480/880] lr: 3.8971e-02 eta: 3:49:34 time: 0.4460 data_time: 0.0244 memory: 23498 grad_norm: 3.1988 top1_acc: 0.2917 top5_acc: 0.7083 loss_cls: 2.9042 loss: 2.9042 2022/09/08 11:33:23 - mmengine - INFO - Epoch(train) [6][500/880] lr: 3.8971e-02 eta: 3:49:25 time: 0.4565 data_time: 0.0225 memory: 23498 grad_norm: 3.2057 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 2.8763 loss: 2.8763 2022/09/08 11:33:32 - mmengine - INFO - Epoch(train) [6][520/880] lr: 3.8971e-02 eta: 3:49:15 time: 0.4488 data_time: 0.0246 memory: 23498 grad_norm: 3.3441 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0293 loss: 3.0293 2022/09/08 11:33:41 - mmengine - INFO - Epoch(train) [6][540/880] lr: 3.8971e-02 eta: 3:49:05 time: 0.4479 data_time: 0.0253 memory: 23498 grad_norm: 3.1027 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.9675 loss: 2.9675 2022/09/08 11:33:50 - mmengine - INFO - Epoch(train) [6][560/880] lr: 3.8971e-02 eta: 3:48:55 time: 0.4464 data_time: 0.0251 memory: 23498 grad_norm: 3.2701 top1_acc: 0.2917 top5_acc: 0.5000 loss_cls: 2.9193 loss: 2.9193 2022/09/08 11:34:00 - mmengine - INFO - Epoch(train) [6][580/880] lr: 3.8971e-02 eta: 3:48:48 time: 0.4669 data_time: 0.0243 memory: 23498 grad_norm: 3.2281 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.9547 loss: 2.9547 2022/09/08 11:34:08 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 11:34:08 - mmengine - INFO - Epoch(train) [6][600/880] lr: 3.8971e-02 eta: 3:48:37 time: 0.4440 data_time: 0.0235 memory: 23498 grad_norm: 3.1720 top1_acc: 0.3750 top5_acc: 0.4167 loss_cls: 3.0498 loss: 3.0498 2022/09/08 11:34:17 - mmengine - INFO - Epoch(train) [6][620/880] lr: 3.8971e-02 eta: 3:48:28 time: 0.4502 data_time: 0.0241 memory: 23498 grad_norm: 3.0904 top1_acc: 0.2083 top5_acc: 0.5833 loss_cls: 2.9063 loss: 2.9063 2022/09/08 11:34:26 - mmengine - INFO - Epoch(train) [6][640/880] lr: 3.8971e-02 eta: 3:48:18 time: 0.4457 data_time: 0.0246 memory: 23498 grad_norm: 3.0404 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 2.8292 loss: 2.8292 2022/09/08 11:34:35 - mmengine - INFO - Epoch(train) [6][660/880] lr: 3.8971e-02 eta: 3:48:08 time: 0.4483 data_time: 0.0265 memory: 23498 grad_norm: 3.0399 top1_acc: 0.2500 top5_acc: 0.5833 loss_cls: 3.0222 loss: 3.0222 2022/09/08 11:34:44 - mmengine - INFO - Epoch(train) [6][680/880] lr: 3.8971e-02 eta: 3:47:58 time: 0.4438 data_time: 0.0236 memory: 23498 grad_norm: 3.2124 top1_acc: 0.2500 top5_acc: 0.5417 loss_cls: 2.8710 loss: 2.8710 2022/09/08 11:34:53 - mmengine - INFO - Epoch(train) [6][700/880] lr: 3.8971e-02 eta: 3:47:47 time: 0.4446 data_time: 0.0212 memory: 23498 grad_norm: 3.2771 top1_acc: 0.4167 top5_acc: 0.5000 loss_cls: 2.9275 loss: 2.9275 2022/09/08 11:35:02 - mmengine - INFO - Epoch(train) [6][720/880] lr: 3.8971e-02 eta: 3:47:38 time: 0.4552 data_time: 0.0240 memory: 23498 grad_norm: 3.1098 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.9529 loss: 2.9529 2022/09/08 11:35:11 - mmengine - INFO - Epoch(train) [6][740/880] lr: 3.8971e-02 eta: 3:47:28 time: 0.4446 data_time: 0.0225 memory: 23498 grad_norm: 3.1367 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.9037 loss: 2.9037 2022/09/08 11:35:20 - mmengine - INFO - Epoch(train) [6][760/880] lr: 3.8971e-02 eta: 3:47:18 time: 0.4460 data_time: 0.0243 memory: 23498 grad_norm: 3.3354 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.8839 loss: 2.8839 2022/09/08 11:35:29 - mmengine - INFO - Epoch(train) [6][780/880] lr: 3.8971e-02 eta: 3:47:08 time: 0.4444 data_time: 0.0221 memory: 23498 grad_norm: 3.2948 top1_acc: 0.2917 top5_acc: 0.6667 loss_cls: 2.8618 loss: 2.8618 2022/09/08 11:35:38 - mmengine - INFO - Epoch(train) [6][800/880] lr: 3.8971e-02 eta: 3:46:59 time: 0.4590 data_time: 0.0244 memory: 23498 grad_norm: 3.1696 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.9450 loss: 2.9450 2022/09/08 11:35:47 - mmengine - INFO - Epoch(train) [6][820/880] lr: 3.8971e-02 eta: 3:46:49 time: 0.4452 data_time: 0.0234 memory: 23498 grad_norm: 3.4300 top1_acc: 0.2500 top5_acc: 0.5833 loss_cls: 2.9733 loss: 2.9733 2022/09/08 11:35:56 - mmengine - INFO - Epoch(train) [6][840/880] lr: 3.8971e-02 eta: 3:46:39 time: 0.4463 data_time: 0.0248 memory: 23498 grad_norm: 3.0874 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9017 loss: 2.9017 2022/09/08 11:36:05 - mmengine - INFO - Epoch(train) [6][860/880] lr: 3.8971e-02 eta: 3:46:29 time: 0.4443 data_time: 0.0218 memory: 23498 grad_norm: 3.1786 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 3.0103 loss: 3.0103 2022/09/08 11:36:14 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 11:36:14 - mmengine - INFO - Epoch(train) [6][880/880] lr: 3.8971e-02 eta: 3:46:18 time: 0.4366 data_time: 0.0212 memory: 23498 grad_norm: 3.0999 top1_acc: 0.1579 top5_acc: 0.3684 loss_cls: 2.9501 loss: 2.9501 2022/09/08 11:36:18 - mmengine - INFO - Epoch(val) [6][20/130] eta: 0:00:24 time: 0.2207 data_time: 0.0851 memory: 2693 2022/09/08 11:36:21 - mmengine - INFO - Epoch(val) [6][40/130] eta: 0:00:14 time: 0.1592 data_time: 0.0225 memory: 2693 2022/09/08 11:36:25 - mmengine - INFO - Epoch(val) [6][60/130] eta: 0:00:12 time: 0.1721 data_time: 0.0346 memory: 2693 2022/09/08 11:36:28 - mmengine - INFO - Epoch(val) [6][80/130] eta: 0:00:08 time: 0.1695 data_time: 0.0269 memory: 2693 2022/09/08 11:36:31 - mmengine - INFO - Epoch(val) [6][100/130] eta: 0:00:05 time: 0.1729 data_time: 0.0356 memory: 2693 2022/09/08 11:36:35 - mmengine - INFO - Epoch(val) [6][120/130] eta: 0:00:01 time: 0.1623 data_time: 0.0313 memory: 2693 2022/09/08 11:36:37 - mmengine - INFO - Epoch(val) [6][130/130] acc/top1: 0.2802 acc/top5: 0.5591 acc/mean1: 0.2196 2022/09/08 11:36:37 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4/best_acc/top1_epoch_4.pth is removed 2022/09/08 11:36:38 - mmengine - INFO - The best checkpoint with 0.2802 acc/top1 at 6 epoch is saved to best_acc/top1_epoch_6.pth. 2022/09/08 11:36:48 - mmengine - INFO - Epoch(train) [7][20/880] lr: 3.8400e-02 eta: 3:46:14 time: 0.4998 data_time: 0.0728 memory: 23498 grad_norm: 3.1644 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.8569 loss: 2.8569 2022/09/08 11:36:57 - mmengine - INFO - Epoch(train) [7][40/880] lr: 3.8400e-02 eta: 3:46:05 time: 0.4527 data_time: 0.0255 memory: 23498 grad_norm: 3.2121 top1_acc: 0.0417 top5_acc: 0.4167 loss_cls: 2.9396 loss: 2.9396 2022/09/08 11:37:06 - mmengine - INFO - Epoch(train) [7][60/880] lr: 3.8400e-02 eta: 3:45:56 time: 0.4553 data_time: 0.0203 memory: 23498 grad_norm: 3.1499 top1_acc: 0.3333 top5_acc: 0.5417 loss_cls: 2.8076 loss: 2.8076 2022/09/08 11:37:15 - mmengine - INFO - Epoch(train) [7][80/880] lr: 3.8400e-02 eta: 3:45:46 time: 0.4461 data_time: 0.0216 memory: 23498 grad_norm: 3.3078 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9878 loss: 2.9878 2022/09/08 11:37:24 - mmengine - INFO - Epoch(train) [7][100/880] lr: 3.8400e-02 eta: 3:45:36 time: 0.4444 data_time: 0.0206 memory: 23498 grad_norm: 3.0704 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.9118 loss: 2.9118 2022/09/08 11:37:33 - mmengine - INFO - Epoch(train) [7][120/880] lr: 3.8400e-02 eta: 3:45:26 time: 0.4462 data_time: 0.0231 memory: 23498 grad_norm: 3.1714 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.8988 loss: 2.8988 2022/09/08 11:37:41 - mmengine - INFO - Epoch(train) [7][140/880] lr: 3.8400e-02 eta: 3:45:16 time: 0.4460 data_time: 0.0205 memory: 23498 grad_norm: 3.1485 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8073 loss: 2.8073 2022/09/08 11:37:50 - mmengine - INFO - Epoch(train) [7][160/880] lr: 3.8400e-02 eta: 3:45:06 time: 0.4452 data_time: 0.0231 memory: 23498 grad_norm: 3.2605 top1_acc: 0.3333 top5_acc: 0.6250 loss_cls: 2.8071 loss: 2.8071 2022/09/08 11:37:59 - mmengine - INFO - Epoch(train) [7][180/880] lr: 3.8400e-02 eta: 3:44:56 time: 0.4437 data_time: 0.0208 memory: 23498 grad_norm: 3.3499 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.9065 loss: 2.9065 2022/09/08 11:38:08 - mmengine - INFO - Epoch(train) [7][200/880] lr: 3.8400e-02 eta: 3:44:46 time: 0.4464 data_time: 0.0214 memory: 23498 grad_norm: 3.2464 top1_acc: 0.2917 top5_acc: 0.5417 loss_cls: 2.8450 loss: 2.8450 2022/09/08 11:38:17 - mmengine - INFO - Epoch(train) [7][220/880] lr: 3.8400e-02 eta: 3:44:36 time: 0.4433 data_time: 0.0214 memory: 23498 grad_norm: 3.1517 top1_acc: 0.2500 top5_acc: 0.5417 loss_cls: 2.9606 loss: 2.9606 2022/09/08 11:38:26 - mmengine - INFO - Epoch(train) [7][240/880] lr: 3.8400e-02 eta: 3:44:26 time: 0.4421 data_time: 0.0232 memory: 23498 grad_norm: 3.1754 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.9828 loss: 2.9828 2022/09/08 11:38:35 - mmengine - INFO - Epoch(train) [7][260/880] lr: 3.8400e-02 eta: 3:44:15 time: 0.4400 data_time: 0.0203 memory: 23498 grad_norm: 3.1781 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.7275 loss: 2.7275 2022/09/08 11:38:44 - mmengine - INFO - Epoch(train) [7][280/880] lr: 3.8400e-02 eta: 3:44:05 time: 0.4498 data_time: 0.0244 memory: 23498 grad_norm: 3.1865 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 2.8393 loss: 2.8393 2022/09/08 11:38:53 - mmengine - INFO - Epoch(train) [7][300/880] lr: 3.8400e-02 eta: 3:43:55 time: 0.4422 data_time: 0.0200 memory: 23498 grad_norm: 3.2061 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.8927 loss: 2.8927 2022/09/08 11:39:01 - mmengine - INFO - Epoch(train) [7][320/880] lr: 3.8400e-02 eta: 3:43:45 time: 0.4471 data_time: 0.0282 memory: 23498 grad_norm: 3.2925 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.8426 loss: 2.8426 2022/09/08 11:39:10 - mmengine - INFO - Epoch(train) [7][340/880] lr: 3.8400e-02 eta: 3:43:35 time: 0.4416 data_time: 0.0209 memory: 23498 grad_norm: 3.3200 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8084 loss: 2.8084 2022/09/08 11:39:20 - mmengine - INFO - Epoch(train) [7][360/880] lr: 3.8400e-02 eta: 3:43:27 time: 0.4633 data_time: 0.0240 memory: 23498 grad_norm: 3.2853 top1_acc: 0.2083 top5_acc: 0.3750 loss_cls: 2.9905 loss: 2.9905 2022/09/08 11:39:28 - mmengine - INFO - Epoch(train) [7][380/880] lr: 3.8400e-02 eta: 3:43:17 time: 0.4429 data_time: 0.0216 memory: 23498 grad_norm: 3.2728 top1_acc: 0.3333 top5_acc: 0.5417 loss_cls: 2.8977 loss: 2.8977 2022/09/08 11:39:37 - mmengine - INFO - Epoch(train) [7][400/880] lr: 3.8400e-02 eta: 3:43:07 time: 0.4447 data_time: 0.0245 memory: 23498 grad_norm: 3.5571 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.7629 loss: 2.7629 2022/09/08 11:39:46 - mmengine - INFO - Epoch(train) [7][420/880] lr: 3.8400e-02 eta: 3:42:57 time: 0.4452 data_time: 0.0239 memory: 23498 grad_norm: 3.2979 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 2.9466 loss: 2.9466 2022/09/08 11:39:55 - mmengine - INFO - Epoch(train) [7][440/880] lr: 3.8400e-02 eta: 3:42:47 time: 0.4446 data_time: 0.0248 memory: 23498 grad_norm: 3.2751 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0163 loss: 3.0163 2022/09/08 11:40:04 - mmengine - INFO - Epoch(train) [7][460/880] lr: 3.8400e-02 eta: 3:42:37 time: 0.4450 data_time: 0.0225 memory: 23498 grad_norm: 3.1709 top1_acc: 0.2917 top5_acc: 0.5417 loss_cls: 2.8804 loss: 2.8804 2022/09/08 11:40:13 - mmengine - INFO - Epoch(train) [7][480/880] lr: 3.8400e-02 eta: 3:42:27 time: 0.4455 data_time: 0.0247 memory: 23498 grad_norm: 3.2389 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0382 loss: 3.0382 2022/09/08 11:40:22 - mmengine - INFO - Epoch(train) [7][500/880] lr: 3.8400e-02 eta: 3:42:17 time: 0.4458 data_time: 0.0225 memory: 23498 grad_norm: 3.1969 top1_acc: 0.2917 top5_acc: 0.6667 loss_cls: 2.9191 loss: 2.9191 2022/09/08 11:40:31 - mmengine - INFO - Epoch(train) [7][520/880] lr: 3.8400e-02 eta: 3:42:08 time: 0.4459 data_time: 0.0252 memory: 23498 grad_norm: 3.0731 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 2.8232 loss: 2.8232 2022/09/08 11:40:40 - mmengine - INFO - Epoch(train) [7][540/880] lr: 3.8400e-02 eta: 3:41:59 time: 0.4542 data_time: 0.0229 memory: 23498 grad_norm: 3.1405 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.9237 loss: 2.9237 2022/09/08 11:40:49 - mmengine - INFO - Epoch(train) [7][560/880] lr: 3.8400e-02 eta: 3:41:49 time: 0.4452 data_time: 0.0250 memory: 23498 grad_norm: 3.1389 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 2.7818 loss: 2.7818 2022/09/08 11:40:58 - mmengine - INFO - Epoch(train) [7][580/880] lr: 3.8400e-02 eta: 3:41:39 time: 0.4452 data_time: 0.0227 memory: 23498 grad_norm: 3.1503 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.9266 loss: 2.9266 2022/09/08 11:41:07 - mmengine - INFO - Epoch(train) [7][600/880] lr: 3.8400e-02 eta: 3:41:29 time: 0.4467 data_time: 0.0254 memory: 23498 grad_norm: 3.1830 top1_acc: 0.2917 top5_acc: 0.4583 loss_cls: 2.9744 loss: 2.9744 2022/09/08 11:41:15 - mmengine - INFO - Epoch(train) [7][620/880] lr: 3.8400e-02 eta: 3:41:19 time: 0.4433 data_time: 0.0219 memory: 23498 grad_norm: 3.1708 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8303 loss: 2.8303 2022/09/08 11:41:24 - mmengine - INFO - Epoch(train) [7][640/880] lr: 3.8400e-02 eta: 3:41:09 time: 0.4468 data_time: 0.0246 memory: 23498 grad_norm: 3.3364 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 2.9791 loss: 2.9791 2022/09/08 11:41:33 - mmengine - INFO - Epoch(train) [7][660/880] lr: 3.8400e-02 eta: 3:40:59 time: 0.4444 data_time: 0.0214 memory: 23498 grad_norm: 3.4242 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 2.9788 loss: 2.9788 2022/09/08 11:41:42 - mmengine - INFO - Epoch(train) [7][680/880] lr: 3.8400e-02 eta: 3:40:50 time: 0.4502 data_time: 0.0253 memory: 23498 grad_norm: 3.2960 top1_acc: 0.1667 top5_acc: 0.5833 loss_cls: 2.7133 loss: 2.7133 2022/09/08 11:41:51 - mmengine - INFO - Epoch(train) [7][700/880] lr: 3.8400e-02 eta: 3:40:40 time: 0.4458 data_time: 0.0225 memory: 23498 grad_norm: 3.3772 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.9316 loss: 2.9316 2022/09/08 11:42:00 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 11:42:00 - mmengine - INFO - Epoch(train) [7][720/880] lr: 3.8400e-02 eta: 3:40:31 time: 0.4464 data_time: 0.0254 memory: 23498 grad_norm: 3.5320 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0392 loss: 3.0392 2022/09/08 11:42:09 - mmengine - INFO - Epoch(train) [7][740/880] lr: 3.8400e-02 eta: 3:40:21 time: 0.4476 data_time: 0.0239 memory: 23498 grad_norm: 3.4879 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8092 loss: 2.8092 2022/09/08 11:42:18 - mmengine - INFO - Epoch(train) [7][760/880] lr: 3.8400e-02 eta: 3:40:12 time: 0.4518 data_time: 0.0242 memory: 23498 grad_norm: 3.2183 top1_acc: 0.2500 top5_acc: 0.3333 loss_cls: 3.0993 loss: 3.0993 2022/09/08 11:42:27 - mmengine - INFO - Epoch(train) [7][780/880] lr: 3.8400e-02 eta: 3:40:02 time: 0.4469 data_time: 0.0227 memory: 23498 grad_norm: 3.2566 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.8671 loss: 2.8671 2022/09/08 11:42:36 - mmengine - INFO - Epoch(train) [7][800/880] lr: 3.8400e-02 eta: 3:39:53 time: 0.4492 data_time: 0.0234 memory: 23498 grad_norm: 3.2377 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9706 loss: 2.9706 2022/09/08 11:42:45 - mmengine - INFO - Epoch(train) [7][820/880] lr: 3.8400e-02 eta: 3:39:43 time: 0.4473 data_time: 0.0219 memory: 23498 grad_norm: 3.1557 top1_acc: 0.3750 top5_acc: 0.5417 loss_cls: 2.9587 loss: 2.9587 2022/09/08 11:42:54 - mmengine - INFO - Epoch(train) [7][840/880] lr: 3.8400e-02 eta: 3:39:33 time: 0.4458 data_time: 0.0244 memory: 23498 grad_norm: 3.2037 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 2.8802 loss: 2.8802 2022/09/08 11:43:03 - mmengine - INFO - Epoch(train) [7][860/880] lr: 3.8400e-02 eta: 3:39:23 time: 0.4426 data_time: 0.0221 memory: 23498 grad_norm: 3.1971 top1_acc: 0.3333 top5_acc: 0.4167 loss_cls: 2.8492 loss: 2.8492 2022/09/08 11:43:12 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 11:43:12 - mmengine - INFO - Epoch(train) [7][880/880] lr: 3.8400e-02 eta: 3:39:13 time: 0.4433 data_time: 0.0225 memory: 23498 grad_norm: 3.3883 top1_acc: 0.3158 top5_acc: 0.6842 loss_cls: 2.7060 loss: 2.7060 2022/09/08 11:43:22 - mmengine - INFO - Epoch(train) [8][20/880] lr: 3.7709e-02 eta: 3:39:10 time: 0.5176 data_time: 0.0799 memory: 23498 grad_norm: 3.2013 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.9255 loss: 2.9255 2022/09/08 11:43:31 - mmengine - INFO - Epoch(train) [8][40/880] lr: 3.7709e-02 eta: 3:39:02 time: 0.4566 data_time: 0.0232 memory: 23498 grad_norm: 3.1917 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.8036 loss: 2.8036 2022/09/08 11:43:40 - mmengine - INFO - Epoch(train) [8][60/880] lr: 3.7709e-02 eta: 3:38:52 time: 0.4487 data_time: 0.0226 memory: 23498 grad_norm: 3.2000 top1_acc: 0.1667 top5_acc: 0.5417 loss_cls: 2.8193 loss: 2.8193 2022/09/08 11:43:49 - mmengine - INFO - Epoch(train) [8][80/880] lr: 3.7709e-02 eta: 3:38:42 time: 0.4434 data_time: 0.0231 memory: 23498 grad_norm: 3.1614 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.7771 loss: 2.7771 2022/09/08 11:43:58 - mmengine - INFO - Epoch(train) [8][100/880] lr: 3.7709e-02 eta: 3:38:32 time: 0.4385 data_time: 0.0207 memory: 23498 grad_norm: 3.2189 top1_acc: 0.3333 top5_acc: 0.5417 loss_cls: 2.8293 loss: 2.8293 2022/09/08 11:44:07 - mmengine - INFO - Epoch(train) [8][120/880] lr: 3.7709e-02 eta: 3:38:22 time: 0.4452 data_time: 0.0238 memory: 23498 grad_norm: 3.1913 top1_acc: 0.2917 top5_acc: 0.5417 loss_cls: 2.8740 loss: 2.8740 2022/09/08 11:44:16 - mmengine - INFO - Epoch(train) [8][140/880] lr: 3.7709e-02 eta: 3:38:12 time: 0.4444 data_time: 0.0223 memory: 23498 grad_norm: 3.1096 top1_acc: 0.2917 top5_acc: 0.7083 loss_cls: 2.6375 loss: 2.6375 2022/09/08 11:44:25 - mmengine - INFO - Epoch(train) [8][160/880] lr: 3.7709e-02 eta: 3:38:03 time: 0.4482 data_time: 0.0236 memory: 23498 grad_norm: 3.3092 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.7540 loss: 2.7540 2022/09/08 11:44:34 - mmengine - INFO - Epoch(train) [8][180/880] lr: 3.7709e-02 eta: 3:37:53 time: 0.4521 data_time: 0.0267 memory: 23498 grad_norm: 3.1154 top1_acc: 0.2500 top5_acc: 0.5417 loss_cls: 2.8763 loss: 2.8763 2022/09/08 11:44:43 - mmengine - INFO - Epoch(train) [8][200/880] lr: 3.7709e-02 eta: 3:37:44 time: 0.4463 data_time: 0.0245 memory: 23498 grad_norm: 3.0762 top1_acc: 0.1667 top5_acc: 0.4167 loss_cls: 2.9325 loss: 2.9325 2022/09/08 11:44:51 - mmengine - INFO - Epoch(train) [8][220/880] lr: 3.7709e-02 eta: 3:37:34 time: 0.4461 data_time: 0.0231 memory: 23498 grad_norm: 3.2419 top1_acc: 0.2917 top5_acc: 0.5417 loss_cls: 2.7369 loss: 2.7369 2022/09/08 11:45:00 - mmengine - INFO - Epoch(train) [8][240/880] lr: 3.7709e-02 eta: 3:37:24 time: 0.4451 data_time: 0.0244 memory: 23498 grad_norm: 3.1788 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.8474 loss: 2.8474 2022/09/08 11:45:09 - mmengine - INFO - Epoch(train) [8][260/880] lr: 3.7709e-02 eta: 3:37:15 time: 0.4481 data_time: 0.0222 memory: 23498 grad_norm: 3.3974 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 2.7444 loss: 2.7444 2022/09/08 11:45:18 - mmengine - INFO - Epoch(train) [8][280/880] lr: 3.7709e-02 eta: 3:37:05 time: 0.4451 data_time: 0.0242 memory: 23498 grad_norm: 3.3064 top1_acc: 0.3750 top5_acc: 0.5417 loss_cls: 2.9092 loss: 2.9092 2022/09/08 11:45:27 - mmengine - INFO - Epoch(train) [8][300/880] lr: 3.7709e-02 eta: 3:36:55 time: 0.4447 data_time: 0.0233 memory: 23498 grad_norm: 3.3033 top1_acc: 0.2917 top5_acc: 0.5417 loss_cls: 2.8284 loss: 2.8284 2022/09/08 11:45:36 - mmengine - INFO - Epoch(train) [8][320/880] lr: 3.7709e-02 eta: 3:36:46 time: 0.4499 data_time: 0.0250 memory: 23498 grad_norm: 3.3926 top1_acc: 0.1667 top5_acc: 0.3750 loss_cls: 2.9030 loss: 2.9030 2022/09/08 11:45:45 - mmengine - INFO - Epoch(train) [8][340/880] lr: 3.7709e-02 eta: 3:36:36 time: 0.4473 data_time: 0.0215 memory: 23498 grad_norm: 3.3262 top1_acc: 0.2500 top5_acc: 0.5417 loss_cls: 2.8256 loss: 2.8256 2022/09/08 11:45:54 - mmengine - INFO - Epoch(train) [8][360/880] lr: 3.7709e-02 eta: 3:36:27 time: 0.4462 data_time: 0.0245 memory: 23498 grad_norm: 3.2091 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.7961 loss: 2.7961 2022/09/08 11:46:03 - mmengine - INFO - Epoch(train) [8][380/880] lr: 3.7709e-02 eta: 3:36:17 time: 0.4480 data_time: 0.0224 memory: 23498 grad_norm: 3.3195 top1_acc: 0.2500 top5_acc: 0.4583 loss_cls: 2.9811 loss: 2.9811 2022/09/08 11:46:12 - mmengine - INFO - Epoch(train) [8][400/880] lr: 3.7709e-02 eta: 3:36:08 time: 0.4456 data_time: 0.0246 memory: 23498 grad_norm: 3.2833 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 2.7933 loss: 2.7933 2022/09/08 11:46:21 - mmengine - INFO - Epoch(train) [8][420/880] lr: 3.7709e-02 eta: 3:35:58 time: 0.4455 data_time: 0.0210 memory: 23498 grad_norm: 3.3859 top1_acc: 0.2083 top5_acc: 0.5000 loss_cls: 2.9725 loss: 2.9725 2022/09/08 11:46:30 - mmengine - INFO - Epoch(train) [8][440/880] lr: 3.7709e-02 eta: 3:35:48 time: 0.4474 data_time: 0.0252 memory: 23498 grad_norm: 3.2382 top1_acc: 0.4583 top5_acc: 0.5417 loss_cls: 2.7773 loss: 2.7773 2022/09/08 11:46:39 - mmengine - INFO - Epoch(train) [8][460/880] lr: 3.7709e-02 eta: 3:35:40 time: 0.4585 data_time: 0.0223 memory: 23498 grad_norm: 3.5763 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.7860 loss: 2.7860 2022/09/08 11:46:48 - mmengine - INFO - Epoch(train) [8][480/880] lr: 3.7709e-02 eta: 3:35:30 time: 0.4448 data_time: 0.0252 memory: 23498 grad_norm: 3.3185 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 3.0984 loss: 3.0984 2022/09/08 11:46:57 - mmengine - INFO - Epoch(train) [8][500/880] lr: 3.7709e-02 eta: 3:35:20 time: 0.4454 data_time: 0.0223 memory: 23498 grad_norm: 3.2140 top1_acc: 0.2917 top5_acc: 0.5417 loss_cls: 2.8129 loss: 2.8129 2022/09/08 11:47:06 - mmengine - INFO - Epoch(train) [8][520/880] lr: 3.7709e-02 eta: 3:35:11 time: 0.4472 data_time: 0.0244 memory: 23498 grad_norm: 3.1601 top1_acc: 0.2083 top5_acc: 0.4167 loss_cls: 2.8978 loss: 2.8978 2022/09/08 11:47:15 - mmengine - INFO - Epoch(train) [8][540/880] lr: 3.7709e-02 eta: 3:35:01 time: 0.4451 data_time: 0.0226 memory: 23498 grad_norm: 3.2081 top1_acc: 0.2500 top5_acc: 0.6667 loss_cls: 2.8422 loss: 2.8422 2022/09/08 11:47:23 - mmengine - INFO - Epoch(train) [8][560/880] lr: 3.7709e-02 eta: 3:34:52 time: 0.4465 data_time: 0.0240 memory: 23498 grad_norm: 3.0690 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 2.8700 loss: 2.8700 2022/09/08 11:47:32 - mmengine - INFO - Epoch(train) [8][580/880] lr: 3.7709e-02 eta: 3:34:42 time: 0.4458 data_time: 0.0226 memory: 23498 grad_norm: 3.0910 top1_acc: 0.2917 top5_acc: 0.5000 loss_cls: 2.9049 loss: 2.9049 2022/09/08 11:47:41 - mmengine - INFO - Epoch(train) [8][600/880] lr: 3.7709e-02 eta: 3:34:32 time: 0.4445 data_time: 0.0238 memory: 23498 grad_norm: 3.2190 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 2.7055 loss: 2.7055 2022/09/08 11:47:50 - mmengine - INFO - Epoch(train) [8][620/880] lr: 3.7709e-02 eta: 3:34:23 time: 0.4459 data_time: 0.0235 memory: 23498 grad_norm: 3.3042 top1_acc: 0.4167 top5_acc: 0.5417 loss_cls: 2.8515 loss: 2.8515 2022/09/08 11:47:59 - mmengine - INFO - Epoch(train) [8][640/880] lr: 3.7709e-02 eta: 3:34:13 time: 0.4474 data_time: 0.0248 memory: 23498 grad_norm: 3.3551 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.9352 loss: 2.9352 2022/09/08 11:48:08 - mmengine - INFO - Epoch(train) [8][660/880] lr: 3.7709e-02 eta: 3:34:03 time: 0.4435 data_time: 0.0223 memory: 23498 grad_norm: 3.1314 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.8165 loss: 2.8165 2022/09/08 11:48:17 - mmengine - INFO - Epoch(train) [8][680/880] lr: 3.7709e-02 eta: 3:33:54 time: 0.4466 data_time: 0.0255 memory: 23498 grad_norm: 3.1154 top1_acc: 0.3333 top5_acc: 0.6250 loss_cls: 2.8776 loss: 2.8776 2022/09/08 11:48:26 - mmengine - INFO - Epoch(train) [8][700/880] lr: 3.7709e-02 eta: 3:33:45 time: 0.4526 data_time: 0.0230 memory: 23498 grad_norm: 3.2968 top1_acc: 0.3333 top5_acc: 0.7500 loss_cls: 2.8278 loss: 2.8278 2022/09/08 11:48:35 - mmengine - INFO - Epoch(train) [8][720/880] lr: 3.7709e-02 eta: 3:33:35 time: 0.4459 data_time: 0.0242 memory: 23498 grad_norm: 3.2966 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.8851 loss: 2.8851 2022/09/08 11:48:44 - mmengine - INFO - Epoch(train) [8][740/880] lr: 3.7709e-02 eta: 3:33:25 time: 0.4428 data_time: 0.0213 memory: 23498 grad_norm: 3.4092 top1_acc: 0.4167 top5_acc: 0.5000 loss_cls: 2.8916 loss: 2.8916 2022/09/08 11:48:53 - mmengine - INFO - Epoch(train) [8][760/880] lr: 3.7709e-02 eta: 3:33:16 time: 0.4464 data_time: 0.0249 memory: 23498 grad_norm: 3.4359 top1_acc: 0.1667 top5_acc: 0.6250 loss_cls: 2.9602 loss: 2.9602 2022/09/08 11:49:02 - mmengine - INFO - Epoch(train) [8][780/880] lr: 3.7709e-02 eta: 3:33:06 time: 0.4447 data_time: 0.0219 memory: 23498 grad_norm: 3.3499 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8394 loss: 2.8394 2022/09/08 11:49:11 - mmengine - INFO - Epoch(train) [8][800/880] lr: 3.7709e-02 eta: 3:32:57 time: 0.4496 data_time: 0.0254 memory: 23498 grad_norm: 3.2321 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7024 loss: 2.7024 2022/09/08 11:49:19 - mmengine - INFO - Epoch(train) [8][820/880] lr: 3.7709e-02 eta: 3:32:47 time: 0.4429 data_time: 0.0215 memory: 23498 grad_norm: 3.2393 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.6885 loss: 2.6885 2022/09/08 11:49:28 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 11:49:28 - mmengine - INFO - Epoch(train) [8][840/880] lr: 3.7709e-02 eta: 3:32:37 time: 0.4462 data_time: 0.0258 memory: 23498 grad_norm: 3.2284 top1_acc: 0.2917 top5_acc: 0.5000 loss_cls: 2.8664 loss: 2.8664 2022/09/08 11:49:37 - mmengine - INFO - Epoch(train) [8][860/880] lr: 3.7709e-02 eta: 3:32:28 time: 0.4468 data_time: 0.0225 memory: 23498 grad_norm: 3.2037 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.7682 loss: 2.7682 2022/09/08 11:49:46 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 11:49:46 - mmengine - INFO - Epoch(train) [8][880/880] lr: 3.7709e-02 eta: 3:32:17 time: 0.4352 data_time: 0.0213 memory: 23498 grad_norm: 3.1985 top1_acc: 0.3684 top5_acc: 0.6316 loss_cls: 2.6369 loss: 2.6369 2022/09/08 11:49:50 - mmengine - INFO - Epoch(val) [8][20/130] eta: 0:00:24 time: 0.2211 data_time: 0.0819 memory: 2693 2022/09/08 11:49:54 - mmengine - INFO - Epoch(val) [8][40/130] eta: 0:00:14 time: 0.1653 data_time: 0.0278 memory: 2693 2022/09/08 11:49:57 - mmengine - INFO - Epoch(val) [8][60/130] eta: 0:00:12 time: 0.1749 data_time: 0.0396 memory: 2693 2022/09/08 11:50:01 - mmengine - INFO - Epoch(val) [8][80/130] eta: 0:00:08 time: 0.1705 data_time: 0.0339 memory: 2693 2022/09/08 11:50:04 - mmengine - INFO - Epoch(val) [8][100/130] eta: 0:00:05 time: 0.1762 data_time: 0.0385 memory: 2693 2022/09/08 11:50:07 - mmengine - INFO - Epoch(val) [8][120/130] eta: 0:00:01 time: 0.1594 data_time: 0.0273 memory: 2693 2022/09/08 11:50:09 - mmengine - INFO - Epoch(val) [8][130/130] acc/top1: 0.3098 acc/top5: 0.5953 acc/mean1: 0.2453 2022/09/08 11:50:09 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4/best_acc/top1_epoch_6.pth is removed 2022/09/08 11:50:11 - mmengine - INFO - The best checkpoint with 0.3098 acc/top1 at 8 epoch is saved to best_acc/top1_epoch_8.pth. 2022/09/08 11:50:21 - mmengine - INFO - Epoch(train) [9][20/880] lr: 3.6904e-02 eta: 3:32:12 time: 0.5042 data_time: 0.0730 memory: 23498 grad_norm: 3.2084 top1_acc: 0.3750 top5_acc: 0.5417 loss_cls: 2.8102 loss: 2.8102 2022/09/08 11:50:30 - mmengine - INFO - Epoch(train) [9][40/880] lr: 3.6904e-02 eta: 3:32:04 time: 0.4535 data_time: 0.0264 memory: 23498 grad_norm: 3.3342 top1_acc: 0.2083 top5_acc: 0.5417 loss_cls: 2.7925 loss: 2.7925 2022/09/08 11:50:39 - mmengine - INFO - Epoch(train) [9][60/880] lr: 3.6904e-02 eta: 3:31:54 time: 0.4477 data_time: 0.0221 memory: 23498 grad_norm: 3.5152 top1_acc: 0.2500 top5_acc: 0.5833 loss_cls: 2.8870 loss: 2.8870 2022/09/08 11:50:47 - mmengine - INFO - Epoch(train) [9][80/880] lr: 3.6904e-02 eta: 3:31:44 time: 0.4418 data_time: 0.0224 memory: 23498 grad_norm: 3.4584 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.7809 loss: 2.7809 2022/09/08 11:50:56 - mmengine - INFO - Epoch(train) [9][100/880] lr: 3.6904e-02 eta: 3:31:34 time: 0.4400 data_time: 0.0199 memory: 23498 grad_norm: 3.3848 top1_acc: 0.1250 top5_acc: 0.4583 loss_cls: 2.8136 loss: 2.8136 2022/09/08 11:51:05 - mmengine - INFO - Epoch(train) [9][120/880] lr: 3.6904e-02 eta: 3:31:24 time: 0.4432 data_time: 0.0226 memory: 23498 grad_norm: 3.4012 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6921 loss: 2.6921 2022/09/08 11:51:14 - mmengine - INFO - Epoch(train) [9][140/880] lr: 3.6904e-02 eta: 3:31:14 time: 0.4413 data_time: 0.0216 memory: 23498 grad_norm: 3.4132 top1_acc: 0.2083 top5_acc: 0.5417 loss_cls: 2.8141 loss: 2.8141 2022/09/08 11:51:23 - mmengine - INFO - Epoch(train) [9][160/880] lr: 3.6904e-02 eta: 3:31:05 time: 0.4450 data_time: 0.0237 memory: 23498 grad_norm: 3.3450 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.7724 loss: 2.7724 2022/09/08 11:51:32 - mmengine - INFO - Epoch(train) [9][180/880] lr: 3.6904e-02 eta: 3:30:57 time: 0.4623 data_time: 0.0210 memory: 23498 grad_norm: 3.4698 top1_acc: 0.2917 top5_acc: 0.5000 loss_cls: 2.8105 loss: 2.8105 2022/09/08 11:51:41 - mmengine - INFO - Epoch(train) [9][200/880] lr: 3.6904e-02 eta: 3:30:47 time: 0.4443 data_time: 0.0248 memory: 23498 grad_norm: 3.3489 top1_acc: 0.3333 top5_acc: 0.5417 loss_cls: 2.7552 loss: 2.7552 2022/09/08 11:51:50 - mmengine - INFO - Epoch(train) [9][220/880] lr: 3.6904e-02 eta: 3:30:39 time: 0.4614 data_time: 0.0274 memory: 23498 grad_norm: 3.3084 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.8325 loss: 2.8325 2022/09/08 11:51:59 - mmengine - INFO - Epoch(train) [9][240/880] lr: 3.6904e-02 eta: 3:30:29 time: 0.4462 data_time: 0.0243 memory: 23498 grad_norm: 3.2709 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.8754 loss: 2.8754 2022/09/08 11:52:08 - mmengine - INFO - Epoch(train) [9][260/880] lr: 3.6904e-02 eta: 3:30:19 time: 0.4443 data_time: 0.0225 memory: 23498 grad_norm: 3.2606 top1_acc: 0.3333 top5_acc: 0.5417 loss_cls: 2.7567 loss: 2.7567 2022/09/08 11:52:17 - mmengine - INFO - Epoch(train) [9][280/880] lr: 3.6904e-02 eta: 3:30:11 time: 0.4629 data_time: 0.0249 memory: 23498 grad_norm: 3.2140 top1_acc: 0.2083 top5_acc: 0.6667 loss_cls: 2.8580 loss: 2.8580 2022/09/08 11:52:26 - mmengine - INFO - Epoch(train) [9][300/880] lr: 3.6904e-02 eta: 3:30:01 time: 0.4440 data_time: 0.0227 memory: 23498 grad_norm: 3.2886 top1_acc: 0.1250 top5_acc: 0.5417 loss_cls: 2.9407 loss: 2.9407 2022/09/08 11:52:35 - mmengine - INFO - Epoch(train) [9][320/880] lr: 3.6904e-02 eta: 3:29:52 time: 0.4469 data_time: 0.0261 memory: 23498 grad_norm: 3.4232 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7567 loss: 2.7567 2022/09/08 11:52:44 - mmengine - INFO - Epoch(train) [9][340/880] lr: 3.6904e-02 eta: 3:29:42 time: 0.4453 data_time: 0.0229 memory: 23498 grad_norm: 3.3323 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7659 loss: 2.7659 2022/09/08 11:52:53 - mmengine - INFO - Epoch(train) [9][360/880] lr: 3.6904e-02 eta: 3:29:33 time: 0.4464 data_time: 0.0248 memory: 23498 grad_norm: 3.3754 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8752 loss: 2.8752 2022/09/08 11:53:02 - mmengine - INFO - Epoch(train) [9][380/880] lr: 3.6904e-02 eta: 3:29:23 time: 0.4453 data_time: 0.0215 memory: 23498 grad_norm: 3.5379 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8731 loss: 2.8731 2022/09/08 11:53:11 - mmengine - INFO - Epoch(train) [9][400/880] lr: 3.6904e-02 eta: 3:29:14 time: 0.4467 data_time: 0.0258 memory: 23498 grad_norm: 3.3040 top1_acc: 0.1667 top5_acc: 0.5417 loss_cls: 2.7917 loss: 2.7917 2022/09/08 11:53:20 - mmengine - INFO - Epoch(train) [9][420/880] lr: 3.6904e-02 eta: 3:29:04 time: 0.4466 data_time: 0.0223 memory: 23498 grad_norm: 3.5316 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6825 loss: 2.6825 2022/09/08 11:53:29 - mmengine - INFO - Epoch(train) [9][440/880] lr: 3.6904e-02 eta: 3:28:55 time: 0.4452 data_time: 0.0245 memory: 23498 grad_norm: 3.4964 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8349 loss: 2.8349 2022/09/08 11:53:38 - mmengine - INFO - Epoch(train) [9][460/880] lr: 3.6904e-02 eta: 3:28:45 time: 0.4438 data_time: 0.0231 memory: 23498 grad_norm: 3.3611 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.7487 loss: 2.7487 2022/09/08 11:53:46 - mmengine - INFO - Epoch(train) [9][480/880] lr: 3.6904e-02 eta: 3:28:36 time: 0.4440 data_time: 0.0235 memory: 23498 grad_norm: 3.3377 top1_acc: 0.1667 top5_acc: 0.6250 loss_cls: 2.8091 loss: 2.8091 2022/09/08 11:53:55 - mmengine - INFO - Epoch(train) [9][500/880] lr: 3.6904e-02 eta: 3:28:26 time: 0.4451 data_time: 0.0220 memory: 23498 grad_norm: 3.2003 top1_acc: 0.2500 top5_acc: 0.5833 loss_cls: 2.7933 loss: 2.7933 2022/09/08 11:54:04 - mmengine - INFO - Epoch(train) [9][520/880] lr: 3.6904e-02 eta: 3:28:17 time: 0.4479 data_time: 0.0240 memory: 23498 grad_norm: 3.3359 top1_acc: 0.2083 top5_acc: 0.5833 loss_cls: 2.8709 loss: 2.8709 2022/09/08 11:54:13 - mmengine - INFO - Epoch(train) [9][540/880] lr: 3.6904e-02 eta: 3:28:07 time: 0.4456 data_time: 0.0228 memory: 23498 grad_norm: 3.6105 top1_acc: 0.2083 top5_acc: 0.4583 loss_cls: 2.7913 loss: 2.7913 2022/09/08 11:54:22 - mmengine - INFO - Epoch(train) [9][560/880] lr: 3.6904e-02 eta: 3:27:58 time: 0.4457 data_time: 0.0229 memory: 23498 grad_norm: 3.2943 top1_acc: 0.3750 top5_acc: 0.5417 loss_cls: 2.9125 loss: 2.9125 2022/09/08 11:54:31 - mmengine - INFO - Epoch(train) [9][580/880] lr: 3.6904e-02 eta: 3:27:48 time: 0.4452 data_time: 0.0236 memory: 23498 grad_norm: 3.2246 top1_acc: 0.4167 top5_acc: 0.5417 loss_cls: 2.7458 loss: 2.7458 2022/09/08 11:54:40 - mmengine - INFO - Epoch(train) [9][600/880] lr: 3.6904e-02 eta: 3:27:39 time: 0.4528 data_time: 0.0241 memory: 23498 grad_norm: 3.2121 top1_acc: 0.2500 top5_acc: 0.4167 loss_cls: 2.8128 loss: 2.8128 2022/09/08 11:54:49 - mmengine - INFO - Epoch(train) [9][620/880] lr: 3.6904e-02 eta: 3:27:30 time: 0.4465 data_time: 0.0218 memory: 23498 grad_norm: 3.3893 top1_acc: 0.4167 top5_acc: 0.5417 loss_cls: 2.8357 loss: 2.8357 2022/09/08 11:54:58 - mmengine - INFO - Epoch(train) [9][640/880] lr: 3.6904e-02 eta: 3:27:21 time: 0.4507 data_time: 0.0244 memory: 23498 grad_norm: 3.3032 top1_acc: 0.3333 top5_acc: 0.6250 loss_cls: 2.7569 loss: 2.7569 2022/09/08 11:55:07 - mmengine - INFO - Epoch(train) [9][660/880] lr: 3.6904e-02 eta: 3:27:11 time: 0.4451 data_time: 0.0236 memory: 23498 grad_norm: 3.2381 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.6564 loss: 2.6564 2022/09/08 11:55:16 - mmengine - INFO - Epoch(train) [9][680/880] lr: 3.6904e-02 eta: 3:27:01 time: 0.4450 data_time: 0.0246 memory: 23498 grad_norm: 3.1351 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.9359 loss: 2.9359 2022/09/08 11:55:25 - mmengine - INFO - Epoch(train) [9][700/880] lr: 3.6904e-02 eta: 3:26:52 time: 0.4442 data_time: 0.0219 memory: 23498 grad_norm: 3.2898 top1_acc: 0.2500 top5_acc: 0.5833 loss_cls: 2.9314 loss: 2.9314 2022/09/08 11:55:34 - mmengine - INFO - Epoch(train) [9][720/880] lr: 3.6904e-02 eta: 3:26:43 time: 0.4477 data_time: 0.0262 memory: 23498 grad_norm: 3.2733 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.7966 loss: 2.7966 2022/09/08 11:55:43 - mmengine - INFO - Epoch(train) [9][740/880] lr: 3.6904e-02 eta: 3:26:33 time: 0.4440 data_time: 0.0222 memory: 23498 grad_norm: 3.3093 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.7148 loss: 2.7148 2022/09/08 11:55:51 - mmengine - INFO - Epoch(train) [9][760/880] lr: 3.6904e-02 eta: 3:26:23 time: 0.4452 data_time: 0.0243 memory: 23498 grad_norm: 3.3619 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 2.7370 loss: 2.7370 2022/09/08 11:56:00 - mmengine - INFO - Epoch(train) [9][780/880] lr: 3.6904e-02 eta: 3:26:14 time: 0.4460 data_time: 0.0235 memory: 23498 grad_norm: 3.4014 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8155 loss: 2.8155 2022/09/08 11:56:09 - mmengine - INFO - Epoch(train) [9][800/880] lr: 3.6904e-02 eta: 3:26:05 time: 0.4464 data_time: 0.0247 memory: 23498 grad_norm: 3.4684 top1_acc: 0.5000 top5_acc: 0.5833 loss_cls: 2.7766 loss: 2.7766 2022/09/08 11:56:18 - mmengine - INFO - Epoch(train) [9][820/880] lr: 3.6904e-02 eta: 3:25:55 time: 0.4457 data_time: 0.0227 memory: 23498 grad_norm: 3.3586 top1_acc: 0.1250 top5_acc: 0.4583 loss_cls: 2.7869 loss: 2.7869 2022/09/08 11:56:27 - mmengine - INFO - Epoch(train) [9][840/880] lr: 3.6904e-02 eta: 3:25:46 time: 0.4537 data_time: 0.0243 memory: 23498 grad_norm: 3.2138 top1_acc: 0.2500 top5_acc: 0.5417 loss_cls: 2.8807 loss: 2.8807 2022/09/08 11:56:36 - mmengine - INFO - Epoch(train) [9][860/880] lr: 3.6904e-02 eta: 3:25:37 time: 0.4509 data_time: 0.0249 memory: 23498 grad_norm: 3.1793 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.7197 loss: 2.7197 2022/09/08 11:56:45 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 11:56:45 - mmengine - INFO - Epoch(train) [9][880/880] lr: 3.6904e-02 eta: 3:25:28 time: 0.4504 data_time: 0.0220 memory: 23498 grad_norm: 3.3341 top1_acc: 0.4211 top5_acc: 0.6842 loss_cls: 2.7378 loss: 2.7378 2022/09/08 11:56:56 - mmengine - INFO - Epoch(train) [10][20/880] lr: 3.5989e-02 eta: 3:25:24 time: 0.5221 data_time: 0.0852 memory: 23498 grad_norm: 3.3814 top1_acc: 0.2917 top5_acc: 0.5417 loss_cls: 2.8022 loss: 2.8022 2022/09/08 11:57:05 - mmengine - INFO - Epoch(train) [10][40/880] lr: 3.5989e-02 eta: 3:25:14 time: 0.4462 data_time: 0.0217 memory: 23498 grad_norm: 3.3402 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 2.7658 loss: 2.7658 2022/09/08 11:57:14 - mmengine - INFO - Epoch(train) [10][60/880] lr: 3.5989e-02 eta: 3:25:05 time: 0.4477 data_time: 0.0233 memory: 23498 grad_norm: 3.1748 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.8115 loss: 2.8115 2022/09/08 11:57:22 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 11:57:22 - mmengine - INFO - Epoch(train) [10][80/880] lr: 3.5989e-02 eta: 3:24:55 time: 0.4421 data_time: 0.0208 memory: 23498 grad_norm: 3.2519 top1_acc: 0.2917 top5_acc: 0.4583 loss_cls: 2.4565 loss: 2.4565 2022/09/08 11:57:31 - mmengine - INFO - Epoch(train) [10][100/880] lr: 3.5989e-02 eta: 3:24:46 time: 0.4445 data_time: 0.0195 memory: 23498 grad_norm: 3.2801 top1_acc: 0.2917 top5_acc: 0.7083 loss_cls: 2.7086 loss: 2.7086 2022/09/08 11:57:40 - mmengine - INFO - Epoch(train) [10][120/880] lr: 3.5989e-02 eta: 3:24:36 time: 0.4411 data_time: 0.0221 memory: 23498 grad_norm: 3.4590 top1_acc: 0.3750 top5_acc: 0.5417 loss_cls: 2.7510 loss: 2.7510 2022/09/08 11:57:49 - mmengine - INFO - Epoch(train) [10][140/880] lr: 3.5989e-02 eta: 3:24:26 time: 0.4418 data_time: 0.0203 memory: 23498 grad_norm: 3.5071 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.8436 loss: 2.8436 2022/09/08 11:57:58 - mmengine - INFO - Epoch(train) [10][160/880] lr: 3.5989e-02 eta: 3:24:16 time: 0.4424 data_time: 0.0227 memory: 23498 grad_norm: 3.3200 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.7356 loss: 2.7356 2022/09/08 11:58:07 - mmengine - INFO - Epoch(train) [10][180/880] lr: 3.5989e-02 eta: 3:24:07 time: 0.4466 data_time: 0.0213 memory: 23498 grad_norm: 3.3520 top1_acc: 0.2917 top5_acc: 0.7083 loss_cls: 2.7503 loss: 2.7503 2022/09/08 11:58:16 - mmengine - INFO - Epoch(train) [10][200/880] lr: 3.5989e-02 eta: 3:23:58 time: 0.4488 data_time: 0.0239 memory: 23498 grad_norm: 3.3423 top1_acc: 0.2500 top5_acc: 0.5417 loss_cls: 2.8575 loss: 2.8575 2022/09/08 11:58:25 - mmengine - INFO - Epoch(train) [10][220/880] lr: 3.5989e-02 eta: 3:23:48 time: 0.4481 data_time: 0.0211 memory: 23498 grad_norm: 3.2045 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8626 loss: 2.8626 2022/09/08 11:58:34 - mmengine - INFO - Epoch(train) [10][240/880] lr: 3.5989e-02 eta: 3:23:39 time: 0.4465 data_time: 0.0233 memory: 23498 grad_norm: 3.3726 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.8136 loss: 2.8136 2022/09/08 11:58:43 - mmengine - INFO - Epoch(train) [10][260/880] lr: 3.5989e-02 eta: 3:23:30 time: 0.4449 data_time: 0.0235 memory: 23498 grad_norm: 3.2819 top1_acc: 0.2917 top5_acc: 0.7083 loss_cls: 2.7941 loss: 2.7941 2022/09/08 11:58:51 - mmengine - INFO - Epoch(train) [10][280/880] lr: 3.5989e-02 eta: 3:23:20 time: 0.4438 data_time: 0.0235 memory: 23498 grad_norm: 3.2988 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 2.6154 loss: 2.6154 2022/09/08 11:59:00 - mmengine - INFO - Epoch(train) [10][300/880] lr: 3.5989e-02 eta: 3:23:10 time: 0.4441 data_time: 0.0226 memory: 23498 grad_norm: 3.3031 top1_acc: 0.3750 top5_acc: 0.4583 loss_cls: 2.7651 loss: 2.7651 2022/09/08 11:59:09 - mmengine - INFO - Epoch(train) [10][320/880] lr: 3.5989e-02 eta: 3:23:01 time: 0.4447 data_time: 0.0240 memory: 23498 grad_norm: 3.3772 top1_acc: 0.2917 top5_acc: 0.5000 loss_cls: 2.5859 loss: 2.5859 2022/09/08 11:59:18 - mmengine - INFO - Epoch(train) [10][340/880] lr: 3.5989e-02 eta: 3:22:51 time: 0.4443 data_time: 0.0228 memory: 23498 grad_norm: 3.2432 top1_acc: 0.2917 top5_acc: 0.7500 loss_cls: 2.6789 loss: 2.6789 2022/09/08 11:59:27 - mmengine - INFO - Epoch(train) [10][360/880] lr: 3.5989e-02 eta: 3:22:42 time: 0.4463 data_time: 0.0252 memory: 23498 grad_norm: 3.2621 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 2.7409 loss: 2.7409 2022/09/08 11:59:36 - mmengine - INFO - Epoch(train) [10][380/880] lr: 3.5989e-02 eta: 3:22:33 time: 0.4445 data_time: 0.0223 memory: 23498 grad_norm: 3.2839 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.7838 loss: 2.7838 2022/09/08 11:59:45 - mmengine - INFO - Epoch(train) [10][400/880] lr: 3.5989e-02 eta: 3:22:23 time: 0.4477 data_time: 0.0255 memory: 23498 grad_norm: 3.2059 top1_acc: 0.3333 top5_acc: 0.6250 loss_cls: 2.6541 loss: 2.6541 2022/09/08 11:59:54 - mmengine - INFO - Epoch(train) [10][420/880] lr: 3.5989e-02 eta: 3:22:14 time: 0.4493 data_time: 0.0224 memory: 23498 grad_norm: 3.3272 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.7596 loss: 2.7596 2022/09/08 12:00:06 - mmengine - INFO - Epoch(train) [10][440/880] lr: 3.5989e-02 eta: 3:22:16 time: 0.6206 data_time: 0.0330 memory: 23498 grad_norm: 3.2569 top1_acc: 0.2917 top5_acc: 0.6667 loss_cls: 2.8302 loss: 2.8302 2022/09/08 12:00:15 - mmengine - INFO - Epoch(train) [10][460/880] lr: 3.5989e-02 eta: 3:22:06 time: 0.4465 data_time: 0.0259 memory: 23498 grad_norm: 3.3946 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.8833 loss: 2.8833 2022/09/08 12:00:24 - mmengine - INFO - Epoch(train) [10][480/880] lr: 3.5989e-02 eta: 3:21:57 time: 0.4440 data_time: 0.0220 memory: 23498 grad_norm: 3.4172 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6504 loss: 2.6504 2022/09/08 12:00:33 - mmengine - INFO - Epoch(train) [10][500/880] lr: 3.5989e-02 eta: 3:21:48 time: 0.4485 data_time: 0.0269 memory: 23498 grad_norm: 3.4864 top1_acc: 0.3333 top5_acc: 0.7500 loss_cls: 2.6790 loss: 2.6790 2022/09/08 12:00:42 - mmengine - INFO - Epoch(train) [10][520/880] lr: 3.5989e-02 eta: 3:21:38 time: 0.4451 data_time: 0.0224 memory: 23498 grad_norm: 3.5701 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.7632 loss: 2.7632 2022/09/08 12:00:51 - mmengine - INFO - Epoch(train) [10][540/880] lr: 3.5989e-02 eta: 3:21:29 time: 0.4454 data_time: 0.0248 memory: 23498 grad_norm: 3.3752 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.6468 loss: 2.6468 2022/09/08 12:01:00 - mmengine - INFO - Epoch(train) [10][560/880] lr: 3.5989e-02 eta: 3:21:19 time: 0.4442 data_time: 0.0225 memory: 23498 grad_norm: 3.3847 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.6161 loss: 2.6161 2022/09/08 12:01:09 - mmengine - INFO - Epoch(train) [10][580/880] lr: 3.5989e-02 eta: 3:21:10 time: 0.4472 data_time: 0.0241 memory: 23498 grad_norm: 3.2941 top1_acc: 0.2500 top5_acc: 0.5417 loss_cls: 2.9574 loss: 2.9574 2022/09/08 12:01:18 - mmengine - INFO - Epoch(train) [10][600/880] lr: 3.5989e-02 eta: 3:21:00 time: 0.4448 data_time: 0.0211 memory: 23498 grad_norm: 3.3761 top1_acc: 0.3333 top5_acc: 0.6250 loss_cls: 2.7321 loss: 2.7321 2022/09/08 12:01:27 - mmengine - INFO - Epoch(train) [10][620/880] lr: 3.5989e-02 eta: 3:20:51 time: 0.4456 data_time: 0.0248 memory: 23498 grad_norm: 3.3443 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 2.8719 loss: 2.8719 2022/09/08 12:01:35 - mmengine - INFO - Epoch(train) [10][640/880] lr: 3.5989e-02 eta: 3:20:41 time: 0.4438 data_time: 0.0221 memory: 23498 grad_norm: 3.2308 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 2.5978 loss: 2.5978 2022/09/08 12:01:45 - mmengine - INFO - Epoch(train) [10][660/880] lr: 3.5989e-02 eta: 3:20:32 time: 0.4550 data_time: 0.0250 memory: 23498 grad_norm: 3.3928 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 2.6778 loss: 2.6778 2022/09/08 12:01:53 - mmengine - INFO - Epoch(train) [10][680/880] lr: 3.5989e-02 eta: 3:20:23 time: 0.4421 data_time: 0.0210 memory: 23498 grad_norm: 3.4167 top1_acc: 0.2917 top5_acc: 0.6667 loss_cls: 2.8125 loss: 2.8125 2022/09/08 12:02:03 - mmengine - INFO - Epoch(train) [10][700/880] lr: 3.5989e-02 eta: 3:20:14 time: 0.4604 data_time: 0.0256 memory: 23498 grad_norm: 3.4672 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 2.6482 loss: 2.6482 2022/09/08 12:02:11 - mmengine - INFO - Epoch(train) [10][720/880] lr: 3.5989e-02 eta: 3:20:05 time: 0.4444 data_time: 0.0224 memory: 23498 grad_norm: 3.4287 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.8326 loss: 2.8326 2022/09/08 12:02:21 - mmengine - INFO - Epoch(train) [10][740/880] lr: 3.5989e-02 eta: 3:19:56 time: 0.4532 data_time: 0.0258 memory: 23498 grad_norm: 3.5497 top1_acc: 0.2500 top5_acc: 0.5417 loss_cls: 2.8375 loss: 2.8375 2022/09/08 12:02:29 - mmengine - INFO - Epoch(train) [10][760/880] lr: 3.5989e-02 eta: 3:19:46 time: 0.4438 data_time: 0.0221 memory: 23498 grad_norm: 3.4006 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7881 loss: 2.7881 2022/09/08 12:02:38 - mmengine - INFO - Epoch(train) [10][780/880] lr: 3.5989e-02 eta: 3:19:37 time: 0.4455 data_time: 0.0237 memory: 23498 grad_norm: 3.3155 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 2.7926 loss: 2.7926 2022/09/08 12:02:47 - mmengine - INFO - Epoch(train) [10][800/880] lr: 3.5989e-02 eta: 3:19:28 time: 0.4515 data_time: 0.0241 memory: 23498 grad_norm: 3.4055 top1_acc: 0.2917 top5_acc: 0.7083 loss_cls: 2.7357 loss: 2.7357 2022/09/08 12:02:56 - mmengine - INFO - Epoch(train) [10][820/880] lr: 3.5989e-02 eta: 3:19:18 time: 0.4462 data_time: 0.0254 memory: 23498 grad_norm: 3.3246 top1_acc: 0.2083 top5_acc: 0.4583 loss_cls: 2.9123 loss: 2.9123 2022/09/08 12:03:05 - mmengine - INFO - Epoch(train) [10][840/880] lr: 3.5989e-02 eta: 3:19:09 time: 0.4450 data_time: 0.0208 memory: 23498 grad_norm: 3.4451 top1_acc: 0.2500 top5_acc: 0.4583 loss_cls: 2.8075 loss: 2.8075 2022/09/08 12:03:14 - mmengine - INFO - Epoch(train) [10][860/880] lr: 3.5989e-02 eta: 3:18:59 time: 0.4446 data_time: 0.0250 memory: 23498 grad_norm: 3.4244 top1_acc: 0.2500 top5_acc: 0.6667 loss_cls: 2.9093 loss: 2.9093 2022/09/08 12:03:23 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 12:03:23 - mmengine - INFO - Epoch(train) [10][880/880] lr: 3.5989e-02 eta: 3:18:51 time: 0.4621 data_time: 0.0200 memory: 23498 grad_norm: 3.3765 top1_acc: 0.3684 top5_acc: 0.5789 loss_cls: 2.7821 loss: 2.7821 2022/09/08 12:03:28 - mmengine - INFO - Epoch(val) [10][20/130] eta: 0:00:24 time: 0.2265 data_time: 0.0896 memory: 2693 2022/09/08 12:03:31 - mmengine - INFO - Epoch(val) [10][40/130] eta: 0:00:14 time: 0.1614 data_time: 0.0245 memory: 2693 2022/09/08 12:03:35 - mmengine - INFO - Epoch(val) [10][60/130] eta: 0:00:11 time: 0.1708 data_time: 0.0330 memory: 2693 2022/09/08 12:03:38 - mmengine - INFO - Epoch(val) [10][80/130] eta: 0:00:08 time: 0.1630 data_time: 0.0261 memory: 2693 2022/09/08 12:03:41 - mmengine - INFO - Epoch(val) [10][100/130] eta: 0:00:04 time: 0.1661 data_time: 0.0293 memory: 2693 2022/09/08 12:03:44 - mmengine - INFO - Epoch(val) [10][120/130] eta: 0:00:01 time: 0.1659 data_time: 0.0306 memory: 2693 2022/09/08 12:03:47 - mmengine - INFO - Epoch(val) [10][130/130] acc/top1: 0.3199 acc/top5: 0.6097 acc/mean1: 0.2528 2022/09/08 12:03:47 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4/best_acc/top1_epoch_8.pth is removed 2022/09/08 12:03:48 - mmengine - INFO - The best checkpoint with 0.3199 acc/top1 at 10 epoch is saved to best_acc/top1_epoch_10.pth. 2022/09/08 12:03:58 - mmengine - INFO - Epoch(train) [11][20/880] lr: 3.4970e-02 eta: 3:18:44 time: 0.4931 data_time: 0.0663 memory: 23498 grad_norm: 3.2700 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.7451 loss: 2.7451 2022/09/08 12:04:07 - mmengine - INFO - Epoch(train) [11][40/880] lr: 3.4970e-02 eta: 3:18:35 time: 0.4488 data_time: 0.0197 memory: 23498 grad_norm: 3.3881 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.7426 loss: 2.7426 2022/09/08 12:04:16 - mmengine - INFO - Epoch(train) [11][60/880] lr: 3.4970e-02 eta: 3:18:26 time: 0.4509 data_time: 0.0246 memory: 23498 grad_norm: 3.3439 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 2.5886 loss: 2.5886 2022/09/08 12:04:25 - mmengine - INFO - Epoch(train) [11][80/880] lr: 3.4970e-02 eta: 3:18:17 time: 0.4560 data_time: 0.0211 memory: 23498 grad_norm: 3.2905 top1_acc: 0.4583 top5_acc: 0.5417 loss_cls: 2.6604 loss: 2.6604 2022/09/08 12:04:34 - mmengine - INFO - Epoch(train) [11][100/880] lr: 3.4970e-02 eta: 3:18:08 time: 0.4541 data_time: 0.0255 memory: 23498 grad_norm: 3.3208 top1_acc: 0.5000 top5_acc: 0.5833 loss_cls: 2.6660 loss: 2.6660 2022/09/08 12:04:43 - mmengine - INFO - Epoch(train) [11][120/880] lr: 3.4970e-02 eta: 3:17:59 time: 0.4470 data_time: 0.0213 memory: 23498 grad_norm: 3.2619 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.7617 loss: 2.7617 2022/09/08 12:04:52 - mmengine - INFO - Epoch(train) [11][140/880] lr: 3.4970e-02 eta: 3:17:50 time: 0.4476 data_time: 0.0216 memory: 23498 grad_norm: 3.4731 top1_acc: 0.2917 top5_acc: 0.6667 loss_cls: 2.6859 loss: 2.6859 2022/09/08 12:05:01 - mmengine - INFO - Epoch(train) [11][160/880] lr: 3.4970e-02 eta: 3:17:40 time: 0.4457 data_time: 0.0216 memory: 23498 grad_norm: 3.3140 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 2.7269 loss: 2.7269 2022/09/08 12:05:10 - mmengine - INFO - Epoch(train) [11][180/880] lr: 3.4970e-02 eta: 3:17:31 time: 0.4442 data_time: 0.0210 memory: 23498 grad_norm: 3.3618 top1_acc: 0.3333 top5_acc: 0.5417 loss_cls: 2.7711 loss: 2.7711 2022/09/08 12:05:19 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 12:05:19 - mmengine - INFO - Epoch(train) [11][200/880] lr: 3.4970e-02 eta: 3:17:21 time: 0.4438 data_time: 0.0224 memory: 23498 grad_norm: 3.4007 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7532 loss: 2.7532 2022/09/08 12:05:28 - mmengine - INFO - Epoch(train) [11][220/880] lr: 3.4970e-02 eta: 3:17:12 time: 0.4451 data_time: 0.0214 memory: 23498 grad_norm: 3.3135 top1_acc: 0.3750 top5_acc: 0.5417 loss_cls: 2.6260 loss: 2.6260 2022/09/08 12:05:36 - mmengine - INFO - Epoch(train) [11][240/880] lr: 3.4970e-02 eta: 3:17:02 time: 0.4418 data_time: 0.0223 memory: 23498 grad_norm: 3.3625 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.4550 loss: 2.4550 2022/09/08 12:05:45 - mmengine - INFO - Epoch(train) [11][260/880] lr: 3.4970e-02 eta: 3:16:53 time: 0.4492 data_time: 0.0216 memory: 23498 grad_norm: 3.4288 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7551 loss: 2.7551 2022/09/08 12:05:54 - mmengine - INFO - Epoch(train) [11][280/880] lr: 3.4970e-02 eta: 3:16:44 time: 0.4472 data_time: 0.0273 memory: 23498 grad_norm: 3.5124 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 2.6647 loss: 2.6647 2022/09/08 12:06:03 - mmengine - INFO - Epoch(train) [11][300/880] lr: 3.4970e-02 eta: 3:16:34 time: 0.4461 data_time: 0.0222 memory: 23498 grad_norm: 3.2553 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.7915 loss: 2.7915 2022/09/08 12:06:12 - mmengine - INFO - Epoch(train) [11][320/880] lr: 3.4970e-02 eta: 3:16:25 time: 0.4443 data_time: 0.0237 memory: 23498 grad_norm: 3.4506 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.6849 loss: 2.6849 2022/09/08 12:06:21 - mmengine - INFO - Epoch(train) [11][340/880] lr: 3.4970e-02 eta: 3:16:15 time: 0.4459 data_time: 0.0219 memory: 23498 grad_norm: 3.3914 top1_acc: 0.5417 top5_acc: 0.6250 loss_cls: 2.6836 loss: 2.6836 2022/09/08 12:06:30 - mmengine - INFO - Epoch(train) [11][360/880] lr: 3.4970e-02 eta: 3:16:06 time: 0.4452 data_time: 0.0232 memory: 23498 grad_norm: 3.4866 top1_acc: 0.2917 top5_acc: 0.7500 loss_cls: 2.6926 loss: 2.6926 2022/09/08 12:06:39 - mmengine - INFO - Epoch(train) [11][380/880] lr: 3.4970e-02 eta: 3:15:56 time: 0.4429 data_time: 0.0208 memory: 23498 grad_norm: 3.5714 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 2.7335 loss: 2.7335 2022/09/08 12:06:48 - mmengine - INFO - Epoch(train) [11][400/880] lr: 3.4970e-02 eta: 3:15:47 time: 0.4502 data_time: 0.0238 memory: 23498 grad_norm: 3.4791 top1_acc: 0.2083 top5_acc: 0.5833 loss_cls: 2.8850 loss: 2.8850 2022/09/08 12:06:57 - mmengine - INFO - Epoch(train) [11][420/880] lr: 3.4970e-02 eta: 3:15:38 time: 0.4451 data_time: 0.0227 memory: 23498 grad_norm: 3.3398 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.6423 loss: 2.6423 2022/09/08 12:07:06 - mmengine - INFO - Epoch(train) [11][440/880] lr: 3.4970e-02 eta: 3:15:29 time: 0.4510 data_time: 0.0258 memory: 23498 grad_norm: 3.3949 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.6392 loss: 2.6392 2022/09/08 12:07:15 - mmengine - INFO - Epoch(train) [11][460/880] lr: 3.4970e-02 eta: 3:15:19 time: 0.4454 data_time: 0.0215 memory: 23498 grad_norm: 3.4408 top1_acc: 0.2917 top5_acc: 0.5417 loss_cls: 2.7223 loss: 2.7223 2022/09/08 12:07:24 - mmengine - INFO - Epoch(train) [11][480/880] lr: 3.4970e-02 eta: 3:15:10 time: 0.4478 data_time: 0.0246 memory: 23498 grad_norm: 3.5722 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8710 loss: 2.8710 2022/09/08 12:07:32 - mmengine - INFO - Epoch(train) [11][500/880] lr: 3.4970e-02 eta: 3:15:01 time: 0.4423 data_time: 0.0208 memory: 23498 grad_norm: 3.5241 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.7976 loss: 2.7976 2022/09/08 12:07:42 - mmengine - INFO - Epoch(train) [11][520/880] lr: 3.4970e-02 eta: 3:14:52 time: 0.4547 data_time: 0.0247 memory: 23498 grad_norm: 3.3877 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.7067 loss: 2.7067 2022/09/08 12:07:51 - mmengine - INFO - Epoch(train) [11][540/880] lr: 3.4970e-02 eta: 3:14:43 time: 0.4485 data_time: 0.0237 memory: 23498 grad_norm: 3.4510 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.5976 loss: 2.5976 2022/09/08 12:07:59 - mmengine - INFO - Epoch(train) [11][560/880] lr: 3.4970e-02 eta: 3:14:33 time: 0.4453 data_time: 0.0245 memory: 23498 grad_norm: 3.1543 top1_acc: 0.2500 top5_acc: 0.7083 loss_cls: 2.8549 loss: 2.8549 2022/09/08 12:08:08 - mmengine - INFO - Epoch(train) [11][580/880] lr: 3.4970e-02 eta: 3:14:24 time: 0.4445 data_time: 0.0230 memory: 23498 grad_norm: 3.3992 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.6962 loss: 2.6962 2022/09/08 12:08:17 - mmengine - INFO - Epoch(train) [11][600/880] lr: 3.4970e-02 eta: 3:14:14 time: 0.4453 data_time: 0.0250 memory: 23498 grad_norm: 3.5468 top1_acc: 0.2083 top5_acc: 0.6667 loss_cls: 2.7517 loss: 2.7517 2022/09/08 12:08:26 - mmengine - INFO - Epoch(train) [11][620/880] lr: 3.4970e-02 eta: 3:14:05 time: 0.4458 data_time: 0.0242 memory: 23498 grad_norm: 3.3146 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.6401 loss: 2.6401 2022/09/08 12:08:35 - mmengine - INFO - Epoch(train) [11][640/880] lr: 3.4970e-02 eta: 3:13:56 time: 0.4471 data_time: 0.0248 memory: 23498 grad_norm: 3.2280 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 2.7279 loss: 2.7279 2022/09/08 12:08:44 - mmengine - INFO - Epoch(train) [11][660/880] lr: 3.4970e-02 eta: 3:13:46 time: 0.4458 data_time: 0.0235 memory: 23498 grad_norm: 3.2694 top1_acc: 0.4167 top5_acc: 0.8333 loss_cls: 2.6053 loss: 2.6053 2022/09/08 12:08:53 - mmengine - INFO - Epoch(train) [11][680/880] lr: 3.4970e-02 eta: 3:13:37 time: 0.4458 data_time: 0.0241 memory: 23498 grad_norm: 3.4686 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.7006 loss: 2.7006 2022/09/08 12:09:02 - mmengine - INFO - Epoch(train) [11][700/880] lr: 3.4970e-02 eta: 3:13:28 time: 0.4450 data_time: 0.0229 memory: 23498 grad_norm: 3.3408 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6138 loss: 2.6138 2022/09/08 12:09:11 - mmengine - INFO - Epoch(train) [11][720/880] lr: 3.4970e-02 eta: 3:13:18 time: 0.4464 data_time: 0.0251 memory: 23498 grad_norm: 3.3850 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 2.7473 loss: 2.7473 2022/09/08 12:09:20 - mmengine - INFO - Epoch(train) [11][740/880] lr: 3.4970e-02 eta: 3:13:09 time: 0.4455 data_time: 0.0240 memory: 23498 grad_norm: 3.6121 top1_acc: 0.2500 top5_acc: 0.5833 loss_cls: 2.7446 loss: 2.7446 2022/09/08 12:09:29 - mmengine - INFO - Epoch(train) [11][760/880] lr: 3.4970e-02 eta: 3:13:00 time: 0.4577 data_time: 0.0250 memory: 23498 grad_norm: 3.5536 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6397 loss: 2.6397 2022/09/08 12:09:38 - mmengine - INFO - Epoch(train) [11][780/880] lr: 3.4970e-02 eta: 3:12:51 time: 0.4465 data_time: 0.0233 memory: 23498 grad_norm: 3.3789 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.7231 loss: 2.7231 2022/09/08 12:09:47 - mmengine - INFO - Epoch(train) [11][800/880] lr: 3.4970e-02 eta: 3:12:42 time: 0.4466 data_time: 0.0254 memory: 23498 grad_norm: 3.4303 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.6356 loss: 2.6356 2022/09/08 12:09:56 - mmengine - INFO - Epoch(train) [11][820/880] lr: 3.4970e-02 eta: 3:12:32 time: 0.4451 data_time: 0.0219 memory: 23498 grad_norm: 3.3766 top1_acc: 0.2917 top5_acc: 0.4583 loss_cls: 2.6582 loss: 2.6582 2022/09/08 12:10:04 - mmengine - INFO - Epoch(train) [11][840/880] lr: 3.4970e-02 eta: 3:12:23 time: 0.4456 data_time: 0.0235 memory: 23498 grad_norm: 3.4334 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.8055 loss: 2.8055 2022/09/08 12:10:13 - mmengine - INFO - Epoch(train) [11][860/880] lr: 3.4970e-02 eta: 3:12:13 time: 0.4436 data_time: 0.0228 memory: 23498 grad_norm: 3.3668 top1_acc: 0.5417 top5_acc: 0.6250 loss_cls: 2.7662 loss: 2.7662 2022/09/08 12:10:23 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 12:10:23 - mmengine - INFO - Epoch(train) [11][880/880] lr: 3.4970e-02 eta: 3:12:05 time: 0.4592 data_time: 0.0218 memory: 23498 grad_norm: 3.5096 top1_acc: 0.1579 top5_acc: 0.5789 loss_cls: 2.7687 loss: 2.7687 2022/09/08 12:10:33 - mmengine - INFO - Epoch(train) [12][20/880] lr: 3.3854e-02 eta: 3:11:59 time: 0.5210 data_time: 0.0795 memory: 23498 grad_norm: 3.4693 top1_acc: 0.1250 top5_acc: 0.4583 loss_cls: 2.8301 loss: 2.8301 2022/09/08 12:10:42 - mmengine - INFO - Epoch(train) [12][40/880] lr: 3.3854e-02 eta: 3:11:50 time: 0.4540 data_time: 0.0228 memory: 23498 grad_norm: 3.4688 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.6013 loss: 2.6013 2022/09/08 12:10:51 - mmengine - INFO - Epoch(train) [12][60/880] lr: 3.3854e-02 eta: 3:11:41 time: 0.4497 data_time: 0.0222 memory: 23498 grad_norm: 3.5832 top1_acc: 0.2083 top5_acc: 0.6250 loss_cls: 2.6160 loss: 2.6160 2022/09/08 12:11:00 - mmengine - INFO - Epoch(train) [12][80/880] lr: 3.3854e-02 eta: 3:11:32 time: 0.4497 data_time: 0.0226 memory: 23498 grad_norm: 3.5698 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.6959 loss: 2.6959 2022/09/08 12:11:09 - mmengine - INFO - Epoch(train) [12][100/880] lr: 3.3854e-02 eta: 3:11:23 time: 0.4477 data_time: 0.0215 memory: 23498 grad_norm: 3.4190 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.7462 loss: 2.7462 2022/09/08 12:11:18 - mmengine - INFO - Epoch(train) [12][120/880] lr: 3.3854e-02 eta: 3:11:13 time: 0.4433 data_time: 0.0216 memory: 23498 grad_norm: 3.2486 top1_acc: 0.4167 top5_acc: 0.5417 loss_cls: 2.6700 loss: 2.6700 2022/09/08 12:11:27 - mmengine - INFO - Epoch(train) [12][140/880] lr: 3.3854e-02 eta: 3:11:04 time: 0.4514 data_time: 0.0206 memory: 23498 grad_norm: 3.3557 top1_acc: 0.2083 top5_acc: 0.6250 loss_cls: 2.7094 loss: 2.7094 2022/09/08 12:11:36 - mmengine - INFO - Epoch(train) [12][160/880] lr: 3.3854e-02 eta: 3:10:55 time: 0.4507 data_time: 0.0240 memory: 23498 grad_norm: 3.3171 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 2.7607 loss: 2.7607 2022/09/08 12:11:45 - mmengine - INFO - Epoch(train) [12][180/880] lr: 3.3854e-02 eta: 3:10:46 time: 0.4517 data_time: 0.0219 memory: 23498 grad_norm: 3.4238 top1_acc: 0.2917 top5_acc: 0.6667 loss_cls: 2.6621 loss: 2.6621 2022/09/08 12:11:54 - mmengine - INFO - Epoch(train) [12][200/880] lr: 3.3854e-02 eta: 3:10:37 time: 0.4431 data_time: 0.0239 memory: 23498 grad_norm: 3.4126 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 2.5348 loss: 2.5348 2022/09/08 12:12:03 - mmengine - INFO - Epoch(train) [12][220/880] lr: 3.3854e-02 eta: 3:10:28 time: 0.4522 data_time: 0.0215 memory: 23498 grad_norm: 3.4672 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5799 loss: 2.5799 2022/09/08 12:12:12 - mmengine - INFO - Epoch(train) [12][240/880] lr: 3.3854e-02 eta: 3:10:18 time: 0.4452 data_time: 0.0237 memory: 23498 grad_norm: 3.4537 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6518 loss: 2.6518 2022/09/08 12:12:21 - mmengine - INFO - Epoch(train) [12][260/880] lr: 3.3854e-02 eta: 3:10:09 time: 0.4445 data_time: 0.0194 memory: 23498 grad_norm: 3.2667 top1_acc: 0.5417 top5_acc: 0.6667 loss_cls: 2.6347 loss: 2.6347 2022/09/08 12:12:30 - mmengine - INFO - Epoch(train) [12][280/880] lr: 3.3854e-02 eta: 3:10:00 time: 0.4606 data_time: 0.0236 memory: 23498 grad_norm: 3.3008 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.7264 loss: 2.7264 2022/09/08 12:12:39 - mmengine - INFO - Epoch(train) [12][300/880] lr: 3.3854e-02 eta: 3:09:51 time: 0.4454 data_time: 0.0237 memory: 23498 grad_norm: 3.3849 top1_acc: 0.4167 top5_acc: 0.8333 loss_cls: 2.6278 loss: 2.6278 2022/09/08 12:12:48 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 12:12:48 - mmengine - INFO - Epoch(train) [12][320/880] lr: 3.3854e-02 eta: 3:09:43 time: 0.4641 data_time: 0.0230 memory: 23498 grad_norm: 3.4733 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.7410 loss: 2.7410 2022/09/08 12:12:57 - mmengine - INFO - Epoch(train) [12][340/880] lr: 3.3854e-02 eta: 3:09:33 time: 0.4466 data_time: 0.0244 memory: 23498 grad_norm: 3.2934 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.6449 loss: 2.6449 2022/09/08 12:13:06 - mmengine - INFO - Epoch(train) [12][360/880] lr: 3.3854e-02 eta: 3:09:24 time: 0.4483 data_time: 0.0236 memory: 23498 grad_norm: 3.3199 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.6868 loss: 2.6868 2022/09/08 12:13:15 - mmengine - INFO - Epoch(train) [12][380/880] lr: 3.3854e-02 eta: 3:09:15 time: 0.4442 data_time: 0.0224 memory: 23498 grad_norm: 3.3253 top1_acc: 0.3750 top5_acc: 0.7917 loss_cls: 2.5668 loss: 2.5668 2022/09/08 12:13:24 - mmengine - INFO - Epoch(train) [12][400/880] lr: 3.3854e-02 eta: 3:09:06 time: 0.4651 data_time: 0.0245 memory: 23498 grad_norm: 3.4664 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 2.7725 loss: 2.7725 2022/09/08 12:13:33 - mmengine - INFO - Epoch(train) [12][420/880] lr: 3.3854e-02 eta: 3:08:57 time: 0.4424 data_time: 0.0207 memory: 23498 grad_norm: 3.3361 top1_acc: 0.2500 top5_acc: 0.5417 loss_cls: 2.8010 loss: 2.8010 2022/09/08 12:13:42 - mmengine - INFO - Epoch(train) [12][440/880] lr: 3.3854e-02 eta: 3:08:48 time: 0.4453 data_time: 0.0252 memory: 23498 grad_norm: 3.4291 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.5396 loss: 2.5396 2022/09/08 12:13:51 - mmengine - INFO - Epoch(train) [12][460/880] lr: 3.3854e-02 eta: 3:08:38 time: 0.4439 data_time: 0.0223 memory: 23498 grad_norm: 3.3726 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 2.7104 loss: 2.7104 2022/09/08 12:14:00 - mmengine - INFO - Epoch(train) [12][480/880] lr: 3.3854e-02 eta: 3:08:29 time: 0.4468 data_time: 0.0256 memory: 23498 grad_norm: 3.3719 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 2.7451 loss: 2.7451 2022/09/08 12:14:09 - mmengine - INFO - Epoch(train) [12][500/880] lr: 3.3854e-02 eta: 3:08:20 time: 0.4450 data_time: 0.0222 memory: 23498 grad_norm: 3.4632 top1_acc: 0.2083 top5_acc: 0.5417 loss_cls: 2.6316 loss: 2.6316 2022/09/08 12:14:18 - mmengine - INFO - Epoch(train) [12][520/880] lr: 3.3854e-02 eta: 3:08:10 time: 0.4472 data_time: 0.0254 memory: 23498 grad_norm: 3.5109 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.6959 loss: 2.6959 2022/09/08 12:14:27 - mmengine - INFO - Epoch(train) [12][540/880] lr: 3.3854e-02 eta: 3:08:01 time: 0.4464 data_time: 0.0221 memory: 23498 grad_norm: 3.4778 top1_acc: 0.1667 top5_acc: 0.5417 loss_cls: 2.7098 loss: 2.7098 2022/09/08 12:14:35 - mmengine - INFO - Epoch(train) [12][560/880] lr: 3.3854e-02 eta: 3:07:52 time: 0.4467 data_time: 0.0255 memory: 23498 grad_norm: 3.4921 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 2.5831 loss: 2.5831 2022/09/08 12:14:45 - mmengine - INFO - Epoch(train) [12][580/880] lr: 3.3854e-02 eta: 3:07:43 time: 0.4601 data_time: 0.0238 memory: 23498 grad_norm: 3.3238 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6501 loss: 2.6501 2022/09/08 12:14:54 - mmengine - INFO - Epoch(train) [12][600/880] lr: 3.3854e-02 eta: 3:07:34 time: 0.4504 data_time: 0.0295 memory: 23498 grad_norm: 3.2545 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.6277 loss: 2.6277 2022/09/08 12:15:03 - mmengine - INFO - Epoch(train) [12][620/880] lr: 3.3854e-02 eta: 3:07:25 time: 0.4593 data_time: 0.0215 memory: 23498 grad_norm: 3.4625 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.4923 loss: 2.4923 2022/09/08 12:15:12 - mmengine - INFO - Epoch(train) [12][640/880] lr: 3.3854e-02 eta: 3:07:16 time: 0.4506 data_time: 0.0294 memory: 23498 grad_norm: 3.3082 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7371 loss: 2.7371 2022/09/08 12:15:21 - mmengine - INFO - Epoch(train) [12][660/880] lr: 3.3854e-02 eta: 3:07:07 time: 0.4449 data_time: 0.0220 memory: 23498 grad_norm: 3.4102 top1_acc: 0.4583 top5_acc: 0.5833 loss_cls: 2.4509 loss: 2.4509 2022/09/08 12:15:30 - mmengine - INFO - Epoch(train) [12][680/880] lr: 3.3854e-02 eta: 3:06:58 time: 0.4474 data_time: 0.0246 memory: 23498 grad_norm: 3.5020 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6733 loss: 2.6733 2022/09/08 12:15:39 - mmengine - INFO - Epoch(train) [12][700/880] lr: 3.3854e-02 eta: 3:06:48 time: 0.4473 data_time: 0.0254 memory: 23498 grad_norm: 3.4330 top1_acc: 0.3333 top5_acc: 0.7500 loss_cls: 2.7063 loss: 2.7063 2022/09/08 12:15:48 - mmengine - INFO - Epoch(train) [12][720/880] lr: 3.3854e-02 eta: 3:06:39 time: 0.4519 data_time: 0.0253 memory: 23498 grad_norm: 3.2726 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.7228 loss: 2.7228 2022/09/08 12:15:57 - mmengine - INFO - Epoch(train) [12][740/880] lr: 3.3854e-02 eta: 3:06:30 time: 0.4442 data_time: 0.0226 memory: 23498 grad_norm: 3.3038 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.8508 loss: 2.8508 2022/09/08 12:16:06 - mmengine - INFO - Epoch(train) [12][760/880] lr: 3.3854e-02 eta: 3:06:21 time: 0.4459 data_time: 0.0246 memory: 23498 grad_norm: 3.4164 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.6340 loss: 2.6340 2022/09/08 12:16:14 - mmengine - INFO - Epoch(train) [12][780/880] lr: 3.3854e-02 eta: 3:06:11 time: 0.4438 data_time: 0.0210 memory: 23498 grad_norm: 3.3870 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8047 loss: 2.8047 2022/09/08 12:16:23 - mmengine - INFO - Epoch(train) [12][800/880] lr: 3.3854e-02 eta: 3:06:02 time: 0.4440 data_time: 0.0236 memory: 23498 grad_norm: 3.3770 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.6578 loss: 2.6578 2022/09/08 12:16:32 - mmengine - INFO - Epoch(train) [12][820/880] lr: 3.3854e-02 eta: 3:05:53 time: 0.4447 data_time: 0.0230 memory: 23498 grad_norm: 3.4299 top1_acc: 0.4167 top5_acc: 0.5417 loss_cls: 2.5744 loss: 2.5744 2022/09/08 12:16:41 - mmengine - INFO - Epoch(train) [12][840/880] lr: 3.3854e-02 eta: 3:05:43 time: 0.4467 data_time: 0.0237 memory: 23498 grad_norm: 3.5885 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5871 loss: 2.5871 2022/09/08 12:16:50 - mmengine - INFO - Epoch(train) [12][860/880] lr: 3.3854e-02 eta: 3:05:34 time: 0.4450 data_time: 0.0217 memory: 23498 grad_norm: 3.5967 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.4925 loss: 2.4925 2022/09/08 12:16:59 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 12:16:59 - mmengine - INFO - Epoch(train) [12][880/880] lr: 3.3854e-02 eta: 3:05:24 time: 0.4360 data_time: 0.0215 memory: 23498 grad_norm: 3.5327 top1_acc: 0.1579 top5_acc: 0.5263 loss_cls: 2.6679 loss: 2.6679 2022/09/08 12:17:03 - mmengine - INFO - Epoch(val) [12][20/130] eta: 0:00:23 time: 0.2179 data_time: 0.0818 memory: 2693 2022/09/08 12:17:06 - mmengine - INFO - Epoch(val) [12][40/130] eta: 0:00:14 time: 0.1629 data_time: 0.0261 memory: 2693 2022/09/08 12:17:10 - mmengine - INFO - Epoch(val) [12][60/130] eta: 0:00:11 time: 0.1696 data_time: 0.0323 memory: 2693 2022/09/08 12:17:13 - mmengine - INFO - Epoch(val) [12][80/130] eta: 0:00:08 time: 0.1620 data_time: 0.0274 memory: 2693 2022/09/08 12:17:16 - mmengine - INFO - Epoch(val) [12][100/130] eta: 0:00:04 time: 0.1659 data_time: 0.0326 memory: 2693 2022/09/08 12:17:20 - mmengine - INFO - Epoch(val) [12][120/130] eta: 0:00:01 time: 0.1595 data_time: 0.0268 memory: 2693 2022/09/08 12:17:22 - mmengine - INFO - Epoch(val) [12][130/130] acc/top1: 0.3502 acc/top5: 0.6418 acc/mean1: 0.2755 2022/09/08 12:17:22 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4/best_acc/top1_epoch_10.pth is removed 2022/09/08 12:17:23 - mmengine - INFO - The best checkpoint with 0.3502 acc/top1 at 12 epoch is saved to best_acc/top1_epoch_12.pth. 2022/09/08 12:17:33 - mmengine - INFO - Epoch(train) [13][20/880] lr: 3.2649e-02 eta: 3:05:17 time: 0.4986 data_time: 0.0697 memory: 23498 grad_norm: 3.4242 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.4629 loss: 2.4629 2022/09/08 12:17:42 - mmengine - INFO - Epoch(train) [13][40/880] lr: 3.2649e-02 eta: 3:05:08 time: 0.4458 data_time: 0.0221 memory: 23498 grad_norm: 3.5055 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 2.6298 loss: 2.6298 2022/09/08 12:17:51 - mmengine - INFO - Epoch(train) [13][60/880] lr: 3.2649e-02 eta: 3:04:59 time: 0.4461 data_time: 0.0187 memory: 23498 grad_norm: 3.4430 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.5273 loss: 2.5273 2022/09/08 12:18:00 - mmengine - INFO - Epoch(train) [13][80/880] lr: 3.2649e-02 eta: 3:04:49 time: 0.4457 data_time: 0.0218 memory: 23498 grad_norm: 3.4997 top1_acc: 0.5000 top5_acc: 0.5833 loss_cls: 2.6219 loss: 2.6219 2022/09/08 12:18:09 - mmengine - INFO - Epoch(train) [13][100/880] lr: 3.2649e-02 eta: 3:04:40 time: 0.4480 data_time: 0.0206 memory: 23498 grad_norm: 3.2842 top1_acc: 0.5000 top5_acc: 0.5417 loss_cls: 2.5278 loss: 2.5278 2022/09/08 12:18:18 - mmengine - INFO - Epoch(train) [13][120/880] lr: 3.2649e-02 eta: 3:04:31 time: 0.4454 data_time: 0.0235 memory: 23498 grad_norm: 3.4504 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5197 loss: 2.5197 2022/09/08 12:18:27 - mmengine - INFO - Epoch(train) [13][140/880] lr: 3.2649e-02 eta: 3:04:22 time: 0.4450 data_time: 0.0196 memory: 23498 grad_norm: 3.6615 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 2.6733 loss: 2.6733 2022/09/08 12:18:36 - mmengine - INFO - Epoch(train) [13][160/880] lr: 3.2649e-02 eta: 3:04:13 time: 0.4658 data_time: 0.0246 memory: 23498 grad_norm: 3.5567 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.5643 loss: 2.5643 2022/09/08 12:18:45 - mmengine - INFO - Epoch(train) [13][180/880] lr: 3.2649e-02 eta: 3:04:04 time: 0.4428 data_time: 0.0200 memory: 23498 grad_norm: 3.5504 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.5696 loss: 2.5696 2022/09/08 12:18:54 - mmengine - INFO - Epoch(train) [13][200/880] lr: 3.2649e-02 eta: 3:03:55 time: 0.4450 data_time: 0.0238 memory: 23498 grad_norm: 3.4801 top1_acc: 0.4167 top5_acc: 0.5000 loss_cls: 2.7095 loss: 2.7095 2022/09/08 12:19:02 - mmengine - INFO - Epoch(train) [13][220/880] lr: 3.2649e-02 eta: 3:03:45 time: 0.4430 data_time: 0.0202 memory: 23498 grad_norm: 3.4626 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 2.5180 loss: 2.5180 2022/09/08 12:19:11 - mmengine - INFO - Epoch(train) [13][240/880] lr: 3.2649e-02 eta: 3:03:36 time: 0.4456 data_time: 0.0231 memory: 23498 grad_norm: 3.4611 top1_acc: 0.2500 top5_acc: 0.5417 loss_cls: 2.7001 loss: 2.7001 2022/09/08 12:19:20 - mmengine - INFO - Epoch(train) [13][260/880] lr: 3.2649e-02 eta: 3:03:26 time: 0.4415 data_time: 0.0213 memory: 23498 grad_norm: 3.5397 top1_acc: 0.2500 top5_acc: 0.6667 loss_cls: 2.7192 loss: 2.7192 2022/09/08 12:19:29 - mmengine - INFO - Epoch(train) [13][280/880] lr: 3.2649e-02 eta: 3:03:17 time: 0.4445 data_time: 0.0238 memory: 23498 grad_norm: 3.5610 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.6062 loss: 2.6062 2022/09/08 12:19:38 - mmengine - INFO - Epoch(train) [13][300/880] lr: 3.2649e-02 eta: 3:03:08 time: 0.4451 data_time: 0.0241 memory: 23498 grad_norm: 3.5589 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.6659 loss: 2.6659 2022/09/08 12:19:47 - mmengine - INFO - Epoch(train) [13][320/880] lr: 3.2649e-02 eta: 3:02:58 time: 0.4451 data_time: 0.0237 memory: 23498 grad_norm: 3.4135 top1_acc: 0.4167 top5_acc: 0.8333 loss_cls: 2.6227 loss: 2.6227 2022/09/08 12:19:56 - mmengine - INFO - Epoch(train) [13][340/880] lr: 3.2649e-02 eta: 3:02:50 time: 0.4607 data_time: 0.0216 memory: 23498 grad_norm: 3.6249 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.6307 loss: 2.6307 2022/09/08 12:20:05 - mmengine - INFO - Epoch(train) [13][360/880] lr: 3.2649e-02 eta: 3:02:40 time: 0.4445 data_time: 0.0242 memory: 23498 grad_norm: 3.4719 top1_acc: 0.4167 top5_acc: 0.8333 loss_cls: 2.3820 loss: 2.3820 2022/09/08 12:20:14 - mmengine - INFO - Epoch(train) [13][380/880] lr: 3.2649e-02 eta: 3:02:31 time: 0.4469 data_time: 0.0233 memory: 23498 grad_norm: 3.5396 top1_acc: 0.2083 top5_acc: 0.4167 loss_cls: 2.7756 loss: 2.7756 2022/09/08 12:20:23 - mmengine - INFO - Epoch(train) [13][400/880] lr: 3.2649e-02 eta: 3:02:22 time: 0.4458 data_time: 0.0251 memory: 23498 grad_norm: 3.4272 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.6528 loss: 2.6528 2022/09/08 12:20:32 - mmengine - INFO - Epoch(train) [13][420/880] lr: 3.2649e-02 eta: 3:02:13 time: 0.4548 data_time: 0.0243 memory: 23498 grad_norm: 3.6037 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.7327 loss: 2.7327 2022/09/08 12:20:41 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 12:20:41 - mmengine - INFO - Epoch(train) [13][440/880] lr: 3.2649e-02 eta: 3:02:04 time: 0.4451 data_time: 0.0256 memory: 23498 grad_norm: 3.4565 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.5368 loss: 2.5368 2022/09/08 12:20:50 - mmengine - INFO - Epoch(train) [13][460/880] lr: 3.2649e-02 eta: 3:01:55 time: 0.4540 data_time: 0.0278 memory: 23498 grad_norm: 3.3707 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6446 loss: 2.6446 2022/09/08 12:20:59 - mmengine - INFO - Epoch(train) [13][480/880] lr: 3.2649e-02 eta: 3:01:46 time: 0.4473 data_time: 0.0243 memory: 23498 grad_norm: 3.4087 top1_acc: 0.2083 top5_acc: 0.6250 loss_cls: 2.4768 loss: 2.4768 2022/09/08 12:21:08 - mmengine - INFO - Epoch(train) [13][500/880] lr: 3.2649e-02 eta: 3:01:36 time: 0.4453 data_time: 0.0230 memory: 23498 grad_norm: 3.4466 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5159 loss: 2.5159 2022/09/08 12:21:17 - mmengine - INFO - Epoch(train) [13][520/880] lr: 3.2649e-02 eta: 3:01:27 time: 0.4502 data_time: 0.0252 memory: 23498 grad_norm: 3.5181 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 2.6046 loss: 2.6046 2022/09/08 12:21:26 - mmengine - INFO - Epoch(train) [13][540/880] lr: 3.2649e-02 eta: 3:01:18 time: 0.4484 data_time: 0.0241 memory: 23498 grad_norm: 3.4478 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 2.6525 loss: 2.6525 2022/09/08 12:21:35 - mmengine - INFO - Epoch(train) [13][560/880] lr: 3.2649e-02 eta: 3:01:09 time: 0.4570 data_time: 0.0250 memory: 23498 grad_norm: 3.4609 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.7702 loss: 2.7702 2022/09/08 12:21:44 - mmengine - INFO - Epoch(train) [13][580/880] lr: 3.2649e-02 eta: 3:01:00 time: 0.4469 data_time: 0.0235 memory: 23498 grad_norm: 3.4143 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 2.6600 loss: 2.6600 2022/09/08 12:21:53 - mmengine - INFO - Epoch(train) [13][600/880] lr: 3.2649e-02 eta: 3:00:51 time: 0.4467 data_time: 0.0231 memory: 23498 grad_norm: 3.4741 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.6483 loss: 2.6483 2022/09/08 12:22:02 - mmengine - INFO - Epoch(train) [13][620/880] lr: 3.2649e-02 eta: 3:00:41 time: 0.4439 data_time: 0.0213 memory: 23498 grad_norm: 3.5948 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 2.5270 loss: 2.5270 2022/09/08 12:22:11 - mmengine - INFO - Epoch(train) [13][640/880] lr: 3.2649e-02 eta: 3:00:32 time: 0.4434 data_time: 0.0238 memory: 23498 grad_norm: 3.5113 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 2.6602 loss: 2.6602 2022/09/08 12:22:19 - mmengine - INFO - Epoch(train) [13][660/880] lr: 3.2649e-02 eta: 3:00:23 time: 0.4440 data_time: 0.0213 memory: 23498 grad_norm: 3.5046 top1_acc: 0.2083 top5_acc: 0.5417 loss_cls: 2.6118 loss: 2.6118 2022/09/08 12:22:28 - mmengine - INFO - Epoch(train) [13][680/880] lr: 3.2649e-02 eta: 3:00:14 time: 0.4458 data_time: 0.0262 memory: 23498 grad_norm: 3.4558 top1_acc: 0.3333 top5_acc: 0.7500 loss_cls: 2.6283 loss: 2.6283 2022/09/08 12:22:37 - mmengine - INFO - Epoch(train) [13][700/880] lr: 3.2649e-02 eta: 3:00:04 time: 0.4424 data_time: 0.0224 memory: 23498 grad_norm: 3.4329 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 2.7029 loss: 2.7029 2022/09/08 12:22:46 - mmengine - INFO - Epoch(train) [13][720/880] lr: 3.2649e-02 eta: 2:59:55 time: 0.4493 data_time: 0.0260 memory: 23498 grad_norm: 3.4386 top1_acc: 0.2500 top5_acc: 0.5833 loss_cls: 2.7566 loss: 2.7566 2022/09/08 12:22:55 - mmengine - INFO - Epoch(train) [13][740/880] lr: 3.2649e-02 eta: 2:59:46 time: 0.4439 data_time: 0.0224 memory: 23498 grad_norm: 3.4870 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.5849 loss: 2.5849 2022/09/08 12:23:04 - mmengine - INFO - Epoch(train) [13][760/880] lr: 3.2649e-02 eta: 2:59:36 time: 0.4469 data_time: 0.0255 memory: 23498 grad_norm: 3.4670 top1_acc: 0.3333 top5_acc: 0.5417 loss_cls: 2.5888 loss: 2.5888 2022/09/08 12:23:13 - mmengine - INFO - Epoch(train) [13][780/880] lr: 3.2649e-02 eta: 2:59:27 time: 0.4441 data_time: 0.0223 memory: 23498 grad_norm: 3.4865 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 2.4363 loss: 2.4363 2022/09/08 12:23:22 - mmengine - INFO - Epoch(train) [13][800/880] lr: 3.2649e-02 eta: 2:59:18 time: 0.4480 data_time: 0.0285 memory: 23498 grad_norm: 3.3972 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.4573 loss: 2.4573 2022/09/08 12:23:31 - mmengine - INFO - Epoch(train) [13][820/880] lr: 3.2649e-02 eta: 2:59:09 time: 0.4430 data_time: 0.0219 memory: 23498 grad_norm: 3.6215 top1_acc: 0.2917 top5_acc: 0.5000 loss_cls: 2.6067 loss: 2.6067 2022/09/08 12:23:40 - mmengine - INFO - Epoch(train) [13][840/880] lr: 3.2649e-02 eta: 2:58:59 time: 0.4478 data_time: 0.0247 memory: 23498 grad_norm: 3.5937 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 2.5459 loss: 2.5459 2022/09/08 12:23:49 - mmengine - INFO - Epoch(train) [13][860/880] lr: 3.2649e-02 eta: 2:58:50 time: 0.4475 data_time: 0.0229 memory: 23498 grad_norm: 3.6043 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7670 loss: 2.7670 2022/09/08 12:23:58 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 12:23:58 - mmengine - INFO - Epoch(train) [13][880/880] lr: 3.2649e-02 eta: 2:58:41 time: 0.4459 data_time: 0.0222 memory: 23498 grad_norm: 3.6658 top1_acc: 0.3158 top5_acc: 0.6316 loss_cls: 2.6199 loss: 2.6199 2022/09/08 12:24:08 - mmengine - INFO - Epoch(train) [14][20/880] lr: 3.1361e-02 eta: 2:58:35 time: 0.5134 data_time: 0.0781 memory: 23498 grad_norm: 3.6141 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.4464 loss: 2.4464 2022/09/08 12:24:17 - mmengine - INFO - Epoch(train) [14][40/880] lr: 3.1361e-02 eta: 2:58:26 time: 0.4526 data_time: 0.0285 memory: 23498 grad_norm: 3.4811 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.5387 loss: 2.5387 2022/09/08 12:24:26 - mmengine - INFO - Epoch(train) [14][60/880] lr: 3.1361e-02 eta: 2:58:16 time: 0.4471 data_time: 0.0218 memory: 23498 grad_norm: 3.5175 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4570 loss: 2.4570 2022/09/08 12:24:35 - mmengine - INFO - Epoch(train) [14][80/880] lr: 3.1361e-02 eta: 2:58:07 time: 0.4495 data_time: 0.0262 memory: 23498 grad_norm: 3.5612 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 2.5549 loss: 2.5549 2022/09/08 12:24:44 - mmengine - INFO - Epoch(train) [14][100/880] lr: 3.1361e-02 eta: 2:57:58 time: 0.4460 data_time: 0.0208 memory: 23498 grad_norm: 3.4551 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.3906 loss: 2.3906 2022/09/08 12:24:53 - mmengine - INFO - Epoch(train) [14][120/880] lr: 3.1361e-02 eta: 2:57:49 time: 0.4474 data_time: 0.0221 memory: 23498 grad_norm: 3.4871 top1_acc: 0.2083 top5_acc: 0.7083 loss_cls: 2.6109 loss: 2.6109 2022/09/08 12:25:02 - mmengine - INFO - Epoch(train) [14][140/880] lr: 3.1361e-02 eta: 2:57:40 time: 0.4535 data_time: 0.0191 memory: 23498 grad_norm: 3.5111 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 2.6737 loss: 2.6737 2022/09/08 12:25:11 - mmengine - INFO - Epoch(train) [14][160/880] lr: 3.1361e-02 eta: 2:57:31 time: 0.4481 data_time: 0.0219 memory: 23498 grad_norm: 3.5990 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6637 loss: 2.6637 2022/09/08 12:25:20 - mmengine - INFO - Epoch(train) [14][180/880] lr: 3.1361e-02 eta: 2:57:22 time: 0.4476 data_time: 0.0213 memory: 23498 grad_norm: 3.5656 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.5427 loss: 2.5427 2022/09/08 12:25:29 - mmengine - INFO - Epoch(train) [14][200/880] lr: 3.1361e-02 eta: 2:57:12 time: 0.4473 data_time: 0.0210 memory: 23498 grad_norm: 3.8998 top1_acc: 0.4167 top5_acc: 0.5417 loss_cls: 2.6601 loss: 2.6601 2022/09/08 12:25:38 - mmengine - INFO - Epoch(train) [14][220/880] lr: 3.1361e-02 eta: 2:57:03 time: 0.4469 data_time: 0.0209 memory: 23498 grad_norm: 3.6333 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 2.5103 loss: 2.5103 2022/09/08 12:25:46 - mmengine - INFO - Epoch(train) [14][240/880] lr: 3.1361e-02 eta: 2:56:54 time: 0.4451 data_time: 0.0219 memory: 23498 grad_norm: 3.5139 top1_acc: 0.4167 top5_acc: 0.5417 loss_cls: 2.5659 loss: 2.5659 2022/09/08 12:25:56 - mmengine - INFO - Epoch(train) [14][260/880] lr: 3.1361e-02 eta: 2:56:45 time: 0.4522 data_time: 0.0220 memory: 23498 grad_norm: 3.5975 top1_acc: 0.4167 top5_acc: 0.8333 loss_cls: 2.6264 loss: 2.6264 2022/09/08 12:26:04 - mmengine - INFO - Epoch(train) [14][280/880] lr: 3.1361e-02 eta: 2:56:36 time: 0.4455 data_time: 0.0229 memory: 23498 grad_norm: 3.5008 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5856 loss: 2.5856 2022/09/08 12:26:13 - mmengine - INFO - Epoch(train) [14][300/880] lr: 3.1361e-02 eta: 2:56:27 time: 0.4527 data_time: 0.0206 memory: 23498 grad_norm: 3.4988 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7458 loss: 2.7458 2022/09/08 12:26:22 - mmengine - INFO - Epoch(train) [14][320/880] lr: 3.1361e-02 eta: 2:56:17 time: 0.4452 data_time: 0.0234 memory: 23498 grad_norm: 3.4922 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6825 loss: 2.6825 2022/09/08 12:26:31 - mmengine - INFO - Epoch(train) [14][340/880] lr: 3.1361e-02 eta: 2:56:08 time: 0.4460 data_time: 0.0193 memory: 23498 grad_norm: 3.5016 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.5750 loss: 2.5750 2022/09/08 12:26:40 - mmengine - INFO - Epoch(train) [14][360/880] lr: 3.1361e-02 eta: 2:55:59 time: 0.4449 data_time: 0.0225 memory: 23498 grad_norm: 3.5493 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.6488 loss: 2.6488 2022/09/08 12:26:49 - mmengine - INFO - Epoch(train) [14][380/880] lr: 3.1361e-02 eta: 2:55:50 time: 0.4507 data_time: 0.0194 memory: 23498 grad_norm: 3.4566 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 2.4718 loss: 2.4718 2022/09/08 12:26:58 - mmengine - INFO - Epoch(train) [14][400/880] lr: 3.1361e-02 eta: 2:55:41 time: 0.4442 data_time: 0.0223 memory: 23498 grad_norm: 3.4952 top1_acc: 0.3750 top5_acc: 0.7917 loss_cls: 2.3931 loss: 2.3931 2022/09/08 12:27:07 - mmengine - INFO - Epoch(train) [14][420/880] lr: 3.1361e-02 eta: 2:55:31 time: 0.4448 data_time: 0.0211 memory: 23498 grad_norm: 3.5516 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 2.5790 loss: 2.5790 2022/09/08 12:27:16 - mmengine - INFO - Epoch(train) [14][440/880] lr: 3.1361e-02 eta: 2:55:22 time: 0.4428 data_time: 0.0221 memory: 23498 grad_norm: 3.6301 top1_acc: 0.3333 top5_acc: 0.5417 loss_cls: 2.6872 loss: 2.6872 2022/09/08 12:27:25 - mmengine - INFO - Epoch(train) [14][460/880] lr: 3.1361e-02 eta: 2:55:13 time: 0.4452 data_time: 0.0204 memory: 23498 grad_norm: 3.5463 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.6995 loss: 2.6995 2022/09/08 12:27:34 - mmengine - INFO - Epoch(train) [14][480/880] lr: 3.1361e-02 eta: 2:55:03 time: 0.4414 data_time: 0.0241 memory: 23498 grad_norm: 3.5260 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.4501 loss: 2.4501 2022/09/08 12:27:42 - mmengine - INFO - Epoch(train) [14][500/880] lr: 3.1361e-02 eta: 2:54:54 time: 0.4390 data_time: 0.0193 memory: 23498 grad_norm: 3.4785 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.4306 loss: 2.4306 2022/09/08 12:27:51 - mmengine - INFO - Epoch(train) [14][520/880] lr: 3.1361e-02 eta: 2:54:44 time: 0.4403 data_time: 0.0206 memory: 23498 grad_norm: 3.5397 top1_acc: 0.2083 top5_acc: 0.5000 loss_cls: 2.5004 loss: 2.5004 2022/09/08 12:28:00 - mmengine - INFO - Epoch(train) [14][540/880] lr: 3.1361e-02 eta: 2:54:35 time: 0.4443 data_time: 0.0214 memory: 23498 grad_norm: 3.3732 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.5277 loss: 2.5277 2022/09/08 12:28:09 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 12:28:09 - mmengine - INFO - Epoch(train) [14][560/880] lr: 3.1361e-02 eta: 2:54:25 time: 0.4392 data_time: 0.0231 memory: 23498 grad_norm: 3.5104 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.4441 loss: 2.4441 2022/09/08 12:28:18 - mmengine - INFO - Epoch(train) [14][580/880] lr: 3.1361e-02 eta: 2:54:16 time: 0.4408 data_time: 0.0218 memory: 23498 grad_norm: 3.5959 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6694 loss: 2.6694 2022/09/08 12:28:27 - mmengine - INFO - Epoch(train) [14][600/880] lr: 3.1361e-02 eta: 2:54:07 time: 0.4427 data_time: 0.0222 memory: 23498 grad_norm: 3.4997 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.6029 loss: 2.6029 2022/09/08 12:28:35 - mmengine - INFO - Epoch(train) [14][620/880] lr: 3.1361e-02 eta: 2:53:57 time: 0.4419 data_time: 0.0219 memory: 23498 grad_norm: 3.5711 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.5675 loss: 2.5675 2022/09/08 12:28:44 - mmengine - INFO - Epoch(train) [14][640/880] lr: 3.1361e-02 eta: 2:53:48 time: 0.4426 data_time: 0.0234 memory: 23498 grad_norm: 3.5479 top1_acc: 0.3333 top5_acc: 0.6250 loss_cls: 2.6664 loss: 2.6664 2022/09/08 12:28:53 - mmengine - INFO - Epoch(train) [14][660/880] lr: 3.1361e-02 eta: 2:53:39 time: 0.4451 data_time: 0.0219 memory: 23498 grad_norm: 3.5264 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.5809 loss: 2.5809 2022/09/08 12:29:02 - mmengine - INFO - Epoch(train) [14][680/880] lr: 3.1361e-02 eta: 2:53:29 time: 0.4408 data_time: 0.0221 memory: 23498 grad_norm: 3.5400 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.5422 loss: 2.5422 2022/09/08 12:29:11 - mmengine - INFO - Epoch(train) [14][700/880] lr: 3.1361e-02 eta: 2:53:20 time: 0.4430 data_time: 0.0203 memory: 23498 grad_norm: 3.7800 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 2.5619 loss: 2.5619 2022/09/08 12:29:20 - mmengine - INFO - Epoch(train) [14][720/880] lr: 3.1361e-02 eta: 2:53:11 time: 0.4410 data_time: 0.0227 memory: 23498 grad_norm: 3.5457 top1_acc: 0.3750 top5_acc: 0.5417 loss_cls: 2.4778 loss: 2.4778 2022/09/08 12:29:28 - mmengine - INFO - Epoch(train) [14][740/880] lr: 3.1361e-02 eta: 2:53:01 time: 0.4413 data_time: 0.0200 memory: 23498 grad_norm: 3.5160 top1_acc: 0.2917 top5_acc: 0.5417 loss_cls: 2.5143 loss: 2.5143 2022/09/08 12:29:37 - mmengine - INFO - Epoch(train) [14][760/880] lr: 3.1361e-02 eta: 2:52:52 time: 0.4396 data_time: 0.0220 memory: 23498 grad_norm: 3.5436 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4955 loss: 2.4955 2022/09/08 12:29:46 - mmengine - INFO - Epoch(train) [14][780/880] lr: 3.1361e-02 eta: 2:52:43 time: 0.4453 data_time: 0.0213 memory: 23498 grad_norm: 3.4872 top1_acc: 0.2917 top5_acc: 0.5417 loss_cls: 2.5266 loss: 2.5266 2022/09/08 12:29:55 - mmengine - INFO - Epoch(train) [14][800/880] lr: 3.1361e-02 eta: 2:52:33 time: 0.4461 data_time: 0.0217 memory: 23498 grad_norm: 3.5818 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.5585 loss: 2.5585 2022/09/08 12:30:04 - mmengine - INFO - Epoch(train) [14][820/880] lr: 3.1361e-02 eta: 2:52:24 time: 0.4446 data_time: 0.0211 memory: 23498 grad_norm: 3.6380 top1_acc: 0.2500 top5_acc: 0.4583 loss_cls: 2.5895 loss: 2.5895 2022/09/08 12:30:13 - mmengine - INFO - Epoch(train) [14][840/880] lr: 3.1361e-02 eta: 2:52:15 time: 0.4440 data_time: 0.0218 memory: 23498 grad_norm: 3.6273 top1_acc: 0.3333 top5_acc: 0.7500 loss_cls: 2.6288 loss: 2.6288 2022/09/08 12:30:22 - mmengine - INFO - Epoch(train) [14][860/880] lr: 3.1361e-02 eta: 2:52:05 time: 0.4414 data_time: 0.0206 memory: 23498 grad_norm: 3.5728 top1_acc: 0.2500 top5_acc: 0.4167 loss_cls: 2.7487 loss: 2.7487 2022/09/08 12:30:30 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 12:30:30 - mmengine - INFO - Epoch(train) [14][880/880] lr: 3.1361e-02 eta: 2:51:56 time: 0.4351 data_time: 0.0206 memory: 23498 grad_norm: 3.4780 top1_acc: 0.3158 top5_acc: 0.4737 loss_cls: 2.5318 loss: 2.5318 2022/09/08 12:30:35 - mmengine - INFO - Epoch(val) [14][20/130] eta: 0:00:23 time: 0.2175 data_time: 0.0812 memory: 2693 2022/09/08 12:30:38 - mmengine - INFO - Epoch(val) [14][40/130] eta: 0:00:15 time: 0.1669 data_time: 0.0298 memory: 2693 2022/09/08 12:30:42 - mmengine - INFO - Epoch(val) [14][60/130] eta: 0:00:12 time: 0.1723 data_time: 0.0347 memory: 2693 2022/09/08 12:30:45 - mmengine - INFO - Epoch(val) [14][80/130] eta: 0:00:08 time: 0.1677 data_time: 0.0315 memory: 2693 2022/09/08 12:30:48 - mmengine - INFO - Epoch(val) [14][100/130] eta: 0:00:04 time: 0.1641 data_time: 0.0287 memory: 2693 2022/09/08 12:30:51 - mmengine - INFO - Epoch(val) [14][120/130] eta: 0:00:01 time: 0.1600 data_time: 0.0305 memory: 2693 2022/09/08 12:30:53 - mmengine - INFO - Epoch(val) [14][130/130] acc/top1: 0.3333 acc/top5: 0.6253 acc/mean1: 0.2823 2022/09/08 12:31:04 - mmengine - INFO - Epoch(train) [15][20/880] lr: 3.0000e-02 eta: 2:51:49 time: 0.5121 data_time: 0.0794 memory: 23498 grad_norm: 3.4876 top1_acc: 0.2917 top5_acc: 0.6667 loss_cls: 2.4732 loss: 2.4732 2022/09/08 12:31:13 - mmengine - INFO - Epoch(train) [15][40/880] lr: 3.0000e-02 eta: 2:51:40 time: 0.4494 data_time: 0.0261 memory: 23498 grad_norm: 3.6047 top1_acc: 0.2500 top5_acc: 0.5833 loss_cls: 2.5933 loss: 2.5933 2022/09/08 12:31:22 - mmengine - INFO - Epoch(train) [15][60/880] lr: 3.0000e-02 eta: 2:51:31 time: 0.4523 data_time: 0.0251 memory: 23498 grad_norm: 3.4465 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.5356 loss: 2.5356 2022/09/08 12:31:31 - mmengine - INFO - Epoch(train) [15][80/880] lr: 3.0000e-02 eta: 2:51:22 time: 0.4486 data_time: 0.0226 memory: 23498 grad_norm: 3.5662 top1_acc: 0.2917 top5_acc: 0.4583 loss_cls: 2.6451 loss: 2.6451 2022/09/08 12:31:40 - mmengine - INFO - Epoch(train) [15][100/880] lr: 3.0000e-02 eta: 2:51:13 time: 0.4531 data_time: 0.0236 memory: 23498 grad_norm: 3.7337 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.5444 loss: 2.5444 2022/09/08 12:31:49 - mmengine - INFO - Epoch(train) [15][120/880] lr: 3.0000e-02 eta: 2:51:04 time: 0.4483 data_time: 0.0231 memory: 23498 grad_norm: 3.6678 top1_acc: 0.2917 top5_acc: 0.4583 loss_cls: 2.6292 loss: 2.6292 2022/09/08 12:31:58 - mmengine - INFO - Epoch(train) [15][140/880] lr: 3.0000e-02 eta: 2:50:55 time: 0.4570 data_time: 0.0234 memory: 23498 grad_norm: 3.5980 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.5287 loss: 2.5287 2022/09/08 12:32:07 - mmengine - INFO - Epoch(train) [15][160/880] lr: 3.0000e-02 eta: 2:50:46 time: 0.4495 data_time: 0.0213 memory: 23498 grad_norm: 3.6135 top1_acc: 0.2500 top5_acc: 0.4583 loss_cls: 2.6370 loss: 2.6370 2022/09/08 12:32:16 - mmengine - INFO - Epoch(train) [15][180/880] lr: 3.0000e-02 eta: 2:50:37 time: 0.4533 data_time: 0.0218 memory: 23498 grad_norm: 3.5208 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 2.5227 loss: 2.5227 2022/09/08 12:32:25 - mmengine - INFO - Epoch(train) [15][200/880] lr: 3.0000e-02 eta: 2:50:28 time: 0.4623 data_time: 0.0215 memory: 23498 grad_norm: 3.5859 top1_acc: 0.2500 top5_acc: 0.7083 loss_cls: 2.4962 loss: 2.4962 2022/09/08 12:32:34 - mmengine - INFO - Epoch(train) [15][220/880] lr: 3.0000e-02 eta: 2:50:19 time: 0.4518 data_time: 0.0221 memory: 23498 grad_norm: 3.8124 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5179 loss: 2.5179 2022/09/08 12:32:43 - mmengine - INFO - Epoch(train) [15][240/880] lr: 3.0000e-02 eta: 2:50:10 time: 0.4459 data_time: 0.0219 memory: 23498 grad_norm: 3.6324 top1_acc: 0.3750 top5_acc: 0.5417 loss_cls: 2.5696 loss: 2.5696 2022/09/08 12:32:52 - mmengine - INFO - Epoch(train) [15][260/880] lr: 3.0000e-02 eta: 2:50:01 time: 0.4537 data_time: 0.0235 memory: 23498 grad_norm: 3.6747 top1_acc: 0.3750 top5_acc: 0.5417 loss_cls: 2.5955 loss: 2.5955 2022/09/08 12:33:01 - mmengine - INFO - Epoch(train) [15][280/880] lr: 3.0000e-02 eta: 2:49:53 time: 0.4680 data_time: 0.0211 memory: 23498 grad_norm: 3.5809 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 2.3354 loss: 2.3354 2022/09/08 12:33:11 - mmengine - INFO - Epoch(train) [15][300/880] lr: 3.0000e-02 eta: 2:49:44 time: 0.4533 data_time: 0.0227 memory: 23498 grad_norm: 3.6095 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 2.5845 loss: 2.5845 2022/09/08 12:33:20 - mmengine - INFO - Epoch(train) [15][320/880] lr: 3.0000e-02 eta: 2:49:35 time: 0.4504 data_time: 0.0218 memory: 23498 grad_norm: 3.5355 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.4216 loss: 2.4216 2022/09/08 12:33:29 - mmengine - INFO - Epoch(train) [15][340/880] lr: 3.0000e-02 eta: 2:49:26 time: 0.4527 data_time: 0.0228 memory: 23498 grad_norm: 3.5262 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4757 loss: 2.4757 2022/09/08 12:33:38 - mmengine - INFO - Epoch(train) [15][360/880] lr: 3.0000e-02 eta: 2:49:17 time: 0.4656 data_time: 0.0206 memory: 23498 grad_norm: 3.5036 top1_acc: 0.2917 top5_acc: 0.6667 loss_cls: 2.5317 loss: 2.5317 2022/09/08 12:33:47 - mmengine - INFO - Epoch(train) [15][380/880] lr: 3.0000e-02 eta: 2:49:08 time: 0.4520 data_time: 0.0245 memory: 23498 grad_norm: 3.4483 top1_acc: 0.2500 top5_acc: 0.7083 loss_cls: 2.3931 loss: 2.3931 2022/09/08 12:33:56 - mmengine - INFO - Epoch(train) [15][400/880] lr: 3.0000e-02 eta: 2:48:59 time: 0.4483 data_time: 0.0203 memory: 23498 grad_norm: 3.6193 top1_acc: 0.2917 top5_acc: 0.7083 loss_cls: 2.3533 loss: 2.3533 2022/09/08 12:34:05 - mmengine - INFO - Epoch(train) [15][420/880] lr: 3.0000e-02 eta: 2:48:50 time: 0.4508 data_time: 0.0209 memory: 23498 grad_norm: 3.7180 top1_acc: 0.3750 top5_acc: 0.7917 loss_cls: 2.5061 loss: 2.5061 2022/09/08 12:34:14 - mmengine - INFO - Epoch(train) [15][440/880] lr: 3.0000e-02 eta: 2:48:41 time: 0.4549 data_time: 0.0209 memory: 23498 grad_norm: 3.7100 top1_acc: 0.2917 top5_acc: 0.3750 loss_cls: 2.5067 loss: 2.5067 2022/09/08 12:34:23 - mmengine - INFO - Epoch(train) [15][460/880] lr: 3.0000e-02 eta: 2:48:32 time: 0.4511 data_time: 0.0216 memory: 23498 grad_norm: 3.7952 top1_acc: 0.2917 top5_acc: 0.5000 loss_cls: 2.5203 loss: 2.5203 2022/09/08 12:34:32 - mmengine - INFO - Epoch(train) [15][480/880] lr: 3.0000e-02 eta: 2:48:23 time: 0.4483 data_time: 0.0203 memory: 23498 grad_norm: 3.6199 top1_acc: 0.2083 top5_acc: 0.5417 loss_cls: 2.5213 loss: 2.5213 2022/09/08 12:34:41 - mmengine - INFO - Epoch(train) [15][500/880] lr: 3.0000e-02 eta: 2:48:14 time: 0.4507 data_time: 0.0214 memory: 23498 grad_norm: 3.5721 top1_acc: 0.3333 top5_acc: 0.5417 loss_cls: 2.4775 loss: 2.4775 2022/09/08 12:34:50 - mmengine - INFO - Epoch(train) [15][520/880] lr: 3.0000e-02 eta: 2:48:05 time: 0.4452 data_time: 0.0191 memory: 23498 grad_norm: 3.5679 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.4917 loss: 2.4917 2022/09/08 12:34:59 - mmengine - INFO - Epoch(train) [15][540/880] lr: 3.0000e-02 eta: 2:47:56 time: 0.4502 data_time: 0.0230 memory: 23498 grad_norm: 3.5621 top1_acc: 0.2500 top5_acc: 0.6667 loss_cls: 2.4762 loss: 2.4762 2022/09/08 12:35:08 - mmengine - INFO - Epoch(train) [15][560/880] lr: 3.0000e-02 eta: 2:47:47 time: 0.4464 data_time: 0.0204 memory: 23498 grad_norm: 3.7414 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 2.4094 loss: 2.4094 2022/09/08 12:35:17 - mmengine - INFO - Epoch(train) [15][580/880] lr: 3.0000e-02 eta: 2:47:38 time: 0.4684 data_time: 0.0231 memory: 23498 grad_norm: 3.6860 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 2.4930 loss: 2.4930 2022/09/08 12:35:26 - mmengine - INFO - Epoch(train) [15][600/880] lr: 3.0000e-02 eta: 2:47:29 time: 0.4497 data_time: 0.0253 memory: 23498 grad_norm: 3.6266 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6235 loss: 2.6235 2022/09/08 12:35:35 - mmengine - INFO - Epoch(train) [15][620/880] lr: 3.0000e-02 eta: 2:47:20 time: 0.4502 data_time: 0.0239 memory: 23498 grad_norm: 3.7652 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.5368 loss: 2.5368 2022/09/08 12:35:44 - mmengine - INFO - Epoch(train) [15][640/880] lr: 3.0000e-02 eta: 2:47:11 time: 0.4462 data_time: 0.0197 memory: 23498 grad_norm: 3.5072 top1_acc: 0.3750 top5_acc: 0.5417 loss_cls: 2.4537 loss: 2.4537 2022/09/08 12:35:53 - mmengine - INFO - Epoch(train) [15][660/880] lr: 3.0000e-02 eta: 2:47:02 time: 0.4438 data_time: 0.0218 memory: 23498 grad_norm: 3.4233 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.4470 loss: 2.4470 2022/09/08 12:36:02 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 12:36:02 - mmengine - INFO - Epoch(train) [15][680/880] lr: 3.0000e-02 eta: 2:46:52 time: 0.4411 data_time: 0.0187 memory: 23498 grad_norm: 3.5644 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.5714 loss: 2.5714 2022/09/08 12:36:11 - mmengine - INFO - Epoch(train) [15][700/880] lr: 3.0000e-02 eta: 2:46:43 time: 0.4456 data_time: 0.0228 memory: 23498 grad_norm: 3.5760 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.4765 loss: 2.4765 2022/09/08 12:36:20 - mmengine - INFO - Epoch(train) [15][720/880] lr: 3.0000e-02 eta: 2:46:34 time: 0.4430 data_time: 0.0199 memory: 23498 grad_norm: 3.4762 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 2.5330 loss: 2.5330 2022/09/08 12:36:29 - mmengine - INFO - Epoch(train) [15][740/880] lr: 3.0000e-02 eta: 2:46:25 time: 0.4442 data_time: 0.0228 memory: 23498 grad_norm: 3.4415 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.3809 loss: 2.3809 2022/09/08 12:36:38 - mmengine - INFO - Epoch(train) [15][760/880] lr: 3.0000e-02 eta: 2:46:16 time: 0.4608 data_time: 0.0201 memory: 23498 grad_norm: 3.3493 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 2.4813 loss: 2.4813 2022/09/08 12:36:47 - mmengine - INFO - Epoch(train) [15][780/880] lr: 3.0000e-02 eta: 2:46:07 time: 0.4502 data_time: 0.0239 memory: 23498 grad_norm: 3.4977 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5906 loss: 2.5906 2022/09/08 12:36:56 - mmengine - INFO - Epoch(train) [15][800/880] lr: 3.0000e-02 eta: 2:45:58 time: 0.4617 data_time: 0.0207 memory: 23498 grad_norm: 3.5839 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5720 loss: 2.5720 2022/09/08 12:37:05 - mmengine - INFO - Epoch(train) [15][820/880] lr: 3.0000e-02 eta: 2:45:49 time: 0.4516 data_time: 0.0309 memory: 23498 grad_norm: 3.5740 top1_acc: 0.2917 top5_acc: 0.7500 loss_cls: 2.3885 loss: 2.3885 2022/09/08 12:37:14 - mmengine - INFO - Epoch(train) [15][840/880] lr: 3.0000e-02 eta: 2:45:41 time: 0.4639 data_time: 0.0199 memory: 23498 grad_norm: 3.6141 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4623 loss: 2.4623 2022/09/08 12:37:23 - mmengine - INFO - Epoch(train) [15][860/880] lr: 3.0000e-02 eta: 2:45:31 time: 0.4453 data_time: 0.0223 memory: 23498 grad_norm: 3.5610 top1_acc: 0.1250 top5_acc: 0.4583 loss_cls: 2.6327 loss: 2.6327 2022/09/08 12:37:32 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 12:37:32 - mmengine - INFO - Epoch(train) [15][880/880] lr: 3.0000e-02 eta: 2:45:22 time: 0.4329 data_time: 0.0214 memory: 23498 grad_norm: 3.6151 top1_acc: 0.3158 top5_acc: 0.5263 loss_cls: 2.4181 loss: 2.4181 2022/09/08 12:37:42 - mmengine - INFO - Epoch(train) [16][20/880] lr: 2.8574e-02 eta: 2:45:15 time: 0.5197 data_time: 0.0834 memory: 23498 grad_norm: 3.6635 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.5637 loss: 2.5637 2022/09/08 12:37:52 - mmengine - INFO - Epoch(train) [16][40/880] lr: 2.8574e-02 eta: 2:45:06 time: 0.4619 data_time: 0.0246 memory: 23498 grad_norm: 3.6069 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.3217 loss: 2.3217 2022/09/08 12:38:01 - mmengine - INFO - Epoch(train) [16][60/880] lr: 2.8574e-02 eta: 2:44:58 time: 0.4566 data_time: 0.0212 memory: 23498 grad_norm: 3.8140 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2890 loss: 2.2890 2022/09/08 12:38:10 - mmengine - INFO - Epoch(train) [16][80/880] lr: 2.8574e-02 eta: 2:44:48 time: 0.4450 data_time: 0.0194 memory: 23498 grad_norm: 3.6511 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 2.4823 loss: 2.4823 2022/09/08 12:38:19 - mmengine - INFO - Epoch(train) [16][100/880] lr: 2.8574e-02 eta: 2:44:39 time: 0.4499 data_time: 0.0215 memory: 23498 grad_norm: 3.5657 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 2.3869 loss: 2.3869 2022/09/08 12:38:28 - mmengine - INFO - Epoch(train) [16][120/880] lr: 2.8574e-02 eta: 2:44:30 time: 0.4549 data_time: 0.0204 memory: 23498 grad_norm: 3.5647 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3935 loss: 2.3935 2022/09/08 12:38:37 - mmengine - INFO - Epoch(train) [16][140/880] lr: 2.8574e-02 eta: 2:44:22 time: 0.4585 data_time: 0.0205 memory: 23498 grad_norm: 3.4087 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 2.3244 loss: 2.3244 2022/09/08 12:38:46 - mmengine - INFO - Epoch(train) [16][160/880] lr: 2.8574e-02 eta: 2:44:13 time: 0.4609 data_time: 0.0211 memory: 23498 grad_norm: 3.5303 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2543 loss: 2.2543 2022/09/08 12:38:55 - mmengine - INFO - Epoch(train) [16][180/880] lr: 2.8574e-02 eta: 2:44:04 time: 0.4558 data_time: 0.0264 memory: 23498 grad_norm: 3.4995 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3754 loss: 2.3754 2022/09/08 12:39:04 - mmengine - INFO - Epoch(train) [16][200/880] lr: 2.8574e-02 eta: 2:43:55 time: 0.4629 data_time: 0.0218 memory: 23498 grad_norm: 3.5801 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 2.3356 loss: 2.3356 2022/09/08 12:39:14 - mmengine - INFO - Epoch(train) [16][220/880] lr: 2.8574e-02 eta: 2:43:46 time: 0.4491 data_time: 0.0213 memory: 23498 grad_norm: 3.5595 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5851 loss: 2.5851 2022/09/08 12:39:22 - mmengine - INFO - Epoch(train) [16][240/880] lr: 2.8574e-02 eta: 2:43:37 time: 0.4488 data_time: 0.0248 memory: 23498 grad_norm: 3.6070 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.3672 loss: 2.3672 2022/09/08 12:39:31 - mmengine - INFO - Epoch(train) [16][260/880] lr: 2.8574e-02 eta: 2:43:28 time: 0.4481 data_time: 0.0216 memory: 23498 grad_norm: 3.6827 top1_acc: 0.4583 top5_acc: 0.5833 loss_cls: 2.4406 loss: 2.4406 2022/09/08 12:39:40 - mmengine - INFO - Epoch(train) [16][280/880] lr: 2.8574e-02 eta: 2:43:19 time: 0.4457 data_time: 0.0223 memory: 23498 grad_norm: 3.7196 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.3978 loss: 2.3978 2022/09/08 12:39:49 - mmengine - INFO - Epoch(train) [16][300/880] lr: 2.8574e-02 eta: 2:43:10 time: 0.4537 data_time: 0.0243 memory: 23498 grad_norm: 3.9270 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.5290 loss: 2.5290 2022/09/08 12:39:58 - mmengine - INFO - Epoch(train) [16][320/880] lr: 2.8574e-02 eta: 2:43:01 time: 0.4466 data_time: 0.0214 memory: 23498 grad_norm: 3.8184 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5093 loss: 2.5093 2022/09/08 12:40:07 - mmengine - INFO - Epoch(train) [16][340/880] lr: 2.8574e-02 eta: 2:42:52 time: 0.4585 data_time: 0.0205 memory: 23498 grad_norm: 3.7489 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 2.4149 loss: 2.4149 2022/09/08 12:40:17 - mmengine - INFO - Epoch(train) [16][360/880] lr: 2.8574e-02 eta: 2:42:43 time: 0.4523 data_time: 0.0221 memory: 23498 grad_norm: 3.8178 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 2.4014 loss: 2.4014 2022/09/08 12:40:26 - mmengine - INFO - Epoch(train) [16][380/880] lr: 2.8574e-02 eta: 2:42:34 time: 0.4599 data_time: 0.0207 memory: 23498 grad_norm: 3.6240 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 2.3241 loss: 2.3241 2022/09/08 12:40:35 - mmengine - INFO - Epoch(train) [16][400/880] lr: 2.8574e-02 eta: 2:42:25 time: 0.4473 data_time: 0.0210 memory: 23498 grad_norm: 3.7737 top1_acc: 0.3333 top5_acc: 0.5417 loss_cls: 2.3956 loss: 2.3956 2022/09/08 12:40:44 - mmengine - INFO - Epoch(train) [16][420/880] lr: 2.8574e-02 eta: 2:42:16 time: 0.4496 data_time: 0.0204 memory: 23498 grad_norm: 3.7993 top1_acc: 0.5000 top5_acc: 0.5833 loss_cls: 2.3725 loss: 2.3725 2022/09/08 12:40:53 - mmengine - INFO - Epoch(train) [16][440/880] lr: 2.8574e-02 eta: 2:42:07 time: 0.4472 data_time: 0.0210 memory: 23498 grad_norm: 3.7356 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.3359 loss: 2.3359 2022/09/08 12:41:02 - mmengine - INFO - Epoch(train) [16][460/880] lr: 2.8574e-02 eta: 2:41:58 time: 0.4528 data_time: 0.0212 memory: 23498 grad_norm: 3.7466 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.6208 loss: 2.6208 2022/09/08 12:41:11 - mmengine - INFO - Epoch(train) [16][480/880] lr: 2.8574e-02 eta: 2:41:49 time: 0.4503 data_time: 0.0223 memory: 23498 grad_norm: 3.8502 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.5838 loss: 2.5838 2022/09/08 12:41:20 - mmengine - INFO - Epoch(train) [16][500/880] lr: 2.8574e-02 eta: 2:41:40 time: 0.4529 data_time: 0.0214 memory: 23498 grad_norm: 3.8346 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 2.4994 loss: 2.4994 2022/09/08 12:41:29 - mmengine - INFO - Epoch(train) [16][520/880] lr: 2.8574e-02 eta: 2:41:31 time: 0.4552 data_time: 0.0235 memory: 23498 grad_norm: 3.7850 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 2.5575 loss: 2.5575 2022/09/08 12:41:38 - mmengine - INFO - Epoch(train) [16][540/880] lr: 2.8574e-02 eta: 2:41:22 time: 0.4540 data_time: 0.0208 memory: 23498 grad_norm: 4.0099 top1_acc: 0.5417 top5_acc: 0.6250 loss_cls: 2.6094 loss: 2.6094 2022/09/08 12:41:47 - mmengine - INFO - Epoch(train) [16][560/880] lr: 2.8574e-02 eta: 2:41:13 time: 0.4524 data_time: 0.0222 memory: 23498 grad_norm: 3.6054 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.4273 loss: 2.4273 2022/09/08 12:41:56 - mmengine - INFO - Epoch(train) [16][580/880] lr: 2.8574e-02 eta: 2:41:04 time: 0.4539 data_time: 0.0206 memory: 23498 grad_norm: 3.6837 top1_acc: 0.3333 top5_acc: 0.5417 loss_cls: 2.6056 loss: 2.6056 2022/09/08 12:42:05 - mmengine - INFO - Epoch(train) [16][600/880] lr: 2.8574e-02 eta: 2:40:55 time: 0.4557 data_time: 0.0233 memory: 23498 grad_norm: 3.5244 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.6330 loss: 2.6330 2022/09/08 12:42:14 - mmengine - INFO - Epoch(train) [16][620/880] lr: 2.8574e-02 eta: 2:40:46 time: 0.4542 data_time: 0.0206 memory: 23498 grad_norm: 3.5651 top1_acc: 0.2917 top5_acc: 0.7917 loss_cls: 2.5970 loss: 2.5970 2022/09/08 12:42:23 - mmengine - INFO - Epoch(train) [16][640/880] lr: 2.8574e-02 eta: 2:40:37 time: 0.4457 data_time: 0.0210 memory: 23498 grad_norm: 3.5882 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.5299 loss: 2.5299 2022/09/08 12:42:32 - mmengine - INFO - Epoch(train) [16][660/880] lr: 2.8574e-02 eta: 2:40:28 time: 0.4549 data_time: 0.0215 memory: 23498 grad_norm: 3.5844 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4132 loss: 2.4132 2022/09/08 12:42:41 - mmengine - INFO - Epoch(train) [16][680/880] lr: 2.8574e-02 eta: 2:40:19 time: 0.4473 data_time: 0.0206 memory: 23498 grad_norm: 3.5614 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5292 loss: 2.5292 2022/09/08 12:42:51 - mmengine - INFO - Epoch(train) [16][700/880] lr: 2.8574e-02 eta: 2:40:11 time: 0.4696 data_time: 0.0280 memory: 23498 grad_norm: 3.7688 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.4144 loss: 2.4144 2022/09/08 12:43:00 - mmengine - INFO - Epoch(train) [16][720/880] lr: 2.8574e-02 eta: 2:40:02 time: 0.4481 data_time: 0.0234 memory: 23498 grad_norm: 3.6746 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.5655 loss: 2.5655 2022/09/08 12:43:09 - mmengine - INFO - Epoch(train) [16][740/880] lr: 2.8574e-02 eta: 2:39:53 time: 0.4523 data_time: 0.0220 memory: 23498 grad_norm: 3.5184 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4928 loss: 2.4928 2022/09/08 12:43:18 - mmengine - INFO - Epoch(train) [16][760/880] lr: 2.8574e-02 eta: 2:39:44 time: 0.4517 data_time: 0.0203 memory: 23498 grad_norm: 3.5277 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 2.4405 loss: 2.4405 2022/09/08 12:43:27 - mmengine - INFO - Epoch(train) [16][780/880] lr: 2.8574e-02 eta: 2:39:35 time: 0.4552 data_time: 0.0204 memory: 23498 grad_norm: 3.5157 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 2.2867 loss: 2.2867 2022/09/08 12:43:36 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 12:43:36 - mmengine - INFO - Epoch(train) [16][800/880] lr: 2.8574e-02 eta: 2:39:25 time: 0.4474 data_time: 0.0200 memory: 23498 grad_norm: 3.6993 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4308 loss: 2.4308 2022/09/08 12:43:45 - mmengine - INFO - Epoch(train) [16][820/880] lr: 2.8574e-02 eta: 2:39:16 time: 0.4504 data_time: 0.0215 memory: 23498 grad_norm: 3.8818 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.4716 loss: 2.4716 2022/09/08 12:43:54 - mmengine - INFO - Epoch(train) [16][840/880] lr: 2.8574e-02 eta: 2:39:07 time: 0.4481 data_time: 0.0207 memory: 23498 grad_norm: 3.6635 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.4574 loss: 2.4574 2022/09/08 12:44:03 - mmengine - INFO - Epoch(train) [16][860/880] lr: 2.8574e-02 eta: 2:38:59 time: 0.4603 data_time: 0.0205 memory: 23498 grad_norm: 3.5303 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 2.4326 loss: 2.4326 2022/09/08 12:44:12 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 12:44:12 - mmengine - INFO - Epoch(train) [16][880/880] lr: 2.8574e-02 eta: 2:38:49 time: 0.4331 data_time: 0.0191 memory: 23498 grad_norm: 3.7510 top1_acc: 0.1579 top5_acc: 0.6316 loss_cls: 2.5990 loss: 2.5990 2022/09/08 12:44:16 - mmengine - INFO - Epoch(val) [16][20/130] eta: 0:00:23 time: 0.2147 data_time: 0.0789 memory: 2693 2022/09/08 12:44:19 - mmengine - INFO - Epoch(val) [16][40/130] eta: 0:00:14 time: 0.1616 data_time: 0.0250 memory: 2693 2022/09/08 12:44:22 - mmengine - INFO - Epoch(val) [16][60/130] eta: 0:00:11 time: 0.1683 data_time: 0.0336 memory: 2693 2022/09/08 12:44:26 - mmengine - INFO - Epoch(val) [16][80/130] eta: 0:00:08 time: 0.1616 data_time: 0.0239 memory: 2693 2022/09/08 12:44:29 - mmengine - INFO - Epoch(val) [16][100/130] eta: 0:00:04 time: 0.1666 data_time: 0.0303 memory: 2693 2022/09/08 12:44:32 - mmengine - INFO - Epoch(val) [16][120/130] eta: 0:00:01 time: 0.1591 data_time: 0.0262 memory: 2693 2022/09/08 12:44:35 - mmengine - INFO - Epoch(val) [16][130/130] acc/top1: 0.3666 acc/top5: 0.6570 acc/mean1: 0.2947 2022/09/08 12:44:35 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4/best_acc/top1_epoch_12.pth is removed 2022/09/08 12:44:36 - mmengine - INFO - The best checkpoint with 0.3666 acc/top1 at 16 epoch is saved to best_acc/top1_epoch_16.pth. 2022/09/08 12:44:46 - mmengine - INFO - Epoch(train) [17][20/880] lr: 2.7092e-02 eta: 2:38:41 time: 0.4953 data_time: 0.0692 memory: 23498 grad_norm: 3.5444 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 2.3710 loss: 2.3710 2022/09/08 12:44:55 - mmengine - INFO - Epoch(train) [17][40/880] lr: 2.7092e-02 eta: 2:38:32 time: 0.4542 data_time: 0.0259 memory: 23498 grad_norm: 3.5109 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.4393 loss: 2.4393 2022/09/08 12:45:04 - mmengine - INFO - Epoch(train) [17][60/880] lr: 2.7092e-02 eta: 2:38:23 time: 0.4477 data_time: 0.0237 memory: 23498 grad_norm: 3.5474 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.3779 loss: 2.3779 2022/09/08 12:45:13 - mmengine - INFO - Epoch(train) [17][80/880] lr: 2.7092e-02 eta: 2:38:14 time: 0.4429 data_time: 0.0206 memory: 23498 grad_norm: 3.6704 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.3146 loss: 2.3146 2022/09/08 12:45:22 - mmengine - INFO - Epoch(train) [17][100/880] lr: 2.7092e-02 eta: 2:38:05 time: 0.4493 data_time: 0.0204 memory: 23498 grad_norm: 3.7311 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.5218 loss: 2.5218 2022/09/08 12:45:31 - mmengine - INFO - Epoch(train) [17][120/880] lr: 2.7092e-02 eta: 2:37:56 time: 0.4451 data_time: 0.0208 memory: 23498 grad_norm: 3.6534 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.4266 loss: 2.4266 2022/09/08 12:45:40 - mmengine - INFO - Epoch(train) [17][140/880] lr: 2.7092e-02 eta: 2:37:47 time: 0.4686 data_time: 0.0205 memory: 23498 grad_norm: 3.6108 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.4569 loss: 2.4569 2022/09/08 12:45:49 - mmengine - INFO - Epoch(train) [17][160/880] lr: 2.7092e-02 eta: 2:37:38 time: 0.4444 data_time: 0.0267 memory: 23498 grad_norm: 3.5853 top1_acc: 0.4167 top5_acc: 0.5417 loss_cls: 2.3383 loss: 2.3383 2022/09/08 12:45:58 - mmengine - INFO - Epoch(train) [17][180/880] lr: 2.7092e-02 eta: 2:37:29 time: 0.4617 data_time: 0.0196 memory: 23498 grad_norm: 3.5101 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 2.3256 loss: 2.3256 2022/09/08 12:46:07 - mmengine - INFO - Epoch(train) [17][200/880] lr: 2.7092e-02 eta: 2:37:20 time: 0.4424 data_time: 0.0206 memory: 23498 grad_norm: 3.5075 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.3983 loss: 2.3983 2022/09/08 12:46:16 - mmengine - INFO - Epoch(train) [17][220/880] lr: 2.7092e-02 eta: 2:37:11 time: 0.4470 data_time: 0.0204 memory: 23498 grad_norm: 3.5413 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.3937 loss: 2.3937 2022/09/08 12:46:25 - mmengine - INFO - Epoch(train) [17][240/880] lr: 2.7092e-02 eta: 2:37:01 time: 0.4426 data_time: 0.0227 memory: 23498 grad_norm: 3.5564 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.3587 loss: 2.3587 2022/09/08 12:46:34 - mmengine - INFO - Epoch(train) [17][260/880] lr: 2.7092e-02 eta: 2:36:52 time: 0.4451 data_time: 0.0211 memory: 23498 grad_norm: 3.7315 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 2.2839 loss: 2.2839 2022/09/08 12:46:43 - mmengine - INFO - Epoch(train) [17][280/880] lr: 2.7092e-02 eta: 2:36:43 time: 0.4433 data_time: 0.0209 memory: 23498 grad_norm: 3.7800 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.3158 loss: 2.3158 2022/09/08 12:46:52 - mmengine - INFO - Epoch(train) [17][300/880] lr: 2.7092e-02 eta: 2:36:34 time: 0.4469 data_time: 0.0203 memory: 23498 grad_norm: 3.6382 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 2.5074 loss: 2.5074 2022/09/08 12:47:01 - mmengine - INFO - Epoch(train) [17][320/880] lr: 2.7092e-02 eta: 2:36:25 time: 0.4602 data_time: 0.0215 memory: 23498 grad_norm: 3.6823 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 2.4524 loss: 2.4524 2022/09/08 12:47:10 - mmengine - INFO - Epoch(train) [17][340/880] lr: 2.7092e-02 eta: 2:36:16 time: 0.4525 data_time: 0.0249 memory: 23498 grad_norm: 3.6731 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 2.4570 loss: 2.4570 2022/09/08 12:47:19 - mmengine - INFO - Epoch(train) [17][360/880] lr: 2.7092e-02 eta: 2:36:07 time: 0.4456 data_time: 0.0213 memory: 23498 grad_norm: 3.6266 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4922 loss: 2.4922 2022/09/08 12:47:28 - mmengine - INFO - Epoch(train) [17][380/880] lr: 2.7092e-02 eta: 2:35:58 time: 0.4493 data_time: 0.0191 memory: 23498 grad_norm: 3.7409 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4195 loss: 2.4195 2022/09/08 12:47:37 - mmengine - INFO - Epoch(train) [17][400/880] lr: 2.7092e-02 eta: 2:35:49 time: 0.4485 data_time: 0.0238 memory: 23498 grad_norm: 3.6903 top1_acc: 0.5417 top5_acc: 0.6667 loss_cls: 2.4111 loss: 2.4111 2022/09/08 12:47:46 - mmengine - INFO - Epoch(train) [17][420/880] lr: 2.7092e-02 eta: 2:35:40 time: 0.4464 data_time: 0.0196 memory: 23498 grad_norm: 3.8393 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.4267 loss: 2.4267 2022/09/08 12:47:55 - mmengine - INFO - Epoch(train) [17][440/880] lr: 2.7092e-02 eta: 2:35:31 time: 0.4633 data_time: 0.0216 memory: 23498 grad_norm: 3.8116 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 2.4044 loss: 2.4044 2022/09/08 12:48:04 - mmengine - INFO - Epoch(train) [17][460/880] lr: 2.7092e-02 eta: 2:35:22 time: 0.4469 data_time: 0.0195 memory: 23498 grad_norm: 3.7133 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3964 loss: 2.3964 2022/09/08 12:48:13 - mmengine - INFO - Epoch(train) [17][480/880] lr: 2.7092e-02 eta: 2:35:13 time: 0.4510 data_time: 0.0260 memory: 23498 grad_norm: 3.9336 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4961 loss: 2.4961 2022/09/08 12:48:22 - mmengine - INFO - Epoch(train) [17][500/880] lr: 2.7092e-02 eta: 2:35:03 time: 0.4441 data_time: 0.0215 memory: 23498 grad_norm: 3.8422 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.4825 loss: 2.4825 2022/09/08 12:48:31 - mmengine - INFO - Epoch(train) [17][520/880] lr: 2.7092e-02 eta: 2:34:54 time: 0.4446 data_time: 0.0247 memory: 23498 grad_norm: 3.8100 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.3961 loss: 2.3961 2022/09/08 12:48:40 - mmengine - INFO - Epoch(train) [17][540/880] lr: 2.7092e-02 eta: 2:34:45 time: 0.4507 data_time: 0.0234 memory: 23498 grad_norm: 3.9024 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 2.0198 loss: 2.0198 2022/09/08 12:48:49 - mmengine - INFO - Epoch(train) [17][560/880] lr: 2.7092e-02 eta: 2:34:36 time: 0.4445 data_time: 0.0208 memory: 23498 grad_norm: 3.7892 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3691 loss: 2.3691 2022/09/08 12:48:57 - mmengine - INFO - Epoch(train) [17][580/880] lr: 2.7092e-02 eta: 2:34:27 time: 0.4447 data_time: 0.0190 memory: 23498 grad_norm: 3.6965 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.5149 loss: 2.5149 2022/09/08 12:49:06 - mmengine - INFO - Epoch(train) [17][600/880] lr: 2.7092e-02 eta: 2:34:18 time: 0.4477 data_time: 0.0202 memory: 23498 grad_norm: 3.8006 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.4476 loss: 2.4476 2022/09/08 12:49:15 - mmengine - INFO - Epoch(train) [17][620/880] lr: 2.7092e-02 eta: 2:34:09 time: 0.4472 data_time: 0.0213 memory: 23498 grad_norm: 3.8452 top1_acc: 0.2917 top5_acc: 0.5000 loss_cls: 2.3405 loss: 2.3405 2022/09/08 12:49:24 - mmengine - INFO - Epoch(train) [17][640/880] lr: 2.7092e-02 eta: 2:33:59 time: 0.4468 data_time: 0.0204 memory: 23498 grad_norm: 3.8981 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.5110 loss: 2.5110 2022/09/08 12:49:33 - mmengine - INFO - Epoch(train) [17][660/880] lr: 2.7092e-02 eta: 2:33:50 time: 0.4435 data_time: 0.0189 memory: 23498 grad_norm: 3.8559 top1_acc: 0.5000 top5_acc: 0.9167 loss_cls: 2.4308 loss: 2.4308 2022/09/08 12:49:42 - mmengine - INFO - Epoch(train) [17][680/880] lr: 2.7092e-02 eta: 2:33:41 time: 0.4441 data_time: 0.0200 memory: 23498 grad_norm: 3.8626 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.5893 loss: 2.5893 2022/09/08 12:49:51 - mmengine - INFO - Epoch(train) [17][700/880] lr: 2.7092e-02 eta: 2:33:32 time: 0.4454 data_time: 0.0186 memory: 23498 grad_norm: 3.8619 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4302 loss: 2.4302 2022/09/08 12:50:00 - mmengine - INFO - Epoch(train) [17][720/880] lr: 2.7092e-02 eta: 2:33:23 time: 0.4444 data_time: 0.0218 memory: 23498 grad_norm: 3.8860 top1_acc: 0.4583 top5_acc: 0.5833 loss_cls: 2.7451 loss: 2.7451 2022/09/08 12:50:09 - mmengine - INFO - Epoch(train) [17][740/880] lr: 2.7092e-02 eta: 2:33:14 time: 0.4560 data_time: 0.0194 memory: 23498 grad_norm: 3.7304 top1_acc: 0.2917 top5_acc: 0.6667 loss_cls: 2.4758 loss: 2.4758 2022/09/08 12:50:18 - mmengine - INFO - Epoch(train) [17][760/880] lr: 2.7092e-02 eta: 2:33:04 time: 0.4446 data_time: 0.0204 memory: 23498 grad_norm: 3.7243 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 2.4257 loss: 2.4257 2022/09/08 12:50:27 - mmengine - INFO - Epoch(train) [17][780/880] lr: 2.7092e-02 eta: 2:32:55 time: 0.4477 data_time: 0.0211 memory: 23498 grad_norm: 3.8300 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.3361 loss: 2.3361 2022/09/08 12:50:36 - mmengine - INFO - Epoch(train) [17][800/880] lr: 2.7092e-02 eta: 2:32:46 time: 0.4433 data_time: 0.0233 memory: 23498 grad_norm: 3.8605 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.5007 loss: 2.5007 2022/09/08 12:50:45 - mmengine - INFO - Epoch(train) [17][820/880] lr: 2.7092e-02 eta: 2:32:37 time: 0.4463 data_time: 0.0188 memory: 23498 grad_norm: 3.8046 top1_acc: 0.2917 top5_acc: 0.7083 loss_cls: 2.5501 loss: 2.5501 2022/09/08 12:50:53 - mmengine - INFO - Epoch(train) [17][840/880] lr: 2.7092e-02 eta: 2:32:28 time: 0.4415 data_time: 0.0232 memory: 23498 grad_norm: 3.7181 top1_acc: 0.3333 top5_acc: 0.6250 loss_cls: 2.4195 loss: 2.4195 2022/09/08 12:51:02 - mmengine - INFO - Epoch(train) [17][860/880] lr: 2.7092e-02 eta: 2:32:19 time: 0.4459 data_time: 0.0199 memory: 23498 grad_norm: 3.6802 top1_acc: 0.2917 top5_acc: 0.6667 loss_cls: 2.4532 loss: 2.4532 2022/09/08 12:51:11 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 12:51:11 - mmengine - INFO - Epoch(train) [17][880/880] lr: 2.7092e-02 eta: 2:32:09 time: 0.4318 data_time: 0.0184 memory: 23498 grad_norm: 3.8933 top1_acc: 0.4211 top5_acc: 0.5789 loss_cls: 2.4708 loss: 2.4708 2022/09/08 12:51:21 - mmengine - INFO - Epoch(train) [18][20/880] lr: 2.5564e-02 eta: 2:32:02 time: 0.5086 data_time: 0.0722 memory: 23498 grad_norm: 3.7886 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.3183 loss: 2.3183 2022/09/08 12:51:30 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 12:51:30 - mmengine - INFO - Epoch(train) [18][40/880] lr: 2.5564e-02 eta: 2:31:53 time: 0.4566 data_time: 0.0221 memory: 23498 grad_norm: 3.6925 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2045 loss: 2.2045 2022/09/08 12:51:39 - mmengine - INFO - Epoch(train) [18][60/880] lr: 2.5564e-02 eta: 2:31:44 time: 0.4503 data_time: 0.0230 memory: 23498 grad_norm: 3.6867 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.1383 loss: 2.1383 2022/09/08 12:51:48 - mmengine - INFO - Epoch(train) [18][80/880] lr: 2.5564e-02 eta: 2:31:35 time: 0.4500 data_time: 0.0211 memory: 23498 grad_norm: 3.8036 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.3829 loss: 2.3829 2022/09/08 12:51:57 - mmengine - INFO - Epoch(train) [18][100/880] lr: 2.5564e-02 eta: 2:31:26 time: 0.4552 data_time: 0.0272 memory: 23498 grad_norm: 3.7823 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 2.3340 loss: 2.3340 2022/09/08 12:52:06 - mmengine - INFO - Epoch(train) [18][120/880] lr: 2.5564e-02 eta: 2:31:16 time: 0.4451 data_time: 0.0204 memory: 23498 grad_norm: 4.0098 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 2.3939 loss: 2.3939 2022/09/08 12:52:16 - mmengine - INFO - Epoch(train) [18][140/880] lr: 2.5564e-02 eta: 2:31:08 time: 0.4602 data_time: 0.0226 memory: 23498 grad_norm: 3.8877 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3491 loss: 2.3491 2022/09/08 12:52:25 - mmengine - INFO - Epoch(train) [18][160/880] lr: 2.5564e-02 eta: 2:30:59 time: 0.4481 data_time: 0.0208 memory: 23498 grad_norm: 3.8717 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.2485 loss: 2.2485 2022/09/08 12:52:34 - mmengine - INFO - Epoch(train) [18][180/880] lr: 2.5564e-02 eta: 2:30:50 time: 0.4533 data_time: 0.0262 memory: 23498 grad_norm: 4.0286 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4273 loss: 2.4273 2022/09/08 12:52:42 - mmengine - INFO - Epoch(train) [18][200/880] lr: 2.5564e-02 eta: 2:30:40 time: 0.4476 data_time: 0.0204 memory: 23498 grad_norm: 4.0559 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 2.5562 loss: 2.5562 2022/09/08 12:52:52 - mmengine - INFO - Epoch(train) [18][220/880] lr: 2.5564e-02 eta: 2:30:31 time: 0.4521 data_time: 0.0232 memory: 23498 grad_norm: 3.9275 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 2.3825 loss: 2.3825 2022/09/08 12:53:00 - mmengine - INFO - Epoch(train) [18][240/880] lr: 2.5564e-02 eta: 2:30:22 time: 0.4449 data_time: 0.0200 memory: 23498 grad_norm: 3.7660 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 2.4377 loss: 2.4377 2022/09/08 12:53:10 - mmengine - INFO - Epoch(train) [18][260/880] lr: 2.5564e-02 eta: 2:30:13 time: 0.4540 data_time: 0.0248 memory: 23498 grad_norm: 3.8310 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.5927 loss: 2.5927 2022/09/08 12:53:19 - mmengine - INFO - Epoch(train) [18][280/880] lr: 2.5564e-02 eta: 2:30:04 time: 0.4491 data_time: 0.0219 memory: 23498 grad_norm: 3.8097 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.3657 loss: 2.3657 2022/09/08 12:53:28 - mmengine - INFO - Epoch(train) [18][300/880] lr: 2.5564e-02 eta: 2:29:56 time: 0.4799 data_time: 0.0230 memory: 23498 grad_norm: 3.8196 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.4933 loss: 2.4933 2022/09/08 12:53:37 - mmengine - INFO - Epoch(train) [18][320/880] lr: 2.5564e-02 eta: 2:29:47 time: 0.4506 data_time: 0.0211 memory: 23498 grad_norm: 3.8335 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5014 loss: 2.5014 2022/09/08 12:53:46 - mmengine - INFO - Epoch(train) [18][340/880] lr: 2.5564e-02 eta: 2:29:38 time: 0.4589 data_time: 0.0225 memory: 23498 grad_norm: 3.8907 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 2.3315 loss: 2.3315 2022/09/08 12:53:55 - mmengine - INFO - Epoch(train) [18][360/880] lr: 2.5564e-02 eta: 2:29:29 time: 0.4529 data_time: 0.0202 memory: 23498 grad_norm: 3.9636 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.5710 loss: 2.5710 2022/09/08 12:54:04 - mmengine - INFO - Epoch(train) [18][380/880] lr: 2.5564e-02 eta: 2:29:20 time: 0.4553 data_time: 0.0209 memory: 23498 grad_norm: 4.0536 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 2.4522 loss: 2.4522 2022/09/08 12:54:13 - mmengine - INFO - Epoch(train) [18][400/880] lr: 2.5564e-02 eta: 2:29:11 time: 0.4490 data_time: 0.0198 memory: 23498 grad_norm: 3.8430 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 2.5482 loss: 2.5482 2022/09/08 12:54:23 - mmengine - INFO - Epoch(train) [18][420/880] lr: 2.5564e-02 eta: 2:29:02 time: 0.4589 data_time: 0.0235 memory: 23498 grad_norm: 3.7532 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 2.3665 loss: 2.3665 2022/09/08 12:54:32 - mmengine - INFO - Epoch(train) [18][440/880] lr: 2.5564e-02 eta: 2:28:53 time: 0.4525 data_time: 0.0208 memory: 23498 grad_norm: 3.8088 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 2.3515 loss: 2.3515 2022/09/08 12:54:41 - mmengine - INFO - Epoch(train) [18][460/880] lr: 2.5564e-02 eta: 2:28:44 time: 0.4559 data_time: 0.0229 memory: 23498 grad_norm: 3.8493 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.3737 loss: 2.3737 2022/09/08 12:54:50 - mmengine - INFO - Epoch(train) [18][480/880] lr: 2.5564e-02 eta: 2:28:35 time: 0.4505 data_time: 0.0213 memory: 23498 grad_norm: 3.7355 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 2.3673 loss: 2.3673 2022/09/08 12:54:59 - mmengine - INFO - Epoch(train) [18][500/880] lr: 2.5564e-02 eta: 2:28:27 time: 0.4581 data_time: 0.0234 memory: 23498 grad_norm: 3.7291 top1_acc: 0.3333 top5_acc: 0.7500 loss_cls: 2.4043 loss: 2.4043 2022/09/08 12:55:08 - mmengine - INFO - Epoch(train) [18][520/880] lr: 2.5564e-02 eta: 2:28:18 time: 0.4514 data_time: 0.0212 memory: 23498 grad_norm: 3.8039 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 2.2389 loss: 2.2389 2022/09/08 12:55:17 - mmengine - INFO - Epoch(train) [18][540/880] lr: 2.5564e-02 eta: 2:28:09 time: 0.4539 data_time: 0.0218 memory: 23498 grad_norm: 3.8558 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 2.3011 loss: 2.3011 2022/09/08 12:55:26 - mmengine - INFO - Epoch(train) [18][560/880] lr: 2.5564e-02 eta: 2:27:59 time: 0.4458 data_time: 0.0201 memory: 23498 grad_norm: 3.8054 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.4354 loss: 2.4354 2022/09/08 12:55:35 - mmengine - INFO - Epoch(train) [18][580/880] lr: 2.5564e-02 eta: 2:27:50 time: 0.4500 data_time: 0.0247 memory: 23498 grad_norm: 3.8350 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.4153 loss: 2.4153 2022/09/08 12:55:44 - mmengine - INFO - Epoch(train) [18][600/880] lr: 2.5564e-02 eta: 2:27:41 time: 0.4442 data_time: 0.0201 memory: 23498 grad_norm: 3.8077 top1_acc: 0.2917 top5_acc: 0.6667 loss_cls: 2.4735 loss: 2.4735 2022/09/08 12:55:53 - mmengine - INFO - Epoch(train) [18][620/880] lr: 2.5564e-02 eta: 2:27:33 time: 0.4739 data_time: 0.0214 memory: 23498 grad_norm: 3.7674 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 2.4391 loss: 2.4391 2022/09/08 12:56:02 - mmengine - INFO - Epoch(train) [18][640/880] lr: 2.5564e-02 eta: 2:27:24 time: 0.4504 data_time: 0.0236 memory: 23498 grad_norm: 3.7549 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.4415 loss: 2.4415 2022/09/08 12:56:11 - mmengine - INFO - Epoch(train) [18][660/880] lr: 2.5564e-02 eta: 2:27:15 time: 0.4539 data_time: 0.0228 memory: 23498 grad_norm: 3.8678 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.3454 loss: 2.3454 2022/09/08 12:56:20 - mmengine - INFO - Epoch(train) [18][680/880] lr: 2.5564e-02 eta: 2:27:06 time: 0.4481 data_time: 0.0203 memory: 23498 grad_norm: 3.7547 top1_acc: 0.1667 top5_acc: 0.4167 loss_cls: 2.4500 loss: 2.4500 2022/09/08 12:56:30 - mmengine - INFO - Epoch(train) [18][700/880] lr: 2.5564e-02 eta: 2:26:57 time: 0.4577 data_time: 0.0225 memory: 23498 grad_norm: 3.8277 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.3664 loss: 2.3664 2022/09/08 12:56:39 - mmengine - INFO - Epoch(train) [18][720/880] lr: 2.5564e-02 eta: 2:26:48 time: 0.4485 data_time: 0.0204 memory: 23498 grad_norm: 3.7225 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.5330 loss: 2.5330 2022/09/08 12:56:48 - mmengine - INFO - Epoch(train) [18][740/880] lr: 2.5564e-02 eta: 2:26:39 time: 0.4649 data_time: 0.0247 memory: 23498 grad_norm: 3.8283 top1_acc: 0.4583 top5_acc: 0.8750 loss_cls: 2.5061 loss: 2.5061 2022/09/08 12:56:57 - mmengine - INFO - Epoch(train) [18][760/880] lr: 2.5564e-02 eta: 2:26:30 time: 0.4481 data_time: 0.0197 memory: 23498 grad_norm: 3.7796 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.4170 loss: 2.4170 2022/09/08 12:57:06 - mmengine - INFO - Epoch(train) [18][780/880] lr: 2.5564e-02 eta: 2:26:21 time: 0.4663 data_time: 0.0219 memory: 23498 grad_norm: 3.9288 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.4235 loss: 2.4235 2022/09/08 12:57:15 - mmengine - INFO - Epoch(train) [18][800/880] lr: 2.5564e-02 eta: 2:26:12 time: 0.4460 data_time: 0.0210 memory: 23498 grad_norm: 3.7265 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.3735 loss: 2.3735 2022/09/08 12:57:24 - mmengine - INFO - Epoch(train) [18][820/880] lr: 2.5564e-02 eta: 2:26:03 time: 0.4509 data_time: 0.0239 memory: 23498 grad_norm: 3.7214 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4089 loss: 2.4089 2022/09/08 12:57:33 - mmengine - INFO - Epoch(train) [18][840/880] lr: 2.5564e-02 eta: 2:25:54 time: 0.4626 data_time: 0.0205 memory: 23498 grad_norm: 3.7775 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 2.4311 loss: 2.4311 2022/09/08 12:57:42 - mmengine - INFO - Epoch(train) [18][860/880] lr: 2.5564e-02 eta: 2:25:45 time: 0.4575 data_time: 0.0248 memory: 23498 grad_norm: 3.6119 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3366 loss: 2.3366 2022/09/08 12:57:51 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 12:57:51 - mmengine - INFO - Epoch(train) [18][880/880] lr: 2.5564e-02 eta: 2:25:36 time: 0.4353 data_time: 0.0179 memory: 23498 grad_norm: 3.8600 top1_acc: 0.5263 top5_acc: 0.8421 loss_cls: 2.2019 loss: 2.2019 2022/09/08 12:57:56 - mmengine - INFO - Epoch(val) [18][20/130] eta: 0:00:24 time: 0.2206 data_time: 0.0846 memory: 2693 2022/09/08 12:57:59 - mmengine - INFO - Epoch(val) [18][40/130] eta: 0:00:14 time: 0.1612 data_time: 0.0247 memory: 2693 2022/09/08 12:58:02 - mmengine - INFO - Epoch(val) [18][60/130] eta: 0:00:11 time: 0.1657 data_time: 0.0306 memory: 2693 2022/09/08 12:58:05 - mmengine - INFO - Epoch(val) [18][80/130] eta: 0:00:08 time: 0.1660 data_time: 0.0256 memory: 2693 2022/09/08 12:58:09 - mmengine - INFO - Epoch(val) [18][100/130] eta: 0:00:05 time: 0.1669 data_time: 0.0308 memory: 2693 2022/09/08 12:58:12 - mmengine - INFO - Epoch(val) [18][120/130] eta: 0:00:01 time: 0.1619 data_time: 0.0270 memory: 2693 2022/09/08 12:58:15 - mmengine - INFO - Epoch(val) [18][130/130] acc/top1: 0.3730 acc/top5: 0.6627 acc/mean1: 0.3038 2022/09/08 12:58:15 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4/best_acc/top1_epoch_16.pth is removed 2022/09/08 12:58:16 - mmengine - INFO - The best checkpoint with 0.3730 acc/top1 at 18 epoch is saved to best_acc/top1_epoch_18.pth. 2022/09/08 12:58:27 - mmengine - INFO - Epoch(train) [19][20/880] lr: 2.4001e-02 eta: 2:25:28 time: 0.5099 data_time: 0.0727 memory: 23498 grad_norm: 3.9132 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.2918 loss: 2.2918 2022/09/08 12:58:36 - mmengine - INFO - Epoch(train) [19][40/880] lr: 2.4001e-02 eta: 2:25:19 time: 0.4512 data_time: 0.0238 memory: 23498 grad_norm: 3.8226 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 2.2784 loss: 2.2784 2022/09/08 12:58:44 - mmengine - INFO - Epoch(train) [19][60/880] lr: 2.4001e-02 eta: 2:25:10 time: 0.4471 data_time: 0.0215 memory: 23498 grad_norm: 3.6980 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 2.2220 loss: 2.2220 2022/09/08 12:58:54 - mmengine - INFO - Epoch(train) [19][80/880] lr: 2.4001e-02 eta: 2:25:01 time: 0.4613 data_time: 0.0205 memory: 23498 grad_norm: 3.8132 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 2.2818 loss: 2.2818 2022/09/08 12:59:03 - mmengine - INFO - Epoch(train) [19][100/880] lr: 2.4001e-02 eta: 2:24:53 time: 0.4556 data_time: 0.0209 memory: 23498 grad_norm: 3.7755 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.2038 loss: 2.2038 2022/09/08 12:59:12 - mmengine - INFO - Epoch(train) [19][120/880] lr: 2.4001e-02 eta: 2:24:43 time: 0.4500 data_time: 0.0205 memory: 23498 grad_norm: 3.9030 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 2.1952 loss: 2.1952 2022/09/08 12:59:21 - mmengine - INFO - Epoch(train) [19][140/880] lr: 2.4001e-02 eta: 2:24:34 time: 0.4507 data_time: 0.0243 memory: 23498 grad_norm: 3.8430 top1_acc: 0.2917 top5_acc: 0.7083 loss_cls: 2.2402 loss: 2.2402 2022/09/08 12:59:30 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 12:59:30 - mmengine - INFO - Epoch(train) [19][160/880] lr: 2.4001e-02 eta: 2:24:25 time: 0.4522 data_time: 0.0221 memory: 23498 grad_norm: 3.9773 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 2.3642 loss: 2.3642 2022/09/08 12:59:39 - mmengine - INFO - Epoch(train) [19][180/880] lr: 2.4001e-02 eta: 2:24:16 time: 0.4553 data_time: 0.0230 memory: 23498 grad_norm: 3.7569 top1_acc: 0.1667 top5_acc: 0.5417 loss_cls: 2.1499 loss: 2.1499 2022/09/08 12:59:48 - mmengine - INFO - Epoch(train) [19][200/880] lr: 2.4001e-02 eta: 2:24:08 time: 0.4554 data_time: 0.0192 memory: 23498 grad_norm: 3.8591 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.4349 loss: 2.4349 2022/09/08 12:59:57 - mmengine - INFO - Epoch(train) [19][220/880] lr: 2.4001e-02 eta: 2:23:59 time: 0.4542 data_time: 0.0240 memory: 23498 grad_norm: 3.8562 top1_acc: 0.5417 top5_acc: 0.6250 loss_cls: 2.4596 loss: 2.4596 2022/09/08 13:00:06 - mmengine - INFO - Epoch(train) [19][240/880] lr: 2.4001e-02 eta: 2:23:50 time: 0.4553 data_time: 0.0203 memory: 23498 grad_norm: 3.9621 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.4187 loss: 2.4187 2022/09/08 13:00:15 - mmengine - INFO - Epoch(train) [19][260/880] lr: 2.4001e-02 eta: 2:23:41 time: 0.4514 data_time: 0.0215 memory: 23498 grad_norm: 3.8298 top1_acc: 0.5833 top5_acc: 0.6667 loss_cls: 2.3058 loss: 2.3058 2022/09/08 13:00:24 - mmengine - INFO - Epoch(train) [19][280/880] lr: 2.4001e-02 eta: 2:23:32 time: 0.4515 data_time: 0.0218 memory: 23498 grad_norm: 3.6989 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.2543 loss: 2.2543 2022/09/08 13:00:34 - mmengine - INFO - Epoch(train) [19][300/880] lr: 2.4001e-02 eta: 2:23:23 time: 0.4631 data_time: 0.0213 memory: 23498 grad_norm: 3.9048 top1_acc: 0.3750 top5_acc: 0.7917 loss_cls: 2.5519 loss: 2.5519 2022/09/08 13:00:43 - mmengine - INFO - Epoch(train) [19][320/880] lr: 2.4001e-02 eta: 2:23:14 time: 0.4518 data_time: 0.0227 memory: 23498 grad_norm: 3.9420 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3750 loss: 2.3750 2022/09/08 13:00:52 - mmengine - INFO - Epoch(train) [19][340/880] lr: 2.4001e-02 eta: 2:23:05 time: 0.4552 data_time: 0.0224 memory: 23498 grad_norm: 3.8855 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.3406 loss: 2.3406 2022/09/08 13:01:01 - mmengine - INFO - Epoch(train) [19][360/880] lr: 2.4001e-02 eta: 2:22:56 time: 0.4503 data_time: 0.0217 memory: 23498 grad_norm: 3.8981 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.3949 loss: 2.3949 2022/09/08 13:01:10 - mmengine - INFO - Epoch(train) [19][380/880] lr: 2.4001e-02 eta: 2:22:47 time: 0.4720 data_time: 0.0225 memory: 23498 grad_norm: 3.8917 top1_acc: 0.6667 top5_acc: 0.7083 loss_cls: 2.3121 loss: 2.3121 2022/09/08 13:01:19 - mmengine - INFO - Epoch(train) [19][400/880] lr: 2.4001e-02 eta: 2:22:38 time: 0.4530 data_time: 0.0209 memory: 23498 grad_norm: 3.9551 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.4987 loss: 2.4987 2022/09/08 13:01:28 - mmengine - INFO - Epoch(train) [19][420/880] lr: 2.4001e-02 eta: 2:22:29 time: 0.4512 data_time: 0.0215 memory: 23498 grad_norm: 3.9670 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2716 loss: 2.2716 2022/09/08 13:01:37 - mmengine - INFO - Epoch(train) [19][440/880] lr: 2.4001e-02 eta: 2:22:20 time: 0.4500 data_time: 0.0196 memory: 23498 grad_norm: 3.9260 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4566 loss: 2.4566 2022/09/08 13:01:46 - mmengine - INFO - Epoch(train) [19][460/880] lr: 2.4001e-02 eta: 2:22:11 time: 0.4554 data_time: 0.0227 memory: 23498 grad_norm: 3.9386 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.3040 loss: 2.3040 2022/09/08 13:01:55 - mmengine - INFO - Epoch(train) [19][480/880] lr: 2.4001e-02 eta: 2:22:02 time: 0.4517 data_time: 0.0203 memory: 23498 grad_norm: 3.9984 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 2.3543 loss: 2.3543 2022/09/08 13:02:04 - mmengine - INFO - Epoch(train) [19][500/880] lr: 2.4001e-02 eta: 2:21:53 time: 0.4538 data_time: 0.0238 memory: 23498 grad_norm: 3.9158 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 2.1678 loss: 2.1678 2022/09/08 13:02:14 - mmengine - INFO - Epoch(train) [19][520/880] lr: 2.4001e-02 eta: 2:21:45 time: 0.4670 data_time: 0.0196 memory: 23498 grad_norm: 3.8988 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 2.4309 loss: 2.4309 2022/09/08 13:02:23 - mmengine - INFO - Epoch(train) [19][540/880] lr: 2.4001e-02 eta: 2:21:36 time: 0.4595 data_time: 0.0259 memory: 23498 grad_norm: 3.7702 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 2.2710 loss: 2.2710 2022/09/08 13:02:32 - mmengine - INFO - Epoch(train) [19][560/880] lr: 2.4001e-02 eta: 2:21:27 time: 0.4564 data_time: 0.0201 memory: 23498 grad_norm: 3.8311 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 2.3879 loss: 2.3879 2022/09/08 13:02:41 - mmengine - INFO - Epoch(train) [19][580/880] lr: 2.4001e-02 eta: 2:21:18 time: 0.4535 data_time: 0.0229 memory: 23498 grad_norm: 3.8799 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.3308 loss: 2.3308 2022/09/08 13:02:50 - mmengine - INFO - Epoch(train) [19][600/880] lr: 2.4001e-02 eta: 2:21:09 time: 0.4626 data_time: 0.0199 memory: 23498 grad_norm: 3.8011 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4589 loss: 2.4589 2022/09/08 13:03:00 - mmengine - INFO - Epoch(train) [19][620/880] lr: 2.4001e-02 eta: 2:21:00 time: 0.4534 data_time: 0.0228 memory: 23498 grad_norm: 3.7959 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 2.3446 loss: 2.3446 2022/09/08 13:03:09 - mmengine - INFO - Epoch(train) [19][640/880] lr: 2.4001e-02 eta: 2:20:51 time: 0.4505 data_time: 0.0223 memory: 23498 grad_norm: 3.7787 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.3841 loss: 2.3841 2022/09/08 13:03:18 - mmengine - INFO - Epoch(train) [19][660/880] lr: 2.4001e-02 eta: 2:20:42 time: 0.4536 data_time: 0.0235 memory: 23498 grad_norm: 4.0481 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.2964 loss: 2.2964 2022/09/08 13:03:27 - mmengine - INFO - Epoch(train) [19][680/880] lr: 2.4001e-02 eta: 2:20:33 time: 0.4517 data_time: 0.0196 memory: 23498 grad_norm: 4.0060 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 2.1350 loss: 2.1350 2022/09/08 13:03:36 - mmengine - INFO - Epoch(train) [19][700/880] lr: 2.4001e-02 eta: 2:20:24 time: 0.4516 data_time: 0.0229 memory: 23498 grad_norm: 3.8901 top1_acc: 0.3750 top5_acc: 0.9167 loss_cls: 2.2581 loss: 2.2581 2022/09/08 13:03:45 - mmengine - INFO - Epoch(train) [19][720/880] lr: 2.4001e-02 eta: 2:20:15 time: 0.4498 data_time: 0.0208 memory: 23498 grad_norm: 3.9237 top1_acc: 0.3333 top5_acc: 0.6250 loss_cls: 2.3255 loss: 2.3255 2022/09/08 13:03:54 - mmengine - INFO - Epoch(train) [19][740/880] lr: 2.4001e-02 eta: 2:20:06 time: 0.4497 data_time: 0.0219 memory: 23498 grad_norm: 3.7215 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.3700 loss: 2.3700 2022/09/08 13:04:03 - mmengine - INFO - Epoch(train) [19][760/880] lr: 2.4001e-02 eta: 2:19:57 time: 0.4493 data_time: 0.0206 memory: 23498 grad_norm: 3.7683 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.3219 loss: 2.3219 2022/09/08 13:04:12 - mmengine - INFO - Epoch(train) [19][780/880] lr: 2.4001e-02 eta: 2:19:48 time: 0.4536 data_time: 0.0222 memory: 23498 grad_norm: 3.7969 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 2.3372 loss: 2.3372 2022/09/08 13:04:21 - mmengine - INFO - Epoch(train) [19][800/880] lr: 2.4001e-02 eta: 2:19:39 time: 0.4555 data_time: 0.0258 memory: 23498 grad_norm: 3.7312 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3999 loss: 2.3999 2022/09/08 13:04:30 - mmengine - INFO - Epoch(train) [19][820/880] lr: 2.4001e-02 eta: 2:19:30 time: 0.4551 data_time: 0.0226 memory: 23498 grad_norm: 3.7729 top1_acc: 0.3750 top5_acc: 0.5417 loss_cls: 2.3677 loss: 2.3677 2022/09/08 13:04:39 - mmengine - INFO - Epoch(train) [19][840/880] lr: 2.4001e-02 eta: 2:19:21 time: 0.4506 data_time: 0.0192 memory: 23498 grad_norm: 3.8180 top1_acc: 0.3333 top5_acc: 0.7917 loss_cls: 2.2869 loss: 2.2869 2022/09/08 13:04:48 - mmengine - INFO - Epoch(train) [19][860/880] lr: 2.4001e-02 eta: 2:19:12 time: 0.4491 data_time: 0.0227 memory: 23498 grad_norm: 3.7809 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.2310 loss: 2.2310 2022/09/08 13:04:57 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 13:04:57 - mmengine - INFO - Epoch(train) [19][880/880] lr: 2.4001e-02 eta: 2:19:02 time: 0.4327 data_time: 0.0184 memory: 23498 grad_norm: 3.8065 top1_acc: 0.3158 top5_acc: 0.7895 loss_cls: 2.3886 loss: 2.3886 2022/09/08 13:05:07 - mmengine - INFO - Epoch(train) [20][20/880] lr: 2.2411e-02 eta: 2:18:55 time: 0.5183 data_time: 0.0820 memory: 23498 grad_norm: 3.7841 top1_acc: 0.2917 top5_acc: 0.6667 loss_cls: 2.3978 loss: 2.3978 2022/09/08 13:05:16 - mmengine - INFO - Epoch(train) [20][40/880] lr: 2.2411e-02 eta: 2:18:46 time: 0.4490 data_time: 0.0250 memory: 23498 grad_norm: 3.7613 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 2.2079 loss: 2.2079 2022/09/08 13:05:25 - mmengine - INFO - Epoch(train) [20][60/880] lr: 2.2411e-02 eta: 2:18:37 time: 0.4502 data_time: 0.0203 memory: 23498 grad_norm: 3.8436 top1_acc: 0.2917 top5_acc: 0.8333 loss_cls: 2.3278 loss: 2.3278 2022/09/08 13:05:34 - mmengine - INFO - Epoch(train) [20][80/880] lr: 2.2411e-02 eta: 2:18:28 time: 0.4461 data_time: 0.0206 memory: 23498 grad_norm: 3.8900 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 2.1737 loss: 2.1737 2022/09/08 13:05:43 - mmengine - INFO - Epoch(train) [20][100/880] lr: 2.2411e-02 eta: 2:18:18 time: 0.4493 data_time: 0.0201 memory: 23498 grad_norm: 4.0152 top1_acc: 0.2917 top5_acc: 0.6667 loss_cls: 2.2811 loss: 2.2811 2022/09/08 13:05:52 - mmengine - INFO - Epoch(train) [20][120/880] lr: 2.2411e-02 eta: 2:18:09 time: 0.4476 data_time: 0.0205 memory: 23498 grad_norm: 3.9472 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.3115 loss: 2.3115 2022/09/08 13:06:01 - mmengine - INFO - Epoch(train) [20][140/880] lr: 2.2411e-02 eta: 2:18:00 time: 0.4442 data_time: 0.0212 memory: 23498 grad_norm: 4.1175 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 2.3181 loss: 2.3181 2022/09/08 13:06:10 - mmengine - INFO - Epoch(train) [20][160/880] lr: 2.2411e-02 eta: 2:17:51 time: 0.4436 data_time: 0.0213 memory: 23498 grad_norm: 4.0799 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2944 loss: 2.2944 2022/09/08 13:06:19 - mmengine - INFO - Epoch(train) [20][180/880] lr: 2.2411e-02 eta: 2:17:42 time: 0.4466 data_time: 0.0215 memory: 23498 grad_norm: 4.0612 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 2.2659 loss: 2.2659 2022/09/08 13:06:27 - mmengine - INFO - Epoch(train) [20][200/880] lr: 2.2411e-02 eta: 2:17:33 time: 0.4427 data_time: 0.0209 memory: 23498 grad_norm: 4.1191 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2951 loss: 2.2951 2022/09/08 13:06:36 - mmengine - INFO - Epoch(train) [20][220/880] lr: 2.2411e-02 eta: 2:17:24 time: 0.4539 data_time: 0.0211 memory: 23498 grad_norm: 4.0707 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2498 loss: 2.2498 2022/09/08 13:06:45 - mmengine - INFO - Epoch(train) [20][240/880] lr: 2.2411e-02 eta: 2:17:15 time: 0.4498 data_time: 0.0202 memory: 23498 grad_norm: 3.9887 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.1862 loss: 2.1862 2022/09/08 13:06:54 - mmengine - INFO - Epoch(train) [20][260/880] lr: 2.2411e-02 eta: 2:17:05 time: 0.4453 data_time: 0.0210 memory: 23498 grad_norm: 3.9511 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 2.2906 loss: 2.2906 2022/09/08 13:07:03 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 13:07:03 - mmengine - INFO - Epoch(train) [20][280/880] lr: 2.2411e-02 eta: 2:16:56 time: 0.4470 data_time: 0.0202 memory: 23498 grad_norm: 3.8872 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 2.3076 loss: 2.3076 2022/09/08 13:07:12 - mmengine - INFO - Epoch(train) [20][300/880] lr: 2.2411e-02 eta: 2:16:47 time: 0.4449 data_time: 0.0211 memory: 23498 grad_norm: 4.0468 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 2.3360 loss: 2.3360 2022/09/08 13:07:21 - mmengine - INFO - Epoch(train) [20][320/880] lr: 2.2411e-02 eta: 2:16:38 time: 0.4491 data_time: 0.0219 memory: 23498 grad_norm: 3.8917 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.3659 loss: 2.3659 2022/09/08 13:07:30 - mmengine - INFO - Epoch(train) [20][340/880] lr: 2.2411e-02 eta: 2:16:29 time: 0.4490 data_time: 0.0228 memory: 23498 grad_norm: 3.9413 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.3858 loss: 2.3858 2022/09/08 13:07:39 - mmengine - INFO - Epoch(train) [20][360/880] lr: 2.2411e-02 eta: 2:16:20 time: 0.4487 data_time: 0.0198 memory: 23498 grad_norm: 3.8718 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 2.1735 loss: 2.1735 2022/09/08 13:07:48 - mmengine - INFO - Epoch(train) [20][380/880] lr: 2.2411e-02 eta: 2:16:11 time: 0.4450 data_time: 0.0218 memory: 23498 grad_norm: 3.8295 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.2028 loss: 2.2028 2022/09/08 13:07:57 - mmengine - INFO - Epoch(train) [20][400/880] lr: 2.2411e-02 eta: 2:16:02 time: 0.4452 data_time: 0.0210 memory: 23498 grad_norm: 4.0511 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.1504 loss: 2.1504 2022/09/08 13:08:06 - mmengine - INFO - Epoch(train) [20][420/880] lr: 2.2411e-02 eta: 2:15:52 time: 0.4461 data_time: 0.0227 memory: 23498 grad_norm: 3.9871 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.2348 loss: 2.2348 2022/09/08 13:08:15 - mmengine - INFO - Epoch(train) [20][440/880] lr: 2.2411e-02 eta: 2:15:43 time: 0.4452 data_time: 0.0205 memory: 23498 grad_norm: 3.9432 top1_acc: 0.2500 top5_acc: 0.7083 loss_cls: 2.4471 loss: 2.4471 2022/09/08 13:08:24 - mmengine - INFO - Epoch(train) [20][460/880] lr: 2.2411e-02 eta: 2:15:34 time: 0.4485 data_time: 0.0242 memory: 23498 grad_norm: 3.8247 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 2.2772 loss: 2.2772 2022/09/08 13:08:33 - mmengine - INFO - Epoch(train) [20][480/880] lr: 2.2411e-02 eta: 2:15:25 time: 0.4420 data_time: 0.0192 memory: 23498 grad_norm: 4.0983 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 2.4597 loss: 2.4597 2022/09/08 13:08:42 - mmengine - INFO - Epoch(train) [20][500/880] lr: 2.2411e-02 eta: 2:15:16 time: 0.4446 data_time: 0.0237 memory: 23498 grad_norm: 3.9904 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2894 loss: 2.2894 2022/09/08 13:08:50 - mmengine - INFO - Epoch(train) [20][520/880] lr: 2.2411e-02 eta: 2:15:06 time: 0.4415 data_time: 0.0192 memory: 23498 grad_norm: 3.9087 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.2742 loss: 2.2742 2022/09/08 13:08:59 - mmengine - INFO - Epoch(train) [20][540/880] lr: 2.2411e-02 eta: 2:14:57 time: 0.4461 data_time: 0.0211 memory: 23498 grad_norm: 4.0378 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2462 loss: 2.2462 2022/09/08 13:09:08 - mmengine - INFO - Epoch(train) [20][560/880] lr: 2.2411e-02 eta: 2:14:48 time: 0.4426 data_time: 0.0220 memory: 23498 grad_norm: 4.0634 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 2.2962 loss: 2.2962 2022/09/08 13:09:17 - mmengine - INFO - Epoch(train) [20][580/880] lr: 2.2411e-02 eta: 2:14:39 time: 0.4513 data_time: 0.0229 memory: 23498 grad_norm: 3.9141 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.4260 loss: 2.4260 2022/09/08 13:09:26 - mmengine - INFO - Epoch(train) [20][600/880] lr: 2.2411e-02 eta: 2:14:30 time: 0.4394 data_time: 0.0213 memory: 23498 grad_norm: 3.9426 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3011 loss: 2.3011 2022/09/08 13:09:35 - mmengine - INFO - Epoch(train) [20][620/880] lr: 2.2411e-02 eta: 2:14:21 time: 0.4432 data_time: 0.0227 memory: 23498 grad_norm: 4.0567 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.4082 loss: 2.4082 2022/09/08 13:09:44 - mmengine - INFO - Epoch(train) [20][640/880] lr: 2.2411e-02 eta: 2:14:12 time: 0.4571 data_time: 0.0239 memory: 23498 grad_norm: 3.9203 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.1847 loss: 2.1847 2022/09/08 13:09:53 - mmengine - INFO - Epoch(train) [20][660/880] lr: 2.2411e-02 eta: 2:14:03 time: 0.4435 data_time: 0.0203 memory: 23498 grad_norm: 3.9433 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2682 loss: 2.2682 2022/09/08 13:10:02 - mmengine - INFO - Epoch(train) [20][680/880] lr: 2.2411e-02 eta: 2:13:53 time: 0.4475 data_time: 0.0284 memory: 23498 grad_norm: 3.9137 top1_acc: 0.3333 top5_acc: 0.6250 loss_cls: 2.3928 loss: 2.3928 2022/09/08 13:10:11 - mmengine - INFO - Epoch(train) [20][700/880] lr: 2.2411e-02 eta: 2:13:44 time: 0.4404 data_time: 0.0206 memory: 23498 grad_norm: 3.9279 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.2784 loss: 2.2784 2022/09/08 13:10:19 - mmengine - INFO - Epoch(train) [20][720/880] lr: 2.2411e-02 eta: 2:13:35 time: 0.4422 data_time: 0.0201 memory: 23498 grad_norm: 3.8033 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.2795 loss: 2.2795 2022/09/08 13:10:28 - mmengine - INFO - Epoch(train) [20][740/880] lr: 2.2411e-02 eta: 2:13:26 time: 0.4440 data_time: 0.0226 memory: 23498 grad_norm: 3.7690 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.2835 loss: 2.2835 2022/09/08 13:10:37 - mmengine - INFO - Epoch(train) [20][760/880] lr: 2.2411e-02 eta: 2:13:17 time: 0.4415 data_time: 0.0223 memory: 23498 grad_norm: 3.9566 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.4266 loss: 2.4266 2022/09/08 13:10:46 - mmengine - INFO - Epoch(train) [20][780/880] lr: 2.2411e-02 eta: 2:13:07 time: 0.4429 data_time: 0.0220 memory: 23498 grad_norm: 4.0224 top1_acc: 0.3333 top5_acc: 0.6250 loss_cls: 2.2611 loss: 2.2611 2022/09/08 13:10:55 - mmengine - INFO - Epoch(train) [20][800/880] lr: 2.2411e-02 eta: 2:12:58 time: 0.4432 data_time: 0.0208 memory: 23498 grad_norm: 3.9419 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 2.3112 loss: 2.3112 2022/09/08 13:11:04 - mmengine - INFO - Epoch(train) [20][820/880] lr: 2.2411e-02 eta: 2:12:49 time: 0.4454 data_time: 0.0213 memory: 23498 grad_norm: 3.9528 top1_acc: 0.2917 top5_acc: 0.5000 loss_cls: 2.3145 loss: 2.3145 2022/09/08 13:11:13 - mmengine - INFO - Epoch(train) [20][840/880] lr: 2.2411e-02 eta: 2:12:40 time: 0.4419 data_time: 0.0212 memory: 23498 grad_norm: 4.1029 top1_acc: 0.5417 top5_acc: 0.6667 loss_cls: 2.3996 loss: 2.3996 2022/09/08 13:11:22 - mmengine - INFO - Epoch(train) [20][860/880] lr: 2.2411e-02 eta: 2:12:31 time: 0.4486 data_time: 0.0263 memory: 23498 grad_norm: 4.0365 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 2.2846 loss: 2.2846 2022/09/08 13:11:30 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 13:11:30 - mmengine - INFO - Epoch(train) [20][880/880] lr: 2.2411e-02 eta: 2:12:21 time: 0.4359 data_time: 0.0194 memory: 23498 grad_norm: 4.1103 top1_acc: 0.4211 top5_acc: 0.6316 loss_cls: 2.2541 loss: 2.2541 2022/09/08 13:11:35 - mmengine - INFO - Epoch(val) [20][20/130] eta: 0:00:24 time: 0.2249 data_time: 0.0884 memory: 2693 2022/09/08 13:11:38 - mmengine - INFO - Epoch(val) [20][40/130] eta: 0:00:14 time: 0.1625 data_time: 0.0247 memory: 2693 2022/09/08 13:11:42 - mmengine - INFO - Epoch(val) [20][60/130] eta: 0:00:12 time: 0.1717 data_time: 0.0344 memory: 2693 2022/09/08 13:11:45 - mmengine - INFO - Epoch(val) [20][80/130] eta: 0:00:08 time: 0.1645 data_time: 0.0274 memory: 2693 2022/09/08 13:11:48 - mmengine - INFO - Epoch(val) [20][100/130] eta: 0:00:05 time: 0.1758 data_time: 0.0386 memory: 2693 2022/09/08 13:11:52 - mmengine - INFO - Epoch(val) [20][120/130] eta: 0:00:01 time: 0.1606 data_time: 0.0273 memory: 2693 2022/09/08 13:11:54 - mmengine - INFO - Epoch(val) [20][130/130] acc/top1: 0.3802 acc/top5: 0.6830 acc/mean1: 0.3230 2022/09/08 13:11:54 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4/best_acc/top1_epoch_18.pth is removed 2022/09/08 13:11:55 - mmengine - INFO - The best checkpoint with 0.3802 acc/top1 at 20 epoch is saved to best_acc/top1_epoch_20.pth. 2022/09/08 13:12:05 - mmengine - INFO - Epoch(train) [21][20/880] lr: 2.0805e-02 eta: 2:12:13 time: 0.4958 data_time: 0.0688 memory: 23498 grad_norm: 3.9508 top1_acc: 0.2917 top5_acc: 0.6250 loss_cls: 2.2891 loss: 2.2891 2022/09/08 13:12:14 - mmengine - INFO - Epoch(train) [21][40/880] lr: 2.0805e-02 eta: 2:12:04 time: 0.4448 data_time: 0.0211 memory: 23498 grad_norm: 4.0323 top1_acc: 0.2500 top5_acc: 0.7917 loss_cls: 2.3526 loss: 2.3526 2022/09/08 13:12:23 - mmengine - INFO - Epoch(train) [21][60/880] lr: 2.0805e-02 eta: 2:11:55 time: 0.4500 data_time: 0.0218 memory: 23498 grad_norm: 3.9855 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.2164 loss: 2.2164 2022/09/08 13:12:32 - mmengine - INFO - Epoch(train) [21][80/880] lr: 2.0805e-02 eta: 2:11:46 time: 0.4453 data_time: 0.0242 memory: 23498 grad_norm: 4.0035 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.2224 loss: 2.2224 2022/09/08 13:12:41 - mmengine - INFO - Epoch(train) [21][100/880] lr: 2.0805e-02 eta: 2:11:37 time: 0.4447 data_time: 0.0213 memory: 23498 grad_norm: 3.9354 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 2.1017 loss: 2.1017 2022/09/08 13:12:49 - mmengine - INFO - Epoch(train) [21][120/880] lr: 2.0805e-02 eta: 2:11:28 time: 0.4432 data_time: 0.0211 memory: 23498 grad_norm: 3.9646 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.2159 loss: 2.2159 2022/09/08 13:12:58 - mmengine - INFO - Epoch(train) [21][140/880] lr: 2.0805e-02 eta: 2:11:18 time: 0.4454 data_time: 0.0208 memory: 23498 grad_norm: 4.1456 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 2.3133 loss: 2.3133 2022/09/08 13:13:07 - mmengine - INFO - Epoch(train) [21][160/880] lr: 2.0805e-02 eta: 2:11:09 time: 0.4421 data_time: 0.0211 memory: 23498 grad_norm: 4.0905 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.1943 loss: 2.1943 2022/09/08 13:13:16 - mmengine - INFO - Epoch(train) [21][180/880] lr: 2.0805e-02 eta: 2:11:00 time: 0.4436 data_time: 0.0209 memory: 23498 grad_norm: 3.9906 top1_acc: 0.3750 top5_acc: 0.7917 loss_cls: 2.3017 loss: 2.3017 2022/09/08 13:13:25 - mmengine - INFO - Epoch(train) [21][200/880] lr: 2.0805e-02 eta: 2:10:51 time: 0.4624 data_time: 0.0219 memory: 23498 grad_norm: 4.0180 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.2876 loss: 2.2876 2022/09/08 13:13:34 - mmengine - INFO - Epoch(train) [21][220/880] lr: 2.0805e-02 eta: 2:10:42 time: 0.4485 data_time: 0.0212 memory: 23498 grad_norm: 3.9642 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.2550 loss: 2.2550 2022/09/08 13:13:43 - mmengine - INFO - Epoch(train) [21][240/880] lr: 2.0805e-02 eta: 2:10:33 time: 0.4544 data_time: 0.0229 memory: 23498 grad_norm: 4.0785 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 2.1112 loss: 2.1112 2022/09/08 13:13:52 - mmengine - INFO - Epoch(train) [21][260/880] lr: 2.0805e-02 eta: 2:10:24 time: 0.4453 data_time: 0.0210 memory: 23498 grad_norm: 4.0672 top1_acc: 0.5417 top5_acc: 0.6667 loss_cls: 2.0858 loss: 2.0858 2022/09/08 13:14:01 - mmengine - INFO - Epoch(train) [21][280/880] lr: 2.0805e-02 eta: 2:10:15 time: 0.4482 data_time: 0.0216 memory: 23498 grad_norm: 3.9928 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.1311 loss: 2.1311 2022/09/08 13:14:10 - mmengine - INFO - Epoch(train) [21][300/880] lr: 2.0805e-02 eta: 2:10:06 time: 0.4431 data_time: 0.0210 memory: 23498 grad_norm: 4.1763 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.2888 loss: 2.2888 2022/09/08 13:14:19 - mmengine - INFO - Epoch(train) [21][320/880] lr: 2.0805e-02 eta: 2:09:57 time: 0.4491 data_time: 0.0232 memory: 23498 grad_norm: 4.1468 top1_acc: 0.4583 top5_acc: 0.8750 loss_cls: 2.0568 loss: 2.0568 2022/09/08 13:14:28 - mmengine - INFO - Epoch(train) [21][340/880] lr: 2.0805e-02 eta: 2:09:48 time: 0.4462 data_time: 0.0200 memory: 23498 grad_norm: 4.1196 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 2.2562 loss: 2.2562 2022/09/08 13:14:37 - mmengine - INFO - Epoch(train) [21][360/880] lr: 2.0805e-02 eta: 2:09:39 time: 0.4491 data_time: 0.0244 memory: 23498 grad_norm: 3.9138 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 2.1956 loss: 2.1956 2022/09/08 13:14:46 - mmengine - INFO - Epoch(train) [21][380/880] lr: 2.0805e-02 eta: 2:09:29 time: 0.4457 data_time: 0.0187 memory: 23498 grad_norm: 4.0955 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.3556 loss: 2.3556 2022/09/08 13:14:55 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 13:14:55 - mmengine - INFO - Epoch(train) [21][400/880] lr: 2.0805e-02 eta: 2:09:20 time: 0.4467 data_time: 0.0209 memory: 23498 grad_norm: 3.9777 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.1853 loss: 2.1853 2022/09/08 13:15:04 - mmengine - INFO - Epoch(train) [21][420/880] lr: 2.0805e-02 eta: 2:09:11 time: 0.4495 data_time: 0.0227 memory: 23498 grad_norm: 3.9954 top1_acc: 0.3750 top5_acc: 0.7917 loss_cls: 2.3508 loss: 2.3508 2022/09/08 13:15:13 - mmengine - INFO - Epoch(train) [21][440/880] lr: 2.0805e-02 eta: 2:09:02 time: 0.4479 data_time: 0.0237 memory: 23498 grad_norm: 4.0084 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 2.0992 loss: 2.0992 2022/09/08 13:15:22 - mmengine - INFO - Epoch(train) [21][460/880] lr: 2.0805e-02 eta: 2:08:53 time: 0.4442 data_time: 0.0212 memory: 23498 grad_norm: 3.9753 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.1777 loss: 2.1777 2022/09/08 13:15:31 - mmengine - INFO - Epoch(train) [21][480/880] lr: 2.0805e-02 eta: 2:08:44 time: 0.4465 data_time: 0.0198 memory: 23498 grad_norm: 4.1693 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.1180 loss: 2.1180 2022/09/08 13:15:39 - mmengine - INFO - Epoch(train) [21][500/880] lr: 2.0805e-02 eta: 2:08:35 time: 0.4432 data_time: 0.0205 memory: 23498 grad_norm: 4.0840 top1_acc: 0.5417 top5_acc: 0.6250 loss_cls: 2.2039 loss: 2.2039 2022/09/08 13:15:48 - mmengine - INFO - Epoch(train) [21][520/880] lr: 2.0805e-02 eta: 2:08:26 time: 0.4483 data_time: 0.0229 memory: 23498 grad_norm: 4.1035 top1_acc: 0.2500 top5_acc: 0.6667 loss_cls: 2.3525 loss: 2.3525 2022/09/08 13:15:57 - mmengine - INFO - Epoch(train) [21][540/880] lr: 2.0805e-02 eta: 2:08:17 time: 0.4461 data_time: 0.0207 memory: 23498 grad_norm: 4.1241 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 2.2377 loss: 2.2377 2022/09/08 13:16:06 - mmengine - INFO - Epoch(train) [21][560/880] lr: 2.0805e-02 eta: 2:08:07 time: 0.4445 data_time: 0.0201 memory: 23498 grad_norm: 4.1373 top1_acc: 0.3750 top5_acc: 0.5417 loss_cls: 2.3956 loss: 2.3956 2022/09/08 13:16:15 - mmengine - INFO - Epoch(train) [21][580/880] lr: 2.0805e-02 eta: 2:07:58 time: 0.4508 data_time: 0.0210 memory: 23498 grad_norm: 3.8961 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 2.0407 loss: 2.0407 2022/09/08 13:16:24 - mmengine - INFO - Epoch(train) [21][600/880] lr: 2.0805e-02 eta: 2:07:49 time: 0.4461 data_time: 0.0214 memory: 23498 grad_norm: 3.9930 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 2.1375 loss: 2.1375 2022/09/08 13:16:33 - mmengine - INFO - Epoch(train) [21][620/880] lr: 2.0805e-02 eta: 2:07:40 time: 0.4476 data_time: 0.0209 memory: 23498 grad_norm: 3.9653 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.2630 loss: 2.2630 2022/09/08 13:16:42 - mmengine - INFO - Epoch(train) [21][640/880] lr: 2.0805e-02 eta: 2:07:31 time: 0.4550 data_time: 0.0218 memory: 23498 grad_norm: 3.9648 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.2437 loss: 2.2437 2022/09/08 13:16:51 - mmengine - INFO - Epoch(train) [21][660/880] lr: 2.0805e-02 eta: 2:07:22 time: 0.4436 data_time: 0.0222 memory: 23498 grad_norm: 3.9512 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.1580 loss: 2.1580 2022/09/08 13:17:00 - mmengine - INFO - Epoch(train) [21][680/880] lr: 2.0805e-02 eta: 2:07:13 time: 0.4493 data_time: 0.0214 memory: 23498 grad_norm: 4.0993 top1_acc: 0.2083 top5_acc: 0.5833 loss_cls: 2.2616 loss: 2.2616 2022/09/08 13:17:09 - mmengine - INFO - Epoch(train) [21][700/880] lr: 2.0805e-02 eta: 2:07:04 time: 0.4458 data_time: 0.0205 memory: 23498 grad_norm: 4.2110 top1_acc: 0.4583 top5_acc: 0.5833 loss_cls: 2.3067 loss: 2.3067 2022/09/08 13:17:18 - mmengine - INFO - Epoch(train) [21][720/880] lr: 2.0805e-02 eta: 2:06:55 time: 0.4461 data_time: 0.0210 memory: 23498 grad_norm: 4.1254 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 2.1421 loss: 2.1421 2022/09/08 13:17:27 - mmengine - INFO - Epoch(train) [21][740/880] lr: 2.0805e-02 eta: 2:06:46 time: 0.4426 data_time: 0.0202 memory: 23498 grad_norm: 4.1042 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1316 loss: 2.1316 2022/09/08 13:17:36 - mmengine - INFO - Epoch(train) [21][760/880] lr: 2.0805e-02 eta: 2:06:36 time: 0.4466 data_time: 0.0238 memory: 23498 grad_norm: 4.0949 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 2.0980 loss: 2.0980 2022/09/08 13:17:45 - mmengine - INFO - Epoch(train) [21][780/880] lr: 2.0805e-02 eta: 2:06:27 time: 0.4441 data_time: 0.0225 memory: 23498 grad_norm: 4.1205 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.3894 loss: 2.3894 2022/09/08 13:17:54 - mmengine - INFO - Epoch(train) [21][800/880] lr: 2.0805e-02 eta: 2:06:18 time: 0.4492 data_time: 0.0227 memory: 23498 grad_norm: 4.1174 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.3286 loss: 2.3286 2022/09/08 13:18:02 - mmengine - INFO - Epoch(train) [21][820/880] lr: 2.0805e-02 eta: 2:06:09 time: 0.4464 data_time: 0.0234 memory: 23498 grad_norm: 4.1348 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.1656 loss: 2.1656 2022/09/08 13:18:11 - mmengine - INFO - Epoch(train) [21][840/880] lr: 2.0805e-02 eta: 2:06:00 time: 0.4479 data_time: 0.0217 memory: 23498 grad_norm: 4.0981 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 2.2731 loss: 2.2731 2022/09/08 13:18:20 - mmengine - INFO - Epoch(train) [21][860/880] lr: 2.0805e-02 eta: 2:05:51 time: 0.4480 data_time: 0.0211 memory: 23498 grad_norm: 4.0717 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 2.0692 loss: 2.0692 2022/09/08 13:18:30 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 13:18:30 - mmengine - INFO - Epoch(train) [21][880/880] lr: 2.0805e-02 eta: 2:05:42 time: 0.4547 data_time: 0.0203 memory: 23498 grad_norm: 4.2028 top1_acc: 0.5263 top5_acc: 0.7895 loss_cls: 2.2657 loss: 2.2657 2022/09/08 13:18:40 - mmengine - INFO - Epoch(train) [22][20/880] lr: 1.9195e-02 eta: 2:05:34 time: 0.5145 data_time: 0.0797 memory: 23498 grad_norm: 4.2205 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 2.2229 loss: 2.2229 2022/09/08 13:18:49 - mmengine - INFO - Epoch(train) [22][40/880] lr: 1.9195e-02 eta: 2:05:25 time: 0.4486 data_time: 0.0209 memory: 23498 grad_norm: 4.2001 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.0839 loss: 2.0839 2022/09/08 13:18:58 - mmengine - INFO - Epoch(train) [22][60/880] lr: 1.9195e-02 eta: 2:05:16 time: 0.4523 data_time: 0.0206 memory: 23498 grad_norm: 4.3075 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.1562 loss: 2.1562 2022/09/08 13:19:07 - mmengine - INFO - Epoch(train) [22][80/880] lr: 1.9195e-02 eta: 2:05:07 time: 0.4469 data_time: 0.0197 memory: 23498 grad_norm: 4.2180 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.3777 loss: 2.3777 2022/09/08 13:19:16 - mmengine - INFO - Epoch(train) [22][100/880] lr: 1.9195e-02 eta: 2:04:58 time: 0.4576 data_time: 0.0211 memory: 23498 grad_norm: 4.4184 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.9952 loss: 1.9952 2022/09/08 13:19:25 - mmengine - INFO - Epoch(train) [22][120/880] lr: 1.9195e-02 eta: 2:04:49 time: 0.4503 data_time: 0.0212 memory: 23498 grad_norm: 4.2917 top1_acc: 0.3333 top5_acc: 0.6250 loss_cls: 2.2923 loss: 2.2923 2022/09/08 13:19:34 - mmengine - INFO - Epoch(train) [22][140/880] lr: 1.9195e-02 eta: 2:04:40 time: 0.4620 data_time: 0.0219 memory: 23498 grad_norm: 4.2913 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 2.2375 loss: 2.2375 2022/09/08 13:19:43 - mmengine - INFO - Epoch(train) [22][160/880] lr: 1.9195e-02 eta: 2:04:31 time: 0.4484 data_time: 0.0203 memory: 23498 grad_norm: 4.1919 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.2910 loss: 2.2910 2022/09/08 13:19:52 - mmengine - INFO - Epoch(train) [22][180/880] lr: 1.9195e-02 eta: 2:04:22 time: 0.4601 data_time: 0.0251 memory: 23498 grad_norm: 4.2404 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 2.1901 loss: 2.1901 2022/09/08 13:20:01 - mmengine - INFO - Epoch(train) [22][200/880] lr: 1.9195e-02 eta: 2:04:13 time: 0.4515 data_time: 0.0220 memory: 23498 grad_norm: 4.2974 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.1119 loss: 2.1119 2022/09/08 13:20:11 - mmengine - INFO - Epoch(train) [22][220/880] lr: 1.9195e-02 eta: 2:04:04 time: 0.4571 data_time: 0.0217 memory: 23498 grad_norm: 4.4787 top1_acc: 0.5833 top5_acc: 1.0000 loss_cls: 2.0823 loss: 2.0823 2022/09/08 13:20:20 - mmengine - INFO - Epoch(train) [22][240/880] lr: 1.9195e-02 eta: 2:03:55 time: 0.4494 data_time: 0.0217 memory: 23498 grad_norm: 4.4213 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 2.2773 loss: 2.2773 2022/09/08 13:20:29 - mmengine - INFO - Epoch(train) [22][260/880] lr: 1.9195e-02 eta: 2:03:46 time: 0.4584 data_time: 0.0227 memory: 23498 grad_norm: 4.5530 top1_acc: 0.4583 top5_acc: 0.5833 loss_cls: 2.3542 loss: 2.3542 2022/09/08 13:20:38 - mmengine - INFO - Epoch(train) [22][280/880] lr: 1.9195e-02 eta: 2:03:37 time: 0.4502 data_time: 0.0203 memory: 23498 grad_norm: 4.3447 top1_acc: 0.3750 top5_acc: 0.5417 loss_cls: 2.2209 loss: 2.2209 2022/09/08 13:20:47 - mmengine - INFO - Epoch(train) [22][300/880] lr: 1.9195e-02 eta: 2:03:29 time: 0.4639 data_time: 0.0217 memory: 23498 grad_norm: 4.2049 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.1061 loss: 2.1061 2022/09/08 13:20:56 - mmengine - INFO - Epoch(train) [22][320/880] lr: 1.9195e-02 eta: 2:03:19 time: 0.4500 data_time: 0.0199 memory: 23498 grad_norm: 4.0330 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.3247 loss: 2.3247 2022/09/08 13:21:05 - mmengine - INFO - Epoch(train) [22][340/880] lr: 1.9195e-02 eta: 2:03:11 time: 0.4683 data_time: 0.0227 memory: 23498 grad_norm: 4.2151 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 2.2430 loss: 2.2430 2022/09/08 13:21:14 - mmengine - INFO - Epoch(train) [22][360/880] lr: 1.9195e-02 eta: 2:03:02 time: 0.4524 data_time: 0.0214 memory: 23498 grad_norm: 4.1686 top1_acc: 0.3333 top5_acc: 0.7500 loss_cls: 2.3879 loss: 2.3879 2022/09/08 13:21:24 - mmengine - INFO - Epoch(train) [22][380/880] lr: 1.9195e-02 eta: 2:02:53 time: 0.4580 data_time: 0.0235 memory: 23498 grad_norm: 4.1591 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.2142 loss: 2.2142 2022/09/08 13:21:33 - mmengine - INFO - Epoch(train) [22][400/880] lr: 1.9195e-02 eta: 2:02:44 time: 0.4501 data_time: 0.0199 memory: 23498 grad_norm: 4.2093 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 2.2046 loss: 2.2046 2022/09/08 13:21:42 - mmengine - INFO - Epoch(train) [22][420/880] lr: 1.9195e-02 eta: 2:02:35 time: 0.4573 data_time: 0.0218 memory: 23498 grad_norm: 4.3625 top1_acc: 0.2917 top5_acc: 0.5833 loss_cls: 2.3145 loss: 2.3145 2022/09/08 13:21:51 - mmengine - INFO - Epoch(train) [22][440/880] lr: 1.9195e-02 eta: 2:02:26 time: 0.4496 data_time: 0.0203 memory: 23498 grad_norm: 4.3430 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2221 loss: 2.2221 2022/09/08 13:22:00 - mmengine - INFO - Epoch(train) [22][460/880] lr: 1.9195e-02 eta: 2:02:17 time: 0.4611 data_time: 0.0224 memory: 23498 grad_norm: 4.3508 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.1493 loss: 2.1493 2022/09/08 13:22:09 - mmengine - INFO - Epoch(train) [22][480/880] lr: 1.9195e-02 eta: 2:02:08 time: 0.4507 data_time: 0.0196 memory: 23498 grad_norm: 4.2835 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1477 loss: 2.1477 2022/09/08 13:22:18 - mmengine - INFO - Epoch(train) [22][500/880] lr: 1.9195e-02 eta: 2:01:59 time: 0.4568 data_time: 0.0223 memory: 23498 grad_norm: 4.2239 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.2253 loss: 2.2253 2022/09/08 13:22:27 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 13:22:27 - mmengine - INFO - Epoch(train) [22][520/880] lr: 1.9195e-02 eta: 2:01:50 time: 0.4482 data_time: 0.0211 memory: 23498 grad_norm: 4.2014 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 2.3039 loss: 2.3039 2022/09/08 13:22:36 - mmengine - INFO - Epoch(train) [22][540/880] lr: 1.9195e-02 eta: 2:01:41 time: 0.4674 data_time: 0.0221 memory: 23498 grad_norm: 4.1599 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0929 loss: 2.0929 2022/09/08 13:22:45 - mmengine - INFO - Epoch(train) [22][560/880] lr: 1.9195e-02 eta: 2:01:32 time: 0.4498 data_time: 0.0215 memory: 23498 grad_norm: 4.1325 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 2.1960 loss: 2.1960 2022/09/08 13:22:55 - mmengine - INFO - Epoch(train) [22][580/880] lr: 1.9195e-02 eta: 2:01:23 time: 0.4560 data_time: 0.0224 memory: 23498 grad_norm: 4.2880 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.0720 loss: 2.0720 2022/09/08 13:23:04 - mmengine - INFO - Epoch(train) [22][600/880] lr: 1.9195e-02 eta: 2:01:14 time: 0.4497 data_time: 0.0226 memory: 23498 grad_norm: 4.1839 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.2103 loss: 2.2103 2022/09/08 13:23:13 - mmengine - INFO - Epoch(train) [22][620/880] lr: 1.9195e-02 eta: 2:01:05 time: 0.4554 data_time: 0.0227 memory: 23498 grad_norm: 4.3712 top1_acc: 0.3333 top5_acc: 0.7917 loss_cls: 2.2972 loss: 2.2972 2022/09/08 13:23:22 - mmengine - INFO - Epoch(train) [22][640/880] lr: 1.9195e-02 eta: 2:00:56 time: 0.4481 data_time: 0.0212 memory: 23498 grad_norm: 4.1861 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0039 loss: 2.0039 2022/09/08 13:23:31 - mmengine - INFO - Epoch(train) [22][660/880] lr: 1.9195e-02 eta: 2:00:47 time: 0.4580 data_time: 0.0220 memory: 23498 grad_norm: 4.1424 top1_acc: 0.3333 top5_acc: 0.6250 loss_cls: 2.2462 loss: 2.2462 2022/09/08 13:23:40 - mmengine - INFO - Epoch(train) [22][680/880] lr: 1.9195e-02 eta: 2:00:38 time: 0.4486 data_time: 0.0208 memory: 23498 grad_norm: 4.1978 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2184 loss: 2.2184 2022/09/08 13:23:49 - mmengine - INFO - Epoch(train) [22][700/880] lr: 1.9195e-02 eta: 2:00:29 time: 0.4534 data_time: 0.0225 memory: 23498 grad_norm: 4.1662 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 2.3755 loss: 2.3755 2022/09/08 13:23:58 - mmengine - INFO - Epoch(train) [22][720/880] lr: 1.9195e-02 eta: 2:00:20 time: 0.4498 data_time: 0.0216 memory: 23498 grad_norm: 4.2017 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 2.1605 loss: 2.1605 2022/09/08 13:24:07 - mmengine - INFO - Epoch(train) [22][740/880] lr: 1.9195e-02 eta: 2:00:11 time: 0.4534 data_time: 0.0203 memory: 23498 grad_norm: 4.1142 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.1012 loss: 2.1012 2022/09/08 13:24:16 - mmengine - INFO - Epoch(train) [22][760/880] lr: 1.9195e-02 eta: 2:00:02 time: 0.4491 data_time: 0.0210 memory: 23498 grad_norm: 4.0472 top1_acc: 0.2917 top5_acc: 0.6667 loss_cls: 2.1478 loss: 2.1478 2022/09/08 13:24:25 - mmengine - INFO - Epoch(train) [22][780/880] lr: 1.9195e-02 eta: 1:59:53 time: 0.4564 data_time: 0.0226 memory: 23498 grad_norm: 4.1951 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.4431 loss: 2.4431 2022/09/08 13:24:34 - mmengine - INFO - Epoch(train) [22][800/880] lr: 1.9195e-02 eta: 1:59:44 time: 0.4518 data_time: 0.0208 memory: 23498 grad_norm: 4.2289 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.3065 loss: 2.3065 2022/09/08 13:24:43 - mmengine - INFO - Epoch(train) [22][820/880] lr: 1.9195e-02 eta: 1:59:35 time: 0.4497 data_time: 0.0210 memory: 23498 grad_norm: 4.1891 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.2174 loss: 2.2174 2022/09/08 13:24:52 - mmengine - INFO - Epoch(train) [22][840/880] lr: 1.9195e-02 eta: 1:59:26 time: 0.4556 data_time: 0.0196 memory: 23498 grad_norm: 4.1804 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.3734 loss: 2.3734 2022/09/08 13:25:01 - mmengine - INFO - Epoch(train) [22][860/880] lr: 1.9195e-02 eta: 1:59:17 time: 0.4518 data_time: 0.0209 memory: 23498 grad_norm: 4.1213 top1_acc: 0.4167 top5_acc: 0.5417 loss_cls: 2.2879 loss: 2.2879 2022/09/08 13:25:10 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 13:25:10 - mmengine - INFO - Epoch(train) [22][880/880] lr: 1.9195e-02 eta: 1:59:08 time: 0.4380 data_time: 0.0172 memory: 23498 grad_norm: 4.0641 top1_acc: 0.4737 top5_acc: 0.8947 loss_cls: 2.2646 loss: 2.2646 2022/09/08 13:25:14 - mmengine - INFO - Epoch(val) [22][20/130] eta: 0:00:24 time: 0.2226 data_time: 0.0862 memory: 2693 2022/09/08 13:25:18 - mmengine - INFO - Epoch(val) [22][40/130] eta: 0:00:14 time: 0.1623 data_time: 0.0256 memory: 2693 2022/09/08 13:25:21 - mmengine - INFO - Epoch(val) [22][60/130] eta: 0:00:11 time: 0.1683 data_time: 0.0295 memory: 2693 2022/09/08 13:25:24 - mmengine - INFO - Epoch(val) [22][80/130] eta: 0:00:08 time: 0.1661 data_time: 0.0285 memory: 2693 2022/09/08 13:25:28 - mmengine - INFO - Epoch(val) [22][100/130] eta: 0:00:05 time: 0.1705 data_time: 0.0303 memory: 2693 2022/09/08 13:25:31 - mmengine - INFO - Epoch(val) [22][120/130] eta: 0:00:01 time: 0.1592 data_time: 0.0274 memory: 2693 2022/09/08 13:25:33 - mmengine - INFO - Epoch(val) [22][130/130] acc/top1: 0.4035 acc/top5: 0.7019 acc/mean1: 0.3283 2022/09/08 13:25:33 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4/best_acc/top1_epoch_20.pth is removed 2022/09/08 13:25:34 - mmengine - INFO - The best checkpoint with 0.4035 acc/top1 at 22 epoch is saved to best_acc/top1_epoch_22.pth. 2022/09/08 13:25:44 - mmengine - INFO - Epoch(train) [23][20/880] lr: 1.7589e-02 eta: 1:59:00 time: 0.4989 data_time: 0.0671 memory: 23498 grad_norm: 4.1496 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1093 loss: 2.1093 2022/09/08 13:25:53 - mmengine - INFO - Epoch(train) [23][40/880] lr: 1.7589e-02 eta: 1:58:50 time: 0.4494 data_time: 0.0214 memory: 23498 grad_norm: 4.2429 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.1951 loss: 2.1951 2022/09/08 13:26:02 - mmengine - INFO - Epoch(train) [23][60/880] lr: 1.7589e-02 eta: 1:58:41 time: 0.4530 data_time: 0.0210 memory: 23498 grad_norm: 4.1412 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 2.0571 loss: 2.0571 2022/09/08 13:26:11 - mmengine - INFO - Epoch(train) [23][80/880] lr: 1.7589e-02 eta: 1:58:32 time: 0.4540 data_time: 0.0207 memory: 23498 grad_norm: 4.1710 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 2.1913 loss: 2.1913 2022/09/08 13:26:20 - mmengine - INFO - Epoch(train) [23][100/880] lr: 1.7589e-02 eta: 1:58:23 time: 0.4532 data_time: 0.0244 memory: 23498 grad_norm: 4.1179 top1_acc: 0.5417 top5_acc: 0.9583 loss_cls: 2.0883 loss: 2.0883 2022/09/08 13:26:29 - mmengine - INFO - Epoch(train) [23][120/880] lr: 1.7589e-02 eta: 1:58:14 time: 0.4505 data_time: 0.0206 memory: 23498 grad_norm: 4.1408 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 2.0220 loss: 2.0220 2022/09/08 13:26:38 - mmengine - INFO - Epoch(train) [23][140/880] lr: 1.7589e-02 eta: 1:58:05 time: 0.4491 data_time: 0.0222 memory: 23498 grad_norm: 4.1452 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 2.1171 loss: 2.1171 2022/09/08 13:26:47 - mmengine - INFO - Epoch(train) [23][160/880] lr: 1.7589e-02 eta: 1:57:56 time: 0.4481 data_time: 0.0212 memory: 23498 grad_norm: 4.2145 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 2.0002 loss: 2.0002 2022/09/08 13:26:56 - mmengine - INFO - Epoch(train) [23][180/880] lr: 1.7589e-02 eta: 1:57:47 time: 0.4463 data_time: 0.0207 memory: 23498 grad_norm: 4.1842 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 2.0753 loss: 2.0753 2022/09/08 13:27:05 - mmengine - INFO - Epoch(train) [23][200/880] lr: 1.7589e-02 eta: 1:57:38 time: 0.4448 data_time: 0.0213 memory: 23498 grad_norm: 4.3403 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1460 loss: 2.1460 2022/09/08 13:27:14 - mmengine - INFO - Epoch(train) [23][220/880] lr: 1.7589e-02 eta: 1:57:29 time: 0.4532 data_time: 0.0213 memory: 23498 grad_norm: 4.3475 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 2.0879 loss: 2.0879 2022/09/08 13:27:23 - mmengine - INFO - Epoch(train) [23][240/880] lr: 1.7589e-02 eta: 1:57:20 time: 0.4544 data_time: 0.0199 memory: 23498 grad_norm: 4.3606 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.9471 loss: 1.9471 2022/09/08 13:27:32 - mmengine - INFO - Epoch(train) [23][260/880] lr: 1.7589e-02 eta: 1:57:11 time: 0.4509 data_time: 0.0224 memory: 23498 grad_norm: 4.3895 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.1932 loss: 2.1932 2022/09/08 13:27:41 - mmengine - INFO - Epoch(train) [23][280/880] lr: 1.7589e-02 eta: 1:57:02 time: 0.4466 data_time: 0.0238 memory: 23498 grad_norm: 4.3518 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 2.1330 loss: 2.1330 2022/09/08 13:27:50 - mmengine - INFO - Epoch(train) [23][300/880] lr: 1.7589e-02 eta: 1:56:53 time: 0.4493 data_time: 0.0224 memory: 23498 grad_norm: 4.4441 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.1906 loss: 2.1906 2022/09/08 13:27:59 - mmengine - INFO - Epoch(train) [23][320/880] lr: 1.7589e-02 eta: 1:56:44 time: 0.4475 data_time: 0.0216 memory: 23498 grad_norm: 4.3200 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2502 loss: 2.2502 2022/09/08 13:28:08 - mmengine - INFO - Epoch(train) [23][340/880] lr: 1.7589e-02 eta: 1:56:35 time: 0.4480 data_time: 0.0213 memory: 23498 grad_norm: 4.3561 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 2.0796 loss: 2.0796 2022/09/08 13:28:17 - mmengine - INFO - Epoch(train) [23][360/880] lr: 1.7589e-02 eta: 1:56:26 time: 0.4478 data_time: 0.0205 memory: 23498 grad_norm: 4.3610 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2480 loss: 2.2480 2022/09/08 13:28:26 - mmengine - INFO - Epoch(train) [23][380/880] lr: 1.7589e-02 eta: 1:56:17 time: 0.4471 data_time: 0.0221 memory: 23498 grad_norm: 4.3212 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.0892 loss: 2.0892 2022/09/08 13:28:35 - mmengine - INFO - Epoch(train) [23][400/880] lr: 1.7589e-02 eta: 1:56:08 time: 0.4526 data_time: 0.0209 memory: 23498 grad_norm: 4.0828 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 2.2472 loss: 2.2472 2022/09/08 13:28:44 - mmengine - INFO - Epoch(train) [23][420/880] lr: 1.7589e-02 eta: 1:55:59 time: 0.4505 data_time: 0.0221 memory: 23498 grad_norm: 4.1719 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.1580 loss: 2.1580 2022/09/08 13:28:53 - mmengine - INFO - Epoch(train) [23][440/880] lr: 1.7589e-02 eta: 1:55:49 time: 0.4476 data_time: 0.0203 memory: 23498 grad_norm: 4.1026 top1_acc: 0.5417 top5_acc: 0.6250 loss_cls: 2.0775 loss: 2.0775 2022/09/08 13:29:02 - mmengine - INFO - Epoch(train) [23][460/880] lr: 1.7589e-02 eta: 1:55:40 time: 0.4503 data_time: 0.0208 memory: 23498 grad_norm: 4.1801 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2487 loss: 2.2487 2022/09/08 13:29:11 - mmengine - INFO - Epoch(train) [23][480/880] lr: 1.7589e-02 eta: 1:55:31 time: 0.4487 data_time: 0.0220 memory: 23498 grad_norm: 4.2659 top1_acc: 0.2500 top5_acc: 0.4583 loss_cls: 2.2359 loss: 2.2359 2022/09/08 13:29:20 - mmengine - INFO - Epoch(train) [23][500/880] lr: 1.7589e-02 eta: 1:55:22 time: 0.4508 data_time: 0.0220 memory: 23498 grad_norm: 4.2245 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 2.2277 loss: 2.2277 2022/09/08 13:29:29 - mmengine - INFO - Epoch(train) [23][520/880] lr: 1.7589e-02 eta: 1:55:13 time: 0.4428 data_time: 0.0206 memory: 23498 grad_norm: 4.4189 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.2265 loss: 2.2265 2022/09/08 13:29:38 - mmengine - INFO - Epoch(train) [23][540/880] lr: 1.7589e-02 eta: 1:55:04 time: 0.4473 data_time: 0.0207 memory: 23498 grad_norm: 4.2875 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.1278 loss: 2.1278 2022/09/08 13:29:47 - mmengine - INFO - Epoch(train) [23][560/880] lr: 1.7589e-02 eta: 1:54:55 time: 0.4527 data_time: 0.0209 memory: 23498 grad_norm: 4.4452 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.1558 loss: 2.1558 2022/09/08 13:29:56 - mmengine - INFO - Epoch(train) [23][580/880] lr: 1.7589e-02 eta: 1:54:46 time: 0.4474 data_time: 0.0201 memory: 23498 grad_norm: 4.2154 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 2.2714 loss: 2.2714 2022/09/08 13:30:05 - mmengine - INFO - Epoch(train) [23][600/880] lr: 1.7589e-02 eta: 1:54:37 time: 0.4448 data_time: 0.0201 memory: 23498 grad_norm: 4.1708 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.2857 loss: 2.2857 2022/09/08 13:30:14 - mmengine - INFO - Epoch(train) [23][620/880] lr: 1.7589e-02 eta: 1:54:28 time: 0.4482 data_time: 0.0228 memory: 23498 grad_norm: 4.3587 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 2.0539 loss: 2.0539 2022/09/08 13:30:23 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 13:30:23 - mmengine - INFO - Epoch(train) [23][640/880] lr: 1.7589e-02 eta: 1:54:19 time: 0.4487 data_time: 0.0210 memory: 23498 grad_norm: 4.2786 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 2.1578 loss: 2.1578 2022/09/08 13:30:32 - mmengine - INFO - Epoch(train) [23][660/880] lr: 1.7589e-02 eta: 1:54:10 time: 0.4465 data_time: 0.0225 memory: 23498 grad_norm: 4.2873 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 1.9533 loss: 1.9533 2022/09/08 13:30:41 - mmengine - INFO - Epoch(train) [23][680/880] lr: 1.7589e-02 eta: 1:54:01 time: 0.4479 data_time: 0.0191 memory: 23498 grad_norm: 4.1753 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 2.1730 loss: 2.1730 2022/09/08 13:30:50 - mmengine - INFO - Epoch(train) [23][700/880] lr: 1.7589e-02 eta: 1:53:51 time: 0.4451 data_time: 0.0204 memory: 23498 grad_norm: 4.2780 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 2.2071 loss: 2.2071 2022/09/08 13:30:58 - mmengine - INFO - Epoch(train) [23][720/880] lr: 1.7589e-02 eta: 1:53:42 time: 0.4434 data_time: 0.0208 memory: 23498 grad_norm: 4.2048 top1_acc: 0.5417 top5_acc: 0.6667 loss_cls: 2.0782 loss: 2.0782 2022/09/08 13:31:07 - mmengine - INFO - Epoch(train) [23][740/880] lr: 1.7589e-02 eta: 1:53:33 time: 0.4453 data_time: 0.0234 memory: 23498 grad_norm: 4.2088 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 2.0046 loss: 2.0046 2022/09/08 13:31:16 - mmengine - INFO - Epoch(train) [23][760/880] lr: 1.7589e-02 eta: 1:53:24 time: 0.4471 data_time: 0.0199 memory: 23498 grad_norm: 4.2104 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 2.0130 loss: 2.0130 2022/09/08 13:31:25 - mmengine - INFO - Epoch(train) [23][780/880] lr: 1.7589e-02 eta: 1:53:15 time: 0.4495 data_time: 0.0234 memory: 23498 grad_norm: 4.3331 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.1156 loss: 2.1156 2022/09/08 13:31:34 - mmengine - INFO - Epoch(train) [23][800/880] lr: 1.7589e-02 eta: 1:53:06 time: 0.4457 data_time: 0.0215 memory: 23498 grad_norm: 4.4136 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 2.1051 loss: 2.1051 2022/09/08 13:31:43 - mmengine - INFO - Epoch(train) [23][820/880] lr: 1.7589e-02 eta: 1:52:57 time: 0.4459 data_time: 0.0247 memory: 23498 grad_norm: 4.3854 top1_acc: 0.3750 top5_acc: 0.5417 loss_cls: 2.1615 loss: 2.1615 2022/09/08 13:31:52 - mmengine - INFO - Epoch(train) [23][840/880] lr: 1.7589e-02 eta: 1:52:48 time: 0.4455 data_time: 0.0206 memory: 23498 grad_norm: 4.2102 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.0552 loss: 2.0552 2022/09/08 13:32:01 - mmengine - INFO - Epoch(train) [23][860/880] lr: 1.7589e-02 eta: 1:52:39 time: 0.4452 data_time: 0.0222 memory: 23498 grad_norm: 4.3449 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 2.0263 loss: 2.0263 2022/09/08 13:32:10 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 13:32:10 - mmengine - INFO - Epoch(train) [23][880/880] lr: 1.7589e-02 eta: 1:52:29 time: 0.4389 data_time: 0.0194 memory: 23498 grad_norm: 4.2662 top1_acc: 0.4211 top5_acc: 0.6842 loss_cls: 2.2214 loss: 2.2214 2022/09/08 13:32:20 - mmengine - INFO - Epoch(train) [24][20/880] lr: 1.5999e-02 eta: 1:52:21 time: 0.5164 data_time: 0.0776 memory: 23498 grad_norm: 4.1948 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 2.0262 loss: 2.0262 2022/09/08 13:32:29 - mmengine - INFO - Epoch(train) [24][40/880] lr: 1.5999e-02 eta: 1:52:12 time: 0.4509 data_time: 0.0287 memory: 23498 grad_norm: 4.2869 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0305 loss: 2.0305 2022/09/08 13:32:38 - mmengine - INFO - Epoch(train) [24][60/880] lr: 1.5999e-02 eta: 1:52:03 time: 0.4541 data_time: 0.0211 memory: 23498 grad_norm: 4.4183 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 2.0588 loss: 2.0588 2022/09/08 13:32:47 - mmengine - INFO - Epoch(train) [24][80/880] lr: 1.5999e-02 eta: 1:51:54 time: 0.4494 data_time: 0.0210 memory: 23498 grad_norm: 4.3843 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.9254 loss: 1.9254 2022/09/08 13:32:56 - mmengine - INFO - Epoch(train) [24][100/880] lr: 1.5999e-02 eta: 1:51:45 time: 0.4553 data_time: 0.0209 memory: 23498 grad_norm: 4.4081 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 2.0651 loss: 2.0651 2022/09/08 13:33:05 - mmengine - INFO - Epoch(train) [24][120/880] lr: 1.5999e-02 eta: 1:51:36 time: 0.4479 data_time: 0.0206 memory: 23498 grad_norm: 4.4912 top1_acc: 0.3333 top5_acc: 0.7500 loss_cls: 2.1220 loss: 2.1220 2022/09/08 13:33:14 - mmengine - INFO - Epoch(train) [24][140/880] lr: 1.5999e-02 eta: 1:51:27 time: 0.4548 data_time: 0.0209 memory: 23498 grad_norm: 4.4898 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 2.0285 loss: 2.0285 2022/09/08 13:33:23 - mmengine - INFO - Epoch(train) [24][160/880] lr: 1.5999e-02 eta: 1:51:18 time: 0.4494 data_time: 0.0195 memory: 23498 grad_norm: 4.4955 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 2.1551 loss: 2.1551 2022/09/08 13:33:33 - mmengine - INFO - Epoch(train) [24][180/880] lr: 1.5999e-02 eta: 1:51:09 time: 0.4682 data_time: 0.0214 memory: 23498 grad_norm: 4.3596 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 1.9785 loss: 1.9785 2022/09/08 13:33:42 - mmengine - INFO - Epoch(train) [24][200/880] lr: 1.5999e-02 eta: 1:51:00 time: 0.4532 data_time: 0.0212 memory: 23498 grad_norm: 4.5640 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.1557 loss: 2.1557 2022/09/08 13:33:51 - mmengine - INFO - Epoch(train) [24][220/880] lr: 1.5999e-02 eta: 1:50:51 time: 0.4576 data_time: 0.0239 memory: 23498 grad_norm: 4.4534 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0141 loss: 2.0141 2022/09/08 13:34:00 - mmengine - INFO - Epoch(train) [24][240/880] lr: 1.5999e-02 eta: 1:50:42 time: 0.4509 data_time: 0.0207 memory: 23498 grad_norm: 4.3570 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 2.0363 loss: 2.0363 2022/09/08 13:34:09 - mmengine - INFO - Epoch(train) [24][260/880] lr: 1.5999e-02 eta: 1:50:34 time: 0.4585 data_time: 0.0214 memory: 23498 grad_norm: 4.3077 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 2.1029 loss: 2.1029 2022/09/08 13:34:18 - mmengine - INFO - Epoch(train) [24][280/880] lr: 1.5999e-02 eta: 1:50:24 time: 0.4495 data_time: 0.0208 memory: 23498 grad_norm: 4.3859 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.9503 loss: 1.9503 2022/09/08 13:34:27 - mmengine - INFO - Epoch(train) [24][300/880] lr: 1.5999e-02 eta: 1:50:15 time: 0.4547 data_time: 0.0215 memory: 23498 grad_norm: 4.3823 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 2.0802 loss: 2.0802 2022/09/08 13:34:36 - mmengine - INFO - Epoch(train) [24][320/880] lr: 1.5999e-02 eta: 1:50:07 time: 0.4542 data_time: 0.0224 memory: 23498 grad_norm: 4.7133 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 2.1711 loss: 2.1711 2022/09/08 13:34:45 - mmengine - INFO - Epoch(train) [24][340/880] lr: 1.5999e-02 eta: 1:49:58 time: 0.4565 data_time: 0.0225 memory: 23498 grad_norm: 4.4830 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 1.9924 loss: 1.9924 2022/09/08 13:34:54 - mmengine - INFO - Epoch(train) [24][360/880] lr: 1.5999e-02 eta: 1:49:49 time: 0.4520 data_time: 0.0232 memory: 23498 grad_norm: 4.4067 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.0756 loss: 2.0756 2022/09/08 13:35:04 - mmengine - INFO - Epoch(train) [24][380/880] lr: 1.5999e-02 eta: 1:49:40 time: 0.4564 data_time: 0.0208 memory: 23498 grad_norm: 4.4457 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.9156 loss: 1.9156 2022/09/08 13:35:13 - mmengine - INFO - Epoch(train) [24][400/880] lr: 1.5999e-02 eta: 1:49:31 time: 0.4712 data_time: 0.0200 memory: 23498 grad_norm: 4.4206 top1_acc: 0.3750 top5_acc: 0.8333 loss_cls: 2.1586 loss: 2.1586 2022/09/08 13:35:22 - mmengine - INFO - Epoch(train) [24][420/880] lr: 1.5999e-02 eta: 1:49:22 time: 0.4612 data_time: 0.0252 memory: 23498 grad_norm: 4.5196 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.0879 loss: 2.0879 2022/09/08 13:35:32 - mmengine - INFO - Epoch(train) [24][440/880] lr: 1.5999e-02 eta: 1:49:13 time: 0.4673 data_time: 0.0210 memory: 23498 grad_norm: 4.4556 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9920 loss: 1.9920 2022/09/08 13:35:41 - mmengine - INFO - Epoch(train) [24][460/880] lr: 1.5999e-02 eta: 1:49:04 time: 0.4560 data_time: 0.0210 memory: 23498 grad_norm: 4.5399 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.9856 loss: 1.9856 2022/09/08 13:35:50 - mmengine - INFO - Epoch(train) [24][480/880] lr: 1.5999e-02 eta: 1:48:56 time: 0.4778 data_time: 0.0213 memory: 23498 grad_norm: 4.4930 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 2.1530 loss: 2.1530 2022/09/08 13:35:59 - mmengine - INFO - Epoch(train) [24][500/880] lr: 1.5999e-02 eta: 1:48:47 time: 0.4538 data_time: 0.0230 memory: 23498 grad_norm: 4.4563 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9474 loss: 1.9474 2022/09/08 13:36:08 - mmengine - INFO - Epoch(train) [24][520/880] lr: 1.5999e-02 eta: 1:48:37 time: 0.4471 data_time: 0.0200 memory: 23498 grad_norm: 4.5647 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 2.0002 loss: 2.0002 2022/09/08 13:36:17 - mmengine - INFO - Epoch(train) [24][540/880] lr: 1.5999e-02 eta: 1:48:28 time: 0.4517 data_time: 0.0212 memory: 23498 grad_norm: 4.6328 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.1313 loss: 2.1313 2022/09/08 13:36:26 - mmengine - INFO - Epoch(train) [24][560/880] lr: 1.5999e-02 eta: 1:48:19 time: 0.4456 data_time: 0.0204 memory: 23498 grad_norm: 4.5167 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.0095 loss: 2.0095 2022/09/08 13:36:35 - mmengine - INFO - Epoch(train) [24][580/880] lr: 1.5999e-02 eta: 1:48:10 time: 0.4503 data_time: 0.0219 memory: 23498 grad_norm: 4.6840 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 2.2034 loss: 2.2034 2022/09/08 13:36:44 - mmengine - INFO - Epoch(train) [24][600/880] lr: 1.5999e-02 eta: 1:48:01 time: 0.4494 data_time: 0.0198 memory: 23498 grad_norm: 4.4107 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.1860 loss: 2.1860 2022/09/08 13:36:53 - mmengine - INFO - Epoch(train) [24][620/880] lr: 1.5999e-02 eta: 1:47:52 time: 0.4559 data_time: 0.0209 memory: 23498 grad_norm: 4.6035 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.0636 loss: 2.0636 2022/09/08 13:37:02 - mmengine - INFO - Epoch(train) [24][640/880] lr: 1.5999e-02 eta: 1:47:43 time: 0.4552 data_time: 0.0205 memory: 23498 grad_norm: 4.5323 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.2998 loss: 2.2998 2022/09/08 13:37:12 - mmengine - INFO - Epoch(train) [24][660/880] lr: 1.5999e-02 eta: 1:47:34 time: 0.4541 data_time: 0.0210 memory: 23498 grad_norm: 4.4666 top1_acc: 0.3333 top5_acc: 0.7500 loss_cls: 2.0919 loss: 2.0919 2022/09/08 13:37:21 - mmengine - INFO - Epoch(train) [24][680/880] lr: 1.5999e-02 eta: 1:47:25 time: 0.4529 data_time: 0.0224 memory: 23498 grad_norm: 4.5211 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.1438 loss: 2.1438 2022/09/08 13:37:30 - mmengine - INFO - Epoch(train) [24][700/880] lr: 1.5999e-02 eta: 1:47:16 time: 0.4498 data_time: 0.0212 memory: 23498 grad_norm: 4.5918 top1_acc: 0.3750 top5_acc: 0.7917 loss_cls: 2.0607 loss: 2.0607 2022/09/08 13:37:39 - mmengine - INFO - Epoch(train) [24][720/880] lr: 1.5999e-02 eta: 1:47:07 time: 0.4477 data_time: 0.0202 memory: 23498 grad_norm: 4.5471 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.9953 loss: 1.9953 2022/09/08 13:37:48 - mmengine - INFO - Epoch(train) [24][740/880] lr: 1.5999e-02 eta: 1:46:58 time: 0.4566 data_time: 0.0215 memory: 23498 grad_norm: 4.5855 top1_acc: 0.2083 top5_acc: 0.8333 loss_cls: 2.1967 loss: 2.1967 2022/09/08 13:37:57 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 13:37:57 - mmengine - INFO - Epoch(train) [24][760/880] lr: 1.5999e-02 eta: 1:46:49 time: 0.4552 data_time: 0.0198 memory: 23498 grad_norm: 4.5861 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.2726 loss: 2.2726 2022/09/08 13:38:06 - mmengine - INFO - Epoch(train) [24][780/880] lr: 1.5999e-02 eta: 1:46:40 time: 0.4544 data_time: 0.0201 memory: 23498 grad_norm: 4.4706 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.1336 loss: 2.1336 2022/09/08 13:38:15 - mmengine - INFO - Epoch(train) [24][800/880] lr: 1.5999e-02 eta: 1:46:31 time: 0.4511 data_time: 0.0205 memory: 23498 grad_norm: 4.4721 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.0539 loss: 2.0539 2022/09/08 13:38:24 - mmengine - INFO - Epoch(train) [24][820/880] lr: 1.5999e-02 eta: 1:46:22 time: 0.4621 data_time: 0.0216 memory: 23498 grad_norm: 4.6709 top1_acc: 0.5417 top5_acc: 0.6667 loss_cls: 2.1728 loss: 2.1728 2022/09/08 13:38:33 - mmengine - INFO - Epoch(train) [24][840/880] lr: 1.5999e-02 eta: 1:46:13 time: 0.4496 data_time: 0.0210 memory: 23498 grad_norm: 4.6487 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 2.2121 loss: 2.2121 2022/09/08 13:38:42 - mmengine - INFO - Epoch(train) [24][860/880] lr: 1.5999e-02 eta: 1:46:04 time: 0.4509 data_time: 0.0208 memory: 23498 grad_norm: 4.5771 top1_acc: 0.3333 top5_acc: 0.6250 loss_cls: 2.2977 loss: 2.2977 2022/09/08 13:38:51 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 13:38:51 - mmengine - INFO - Epoch(train) [24][880/880] lr: 1.5999e-02 eta: 1:45:55 time: 0.4346 data_time: 0.0178 memory: 23498 grad_norm: 4.6328 top1_acc: 0.3684 top5_acc: 0.4737 loss_cls: 2.1804 loss: 2.1804 2022/09/08 13:38:55 - mmengine - INFO - Epoch(val) [24][20/130] eta: 0:00:24 time: 0.2234 data_time: 0.0864 memory: 2693 2022/09/08 13:38:59 - mmengine - INFO - Epoch(val) [24][40/130] eta: 0:00:14 time: 0.1628 data_time: 0.0259 memory: 2693 2022/09/08 13:39:02 - mmengine - INFO - Epoch(val) [24][60/130] eta: 0:00:12 time: 0.1788 data_time: 0.0413 memory: 2693 2022/09/08 13:39:05 - mmengine - INFO - Epoch(val) [24][80/130] eta: 0:00:08 time: 0.1637 data_time: 0.0280 memory: 2693 2022/09/08 13:39:09 - mmengine - INFO - Epoch(val) [24][100/130] eta: 0:00:05 time: 0.1781 data_time: 0.0356 memory: 2693 2022/09/08 13:39:12 - mmengine - INFO - Epoch(val) [24][120/130] eta: 0:00:01 time: 0.1582 data_time: 0.0253 memory: 2693 2022/09/08 13:39:14 - mmengine - INFO - Epoch(val) [24][130/130] acc/top1: 0.4273 acc/top5: 0.7302 acc/mean1: 0.3557 2022/09/08 13:39:14 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4/best_acc/top1_epoch_22.pth is removed 2022/09/08 13:39:16 - mmengine - INFO - The best checkpoint with 0.4273 acc/top1 at 24 epoch is saved to best_acc/top1_epoch_24.pth. 2022/09/08 13:39:25 - mmengine - INFO - Epoch(train) [25][20/880] lr: 1.4436e-02 eta: 1:45:46 time: 0.4903 data_time: 0.0695 memory: 23498 grad_norm: 4.3348 top1_acc: 0.5000 top5_acc: 0.5833 loss_cls: 2.0258 loss: 2.0258 2022/09/08 13:39:34 - mmengine - INFO - Epoch(train) [25][40/880] lr: 1.4436e-02 eta: 1:45:37 time: 0.4484 data_time: 0.0209 memory: 23498 grad_norm: 4.4404 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.8739 loss: 1.8739 2022/09/08 13:39:43 - mmengine - INFO - Epoch(train) [25][60/880] lr: 1.4436e-02 eta: 1:45:28 time: 0.4531 data_time: 0.0234 memory: 23498 grad_norm: 4.3888 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 1.8295 loss: 1.8295 2022/09/08 13:39:52 - mmengine - INFO - Epoch(train) [25][80/880] lr: 1.4436e-02 eta: 1:45:19 time: 0.4461 data_time: 0.0202 memory: 23498 grad_norm: 4.4522 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0201 loss: 2.0201 2022/09/08 13:40:01 - mmengine - INFO - Epoch(train) [25][100/880] lr: 1.4436e-02 eta: 1:45:10 time: 0.4511 data_time: 0.0205 memory: 23498 grad_norm: 4.4988 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.0614 loss: 2.0614 2022/09/08 13:40:11 - mmengine - INFO - Epoch(train) [25][120/880] lr: 1.4436e-02 eta: 1:45:02 time: 0.4802 data_time: 0.0242 memory: 23498 grad_norm: 4.5144 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.0764 loss: 2.0764 2022/09/08 13:40:20 - mmengine - INFO - Epoch(train) [25][140/880] lr: 1.4436e-02 eta: 1:44:53 time: 0.4510 data_time: 0.0179 memory: 23498 grad_norm: 4.4058 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 2.0487 loss: 2.0487 2022/09/08 13:40:29 - mmengine - INFO - Epoch(train) [25][160/880] lr: 1.4436e-02 eta: 1:44:43 time: 0.4462 data_time: 0.0230 memory: 23498 grad_norm: 4.6448 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2251 loss: 2.2251 2022/09/08 13:40:38 - mmengine - INFO - Epoch(train) [25][180/880] lr: 1.4436e-02 eta: 1:44:34 time: 0.4549 data_time: 0.0201 memory: 23498 grad_norm: 4.4664 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 2.1123 loss: 2.1123 2022/09/08 13:40:47 - mmengine - INFO - Epoch(train) [25][200/880] lr: 1.4436e-02 eta: 1:44:25 time: 0.4483 data_time: 0.0224 memory: 23498 grad_norm: 4.4123 top1_acc: 0.4583 top5_acc: 0.8750 loss_cls: 1.9484 loss: 1.9484 2022/09/08 13:40:56 - mmengine - INFO - Epoch(train) [25][220/880] lr: 1.4436e-02 eta: 1:44:16 time: 0.4501 data_time: 0.0207 memory: 23498 grad_norm: 4.4760 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.1257 loss: 2.1257 2022/09/08 13:41:05 - mmengine - INFO - Epoch(train) [25][240/880] lr: 1.4436e-02 eta: 1:44:07 time: 0.4500 data_time: 0.0251 memory: 23498 grad_norm: 4.4425 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.0627 loss: 2.0627 2022/09/08 13:41:14 - mmengine - INFO - Epoch(train) [25][260/880] lr: 1.4436e-02 eta: 1:43:58 time: 0.4570 data_time: 0.0207 memory: 23498 grad_norm: 4.6626 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9391 loss: 1.9391 2022/09/08 13:41:23 - mmengine - INFO - Epoch(train) [25][280/880] lr: 1.4436e-02 eta: 1:43:49 time: 0.4496 data_time: 0.0257 memory: 23498 grad_norm: 4.6855 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.9831 loss: 1.9831 2022/09/08 13:41:32 - mmengine - INFO - Epoch(train) [25][300/880] lr: 1.4436e-02 eta: 1:43:40 time: 0.4490 data_time: 0.0195 memory: 23498 grad_norm: 4.6220 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.0522 loss: 2.0522 2022/09/08 13:41:41 - mmengine - INFO - Epoch(train) [25][320/880] lr: 1.4436e-02 eta: 1:43:31 time: 0.4457 data_time: 0.0237 memory: 23498 grad_norm: 4.6053 top1_acc: 0.4583 top5_acc: 0.6250 loss_cls: 2.0714 loss: 2.0714 2022/09/08 13:41:50 - mmengine - INFO - Epoch(train) [25][340/880] lr: 1.4436e-02 eta: 1:43:22 time: 0.4522 data_time: 0.0215 memory: 23498 grad_norm: 4.6597 top1_acc: 0.2917 top5_acc: 0.5000 loss_cls: 2.0583 loss: 2.0583 2022/09/08 13:41:59 - mmengine - INFO - Epoch(train) [25][360/880] lr: 1.4436e-02 eta: 1:43:13 time: 0.4462 data_time: 0.0233 memory: 23498 grad_norm: 4.7866 top1_acc: 0.2083 top5_acc: 0.7083 loss_cls: 1.9940 loss: 1.9940 2022/09/08 13:42:08 - mmengine - INFO - Epoch(train) [25][380/880] lr: 1.4436e-02 eta: 1:43:04 time: 0.4476 data_time: 0.0186 memory: 23498 grad_norm: 4.4947 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0342 loss: 2.0342 2022/09/08 13:42:17 - mmengine - INFO - Epoch(train) [25][400/880] lr: 1.4436e-02 eta: 1:42:55 time: 0.4562 data_time: 0.0276 memory: 23498 grad_norm: 4.5771 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0611 loss: 2.0611 2022/09/08 13:42:26 - mmengine - INFO - Epoch(train) [25][420/880] lr: 1.4436e-02 eta: 1:42:46 time: 0.4437 data_time: 0.0192 memory: 23498 grad_norm: 4.5348 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 2.0772 loss: 2.0772 2022/09/08 13:42:35 - mmengine - INFO - Epoch(train) [25][440/880] lr: 1.4436e-02 eta: 1:42:37 time: 0.4446 data_time: 0.0229 memory: 23498 grad_norm: 4.6545 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.0385 loss: 2.0385 2022/09/08 13:42:44 - mmengine - INFO - Epoch(train) [25][460/880] lr: 1.4436e-02 eta: 1:42:28 time: 0.4464 data_time: 0.0212 memory: 23498 grad_norm: 4.6674 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 2.2609 loss: 2.2609 2022/09/08 13:42:53 - mmengine - INFO - Epoch(train) [25][480/880] lr: 1.4436e-02 eta: 1:42:19 time: 0.4534 data_time: 0.0230 memory: 23498 grad_norm: 4.5996 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.0902 loss: 2.0902 2022/09/08 13:43:02 - mmengine - INFO - Epoch(train) [25][500/880] lr: 1.4436e-02 eta: 1:42:10 time: 0.4531 data_time: 0.0213 memory: 23498 grad_norm: 4.5928 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9362 loss: 1.9362 2022/09/08 13:43:11 - mmengine - INFO - Epoch(train) [25][520/880] lr: 1.4436e-02 eta: 1:42:01 time: 0.4454 data_time: 0.0225 memory: 23498 grad_norm: 4.5666 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 1.9345 loss: 1.9345 2022/09/08 13:43:20 - mmengine - INFO - Epoch(train) [25][540/880] lr: 1.4436e-02 eta: 1:41:51 time: 0.4462 data_time: 0.0220 memory: 23498 grad_norm: 4.6142 top1_acc: 0.2917 top5_acc: 0.7083 loss_cls: 2.0653 loss: 2.0653 2022/09/08 13:43:29 - mmengine - INFO - Epoch(train) [25][560/880] lr: 1.4436e-02 eta: 1:41:42 time: 0.4455 data_time: 0.0229 memory: 23498 grad_norm: 4.6509 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0448 loss: 2.0448 2022/09/08 13:43:38 - mmengine - INFO - Epoch(train) [25][580/880] lr: 1.4436e-02 eta: 1:41:33 time: 0.4495 data_time: 0.0207 memory: 23498 grad_norm: 4.6474 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 2.1508 loss: 2.1508 2022/09/08 13:43:47 - mmengine - INFO - Epoch(train) [25][600/880] lr: 1.4436e-02 eta: 1:41:24 time: 0.4469 data_time: 0.0222 memory: 23498 grad_norm: 4.7422 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0856 loss: 2.0856 2022/09/08 13:43:56 - mmengine - INFO - Epoch(train) [25][620/880] lr: 1.4436e-02 eta: 1:41:15 time: 0.4616 data_time: 0.0218 memory: 23498 grad_norm: 4.8466 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0970 loss: 2.0970 2022/09/08 13:44:05 - mmengine - INFO - Epoch(train) [25][640/880] lr: 1.4436e-02 eta: 1:41:06 time: 0.4467 data_time: 0.0230 memory: 23498 grad_norm: 4.6393 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 2.0770 loss: 2.0770 2022/09/08 13:44:14 - mmengine - INFO - Epoch(train) [25][660/880] lr: 1.4436e-02 eta: 1:40:57 time: 0.4479 data_time: 0.0227 memory: 23498 grad_norm: 4.4202 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.0083 loss: 2.0083 2022/09/08 13:44:23 - mmengine - INFO - Epoch(train) [25][680/880] lr: 1.4436e-02 eta: 1:40:48 time: 0.4452 data_time: 0.0226 memory: 23498 grad_norm: 4.4906 top1_acc: 0.4167 top5_acc: 0.6250 loss_cls: 2.1473 loss: 2.1473 2022/09/08 13:44:32 - mmengine - INFO - Epoch(train) [25][700/880] lr: 1.4436e-02 eta: 1:40:39 time: 0.4595 data_time: 0.0220 memory: 23498 grad_norm: 4.4946 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 2.1134 loss: 2.1134 2022/09/08 13:44:41 - mmengine - INFO - Epoch(train) [25][720/880] lr: 1.4436e-02 eta: 1:40:30 time: 0.4450 data_time: 0.0219 memory: 23498 grad_norm: 4.5967 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0532 loss: 2.0532 2022/09/08 13:44:50 - mmengine - INFO - Epoch(train) [25][740/880] lr: 1.4436e-02 eta: 1:40:21 time: 0.4444 data_time: 0.0196 memory: 23498 grad_norm: 4.6655 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 2.0984 loss: 2.0984 2022/09/08 13:44:58 - mmengine - INFO - Epoch(train) [25][760/880] lr: 1.4436e-02 eta: 1:40:12 time: 0.4429 data_time: 0.0213 memory: 23498 grad_norm: 4.5239 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 1.9995 loss: 1.9995 2022/09/08 13:45:07 - mmengine - INFO - Epoch(train) [25][780/880] lr: 1.4436e-02 eta: 1:40:03 time: 0.4378 data_time: 0.0196 memory: 23498 grad_norm: 4.4435 top1_acc: 0.3750 top5_acc: 0.6667 loss_cls: 2.1072 loss: 2.1072 2022/09/08 13:45:16 - mmengine - INFO - Epoch(train) [25][800/880] lr: 1.4436e-02 eta: 1:39:53 time: 0.4408 data_time: 0.0228 memory: 23498 grad_norm: 4.4732 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0381 loss: 2.0381 2022/09/08 13:45:25 - mmengine - INFO - Epoch(train) [25][820/880] lr: 1.4436e-02 eta: 1:39:44 time: 0.4410 data_time: 0.0199 memory: 23498 grad_norm: 4.5503 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.0907 loss: 2.0907 2022/09/08 13:45:34 - mmengine - INFO - Epoch(train) [25][840/880] lr: 1.4436e-02 eta: 1:39:35 time: 0.4470 data_time: 0.0222 memory: 23498 grad_norm: 4.6056 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 2.1116 loss: 2.1116 2022/09/08 13:45:43 - mmengine - INFO - Epoch(train) [25][860/880] lr: 1.4436e-02 eta: 1:39:26 time: 0.4405 data_time: 0.0203 memory: 23498 grad_norm: 4.6312 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1378 loss: 2.1378 2022/09/08 13:45:51 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 13:45:51 - mmengine - INFO - Epoch(train) [25][880/880] lr: 1.4436e-02 eta: 1:39:17 time: 0.4390 data_time: 0.0206 memory: 23498 grad_norm: 4.6334 top1_acc: 0.4737 top5_acc: 0.6842 loss_cls: 2.1182 loss: 2.1182 2022/09/08 13:46:02 - mmengine - INFO - Epoch(train) [26][20/880] lr: 1.2908e-02 eta: 1:39:09 time: 0.5243 data_time: 0.0895 memory: 23498 grad_norm: 4.3417 top1_acc: 0.6667 top5_acc: 0.7500 loss_cls: 2.0386 loss: 2.0386 2022/09/08 13:46:11 - mmengine - INFO - Epoch(train) [26][40/880] lr: 1.2908e-02 eta: 1:39:00 time: 0.4568 data_time: 0.0244 memory: 23498 grad_norm: 4.4649 top1_acc: 0.3333 top5_acc: 0.7500 loss_cls: 1.9768 loss: 1.9768 2022/09/08 13:46:20 - mmengine - INFO - Epoch(train) [26][60/880] lr: 1.2908e-02 eta: 1:38:51 time: 0.4643 data_time: 0.0226 memory: 23498 grad_norm: 4.4725 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7706 loss: 1.7706 2022/09/08 13:46:29 - mmengine - INFO - Epoch(train) [26][80/880] lr: 1.2908e-02 eta: 1:38:42 time: 0.4564 data_time: 0.0245 memory: 23498 grad_norm: 4.4167 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.8295 loss: 1.8295 2022/09/08 13:46:39 - mmengine - INFO - Epoch(train) [26][100/880] lr: 1.2908e-02 eta: 1:38:33 time: 0.4591 data_time: 0.0246 memory: 23498 grad_norm: 4.4875 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.0407 loss: 2.0407 2022/09/08 13:46:48 - mmengine - INFO - Epoch(train) [26][120/880] lr: 1.2908e-02 eta: 1:38:24 time: 0.4507 data_time: 0.0208 memory: 23498 grad_norm: 4.7492 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.9343 loss: 1.9343 2022/09/08 13:46:57 - mmengine - INFO - Epoch(train) [26][140/880] lr: 1.2908e-02 eta: 1:38:15 time: 0.4573 data_time: 0.0241 memory: 23498 grad_norm: 4.5459 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.9459 loss: 1.9459 2022/09/08 13:47:06 - mmengine - INFO - Epoch(train) [26][160/880] lr: 1.2908e-02 eta: 1:38:06 time: 0.4507 data_time: 0.0207 memory: 23498 grad_norm: 4.5502 top1_acc: 0.5417 top5_acc: 0.6250 loss_cls: 1.9699 loss: 1.9699 2022/09/08 13:47:15 - mmengine - INFO - Epoch(train) [26][180/880] lr: 1.2908e-02 eta: 1:37:57 time: 0.4604 data_time: 0.0241 memory: 23498 grad_norm: 4.6518 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.9411 loss: 1.9411 2022/09/08 13:47:24 - mmengine - INFO - Epoch(train) [26][200/880] lr: 1.2908e-02 eta: 1:37:48 time: 0.4509 data_time: 0.0201 memory: 23498 grad_norm: 4.7901 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 1.9868 loss: 1.9868 2022/09/08 13:47:33 - mmengine - INFO - Epoch(train) [26][220/880] lr: 1.2908e-02 eta: 1:37:39 time: 0.4620 data_time: 0.0221 memory: 23498 grad_norm: 4.7610 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 2.0448 loss: 2.0448 2022/09/08 13:47:42 - mmengine - INFO - Epoch(train) [26][240/880] lr: 1.2908e-02 eta: 1:37:30 time: 0.4537 data_time: 0.0203 memory: 23498 grad_norm: 4.7177 top1_acc: 0.4167 top5_acc: 0.9167 loss_cls: 2.0414 loss: 2.0414 2022/09/08 13:47:52 - mmengine - INFO - Epoch(train) [26][260/880] lr: 1.2908e-02 eta: 1:37:21 time: 0.4606 data_time: 0.0234 memory: 23498 grad_norm: 4.8381 top1_acc: 0.7917 top5_acc: 0.8333 loss_cls: 1.8253 loss: 1.8253 2022/09/08 13:48:01 - mmengine - INFO - Epoch(train) [26][280/880] lr: 1.2908e-02 eta: 1:37:12 time: 0.4553 data_time: 0.0211 memory: 23498 grad_norm: 4.6534 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 2.0709 loss: 2.0709 2022/09/08 13:48:10 - mmengine - INFO - Epoch(train) [26][300/880] lr: 1.2908e-02 eta: 1:37:03 time: 0.4564 data_time: 0.0221 memory: 23498 grad_norm: 4.7330 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.7259 loss: 1.7259 2022/09/08 13:48:19 - mmengine - INFO - Epoch(train) [26][320/880] lr: 1.2908e-02 eta: 1:36:54 time: 0.4627 data_time: 0.0210 memory: 23498 grad_norm: 4.5831 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0556 loss: 2.0556 2022/09/08 13:48:28 - mmengine - INFO - Epoch(train) [26][340/880] lr: 1.2908e-02 eta: 1:36:45 time: 0.4675 data_time: 0.0273 memory: 23498 grad_norm: 4.7582 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.9625 loss: 1.9625 2022/09/08 13:48:37 - mmengine - INFO - Epoch(train) [26][360/880] lr: 1.2908e-02 eta: 1:36:36 time: 0.4516 data_time: 0.0200 memory: 23498 grad_norm: 4.8308 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 2.1065 loss: 2.1065 2022/09/08 13:48:47 - mmengine - INFO - Epoch(train) [26][380/880] lr: 1.2908e-02 eta: 1:36:27 time: 0.4578 data_time: 0.0215 memory: 23498 grad_norm: 4.5889 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 2.0594 loss: 2.0594 2022/09/08 13:48:56 - mmengine - INFO - Epoch(train) [26][400/880] lr: 1.2908e-02 eta: 1:36:18 time: 0.4541 data_time: 0.0190 memory: 23498 grad_norm: 4.7268 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.9623 loss: 1.9623 2022/09/08 13:49:05 - mmengine - INFO - Epoch(train) [26][420/880] lr: 1.2908e-02 eta: 1:36:09 time: 0.4550 data_time: 0.0237 memory: 23498 grad_norm: 4.7159 top1_acc: 0.4583 top5_acc: 0.5833 loss_cls: 2.0154 loss: 2.0154 2022/09/08 13:49:14 - mmengine - INFO - Epoch(train) [26][440/880] lr: 1.2908e-02 eta: 1:36:01 time: 0.4585 data_time: 0.0201 memory: 23498 grad_norm: 4.7879 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.1941 loss: 2.1941 2022/09/08 13:49:23 - mmengine - INFO - Epoch(train) [26][460/880] lr: 1.2908e-02 eta: 1:35:52 time: 0.4564 data_time: 0.0231 memory: 23498 grad_norm: 4.7089 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 2.0607 loss: 2.0607 2022/09/08 13:49:32 - mmengine - INFO - Epoch(train) [26][480/880] lr: 1.2908e-02 eta: 1:35:43 time: 0.4495 data_time: 0.0202 memory: 23498 grad_norm: 4.6634 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 1.7767 loss: 1.7767 2022/09/08 13:49:41 - mmengine - INFO - Epoch(train) [26][500/880] lr: 1.2908e-02 eta: 1:35:33 time: 0.4496 data_time: 0.0225 memory: 23498 grad_norm: 4.7542 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7969 loss: 1.7969 2022/09/08 13:49:50 - mmengine - INFO - Epoch(train) [26][520/880] lr: 1.2908e-02 eta: 1:35:24 time: 0.4491 data_time: 0.0207 memory: 23498 grad_norm: 4.7307 top1_acc: 0.2917 top5_acc: 0.5417 loss_cls: 1.9372 loss: 1.9372 2022/09/08 13:49:59 - mmengine - INFO - Epoch(train) [26][540/880] lr: 1.2908e-02 eta: 1:35:15 time: 0.4505 data_time: 0.0233 memory: 23498 grad_norm: 4.8390 top1_acc: 0.5833 top5_acc: 0.6667 loss_cls: 1.9083 loss: 1.9083 2022/09/08 13:50:08 - mmengine - INFO - Epoch(train) [26][560/880] lr: 1.2908e-02 eta: 1:35:06 time: 0.4551 data_time: 0.0205 memory: 23498 grad_norm: 4.5960 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 2.0783 loss: 2.0783 2022/09/08 13:50:17 - mmengine - INFO - Epoch(train) [26][580/880] lr: 1.2908e-02 eta: 1:34:57 time: 0.4555 data_time: 0.0239 memory: 23498 grad_norm: 4.6962 top1_acc: 0.3333 top5_acc: 0.5833 loss_cls: 2.0258 loss: 2.0258 2022/09/08 13:50:26 - mmengine - INFO - Epoch(train) [26][600/880] lr: 1.2908e-02 eta: 1:34:48 time: 0.4549 data_time: 0.0216 memory: 23498 grad_norm: 4.7079 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9997 loss: 1.9997 2022/09/08 13:50:36 - mmengine - INFO - Epoch(train) [26][620/880] lr: 1.2908e-02 eta: 1:34:39 time: 0.4546 data_time: 0.0240 memory: 23498 grad_norm: 4.6241 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.0126 loss: 2.0126 2022/09/08 13:50:45 - mmengine - INFO - Epoch(train) [26][640/880] lr: 1.2908e-02 eta: 1:34:30 time: 0.4552 data_time: 0.0199 memory: 23498 grad_norm: 4.7935 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.9266 loss: 1.9266 2022/09/08 13:50:54 - mmengine - INFO - Epoch(train) [26][660/880] lr: 1.2908e-02 eta: 1:34:22 time: 0.4680 data_time: 0.0228 memory: 23498 grad_norm: 4.5727 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 2.2440 loss: 2.2440 2022/09/08 13:51:03 - mmengine - INFO - Epoch(train) [26][680/880] lr: 1.2908e-02 eta: 1:34:13 time: 0.4549 data_time: 0.0242 memory: 23498 grad_norm: 4.7742 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 2.0935 loss: 2.0935 2022/09/08 13:51:12 - mmengine - INFO - Epoch(train) [26][700/880] lr: 1.2908e-02 eta: 1:34:04 time: 0.4525 data_time: 0.0247 memory: 23498 grad_norm: 4.9069 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 2.0873 loss: 2.0873 2022/09/08 13:51:21 - mmengine - INFO - Epoch(train) [26][720/880] lr: 1.2908e-02 eta: 1:33:55 time: 0.4505 data_time: 0.0192 memory: 23498 grad_norm: 4.7877 top1_acc: 0.4167 top5_acc: 0.8333 loss_cls: 1.9076 loss: 1.9076 2022/09/08 13:51:30 - mmengine - INFO - Epoch(train) [26][740/880] lr: 1.2908e-02 eta: 1:33:46 time: 0.4623 data_time: 0.0290 memory: 23498 grad_norm: 4.7649 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 1.9044 loss: 1.9044 2022/09/08 13:51:39 - mmengine - INFO - Epoch(train) [26][760/880] lr: 1.2908e-02 eta: 1:33:37 time: 0.4465 data_time: 0.0196 memory: 23498 grad_norm: 4.6320 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 2.0635 loss: 2.0635 2022/09/08 13:51:48 - mmengine - INFO - Epoch(train) [26][780/880] lr: 1.2908e-02 eta: 1:33:27 time: 0.4522 data_time: 0.0252 memory: 23498 grad_norm: 4.6008 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 2.0005 loss: 2.0005 2022/09/08 13:51:57 - mmengine - INFO - Epoch(train) [26][800/880] lr: 1.2908e-02 eta: 1:33:18 time: 0.4522 data_time: 0.0202 memory: 23498 grad_norm: 4.5625 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.9922 loss: 1.9922 2022/09/08 13:52:06 - mmengine - INFO - Epoch(train) [26][820/880] lr: 1.2908e-02 eta: 1:33:09 time: 0.4526 data_time: 0.0230 memory: 23498 grad_norm: 4.5621 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 1.8390 loss: 1.8390 2022/09/08 13:52:16 - mmengine - INFO - Epoch(train) [26][840/880] lr: 1.2908e-02 eta: 1:33:00 time: 0.4515 data_time: 0.0201 memory: 23498 grad_norm: 4.6144 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.8900 loss: 1.8900 2022/09/08 13:52:25 - mmengine - INFO - Epoch(train) [26][860/880] lr: 1.2908e-02 eta: 1:32:51 time: 0.4506 data_time: 0.0228 memory: 23498 grad_norm: 4.7087 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1530 loss: 2.1530 2022/09/08 13:52:33 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 13:52:33 - mmengine - INFO - Epoch(train) [26][880/880] lr: 1.2908e-02 eta: 1:32:42 time: 0.4376 data_time: 0.0176 memory: 23498 grad_norm: 4.6479 top1_acc: 0.3684 top5_acc: 0.5789 loss_cls: 2.0143 loss: 2.0143 2022/09/08 13:52:38 - mmengine - INFO - Epoch(val) [26][20/130] eta: 0:00:23 time: 0.2174 data_time: 0.0795 memory: 2693 2022/09/08 13:52:41 - mmengine - INFO - Epoch(val) [26][40/130] eta: 0:00:14 time: 0.1583 data_time: 0.0246 memory: 2693 2022/09/08 13:52:44 - mmengine - INFO - Epoch(val) [26][60/130] eta: 0:00:12 time: 0.1775 data_time: 0.0413 memory: 2693 2022/09/08 13:52:48 - mmengine - INFO - Epoch(val) [26][80/130] eta: 0:00:08 time: 0.1628 data_time: 0.0261 memory: 2693 2022/09/08 13:52:51 - mmengine - INFO - Epoch(val) [26][100/130] eta: 0:00:04 time: 0.1630 data_time: 0.0272 memory: 2693 2022/09/08 13:52:54 - mmengine - INFO - Epoch(val) [26][120/130] eta: 0:00:01 time: 0.1599 data_time: 0.0255 memory: 2693 2022/09/08 13:52:56 - mmengine - INFO - Epoch(val) [26][130/130] acc/top1: 0.4330 acc/top5: 0.7248 acc/mean1: 0.3626 2022/09/08 13:52:56 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4/best_acc/top1_epoch_24.pth is removed 2022/09/08 13:52:58 - mmengine - INFO - The best checkpoint with 0.4330 acc/top1 at 26 epoch is saved to best_acc/top1_epoch_26.pth. 2022/09/08 13:53:08 - mmengine - INFO - Epoch(train) [27][20/880] lr: 1.1426e-02 eta: 1:32:34 time: 0.4916 data_time: 0.0660 memory: 23498 grad_norm: 4.6046 top1_acc: 0.6667 top5_acc: 0.7083 loss_cls: 2.1604 loss: 2.1604 2022/09/08 13:53:16 - mmengine - INFO - Epoch(train) [27][40/880] lr: 1.1426e-02 eta: 1:32:24 time: 0.4457 data_time: 0.0227 memory: 23498 grad_norm: 4.6435 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0133 loss: 2.0133 2022/09/08 13:53:25 - mmengine - INFO - Epoch(train) [27][60/880] lr: 1.1426e-02 eta: 1:32:15 time: 0.4477 data_time: 0.0216 memory: 23498 grad_norm: 4.5348 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.7811 loss: 1.7811 2022/09/08 13:53:35 - mmengine - INFO - Epoch(train) [27][80/880] lr: 1.1426e-02 eta: 1:32:07 time: 0.4618 data_time: 0.0229 memory: 23498 grad_norm: 4.7104 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 1.8229 loss: 1.8229 2022/09/08 13:53:44 - mmengine - INFO - Epoch(train) [27][100/880] lr: 1.1426e-02 eta: 1:31:57 time: 0.4525 data_time: 0.0212 memory: 23498 grad_norm: 4.6928 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.8901 loss: 1.8901 2022/09/08 13:53:53 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 13:53:53 - mmengine - INFO - Epoch(train) [27][120/880] lr: 1.1426e-02 eta: 1:31:48 time: 0.4454 data_time: 0.0226 memory: 23498 grad_norm: 4.7371 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.7467 loss: 1.7467 2022/09/08 13:54:02 - mmengine - INFO - Epoch(train) [27][140/880] lr: 1.1426e-02 eta: 1:31:39 time: 0.4495 data_time: 0.0191 memory: 23498 grad_norm: 4.7416 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.7737 loss: 1.7737 2022/09/08 13:54:11 - mmengine - INFO - Epoch(train) [27][160/880] lr: 1.1426e-02 eta: 1:31:30 time: 0.4459 data_time: 0.0202 memory: 23498 grad_norm: 4.7921 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.9516 loss: 1.9516 2022/09/08 13:54:19 - mmengine - INFO - Epoch(train) [27][180/880] lr: 1.1426e-02 eta: 1:31:21 time: 0.4453 data_time: 0.0222 memory: 23498 grad_norm: 4.8636 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 2.0872 loss: 2.0872 2022/09/08 13:54:28 - mmengine - INFO - Epoch(train) [27][200/880] lr: 1.1426e-02 eta: 1:31:12 time: 0.4395 data_time: 0.0201 memory: 23498 grad_norm: 4.7591 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 2.0666 loss: 2.0666 2022/09/08 13:54:37 - mmengine - INFO - Epoch(train) [27][220/880] lr: 1.1426e-02 eta: 1:31:03 time: 0.4495 data_time: 0.0230 memory: 23498 grad_norm: 4.6841 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.8898 loss: 1.8898 2022/09/08 13:54:46 - mmengine - INFO - Epoch(train) [27][240/880] lr: 1.1426e-02 eta: 1:30:54 time: 0.4430 data_time: 0.0203 memory: 23498 grad_norm: 4.7310 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.9993 loss: 1.9993 2022/09/08 13:54:55 - mmengine - INFO - Epoch(train) [27][260/880] lr: 1.1426e-02 eta: 1:30:45 time: 0.4439 data_time: 0.0234 memory: 23498 grad_norm: 4.8200 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 1.8987 loss: 1.8987 2022/09/08 13:55:04 - mmengine - INFO - Epoch(train) [27][280/880] lr: 1.1426e-02 eta: 1:30:36 time: 0.4427 data_time: 0.0224 memory: 23498 grad_norm: 4.7280 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.8977 loss: 1.8977 2022/09/08 13:55:13 - mmengine - INFO - Epoch(train) [27][300/880] lr: 1.1426e-02 eta: 1:30:27 time: 0.4608 data_time: 0.0221 memory: 23498 grad_norm: 4.7265 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 1.8012 loss: 1.8012 2022/09/08 13:55:22 - mmengine - INFO - Epoch(train) [27][320/880] lr: 1.1426e-02 eta: 1:30:18 time: 0.4462 data_time: 0.0215 memory: 23498 grad_norm: 4.6759 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 1.9255 loss: 1.9255 2022/09/08 13:55:31 - mmengine - INFO - Epoch(train) [27][340/880] lr: 1.1426e-02 eta: 1:30:08 time: 0.4422 data_time: 0.0202 memory: 23498 grad_norm: 4.7388 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.8776 loss: 1.8776 2022/09/08 13:55:40 - mmengine - INFO - Epoch(train) [27][360/880] lr: 1.1426e-02 eta: 1:29:59 time: 0.4449 data_time: 0.0217 memory: 23498 grad_norm: 4.6751 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7931 loss: 1.7931 2022/09/08 13:55:49 - mmengine - INFO - Epoch(train) [27][380/880] lr: 1.1426e-02 eta: 1:29:50 time: 0.4397 data_time: 0.0196 memory: 23498 grad_norm: 4.7692 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.7810 loss: 1.7810 2022/09/08 13:55:57 - mmengine - INFO - Epoch(train) [27][400/880] lr: 1.1426e-02 eta: 1:29:41 time: 0.4472 data_time: 0.0218 memory: 23498 grad_norm: 4.9192 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 1.9296 loss: 1.9296 2022/09/08 13:56:06 - mmengine - INFO - Epoch(train) [27][420/880] lr: 1.1426e-02 eta: 1:29:32 time: 0.4396 data_time: 0.0194 memory: 23498 grad_norm: 4.7957 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.9814 loss: 1.9814 2022/09/08 13:56:15 - mmengine - INFO - Epoch(train) [27][440/880] lr: 1.1426e-02 eta: 1:29:23 time: 0.4501 data_time: 0.0212 memory: 23498 grad_norm: 4.6761 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 1.8686 loss: 1.8686 2022/09/08 13:56:24 - mmengine - INFO - Epoch(train) [27][460/880] lr: 1.1426e-02 eta: 1:29:14 time: 0.4419 data_time: 0.0200 memory: 23498 grad_norm: 4.8095 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8045 loss: 1.8045 2022/09/08 13:56:33 - mmengine - INFO - Epoch(train) [27][480/880] lr: 1.1426e-02 eta: 1:29:05 time: 0.4447 data_time: 0.0199 memory: 23498 grad_norm: 5.0231 top1_acc: 0.5000 top5_acc: 0.5833 loss_cls: 1.9352 loss: 1.9352 2022/09/08 13:56:42 - mmengine - INFO - Epoch(train) [27][500/880] lr: 1.1426e-02 eta: 1:28:56 time: 0.4494 data_time: 0.0303 memory: 23498 grad_norm: 4.7438 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.8850 loss: 1.8850 2022/09/08 13:56:51 - mmengine - INFO - Epoch(train) [27][520/880] lr: 1.1426e-02 eta: 1:28:47 time: 0.4428 data_time: 0.0233 memory: 23498 grad_norm: 4.9221 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 1.8277 loss: 1.8277 2022/09/08 13:57:00 - mmengine - INFO - Epoch(train) [27][540/880] lr: 1.1426e-02 eta: 1:28:37 time: 0.4432 data_time: 0.0219 memory: 23498 grad_norm: 4.8286 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.7199 loss: 1.7199 2022/09/08 13:57:09 - mmengine - INFO - Epoch(train) [27][560/880] lr: 1.1426e-02 eta: 1:28:28 time: 0.4437 data_time: 0.0218 memory: 23498 grad_norm: 4.7205 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.9068 loss: 1.9068 2022/09/08 13:57:17 - mmengine - INFO - Epoch(train) [27][580/880] lr: 1.1426e-02 eta: 1:28:19 time: 0.4434 data_time: 0.0224 memory: 23498 grad_norm: 4.8403 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.8432 loss: 1.8432 2022/09/08 13:57:26 - mmengine - INFO - Epoch(train) [27][600/880] lr: 1.1426e-02 eta: 1:28:10 time: 0.4446 data_time: 0.0201 memory: 23498 grad_norm: 4.7444 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.8591 loss: 1.8591 2022/09/08 13:57:35 - mmengine - INFO - Epoch(train) [27][620/880] lr: 1.1426e-02 eta: 1:28:01 time: 0.4433 data_time: 0.0242 memory: 23498 grad_norm: 4.7472 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.9236 loss: 1.9236 2022/09/08 13:57:44 - mmengine - INFO - Epoch(train) [27][640/880] lr: 1.1426e-02 eta: 1:27:52 time: 0.4455 data_time: 0.0214 memory: 23498 grad_norm: 4.7922 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.9043 loss: 1.9043 2022/09/08 13:57:53 - mmengine - INFO - Epoch(train) [27][660/880] lr: 1.1426e-02 eta: 1:27:43 time: 0.4485 data_time: 0.0230 memory: 23498 grad_norm: 4.9423 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0486 loss: 2.0486 2022/09/08 13:58:02 - mmengine - INFO - Epoch(train) [27][680/880] lr: 1.1426e-02 eta: 1:27:34 time: 0.4441 data_time: 0.0198 memory: 23498 grad_norm: 4.9192 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.9991 loss: 1.9991 2022/09/08 13:58:11 - mmengine - INFO - Epoch(train) [27][700/880] lr: 1.1426e-02 eta: 1:27:25 time: 0.4447 data_time: 0.0223 memory: 23498 grad_norm: 4.8853 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.9171 loss: 1.9171 2022/09/08 13:58:20 - mmengine - INFO - Epoch(train) [27][720/880] lr: 1.1426e-02 eta: 1:27:16 time: 0.4616 data_time: 0.0215 memory: 23498 grad_norm: 4.9033 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8482 loss: 1.8482 2022/09/08 13:58:29 - mmengine - INFO - Epoch(train) [27][740/880] lr: 1.1426e-02 eta: 1:27:07 time: 0.4388 data_time: 0.0218 memory: 23498 grad_norm: 4.9334 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 1.8610 loss: 1.8610 2022/09/08 13:58:38 - mmengine - INFO - Epoch(train) [27][760/880] lr: 1.1426e-02 eta: 1:26:58 time: 0.4685 data_time: 0.0272 memory: 23498 grad_norm: 4.9761 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.9283 loss: 1.9283 2022/09/08 13:58:47 - mmengine - INFO - Epoch(train) [27][780/880] lr: 1.1426e-02 eta: 1:26:49 time: 0.4396 data_time: 0.0207 memory: 23498 grad_norm: 4.8555 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.8970 loss: 1.8970 2022/09/08 13:58:56 - mmengine - INFO - Epoch(train) [27][800/880] lr: 1.1426e-02 eta: 1:26:40 time: 0.4463 data_time: 0.0293 memory: 23498 grad_norm: 4.6951 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.8684 loss: 1.8684 2022/09/08 13:59:05 - mmengine - INFO - Epoch(train) [27][820/880] lr: 1.1426e-02 eta: 1:26:30 time: 0.4407 data_time: 0.0227 memory: 23498 grad_norm: 4.7369 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.9791 loss: 1.9791 2022/09/08 13:59:14 - mmengine - INFO - Epoch(train) [27][840/880] lr: 1.1426e-02 eta: 1:26:21 time: 0.4427 data_time: 0.0226 memory: 23498 grad_norm: 4.8484 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7674 loss: 1.7674 2022/09/08 13:59:22 - mmengine - INFO - Epoch(train) [27][860/880] lr: 1.1426e-02 eta: 1:26:12 time: 0.4379 data_time: 0.0221 memory: 23498 grad_norm: 5.1194 top1_acc: 0.4167 top5_acc: 0.7083 loss_cls: 1.9929 loss: 1.9929 2022/09/08 13:59:31 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 13:59:31 - mmengine - INFO - Epoch(train) [27][880/880] lr: 1.1426e-02 eta: 1:26:03 time: 0.4279 data_time: 0.0177 memory: 23498 grad_norm: 5.1609 top1_acc: 0.4211 top5_acc: 0.7895 loss_cls: 2.0121 loss: 2.0121 2022/09/08 13:59:41 - mmengine - INFO - Epoch(train) [28][20/880] lr: 1.0000e-02 eta: 1:25:54 time: 0.5135 data_time: 0.0820 memory: 23498 grad_norm: 4.7525 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.8760 loss: 1.8760 2022/09/08 13:59:50 - mmengine - INFO - Epoch(train) [28][40/880] lr: 1.0000e-02 eta: 1:25:45 time: 0.4492 data_time: 0.0240 memory: 23498 grad_norm: 4.8582 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.7302 loss: 1.7302 2022/09/08 13:59:59 - mmengine - INFO - Epoch(train) [28][60/880] lr: 1.0000e-02 eta: 1:25:36 time: 0.4570 data_time: 0.0206 memory: 23498 grad_norm: 5.0236 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.8940 loss: 1.8940 2022/09/08 14:00:08 - mmengine - INFO - Epoch(train) [28][80/880] lr: 1.0000e-02 eta: 1:25:27 time: 0.4514 data_time: 0.0213 memory: 23498 grad_norm: 5.0519 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 1.9121 loss: 1.9121 2022/09/08 14:00:18 - mmengine - INFO - Epoch(train) [28][100/880] lr: 1.0000e-02 eta: 1:25:18 time: 0.4550 data_time: 0.0208 memory: 23498 grad_norm: 5.0273 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.8101 loss: 1.8101 2022/09/08 14:00:26 - mmengine - INFO - Epoch(train) [28][120/880] lr: 1.0000e-02 eta: 1:25:09 time: 0.4476 data_time: 0.0220 memory: 23498 grad_norm: 4.9478 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.7356 loss: 1.7356 2022/09/08 14:00:36 - mmengine - INFO - Epoch(train) [28][140/880] lr: 1.0000e-02 eta: 1:25:01 time: 0.4776 data_time: 0.0183 memory: 23498 grad_norm: 4.9676 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.8881 loss: 1.8881 2022/09/08 14:00:45 - mmengine - INFO - Epoch(train) [28][160/880] lr: 1.0000e-02 eta: 1:24:51 time: 0.4477 data_time: 0.0238 memory: 23498 grad_norm: 4.9109 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.8213 loss: 1.8213 2022/09/08 14:00:54 - mmengine - INFO - Epoch(train) [28][180/880] lr: 1.0000e-02 eta: 1:24:42 time: 0.4513 data_time: 0.0231 memory: 23498 grad_norm: 5.0208 top1_acc: 0.6250 top5_acc: 0.6667 loss_cls: 1.9601 loss: 1.9601 2022/09/08 14:01:03 - mmengine - INFO - Epoch(train) [28][200/880] lr: 1.0000e-02 eta: 1:24:33 time: 0.4459 data_time: 0.0227 memory: 23498 grad_norm: 4.9768 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6578 loss: 1.6578 2022/09/08 14:01:12 - mmengine - INFO - Epoch(train) [28][220/880] lr: 1.0000e-02 eta: 1:24:24 time: 0.4480 data_time: 0.0203 memory: 23498 grad_norm: 4.9359 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.6213 loss: 1.6213 2022/09/08 14:01:21 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 14:01:21 - mmengine - INFO - Epoch(train) [28][240/880] lr: 1.0000e-02 eta: 1:24:15 time: 0.4497 data_time: 0.0212 memory: 23498 grad_norm: 4.9392 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 1.7596 loss: 1.7596 2022/09/08 14:01:30 - mmengine - INFO - Epoch(train) [28][260/880] lr: 1.0000e-02 eta: 1:24:06 time: 0.4462 data_time: 0.0224 memory: 23498 grad_norm: 4.9218 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9096 loss: 1.9096 2022/09/08 14:01:39 - mmengine - INFO - Epoch(train) [28][280/880] lr: 1.0000e-02 eta: 1:23:57 time: 0.4513 data_time: 0.0207 memory: 23498 grad_norm: 4.9678 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.7822 loss: 1.7822 2022/09/08 14:01:48 - mmengine - INFO - Epoch(train) [28][300/880] lr: 1.0000e-02 eta: 1:23:48 time: 0.4494 data_time: 0.0206 memory: 23498 grad_norm: 4.8971 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.8522 loss: 1.8522 2022/09/08 14:01:57 - mmengine - INFO - Epoch(train) [28][320/880] lr: 1.0000e-02 eta: 1:23:39 time: 0.4469 data_time: 0.0235 memory: 23498 grad_norm: 4.9212 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.8936 loss: 1.8936 2022/09/08 14:02:06 - mmengine - INFO - Epoch(train) [28][340/880] lr: 1.0000e-02 eta: 1:23:30 time: 0.4458 data_time: 0.0202 memory: 23498 grad_norm: 4.9593 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8201 loss: 1.8201 2022/09/08 14:02:15 - mmengine - INFO - Epoch(train) [28][360/880] lr: 1.0000e-02 eta: 1:23:21 time: 0.4451 data_time: 0.0227 memory: 23498 grad_norm: 4.9127 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.9485 loss: 1.9485 2022/09/08 14:02:24 - mmengine - INFO - Epoch(train) [28][380/880] lr: 1.0000e-02 eta: 1:23:12 time: 0.4463 data_time: 0.0213 memory: 23498 grad_norm: 4.8883 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.8609 loss: 1.8609 2022/09/08 14:02:33 - mmengine - INFO - Epoch(train) [28][400/880] lr: 1.0000e-02 eta: 1:23:03 time: 0.4486 data_time: 0.0218 memory: 23498 grad_norm: 4.9992 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.8954 loss: 1.8954 2022/09/08 14:02:41 - mmengine - INFO - Epoch(train) [28][420/880] lr: 1.0000e-02 eta: 1:22:54 time: 0.4467 data_time: 0.0241 memory: 23498 grad_norm: 5.0436 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.7709 loss: 1.7709 2022/09/08 14:02:50 - mmengine - INFO - Epoch(train) [28][440/880] lr: 1.0000e-02 eta: 1:22:45 time: 0.4461 data_time: 0.0209 memory: 23498 grad_norm: 4.9597 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.8112 loss: 1.8112 2022/09/08 14:02:59 - mmengine - INFO - Epoch(train) [28][460/880] lr: 1.0000e-02 eta: 1:22:36 time: 0.4488 data_time: 0.0201 memory: 23498 grad_norm: 4.9900 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 2.0274 loss: 2.0274 2022/09/08 14:03:09 - mmengine - INFO - Epoch(train) [28][480/880] lr: 1.0000e-02 eta: 1:22:27 time: 0.4602 data_time: 0.0226 memory: 23498 grad_norm: 4.8778 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7476 loss: 1.7476 2022/09/08 14:03:18 - mmengine - INFO - Epoch(train) [28][500/880] lr: 1.0000e-02 eta: 1:22:18 time: 0.4580 data_time: 0.0215 memory: 23498 grad_norm: 4.9841 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0515 loss: 2.0515 2022/09/08 14:03:27 - mmengine - INFO - Epoch(train) [28][520/880] lr: 1.0000e-02 eta: 1:22:09 time: 0.4467 data_time: 0.0232 memory: 23498 grad_norm: 4.8788 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.7338 loss: 1.7338 2022/09/08 14:03:36 - mmengine - INFO - Epoch(train) [28][540/880] lr: 1.0000e-02 eta: 1:21:59 time: 0.4465 data_time: 0.0209 memory: 23498 grad_norm: 4.8201 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.5903 loss: 1.5903 2022/09/08 14:03:44 - mmengine - INFO - Epoch(train) [28][560/880] lr: 1.0000e-02 eta: 1:21:50 time: 0.4444 data_time: 0.0192 memory: 23498 grad_norm: 5.0791 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9425 loss: 1.9425 2022/09/08 14:03:53 - mmengine - INFO - Epoch(train) [28][580/880] lr: 1.0000e-02 eta: 1:21:41 time: 0.4432 data_time: 0.0203 memory: 23498 grad_norm: 4.8044 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9584 loss: 1.9584 2022/09/08 14:04:02 - mmengine - INFO - Epoch(train) [28][600/880] lr: 1.0000e-02 eta: 1:21:32 time: 0.4575 data_time: 0.0247 memory: 23498 grad_norm: 4.9712 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8088 loss: 1.8088 2022/09/08 14:04:11 - mmengine - INFO - Epoch(train) [28][620/880] lr: 1.0000e-02 eta: 1:21:23 time: 0.4445 data_time: 0.0215 memory: 23498 grad_norm: 4.9595 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.7526 loss: 1.7526 2022/09/08 14:04:20 - mmengine - INFO - Epoch(train) [28][640/880] lr: 1.0000e-02 eta: 1:21:14 time: 0.4485 data_time: 0.0256 memory: 23498 grad_norm: 5.0082 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8725 loss: 1.8725 2022/09/08 14:04:29 - mmengine - INFO - Epoch(train) [28][660/880] lr: 1.0000e-02 eta: 1:21:05 time: 0.4435 data_time: 0.0195 memory: 23498 grad_norm: 4.9244 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.8014 loss: 1.8014 2022/09/08 14:04:38 - mmengine - INFO - Epoch(train) [28][680/880] lr: 1.0000e-02 eta: 1:20:56 time: 0.4406 data_time: 0.0204 memory: 23498 grad_norm: 5.0067 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.7055 loss: 1.7055 2022/09/08 14:04:47 - mmengine - INFO - Epoch(train) [28][700/880] lr: 1.0000e-02 eta: 1:20:47 time: 0.4414 data_time: 0.0191 memory: 23498 grad_norm: 5.0470 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8832 loss: 1.8832 2022/09/08 14:04:56 - mmengine - INFO - Epoch(train) [28][720/880] lr: 1.0000e-02 eta: 1:20:38 time: 0.4438 data_time: 0.0216 memory: 23498 grad_norm: 5.1733 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.7382 loss: 1.7382 2022/09/08 14:05:05 - mmengine - INFO - Epoch(train) [28][740/880] lr: 1.0000e-02 eta: 1:20:29 time: 0.4459 data_time: 0.0194 memory: 23498 grad_norm: 5.0059 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.7560 loss: 1.7560 2022/09/08 14:05:14 - mmengine - INFO - Epoch(train) [28][760/880] lr: 1.0000e-02 eta: 1:20:20 time: 0.4471 data_time: 0.0219 memory: 23498 grad_norm: 4.9939 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 1.8384 loss: 1.8384 2022/09/08 14:05:22 - mmengine - INFO - Epoch(train) [28][780/880] lr: 1.0000e-02 eta: 1:20:11 time: 0.4419 data_time: 0.0210 memory: 23498 grad_norm: 5.1634 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 1.9332 loss: 1.9332 2022/09/08 14:05:31 - mmengine - INFO - Epoch(train) [28][800/880] lr: 1.0000e-02 eta: 1:20:01 time: 0.4445 data_time: 0.0216 memory: 23498 grad_norm: 5.1124 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8301 loss: 1.8301 2022/09/08 14:05:40 - mmengine - INFO - Epoch(train) [28][820/880] lr: 1.0000e-02 eta: 1:19:52 time: 0.4427 data_time: 0.0224 memory: 23498 grad_norm: 5.0240 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8712 loss: 1.8712 2022/09/08 14:05:49 - mmengine - INFO - Epoch(train) [28][840/880] lr: 1.0000e-02 eta: 1:19:43 time: 0.4425 data_time: 0.0211 memory: 23498 grad_norm: 5.0708 top1_acc: 0.3333 top5_acc: 0.7083 loss_cls: 1.9684 loss: 1.9684 2022/09/08 14:05:58 - mmengine - INFO - Epoch(train) [28][860/880] lr: 1.0000e-02 eta: 1:19:34 time: 0.4425 data_time: 0.0210 memory: 23498 grad_norm: 5.0082 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.7899 loss: 1.7899 2022/09/08 14:06:07 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 14:06:07 - mmengine - INFO - Epoch(train) [28][880/880] lr: 1.0000e-02 eta: 1:19:25 time: 0.4322 data_time: 0.0202 memory: 23498 grad_norm: 5.1080 top1_acc: 0.2632 top5_acc: 0.5789 loss_cls: 1.8895 loss: 1.8895 2022/09/08 14:06:11 - mmengine - INFO - Epoch(val) [28][20/130] eta: 0:00:25 time: 0.2363 data_time: 0.0918 memory: 2693 2022/09/08 14:06:14 - mmengine - INFO - Epoch(val) [28][40/130] eta: 0:00:14 time: 0.1581 data_time: 0.0238 memory: 2693 2022/09/08 14:06:18 - mmengine - INFO - Epoch(val) [28][60/130] eta: 0:00:12 time: 0.1715 data_time: 0.0356 memory: 2693 2022/09/08 14:06:21 - mmengine - INFO - Epoch(val) [28][80/130] eta: 0:00:08 time: 0.1669 data_time: 0.0295 memory: 2693 2022/09/08 14:06:25 - mmengine - INFO - Epoch(val) [28][100/130] eta: 0:00:05 time: 0.1685 data_time: 0.0336 memory: 2693 2022/09/08 14:06:28 - mmengine - INFO - Epoch(val) [28][120/130] eta: 0:00:01 time: 0.1613 data_time: 0.0286 memory: 2693 2022/09/08 14:06:30 - mmengine - INFO - Epoch(val) [28][130/130] acc/top1: 0.4838 acc/top5: 0.7676 acc/mean1: 0.4106 2022/09/08 14:06:30 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4/best_acc/top1_epoch_26.pth is removed 2022/09/08 14:06:31 - mmengine - INFO - The best checkpoint with 0.4838 acc/top1 at 28 epoch is saved to best_acc/top1_epoch_28.pth. 2022/09/08 14:06:41 - mmengine - INFO - Epoch(train) [29][20/880] lr: 8.6387e-03 eta: 1:19:16 time: 0.4968 data_time: 0.0684 memory: 23498 grad_norm: 4.7781 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.7676 loss: 1.7676 2022/09/08 14:06:50 - mmengine - INFO - Epoch(train) [29][40/880] lr: 8.6387e-03 eta: 1:19:07 time: 0.4473 data_time: 0.0226 memory: 23498 grad_norm: 4.9079 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.7247 loss: 1.7247 2022/09/08 14:06:59 - mmengine - INFO - Epoch(train) [29][60/880] lr: 8.6387e-03 eta: 1:18:58 time: 0.4475 data_time: 0.0229 memory: 23498 grad_norm: 4.9504 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.7822 loss: 1.7822 2022/09/08 14:07:08 - mmengine - INFO - Epoch(train) [29][80/880] lr: 8.6387e-03 eta: 1:18:49 time: 0.4434 data_time: 0.0224 memory: 23498 grad_norm: 4.9539 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8778 loss: 1.8778 2022/09/08 14:07:17 - mmengine - INFO - Epoch(train) [29][100/880] lr: 8.6387e-03 eta: 1:18:40 time: 0.4435 data_time: 0.0224 memory: 23498 grad_norm: 4.9220 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.8259 loss: 1.8259 2022/09/08 14:07:25 - mmengine - INFO - Epoch(train) [29][120/880] lr: 8.6387e-03 eta: 1:18:31 time: 0.4428 data_time: 0.0226 memory: 23498 grad_norm: 4.8888 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6043 loss: 1.6043 2022/09/08 14:07:34 - mmengine - INFO - Epoch(train) [29][140/880] lr: 8.6387e-03 eta: 1:18:22 time: 0.4448 data_time: 0.0211 memory: 23498 grad_norm: 5.0695 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.6540 loss: 1.6540 2022/09/08 14:07:43 - mmengine - INFO - Epoch(train) [29][160/880] lr: 8.6387e-03 eta: 1:18:13 time: 0.4406 data_time: 0.0218 memory: 23498 grad_norm: 5.0115 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.7961 loss: 1.7961 2022/09/08 14:07:52 - mmengine - INFO - Epoch(train) [29][180/880] lr: 8.6387e-03 eta: 1:18:04 time: 0.4423 data_time: 0.0197 memory: 23498 grad_norm: 5.0432 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.5717 loss: 1.5717 2022/09/08 14:08:01 - mmengine - INFO - Epoch(train) [29][200/880] lr: 8.6387e-03 eta: 1:17:55 time: 0.4444 data_time: 0.0206 memory: 23498 grad_norm: 5.0588 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.7965 loss: 1.7965 2022/09/08 14:08:10 - mmengine - INFO - Epoch(train) [29][220/880] lr: 8.6387e-03 eta: 1:17:45 time: 0.4399 data_time: 0.0206 memory: 23498 grad_norm: 5.0505 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.7412 loss: 1.7412 2022/09/08 14:08:19 - mmengine - INFO - Epoch(train) [29][240/880] lr: 8.6387e-03 eta: 1:17:36 time: 0.4459 data_time: 0.0226 memory: 23498 grad_norm: 4.9995 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.6758 loss: 1.6758 2022/09/08 14:08:28 - mmengine - INFO - Epoch(train) [29][260/880] lr: 8.6387e-03 eta: 1:17:27 time: 0.4534 data_time: 0.0227 memory: 23498 grad_norm: 4.9992 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7522 loss: 1.7522 2022/09/08 14:08:37 - mmengine - INFO - Epoch(train) [29][280/880] lr: 8.6387e-03 eta: 1:17:18 time: 0.4445 data_time: 0.0216 memory: 23498 grad_norm: 4.8933 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.7269 loss: 1.7269 2022/09/08 14:08:45 - mmengine - INFO - Epoch(train) [29][300/880] lr: 8.6387e-03 eta: 1:17:09 time: 0.4418 data_time: 0.0206 memory: 23498 grad_norm: 4.9547 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.7812 loss: 1.7812 2022/09/08 14:08:54 - mmengine - INFO - Epoch(train) [29][320/880] lr: 8.6387e-03 eta: 1:17:00 time: 0.4436 data_time: 0.0209 memory: 23498 grad_norm: 4.9191 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.8627 loss: 1.8627 2022/09/08 14:09:04 - mmengine - INFO - Epoch(train) [29][340/880] lr: 8.6387e-03 eta: 1:16:51 time: 0.4645 data_time: 0.0197 memory: 23498 grad_norm: 5.0039 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 1.7312 loss: 1.7312 2022/09/08 14:09:12 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 14:09:12 - mmengine - INFO - Epoch(train) [29][360/880] lr: 8.6387e-03 eta: 1:16:42 time: 0.4458 data_time: 0.0216 memory: 23498 grad_norm: 5.0254 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7512 loss: 1.7512 2022/09/08 14:09:21 - mmengine - INFO - Epoch(train) [29][380/880] lr: 8.6387e-03 eta: 1:16:33 time: 0.4396 data_time: 0.0195 memory: 23498 grad_norm: 5.0306 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.8643 loss: 1.8643 2022/09/08 14:09:30 - mmengine - INFO - Epoch(train) [29][400/880] lr: 8.6387e-03 eta: 1:16:24 time: 0.4463 data_time: 0.0232 memory: 23498 grad_norm: 5.1320 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.7110 loss: 1.7110 2022/09/08 14:09:39 - mmengine - INFO - Epoch(train) [29][420/880] lr: 8.6387e-03 eta: 1:16:15 time: 0.4524 data_time: 0.0224 memory: 23498 grad_norm: 5.0924 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.7691 loss: 1.7691 2022/09/08 14:09:48 - mmengine - INFO - Epoch(train) [29][440/880] lr: 8.6387e-03 eta: 1:16:06 time: 0.4426 data_time: 0.0211 memory: 23498 grad_norm: 5.1293 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.8990 loss: 1.8990 2022/09/08 14:09:57 - mmengine - INFO - Epoch(train) [29][460/880] lr: 8.6387e-03 eta: 1:15:57 time: 0.4476 data_time: 0.0265 memory: 23498 grad_norm: 5.1095 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8249 loss: 1.8249 2022/09/08 14:10:06 - mmengine - INFO - Epoch(train) [29][480/880] lr: 8.6387e-03 eta: 1:15:48 time: 0.4476 data_time: 0.0202 memory: 23498 grad_norm: 5.2641 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.6485 loss: 1.6485 2022/09/08 14:10:15 - mmengine - INFO - Epoch(train) [29][500/880] lr: 8.6387e-03 eta: 1:15:39 time: 0.4430 data_time: 0.0210 memory: 23498 grad_norm: 5.1331 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.7281 loss: 1.7281 2022/09/08 14:10:24 - mmengine - INFO - Epoch(train) [29][520/880] lr: 8.6387e-03 eta: 1:15:30 time: 0.4474 data_time: 0.0202 memory: 23498 grad_norm: 5.4084 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8722 loss: 1.8722 2022/09/08 14:10:33 - mmengine - INFO - Epoch(train) [29][540/880] lr: 8.6387e-03 eta: 1:15:20 time: 0.4425 data_time: 0.0195 memory: 23498 grad_norm: 5.3240 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.8429 loss: 1.8429 2022/09/08 14:10:42 - mmengine - INFO - Epoch(train) [29][560/880] lr: 8.6387e-03 eta: 1:15:11 time: 0.4430 data_time: 0.0227 memory: 23498 grad_norm: 5.1555 top1_acc: 0.6250 top5_acc: 0.7083 loss_cls: 1.7253 loss: 1.7253 2022/09/08 14:10:51 - mmengine - INFO - Epoch(train) [29][580/880] lr: 8.6387e-03 eta: 1:15:02 time: 0.4517 data_time: 0.0208 memory: 23498 grad_norm: 5.1851 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.8064 loss: 1.8064 2022/09/08 14:10:59 - mmengine - INFO - Epoch(train) [29][600/880] lr: 8.6387e-03 eta: 1:14:53 time: 0.4452 data_time: 0.0220 memory: 23498 grad_norm: 5.1246 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.7697 loss: 1.7697 2022/09/08 14:11:08 - mmengine - INFO - Epoch(train) [29][620/880] lr: 8.6387e-03 eta: 1:14:44 time: 0.4406 data_time: 0.0196 memory: 23498 grad_norm: 5.1929 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.8143 loss: 1.8143 2022/09/08 14:11:17 - mmengine - INFO - Epoch(train) [29][640/880] lr: 8.6387e-03 eta: 1:14:35 time: 0.4433 data_time: 0.0223 memory: 23498 grad_norm: 5.3077 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 1.6506 loss: 1.6506 2022/09/08 14:11:26 - mmengine - INFO - Epoch(train) [29][660/880] lr: 8.6387e-03 eta: 1:14:26 time: 0.4504 data_time: 0.0196 memory: 23498 grad_norm: 5.2102 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7320 loss: 1.7320 2022/09/08 14:11:35 - mmengine - INFO - Epoch(train) [29][680/880] lr: 8.6387e-03 eta: 1:14:17 time: 0.4419 data_time: 0.0222 memory: 23498 grad_norm: 4.9840 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.8732 loss: 1.8732 2022/09/08 14:11:44 - mmengine - INFO - Epoch(train) [29][700/880] lr: 8.6387e-03 eta: 1:14:08 time: 0.4504 data_time: 0.0205 memory: 23498 grad_norm: 4.9476 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 2.0414 loss: 2.0414 2022/09/08 14:11:53 - mmengine - INFO - Epoch(train) [29][720/880] lr: 8.6387e-03 eta: 1:13:59 time: 0.4467 data_time: 0.0235 memory: 23498 grad_norm: 5.1519 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 1.7873 loss: 1.7873 2022/09/08 14:12:02 - mmengine - INFO - Epoch(train) [29][740/880] lr: 8.6387e-03 eta: 1:13:50 time: 0.4420 data_time: 0.0206 memory: 23498 grad_norm: 5.0621 top1_acc: 0.6667 top5_acc: 0.7500 loss_cls: 1.8612 loss: 1.8612 2022/09/08 14:12:11 - mmengine - INFO - Epoch(train) [29][760/880] lr: 8.6387e-03 eta: 1:13:41 time: 0.4503 data_time: 0.0228 memory: 23498 grad_norm: 5.2254 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.7875 loss: 1.7875 2022/09/08 14:12:20 - mmengine - INFO - Epoch(train) [29][780/880] lr: 8.6387e-03 eta: 1:13:32 time: 0.4438 data_time: 0.0217 memory: 23498 grad_norm: 5.1340 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7419 loss: 1.7419 2022/09/08 14:12:29 - mmengine - INFO - Epoch(train) [29][800/880] lr: 8.6387e-03 eta: 1:13:23 time: 0.4509 data_time: 0.0283 memory: 23498 grad_norm: 5.0567 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.6893 loss: 1.6893 2022/09/08 14:12:38 - mmengine - INFO - Epoch(train) [29][820/880] lr: 8.6387e-03 eta: 1:13:14 time: 0.4426 data_time: 0.0213 memory: 23498 grad_norm: 5.2263 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.7151 loss: 1.7151 2022/09/08 14:12:46 - mmengine - INFO - Epoch(train) [29][840/880] lr: 8.6387e-03 eta: 1:13:04 time: 0.4454 data_time: 0.0230 memory: 23498 grad_norm: 5.2049 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.8063 loss: 1.8063 2022/09/08 14:12:55 - mmengine - INFO - Epoch(train) [29][860/880] lr: 8.6387e-03 eta: 1:12:55 time: 0.4436 data_time: 0.0203 memory: 23498 grad_norm: 5.3200 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.7137 loss: 1.7137 2022/09/08 14:13:04 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 14:13:04 - mmengine - INFO - Epoch(train) [29][880/880] lr: 8.6387e-03 eta: 1:12:46 time: 0.4358 data_time: 0.0217 memory: 23498 grad_norm: 5.2301 top1_acc: 0.5263 top5_acc: 0.7368 loss_cls: 1.8264 loss: 1.8264 2022/09/08 14:13:15 - mmengine - INFO - Epoch(train) [30][20/880] lr: 7.3511e-03 eta: 1:12:38 time: 0.5223 data_time: 0.0840 memory: 23498 grad_norm: 5.0175 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5619 loss: 1.5619 2022/09/08 14:13:24 - mmengine - INFO - Epoch(train) [30][40/880] lr: 7.3511e-03 eta: 1:12:29 time: 0.4600 data_time: 0.0205 memory: 23498 grad_norm: 5.0573 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.7010 loss: 1.7010 2022/09/08 14:13:33 - mmengine - INFO - Epoch(train) [30][60/880] lr: 7.3511e-03 eta: 1:12:20 time: 0.4547 data_time: 0.0221 memory: 23498 grad_norm: 5.1252 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.7512 loss: 1.7512 2022/09/08 14:13:42 - mmengine - INFO - Epoch(train) [30][80/880] lr: 7.3511e-03 eta: 1:12:11 time: 0.4471 data_time: 0.0217 memory: 23498 grad_norm: 5.1211 top1_acc: 0.5833 top5_acc: 0.6667 loss_cls: 1.7818 loss: 1.7818 2022/09/08 14:13:51 - mmengine - INFO - Epoch(train) [30][100/880] lr: 7.3511e-03 eta: 1:12:02 time: 0.4713 data_time: 0.0191 memory: 23498 grad_norm: 5.3238 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.7504 loss: 1.7504 2022/09/08 14:14:00 - mmengine - INFO - Epoch(train) [30][120/880] lr: 7.3511e-03 eta: 1:11:53 time: 0.4494 data_time: 0.0207 memory: 23498 grad_norm: 5.2421 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.7926 loss: 1.7926 2022/09/08 14:14:09 - mmengine - INFO - Epoch(train) [30][140/880] lr: 7.3511e-03 eta: 1:11:44 time: 0.4571 data_time: 0.0218 memory: 23498 grad_norm: 5.2503 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6736 loss: 1.6736 2022/09/08 14:14:18 - mmengine - INFO - Epoch(train) [30][160/880] lr: 7.3511e-03 eta: 1:11:35 time: 0.4501 data_time: 0.0208 memory: 23498 grad_norm: 5.1458 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.5903 loss: 1.5903 2022/09/08 14:14:27 - mmengine - INFO - Epoch(train) [30][180/880] lr: 7.3511e-03 eta: 1:11:26 time: 0.4533 data_time: 0.0206 memory: 23498 grad_norm: 5.3355 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.7495 loss: 1.7495 2022/09/08 14:14:36 - mmengine - INFO - Epoch(train) [30][200/880] lr: 7.3511e-03 eta: 1:11:17 time: 0.4445 data_time: 0.0208 memory: 23498 grad_norm: 5.2187 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6415 loss: 1.6415 2022/09/08 14:14:46 - mmengine - INFO - Epoch(train) [30][220/880] lr: 7.3511e-03 eta: 1:11:08 time: 0.4696 data_time: 0.0212 memory: 23498 grad_norm: 5.4316 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8348 loss: 1.8348 2022/09/08 14:14:55 - mmengine - INFO - Epoch(train) [30][240/880] lr: 7.3511e-03 eta: 1:10:59 time: 0.4441 data_time: 0.0203 memory: 23498 grad_norm: 5.1576 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.6675 loss: 1.6675 2022/09/08 14:15:04 - mmengine - INFO - Epoch(train) [30][260/880] lr: 7.3511e-03 eta: 1:10:50 time: 0.4529 data_time: 0.0204 memory: 23498 grad_norm: 5.2317 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.7344 loss: 1.7344 2022/09/08 14:15:13 - mmengine - INFO - Epoch(train) [30][280/880] lr: 7.3511e-03 eta: 1:10:41 time: 0.4453 data_time: 0.0208 memory: 23498 grad_norm: 5.0807 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.7161 loss: 1.7161 2022/09/08 14:15:22 - mmengine - INFO - Epoch(train) [30][300/880] lr: 7.3511e-03 eta: 1:10:32 time: 0.4492 data_time: 0.0221 memory: 23498 grad_norm: 5.4387 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.6949 loss: 1.6949 2022/09/08 14:15:31 - mmengine - INFO - Epoch(train) [30][320/880] lr: 7.3511e-03 eta: 1:10:23 time: 0.4689 data_time: 0.0218 memory: 23498 grad_norm: 5.2430 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6441 loss: 1.6441 2022/09/08 14:15:40 - mmengine - INFO - Epoch(train) [30][340/880] lr: 7.3511e-03 eta: 1:10:14 time: 0.4483 data_time: 0.0236 memory: 23498 grad_norm: 5.3499 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7165 loss: 1.7165 2022/09/08 14:15:49 - mmengine - INFO - Epoch(train) [30][360/880] lr: 7.3511e-03 eta: 1:10:05 time: 0.4483 data_time: 0.0204 memory: 23498 grad_norm: 5.4605 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.7176 loss: 1.7176 2022/09/08 14:15:58 - mmengine - INFO - Epoch(train) [30][380/880] lr: 7.3511e-03 eta: 1:09:56 time: 0.4439 data_time: 0.0184 memory: 23498 grad_norm: 5.3852 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 1.6551 loss: 1.6551 2022/09/08 14:16:07 - mmengine - INFO - Epoch(train) [30][400/880] lr: 7.3511e-03 eta: 1:09:47 time: 0.4428 data_time: 0.0211 memory: 23498 grad_norm: 5.4285 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.6898 loss: 1.6898 2022/09/08 14:16:15 - mmengine - INFO - Epoch(train) [30][420/880] lr: 7.3511e-03 eta: 1:09:37 time: 0.4428 data_time: 0.0191 memory: 23498 grad_norm: 5.4001 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 1.7612 loss: 1.7612 2022/09/08 14:16:25 - mmengine - INFO - Epoch(train) [30][440/880] lr: 7.3511e-03 eta: 1:09:29 time: 0.4682 data_time: 0.0206 memory: 23498 grad_norm: 5.4050 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.7723 loss: 1.7723 2022/09/08 14:16:34 - mmengine - INFO - Epoch(train) [30][460/880] lr: 7.3511e-03 eta: 1:09:19 time: 0.4453 data_time: 0.0200 memory: 23498 grad_norm: 5.3356 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.7024 loss: 1.7024 2022/09/08 14:16:43 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 14:16:43 - mmengine - INFO - Epoch(train) [30][480/880] lr: 7.3511e-03 eta: 1:09:10 time: 0.4468 data_time: 0.0204 memory: 23498 grad_norm: 5.3910 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8049 loss: 1.8049 2022/09/08 14:16:52 - mmengine - INFO - Epoch(train) [30][500/880] lr: 7.3511e-03 eta: 1:09:01 time: 0.4456 data_time: 0.0189 memory: 23498 grad_norm: 5.4022 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 1.7123 loss: 1.7123 2022/09/08 14:17:00 - mmengine - INFO - Epoch(train) [30][520/880] lr: 7.3511e-03 eta: 1:08:52 time: 0.4455 data_time: 0.0201 memory: 23498 grad_norm: 5.3452 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.8174 loss: 1.8174 2022/09/08 14:17:09 - mmengine - INFO - Epoch(train) [30][540/880] lr: 7.3511e-03 eta: 1:08:43 time: 0.4445 data_time: 0.0197 memory: 23498 grad_norm: 5.4254 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6809 loss: 1.6809 2022/09/08 14:17:18 - mmengine - INFO - Epoch(train) [30][560/880] lr: 7.3511e-03 eta: 1:08:34 time: 0.4490 data_time: 0.0205 memory: 23498 grad_norm: 5.3951 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.7283 loss: 1.7283 2022/09/08 14:17:27 - mmengine - INFO - Epoch(train) [30][580/880] lr: 7.3511e-03 eta: 1:08:25 time: 0.4455 data_time: 0.0207 memory: 23498 grad_norm: 5.3530 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.8031 loss: 1.8031 2022/09/08 14:17:36 - mmengine - INFO - Epoch(train) [30][600/880] lr: 7.3511e-03 eta: 1:08:16 time: 0.4440 data_time: 0.0208 memory: 23498 grad_norm: 5.3868 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6032 loss: 1.6032 2022/09/08 14:17:45 - mmengine - INFO - Epoch(train) [30][620/880] lr: 7.3511e-03 eta: 1:08:07 time: 0.4480 data_time: 0.0207 memory: 23498 grad_norm: 5.4675 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.7570 loss: 1.7570 2022/09/08 14:17:54 - mmengine - INFO - Epoch(train) [30][640/880] lr: 7.3511e-03 eta: 1:07:58 time: 0.4455 data_time: 0.0212 memory: 23498 grad_norm: 5.4418 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7455 loss: 1.7455 2022/09/08 14:18:03 - mmengine - INFO - Epoch(train) [30][660/880] lr: 7.3511e-03 eta: 1:07:49 time: 0.4443 data_time: 0.0198 memory: 23498 grad_norm: 5.5804 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.6731 loss: 1.6731 2022/09/08 14:18:12 - mmengine - INFO - Epoch(train) [30][680/880] lr: 7.3511e-03 eta: 1:07:40 time: 0.4450 data_time: 0.0211 memory: 23498 grad_norm: 5.4380 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.8148 loss: 1.8148 2022/09/08 14:18:21 - mmengine - INFO - Epoch(train) [30][700/880] lr: 7.3511e-03 eta: 1:07:31 time: 0.4437 data_time: 0.0209 memory: 23498 grad_norm: 5.4761 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.7816 loss: 1.7816 2022/09/08 14:18:30 - mmengine - INFO - Epoch(train) [30][720/880] lr: 7.3511e-03 eta: 1:07:22 time: 0.4482 data_time: 0.0198 memory: 23498 grad_norm: 5.3633 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.7042 loss: 1.7042 2022/09/08 14:18:39 - mmengine - INFO - Epoch(train) [30][740/880] lr: 7.3511e-03 eta: 1:07:13 time: 0.4445 data_time: 0.0195 memory: 23498 grad_norm: 5.4144 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.6878 loss: 1.6878 2022/09/08 14:18:48 - mmengine - INFO - Epoch(train) [30][760/880] lr: 7.3511e-03 eta: 1:07:04 time: 0.4499 data_time: 0.0227 memory: 23498 grad_norm: 5.5407 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 1.6710 loss: 1.6710 2022/09/08 14:18:56 - mmengine - INFO - Epoch(train) [30][780/880] lr: 7.3511e-03 eta: 1:06:55 time: 0.4425 data_time: 0.0202 memory: 23498 grad_norm: 5.3875 top1_acc: 0.2500 top5_acc: 0.4583 loss_cls: 1.7090 loss: 1.7090 2022/09/08 14:19:05 - mmengine - INFO - Epoch(train) [30][800/880] lr: 7.3511e-03 eta: 1:06:45 time: 0.4524 data_time: 0.0201 memory: 23498 grad_norm: 5.3724 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.8268 loss: 1.8268 2022/09/08 14:19:14 - mmengine - INFO - Epoch(train) [30][820/880] lr: 7.3511e-03 eta: 1:06:36 time: 0.4439 data_time: 0.0185 memory: 23498 grad_norm: 5.4563 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.7050 loss: 1.7050 2022/09/08 14:19:23 - mmengine - INFO - Epoch(train) [30][840/880] lr: 7.3511e-03 eta: 1:06:27 time: 0.4494 data_time: 0.0202 memory: 23498 grad_norm: 5.4320 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.8387 loss: 1.8387 2022/09/08 14:19:32 - mmengine - INFO - Epoch(train) [30][860/880] lr: 7.3511e-03 eta: 1:06:18 time: 0.4405 data_time: 0.0190 memory: 23498 grad_norm: 5.3898 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.6925 loss: 1.6925 2022/09/08 14:19:41 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 14:19:41 - mmengine - INFO - Epoch(train) [30][880/880] lr: 7.3511e-03 eta: 1:06:09 time: 0.4326 data_time: 0.0179 memory: 23498 grad_norm: 5.5409 top1_acc: 0.6316 top5_acc: 0.8421 loss_cls: 1.6468 loss: 1.6468 2022/09/08 14:19:45 - mmengine - INFO - Epoch(val) [30][20/130] eta: 0:00:23 time: 0.2171 data_time: 0.0772 memory: 2693 2022/09/08 14:19:48 - mmengine - INFO - Epoch(val) [30][40/130] eta: 0:00:14 time: 0.1600 data_time: 0.0244 memory: 2693 2022/09/08 14:19:52 - mmengine - INFO - Epoch(val) [30][60/130] eta: 0:00:11 time: 0.1674 data_time: 0.0302 memory: 2693 2022/09/08 14:19:55 - mmengine - INFO - Epoch(val) [30][80/130] eta: 0:00:08 time: 0.1687 data_time: 0.0347 memory: 2693 2022/09/08 14:19:58 - mmengine - INFO - Epoch(val) [30][100/130] eta: 0:00:04 time: 0.1638 data_time: 0.0292 memory: 2693 2022/09/08 14:20:02 - mmengine - INFO - Epoch(val) [30][120/130] eta: 0:00:01 time: 0.1611 data_time: 0.0259 memory: 2693 2022/09/08 14:20:04 - mmengine - INFO - Epoch(val) [30][130/130] acc/top1: 0.4821 acc/top5: 0.7703 acc/mean1: 0.4139 2022/09/08 14:20:14 - mmengine - INFO - Epoch(train) [31][20/880] lr: 6.1455e-03 eta: 1:06:01 time: 0.5085 data_time: 0.0747 memory: 23498 grad_norm: 5.2955 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6367 loss: 1.6367 2022/09/08 14:20:23 - mmengine - INFO - Epoch(train) [31][40/880] lr: 6.1455e-03 eta: 1:05:51 time: 0.4494 data_time: 0.0233 memory: 23498 grad_norm: 5.4190 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.5222 loss: 1.5222 2022/09/08 14:20:32 - mmengine - INFO - Epoch(train) [31][60/880] lr: 6.1455e-03 eta: 1:05:42 time: 0.4491 data_time: 0.0219 memory: 23498 grad_norm: 5.3671 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.5971 loss: 1.5971 2022/09/08 14:20:41 - mmengine - INFO - Epoch(train) [31][80/880] lr: 6.1455e-03 eta: 1:05:33 time: 0.4481 data_time: 0.0221 memory: 23498 grad_norm: 5.3887 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.5742 loss: 1.5742 2022/09/08 14:20:50 - mmengine - INFO - Epoch(train) [31][100/880] lr: 6.1455e-03 eta: 1:05:24 time: 0.4506 data_time: 0.0215 memory: 23498 grad_norm: 5.4540 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7442 loss: 1.7442 2022/09/08 14:20:59 - mmengine - INFO - Epoch(train) [31][120/880] lr: 6.1455e-03 eta: 1:05:15 time: 0.4511 data_time: 0.0264 memory: 23498 grad_norm: 5.2544 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6757 loss: 1.6757 2022/09/08 14:21:08 - mmengine - INFO - Epoch(train) [31][140/880] lr: 6.1455e-03 eta: 1:05:06 time: 0.4503 data_time: 0.0219 memory: 23498 grad_norm: 5.3126 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6464 loss: 1.6464 2022/09/08 14:21:17 - mmengine - INFO - Epoch(train) [31][160/880] lr: 6.1455e-03 eta: 1:04:57 time: 0.4461 data_time: 0.0201 memory: 23498 grad_norm: 5.4127 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.7153 loss: 1.7153 2022/09/08 14:21:26 - mmengine - INFO - Epoch(train) [31][180/880] lr: 6.1455e-03 eta: 1:04:48 time: 0.4512 data_time: 0.0220 memory: 23498 grad_norm: 5.3080 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.6911 loss: 1.6911 2022/09/08 14:21:35 - mmengine - INFO - Epoch(train) [31][200/880] lr: 6.1455e-03 eta: 1:04:39 time: 0.4454 data_time: 0.0208 memory: 23498 grad_norm: 5.3034 top1_acc: 0.8333 top5_acc: 0.8750 loss_cls: 1.6255 loss: 1.6255 2022/09/08 14:21:44 - mmengine - INFO - Epoch(train) [31][220/880] lr: 6.1455e-03 eta: 1:04:30 time: 0.4534 data_time: 0.0224 memory: 23498 grad_norm: 5.2148 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.5685 loss: 1.5685 2022/09/08 14:21:53 - mmengine - INFO - Epoch(train) [31][240/880] lr: 6.1455e-03 eta: 1:04:21 time: 0.4469 data_time: 0.0199 memory: 23498 grad_norm: 5.2822 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.5597 loss: 1.5597 2022/09/08 14:22:02 - mmengine - INFO - Epoch(train) [31][260/880] lr: 6.1455e-03 eta: 1:04:12 time: 0.4509 data_time: 0.0240 memory: 23498 grad_norm: 5.3291 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.6868 loss: 1.6868 2022/09/08 14:22:11 - mmengine - INFO - Epoch(train) [31][280/880] lr: 6.1455e-03 eta: 1:04:03 time: 0.4492 data_time: 0.0205 memory: 23498 grad_norm: 5.4178 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6314 loss: 1.6314 2022/09/08 14:22:20 - mmengine - INFO - Epoch(train) [31][300/880] lr: 6.1455e-03 eta: 1:03:54 time: 0.4504 data_time: 0.0228 memory: 23498 grad_norm: 5.4773 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6430 loss: 1.6430 2022/09/08 14:22:29 - mmengine - INFO - Epoch(train) [31][320/880] lr: 6.1455e-03 eta: 1:03:45 time: 0.4670 data_time: 0.0217 memory: 23498 grad_norm: 5.5493 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6732 loss: 1.6732 2022/09/08 14:22:38 - mmengine - INFO - Epoch(train) [31][340/880] lr: 6.1455e-03 eta: 1:03:36 time: 0.4480 data_time: 0.0218 memory: 23498 grad_norm: 5.4899 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.5841 loss: 1.5841 2022/09/08 14:22:48 - mmengine - INFO - Epoch(train) [31][360/880] lr: 6.1455e-03 eta: 1:03:27 time: 0.4674 data_time: 0.0213 memory: 23498 grad_norm: 5.4929 top1_acc: 0.5417 top5_acc: 0.6250 loss_cls: 1.7478 loss: 1.7478 2022/09/08 14:22:57 - mmengine - INFO - Epoch(train) [31][380/880] lr: 6.1455e-03 eta: 1:03:18 time: 0.4524 data_time: 0.0195 memory: 23498 grad_norm: 5.6278 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.6913 loss: 1.6913 2022/09/08 14:23:06 - mmengine - INFO - Epoch(train) [31][400/880] lr: 6.1455e-03 eta: 1:03:09 time: 0.4646 data_time: 0.0255 memory: 23498 grad_norm: 5.5668 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6652 loss: 1.6652 2022/09/08 14:23:15 - mmengine - INFO - Epoch(train) [31][420/880] lr: 6.1455e-03 eta: 1:03:00 time: 0.4477 data_time: 0.0205 memory: 23498 grad_norm: 5.3644 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.7372 loss: 1.7372 2022/09/08 14:23:24 - mmengine - INFO - Epoch(train) [31][440/880] lr: 6.1455e-03 eta: 1:02:51 time: 0.4474 data_time: 0.0232 memory: 23498 grad_norm: 5.4523 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.6284 loss: 1.6284 2022/09/08 14:23:33 - mmengine - INFO - Epoch(train) [31][460/880] lr: 6.1455e-03 eta: 1:02:42 time: 0.4469 data_time: 0.0204 memory: 23498 grad_norm: 5.5028 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.5811 loss: 1.5811 2022/09/08 14:23:42 - mmengine - INFO - Epoch(train) [31][480/880] lr: 6.1455e-03 eta: 1:02:33 time: 0.4452 data_time: 0.0218 memory: 23498 grad_norm: 5.4622 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.6402 loss: 1.6402 2022/09/08 14:23:51 - mmengine - INFO - Epoch(train) [31][500/880] lr: 6.1455e-03 eta: 1:02:24 time: 0.4540 data_time: 0.0204 memory: 23498 grad_norm: 5.6367 top1_acc: 0.5417 top5_acc: 0.9583 loss_cls: 1.6095 loss: 1.6095 2022/09/08 14:24:00 - mmengine - INFO - Epoch(train) [31][520/880] lr: 6.1455e-03 eta: 1:02:15 time: 0.4458 data_time: 0.0221 memory: 23498 grad_norm: 5.3716 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.5926 loss: 1.5926 2022/09/08 14:24:09 - mmengine - INFO - Epoch(train) [31][540/880] lr: 6.1455e-03 eta: 1:02:06 time: 0.4566 data_time: 0.0223 memory: 23498 grad_norm: 5.4445 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6651 loss: 1.6651 2022/09/08 14:24:18 - mmengine - INFO - Epoch(train) [31][560/880] lr: 6.1455e-03 eta: 1:01:57 time: 0.4516 data_time: 0.0212 memory: 23498 grad_norm: 5.5553 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.5082 loss: 1.5082 2022/09/08 14:24:27 - mmengine - INFO - Epoch(train) [31][580/880] lr: 6.1455e-03 eta: 1:01:48 time: 0.4625 data_time: 0.0258 memory: 23498 grad_norm: 5.7401 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.6743 loss: 1.6743 2022/09/08 14:24:36 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 14:24:36 - mmengine - INFO - Epoch(train) [31][600/880] lr: 6.1455e-03 eta: 1:01:39 time: 0.4492 data_time: 0.0257 memory: 23498 grad_norm: 5.4702 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6691 loss: 1.6691 2022/09/08 14:24:45 - mmengine - INFO - Epoch(train) [31][620/880] lr: 6.1455e-03 eta: 1:01:30 time: 0.4449 data_time: 0.0198 memory: 23498 grad_norm: 5.6971 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.6027 loss: 1.6027 2022/09/08 14:24:54 - mmengine - INFO - Epoch(train) [31][640/880] lr: 6.1455e-03 eta: 1:01:21 time: 0.4427 data_time: 0.0209 memory: 23498 grad_norm: 5.5706 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 1.6915 loss: 1.6915 2022/09/08 14:25:03 - mmengine - INFO - Epoch(train) [31][660/880] lr: 6.1455e-03 eta: 1:01:12 time: 0.4484 data_time: 0.0202 memory: 23498 grad_norm: 5.5825 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.7695 loss: 1.7695 2022/09/08 14:25:12 - mmengine - INFO - Epoch(train) [31][680/880] lr: 6.1455e-03 eta: 1:01:03 time: 0.4494 data_time: 0.0202 memory: 23498 grad_norm: 5.5527 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.6835 loss: 1.6835 2022/09/08 14:25:21 - mmengine - INFO - Epoch(train) [31][700/880] lr: 6.1455e-03 eta: 1:00:54 time: 0.4449 data_time: 0.0206 memory: 23498 grad_norm: 5.7937 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.6365 loss: 1.6365 2022/09/08 14:25:30 - mmengine - INFO - Epoch(train) [31][720/880] lr: 6.1455e-03 eta: 1:00:45 time: 0.4633 data_time: 0.0234 memory: 23498 grad_norm: 5.4457 top1_acc: 0.4167 top5_acc: 0.8333 loss_cls: 1.5567 loss: 1.5567 2022/09/08 14:25:39 - mmengine - INFO - Epoch(train) [31][740/880] lr: 6.1455e-03 eta: 1:00:36 time: 0.4476 data_time: 0.0245 memory: 23498 grad_norm: 5.9790 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 1.6508 loss: 1.6508 2022/09/08 14:25:48 - mmengine - INFO - Epoch(train) [31][760/880] lr: 6.1455e-03 eta: 1:00:27 time: 0.4639 data_time: 0.0226 memory: 23498 grad_norm: 5.7883 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7071 loss: 1.7071 2022/09/08 14:25:57 - mmengine - INFO - Epoch(train) [31][780/880] lr: 6.1455e-03 eta: 1:00:18 time: 0.4433 data_time: 0.0193 memory: 23498 grad_norm: 5.7681 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.6025 loss: 1.6025 2022/09/08 14:26:06 - mmengine - INFO - Epoch(train) [31][800/880] lr: 6.1455e-03 eta: 1:00:09 time: 0.4472 data_time: 0.0219 memory: 23498 grad_norm: 5.7228 top1_acc: 0.4167 top5_acc: 0.5833 loss_cls: 1.5857 loss: 1.5857 2022/09/08 14:26:15 - mmengine - INFO - Epoch(train) [31][820/880] lr: 6.1455e-03 eta: 1:00:00 time: 0.4468 data_time: 0.0199 memory: 23498 grad_norm: 5.8202 top1_acc: 0.6250 top5_acc: 0.7083 loss_cls: 1.8325 loss: 1.8325 2022/09/08 14:26:24 - mmengine - INFO - Epoch(train) [31][840/880] lr: 6.1455e-03 eta: 0:59:51 time: 0.4550 data_time: 0.0222 memory: 23498 grad_norm: 5.7205 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 1.6269 loss: 1.6269 2022/09/08 14:26:33 - mmengine - INFO - Epoch(train) [31][860/880] lr: 6.1455e-03 eta: 0:59:42 time: 0.4443 data_time: 0.0200 memory: 23498 grad_norm: 5.7302 top1_acc: 0.4167 top5_acc: 0.8333 loss_cls: 1.5925 loss: 1.5925 2022/09/08 14:26:42 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 14:26:42 - mmengine - INFO - Epoch(train) [31][880/880] lr: 6.1455e-03 eta: 0:59:32 time: 0.4336 data_time: 0.0199 memory: 23498 grad_norm: 5.7751 top1_acc: 0.5263 top5_acc: 0.5789 loss_cls: 1.7082 loss: 1.7082 2022/09/08 14:26:52 - mmengine - INFO - Epoch(train) [32][20/880] lr: 5.0298e-03 eta: 0:59:24 time: 0.5282 data_time: 0.0735 memory: 23498 grad_norm: 5.5042 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5931 loss: 1.5931 2022/09/08 14:27:01 - mmengine - INFO - Epoch(train) [32][40/880] lr: 5.0298e-03 eta: 0:59:15 time: 0.4580 data_time: 0.0227 memory: 23498 grad_norm: 5.4134 top1_acc: 0.3750 top5_acc: 0.8333 loss_cls: 1.6051 loss: 1.6051 2022/09/08 14:27:10 - mmengine - INFO - Epoch(train) [32][60/880] lr: 5.0298e-03 eta: 0:59:06 time: 0.4513 data_time: 0.0197 memory: 23498 grad_norm: 5.5245 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.5620 loss: 1.5620 2022/09/08 14:27:19 - mmengine - INFO - Epoch(train) [32][80/880] lr: 5.0298e-03 eta: 0:58:57 time: 0.4517 data_time: 0.0208 memory: 23498 grad_norm: 5.3932 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5956 loss: 1.5956 2022/09/08 14:27:29 - mmengine - INFO - Epoch(train) [32][100/880] lr: 5.0298e-03 eta: 0:58:48 time: 0.4613 data_time: 0.0185 memory: 23498 grad_norm: 5.6112 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.6016 loss: 1.6016 2022/09/08 14:27:38 - mmengine - INFO - Epoch(train) [32][120/880] lr: 5.0298e-03 eta: 0:58:39 time: 0.4623 data_time: 0.0210 memory: 23498 grad_norm: 5.8010 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.5684 loss: 1.5684 2022/09/08 14:27:47 - mmengine - INFO - Epoch(train) [32][140/880] lr: 5.0298e-03 eta: 0:58:30 time: 0.4640 data_time: 0.0200 memory: 23498 grad_norm: 5.7504 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.5173 loss: 1.5173 2022/09/08 14:27:56 - mmengine - INFO - Epoch(train) [32][160/880] lr: 5.0298e-03 eta: 0:58:21 time: 0.4578 data_time: 0.0226 memory: 23498 grad_norm: 5.7361 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.5524 loss: 1.5524 2022/09/08 14:28:06 - mmengine - INFO - Epoch(train) [32][180/880] lr: 5.0298e-03 eta: 0:58:12 time: 0.4626 data_time: 0.0188 memory: 23498 grad_norm: 5.9388 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.5866 loss: 1.5866 2022/09/08 14:28:15 - mmengine - INFO - Epoch(train) [32][200/880] lr: 5.0298e-03 eta: 0:58:03 time: 0.4545 data_time: 0.0233 memory: 23498 grad_norm: 5.7598 top1_acc: 0.5000 top5_acc: 0.5833 loss_cls: 1.6505 loss: 1.6505 2022/09/08 14:28:24 - mmengine - INFO - Epoch(train) [32][220/880] lr: 5.0298e-03 eta: 0:57:54 time: 0.4533 data_time: 0.0215 memory: 23498 grad_norm: 5.8055 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.5391 loss: 1.5391 2022/09/08 14:28:33 - mmengine - INFO - Epoch(train) [32][240/880] lr: 5.0298e-03 eta: 0:57:45 time: 0.4474 data_time: 0.0216 memory: 23498 grad_norm: 5.7276 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.5220 loss: 1.5220 2022/09/08 14:28:42 - mmengine - INFO - Epoch(train) [32][260/880] lr: 5.0298e-03 eta: 0:57:36 time: 0.4595 data_time: 0.0204 memory: 23498 grad_norm: 5.8309 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.6731 loss: 1.6731 2022/09/08 14:28:51 - mmengine - INFO - Epoch(train) [32][280/880] lr: 5.0298e-03 eta: 0:57:27 time: 0.4575 data_time: 0.0253 memory: 23498 grad_norm: 5.7068 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6408 loss: 1.6408 2022/09/08 14:29:00 - mmengine - INFO - Epoch(train) [32][300/880] lr: 5.0298e-03 eta: 0:57:18 time: 0.4573 data_time: 0.0202 memory: 23498 grad_norm: 5.9276 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.5451 loss: 1.5451 2022/09/08 14:29:09 - mmengine - INFO - Epoch(train) [32][320/880] lr: 5.0298e-03 eta: 0:57:09 time: 0.4502 data_time: 0.0234 memory: 23498 grad_norm: 5.9142 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.5367 loss: 1.5367 2022/09/08 14:29:18 - mmengine - INFO - Epoch(train) [32][340/880] lr: 5.0298e-03 eta: 0:57:00 time: 0.4629 data_time: 0.0207 memory: 23498 grad_norm: 5.9473 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.6958 loss: 1.6958 2022/09/08 14:29:28 - mmengine - INFO - Epoch(train) [32][360/880] lr: 5.0298e-03 eta: 0:56:51 time: 0.4557 data_time: 0.0265 memory: 23498 grad_norm: 5.8851 top1_acc: 0.4583 top5_acc: 0.6667 loss_cls: 1.7029 loss: 1.7029 2022/09/08 14:29:37 - mmengine - INFO - Epoch(train) [32][380/880] lr: 5.0298e-03 eta: 0:56:42 time: 0.4486 data_time: 0.0186 memory: 23498 grad_norm: 5.8008 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.5882 loss: 1.5882 2022/09/08 14:29:46 - mmengine - INFO - Epoch(train) [32][400/880] lr: 5.0298e-03 eta: 0:56:33 time: 0.4529 data_time: 0.0233 memory: 23498 grad_norm: 5.6241 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.4994 loss: 1.4994 2022/09/08 14:29:55 - mmengine - INFO - Epoch(train) [32][420/880] lr: 5.0298e-03 eta: 0:56:24 time: 0.4499 data_time: 0.0205 memory: 23498 grad_norm: 5.7954 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.6412 loss: 1.6412 2022/09/08 14:30:04 - mmengine - INFO - Epoch(train) [32][440/880] lr: 5.0298e-03 eta: 0:56:15 time: 0.4499 data_time: 0.0213 memory: 23498 grad_norm: 5.8743 top1_acc: 0.5417 top5_acc: 0.7083 loss_cls: 1.6839 loss: 1.6839 2022/09/08 14:30:13 - mmengine - INFO - Epoch(train) [32][460/880] lr: 5.0298e-03 eta: 0:56:06 time: 0.4484 data_time: 0.0212 memory: 23498 grad_norm: 5.9263 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.6534 loss: 1.6534 2022/09/08 14:30:22 - mmengine - INFO - Epoch(train) [32][480/880] lr: 5.0298e-03 eta: 0:55:57 time: 0.4471 data_time: 0.0212 memory: 23498 grad_norm: 5.9313 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.6587 loss: 1.6587 2022/09/08 14:30:30 - mmengine - INFO - Epoch(train) [32][500/880] lr: 5.0298e-03 eta: 0:55:48 time: 0.4448 data_time: 0.0217 memory: 23498 grad_norm: 5.8999 top1_acc: 0.7500 top5_acc: 0.7917 loss_cls: 1.5358 loss: 1.5358 2022/09/08 14:30:39 - mmengine - INFO - Epoch(train) [32][520/880] lr: 5.0298e-03 eta: 0:55:39 time: 0.4442 data_time: 0.0205 memory: 23498 grad_norm: 5.9788 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.7236 loss: 1.7236 2022/09/08 14:30:49 - mmengine - INFO - Epoch(train) [32][540/880] lr: 5.0298e-03 eta: 0:55:30 time: 0.4620 data_time: 0.0211 memory: 23498 grad_norm: 6.0664 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.5196 loss: 1.5196 2022/09/08 14:30:58 - mmengine - INFO - Epoch(train) [32][560/880] lr: 5.0298e-03 eta: 0:55:21 time: 0.4497 data_time: 0.0246 memory: 23498 grad_norm: 5.8118 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.6722 loss: 1.6722 2022/09/08 14:31:07 - mmengine - INFO - Epoch(train) [32][580/880] lr: 5.0298e-03 eta: 0:55:12 time: 0.4706 data_time: 0.0255 memory: 23498 grad_norm: 5.7909 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.6687 loss: 1.6687 2022/09/08 14:31:16 - mmengine - INFO - Epoch(train) [32][600/880] lr: 5.0298e-03 eta: 0:55:03 time: 0.4462 data_time: 0.0212 memory: 23498 grad_norm: 5.8273 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4643 loss: 1.4643 2022/09/08 14:31:25 - mmengine - INFO - Epoch(train) [32][620/880] lr: 5.0298e-03 eta: 0:54:54 time: 0.4520 data_time: 0.0237 memory: 23498 grad_norm: 5.7600 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.5596 loss: 1.5596 2022/09/08 14:31:34 - mmengine - INFO - Epoch(train) [32][640/880] lr: 5.0298e-03 eta: 0:54:45 time: 0.4470 data_time: 0.0194 memory: 23498 grad_norm: 5.6357 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7018 loss: 1.7018 2022/09/08 14:31:43 - mmengine - INFO - Epoch(train) [32][660/880] lr: 5.0298e-03 eta: 0:54:36 time: 0.4447 data_time: 0.0222 memory: 23498 grad_norm: 5.7243 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.4717 loss: 1.4717 2022/09/08 14:31:52 - mmengine - INFO - Epoch(train) [32][680/880] lr: 5.0298e-03 eta: 0:54:26 time: 0.4517 data_time: 0.0256 memory: 23498 grad_norm: 5.7107 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.5389 loss: 1.5389 2022/09/08 14:32:01 - mmengine - INFO - Epoch(train) [32][700/880] lr: 5.0298e-03 eta: 0:54:17 time: 0.4433 data_time: 0.0214 memory: 23498 grad_norm: 5.6105 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.5053 loss: 1.5053 2022/09/08 14:32:10 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 14:32:10 - mmengine - INFO - Epoch(train) [32][720/880] lr: 5.0298e-03 eta: 0:54:08 time: 0.4451 data_time: 0.0214 memory: 23498 grad_norm: 5.8732 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.6370 loss: 1.6370 2022/09/08 14:32:19 - mmengine - INFO - Epoch(train) [32][740/880] lr: 5.0298e-03 eta: 0:53:59 time: 0.4475 data_time: 0.0189 memory: 23498 grad_norm: 5.7167 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.5153 loss: 1.5153 2022/09/08 14:32:27 - mmengine - INFO - Epoch(train) [32][760/880] lr: 5.0298e-03 eta: 0:53:50 time: 0.4432 data_time: 0.0194 memory: 23498 grad_norm: 5.9985 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.6541 loss: 1.6541 2022/09/08 14:32:37 - mmengine - INFO - Epoch(train) [32][780/880] lr: 5.0298e-03 eta: 0:53:41 time: 0.4601 data_time: 0.0209 memory: 23498 grad_norm: 5.6327 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.5539 loss: 1.5539 2022/09/08 14:32:46 - mmengine - INFO - Epoch(train) [32][800/880] lr: 5.0298e-03 eta: 0:53:32 time: 0.4491 data_time: 0.0219 memory: 23498 grad_norm: 5.7705 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.5054 loss: 1.5054 2022/09/08 14:32:54 - mmengine - INFO - Epoch(train) [32][820/880] lr: 5.0298e-03 eta: 0:53:23 time: 0.4442 data_time: 0.0200 memory: 23498 grad_norm: 5.8094 top1_acc: 0.3750 top5_acc: 0.7917 loss_cls: 1.8012 loss: 1.8012 2022/09/08 14:33:03 - mmengine - INFO - Epoch(train) [32][840/880] lr: 5.0298e-03 eta: 0:53:14 time: 0.4432 data_time: 0.0203 memory: 23498 grad_norm: 5.6941 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.5397 loss: 1.5397 2022/09/08 14:33:12 - mmengine - INFO - Epoch(train) [32][860/880] lr: 5.0298e-03 eta: 0:53:05 time: 0.4440 data_time: 0.0201 memory: 23498 grad_norm: 6.0267 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5059 loss: 1.5059 2022/09/08 14:33:21 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 14:33:21 - mmengine - INFO - Epoch(train) [32][880/880] lr: 5.0298e-03 eta: 0:52:56 time: 0.4324 data_time: 0.0200 memory: 23498 grad_norm: 5.8318 top1_acc: 0.6316 top5_acc: 0.8947 loss_cls: 1.5254 loss: 1.5254 2022/09/08 14:33:25 - mmengine - INFO - Epoch(val) [32][20/130] eta: 0:00:23 time: 0.2170 data_time: 0.0815 memory: 2693 2022/09/08 14:33:29 - mmengine - INFO - Epoch(val) [32][40/130] eta: 0:00:14 time: 0.1602 data_time: 0.0247 memory: 2693 2022/09/08 14:33:32 - mmengine - INFO - Epoch(val) [32][60/130] eta: 0:00:12 time: 0.1729 data_time: 0.0378 memory: 2693 2022/09/08 14:33:35 - mmengine - INFO - Epoch(val) [32][80/130] eta: 0:00:08 time: 0.1643 data_time: 0.0260 memory: 2693 2022/09/08 14:33:39 - mmengine - INFO - Epoch(val) [32][100/130] eta: 0:00:05 time: 0.1724 data_time: 0.0337 memory: 2693 2022/09/08 14:33:42 - mmengine - INFO - Epoch(val) [32][120/130] eta: 0:00:01 time: 0.1589 data_time: 0.0256 memory: 2693 2022/09/08 14:33:44 - mmengine - INFO - Epoch(val) [32][130/130] acc/top1: 0.5023 acc/top5: 0.7868 acc/mean1: 0.4285 2022/09/08 14:33:44 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4/best_acc/top1_epoch_28.pth is removed 2022/09/08 14:33:45 - mmengine - INFO - The best checkpoint with 0.5023 acc/top1 at 32 epoch is saved to best_acc/top1_epoch_32.pth. 2022/09/08 14:33:55 - mmengine - INFO - Epoch(train) [33][20/880] lr: 4.0111e-03 eta: 0:52:47 time: 0.4920 data_time: 0.0656 memory: 23498 grad_norm: 5.8503 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.4311 loss: 1.4311 2022/09/08 14:34:04 - mmengine - INFO - Epoch(train) [33][40/880] lr: 4.0111e-03 eta: 0:52:38 time: 0.4512 data_time: 0.0272 memory: 23498 grad_norm: 5.8596 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.5725 loss: 1.5725 2022/09/08 14:34:13 - mmengine - INFO - Epoch(train) [33][60/880] lr: 4.0111e-03 eta: 0:52:29 time: 0.4531 data_time: 0.0203 memory: 23498 grad_norm: 5.7305 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5078 loss: 1.5078 2022/09/08 14:34:22 - mmengine - INFO - Epoch(train) [33][80/880] lr: 4.0111e-03 eta: 0:52:20 time: 0.4482 data_time: 0.0232 memory: 23498 grad_norm: 5.8989 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5384 loss: 1.5384 2022/09/08 14:34:31 - mmengine - INFO - Epoch(train) [33][100/880] lr: 4.0111e-03 eta: 0:52:11 time: 0.4475 data_time: 0.0177 memory: 23498 grad_norm: 5.7723 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.3508 loss: 1.3508 2022/09/08 14:34:40 - mmengine - INFO - Epoch(train) [33][120/880] lr: 4.0111e-03 eta: 0:52:02 time: 0.4563 data_time: 0.0213 memory: 23498 grad_norm: 5.9336 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.5589 loss: 1.5589 2022/09/08 14:34:49 - mmengine - INFO - Epoch(train) [33][140/880] lr: 4.0111e-03 eta: 0:51:53 time: 0.4451 data_time: 0.0182 memory: 23498 grad_norm: 5.5671 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5565 loss: 1.5565 2022/09/08 14:34:58 - mmengine - INFO - Epoch(train) [33][160/880] lr: 4.0111e-03 eta: 0:51:44 time: 0.4461 data_time: 0.0256 memory: 23498 grad_norm: 5.8460 top1_acc: 0.3750 top5_acc: 0.5833 loss_cls: 1.5592 loss: 1.5592 2022/09/08 14:35:07 - mmengine - INFO - Epoch(train) [33][180/880] lr: 4.0111e-03 eta: 0:51:35 time: 0.4440 data_time: 0.0205 memory: 23498 grad_norm: 5.9939 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.6169 loss: 1.6169 2022/09/08 14:35:16 - mmengine - INFO - Epoch(train) [33][200/880] lr: 4.0111e-03 eta: 0:51:26 time: 0.4564 data_time: 0.0223 memory: 23498 grad_norm: 6.0256 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.5181 loss: 1.5181 2022/09/08 14:35:25 - mmengine - INFO - Epoch(train) [33][220/880] lr: 4.0111e-03 eta: 0:51:17 time: 0.4466 data_time: 0.0217 memory: 23498 grad_norm: 6.0973 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.5902 loss: 1.5902 2022/09/08 14:35:34 - mmengine - INFO - Epoch(train) [33][240/880] lr: 4.0111e-03 eta: 0:51:08 time: 0.4462 data_time: 0.0205 memory: 23498 grad_norm: 5.9859 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.6249 loss: 1.6249 2022/09/08 14:35:43 - mmengine - INFO - Epoch(train) [33][260/880] lr: 4.0111e-03 eta: 0:50:59 time: 0.4434 data_time: 0.0197 memory: 23498 grad_norm: 5.8793 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.4446 loss: 1.4446 2022/09/08 14:35:52 - mmengine - INFO - Epoch(train) [33][280/880] lr: 4.0111e-03 eta: 0:50:50 time: 0.4450 data_time: 0.0206 memory: 23498 grad_norm: 5.7232 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.5245 loss: 1.5245 2022/09/08 14:36:01 - mmengine - INFO - Epoch(train) [33][300/880] lr: 4.0111e-03 eta: 0:50:41 time: 0.4436 data_time: 0.0206 memory: 23498 grad_norm: 6.1065 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.4803 loss: 1.4803 2022/09/08 14:36:10 - mmengine - INFO - Epoch(train) [33][320/880] lr: 4.0111e-03 eta: 0:50:32 time: 0.4469 data_time: 0.0228 memory: 23498 grad_norm: 5.8104 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.5366 loss: 1.5366 2022/09/08 14:36:19 - mmengine - INFO - Epoch(train) [33][340/880] lr: 4.0111e-03 eta: 0:50:22 time: 0.4474 data_time: 0.0229 memory: 23498 grad_norm: 6.0650 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.5076 loss: 1.5076 2022/09/08 14:36:28 - mmengine - INFO - Epoch(train) [33][360/880] lr: 4.0111e-03 eta: 0:50:13 time: 0.4540 data_time: 0.0221 memory: 23498 grad_norm: 5.8760 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.4721 loss: 1.4721 2022/09/08 14:36:37 - mmengine - INFO - Epoch(train) [33][380/880] lr: 4.0111e-03 eta: 0:50:04 time: 0.4440 data_time: 0.0187 memory: 23498 grad_norm: 6.0927 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.6195 loss: 1.6195 2022/09/08 14:36:45 - mmengine - INFO - Epoch(train) [33][400/880] lr: 4.0111e-03 eta: 0:49:55 time: 0.4435 data_time: 0.0213 memory: 23498 grad_norm: 6.1298 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.5555 loss: 1.5555 2022/09/08 14:36:54 - mmengine - INFO - Epoch(train) [33][420/880] lr: 4.0111e-03 eta: 0:49:46 time: 0.4442 data_time: 0.0198 memory: 23498 grad_norm: 5.9119 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 1.3899 loss: 1.3899 2022/09/08 14:37:03 - mmengine - INFO - Epoch(train) [33][440/880] lr: 4.0111e-03 eta: 0:49:37 time: 0.4426 data_time: 0.0204 memory: 23498 grad_norm: 5.9196 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.5297 loss: 1.5297 2022/09/08 14:37:12 - mmengine - INFO - Epoch(train) [33][460/880] lr: 4.0111e-03 eta: 0:49:28 time: 0.4495 data_time: 0.0210 memory: 23498 grad_norm: 5.9687 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 1.4765 loss: 1.4765 2022/09/08 14:37:21 - mmengine - INFO - Epoch(train) [33][480/880] lr: 4.0111e-03 eta: 0:49:19 time: 0.4443 data_time: 0.0236 memory: 23498 grad_norm: 5.9087 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.5250 loss: 1.5250 2022/09/08 14:37:30 - mmengine - INFO - Epoch(train) [33][500/880] lr: 4.0111e-03 eta: 0:49:10 time: 0.4494 data_time: 0.0218 memory: 23498 grad_norm: 5.9721 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.6606 loss: 1.6606 2022/09/08 14:37:39 - mmengine - INFO - Epoch(train) [33][520/880] lr: 4.0111e-03 eta: 0:49:01 time: 0.4444 data_time: 0.0226 memory: 23498 grad_norm: 5.9060 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6278 loss: 1.6278 2022/09/08 14:37:48 - mmengine - INFO - Epoch(train) [33][540/880] lr: 4.0111e-03 eta: 0:48:52 time: 0.4429 data_time: 0.0182 memory: 23498 grad_norm: 6.0093 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.5179 loss: 1.5179 2022/09/08 14:37:57 - mmengine - INFO - Epoch(train) [33][560/880] lr: 4.0111e-03 eta: 0:48:43 time: 0.4439 data_time: 0.0226 memory: 23498 grad_norm: 6.0728 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.5340 loss: 1.5340 2022/09/08 14:38:06 - mmengine - INFO - Epoch(train) [33][580/880] lr: 4.0111e-03 eta: 0:48:34 time: 0.4479 data_time: 0.0213 memory: 23498 grad_norm: 5.9063 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4409 loss: 1.4409 2022/09/08 14:38:14 - mmengine - INFO - Epoch(train) [33][600/880] lr: 4.0111e-03 eta: 0:48:25 time: 0.4430 data_time: 0.0242 memory: 23498 grad_norm: 6.0194 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.4907 loss: 1.4907 2022/09/08 14:38:23 - mmengine - INFO - Epoch(train) [33][620/880] lr: 4.0111e-03 eta: 0:48:16 time: 0.4452 data_time: 0.0182 memory: 23498 grad_norm: 6.1279 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.5237 loss: 1.5237 2022/09/08 14:38:32 - mmengine - INFO - Epoch(train) [33][640/880] lr: 4.0111e-03 eta: 0:48:07 time: 0.4448 data_time: 0.0223 memory: 23498 grad_norm: 5.9146 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3912 loss: 1.3912 2022/09/08 14:38:41 - mmengine - INFO - Epoch(train) [33][660/880] lr: 4.0111e-03 eta: 0:47:58 time: 0.4462 data_time: 0.0212 memory: 23498 grad_norm: 5.9567 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.4474 loss: 1.4474 2022/09/08 14:38:50 - mmengine - INFO - Epoch(train) [33][680/880] lr: 4.0111e-03 eta: 0:47:49 time: 0.4413 data_time: 0.0210 memory: 23498 grad_norm: 6.1621 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.5132 loss: 1.5132 2022/09/08 14:38:59 - mmengine - INFO - Epoch(train) [33][700/880] lr: 4.0111e-03 eta: 0:47:40 time: 0.4478 data_time: 0.0187 memory: 23498 grad_norm: 5.9002 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.5194 loss: 1.5194 2022/09/08 14:39:08 - mmengine - INFO - Epoch(train) [33][720/880] lr: 4.0111e-03 eta: 0:47:31 time: 0.4430 data_time: 0.0226 memory: 23498 grad_norm: 5.9927 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.5464 loss: 1.5464 2022/09/08 14:39:17 - mmengine - INFO - Epoch(train) [33][740/880] lr: 4.0111e-03 eta: 0:47:21 time: 0.4421 data_time: 0.0190 memory: 23498 grad_norm: 5.9255 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.3605 loss: 1.3605 2022/09/08 14:39:26 - mmengine - INFO - Epoch(train) [33][760/880] lr: 4.0111e-03 eta: 0:47:12 time: 0.4461 data_time: 0.0211 memory: 23498 grad_norm: 6.4169 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.4539 loss: 1.4539 2022/09/08 14:39:35 - mmengine - INFO - Epoch(train) [33][780/880] lr: 4.0111e-03 eta: 0:47:03 time: 0.4442 data_time: 0.0204 memory: 23498 grad_norm: 6.0587 top1_acc: 0.4583 top5_acc: 0.7917 loss_cls: 1.5858 loss: 1.5858 2022/09/08 14:39:44 - mmengine - INFO - Epoch(train) [33][800/880] lr: 4.0111e-03 eta: 0:46:54 time: 0.4495 data_time: 0.0208 memory: 23498 grad_norm: 5.9633 top1_acc: 0.5417 top5_acc: 0.6250 loss_cls: 1.6075 loss: 1.6075 2022/09/08 14:39:52 - mmengine - INFO - Epoch(train) [33][820/880] lr: 4.0111e-03 eta: 0:46:45 time: 0.4441 data_time: 0.0209 memory: 23498 grad_norm: 5.8539 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.4741 loss: 1.4741 2022/09/08 14:40:01 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 14:40:01 - mmengine - INFO - Epoch(train) [33][840/880] lr: 4.0111e-03 eta: 0:46:36 time: 0.4460 data_time: 0.0242 memory: 23498 grad_norm: 5.9313 top1_acc: 0.4167 top5_acc: 0.6667 loss_cls: 1.5352 loss: 1.5352 2022/09/08 14:40:10 - mmengine - INFO - Epoch(train) [33][860/880] lr: 4.0111e-03 eta: 0:46:27 time: 0.4444 data_time: 0.0209 memory: 23498 grad_norm: 5.9593 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.4186 loss: 1.4186 2022/09/08 14:40:19 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 14:40:19 - mmengine - INFO - Epoch(train) [33][880/880] lr: 4.0111e-03 eta: 0:46:18 time: 0.4516 data_time: 0.0200 memory: 23498 grad_norm: 6.0160 top1_acc: 0.6316 top5_acc: 0.6842 loss_cls: 1.4635 loss: 1.4635 2022/09/08 14:40:30 - mmengine - INFO - Epoch(train) [34][20/880] lr: 3.0962e-03 eta: 0:46:09 time: 0.5228 data_time: 0.0833 memory: 23498 grad_norm: 5.8902 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.4557 loss: 1.4557 2022/09/08 14:40:39 - mmengine - INFO - Epoch(train) [34][40/880] lr: 3.0962e-03 eta: 0:46:00 time: 0.4610 data_time: 0.0222 memory: 23498 grad_norm: 5.9484 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.3220 loss: 1.3220 2022/09/08 14:40:48 - mmengine - INFO - Epoch(train) [34][60/880] lr: 3.0962e-03 eta: 0:45:51 time: 0.4466 data_time: 0.0200 memory: 23498 grad_norm: 6.0104 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.4493 loss: 1.4493 2022/09/08 14:40:57 - mmengine - INFO - Epoch(train) [34][80/880] lr: 3.0962e-03 eta: 0:45:42 time: 0.4469 data_time: 0.0233 memory: 23498 grad_norm: 6.0475 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 1.3904 loss: 1.3904 2022/09/08 14:41:06 - mmengine - INFO - Epoch(train) [34][100/880] lr: 3.0962e-03 eta: 0:45:33 time: 0.4491 data_time: 0.0183 memory: 23498 grad_norm: 5.9728 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.4268 loss: 1.4268 2022/09/08 14:41:15 - mmengine - INFO - Epoch(train) [34][120/880] lr: 3.0962e-03 eta: 0:45:24 time: 0.4449 data_time: 0.0194 memory: 23498 grad_norm: 5.8670 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.4952 loss: 1.4952 2022/09/08 14:41:24 - mmengine - INFO - Epoch(train) [34][140/880] lr: 3.0962e-03 eta: 0:45:15 time: 0.4450 data_time: 0.0200 memory: 23498 grad_norm: 5.9962 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4322 loss: 1.4322 2022/09/08 14:41:33 - mmengine - INFO - Epoch(train) [34][160/880] lr: 3.0962e-03 eta: 0:45:06 time: 0.4494 data_time: 0.0206 memory: 23498 grad_norm: 5.9617 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 1.3521 loss: 1.3521 2022/09/08 14:41:42 - mmengine - INFO - Epoch(train) [34][180/880] lr: 3.0962e-03 eta: 0:44:57 time: 0.4467 data_time: 0.0190 memory: 23498 grad_norm: 6.0590 top1_acc: 0.4583 top5_acc: 0.7083 loss_cls: 1.6072 loss: 1.6072 2022/09/08 14:41:50 - mmengine - INFO - Epoch(train) [34][200/880] lr: 3.0962e-03 eta: 0:44:48 time: 0.4472 data_time: 0.0213 memory: 23498 grad_norm: 6.0228 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.5421 loss: 1.5421 2022/09/08 14:41:59 - mmengine - INFO - Epoch(train) [34][220/880] lr: 3.0962e-03 eta: 0:44:39 time: 0.4480 data_time: 0.0175 memory: 23498 grad_norm: 5.9987 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.5632 loss: 1.5632 2022/09/08 14:42:08 - mmengine - INFO - Epoch(train) [34][240/880] lr: 3.0962e-03 eta: 0:44:30 time: 0.4461 data_time: 0.0236 memory: 23498 grad_norm: 6.0967 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.4330 loss: 1.4330 2022/09/08 14:42:18 - mmengine - INFO - Epoch(train) [34][260/880] lr: 3.0962e-03 eta: 0:44:21 time: 0.4598 data_time: 0.0192 memory: 23498 grad_norm: 5.9758 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4494 loss: 1.4494 2022/09/08 14:42:27 - mmengine - INFO - Epoch(train) [34][280/880] lr: 3.0962e-03 eta: 0:44:12 time: 0.4541 data_time: 0.0261 memory: 23498 grad_norm: 6.1449 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.4503 loss: 1.4503 2022/09/08 14:42:36 - mmengine - INFO - Epoch(train) [34][300/880] lr: 3.0962e-03 eta: 0:44:03 time: 0.4604 data_time: 0.0194 memory: 23498 grad_norm: 6.2488 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3778 loss: 1.3778 2022/09/08 14:42:45 - mmengine - INFO - Epoch(train) [34][320/880] lr: 3.0962e-03 eta: 0:43:54 time: 0.4539 data_time: 0.0235 memory: 23498 grad_norm: 6.2958 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.5440 loss: 1.5440 2022/09/08 14:42:54 - mmengine - INFO - Epoch(train) [34][340/880] lr: 3.0962e-03 eta: 0:43:45 time: 0.4487 data_time: 0.0206 memory: 23498 grad_norm: 6.0061 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.4276 loss: 1.4276 2022/09/08 14:43:03 - mmengine - INFO - Epoch(train) [34][360/880] lr: 3.0962e-03 eta: 0:43:36 time: 0.4464 data_time: 0.0220 memory: 23498 grad_norm: 6.1494 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3466 loss: 1.3466 2022/09/08 14:43:12 - mmengine - INFO - Epoch(train) [34][380/880] lr: 3.0962e-03 eta: 0:43:27 time: 0.4668 data_time: 0.0209 memory: 23498 grad_norm: 6.1973 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.2977 loss: 1.2977 2022/09/08 14:43:21 - mmengine - INFO - Epoch(train) [34][400/880] lr: 3.0962e-03 eta: 0:43:18 time: 0.4454 data_time: 0.0230 memory: 23498 grad_norm: 6.3154 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.5291 loss: 1.5291 2022/09/08 14:43:30 - mmengine - INFO - Epoch(train) [34][420/880] lr: 3.0962e-03 eta: 0:43:09 time: 0.4529 data_time: 0.0204 memory: 23498 grad_norm: 5.9961 top1_acc: 0.4167 top5_acc: 0.7917 loss_cls: 1.5584 loss: 1.5584 2022/09/08 14:43:39 - mmengine - INFO - Epoch(train) [34][440/880] lr: 3.0962e-03 eta: 0:43:00 time: 0.4431 data_time: 0.0223 memory: 23498 grad_norm: 6.1648 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.5894 loss: 1.5894 2022/09/08 14:43:48 - mmengine - INFO - Epoch(train) [34][460/880] lr: 3.0962e-03 eta: 0:42:51 time: 0.4467 data_time: 0.0208 memory: 23498 grad_norm: 6.1673 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.3945 loss: 1.3945 2022/09/08 14:43:57 - mmengine - INFO - Epoch(train) [34][480/880] lr: 3.0962e-03 eta: 0:42:42 time: 0.4502 data_time: 0.0222 memory: 23498 grad_norm: 6.2567 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 1.5774 loss: 1.5774 2022/09/08 14:44:06 - mmengine - INFO - Epoch(train) [34][500/880] lr: 3.0962e-03 eta: 0:42:33 time: 0.4648 data_time: 0.0199 memory: 23498 grad_norm: 6.2306 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.5671 loss: 1.5671 2022/09/08 14:44:15 - mmengine - INFO - Epoch(train) [34][520/880] lr: 3.0962e-03 eta: 0:42:24 time: 0.4461 data_time: 0.0209 memory: 23498 grad_norm: 6.2243 top1_acc: 0.7083 top5_acc: 1.0000 loss_cls: 1.4157 loss: 1.4157 2022/09/08 14:44:24 - mmengine - INFO - Epoch(train) [34][540/880] lr: 3.0962e-03 eta: 0:42:15 time: 0.4465 data_time: 0.0187 memory: 23498 grad_norm: 6.3693 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.4767 loss: 1.4767 2022/09/08 14:44:33 - mmengine - INFO - Epoch(train) [34][560/880] lr: 3.0962e-03 eta: 0:42:06 time: 0.4456 data_time: 0.0229 memory: 23498 grad_norm: 6.0100 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.5249 loss: 1.5249 2022/09/08 14:44:42 - mmengine - INFO - Epoch(train) [34][580/880] lr: 3.0962e-03 eta: 0:41:57 time: 0.4534 data_time: 0.0208 memory: 23498 grad_norm: 6.1673 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.4616 loss: 1.4616 2022/09/08 14:44:51 - mmengine - INFO - Epoch(train) [34][600/880] lr: 3.0962e-03 eta: 0:41:48 time: 0.4473 data_time: 0.0214 memory: 23498 grad_norm: 6.0465 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3496 loss: 1.3496 2022/09/08 14:45:00 - mmengine - INFO - Epoch(train) [34][620/880] lr: 3.0962e-03 eta: 0:41:39 time: 0.4625 data_time: 0.0254 memory: 23498 grad_norm: 6.2244 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.5581 loss: 1.5581 2022/09/08 14:45:09 - mmengine - INFO - Epoch(train) [34][640/880] lr: 3.0962e-03 eta: 0:41:30 time: 0.4500 data_time: 0.0292 memory: 23498 grad_norm: 6.2517 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.5850 loss: 1.5850 2022/09/08 14:45:18 - mmengine - INFO - Epoch(train) [34][660/880] lr: 3.0962e-03 eta: 0:41:21 time: 0.4477 data_time: 0.0204 memory: 23498 grad_norm: 6.1741 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.5743 loss: 1.5743 2022/09/08 14:45:27 - mmengine - INFO - Epoch(train) [34][680/880] lr: 3.0962e-03 eta: 0:41:12 time: 0.4466 data_time: 0.0237 memory: 23498 grad_norm: 6.2629 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.4815 loss: 1.4815 2022/09/08 14:45:36 - mmengine - INFO - Epoch(train) [34][700/880] lr: 3.0962e-03 eta: 0:41:03 time: 0.4459 data_time: 0.0207 memory: 23498 grad_norm: 6.2441 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.4193 loss: 1.4193 2022/09/08 14:45:45 - mmengine - INFO - Epoch(train) [34][720/880] lr: 3.0962e-03 eta: 0:40:54 time: 0.4440 data_time: 0.0219 memory: 23498 grad_norm: 6.2308 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.4074 loss: 1.4074 2022/09/08 14:45:54 - mmengine - INFO - Epoch(train) [34][740/880] lr: 3.0962e-03 eta: 0:40:45 time: 0.4416 data_time: 0.0217 memory: 23498 grad_norm: 6.1978 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5691 loss: 1.5691 2022/09/08 14:46:03 - mmengine - INFO - Epoch(train) [34][760/880] lr: 3.0962e-03 eta: 0:40:35 time: 0.4468 data_time: 0.0270 memory: 23498 grad_norm: 6.2936 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.4986 loss: 1.4986 2022/09/08 14:46:12 - mmengine - INFO - Epoch(train) [34][780/880] lr: 3.0962e-03 eta: 0:40:26 time: 0.4434 data_time: 0.0213 memory: 23498 grad_norm: 6.2796 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.5052 loss: 1.5052 2022/09/08 14:46:21 - mmengine - INFO - Epoch(train) [34][800/880] lr: 3.0962e-03 eta: 0:40:17 time: 0.4529 data_time: 0.0216 memory: 23498 grad_norm: 6.1086 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.3196 loss: 1.3196 2022/09/08 14:46:30 - mmengine - INFO - Epoch(train) [34][820/880] lr: 3.0962e-03 eta: 0:40:08 time: 0.4410 data_time: 0.0206 memory: 23498 grad_norm: 6.5794 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 1.5388 loss: 1.5388 2022/09/08 14:46:38 - mmengine - INFO - Epoch(train) [34][840/880] lr: 3.0962e-03 eta: 0:39:59 time: 0.4439 data_time: 0.0233 memory: 23498 grad_norm: 6.1562 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.4288 loss: 1.4288 2022/09/08 14:46:47 - mmengine - INFO - Epoch(train) [34][860/880] lr: 3.0962e-03 eta: 0:39:50 time: 0.4465 data_time: 0.0273 memory: 23498 grad_norm: 6.3984 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4976 loss: 1.4976 2022/09/08 14:46:56 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 14:46:56 - mmengine - INFO - Epoch(train) [34][880/880] lr: 3.0962e-03 eta: 0:39:41 time: 0.4312 data_time: 0.0208 memory: 23498 grad_norm: 6.4005 top1_acc: 0.3684 top5_acc: 0.7368 loss_cls: 1.3703 loss: 1.3703 2022/09/08 14:47:01 - mmengine - INFO - Epoch(val) [34][20/130] eta: 0:00:25 time: 0.2286 data_time: 0.0909 memory: 2693 2022/09/08 14:47:04 - mmengine - INFO - Epoch(val) [34][40/130] eta: 0:00:14 time: 0.1629 data_time: 0.0251 memory: 2693 2022/09/08 14:47:07 - mmengine - INFO - Epoch(val) [34][60/130] eta: 0:00:11 time: 0.1671 data_time: 0.0311 memory: 2693 2022/09/08 14:47:10 - mmengine - INFO - Epoch(val) [34][80/130] eta: 0:00:08 time: 0.1643 data_time: 0.0275 memory: 2693 2022/09/08 14:47:14 - mmengine - INFO - Epoch(val) [34][100/130] eta: 0:00:05 time: 0.1692 data_time: 0.0339 memory: 2693 2022/09/08 14:47:17 - mmengine - INFO - Epoch(val) [34][120/130] eta: 0:00:01 time: 0.1589 data_time: 0.0264 memory: 2693 2022/09/08 14:47:19 - mmengine - INFO - Epoch(val) [34][130/130] acc/top1: 0.5206 acc/top5: 0.8018 acc/mean1: 0.4546 2022/09/08 14:47:20 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4/best_acc/top1_epoch_32.pth is removed 2022/09/08 14:47:22 - mmengine - INFO - The best checkpoint with 0.5206 acc/top1 at 34 epoch is saved to best_acc/top1_epoch_34.pth. 2022/09/08 14:47:32 - mmengine - INFO - Epoch(train) [35][20/880] lr: 2.2909e-03 eta: 0:39:32 time: 0.4853 data_time: 0.0563 memory: 23498 grad_norm: 6.2404 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.3964 loss: 1.3964 2022/09/08 14:47:41 - mmengine - INFO - Epoch(train) [35][40/880] lr: 2.2909e-03 eta: 0:39:23 time: 0.4744 data_time: 0.0280 memory: 23498 grad_norm: 6.3556 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.3650 loss: 1.3650 2022/09/08 14:47:50 - mmengine - INFO - Epoch(train) [35][60/880] lr: 2.2909e-03 eta: 0:39:14 time: 0.4488 data_time: 0.0218 memory: 23498 grad_norm: 6.1477 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.4143 loss: 1.4143 2022/09/08 14:47:59 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 14:47:59 - mmengine - INFO - Epoch(train) [35][80/880] lr: 2.2909e-03 eta: 0:39:05 time: 0.4470 data_time: 0.0214 memory: 23498 grad_norm: 6.2714 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.2899 loss: 1.2899 2022/09/08 14:48:08 - mmengine - INFO - Epoch(train) [35][100/880] lr: 2.2909e-03 eta: 0:38:56 time: 0.4461 data_time: 0.0200 memory: 23498 grad_norm: 6.3675 top1_acc: 0.4167 top5_acc: 0.7500 loss_cls: 1.3975 loss: 1.3975 2022/09/08 14:48:17 - mmengine - INFO - Epoch(train) [35][120/880] lr: 2.2909e-03 eta: 0:38:47 time: 0.4459 data_time: 0.0206 memory: 23498 grad_norm: 6.3042 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3550 loss: 1.3550 2022/09/08 14:48:26 - mmengine - INFO - Epoch(train) [35][140/880] lr: 2.2909e-03 eta: 0:38:38 time: 0.4448 data_time: 0.0191 memory: 23498 grad_norm: 6.1859 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.4801 loss: 1.4801 2022/09/08 14:48:35 - mmengine - INFO - Epoch(train) [35][160/880] lr: 2.2909e-03 eta: 0:38:29 time: 0.4540 data_time: 0.0222 memory: 23498 grad_norm: 6.4131 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.3075 loss: 1.3075 2022/09/08 14:48:44 - mmengine - INFO - Epoch(train) [35][180/880] lr: 2.2909e-03 eta: 0:38:20 time: 0.4528 data_time: 0.0185 memory: 23498 grad_norm: 6.3911 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.5208 loss: 1.5208 2022/09/08 14:48:53 - mmengine - INFO - Epoch(train) [35][200/880] lr: 2.2909e-03 eta: 0:38:11 time: 0.4486 data_time: 0.0208 memory: 23498 grad_norm: 6.3727 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3882 loss: 1.3882 2022/09/08 14:49:02 - mmengine - INFO - Epoch(train) [35][220/880] lr: 2.2909e-03 eta: 0:38:02 time: 0.4477 data_time: 0.0197 memory: 23498 grad_norm: 6.3970 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.3735 loss: 1.3735 2022/09/08 14:49:11 - mmengine - INFO - Epoch(train) [35][240/880] lr: 2.2909e-03 eta: 0:37:53 time: 0.4454 data_time: 0.0223 memory: 23498 grad_norm: 6.4619 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.3715 loss: 1.3715 2022/09/08 14:49:20 - mmengine - INFO - Epoch(train) [35][260/880] lr: 2.2909e-03 eta: 0:37:44 time: 0.4450 data_time: 0.0189 memory: 23498 grad_norm: 6.5226 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.4277 loss: 1.4277 2022/09/08 14:49:29 - mmengine - INFO - Epoch(train) [35][280/880] lr: 2.2909e-03 eta: 0:37:35 time: 0.4474 data_time: 0.0233 memory: 23498 grad_norm: 6.5014 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.5302 loss: 1.5302 2022/09/08 14:49:38 - mmengine - INFO - Epoch(train) [35][300/880] lr: 2.2909e-03 eta: 0:37:26 time: 0.4490 data_time: 0.0200 memory: 23498 grad_norm: 6.3362 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.3325 loss: 1.3325 2022/09/08 14:49:47 - mmengine - INFO - Epoch(train) [35][320/880] lr: 2.2909e-03 eta: 0:37:17 time: 0.4475 data_time: 0.0233 memory: 23498 grad_norm: 6.3864 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.3231 loss: 1.3231 2022/09/08 14:49:56 - mmengine - INFO - Epoch(train) [35][340/880] lr: 2.2909e-03 eta: 0:37:08 time: 0.4501 data_time: 0.0199 memory: 23498 grad_norm: 6.5009 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.3890 loss: 1.3890 2022/09/08 14:50:05 - mmengine - INFO - Epoch(train) [35][360/880] lr: 2.2909e-03 eta: 0:36:59 time: 0.4455 data_time: 0.0224 memory: 23498 grad_norm: 6.3611 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.4290 loss: 1.4290 2022/09/08 14:50:14 - mmengine - INFO - Epoch(train) [35][380/880] lr: 2.2909e-03 eta: 0:36:50 time: 0.4523 data_time: 0.0185 memory: 23498 grad_norm: 6.3679 top1_acc: 0.4167 top5_acc: 0.8333 loss_cls: 1.4702 loss: 1.4702 2022/09/08 14:50:23 - mmengine - INFO - Epoch(train) [35][400/880] lr: 2.2909e-03 eta: 0:36:41 time: 0.4489 data_time: 0.0203 memory: 23498 grad_norm: 6.6664 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.4924 loss: 1.4924 2022/09/08 14:50:32 - mmengine - INFO - Epoch(train) [35][420/880] lr: 2.2909e-03 eta: 0:36:32 time: 0.4573 data_time: 0.0191 memory: 23498 grad_norm: 6.4659 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.3349 loss: 1.3349 2022/09/08 14:50:41 - mmengine - INFO - Epoch(train) [35][440/880] lr: 2.2909e-03 eta: 0:36:23 time: 0.4520 data_time: 0.0210 memory: 23498 grad_norm: 6.3704 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4260 loss: 1.4260 2022/09/08 14:50:50 - mmengine - INFO - Epoch(train) [35][460/880] lr: 2.2909e-03 eta: 0:36:14 time: 0.4719 data_time: 0.0215 memory: 23498 grad_norm: 6.3917 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.4101 loss: 1.4101 2022/09/08 14:50:59 - mmengine - INFO - Epoch(train) [35][480/880] lr: 2.2909e-03 eta: 0:36:05 time: 0.4527 data_time: 0.0251 memory: 23498 grad_norm: 6.5914 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.3767 loss: 1.3767 2022/09/08 14:51:08 - mmengine - INFO - Epoch(train) [35][500/880] lr: 2.2909e-03 eta: 0:35:56 time: 0.4518 data_time: 0.0193 memory: 23498 grad_norm: 6.5104 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.5056 loss: 1.5056 2022/09/08 14:51:17 - mmengine - INFO - Epoch(train) [35][520/880] lr: 2.2909e-03 eta: 0:35:47 time: 0.4509 data_time: 0.0203 memory: 23498 grad_norm: 6.6208 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.3270 loss: 1.3270 2022/09/08 14:51:26 - mmengine - INFO - Epoch(train) [35][540/880] lr: 2.2909e-03 eta: 0:35:38 time: 0.4527 data_time: 0.0194 memory: 23498 grad_norm: 6.5447 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.3632 loss: 1.3632 2022/09/08 14:51:35 - mmengine - INFO - Epoch(train) [35][560/880] lr: 2.2909e-03 eta: 0:35:29 time: 0.4508 data_time: 0.0208 memory: 23498 grad_norm: 6.4829 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.3699 loss: 1.3699 2022/09/08 14:51:45 - mmengine - INFO - Epoch(train) [35][580/880] lr: 2.2909e-03 eta: 0:35:20 time: 0.4663 data_time: 0.0197 memory: 23498 grad_norm: 6.4597 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.5013 loss: 1.5013 2022/09/08 14:51:54 - mmengine - INFO - Epoch(train) [35][600/880] lr: 2.2909e-03 eta: 0:35:11 time: 0.4496 data_time: 0.0229 memory: 23498 grad_norm: 6.5465 top1_acc: 0.6667 top5_acc: 0.9583 loss_cls: 1.3704 loss: 1.3704 2022/09/08 14:52:03 - mmengine - INFO - Epoch(train) [35][620/880] lr: 2.2909e-03 eta: 0:35:02 time: 0.4539 data_time: 0.0248 memory: 23498 grad_norm: 6.5900 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.4765 loss: 1.4765 2022/09/08 14:52:12 - mmengine - INFO - Epoch(train) [35][640/880] lr: 2.2909e-03 eta: 0:34:53 time: 0.4502 data_time: 0.0241 memory: 23498 grad_norm: 6.4925 top1_acc: 0.4583 top5_acc: 0.7500 loss_cls: 1.3551 loss: 1.3551 2022/09/08 14:52:21 - mmengine - INFO - Epoch(train) [35][660/880] lr: 2.2909e-03 eta: 0:34:44 time: 0.4507 data_time: 0.0217 memory: 23498 grad_norm: 6.4265 top1_acc: 0.8333 top5_acc: 0.9583 loss_cls: 1.4005 loss: 1.4005 2022/09/08 14:52:30 - mmengine - INFO - Epoch(train) [35][680/880] lr: 2.2909e-03 eta: 0:34:35 time: 0.4500 data_time: 0.0211 memory: 23498 grad_norm: 6.6377 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4344 loss: 1.4344 2022/09/08 14:52:39 - mmengine - INFO - Epoch(train) [35][700/880] lr: 2.2909e-03 eta: 0:34:26 time: 0.4497 data_time: 0.0219 memory: 23498 grad_norm: 6.5491 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.4834 loss: 1.4834 2022/09/08 14:52:48 - mmengine - INFO - Epoch(train) [35][720/880] lr: 2.2909e-03 eta: 0:34:17 time: 0.4555 data_time: 0.0186 memory: 23498 grad_norm: 6.5959 top1_acc: 0.7500 top5_acc: 0.7917 loss_cls: 1.3682 loss: 1.3682 2022/09/08 14:52:57 - mmengine - INFO - Epoch(train) [35][740/880] lr: 2.2909e-03 eta: 0:34:08 time: 0.4501 data_time: 0.0178 memory: 23498 grad_norm: 6.5114 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3763 loss: 1.3763 2022/09/08 14:53:06 - mmengine - INFO - Epoch(train) [35][760/880] lr: 2.2909e-03 eta: 0:33:58 time: 0.4440 data_time: 0.0214 memory: 23498 grad_norm: 6.4930 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.4823 loss: 1.4823 2022/09/08 14:53:15 - mmengine - INFO - Epoch(train) [35][780/880] lr: 2.2909e-03 eta: 0:33:49 time: 0.4485 data_time: 0.0207 memory: 23498 grad_norm: 6.3877 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.4347 loss: 1.4347 2022/09/08 14:53:24 - mmengine - INFO - Epoch(train) [35][800/880] lr: 2.2909e-03 eta: 0:33:40 time: 0.4484 data_time: 0.0203 memory: 23498 grad_norm: 6.4542 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4111 loss: 1.4111 2022/09/08 14:53:33 - mmengine - INFO - Epoch(train) [35][820/880] lr: 2.2909e-03 eta: 0:33:31 time: 0.4507 data_time: 0.0194 memory: 23498 grad_norm: 6.5725 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.3439 loss: 1.3439 2022/09/08 14:53:42 - mmengine - INFO - Epoch(train) [35][840/880] lr: 2.2909e-03 eta: 0:33:22 time: 0.4484 data_time: 0.0212 memory: 23498 grad_norm: 6.6103 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.4258 loss: 1.4258 2022/09/08 14:53:51 - mmengine - INFO - Epoch(train) [35][860/880] lr: 2.2909e-03 eta: 0:33:13 time: 0.4495 data_time: 0.0196 memory: 23498 grad_norm: 6.6356 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.4535 loss: 1.4535 2022/09/08 14:54:00 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 14:54:00 - mmengine - INFO - Epoch(train) [35][880/880] lr: 2.2909e-03 eta: 0:33:04 time: 0.4379 data_time: 0.0189 memory: 23498 grad_norm: 6.5464 top1_acc: 0.5789 top5_acc: 0.8947 loss_cls: 1.3521 loss: 1.3521 2022/09/08 14:54:10 - mmengine - INFO - Epoch(train) [36][20/880] lr: 1.6004e-03 eta: 0:32:55 time: 0.5226 data_time: 0.0894 memory: 23498 grad_norm: 6.3428 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.4798 loss: 1.4798 2022/09/08 14:54:19 - mmengine - INFO - Epoch(train) [36][40/880] lr: 1.6004e-03 eta: 0:32:46 time: 0.4490 data_time: 0.0233 memory: 23498 grad_norm: 6.3611 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.2518 loss: 1.2518 2022/09/08 14:54:28 - mmengine - INFO - Epoch(train) [36][60/880] lr: 1.6004e-03 eta: 0:32:37 time: 0.4487 data_time: 0.0218 memory: 23498 grad_norm: 6.5942 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4454 loss: 1.4454 2022/09/08 14:54:37 - mmengine - INFO - Epoch(train) [36][80/880] lr: 1.6004e-03 eta: 0:32:28 time: 0.4519 data_time: 0.0201 memory: 23498 grad_norm: 6.3516 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.4137 loss: 1.4137 2022/09/08 14:54:46 - mmengine - INFO - Epoch(train) [36][100/880] lr: 1.6004e-03 eta: 0:32:19 time: 0.4510 data_time: 0.0234 memory: 23498 grad_norm: 6.2793 top1_acc: 0.7500 top5_acc: 0.7917 loss_cls: 1.3749 loss: 1.3749 2022/09/08 14:54:55 - mmengine - INFO - Epoch(train) [36][120/880] lr: 1.6004e-03 eta: 0:32:10 time: 0.4446 data_time: 0.0199 memory: 23498 grad_norm: 6.3456 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4122 loss: 1.4122 2022/09/08 14:55:04 - mmengine - INFO - Epoch(train) [36][140/880] lr: 1.6004e-03 eta: 0:32:01 time: 0.4482 data_time: 0.0227 memory: 23498 grad_norm: 6.3994 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.4613 loss: 1.4613 2022/09/08 14:55:13 - mmengine - INFO - Epoch(train) [36][160/880] lr: 1.6004e-03 eta: 0:31:52 time: 0.4599 data_time: 0.0203 memory: 23498 grad_norm: 6.3933 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.3430 loss: 1.3430 2022/09/08 14:55:22 - mmengine - INFO - Epoch(train) [36][180/880] lr: 1.6004e-03 eta: 0:31:43 time: 0.4478 data_time: 0.0253 memory: 23498 grad_norm: 6.3764 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.3382 loss: 1.3382 2022/09/08 14:55:31 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 14:55:31 - mmengine - INFO - Epoch(train) [36][200/880] lr: 1.6004e-03 eta: 0:31:34 time: 0.4454 data_time: 0.0210 memory: 23498 grad_norm: 6.5367 top1_acc: 0.6667 top5_acc: 0.7500 loss_cls: 1.3500 loss: 1.3500 2022/09/08 14:55:40 - mmengine - INFO - Epoch(train) [36][220/880] lr: 1.6004e-03 eta: 0:31:25 time: 0.4464 data_time: 0.0225 memory: 23498 grad_norm: 6.6563 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.3887 loss: 1.3887 2022/09/08 14:55:49 - mmengine - INFO - Epoch(train) [36][240/880] lr: 1.6004e-03 eta: 0:31:16 time: 0.4428 data_time: 0.0207 memory: 23498 grad_norm: 6.4967 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.4523 loss: 1.4523 2022/09/08 14:55:58 - mmengine - INFO - Epoch(train) [36][260/880] lr: 1.6004e-03 eta: 0:31:07 time: 0.4433 data_time: 0.0230 memory: 23498 grad_norm: 6.6796 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.3889 loss: 1.3889 2022/09/08 14:56:07 - mmengine - INFO - Epoch(train) [36][280/880] lr: 1.6004e-03 eta: 0:30:58 time: 0.4423 data_time: 0.0197 memory: 23498 grad_norm: 6.5424 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.3383 loss: 1.3383 2022/09/08 14:56:15 - mmengine - INFO - Epoch(train) [36][300/880] lr: 1.6004e-03 eta: 0:30:49 time: 0.4450 data_time: 0.0225 memory: 23498 grad_norm: 6.6152 top1_acc: 0.9583 top5_acc: 0.9583 loss_cls: 1.5345 loss: 1.5345 2022/09/08 14:56:24 - mmengine - INFO - Epoch(train) [36][320/880] lr: 1.6004e-03 eta: 0:30:40 time: 0.4430 data_time: 0.0201 memory: 23498 grad_norm: 6.6014 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.3634 loss: 1.3634 2022/09/08 14:56:33 - mmengine - INFO - Epoch(train) [36][340/880] lr: 1.6004e-03 eta: 0:30:31 time: 0.4445 data_time: 0.0219 memory: 23498 grad_norm: 6.4526 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.4552 loss: 1.4552 2022/09/08 14:56:42 - mmengine - INFO - Epoch(train) [36][360/880] lr: 1.6004e-03 eta: 0:30:22 time: 0.4465 data_time: 0.0208 memory: 23498 grad_norm: 6.7303 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.3656 loss: 1.3656 2022/09/08 14:56:51 - mmengine - INFO - Epoch(train) [36][380/880] lr: 1.6004e-03 eta: 0:30:13 time: 0.4501 data_time: 0.0214 memory: 23498 grad_norm: 6.5135 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 1.2663 loss: 1.2663 2022/09/08 14:57:00 - mmengine - INFO - Epoch(train) [36][400/880] lr: 1.6004e-03 eta: 0:30:04 time: 0.4484 data_time: 0.0223 memory: 23498 grad_norm: 6.5352 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.2064 loss: 1.2064 2022/09/08 14:57:09 - mmengine - INFO - Epoch(train) [36][420/880] lr: 1.6004e-03 eta: 0:29:55 time: 0.4432 data_time: 0.0205 memory: 23498 grad_norm: 6.4580 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.2574 loss: 1.2574 2022/09/08 14:57:18 - mmengine - INFO - Epoch(train) [36][440/880] lr: 1.6004e-03 eta: 0:29:46 time: 0.4476 data_time: 0.0250 memory: 23498 grad_norm: 6.6597 top1_acc: 0.9167 top5_acc: 0.9583 loss_cls: 1.1998 loss: 1.1998 2022/09/08 14:57:27 - mmengine - INFO - Epoch(train) [36][460/880] lr: 1.6004e-03 eta: 0:29:37 time: 0.4454 data_time: 0.0184 memory: 23498 grad_norm: 6.3777 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.2990 loss: 1.2990 2022/09/08 14:57:36 - mmengine - INFO - Epoch(train) [36][480/880] lr: 1.6004e-03 eta: 0:29:28 time: 0.4444 data_time: 0.0234 memory: 23498 grad_norm: 6.4900 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3342 loss: 1.3342 2022/09/08 14:57:45 - mmengine - INFO - Epoch(train) [36][500/880] lr: 1.6004e-03 eta: 0:29:19 time: 0.4454 data_time: 0.0200 memory: 23498 grad_norm: 6.3898 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.3959 loss: 1.3959 2022/09/08 14:57:54 - mmengine - INFO - Epoch(train) [36][520/880] lr: 1.6004e-03 eta: 0:29:10 time: 0.4425 data_time: 0.0232 memory: 23498 grad_norm: 6.4735 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.3851 loss: 1.3851 2022/09/08 14:58:02 - mmengine - INFO - Epoch(train) [36][540/880] lr: 1.6004e-03 eta: 0:29:01 time: 0.4453 data_time: 0.0209 memory: 23498 grad_norm: 6.4168 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2339 loss: 1.2339 2022/09/08 14:58:11 - mmengine - INFO - Epoch(train) [36][560/880] lr: 1.6004e-03 eta: 0:28:52 time: 0.4425 data_time: 0.0214 memory: 23498 grad_norm: 6.6397 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 1.2130 loss: 1.2130 2022/09/08 14:58:20 - mmengine - INFO - Epoch(train) [36][580/880] lr: 1.6004e-03 eta: 0:28:43 time: 0.4473 data_time: 0.0203 memory: 23498 grad_norm: 6.5592 top1_acc: 0.5417 top5_acc: 0.9583 loss_cls: 1.2570 loss: 1.2570 2022/09/08 14:58:29 - mmengine - INFO - Epoch(train) [36][600/880] lr: 1.6004e-03 eta: 0:28:33 time: 0.4441 data_time: 0.0231 memory: 23498 grad_norm: 6.6615 top1_acc: 0.5833 top5_acc: 0.9583 loss_cls: 1.2611 loss: 1.2611 2022/09/08 14:58:38 - mmengine - INFO - Epoch(train) [36][620/880] lr: 1.6004e-03 eta: 0:28:24 time: 0.4456 data_time: 0.0209 memory: 23498 grad_norm: 6.6827 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.2962 loss: 1.2962 2022/09/08 14:58:47 - mmengine - INFO - Epoch(train) [36][640/880] lr: 1.6004e-03 eta: 0:28:15 time: 0.4454 data_time: 0.0260 memory: 23498 grad_norm: 6.7800 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5901 loss: 1.5901 2022/09/08 14:58:56 - mmengine - INFO - Epoch(train) [36][660/880] lr: 1.6004e-03 eta: 0:28:06 time: 0.4464 data_time: 0.0187 memory: 23498 grad_norm: 6.6468 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 1.3329 loss: 1.3329 2022/09/08 14:59:05 - mmengine - INFO - Epoch(train) [36][680/880] lr: 1.6004e-03 eta: 0:27:57 time: 0.4473 data_time: 0.0240 memory: 23498 grad_norm: 6.7423 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.4048 loss: 1.4048 2022/09/08 14:59:14 - mmengine - INFO - Epoch(train) [36][700/880] lr: 1.6004e-03 eta: 0:27:48 time: 0.4532 data_time: 0.0224 memory: 23498 grad_norm: 6.6239 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.3334 loss: 1.3334 2022/09/08 14:59:23 - mmengine - INFO - Epoch(train) [36][720/880] lr: 1.6004e-03 eta: 0:27:39 time: 0.4519 data_time: 0.0272 memory: 23498 grad_norm: 6.8405 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.4037 loss: 1.4037 2022/09/08 14:59:32 - mmengine - INFO - Epoch(train) [36][740/880] lr: 1.6004e-03 eta: 0:27:30 time: 0.4474 data_time: 0.0212 memory: 23498 grad_norm: 6.6599 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.3762 loss: 1.3762 2022/09/08 14:59:41 - mmengine - INFO - Epoch(train) [36][760/880] lr: 1.6004e-03 eta: 0:27:21 time: 0.4514 data_time: 0.0251 memory: 23498 grad_norm: 6.8855 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.3379 loss: 1.3379 2022/09/08 14:59:50 - mmengine - INFO - Epoch(train) [36][780/880] lr: 1.6004e-03 eta: 0:27:12 time: 0.4478 data_time: 0.0205 memory: 23498 grad_norm: 6.7345 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.4447 loss: 1.4447 2022/09/08 14:59:59 - mmengine - INFO - Epoch(train) [36][800/880] lr: 1.6004e-03 eta: 0:27:03 time: 0.4504 data_time: 0.0252 memory: 23498 grad_norm: 6.6207 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.4118 loss: 1.4118 2022/09/08 15:00:08 - mmengine - INFO - Epoch(train) [36][820/880] lr: 1.6004e-03 eta: 0:26:54 time: 0.4476 data_time: 0.0196 memory: 23498 grad_norm: 6.6034 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.2726 loss: 1.2726 2022/09/08 15:00:17 - mmengine - INFO - Epoch(train) [36][840/880] lr: 1.6004e-03 eta: 0:26:45 time: 0.4470 data_time: 0.0229 memory: 23498 grad_norm: 6.7690 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.3066 loss: 1.3066 2022/09/08 15:00:26 - mmengine - INFO - Epoch(train) [36][860/880] lr: 1.6004e-03 eta: 0:26:36 time: 0.4474 data_time: 0.0211 memory: 23498 grad_norm: 6.7766 top1_acc: 0.5417 top5_acc: 0.9167 loss_cls: 1.4802 loss: 1.4802 2022/09/08 15:00:35 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 15:00:35 - mmengine - INFO - Epoch(train) [36][880/880] lr: 1.6004e-03 eta: 0:26:27 time: 0.4470 data_time: 0.0267 memory: 23498 grad_norm: 6.7943 top1_acc: 0.6842 top5_acc: 0.7895 loss_cls: 1.3690 loss: 1.3690 2022/09/08 15:00:39 - mmengine - INFO - Epoch(val) [36][20/130] eta: 0:00:24 time: 0.2205 data_time: 0.0839 memory: 2693 2022/09/08 15:00:42 - mmengine - INFO - Epoch(val) [36][40/130] eta: 0:00:14 time: 0.1634 data_time: 0.0283 memory: 2693 2022/09/08 15:00:46 - mmengine - INFO - Epoch(val) [36][60/130] eta: 0:00:11 time: 0.1682 data_time: 0.0312 memory: 2693 2022/09/08 15:00:49 - mmengine - INFO - Epoch(val) [36][80/130] eta: 0:00:08 time: 0.1663 data_time: 0.0278 memory: 2693 2022/09/08 15:00:52 - mmengine - INFO - Epoch(val) [36][100/130] eta: 0:00:05 time: 0.1699 data_time: 0.0329 memory: 2693 2022/09/08 15:00:56 - mmengine - INFO - Epoch(val) [36][120/130] eta: 0:00:01 time: 0.1594 data_time: 0.0264 memory: 2693 2022/09/08 15:00:58 - mmengine - INFO - Epoch(val) [36][130/130] acc/top1: 0.5434 acc/top5: 0.8162 acc/mean1: 0.4665 2022/09/08 15:00:58 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4/best_acc/top1_epoch_34.pth is removed 2022/09/08 15:00:59 - mmengine - INFO - The best checkpoint with 0.5434 acc/top1 at 36 epoch is saved to best_acc/top1_epoch_36.pth. 2022/09/08 15:01:09 - mmengine - INFO - Epoch(train) [37][20/880] lr: 1.0293e-03 eta: 0:26:18 time: 0.4957 data_time: 0.0690 memory: 23498 grad_norm: 6.8341 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.3849 loss: 1.3849 2022/09/08 15:01:19 - mmengine - INFO - Epoch(train) [37][40/880] lr: 1.0293e-03 eta: 0:26:09 time: 0.4669 data_time: 0.0278 memory: 23498 grad_norm: 6.8307 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.5227 loss: 1.5227 2022/09/08 15:01:27 - mmengine - INFO - Epoch(train) [37][60/880] lr: 1.0293e-03 eta: 0:26:00 time: 0.4473 data_time: 0.0205 memory: 23498 grad_norm: 6.8294 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.3487 loss: 1.3487 2022/09/08 15:01:36 - mmengine - INFO - Epoch(train) [37][80/880] lr: 1.0293e-03 eta: 0:25:51 time: 0.4466 data_time: 0.0210 memory: 23498 grad_norm: 6.8455 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.3200 loss: 1.3200 2022/09/08 15:01:46 - mmengine - INFO - Epoch(train) [37][100/880] lr: 1.0293e-03 eta: 0:25:42 time: 0.4684 data_time: 0.0239 memory: 23498 grad_norm: 6.6687 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.3695 loss: 1.3695 2022/09/08 15:01:55 - mmengine - INFO - Epoch(train) [37][120/880] lr: 1.0293e-03 eta: 0:25:33 time: 0.4568 data_time: 0.0257 memory: 23498 grad_norm: 6.4809 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.3032 loss: 1.3032 2022/09/08 15:02:04 - mmengine - INFO - Epoch(train) [37][140/880] lr: 1.0293e-03 eta: 0:25:24 time: 0.4591 data_time: 0.0234 memory: 23498 grad_norm: 6.6727 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.3017 loss: 1.3017 2022/09/08 15:02:13 - mmengine - INFO - Epoch(train) [37][160/880] lr: 1.0293e-03 eta: 0:25:15 time: 0.4502 data_time: 0.0214 memory: 23498 grad_norm: 6.7636 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.4076 loss: 1.4076 2022/09/08 15:02:22 - mmengine - INFO - Epoch(train) [37][180/880] lr: 1.0293e-03 eta: 0:25:06 time: 0.4567 data_time: 0.0229 memory: 23498 grad_norm: 6.9830 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.3880 loss: 1.3880 2022/09/08 15:02:31 - mmengine - INFO - Epoch(train) [37][200/880] lr: 1.0293e-03 eta: 0:24:57 time: 0.4487 data_time: 0.0210 memory: 23498 grad_norm: 6.7351 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.3621 loss: 1.3621 2022/09/08 15:02:40 - mmengine - INFO - Epoch(train) [37][220/880] lr: 1.0293e-03 eta: 0:24:48 time: 0.4533 data_time: 0.0234 memory: 23498 grad_norm: 6.9662 top1_acc: 0.3750 top5_acc: 0.7083 loss_cls: 1.3574 loss: 1.3574 2022/09/08 15:02:49 - mmengine - INFO - Epoch(train) [37][240/880] lr: 1.0293e-03 eta: 0:24:39 time: 0.4494 data_time: 0.0211 memory: 23498 grad_norm: 6.9195 top1_acc: 0.5833 top5_acc: 0.6250 loss_cls: 1.3307 loss: 1.3307 2022/09/08 15:02:58 - mmengine - INFO - Epoch(train) [37][260/880] lr: 1.0293e-03 eta: 0:24:30 time: 0.4570 data_time: 0.0218 memory: 23498 grad_norm: 6.8464 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.2239 loss: 1.2239 2022/09/08 15:03:07 - mmengine - INFO - Epoch(train) [37][280/880] lr: 1.0293e-03 eta: 0:24:21 time: 0.4469 data_time: 0.0226 memory: 23498 grad_norm: 6.8087 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.3870 loss: 1.3870 2022/09/08 15:03:16 - mmengine - INFO - Epoch(train) [37][300/880] lr: 1.0293e-03 eta: 0:24:12 time: 0.4476 data_time: 0.0208 memory: 23498 grad_norm: 6.7549 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.2193 loss: 1.2193 2022/09/08 15:03:25 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 15:03:25 - mmengine - INFO - Epoch(train) [37][320/880] lr: 1.0293e-03 eta: 0:24:03 time: 0.4473 data_time: 0.0228 memory: 23498 grad_norm: 6.7216 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.3462 loss: 1.3462 2022/09/08 15:03:35 - mmengine - INFO - Epoch(train) [37][340/880] lr: 1.0293e-03 eta: 0:23:54 time: 0.4642 data_time: 0.0194 memory: 23498 grad_norm: 6.8691 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.2862 loss: 1.2862 2022/09/08 15:03:44 - mmengine - INFO - Epoch(train) [37][360/880] lr: 1.0293e-03 eta: 0:23:45 time: 0.4488 data_time: 0.0239 memory: 23498 grad_norm: 6.8116 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4330 loss: 1.4330 2022/09/08 15:03:53 - mmengine - INFO - Epoch(train) [37][380/880] lr: 1.0293e-03 eta: 0:23:36 time: 0.4576 data_time: 0.0187 memory: 23498 grad_norm: 6.8049 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2767 loss: 1.2767 2022/09/08 15:04:02 - mmengine - INFO - Epoch(train) [37][400/880] lr: 1.0293e-03 eta: 0:23:27 time: 0.4477 data_time: 0.0244 memory: 23498 grad_norm: 6.8881 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.3158 loss: 1.3158 2022/09/08 15:04:11 - mmengine - INFO - Epoch(train) [37][420/880] lr: 1.0293e-03 eta: 0:23:18 time: 0.4498 data_time: 0.0184 memory: 23498 grad_norm: 6.9179 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.4302 loss: 1.4302 2022/09/08 15:04:20 - mmengine - INFO - Epoch(train) [37][440/880] lr: 1.0293e-03 eta: 0:23:09 time: 0.4477 data_time: 0.0239 memory: 23498 grad_norm: 6.7581 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2229 loss: 1.2229 2022/09/08 15:04:29 - mmengine - INFO - Epoch(train) [37][460/880] lr: 1.0293e-03 eta: 0:23:00 time: 0.4486 data_time: 0.0217 memory: 23498 grad_norm: 6.8422 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.3226 loss: 1.3226 2022/09/08 15:04:37 - mmengine - INFO - Epoch(train) [37][480/880] lr: 1.0293e-03 eta: 0:22:51 time: 0.4450 data_time: 0.0233 memory: 23498 grad_norm: 6.7849 top1_acc: 0.7500 top5_acc: 0.8333 loss_cls: 1.3632 loss: 1.3632 2022/09/08 15:04:46 - mmengine - INFO - Epoch(train) [37][500/880] lr: 1.0293e-03 eta: 0:22:42 time: 0.4436 data_time: 0.0178 memory: 23498 grad_norm: 6.8263 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.3184 loss: 1.3184 2022/09/08 15:04:55 - mmengine - INFO - Epoch(train) [37][520/880] lr: 1.0293e-03 eta: 0:22:33 time: 0.4515 data_time: 0.0248 memory: 23498 grad_norm: 6.9015 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.3282 loss: 1.3282 2022/09/08 15:05:04 - mmengine - INFO - Epoch(train) [37][540/880] lr: 1.0293e-03 eta: 0:22:24 time: 0.4429 data_time: 0.0181 memory: 23498 grad_norm: 6.7263 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.3851 loss: 1.3851 2022/09/08 15:05:13 - mmengine - INFO - Epoch(train) [37][560/880] lr: 1.0293e-03 eta: 0:22:15 time: 0.4466 data_time: 0.0239 memory: 23498 grad_norm: 6.7675 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.4287 loss: 1.4287 2022/09/08 15:05:22 - mmengine - INFO - Epoch(train) [37][580/880] lr: 1.0293e-03 eta: 0:22:06 time: 0.4462 data_time: 0.0189 memory: 23498 grad_norm: 6.7849 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.2364 loss: 1.2364 2022/09/08 15:05:31 - mmengine - INFO - Epoch(train) [37][600/880] lr: 1.0293e-03 eta: 0:21:57 time: 0.4463 data_time: 0.0232 memory: 23498 grad_norm: 6.8911 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.3100 loss: 1.3100 2022/09/08 15:05:40 - mmengine - INFO - Epoch(train) [37][620/880] lr: 1.0293e-03 eta: 0:21:48 time: 0.4487 data_time: 0.0234 memory: 23498 grad_norm: 6.9506 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.3717 loss: 1.3717 2022/09/08 15:05:49 - mmengine - INFO - Epoch(train) [37][640/880] lr: 1.0293e-03 eta: 0:21:39 time: 0.4445 data_time: 0.0230 memory: 23498 grad_norm: 6.8260 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.2606 loss: 1.2606 2022/09/08 15:05:58 - mmengine - INFO - Epoch(train) [37][660/880] lr: 1.0293e-03 eta: 0:21:29 time: 0.4482 data_time: 0.0185 memory: 23498 grad_norm: 6.9451 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.2422 loss: 1.2422 2022/09/08 15:06:07 - mmengine - INFO - Epoch(train) [37][680/880] lr: 1.0293e-03 eta: 0:21:20 time: 0.4476 data_time: 0.0229 memory: 23498 grad_norm: 6.6979 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.1367 loss: 1.1367 2022/09/08 15:06:16 - mmengine - INFO - Epoch(train) [37][700/880] lr: 1.0293e-03 eta: 0:21:11 time: 0.4430 data_time: 0.0177 memory: 23498 grad_norm: 6.8108 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.2676 loss: 1.2676 2022/09/08 15:06:25 - mmengine - INFO - Epoch(train) [37][720/880] lr: 1.0293e-03 eta: 0:21:02 time: 0.4442 data_time: 0.0235 memory: 23498 grad_norm: 7.0402 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 1.3950 loss: 1.3950 2022/09/08 15:06:33 - mmengine - INFO - Epoch(train) [37][740/880] lr: 1.0293e-03 eta: 0:20:53 time: 0.4445 data_time: 0.0179 memory: 23498 grad_norm: 6.9758 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.1956 loss: 1.1956 2022/09/08 15:06:42 - mmengine - INFO - Epoch(train) [37][760/880] lr: 1.0293e-03 eta: 0:20:44 time: 0.4439 data_time: 0.0232 memory: 23498 grad_norm: 6.6403 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.2825 loss: 1.2825 2022/09/08 15:06:51 - mmengine - INFO - Epoch(train) [37][780/880] lr: 1.0293e-03 eta: 0:20:35 time: 0.4425 data_time: 0.0202 memory: 23498 grad_norm: 6.9190 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.2244 loss: 1.2244 2022/09/08 15:07:00 - mmengine - INFO - Epoch(train) [37][800/880] lr: 1.0293e-03 eta: 0:20:26 time: 0.4481 data_time: 0.0233 memory: 23498 grad_norm: 6.7969 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.2144 loss: 1.2144 2022/09/08 15:07:09 - mmengine - INFO - Epoch(train) [37][820/880] lr: 1.0293e-03 eta: 0:20:17 time: 0.4419 data_time: 0.0176 memory: 23498 grad_norm: 6.7191 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 1.3113 loss: 1.3113 2022/09/08 15:07:18 - mmengine - INFO - Epoch(train) [37][840/880] lr: 1.0293e-03 eta: 0:20:08 time: 0.4464 data_time: 0.0230 memory: 23498 grad_norm: 6.7260 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.2980 loss: 1.2980 2022/09/08 15:07:27 - mmengine - INFO - Epoch(train) [37][860/880] lr: 1.0293e-03 eta: 0:19:59 time: 0.4450 data_time: 0.0190 memory: 23498 grad_norm: 7.0125 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.2848 loss: 1.2848 2022/09/08 15:07:35 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 15:07:35 - mmengine - INFO - Epoch(train) [37][880/880] lr: 1.0293e-03 eta: 0:19:50 time: 0.4328 data_time: 0.0204 memory: 23498 grad_norm: 6.8058 top1_acc: 0.6316 top5_acc: 0.8421 loss_cls: 1.2578 loss: 1.2578 2022/09/08 15:07:46 - mmengine - INFO - Epoch(train) [38][20/880] lr: 5.8116e-04 eta: 0:19:41 time: 0.5082 data_time: 0.0732 memory: 23498 grad_norm: 6.8885 top1_acc: 0.6250 top5_acc: 0.8333 loss_cls: 1.1629 loss: 1.1629 2022/09/08 15:07:55 - mmengine - INFO - Epoch(train) [38][40/880] lr: 5.8116e-04 eta: 0:19:32 time: 0.4603 data_time: 0.0210 memory: 23498 grad_norm: 6.7956 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3010 loss: 1.3010 2022/09/08 15:08:04 - mmengine - INFO - Epoch(train) [38][60/880] lr: 5.8116e-04 eta: 0:19:23 time: 0.4544 data_time: 0.0224 memory: 23498 grad_norm: 6.7461 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2445 loss: 1.2445 2022/09/08 15:08:13 - mmengine - INFO - Epoch(train) [38][80/880] lr: 5.8116e-04 eta: 0:19:14 time: 0.4496 data_time: 0.0203 memory: 23498 grad_norm: 6.8099 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.3625 loss: 1.3625 2022/09/08 15:08:22 - mmengine - INFO - Epoch(train) [38][100/880] lr: 5.8116e-04 eta: 0:19:05 time: 0.4529 data_time: 0.0201 memory: 23498 grad_norm: 6.6934 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2585 loss: 1.2585 2022/09/08 15:08:31 - mmengine - INFO - Epoch(train) [38][120/880] lr: 5.8116e-04 eta: 0:18:56 time: 0.4510 data_time: 0.0229 memory: 23498 grad_norm: 6.8857 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.3017 loss: 1.3017 2022/09/08 15:08:40 - mmengine - INFO - Epoch(train) [38][140/880] lr: 5.8116e-04 eta: 0:18:47 time: 0.4537 data_time: 0.0208 memory: 23498 grad_norm: 6.8216 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.4570 loss: 1.4570 2022/09/08 15:08:49 - mmengine - INFO - Epoch(train) [38][160/880] lr: 5.8116e-04 eta: 0:18:38 time: 0.4589 data_time: 0.0226 memory: 23498 grad_norm: 6.8002 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2042 loss: 1.2042 2022/09/08 15:08:58 - mmengine - INFO - Epoch(train) [38][180/880] lr: 5.8116e-04 eta: 0:18:29 time: 0.4532 data_time: 0.0225 memory: 23498 grad_norm: 6.9435 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.2235 loss: 1.2235 2022/09/08 15:09:07 - mmengine - INFO - Epoch(train) [38][200/880] lr: 5.8116e-04 eta: 0:18:20 time: 0.4520 data_time: 0.0226 memory: 23498 grad_norm: 6.8502 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.2798 loss: 1.2798 2022/09/08 15:09:16 - mmengine - INFO - Epoch(train) [38][220/880] lr: 5.8116e-04 eta: 0:18:11 time: 0.4520 data_time: 0.0202 memory: 23498 grad_norm: 6.9174 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.2630 loss: 1.2630 2022/09/08 15:09:25 - mmengine - INFO - Epoch(train) [38][240/880] lr: 5.8116e-04 eta: 0:18:02 time: 0.4516 data_time: 0.0206 memory: 23498 grad_norm: 6.8585 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2028 loss: 1.2028 2022/09/08 15:09:35 - mmengine - INFO - Epoch(train) [38][260/880] lr: 5.8116e-04 eta: 0:17:53 time: 0.4538 data_time: 0.0198 memory: 23498 grad_norm: 6.7676 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.2895 loss: 1.2895 2022/09/08 15:09:44 - mmengine - INFO - Epoch(train) [38][280/880] lr: 5.8116e-04 eta: 0:17:44 time: 0.4485 data_time: 0.0228 memory: 23498 grad_norm: 6.8662 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.2282 loss: 1.2282 2022/09/08 15:09:53 - mmengine - INFO - Epoch(train) [38][300/880] lr: 5.8116e-04 eta: 0:17:35 time: 0.4574 data_time: 0.0200 memory: 23498 grad_norm: 6.8191 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.2407 loss: 1.2407 2022/09/08 15:10:02 - mmengine - INFO - Epoch(train) [38][320/880] lr: 5.8116e-04 eta: 0:17:26 time: 0.4702 data_time: 0.0227 memory: 23498 grad_norm: 6.7675 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.2526 loss: 1.2526 2022/09/08 15:10:11 - mmengine - INFO - Epoch(train) [38][340/880] lr: 5.8116e-04 eta: 0:17:17 time: 0.4503 data_time: 0.0202 memory: 23498 grad_norm: 6.9310 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.2219 loss: 1.2219 2022/09/08 15:10:20 - mmengine - INFO - Epoch(train) [38][360/880] lr: 5.8116e-04 eta: 0:17:08 time: 0.4519 data_time: 0.0227 memory: 23498 grad_norm: 7.0024 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.1780 loss: 1.1780 2022/09/08 15:10:29 - mmengine - INFO - Epoch(train) [38][380/880] lr: 5.8116e-04 eta: 0:16:59 time: 0.4516 data_time: 0.0202 memory: 23498 grad_norm: 6.8760 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.2602 loss: 1.2602 2022/09/08 15:10:38 - mmengine - INFO - Epoch(train) [38][400/880] lr: 5.8116e-04 eta: 0:16:50 time: 0.4532 data_time: 0.0236 memory: 23498 grad_norm: 6.8577 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.3139 loss: 1.3139 2022/09/08 15:10:47 - mmengine - INFO - Epoch(train) [38][420/880] lr: 5.8116e-04 eta: 0:16:41 time: 0.4563 data_time: 0.0214 memory: 23498 grad_norm: 6.8727 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.3044 loss: 1.3044 2022/09/08 15:10:56 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 15:10:56 - mmengine - INFO - Epoch(train) [38][440/880] lr: 5.8116e-04 eta: 0:16:32 time: 0.4522 data_time: 0.0231 memory: 23498 grad_norm: 7.1397 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.0633 loss: 1.0633 2022/09/08 15:11:06 - mmengine - INFO - Epoch(train) [38][460/880] lr: 5.8116e-04 eta: 0:16:23 time: 0.4560 data_time: 0.0223 memory: 23498 grad_norm: 7.0673 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.3413 loss: 1.3413 2022/09/08 15:11:15 - mmengine - INFO - Epoch(train) [38][480/880] lr: 5.8116e-04 eta: 0:16:14 time: 0.4505 data_time: 0.0224 memory: 23498 grad_norm: 6.8939 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.3236 loss: 1.3236 2022/09/08 15:11:24 - mmengine - INFO - Epoch(train) [38][500/880] lr: 5.8116e-04 eta: 0:16:05 time: 0.4623 data_time: 0.0232 memory: 23498 grad_norm: 6.9621 top1_acc: 0.8750 top5_acc: 0.9583 loss_cls: 1.4220 loss: 1.4220 2022/09/08 15:11:33 - mmengine - INFO - Epoch(train) [38][520/880] lr: 5.8116e-04 eta: 0:15:56 time: 0.4540 data_time: 0.0240 memory: 23498 grad_norm: 6.9201 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.1881 loss: 1.1881 2022/09/08 15:11:42 - mmengine - INFO - Epoch(train) [38][540/880] lr: 5.8116e-04 eta: 0:15:47 time: 0.4570 data_time: 0.0189 memory: 23498 grad_norm: 6.9893 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.1972 loss: 1.1972 2022/09/08 15:11:51 - mmengine - INFO - Epoch(train) [38][560/880] lr: 5.8116e-04 eta: 0:15:38 time: 0.4501 data_time: 0.0228 memory: 23498 grad_norm: 6.8817 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.2404 loss: 1.2404 2022/09/08 15:12:00 - mmengine - INFO - Epoch(train) [38][580/880] lr: 5.8116e-04 eta: 0:15:29 time: 0.4700 data_time: 0.0171 memory: 23498 grad_norm: 7.1660 top1_acc: 0.7500 top5_acc: 0.7917 loss_cls: 1.3060 loss: 1.3060 2022/09/08 15:12:10 - mmengine - INFO - Epoch(train) [38][600/880] lr: 5.8116e-04 eta: 0:15:20 time: 0.4571 data_time: 0.0241 memory: 23498 grad_norm: 7.0136 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.2310 loss: 1.2310 2022/09/08 15:12:19 - mmengine - INFO - Epoch(train) [38][620/880] lr: 5.8116e-04 eta: 0:15:11 time: 0.4619 data_time: 0.0197 memory: 23498 grad_norm: 6.8546 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.1063 loss: 1.1063 2022/09/08 15:12:28 - mmengine - INFO - Epoch(train) [38][640/880] lr: 5.8116e-04 eta: 0:15:02 time: 0.4517 data_time: 0.0224 memory: 23498 grad_norm: 6.9795 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.3453 loss: 1.3453 2022/09/08 15:12:37 - mmengine - INFO - Epoch(train) [38][660/880] lr: 5.8116e-04 eta: 0:14:53 time: 0.4615 data_time: 0.0295 memory: 23498 grad_norm: 6.8869 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.2966 loss: 1.2966 2022/09/08 15:12:46 - mmengine - INFO - Epoch(train) [38][680/880] lr: 5.8116e-04 eta: 0:14:44 time: 0.4551 data_time: 0.0237 memory: 23498 grad_norm: 7.0134 top1_acc: 0.7083 top5_acc: 0.7917 loss_cls: 1.3465 loss: 1.3465 2022/09/08 15:12:55 - mmengine - INFO - Epoch(train) [38][700/880] lr: 5.8116e-04 eta: 0:14:35 time: 0.4500 data_time: 0.0206 memory: 23498 grad_norm: 6.9300 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2322 loss: 1.2322 2022/09/08 15:13:04 - mmengine - INFO - Epoch(train) [38][720/880] lr: 5.8116e-04 eta: 0:14:26 time: 0.4459 data_time: 0.0198 memory: 23498 grad_norm: 6.9465 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.2568 loss: 1.2568 2022/09/08 15:13:13 - mmengine - INFO - Epoch(train) [38][740/880] lr: 5.8116e-04 eta: 0:14:17 time: 0.4451 data_time: 0.0198 memory: 23498 grad_norm: 6.8753 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.1995 loss: 1.1995 2022/09/08 15:13:22 - mmengine - INFO - Epoch(train) [38][760/880] lr: 5.8116e-04 eta: 0:14:08 time: 0.4515 data_time: 0.0214 memory: 23498 grad_norm: 7.0973 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.2474 loss: 1.2474 2022/09/08 15:13:31 - mmengine - INFO - Epoch(train) [38][780/880] lr: 5.8116e-04 eta: 0:13:59 time: 0.4431 data_time: 0.0209 memory: 23498 grad_norm: 7.0106 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3601 loss: 1.3601 2022/09/08 15:13:40 - mmengine - INFO - Epoch(train) [38][800/880] lr: 5.8116e-04 eta: 0:13:50 time: 0.4492 data_time: 0.0189 memory: 23498 grad_norm: 6.8709 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.2892 loss: 1.2892 2022/09/08 15:13:49 - mmengine - INFO - Epoch(train) [38][820/880] lr: 5.8116e-04 eta: 0:13:41 time: 0.4447 data_time: 0.0203 memory: 23498 grad_norm: 6.8855 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.2892 loss: 1.2892 2022/09/08 15:13:58 - mmengine - INFO - Epoch(train) [38][840/880] lr: 5.8116e-04 eta: 0:13:31 time: 0.4423 data_time: 0.0214 memory: 23498 grad_norm: 7.0062 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.2841 loss: 1.2841 2022/09/08 15:14:07 - mmengine - INFO - Epoch(train) [38][860/880] lr: 5.8116e-04 eta: 0:13:22 time: 0.4473 data_time: 0.0198 memory: 23498 grad_norm: 6.9107 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2016 loss: 1.2016 2022/09/08 15:14:15 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 15:14:15 - mmengine - INFO - Epoch(train) [38][880/880] lr: 5.8116e-04 eta: 0:13:13 time: 0.4371 data_time: 0.0195 memory: 23498 grad_norm: 6.9914 top1_acc: 0.6316 top5_acc: 0.8421 loss_cls: 1.2755 loss: 1.2755 2022/09/08 15:14:20 - mmengine - INFO - Epoch(val) [38][20/130] eta: 0:00:24 time: 0.2192 data_time: 0.0808 memory: 2693 2022/09/08 15:14:23 - mmengine - INFO - Epoch(val) [38][40/130] eta: 0:00:14 time: 0.1585 data_time: 0.0242 memory: 2693 2022/09/08 15:14:26 - mmengine - INFO - Epoch(val) [38][60/130] eta: 0:00:11 time: 0.1701 data_time: 0.0344 memory: 2693 2022/09/08 15:14:30 - mmengine - INFO - Epoch(val) [38][80/130] eta: 0:00:08 time: 0.1659 data_time: 0.0281 memory: 2693 2022/09/08 15:14:33 - mmengine - INFO - Epoch(val) [38][100/130] eta: 0:00:05 time: 0.1673 data_time: 0.0320 memory: 2693 2022/09/08 15:14:36 - mmengine - INFO - Epoch(val) [38][120/130] eta: 0:00:01 time: 0.1588 data_time: 0.0267 memory: 2693 2022/09/08 15:14:38 - mmengine - INFO - Epoch(val) [38][130/130] acc/top1: 0.5457 acc/top5: 0.8231 acc/mean1: 0.4710 2022/09/08 15:14:39 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4/best_acc/top1_epoch_36.pth is removed 2022/09/08 15:14:40 - mmengine - INFO - The best checkpoint with 0.5457 acc/top1 at 38 epoch is saved to best_acc/top1_epoch_38.pth. 2022/09/08 15:14:50 - mmengine - INFO - Epoch(train) [39][20/880] lr: 2.5899e-04 eta: 0:13:04 time: 0.5052 data_time: 0.0718 memory: 23498 grad_norm: 7.0177 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.1089 loss: 1.1089 2022/09/08 15:14:59 - mmengine - INFO - Epoch(train) [39][40/880] lr: 2.5899e-04 eta: 0:12:55 time: 0.4575 data_time: 0.0292 memory: 23498 grad_norm: 6.9480 top1_acc: 0.7083 top5_acc: 0.9583 loss_cls: 1.2200 loss: 1.2200 2022/09/08 15:15:08 - mmengine - INFO - Epoch(train) [39][60/880] lr: 2.5899e-04 eta: 0:12:46 time: 0.4552 data_time: 0.0201 memory: 23498 grad_norm: 7.0884 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.3004 loss: 1.3004 2022/09/08 15:15:17 - mmengine - INFO - Epoch(train) [39][80/880] lr: 2.5899e-04 eta: 0:12:37 time: 0.4540 data_time: 0.0237 memory: 23498 grad_norm: 6.9192 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.1752 loss: 1.1752 2022/09/08 15:15:26 - mmengine - INFO - Epoch(train) [39][100/880] lr: 2.5899e-04 eta: 0:12:28 time: 0.4537 data_time: 0.0222 memory: 23498 grad_norm: 6.9497 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.1612 loss: 1.1612 2022/09/08 15:15:35 - mmengine - INFO - Epoch(train) [39][120/880] lr: 2.5899e-04 eta: 0:12:19 time: 0.4484 data_time: 0.0207 memory: 23498 grad_norm: 6.8858 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.2185 loss: 1.2185 2022/09/08 15:15:44 - mmengine - INFO - Epoch(train) [39][140/880] lr: 2.5899e-04 eta: 0:12:10 time: 0.4592 data_time: 0.0206 memory: 23498 grad_norm: 7.1684 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.2618 loss: 1.2618 2022/09/08 15:15:53 - mmengine - INFO - Epoch(train) [39][160/880] lr: 2.5899e-04 eta: 0:12:01 time: 0.4473 data_time: 0.0212 memory: 23498 grad_norm: 6.9055 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.2238 loss: 1.2238 2022/09/08 15:16:03 - mmengine - INFO - Epoch(train) [39][180/880] lr: 2.5899e-04 eta: 0:11:52 time: 0.4665 data_time: 0.0218 memory: 23498 grad_norm: 6.8689 top1_acc: 0.8750 top5_acc: 0.9167 loss_cls: 1.1352 loss: 1.1352 2022/09/08 15:16:12 - mmengine - INFO - Epoch(train) [39][200/880] lr: 2.5899e-04 eta: 0:11:43 time: 0.4487 data_time: 0.0219 memory: 23498 grad_norm: 6.9668 top1_acc: 0.6250 top5_acc: 0.7917 loss_cls: 1.2155 loss: 1.2155 2022/09/08 15:16:21 - mmengine - INFO - Epoch(train) [39][220/880] lr: 2.5899e-04 eta: 0:11:34 time: 0.4663 data_time: 0.0197 memory: 23498 grad_norm: 6.8953 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.2860 loss: 1.2860 2022/09/08 15:16:30 - mmengine - INFO - Epoch(train) [39][240/880] lr: 2.5899e-04 eta: 0:11:25 time: 0.4462 data_time: 0.0215 memory: 23498 grad_norm: 6.8626 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.1094 loss: 1.1094 2022/09/08 15:16:39 - mmengine - INFO - Epoch(train) [39][260/880] lr: 2.5899e-04 eta: 0:11:16 time: 0.4573 data_time: 0.0235 memory: 23498 grad_norm: 6.9069 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1482 loss: 1.1482 2022/09/08 15:16:48 - mmengine - INFO - Epoch(train) [39][280/880] lr: 2.5899e-04 eta: 0:11:07 time: 0.4469 data_time: 0.0218 memory: 23498 grad_norm: 7.0725 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.2343 loss: 1.2343 2022/09/08 15:16:57 - mmengine - INFO - Epoch(train) [39][300/880] lr: 2.5899e-04 eta: 0:10:58 time: 0.4461 data_time: 0.0212 memory: 23498 grad_norm: 6.9858 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.2427 loss: 1.2427 2022/09/08 15:17:06 - mmengine - INFO - Epoch(train) [39][320/880] lr: 2.5899e-04 eta: 0:10:49 time: 0.4492 data_time: 0.0278 memory: 23498 grad_norm: 6.8997 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.0951 loss: 1.0951 2022/09/08 15:17:15 - mmengine - INFO - Epoch(train) [39][340/880] lr: 2.5899e-04 eta: 0:10:40 time: 0.4448 data_time: 0.0191 memory: 23498 grad_norm: 7.2711 top1_acc: 0.5417 top5_acc: 0.7917 loss_cls: 1.2774 loss: 1.2774 2022/09/08 15:17:24 - mmengine - INFO - Epoch(train) [39][360/880] lr: 2.5899e-04 eta: 0:10:31 time: 0.4527 data_time: 0.0304 memory: 23498 grad_norm: 6.6747 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.0664 loss: 1.0664 2022/09/08 15:17:33 - mmengine - INFO - Epoch(train) [39][380/880] lr: 2.5899e-04 eta: 0:10:22 time: 0.4427 data_time: 0.0209 memory: 23498 grad_norm: 7.0690 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.4006 loss: 1.4006 2022/09/08 15:17:42 - mmengine - INFO - Epoch(train) [39][400/880] lr: 2.5899e-04 eta: 0:10:13 time: 0.4440 data_time: 0.0221 memory: 23498 grad_norm: 6.9429 top1_acc: 0.8333 top5_acc: 0.9167 loss_cls: 1.2704 loss: 1.2704 2022/09/08 15:17:50 - mmengine - INFO - Epoch(train) [39][420/880] lr: 2.5899e-04 eta: 0:10:04 time: 0.4433 data_time: 0.0201 memory: 23498 grad_norm: 6.9112 top1_acc: 0.5833 top5_acc: 0.8750 loss_cls: 1.1963 loss: 1.1963 2022/09/08 15:17:59 - mmengine - INFO - Epoch(train) [39][440/880] lr: 2.5899e-04 eta: 0:09:55 time: 0.4492 data_time: 0.0223 memory: 23498 grad_norm: 6.8679 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.1964 loss: 1.1964 2022/09/08 15:18:08 - mmengine - INFO - Epoch(train) [39][460/880] lr: 2.5899e-04 eta: 0:09:46 time: 0.4429 data_time: 0.0207 memory: 23498 grad_norm: 7.0660 top1_acc: 0.5833 top5_acc: 0.9167 loss_cls: 1.2542 loss: 1.2542 2022/09/08 15:18:17 - mmengine - INFO - Epoch(train) [39][480/880] lr: 2.5899e-04 eta: 0:09:37 time: 0.4470 data_time: 0.0212 memory: 23498 grad_norm: 7.0260 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.2312 loss: 1.2312 2022/09/08 15:18:26 - mmengine - INFO - Epoch(train) [39][500/880] lr: 2.5899e-04 eta: 0:09:28 time: 0.4468 data_time: 0.0189 memory: 23498 grad_norm: 6.8999 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.1637 loss: 1.1637 2022/09/08 15:18:35 - mmengine - INFO - Epoch(train) [39][520/880] lr: 2.5899e-04 eta: 0:09:19 time: 0.4474 data_time: 0.0221 memory: 23498 grad_norm: 7.0330 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.2412 loss: 1.2412 2022/09/08 15:18:44 - mmengine - INFO - Epoch(train) [39][540/880] lr: 2.5899e-04 eta: 0:09:10 time: 0.4450 data_time: 0.0208 memory: 23498 grad_norm: 7.0108 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.1938 loss: 1.1938 2022/09/08 15:18:53 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 15:18:53 - mmengine - INFO - Epoch(train) [39][560/880] lr: 2.5899e-04 eta: 0:09:01 time: 0.4654 data_time: 0.0206 memory: 23498 grad_norm: 7.0635 top1_acc: 0.5000 top5_acc: 0.7917 loss_cls: 1.3484 loss: 1.3484 2022/09/08 15:19:02 - mmengine - INFO - Epoch(train) [39][580/880] lr: 2.5899e-04 eta: 0:08:52 time: 0.4479 data_time: 0.0209 memory: 23498 grad_norm: 7.0374 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.3140 loss: 1.3140 2022/09/08 15:19:11 - mmengine - INFO - Epoch(train) [39][600/880] lr: 2.5899e-04 eta: 0:08:43 time: 0.4618 data_time: 0.0217 memory: 23498 grad_norm: 6.8111 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.1618 loss: 1.1618 2022/09/08 15:19:21 - mmengine - INFO - Epoch(train) [39][620/880] lr: 2.5899e-04 eta: 0:08:34 time: 0.4541 data_time: 0.0257 memory: 23498 grad_norm: 7.0655 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.1623 loss: 1.1623 2022/09/08 15:19:30 - mmengine - INFO - Epoch(train) [39][640/880] lr: 2.5899e-04 eta: 0:08:25 time: 0.4511 data_time: 0.0210 memory: 23498 grad_norm: 6.8249 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.1846 loss: 1.1846 2022/09/08 15:19:39 - mmengine - INFO - Epoch(train) [39][660/880] lr: 2.5899e-04 eta: 0:08:16 time: 0.4520 data_time: 0.0197 memory: 23498 grad_norm: 7.0457 top1_acc: 0.7917 top5_acc: 1.0000 loss_cls: 1.3162 loss: 1.3162 2022/09/08 15:19:48 - mmengine - INFO - Epoch(train) [39][680/880] lr: 2.5899e-04 eta: 0:08:07 time: 0.4485 data_time: 0.0215 memory: 23498 grad_norm: 7.0386 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.1694 loss: 1.1694 2022/09/08 15:19:57 - mmengine - INFO - Epoch(train) [39][700/880] lr: 2.5899e-04 eta: 0:07:58 time: 0.4479 data_time: 0.0193 memory: 23498 grad_norm: 7.0265 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.3402 loss: 1.3402 2022/09/08 15:20:06 - mmengine - INFO - Epoch(train) [39][720/880] lr: 2.5899e-04 eta: 0:07:49 time: 0.4507 data_time: 0.0229 memory: 23498 grad_norm: 7.0275 top1_acc: 0.5417 top5_acc: 0.8333 loss_cls: 1.3436 loss: 1.3436 2022/09/08 15:20:15 - mmengine - INFO - Epoch(train) [39][740/880] lr: 2.5899e-04 eta: 0:07:40 time: 0.4515 data_time: 0.0185 memory: 23498 grad_norm: 7.2606 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.2440 loss: 1.2440 2022/09/08 15:20:24 - mmengine - INFO - Epoch(train) [39][760/880] lr: 2.5899e-04 eta: 0:07:31 time: 0.4509 data_time: 0.0237 memory: 23498 grad_norm: 6.8843 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.2239 loss: 1.2239 2022/09/08 15:20:33 - mmengine - INFO - Epoch(train) [39][780/880] lr: 2.5899e-04 eta: 0:07:22 time: 0.4547 data_time: 0.0198 memory: 23498 grad_norm: 7.0548 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.3377 loss: 1.3377 2022/09/08 15:20:42 - mmengine - INFO - Epoch(train) [39][800/880] lr: 2.5899e-04 eta: 0:07:13 time: 0.4460 data_time: 0.0227 memory: 23498 grad_norm: 7.0755 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.1448 loss: 1.1448 2022/09/08 15:20:51 - mmengine - INFO - Epoch(train) [39][820/880] lr: 2.5899e-04 eta: 0:07:04 time: 0.4489 data_time: 0.0224 memory: 23498 grad_norm: 6.9780 top1_acc: 0.7083 top5_acc: 1.0000 loss_cls: 1.3275 loss: 1.3275 2022/09/08 15:21:00 - mmengine - INFO - Epoch(train) [39][840/880] lr: 2.5899e-04 eta: 0:06:55 time: 0.4527 data_time: 0.0234 memory: 23498 grad_norm: 7.0035 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.1563 loss: 1.1563 2022/09/08 15:21:09 - mmengine - INFO - Epoch(train) [39][860/880] lr: 2.5899e-04 eta: 0:06:46 time: 0.4481 data_time: 0.0202 memory: 23498 grad_norm: 6.8324 top1_acc: 0.6667 top5_acc: 0.7917 loss_cls: 1.2142 loss: 1.2142 2022/09/08 15:21:17 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 15:21:17 - mmengine - INFO - Epoch(train) [39][880/880] lr: 2.5899e-04 eta: 0:06:36 time: 0.4373 data_time: 0.0197 memory: 23498 grad_norm: 7.0366 top1_acc: 0.7368 top5_acc: 0.7895 loss_cls: 1.1214 loss: 1.1214 2022/09/08 15:21:28 - mmengine - INFO - Epoch(train) [40][20/880] lr: 6.4854e-05 eta: 0:06:27 time: 0.5115 data_time: 0.0715 memory: 23498 grad_norm: 6.9506 top1_acc: 0.5833 top5_acc: 0.7500 loss_cls: 1.2395 loss: 1.2395 2022/09/08 15:21:37 - mmengine - INFO - Epoch(train) [40][40/880] lr: 6.4854e-05 eta: 0:06:18 time: 0.4667 data_time: 0.0222 memory: 23498 grad_norm: 7.0108 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.3305 loss: 1.3305 2022/09/08 15:21:46 - mmengine - INFO - Epoch(train) [40][60/880] lr: 6.4854e-05 eta: 0:06:09 time: 0.4522 data_time: 0.0205 memory: 23498 grad_norm: 7.0049 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.2787 loss: 1.2787 2022/09/08 15:21:55 - mmengine - INFO - Epoch(train) [40][80/880] lr: 6.4854e-05 eta: 0:06:00 time: 0.4581 data_time: 0.0219 memory: 23498 grad_norm: 7.0380 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1403 loss: 1.1403 2022/09/08 15:22:04 - mmengine - INFO - Epoch(train) [40][100/880] lr: 6.4854e-05 eta: 0:05:51 time: 0.4559 data_time: 0.0248 memory: 23498 grad_norm: 7.0018 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.2347 loss: 1.2347 2022/09/08 15:22:14 - mmengine - INFO - Epoch(train) [40][120/880] lr: 6.4854e-05 eta: 0:05:42 time: 0.4605 data_time: 0.0217 memory: 23498 grad_norm: 6.9739 top1_acc: 0.6667 top5_acc: 0.7500 loss_cls: 1.2582 loss: 1.2582 2022/09/08 15:22:23 - mmengine - INFO - Epoch(train) [40][140/880] lr: 6.4854e-05 eta: 0:05:33 time: 0.4505 data_time: 0.0243 memory: 23498 grad_norm: 7.0505 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2346 loss: 1.2346 2022/09/08 15:22:32 - mmengine - INFO - Epoch(train) [40][160/880] lr: 6.4854e-05 eta: 0:05:24 time: 0.4559 data_time: 0.0230 memory: 23498 grad_norm: 6.9322 top1_acc: 0.5833 top5_acc: 0.7083 loss_cls: 1.1843 loss: 1.1843 2022/09/08 15:22:41 - mmengine - INFO - Epoch(train) [40][180/880] lr: 6.4854e-05 eta: 0:05:15 time: 0.4469 data_time: 0.0202 memory: 23498 grad_norm: 6.9406 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.1338 loss: 1.1338 2022/09/08 15:22:50 - mmengine - INFO - Epoch(train) [40][200/880] lr: 6.4854e-05 eta: 0:05:06 time: 0.4466 data_time: 0.0224 memory: 23498 grad_norm: 6.9690 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.2579 loss: 1.2579 2022/09/08 15:22:59 - mmengine - INFO - Epoch(train) [40][220/880] lr: 6.4854e-05 eta: 0:04:57 time: 0.4486 data_time: 0.0204 memory: 23498 grad_norm: 7.0710 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.2233 loss: 1.2233 2022/09/08 15:23:07 - mmengine - INFO - Epoch(train) [40][240/880] lr: 6.4854e-05 eta: 0:04:48 time: 0.4432 data_time: 0.0226 memory: 23498 grad_norm: 6.8147 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3314 loss: 1.3314 2022/09/08 15:23:16 - mmengine - INFO - Epoch(train) [40][260/880] lr: 6.4854e-05 eta: 0:04:39 time: 0.4495 data_time: 0.0198 memory: 23498 grad_norm: 7.0894 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.2846 loss: 1.2846 2022/09/08 15:23:25 - mmengine - INFO - Epoch(train) [40][280/880] lr: 6.4854e-05 eta: 0:04:30 time: 0.4459 data_time: 0.0205 memory: 23498 grad_norm: 7.1064 top1_acc: 0.5417 top5_acc: 0.8750 loss_cls: 1.2808 loss: 1.2808 2022/09/08 15:23:34 - mmengine - INFO - Epoch(train) [40][300/880] lr: 6.4854e-05 eta: 0:04:21 time: 0.4493 data_time: 0.0187 memory: 23498 grad_norm: 7.2342 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.1632 loss: 1.1632 2022/09/08 15:23:43 - mmengine - INFO - Epoch(train) [40][320/880] lr: 6.4854e-05 eta: 0:04:12 time: 0.4466 data_time: 0.0221 memory: 23498 grad_norm: 7.0632 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.2544 loss: 1.2544 2022/09/08 15:23:52 - mmengine - INFO - Epoch(train) [40][340/880] lr: 6.4854e-05 eta: 0:04:03 time: 0.4471 data_time: 0.0186 memory: 23498 grad_norm: 7.0930 top1_acc: 0.7500 top5_acc: 0.9583 loss_cls: 1.1862 loss: 1.1862 2022/09/08 15:24:01 - mmengine - INFO - Epoch(train) [40][360/880] lr: 6.4854e-05 eta: 0:03:54 time: 0.4475 data_time: 0.0220 memory: 23498 grad_norm: 6.9938 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.2649 loss: 1.2649 2022/09/08 15:24:10 - mmengine - INFO - Epoch(train) [40][380/880] lr: 6.4854e-05 eta: 0:03:45 time: 0.4444 data_time: 0.0201 memory: 23498 grad_norm: 7.0259 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.1124 loss: 1.1124 2022/09/08 15:24:19 - mmengine - INFO - Epoch(train) [40][400/880] lr: 6.4854e-05 eta: 0:03:36 time: 0.4460 data_time: 0.0219 memory: 23498 grad_norm: 7.2433 top1_acc: 0.7917 top5_acc: 0.9167 loss_cls: 1.3349 loss: 1.3349 2022/09/08 15:24:28 - mmengine - INFO - Epoch(train) [40][420/880] lr: 6.4854e-05 eta: 0:03:27 time: 0.4500 data_time: 0.0203 memory: 23498 grad_norm: 7.0770 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.3140 loss: 1.3140 2022/09/08 15:24:37 - mmengine - INFO - Epoch(train) [40][440/880] lr: 6.4854e-05 eta: 0:03:18 time: 0.4447 data_time: 0.0210 memory: 23498 grad_norm: 7.2360 top1_acc: 0.7083 top5_acc: 0.8750 loss_cls: 1.1872 loss: 1.1872 2022/09/08 15:24:46 - mmengine - INFO - Epoch(train) [40][460/880] lr: 6.4854e-05 eta: 0:03:09 time: 0.4532 data_time: 0.0194 memory: 23498 grad_norm: 7.0719 top1_acc: 0.7083 top5_acc: 0.8333 loss_cls: 1.2434 loss: 1.2434 2022/09/08 15:24:55 - mmengine - INFO - Epoch(train) [40][480/880] lr: 6.4854e-05 eta: 0:03:00 time: 0.4523 data_time: 0.0258 memory: 23498 grad_norm: 7.1490 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.2168 loss: 1.2168 2022/09/08 15:25:04 - mmengine - INFO - Epoch(train) [40][500/880] lr: 6.4854e-05 eta: 0:02:51 time: 0.4486 data_time: 0.0192 memory: 23498 grad_norm: 6.9947 top1_acc: 0.6250 top5_acc: 0.9583 loss_cls: 1.2565 loss: 1.2565 2022/09/08 15:25:13 - mmengine - INFO - Epoch(train) [40][520/880] lr: 6.4854e-05 eta: 0:02:42 time: 0.4500 data_time: 0.0226 memory: 23498 grad_norm: 7.0254 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.1333 loss: 1.1333 2022/09/08 15:25:22 - mmengine - INFO - Epoch(train) [40][540/880] lr: 6.4854e-05 eta: 0:02:33 time: 0.4532 data_time: 0.0202 memory: 23498 grad_norm: 7.2099 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.2631 loss: 1.2631 2022/09/08 15:25:31 - mmengine - INFO - Epoch(train) [40][560/880] lr: 6.4854e-05 eta: 0:02:24 time: 0.4565 data_time: 0.0226 memory: 23498 grad_norm: 6.9218 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.4257 loss: 1.4257 2022/09/08 15:25:40 - mmengine - INFO - Epoch(train) [40][580/880] lr: 6.4854e-05 eta: 0:02:15 time: 0.4504 data_time: 0.0217 memory: 23498 grad_norm: 7.0952 top1_acc: 0.7917 top5_acc: 0.9583 loss_cls: 1.2471 loss: 1.2471 2022/09/08 15:25:49 - mmengine - INFO - Epoch(train) [40][600/880] lr: 6.4854e-05 eta: 0:02:06 time: 0.4483 data_time: 0.0240 memory: 23498 grad_norm: 6.8145 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.2100 loss: 1.2100 2022/09/08 15:25:58 - mmengine - INFO - Epoch(train) [40][620/880] lr: 6.4854e-05 eta: 0:01:57 time: 0.4464 data_time: 0.0209 memory: 23498 grad_norm: 6.8305 top1_acc: 0.7083 top5_acc: 0.9167 loss_cls: 1.1626 loss: 1.1626 2022/09/08 15:26:07 - mmengine - INFO - Epoch(train) [40][640/880] lr: 6.4854e-05 eta: 0:01:48 time: 0.4469 data_time: 0.0232 memory: 23498 grad_norm: 7.0515 top1_acc: 0.4583 top5_acc: 0.8333 loss_cls: 1.4510 loss: 1.4510 2022/09/08 15:26:16 - mmengine - INFO - Epoch(train) [40][660/880] lr: 6.4854e-05 eta: 0:01:39 time: 0.4480 data_time: 0.0198 memory: 23498 grad_norm: 6.9644 top1_acc: 0.6667 top5_acc: 0.9167 loss_cls: 1.1865 loss: 1.1865 2022/09/08 15:26:25 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 15:26:25 - mmengine - INFO - Epoch(train) [40][680/880] lr: 6.4854e-05 eta: 0:01:30 time: 0.4550 data_time: 0.0301 memory: 23498 grad_norm: 6.9547 top1_acc: 0.6250 top5_acc: 0.9167 loss_cls: 1.2852 loss: 1.2852 2022/09/08 15:26:34 - mmengine - INFO - Epoch(train) [40][700/880] lr: 6.4854e-05 eta: 0:01:21 time: 0.4532 data_time: 0.0217 memory: 23498 grad_norm: 7.1275 top1_acc: 0.5417 top5_acc: 0.7500 loss_cls: 1.2472 loss: 1.2472 2022/09/08 15:26:43 - mmengine - INFO - Epoch(train) [40][720/880] lr: 6.4854e-05 eta: 0:01:12 time: 0.4510 data_time: 0.0231 memory: 23498 grad_norm: 6.9966 top1_acc: 0.6667 top5_acc: 0.8750 loss_cls: 1.2010 loss: 1.2010 2022/09/08 15:26:52 - mmengine - INFO - Epoch(train) [40][740/880] lr: 6.4854e-05 eta: 0:01:03 time: 0.4449 data_time: 0.0216 memory: 23498 grad_norm: 7.0213 top1_acc: 0.7500 top5_acc: 0.9167 loss_cls: 1.2171 loss: 1.2171 2022/09/08 15:27:01 - mmengine - INFO - Epoch(train) [40][760/880] lr: 6.4854e-05 eta: 0:00:54 time: 0.4509 data_time: 0.0210 memory: 23498 grad_norm: 7.0390 top1_acc: 0.5000 top5_acc: 0.7083 loss_cls: 1.2685 loss: 1.2685 2022/09/08 15:27:10 - mmengine - INFO - Epoch(train) [40][780/880] lr: 6.4854e-05 eta: 0:00:45 time: 0.4451 data_time: 0.0202 memory: 23498 grad_norm: 7.0700 top1_acc: 0.7917 top5_acc: 0.8750 loss_cls: 1.1505 loss: 1.1505 2022/09/08 15:27:19 - mmengine - INFO - Epoch(train) [40][800/880] lr: 6.4854e-05 eta: 0:00:36 time: 0.4466 data_time: 0.0228 memory: 23498 grad_norm: 7.1267 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.2242 loss: 1.2242 2022/09/08 15:27:28 - mmengine - INFO - Epoch(train) [40][820/880] lr: 6.4854e-05 eta: 0:00:27 time: 0.4657 data_time: 0.0188 memory: 23498 grad_norm: 6.8853 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3361 loss: 1.3361 2022/09/08 15:27:37 - mmengine - INFO - Epoch(train) [40][840/880] lr: 6.4854e-05 eta: 0:00:18 time: 0.4586 data_time: 0.0272 memory: 23498 grad_norm: 7.0178 top1_acc: 0.5833 top5_acc: 0.7917 loss_cls: 1.1407 loss: 1.1407 2022/09/08 15:27:46 - mmengine - INFO - Epoch(train) [40][860/880] lr: 6.4854e-05 eta: 0:00:09 time: 0.4468 data_time: 0.0190 memory: 23498 grad_norm: 6.9918 top1_acc: 0.5833 top5_acc: 0.8333 loss_cls: 1.2962 loss: 1.2962 2022/09/08 15:27:55 - mmengine - INFO - Exp name: tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_20220908_105408 2022/09/08 15:27:55 - mmengine - INFO - Epoch(train) [40][880/880] lr: 6.4854e-05 eta: 0:00:00 time: 0.4395 data_time: 0.0227 memory: 23498 grad_norm: 7.0285 top1_acc: 0.6842 top5_acc: 0.8421 loss_cls: 1.1668 loss: 1.1668 2022/09/08 15:27:55 - mmengine - INFO - Saving checkpoint at 40 epochs 2022/09/08 15:28:02 - mmengine - INFO - Epoch(val) [40][20/130] eta: 0:00:25 time: 0.2309 data_time: 0.0958 memory: 2693 2022/09/08 15:28:05 - mmengine - INFO - Epoch(val) [40][40/130] eta: 0:00:14 time: 0.1649 data_time: 0.0266 memory: 2693 2022/09/08 15:28:08 - mmengine - INFO - Epoch(val) [40][60/130] eta: 0:00:11 time: 0.1696 data_time: 0.0339 memory: 2693 2022/09/08 15:28:12 - mmengine - INFO - Epoch(val) [40][80/130] eta: 0:00:08 time: 0.1635 data_time: 0.0259 memory: 2693 2022/09/08 15:28:15 - mmengine - INFO - Epoch(val) [40][100/130] eta: 0:00:05 time: 0.1729 data_time: 0.0364 memory: 2693 2022/09/08 15:28:18 - mmengine - INFO - Epoch(val) [40][120/130] eta: 0:00:01 time: 0.1367 data_time: 0.0137 memory: 2693 2022/09/08 15:28:20 - mmengine - INFO - Epoch(val) [40][130/130] acc/top1: 0.5478 acc/top5: 0.8218 acc/mean1: 0.4732 2022/09/08 15:28:20 - mmengine - INFO - The previous best checkpoint /mnt/cache/lilin/Repos/mmaction2/work_dirs/tin_imagenet-pretrained-r50_8xb6-1x1x8-40e_sthv2-rgb_lr0.01*4/best_acc/top1_epoch_38.pth is removed 2022/09/08 15:28:21 - mmengine - INFO - The best checkpoint with 0.5478 acc/top1 at 40 epoch is saved to best_acc/top1_epoch_40.pth.